{ "cells": [ { "cell_type": "markdown", "id": "3df36883-3c1c-4008-98ca-0d641820d9ef", "metadata": {}, "source": [ "## Dataset exploration\n", "\n", "This is probably going to be a minimal EDA notebook looking at tool calling datasets that exists in market right now" ] }, { "cell_type": "code", "execution_count": 1, "id": "63d7e44e-d808-4628-ab7a-540aa6d0fd72", "metadata": {}, "outputs": [], "source": [ "#!pip install datasets" ] }, { "cell_type": "code", "execution_count": 96, "id": "52075b0f-61be-4898-be35-bd72bd022efc", "metadata": {}, "outputs": [], "source": [ "from datasets import load_dataset\n", "import pandas as pd\n", "import numpy as np\n", "from collections import Counter, defaultdict\n", "import json\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import re\n", "from tqdm import tqdm\n", "import networkx as nx" ] }, { "cell_type": "markdown", "id": "c3c59bbd-1060-4b71-9ceb-1e70d733b8a4", "metadata": {}, "source": [ "### Hermes-Function-Calling v1\n", "\n", "- Apache 2.0\n", "- Single-Turn: 2k\n", "- Func_calling: 2k\n", "- Glaive: 5k\n", "- Json mode agent: 1.3k\n", "- Json mode single: 1.24k\n", "\n", "https://huggingface.co/datasets/NousResearch/hermes-function-calling-v1" ] }, { "cell_type": "code", "execution_count": 26, "id": "22a4366c-4a9a-45f8-b12d-603b0ab2df5f", "metadata": {}, "outputs": [], "source": [ "d = load_dataset(\"NousResearch/hermes-function-calling-v1\")" ] }, { "cell_type": "code", "execution_count": 27, "id": "bb2798bd-0d22-47c6-9346-4fde13b64c54", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Dataset({\n", " features: ['id', 'conversations', 'category', 'subcategory', 'task'],\n", " num_rows: 1893\n", "})" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train']" ] }, { "cell_type": "code", "execution_count": 28, "id": "bc731c69-3ef5-4e34-98b6-e07646241d09", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['id', 'conversations', 'category', 'subcategory', 'task'])" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][123].keys()" ] }, { "cell_type": "code", "execution_count": 29, "id": "0b54ea4f-3f2a-48dc-8efc-9cff09dd46db", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'id': '936b90da-dbeb-4864-a6e6-28899965265d',\n", " 'conversations': [{'from': 'system',\n", " 'value': \"You are a function calling AI model. You are provided with function signatures within XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions.\\n\\n[{'type': 'function', 'function': {'name': 'scale_up_cluster', 'description': 'Scales up the number of compute nodes in an HPC cluster.', 'parameters': {'type': 'object', 'properties': {'cluster_name': {'type': 'string', 'description': 'The name of the HPC cluster to scale up.'}, 'node_type': {'type': 'string', 'description': 'The type of compute node to add to the cluster.'}, 'additional_nodes': {'type': 'integer', 'description': 'The number of additional compute nodes to add to the cluster.'}}, 'required': ['cluster_name', 'node_type', 'additional_nodes']}}}, {'type': 'function', 'function': {'name': 'scale_down_cluster', 'description': 'Scales down the number of compute nodes in an HPC cluster.', 'parameters': {'type': 'object', 'properties': {'cluster_name': {'type': 'string', 'description': 'The name of the HPC cluster to scale down.'}, 'node_type': {'type': 'string', 'description': 'The type of compute node to remove from the cluster.'}, 'remove_nodes': {'type': 'integer', 'description': 'The number of compute nodes to remove from the cluster.'}}, 'required': ['cluster_name', 'node_type', 'remove_nodes']}}}]\\n\\nFor each function call return a json object with function name and arguments within tags with the following schema:\\n\\n{'arguments': , 'name': }\\n\\n\"},\n", " {'from': 'human',\n", " 'value': \"Our High Performance Computing (HPC) cluster, designated as 'CFD-Sim-Cluster', is engaged in complex computational fluid dynamics simulations. With an influx of computational tasks forecasted for the upcoming week, we need to proactively expand our cluster's capacity. Therefore, I request the addition of 50 new compute nodes, specifically of the 'c5.18xlarge' type, to handle the anticipated surge in processing demands. Once the simulations have been concluded and the need for augmented resources subsides, we will need to scale back by decommissioning the same number of nodes. Could you facilitate the necessary API calls to scale our HPC cluster up and subsequently down as per the described requirements?\\n\\nHere are the details for the API calls:\\n1. Scale up the cluster 'CFD-Sim-Cluster' by adding 50 compute nodes of type 'c5.18xlarge'.\\n2. After completion of the high-demand period, scale down the 'CFD-Sim-Cluster' by removing 50 nodes of type 'c5.18xlarge'.\\n\\nI would like these API calls to be initiated to adjust our cluster's resources accordingly.\"},\n", " {'from': 'gpt',\n", " 'value': \"\\n{'arguments': {'cluster_name': 'CFD-Sim-Cluster', 'node_type': 'c5.18xlarge', 'additional_nodes': 50}, 'name': 'scale_up_cluster'}\\n\\n\\n{'arguments': {'cluster_name': 'CFD-Sim-Cluster', 'node_type': 'c5.18xlarge', 'remove_nodes': 50}, 'name': 'scale_down_cluster'}\\n\\n\"}],\n", " 'category': 'Data Centers and High Performance Computing',\n", " 'subcategory': 'Cluster Scaling',\n", " 'task': 'Scale High Performance Computing (HPC) Systems Up or Down with API Calls (POST Requests)'}" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][123]" ] }, { "cell_type": "code", "execution_count": 30, "id": "4802c0f3-9501-4d0c-a6a8-a4a614970e70", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'id': 'f9b15d86-fb69-4f05-a65e-18f2f7b5369d',\n", " 'conversations': [{'from': 'system',\n", " 'value': \"You are a function calling AI model. You are provided with function signatures within XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions.\\n\\n[{'type': 'function', 'function': {'name': 'min_max_normalize', 'description': 'Apply Min-Max normalization to scale features in the dataset to a specified range.', 'parameters': {'type': 'object', 'properties': {'data': {'type': 'string', 'description': 'The path to the dataset file.'}, 'feature_range': {'type': 'object', 'properties': {'min': {'type': 'number', 'description': 'The minimum value of the target range for normalization.'}, 'max': {'type': 'number', 'description': 'The maximum value of the target range for normalization.'}}, 'required': ['min', 'max']}}, 'required': ['data', 'feature_range']}}}, {'type': 'function', 'function': {'name': 'z_score_normalize', 'description': 'Apply Z-Score normalization to standardize features in the dataset to have a mean of 0 and a standard deviation of 1.', 'parameters': {'type': 'object', 'properties': {'data': {'type': 'string', 'description': 'The path to the dataset file.'}}, 'required': ['data']}}}, {'type': 'function', 'function': {'name': 'decimal_scaling_normalize', 'description': 'Apply Decimal Scaling normalization to shift the decimal point of values of the data.', 'parameters': {'type': 'object', 'properties': {'data': {'type': 'string', 'description': 'The path to the dataset file.'}}, 'required': ['data']}}}]\\n\\nFor each function call return a json object with function name and arguments within tags with the following schema:\\n\\n{'arguments': , 'name': }\\n\\n\"},\n", " {'from': 'human',\n", " 'value': \"I have a dataset, `dataset_normalized.csv`, which contains several features for a machine learning project. However, this data encompasses features with heterogeneous scales and units, which may hinder the predictive model's performance. To ensure that each feature has an equal impact on the model, the features need to be normalized to the same scale. I would like to perform Min-Max normalization on this data to adjust the features to a scale between 0 and 1. Here is the dataset for reference:\\n\\n```markdown\\n| Feature1 | Feature2 | Feature3 | ... | FeatureN |\\n|----------|----------|----------|-----|----------|\\n| 15 | 100 | 0.75 | ... | 40 |\\n| 22 | 80 | 0.85 | ... | 35 |\\n| 18 | 90 | 0.65 | ... | 38 |\\n| ... | ... | ... | ... | ... |\\n| 20 | 95 | 0.70 | ... | 37 |\\n```\\n\\nCould you please apply Min-Max normalization using the `min_max_normalize` function to scale the features within the range of 0 to 1 for the `dataset_normalized.csv` file? This preprocessing will ensure that our machine learning algorithm evaluates all features fairly.\"},\n", " {'from': 'gpt',\n", " 'value': \"\\n{'arguments': {'data': 'dataset_normalized.csv', 'feature_range': {'min': 0, 'max': 1}}, 'name': 'min_max_normalize'}\\n\\n\"}],\n", " 'category': 'Data Processing',\n", " 'subcategory': 'Data Normalization',\n", " 'task': 'Data normalization methods'}" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][400]" ] }, { "cell_type": "code", "execution_count": 31, "id": "97277dc8-3b63-486c-ab68-516c065937b3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'AI Model Integration',\n", " 'API Call',\n", " 'Accounting & Finance',\n", " 'Algorithmic Trading',\n", " 'Annotation',\n", " 'Blockchain Integration',\n", " 'Business Intelligence',\n", " 'CRM',\n", " 'Cloud Platforms',\n", " 'Code Interpreters',\n", " 'Communication Services Software',\n", " 'Compliance',\n", " 'Consumer Discretionary Software',\n", " 'Consumer Staples Software',\n", " 'Data Centers and High Performance Computing',\n", " 'Data Privacy',\n", " 'Data Processing',\n", " 'Database Management',\n", " 'Decentralized Apps (DApps)',\n", " 'Desktop Applications',\n", " 'DevOps',\n", " 'Document Ranking',\n", " 'E-commerce Platforms',\n", " 'Energy Software',\n", " 'Financial Services Apps',\n", " 'Financial Software',\n", " 'Git Operations',\n", " 'HR',\n", " 'Healthcare Software',\n", " 'Identity and Access Management (IAM)',\n", " 'Industrial Software',\n", " 'Information Extraction',\n", " 'Information Retrieval (RAG)',\n", " 'Information Technology Software',\n", " 'IoT Platforms',\n", " 'IoT and Home Automation',\n", " 'Low-Code Enterprise Platforms',\n", " 'Marketing',\n", " 'Materials Software',\n", " 'Mobile Applications',\n", " 'Model APIs',\n", " 'Named Entity Recognition',\n", " 'Networking and Cybersecurity',\n", " 'Office Administration',\n", " 'OpenAI API Integration',\n", " 'Operating System Functions',\n", " 'Productivity Tools Integration',\n", " 'Project Management',\n", " 'Quantum Computing',\n", " 'Real Estate Software',\n", " 'Relation Extraction',\n", " 'Robotic Process Automation (RPA)',\n", " 'Robotics and Automation',\n", " 'SAP',\n", " 'SaaS Platforms',\n", " 'Services Industry Software',\n", " 'Text Classification',\n", " 'Topic Modelling',\n", " 'Use Apps',\n", " 'Utilities Software',\n", " 'Voice Assistants',\n", " 'Web APIs',\n", " 'Web Browser Agent'}" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "set(d['train']['category'])" ] }, { "cell_type": "code", "execution_count": 35, "id": "7a5b4656-8788-4776-9e2b-ab807e44797a", "metadata": {}, "outputs": [], "source": [ "def extract_functions_from_system(system_message):\n", " tools_match = re.search(r'(.*?)', system_message, re.DOTALL)\n", " if tools_match:\n", " tools_str = tools_match.group(1).strip()\n", " # Convert Python string representation to valid JSON\n", " tools_str = tools_str.replace(\"'\", '\"')\n", " try:\n", " return json.loads(tools_str)\n", " except json.JSONDecodeError as e:\n", " print(f\"Error parsing tools string: {tools_str[:100]}...\")\n", " return []\n", " return []\n", "\n", "def extract_tool_calls(gpt_message):\n", " tool_calls = []\n", " matches = re.finditer(r'(.*?)', gpt_message, re.DOTALL)\n", " for match in matches:\n", " try:\n", " tool_call_str = match.group(1).strip()\n", " # Clean up the string and ensure it's valid JSON\n", " tool_call_str = tool_call_str.replace(\"'\", '\"')\n", " tool_call = json.loads(tool_call_str)\n", " tool_calls.append(tool_call)\n", " except json.JSONDecodeError as e:\n", " print(f\"Error parsing tool call: {tool_call_str[:100]}...\")\n", " continue\n", " return tool_calls" ] }, { "cell_type": "markdown", "id": "33ff384a-25ae-4196-8879-4131e8d536b7", "metadata": {}, "source": [ "#### Some EDA\n", "\n", "The analsysis is on a part of the dataset but still gets us a good overview" ] }, { "cell_type": "code", "execution_count": 36, "id": "b31b578d-27fb-432a-ad8f-215515257e5f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ " 63%|█████████████████████████████████▉ | 1190/1893 [00:00<00:00, 5958.41it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"appliance_id\": \"WM-002\", \"auto_off\": True}, \"name\": \"set_washing_machine_auto_off\"}...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"confirmation_required\": True}, \"name\": \"lock_all_smart_doors\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"device_id\": \"smart_plug_123\", \"on_time\": \"19:00\", \"off_time\": \"23:00\", \"repeat_daily...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"function_type\": \"periodic\", \"fourier_components\": 5, \"auxiliary_qubits\": 2, \"control...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"category\": \"cybersecurity\", \"include_hardware_specs\": True, \"include_software_tools\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"client_data\": [{\"client_id\": \"client_001\", \"services\": [{\"service_id\": \"service_001\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"hotel_id\": \"H1001\", \"check_in_enabled\": True, \"check_out_enabled\": True}, \"name\": \"a...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"title\": \"Cybersecurity Fundamentals\", \"description\": \"An in-depth training initiativ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"locationId\": \"12345\", \"includeOffline\": True}, \"name\": \"getConnectedDevicesStatus\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"user_id\": \"user123\", \"parental_settings\": {\"enabled\": True, \"rating_limit\": \"PG-13\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"feedback_data\": \"{\"feedback_entries\": [{\"customer_id\": \"JD_8098\",\"date\": \"2023-03-15...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"user_id\": \"USR19876C\", \"preferences\": {\"default_volume\": 65, \"favorite_genres\": [\"Sc...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"data_transfer_rate\": 700, \"voice_channels\": 20, \"video_conferencing\": True}, \"name\":...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"feature_id\": \"12345\", \"user_id\": \"67890\", \"rating\": 4, \"comments\": \"The new interfac...\n", "Error parsing tool call: {\"arguments\": {\"comments\": \"The new interface is intuitive and user-friendly, though I\"d like quicke...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"content_types\": [\"quiz\", \"poll\", \"game\"], \"embeddable\": True, \"track_engagement\": Tr...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"system_id\": \"HES12345678\", \"error_logs\": \"[2023-04-01T10:15:30Z] ERROR: Voice recogn...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"auth_method\": \"OAuth2\", \"required_fields\": [\"email\", \"password\"], \"optional_fields\":...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"historical_data\": \"{\"year\": \"2020\", \"monthly_active_users\": [100000, 105000, 110000]...\n", "Error parsing tool call: {\"arguments\": {\"forecasted_demand\": \"\", \"simulation_parameters\": {\"peak_hours\": [\"08:00\", \"12:00\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"yield_data\": \"{\"processes\": [{\"batch_id\": \"RX1001\",\"reactants\": [\"ChemA\", \"ChemB\"],\"...\n", "Error parsing tool call: {\"arguments\": {\"energy_data\": \"{\"processes\": [{\"process_id\": \"PR1001\",\"step\": \"Reaction\",\"electricit...\n", "Error parsing tool call: {\"arguments\": {\"material_cost_data\": \"{\"materials\": [{\"material_id\": \"Mat1\",\"name\": \"Sulphuric Acid\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inventory_database\": \"{\"materials\":[{\"id\":\"mat_001\",\"name\":\"Cement\",\"quantity\":150,\"...\n", "Error parsing tool call: {\"arguments\": {\"inventory_database\": \"{\"materials\":[{\"id\":\"mat_001\",\"name\":\"Cement\",\"quantity\":150,\"...\n", "Error parsing tool call: {\"arguments\": {\"inventory_database\": \"{\"materials\":[{\"id\":\"mat_001\",\"name\":\"Cement\",\"quantity\":150,\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"supplier_data\": \"{\"Suppliers\": [{\"SupplierID\": \"S001\", \"DeliveryTime\": \"48 hours\", \"...\n", "Error parsing tool call: {\"arguments\": {\"delivery_data\": \"{\"Deliveries\": [{\"DeliveryID\": \"D001\", \"Route\": [\"Warehouse A\", \"Lo...\n", "Error parsing tool call: {\"arguments\": {\"inventory_data\": \"{\"Inventory\": [{\"ProductID\": \"P001\", \"CurrentStock\": 350, \"Forecas...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"collection_data\": \"{\"metals_collected\": [{\"type\": \"Copper\", \"quantity_kg\": 3250, \"co...\n", "Error parsing tool call: {\"arguments\": {\"sorting_data\": \"{\"sorting_process\": [{\"metal_type\": \"Copper\", \"time_taken_seconds\": ...\n", "Error parsing tool call: {\"arguments\": {\"processing_data\": \"{\"processing_times\": [{\"metal_type\": \"Copper\", \"processing_time_m...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"departure_city\": \"Los Angeles\", \"destination_city\": \"Auckland\", \"departure_date\": \"2...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"origin\": \"NYC\", \"destination\": \"TYO\", \"departure_date\": \"2023-05-15\", \"return_date\":...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"server_type\": \"on-premises\", \"backup_frequency\": \"nightly\", \"encryption_enabled\": Tr...\n", "Error parsing tool call: {\"arguments\": {\"recovery_type\": \"selective\", \"encryption_enabled\": True}, \"name\": \"configure_recover...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"log_compliance\": True}, \"name\": \"enable_action_logging\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"model_name\": \"fasterrcnn_resnet50_fpn\", \"pretrained\": True}, \"name\": \"load_pretraine...\n", "Error parsing tool call: {\"arguments\": {\"model\": None, \"image_paths\": [\"gs://wildlife-expedition-bucket/image1.jpg\", \"gs://wi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"model_name\": \"wav2vec2\", \"pretrained\": True}, \"name\": \"load_speech_recognition_model...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"model_name\": \"neural_style_transfer\", \"pretrained\": True}, \"name\": \"load_style_trans...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"model_name\": \"mobilenet_v2\", \"pretrained\": True}, \"name\": \"load_model_from_torch_hub...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"model_name\": \"facenet\", \"pretrained\": True}, \"name\": \"load_facial_recognition_model\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"model\": None, \"document\": \"Neural networks play a crucial role in the development of...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"text_batch\": [\"Great service, I\"m very satisfied.\", \"The product arrived damaged, I\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"train_features\": \"Wall_Area, Roof_Area, Overall_Height, ...\\n210.0, 220.0, 3.5, ...\\...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"project_identifier\": \"NextGen Software\", \"include_tasks\": True, \"include_blockers\": ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"category\": None, \"features\": [\"language learning\"]}, \"name\": \"find_gamification_apps...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"category\": None, \"features\": [\"virtual room layout\", \"adjustable wall heights\", \"ext...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"recipient\": \"+1234567890\", \"subject\": \"Quarterly Planning Meeting\", \"body\": \"Hi Jami...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"sync_accounts\": True, \"track_spending\": True, \"manage_bills\": True, \"financial_goals...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"category\": None, \"number_of_games\": 5}, \"name\": \"get_trending_games\"}...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"user_id\": \"tm_456\", \"preferences\": {\"task_prioritization\": True, \"deadline_reminders...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"device_type\": \"Android\", \"sort_criteria\": {\"genre\": True, \"mood\": True}}, \"name\": \"o...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"start_location\": \"San Francisco\", \"end_location\": \"Los Angeles\", \"avoid_tolls\": True...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"posts\": [{\"platform\": \"Facebook\", \"image_path\": \"/path/to/facebook/image.jpg\", \"capt...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"package_name\": \"numpy\", \"upgrade\": True}, \"name\": \"install_package\"}...\n", "Error parsing tool call: {\"arguments\": {\"package_name\": \"pandas\", \"upgrade\": True}, \"name\": \"install_package\"}...\n", "Error parsing tool call: {\"arguments\": {\"package_name\": \"requests\", \"upgrade\": True}, \"name\": \"install_package\"}...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"language\": \"Python\", \"code_snippet\": \"print(\"Hello, Python!\")\", \"expected_output\": \"...\n", "Error parsing tool call: {\"arguments\": {\"language\": \"JavaScript\", \"code_snippet\": \"console.log(\"Hello, JavaScript!\")\", \"expec...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"code\": \"def factorial(n):\\n return 1 if n==0 else n*factorial(n-1)\\n\\ntry:\\n r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"source_code\": \"def calculate_sum(a, b):\\n total = a + b\\n return total\\n\\nresu...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"script_path\": \"/home/user/project/scripts/data_processor.py\", \"include_memory\": True...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"language\": \"Python\", \"test_case\": \"Test the \"add\" function with inputs 2 and 3.\", \"e...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"historical_data\": \"Stock_Pair_1.csv\", \"cointegration_result\": True}, \"name\": \"genera...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"network_data\": \"{\"network_performance\": [{\"timestamp\": \"2023-04-01T09:15:00Z\",\"serve...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"dashboard_title\": \"AlgoTrade Performance Dashboard\", \"kpi_metrics\": [\"total return\",...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"strategy_types\": [\"momentum trading\", \"mean reversion\", \"arbitrage\"], \"historical_da...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"historical_data\": \"SP500_historical_stock_data.csv\", \"real_time_data_feed\": True}, \"...\n", "Error parsing tool call: {\"arguments\": {\"historical_data\": \"SP500_historical_stock_data.csv\", \"real_time_data_feed\": True}, \"...\n", "Error parsing tool call: {\"arguments\": {\"historical_data\": \"SP500_historical_stock_data.csv\", \"real_time_data_feed\": True}, \"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"text_snippets\": [\"Apple\"s latest iPhone model receives overwhelming positive reviews...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"real_time_processing\": True, \"data_sources\": [\"Exchange feeds\", \"Direct market acces...\n", "Error parsing tool call: {\"arguments\": {\"storage_type\": \"Scale-out NAS\", \"data_protection\": True}, \"name\": \"setupDataStorageS...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"asset_id\": \"ENRG00123\", \"inspection_data\": \"{\"asset_id\":\"ENRG00123\",\"inspection_resu...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"sensor_data\": \"{\"sensor_readings\":[{\"sensor_id\":\"T101\",\"value\":395,\"unit\":\"K\",\"times...\n", "Error parsing tool call: {\"arguments\": {\"historical_maintenance_records\": \"{\"maintenance_records\":[{\"equipment_id\":\"Pump_A3\",...\n", "Error parsing tool call: {\"arguments\": {\"optimization_data\": \"{\"sensor_readings\":[{\"sensor_id\":\"T101\",\"value\":395,\"unit\":\"K\",...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"asset_id\": \"P-2543\", \"inspection_date\": \"2023-04-01\", \"outcome_details\": {\"condition...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"service_requests\": \"{\"id\": \"SR1001\", \"serviceType\": \"Electric\", \"location\": \"321 Oak...\n", "Error parsing tool call: {\"arguments\": {\"operation_data\": \"{\"operationId\": \"OP3001\", \"agentId\": \"FA2001\", \"status\": \"In Progr...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"fuel_consumption_data\": \"{\"fuels\":[{\"type\":\"Coal\",\"consumption\":50000},{\"type\":\"Natu...\n", "Error parsing tool call: {\"arguments\": {\"operational_parameters\": \"{\"energy_output\":\"500MWh\",\"fuel_feed_rate\":\"2000kg/h\",\"ope...\n", "Error parsing tool call: {\"arguments\": {\"historical_emissions\": \"{\"records\":[{\"date\":\"2021-01-01\",\"emissions\":800},{\"date\":\"2...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"demographic_data\": \"{\"population_age_groups\":{\"0-14\":15,\"15-24\":12,\"25-54\":42,\"55-74...\n", "Error parsing tool call: {\"arguments\": {\"water_usage_data\": \"{\"monthly_water_usage\":{\"Jan\":50,\"Feb\":45,\"Mar\":40,\"Apr\":35,\"May...\n", "Error parsing tool call: {\"arguments\": {\"water_usage_data\": \"{\"monthly_water_usage\":{\"Jan\":50,\"Feb\":45,\"Mar\":40,\"Apr\":35,\"May...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"mapId\": \"map123\", \"layerName\": \"Gas Pipeline Network\", \"layerType\": \"line\", \"visibil...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"mapId\": \"map_001\", \"layerName\": \"Electricity Coverage\", \"layerType\": \"line\", \"visibi...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"energy_output_data\": \"{\"solar_panels\": [{\"id\": \"SP1\", \"output\": 50, \"timestamp\": \"20...\n", "Error parsing tool call: {\"arguments\": {\"historical_energy_data\": \"{\"solar_panels\": [{\"id\": \"SP1\", \"output\": 50, \"timestamp\":...\n", "Error parsing tool call: {\"arguments\": {\"current_settings\": \"{\"solar_panels\": [{\"id\": \"SP1\", \"setting\": \"default\"},{\"id\": \"SP...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"network_data\": \"{\"network_logs\": [{\"timestamp\": \"2023-03-15T08:30:00Z\",\"source_ip\": ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"code\": \"const foo = { bar: \"baz\" };\", \"style_guide\": \"Airbnb\"}, \"name\": \"format_code...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"server_types\": [\"physical_servers\", \"virtual_machines\", \"cloud_services\"], \"backup_f...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"firewall_id\": \"fw-12345\", \"include_rules\": True}, \"name\": \"audit_firewall_settings\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"dataset_path\": \"/company/dataset/images\", \"deduplication_method\": \"content_aware\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"file_path\": \"sales_records.csv\", \"storage_tier\": \"cold\", \"encryption\": True, \"indexi...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"dataset\": \"industry_survey_responses.csv\", \"strata_column\": \"Industry\", \"sample_size...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"queries\": [\"SELECT * FROM orders INNER JOIN customers ON orders.customer_id = custom...\n", "Error parsing tool call: {\"arguments\": {\"table\": \"customers\", \"query_patterns\": [\"SELECT * FROM orders INNER JOIN customers O...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"date\": None}, \"name\": \"get_current_quarter\"}...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"database_name\": \"SQLServerDB\", \"backup_type\": \"full\", \"encryption_enabled\": True, \"p...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"include_memory_usage\": None, \"include_state\": None}, \"name\": \"list_active_processes\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"directory\": \"/var/log\", \"text\": \"ERROR\", \"recursive\": True}, \"name\": \"find_files_con...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"path\": \".\", \"all_files\": True}, \"name\": \"list_directory_contents\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"supply_chain_data\": \"{\"inventory_levels\":{\"engines\":120,\"transmissions\":75,\"tires\":5...\n", "Error parsing tool call: {\"arguments\": {\"production_data\": \"{\"line_capacity\":{\"Line 1\":\"5 vehicles per hour\",\"Line 2\":\"4 vehi...\n", "Error parsing tool call: {\"arguments\": {\"quality_data\": \"{\"defect_rates\":{\"Electrical systems\":\"1%\",\"Powertrain\":\"2%\"},\"inspe...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"supplier_database\": \"{\"suppliers\": [{\"supplier_id\": \"S001\", \"name\": \"AutoParts Co.\",...\n", "Error parsing tool call: {\"arguments\": {\"inventory_data\": \"{\"items\": [{\"part_id\": \"P1001\", \"current_stock\": 150, \"optimal_sto...\n", "Error parsing tool call: {\"arguments\": {\"parts_tracking_system\": \"{\"parts\": [{\"part_id\": \"P1001\", \"location\": \"Warehouse\", \"s...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"historical_sales_data\": \"{\"sales\": [{\"date\": \"2021-01-01\", \"product_id\": \"A01\", \"uni...\n", "Error parsing tool call: {\"arguments\": {\"supplier_metrics\": \"{\"suppliers\": [{\"supplier_id\": \"S001\", \"delivery_time_days\": 5, ...\n", "Error parsing tool call: {\"arguments\": {\"logistics_data\": \"{\"logistics\": [{\"shipment_id\": \"L001\", \"outlet_id\": \"R001\", \"deliv...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"sales_history\": \"Previous 6 months\", \"trend_analysis\": True}, \"name\": \"predict_inven...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"service_order_id\": \"SVO-7781\", \"customer_id\": \"CUST-9809\", \"vehicle_id\": \"VHCL-3078\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inventory_database\": \"{\"products\":[{\"item_id\":\"SM123\",\"name\":\"Smartphone Model X\",\"s...\n", "Error parsing tool call: {\"arguments\": {\"suppliers_list\": \"{\"suppliers\":[{\"supplier_id\":\"SUP1\",\"name\":\"MicroChips Ltd\",\"compo...\n", "Error parsing tool call: {\"arguments\": {\"tracking_system\": \"{\"shipments\":[{\"shipment_id\":\"SH001\",\"sku\":\"SM123\",\"current_locat...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"reports_json\": \"/path/to/consulting_reports.json\", \"entity_types\": [\"Organization\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"automotive_texts\": \"The 2020 Lexus RX 350 redefines luxury and performance, featurin...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"product_models\": [\"X100\", \"Y200\", \"Z300\"], \"metrics\": [\"output\", \"defect_rates\", \"ma...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"file_path\": \"path/to/project_update.pptx\", \"slide_number\": 3, \"new_layout\": \"Title: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"user_id\": \"entrepreneur123\", \"calendar_type\": \"google\", \"view_type\": \"monthly\", \"rem...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"audio_url\": \"https://example.com/audio/customer-service-call1.mp3\", \"language_code\":...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"enableHighAccuracy\": True, \"timeout\": 30000, \"maximumAge\": 60000}, \"name\": \"getCurre...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"criteria\": [\"unusual_format\", \"missing_information\"], \"action\": \"log_and_route\", \"at...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inventory_data\": \"{\"warehouse_A\": {\"item_1\": 20, \"item_2\": 50}, \"warehouse_B\": {\"ite...\n", "Error parsing tool call: {\"arguments\": {\"supplier_schedule_data\": \"{\"supplier_1\": {\"next_delivery_date\": \"2023-04-15\", \"order...\n", "Error parsing tool call: {\"arguments\": {\"shipment_tracking_data\": \"{\"shipment_1\": {\"expected_delivery\": \"2023-04-10\", \"curren...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"source_portal\": \"Our Online Portal\", \"target_crm\": \"Our CRM System\", \"data_fields\": ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"source_systems\": [\"CRM\", \"Customer Support\", \"Sales Transactions\"], \"primary_key\": \"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"source_system\": \"legacy_CRM\", \"target_system\": \"cloud_CRM\", \"data_types\": [\"contact_...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"student_data\": \"StudentID,FirstName,LastName,Email,AcademicRecord,CoursePreference\\n...\n", "Error parsing tool call: {\"arguments\": {\"course_list\": \"CourseID,CourseName,InstructorID,AvailableSlots\\nMath101,Calculus I,P...\n", "Error parsing tool call: {\"arguments\": {\"grading_format\": \"{\"grading_scale\":{\"A\":\"90-100\",\"B\":\"80-89\",\"C\":\"70-79\",\"D\":\"60-69\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inquiry_sources\": [\"email\", \"website\", \"phone\"], \"crm_system\": \"Salesforce\", \"lead_p...\n", "Error parsing tool call: {\"arguments\": {\"product_catalog\": \"healthcare_products_catalog.json\", \"availability_check\": True, \"d...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"source_format\": [\"PDF\", \"paper_copy\", \"digital_document\"], \"target_format\": \"cloud_b...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"exception_type\": \"System\", \"log_to_database\": True, \"notify_support\": True, \"include...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"case_files_directory\": \"/cases/2023\", \"output_format\": \"PDF\", \"indexing\": True}, \"na...\n", "Error parsing tool call: {\"arguments\": {\"client_data_source\": \"CRM_system\", \"background_check_required\": True, \"risk_assessme...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"table_identifier\": \"//table[@id=\"transaction_table\"]\", \"columns\": [\"Transaction ID\",...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"deployments\": [{\"image\": \"service-a:latest\", \"replicas\": 2, \"service_port\": 8080, \"e...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"production_forecast\": \"{\"products\": [{\"product_id\": \"P001\", \"forecasted_quantity\": 5...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"pickup_location\": \"downtown hotel\", \"dropoff_location\": \"city\"s main train station\",...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"flight_data\": [{\"flight_number\": \"DL403\", \"estimated_arrival\": \"2023-05-30T18:45:00+...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"service_requests\": \"{\"service_requests\":[{\"Request ID\":\"SR001\",\"Location\":\"1234 Elm ...\n", "Error parsing tool call: {\"arguments\": {\"assignments\": \"{\"assignments\":[]}\", \"traffic_data\": \"{\"traffic_data\":[{\"Route\":\"A1 t...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"erp_system_id\": \"erp_789\", \"manufacturing_data\": \"{\"order_id\": \"order_123\", \"product...\n", "Error parsing tool call: {\"arguments\": {\"erp_system_id\": \"erp_789\", \"inventory_data\": \"{\"product_id\": \"prod_456\", \"location\":...\n", "Error parsing tool call: {\"arguments\": {\"erp_system_id\": \"erp_789\", \"quality_data\": \"{\"product_id\": \"prod_456\", \"defect_rate\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"delivery_data\": \"path/to/delivery_data.csv\", \"cost_constraints\": {\"max_cost\": None, ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"The solar system consists of the sun and all the objects that orbit it, incl...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"feedback_records\": \"[{\"feedback_id\": \"FB001\",\"customer_id\": \"CU789456\",\"timestamp\": ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"interaction_logs\": \"{\"interactions\":[{\"customer_id\":\"58293\",\"date\":\"2023-04-05\",\"int...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"customer_id\": \"CUST12345\", \"preferences\": {\"email\": True, \"sms\": True, \"phone\": Fals...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"departments\": [{\"department_id\": \"ER\", \"shift_requirements\": {\"day\": 4, \"night\": 3}}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inventory_data\": \"{\"inventory\": [{\"product\": \"Amoxicillin\", \"quantity\": 1500, \"turno...\n", "Error parsing tool call: {\"arguments\": {\"expiration_data\": \"{\"expiration\": [{\"product\": \"Amoxicillin\", \"quantity\": 200, \"expi...\n", "Error parsing tool call: {\"arguments\": {\"logistics_data\": \"{\"routes\": [{\"deliveryId\": \"DL001\", \"origin\": \"Warehouse A\", \"dest...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"historical_sales\": \"{\"sales_records\":[{\"product_id\":\"HX12\",\"date\":\"2022-03-15\",\"quan...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"platform\": \"Twitter\", \"count\": 2, \"authentication_token\": None}, \"name\": \"retrieve_l...\n", "Error parsing tool call: {\"arguments\": {\"platform\": \"Twitter\", \"content\": \"Excited to learn about tech stacks for desktop app...\n", "Error parsing tool call: {\"arguments\": {\"platform\": \"Twitter\", \"post_id\": \"1234567890\", \"authentication_token\": None}, \"name\"...\n", "Error parsing tool call: {\"arguments\": {\"platform\": \"Twitter\", \"post_id\": \"123456789\", \"comment\": \"This is a fascinating post...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"branch_name\": \"feature-branch\", \"checkout\": True}, \"name\": \"create_branch\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"launch_config\": \"{\\n \"version\": \"0.2.0\",\\n \"configurations\": [\\n {\\n \"name...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"project_id\": \"Event_Coverage_Final\", \"resolution\": \"1080p\", \"watermark\": False}, \"na...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"recipient\": \"colleague@example.com\", \"subject\": \"Project Update - Milestones and Nex...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"title\": \"Meeting Summary\", \"content\": \"This note summarizes the key points from the ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"source\": None, \"file_names\": [\"work_presentation.pptx\", \"annual_report.xlsx\"]}, \"nam...\n", "Error parsing tool call: {\"arguments\": {\"drive\": None, \"file_paths\": [\"E:/movies/old_movie_1.mp4\", \"E:/movies/old_movie_2.avi...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"directory\": \"C:\\\\Users\\\\Username\\\\Documents\", \"extension\": \".txt\", \"include_subdirec...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"Ever since I started using this product, I’ve noticed a significant change i...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"Ever since I started using this product, I’ve noticed a significant change i...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"Ever since I started using this product, I’ve noticed a significant change i...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"applicant_details\": {\"company_name\": \"GlobalRisk Inc.\", \"industry\": \"property insura...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"user_id\": \"user123\", \"transaction_data\": \"Date,Description,Amount,Account ID\\n2023-0...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"client_id\": \"JD-2458\", \"account_type\": \"joint\", \"options\": {\"margin\": True, \"options...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"loan_ids\": [\"LN001\", \"LN002\", \"LN003\", \"LN004\", \"LN005\"], \"historical_data\": True}, ...\n", "Error parsing tool call: {\"arguments\": {\"loan_ids\": [\"LN001\", \"LN002\", \"LN003\", \"LN004\", \"LN005\"], \"current_exposure\": True},...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"transaction_history\": \"{\"transactions\":[{\"customer_id\":\"C12345678\",\"date\":\"2023-03-1...\n", "Error parsing tool call: {\"arguments\": {\"customer_id\": \"C12345678\", \"interaction_logs\": \"{\"interactions\":[{\"customer_id\":\"C12...\n", "Error parsing tool call: {\"arguments\": {\"survey_responses\": \"{\"responses\":[{\"survey_id\":\"S987654\",\"customer_id\":\"C12345678\",\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"claims_list\": \"details such as claim ID, claimant\"s name, date of claim, type of wea...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"metrics\": [\"average_test_scores\", \"graduation_rates\", \"attendance_rates\"], \"level\": ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"Pouvez-vous m\"aider avec ma commande?\", \"source_language\": \"fr\", \"target_lan...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"specialization\": \"Kitchen renovation\", \"minimum_experience\": 5, \"license_required\": ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"source_datasets\": [\"temperature_data_2010-2020\", \"precipitation_data_2010-2020\", \"sa...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"template\": \"Dear {first_name},\\n\\nWe\"re excited to offer you an exclusive deal to st...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"by_region\": True}, \"name\": \"generate_pipeline_report\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"supply_chain_data\": [{\"supplier_id\": \"S12345\", \"manufacturer_id\": \"M54321\", \"transac...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"reviews\": [\"Absolutely loved the stay! The rooms were immaculately clean, and the ho...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"feedback_data\": \"[{\"customerId\":\"C13579\",\"feedbackDate\":\"2023-03-15\",\"comments\":\"The...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"product_database\": \"{\"products\": [{\"sku\": \"RX001\",\"name\": \"Amoxillin\",\"stock_level\":...\n", "Error parsing tool call: {\"arguments\": {\"supplier_information\": \"{\"suppliers\": [{\"supplier_id\": \"SUP1001\",\"name\": \"Pharma Sup...\n", "Error parsing tool call: {\"arguments\": {\"distribution_data\": \"{\"distribution\": [{\"route_id\": \"R101\",\"from\": \"Central Warehous...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"historical_sales_data\": \"{\"2019_Q3\": {\"apples\": 1200, \"oranges\": 900}, \"2019_Q4\": {\"...\n", "Error parsing tool call: {\"arguments\": {\"delivery_destinations\": \"{\"destinations\": [{\"id\": 1, \"address\": \"1234 Market St, Cit...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inventory_data\": \"{\"inventory\":[{\"product_name\":\"Hydrating Facial Cleanser\",\"SKU\":\"H...\n", "Error parsing tool call: {\"arguments\": {\"suppliers_data\": \"{\"suppliers\":[{\"supplier_name\":\"Natural Ingredients Ltd.\",\"deliver...\n", "Error parsing tool call: {\"arguments\": {\"shipment_tracking_data\": \"{\"shipments\":[{\"carrier\":\"FastDelivery Couriers\",\"tracking...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"items\": [{\"item_id\": \"OTC456789\", \"quantity\": 2, \"price\": 5}, {\"item_id\": \"OTC987654...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"customer_details\": {\"name\": \"Alison O\"Brien\", \"email\": \"alison.obrien@email.com\", \"p...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inventory_database\": \"{\"products\":[{\"product_id\":\"A123\",\"name\":\"Organic Apples\",\"sto...\n", "Error parsing tool call: {\"arguments\": {\"inventory_database\": \"{\"products\":[{\"product_id\":\"A123\",\"name\":\"Organic Apples\",\"sto...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"inventory_data\": \"{\"products\": [{\"id\": \"P001\", \"name\": \"Organic Apples\", \"quantity\":...\n", "Error parsing tool call: {\"arguments\": {\"suppliers_network\": \"{\"suppliers\": [{\"id\": \"S001\", \"name\": \"Fresh Farms Ltd.\", \"cont...\n", "Error parsing tool call: {\"arguments\": {\"logistics_data\": \"{\"shipments\": [{\"tracking_number\": \"1Z999AA10123456784\", \"carrier\"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"layout_blueprint\": \"residential_area_blueprint.pdf\", \"utility_requirements\": {\"water...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"facility_id\": \"FAC123\", \"camera_types\": [\"infrared\", \"HD\"], \"motion_detection\": True...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"Egnyte embeds AI into a variety of content-related workflows and understand ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"I\"m amazed at the quality of the product. Exceeded my expectations!\", \"langu...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"I\"m amazed at the quality of the product. Exceeded my expectations!\", \"langu...\n", "Error parsing tool call: {\"arguments\": {\"text\": \"I\"m amazed at the quality of the product. Exceeded my expectations!\", \"langu...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"num_devices\": 10, \"rounds_per_epoch\": 5, \"secure_aggregation\": True}, \"name\": \"initi...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"title\": \"Board Meeting\", \"description\": \"Discussing quarterly goals\", \"location\": \"O...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"file_path\": \"/data/data/com.mygame.app/game_progress.json\", \"content\": \"{\"level\": 5,...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"hd_video_enabled\": True, \"microphone_mode\": \"VoiceIsolation\", \"camera_orientation\": ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"category\": None, \"features\": [\"genre categorization\", \"sort by artist\", \"sort by alb...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"start_location\": \"San Francisco, CA\", \"end_location\": \"Los Angeles, CA\", \"avoid_high...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"participant_count\": 5, \"add_participants_enabled\": True, \"multitasking_support\": Tru...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"browser_name\": \"chrome\", \"headless\": True}, \"name\": \"initialize_browser\"}...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"urls\": [\"https://www.marketwatch.com/\", \"https://www.bloomberg.com/markets/stocks\", ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"browser_name\": \"chrome\", \"headless\": True}, \"name\": \"initialize_browser\"}...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"min_length\": 12, \"require_uppercase\": True, \"require_numbers\": True, \"require_specia...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"event_name\": \"All-Day Outdoor Team-Building Activity\", \"event_date\": \"2023-05-20\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"virtual_network_name\": \"VNet1\", \"enable_ddos_protection\": True}, \"name\": \"enable_ddo...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"project_id\": \"my-gcp-project\", \"include_bindings\": True}, \"name\": \"audit_iam_policie...\n", "Error parsing tools string: ...\n", "Error parsing tool call: {\"arguments\": {\"task_name\": \"daily_data_load_task\", \"schedule\": \"0 2 * * *\", \"warehouse\": \"my_wareho...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do you define \"alternative methods of grading\" and what are some e...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide more examples of a reader\"s purpose in reading a text?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given information, how would you advise someone to approa...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think would be the most...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you think of other ways to convert a matrix into reduced row-echel...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the purpose of the Gauss-Jordan elimination procedure?\", \"How ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What can be done if a homogeneous system is inconsistent?\", \"How can o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, can you infer the number of poss...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is propositional logic and why do computer scientists study it?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"an you identify any connections between vector addition and scalar mul...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why is it important to set up a strong and engaging introduction for a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What might be the next logical step for a computer science student aft...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what can we conclude about the r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the rationale behind rule 3 in computing Pr(U ∪ R)?\", \"How can...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of embodied cognition be applied to understanding ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how effective is matrix and vector notation in solvin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does probability help us make predictions about uncertain events?\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What do you think would happen if an edge is removed from a free tree?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What potential challenges or obstacles might a reader face when trying...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What do you think would happen if we used a different method to conver...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given information, can we conclude that probability measu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In what other real-world scenarios might partial permutations be appli...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"hy is it important to have a clear understanding of vector space prope...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide any tips for effectively using quantifiers in predicat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can we predict about the solut...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do different industries and media view the borrowing or stealing o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could you use the two\"s-complement scheme to find the difference b...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can you troubleshoot and identify any faulty conclusions in a proo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your opinion on the use of spatial positioning in graph diagra...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some effective ways to cope with writing anxiety?\", \"How can ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what might be a potential outcome o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you give an example of a statement in predicate logic that could h...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can understanding the sociohistorical context of an argument aid i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the reasoning behind the inclusion of the unexpressed premise ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the text, what may be some potential challenges for a writer ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can be used to make writing more concise?\", \"How can o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we determine if a film or text is truly promoting gender equal...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of interpretive position and lens relate to the ov...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do you think the concepts and information discussed in this docume...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of presuppositions be applied to real-world situat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the key differences between the frequentist and Baye...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How effectively does the author present the advantages and disadvantag...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the running time of an algorithm vary depending on the type o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think is the author\\\"s ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concepts of syntax and tone be applied to improve one\"s wr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the example given in the text, can you explain the concept of...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what are some potential conseque...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the chapter, what do you think the future ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can be used to avoid falling into the trap of writing ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How many different finishes are possible for the top ten golfers in a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how effective is the use of the \"primed\" symbols in t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"ow can one effectively use electronic copies of books to enhance their...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, do you think Aristotelian or Rogerian argumentation i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what do you think could happen i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are some common errors or mistakes that people m...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most challenging aspect of using mathemat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the definition of a nonsingular matrix?\", \"How is a si...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What resources are recommended for beginning research?\", \"How can one ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What steps would you take to troubleshoot and resolve a problem with a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why is it important to give credit to the original author when using o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you agree with the statement that \"all writing is created by people...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a partial permutation and a reg...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which type of relation (extensional or intensional) i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which type of tree (free or rooted) is more useful in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the concept of an \"ideal reader\" in your own words?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What might be a potential issue with relying on thesaurus syndrome to ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain what is meant by a \"homogeneous system\"?\", \"What do yo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are relations and sets connected?\", \"Can you provide an example of...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the concept of exigency and its role in writing in you...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your opinion on the statement that \"argument is a conversation...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of interpretation be applied to other forms of med...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one troubleshoot and determine if a proposition is atomic or c...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes for a successful and effective introductio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"ow does the definition of vector equality differ from traditional noti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the relationship between discrete mathematics and comp...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a problem that may arise during the rese...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the thought process behind using rubrics as a tool for...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the difference between a direct proof and an indirect proof?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we use conditional probability to troubleshoot problems in cal...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some potential underlying causes of writing anxiety?\", \"Can w...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a situation where a briefcase would be m...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between a free tree and a rooted tree?\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one efficiently compute the null space of a matrix?\", \"What ar...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What logical inferences can we make based on the given information abo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can alternative grading methods be applied to different subject ar...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a writing task that may cause writing an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can be used to understand an audience\"s values and bel...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one determine if a tree is a binary tree or not?\", \"Can you su...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information presented in the document, what is likely to ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do backpacks and briefcases differ in terms of functionality and p...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Who is responsible for overseeing the police?\", \"How can Ahmed further...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the proof, what can be inferred about the ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what can you infer about the rel...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we use the principles of probability to make more informed dec...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of pivot columns and free variables related in a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of how a thesis that simply posits reasons ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, is it more useful to think of sets as abstract concep...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the logical operator ⇒ play a crucial role in automated knowl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the decision to use \"primed\" symb...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might an organic structure for an argumentative paper allow for mo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between a consistent and an inconsisten...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of a predicate be applied to real-world situations...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important property of a matrix in re...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to a writer looking to create a sense of ur...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the null space of a matrix and how is it related to homogeneou...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most significant or useful aspect of pred...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a claim and data in the Toulmin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind using row operations to solve sys...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one effectively balance a binary search tree to prevent perfor...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what is the maximum value that can ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some potential obstacles a writer may face when trying to eff...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you agree with the author\"s argument that backpacks are more practi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how does the use of predicates and quantifiers in pre...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In what ways has the internet changed the research process?\", \"How can...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why is the Fundamental Theorem of Counting considered a fundamental co...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the Archetypes be used to help guide understanding of definiti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think is the purpose of...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given text, what do you think would happen to the total n...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the use of the examples given in the document to expla...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, how would you define the concept of...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to someone attempting to prove a propositio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we apply the concept of equation operations to real-world situ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are some strengths and weaknesses of using truth...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might the concept of mathematical induction be applied to real-wor...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Is the set { Will, Smith } the same as the set { Smith, Will }?\", \"Wha...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the purpose and importance of the \"⇒\" operator in pr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the given text, can you make any logical i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one make logical inferences based on the information presented...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might writing anxiety be connected to one\"s personal experiences a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can be inferred about the rela...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why do you think it is important for students to learn how to read and...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which scheme is the most efficient for representing n...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique or assess the effectiveness of the examples used in t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes an argument \"good\" or effective?\", \"Can yo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a directed and undirected graph...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, can you infer any potential drawbac...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the potential benefits of using an \"I\" voice in academic writ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What do you think would happen to the efficiency of a binary search tr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the use of alternative grading methods address potential bias...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are partial permutations and combinations connected in terms of th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important factor in determining the ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind using the Gauss-Jordan eliminatio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are Theorem EOPSS and equation operations connected in the process...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between the two types of quantifiers in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of degree and adjacency connected in the context ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the use of exigency connect a writer\"s thesis with the audien...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the main argument presented in the organic college paper examp...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you come up with a different way of counting the number of possibl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might asking students to write only in standardized English be pro...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you suggest approaching a proof that requires the use of the...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can a computer science student best approach learning and understa...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you diagnose and solve a problem in a system of equations wi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Who argues that previous studies were incomplete and why?\", \"What is t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the purpose of using the reduced row-echelon form of an augmen...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the main argument of the text in your own words?\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What challenges may arise in determining the production schedule for t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one ensure that their argument is not violating any of the rul...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide reasoning behind the design decision to use different ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design of the notation used t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of concision and correctness connected in writing...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the formula for calculating condi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to the production manager for making the be...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we easily recognize when a system of linear equations is incon...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the two types of quantifiers in predicate logic and how do th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the distributive property of sets, proved in Chapter 2, be app...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can writers troubleshoot the issue of feeling overwhelmed by the r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the value of r in the given system of equations?\", \"How many n...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can developing a regular writing practice help mitigate writing an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the text, what are some common strategies for managing writin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you believe that a reader\"s background and purpose can significantl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do different bases relate to the concept of place value in a numbe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what do you predict will be ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between the concepts of \"intension\" and...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the different rules and concepts of probability discussed in th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the use of recursion in tree traversal?\", \"In your op...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind using the CRAAP test as a tool fo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes recursion such a powerful and useful tool ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How many different combinations are possible with two values (0 or 1) ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the four strategies for invoking exigency relate to each other ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what is likely to be the mai...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the difference between the universal quantifier and the existe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What steps can we take to address any potential issues or flaws in our...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the purpose and function of De Morgan\"s Laws in logi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important rule for ethical arguments...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the definition of a proper subset and how does it differ from ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can be used to approach global revision?\", \"How can in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most efficient way to convert numbers fro...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between the sign-magnitude and two\"s-co...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might an author use fluff in their writing?\", \"In what ways can re...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of partitions be applied to real-world situations?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of a free tree differ from that of a rooted tree?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the first step in proving by mathematical induction and what i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can be used to troubleshoot and resolve potential issu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What might be the next logical step in the conversion process if we wa...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the significance of converting numbers from decimal to hex in ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How has language changed in the digital age, and what are some books t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some potential challenges that instructors may face when impl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a Tier 4 source and explain why it may n...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, why do computer science students...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the differences between sets and arrays?\", \"How are ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the traditional method of grading and why is it still widely u...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Is the equation x^2 + xy + tan(y^3) = 0 linear or not? Why or why not?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes a source credible and reliable?\", \"How can...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What does the equation 0 = 0 mean and how does it affect the solution ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain how the variables b, s, and f are related to the produ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important aspect of a good thesis?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the text, why is it important to have a learning community du...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the use of the BST property in or...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your opinion on the effectiveness of the five-paragraph struct...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between directed and open-ended questio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of \"writing invites discovery\" be applied to other...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are the strengths and weaknesses of using rubric...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the importance of having a clear and specific thesis i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you identify any relationships between sets and boolean logic?\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the different tiers of secondary sources relate to each other i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do alternative grading methods connect to broader discussions and ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the concept of \"argument as a dance\" and how it relate...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why is it important for students to move beyond the five-paragraph str...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which operation is more important for effectively com...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of place value be applied to other numerical syste...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can you predict about the numb...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the techniques and resources discussed in this chapter relate t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does violating the rules for critical engagement lead to fallaciou...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind using discrete mathematics in com...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between an endorelation and a regular r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the author\"s opinion on using matrix multiplication as the def...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design decision to use the re...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, do you think traditional grading accurately reflects ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what can we infer about the ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of the strong form and weak form of mathematical ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of how matrix and vector notation can be ap...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you identify any connections or relationships between the three-st...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what are some potential challeng...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the use of specific examples in t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why is it important for instructors to consider alter...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your own words, explain the concept of a predicate and how it diffe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to someone trying to understand this proof?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you give an example of a situation in which probability played a r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"hat strategies can be used to troubleshoot problems involving vector s...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the difference between the two types of quantifiers in predica...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are binary numbers connected to the fundamental unit of storage in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the two\"s-complement scheme allow for addition and subtractio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can be inferred about the impo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given text, do you agree with the author\"s definition of ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on Theorem HSC, why can we say that the system is consistent?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might you troubleshoot issues with graph traversal if the graph co...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most challenging aspect of converting a m...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the definition of critical thinking according to the AAC&U?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can writers use to make their writing more concise?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain a common mistake or misunderstanding students may have...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the role of background knowledge in calculating condit...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What reasoning can be given for the decision to narrow the focus of Ah...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can writers balance the use of stylistic modes and communication s...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can understanding the appeals of ethos, logos, and pathos help us ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what may be the next topic covered ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of critical thinking be applied to other areas of ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we determine the meaning behind a relation?\", \"How can we diff...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the primary purpose of revision?\", \"How can a learning communi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, can you make any logical inferences...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you troubleshoot potential issues that may arise when dealin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does understanding the context and values of an audience play a ro...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the cardinality of the set of all integers?\", \"How is the inte...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the definition of syntax and where does the word originate fro...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important logical operator?\", \"Can y...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the use of mathematical notation in the given text?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the purpose of the CRAAP test?\", \"How does the relevance of a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of independent choices relate to the Fundamental ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are your thoughts on the overall structure and organization of th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we use the tools of sets, relations, and functions to predict ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you assess the effectiveness of a solution set for a system ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided in the text, what is a likely conseq...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the focus of discrete mathematics?\", \"How does the concept of ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given probabilities for each contestant, what is the like...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of religious influence on government be applied to...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what can we infer about the role...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a system of linear equations an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important concept to understand abou...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your opinion on the effectiveness of the five-paragraph theme ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What does the number seventeen really represent, beyond its base 10 re...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the rules for ethical arguments be applied to real-world situa...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind Toulmin\"s decision to study argum...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Is a relation always a subset of the Cartesian product between two set...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In what ways can the Fundamental Theorem of Counting be applied in rea...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you predict will be the mai...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of reduced row-echelon form connect to other topi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of permutations and combinations related?\", \"Can ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might round-off errors affect the accuracy of solutions when using...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of embodiment and religion connect in the context ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the CRAAP test help determine the credibility and use value of...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of \"tautologies\" in propositional logic be appli...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind counting two additional places wh...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you predict would happen if...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What steps can be taken to troubleshoot or address Ahmed\"s initial res...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the technique of marking leading 1\"s in the reduced row-echelo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the use of the \"n-choose-k\" notation for binomial coef...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of a base be applied in real-world situations, out...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what can we infer about the proc...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the rules for a valid probability...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the frequentist view of probability and its limitatio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the \"primed\" symbols play a role in the proof?\", \"In what ways ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of concision be applied to different types of writ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are matrices and vectors connected to each other in linear algebra...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most effective way to use probability to ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why do you think concision is important in writing?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a proposition that cannot be true or fal...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are the potential drawbacks or limitations of us...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you agree with the author\"s definition and explanation of interpret...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the author\"s perspective on the purpose of discrete m...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of \"argument as a dance\" be applied to real-world ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you diagnose and solve performance issues with a binary sear...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some common issues that may arise when working with matrices ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why do you think the author emphasizes the importance of pruning in th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of free and dependent variables be applied in real...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given information, what is likely to be the next concept ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What do you think would happen if we tried to add two numbers that res...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of \"implication\" and \"equivalence\" connected in p...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What might happen to the solution set of a system of linear equations ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how useful is the concept of nonsingular matrices in ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a counting problem that can be solved us...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the main points of comparison between backpacks and briefcase...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes the Fundamental Theorem of Counting a powe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to someone who is struggling to choose betw...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one troubleshoot if a set is a proper subset of another set?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the main differences between backpacks and briefcases?\", \"Whi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you define the term \"essay\" as it was popularized by Michel de Mon...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can be used to troubleshoot and resolve issues that ar...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we overcome our dependence on decimal numbers and think more a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes a successful use of exigency in writing?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can students troubleshoot challenges they may face when understand...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the truth value of A ∧ C?\", \"Is the proposition B ∨ C true or ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most challenging aspect of using quantifi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you think of any common mistakes or pitfalls that students may enc...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one ensure that their subsets are mutually exclusive and colle...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the use of the complement in coun...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the concept of partial permutations and provide an e...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to someone trying to determine whether a gr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the shortest route between any two nodes in a free tree?\", \"Ho...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what do you think would happ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can mathematical induction be applied to different types of proble...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind designating a root in a rooted tr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given text, what do you think the author\"s stance is on t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you think of a real-world situation where the concept of mathemati...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the importance of appealing to an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how effective is the use of a queue data structure fo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the main differences between a one-story, two-story,...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind treating the left and right child...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some potential issues that can arise when dealing with sets o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the advice to remove contractions...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of pivot columns and reduced row-echelon form rela...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we apply the principles of probability to real-world situation...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given examples, can you infer why the chosen base dictate...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the Big O complexity of an algorithm and how is it related to ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, which type of bag would you recomme...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can be inferred about the rela...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of recursion relate to the use of BSTs in organiz...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can a reader ensure that they are approaching a text with an open ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the use of the logical operator ⇒ in artificial intel...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the purpose of a freewrite and how can it benefit students in ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can you define a power set and what is its significance?\", \"Can yo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of tone and voice connected in writing?\", \"Can yo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of warrants help us analyze and construct argumen...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you think the theorems presented in this section are comprehensive ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of subsets and partitions relate to the idea of bi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what do you think will happen if...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you approach troubleshooting a proof that requires the use o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what do you think is likely to h...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of exponential growth apply to the license plate ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one identify and address fallacies in their own arguments?\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most useful aspect of using matrix and ve...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information presented in the text, what do you predict wi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the meaning of \"primed\" symbols in the context of the ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the \"simple trick\" be applied in problem-solving and counting ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the importance of understanding interpretive position ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the main focus of pragma-dialectics in the study of argumentat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, can you predict what the number ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does concision contribute to the overall effectiveness of writing?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important concept to understand when...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can you quickly and effectively find Tier 1 sources for your resea...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you think inquiry-based research is a more effective method than no...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why do you think it is important to remove unnecessary words in writin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of overflow and the use of different schemes for r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you believe that asking students to write only in standardized Engl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how does understanding an audience\"s context and valu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the information presented in this chapter be applied to other ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Imagine you had all the time in the world to research a topic that you...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some potential challenges that a writer may face when using t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of a nonsingular matrix be applied to real-world s...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concepts of linear algebra be applied in determining daily...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide examples of abstract and concrete objects?\", \"How does...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What challenges might arise when converting numbers from decimal to bi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concepts and techniques of linear algebra be applied to gr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which of the four strategies for invoking exigency is...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are trees used in computer programming?\", \"Can you provide other e...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the use of the term \"adjacent\" in the context of graph...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important aspect of Theorem EOPSS an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you approach building a tree for a given set of data?\", \"Wha...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the CRAAP test be applied to evaluate sources outside of tradi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between free and dependent variables in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of free variables be applied to real-world situati...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of inquiry-based research be applied to other area...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the definition of the null space of a matrix?\", \"How many solu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you define a relation extensionally and intensionally?\", \"What is ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind using different schemes for repre...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can understanding the root causes of writing anxiety help a writer...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you diagnose and solve a problem related to understanding an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of how violating the freedom rule can hinde...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the key differences between the five-paragraph theme and the ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain how the number of nodes on level k of a perfect binary...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In what ways can the concepts of propositional logic and logical opera...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes mathematical induction a powerful tool in ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the geometry of the two equations, why do we believe that (3,...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can curiosity be used as a driving force in research?\", \"What are ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What do you think is likely to happen if writers do not pay attention ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might the three-story thesis framework be applied to other forms o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of graph traversal be applied to real-world situat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the given text, what do you predict will b...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the significance of the free and dependent variables i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can be inferred about Ahmed\"s ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you think that trees are the most common data structure in computer...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the use of different research techniques and resources help to...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the Fundamental Theorem of Counting be applied in real-world s...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are the strengths and weaknesses of using a bina...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the use of the reduced row-echelon form in determinin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What steps can a writer take to ensure they are properly citing their ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you agree with the author\"s perspective on revision? Why or why not...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the techniques used to solve systems of linear equations be ap...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between counting permutations and parti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of discrete values be applied to real-world situ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the opposite of concrete?\", \"Would you call a quantity of wate...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can a student best approach solving a system of linear equations u...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the best way to determine which direction to set out on when c...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design decision to use vertic...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind using in-degree and out-degree to...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, why do some people prefer backpacks...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the operators in propositional logic be combined to form compl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important operator in propositional ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between an atomic and a compound propos...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between concision and simplicity in wri...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the four tiers of secondary sources and their respective char...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what is likely to happen next in te...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the four steps in the proof connect and relate to each other?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is an example of a global revision activity mentioned in the text...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the main argument of the book \"Because Internet Understanding ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the debate between backpacks and briefcases relate to larger ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How many different license plates are possible if every character must...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the use of Theorem NMRRI in determining if a matrix is...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can be inferred about the role...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does using matrix and vector notation make it easier to solve syst...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the understanding of citation practices be applied in new writ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the difference between a rooted tree and a binary tree?\", \"Can...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can be inferred about the impa...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the ideas of the base case and the inductive step connected in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are your thoughts on the power and purpose of inquiry in our ever...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the reverse outlining process work?\", \"What are some common r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of \"argument as a dance\" and Toulmin\\\"s method of...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what is the maximum number of ch...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the author connect the concept of revision to the idea of an ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one effectively identify and evaluate the credibility of sourc...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we resolve confusion between an endorelation and a regular rel...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What approach should one take when solving a system of equations with ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why are Tier 1 sources considered the most preferable...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are the strengths and weaknesses of the three-st...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think will happen if a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a Tier 4 source that may be considered a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the use of recursion in tree traversal relate to the concept ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might the company adapt to changes in the food industry?\", \"In wha...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Was this thesis-first or inquiry-based research?\", \"What were the bene...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the BST property and how does it differ from other types of bi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What should a writer do if they are struggling to rephrase a quote or ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"n your opinion, how effective is the use of symbols in defining vector...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes for a successful row-reduction process?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the best approach to solving a counting problem using the Fund...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the purpose of invoking exigency in writing?\", \"How does Wendy...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What proof techniques can be used to solve systems of linear equations...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what might be a potential downside ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how effective is the Fundamental Theorem of Counting ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the principles of probability relate to other fields of study, ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does writing anxiety differ from procrastination?\", \"What factors ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the null space of the matrix B?\", \"Can you prove or disprove t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you give some tips on how to effectively use matrix and vector not...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, can you infer why it is important t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of a three-story thesis be applied to other form...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain how Theorem NMUS can help us troubleshoot solutions to...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the idea of an essay as an attempt connect to the concept of ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how effective is Theorem EOPSS in helping us solve sy...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the definition of writing anxiety and how can someone know if ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a direct proof and an indirect ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What scheme would you recommend for representing negative numbers in a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what makes a source \"good\" for research?\", \"Do you th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you predict what the next step would be in a mathematical inductio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of slope and intersection relate to solving system...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are nonsingular matrices and their null spaces connected to system...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What steps can be taken if the matrix does not end up in reduced row-e...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What strategies can be used to troubleshoot and solve a system of line...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how efficient is Prim\"s algorithm in finding the shor...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the author describe the focus and approach of this book?\", \"W...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why do we say that x3 is a \"free\" or \"independent\" variable in the giv...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Is faveSport now also bijective?\", \"How can we alter things so that it...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What steps should be taken if a source does not pass the CRAAP test?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what is the underlying purpose of t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the proof, what can be predicted about the...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the explanation of endorelations, can you predict how the ext...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the logical operators ∧ and ∨ relate to set operations ∩ and ∪?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the different strategies for avoiding fluff connect to each oth...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between context and argument in an intr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can you determine the unique solution to a system of equations usi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Why do you think academic institutions have strict standards for plagi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you predict would happen if...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design of using capital lette...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how does counting the complement of a set make counti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between a matrix and a vector in linear...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a research question that hits all four c...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How many distinct symbols do we use to represent numbers in a base 10 ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice does the author give to students regarding the use of the ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you think of a time when you had difficulty revising a piece of wr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design decision to define the...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of critical thinking relate to the idea of thinki...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the elements of the CRAAP test interrelate with each other?\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the main purpose of interpretation and how is it unique to eac...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Summarize the concept of graph traversal and how it can be done using ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you predict will happen in ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What reasons does the author give for their preference for backpacks o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in this chapter, what strategies and resource...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what do you think is the lik...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide any tips for effectively using the CRAAP test?\", \"How ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why is revision often seen as a sign of weakness or i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can you future-proof questions and answers in case they become div...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the best approach to revising for fluff in writing?\", \"How can...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why do writers tend to use fluff in their writing?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think the next major de...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your assessment of the proof of Theorem REMEF?\", \"Can you crit...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the main points of the chapter regarding alternative...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most useful theorem for solving systems o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify why it is important to use specific and diversified qu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some common mistakes or misconceptions that may arise when wo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In what ways do authors typically use exigency in genres that are not ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you offer to someone trying to solve a counting prob...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between an in-degree and an out-degree ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What do you think will happen if the storage capacities or raw ingredi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the weak form and what are the two things that need to be prov...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, why do some writers choose to in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the role of religion in the Middle East?\", \"How has religion i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the effectiveness of the \"simple trick\" in counting p...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which strategy for avoiding fluff is the most effecti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the meaning of the term \"constructive proof\"?\", \"How d...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of a tree be applied to organizing and representin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think will be the futur...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might the concept of mathematical induction be applied to other br...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of indirect proof and recursion connected?\", \"Can...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the use of decimal numbers as the default in our unde...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are numbers stored and represented in computer systems?\", \"What is...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the use of matrix and vector notation in linear algebr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can be inferred about the role...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design decision to use equati...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the concept of presuppositions and how it relates to a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the three main categories for secondary sources?\", \"What is t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the distinction between a subset and a proper subset?\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of an \"ideal reader\" be applied to the revision pr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In what ways can the size and shape of a binary tree impact its functi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind using row operations to convert a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think is likely to happ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of exigency be applied in real-world writing situa...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does writing anxiety manifest for different writers?\", \"Can writin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how important is it for individuals to have a basic u...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the rules for ethical arguments connect to the concept of criti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some potential challenges in determining whether a graph is c...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of \"root,\" \"ancestor,\" and \"parent\" related in a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the benefits of using inquiry-based research as opposed to no...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why do people often think of numbers as being represe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are algebraic and geometric approaches related in the study of lin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What was the last thing you were truly curious about? How did you find...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide more examples of when a text that is not current can s...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your assessment of the sources listed in the four tiers?\", \"Ho...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the three main algebras that are commonly used and studied?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given text, what advice would you give to someone trying ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to a novice writer who struggles with formu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which scheme is the most effective for representing n...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of free and dependent variables relate to the redu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided in the text, what do you predict wou...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you troubleshoot a counting problem that involves both permu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Describe the process of inquiry-based research.\", \"What is the differe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is meant by \"antiracist police trainings and strategies\" in the r...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between critical thinking and thinking ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most effective way to approach revision?\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the chapter, why do some instructors choos...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does discussing exigency at the beginning of a writing project hel...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information presented in the document, what can we infer ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the guidelines for constructing an organic college paper be ap...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one effectively understand and use the logical operator ⇒?\", \"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we effectively use probability to estimate the likelihood of o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, can you explain why a valid proo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the discussion of Toulmin\"s method, what advice would you giv...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can students best approach open-ended assignments that may not hav...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design and use of quantifiers...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can writers avoid using vague or generic phrases in their introduc...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, is it more important to focus on correct usage or cri...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind Bloomberg\"s decision to invoke th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what do you predict will happen ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might converting numbers from decimal to binary be useful in real-...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the three key differences between a more organic structure an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the best approach for converting numbers from decimal to hex?\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do different interpretations of the concept of probability affect ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you identify any connections between the topics of obesity rates a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what can be inferred about t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a set with infinite cardinality?\", \"Can ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the meaning of \"row-reducing\" a matrix?\", \"How does th...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the Big O complexity of searching for a specific name in a sim...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, how does inquiry-based research ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important factor to consider when ev...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can we determine about the sol...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of probability be applied in a real-world scenar...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify how Theorem EOPSS is used in the process of solving sy...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of combinations be applied to solve the problem ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the system of equations represented by the given augmented ma...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain a potential issue that may arise when trying to find t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of reverse outlining be applied to other forms o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to students who struggle to find a purpose ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a proposition template and a pr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can a computer scientist use their understanding of discrete mathe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the concept of mathematical induction and its purpos...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, can you infer the relationship betw...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most challenging aspect of solving counti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which interpretation of probability (frequentist or B...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What steps should be taken to convert a matrix to reduced row-echelon ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between a full, complete, and perfect b...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the use of the strong form of mat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the implications of a matrix being singular or nonsingular?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How have religion\"s influence on government impacted the day-to-day li...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In what ways can a text that is relevant to a topic be used in a resea...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the four steps in the proof and what is the goal of the first...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of a null space relate to the solutions of a homo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the decision to only produce 1500...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you critique the author\"s approach to explaining the concept of pr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between abstract and concrete objects?\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most effective way to avoid overcounting ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"According to the Fundamental Theorem of Counting, how many ways can a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the use of notation in expressing relations?\", \"How do...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the text, what might be some potential consequences of not ad...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between open-ended and directed questio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, why do accusations of plagiarism...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the examples of Apple and pop musicians borrowing from other so...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the concept of \"recursive\" in relation to tree travers...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what might be the potential outcome...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the text, what can you infer about the importance of logic in...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the main focus of the study of probability?\", \"How does probab...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what is likely to happen if one ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of recursion be applied to other areas of computer...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of critical thinking and thinking critically relat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, can you infer any common the...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the purpose of Theorem EOPSS and how does it help us in solvin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How many pivot columns does the matrix C have in reduced row-echelon f...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important aspect of discrete mathema...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"ased on the information provided, what can we infer about the importan...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the information provided in a scholarly article be applied to ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why do some people argue that reposting helps spread ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given information, what do you predict would happen if we...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how effective is the author\"s approach to teaching li...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some strategies for overcoming confirmation bias in the resea...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you justify the author\"s statement that revision is the writing?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your opinion on the use of linear algebra in solving real-worl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you troubleshoot and identify any potential errors or incorrect ou...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of \"interpretation\" relate to the examples of Mad...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How effective do you think the concept of Big O complexity is in predi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we apply the concept of conditional probability to make more a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between paraphrasing and patchwriting?\"...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the author\\\"s preference for thin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How has the definition of an essay evolved over time?\", \"In what ways ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the definition of a matrix?\", \"What is the purpose of using bo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are some strategies for identifying and eliminating passive voice...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you share your thoughts on the concept of partitions and their imp...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are trees and graphs related to each other?\", \"Can you identify an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the name of the rule of logic that is considered the workhorse...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can students who are used to the five-paragraph structure adapt to...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do different cultures and contexts shape the elements of argumenta...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you troubleshoot and resolve errors that may arise when usin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the different types of proof mentioned in the text?\", \"How do...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the use of quantifiers in predica...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the Fundamental Theorem of Counting and what does it state?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given examples, what do you think would happen if we cont...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think would happen if c...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What advice would you give to someone who is struggling to understand ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you think religion plays a significant role in Middle Eastern polit...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"n your opinion, how does the definition of vector equality make solvin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might the concept of reduced row-echelon form be applicable in rea...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do different writers approach and cope with writing anxiety?\", \"Do...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, can you infer why a graph must be b...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████████████████████████████████████████████████| 1893/1893 [00:00<00:00, 5791.39it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of Big O complexity and binary search trees relate...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What tips or strategies would you suggest for converting a matrix into...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of vector addition and scalar multiplication conn...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the process of determining the production schedule f...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, are there any potential benefits to experiencing writ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the main goal of the theorems presented in this section?\", \"Ho...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How is probability defined?\", \"What is the purpose of studying probabi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the text, what can be predicted about the ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what can be predicted about ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information in the document, what is the purpose of rubri...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what is the Big O complexity of add...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"As an instructor, how could you effectively incorporate alternative gr...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the text, what is the purpose of the organic structure in col...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the text, what role does a reader\"s purpose play in the inter...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what do you think is likely to be t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you go about troubleshooting issues related to overflow in a...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are the strengths and limitations of using mathe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of how to convert a binary number to a deci...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are nonsingular matrices and their null spaces related?\", \"What is...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is your advice for determining if a matrix is nonsingular or sing...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the reasoning behind recommending the use of academic database...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you believe that the CRAAP test is an effective tool for evaluating...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might the behavior of x3 in the given system of equations affect t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How effective and efficient do you believe the production schedule for...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you agree with the author\"s argument that treating unintentional pl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one troubleshoot an argument that is not effectively appealing...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does our dependence on decimal numbers affect our understanding of...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, are the rules for a valid probability measure suffici...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the three different schemes for treating negative nu...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are the strengths and weaknesses of using quanti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a one-story thesis and a two-st...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you give an example of a real-world problem that can be represente...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important concept to understand when...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of permutations be applied in real-world scenarios...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what is the author\"s background and...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the given definitions, what can be inferred about the relatio...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How might the use of reframing an issue or creating a counterintuitive...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide reasoning behind the choice of symbols for proper and ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could a tree data structure be used to organize and store files on...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"an you clarify the difference between vector equality and traditional ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the elements of style that writers can use to make effective ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a real-world scenario where the relation...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the reasoning behind the design decision to use \"1\" an...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information given, what do you think will be the next top...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we use conflict and disagreement to challenge our own assumpti...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What can be inferred about the concept of factorial from the examples ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you identify any potential errors or mistakes that could occur whe...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, can you infer why binary search tre...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"ow can the concept of vector equality be applied to real-world scenari...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What are the two types of trees discussed in the text?\", \"How does the...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which type of proof is the most powerful?\", \"Do you t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the recommended text for learning about the relationships betw...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what are the benefits and limitations of defining rel...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of Big O complexity be applied to improve the ef...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of sets and predicates related in predicate logic...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"ow does the concept of vector equality relate to systems of equations?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of confirmation bias and flexibility relate to eac...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of precision and ambiguity in language connect to ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what would be the expected running ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could we troubleshoot or resolve any issues with calculating the p...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"According to the text, what is the purpose of Aristotelian argumentati...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a problem that could be solved using mat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"ased on the information provided, what do you predict will be discusse...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the concept of \"rooted tree terminology\" discussed i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one efficiently traverse a tree in pre-order, post-order, and ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you clarify the difference between a computational exercise and a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you recommend approaching the task of organizing and accessi...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is Robert A. Beezer\"s professional website?\", \"What is the ISBN o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what can you infer about the role o...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you recommend avoiding contradictions when dealing with sets...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the concept of a sample space and its role in probabil...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of reduced row-echelon form be applied in solving ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do the concepts of sample space, outcomes, and events relate to ea...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the author suggest using the open source software system, Sag...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Do you think the concept of a null space is an important concept to un...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a sentence that has been made more power...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How could the concept of sets be applied in a real-world situation?\", ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how can rubrics be used as effective tools for guidin...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, which structure (five-paragraph or organic) allows fo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you suggest any potential issues that may arise when converting a ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you provide an example of a situation where the strong form of mat...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of ethos, pathos, and logos connected to understa...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can we interpret the statement \"mathematics is a language\" and wha...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, what is the most important aspect of solving systems ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the internet serve as a valuable resource for research?\", \"Wh...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Based on the information provided, what is the maximum value that can ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How would you suggest approaching the task of defining multiple inputs...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What reasoning does the author provide for using a delayed approach to...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, how well does the document explain the process of con...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you assess the usefulness of the recommended sources for beginning...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the concept of relations be applied in real-world scenarios?\",...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the definition of a directed graph and how does it differ from...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can writers increase the impact of their arguments through the use...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What is the purpose of giving credit to original authors in academic w...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can one diagnose and address issues of wordiness in their writing?...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do academic journals use peer review to determine which articles t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"What potential issues or challenges might arise when trying to apply t...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the example of solving systems of linear equations relate to ...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you summarize the four steps in the proof?\", \"How does the proof d...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How can the techniques and resources discussed in this chapter be appl...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"In your opinion, why is it important to cast a problem in the right fo...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How are the concepts of a null space and a homogeneous system connecte...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"hat is the importance of understanding vector equality in constructing...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How do you see the concepts of arguable thesis and organic structure i...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How does the concept of a base affect the digits used in a number syst...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"Can you explain the difference between a base case and an inductive hy...\n", "Error parsing tools string: ...\n", "Error parsing tool call: \\n{\"arguments\": {\"queries\": [\"How is a matrix defined and what is its purpose in linear algebra?\", \"...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "records = []\n", "for split in d: # Assuming dataset is loaded as 'd'\n", " for item in tqdm(d[split]):\n", " record = {\n", " 'id': item['id'],\n", " 'category': item['category'],\n", " 'subcategory': item['subcategory'],\n", " 'task': item['task'],\n", " 'split': split\n", " }\n", " \n", " conversations = item['conversations']\n", " system_msg = next(msg['value'] for msg in conversations if msg['from'] == 'system')\n", " human_msg = next(msg['value'] for msg in conversations if msg['from'] == 'human')\n", " gpt_msg = next(msg['value'] for msg in conversations if msg['from'] == 'gpt')\n", " \n", " available_functions = extract_functions_from_system(system_msg)\n", " tool_calls = extract_tool_calls(gpt_msg)\n", " \n", " record.update({\n", " 'num_available_functions': len(available_functions),\n", " 'num_tool_calls': len(tool_calls),\n", " 'human_msg_length': len(human_msg),\n", " 'available_functions': [f['function']['name'] for f in available_functions],\n", " 'called_functions': [call['name'] for call in tool_calls],\n", " 'conversation_turns': len(conversations),\n", " 'human_msg': human_msg,\n", " 'gpt_msg': gpt_msg\n", " })\n", " records.append(record)\n", "\n", "df = pd.DataFrame(records)" ] }, { "cell_type": "code", "execution_count": 37, "id": "d5a3a628-17be-48c9-8d2c-35fe18ec3deb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
idcategorysubcategorytasksplitnum_available_functionsnum_tool_callshuman_msg_lengthavailable_functionscalled_functionsconversation_turnshuman_msggpt_msg
085f6c398-69c7-4df2-aed1-29d614a93a26IoT and Home AutomationSecurity Camera ManagementView and Manage Security Camera Feedstrain031670[][get_camera_live_feed, record_camera_feed, get...3I've recently installed a new security system ...<tool_call>\\n{'arguments': {'camera_id': 'fron...
189ef3c87-66bd-46ee-9297-15398fd9a235IoT and Home AutomationSmart Home SetupSet Up a Smart Home Systemtrain02916[][initialize_smart_home_system, create_device_g...3I've recently equipped my home with various sm...<tool_call>\\n{'arguments': {'device_list': ['P...
214657d01-d6d1-46df-8eb1-7267ba820683IoT and Home AutomationThermostat ControlAdjust Smart Thermostat Settingstrain01757[][set_thermostat_schedule]3I recently installed a smart thermostat model ...<tool_call>\\n{'arguments': {'thermostat_id': '...
3c483f963-8a29-4ff0-a684-89be0d0f2843IoT and Home AutomationVoice Commands for Home TasksPerform Home Tasks Using Voice Commandstrain031058[][activate_voice_command, set_thermostat, activ...3I just arrived home and I'm carrying several b...<tool_call>\\n{'arguments': {'command': 'Activa...
481ad724a-bb74-420f-8221-91557b7e5930IoT and Home AutomationLighting ControlControl Smart Lights in a Hometrain02556[][set_smart_light_color, sync_lights_with_autom...3I am preparing my living room for a cozy movie...<tool_call>\\n{'arguments': {'room': 'living ro...
..........................................
188890b96a9f-85c3-459f-95bd-7c58557a4b02Information ExtractionJson SchemaStructured json schema extaction with function...train009349[][]3Can you help me extract queries from the follo...<tool_call>\\n{\"arguments\": {\"queries\": ['hat i...
1889f698e236-d733-4a24-af41-64831a7139acInformation ExtractionJson SchemaStructured json schema extaction with function...train0013462[][]3Can you help me extract queries from the follo...<tool_call>\\n{\"arguments\": {\"queries\": ['How d...
18900eed5d10-8d6e-4aaf-9b49-ad299ee02c5dInformation ExtractionJson SchemaStructured json schema extaction with function...train0011526[][]3Can you help me extract queries from the follo...<tool_call>\\n{\"arguments\": {\"queries\": ['How d...
1891cf305996-bae4-46f2-b725-d540b1d3ea5cInformation ExtractionJson SchemaStructured json schema extaction with function...train0010049[][]3Can you help me extract queries from the follo...<tool_call>\\n{\"arguments\": {\"queries\": ['Can y...
189298c8fda0-ca02-4d3c-ac96-c5bd6bf6904aInformation ExtractionJson SchemaStructured json schema extaction with function...train0010025[][]3Can you help me extract queries from the follo...<tool_call>\\n{\"arguments\": {\"queries\": ['How i...
\n", "

1893 rows × 13 columns

\n", "
" ], "text/plain": [ " id category \\\n", "0 85f6c398-69c7-4df2-aed1-29d614a93a26 IoT and Home Automation \n", "1 89ef3c87-66bd-46ee-9297-15398fd9a235 IoT and Home Automation \n", "2 14657d01-d6d1-46df-8eb1-7267ba820683 IoT and Home Automation \n", "3 c483f963-8a29-4ff0-a684-89be0d0f2843 IoT and Home Automation \n", "4 81ad724a-bb74-420f-8221-91557b7e5930 IoT and Home Automation \n", "... ... ... \n", "1888 90b96a9f-85c3-459f-95bd-7c58557a4b02 Information Extraction \n", "1889 f698e236-d733-4a24-af41-64831a7139ac Information Extraction \n", "1890 0eed5d10-8d6e-4aaf-9b49-ad299ee02c5d Information Extraction \n", "1891 cf305996-bae4-46f2-b725-d540b1d3ea5c Information Extraction \n", "1892 98c8fda0-ca02-4d3c-ac96-c5bd6bf6904a Information Extraction \n", "\n", " subcategory \\\n", "0 Security Camera Management \n", "1 Smart Home Setup \n", "2 Thermostat Control \n", "3 Voice Commands for Home Tasks \n", "4 Lighting Control \n", "... ... \n", "1888 Json Schema \n", "1889 Json Schema \n", "1890 Json Schema \n", "1891 Json Schema \n", "1892 Json Schema \n", "\n", " task split \\\n", "0 View and Manage Security Camera Feeds train \n", "1 Set Up a Smart Home System train \n", "2 Adjust Smart Thermostat Settings train \n", "3 Perform Home Tasks Using Voice Commands train \n", "4 Control Smart Lights in a Home train \n", "... ... ... \n", "1888 Structured json schema extaction with function... train \n", "1889 Structured json schema extaction with function... train \n", "1890 Structured json schema extaction with function... train \n", "1891 Structured json schema extaction with function... train \n", "1892 Structured json schema extaction with function... train \n", "\n", " num_available_functions num_tool_calls human_msg_length \\\n", "0 0 3 1670 \n", "1 0 2 916 \n", "2 0 1 757 \n", "3 0 3 1058 \n", "4 0 2 556 \n", "... ... ... ... \n", "1888 0 0 9349 \n", "1889 0 0 13462 \n", "1890 0 0 11526 \n", "1891 0 0 10049 \n", "1892 0 0 10025 \n", "\n", " available_functions called_functions \\\n", "0 [] [get_camera_live_feed, record_camera_feed, get... \n", "1 [] [initialize_smart_home_system, create_device_g... \n", "2 [] [set_thermostat_schedule] \n", "3 [] [activate_voice_command, set_thermostat, activ... \n", "4 [] [set_smart_light_color, sync_lights_with_autom... \n", "... ... ... \n", "1888 [] [] \n", "1889 [] [] \n", "1890 [] [] \n", "1891 [] [] \n", "1892 [] [] \n", "\n", " conversation_turns human_msg \\\n", "0 3 I've recently installed a new security system ... \n", "1 3 I've recently equipped my home with various sm... \n", "2 3 I recently installed a smart thermostat model ... \n", "3 3 I just arrived home and I'm carrying several b... \n", "4 3 I am preparing my living room for a cozy movie... \n", "... ... ... \n", "1888 3 Can you help me extract queries from the follo... \n", "1889 3 Can you help me extract queries from the follo... \n", "1890 3 Can you help me extract queries from the follo... \n", "1891 3 Can you help me extract queries from the follo... \n", "1892 3 Can you help me extract queries from the follo... \n", "\n", " gpt_msg \n", "0 \\n{'arguments': {'camera_id': 'fron... \n", "1 \\n{'arguments': {'device_list': ['P... \n", "2 \\n{'arguments': {'thermostat_id': '... \n", "3 \\n{'arguments': {'command': 'Activa... \n", "4 \\n{'arguments': {'room': 'living ro... \n", "... ... \n", "1888 \\n{\"arguments\": {\"queries\": ['hat i... \n", "1889 \\n{\"arguments\": {\"queries\": ['How d... \n", "1890 \\n{\"arguments\": {\"queries\": ['How d... \n", "1891 \\n{\"arguments\": {\"queries\": ['Can y... \n", "1892 \\n{\"arguments\": {\"queries\": ['How i... \n", "\n", "[1893 rows x 13 columns]" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 38, "id": "54f52b4d-10c6-4f9d-9c79-a9cba1af3664", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dataset Overview:\n", "Total samples: 1893\n", "Number of unique categories: 63\n", "Number of unique subcategories: 865\n", "\n", "Average tool calls per conversation: 1.03\n", "Average available functions: 0.00\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"Dataset Overview:\")\n", "print(f\"Total samples: {len(df)}\")\n", "print(f\"Number of unique categories: {df['category'].nunique()}\")\n", "print(f\"Number of unique subcategories: {df['subcategory'].nunique()}\")\n", "print(f\"\\nAverage tool calls per conversation: {df['num_tool_calls'].mean():.2f}\")\n", "print(f\"Average available functions: {df['num_available_functions'].mean():.2f}\")\n", "\n", "# Category Analysis\n", "plt.figure(figsize=(15, 6))\n", "df['category'].value_counts().plot(kind='bar')\n", "plt.title('Distribution of Categories')\n", "plt.xticks(rotation=45, ha='right')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 39, "id": "838fb6dc-df59-4cdb-8449-ae9a93e6b243", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Top 10 Subcategories:\n", "subcategory\n", "Json Schema 793\n", " JSON Schema 26\n", "Android 21\n", "JSON Schema 14\n", "iPhone 13\n", "Data Retrieval 11\n", "Microsoft 365 7\n", "Hugging Face 7\n", "Data Modification 7\n", "Salesforce 5\n", "Name: count, dtype: int64\n" ] } ], "source": [ "subcategory_counts = df['subcategory'].value_counts().head(10)\n", "print(\"\\nTop 10 Subcategories:\")\n", "print(subcategory_counts)\n" ] }, { "cell_type": "code", "execution_count": 40, "id": "87706f21-5cb0-416b-8139-cb2dfabd8be6", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAABKMAAAJOCAYAAABr8MR3AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3WeYFFX69/Ff58mBMOQBBBQJggGzAiq6qIiL4JoVc05rABOsioiuimBAEQSz4q6uERQUBJUsCJIlx4FhmGFyh/O88On+T4493T0z38911QXdU111Vzp16q5TpyzGGCMAAAAAAAAgBKzhDgAAAAAAAACNB8koAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAIB6YOvWrbJYLJo2bVq4Q8H/d91116lDhw4hmVeHDh103XXXBT5PmzZNFotFS5cuDcn8+/Xrp379+oVkXgCAho9kFAAAaHT8F/JlDSNGjAhrbB988IHGjx8f1hhK6tevn3r06FHm3w4cOCCLxaLRo0eHNqggGz16dLH9ICYmRqmpqRo0aJDefvttFRQUBGU+a9as0ejRo7V169agTC+YIjk2AEDDYg93AAAAAOHy5JNPqmPHjsW+Ky/pEioffPCBVq9erXvvvbfY9+3bt1deXp4cDkd4AmskXn/9dcXFxamgoEC7du3SrFmzdP3112v8+PH66quv1K5du8C4kydPls/nq9b016xZo3/961/q169ftVpVrV+/XlZr3d5Hrii27777rk7nDQBoXEhGAQCARmvgwIE64YQTwh1GlVgsFkVFRYU7jAZv6NChatasWeDzE088offff1/XXHONhg0bpoULFwb+VteJQWOM8vPzFR0dLZfLVafzqozT6Qzr/AEADQuP6QEAAJShvEfPyuu75+eff9b999+v5s2bKzY2Vn//+9+1f//+Ur//9ttv1bdvX8XHxyshIUF9+vTRBx98IOmvx+G+/vprbdu2LfC4mL+FSnl9Rv3www8644wzFBsbq6SkJA0ePFhr164tNo7/EbRNmzbpuuuuU1JSkhITEzV8+HDl5ubWaj2V5fDhw7r33nvVoUMHuVwupaSkaMCAAVq+fHlgnPnz52vYsGFKTU2Vy+VSu3btdN999ykvL6/U9GbMmKFu3bopKipKPXr00GeffVZmf00+n0/jx49X9+7dFRUVpRYtWuiWW25RRkZGrZbnyiuv1I033qhFixbp+++/D3xfVgwfffSRjj/++MD27dmzp15++WVJf+0rw4YNkyT1798/sI3nzp0r6a9968ILL9SsWbN0wgknKDo6Wm+88Ubgb0X3O7/c3Fzdcsstatq0qRISEnTNNdeUWt6q7MuVxVZWn1FpaWm64YYb1KJFC0VFRalXr16aPn16sXH8++2///1vvfnmm+rUqZNcLpf69OmjJUuWlLm+AQANHy2jAABAo5WZmakDBw4U+65oq5jquOuuu5ScnKxRo0Zp69atGj9+vO688059/PHHgXGmTZum66+/Xt27d9fIkSOVlJSk3377TTNnztQVV1yhRx99VJmZmdq5c6deeuklSVJcXFy585w9e7YGDhyoI444QqNHj1ZeXp4mTpyo0047TcuXLy+VKLn00kvVsWNHjR07VsuXL9dbb72llJQUjRs3rkbLXJ5bb71Vn376qe68805169ZN6enpWrBggdauXavjjjtO0l8JptzcXN12221q2rSpFi9erIkTJ2rnzp2aMWNGYFpff/21/vGPf6hnz54aO3asMjIydMMNN6hNmzal5nvLLbdo2rRpGj58uO6++25t2bJFr7zyin777Tf9/PPPtWrJdPXVV+vNN9/Ud999pwEDBpQ5zvfff6/LL79cZ599dmCdrl27Vj///LPuuecenXnmmbr77rs1YcIEPfLIIzr66KMlKfCv9NfjeJdffrluueUW3XTTTTrqqKMqjOvOO+9UUlKSRo8erfXr1+v111/Xtm3bNHfuXFksliovX1ViKyovL0/9+vXTpk2bdOedd6pjx46aMWOGrrvuOh06dEj33HNPsfE/+OADHT58WLfccossFouee+45DRkyRJs3b+bRUwBohEhGAQCARuucc84p9Z0xpkbTatq0qb777rtAAsDn82nChAnKzMxUYmKiMjMzdffdd+vEE0/U3Llziz1y55/ngAED1KZNG2VkZOiqq66qdJ4PPvigmjRpol9//VVNmjSRJF188cU69thjNWrUqFKtVI499lhNmTIl8Dk9PV1TpkwJejLq66+/1k033aQXXngh8N1DDz1UbJxx48YpOjo68Pnmm29W586d9cgjj2j79u1KTU2VJI0cOVJt2rTRzz//HEjMnX322erXr5/at28f+P2CBQv01ltv6f3339cVV1wR+L5///7629/+phkzZhT7vrr8fYn9+eefFS53QkKCZs2aJZvNVurvRxxxhM444wxNmDBBAwYMKPPtdJs2bdLMmTN13nnnVSkup9OpOXPmBBI67du310MPPaQvv/xSF110UZWmUdXYinrzzTe1du1avffee7ryyisl/ZWE7Nu3rx577DFdf/31io+PD4y/fft2bdy4UcnJyZKko446SoMHD9asWbN04YUXVjlOAEDDwGN6AACg0Xr11Vf1/fffFxtq6uabby7WEuWMM86Q1+vVtm3bJP3Vaubw4cMaMWJEqb6fqtOCxW/Pnj1asWKFrrvuukAiSpKOOeYYDRgwQN98802p39x6663FPp9xxhlKT09XVlZWtedfkaSkJC1atEi7d+8ud5yiiaicnBwdOHBAp556qowx+u233yRJu3fv1qpVq3TNNdcUayHWt29f9ezZs9j0ZsyYocTERA0YMEAHDhwIDMcff7zi4uL0448/1mqZ/PM/fPhwueMkJSUpJyenVvtRx44dq5yIkv7a74q2LLrttttkt9vL3P7B9M0336hly5a6/PLLA985HA7dfffdys7O1rx584qN/49//COQiJL+2vckafPmzXUaJwAgMpGMAgAAjdaJJ56oc845p9hQU/6WPH7+C29//z3+FjXBelufP8lV1mNcRx99tA4cOKCcnJxqxVgbRRNqzz33nFavXq127drpxBNP1OjRo0slHbZv3x5IpMXFxal58+bq27evpL8en5T+bxk7d+5can4lv9u4caMyMzOVkpKi5s2bFxuys7OVlpZWq+XLzs6WpGKtfUq6/fbbdeSRR2rgwIFq27atrr/+es2cObNa8yn5dsfKdOnSpdjnuLg4tWrVSlu3bq3WdKpr27Zt6tKlS6k3/Pkf6/NvO7+63PcAAPUPj+kBAABUg9frLfP7sh7Lkmr+2F9dqGmMUVFRZXYsLinQAXrR1l6XXnqpzjjjDH322Wf67rvv9Pzzz2vcuHH673//q4EDB8rr9WrAgAE6ePCgHn74YXXt2lWxsbHatWuXrrvuOvl8vmovm8/nU0pKit5///0y/968efNqT7Oo1atXSyo7MeaXkpKiFStWaNasWfr222/17bff6u2339Y111xT6pHJ8hRtMVbXytuX60J9OD4AAKFDMgoAAKAMycnJOnToULHvCgsLtWfPnhpNr1OnTpL+SmpUlNCo6iN7/v6S1q9fX+pv69atU7NmzRQbG1uDSMue1w8//KC8vLxSyRL//Iv23yRJrVq10u23367bb79daWlpOu644zRmzBgNHDhQq1at0oYNGzR9+nRdc801gd+UfLzNP81NmzaViqnkd506ddLs2bN12mmn1UlC591335WkSh+hczqdGjRokAYNGiSfz6fbb79db7zxhh5//HF17ty5Ro9kVmTjxo3q379/4HN2drb27Nmj888/P/BdVffl6sTWvn17/f777/L5fMVaR61bty7wdwAAysNjegAAAGXo1KmTfvrpp2LfvfnmmzVuTXLuuecqPj5eY8eOVX5+frG/FW0dEhsbG3hMrSKtWrVS7969NX369GKJhtWrV+u7774rloyorfPPP19ut1tvvPFGse99Pp9ef/11OZ1OnX322ZL+am1TMv6UlBS1bt1aBQUFkv6vlUzR5TbG6OWXXy72u9atW6tHjx565513Ao/JSdK8efO0atWqYuNeeuml8nq9euqpp0rF7/F4SiVjquODDz7QW2+9pVNOOSWwnGVJT08v9tlqteqYY46RpMCy+xOEtYmnqDfffFNutzvw+fXXX5fH49HAgQMD31V1X65ObOeff7727t1b7G2RHo9HEydOVFxcXOCRSwAAykLLKAAAgDLceOONuvXWW3XJJZdowIABWrlypWbNmqVmzZrVaHoJCQl66aWXdOONN6pPnz664oorlJycrJUrVyo3NzfwGNfxxx+vjz/+WPfff7/69OmjuLg4DRo0qMxpPv/88xo4cKBOOeUU3XDDDcrLy9PEiROVmJio0aNH13TRSxk0aJDOPfdc3XfffVq8eLFOPfVU5ebm6osvvtDPP/+sp59+OvAY3OHDh9W2bVsNHTpUvXr1UlxcnGbPnq0lS5YE3q7XtWtXderUSQ888IB27dqlhIQE/ec//ymz/6BnnnlGgwcP1mmnnabhw4crIyNDr7zyinr06FEsQdW3b1/dcsstGjt2rFasWKFzzz1XDodDGzdu1IwZM/Tyyy9r6NChlS7rp59+qri4OBUWFmrXrl2aNWuWfv75Z/Xq1UszZsyo8Lc33nijDh48qLPOOktt27bVtm3bNHHiRPXu3TvQl1Lv3r1ls9k0btw4ZWZmyuVy6ayzzlJKSkqVt0dRhYWFOvvss3XppZdq/fr1eu2113T66acXe5NeVffl6sR2880364033tB1112nZcuWqUOHDvr000/1888/a/z48RX2rQUAgAwAAEAj8/bbbxtJZsmSJeWO4/V6zcMPP2yaNWtmYmJizHnnnWc2bdpk2rdvb6699tpKp/Xjjz8aSebHH38s9v0XX3xhTj31VBMdHW0SEhLMiSeeaD788MPA37Ozs80VV1xhkpKSjCTTvn17Y4wxW7ZsMZLM22+/XWx6s2fPNqeddlpgeoMGDTJr1qwpNs6oUaOMJLN///4y18OWLVsqXmHGmPz8fDN69GjTtWtX43K5TGxsrDn55JPNe++9V2y8goIC8+CDD5pevXqZ+Ph4Exsba3r16mVee+21YuOtWbPGnHPOOSYuLs40a9bM3HTTTWblypVlLuNHH30UmG+PHj3MF198YS655BLTtWvXUnG++eab5vjjjzfR0dEmPj7e9OzZ0zz00ENm9+7dFS6ffx35h6ioKNO2bVtz4YUXmqlTp5r8/PxSv7n22msD28cYYz799FNz7rnnmpSUFON0Ok1qaqq55ZZbzJ49e4r9bvLkyeaII44wNput2D7Svn17c8EFF5QZX3n73bx588zNN99skpOTTVxcnLnyyitNenp6sd9WdV+uKLa+ffuavn37Fht33759Zvjw4aZZs2bG6XSanj17ltp2/v32+eefL7VMksyoUaPKXF4AQMNmMYZeAwEAAFC/9O7dW82bNy/VzxQAAIh89BkFAACAiOV2u+XxeIp9N3fuXK1cuVL9+vULT1AAAKBWaBkFAACAiLV161adc845uuqqq9S6dWutW7dOkyZNUmJiolavXq2mTZuGO0QAAFBNdGAOAACAiJWcnKzjjz9eb731lvbv36/Y2FhdcMEFevbZZ0lEAQBQT9EyCgAAAAAAACFDn1EAAAAAAAAIGZJRAAAAAAAACBn6jAIq4fP5tHv3bsXHx8tisYQ7HAAAAAAAIpIxRocPH1br1q1ltZbf/olkFFCJ3bt3q127duEOAwAAAACAemHHjh1q27ZtuX8nGQVUIj4+XtJfB1NCQkKYowEAAAAAIDJlZWWpXbt2gevo8pCMAirhfzQvISGBZBQAAAAAAJWorIsbOjAHAAAAAABAyJCMAgAAAAAAQMiQjAIAAAAAAEDIkIwCAAAAAABAyJCMAgAAAAAAQMiQjAIAAAAAAEDIkIwCAAAAAABAyJCMQr33008/adCgQWrdurUsFos+//zzcse99dZbZbFYNH78+JDFBwAAAAAA/g/JKNR7OTk56tWrl1599dUKx/vss8+0cOFCtW7dOkSRAQAAAACAkuzhDgCorYEDB2rgwIEVjrNr1y7dddddmjVrli644IIQRQYAAAAAAEoiGYUGz+fz6eqrr9aDDz6o7t27Vzp+QUGBCgoKAp+zsrLqMjwAAAAAABoVHtNDgzdu3DjZ7XbdfffdVRp/7NixSkxMDAzt2rWr4wgBAAAAAGg8SEahQVu2bJlefvllTZs2TRaLpUq/GTlypDIzMwPDjh076jhKAAAAAAAaD5JRaNDmz5+vtLQ0paamym63y263a9u2bfrnP/+pDh06lPkbl8ulhISEYgMAAAAAAAgO+oxCg3b11VfrnHPOKfbdeeedp6uvvlrDhw8PU1QAAAAAADReJKNQ72VnZ2vTpk2Bz1u2bNGKFSvUpEkTpaamqmnTpsXGdzgcatmypY466qhQhwoAAAAAQKNHMgr13tKlS9W/f//A5/vvv1+SdO2112ratGlhigoAAAAAAJSFZBTqvX79+skYU+Xxt27dWnfBAAAAAACACtGBOQAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBQAAAAAAABChmQUAAAAAAAAQoZkFAAAAAAAAEKGZBTqvZ9++kmDBg1S69atZbFY9Pnnnwf+5na79fDDD6tnz56KjY1V69atdc0112j37t3hCxgAAAAAgEaMZBTqvZycHPXq1Uuvvvpqqb/l5uZq+fLlevzxx7V8+XL997//1fr163XRRReFIVIAAAAAAGAxxphwBwEEi8Vi0WeffaaLL7643HGWLFmiE088Udu2bVNqamql08zKylJiYqIyMzOVkJAQxGgBAAAAAGg4qnr9bA9hTEBEyMzMlMViUVJSUpl/LygoUEFBQeBzVlZWiCIDAAAAAKDh4zE9NCr5+fl6+OGHdfnll5ebpR07dqwSExMDQ7t27UIcJQAAAAAADRfJKDQabrdbl156qYwxev3118sdb+TIkcrMzAwMO3bsCGGUAAAAAAA0bDymh0bBn4jatm2bfvjhhwqfXXW5XHK5XCGMDgAAAACAxoNkFBo8fyJq48aN+vHHH9W0adNwhwQAAAAAQKNFMgr1XnZ2tjZt2hT4vGXLFq1YsUJNmjRRq1atNHToUC1fvlxfffWVvF6v9u7dK0lq0qSJnE5nuMIGAAAAAKBRshhjTLiDAGpj7ty56t+/f6nvr732Wo0ePVodO3Ys83c//vij+vXrV+n0q/pqSgAAAAAAGrOqXj/TMgr1Xr9+/VRRTpV8KwAAAAAAkYO36QEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEah3vvpp580aNAgtW7dWhaLRZ9//nmxvxtj9MQTT6hVq1aKjo7WOeeco40bN4YnWAAAAAAAGjmSUaj3cnJy1KtXL7366qtl/v25557ThAkTNGnSJC1atEixsbE677zzlJ+fH+JIAQAAAACAPdwBALU1cOBADRw4sMy/GWM0fvx4PfbYYxo8eLAk6Z133lGLFi30+eef67LLLgtlqAAAAAAANHq0jEKDtmXLFu3du1fnnHNO4LvExESddNJJ+vXXX8MYGQAAAAAAjRMto9Cg7d27V5LUokWLYt+3aNEi8LeSCgoKVFBQEPiclZVVdwECAAAAANDI0DIKKGHs2LFKTEwMDO3atQt3SAAAAAAANBgko9CgtWzZUpK0b9++Yt/v27cv8LeSRo4cqczMzMCwY8eOOo8TAAAAAIDGgmQUGrSOHTuqZcuWmjNnTuC7rKwsLVq0SKecckqZv3G5XEpISCg2AAAAAACA4KDPKNR72dnZ2rRpU+Dzli1btGLFCjVp0kSpqam699579fTTT6tLly7q2LGjHn/8cbVu3VoXX3xx+IIGAAAAAKCRIhmFem/p0qXq379/4PP9998vSbr22ms1bdo0PfTQQ8rJydHNN9+sQ4cO6fTTT9fMmTMVFRUVrpABAAAAAGi0LMYYE+4ggEiWlZWlxMREZWZm8sgeAAAAAADlqOr1M31GAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgFAI9dhxNfhDgEAAABAI0IyCgAAAAAAACFDMgoAAAAAAAAhQzIKAAAAAAAAIUMyCgAAAAAAACFDMgoAAAAAAAAhQzIKAAAAAAAAIUMyCgAAAAAAACFDMgoAAAAAAAAhQzIKAAAAAAAAIUMyCgAAAAAAACFDMgoAAAAAAAAhQzIKAAAAAAAAIUMyCgAAAAAAACFDMgoAAAAAAAAhQzIKAAAAAAAAIUMyCg2e1+vV448/ro4dOyo6OlqdOnXSU089JWNMuEMDAAAAAKDRsYc7AKCujRs3Tq+//rqmT5+u7t27a+nSpRo+fLgSExN19913hzs8AAAAAAAaFZJRaPB++eUXDR48WBdccIEkqUOHDvrwww+1ePHiMEcGAAAAAEDjw2N6aPBOPfVUzZkzRxs2bJAkrVy5UgsWLNDAgQPLHL+goEBZWVnFBgAAAAAAEBy0jEKDN2LECGVlZalr166y2Wzyer0aM2aMrrzyyjLHHzt2rP71r3+FOEoAAAAAABoHWkahwfvkk0/0/vvv64MPPtDy5cs1ffp0/fvf/9b06dPLHH/kyJHKzMwMDDt27AhxxAAAAAAANFy0jEKD9+CDD2rEiBG67LLLJEk9e/bUtm3bNHbsWF177bWlxne5XHK5XKEOEwAAAACARoGWUWjwcnNzZbUW39VtNpt8Pl+YIgIAAAAAoPGiZRQavEGDBmnMmDFKTU1V9+7d9dtvv+nFF1/U9ddfH+7QAAAAAABodEhGocGbOHGiHn/8cd1+++1KS0tT69atdcstt+iJJ54Id2gAAAAAADQ6JKPQ4MXHx2v8+PEaP358uEMBAAAAAKDRo88oAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAANVocRX4c7BAAAAABACSSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKPQKOzatUtXXXWVmjZtqujoaPXs2VNLly4Nd1gAAAAAADQ69nAHANS1jIwMnXbaaerfv7++/fZbNW/eXBs3blRycnK4QwMAAAAAoNEhGYUGb9y4cWrXrp3efvvtwHcdO3YMY0QAAAAAADRePKaHBu+LL77QCSecoGHDhiklJUXHHnusJk+eXO74BQUFysrKKjYAAAAAAIDgIBmFBm/z5s16/fXX1aVLF82aNUu33Xab7r77bk2fPr3M8ceOHavExMTA0K5duxBHjIaiw4ivwx0CAAAAAEQcklFo8Hw+n4477jg988wzOvbYY3XzzTfrpptu0qRJk8ocf+TIkcrMzAwMO3bsCHHEAAAAAAA0XCSj0OC1atVK3bp1K/bd0Ucfre3bt5c5vsvlUkJCQrEBAAAAAAAEB8koNHinnXaa1q9fX+y7DRs2qH379mGKCAAAAACAxotkFBq8++67TwsXLtQzzzyjTZs26YMPPtCbb76pO+64I9yhAQAAAADQ6JCMQoPXp08fffbZZ/rwww/Vo0cPPfXUUxo/fryuvPLKcIcGAAAAAECjYw93AEAoXHjhhbrwwgvDHQYAAAAAAI0eLaMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjgAamw4ivwx0CAKAGSpbflOcAAKChIhkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGYVG59lnn5XFYtG9994b7lAAAAAAAGh0SEahUVmyZIneeOMNHXPMMeEOBQAAAACARolkFBqN7OxsXXnllZo8ebKSk5PDHQ4AAAAAAI0SySg0GnfccYcuuOACnXPOOeEOBQAAAACARsse7gCAUPjoo4+0fPlyLVmypNJxCwoKVFBQEPiclZVVl6EBAAAAANCo0DIKDd6OHTt0zz336P3331dUVFSl448dO1aJiYmBoV27diGIEgAANGQdRnwd7hAAAIgYJKPQ4C1btkxpaWk67rjjZLfbZbfbNW/ePE2YMEF2u11er7fY+CNHjlRmZmZg2LFjR5giBwAAAACg4eExPTR4Z599tlatWlXsu+HDh6tr1656+OGHZbPZiv3N5XLJ5XKFMkQAAAAAABoNklFo8OLj49WjR49i38XGxqpp06alvgcAAAAAAHWLx/QAAAAAAAAQMrSMQqM0d+7ccIcAAAAAAECjRMsoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKAAAAAAAAIQMySgAAAAAAACEDMkoAAAAAAAAhAzJKKAR6jDi64ieX6jjQ91ie4YX6x/hxP5XN1ivjRvbv+Yifd3VVXyRvtxonEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQAAAAAAIGRIRgEAAAAAACBkSEahwRs7dqz69Omj+Ph4paSk6OKLL9b69evDHRYAAAAAAI0SySg0ePPmzdMdd9yhhQsX6vvvv5fb7da5556rnJyccIcGAAAAAECjYw93AEBdmzlzZrHP06ZNU0pKipYtW6YzzzwzTFEBAAAAANA40TIKjU5mZqYkqUmTJmGOBAAAAACAxoeWUWhUfD6f7r33Xp122mnq0aNHmeMUFBSooKAg8DkrKytU4QEAAAAA0ODRMgqNyh133KHVq1fro48+KnecsWPHKjExMTC0a9eu2N87jPi6rsOsVHViqG68kbB8VVWfYq2qksvUEJcxEtXFem/Ix16kqcm6q+g3odoWwZxPVadVl8sWyftwbWOLxGWLxJjqo0hcj1WJKdhxR+J6CLbGsIwNDfXiho1kFBqNO++8U1999ZV+/PFHtW3bttzxRo4cqczMzMCwY8eOEEYJAAAAAEDDxmN6aPCMMbrrrrv02Wefae7cuerYsWOF47tcLrlcrhBFBwAAAABA40IyCg3eHXfcoQ8++ED/+9//FB8fr71790qSEhMTFR0dHeboAAAAAABoXHhMDw3e66+/rszMTPXr10+tWrUKDB9//HG4QwMAAAAAoNGhZRQaPGNMuEMAAAAAAAD/Hy2jAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKMAAAAAAAAQMiSjAAAAAAAAEDIkowAAAAAAABAyJKOAaugw4utSn4t+F+zP5Y1T0d/LG6emv/f/PRjLUdvxq7McdbWt6nK5q7Id62KfK2se4V4PwThOahNjdWMOxnJXd/xglBeRuC1quw/X5Dd1tc/W9nivzjKVF3Mo94eyYigvrnB9ruk0avv7uphGbaYXjBgiYT0Eaz2GO4aqHs/laQjrwf85FNs7nDGE67ioyfQjYX8oGXdNliPYMUTCeoj0GHqMmqWqIBkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGQUAAAAAAICQIRkFAAAAAACAkCEZBQAAAAAAgJAhGYVG49VXX1WHDh0UFRWlk046SYsXLw53SAAAAAAANDoko9AofPzxx7r//vs1atQoLV++XL169dJ5552ntLS0cIcGAAAAAECjQjIKjcKLL76om266ScOHD1e3bt00adIkxcTEaOrUqeEODQAAAACARsUe7gCAulZYWKhly5Zp5MiRge+sVqvOOecc/frrr6XGLygoUEFBQeBzZmamJCkrK0u+gtzA/yXV+edQzKOqn4mBGCIthkg6ToiBGMr6TAzEEGkxRNJxQgzEUNZnYiCGSIshko6T+haDMUYVsZjKxgDqud27d6tNmzb65ZdfdMoppwS+f+ihhzRv3jwtWrSo2PijR4/Wv/71r1CHCQAAAABAg7Bjxw61bdu23L9bQxgLUC+MHDlSmZmZgSEjI0Pz588Pd1gAAAAAAES8xYsXq3Xr1hWOw2N6aPCaNWsmm82mffv2Fft+3759atmyZanxXS6XXC5Xse86dOhQlyECAAAAANAgtGrVSlZrxW2faBmFBs/pdOr444/XnDlzAt/5fD7NmTOn2GN7AAAAAACg7tEyCo3C/fffr2uvvVYnnHCCTjzxRI0fP145OTkaPnx4uEMDAAAAAKBRIRmFRuEf//iH9u/fryeeeEJ79+5V7969NXPmTLVo0aJKv09ISNBpp50mn8+nk046SYsWLZLP55PVaq3Tz5LqfB7EUH9jIgZiIAZiiOQYIjEmYiAGYiCGSI4hEmMiBmKobgx2u10JCQmVXmPzNj0AAAAAAACEDH1GAQAAAAAAIGRIRgEAAAAAACBkSEYBAAAAAAAgZEhGAQ1MTbuBq8/dx9Xn2AEAQMNBnQSILME4Jjmu6wbJKDRaS5culaTAWwH8/IVNpBU6Bw8erNJ4Foul1DJV9XeRtsxVsX379iovs9vtrtW8qrt+lixZUq3xt2/fXuq7mmxLqeJYi/6tPm7z2ii5vB6Pp9h3aWlptZpeZVauXFmr6QV7e1W0f1VlXkV/X9vYavL7TZs2acOGDbWab1UYYxrdsRJKoVq3mzdvDsl8Gsq+EuwLuE2bNkmSMjIyyvx7yfnt2bMnqLGEStE6yQ8//FDhuJWdj2uy3HW5rkK1HWpa94kkWVlZ4Q6hUpVtz/Xr11dpvOooWW8oeX4N1nEgSbNnz9aWLVtqfG20atUq/e9//ysWa21jqiuRFk9VkYxCozRq1ChdcskluvXWW5WRkaH77rtPP//8s3w+X6DA8hfA+fn5xX7rL8zKKpB8Pl+ZhV3R7z0ej7xeb+B3/qHod5ICnyVpypQpGjFihDIzMwPjjB8/PlChM8bopptu0sCBAyX9X0XIP42SMRWd9uOPP67XXnutWBKu6DJmZ2eXWhav1ytjjAoLC0sts8fjKbX8RedZdNputzswvn++Pp+vWAxFf1PyBPb000+rb9+++v3332W1WgPTKrmNjDEaMWKEbr311lLbs6y4Ss636DyLfuf1epWVlVVsPl6vV16vV6NHj9btt9+uL774IjAt/99LbnPpr33yyiuv1KpVqwLr2OPx6KefftLKlSu1bNmyMtdryeSpMUZ33nmnfvjhh8D69M/bH4fFYgmMW/QE7fF4im1P/7YveQL2L2PR7yZNmqT09PQy4yu6/Xw+n9xud7H5FI2v6PhFE0X+deX1ejV27FgtWrSoWFwl4/N//vzzz3Xw4EH5fD5lZmbKYrEE9pO+fftq+PDhys/PlzFGV1xxhYYOHapNmzZVeJxL0rBhw/TBBx8EkrglK1Ql148xRo8++qhuv/12ff/996X2M6/XG9g2/mV95ZVXtGzZssDnbdu2Fft7yXVX1nFYcj/z+/zzz3X//ffr5ZdfLrV9v/32W2VlZQX2k/LKNK/XK6vVGojBP37R5ffP3z9OeeVDRcken8+n2267TStWrCgWz7/+9S+deeaZuvbaa7Vw4cJSZVHJz+Vty6LzLlpu+uXl5enAgQM6dOiQfD5fmeu26LFW1r5TVjwlFRYWBsb7448/Av8ves4o+m9Zx37ReZUVQ8llLq+8K1oOl3d8ljyui25bf5wTJkzQrl27So1bdJ8oOu3MzExlZGQExh83bpxWrlxZat298MIL+vPPP4stS9FlK/l/n8+nb775Rp07d9Y333xTKp6yplOyrC+qoiTsM888o40bN0qS9u3bVyqO8vjXScltV3I9Ff1bWdu+rGUp67uS/y8635JljN97770XSOhVdMF411136a677pKkQJnlP14vvfRSjRo1Snv27NGSJUuKlWn+89GXX36pf/7zn+rdu7fWr19f7LxVdJ2UVZ74fD71799fTz/9dOB841+/Za2X8rZtyW3m/33Rfb3kOrv99tt12mmn6cCBA7Jarfr99991zjnn6P777y9zW3k8Hi1fvlxS8RuOxhi99NJLcrvdgXNWWdur6DTLOsf7z9VFYy1re5Xc70rWUSVp7dq1ZZYH/uUoui7LOo6Klin+ukbR74v+tmj5tnv37mLrv+j8ylqOknWBostR9O/+dVr0+KroHFRWAsUfX1nb9uabb9YLL7ygtLS0co+7ot+53e5Sx13Rfa/oOii6L3711VelYipZRyurXMnKygpcQ9x7772aN29eqeV47rnndNZZZ2n+/Pl67rnnAjd+Sq6vkvU5//yLniv9/xZdj+np6aXWTdFEtVT2TeSS+0HROmPRcZ5//nldccUV6tSpk1asWFFuQqq8a6SXX35ZxxxzjIYNG6Z//etfgen+8ssvgTpPyfNheftm0XmVrCsUPR+WjKFoGVb0b2Vdn/jjKev8VnSa/r+VLPvKitUYox07dpTa5uUdKzVigEboxRdfNC6Xy0gy559/vklMTDQ9e/Y0ixcvNtdee6056aSTzIknnmgGDx5sXnzxRVNYWGgKCgqM2+02BQUFZsuWLea3334zbrfb/Pe//zUFBQXG6/WagwcPmsOHDxuv12u8Xq8pKCgwHo/HuN1uk5aWZv71r3+Z6dOnm++++8689dZbZvbs2cYYYzZu3Gi2b99usrKyzMKFC40xxmzdutUYY8wLL7xgLBaLef755826detMYWGhGTp0qOnQoYPZuHGjyc7ONllZWWbSpEmmVatW5sILLzRZWVkmPz/fuN1u4/P5zIEDB4zb7TbTpk0zq1evNsYYs2zZMrNgwQJzxhlnmCOOOMI8/vjjxuv1mh07dpj9+/cbt9tt7r33XjNq1Cjz888/m0OHDhmfz2f27t1rvF6veeqpp8yTTz5pDhw4YLKyssz06dPNDz/8YIwxpqCgwDz66KPmhRdeMD6fz2RnZxuPx2Ouu+46M2bMGHPgwAGzefNm43a7zfLly837779vZsyYYbKzs012drb5/vvvzbJly8zChQvN448/bj7++GOTn59v5s2bZ7Kzs83hw4eNz+czn3/+uTnzzDNN27ZtzbBhw8xll11mvvnmG1NQUGCMMWbt2rUmLy/P5OXlmXvvvdeccMIJ5q677jI5OTnGGGP27NljfD6fcbvdZty4cWbr1q3mwIEDZv369cbtdpv8/HzTu3dv07FjR3P22Wcbt9tt5syZY84//3yzZMkS88QTT5jJkycbt9ttHnroIfPFF1+YwsJCc/DgQfPee++Zk046yZx33nlmzJgxxu12G7fbbd577z2zdetWs3LlSnPgwAGzf/9+8+CDD5obbrjBnHXWWeb88883EydONBkZGeaOO+4wMTExRpIZP3688Xg8xuPxGK/Xa9xut8nJyTE+n8/s2LHD5OTkGLfbbf7973+bNm3amI4dO5o5c+aYefPmmZycHJOenm6mTZtm9u3bZzIzM82IESPMI488YjIzM81TTz1lvvrqK7NgwQLj8XjMzp07zRNPPGHuueces2PHDvPbb7+ZnJwcs2bNGvPEE0+YmTNnGmOMcbvdZtasWebvf/+7OeWUU4zX6zVffPGFmThxopkxY4bxeDzG5/MZn89ntm/fbj766COza9cu88UXX5gFCxaY//znP+bnn382v//+uzHGmLS0NLNjxw5jjDGrV682K1euNF6v18ydO9f8/vvvxuv1mhdeeMH07t3b9O/f3yxatMj88ccf5sCBA4G/zZo1y3g8HmOMMY888oiRZJ599llz3333mYEDB5q1a9caj8djXnzxRZOYmGhsNpsZNGiQ2bt3r5k8ebJJSEgwF198sdm4caN56qmnzE8//WTcbrd59tlnzfTp001+fr7JyMgw119/vbHb7WbGjBlmz549geP866+/Nhs3bgws+4cffmjWr19vrr32WvPSSy+ZM8880/Tv3998+umngeNt586d5r777jPt2rUzL774olm+fLmZM2eOadeunRk+fLhZsmSJefLJJ01SUpJ5/PHHA+u+sLAwsKyDBw82w4cPN3l5eWbLli2BMmjChAmB8dLS0sxVV11l7rzzTtOmTRvTrVs3c8opp5iXXnopsJ2GDh1qYmJizOuvv27eeecds2HDBuPxeMyaNWvMqlWrjMfjMS+//LJ55513zK+//mp27Nhh7rrrLnP11VebP/74w3i9XnPo0CFTUFBgCgsLzaxZs8zKlStNRkaGmT17tpk+fbrJzMw0t956q/npp5+MMcbMnz/f/Prrr8bj8ZihQ4eaBx54wHi9XjNlyhSzYcMGk5WVZbp162ZSU1PNl19+Gdj///nPf5qjjz7aJCUlmb59+5oFCxYYr9dr/vzzTzN+/Hizc+dOc+jQIfPZZ5+ZjRs3mpycnMDx4//3zz//NBkZGSY7O9vs2bPHbNy40cyZM8esX7/efPPNN+aZZ54x48aNMw6Hw7hcLvPkk0+agoICU1BQYD7//HOzadMms3//fjNu3DizY8cOc+jQIfPf//7X/P7772bZsmUmPT3d7Nixw/h8vsC2SktLM7Nnzzb79+83Ho/H/Pvf/w6USV6v19x8882mX79+ZvLkyWbdunXGGGM8Ho+ZOXOmufzyy83YsWPN2rVrTUFBgfniiy/Mrl27AuWB1+s1q1atMm632xw8eNBs2rTJeDyewHHlL4/962D37t1m8+bNZt++fYG/r1mzxuTn55v8/HzzySefmJ07d5oNGzaYNWvWGK/Xa3w+n5k1a5ZZtWqVycjIMJdeeqmZMmWK2bx5s/F4PObpp582y5cvN19//bXp2LGjufzyy83s2bON1+s1ixYtMhs3bjQLFiwwWVlZ5v777zcXX3yxWblypbnxxhtNq1atzKBBg8x///tf88MPP5g2bdqYQYMGmf/973+Bfdp/Thw2bJjZvHmz8fl8gTLDP47P5zM7d+40+fn5xufzBc7Lp59+uklISAhMb//+/cbn85k5c+aYP/74w+Tn55tVq1aZ9PR04/F4zKFDh8zMmTMD2+6ZZ54xq1evDhxT/rInIyPD7Ny50+zYscNYLBZz4YUXmssuu8yccMIJ5uDBg6awsNAUFhYGzjezZs0ymZmZgXXu8/lMYWGhGTZsmHnsscfM1q1bzbZt28y3335rjjzySHPo0CHjdrvNvn37Auf1RYsWmVWrVpmCggLz0EMPmffff99kZWWZwsLCwDGyZ88ec+jQocB6cLvdgWPB/3nLli3m8OHDxhhjnn32WTN//nzzwAMPmCeeeCJwnKSnp5u3337bWK1WM2LECLNhw4bAet+7d69xu92BdXTgwAFz5plnmiOOOMLcfffdZvr06ea3334zzzzzjHE6nUaSad++vUlNTTWSzKeffmpmzpxpfvnlF5OZmWn69etnEhMTzXXXXWe6detmmjdvbq6//nqzefPmwDHi9XrNgQMHzK+//mq8Xq/5/vvvzd69e40xxkyePNlYLBZjsVjMSy+9ZIwx5uOPPzb33XefKSwsNGvWrDG7d+8OrCN/eTp69Gjz66+/mry8vMBy5+bmmgULFpjCwkKzf/9+s3//fvPRRx+ZvXv3mg0bNph3333X+Hw+89hjj5kJEyaY9957z8TFxZlOnTqZzMxMk5ubayZNmmSio6PNP/7xD2OMMVu2bDGPP/64GTt2rHnttdeMJNO9e3fTp08fk5GRYYYPH25atGhh+vXrZzZt2mS+/vrrQHnqr5v49+cNGzaYTz/9NFAG+NdNYWGhufHGG82dd95pCgsLjTHG/Pe//zVpaWnmp59+CtTnjDFm5cqVZuLEiWbOnDnm2WefNa+99prJz883W7ZsMQ899JBZsmSJ6d27t+nVq5eZPXu2efzxx81HH31k1q1bZ7xerzl8+LBZuHBhoJ61cuVKs2LFCpOTk2Nyc3MD22zx4sUmJyfHLFmyxOzfv98sWbLEvPfee2bUqFFmxYoVJj093WzcuNG8+OKL5n//+59JT083PXv2NJ06dTL79u0LnFM3bNhgDh8+HCiDs7KyzPLly8369etNRkaG8Xg8Zt26dWbXrl2B89dNN91kfvjhh0AdKisrK3DsTJ061Xg8HvPKK68Eztf79u0zBQUF5sknnwz83+fzGa/Xaz755BOTnp5uvF6vufrqq83gwYPNH3/8YVauXGm2bdtmjDFmxIgR5qKLLjKpqalm5MiRZvfu3SYtLc0cOnTIeL1ek52dbb766qvAvjdq1Cjz1ltvmcOHD5vMzEyzatWqwLr75ZdfzE8//WRyc3PNnDlzzI4dO8zatWuN2+02r776qrFYLOa+++4z27dvN2632+zatcts27bNZGRkmDfeeMPMnTvXHD582MycOdO8++67Jj093TzxxBMmNTXVJCUlmeHDh5szzjjDpKammj59+gT2H6/Xa2bOnGmGDBliunXrZiSZk046yaxZs8YYY0x+fr7ZuXOn2blzp8nKyjJZWVnmvffeM7/88osxxpiFCxeazMxMk5aWZn788UeTk5NjDhw4YAoLC80ff/xhBg0aZBITE82nn35qfD6fueGGG8yxxx5runTpYmbNmmVGjRpldu/ebR5++GHz3nvvmYyMDHPrrbeaUaNGBc6jY8aMMZMnTzazZ882Pp/PbNu2zbjdbnPHHXeYb7/91uzatcucddZZJi4uzkRHR5tly5aZnJwcs3r16kCdzX++KCgoMLt27SpWz96+fbv529/+ZiQZm81mnnzySdO3b1/TtGnTwHK+8847xuPxmE8++aRY2TFjxozAtP3HgL+cdLvdZv78+WbDhg1m5syZ5qWXXjJbtmwxO3fuNMuXLzcff/xx4Hxxzz33mFNOOcWcddZZ5qeffgrUFTwej1m6dKk5ePCgWbhwofntt99MQUFBoK65atUqs2bNGuPz+cyKFSvM22+/bdLS0ozP5zMLFiwwW7duNXv37jXvvPOO+eSTTwLnoJycHLN//36Tn59vjDHmgQceMH/729/MihUrjNfrNWPGjDE//PBDII5gsBgTzNQWEPncbrccDocee+wxPffcc4GMc2Jiorxer3JychQXFyer1arMzEy98cYb2rp1q9xutw4cOKB58+Zp3759cjgcat26tdauXauBAwdq0aJFcrlciomJkd1u13HHHaeoqCh16NBB11xzjXr37i2LxaLMzEwZY9S5c2fl5eVpwIAB+uGHH9StWzcdPnxYa9euVZs2bWS322WM0YoVK/Tkk0/qgw8+0CmnnKJly5bp999/10UXXSSHw6Hk5GTl5+drw4YN+vPPP5Wenq7mzZvr73//u1wul1avXq3c3FxdeOGFevnll9W5c2eNHz9e5513npo1a6YTTzxRH374obp06aL27dtr7dq1kqR///vfuvfee9WxY0cdPHhQRx11lLZu3arc3Fydf/75evPNN+VwONSiRQu1atVKK1eulM1m06RJk7Rz505NnDhRDz30kJYuXaqvv/5aX375pc455xxlZ2frggsu0NKlS2W327V//34VFBQoNjZWPXr00MGDB7Vx40bFxcXJ4XAEWl80a9ZMmzZtUqdOnWS323XWWWfJ4XBowoQJgW1rt9t1zz33qF+/fvroo4/0v//9T9ddd51cLpcyMjI0a9YsHTp0SEcffbSOP/54rVq1ShMnTtTNN9+sZcuW6aSTTpLH41FeXp5SUlJ06NChQGuM6Ohode3aVXv27NG+ffsCdwVWrlype++9Vz/++KPi4+MVHx+v9u3b69dff1WrVq1UWFiojIwMXX755Vq5cqU2bNigmJgYZWVlqXnz5rJYLDpw4ICaNGmi7t27a+7cuTLG6Nxzz9V3330n6a+7xddcc41Gjhypt99+Wy6XS1u3blVMTIx2796tL774Queff77atm2rKVOmqHv37lqzZo2MMUpOTlaHDh2UnZ2tdevWKSEhQR06dNCaNWvUvXt3RUVFqWnTpvrtt9+UmZmpYcOG6d1335XValXnzp2VmZmpPXv2qHXr1srOzlZWVpauuOIKOZ1OZWdn69NPP1VsbKwuuOACtWzZUhMmTFCPHj3UqlUrHX/88dq2bZsOHTqktWvXKjMzU7Gxsdq5c6ccDoeMMXI6nTrllFPUo0cPTZs2TQkJCYqKitKff/6pI444Qvn5+dq/f79atGghh8OhLVu2qE2bNtqzZ49atmyp/fv3q3Xr1urRo4e+/PJLde3aVTfccIMWLlyo//znP+rXr5/mzp2r5s2bKysrS4mJibr99tuVnJyse++9V1arVV6vV+3atdPu3bt1wQUX6Ntvv5XL5VJ2drYcDofOPPNMzZ8/X2eddZa2bt2qv//973rwwQd1yimnaP369YqPj9fjjz+upUuX6pNPPtFpp52me+65R+3bt9c555yjUaNG6dVXX9XevXvldDplsVh01FFHqUuXLlq5cqVWrVqlI488Ups3b5YxRv379w/cOV65cqUSExN16qmn6qOPPpLD4dCjjz6qgwcPyuVy6b777tM999yjuXPnav/+/WrTpo1cLpeGDh2qKVOmKD09XSNGjNCUKVOUmZmpNm3aaNeuXerYsWOxY2/UqFH6/fff9b///S9w93L//v0aNmyYzj77bD3++OOSpE6dOmnhwoVq3bp1IIb8/Hx16NBBTZo0kdVq1bZt23T33Xfr1Vdf1bZt22S32wP7vCR169ZNa9as0T//+U+tWrVKP//8s8477zwdPnxY33//veLj4wN3Mi+99FI99thjuu6667Rq1SpZrVY9+OCDat26tW6//Xa1aNFC+/fvlyT16dNHxx13nGbMmBG46925c2etXbtWxx9/vIYPH66MjAzt2bNHnTp10scff6xt27apefPm2rVrlw4ePCi73S63262CggLZbDZ5PB6dd955WrVqlXbv3i2Xy6UXX3xRX3zxhb7//nt169ZNO3fu1KFDh3TGGWdo9erVyszMVFJSkmJjY3XSSSdp2bJlOuqoo/Too4/qoYce0s6dO5WWlqazzjpL0l8t0c477zy9/PLLuvHGG7Vp0yYVFhbq4MGDslgsuuWWW7RgwQLt3btXBw4cUOfOnZWdnS23262DBw/qyCOPVIcOHbR161a1atVK+/fv1wknnKAVK1Zo9+7dOvbYY2WxWHTppZfqgw8+kMvl0pFHHqkVK1Zo165dysjI0JFHHqkxY8bo6aef1h9//KGEhARZrVZt2rRJ11xzjT777DN17NhRd999t1588UWtWbNGMTExio+P165du+R0OtWyZUtFRUVp48aNuvnmm/XJJ58EWjv5y8UNGzaooKBAkhQXFxdofRkVFaX8/HxZrVZZrVZZLBadc845mjdvntxut5o0aaIbb7xRM2bM0Pbt29W3b1/NmzdPnTp1UnZ2ttq0aSOn06nU1FSlpaUpIyNDBw4c0IMPPqg//vhDO3fuVMeOHTVhwgT16dNHy5YtU4cOHXTMMccoOjpan332mdq2batjjjlG69at09FHH60TTjhBEydO1Pbt23Xbbbdp3rx5WrdunR566CEdeeSR+u6772S329WxY0d9+umnyszM1F133SWLxaKnnnpK0dHR6tevnx599FH99NNPWrp0qTZs2KCdO3cqKytLXbt2VdOmTbVnzx4lJCTo3HPP1aRJk7Rr1y5ZLBalpKQoLi5OmzdvVmJiou6//37Nnz9fffr00ezZs7V48WIlJSWpY8eOWrt2rXr37q3s7Gz16dNHVqtVixYtUnZ2tnr27KlHHnlEs2fP1uzZs7Vu3TplZGTo3nvvVUZGhiZPnqxLL71UkvTJJ58oOTk5UPYnJydL+qsVRV5enpo2barVq1erT58+GjJkiL777jt5PB698MIL2r59u6KiopSTk6OnnnpKa9euVV5enux2ux5//HGtWbNGX375pXJyciRJ8fHxysnJkc/n09FHH60DBw4oJydHubm5gRaX/n3E5XKpZcuWeuSRR3TSSSdpzZo1evjhh5WZmanzzjtPP/zwgwYNGqQmTZooISFBy5cvD7RKHjp0qP7zn//IGKOePXtq9erV6ty5s84991zl5OTozDPP1NSpU7V48WL169dPJ598sn799VetXr1aHo9Hbdu2lTFGa9asUfPmzXXo0CGdfvrp+v777+VwONS5c2dt2rRJ99xzjz766CNt375dzZo1U9u2bZWamiqbzaY//vhDGzZsUEpKirKzswNl5umnn67Zs2dr9+7dstvt6tmzp1atWiWPx6PmzZurZcuW+vPPP3X11Vfrm2++UXp6utq0aSO3261bbrlFEydOVFZWlgYNGqQOHTooNzdXO3fu1O7du7Vy5UpZLBYNGDBA69evV1paml566SUNHz5cQ4YMUXR0tA4ePKivvvpKSUlJSk1N1Zo1a9S6dWulpKRo6dKlslqt6t69e6DstVqtMsbokksu0b59+3TkkUfqk08+kdVq1bBhw/Tmm28qNjZWUVFR6t27t5o0aaLY2Fj9+OOP2r9/v1wulwoLC2W32wN1rfj4eJ166qlavHixCgsLlZOTo4SEBDmdTqWlpcnpdOriiy9WcnKy5syZo23btql9+/aKjo7Wzp071bRpU+3YsUMOh0MnnniisrKytHbtWjmdTsXFxcnpdOrPP//UGWecEdh/Dx8+HDh37N27V4MHD9bcuXPldDp16NAh2Ww2JScna/fu3brvvvuUnJysFi1a6Mknn9SePXs0YMAA7d27V2vWrJHH41GLFi20d+9epaamqnnz5vrtt990/vnna+HChcrMzNRZZ52l33//XcnJyTr33HP15ptvKi8vT82aNVPTpk21YcMGNWvWTBaLRUlJSUpOTtZtt92mCRMmaPny5YqNjVXr1q21efNmnX322dq1a5eOOOII/fbbb8rKylJmZqaaN2+u/v376/vvv1fTpk2VlpamrKwsXXbZZfrmm2/kdDp14MCBYl1yOJ1OFRYWBq5DHA6HevTooezsbF1//fWaOXOmli5dqri4OGVkZCgvL08nn3yyHnroIS1atEhz587Vhg0blJSUpKioKK1fv17GmMD6OP7447V7927l5+froosu0uLFi5Wbm6uMjAx5vV7l5uYqLi5OXbt21fLly2Wz2ZSSkqKdO3cWOy906dJFBQUFgRY6xx13nPLy8rRlyxalpqZq8+bNGjlypF599VXddtttGjNmjBwOh7p3767169crLy9PUVFRcrvdOvHEE7VlyxYde+yxuueee/Taa6+pf//+ev/99wPXHP5jITMzU6eeeqpmzJhR7DrSYrGoY8eO6tSpk3766SfdcMMNeu2113T11Verffv2+vLLL/X777/r3XffDVxLXHLJJfrmm2/0xx9/6NChQ/r3v/8dqH9KUmpqqnJzc5Wdna2cnBylpqbK5XJp48aNGjRokL766itZrVb17dtXY8aM0WOPPRZ4QsDj8ahHjx7Ky8vTmjVr5HA45Ha7FRUVpSOPPFKJiYmaP3++rrrqKu3du1e//PKLLBaLunfvrmXLlikmJkZXXHGFMjMztW/fPm3cuFEDBw7Uo48+qrPOOkvbtm1TQkKCvvvuO916663Kzs7WCSecoJdeeknNmzcPtMqqsaCltYB6wN9aqbCw0Pz444/m1FNPNVar1UgK22CxWIwk06RJE+N0OgPx+L+XZFq3bm2OPvroUr/1t+4qOjgcjjLn43A4ik2zsiE2NjZwF9PfOqe8ISoqKvB/q9Vq7Ha76dixY7HvSy5veXGXXH673V6n694/P3+s0dHRxdar3W4vFlvJ/aVr167GZrMV+64uYw7GvlbRZ/82r2hISEgwkkzPnj1Ny5YtA7/xb3v/eEXXi81mM8nJycWmk5SUVKXjz2KxGLvdXiresmK1WCyB7ZWcnFzu8VBym1VnuPnmm03nzp3LjTUmJsZERUWVOw//eirrWChrfVgsFtO0adNS48XHx1d6TFd3Xyy5jcrbT6pTllQ2lLcuyhri4uKM1Wots+yrKObajlvZcWG320uNU/Jz0XVbtEwtax8tK6bytk3JbdyqVativ7darSYxMbHSdVbZ+ilrXmWNW5t9o7zfVmWa8fHxpZax6PGUmppqrFZrseOy6Lr3z6Os81Z5g8vlqjS2mJiYUuOUPM4tFkup8iI6Ojrwf5vNVuP1Gh0dXWy7FV2+svap6pYZRc+j/v/79/2SMcfFxVW77I2Pj690X/CXhRaLxaSkpJjExMQa74Mlt03btm2LbYeSy1OV9VPZ/Equc/9vyto+JbeT3W6vcLzqxFKVweVylSrvunTpYgYNGlTraZccbDZbtfaXiuoTTZo0KXd5yjvmu3btWuq7hISEal03VFZ/rs5yJCcnm5SUlCpvy6SkpAr3hcrqhNWJt+RxWjJul8sV2JYWi8UkJCSY3r17V7rMHTp0KDc+/+e4uLjANqzOMlR1O5bcB4vOIyoqqtxtbLFYTGxsrHE4HKZ58+ZVKlurs79Xtawuee1S3e3ctGlTY7PZTFxcXOC3559/fqCFf23RMgqNin93f/DBB/XWW28pJiamWAeZCK/HH39c//73v2WMUX5+fuAOTkxMjHJzcwPjtW3bNnDnJFxKdvhusViK3eWoCv/d38pER0crLy+v3L/77x7VN506dQr0+1Keov1b2Wy2aq3fhqKuXi7gb4ESznWamJgY6AuvOvzHjtVqld1uL9Y3SiQJ1rYrb9/3tzDwK6tMiY2NDbRGCaWqlm/hUl9e2uF0OuV2u2sUa3x8vA4fPhz4HOxldrlcgT4Ay1Jy/6wpfwuOiuLwt7iryTKWF2ek78NVVZfL4V/3JedR2XaoD+u2smUI1v4drHjKU9XzR2Xfl6e629K/HMEqj+q6LC9ZjgZLybp90fpuXQrGsZeQkKCWLVvq1ltv1aWXXqomTZooOjq6RtMiGYVGJT8/Xxs3btRpp52m3NzcUp3pIbx69Oih1atXV2nccF9IlDy5WywWtWnTpspJslBXYqqq6KMzjV1tkl/h3j/rQrD3WX9T8vqiPlw8hUpVEuChOAaqOw+n0xmxiUvUXkpKSrXfiFoXqrpfVpYottlspTo2jjRNmjSp8tueyxOp9aFgaqw300LBYrEoISGhRje2qjOPcB+H4bqxVJaYmJjAY7ZRUVG68cYbNWLECMXHx1d7WiSj0Ghccskl6tmzp8477zydeeaZio2NDRRc0dHRgTdqAQAAAEBDQUIMweRvsfq3v/1N8+bN08qVK9WlS5dqT8deB7EBEaNoM9CjjjpKTz31lAoKCuTxeIpl0Ct6BAoAAAAA6isSUQi2Ll26KC0tTU2bNtWBAwdqlIyiZRQaLP/jFMYY7du3T5I0bdo0Pfroo+EMq1KR0BS0senSpYs2btwY7jAAAAAAIOJFRUXJYrGoSZMm2r59u6xWa7WnQTIKDZIxJpDQGTNmjKZOnarc3FwVFhbq0KFD4Q0OAAAAAIB6pOgLI6S/uro5cOCAYmJiAi+WqQ4e00ODZLFYZLFYNHr0aD399NPyer10PgsAAAAggL6UgKrzJ6KcTqeMMfr+++8DCSqXy1Xt6VW/LRVQT6Snp+utt96Sw+GQJBJRAAAAgP56e259Z7FYaj0NElFA+fzHWNOmTdWiRQs5HA717NlT48ePV9OmTXXw4EF5PJ4aJaIkklFooHw+nzZs2KBdu3bJ6/UG5WQFAGi4OE8AaEyys7PDHUKF7HZ7peUyvc0AdcsYoyOOOEIHDx6Uy+WSxWLRzp07FRMTo0OHDqlr1641TkRJ9BmFBqLoW/OKJp9iYmJUWFgY5ugAAAAAhBvddgDV53A4At3eLFy4ULt27VKXLl109NFH12q69BmFes9/Qjl06JA8Ho9yc3PVrFkzXXXVVTS9BQAAACCJbjuAmmjTpo0kac6cOUpNTVWvXr1kt9c+lUTLKNRr/hPKo48+qs8++0w2m02bNm1SbGysMjIyFBsbq9zcXJrxAgAAAABQidTUVB08eFDZ2dmKi4vTSy+9pGuuuUY2m00+ny/QJ3NtkYxCvVRYWCin0xlIRp1zzjn68ccfZbfb5fF4whwdAADV43A45Ha7wx0GADQK/u49AJStadOmSk9PV3Jysvbu3Sun0ymv1yubzRa0edCBOeqdk08+WWPGjNEff/whi8WiXbt2adu2bQ0qEdWjR49whwAACCEeK0ekCdadbyASlOwMnUQUULH09HT16dNHAwYMkNVqlTEmqIkoiZZRqGfuvfdeTZo0SbGxserdu7fuu+8+denSRSeddJK8Xm/EvxkEAAAAAIBIYrPZFBUVpfz8fNlsNiUmJsrj8WjBggU66qijgp6IkujAHPXMjz/+KIvFouTkZPXs2VN33323nE6nMjMzwx0aAAAAAAD1jtfrVV5enqKionTWWWdp06ZN+vDDD9W1a1dZrXXzQB0to1AvGGNksVh07bXX6p133lFMTIxyc3PVrl077dy5k6a2ACKKxWKRy+VSfn5+uEMBAAAASvH3CyVJCQkJgc8LFixQ8+bN1aJFi1KPuAYTfUahXvAfBC+99JKioqKUm5srSdq1a1edZWoBoKaMMSSiAAAAELHatm0rm80mh8Oh5ORkXXrppdqzZ4969uypJk2a1GkiSuIxPdQza9euVWxsbOAiz/82PQCIZA3pBQsAAACo/1auXClJiomJ0fjx4zV48GAZY+TxeOR0Out8/jQpQb1RUFCgLl266KqrrlKrVq3CHQ4AlFLeHSQSUUDDZrdzfxcAEDmq2uF48+bNdeKJJ+q8886Tz+eT1WoN2TmNPqNQL/h8Pvl8PtlsNh133HH6448/JElutzvMkQEAAACoLZfLpcLCQvqCBeqYw+FQTEyM2rZtK6vVqvnz5ys2NlZWqzWkXeDQMgoRz+fzyWKxyG636+KLL9aKFSsUHR0d7rBQCe4SAwCAhsDlcoU7hEahoKCARBRQxywWizp37ixJSk5O1qJFi5SQkCBJIe+LmZZRiGher1fGGNntdt1xxx166623VFhYGHgUpqHvvhaLpcEvY0NgsVjUrFkz7d+/P9yhACFD+YTGjr7gAAD1TYsWLfT7779r1apV6t+/v6xWq7xeb5Uf6wsmWkYh4jz11FOaNWuWpL8udmw2m4YNG6ZJkybJ5/OpefPmMsY0iougulpG3kAYXMYYElFodBpDGYzIU9dv9qkOElFA8FA3BepeXFycLr74YiUnJ6tfv36yWq0yxoQlESXxNj1EEJ/Pp7S0NL366qv6+eefFRUVpb59++rQoUP67LPPAv1GHThwINyh1nu8hRBAVVmtVsoMRAySoEB4VNQatrotZcsan/MMEHw2my3Q6qlFixbas2eP2rdvL6vVKovFos2bN6t169aKiooKS3ykoBERfD6fjDFq2bKlRowYoVWrVun666/X1KlTA6+c9KMiikgVFRUVtjsLQF3hAiHy+ft6AIC6UlH9u7p18+qMT4sp1DeR1G/uueeeK+mvrm9eeOEF/fDDD7r//vtls9n0yiuvaMCAAWFt6EGfUYgIPp9Pixcv1ieffKLp06crKipKe/fulc/nU3JysnJyclRYWBjuMAEAAAAACLmoqCjl5+eX+bfY2Fjl5eXJ5/PJ6XTK7Xara9euSkxM1C233KKrrrpKr7zyilwul4wxeuyxx/Taa6/psssuC/FS/B+SUQg7Y4xGjx6t119/XZmZmbJareUeZAAAAAAAoHzR0dHKy8tTq1attGHDBr3//vu68847dd111+mTTz7R1KlTdckll4Q1RpJRCBtjTKAj0szMTHXu3Fnp6elyOp0qKCgIc3SRgbdVIZwSExOVmZlZ6nuHwyG32x2GiCIXxyrqA/ZTAAAahqrUx2NiYnTyySdr6NChevjhh3XVVVfpgw8+0JQpU8KeiJLowBxh5E9GFRYWyuFwqEmTJkpPT6d/kiK4aEA4lZWIkkQiqgwcqxUjCRIZ2Aa1l5KSorS0tHCH0eBQRiBUXC5Xnd/0Zn+OPA3xZSwl6+MWi0XR0dFKTEzUnj171LZtWw0ePFg9e/bUgw8+qBtvvFHjx4/Xf/7zH/39738PU9TF0SMcwsIYI6vVqpdeekmXXHKJ9u3bp+7du8sYw4UuADQwVMrRUJCIqhuUEQiVUDx9wf4ceRpaIqooq9Uqu92utm3bKjc3V3v37lXXrl3VrFkzpaam6oEHHtC0adM0evRofffddxGTiJJ4TA9h4C8M8vLyNHDgQC1ZskSnnHKK5s2bV6qgsNvt8ng84QgTAAAAABBkNptNXq833GE0CP5OzYu2yEtNTdW6det033336fTTT9dll10WUW/58yMZhZDz+Xwyxui6667T/PnztW3btsDfYmNjlZOTU6Pp0iS2Zip6KwMAAAAAIHIUve51Op2S/mohNW7cOG3ZskXbtm3TkCFDFB8fr8GDB4cz1ArxmB5Couijd1arVW+99Zbee++9Yoko6a/WUlZrzXZLElE1QyKqYfG/FACojMvlCncIdS4pKSncIaAMNpst3CE0OAkJCeEOIWhqWg8M1fRQe9RVgNopet3btm1bDRgwQPfff7+MMXrjjTeUkpKi22+/XTExMWGMsnKR11YLDcqtt96qV155RQ6HQ5L0zDPPKDk5WYcPHy6zeWZDfp4XlYuExzLreweHDTEpS6vHutEY3lp66NChsM27vj6CEMzOfcs7duvjeol0WVlZ4Q4haIJ9Dq7P5/SGinN6/Vff68sNQUxMjHw+n3bv3q2YmBh5PB798ssvuvrqq/XRRx9p6tSpGjBgQLjDrBC3ClBnFi9erPT0dH3xxReS/jrx7NmzR88//7wmTJigJk2alLo7GhUVFY5QUQ11mWGvq0RUde7AcWKtulDdbW7durWio6NDMi8gWOprwqWgoEB2uz0ox3dZF5y0UokM4dgOtIYBGg7qy+HXvXt39e3bVw6HQ3/88Yfmz5+vK664Qh9++KGmTJmioUOHhjvEStFnFOqM2+3W119/rSFDhmjYsGHq16+fVq1apV27dmnt2rXauHGjHA5Hqbfn1de7yY1FOLYP+wQAAACAxqxTp076888/Jf2V4I+Pj1eTJk20detWNW/eXDk5OXr33Xc1ZMiQMEdaNSSjEHRDhw7VBRdcoOHDhys3N1djxozRM888I4vFoqOPPlp//vlno3g8BAAAAKgIj6Kjpth3Qivc67t58+bav39/4HN0dLSaN2+uAQMGaO/evZo/f74mT56sSy+9NGwxVhdtpRFU+fn5at68uW6++WZ9/PHHio6OVr9+/RQfHy9jjNasWUMiCgAAhJS/78pgoRN2BAvJBNQU+05ohXt9F01EJSUl6dZbb9U///lPTZ06VZJ05plnavDgwWGPszrowBxBFRUVpeeee04JCQm6/PLLZYzR119/XepRPKfTKY/H06ifNw53dh0AgMaiZD2ktnh0HAAQSg6HQy6XS9nZ2Ro4cKCOOOIIPfroozr//PP166+/av78+fXuTckkoxB0xhg98sgjMsbo8ssvl91uL5V0KSwsDFN0kaPkOgl1copkGAAAkYPzcmSJiopSfn5+uMMA0AgVPR9ERUXJ6XQqNzdXOTk5atu2rU455RSNGDFCF110kTZs2KA5c+aoW7duYY66+nhMD0Hj8/l0ySWX6Msvv9Tf//53DRgwQLGxsfJ4PNxBrIJQV0Cp8AKRj7dPobFqjPt+qM/LCQkJIZ1ffUMiCkC4FD0f5OfnKzU1VV6vV926ddMDDzygUaNGaerUqXr66af17bffqnfv3uELthZoGYWgMMbIYrHo1FNP1Y4dO5SZmam3335bOTk5iomJUW5ubrhDBIB6pzoXp3FxccrOzq7DaCJHWW9iReWsVmu9eTyeGyZ1Lysrq962xqpP+zIA1IS/fLZarfrzzz/1yiuv6MQTT1S/fv305ptv1quOysvD2/QQFF6vV8uXL9fnn3+uF154QcYYud1uGWPoHwpoxMpLkNTXC6BI5nK5eEEEUMf69++vH3/8MWTzs9lsdd66PBTzAFC/xcfH6/Dhw+EOo1GIjo5WTEyMDh48GKgrd+3aVTNnzlR8fLz27Nmj7t27hznK4CAZhVrx+XyyWq164403dOuttyopKUmdOnVSenq6tm7dWmxc7mIBAID6gIQ5UHskOoGqKXmdXLQFuMVikc1m06+//qoTTjghXCHWCfqMQo35E1Eej0enn366unTpokOHDmnTpk3q3bt3qdcek4hCJLHb7fXujRMAgNAgEQXUHokooGr818n+62f/Ochisej5559Xp06dSl1bNwQko1Bt/oPDarVq+fLlGjFihPr27astW7ZIkjIzM/XFF19wAkJE83g8PNIEAEA9YrVy6QJUR0NMYDRU7dq1k8/nU1RUlDwejyTp/fff186dO2WxWNS2bdswRxh8dGCOavFnbY0x2rBhg44//ng1adJESUlJSk9PLzUezdwBAOHA4yHAX8JVF6uL+dLKHqgezoP1R15enqxWa+BNnqNGjdJXX32l7777Tt9//72aN28e5giDj9sLqDL/Y3mS9Nxzz2nAgAGy2+3KyMjQ5s2bFRcXp/bt2xf7DYmoyNEYX5MNoGyNoTygAl53GsP+05CEqy5GHRAAKufvNqRow44ZM2boH//4h3w+n+bOnavevXuHKbq6RQfmqBZjjB555BFNmzZNaWlpxe5QxcbGKicnJ4zRoSoa0+vfATRutI5CqDkcDnk8nqAkYnjxy1+cTqcKCwvDHUa56rrlmd1uDzyyA6Dhstvtslqtevfdd3XppZfK6/XK5/PJ4XCEO7Q6Q8soVIn/JPv111/rf//7n4YMGVJqHBJR9UN2draio6Or/Tu7vX4+1Wuz2ZScnBzuMEqhZQFQ90hEIdTcbnfQEhMkov7SokULJSUlhTuMctX1fX0SUUDDZ7VaA/1C9e/fX8YY2Wy2Bp2IkugzCpXwV4SsVqsKCwuVkJCga665Rh999FGxv1Fhql/y8vKq/ZtgVIbCcXfT5/MpNzc3pPOsippUXou+5hUAgMZgx44d4Q4BQAMUjnp1hw4dtHXrVklScnJyIAl1xRVXKCcnJ1DeNZab1iSjUK6ir5S84447tHbtWqWmpurTTz8NXNxbrVZ16tRJGzduDGeoqCfC0czeGNNg3ppHIiqy8IIGAACA+sntdof8cf6tW7eqadOmSk9Pl8vl0t///nfdfPPNmj59uj755BP98MMPDbKj8vLQZxTKZIyRxWKRz+fTzz//rIsvvjjQmqZkqxp/p+a0jgIAAAAAoHwpKSlKS0vT5MmTtWnTJi1atEgvv/yyjjnmmHCHFlK0jEKZ/Hf8P/30U02YMEHZ2dkyxpTZMoMkFAAAAAAAZTvyyCO1ceNGxcfHKy0tTWeffbays7P1zjvvaObMmY0uESXRgTnKYIzR119/rZ07d2rKlClauHChvF6vunTpEu7QEARt2rQJdwgAGqj6+qIDoCR/q28AQONis9nqZLqxsbFq1qyZDh8+rA4dOmjw4MF68skn9fzzzzfKRJTEY3oowhgjY4zee+893XHHHRo5cqS6du2qoUOHyhjDq2UBAKiFSOlnLCoqSvn5+eEOI6I5nU6dccYZmjNnTrhDAQAEUajPxRaLRYmJiTp06JAkqUePHrrlllv06KOPavLkybr00ktDFkukIRkFScXfmjdjxozAQdGsWTMdOHAgnKEBAACEHDfhwis6Olr5+fkRkcAF0DjFxMQE5a3c/o7S27ZtqxEjRuiRRx5p9IkoiWQU9H+dlRtjNHr0aL366qtKT08vNk5SUlIgm4vyWa1W+tACAACoJZKBiGTU+VEZl8ulzp07y263a/fu3Ro/frxcLpeGDh2qTz/9VEOGDJHFYgl3mGFFMgqS/moZ9fTTT+ull16S1WpVmzZttGrVqnCHhUYq1K9Zran6EieAhqNDhw7aunVruMMAUAXUE4DGy2Kx6Oyzz1ZycrKGDh2qSy65RB6PR1OmTNEVV1yhpKSkcIcYdvTOCPl8Ph06dEhz5sxR165dlZmZSSIKYRWqiltt70ZQwWx4nE5nuEMAKkQiCg1ZkyZNwh1CUFFPqD94aQGCzRijxYsXa+fOnRoyZIiMMZoyZYpefvll7dy5M9zhRQSOOujzzz9XQUGBfv/9dy1ZsqTUibOxNx+sr+rqTRDhVNabumrz9i4ahqKkwsLCcIcANDpcBMLv4MGDQZ0eddjIEslvXOWRO9RWbGxssc8tW7ZUly5dNGfOHNlsNk2ePFkjR47U008/rR49eoQpysgSuSUC6oy/j6h3331X+/bt008//aTevXsrMzOzzItzLtjrp4Z4N66sviPoTwJApKGvm+rhIhB1JVLqsJHyJs1wo1xEQ2OxWAJDTk5O4PsmTZro5Zdf1sCBA+VyufT6669r5MiRevvttzVkyJAwRhxZuBXVyPh8PlksFi1YsEDXXnutVq9erQ8//FBjx47lJAnUI425JUEk31lFzURHR5f7t/rYypMLLqC0+nTeCnas1LGB4EtOTq6w/hAKxhj5fD7FxsaqadOmkv7q23HHjh266KKLFBMTo9dee02PPPKIpk6dSiKqhPpzVkBQ+E+u3377rdq3b6/p06erZ8+eWr9+fZgjqz9o8h0Zwn3yCbfG3JKAC/2GJy8vr9y/kXyMDC1atAh3CPVWMBMb9blfu5qct8KVwGrM51hEBofDEe4QIl5GRkaF9YdQysrKUnp6utq2bauEhATZ7XbZbDbNnTtXzzzzjCZPnqxLLrkk3GFGHN6m10g8//zzuvHGG5WYmKiPP/5YI0aM0ODBgzVlyhTl5uaGOzwAQD1XV6+55pE3AAAQaYrWe+x2uy6//HLZbDa9+eabstvtslgsWrdunQ4fPqw+ffqEOdrIRDKqEdiwYYO6du2qSy65RG+++aZ+/PFHzZo1SwUFBdq7d69atmyp6dOnhztMAEAdo98SAACA2nE4HLLb7YGWWUlJSZozZ06gH+b4+HhadlcByagGzt9Z+dKlS9W/f3+1aNFCLVu21OLFi+V2uyX91R9HVFRUsU7XgEhT3y6i61u8AAAEU3R0tOx2uw4fPhzuUAAg6Pwto4455hidfPLJevnllzV16lRNmzZNc+bMUXx8fLhDjHik6xowY0wgGfXFF1+osLBQW7Zs0Z9//hkYx2KxyOv1NshElMPhCCTcUP8VTey4XC4VFBSEMZrKJSQkKDMzM9xhAEFhsVhktVqr/JbOunpkDw0P5+qGK1L6cgGAYHO5XHK73XK5XGrWrJkmTpyot99+WyNHjtRbb71FIqqKaBnVgPkTUYsXL9Ztt92m9u3ba/78+Tpw4EC4QwMA1EMkmeqWzWarcsIPAIBI1FjOZc2aNVN8fLyWL1+ujz/+WA899JCmTp1KR+XVwNv0GjCLxaKPP/5YF198sVasWCGr1dpoHxtq0qRJuEMAgHqPRFTdagyV94pERUWFOwQAQC019HOZxWJRbGys7r//fq1bt06ffPKJHnzwQRJRNUAyqgHyXyzs3btX8fHxcrvd8vl8mjVrliwWi5KSksIbYBgcPHgw3CEAAIAK5OfnhzsEAEHicrlktXKpWZ9wQ6BsJTsiN8aoV69eeuCBB/TZZ5/plltu0bRp00hE1QAlRAPi8/nk8/lkjNHcuXP1t7/9TampqYHKXV5enlwulw4dOhTeQIEgi42NDXcIAMKACx0AiEwFBQW0pq1nuCFQNo/HU+xzSkqKLr30Uk2cOFHGGM2aNUtDhgwJU3T1G31GNRA+n08Wi0V//vmnCgsLdf/99+u7775TVFRUg+pAkjeUoaFgXw4+p9OpwsLCcIcRERpy304cO8HHOgUQiRryuayxi42NVWFhYcheYFGbfclutweutVNTU3XPPffowQcf1LRp0/SPf/xDNpstyNE2HtxSbAB8Pp+sVqtWrVqlLl26qH///vruu+9kjFFeXp6aN2/eYO4eU1luXBpy4c6+HHwNMREVHR1do9815Mo7x07wRfpbf2j9Wn9YLJZwh4AGxP8ypmByOBxBnR5qJicnR3FxcSGr61e3XtSsWTPdfffdiomJUcuWLfWvf/1LhYWF+uc//6nHH39c7733nq644ooGfa0SCrSMakBuuOEGvf322/Wios5d2IaHu1eIBJQtaEyq+8Yih8MRsrvQaJzYxxDpqCfUP8F+O19Vyqm4uDh99dVXcrlcOvvss9WhQwddeOGFmjRpkt566y0NGzYsaPE0ZiSjGohly5bppptuktvt1urVqwPfUykIH5fLpYKCgnCHgSBKSEhQVlZWuMMAgIBevXpp5cqVYZt/+/bttW3btrDNH0D4ORwOJSUlaf/+/eEOBQiaLl26qHPnztq2bZsOHTqkvXv36umnn9bIkSPDHVqD0TCe3WqE/J2V+4djjz1W11xzTam3INQ2EeV0Omv1+8o05Kaydb3uwq0xNsXPyspqlG+jBBC5wpmIkkQiCmVqjHWExsztdpOIQoOTnZ0tt9utZcuWqX///mrWrJnatGkT7rAaFHvloyDSFH0UatGiRdqwYYOys7P1/fffa9OmTZKC1wS1rvtgacittg4fPhzuEOpUMPav+thUmrdRAo1LfSyngHDjmAFQGzXp/iNYTwQ5HA4NGTJEzz33nFJSUuRwOHTKKafos88+U5MmTWo9ffwfHtOrZ/wd+Rlj9PDDD+udd95RZmamCgsLg9JfD5Xuhquqjw2Geh8I9nPgwcAjlgBQO0UvJKhbAKhMuMuJuLg45ebm0v9pI+ZwOOR0OpWfn6/vv/9erVq1Ups2bfTee+9pxIgRmjp1qi655JJwh9mgkIyqp5588kk9//zzcrvd8nq9SkxMVH5+vnJycsIdGoIoKSkprC1xnE5nWN5QRmfoCIZwV2wBoLGh3EV9Fx0drby8vHCH0Wj53wAfiusAi8WiqKioUtv7hRdekM1m0wcffKAhQ4bomWeeIRFVR+gzqp4xxmj37t2aNWuWTj31VHk8Hnk8HvXo0UNdunSp0jSsVmuD7qupLpXXB4K/4Ay2ookol8tVJ/OoSDgSUVLdnoB4BWvd7a+Rpr5eENHXCvwieV+gLEVZ6mu5WxvNmjULdwgIIhJR4eXvDzkUjDHKy8tTQkKCTj/9dElS27ZtFRUVpSeeeEJHH320xowZo7fffptEVB1pHFckDYDP5ws8oudwOLRz504tXLhQXq9Xbdq0UX5+vlasWFHlaTXkvprqUnmVLH+hWZcX+fXlsbGqrINwJkO8Xq+aNWsmu73xdplHq7PI1hgv5lC2SN4XvF5vlZJlJK3Q0B04cCDcIQANUjBvyJT3Yimbzaa8vDwtWLBARxxxhB5++GGNGDFCzz33nNLS0jR58mQNGTIkaHGgOB7Tqwd8Pp8sFossFotmz56tBQsWaNy4ccrPz5cUvM7aUH00R68Zp9Mpj8dDUgRARAjXI8kAEC71vdxLSEhQVlZWuMNoMGp7TWO1WmW324O6TwW7X9kWLVqoRYsW+v3330v9rWnTpho9erQeffRRTZ06VYMHD9bBgweVkpIStPmjNJJREc4YExhGjhypzz77TDk5OUpLS4u4Tp/rgt1ul8fjqfV0gtUHUVUL6uTkZGVkZNR6fggdEouINOyTda8+JcbbtWunHTt2hDsMNBKUPwDqkj/RFOqypnXr1tq7d2+x837z5s11yy23aNy4cXr//fc1bNiwkMXT2PGYXoSzWCzyer164YUXNHHiRMXHxys/P19er1fR0dHhDq9GqvN4VDASUVLwHkuqamFJIqr+odLdsEVSP1lVLQPZJ+tesN5EW55gPg5MIqp8kdy3Vn1VUfnjb60PADXlb1QR6rpOWlqabDZb4Dp66NChGjlypN5880299NJLJKJCjJZREa6wsFC5ubk69dRTtW7dOjmdThUUFNSbt42Vl+3mjlvolLWu4+PjlZubG/LWdWx3IHg4nmqOtyUBtdOxY0cdOnQoom6+USbWHZfLFXF9l7K96z+n0ymfzxe0xgcViYmJUbdu3bR06dJAH8zDhg3T3r17tWTJEk2aNEmXX355nceB4iLnVjFkjCmVHLDZbPruu++0du1aGWMCna9VJREV7rtWDoej3I5LI/nkUZU3DUZHR0dUS4uKGGNKLVN2dnadJqKSkpLKjaU+aWgd7zbmTtvrg6ZNm1ZrfGOMXC5XvSmLgq02b4WtD4moDh06hDsEoFxbtmwp9sbfSFDf6hj1SXUSUaF6+7MxhnpNA1Bex+LBlJCQoKuuukrGGFmtVhlj1LRpU73//vv69ddfNXXqVBJRYdI4a7AR6s8//wwkkKZMmaL58+fLarXqq6++CoyTnZ1d5elVdlKu64Pf7XbXOtNd1wm1sqZflc7g8/Ly6kXLNOmvx5PcbnexZa3rClukVVBrqqH1y1ad4zHcyezGKD09vdq/KSgoqDdlUbA19Bd3bN26tU6m63Q6G20Cs6YoD8tG8gdlCWULqlC0qEFwlFWO+p8Aquv5+ju6T05OltVqVa9evXTgwAHFxMRo+vTpuuSSS+o0BpSPx/QixO+//67jjjtO06ZN0++//65XXnlFqampmjZtmoYPH65169ZJKv7mvEh7VI/mshUL5fYq+YYU/7Zp0aKF9u3bF5IYgiHS9nH8n2C/4SQUKKOAsqWkpCgtLS3cYSDCxcfH6/Dhw+EOI6IE60U7jYXD4ZDFYqnSG9ci8dFA1Jy/Tl+ybp+YmKjMzMygzqusOqrFYpHNZpPP55PD4VB0dLRee+01WkSFGcmoCLFnzx5NmTJFTz31lCwWi1q1ahW4K2qxWGS32+X1euvthXlNkgqhfgNeQ1LWMqekpMjtdkdU/w6o38J9bJVVRoQ7pvqk6M0NhFZ9SeZyod24WK1WDR06VHa7XR9++CFlKYCgatq0qU455ZRiT/1IpW+IJCQkKCEhQTt37qzxvJo1a6aDBw8G6on++mFUVJRef/11de/eXX369Knx9BEcJKMiyKRJk3TbbbdJkrp166Y1a9YE/lbfLrASEhICTSIrUrIFT7DRsqZx4gKqfqlv5VtNUR4BqA+Sk5MrvHFltVrlcrnqRd9rdSFSk8lVPZdG8rmovre+i+R1WxN1cZ1WnTpfbeuHsbGxuvXWW/Xnn3/q888/V5MmTTR+/Hhdfvnl9DcWIUhGhZG/sFq6dKn69OmjXbt26fLLL9fatWuVnp5e6gCsLxds9SXO+q7kek5OTlZ2djYtHVBvRGqFPpI0tIptsLBeqofHXQAAFYmKilJ+fn7Qp5ucnCy3212tfo+DweFwyOPx6OKLL9YPP/ygo48+WikpKfr4448VFRUV0lhQPnqwDBP/M7NTpkzRySefrAEDBmjy5MlaunRp4G6UP9Fw1FFHhSTBE6wOTWsaZ6g6CLVYLA2iM9KS6zkrK4tEVIglJCQEdXqh3i+rM7+6iK2yRFRcXFzQ51nfkHApWySsl/p0HikoKOB4QoNCq4aa4wUG1dcY1lkwElFt2rTRW2+9Vext1KmpqSosLCx2/RUbG1vreZWlaLkQHR2tLl266KuvvtILL7ygrVu36tFHHyURFWFoGRUGxpjAqyVHjhypCRMmKDc3V4mJiYFH29gsNUOrrLIdeeSR2r59e53c8SgqmC1dWrduLYvFon379hV75K68O/xs+/qjefPm2r9/f7HvKtp3Sj52mZiYKJvNpoMHD9ZpnEBDU51ysq4fo0f94N8Pytt3kpKSGswbdMtTlf4J/ecpfx+v1EdKo57WcPm3rdVqVWpqqjIzM0PeR63NZtPxxx+vP/74Q7m5uTLG6KGHHtLll1+u3r17Kz8/n0RUBCIZFUbPPvusxo0bp9NPP11Lly7V3r17JVFYV1U4O98t78K5IT46UtVlCuWyt2zZMnC8oOGrah90DUVlx1J1zhFxcXEhbxoPoH6wWq2BG6SoueTkZGVmZpbqKDkYLr74Yn3++edBmVZFKks+V7ZMNa2TWywWde3aVWvXri337x07dtTmzZurPe1Q43z71w1jt9sdsuuBsvZLp9Opvn376t5771W/fv3kcrkCLdvqU4vmxoJkVBj4fD5lZGTosssu04oVK5SRkSGfzxc4mE499VT9+uuv5Rb61SnswpXYakgVnPJO0PXhTVRV2f4VPSPeqlUr7d27t0Fsx3Coq+fvG4qGkngv2XIr1MmzitZjQ0yQA6ge/w00/4WYv7yorNUTgOIq6n/vlFNO0bJlyxpFi9LyyoyoqCjFx8crIyMjLC8S8pdxP/74o0499dTAZx7rjVwN/wHYCFH0gP3hhx80atQoud1uxcXFBZrzOhwOnXnmmVq8eHGFlQJ/IiqcB5bT6ax0nKLPC9dnLperzO/9iaiYmJhKp1GV9VWRijL5Ff2tKpXLipIle/bsKXMawb6z4HA4gjq9SEEiqnz+isxJJ51U5t/qcr7BVrLCFepWXBUd50UTUbXt86IuzjkN7S5lY+hXBPVP0Zbc/vLCarWqsLBQDoejQSeianNMVlbm8chP1ZS1Dcpat9HR0RVOJyUlJexlrD8RdfTRR+vkk08u9rdff/017EmPivoGDOb51v9IXkn5+fllJqLq+prQ6XTqxBNPVOfOndWnTx+ddNJJstlsstvtYd8mqBgto0LAGBMoAD744AO9++67Sk9P19q1a5WdnR24c3366aerZcuW+vzzzyvMJhe9sxWKV6BG4huvIuEunr9llM1mk8PhqDDxUN03GRVtzVBRy4aSLTL8qrLNSo5T3f5BQrFfROK+J1V//4vU5Qg3i8Uil8ulE088UT/99FNI5llXbxXzd8xZ162QOnbsqC1bttTpPBB5IuGch4aNlrw1Ex0drby8vHCHUa9U9GRB0bKuPjyBUF9Vt14aExOj3NzcwGd/Isrn84W1juvvo83hcGjz5s1KTEyU3W5XVFRUoA83RDaSUXXM/9Y8Sfrjjz909dVXS/rrLtXvv/8u6f+SAOUVuiWbVZfFn3Guq8KgMVWEK1rWooVxKE6SLpdLTZs21d69ewMXuf75lpWkKtqRqM1mU4sWLUq1bmpM2xKRLz4+Xu3atdOff/4ZklfPN2vWTAcPHozoR9eqWlEPFx79Cw+r1Rqo9Fdn/VelDgGguMTERBljlJubW+njRk6nUw6HQzk5OYHPtX1UKyYmRnl5eaWO26qeA8o77lNSUpSWllar2BAZYmNjA/tcXfO3WiuaeK1Kx/4lBbsOY7FY5HQ6VVBQoGOOOUbLly8PnCcbyhM6DR3JqBB58MEHtWXLFu3evVtr1qyRzWbTEUccoaVLl1bp923bttWePXvqNPNc2QVGea1wIkldXyTZ7fZA4R+qdeGfX8l+aKraeirSlLzQbtGihbp27ar169dr7969vMEJQVPTSk8kJHwqSyCEqiVWJKlP5VxdqU75SKuCxqG88srf8rQuWjtxLJYW7LcK+luqharVSVXq+BaLRXFxccrJyWH7VyAS6hB+dRGL3W6X0+ks1lKqpNTUVG3fvr3SaVXlPFXZMnTp0kUej0fLly9XUlJSpfNEZKFzgxCYNm2aJk+erOOOO05ff/211q1bp2OPPVZpaWlV6isnMTFRO3furPOTUWUnlvrwmFFdnxw9Ho8KCgrk8XjqtK+T6OjowL7hv+tRtNDv2LGj7r///kDz08qWu7x+r8IlISEh8P99+/Zp3rx5gbfjlXehVVlfAvUdd3CCzxhTo/7aaltxq2nZUPR3RV8AkZKSUmpcY0zYLwZC3d+TxWKpUh99dTHfSFGdRH11ElHh7rcvktZxfVNeedWrV69AIirY589wlz3hUtH5JJiJKOn/+pysTt27NsdRVW6wGmN0+PDhOqmv+OupVV2G2vbFWpeMMdXuTywmJqbC35RcL1XdBrWpzzRp0kTSX+vaP/927dpJKt4nqtPpLLU9tm/fXqVH5Co7T/lfiFWyDHO5XHr55Ze1ZMkSjRkzRmvWrFFSUhKPGtdDJKPqWG5urjZt2qR27drpscce0xNPPKEWLVrozDPP1M6dOystrOLi4vT555+XOqDj4+PrMuxi/I8Z1rRAC/aJpa4SK+XNv2QB6C/o6vKuR15eXqkKSNGKwpYtW/TBBx/IGCO73V7pOnY6nYqNja12HHVxgeB2u2vUz5m/aXA4LkYrE4yKWSiTvUW3a7g6A7VYLCGZt//ivS7mVV5Fq6ZlgzFGvXr1KvV9VY+XmhzjteHvt7Cu2O12NW/ePPDZ6/UqNzc35PtspNzhrksWi0U2my3k+5BfMNaxzWZr8DctqsJ/fPi7gpBUbp9G9T0JWFc3ccpbL/43D1Y0rt1uD9t51d+pdF1v15q2uKxovfgf069qWRCJLeiLrvfKkiIly6rc3NwKf1NyvVRUZ6xo+1d048Futwf6wZWkgwcPSpKOO+64QJ1tx44d8ng8xRLSHo9HTZs2LTXfYDxB4vP5ZLFYSpVhbrdbL774oiwWiy655JJAH1G8VKD+IRlVh0477TR9+umncrlccjqduuqqq/TKK6/oxBNPVHx8vO677z653W61bNmyzAqU3W5Xs2bNdOWVV5Y6oItenBx55JHV7qAtLi6uyidxf4FT05NbsE8sVe1XprpJq8LCwjITUnXZMWVFb71wOBzFWhCVtHv3bsXExOihhx6qtOJz+PDhCp8rL2/bVnXbVXff8E+3ouUrT+vWrcvcTlarNXDHJtTqQ6vBoopu13Dd4fa37Klo3wlmpaIulrPkfhiMC6OVK1eWOp79ZVBl5Xw4HsmqyxdoOJ1O3XLLLaXKcv/5MtxvVQolq9VarZYA1W01UFhYKK/XG7L+R4Kh5H7h9XoDx8qZZ54ZjpAqFYrkj7+sK6/MczqdNbrJWNnxFo6OgoN97vXX11u2bFnuOCXXWcnPJS/UQ83n88kYU2H9sjJ1lZTu2bNnmd83lE6mq3M8lezLtaqio6MVFxcnh8Mhm80W+G1VE/EV1RO8Xq+8Xm+p88eGDRvkcDg0Y8aMMssBn89X7tu3g6HodKOjo9WiRQvt2rVL/fv3V8+ePQMxNZT9qNExqBNer9e8/fbbJi8vz6xYscJYrVZz6623mmHDhhlJRpJxOp2B/0syVqu12GeLxWKaNGlS7LuSQ3R0dKnfMfzfkJiYWK3xXS6Xadu2bZXHt1gstYovLi7O2O32wOei/y85XHPNNaZ3795hWY+1Xc7WrVsbm81WpXFL7s+dOnUKyzLXh6G22yUcQ8nt63A4gr4cFU2vrP0wWPOPiooKyvqpTZnesmXLWm+TSBlcLlep82TRoV27dsblcgV9H/EPFZXHtRkcDkeZ07bZbFUuJxkqHsJx3oik48hisdT42KhssNvtJjo6OuzLWFZcwZhOkyZNjMPhqHS8kuOUN//anF/K+m1VpxcdHV0nZVgk7efBHiKp/O3WrVuVx42NjS3zeK9JGeDfvmXtZ88++6w54YQTQrIOjzrqKHPnnXcW++6OO+4whYWFxu12m8LCQpObm2uMMebbb781v/76a5iv/FFTJKPqwOHDhwP//+ijj8yTTz5pBg8ebGw2m7n77rsrTTCVVShUtTCqyQFf0xNLVU9yNY0rGIPNZqv2ybhNmzYmJSWlzL/V9cV/TEyMOeKII0znzp1L/a2ii7L6kJS48cYbTbt27cI2//qwjupisNls5e7PwV6/tamkhmv7tGjRwsTHx4dl3iUvZhISEkx0dHSgMte+ffuwxOUfnnzySdO3b986nUdNt7vVaq2zi+1gxFfZ0KNHjwrL9Po8xMTEhD0Ghr+GqiRVqjt07Ngx7MsVyqFoGVCVc1x5ZUZ55VVl06xtGVTR8VjdZZPKTzZUNc5ITWZZrVYTFxcX9jjKG/yxxcXFVauM9ZcB5V17lrXd/NuoR48epbZ9UlJSyOprRcsvq9VqnnjiCePz+Ux+fr7xer3GGGNeffVVk5iYaBYuXBiuy37UEsmoIPv888/NWWedZYwx5swzzzRRUVFmyJAhRvrrrnlCQkKxgrhooW632yutXDdr1syccsopNTqoU1NTS51EanpSsFgstb74DPZQWTa+rFjL+s7pdJqoqCiTnJwckritVquJj483MTExJioqqtQFqMViMTExMcVabJVsgVHeXZHKhl69elX6u2Bu44q2UWUnt9rcIWxMQ1nrJBx3++qqVUl1hqq0VApFQiMcQzCOW4fDUe3WpcEaytt/mjdvXmd3+ytLDtWkNUhZx+MRRxxhJAUtCRqOcrC8edrt9oiqFzSkobL9r+g2ufzyy0NWhwnlUBf7VnJysrHb7VU6jso6XzgcjmLn2JrEWN4No2CUdbU5/7tcrmqVL1artdT8OnToENZ9xuFwlFm21zZRa7fb6+Rme3nr22q1ms6dO5sjjzzSSOXXb8pKVFWUiDrxxBMD+2zJa9LExMRS13oxMTHF9te6ruvFx8ebUaNGmZNPPtnk5uYar9drCgoKjDHG3HzzzSYmJsZ88skn4bz0Ry2RjAqyd955xyQnJwcOfP8Jzn+AX3fddYHsdmUV34pOIFT2glfAV2Xd1vXFfKtWrYzNZgucHJOTk43T6TQJCQlGqviiJRgXIiWnEYzlPf/886t0koqOjm40SaVQLGdjWZc1XfZgJJ8qq8Q2a9YsKMtTnXK+LlpAhGtwuVxm3rx55sYbbwzpfNu3b1/hOq8ouZmQkFDl5FLReUTi4051OdTnukskPcIjVVzehfo8UJ+3a1XjL2/7H3/88aZNmza1Wu8V3YyuzjSDWZ5Udk6x2WylysSSLVYj7ZgJVVy1qWfYbLZyf1807pNOOqnKj/IdccQRxa5FSw4Wi8XY7XYTFRVlOnToYGw2W2D8AQMGBMYpup3rat35r5/987NYLOaaa64JPJo3adIkc9NNN5l//OMfRpIZNWpUuC/9UUsko4Joy5YtplmzZsVOBgMGDAgcUP5Hr6pzN9TfKiY1NbXY906nM2IL+fo+hKoSVzRRY7FYTFxcXLF5l9d0tqIET1VjLzleQkJCsYLfP69grMt27doF/UK5se/7TqezwkpnpCSkHA6HOfnkkyvdR6oynarMryrTKq8vlVBcTBV9BK+8uKtyARCM9VDb7VrX6+qf//ynGTNmTJ3Oo7KL+bLuejudzhpdaFS2TUqW66Fu1RJJyYS66EcuHENZ6zQSWow2hCFc67FoPank9o2KiqpVEiI5OTmQ1Kpo3kWH2tSF6uIYs1qtxuFwVPq4WzD6Vwz2Nq3pUF7rqOpMt+R+Y7fbA/t4165dzemnn17mNh8zZkyF3TAUvd6sbF9xOp0mPj7eDBkypFiL6Kqci4J9/ig5PZfLZfbs2WMmTZpk4uLizJlnnmkkmQceeCDcl/4IApJRQeDz+YwxxuzevdtcfvnlgWbqTZs2NW3atDEWiyVQeU9KSqpWoew/4dWmz5eSTTZrWvBaLJYqd44biopkdQq/isYtK9a6rOg4HI7ANvXPu3Xr1oH+lEqeMIqe1OsqCdOhQwfTrFmzUk3Vo6OjzdFHH13l+ZYcz2KxmFNPPbXCvm+q+4y+zWaLqAunmg7BSvaFezkqGqKioqrUjL2iyo7D4QjcAavp+ix5PB9//PFVnobL5aqzinNNj+dI3+6Vrf+qDEUr0f5O3auabKzOfCpKrNntdtO+fftSNw5q2vqgqsd8fHx8lW9aNbb+e4Kxzeti/sGIoazyoK7PdWW1iq6ozPYfL/UxqVbWyzO6dOlSbtlSVgsVfx2+aBlgsVhMVFRUnfcB56871vT3NenLzd86v6x1U94+5HA4zAMPPGC6dOlS7nZoTC3iiw4VPbJYsk/V1q1bB46zksdlyZvGwdr3Tj31VHP77bebiy66KKTrpWfPnsU+9+jRI3DsdevWzdxwww3mlVdeMYmJiWbIkCHGarWSiGpASEbVUmFhYaATtbS0NDNu3LhAf0P+gsVfaPhP4tUtgCurHFQ01OdHN6p70i3Z6bd/PdtsNpOammq6d+9e7G8tWrQI6fL443G5XMVOOv6TutVqLXUyatasWeBC2F/5CcZjRmVVeuPi4kzPnj3LvPD2z7OylgR2u73YydZfyTvqqKOM0+ms0X5css+a+rxP18XgcrnqTUsx/74RrAuZoncPa/rbkvt0WXfk6uqNbfWtMl4yCRMTE2PuvvvuoG3L4447rty/19WFXll9nBQdyrsYq+6ylUy6F71JJZV+C2J9OaYbyxDu7VHRG66CPVRlHlVNDkfK0KJFi2LJGH8L2fLOH/5js2TSxGKxmM6dOwdaSFY0jZLrtKpJ7Orua1WtV3Xr1q3GLxcoecOoZHncvHnzwP/rY6JSqvzJA6n8xgO1PRb8CW1/f4L+oWPHjoFGCf7WumXdqKhq347ltfgtui+1adPGnH322cW2cXWXr7rXb126dClzHp07dzYpKSnmtddeMwkJCYE+oiZMmBDmq38EE8moWvB4PIFE1AUXXBB4lK5du3bFCjSr1Vrq4K/OgV3WiSlYFaOiFeTqnED8Fw3+wqomBXFdVe78y+E/abRu3dq0atWqVEWkLubtH2py4WS1Wk2bNm0ChXhVk2WV3UH3d8he9Dv/Y3n+oeS2KCvhU9EbN0oORe+I+addnZZ11R3qouWK/5n5qo5fctxgVE6qOm58fHyVWpiF4uIhNTW1zORNixYtAvtC9+7dS1XMa3PHN1Rv7KxOGVnVx7Lq0wVdWUPr1q2D1nqjbdu2xV7U0NCG8ra1/3Hm8tZjMB9lbcyD0+mstD+3yt7SWNm2qMvHj4q+hKassqi6j4I2psG/7EceeaQ5+eSTA+uxJueOovWl8rZ3dfp/8t/IK297V5YkiYmJqVIyIjo6ukr1yrJiLGs5S47Xpk0b065duwpbCjaEVu1VXWc12a/atGlTqvVUkyZNAtNv1apV4Pui1xnNmjULjFOVMqhktyDlDZUdH8Hcnv4bQ0XPZT169DCvvfaasdvt5pVXXjFnnXWW+fTTT8N89Y9gswo14vP5ZLVaZbVadeaZZ+rrr79WWlqaunTpol27dsnj8UiS7Ha7JMlqLb6qjTFVnpfX663Sd37R0dGyWCyVTrdFixZKSEgIfPbHfMIJJ1T626ysLB133HEqLCyUVL3l8atoGSqL32azlfu7mJgYSVJ+fr4kyeFwKDo6OjDO+eefX91Qq82/XqqyHaxWq2w2m3w+n3bt2iWfzyeLxaJ9+/aVGres6R0+fFiSFBUVVW4s+fn5xX6blZWl/8fed8dHVWbv3+m9Z5LJZCaZ9N5IJYUkJCSBQAiEFnqvQZAaaYpUEekCUsWGoLKKKIuiIHaxF9yiq6uurgUrKiXJ8/sjv/PuvXfuJAHL7n6X+/m8H8jMnVvect5TnvMchULBoc0hzeYpx3GcyWTi8vLy/K4DgN1Dq9Vycrmca21tlXwfl8vF2e12juP+Nc4qlYobPnx4wH74Jcf58+c5lUr1q16zpaXlsua1uB8D/VYsC9q7XmePH374gTt37twVX1Mmk/k9V2fmrvhQKpUCucA/+PPZ4/FwKSkpgu+l5pL4kOo7tVrNZBcdXq9X8LfP52O/FV+D5rRKpWKyg86j8SR509zczJlMpoDPx+8zcV+L+5Oe+XJlp8ViEfz9a8/7zhyhoaHs/59++mmnxo5/qNVqyc8/+eQT7tNPP+WUSqVAZv/aR2fXIJ0n1cedWR8Wi0XwrlJjrdfrBXuA1NGZOXLp0qUOz/lPOzo7DuLfGAyGK7rfxYsXua+++qrdc1pbW7kLFy4E/L6jsQikm/zSQyaTcR999BHn8Xg4l8sl0J9kMhknk8kCPhvNX7Gc5Lg2PfB/4WhubuYUCgUnl8u5mpoatn7FcqajuWWxWNhv5XI50zOl7id1SI0RAK65udlPpnz00UecRqPhlEplQJnJcRz3008/cd9//z0nk8naPe/nn3/mPv/8c4GeIiXHAPjN4/Pnzwt+R+cZDAYuPDyc4ziO+/LLL7lPPvmk3TVyuXvF5R5Xorf8GkdnZLRGo+nw+y+//JL78MMPmU5mNpu57777jouLi+NUKhX32WefsfP5Mv+rr77iAHBms1kgv8RjRkcg2Wu1Wtv9W3y0trZySqWS0+v1nMFg6JT8MxgMnFqt9lt7jz32GBcTE8P16NGDq6io4Pbu3csdO3aM+8c//sHdf//93LRp07g777yTq6+v7/AeV4//suN3dHz9nzhaWloYGgoAxowZw7y5aWlpgrLG7Xmdfy1U0JVCbvm/F3u2u3XrBpVKFTA9oSNP+H9SpJ+eJVBZ09+rUYoaRTJsNhs0Gg2D3oqjXnxoeGdRVjT3+Ige/lg5nc4Oo+f8iFagOep0Ov3yu/kQ7eTkZPbMvxdi5bdsl8NF1Nn2SyPUv8Uz/VrPIZ434pLXfKSc1PmBPrucNGfiGLrc9+FHsw0GA4xGY7vVZy53jH9r2fifJHul+pQ/jtRcLhdkMpkg4hsfHx+Qb6SjedLenJD6P79JkQdLIZt/acqgeN9Wq9V+BSQu570CoTD+k0iCL2d8As2Vjs7/PZ7p926EuG8vnTg4ODhgX/3a7/DvkjG/ls4cGRmJd99994rTb6XkulwuD8iLeTn3kclkGDVqlCS3rNT7B3qWX2OMOtIjlEqloJqeRqORnIPEu/Vb82lJtd9q/V6pXCWC8M48t0qlQlNTEzIzM6HT6TBhwgTJuUQZFfx78MdBrAvR3ODvQU6nk80b4iCkZ7icuUGo087OP/GcJmRdSUkJ6urqmK39zTffMG7mq8f/zeOqM+oyD74javr06TAYDFAoFJg4cSITMnq9HnFxcZIC7KabbgqY7kQQcr5iSef+0nKt7W3kYoFDKQPiHHEpwS4WhHSvX9MgvhyjT2xwEHS5PdLr6OhoyGQySQXg13h2m80mSMmhjSwqKkrgxPF6vYK/O1K+AvWLGObK7xfxuIjPozEn4yguLg4DBgxgv+f3ITm96DOr1SqZqiaTyfwUEf7v/tPaf5MB95/UxIqS2PnJJ+0Xk+C25/Tht44cpR01vkzobAuUrtkRf5rJZPJzvNH/A/3210hR+zU4jn6LFmi9azQaBAcHC/a49shxxa29kuiXM1fo+eLj4zs8tzNBoPbkW6Axam9uXGn7dwdiOmrtve/lcLV1lF53Je1Ki2WkpKT8KvcPCgpCUVER7rnnHr/+4qfuyOXydoNNDQ0NfkVwpOaweK1IORA8Ho9AT/lva0qlEkFBQUzXCRSwvBI94HJ0tqCgINx5552C77RaLaKioiT7PTQ0lM1FsjE6Kyc7I1NIjkpxJkqdL8W1J5fL4fF4AtoKHV3z92hXIl8DyYDLkQ3tpWhzXJsuHhkZicTERIwYMQIKhQI6nY5VaJ8zZ05Ah55CoYDb7RZ8Foi2QTy/xDaTw+FgzyRlE1ksFiiVSsH64KcOX266eGRkpF/aq9vtxs8//wwAV51Q/yPHVWdUJ4/a2losWLAAQJtDaunSpbDZbFi0aBFkMhny8vKYQFGpVH5CPSMjA0qlElarFX379pUUUCSg+RFi/kK/nJaTk4OCggI/AdLZ36tUKklUi5h3yWAw+OWgy2SydqunXUnraAMJDg5mRqbYcafT6ZCRkRGQhPvXNADoOvzKeNSPycnJeOWVV1BbW8vOE/fx4sWL/QgMA43/5c6L6OjoTr+zTCZDSkoKUlNTUVhYKHm+Wq2GTqeDXC5Hly5doFQq0bVrV8E5RLb4SxF8v2dTq9WSSsZ/WkS4PUVIoVBcttOF49qM5I7QbA6HQ5J3pVevXgJFxGQywePxQK1Ws3fIycnBtGnTcObMGSQkJEClUjFkjLjCnVKpRGJi4i/qO7lcHnDuiZ1MSqWyXWWP4zrPy8N3uHGccJ0HBwdLRkd/qTEh7rtfa/51xvAM1G80R0lxlXoPftUc8fvyo7SXo/h3ZpxUKlWHz/1LxqC9ZjKZJMdIq9Wid+/enbrG7+HM/60c84HG50p5r/hOmV+zX35PlClfHoWHhzOkglqtRl5eHlJTU9G7d29mMEr9juP89Z+wsLBO809KIfba6+//lpaXl4eMjAxwXNseV1JSgr179wreUa/Xd2r+uVwuOJ3Oy96XqYgL/7OO9lr+Hu50OtnffJuD/rZarWzsO3IGBRpPcqLyg6ftOY6k+AL1ev1/HDdZZ6uR/97z2u12w2q1wmq1QqlUolu3bggJCZGs+sgfh0AINH6Qg4+2lWo098ROLPFvAjm1SPeX+q49NPmwYcME17TZbBg5ciRWr16N7OxsxMbG4ty5cwCAS5cu/TvN/qvH73hcdUZ14vjxxx9x5MgR5qm97rrrEBYWhhtvvBHDhw8XLLZ169YJ0q74ZNSBNh7+4jebzb9YmRKns3SGiNlkMjEFR5xWw/8/kRPSZ1qtlsFIf2vBHUjAiQnLZTKZZDRYLpdj5MiRgg2er2xfbr+3F+mn56BntlgsMBgMsNvtUKlUyMvLY33Ws2dPNjf0ej2D5VOLjY1tF9rbHmqD/x0h1sTzQer34si9Wq0WIOX4726xWJCQkACNRuNnuEZFRSE7O/tXnQftKd6/dbvStdkZ1B1duzMKcWee40oUK0LV8a8fSBmRur54fsnlcthsNsE6i4qKwqVLl1BRUcF+k5SU5IdCUKvVfo7Zy21Go1FA+kvNZDIFRIxcjuO0o9QqfoEHsQLW3tiKlfnOzrvLcVD/mggqseNTqj86iuJ35DxVKBQBjWPxmrlcZ59US0tLkyzr3t7YXU5TKpUIDw9HYWGh5PdSSFP+nPq/2gKNk3iMxXpKRwirfyca43JaSkoKevbsKUjPS0lJwbfffou9e/ciPz8fo0aNatfg72iOmEymy9o7NRqNQJ/5T5gP4mY0GiXXK/WTXq/H1q1bwXFtsiYlJYX1k9jp2l7f0rpt73nFv1cqlSzI3FlHjcFgYJXUxM+Vk5MjOFer1TId8pcgfyh4Q07QsLAwFtgSV3rm7x8Gg+G/soDCv9OpSvqOzWZj+qHdbhekPUr9Lj8/H4MGDWJ/S+1Hgd6L0vE4rq2yIj8Vnta41O8COb/ae85A88HhcAhQdaQvZmZmokePHvjxxx8BABcuXPh3mv1Xj9/5uOqM6uD44IMPAPzLQ1tdXQ2lUok1a9bgzjvvxMsvvyxYjEajURCF4qdlSS1QsRLVntFxJfw7arUaCxYs6PA8g8GAxsZG+Hw+mEwmmM1mhIeHC6DBgZrZbIZOp/tdNiMSYhTpMBqNgighRXLkcjl8Pp8fouf3VKZ69+7NNgp+xDYsLIyVBqb34DtxNBqNoPIYfSZlrKlUKvTr1w/BwcF+m4JUVNtqtfqNEx+pF4jnxmAwsNQjlUqFgoICJCQksD5NS0sTzE+NRgOFQiFAhv0ntd96HnRWybmcijsdPf8vfSfxOu/MM0iNbffu3ZmjR6fTISwsDMuXLxdUexk4cCCKioqg0+nYc0dERCA2NlbyPcTP8luPX1BQkGSqshSqsj1HcXh4uN+a8nq9V+xQ6Oi9LxeRSrKgM86u9lBmgVqgOUTyhH9eZ7gIpc4JCQm5IkdDZ9LxpPZmcaUjqX7iO5/tdrvkeBPHn1wuR3x8fKfGgNDVVzJ3/hMa33kbSH78FogvjUYjiebsbEqSuBmNxstGf+j1+k5fn4JXiYmJiI2NhcPhwNSpU3Hfffexc7KzswMi+H5tx5HVapXkU/tPajqdDnFxcRgyZIhgnGi9yGQyTJ8+3S+o9ltVNZVCk9O9xMhlSm8T/zYkJARKpZIFMuRyOUOqd3R/m812xY4pKXlFwdxAQajLucdvsX8HWlvtje/l7MNXGtxr73pGoxGjR48WOPo0Go0AlCDu29DQUFitVrhcLsl3DsS9J5PJkJaWhkGDBjE76pfIWqPRyBBb4vdUKpUdyiCDwQC9Xg+9Xo+CggLce++9LCXvKiLqf++46oxq5yB+p9dffx0A8Omnn7J8WrPZDJVKhV69ejFPr9SCM5lMAuWRv0H9EkFADoJfKvD5AsNgMKB///5McPl8Pni9Xr/0NikBLpPJrpjv5LeI9BIBe+/evSWdMnFxcQEj0pfb+EY2v5GhIRWB1Gg0SE1NhU6nQ2ZmJmQyGQYOHCh4VrGRy3ciiTcoh8PB+HjE40KfeTweSYNOq9Vi9uzZks/J/4zmhcPhYEZpZGSkn5HqcDgwcODA/xio9pXOS3Ek8Ndu0dHRyM3N9fv8ShxRv0Xj38dkMsHlckk+a+/evZlhyVe26d+QkBBcuHABWVlZcLvdbE4S6S5/XhuNxoAGal1dnYAnRepZApF1BmqBHCydMfgDjYNWqxXcVxxxVCqVfs6YQNeRepeOfvdrBQUuh0Q+kKOIf574ucxms2Av/L1RjlLGotQ7azQaKJXKK0417sw+Hxoa2iHiqr1x7ays/T1kcnv3+C2QCL9mEIxQob9UJzGZTJLvunbt2g5/xy/+kZ2djUuXLmHMmDGoq6vDqVOnBMGjtLQ0PxlxpfNUJpP9V6BbAq0ntVqN3r17s32IL1tiY2OZbpWTkyPYY/g6V0JCAurr69tds4Qc6ug5Q0JCLivNle7Jn3v8sVSr1X7oL61WK3ASilOupJpUpkR7ROh8OanX6y8bpd/RuP2a8yJQMIZ0184UxZC6biDHeXvvG8jOoz3G6XQiPj4eSUlJyMjIYM8mk8n89kL+fKZzQkNDBXNBjJbjuDb9fODAgYIxt9lsfoAJvo0nlSJI/yebkJ6/vX4jrtyIiAhMmDBB0J9arRZ9+/bFd999h+rqavTs2RPNzc0AhLzMV4//neOqM6qd45NPPkH//v3hcDjw+uuv44YbboBcLkdqaqogohKI/4Hj2hQKjUaDpKQkwSbjcrkEZITJycnsO4vFgrS0tA6FpJQyzW86nY4JNTFBsBSiiJ5rxYoV0Ol0CA0N7dCQ5xtI4nScy20dGdn8PqaUDbVajW3btmHmzJmSz0bRUKkIwq+lGPNh2UQkSO9is9lQUVHB+po2cpvNBqPRCJPJhOjoaFRVVfltXFqt1m9Tai9Huz0lgaJrhGySOkd8bblc7ueAmD17NnuXX9J/Tqfzin8faK0F6pv2Knz8O0nUf617/1rpJ6SUuFwuP2OsvWfdtGkTDh48iNzcXKjVaoYA4JN36/V6mM1mJCYmQq1WszGkNDxS8NtDZ91///1+VRylzu2s00ZqTvF5OPito5Q2sUIn9X17zyMl+34No/i3aBaLBatWrRJA/ikdkuYj7V/0zrQGpQoZREZGCvbDjsZX6jrU7Hb7LyLs1ul0fuupqqpK0lHWGU42cmSJ51lH7yfVxCnl4eHhzFitqqr6RSmtVqtVsk//3altUvqEXO5f5UlqT+us460jveNK5LRKpbrsoIHRaPRzJF1//fX4/vvvUV1dDafTKYnKEzu2k5OTkZiYyMaOP3eVSmWnHBb/zvZrOMT4gTm5XI6kpCRBIMPn87G+tlqtzMnDz2SQy+WorKxkc4Q+F+tZVMRIat4EWtOEjJKSh/T+KpWKVV3mOA7V1dXo0qWL317SWT4w8X34f/PTyfnn6PV65ohxOBwwGo0oKCi4bLnwWwf2+M9sMpkkHTNih05nm1wuR2Ji4hUhtgP1k8vlgtfrRX5+PjIzMxnKSIqrtzNyJBA/lF6vx+bNm5nNajAY2LwsKyuD0+lEVFSU37gvWrSIzQmxszvQfNNqtYwbmd/nKSkpyMzMFPQXySS73Y7U1FRGgXPVEfW/e1x1RnVwfPbZZ+jXrx/MZjP69OnDqubxI//iBWuxWBh8Ubyx0sZntVr9hExRURHCwsI6LI8ZqPw0x3FITU31q+Sn1WoF1Q74Qo485vwc+OLiYixZsoRdMyIiAi6Xy487RqryypUK/I4Er0wmg8ViYSl4VGEiJiYGmZmZCAsLQ2ZmpqSBoNVq/dAKv0UjgnC32434+HgW4ejTp4/gvciZI5fLkZmZCZvNxjY8iuDQuaGhoVi2bFlAhTgqKsqvmmB6eroA2aFWq6HValmli44QAZ1VvvnRXz431m/Zx7+kBUJv/B7tlxjIpKD81qgGuVwOo9GIqqqqgGtFp9P5OWxmzpyJ06dPIz09HSaTCevXr2ckzFqtFuHh4bBYLJDJZBg0aBBqa2sFSnhQUJAf4on/PTnE586diyNHjiAnJwd6vR5arRZGo1HSYFUoFH6GG7//pHjM3G43zpw5I5BzVGFIykDiO2L45/ODDOTc6Ch97pc4ndqbFx0psmRYic/rSMlOTEzEsGHD2Lnr1q0TOOzEDgOXywWz2czQXnR9MuTUarXA0R2ouVwu2O12mM1mSVJaj8fzi7iwaJ6KU6T5c6mjPhVXGSK0DSGo+f1C6dfi/hYbMVJR+cTERPa7+fPno7Gx8Yrl24033ohevXpdcb9dbpNaT2JkGCFBxOclJCRAqVT66UFSVYGjoqL8+qSoqMivv/Py8jp0GF9Oa89YJyeI+F4xMTEYP3683zvExcUhKSmJyV2bzeanJ+Tn5wvSEC0WS8B00kAcgPw+5K/P9t6zo4IPv1aTmtdUBZlPB0DPw5eJJpMJcrkcubm5gvRK2pvElcH49yMORPosJiZG8vnEDj/+d0qlUkA8rtVqoVKp4PV6/caC3kelUrE5fvDgQcE46HQ6gQ1CzyaTtaV9BULqdyRbxc5sCrJrNBqMHDkSJSUlbK+WClR2BiX0ezSFQoEBAwYgLCzsiveCjuRxoMZHC3XUH+3tufR/q9WKBx988IqLGCkUClitVkRGRuLAgQNsfRsMBkRHR6OgoAAej8dvnbtcLixZsiTgs/NtSmorV65ERUWFpKOT5izphSqVCm63G9HR0Ywb6mpq3v/2cdUZ1Ynj008/RW1tLfR6PU6ePInDhw/D7XYzbzN/4UVGRvp5qfmRervdjj179mDp0qWC36anp8Nms6GoqKhDgSfewPjXoah0Z7hooqOj0aNHD4wbNw4KhQLh4eGoqqpCZWUlzp49yyDjI0aMkORb4DgO1157bcCUlstVSAhGK+V5l8vl6N+/P8xmM+rq6gROD6qKRDnQer3+iksPd1aZVyqVsNlsTIjzlRaOa1OYs7Ky/DYdtVqN7OxsJCQkICMjg6XOdfQcUuckJSWB4zhBmqhCoRAo6VVVVX6GN/UNIcdog+LPK3HqKb/cq1arFUQHFQoFsrKyUFRU9G9FGnW2qVQqv4qV1PjvJZUK+UvmkEqlknScuN3udpV+ilB2RqELdE6gSKhUa2/dxsXFYceOHYJ3pagpGUCkmA8dOhTPPfccnE4nXC4XVCoVEhMTcc011wiuWV5ejlOnTqG2ttbvfkSc361bNyiVSmRnZ6OgoECAuqqvr/fr/444C8TpfATFT0pKQnp6usDR0V6Em59W4/P5/PgpyBFhtVqZXOMbzWID2mg0XjaC75cq+r80XdxsNgeUt/xxCgsLY88qrlyoUCgYcrO996OxHTZsGK677rqAz26z2dpFivKbVquV3C87k5aRm5sbcP+jdAT+HKJ5xj9Po9F0iCjmPwtVqOQ/i1Rlo47GlS/fZsyY8YvmEMf5G7OXO+8CIWIorZXj2uSB1WrFzTff3Kn0a7vdLomSEKcqabValibDrzp7uU08jgaDwc8pxH9vPmcbfS6TyZCTk8MCk0qlkhEWU4VR/jX4a4x/n84Q7XcmwPGfuKcTUomciD6fD/3790d8fLzAMUQyhnREvizX6/Xo3r07nnzySUkZGhwcDIVCgaCgIEn5YDKZJJG6Pp9PMJfFa16cmt4eqqpPnz5YsWKFAM1GzxqoSI/BYJBEIimVSkkHPmU1OBwOxgPKb3FxcdDr9SxoGuiZab7/VmN+OVkXtPfz9Vapc9r7faB51959xcEG2q/EVQ61Wq3AhikoKMCqVavYO6pUKqa3d7S/8/cZjhPKYZlMhm7duqGgoAA33XQTu7/H40GfPn1YcP/WW2/Fxo0bA651+py/DsLCwgT6Du3her3ez37wer3o1q0bamtr0djYiL59+2LHjh0MCXXx4sV/s5V/9fh3H1edUaJDCibY0tKCTz75BMXFxbBarWhsbERCQgLMZrPkhiAWyKSwkwKk1WoFERaXy4Wqqip069ZNoKC3JxhUKhUsFovkOQqFAhEREQE5OAiWSdFao9GItWvXorS0FC6XC/n5+cww7NOnD3OwSeWat9cCGRbtbVjkJNDr9QJFwmAwsBzkadOmoaKigilwfMSLwWBAUFAQ4uLiBPfnO1JIAF/uZihuY8eOZXnbXbt2lRwnfvSIxkOhUGD+/Pl4+OGH0bVr107166BBg/yiPB6PR7DZ8d+XD/cn6Df/nW02GzIyMpghxU8nMRqNsFgssNvtCA4OZoiq7OxsARkoXau2thY+nw9yufxXqzTFv4dCobjs1Lz2WnvcApfTpFJ6OuIkoOiq2JigOdyRMpeamuqHLOpsGz58eLuIJ/Fn/D7n8/tw3L+qsrhcLoaq7NGjB1sHcrkc3bt3x5tvvsn6iFL3NBqNAImpVquRlZXlV/yB5rFSqUR5ebmfw0MmkzEHoUqlEowpv9JLZGQkm/PLli0LqFBGRERg1qxZSE9PR7du3fy+lzJqqdE6by+C2pkobaA0wY7ar8n10pEskslkcDqdDHEQaA3q9Xq4XC4/Y5nOv1znibi1d/7lBEKk5Et0dDQ0Go1AsSekAv/atC74SGlKm6K1LF7ToaGhMBqNgucnpB9//igUCkyfPt1vPAL1W3ucgp1tdP/OjIVGo/FzKPK/F1cUvpyx4COZIyMj2f5C+lNeXl6HJcnbm9dBQUF+TkSVSiUw1jMzMzFixIhOP7tOp0P37t0Fn7XHPUfoJqm56nQ6MXjwYMyZM8fv+TtCLf47WiBy8yuZh1J7EY099ZdOp2N6XkREBEpLS3Hy5En07t3bTwbLZDLccsstWLhwIfuM9KN+/fr5OR9pDoi5DOld6HOHw4EuXbqwc7p06YLu3buzwBH/PfhpgxqNBnq9njmppBz5RqMRt99+OyvoYTAYkJqaiuDgYMbTyXEcQ7xL9SGlZJFjoL29ie9UEOuOHNeGtONTXqjV6oC6TqB5yr/+lQRQrkTXI3kt7uOOrtXe91KOf34jpyfH/UuepaenY9y4cSxYLkaBNzY2+iEm1Wq1YMwIVSQ1dnwZwL+2yWRCUVERCgoKsH//ftxwww2YO3cu+vTpA4PBwIJfCoUCQ4cODejwIyclf04rFAq4XC4W+KP3pvUxY8YM9h3dR6/XIy0tTZCaR6TlV4//7eOqM4p38B1RL7zwAp5//nmcPHkSL730EiZOnIgePXqgtrYWKpUKVqsV1dXVDC7bv39/SeJIvkFdV1cHo9EoMGKLi4sxceJExg8UiHxSiieB0s84TroyUHV1NcxmM4xGIxPGer0eVquVbYgc12ZIxcbGIikpCdXV1Wzjuuaaa9g5FosFERER7UK8f81mNpuZoalQKJCbmwufz4eQkBCEhIQgOTkZZrMZTU1NAicPv9/FGyvHccjIyGCVi35paXNy8mRmZuKWW25hAlmsHJIxIh5Di8WCgoIC9OvXj0VwUlJSJCPGNI90Op3fRi6TyZCYmCgweqQQdvQZKUF8h6hM1sbdIjacDAYDU2qio6NhNpv9nIxSioVKpWqX3ydQ42++gcrJ/hI4OJ8rrb1zr3Se840zvqIqbmTIi9+dnH/0mRRxMr+K4S95Po77Fy8ZoS3IWSTmCaBn5l9nwoQJSEtLg8PhgMvlwm233YZ9+/Yx3gCtVousrCx06dJF4LRQKBTo1asXBg8eLDl2/MgvGen88+haISEhfigDfnlrcRRXoVAgMTERiYmJAecMvSOhWMX9J4Vs0el0TDEXp0iLC1iIryM2vH7rdIYrcVoROo3/jFQRkM9rIn52QrSIjSV+//H7WHweBXEC9UlnjRNC/dLfUugAanz5Q0o+/7kiIiKYcz7QuBHCQAoJpVAoMHLkSMTFxflVuxLLHJVKxVA14nXLR2kS4pD/LHw0zu+1ZwdyPOh0OgFPXEctKipKsGaDgoKQmZmJhIQEuN1uQQoVpQx1NBf4nJwdzRXxeAZqgdaS1P5stVr9KBL43/PlGc37n3/+GbfcckuHz0rtco11KfT+L2liVM0vSSvX6XQCuV9TU+Ont4SHh2PDhg1ISkpCdHQ0Zs6cieDgYMTFxaGuro71j8lkwuDBg/Hyyy8LEP7i/jIajQFTG3U6HVJTU1k/ifUkWmN8OSgec+pnQjWKq5Cp1WpER0dDqVQyNBytHSnbQKPRYNmyZQgJCZEcS/69i4uLkZKS0uGYyGQy5ObmMkcv6dEkM7VarcCx0x5a3OVyobi42O/zK6HyIKL+3wKlx9c7FAqFH+JSvM71ej1DzfHRjHxUM8nrCRMmoHv37khISEBCQgIcDgd27drlpxPw9UH+ONM8k+KTo0A03V/MXcwPUjz00EPsWtOmTQvYj51JR+T/Njk5GRUVFX57zKhRo6DVarFs2TKGAuvVqxcmTJiAhQsXMkcUkZZfPa4eV51R///ge2cXLFiAqKgohIaGMmFcXFyM8PBwvPHGGyxCrtPpGEfI2bNnJQUvncdxbUiWbt26CZwTzz//PI4cOYJ7771XUpnvDOGpmKOCri2TtZXyFAux/Px8+Hw+KBQKeL1ezJo1CytWrMC0adOYgI2IiEBJSQk0Gg2L9FqtVkyYMKHDai3i9+jSpUu7xNlkAPKNXYPBALfbjaKiIgQHB6Ourg61tbVwuVwoKChgqAgS6uTo4W8OHMcFRI8FikgGasRNQ5sMITbonuJrTZ48mZGSUwSBNilSiFQqFZKTkwXP6nA4EB8f72cw0/lOpxNHjhwRbAx8R6TH40FGRobfJkobuVQqHc0zcqzyNzm5XA6n04m0tDRcd911CAoKEvCPtVcBa9y4cZ3u347mUEctNDQUwcHB6NKly29C+ny5DjBxCpj4e7vd3i6nEb1DUFDQZStgdrsd3377rR+ng9Q85T+/SqVCeHg4srOzJZVomsvi59XpdIiMjITRaMTbb7+Nv/zlL8jKymK/i4qKwiOPPMIUFkIvDhw4ECNHjhTcx+l0CvgI6L5GoxGxsbGsL2iuRkREwGQyMWcJzWO6Hl1HrVYz5JRMJvNTiOlvlUoFu93O5IqYkLO9Rs9mNBo7hZTSaDQBucT4KW3ttfaeTafTSToi+LxW1MQGTaDGd+CTPKqvrxcU3KD9TaPRQKPRICMjgyELysvLsX79eowaNapThhHfiUR7Mf89aKy9Xi+2bNniJ9cVCgUmTZokQNzxI9fidcO/F//5xPeVel4+2iksLIztk/zrKhQKFBcXC2SUlDNUPK/MZjMSEhJgtVpZaig/rVVKDgcaT3EkvbOtI7kaSE6Rc0xKhgR6Vj4Kxul04syZM7jhhhug0+lgsVjaRScESs/s6L58ZIJarQ54nStZlxqNBpMnT2Z7ckJCAltzVVVVmDhxIkpKSmAymZiu9MorrzDdriO+To7jUFhY6GcM8+8/ffr0gPOO2pUim6/EmdWeY5xffIdaYmKiH/p1/PjxjEPL6XRiypQpqKysZEitoKAgVtWOECkymQxr167FkiVLMHDgQHY9h8MhcERkZmYKdCuZTIauXbtKzlXxu9jtdsTExLDP+UG0QGtPp9PB6/VixIgRzEFJ8pYQgeLfeL1exMXFQa1Ws6wCcqCL54Db7cb+/fsZUjjQmGg0GoFjRSwL+c8vDlKI+4Dm7S91Ikm9D78Rn+yVXp94x8TvIg5Y898xMTER5eXl4Lh/kXeHhIQIruNwOLBhwwaWReF2u9G3b1+oVCro9Xr07NnTr8847l9BDxo3/tinp6ez5+D3q1KpZEjeqKgo7NixA9OnT4dC0UaW37dvX0RGRrL0QOqvuLg4wTP7fD706NFDck1TAI2ffk62JqGkaK7n5eWhsbERBw4cgM1mQ15eHl5//XXmgLrKEXX14B9XnVEQOqKWLl2KkJAQnDp1Co8//rhgk1m3bh127twpqJZGBkVqaiqDUUpxApBgEisVoaGhfhw8HCdUPnQ6nWQ0XrwxhIeHs02Mb2DylWGTyQS9Xo+KigokJydDo9EgPz8fUVFRjGj3zTffxLRp0xAWFgaj0SjYvMRGtpTAEkdLtFotKisrO8XxQNcNDg5mJO/FxcUYNWoU+vTpA5VKxSDa4k3C7XYLNiyn09mu0n25lf88Hg9yc3PBcRyL+JtMJmZ88ZFGbrdbAPeWyf5VhYJfsp36z+Vysc1BqVTC6/UK5k5cXBwOHTqE+Ph4pgBIKTgdpb6Eh4cLFCxKz+PfKzs7GxEREX4pGFKILZvNJjAYxf3b2ejxlTSp59FoNJJIlLKysl98v4SEhHYJ2gMZqeJ5xv9bnD7JbzSmpBDxf0dpvz169JD8bSD0B11D6lk9Hg/effdd7Ny5k5HT6/V65Ofnw2w2w2AwQKVSsbQGjUaDmpoaFuEtLS3F0aNH0dLSgnPnzmHq1KnsXh6Ph8ksQliq1WpYLBaBwieT/Su9wev1orCwEBERERgxYgTS09MZcosQEgaDASdOnGBk2hzXli6o0+mQnp4OjvuXccqPrK5fvx5er5cpUVOnThVEfK1WK+RyuSRXnlTlN5LXFosFmZmZUKlUGDJkSKfnltR4BFLAA603qecRr7UrKTVOzzJp0iS/Knl8pAo1g8GABQsWYNCgQfD5fBgzZgwSEhJgs9nQtWtXvPTSS2hsbBQ8YyBZLXYsOZ1Ov/VdX1+PxMREZGRkIC8vDyqVChMnTkR0dLRfGjf/3fjVggIZe8HBwcwhaTKZGBeLy+WSlGEymUxQXYucnOJS2kRaLl7/er0eBQUFfs86fPhwHD58GHl5eWx/qKysFPRPXl5ehwUkyOFCfa9QKFBYWOj3DlK/7d+/f0CiZ5VKhaysLEa8LB5L2qsSExMDzsHk5GTB72hcLBYLiouLkZeXh9tuu00SvSJ+5uzsbMn5pFQqMXPmTL80afq/WHeRWpdXmh5qMBjgdDqZzPZ6vZg2bRpSUlLQt29fDB48GMnJyVCr1TCbzQLUg5QOeDn3bm99X0nAo732S5F4hMTmOA6TJk0SOEUsFgvrF6omSZUL5XI57HY78vPzmT74+eef+1EoDBkyBADwwQcf4IcffmDoM+KhovXl8XigVCoF8kYmk2HYsGEM9aTX6zFw4EABIpfOLS8vZ88qTrnio5f4OpxGo0F8fLzAGUBOWUJHiXUqg8GA0NBQ3HXXXdDr9bjuuuswePBgP5lD9zCZTPB4PGxvo3lD+67ZbEZYWBiioqJQW1sLr9fbqbn1a6aKi/vyP6UFWidEUs+3Qej59Xo9PvroI2RnZwsKBHg8HixatEgSJUX/l0KeEScZP/jFn0d5eXnIyMjAyJEjkZWVxSql0p5Dv9NoNIiNjYVMJkNMTAwyMjIgl7dVaQ1k83Fcm50jdroplUrk5+dj586dyMvLQ1BQEKKiopCfn4+HHnoIBw8exLBhw646oK4eAY//aWfUvn37cO7cOfb3u+++i9raWjz88MNYtWoVI4jmC/0ePXpAqVQiLS0NmZmZrKJHZ6Cn/KgVcSBdrtCj1q1bNz9FnRRqvhITHR3NFGiCcjqdTmRkZODcuXN4++23sX79evTo0QNutxvvv/8+/vSnPzFEAxmkUpFXKYQU/178z/m8OGI0gBRSZ8eOHViwYAHjiSosLIRCoUBcXBzS0tKgVCoFRqyYh0sMazWbzQgPDxdsmOJIe2eawWBAZGQk8vLyWNpa165d4Xa74fP5MGrUKJaexc/Hnj17NtsAKLLLf46ePXuiT58+gufhI1uCg4OxYsUK1r+0uZBR5XA42Hw1m82or6+XRAmJ31dcFUOlUsHhcMBmswmMlPb6SaoalHjsA33emTVDzrzOKsxEEMo/X6PRSM7hzpIcU5s7d26730+ePFnyfTurqInXhtVqZU42caqLXN45ji66d3vpUjJZGxH47bffjhEjRiAhIQFRUVEIDg5GYWEh0tPTYbfbUVZWhri4OOYUXrp0KZM7CQkJqKmpwYMPPgigTdmnVC66F6Xe8Z3p4jEgJwxFK/Pz89GzZ09oNBrMmjULDoeDGSx2ux0333wzQ4CS0r5jxw506dKFIbT4CCmLxYLFixcjLS2Npb2K+b9UKhVLDaB5IlWBjz8WoaGhmDlzJntfq9Xa6TLqBoNBMtW6sy2QAXg560b8PnRNKrLAR5kG4jYjR11KSgoGDRqEyspKuN1uOBwOPPzwwwgODkZJSQlWr14tQD4RGiVQaotCoWDIBj4prVKpREFBAbZt2yaoekgOUvpdXl6eX+Sc0BL8+UGOEjICysvLmQNOq9UyB6tMJmPXE/c9n0eN49rQAzt37vR7J+pnqTHj710U2e6I65Cu2Z7DUYxs+yWpVNT0ej3rA4r+d/SMNHbi75KSklhfKRQK9O7dGzt37oTX60VsbCy+/vpr7Nixw484V3wfhUKBRYsW+X1O8lKMuKN511kC5kDptRkZGYJ5FhERwf5WKBQ4fPgwPvvsMxa4NJvNCAkJQX5+PioqKlBVVSVIsaf3EwevAjVKMxLP9fbS02jc2rvu5aTE/tL5FBMTg5SUFISGhuL999/Hhg0bWOBLpVKhrKwMhw4dwvXXX88CRGlpaUzuEhKPUvYoKEFNo9Fg165dGDhwIJ555hn88MMP2LhxI1sTJSUliI2Nhc1mQ3BwMEthp9+7XC5UVlayfiVqBYVCIek8kMna0i7j4uL8ZDztffwgYUxMDOOUslqtsNvtzBG/ZcsWbNy4EZGRkQLkpVarRZ8+faDX69GtWzfGsUaODgr+cFxbAIGfFkYyUqFQCLI27rzzTowdO/ay58GVzAE+F6lUyrfU9Turu1/O/tceejwQopZ+R2mqKpVK4AiMj4/HvHnzJDnqAt1PKiVRXEGT49r24V69erHgZEhICNavX4+HHnqIzQ+tVsv0JXGBlOuvv549lzgoKLXfqFQqpKSk4Ntvv2XziVB5Q4cOxWuvvYaLFy/i3nvvFdDDPPXUUwz0cdUhdfWQOv5nnVHr16/HkCFDBDxRX375JW677TbMnDmTkZPTpsgX3KWlpSgoKEB2drYgNU9KOIaFhfkZoqWlpZg1a5YklFoc0Q4k2KUqztFv+NBYcuTQZltYWIgdO3bgwoULOH/+PC5evIiVK1eydwwNDUX//v39jF6v1yswlKk/xOgoKS4c8UZSX18v8Lw7HA7G/RAUFITc3Fz89NNP+OGHH3DDDTcwIex0Olmf5eXlCVLcxAJTvLFEREQIxoGcMIGMAY5ri0BIkUv6fD7k5ORg2rRpMBgM6Nu3L6qrq+H1eqHX6xETE8MEO5+Ylq8gyuVygXFL0WT+ZkGOJnp/PlkzvVt8fDwqKyuxYsUKAWJDoVAI5pcUIoZIKMVQ6sjISJYCOWLECIHiL1UqWy6XC9J0OtM6q0hI5crzW2fSWMXP2tlnCVRBsj3nGzlXiNhe/F2g57BYLKxvxdcOhHKReg+xvOBHdvm/DUQi6na7kZKSguzsbISGhsLn8yEhIQGPP/445s+fD5PJBIfDgaVLlyIrKwujRo3Ck08+iRtvvBF6vR5xcXHIy8vDs88+i927d2PMmDEscuf1eiGXy+F2uxnqUcohSX/HxsYKDGuj0Yjhw4f78UgplUpGqG61WtGlSxfY7XaMGDFCYBxYrVaYzWa2psLDwzFkyBAYjUZBv7WH6JOSu3wnIZ+3KtA8ovlMBgDH+XOkBGpS6bu/1nqjc8TVqEpLS6HRaBAUFASz2SyYoySHwsLCBBFX+i29Z58+fXDhwgXEx8dDq9UiPz8fQ4cOBce1VRLiy5hAz6bX65lThoJAdD+xHFAqlVi0aBFWrVrFUEz89GN+46MaaA3yq5zynTy0Lui3DodDEO2mz3v16iVwysjl8nZRS2Intkqlwt69ewW/j4yM7NDQo3T1zoy1uC8CpcFIySN+X4rnuxQPGKFO+PcQp05yXFv1V6oGvGzZMuaw3L17N6Kjo/HXv/4VQ4cOFdwzkEOeriFVHY+qh/HRcZT6Z7VaO0RxE2Kc3zfE+UP973Q6MXr0aCiVSmRmZqKkpAQlJSWYP38+rr/+ephMJkyePBm7du1CXFwcYmNj8eyzzzKya7HcJh2hozmQkZHBgjj8MZTatwjJcaVOJKlgDq3/K0W20DwJDw/H/v37YTQaMXToUNhsNmzatAkTJ07E3XffjenTpzMDe8OGDTh58iRMJhNDF2VnZ6OkpIQVDOAXedHpdMjMzMTo0aPxwgsv4IcffsDq1aths9lYUJNQmK+88gqWL18uSOOUyWRYvHgxVq5ciZiYGKYnarVahiLmp9iFhIRAqVSisrLSb306HA6cO3cOTz75JJtHfJoEu93O7knf8QOdfBnE32sIgT916lRs27aNBV3Ea3vlypVYtWoVq9xIacSJiYksCMxx7ZPx89+Fnps/FzqaD/zvpJBC4s/Ec5bSNPkySMxJyZdH1KKjo/3mcEfOMGq097ndbsZtSL/jO3aI9ys4OBhutxvTp08XXENK7naU4UB95na72T137NiBqqoqVg1YrVazuUO/GTVqlN91FAqFYD9Vq9UCuSiWDSkpKczupZT/cePGISkpCSEhIejTpw8GDBiAoKAgyGQyDBgw4CpJ+dWjw+N/1hkF/MtD+8wzz+Drr79GS0sL7r33XoSHh6O+vh719fWYMWMGI/nlQ11JWSGHBgkiqei5WLDRxhRoI6bvxFxQgcpn6/V65syhz4xGI0NUmEwmdOnShXnHly9fjpaWFjQ3N2PBggWS+fkcx/mVh6VNsD0B2ZFQ5TiOcXHxI9MymQzl5eUoKCiAxWKB1+vFc889h7179wqUGzIqSBkWV6DoTBMr4oHSDanfhw4dyqJr9Ay7du1iENc5c+YgISEBPp+PpfdwXFtqncViQVJSkp9DxePx4Pz585KKye233w6DwQC9Xo/4+HiUlJQwJXfChAlYunQpOz8zMxOZmZkYNmwY4uPjERoaiqKiIsEGy48Mio14uqfNZmMVxGQyGUO/BAUFCdAlM2bM+FUh/fRM/DRDqbFISUmRNDrba5eLerqcOWSxWAT5/uJxJKOb1mJnrknpqYG+j4iIEMgg8fdipSYQ8ozWemhoKI4dOyao0mIymfDHP/4RLS0tGDp0KAYNGoTJkyfjjTfewIsvvohx48ZhyJAh2LJlC6smNHXqVJw5cwYLFy6EXq9HaWkplixZAoPBwNYIjbPT6WTzi+PaZFdKSgpMJhMz3snZqtPpYDabWWWtiIgI5OfnY9GiRcxgo3d0uVzMaTtjxgyMHTsWH3/8MWw2GwwGA5KTkzF//nz8/e9/x0MPPYSEhARB1TN+302ePBkxMTECg4Dj2pRUImznyxF+2WaVSoVHHnmkw7lHTp3k5GRBpaZAY3u5TTzu9Dz0noGIesXry263Q6fTwWaz+SEtCYpPY0BcdTTHyCD2er04f/48Lly4gNmzZ7O1otVqkZub65d6J+4Lm80GvV4Pk8nEeBrVajWSk5NZOimdb7PZYLfbUVxcjNdeew3r168X9IlSqWTGBs0hfloQ7bFqtVrgLOSvc0K98T9PTExkqCmOa0NPuFwuls6t0WhQWVkpibypqKjwq6KoVCpx7Ngx3H///XA6nWyuip2hUrKY9n16T6PRiJqaGsE5ZWVlfogRnU7nx2FCfcK/T3BwMHr27CnpGBFX4hIbjdTfhAjiGz38McrKysL777+P+Ph4yGRthPlerxd1dXUoLCwMSGwvDgDo9XqG8KT55Ha7BWjbQE44MsSkuGj4+hI/MEfX4sv88PBwtLa24tFHH0Vqaiq0Wi0yMzORkpKC6Oho/PDDD/j666+RmJgIl8vl51Cg+Xg5+5lMJkNCQkKHxUYCofsup0mR+V9pylZsbKyAF0qj0WDEiBHQarU4cOAA/vznPyMoKAgOh4PJHUJCbdu2DVu2bGFjK953wsPDGXk4x7Wl3Xfp0gUjRozACy+8gB9//BEtLS0YMGCAIP20srISpaWlbA3Ss1VXVzPnEh95TY4/ft/QGqAKZvy5ERYWhpdfftmPSoDfD6WlpbDb7YiIiGBBWL7jg4/KIvQxx3GM1DohIQFKpZI5CPj3SU1NRX19PRobG5lM4OthfNR9e3JHav10FmnYmWsFKghDASDxXBdXTHa5XJJrffjw4ZLrpzPPlZiYyCpP02eEkKqurhY45xQKBcaOHcuc3tQ6g/QSB0b4/U/6MyGQ9Xo93G43dDodZs+eLQi22O12TJw4UVI/4O+74sAYn5aG/+5UVV6r1eLBBx9kqEaqKrlmzRqcP38eALBu3TqsWLHi32nyXz3+g4//SWfUhQsX2P+ffPJJREREYOnSpXjnnXdwxx13ICQkBDabjUVo+KXJ+ZsZf0FTxN9sNgvKQfONbLFxQ43viW5P0BMiQApJUFpaCpfLhcbGRgZB3717N3r37g25vK2865133okFCxZAoVBgxYoVeOSRR+D1ehEUFIQTJ074VRJKSkqShNKLI270b3sQVnF/0Of0nc1mg9lsxuTJkxkRp8vlwsKFC1FUVCSIVMbFxbHf8Z+P+l98/86kg4mVfD7KxGQyYcSIEWyDr6mpgcvlgtFoRHx8PIqLi1nfRUdHM6VFq9Xi7rvvxquvvioZnTUajQL4NL2PwWBgTkR6H6VSib1796K1tRXvv/8+unbtCovFAoVCgczMTPh8PjgcDixYsACXLl3Cd9995wcJJ76flJQU1v8ExSWHK19pb6+/FAqFZBl62pS1Wm2nU5T480ir1QbkxDEYDAHRBXwEFTkIxfOD+oA/X/hz/nI5xCiSSEqQlPHKcW0KZyBHcqB+ED87P22qs40c5fyUOGo2m42lvXz00UcIDw9nabCtra24ePEioqKiMHXqVFx33XWIjY1lPGgLFizAm2++ibi4OISFhSE7OxvTpk3D22+/jQULFjDEXVRUFHw+H06dOsWUZ1rXHNfm7M7KysLgwYOxaNEiRjpLRndMTAwUCgXmzJkjqO4TFhaG/Px81tcejwdGoxHp6elsHQ8bNgybNm1ia3HOnDloaWnBTz/9hIsXLzIFVCaT+cHT7XY7CgoK/DhsaBz4ewJ/THr27MnSr8Up1FIpUXTOlaRKdSTP+N+T/CM5Q+XC6X3E1+IjaoODg2EymZCTk8MqBpIjpk+fPpg6dSpbU2azmVWDlMvlKC8vZ8UyvvrqK9x7772IjIzEgQMHmDNSq9XikUcewfPPP4/MzEzB8xLJK/UzOYg4jmPPlZKSgnHjxsFms8FoNAoKLFBggN+/5OTPyspCbGyswCHD36fkcjlmzJjB0Hl0TZVKhbCwMJY6Rn03cOBAhoClNRYVFYVDhw7hxhtvZLxp5PiSIpKmucg3At944w3U1NQgNzdXEDzg6xhSjeanuHpre87sy2mEKCDHHMlOvgyleWIwGJgjXaVSYdGiRUwWEJKa9jzqu5kzZyI/P19Q4bW4uBher1fAGSReT8TTRu+tVqvh9XoFlXkjIyORnp6OhoYGhIeHQ6vVor6+HmvWrGkXHRZof6C0Yf5n/DmXmZmJxx57DAcPHhScFxMTg4sXL6K1tRUtLS1YsWKF4B7kABY7dsROwPZkQVRUlOQ7id+lo6I0v0QWSZ0nLq5C8sPlcmHLli1+3DvBwcE4fPgw23NlsjZqA7fbjYyMDJhMJmRlZWH37t2YPHkyG3vSo2icZDIZCgoKGMdgVlYWsrOzMXz4cLzwwgtoaWnBnDlzJMc6Pj5eUO1WLpdLIkL570tZBfzPaV9Rq9VISUlBfn4+63+6dkpKCnr27Mn0HYVCgfLycqSnpwvQvnl5eUym8FPDiQeU1phMJkN+fr6Ag8tisbAMBblcjuLiYixevBgcxwl0N77NIzWeHRU2IO6+K51f1GbPno1+/fr5fR5IlonlrHiOK5VK2Gw2REdHSwbjyckY6Hn47yROq/Z4PMjLy0N9fT2TlSaTCVqtltkCUqmxJSUlTA+yWCws3ZL6mRC7hP7muDY9tGvXruxZIyMjkZGRwdBR4iwJkonid7BYLOjatatkMZN+/fph5syZgs+0Wi1SU1Oh1+vZ2r3rrrvYnCoqKmKZR9u2bYNer8fdd9/97zL7rx7/4cf/pDOKDloY11xzDXQ6Hbp27Yr+/fuztAP+wiPFig/fFwsumUyGsWPHoqioCC6XSyDgDAaDACYs1cSlXvnXdjgcyMnJ8eMaslgsWLJkCfusqakJN9xwA+x2Oz7//HMcPXoUdXV1KCsrQ3x8PGJiYrBmzRpwHIdFixaha9euGD9+PO677752hS1fgHekuAQS4HQ9t9uNgQMHomvXrgwFodVqceLECXzzzTdITU1l70eortTUVBQWFqJHjx4soio2+PgRbqk+7Gizk8lksNlsfhsTGZIJCQmoqqrCsGHDGPlgTk6OINLW0NDACCCJS4NInqXmDSHYaDOgPuaTwNJ75ebmokuXLujatStSUlLw1VdfCXilKAqek5ODkydP4s0335S8X15eHqxWK1OW+BG9oUOH4sYbb2QbmFwuR0NDg1+/UpSN/xnxe/EdpmFhYe1W3BMbi4SAaW+c+MgK8fjR/71eLyoqKvx+Gx8f3+lqe+J5Hh8fL1lemR/Zys/PF3xPqZOBnGg6na5dR5U4ktpR4xthHo8HaWlpcLvdzAjiOyFozKKioqDX65Gbmwu1Wo36+noEBQVBrVZj1apVsNvtePLJJ3HixAns2bMHKpUKY8eOxXvvvYekpCSWznfzzTfj1KlTmDt3LgwGA7RaLdavXw8ADF1HVShpTlClxk8//RSTJk1iaVIJCQlISkrCvn37MGrUKIEzxWw244477kBkZCTi4uLQt29f5lwym83MuaRQKNjc6t+/P4C2UsInTpxgChd/DvHHyGg0IiwsjK1DSr3g9x2/DznuX/xe/PUgJpgXI9+0Wu1lO0E726gSqvhzek8peWQymRhPCDmo+alWVOSCquGRo8br9TJlWyaTITY2Fs3NzXj33XeRn5+PadOm4dZbb8XSpUsBAD/++CMrSGE0GpGdnQ25vI1ripRsknvx8fFoaGjA+PHj2XOHh4fDaDQiKioK3bt3h9PpRGJiInr06IGYmBgmb/nvSP8vLCxEc3Mzhg0bxsZX7JRzuVyIiIjAhAkTsGLFCkaCTHPz1ltvxbBhw5CWlsZ+x3ecJSYmIjQ0FNOmTcOBAwcEwZSSkhJJ/g9KEXM4HKzfqdok7akOhwM+n8/PgSlVXW7y5MmC96J/+c8SyJEQSGYHBwezdTFnzhwBWTt/3zebzYLKrSkpKcjIyIDBYEBVVRVGjx4Nq9UKo9GIBx54AJ999hlOnz6Nhx9+GLm5uQgLC2OIj1tuuQX9+/dHeHg4YmNj2RrLzc1lgRWpxkdOUp9qNBrmUKDfer1epKWl+TkN+ONiNpvhcDj8KpFlZWVJOpOjo6MRGhrKHEekC1itVpw8eRKxsbHIy8vDxo0b8fXXX2PJkiVwOBzo1auX4DritCd6XvH9aI+gOS9GTvTp04et37KyMkybNs2vr35N2dMZ5wOlQ5P+RzImPj4ea9asEegXarWajV9RURF8Ph9Onz4NubyN3L+8vBwGgwEejwc5OTlwOp1QqVSIioqC0WhkTr1Ro0YhLi4OdXV1GDduHGQyGa699lrk5ORg9OjRaGpqQkxMDLp16+bH/1RYWIi77rqLzXe+HtG1a1eo1WoMHjwYf/nLX5jzNRCCmQoLqVQq9jeNg1arxZAhQ3D//fcjPj7ery8JIS6TyXDfffdh8ODBgjlYUFCAF198Efn5+UyHk8n+lfbZt29f7N27F263G127dhWgEmk/stlsjHqhPYdMZ5yYUmhvcd+IU20D8SfW19d3OLcoGBJoTks5d/lplVJzOT09XbCnOBwOgb5AQV0K8Or1ekRGRuK1115Dbm4u7HY7o26ga/Dnd1RUFNavX89sDULTkk5GY0BOQ41Gg5ycHMTHx2PQoEHYvHkzDAYDNm7ciPfeew+DBg1i1w4JCRFUM6UmVcmXAhb8wCEhvi0WC9auXSvoQ51Oh/z8fLz//vuora1l97BarQwRtX37dpjNZjzwwAO/v5F/9fivOf6nnFEPPPAAGhoaAADDhg2DTqfDkiVLMGPGDHBcG+LG4/FgypQpaGxsZIalxWLB22+/jYyMDKSnp/vl0dICrKiowD/+8Q88/PDDgsgCcQY899xzfvBy/v/Lysowbtw4gRBMTk5Gz549WRnn3NxcATpJo9HA4XAISDIrKipYFaOuXbti+fLlLOLRv39/vPvuuzh27BguXLiA/v37Y8GCBey6gYxmKYVLKv/YZrNh/PjxATdhh8PBrkUVYsjYI+JIuVyOFStWoH///qyPkpOTMWbMGEyZMoUhL/icTxSVpmdtL1rS0UaWlZUlcPLQ56mpqTh//jyGDh2K2tpa/PGPf0RQUBBMJhNCQkIQEhKC0tJSOBwOeL1eDBs2jDkfyXnDNzyDgoKwYcMGNDY2ss+MRiOr4sJxbdHT0tJShISEMCW6sLAQzzzzDB599FG/tBna7J577jkAYKkzRJpP5N6pqanM6FQoFIKywJWVlew5S0pKMG3aNBbZCdSPKpWKIRv4CgF/XKQaOXP4KIiOxiw3N7fdcexIse6Moix1DY1GgwkTJvhxEWg0Gng8Hvb8fF6f9hQiKQcp3+lCSlJ7z8lPH1ar1YiKikJJSQkzoGJjY1FTU8Oq8KhUKjQ1NWHfvn2sIopOp0NiYiL++c9/Yvr06bDZbAgNDcUPP/yAuro6NDU1AQDuvfdeAGDcFps3b8Zf//pXJCUlITIyEpMnT4bH42FzZ8WKFfjmm2/w/fffM74hUoopXYXeY/v27Whubsbrr7/OiPM1Gg2mTZsGr9eL3NxcnDt3jpUqJhh6U1MTHA4HzGYz1q5diz179mD8+PFQqVTo1q0bJk+ezDhUZs6cidraWowbN05Q0ZLj2tLWbrzxRkl5xnfqENcWRV1pnUrJR5vNJjn+vwZptLhJ8ZsFQnYR54/UWhCnetM6ps+oUuCUKVNYqp/VakVCQgLmzZsHjmtzMD7yyCMAgJaWFvTr14/N6aioKLz00ksMpcZHt/AJV+Pi4qDX6+FwOJCeno7q6mooFG2VVfnOD71ejwULFuCJJ55ATk4OQkNDMWnSJOYcGzp0KEJCQgQk/lu2bAEA/PTTTwzNOGHCBLbm+P3RvXt3/PDDD/j444/9nFtarRa1tbXsN1lZWYx82mKxQK/XIzY2FiaTiSE66LdTpkzBww8/LEiXVKlUmDdvHkOY9enTBykpKQL0ltT+zDcm6T09Ho+AB4ScMfQbu93ul3bUmXkaFBSEuro6FBQU4OTJk34GuVguUp+aTCZkZGSgrq4O4eHhCAkJQXp6OqxWK15//XVcuHABFy9eBNBWSMbpdLIUvYSEBBZ15z9vdHQ0GhsbJfkKydjjUyhERkZCrVajoKCAOVB1Oh0GDBjACKmlrsPvCymZzdc3qD+oImJQUBDj47TZbPjiiy8AAC+99BLTGzZv3oz+/fvj2muvxfbt2zFs2DCB3OfrOYHGKTU11e/Z+L8ZO3YsFi9eDKPRiJCQEIGxf6WoFfFaaW+fb69v+UgvnU7HqAnWrFmDjRs3YuHChZgxYwbmzZuH8vJyhpT6+eefsXfvXiiVSgwYMACpqalsDZhMJoaSq62thclkwq233oq9e/di0KBBDNU7ZswY/Pzzz7jnnnsQERGBqqoq1NTUMCcrPSPJTNLBSBey2WyYMWMG8vLy4PV6ER4ejr59+2Lbtm1+qbx8+TFixAh88MEHmDFjhp9zUSZr4wL66quvsHHjRhYUcLvdcLvdWLduHSZMmAC9Xo+pU6ciODgYW7duFVynW7duCAoKwqFDh5hNYbfbYbfb4XQ60djYiGHDhgneUSrdsr1x+7VboKCM+H6BnEY0f/jBE9pTxE7ky2n8PVAmk7GKpjQn+Jkz4iJEhNxbunQp43ci3Ux8n/z8fHYfu93OZL3b7WZoa7VajeLiYpSVlTHZSMHM+++/Hy0tLVi/fj0sFovACajT6RAZGekn00nO8HV7coRpNBr06tULpaWl7JyXX36ZBdhI573ttttw6dIlbN68GUqlEj179mSyfOvWrTCbzbj//vt/Jyv/6vHfevzPOKNaW1tx5MgRqNVqBuudOHEigoODYTQa8dprr2HkyJGQy+VITU3FmjVroNFoYLPZEBkZibCwMISGhsJqtSInJwdGoxHh4eHo0aMHq5DGcW2pC1OmTPHbiOLi4piRyI/YiUtEl5SUCJAqcrkc3bp1Q0hICJYuXYq6ujomtPmKUkJCAhYsWCDYVGQyGTIzM7Fx40amhGRnZ6OwsBAbNmzAnXfeKSipXVJSguLiYpbzHEjpoEbedv4mRlW27Ha7pFMoJyeHRbxnzpyJ3bt345133kFjYyNmz54Nj8eD1atXo6WlBU1NTX4pNBzHMa6P0NBQbNmyxW8z6qi8tVREgH8PtVqNhIQE5rwcNGgQDhw4gAsXLuCHH37A9u3bkZGRgeLiYlZWd8yYMUhMTITNZkNISAiamprw888/4/XXX4fNZkNGRgbGjBkjGGv+BkOfd+3alSnX5HSjcV24cCG2bduG2NhYRohKkcEJEyYwLq7ExER88cUXOH/+PE6cOAGPxyNICSJ+gd69e8NoNMJsNsPpdAoIN0m5dbvdTJmRShFtT2lwOBzMQSU25KhFRUVh4MCBLEIqFbWSujYh9JTKtpK6FOUmY4DvBCwvL5e8RqBn50Oj+ffTarWIj4/Hhg0bkJmZKXCe8bk9vF4vQ/e1p+CIP4uIiEBWVpakU85gMDB4N99Q4RuYtO5sNhvjZvJ4PEhPT0diYiJSU1OxZcsWXLp0CS0tLfjHP/6Bfv36wel04sknn8SFCxdw7tw5vPjii/jnP/8JAEhMTMTcuXPx8ccfQ61Wo0ePHgCAmTNnorS0FN9//z1ee+01xtmwYcMGpKenIzQ0FOXl5Thw4ABOnDiBESNGICwsjFUo6tGjh4CLLSgoCADw4Ycf4o033mCGBY3tZ599hs2bN6Ourg5jxowBx3EMoaHX69k1T5w4gebmZhw/fhzz589nxj4/gMAnKuZXGyopKfFL23Q6nYiNjUVxcTFSU1OxaNEi1NbWCkqvSzWxU0esDEtVqhEjraRaIFnc3tym31BamfhcKeQd3yHKP5/QFfSs1H8kM2WytkITWq0WgwcPxv33348zZ87A4/EgJCQEOp0Offv2xenTp3H8+HFBwQb+Ptq3b18sW7YMbrebXc/hcOBPf/oTcnNz2fk0n8xmM+rq6jB69GgUFBQwDjGKJJOznQiOhw8fjqKiIubIJHlFpK/0vgkJCfjggw/w1FNPCRx+ZKBYLBaUlJQIUl/4fC18Y1atVjMZSunVpD+Ix9FoNCI0NPSyOVd0Oh3S0tKwatUqZGVlMZlqMpkQGRn5q5RfJ7QF30Brby4OGDCAcc4Qskyj0WDQoEEIDQ3FNddcg7/+9a944oknsG/fPkyePBnx8fGswp1cLkdcXBzOnTvHAod0n6CgIERGRgpSgWgOOhwOBAcHQ6PRsLRQGjsa4759+7KqwYHWkBSSlr/2t23bhoMHDwrWDFEMrFy5Enl5eWwdhYaG4uDBgwCAt956S8CHSXuI1WoVFJiw2+0BC9ZwnNCJQNfr2rWrgAuQ49r2l6lTpyI8PNyPY/SXNqm9m98KCgoC9i+laVqtVuZcSUtLQ1RUFO677z4AbU7t1tZWnD59mnErTZkyBQBw3333MRlAOrNMJmO6oF6vx/bt23H27FlUVFSgV69eaGpqYjQHDzzwAC5duoScnBycPn0ajY2NyM3NZes3OztboM+bzWYWiNVoNAyp73Q6GYceIWNorlBwU6FQwOfzISoqCrfffjtuv/12Rsi/bds2loYmk8mQlpaGv/zlL/D5fAxJxXEcbrvtNkRFRUGr1aKsrAyrV6/GxYsXccsttwgcfHFxcRg0aBBLAyTuN41Gg4KCAsTGxiI0NBQqlQo5OTkCZ8hv0SwWi5/eRPNdPI/ba263W1BUit9MJhPUajVDhdHeFxkZKXB2lZSUSPIm6vX6gJUl+Wl/5KChNFB6FjHnnl6vZ3QnpJPy14EUQpbsL6fTCZfLhbCwMERFRbEgdWZmJtavX48RI0aw4kV79uwBACxZsoT1r3hfcblcUCgUAmS00+nEyJEjBamr1IqKiiQdpRQE4jiO8UgWFxcze6G5uRkAmCP1KiLq6tGZ4/+8M6pnz5549dVX2d+0Qffp0wd33XUXbDYbwsLCMGvWLLz11ltM4SSEiMvlQkxMjKA8OaFPYmNjceDAAeTn5yM0NNQP1qtWqwWGRSBElNPpFCglFEnkK6JZWVnIzc2FXq/HuHHjsGrVKgaDDwkJgd1ux8CBAxEcHAy5XI7Y2FgolUrm3CouLmYebyIOJwOe7unxeFBWVtZuWpW4KZVKQXlu+lyn08FgMOD5558X8CWRAeFyudCjRw+cPXsWQBuZ/IkTJxAbG4sPPvgAX3zxBQwGA2JiYjBgwAC/9CeHw4G//vWvApg+bRZ8xbOjd5HJZH7Oh5iYGCQmJuLmm2/GRx99hNbWVtx8880YMGAAsrKy0NDQwDbDPn36ICEhAU1NTaitrWW8XklJSRg+fDg2btyIgQMHCsZSrVb7RVDIsOEbzBEREUhKSoLVaoVOp8Mbb7wBADh8+DBTho1GI44fP47nn38eBoMBY8eORXFxMaqqqtDU1IRnn30WlZWVkMlkSE9PR1RUFPLz8wVVNpYtW4aSkhJG9ksOnry8PKjVasTExPjNV+IdEo87VaCk5ysqKuowkpaRkYHU1FQ4nU5MnToV1dXVgu/DwsL8HGH8COiiRYsQFRXFUsHoHfh9K0675SsDHNemqEtVrRNHewcOHIiHHnqIVVwSpytKVdYi/rWO1hLNXzGHHL0nKTN8KDX/XnK5HEVFRcjPz8fZs2exYsUKcBzHnlMmk2HhwoVoaWnBn//8ZyYTCwoKUFdXh+bmZrS0tOCWW27B5MmT8fe//x0rVqxAZGQkTp8+jVOnTsHj8aC6uhqLFi1CRUUFgLZ0Z4rONTQ0wO12Y+rUqYiKioLL5UJ8fDxDGzqdTuTk5ODMmTNYtWoVGhsb2Vj169cPmZmZ+Prrr/HUU08xZVGlUuHhhx9GSkoKzGYzxo4di2nTprF0ToVCgTFjxsBgMKC8vBwvv/wygLaUvG+++QZz5sxh67uoqAgxMTG4/vrrBVXz+HJCoVBgz549SExMRFxcHG655RY2t48cOYLrrruO8YeEhoaipKSEpduazWaBLKf1I2XQiiuPUj9oNBrGzyQ1Ry4XWUV8RYHWoUajQWRkJKqqqvzOmTVrFnw+H3v+oKAg6PV66PV6FlQIDg7GgAEDEBERAbvdjhkzZuCZZ55BRUUFwsPDERQUhJCQEEyYMIHxe9XW1uLaa6+FXq/H3r17mczm8zDNnj0bTz/9NKxWK+OLi4iIYP2m0WiYI6mkpATdu3dn+yYhVun9i4uLGREyjTmRi9PfKpUKgwcP9uPYyMzMRGJiIuRyOSO/FqfVVFZWYsOGDdi0aRMOHTqE2tpahkJLTEyEwWBASkoKrFarQCcoKCjAddddh+uvv571wbhx42A2m5k8MplMGDZsmCAwIyYK58/d2tpaPP/888xQEAevArVA35Ne43K5BHw59H5S1xBzVR08eBBLliyBSqXCsmXLcOzYMej1elRUVDAEVHBwMCvuotVqsWvXLkF0v3v37kyO0b34DhsqHkPpuVarFV6vF0OHDhUg8GQymWA/6AzSg4/mJllF63z79u3YvHkzdDodVCoVIiIioFQqsXnzZixatAhWqxUFBQUYOnQozGYzrFYr3n//fezevVtQ8ITmRWxsLEt5599fvBeJUYv8d3c6nez3MllbJUqXywWPx4Nx48Zdlo7X2XnS2T7kP6vNZoNarUZOTg5++ukn/OEPf0BRUREeeOAB6PV6lJWV4bbbbsN7773HKnL99a9/RXJyMjiOw+jRo7FlyxZs2LABHo8HqampAnoCmUyGJUuW4IMPPkB1dTXS09NRWlqKLVu2YO/evcwpd/DgQVx77bU4f/48brjhBsTFxSEoKAjXX389rFYrysvLkZmZyfbY/fv3IyUlReD80Wg0uOaaa9ic5/OoEaLTaDSitLSUpcXzHdZUqIGPrCbE+fDhw5mTJC4ujjknFQoFCgoKcMMNN8BgMGDatGkCom+ZTMZQXtHR0YIgSmpqKpsvhLAmJxd/nKTS7KTSfzvTAvFH8YMsgRxi/L1PpVIJCkbw3zc6Ohr19fXsuWUyWUDyc/G9ZLI23j6xvsZ/Pq1Wi5SUFBYUo8rT5eXlArmcl5fnh0DmBynlcrmkXlhUVMSQlRqNhqVyErry22+/RU1NDe6++248/vjj+PLLL9Hc3IyXX36Z7bk0blQ9mNYfOUqpeq/dbkdmZib27Nkj0DmcTidzRMlkbTya/AIlHMexIjCk+8XGxjJE1HfffYfZs2czNP3V4+rR0fF/2hnV3NyM2bNns9zVlpYW7Ny5Exs2bIDVakVtbS3GjBkDk8kEo9EIk8nE4PpKpRKDBg1ikVUq90qCLSsri1XaOH78ODZt2uRniPIVgvba6NGj0adPH/a3Xq+H1WrF7t27BeWDCa5LPDJyuRxTpkzB0KFDGUmnQqHA7t270draiiVLljCDSCZrq1Jz4sQJ9O3blwlHvV6PoKAgvyp5MTExAoQRXUfq+aXg2VqtFseOHcPx48dRUVHBCFcjIiJgtVoZ3Jlg/ydOnMCbb74Jq9WKpUuX4oMPPmCpNPX19SgsLBSkANHmSgb86tWrJaut8fl4pDYeutbkyZOZ0k2efqfTibvvvhvz58+Hw+HA3Llz0aVLF6YEGwwGlkZCxh6lllAfJCQkYM2aNUhNTWX9V1NTg5MnTwpSRyiFjuPaHI+nTp3Ce++9J4i2fvbZZ2hubsb999/Prq9UKlku+r59+9Da2oqRI0ciOjoaHo8HK1euRO/evbF06VIkJSWhpqYGhYWFAkTIsGHDcPLkScydOxd2ux0bNmzAkCFDkJCQwJxuXq/XL0pPUWdxn1K/0j2k4NfEL0N/U055a2srtm/fLhhHij7y70U8CzU1NairqwvI3cE3igLNX35ZZP49+Cml1IhbgMrM0wbfXtQ30LonyHyg7+l5A0XFpZA1CoUCzzzzDADg7Nmz2LhxI0aOHIkTJ04gMzMTWVlZWLduHSorK/HRRx8BAK699lr069cPADBv3jwEBQXhnnvuwd///nds3boV2dnZyMrKwunTp/H0008jLCwMDocDo0ePxtmzZ1nkv2fPnmhubsauXbsY+igoKAg5OTk4evQohg0bhoEDBzJic6vVisOHD+PgwYNYsGAB5HI59Ho93nzzTdx///3YtGkTS3fW6XRYsWIFHnzwQYSHh2Ps2LGYPHkyBg8ejHXr1kEmkzEFkUgzL1y4gObmZuzZs4cpk263G3PnzsWzzz7LnOSE0uCnPn/33XcsjZXQORzXliKqUqlQWlqK+Ph4lvJaU1PD5BXxbfFljPj/HNeWRicuXiAeYzEylI9e7Eipp3P4Ti4+PwvNfYrOhoWFMdQp/f6hhx5i93S5XLBarbBYLLBYLJDL2wpjeDwe5qRyOp145513MG/ePLjdbvh8PobE1Ov1+OMf/4iwsDAYjUbk5+dDo9GgsbERLpcLcXFxyMnJYeMil8uxefNmDBw4EBaLBR6Ph+1lDocDN954I6677jqo1Wrs3LkT+/fvh0KhYNWkNBoNcx5FRUVhxowZAkeT0WhEVlYWunTpIuh7quIoNvZpr6RqRPw9MzIyEocOHcKOHTuwevVqHD9+XNDHOp0OXbp0YXsWXTc0NBSvvPIK1q5di+HDh6OwsBByuZzxOpHzZfbs2XjwwQfZ2ISHhzOHQlJSErteQUEBS8NyuVwYMWIEIiIiOk1QTXNGimCa4/5lZFNAiR+kEzvgybnSr18/XLhwge2jer0effv2xQ033IDz58+jtLSU7RtarZY5iu666y5WEIR/Xb1eLzCGSQcwGo0YPnw4oqKiUFFRAbPZjKCgIObMpPMJAcd3BPGbuEIv/RsbG4u//e1vuPXWW5kRT8gI4sh77bXXsHXrVshkbbxmPp8Pubm5GDVqFB599FGYTCZs27YNhw8fxvTp01FXV8cKNdB8MBgMl1X8g//cfEcnBTUpPdFoNMLlcknua51tUvucGK3ZUVohx7Uht/Lz81kgZ/Hixfjpp5/Qp08f1NTU4OjRo6ivr4fP54PFYoHJZEL//v2xYcMGtLa24q233mLBJ74sdLlcuP7669naoHmYm5uLnJwcVFdXo6ioiKGAly1bhrCwMAQFBeGhhx4CAMyePZshZ1euXIldu3YxBx/JBrfbDa1Wi5ycHGg0GixevJjxHS5fvlyQXaDT6WA0GlFdXY3s7GzGh0jzmtY69a3L5UJOTg7ry8cffxytra2YM2cOfD4fiouLYTQameOL1mpDQwNqamrQtWtXP27aqqoqfPHFFygtLYVCoUBWVhbi4+MFyNRBgwbh888/Z5Qg/DXH33vE8+Fyqxa31/jObvF9AqWBUlCEkLD87/h/y2QygTOI+o1oAaQaBen5HEz0eUFBAUu9s9vtgn2Vz59E70XjTUE2AgFIravc3Fz06dMHcrlcMB+Sk5MRGxuLlJQUbNy4ESEhIXjxxRdx++23IyEhgQXEbDYb8vPzYbPZ/GQJ7T+EkJs4cSLbV3U6HZKSkthzUSDUarWyoDSlDT733HM4dOgQ9u7di3HjxjFHFCGjfv7559/P2L96/Ncf/6edUfxj9erVePLJJwEAu3btwvr165mQ3bZtG8xmM1QqFQYNGsS4flQqFSuFqlKpGDrD4/EIUFBRUVEsamE0GtGtWzcUFBQgPDycRYL5CoM4KkWCgX/NtLQ0XLhwAY8//jhLveG4NiU0NTWVecm3bNmCixcvonv37lCr1bjnnnsAtKUlvvfee9i0aRNGjx6N/Px87N27F2+99RZsNhtTeD0eD5566ikmVPV6PUJCQnDPPffg2Wef9UOUEMcM/S12NNBmQgodocN27tzJjAAq9x0ZGcmUyg8//BDfffcdpk+fDovFwgxwjUaDzMxM9tuVK1fCbrcLUkVqa2vx9ttv46abbmKfUfRcvBmJuVXIaLbZbPD5fAzKOm7cOGzYsAGvvPIKIiMjceLECbzxxhvo3bs37rzzTuTl5SElJYURrfbu3RuzZ89mxOBWqxVOpxM2mw1xcXEYPny4pFOBeGfIoUG52rNnz8bevXvZnMjLy8O8efOwcOFC7N+/H8eOHcO2bduYsZmRkYGzZ8/izJkzzFjLzc1Fc3Mzmpub0draip07dyIhIQEVFRWYMmUK7rnnHhQXFzNC4sjISDz11FMA2qKPRBwtRnDx5wLB06WUlCFDhkimmfCjPfzzOa7NUXfNNdcgIyPDj8CUnFv8Z3A6nZg1axb7vVjJprlGf0txgfGfw2g0MkVSiiSf49oMsurqaoESQ/w67aXVSClY6enprI/5iol43nbExxEXFwedTseQKM899xwefPBBbNu2DTt27MCZM2dw4sQJhpzcuXMnfvzxR1y8eBH5+fkYNWoUjh8/Dp/Px5xZTU1NCAsLY+tUqVQiOTkZUVFRUKlUSE9Px5IlS1gaQ0JCAu6++240NzczJ0ZlZSVCQkIwc+ZMdO/eHQsXLsRtt93GxuKjjz5Cc3Mzzp07h+3bt7MxLS4uhkwmQ48ePRihp8fjwalTpzBixAhGtP3II4/g22+/RWJiImQyGbZs2YKff/6Zzfnm5mY0NDQIxtjtdmPt2rVITU1lnD5iw5M4dfiITH4ln1OnTuHjjz/G0KFDmfzgo3rEqc5UwKK9+SDV+GTTYrlVWloKn8+H8vJylJSUMGNBpVIxI47OLygogEajgdFoRGpqKux2OzMiKCJKRmR5eTnbsyi1g/htqJ9J9pPzJzQ0FEqlEg0NDVi1ahVCQ0Oxd+9eeL1eFBcXg+PaDO3a2lps2bKFycKgoCC43W4MGTIERqMRN910E1OmyRk0b948qFQqJCQkIDg4WBD0UavVWLJkCVasWIH58+ejvLwc0dHRyMvLY0o/pafpdDqUlZVBo9Gw9BQiE+f3VX5+PquSlZ2dDY/HwxDVXbp0QWhoKIKDg5Geno74+Hgmcyg6npWVBaPRKOBQ8vl8ePzxx3H8+HGYTCbmXKO9cuLEiTAYDOjZs6egIAnNReIKLC0tFVSp69WrF+t7nU6HmJgYHDlyBAkJCcjNzUVDQwMUCkW7aV5ieUkyLtA5BQUFfigFSqkjGWY2m2EymZCdnc1Spe12OyorK5GXl4e+fftCoVDg888/x8iRI1nUnWTh4MGD0dDQAJVKhfLyckGaq0ajwbJlywS6B/0/KCgIu3fvBgDmHOjSpQuMRqNAvtbU1PhxTclkbWnBK1asQFVVlWCdkm700ksv4dKlS+jRo4efAbl3714Abdx6fKL1tLQ0HDp0CEajEePHj0fv3r2Z483pdGLOnDmCQhgUXBJTPfBJjMVjIpPJUFFRwXg2qVHQhAJQgQjfxfumlNNJ7HRQqVQdVolVKBRITk4WXF+hULD07xdeeIE593w+H2JiYvCnP/0JNTU1bM5wHIc77rgDxcXFiIqKwrvvvgsAeOSRR5icSklJYeud0ogWL17M5EtqaioKCgqQmZmJn376CUCb0yk7Oxu9e/dGcHAw9Ho9Dhw4gB49ejCkEFXoJCd9fHw8G6eEhAR89dVX6NOnD8xmM2JiYljquLgfaP6WlZX56QiPPvooKioqoNPpBE4o+r5Xr16orq6G3W7H0qVLodPpEBcXhwceeAATJ04UrBun08mK/igUbRU96XmGDx8OhUKB6upqNDU1ISgoSFDMRqlUIiwsjK1v8VgrlUqG2JHap/jvLUZris8n54fUPFOpVBg3blzA/VFKNvHRyPzr8P/OysoSVGTtaL5brVamN5C9wdcThg4diu+//x633XYbexeZTIapU6dCLpcz5DYFLZctW8bsOP67qdVqVFRUCKgEZDIZVq5cifHjx8NoNOK+++7Dyy+/jIULF2LFihXYvHkzzGYz7r33Xjz++ONYvXq1IL0wIiICcXFxrIiCOKg1aNAgrFy5EsePH0ePHj2YQ//111/H0KFDBf3ARxOHhobi448/RlxcHJqamvDUU0+x4B/QluFy9bh6XMnxf94ZNXbsWDz//PPo0aMHLBYLI6Tll44lJZyUPlJ4CXobHR3NFG8SZATZFws2tVqNkJAQhrQiocPnoSBIurjaXmFhoYAUfMKECUhNTUV2djY2btzIHBMqlQq5ubkwGo0YO3YsVq1aBYVCgUmTJgFoc7wRGuxvf/sbNm/ejJiYGOzbtw/r1q0Dx7WRrVssFhiNRsadRU43eh6Px+NXPpneXa1WM0cd/zviTOK4tojt5MmTkZmZCZ1OB6vViri4OBw6dAj3338/ysrKoFKpsG3bNrS2tmLr1q2sWhDl/2dlZWH+/PlsrPr3789IYsnZRJWxSODyc/SlNjqCvIo3IkKe9evXD6+//jpaWlrw5ptvIjQ0FMuWLUNaWhrS09Nx9OhRPP7441Cr1RgxYgSDA/PROTU1Nfjqq6/w6aefoqKiAsXFxbjpppswevRoASKKEGhyuRzh4eGoqKgQpA653W7cfvvtgjLaRCx4++23s6piarUaZrMZXbt2RVxcHBSKtjLX33zzDYtUnDt3Drt370ZCQgKGDBkCoG3zeOyxx7Bjxw4kJyfjm2++QWtrK5qampCcnOzHC3L99dcL5ihVELPb7Zg0aRL7nKKvtLkaDAY2hvxNlxyjYoVgyJAh6NOnj1+aq0zWVtLZ4/EIiMz5c5fGWWr86XyxI2zgwIHsu6SkJIby4DiO9T3fEKaNWeoefAVQSrGRUoRIueE4/wo1Wq0WkydPZvB9nU6Ha665RhAZDgkJQVVVFU6ePIni4mL4fD4EBQWhqKgIBoMBBQUFGDBgAPR6PdxuN7xeL7p3746GhgYkJSXh4sWL2LNnD5sDN910E0JDQ/Hiiy8CAK6//npwXJvSf+ONN+L48eMoKytjKX5/+tOfkJ6ejpCQEIwaNQoff/wxXnvtNTidTmRnZ6NHjx5ITU3FpUuXsG/fPhiNRiQlJeH8+fN44YUXAADTp08XKH/kqN2yZQvGjh2LoKAgVFdXo7GxkSF5XC4XfD4f0tPTsWzZMigUCtx66604f/483nrrLYwdO5Y5FfV6PXr37g29Xo+wsDDk5OQgLy8PISEh0Ov1yMrKwu233854H9RqNVvb5JChMVm2bBmeeeYZJte0Wi1LieIrrdQuJ3osVqgDnRcaGgqPxwO3241hw4axlFgymvj7S3h4ODOIKF2Evyb493z55ZeRn58vIGfPz8+HSqVCVVWVwLgwGo24ePEilixZAo1GA51Oh+joaMyZMwfffPMNRo0aBYVCIVirxIFChjLxchGxdXx8PLKzs7Fy5Ur2fIsWLcLChQtxzTXXIDk5maHWgoODGfqKnik4OBj19fVYvnw5Q+RSdFihUKB3797o1q0bex6DwcA4yvhjQHvZPffcA6vViqamJhiNRkZ6fvz4cVy8eFHgKCkuLmYBnBkzZuDGG29k/bhlyxZ88803KCgoQH19PSIiIiCXyxEdHY0PPvgAixYtgkwmw9atW7FixQqBfLHZbHA4HCgsLMRf/vIX9r4VFRWYPXs2KioqMGLECGRnZ6N///5YtmwZkpOTBU4e8b4nJWuoEf8cPR//O7VajTVr1iA8PFyA1KNUVbqHQqFA3759WYrhAw88gIKCAlRXV8NkMmHHjh3o168fkpOTMXv2bKxfv16AGKOxJ7JePuLG4/Ewp4PNZmOIdr1ejzlz5uD8+fOSjhcK1Oj1er+qraRLEI8dpdBYrVbs378f5eXlcLvdWL58OYxGI+644w6MHj0acrmcIZ/XrVuHrKwsNDY24q677gLHcRg2bBgsFgs2bdrEeEtp/VEAY/PmzYJUWnKEkkOK//5Wq5UFr/jjSamdFJSg78jZvHDhQuTk5PjNgUAcdfw9TK1W+8kw/j3a+z0f7cJHFN5+++0AgC+++AI1NTXQ6XRMniUnJyMvLw87duxAbGwsdu3aBb1ej127dgEAbr75ZowYMQK5ubnQaDR46aWXcPz4cTbfXS4X9uzZg48//hgrV67E0qVLsWvXLobeuPPOO2E0GvHCCy/gu+++w9///ndMmjQJGo0G99xzDwYOHMj4NPmVGPl90qVLF6Znk4ORbAWPxwODwYC9e/diwIABTFZSKid/zk2aNAnbtm1DdXU1Hn74YSiVSsTHxzM5MnbsWGRlZaG+vh69e/eGx+OBzWZjsqihoYHpW7TOzWYzfD4f1q5dyzItaB/as2cPYmJimBNQHHCmIhXivae9PYzQX53d4zpqPp9Pcv3y5bz4+cghnZ+fz9INxdXHpX4nXgt8GUa2DCHsqLJ0bGwsQ9OdP38e+/btY/cICwtjaYH89Ux2kzgwoNFoWGEW/rMaDAbccMMNGDp0KIKCgpguNnHiROj1etx7773Iy8uDxWJBZGSkgGNPJpMxehn+c3BcW2D7/PnzuPbaaxnljEqlQnJyMmbNmsXePywsTKC3x8TEML7RxMREREVFMa4qSqG9elw9rvT4P+mMIk/t3//+d5SWlsLtduPll19mEM0NGzbgjjvukDT6PB4PgyYmJyczvp2ioiLU1tYy7hPyxPOjV0SGTguflHOOa1N4yUFCqRx8JJTdbsdPP/2E6667Dl6vl0UiiJ/j+PHjmDJlCkvTo4gGVelJSEhAc3Mznn32WeTk5KC5uRkzZ85Ev379GFErcUXR+xH3DF+Z5FeIIuFYVFQkgHoSNHfAgAGCiCQ57zQaDUMU0PcUSXU4HPjHP/6BQ4cOMdJGAPj+++9x44034qGHHmKKmZjwj6rjkLLB70t+XnRpaamAN0rcCGpK40KbOkGxu3TpgvHjx+PNN9/EP/7xD5hMJkRHR0OhULAI/ahRo5CUlIQ1a9Zg8eLFgihtcHAwEhMTMX78eDYPc3NzERUVhb59+8LtdiMpKQmlpaWYO3cufD4fysrKcPHiRZYPTgbyqFGjsG7dOpb3X1FRgZ07dyI5ORkymQyzZs1ixPtGoxE33HAD7rzzTpw4cQJarRaNjY347rvvALRtGD/88AP27t2L5ORkVFVVobW1FS0tLdi8eTPi4+Nx5MgRbNq0CaGhodiwYQNTpNRqNXr37s2UQrGzpbKykkX6jUYjHn30UTZuaWlp+Oabb3Dw4EG/iBnxTxUWFmLs2LGC9NE+ffpIokkoRYzQC/zv+YpGIF4MKSg4PRc5QUtKShAWFoZVq1Zh+PDhbC7Sbwg1KQVdV6vVATmipAj2KeWD0lb5c5wi+hUVFZDJZOy6/BQdMky8Xi8+/vhj7N69G6GhoXj55ZfR2tqKb775BoWFhVAoFJg4cSJOnTqF9PR0uFwunDlzhikSmzZtQkJCAs6cOYNRo0Zh//79aG5uZvwdjY2NsFgsSEhIQEJCAksF2rFjB5qamgTExgUFBXjhhRewc+dOaDQaOJ1OPProo/j4449RW1uLHj16IDo6min5U6ZMgd1ux6hRo1hKDX2nVqvx6KOPoq6uDrGxsWhsbMTtt98OlUqFhoYG9pytra1YuXIlZDIZ+vfvj7i4OKacc1xbGsMPP/yAmTNnsiqPZNDFxsYiKSkJ9957L/R6Pex2O4xGI4qLi3H06FFMmzaNjRMZytXV1ZDL5di/fz+uvfZav7lUVFSE3r17s6p6fPSDuIkRhx2dQ/PY5XIhPz+foTpiY2PZ3pSbm8t4nMSOCP49bDabwNAgFBH9n/h3Ro4cyWRgr169EBwcjJEjR+Lw4cOwWCxYv349C3bodDpGIF9bW4vExEQ2Dl27dmVoxhEjRmD79u0MRWQymVBaWopz585h8+bNjCiW4zgcOHAAZ8+eRXV1NXQ6HeONqampwapVqwTGUHh4OM6dO4cVK1YwpzKNS0NDA9566y1BIIB0AQpCBQcHs/Q2g8GAdevWobW1VYCYMRgMyM3NhcPhQH19vQC96PF4kJGRgX/+85+sHDyllqempmLjxo0MoVVVVYXPP/8c27dvR0hICORyOSZMmIDt27cLdARCQCUnJzPkBu1HDocDOTk52LBhA3P+kvHDR4DxZWJ7jgSSo9dffz0AYNCgQYL563A4EBQUJEC9KJVKDB06FB6Phzlx6TydTsfS9Y1GIwtAUWVS0k0iIyMZaorGjHSLuXPn4sSJE/D5fPD5fCy99v3330fv3r1ZqozD4WAIlnXr1qG+vp5dK9DaojlLzgJC/TocDmRnZ6O5uRk//fQTqqqqGBEzyc377rsPTqeTzSGFQoFbbrkFH374IVtXw4cPx7Fjx/D444+zoh60p6tUKjzzzDN+zjHin5TSX/h6G5/bJTY2FhkZGQylSelLNTU1nQqktNeo4Ar/3mKne3tcVFVVVQgNDUVDQwPmzJkDtVrNHFJUsfL555/HiRMn8NVXXyErKwszZ85kRjHpil988QWqq6uh1+sRHR3N0u5efPFFTJ8+HdOnT2fykAjQSf8B2tKINmzYgKKiIvbZ3/72N/z5z3/GyJEjYTab8eCDDyIyMhJmsxnbt2/HH//4Rxb8ofmh1WqRn5+PCxcu4N133xWkBur1epSWlqKlpQUXLlzAhAkTYLPZWCoVcdBxXJteO2rUKDgcDshkMrae09LSMGDAANhsNkRERECtVuPIkSP49NNP8frrr7Mqvrt378ZHH32ElJQUhrqSyWSYN28evv32WwGXplarxYwZM9DY2IiCgoKA3HO0f3RmXtCakkKEkUwk2R8oLZ2fSSHe46Sq/JnNZr9CRCqVCsXFxSwVPSwsTNLZLs6YEL8LvQ+dQ1VpqSgHUadQAKqyshLvvvsu7r//fgHySWwjKpVK+Hw+DBs2TCCb6d5Wq5WtS3IQOhwOPP300xg+fDhkMhlLNddoNMzhVV1djfLycgGFCV2ztLRUEESNjIzE119/jRdeeEGwVvPy8vz6R6fTCcjQW1pa8MUXX+DIkSOw2+0IDw9nge6rx9Xjlx7/55xRfMjg3/72N/zxj3/EgAEDEBoayiDMdrsddXV1yM3NFQhEu92Ot99+Gw0NDQgLC4NKpUJ4eDhyc3ORmZmJKVOmoKamBjabDVqtFps2bUJxcTGr0ONyuTB//nxWWYrKjOp0OthsNobM4qeCENcGVbSora3F8uXLmeKpVCoRFRWF4uJidO3aFWVlZSzKHxMTg9DQUMTExAjydVtbW/GnP/0J0dHROHXqFB5//HE0NTUJNhuz2SyIPJDhR2guvkALCgpiOdN8iHFwcDBzQPBJ//R6PZ544gmMHz+ekVRS6gLHcRg1ahTMZjNTLvbs2YNRo0bBbrcjLy8PP//8M/bs2cMMfYvFgsmTJ2PEiBFMsNvtdowYMYIpSTKZDMnJydizZw/q6upYmmWgTYcMkG3btqGsrAylpaVwOBxoaGjASy+9hMzMTIwbNw4fffQRpk+fDrlcjoEDByIyMhJFRUWMfHLt2rWYOnWqYFMhOHNKSgomTpwIAHjyyScZFLqxsRFHjx5FTEwMm38DBw4E0OaUGzhwIA4fPoxXXnkFGRkZjMh8+vTpCAsLQ0ZGBuMMofSB/fv3Y/z48bhw4QJuuOEGzJgxgyHGRo8eje+++44pXh9++CHq6+uRlpbGNpMzZ86wPunRowf27duHI0eO4IknnhC8l1qtZqk6/PlE0Rj6rKKiginiarUae/fuxccffyzY9Oh3VqsVsbGxsFgsmDFjhh9/y4kTJ5jiIZfLUVNTw5Q1sSIxdepUQeUarVbrx33G/w2l3hICgJQAhUKB1atX45tvvsFnn32G2tpapmhIkV6LlaWOFDgp8ne+A4uUGf781el0rFoPfTZ48GAG1ZfL5Vi4cCFWrVrFol8tLS3Yv38/TCYT8vLyUFVVBQB4+umn4Xa70atXLyYv33nnHSgUCixcuBCHDh3CN998g9OnTyMiIgIpKSnYsmULI5dPTU3Fn//8Z/Tr1w9Go5EZ9vfddx/S09NhMBhQXFyMp59+Gn/4wx9Ydb+QkBBkZmbi+uuvh8fjgVwuZ1HM+Ph4lJWVoX///rDb7YiPj2ewejKC7rjjDrS0tODSpUu4+eaboVKpsGDBAib7AKC+vh4ulwvHjh1DbGysYG5OmjQJjz76KEM/kPN61KhROHnyJHw+H/r37w+fz8eQfsXFxfjTn/6EefPmsfEoLS1FY2MjFAoFli5d6lfEgf4tKChgyBkykMQIAalGDjz622AwCNJH3W43QkJCsGnTJlRUVCAkJARbt27F+vXrGRdOjx49mFEeERGB4OBgdO/eXRAw4TdxWmqXLl3YvkbzjxBk9fX1KCgowNSpU5GWlobVq1cDAEOtcVxbefGamhp88MEHuOaaaxh3VHx8vODZ1q1bh7/85S+w2WwICgrCBx98gJ9//hk1NTUoKiqCXq9HRkYGKisr0a1bN0RFRSEyMpKtPzI++JFws9mM/Px8fP3115gyZQp7h7i4OEydOhUTJ05kVVBTU1NZn+j1emzevBk7d+7E5MmTMWjQICiVSgwZMgSLFi2CwWBAUVGRwPFE5a9pTdO+3aVLF+Tm5iIrK0vg7IuKioJarWbVeYkDSTweCoUCKSkpAgMtODgYRUVFMBqNyM3NZfJq1KhRCA0NRX5+PjZu3MjIZel32dnZMJvNkqg9/pzjyx+tVovQ0FCMGzcOY8aMgdfrFTyn1+vFF198geXLl7P5PWbMGHz44YdIS0uDyWTCmjVrEBERAYvFgu7du8NqtWL69Ok4evQonnnmGTzyyCOC9P2MjAwcOnTIr4iFQqFgRRfuvfdepqeYzWaEhoYiLS0NQ4YMYToeIaCmTp2K++67T7JyFv/a9F784JnRaGQckS+//DJaWlrw008/MTn92muvAWhDF3/yySeCZz58+DDmz5+P+Ph4xMbGMv2K+phSZygdme4rZXhL7TWEQiPHB1+WUKCE+t/r9frxxtTU1AREj7fX+MESqc/478KfJ5QqGBwcjJ07dwJo4yeUyWQ4evQo24NIR3n22WdZZTSTyYStW7eyc86cOYOioiI0NDSA49ocz8RP8+OPP+LcuXOYMGECQ9Xt379fcNKq2y8AAQAASURBVG0ALM3pxx9/xPz58xmHU01NjaCPamtr4XQ6sXz5coYEk8lkyMvLQ3h4OCv+8MQTT2DYsGFsvPLz8/Hhhx/i3LlzaG5uxquvvsrGKD09HRUVFTAajbBYLNDpdHA6nbjmmmtgs9lgMBjg9Xrx8MMPIyMjg9kQ8fHxeO+995CQkIAdO3YgIiKCOX7nz5+PAQMGsABJTEwM3njjDbS0tOD8+fPo1q0bI02nOSJGvonHmjjRAqX4tsc7Jkbtib/j7zPk8KDAJD/tecWKFXC5XAJZJpPJWMBU6h5r1qxBfX09+vfvL8iA4bf169ejsbFRUh6qVCo4HA7Gy8sHFcjlcpw6dYoFB2muU8o0BbYCyViLxQKNRsP28/DwcKabmM1m3HjjjWwfqa2tZQ7Nt956C3369EFYWBj27dvHKCyo2ANdPzMz04/rkPQPq9WKMWPGYPny5YiOjmaO/nXr1gn482jsaIyoWE9cXBzi4+MRERGBqKgolu561SF19fg1jv9zzig65s6dyzaYwYMHs0ghkaByHIddu3bh6aefxuDBg5k32OPxICEhARaLhVXVSEtLYwY1eaNDQkLg9XqZgN+zZw/z4ufm5iI7O9uvIg8R/5ICKi4jTZFOQkAlJSUxJVmtVkOn0+HIkSPYsmUL1qxZg1WrVmHfvn1obm7GxYsXGWR4xYoVAqORiGnb20TIURIVFQWdTifYFKhRKh8JLblczjz5fOM6LCwM48aNQ2lpKQoLCxEWFoYBAwYIohxz585l40RRaFKWBw0ahAsXLmDXrl2QydpSGo8ePSpwSHg8HkG0nRwPwcHBOHDgAOMY4KcM8JVNatXV1XjxxRfR0tKClpYWXLx4EZcuXcKrr76KhIQE5OXlITExkRHYE2KGKtx5vV6mkJSWlqKkpIT1+y233IKkpCSUlJQwYzU1NRVlZWXYsmULQ2Y4nU6EhISwyi1er5c5FY8fP842ti5duiA+Pp6Vw6aIl1wuZyisVatWwW634/jx43jiiSewc+dOGAwGDBs2DN9//z2WLVuGpKQkaDQa3HnnnQDaHLjbt28XKMIejwculwsFBQV+3BX86BF/46O+NZvN6NevHxwOB/uOqqC1R6Tr9Xrx2GOP4amnnhIY9TTGRHy/e/dujBo1Cv3792f34G+k3bt39+OyoAjxkCFD/LgN6LdKpZJVNOzVqxcuXbrEeNdISeUTO5JzpT2Frj3SdD5JMZ3H5wjyer0ChyV/ndFn9fX1WLhwIaqqqlhVqgEDBiA9PR3nzp0D0Ba5P3bsGE6fPg2ZTIY333wTra2tePrppxEREYGCggImN2+77TaoVCpMmzYNjz32GMaPH88QEBcuXEBKSgry8/NRXV2NgwcPQq/XIzk5GSEhIbjpppsAgHGrFRcXY8CAAVi9ejVuvvlmhuyaMGECg5SnpaUhJCSE8TYRUoBSVAmRRErhsWPH8MMPP6C+vh5TpkzBnj17oFKpBFUC8/LycOTIEfz444+oq6tj19VqtTAajXC73QgKCmJpjCtWrMD58+exatUq9OzZk6WhkrxSq9Xo378/Hn/8cQF6gVAUNFfFBi9FF2fNmoW5c+cK1g99LyWH6XMxGo8UdwpscBzHUkciIiJw5swZbNmyhXFGEVk2KdJqtRpbt27Fjh072DrkG6R5eXlMxlqtVrzyyivYvn07JkyYgMTERCgUCuzYsQNPPPEEkpOTWYEHSjM7e/Ysunbtiq5du+LYsWMYOHAgnE6nIODSpUsXpKSkICsrC4sXL0a/fv2gUCjQ1NSE+fPnM9RteHg4K5BA1cWampoQExPDgib8dU3vUFxczOYWIYD5fEEc11a9s6qqiqUUjhw5kjk8S0pKYLVaWUXGfv36sX3ZYrEgPj4e+/fvFxDrZ2dnM+PAZDLh9ttvR3NzMwYNGsSi2CdOnMDYsWNZgEWhaCsp39LSwtBPVLJcnBbn8/n8+JHuvfdeFqletGgROK6tUlV+fj5DS5Khy79WTEyMnxOfP5+XL18uWaGWUJXknCGkM1WOIwcbx3F45JFHMGbMGGg0Grz33nt49dVXmVyLj4+H3W6Hx+NBWFgYYmNjUVBQIJiHWq2WIb75z+dwOHD06FFUVVUhJyeHpVA1NDSgsrISKSkpWLx4MZKSkpCTk4OMjAyEhoaioqKCpYZKvTfJFn4fBwUFQavVwmQyYefOnWhtbWUOjw8++ADBwcEYPnw4qwZ89uxZ5ObmorKyEgsWLEBdXR3MZjP69+/PjL34+HjGt8dxbU5Ms9mM0tJSVsAkMzNTkK5H8kcqsEbcpXQuyQSiMSCHnJQzgeY0H3nXXhBFrAOQcyCQw0GtVrPnUSgUiImJYelu/ApbW7du9eOZuXjxIl599VX06tULOp0ODQ0NANqcUE888QR69OiB8vJynDt3jqXr9u7dW3CNw4cPo76+HmVlZaioqMCFCxfYd83Nzfj000+RlZXFytcfPHgQO3bsQHh4OCIiItDY2MgCvDQ3PR4PzGYze/devXqxfiFEvcPhQGRkJDPYz5w5AwDYvn07c3ZToaS3334bvXr1EjhfqIIxpXoRhyml4E6bNg3p6en4+eefMXXqVEEamcvlQnl5OebPn4/S0lLExMTgpptuQs+ePZGQkACXy8XWdmZmJnbu3CnQ42j8nU4nQx5J2QEdzRf6vD1nlVjG0R5PPKz0vdhhSkEpItPWaDSIiopCUFAQbDYbzGazJEKIv7fx5y1xBfPPl8lkWLx4MSswQ6n4SUlJkMlkKCsrg8ViQX19PbPlaG/2+Xy49957Wb/x+4gvX+RyOeLj48Fx/+IbpTVjNBoRHh7O5mxLSwuam5vxl7/8BW+99RYefPBBljYvk8mYE4y4naR0zqysLIb4pzmr0+lw4cIFfPLJJ5gwYQJDlvHHUKvVYufOnfjwww9x/fXXIzo6GgUFBcwBRTbn1ePq8UuP/zPOKL53dv/+/YiIiGAbTGxsLEpLS1FaWuqXotOrVy+GpqGNnaCyVVVVCA4OhkKhQEJCAm688UbY7XYBkbJKpcKAAQPwt7/9jRGPiisp+Xw+bNmyBQkJCRgzZgxTEEwmE1wuFxoaGgT5vQTPDgoKQr9+/QSQapfLxSJJ9M4tLS347LPPALQha6677jqmGMtkMnTr1g0RERGYNWuWQGnhuDZjhoR0Tk4Ohg0bxvLFxSVdVSoVXC6Xn7Crra1lSkFERAROnz6NlJQUxofQ1NTEyIAfe+wxDB06FMHBwYz4sUuXLoiJicHGjRshl8uRm5uLZ555BmfPnmWCmvi8KI3QarUyritCDISEhECn0+G5557DCy+8gNWrV7NKOpSyxneehIaGIigoCBkZGXjnnXfQ2trK0tYoXZIiJ2azGTt27EB2djYiIiIQFBTEOD80Gg3WrFnDUgNpIy0pKcHUqVPZxslxHOM0oGjX6tWrkZeXx9IojUYjcyIQyu/QoUNss54wYQLeeOMNAG2Isri4OAbD3bp1K/r164fZs2cL1sZjjz0GvV6PtLQ0tllTpLG5uRnbt2+H2WzGLbfcIjBebDYbevTogbKyMr/NrT1CbaPRyJyuERERbBOm3xiNRpaiIFZoYmJicPz4cUHVE45rgy3n5uYiPDycOXzHjx8Pp9OJ5557jqEVCSVXWVkpQBppNBq8++67ePXVV+Hz+QT35f+fHAqFhYV46qmn0Lt3b5jNZj+liB9Ra09hoxK6Uk44hUKBuro6VkmT71Dj/0vIAnLM0fqbPXs2fvzxR/Tq1YsVLvjjH/+I119/HQqFAjfccINgHrzwwgtISUnBe++9xz578sknkZiYyCrrtba24sEHH4TX62VOV6vVijlz5jBOpvDwcBw+fBhGoxH9+/dnpK3Z2dn48MMP2bUPHTrE0p7nzZuHadOmsfHR6/WYP38+/vCHP+DgwYOoq6tjHDDdunVjnEKzZs2CWq1GdHQ0W+fp6emIi4vDxYsXceHCBezevRsc11aR6fjx4xg2bBjmzZuH1atXw2azwWazoaioiBnW1dXV6N69OzZv3owRI0agpKQE58+fx+jRo+Hz+ZhhwR8DWhdWq1XAm0RErBzXBucXIzqioqKQnJzMUmnoHQMRRPMdo/QZn8h/4MCBeOqpp/DMM8+wvYiU3oEDB8JsNuPAgQN46KGH0NjYyAyR3NxcxoEUHBwMh8OByZMns/nO3xfJWdezZ09s2rQJr7/+OgAwPony8nL4fD7s2rULJ06cQFBQEBYuXIhXXnkFarUaCQkJOHnyJDN8+LwV1157LXNKE7l9aGgowsPD0draitWrV7MUI4vFArvdjgULFuDQoUNoaWnBmjVr2D5NxSf27NmDw4cPs76j/Zn20bS0NCQkJAg47ChtKS0tDcnJycjJyUFaWhrmz5+Puro6WCwWvPrqq3j++ecFa534sziOw7XXXsuQBuSwGTJkCL7//nts3ryZIZirq6vx8ccf4/z58zh16hTcbjc0Gg0WLFiAXbt2gePakEujRo1ilazI6Ul7KAUeyJE0YcIEts6++eYbLFy4EDKZDIWFhcyhR8/Nd3AbjUZGDi+WRRzHYcqUKaioqBDIXT5/yh133AG32804YsjBfPHiRaxdu5Y9s9FoxFtvvcWKCLz66qtsHsfHx6Nnz55sn5w7dy6mTJkimO8GgwEbNmwQEP+TQzk6Oho//fQTbrrpJsYvxC80sHv3brz55psoLS1FamoqXC4XM9qlDOixY8di0qRJWLVqFavAd80117B0wr1792LJkiWor69n5Oh79+5F165d0bt3b7z55pt48sknodFokJiYiNtuuw3x8fFITk6Gx+OBTqdDSUkJ4y1du3Yt2xO7d+8Og8HAHFX8QB8fjcEfJxo7saHLR3hR4yPyCK1PgTVqVF2wPaQv35HHd6bzi4PQeaRDDx48mAXhdDodFi1ahIqKCpSVlbH0PDqkiI8/++wzLF68GDKZDImJiaxMvU6nw8SJE/H555/jiy++YMUFKisr8fLLL+P9999HTU0Nli9fjnfeeQcymQzz589HRUUFFi9ezBzN8+fPh9vtRnp6Ot588028/PLLrApn37598eSTT2LVqlWC/u7bty/j+iT9nxydGRkZOH/+PO6++25ERUXBbDYjOTkZmzdvhsvlgtPpRLdu3aDT6dC7d2/069cPwcHBSEtLY302cuRI/Pjjj3j33Xfx9ttvo6qqClFRUXjqqaegUCiQmpqKAQMGAGjjDiotLYXZbGYZCEFBQViwYAG2b9/OnJo0Xna7HS6XCzabDfPnz2ep0VJ7UW1trR9KXWrt8IMx/LknRnWLm9FoRFNTk99cNRgMfnYHXZ/mL/85qqurMXbsWJhMJj9EEN8ZRe8YaN/ly3ePx8PWEuk1PXv2ZEht0l3tdjvS0tIE68btduObb75hc5LjOL/AKCHk+A6rQYMGMdoTuVyOw4cPA2irSEc2CQD06tULQUFBOHToEKxWK1JTU1lf0/NGRkYiNzdXoLt069YNN910E+O4pb3h5ptvxsCBA+F2u2E0Gtl8JKoEl8sFt9uNxYsXo0ePHkhLS/Ormnf1uHr8Gsd/vTNq1apVeP/999nfTz75JObNm4ddu3Zh7dq1mDBhAl588UV06dIFRUVFjBMmMjISer0ehYWFsNls2LVrF6tMQ0IpMTERBoMBY8eORU5ODhQKBcuzTk1NhcPhwIABA6DT6XDs2DE89thjCA4OFkBK5XI53nrrLYwYMQI1NTX4+eefMX36dCQlJcFkMmHfvn34/vvvcccddyAkJATh4eECpcJut2PgwIEoLS1lRJS0GQFtDouTJ0+ioqIC8+fPR0hICOx2O1avXg2Oa0sTIYJpq9XKjCzaSJYsWYIHHniAKdXkwIqNjfVDERHvCKE6+BsVCdW4uDi0trbi6NGjrEKgXq9HfHw80tLSMH78eNx5550YNmwYcnNzYbfbWTqfVqtlhLOnTp3C008/zTamkJAQqFQqxMfHw2KxMIh7UVERdDqdwFCdNWsWIiIiGBcKVWKjkqSkgBH/1+jRoxkyCmgjx3Q4HHjyySexdetW9puYmBh8++23uHDhAquixSf7o43H5XIxhZ6/UcfGxjISao77F4Hnpk2bsGrVKqxbt44JeorCUuThwIEDsFgs6NWrF+68804888wzqKioQF1dHT788EPMmzcPRqMRERERGDt2LABg5cqVeP755wEAffv2ZRvg3XffDQD4+uuv0dTUBLPZjOnTp+ORRx7BkCFDBApu7969GVw7kJJL15Vy8FCEWbxhExca/3f0f6pWxVcmHA4HoqOjmaOU7xANDw/Hxo0bERwcLPh86tSpAk6nAQMG4J///CcjgOU4jvF30HqgNBz6m1AV/GeRy+Xw+XzQ6/VISEjwixpHRkb6rR2xoUDKQ3h4OItoiWHz9H16ejpSU1ORmJjI1gHHtXFwJCcnw+1247bbbsOlS5dYKsLu3buhUqkwa9YsPPvsszhz5gx69uyJ4uJiQSozAAa35h+ff/453nvvPRw8eJChlciwIkj3pk2bAAC33norc7rdeOONzKn7zjvvwGg0IiwsDB9++CG++uorRhRtNBoRFRWFxsZGNDQ0YOnSpXA6nfB6vSgqKoJWq2Uk7PHx8bj99tvRpUsX9OjRAytWrGDIwYsXL6K1tRV1dXXwer1svZOz12AwsOpWtI61Wi1iYmIAADt27EBiYiK+/vprlkorTmfiy/OwsDCkp6dj1apVSExMRE1NDXN6WiwWpKamClJ94uLiBJV+UlJSIJO1VVEMxCvGl6n0f75Td8KECYxUPzw8HIMGDWJzYvr06WxfoH9XrVqF4uJilnK+atUqLF26FH/4wx8E3Hv8d/zjH/+It99+G/Hx8bjjjjsAtDkqZ86cCZVKhX79+sHj8eDFF19kFU4jIiLg8/lgs9lYat3IkSOxcOFCZGZmIicnByEhIQgLC2OooC+++AILFy5ERkYGNmzYwOQwpUp37doVI0eOxLFjxzB37lw4nU40NTWx9EuNRoPU1FTcdNNNzEggYyg0NBRDhw7FCy+8gB07dqC4uJhVhuS4tuqI33//PT744AOcOnUK3bp1w8KFC/HRRx+hsLAQer0e48aNw5EjRxhCii9LqLLjwYMHmfOc0B8k7wsLCxEREYFp06bh5MmTOH/+PEpLSzF79my43W6W0r9+/XqMHDkSHNeGgA0JCREgS2j+0JxxOp349ttvGZr3hx9+QK9evcBxnIDTj3j5+KmihJghmUzvRboPORyJC4zOIdoBr9eLDRs2wGw2IzIyEq+99hpaWlqwYcMGlv5qt9vx6quvsnmzdu1a9OzZk6W+hIaGori4mDkzfD4fc6jRHMzNzcXw4cPR0NDA9BOz2YyIiAhs374de/fuxXfffYfRo0ejsrKS7VODBw9mcygxMRFhYWHsvcXpQ16vF+PGjYPZbMa0adMQFBSE6Oho2Gw23HrrrZg/fz70ej1LzYyMjGQpqQcPHmRE+NHR0SxoYDabce211+KGG27ArFmzIJe3Vdv8wx/+gJ49e8LhcLCiMxzXhjinSmZer5fpXuTcTE9PZwFDcmQTkp0cScOGDUNlZSVby0uWLBHshYRKlJIzfHLrzsgjg8HA9lUygHU6HXr27MnWZGxsLLKzs5GZmYnMzEwYDAbs27cPn3zyCdLT0zFlypRO6fc//vgjxo4dy4q2LF++nBE6U+Xfzz77jPGCORwORmXw888/48MPP4TNZoNarYbL5UJwcDAyMzPR1NQEvV4PmUzGgooU0HrqqaeQlZWF/v37Y+jQoSgrK0NOTg5L6d+6dSvTr/lrqnv37iwt7p577mEVqgk9s3XrVhYoJtvjyy+/ZJUWFYq24gp//etf/Xgcv/76a+zZs4fx2VFRoOzsbCxbtgwPP/ww2yeIeH3u3LmYNGkSKyKSl5cnQNxJOaT5egtf5xETr0txO4l1QJI54vvwzxE7kNprfPnOb+L0Mo5rczAbDAY/3ayyslKA6gsODmZri4KohAyTy9v4ST///HO8//77yM7OZrx5VqsVO3fuhNFoxJw5c+DxeGC32xmQYfHixdiwYYOfHmiz2eB2u1mRFI77F+9nTEwMsrKy0NTUxLJd6GhtbcUTTzzBdCcK6m3cuJE5t4KDg1kxI61Wy1BOKpUKZrMZGRkZKCsrY2n1NIYDBw7EqFGjkJ2djbKyMrjdblRUVOCOO+5gRaqoQiPpW1cdUVePX/v4r3ZG/fnPf8bgwYPZwvjwww/ZBjNhwgRce+21kMlkWLJkCV588UWkpqayaEVQUBAjolu7di3Onz+PF198Ef/85z9RXl7OBMXevXtx4cIF3HPPPcjLy4NCoWCRDdqQx40bh/T0dFitVgwfPpyVw6ZrENn4Pffcw56VqjKEh4cjJSUFtbW1qKurwxtvvMGMF5PJhAMHDuC9997Dn//8Z3z11VdISUnBc889J+iHP/zhDwK0R15eHj755BNMnjxZsCnExMTAbDYzBw8JSiJV5cNV+YpJTU2NH/pDoVCgtraWCULa7DmOw8mTJ/H111+zawQFBSE0NBQ5OTnIzs5GWFgYtm3bhlGjRiEyMhILFy5kUHSz2YzMzEzU1dWhpKSEbUBWqxVmsxnPPfccZDIZ2+j5yhRFnOVyOUaNGoWHH34YkydP9iv7arVaMWnSJCxYsIAZ8BcvXmSGUPfu3TF58mQGsX7ppZdYVDcnJ4eluqnVahw4cIDNA41Ggx07dsDtdiMiIoKVVc3IyMDrr78uSBmkcveffPIJamtrmWEP+EcJ6e8zZ87A4XCw1BxxhHDBggUsKp2RkYG4uDg230gRzczMxOnTp3H99dczBxqlcW7fvh19+/Zl6Zg01vHx8YKqd3zlQEy6SnOf0g3T0tIEfBZ0XY1GwwwrKYVEpVIhNTUVsbGxmD17NlMYKMqkVqvZ/81mM6Kjo1m5Yn4kv3///gFRSTQvlEol5s+fjy1btrCKiBQZouvzFR9SPqkP+EpaUVGRZAVKm82GpKQkREREMMcNfUdKLkGuKdq4fv16mEwmhlQhhXXt2rXYv38/Ro4cicbGRlRWVuLmm2/2UxAeeOABhIaGwu12IyYmBgUFBZcd1Tp58iTq6+tRXl6Om266CevXr4fdbofFYkF1dTXOnj2L77//nqEvsrOzmQP0xIkTUKlUjPfgyy+/RHBwMEPMUKnxvLw82Gw2hIaGIiIigjnuSLlMSEjAnDlzcNttt6FLly6YNGkS3njjDTQ3N6Nv37646667EBsbC4PBALvdjueff15g2B48eBAfffQR8vLyWMRw2bJlaG5uxujRo9GnTx/m/M3MzGR8IAqFAqNGjYJOp4NarWbOrvT0dGRkZODmm29GVlYWxo4di9DQUGawWywWAdKD5hiliGdnZ0Ov1yMlJUWSoJhaIK4Omrc7duxAnz590NjYiNLSUoYgI5QcVcV0Op0MMcNPHaB1QuuTr7gvXboUdrsdOp0Ob7zxBr766ivm4CKk5OTJkwG0Ocz/9re/4dSpU2hpacHp06fh9XphNBqxfv16tLS0oLy8nAVUNBoNZs+ezYJI//jHPzB16lR069aNFVuYNWsW6xtaF263G/fffz/efPNNNDQ0ICEhATKZjBkXXq/Xj5g5NDQUXbt2xYwZMzB48GAcOnSIzauSkhJ8/fXXWL16NaZOnYo1a9bg4sWLaGpqQmhoKOvn1NRUvPvuu8xJTVFx4npJTExERUUFc3qo1WpMmjQJ7777LtLS0tg+39DQwByn5FBYtmyZwNlPhRsyMzNht9sFRn96ejrOnDnDuBKXLl2KP/3pT3j//fexevVqpptQVUW+fDEYDIKULP573HbbbWxP8Xq9SExMxFtvvYV33nmHkd/HxMSgoaGBpf8dO3aMoZFuueUW/Pjjj+jduzd27tyJt956C0OGDGEOgx9++AHXXnstDAYDqqqqcOrUKcbpePToUSxcuBAcx7GIvHiP2bZtG3788Ufs2rWL6RlarRaZmZno06cPS9Wh4AbNzbfffps5/PhGLB8tQshGlUoFp9PJ0CQDBw7EG2+8gcLCQjz22GPo1asXCgoKcN111zHHKR0vvfQS3nrrLRw7dgxlZWW49957MXPmTMjlctTV1bF7eb1ehISEMH7KpUuXQq1Ww2azoaSkBFlZWThw4ABzTpDTR9wnhJBWqVTIyspi1Zv5AY/09HTBe/L3XZfLJZmySGlPfNkg/j3HtVXlowIGHMdh5MiRGDRoECwWC4YMGcJSYwk9t23bNgwbNgxpaWm477778Pnnn/sFRKSOlpYWnDt3Dr1798aWLVsAAI8++ihMJhPjG71w4QIuXbqEf/7zn1i9ejWefvppJocAYPz48dDpdHj44YfR2tqKL774AoMGDUJKSgpmzZqF8PBwVFZW4q677sKIESOQmZkJoI2wX6fTISwsDIWFhaivr2eOt27dumHGjBnQ6/WIi4tjhOQmkwl33303WltbcenSJSxbtkzg8C0oKIDJZGJzgwIvhYWF8Hg8CAoKQlRUFAYNGoR3332X6XwKhYIVEjh48KDA0ezxeJjTLSIiAtHR0SgrK8Mdd9yBBx54AF6vFwkJCXA6nX4VQznuXwhMnU4Hs9nMinfQ+FNxDHLY8e0GqRYIeSRG1vFtCXLQ0XdSTiRqXq9X8Ft+mir/3dxuN/Ly8iQRWvQsxN0kl8sZPUNTUxMOHDiAbdu2MUfMwIEDMX78eMTHx2P06NFwOp2sqvW8efPQs2dPVFdXMyQsx3GMv5Yf3CW5Rb8l553T6UTPnj2xfft2Nm8vXbqECxcusMAeBeNkMhlSU1MF+7gUKp90cKoeT+cFBwfj4YcfxqVLl/D8888zfs4dO3ZAoVDA5/Nh3LhxaGlpQWtrK+655x5UVlaioKAA5eXlbL1dPa4ev/bxX+2MAv5FSvjwww/jq6++wunTpxncc8CAAcjOzoZMJsPMmTNx3333QS6Xo6GhAYWFhUy4+Xw+fPLJJ9i+fTvee+89nD17lhF2V1RU4MSJE3jkkUdYFK+4uBiPP/449Ho9iouLoVAoWGWfmJgYHD58GNdeey0j2OU4jhkDBL+88cYbwXFtEcQJEybAYrEgLCwMN910k8BISE5Oxi233IK5c+eipqYGXbt2ZU4Tevfjx48zRFNmZiZCQkJQXV2NiRMn+pHkqlQqP34Eeo7Ro0dj2LBhAiWEHFkhISEoKChg6Tsc1+YYmDVrFktNkclkWLVqFYC2vP9FixbBZDLBZDJh7ty5eOyxx3Dp0iUMHToUI0eOZFFDjmtLZ6H0nT59+rBKFatXr0ZMTAzbnGJjY9m5/OdPS0vDn//8ZzgcDphMJuj1eqxZswYAsHjxYrZJErHnnj17WJlSMtC//PJLXHfddaz0cnBwMBYsWIBz587h2WefhdPpZNWeiFfn0qVLrI/y8vLw9NNPswpDVP757Nmz2LdvH9s0Bg0ahKysLFgsFpbHTwI+kJOgpaUFa9euhd1uh8lkYmk0FosFy5cvxz//+U98+eWXLJU0ODgYf/jDHwC0OWnJWVBeXo6QkBCMHj0a69evZ9WMRowYgd69eyM4OBgvvfQSFi9eLKkMEDqP49oi+PxKLRzXZtD6fD40NTUhPT2dQcGJVFWn08FkMsFmswkI/sn4J6NIo9Fg2LBhSElJETiDiC+G+GDo85iYGHg8HkZgy1dKJk2aJHCaUrVKmrNGoxFHjx5lPBLh4eGoqKhgTma+E5NQQmQoxcbG+hGuy2RtXFJS0UNCFFosFiiVSvYONIe0Wi2LMlKaWnFxMSshrlKp8OKLL+Lrr7/GBx98gJ49ezLSf6njs88+w+uvv46XXnpJoOh05vjss88QHR0No9GIVatWobW1FYsXL4bL5WKODYvFgi5dujACYXIUk1OH0FkUTdu0aRNTpNRqNaKiogAAQ4cORWJiIlOYNRoNc07HxcVhxowZAIBdu3YhNzcXubm5yMnJgclkQn5+PtxuN4sq3nfffcww9fl8qKioQE5ODnPOvvzyyzh9+jTmzJkDm82Gm266CZs3b2bFDCIjI1mVsvDwcKjVaqxcuRK5ubnM2UQQ/VWrVjFCb4Ls9+zZE+PHjxekdxgMBoFRSfOIotGBosPUn6TkEiJq+fLlOHLkCEwmE95++238/PPPWL9+PQwGA8LDw3HgwAEcPXqUoRDsdrtf6is57wsKCgRpDNHR0SztISYmBlqtFqWlpZg3bx5L6e3VqxfUajV2797N0orpaG5uxhtvvIGYmBjk5OSgW7duSElJYfx3hCbdtm0bm5OnT58Gx3HYvn077r//fvTq1QvPPvssiouLGcKNiNg1Gg18Ph9+/PFHzJgxg3EqdenShRnIVBCBkIQ+n48p/7fddhsz/ObMmcMMMZPJxCp+TZw4ETabjaU0VVRU4L333kNtbS0bK/5eevDgQTz77LOCalb0ewrSREVF4YEHHsA999zDnM+HDh3CnXfeyWSFXC5H//79kZOTw+YPGbQpKSn4y1/+gl69eiEjI4PJJT45dbdu3RAfH48tW7YInJnEocXniOG4Nke7UtlWjZdSfYKDg3Hq1Cls3bqVFQrJzMxEjx490L17d2zZsgUXLlzAs88+C6VSiZSUFPh8PsTFxbE9tbm5GXV1dQgKCsLzzz+Pu+++m+lUxOdpt9tRXV2N77//HvX19ewZBw0axHQtQuEBbY6HNWvWoFu3boiNjWWy02Qy4fHHH8f58+cZZyPJa7VazYxOvoFLegC/fyIiIvDTTz9h7dq1DD3mdDpRUFDA0lM+++wzTJkyBSUlJcxxSvvzqVOnkJeXh4iICFaNmcaIvxcUFBSgtLQUQUFBLLWR49qCPomJidi/fz8bX0LQlpaWIjExkaFoKUUyIiICzzzzDAvCxsTEsMANOafEsqWiogIDBgzw06GokiP9LebeIWd7Xl4ec9rRc8ydOxdNTU34+uuvMXHiRGg0GlRWViI5ORk1NTXYsWMH6v4fe28dFfW6to/PMEPPDEN3DN3d3Y2AWISBGNiJitiI2A0qBrbYvd0m9jbZttvurW4bVFDi+v3Beu4zA7jPPu/3nPf3nrX2sxZLHYeJTzzP/Vz3FSkpcHV1xefPn9HU1ITly5e3aqy2FREfGhqKqqoqHDx4EAKBgCwGvn37hrKyMpw8eVLm9+vr63Hjxg0y//b396dz9fLlSxgaGsLGxgb+/v44fPgwjIyM0KNHD6xevZrYx2x9Y74+HA6H2Kxsbfbw8MDw4cPpura0tIRAIMC2bdswdepUnD17FsuXL5eRaXl4eOD06dNISUmBj48PBg8ejGnTpuHmzZsIDQ3F4sWLERISgt9//52+E/NxHDhwIBYvXgxjY2NoaWlBUVEREyZMAACMGTMGtra2OHnyJJydnem7szlFT08Pfn5+MDAwaHU9hIWF0XONjIxkgloGDBggA2L/yHeN/fwZu67l9cY+h7KyMrGu2/o96fpKUVGR5L3SbEd2jUo3Hvl8PlxcXIipK/2aDGjk8XjIzc3FmzdvkJeXBzk5OTq3cnJyMnUZCyNavHgxrZd6enpwd3fHzZs3aQ/ImPSMoc2am2pqaiTFlZOTQ0BAAM6ePQsOp7lZOWXKlDbrsytXrqBfv34EvAmFQpw5cwaDBw+m75OUlARzc3Oa41ii+bhx4yASiWBkZISJEyciKCgInp6eWLp0KZqamvDw4UPyyGTG6yNGjMClS5dw7949JCQkoKioCLdu3QKXy8XBgwf/ad349/h7/E/Gfz0YBTQvMCYmJujevTttRLS1tdGjRw+cOnUKubm5ZAzu4+ODCRMmQCAQIDY2FleuXKFCNTk5mRa2PXv2kLRJSUkJEokE9vb20NbWpkSE9evXIy8vj5JSWAKDkZERRaZv3bqVFnUHBwcoKioiJSUFaWlpsLOzg56eHmbPno2FCxfShOnm5oarV6/i+PHjSExMhIuLCwwMDODl5UXAifSEVVpaCgMDA8yfPx/x8fEIDAyEhoYGNDU1ceLEiVbdYj6fTyaf0p4nCgoKmD9/Pvbu3Qs7OzsZ9J1tqIKCgnDkyBH6Tnw+nyQTHA4Hw4cPR01NDRYvXoy9e/fiyZMnuHv3LgFojY2NCA0NpQSsLVu2gMvl0udl6RIcTnPH7fbt22Rmywo6aUCEfbbr168jJiaGCkiBQAA7Ozs8f/4cQDMziCWV+Pr6Ijk5WaY7N2fOHPj5+UFdXR05OTnQ09PD+PHjwefzkZ2dDQDIyckhk1llZWUMGzYMa9asAZfLRWRkJKysrKCrq0sJN3fv3kVtbS3q6uqQmpoKZ2dnzJs3DyYmJhAIBFBUVISJiQnq6uqwcuXKNuVSwD86hAkJCSgtLUVVVRXCwsKoKGXHbdGiRairq8O5c+eQlZVFBr3GxsZwdHREZWUl+vXrh02bNuHVq1cA/tE5VFNTg7+/P8rKyjBr1iwq4lsWEsyX4EfFAjtvT58+RXZ2Nm3C2fXECoGWnWoulyuTZOfv74+PHz+iuLiYjF2lCxhWeLB7lH0HBub8yDicfV4GfLVr1w7x8fHQ1NSEk5MT+Quxe0aapSPt2yTdJWxZ4PF4PAJtW3pNMZmJtDcIK1ikCy5p3zmhUAgPDw/qcjHvB39/f5k54a+wnf5KR5qNpqYmXL16lUwrmUfXli1bMHXqVPKe0dXVpespNTWV5Ivz589HUVERvL29CRiurq6mdL5Tp07ByMgIo0ePRkREBPLy8lBWVgZ3d3dUVFTAwMCAwAJnZ2f6XLt378a0adMwYsQI7NixA5qamsTAGjhwIJSUlKCoqIj58+djypQp8Pb2hpOTE+bOnYu6ujrU1tZi9uzZcHJywpYtW8g0WE5OjiTZFhYWBETo6+vDx8cHTk5OSEtLg4WFBXg8HiQSCWxtbTFnzhyS6DA5FwOZWGEvDahyOM0Msj8r6tm57969O3bv3o0ZM2YgNzcXrq6usLKyItD4yZMnMnT+WbNmQSAQoGfPnujduzd69uyJ1NRUDB8+XOZ+ZmC7j48PLC0t6Z7r3bs3MjMzCehbt24ddu7cibFjx5I33bZt2wAAI0aMAJfLxb59+9q8dpYvXw6RSASxWIz4+Hh8+vQJ58+fB4/HQ3BwsIx3GWN6MODAwMCAjIal5YzMi05NTQ1Xr15FfX093X+6urq08RCJRBgzZgxJwsLDw2mty8vLw5EjR9CjRw9ik33+/JmYxDExMQgPD8eQIUMgFospCdLY2BjDhw+HWCwmsJl52Ojo6JDZLZNqMQYkS6Vj97u07xtjN7C5r+Wmjc2TqqqqcHNzow1+fX09goODZeZE9lzG2GLJWtIbSR0dHdr0GRoawt7enuYoxtB0dnYmUIrP56OyshLnz5+HmpoaXF1dcePGDZpvLl++DD8/P7In6NevH06fPo2mpibcvn0bISEhBCozoI7NvTNmzICpqSlcXV0xduxYSmraunUrHj58SKwyNTU1PHr0CBERERg2bBiamprw9u1bBAcHQygUwtXVFevWrcOePXugqqoqY46sp6cHBwcHaGpq0rzO4/Ggp6cnI1G1sbHB58+fKTGvqKiI1oqRI0dSvVVfX09BEGfOnJGZUxsaGuDl5SVzTlhTikl42Dk6dOgQ+coMHDiQ5gMtLS2EhYUhJiaGvoOamhqMjY0xfvx4kqlHR0cjJyeHpNEcDgdTpkxptRa3b9++FQjQ1pr9z/5fuk5k16iHhwc0NTXh7+8PLpeLFStWAGj2qLS2tsajR49w+/ZtODk5wcfHBzNmzACfz8e6deswevRoiMViPHz4UGbOYGPTpk1YtGgRACAlJYXsGZhnFwA8f/4cYWFh9L5s1NfX48KFC+jUqRMBaMwnCgAuX75Mdgks1dHY2Bg9evQgmwg+n4+kpCTy4OFwmkFEafsAOTk5bNy4Edra2oiJiYGCggIBN6qqqigtLUVpaSml/rFr38fHhwDks2fPorq6GgkJCYiLi0NjY6NMY4k1nXft2gUTExMYGhrCwcEBYWFhGD58OOzs7ODs7AwNDQ1Kd7x+/ToyMzNJMisQCBAVFQUlJSXk5OSQNYD0ueZym6Xj0mnHzFtUOim2raaJpqZmK/aelZVVm4x05i3L4XDI6oCtj2xObOlTxeZ89pi5uTmcnJxkXp/d12yeY4+bmppS7Sh9/bKGpkAgoPv40qVL1NgwMzPD2bNnUVRURGE+Dg4OxIi8efMmnJ2dIZFIoKGhAS8vL/j6+qKiokLmc8nJyWHmzJk4evQosUzZmmFkZISHDx/i6tWrOHDgANVvu3btouTQqKgomTQ/1rydN28eyVfZe9na2iIoKIhSF58+fQonJye4uroiIiICjY2N+PbtG7KysuDi4kI+ueXl5bC1tUV0dDQqKiooJd3Q0BBubm7EvLOysiK/2r/H3+PfPf6rwaj09HQ8efIEQPMCw9IxLCwscPz4cRgbG8PJyQk6OjpITk6mBZShvw0NDfj48SNiYmKIVdTY2IhHjx7B09MTERERVET27dsXCxcuhEAgQFxcHCQSCSorK2FgYIBhw4bRhODo6Eib0Rs3btBCIi8vTxtl6UUgMzMT9vb2iIuLI/mKpqYm3r9/jwsXLiAyMhISiQRTpkwhSRlLWWCGr6GhobCwsMCHDx+wc+dOODg4UEqERCIh2ZV054Gl2DDDTumJfMyYMUhKSpKRI7ENeWJiIuLi4tC5c2c4OzsTc2Xx4sU4cuQIrl27hqdPnyIuLg6rVq0C0Lyg1tTU4NSpU7C3t4dIJEJISAhGjx6NrKwsSq1gIBKbYM3MzNCvXz84OTnJFNxMNiO9yLGFRV9fHwoKCti9ezcZg//xxx/o3r07eDwe1q9fjydPntAi39TUhFGjRkFLSwuenp4YOHAgLl++jKSkJMTExKC0tBRcbnMKBTt/LOVQTq45WtrZ2RkeHh5YuXIlHBwcwOPxMGrUKACgc5Wamork5GQ0NTXhzZs3tNm7efMmhgwZAgUFBWzfvp2u7bY6hCEhIbh48SIOHjwIJSUlmJqa4tixY3j+/Dkl9s2cORN1dXUYNWoUTExMoK2tDRUVFYwdOxZfvnyRScF49+4d+ZtcunQJ27dvx/PnzzF06FBoaGjA29u7TfPFtopbxuBghaunpycxMdjizp7bpUsXdOvWTYZiza4xBv4YGxtTETd37ly8ePEC/v7+dD/Y2NigoKCANrDSn8XAwADXrl2Di4uLDOglFArpuXp6egQqSwMFpqamqK2tRVRUFHnyrF+/HrNmzQKH0wyASSfYSBc27H6Rk5Oj64N5aLDXZwbW0seNpee09GhITEykLtvAgQPR0NCAnJwcBAcHY/ny5Th48CCdz383dfr169d07zKWi0gkwrx58/Dy5UucOHGC5DuqqqpwcnLCoEGDYGhoSJ5Z/fv3x5EjRzB48GDY29sjNTUVkyZNgqqqKrS1tfHmzRt4enqSVHnChAkwMzNDx44d8f79e/LCMzAwgIWFBXJycnDixAm8f/8eAFBYWIhNmzbh2LFjrQDCkpISAM2+aIGBgbC2tqY5FAA+ffqEAQMGIC0tDY6OjlBQUICKigrk5OTg7+8PQ0NDKrBZZ9PBwQFmZmZwdXXFsWPHaN5k59fY2JjOF5fLpYKcFf7Sc5ahoSHdE1wut5UsgbHrNDU1MXr0aDg4OGDkyJH49OkTXr58ibi4OGhra5OUWDp559SpUzhy5Aji4+Px+PFj2NjYQE9Pj44PYx+ye5kxLNq3b4/9+/dj//79MDU1haenJwFd+/fvh6amJvT19UkyAzRHpP/o2mPeKUze2LlzZ3z+/BmnT58Gj8dDUlIS1q1bh0GDBtFalZ2dDW1tbSgoKBALODExETk5OcTEUFJSwrx581BXV4f8/Hy6DxkIzeVySTbJNszS4SBaWlrQ0dGBmpoagbm7du2CmpoaIiMjyTxaJBLBw8ODWMfS96tAIEBRUREMDQ1lNj/t2rXDs2fPMG3aNPj4+EBOTg7h4eHYvn07hg8fDi6XCzMzM8yfPx/du3en+YudI/YeAoEAXbt2RWZmJrENDAwM0KFDB9TW1uLEiRNwd3cnhnfLzRaHwyFfESbZ4HA4yMrKwt69e2FqakoyMMa45HK5lD6ZlZWFoUOHIiUlBRoaGrC0tIREIoGnpyfS0tJIYikdFrNs2TJYWVkhNTWVmI5MBqOhoQE3NzeMHDmSPl9ycjIePnyIhIQE8kQzNzcHn89HTEwM/P39IRAIqDFibW1N1/nVq1fx6dMnLF26lIzBFRQUMG/ePDrO0sciIiICmpqaZI7O7gV2jy9fvhz19fVYvHgxMjMz8enTJ1y6dAk8Hg+ZmZl4/PgxzbV37tyBtbU1zp07R55sDx48QHFxMdTU1JCVlUXBDTweD9HR0VBWViZgmsNpBqDCwsIgFAqpgcXYONKACJsz9PT08NNPPxHTX1tbG+vWraN4+oyMDGRlZZGMiRnqMzkQ2/C3XLfZutvyMXZNM49VOTk5GX9FLpeL48ePY+7cubCwsIC3tzf4fD7GjRuHpKQkhIeHU7167do1ZGVl4cWLFyRdU1NTI/ZPQ0ODTJPkxo0b5DW1Y8cO3Lx5E97e3tDX16fk0w8fPpAHYssmDJMFvn37ttU5ZGPnzp1QVFREYmIi3r9/T4CUUCiEs7MzVFRU0KFDBwKo2T3I7AGYbyUDhd68eYOSkpJWx5LLbTY9Hzp0KAGMIpEInp6esLCwwJ49exAeHg4HBweaa9mxkK4Bt2/fjqKiIqxZswYXL15EY2MjHj58iK5du0JbW5u8AsvLy5GXl4ehQ4eiXbt2MnOip6cnpk6dSteWNFNWLBbD2dlZBqzm8XgoLy/Hjh072kxpa8kAl54HGQOWzZfS82dLCbF07SfdaGZAvjSIy16DJRe2vG5jY2ORkZEh8xifzyelhampKeTl5SEWi+nc1NbW4vXr14iJiYGhoSFZBSxatAhHjx4l8C4hIYEYkY2NjXj16hUuX76MWbNmkQVLU1MTfv/9d2oWM/Pwy5cv48OHD1ixYgXS09MxZMgQYviyUVpaiokTJyIyMhICgQA9evSAkpIStm/fjuDgYBkAUdrvjPlEcTgceHt749OnT/j8+TNKSkqo9mZp62zfI5FIKOiorq4OVVVVaGxsRH19PR4/foxffvlFRu7KmHcsKOvv8ff4d4//WjDq06dPSE9Pl4lsPXv2LEWhjx8/Hr169YKcnByCg4OxadMmWlDs7e2hq6uLgQMHYsiQIWSkLRKJsHXrVipOWWfQ2toagYGBePbsGTw8PBAWFoagoCBa6M3MzKCrq4u5c+fi69evBG45Ojri9u3bmD59Or2+tIGqpqYmKisrUVFRgZCQEPj6+kJBQQFCoZBAjsjISJJBtDS1GzVqFLFf5OTkMGLECLx48QLt27eHsrIyAQ2MdcKSeLS0tGBvb48OHTpAUVERu3fvBpfLRUVFBVHbtbW1sWDBAowbNw6ZmZnQ0NCgDom1tTUllwgEAvj7++PNmzeor6/H27dviZ3FioSmpiZUVlbCwsICfD4fCxcuxKxZs8iHSFFRkTr+CxYswMaNG4kGyza8rMPNClMul0sTJHve+PHjsXz5cujp6cHU1BQbN25ERkYG5s2bRx0pNhhL68iRIzAxMcHp06dhb2+PvLw8AM3diYSEBKiqqsporp2dnamjqaSkBG1tbRw4cADR0dEUR62uro7Xr19TMdbY2EgMDVZks4KTdYSEQiEePnwoI78Emov98ePHA/hHh1BZWRlOTk5ISkpCQ0MDdQijoqJgZ2dHTJ9Tp04BAAYPHkyAE9Bsjl5WVoaAgABKKzp16hRu3bpFbAYmmdi0aZNMl5ZtcloWJTweDyKRCD4+PjA0NCRgT0FBgTp0rKDg8XjYtm0bli5dSvIatklm3kSsQGHxwt26dUNqaipcXV3JCJnR6dm9xD4POycrV66UAYLU1dURHh6O/Px8CIVCJCYmIjQ0FPr6+gSQuLu7Y+HChTA3N0dqaiocHR3h5eWFsrIykvqxeaQl0OXm5tYKXONwms2ObW1tSSrJCgn2HHl5eSQmJtL9p6ioSDLFo0ePYsiQIRAKhSgoKKCCh91XbF74d44BAwYgOjpaZoPQtWtXAnwdHBxI6vrw4UNoamoSu4vRuBcsWAAul4uePXtiw4YNmD9/Pry9vREcHAxfX1/weDwyV5VIJHj69CkkEgmUlZUREBCArVu3IigoCHFxcXjz5g1KS0uJhu7t7Y3w8HBwuVwUFRXhzJkzWL16NQFBIpEIZ86cQVVVFYKDg6GmpiYDrKSkpCA8PBwikQhr1qyRAQrZfR0TE4MxY8ZATU1NhsXm4eGBuro6NDU1obi4mM6Vs7Mz3r59SwAq28Cx88w+G5NnSoOXrHBn0c5MLqWkpITU1FQq9JlxMgA8e/YM8fHx0NXVxfXr1wEA06dPR4cOHXD27Fl07doVqampuH//fiuTck9PT+jo6EAoFJLBepcuXaCkpISIiAi6rtkGh73f6dOnkZycTExR6cEAqbaYd1VVVZBIJBAIBEhPT0dNTQ1Onz5Nx8fc3BzOzs60vs2YMQNGRkZQVFSEt7c3DA0NcefOHUqD1dPTw/79+4l1zKS/MTEx6NOnD0mDGfORrTvKysooLi7Gs2fPKG318+fPxNBbvHgxvn//jj59+sjMbZ06dUJubi5MTU1pc8W62+np6ejduzfNiSoqKhRdX1BQAHt7e4SFhSEpKQnZ2dnw8vKCl5cXya179+4NHo8HAwMDzJ49Gz/99BP51QkEApK8Tpw4EVxuc+T406dP8fz5c4wdOxZPnjxpxRRmPwYGBvD09IRQKISFhQVEIhExTBwcHLB8+XIMHToUHh4eyMzMxNy5c6GgoICoqCgKKKisrMT27duxZMkSFBUVYceOHRT4cfz4cQqLYeP8+fN07saNG4fu3btTyAhjiw0ZMoSuxTFjxmD69OnQ19en9FK2puvo6ODcuXMoLy8n8Pb169cYOnQoQkJC8PTpU9TW1uLhw4d0/OPi4sgInqWiBQYG0rzAztHYsWNx7NgxPHr0CMOGDYOioiIqKiqwZMkSSCQS9O/fn65TBpxu2LABJ0+eREJCAsn27ty5g44dO2LChAkwMTHBqFGjZOZ3dr3k5eURU1Ka1SHtsZOTk0PXLgMLWkpofX19sXfvXpKu7t27F8uWLaNAHnl5eaipqdH8wT5HWFgYeaiyuYDL5cLGxkYGQGmr0SQnJ4fAwEACG+zt7YldfPToUSxfvpwkv0pKSvD19aW5VrpeBZqBIi632Y5hzZo19DibN0aOHIm0tDT4+/tDXV0dNjY2WLJkCXr16kUgs7+/P/z9/eHm5tYmK1j6HLYEv6XPoaWlJVxdXZGTk4NVq1Zh1KhRxIz39fWlBhHz/eHz+Wjfvj2BpPPnz6dGcV1dHUaOHAkutznEhzVVGeh/7949AEBWVhaB5woKCnB0dERqamorxYN0DThy5Egyp7azs0P37t3x4sULNDY24unTpxg5ciQ8PT2pLho6dCg6dOhALC5WnzFVhrW1Nfh8PlatWkX+cy1/GHtdS0sLS5cuRWJiIlktSD+vLTYSA3gVFRVJZt3y9X/kO8Ua8v/sh8/no3Pnzq0MzRUVFTFr1iyZlEcO5x8WCyYmJsTk43CaGVW+vr6wsLCAhYUFDh8+LAN+lZeX48GDBzA3NyfPQMakApoTGe3t7aGqqor+/fvLNGpYM0JfX18mBbupqQnV1dUYOnQounTpgsbGRixduhRCoRBbtmxBdXU1paGGhYVh9OjR0NfXx/jx46kRqqioCLFYjPz8fHTr1g1DhgwhYHDevHmor6/H7Nmzoampie7du9O1xa6zzp07o3///q3W6pbr940bN9C1a1doamoS8+7v8ff4T4z/SjCqpUfFkiVLUFJSgvDwcBw6dIi6Qk5OThg7dixSU1Nx9uxZxMbGIjAwkHxGYmNjkZycjLFjx+Lhw4fIzc2FUCjE7t27KcmNSakOHz4MAFi1ahX8/PwQExODoqIi8g+Jj48HAAJkGC3b0NAQ3bp1o8QWBwcHmcXf2tqa5Arv3r2DpaUlpk+fjoMHD+LWrVsy9HDp8fPPP8PAwAAVFRWor6+nSGiRSEQLtXRh4ejoSMCDj48PLRCqqqo4evQobG1tcfXqVTx48IAWky5dutCiyJJmGNvj559/BtAsmWEFiKurKwIDA+Hq6tqqSLhw4QIsLS0JIOnRowe4XC7RyNkku2bNGjQ1NWHevHk06SYkJKBnz54y/lcqKipITEyUAYuUlZURHh4OiUQCX19fmJmZUUfY1NSUgEsG4ADNk7K6ujpu3ryJoqIiSCQSnD9/HgBw79497N69mwy2pbs9mZmZSEtLo+QYf39/WFlZgcfjQVNTEzdv3pQpkGpqalBUVITs7Gz06tULz549Q3h4OBWAR44ckVksgOaFQCQSQVdXFzt27MC1a9fg7e1N31dfXx+PHz+mDmF9fT0GDx4MNTU1JCYm4tOnT9i2bRvEYjFKS0vR2NiIEydOYNeuXZg1axbatWsHT09PGSNeRklnPzY2NuRvI+1BIt2NYcUB2wAlJiYS+4B1b5KSkui7smuvR48e5AHA4/GwZs0aLFq0iOjMHE6zYXxLrx3msSPtF8C6yux5UVFRGDBgADgcDvk08Xg8BAQEAAB5ePXp0wfdunWjlC8GKFpaWsLFxQWdOnWSkc2xIiU2NhaGhoawtram92SJbSwJSUVFheQ1Lb1amF9U165d6XwaGhrSxqNnz54Qi8Xo2LEjDh8+DFNTU/D5fCxfvhxA28y5f9d4/vw5XYefPn3C+PHjoa2tjeLiYlhbW5NvyaZNmwAAERERlI44YsQIbNu2Derq6hg3bhwlWVpYWEBfXx/Lly/H27dvsXjxYjoO/v7+CAgIgLW1NSZMmACRSISCggKZzty7d+8wa9YsGBgYyICaLAygsLAQRUVFMn4+zAyVbY4aGhpw+PBhZGdn09yXmJgIGxsbiEQipKenw9LSElwulzayHz9+xJ49e9C1a1eEhIQgNDQUFRUVePbsGSIiIpCSkkLsJ0NDwzYlogMGDMC0adOoQJbeqDLZDZtXQkJCKH1JLBZDLBbD1NQUHTp0QF5ensyc8uzZMyQlJUFOTg4JCQmQk2tO72NAR0hICAYOHChzXzCpuKamJjETMzMzqbHC2DYWFhZwd3fHiRMnZK61sWPHIjg4+IceZWycOnUKz549o3+fP38egYGBsLS0RO/evfHlyxeUlpaSn4m/vz9u3LhB3VkW8KGjo4OOHTsiJiYGKioqGDhwIMlVpL1D2Hqrra0tw1YLDg7GrVu3EBYWBgcHBxw9ehTv379HQ0MD1RHDhg1DRkYGvnz5gqamJpIkysnJYf78+Th27BgZFbMUOrFYjN27d5Pn4IULF2QYCJs2bcKUKVPg6emJjRs3wtHREf7+/vD09MTOnTvB4/FgYWGBoKAgREZGQkVFBaGhoViyZAl+/vlnyMnJQSgUIjs7mxJVFy5cSGDigQMHiBXH5iw2P0tff6z7zuakuXPnYsCAAeDz+dDT0yMmyO3bt9HQ0IDCwkL4+/sTMFVQUADgH2ExzFT36dOnBLoUFhYC+IecnIU4JCcno0uXLgTc6evrY+rUqaivr8fEiRPp/jc3N0dcXByCg4NhbGwMdXV18tFs37497t27h0ePHiErKwsPHjxAaGhoK5+g6OhoWusZ0MPn8ylVbOrUqWRmLC8vj/DwcFRXV9NrDB06FEpKSti2bRvWrFkDKysr9O3bF1++fCEwg4HrPXr0oHrs+/fvyMvLg56eHjQ0NFBQUEAG/8zfjF2jLOGX3f/sWmUm0uxP5nPm6OhIrK9OnTpBIBAgNTUVjx49wq5du6ChoUFMWVbzsnPOErXYdcCuCfZ52LXaElxo+cPW665du4LH42HEiBGU3KuiooKQkBD89ttv+Pr1K37++WfyJmTeTS3BlRcvXuDSpUuYPHkyBAIBli5dSv9fXl4OsViMy5cv4/3793j58iWioqIoXbCsrAzTpk3D5MmTsWLFCmJUtcXM/GfnsHv37mhoaEBVVRV5IHp4eEBBQQGJiYl0fPT09MgjlMNpTu7l8/lYsmQJvn//jr59+xKrnsmppkyZQmzXBQsWkCcbG+vWrcPx48exfft23Lp160+9HK9evYrExERUVVXh8+fPKC0tRVBQEFJTU/HixQtaB+Lj4yEQCHDu3DkAoBRcDoeD0NBQGbsAc3Nz6OrqQklJiRiFbZ17dh8xIDcsLAyJiYkyAU/S1wm7vlpKg0UiETUVf/Q+0hLjtgBRFhjEGFTs2p07d65MMh277xngxvZEhoaG8PLyIvYzn89HWVkZioqKMGLECJKsf/r0iQA6tofcuXMnHj58CGNjY6iqqlIKtjQrtKysjObf6OhoAqyY55iNjQ169+5NjSMmx2xqakJpaSmEQiG2bt2Ke/fuEdtRWg5qY2ODb9++obKyUsbCwcbGBo6OjujUqRPGjRtHPrx3797F58+fsW/fPigpKSE/P19mvvTy8sK4cePaWrpp1NfXo6qqCiNGjCBp9t/j7/GfGv91YFRqaipGjx6Njx8/AmhmeVhaWsLExIQ6KYzeKScnh6ioKMybNw96enoQi8VkkKusrAwNDQ2EhITg5s2b2LVrF/bv34/BgweDy+WSQSOTZolEIowfPx6///47li1bBl9fX8jJyVH3SUFBAf369cO5c+dQW1uLzMxM8nTw9vaGnJwcxXorKipi//79ZDSppqaGUaNGITExEY6Ojvjw4QOAfyzgjY2NmDNnDpKSkug4lJeXw8fHB3V1dRg7diylejFmE/PQ0NLSoslLIpFg586dEAqFiI2NpQ1QUFAQfH19ybPo8OHDVLAsW7YM1dXVKC8vp26tra0tFBUVKTXr1q1bWLBgASZOnIj169cjMzMT58+fl1lcKysrIZFI0NjYiA0bNkBOTg5dunQBANLvs9j5uro6fP36lcAa1t1lqW7SxsDq6urQ1dUlwEJJSYk2GZs2bUJqaioGDRokA+rNnz8fhoaGGDhwIHWfr127hsuXLyMhIQExMTG4ePEi5s6dSx1pLy8vjBo1iopZTU1N2tR6enpSgXTs2DEIhUJ06dKFPoe0pwQbNTU1mDx5MjEodHV1cebMGSqwRo4cSVp8sVgMGxsbTJs2jeQq7PsrKSnB0dGRwIN3795BVVUVkZGROHnyJKXZNDY2Yvjw4dDQ0CCWHrvOWReMATvSRSx7L0tLy1YdeNaNZqwYxvzhcJoTGhnTw97envTszLyYgaZsg25qaorBgweTWbaLiwvy8vKgr6+PwsJCkhTZ29sT0KWhoUGG5qNHj4afnx/s7e3pM4eEhODIkSMIDAyEiooK+bmx88AKSAa4MSka8+BgBYk0wMEeZ/d+y4Ksc+fOKCoqonlBX1+fOvItqeYcDgczZ86En58fAWsMqBMIBNixYwd0dXVhY2MDZ2dn9OjRA1FRUf+uqfSHg807a9asgaKiIhwdHXH69GkAIMNdFiG9ceNGdOrUiQIizp07BzMzMyxYsABTpkyhgjYwMBCxsbEUcT5o0CDo6+sjKSkJqampyMvLQ319PWpqajBu3DjY2tpSghC7d0pLS6Gurk6pNIxdyCS448ePx86dO8HhNKcA5eXl4cSJEwQYvH//HpGRkQgJCaHivF27dsjKykJpaSnk5eWRlZVF8yeLE2fHY9++fcjKyiIZFwMUJRIJ0f6NjY1x9OhRYmcwHypnZ+dWgCmfz8e0adMoXYzDaWaD3Lt3D0VFRbC1tUWvXr3Q0NCAMWPGwNfXtxULrq6uDrNnz0Z4eDjEYjF69epFDEoOp5lFVFRUJLPhYOaq6urqSE1NRUBAAOzt7TFw4EDcvn0b3759w8mTJ2FmZoZOnTrh2LFjAJolj/7+/ujateufXj9Pnz6FsrIyJk6cKGPE29jYiOXLlxPDzNbWlkBqNicUFBTg6NGj6NOnDzVQAgICYGJigqSkJJI5X758Gd7e3rTWCwQCYlgmJSUhIiKCwAllZWVYW1vj0KFDMDU1xaRJk8jQuK6uDpGRkejcuTMAkA/LxIkTwePxZJKlmDyPvY+TkxPevHmDO3fuIDExEcbGxlBTU4OBgQF8fX1x+fJlakgdOHAAv/76KzEtVFRUIJFIyDA+LS0NRkZG0NHRwc2bN2ndUVdXR2lpKYEe0smH2traxFJh55Z5T0mbmjNgljHaxo8fT1Ip1owYOXIkHj16JHP/M2CqJRNz7969ePPmDaUmRkdHy3TNQ0NDsWHDBgLJbG1t0alTJ8TFxWHSpElYsGABAgICEBwcDAMDAwQHByMiIgLp6ek0d9TX12POnDngcrkICwvD69evaa6MiYnB27dvaV5gzGM3NzcCdBhQ3bNnT5w/fx737t0jywV2vA4fPoyGhgYCTpkH2rFjx1BeXg4rKyv07t0btbW1JPcaOnQogQANDQ0UjsKagexHQ0MDxsbGxI5gc76bmxv4fD6lA7MIesZqcXBwoIQuOzs7Oh4A6HiEhobi9evXqKqqIkmRv78/zR8McGq5+ZdmabLrQ0tLCz4+PjIMLeapJW14r62tjbFjxxLj/sGDB8QqdXBwwNOnT2XWj4aGBpm5avTo0cjNzcXbt2/R1NSEz58/Y8yYMRAKhdRgKSgogKmpKckfgWa2JwOst27dKvMe7BwArcFvAH96Dtm8dOvWLXh5eSExMRHPnz/H1q1boaCgQKm29vb20NTUJK83OTk5lJWVEeC2e/duaGpqUj2lrq6ODx8+4Pr168jIyIC6ujr8/f2hoKBA4LH0fNjW39nYtGkTmc1LNylXrVqFoKAgtG/fnq7FefPmITg4GEAzEMXqviVLlkBOTo7sGqRrt7Vr10JfX588Ttm9webNH5mV8/n8Vq/HgKiWlgnsh8mr26qjGGAkzeRjvmjsefr6+lR3s7WWAT8tmfvsx9vbm+o3R0dHXLlyhepNPT09bNy4ER8+fEBsbCzJkCMjI6Grq4vi4mJwuVxYWFjQPceUK126dEFJSQny8vJkWKHLly+nmjwpKQn9+vXDtWvXYG1tjbS0NHh6eqJDhw4kcQaazemFQiG2bduGq1evUl3JgE1pY/aVK1di586d1DTlcJqtASZNmoS7d+9i7NixMDY2hqKiIgYNGkTXW2lpKRQUFBAeHk77Ujs7u79s7dCS3fj3+Hv8J8Z/HRjFFqdp06YRaPP27Vv4+vqSt0NgYCDmzJlDSDWX2+xnc+DAARw5cgRycnKws7NDZWUlXF1dKYHnxIkTuHPnDqZMmUIG6F++fEFJSQkMDQ2hqKgIU1NTiiD39fWFvr4+EhMToaenB1VVVdjb28Pe3h4eHh6ora2lz9CnTx8ZHX5OTg7y8vJoE+Ls7IwVK1YgKioKhYWFMhPAsmXLoK6ujnXr1tFjc+fOhYaGBu7duwcfHx8sXLgQkZGRlLbEvLFYYcS6uZMnT0bXrl1lfBMUFBRw9+5dYg/89NNPcHV1hUgkgrq6Onr06IHbt29T8cE61V27dsXXr19lOufXr1/HqFGjZDrnTU1NqKqqQmxsLJYuXQqBQABra2tcvXoVI0aMgJycHJnQjhs3DmVlZejTpw8V/SoqKrC0tMSIESPw6tUrGZNFFl2/detWeszDw4PkTKyTCzQXLkuXLoWGhgbGjh0LiUSC9evXg8drjs5taGjA7t27KTFJWmrj7+8PsViMmTNn4ueff4ZIJKKF19zcHHv37iWG288//wxVVVVkZ2fjy5cvAEAJQwAwbdo0pKSk4KeffsKlS5cwadIkYgGcP38eq1atIvbC77//jpcvX8LR0ZHim5WUlJCZmQkzMzPIycnB09MTv//+Oy0uw4cPR2BgIJSUlMjws6SkhEAcaTaZpaUlMjMz0bFjR2I/aWlpwc7OTmYDq6ysjMGDByMoKEgmMapHjx4wMDAg6RFLFFFWVibpHJOLGhgYwMbGhopcBwcHWFpayiRJMcmXsrIyRowYASsrKyxcuBCLFy8muaW1tTUZTnM4zQyX+Ph4fP78GTNmzJApkry9vWFnZwcut9lknjFe4uLiaFNuYmJCYIGbmxuZrrNzzwAiPT29VsWWNDDICrWcnBySlw4aNEhmU6CkpERsKtZ97dq1KwIDA4n1w56/atUqfPjwAb/88gt5FEjLkv/dg0lXpe9lb29vqKmp4cmTJzh48CC0tbXh7e2NwMBAaGtrQ05ODmZmZuRHMG3aNMTHx+P9+/dISEhAt27d0LVrVyqSPDw8sH//fmzZsgUDBw6EpaUlnc8BAwbg4cOHeP36NSZOnAg7Ozvk5ORQ8TZkyBAEBQWhQ4cOcHd3pyLz8ePHmDNnDng8HgoKCnDp0iWZQottWBsbG/Hu3TvY2NjIdF8lEgnu3LmDFStWQE5ODra2tuT9p6ysjKSkJDouL1++pGTUrKwsZGdnk+/YihUr6D6vrq5uszBnfiNs0ycQCODp6QlLS0u6T3R0dCgNyc3NDZ06dUJ6ejpCQkJw9uxZ1NTUyMji6urqYG9vj8LCQqxevZrei5n7sg6niYkJvbeXlxdMTU2RnJyMjIwMaGtro7S0FHfv3qXXPXLkCMzMzKCtrY2IiAikpqbCz8+PmDp/xs47ceIEzMzMMHnyZNowAc2FLfPW8vPzI08sdmx4PB5Fw1tYWMDJyQnm5uYIDg6mlKiOHTsSmJWXl4fbt2/j9u3bKC4uJjDa2toaXl5eCAkJgb29PXWqBw0aBB8fH0ydOpUaWiyEgvnEycnJYenSpZg1axa0tLSIieXo6Ijw8HBoaWnR/BMXFwc/Pz94enoiPj4eAwYMoObK8uXLkZ2dTVLEY8eOYfr06QQmMdkHA5HYPBMTE4PCwkKEhIRAQ0MDQUFBmDp1KiQSCSZMmAAVFRVkZmaisLCQGlzsczO5p7TPFZsn1dXVsXnzZhgbG8PPzw+LFi2CkZERYmJioKenh9GjR5OvTksAiv0pHRbz9u1bnD17FsbGxggODqbuOwNDhUIh5s2bBwMDAzg7O8PW1hZaWlowMzMjRjkD2r59+4bi4mIkJCQQ0LRo0SJkZWUhNjYWjY2NOHjwIDH67ty5IzNXHTt2DJMnT0bPnj2JudGuXTtoaWnBwMCA0vOYDFooFOL06dOtgNOFCxfSvbV8+XLweDz069cP7969Q2VlJbhcLvr374+nT5/i2rVrMDExobqQ+Xex+TsrKwuGhoYQi8Xkc8lSY5WUlNC+fXtiRnl6elIIgqWlJdatW4dp06ZBU1MTkyZNouORmZlJx6O8vByOjo40r7Jzza4j1qxpCRqwtFAOp7lJ4OHhQYxJ9pyQkBAZZgwzv2f/X15eTnN4enp6q42tdP0aFxdHTCFPT0/k5ubi9evXePv2LbFnBw0aBHNzcygqKlITb/78+VBSUsKkSZOgoqKCsLAwYuNKzz0/Ar9/dA7l5OTQv39/jBkzBiEhIUhOTkZNTQ2tEbt27aJGA6trGFju6OiI2tpa1NTU4MOHD8QwOnz4MIKCgsDhNPvLss8ozaxm9eH48eNl/KvaGo2NjcjPz4eFhQVsbGxaNSFWrVqF0NBQhISE4M2bN1izZg0yMzOxd+9eAqIAUMCSkpISfR92DlVUVMgOICcnB+rq6mSpIA1cMllby5CWlgwmHR0dquPZvkZLS0vmeW2xntjjLNWNzWfSYGinTp0QGBgIRUVFmetXeq1j64g00MWIAhxOswE9O6+srrO1tYWbmxu+ffuGMWPGQCQSwc/Pj9h00kByXFwcLl68SMxwxgp9/fo11WWjR4+moIeUlBSoq6sjKioKnp6eWLJkCbKzs2neKi0tJU8oFvggDT4tW7ZMhgUlne7KggPk5ORQUlKCnTt3Ql1dneTMwcHBSElJwc2bNwE0p9VmZmaiR48eGD58+D9N7/57/D3+t8d/DRglvfgsXryYJgIGSDGJm76+PnR1dRETE4M//vgD586dk6F0M7rxwIEDAYBMBw0MDNC7d28CnbS0tGjhq62tpQ2kvLw8XFxcaCM5d+5cvHr1Clu2bIG7uzuEQiEBX9XV1WjXrh309PSgrq5ODAllZWUqaKdNm0aGv1ZWVrC2tpYBckpLSyESicjcmi2YFy5cgIODA/r06QM9PT1s27ZNJnWIdbDY55WmqLMO/rFjxzBq1Cjqari5uWH06NEU58nAIB0dHWRmZsLDw4OSwNzd3RETE9Pm+WFj2bJl2L9/PwDgy5cv5Dk1c+ZMmqg5nGapYmpqKhYsWEC+KsyThgEaPB4PGzZswNWrV2FiYiLjxxIdHQ2RSIS5c+di3LhxkJeXx7BhwwDIUp9ZLPm2bduwatUqODg44MOHD1i2bBn4fD4GDx6MQ4cOEc2eLVbsmPn6+uLVq1dobGwkBgaX22xIGxUVBVNTU/JlYgypnJwcSukBmhcrdXV1TJ06FZcuXZLpErKNKEvQ4PF4OHPmDCZOnChDs87IyKDvFB4eTuAjkx5u2bIFdnZ2iIiIIC+vrl27koyIRbiyNKmZM2fKGEkyQ2pphpClpSV5Bkh73lRUVGDp0qV0vFJSUqioZca57LkMrGFeCuzfxsbGVHiYmJhQyoqvry8xhsaNG4cDBw6gU6dOxFq0trYGj8cDn8+HhoYGDAwMoKmpKeMXwCjKSUlJtBFhRpWqqqpYt24dysvLyW9GXl4eRkZGyMjIaGWQyQoF6YJKKBQS81H6uXFxcRCLxSgrKyMaujSTqqWPgqamJuzt7aGmpkY6fzk5OaKEs3tf+s9/55AGok6fPo2xY8ciNzcXZ86cQVBQEExMTJCQkIBRo0bh1KlTyMrKgqamJoRCIaKiogiEyc7Opm6dgYEBQkNDifkVExODtLQ0WFpawsjICFpaWjh+/DgAoE+fPhCLxSTj/f333xEfHw8ul4tJkybh0aNHyMzMhK+vL0mOevToAX9/fyQmJmLOnDno0KED5OTkiEEqvSFi3+3Dhw/w9/dHYGCgDIsuODgYAwcOpFSerKwsApqNjIyIOcNYqJMnTwbQXMxlZmbS/HHr1i2sXbsWPj4+UFRUxIgRI2BpaSlzT7Bi09XVFYqKiujatStmzJiBSZMmQUlJCcbGxggLC8OuXbuQm5uLLl26IDQ0lKQkLHErKysLU6ZMwfXr16GiooLY2FiUlJTIgMgdOnRAt27dsHv3blRVVcHc3JzkVfHx8bSZjY2NlQEeGIh+5swZmJqawt3dXeZa/CugKPNiYoBUU1MTpk2bBgMDA1haWiI2NpZkYCtWrICvry/du6xbf+rUKaxZswZ1dXXYvXs3hg8fDk9PT2IhOTs7k/QhKysLzs7OxAoTCASoqKjA0KFD4e7uTpvcIUOGwMPDQ6Z+2LBhAzp06AAjIyN4eXkhODgYI0aMwODBg5GcnIywsDDU1dXh5MmT0NLSQmRkJLZu3UopsCx5qKamBvv27YOioiKioqJw//59DBkyhAJMdHR0YGhoSJs16U1eVFQUVFRU4Ofnh7i4OKxYsQIvX76Et7c3bG1toampidDQUJKyCAQCmJqawt/fn3wUpec9Ozs7krCwzR2TnM+ePRtAc/3D4/HQuXNnGBkZYezYsTKde3Y9SI/Lly/D3d0dPXv2xPv377F27VrIy8tDQ0MD8+fPJ8NpJycnACAZCjuvhoaGcHJyQnp6Orp160avn52djcDAQHz69AlfvnwhHz3pe/jEiRMQCoVIT0+n8zl27Fh4enqipKSE5rG1a9eCy+WiS5cuyMvLg6urK6Kjo/H161eEhoZCSUkJ2dnZqK6ubhM4ZRIzS0tLCAQCzJo1C0Bzo4ndh+3btyeGApMijhw5UqY2YQbsBgYGiI+Px4IFC2BgYED/r66ujm7duuHTp0/o2LEjDAwMYGpqSkEvysrKePPmDWpra+l4NDQ0YOTIkdDV1aUEYBMTEwKPDAwMyECdJQdHRETQBp69N9uUs3Vp7NixrQJL1NTUIC8vT7IndXV19OrVC6qqqnB2dsbcuXNlmN9sPmcjLS2N5nB2j2ppaRE4/PbtW5SUlMDf3x/x8fHg8XjEXBwxYgQqKirw888/Iy0tDeHh4YiMjGxz7vkR+P1n57BDhw7g8XjQ1tamsCGg2aPJz8+P2FAMYGnfvj1J8/39/an+6NWrF/Ly8iCRSOjYxsXF4d69e/j1119przBt2jSEhITAwcGhFQjQ1pr+/ft3zJ49GxYWFujbty+xOdlYtGgR+vfvj8bGRty+fZvqrPLycty8eROLFy+GsbExvLy8kJGRgV9//RXTp0+HtbU12THIy8sjNjaWTNt5PF6rMA0lJSV07NgRXC5XxjKB1e9isVgmLZTDaW4QMvmj9LwkLaFm/5Zer9TU1Ih1zGpENp+z+YN5/zFmNIfTHHbEGEDsMdb0yM3NpYZXbm4u1qxZQymEM2bMQENDA16+fAkLCwsoKSlBU1NThk0nJycHiUSCHj16YO/evTh69CjOnTsHExMT2Nvbw8LCArNmzcKnT5/w7NkzJCYmQkNDA2PGjMHy5cspdGDChAl0jb158wa5ubnYsmWLzPzKAF9FRUUKt5D2uGKNGg6Hg7S0NJSUlODdu3eIiooiKfD3799RUVGB8PBwtGvXjlirLefxf3fozd/j7/H/Mv5rwChA9mZiBrlTp07FvXv38P79e7x48QJeXl7UzY2Ojsa7d+8ANEdHs0lWJBKhvr5eBpzQ19eHnJwcyaCY58uWLVtw+vRpaGtrkweNt7c3LepsU8LGuXPn4OHhAXt7e/I/sLGxgY+PDzE7pCfibt264e7du/jpp58QERFBsdn19fVYsmQJfb7z58/jl19+wYULFwAA27ZtQ3h4OPkQSE9iHE5zl5nJyJg08OzZs3j48CGmTZsGLrfZr6lfv35Ee2UTno6ODvbt2wdjY2Noamqia9euaNeuHQYMGIC6ujosW7YMXC4X3t7eZObLPjMbDx48QEJCAuzs7HD48GHcuHEDjo6OkJeXh52dHfr16wehUEgys8+fP+PZs2e0GenZsycAYOPGja26L3Z2djJJbWxiZp4VMTExMDY2lrleli1bBjU1NaJ6l5SUwNbWFh8+fCBwiWnCWRevuroaixYtAofTzCSQ9sZiBaW7uzsiIyPpmEpTyY8ePUrXKAD88ssvEIvFMDExgZ6eHnUJnz9/jrdv36KgoABcLpfMC+Xl5eHk5AQ1NTXqxHO5XOjo6JBPR1NTEyIiIsDlcqmj09jYiNmzZ8Pd3R0SiQRhYWFQV1cniRMrQlRUVJCbm4t58+ahb9++VGjIycmRNC4zM1OmS8Y27qz4VlFRwYIFC6CgoAA+n4/s7GwyM5UuHvr06YMOHTrQtThkyBCsXLkSFhYWUFRURHBwMFasWEFMtpKSEmIVamtrQ1dXF5aWlvDw8CD/lvbt28Pb21umeGJyVVYosY7SsmXLCNxgCz0Dfr9+/Yr6+npMmzaNYs2ZCTv7DkOGDKF7jBVHzJySHRdmXMred+bMmcQm5HK5Mt081i1loJSrqys2b96Mr1+/okOHDuBwmjusXC4XP/30079h9vzxkC6E8/PzSXawatUqPHr0CA8fPoS/vz94vH+kRL548QJpaWnYvXs3Ghoa6N4vLCwk8JLd3xwOBxMmTADQnMrG2C/p6ekAQElmpaWlAEB+QkKhELm5uZg4cSK8vLzI34IlTy1atAjr168nDzxTU1OIRCIEBgbK3PvSfy8oKICnpyeKi4spwVTam0FVVZV8dCwtLfHLL7+goqKCuo3q6urg8XiYP38+bt++jUWLFtHaIRKJkJ+fj8jISNjZ2WHAgAHYsGEDkpOTaTPessj39vYm1t5PP/2E0NBQWFtbw9LSEsOHD4ehoSGuXr2KS5cuQSwWY9euXcSaMDc3R1RUFPr27QsFBQU4ODhAWVkZM2fOJNkOM9t2cnJCamoq5s+fL+Onoa6uDrFYjLq6Oty6dQtlZWXw9PSEra0t9uzZA6BZYm1mZoasrKx/2TvixIkTMDc3R9euXbFw4UJ4eXmR0bGJiQmGDx9OkpenT5/i/PnzCA4OJlZUr169cPHiRQDNm91NmzZBX18fCxcuxNChQ6GiokISs5KSEtowsePt4uICkUjU6nMzQKqoqAgfPnzAjBkz4OPjg9jYWPIDY/KMluETmpqaZGD99OlTSh5i4OeYMWNgamqKzp07o76+Ho2NjVi0aBElVQkEAkr9ZfObNDhtbGwMe3t7fPz4EY2NjXj58iVJ+jkcDnr16oWysjKSVrEgEAbIS2+I79+/jxEjRtAcxACsqKgoVFVVAWhO6mIyWB6PR6yKPxtVVVVwdXWFo6MjkpKSKPFWIBBQyqWRkRFt3D08PCCRSDBmzBjMmDEDX79+RUREhIyXyS+//ELsWisrKzg5OeHQoUNYs2YN9u7dSyDZ4cOHiXk8duxYaGpq4vjx4/j9999lAFUWNCIQCCAWi9G7d29kZmZCXV0dAwcOhJ+fHwYNGoSPHz+2Ak6BZkB80KBBWLNmjQwAwti8p06dQvv27em8ODk5YdWqVeSHxc4DM8K+cOECCgsLoaOjAz8/P1rP9PX1ybtSV1cX165dw6ZNmwjEdHR0pOPx7ds3HDhwABKJBPPmzcPmzZtJ/tuxY0cZ3zA7Ozt4e3vDxcUFT548wcqVKymwgM0XLD2Ry+XS3Mm+D5MyTZw4ESoqKli/fj3V1qxGkb5WUlJSoKSkhMuXL6OxsRELFy4En89H7969AQA//fQThEIhli1bBqAZ0GYsS1ZHlpeXQ15eHnl5eThz5gzVkUVFRbh16xa4XC75t7Ycf3YOy8vLZerTI0eO4NatWzhz5gzk5eXRtWtXPH/+XMa3asWKFfDz80NkZCSF6GRnZyM7O5vSOjmcZh8poVCIFStWYOzYsTLsI5YQ3bt3bwQGBiIlJaVVal7LJME7d+6QxKq+vh7FxcXw8fHBgAEDZHzO2HUONM+NW7duhbKyMvz8/Ais53Kb/fRu376NyspKbN68GT4+PhAIBMQgZD5K0gCldHNNRUUFZmZm4PP5bRqMt/SJYj8/YkSxJrn0c0NCQqCgoCAT5MGey5LwFBQUKAF04cKFWL9+fav3Y7W1mpoaAgICMGrUKMjLy6Nv376ws7ODqakp3Nzc0L9/f2LTPX/+HA0NDbh69SosLCyo2S3NpmMgr4GBAbp37453797h1KlTMDQ0hK2tLXx8fODh4YHffvsNkyZNgqurK9meXLt2DStXrmzln8ZS+X777Td6jFmTsJ/k5GR0794dkydPpga1iooKxo8fD7FYDHd3d2KJ29raytiRbN68mRjNzAf37/H3+L86/qvAKKD5RmY3LgMKLCwsYGZmhoyMDKxduxa+vr4QiUTQ19dHWFgY+vTpQ4ZwSkpK0NfXR/fu3aGuro5t27bhxIkTJCPp0KED5s+fT8AHo0saGxvj559/JsnbmDFjYGJigsjISIwZM4YKO6AZQGGbMMYiWblyJV6+fInLly/D19eXCgYNDQ34+PgQsFRfX4+GhgaUlZWBy+Vix44dGDduHCQSCaysrCAUChEaGgqhUEiR8C0Xgf79+yMyMhJKSkowMDAg+cf48eOxdetWqKurY/z48WSwvGPHDvzyyy/w8PAgmZC/vz+0tLRgZWWFly9f0oahpqYGo0aNItBGulvOxoQJE7Br1y4cPXoUmZmZ0NLSQmBgICXDsC4u00VbWVnBz88Pfn5+sLCwQEBAAGnG1dTU0Lt3b2KVKSgo4OLFi9i4cSMVXiKRCEFBQZRSER8fj+HDh9P1sn37dnC5XGKXAaDCJicnhx579OgRAXja2tooLy+niG1WsCQkJKBfv37Q0tJCUFAQbt26RYtmWVkZgGY/KBaBKi0Z6tatG+Tk5AhwlO4Sfv36lbqEDg4OMnr1yMhIDBo0CPn5+eSfpaenh5KSEjx8+BAA0LNnT2hpaaFdu3ZU4OXl5WHAgAEYO3YsoqOjSXfPmF9Me66qqkqbJwbEcjjNbB1dXV1oaGhQgSVdHLBEO1aM9OrVCxkZGcR+YgWKv78/AODr169ITU0lUOPLly9Ys2YNsaKYoeKuXbtQUlKCjIwMOu9cLhd2dnY4deoUFUS2trbo3r07qqqqoKWlBZFIBBUVFcyZM4fuDwYyaGlpYf369dDQ0ICenh7mzZtHIBQ7P9nZ2fDz88PIkSMJTLO2toazszNCQkIouUvaG0v6Jzs7u5UnEGOjMTaDsbExMjIyKDVNOvZ44MCB5LeRn5+PDx8+UOT4/8aYOHEixGIx9PT0WhX8z549I3+JwYMHIzg4GN7e3iSHZelaffv2xYgRI1BQUIDk5GTy3Dt//jwqKiogFApha2sLNTU1HDt2jGS7zMi2trYWnTp1grKyMiV5CoVCFBcXY9euXcRECA4OhqqqKgEF+vr6GDx4MGpqaugYtuwETpw4kTauL1++xMOHD+Hg4AAFBQUEBQWBy/2HoS8DS37//XfU1NSgvLwcqampxLzU09ODlZUVOnfujH79+snQ+cPCwqCqqoro6Gj4+PhAU1MTkydPlmE3MlmVkZERFdnm5uZQUlJCfHw8Xbfh4eHkecXMrwHg7t27cHd3p0SnFStWkOyCSc87depEcyZjcD548ADnz59HUlISLl68iK5du0JPTw/5+flwd3en79i9e3doaGjg/fv3AJqZnlZWVmjXrh2uXbv2l64ntsm6ePEigoKCYG1tDTs7O6Snp8PExAQ2NjYwMDAgsImdr3HjxiEyMhJVVVVwd3dH7969cePGDRw/fhz9+/eXSeEqKSmBkZERRo8ejeDgYBQVFWHs2LGYMWMGyYMSExPp+dJsuaFDh8Lb2xujR4/Grl27yI/kzp07qK2tRXJyMvT09LBs2TJMmjQJPXv2RJ8+fbBly5ZWPjnAP5KHNDQ08Ouvv8p4Pk6YMAFqamqwtraGj48PtLS0yD9q6NChFH6hoKCA7Oxs2sh8//4db9++xZAhQ2hj6OHhgc+fP+PgwYMyLAMrKyvk5+dDQUEB5ubmyMrKkkmNZSbfycnJsLW1pePKRkNDAwFTf2VMmjQJPB4PycnJePToEbZt2wYdHR2EhIRg1apVePbsWSvD6ZqaGlRWVpI/Zsu57fLlyygoKMCMGTMwYsQIWFhYwM3NrU3mMUtAXbt2rcxr1NfXY9asWdDU1MSYMWPA4TRL5hiwc+PGDXz//h1FRUWwsLDAnDlzADSDGebm5ujWrRsWLlyI2NhYmVTRuro6Yk47ODigsbERjx8/JgBHIBBAX18fvXr1ok01Ww98fHxw7tw5eHt7Y9++fbh37x4Bnmwu4PP5ePXqFZ0Ldjzy8/MxY8YMAsTKysqgr68PFRUVAuY5HA7y8vIwZ84cYkgpKCgQA8bJyQmurq7EOmaAA1tfGRDB1i3p+lJPTw88Ho+S58rLy7F+/Xrk5+dDUVERAwYMgK2tLbhcLjZv3gyguTZXUlKCg4MDrl69ioMHD8rM89++fUNZWRl5+rHR1NRE15GRkRExDmtra/H48WNYWVlRKllbo+U5jImJQXR0NP3/iRMnsGfPHty5c4dYkUeOHAGfz0ePHj0wePBgBAYGyjCFnz17Bk9PT7IwEIlEMpJYY2NjCAQCYntVVFRQ2E94eDidy0ePHrVq3EqvUfn5+bCysoKBgQF0dHRQUFBA9UlRUZEMeCo9pAEp1jzU0tKCsbExeUBt2rQJvr6+ZEfA5XLh4+NDADVjNjGvXWlfJrYW+fj4YNOmTW16ZUr7TrFrT/p3Wz5fU1NTBmBnElb2fMaWZ9cqYwlxOBxkZmYiOzubkn2lX9/NzQ1TpkyBo6MjgoKCsHz5cmzatAk6OjokGWRBBW2x6a5evQpnZ2cIhUIoKytj1qxZqK6uJtUJU4hkZWXhypUrOH36NIyNjZGcnIyoqCjo6Ohg+vTpEIvF6NevX6u5VHq+Yyl6mpqaMDU1hYODA/nosSYD859i6e1snmfzh/S9q6Ojg8uXL8u859atW+Hi4oLRo0f/8J75e/w9/i+M/zowCpAtWhmbo2vXrggKCoK6ujquXr2KnJwc3L17F8bGxtDQ0IC9vT3Onz+PhoYGBAYGQk5ODsOGDcP79+/xxx9/IDY2lgzstLW1KaaVMS0kEgmxdnx8fPDu3TucPXsWenp6MDIyog7RvXv38PTpU5SXl5OJrYKCAh4+fIja2lo8ffoUgwcPhp+fH3kJZGRkYODAgVQo19bWYsWKFdi5cycKCwuhq6uL48ePo7a2lqJ/9fX1UVlZiTdv3shEUTOPCzMzMygrK8Pf3x8qKioYPnw4FBQUIBKJsGDBAjQ0NFAMeVhYGDZs2ACxWIzly5djwYIFtGgwmR3rXOfm5sLY2Bjbt2/HwYMHqfPLxv79+6k7xs6RvLw8LC0tsX37drx8+RLu7u5ktH78+HEUFRVh3LhxWLFiBQoKCuDh4UGFlkgkok2adNF98+ZNdOzYkbp8CxYswJUrVxAfHw93d3fU19fTdfL48WMcPXpU5hq6fv06oqKiaHPdp08fJCcnw8XFRcaUnrE1tmzZAnV1daioqFBRMnXqVDItZHKTxsZGrF69GgsWLCBQqL6+Hh8/foSnpycl7bEuIbtu1qxZgyNHjgBoLnoXLlwILrfZq8rc3Bzx8fGIj49HUVERZs6cSQvQkCFDSK5w6dIlaGlpISkpCU+fPoVQKMTmzZtx6NAhrF27Voad0XIRZ1Rrc3NzGZ16ZmYmpk6dSowfdXV15OfnQ1tbm8BELrc5xap79+4EYDIPC2bGGBYWhitXriAtLQ29e/eGv78/Lczr16+HSCRCZGQkunXrBk1NTQQGBtIGncP5hwkv+8w6OjqwsrLCH3/8gS1btlBSpKmpKXx8fNC5c2diP1lZWUFeXh7p6emoqqqiYo4Bv9u3b8fChQsxd+5cyMvLw9bWlgoroVCIqVOnUvGuqqpKRRRLI2OFWFsG5dIyCOljzwA+aVkSh8NBbm6uTIH6ozTNf/d49OgRnJycMGDAADg4OODevXu4fPkyioqKyKtu79690NTUhLq6uoypKmNvWFhYEHBUXV2NhoYGSvVkfmdmZmZwcXGhuGA+n4+SkhIAzXPMzJkzyQuKdd+ZtxI7j2zOZ9eEubm5THpnW0DUs2fP4OPjIyP7effuHTIzM+Hp6Qk7OzvamLH0RbFYjCtXruDw4cOoqKjAoUOH8PLlSwwaNAhCoRABAQHYu3cvgGbgl8vlIjw8HKtXryb/C3V1dQQFBaGurg4FBQVU7MvJyVFCImsWMLZXUVERFeBjx46lYxMaGoqBAwdi2rRp6NChA9LT07Fs2TKSG+/bt4+kWAKBAL6+vtRh1tDQgKGhISIjIzF16lQsW7YM3759w61btyieet68eeQxcfToUfIjYcfy4MGDcHFxkZHB/GhIH//Ro0dTsIi8vDyGDx+O48ePw9DQkKLaGSBVU1OD6Oho9OjRA0AzA4cZDDPT/Pnz58u81+LFi2FoaAgfHx9iFDCz9Llz50IsFsuYrjMJItAsD+3evTul6PF4PMTExODz58/4+vUrIiMj4erqigULFuDly5d48uQJwsLCEBkZ2eo+raqqwvDhw0ny8+jRI7x48QIHDx6Eu7s7fvrpJ6xevZoYUVpaWhCLxejZsycGDBiAc+fOkanz4sWL8e3bN3h6eiIgIADR0dE0L4vFYri6umLnzp2wtbWVmcN5PB5sbW0RERGBUaNGoaSkBHfv3sXly5dhZmaGiooKeHl5ISIiAo6Ojujduzedc+nxVwCpgoICuLq6EohZU1ODZ8+ewdvbGxYWFq0Mp5uamnDkyBEkJiYiJiamVeKu9Fi5ciV0dXVJtjtnzhxwOByZ12T+aF27dpU5F42NjUhKSsKYMWMANNck9fX1OHbsGN1jQDMgsmbNGpn3v3z5MmJjY+Hg4ICEhASZBN5+/frBysoKAoEA8vLycHNzQ0JCAqqrqxEeHk5zvqqqKng8HmbMmAFdXV2oqamBz+dj3bp12LJlC96/f4+TJ09CR0cHGRkZsLe3h1gshpaWFjIzM8kzS3pIJ67Fx8dDUVERXbp0IWCBNT0ZS459FisrKxgZGcls/KV964RCIczNzcn4XVVVFbGxsVi8eDF5IOnr6yMwMBDx8fHU1GloaMDbt2+xaNEimJubg8fj0dy6cuVKhIeHo6KigvzD1NTUyL8SaE5sDQsLw6pVq9q8tp4/f06MQ/bdx4wZA1tbW2r0/Wiwc6ipqQlXV1eyvRg6dCh0dXWhrq4OW1tbREdHk4/TkSNHoKCgAHd3dzg7O9PvjBkzBgsWLMCxY8egoqICFxcXWFtbY+LEiThy5Agd58DAQLqm6uvrcejQIfLSHDhwoMw11palBQNPjx07hsrKSqxatQoKCgrULG0LPJUezB+1Xbt2mDZtGu7evUssZR8fH8TFxWHQoEEEaDBJ36JFi4hF/mc/fD4fhYWFMDc3p8aGtI0BW4vDwsJkPBFb2hFIN2P4fL7MazDvxXnz5uHq1atwcnKCgoKCjPRaujaNj49Hamoqgb4aGhqwsLDApk2biCXF5pgXL15g3rx58Pf3x5gxYyiFsS023cGDB6GhoQE1NTUkJCSgffv2cHV1pQTTvn370hzQpUsX5Ofnw8zMDMnJyZgyZQpSU1PJ/5PNX2ywa5ldAw8ePECfPn1gYGAAgUBANYh0oAA7vkzqnZ6ejnv37pH3paurKw4ePIiEhAR4eXnJECOA5rX8P2Ht8Pf4e/w7x38lGAU0Awy+vr44evQoMaR4PB4V79++fcPOnTthZ2cHQ0NDkrfV1dXh06dPCAkJgbGxMWJiYnD//n3U1taioKAAHE6zDGfAgAEy8h82SaSmpsLDwwPZ2dl48uQJeYN069YN2dnZsLW1hYaGBgIDA1FYWEjMJQ0NDWRkZJAu2crKCqtXr0bPnj1lurXSBdpvv/2G+Ph4kkusW7dOxpy8V69e+Omnn9C7d29KJVJRUYGGhgZMTU0xY8YMPH78GBKJBAcOHEBcXBw0NDSoIzR9+nSkpKQgPDwc7u7umDFjBurr67F7927aQIeFhckc9wsXLiA6OpoKOuAfG+VVq1Zh6dKlmDdvHv3f2LFj4eLigs6dO8PJyQmHDx/G06dPYWdnB0VFRejo6ODEiRM4d+4c+vXrBw0NDezfvx979uyhhYyZJTKqMIfTHPVqbW0NkUhE50kikSA0NPRPi1zp0dTUhF27dhH4ZGRkBH9/fzg7O9OCV1hYSDGsYWFhCAkJwfHjxzF58mQYGhoSQ4gVSEy/LS3fZAsBY+zFxcXJdAmrq6vh5OQkY24INHfYtLW1IRaLya+htraWNr6ampp0vUuzELS1tZGWlobAwEBERkbCyspKRnfPrpOW4Im1tTW2bdtGxTN73NLSEvHx8QS+5OTkkMG99DlSU1ODmZkZMayCg4OhpqYGNTU1aGtrIy4ujsxXWxrj/vrrrwSgbt68GU1NTdi5cyd69uxJMfUs7Yil3AwaNAjDhg1Dly5dsH79eggEAvKjUlRUROfOnREVFYXo6Gikp6dj1qxZSE1NxYABA/DmzRsAzd1IxjbgcrmIjY3FsGHDKNGNHSMGxjF/MGVlZYhEIsTGxuKPP/6Q6QoaGhoiJiaGClV9fX1IJBIC0vh8PrEWJRIJtm/fjrNnz0JNTY3CGf7To2Vx8vz5c7i5uSEzMxPGxsZIT0+Hu7s7UdsXLlyInTt34uDBgzKhANIg2dWrV2FpaQlTU1Okpqbi+/fvePHiBYFHBgYGGDx4MOrr63Hx4kWSiLEu9M6dO6GoqAhzc3M4ODigb9++UFJSQm5urgwotXXrVkgkEigoKCAwMBBcLhe7du1q1XWUHr/99htEIhH27dsHAATgnjhxAsePH8eCBQugpaWFtLQ0DB06lAAhDqc5ap35Ow0YMAB3797FuXPn4ObmhpycHFy+fBkhISHU1TYwMIC1tTUMDQ0J3Dxy5AiEQiGmT58Oc3NzjB8/HqWlpejRowcCAgLQt29fuLm5YcmSJVTYZ2Vl0Xe5fv06cnJykJGRgVWrVtFGs7i4GLa2tsRgunHjBtq1awcdHR1IJBICzhUVFUnCJRKJYGpqig0bNtAxk5Z/NDQ0IDY2Fu3atWt1n0oDOX/l2tq0aRP09PQwefJkaGtrIz09HXJyclizZg0ePHgAPT09Mu/29PSEk5OTTDpoU1MTzp8/j+zsbPz666+wtrZGVFRUK3aWtMRs9uzZlAAIAHv27IFIJELXrl1lPtv8+fOxZs0a7NmzBw8ePMDKlSthZ2cHHo+HpKQkfPnyBV++fEFMTAxdl+3bt0dsbGwrqQ37+/fv39HY2IjJkyfDy8sLhoaGCA0NxZAhQ/Dt2zccPnyYDJEZKCAvL4/IyEi8efMGHz58wIQJE0hew+PxEBAQAGVlZaolBAIBMWnEYjFJR9kaGB8fDycnJ1y8eBFpaWnkmcnmPHY8L126BC8vL3To0IEYtn9lsGthypQp8PT0xMmTJ9G9e3dqvrCNe1uG03V1daiqqvrTOHugWUbJwKRdu3ZBVVWVmMcbNmzAhQsX8OzZM5iamqK0tJRe/48//gAAmJiYIDAwkJpS379/R319PYYOHYrw8PBWcifpWqGurg7v37+n1/z+/TtiY2PB4TQnNZqZmclsqrt06YK3b9+iY8eOBLjz+Xzs27cPHTp0gFAohJqaGkJDQ4k51KdPH/Tv3x/19fU4efIkhgwZAm9vbwwZMqTV3CX976KiImIqSW/OpcNoWK3q5+dH0h4ul0sSUTanMd8+kUhEr2NpaYkuXbrg/v375LEoJycHX19fyMvLw8rKCn369EFdXR3q6uqwePFiGfuDq1evws3NjcDSlv5hdXV1+PDhA+Li4hAUFPSXQE/GONTU1JRJbfyzUVNTA2dnZ3h5eWHnzp3YtWsX7O3tceLECTx//hwbNmxAVFQUnJycKEXy+PHjdCwnTZqEDx8+IDQ0FMHBwRg+fDisrKxonXdzc8PEiROpuaCjo4PVq1ejrKwMJ0+eRFNTEw4ePEigQnl5ucznawmepqSkUEOTjb8CnrLBwod8fX1x/fp1nDhxgmwWeDyejPk8a+pZWlrKKCta1oN9+vRBZGSkjKSOsS7fv3+PTZs24ejRozI+Uunp6RTg0JIRxVQR0k250aNHy9xPBgYG6N+/P6U5sjTTHzX62N8ZU435qLGwjpEjR+KXX37B/fv3ER8fT3MKCzUB2mZE+vn5QSKRICgoCIsXL6bnjhs3Dtra2pg1axasra2hpaUFW1tbYk6ztXrevHmIiYmROVfS93F5eTny8vIQGBgIsVhMzfLo6GhwuVwsWbIEeXl5sLOzg7a2NoyNjSGRSODv70/J5vLy8ujWrRu95sGDB5GUlAQvL68275O/zcr/Hv+Xx38NGNVygb5z5w709fXx6tUr7NmzhybMlStX4uvXr1i6dCkuXbqEbt26QSQSYdy4cTK6/+HDh8tQWIFmc1smIZOXl8eJEycQGRkJOTk5DBkyBL1794aSkhLi4uJI329nZ4djx45RwZ+fn49Bgwahe/fuxIpgnVAmF7KwsIBEIsHu3btlKLbS35Gh28uWLcOXL19w6tQpKkKlvVh0dHTg4eEBQ0NDREREkHeEm5sb3Nzc4OTkBHt7e4SHh8PBwQFeXl549eoV3r9/T4aY169fh42NDVHgnz9/jtzcXNJbM2Pv48ePIzo6Gs7OzjLMI6DZiJJ1TUaMGEEFICtYCwsL4enpSZvJY8eOkdyLLToaGhrw9fUF0OwvwOVyoaamBl1dXQiFQmhqamLt2rUEcPTo0QNv377FhQsXkJub+5eK3Jb/t3btWigrK8PAwADl5eVobGzE8+fPYWxsDAsLC8jJySElJQUuLi4wMzPDiRMnADTrwJlvwNq1a/H8+XM8evQIMTEx8PT0JM+v6Oho2NraYvPmzUhJSSEmjLe3N1avXo09e/YgICAAqqqqFHEsPe7fv49jx45hzJgxsLGxQfv27WFsbAx9fX0yM5W+P3777TdcunQJXC6XvJsuXbqEL1++oF+/frTgMxoyA5OEQiElRDIgSlVVlfxYmpqaSCOvqKiIkJAQFBcX08aKyY04HA5MTU2RkJBAmnYmQ7K2tqYNizQgxcagQYOgoqKCnJwc9O3bFw4ODjh//jzc3d2pkBkxYgT09fWpUOZwmtlXv/zyC+bOnUugm4qKCoUOGBkZIT4+HpMnTyZfmfz8fFy4cAHBwcG4cOECmpqaMHv2bHA4zYb4r169wv379xEVFQWBQABlZWUYGxtDR0eHkhT79+9P8gfp7qKZmRnEYjEyMzMp+ZFdy3PmzIGBgQGysrIwcuRIBAQEYODAgairq8O1a9cwYcKEVp5H/+4hPc+cP38er1+/RlNTE9q3b0+FpK+vLw4dOoTq6mrExMSgoKAA7dq1w8KFCwGgTfYR0LwZMTU1hYKCAtavXw+gOXaamZKGh4ejpKQE0dHRMDY2hqOjIxWQ7u7u0NbWhpubG81ZCxYsQE1NDTHk4uLiADQb49rZ2SEkJIRYPm19vx07duDx48d49uwZbGxssHz5cixbtgz29vb0+Q8cOIC0tDSEhobi48ePqK2txb59++Dt7Q2hUEjyi0WLFoHL5SItLQ3379/H6dOnYWFhARUVFSgoKEBPTw+urq5wdXWFhYUFGaiy64Idj27dukEsFsPa2ho6Ojrw9PTEgQMH4OzsTJK6tLQ0WhPOnDmDadOmIT09HZ07d8bt27dRUVEBLpeL3NxcSgOV7rqePn0aCgoKEIvF5MMkEAgo3rl79+6wtrbG2rVrCWCqrq7Gzp07ER4eDhcXFxlAiI1/5bqsrKxEr169MHfuXAqMePr0KRYsWABFRUWcOXMGVVVVUFJSQkZGBqZMmYIlS5a0yQZk71tVVQU3N7dWEjOg2fvo+/fviIqKgpqaGk6fPk2/u2/fPojFYnTu3Bk3b94k4Nvd3V1GArZp0yY4OTmBz+ejXbt2xJBKS0uDkpISdu/e/adrTFNTE8aPH0/ge2BgIGJiYshMPTU1FRKJBJMmTaLAEpFIBC0tLSxZsgSNjY348uULpk+fTrH3b9++xcuXL9GjRw9KY1NRUYGOjg709PTIXDg1NRXx8fGIiYnBmzdv6O8/+pxAs09TyybIXx3Xrl0jw2lpSeJfMZxmz/3RGDBgAGbMmIG9e/dCVVWVGMRjxoyBuro60tLSUFdXh65du0JHRwfHjx/H7Nmz0a9fP9y7dw+2trYQCATUhGwpAf1nQ9rP5+HDhwgPD4eZmRm4XC4GDhwow/iQl5cnk/DQ0FB6nG34g4ODsWzZMoSEhCApKQk7duxAamoqtLW1MWPGDABAp06dsG7dOpnj2HKMGDEC6urq5J/D1hWW6Mbe19jYGGKxGE5OTlBVVYWamhqmT58OiUQiw0RxdnaGu7s7rffy8vIkldLX1yewPyEhgf7fxcUFnz9/RllZGUpLSymhkX2+tLQ0+Pv7k1fqkiVLWvmH+fv7w83N7S81DRnjcMSIEX/Zr44du9raWsTExCA4OBh5eXkYPHiwzPNOnjyJ4OBg9O/fn+qSK1euYMWKFeDz+Rg5ciQOHTqEuLg4SiBmjW8G6uXk5GD16tXEcrazs8OKFStk3mPKlCn47bffWn0+4B8Asb29PfLy8gCAamcAPwRPz507R39fsGABseo7deoES0tLqKioYOXKlWhqasKOHTtkEpCZ5JKtqRoaGuSPyYA25oGakJAAFRUVGWuCvLw81NfXo7q6Gnv37sWgQYPodVVUVGBubk6yMtZYYWzBlgCVRCKReZwxrpiNB5/Pl5H8tQSk2N/FYjGmTJmCyZMno6ysDN+/f5eRexoZGclcc22FMkgzIr9//45ff/0VPj4+6N27N+7evYvHjx/Dy8sLBw4cAABSRbi7u6OmpkamtpUerFZi13leXh50dHQoMEVLSwuDBw/G/v37IRAIoKuri0uXLuHbt28k12bhGfLy8sRA53K5rZhXR44cQUpKCkxNTSkZ9+/x9/hvGP8nwaiWN7N0McU2F2/evEF4eDgmTpwINTU1LFmyBFu3bkV9fT1mzJiBsLAwnDx5Ep8+fUK3bt3g7e2NkpIS1NfX48iRI+QR5ePjg2fPngFonqCYOTmH00yjd3d3x+HDh8nQrri4GH369EFcXBz09fUpYSEuLg5aWlq02DONtby8PIYOHYq8vDwYGhrC3t4etbW18PDwkJGMtJQ16Ojo4N27dzQZxcfHQyAQID09nbozKioqZFqXmZmJbt26YciQIeTToq+vDw0NDUgkEjg6OpJ0RFFRkYqF+vp63L17FzweDxMmTMDp06cRFxeHiIgIirll0dYODg6Ijo7G9+/f8fjxY5pcmfHy1atXERYWBktLS2IKVVVVkUwnJCQEenp6cHNzw7Bhw8g8WCAQwNrammRkM2bMgKqqKi2g6urqMDc3h5ubG+Li4rB9+3YEBwfD0tISZ8+elbk+WsoG/2xMmDABgwYNgpmZGTp27AgnJyccPHgQDQ0NePjwIeLi4oi+zooNY2NjTJw4EVVVVRg0aBCcnZ3JRN7X1xe+vr74/v07Ro0aBW1tbejo6JC3Vc+ePUnC4OvrCxMTEzg5OUFHRweBgYEkMWKjd+/eVKx+/vwZU6dOpWPE0mmAfxRzCxYsgLq6OqysrODi4gJjY2OYm5vj4MGDWLlyJYRCIXr16gWRSARra2vcvXsXFy5cgJubGxVYTDrKorfv3buH+vp6fPv2Ddu3b8fFixdha2uLpKQkpKSkUPHarVs3cLlc6OnpQVNTE1paWkTvZ/HjrMPUcnPErv05c+aQr4y+vj42bNgAANi9ezcxQXbs2EFeJazjq6CggPDwcFRWViI0NBRGRkYwMTGhwl1FRQX29vZULKxbtw5cbnOaYFZWFr5//44lS5agsLCQipzIyEjcv38fOTk5lEAoLy9P6ULsfG7fvh2enp4yYJScnBwUFRXx66+/4siRI/R8eXl5XLx4EcOGDYOuri4yMzMxcOBAuLi44PXr163mu/8EICV9bxQUFMDe3h47duyg/ztz5gwKCgpkQGgnJydYWVkRCN3WuZP+9759+yAUCuHj44Pu3bvDyMgIKSkpdO2qqakhIiKCmFPFxcUoLi7GsmXLqCh2dnaGr68vrl69ih07doDL5RJYk5ubCw8PDxQXF7eSSrX04DA0NCQArVu3btDR0cGKFSvg4OCAnTt34uvXr0hKSoK3tzfk5eXx8uVLfPz4kUBkNkczmS4zDu3YsSOOHj0KX19f8Hg8MpnPyMggpuXChQuxf/9+ClvQ0NDA2bNnsW7dOhgZGUFFRQWdOnXC9+/fce/ePdpQZmZmyhzTQYMGwdTUFJqamti4cSMePnyIpqYmLF++HHJycnB1dYWcnBxiYmKwZs0aVFZWIjo6mpoWqamp2LNnDzQ1NWFkZES+U1lZWbCxscHatWtRW1uLBw8eYPz48cjJyfl/locy2aZAIMDUqVNlAiPev3+PpKQk9OvXDwAwc+ZM3LlzR+b329qgSgNSzEuKJelJj9raWnTs2BGamppUrDc1NeHo0aPQ1dWFnp4e+Hw+Tp06hUOHDiE/Px9c7j/CJzZs2EC+dCx198uXLxg4cGCbpsPS19yJEyfg7u6OXbt2wdvbG7NmzSJmJ2u8GBgY4NGjR/j555+RkZGBgwcPolevXrCwsKDNUlhYGJSUlKCnpwcPDw/k5ubi+vXrsLa2Jrnw4MGDYWBggLi4OGRmZkJXVxedOnXC4MGDERoaCgcHhzYZXC0/958BIP9sSBtOX7x48V8ynP6z95wyZQqlDjIgasqUKdDU1ISPjw8Znzc1NaFTp05QUVGBkpISYmNj4e3tDXNzcyQkJCA2NpYAqc+fP8tIQH80Wp7PxsZGlJaWIjQ0FJaWluByueRrJ+0RqK6ujtDQUKrPeDwe9PX1ERkZiVevXhGr3M7ODpqamlBSUkJUVBT8/f0hkUho89gW2Hn48GG4u7ujsrIS+fn5tP4pKCgQMCLtW2dlZUV+ju3atcOXL19gaGgIOTk56OnpUSNH2rOQy+XCzc2N2DLKysrErNLR0aHm19OnTxEWFoaZM2fS/Sdt/P3+/Xu8fPkSUVFRf+of1vI7/tmQVg/8syG98WdSWxZG0HKMHj0aLi4uVGezwXyGjIyMIBKJwOfzaR1jAQzMM6qyspJkpKqqqq1kUtJ1nfT1PmfOHPTr1w/Pnz9HUVERJBLJD/3zpMdvv/0Ga2trDBw4EMOGDQOfzyep7fnz5+Ht7Q1nZ2cAwOvXr/HTTz9BIpFAT08PlpaW1HxlABFrvkszpKytrcnjMDExEc+ePYOrqys1Lo8ePQpvb2/Y2dkhPDwcWlpaxLZnlgasEcPsNliqHJMTS4NLioqK5HnIgj1UVVXp/rKwsCDmvfSxZ4BXu3btKEhFusH/4sULXLhwAZWVlf/0mmvJiGRAqLe3N7p06YKTJ0/CxcUFX758wY4dOyAQCDB69Gh0794dnz9/xsaNG3Hv3r02X/vevXtoamrCgQMHoKWlRYAl86wcPXo0qSVcXFwwZcoUlJWV4dixYzK+nJcuXUJBQQGGDh2KhIQEaGtrkyUKG/v378eoUaP+ZkL9Pf6rxv85MKpl1156kWi5uejTpw+4XC6GDx9OE8iVK1cgFAqhra1NTJ8PHz4gIyMDfn5+KCkpwfLly+Hg4IB9+/bB1NQUkydPxpMnTwA0x74yo2kOp9nDBWj2S2HvxW7yqqoqODs7U9dEVVUVmzdvRlxcHJSVlWFubg4DAwOkp6ejsbGRNgQmJibw9PRsc7KoqqpCly5dqBvPPpOJiQm8vb0BNE9sXl5eUFBQQHp6Oh49eoTw8HCi+W7atAkuLi7o2bMnFi9ejBUrVmDNmjXQ1tbGlClT4O7uDnNzcyQmJhLYUFZWRh47Pj4+Mh2EN2/e4P79+7h79y7FKwcGBuKnn37C0KFDweVy8fz5cwDNXkwuLi5wcXFBdXU1Nm7cSDKCkSNHYsKECZCXl4erqyvs7OxQXFxMhRyHw0FQUBDEYjEKCgqwZcsWeHh4wMTEBBEREZg9ezZ1F7du3QpbW1toa2tj5syZ//K1tW/fPigpKWH06NGwtbXFoUOH0LlzZzg6OuLnn39GU1MTKioqsGvXLpiZmeHixYu4fPkyZs2aBR6Ph/Hjx9MxOnjwILZt24bTp0+jsbERR48ehUgkQnh4OPz9/Yk2n52dTV1CS0tLeHl5wdPTkzo2zMMIaC6+li1bJuMjdubMGQQEBEBFRQXjxo1DY2MjPZ/J2nr16oXBgwejoKCAQDAGqOnq6iI4OBjGxsZQVlYm6jxjjUgXB0yD7+XlhUePHqG6uhpJSUnIycnBnDlzUFhYiOXLl0NXVxcODg7gcJrTd5jJN3udu3fvkom89Pdra9y8eZMALR0dHQI0z549CwsLC0r5YvG2rLC2sbGBsrIyQkJCcOTIEQQGBsLa2hpisRgODg5QUlLCggULAPxjk8uozhKJhGjh5eXlKC4uJkCaGcgfP34cN2/eJIYcAwGYCaiWlhbGjRsnYwYrEAiocFq9ejUSExPB5XIpkSsvLw9mZmaIiYkBj8fDrl27ZI7Ff5IZBQDjx4+Hrq4uDh06RLJd6ffesGEDMetYTP2fdbI/f/6M4uJi8uDo06cPbZYYoFNXV4e1a9dCU1OTIoeli8cjR45AU1OTEuZcXFzIbyQsLAxmZmaIiIiAQCCAUCgk2U5bG9opU6ZAS0sL58+fp+/HNq5aWlowMDCAo6MjgoOD4eDggCdPniA4OBhycnKwsbGBnZ0dtmzZgg8fPuDixYswMzOja4htPBISEhASEkKeV3v27IGSkhICAgIgkUhQXFyM+vp6XL16FTExMSShYR47zBumoaEB3759IznS6NGjcffuXVy/fh0jR46EqqoqDA0NiekjPRhrQVtbmzw6JBIJoqOjcfXqVdpIMU815hHDwhy6du0KOzs7bNy4EQ0NDaiurpYp5v9fBksncnd3x7Zt24jBBQA5OTmIiYlBTU0N2rVrh8WLF/9L71dVVQVPT0+SmLEfNpqampCamioDSAHNMupOnTph9OjR+PXXX6GlpQV5eXmSxrLwifLycqiqqrZaiwHZ4yJ97dXU1OCPP/5AaGgo4uPjERoaCm1tbSxduhQPHz4kOYqcnBw6deqE4OBg2NnZ4du3b3j16hVUVFTw888/Y/bs2RAIBDA3N8fnz58p6OLAgQM0NzGfyJycHPJTy8rKQnp6OlJSUpCfn/8vAYr/L/PN/9RwWvrYHTx4EIcPH5Y51sxw/dy5c7h+/ToCAgJIevX48WNUVlaiT58+mDBhAgQCAWJiYhAbG4uhQ4eS3UBSUhJUVVV/KAH90XFoamrChAkTIJFI8OLFCzQ2NiI0NBQZGRkUclBQUIAxY8bA398fOjo6tHG2s7MjyThj7jKQ4datW9i0aROmT5+OwsJC9OzZE/7+/pSa2dDQgEePHskcm9LSUvTu3ZvquylTplCNyYymfX19ZRjzampq6Ny5MzicZvPyJUuWkDdddHQ0Dh06BF1dXWKlMGYL85szNzeHpqYmVFRUoK+vj/r6etTV1eHNmzeIjY1tJbErKCho0/j7R/5hwH9eNsRqUukwgjVr1sjsKbZv3w4HBwf8/vvvbf4+Swhk4ApjOI8aNYrM47W1teHv709SqqSkJBkmVFuDNSs3btyIJ0+e4PLly0hKSkJsbCxdKz8CTz99+oQlS5ZAQ0MDAoGAGGNNTU2ora1FWVkZ1UnSoA/zVmK1U0sQigGQDJBidaC+vj6WLFmCS5cuIT4+niRx8vLy1CBizXG2b9LT0yOrEy6XC3Nzc0rElWZosdTdoKAgGBgYYPbs2XBxcYGfnx8cHR2hqqqKiIgIqKurw8LCgvzPioqKsGHDBjJhDwkJoebln81lf/Wak37ehQsXEBISgsuXL8PExASDBg2Curq6jNfllStXEBMTg8rKylavdfXqVfB4PKxbtw5xcXEkA926dSv4fD75yi1evBinTp1CSEgIhg0b1qanmvR3u3btGpKTk6Gvr//DOfZvQOrv8d8y/k+BUS0juD08PMgPgG0uLly4IJMmkZGRAV1dXQwcOJD0ssbGxoiMjERycjJN7O/fv0dGRgbFq9ra2lI8p5GREYYMGYJTp05h586dOHToEPr37w8PDw9oaWlRMXvkyBH079+fgKvGxkZKJhIKhdDQ0EBVVRWePHmCTp06EcpvYWGBuro6TJo0CQ4ODsSeAWQni4qKCvj5+cHX15dinZ88eSKTbJGQkABnZ2fyX2KJJzY2NjJ0+LKyMri7u6Nv374oKSnBqFGjZJLv1q9fj7CwMMTHx5Nm/uHDh7hx48Y/lbrduXMHMTExMDU1hVgsbkWfvnHjBpydneHq6oqCggJkZGSgoqKCNussOt3NzQ2TJ0+mDQGLYmY0c+YjIi8vD4FAQElQMTExsLe3h6WlZavv/VeGtLfVrVu3aJN09uxZdOnSBc7OztizZw/s7e3h5eWFQYMGAWgGiGpqarB48WLweLxWGn82Bg0aBD6fj8uXL2P58uXEYAsJCcHixYtx8ODBVl1CacZQy8V0xYoV6NmzJ2pqalBdXY358+eDy+VSqtSqVaswdOhQmJqawsTEBA4ODnj48CGysrJkNj/l5eUYNGgQrK2tYWJiApFIhI4dO2LMmDHQ09Oj88OK6m7dusHU1BR2dnYIDg6GtrY2JBIJoqKikJSURJJMVuSyDhifz6dNfUu2V8vFsSWQMGrUKCqGZs2ahevXryM2NhaBgYEoLi5GWloajIyMEBUVBWNjYygpKSEtLY1i7cPDw3Hq1ClcuHABq1atwpkzZzBs2DCEhISgpqYG586dI4bU5s2bweE0G5FLR1S/ePEC/v7+4HK5MpT7/v37w8XFBUAzQMYKN+nutLe3N/h8PiQSCbS0tKCkpITq6mq8e/cOurq64PP50NbWxtu3b3Hs2DFER0fDycmpTaDhPzUePHhAzCCgeYN+/fp1zJkzhx5bs2YNvLy84Ofnh5s3bxLw2dacsGTJEiQnJyMsLEzm/Jqbm4PP5+PChQsywCljmnbr1g3Hjx/Hb7/9hjNnziA/Px9KSkpwdHRE+/btKVLayckJv/zyC4YOHQoXFxfo6emRH0xbQNS7d+8QGRlJsrjnz59j79696NOnD7Zu3Yrs7GxKskpNTaXv9Pvvv2Pt2rVYu3YtGhoayIejuLgYCQkJBGotWrQIWVlZiImJQWhoKLG3mCSGy+VSIc0MzhsbG5GRkYGQkBC8fPlSpvsqvTkrLy+HSCSCkZER7Ozs4OLigokTJ5JJuTQzp66ujuRtzEMwKCgIQUFB5BNUXFwMJSUljBgxAr///jtevHiByMhIeHp6EgDavXt3qKmp4eDBg3QM/11g6NWrV+Hi4oJu3bpRmEVubi7s7e2RmJgoI/v+VwfzPho1ahTs7e2hqqqK/v37y0hYmByKNQqAZglY9+7dsWHDBigoKMDU1BSDBw/GgwcPZMInXFxcYGRkhAkTJrR5TKSvvdmzZyM3NxdPnjzBvHnzoKqqCqFQiGHDhhFTIy0tjaSb2tra6NixI9UBN2/ehLGxMRl8jx8/Hjwej9Ikly1bhvfv30NLS4skfZ6envDy8oKNjQ34fD6Kiopafc7/rc3Iv2o4Lf0ZR4wYAQ0NDWIeFxYWAmiWjfr4+MDU1JQYqYaGhjh69Cg6d+4MLy8veHh4UPjGhw8fZOaE+vp6PHjwAAcOHPhTCWhbn+3SpUtITU3FxIkTybMnJSWFghiYdDw0NBQzZsyApaUlbcSVlZUxaNAgcDgcYrLZ2NgQ4CHdQCotLYVYLMbmzZtRX1+PHj16kN9kY2Mj8vPzZaT0ubm56NatG7p27QonJydiobAwEWtrawQEBCAuLg5KSkpQV1en5GNra2tKV/bx8UFAQAB9Zuk/BQIBbGxsEB4eDi8vL5LY+fn5tZLYsePI7BiY8Tf7/z/zD/tPjrVr1yI+Pp5YcV+/fkVUVBRcXV2xcOFCmTCCqKioNj/TmjVroK6ujoqKChngzsPDA4MHD4aamhpMTExgYWGBsrIyNDQ0YPfu3UhJSflTluGRI0cgkUharfm7d+9Gu3bt/hQ8ZZ9z165dZNjN5IfsPb99+4ZJkybROWWeYCz8QzrIRtrsnjWPWPgM+1FSUgKPx4ODgwPmzJmD7t27E1suPDycmPV6enpQU1MjGalQKKTQH+ZVqKioiMjISGKKe3h4kB8b+0lISICRkRG4XC41gFgKIEsnZsEJHh4e5HsbERHxL+8F2hrS5+7Vq1ckSQSAuXPngs/no0+fPvScL1++ICEhATExMW2e9xcvXqCwsJCSqNXU1GBhYQFFRUVMmDCBPNV27NiBadOmYdOmTTKA77x582hubzmuXbuG1NRUGBkZEfni7/H3+G8c/6fAKDYmTZoETU1NnDx5Eq9evWpzc3Hs2DH06tULa9euRVZWFuzt7akD/Pr1a2zatAlhYWFITk6WYUjFxcWR0STr0mZmZlIKkYaGBszMzBAdHU0+Kmpqapg5cyZCQkLg4OBA5rdsLFiwAH5+flBXV0fXrl1x4cIFPHz4EKmpqeQb9f79e9y4cQOzZs2iDXrLgmjJkiXw8PCAmpoapTawDbWNjQ1sbW0RGxuL4cOH4/v376isrERAQAA4HA7GjRsHQJbOvGrVKtIka2pqUjHAxoYNGxAWFtZmJ+dHiyl7vLCwEIqKivD29iaDdenfuXHjBtzc3Mh36JdffoGqqio8PDwQHByMgQMHypgZ8vl86OnpyWjK1dXVKXVMXV0d7u7uePLkCW7duoXs7GwYGxvj/fv3P9wks/Fn3lbsuDNZ0oIFCxAREQF5eXmIxWKoqqqSTw0bDJBSUFDAsGHDWr1fSkoKlJWVCYArLS2lLqGuri78/f1JltVWl7DlsZ80aRIVQDU1NQCajeEZHV9RURGGhoZQVVWFiooK0tLSUF9fjwsXLlBhYGxsjMGDB+PkyZMQCoWQSCSUYqekpITz58/j7du3JFnx8fGBgYEBUfrl5eWho6ODS5cuoaGhAbt27SJpy4gRIyAWi3H69GlUVlaST5StrS3u3r37ww2R9PdkKZRAc1w7K4wMDQ3h5+eHwsJC8Hg8SgXS0tJCfn4+Mfy6detG0hrGZmTFW+fOnSldydPTE6WlpfTejOXSvn17vHv3DkBzp5/dbyoqKjhw4ABGjRpFXbk3b97g999/p+uXbQYOHz4MX19fKrT4fD4MDQ1hYmKCkJAQODk5UZw2k/LExMTAw8PjX5Ih/KujZYLLrVu3YG1tjb179+Lw4cPo3bs3XF1dYWJiAmdnZ1RUVJC5vzS1veXrsD+nT5+Ojh07gs/no2/fvsjLy8P169cxbNgw8Hg8rF69msCTpqYmVFdXE+ssKCiIjrOysjIZ4VtaWiI2NpY2VAYGBtQxdXNzo9Sitq6t9+/fw8DAAAUFBThx4gRcXFygpqZGzA2WkNm5c2cMHDgQX79+bfP4szklOzsbAQEB+PTpE2pra+Hm5kbd6pSUFOjq6pJU6d69e/D09IREIoGKigqZmDY2NmL+/Pnw9PTEp0+fZM5Ly/Hs2TOcOnUKVVVVePPmDUnc2PXZ1NSEq1evEkP22LFjlGy6Z88eREdHIy4uDqdOncKECRMQEBAg41vx/PlzeHt7QyKRECBVWFj4HwMuqqqqYG9vD11dXXh6ekJZWZlCCKKjo2USy/7KkH7exo0bYWpqioqKCpSVlcHKygqpqakyCUIdOnQAh8Oh7nFQUBDds0uWLMGcOXPg6uqKvn37IigoCFOmTMHLly/Rq1cvunZ/NC5cuICcnBxoa2sjISEBK1euxJcvX7B06VLyXzl27BiuXr2KlJQU7NmzB5WVldDT00NwcDAqKipw4MABxMfHw83NDQ0NDQRwjhw5kiTDZ86cwZUrVyilSSQSYdSoUTh8+DDq6+vRpUsXGTPb/z/HPzOcll6PHz16BGdnZ/z666+4fPky5s6dS8xjNhjzmPlFiUQi8vMBQIwLaQYku3e3bNlCbE02/kwCytJww8LC4OrqCmdnZ1hbW6O4uBibNm2CtbU1JViJRCLIycnB2dkZlpaWMDExgZ+fH8LCwsDhcNCuXTsAoM26RCKRkWMvWbIEIpEI27Zto/dnvmdAM7tULBZj2bJlxMZSVFQkAIDH47VKNGPrrlAoRGlpKfr370+sFTs7O0ycOJFS3hizh4FdTF4fERGBkJAQqKurIyIi4i9J7KT9w6THX/UP+3ePVatWwdfXF5mZmdSQ/lfDCNjc+fHjRyxevJjSUk1MTEjm7+/vjx49emDWrFmUICv9Gj/6bKy50PJ5PwJPW7L5nj59ijt37qCkpAROTk4yKby//vorgoODwePxMHz4cPj4+GDw4MEyPkuMncTlcok1K30dSTPsWIMxJiYGPj4+8PX1xcSJE+Hi4gKxWAyhUIhx48ZR7c5ALx6Ph8DAQERERJA3FIfDgYmJCfn1GRkZQVdXFwoKCsjPzyefW3d3d3A4HHTp0gXfvn1Djx49qFnK0pqdnZ0RFxeHoqIiXLt27Z9Kgv/VwVQkvr6+mDp1Kt69e4dv375hwIAB4HK56Nu3L3r16oXw8HAZ0LCt815WViYD+jLwrqSkBJs2bYKhoSH5ALIah3kfKysrE+urrXH9+nWEhITQfPP3+Hv8N47/c2DUixcv4OfnJwOctNxcdO7cGd7e3vD09IShoSGSkpIgEAigqqpK7B+2YY6OjkZKSgrpamtqakgCJS8vj9jYWOjq6qJPnz7UQdLV1aUucVNTE/r06YOAgACkpKQgODgYRUVFJFd7/vw5vLy8KFKXJRglJCQgKiqKFn2WsMFGW5ufpqYmbNmyBc7OzkT9PnbsGHbu3In8/HxoaGggNTVVhsZbVVWFGzduoL6+nrrs0nr5LVu2YNy4cbC0tERUVJRMMQQ0S/qcnZ0xcuTIPz0vLb0yjh49ikOHDiExMVGm6wU0m26/ePECly5dolQx1uVgbChp0015eXno6+uT3JEllbHJOzIyEhYWFiRxnDlzJtTU1LBlyxY61z8ajx8/pr//yNuqqakJW7duJW8sMzMzmJub4+7du5RsxDawbHz+/BnTpk1DUFAQHXN2fvPz82X8r9i5PnDgAHg8HnR1dbFx40Y659Lj7NmzZChcUFCAFStWUKwvKyoYGDphwgQIhULExcUhLi4Otra25FXDihiWRiJNxReLxTh8+DBu376NgIAAaGlpISoqCkuXLiVfHBZre/z4cRw7dgyurq4YMGAA6uvrsXXrVggEAixbtgxAs0kni5GXSCRE8+/evfsPz01LjzRbW1toamoiKCgIO3fuxC+//AIjIyOEh4djzZo1cHZ2hqKiIvT19anTJhAIkJeXB3Nzc3Ts2BE9evSAvr4+li5dShr79+/fQ19fH7169YKGhgaOHz8uw0wBQIXPsGHD8ObNGzx48ABKSkrUnWQAyeLFiyEWi/Hs2TMkJyfD1NSUUmpYR9nNzY1YNxwOB1OmTMHEiRMxceJErFixAr/99hvc3d0hEolgb2//TyPO/51DWq4UEhJCzKUhQ4bgwIEDqK6uhre3N4qLi2V+70cFdkufjX379iE2NhZ8Ph8mJiaYP38+Ac2MqQMAHz9+RN++fZGdnQ0dHR3k5eVBLBZTlHiXLl0QFRUFPz8/YksaGRkhLi6ONkPSG86Wo7GxEStWrKCNa0ZGBhITE2FnZ0febh8+fMDWrVuho6NDnoE/2jycOXMG8vLycHR0hImJCRQVFeHq6oodO3bg5s2bMDIyogTKXr16YerUqRAIBFBSUoKTkxM+fPiAP/74A0FBQUhLS/uLZ+sfQ5q9CTQboDKGDJ/PlzHmra+vx969exEbGwsvLy8MGTIEnp6edK7YtXbkyBGoqqrCxsaGknyA/9w1eP36dUonmjVrFsm+GUvxrzCjiouL8eDBA/r38ePHMWrUKJngh/Pnz8PDwwPt2rWjRL2DBw+S5wdjWPv4+EAkEuHcuXN4/vw5CgsLIRaLqfEUHR1NDSmg7WvjwYMHMDMzg1AoRHx8PLhcLgFedXV1FFahoKBA4SXsPjh+/Dg1RYYMGYK4uDjMnTsXAJCcnEzy1P79+0NfXx8GBgYwMzODSCRCcXGxDMjf2NiIiIiIHzJ1/zfHv2I4PXv2bHTt2pWYxwD+KfP4yZMnrcygfX19weVy6f6Qfi0mAf2ro7a2Fvv376cmmJaWFsmSGAuXxb7r6+tTQ6Jv374wMzODvr4+OBwOxGIxmeLHx8dDXV0d8vLy6NmzJz5//iwDRAGtQwIGDBgAFRUVWFlZIS0tDaqqqrCzsyOplUQigZOTE3x8fKChoSFj8iwnJ4f58+ejsbERjx49IuNzDQ0NKCkpUVAMe76Ojg75IU6aNIkaKMrKyiSxa9mAaGuekPYPu3Tp0r/sH/Y/HT+atzdt2oTAwEB06dKFaua/EkbAvmNxcTH09fUxatQofPnyBQEBAWQnwZg+EokE165dI+mj9O+3HOxxaf889jg7nm2Bp9J7hVevXuHz589UA7558wZz586Fo6MjBgwYgEOHDpGXmUAgwN27dzFp0iRoaGjQHkVausfj8RAWFgYdHR1oa2sTK14gEEBHRwfx8fFISEgAl8slOZ2rqyvevXuH5cuXg8fjwd7eHnv27KF7gXlsMp/Q2tpavH37FgKBAA4ODvDz80NgYCDCw8NJCmpubo6zZ8+isrISVlZW8PHxgUQiIQCWXbeswc0sKCwtLfHly5d/Kgn+K0P6vK1evRqamppYvnw5MjIy4O/vj/T0dDpnq1atIq++8ePHt2JctmzczZ07F0KhEH379iVjdjMzM7i4uCAvLw9BQUHQ09Ojmr+hoQELFiyAUCgkSf2fjQcPHvyPPP/+Hn+P/yvj/xwY9eDBA6ipqZFchA3pzcWoUaPw888/A2jueqqpqUFZWRnbtm2TYU1VVFSguLgY8fHxCAoKwogRI6iYbWhoIENo5i0TGRmJAwcOUDHLFheg2QiwsbERp06dwufPnzF27FhIJBLMmzcPFy9eRHR0NFRVVSEQCKCnpwdfX1/Mnj0bOjo6UFBQQEhICADQJpmNvXv3Yv369Vi8eDEV5sz018bGBj179oSpqSkiIiJgb28PHo+H0NBQoh+zwZgHbMyZMwempqbkSzJ//nz4+vqiV69eFH/MxuHDh/90EyL9ee/evYsnT54QqHX37l3ExsYiPDwcW7duJWBBVVUVAQEBWLJkCS1a3t7eaNeuHQoLC8lfKDo6mjp0CgoK1LVjCWzKyspo3749goKCoKGhAU1NTQgEAiri/mycOHECQUFB/9Tbisk+X758iUOHDqGiogJv3rxBQ0MDPn78iDFjxpC5IBtMn8+MhAcOHIjp06fj8ePHuHbtGuTk5KCvr4/Y2FicOHECmzdvhoeHB0QiEcLCwhAZGSlzvoDma0xRURHp6eno168f1NTUKML827dvKCwshI+PDwYNGoQPHz5g5cqVCAoKAgACzeTl5bF37158+vQJw4YNg7y8PDIzMzFnzhyZGF99fX2Ym5tDV1cX2traUFRUhEAgwIIFC9DU1IRZs2aBy+UiLCwMr1+/xpgxY9C5c2fs3LmTuq5sLFu2DBkZGRgwYACxHaQ9sP4sqppFv+/atQurV69GUFAQSRDv3bsHHR0dkkaoq6tj165dxN5iHd/8/HxYWFggPT0deXl5rYws79+/D29vbwIvWQQ7Y/uUlpZSsgyjQ+fl5UFPTw/Lli2DtrY2PD09cevWLZiamsLKygqWlpb4/v07fv75Z1hbW8PW1hYGBgbo27cvli5dilmzZkFBQQF9+/ZtJV34/Pkz3r17h/v37//LRq7/08ESFseOHUuP7du3j4p0NoKCgjBnzhwAfy5LmjdvHjp37ozQ0FCMHj2aAJ23b9+ioqICQqGQNmZMqjJu3DjMmTMH4eHh8PDwQGJiIkpLS5Gfnw8HBwcIBAJkZGRAXl4e3bt3h42NDfT09GBkZAQnJ6dWkra2RkvpVE5ODsaPH4+NGzfi+fPnxI4yMzPD5s2boaur+6egKRuXL1+Gr68vFdMsKEA6LcrAwADq6upQUlKCQCCgBCIjIyOkpqYiJCSE7vl/RarS1NREzZMuXbpAV1cXc+fOhb29PQQCAezt7WXAPgDYunUrhg0bhmvXroHP57diLOzfvx/t2rXD2LFj/9eKWOl0Immj17/y/nfu3EHnzp3pPD19+pRAaSbrYuPcuXPw8PBA+/bt0b59e5KAGRgYwNzcHOvXr0d1dTXc3NyoK29lZQVjY2Okp6fD0dERycnJf+otxEafPn1ovWI1C5tTxGIxGfIbGhrKMLUbGxtx8uRJWFtbIygoiNJvt2zZgps3b5J0A2huqJw8eRL+/v4k3aivr0dNTQ1OnTqFxMREuj/+r4x/xvSsqanBiBEj/kfMY/Yc6e9eWlr6p8m/Pxq7du0i8/xRo0ahf//+KC8vh0AggKamJhQUFDB9+nRERESQdCg3NxeFhYUICgqCSCSCk5MTbGxsaE3y8vKi0I4NGzZAX18fQUFBOHz4MLhcLnr27Al9fX0ZHyXpcePGDXotBmQuXLgQX79+JZYVM7FnskCRSEQgA5MJ//rrr7hy5Qri4+Ohq6tLLP3y8nKsXr26FTP93LlzOHfuHLy8vJCQkIBDhw5BRUUFoaGhf1li9z/1D/t3jEOHDrUCcjZs2IDAwEB07twZV65cAfDnYQTSf1+4cCE4HA569+6Nuro69O3blzwxNTQ0EBsbi5qaGkqt/KvzaMvmAhttgafSr1lcXIzg4GA4OzsjPT2dTMvfvHmDefPmwd7eHkZGRtTk5XK52Lt3L7y8vGBtbQ17e3uIxWICnBhLR0tLi9KqeTweWXDY2dnh/fv32LdvH/Ly8jBkyBCcO3cOHA4Hv/76K6ZNm0ayeQbeSiQSel2hUIj9+/fj48eP2L17N5ydnSlEIyoqCvr6+jLeara2tpgzZw7Ni4aGhrCwsKBEPgMDA7i5ueG3337Djh07YGRkRMzLP5ME/6vjyJEjGD16NKVEAs01rr+/Pzp37kz7p5bNuLZM6m/fvo1z585h+PDhCAwMRHV1NfLy8uielZeXh6KiIvllLVu2DPX19cTelf4MbY3/Dcnr3+Pv8b8x/n8Fo9q6kR48eABbW1uUlJS0mtzXrVuHIUOGENW3sbERVlZW4HA4SEtLa8Wa0tPTQ1lZGdasWYPMzEx06tSpzWJ22LBhZM4NNHfCWTG7f/9+AKBJrqmpCYWFhVBRUUFUVBRtwi5fvoygoCAyDWTaYJFIhMOHD8vovdnIy8sjfyvmjbJ9+3akpaXJaKxZismBAwfA5XJhYGCAqKgo3L59u83NWW5uLpSVlZGbmyujI541axb8/f3bBKRavkZb52jixIlUeLFj29jYiHv37iE+Ph52dnakd1dRUcHIkSOhoKCAnj17IiMjgwofZnTI5XLJdFVdXR1isRhmZmZQVVWFuro6cnNzMXPmTHC5XBgZGcHY2BgKCgrYsmXLX+rg37t37596Wzk5OcHV1RXV1dUYO3Ys7OzsoKenB09PT/Tt2xevX7/G27dvUVBQAJFIhLKyMpljMmnSJKiqqqJDhw5QVlZGVFQUjh49ivLycvB4PDKxdnV1hZ6eHqZMmdJml5C95p07d0iyxMxc2XdlgJSvry8GDx6MpUuXol27dlizZg0EAgEmTZoEiUSCxMRETJo0CaampvDy8sKTJ0+wd+9eKCkpwcrKCiKRCMrKyti4cSOOHDmCrVu3IisrC/Hx8Xjz5g2+fv1KvjiBgYH49u0b9u7dC3d3dxkzcKDZTDMhIQHDhw9HXV0dqqqqyP+qZbpZy1EpFf0ONANTXbp0wbx586CkpIQzZ85g48aNVFh17NiRutYlJSXo1q0bFeODBw+GiooKJkyYIONPBDT7sYhEIuzbtw+LFi1CWloaIiIiMHPmTHz58gXfv3/HsGHDoKGhAWVlZfTs2RMWFhbg8XiorKyEUCiEpaUlPn78SKmSz549w5s3b3Dx4kUKMjA3N4eenh569+4NoBnsYRHx3759o2PB5pT/lxSrf3VUV1djwYIFUFBQIEkvGzU1NZQe6eLi8k83taNHj4aWlhZKSkowa9YsWFlZwcvLS6Y4q6qqgo2NDfz9/XH8+HEsX74crq6u8Pb2RlJSEr5//46QkBBcuXKFAiMWLVqEpqYmbNq0idgHXC4X6urqWLduHV1Tf2Xk5eVBV1cXw4YNQ0pKCvT19WFlZQUnJyf89ttvGDduHOzs7MDlcpGcnPxPi7ry8nKoqalRWtTEiRPJeDQuLg4XLlzAtGnTMHr0aEyYMAHh4eFkNi0SibBmzRp6j/+JVKWpqQk9e/aEUCiEUCikZNPKykp07NgRzs7OrQApNlauXAl5eXmMHDkSFy5cwP379xEfH48xY8bQc/63vIWk04lu3779L/0uO3579+7F27f/H3tnHR3l1XXxzEzc3ZUE4m4QIQmQkECw4AS3UmiBIinu2lKkOMWd4i4tQV+cQApFCxQvLkmxyO/7I+u53wwJ0hYJ7ey1ukpGnnn03nP3OWfvuxw+fBhnZ2eSkpLEokT6zKFDh7C1tcXKykq0gA0bNgwNDQ1iYmJErODp6SmqbiUR9Vu3bqloepUE6Xx17doVbW1typUrR6dOncjOzqagoID09HSSkpI4dOgQM2bMQCaT0blzZwICAgQx+OLFCxo1aiRaUSWHW2WCs1y5ckRFRalo9Ujj644dO0hNTf2g1ZV/FyWNcVeuXHlt5fGoUaNE5bEyCgsLix17YWGRhX1Jzr/watOFxMREDA0NiYmJQU9Pj2PHjgm90oiICDw8PGjcuDF9+vRBoVCI+C4uLg4PDw+0tLRYsWIFX375JbVr1xa6inK5HGdnZ0xNTdHW1hYV2ocOHeLevXsqcZly9YSEDRs2CHFpY2Nj4uLiWLt2Lc+fP1chkWxtbTE0NERfX5+1a9cKnUipoiQ4OJiYmBiuX7+OiYkJOjo6NG3aVLReSQLcGhoaJCQkAIhYeOPGjaSlpf3lFru/qh/2d6F8Tx07dgwnJye++OILoYEqYc6cORgZGdG4cePXmhEoY+3atXTr1o3atWuLsXP79u1ER0djYGAgYjqpevp1LVolQUouvC152qdPH6ysrFiwYAELFiwgOjoaDw8PMe7dv3+fKVOmYGNjQ0JCgtC4io2NxdHRUWg8SRW8+vr6GBkZCeKoXLlyHD58WJjCmJiYCNOh1NRU4V65b98+fH19+e233wgICBCV9lKMZmpqio6ODi4uLiLGT0pKIiMjg/T0dFxdXfHx8cHLy0vIPpw7dw4XFxecnJwIDQ1l2rRpwrnO1taWHTt2iPtJijGk+2nnzp2vbQn+q9i9ezd+fn5YW1uLOA2Kruv06dNFpd0ff/xR4veVx6o+ffrg5eWFra0t9vb2WFlZcfnyZSGHIRnDyOVy9PT0iImJwcXFBS8vLzQ0NBg3btwb91f59w4ePCiS7Wqo8anho5FRyoP2gwcPRGsSFDntmJubk5mZKT73559/UqNGDZo3b87jx4/Zs2ePENr77LPPVKqmpEV+kyZNaNOmjdiuVJX0umBW+r1Dhw7h6OhIr169RFvE+fPnuXfvHvHx8XzxxRcoFAo+//xzMXkcPXpU9KSHhYWho6ODubm5aKNTPubZs2dja2srsjWrV69GQ0ODTZs2ceLECVq2bCkIqb59+7J48WKMjY2ZOnUqO3bsUBFJVM5CJiUlIZPJ8PHxITY2lqioKKHpBEXVAlK7yMsuWq/DkCFDsLKyYuvWreTm5lKnTh1MTU1FdmbhwoUisK9WrRovXrzgwYMH1KlTR7RDSkGUgYEBXl5ehISE4OrqSkBAAFu3bmXTpk0i62RiYkJqairff/89TZs2FS4cUkXUmyb912lbKUPStpIcGKWWFcnBSApebt68Sb9+/ZDJZEJn5eTJk9SrV499+/YBRS0E0dHRVKpUiZ9//llkCaXJSMoS/vbbbypZQuVjmT59uhB/bNasmajakj7z7Nkzhg8fjqurq0qpfbly5Vi9ejUXL17ExcUFfX19tLS0GDp0KNu3b6dMmTJMnjyZlStXEhAQIL4nEXQtW7YkOjqa1atX07RpUxFklS1blpycHJ49e0abNm1wdnbm+++/Fw4wycnJBAcHF6v4eNOiSLJ+NzIyYtiwYeL1Fy9ecP/+fSIiImjZsiU3b94UgZVU1ixVQty/f18I23bp0oVjx46pPAurVq3i999/F26BKSkp2NvbEx4eTkxMjCCxGzRoIFrsLC0tsbGxoU2bNjRu3JiYmBisra0pW7Ys9+/f58iRIwwfPpyKFSvi4eFBmTJl+Pnnn2nevDmamprCUScuLo7k5GQVguvQoUOkpqaWuMB6l3jVtnNzc5k4cWKxrOyMGTMIDg4mISHhjYva48eP4+fnJ56L9evXqzjbKePo0aOEhobStm1bESQtWLBAuKFK7UiSu4+0SL927RrR0dG0bNmSqlWrisWQ8hzxOmzevBk3NzcOHjxIYWEhAwcORC6Xq+g65Ofnk52dzdKlS19pHKCMPn36EB0dTUFBARkZGVhaWjJs2DCcnJzQ0tLC3d1dBMrSPJOZmUmfPn3w8fGhevXqYpz4O7h7965IUjRq1EgleSIRUiEhIfz8888lfl+5YsHR0VFFhPhDZ1cld6KSHKzehJs3b+Ls7EyLFi24d+8e+/btw8nJiZYtW4oqUiia52rWrMkXX3whXsvJyRFJER0dHZVYIT09nebNm7+ySuJVOH78OHK5nDp16hAcHEzbtm05efIkDRo0EM6/L168YO3atbx48YIBAwZgb2/Pn3/+yZw5czA1NWXmzJloaWlRo0YNEhMTiYuLY/bs2W/U6lEm/5VfL21QPo+SWcG9e/fIz8/n6dOnJVYeA6LyGIrfo6869pedf5XfKwl//vmnGH+kdhhJD2fy5Mn8+OOPeHl5oaenR926ddHX18fe3l7cQ1paWmRkZNCpUycGDBhA3759RQWShYUFLi4uzJgxgwkTJvD48eNi+yT9vXfvXhQKBU2aNBGvZWRkIJPJhGZmdHQ0DRs2FK53UpuVJDI9depU1q1bJ17z8vKiVatWtG7dmsOHDwvHsvLly6OpqYmOjg4rV66kfv36ov2sY8eOHD58mAsXLlCtWrV/3GL3Jv2wvwvle2rt2rU8ePCACRMmEBYWRufOnYsRUpIZgTTHvK7q99atW7i5uYlkqfLYaW9vj52dHVFRUZiZmeHl5cWJEyeAv/b8SZqMb0Oebt68mcDAQPbv3w8UEZWGhoZ4e3tjb2/PiRMn6NixIz4+Pjg4OBAeHi7iMuleVCYw5XI57u7uIkaUZBy8vb1VtKKk1k9LS0t27drFqVOnSElJISYmhm+++UZ81sHBQWX7zs7O1K9fn7i4OHGfJiYmCgOezp07i5bAqKgoVq5cycWLF8W5qFChAlAkK2Bvb0+1atXEuThx4oS4n6RE4Nu0BL8tnj59ypAhQ3B0dKRevXoqMYfUBeHp6amiaVcSpK4YaT0hud5K69G7d+8yefJkvL29cXR0JCEhgcqVK+Pv7y/i0jdB+R6eOHEiZcqUeWfnQQ01PjQ+epvekCFDCA4OJi4uTrDvAGlpaRgbG9OqVSs6duxIbGwsvr6+PH/+nB07dlCtWjVCQkKEttPFixc5d+6c+L6ko6C8TXj7YBaKymnz8/P5448/RNn8rl27MDQ0ZPHixWzevBldXV3at29PXl4eT5484fr16/Tt25c6depQp04dYmNjuXr1arHFXd++fYXWx+LFizEyMhID3MOHD7l8+TIuLi5oamoybtw4jIyMVOyvhw8fzsCBA1Um0YYNGyKTyUSr0dixY0XWVmpRgqJqns8+++y1wfbLQXlqaqoQkF+9ejVmZmYim3nlyhVBLAwYMEAMkj169MDCwoKAgABcXFwYPHiwqBawsLAQzi4WFhbMmjWL3NxcqlSpgpGREZ6enoSFhWFlZUXZsmVxdHRk06ZNKtbBr9vvV2lbvVz2WlBQwP79+3FwcBDl0Zs2bRIORoAQS/7jjz9EGe2UKVOIjo4mNjZWRYfr3LlzREdHU6VKFdavX18sS1hQUKCSJVSeUHr37k3Dhg05ffo02dnZmJqa0qhRo2KCxwUFBXz55ZfY2tqSkZGBlpYW4eHhyOVykpOTRRCRmJjI/v37WbBgAfHx8YLY6tevn6g0O3HiBHXr1qVZs2ZCRF4KZqX/S45Qz549o2nTpgQGBqJQKIiMjKRSpUoqAsQbNmxQeQ5fB2Xr94MHD4rjy8rKwsDAACsrK/744w+ys7NxcnISJd2Sk8m9e/dwd3cnICBApRoqPz+f3r17i8UgFGkkKRQKpk2bRseOHYWmgRQ8zZs3j8DAQMqUKYOJiQlRUVEMHToUd3d3dHV1kclkDB48mK5du2JlZcWUKVMICgrCzMwMS0tLrKysmDNnDk2aNOHHH38kPT2dZs2a8eLFC7Zu3Sr0EsLCwj4YCfDtt98yfvx4ldckQkomk6loQylXG0pBddOmTTl48KDK93fs2IGbmxtQNA4YGhoKJ8Lc3FwWL16sUiF15MgRQkNDqVu3Lps2bRLtSCtXrlRpR5L0Rr788kuioqIICwv724uhWbNmUbFiRaCoXc3IyEi0o+Xm5qpoJEl41UJCukaS9tLBgwdxcHAQts7Dhw9HQ0MDT0/PYq0s0v18+vRpoQP4toRUSfdGdnY2LVu2RFtbW1RBKS9mK1euTIsWLV65zevXr3Po0CF27NjxwdpDXwWpdfXvQCI5W7duzf3799m7d6+Yw0+cOFGsBUx57s3JyWHIkCFoaWmJFrC/q7kknXupyqFy5cp4eHhQq1YtIXIcHx+vct/Onj2bmJgY/vzzT/r27UtMTAwFBQXs3buXc+fOCaMLSatHwl9pTy1NeLlSQLnyuEOHDiVWHr9uGyXhbeOYkl67c+cO0dHRREZGYm1tzYIFCwQxJLU016xZE319fRo0aEDNmjVxcXHBwsKCwMBAYRDSrVs3HBwcMDIyYuLEiZw5c4abN29y9+5dkpKShCPjqzBo0CAiIiLQ19cnKiqKzZs3c/v2beEuK7nmyeVy9PX1WbduHfr6+oIA6Ny5M0uWLMHAwIBp06bRq1cv7OzskMvllC9fnpiYGBISEqhYsaKY21esWMHjx49JS0sjIiKCihUrvtMWu7+iH/ZX8HLMZGNjI+YgyYygS5cugpB6WzMCQGj+nT9/nqioKDw9Pdm4cWOJY+e+ffsEqf53KxLfhjzdv38/GRkZQFFVtVSVfPDgQezt7TE1NcXKykpos2pra2NqaioMipRFyzU0NHBxcRHnQ0dHR1TmODg4EBsby+nTp3nx4gVz5syhR48eQs9VIoqePXtGbGwsISEhtG7dmnr16gk3YQ0NDdzd3Vm5ciWbNm0SpJ6Liwv79u1j4cKF2NraCgOizp07I5fLmT17NhcuXBBSEgsWLKCwsJA9e/bg4uJCVFTUK++nd2X+ouxGOHz4cMLDw+natWsxQmrt2rWvHYdzc3OFBAH8/3qiRYsWaGlp0a1bN/bt28eFCxdITk5m2LBhnDp1Cg0NDeLj40lNTcXT05Pp06cLF7+X12PKz8C0adOEI6caanyq+OBklPJDNXXqVCwtLfn222/p2LEjtra2NGzYULw/YsQImjdvTmpqKt27dxeDtCTcXVJA/TY6Cm8KZpUh6d7cv3+fChUqCKeH/v37k5uby6ZNmwQhtWrVKnr06KGi3/T06VOVfZCEB9PS0sjIyODw4cPC6tnY2FhUVowbN47Zs2eLjJXk/FZQUMDjx4/FOZGwcOFCFeZ93bp1mJiY0Lt3b2rWrEmZMmWEzTi8fYvQgAEDGDVqFA4ODpw9e5YdO3aoLECfPHlC37592bp1qyAWsrKy2LZtG25ubvTo0QNdXV1MTU358ssvCQ0NJSEhQQgiKhQKFAqFaO+Li4tDJpMJQWszMzPatm0rzuc/0bZKSUmhUqVKKsTc5MmTefbsmXAw2rRpk0qW9vnz58yYMaNYC8zu3btxd3fH1NRU6JdJOH/+PBUrViQkJESlLPx1WcLDhw8THR0tsl9Q1C5qampK06ZNuX//PoWFhaSnp9OnTx/R3vb8+XMWL16MnZ2dqB6T7Mr19PTo06cPEyZMQFNTk5s3b/Lw4UNq1qxJUlISXbp0oaCggDFjxqBQKOjUqZNo8ZTJZFSvXp1ly5ahra0t7ivJjWvbtm0qIrp5eXlMnToVCwsLFaHsNyE7Oxt/f3+aN2/OsWPH2Lp1K926dRM2ytbW1uzdu5fjx4/j4eEhqg2bNWtG5cqVMTIyom3btirXXxIpPnToEA8ePCA/P5958+YRFBSEtbU1ycnJKBQKdHR0MDY2RiaT0aNHD86ePUtmZiaBgYEYGBgIUi89PZ2ZM2eK+zQgIIAKFSrg4uKCoaEhJiYmGBgYcOLECc6dO8eiRYuE1fCBAwfIy8vj5s2bHD169INVMeTm5tK1a1d0dXWLLfAePXoknD579uyp8p50PU+cOEFGRkaxQC8rK4vk5GSmTZuGkZGRSjXD3r17ad68uaiWlHDw4EH8/PxIS0sTGeWS2pE8PT3R0tISFu7BwcHk5ub+5cWQ1JYtPcvSWAVFblUZGRnFjBxKgkTGZWdni5YWPz8/5HI5Fy9eZPXq1ejp6REcHEylSpVISEhg/vz5goxTJkgvXrxIxYoVVQwVXgXlcSwnJ4c7d+6Ivy9dukTDhg2F26wypBaxt0Vpbel6G2RlZREUFETr1q25e/cue/fuxdXVlVq1anHhwoW3agGLiopi9+7d/1hzSTJLcXZ2FvqVJiYmmJqaIpfL2b59O9evXycnJ4cqVaqIttAhQ4YQFhZWTFMuMzMTfX19FWOQT10b5OVKgbepPH7fkNqBnj17xt27d4mIiEAul/Pll18KDaquXbsKosbZ2RknJyehLzh69GjGjx+PXC7H39+fSpUqYWpqyoEDB7h69SqXLl0iOTmZsLCw195b48aNw9zcnO7duwvjE7lcTlRUFP3796dnz56inUoiG6QWPmkOkkSrK1WqhJ2dHZUrVxYmMJKkxIsXL2jbtq2IEVq2bIm3tzcmJibi/r9y5Qr79u17py1278sp9uV5XsKUKVOoUKEC1apVY8yYMa81I1B+rs6dO4eXl5eoLr18+TJBQUEkJiYKMwRAuGHDPyPVS8Kr7pNbt26Rl5dH1apVRZv98+fPBdlToUIFtm7dqiJkr6uri4ODA1ZWVujq6mJvby/um6SkJAoKCkQM6+3tLeQbVq1aJY4TICEhAU9PTw4ePMitW7fYs2eP+I0yZcqgo6NDs2bN8Pf3F3GTra0tAQEB2NjYUKVKFTw9PalYsaKIW3/99VcUCgW9e/dmwoQJQpZh3rx5yGQylYrWzMxMvL29hdvyh3AefvbsGYMHDyYyMrIYISVBOj8ljc3SekJKREpxkqSnaWVlpdItMXHiRJydnUWM06pVK8qWLatCSAEiMS1h2rRpKkYIaqjxqeKjVUZt376dmTNnisDj6dOnrFq1ChMTE+rXry8+J+kBSHh5sH55YnlbHQXlYFYipJSD2Ze3vXbtWmHvKgnVSu5sEiHl4uJCamqqyv5mZmaKya1r165CHHjdunVC4FYulxMWFkaNGjWEpX2rVq24ceMGtWrVEj3Z+/fvF4KUwcHBKufi999/Z968eVy4cIFff/0VNzc3oe0zZ84cNDU1MTU1FZVk0vl6GcrHvHTpUpycnDh58iRNmzalatWq6OvrM2vWLPGZ69evExsby4IFC8jOziYwMJDmzZszYMAAfH192b9/vyiDP3jwIN988w2RkZEkJSWhoaGBubm50IUpV64c8+bN49ChQ/Tt25dhw4apuFS8LqB7k7YVFJFEKSkpxMXF0bdvX4KDg9HX16egoIDatWsLByPl47t27Rrx8fHMnDmzxHuobNmy1KpVq1gFyenTp+nQoYMK+fCqLOHkyZNp2LAhderUEVVG0vHs27cPU1NTgoODCQkJwd3dXVShKQv33r59m8OHDxMXF4exsTG6urocOHCA/Px8rl69SsWKFYX2Vrly5VQ0DvLy8pgxYwZyuZxWrVoREhJCRkYGMTExtG7dmqVLl6KtrU3btm1VJkPlSq1p06ZhYmLySlHWV2HdunWEhYXh4+Mjysb19fVxc3NT0cjZvHkzWVlZ2NraCqF2GxsbgoKCeP78ucgW3bt3j8qVK4sqvmvXrrFjxw6aN2/OpEmTaNiwIebm5pQrV47w8HChc6ahoSHaBZUrqyQb6KNHjzJ16lTi4uLo3Lkz7du3x8LCgilTplCrVi20tbUxMzMjLCyM1NRUmjVrRs2aNfH39+f+/fsqx/w+qhhKepavXLlC//79i5FGUJRRjouLIyEhoUQ9O2VMnz6dTZs2AUVtLYGBgchkMr755hvxmadPn5KSkkJaWlqx45PakY4ePcrdu3e5efPmK9uRvv32W/bu3cvu3bvFs/BXF0OnT59GW1sbmUzGnDlzxOtPnjyhatWqtGnT5o2Le2Uy7ubNmwwdOlQE+k5OTvTu3RsDAwP8/PxE9ZZUjfjrr7+qbP+bb75RcXx7HZS/N2zYMGJiYnB2dqZ27dr8/PPPFBQUcPnyZRo3boyVlRV79+4tto3SWiXzrpGVlUVgYCBt2rThwYMHzJ07l4oVKwrzide1gD158oTMzMx3prlUUFAgqhymTZvG0KFD+fzzz0WFt6urK35+fgQEBIjfys7ORqFQFBOX37JlC3Xr1v3LWj2lEa+rFHhd5fH7RGFhIQ8ePMDIyEhUExw6dIirV6/i6uqKlpYWnTp1YtasWejo6BRrcZL+bWhoiJOTE0FBQaLFLjw8HBcXF+HaWaFChWL31svP56BBg1i1ahXDhg3DxsYGHx8f5HI5ZmZm2NnZ0alTJyIjI4tVuLRq1Qp7e3vq1asnqqSk9jttbW0RS2pqalK/fn1u3LhB//79adSoEa6ursjlcszNzUlLSxNaZMr3//tqsXsXuHfvHlWqVFGZ5zMzM2nfvj0//vgjw4cPJz09HT8/P2rXrv3GauQxY8bQokULOnXqpOLUevHiRYKCgoQ+3/uE8n1x8uRJDhw4oJLYuXTpEnZ2dixbtoyCggKmTp2KiYkJVapU4ZtvvmHAgAEq4uTKrnlVq1bFzc2NqlWriva6Ro0acezYMTw8PDA0NMTQ0BAtLS2cnZ1FNefvv/9OREQEGzdu5LvvvqNmzZq0a9dOPBOVK1emffv2yGQyUlJSMDc3x9DQkP79+xMVFUVgYCAvXrzg999/LybLMHfuXLS0tOjYsSMxMTE0btyYlJQUlRZyCS+Lhb9PKBNSQ4YMISoqipYtWxYzHALV+2nJkiVMnDgR4LXriaioKPr06SMI34yMDFHdppxwa9GiBV5eXnz//fdcunSJhIQEEhMTxfsvO3KqocanjA9GRikPtEeOHEGhUKCnp8eGDRvE68+fP2fVqlWYmZnRuHHjYtt4m+zgX9FRkAgpKZjNzMxU0WKS8PXXX2NnZ8fo0aNp3769yCbY2tpSvXp1WrZsiZeXFzKZjM8++0zs640bN0hKSqJSpUo0bNgQbW1tMdhcunSJxo0bo6enR7NmzUSGQypplSqyzp8/T40aNTAzM8PIyEi0NEqD9YYNG1i6dKnKpDVjxgxiY2NFFdaaNWuoU6eOSpvfm7Bz5046dOgg2nwmTZqEq6srNWrUEJ95/PgxKSkpxMfHC9e0o0eP4uPjg7GxMYaGhkRFReHl5YW3tzchISEsWrSIChUq4OrqSpUqVVi9ejVxcXEim5ycnCxaWZRFZN82M/w6bauCggJ+++032rZtS3h4OMbGxgQFBbF69WpOnDih4mD07NkzHjx4QHJysnAwWrlyJZMmTWLbtm2CYNi/fz8eHh6kpaUVI6QkKN9PJWV1Ro8ejba2No6Ojpw6dUq8Lh3zpUuX6NKlCwMHDiQvL0+0twUHB5OVlSXa76BIb026F5s0acKjR4/Iz8/n9u3bTJ8+HW9vb5WqL2nfnjx5Qps2bZDL5fj6+vLgwQO+++47oqKiaN26NcuWLUNPT4/GjRuzZ88elQXSP8nOnDp1CktLS1xdXcVCv0GDBuL9UaNGiXtp27ZtnDhxAgcHB8qXLy8WN3l5eeK83r17F3t7e/r27cvy5cupW7cuYWFhhISE4ODgQL9+/fD09OTQoUMUFBTQsWNHLC0tqVevHtnZ2YLweP78OQsWLCAwMBB9fX1BIt+8eZO8vDy8vLxo0qQJ+fn5bN26FWtra+RyOV5eXmRlZYnzUr169fe+uHpZf085S3z16lX69Omj0gLz559/0rBhQ1F1AbyS8L9w4QKpqal4e3uLAPXatWs4OTkRGxvL2LFjmTFjBpUqVcLPz6+YFgog2pGUnRXfph3pnyyGli9fjp6eHhkZGezYsYPMzEwSExNVBGLfdkyZPn06nTt3RiaTibYGSVg4KCiIp0+fcubMGfT19alcubLKGDt9+nT09fXFoultMXDgQCwsLJgwYQJz5swhIiKCyMhI5s2bBxQR682aNUMmk71Xh6rSjMLCQrKysggNDcXT01MkH15nPqGMZ8+evdNqxZfjBunvtWvXsmjRIhYuXFismltqT+3ZsydHjhzhwoULVK9e/R9r9XxM/JVKgVdVHr/rMVO6FtK+rVy5EmtrayZOnEjXrl0JCQnh+fPnXL16VVQ+2dnZ4eTkRLdu3UTLp+SopqGhgampKf7+/ipVS8OHD2fr1q2sWLGCvXv3Fru3pOufmZnJhg0bWLZsGS1atGD27NlUqFCBDRs28ODBA3x9fYW+pqGhIbq6unTu3Flo/Ej716ZNG0xMTIRYtNROJe3Ppk2bWLlyJfr6+tSpU4c//viD1atXc+zYMc6cOUNubq4gX5TP+ftqsXtXuH//vpjnSzIumjx5Mvn5+dy7d69EMwLlZ/XRo0d8/vnn6OrqkpycLF6XYpxLly4RGhpKcHAwR48efS/H83LrYWBgINbW1lSuXJm6desKiYfU1FRCQ0MpX748enp6osJbLpejqamJlpYWjRs3FhVQ0n2QlpZGly5d8PLyYsSIEejp6aGvr8+gQYPIy8tj8eLFwsFu5MiR4j69c+cOzs7O+Pn5oaOjg76+PrVr16ZChQqC+NLQ0CAgIABjY2Phdu3g4EC7du2EVq5y3Cp1T0DRc2hnZ4e+vr5oUZViufdBwr9qjH7V5549e0aPHj1o167da78rac8GBwezevXqYo6o0noiJSVFrCegqEBBqtAvKcbp0KGD0CYNCwsT52Tbtm1YW1v/5eSvGmqUVnzwyiipTWHSpElYWlrSoUMHlfefP3/OmjVrkMlkKiK7fwdvkyGWgtm0tDRycnIAVBZNp0+fxs7OjrVr14r3Lly4QFBQEI6OjjRv3py6devSr18/Nm7ciI6ODoMHDxbb379/v3BXkQIwaeLZvXs3FhYWGBgYiIHdwMCAlStX8vTpU3744QdOnDghNKTWrl2rQrRlZGRgYGBA2bJl0dTUZOLEiaLX287OTlQX1KhRg969e/8tcWlJVyY/P5+vvvqKwMBAgoKCqF+/PpGRkSLzIWXVCgoKGD9+vCgR19bWZsiQIZw5cwZzc3N0dHSEjaxcLqdx48b89ttvZGZmYmBggLm5OeXLl39rbZW/om0lTXKdO3emVq1ar20ZioqKokKFCiJL06NHD6ytrXFzc8Pb25vmzZsLUeYDBw5Qrlw56tev/0pHKwmvWgDPnDkTCwsLunbtqtLKU9LiPi8vj2PHjhEYGEhoaCgBAQF07dqVPXv2EBUVRZs2bShXrhy2tra0adOGkydPkpmZSbVq1QgNDRXkjbQvY8aMES1sDRo0EPpIBQUFfPfdd0RHR5Oens748eMxMzMjMTFRfHfixImYmJgI8de/g0aNGomsrhTYnDt3TmX/jI2NMTAwYMuWLWRlZREZGUnbtm2FLffL51JXVxe5XI6lpSUNGzbk8uXLpKenU61aNeRyOf369WPv3r2kpKRgYmKCvr4+JiYmJCQksHr1avLz83n+/DkjR47EysoKExMT4Zx56dIltLW1MTAwYOfOndy9e5e0tDRWrFihcp2qVatG48aN32uLjfLvjR49Wrhu1ahRQ2QTb968ycCBA5HJZISGhuLt7a3imveq/RswYABr1qxh+/btpKen4+/vLyorL126REpKCkFBQcTFxdG6dWvxfL283b/TjvRPF0P5+fksXrwYBwcHHBwcCA0NFS5+0vuvgrLZxG+//UZqaioeHh5MnjyZwYMHCyeigIAAxowZw4wZM3BxcUFHR0fcI1K1oLGx8V96NgoLC7ly5Qr+/v4q7cQ5OTk0bNiQ0NBQocmWnZ3N4MGDP+l2u3eBzp07o6urK0ibv9MC9iZtIWW86Xl+Uwv8y9dLWSD5XWj1fEz8nUqBhISEEiuP3wfOnDlDYWEhGzZsQC6XC8dj5TEmLy+PxMREnJ2dSUlJwd3dHScnJ8LCwrC0tBQ6ir/88gsxMTG4ubmhoaGBm5tbiSSadB9I133p0qVoaGigpaUlWuvDw8Np0KABv/zyC7t27RLOZ8qEgqWlpWjjk8gGuVyOh4cHQUFB3L59m1GjRuHn5yfaz6UE1r59+9DT06NBgwZUqlRJaCnC/xsulIT32RL1TzFz5swSjYskMwJlvOn4Lly4wNdff41MJhOEv/L758+fp0WLFu+96vSbb74RUgdSq72Ghga7du0C4KuvvlIhQ21sbOjcubO4/zQ0NKhXr54QwpYqmPT09AgJCREmPkOHDkUul2Nqakq3bt3Izs4W4u/SMywd+4IFC0S756ZNm2jWrBm2tra0bdtWhfSSfktqy3N1deXWrVsq451y94REvpw/f57AwECVQoD3kcBTrq5SLoJ4FaR9UY6VS7r+PXr0oG7dum9cTzg7O+Pj4yO2d+PGDcqXL09ycjInT57k0qVLbNy4kfr166vI0mRmZrJp0yaV8/jHH39w4MCBf3Q+1FCjNOGDklFr164lODiY+/fvc//+fSZNmoSxsTE9evRQ+dzz58/ZvXv3BxNXPXjwoBAelSA9+MeOHcPCwkJUrEikS3Z2NmZmZlSuXFmlmkVaeEmVMydOnCA+Pp7Q0FCSk5PZtm0bM2fOZN++fTx9+hQfHx/i4uIwNDSkVatWxMfHk5KSwpQpU6hcubLKQkbZWebChQvExMSwb98+7t27x5gxY5DJZIwaNYrMzEzq1KmDubk5Hh4e+Pj4/OVqgOzsbDw8PIiKihI2xPn5+cLy9ssvv2Ts2LEqbXRPnjyhZ8+eODk54e/vL0rHDQ0NiY6OxsTEBF1dXfT19enWrZsQMh8zZgz5+fls374dmUyGk5OT6A9/W7ytttV3330nWobu37/P9evX3+hglJ2dTfXq1cnKyiI3N5cpU6YQGxtLnTp1BCF18OBBjI2NhehpSVCeyO7du1fMhnX8+PE4ODjQp08fLl++LF5XvmbK4oVZWVmYmJiIijrJBeXWrVssXrwYAwMDQkJCkMlkQtPi5cW4RGgaGRkJK1vJinzYsGEUFBTwww8/EBkZib29PVFRUaKi6ujRo/j6+v5l4cSXReh/+uknli9fLmyqdXV1SU1N5cSJE+JYR44ciYmJCfXq1RPHrmwR//IiyMLCgu+++44OHToQFxdHamqq0GMzNjZGLpeLxZ+VlRVpaWmUK1eOcuXKYWhoyLJly+jVq5ewL5aCful6pKamYmpqipGREUFBQcTGxlJQUMCjR4/YsGEDVatWVbF8ft+aL3369BEZ4W3btmFjY0OlSpU4f/48gDB+6N69OyNGjCiWqQfV+3Pjxo3o6uqKTPD+/ftp2LAh/v7+bNu2DSh65h8+fKgS5JU0Zv/yyy9/ux3pny6Gbt++LfTjSsqQlwTpPAwYMIBJkyYxadIk6tWrh5+fH2vXrhWtX35+fnh5eQm3x7lz54rtT58+/a2qBQsLC4uRE3fu3MHNzU2M/dJ5efbsGQ4ODiUKbZdWJ7X3CeUWMElQfsOGDe+kBUz5WVizZg0zZ85k1KhRKvodEpSfbeV/KxOTL7/3Ml42uoB/rtXzofEuKgXeJ3x9fTExMaFs2bKUL19eEEsVKlTg9u3b5Obmqow3YWFhaGpqCrcrPT09oZMjHe/cuXP57LPPqFOnDtra2nz11VdvvMcaNWokEi9GRkbC8czV1RVbW1vq169P06ZNcXd3JyEhAR0dHZUqlBEjRgDg7u6OTCYTLsA5OTls3boVc3NzkYTT1NSkU6dObNu2jRYtWqChoYGZmdkrrek/NVy+fLlE46K3MSOYMmUKfn5+4pm+cuUKXbp0wcDAgEWLFonPvTwvvUtCSnlMePbsGXXq1BFk2MaNGzEyMhIt3j169BAxh6WlpWjJlHQ0ZTIZCoVCEESWlpZkZWWJ+0ZLS4uwsDCgyKEvOjoaW1tbkQj09vYuMV7p1KmTIJsaN25MvXr1WLp0KSNHjsTLy0u0gsrlcpycnKhYsSJnz56ladOmJT4LWVlZ+Pj4YGtrS2pqKmlpaQQHB6sY4bxrrFu3jkqVKgFF1Uhubm5vNa6+qppOgrIEwf37918pQfD555/j6+srEnLSduPj46lRowabNm0iNTWV6Oho6tevj5GREe3atSv2e8qFEmqo8W/CByWjVq9ejY2NjXCtu3fvHpMnT8bCwqKYkK6EDxFkP3v2jKlTp2JnZ0fr1q3F65JQobOzc7H9u3fvnljoN2nSRLzerVs3oqKiRItcYWGh0IYIDAzE2dkZQ0NDzp8/z8mTJxk9ejSWlpZUrVoVKNIIio2NxdraGn9/f/Lz86lUqRKjRo1S+e1z587Rq1cvlYFbEtP8/vvv2bFjB6tXr2bq1KklLjzfBtnZ2QQFBdG2bdtXZmelc7Ru3Tr8/PxwcHCgYcOGODo68vXXX4vsnUwmQ19fn+joaAwNDYWt65QpU3j06BE3b94kPz+fI0eOvFV/+N/VtqpZs6ZwMHqblqElS5ZQuXJl6tWrpxKozp49m9jYWNLS0gSp9Ouvv76V29HgwYMFOdeuXTuhxwNFDoiOjo7069ePixcvvnIbc+bMITo6WrQ3hoWFifJ8ExMTFi1ahLW1Nc2bN2f//v1cunSpWNbp559/xtXVlWrVqokA9/z58yxdulQEuu3btxc6NQcPHlQ5vnv37pVYmfQ6KJ/3KVOm0KFDB+bMmcPatWv55ZdfsLGxQU9PD0NDQw4fPgwgronUuip9vySL+C1btpCRkcH8+fOBooqS/v37C1H20aNHM3fuXAIDA/H09KRMmTLs3buXvLw8URVWrlw5tLW1MTIyYtOmTVhbWxMXF4eGhga7d++msLCQbdu2Ua1aNQwNDdHW1hZZ2ezsbJo1a0Z6eroKUfs+sXXrVvz9/UVVnqTJYmNjg6+vryCk4NXteMqYPXs206ZNY9y4cSqv79u3j0aNGhEQEFBi69DrFtulpR3pTc5b0jFs3LgRhUKBm5sbtra2eHt74+7ujre3NytWrKBfv37o6OiQlpaGk5MTrq6u5Ofnk5eXx8SJE9HV1X2riijlazN79mwOHDjAn3/+Sbly5ejYsaN4Txp76tSpI1xY/4t4XQvYli1b3nkLWM+ePXFxcaFy5cpERERga2vL4MGDmTFjBt98840KOaW8bxMmTMDR0VFl0S+RU29CadbqeRu8baWAVMX5T/W6XgXlZz0/P582bdpw/PhxFi5cSP/+/UUrnLSA9/LyElVaWVlZ+Pn5UbNmTYKCgrCwsEBDQwM/Pz8hin/v3j2SkpIYMmSIEMWPiYl57Tj4+eefo62tTaVKlUhOThZEgeTSJyWVtLW1sbe35/Tp04SGhmJtbS0+26tXL6BoUe3h4YFMJqNKlSoMGzaM1NRUfHx8MDAwYNOmTaxatQonJyccHBywtbXF1tYWHR0d+vTp86+qqHwb46KXcfz4cZydnYmPjxfP8eXLl/nqq68wNjZm8eLF73Wfle/Pixcv8vz5c2JiYli/fj0bNmzA0NBQVPXv2bMHfX19ypQpg42NDb169RLSBso6ZtbW1oIYMjU1pWzZskLr0MzMDGtra6pVqybm3u7du6OhoUGDBg2KtRArVzaXLVuW3bt3o6enR1xcHGfOnKFGjRpCX01yL5UcRG/dulWsIlAZJ06cwM3NjdjYWBWDkfdViXfq1CksLCzw9PTE2NhYrEFf96wqv7d27doSx2JlR9RXrScmTZrE9evXxfZWr14tknwLFiwgKioKfX19oSMFRTpyDRo0+E8mmdT4b+K9kVGvcqyoUaMGVapUEYPOgwcPmDx5MtbW1sKy/WMgNzeXefPm4eLiQtWqVVm9ejWrVq0iPz+fUaNGERERwZgxY8Tn//zzT9LT0/nll18oKCjg6dOn5OfnM2DAAE6cOMGSJUuYMmUKCxYsUBHA1dTUJD4+noYNG+Lt7Y1CoRAZukqVKlGjRg2Cg4MxNDTE29tbaGFIWYM+ffoQHh6OiYkJAQEBnDlzRuU4xo0bh7a2drHM0N8NPLKysggJCaFdu3YqpezKpcx5eXmcOnUKfX19jI2NMTY2ZuzYsRgZGdG7d2+ioqIoU6YMlpaWxMfHo6uri7e3Nw0bNiQ/P5+5c+cybtw4IRCoLCD5JryttlVycjLx8fEMGjTorVuGJCFrd3d3PD09i53D2bNnEx8fT1xcHLdv3xavv+5c9+/fHxsbG+bPn8/u3bvx8fEhPj5eJfAZP348CoVCZPdfRs+ePbGwsMDNzY3o6GgcHBwwNzdHW1ubpKQkZDKZCJ4l56aS9m327Nn4+vqSlJSEt7c3y5YtIz4+nsTERNq3b4+9vT0aGhqi4uNtju9NkPalZ8+e6OvrY2Zmhp+fH7q6urRo0YKffvoJGxsb9PX18fT0JD4+npCQEJXqAuXfV3az2b9/PwEBAVhYWLBkyRJhaBAREYGOjo5oX5s/fz6ampr4+/vj6OjIhg0b2LJlC9bW1jRp0oSTJ09ibGyMtrY2c+fOZc2aNejq6mJkZMTJkyfJz88Xx3Hjxg1SUlJwdXUVTlHKgcf7CCZeDqD279/Pt99+CxSRcRYWFkybNo3ff/8dKyurYtWbr9ve3bt3KVOmDDKZTLh1Kp/v/fv306RJE2xsbETF5NviU2lHmj17NnXr1sXQ0FDF/cvU1JQqVaoQEBDAypUrmTx5MlFRUTRq1EiU3j969Iju3buzdOnSN/6O5NK3YMECvv76a0xNTUWWf/Xq1ejo6AixVyiaU0NDQ4tVmP1X8KFbwObNm4eNjQ3Hjx8HiqoJpAVflSpVBDn1888/qzwj06ZNw9zcXKW6QiKn3uTiWNq1et6Et60UUK48hvenESXtU8+ePencuTObN29mzJgxZGZmsmfPHszMzAgNDUVbW5uoqCi6du3Khg0bGDNmDBYWFpw5c4YRI0Ygl8vR1dVl165dtG/fHh0dHby9vQkPDxf7/vTpU5Xq9Zf34/nz58TGxmJiYoKHhweVKlVCoVAgk8no2rUrWlpa2NraCuFpSXPT1tYWfX19NDU1cXZ2RktLiy+//JIGDRowb948HB0dUSgU1KxZkwMHDnDr1i1atmxJ2bJl2bBhA3fu3OHYsWMkJCTw448/MmPGDExNTblw4cIn79IIb2dc9HISQjruX3/9FXd3d2JiYlQIqe7duyOTyUQV8PvYZwlfffUVaWlp/P777zRq1IgqVapgamrKpEmTBMkxadIkNDU1sbW1RVtbG0tLS5WKeEnPUKr809TUFNV0urq6uLm5YWlpibm5OQqFAlNTUyZOnIihoSF2dnZi7i0ptjt16hQKhYKBAweyZ88e9PT0aN68Oenp6WhoaGBjY4O7uzt2dnY0adKE5OTkt6reOXbsGJGRkbRr104lKfO+0LhxY2QyGTExMW/Uo1K+PtOmTUMmk4lWSeX33yRBUL58eczMzGjfvj3Z2dncvn0bfX190tPT+e2334CicUMyzZIQHx//n046qfHfw3uvjHo5yFi5ciXly5dXYZkfPnzIN998Q0pKygefHJUXllu3bqV8+fJoaGgIO9ROnTqxdetWunTpgo+PD7Vr1xYZsODgYFGqPWHCBDHAde/eHXNzc7y9vXFycqJ69eqi9UlHRwd7e3vkcjlubm64urpSt25dLC0t8fb2pn379nz33Xf88ssvLFmyhG+//Vacw4ULF2JnZ8f3339P165d0dfXp0ePHsXswocNG0ZUVNQ7O5dZWVmEh4dTr149Ll68yMqVK0usZgsODkZDQ0M4lE2dOlUQdQ0aNEBHR0eQb4mJiTx9+lQlu/hX8Xe0rV7XMpSWllasZejFixeMGTMGd3d3Pvvss2LWqhMnTqRjx45vNflmZmbi6+srsh/79u1DW1sbHx8fIiMjVaqyli5dWmIwtXnzZtzc3NiyZQvTpk1j/vz5aGtrY2xsjIuLC40aNSItLQ2ZTEa1atXEJKmsCyH9e/z48Xh5eZGdnU1cXByOjo4MHjyYgwcPsnz5ckaNGkVAQICKIPa7wIwZM0SpuST6/v333wuhzd27d+Pq6oquri46Ojqi8uxt7udx48bh4eFBYmIit27d4tmzZ/z4448MGjSIJUuW4OLiIgjhlStXYm5uToUKFShfvjwZGRlcuHCB58+fY25ujpOTkyCGx4wZQ0hICD4+PvTv35/169eL8/nzzz+LVgtJmPNt9/evQnmbixcvFlUgd+/eJTc3l4SEBPr37w8UibyGh4cXq95UhvLYIbmDZmdnk5CQgIeHhyhlVx7Hd+7cyYABA/4WKVka25GUz+nt27dFxrly5coArF+/XrR+Se2K1tbWHDlyhGfPnhXT4ntbu28pSSFVN0oVflL72YQJE9DS0iI5OZkWLVoQFxeHt7f3fzJb+iFawF4ew4cMGUK3bt2AovFYV1cXY2Njjh8/zuPHj9m8eTMymUzoScL/Oxwpj+USOfVXKi1Ks1bP6/A2lQIS3lbD8p+gZ8+e2NjY8NVXX1G/fn3c3NxwcnLCxMSEdevW4erqSrNmzVizZg2mpqaUK1cOExMTUU1iaGgopAMkIt3Q0BA9PT3kcrmo6lA+hpKIKOnfTZs2xcXFBSsrKxQKBRkZGXTo0EFoJdrb2wt3V8kkwcjIiB9//JGIiAgUCgWOjo4YGxvj4+PD1KlTCQkJQS6X4+npybJlyygsLOTUqVN89tlnKBQKfHx8cHNzw9fXl/z8fFasWEG5cuWKubx+ynhb46JVq1aJf0vX6eTJk5QpU4aKFSuK+O7ChQt8//33732sPXfuHCEhIcIV9ciRIxgYGODp6cnBgwfZs2cPtWrVwtzcHLlcTnp6Oh4eHkI7zN3dXVTDy+VyDAwMsLS0FCSnmZmZqPa+du0aW7duFeYYmpqa1KlT563m3unTp6OpqUnnzp357rvv0NXVRU9PDx0dHbp168awYcOoXr06S5YsKVHn9FV4WW7hXeLl+Gvt2rUsX74cBwcHqlatyp07d0r8nPLYO23aNExNTV9Z5fw2EgQRERGEhobSpk0bHj16xO7du3Fzc6N58+YqCbjHjx+za9cuqlatqmK0ooYa/wW8czJKeQBasGABFhYWTJ48WZRF5uTk4OfnV6wKKicnp1hW6UOie/fuIgNVtmxZdHV1qVChAjKZjNatW5OZmcmyZcuEHXrdunV58eIF06ZNQ0NDg/Xr1wNFeh/VqlUjOzubW7dusWHDBuH+deTIEb788kvkcjlVqlRhxIgRbN68GQMDA2rUqIGnpyddu3YVE6JygLN9+3Y6duyoUpE0efJk0Q73MiH1rs/lwYMHadWqFQUFBdy6dYtRo0bh6+urovelLK7o7OzMihUr+N///seDBw+oWrUqLi4uYmC/cuUKly5domrVqirZxb+Kv6NtVVLLULVq1VQs2ufMmSOqSfLy8hg5ciSRkZF06tSpmG7ImwRrJZw9e1Zom0jaDnPnzuX69etYWloSGxtbzPFJaoOUMGLECCIjI3n27BnLly/HyMiI+Ph4mjZtyrZt2wgMDKRTp05UqlSJihUriioz5X0bP348derUEW2mX3/9NVBEaEDRs1ijRg28vLyEEOi7mBil89SmTRvc3NxYunQp586do2PHjigUCvH8paWlcfbsWX7++WfS09NF+5MyXueCMn78eMqXL0/btm25ffs2L1684MGDB+Tk5GBjY4OBgQGLFy/m0qVLxMTEUKZMGUxMTIiOjiYtLY1ffvkFJycnAgMDMTAwoFOnTkARuRMSEoKBgQHDhw8Xv7lr1y569+5N796932sAUdKCPCQkRFTy3b9/Hzc3NyHOmZOTQ/PmzTl9+nSJ52vXrl3ExsayadMmunbtikwmE8TfiRMnCAwMJDAwUNzvJR3bP1lIloZ2pN9//13cl8pknKmpKU5OTixZsgRDQ0Px3D5//pwePXrQokULlaD1r4yzytdCSlLo6+urjO1QdG4l8is9PZ0uXbr87Zbrfws+RAuYdH2aNWtG69at2blzJ0ZGRqSmpgpyqmHDhujo6Agy4vHjx0yfPh0TExMVDb1/4jT6KeGfmBW8L2zevBlXV1eR8Pjxxx/R1dVl7ty51K9fHwsLC8qUKcOIESMoLCykdevWyOVyQRZJ7U+VK1cWovjffPMNwcHBVKhQgT59+iCTyUpcqO7YsUPEhA0aNKBjx46cOnVK6O9oaGjg4OBAp06dmDx5MnZ2dmhoaBAYGIiRkZFoE9fQ0CAiIoK8vDweP35MQEAAcrmcoKAgEhIS0NTUpEyZMkyePJnIyEjc3NxYtmyZaDnetWsX48ePZ86cOWLs6Nq1K3Fxce88yVRa8HI1mjR/Xbx4USS8JEj34P79+zEwMKBu3brFzsu7nNOV7/kRI0ZQr149GjduLJ6XdevWER8fLyqelAXsJW0nExMTDA0NUSgUmJubq7TqSZ+zsrJi8eLFzJw5E5lMhpaWljB0WLRokdCUMjc3f6u5t7CwkDVr1oiWT0ksXS6X4+fnR9myZfH393/rRIwySpJb+KdQvgdu377N/fv3xb5lZ2dja2tL1apVVQjZl+fftx2730aCYOrUqQQFBdG6dWvu37/P3r17cXJyokWLFmJtvHnzZpo1a0b16tXfW+uyGmqUVrxTMkp5AFi1ahX79++nW7duVKpUCUtLS/r06cOJEyf46aefCA4OFpowyvgYRNRPP/2EiYkJycnJLF26lPv379O2bVtkMhnBwcEYGxvTuHFjUdYsHeeQIUMwMjISwcj3339PSEgIderUERPgiRMnmDRpEnZ2doSFhXHjxg1q166NoaGhyNpNmzaN4cOHC1HN9PR04ewH/18BZGhoKNrRJEyaNAlHR0f69OlTrNTzXZ/LwsJCcfy3bt1i5MiR+Pj48Pnnn3Pv3j2ePn1KRkaGmBS1tbWxtrbGw8OD4OBgpkyZQmRkJC4uLpiZmVG+fHkqVKjwjwfet9G2enn7yi1D9vb2omWoY8eOaGlpYWVlhbW1NX379hW2x8OHD6dChQp8+eWXPHz4sNi5eROeP38uzlO1atUYNGiQuJfi4uKws7MTrVFQpKmkXGmTkZGBnZ0dOjo6+Pv7o62tzdSpU0lISCA9PZ3Vq1fTpUsXkpOThRj5y/vWq1cv7OzsGDFiBCtXrhSl3p999hnbtm1j8+bNIiD28/P7xwLcJZEgGRkZ+Pr60q5dO3x9fdHX1ycmJoZOnTphamqKTCYjISFBtLRIpgElbXPNmjWMGjWKuXPncujQIZXfkO4JqYVy1apVaGpq0qNHD2H73KRJExYvXkzjxo3R1tamZcuWVKxYEV9fX7S0tNDV1eXrr7/mjz/+4O7du1SpUgUjIyM8PDxYu3Ytx48fp1atWnTp0kX89vsOIJQX5Obm5nh6ejJ37lwKCgoICQkhNjaWhQsXkpCQQGRk5Cu1G86fP69CEr/cFnTy5EkCAgIICgoS49m7OrbS0I60a9cuYmJiBBmnoaHB0KFDAahUqZKwzJaIqLy8PNH6NXv2bOCfnY8nT57wxx9/cOTIETGXvOy4WhL+qxnT99UCtmvXLkEcdOjQQVQWbtmyheDgYBQKBdOmTaN58+a0bt2aTZs2oampKSrnAJo0aYKGhoYKMSGRU/92IkoZ/8Ss4F3jhx9+oGLFikBRnCRVa0NRNX5sbCyampq0atWK3r174+DggImJCd988w3Vq1dn4MCBmJqaCl2ppk2bUqlSJXx8fHj69Cl//PEHU6ZMUbm/CgsLuXv3LlFRUaSkpFCuXDkhMm5tbU2jRo0wMjJCoVBgYmJCYGAgNjY2Ktqaurq6aGpqUqlSJcqWLYtcLqd27dpi+0OHDhWt5yEhISpzdNWqVXF0dGTp0qVCt1TChQsX6NixIyYmJqWmJfp9Yv369Xz22WdCU66wsJCtW7diY2ND/fr1VT5769YtAgMDRSz0PqActzx+/Ji5c+cik8koW7as0JZbuXIlVlZWeHh4CCKqVq1aeHh4UL9+fWH6I72np6eHjY0NQ4cOpV27dmhrayOTyYiOjqZ79+6iayA1NRVLS0uOHz9Obm4uEydOFHPvy3PY6+aeO3fucP78ec6dO8exY8c4ePAgvXv3ZvTo0f9II/PvkFivgvL+Dx06lMTERMqUKUOTJk1YvXo1ULQuk4wJtmzZQnJyMuHh4eIaff/991hYWLz12P02EgRZWVklElItW7bk/PnzFBQUcPLkyffqKKiGGqUV74yMennB6+DgIALrq1evsnjxYipUqEBISAheXl44OTmJgP5juwPMnz8fZ2dnlixZwoMHDzh8+DDOzs5Uq1YNmUxGXFyc+L8kQpqcnIxCoWDFihUUFhby/PlzfvjhB9zd3SlXrhwAvXv3xtvbG1tbW8zMzIQj17Vr1+jXrx9yuVy4nJUrV47OnTsTERFBt27dip2T7OxsypUrR2JiomDSJUyZMgWFQqEiBPi+oEzG3b59mypVqqCvr4+JiQlNmjRh+vTpmJubi4yNZPdapkwZwsPDefHiBVu3bmXFihXs3bv3nQ28r9K2eh1ebhn69ttv0dPTw8nJiZUrVzJ79my0tbVp06YNUJTlHT58OO7u7nz33Xd/e19zc3MJDg7mm2++AYpKzFu0aMHGjRvF+bh48SKOjo60a9eO3377jVWrVmFra8ukSZOEpoRCoWDGjBls2bJFBLzm5uYqAp7KgcaxY8fw9PRkx44dQNEiTGpFdXZ2xsHBAQ8PD5ycnEhLSxOC4X/32rys2/H111/Tp08fBg4cSNu2bUlISKB69epUrFiRhw8fsnLlSjw8PGjYsOErdQeUx5mMjAwcHR2Ji4sjNjaWqKgo1q1bR69evbC3t8fIyAhjY2OSkpK4f/8+EyZMwNDQkBo1ajBhwgSqVq1KVFQUw4cPJyEhAS8vL0JDQ6lXrx4TJkwQulGRkZEEBQURExNDUFAQOTk5pKSkYG5ujqOjI2FhYR+sraakBXlSUhLh4eEsW7aMY8eOERERQUBAAImJiWK/Xj6X0t9Dhw5FR0eHiIgIYfusDKkCy87Ojj///POdH8/HbEc6e/asIOOMjIzw9vZWaf3y9/dHV1eXoKAg7ty5w4MHD0hOTn4n7l/Tp0/Hw8NDtApcu3aNvn37qrgnQVHLtVTZ8V/Hu24BKyws5N69e4I4qFu3LgYGBsyePZv169dz48YNypUrh7W1NVOmTGHNmjV4eXmJti1pXHz8+DGVK1dWWeBKRP/biNj/21BazArmzZtHeno69evXRy6Xo6OjQ8eOHTlw4ACrVq3im2++oUKFCujq6hIbG4uuri729vb4+/sTEBDAsWPHmD59uqg6cXBwoEWLFkydOrWY2/PLc+T58+cxMzNDQ0ODL7/8kq1btzJ79mw0NTWxtrbG1dVVuJ5Jc7lU+aKhoUH9+vUxMDCgVq1ahIaGoqGhQXp6urivT506haurKz/++COASvLS3d1dVMxK42tOTg6zZ88mLS3tP0FEzZw5E3t7e7755huVNlrJfMTCwoIGDRqI1//880/atm3L8ePH30sySXn+HTNmDJ9//jmnT59m6dKlyOVy+vXrJ66VRGxra2tjYGCArq4u6enpPHz4ULhQK1dM9e3bl9zcXB4/fkyjRo3Q0dHBwsICPT09JkyYABRJfEiJx19//RUoPvf+8MMPQlj7bY9HShS+T43Mv4t+/fphYWHBqlWr2LBhAwkJCZiZmYk13IULFyhbtiwBAQFER0eL83H58mWMjIxEBefb4m0kCEoipCSNW+Xulo+9JlZDjQ+Nd96mN2TIEKEF83K56+3bt9m/fz9169bFzMwMFxeXd1qa+TYoifU/fPiwEDKGIhv56tWrs3fvXkGqBAYGigXy5MmTMTIyEuX4Ulbj4cOHLFy4EFNTU4KDg7G2tmb79u1cvXpViDJLFvB3794lMDAQc3NzGjduzIsXL4Qg5avavo4fP05wcHCJhMvKlSvfa0VGSQKQ/fr1w9zcnKZNm+Lo6Ci0Flq1asXx48dZvnw5Tk5OQgg7IyNDfPd12/67eFnb6k1Q3g+pNUtPT0+lbDkzMxOZTCbEcp8/f868efP+0bm+d+8elStXpmbNmgwZMoTExEQVkW7p/8eOHSM0NJQuXbrQoUMHxo4dCxS5y+nq6lK5cmV0dXXp378/AQEBmJqa0rVrV/Ly8oqJwOfn57Nnzx4CAwOBoiohZeep3377jTlz5nDu3Dlu3rwpvv8u7ill3Y60tDRCQkLo0KEDOTk5tGrVipiYGO7evUtKSgo2NjYqQcCr7o3vv/8eFxcX9u3bR0FBAWPHjkVbWxs7Ozusra1Zs2YNmzZtwtHRESMjIw4ePCjaWitVqoSvr6/QDZAylM7Ozly7do0XL17QrFkz+vTpw6lTpxg3bhwDBw5k/vz5KtUW//vf/1QcBj9EIFbSgvzatWtERERQtmxZfvzxR/Ly8rh//36J+/XyPbZ9+3a2bdtGamoqCQkJKi1GEiSHwH9TybgyGadQKDAzM8PLy6tY65eNjQ06OjpoaWlRvnz5d+b+debMGTw9PQkPDy9GSOno6PDll19SpUoVypUr9686738H77sF7Pz587i5uSGTyRg1apQKOaWvr0/16tUpU6YMBgYGmJmZYWBgwMSJE8nNzeXo0aNUq1aNkJAQlefs999/F+L3/0V8TLMC6Xk5ffq0IHk6duzIjBkzKFu2LKmpqYSGhtKyZUs2bNig0o6noaFBaGgoxsbGIqaZOHEigwYNIjo6mqtXr5KQkFCiuYhy3Hbq1CksLS2xs7PDy8sLPz8/7t+/T2ZmpqiC+u6775DL5cjlcsqVK4eLiwsaGhpUqFABd3d35s2bh5GREXXq1KFixYpERkbSp08foGhMDwgIoGHDhmIsk56H1NRUXF1dCQgIUDnPEmHxb8e6deswMTEpZiKhLF2xbds2rKysiImJEcmo6Ojo1zrAvQtkZGRgaWnJ4sWLRYz6ww8/IJfLGTp0KAUFBdSuXVsQkAYGBsjlcrS1tTl58iQnT57EwcEBhUIhqqecnZ1xc3PjwoULJCcn06BBA0FWrVmzBihqAWvfvj0jR44sMU65cuUKISEhovPiTSS+BGnuKm24fPky5cuXF2Pwli1bMDY2FjIYUmXm8+fPOXPmTLFnSNmQ6O/gdRIEEiHVpk0bHjx4QGZmJnXq1FETUGr8p/FOyah79+5RpUoVFi5cCBQF17t27aJ58+bMnDmTy5cvi89u27aN2NhYkc38EO15Lzv8Sb955coV4uPjady4MYcOHRIL5KysLOrWrUtERIQQH33+/Dk1atQQGanly5erEC2PHz9m5syZotrgm2++Ea55kuPVs2fPyMnJYciQIYSHh4sKDR8fHzEJvGpgUq4AkjIcyngfk6jytZkyZQqdO3emfv36+Pj4sH37dh49ekTTpk1Fhi8lJUVlsD969CgTJkxAW1tbpZ3pfUBZ2+p1UH7/5s2bZGVlYWFhQatWrYCiY5Ympq5du1KpUqVigdw/OdeHDh0iKSmJ6OhoUlNTX1nBcvToUcLCwjAzMxMtRPn5+SxevBg7Ozt0dXWxsrKiRo0aoiw/Pz+fn376STyHn332GV27duX06dP4+/szbNgwjI2NVSrp9uzZQ2xsrLinlG3u/wkkwXWpumPZsmXo6OiwYMECoEj8W1NTE0NDQ7S1tfHz8yumcfUyHj9+TPPmzQVBKAWftWrVwt/fHwsLC9F28+LFC2JjY0UWWS6X06tXL+7du8e3337L559/zoEDBwgNDUUmk4kMZUxMDO3atRO/KZ2Lp0+fsn///mL79L4Jg7ddkMfHx6tUiJQkogtFwqmXL18WrZDnzp0jJSWFSpUqqXx/8uTJwuUSPn0Ng5fJuJ49e2JoaEhsbCwxMTFMnz69WOtX586dCQwMZMaMGX+LeHyVk9Nvv/2Gr68vISEhIqi/ffu2cOlr0qTJK8eF/yLeRwtYQUEBZ86cIT4+nvDwcGrWrMm0adNwc3NDLpczceJEHj58yOXLl1m7di0bNmzxZFdWAABYlUlEQVQgPT2dMmXKYGRkRHBwMPHx8WqNjxLwoc0KRo4cqSJVsHPnTmrVqoWWlhYZGRns2LGDiRMniorZli1b0rNnT4YNG0br1q1Fy5y2tja+vr7o6enh5uYGFCUa79+//0pRfOXxQBpTfXx8CA8Px9jYGLlcTkREBPfv36dr165YWVkRGxsryDIXFxe0tLSQyWR8++23REZG0qpVK8aNG4dMJqN3795UrVoVPT09cf///PPPGBgYFHPdatasGYcPH8bHx4eGDRu+8/NcWiEl0NLT0/n888/fOGaeOnWKmJgY4uPjqVGjxnsfa3/++Wfc3NyEWLmEgoICpk+fjoaGBv369cPIyIjJkycLUknSEzM2NmbLli2YmJhQpkwZ7O3tadKkiXDOMzMzw9/fn8ePH4t4fPv27Tx8+JCaNWvyxRdfiN8saf764osv8PLyeu0xKMeEM2bMoH379qVCe+zla3b27Fns7Oz4448/WLduHYaGhiLeffLkCdOmTRNudq/axt/F20gQZGVlERoaSlpamkpVo3qeV+O/indKRt2/fx97e3v69u3Lrl27aNiwIREREURGRmJhYcG4ceNUPl+1alWaNWv2LnfhlVAeRMeMGUOLFi2oW7eucHDYsWMHvr6+1KxZk86dO4sFsoGBgWh7kiYr5YH8119/Fc4UUpDw6NEjvL29sba2JiQkRGQ4zp49y/Pnz5kxYwa7du3i0aNHDB8+nNatW9OuXbu3Fqf9qxVA/wTKi7eMjAzMzMyoVasW4eHhaGho8NVXXwmR36SkJKytrdHQ0KBx48Yqg31ubi4jR44kNjb2vROPbxIUV379u+++4/PPP+fatWsMGTIENzc3oWUmbadfv35UqVLltb/5VyYRabuPHz/myZMnbyxx/uWXX3B1dSUkJERFQ+r27dvUq1ePuLg4sY0XL17w+PFjsaCuUaOGigNUo0aNhAujhGfPnlGjRg3q1q37zifDWbNmCd0OSXBdOShYsGAB9evXJzg4WGTtpP8klLRP586d48KFC/z666+4ubkxevRo7OzsRCm6qakpW7ZsEeekYsWKuLu7k5GRgZaWFqGhoZiYmIhKo4CAAKZNm4ZcLmfIkCE0bdqU2NhYbty4ofI8XrhwgXr16gm79w+Nv7sgV37mBg4ciL+/P56entja2ops4fnz56lWrRpxcXH07duX1NRULCws/jUBUklkXNeuXYmJieHMmTMkJydTqVIlpk2bJlq/2rRpI8i4wsLCYoYCfwXKmXrpepw/fx5fX1/CwsJUsszPnz8vla0PHxvvogXsVffziRMnRMuvv7+/IKeU23ygiJi4dOkSa9eu5ZdfflFrfLwF3rdZwdmzZ2nYsKF4Nq9cuYK+vj4ymYz69evj4OCAnZ0doaGhxMTEYG1tLcSe9fX1KVOmDGFhYZiammJhYYG2tjbu7u7I5XKcnZ1fK4qvfN27d+9OrVq1yM7OJj09HUtLSxISEtDR0UEmk+Hq6kpSUhLa2tpoaWlhbW2Nvr6+aCOUxuJq1aphYGDAzJkzOXLkCHl5eYwdOxYXFxeaNGkiKp7mzJmDgYEBsbGxtGzZkvLlywuZiK+++kpF1+y/gEePHuHo6Mj3339f4vvSsyoRKIWFhSrt5+/zGZ49eza+vr4q5I3yvfTtt98KYrJr165cv36dOnXqoKGhga6uroqouYWFBc+ePePJkyccP36c0NBQoqOjRfLoiy++EI6Pnp6e+Pr68uLFC0aNGlWMhJHu4xs3buDn58ekSZNK3H/lGGL69Oloa2uruBN+LLysVfz7779z584dKlWqxKBBgzAxMVFJvB4/fpy6desKV+v3hTdJEBw8eJAWLVr8a+IrNdT4J3jnbXozZ87EzMwMY2NjMjIyRGDYrFkz4cwlPXwdOnSgXr16713MUvlhHzJkCObm5rRp00YsSKVS1r1799KqVSusra1xc3PD0dGRESNGiEqNlycqaXA+ceIE9vb2KBQKIX6ampoqMhoxMTEYGRnRpEkTzp07R0JCAjNnzlTZhoS3nQzftgLoXaCgoIDr16/Trl07Ro8ezcWLF7lz5w7lypVDW1sbbW1txowZw/Xr1/n6668pU6YMmpqaKmLcUFRV8qEcE99m+xkZGcJ15PLlyxw9epQaNWqQnJwsCKnc3FySkpJo2bLlW/3WkiVLOHPmzFvt41+5dtnZ2QQGBtK8eXMRzD9+/JioqChRwaO8vXv37uHp6SlaTyRs3bqVyMhI4uLiGDNmDFOmTKFKlSoqYuXv8p6SdDs2bdqkkp2CotbS4cOHc/r0aRWNl1cRUZs3b2bp0qX8+uuv4vUZM2YQGxtLbm4uV65cwdPTEyMjIwYNGlRMy8DLy4t69eoxePBgFAoFlpaW+Pr6kpSUJI596tSpKBQKunXrhomJCQ0aNODs2bM8efKE27dvU716dSpXrvxRA4h/siAfMmQIVlZWbN26ldzcXOrUqYOpqamoiPvtt99o27Yt8fHxKq4un3rA9DIZ5+fnh6enJ4aGhri4uPD06VPOnz9PcnIycXFxpKeno1Ao0NTUZNGiRcW28Vdx9epVtLW1SUpKKrZPx44dw9TUlJSUlGIVIx/D0KO045+0gL3sSLlz507++OMPUWl46NAhUSkxbtw44uPjsbCweO34//J21VDFhzIrkJ6V9evXc/fuXaH9mZSUxOLFiwUB3bRpU8zMzDA1NRUyDMbGxmzevJmrV69SsWJFnJ2d0dDQoEaNGgwbNuyVovjKz2dERAQKhQJdXV1MTEzQ0dHB3NwcHx8fxo8fj62trYrWj5aWFnp6ekInKi0tjc2bN4u5W0tLizFjxgCI+HPJkiVER0fTsGFDMWafOHGCJk2a0LhxYz777DMxZqelpYkY8b8yjuTm5uLi4lIsWaOMe/fukZSUVGyceF/nSNru5MmT8fLyEmSUdF0KCgpITEzE3d0dXV1dFAoFcrmcwMBAWrZsSWxsrBArl8vl+Pr6Ymtry48//iiu9caNG5HJZERFRQnSd/v27cyfP1/IC1SsWJGKFSuKsWrRokVcu3ZNVPzn5ubSvHlzIZb/qnMjucyVBj085f2STAgkIrJ9+/bIZDJ69uwpPpObm0u1atVeqUn6ofG2TtxqqPFvxzsno6CoX/fcuXPi74KCAipXrkzfvn3Fa0ePHsXV1fWDVhjcvHmTTp06sW/fPvFamzZtMDAwEAx/fn4+d+/e5eLFiyoL2TfZmq9ZswZLS0sUCgUdOnRgxIgRuLu74+joSH5+Phs3bsTAwAAHBweioqLEd5UH0786GX6IgaywsJAFCxagr6+Pubk51tbWQhQxKChIBFf+/v506NCB7OxsqlSpQpkyZVR6tEva74+JV5VMr127lpo1a2JgYEBYWBj+/v6vdJU7cuSI+Hd+fr5o9XubFgTl7Uhl/W9CVlYWPj4+2NnZUaNGDerVq6eSqVXe5oMHD6hWrRoVK1YkMTGR+fPni/c2bNhA586dsbOzIzExkZYtW/4jJ5TX4fTp08LhZc6cOeL1J0+ekJSURKtWrd6KoOzVqxcGBgaULVsWhULBxIkTefHiBT169MDMzIwRI0bw/PlzqlSpgpWVFeHh4Vy5ckWFkJKqWmbPno2XlxdZWVmcO3dOBIXSsS9YsACZTMagQYOwsbHB398fd3d3IiIiCAoKKhUEzdsuyF9u00tNTRXtm6tXr8bMzIwpU6YA/5/Jy8nJIScn519ZmfMyGVepUiU0NDTo1KkT8P9kXEBAALa2tiQkJFClSpW/7PZT0r2xe/duHB0dSU5OVnn93r17REREIJPJ3kh6qFGEv9MC9vLCxdvbG0NDQypWrMiAAQM4cOAAO3fuZOvWrVSpUgUfHx+cnZ3R09OjevXqIkaoVKmSMJ9Q4+3xIcwKbt68ibOzMy1atODevXvs27cPKysrbGxsmDhxIp06dUJDQ0MQ91WrVhXi5A8fPuT58+ecP3+e4OBgrKysRDXjy/OIMgoLC2nVqhUKhYJx48ZRsWJFUc1ibW2Nrq4uWlpaWFpaqoiWS//p6Oigq6uLnp4eOjo6WFlZoaenR2BgINWrVy+W3Fq0aBHR0dE0aNCAEydOFDsHjx49onv37lhZWXHq1Kn3dKZLB6RqVeW/y5cvT3R0tEqlqfKzf+jQIdLS0rh+/foH3ddTp06hUCgYOHCgyuu1atUS94uWlhZmZmaietvAwIAqVaoQFhaGhoYG9erVE5VROjo6fP7553Tu3Jn4+HiMjY2pX78+nTt3LmZydPz4cXx8fEQic9OmTdja2uLh4UG9evWEttK5c+cwNTUVMiQvY+rUqaXSIVTSKj506JCK03V6ejo2NjZ88cUXdO3alfj4+PeWeP27KA3rITXU+Nh4L2SUhJycHPbs2UNqaqqKw5eEDyl+t2TJEmQyGV5eXsUcI9q0aYOhoSFr1qwpto9vM1h169aNWrVqERwcLEpppUWsQqHA2dmZChUq4Ovri1wup1WrVuTm5r4TfYkPMZBlZmZStmxZNDQ0WLRoEQ8fPmTkyJFYW1tTsWJF5HI59vb26OnpERwcjJ+fH5cvX6Zfv37IZDJReVaa8HLJtPJ1vnDhAps3b2bIkCFMnTq1RKJm1KhR+Pn5CdF7KKpwcHd359GjR6/9beVrNmnSJJo2bcr9+/ffar9PnDiBh4cHfn5+KkLqryIMbt68SbVq1UhISFAhpKC4SOP7Ih2WL1+Onp6e0O3IzMwkMTGRgICAEjPMyn8XFhZy6dIlYmJi2LdvH3fv3mXMmDHIZDLi4+OxtLTExMQEDQ0NjIyMKFu2LBcvXsTX15eIiAjhnKK8zYkTJ6pkKKWAtrCwkOXLl3P69Gm2bNlCXl4et27dYtGiRYwePZoFCxZ8ULHyN+GvLMgHDBjAqFGjcHBw4OzZs+zYsaOYjkLfvn25cuWKyvdKQ7D2T/A2ZFyzZs3Q0tKiW7duHDlyhF9++YWqVasybNiwv+X+pfybP/30E6tWrWLjxo1AkTbby4TU06dPad26NdnZ2WrNob+Bv9oCNnToUGxtbdm2bRvPnj2jYcOGGBoaYmZmhpGRERUrVuTzzz9n1qxZjB8/nn379lG1alV8fHzw9PTE09PzvVdzq/H3cfToUUJDQ2ndujX37t1j6dKl6OrqYmBggJGREeHh4Rw/fpytW7cK0ws/Pz8CAgIYN24cu3fv5qeffhKi+NJ4Ic0fmZmZ4rdyc3P59ddfKVOmDM7OzsyfPx8dHR0UCgU1a9bE1tYWhUJBpUqV0NTUpFGjRixfvpyOHTtibW2NkZER+vr6rFq1inbt2lGzZk20tbUxMTHByspKEBCXLl1SOcY5c+ZgZGRE48aNOXDggHj9t99+Y8iQIZQrV+69tEOWNpw/f178e8aMGZw5c4Zt27aho6ND27ZtefTokRiPCwsLefLkCWlpaTRu3PijkADTpk1DU1OTzp07s2XLFjZv3oypqSlWVlYEBQURFhYmdMQkcXuZTIa1tTUtWrTg2rVr9OjRg6ZNm2JnZ4eBgQGBgYG0a9eOpUuXYm1tLc6J8jyUnZ2NgYGB0HkKCgri6dOnzJ07l7Zt26KtrU16ejrfffcdnTp14vPPPy+m3TlnzhwMDQ1LHRFVklZxZmYm7dq1Y8GCBTRt2pTGjRtTu3Zt+vTp894Sr2qoocbfx3sjowoLC9mxYwepqalUrVpVpTf6Yyxw/vzzTxo1aoRMJhPixsqTkVTSqdxHPH78+De6j8ybNw8zMzMh0m1hYSEC24YNGyKTyWjcuLEo8962bRsymUyIUZc2lHRt7ty5Q1hYGO7u7jg7O7N//36RfZowYYIIvoKCgujTpw9//vkneXl5XLt2jenTp5eqQf9VJdPKGbYff/zxlX31ErZv306dOnWoVKkS69atA4oyXyEhISqVSiVlUSVMnz4dfX39Eh3MXodDhw7Rvn37t66Mu3jxItWrVycxMZFZs2aJku2vv/66xP1615AE1x0cHHBwcCA0NFRFMPTlc/Ryu+G5c+fo1auXyudq1KiBhoYG3bt3Z8eOHbRr1w6ZTEadOnW4evUqv//+OwEBAbi6uharPHtVhjInJ4eaNWsKYfSXWwaVj6e04eUFufI5XLp0KU5OTpw8eZKmTZtStWpV9PX1mTVrlvjM9evXiY2NFcLy/za8iYxbvHgxBgYG2NnZqVSaXbx48S+5fyk/R7169cLBwYGgoCB0dXVp06YNZ8+eZc+ePbi6uhIUFMSAAQOoWLEiFSpUeO9OTv9GvE0LmPI1OXv2LJGRkSKJ8NNPP6GlpYWOjg6Ojo588cUXpKWlYW9vT6dOncT8cOLECZYsWcL48ePVi5lPAFlZWQQGBtKqVSvu379PQkICGhoamJqaEhQUhKenJyYmJqJlu2PHjvj6+qKtrc2UKVNeqcG3dOlSZDIZc+fOpXfv3kRGRnLz5k1atWpF2bJl6dixIxoaGtSsWZOlS5eiUCjQ0dHBxMQEhUKBubk5RkZGWFhYYGRkhK6uLnK5HCsrK0xNTSlfvjzh4eF06dKFWrVqYWVlRWhoKJ07dy5GSAUGBuLo6KjSklZYWMiZM2fei0B8aUN2djaamposWLCAXr16YWpqysWLF3n+/Dnffvst2tra1K5dm+XLl3P16lWWL19OUlKSSmL8Q65FpFbLNWvWYG9vL/TJdHR0mDBhAgEBAejp6Ynqp4yMDOrWrSuqwRs0aECPHj3o27cvixcv5sqVK3Tq1IkKFSrg6urKsmXLsLGxoUWLFiXOIT/88ANaWloYGhqyZ88elfd+/vlnevXqhYeHBzKZDENDQ2EGIJ2jQYMGiVi3NOFVWsVhYWE4ODiIOV55HlDPsWqoUbrwXiujnj17RlZW1gcX+HzVBPPixQtSUlKwtbUVmkDKULY9lTLizZo1U3E7eBkDBgwQlrCdO3emV69e/PLLL2JQ/+yzz4Ciha4UIBw8eLBUBrLKg/WaNWtYsmQJ27dv5969e9jb29OyZUu8vLzQ09NDV1cXBwcH4QAzZcoUCgsLhUD7jh07VLZd2o73TYTEq0QclbF3715q165NfHw8mzZt4uDBgwQFBfHkyZM3fvef9t3/1RbNixcvkpaWhre3N2XKlMHPz++DZ/dv374tdDvepgWsT58+hIeHY2JiQkBAgGhXuH79Oi1atKB58+Zoa2tTt25dzMzM6N+/PyYmJtSpU4dLly5x6dIlmjZtWqJD5fTp09HS0qJz585s27aNnTt3kpSUpFKtJaG0Vwe9bkG+c+dOOnToICybJ02ahKurKzVq1BCfefz4MSkpKcTHx/9rgrS/Q8ZFREQwcODAd+L+JQnqSy6SEydORCaT0aBBA3777TcuXbok9Mfq1KlTqtoGPkW8qgVMeU775ZdfePToEcuWLeP+/fvs3r0bCwsL3Nzc2LBhA1WrVsXY2BhNTU2qVauGp6cnXbt2LbHS9d/ynPxbIY2JgYGBpKWlCfcxU1NTIiIi8PDwwN/fHyiqqNHS0sLBwQEzMzNOnz79Sg2+nJwcBg0aJCrcY2JiSE1NZefOnSgUCpycnNDT0yMhIQEDAwOhF6qtrY21tTUWFhaCgGrXrh39+/dHJpOhp6dH165d2bt3L19//TU2NjZMmjSJwsJCvvvuOwIDA+nSpYsgpG7evEnbtm2ZO3euSuXPfwk3b95k6NCh6OnpYWJiotJ29/DhQ5YsWYKjoyN6enrIZDICAgKoV6/eR3O+lK7PoEGDhMNi2bJlxZgjk8mwtbXFyMgIW1tbNm3aREJCAp06dRLHUKFCBerVq4ebmxv9+vWjoKCA3377jX79+uHt7Y1MJqNWrVoUFhYSGxurIuQuzUEKhYKZM2eqCLdL5+Phw4eMHj2aoKAgYar0KdxXr9IqTk9PF1rFaqihRunFeyWjlPGhgmzl31m4cCFff/01vXv3Fr3/BQUFpKSkYG9vX8w1TYK0GN2zZw+mpqY0adKkWIWU9J2RI0cSFhbGkydP6NSpEyNGjGD9+vXo6ekJi+BVq1Yxd+5cxo8fr2KTXtoIGgm9e/fGwMAAPz8/ZDKZqOoyMDBAW1sbBwcHIfqpUCiIjIwEiiaza9euqQi0l2b8FUJCGcr3y+7du6lVqxZJSUl06NABDw8PunXrRp8+fejXrx/9+/enY8eObNu2TXxn2rRp76Tv/q8GCTdu3GD9+vXMnDmzVGT3Xx4TlP9esmQJdnZ2fP/993Tt2lU4AP7+++88ffqUVatW8eDBAz7//HN0dHQE2fLdd98hk8lISEhQqYhSXqzu3buXn376iaFDh+Ls7IyDg0MxIfOSNN1Kg4Xx6/DygvzmzZu4u7tjZGTEyJEjgaLj+uqrrwgMDCQoKIj69esTGRlJYGDgv9Ke/u+Scf/E/UsiS6U5Z+XKlSpkaVpaGteuXQNUr1lpnQ8+VSg/u926dSMuLo7Lly8L/a969erRtm1blixZwv3796lfvz5aWlpUqVKFgoICqlatiqWlJenp6a9NSKlRuqA8j9SuXRtjY2PMzMwwMzPDzc0NX19ffH19sbCwoFy5ckRFRWFtbY2mpqbQ4JPamEoSxc/NzWXAgAFoaGjw2WefERUVRbVq1Rg7dqyKFlRMTAz6+vro6+sLXSBNTU169OjBpEmTUCgUNGzYkISEBPT19XFycmLgwIFYWlqyf/9+lartKVOmUKFCBapVq8aYMWNISkoiKSnpPy+APGPGDGQyGfr6+sybN6/Y+48ePSIrK4utW7dy9erVj6aDKF2f2bNni7hZ0gjT19dHQ0MDW1tbXF1dMTU1xczMDCsrKypUqEBoaKho3XN2dmbAgAHo6uoyd+5cld/Izs5m6dKl5OXlkZ+fz+rVq1XWGwcOHODGjRuMGzcOuVzOpEmTSlyPSARoeHj4JzXuvY1WsRpqqFE68cHIqA+Nnj17YmdnR9u2bWnRogWmpqbC6e7JkydUr14dJycn/ve//xX7rvLEvnv3bnR1dencubPIkL7syKOpqcmgQYMYPHgwDg4OGBkZUadOHRITE+nTpw937twhKSmJIUOGvOej/ntQ1ue5ceMG8fHxHD58mKtXrzJ//nw0NTVp2bIlvr6++Pj4MHz4cGJiYtDV1UVfX5++ffvy4MEDHjx4QEpKCrGxsZ/EgrawsJA1a9a8kZCQ8KqALzMzkzp16lCmTBlMTEz44osvSExMJDk5mbS0NGrXri0m+h9++KHU9N2X1mu0c+dOOnbsqBJcTp48GUdHR77++mt+//13cY1GjhxJ9erVefjwIYWFhUycOJGmTZu+0i2lV69euLq6EhoairGxMbVr12b16tVCyBxKdkqaMGEC9evXf2PbbmlDdnY2Hh4eREVFCcH9/Px81q5dS7du3fjyyy8ZO3ZsqSAn3zX+LhknVfT+XfcvZbL08OHDuLq6CtMHiSyNj48vUc9MjXePq1evEh8fz65du8Rr3bp1w9LSkqpVq4pK1jJlylC5cmVxH3Tp0oWIiAi6dev2n13sf2pQfo5q1aqFXC7H1tYWXV1dRo8eTWJiIhEREfj7+1O+fHni4+MpV64cBgYGXLp0if3797Njx45ilZEvi10/efKE/v37qxBS0nwvueMpO+fJ5XIUCgUymQx3d3d27NghKqyio6Np3bo1GhoaBAcHF9O+ad++PT/++CPDhw8nPT0dPz8/ateuXaJxyb8dL1eBXb9+nSNHjjB48GAMDQ2ZNm2aeP9V5+VDt+Ypo3Llyjg7O6OtrY2WlpYgmbS1tdHR0REaUdK9Y29vj5mZGXK5nGHDhhEdHY1MJqNXr15AETG6c+fOYr+rPI8PGzaMr776SuX9ESNGCEJKuUJeigmvX7+OjY2NqOz9lPAmrWI11FCj9OFfSUZt3rwZFxcX9u/fDxS5j+jp6am0Zbx48YLw8HBq1qyp8l3lCWzQoEF06dIFGxsb4XSkXLK/detWfvrpJ/r06YOWlhY9evQgMjISXV1ddHR0aNCgAZcuXSI5OZnw8PBSOSgqT5a3bt3ixIkTfPXVVyqtZqmpqchkMjExli1blkaNGmFgYICGhgZlypQhKiqKqKgoFXe30kp2vIw7d+7w22+/lUhISFC+LxYuXMiECRNUnAJ37twpNCZe7sdXxsyZM1m9evW7PYB/ESQCwdDQUFSzSJg0aRKOjo706dNHaHpJrRIPHz7k6dOnpKamiooUUL2/J06ciI2NjaiIHDNmDHK5XMVRsaSWh+nTp2NkZMTixYvf/QF/AGRnZxMUFETbtm1fq330qTyvfwX/hIz7J+5fJZGlUHQPNmvWrNRYS//b8c0331ChQgWSk5O5e/cuAFeuXCE+Pp7WrVsTERFB1apViYqKwsjIiNq1awu79QYNGrBgwYL/fPXJp4ghQ4agr6+Pr68vjx8/pnbt2piamvLTTz8RERGBs7MzlStXJj4+nurVq4sFufTcvqoyctasWZw+fRooIp0lQqpdu3ZUqFCBpKQkOnfuTHh4ONra2hgaGgpyqm/fvrRq1QpNTU0sLS2xs7PD3t6e6Ohohg0bhra2NpaWliVq39ja2jJ58mTy8/O5d+/ev9Lp9E1Qfv5Onz7NgQMHuHv3LoWFheTm5tKrVy+MjIz44YcfxOdGjBhRoiTHh8DLMaMkKxAWFoaWlhZDhw5FLpcL9zyFQoGXlxexsbGULVsWTU1NFAoFcrmc2NhY0XFRrVo1MVevXr2ajIyM1zoyT5o0CZlMRr9+/VReHzFiBJqamkyZMkWlQgqKYiMrK6sP7jj4T/E6rWI11FCj9OJfSUZNnTqVKlWqAEUtEkZGRiJj8vjxY0EWvHjx4pUB5siRIzE3N+fnn39m+/bt/PDDDxgYGJCens7jx4/p3r075ubmODk54eTkRKNGjbC2tsbU1FSUY5uZmVG+fHkqVKhQ6gfFXr16ERgYiIODA2XLluXXX38Fihw0TE1NGTlyJDo6OqSnpxMWFoa5uTllypTB09MTJycnBgwYwA8//FCq3Mb+Ll6+J5SDiu7du2NhYUFAQAAuLi7Ex8eL95RFzZWJC2lxo8bbITs7m3LlypGYmFjMonjKlCkoFAohSrl//360tLTw8/OjbNmyr82EtWvXTlQnLlu2DFNTU6ZMmQIUVcOUpC31T7W9SguysrIICQmhXbt2f6va51PGxyDjpDFDIksfPXr0RrJUjXePrVu3YmFhgYWFBWfPnlUhp37//XeGDx9Oq1ataNeuHYMGDSIiIoKkpCSioqLw8fEpcUxQo/RB+frk5+eTmppK3bp1CQsLY9myZZiZmQn9nG3btqGvr0/FihWZM2eOqKJRJqRLqozMzc3F0tKS4OBgduzYwY0bN7h06ZIgpNq0aUNUVBQxMTFs3LiRs2fPsnr1auLi4mjSpAmGhoYMHDiQ0NBQKlasyNChQ8nJyeHOnTu4urpiZGTEmDFj3lr75r90TyrHYH369MHb2xtbW1vCwsLo0KEDt27d4u7du/Tr1w8dHR2+/PJLqlSpQrly5T5KzK18bbp37y5a7+RyOdbW1qL66dtvvyUsLEzoiEmxjKmpKbVr10ZbWxsNDQ1RVTdnzhyx3ZycHKpWrUqbNm3E+Tl48KCI3bt168a6devIy8tj7ty5aGlp0adPH5X9HDVqFDKZrFh8M2bMGI4fP/6ezs77xcfSKlZDDTX+Pv5VZJQ0IC9ZsoSWLVuyfPlyldJdgPXr19OtWzf++OMP8VpJ2jV16tShR48eKtuWgphGjRrh6+vLsWPHOHLkCGPHjhX2vQYGBgwaNIhNmzaxYsUKdu7cWSoHReUJeuHChbi4uDBhwgSGDRuGpqYmbdu25ebNm/Tt25eYmBgKCgqYNWsWFStW5Ny5c/j5+eHu7s6IESNElYp0/ksr4fZPcffuXerUqcOJEyd48OABP//8Mx4eHoSFhYnP7Nixg4oVK/LFF198xD399HH8+HGCg4NLJE9Wrlypco8dPXqUvn37Mnr0aPGMvZzp+/PPPylfvjwLFizg8OHDKk5qeXl5DBkyRDhsSZgxYwbGxsaloqXyXSArK4vw8HDq1avHxYsXP/bufFB8LDLur5ClavwzvGpxvmvXLoyMjGjSpAlr165VIaeUF7k5OTkMHTqU1q1b0759e3Gd/q3z2b8Ryq6Z69atQy6Xo62tLcb6J0+e0KhRI1JSUlSc8kq6d5Tbl6T3b9++jaWlJQYGBjg4OJCcnMyPP/7IgAED0NTUxN/fX2gBOTo6YmdnR0REBKdPn6ZPnz4YGxszaNAgKleujJeXF5aWlpibm6NQKDh06BAAv//+u1r75hUYM2YM1tbWbN++HYCmTZtiaWkp5Dbu3r3L5MmTiYqKokmTJh/dGOLWrVs0bdqUY8eO0bt3b1xdXbG1tcXAwAAdHR0yMjL49ttv0dHREcSTgYEB9erVo27duowcORILCws0NDTQ0tIiIyODHTt2kJmZSWJiooq+6YULF/D19aV9+/a0atUKmUwmki95eXnMnj27REJq/vz5JUoT/BvwXyJs1VDjU8YnTUa9aqDZuXMnBgYGwuVNwp9//knVqlVp3779KwfdwsJCXrx4QVhYGK1btxavSwFpdHQ0GhoaeHh4CDeKnJwcGjRogIaGBnXr1i32ndft64fGyJEjhWUrFJ2r7t27q4ghbt68WTgB9uzZk7CwMCH6Kk3uP/30E/r6+iQkJLBkyRLg3zeRKWPy5Ml4e3tTo0YNISxaUFDA3r178fDwIDw8XHz26NGjpeZ6f8pQJhCkbJ8yXrVIVF5ETJo0iRs3bgBFLTvOzs5oaWkxf/588ZmHDx9SuXJloSskfU+hULBq1ap3dTilAgcPHqRVq1b/yfvzY5FxJZGlakLq3UL5ft6+fTvz5s1j7dq1Yq776aefMDAwoFWrVmzdulWQU5JAb0FBQYk6M+rrVLrxJtdMbW1tFAoFPXv25MiRI+zbtw9zc3Pq169fzCnvVZASG4WFhfTv3x9LS0vs7e3x9PSkcuXKGBkZsWDBAmJiYtDS0qJXr16UK1cOFxcXQYZt3LiRmzdv0q9fP1Hh8r///Y9u3bpRvXp1FdJAglr75v9RUFBAbm4uqampIqbftGkTRkZGTJ8+HSia96Vr9ezZs4/Syqh8Py5YsAArKysqVarE7du3+eWXX5DL5SQkJAjBcltbW8zMzDA1NcXY2BgTExP09PSIjo7mzp07/Prrr6Snp7NhwwYWLlyIg4MDDg4OhIaGUqNGjWIdF0uXLsXW1hZtbW1R7SSdhxcvXjB79my0tbWLteyBeqxTQw01Ph4+WTJKOWicO3cu33zzDbNmzRKT0Q8//IBMJmPo0KH89NNP7Nmzh8TERAIDA1WyAK9alE2dOhVHR0c2btwoXsvJyaFixYooFAosLS3Fd3fv3o2TkxOtW7dGW1u7mFhgacHZs2dp2LChmLiuXLmCvr6+OE/K2Lx5M5qamjRs2BCFQsGgQYNU3t+yZYvQSJKyi/9W5Ofns3DhQnx9fXFxcVF5r6CggP/97394enqW+J4a/wx/lUBQPucDBgxAJpNRrVo1oIiISUlJwd/fX1THXLt2jZSUFCIjI1WCsVWrVrFs2bJ3fDSlA/9lDZzSQMapg/73h549e+Lu7k5wcDCJiYm4uLgwdepU5s2bx/DhwzEwMKBNmzasX79ekFPKFufKccW/Obnyb8PrXDNXrFiBtbU1Dg4O6OjoYGhoSG5ubolOeS9j7NixxMXFcf/+fXbt2kVISAh79+7l1q1b2NraolAoCAsLQ19fn5CQECZPnsypU6fo3r07RkZGDBs2jDJlylCtWjX279/PH3/8wfTp00vUplNOrqi1b0p+/uLj48nOzmbr1q0qXQ/Pnz9nxowZ7Nq1S2Vs/5DPsPJvrVmzhgULFhAbG4uVlRW5ubkUFhYyZ84ctLS0sLGxEe13ZmZmJCYmEhcXh4aGhnDXW7BgASkpKTRo0EBs++bNm5w7d47Lly+rkG3SMe/atQsvLy+8vLz4/PPPi93bL168YM6cOchkMpWOETXUUEONj4lPloyS0KdPHywsLAgKCsLT05OEhAQhvj127FjKlCmDmZkZkZGRVKtWTWVSV560du3axerVq/njjz8oLCzk0qVL1K9fn7i4ONavXw/A/fv3qVSpEjVq1FCpurp+/TrHjh0jNzeXUaNGERsbW2oDWWm/1q9fz927dzl8+DDOzs4kJSUVszDfunUrMpmMBg0aoKWlJbKLFy5coHr16gwfPvyts4ufEkq6djk5OaxYsQIbG5tiovcFBQVkZmbSoEGD/1Sw+KHwNgRCQUGByvudO3fG0tKSJk2akJqaKl5fuXIlycnJGBoa4uvrS1BQEBEREWJc+K8QBaV1fPoQ+C+Tcf9mzJo1CxsbG2Fc8t1336GhoYGNjQ0hISEkJiaKReDw4cPJzMzEyMiINm3akJub+5H3Xo2/i7dxzUxNTcXHxwd3d3eRsMzIyMDLy4ubN2+KbSmPCQUFBRw8eBBTU1Nq1KjBuXPn6NOnD/n5+WzZsgVjY2M0NDQoW7Ys3t7eQmjayclJVM+vXLmSM2fOYGlpSUJCgjBRgDcbJPyXtW+U56clS5YwceJEAGrXro2npycmJiYqhkTXrl0jISGB2bNnf/B9heLGR/7+/mRlZbFt2zbKli1L+fLlRWxYt25dZDKZaMuTyWTIZDLKlSuHm5sbzZo1Qy6XY29vT2ho6GtdE1++J54/f05+fj4LFiwgJCSENm3aFNPdLCwsZMOGDf+p+0kNNdQo3fjkyCjlYOHp06c0atSI48ePk5uby8aNGwkODiY8PFwQUhcvXuTMmTNcuXLllWW7PXr0wMrKCgsLC5ydnZk6daoIBJo2bYqenh5ubm64ubnh5+dHTk4OvXr1UtGdUd4n6XdK64Lv5s2bODs706JFC+7du8e+fftwcnKiZcuWxSauAwcOkJeXJ7KLjo6OODg4EBwczNOnT98qu/gpQfn+unLlCnfu3BFteTk5OSxfvhwXFxfS0tJUvqd8rdWE1LvHXyEQunTpgomJCRcuXGDLli0EBASoXJ/ff/+dNWvWMGnSJNauXfuvEN1X46+htI7Navx9dOnSRVier1mzBh0dHYyNjdm/fz85OTkMHDgQmUzGqFGjxLO+fft2ZDIZw4cP/5i7rsY/xF9xzTx58iTp6enFnPKU55b169dz4sQJAL766iv09PSoUqUK169fp7CwkPr161OzZk0SExMJDQ2lXr166OrqisqWVq1a0aNHD+RyOePHj6d8+fJYWVnRuHFjQZb+FfyXiHPlYz158iTBwcEEBwezevVqfv31VyIiIvD39weKCLsHDx6QkpJCbGzsR4+9Tp48SVpamkjOFhQUsHXrVvz8/IiJieHixYuUL1+eZcuWsWfPHvr164eBgQE9evTg66+/xsvLi06dOlGmTBkVbcySYhPl87RhwwZWrlzJrl27xGs//PADISEhfPbZZyI+r1WrFlu3bhWfUcc8aqihRmnAJ0VGKQ++58+fJzs7m8TERC5dugQUBR8///wzwcHBRERECELq5W0oT1iZmZlERESwa9cubt++TYcOHfDy8uLbb7/l2bNn9OzZExcXF4yMjHBxcaF9+/bcunWLW7du0bdvX4yNjZkxY0ax3ynti52jR48SGhpK69atuX//Pnv37hWElBSEKSMvL49r166xf/9+du/eLa5Fr169imUXP1Uo31/Dhg0jNDQUX19fKlSoINq6cnNzWb58OW5ubtSrV+9j7ep/EiU9UzVr1hTCrlKFmqWlpQi+1q9fj5mZGXfu3Hlt4PWxg1g11FDjn6FTp06MHj2a9evXY2hoSEJCAr169aKgoIDOnTujo6PD5MmTgaLEwtWrVwE4cuSIelH2L8DbuGbm5eVx+PDhYk55ynNLRkYGnp6eDB06lK5du2JlZcWIESOwtLSkWrVqZGZm4urqSpkyZXBwcCAwMFDECc7OzoIouXPnDqNGjUIulxMYGMjhw4fR19dnwIAB7/dE/EvQo0cP6tatS1RUFGZmZnh6ejJ16lSWLFmCo6Mj5cqVIyoqiqioKIKDgz96K+P06dMJDg4mJCRErEkKCgrIy8tj69atBAQEEB4ejp2dHX/88Qfr1q3D0NCQ/v3706xZM4yNjYWTnjJJWtLxKN+v3bp1w9raGltbW/z8/OjSpYt4b+bMmURERBAREUF4eDgODg5vrMhTQw011PjQ+KTIKAm9evXC2tqaoKAgrK2tOX/+vHgvPz+f7du3ExYWhpubm4qW0dmzZ1W2s2DBArp27arimgfQtWtXvL29SU1NxcrKqphzx+7duwFUBCnXrFnzvg73vSErK4ugoCAVQsrV1ZVatWqpiJyXhJMnT9KsWbNi2cV/A/r06YO1tTXLli1jx44dREdHY2lpKTKaubm5rFixAl1d3WLOJGp8OPz5559s3LixmF6ZMjGalZWFg4MDt27dAoqCuNatW3P37t0Puq9qqKHGu8GrqkSGDBmCg4MDRkZGTJ06VZBTixcvRqFQUKNGDfH9uXPnMmHCBBXXTTUh9enjbV0zX9X69O2332JhYcGBAwdYv349bm5u7N27FyiKH93c3LCyskJLSwuZTIajoyMKhQKZTIauri4NGjRQIUoiIiIwMTHh888/B4qIT3Xi482YM2cOpqamHD16lPv373Pz5k2hqzR79myuXr3KiBEjGDx4MDNnzvwo1c0vj0MnTpwgICAALS0tFi5cqPL+8uXLhaC5g4MDgwYNwsTEhEmTJpGVlcVXX33Ft99+S9myZZk3b95b78O5c+eIjo4mOzubU6dOMW7cOMqWLUubNm3EZ9auXcuIESPo3r272kBDDTXUKJX4JMgo5UF93bp1uLm5sWLFCiZPnkxAQAB+fn48fPhQfCY/P5+NGzfSsmVLMUnVqFFDpYICIDExEZlMRlJSkkq2oKCggE6dOmFkZERKSgqPHj0q0bkjLy+vREHKTwkSIdWmTRsePHhAZmYmderUeW1ZeF5eHllZWcWyi58qlI/1wIEDREVFiXLndevWYWpqir+/P4aGhoKQysnJYceOHerA8iNBOfMIMG7cOBVtKOl5vnPnDvb29uI+rV69OmZmZp/s86qGGv9lKI/VW7duFeYkEpKSkjA1NeXAgQP06NFDiEy7uLiIZ/7evXskJSUxZMiQD77/arx/vK3phaQTJs3hOTk51KhRQ4igz5w5E19fX+7duye+8+jRIzp37oyenh7p6ekEBwdTvXp1IiMj0dXVxdnZmc2bN6sQJa1bt6Zq1aoqc446bng9+vbtS0xMjIoW5NWrV4mIiMDd3Z3ly5eLz0qE4oc8p8rj0OrVq0VC/OLFiwQGBhIXF8fOnTsB6N27Nw4ODowbN45Dhw7Rrl07ZDIZPXv2FNt48OAB1apVo2rVqm/dkjlr1ixSUlJU1jkPHz5k6tSpuLu707Zt2xK/p7731FBDjdKGT4KMkjBnzhzGjRvH2LFjgaIJ4eTJkwQFBeHv78+jR4/EZ5UH9OjoaIKDg0UWVCrPB2jVqhWOjo7MmjVLxVUHwNbWlurVq7Nly5YSnTukCikJn+oCNysri9DQUNLS0oTVNbxZp+DfVu47bNgwOnfuzIgRI4CixY61tTWTJ0/mypUrlC1bFltbWxFkSFBP7h8Wo0ePRiaTiVaMZ8+eMXPmTKysrGjZsqX4XF5eHrdv38bKyoqtW7fSoEEDypUr99HL+dVQQ42/DuUqlu7du2Nubo6joyNOTk4MHTqUrVu3snbtWnx8fHBxccHMzAwTExMUCgV79+7l2rVr/PbbbyQnJxMeHv7JztdqvBlvMr3o3bs3kZGR3L9/X7yWm5uLh4cHgwcPBmDy5Ml4eXnx4MEDnjx5wrlz5ygoKKBv3754e3tz9OhRoRF69epVfH190dbWJi4uTlSLP3r0iKioqFcSA2qoQnrGhwwZQlhYGE+fPgX+P9bMzMxEX1+fhIQElixZovKdD72PAF9//TXOzs70799fkJvnzp3D39+f5ORkWrdujaWlJYcOHVJJmDdp0gQbGxu++OILunbtSnx8PH5+fuI43xR75+Tk0LNnT5ycnIiJiVF57+HDh0ybNg1PT0+1lIQaaqjxSeCTIaOePn2Kt7c3MpmML774QuU9SeQwKChIiE1LGDhwIIGBgWICWbRoEfXr12ffvn3iM3Xr1sXX15f58+czb968Ep07Zs6cKT4vOXcov/ap4+DBg7Ro0eI/K5S5ZMkSnJyc+OWXX7hz5w5QpEcktXDm5eVRvXp1rKysSEhI+Cj7q0YRrl27RlpaGhYWFhw/fhwoCvoXLVqEvb09zZs3F5/Nzc3F19cXTU1NfH19/3OueWqo8W+A8gLw0qVLBAQEkJWVxdGjRxk7diwymQw9PT2cnJxwcnKiRYsWrFixgm3bthEZGSnIqfLly1OhQgU1If0fwKtMLwoLC5k5cyYxMTGkpqYKQurBgwdUrlyZFi1akJOTw6+//opCoWDgwIEcO3aMli1bcuXKFfr27YupqSnfffcdUESUFBYWkpmZia6uLvr6+piampKamkpaWhrBwcGilby0a4mWFvzyyy8oFAoGDRqk8vqWLVuoW7culSpVokqVKsVa9D8kpJbOI0eOCKJJGk/OnTuHj48PlpaWfP3110BR3JKZmUm7du1YsGABTZs2pXHjxtSuXZs+ffq8toWupLj8ypUrDB48GGNjY/r166fy3qNHj/juu+9o0KDBfyqmV0MNNT5NlFoyqqRJ+/bt2yQlJeHi4sKvv/6q8t6vv/6Kvb09zZo1U3m9W7duhISEAP9PTIWGhtKyZUsOHDggBuq6devi4eGBi4sLgYGBn4Rzx7vGf9XyfOfOnXTo0EGU5xcWFnLnzh3KlCkj+vdzcnKoV68e//vf/9QBZSnAzZs3qVOnjorY56NHj1i4cGExQqpx48b4+fmp9RLUUOMTx5gxY2jWrJlKQurkyZM4ODggl8tp3bo1Y8eORaFQ0L9/f/GZzZs3s2LFCvbu3SvmN/U48O/Hq+bqgoICFi9eTFRUFNWqVROteCtWrEAmkzF48GDu3LnD9OnT0dLSwtXVlcjISDIzM6lQoQIaGhrFhMgloiQiIgI9PT1iYmJU3Jb/bZXk7xtz5sxBS0uLnj17cuTIES5cuED16tUZPnw4p06dQiaTCde6D42nT5+SlpbGmDFjgP+PmZXXBIcOHUIulxMZGcmuXbto2LAhERERhIWF4eDgIO6NNzkxK8fj2dnZ7NmzR8gUSC6hXl5eDBw4UOV7ubm5/9mYXg011Pi0UCrJKOWB848//lAppb537x7h4eF4e3sXEyS/dOmSGMylQXjPnj14e3vj7++PqakpDx8+ZOXKlYSFhdGsWTMOHDgAFDl3ODg4oKmpiaGhYal37nhf+K8RLTdv3sTd3R0jIyNGjx6t8l7dunWxs7NjwoQJxMTEEBkZKa63enL/+Lhx48YrCSkHBwcVYlq9AFVDjU8bOTk5dO/eHQMDA1JSUoD/J6c6dOjApEmT0NbWplOnTkyaNAmFQiF0Il+Gevz+70J5gb5o0SKioqJISUkRFdEzZ85ES0uLuLg4oqKi8PT0REtLCwcHB3x9fUlMTBSf6d69e4lEiYaGBl5eXrRr107FYEeNv4YVK1ZgbW2No6MjDg4OBAcH8/TpU37//XfKli37StfE941Hjx7h5OSkUrkl3Vd//vmnMFEZPXo0ZmZmGBsbk5GRIciz9PR0lYTZq6Acj/fp0wcPDw/KlSuHo6MjnTp14vLly9y+fZuBAwfi7e0tWkxftQ011FBDjdKIUklGSejbty+hoaE4Ojry/fffc/nyZaCIkAoLC8PHx4dz584V+97LBFHVqlWRyWQkJyeL1xYtWiQIqX79+gnnjm7dunHt2rVS59yhxvtDdnY2Hh4eREVFibYvKHJHadSoEeHh4dSpU+et+/nVePd41Tm/du1aiYTUokWLkMvlKiLF6uumhhqfDl7VmjJgwABkMhljx45VIadyc3MZNWoUsbGxPH78WJBTX3311UfYezVKG0palOfn57Nw4UJRISW5rO7evZtvv/2Wzp07M378eG7evMlvv/3GqVOnxH25bNmy1xIlS5cuJSIigkaNGnH69OkPeqz/Jly7do39+/eze/duce579eqFl5eXinPuh8Tz58+pX78+TZs2LbYP+/bto0GDBuL1y5cvq1z/goICKleu/EqiXILy/Tp27FhsbGyEXmn79u0xNTUVTo83btxg8ODBmJmZMWvWrHdyjGqooYYaHwqlloxatGgRzs7OzJo1ix49emBmZkbnzp05c+YMAPfv3ycyMhILCwuuXLnyyu3cu3eP1NRUhgwZgo+PD40aNVL5jfDwcAICAggICFBx7vj9999LjXOHGu8f2dnZBAUF0bZtW06cOKHy3r1798R1VxOQHx4vux3u379fVDRCUSBWu3ZtFULq4cOHbN26Vf2cqqHGJwjlZ/7MmTP873//486dO+Tn5/P06VN69eqFoaEhI0aMEOTUlClThKA0FFVSSeSUujrgvw3l++nSpUvcuHFDkAV5eXksWLCgWIXUy2So8lwivfcmouTQoUPExcVx48aN93p8/xWcPHmSZs2aYWFhIeb6j4X58+ejo6PD0KFDVRLltWrVKtEVLycnhz179pCamoq/v/8rY8kLFy6If+fn51NQUEDdunVFS+CaNWswMTERbX6SyPv169eZNWuWOuZRQw01PjmUGjLq5YF7xYoVTJo0Sfy9cOFCHB0d+fLLL0V73p07d2jTps0bB9/8/HwKCwuZNWsWXl5eNG7cGCgilhYvXoyJiQn29val0rlDjQ+HrKwsQkJCaNeuHSdPniz2vvraf3gon/O+fftSpkwZypYti5GREcOHDxcBnaQhJTnXKEMdnKmhxqeDl1tTvL29sbGxISwsjA4dOvC///2PTZs20a1bN4yMjJg8ebIgpyTHW2kbyuSUevz+b0I5thw8eDDh4eG4uLiQnJzM2rVrgf8npKKjo0lNTRWE1F/Bq4gSKa5U458hLy+PrKwsunfvXmJ89jEwadIkbG1tKV++PNHR0SK5/XIVfWFhITt27CA1NZWqVau+UuajQ4cOJCUlcfToUfHakydPiImJ4dChQ+zdu7eYs/eECROKOXurYx411FDjU0KpIKOUg8Q5c+bQt29fUlJShKC0hEWLFuHo6Ejnzp2LTUZvM/jm5uYye/ZsvLy8aNKkiXh9+vTppd65Q40Pg6ysLMLDw6lXr54QiVTj40B5XBg6dCg2Njbs3r2bZ8+e0aNHD2QyGT179hSB3c2bN6lYsSJVq1b9WLushhpqvCOMGTMGa2trfv75ZwCaNm2Knp4erq6u2NraEhgYSEhICBoaGsyfP5++fftibGzMjBkzim1LTUSp0b9/f6ysrFi7di2ZmZnUrFkTIyMjli1bBhSRHQsXLqRcuXLCRfdtURqJkn8rSoMQvDLBmZmZyZQpU/jiiy+YOHHiK41Snj17RlZW1mv1K3/++Wfc3d1p3LgxR44cEa+3aNECJycn9PX1mT9/vnj9zp07xMfHqyTu1VBDDTU+NXx0Mko5SOzXrx+6urpUqlQJmUxG+fLlOXjwoMrnFy9ejEKhYOzYsX/r93Jzc5kzZw6+vr4qi9bS7NyhxofFwYMHadWqlVpj6CNh3rx55Obmir/Pnj1LzZo1Wb9+PVBUpm5qakrbtm3R0tIiIyNDZJ/v3bunvm5qqPEJo6CggNzcXFJTU5kyZQoAmzZtQkdHByMjI7Zv387z589p0qQJ5ubmZGRkkJeXx82bN+nXrx8ymYw1a9Z85KNQ42NDObbctWsXISEhQmNn8+bNGBkZERcXh6GhIStWrACKiI4tW7b87cqS0kCUqPFh8DqC+033T0kxinTv7N+/H3d3d5o1a8b+/fsB+OWXX4iOjsbX15fCwkIKCwu5d+8eycnJREVFqSuh1FBDjU8aH52MknDkyBHatm3L//73PwBWr15NaGgozZs35/Dhwyqf3bZt2z8afHNzc5k0aRKNGzdWmRRKq3OHGh8eakvcj4Nx48bRqFEjlfN+584dZsyYwZ9//smePf/X3r3H13Tl/x9/nZNE0hBNGQmlzUTLA0GTGJcZ1UeiaEcyjQihKClK3WlQVW0NFSHuDw8TcYnWiHvEJaGtW+JaKqGEumsp0TLimus5+/eHX84kHe23dUlE3s9/JDtn772Oxz7r7P1Zn/VZO4waNWrYRgL79OljmEwmo2/fvves6SEij797Pdj5+fkZhw4dMjZu3GiUL1/eaNCggTFnzhwjJyfHGDRokOHs7GzMnTvXMIy701WysrKMjIwMY+7cuartV8YV7v9v3rxp/PTTT8bo0aMNq9VqfPHFF4abm5sRHR1tnDlzxmjYsKHh7OxsLFq0qMgx9IBf9tzrvuH33Es8aOZl4XMcOXLEGDZsmFGhQgWjY8eOthqmS5cuNRo0aGC4u7sbf/vb34zGjRsbvr6+T+zK3iJSdpgMwzAoYatWrSIyMhJ7e3uSkpKoVKmSbfukSZOoW7cuQ4YMoVGjRkX2s1gs2NnZ3dc5s7OzcXR0xGQyYbVaMZvNAPz444+cP3+evLw8mjdvjtls5oMPPiAhIYFt27ZRtWrVB3uzUmoYhoHJZCrpZpQ5+fn52Nvbs2vXLurVq8czzzzD7du3KV++POHh4WRkZDB//nyeeuopxowZwzfffENOTg5btmyxfY5FpHQo3M8uW7aMK1euMGDAANq3b8+xY8fIyMhg2rRpLF68mJkzZ3LkyBG6d+9Oly5d+Pzzz8nNzeWzzz6jTp06tGjRwnbcgn5EypbC93NTp07l1KlTfPDBB7i5ueHk5ERoaCienp5ERkZiMpkIDQ0lPT2dGjVqsGnTJgB975dBha+bo0ePcuvWLTw8PKhUqRIODg6/ul/h/uv69es8/fTT992G4cOHs3LlSkJDQ8nIyGDFihUEBAQwYcIE6taty8WLF/n3v/8NQNWqVenatSt2dnbq60SkdCvRUNj/Fx8fb/j5+RkuLi7G1q1bi/xt1apVRtOmTY2AgADbSnoP02+NaDxOK3eIPOkK12TbunWr4eHhYYwbN864fv26YRh3ay60atXKtiJmTk6OERQUVGRKjjKiREqPX2YE+Pj4GN7e3saaNWuM9PR044UXXjCqVatmGIZhvPHGG0atWrUMe3t7o1atWrZMgAsXLhj+/v7G/PnzS+Q9yONp5MiRRpUqVYy4uDhb/cfMzEzjhRdeMCZOnGgYhmHcuHHD6Nixo7Fu3TrVFSvDfrlQSu3atY2aNWsanp6exvDhw42TJ0/+n/tFR0cbI0aMMG7evPm7zjlx4kTj1KlTtt/37t1rVKlSpUgx8m3bthlVqlQx3njjjV+dmaGMKBEp7Yo9lF549KFAcHAwLi4uTJgwgU8//RQ7OzteeeUVAEJCQrhz5w7JycnUqlXrobfn10bA8vPzyc3Nxc3NjeTkZLy8vB76uUXkv8qVKwfA/v378ff3JygoiMTERMxmMwMHDuTpp5+me/fu9OjRg2vXrnHx4kUAAgICgLsjlMqMEik9Cj6vI0aM4OzZszg5OfHdd98xatQoQkNDsVgsXLlyherVq+Pm5salS5ewt7cnPT2d/Px8MjMzeeedd8jPzycsLKxk34w8NrZs2cLKlStZs2YNzZs3t22vWLEir732GjExMWRnZ7Nt2zays7Np27bt/2TJS9lR8BwwdepU5s+fT1xcHC1btqR79+4sWrSIDh068OKLLxbZxyiUERUTE8PgwYOJi4ujQoUK/+f5Tpw4wcGDBxkxYoRtm4ODA+XKlcPFxQW4O/PDz8+PuLg4Xn/9dZ555hl69epVJPsTuO/ZISIij4tinaZX+It+69at3L59m7y8PNq3bw/Al19+yfTp07FarYwZM+Z/Ot1fHqM45OXl/WaKrog8mPj4eFatWkVcXBzDhg0jJSWFPXv2UK5cOYYOHcrOnTtp164dAwcOxNXVlWXLlrFp0ybc3d2ZMGEC9vb2DzRlV0RKzqJFixg2bBhbtmzB09OTnJwcmjVrxu3bt3F1deXnn3/GwcGBZs2a8eyzz5KUlISzszOVK1fGZDKRlZXF119/jYODg/oBASA2NpapU6eyc+dOXF1dgf8GD/bu3cvq1atJTk7Gw8ODuLg4HBwcFIgqwwzDIC8vj44dO9KqVSsGDRrE+vXr6datG5MnT6Zv377k5uZitVpxcnIqEoiaO3cuI0eOJDY21vYs83vPaTKZSExMxMPDA1dXV+rVq8e8efPo1KkTubm5ODg4cPv2bby9vTlz5gxjx47l448/flT/DSIiJaJYM6MKvuiHDx/O8uXLsbe3586dO4wfP57FixfTpk0brFYrs2bNYuLEieTk5NCqVat7HqO4KBAl8ugYhoGjoyOrV6/Gx8eHM2fOsHv3bluW1IwZMxg6dCgJCQmYzWb69+9P586dCQkJsX02VS9BpPQ6deoU9evXx9vbG4DPP/+czMxMatSowe3bt4mKimLlypXcvHmTpk2b8tFHH/HZZ59hsVioXr06YWFhqpsiwH8f8LOysrBYLEW2F/wtIyODrl27EhkZidlsxmQy6dop4/Lz87Gzs+Onn37C39+flJQUunTpwpQpU+jbty85OTnMmzePJk2a0KRJkyKBqPfff5+FCxf+oUAUYLsWBw4ciJ+fH+PHj2fUqFGEhYXx7LPP2gbjLRYLrVq1IiAggLZt2z709y4iUtKKfRhowYIFLFq0iLVr15KcnMzevXtxdHQkODiY8+fP8/rrrzNgwACuXr1KUlJScTdPRIpB27ZtSUtLw2QyERAQQJs2bTh06BB+fn62KbF5eXnA3YBUixYtWLt2LZGRkdy6datIkFgPESKlT0FStqOjI9nZ2eTm5mI2mzl+/DgNGjRg5syZXL58maVLlxIUFERWVhYRERHs3buXDz/8kI8//piePXtiZ2eHxWJRPyC2IIG/vz8nT55kxowZtu1ms5mbN28SGxvLjh07sLOzw2QyYRiGrp0y5ptvvrH9PGvWLFJSUrCzs+P5558nODiYtm3bMnv2bPr27QtAZmYmq1at4tChQ7b9oqOjGTlyJAsWLCAkJOS+2lG1alVWr17NkSNHGDduHI0aNaJPnz74+fnx0UcfMW3aNEJCQkhLSyMwMNDW14mIPEmKPRh18uRJWrVqha+vL8899xyenp7s3r0bJycnW8cfEBDAzJkzmTJlSnE3T0QeMYvFQr169ahXr55tW1BQEDNmzCAlJYXu3bsDd7MSs7OzAZg+fTre3t5kZGRQvnz5Emm3iDw8BYGDdu3akZaWRmRkJADOzs5kZ2dz584d2rZti2EYJCQkMH78eC5dusScOXNYtmxZkWNpap4UVrduXebMmUNERARDhgzhq6++Ijk5mQ4dOnDu3Dn69etne61Wzitbjh8/TteuXRk0aBDvvfce4eHhVKtWDYDw8HAqV65MrVq16NGjB4ZhkJmZydtvv43FYqFnz56243z//fcsXLjwvgNRBXx9fYmJiSEtLY01a9YQGhpKTEwMGzZsYPny5Tg7O7Nz505b4FR9nYg8aR5pzah7zcHv1q0bJ06cYN++fQBkZ2fj5OTEihUrGDNmDJs3b+b555//zWOIyJNh6tSp+Pr64u/vD2Cr0xAUFMTnn39ue93OnTt5+eWXbVMtCtdsEJHSbdGiRfTp04ehQ4fSqFEjunbtSs2aNQkLCyM4OBgvLy8mTJjAgQMHuHbtGmazmcTERNt0XpFfMgyDdevWMXjwYCwWC66urlSvXp0NGzaovlgZduPGDeLi4vjwww/Jzc1l7969eHl5YRgGubm5LFmyhKioKO7cuYOnp6cta7OgLt2jqiObmppKnz598PX1Zfz48bi7u9vqRmkqqYg8yR5ZlOeXxcoPHz4MQO/evcnIyGD69OkAODk5AXdX0nJwcMDR0bFoAxWIEnkiWa1WvvjiC4KDg9m1axcAgYGBxMXFsX79ejp37szRo0f5+9//zrhx4xSIEnlChYWFsXTpUj777DOGDx+Oi4sLp06d4sqVK5w+fRoPDw82btyIr68vs2fPZsuWLaSkpJR0s+UxZjKZCAoK4sCBAyQnJ7NmzRo2btyIg4ODrUaQlC2GYVCxYkVbJpS7uzsxMTHA3evF0dGRbt26kZiYSM+ePWnZsiXvvPMO+/fvt103j6qOrK+vL/PmzSM1NZUBAwZw+vRpypUrZ1vlUYEoEXlSPZLMqMIPi++//z4bN26kZ8+evPPOO9y6dYtJkyaxZ88eAgMDCQ8PtxXxMwyDDRs26EFT5Al0ryzHvLw8unbtytatW0lISLBlP23bto0uXbrg6upKxYoV2bVrlxYTEHnC/fjjj5w/f568vDzbfUFWVhZZWVnUqVOH/fv3c/nyZVq3bs2qVato2LBhSTdZShll25c9vxzIOn/+PFlZWWzevJno6GiaN2/Ov/71r988RnFl0u3bt4/o6Gjmz5+v61REyoRHOk1v8uTJREVFkZCQgLe3t63Wy9mzZ1mwYAELFiwgOzsbd3d3XFxc2L17t5bYFXkCFf5Mnz17FgBPT0/g7o1iSEgIKSkptoAU3C0a+t1339GkSRPMZrPS1EXKkPT0dD755BO++uorpk+fTlhYGGazmQ8++ICEhAS2bdtG1apVS7qZIvIYK3zvcfnyZSpUqABA+fLluXLlCosXLyY2NpZXXnmF2bNnAzBixAj+8Y9/8Morr5RIJnbBOfUsJCJlwSPLjLp+/TqdOnWiXbt29OvXz9a5FowuZGdnc+vWLbZu3YqbmxstWrTQ8swiT7hRo0axfv16vv/+e3r06EH37t1p2rQpAO3bt2fnzp2sWbOG5s2bF9lPN2UiZUd+fj6HDx9myZIlvP3223h5eZGens6kSZNISkpi8+bNeHt7l3QzReQxVvi+ITIyko0bN5KZmYmXlxdjxoyhXr16XL16lcWLFzN//nz+9Kc/8dRTT3H48GHOnTtXos8iKkcgImXFI+lpTSYTdnZ2nDlzhtzcXNs2uLvqTVZWFufPn6d27dqEhoba9tPyzCJPlsKp7cuWLWPZsmVERUWRmZlJVFQUly5dYuDAgbRs2ZL4+Hg6duxIixYtOHjwYJEpOApEiZQd9vb2+Pj4UL9+fVutltzcXNzc3EhOTsbLy6ukmygij7mC+4YPP/yQefPmMW3aNACio6MJCgpi9erVNGzYkB49evDcc8+xZs0aHB0dWbduHfb29iVa5F6BKBEpKx5KZtS9shauXr1Kq1ataNy4MTExMUVe8+233xIbG0t4eDg1atR40NOLyGMmMjKS0NBQatasCUBycjJJSUnUrl2bXr16AXdrI/Tv358aNWowZMgQ24p6o0ePZvz48SowKyJFPKqVrETkybRp0yZGjRpFdHQ0zZo1IzExkc6dO/P888+TmZnJF198Qf369f/nOUazNEREiscDpxsU7sBPnz7N2bNnuXz5MpUrV+aTTz5h4cKFREVF2aL8t27dYtSoUZw7d47q1as/6OlF5DFz4sQJDh48iIeHBwDnz5+nbdu2tkyoAk2aNGHOnDlcuHCB2bNns2nTJgAiIiJsU3ZFRAooECUif4SrqyuvvfYazZo1IykpibCwMCZPnkxsbCwA7dq1Iy0trUggyjAMBaJERIrJA2VGFZ7TPHbsWOLj48nLy+P69euMGzeO4OBgVqxYwYABA2jZsiVms5k7d+5w48YNDhw4gIODg+ZFizyBCj7XGzZs4K9//Stnz54lJCSEOnXqMGnSpCL1Xvbv30/79u3p1q0bEydOLLlGi4iISKn0a7Ulf/rpJypVqkRgYCBNmjRh3Lhx5Ofn07p1a9LT02natCnr168vgRaLiMgDZUYVBJHGjx/PnDlzmDJlCt988w3NmjVj5MiRXL16lX79+rF37158fX2pVasWgYGBpKam2upAKBAl8uQxmUxkZGQwYMAAwsPDqVmzJsuWLePYsWPMnDmTw4cP217buHFjvvzySz799NMSbLGIiIiURoUDUenp6Xz99dccPXoUADc3Ny5cuMCRI0eoX78+ANevX6dKlSosWbKEtWvXlli7RUTKuvvKjCrc6VutVoKCgujcuTNdu3YlISGBnj178umnn9K/f39bjYdfFgIsycKAIlI8UlNT6dOnDy+99BJTpkzh6NGjvPnmm7z66quEh4fbbgwLqF8QERGR36vwDIvRo0eTlJTEpUuXaNCgAa6urqxatQrDMHjjjTe4dOkSQ4YMITY2FovFwrZt2zCbzVqxV0SkhNxXz1vQYX/yySdERUWRlpZG48aN2b59O2+99RYRERH079+frKws/vnPf3LhwoX/ecDUA6fIk8/X15d58+aRmprK8OHDqVevHkuXLmX79u2MGTOGM2fOFHm9+gURERH5vQoCUVFRUcTExDB79mzOnDlDgwYNiI+PZ8eOHZhMJgYPHoy7uzsRERE4OTmxefNmBaJERErYH+p9rVar7efly5cTGxtLYGAg/v7+DB48mICAAGbOnMm7774LwLVr10hJSWH79u0PtdEiUnr4+PiwcOFCUlNTGTFiBF5eXixcuBCz2cyf//znkm6eiIiIlDKFJ3bk5OSwZ88epk2bxssvv0xycjILFiwgJiaGFi1aYLFYaN26NYmJiWzdupXExERbuRAFokRESs4f6oELOuzk5GS2b99OeHg4Xl5eNGvWjOPHj/Pqq6/Ss2dPAG7evEnv3r2xs7PjzTfffPgtF5FSoyAgdfDgQXr16kXjxo2Jj4+3jUqKiIiI/B5Wq9WWEXX27FlMJhM///wzlSpVIjExkU6dOjF58mR69+5NXl4e0dHRbNiwAYBq1aphMpmwWq1aNU9EpIT94eGAjIwMevXqxZIlS8jKygLg3XffJTg4mB9++AEfHx9CQ0Np3bo1Fy9e5Msvv8TOzg6LxfLQGy8ipYePjw9z5szBxcUFZ2dn23aNSoqIiMjvYRiG7b7hvffeY/jw4Vy6dIkaNWowc+ZM3nrrLSZPnmybpZGRkUFiYiI///xzkePo3kNEpOTdVwHzb7/9lpCQENzc3Jg1axaNGjXCYrGQmJhIcnIyeXl5eHp6MmjQIOzt7cnPz9fog4gA/y02qjoNIiIicj9OnjxJ586dmTVrFs2bN+fAgQP4+fnx0ksvsW7dOlxdXbl27Rrdu3fnxo0bbN++XXUpRUQeM/cVjIK7AakePXrwl7/8hUGDBtGwYcN7vk6rY4nILxVe/UZERETktxS+b5g4cSKpqak4ODiwcOFCnJycAEhMTKRDhw54e3uTnZ1NhQoVuHXrFvv27bvnyt4iIlKy7jsYBZCWlkbv3r1p1KgRQ4YMwcvL62G2TUREREREyrDCmdQ3b94kPj6et99+mxdffJEdO3bg7u5uC1YdO3aMr776iv/85z/UqlWLzp07Y2dnp1kaIiKPoQcKRsHdgFTfvn3x8PBg8uTJeHp6Pqy2iYiIiIhIGVU4EDV16lROnz7N4MGDOXToEF26dGH06NGMHTsWOzu7X53+r4woEZHH0wMXbPHx8WH27Nm4uLjg4eHxMNokIiIiIiJlXEFw6f333ycyMpIWLVrg6OhIp06dmDt3LhEREUyaNKlIIOqX4+wKRImIPJ4eSr5qkyZNaNy4sYoSi4iIiIjIQ7NlyxZWrlxJQkICzZs3t23v3bs3VquV/v37AzBq1CjMZrNqUoqIlBIPbfK0yWQqstyqiIiIiIjIg/jhhx9wdnYuUpu2oEZUnz59qFChAt26daN69er06NGjBFsqIiJ/xEOt5KeRCBEREREReVAFAaesrCwsFkuR7QX/rl69Gl9fXzZt2kTLli1LqqkiInIflMYkIiIiIiKPlYJBbn9/f06ePMmMGTNs200mE7dv32bx4sVs3ryZNm3aYG9vT35+fgm2WERE/ogHXk1PRERERETkUYmJiWHgwIH069ePwMBAypUrR0REBBkZGRw4cAB7+4c62UNERIqBglEiIiIiIvLYMgyDdevWMXjwYCwWC66urlSvXp0NGzbg4OCAxWLRqnkiIqWMglEiIiIiIvLYu3LlCtevX8dqtfLCCy9gNpvJz89XZpSISCmkYJSIiIiIiJQ6VqtVK3mLiJRSCkaJiIiIiIiIiEix0VCCiIiIiIiIiIgUGwWjRERERERERESk2CgYJSIiIiIiIiIixUbBKBERERERERERKTYKRomIiIiIiIiISLFRMEpERERERERERIqNglEiIiIiIiIiIlJsFIwSEREREREREZFio2CUiIiIiIiIiIgUGwWjRERERERERESk2CgYJSIiIiIiIiIixeb/AZ5XjYTCBaNkAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "all_called_functions = [f for funcs in df['called_functions'] for f in funcs]\n", "function_counts = Counter(all_called_functions)\n", "\n", "plt.figure(figsize=(12, 6))\n", "pd.Series(function_counts).plot(kind='bar')\n", "plt.title('Function Usage Distribution')\n", "plt.xticks(rotation=45, ha='right')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 41, "id": "25bc2cfc-2512-4105-9e87-fe02912023b5", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 6))\n", "sns.histplot(data=df, x='human_msg_length', bins=50)\n", "plt.title('Distribution of Human Message Lengths')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 42, "id": "1aa539ae-1eff-4596-9da7-c3832d19b42f", "metadata": {}, "outputs": [], "source": [ "function_pairs = []\n", "for functions in df['called_functions']:\n", " if len(functions) > 1:\n", " pairs = [(f1, f2) for i, f1 in enumerate(functions) \n", " for f2 in functions[i+1:]]\n", " function_pairs.extend(pairs)" ] }, { "cell_type": "code", "execution_count": 43, "id": "e4556193-3eac-4675-b0de-839cc2322191", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Top Function Co-occurrences:\n", "get_social_media_statistics & get_social_media_statistics: 36\n", "registerDeviceWithIoTCore & configureDeviceMQTT: 25\n", "get_market_prices & get_account_balance: 18\n", "get_account_balance & get_account_balance: 15\n", "registerDeviceWithIoTCore & registerDeviceWithIoTCore: 10\n" ] } ], "source": [ "cooccurrence = Counter(function_pairs)\n", "print(\"\\nTop Function Co-occurrences:\")\n", "for (f1, f2), count in sorted(cooccurrence.items(), key=lambda x: x[1], reverse=True)[:5]:\n", " print(f\"{f1} & {f2}: {count}\")" ] }, { "cell_type": "code", "execution_count": 44, "id": "6d0350ca-bb2b-48bd-8fd8-a08d522e5789", "metadata": {}, "outputs": [], "source": [ "function_by_category = df.groupby('category')['called_functions'].apply(\n", " lambda x: Counter([f for funcs in x for f in funcs])\n", ").reset_index()\n" ] }, { "cell_type": "code", "execution_count": 45, "id": "75ec12d2-3904-4a4e-86f2-05a0d0590190", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAABWEAAAPdCAYAAADrsapyAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3XlcTfn/B/DXad83WyESrZTsQ0wxKNuX0dgHYQxjmywjy6CQnVHM+BqawjBDY/0yZWkUYmQrTIs0EibD2Euluuf3R7/OdFUqbt3K6/l4nMfMPcvn8z6fe+5N7z7nfQRRFEUQERERERERERERUYVQUXYARERERERERERERDUZk7BEREREREREREREFYhJWCIiIiIiIiIiIqIKxCQsERERERERERERUQViEpaIiIiIiIiIiIioAjEJS0RERERERERERFSBmIQlIiIiIiIiIiIiqkBMwhIRERERERERERFVICZhiYiIiIiIiIiIiCoQk7BERERERFVISkoKBEFAcHCwskOpkTw9PaGnp6fsMIiIiOg9wyQsEREREdVYwcHBEASh2GXOnDlKjW3Xrl1Yv369UmN4naurK1q0aFHstn/++QeCIMDHx6dyg6rG8vLyEBQUBFdXV5iYmEBTUxMWFhYYM2YMLl68WO724uLi4OPjg5SUFMUHS0RERBVKTdkBEBERERFVtMWLF6NJkyZy60pKNlaWXbt24fr16/Dy8pJb37hxY2RmZkJdXV05gZFCZGZmYuDAgQgLC8OHH36IefPmwcTEBCkpKdizZw+2bduG1NRUNGzYsMxtxsXFwdfXF66urrCwsKi44ImIiEjhmIQlIiIiohqvV69eaNu2rbLDKBNBEKClpaXsMOgdffXVVwgLC8M333xTJNG+aNEifPPNN8oJrBLIZDK8evWK1zEREVEhLEdARERERO+1km6xt7CwgKenp/S6oLRBVFQUZsyYgTp16kBXVxcff/wxHj58WOT40NBQuLi4QF9fHwYGBmjXrh127doFIP+2/yNHjuD27dtSeYSCmY0l1YT97bff0KVLF+jq6sLIyAj9+/dHfHy83D4+Pj4QBAE3b96Ep6cnjIyMYGhoiDFjxuDly5fvNE7FefHiBby8vGBhYQFNTU3UrVsXPXr0wOXLl6V9Tp8+jUGDBqFRo0bQ1NSEubk5pk+fjszMzCLthYSEwN7eHlpaWmjRogX2798PT0/PIrM+ZTIZ1q9fj+bNm0NLSwv16tXDhAkT8OTJkzLH/ueff8LNzQ26urqoX78+Fi9eDFEUAQCiKMLCwgL9+/cvclxWVhYMDQ0xYcKEEtu+e/cuNm/ejB49ehRJwAKAqqoqZs2aJc2CvX37NiZNmgQbGxtoa2ujVq1aGDRokFzZgeDgYAwaNAgA0LVrV+m6iYiIkPYJDQ2VrhF9fX306dMHf/zxR5H+yzrOGRkZmDlzJszNzaGpqQkbGxusWbNGGqcCgiBgypQp2LlzJ5o3bw5NTU2Ehoa+0xgSERHVNJwJS0REREQ13rNnz/DPP//Iratdu/ZbtTV16lQYGxtj0aJFSElJwfr16zFlyhTs3r1b2ic4OBhjx45F8+bNMXfuXBgZGeHKlSsICwvD8OHDMX/+fDx79gx3796VZkS+6WFRJ06cQK9evWBpaQkfHx9kZmZiw4YNcHZ2xuXLl4skzwYPHowmTZpg+fLluHz5MrZu3Yq6deti5cqVb3XOJZk4cSJ++eUXTJkyBfb29nj06BHOnDmD+Ph4tG7dGkB+wu/ly5f44osvUKtWLURHR2PDhg24e/cuQkJCpLaOHDmCIUOGwMHBAcuXL8eTJ08wbtw4NGjQoEi/EyZMQHBwMMaMGYNp06bh1q1b2LhxI65cuYKoqKhSSznk5eXB3d0dH3zwAVatWoWwsDAsWrQIubm5WLx4MQRBwKeffopVq1bh8ePHMDExkY793//+h+fPn+PTTz8tsf3Q0FDk5uZi5MiRZRrHCxcu4OzZsxg6dCgaNmyIlJQUbNq0Ca6uroiLi4OOjg4+/PBDTJs2DQEBAZg3bx7s7OwAQPrvjh07MHr0aLi5uWHlypV4+fIlNm3ahM6dO+PKlSvSNVLWcRZFEf/5z39w8uRJjBs3Dk5OTjh69Ci++uor3Lt3r8hM3t9++w179uzBlClTULt2bTRp0uSdxpCIiKjGEYmIiIiIaqigoCARQLFLAQDiokWLihzbuHFjcfTo0UXa6t69uyiTyaT106dPF1VVVcWnT5+KoiiKT58+FfX19cUOHTqImZmZcm0WPq5Pnz5i48aNi/R769YtEYAYFBQkrXNychLr1q0rPnr0SFoXGxsrqqioiKNGjZLWLVq0SAQgjh07Vq7Njz/+WKxVq1bxg1SIi4uL2Lx582K3PXz4sMhYGRoaipMnT35jmy9fviyybvny5aIgCOLt27eldQ4ODmLDhg3FFy9eSOsiIiJEAHLjdPr0aRGAuHPnTrk2w8LCil3/utGjR4sAxKlTp0rrZDKZ2KdPH1FDQ0N8+PChKIqimJiYKAIQN23aJHf8f/7zH9HCwkLuvXzd9OnTRQDilStX3hhLgeLG6Ny5cyIAcfv27dK6kJAQEYB48uRJuX1fvHghGhkZiePHj5dbf//+fdHQ0FBufVnH+cCBAyIAcenSpXJtfvLJJ6IgCOLNmzeldQBEFRUV8Y8//pDb913GkIiIqKZhOQIiIiIiqvG+/fZbHD9+XG55W59//jkEQZBed+nSBXl5ebh9+zYA4Pjx43jx4gXmzJlTpCZm4ePKKi0tDTExMfD09JSbTejo6IgePXrg119/LXLMxIkT5V536dIFjx49wvPnz8vd/5sYGRnh/Pnz+Ouvv0rcR1tbW/r/jIwM/PPPP+jUqRNEUcSVK1cAAH/99ReuXbuGUaNGyc0IdnFxgYODg1x7ISEhMDQ0RI8ePfDPP/9IS5s2baCnp4eTJ0+WKfYpU6ZI/19wO/2rV69w4sQJAIC1tTU6dOiAnTt3Svs9fvwYoaGhGDFixBvfy4Jx1tfXL1MshccoJycHjx49QrNmzWBkZCRX2qEkx48fx9OnTzFs2DC5MVFVVUWHDh2kMSnPOP/6669QVVXFtGnT5NbPnDkToigiNDRUbr2Liwvs7e3l1r3LGBIREdU0LEdARERERDVe+/btFfZgrkaNGsm9NjY2BgCpHmlycjIAoEWLFgrpryC5a2NjU2SbnZ0djh49ioyMDOjq6pYpRgMDg3eKp3DibNWqVRg9ejTMzc3Rpk0b9O7dG6NGjYKlpaW0T2pqKhYuXIhDhw4Vqdn67NkzuXNs1qxZkf6aNWsml4hMSkrCs2fPULdu3WLje/DgQannoKKiIhcjkJ8wBCBXh3XUqFGYMmUKbt++jcaNGyMkJAQ5OTmllhkoGOMXL16UGgsAZGZmYvny5QgKCsK9e/fkaq4WjNGbJCUlAQC6dev2xnjKM863b99G/fr1iySSC8ofFLRVoEmTJsX2/bZjSEREVNMwCUtEREREVIy8vLxi16uqqha7XnztYUXK9LYxamlpFfvALADSg70Kz+4dPHgwunTpgv379+PYsWNYvXo1Vq5ciX379qFXr17Iy8tDjx498PjxY3h7e8PW1ha6urq4d+8ePD09IZPJyn1uMpkMdevWlZtdWVidOnXK3WZJhg4diunTp2Pnzp2YN28efvzxR7Rt27bYhHhhtra2AIBr167Bycmp1H6mTp2KoKAgeHl5oWPHjjA0NIQgCBg6dGiZxqhgnx07dsDU1LTIdjW1iv+1r/Bs3sLedgyJiIhqGiZhiYiIiOi9ZmxsjKdPn8qte/XqFdLS0t6qvaZNmwIArl+/XuyMwwJlvRW7cePGAIDExMQi2xISElC7dm25WbDvonHjxvjtt9+QmZlZJKlW0H9BPAXMzMwwadIkTJo0CQ8ePEDr1q3h5+eHXr164dq1a7hx4wa2bduGUaNGSce8Xg6ioM2bN28Wien1dU2bNsWJEyfg7OxcYuKvNDKZDH/++ac0+xUAbty4AQByDzkzMTFBnz59sHPnTowYMQJRUVFYv359qe336tULqqqq+PHHH8s04/OXX37B6NGjsXbtWmldVlZWkeuypGum4JqrW7cuunfvXmI/5Rnnxo0b48SJE3jx4oXcbNiEhAS5tkrztmNIRERU07AmLBERERG915o2bYpTp07Jrfv+++9LnAlbmp49e0JfXx/Lly9HVlaW3LbCM1F1dXXLdKu5mZkZnJycsG3bNrmk3PXr13Hs2DH07t37reIsTu/evZGTk4PNmzfLrZfJZNi0aRM0NDTw0UcfAcifKfx6/HXr1kX9+vWRnZ0N4N8ZuYXPWxRF+Pv7yx1Xv359tGjRAtu3b0d6erq0PjIyEteuXZPbd/DgwcjLy8OSJUuKxJ+bm1skcVmSjRs3ysW0ceNGqKurS+dXYOTIkYiLi8NXX30FVVVVDB06tNS2zc3NMX78eBw7dgwbNmwosl0mk2Ht2rW4e/cugPxxen2W8oYNG4pcgwXJ9tfP0c3NDQYGBli2bBlycnKK9Pfw4UMA5Rvn3r17Iy8vT26cAOCbb76BIAjo1avXm4ZAztuMIRERUU3DmbBERERE9F777LPPMHHiRHh4eKBHjx6IjY3F0aNHUbt27bdqz8DAAN988w0+++wztGvXDsOHD4exsTFiY2Px8uVLbNu2DQDQpk0b7N69GzNmzEC7du2gp6eHfv36Fdvm6tWr0atXL3Ts2BHjxo1DZmYmNmzYAENDQ/j4+LztqRfRr18/9OzZE9OnT0d0dDQ6deqEly9f4tChQ4iKisLSpUul2/1fvHiBhg0b4pNPPkHLli2hp6eHEydO4MKFC9KMTltbWzRt2hSzZs3CvXv3YGBggL179xapDQsAy5YtQ//+/eHs7IwxY8bgyZMn2LhxI1q0aCGXMHRxccGECROwfPlyxMTEoGfPnlBXV0dSUhJCQkLg7++PTz755I3nqaWlhbCwMIwePRodOnRAaGgojhw5gnnz5hUpZ9CnTx/UqlULISEh6NWrV4m1aF+3du1aJCcnY9q0adi3bx/69u0LY2NjpKamIiQkBAkJCVIysm/fvtixYwcMDQ1hb2+Pc+fO4cSJE6hVq5Zcm05OTlBVVcXKlSvx7NkzaGpqolu3bqhbty42bdqEkSNHonXr1hg6dCjq1KmD1NRUHDlyBM7OzlIytazj3K9fP3Tt2hXz589HSkoKWrZsiWPHjuHgwYPw8vKSZt+WxduOIRERUY0iEhERERHVUEFBQSIA8cKFCyXuk5eXJ3p7e4u1a9cWdXR0RDc3N/HmzZti48aNxdGjR5fa1smTJ0UA4smTJ+XWHzp0SOzUqZOora0tGhgYiO3btxd/+uknaXt6ero4fPhw0cjISAQgNm7cWBRFUbx165YIQAwKCpJr78SJE6Kzs7PUXr9+/cS4uDi5fRYtWiQCEB8+fFjsONy6devNAyaKYlZWlujj4yPa2tqKmpqaoq6urvjBBx+IP/74o9x+2dnZ4ldffSW2bNlS1NfXF3V1dcWWLVuK3333ndx+cXFxYvfu3UU9PT2xdu3a4vjx48XY2Nhiz/Hnn3+W+m3RooV46NAh0cPDQ7S1tS0S5/fffy+2adNG1NbWFvX19UUHBwdx9uzZ4l9//fXG8xs9erSoq6srJicniz179hR1dHTEevXqiYsWLRLz8vKKPWbSpEkiAHHXrl2ljl9hubm54tatW8UuXbqIhoaGorq6uti4cWNxzJgx4pUrV6T9njx5Io4ZM0asXbu2qKenJ7q5uYkJCQlFrkFRFMUtW7aIlpaWoqqqapHr7uTJk6Kbm5toaGgoamlpiU2bNhU9PT3FixcvyrVR1nF+8eKFOH36dLF+/fqiurq6aGVlJa5evVqUyWRy+wEQJ0+e/MaxeNsxJCIiqikEUaxCTxAgIiIiIiIqxMnJCXXq1ClSR7YyTZ8+HYGBgbh//z50dHSUFkdFquhxfh/GkIiI6E1YE5aIiIiIiJQuJycHubm5cusiIiIQGxsLV1dX5QSF/Adk/fjjj/Dw8KgRyUNljHNNG0MiIqK3wZqwRERERESkdPfu3UP37t3x6aefon79+khISMB///tfmJqaYuLEiZUez4MHD3DixAn88ssvePToEb788stKj6EiVOY419QxJCIiehtMwhIRERERkdIZGxujTZs22Lp1Kx4+fAhdXV306dMHK1asKPKAqsoQFxeHESNGoG7duggICICTk1Olx1ARKnOca+oYEhERvQ3WhCUiIiIiIiIiIiJ6gxcvXmDBggXYv38/Hjx4gFatWsHf3x/t2rUr0/GsCUtERERERERERET0Bp999hmOHz+OHTt24Nq1a+jZsye6d++Oe/fulel4zoQlIiIiIiIiIiKi90p2djays7Pl1mlqakJTU7PIvpmZmdDX18fBgwfRp08faX2bNm3Qq1cvLF26tNT+WBOWiN4oODgYXl5eePr0aZmPEQQB+/fvx4ABAyosrqoqIiICXbt2xZMnT2BkZFSJPV+qxL5I4Z4mAkY2jKEqqa7jURlxv6mP6jpuRERERFVGG2UHUKF8harzb0Vx0TD4+vrKrVu0aBF8fHyK7Jubm4u8vDxoaWnJrdfW1saZM2fK1B+TsERKdO7cOXTu3Bnu7u44cuSI3LaUlBQ0adIEV65cKfEhBq6uroiMjMTy5csxZ84cuW19+vTBr7/+WuIXiDJ5enri6dOnOHDgQJmPqYqJXVdXVzg5OWH9+vXSuk6dOiEtLQ2GhoaVFoeXlxfCwsLAGxuIiIiIiIiqP3V1dfj6+sLDw0PZodRoc+fOxYwZM+TWFTcLFgD09fXRsWNHLFmyBHZ2dqhXrx5++uknnDt3Ds2aNStTf6wJS6REgYGBmDp1Kk6dOoW//vrrrdowNzdHcHCw3Lp79+4hPDwcZmZmCojy/ZOTk/PWx2poaMDU1BSCICgwopL5+fkhNDSUCVgiIiIiIqIaIicnB/PmzUNSUpKyQ6nRNDU1YWBgILeUlIQFgB07dkAURTRo0ACampoICAjAsGHDoKJStvQqk7BESpKeno7du3fjiy++QJ8+fYokUsuqb9+++OeffxAVFSWt27ZtG3r27Im6devK7fvkyROMGjUKxsbG0NHRQa9evYp8qQcHB6NRo0bQ0dHBxx9/jEePHhXp8+DBg2jdujW0tLRgaWkJX19f5ObmvlX8QP6M0mnTpmH27NkwMTGBqamp3OxdCwsLAMDHH38MQRCk12WJJSEhAZ07d4aWlhbs7e1x4sQJCIIgzcJNSUmBIAjYvXs3XFxcoKWlhZ07d+LRo0cYNmwYGjRoAB0dHTg4OOCnn36S2vX09ERkZCT8/f0hCAIEQUBKSgoiIiIgCIJc+Ya9e/eiefPm0NTUhIWFBdauXSt3/hYWFli2bBnGjh0LfX19NGrUCN9//32Zxi4kJARaWlpQU1OR4iAiIiIiIqLqb8WKFcoOQeFUqtBSXk2bNkVkZCTS09Nx584dREdHIycnB5aWlmU+dyJSgj179sDW1hY2Njb49NNP8cMPP7zVbEYNDQ2MGDECQUFB0rrg4GCMHTu2yL6enp64ePEiDh06hHPnzkEURfTu3Vua+Xn+/HmMGzcOU6ZMQUxMDLp27VqkuPTp06cxatQofPnll4iLi8PmzZsRHBwMPz+/csde2LZt26Crq4vz589j1apVWLx4MY4fPw4AuHDhAgAgKCgIaWlp0uvSYsnLy8OAAQOgo6OD8+fP4/vvv8f8+fOL7X/OnDn48ssvER8fDzc3N2RlZaFNmzY4cuQIrl+/js8//xwjR45EdHQ0AMDf3x8dO3bE+PHjkZaWhrS0NJibmxdp99KlSxg8eDCGDh2Ka9euwcfHBwsWLCiSdF+7di3atm2LK1euYNKkSfjiiy+QmJj4xjHLyMhAZmYmsrKykJsrgyiKnBFbzTBnTkREREREAKCiogItLQ2oqKhIS0JCgrLDomLo6urCzMwMT548wdGjR9G/f/8yHcckLJGSBAYG4tNPPwUAuLu749mzZ4iMjHyrtsaOHYs9e/YgIyMDp06dwrNnz9C3b1+5fZKSknDo0CFs3boVXbp0QcuWLbFz507cu3dPmhXq7+8Pd3d3zJ49G9bW1pg2bRrc3Nzk2vH19cWcOXMwevRoWFpaokePHliyZAk2b978VrEXcHR0xKJFi2BlZYVRo0ahbdu2CA8PBwDUqVMHAGBkZARTU1PpdWmxHD9+HMnJydi+fTtatmyJzp07l5gs9vLywsCBA9GkSROYmZmhQYMGmDVrFpycnGBpaYmpU6fC3d0de/bsAQAYGhpCQ0MDOjo6MDU1hampKVRVVYu0u27dOnz00UdYsGABrK2t4enpiSlTpmD16tVy+/Xu3RuTJk1Cs2bN4O3tjdq1a+PkyZPFxpqdnY3nz5/jjz/+eIuRpqqEM5eJiIiIiCifCEEQpMk1oigiIyND2UFRIUePHkVYWBhu3bqF48ePo2vXrrC1tcWYMWPKdDyTsERKkJiYiOjoaAwbNgwAoKamhiFDhiAwMPCt2mvZsiWsrKzwyy+/4IcffsDIkSOhpib/3L34+HioqamhQ4cO0rpatWrBxsYG8fHx0j6FtwNAx44d5V7HxsZi8eLF0NPTk5aC2aAvX758q/iB/CRsYWZmZnjw4MEbjyktlsTERJibm8PU1FQ6pn379sW21bZtW7nXeXl5WLJkCRwcHGBiYgI9PT0cPXoUqamp5Tqv+Ph4ODs7y61zdnZGUlIS8vLypHWFz18QBJiampZ4/suXL4ehoSG6dOlSrliIiIiIiIiIlEnZJQjepRzBs2fPMHnyZNja2mLUqFHo3Lkzjh49CnV19TIdr1b6LkSkaIGBgcjNzUX9+vWldaIoQlNTExs3boShoWG52xw7diy+/fZbxMXFSbfMV4T09HT4+vpi4MCBRbZpaWm9dbuvf2kJggCZTFZpsejq6sq9Xr16Nfz9/bF+/Xo4ODhAV1cXXl5eePXqVbnaLavynH/BExxfvnwJFxeXComHKgfLRxARERERUb78WbCF75Z7/fdUUq7Bgwdj8ODBb308k7BElSw3Nxfbt2/H2rVr0bNnT7ltAwYMwE8//YSJEyeWu93hw4dj1qxZaNmyJezt7Ytst7OzQ25uLs6fP49OnToBAB49eoTExERpfzs7O5w/f17uuN9//13udevWrZGYmIhmzZqVO8Z3oa6uLjdztCyx2NjY4M6dO/j7779Rr149AP/Wly1NVFQU+vfvL5WMkMlkuHHjhtzYamhoFInpdXZ2dnIPTSto29rautjyBWWhqakpPcVRW1sboigiN/cV8vLyE3pM7FUffKuIiIiIiAjI/50zK0t+0o+tra2SoqGKwCQsUSU7fPgwnjx5gnHjxhWZ8erh4YHAwMC3SsIaGxsjLS2txGnwVlZW6N+/P8aPH4/NmzdDX18fc+bMQYMGDaQi0tOmTYOzszPWrFmD/v37S/VOClu4cCH69u2LRo0a4ZNPPoGKigpiY2Nx/fr1Ig/xUiQLCwuEh4fD2dkZmpqaMDY2LjWWHj16oGnTphg9ejRWrVqFFy9e4OuvvwZQei3OgvIOZ8+ehbGxMdatW4e///5bLglrYWGB8+fPIyUlBXp6ejAxMSnSzsyZM9GuXTssWbIEQ4YMwblz57Bx40Z89913ChmXQYMGYfv27Qppi4iIiIiIiKoOb29vZYegcO9zXdT3+dyJlCIwMBDdu3cvtuSAh4cHLl68iKtXr75V20ZGRm+8XSEoKAht2rRB37590bFjR4iiiF9//VVK3H7wwQfYsmUL/P390bJlSxw7dkxKWhZwc3PD4cOHcezYMbRr1w4ffPABvvnmGzRu3PitYi6rtWvX4vjx4zA3N0erVq3KFIuqqioOHDiA9PR0tGvXDp999hnmz58PoPRyBV9//TVat24NNzc3uLq6wtTUFAMGDJDbZ9asWVBVVYW9vT3q1KlTbL3Y1q1bY8+ePfj555/RokULLFy4EIsXL4anp+e7DwqA+fPnw93dnQ94IiIiIiIiqiHU1dXh5+cHa2trZYdCCiSIvG+ViN4jUVFR6Ny5M27evImmTZsqOxwFuqTsAOhdPE0EjGwYQ1VSXcejMuJ+Ux/VddyIiIiIqow2yg6gQq0Uqs6/Fb3FxErtj+UIiKhG279/P/T09GBlZYWbN2/iyy+/hLOzc41KwHp5eSEsLIy1YImIiIiIiGoAdXV1+Pr6wsPDQ9mhkAKxHAER1WgvXrzA5MmTYWtrC09PT7Rr1w4HDx5UdlgK4+fnh9DQUCZgiYiIiIiIaoicnBzMmzcPSUlJyg6FFIjlCIiIqjEnJyeIoojc3FfIy8v/OufXevUkCADfOqrJNDTU8epVzhv3EYT8ByfKZG//YSiokc3vQqpompoaePUqh9fa/1NRebfPLhFVL4Ig8Pvv/1Xkv+M7d+6MwMDAimlcSVZXoXIEX7EcARERlUVGRgYyMzOVHQYpCP8NS9WRigogkxVdr6urhYyMLLl1pSVg8717Eoe/EJKiqKqqIC9PVuIv19nZryo9pqr8BzsmYImqp7f9A4qyf95Wpe9DRcahoiIA+PehywkJCYprnJSO5QiIiKqplJQUZYdARFQsDQ31tzpO2b/QERX276xqJQdSSEFMRESKUl2/V6pr3KURxfx/DxUsGRkZyg6JFIgzYYmIiIiIiIiIiKjC1cz0edkwCUtEVE1ZWFgoOwQiomKVrfRAUawvR1VJwbVYtW55rSKBEFGNUV2/V6pr3KXJn+D7b5pSV1dXabGQ4rEcARFRNaWrqwttbW1oaWlBTU0FgiDU2Nty3gd866g6Kq4eLIAi9WCBspYoEP+/Ftrb43chKUpeXv4FXtLv+VpaGpV+rVXlnMO7fnaJSDnetp6zsn/WVqXvQ0UOhUwmQiaTSYutra3iGielYxKWiKgaGzRoELKyspCbK5PqBlH1xLeOarqyzI4VxXd/uA+/C6myZGW94rVWCB/MRfR+4fffvypyKLy9vSuucSVRqUJLZWMSloioGps/fz7c3d2V/pdoIiIiIiIiUgx1dXX4+fnB2tpa2aGQAgki/3xBRFQDXFJ2AMrzNBEwslHe8e+qcP9PE/P/+7bxKPNclD2Ob/Km2N5lzCv7nKvCGBfEUNJ/S9q/8Gug6L7F7fem16X1U5Zj3oUy3/uqcB28ydvG9zbHVdZYFFy3BSrzWitJVbkOKjqOqnKe74vSvtPL246i4/p/4q3DEIytSo+1PHFURDvlGc+qcK2XJd4q+G9N8dZhCE36KrzdCjuuTNpUULtVwzqh6nyvzxATS99JgZiEJaIyc3V1hZOTE9avX6/sUN5KdY//zd7jJCwRlU9V+EWPiIiIiEpQs5Ow66tQEtarkpOwapXaG9F74ty5c+jcuTPc3d1x5MgRZYdTbhEREejatSuePHkCIyMjaf2+ffugrl6WB6u8u7CwMMydOxcJCQkwMTFB//798d1335V6nKenJ7Zt21ZkfVJSUqXGX5m8vLwQFhbGukxEREREREQ1gLq6Onx9feHh4aHsUEiBWBOWqAIEBgZi6tSpOHXqFP766y9lh6MwJiYm0NfXr/B+srKyMHDgQDg6OuLatWs4cuQInJycyny8u7s70tLS5JYmTZpUWvyVyc/PD6GhoUzAEhERERER1RA5OTmYN28ekpKSlB2Kwin7YVx8MBdRDZKeno7du3fjiy++QJ8+fRAcHFxkn//9739o164dtLS0ULt2bXz88cfStuzsbHh7e8Pc3Byamppo1qwZAgMDpe2RkZFo3749NDU1YWZmhjlz5iA3N1fabmFhUeR2eycnJ/j4+EivBUHA1q1b8fHHH0NHRwdWVlY4dOgQACAlJQVdu3YFABgbG0MQBHh6egLIv53fy8tLrq9ly5Zh7Nix0NfXR6NGjfD999/L9X327Fk4OTlBS0sLbdu2xYEDByAIAmJiYt44jqqqqhgxYgSaNWsGJycnfP7552/cvzBNTU2YmprKLaqqqm8Vv7e3N6ytraGjowNLS0ssWLAAOTn/PuHbx8cHTk5O2LFjBywsLGBoaIihQ4fixYsX0j4ymQyrVq1Cs2bNoKmpiUaNGsHPz0/afufOHQwePBhGRkbSrN+UlJQynWtISAi0tLSgpqYCQRD4gC4iIiIiIqIaYsWKFcoOgRSISVgiBduzZw9sbW1hY2ODTz/9FD/88IPcLMUjR47g448/Ru/evXHlyhWEh4ejffv20vZRo0bhp59+QkBAAOLj47F582bo6ekBAO7du4fevXujXbt2iI2NxaZNmxAYGIilS5eWO05fX18MHjwYV69eRe/evTFixAg8fvwY5ubm2Lt3LwAgMTERaWlp8Pf3L7GdtWvXom3btrhy5QomTZqEL774AomJ+XVVnj9/jn79+sHBwQGXL1/GkiVL4O3tXWpsWlpacHNzw+zZs/H48eNyn1t5vCl+ANDX10dwcDDi4uLg7++PLVu24JtvvpFrIzk5GQcOHMDhw4dx+PBhREZGyv2wnDt3LlasWIEFCxYgLi4Ou3btQr169QDk/4XTzc0N+vr6OH36NKKioqCnpwd3d3e8evXqjbFnZGQgMzMTWVlZyM2VQRRFzoglIiIiIiKqplRUBKioqEhLQkKCskMiBWJNWCIFCwwMxKeffgog/7b4Z8+eITIyEq6urgDybx8fOnQofH19pWNatmwJALhx4wb27NmD48ePo3v37gAAS0tLab/vvvsO5ubm2LhxIwRBgK2tLf766y94e3tj4cKFUFEp+99VPD09MWzYMADAsmXLEBAQgOjoaLi7u8PExAQAULduXbmasMXp3bs3Jk2aBCB/1ug333yDkydPwsbGBrt27YIgCNiyZQu0tLRgb2+Pe/fuYfz48W9s09fXF1euXMHQoUPh4uKCo0ePon79+gCAqVOn4tatWzh8+HCJxx8+fFhKXANAr169EBISUu74AeDrr7+W9rWwsMCsWbPw888/Y/bs2dJ6mUyG4OBgqdTByJEjER4eDj8/P7x48QL+/v7YuHEjRo8eDQBo2rQpOnfuDADYvXs3ZDIZtm7dKs1iDQoKgpGRESIiItCzZ88iMWdnZyM7O5s/kImIiIiIiGqQ/Dk1/06sycjIUFosFeV9ng3KJCyRAiUmJiI6Ohr79+8HAKipqWHIkCEIDAyUkrAxMTElJiFjYmKgqqoKFxeXYrfHx8ejY8eOcrecOzs7Iz09HXfv3kWjRo3KHKujo6P0/7q6ujAwMMCDBw/KfHxx7QiCAFNTU6mdxMREODo6QktLS9qn8Kzf4jx58gTLly/Hvn370Lt3b6iqqsLZ2RnHjh2DlZUVrl27hl69er2xja5du2LTpk1y5/c28QP5SdKAgAAkJycjPT0dubm5MDAwkGvDwsJCrtasmZmZ1EZ8fDyys7Px0UcfFdt/bGwsbt68WaRWbVZWFpKTk4s9Zvny5fD19YWGhgYsLCxKPDciIiIiIiIiqhqYhCVSoMDAQOTm5kqzNgFAFEVoampi48aNMDQ0hLa2donHv2lbWamoqBS5Jb1wDdMC6urqcq8FQYBMJit3f4pqp0BiYiKys7PRqlUrAMDixYvx/PlzdO7cGevXr8fvv/+OnTt3vrENXV1dNGvWrEz9vSn+c+fOYcSIEfD19YWbmxsMDQ3x888/Y+3atWVuo7T3ND09HW3atCn2nOrUqVPsMXPnzsWMGTPw8uXLEhP2REREREREVL3kz7f6d9LVmyYUUfXzPs8CJlKo3NxcbN++HWvXrkVMTIy0xMbGon79+vjpp58A5M+8DA8PL7YNBwcHyGQyREZGFrvdzs4O586dk0uyRkVFQV9fHw0bNgSQn7hLS0uTtj9//hy3bt0q17loaGgAAPLy8sp13OtsbGxw7do1ZGdnS+suXLjwxmMaNGgAADh16pS07ptvvkHfvn0xfPhwTJgwQdqnop09exaNGzfG/Pnz0bZtW1hZWeH27dvlasPKygra2tolvuetW7dGUlIS6tati2bNmskthoaGxR6jqakJAwMDmJqaQltbmw/mIiIiIiIiqgFkMhEymUxabG1tlR2SwqlUoaWyMQlLpCCHDx/GkydPMG7cOLRo0UJu8fDwQGBgIABg0aJF+Omnn7Bo0SLEx8fj2rVrWLlyJYD829pHjx6NsWPH4sCBA7h16xYiIiKwZ88eAMCkSZNw584dTJ06FQkJCTh48CAWLVqEGTNmSPVgu3Xrhh07duD06dO4du0aRo8eDVVV1XKdS+PGjSEIAg4fPoyHDx8iPT39rcZk+PDhkMlk+PzzzxEfH4+jR49izZo1AFBistDc3BxDhw7F5MmTsX37diQnJyM8PBzJycnQ1dXFoUOH3qpswtuwsrJCamoqfv75ZyQnJyMgIEAqNVFWWlpa8Pb2xuzZs6Xz+f3336XrYcSIEahduzb69++P06dPS+/5tGnTcPfu3VLbHzRoEB/MRUREREREVAOV5cHWVH0wCUukIIGBgejevXuxsxc9PDxw8eJFXL16Fa6urggJCcGhQ4fg5OSEbt26ITo6Wtp306ZN+OSTTzBp0iTY2tpi/PjxUjHuBg0a4Ndff0V0dDRatmyJiRMnYty4cXIPj5o7dy5cXFzQt29f9OnTBwMGDEDTpk3LdS4NGjSAr68v5syZg3r16mHKlClvNSYGBgb43//+h5iYGDg5OWH+/PlYuHAhAMjViX3dtm3bMGPGDPj5+aF58+aYMGECXFxccPv2bRgaGuI///kPMjMz3yqm8vjPf/6D6dOnY8qUKXBycsLZs2exYMGCcrezYMECzJw5EwsXLoSdnR2GDBkiJZJ1dHRw6tQpNGrUCAMHDoSdnR3GjRuHrKysIrVnizN//ny4u7tzBiwREREREVENoa6uDj8/P1hbWys7FFIgQeS0KSKqRDt37sSYMWPw7NkzhdTApQKXlB1A9fA0ETCyqbg2ytO+ImJ5n3H86H1U6LoXI9ZBcJ2h3Hio6ivvd2VFfLcW06Z46zAEYyt+j1d31e1ncXWLl4p6mpj/30LvY7X4eVjua69NhYVSFfxXqDqfw4liYqX2xwdzEVGF2r59OywtLdGgQQPExsbC29sbgwcPZgJWgby8vBAWFsZSBERE753hyg6AiIioCqh5Pw/V1dXh6+sLDw8PZYdCCsQkLBFVqPv372PhwoW4f/8+zMzMMGjQIPj5+Sk7rBrDz88PoaGhyg6DiIiIiIioUgmCUGMnouTk5GDevHlwdHSElZWVssNRqPe5LirLERARVWNOTk4QRRG5ua+Ql5f/dc6v9aIEAeCwEBERVU1qaqrIzc1TdhhEVM2oq6siJ6dmf3d07txZeqhzTfF9FSpH8DnLERARUVlkZGRUygPKaoKa/Ffy9w0T6kRE1Zuqqgry8mRy65iAJaK3URMTsCoqAoB/H7qckJCgvGBI4ZiEJSKqplJSUpQdQrXBBGzNwYQ6EVH1JghC6TsREb2n8v+Z+++/dTMyMpQWS0V5n8sRvM/nTkRERERERERERFThOBOWiKiasrCwUHYI1QZnT9YcfB+JiKo3lh4gIipZ/s0C/94xoKurq7RYSPGYhCUiqqZ0dXWhra3NB3OVAYek5uB7SURU8/DBXET0Nmrig7lkMhGFyxHY2toqL5gK8j7fkv8+nzsRUbU3aNAgZGVlITdXBlEUmYAtAceFiIio6mIClojeRk1LwBbH29tb2SGQAjEJS0RUjc2fPx/u7u58yAUREREREVENoa6uDj8/P1hbWys7FFIgQeT0ICIihfD09MTTp09x4MABJfR+SQl9VkNPEwEjm4prozztKyKW9xnHj95Hha57MWIdBNcZyo2Hqr7yfldWxHdrMW2Ktw5DMLbi93h1V91+Fle3eKmop4n5/y30PlaLn4flvvbaVFgoVUGwUHU+h55iYqX2xyQsESnNuXPn0LlzZ7i7u+PIkSOV3n9ERAS6du2KJ0+ewMjIqMzHpaSkoEmTJrhy5QqcnJyk9c+ePYMoiuVqSxG8vLwQFhbGW+6JiIiIiIhqAHV1dfj6+sLDw0PZoSjc+5yEZTkCIlKawMBATJ06FadOncJff/2l7HDemaGhYaUnYP38/BAaGsoELBERERERUQ2Rk5ODefPmISkpSdmhkAIxCUtESpGeno7du3fjiy++QJ8+fRAcHCxti4iIgCAICA8PR9u2baGjo4NOnTohMfHfv1L5+PjAyckJO3bsgIWFBQwNDTF06FC8ePFC2ic7OxvTpk1D3bp1oaWlhc6dO+PChQsA8mezdu3aFQBgbGwMQRDg6ekJAAgLC0Pnzp1hZGSEWrVqoW/fvkhOTpbabdKkCQCgVatWEAQBrq6uAPLLEQwYMKBM/Zf1PEsTEhICLS0tqKmpQBAE1oYlIiIiIiKqIVasWKHsEBROpQotlY1JWCJSij179sDW1hY2Njb49NNP8cMPPxSZzTl//nysXbsWFy9ehJqaGsaOHSu3PTk5GQcOHMDhw4dx+PBhREZGyv2Qmj17Nvbu3Ytt27bh8uXLaNasGdzc3PD48WOYm5tj7969AIDExESkpaXB398fAJCRkYEZM2bg4sWLCA8Ph4qKCj7++GPIZDIAQHR0NADgxIkTSEtLw759+4o9xzf1X57zLElGRgYyMzORlZWF3FwZRFHkjFgiIiIiIqJqSkVFgIqKirQkJCQoOyRSICZhiUgpAgMD8emnnwIA3N3d8ezZM0RGRsrt4+fnBxcXF9jb22POnDk4e/YssrKypO0ymQzBwcFo0aIFunTpgpEjRyI8PBxAfoJy06ZNWL16NXr16gV7e3ts2bIF2traCAwMhKqqKkxMTAAAdevWhampKQwNDQEAHh4eGDhwIJo1awYnJyf88MMPuHbtGuLi4gAAderUAQDUqlULpqamUjuFldZ/ec7zddnZ2Xj+/Dn++OOPco05ERERERERVV2iCGlyjSiKyMjIUHZICidUoaWyMQlLRJUuMTER0dHRGDZsGABATU0NQ4YMKZKcdHR0lP7fzMwMAPDgwQNpnYWFBfT19eX2KdienJyMnJwcODs7S9vV1dXRvn17xMfHvzG+pKQkDBs2DJaWljAwMICFhQUAIDU1tcznWJ7+SzvP1y1fvhyGhobo0qVLmeMhIiIiIiIiIuVhEpaIKl1gYCByc3NRv359qKmpQU1NDZs2bcLevXvx7NkzaT91dXXp/wtqnRaUBHh9e8E+hbe/rX79+uHx48fYsmULzp8/j/PnzwMAXr169c5tF6e083zd3Llz8ezZM9y+fbtC4iEiIiIiIqLKJwiQnvUhCAJ0dXWVHRIpEJOwRFSpcnNzsX37dqxduxYxMTHSEhsbi/r16+Onn35SSD9NmzaFhoYGoqKipHU5OTm4cOEC7O3tAQAaGhoAgLy8PGmfR48eITExEV9//TU++ugj2NnZ4cmTJ3JtF3fc2/T/tjQ1NWFgYABTU1Noa2vzwVxEREREREQ1gEwmQiaTSYutra2yQ1I4ZT+MS5kP5lJTQp9E9B47fPgwnjx5gnHjxkk1WAt4eHggMDAQq1evfud+dHV18cUXX+Crr76CiYkJGjVqhFWrVuHly5cYN24cAKBx48YQBAGHDx9G7969oa2tDWNjY9SqVQvff/89zMzMkJqaijlz5si1XbduXWhrayMsLAwNGzaElpZWkXMpS/+KMGjQIGzfvl1h7REREREREVHV4O3trewQSIE4E5aIKlVgYCC6d+9eJGkJ5CdhL168iKtXryqkrxUrVsDDwwMjR45E69atcfPmTRw9ehTGxsYAgAYNGsDX1xdz5sxBvXr1MGXKFKioqODnn3/GpUuX0KJFC0yfPr1IUlhNTQ0BAQHYvHkz6tevj/79+79V/4owf/58uLu7cwYsERERERFRDaGurg4/Pz9YW1srOxRSIEEURVHZQRAR0bu6pOwAiIiIiIioNE8TASMbZUdBVVobZQdQoX4Sqs71P0xMrNT+WI6AiKia8/LyQlhYGPg3NSIiIiIioupPXV0dvr6+8PDwUHYopEAsR0BEVI35+fkhNDSUCVgiIiIiIqIaIicnB/PmzUNSUpKyQyEFYhKWiKgaCwkJgZaWFtTUVCAIAmvDEhERERER1RArVqxQdggKp1KFlsrGcgRERNVURkYGMjMzlR0GERERERERKYCKigDg34k1CQkJyguGFI5JWCKiaiolJUXZIRAREREREZGC5FeZ+7fUXEZGhtJiIcVjEpaIiIiIiIiIiIgq3PtcF5VJWCKiasrCwkLZIRAREREREZGC5D/i499yBLq6ukqLhRSPSVgiompKV1cX2traEEURubmvkJeXf9uKKIqlHElERERERERVjUwmonA5AltbW+UFU0He55mw7/O5ExFVe4MGDUJWVhZyc2UQRZEJWCIiIiIiohrC29tb2SGQAjEJS0RUjc2fPx/u7u4QBKH0nYmIiIiIiKjKU1dXh5+fH6ytrZUdCimQIHLaFBFRDXBJ2QHQ00TAyEbZURARERHR+4T/Bq2B2ig7gAq1X6g61+vHYmKl9seZsEQ1QEREBARBwNOnT5UditK5urrCy8tLem1hYYH169dLrwVBwIEDByo9LnoP8B+/RET0uqeV+8sdEb2H+G9QomqDD+YiqmCenp7Ytm2b9NrExATt2rXDqlWr4OjoqJA+OnXqhLS0NBgaGiqkPUULDg6Gl5dXuZLErq6ucHJykkugKkJaWhqMjY0V2qayeXl5ISwsjPVgiYiIiIiIagB1dXX4+vrCw8ND2aGQAnEmLFElcHd3R1paGtLS0hAeHg41NTX07dtXYe1raGjA1NSUdUHLwNTUFJqamsoOQ2H8/PwQGhrKBCwREREREVENkZOTg3nz5iEpKUnZoSicShVaKhuTsESVQFNTE6ampjA1NYWTkxPmzJmDO3fu4OHDhwCKLycQExMDQRCQkpICALh9+zb69esHY2Nj6Orqonnz5vj111+LPT44OBhGRkY4evQo7OzsoKenJyWCC9u6dSvs7OygpaUFW1tbfPfdd9K2V69eYcqUKTAzM4OWlhYaN26M5cuXAwBEUYSPjw8aNWoETU1N1K9fH9OmTSvzePj4+MDJyQk7duyAhYUFDA0NMXToULx48QJA/uzhyMhI+Pv7QxAEuXG4fv06evXqBT09PdSrVw8jR47EP//8U+a+Xy9HcPbsWTg5OUFLSwtt27bFgQMHIAgCYmJipH1K69PV1RXTpk3D7NmzYWJiAlNTU/j4+Mj1+/TpU0yYMAH16tWDlpYWWrRogcOHD0vbz5w5gy5dukBbWxvm5uaYNm0aMjIySj2fkJAQaGlpQU1NRRorIiIiIiIiqv5WrFih7BBIgZiEJapk6enp+PHHH9GsWTPUqlWrzMdNnjwZ2dnZOHXqFK5du4aVK1dCT0+vxP1fvnyJNWvWYMeOHTh16hRSU1Mxa9YsafvOnTuxcOFC+Pn5IT4+HsuWLcOCBQuk0gkBAQE4dOgQ9uzZg8TEROzcuRMWFhYAgL179+Kbb77B5s2bkZSUhAMHDsDBwaFc45CcnIwDBw7g8OHDOHz4MCIjI6UfMP7+/ujYsSPGjx8vzSA2NzfH06dP0a1bN7Rq1QoXL15EWFgY/v77bwwePLhcfRd4/vw5+vXrBwcHB1y+fBlLliyBt7e33D5l7XPbtm3Q1dXF+fPnsWrVKixevBjHjx8HAMhkMvTq1QtRUVH48ccfERcXhxUrVkBVVVUaC3d3d3h4eODq1avYvXs3zpw5gylTprwx/oyMDGRmZiIrKwu5uTKIosgZsURERERERNWUiooAFRUVaUlISFB2SKRArAlLVAkOHz4sJUwzMjJgZmaGw4cPQ0Wl7H8HSU1NhYeHh5TstLS0fOP+OTk5+O9//4umTZsCAKZMmYLFixdL2xctWoS1a9di4MCBAIAmTZogLi4OmzdvxujRo5GamgorKyt07twZgiCgcePGcrGYmpqie/fuUFdXR6NGjdC+ffsynwuQn5gMDg6Gvr4+AGDkyJEIDw+Hn58fDA0NoaGhAR0dHZiamkrHbNy4Ea1atcKyZcukdT/88APMzc1x48YNWFtblyuGXbt2QRAEbNmyBVpaWrC3t8e9e/cwfvz4cvfp6OiIRYsWAQCsrKywceNGhIeHo0ePHjhx4gSio6MRHx8v7V/4/Vu+fDlGjBghPVDMysoKAQEBcHFxwaZNm6ClpSUXd3Z2NrKzs/kDmYiIiIiIqAbJn1Pz78SastwdWd28z7NB3+dzJ6o0Xbt2RUxMDGJiYhAdHQ03Nzf06tULt2/fLnMb06ZNw9KlS+Hs7IxFixbh6tWrb9xfR0dHSsACgJmZGR48eAAg/4s8OTkZ48aNg56enrQsXboUycnJAPJLAsTExMDGxgbTpk3DsWPHpLYGDRqEzMxMWFpaYvz48di/fz9yc3PLMySwsLCQErCvx1eS2NhYnDx5Ui5mW1tbAJDiLo/ExEQ4OjrKJTlfTyaXtc/XH7JW+HxiYmLQsGHDEpPEsbGxCA4OluvDzc0NMpkMt27dKrL/8uXLYWhoiC5dupT7nImIiIiIiIio8nEmLFEl0NXVRbNmzaTXW7duhaGhIbZs2YKlS5dKM2IL30qek5Mj18Znn30GNzc3HDlyBMeOHcPy5cuxdu1aTJ06tdg+1dXV5V4LgiC1n56eDgDYsmULOnToILdfwS3yrVu3xq1btxAaGooTJ05g8ODB6N69O3755ReYm5sjMTERJ06cwPHjxzFp0iSsXr0akZGRRfotSXHxyWSyNx6Tnp6Ofv36YeXKlUW2mZmZlanf8iprn286H21t7VL7mDBhQrF1dRs1alRk3dy5czFjxgy8fPkSLi4uZToPIiIiIiIiqtryH/Hx73M+dHV1lRZLRXmfZ4MyCUukBIKQX+clMzMTAFCnTh0AQFpaGoyNjQFA7sFQBczNzTFx4kRMnDgRc+fOxZYtW0pMwr5JvXr1UL9+ffz5558YMWJEifsZGBhgyJAhGDJkCD755BO4u7vj8ePHMDExgba2Nvr164d+/fph8uTJsLW1xbVr19C6detyx1McDQ0N5OXlya1r3bo19u7dCwsLC6ipvfvXl42NDX788UdkZ2dDU1MTAHDhwgWF9+no6Ii7d++WWDKhdevWiIuLk0vUv4mmpiY0NTVhYGAAbW1tiKKI3NxXyMvLT7KzLiwREREREVH1I5OJKFyOoOAuTFK+vLw8+Pj44Mcff8T9+/dRv359eHp64uuvvy7zA7Lf5wQ0UaXJzs7G/fv3cf/+fcTHx2Pq1KnSDEsAaNasGczNzeHj44OkpCQcOXIEa9eulWvDy8sLR48exa1bt3D58mWcPHkSdnZ2bx2Tr68vli9fjoCAANy4cQPXrl1DUFAQ1q1bBwBYt24dfvrpJyQkJODGjRsICQmBqakpjIyMEBwcjMDAQFy/fh1//vknfvzxR2hra8vVjX1XFhYWOH/+PFJSUvDPP/9AJpNh8uTJePz4MYYNG4YLFy4gOTkZR48exZgxY4okbMti+PDhkMlk+PzzzxEfH4+jR49izZo1ACB9iSqiTxcXF3z44Yfw8PDA8ePHpRnGYWFhAABvb2+cPXsWU6ZMQUxMDJKSknDw4MFSH8wF5JeG4IO5iIiIiIiIap7XHxxNyrNy5Ups2rQJGzduRHx8PFauXIlVq1Zhw4YNZW6DSViiShAWFgYzMzOYmZmhQ4cOuHDhAkJCQuDq6gog/1b2goSno6MjVq5ciaVLl8q1kZeXh8mTJ8POzg7u7u6wtrbGd99999YxffbZZ9i6dSuCgoLg4OAAFxcXBAcHo0mTJgAAfX19rFq1Cm3btkW7du2QkpKCX3/9FSoqKjAyMsKWLVvg7OwMR0dHnDhxAv/73/9Qq1att47ndbNmzYKqqirs7e1Rp04dpKamon79+oiKikJeXh569uwJBwcHeHl5wcjIqFwPOStgYGCA//3vf4iJiYGTkxPmz5+PhQsXAoBUJ1ZRfe7duxft2rXDsGHDYG9vj9mzZ0tJXEdHR0RGRuLGjRvo0qULWrVqhYULF6J+/fqltjt//ny4u7uX+S9vREREREREVLWpq6vDz8+v3A+frg5UqtCSnZ2N58+fyy3Z2dnFxn327Fn0798fffr0gYWFBT755BP07NkT0dHRZT53QeS0KSIiyc6dOzFmzBg8e/as1FquVcslZQdARIr0NBEwslF2FERERERU6dooO4AKFSpUnX/jnl80DL6+vnLrFi1aBB8fnyL7Llu2DN9//z2OHTsGa2trxMbGomfPnli3bt0byzwWxpqwRPRe2759OywtLdGgQQPExsbC29sbgwcPrlYJWC8vL4SFhbEUARERERERUQ2grq4OX19feHh4KDuUGq3godeFFTwv5nVz5szB8+fPYWtrC1VVVeTl5cHPz6/MCViASVgies/dv38fCxcuxP3792FmZoZBgwbBz89P2WGVmZ+fH0JDQ5UdBhERERERESlITk4O5s2bB0dHR1hZWSk7HIWqSoX0Ch56XRZ79uzBzp07sWvXLjRv3hwxMTHw8vJC/fr1MXr06DK1wXIERETVmJOTE0RRRG7uK+Tl5X+d82udiIiIiIio+uvcuTMCAwOVHYZChVWhcgTuYmKZ9zU3N8ecOXMwefJkad3SpUvx448/IiEhoUxtcCYsEVE1lZGRgczMTGWHQURERERERAqgoiKg8FzRsib3qOK9fPmyyMO5VVVVIZPJytwGk7BERNVUSkqKskMgIiIiIiIiBcm/qfHfOxszMjKUFktFUSl9lyqpX79+8PPzQ6NGjdC8eXNcuXIF69atw9ixY8vcBpOwRERERERERERERCXYsGEDFixYgEmTJuHBgweoX78+JkyYgIULF5a5DdaEJSKqpjIyMtC6dWtlh0FEREREREQK8Ho5AhMTE0RFRSkvoApwrArVhO1ZjpqwisCZsERE1ZSuri60tbX5YC4iIiIiIqIaQCYTUbgcga2trfKCqSDVtRyBIrzP505EVO0NGjQIWVlZyM2VQRRFJmCJiIiIiIhqCG9vb2WHQArEJCwRUTU2f/58uLu7QxCE0ncmIiIiIiKiKk9dXR1+fn6wtrZWdigKp1KFlsrGmrBEVIQgCNi/fz8GDBhQof1YWFjAy8sLXl5eb3V8REQEunbtiidPnsDIyOidYomKisLEiRORkJCAPn364MCBA+/UXuW7pOwAiEiRniYCRlWnXhYRERERVZY2yg6gQv1WhWrCdmNNWCKqSPfv34efnx+OHDmCe/fuoW7dunBycoKXlxc++ugjZYcnx8fHB76+vgAAVVVVNGzYEB9//DGWLFkCPT29t2rT1dUVTk5OWL9+vdz6GTNmwMnJCaGhoW/dtrJ4eXkhLCyMpQiIiIiIiIhqAHV1dfj6+sLDw0PZoZACMQlL9B5JSUmBs7MzjIyMsHr1ajg4OCAnJwdHjx7F5MmTkZCQoOwQi2jevDlOnDiB3NxcREVFYezYsXj58iU2b96s0H6Sk5MxceJENGzY8K3bePXqFTQ0NBQYVen8/PwQGhpaqX0SERERERFRxcnJycG8efPg6OgIKysrZYejUO9zJT3WhCV6j0yaNAmCICA6OhoeHh6wtrZG8+bNMWPGDPz+++8lHnft2jV069YN2traqFWrFj7//HOkp6dL211dXYuUFBgwYAA8PT2l1w8ePEC/fv2gra2NJk2aYOfOnWWKWU1NDaampmjYsCGGDBmCESNG4NChQ8Xu++jRIwwbNgwNGjSAjo4OHBwc8NNPP0nbPT09ERkZCX9/fwiCAEEQkJKSAkEQ8OjRI4wdOxaCICA4OBgAEBkZifbt20NTUxNmZmaYM2cOcnNz5c57ypQp8PLyQu3ateHm5oaIiAgIgoCjR4+iVatW0NbWRrdu3fDgwQOEhobCzs4OBgYGGD58OF6+fCm19csvv8DBwUEa4+7duyMjI6PU8QkJCYGWlhbU1FSkcyIiIiIiIqLqb8WKFcoOgRSISVii98Tjx48RFhaGyZMnQ1dXt8j2kmqqZmRkwM3NDcbGxrhw4QJCQkJw4sQJTJkypVz9e3p64s6dOzh58iR++eUXfPfdd3jw4EG5z0NbWxuvXr0qdltWVhbatGmDI0eO4Pr16/j8888xcuRIREdHAwD8/f3RsWNHjB8/HmlpaUhLS4O5uTnS0tJgYGCA9evXIy0tDUOGDMG9e/fQu3dvtGvXDrGxsdi0aRMCAwOxdOlSuT63bdsGDQ0NREVF4b///a+03sfHBxs3bsTZs2dx584dDB48GOvXr8euXbtw5MgRHDt2DBs2bAAApKWlYdiwYRg7dizi4+MRERGBgQMHllpeICMjA5mZmcjKykJurgyiKLIkARERERERUTWloiJARUVFWqri3ar09liOgOg9cfPmTYiiCFtb23Idt2vXLmRlZWH79u1S8nbjxo3o168fVq5ciXr16pXaxo0bNxAaGoro6Gi0a9cOABAYGAg7O7tyxXLp0iXs2rUL3bp1K3Z7gwYNMGvWLOn11KlTcfToUezZswft27eHoaEhNDQ0oKOjA1NTU2k/U1NTCIIAQ0NDaf13330Hc3NzbNy4EYIgwNbWFn/99Re8vb2xcOFCqKjk/w3LysoKq1atktpKS0sDACxduhTOzs4AgHHjxmHu3LlITk6GpaUlAOCTTz7ByZMn4e3tjbS0NOTm5mLgwIFo3LgxAMDBwaHEccjOzkZ2djZ/IBMREREREdUg+XNq/p1YU5a7I6sbFeH9nTjEmbBE74m3nSEZHx+Pli1bys2edXZ2hkwmQ2Ji2Z4kGB8fDzU1NbRp8+9THm1tbUucfVvYtWvXoKenB21tbbRv3x4dO3bExo0bi903Ly8PS5YsgYODA0xMTKCnp4ejR48iNTW1THG+HnPHjh3lbu93dnZGeno67t69K60rfE6FOTo6Sv9fr1496OjoSAnYgnUFM4FbtmyJjz76CA4ODhg0aBC2bNmCJ0+elBjb8uXLYWhoiC5dupT7vIiIiIiIiIio8jEJS/SesLKygiAIFTJ7UkVFpUiSNycnRyFt29jYICYmBvHx8cjMzMShQ4dKnH27evVq+Pv7w9vbGydPnkRMTAzc3NxKLF+gCMWVdgDyn2ZZQBAEudcF62QyGQBAVVUVx48fR2hoKOzt7bFhwwbY2Njg1q1bxbY9d+5cPHv2DLdv31bQWRAREREREZGyCQKkZ30IglDi75tUPTEJS/SeMDExgZubG7799ttib2l4+vRpscfZ2dkhNjZW7pioqCioqKjAxsYGAFCnTh3pNnwgf0bq9evXpde2trbIzc3FpUuXpHWJiYkl9lmYhoYGmjVrBgsLC2hoaLxx36ioKPTv3x+ffvopWrZsCUtLS9y4caNIe3l5eaX2a2dnh3Pnzskll6OioqCvr4+GDRuWenx5CYIAZ2dn+Pr64sqVK9DQ0MD+/fuL3VdTUxMGBgYwNTWFtrY2H8xFRERERERUA8hkImQymbSUt5xgdZCfaK4aS2VjEpboPfLtt98iLy8P7du3x969e5GUlIT4+HgEBASgY8eOxR4zYsQIaGlpYfTo0bh+/TpOnjyJqVOnYuTIkdKM1G7duuHIkSM4cuQIEhIS8MUXX8glWG1sbODu7o4JEybg/PnzuHTpEj777DNoa2sr9PysrKxw/PhxnD17FvHx8ZgwYQL+/vtvuX0sLCxw/vx5pKSk4J9//pFmo75u0qRJuHPnDqZOnYqEhAQcPHgQixYtwowZM6R6sIpy/vx5LFu2DBcvXkRqair27duHhw8flqlm7qBBg/hgLiIiIiIiohrI29tb2SGQAjEJS/QesbS0xOXLl9G1a1fMnDkTLVq0QI8ePRAeHo5NmzYVe4yOjg6OHj2Kx48fo127dvjkk0/w0UcfydVlHTt2LEaPHo1Ro0bBxcUFlpaW6Nq1q1w7QUFBqF+/PlxcXDBw4EB8/vnnqFu3rkLP7+uvv0br1q3h5uYGV1dXmJqaYsCAAXL7zJo1C6qqqrC3t0edOnVKrBfboEED/Prrr4iOjkbLli0xceJEjBs3Dl9//bVCYwYAAwMDnDp1Cr1794a1tTW+/vprrF27Fr169Sr12Pnz58Pd3Z0zYImIiIiIiGoIdXV1+Pn5wdraWtmhKJxQhZbKJoicNkVEVANcKn0XRXv6/w9mM7Kp/L6V5Wli5Z+vMvokIuWoyp/3qhwbVV+8rv4dA44FVZTqdG1Vp1grVPEPf64pTqtVncRyl9wbpe+kQEzCEhHVCEpIwlLJ+A9IIqru+D1W/fA9e3ccQyKqEpiErSyVnYRVq9TeiIhI4by8vBAWFsZ6sERERERERDWAuro6fH194eHhoexQFE4Q3t/fW1kTloioGvPz80NoaCgTsERERERERDVETk4O5s2bh6SkJGWHQgrEJCwRUTUWEhICLS0tqKmpQBAEPqCLiIiIiIiohlixYoWyQyAFYjkCIqJqKiMjA5mZmcoOg4iIiIiIiBRARUUA8O/EmoSEBOUFU0He53lDTMISEVVTKSkpyg6BiIiIiIiIFCS/yty/peYyMjKUFgspHssREBEREREREREREVUgzoQlIqqmLCwslB0CERERERERKUj+rfr/3q+vq6urtFgqCssREBFRtaOrqwttbW2Ioojc3FfIy8u/bUUUxVKOJCIiIiIioqpGJhNRuByBra2t8oIhhWM5AiKiamzQoEHIyspCbq4MoigyAUtERERERFRDeHt7KzsEUiDOhCUiqsbmz5+PBw8e4OjRo0zAEhERERER1QDq6urw8fGBtbW1skNROBXh/f29VRD5Wzu9JwRBwP79+zFgwIAK6yM4OBheXl54+vRphfWhbJ6ennj69CkOHDig7FDe2suXLzFy5EgcP34cL168wJMnT2BkZKTssN7RpaKrniYCRjZyq8SIdRBcZ1ROSDVFMeNYZVTl2IgqEq/9ilHWceX40+tKuiaUda3wGq2SZNMnQuWb//L9UTZFjH91eA+rQ4wlaqPsACrU71rNlB2C5IOsm5XaH5Ow76H79+/Dz88PR44cwb1791C3bl04OTnBy8sLH330kbLDqzD379+HsbExNDU1FdKehYUFvLy84OXlJa3LzMzEixcvULduXYX0UZJbt25h/vz5iIiIwOPHj1G7dm20adMGK1eurPCaMc+ePYMoikpLWkZGRsLX1xcxMTHIyspCgwYN0KlTJ2zZsgUaGhplamPTpk1YtGgRfvvtN9SuXRuZmZmwtLTElStX4OTkVLEnUAG8vLwQFhbGmbBEREREVKVMmTIFU6dOxYULFzB58mQ8e/ZM2SERVQvq6urw9fWFh4eHskNRuPNVKAnboZKTsKwJ+55JSUlBmzZt8Ntvv2H16tW4du0awsLC0LVrV0yePFnZ4VUoU1NThSVgS6KtrV3hCdicnBz06NEDz549w759+5CYmIjdu3fDwcHhnWbgvnr1qkz7GRoaKi0BGxcXB3d3d7Rt2xanTp3CtWvXsGHDBmhoaCAvL6/M7SQnJ8POzg4tWrSAqakpBCU9nrGsY/4mfn5+CA0NZQKWiIiIiKqkGzduYMyYMUzAEpVDTk4O5s2bh6SkJGWHQgrEJOx7ZtKkSRAEAdHR0fDw8IC1tTWaN2+OGTNm4Pfff5f2S01NRf/+/aGnpwcDAwMMHjwYf//9t7Tdx8cHTk5O+OGHH9CoUSPo6elh0qRJyMvLw6pVq2Bqaoq6devCz89Prn9BELB582b07dsXOjo6sLOzw7lz53Dz5k24urpCV1cXnTp1QnJysnSMp6dnkRICXl5ecHV1lV67urpi2rRpmD17NkxMTGBqagofH58ifRe+hf7u3bsYNmwYTExMoKuri7Zt2+L8+fMA8pN0/fv3R7169aCnp4d27drhxIkTcv3dvn0b06dPhyAIUhIvODi4SIJy06ZNaNq0KTQ0NGBjY4MdO3YUiWvr1q34+OOPoaOjAysrKxw6dKj4NxDAH3/8geTkZHz33Xf44IMP0LhxYzg7O2Pp0qX44IMPpP3u3LmDwYMHw8jICCYmJujfvz9SUlKKjKufnx/q168PGxsbzJs3Dx06dCjSZ8uWLbF48WK54wrIZDKsWrUKzZo1g6amJho1aiT3vpcWR0REBNq3bw9dXV0YGRnB2dkZt2/fLvbcjx07BlNTU6xatQotWrRA06ZN4e7uji1btkBbW1vab+/evWjevDk0NTVhYWGBtWvXSttcXV2xdu1anDp1CoIgwNXVFU2aNAEAtGrVSlp3/fp1qKio4OHDhwCAx48fQ0VFBUOHDpXaWrp0KTp37gwAyMvLw7hx49CkSRNoa2vDxsYG/v7+cvEXN+ZlGaM3CQkJgZaWFtTUVOSuRSIiIiKiqiAvLw85OTnKDoOoWlqxYoWyQyAFYhL2PfL48WOEhYVh8uTJ0NXVLbK9IHkok8nQv39/PH78GJGRkTh+/Dj+/PNPDBkyRG7/5ORkhIaGIiwsDD/99BMCAwPRp08f3L17F5GRkVi5ciW+/vprKbFZYMmSJRg1ahRiYmJga2uL4cOHY8KECZg7dy4uXrwIURQxZcqUcp/ftm3boKuri/Pnz2PVqlVYvHgxjh8/Xuy+6enpcHFxwb1793Do0CHExsZi9uzZkMlk0vbevXsjPDwcV65cgbu7O/r164fU1FQAwL59+9CwYUMsXrwYaWlpSEtLK7af/fv348svv8TMmTNx/fp1TJgwAWPGjMHJkyfl9vP19cXgwYNx9epV9O7dGyNGjMDjx4+LbbNOnTpQUVHBL7/8UuLsz5ycHLi5uUFfXx+nT59GVFQU9PT04O7uLjf7Mjw8HImJiTh+/DgOHz6MESNGIDo6Wi4J/scff+Dq1asYPnx4sX3NnTsXK1aswIIFCxAXF4ddu3ahXr16ZYojNzcXAwYMgIuLC65evYpz587h888/LzGRaGpqirS0NJw6darY7QBw6dIlDB48GEOHDsW1a9fg4+ODBQsWIDg4GED+ezd+/Hh07NgRaWlp2LdvH6KjowEAJ06ckNY1b94ctWrVQmRkJADg9OnTcq+B/NIIBX8MkMlkaNiwIUJCQhAXF4eFCxdi3rx52LNnj1x8r495Wd+r4mRkZCAzMxNZWVnIzZVBFEXOiCUiIiKiKqVOnToAUCNvqyZSNBUVASoqKtKSkJCg7JAUThCqzlLZ1Cq/S1KWmzdvQhTFUmuGhoeH49q1a7h16xbMzc0BANu3b0fz5s1x4cIFtGvXDkB+0umHH36Avr4+7O3t0bVrVyQmJuLXX3+FiooKbGxssHLlSpw8eVJuduWYMWMwePBgAIC3tzc6duyIBQsWwM3NDQDw5ZdfYsyYMeU+P0dHRyxatAgAYGVlhY0bNyI8PBw9evQosu+uXbvw8OFDXLhwASYmJgCAZs3+rUvSsmVLtGzZUnq9ZMkS7N+/H4cOHcKUKVNgYmICVVVV6Ovrw9TUtMSY1qxZA09PT0yaNAkApBnHa9asQdeuXaX9PD09MWzYMADAsmXLEBAQgOjoaLi7uxdps0GDBggICMDs2bPh6+uLtm3bomvXrhgxYgQsLS0BALt374ZMJsPWrVulhGZQUBCMjIwQERGBnj17AgB0dXWxdetWuVqqLVu2xK5du7BgwQIAwM6dO9GhQwe58Snw4sUL+Pv7Y+PGjRg9ejQAoGnTptLs0NLiaNu2LZ49e4a+ffuiadOmAAA7O7sSx3PQoEE4evQoXFxcYGpqig8++AAfffQRRo0aBQMDAwDAunXr8NFHH0nxW1tbIy4uDqtXr4anpydMTEygo6MDDQ0N6b17/vw5AKBWrVpy7+eHH36IiIgIfPLJJ4iIiMCYMWOwdetWJCQkoGnTpjh79ixmz54N4N+aPQWaNGmCc+fOYc+ePdL1XtyY//jjj2V6rwrLzs5GdnZ2jfyBTEREREQ1x9WrV3HpUv4DZAvfeUlExcufU/PvxJqMjAylxUKKx5mw75GyzpCLj4+Hubm5lIAFAHt7exgZGSE+Pl5aZ2FhAX19fel1vXr1YG9vDxUVFbl1Dx48kGvf0dFRbjsAODg4yK3LysqSEmNlVbhdADAzMyvSd4GYmBi0atVKSsC+Lj09HbNmzYKdnR2MjIygp6eH+Ph4aSZsWcXHx8PZ2VlunbOzs9w4vh67rq4uDAwMSowdACZPnoz79+9j586d6NixI0JCQtC8eXNp5m9sbCxu3rwJfX196OnpQU9PDyYmJsjKypKb5erg4FDkYVYjRozArl27AORfMz/99BNGjBhR4vllZ2eX+EC30uIwMTGBp6cn3Nzc0K9fP/j7+5c4qxgAVFVVERQUhLt372LVqlVo0KABli1bhubNm0vHlTTmSUlJ5aobCwAuLi6IiIgAkD/rtVu3blJi9sKFC8jJyZHr69tvv0WbNm1Qp04d6Onp4fvvvy9yzbw+5mV9rwpbvnw5DA0N0aVLl3KdDxERERFRZTp16hTOnTsHALh3756SoyEiUi4mYd8jVlZWEARBYbPn1NXV5V4LglDsuoJb/Is7rmDmX3HrCo5TUVEpkkAurqZQWfouULh+aHFmzZqF/fv3Y9myZTh9+jRiYmLg4OCgkAcpFac8sRfQ19dHv3794Ofnh9jYWHTp0gVLly4FkJ9EbtOmDWJiYuSWGzduyJUVKK4sxbBhw5CYmIjLly/j7NmzuHPnTpFSFAVKG8eyxBEUFIRz586hU6dO2L17N6ytrUv9K3mDBg0wcuRIbNy4EX/88QeysrLw3//+943HvA1XV1fExcUhKSkJcXFx6Ny5M1xdXREREYHIyEi0bdsWOjo6AICff/4Zs2bNwrhx43Ds2DHExMRgzJgxRa6Z18e8rO9VYXPnzsWzZ89KrJ1LRERERERE1U/+bfKCtBT3O3t1p+wSBMosR8Ak7HvExMQEbm5u+Pbbb4ud0v706VMA+beD37lzB3fu3JG2xcXF4enTp7C3t6+scCV16tQpMjsyJibmndp0dHRETExMiXVXo6Ki4OnpiY8//hgODg4wNTUt8qAkDQ2NUmdW2tnZISoqqkjbih5HQRBga2srva+tW7dGUlIS6tati2bNmskthoaGb2yrYcOGcHFxwc6dO7Fz50706NEDdevWLXZfKysraGtrIzw8vNjtZY2jVatWmDt3Ls6ePYsWLVpIM3HLwtjYGGZmZtK5lzTm1tbWUFVVLbaNgpmpr7+fDg4OMDY2xtKlS+Hk5AQ9PT24uroiMjISERERcg+Hi4qKQqdOnTBp0iS0atUKzZo1K3Ema2Fv815pamrCwMAApqam0NbW5oO5iIiIiIiIagCZTIRMJpOW0spJUvXCJOx75ttvv0VeXh7at2+PvXv3IikpCfHx8QgICEDHjh0BAN27d4eDgwNGjBiBy5cvIzo6GqNGjYKLiwvatm1b6TF369YNFy9exPbt25GUlIRFixbh+vXr79TmsGHDYGpqigEDBiAqKgp//vkn9u7dK90qY2VlhX379iEmJgaxsbEYPnx4kZmpFhYWOHXqFO7du4d//vmn2H6++uorBAcHY9OmTUhKSsK6deuwb98+zJo1661jj4mJQf/+/fHLL78gLi4ON2/eRGBgIH744Qf0798fQH5Jgdq1a6N///44ffo0bt26hYiICEybNg13794ttY8RI0bg559/RkhISImlCABAS0sL3t7emD17NrZv347k5GT8/vvvCAwMLFMct27dwty5c3Hu3Dncvn0bx44dQ1JSUol1YTdv3owvvvgCx44dQ3JyMv744w94e3vjjz/+QL9+/QAAM2fORHh4OJYsWYIbN25g27Zt2Lhx4xvHvG7dutDW1kZYWBj+/vtvPHv2DEB+cvvDDz/Ezp07pYSro6MjsrOzER4eDhcXF6kNKysrXLx4EUePHsWNGzewYMECXLhwoUxj/S7v1aBBg/hgLiIiIiKqkmbPno127dpJd48ZGxsrOSKi6sXb21vZIZACMQn7nrG0tMTly5fRtWtXzJw5Ey1atECPHj0QHh6OTZs2AchPPB08eBDGxsb48MMP0b17d1haWmL37t1KidnNzQ0LFiyQfoC/ePECo0aNeqc2NTQ0cOzYMdStWxe9e/eGg4MDVqxYIc2UXLduHYyNjdGpUyf069cPbm5uaN26tVwbixcvRkpKCpo2bSo98fN1AwYMgL+/P9asWYPmzZtj8+bNCAoKkptBWV4NGzaEhYUFfH190aFDB7Ru3Rr+/v7w9fXF/PnzAQA6Ojo4deoUGjVqhIEDB8LOzg7jxo1DVlaW9ACrN/nkk0/w6NEjvHz5EgMGDHjjvgsWLMDMmTOxcOFC2NnZYciQIVI929Li0NHRQUJCAjw8PGBtbY3PP/8ckydPxoQJE4rtq3379khPT8fEiRPRvHlzuLi44Pfff8eBAwekhGjr1q2xZ88e/Pzzz2jRogUWLlyIxYsXw9PTs8RzUFNTQ0BAADZv3oz69etLyWwgvy5sXl6e9J6pqKjgww8/hCAIcvVgJ0yYgIEDB2LIkCHo0KEDHj16JD2Q7U3e9b2aP38+3N3dOQOWiIiIiKocU1NTrFu3Dhs3bgQAPHnyRMkREVUP6urq8PPzg7W1tbJDUThBEKvMUunnLnLaFBFRDXCp6KqniYCRjdwqMWIdBNcZlRNSTVHMOFYZVTk2oorEa79ilHVcOf70upKuCWVdK7xGqyTZ9IlQ+ea/fH+UTRHjXx3ew+oQY4naKDuACnVRt6myQ5C0zSi9hKAiMQlLRFTNeXl5ISwsjKUIiIiIiIiIagB1dXX4+vrCw8ND2aEo3GW9qpOEbZ1euUlYliMgIqrG/Pz8EBoaygQsERERERFRDZGTk4N58+YhKSlJ2aGQAjEJS0RUjYWEhEBLSwtqaioQBIG1YYmIiIiIiGqIFStWKDsEUiA1ZQdARERvJyMjA5mZmcoOg4iIiIiIiBRARUUA8O/EmoSEBOUFU0He53lDTMISEVVTKSkpyg6BiIiIiIiIFCS/yty/peYyMjKUFgspHssREBEREREREREREVUgzoQlIqqmLCwslB0CERERERERKUj+rfr/3q+vq6urtFgqioD396HSTMISEVVTurq60NbWhiiKyM19hby8/B9movj+/lAjIiIiIiKqrmQyEYXLEdja2iovGFI4liMgIqrGBg0ahKysLOTmyiCKIhOwRERERERENYS3t7eyQyAFYhKWiKgamz9/Ptzd3SG8z4+YJCIiIiIiqkHU1dXh5+cHa2trZYeicIJQdZZKP3eR06aIiGqAS8oOgIhI3tNEwMhG2VEQEVFZ8DubqAppo+wAKlSsgaWyQ5C0fP5npfbHmbBEFUQQBBw4cEDZYRRhYWGB9evXKzsMpfv+++9hbm4OFRUVjgdVT08T3207UUXjL/M1D79XqDhV/bqozPiK66vwusoeq/L0x+/smqWk976qf16JajjOhCUAwP379+Hn54cjR47g3r17qFu3LpycnODl5YWPPvpI2eFVGZ6enti2bRsAQE1NDSYmJnB0dMSwYcPg6ekJFZV//65x//59GBsbQ1NTUymxBgcHw8vLC0+fPpVb//DhQ+jq6kJHR0cpcb2rhw8fYuHChThy5Aj+/vtvGBsbo2XLlli4cCGcnZ3L1Mbz589Ru3ZtrFu3Dh4eHjA0NETv3r3h5ORULROyXl5eCAsLYz1YIiIiIiKiGkBdXR2+vr7w8PBQdigKd9Ww6syEdXxWuTNh1Sq1N6qSUlJS4OzsDCMjI6xevRoODg7IycnB0aNHMXnyZCQkJCg7xEr36tUraGhoFLvN3d0dQUFByMvLw99//42wsDB8+eWX+OWXX3Do0CGoqeV/rExNTSsktry8PAiCIJfwLY86deooOKK3k5OTA3V19XIf5+HhgVevXmHbtm2wtLTE33//jfDwcDx69KjMbaSmpiInJwd9+vSBmZlZuWNQFFEUkZeXJ10zb8PPzw+hoaEKjIqIiIiIiIiUKScnB/PmzYOjoyOsrKyUHQ4pCMsRECZNmgRBEBAdHQ0PDw9YW1ujefPmmDFjBn7//Xdpv9TUVPTv3x96enowMDDA4MGD8ffff0vbfXx84OTkhB07dsDCwgKGhoYYOnQoXrx4Ie3zyy+/wMHBAdra2qhVqxa6d++OjIwMAICrqyu8vLzkYhswYAA8PT2l1xYWFli6dClGjRoFPT09NG7cGIcOHcLDhw+l2BwdHXHx4kW5ds6cOYMuXbpAW1sb5ubmmDZtmtRvQbtLlizBqFGjYGBggM8//7zE8dLU1ISpqSkaNGiA1q1bY968eTh48CBCQ0MRHBws7Ve4HMGrV68wZcoUmJmZQUtLC40bN8by5culfZ8+fYoJEyagXr160NLSQosWLXD48GEA+TNajYyMcOjQIdjb20NTUxOpqanIzs7GrFmz0KBBA+jq6qJDhw6IiIgAAERERGDMmDF49uwZBEGAIAjw8fGRzrXwbE9FvK9hYWHo3LkzjIyMUKtWLfTt2xfJycnS9pSUFAiCgN27d8PFxQVaWlr4/vvvYWBggF9++UVufA8cOABdXV259guP0+nTp7Fy5Up07doVjRs3Rvv27TF37lz85z//KdM5BQcHw8HBAQBgaWkJQRDg6emJyMhI+Pv7S+OVkpKCtm3bYs2aNVK7AwYMgLq6OtLT0wEAd+/ehSAIuHnzJgBgx44daNu2LfT19WFqaorhw4fjwYMH0vEREREQBAGhoaFo06YNNDU1cebMGchkMixfvhxNmjSBtrY2WrZsWWRcShISEgItLS2oqalIsRMREREREVH1t2LFCmWHoHAqglhllko/90rvkaqUx48fIywsDJMnT4aurm6R7UZGRgAAmUyG/v374/Hjx4iMjMTx48fx559/YsiQIXL7Jycn48CBAzh8+DAOHz6MyMhI6UsjLS0Nw4YNw9ixYxEfH4+IiAgMHDiw3LdQf/PNN3B2dsaVK1fQp08fjBw5EqNGjcKnn36Ky5cvo2nTphg1apTUbnJyMtzd3eHh4YGrV69i9+7dOHPmDKZMmSLX7po1a9CyZUtcuXIFCxYsKFdM3bp1Q8uWLbFv375itwcEBODQoUPYs2cPEhMTsXPnTlhYWADIH9tevXohKioKP/74I+Li4rBixQqoqqpKx798+RIrV67E1q1b8ccff6Bu3bqYMmUKzp07h59//hlXr17FoEGD4O7ujqSkJHTq1Anr16+HgYEB0tLSkJaWhlmzZhWJSxHvKwBkZGRgxowZuHjxIsLDw6GiooKPP/4YMplMrp05c+bgyy+/RHx8PAYOHIihQ4ciKChIbp+goCB88skn0NfXLxKvnp4e9PT0cODAAWRnZxc71qWd05AhQ3DixAkAQHR0NNLS0uDv74+OHTti/Pjx0niZm5vDxcVFSmyLoojTp0/DyMgIZ86cAQBERkaiQYMGaNasGYD8v1YuWbIEsbGxOHDgAFJSUuT+iFB4HFasWIH4+Hg4Ojpi+fLl2L59O/773//ijz/+wPTp0/Hpp58iMjKy2HMsPO6ZmZnIyspCbq4MoiiyJAEREREREVE1pKqqAhWV/LteC5b38c7kmozlCN5zN2/ehCiKsLW1feN+4eHhuHbtGm7dugVzc3MAwPbt29G8eXNcuHAB7dq1A5CfAAsODpYSaCNHjkR4eDj8/PyQlpaG3NxcDBw4EI0bNwYAaUZiefTu3RsTJkwAACxcuBCbNm1Cu3btMGjQIACAt7c3OnbsiL///humpqZYvnw5RowYIc2ytbKyQkBAAFxcXLBp0yZoaWkByE+kzpw5s9zxFLC1tcXVq1eL3ZaamgorKyt07twZgiBI5w8AJ06cQHR0NOLj42FtbQ0gf4ZmYTk5Ofjuu+/QsmVLqb2goCCkpqaifv36AIBZs2YhLCwMQUFBWLZsGQwNDSEIwhvLIijifQVQpE7NDz/8gDp16iAuLg4tWrSQ1nt5eWHgwIHS688++wydOnVCWloazMzM8ODBA/z6669SkvR1ampqCA4Oxvjx4/Hf//4XrVu3houLC4YOHQpHR8cyn1OtWrUA5JdmKBgfDQ0N6OjoyI2Xq6srAgMDkZeXh+vXr0NDQwNDhgxBREQE3N3dERERARcXF2n/sWPHSv9vaWmJgIAAtGvXDunp6dDT05O2LV68GD169AAAZGdnY9myZThx4gQ6duwoHXvmzBls3rxZrv0C2dnZyM7O5g9kIiIiIiKiGkIQBMhkIoB/J9YUvoOXqj/OhH3PlXXWXHx8PMzNzaWkFgDY29vDyMgI8fHx0joLCwu5GYwFiTUAaNmyJT766CM4ODhg0KBB2LJlC548eVLumAuSbQBQr149APLJ3IJ1Bf3GxsYiODhYmkWpp6cHNzc3yGQy3Lp1Szqubdu25Y6lMFEUS7wV3NPTEzExMbCxscG0adNw7NgxaVtMTAwaNmwoJWCLo6GhIXfe165dQ15eHqytreXOKzIyUq4MQGkU8b4CQFJSEoYNGwZLS0sYGBhIs3xTU1Pl+nt9jNu3b4/mzZtLDzv78ccf0bhxY3z44Yclxuzh4YG//voLhw4dkhKhrVu3lkpBlPWcyqJLly548eIFrly5gsjISLi4uMDV1VWaHRsZGQlXV1dp/0uXLqFfv35o1KgR9PX1pQTqm8bh5s2bePnyJXr06CH3Xm7fvr3E93L58uUwNDREly5dynU+RERERERERMokCFVnqWxMwr7nrKysIAiCwmbUvf6gpfy/5OTfkq6qqorjx48jNDQU9vb22LBhA2xsbKREqIqKSpGkcE5Ozhv7KEh6FreuoN/09HRMmDABMTEx0hIbG4ukpCQ0bdpUOq64cgzlER8fjyZNmhS7rXXr1rh16xaWLFmCzMxMDB48GJ988gkAQFtbu9S2tbW15RK86enpUFVVxaVLl+TOKz4+Hv7+/u90HsV50/sKAP369cPjx4+xZcsWnD9/HufPnweQXwu3sOLG+LPPPpMSqEFBQRgzZkypdU21tLTQo0cPLFiwAGfPnoWnpycWLVr0Nqf2RkZGRmjZsiUiIiKkhOuHH36IK1eu4MaNG0hKSpISrRkZGXBzc4OBgQF27tyJCxcuYP/+/QDePA4F9WWPHDki917GxcWVWBd27ty5ePbsGW7fvq3wcyYiIiIiIqLKlz+xC9KzPgRBeOc8BVUtTMK+50xMTODm5oZvv/222GnuT58+BQDY2dnhzp07uHPnjrQtLi4OT58+hb29fZn7EwQBzs7O8PX1xZUrV6ChoSElqurUqYO0tDRp34JbwN9V69atERcXh2bNmhVZNDQ03rl9APjtt99w7dq1IrflF2ZgYIAhQ4Zgy5Yt2L17N/bu3YvHjx/D0dERd+/exY0bN8rcX6tWrZCXl4cHDx4UOafCt9fn5eW9sR1FvK+PHj1CYmIivv76a3z00Uews7Mr1wznTz/9FLdv30ZAQADi4uIwevToMh9bwN7eXrp+3/acShovFxcXnDx5EqdOnYKrqytMTExgZ2cHPz8/mJmZSTOYExIS8OjRI6xYsQJdunSBra2t3GzhN8Ve8LC119/LwrN5C9PU1ISBgQFMTU2hra3NB3MRERERERFVc3l5MshkImQymbSUVjqSqhcmYQnffvst8vLy0L59e+zduxdJSUmIj49HQECAVKOye/fucHBwwIgRI3D58mVER0dj1KhRcHFxKfNt/OfPn8eyZctw8eJFpKamYt++fXj48CHs7OwA5NdkPXLkCI4cOYKEhAR88cUXUhL4XXh7e+Ps2bOYMmUKYmJikJSUhIMHDxZ5MFdZZWdn4/79+7h37x4uX76MZcuWoX///ujbty9GjRpV7DHr1q3DTz/9hISEBNy4cQMhISEwNTWFkZERXFxc8OGHH8LDwwPHjx/HrVu3EBoairCwsBJjsLa2xogRIzBq1Cjs27cPt27dQnR0NJYvX44jR44AyC8hkJ6ejvDwcPzzzz94+fJlkXYU8b4aGxujVq1a+P7773Hz5k389ttvmDFjRpmOLTh+4MCB+Oqrr9CzZ080bNiwxH0fPXqEbt264ccff8TVq1dx69YthISEYNWqVejfv/87nZOFhQXOnz+PlJQU/PPPP9JMX1dXVxw9ehRqamrSD0BXV1fs3LlTrl5ro0aNoKGhgQ0bNuDPP//EoUOHsGTJklLPX19fH7NmzcL06dOxbds2JCcn4/Lly9iwYYNUpuFNBg0axAdzERERERER1UDe3t7KDkHhhCq0VDYmYQmWlpa4fPkyunbtipkzZ6JFixbo0aMHwsPDsWnTJgD5M1gPHjwIY2NjfPjhh+jevTssLS2xe/fuMvdjYGCAU6dOoXfv3rC2tsbXX3+NtWvXolevXgDyH2o0evRoKWFmaWmJrl27vvP5OTo6IjIyEjdu3ECXLl3QqlUrLFy4UHqgVXmFhYXBzMwMFhYWcHd3x8mTJxEQEICDBw9CVVW12GP09fWxatUqtG3bFu3atUNKSgp+/fVXqKjkfwT37t2Ldu3aYdiwYbC3t8fs2bNLncUaFBSEUaNGYebMmbCxscGAAQNw4cIFNGrUCADQqVMnTJw4EUOGDEGdOnWwatWqIm0o4n1VUVHBzz//jEuXLqFFixaYPn06Vq9eXebjAWDcuHF49eqV3IOtiqOnp4cOHTrgm2++wYcffogWLVpgwYIFGD9+PDZu3PhO5zRr1iyoqqrC3t4ederUkeq4dunSBTKZTC7h6urqiry8PLl6sHXq1EFwcDBCQkJgb2+PFStWYM2aNWU6/yVLlmDBggVYvnw57Ozs4O7ujiNHjpRY3qKw+fPnw93dnTNgiYiIiIiIagh1dXX4+fm98dkxVP0IIqdNEZGS7dixA9OnT8dff/2lsBIR759Lyg6ASvM0ETCyUXYUFavgHEs5V/HWYQhN+patLaJ3UVWuo6oSx+uqalxEilbea72qfDaqShxEyqSoz0FZ26kSn7s2Su6/YsUZlz7ZqLLYP7lV+k4KpFapvRERFfLy5UukpaVhxYoVmDBhAhOwb8nLywthYWEsRUDVzC5lB0BEREREVCWpq6vD19f3jc+dqa4E4f39vZXlCIhIaVatWgVbW1uYmppi7ty5yg6nWvLz80NoaCgTsERERERERDVETk4O5s2bh6SkJGWHQgrEcgRERNWYk5MTRFFEbu4r5OXlf53za52IiMpLEAD++CAiIqpaOnfujMDAQGWHoVDxJhbKDkFi9zilUvtjOQIiomoqIyMDmZmZyg6DiIhqACZgiYiIlE9FRQDw70OXExISlBdMBXmfnynNJCwRUTWVkpKi7BCIiIiIiIhIQfL/KPrvX0YzMjKUFgspHpOwREREREREREREVOFUOBOWiIiqGwsLC2WHQERERERERAqSf6v+v1lKXV1dpcVCiqei7ACIiOjt6OrqQltbG1paWlBTU4EgCBDe5wI7RET01vjjg4iISPlkMhEymUxabG1tlR0S/T8LCwvpd+7Cy+TJk8vcBpOwRETV2KBBg5CVlYXcXBlEUYTIJ6sQEdFb4I8PIiKiqsfb21vZISicIIhVZimPCxcuIC0tTVqOHz8OIP938rJiOQIiomps/vz5ePDgAY4ePcoELBERERERUQ2grq4OHx8fWFtbKzsU+n916tSRe71ixQo0bdoULi4uZW5DEPlbOylYREQEunbtiidPnsDIyOid2vL09MTTp09x4MCBMh9jYWEBLy8veHl5vVPfiuLj44NNmzbhwYMH2L9/PwYMGKDskKgCBQcHw8vLC0+fPq3kni9Vcn9Ubk8TASMbZUdRsQrOsZRzFW8dhtCkb9naInoXVeU6qipxvK6qxkWkaOW91qvKZ6OqxEGkTIr6HJS1nSrxuWuj5P4rVlKdxsoOQdLo7g1kZ2fLrdPU1ISmpuYbj3v16hXq16+PGTNmYN68eWXuT6kzYT09PbFt27b8QNTUYGJiAkdHRwwbNgyenp5QUSl7tQRFJz5u3rwJPz8/HD9+HA8fPkT9+vXxwQcfYObMmWjbtq1C+gCqXsKwspR03j4+Pjhw4ABiYmIAAP7+/pUyu6/wtaiuro5GjRph1KhRmDdvHtTU3v5jEh8fD19fX+zfvx8ffPABjI2NFRVyjbB3715s2LABV65cQV5eHiwtLfHJJ59gypQpMDExUXZ4pSruOh4yZAh69+5dqXF4eXkhLCyMM2Gpmtml7ACIiIiIiKokdXV1+Pr6wsPDQ9mhKFxVKkO/fPly+Pr6yq1btGgRfHx83njcgQMH8PTpU3h6eparP6XXhHV3d0daWhpSUlIQGhqKrl274ssvv0Tfvn2Rm5urlJguXryINm3a4MaNG9i8eTPi4uKwf/9+2NraYubMmUqJqTSvXr1SdggVwtDQ8J1n05ZVwbWYlJSEmTNnwsfHB6tXr36rtvLy8iCTyZCcnAwA6N+/P0xNTUv9a0pJcnJy3uq4qmz+/PkYMmQI2rVrh9DQUFy/fh1r165FbGwsduzYoezw3pq2tjbq1q1baf35+fkhNDSUCVgiIiIiIqIaIicnB/PmzUNSUpKyQ6nR5s6di2fPnsktc+fOLfW4wMBA9OrVC/Xr1y9Xf0pPwmpqasLU1BQNGjRA69atMW/ePBw8eBChoaEIDg6W9lu3bh0cHBygq6sLc3NzTJo0Cenp6QDyb38fM2YMnj17Jj2drCBrvWPHDrRt2xb6+vowNTXF8OHD8eDBgxLjEUURnp6esLKywunTp9GnTx80bdoUTk5OWLRoEQ4ePCjte+fOHQwePBhGRkYwMTFB//79kZKSIm339PTEgAEDsGbNGpiZmaFWrVqYPHmylFBzdXXF7du3MX369CJPNT9z5gy6dOkCbW1tmJubY9q0acjIyJC2W1hYYMmSJRg1ahQMDAzw+eef49WrV5gyZQrMzMygpaWFxo0bY/ny5SWe64ULF9CjRw/Url0bhoaGcHFxweXLl+X2EQQBW7duxccffwwdHR1YWVnh0KFDcvv8+uuvsLa2hra2Nrp27So3Bu+qYAwLvHjxAiNGjICuri7MzMzwzTffwNXVtciM2pcvX2Ls2LHQ19dHo0aN8P3335faV8G12LhxY3zxxRfo3r27dK7Z2dmYNWsWGjRoAF1dXXTo0AERERHSscHBwTAyMsKhQ4dgb28PTU1NjB07Fv369QMAqKioSO+vTCbD4sWL0bBhQ2hqasLJyQlhYWFSWykpKRAEAbt374aLiwu0tLSwc+dOaSyWLVuGevXqwcjICIsXL0Zubi6++uormJiYoGHDhggKCpI7L29vb1hbW0NHRweWlpZYsGCBXFLXx8cHTk5O2LFjBywsLGBoaIihQ4fixYsX0j4ymQyrVq1Cs2bNoKmpiUaNGsHPz0/aXtpn4XXR0dFYtmwZ1q5di9WrV6NTp06wsLBAjx49sHfvXowePVrad9OmTWjatCk0NDRgY2NTJEErCAI2b96Mvn37QkdHB3Z2djh37hxu3rwJV1dX6OrqolOnTlJCvPA5b968Gebm5tDR0cHgwYPx7NkzaZ/irqsBAwZIf+kq6fNbcC2UZ3zLel0XJyQkBFpaWlBTUynyPUJERERERETV14oVK5QdQo2mqakJAwMDuaW0yXO3b9/GiRMn8Nlnn5W7P6UnYYvTrVs3tGzZEvv27ZPWqaioICAgAH/88Qe2bduG3377DbNnzwYAdOrUCevXr4eBgYH0lLJZs2YByP/rwZIlSxAbG4sDBw4gJSXljdOFY2Ji8Mcff2DmzJnFlkMoSK7k5OTAzc0N+vr6OH36NKKioqCnpwd3d3e5WaknT55EcnIyTp48iW3btiE4OFhKLu/btw8NGzbE4sWLpbgBIDk5Ge7u7vDw8MDVq1exe/dunDlzBlOmTJGLZc2aNWjZsiWuXLmCBQsWICAgAIcOHcKePXuQmJiInTt3wsLCosRzffHiBUaPHo0zZ87g999/h5WVFXr37i2XHAIAX19fDB48GFevXkXv3r0xYsQIPH78GEB+8m3gwIHo168fYmJi8Nlnn2HOnDkl9vmuZsyYgaioKBw6dAjHjx/H6dOniySOAWDt2rVo27Ytrly5gkmTJuGLL75AYmJiufrS1taW3sspU6bg3Llz+Pnnn3H16lUMGjQI7u7ucn+VevnyJVauXImtW7fijz/+QEBAgJQQLfz++vv7Y+3atVizZg2uXr0KNzc3/Oc//ynyF645c+bgyy+/RHx8PNzc3AAAv/32G/766y+cOnUK69atw6JFi9C3b18YGxvj/PnzmDhxIiZMmIC7d+9K7ejr6yM4OBhxcXHw9/fHli1b8M0338j1lZycjAMHDuDw4cM4fPgwIiMj5b7s586dixUrVmDBggWIi4vDrl27UK9ePQBl/ywUtnPnTujp6WHSpEnFbi/4nO3fvx9ffvklZs6cievXr2PChAkYM2YMTp48Kbd/wR8kYmJiYGtri+HDh2PChAmYO3cuLl68CFEUi3x+bt68iT179uB///sfwsLCpGulrEr6/BantPEt63X9uoyMDGRmZiIrKwu5uTKIosgZsURERERERNWUiooAFRUVaUlISFB2SAonCFVneRtBQUGoW7cu+vTpU+5jlVoT9k1sbW1x9epV6XXhGWEWFhZYunQpJk6ciO+++w4aGhowNDSEIAgwNTWVa2fs2LHS/1taWiIgIADt2rVDeno69PT0ivRbkAiztbV9Y3y7d++GTCbD1q1bpZlnQUFBMDIyQkREBHr27AkAMDY2xsaNG6GqqgpbW1v06dMH4eHhGD9+PExMTKCqqirN0i2wfPlyjBgxQjpnKysrBAQEwMXFBZs2bYKWlhaA/GR14fIIqampsLKyQufOnSEIAho3fnOx427dusm9/v7772FkZITIyEj07fvvA1M8PT0xbNgwAMCyZcsQEBCA6OhouLu7S7MU165dCwCwsbHBtWvXsHLlyjf2DeTP0Pz666/l1r169Qr29vbF7v/ixQts27YNu3btwkcffQQgf8yLm/7du3dvKaHm7e2Nb775BidPnoSNTekFtkVRRHh4OI4ePYqpU6ciNTUVQUFBSE1NlfqaNWsWwsLCEBQUhGXLlgHIT0Z+9913aNmypdRWQTKx8Pu7Zs0aeHt7Y+jQoQCAlStX4uTJk1i/fj2+/fZbaT8vLy8MHDhQLjYTExMEBARARUUFNjY2WLVqFV6+fCkVgi5Ilp45c0Zqv/AYW1hYYNasWfj555+lP2IA+TNdg4ODoa+vDwAYOXIkwsPD4efnhxcvXsDf3x8bN26UZqg2bdoUnTt3BlD2z0JhSUlJsLS0hLq6+hvfizVr1sDT01N6L2fMmIHff/8da9asQdeuXaX9xowZg8GDBwPIf787duyIBQsWSMnrL7/8EmPGjJFrOysrC9u3b0eDBg0AABs2bECfPn2wdu3aIt8jxSnp81uc0sa3rNd1gezsbGRnZ9fIH8hERERERETvq/w5Nf9OrCl8RzQpn0wmQ1BQEEaPHv1Wzw+qsklYURTlbqs9ceIEli9fjoSEBDx//hy5ubnIysrCy5cvoaOjU2I7ly5dgo+PD2JjY/HkyRPIZDIA+QnL4pJ9ZZ1FFhsbi5s3b0pJlQJZWVlytz03b94cqqqq0mszMzNcu3at1LavXr2KnTt3ysUlk8lw69Yt2NnZAUCRB4R5enqiR48esLGxgbu7O/r27VtsAqzA33//ja+//hoRERF48OAB8vLy8PLlS6Smpsrt5+joKP2/rq4uDAwMpJIO8fHx6NChg9z+HTt2fOP5Ffjqq6+KzEoOCAjAqVOnit3/zz//RE5ODtq3by+tMzQ0LDaxWjjmguT8m8pQAMDhw4ehp6eHnJwcyGQyDB8+HD4+PoiIiEBeXh6sra3l9s/OzkatWrWk1xoaGnL9Fuf58+f466+/4OzsLLfe2dkZsbGxcuuKewBc8+bN5WZo16tXDy1atJBeq6qqolatWnLnunv3bgQEBCA5ORnp6enIzc2FgYGBXLsWFhZy17KZmZnce5ydnS0lCF9X1s9CYWX9nMXHx+Pzzz+XW+fs7Ax/f3+5dYXHvWCGroODg9y6rKwsPH/+XDr3Ro0aSQlYIP+6lclkSExMLFMStjzeNL7lua4LFBQP19DQeONsdyIiIiIiIqKqRBCq792bJ06cQGpqqtyEz/KosknY+Ph4NGnSBEB+jcy+ffviiy++gJ+fH0xMTHDmzBmMGzcOr169KjEJm5GRATc3N7i5uWHnzp2oU6cOUlNT4ebmVuJt0gWJtoSEBLRq1arE+NLT09GmTRu5RGmBOnXqSP//+kw/QRCkRPCb2p4wYQKmTZtWZFujRo2k/9fV1ZXb1rp1a9y6dQuhoaE4ceIEBg8ejO7du+OXX34ptp/Ro0fj0aNH8Pf3R+PGjaGpqYmOHTsWGZu3OYeyqF27Npo1aya3zsTE5J3bBd4u5q5du2LTpk3Q0NBA/fr1pb9qpKenQ1VVFZcuXZJLqAOQm02tra2t0Hqcr7+/QPHn9aZzPXfuHEaMGAFfX1+4ubnB0NAQP//8szRz+U3tFrShra39xjjL+lkozNraGmfOnEFOTk6ps2HLonAbBe9BcevKc92qqKgUSRa/7QPSFP0Zmjt3LmbMmIGXL1/CxcXlrdshIiIiIiKiqiP/V9d/8wrF5QVIeXr27PlOJQCrZE3Y3377DdeuXYOHhweA/NmsMpkMa9euxQcffABra2v89ddfcsdoaGggLy9Pbl1CQgIePXqEFStWoEuXLrC1tS11NqSTkxPs7e2xdu3aYpMkT58+BZCf8ExKSkLdunXRrFkzucXQ0LDM51pc3K1bt0ZcXFyRdps1awYNDY03tmdgYIAhQ4Zgy5Yt2L17N/bu3SvVb31dVFQUpk2bht69e6N58+bQ1NTEP//8U+bYAcDOzg7R0dFy637//fdytVFWBbevX7hwQVr37Nkz3LhxQyHt6+rqolmzZmjUqJHctPJWrVohLy8PDx48KPJ+lHfGpIGBAerXr4+oqCi59VFRUSWWYXgXZ8+eRePGjTF//ny0bdsWVlZWuH37drnasLKygra2NsLDw4vd/jafheHDhyM9PR3fffddsdsLPmd2dnYVNlapqaly3yO///67VOYByE8gF67zmpeXh+vXr8u1Udznt7ze5rouKB5uamoKbW1tPpiLiIiIiIioBpDJ8u+CLlhKK5VJ1YvSk7DZ2dm4f/8+7t27h8uXL2PZsmXo378/+vbti1GjRgEAmjVrhpycHGzYsAF//vknduzYgf/+979y7VhYWCA9PR3h4eH4559/8PLlSzRq1AgaGhrScYcOHcKSJUveGI8gCAgKCsKNGzfQpUsX/Prrr/jzzz9x9epV+Pn5oX///gCAESNGoHbt2ujfvz9Onz6NW7duISIiAtOmTZN7KFJpLCwscOrUKdy7d09KgHp7e+Ps2bOYMmUKYmJikJSUhIMHDxZ5sNDr1q1bh59++gkJCQm4ceMGQkJC8H/s3Xtcjvf/B/DXddddd92dRJRj6IyIMMyw2bcYY0xOQ86GpRGNHIo1MecZszmEOc2cNibMZORsyqmSSLOFDZnS+b5/f/Tr4q67ustdd4fX8/G4HnTd1/X5vK/rPr/vz/X+WFtbq8zU/ip7e3ts3boV0dHROH/+PIYOHVrsqMf8JkyYgLi4OEyfPh2xsbHYvn27OPGYtpmammLEiBGYPn06Tpw4gRs3bmD06NGQSCRlmnhycHDA0KFDMXz4cOzduxd3797FhQsXsHDhQhw6dKjE7U2fPh2LFi3Crl27EBsbi88++wyRkZGYMmWK1mO3t7dHYmIidu7cifj4eKxatQr79u0rURsymQz+/v6YMWMGtmzZgvj4eJw7dw4bNmwAULrnQvv27TFjxgxMmzYNM2bMwNmzZ3Hv3j0cP34cAwYMwObNmwHknqvQ0FCsXbsWcXFxWLZsGfbu3StOvPc6ZDIZRowYgaioKJw6dQo+Pj7w8vISE+tvv/02Dh06hEOHDiEmJgYff/yxmBzOo+75W1Kv+7geMGAAJ+YiIiIiIiKqgvz9/XUdgtZJhIqzlPuxl3+XqsLCwmBjYwNbW1t4enrixIkTWLVqFQ4cOCBe+t2yZUssW7YMixYtQvPmzbFt2zYsXLhQpZ2OHTtiwoQJGDhwIKysrLB48WJYWVkhNDQUu3fvhouLC0JCQrBkyZJiY2rXrh0uXboEOzs7jB07Fs7Oznj//fdx48YNrFixAgBgbGyM33//HQ0bNkS/fv3g7OyM0aNHIz09vUC9zaLMnz8fCQkJaNq0qXjptqurK06ePCkmgt3c3DB37twiJ+oBcpM5ixcvhru7O9q2bYuEhAT88ssvKjVEX7VhwwY8ffoUrVu3xrBhw+Dj44PatWtrHDuQWx5hz5492L9/P1q2bIlvvvlGnKiqLCxbtgwdOnRAr1690L17d3Tq1AnOzs7iZGVlZdOmTRg+fDimTZsGR0dH9O3bFxcvXlQpD6EpHx8fTJ06FdOmTUOLFi0QFhaGn376Cfb29lqP+/3338enn36KyZMno1WrVjhz5gzmzJlT4nbmzJmDadOmYe7cuXB2dsbAgQPFUeWlfS4sWrQI27dvx/nz5+Hh4YFmzZph6tSpcHV1FScA69u3L1auXIklS5agWbNmWLduHTZt2oSuXbuW6ny8ys7ODv369UPPnj3xv//9D66uriojc0eNGoURI0Zg+PDh6NKlC5o0aaIyGRig/vlbGq/zuA4ICICnpydHwBIREREREVURUqkUwcHBBeamocpNUHLYFFViqampqFevHpYuXYrRo0frOhyqJAIDA7F//35ERkbqOhS1Sve4vlymMYmSYwGLwicNIyIiIiKiSqIif7avyLGVuTa6DqBMJViXfDBbWbF9kFj8RlpUYSfmIlLnypUriImJQbt27fDs2TPMnz8fAMQyEUSVUYV9XKv74FNtPwgR5fPq86Naf0kgIiKiSqsif36pyLHRa6nOF3EyCUuVzpIlSxAbGwsDAwO0adMGp06dQq1atXQdFtFreZ3Hta+vL8LCwlgPloiIiIiIqAqQSqUICgoSJ6ynqoHlCIiIKrHg4GBs2bJF12EQERERERGRlh08eLBM5o/RpXs2FaccQaOk8i1HoPOJuYiIqPR2794NmUwGfX0JBEHgBF1ERERERERVREhIiK5D0DpBqDhLeWM5AiKiSio1NRVpaWm6DoOIiIiIiIi0QCIRALzMDsbExOguGNI6JmGJiCqphIQEXYdAREREREREWpJbMPRl1dDU1FSdxULaxyQsERERERERERERlTkB1XdqKiZhiYgqKVtbW12HQERERERERFqSW6f0ZTkCuVyus1hI+5iEJSKqpORyOYyMjKBUKpGdnYmcnNxfFJXK6vvLIhERERERUWWlUCjxajkCJycn3QVTRqrzXNISXQdARESlN2DAAKSnpyM7WwGlUskELBERERERURXh7++v6xBIi5iEJSKqxAICAuDp6QmhOv+cSEREREREVIVIpVIEBwfDwcFB16GQFglKDpsiItKa0NBQ+Pr6Ijk5uZx7vlzO/RGVg+RYwMJR11FoLn+8FT3+ih4fEZGu8XWy8tHWfcb7vmopq/uzzB5vbV6/zQrsrwYNdR2CqN6fieXaH5OwRNWEt7c3Nm/eDADQ19eHpaUlXF1dMXjwYHh7e0Mi0XxgvDYTjV27dsXJkycBAIaGhmjSpAkmT56MiRMnvnbbupCWlobnz5+jdu3a5danr68vwsLCWIqAiIiIiIioCpBKpQgKCkL//v11HYrWVeckLMsREFUjnp6eSEpKQkJCAg4fPoxu3bphypQp6NWrF7Kzs3UW19ixY5GUlISbN2/Cy8sLkyZNwo4dO9Rum5mZWc7RlYyRkVG5JmCDg4Nx+PBhJmCJiIiIiIiqiKysLMyaNQtxcXG6DoW0iElYomrE0NAQ1tbWqFevHlq3bo1Zs2bhwIEDOHz4MEJDQ8Xtli1bhhYtWkAul6NBgwaYOHEiUlJSAADh4eEYOXIknj17BkEQIAgCAgMDAQBbt26Fu7s7TE1NYW1tjSFDhuDRo0fFxmVsbAxra2s0adIEgYGBsLe3x08//QQgd6Ts5MmT4evri1q1asHDwwMAcPLkSbRr1w6GhoawsbHBZ599ppJIVigUWLx4Mezs7GBoaIiGDRsiODhYvP3PP/+El5cXLCwsYGlpiT59+iAhIUG8PTw8HO3atYNcLoeFhQU6deqEe/fuAQCioqLQrVs3mJqawszMDG3atMGlS5cA5I4StrCwENsJDAxEq1atsHXrVtja2sLc3ByDBg3C8+fPxW2eP3+OoUOHQi6Xw8bGBsuXL0fXrl3h6+tb7LnbvXs3ZDIZ9PUl4v1BRLrHpyIRERERlZS+vmqaLiQkREeRlB1BUnGW8sYkLFE19/bbb6Nly5bYu3evuE4ikWDVqlW4ceMGNm/ejN9++w0zZswAAHTs2BErVqyAmZkZkpKSkJSUBD8/PwC5v9YtWLAAUVFR2L9/PxISEuDt7V3imIyMjFRGvG7evBkGBgaIiIjAN998g7/++gs9e/ZE27ZtERUVhbVr12LDhg34/PPPxX1mzpyJkJAQzJkzBzdv3sT27dtRp04dMU4PDw+Ympri1KlTiIiIgImJCTw9PZGZmYns7Gz07dsXXbp0wdWrV3H27FmMGzdOTHAOHToU9evXx8WLF3H58mV89tlnkEqlhR5PfHw89u/fj4MHD+LgwYM4efKkypvp1KlTERERgZ9++gnHjh3DqVOn8McffxR7nlJTU5GWlob09HRkZyugVCo5IpaoguBTkYiIiIhKSk9PDzKZDBKJBBKJBDExMboOibRIX9cBEJHuOTk54erVq+Lfr47AtLW1xeeff44JEyZgzZo1MDAwgLm5OQRBgLW1tUo7o0aNEv/fpEkTrFq1Cm3btkVKSgpMTEyKjSMnJwc7duzA1atXMW7cOHG9vb09Fi9eLP4dEBCABg0aYPXq1RAEAU5OTvj777/h7++PuXPnIjU1FStXrsTq1asxYsQIAEDTpk3x5ptvAgB27doFhUKB9evXi4nVTZs2wcLCAuHh4XB3d8ezZ8/Qq1cvNG3aFADg7Ows9p+YmIjp06fDyclJjK8oCoUCoaGhMDU1BQAMGzYMx48fR3BwMJ4/f47Nmzdj+/bteOedd8RY6tatW2h7GRkZyMjI4BsyERERERFRFZKTo4BUqi8OrklNTdVxRKRNHAlLRFAqlSqXsf/666945513UK9ePZiammLYsGF4/PgxXrx4UWQ7ly9fRu/evdGwYUOYmpqiS5cuAHKTlkVZs2YNTExMYGRkhLFjx+LTTz/Fxx9/LN7epo3q7JDR0dHo0KGDSsydOnVCSkoK7t+/j+joaGRkZIhJzfyioqJw+/ZtmJqawsTEBCYmJrC0tER6ejri4+NhaWkJb29veHh4oHfv3li5ciWSkpLE/adOnYoxY8age/fuCAkJQXx8fJHHZ2trKyZgAcDGxkYs03Dnzh1kZWWhXbt24u3m5uZwdCx8ls2FCxfC3NwcnTt3LrJfIiIiIiIioopEECrOUt6YhCUiREdHo3HjxgCAhIQE9OrVC66urtizZw8uX76Mr7/+GkDRk2KlpqbCw8MDZmZm2LZtGy5evIh9+/YVux+Qe3l/ZGQk7t69i9TUVCxbtgwSycuXJ7lcXqLjMTIyKvL2lJQUtGnTBpGRkSrLrVu3MGTIEAC5o1HPnj2Ljh07YteuXXBwcMC5c+cA5NZ5vXHjBt577z389ttvcHFxEY9VnfylCgRBgEKhKNExvWrmzJl49uyZWKOWiIiIiIiIKj89PYk4SEoQhBJ/F6aKjUlYomrut99+w7Vr19C/f38AuaNZFQoFli5dijfeeAMODg74+++/VfYxMDBATk6OyrqYmBg8fvwYISEh6Ny5M5ycnDSalAvIHflpZ2eHevXqqSRfC+Ps7IyzZ8+q1D+NiIiAqakp6tevD3t7exgZGeH48eNq92/dujXi4uJQu3Zt2NnZqSzm5ubidm5ubpg5cybOnDmD5s2bY/v27eJtDg4O+PTTT3H06FH069cPmzZt0uhY82vSpAmkUikuXrwornv27Blu3bpV6D6GhoYwMzODtbU1jIyMODEXUQXEpyIRERERlVROjgLp6elQKBRQKBRiCbwqRSJUnKW8D73ceyQincnIyMCDBw/w119/4Y8//sAXX3yBPn36oFevXhg+fDgAwM7ODllZWfjqq69w584dbN26Fd98841KO7a2tkhJScHx48fx77//4sWLF2jYsCEMDAzE/X766ScsWLCgTI5j4sSJ+PPPP/HJJ58gJiYGBw4cwLx58zB16lRIJBLIZDL4+/tjxowZ2LJlC+Lj43Hu3Dls2LABQO7I21q1aqFPnz44deoU7t69i/DwcPj4+OD+/fu4e/cuZs6cibNnz+LevXs4evQo4uLi4OzsjLS0NEyePBnh4eG4d+8eIiIicPHiRZWasSVhamqKESNGYPr06Thx4gRu3LiB0aNHQyKRaJRQHTBgACfmIqqA+FQkIiIiopLKzlYd7OTv76+jSKgsMAlLVI2EhYXBxsYGtra28PT0xIkTJ7Bq1SocOHAAenp6AICWLVti2bJlWLRoEZo3b45t27Zh4cKFKu107NgREyZMwMCBA2FlZYXFixfDysoKoaGh2L17N1xcXBASEoIlS5aUyXHUq1cPv/zyCy5cuICWLVtiwoQJGD16NGbPni1uM2fOHEybNg1z586Fs7MzBg4cKI7MNTY2xu+//46GDRuiX79+cHZ2xujRo5Geng4zMzMYGxsjJiYG/fv3h4ODA8aNG4dJkyZh/Pjx0NPTw+PHjzF8+HA4ODjAy8sLPXr0QFBQUKmPZ9myZejQoQN69eqF7t27o1OnTnB2doZMJit234CAAHh6enIELBERERERURUhlUoRHBwMBwcHXYdCWiQoOWyKiKhCSU1NRb169bB06VKMHj1aw70ul2lM5So5FrAofGIyItIBPi+JiConvn5TeeFjTSuU4csgdN2m6zDK1AO7RroOQWR9u3znWdEv196IiKiAK1euICYmBu3atcOzZ88wf/58AECfPn002t/X1xdhYWEsRUBERERERFTpOaJWrVpYu3YtXF1ddR0MaRHLERARVQBLlixBy5Yt0b17d6SmpuLUqVOoVatWsfsFBwfj8OHDTMASERERERFVEf/++y+GDx+Ox48f6zoU0iKWIyAiqsRatWoFpVKJ7OxM5OTkvpzzZZ2IiIiIiKhy09PTg6+vL8aNG6frULTqob2trkMQ1YlLKNf+WI6AiKiSSk1NRVpamq7DICIiIiIiotckCACUuf9RKpWQSCS4cuWKrsMiLWISloiokkpISNB1CERERERERKQF4gWNypdXOP7777+6C4i0jklYIiIiIiIiIiKiCqSqlpkTqvHsVNX40ImIKjdbW1tdh0BERERERERaIAiARAAkktxUnVKp1GiyZqo8OBKWiKiSksvlMDIy4sRcRERERERElZxSmVsSFkqFuM7NzU1n8ZD2cSQsEVElNmDAAKSnpyM7WwGlUskELBERERERURVgYGCAfv366ToM7ROEirOUMyZhiYgqsYCAAHh6ekLQwRsIERERERERaV+tWrWwZcsWliOoYgQlh00RVUhdu3ZFq1atsGLFCgC59T99fX3h6+tbJv0lJCSgcePGuHLlClq1alUmfZS1DRs2YNeuXTh69KiuQym1QYMGoW3btpg2bVoJ97xcJvHoRHIsYOGo6yiI6FV8XhIRVU58/abywseaVijDl0Houk3XYZSpf1wa6zoEkdXNu+XaH2vCUoXl7e2NzZs3AwD09fVhaWkJV1dXDB48GN7e3mKx6orC29sbycnJ2L9/f5m0f/HiRcjl8jJpu6R27NiBjz76CBMmTMDXX3+t63AAAOnp6ZgzZw52794trgsMDERQUBAAQE9PDxYWFnBxcUG/fv3w8ccfw9DQsEA748ePx/r167Fz504MGDCg3OLPM3v2bLz11lsYM2YMzM3NNdrH19cXYWFhLEVARERERERU6TlCKpUiKCgI/fv313UwpEUVK4tFlI+npyeSkpKQkJCAw4cPo1u3bpgyZQp69eqF7OxsXYdXKllZWaXaz8rKCsbGxlqOpnQ2bNiAGTNmYMeOHUhPT9d1OACAH3/8EWZmZujUqZPK+mbNmiEpKQmJiYk4ceIEBgwYgIULF6Jjx454/vy5yrYvXrzAzp07MWPGDGzcuLE8wxc1b94cTZs2xffff6/R9sHBwTh8+DATsERERERERFVEVlYWZs2ahbi4OF2HQlrEJCxVaIaGhrC2tka9evXQunVrzJo1CwcOHMDhw4cRGhoqbpecnIwxY8bAysoKZmZmePvttxEVFaXS1s8//4y2bdtCJpOhVq1a+OCDD8TbMjIy4Ofnh3r16kEul6N9+/YIDw8Xbw8NDYWFhQWOHDkCZ2dnmJiYiAliIHfE5ebNm3HgwAEIggBBEBAeHo6EhAQIgoBdu3ahS5cukMlk2LZtGx4/fozBgwejXr16MDY2RosWLbBjx44iz4Wtra1YmiA0NFTs59UlMDBQ3H79+vVwdnaGTCaDk5MT1qxZo9LehQsX4ObmBplMBnd3d1y5ckWj++Tu3bs4c+YMPvvsMzg4OGDv3r0qt+edq/3798Pe3h4ymQweHh74888/xW0CAwPRqlUrrFu3Dg0aNICxsTG8vLzw7NkzcZvw8HC0a9cOcrkcFhYW6NSpE+7du1doXDt37kTv3r0LrNfX14e1tTXq1q2LFi1a4JNPPsHJkydx/fp1LFq0SGXb3bt3w8XFBZ999hl+//13lZiB3NHOffv2RVBQkPhYmzBhAjIzM8VtunbtismTJ2Py5MkwNzdHrVq1MGfOHJUk6Zo1a8RzU6dOHXz44Ycq/fTu3Rs7d+4s9FjzxyyTyaCvLxEfB0RERERERFT5hYSE6DoErRMkQoVZyhuTsFTpvP3222jZsqVK8m/AgAF49OgRDh8+jMuXL6N169Z455138OTJEwDAoUOH8MEHH6Bnz564cuUKjh8/jnbt2on7T548GWfPnsXOnTtx9epVDBgwAJ6eniq/Or148QJLlizB1q1b8fvvvyMxMRF+fn4AAD8/P3h5eYmJ2aSkJHTs2FHc97PPPsOUKVMQHR0NDw8PpKeno02bNjh06BCuX7+OcePGYdiwYbhw4YJG52DgwIFiP0lJSdixYwf09fXFUaDbtm3D3LlzERwcjOjoaHzxxReYM2eOWN4hJSUFvXr1gouLCy5fvozAwEDxWIqzadMmvPfeezA3N8dHH32EDRs2FNjmxYsXCA4OxpYtWxAREYHk5GQMGjRIZZvbt2/jhx9+wM8//4ywsDBcuXIFEydOBABkZ2ejb9++6NKlC65evYqzZ89i3LhxRSYYT58+DXd3d42OwcnJCT169CiQQN6wYQM++ugjmJubo0ePHiqJ/jzHjx9HdHQ0wsPDsWPHDuzdu1cseZBn8+bN0NfXx4ULF7By5UosW7YM69evBwBcunQJPj4+mD9/PmJjYxEWFoa33npLZf927drhwoULyMjIKPI4UlNTkZaWhvT0dGRnK6BUKjkiloiIiIiIqJKSSARIJBJxiYmJ0XVIpEWsCUuVkpOTE65evQogN/l24cIFPHr0SKzxuWTJEuzfvx8//vgjxo0bh+DgYAwaNEglWdayZUsAQGJiIjZt2oTExETUrVsXQG5SNSwsDJs2bcIXX3wBIPdygG+++QZNmzYFkJu4nT9/PgDAxMQERkZGyMjIgLW1dYF4fX190a9fP5V1ryY9P/nkExw5cgQ//PCDSnK4MEZGRjAyMgIAxMfHY9KkSfjiiy/w7rvvAgDmzZuHpUuXin02btwYN2/exLp16zBixAhs374dCoUCGzZsgEwmQ7NmzXD//n18/PHHRfarUCgQGhqKr776CkDuJFLTpk3D3bt30bjxy+LaWVlZWL16Ndq3bw8gNynp7OyMCxcuiMeXnp6OLVu2oF69egCAr776Cu+99x6WLl0KAwMDPHv2DL169RLPt7Ozc6FxJScn49mzZ+L9pwknJyeVCbzi4uJw7tw5MTH70UcfYerUqZg9e7ZK8tfAwAAbN26EsbExmjVrhvnz52P69OlYsGCBWKe4QYMGWL58OQRBgKOjI65du4bly5dj7NixSExMhFwuR69evWBqaopGjRrBzc1NJba6desiMzMTDx48QKNGjQrEnpGRgYyMDL4hExERERERVSG5Y2peDqxJTU3VWSykfRwJS5WSUqkUE2NRUVFISUlBzZo1YWJiIi53795FfHw8ACAyMhLvvPOO2rauXbuGnJwcODg4qOx/8uRJcX8AMDY2FhOCAGBjY4NHjx5pFG/+EZo5OTlYsGABWrRoAUtLS5iYmODIkSNITEws0XnIS1S+9957mD59OoDcF+n4+HiMHj1a5Xg+//xz8Xiio6Ph6uoKmUwmttWhQ4di+zt27BhSU1PRs2dPAECtWrXw7rvvFqifqq+vj7Zt24p/Ozk5wcLCAtHR0eK6hg0bignYvP4VCgViY2NhaWkJb29veHh4oHfv3li5cqVY+kGdtLQ0AFA5nuK8+hgCgI0bN8LDwwO1atUCAPTs2RPPnj3Db7/9prJfy5YtVWrzdujQASkpKSqlC9544w2Vtjt06IC4uDjk5OTg3XffRaNGjdCkSRMMGzYM27Ztw4sXL1T6yEuw51+fZ+HChTA3N0fnzp01Pl4iIiIiIiIiXROEirOUN46EpUopOjpaHHmZkpICGxsblRqueSwsLAC8TGqpk5KSAj09PVy+fBl6enoqt5mYmIj/l0qlKrcJgqDxpd9yuVzl7y+//BIrV67EihUr0KJFC8jlcvj6+qrUFi1OTk4OBg4cCDMzM3z77bcqxwMA3333nTgSNU/+4yupDRs24MmTJyrnU6FQ4OrVqwgKChJHgmrDpk2b4OPjg7CwMOzatQuzZ8/GsWPH8MYbbxTYtmbNmhAEAU+fPtW4/VcfQzk5Odi8eTMePHgAff2XL4s5OTnYuHFjoQn80jA1NcUff/yB8PBwHD16FHPnzkVgYCAuXrwoPl7zymhYWVmpbWPmzJmYOnUqXrx4gS5dumgtNiIiIiIiItKd3MTgy+xg/lwCVW5MwlKl89tvv+HatWv49NNPAQCtW7cWk2e2trZq93F1dcXx48cxcuTIAre5ubkhJycHjx49eq2RhQYGBsjJydFo24iICPTp0wcfffQRgNxE5q1bt+Di4qJxf59++imuXbuGS5cuqYwArVOnDurWrYs7d+5g6NChavd1dnbG1q1bkZ6eLu577ty5Ivt7/PgxDhw4gJ07d6JZs2bi+pycHLz55ps4evQoPD09AeTWdL106ZJYeiA2NhbJyckqJQUSExPx999/iyUEzp07B4lEAkdHR3EbNzc3uLm5YebMmejQoQO2b9+uNglrYGAAFxcX3Lx5E//73/+KPA4AiImJQVhYGGbOnAkA+OWXX/D8+XNcuXJFJVF9/fp1jBw5EsnJyWKCNCoqCmlpaWIi+ty5czAxMUGDBg3E/c6fP6/S37lz52Bvby+2ra+vj+7du6N79+6YN28eLCws8Ntvv4nlI65fv4769euLo3LzMzQ0hKGhIczMzGBkZASlUons7Ezk5OT+KMC6sERERERERJWPQqHEq+UInJycdBcMaR3LEVCFlpGRgQcPHuCvv/7CH3/8gS+++AJ9+vRBr169MHz4cABA9+7d0aFDB/Tt2xdHjx5FQkICzpw5g4CAAFy6dAlAbo3UHTt2YN68eYiOjsa1a9ewaNEiAICDgwOGDh2K4cOHY+/evbh79y4uXLiAhQsX4tChQxrHamtri6tXryI2Nhb//vsvsrKyCt3W3t4ex44dw5kzZxAdHY3x48fj4cOHGve1adMmrFmzBt988w0EQcCDBw/w4MEDcRRsUFAQFi5ciFWrVuHWrVu4du0aNm3ahGXLlgEAhgwZAkEQMHbsWNy8eRO//PILlixZUmSfW7duRc2aNeHl5YXmzZuLS8uWLdGzZ0+VCbqkUik++eQTnD9/HpcvX4a3tzfeeOMNlXq3MpkMI0aMQFRUFE6dOgUfHx94eXnB2toad+/excyZM3H27Fncu3cPR48eRVxcXJF1YT08PHD69OkC67Ozs/HgwQP8/fffuHbtGr766it06dIFrVq1Eks4bNiwAe+99x5atmypcmxeXl6wsLDAtm3bxPYyMzMxevRo8bzNmzcPkydPVhkFnJiYiKlTpyI2NhY7duzAV199hSlTpgAADh48iFWrViEyMhL37t3Dli1boFAoVJLPp06d0iiZDOROSseJuYiIiIiIiKoef39/XYegdYKk4izljSNhqUILCwuDjY0N9PX1UaNGDbRs2RKrVq3CiBEjxKSXIAj45ZdfEBAQgJEjR+Kff/6BtbU13nrrLdSpUwcA0LVrV+zevRsLFixASEgIzMzMVGak37RpEz7//HNMmzYNf/31F2rVqoU33ngDvXr10jjWsWPHIjw8HO7u7khJScGJEycKHZk7e/Zs3LlzBx4eHjA2Nsa4cePQt29fPHv2TKO+Tp48iZycHLz//vsq6+fNm4fAwECMGTMGxsbG+PLLLzF9+nTI5XK0aNECvr6+AHLLLPz888+YMGEC3Nzc4OLigkWLFqF///6F9rlx40Z88MEHKrVO8/Tv3x/Dhg3Dv//+CyC3fq6/vz+GDBmCv/76C507d1ZJ0gKAnZ0d+vXrh549e+LJkyfo1asX1qxZI+4fExODzZs34/Hjx7CxscGkSZMwfvz4QuMbPXo03N3d8ezZM5ibm4vrb9y4ARsbG+jp6cHc3BwuLi6YOXMmPv74YxgaGuLhw4c4dOgQtm/fXqBNiUSCDz74ABs2bMCkSZMAAO+88w7s7e3x1ltvISMjA4MHD0ZgYKDKfsOHD0daWhratWsHPT09TJkyBePGjQOQWyJj7969CAwMRHp6Ouzt7bFjxw5xdHF6ejr279+PsLCwQo/1VQEBAXj06BGOHDnCBCwREREREVEVIJVKERgYCAcHB12HQlokKPmtnYi0KDQ0FL6+vkhOTi50m8DAQOzfvx+RkZFa7XvAgAFo3bq1WGZA27y9vZGcnIz9+/cXuk3Xrl3RqlUrrFixolR9rF27Fvv27cPRo0dLuOflUvVHVKjkWMDCsfjtqpLqeMxERET0+vgZgrSqja4DKFNP3JoWv1E5sbwSX/xGWsRyBERUZXz55Zcqk6lVRlKpFF999ZWuw6CKIjm2fNt4ddvy/iKRHFt0rK/e9prnRXn3oPobND3m0vSvafyatK2NxwVRafHxR8XhY6R6Ku5+L8/HRVn0VVyb1SEBy+d28XiOqBgsR0BEVYatrS0++eQTXYfxWsaMGVPifXx9fREWFsZyBEQlUrAECRERERFRRSCVShEUFFRkyUCqfFiOgIioEgsODsaWLVt0HQYRERERERFp2cGDB2Fvb6/rMLTqaeuKU46gxh8sR0BERBravXs3ZDIZ9PUlEARB7cRpREREREREVPmEhIToOgTSIpYjICKqpFJTU5GWlqbrMIiIiIiIiEgLJBIBwMuBNTExMboLhrSOSVgiokoqISFB1yEQERERERGRluQWDH1ZNTQ1NVVnsZQVQVJ9r95kOQIiIiIiIiIiIiKiMsSRsERElZStra2uQyAiIiIiIiItyZ3i4+VIUblcrrNYSPuYhCUiqqTkcjmMjIygVCqRnZ2JnJzcy1aUSmUxexIREREREVFFo1Ao8Wo5AicnJ90FU0aEanxNfjU+dCKiym/AgAFIT09HdrYCSqWSCVgiIiIiIqIqwt/fX9chkBYxCUtEVIkFBATA09MTglB9i5sTERERERFVJVKpFMHBwXBwcNB1KKRFgpLDpoiIqoDLug6gakmOBSwcdR2FqooYExERERERaVkbXQdQpv5rb6/rEERm5+PKtT/WhCWiKsPb2xubN28GAOjr68PS0hKurq4YPHgwvL29IZFod/D/5s2bsXr1aty4cQN6enpo3bo1pk+fjl69emm1n+L4+voiLCyMpQiIiIiIiIiqAKlUiqCgIPTv31/XoZAWsRwBEVUpnp6eSEpKQkJCAg4fPoxu3bphypQp6NWrF7Kzs7XWj5+fH8aPH4+BAwfi6tWruHDhAt5880306dMHq1ev1lo/xQkODsbhw4eZgCUiIiIiIqoisrKyMGvWLMTFle9IzXIhqUBLOWMSloiqFENDQ1hbW6NevXpo3bo1Zs2ahQMHDuDw4cMIDQ0FACQnJ2PMmDGwsrKCmZkZ3n77bURFRQEAbt26BUEQEBMTo9Lu8uXL0bRpUwDAuXPnsHTpUnz55Zfw8/ODnZ0dnJ2dERwcDF9fX0ydOhV//vknACA0NBQWFhbYv38/7O3tIZPJ4OHhId4OAFFRUejWrRtMTU1hZmaGNm3a4NKlSxod7+7duyGTyaCvL4EgCKwNS0REREREVEWEhIToOgTSIiZhiajKe/vtt9GyZUvs3bsXADBgwAA8evQIhw8fxuXLl9G6dWu88847ePLkCRwcHODu7o5t27aptLFt2zYMGTIEALBjxw6YmJhg/PjxBfqaNm0asrKysGfPHnHdixcvEBwcjC1btiAiIgLJyckYNGiQePvQoUNRv359XLx4EZcvX8Znn30GqVRa7HGlpqYiLS0N6enpyM5WQKlUckQsERERERFRJSWRCJBIJOKSf3AQVW5MwhJRteDk5ISEhAScPn0aFy5cwO7du+Hu7g57e3ssWbIEFhYW+PHHHwHkJkV37Ngh7nvr1i1cvnwZQ4cOFf9u2rQpDAwMCvRTt25dmJmZ4datW+K6rKwsrF69Gh06dECbNm2wefNmnDlzBhcuXAAAJCYmonv37nBycoK9vT0GDBiAli1bFnosGRkZ+O+//3Djxg2tnBsiIiIiIiLSPaUS4uAapVKJ1NRUXYekdYJQcZbyxiQsEVULSqUSgiAgKioKKSkpqFmzJkxMTMTl7t27iI+PBwAMGjQICQkJOHfuHIDcUbCtW7eGk5OTSnua0tfXR9u2bcW/nZycYGFhgejoaADA1KlTMWbMGHTv3h0hISFiHIVZuHAhzM3N0blzZ41jICIiIiIiIiLdYRKWiKqF6OhoNG7cGCkpKbCxsUFkZKTKEhsbi+nTpwMArK2t8fbbb2P79u0AgO3bt4ujYAHAwcEBd+7cQWZmZoF+/v77b/z3339wcHDQOLbAwEDcuHED7733Hn777Te4uLhg3759hW4/c+ZMPHv2DPfu3dO4DyIiIiIiIqrYckdoCuIil8t1HRJpEZOwRFTl/fbbb7h27Rr69++P1q1b48GDB9DX14ednZ3KUqtWLXGfoUOHYteuXTh79izu3LmjUsN10KBBSElJwbp16wr0tWTJEkilUvTv319cl52drTLRVmxsLJKTk+Hs7Cyuc3BwwKeffoqjR4+iX79+2LRpU6HHY2hoCDMzM1hbW8PIyIgTcxEREREREVUBCoUSCoVCXF69GrOqECRChVlK6q+//sJHH32EmjVrwsjICC1atNB4Um0A0C9xj0REFVhGRgYePHiAnJwcPHz4EGFhYVi4cCF69eqF4cOHQyKRoEOHDujbty8WL14MBwcH/P333zh06BA++OADuLu7AwD69euHjz/+GB9//DG6deuGunXrin106NABU6ZMwfTp05GZmYm+ffsiKysL33//PVauXIkVK1agQYMG4vZSqRSffPIJVq1aBX19fUyePBlvvPEG2rVrh7S0NEyfPh0ffvghGjdujPv37+PixYsqSdyiDBgwAFu2bNHuSSQiIiIiIiKd8/f313UI9P+ePn2KTp06oVu3bjh8+DCsrKwQFxeHGjVqaNwGk7BEVKWEhYXBxsYG+vr6qFGjBlq2bIlVq1ZhxIgRkEhyB///8ssvCAgIwMiRI/HPP//A2toab731FurUqSO2Y2pqit69e+OHH37Axo0bC/SzYsUKuLq6Ys2aNZg9ezb09PTQunVr7N+/H71791bZ1tjYGP7+/hgyZAj++usvdO7cGRs2bAAA6Onp4fHjxxg+fDgePnyIWrVqoV+/fggKCtLoeAMCAvDo0SMcOXKkRHVqiYiIiIiIqGKSSqUIDAwsUZk7KluLFi1CgwYNVK5abdy4cYnaEJT81k5EVGZCQ0Ph6+uL5OTkMu7pchm3X80kxwIWjrqOQlVFjImIiIiIiLSsja4DKFOpb1WcxLL+sWvIyMhQWWdoaAhDQ8MC27q4uMDDwwP379/HyZMnUa9ePUycOBFjx47VvL/XjpiIiHTK19cXYWFhHAlLRERERERUBUilUgQFBWlcpo5KZ+HChQWuQp03bx4CAwMLbHvnzh2sXbsWU6dOxaxZs3Dx4kX4+PjAwMAAI0aM0Kg/joQlIipDZT0SNjg4mDVhiYiIiIiIqqCDBw/C3t5e12FoVWUdCWtgYAB3d3ecOXNGXOfj44OLFy/i7NmzGvUneb1wiYioKN7e3mVaimD37t2QyWTQ15dAEAQIQslneCQiIiIiIqKKJyQkRNchaJ8gVJjF0NAQZmZmKou6BCwA2NjYwMXFRWWds7MzEhMTNT50liMgIqqkUlNTkZaWpuswiIiIiIiISAskEgHAy4E1MTExuguGVHTq1AmxsbEq627duoVGjRpp3AaTsERElVRCQoKuQyAiIiIiIiItyS0Y+rJqaGpqqs5iKStCJb0m/9NPP0XHjh3xxRdfwMvLCxcuXMC3336Lb7/9VuM2KumhExEREREREREREZW9tm3bYt++fdixYweaN2+OBQsWYMWKFRg6dKjGbXAkLBFRJWVra6vrEIiIiIiIiEhLcqf4eFmOQC6X6ywWKqhXr17o1atXqfdnEpaIqJKSy+UwMjKCUqlEdnYmcnJyL1tRKpXF7ElEREREREQVjUKhxKvlCJycnHQXTBkRJNV3MmmWIyAiqsQGDBiA9PR0ZGcroFQqmYAlIiIiIiKqIvz9/XUdAmkRk7BERJVYQEAAPD09IQjV99dEIiIiIiKiqkQqlSI4OBgODg66DoW0SFBy2BQRURVwWdcBkLYlxwIWjrqOgoiIiIiIylUbXQdQptK7V5wSC7JfY8q1P46EJaJKKyEhAYIgIDIy8rXbiomJwRtvvAGZTIZWrVq9dnuVWnKsriNQobx7UNch6EZ1TcBq6/FXwR7HRESkZepe55Njq8frvy6PUdO+K+P9UBFi1kYMFeE4iEgtTsxFVELe3t7YvHlzgfUeHh4ICwvTQURVV2hoKEaOHAkAEAQBdevWxbvvvotFixahdu3apWrT29sbycnJ2L9/v8r6efPmQS6XIzY2FiYmJq8berny9fVFWFhYFa8Hu13XARAREREREZULqVSKoKAg9O/fX9ehkBYxCUtUCp6enti0aZPKOkNDQx1Fo3uZmZkwMDAok7bNzMwQGxsLhUKBqKgojBw5En///TeOHDmi1X7i4+Px3nvvoVGjRqVuoyzPQ2GCg4Nx+PDhcu2TiIiIiIiIyk5WVhZmzZoFV1dX2Nvb6zocrRIk1Xc+E5YjICoFQ0NDWFtbqyw1atQocp/79+9j8ODBsLS0hFwuh7u7O86fPy/evnbtWjRt2hQGBgZwdHTE1q1bVfYXBAHr1q1Dr169YGxsDGdnZ5w9exa3b99G165dIZfL0bFjR8THx4v7BAYGolWrVti4cSMaNmwIExMTTJw4ETk5OVi8eDGsra1Ru3ZtBAcHq/SVnJyMMWPGwMrKCmZmZnj77bcRFRVVoN3169ejcePGkMlk4n7jx49HnTp1IJPJ0Lx5cxw8+PJS8tOnT6Nz584wMjJCgwYN4OPjg9TU1CLPmyAIsLa2Rt26ddGjRw/4+Pjg119/RVpaWoFtc3JyMHr0aDRu3BhGRkZwdHTEypUrVeLevHkzDhw4AEEQIAgCwsPDIQgCLl++jPnz50MQBAQGBgIArl27hrfffhtGRkaoWbMmxo0bh5SUFLE9b29v9O3bF8HBwahbty4cHR3FEgk//PCDeKxt27bFrVu3cPHiRbi7u8PExAQ9evTAP//8I7YVHh6Odu3aQS6Xw8LCAp06dcK9e/eKPDcAsHv3bshkMujrS8Rj0iZJNX6DJCIiIiIi0qWQkBBdh0BaxJGwROUgJSUFXbp0Qb169fDTTz/B2toaf/zxBxQKBQBg3759mDJlClasWIHu3bvj4MGDGDlyJOrXr49u3bqJ7SxYsADLli3DsmXL4O/vjyFDhqBJkyaYOXMmGjZsiFGjRmHy5MkqIyPj4+Nx+PBhhIWFIT4+Hh9++CHu3LkDBwcHnDx5EmfOnMGoUaPQvXt3tG/fHgAwYMAAGBkZ4fDhwzA3N8e6devwzjvv4NatW7C0tAQA3L59G3v27MHevXuhp6cHhUKBHj164Pnz5/j+++/RtGlT3Lx5E3p6emIcnp6e+Pzzz7Fx40b8888/mDx5MiZPnlxgVHFRjIyMoFAokJ2dXeA2hUKB+vXrY/fu3ahZsybOnDmDcePGwcbGBl5eXvDz80N0dDT+++8/sU9LS0skJSWhe/fu8PT0hJ+fH0xMTJCamgoPDw906NABFy9exKNHjzBmzBhMnjwZoaGhYp/Hjx+HmZkZjh07phLLvHnzsGLFCvF+GTJkCExNTbFy5UoYGxvDy8sLc+fOxdq1a5GdnY2+ffti7Nix2LFjBzIzM3HhwoViE6qpqalqk9HapFBU5RIHREREREREFUfuIJiX3wNjYsp34qhyUY3H+TAJS1QKBw8eLFA3dNasWZg1a5ba7bdv345//vkHFy9eFJOYdnZ24u1LliyBt7c3Jk6cCACYOnUqzp07hyVLlqgkYUeOHAkvLy8AgL+/Pzp06IA5c+bAw8MDADBlyhSxhmoehUKBjRs3wtTUFC4uLujWrRtiY2Pxyy+/QCKRwNHREYsWLcKJEyfQvn17nD59GhcuXMCjR4/EEgtLlizB/v378eOPP2LcuHEAci+937JlC6ysrAAAR48exYULFxAdHQ0HBwcAQJMmTcQ4Fi5ciKFDh8LX1xcAYG9vj1WrVqFLly5Yu3atOJq2KHFxcfjmm2/g7u4OU1NTPH78WOX2vLo5eRo3boyzZ8/ihx9+gJeXF0xMTGBkZISMjAxYW1uL21lbW0NfXx8mJibi+u+++w7p6enYsmUL5HI5AGD16tXo3bs3Fi1ahDp16gAA5HI51q9fL5YhSEhIAAD4+fmp3C+DBw/G8ePH0alTJwDA6NGjxWTuf//9h2fPnqFXr15o2rQpAMDZ2bnQ85CRkYGMjIyq+YZMRERERERUTeVO8/FyIExxV45S5cJyBESl0K1bN0RGRqosEyZMAABMmDABJiYm4gIAkZGRcHNzExOw+UVHR4vJuTydOnVCdHS0yjpXV1fx/3lJwBYtWqisS09Px3///Seus7W1hampqco2Li4ukEgkKusePXoEAIiKikJKSgpq1qypchx3795VKXXQqFEjMQGbd4z169cXE7D5RUVFITQ0VKVNDw8PKBQK3L17V+0+APDs2TOYmJjA2NgYjo6OqFOnDrZt21bo9l9//TXatGkDKysrmJiY4Ntvv0ViYmKh2xcmOjoaLVu2FBOwQO59olAoEBv7csbRFi1aqK0Dq8l9lXfOLS0t4e3tDQ8PD/Tu3RsrV65EUlJSobEtXLgQ5ubm6Ny5c4mPi4iIiIiIiIjKH0fCEpWCXC5XGcn6qvnz58PPz09lnZGRkVb6lUql4v/zLlVXty6vzEH+2/O2Ubcub5+UlBTY2NggPDy8QP8WFhbi/19NTgLFH2NKSgrGjx8PHx+fArc1bNiw0P1MTU3xxx9/QCKRwMbGpsh+du7cCT8/PyxduhQdOnSAqakpvvzyS5Xau9qW/zzk0eS+evV+2rRpE3x8fBAWFoZdu3Zh9uzZOHbsGN54440Cbc+cORNTp07Fixcv0KVLF20dChEREREREelQ7lfHl9frF/Z9szITqvFwUCZhibSsdu3aqF27tso6V1dXrF+/Hk+ePFE7GtbZ2RkREREYMWKEuC4iIgIuLi5lHm9+rVu3xoMHD6Cvrw9bW1uN93N1dcX9+/dx69YttaNhW7dujZs3bxaavC6MRCLReJ+IiAh07NhRLOsAQGX0LgAYGBggJyen2LacnZ0RGhqK1NRU8Y0vIiJCLOFQFtzc3ODm5oaZM2eiQ4cO2L59u9okrKGhIQwNDWFmZgYjIyMolUpkZ2ciJyf3shWlUnt1XCUSgXVhiYiIiIiIykHud6+X37+cnJx0FwxpXTXOPxOVXkZGBh48eKCy/Pvvv4VuP3jwYFhbW6Nv376IiIjAnTt3sGfPHpw9exYAMH36dISGhmLt2rWIi4vDsmXLsHfv3gIjastD9+7d0aFDB/Tt2xdHjx5FQkICzpw5g4CAAFy6dKnQ/bp06YK33noL/fv3x7Fjx3D37l1xQjAgt4btmTNnMHnyZERGRiIuLg4HDhzA5MmTtRa7vb09Ll26hCNHjuDWrVuYM2cOLl68qLKNra0trl69itjYWPz777/IyspS29bQoUMhk8kwYsQIXL9+HSdOnMAnn3yCYcOGieUFtOXu3buYOXMmzp49i3v37uHo0aOIi4srsi5sngEDBiA9PR3Z2QoolUqtJmABTsxFRERERESkK/7+/roOgbSISViiUggLC4ONjY3K8uabbxa6vYGBAY4ePYratWujZ8+eaNGiBUJCQqCnpwcA6Nu3L1auXIklS5agWbNmWLduHTZt2oSuXbuW0xG9JAgCfvnlF7z11lsYOXIkHBwcMGjQINy7d6/Y5OOePXvQtm1bDB48GC4uLpgxY4Y46tTV1RUnT57ErVu30LlzZ7i5uWHu3LmoW7eu1mIfP348+vXrh4EDB6J9+/Z4/PixyqhYABg7diwcHR3h7u4OKysrREREqG3L2NgYR44cwZMnT9C2bVt8+OGHeOedd7B69WqtxftqXzExMejfvz8cHBwwbtw4TJo0CePHjy9234CAAHh6eoolD4iIiIiIiKhyk0qlCA4OLnTOlcpMkAgVZin3Y1dqe9gUERHpwGVdB0DalBwLWJRN2YsKhcdJRJoq7fOIzz8iqsiq4mtUVTymctdG1wGUqaz3yr/sYmGkh26Wa3+sCUtEVIldvHgRQUFBuH37ttZLERAREREREVH5k0qlCAoKQv/+/XUdCmkRyxEQEVViv//+OxOwREREREREVUhWVhZmzZqFuLg4XYeidYJQcZbyxiQsEVEldu7cOVhaWkJfP/flnKVhiYiIiIiIqoaQkBBdh0BaxHIERESVVGZmJq5fvw6FQiGu44BYIiIiIiKiykkiEQC8HFkTExOju2BI65iEJSKqpJ4+faqSgCUiIiIiIqLKK3dQzcuRNampqTqLpawIkup7+SbLERARERERERERERGVIY6EJSKqpGrUqAGJRMLRsERERERERFVA7hwfL0eKyuVyncVSZqrxcNBqfOhERJWbgYEBmjdvjpo1a3JiLiIiIiIiokpOoVBCoVCIi5OTk65DIi1iEpaIqBIbMmQInj59iuzs3NGwnJiLiIiIiIioavD399d1CKRFLEdARFSJ1a1bl+UIiIiIiIiIqhCpVIrAwEA4ODjoOhTtq8YTcwlKJcdNEZVG165d0apVK6xYsULXoYgSEhLQuHFjXLlyBa1atdJoH29vbyQnJ2P//v1lGltplOZ4qq/Lug6AtCk5FrBw1HUUZY/HSUSaKu3ziM8/IqrIquJrVFU8pnLXRtcBlKmcfs11HYJIb+/1cu2PI2GJiuDt7Y3NmzcXWB8XF4e9e/dCKpXqIKrCNWjQAElJSahVq5ZW2/3uu++wevVqxMfHQ19fH40bN4aXlxdmzpyp1X7yK6vjKan79++jSZMmcHBwwPXr5fsirQlfX1+EhYWBv6kRERERERFVfoaGhpg3bx769++v61BIi1gTlqgYnp6eSEpKUlkaN24MS0tLmJqa6jo8FXp6erC2toa+vvZ+X9m4cSN8fX3h4+ODyMhIREREYMaMGUhJSXmtdrOysordpiyOpzRCQ0Ph5eWF//77D+fPn9dpLPkFBwfj8OHDTMASERERERFVEZmZmZg1axbi4uJ0HYr2SSrQUs6YhCUqhqGhIaytrVUWPT09dO3aFb6+vuJ2tra2+OKLLzBq1CiYmpqiYcOG+Pbbb1Xa8vf3h4ODA4yNjdGkSRPMmTNHJRkZGBiIVq1aYevWrbC1tYW5uTkGDRqE58+fi9soFAosXrwYdnZ2MDQ0RMOGDREcHAwg9/J9QRAQGRkJAMjJycHo0aPRuHFjGBkZwdHREStXrizR8f/000/w8vLC6NGjYWdnh2bNmmHw4MFin3nWr18PZ2dnyGQyODk5Yc2aNeJteXHt2rULXbp0gUwmw9q1a2FkZITDhw+rtLNv3z6YmprixYsXBY4HAG7cuIFevXrBzMwMpqam6Ny5M+Lj4zWKIzMzE5MnT4aNjQ1kMhkaNWqEhQsXFnn8SqUSmzZtwrBhwzBkyBBs2LBB5fa8GHfu3ImOHTtCJpOhefPmOHnypLhNeHg4BEHAoUOH4OrqCplMhjfeeENlVO29e/fQu3dv1KhRA3K5HM2aNcMvv/xSZGwAsHv3bshkMujrSyAIAgSh+tbXISIiIiIiqgr09PQgCAJCQkJ0HQppEcsREGnR0qVLsWDBAsyaNQs//vgjPv74Y3Tp0gWOjrk1cUxNTREaGoq6devi2rVrGDt2LExNTTFjxgyxjfj4eOzfvx8HDx7E06dP4eXlhZCQEDHpOXPmTHz33XdYvnw53nzzTSQlJSEmJkZtPAqFAvXr18fu3btRs2ZNnDlzBuPGjYONjQ28vLw0OiZra2ucPHkS9+7dQ6NGjdRus23bNsydOxerV6+Gm5sbrly5grFjx0Iul2PEiBHidp999hmWLl0KNzc3yGQynDp1Ctu3b0ePHj1U2urbty+MjY0L9PPXX3/hrbfeQteuXfHbb7/BzMwMERERyM7O1iiOVatW4aeffsIPP/yAhg0b4s8//8Sff/5Z5PGfOHECL168QPfu3VGvXj107NgRy5cvh1wuV9lu+vTpWLFiBVxcXLBs2TL07t0bd+/eRc2aNVW2WblyJaytrTFr1iz07t0bt27dglQqxaRJk5CZmYnff/8dcrkcN2/ehImJSZGxpaamIi0trchtiIiIiIiIqHIQBEAQJNDT04O+vn6h3/WpcmISlqgYBw8eVEmG9ejRA7t371a7bc+ePTFx4kQAuaNely9fjhMnTohJ2NmzZ4vb2traws/PDzt37lRJwioUCoSGhoqlDoYNG4bjx48jODgYz58/x8qVK7F69Woxudm0aVO8+eabauORSqUICgoS/27cuDHOnj2LH374QeMk7Lx589CvXz/Y2trCwcEBHTp0QM+ePfHhhx9CIpGI2yxduhT9+vUT+7l58ybWrVunkoT19fUVtwGAoUOHYtiwYXjx4gWMjY3x33//4dChQ9i3b5/aWL7++muYm5tj586dYj3eV2eLLC6OxMRE2Nvb480334QgCIUmlV+1YcMGDBo0CHp6emjevDmaNGmC3bt3w9vbW2W7yZMni/V61q5di7CwMGzYsEHlvp03bx7effddAMDmzZtRv3597Nu3D15eXkhMTET//v3RokULAECTJk0KjSkjIwMZGRl8QyYiIiIiIqpCcqvMKZGTkwOpVIrU1FRdh6R9kup79SbLERAVo1u3boiMjBSXVatWFbqtq6ur+H9BEGBtbY1Hjx6J63bt2oVOnTrB2toaJiYmmD17NhITE1XasLW1Vak1a2NjI7YRHR2NjIwMvPPOOxrH//XXX6NNmzawsrKCiYkJvv322wJ9FsXGxgZnz57FtWvXMGXKFGRnZ2PEiBHw9PSEQqFAamoq4uPjMXr0aJiYmIjL559/rlImAADc3d1V/u7ZsyekUil++uknAMCePXtgZmaG7t27q40lMjISnTt3VjshmiZxeHt7IzIyEo6OjvDx8cHRo0eLPPbk5GTs3bsXH330kbjuo48+KlCSAAA6dOgg/l9fXx/u7u6Ijo4udBtLS0s4OjqK2/j4+ODzzz9Hp06dMG/ePFy9erXQuBYuXAhzc3N07ty5yPiJiIiIiIiIqGJgEpaoGHK5HHZ2duJiY2NT6Lb5k4OCIEChUAAAzp49i6FDh6Jnz544ePAgrly5goCAAGRmZmrchpGRUYli37lzJ/z8/DB69GgcPXoUkZGRGDlyZIE+NdG8eXNMnDgR33//PY4dO4Zjx47h5MmT4gRd3333nUqy+vr16zh37pxKG/kv4TcwMMCHH36I7du3AwC2b9+OgQMHFjoRV1HHr0kcrVu3xt27d7FgwQKkpaXBy8sLH374YaFtbt++Henp6Wjfvj309fWhr68Pf39/nD59Grdu3SrmjJXMmDFjcOfOHQwbNgzXrl2Du7s7vvrqK7Xbzpw5E8+ePcO9e/e0GgMRERERERHpTm45AgF6enpQKpUFvkNXCbqejIsTcxFVfWfOnEGjRo0QEBAAd3d32NvblziJZm9vDyMjIxw/flyj7SMiItCxY0dMnDgRbm5usLOzKzA6tTRcXFwA5I4+rVOnDurWrYs7d+6oJKvt7OzQuHHjYtsaOnQowsLCcOPGDfz2228YOnRoodu6urri1KlTKpOZ5dE0DjMzMwwcOBDfffcddu3ahT179uDJkydq+9uwYQOmTZumktSNiopC586dsXHjRpVtX004Z2dn4/Lly3B2di50m6dPn+LWrVsq2zRo0AATJkzA3r17MW3aNHz33Xdq4zI0NISZmRmsra1hZGTEibmIiIiIiIiqAKUyt0RhTk4OMjIy4OTkpOuQSItYE5aonNjb2yMxMRE7d+5E27Zti6x9WhiZTAZ/f3/MmDEDBgYG6NSpE/755x/cuHEDo0ePVtvnli1bcOTIETRu3Bhbt27FxYsXNUqO5vn4449Rt25dvP3226hfvz6SkpLw+eefw8rKSry8PigoCD4+PjA3N4enpycyMjJw6dIlPH36FFOnTi2y/bfeegvW1tYYOnQoGjdujPbt2xe67eTJk/HVV19h0KBBmDlzJszNzXHu3Dm0a9cOjo6OxcaxbNky2NjYwM3NDRKJBLt374a1tTUsLCwK9BUZGYk//vgD27ZtK/DGN3jwYMyfPx+ff/65uO7rr7+Gvb09nJ2dsXz5cjx9+hSjRo1S2W/+/PmoWbMm6tSpg4CAANSqVQt9+/YFkFsvt0ePHnBwcMDTp09x4sSJAklcdQYMGIAtW7YUux0RERERERFVDjk5OVAqlfD399d1KKRFHAlLVE7ef/99fPrpp5g8eTJatWqFM2fOYM6cOSVuZ86cOZg2bRrmzp0LZ2dnDBw4UKXu7KvGjx+Pfv36YeDAgWjfvj0eP34sThymqe7du+PcuXMYMGAAHBwc0L9/f8hkMhw/fhw1a9YEkHsp/fr167Fp0ya0aNECXbp0QWhoqEbJXkEQMHjwYERFRRU5ChYAatasid9++w0pKSno0qUL2rRpg++++04s4VBcHKampli8eDHc3d3Rtm1bJCQk4JdffhEnGHvVhg0b4OLiovaXxw8++ACPHj3CL7/8Iq4LCQlBSEgIWrZsidOnT+Onn35CrVq1VPYLCQnBlClT0KZNGzx48AA///wzDAwMAOS+yU6aNAnOzs7w9PSEg4MD1qxZU+z5CwgIgKenJ0fAEhERERERVRGCICA4OFhlIuoqQyJUnKWcCUpl7txrRERUcgkJCWjcuDGuXLmCVq1aqd0mPDwc3bp1w9OnT9WOutWOyyXbPDkWsHB8+X/g5d8l2fd1FdWWNvsh0hQfd0RUUZXX61NeP+X9elhcf5Xp9bksYy3r81CZzrOuVeVzVZWPTRO6On6x3zbl33c5yhniWvxG5URve+ETYpcFjoQlIqou8pKtgOqHCgvHkn3I0OYHkqLaKkk/rx4bUWGPB00eJ9X5CwfA51I1prx7UNchqCrPx6K2+tJmzOraKupHS23K6yd/f2V5n2iS8KhMr89lGWtZn4dX29fGfV7ZnsslaaMiPCbL6vyW9bHlxa2Lzx0V+fNgRXhMUZliTVgiokrO19cXYWFh4IUNRET0erbrOgAiIiICIJVKERQUhP79++s6FO3TQRmAioLlCIiIKrHg4GBOzEVERERERFQFHTx4EPb29roOQ6tyPmqp6xBEet9HlWt/LEdARFSJ7d69GzKZDPr6EgiCwAm6AEiq8S+rRERERERUdYSEhOg6BNIiliMgIqqkUlNTkZaWpuswKhyFghd4EBERERFR5ZM7oOTloJKYmBjdBVNWqvFwUCZhiYgqqYSEBF2HQERERERERFqSWzD05aCS1NRUncVC2leN889EREREREREREREZY8jYYmIKilbW1tdh0BERERERERakjvFx8tyBHK5XGexlJlqPIcHk7BERJWUXC6HkZERlEolsrMzkZOTe9mKUlm9a6JKJALrwhIRERERUaWT+z3m5XcZJycn3QVDWsdyBEREldiAAQOQnp6O7GwFlEpltU/AApyYi4iIiIiIqgZ/f39dh6B9kgq0lDMmYYmIKrGAgAB4enpCEKrvJR1ERERERERViVQqRXBwMBwcHHQdCmmRoOSwKSJ6DYIgYN++fejbt6+uQyk3CQkJaNy4Ma5cuYJWrVrpOpz/d1nXARARUVWQHAtYOOo6CiI+FomoGmuj6wDKVM6oVroOQaS3MbJc+2NNWCJS68GDB1i4cCEOHTqE+/fvw9zcHHZ2dvjoo48wYsQIGBsbAwCSkpJQo0YNACVPTm7evBmrV6/GjRs3oKenh9atW2P69Ono1atXWR5aiXh7eyM5ORn79+8X1zVo0ABJSUmoVauW7gJ7ha+vL8LCwliKgIiIiIiIqAqQSqUICgpC//79dR2K9lXjiblYjoCICrhz5w7c3Nxw9OhRfPHFF7hy5QrOnj2LGTNm4ODBg/j111/Fba2trWFoaFjiPvz8/DB+/HgMHDgQV69exYULF/Dmm2+iT58+WL16tTYPR62srKxS76unpwdra2vo6+v+d6zg4GAcPnyYCVgiIiIiIqIqIisrC7NmzUJcXJyuQyEtYhKWiAqYOHEi9PX1cenSJXh5ecHZ2RlNmjRBnz59cOjQIfTu3VvcVhAEcZRo48aNAQBubm4QBAFdu3ZV2/65c+ewdOlSfPnll/Dz84OdnR2cnZ0RHBwMX19fTJ06FX/++ScAIDQ0FBYWFti/fz/s7e0hk8ng4eEh3p7nwIEDaN26NWQyGZo0aYKgoCBkZ2erxLl27Vq8//77kMvlCA4ORk5ODkaPHo3GjRvDyMgIjo6OWLlypbhPYGAgNm/ejAMHDkAQBAiCgPDwcCQkJEAQBERGRorbnjx5Eu3atYOhoSFsbGzw2WefqfTftWtX+Pj4YMaMGbC0tIS1tTUCAwPF25VKJQIDA9GwYUMYGhqibt268PHxKfa+2r17N2QyGfT1JWKMREREREREVPmFhIToOgTSIiZhiUjF48ePcfToUUyaNAlyuVztNoUl+i5cuAAA+PXXX5GUlIS9e/eq3W7Hjh0wMTHB+PHjC9w2bdo0ZGVlYc+ePeK6Fy9eIDg4GFu2bEFERASSk5MxaNAg8fZTp05h+PDhmDJlCm7evIl169YhNDQUwcHBKm0HBgbigw8+wLVr1zBq1CgoFArUr18fu3fvxs2bNzF37lzMmjULP/zwA4Dc0bpeXl7w9PREUlISkpKS0LFjxwIx//XXX+jZsyfatm2LqKgorF27Fhs2bMDnn3+ust3mzZshl8tx/vx5LF68GPPnz8exY8cAAHv27MHy5cuxbt06xMXFYf/+/WjRooXa85cnNTUVaWlpSE9PR3a2AkqlkiNiiYiIiIiIKimJRIBEIhGXmJgYXYekfUIFWsqZ7q+lJaIK5fbt21AqlXB0VJ0IoVatWkhPTwcATJo0CYsWLSqwr5WVFQCgZs2asLa2LrSPW7duoWnTpjAwMChwW926dWFmZoZbt26J67KysrB69Wq0b98eQG4y09nZGRcuXEC7du0QFBSEzz77DCNGjAAANGnSBAsWLMCMGTMwb948sZ0hQ4Zg5MiRKv0FBQWJ/2/cuDHOnj2LH374AV5eXjAxMYGRkREyMjKKPJ41a9agQYMGWL16NQRBgJOTE/7++2/4+/tj7ty5kEhyf+9ydXUV47G3t8fq1atx/PhxvPvuu0hMTIS1tTW6d+8OqVSKhg0bol27dmr7y8jIQEZGRtV8QyYiIiIiIqqmcsfUvBxYk5qaqrNYSPs4EpaINHLhwgVERkaiWbNmyMjIeO32SjJiU19fH23bthX/dnJygoWFBaKjowEAUVFRmD9/PkxMTMRl7NixSEpKwosXL8T93N3dC7T99ddfo02bNrCysoKJiQm+/fZbJCYmluhYoqOj0aFDB5URwp06dUJKSgru378vrnN1dVXZz8bGBo8ePQIADBgwAGlpaWjSpAnGjh2Lffv2qZQzeNXChQthbm6Ozp07lyhOIiIiIiIiItINJmGJSIWdnR0EQUBsbKzK+iZNmsDOzg5GRkav3YeDgwPu3LmDzMzMArf9/fff+O+//+Dg4KBxeykpKQgKCkJkZKS4XLt2DXFxcZDJZOJ2+csr7Ny5E35+fhg9ejSOHj2KyMhIjBw5Um1c2iCVSlX+FgQBCoUCANCgQQPExsZizZo1MDIywsSJE/HWW2+pnUBs5syZePbsGe7du1cmcRIREREREVH5EwSIc30IglBoicBKTSJUnKW8D73ceySiCq1mzZp49913sXr16hJf+pBXXiAnJ6fI7QYNGoSUlBSsW7euwG1LliyBVCpF//79xXXZ2dm4dOmS+HdsbCySk5Ph7OwMAGjdujViY2NhZ2dXYMkrBaBOREQEOnbsiIkTJ8LNzQ12dnaIj48vcEzFHY+zszPOnj2rMro3IiICpqamqF+/fpH7vsrIyAi9e/fGqlWrEB4ejrNnz+LatWsFtjM0NISZmRmsra1hZGTEibmIiIiIiIiqAIVCCYVCIS5OTk66Dom0iElYIipgzZo1yM7Ohru7O3bt2oXo6GjExsbi+++/R0xMDPT09NTuV7t2bRgZGSEsLAwPHz7Es2fP1G7XoUMHTJkyBdOnT8fSpUsRHx+PmJgYzJ49GytXrsTSpUvRoEEDcXupVIpPPvkE58+fx+XLl+Ht7Y033nhDrJk6d+5cbNmyBUFBQbhx4waio6Oxc+dOzJ49u8jjtLe3x6VLl3DkyBHcunULc+bMwcWLF1W2sbW1xdWrVxEbG4t///1X7cjUiRMn4s8//8Qnn3yCmJgYHDhwAPPmzcPUqVOLTAK/KjQ0FBs2bMD169dx584dfP/99zAyMkKjRo2K3G/AgAGcmIuIiIiIiKgK8vf313UIpEVMwhJRAU2bNsWVK1fQvXt3zJw5Ey1btoS7uzu++uor+Pn5YcGCBWr309fXx6pVq7Bu3TrUrVsXffr0KbSPFStWYM2aNdixYweaN28Od3d3/P7779i/fz8++eQTlW2NjY3h7++PIUOGoFOnTjAxMcGuXbvE2z08PHDw4EEcPXoUbdu2xRtvvIHly5cXm8AcP348+vXrh4EDB6J9+/Z4/PgxJk6cqLLN2LFj4ejoCHd3d1hZWSEiIqJAO/Xq1cMvv/yCCxcuoGXLlpgwYQJGjx5dbBL4VRYWFvjuu+/QqVMnuLq64tdff8XPP/+MmjVrFrlfQEAAPD09OQKWiIiIiIioipBKpQgODi5Rmb5KQ9clCHRYjkBQctgUEVVgoaGh8PX1RXJysq5DqeAu6zoAorKTHAtYOOo6CqLKi88hIiKqjKrt+1cbXQdQpnI+rjjHp7e2fL9H65drb0REpHW+vr4ICwtjKQIiIiIiIqIqQCqVIigoSGWulCqjGl+TX40PnYio8gsODsbhw4eZgCUiIiIiIqoisrKyMGvWLMTFxek6FNIiliMgIqrEWrVqBaVSiezsTOTk5L6c82WdiIiIiIio8nvzzTexYcMGXYehVTmTKlA5gq9ZjoCIiDSQmpqKtLQ0XYdBREREREREWiCRCABeThgVExOju2DKig4mxKoomIQlIqqkEhISdB0CERERERERaUnuRY0vr2xMTU3VWSykfawJS0RERERERERERFSGOBKWiKiSsrW11XUIREREREREpCWCALxajkAul+sslrIiVOPhoNX40ImIKje5XA4jIyPIZDLo60sgCAIEofrW1yEiIiIiIqrMFAolFAqFuDg5Oek6JPp/gYGB4nfuvKWk9w+TsEREldiAAQOQnp6O7GwFlEollEpl8TsRERERERFRhefv76/rEOgVzZo1Q1JSkricPn26RPuzHAERUSUWEBCAR48e4ciRI0zAEhERERERVQFSqRSBgYFwcHDQdSjaJ6m8V2/q6+vD2tq69PtrMRYiqmDCw8PRrVs3PH36FBYWFoVuZ2trC19fX/j6+pZbbLoWERGBCRMmICYmBu+99x7279+v65BKbeXKlQAu6zoMorKTHAtYOOo6CqLKi88hIiKqjKrt+1cbXQdQbWRkZCAjI0NlnaGhIQwNDdVuHxcXh7p160Imk6FDhw5YuHAhGjZsqHF/TMISlTNvb28kJycXSPppmjB9HaGhofD19UVycnKZtF8ecnJy8OWXXyI0NBT37t2DkZER7O3tMXbsWIwZM0bjdqZOnYpWrVrh8OHDMDExQWBgIPbv34/IyMiyC76M+Pr6IiwsjCNhiYiIiIiIqoCaNWvim2++gaurq65D0b4KVBh14cKFCAoKUlk3b948BAYGFti2ffv2CA0NhaOjI5KSkhAUFITOnTvj+vXrMDU11ag/JmGJSCcyMzNhYGBQ4v2CgoKwbt06rF69Gu7u7vjvv/9w6dIlPH36tETtxMfHY8KECahfv36JY9CmrKwsSKXSUu8fHByMw4cPazEiIiIiIiIi0qXHjx/D29sbx44dQ82aNXUdTpU1c+ZMTJ06VWVdYaNge/ToIf7f1dUV7du3R6NGjfDDDz9g9OjRGvVXgfLPRJTf6dOn0blzZxgZGaFBgwbw8fFBamqqePvWrVvh7u4OU1NTWFtbY8iQIXj06JHatsLDwzFy5Eg8e/ZMnMnv1V93Xrx4gVGjRsHU1BQNGzbEt99+q7L//fv3MXjwYFhaWkIul8Pd3R3nz58HkJvQ7NOnD+rUqQMTExO0bdsWv/76q8r+tra2WLBgAYYPHw4zMzOMGzdOo2PM76effsLEiRMxYMAANG7cGC1btsTo0aPh5+cnbpORkQEfHx/Url0bMpkMb775Ji5evAgASEhIgCAIePz4MUaNGgVBEBAaGoqgoCBERUWJ5yY0NBR+fn7o1auX2O6KFSsgCALCwsLEdXZ2dli/fj0A4OLFi3j33XdRq1YtmJubo0uXLvjjjz9U4hcEAWvXrsX7778PuVyO4OBgAMCBAwfQunVryGQyNGnSBEFBQcjOzi70POTZvXs3ZDIZ9PUlYuzaoK/PtwciIiIi0pyWPoYS0f/LysrCnj17dB1GlWZoaAgzMzOVpbAkbH4WFhZwcHDA7du3Ne6P37KJKqj4+Hh4enqif//+uHr1Knbt2oXTp09j8uTJ4jZZWVlYsGABoqKisH//fiQkJMDb21ttex07dsSKFStgZmYmzuT3auJy6dKlcHd3x5UrVzBx4kR8/PHHiI2NBQCkpKSgS5cu+Ouvv/DTTz8hKioKM2bMgEKhEG/v2bMnjh8/jitXrsDT0xO9e/dGYmKiSgxLlixBy5YtceXKFcyZM0ejY8zP2toav/32G/75559Ct5kxYwb27NmDzZs3448//oCdnR08PDzw5MkTNGjQAElJSTAzM8OKFSuQlJSEgQMHYtq0aSozHQ4cOBBdunTB6dOnkZOTAwA4efIkatWqhfDwcADAX3/9hfj4eHTt2hUA8Pz5c4wYMQKnT5/GuXPnYG9vj549e+L58+cq8QUGBuKDDz7AtWvXMGrUKJw6dQrDhw/HlClTcPPmTaxbtw6hoaFigrYwqampSEtLQ3p6OrKzFVAqlVorSWBsLNNKO0RERERUPbAyFtHrEQRA8v+TVuUNsLly5YqOoyoDEqHiLK8hJSUF8fHxsLGx0XgfQckigkTlytvbG99//z1kMtUkV05ODtLT08WasGPGjIGenh7WrVsnbnP69Gl06dIFqampBfYHgEuXLqFt27Z4/vw5TExMCtSZLawmrK2tLTp37oytW7cCAJRKJaytrREUFIQJEybg22+/hZ+fHxISEmBpaanRcTZv3hwTJkwQE6q2trZwc3PDvn37xG1Kc4w3b97Ehx9+iNjYWDRr1gwdO3ZEnz59xEsDUlNTUaNGDYSGhmLIkCEAcpPVeZOPTZ8+HUDur1YrVqwQk9bqasImJyejZs2aOH/+PNq0aYNatWph+vTp2L9/P86dO4dt27bB398f9+/fV3sOFAoFLCwssH37dnFErSAI8PX1xfLly8XtunfvjnfeeQczZ84U133//feYMWMG/v777wLt5hUPj4mJwbBhwwq/E16DiYkMKSnpZdI2ERERERERFSQIgjiwRl9fHy4uLti9e7eOo9IuxfR2ug5BJPnygsbb+vn5oXfv3mjUqBH+/vtvzJs3D5GRkbh58yasrKw066+0gRJR6XXr1g2RkZEqS94l7XmioqIQGhoKExMTcfHw8IBCocDdu3cBAJcvX0bv3r3RsGFDmJqaokuXLgBQYASqJl4t+C0IAqytrcXSBpGRkXBzcys0AZuSkgI/Pz84OzvDwsICJiYmiI6OLhCHu7t7iY8xPxcXF1y/fh3nzp3DqFGj8OjRI/Tu3VuclCs+Ph5ZWVno1KmTuI9UKkW7du0QHR1donNiYWGBli1bIjw8HNeuXYOBgQHGjRuHK1euICUlBSdPnhTPOQA8fPgQY8eOhb29PczNzWFmZoaUlBSNzsP8+fNVzsPYsWORlJSEFy9eFIhr4cKFMDc3R+fOnUt0PERERERERERUcnklGh0dHeHl5YWaNWvi3LlzGidgAU7MRaQTcrkcdnZ2Kuvyj6ZMSUnB+PHj4ePjU2D/hg0bIjU1FR4eHvDw8MC2bdtgZWWFxMREeHh4IDMzs8Qx5Z8cShAEsdyAkZFRkfv6+fnh2LFjWLJkCezs7GBkZIQPP/ywQBxyubxEx1gYiUSCtm3bom3btvD19cX333+PYcOGISAgoMg4S6Nr164IDw+HoaEhunTpAktLSzg7O+P06dM4efIkpk2bJm47YsQIPH78GCtXrkSjRo1gaGiIDh06aHQegoKC0K9fvwL9qxsNnFc8/MWLFypJYG2SSPgbHRERERERUXkRhNxFqcz9Pq6np4datWrpOizte80yALqyc+fO126DSViiCqp169a4efNmgWRtnmvXruHx48cICQlBgwYNAOSWIyiKgYGBWN+0JFxdXbF+/Xo8efJE7WjYiIgIeHt744MPPgCQm1RMSEgott3ijlFTLi4uAHJLETRt2hQGBgaIiIhAo0aNAOSWI7h48SJ8fX0LbaOwc9OlSxds3LgR+vr68PT0BJCbmN2xYwdu3bol1oMFcs/DmjVr0LNnTwDAn3/+iX///bfY+Fu3bo3Y2FiNz4OhoaFYQNzIyAhKpRLZ2ZnIycm9bEUbVWZevGApAiIiIiLSXF7yiIhKR6l8+V0ub74PNzc3HUdF2sShTkQVlL+/P86cOYPJkycjMjIScXFxOHDggFhjtWHDhjAwMMBXX32FO3fu4KeffsKCBQuKbNPW1hYpKSk4fvw4/v33X7WXuqszePBgWFtbo2/fvoiIiMCdO3ewZ88enD17FgBgb2+PvXv3IjIyElFRURgyZIg4ivZ1jlGdDz/8EMuXL8f58+dx7949hIeHY9KkSXBwcICTkxPkcjk+/vhjTJ8+HWFhYbh58ybGjh2LFy9eYPTo0UWem7t37yIyMhL//vsvMjIyAABvvfUWnj9/joMHD4oJ165du2Lbtm2wsbGBg4OD2Ia9vT22bt2K6OhonD9/HkOHDi12FDEAzJ07F1u2bEFQUBBu3LiB6Oho7Ny5E7Nnzy523wEDBpTJxFzZ2cXff0REREREeZiAJdIuiUSCjh076joM0iImYYkqKFdXV5w8eRK3bt1C586d4ebmhrlz56Ju3boAACsrK4SGhmL37t1wcXFBSEgIlixZUmSbHTt2xIQJEzBw4EBYWVlh8eLFGsViYGCAo0ePonbt2ujZsydatGiBkJAQ6OnpAQCWLVuGGjVqoGPHjujduzc8PDzQunXr1z5GdTw8PPDzzz+jd+/ecHBwwIgRI+Dk5ISjR49CXz93cH9ISAj69++PYcOGoXXr1rh9+zaOHDmCGjVqFNpu//794enpiW7dusHKygo7duwAANSoUQMtWrSAlZUVnJycAOQmZhUKRYFSABs2bMDTp0/RunVrDBs2DD4+Pqhdu3ax58HDwwMHDx7E0aNH0bZtW7zxxhtYvny5OJK3KAEBAfD09IQgVM5LOoiIiIiIiKig9PR0fP/997oOQ/skFWgpZ4JSW8OmiIhIhy6/fhPJsYCFY/HryltFiIGoIinuOcHnTPU+B2Vx7NX5fFZE2rw/qvB9q7x7EELjXroOQzOV+X5Ijs3993XjL69zkNdPZT7npVHWx1vdzuerSnvsRe7X5rVCqugUM9vrOgSRZOH5cu2vVEnY1NTUAhPLEBGRLmkhCUtEREREREQ6xiRseSnvJGypJuaqU6cOvLy8MGrUKLz55pvajomIiErA19cXYWFhWqsHS0RERERERLojlUoRFBSE/v376zoU7ZNU31J6paqA8P333+PJkyd4++234eDggJCQEPz999/ajo2IiIoRHByMw4cPMwFLRERERERURWRlZWHWrFmIi4vTdSikRaVKwvbt2xf79+/HX3/9hQkTJmD79u1o1KgRevXqhb179yI7O1vbcRIRkRq7d++GTCaDvr4EgiBwgi4iIiIiIqIqIiQkRNchaJ+uJ+PS4cRcr9WllZUVpk6diqtXr2LZsmX49ddf8eGHH6Ju3bqYO3cuXrx4oa04iYgon9TUVKSlpSE9PR3Z2QoolUqOiCUiIiIiIqqkJBIBEolEXGJiYnQdEmlRqWrC5nn48CE2b96M0NBQ3Lt3Dx9++CFGjx6N+/fvY9GiRTh37hyOHj2qrViJiOgVCQkJug6BiIiIiIiItCR3TM3LgTWpqak6i4W0r1RJ2L1792LTpk04cuQIXFxcMHHiRHz00UewsLAQt+nYsSOcnZ21FScRERERERERERFVZtV4Yq5SJWFHjhyJwYMHIyIiAm3btlW7Td26dREQEPBawRERUeFsbW11HQIRERERERFpSe4UHy+TlHK5XGexkPaVOAmbnZ2NhQsXon///qhTp06h2xkZGWHevHmvFRwRERVOLpfDyMgISqUS2dmZyMnJvWyFdWGJiIiIiIgqH4VCiVfLETg5OekuGNK6Ek/Mpa+vDz8/P6Snp5dFPEREVAIDBgzgxFxERERERERVkL+/v65D0D5JBVrKWam6bNeuHa5cuaLtWIiIqIQCAgLg6ekJQai+dXWIiIiIiIiqEqlUiuDgYDg4OOg6FNKiUtWEnThxIqZNm4b79++jTZs2BWpUuLq6aiU4Inp9giBg37596Nu3b4XvOzAwEPv370dkZGSZxvXgwQMMGzYMZ86cgVQqRXJycpn2V9ZWrlwJ4LLa25ThyyB0nVqu8VQIybGAhWPZt1nafsoivvJsP39fgOb9lVVsee1q2n55nqPXVZlirUy0fV55P1VO1eF+K+nrtDb7fZ0+y+u9vKz6ep14dNUOla2q9PmvpKrzsRdHbextdBIKlb1SJWEHDRoEAPDx8RHXCYIApVIJQRCQk5OjneiIqjFvb28kJydj//79ug5FFB4ejm7duuHp06ewsLAodvukpCTUqFFDqzHs27cPixYtQnR0NBQKBRo2bIh3330XK1as0LiN5cuXIykpCZGRkTA3Ny/xcVU0vr6+CAsLK6IUwZByjYeIiIiIiIhKTyqVIigoCP3799d1KNonqb5XcZYqCXv37l1tx0FEVUhmZiYMDAxgbW2t1XaPHz+OgQMHIjg4GO+//z4EQcDNmzdx7NixErUTHx+PNm3awN7eHgBw8+ZNrcapqbzz9DqCg4Nx+PBhLUVEREREREREupaVlYVZs2bB1dVV/N5KlV+pasI2atSoyIWItK9r167w8fHBjBkzYGlpCWtrawQGBqpsExcXh7feegsymQwuLi4FkpPh4eEQBEHl8vvIyEgIgoCEhAQAwL1799C7d2/UqFEDcrkczZo1wy+//IKEhAR069YNAFCjRg0IggBvb28xtsmTJ8PX1xe1atWCh4cHgNwR8q+O5PX394eDgwOMjY3RpEkTzJkzB1lZWRqfg59//hmdOnXC9OnT4ejoCAcHB/Tt2xdff/21ynZr165F06ZNYWBgAEdHR2zdulW8zdbWFnv27MGWLVvEY1B3XAcPHoSFhYU4sj/vPH322WdiW2PGjMFHH30EAHj8+DEGDx6MevXqwdjYGC1atMCOHTtU4irsPF2/fh09evSAiYkJ6tSpg2HDhuHff//V6Jzs3r0bMpkM+voSCILA2rBEREREr0FfX08n/Uqq8cgwIipcSEiIrkPQPl1PxlXZJuYCckeSffLJJ+jevTu6d+8OHx8fxMfHazM2Ispn8+bNkMvlOH/+PBYvXoz58+eLiVaFQoF+/frBwMAA58+fxzfffFOqmRQnTZqEjIwM/P7777h27RoWLVoEExMTNGjQAHv27AEAxMbGIikp6f9rkb6MzcDAABEREfjmm2/Utm1qaorQ0FDcvHkTK1euxHfffYfly5drHJu1tTVu3LiB69evF7rNvn37MGXKFEybNg3Xr1/H+PHjMXLkSJw4cQIAcPHiRXh6esLLy0s8BnXH1blzZzx//lychPDkyZOoVasWwsPDxb5OnjyJrl27AgDS09PRpk0bHDp0CNevX8e4ceMwbNgwXLhwQSW+/OcpOTkZb7/9Ntzc3HDp0iWEhYXh4cOH8PLyKvZ8pKamIi0tDenp6cjOVkCpVBZRkoCIiIiIXqWnV/DrcHa2bkrrKRT8DEdU3UkkEshkBpBIJOISExOj67BIi0pVjuDIkSN4//330apVK3Tq1AkAEBERgWbNmuHnn3/Gu+++q9UgiSiXq6sr5s2bBwCwt7fH6tWrcfz4cbz77rv49ddfERMTgyNHjqBu3boAgC+++AI9evQoUR+JiYno378/WrRoAQBo0qSJeJulpSUAoHbt2gVqp9rb22Px4sVFtj179mzx/7a2tvDz88POnTsxY8YMjWL75JNPcOrUKbRo0QKNGjXCG2+8gf/9738YOnQoDA0NAQBLliyBt7c3Jk6cCACYOnUqzp07hyVLlqBbt26wsrKCoaEhjIyMxHIJhR1Xq1atEB4eDnd3d4SHh+PTTz9FUFAQUlJS8OzZM9y+fRtdunQBANSrVw9+fn4qsR45cgQ//PAD2rVrV+h5+vzzz+Hm5oYvvvhCXLdx40Y0aNAAt27dUjsbZkZGBjIyMviGTERERPQaeAUREVUsSnG+pTypqak6jIe0rVQjYT/77DN8+umnOH/+PJYtW4Zly5bh/Pnz8PX1LdXIOyLSjKurq8rfNjY2ePToEQAgOjoaDRo0EBOwANChQ4cS9+Hj44PPP/8cnTp1wrx583D16lWN9mvTpvgZHHft2oVOnTrB2toaJiYmmD17NhITEzWOTS6X49ChQ7h9+zZmz54NExMTTJs2De3atcOLFy8A5J6HvB+H8nTq1AnR0dEa95OnS5cuCA8Ph1KpxKlTp9CvXz84Ozvj9OnTOHnyJOrWrSvW58nJycGCBQvQokULWFpawsTEBEeOHClwfPnPU1RUFE6cOAETExNxcXJyAoBCry5YuHAhzM3N0blz5xIfExEREREREZHOSISKs5T3oZdmp+joaIwePbrA+lGjRulsghui6kAqlar8LQgCFAqFxvtLJLlP+Vd/Wctfk3XMmDG4c+cOhg0bhmvXrsHd3R1fffVVsW3L5fIibz979iyGDh2Knj174uDBg7hy5QoCAgKQmZmpcfx5mjZtijFjxmD9+vX4448/cPPmTezatavE7RSna9euOH36NKKioiCVSuHk5ISuXbsiPDwcJ0+eFEfBAsCXX36JlStXwt/fHydOnEBkZCQ8PDwKHF/+85SSkoLevXsjMjJSZcmr76vOzJkz8ezZM9y7d0/rx0xERERUXbCMExFVLLmjYPPm+hAEodjv2VS5lCoJa2VlhcjIyALrIyMjUbt27deNiYhKwdnZGX/++SeSkpLEdefOnVPZxsrKCgBUtlH3XG7QoAEmTJiAvXv3Ytq0afjuu+8AAAYGBgAgTlZVEmfOnEGjRo0QEBAAd3d32NvbayWJaGtrC2NjY/EyDWdnZ0RERKhsExERARcXl0LbKOy48urCLl++XEy45iVhw8PDxXqweX306dMHH330EVq2bIkmTZrg1q1bxcbfunVr3LhxA7a2trCzs1NZCnvDNTQ0hJmZGaytrWFkZMSJuYiIiIhKISen4GAGTsxFRLqiUCiQnp4JhUIhLnlXSVLVUKok7NixYzFu3DgsWrQIp06dwqlTpxASEoLx48dj7Nix2o6RiDTQvXt3ODg4YMSIEYiKisKpU6cQEBCgso2dnR0aNGiAwMBAxMXF4dChQ1i6dKnKNr6+vjhy5Aju3r2LP/74AydOnICzszMAoFGjRhAEAQcPHsQ///yDlJQUjeOzt7dHYmIidu7cifj4eKxatQr79u0r0TEGBgZixowZCA8Px927d3HlyhWMGjUKWVlZYi3q6dOnIzQ0FGvXrkVcXByWLVuGvXv3qtRrza+w46pRowZcXV2xbds2MeH61ltv4Y8//sCtW7dURsLa29vj2LFjOHPmDKKjozF+/Hg8fPiw2GOaNGkSnjx5gsGDB+PixYuIj4/HkSNHMHLkSI2S3QMGDODEXERERERawom5iKgiqZIlP3VdgqCylSOYM2cO5s6di6+++gpdunRBly5dsHr1agQGBqpMvENE5UcikWDfvn1IS0tDu3btMGbMGAQHB6tsI5VKsWPHDsTExMDV1RWLFi3C559/rrJNTk4OJk2aBGdnZ3h6esLBwQFr1qwBkDv5VFBQED777DPUqVMHkydP1ji+999/H59++ikmT56MVq1a4cyZM5gzZ06JjrFLly64c+cOhg8fDicnJ/To0QMPHjzA0aNH4ejoCADo27cvVq5ciSVLlqBZs2ZYt24dNm3apDJqNb+ijqtLly7IyckR97e0tISLiwusra3FPoHcScdat24NDw8PdO3aFdbW1ujbt2+xx1S3bl1EREQgJycH//vf/9CiRQv4+vrCwsJCLB9RlICAAHh6enIELBERERERURUhlUoRHBysdqJmqrwE5WsOm3r+/DkAwNTUVCsBERFRaVxWu1YZvgxC16nlG0pFkBwLWDgWv93rtlnafsoivvJsP39fgOb9lVVsee1q2n55nqPXVZlirUy0fV55P1VO1eF+K+nrtDb7fZ0+y+u9vKz6ep14dNUOla2q9PmvpKrzsRdHbezFT3pdmSkWvanrEEQS/9Pl2p/+6zbA5CsRke5cvHgRQUFBiIuLK2KrIeUWDxERac/kyZPxxhtvYMOGDTh37hzS0tLE244fP46kpCQEBQXh9u3bLEdDRETVilwux5QpU7Br1y7Ex8frOhytk0qlCAoKQv/+/XUdivaV6pr8qqFUSVg3Nze1l74KggCZTAY7Ozt4e3ujW7durx0gEREV7uTJk7h9+7b4tyAA/B5OpSWRCJW2Jp2+vp5KHT8+F6iyKO6xGhcXh9OnTyMrK0tl/YcffoicnBy8ePGijCMkej2CIPBHgiqG9ymVlEQigUJRcCK81/H555/jt99+ExOwBlJ9ZGZlF7p9/s+KFV1WVhZmzZoFV1dX2Nvb6zoc0pJS5Z89PT1x584dyOVydOvWDd26dYOJiQni4+PRtm1bJCUloXv37jhw4IC24yUiolecP38elpaW0NfLfTlftcpX5XY9PQlq1pCXaQwmckO1601NjYvcryzL2OrpSQrMMmxv3wC1apm/druvUle318BA+lp95Ket2ZKl+gVjNTRUjbVNG81nXzWWFf07bnlXKTYxMVL5u3fvTuUcgWaKetwX95wpjlRacEbvwvrT05PA2tqyRO2Xd+lpTR77+QcF5I8x/3O2sP2AsnvMFtfuqoVehd6mJxHg5uamkoDNO6aU/57iv//+Q3Z2ttpkiJGRQYlfP4R8c1QYGKg+zyUSCWQy1XZL+xrl6NigwDpjo9d//TQzlaldb1XTpMj9SnIc6p4Lpibq3wsBwNjYEDLDgs/P4t6TSvKc01fzGl9e8r+X5GduXrafQ9QxNjaEvn7Bcy6RCK99X5eEgYEUMplBgfXGxqqPF03mAXiVpaX2r0bNf6ympsaFPq7y3+eCoP71tjzmLNBmFwYG+hrHLJEU/Kyp6WOrqO00+Rypbn91jyFNT01J7yeJRFLifdq0KVgqQN1zQ538jzcTuSEMDQ3xv//9D4cOHRJj+mRsF3W7v9wv32fFPJrcb3nfd/Iftr19/WL3fV0hISFl3geVn1K9W//777+YNm0aTp06haVLl2Lp0qX4/fff4efnh9TUVBw9ehSzZ8/GggULtB0vERH9v8zMTFy/fh2PHz9Gdo7i/9epjpTKyVHg8dPUMotBX18PKakZam8rLPmRp6wGUAhC7nHnH9HZrVsrdOzYXON2ZGqSjDk5qr/gq/vimXcfaONLgVSqr7WRqVnZBUcf5P/w++DBE43be5Fe+EgDACjv8THJySkqf8fF/V3OEWimqOfF8+e5Ixo1SaaoaycrS3V0R1EjLA0MpHj4UPP7Gyj/kcWaPPbzJx/zx5iTo0DNmgUTXfn3k0iE13rMFnW/FtduUSODchRK1K1bV+XLbo0aFgCAhlaFJ/0AoF49qxK/fiiVwKu7ZGaqPs8VCgWaN2+ildelWrUsCqwzUPNDQn7FfVl2srdWu/7fJylq1+cxNNT8AkH1P8AVHvuLFxmoV6dgIrK4EVklec5lq3mNLy8ZGVlF3p7/9Vmd4j4zlDTZn5OjUHt+a9euUaLH7+v+sJqZmYXmzZsUWP/ihepnp+IS2fk9efIcNSzUJ5QKSzQVJ//jzcBAWuBzT5709MwC+9raFnzulc9oWe1lYTMz1f+opY6hobTAY+nVv4tKUhoaFp58zP9ZXh11rzf530tK8r5W0vtJoVAUuY+65/PDh08LrMv/OCpM/teYlNQM6OvrIyMjQzxuS0tTXI76s8h2CnstkkqLf/1v0qgWgILPk7fealnsviWV+2ORRFxiYmK03ofOSYSKs5T3oZdmpx9++AGDBw8usH7QoEH44YcfAACDBw9GbGzs60VHRESFevr0aYEPXI8eFfyAU5aKSjRq+5IjTRX2mbB+/dowNtb8i4mRBr/OF/UBVBtv6WU9gCQnR/ULampqWiFbVj5Pnz7TdQhqafJFR5P7XbNtCt9IqVRWm3INmozCe93RWq+zf0pq4V9Cr169ihkzZqg8btq3fwMAEP9A/Q9geTT5Ulkaly6pfhksbZIlLk7Nl+XXfFwDgKmp+uR0cWGW5DDUHXNhyao8CX/9V2Bd3g8vVPz9WtKnWGEJbrm8ZAlKbYzktLAoehQ2ULLnUV5IRkbqP6fI5epHg5dU7ih7zbcv6bnVFl2VRSiu36Juf92YNdm9PEYhl6TvtLT0Uralfn1qaioOHz4s/l2jhilsm5YuIVrcD0kAcPXmX2rX16ih/VHpSmXe57TcJTW17AbUUPkrVRJWJpPhzJkzBdafOXMGMlnui75CoRD/T0RE1U9xX0iJiKhov//+O8LDw1XW1ayZOxqnoZVml3FqW7t2zlpp5/HjgknJqsxYVnCkI98nK76KWPe0qFGU2vTiRemSZkTaZGxceE5p1apV4v+Dghbj7Xd6lFkcRV3tkJ+2SolVaZIKtJSzUv1E/sknn2DChAm4fPky2rZtCyB3hu7169dj1qxZAIAjR46gVatWWguUiIhU1ahRo0CR+9q1a5RrDEV9N8kqojB+Wcqr95b/0sz79x/hxQvNR3qmaXCJVJEjDTXuqXBl/d1PT0/1A6VcboQnT6pGYqRGDfMSlVcoL7mPmeJGzxTfjmbbFDFSWxCqzeRlz54VP4Lk9UcllX5/E3nJEirPn+c+Rw30c19/bGxs8PDhwwJXH5TVa3D+y29LO0GPnp6kQBKyuEvSgeLP9fPn6kcIF/d4L8mgMXXP4+JiT88oODLTwsJEo0v1q4PiRxWWrD19fT21Se6SXvGRnf36zyNN7uOSjFrMe/1OS1P/OSU1VTvJ0+zsnBK9T+jqahpdTRJW/OjtwuN6/asvit9Glz8gqK9TXroBeoaGBoU+ph8+fCj+f968mahXu+gyPYX3IS12NKyzvTWibhQcDfv06fMC6/T19QqU8ymJ3Pv35Z0sl5d/XW0qO6XK+86ePRvfffcdLly4AB8fH/j4+ODChQv47rvvEBAQAACYMGECfv75Z60GS0RELxkYGKB58+aoWbOmODFX/tplZT0xV3Z2TqETcxX3K3BZXSWlUChhbCwr0H54eCTOnr2hcTvpamqe5v+Sre4DW959oI3PvllZ2WU6MVf+WlwlmahJ3SQzryrvq+DyX+6ZllYxSysUNfItb2IuTWo7qmsn/8RcSmXh90NmZhbq1KkeE3M9flywNEX+/RQK5Wsd3+uMaCxqQh5D/YJBPXz4CABw71FusrF///5wdCw44cnff/9bqtePV89D/rrREokEN27c1crrkpFR7nvHq4/brMziz2Nx9Txj4x6oXV/LsuhLwjMyNP/CrC6GzCJiFwRA3d2szYkc1b3GlxeZmlG+r9LkcvzinkMlrUOsp6endmIudbWw9fQKfzzn5Lzem7mhoRTXr98psD7/xFyaXA79cttM1KljiafJ6t/nUlIKrtfk8ZH/NdDYWFbo61P+kgeCACQkFHzulc8l8dpNNmoac0ZGVpETcxWVBE1LK7ycjCavC+o+o+Z/vKt7zuR/3OXR9sRc6p7PdeoUHChSWEmNV2VnZ4vvF3nUPZ7v3r2PDu0cimyrsNeizMzsYj8DXIvOnWvg1e0EAfj998gC2+rrv145IIVCCYVCIS5OTppPnEsVn6CsiNdYEBGRRvbu3YvZs2eLtT0NDPSQmVn0RB9EhVE3Mq2yMDTUL1EShYofGUjlQ18iILuQBNOMGTPw66+/Ii4uDs+fFxxtAwBffvkl1q9fXyZzMUgkgtYmByyMvp6A7NdMdFHFpquRilR2KvPnBdINAwP9Uo8OLezzyptvvok7d+7g779zE6RNmtjizp2EQtvR19crdkLEYmNB+U8++/PPP8PBoegEc2WjWPGWrkMQSXx/L9/+SrtjcnKyWH7gyZPcXxT/+OMP/PWX+oLFRESkffXq1VOZXIkJWHodlfkLFROwJcecSMVQWAIWAKytreHt7V1oArZ58+aYPn16mU2GW9YJWABMwFYDTMBWPZX58wLpxutcnl/YS4ipqSk2b94sJiiLSsAChU/YV6JYXrsFzUmlUgQHB1e5BGx1V6qRsFevXkX37t1hbm6OhIQExMbGokmTJpg9ezkjKzgAAQAASURBVDYSExOxZcuWsoiViIgKk7wdsPj/y1GT///L+Kt/W7xyqWre369sp7x7EELjXoW0/cr26tpMzvfl/9VtX71N3fr87anr69U4Xt1HTZzKyEMQuk4tevvC4lUXo7pYizr+ws5zYTFrKl9bKvdXUe0Xdz+9ul7d34U9doDcGGrYqz+/+e/7/H2WRGGPu8JiL+x2DR4/am8r7Lzl36+4x666x3ph7ZakrVf3L+o5WoLXgyK3L+LYleHLoPL8K+w5k7+NV/vNfzyvnpuintPF3Qfq+irqPinq/ijinIjPzfzPlVdfX9U9Nwo57lfPqeLTCZAs/0ZsQxl5CAAgtHoPcfYzYR+3sPBjKuo+fnV7qHluF3U+C3ssF3WMAJRP41Rfw/LHVdTr76v9v9qnuvXq4vn/v5WRhyC0ek/zc6ZOYbHn7x/5Hhv54y7s9TI5Nvdc1bBXH8er7wl591lh5yV/vOrWa7hPka//r8Re7P2iTmHPs/zH+mo/hfVZTHtFnlt1x5VfUY9/Tc59Udu92t7/K/K1pKjn6Kv/L+49qIhzWOLXBg3XqW03L6bino+aflYrTHK+z47q9tX0vbiw94nCPqvkPQZffc8o5vFfaH+axKbm2NXGVdg2xT1eNXmd1uR99lXFnIO853BQjSDMU24v+vW1kM9EBd6P1OyX9xhVRh4CGjkU+vqn0lb+9tQda5GPzzZF3Fb5VeeRsKVKwnbv3h2tW7fG4sWLYWpqiqioKDRp0gRnzpzBkCFDkJCQUAahEpXcgwcPMGzYMJw5cwZSqRTJycm6DkkjoaGh8PX1rTTxaiohIQGNGzfGlStXynXiPltbW/j6+sLX17fQbTIzM+Hi4oItW7agY8eO5RZb/hgcHBzw448/wt3dvYR7Xy6TmESafJCtSv0SEWmCr1FEFYM2novafj7z9YGoaHyOFKGKJ2FXVqAk7JTyTcKWqmLwxYsXsW7dugLr69WrhwcP1BfDJ3pd3t7eSE5Oxv79+zXeZ/ny5UhKSkJkZCTMzc3LLrjXoC5BOHDgQPTs2bPM++7atStOnjwJADA0NETDhg0xcuRIfPbZZxoXaC9JwrhBgwZISkpCrVq1XifsMvHNN9+gcePGKgnYV8+BqakpHB0dMXv2bPTp06fA/gsXLsTs2bMREhKC6dOnF7j9wYMHWLhwIQ4dOoT79+/D3NwcdnZ2+OijjzBixAgYGxvDwMAAfn5+8Pf3x/HjxzWO3dfXF2FhYbzcj4iIiIiIqAqQSqUICgpC//79dR0KaVGpasIaGhriv//+K7D+1q1bsLKyeu2giLQlPj4ebdq0gb29PWrXrl2qNjIzM4vfSMuMjIxKHW9JjR07FklJSYiNjcXMmTMxd+5cfPPNN1rvJzMzE3p6erC2tn7tGSO1TalUYvXq1Rg9enSB2zZt2oSkpCRcunQJnTp1wocffohr164V2G7jxo2YMWMGNm7cWOC2O3fuwM3NDUePHsUXX3yBK1eu4OzZs5gxYwYOHjyIX3/9Vdx26NChOH36NG7cuKFR7MHBwTh8+DATsERERERERFVEVlYWZs2ahbi4OF2HQlpUqiTs+++/j/nz5yMrKwtA7mixxMRE+Pv7M0tP5aZr167w8fHBjBkzYGlpCWtrawQGBoq329raYs+ePdiyZQsEQYC3tzcAIDExEX369IGJiQnMzMzg5eWFhw8fivsFBgaiVatWWL9+PRo3bgyZTAYg93G+bt069OrVC8bGxnB2dsbZs2dx+/ZtdO3aFXK5HB07dkR8fLzYVnx8PPr06YM6derAxMQEbdu2VUm4de3aFffu3cOnn34KQRDEkZehoaGwsLBQOd61a9eiadOmMDAwgKOjI7Zu3apyuyAIWL9+PT744AMYGxvD3t4eP/30U7Hn0djYGNbW1mjUqBFGjhwJV1dXHDt2TLw9IyMDfn5+qFevHuRyOdq3b4/w8HAAQHh4OEaOHIlnz56J8efdB7a2tliwYAGGDx8OMzMzjBs3DgkJCRAEAZGRkWL7169fR48ePWBiYoI6depg2LBh+PfffwEA3377LerWrQuFQrX4f58+fTBq1CiNzrEmLl++jPj4eLz33nsFbrOwsIC1tTUcHBywYMECZGdn48SJEyrbnDx5EmlpaZg/fz7+++8/nDlzRuX2iRMnQl9fH5cuXYKXlxecnZ3RpEkT9OnTB4cOHULv3r3FbWvUqIFOnTph586dGsW+e/duyGQy6OtLVB5DREREREREVLmFhIToOgTtE4SKs5SzUiVhly5dipSUFNSuXRtpaWno0qUL7OzsYGpqiuDgYG3HSFSozZs3Qy6X4/z581i8eDHmz58vJhAvXrwIT09PeHl5ISkpCStXroRCoUCfPn3w5MkTnDx5EseOHcOdO3cwcOBAlXZv376NPXv2YO/evSoJw7ykYmRkJJycnDBkyBCMHz8eM2fOxKVLl6BUKjF58mRx+5SUFPTs2RPHjx/HlStX4Onpid69eyMxMREAsHfvXtSvXx/z589HUlISkpKS1B7nvn37MGXKFEybNg3Xr1/H+PHjMXLkyALJwKCgIHh5eeHq1avo2bMnhg4diidPnmh0LpVKJU6dOoWYmBgYGBiI6ydPnoyzZ89i586duHr1KgYMGABPT0/ExcWhY8eOWLFiBczMzMT4/fz8xH2XLFmCli1b4sqVK5gzZ06BPpOTk/H222/Dzc0Nly5dQlhYGB4+fAgvLy8AwIABA/D48WOV43zy5AnCwsIwdOhQjc6xJk6dOgUHBweYmpoWuk12djY2bNgAACrnBwA2bNiAwYMHQyqVYvDgweJ2APD48WMcPXoUkyZNglwuV9t2/sRpu3btcOrUqWLjTk1NRVpaGtLT05GdrYBSqeSIWCIiIiIiokpKIhEgkUjEJSYmRtchkRaV6ppgc3NzHDt2DBEREYiKikJKSgpat26N7t27azs+oiK5urpi3rx5AAB7e3usXr0ax48fx7vvvgsrKysYGhrCyMgI1tbWAIBjx47h2rVruHv3Lho0aAAA2LJlC5o1a4aLFy+ibdu2AHIvnd+yZUuB8hojR44UE4T+/v7o0KED5syZAw8PDwDAlClTMHLkSHH7li1bomXLluLfCxYswL59+/DTTz9h8uTJsLS0hJ6eHkxNTcUY1VmyZAm8vb0xceJEAMDUqVNx7tw5LFmyBN26dRO38/b2xuDBgwEAX3zxBVatWoULFy7A09Oz0LbXrFmD9evXIzMzE1lZWZDJZPDx8QGQO2p406ZNSExMRN26dQEAfn5+CAsLw6ZNm/DFF1/A3NwcgiCojf/tt9/GtGnTxL/zT9q3evVquLm54YsvvhDXbdy4EQ0aNMCtW7fg4OCAHj16YPv27XjnnXcAAD/++CNq1aolHndx51gT9+7dE48vv8GDB0NPTw9paWlQKBSwtbUVHwMA8N9//+HHH3/E2bNnAQAfffQROnfujJUrV8LExAS3b9+GUqmEo6Nq0flatWohPT0dADBp0iQsWrRIvK1u3bq4d+9eofFmZGQgIyODb8hERERERERVSO6YmpcDa1JTU3UWS5mpxhdvlmok7JYtW5CRkYFOnTph4sSJmDFjBrp37y4mrojKi6urq8rfNjY2ePToUaHbR0dHo0GDBmICFgBcXFxgYWGB6OhocV2jRo3U1jd+tb86deoAAFq0aKGyLj09XayZnJKSAj8/Pzg7O8PCwgImJiaIjo4u0SjNvLg7deqksq5Tp04qMeePTy6Xw8zMrMjzAeTWII2MjERERAR69OiBgIAAcXKqa9euIScnBw4ODjAxMRGXkydPqpRdKIy7u3uRt0dFReHEiRMqbTs5OQGA2P7QoUOxZ88eZGRkAAC2bduGQYMGQSLJffnSxjlOS0sTy07kt3z5ckRGRuLw4cNwcXHB+vXrYWlpKd6+Y8cONG3aVEwEt2rVCo0aNcKuXbuK7PPChQuIjIxEs2bNxGPLY2RkhBcvXhS678KFC2Fubo7OnTtreohEREREREREpEOlGgk7cuRIeHp6Fpg46Pnz/2PvvqOiuro2gD8XGGCkqygWcCxURRBLIhYwasBCLIi9YIuJFSsqNjREbLHERI1BUGOLQdEYRdFXMGLDApqAiETUJCTGKCb0MvP9weeNIyCgAwP4/Na6azm3nLPvmZGyOXeffzF27FiMHj1aJcERlUYikSi9FgShSP3Q11HSY+Mv9vf8EfLi9j2PYc6cOYiIiMDatWvRokULSKVSDBo0qMIW+3qd8TAyMkKLFi0AAN9++y1atGiBd999Fz169EB6ejo0NTVx7do1aGpqKl2nr69fajwljeNz6enp8PDwUJoF+lyDBg0AAB4eHlAoFPjhhx/Qvn17/Pjjj1i/fr14nirGuG7dusUutgUAZmZmaNGiBVq0aIHg4GD07t0b8fHx4te/oKAg/Pzzz0qLjcnlcuzYsQPjx49HixYtIAgCEhMTldpt1qwZgMKE68uePHnyykUOFyxYgFmzZiEzMxMuLi5lvk8iIiIiIiKqugpTCv9NFS3td2qqXl4rCatQKIpd/OXXX3+FkZHRGwdFVFFsbW3x8OFDPHz4UJwNGx8fj7S0NNjZ2am8v+joaHh7e2PAgAEACpOOLz+Sr62tjYKCglLjjo6OxpgxY5TaVnXM+vr6mDFjBubMmYMbN26gTZs2KCgowKNHj0qcdVmW+Evi5OSE0NBQyGQypSTmi3R1dTFw4EDs2bMHd+/ehbW1NZycnMTjZRnj0rRp0wZbtmwp8Wvbcx06dEDbtm0REBCAjRs34tatW7h69SoiIyOVZsc+efIErq6uuH37NmxsbNCzZ09s3rwZ06ZNK9M30Z9++glt2rQp8biOjg50dHRgaGgIqVQKhUKB/PxcFBQUPrbCurBERERERETVj1yuwIvlCJ4/KVqjvMWLSZerHEGbNm3g5OQEQRDQvXt3ODk5iZuDgwO6dOnCurBUpfXo0QP29vYYMWIErl+/jitXrmD06NFwcXEp9dH512FpaSku7hUXF4fhw4cXmZkqk8lw7tw5/Pbbb3j8+HGx7cydOxchISHYsmULkpKS8Nlnn+HQoUNKi2CpyqRJk3Dnzh2EhobCysoKI0aMwOjRo3Ho0CHcu3cPV65cwcqVK/HDDz+I8aenp+PMmTN4/PjxKx+jf9mUKVPw5MkTDBs2DDExMUhOTsbJkycxduxYpcTuiBEj8MMPP2DHjh3iglzPlWWMS9OtWzekp6fj559/LvVcHx8fbNu2Db/99huCgoLQoUMHdO3aFa1atRK3rl27on379uICXV9++SXy8/PRrl07HDhwAAkJCUhMTMQ333yD27dvF5ll/OOPP+L9998vU+xeXl5cmIuIiIiIiKgG8vX1VXcIpELlSsL2798f/fr1g0KhgJubG/r16yduQ4cOxbZt2/DNN99UVKxEb0wQBBw5cgQmJibo2rUrevTogWbNmpVav/N1ffbZZzAxMYGzszM8PDzg5uamNIsTAJYvX46UlBQ0b968xEfQ+/fvj40bN2Lt2rVo2bIltm3bhuDgYLi6uqo85tq1a2P06NFYtmwZ5HI5goODMXr0aMyePRvW1tbo378/YmJiYGFhAQBwdnbGRx99hCFDhsDU1BSrV68uc18NGzZEdHQ0CgoK8P7778Pe3h4+Pj4wNjYWa74ChQt81a5dG4mJiRg+fLhSG2UZ49LUqVMHAwYMwJ49e0o9193dHU2bNkVAQAC++eYbeHp6Fnuep6cndu3ahby8PDRv3hw3btxAjx49sGDBAjg4OKBdu3b4/PPPMWfOHKxYsUK87uLFi3j27BkGDRpUptj9/Pzg7u7+yhm8REREREREVH1IJBIEBATAyspK3aGQCgmK15g2tXPnTgwZMqTEhWyIiKqbmzdvomfPnkhOTi5TvduKMmTIEDg4OGDhwoXlvPJahcRDRPQ2UNw7BqFp3/92pL1Qx9vYWnn/i6/p9T0f46o6nip8r/2F4Viq2FszPj814R6oeqiqn7WyxlVV46dqoq26A6hQ8i9d1R2CSGNyZKX291o1YV+sS0lEVBO0bt0aq1atwr1792Bvb6+WGHJzc2Fvb4+ZM2eW6zofHx+Eh4ezFAER0RvZq+4AqIbR09PDjBkz8LOXA6yth5d+ARER0f+TSCTw9/cv8clLqp5eayZsQUEB1q9fj2+//RYPHjwosgr5kydPVBYgERGVLCAgALt27VJ3GERERPSS9evX43//+x++//57dYdCRETV1LFjx2BpaanuMFTqbZ4JW66asM/5+/vjs88+w5AhQ/Ds2TPMmjULAwcOhIaGBpYtW6biEImIqCQHDx6Erq4utLQ0IAgCa8MSEVUATU0NSCSapZ9I9P90dHTw/vvvFy5kygdViIjoNQUGBqo7BNUThKqzVbLXSsLu2bMH27dvx+zZs6GlpYVhw4bh66+/xpIlS3Dp0iVVx0hERMXIyMhAVlYWsrOzkZ8vh0KhYEkCIiIV0NRU/qFcItFCXl6BmqKh6khLSws5OTmQy+XqDoWIiKoRDQ0BGhoa4nb79m11h0Qq9FpJ2D/++EOsmaivr49nz54BAPr27Vv4114iIqpwKSkp6g6BiKhGenliBP/AReWVkZGBEydOFL7gQypERFRGCgXEyTUKhQIZGRnqDolU6LWSsI0bN0ZqaioAoHnz5jh16hQAICYmBjo6OqqLjoiIiIiIqBratGmTukMgIiKqeoQqtFWy10rCDhgwAGfOnAEATJs2DYsXL4alpSVGjx6NcePGqTRAIiIqnkwmU3cIREQ10ssTX/Py8tUTCFVrf/75p7pDICKiaqawVKkgbnp6euoOiVRI63UuerEw8JAhQ9CkSRNcuHABlpaW8PDwUFlwRERUMj09PUilUigUCuTn56KgoDBrwMdmiYjezPOvp8/J5QpoaWkiP591Yek1KMCSBEREVCZyuQIvruhoY2OjvmAqylu8mPRrzYRduXIlduzYIb5+9913MWvWLPz1119YtWqVyoIjIqJX8/Ly4sJcRESVoKCACVgqn86dO6Nhw4ZMwBIR0Wvz9fVVdwikQq+VhN22bVux2fiWLVti69atbxwUERGVjZ+fH9zd3SG8xX9NJCKqDPwbF5WXgYEBdu7cibZt26o7FCIiqmYkEgkCAgJgZWWl7lBIhV6rHMEff/yBBg0aFNlvamoqLthFRFQZBEHA4cOH0b9//zdq548//sCoUaNw4cIFSCQSpKWlqSS+yrBx40YA19QdBhFRtaW4dwxC077/7UhL/O/fxtbK+198Ta/v+RhX1fFU2Xv9F6z3XcNexd6a8fmpCfdA1UNV/ayVNa6qGj9VEzX8j3dv8fyh10rCmpubIzo6Gk2bNlXaHx0dXfjIDRHVeN7e3khLS0NYWFip5y5btgz+/v6vPKe4x+gjIyPRrVs38XW9evXQuXNnrFmzBs2aNSt3zM9jCQsLQ2xsrNL+9evXIzU1FbGxsTAyMnqtttXFx8cH4eHhLEVARPRG9qo7AKqprIC91sPVHQUREVUjEokE/v7+8PT0VHcopEKvVY5g4sSJ8PHxQXBwMO7fv4/79+9jx44dmDlzJiZOnKjqGImompszZw5SU1PFrXHjxli+fLnSvldJTEzE77//joMHD+Lnn3+Gh4eHymvzJScno23btrC0tES9evVeq43c3FyVxlQWAQEBOHHiBBOwRERERERENUReXh4WLlyIpKQkdYdCKvRaSdi5c+di/PjxmDx5Mpo1a4ZmzZph2rRpmD59OhYsWKDqGImoGsjJycH06dNRr1496OrqonPnzoiJiQEA6Ovrw8zMTNw0NTVhYGCgtO9V6tWrhwYNGqBr165YsmQJ4uPjcffu3WLP9fX1hZWVFWrVqoVmzZph8eLFyMvLAwCEhITA398fcXFxEAQBgiAgJCQEMpkMoaGh2LVrFwRBgLe3NwDgwYMH6NevH/T19WFoaIjBgwfjzz//FPtatmwZHB0d8fXXX6Np06bQ1dUFUFgiYdu2bejbty9q1aoFW1tbXLx4EXfv3oWrqyv09PTg7OyM5ORksa24uDh069YNBgYGMDQ0RNu2bXH16tVSx/3gwYPQ1dWFlpaGeE9ERERERERU/QUGBqo7BNUThKqzVbLXSsIKgoBVq1bhr7/+wqVLlxAXF4cnT55gyZIlqo6PiKqJefPmITQ0FDt37sT169fRokULuLm54cmTJyrtRyqVAih51qmBgQFCQkIQHx+PjRs3Yvv27Vi/fj0AYMiQIZg9ezZatmwpzsAdMmQIYmJi4O7ujsGDByM1NRUbN26EXC5Hv3798OTJE0RFRSEiIgK//PILhgwZotTf3bt3ERoaikOHDimVOFixYgVGjx6N2NhY2NjYYPjw4Zg0aRIWLFiAq1evQqFQYOrUqeL5I0aMQOPGjRETE4Nr165h/vz5kEgkrxyLjIwMZGVlITs7G/n5cigUCs6IJSIiIiIiqqY0NARoaGiI2+3bt9UdEqnQa9WEfU5fXx/t27dXVSxEVE1lZGRgy5YtCAkJQa9evQAA27dvR0REBIKCgjB37lyV9JOamoq1a9eiUaNGsLYuvtD9okWLxH/LZDLMmTMH+/fvx7x58yCVSqGvrw8tLS2l2bdSqRQ6OjqQSqXi/oiICNy6dQv37t2Dubk5AGDXrl1o2bIlYmJixK99ubm52LVrF0xNTZXiGDt2LAYPHgygcHZux44dsXjxYri5uQEAZsyYgbFjx4rnP3jwAHPnzoWNjQ0AwNLSssRxyMnJQU5ODr8hExERERER1SCFc2r+m1iTkZGhtlhI9V5rJiwR0YuSk5ORl5eHTp06ifskEgk6dOiAhISEN26/cePG0NPTQ8OGDZGRkYHQ0FBoa2sXe+6BAwfQqVMnmJmZQV9fH4sWLcKDBw/K3WdCQgLMzc3FBCwA2NnZwdjYWOmemjRpUiQBCwCtW7cW/12/fn0AgL29vdK+7Oxs/PPPPwCAWbNmYcKECejRowcCAwOVShW8bOXKlTAyMkKXLl3KfV9EREREREREaqNRhbZKxiQsEVV5P/74I27evIl//vkHsbGxeOedd4o97+LFixgxYgR69+6NY8eO4caNG/Dz86vQBbP09PSK3f9iKYHndVqL2yeXywEU1pf9+eef0adPH/zvf/+DnZ0dDh8+XGzbCxYswLNnz3D//n2V3AMRERERERGpX2GpUkHcSvp9k6onJmGJ6I01b94c2traiI6OFvfl5eUhJiYGdnZ2b9x+06ZN0bx5cxgYGLzyvAsXLqBJkybw8/NDu3btYGlpWSRRqa2tjYKCglL7tLW1xcOHD/Hw4UNxX3x8PNLS0lRyT8WxsrLCzJkzcerUKQwcOBDBwcHFnqejowNDQ0OYmZlBKpVyYS4iIiIiIqIaQC5XQC6Xi9vzcnVU9QQGBkIQBPj4+JT5GiZhieiN6enp4eOPP8bcuXMRHh6O+Ph4TJw4EZmZmRg/fnylxWFpaYkHDx5g//79SE5OxqZNm4rMJpXJZLh37x5iY2Px+PFj5OTkFNtWjx49YG9vjxEjRuD69eu4cuUKRo8eDRcXF7Rr106lcWdlZWHq1KmIjIzE/fv3ER0djZiYGNja2pZ6rZeXFxfmIiIiIiIiqoF8fX3VHYLqFU73rRrba4qJicG2bduUyhCWBZOwRKQSgYGB8PT0xKhRo+Dk5IS7d+/i5MmTMDExqbQYPvjgA8ycORNTp06Fo6MjLly4gMWLFyud4+npCXd3d3Tr1g2mpqbYt29fsW0JgoAjR47AxMQEXbt2RY8ePdCsWTMcOHBA5XFramri77//xujRo2FlZYXBgwejV69e8Pf3L/VaPz8/uLu7cwYsERERERFRDSGRSBAQEAArKyt1h0IvSU9Px4gRI7B9+/Zy5zsEBadNERHVANfUHQBVR2mJgLG1uqNQn7f9/omoZuPXOCorflaqv+r+Hlb3+FWurboDqFDy4B7qDkGUN/yHIk/H6ujoQEdHp8RrxowZg9q1a2P9+vVwdXWFo6MjNmzYUKb+OBOWiKimSEuE4t4xdUdB1UlV/WE3LbFy+qmq909Eyirra0JNU9rXOI4rPVdR3w9r2mesKt3Py7FU5s80FTEO/JmM1GTlypUwMjJS2lauXFni+fv378f169dfec6raL1uoEREVDV0794dv/766wt79qotFiIiIiIiInozEokE/v7+8PT0VHcoNdqCBQswa9YspX0lzYJ9+PAhZsyYgYiICOjq6r5WfyxHQERUjQUEBGDXrl0wNtZDWlqGusMhIiIiIiIiFTl27BgsLS3VHYZKyUN6qjsEkYZ3RJnPDQsLw4ABA6CpqSnuKygogCAI0NDQQE5OjtKxYvt77UiJiEjtDh48CCsrK1hYmEFLk1/SiYiIiIiIaorAwEB1h0D/r3v37rh16xZiY2PFrV27dhgxYgRiY2NLTcACLEdARFRtZWRkICsrC126dMGOHUHgcw1ERERERETVl4aGAEAQX9++fVt9wZASAwMDtGrVSmmfnp4e6tSpU2R/SZiEJSKqplJSUgAAJiYmTMASERERERFVc4W/1/33y11GRs0rOScIpZ9TUzEJS0RERERERERERFQOkZGR5TqfSVgiompKJpMBAJ4+fQpBAGfDEhERERERVWOFs0T/myqqp6entlhI9ZiEJSKqpvT09CCVSvHjjz+idm1D/P33P+oOiYiIiIiIiF6TXK7Ai+UIbGxs1BdMRXmL6xFwKW0iomrMy8sLd+7cwdOn6eoOhYiIiIiIiFTI19dX3SGQCjEJS0RUjfn5+QEA5HK5miMhIiIiIiIiVZBIJAgICICVlZW6Q1E9oQptlYzlCIjKKDIyEt26dcPTp09hbGys7nCqBG9vb6SlpSEsLEwt/YeEhMDHxwdpaWlv3FZYWBjmzJmDe/fuYdq0adiwYcMbt1lZEhMTAVxTdxhvLi0RMLauvu0TqVNpn++a9PmvKvfyYhzFxVRV4qSa5W34XL0N9/i63mRsOK4le3lsOFbKOB5q0FbdAVAFYRKWVErdSTkAyM3NxYYNG7Bnzx4kJSWhVq1asLa2xoQJEzBy5EhIJBK1xRYSEoKxY8cW2a+jo4Ps7OwytyMIAg4fPoz+/furMLry27hxIxQVuBqUt7c3du7cCaDwL4EWFhYYPXo0Fi5cCC2t1/vyJZPJ4OPjAx8fH6X9kyZNwtixYzF9+nQYGBi8aeiVysfHB+Hh4RX6XhAREREREVHlkEgk8Pf3h6enp7pDIRViEpZqlNzcXLi5uSEuLg4rVqxAp06dYGhoiEuXLmHt2rVo06YNHB0d1RqjoaHh/89c/I+gpsLUeXl5r5WULigogCAIMDIyqoColLm7uyM4OBg5OTk4fvw4pkyZAolEggULFqisj/T0dDx69Ahubm5o2LDha7eTm5sLbW1tlcVVFgEBAThx4kSl9klEREREREQVJy8vDwsXLkTr1q1haWmp7nBUS4MLcxFViqioKHTo0AE6Ojpo0KAB5s+fj/z8fADAsWPHYGxsjIKCAgBAbGwsBEHA/Pnzxeufz2YtyYYNG3Du3DmcOXMGU6ZMgaOjI5o1a4bhw4fj8uXL4hevnJwcTJ8+HfXq1YOuri46d+6MmJgYpbaOHz8OKysrSKVSdOvWDSkpKUX6O3/+PLp06QKpVApzc3NMnz4dGRkZrxwDQRBgZmamtNWvX1887urqiunTp2PevHmoXbs2zMzMsGzZMvG4TCYDAAwYMACCIIivAeDIkSNwcnKCrq4umjVrBn9/f3F8n/e9ZcsWfPDBB9DT00NAQAAiIyMhCAJ++OEHtG7dGrq6unj33Xfx008/ideFhITA2NgYR48ehZ2dHXR0dPDgwQN4e3srzcb97rvvYG9vD6lUijp16qBHjx5K4/H111/D1tYWurq6sLGxwZdffvnKsQIKZwmbmZmhSZMm+Pjjj9GjRw8cPXq02HOTk5PRr18/1K9fH/r6+mjfvj1Onz6tNLb379/HzJkzIQgCBEFAZGSkOPP1vffeE/cBQGhoKFq2bAkdHR3IZDKsW7dOqT+ZTIYVK1Zg9OjRMDQ0xIcffiiO1bFjx2BtbY1atWph0KBByMzMxM6dOyGTyWBiYoLp06eLn3UA+PLLL2FpaQldXV3Ur18fgwYNKnVsAODgwYPQ1dWFlpaGeE9ERERERFR+/FGaqprAwEB1h0AqxCQsVZrffvsNvXv3Rvv27REXF4ctW7YgKCgIn3zyCQCgS5cu+Pfff3Hjxg0AhQnbunXrigmx5/tcXV1L7GPPnj3o0aMH2rRpU+SYRCKBnp4eAGDevHkIDQ3Fzp07cf36dbRo0QJubm548uQJAODhw4cYOHAgPDw8EBsbiwkTJiglg4HChJ+7uzs8PT1x8+ZNHDhwAOfPn8fUqVPfZJgAADt37oSenh4uX76M1atXY/ny5YiIiAAAMVkcHByM1NRU8fWPP/6I0aNHY8aMGYiPj8e2bdsQEhKCgIAApbaXLVuGAQMG4NatWxg3bpy4f+7cuVi3bh1iYmJgamoKDw8P5OXlicczMzOxatUqfP311/j5559Rr149pXZTU1MxbNgwjBs3DgkJCYiMjMTAgQPFR+T37NmDJUuWICAgAAkJCfj000+xePFisdxAWUmlUuTm5hZ7LD09Hb1798aZM2dw48YNuLu7w8PDAw8ePAAAHDp0CI0bN8by5cuRmpqK1NRUODs7izOTQ0NDxX3Xrl3D4MGDMXToUNy6dQvLli3D4sWLERISotTn2rVr4eDggBs3bmDx4sXiWG3atAn79+9HeHg4IiMjMWDAABw/fhzHjx/H7t27sW3bNnz33XcAgKtXr2L69OlYvnw5EhMTER4ejq5du5Y6FhkZGcjKykJ2djby8+VQKBQsSUBERERE9Jr4ozSpm4aGAA0NDXG7ffu2ukMiFWI5Aqo0X375JczNzbF582YIggAbGxv8/vvv8PX1xZIlS2BkZARHR0dERkaiXbt2iIyMxMyZM+Hv74/09HQ8e/YMd+/ehYuLS4l9JCUlvTJJCxQmrrZs2YKQkBD06tULALB9+3ZEREQgKCgIc+fOxZYtW9C8eXNx5qO1tTVu3bqFVatWie2sXLkSI0aMEGuLWlpaYtOmTXBxccGWLVugq6tbbP/Pnj2Dvr6+0r4uXbooPVLeunVrLF26VGx38+bNOHPmDHr27AlTU1MAgLGxMczMzMRr/P39MX/+fIwZMwYA0KxZM6xYsQLz5s0T2wKA4cOHK9Wl/eWXXwAAS5cuRc+ePQEUJoEbN26Mw4cPY/DgwQAKH4f48ssv4eDgUOx9paamIj8/HwMHDkSTJk0AAPb29uLxpUuXYt26dRg4cCAAoGnTpmKy+HnMr6JQKHDmzBmcPHkS06ZNK/YcBwcHpfhWrFiBw4cP4+jRo5g6dSpq164NTU1NGBgYKI3d84Ty85nHAPDZZ5+he/fuYmLVysoK8fHxWLNmDby9vcVr33vvPcyePVt8/eOPPyIvL0/8DAHAoEGDsHv3bvz555/Q19eHnZ0dunXrhrNnz2LIkCF48OAB9PT00LdvXxgYGKBJkybF/iHhuZycHOTk5PAbMhERERERUQ1S+IeA//4aUNqTttXSWzzjnDNhqdIkJCSgY8eOSo9Ld+rUCenp6fj1118BAC4uLoiMjIRCocCPP/6IgQMHwtbWFufPn0dUVBQaNmwolhTQ19cXt48++ggAyjQLMDk5GXl5eejUqZO4TyKRoEOHDkhISBBjfeedd5Su69ixo9LruLg4hISEKMXh5uYGuVyOe/fuldi/gYEBYmNjlbavv/5a6ZzWrVsrvW7QoAEePXr0yvuKi4vD8uXLleKZOHEiUlNTkZmZKZ7Xrl27Yq9/8f5q164Na2trcTwAQFtbu0hcL3JwcED37t1hb28PLy8vbN++HU+fPgVQ+I0jOTkZ48ePV4rvk08+QXJy8ivv69ixY9DX14euri569eqFIUOGKJVneFF6ejrmzJkDW1tbGBsbQ19fHwkJCeJM2PJISEhQ+owAhZ/XpKQkpTICxY1nrVq1xAQsANSvXx8ymUwp+V6/fn3xPe3ZsyeaNGmCZs2aYdSoUdizZ4/Se/aylStXwsjICF26dCn3fRERERERERFR5eNMWKpSXF1dsWPHDsTFxUEikcDGxgaurq6IjIzE06dPlWbBxsbGiv82NDQEUDhbsbJmB6anp2PSpEmYPn16kWMWFhYlXqehoYEWLVq8su2XF8sSBAFyubzUePz9/cWZpi96cVbu85IM5SWVSl9Zb1RTUxMRERG4cOECTp06hc8//xx+fn64fPkyatWqBaBwxvHLyW1NTc1X9tutWzds2bIF2traaNiwIbS0Sv6yNWfOHERERGDt2rVo0aIFpFIpBg0aVGL5AlUobjyLe/9e9Z4aGBjg+vXriIyMxKlTp7BkyRIsW7YMMTExMDY2LtL+ggULMGvWLGRmZr5yZjgRERERERFVH4W/cv/3e/fr/v5OVROTsFRpbG1tERoaCoVCISbzoqOjYWBggMaNGwP4ry7s+vXrxeSSq6srAgMD8fTpU6XHvotLZA4fPhwLFy7EjRs3ijzOnZeXh9zcXDRv3hza2tqIjo4WH5vPy8tDTEyMWFrA1ta2yOJPly5dUnrt5OSE+Pj4UhOqFUEikSjNxnweT2Ji4mvHc+nSJTF5/PTpU9y5cwe2trblakMQBHTq1AmdOnXCkiVL0KRJExw+fBizZs1Cw4YN8csvv2DEiBHlalNPT6/M9xQdHQ1vb28MGDAAQGFi+uUF1bS1tYuMXXFsbW0RHR1dpH0rK6tSE8evQ0tLCz169ECPHj2wdOlSGBsb43//+1+xSXUdHR3o6OjA0NAQUqkUCoUC+fm5KCgonAnOurBEREREROUnCKwLS+ollyvwYjkCGxsb9QVTUd7iFfCYhCWVe/bsmdIsVQCoU6cOJk+ejA0bNmDatGmYOnUqEhMTsXTpUsyaNQsaGoWVMUxMTNC6dWvs2bMHmzdvBgB07doVgwcPRl5eXqmz/nx8fPDDDz+ge/fuWLFiBTp37gwDAwNcvXoVq1atQlBQEBwdHfHxxx9j7ty5qF27NiwsLLB69WpkZmZi/PjxAICPPvoI69atw9y5czFhwgRcu3atyIJMvr6+ePfddzF16lRMmDABenp6iI+PR0REhBh7cRQKBf74448i++vVqyeOQ2lkMhnOnDmDTp06QUdHByYmJliyZAn69u0LCwsLDBo0CBoaGoiLi8NPP/0kLn72KsuXL0edOnVQv359+Pn5oW7duujfv3+Z4gGAy5cv48yZM3j//fdRr149XL58GX/99ZeYyPX398f06dNhZGQEd3d35OTk4OrVq3j69ClmzZpV5n5exdLSEocOHYKHhwcEQcDixYuLzCCWyWQ4d+4chg4dCh0dHdStW7fYtmbPno327dtjxYoVGDJkCC5evIjNmzfjyy+/VEmsLzp27Bh++eUXdO3aFSYmJjh+/Djkcjmsra1LvdbLywu7du1SeUxERERERG8bJmCpqvH19VV3CKRCrAlLKhcZGYk2bdoobf7+/mjUqBGOHz+OK1euwMHBAR999BHGjx+PRYsWKV3v4uKCgoICcYGt2rVrw87ODmZmZqUmpXR0dBAREYF58+Zh27ZtePfdd9G+fXts2rQJ06dPR6tWrQAAgYGB8PT0xKhRo+Dk5IS7d+/i5MmTMDExAVBYTiA0NBRhYWFwcHDA1q1b8emnnyr11bp1a0RFReHOnTvo0qUL2rRpgyVLlqBhw4avjPGff/5BgwYNimyl1Xx90bp16xAREQFzc3Nxxq+bmxuOHTuGU6dOoX379nj33Xexfv16cbZvaQIDAzFjxgy0bdsWf/zxB77//ntoa2uXOSZDQ0OcO3cOvXv3hpWVFRYtWoR169aJi59NmDABX3/9NYKDg2Fvbw8XFxeEhISgadOmZe6jNJ999hlMTEzg7OwMDw8PuLm5wcnJSemc5cuXIyUlBc2bNxcXOSuOk5MTvv32W+zfvx+tWrXCkiVLsHz5cqVFuVTF2NgYhw4dwnvvvQdbW1ts3boV+/btQ8uWLUu91s/PD+7u7q8sFUFERERERETVh0QiQUBAAKysrNQdCqmQoOBzq0RvtcjISHTr1g1Pnz4ttv4oVRfX1B3Am0tLBIxLn/1bZdsnUqfSPt816fNfVe7lxTiKi6mqxEk1y9vwuXob7vF1vcnYcFxL9vLYcKyUcTzUoK26A6hQiv3u6g5BJAwNr9T+WI6AiKia8/HxQXh4OGvBEhERERER1QASiQT+/v7w9PRUdyikQixHQERUjQUEBODEiRNMwBIREREREdUQeXl5WLhwIZKSktQdiuoJQtXZKhmTsERvOVdXVygUCpYiqKYOHjwIXV1daGlpQBAE1oYlIiIiIiKqIQIDA9UdAqkQyxEQEVVTGRkZyMrKUncYREREREREpAIaGgKA/ybW3L59W33BkMoxCUtEVE2lpKSoOwQiIiIiIiJSkcIqc/+VmsvIyFBbLBXmLX54k+UIiIiIiIiIiIiIiCoQZ8ISEVVTMplM3SEQERERERGRihQu8fHfVFE9PT21xUKqxyQsEVE1paenB6lUCoVCgfz8XBQUFD62olAoSrmSiIiIiIiIqhq5XIEXyxHY2NioL5iKovH21iNgOQIiomrMy8sL2dnZyM+XQ6FQMAFLRERERERUQ/j6+qo7BFIhJmGJiKoxPz8/uLu7QxDe3r8mEhERERER1SQSiQQBAQGwsrJSdyikQoKC06aI6A2EhITAx8cHaWlpZb5GJpPBx8cHPj4+FRZXaaKjo/HRRx/h9u3b6NOnD8LCwtQWi2pcU3cARERERERE9MbaqjuACqUI7a3uEESC5/FK7Y81YYmqOG9vb+zcuROTJk3C1q1blY5NmTIFX375JcaMGYOQkJAytZeSkoKmTZvixo0bcHR0fOP4hgwZgt69K++LaEFBAdasWYOQkBDcv38fUqkUlpaWmDhxIiZMmFDmdmbNmgVHR0ecOHEC+vr6WLZsGcLCwhAbG1txwVcQHx8fhIeHsxQBVSlTp07FtGnTsGfPHqxevRrZ2dnqDomIiIiIqFqQSCTw9/eHp6enukMhFWI5AqJqwNzcHPv370dWVpa4Lzs7G3v37oWFhYXa4srLy4NUKkW9evUqrU9/f3+sX78eK1asQHx8PM6ePYsPP/ywXDNxASA5ORnvvfceGjduDGNj4wqJtSzy8vLe6PqAgACcOHGCCViqkoKCgrB8+XImYImIiIiIyiEvLw8LFy5EUlKSukNRPUGoOlslYxKWqBpwcnKCubk5Dh06JO47dOgQLCws0KZNG6Vzw8PD0blzZxgbG6NOnTro27cvkpOTxeNNmzYFALRp0waCIMDV1VU89vXXX8PW1ha6urqwsbHBl19+KR5LSUmBIAg4cOAAXFxcoKuriz179iAkJEQpiZmcnIx+/fqhfv360NfXR/v27XH69OkS702hUGDZsmWwsLCAjo4OGjZsiOnTp5d4/tGjRzF58mR4eXmhadOmcHBwwPjx4zFnzhzxnJycHEyfPh316tWDrq4uOnfujJiYGKX7+PvvvzFu3DgIgoCQkBD4+/sjLi4OgiCI++bMmYO+ffuK7W7YsAGCICA8PFzc16JFC3z99dcAgJiYGPTs2RN169aFkZERXFxccP36daX4BUHAli1b8MEHH0BPTw8BAQEAgCNHjsDJyQm6urpo1qwZ/P39kZ+fX+I4PHfw4EHo6upCS0tDjJ2oqjh8+LC6QyAiIiIiqrYCAwPVHQKpEJOwRNXEuHHjEBwcLL7esWMHxo4dW+S8jIwMzJo1C1evXsWZM2egoaGBAQMGQC6XAwCuXLkCADh9+jRSU1PFxO6ePXuwZMkSBAQEICEhAZ9++ikWL16MnTt3KrU/f/58zJgxAwkJCXBzcyvSf3p6Onr37o0zZ87gxo0bcHd3h4eHBx48eFDsfYWGhmL9+vXYtm0bkpKSEBYWBnt7+xLHwczMDP/73//w119/lXjOvHnzEBoaip07d+L69eto0aIF3Nzc8OTJE5ibmyM1NRWGhobYsGEDUlNTMWTIEMyePRstW7ZEamqquM/FxQXnz59HQUEBACAqKgp169ZFZGQkAOC3335DcnKymMj+999/MWbMGJw/fx6XLl2CpaUlevfujX///VcpvmXLlmHAgAG4desWxo0bhx9//BGjR4/GjBkzEB8fj23btiEkJERM0JYkIyMDWVlZyM7ORn6+HAqFgjNiqcooKCjA3bt31R0GEREREVG1oaEhQENDQ9xu376t7pBIhVgTlqiaGDlyJBYsWID79+8DKFxYav/+/WJC8LmXa8bs2LEDpqamiI+PR6tWrWBqagoAqFOnDszMzMTzli5dinXr1mHgwIEACmfMPk8IjhkzRjzPx8dHPKc4Dg4OcHBwEF+vWLEChw8fxtGjRzF16tQi5z948ABmZmbo0aMHJBIJLCws0KFDhxLb/+yzzzBo0CCYmZmhZcuWcHZ2Rr9+/dCrVy8AhYnJLVu2ICQkRNy3fft2REREICgoCHPnzoWZmRkEQYCRkZE4Bvr6+tDS0lIaky5duuDff//FjRs30LZtW5w7dw5z584VF/GKjIxEo0aN0KJFCwDAe++9pxTrV199BWNjY0RFRSnNqB0+fLhSAn3cuHGYP3++OM7NmjXDihUrMG/ePCxdurTIGOTk5CAnJ4ffkKlKu379Ov8oQERERERUDoU/Pv/3M3RGRobaYqkwb/HDm5wJS1RNmJqaok+fPggJCUFwcDD69OmDunXrFjkvKSkJw4YNQ7NmzWBoaAiZTAYAJc5EBQq/sCcnJ2P8+PHQ19cXt08++USplAEAtGvX7pVxpqenY86cObC1tYWxsTH09fWRkJBQYv9eXl7IyspCs2bNMHHiRBw+fPiVj+Hb2dnhp59+wqVLlzBu3Dg8evQIHh4e4qJcycnJyMvLQ6dOncRrJBIJOnTogISEhFfG/jJjY2M4ODggMjISt27dgra2Nj788EPcuHED6enpiIqKgouLi3j+n3/+iYkTJ8LS0hJGRkYwNDREenp6kXt/eQzj4uKwfPlypbGfOHEiUlNTkZmZWSSulStXwsjICF26dCnX/RBVpsuXL6s7BCIiIiIioiqDM2GJqpFx48aJs0m/+OKLYs/x8PBAkyZNsH37djRs2BByuRytWrVCbm5uie2mp6cDKJwx+s477ygd09TUVHqtp6f3yhjnzJmDiIgIrF27Fi1atIBUKsWgQYNK7N/c3ByJiYk4ffo0IiIiMHnyZKxZswZRUVGQSCTFXqOhoYH27dujffv28PHxwTfffINRo0bBz8/vlbG9DldXV0RGRkJHRwcuLi6oXbs2bG1tcf78eURFRWH27NniuWPGjMHff/+NjRs3okmTJtDR0UHHjh2L3PvLY5ieng5/f/9iZxjr6uoW2bdgwQLMmjULmZmZSklgIiIiIiIiqr4Kl/j4b6poab9/U/XCJCxRNeLu7o7c3FwIglBsPda///4biYmJ2L59uzhL8vz580rnaGtrA4BY5xQA6tevj4YNG+KXX37BiBEj3ijG6OhoeHt7Y8CAAQAKE4wpKSmvvEYqlcLDwwMeHh6YMmUKbGxscOvWLTg5OZWpTzs7OwCFM3qbN28ObW1tREdHo0mTJgAKV5aMiYmBj49PiW1oa2srjclzLi4u2LFjB7S0tODu7g6gMDG7b98+3LlzR2lhs+joaHz55Zfo3bs3AODhw4d4/PhxqfE7OTkhMTFRLGtQGh0dHejo6MDQ0BBSqRQKhQL5+bkoKCh8bIWPgFNVJQgCP59ERERERCWQyxV4sRyBjY2N+oKpKG/xYtJMwhJVI5qamuIj9S/PUAUAExMT1KlTB1999RUaNGiABw8eYP78+Urn1KtXD1KpFOHh4WjcuDF0dXVhZGQEf39/TJ8+HUZGRnB3d0dOTg6uXr2Kp0+fYtasWWWO0dLSEocOHYKHhwcEQcDixYvFRcGKExISgoKCArzzzjuoVasWvvnmG0ilUjGB+rJBgwahU6dOcHZ2hpmZGe7du4cFCxbAysoKNjY20NLSwscff4y5c+eidu3asLCwwOrVq5GZmYnx48eXGIdMJsO9e/cQGxuLxo0bw8DAADo6OujatSv+/fdfHDt2TFyZ0tXVFYMGDUKDBg1gZWWldO+7d+9Gu3bt8M8//2Du3LmQSqWljtmSJUvQt29fWFhYYNCgQdDQ0EBcXBx++uknfPLJJ6+81svLC7t27Sq1D6LKNm/ePHz33Xf45ZdfxH1MwBIRERERlZ2vr6+6QyAVYk1YomrG0NAQhoaGxR7T0NDA/v37ce3aNbRq1QozZ87EmjVrlM7R0tLCpk2bsG3bNjRs2BD9+vUDAEyYMAFff/01goODYW9vDxcXF4SEhKBp06bliu+zzz6DiYkJnJ2d4eHhATc3t1fOaDU2Nsb27dvRqVMntG7dGqdPn8b333+POnXqFHu+m5sbvv/+e3h4eMDKygpjxoyBjY0NTp06BS2twr8rBQYGwtPTE6NGjYKTkxPu3r2LkydPwsTEpMQ4PD094e7ujm7dusHU1BT79u0DUJjYtre3h6mpqfhXyK5du0IulxcpBRAUFISnT5/CyckJo0aNwvTp01GvXr1Sx8zNzQ3Hjh3DqVOn0L59e7z77rtYv359iYnoF/n5+cHd3R3CW/zXRKqazMzMsHPnTixYsAA6OjrqDoeIiIiIqNqQSCQICAhQmvRD1Z+g4LQUIqIa4Jq6AyAiIiIiIqI31lbdAVQoxZG+6g5BJPQ7Vqn9cSYsERFRRUlLVHcEVdfrjk1ljCnfN3obvOpzXtb/A/y/Ur28+H69ze/d23zvqqKuMUxL5PtH1Rc/uwTWhCUiqvZ8fHwQHh7OeptEREREREQ1gEQigb+/Pzw9PdUdCqkQZ8ISEVVjAQEBOHHiBBOwRERERERENUReXh4WLlyIpKQkdYeiehpC1dkq+9YrvUciIlKZgwcPQldXF1paGhAEgQt0ERERERER1RCBgYHqDoFUiOUIiIiqqYyMDGRlZak7DCIiIiIiIlIBDQ0BwH8Ta27fvq2+YCrKWzxxiElYIqJqKiUlRd0hEBERERERkYoUVpn7r9RcRkaG2mIh1WM5AiIiIiIiIiIiIqIKxJmwRETVlEwmU3cIREREREREpCKFT+r/97i+np6e2mKpMCxHQERE1Y2enh6kUikUCgXy83NRUFD42IpCoSjlSiIiIiIiIqpq5HIFXixHYGNjo75gSOVYjoCIqBrz8vJCdnY28vPlUCgUTMASERERERHVEL6+vuoOgVSISVgiomrMz88P7u7uEN7iRzqIiIiIiIhqEolEgoCAAFhZWak7FNUThKqzVfatKzhtiohqqMjISHTr1g1Pnz6FsbFxma6RyWTw8fGBj49PhcametfUHUDNlJYIGFurOwqqzvgZenOvGkOOb8lKGpuqPmZVPT4iopqmAr7uKiI/g+A6S6Vtvl3aqjuACqU43l/dIYiE3mGV2h9rwhKRWnh7e2Pnzp2YNGkStm7dqnRsypQp+PLLLzFmzBiEhISoJ8BS/Prrr2jWrBmsrKzw008/FTn+4sxUQ0NDtGrVCitWrMB7770HoPD+09LSEBYW9sax+Pj4IDw8nKUIiIiIiIioihiu7gCqNYlEAn9/f3h6eqo7FFIhliMgIrUxNzfH/v37kZWVJe7Lzs7G3r17YWFhocbIShcSEoLBgwfjn3/+weXLl4s9Jzg4GKmpqYiOjkbdunXRt29f/PLLLyqNIyAgACdOnGACloiIiIiIqIbIy8vDwoULkZSUpO5QVE/QqDpbJWMSlojUxsnJCebm5jh06JC479ChQ7CwsECbNm2Uzs3JycH06dNRr1496OrqonPnzoiJiVE65/jx47CysoJUKkW3bt2QkpJSpM/z58+jS5cukEqlMDc3x/Tp05GRkVGuuBUKBYKDgzFq1CgMHz4cQUFBxZ5nbGwMMzMztGrVClu2bEFWVhYiIiKKPfe7776Dvb09pFIp6tSpgx49epQproMHD0JXVxdaWhoQBIG1YYmIiIiIiGqIwMBAdYdAKsQkLBGp1bhx4xAcHCy+3rFjB8aOHVvkvHnz5iE0NBQ7d+7E9evX0aJFC7i5ueHJkycAgIcPH2LgwIHw8PBAbGwsJkyYgPnz5yu1kZycDHd3d3h6euLmzZs4cOAAzp8/j6lTp5Yr5rNnzyIzMxM9evTAyJEjsX///lITplKpFACQm5tb5FhqaiqGDRuGcePGISEhAZGRkRg4cGCps1szMjKQlZWF7Oxs5OfLoVAoOCOWiIiIiIiomtLQEKChoSFut2/fVndIqqchVJ2tsm+90nskInrByJEjcf78edy/fx/3799HdHQ0Ro4cqXRORkYGtmzZgjVr1qBXr16ws7PD9u3bIZVKxVmoW7ZsQfPmzbFu3TpYW1tjxIgR8Pb2Vmpn5cqVGDFiBHx8fGBpaQlnZ2ds2rQJu3btQnZ2dpljDgoKwtChQ6GpqYlWrVqhWbNmOHjwYInnZ2ZmYtGiRdDU1ISLi0uR46mpqcjPz8fAgQMhk8lgb2+PyZMnQ19fv9j2cnJy8M8//+Dnn38uc8xERERERERUtSkUECfXKBSKcj+1SVUbF+YiIrUyNTVFnz59EBISAoVCgT59+qBu3bpK5yQnJyMvLw+dOnUS90kkEnTo0AEJCQkAgISEBLzzzjtK13Xs2FHpdVxcHG7evIk9e/aI+xQKBeRyOe7duwdbW9tS401LS8OhQ4dw/vx5cd/IkSMRFBRUJOk7bNgwaGpqIisrC6ampggKCkLr1q2LtOng4IDu3bvD3t4ebm5ueP/99zFo0CCYmJgUG8PKlSvh7+8PbW1tyGSyUmMmIiIiIiIiIvViEpaI1G7cuHFiSYAvvviiwvpJT0/HpEmTMH369CLHyroQ2N69e5Gdna2U8H2eyL1z5w6srKzE/evXr0ePHj1gZGQEU1PTEtvU1NREREQELly4gFOnTuHzzz+Hn58fLl++jKZNmxY5f8GCBZg1axYyMzOLnVlLRERERERE1U/hEh//PSavp6entlgqzFu8jgnLERCR2rm7uyM3Nxd5eXlwc3Mrcrx58+bQ1tZGdHS0uC8vLw8xMTGws7MDANja2uLKlStK1126dEnptZOTE+Lj49GiRYsim7a2dpliDQoKwuzZsxEbGytucXFx6NKlC3bs2KF0rpmZGVq0aPHKBOxzgiCgU6dO8Pf3x40bN6CtrY3Dhw8Xe66Ojg4MDQ1hZmYGqVTKhbmIiIiIiIhqALm8cILP883GxkbdIZEKMQlLRGqnqamJhIQExMfHQ1NTs8hxPT09fPzxx5g7dy7Cw8MRHx+PiRMnIjMzE+PHjwcAfPTRR0hKSsLcuXORmJiIvXv3IiQkRKkdX19fXLhwAVOnTkVsbCySkpJw5MiRMi/MFRsbi+vXr2PChAlo1aqV0jZs2DDs3LkT+fn55b7/y5cv49NPP8XVq1fx4MEDHDp0CH/99VeZyiN4eXlxYS4iIiIiIqIayNfXV90hkAoxCUtEVYKhoSEMDQ1LPB4YGAhPT0+MGjUKTk5OuHv3Lk6ePCnWTbWwsEBoaCjCwsLg4OCArVu34tNPP1Vqo3Xr1oiKisKdO3fQpUsXtGnTBkuWLEHDhg3LFGNQUBDs7OyK/WvkgAED8OjRIxw/frwcd13I0NAQ586dQ+/evWFlZYVFixZh3bp16NWrV6nX+vn5wd3dnTNgiYiIiIiIagiJRIKAgAClcnc1hqBRdbbKvnUFp00REdUA19QdQM2UlggYW6s7CqrO+Bl6c68aQ45vyUoam6o+ZlU9PiKimqYCvu4qIj+D4DpLpW2+XdqqO4AKpYgYrO4QRELPbyu1Py7MRURUzfn4+CA8PJylCIiIiIiIqIoYru4AqjWJRAJ/f394enqqOxRSIZYjICKqxgICAnDixAkmYImIiIiIiGqIvLw8LFy4EElJSeoORfUEoepslYxJWCKiauzgwYPQ1dWFlpYGBEFgbVgiIiIiIqIaIjAwUN0hkAqxHAERUTWVkZGBrKwsdYdBREREREREKqChIQD4b2LN7du31RcMqRyTsERE1VRKSoq6QyAiIiIiIiIVKawy91+puYyMDLXFUmE03t6nN1mOgIiIiIiIiIiIiKgCcSYsEVE1JZPJ1B0CERERERERqUjhEh//zRTV09NTWywVRnh754MyCUtEVE3p6elBKpVCoVAgPz8XBQWFj60oFIpSriQiIiIiIqKqRi5X4MVyBDY2NuoLhlTu7U0/ExHVAF5eXsjOzkZ+vhwKhYIJWCIiIiIiohrC19dX3SHQ/9uyZQtat24NQ0NDGBoaomPHjjhx4kS52mASloioGvPz84O7uzsE4e0tbk5ERERERFSTSCQSBAQEwMrKSt2hqJ4gVJ2tHBo3bozAwEBcu3YNV69exXvvvYd+/frh559/LvutKzhtioioBrim2ubSEgFj68q/tir1QUREyvi1l4iIqBK0VXcAFUoROULdIYhyO+5ATk6O0j4dHR3o6OiU6fratWtjzZo1GD9+fJnO50xYolK4urrCx8enxOPe3t7o379/pcWjaiEhITA2Nq7wflJSUiAIAmJjYyu8r6oiMjISgiAgLS1N3aGU35v8kl0Zv6AzCaAsLbFwIyKqSPzaS0REVDr+XF5trFy5EkZGRkrbypUrS72uoKAA+/fvR0ZGBjp27Fjm/rgwF1UYb29v7Ny5EytXrsT8+fPF/WFhYRgwYEC5alfKZDL4+Pi8MhmqLhs3bnwr6nCePXsWa9asweXLl5GVlQWZTIZevXph1qxZaNSokbrDq5KcnZ2RmpoKIyMjAIUJbx8fH5UnZX18fBAeHv5WfA6JiIiIiIhqOolEAn9/f3h6eqo7FNWrQqX0FixYgFmzZinte9Us2Fu3bqFjx47Izs6Gvr4+Dh8+DDs7uzL3x5mwVKF0dXWxatUqPH36VN2hlFtubm6ZzjMyMqqUmaTqtG3bNvTo0QNmZmYIDQ1FfHw8tm7dimfPnmHdunVqja2s71Nly8vLg7a2NszMzCq0XmtAQABOnDjBBCwREREREVENkZeXh4ULFyIpKUndodRoOjo64kJbz7dXJWGtra0RGxuLy5cv4+OPP8aYMWMQHx9f5v6YhKUK9TxxV9p07vPnz6NLly6QSqUwNzfH9OnTkZGRAaCwHMD9+/cxc+ZMCIIAQRCgUChgamqK7777TmzD0dERDRo0UGpTR0cHmZmZAIAHDx6gX79+0NfXh6GhIQYPHow///xTPH/ZsmVwdHTE119/jaZNm0JXV7fYWH/44QcYGRlhz549AIqWI3B1dcX06dMxb9481K5dG2ZmZli2bJlSG7dv30bnzp2hq6sLOzs7nD59GoIgICwsrMQxCg8PR+fOnWFsbIw6deqgb9++SE5OFo8/f9z/0KFD6NatG2rVqgUHBwdcvHhRqZ2QkBBYWFigVq1aGDBgAP7+++8S+wSAX3/9FdOnT8f06dOxY8cOuLq6QiaToWvXrvj666+xZMkSZGRkwNDQUOn9AApnPevp6eHff/9VundnZ2fo6uqiVatWiIqKUrrmp59+Qq9evaCvr4/69etj1KhRePz4sdL4Tp06FT4+Pqhbty7c3NygUCiwbNkyWFhYQEdHBw0bNsT06dPFa3JycjBnzhw0atQIenp6eOeddxAZGanUb3R0NFxdXVGrVi2YmJjAzc1N/OOBTCbDhg0blM53dHRUel8FQcCWLVvwwQcfQE9PDwEBAUrlCCIjIzF27Fg8e/ZM/BwvW7YMy5cvR6tWrYqMu6OjIxYvXvzK9wYADh48CF1dXWhpaYjtEhERERERUfUXGBio7hDoBdra2mjRogXatm2LlStXwsHBARs3bizz9UzCUoXS1NTEp59+is8//xy//vprseckJyfD3d0dnp6euHnzJg4cOIDz589j6tSpAIBDhw6hcePGWL58OVJTU5GamgpBENC1a1cxkfb06VMkJCQgKysLt2/fBgBERUWhffv2qFWrFuRyOfr164cnT54gKioKERER+OWXXzBkyBClWO7evYvQ0FAcOnSo2Nqle/fuxbBhw7Bnzx6MGFFyMemdO3dCT08Ply9fxurVq7F8+XJEREQAKKwd0r9/f9SqVQuXL1/GV199BT8/v1LHMiMjA7NmzcLVq1dx5swZaGhoYMCAAZDL5Urn+fn5Yc6cOYiNjYWVlRWGDRuG/Px8AMDly5cxfvx4TJ06FbGxsejWrRs++eSTV/Z78OBB5ObmYt68ecUeNzY2hp6eHoYOHYrg4GClY8HBwRg0aBAMDAzEfXPnzsXs2bNx48YNdOzYER4eHmIiOC0tDe+99x7atGmDq1evIjw8HH/++ScGDx5cZHy1tbURHR2NrVu3IjQ0FOvXr8e2bduQlJSEsLAw2Nvbi+dPnToVFy9exP79+3Hz5k14eXnB3d1d/KtibGwsunfvDjs7O1y8eBHnz5+Hh4cHCgoKXjk2L1u2bBkGDBiAW7duYdy4cUrHnJ2dsWHDBhgaGoqf4zlz5mDcuHFISEhATEyMeO6NGzdw8+ZNjB079pX9ZWRkICsrC9nZ2cjPl0OhUHBGLBERERERUTWloSFAQ0ND3J7nN2oUQaPqbG9ILpcXWdjrVVgTlircgAED4OjoiKVLlyIoKKjI8ZUrV2LEiBFivVdLS0ts2rQJLi4u2LJlC2rXrg1NTU0YGBjAzMxMvM7V1RXbtm0DAJw7dw5t2rSBmZkZIiMjYWNjg8jISLi4uAAAzpw5g1u3buHevXswNzcHAOzatQstW7ZETEwM2rdvD6Dw0fZdu3bB1NS0SJxffPEF/Pz88P3334vtlqR169ZYunSpeD+bN2/GmTNn0LNnT0RERCA5ORmRkZHi/QQEBKBnz56vbPPlWjA7duyAqakp4uPjlWZSzpkzB3369AEA+Pv7o2XLlrh79y5sbGywceNGuLu7iwlVKysrXLhwAeHh4SX2m5SUBENDQ6VZxsWZMGGCWAO1QYMGePToEY4fP47Tp08rnTd16lTxXrZs2YLw8HAEBQVh3rx52Lx5M9q0aYNPP/1U6T7Nzc1x584dWFlZiWO6evVq8ZwffvgBZmZm6NGjByQSCSwsLNChQwcAhTOgg4OD8eDBAzRs2FAco/DwcAQHB+PTTz/F6tWr0a5dO3z55Zdimy1btnzl/RZn+PDhSonTX375Rfy3trY2jIyMIAiC0udYX18fbm5uCA4OFj+HwcHBcHFxQbNmzYrtJycnBzk5OTXzGzIREREREdFbqnBOzX8Ta54/IUzqt2DBAvTq1QsWFhb4999/sXfvXkRGRuLkyZNlboMzYalSrFq1Cjt37kRCQkKRY3FxcQgJCYG+vr64ubm5QS6X4969eyW26eLigvj4ePz111+IioqCq6srXF1dERkZiby8PFy4cAGurq4AgISEBJibm4sJWACws7ODsbGxUkxNmjQpNgH73XffYebMmYiIiCg1AQsUJmFf9DwpCQCJiYkwNzdXSsQ9Txi+SlJSEoYNG4ZmzZrB0NAQMpkMQGGSsaS+nydOn/edkJCAd955R+n80lbyUygUZXrEvUOHDmjZsiV27twJAPjmm2/QpEkTdO3atcT+tLS00K5dO/E9iIuLw9mzZ5U+CzY2NgCgVHqhbdu2Sm16eXkhKysLzZo1w8SJE3H48GFx9u+tW7dQUFAAKysrpXajoqLENp/PhH1T7dq1e63rJk6ciH379iE7Oxu5ubnYu3dvkZm0L3q+gmOXLl1eN1QiIiIiIiIiKqNHjx5h9OjRsLa2Rvfu3RETE4OTJ0+WOqHuRZwJS5Wia9eucHNzw4IFC+Dt7a10LD09HZMmTVKq4fmchYVFiW3a29ujdu3aiIqKQlRUFAICAmBmZoZVq1YhJiYGeXl5cHZ2Llecenp6xe5v06YNrl+/jh07dqBdu3alJiUlEonSa0EQipQNKC8PDw80adIE27dvR8OGDSGXy9GqVasiC1O92PfzON+kbysrKzx79kyc4foqEyZMwBdffIH58+cjODgYY8eOLVeN0vT0dHh4eGDVqlVFjr3Y98vvk7m5ORITE3H69GlERERg8uTJWLNmDaKiopCeng5NTU1cu3YNmpqaStfp6+sDAKRS6Svj0tDQKPKYf15eXpHzSvr8lMbDwwM6Ojo4fPgwtLW1kZeXh0GDBpV4/vMVHDMzM8v0RwEiIiIiIiKq+gp/ff7vd+jX/R2zStOonuuYFPdkd3lxJixVmsDAQHz//fdFFopycnJCfHw8WrRoUWTT1tYGUPgo98v1OQVBQJcuXXDkyBH8/PPP6Ny5M1q3bo2cnBxs27YN7dq1E79g2dra4uHDh3j48KF4fXx8PNLS0mBnZ1dq7M2bN8fZs2dx5MgRTJs27Y3GwdraGg8fPlRaFOzFeqDF+fvvv5GYmIhFixahe/fusLW1FReNKg9bW1tcvnxZad+lS5deec2gQYOgra2t9Pj/i9LS0sR/jxw5Evfv38emTZsQHx+PMWPGFDn/xf7y8/Nx7do12NraAij8LPz888+QyWRFPgulffORSqXw8PDApk2bEBkZiYsXL+LWrVto06YNCgoK8OjRoyJtPp+N3Lp1a5w5c6bEtk1NTZGamiq+/ueff145S7skxX2OgcIZwWPGjEFwcDCCg4MxdOjQVyaGn6/gaGZmBqlUyoW5iIiIiIiIagC5XAG5XC5uz58MpZqBSViqNPb29hgxYgQ2bdqktN/X1xcXLlwQF4tKSkrCkSNHxIW5gMLV6c+dO4fffvsNjx8/Fve7urpi3759cHR0hL6+PjQ0NNC1a1fs2bNHaYZgjx49xP6vX7+OK1euYPTo0XBxcSnzI+RWVlY4e/YsQkNDxfq1r6Nnz55o3rw5xowZg5s3byI6OhqLFi0CgBITaCYmJqhTpw6++uor3L17F//73/8wa9ascvc9ffp0hIeHY+3atUhKSsLmzZtfWQ8WKJxlun79emzcuBHjx49HVFQU7t+/j+joaEyaNAkrVqxQinPgwIGYO3cu3n//fTRu3LhIe1988QUOHz6M27dvY8qUKXj69Kn46P2UKVPw5MkTDBs2DDExMUhOTsbJkycxduzYVy6SFRISgqCgIPz000/45Zdf8M0330AqlaJJkyawsrLCiBEjMHr0aBw6dAj37t3DlStXsHLlSvzwww8ACmeWxsTEYPLkybh58yZu376NLVu2iJ+19957D7t378aPP/6IW7duYcyYMUVm1ZaFTCZDeno6zpw5g8ePHyMzM1M8NmHCBPzvf/9DeHj4K0sRvMzLy4sLcxEREREREdVAvr6+6g5B9QSh6myVjElYqlTLly8v8mh869atERUVhTt37qBLly5o06YNlixZIi6i9Py6lJQUNG/eXKlmq4uLCwoKCsTar0BhYvblfYIg4MiRIzAxMUHXrl3Ro0cPNGvWDAcOHChX/NbW1vjf//6Hffv2Yfbs2eW7+f+nqamJsLAwpKeno3379pgwYQL8/PwAALq6usVeo6Ghgf379+PatWto1aoVZs6ciTVr1pS773fffRfbt2/Hxo0b4eDggFOnTokJ4FeZPHkyTp06hd9++w0DBgyAjY0NJkyYAENDQ8yZM0fp3PHjxyM3N7fERGJgYCACAwPh4OCA8+fP4+jRo6hbty4AoGHDhoiOjkZBQQHef/992Nvbw8fHB8bGxtDQKPnLlbGxMbZv345OnTqhdevWOH36NL7//nvUqVMHQOFCV6NHj8bs2bNhbW2N/v37IyYmRix3YWVlhVOnTiEuLg4dOnRAx44dceTIEWhpFVZsWbBgAVxcXNC3b1/06dMH/fv3R/PmzUsf8Jc4Ozvjo48+wpAhQ2Bqaqo0u9jS0hLOzs6wsbEpUrf3Vfz8/ODu7s4ZsERERERERDWERCJBQECAuDg11QyCgtOmiNQuOjoanTt3xt27d18ruVeV7N69GzNnzsTvv/8ulpOg0ikUClhaWmLy5MmvNcsZuKbymKqUtETA2FrdUVBNwM8SERFVN/zeRfSWaVv6KdWYItpb3SGIhE4hldofF+YiUoPDhw9DX18flpaWuHv3LmbMmIFOnTpV6wRsZmYmUlNTERgYiEmTJjEBWw5//fUX9u/fjz/++ANjx44t9/U+Pj4IDw9nKQIiIiIiIqIaQCKRwN/fH56enuoORfWEt/eh/Lf3zonU6N9//8WUKVNgY2MDb29vtG/fHkeOHFF3WG9k9erVsLGxgZmZGRYsWKDucKqVevXqYfny5fjqq69gYmJSrmsDAgJw4sQJJmCJiIiIiIhqiLy8PCxcuBBJSUnqDoVUiOUIiIiqMUdHRygUCuTn56KgoPDLOb+sExERERERVX+dO3dGUFCQusNQKcWFsi9EXdEE5x2V2h/LERARVVMZGRnIyspSdxhERERERESkAhoaAoD/Fl2+ffu2+oKpKG/xotJMwhIRVVMpKSnqDoGIiIiIiIhUpPChxv+ebMzIyFBbLKR6rAlLREREREREREREVIE4E5aIqJqSyWTqDoGIiIiIiIhUpPBJ/f8e19fT01NbLBVGg+UIiIiomtHT04NUKuXCXERERERERDWAXK7Ai+UIbGxs1BcMqRzLERARVWNeXl7Izs5Gfr4cCoWCCVgiIiIiIqIawtfXV90hqJ6gUXW2SsYkLBFRNebn5wd3d3cIb/EKk0RERERERDWJRCJBQEAArKys1B0KqZCg4LQpIiKVSUlJQdOmTXHjxg04OjpWYs/XKrEvNUhLBIyt1R0F1QT8LBERUXXD711Eb5m26g6gQimufKjuEERCh68qtT/WhCV6DQ8fPsTSpUsRHh6Ox48fo0GDBujfvz+WLFmCOnXqqC2uixcvonPnznB3d8cPP/ygdKw8ycF9+/Zh5MiR+Oijj/DFF18oHYuMjES3bt3E1/Xq1UPnzp2xZs0aNGvWDEDhglE+Pj7w8fEptv1ly5YhLCwMsbGxZb630tpUB29vb6SlpSEsLEzcZ25ujtTUVNStW7fS4vDx8UF4eDhLERAREREREdUAEokE/v7+8PT0VHcoqvcWP8XJcgRE5fTLL7+gXbt2SEpKwr59+3D37l1s3boVZ86cQceOHfHkyRO1xRYUFIRp06bh3Llz+P3339+onXnz5mHfvn3Izs4u9pzExET8/vvvOHjwIH7++Wd4eHigoKDgtfusSvLy8l77Wk1NTZiZmUFLq3L+xhUQEIATJ04wAUtERERERFRD5OXlYeHChUhKSlJ3KKRCTMISldOUKVOgra2NU6dOwcXFBRYWFujVqxdOnz6N3377DX5+fuK5MpkMK1aswLBhw6Cnp4dGjRoVmVmalpaGCRMmwNTUFIaGhnjvvfcQFxcnHl+2bBkcHR2xe/duyGQyGBkZYejQofj333+V2klPT8eBAwfw8ccfo0+fPggJCXmt+7t37x4uXLiA+fPnw8rKCocOHSr2vHr16qFBgwbo2rUrlixZgvj4eNy9e/e1+vT29kb//v2xdu1aNGjQAHXq1MGUKVPEZKirqyvu37+PmTNnQhAEpfqn58+fR5cuXSCVSmFubo7p06cjIyNDPJ6amoo+ffpAKpWiadOm2Lt3L2QyGTZs2CCeIwgCtmzZgg8++AB6enoICAhAQUEBxo8fj6ZNm0IqlcLa2hobN24Ur1m2bBl27tyJI0eOiDFFRkYiJSUFgiAozfKNiopChw4doKOjgwYNGmD+/PnIz88Xj7u6umL69OmYN28eateuDTMzMyxbtqxMY3fw4EHo6upCS0ujyNgQERERERFR9RUYGKjuEEiFmIQlKocnT57g5MmTmDx5MqRSqdIxMzMzjBgxAgcOHFCalbhmzRo4ODjgxo0bmD9/PmbMmIGIiAjxuJeXFx49eoQTJ07g2rVrcHJyQvfu3ZVm1CYnJyMsLAzHjh3DsWPHEBUVVeSL8bfffgsbGxtYW1tj5MiR2LFjx2vNjgwODkafPn1gZGSEkSNHIigoqNRrno9Fbm5uuft77uzZs0hOTsbZs2exc+dOhISEiInkQ4cOoXHjxli+fDlSU1ORmpoKoHBc3N3d4enpiZs3b+LAgQM4f/48pk6dKrY7evRo/P7774iMjERoaCi++uorPHr0qEj/y5Ytw4ABA3Dr1i2MGzcOcrkcjRs3xsGDBxEfH48lS5Zg4cKF+PbbbwEAc+bMweDBg+Hu7i7G5OzsXKTd3377Db1790b79u0RFxeHLVu2ICgoCJ988onSeTt37oSenh4uX76M1atXY/ny5Uqfk+JkZGQgKysL2dnZyM+XQ6FQcEYsERERERFRNaWhIUBDQ0Pcbt++re6QVE8Qqs5WyVgTlqgckpKSoFAoYGtrW+xxW1tbPH36FH/99Rfq1asHAOjUqRPmz58PALCyskJ0dDTWr1+Pnj174vz587hy5QoePXoEHR0dAMDatWsRFhaG7777Dh9+WFiwWi6XIyQkBAYGBgCAUaNG4cyZMwgICBD7DgoKwsiRIwEA7u7uePbsGaKiouDq6lrm+3vez+effw4AGDp0KGbPno179+6hadOmxV6TmpqKtWvXolGjRrC2fv0FA0xMTLB582ZoamrCxsYGffr0wZkzZzBx4kTUrl0bmpqaMDAwgJmZmXjNypUrMWLECLFOrKWlJTZt2gQXFxds2bIFKSkpOH36NGJiYtCuXTsAwNdffw1LS8si/Q8fPhxjx45V2ufv7y/+u2nTprh48SK+/fZbDB48GPr6+pBKpcjJyVGK6WVffvklzM3NsXnzZgiCABsbG/z+++/w9fXFkiVLoKFR+Lew1q1bY+nSpeJ9bN68GWfOnEHPnj2LtJmTk4OcnJya+Q2ZiIiIiIjoLVU4p+a/iTUvPuVJ1R9nwhK9hvLMNuzYsWOR1wkJCQCAuLg4pKeno06dOtDX1xe3e/fuITk5WbxGJpOJCVgAaNCggdJszsTERFy5cgXDhg0DAGhpaWHIkCFlmsX6ooiICGRkZKB3794AgLp166Jnz57YsWNHkXMbN24MPT09NGzYEBkZGQgNDYW2tna5+ntRy5YtoampKb5++R6LExcXh5CQEKWxc3Nzg1wux71795CYmAgtLS04OTmJ17Ro0QImJiZF2nqepH3RF198gbZt28LU1BT6+vr46quv8ODBg3LdV0JCAjp27KhUJqBTp05IT0/Hr7/+Ku5r3bq10nWvuv+VK1fCyMgIXbp0KVcsRERERERERKQenAlLVA4tWrSAIAhISEjAgAEDihxPSEiAiYkJTE1Ny9Reeno6GjRogMjIyCLHjI2NxX9LJBKlY4IgQC6Xi6+DgoKQn5+Phg0bivsUCgV0dHSwefNmGBkZlSmeoKAgPHnyRKnUglwux82bN+Hv7y/O2gSAH3/8EYaGhqhXr55Sgvh1lXaPxUlPT8ekSZMwffr0IscsLCxw586dMvevp6en9Hr//v2YM2cO1q1bh44dO8LAwABr1qzB5cuXy9xmeZTn/hcsWIBZs2YhMzMTLi4uFRIPERERERERVa7CuTv/TeB5+ffUGuEtXseESViicqhTpw569uyJL7/8EjNnzlRKVv7xxx/Ys2cPRo8erTTr8dKlS0ptXLp0SSxn4OTkhD/++ANaWlqQyWSvFVN+fj527dqFdevW4f3331c61r9/f+zbtw8fffRRqe38/fffOHLkCPbv34+WLVuK+wsKCtC5c2ecOnUK7u7u4v6mTZsqJYormra2NgoKCpT2OTk5IT4+Hi1atCj2Gmtra+Tn5+PGjRto27YtAODu3bt4+vRpqf1FR0fD2dkZkydPFve9ODu5pJheZmtri9DQUCgUCvFzER0dDQMDAzRu3LjUOIqjo6MDHR0dGBoaQiqVQqFQID8/FwUFhTO0WReWiIiIiIio+pHLFXixHIGNjY36giGVYzkConLavHkzcnJy4ObmhnPnzuHhw4cIDw9Hz5490ahRI6U6rUBhwm316tW4c+cOvvjiCxw8eBAzZswAAPTo0QMdO3ZE//79cerUKaSkpODChQvw8/PD1atXyxTPsWPH8PTpU4wfPx6tWrVS2jw9PctckmD37t2oU6cOBg8erNSGg4MDevfuXe7SBqomk8lw7tw5/Pbbb3j8+DEAwNfXFxcuXMDUqVMRGxuLpKQkHDlyRFyYy8bGBj169MCHH36IK1eu4MaNG/jwww8hlUqVEuXFsbS0xNWrV3Hy5EncuXMHixcvRkxMTJGYbt68icTERDx+/Bh5eXlF2pk8eTIePnyIadOm4fbt2zhy5AiWLl2KWbNmKc0sfl1eXl5cmIuIiIiIiKgG8vX1VXcIpEJMwhKV0/PkXLNmzTB48GA0b94cH374Ibp164aLFy+idu3aSufPnj0bV69eRZs2bfDJJ5/gs88+g5ubG4DCR86PHz+Orl27YuzYsbCyssLQoUNx//591K9fv0zxBAUFoUePHsWWHPD09MTVq1dx8+bNUtvZsWMHBgwYUGxy0tPTE0ePHhWTn+qwfPlypKSkoHnz5mK5h9atWyMqKgp37txBly5d0KZNGyxZskSpLMOuXbtQv359dO3aFQMGDMDEiRNhYGAAXV3dV/Y3adIkDBw4EEOGDME777yDv//+W2lWLABMnDgR1tbWaNeuHUxNTREdHV2knUaNGuH48eO4cuUKHBwc8NFHH2H8+PFYtGiRCkYF8PPzg7u7e6lJZSIiIiIiIqoeJBIJAgICYGVlpe5QVE9Do+pslUxQcNoUUYWRyWTw8fGBj4+PukOh//frr7/C3Nwcp0+fRvfu3dUdjgpdU3cAVN2kJQLG1pV/LZWPKsf6Tdvi+1518b0pHAOA41AdVbXPb1WLh94MvzZQWVS5//dt1R1AhVLcmKLuEERCmy8qtT/OhCWiGu1///sfjh49inv37uHChQsYOnQoZDIZunbtqu7QqqbnP6i+7TG8Dd7kB01V/pDK9/vV3nSsXxzf8rb1/Nrq9Avs2/p5qg7vTUUztuY4VFdV7X2ravHQm+HXBioLfkYqlyBUna2ScWEuIqrR8vLysHDhQvzyyy8wMDCAs7Mz9uzZA4lEou7QVMbHxwfh4eGsB0tERERERFQDSCQS+Pv7w9PTU92hkAqxHAERUTUWEBCAXbt2qTsMIiIiIiIiUrFjx47B0tJS3WGolCJ2qrpDEAmOmyu1P5YjICKqxg4ePAhdXV1oaWlAEAQu0EVERERERFRDBAYGqjsE1VN3CQKWIyAiovLKyMhAVlaWusMgIiIiIiIiFdDQEAD8lxy8ffu2+oIhlWMSloiomkpJSVF3CERERERERKQihQVD/6sampGRobZYSPWYhCUiIiIiIiIiIqKKJ7y9lVGZhCUiqqZkMpm6QyAiIiIiIiIVKSxT+l85Aj09PbXFQqrHJCwRUTWlp6cHqVQKhUKB/PxcFBQUPraiUChKuZKIiIiIiIiqGrlcgRfLEdjY2KgvGFK5t3cOMBFRDeDl5YXs7Gzk58uhUCiYgCUiIiIiIqohfH191R2C6mkIVWer7Fuv9B6JiEhl/Pz84O7uDkGo/G8gREREREREpHoSiQQBAQGwsrJSdyikQoKC06boLeHt7Y20tDSEhYVVaD8ymQw+Pj7w8fEp0/murq5wdHTEhg0bKjQuVaqssayO1Pd+Xqvk/oiIqEpLSwSMrdUdBREVh/8/ieiV2qo7gAql+HmmukMQCS3XV2p/rAlLauXt7Y2dO3cCKPxLj4WFBUaPHo2FCxdCS6tqfzxDQkLg4+ODtLQ0pf0xMTHlKp596NAhSCQS8XV5k7jFKW1W5NKlS7Fs2bLXbv9NpKSkoGnTprhx4wYcHR3LdM2yZcsQFhaG2NjYCo2tPCIjI9GtWzc8ffoUxsbG4v6X38/K4OPjg/DwcJYiICIiIiIiqgEkEgn8/f3h6emp7lBIhap2loveCu7u7ggODkZOTg6OHz+OKVOmQCKRYMGCBUXOzc3Nhba2thqiLDtTU9NynV+7dm2Vx5Camir++8CBA1iyZAkSExPFffr6+irvs6Z4089YRbyfrxIQEIATJ05Uap9ERERERERUcfLy8rBw4UK0bt0alpaW6g6HVIQ1YUntdHR0YGZmhiZNmuDjjz9Gjx49cPToUQCFM2X79++PgIAANGzYENbWhY/t3Lp1C++99x6kUinq1KmDDz/8EOnp6WKbBQUFmDVrFoyNjVGnTh3MmzevyCxBmUxW5JFxR0dHpRmiaWlpmDRpEurXrw9dXV20atUKx44dQ2RkJMaOHYtnz55BEAQIgiBe92K7w4cPx5AhQ5T6yMvLQ926dbFr1y4AhY+vP5/16urqivv372PmzJliuxkZGTA0NMR3332n1E5YWBj09PTw77//FhlTMzMzcTMyMoIgCOLrevXq4bPPPkPjxo2ho6MDR0dHhIeHK11f2vi+7LvvvoO9vb14fo8ePZCRkVHi+S+KjIyEIAg4c+YM2rVrh1q1asHZ2VlMGoeEhMDf3x9xcXHimISEhIjvz4QJE2BqagpDQ0O89957iIuLU2r/k08+Qb169WBgYIAJEyZg/vz5SjNwS/qM7d69G+3atYOBgQHMzMwwfPhwPHr0CEDhbN5u3boBAExMTCAIAry9vQEov58A8PTpU4wePRomJiaoVasWevXqhaSkJPF4SEgIjI2NcfLkSdja2kJfXx/u7u5KifRXOXjwIHR1daGlpSGODxEREREREVV/gYGB6g5B9QSNqrNVMiZhqcqRSqXIzc0VX585cwaJiYmIiIjAsWPHkJGRATc3N5iYmCAmJgYHDx7E6dOnMXXqVPGadevWISQkBDt27MD58+fx5MkTHD58uFxxyOVy9OrVC9HR0fjmm28QHx+PwMBAaGpqwtnZGRs2bIChoSFSU1ORmpqKOXPmFGljxIgR+P7775USmCdPnkRmZiYGDBhQ5PxDhw6hcePGWL58udiunp4ehg4diuDgYKVzg4ODMWjQIBgYGJTrvjZu3Ih169Zh7dq1uHnzJtzc3PDBBx+IicGyjO+LUlNTMWzYMIwbNw4JCQmIjIzEwIEDy/1ovJ+fH9atW4erV69CS0sL48aNAwAMGTIEs2fPRsuWLcUxeZ7Y9vLywqNHj3DixAlcu3YNTk5O6N69O548eQIA2LNnDwICArBq1Spcu3YNFhYW2LJlS5G+X/6MAYXJ8hUrViAuLg5hYWFISUkRE63m5uYIDQ0FACQmJiI1NRUbN24s9r68vb1x9epVHD16FBcvXoRCoUDv3r2Rl5cnnpOZmYm1a9di9+7dOHfuHB48eFDs5+llGRkZyMrKQnZ2NvLz5VAoFCxJQEREREREVE1paAjQ0NAQt9u3b6s7JFIhliOgKkOhUODMmTM4efIkpk2bJu7X09PD119/LT4ivn37dmRnZ2PXrl1i7dXNmzfDw8MDq1atQv369bFhwwYsWLAAAwcOBABs3boVJ0+eLFc8p0+fxpUrV5CQkCCuSNisWTPx+IszTEvi5uYGPT09HD58GKNGjQIA7N27Fx988EGxydPatWtDU1NTnH353IQJE+Ds7IzU1FQ0aNAAjx49wvHjx3H69Oly3RMArF27Fr6+vhg6dCgAYNWqVTh79iw2bNiAL774Anv37i11fF+UmpqK/Px8DBw4EE2aNAEA2NvblzuugIAAuLi4AADmz5+PPn36IDs7G1KpFPr6+tDS0lIak/Pnz+PKlSt49OgRdHR0xHsLCwvDd999hw8//BCff/45xo8fj7FjxwIAlixZglOnThWZ1fvyZwyAmAQGCt/3TZs2oX379khPT4e+vr5YdqBevXpKNWFflJSUhKNHjyI6OhrOzs4AChPD5ubmCAsLg5eXF4DChO/WrVvRvHlzAMDUqVOxfPnyEscqJycHOTk5/IZMRERERERUgxTOqflvYk1ZnzCl6oEzYUntjh07Bn19fejq6qJXr14YMmSIUkkAe3t7peRYQkICHBwclBa/6tSpE+RyORITE/Hs2TOkpqbinXfeEY9raWmhXbt25YorNjYWjRs3FhOwr0NLSwuDBw/Gnj17ABR+AT1y5AhGjBhRrnY6dOiAli1biouYffPNN2jSpAm6du1arnb++ecf/P777+jUqZPS/k6dOiEhIQFA6eP7MgcHB3Tv3h329vbw8vLC9u3b8fTp03LFBQCtW7cW/92gQQMAEB//L05cXBzS09NRp04d6Ovri9u9e/eQnJwMoHCWaocOHZSue/k1UPQzBgDXrl2Dh4cHLCwsYGBgICaIHzx4UOZ7SkhIgJaWltJnsU6dOrC2thbHGwBq1aolJmABiIn2kqxcuRJGRkbo0qVLmWMhIiIiIiIiUjtBqDpbJWMSltSuW7duiI2NRVJSErKysrBz506lBOCL/1YlDQ2NIo9uv/iIuFQqVUk/I0aMwJkzZ/Do0SOEhYVBKpXC3d293O1MmDBBrIUaHByMsWPHVon6n5qamoiIiMCJEydgZ2eHzz//HNbW1rh371652pFIJOK/n9+XXC4v8fz09HQ0aNAAsbGxSltiYiLmzp1brr5f/ow9L8lgaGiIPXv2ICYmRixn8WKpDFV58d6Bwvt/VVmBBQsW4NmzZ7h//77KYyEiIiIiIiL1KMwNCuJWUfkQUg8mYUnt9PT00KJFC1hYWEBLq/QKGba2toiLi1Oalh8dHQ0NDQ1YW1vDyMgIDRo0wOXLl8Xj+fn5uHbtmlI7pqamSosf/fPPP0qJw9atW+PXX3/FnTt3io1DW1sbBQUFpcbr7OwMc3NzHDhwAHv27IGXl1eRpFtZ2h05ciTu37+PTZs2IT4+HmPGjCm175cZGhqiYcOGiI6OVtofHR0NOzs7AKWPb3EEQUCnTp3g7++PGzduQFtbu9w1eF+luDFxcnLCH3/8AS0tLbRo0UJpq1u3LgDA2toaMTExSte9/Lo4t2/fxt9//43AwEB06dIFNjY2RWamPp85+6rPgK2tLfLz85U+i3///TcSExPF8X4dOjo6MDQ0hJmZGaRSKRfmIiIiIiIiqgHkcgXkcrm42djYqDskUiEmYanaGTFiBHR1dTFmzBj89NNPOHv2LKZNm4ZRo0aJ9UpnzJiBwMBAhIWF4fbt25g8eTLS0tKU2nnvvfewe/du/Pjjj7h16xbGjBkDTU1N8biLiwu6du0KT09PRERE4N69ezhx4gTCw8MBADKZDOnp6Thz5gweP36MzMzMEmMePnw4tm7dioiIiFJLEchkMpw7dw6//fYbHj9+LO43MTHBwIEDMXfuXLz//vto3LhxeYcOADB37lysWrUKBw4cQGJiIubPn4/Y2FjMmDEDQNnG90WXL1/Gp59+iqtXr+LBgwc4dOgQ/vrrL9ja2r5WfMWRyWS4d+8eYmNj8fjxY+Tk5KBHjx7o2LEj+vfvj1OnTiElJQUXLlyAn58frl69CgCYNm0agoKCsHPnTiQlJeGTTz7BzZs3S01UWlhYQFtbG59//jl++eUXHD16FCtWrFA6p0mTJhAEAceOHcNff/1VpM4sAFhaWqJfv36YOHEizp8/j7i4OIwcORKNGjVCv379VDI2Xl5eXJiLiIiIiIioBvL19VV3CKqn7hIELEdAVHa1atXCyZMn8eTJE7Rv3x6DBg1C9+7dsXnzZvGc2bNnY9SoURgzZgw6duwIAwMDDBgwQKmdBQsWwMXFBX379kWfPn3Qv39/pbqcABAaGor27dtj2LBhsLOzw7x588SZj87Ozvjoo48wZMgQmJqaYvXq1SXGPGLECMTHx6NRo0ZF6rG+bPny5UhJSUHz5s1hamqqdGz8+PHIzc1VWjSqvKZPn45Zs2Zh9uzZsLe3R3h4OI4ePQpLS0sAZRvfFxkaGuLcuXPo3bs3rKyssGjRIqxbtw69evV67Rhf5unpCXd3d3Tr1g2mpqbYt28fBEHA8ePH0bVrV4wdOxZWVlYYOnQo7t+/LyaLR4wYgQULFmDOnDlwcnLCvXv34O3tDV1d3Vf2Z2pqipCQEBw8eBB2dnYIDAzE2rVrlc5p1KgR/P39MX/+fNSvXx9Tp04ttq3g4GC0bdsWffv2RceOHaFQKHD8+PFXzoYuDz8/P7i7u3MGLBERERERUQ0hkUgQEBDwRmvUUNUjKDhtiqja2L17N2bOnInff/+9yEJSVDY9e/aEmZkZdu/ere5QVOxa6acQEdHbIy0RMC6+jBARqRn/fxLRK7VVdwAVSnG7fGu4VCTBZk2l9ld6AU4iUrvMzEykpqYiMDAQkyZNYgK2jDIzM7F161a4ublBU1MT+/btw+nTpxEREaHu0FTKx8cH4eHhLEVARERERERUA0gkEvj7+8PT01Pdoaiextv7UP7be+dE1cjq1athY2MDMzMzLFiwQN3hVBsvlixo27Ytvv/+e4SGhqJHjx7qDk1lAgICcOLECSZgiYiIiIiIaoi8vDwsXLgQSUlJ6g6FVIjlCIiIqjFHR0coFArk5+eioKDwyzm/rBMREREREVV/nTt3RlBQkLrDUCnFnfnqDkEkWAVWan8sR0BEVE1lZGQgKytL3WEQERERERGRCmhoCAD+W3T59u3b6guGVI5JWCKiaiolJUXdIRAREREREZGKFD7U+N+TjRkZGWqLhVSPSVgiIiIiIiIiIiKqeIJQ+jk1FJOwRETVlEwmU3cIREREREREpCKF+cn/kpR6enpqi4VUj0lYIqJqSk9PD1KplAtzERERERER1QByuQIvliOwsbFRXzCkchrqDoCIiF6fl5cXsrOzkZ8vh0KhYAKWiIiIiIiohvD19VV3CKonaFSdrZIxCUtEVI35+fnB3d0dwltcV4eIiIiIiKgmkUgkCAgIgJWVlbpDIRUSFJw2RUSkMq6urnB0dMSGDRsquedrldwfERFVOWmJgLG1uqMgIqoZ+DWV1KatugOoUIq7fuoOQSS0CKjU/lgTlqgSPHz4EEuXLkV4eDgeP36MBg0aoH///liyZAnq1KlT6fGoL1H4n3/++QerVq1CaGgoUlJSYGxsjFatWmHy5MkYMGBAlZ/ZGRkZiW7duuHp06cwNjYW9x86dAgSiaRSY/Hx8UF4eDhLERAREREREdUAEokE/v7+8PT0VHcoFaBq/65fkViOgKiC/fLLL2jXrh2SkpKwb98+3L17F1u3bsWZM2fQsWNHPHnyRN0hVrq0tDQ4Oztj165dWLBgAa5fv45z585hyJAhmDdvHp49e6buEF9b7dq1YWBgUGn9BQQE4MSJE0zAEhERERER1RB5eXlYuHAhkpKS1B0KqRCTsEQVbMqUKdDW1sapU6fg4uICCwsL9OrVC6dPn8Zvv/0GP7//puILgoCwsDCl642NjRESEiK+9vX1hZWVFWrVqoVmzZph8eLFyMvLE48vW7YMjo6O2L17N2QyGYyMjDB06FD8+++/AABvb29ERUVh48aNEAQBgiAgJSUFISEhSjM6ASAsLExpRurztnfs2AELCwvo6+tj8uTJKCgowOrVq2FmZoZ69eohIODVU/oXLlyIlJQUXL58GWPGjIGdnR2srKwwceJExMbGQl9fHwDw9OlTjB49GiYmJqhVqxZ69eql9E3oeczHjh2DtbU1atWqhUGDBiEzMxM7d+6ETCaDiYkJpk+fjoKCAvE6mUyGFStWYNiwYdDT00OjRo3wxRdfiMdTUlIgCAJiY2PFfWlpaRAEAZGRkUhJSUG3bt0AACYmJhAEAd7e3gAKZxn7+Pgo9fXpp59i3LhxMDAwgIWFBb766iul8bhw4QIcHR2hq6uLdu3aieP+Yv8lOXjwIHR1daGlpSG+n0REREREVPPwR/23T2BgoLpDUD1BqDpbJWMSlqgCPXnyBCdPnsTkyZMhlUqVjpmZmWHEiBE4cOBAuWYxGhgYICQkBPHx8di4cSO2b9+O9evXK52TnJyMsLAwHDt2DMeOHUNUVJT4xXvjxo3o2LEjJk6ciNTUVKSmpsLc3LzM/ScnJ+PEiRMIDw/Hvn37EBQUhD59+uDXX39FVFQUVq1ahUWLFuHy5cvFXi+Xy7F//36MGDECDRs2LHJcX18fWlqFlVK8vb1x9epVHD16FBcvXoRCoUDv3r2Vks6ZmZnYtGkT9u/fj/DwcERGRmLAgAE4fvw4jh8/jt27d2Pbtm347rvvlPpZs2YNHBwccOPGDcyfPx8zZsxAREREmcbA3NwcoaGhAIDExESkpqZi48aNJZ6/bt06tGvXDjdu3MDkyZPx8ccfIzExEUBhWQYPDw/Y29vj+vXrWLFiRZlXwMzIyEBWVhays7ORny+HQqHgjFgiIiIiohpKV1dH3SFQBdPQEKChoSFut2/fVndIpEKsCUtUgZKSkqBQKGBra1vscVtbWzx9+hR//fUX6tWrV6Y2Fy1aJP5bJpNhzpw52L9/P+bNmyful8vlCAkJER+LHzVqFM6cOYOAgAAYGRlBW1sbtWrVgpmZWbnvSS6XY8eOHTAwMICdnR26deuGxMREHD9+HBoaGrC2tsaqVatw9uxZvPPOO0Wuf/z4MZ4+fQobG5tX9pOUlISjR48iOjoazs7OAIA9e/bA3NwcYWFh8PLyAlD4mMaWLVvQvHlzAMCgQYOwe/du/Pnnn9DX1xdjPHv2LIYMGSK236lTJ8yfPx8AYGVlhejoaKxfvx49e/YsdQw0NTVRu3ZtAEC9evWKzCB+We/evTF58mQAhTOZ169fj7Nnz8La2hp79+6FIAjYvn07dHV1YWdnh99++w0TJ04ssb2cnBzk5OTwGzIRERER0VuET73VfIVzav6bWJORkaG2WEj1OBOWqBKUNjtRW1u7zG0dOHAAnTp1gpmZGfT19bFo0SI8ePBA6RyZTKZUl7RBgwZ49OhR+YIuwctt169fH3Z2dtDQ0FDaV1J/ZZ2pmZCQAC0tLaVEbp06dWBtbY2EhARxX61atcQE7PO+ZTKZWNKgpHg6duxY5PWL7apS69atxX8LggAzMzMxnsTERLRu3Rq6urriOR06dHhleytXroSRkRG6dOlSIfESERERERERVQhBo+pslYxJWKIK1KJFCwiCUGJyLyEhAaampuJMSkEQiiQpX3z0/uLFixgxYgR69+6NY8eO4caNG/Dz80Nubq7SNRKJROm1IAiQy+WvjFVDQ+OVfb+q7fL09/x+VTWL803jKc7zhPKL41HcWLxJjOWJ52ULFizAs2fPcP/+/ddug4iIiIiIqheWHqv5CkuVCuKmp6en7pBIhZiEJapAderUQc+ePfHll18iKytL6dgff/yBPXv2iAs6AYUJytTUVPF1UlISMjMzxdcXLlxAkyZN4Ofnh3bt2sHS0vK1EnHa2tpKC1U97/vff/9VetyhLAtDlZeGhgaGDh2KPXv24Pfffy9yPD09Hfn5+bC1tUV+fr5Sbdm///4biYmJsLOze+M4Ll26VOT187IRpqamAKD0Xrw8Fs9nL788juVlbW2NW7duIScnR9wXExPzymt0dHRgaGgIMzMzSKVSLsxFRERERPQWyM7OKf0kqtbkcgXkcrm4lVbGj6oXJmGJKtjmzZuRk5MDNzc3nDt3Dg8fPkR4eDh69uwJKysrLFmyRDz3vffew+bNm3Hjxg1cvXoVH330kdIsSktLSzx48AD79+9HcnIyNm3ahMOHD5c7JplMhsuXLyMlJQWPHz+GXC7HO++8g1q1amHhwoVITk7G3r17ERISooohKCIgIADm5uZ45513sGvXLsTHxyMpKQk7duxAmzZtkJ6eDktLS/Tr1w8TJ07E+fPnERcXh5EjR6JRo0bo16/fG8cQHR2N1atX486dO/jiiy9w8OBBzJgxAwAglUrx7rvvIjAwEAkJCYiKilKqxQsATZo0gSAIOHbsGP766y+kp6e/VhzDhw+HXC7Hhx9+iISEBJw8eRJr164FULaaT15eXlyYi4iIiIjoLcAf9d8+ZV20uXoRqtBWditXrkT79u1hYGCAevXqoX///uKC22XFJCxRBbO0tERMTAyaNWuGwYMHo0mTJujVq5e4GNSLtUvXrVsHc3NzdOnSBcOHD8ecOXNQq1Yt8fgHH3yAmTNnYurUqXB0dMSFCxewePHicsc0Z84caGpqws7ODqampnjw4AFq166Nb775BsePH4e9vT327duHZcuWqWIIiqhduzYuXbqEkSNH4pNPPkGbNm3QpUsX7Nu3D2vWrIGRkREAIDg4GG3btkXfvn3RsWNHKBQKHD9+vMjj/a9j9uzZuHr1Ktq0aYNPPvkEn332Gdzc3MTjO3bsQH5+Ptq2bQsfHx988sknStc3atQI/v7+mD9/PurXr4+pU6e+VhyGhob4/vvvERsbC0dHR/j5+YmJ+RfrxJbEz88P7u7unAFLRERERERUQ0gkEgQEBMDKykrdodD/i4qKwpQpU3Dp0iVEREQgLy8P77//frkWTxMUnDZFVOmWLl2Kzz77DBEREXj33XfVHc5bRyaTwcfHBz4+PuoOpVh79uzB2LFj8ezZM0il0jJeda1CYyIiIiIiokqS9sLsOmPr4o8Xt59qiLbqDqBCKX5Zpu4QRLmNFiiVBgQKy//p6OiUeu1ff/2FevXqISoqCl27di1Tf5wJS6QG/v7+2LRpEy5duvRGCzRRzbBr1y6cP38e9+7dQ1hYGHx9fTF48OByJGCribTyPapRo7zN905vn5c/72/z5/9tvnciInp9xtb/bSUdp4pXmd/H36afGQpXH6sS28qVK2FkZKS0rVy5sky38ezZMwCFT/qWldZrDRgRvbGxY8eqOwSqIv744w8sWbIEf/zxBxo0aAAvLy8EBASU+XofHx+Eh4ezHiwREREREVENIJFI4O/vD09PT3WHUqMtWLAAs2bNUtpXllmwcrkcPj4+6NSpE1q1alXm/liOgIioGgsICMCuXbvUHQYRERERERGp2LFjx2BpaanuMFRKcc9f3SGIhKZLX+u6jz/+GCdOnMD58+fRuHHjMl/HcgRERNXYwYMHoaurCy0tDQiCwAW6iIiIiIiIqjEtrf8eWg8MDFRjJBVFowpt5Td16lQcO3YMZ8+eLVcCFmA5AiKiaisjIwNZWVnqDoOIiIiIiIhUQENDgKamJrS0tJCbm4vbt2+rOyT6fwqFAtOmTcPhw4cRGRmJpk2blrsNJmGJiKqplJQUdYdAREREREREKqJQAAUFBZBIJFAoFMjIyFB3SKpXTZ/enDJlCvbu3YsjR47AwMAAf/zxBwDAyMiozItqsxwBERERERERERERUQm2bNmCZ8+ewdXVFQ0aNBC3AwcOlLkNzoQlIqqmZDKZukMgIiIiIiIiFREEQFNTEwqFAoIgQE9PT90h0f9TKBRv3AaTsERE1ZSenh6kUikUCgXy83NRUFD4TUEV3xyIiIiIiIiocsnlChQUFCA/Px8AYGNjo+aIKkA1LUegCixHQERUjXl5eSE7Oxv5+XIoFAomYImIiIiIiKqx5wlYAPD19VVjJKRqTMISEVVjfn5+cHd3h/AW/zWRiIiIiIioJpFIJAgICICVlZW6QyEVEhScNkVUI0VGRqJbt254+vQpjI2N1d7O28LV1RWOjo7YsGFDJfd8rZL7IyIiIiIioldKSwSMrct5UdsKCaWqUNz/VN0hiIQmCyu1P9aEJaqCvL29sXPnTgCAlpYWGjduDC8vLyxfvhy6uroV1m9xCURnZ2ekpqbCyMiowvoFlO/5RW5ubggPDy9TG5WZAC0pOX3o0CFIJJIK7/9FPj4+CA8PZykCIiIiIiKiGkAikcDf3x+enp7qDoVUiElYoirK3d0dwcHByMvLw7Vr1zBmzBgIgoBVq1ZVahza2towMzOrlL6e3/OLdHR0VNqHQlFY6FxLq2K+/NWuXbtC2i1JQEAATpw4Ual9EhERERERUcXJy8vDwoUL0bp1a1haWqo7HFIR1oQlqqJ0dHRgZmYGc3Nz9O/fHz169EBERIR4XC6XY+XKlWjatCmkUikcHBzw3Xffldje33//jWHDhqFRo0aoVasW7O3tsW/fPvG4t7c3oqKisHHjRgiCAEEQkJKSgsjISAiCgLS0NPHc0NBQtGzZEjo6OpDJZFi3bp1SXzKZDJ9++inGjRsHAwMDWFhY4KuvvirzPb+4mZiYACiceaqtrY0ff/xRPH/16tWoV68e/vzzz1LjP3HiBNq2bQsdHR2cP38eycnJ6NevH+rXrw99fX20b98ep0+fVoonJycHvr6+MDc3h46ODlq0aIGgoCCkpKSgW7duAAATExMIggBvb28AhbNxfXx8xDaePn2K0aNHw8TEBLVq1UKvXr2QlJQkHg8JCYGxsTFOnjwJW1tb6Ovrw93dHampqaWOFwAcPHgQurq60NLSEO+biIiIiIiIqr/AwEB1h6B6gkbV2SoZk7BE1cBPP/2ECxcuQFtbW9y3cuVK7Nq1C1u3bsXPP/+MmTNnYuTIkYiKiiq2jezsbLRt2xY//PADfvrpJ3z44YcYNWoUrly5AgDYuHEjOnbsiIkTJyI1NRWpqakwNzcv0s61a9cwePBgDB06FLdu3cKyZcuwePFihISEKJ23bt06tGvXDjdu3MDkyZPx8ccfIzEx8bXH4Hlyc9SoUXj27Blu3LiBxYsX4+uvv0b9+vVLjX/+/PkIDAxEQkICWrdujfT0dPTu3RtnzpzBjRs34O7uDg8PDzx48EC8ZvTo0di3bx82bdqEhIQEbNu2Dfr6+jA3N0doaCgAIDExEampqdi4cWOxcXt7e+Pq1as4evQoLl68CIVCgd69eyMvL088JzMzE2vXrsXu3btx7tw5PHjwAHPmzCl1TDIyMpCVlYXs7Gzk58uhUChYkoCIiIiIiKia0tAQoKGhIW63b99Wd0ikQixHQFRFHTt2DPr6+sjPz0dOTg40NDSwefNmAIUzND/99FOcPn0aHTt2BAA0a9YM58+fx7Zt2+Di4lKkvUaNGikl9qZNm4aTJ0/i22+/RYcOHWBkZARtbW3UqlXrleUHPvvsM3Tv3h2LFy8GAFhZWSE+Ph5r1qwRZ4MCQO/evTF58mQAgK+vL9avX4+zZ8/C2rrkouTP7/lFCxcuxMKFhcWyP/nkE0RERODDDz/ETz/9hDFjxuCDDz4AgFLjX758OXr27Cm+rl27NhwcHMTXK1aswOHDh3H06FFMnToVd+7cwbfffouIiAj06NEDQOEYv3g9ANSrV6/EBcuSkpJw9OhRREdHw9nZGQCwZ88emJubIywsDF5eXgAKHzXZunUrmjdvDgCYOnUqli9fXuI45eTkICcnh9+QiYiIiIiIapDCOTX/TazJyMhQWyykekzCElVR3bp1w5YtW5CRkYH169dDS0tLLMp99+5dZGZmKiUVASA3Nxdt2rQptr2CggJ8+umn+Pbbb/Hbb78hNzcXOTk5qFWrVrniSkhIQL9+/ZT2derUCRs2bEBBQQE0NTUBAK1btxaPC4IAMzMzPHr0qEz3/KIXa6xqa2tjz549aN26NZo0aYL169eXOe527dopvU5PT8eyZcvwww8/IDU1Ffn5+cjKyhJnwsbGxkJTU7PYhHZZJSQkQEtLC++88464r06dOrC2tkZCQoK4r1atWmICFgAaNGjwyrFauXIl/P39oa2tDZlM9trxEREREREREVWqt7iEHpOwRFWUnp4eWrRoAQDYsWMHHBwcEBQUhPHjxyM9PR0A8MMPP6BRo0ZK15W0kNWaNWuwceNGbNiwAfb29tDT04OPjw9yc3MrJH6JRKL0WhAEyOXyV17z4j2X5MKFCwCAJ0+e4MmTJ9DT0ytTPC+fN2fOHERERGDt2rVo0aIFpFIpBg0aJI6HVCotU7uqUNxYvaqswIIFCzBr1ixkZma+UZKYiIiIiIiIqo7C/OR/Scqy/r5L1QNrwhJVAxoaGli4cCEWLVqErKws2NnZQUdHBw8ePECLFi2UtuLquAJAdHQ0+vXrh5EjR8LBwQHNmjXDnTt3lM7R1tZGQUHBK2OxtbVFdHR0kbatrKzEWbAVJTk5GTNnzsT27dvxzjvvYMyYMUqJ3bLE/1x0dDS8vb0xYMAA2Nvbw8zMDCkpKeJxe3t7yOXyEmvsPq/P+6r+bG1tkZ+fj8uXL4v7/v77byQmJsLOzq5McRZHR0cHhoaGMDMzg1Qq5cJcRERERERENYBcroBcLhc3GxsbdYdUAYQqtFUuJmGJqgkvLy9oamriiy++gIGBAebMmYOZM2di586dSE5OxvXr1/H5559j586dxV5vaWmJiIgIXLhwAQkJCZg0aRL+/PNPpXNkMhkuX76MlJQUPH78uNiZq7Nnz8aZM2ewYsUK3LlzBzt37sTmzZvLtJBUaXJycvDHH38obY8fPwZQmOwcOXIk3NzcMHbsWAQHB+PmzZtYt25dueJ/cTwOHTqE2NhYxMXFYfjw4Urny2QyjBkzBuPGjUNYWBju3buHyMhIfPvttwCAJk2aQBAEHDt2DH/99Zc4O/nlPvr164eJEyfi/PnziIuLw8iRI9GoUaMiJR1el5eXFxfmIiIiIiIiqoF8fX3VHQKpEJOwRNWElpYWpk6ditWrVyMjIwMrVqzA4sWLsXLlStja2sLd3R0//PADmjZtWuz1ixYtgpOTE9zc3ODq6gozMzP0799f6Zw5c+ZAU1MTdnZ2MDU1FeujvsjJyQnffvst9u/fj1atWmHJkiVYvny50qJcrys8PBwNGjRQ2jp37gwACAgIwP3797Ft2zYAhXVTv/rqKyxatAhxcXFljv+5zz77DCYmJnB2doaHhwfc3Nzg5OSkdM6WLVswaNAgTJ48GTY2Npg4caJYGL1Ro0bw9/fH/PnzUb9+fUydOrXYfoKDg9G2bVv07dsXHTt2hEKhwPHjx4uUIHhdfn5+cHd35wxYIiIiIiKiGkIikSAgIABWVlbqDoVUSFBw2hQRUQ1wTd0BEBERERER0YvSEgFj63Je1LZCQqkqFL+uVXcIIqHxmz/RWx5cmIuIqJrz8fFBeHg4SxEQERERERHVABKJBP7+/v/H3n2HRXF9fQD/Lr2DIEWxICJNQREbonQCFizBmtiiYo9iRdEoqFhj7zEq2GPv2BEN9oK9EBVNsUVFirRlz/sH704YAUF/4IKcz/Pso8zOnXum7JQzd+4gMDBQ0aGwEsTdETDGWDkWERGB6OhoTsAyxhhjjDHG2FciOzsboaGhSEhIUHQorARxEpYxxsqx7du3Q0NDAyoqSpBIJOWub1hFhKukVL6WEWOMMcZKFp8LMMbKi1mzZik6hBInv24tC58vjbsjYIyxciotLQ3p6emKDqPYJBLgwwa7imjAK5Nxq2HGGGOsIuNzAcZYWZV7k+i/5OC9e/cUFwwrcZyEZYyxcioxMVHRIXwSiUTC3SYwxhhjjDHGWCFyL5f+u2ZKS0tTWCys5HESljHGGGOMMcYYY4wx9gVU3C5hOAnLGGPllIWFhaJD+CTcCpYxxhhjjDHGCpfbTel/SUptbW2FxcJKHidhGWOsnNLW1oampiaICFJpFnJycpOcZTXZWVBYBfUTW9qUlCTcFxxjjDFWgfG5AGOsrMrdN/23f7K1tVVcMKVFoqToCBSm4s45Y4x9BTp37oyMjAxIpTIQUZlNwBaGX8zFGGOMsS+NzwUYY+VFSEiIokNgJYiTsIwxVo5NnDgR/v7+kEgqbr86jDHGGGOMMfY1UVVVRUREBKytrRUdCitBEipvzaYYY4wV4IqiA8iHHh+ApFbb/F8k3QcMbD5/wnnLF2daSfdz//1f6ixP/tflyxSjom2nJaGsbusfi+tTYi6r88fKloqwnZTUPCpiWX3JOj/1/OhTpldaKsL2K1de1gkrnlJfF86lOO0y4J9Fio7gP1VHfNHquCUsY5/g1KlTkEgkSEpKKvFpR0ZGwsDAoMSnW9okEgn27Nmj6DDKDAsLCyxcuFDRYZQJBSZggf/9hCVv+eJMy8Cm7JywJt3/L9lWWvJegLHyQ5HbaXndVsrK7/pDH4vrU2Iuq/PHypaKsJ2U1DwqYlkVVOen7nOLO/6nnh99yvRKS0XYfuXKyzphxcPrgn0mfjEXqzD69OmDqKgoAICKigqqVauGzp07Y+rUqdDQ0PiisVhYWCA4OBjBwcHCsK5du6J169ZfNI4v6dy5c2jRogX8/f1x8ODBTy4fFhaGPXv2ID4+vuSD+wyRkZEIDg7Ol5C/dOnSF3+DZXBwMA4fPlzu+oNljDHGGGOMMZafqqoqwsPDERgYqOhQWAnilrCsQvH398ezZ8/w6NEjLFiwAKtWrcKUKVMUHRYAQFNTEyYmJooOo9SsWbMGP/74I06fPo1//vlH0eGUGmNjY2hpaX2x+iIiIhAdHc0JWMYYY4wxxhj7SmRnZyM0NBQJCQmKDqXkSSRl5/OFcRKWVSjq6uowMzND9erV0aFDB/j4+ODYsWPC95mZmRg+fDhMTEygoaGBFi1a4NKlS/mmExcXB0dHR2hoaKBZs2a4deuW6PudO3eibt26UFdXh4WFBebNmyd85+HhgSdPnmDkyJGQSCTCC5UK6o5g//79aNy4MTQ0NFC5cmV07NhR+G758uWoU6cONDQ0YGpqik6dOhU6369fv0b37t1hbm4OLS0tODg4YMuWLaJxPDw8MHz4cIwbNw6GhoYwMzNDWFiYaJyEhAS4ublBQ0MD9vb2omX3Mampqfjtt98wePBgtGnTBpGRkaLvC5r3PXv2iJZNeHg4rl+/Liwz+TSePn2K9u3bQ0dHB3p6eujSpQtevHghTCcsLAwNGjTA2rVrUaNGDejo6GDIkCHIycnBnDlzYGZmBhMTE0RERIjqnz9/PhwcHKCtrY3q1atjyJAhSE1NBZDbLcUPP/yAd+/eCfHIl9WH3REUN74NGzbAwsIC+vr66NatG1JSUoq1bLdv3w4NDQ2oqCiJtidWPvD6YowxxhhjjBVm1qxZig6BlSBOwrIK69atWzh79izU1NSEYePGjcPOnTsRFRWFq1evwsrKCn5+fnjz5o2o7NixYzFv3jxcunQJxsbGCAgIQHZ2NgDgypUr6NKlC7p164abN28iLCwMP/30k5A03LVrF6pVq4apU6fi2bNnePbsWYHxHTx4EB07dkTr1q1x7do1nDhxAk2aNAEAXL58GcOHD8fUqVNx//59HD58GG5uboXOa0ZGBpydnXHw4EHcunULAwYMQM+ePXHx4kXReFFRUdDW1saFCxcwZ84cTJ06VUi0ymQyfPvtt1BTU8OFCxewcuVKhISEFGtZb9u2Dba2trCxsUGPHj2wdu3aT2q52bVrV4wePRp169YVllnXrl0hk8nQvn17vHnzBrGxsTh27BgePXqErl27iso/fPgQ0dHROHz4MLZs2YI1a9agTZs2+OuvvxAbG4vZs2dj0qRJuHDhglBGSUkJixcvxu3btxEVFYWTJ09i3LhxAIDmzZtj4cKF0NPTE+IZM2ZMvrg/Jb49e/bgwIEDOHDgAGJjY4t1sE1LS0N6ejoyMjIglcpARNwitpzh9cUYY4wxxhiTU1KSQElJSfjcu3dP0SGxEsR9wrIK5cCBA9DR0YFUKkVmZiaUlJSwdOlSALkJrRUrViAyMhKtWrUCAKxevRrHjh3DmjVrMHbsWGE6U6ZMga+vL4DcxGW1atWwe/dudOnSBfPnz4e3tzd++uknAIC1tTXu3LmDuXPnok+fPjA0NISysjJ0dXVhZmZWaKwRERHo1q0bwsPDhWH169cHkNu6UltbG23btoWuri5q1qwJJyenQqdlbm4uShL++OOPOHLkCLZt2yYkdgHA0dFR6J6hTp06WLp0KU6cOAFfX18cP34c9+7dw5EjR1C1alUAwIwZM4Rl9TFr1qxBjx49AOR2CfHu3TvExsbCw8OjyLJAblcNOjo6UFFRES2zY8eO4ebNm3j8+DGqV68OAFi/fj3q1q2LS5cuoXHjxgByk6Fr166Frq4u7O3t4enpifv37+PQoUNQUlKCjY0NZs+ejZiYGDRt2hQARP31WlhYYPr06Rg0aBCWL18ONTU16OvrQyKRfHQdnjhxotjxRUZGQldXFwDQs2dPnDhxIl/rXLnMzExkZmbyAZkxxhhjjDHGviK5bTT+a6iRlpamsFhKjaTitgetuHPOKiRPT0/Ex8fjwoUL6N27N3744Qeho+uHDx8iOzsbrq6uwviqqqpo0qQJ7t69K5qOi4uL8H9DQ0PY2NgI49y9e1c0DQBwdXVFQkICcnJyih1rfHw8vL29C/zO19cXNWvWhKWlJXr27IlNmzbh/fv3hU4rJycH06ZNg4ODAwwNDaGjo4MjR47g6dOnovEcHR1Ff1epUgUvX74U5qt69epCAhYQL4fC3L9/HxcvXkT37t0B5L4UrWvXrlizZk2RZYsij0me4AQAe3t7GBgYiNaZhYWFkOAEAFNTU9jb20NJSUk0TD6vAHD8+HF4e3vD3Nwcurq66NmzJ16/fv3R5VxS8eVd7gWZOXMm9PX10bJly2LHwhhjjDHGGGOMMcXhJCyrULS1tWFlZYX69etj7dq1uHDhQokkA0uDpqZmod/p6uri6tWr2LJlC6pUqYLJkyejfv36SEpKKnD8uXPnYtGiRQgJCUFMTAzi4+Ph5+eHrKws0XiqqqqivyUSCWQy2f80H2vWrIFUKkXVqlWhoqICFRUVrFixAjt37sS7d+8A5D76/+Fj2fLuHUpCQfP1sXlNTExE27Zt4ejoiJ07d+LKlStYtmwZAORbZqUV38eW+4QJE/Du3Ts8efKkxGNhjDHGGGOMMaYYue+LkggfbW1tRYfEShAnYVmFpaSkhNDQUEyaNAnp6emoXbs21NTUEBcXJ4yTnZ2NS5cuwd7eXlT2/Pnzwv/fvn2LBw8ewM7ODgBgZ2cnmgaQ+yIva2trKCsrAwDU1NSKbBXr6OiIEydOFPq9iooKfHx8MGfOHNy4cQOJiYk4efJkgePGxcWhffv26NGjB+rXrw9LS0s8ePDgo/V/yM7ODn/++aeoD9u8y6EgUqkU69evx7x58xAfHy98rl+/jqpVqwovBzM2NkZKSoroUYv4+HjRtApaZvKY/vzzT2HYnTt3kJSUlG+dfYorV65AJpNh3rx5aNasGaytrfHPP/8UGc+HSis+dXV16OnpwczMDJqamvxirnKM1xdjjDHGGGNMTiYjyGQy4WNra6vokEqBpAx9vixOwrIKrXPnzlBWVsayZcugra2NwYMHY+zYsTh8+DDu3LmDoKAgvH//Hv369ROVmzp1Kk6cOIFbt26hT58+qFy5Mjp06AAAGD16NE6cOIFp06bhwYMHiIqKwtKlS0V9slpYWOD06dP4+++/8e+//xYY25QpU7BlyxZMmTIFd+/exc2bNzF79mwAuX3bLl68GPHx8Xjy5AnWr18PmUwGGxubAqdVp04dHDt2DGfPnsXdu3cxcOBAvHjx4pOWlY+PD6ytrdG7d29cv34dZ86cwcSJEz9a5sCBA3j79i369euHevXqiT6BgYFCK+SmTZtCS0sLoaGhePjwITZv3iy8yCzvMnv8+DHi4+Px77//IjMzEz4+PnBwcMD333+Pq1ev4uLFi+jVqxfc3d3RqFGjT5q/vKysrJCdnY0lS5bg0aNH2LBhA1auXJkvntTUVJw4cQL//vtvgd0UlFZ8eXXu3JlfzFWO8fpijDHGGGOMFaa4L8Nm5QMnYVmFpqKigmHDhmHOnDlIS0vDrFmzEBgYiJ49e6Jhw4b4448/cOTIEVSqVElUbtasWRgxYgScnZ3x/Plz7N+/H2pqagCAhg0bYtu2bdi6dSvq1auHyZMnY+rUqejTp49QfurUqUhMTETt2rVhbGxcYGweHh7Yvn079u3bhwYNGsDLywsXL14EABgYGGDXrl3w8vKCnZ0dVq5ciS1btqBu3boFTmvSpElo2LAh/Pz84OHhATMzMyFpXFxKSkrYvXs30tPT0aRJE/Tv37/QF0fJrVmzBj4+PtDX18/3XWBgIC5fvowbN27A0NAQGzduxKFDh+Dg4IAtW7YgLCws3/j+/v7w9PSEsbExtmzZAolEgr1796JSpUpwc3ODj48PLC0t8dtvv33SvH2ofv36mD9/PmbPno169eph06ZNmDlzpmic5s2bY9CgQejatSuMjY0xZ86cfNMprfjymjhxIvz9/blFJWOMMcYYY4x9JVRVVREREQFra2tFh1LycvtcKBufLz3rxM1wGGPsK3BF0QEwxhj72iTdBwwKfsqGMcYYY6XFWdEBlK4XyxUdwX9Mh3zR6lS+aG2MMcZKXHBwMA4fPsyPtjPGGGOMMcbYV0BVVRXh4eEIDAxUdCisBHF3BIwxVo5FREQgOjqaE7CMMcYYY4wx9pXIzs5GaGgoEhISFB1KyZMolZ3PF8ZJWMYYK8e2b98ODQ0NqKgoQSKRcN+wjDHGGGOMMfaVmDVrlqJDYCWIuyNgjLFyKi0tDenp6YoOgzHGGGOMMcZYCVBSkgD4r2HNvXv3FBcMK3GchGWMsXIqMTFR0SEwxhhjjDHGGCshub3M/dfVXFpamsJiKT0V9+lN7o6AMcYYY4wxxhhjjDHGShG3hGWMsXLKwsJC0SEwxhhjjDHGGCshua/4+K+lqLa2tsJiYSWPk7CMMVZOaWtrQ1NTE0QEqTQLOTm5j60QURElGWOMMcYYY4yVNTIZIW93BLa2tooLprRU4JdJc3cEjDFWjnXu3BkZGRmQSmUgIk7AMsYYY4wxxthXIiQkRNEhsBLESVjGGCvHJk6cCH9/f0gq8N1ExhhjjDHGGPuaqKqqIiIiAtbW1ooOpRQolaHPlyUhbjbFGCunTp06BU9PT7x9+xYGBgb/07Ti4uIwaNAg3Lt3D23atMGePXtKJMYv54qiA2CMMfa1SboPGNgoOgrGGGOsgnFWdACl69Wvio7gP8b9v2h13CcsYxXcq1evMHnyZBw8eBAvXrxApUqVUL9+fUyePBmurq4KrScsLAzh4eEAAGVlZVSrVg0dO3bEtGnToKOj81lxeHh4oEGDBli4cKFo+KhRo9CgQQNER0d/9rQVJTg4GIcPH+auCBhjjDHGGGPsK6Cqqorw8HAEBgYqOhRWgjgJy1gFFxgYiKysLERFRcHS0hIvXrzAiRMn8Pr16zJRT926dXH8+HFIpVLExcWhb9++eP/+PVatWlWi8T18+BCDBg1CtWrVPnsaWVlZUFNTK8GoihYREYHo6OgvWidjjDHGGGOMsdKTnZ2N0NBQODo6ok6dOooOp2RV4K70uE9YxiqwpKQknDlzBrNnz4anpydq1qyJJk2aYMKECWjXrp0w3vz58+Hg4ABtbW1Ur14dQ4YMQWpqqvD969ev0b17d5ibm0NLSwsODg7YsmXLJ9dTEBUVFZiZmaFatWro2rUrvv/+e+zbt6/AcYuKo0+fPoiNjcWiRYsgkUggkUiQmJgIiUSC169fo2/fvpBIJIiMjAQAxMbGokmTJlBXV0eVKlUwfvx4SKVSYXoeHh4YNmwYgoODUblyZfj5+eHUqVOQSCQ4cuQInJycoKmpCS8vL7x8+RLR0dGws7ODnp4evvvuO7x//16Y1o4dO+Dg4ABNTU0YGRnBx8cHaWlpRa7D7du3Q0NDAyoqSsI8McYYY4wxxhgrO1RUlIs1nrKyErS0tIS/Z82aVVohMQXgJCxjFZiOjg50dHSwZ88eZGZmFjqekpISFi9ejNu3byMqKgonT57EuHHjhO8zMjLg7OyMgwcP4tatWxgwYAB69uyJixcvflI9xaGpqYmsrKwCvysqjkWLFsHFxQVBQUF49uwZnj17hurVq+PZs2fQ09PDwoUL8ezZM3Tt2hV///03WrdujcaNG+P69etYsWIF1qxZg+nTp4vqjIqKgpqaGuLi4rBy5UpheFhYGJYuXYqzZ8/izz//RJcuXbBw4UJs3rwZBw8exNGjR7FkyRIAwLNnz9C9e3f07dsXd+/exalTp/Dtt98W2b1AWloa0tPTkZGRAalUBiLiLgkYY4wxxhhjrIyRSnOKNZ5EIoGenh40NDSgpKSEe/fulXJk7Evi7ggYq8BUVFQQGRmJoKAgrFy5Eg0bNoS7uzu6desGR0dHYbzg4GDh/xYWFpg+fToGDRqE5cuXAwDMzc0xZswYYZwff/wRR44cwbZt29CkSZNi11OUK1euYPPmzfDy8irw+6Li0NfXh5qaGrS0tGBmZiaMZ2ZmBolEAn19fWH48uXLUb16dSxduhQSiQS2trb4559/EBISgsmTJ0NJKfceVp06dTBnzhxhWs+ePQMATJ8+Xejrtl+/fpgwYQIePnwIS0tLAECnTp0QExODkJAQPHv2DFKpFN9++y1q1qwJAHBwcCh0OWRmZiIzM5MPyIwxxhhjjDH2FZHJCDk5OZBIJCCiYj0dWe5U4Kc3uSUsYxVcYGAg/vnnH+zbtw/+/v44deoUGjZsKDySDwDHjx+Ht7c3zM3Noauri549e+L169fC4/Q5OTmYNm0aHBwcYGhoCB0dHRw5cgRPnz79pHoKcvPmTejo6EBTUxNNmjSBi4sLli5dWuC4xYmjuO7evQsXFxfR4/2urq5ITU3FX3/9JQxzdi74zZV5k8umpqbQ0tISErDyYS9fvgQA1K9fH97e3nBwcEDnzp2xevVqvH37ttDYZs6cCX19fbRs2fKT54sxxhhjjDHGGGNfHidhGWPQ0NCAr68vfvrpJ5w9exZ9+vTBlClTAACJiYlo27YtHB0dsXPnTly5cgXLli0DAKFbgLlz52LRokUICQlBTEwM4uPj4efnl6/bgI/VUxgbGxvEx8fj7t27SE9Px759+2BqalrguMWNoyRpa2sXOFxVVVX4v0QiEf0tHyaTyQAAysrKOHbsGKKjo2Fvb48lS5bAxsYGjx8/LnDaEyZMwLt37/DkyZMSmgvGGGOMMcYYY4qmpCSBsrIyiAgSiaTQ601WPnESljGWj729vfDYw5UrVyCTyTBv3jw0a9YM1tbW+Oeff0Tjx8XFoX379ujRowfq168PS0tLPHjw4JPqKYyamhqsrKxgYWEBNTW1j45bnDjU1NSQk1N0fzx2dnY4d+6cqI/VuLg46Orqolq1akWW/1QSiQSurq4IDw/HtWvXoKamht27dxc4rrq6OvT09GBmZgZNTU1+MRdjjDHGGGOMlWHFfTEXESE5ORkZGRmQyWSwtbUt5cgUQakMfb4sTsIyVoG9fv0aXl5e2LhxI27cuIHHjx9j+/btmDNnDtq3bw8AsLKyQnZ2NpYsWYJHjx5hw4YNohdQAbn9oh47dgxnz57F3bt3MXDgQLx48eKT6ikJRcUB5PZpe+HCBSQmJuLff/8VWqN+aMiQIfjzzz/x448/4t69e9i7dy+mTJmCUaNGCf3BlpQLFy5gxowZuHz5Mp4+fYpdu3bh1atXsLOzK7Js586d+cVcjDHGGGOMMVaGFffFXDk5MqHbPwAICQkprZCYAvCLuRirwHR0dNC0aVMsWLAADx8+RHZ2NqpXr46goCCEhoYCyO2vdP78+Zg9ezYmTJgANzc3zJw5E7169RKmM2nSJDx69Ah+fn7Q0tLCgAED0KFDB7x7967Y9ZSEouIAgDFjxqB3796wt7dHeno6Hj9+DAsLi3zTMjc3x6FDhzB27FjUr18fhoaG6NevHyZNmlRi8crp6enh9OnTWLhwIZKTk1GzZk3MmzcPrVq1KrLsxIkT8fLlSxw5coQTsIwxxhhjjDH2FVBSUsK0adNgbW2t6FBYCZIQX7UzxthX4IqiA2BySfcBAxtFR1Hy5PP1tc7f14jXVa6k+7n/KnpZfO764PXIGPva8TkG+9IK29ZKehssaHrFqqPglz9/Nd5EKTqC/xj2/qLVcXcEjDHGWEn63BM3eaKorJLPV1m8OCrry07uS8f5sXVVXpZZSTCwKRvb7efGUNqxV6RtoSxSxPLndc7Kmi9xjsHbPS+DvArb1kp6GyxoemXhnIQpDHdHwBhj5VyvXr1w4cIFRYfBGGOMMcYYY6wEqKurY8qUKQgMDFR0KKWg4r5MmlvCMsZYORYREcEJWMYYY4wxxhj7imRlZSE0NBQJCQmKDoWVIE7CMsZYObZ9+3ZoaGjAyEgPKiq8S2eMMcYYY4yx8k5ZWRkSiQSzZs1SdCisBHF3BIwxVk6lpaUhPT0dAJCRkaHgaBhjjDHGGGOM/a8kEgmUlZWhoqKCe/fuKTqckiepuI2HKu6cM8ZYOZeYmKjoEBhjjDHGGGOMlSAiQk5ODiQSCdLS0hQdDitBnIRljDHGGGOMMcYYY4yxUsTdETDGWDllYWGh6BAYY4wxxhhjjJUgeXcERAQdHR1Fh1PyJBJFR6Aw3BKWMcbKKW1tbWhqavKLuRhjjDHGGGPsKyHvjiAzMxO2traKDoflcfr0aQQEBKBq1aqQSCTYs2fPJ5XnK3bGGCvHOnfujIyMDLx+nQypVKbocBhjjDHGGGOM/Y9ycnJARAgJCVF0KCyPtLQ01K9fH8uWLfus8twdAWOMlWMTJ07E3bt3cenSJUWHwhhjjDHGGGOsBBARnJycYG1trehQSkHZ6Y4gMzMTmZmZomHq6upQV1cvcPxWrVqhVatWn10fJ2EZY6UmLCwMe/bsQXx8fKnX5eHhgQYNGmDhwoUAgPfv36Nnz544duwYUlJS8PbtWzRo0ADBwcEIDg4utThOnToFT09PvH37FgYGBqVWT14bN24EcOWL1FUqku4DBjaKjoIxxhhj7OvD51mMlUPOig6gwpg5cybCw8NFw6ZMmYKwsLBSqY+TsIyVM5IiOrH+X3YYiYmJqFWrFq5du4YGDRoUOf7OnTuxZMkSXLt2DTk5ObC0tESnTp0wbNgwGBoaflYMn2vXrl1QVVUV/o6KisKZM2dw9uxZVK5cGfr6+rh06RK0tbVLrM4PE78A0Lx5czx79gz6+volVk9RgoODcfjwYRDRF6uTMcYYY4wxxljpUFVVRXh4OAIDAxUdSsmTlJ2eUSdMmIBRo0aJhhXWCrYklJ05Z4wVy7Nnz4TPwoULoaenJxo2ZsyYLxLHxIkT0bVrVzRu3BjR0dG4desW5s2bh+vXr2PDhg1fJIa8DA0NoaurK/z98OFD2NnZoV69ejAzM4NEIoGxsTG0tLRKNQ41NTWhvi8hIiIC0dHRnIBljDHGGGOMsa9EdnY2QkNDkZCQoOhQvmrq6urQ09MTfTgJyxgTmJmZCR99fX1IJBLRsK1bt8LOzg4aGhqwtbXF8uXLhbJ9+/aFo6Oj0OdJVlYWnJyc0KtXLwBArVq1AABOTk6QSCTw8PAoMIaLFy9ixowZmDdvHubOnYvmzZvDwsICvr6+2LlzJ3r37l1guUuXLsHX11domeru7o6rV68K3xMRwsLCUKNGDairq6Nq1aoYPny48P3y5ctRp04daGhowNTUFJ06dRK+8/DwELoZ8PDwwLx583D69GnRfFhYWIharSYlJWHgwIEwNTWFhoYG6tWrhwMHDgAAXr9+je7du8Pc3BxaWlpwcHDAli1bhLJ9+vRBbGwsFi1aBIlEAolEgsTERJw6dQoSiQRJSUnCuDt37kTdunWhrq4OCwsLzJs3T7RcLCwsMGPGDPTt2xe6urqoUaMGfvnllwKX4Ye2b98ODQ0NqKgoCXEwxhhjjDHGGCv/Zs2apegQWAniJCxjX5FNmzZh8uTJiIiIwN27dzFjxgz89NNPiIqKAgAsXrwYaWlpGD9+PIDc1qxJSUlYunQpgNzkKgAcP34cz549w65duwqtR0dHB0OGDCnw+8L6Qk1JSUHv3r3x+++/4/z586hTpw5at26NlJQUALnJygULFmDVqlVISEjAnj174ODgAAC4fPkyhg8fjqlTp+L+/fs4fPgw3NzcCqxn165dCAoKgouLS6HzIZPJ0KpVK8TFxWHjxo24c+cOZs2aBWVlZQBARkYGnJ2dcfDgQdy6dQsDBgxAz549hWW0aNEiuLi4ICgoSGiFXL169Xz1XLlyBV26dEG3bt1w8+ZNhIWF4aeffkJkZKRovHnz5qFRo0a4du0ahgwZgsGDB+P+/fsFzp9cWloa0tPTkZGRAalUBiLiFrGMMcYYY4wxVk4pKUmgpKQkfO7du6fokEqBpAx9vizuE5axr8iUKVMwb948fPvttwByW7beuXMHq1atQu/evaGjo4ONGzfC3d0durq6WLhwIWJiYqCnpwcAMDY2BgAYGRnBzMys0HoSEhJgaWkp6oO1OLy8vER///LLLzAwMEBsbCzatm2Lp0+fwszMDD4+PlBVVUWNGjXQpEkTAMDTp0+hra2Ntm3bQldXFzVr1oSTk1OB9RgaGkJLS0voGqAgx48fx8WLF3H37l3hjZOWlpbC9+bm5qKuHX788UccOXIE27ZtQ5MmTaCvrw81NTVoaWl9dFnNnz8f3t7e+OmnnwAA1tbWuHPnDubOnYs+ffoI47Vu3VpIaoeEhGDBggWIiYmBjU3+FynI3+D4dR6QGWOMMcYYY6xiym1T81/DmrS0NIXFwvJLTU3FH3/8Ifz9+PFjxMfHw9DQEDVq1CiyPLeEZewrkZaWhocPH6Jfv37Q0dERPtOnT8fDhw+F8VxcXDBmzBhMmzYNo0ePRosWLT65rs9tbfnixQsEBQWhTp060NfXh56eHlJTU/H06VMAQOfOnZGeng5LS0sEBQVh9+7dkEqlAABfX1/UrFkTlpaW6NmzJzZt2oT3799/VhwAEB8fj2rVqgkJ2A/l5ORg2rRpcHBwgKGhIXR0dHDkyBEh1uK6e/cuXF1dRcNcXV2RkJCAnJwcYZijo6Pwf3kXEy9fvixwmjNnzoS+vj5atmz5SbEwxhhjjDHGGGPs81y+fBlOTk5Cg7BRo0bByckJkydPLlZ5TsIy9pVITU0FAKxevRrx8fHC59atWzh//rwwnkwmQ1xcHJSVlUV3cD6FtbU1Hj16hOzs7E8q17t3b8THx2PRokU4e/Ys4uPjYWRkhKysLABA9erVcf/+fSxfvhyampoYMmQI3NzckJ2dDV1dXVy9ehVbtmxBlSpVMHnyZNSvX1/U9+qn0NTU/Oj3c+fOxaJFixASEoKYmBjEx8fDz89PiLWkfdiqWCKRQCaTFTjuhAkT8O7dOzx58qRUYmGMMcYYY4wx9uVJJBDe9SGRSKCtra3okEpe7kyWjc8n8vDwELoBzPv5sLvBwnASlrGvhKmpKapWrYpHjx7ByspK9JG/cAvITS7eu3cPsbGxOHz4MNatWyd8p6amBgCiFpoF+e6775Camip66VdehSVG4+LiMHz4cLRu3Vp4UdW///4rGkdTUxMBAQFYvHgxTp06hXPnzuHmzZsAABUVFfj4+GDOnDm4ceMGEhMTcfLkySKXTUEcHR3x119/4cGDB4XG2r59e/To0QP169eHpaVlvnHV1NSKXFZ2dnaIi4vLN21ra2uh/9lPJX+Do5mZGTQ1NfnFXIwxxhhjjDH2FZDJCDKZTPjY2toqOiRWgrhPWMa+IuHh4Rg+fDj09fXh7++PzMxMXL58GW/fvsWoUaNw7do1TJ48GTt27ICrqyvmz5+PESNGwN3dHZaWljAxMYGmpiYOHz6MatWqQUNDA/r6+vnqadq0KcaNG4fRo0fj77//RseOHVG1alX88ccfWLlyJVq0aIERI0bkK1enTh1s2LABjRo1QnJyMsaOHStqkRoZGYmcnBw0bdoUWlpa2LhxIzQ1NVGzZk0cOHAAjx49gpubGypVqoRDhw5BJpMV2Gdqcbi7u8PNzQ2BgYGYP38+rKyscO/ePUgkEvj7+6NOnTrYsWMHzp49i0qVKmH+/Pl48eIF7O3thWlYWFjgwoULSExMhI6ODgwNDfPVM3r0aDRu3BjTpk1D165dce7cOSxdurTQBPan6ty5M9avX18i02KMMcYYY4wxVnaEhIQoOgRWgrglLGNfkf79++PXX3/FunXr4ODgAHd3d0RGRqJWrVrIyMhAjx490KdPHwQEBAAABgwYAE9PT/Ts2RM5OTlQUVHB4sWLsWrVKlStWhXt27cvtK7Zs2dj8+bNuHDhAvz8/FC3bl2MGjUKjo6O6N27d4Fl1qxZg7dv36Jhw4bo2bMnhg8fDhMTE+F7AwMDrF69Gq6urnB0dMTx48exf/9+GBkZwcDAALt27YKXlxfs7OywcuVKbNmyBXXr1v3s5bVz5040btwY3bt3h729PcaNGye0bJ00aRIaNmwIPz8/eHh4wMzMDB06dBCVHzNmDJSVlWFvbw9jY+MC+4tt2LAhtm3bhq1bt6JevXqYPHkypk6dKnop1/9i4sSJ8Pf35xawjDHGGGOMMfaVUFVVRURERKHvMCnflMrQ58uS0Oe+YYcxxlgZckXRAXy+pPuAwee1aGaMMcYYYx/B51mMlUPOig6gdCXvUHQE/9Hr9EWr4+4IGGOsnAsODsbhw4fB99QYY4wxxhhjrPxTVVVFeHg4AgMDFR0KK0HcHQFjjJVjERERiI6O5gQsY4wxxhhjjH0lsrOzERoaioSEBEWHUvIkkrLz+cI4CcsYY+XY9u3boaGhARUVJUgkEu4bljHGGGOMMca+ErNmzVJ0CKwEcXcEjDFWTqWlpSE9PV3RYTDGGGOMMcYYKwFKShIA/zWsuXfvnuKCKS2SitselJOwjDFWTiUmJio6BMYYY4wxxhhjJSS3l7n/uppLS0tTWCys5FXc9DNjjDHGGGOMMcYYY4x9AdwSljHGyikLCwtFh8AYY4wxxhhjrITkvuLjv+4ItLW1FRZL6am47zHhJCxjjJVT2tra0NTUBBFBKs1CTk7uYytEVERJxhhjjDHGGGNljUxGyNsdga2treKCYSWOuyNgjLFyrHPnzsjIyIBUKgMRcQKWMcYYY4wxxr4SISEhig6BlSBOwjLGWDk2ceJE+Pv7QyKpuI90MMYYY4wxxtjXRFVVFREREbC2tlZ0KCVPIik7ny8968TNphhj7CtwRdEBMMYYY4wxxhj7nzkrOoDSlbZX0RH8R7v9F62OW8Iyxhhjckn3v+76Pkd5iJGVvNJY7x9Ok7ct9oE0t+4fHyHpfqluN3RqfqlNu0D8G2AVUVnY7ksgBnp8oMSnWSaUp/koT7EW5muYB/ZJ+MVcjLEyz8PDAw0aNMDChQtFwyMjIxEcHIykpKRSrf+vv/6CpaUlrK2tcevWrVKt63MEBwfj8OHD3B8sY4yxcsnExATNmzdHdJIGMm2+U3A0iq6fMVZ+bFZ0AOwrpqqqivDwcAQGBio6lFJQcduDVtw5Z4yxYoqMjESXLl2QnJyMCxcuKDockYiICERHR3MCljHGWLmkp6eHAQMGYM+ePcjMzFR0OIwxxliZkJ2djdDQUCQkJCg6FFaCOAnLGPtqnDp1Ck2aNIG2tjYMDAzg6uqKJ0+eCN/v3bsXDRs2hIaGBiwtLREeHg6pVPrRaRIR1q1bh549e+K7777DmjVrRN8nJiZCIpFg69ataN68OTQ0NFCvXj3ExsaK4pJIJDh48CAcHR2hoaGBZs2aiVrVPnnyBAEBAahUqRK0tbVRt25dHDp0qMh53r59OzQ0NKCiogSJRMIv6GKMMVauBAUFYcuWLf//16fdUORjHmPsf8W7EVbWzZo1S9EhsBLESVjG2FdBKpWiQ4cOcHd3x40bN3Du3DkMGDBAuEA7c+YMevXqhREjRuDOnTtYtWoVIiMjERER8dHpxsTE4P379/Dx8UGPHj2wdetWpKWl5Rtv7NixGD16NK5duwYXFxcEBATg9evX+caZN28eLl26BGNjYwQEBCA7OxsAMHToUGRmZuL06dO4efMmZs+eDR0dnY/GlpaWhvT0dGRkZEAqlYGIuEUsY4yxcqVly5Z4+PDh//9VcDZEWVmpwEQJH/MYY/8r3o2wskRZWQlKShIoKSkJn3v37ik6rJInkZSdzxfGSVjG2FchOTkZ7969Q9u2bVG7dm3Y2dmhd+/eqFGjBgAgPDwc48ePR+/evWFpaQlfX19MmzYNq1at+uh016xZg27dukFZWRn16tWDpaUltm/fnm+8YcOGITAwEHZ2dlixYgX09fXztZqdMmUKfH194eDggKioKLx48QK7d+8GADx9+hSurq5wcHCApaUl2rZtCzc3twJjyszMRHJyMm7fvv05i4oxxhgrM4q64QjktnjlRAljjLGvnfx4J29cQ0QFNgBi5RcnYRljXwVDQ0P06dMHfn5+CAgIwKJFi/Ds2TPh++vXr2Pq1KnQ0dERPkFBQXj27Bnev39f4DSTkpKwa9cu9OjRQxjWo0ePfMlVAHBxcRH+r6KigkaNGuHu3buFjmNoaAgbGxthnOHDh2P69OlwdXXFlClTcOPGjULndebMmdDX10fLli2LWCqMMcZY2cZdCjDGGGMVjVIZ+nxZnIRljJV5enp6ePfuXb7hSUlJ0NfXF/5et24dzp07h+bNm+O3336DtbU1zp8/DwBITU1FeHg44uPjhc/NmzeRkJAADQ2NAuvdvHkzMjIy0LRpU6ioqEBFRQUhISH4/fff8eDBgxKdx/79++PRo0fo2bMnbt68iUaNGmHJkiUFjjthwgS8e/dO1N8tY4wxVh6J+2YvuLkrEXG/jYwxxr568uOd/F0fEokE2traig6LlSBOwjLGyjwbGxtcvXo13/CrV6/C2tpaNMzJyQkTJkzA2bNnUa9ePWzevBkA0LBhQ9y/fx9WVlb5PkpKBe8K16xZg9GjR4sSt9evX0fLli2xdu1a0bjyZC+Qe0F55coV2NnZFTrO27dv8eDBA9E41atXx6BBg7Br1y6MHj0aq1evLjAudXV16OnpwczMDJqamvxiLsYYY+XWzZs3Ubt27Y+Ok5MjK7A7Aj7mMcb+V7wbYWVJTo4MMhlBJpMJH1tbW0WHxUoQJ2EZY2Xe4MGD8eDBAwwfPhw3btzA/fv3MX/+fGzZsgWjR48GADx+/BgTJkzAuXPn8OTJExw9ehQJCQlCknPy5MlYv349wsPDcfv2bdy9exdbt27FpEmTCqwzPj4eV69eRf/+/VGvXj3Rp3v37oiKihK13lm2bBl2796Ne/fuYejQoXj79i369u0rmubUqVNx4sQJ3Lp1C3369EHlypXRoUMHAEBwcDCOHDmCx48f4+rVq4iJicmXxC1I586d+cVcjDHGyq2oqCgMGjTo///6tGwIH/MYY/8r3o2wsi4kJETRIZQ8Rb+Mi1/MxRhjhbO0tMTp06dx7949+Pj4oGnTpti2bRu2b98Of39/AICWlhbu3buHwMBAWFtbY8CAARg6dCgGDhwIAPDz88OBAwdw9OhRNG7cGM2aNcOCBQtQs2bNAutcs2YN7O3tC7zz2LFjR7x8+RKHDh0Shs2aNQuzZs1C/fr18fvvv2Pfvn2oXLmyqNysWbMwYsQIODs74/nz59i/fz/U1NQAADk5ORg6dCjs7Ozg7+8Pa2trLF++vMhlM3HiRPj7+3NrIMYYY+XSzZs3cfDgQQwYMKDQ7oEYY4yxikZVVRURERH5nvxk5ZuE+BYyY4x9tsTERNSqVQvXrl1DgwYNChzn1KlT8PT0xNu3b2FgYFBKkVz5+NdJ9wEDm1Kqu4z52uf1c+bvf10mpb1My+o6+1/iKqvz9Lm+pvnJOy/Fna+vaf6/Bh+uj4+tn08Z91PqB77qbYIeH4CkVtv/BhS03Ph38UXlWyesYvmcYxcrx5wVHUDpSo9WdAT/0Wz1RatT+aK1McYYK3HBwcE4fPgwP5bJGGOMsRK0WdEBsHx4nTBWUaiqqiI8PByBgYGKDqXkVeCnOLk7AsYYK8ciIiIQHR3NCVjGGGOMMcYY+0pkZ2cjNDQUCQkJig6FlSDujoAxxsqxBg0agIgglWYhJyd3d867dcYYY4wxxhgr/1q0aIE1a9YoOoySlXFY0RH8R8P/i1bH3REwxlg5lZaWhvT0dEWHwRhjjDHGGGOsBCgpSQD897j+vXv3FBdMqam4D+VzEpYxxsqpxMRERYfAGGOMMcYYY6yE5D7U+N+TjWlpaQqLhZU8TsIyxhhjjDHGGGOMMcZKXwV+MRcnYRljrJyysLBQdAiMMcYYY4wxxkpIbn7yvySltra2wmJhJY+TsIwxVk5pa2tDU1OTX8zFGGOMsVIjkcgfj2WMMVbaZDJC3u4IbG1tFRcMK3EVtzdcxhj7CnTu3BkZGRmQSmUgIk7AMsYYY6xE8akFY4wpTkhIiKJDKAWSMvT5sjgJyxhj5djEiRPh7+8PSQXuV4cxxhhjjDHGviaqqqqIiIiAtbW1okNhJUhC3GyKMVZMFhYWCA4ORnBwsKJD+SweHh5o0KABFi5cqOhQSsEVRQdQ8STdBwxsFB1F+fI1LLPizMPXMJ+ljZcRY+UP/24ZY+wLcVZ0AKUr87iiI/iPus8XrY6TsIxVAAEBAcjOzsbhw4fzfXfmzBm4ubnh+vXrcHR0/Oh0Xr16BW1tbWhpaZVWqACA9PR0mJubQ0lJCX///TfU1dVLZLpv3ryBqqoqdHV1ixy3NBO2JZ3MDg4OxuHDh7krAsYYY4wxxhj7CqiqqiI8PByBgYGKDqXkZZ1UdAT/UfP6otVxdwSMVQD9+vXDsWPH8Ndff+X7bt26dWjUqFGRCVgAMDY2LvUELADs3LkTdevWha2tLfbs2VNi0zU0NCxWArY8iYiIQHR0NCdgGWOMMcYYY+wrkZ2djdDQUCQkJCg6FFaCOAnLWAXQtm1bGBsbIzIyUjQ8NTUV27dvR79+/QD8l/xUV1eHhYUF5s2bJxrfwsJC1DI0KSkJAwcOhKmpKTQ0NFCvXj0cOHBA+P73339Hy5YtoampierVq2P48OFIS0srMt41a9agR48e6NGjB9asWSP6jogQFhaGGjVqQF1dHVWrVsXw4cOF75cvX446depAQ0MDpqam6NSpk/Cdh4eHqPVpYeP26dMHsbGxWLRoESQSCSQSCRITE5GTk4N+/fqhVq1a0NTUhI2NDRYtWiSKr0+fPujQoQN+/vlnVKlSBUZGRhg6dCiys7OFGJ48eYKRI0cK0waAJ0+eICAgAJUqVYK2tjbq1q2LQ4cOFbmstm/fDg0NDaioKImmxxhjjDHGGGOsfJs1a5aiQ2AlSEXRATDGSp+Kigp69eqFyMhITJw4UUjUbd++HTk5OejevTuuXLmCLl26ICwsDF27dsXZs2cxZMgQGBkZoU+fPvmmKZPJ0KpVK6SkpGDjxo2oXbs27ty5A2VlZQDAw4cP4e/vj+nTp2Pt2rV49eoVhg0bhmHDhmHdunWFxvrw4UOcO3cOu3btAhFh5MiRePLkCWrWrAkgN1G8YMECbN26FXXr1sXz589x/fp1AMDly5cxfPhwbNiwAc2bN8ebN29w5syZAuv52LiLFi3CgwcPUK9ePUydOhVAbitgmUyGatWqYfv27TAyMsLZs2cxYMAAVKlSBV26dBGmHRMTgypVqiAmJgZ//PEHunbtigYNGiAoKAi7du1C/fr1MWDAAAQFBQllhg4diqysLJw+fRra2tq4c+cOdHR0Prpe09LSkJ6e/tFxGGOMMcYYY4yVD0pKEgD/Nay5d++e4oIpNRW34RAnYRmrIPr27Yu5c+ciNjYWHh4eAHK7IggMDIS+vj7mz58Pb29v/PTTTwAAa2tr3LlzB3Pnzi0wCXv8+HFcvHgRd+/eFd7YaGlpKXw/c+ZMfP/990LL0zp16mDx4sVwd3fHihUroKGhUWCca9euRatWrVCpUiUAgJ+fH9atW4ewsDAAwNOnT2FmZgYfHx+oqqqiRo0aaNKkifCdtrY22rZtC11dXdSsWRNOTk4F1vOxcfX19aGmpgYtLS2YmZkJZZSVlREeHi78XatWLZw7dw7btm0TJWErVaqEpUuXQllZGba2tmjTpg1OnDiBoKAgGBoaQllZGbq6uqJpP336FIGBgXBwcMi3LD+UmZmJzMzMr/SAzBhjjDHGGGMVU24vc/91NVecJ0lZ+cHdETBWQdja2qJ58+ZYu3YtAOCPP/7AmTNnhK4I7t69C1dXV1EZV1dXJCQkICcnJ9/04uPjUa1aNSEB+6Hr168jMjISOjo6wsfPzw8ymQyPHz8usExOTg6ioqLQo0cPYViPHj0QGRkJmUwGAOjcuTPS09NhaWmJoKAg7N69G1KpFADg6+uLmjVrwtLSEj179sSmTZvw/v37Auv6lHHzWrZsGZydnWFsbAwdHR388ssvePr0qWicunXrCi2CAaBKlSp4+fLlR6c7fPhwTJ8+Ha6urpgyZQpu3LhR6LgzZ86Evr4+WrZsWWS8jDHGGGOMMcYYUzxOwjJWgfTr1w87d+5ESkoK1q1bh9q1a8Pd3f2zpqWpqfnR71NTUzFw4EDEx8cLn+vXryMhIQG1a9cusMyRI0fw999/o2vXrlBRUYGKigq6deuGJ0+e4MSJEwCA6tWr4/79+1i+fDk0NTUxZMgQuLm5ITs7G7q6urh69Sq2bNmCKlWqYPLkyahfvz6SkpLy1fUp48pt3boVY8aMQb9+/XD06FHEx8fjhx9+QFZWlmg8VVVV0d8SiURIIhemf//+ePToEXr27ImbN2+iUaNGWLJkSYHjTpgwAe/evcOTJ08+Ok3GGGOMMcYYY+WHRALhXR8SiQTa2tqKDqnkSZTKzucL4yQsYxVIly5doKSkhM2bN2P9+vXo27ev0D+snZ0d4uLiROPHxcXB2tpa1KpTztHREX/99RcePHhQYF0NGzbEnTt3YGVlle+jpqZWYJk1a9agW7duosRtfHw8unXrJnpBl6amJgICArB48WKcOnUK586dw82bNwHk9n/r4+ODOXPm4MaNG0hMTMTJkycLrO9j46qpqeVrARwXF4fmzZtjyJAhcHJygpWVFR4+fFjgtD+moGkDuQnmQYMGYdeuXRg9ejRWr15dYHl1dXXo6enBzMwMmpqa/GIuxhhjjDHGGPsKyGQEmUwmfGxtbRUdEitB3CcsYxWIjo4OunbtigkTJiA5OVnU1+vo0aPRuHFjTJs2DV27dsW5c+ewdOlSLF++vMBpubu7w83NDYGBgZg/fz6srKxw7949SCQS+Pv7IyQkBM2aNcOwYcPQv39/4WVTx44dw9KlS/NN79WrV9i/fz/27duHevXqib7r1asXOnbsiDdv3mDfvn3IyclB06ZNoaWlhY0bN0JTUxM1a9bEgQMH8OjRI7i5uaFSpUo4dOgQZDIZbGxs8tVX1LgWFha4cOECEhMToaOjA0NDQ9SpUwfr16/HkSNHUKtWLWzYsAGXLl1CrVq1Pmk9WFhY4PTp0+jWrRvU1dVRuXJlBAcHo1WrVrC2tsbbt28RExMDOzu7IqfVuXNnrF+//pPqZ4wxxhhjjDFW9oWEhCg6hFJQcRsOcUtYxiqYfv364e3bt/Dz80PVqlWF4Q0bNsS2bduwdetW1KtXD5MnT8bUqVMLfCmX3M6dO9G4cWN0794d9vb2GDdunNDC09HREbGxsXjw4AFatmwJJycnTJ48WVRnXuvXr4e2tja8vb3zfeft7Q1NTU1s3LgRBgYGWL16NVxdXeHo6Ijjx49j//79MDIygoGBAXbt2gUvLy/Y2dlh5cqV2LJlC+rWrZtvmkWNO2bMGCgrK8Pe3h7GxsZ4+vQpBg4ciG+//RZdu3ZF06ZN8fr1awwZMuRTFj8AYOrUqUhMTETt2rVhbGwMILc/3KFDh8LOzg7+/v6wtrYuNAGe18SJE+Hv788tYBljjDHGGGPsK6GqqoqIiIhC38HCyicJEVHRozHGGCvbrig6gIon6T5gkL+VNfuIr2GZFWcevob5LG28jBgrf/h3yxhjX4izogMoXdmnFR3Bf1Tdvmh13B0BY4yVc8HBwTh8+DD4nhpjjDHGGGOMlX+qqqoIDw9HYGCgokMpeRX4KU7ujoAxxsqxiIgIREdHcwKWMcYYY4wxxr4S2dnZCA0NRUJCgqJDYSWIk7CMMVaObd++HRoaGlBRUYJEIuG+YRmrAPhnzhhjjDFWMcyaNUvRIbASxN0RMMZYOZWWlob09HRFh8EY+8K44TtjjDHG2NdJSUkC4L877vfu3VNcMKVFUnHbg3ISljHGyqnExERFh8AYY4wxxhhjrITk3mz/7457WlqawmJhJa/ipp8ZY4wxxhhjjDHGGGPsC+CWsIwxVk5ZWFgoOgTGGGOMMcYYYyUkt+///7oj0NbWVlgspafivuCAk7CMMVZOaWtrQ1NTE0QEqTQLOTm5j60QdxjJ2FdNIuF+YRljjDHGvkYyGSFvdwS2traKC4aVOO6OgDHGyrHOnTsjIyMDUqkMRMQJWMYqAP6ZM8YYY4xVDCEhIYoOoeRJJGXn84VxEpYxxsqxiRMnwt/fHxIFHEAYY4wxxhhjjJU8VVVVREREwNraWtGhsBIkIW42xRhjX4Erig7gy0u6DxjYKDoKxr6MD7d33v7LDl4XjLGyojj7o9LcZ/H+kLES4qzoAEqX7JyiI/iPksuXre6L1sYY+2JOnToFiUSCpKQkRYfCWOngk3xWkXy4vfP2X3bwumDs65R0/3/7XhEMbIqO63P2WcWdV94fsrLyu1BkHGVlGZRpSmXo82Xxi7kYU7CVK1di7NixePv2LVRUcn+SqampqFSpElxdXXHq1Clh3FOnTsHT0xN//PEHateuXSrxWFhY4MmTJwAAJSUlmJqaolWrVvj5559RqVKlUqmzrPDz88Px48dx/vx5NG7cWCEx9OnTB0lJSdizZ0+xywQHB+Pw4cPcHyxjjDHGGGOMfQVUVVURHh6OwMBARYfCShC3hGVMwTw9PZGamorLly8Lw86cOQMzMzNcuHABGRkZwvCYmBjUqFGj1BKwclOnTsWzZ8/w9OlTbNq0CadPn8bw4cMLHT8nJwcymaxUY/pfFRXj06dPcfbsWQwbNgxr1679gpH9byIiIhAdHc0JWMYYY4wxxhj7SmRnZyM0NBQJCQmKDoWVIE7CMqZgNjY2qFKlSr4Wr+3bt0etWrVw/vx50XBPT08AgEwmw8yZM1GrVi1oamqifv362LFjR77px8XFwdHRERoaGmjWrBlu3bpVZEy6urowMzODubk5PD090bt3b1y9elX4PjIyEgYGBti3bx/s7e2hrq6Op0+f4u3bt+jVqxcqVaoELS0ttGrVSjhoEBGMjY1FMTZo0ABVqlQR/v7999+hrq6O9+/fg4gQFhaGGjVqQF1dHVWrVhUlgjMzMzFmzBiYm5tDW1sbTZs2FS3DwmIszLp169C2bVsMHjwYW7ZsQXp6uuj7lJQUfP/999DW1kaVKlWwYMECeHh4IDg4+JNjOnLkCOzs7KCjowN/f388e/YMABAWFoaoqCjs3bsXEokEEolEVL4g27dvh4aGBlRUlIQyjDHGGGOMMcbKv1mzZik6hJInkZSdzxfGSVjGygBPT0/ExMQIf8fExMDDwwPu7u7C8PT0dFy4cEFIws6cORPr16/HypUrcfv2bYwcORI9evRAbGysaNpjx47FvHnzcOnSJRgbGyMgIADZ2dnFju3vv//G/v370bRpU9Hw9+/fY/bs2fj1119x+/ZtmJiYoE+fPrh8+TL27duHc+fOgYjQunVrZGdnQyKRwM3NTUgqvn37Fnfv3kV6ejru3bsHAIiNjUXjxo2hpaWFnTt3YsGCBVi1ahUSEhKwZ88eODg4CPUPGzYM586dw9atW3Hjxg107twZ/v7+ojuFBcVYECLCunXr0KNHD9ja2sLKyipfQnvUqFGIi4vDvn37cOzYMZw5c0aUmP6UmH7++Wds2LABp0+fxtOnTzFmzBgAwJgxY9ClSxchMfvs2TM0b9680HWTlpaG9PR0ZGRkQCqVgYi4RSxjjDHGGGOMlVNKShIoKSkJH/m1Mvs6cJ+wjJUBnp6eCA4OhlQqRXp6Oq5duwZ3d3dkZ2dj5cqVAIBz584hMzMTnp6eyMzMxIwZM3D8+HG4uOS+zc/S0hK///47Vq1aBXd3d2HaU6ZMga+vLwAgKioK1apVw+7du9GlS5dC4wkJCcGkSZOQk5ODjIwMNG3aFPPnzxeNk52djeXLl6N+/foAgISEBOzbtw9xcXFC4nDTpk2oXr069uzZg86dO8PDwwOrVq0CAJw+fRpOTk4wMzPDqVOnYGtri1OnTgmxP336FGZmZvDx8YGqqipq1KiBJk2aCN+tW7cOT58+RdWqVQHkJjAPHz6MdevWYcaMGQXGWJjjx4/j/fv38PPzAwD06NEDa9asQc+ePQHktoKNiorC5s2b4e3tDSC35ay87k+NaeXKlUKXEsOGDcPUqVMBADo6OtDU1ERmZibMzMwKjTczMxOZmZl8QGaMMcYYY4yxr0hum5r/GtakpaUpLBZW8rglLGNlgIeHB9LS0nDp0iWcOXMG1tbWMDY2hru7u9Av7KlTp2BpaYkaNWrgjz/+wPv37+Hr6wsdHR3hs379ejx8+FA0bXmSFgAMDQ1hY2ODu3fvfjSesWPHIj4+Hjdu3MCJEycAAG3atEFOTo4wjpqaGhwdHYW/7969CxUVFVGLWSMjI1F97u7uuHPnDl69eoXY2Fh4eHjAw8MDp06dQnZ2Ns6ePQsPDw8AQOfOnZGeng5LS0sEBQVh9+7dkEqlAICbN28iJycH1tbWovmPjY0Vzf+HMRZm7dq16Nq1q/BitO7duyMuLk6Y1qNHj5CdnS0kgQFAX18fNjb/vQG2uDFpaWmJ+vStUqUKXr58WWSMec2cORP6+vpo2bLlJ5VjjDHGGGOMMcYUS6kMfb4sbgnLWBlgZWWFatWqISYmBm/fvhVag1atWhXVq1fH2bNnERMTAy8vLwBAamoqAODgwYMwNzcXTUtdXf1/jqdy5cqwsrICANSpUwcLFy6Ei4sLYmJi4OPjAwDQ1NT85P5HHRwcYGhoiNjYWMTGxiIiIgJmZmaYPXs2Ll26hOzsbKEVbfXq1XH//n0cP34cx44dw5AhQzB37lzExsYiNTUVysrKuHLlCpSVlUV16OjoCP8vToxv3rzB7t27kZ2djRUrVgjDc3JysHbtWkRERBRr3oobk6qqqug7iUTyyV0ITJgwAaNGjcL79+9FrZ4ZY4wxxhhjjJVfuZev/13DamtrKywWVvK4JSxjZYSnpydOnTqFU6dOCa1BAcDNzQ3R0dG4ePGi0B9s3hdNWVlZiT7Vq1cXTTfvi73evn2LBw8ewM7O7pNikycVP3xZVV52dnaQSqW4cOGCMOz169e4f/8+7O3tAeQmHFu2bIm9e/fi9u3baNGiBRwdHZGZmYlVq1ahUaNGooOMpqYmAgICsHjxYpw6dQrnzp3DzZs34eTkhJycHLx8+TLf/H/sMf6CbNq0CdWqVcP169cRHx8vfObNm4fIyEjk5OTA0tISqqqquHTpklDu3bt3ePDggfB3ScWkpqYmanFcEHV1dejp6cHMzAyampr8Yi7GGGOMMcYY+wrIZASZTCZ8bG1tFR0S+8CyZctgYWEBDQ0NNG3aFBcvXix2WW4Jy1gZ4enpiaFDhyI7O1vUutHd3R3Dhg1DVlaWkITV1dXFmDFjMHLkSMhkMrRo0QLv3r1DXFwc9PT00Lt3b6H81KlTYWRkBFNTU0ycOBGVK1dGhw4dPhpLSkoKnj9/DiLCn3/+iXHjxsHY2PijL4mqU6cO2rdvj6CgIKxatQq6uroYP348zM3N0b59e2E8Dw8PjB49Go0aNRJaiLq5uWHTpk0YO3asMJ48Adq0aVNoaWlh48aN0NTURM2aNWFkZITvv/8evXr1wrx58+Dk5IRXr17hxIkTcHR0RJs2bYq93NesWYNOnTqhXr16ouHVq1fHhAkTcPjwYbRp0wa9e/fG2LFjYWhoCBMTE0yZMgVKSkpC0tPa2rpEYrKwsMCRI0dw//59GBkZQV9fP1/r2bw6d+6M9evXF3t+GWOMMcYYY4yVDyEhIYoOoeSV44ZDv/32G0aNGoWVK1eiadOmWLhwIfz8/HD//v1CXwSeF7eEZayM8PT0RHp6OqysrGBqaioMd3d3R0pKCmxsbFClShVh+LRp0/DTTz9h5syZsLOzg7+/Pw4ePIhatWqJpjtr1iyMGDECzs7OeP78Ofbv3w81NbWPxjJ58mRUqVIFVatWRdu2baGtrY2jR4/CyMjoo+XWrVsHZ2dntG3bFi4uLiAiHDp0SJREdHd3R05Ojqi1r4eHR75hBgYGWL16NVxdXeHo6Ijjx49j//79Qgzr1q1Dr169MHr0aNjY2KBDhw64dOkSatSo8dEY87py5QquX7+OwMDAfN/p6+vD29sba9asAQDMnz8fLi4uaNu2LXx8fODq6go7OztoaGiI5v9/jSkoKAg2NjZo1KgRjI2NERcX99HxJ06cCH9/f24ByxhjjDHGGGNfCVVVVURERMDa2lrRoXzVMjMzkZycLPpkZmYWOv78+fMRFBSEH374Afb29li5ciW0tLSwdu3a4lVIjDHGPllqairp6+vTr7/+quhQKCMjg6ZMmUIZGRlcjst9FeXKQ4xcjsvxb4HLcTn+LXA5Lvely5WHGLlcyZdjpWfKlCkEQPSZMmVKgeNmZmaSsrIy7d69WzS8V69e1K5du2LVx0lYxhgrhqtXr9LmzZvpjz/+oCtXrlD79u1JX1+fXr16pejQ6N27dwSA3r17x+W43FdRrjzEyOW4HP8WuByX498Cl+NyX7pceYiRy5V8OVZ6MjIy6N27d6JPYUnyv//+mwDQ2bNnRcPHjh1LTZo0KVZ93CcsY4wV088//4z79+9DTU0Nzs7OOHPmDCpXrqzosBhjjDHGGGOMMfaJ1NXVoa6u/sXq4yQsY4wVg5OTE65cuaLoMBhjjDHGGGOMMfaFVa5cGcrKynjx4oVo+IsXL2BmZlasafCLuRhjjDHGGGOMMcYYY6wQ8idiT5w4IQyTyWQ4ceIEXFxcijUNbgnLGGPlnLq6OqZMmfLJj1FwOS5XVsuVhxi5HJfj3wKX43L8W+ByXO5LlysPMXK5ki/Hyo5Ro0ahd+/eaNSoEZo0aYKFCxciLS0NP/zwQ7HKS4iISjlGxhhjjDHGGGOMMcYYK9eWLl2KuXPn4vnz52jQoAEWL16Mpk2bFqssJ2EZY4wxxhhjjDHGGGOsFHGfsIwxxhhjjDHGGGOMMVaKOAnLGGOMMcYYY4wxxhhjpYiTsIwxxhhjjDHGGGOMMVaKOAnLGGOMMcYYY4wxxhhjpYiTsIwxxhj7Ih49eqToEFgFwe+dZYwxxhhjZQ0nYRljrIySyWRftBxjxfVhgqs4Ca9Dhw7BysoKhw4dKq2w8uHfQsVz4sQJJCcnQyKRfFK5L520/dLbJielWWk6ePCgokMoNv4tlG9519+nrMucnJzSCKdQn7Od/S/Hhc9dLv9LPf9rWf4tsoqKk7CMMVZGKSnl7qKzsrIAFO9k5ebNm0K5+fPnY9euXcWu78OTv+KeHH3Jk6i8daWnpxe7XEEntsU52f3SifAvWS5vmffv339SOXmC68WLFwBQrIRX69at0bt3b3z//feIjo7+xGg/j/y3cO7cOaSmppbZC5PP8Tm/1//lAu9zyhYU0+fGWZxyS5cuRWBgILZv347U1NTiBQnxNv3s2bNPKve55NvmlStXSr2+vPP37t27YpeTL/NPvbj/X/YtXxInwgv2qXHu3bsXAQEBWLJkSSlFVLLkv4WUlJRSredz92OscHn3ZXn/X5TMzEwoKysDAN68eVPsuuSkUuknRvrfdvb27dtil5EfF0JCQrB169ZilyMiob60tLRiLZe881fcfWHeZf769etixycnL3vjxg3R38XxpX47n5us/9xrKFYxcRKWMcbKmLwH8o0bN8LW1lZo2fWxg/rDhw9Rv359TJ8+HWPHjsXUqVNRr169YtcpP/m7ePEiMjMzi30SJx/vzp07n3SBDwARERFYuXIlgOKdsMjr+uWXX7B+/XohhqJilM/b/fv3kZCQgL///lsYVpxyUVFRiImJERLixS23Z88e3Lhx45PLbd26tdgtRvOWu3TpEv78889PKrN8+XIsX778k8vNmjUL4eHhuHjxYrHiBIB169YhMDAQXbp0KXYi9n+5kCUixMbGwtPTE+/evSvyN1TYtvQp2+a0adOwbt26Ypf7nNYredfD6dOnkZ2dXeTvNW+Zs2fPIj4+HgkJCZ9c386dO3Hw4MEiL1Ty7htSUlKEpOinxLl9+3bs3bu3WOUAYNiwYfj222/x888/Y+vWrcVKsny4TU+YMKFY23TecpcvX8aBAwdw8+ZNvHr1CkDh63LHjh0YPXo0AGDkyJEYPXo0kpKSPqm+/fv349SpU0WW+bBcREQEhg8fjkePHhW5reVdf+np6cL4Eonko/vcvPUtW7YMc+fOLVZiO2+5hQsXYs6cOcW6GM4by4fzVNw45dt0cZTEPuJTlPSNuU9Z7y9fvixWXd988w3mzp2LkSNHYvHixZ8U5+cmKv7XBMf69esxYcIE5OTkFOsc4lOGy7/Lu384c+YMpFJpsbeBvNMuzvmD3Ofc+PrYfHys7OfeZPtcRCQs0759+8LHx6dY5Y4dO4b58+cDAAYPHoxOnTohOzv7o2Xyrr/58+dj3rx5xU7e7tu3D48fPwYATJgwAWFhYUXWl3e57d27F1FRUahSpUqx6jt06BDu3bsHABg3bhxGjBhRrOOzfP5+++037NmzB5mZmcUuM336dPTo0QMPHz4sVox5bdu2DQMGDChymcjrLMz/sl0X5tWrV0Kyfv369cJyLUreZRMdHY03b9581v6eVSDEGGOszMjJyRH+v2vXLpo1axZJJBLy9PSk5ORkIiKSyWQFlpVKpbRt2zZSUVEhPT09evjwYb5pFlXnpEmTqHHjxhQVFUUymazQugoq980339Du3bspKyur0DIfTm/q1KlkbGxMt2/f/miMHwoKCiIzMzN6//59gdMtqL7JkydT3bp1ydbWloyNjWnx4sX0+vXrIsuFhISQmZkZLVmyhN6+ffvRuPKWGzduHJmbm9OKFSvo3bt3xS43duxYsrS0pLlz59LLly+LvQ4mTJhATZs2pS1btlBqamqx6zI2NqYNGzbQn3/++dEY8xo7dixVrlyZtm3bRv/880+hMRWmX79+pKOjQ4cOHfroeHmnFR0dTfv27aNr164VO065pk2b0oABAz66LPN+t3z5cpowYQJNmjSpWPOT19ChQ6lJkyaFblsF1Xn8+HEKCQmhNm3a0KZNm+jevXvFinPSpElkYWFBGzduLHacY8aMITMzMzIxMSEXFxeKiooqVoxEudt09erVad26dfT8+fMCxyESr7e5c+eSu7s7NW7cmHr06EFSqbRYdY0dO5YsLCxoxYoV9OzZs0Lrkss73d69e5O1tTX9+uuvwn6zKPJteteuXfT06dOPjvvh/sHa2posLS3J1dWVvLy86O7du4XGGBUVRRKJhJo1a0a6urp048aNImP7cB3UqlWL1q1bRy9fvixwnIKMGzeOqlSpQr/++iv9/fffHx037/pbuHAhtW3blvz9/SkkJISys7OFefmYsWPHkqmpKa1fv54SExM/Ou6H5czNzWn27Nn59i0fi/OXX36hQYMGUd++fWnJkiUfLffhdlarVi1asWLFR7fpD+s7cOAAbd68mVasWCEsk+LEOX/+fOrZs+dHxy+o3NGjR2n16tW0Z8+eIo+XectdvHiRzp8/T2fOnPmk+mbMmEHffPNNodvyh9LT02nu3LkkkUho0aJFxSqTt74XL15QYmIipaenC8MK26bzlrt//z49ePCAHjx4UKw65UaNGkXW1tZF1pV3+Pr162nevHm0cuVKYVhRv4Nx48ZRpUqVyMTEhKysrCgmJuaj50hE4vlbvXo1bdiwQfRbL065lJSUQuejsDLLly+n4OBgCggIoF27dn10P/Hhunv06FGx6sv73b///ktSqZQyMzPzTfNj7t27Ry1btqSTJ08WOa5UKqWgoCBycnIiDw8PMjQ0pDt37hSrHqLc/UOVKlVo8eLFov1DYVJSUsjd3Z0MDAyob9++pKWlRdevXy92fQcOHKAhQ4bQggULijV+RkYGNWvWjMzNzalnz56kp6dHN2/e/GiZgs5T161bV+T+Nm+ZqlWr0rp16+jx48fFKpPX7du3SVVVtchzjw/373379qXevXvTrFmziqwjb9n9+/cXa/8XFxdHysrK9ODBAxozZgxVrVqVnjx5UmS5vMszNDSUqlWrRitXrizyd84qNk7CMsZYGSRPQERERFDPnj2patWq5OTkVGAiNu/JxsGDB0kikZCSkhJNmzZNGF7UBTpRbhLPyMiITp48WawT/rzljI2N6cCBA/kST3ljKyiGP//8k7799lsaPXp0ocmSvOXkJ+tERC4uLtS9e/dizVtERAQZGxvTiRMnKCMjg77//nvS0dEp8mJ27ty5ZGxsTFevXhXmpTj1LVq0iExMTOjy5cuUlpZW5Phys2fPpsqVK9OFCxeKXYaI6KeffiJjY2M6evRosZNOv/76K1WtWlWU1JRKpUVeaOzcuZOqV68uurBISkqiq1evCn8Xtd6JiH744YdiJWKJiMaPH0/a2tpkbW1NqqqqtGrVqgLH+/AiTr69zJs3j9zc3OjFixcfjYmIKDw8nAwMDKht27ZkYmJCDRs2FG5oFMehQ4fI3t5eWIdFXVju2rWL9PT0qH///jRq1CiqWrUqdezYschE4KRJk8jExIRiY2OF+SpI3nm9cuUKWVtb04ULF2j//v00YsQIqlatWqHLM6+5c+eSmZkZnT17VjRcPn8FJSMmTJhAVapUofnz59OePXtIX1+f2rdvX+SFzdy5c8nExCRfXQXNU155k2G9evUia2trWr16dZG/ib1791KNGjWE34JMJqPk5GTR77CgOpcuXUomJibCBd64ceNIQ0ODoqOj842bdzvw9fUliURCffr0KXKe8po5cyaZmprS77//XuB2Vdi2tm/fPjIzM6PLly8Lw969e0cJCQkfvVkwfvx4MjU1pdmzZ9P06dPJ1taW2rZtK1xcFpaAWrt2LVWtWlVUHxF9dDslyt0nGRsb59snSaXSjy4fecI3NDSUgoODycTEhHr16vXRuoiI5syZ81nbmfz47ObmRvb29mRtbU1xcXFFJm7PnDlDISEhJJFIaNy4cUXGJzdu3DiqUaMGubm5UfPmzcnBwYH27t1bZMwTJkwge3t7srGxoRo1atD3339f5A1B+fxVqVKFNm3aRH/88Uex40xLS6M5c+YUKxH74Q1SNzc30tXVpe7du9OcOXOKVW7SpEnk7OxMNWrUoEaNGtFPP/1UZBn5+nj//j1ZWVmJzpM+Vm706NFkZGREDRo0oFq1alHLli2F7/P+DvKWuXjxIjk6OtKJEyfo1q1b1LFjRzI0NKR9+/YVmqD58AaBiYkJRUZGFisBKDdjxgxydXWlbt260Zo1a/LNe0HGjRtHJiYmFBYWRn369CErKysKCgoSbnQXFuOUKVOoUaNGZGJiQl5eXrRy5cp8CeCC7Nmzh5ycnKhp06Y0evRoIZlX1PFyzZo15OvrS127dqWsrKxiJ25dXFxIIpFQcHBwgfNRkLVr15KxsbHoXCczM5OSk5M/mnxPSUkhExMTUldXpwMHDhARFXmjhojo+vXr1LhxY9LX1xd+A8U5LhARVa5cmTQ1NWnnzp3FGp8o97zIzMyMzp07Jxou3zYLWrZHjx4lc3NzUZmkpCS6fv16gY0UPjxvli+HsWPHUseOHenNmzfFuoFoZmZG48ePp6lTp5JEIqF+/foVOv6HSWZra2tasWIF/fvvvwWOIz9PfPXqFfXs2ZN0dXVJX1+/WAnmvNvBlClTyNjYmM6ePVtkgw3GOAnLGGNlzLVr18jU1JQOHz4sDDt37hzZ29tTw4YNRYnYvCdJt2/fplevXtG///5LmzZtIhUVFZo0aVKx6rx+/TrVrVuXfv/9dyIievv2Ld27d4/mz58vtBoo6ETp3LlzZGlpSefPnyciotTUVHr48CFt2bJFaM334YlceHg4BQUFUUJCAhERRUZGkrW1tXDhXdjJ7cyZM2nEiBF0+vRpIiLavXs3ubm50Z49ez46bxkZGdSmTRvhrvuuXbuoUqVKtHz5clF9H7b8lUql1K1bN5oxYwYRET1+/Jj27NlDPj4+NGbMGDpx4oSwrD7UrVs3mjBhgjDdvP8WRCaTUVJSErVu3VpoZfPw4UPau3cvtW/fnoYOHSokxuXrSO727dtka2tLx48fJyKi169f0/Xr12nRokVCMqhLly75Wh2MHTuWunTpQkREDx48oNWrV5OTkxM5OjrSL7/8UmisUVFR1KRJE5LJZHT//n2aMWMG1apVi2rUqEEBAQH55ouI6OzZs7RkyRLaunWrKCldWCI27zJ79OgRubi40IULF+jhw4c0b948UlJSorlz5xYa48WLF0V///3332RoaEgRERH5xv1w++zfvz/9/vvvJJVK6a+//iJnZ2eqV69evmRE3vX54QWWt7c3+fn5FRqfvGxiYiLVrVtXSILKZDLS0tKi8ePHF1qGKHdbbNiwIe3fv5+IclsU3bhxg8LDwyk2NrbARMuaNWsoKChI2C6JiB49eiS0PPzYOk9LSyM/Pz+aPXu2UP+BAweoa9eu1KdPnwJvDh08eJDs7e2FBGV0dDRpa2uTgYEBNWvWTJRklpfLycmh5ORk8vf3p3nz5gkx7tmzh7799lvq1auXsP3kLVOYHj16FCsRGxkZSY6OjkSU28oqIiKCateuTYaGhtSpU6d848tkMpJKpdSzZ09h/7Bv3z7S1dUVlmNaWhq9efMmX9k1a9ZQmzZtaNq0aaSurk5jxowRvvvYhf3bt2/Jzc1N2G89efKEjh49Sv369aNRo0aJYvtwmaxbt47c3NyIiCg+Pp6mTZtGVlZWVKNGDQoKChK1NJbbvn072dnZCfv23bt3k7a2NhkbG1OLFi1ELWI/rG/cuHEUGBgoLM+VK1eSk5MT1apVizZu3Fjg/MlkMho3bhwNHTqUiIju3LlDK1euJAcHB2rRogVFRUUJyyfvcoqNjSUrKyshKbBjxw7S1tam1atX55t+XsnJyeTr6yu0mn38+DHt27ePunTpQkFBQUIi4sNyv/76K5mYmAjHqz179pBEIhEdrwva148dO5ZsbW1p+PDh1Lx5c1JSUqKBAwcWuCzyioqKoipVqlBcXBwREf3888+krq5eZLJl7ty5ZGRkROfPnyepVErTpk0jiUQirM/CHDlyhGrUqCGMJ5PJ6N27d3TlyhXRTdC86/zD7XbmzJnFbhEbFhZGRkZGdOjQIYqPj6fWrVuTqalpkTdIp02bRoaGhnTq1Cl68uQJDRgwgCQSSZGtAOUyMjJo9OjR1L59+yJbrL1+/Zo6depEN2/epHfv3lFMTAzZ2tqSk5OTKBH74TK5e/cuhYeHi6bVqVOnQhOxecsvWbKEzMzM8t3cLOqG0vLly8nU1JTCw8PJz8+PGjZsKDqeFLS/PH78ONWuXVu4aXL8+HFSUVGhzZs3f7SuadOmkYmJCe3atYvevHlDjRs3Jjs7uyLX3c2bN6ly5co0a9YsGjx4MHl7e5Obm5vQmrmwfXpKSgqNGTOGqlevTk2aNBGGF7TflK+XzMxMev36NfXv35+6du1KzZo1o5kzZwpPC31snytPSBMR3b17l5YtW0Z2dnbk5uZGc+fOLTSx+s8//1DDhg2pUaNGVLVq1ULnq6D9RFRUFDk6OpK9vT3dunWr0PHyzvurV6/IwsKCHB0dycrKSvR0RUHnKTKZjDIzM6l9+/Y0ZcoUIso939y9eze1b9+eOnfuTH/99ZcoZvl0oqKiyMnJiYhyb+qGhYWRlZUVaWtrU9++fUU32vLW/eGN123btpGRkRHFx8d/dB7j4uLIyspKOO/dvXs3aWlp0YoVKwpdJnLyxheF3bSUyWTk6elJU6dOFYbJ913a2trCvqSgsqtWrRKO7zk5OfT8+XNq0aIFbd++nYiInj17RufPn6dhw4bRzp07CzzGsoqNk7CMMVbGxMbGkp6enugRTqlUSkePHiU1NTXy8vKi9+/fiy62Q0NDycvLizZt2kRSqZQyMjLo119/JRUVFQoLCxOmM3r0aDp48GC+Ou/cuSO0FL158yYNGTKEbGxsqGbNmh9tMXrt2jWys7Oj33//na5fv04jRoyg2rVrk6WlJenp6eV7DOvFixdkZ2dHEomEhg0bRuHh4SSVSql3797k7OwsjPfhCdnLly+pRYsWpK2tTX5+fjR+/HjKyMigtm3b0vfffy+Ml5OTk6/sixcvyMzMjOLj4yk2NpZ0dHSEE7j09HSaMGECPXz4UFTu33//pZycHGratCl98803tHHjRvL39ydvb2/q2LEjOTk50Q8//EBdunShvn37iupLTk4mS0tL4eQ27/xkZWVRQkJCgYkLIqJWrVqRt7c37d69m/z9/cnNzY169OhBJiYm9N133wmPMm/dulUo8+TJE3JwcKD169fTuXPnqH///mRvb09169YlVVVV2rZtG/Xr1480NTVp27ZtQrmwsDBq1KgRDR06lBo3bkydOnWiESNG0OjRo8nc3Jz+/PPPAmPcsmUL2dvbU+vWrcnCwoJ69uxJP//8M23btq3AVmUHDhwgVVVVoSVKp06dRK0ofvjhB6pUqZKQTM9bZ1JSEt26dYvGjRsnulhasmQJSSQS+vnnn0XLV15fzZo1qVGjRnT48GHhMckFCxaQu7u7qFVr3rquXbtGp0+fph49eogewX358iU5OzuTg4MD/fHHH7Ro0SLRhfDy5cspIiJCNN2TJ0+Sk5OTkICUyWT022+/CYl7uUePHlHDhg0pIyOD7t+/T+bm5hQUFCR8f+XKlXxdS7x+/ZqeP39OOjo6FB0dTefPn6f+/fuTo6MjmZubU40aNYTfuHy5PHv2jLp06UIGBgb5WpA8evRIaGk3f/58KkhmZiZ17NiRvvvuO/rll1+oTZs25O3tTQEBAeTo6EitW7fOd0F6/PhxYXrR0dFkaGhIq1atort375Kenh61b98+3yOs8vXx7bffkr+/P0VGRpK/vz95eXlR165dydLSkvz9/fONT5S7XU6aNIl+/vlnUStBeSL2119/pZSUlAIv9g4fPkz29vbk7u5ONWvWpF69etGCBQvo8OHDpKKiQrGxsQX+Frp27Uo7duyg6Oho0X4lOzub1qxZQ1u3bhUlWn7++WcyMzMT9qeRkZGkpqYmSsQSEcXExOSr6/379+Tn50cDBw6kTZs2UYcOHcjNzY18fX2F3yERCTe3iHITcefPn6eYmBiSSCTUrVs3qlq1KvXo0YNWr15NS5cuJVNT0wK7RNi+fbuQsN+/fz8ZGhrS4sWLaceOHaShoSG0iM2bTN+7dy+9efOG5s+fT3Z2djRw4EBycnKizp070/jx42ns2LGkqalJf//9d4E3p8aPH0/Kyso0b948cnJyovbt21N4eDi1a9eO6tWrRyEhIcJxUb4/2Lp1q3Ds2LlzJ+nq6go3slJSUgptaS+Tyah9+/YUEBBAmzZtotatW5OHhwd16tSJqlWrRh07diyw3MSJEyk0NFSoW09PT1jveX+reefr2LFjpKenJ9xATEpKoqioKNLU1KTBgwcXWI/c6NGjhXF27dolmr/U1NR8vyF53b169RIS0Tt37iQDAwOhXN5H/j+0bt06qlu3LhHl3pwNDw+nOnXqkIqKCvXq1YsyMjJEv4XFixdT//79ycfHh5YsWSI8wi5vEbt48eJC6/r777+pRYsWQmvB48ePk5aWltB6s7DkaEpKCgUEBAiJ6H379pGBgYFwM6ugx9tXrVpFbdu2pcuXLws3qS5fvkxqamqi4+mHli9fTnXq1KHWrVuLki7nzp0jW1tbatiwoXADV17f9OnTqW3btlSlShVq165dvpahnTt3JmNjY9q2bRtlZ2fTd999Jxwr5NMYOHCgsN4fPnxImzdvpubNm1P79u1px44dwrQ+3C/NmTNH+P7Fixc0ffp0sre3F7W8/rDM7t27qXnz5kSUu03r6uoKN3tSU1Pp9OnTlJGRIYwvk8no5cuX1Lx5c+Gc4uTJk6SjoyPchMrOzi70iZiLFy/S6NGjhb/3799P33zzDbm6uooSloU9PRUeHk7a2tqiG4p56/rYjbmBAwdS48aNadasWaL1UlCSLDQ0lJSUlCgsLIwcHByoY8eOFB4eTr169aL69esLN8YLqi89PZ3+/fdf8vb2pipVqoj2y0QkatmclpZGr169Ev7esWMHNW/enAIDA4XGDIU9/Sb/v3x5ubq6Uu3atfPdjMjb3ZT8+PPdd99Rx44dadGiReTn50d+fn4UGBhIzZs3J3d3d9FNF/nyiY+PJ4lEQt988w2ZmZlRnz59KCoqinbv3k3KysrCuV3eGA8dOkSVKlWi0NBQ0blfYGAg+fv7F9jaWm779u3C/n3Xrl2ko6Mj7MeSk5ML3b+/evWKWrRoQRs2bCAioqdPn9KxY8eoX79+NHnyZGG833//XbRtP336lC5cuEC9evUiHR0d4WZU3vObHTt2UO3atWno0KGUlJQkLF9DQ0NaunQpxcXFUY8ePcjZ2Znq1q1LxsbGFBkZSUTFb9nMvn6chGWMMQUq6ICclJREtWrVElpYyb169Yrq169P2tra1KhRI2H45MmTycjIiI4cOSJ63CYrK4t+/fVXUlZWpnbt2lGLFi3I2tpadGIll5ycTF26dCFzc3PS0tKioUOHCnd07ezsaNasWQWeaN69e5dcXFyocePGpKmpSQMHDqStW7fSgwcPyMHBgdauXZuvzJ49e0hLS4vGjRtHgwYNIjs7O9q8eTNZWFgIrRsLWi5r1qwhS0tL2r17Nzk7O1PPnj1p9uzZJJFI6NdffyUi8Ylf3v7M+vfvT97e3qSlpSWK6dmzZ+Tm5kbr1q0T6pw8eTKNHTuWiIhu3LhBdnZ2VKNGDQoLCxMSjLNmzaK6detSYmKisDzztvAcNGgQNWvWjO7fvy+an2vXrtHAgQNFCfYNGzYIrcO2b99OPj4+pKOjQz/99JPQ+mnu3Ln07bffUlZWFo0dO5Y0NDRoy5YtRJS7XQQEBFCjRo1IWVmZfvzxR9q/fz/9+++/5OnpKSzT0aNHk7q6Ov32229ElNv6dfjw4eTq6kqLFy8WTsz37dtHbm5uom3pyZMnopagq1evpmHDhtHGjRuFFhP37t2jhg0bCol3+Tz3799fSFLEx8eTtbU1tWvXTtSiV574yJvEmDhxIrm4uJC5uTk5OTnlSzYsXbqUVFVVRSfUz58/p4yMDLpy5Qp17dqVnJ2dyc7OjtauXUtr164lOzs7IcGVd1sZM2YMGRkZkYWFBUkkEvrtt99ESd+XL19SkyZNyNDQkCQSCfXq1UtIxPbo0YPc3NxIR0eHpk2bJvRT16BBA5owYQLJZDJ6/fo1ValShb755htR32SXLl2imjVr0sWLF6l27doUFBQkxHXlyhX6/vvvaeHChUKLmHHjxgmt5/r27Uva2tqkra1NI0aMEBIZDRo0oIkTJ9KHLly4IDxqt2vXLtF3jx8/poEDB1L79u0LfbQ2KiqKfHx8SE9Pj8LCwoSLqcmTJ1Pr1q1F6yUmJoZkMhk9ffqUUlNTqWXLlsLNoFevXpGDg0O+RwojIyOFR3w3b95Mbdu2JT09PZoyZYpQ1+zZs6lz58759g/yx3b9/PzI2dmZjIyMKCQkRPi+Z8+eZGdnRwsWLBAu+B48eEA3btwQ9hO7d++mwYMH05YtW4S+8RISEqhx48aix+Pz9ic4YMAAqlq1Kunr64taXr548YK8vb1F/frdvn2bRo0aJboRkp2dTevXrycNDQ0aPnw4PX78mFq3bk3t27cvcB84f/58atmyJWloaNDEiROF31BwcDD179+fbt26RRKJhDZt2kQjRoygSpUqCRfxO3bsoL59+9KGDRuEef7333/JyclJ2JcQ5e5n5a2W/vzzT3r37h01a9ZMaEX+/PlzsrGxIYlEQgEBAdSsWTM6fvw4jRo1ijQ1NenNmzd09+5d+umnn8jFxYWWLFki3NQ4duwYubm5ibq7SUpKEp4myMnJoSFDhpCjoyPNmzdP2O7Pnz9P9vb2ZGtrS15eXqKEwtGjR6lTp060adMm0QW6/LvBgweLHivNu1w3bNhAvr6+pK2tLdrfTps2jbp27VrgMa9du3YUHBxMZ86cESWrZDIZTZkyRbgxlNfmzZupVq1aoov99PR04WaSvKViQYmnMWPG0Pz58+no0aOi+cvJyaH169fTsmXL8iVV09LSyNramtavX08xMTH5bhD89NNPtG/fvgLn7/r166Snp0ctW7Ykc3Nz6tOnD61du1ZI5Ofdb48bN46MjY1pwYIFNGbMGLKxsaG2bdtSRkYGvX//nubOnUsqKirCtvPhvP3777/CcXTPnj35bpCuXbuWbty4ka/cmzdvyNzcnGJjY+nIkSOicpmZmTRz5kxhXRLl/m62bNlCjRo1osaNG1PLli3pxIkTlJKSQtOmTaNvv/1WdLyTk0qltGXLFnJ0dKTq1auLvpPJZHT+/HmqW7cumZubC8NXrlxJ+vr6FBoaSu7u7qSnp0fLly/P93SCl5cX+fv707t37+ibb74hfX194QmOzMxM6tOnD3l5eVFYWBh5eHhQu3btqFevXvT999+Ti4sLvX79WrT+duzYQbt27aLWrVvT7t27heEvX76kiIgIqlu3Lo0fP77Adb5+/Xry8PAQbhYsXbpU+G7Xrl00bNiwfEnKFy9eUP369Sk1NZUOHjwoWgdpaWmi/kLl6+/UqVO0YMECGjlyZL6bgfJErLu7O929ezffzdjMzEwhKf/nn3/S5MmTycbGRtTS+MNWrUuWLKHvv/+exo8fL9wAzc7OpoEDB1KzZs0oPDyc/vzzT/L09BRa7iclJYkSpKNHjyY3NzdatGiRsB+7ePEiOTs705MnT0Tb5tatW2nevHmi84e//vqLvL29qVq1anT79m3Kysqi7t27C8fomTNnkpeXF1lZWVGnTp2EbWDjxo3CTaG8fcR/WN+0adNo9+7dwj41JSWFWrRoQXXq1KErV65QSkoKubm5kYODAyUlJdGwYcOoWrVqJJVKaePGjdSuXTsyNjamadOmCXXPmjVL9ATI1q1bycnJiS5dukREuQn3/v3709atW4WWr8nJydSkSZN8fa9OmDCBhg8fTps2baJ69epR48aNqU2bNnT16lVasmQJtWvXTjim5k10ytd/XFwctW3bllauXJlv/37y5Enq1atXgTeiMjMzycPDg/r27UsHDhygjh07kouLC7Vq1Yq0tbVp+PDhovFnzpxJ3bp1E87nnz9/Tt26dSMdHR1Rtzpz5syhO3fu0KxZs6h58+Y0ePBg4fglvzmgo6NDo0ePFp6OaN26NQ0ZMiRfjKxi4yQsY4wpyIetBOQH/+zsbBoxYgS1bNlSuHtKlHty2K1bN9q3bx9ZWVnRzz//TAkJCdSgQYN8/cPlPVE7evQodezYkYYOHSpcBEqlUjpy5AhFRkbS5s2bKSkpid6/f08HDhyg06dPC7Glp6dTs2bNaN26dcL04uLiaPv27XQerN+EAAEAAElEQVT+/HnKyMigJ0+e0ObNm+no0aPC9NPT06lhw4ZCC5MtW7ZQVFSUMI8TJkyg3r1704sXL2jixIlUv359MjQ0JGtra1GLgS1btohestKxY0fhEfqxY8dS//79SSKRUKVKlUR3/qdNm0a9e/emI0eOEFHuI6S1a9cWtdhLSkoia2trqlevnujkvXv37qJH91NTU0UXINnZ2WRoaEimpqbC/CxdupQaNmwonJDu2LGDnJ2dadCgQcL8vH79mgICAsjT01NYvmPGjCELCwuaNm0avXnzRnhJxYcvyfL09KQBAwYIf4eGhor6//r777/p9OnT+fr2atq0qagl0qhRo0hNTU1IumRnZ4uSx5mZmdS2bVtq166dsA2FhISQjY0N6evr0/fff5/vJTtSqZSSkpIoICCAPDw8hGX5999/06tXryg0NFR0EhsfH082NjYUEBAgajUrT+YS5bbGqlq1Ks2cOZNGjRpFEomEQkJC8l0oz5gxg1q0aEEymYymTZtGPj4+olaEly9fpp9//plq1qxJ3bp1I4lEQi1bthRdEB8+fJicnJxo3759dPr0aWrevDlZWlpSXFyc6Df6/Plz6tu3L8XExJCBgQF99913wndpaWm0YsUK8vf3J3Nzcxo+fDgNHDiQjIyMhO3yzp075OjoSG3atKFTp04JZb/99luSSCSi6RHl/kYaNWpE3t7epKGhQb169SItLS3h8T2pVEonT57M1++mu7u7sM7fvXsneiT+1q1b1LNnT7K3txddqBPlPkKZt2uOZcuW0aBBg6ht27a0bt06SktLI6lUmq+vWldXV1JWVqbp06dTSEgI6ejoiC4anz59SlZWVnTs2DEiyv3d/fDDD3Tr1i2hr0+ZTEa7du2i5s2bC614k5OTRdsEUW43D3lbCsvXn7yfVKLcpMOqVatIQ0ND1Bo9ICCAunXrRjKZjEJDQ8nZ2ZkqV65MXl5eon4CiXJ/F/Lfa8uWLYXtYPLkydSgQQMhxvfv31PLli2pZs2a9PLlS3rz5g09f/6c/P39qVmzZpSdnU0ymYxOnDhBEomEdHV1Ra3Y5HVt27aNtLS0yNbWlho0aCAkG1avXk0jR46kXr160a5du4THkT/so9jb25t+/PFHIsrt509DQ4N0dHSEGyIf9tsrlUopNTWV/P39qUGDBuTk5ETLly+nkSNHkkQiEe2Db968SdWqVaMrV64I67Nbt2508uRJOnv2LHXq1ImqV69OBgYG+brsyPvixMzMTGrTpg21bt1a2LfMmjWL3NzcyNHRkb755hsh6Zp3n5SdnU3+/v7Url072rlzJ3l5eZGnp6ewj7x79y5Vrlw5X6vL9PR08vf3px49egj1rVy5koKCgui7774TPc764aOyXl5eoq4CLl68KFzo79q1ixo0aEAqKiqiLjySk5OpTZs2ouS/3JUrV0hXVzdfq62bN28KN3aGDRsmGl9u4cKFpKysTBoaGqLjcFJSEvn4+NCAAQOEpPrIkSOFJEhYWBj5+PiQlpaW6AbBy5cvqVWrVqKuAm7evElPnjwR+gfOm2SRJ6Rev35NzZo1ExI1Z8+eJRsbG6GlWHR0dL4YiXL7K3d1dRUdY+U3216+fEmOjo40cOBAMjQ0pGXLlgnj3Lp1i9q0aSNaZi9fvhSOuX369KHvv/+e9PT0RH1aJyYmUps2bYRj3MKFC0kikQg3RKOjo6lfv35UtWpVCggIIBcXF2rQoAHdu3ePcnJy8iUpU1JSaM+ePWRmZkatWrUSfSeTySg2Npa6d+9OUqmUzp07R4MGDRK6iSHKfdLD2tqafvnll3xdCciT7i9fvhQSPvJ+qC9fvkwBAQFUt25dmjNnjtAtwerVq8nHx0eUeB8zZgzp6OhQjRo1SEtLi3r06CGq5+XLlzRz5kwyNDQUbhpERkYK50fJycnCDUh5y0Gi3N9Q69atRb8h+TxkZ2dTvXr1qH379qSvry/6LSQkJJC7u7toOezZs4c0NTXJ3t6eqlWrRpUqVcrX5+bBgwepadOm5OfnR1lZWSSTyejnn3+mb775hlq0aEGDBw8WzgESExNpypQpZGdnJzxOnnfdyRsndO7cmZo2bUq2trZC9wrZ2dk0fPhwcnBwIHNzc2rUqBFlZmZSREQEubq6Uq1atcjb21s4l8h78yQzM5P8/f2pTZs2+V6MqqmpSc2bNxdu1Mpb9f7111/k7+9PKioq5OzsTFZWVpSVlUWTJk0iU1NTWr16NcXHx1OlSpXI3d1dSKiuX7+evLy8yMvLK1/CNzQ0lHR0dKhZs2akpKRE/fr1E36bqamp5O7uTtra2uTo6EgmJiZUr149atiwIRkZGYme9Hn79m2+/ob9/f1F/ZXv2LGDfH19ycfHR9gO5fOelZVFycnJ1KpVK3JxcRH9zvft20fVqlUTluM///xDx44dIw8PD2revDk1adKEJBIJhYaGipbl5s2b6ciRI/Tu3Tt68OAB2drakkQiEbpDIso9trRq1arQl33KZDKaP38+NW/enNTU1CgkJEQ47xo5ciT98MMPovH37NlDKioqNHDgQGF9v3z5krp3704aGhq0cOFCMjExodq1awv9lM+YMYOaNWtGgwcPFlrExsfHC8cxeRxeXl40ffr0fDGyio2TsIwxpgB5TzjmzZtH3bp1o/r169PcuXPpwYMH9Pr1a+rWrRs1bNhQeKywZcuW5ObmRsnJydSoUSMKDg6mBw8ekKmpaYGPr2ZkZAgXVXkf68vOzqaxY8eSlZUVOTs7k7e3NxkaGopOzNLT0+n+/fvUtm1batiwoZC4HDduHNWuXZvq1q1LTZs2JRcXF1GfZRkZGfTXX39R69atqXHjxiSVSun9+/fk7e1NLVq0oNatW9PLly/pxIkT1KtXL+HxzGPHjtHAgQOFBKVMJqPnz59TUFAQGRsbU6dOnSgxMZEePHhAXbp0EZK7ly5dogEDBlCTJk2EZTp+/HgyMjKi3bt3i5I4EydOpAYNGlDdunWpXbt25ODgQOrq6tShQwc6ceKEcCLn6uoqXNTlXU/Jycm0e/duaty4MamoqAjTvnv3Lt25c0do6Si/K758+XJq0aIFmZmZUdOmTcnBwYHq168vrItVq1aRsbFxvv5L5VJTU+nkyZP0zTffUL169YR1sHjxYpo/fz5JJBLS09MTtWIjyk1gPHz4kPz8/MjJySnfY+IjRowgNTU1oUWsfN62bNlCfn5+5ODgIMQYFRVFFhYWtGnTJtq0aROZmZmRr6+v0CIiKyuLlixZIvQ9Jy/322+/Ue3atYWXU3zYf9f169epXr165O7unq+PwrNnz9LIkSNFj4hGRkYKJ+sfvkhIJpPRhAkTqHLlyrRv374CW0XcuXOHtm/fTn5+fmRmZiZsd5s2baLg4OB8L3Rp0qSJ0A+ZfHvMe6IfExNDenp61L17d1Hr3efPn9OFCxfIy8uLGjVqRBKJhJYtW0ZZWVkklUrp6tWrZGNjQ506daLY2Fhhfj08PMjBwYHOnj1L+/bto9GjR5Ouri5dv36d0tPTqUqVKqSmpiYk8D5cp6mpqULSwtHRkbKzs2n69Onk4uJCdnZ25OvrK2xnt2/fpt69e5O9vX2BL/eR981pbGxMs2fPph9//FFopSO/OElOTqa4uDjy8/Mje3t7Wr58OWloaJCenp6QHJPHmJGRQTVr1hSSaN7e3tSsWTPhtyW/cZGUlESBgYGiVrVEuUmQ06dPk6+vLzk4OIj6tSPKTUo4OjqKfqtpaWk0d+5cUb96RLm/5xkzZpCRkRGdOnWKnj17RgMHDiSJRCIkP96/fy8kOpydnYVtWv7yu0OHDon2K5cvXyZra2uqXr061a5dm5o1a0aNGjXK9/IqeZ+cY8eOFS7Y8vrrr7/o5MmTwnyMHj2aTExMaOLEidSzZ0+qVasWDRw4UPg+OTmZLl26RH5+fqL9g7xPO2VlZdqwYYPowl0mk1FGRobQotbZ2ZkePXpEw4YNoypVqpC+vn6+VknyLmS6detG586dI19fX2rVqpUQx08//UQSiYQaNmwo6hdV/n1KSgrt2LGDvLy8RPu/iRMnkqmpKa1du5auX79OZmZm1LhxY+GGV1paGkVFRZGRkRHVqFFDKLdt2zby9PQkT09P4YbQ8ePHSVVVlYKCgui3336jAwcOkI+Pj2h7kbeWnjJlCo0ZM4ZMTEyoW7duou3s999/J19fX9HyDAkJoSZNmtCaNWsoMzOT/vjjDwoMDKT69evT5s2bSSqV0p07d6h169bk7OwslMt7zH358iV16NCB2rdvL/zuiXJb9PXp00foZ3b//v00ZcoUqlevnmj/PHDgQNLS0qKzZ8/S48eP6Y8//hCOC4aGhjRt2jRhO5Yn3g8fPky1a9cmT09PYZ3+888/1Lp1a1GyJCQkhGrVqkWVK1em7777Lt8b57OysoT+yps3by6s10OHDlG9evWIKDdJo6urK+znU1JSaP/+/ZSRkUHZ2dmimzuzZs2iH374QdhP/PLLLySRSERJkZSUFGrdujV5e3uLfj+9e/cWbjTKy3Xq1En4Pf3777/UunVrcnd3J6lUSqdPn6awsDDhKYG8Tp06RYsWLaLatWuTRCKhwMBA0RMr586dE91U2Lt3L1lYWFDbtm1F05GXOXr0KFlZWZGpqWm+ZLs8Efvrr7+Kfvt5H9m/ceMGeXl5kampqXB8/fAmmlQqpTZt2lDXrl2Fel++fEne3t50/fp1SkhIoOXLl5OhoWG+bi6eP39O69evJ6lUSmPHjqXq1atTSEiI8Bj8wYMHqVq1atS+fXuKiYmhnTt35tu3LFy4kMaPHy8sl82bNwvJbLn3799TmzZtyMfHR1h3qampNGnSJFq7di1JpVI6deoUeXp6kqWlZb7j9ZEjR4SbIhMmTCATExNatmwZLVy4kOrXr08uLi5CkjIxMZHCwsLI0NBQ9ITTzZs3ady4ccK2cvPmTRo8eDCZm5vTpk2bhGV59uxZOnToEEmlUpo8eTKZmprShg0b6PHjx1S9enVq1KiRsI9JS0ujZcuW0TfffCPaj+Xk5NC9e/fI29tbWG/nzp2jypUrU7du3YTkv1QqpdWrV9Py5cspKyuLHj58SA4ODsI+8/fff893w4SIaMWKFTR06NB8XSe1bt1amD/5y0B79OghepnkihUr6Ndff6Xs7GzhZm+3bt0K7HohOTmZYmJiCj3OHjhwgPz9/cnT01O4SZSenk6//PILubq6UuPGjUXLZN++fTR48GDhBWMf3tyIjo6m2bNnk5mZGdna2gpd4shfCrhq1SphPR86dIhUVFSoX79+tG7dOtq3bx95e3uTo6OjcFNGJpNRZGQkjRw5koYPHy6cK8kTuXm5ubkJ3WHcvn1bOGc/cuQIaWpqUlBQkOhcZ+TIkcILDuU3CHNycig7O5siIiKoadOmNHjwYNFvNSUlhS5evEht27YVLU/G5DgJyxhjX9CHj9XJE4ahoaE0cOBAoe+xixcv0tu3b2nRokXk7OxMTZo0oYCAAOHEwN/fn6ZPn043b94kfX19oUVk3gu/M2fO0PLly/P1U7dmzRoyMTERkjLyixl59wNSqVToi7FFixbCNOUvfJC3OJs8eTKpq6sLrR2kUinNnTuXfH19ycXFRZSEePfuHR05coRatmxJVatWpV9++YU8PT2pQ4cOQmxJSUn5XraTkpJCV69eJVtbW3J3d6dRo0bRmDFjKDQ0VNRaSl7uzJkzVKdOHdGFbt6TvyNHjlBoaCiNGjWKlixZQidPnqQWLVpQ+/bthcfVXFxchBP6D1989t1331HLli2pbt26tGPHDho0aBB16NCBsrKy6O7du1StWjXy9PQULrSuXbtGkZGR1KtXL/rll1+EE7Hs7GwaNGiQ0Popb79ecidOnKA+ffpQu3bthGUZGhpKxsbGtGHDBlqwYAF16dKF1NXVhYSlTCajxYsXk6+vL7m5uVFWVhbdvHmTfv/9d1G/vj/++COpq6sLj0Y/e/aMRowYQQMHDhRijI6OppkzZ4rervzo0SOqVasWffPNN8KJ+OrVq2nixIlCjPfv3ydra2uaPXs2RUVFUcOGDcnNzS1fwu/q1avUpEkToWWlTCaj69evk4aGBqmpqeXrS1CeiJ00aZLoceb4+HiytbUVWvXk3SYKeqRb/tbonJwcodVK+/bt843XtGlTsrGxoZMnTwqPpxPlJnyysrLo9OnTpKenRz169MjXwikrK4sePHhA/fr1I3Nzc0pOTqbt27fTmDFjyMHBgZSUlMjNzU24YIqJiaGAgADS1dWlunXrkoeHh9Di9dWrV+Tm5kaurq6iF1nkTWzs2bOHWrZsSe7u7pSVlUVTpkwhIyMjWrp0Ka1Zs0Zo3Su/MLl69Sr17duXjIyMhIS03JkzZ8ja2lpIjh84cIA0NDRErfLPnDlDHTt2pI4dO1JWVhZt27aNlJSUhC4Z5OQXSGfPnqXatWtTvXr1yNPTU9hWpk2bRpaWlkIrWfkL1PL2Yx0dHU29e/cW6iISJ6EPHjxIJiYmoptBRLkt9vP26UaUe0HWpk0bIcF16NAh0tXVFS585fFGRkZSeHi4UM/Dhw+pQYMGosRYXjk5ObRu3TpatWoV7dq1S1g3H154jR8/npSUlGjVqlWi/deHF6hHjhyh2rVrC9vHrl27SENDg9avXy+Mc+jQIWrbtq3QNytRbkI0KCiIbt++TT///DMpKyvne+FaRkYGnTx5ksaNGyeUW7JkCWlra1O9evVErRGlUillZWXR2rVrydbWlmrWrEktW7YUygUHB9N3331H+/bto27dupGbm1u+ri4ePXpEEydOpKFDh4qWZ8OGDYVk1dGjR0lPT0/0qOmzZ8+oV69e1Lx5c2FZyctv376dPD09ycPDQ0iS7Nu3jxwdHalatWrk4uJCgYGBQpyxsbFUp04dIWmxc+fOfC/vOn78OH333XeiFzVNnTqVKleuTCdPnhS1nr927RoFBgZS9erVycjIiBo0aCA6Vs6ePVuYljwpGhMTQx4eHuTh4UELFy6ko0ePkq+vL7Vp04aePHlCNWvWJF9fXzIxMaHjx4+LEv0vX76kTp06ka6uLpmamlKjRo3I1dWVsrKyaMWKFWRgYEAaGhp09OhRIvrveLhp0yays7MjOzs7ql+/PjVp0kR0Y+HQoUNUs2ZNOnbsGC1dupQ6dOhAzZo1E47pGRkZQjch8hsL8r7Cjxw5Qp6enrRt2zZRtwzy7TcoKChfNxDjxo2jKlWq0IoVK4T1lp2dTZMmTSKJRELff/89devWjTw8PKhevXpCnCEhIWRiYkKbNm0S7YtnzpxJBgYG5OXlRX5+ftSiRQuhJfnJkyepatWqZGRkJJyzyFve5/X69WsKCwuj5s2b05MnTygkJIRq1KhB1apVIzU1Nfrxxx+FGzl79+6l2rVri54UyWv8+PFUuXJl6t+/f76bhf379yc9PT3at29fvnITJ04kNzc38vDwIBUVFdLX1xftt5KSkmjbtm3UunVr0XKZM2cONWnShDp37iwcg5KTk4VzvIIegV6xYgVVrlyZrl69KjpfTEtLo6NHj1L9+vWFBGTnzp2FcUaNGkUmJia0ceNGYd39888/NHHiRDIwMBBazLq7u4tu5F64cIEqVapEzZs3F52XXbp0iXx9fcnS0jLf0zVEuS0T69atKyyHvXv3ko6ODlWvXp3q1q0rJI8fPnxIv/76q7DP3bt3L1WpUoXs7OxE07137x4NGTKEqlevLmrtK5PJ6M8//yRnZ2dh3Zw6dUrUv61MJqO3b9/SzJkzqW/fvqLzuBkzZlCbNm2oc+fOor5Nz549S5UrV6bu3btTu3bt6LfffhMt7xs3bpC9vb1o3uQ3MZKTk0UvRct7Xrx06VIKDAykjh07ilpDy1+E2bNnTzp37pzoxWSZmZkUHh5OEydOpEaNGtGQIUOEpx3kx54zZ85Q586dhXW+e/du0RMtRLn72FatWpGnp6fwhM+hQ4coLCxMtExu3rxJTZo0IX19faEFaN4X2OV1/vx5srS0pPXr19Mvv/xCpqamdPny5Xz9Qe/cuZN8fHzIyMiIWrZsSZ06dRJdY4wdO5bMzMzoxx9/pAEDBpCBgYHohZWpqal08eJF8vX1FW5UT5o0iXx9fWn37t3Csf/w4cP5ErFEuTcx5POwbNky4XpJnoj9sEXsoUOH6JtvviEfH598N2QZI+IkLGOMfXHyk574+HiqU6eO6NHkkydPUkBAALVv317UUX/eROq4cePI1NRUOIkaMGAA6erqCskZotw71H5+fgW+9GPs2LFCyz95R/fyk82UlBRKT0+nhIQE2rZtm3DRkp2dTf3796dJkyYRUe5Jo66urtBiNC0tjd6/f0/Xr1+nVatWkVQqpRMnTtDWrVvp8OHDotYf48aNo1atWpGvry9JJBKaOnVqvuRjVFQUxcbGCi0uUlJSaPLkyRQQEECqqqokkUhE/ZYR5Z7kHT58mGrUqJHvcd0P5T0ZOn78ODVv3pwCAgLo+PHj1K1bN+FRqLdv31JaWhplZGRQ8+bNadGiRZSenk49evQgCwsLUlVVFT0OLk/Eenl5CRdh06ZNo44dOwpJQXnd8rfQfigjI0NIvjx48EBYNs+fPycHBwdRoiIjI4OGDx9OGhoaQoLtzz//FNbdhAkTyNHRkUxNTcnLy4u+/fZboeyoUaNIQ0NDSCy9e/dOiPGvv/4iiURCEokkX39+jx49IktLS/L19RX1lUmU2ypw5MiRNGzYMGH8GzdukLe3N/n5+Qkv38obf95p0/+x959RUW1btzB8ShRQcs4550yRlZxFURQVRMwoKEpQUEEFMSu6zYqKEXMCsxgxAiZUEMWIiFkyFFX9+1Hfmrsm5T73POc+9/3FaO20sy1q1VprxjH76KMP8CUoGPZzz0OAh4cH/vWvf1Hpp5cuXYKSkpJQKjRAByWYAwtT4OTXr1/o6upCVFQU9PT0cPDgQcrpBgA9PT14e3tj4MCBePjwIZKTkyEnJ0fS9xggNjY2lhT5ECw4VF9fDysrK+Tl5UFUVBQ7duzA9evXcenSJairq8PHx4diQj979gw/fvwggE9paSlqa2vB4XDw+/dvREREQF5enip419jYiPv37+PWrVvo7u7Gp0+fYGFhQRg/jA0bNgx6enoE3Ll9+zaWLFkidDA4ffo0bGxsAPDBLkGGW0tLCy5cuAAej4fnz5+Tg1d9fT2qqqqwZcsWyMrKknVC0Do7O6mDDIfDQUxMDFgsFjQ1NbFgwQJcvXoVR44cgZOTEwFmmXYRPOQJWnV1NRwdHZGUlERYRwBfVkReXp7SqGtra4O1tTWuXr2K4uJi6uDb1dWF9evXw9bWlpLJ6O7uxsOHD6lCg4LjVfAgLLiOFRYWIiMjA9nZ2VQl+5SUFJLKLgjECtr+/fvh4uLyj33AvNODBw/IPS9evAhTU1MqlT0nJwciIiIUS2zGjBkEjGTWowcPHuDu3btISkoCm83G6tWrqefhcDj48eMHqqqqyP2uXLkCRUVFAuLfuXMHw4YNg5eXFzXPjx07htraWuoQ/vjxY+jo6ACAkJ7k79+/sX37dhJ0Y+bw0qVLib410y4MqMmALV+/fiUyKILj7OjRo2RM9yxu1dzcTMDLZ8+eEeb7hw8f4OLiQvS6GWPmy5cvX/DixQscOHAAd+/eJe2yZMkSyMjIICkpCdbW1lBUVCSAyu3bt5GYmEiCLR4eHuTwb2VlBXV1ddKeTU1NePXqFbZt20bAzKtXr6KkpAQ3btwgz3H27FkoKChAWVkZubm5QtIK9+/fR1FRERYvXowjR46Q644dO4bExESqr8vKyjBy5Eiw2WwiuXHixAnk5OSAw+Fg06ZNhAna2dkJQ0NDsFgsKtOhvb0dwcHBFFsT4ANbWlpaFBAnaIcPH0ZcXBzGjRuHvLw8Ms9v3rwJPT29fwysnjx5Erm5uZg+fTo2bdpErnv27BlSUlIgISFBaWQLXsv4Nz9+/ICioiKGDx8OJSUllJaW4s2bNzhw4AAsLCwQGxuL169fg8Ph4OTJk5CQkCC68T1/My0tDba2tli8eDHFjAP48jk919uCggJISEjg9u3baGxsxJ07dzB48GBISUkRZuXbt28RHR2NMWPGUEzro0ePQl1dHfr6+tRawgCxampqGDVqFPmcx+Nh8uTJpEiXoDyJ4HdevXqF79+/k/7btWsXNDQ0qLWFkWzhcrk4f/48IiIiMHnyZOTm5lJr9bt37xAREQEWi4Vz585R7/7gwQMEBwdDVlZWaNyWlJQQaY/i4mISVLxw4QKkpaXh6uoqlEbPSPSMGDGCCkowVlNTAyMjI/Tp04diK9fW1sLExITcS3A9am5uxp49e9Da2kppNjNtdvToUbKHMT45853bt29DVVUV8vLykJOTw+nTp8l69u3bNxgZGWHGjBmQkZGh/LqHDx/Cy8uL2ruY39y8eTMkJCSgo6MjVHzr7NmzpFAmE3TvWdhzzZo1sLOzw7Rp0yifqbq6Gm/evAGXy0VNTQ3MzMwwfPhwIaYyU4DVz8+PjIc/AawHDhyAg4MDTExMiJ8ouB48f/6c/DsxMRF+fn6YMGECJk6c+I+/2d7ejoaGBvz8+ZMaY5cuXYKenh7Z14qKijBgwABSKwLgr2NRUVEIDg5GV1cXMjIyoKSkhOLiYqGASUlJCQYMGICpU6cKtV99fT0iIiJgbGxMQHtBIHbatGmkAOjNmzf/MSDba73WC8L2Wq/1Wq/9f2Bz5swRKpZTVVUFFRUVISba5cuXISMjg8uXLwP428GvrKyEl5cXZGVlkZCQQFIM379/j6FDh6Jv377IzMxEWloafH19YWlpKQQqAXxGxpw5c3D69GnK2eTxeNiyZQtWrlxJOQyMEzFu3Djs2bMH58+fp67r7u5GQUEBpaOampoKFRUVWFhYoG/fvggMDKRAoYsXL2LRokUknZCxtLQ0qKurw9DQENra2rCzsyMHeoZtmpGRQaqzMsY4bAcOHICioiJJcRYsQnbu3DmUlJRQBybGwbp+/Trc3d0REBAAFosFCQkJmJiYQE9PD+rq6ujfvz/k5eXJtYwWrY2NDY4ePUrd58WLF9DW1kZgYCAaGhooAIlJi+LxeEhOToaZmRlevnxJOaf19fVCeqlcLhcNDQ1QUlIirFfmQPDz5084OTlRFVgBPktGQUEBN2/eRGtrK5KTk8FisajDLKO3Kgh4Mc/y+PFjyMvLw8fHh4DagkDsgAEDEBsbSwqg/P79G6NHj4aCggL8/f0haI8ePYKPjw/CwsII+1bwQNPU1EQ5u4WFhVBXV0dycjI52JSXl2P27Nk4ffo0NT6vXr0KXV1dofYC+M54zwI0Y8eOhbm5OblfZ2cnkVM4fPiwUOG6kpIShISEQE9PD/Ly8qQtmHkhCMS2tLTg4sWLFDPW0NAQERERcHd3p373+fPnUFVVhZeXF1kDelaKNzIyQlFREQFl6+vrSSGNBw8eICwsDI6OjhQg8ObNG2hoaBBmsCBIaGhoSFWl7qkVCvAPoQEBAQSsEmS4nT17FpMnTyapxN+/f0drayt57s+fP2Pt2rWQlZWl9FgzMzOpdU4wsDBp0iSMHTsWs2bNQlhYGHx9fREVFYWMjAzy7IJM8QMHDmD58uVIS0sja+ChQ4dgbGyMmJgYHDhwAGVlZbC1tYWjoyO4XC6VWjhkyBBERkZCTk6Oere6ujoEBgZSsguMff78GQYGBhQ7mxmDJ06coJhVwN+F3qKiomBhYQEzMzNKY48pridYKEzQDh06hMjISJw5c4ZaawF+AGzGjBkUG7ywsBBJSUlEF1awP3Nzc8FisTB58mS4urrCxMSEPDsTOGC+X1dXh6lTp4LNZiM/P5/8xtKlSylm5qZNm5CXl4dly5ZRz3337l1ERUXBxcUFS5cuRUhICLS1tSkJBYA/55iiJlJSUhRb99mzZ9DR0YGioiKZi42NjUhJSYG4uDjVZwwQ6+3tTUCcP1VkLy0txdChQ7F3716h4i6XL1/GpEmTKB1uLpeLz58/Q1NTkwS3egLvPbWRmfabNGkSNdbHjh0LVVVVCsz98uUL2aOAv/dLSUlJ1NTU4MmTJ5gxYwZMTEwgKysLdXX1PwaZBKU21q9fDw0NDcyfP/+PzyZoz58/h5ubm9A8BfhAbHR0NFxdXYVYm6Wlpejbty/5/OHDh9DV1YWfnx8OHDiAvXv3ws/Pj0phF2Tl2tjY/DFo8U9ABaNdr6+vTwVwBAGaP+m4Mr/37t07pKSkQEtLiwKbuVwuAQSZ7zJpwz3Zo8XFxdDQ0MCyZcvw4MEDtLa2EhA8Pz8fw4cPR3JyMiV5kJycDHt7eyxevJikOv/p+QA+C1YwIwjgg66+vr5QUlIiDH/B9xcET4uLiyEtLY2xY8dSv9HU1IT169dT2qVcLhceHh5CwCzAD1D1DKoy12RnZxOZmOrqavz111+wtLSEuro6pdn/T+/47t07hISEQFlZmQqUAfzgzZAhQygdasY+fvyI1tZWeHl5Ed3XX79+wc7ODmJiYhg5ciT1DoxVVlYiPDwcpqamJMOJsdDQUIiKiqKwsJCMxY6ODlhZWWHcuHFCGsPPnz+Hh4cHLl++TNqx5zg8e/YsWCwWEhISyLzm8Xjgcrm4du0aQkJCMGLECMjJyeHUqVNk3c3IyIC0tDRVpKyjowNhYWEIDQ39R+Bu//79UFFRQWJiolC7HT9+HDExMeByuVi+fDkGDhyIESNGUBkOa9euhYODAyZMmICrV6/Cy8sL9vb2AICdO3eCw+GgoKAA3t7eGDlypBCpwcXFBdra2khKShIKaggGvo8cOQJPT08MGTKEAMY8Hg8xMTGIjIwk7TdixAhERkbCycmJaHELZjJ1dnbiwYMHaGpqwtKlSwmpg7lXQUEBPD09AfCDSz2DbIcOHQKPxyNByzt37kBfX5+wrFtaWvDq1SscPHiQyLIxfdpzjwP4+9y4ceNgYWFBMrwYVrSbmxvGjBlD+bN/KobXa73WC8L2Wq/1Wq/9P7afP38iNjYWLi4ulLD8o0ePoKKiQkA1QYfLysqKMBAZS09Ph4yMDEJDQ2FiYoKBAweSw39XVxfy8vIwcOBABAQEYOrUqVShr/LyclK8Y+PGjbC2toaUlBTFJv3x4weCg4OpavOPHj0ijlBqairk5OQgJSVFpah/+/YNPj4+WLp0KQA+IKCiooI7d+6gvb0djx49QmRkJHx9fYVSVe/fv0/eu7CwEIqKirh58yba2tpw8+ZNTJw4EVpaWkIMivPnz/8xtaerqwuGhobw8/OjPm9tbUVwcDAljr9s2TKMHz+egAvXrl2Dq6sr3NzckJGRgerqajx58gTnz58nrCyAzwSYOnUqbt68icjISLi4uGDv3r1U/7148QL9+vXDzJkzyWenT5+GqqoqKYjEFMPw8PDA/fv38e3bN9TX1yMkJASenp5/fL+hQ4fCy8uLMGwYR3XUqFHQ1dWFl5cXAL5TOWzYMALKlpSUUGnXgqyZtWvXkmdnxgxz7/LycgwYMABRUVGEbcaMh4aGBkRERFC6ilVVVRg7diyUlJQoFgLAB3UdHBwwfPhwKrWXkbBwc3NDaGgoVZRCQ0MDycnJBIBgnO5t27YR7cLfv38TrT5BZgxTZEwQoFyxYgW0tbVhYmKCvXv3kgOMIBDbE1QH+Dq6LBYLLi4ulOYa41zfuHEDcnJycHBwgLu7OzmIMVpmCQkJYLPZpP0YkO/kyZMQExODv78/VXV80aJFUFFRQWlpqRBb8sePHxgyZAhYLBZ0dHRgYGBAimMwZmpqiri4OKotAH5xqlmzZlHPDvCDFwwjt7m5GVpaWmCxWBQ4xhQ6GjVqFHg8HlauXAkvLy+4urpi+PDh5ED75csX5OfnQ1JSEsOGDYOfnx/09fXJmMrNzcXSpUsJgLp69WokJyejpqYGDx48gIuLC2Fh95QYmD17NhQVFeHv7w8DAwNoamoSduTx48cxZMgQiIqKwsbGhkgz7Ny5E56enmTOnDp1CiwWC8HBwaRtf/z4gZCQEHh5eZHnzMvLI2nZv3//xtChQzFo0CCKQcUUjYqNjSWfXb58Gerq6qQ/GWaniYkJlZmQkJAAT09PCqRimDwfPnyAlJQUWCwWxWJl+iAuLo4CHpisAkGpAMH+3b59O0JDQxEfH0/+vnLlSgwePBgeHh5YtGgRWQfr6uqQkJAABwcHxMfHIzQ0FKqqqlTBPVdXV7BYLALoCx68y8vLMW3aNNjZ2RHWEQCsW7cOixcvJhXCGVa5IADBFAIyMjLCwIEDSZ/v3r0b79+/R1ZWltC+deTIEfj6+sLKyoqa/0VFReRA/fbtW6iqqoLFYlEFqZj2HD16tBCQ8+nTJ6irq5M9Q3A9ZgIgjI4hwF+vREREYGZmRjEGAT4Qq6amhv379+PXr19UCnB8fDxUVFRw9+5dBAQEQFFREdLS0pg2bRpJeVVVVaWeG+CD/2ZmZhRgtHLlSmhoaGDhwoUElA4PDxfS3Qb488DT0xOmpqYkkMbY7du34efnR1hpzPu3tbUhLi4OCQkJaG9vB4fDwZMnT+Du7g5TU1O4uLhgzJgxf0y/PXDgAOTl5Qmzjtm7uFwuTp48KcSEFHxPERERwgbumcUiWEj04MGDWLFiBTIyMgjY19DQgLS0NJiYmGDt2rUA+EHx+Ph40ucnT57Ev/71LwwcOJCAQExhKIAvvSQvLw95eXkCti5atAgKCgoYO3Ys3N3dYWxsTPXFrFmz4OzsjNTUVCG5GkHLzs6GhoYGJS8D8IuJMuugYObD9evXcfDgQdy4cYMEDk6ePAlJSUlKV5fL5VIBMkbDMiUlBR4eHqiqqqLG/MuXL+Hr6/tHIHbLli0wMTFBbGwsrKysMHLkSCxYsAC5ubno27cvamtrSVCVyZK4ceMGrly5QtbYL1++wN/fHyoqKhQQy+Vyyd7x6tUrPH/+nJKxeP78OdTV1UnGWENDA0aOHIlLly6Rft+3bx9WrFiBmTNn4vnz5+ByuXj8+DFGjhwJKysrlJaWUu+alJREJHYYQJTRChcskNne3o7Q0FAEBQVR/t2VK1dw8OBBHD58mLAojx8/TgrsMft/Txans7MzTE1NCXD34sULREVFwcDAADNmzMC8efPg7e1NESgY6Y9Dhw5Re8Hu3buF/CPBNX/NmjWQl5dHZmYmwsLCYGpqSgVgN27cCHd3d6ioqEBUVBSPHj0i9QIYyY8dO3bAy8sL0dHRZH5+/foVcXFxOHjwINUm+fn5GDJkCEJCQpCamkr+dujQIXh7e2Po0KEEiGUK0HK5XDx58gSysrK4f/8+cnJyoKGhIbRe1dbWIi4uDjt37oSBgQEiIiIoH/LEiRMYM2YMDh06JBRkGzp0KLS0tKigZUVFBczMzHDr1i08fvwYM2fOhIGBAfT19SEtLU2yCu/cuUPeo6c/fufOHcTGxgoBsXPnzsWkSZN6gdde+z9aLwjba73Wa732/4E1NDRgxowZYLPZBKwEgGnTpkFGRoYCdn7+/AkrKyuqyvBff/0FbW1tkvp+6NAhsFgsODk5oaCggDiYPVOiORwOMjMzYW1tjSNHjoDH45FCWSoqKjh37hwaGxtRW1uLoKAgqrDIggULYGFhQVJpeTweQkNDoaKigrdv36KxsRFr1qyBv78/2Gw2caRTUlJIyqJgSrqXlxdhg+3cuZN6Rg6Hg9TUVAwbNoxqtxcvXmDkyJEYPnw4WltbSbVxwXaJiYnBokWLiJN+4cIFaGpqwsnJCcePH8fevXtJwSnBAmNqamrYtGkTdfhjGLFDhw4lbKb29nYkJCRg4MCBCA4OhpSUFCls8OPHD1JhuScQ++bNG+K4PXjwAJcuXUJMTAysra0JGM2kjhsZGUFZWRkODg6ws7Mjh9gXL15QBdPOnDkDV1dXxMfHk8NNZ2cnBg8ejLKyMurA5ebmhtOnT/8x7Xrjxo1CDNGVK1ciOjoa3t7eyMnJIVIA9+/fR//+/TFixAihg3JiYqJQxejq6mqMGTMGHh4eQpWyq6qqqN/IzMyEsrIytm/fjgsXLkBJSQmOjo6EPbRnzx5ISEjAwMCAgESvX78mbCsmXa+yshLy8vIYNGgQ1qxZg8LCQvj4+AgV2FFSUkJOTg5mz54NAwMDTJs2jRxwOzs7ERwcDE1NTcKeYcbbkSNHsHPnTkRERMDPzw9X//+F8ATH4uXLlxEQEEBYaK9evcLNmzdRV1eH0tJSsFgsIYmAM2fOwNnZGWw2m1xXX18Pe3t78t2GhgbcvXsXGRkZFGt9//792L59OzgcDtauXYsZM2YQxkpRURF0dXWFKrWz2WxkZ2dTzz1nzhzo6uoiJyeHAJV3796FqqoqwsPDcfToURw6dIgqWJSRkQEVFRVs2rQJBw8ehJ6eHpydnclB58ePHzh69ChCQkIwfvx4CpRZuXIlDA0NER4ejl27dqGtrQ2WlpZUAY/c3FxER0dTB58zZ85ATU0Njx49Ip+npKRQEh0tLS2oq6tDXV0dGdvbt2+Ho6MjwsPDyYF5+/btEBERga+vL7y8vODp6UkVW2lpacGYMWPAYrFI4ZTa2lq4ubmBzWYjLi6OVNIWHGMA/3BsYGBAMWF+/fqFlStXwsnJiWI0Mv2QlpYGTU1N5OXlkWc8e/YspKWlMWXKFJw/fx7nzp0TKhol2I9xcXFQUVGhZA7+xPoH+OufoqIi1q1bh/nz58PJyQkhISEk0PLu3TssWbIEwcHBlPYe83u3bt1CYGAglJSUyLgVBGLb2tooje+UlBQoKipi7969ZP7X1tYiJCQE9vb2iI+Px/z584meZHl5Ofr160eqZzOH9/r6esyfP18IiN2zZw+mT59OxsXcuXOhrq6OVatWEQDszp07EBcXR2xsLPbt24dTp04JsTY/fvyIzs5OAoCsWrUKffr0ofQZOzo6YG9vD1VVVSGmWnh4OKkw3/Nv8fHx6NOnDxVQPHnyJCZNmkTA/p8/f2Lv3r24du0aac/Ozk64u7sLFWCsra1FVFQUvL29KdBh1apV0NHRQVhYGFxdXaGmpkZ+q6OjgwowlZSUwM/Pjyryw9jTp0/B5XJJNXrGtm3bBllZWWocc7lcNDY24vfv3//Ian3w4AHMzMwwb948iqnb0dEBLy8vyi8SvPb79+9wc3PD4MGDqb2jo6ODqjrOaJZ6eXnBwsKCsPi7urrw8eNHpKenw9zcHIsXL8bnz59Jmzx58gQ8Hg91dXVYsmQJ+vfvTzJWmHfZsGEDbG1tCehSVFSEjIwMsv/U1NRg9uzZ0NDQoPoiPj4e48ePJ2Dzn+zevXuwtbVFVlYWJdt06dIlTJgwAUuXLqX8Fn19fVKgytnZmQBWp0+fJqxKwXvdu3ePCsI/fvwYcnJyGDlyJG7fvg0Oh0MyLASDUI2NjWTufPjwAXl5efDx8cGWLVtI+9y8eRPu7u5oaGggc/3o0aNQVlaGhYUFWCwWfH19iZZ1Y2MjAgICoKmpSaWjA3xGsJOTExQVFREYGIgZM2YA4K9bbDYbgYGBuHDhAvz8/ODn50cVMFRTU8P48ePh7u4OPT09ErC4ffs2oqOjYWtrK5QFNXXqVEpn+927d4iLi4Oenh5iYmKQnJyMgQMHUhq8XC4XaWlpMDIygrW1Nby9vaGiokICC6dPn4aIiAhmzpxJaRcnJycjMDAQfn5+UFRUhJKSEgHuqqursWbNGlhbWyMyMhLJyclUqn16ejqMjIzg4OAAe3t7aGlpEd9s9+7d0NTUREpKCiXddOvWLeTl5ZFsmC9fvmD16tXQ0dEhQViAP24fP35MMqmkpKSEAp87duzAoEGDYG9vj7y8PAwaNAg+Pj4Uu5rRQk5LS0NSUhIUFRXh4uJC/JH9+/fDz88PXl5e1HNu2bIFampqxHevqKiAv78//P39SWbTp0+fEB4eDjc3N3R0dGDfvn1EPoyZL/fv34e0tDQphMpYW1sb/P39MW7cOPB4POK3v3jxgsyf/v37Y8qUKSgqKsLLly9haWmJXbt2UWNl48aNGD16NOLi4kgghxlfsbGxsLS0JNkBgrrTvUBsr/076wVhe63Xeq3X/h+bIHMwMTERbDab0tlkiivNmTMHOTk5CAgIoADDtrY2LFq0iKSHHjt2DLKysli2bBn8/PxgYGCAHTt2CG34PB4Pubm5UFZWxqVLlyh9spaWFri4uMDCwgISEhJwdXUlhT4APvNDSUkJly5dIs47wE8VdXR0hIqKChQUFCAuLg5VVVVywO/u7kZ6ejpx0gQPH4cOHYKoqCj2798PFouF1NRU6nmzsrJgb28vVDl88+bNUFJSQmNjI+W0L1q0iBwmzMzM4OHhQfRNnz17Bm9vbxgaGsLGxgaRkZHk3S5dugRNTU0qZVQw9enatWvw9PSEp6cn0WQDAA0NDUhISFBsZoAPsDBO4r59+6iKxwDfAdfS0sLXr1/x4MEDUpmeAWI5HA6Ki4tRUFCAkydPkkNQamoqjIyMIC4ujtGjR5PD1rZt2+Dk5AQdHR2MHTsWtra2sLS0RHd3N44fP47Hjx+jq6sL0dHR8PPzE0q7fv/+PYKCgig285w5cyAvL4/FixdjxIgR8PDwgIWFBQEoHzx4AElJSfj6+lJss1OnTsHY2Bi/f/+mDs5VVVWIiYmBm5sbVUxI0F6/fg07OzsihVBcXAwZGRkq9bq1tRVDhw6FqKgodXi4dOkSoqKiYGtrSw7Cb968QXBwMKytreHk5IQRI0aQPj9w4AD09fVJEOP27dtgsVgwMDDAhAkTiH5aR0cHkpOTSR98/vyZAi3OnDmDkJAQ+Pn5UbIOR48epdLKq6qqYGNjgwULFhBAec6cORATE8OePXtI4GHevHlYsGABBZA1NDTAyckJa9euxenTpxETEwNnZ2fY2NjA0NAQixYtAkADcKtXr4aysjIWLFiAz58/o62tDatXr4aqqiphd3l4eMDMzIzqpyVLlkBBQQEPHjwQKoRx//59ODk5wcDAAGw2G9HR0ejq6sK5c+dgbW1N2HPM4V9ZWRnGxsYU40RwHggGUB49eoR58+ZBTk4O06dPx7p166CmpkbAbUA4RbmgoAAWFhb4/v079Q5Tp06Fnp4eurq6qPs9ePCA6BoePHgQrq6uCAkJIevg1atXkZubi5SUFGzdulVIc/bbt29ISEhAv379iD7m27dvsWjRInh4eCAgIACTJk2iNBoBPhhvaGj4R1BLRERESKfwr7/+gqKiIioqKqhUbWZdMDAwIIVymCKAAD/w8PTpU0pTePjw4bCwsMC+ffvIeOzJ4CkqKoKpqSlZ20pKSiAmJgZTU1N4e3sTgIypbM/02devXykQ7MmTJ3B1dYWBgQFh5DHPJjg2jx8/Di0tLYrdxPy9uroaq1evhouLC4YPH45Zs2aR+RYYGAgWi4URI0ZQ/c0AsdLS0tS6xhhTTKu8vJy0ATMurl+/DkdHR2hpacHNzY0qPJSVlQUbGxvY29sjKysLjY2N4HA4RLJl9OjRiI2NJcAMA9ReuHCB0mb09/eHmpoarly5ItT2OTk55LNZs2ZBTU0NMjIycHR0JPOasfb2drx+/RphYWGws7P7Y2bEmzdvEB0dDU9PT2rd3L17N2bPno2EhATSditWrEBQUBB8fHwwadIkArAVFxfD398fISEhQgy03bt3w9XVFUVFRdQa5efnh8jISCHZDsE07R07dmDRokVURk9OTg6MjY0xadIkFBcX48KFC/D394etrS15zk2bNmHy5MnIzMwkYN/+/fvh5eUFFxcXnDx5EoWFhQgMDCQFdk6dOgVlZWU8fvyYjJ/U1FQoKSkRGYja2lpMmTKF0qo9cuQILC0tyV7Y1dWF4OBgqKmp4eHDh/j16xdaW1vh7++P4cOH4969e4iNjYWZmRmMjY0pIPr169eYPXs2NDU1qQwCQYYoACKnsm/fPuIfZWRkwNXVFTNmzMCbN2/w6tUrhIWFUSzxzZs3U4VRFy1aBDExMQLm8Xg8nD59GiwWC3l5eQD+3te1tbWhoqJC1tfy8nIYGxsTSYGewd8FCxbA1dUVurq6+Ouvv8iaLqjh3t7ejrCwMAQGBpL59eDBA8jJyWHbtm1EimnYsGEYOHAg6YcPHz7A1dUVxsbG5H7MPnT16lW8f/8eEyZMAIvFQnl5ObhcLg4fPgxHR0cYGBjAx8eHXHf48GFoamoS5uLFixfBYrGIhAjA38f8/PxItoJggdJp06ZBTEyMSGm9e/cOO3fuJJINc+bMofaFrVu3QklJiay5mzZtAovFojS/T548CRaLhTVr1gDgZ3jJyMigsrISX758wdevXzF48GDIysri1KlTFBlB0Lq7u8n9GGb93r17wWKxKOmLnTt3QkREhADPpaWlUFNTg6qqKlWv4OvXr1i9ejV0dXWJ783ck5Gs0dLSQmVlpdCznDt3DuPGjYO9vT3lV3G5XFRVVUFXV5cEKwG+38Rk6zG2Y8cOIfmCrq4umJiYwNramrzj+fPnERkZif79+8PY2BhmZmZwcHAge2NXVxf27NkDV1dXhIeHE/+KIabMmTMHxcXFKC0tha+vL1kj9u/fDzExMbLvVVRUoKioCJcuXSLjur29Hfb29iQ7EeDPIVVVVaSkpGDmzJnQ0dEhsj8AP7gXFxdHsvgY+1Phvl7rNUHrBWF7rdd6rdf+H1lP3SiAf4BMTEyEs7MzpTWUk5MDHx8feHp6IjY2ljg5O3fuRE1NDZ4/f47Gxka8fPkSpqamJBpbVlYGKSkpmJub48SJE1QEtrGxEc7OzhTYBvydmtzZ2Yny8nIUFRXh3r17xDl6//49nJychAqSCFpYWBgyMzMxatQouLi4IDU1lRzSGCdU0JEB+I6ckpIStm3bRoBVweqlBw8ehK6uLvbu3UsYvQD/4Gxra0sBAOXl5Zg+fTpxeh49eoT4+HjY2dlRz/3+/XuqwASHw8HevXthb2+Pzs7OP2rMAfyD9dSpU8HlctHV1YUHDx6AxWKBzWbD29tbqEr679+/MWTIEBgaGlLOKAPkCGqulpeXCwGxAA1YHTp0CAYGBjhx4gQ5KPr7+5ND1JMnTzBnzhyMHTsWM2fORFdXF16/fg0ZGRny/nfv3oWkpCTc3Nzw/ft3dHd349u3bwgJCYGHhwd516dPn8LExIR6xps3b2LIkCFwdnYmoMzdu3fh7u5O9cOzZ88gJiZGDss9gVjmPQ8cOCCkp3bnzh2oqakB+LsYhqCOF8No+PXrF7Zs2QIFBQXK+b1y5QoiIyNha2tLANGOjg78/v1bqM+Li4sJ0/LUqVOQlZXFrl27sGXLFoiJiWHy5MkU4A7wQRkLCwuw2WxKJ7C4uBhhYWHw9PTEjh07EBwcDBMTE9KeDLgxefJksNls5Obmorm5GS0tLZg3bx769OkDKysrWFtbQ1JS8o/pn/Hx8bC2toaIiAjS0tJw5coVdHV1YciQIRg1ahQ5NGRlZRFNvvz8fKirqyMzMxPfvn0Dh8PBrVu3EBkZiTFjxmDGjBlUah0jP8JImrx9+xbnzp1DZGQkcnNz0dTUhI6ODtTX1+PHjx+k/4qLi5GTkwOAz9ZUVFTExo0bUVlZCRkZGbi6uqKhoUGISZKcnAx/f3+cOXOGsD0ZsNrNzQ3S0tKIj4+ngkU8Ho+0z9atW6GpqUkOYwzA1tDQAElJSaKhDYCw/w8dOoTu7m50d3dj3759cHV1RWhoKLk/oynJ2NevXylt0Pb2dkycOJECYhkTBOcFx/2rV69gYmKC8ePHU0VN3r17B0tLS0p2AgAmTJggVChH8Jl+/fqFN2/eoL6+nozpjIwMWFpawsjICBoaGlSAYtiwYbCyssL+/fuFiooA/EBCcnIyAD6ArqCggI0bN2Lv3r2Qk5NDcHAw6urqqH0rOzsbAwcOhJSUFGJiYoisSXl5OXx8fGBsbIyPHz9i+/btQkVO1qxZA1dXV0pW4//EEPr06RPi4uKwYcMGiIqKYsqUKdTv1tfXIysrSwgA+f37N0JCQkja7vv370nAZs2aNfj16xfa2trw+fNnfPv2jbzj7t27oaioiN27dyM+Ph4eHh4YNmwYSSs+duwYhg8fjlGjRiEtLY2A05WVlRATE0NSUhKVseDt7Q0NDQ0KiBVsz/v378PV1RXl5eV49uwZ5s6dCwcHBypdeN++fRg0aBAVHD1w4ACRKGCsrq4O0dHRcHBwoDIPBMckw1TLzs7GnDlzoKOjAwsLCwIenzhxAsHBwXBycqLS1A8dOoSZM2dCXFwcERERBFDdvXs3/P39iSatIMgI8OeflJQU/P39ISUlBVdXV8Ky3rBhAwHYHRwc4O/vT95v0aJFkJCQQGxsLGRkZODh4UHmHdOPUlJSsLe3pwIS27Ztg4ODA5qbm6n3TkhIgJqaGvEnBBmbb968wdevXxEWFgYfHx8SLHzz5g2GDh0KMTExmJubw9zcHFZWVujq6kJraytev36NuLg49OvXjxp7AB+ITUtLg4iICNGyFwxEZ2Zmon///vD09CQBhvfv36O7uxu5ubmE+W1kZETuyWjeTpkyBXPnzgXA97EEC6O2tLSQIPXNmzfB4XBI1fkbN27g6tWrmDhxIsTExIgc0tu3b3Hx4kWsXLmSFPIE+GCvsrIyNm/ejClTpkBDQ4Ma3y0tLTh48CB8fX1ha2tLAXJbt26Fvb09Ojo6SDu/evUKgwcPRnBwMPns48ePxK/4+fMnQkJCCHB67tw5SElJCckZdXZ2EtkDZnxv2LCBZE/t37+fCsw0NTWRjAiG1b1o0SIMGjSImkPTp08nQOw/rUuCgROGeX3ixAmqqO3v37/R3NwMLpeLGzdukHG4ZMkSeHl5UfIWABAcHAwtLS2cPn36Hws0pqWlkTl35MgRSq9WkKxQXFxMnrGmpgYpKSmQlJQkOrqMffv2DWvXroW4uDiVSVBZWYmamhq4u7tDX1+fKijV8/qewdHy8nKoqKgQ1iszHl69egVZWVmqTgFjOTk5ZK3jcDiwtLSEqakpYeF+/foV58+fx4YNG3DkyBGhAGlnZycJEIWGhhIgtqCgAMbGxlBSUgKbzUZ4eDiVUeDj4wNNTU0hX6+jowMfP35ESEgInJycyDvu3bsXRkZGJDh16NAh9O/fn6xRjF27dg2LFy/+Y5v1Wq/9k/WCsL3Wa73Wa/8PTNCZa2pqIhpIAN8BZYBYhrEA8J04QTba8uXLISIigpqaGkpfydbWlqQ6nTlzBsOHD8eCBQuEotc/f/6EgoIC0c4UfKa2tjYqXUrwuZ89ewZJSUmqgrbgdcOHD4eWlhb5d05ODuzt7TF79mwCkKSnp0NUVBTbtm3Ds2fP8OnTJygrK0NCQgI8Hg8tLS3YtGkTFBUVKQAhLi6OFHt4/PgxPnz4gICAAPj5+ZHnOHbsGGxtbWFra0uxdJ88eYLx48cLHUZ79klhYSEUFBTIIaCnNt379++pd2au6+joQEtLC0lh7nkY/vnzJ9LS0ogjtnPnTvTt2xdWVlYU+wLgR+HHjRsHKysrIUD38uXLSE9Pp9KqXrx4ATc3N/j5+VFMOsHnZCQdjI2NSbuUlJRAXFwcLi4usLW1haysLHR1dan08Lt370JCQoJiTfB4PJw/fx5WVlYkNb+pqQna2trQ1taGrq4uIiIiMH36dBgYGGDXrl1ClaABfurj5MmTKY1EBqRuamqCn58f0tPTqcMMwO/LwMBAArL//PkTmzZtgoKCAklTBP4GYu3s7Ai4JdgmzH9/+fIFnz9/xpcvX8Bms4mOaEdHB3R1daGiokLSYXk8Hnbu3AlFRUVs2rQJaWlp0NXVpYqNXbhwATExMTAxMUFAQABpz5s3byIoKIh8LykpiaTxMUBAWVkZ1q5di7Vr1xLw+vz58ygqKsK+ffvIeHv27Blh+DDm6uoKZWVl2NjYIDExEWJiYhSIu3btWqirq2PevHlUISVBE2Ru2tnZISoqCqWlpRg8eDBcXV2JrmpaWhoJQvz48YMCWt69e4f29nYMGjQICxYsIH3k5OQEFouFqKgocr/09HSoqqoiIyMDU6dOhby8PJKTk4mmW3t7O9asWQMTExP4+PjgxIkTRJdx5syZCAwMJJq32traGDp0KPU+T58+hbGxMTnA/RP7nwFimVRGQaAeABYuXAg2mw15eXkEBQVh165dpNDIpEmTICYmRtI7Ba/bsmULUlNTMWXKFHJYu3HjBmRlZTFy5Ehs27YNN27cgIaGBmRkZKiDWmdnJ2xsbCjGG/PbHR0dqK6uFmLUMNqFt27dQnNzM2FqCh4smSrvFy5cQGdnp1B2wadPn/D792+4ubmRPailpQUWFhZQVlamgg4LFy6EkpISjh07hsePH4PNZsPU1JSwAO/duwcfHx+Ii4tjyJAhQkBGeno6nJycqH4A+OtqcXEx0XD8JyspKYGoqCimTp1KAbHv37/Htm3bqH2vubkZ+vr6mDJlClkb3Nzc4O3tDQUFBaEiVAB/Ls+ZM4eSCtm1axc8PT0xdOhQAsoLAkuC71FQUABtbW0kJycTnWMA8PHxgY6OjlAadFFREYYPH0618Y8fP7Bo0SI4ODgQDetXr15h3759lBavvb09CWQI2sePH6GnpwdbW1uytjFWW1sLAwMD6pqWlhY4OjrC1taWfHbgwAHMmjULXC6XsM0FgZaUlBTo6+uTMSMqKiqUzQLwWXDh4eGEUffp0yeYmprC1taWKmr48uVLfPr0iZIsio6OJgz7Hz9+wNfXFx4eHoTtCfDBQ6b6+IsXLwgYp6CgQNqKCdC8fv0aSkpKuHHjBg4dOkQCVkx6OMAfRxEREfD09KTGwNGjR5GQkICEhAR0d3cjMTERHh4eAPgFyaKjo2FkZEQ9G8DXVt2wYYMQIFNTUwN/f38yTysrK6GsrIwhQ4YQgLqjowPnzp2jQDAmkDJx4kTs3LkTFy5cECqMumvXLuzcuZNcs3btWixfvpwC4drb25GUlARRUVECEPe0Bw8eIDk5mQKXd+zYAVNTUyQmJqKmpga/fv3C4sWLqaAes/9t374dZmZmZN0V1JZnsVhUsJ+x5uZmmJub49atW0LSSZ2dnVi/fj2VdQL87ZNlZGQgOjoa9+/fFyoiuX37dixYsIAELOfNmwdFRUWcP39eSFZp+vTp6N+/vxABoKeNGTMGWVlZQs/J5XKxadMmrFq1irTFihUr0NLSgqVLlxJ/mekHgA82s1gsiImJUQxKQYuIiEB6ejouXrxIvR+Px8Py5cspCQ/g7729vr4eKSkp0NPTI4xcxhoaGlBUVET6pqf+PZvNhr6+PlXodNGiRWhvbyd+JeMfNjU14evXr5CVlaWKVnZ3d+Pnz5+wtLSk/FjG8vPzYWZmRoJAHA4HVlZWMDMzw4MHD/4IZnZ3d2PJkiUkANjZ2YnCwkK4uLggLCyMALEfP35EXV0dCVquXr2a6Px2dnYiKCgI6urqxN/lcDhYtWoVAgIC4OLiQvnGf/31FxYuXAiAH7CUk5PD2rVrsWHDBvTp04ciBQg+Z6/12n9ivSBsr/Var/Xa/7IJOpmrVq1CWFgY2Gw2FixYQJhRDBDLVJHuaRUVFVi/fj1hLTC/uWvXLpibm6O4uBhfv35FeHg4FixYQDE5ExMTMXnyZHR1dUFPT48CORkHoaysDOvXrxc6nAP8w4+5uTny8vIo1gHAP3BqaWkRYI55vuzsbLDZbMyePZs4dYsWLYKkpCTU1dVhYGAASUlJwtI8f/48Xr58SYA1wQJWU6dOhY2NDcTExGBtbQ1HR0eKbXHhwgUEBgZCUlKS3J+xJ0+ekGJePZlrjD169AjGxsbIysqigCpGm45hKPN4PNTX11NsNoAPYDD6VoJArGC/t7a2orq6GsHBwRAVFSWav4Ige0VFBQYPHkwcRC6Xi/fv30NWVpakVQladXU13NzcEBwcLATcMr9bUVEBFxcXSsPwxYsXWL9+PdLS0jB27FhyQGX69PXr17C1tSX6oox1d3dDS0uLkl948eIFnj59inXr1iEzMxPe3t7o378/qeA9dOhQpKamoqioCGVlZeByuTh9+jQiIiLw6tUrUuCKAYGio6MhJiZG9X9bWxuCg4MRFhZGObTfvn3D5s2bIS8vLwTERkVFQUNDgypg0tjYKFTVt6qqCgYGBgTIrqurQ3x8PHbu3En6r6SkBDt37sThw4dJ2168eBFqampUwbfv379TjE8Oh4OqqiqwWCyKjT1z5kzY29sjNzf3j0B1SkoKVFRUYG1tDTExMbi5ueH48eNkTv/+/RvPnz9HUFAQLC0tce/ePcjJyaF///4kUCIohbB27VpoampiwYIFfyzYIWjHjx+HiYkJpKSkkJGRQZjW8+bNg6enJ2bMmAEDAwOoqalhzJgxpE0A/rjR0dEhem7fv3/HqFGjSAVigM9e09XVJQDp3bt3wWKxiL4lM964XC7evXuHjo4ObNu2DVJSUnB2doa0tDQFbJ09exZqamoICAjAjRs3cO3aNYSFhcHFxQXd3d34+vXrH9n/ggzgoqIiGBgYUAXbFi9eDAUFBRQUFOD48eMIDQ2Fq6srlixZAi6Xi5aWFiQkJIDFYlEyA6mpqZCVlUVISAhcXV0hKipKmEtlZWUktdnKygoeHh6E8SRYqGfu3Lnw8PAQKub07NkzREZGorq6mhpjUVFRhL18/PhxyMrKUpq4jI0ePRrz58+HpaUl7OzsMHv2bOrZnz59SklAvH37FsOGDcOxY8eIrt379+/h7OxM1tLr16+jf//+Qu1bVlaGxMREsvZfu3aNsEivX78OFotFpcsD/H0mMjKSAr4OHz6MdevWITc3F3V1deR9zp49C1FRUSQkJBAgtqfUheBvKCsrQ1ZWFnPnziVByKSkJCo4APC1E62srKCkpCRUNHLXrl0YOHAgIiMj8e7dO6HAqqAVFBSQIjmC49Xa2hpDhgyhrouJiYGKiopQ8cgfP35g8eLFcHR0JFkYAH8fEtQW9/f3R1BQENEgZGz48OEQFxfH4MGDKbD40aNHUFJSIoFApo8+f/4MZWVlbNiwgfr+8uXL4e/vD0dHR0RERFBSLd+/f8fEiRMRGRkJFotFQEnG1q5dC3Nzc/j7+xP9RYC/dpuamsLe3h41NTVCgYXNmzfDwcEBbDabYqIL7rWHDx/G2bNnMXXqVAD8/mQKv3379g3m5uaIjIykfpdZ7+/du4e8vDywWCwEBARAUlKSCnAxQKyXlxdJTQeA2NhYsFgshIWFQU5OjtpfKioqSKZHz75gTLDIX0BAACIjI6k5yrAIIyMjCav48uXLpO8XLFhA1pOMjAxISUlBUlKSmn/fv3+Hr68v+V5LSwuCg4PBYrEwfvx4AHRgZ8aMGRgwYAC1lgP8wFH//v2pbBrGCgoKYGpqiqSkJLx580bIT2CMWd8FATmAD0Cbm5tThezOnDmDuro6tLW1ITw8HCNHjoScnBy1Trx+/RqhoaGUv5OTk0MyMZ4+fQpFRUWiw8wYU+AvISGBFAqzsrIS8gkF/bHp06cTDfB/2i9XrVoFOzs7SElJUeDit2/fEBQURFiyW7duBYvFwqNHj/Dhwwfo6elRRdOY9k5LS0NGRoYQEMpYQUEB2Gw2xMXFKYCZYQ8zAOGmTZtIpklxcTG+f/+Or1+/ChWkE3yv9evXY9y4cfD09MTJkyep+eri4gJ9fX2sXr0aAQEB0NXVxbVr1+Du7o7bt29j1qxZkJKSwocPH8DlcpGeng5HR0dqLe/s7IStrS1VrI6x8vJyWFtbU+OMw+HA2toa1tbWfwSl29vbSR8x1wkCsYLSBIK2adMmsNlswuRmivRqaGgQILa8vBx5eXlkLB8+fBi/f/8mWtFfvnyBra0t8YWfP38OFRUVsFgszJ8//49912u99n+yXhC213qt13rt/5FlZGSQVN3FixeDzWbD39+fsN8+fvyIGTNmQF9fn3L8y8rKSIS8J9vy48ePRKtLQ0MDtra2xIHj8XgoKyuDtbU1rl69Ch6PhyVLlsDa2poSk+dwOAgMDMTw4cOJc97a2koYAO3t7YiJiQGbzaYOpl1dXQgJCYGysjKsrKyQkpICFouFb9++oaWlBQsWLCDVgBn2QUVFBUpLS3Hq1CnY2NggMDAQcXFxEBcXx69fv/Dr168/Mhyrqqpw6dIlKp1T0PG/desWgoOD4enpSVUrZ+6Zm5tLMZXmzZuH8ePHkwP5ihUrYGJigqlTp+L8+fO4dOkSAgICKG26xYsXw9raGrq6urCzs0N5eTkBUT59+gR/f394e3ujsLAQpaWlJO1q8uTJmDJlCrhcLqqrq0mKF6OlKvgeL168II4xw5C4d+8eTE1N4enpKaQrWV1dDSMjIwKsnzp1SojxGBkZCVdXV/w7y8vLow5KkZGRpIowY79+/YKjo+M/aroCfODAzc0NMTExOHnyJObOnQtHR0cYGxtDQ0MDjY2NuHfvHrS0tGBqagp5eXlKP/HNmzdwdHSEu7s7pk+fjhUrVsDLy4ukYr569QpPnz4lB9eOjo4/ArFnz55FRkYG6fOFCxfCyckJysrK8PX1xdatW9Hc3IzHjx/DzMwMWVlZOH/+PEJDQxEeHk5plUpKSqJfv37U3ONwOLh48SI0NDQIg0rQmMrTAB90HTlyJKWNOnPmTLDZbGRkZFBVfffu3QsVFRVUVFSgqakJnz9/RlBQEAYNGkQOjLt374aHhwdJ23306BEMDQ1hYmICNptNACFBfcZ169ahT58+2Lp1K3XwKisrw8mTJ/HkyRPy/ZaWFgqs5vF4MDU1hZSUFBITE5GdnY0lS5ZAX18fmpqaWL16NfmepaUl3N3dcerUKXh7e8PT05Pcr7u7m3wO8Jl2gmye5uZmVFRUCB1AORwO/Pz8wGKxMGrUKOpvnZ2duH37NhwcHKCurg5jY2N4e3uTw/SbN2+gpKT0R/Z/e3s7vnz5Ai6Xi4sXLxKgsaGhQWic//79GykpKXBwcCAsrC9fvmDlypWknxsaGhAXF0cxyJcvXw45OTmiz/fz5098/vyZSu/fvn075OXlCUh58eJFGBoaYvLkyYQFWF9fDx0dHUhKSlLM0aamJqirq6OkpARXr14VKrg3f/58XLlyBbt374a+vj7i4uIwadIkJCYmQlRUFDY2NuQA+/nzZzg7O2PMmDG4cuUKdHV1YWBgQAJzjKSNra0tmpubSfotc7+2tjbs3bsXb9++pfqwrKwMGhoayMzMJHMgIyMD/fr1w9KlS1FVVYWKigoEBwfD1taWvN/s2bOhpKQELy8vqKmpwcjICOvXryeBi/Pnz2PAgAGIjo6mDttHjx7F8uXL8ddffxFg7cuXL1TwjMvlws/PT4i5yeFwsGzZMujo6PzxEF9YWAhzc3NkZGSQz5YtWwYvLy9ERkZSAMOOHTuINARz4GcyLARBx/fv3yMpKQkaGhpC+uI/f/5EamoqKSQD8FnnX79+JftzZWUlvL29ERQURFiYnZ2diI+PR2xsLAnIMHOitbUVKioqFCuyu7sbzc3NsLe3x6pVq8jnmZmZUFRUxL59+3Dy5EmYm5tDQ0MDP3/+pObSmzdvUFRUJFQgrrKyEoaGhpCVlSUFeJjrvn//DktLS2hrawsxEZ89ewYrKytISkoKgeENDQ0IDAyEmZkZJk+eDFNTUzg7O0NGRobcg8Ph4MCBA7C1tYW/vz8ePnyIGzduEK125hkcHBzAYrEwb9488mzMO3z48AERERHQ09NDVlYWub+ZmRn69u1L5GwE7d9ltAjamTNnwGKxoKqqSp6ZabOKigqoq6vDx8cH5eXl0NLSgrOzMxITEyEhIUEBl0OHDoWioiJqa2vR0NCADx8+IDAwEM7OzpRf8e7dO8THx0NKSoowbwWBWEbbuKetXLkSkpKSmDx5spBfsXPnTsjKymL16tXkt549e4ZLly7h+vXrZO6sWrUKffv2xdq1a/Hhwwc0NTUhMzMTenp6RA7iyZMnkJGRIQG8w4cPg8ViITw8nPhBDNA4cOBACujNy8uDhYUFXr9+ja6uLqxYsQLa2tqYP38+6uvr4e/vD2dnZ6IFCvD9RVlZWaHMEgCUFMDKlSuptay0tBS3bt0igYhv377BxcUFmpqauHr1Kn78+IHXr18TKQ8Oh4NLly5h8eLFZBx3dXVhx44dsLCwwIgRI/DmzRs8evQIQUFBSEhIoPbL69evo7S0lMyPuro6eHt7w9LSEqdOnUJHRwdqamoQHBwMR0dHUrirZ6YJE9Suq6tDeno6zMzMqPk/d+5cqKioICUlBUlJSZCVlUV2djY5mwB8n9DX15cEOq5du4bBgwdDR0cH8vLylM/w9OlTxMfHw9DQENOnT8fatWvh4+MDCwuLf2Tczpw5E9ra2pQ/xOFwoKKigpiYGCH5Kqb9MzIywGKxyH7NALHu7u5wc3MTkuCpqqqCtrY25e+2tbUhJCQEmpqauH37NsrKykiwMTk5GWJiYtQaVVZWBgMDA7KnVFdXY/To0bhw4UIv87XX/mvrBWF7rdd6rdf+F6xnUZsjR45QxU/OnTtHNMY8PDxQW1sLgO8sC0ZgX716ha6uLuTn52PAgAHIzMwEQLNh6uvrcebMGUrHi8Ph4MiRIxg1ahQSExPJc7x58wZJSUkwNDREcHAwJk2aBFdXV6ri66JFi+Dt7Q0bGxuSxv/161f4+/vD3t4ew4YNw7x580ghr3fv3kFaWhr9+/enKqm2trYSIDYlJYU404Lp/GJiYpCUlKSA0x8/fhAgltEqFLwO4INj9+7doxy/y5cvY/DgwfD29qYqTgtaSkoKlJWVkZqaivDwcBgYGJDINRPlZ7FYJM2TaZN58+ZBTU0N+/fvx/v372FtbQ0bGxuUlJRQWpS2traYNGkSAYRDQ0MhIyNDHZxevnwJNpsNIyMjArz0lI4oKCjAtGnTCMuLcfpGjBhBFd4B+GOmu7sbDx48gI2NDaSkpJCfn0/YA3V1dTA2NqYYJT2ZR9OmTYO4uDgBEbhcLtzc3GBhYYGEhASsW7cOvr6+VIE4xhjwiumfrKwsBAcHU9/h8XhobGwk35k6dSpERETg7+8vJM3w6tUrzJ07F87OzggLC0NiYiI4HA4yMzNhaGgIFRUVKCsrY/ny5aivr0d3dzc2b94MRUVFarwwtnDhQigrK+P48eP4/v07HBwcYG5uTg6/ixYtgrGxMXR1deHm5kYVE/r16xd27doFDQ0NIdZcd3c3Ll++jH/961+YNWsWadOeTv+RI0egoKAg1G8TJkyAt7c3VW18wYIF8Pf3B5fLpYqBsdlsREREkOdiQEOAP8++ffuG27dvw97eHo6OjgSgEezn06dPC+lCampqwsjICGpqapg1axbF7GpqakJpaSmpar13714K2C0vL0dkZCTU1NQIE+vatWtwcHCAhYUF/Pz8qFQ+gM8mtLOzw8WLFyEtLU2xhw4fPoxJkyaROcFYR0cHli9fjuzsbKioqCAhIYHqA8Zqa2uFNAK7urqEKkALsv/z8/Op4lfd3d1oaWmBqakpAYeZ73d1dcHU1PSPY6ygoAAyMjKwtLTEq1evhGQNpKSkKKkUxrhcLp4/fw4HBweYmJiQdz969CicnZ2hr69PigkyBbmCgoKotTAlJQWhoaEYMGAApZvY0NCAoKAgxMTEQFxcHAcOHKAYm0+ePIGxsTGsrKwIE3z9+vWkUJWKigocHR2Rl5dHABUGDE5ISICcnBzVf4xkiKCWNPP3zMxMODk5kYrvHR0dWLduHWRkZKCmpgYTExMMGjSIjJejR49CTU0Njx49Ip9NnjyZSMsw4/jUqVMYOHCgUGV0NpsNGxsb9OnTh6SrAvwxfeXKFYSGhsLCwkIINGT6e/ny5XB2dsa0adOEskNKSkrImPjrr78gJydHNNzZbDbF4mekCeLj4ykQ+O3bt/jy5QsBlD9+/IiEhASw2WwKBGWemXm+zMxMGBgYwMjICDY2NqStnzx5gqCgIDg4OCAkJAReXl6wsbEh7ZKbm4tNmzaR/l+4cCHs7e0JYxrgzxcHBwcSMGACYkwA4/Tp05CVlSV92nMP6Zklw1hVVRXU1dURFBRE9jPB4m6jRo36I3Dx6tUrWFlZEZa7oH38+BEzZ85Ee3s7CdAwGSSMtbW14cyZM3BxcYG0tLTQGOvo6EBSUhJh0zHSBDwejwBEJSUlkJOTI3IoXV1dCA8PR1hYGCQlJVFUVCRUjKyiogKhoaFURougMe9+5coViIiIYMKECYR1KKiPHhYWBi6Xizdv3kBCQgIDBgwg/iNzT0a3U1FREZqamnBycgKbzSbvKLi21dfXIzIyErKyskSyRhCIZZ6zs7OTum7JkiVQV1dHbm6ukGRVcXEx6e8jR45AQ0MDOjo60NHRgYaGBtnz1q5dC1FRUejp6cHCwgKqqqqUrwjwQT5PT09y7y1btqBPnz4ICAgg9RGsra2F9pQ7d+7AysqKBEnr6uqwatUqwn5XVlamJIK6u7tx79496OrqEjkZwX46evQo0ZBmjMPhYM6cOZCWloaenh6UlZUJyN7Y2Ahra2tYWFgQDXRXV1d0dXXh1q1b0NbWhoyMDFUb4Pfv3zh06BDMzc0hLS1NCi0Knhvmzp0LKSkp6OnpQUZGhmR5vXjxAl5eXjAxMYGcnBycnJyI3/JPmSaCmVAfPnzAlClTEB0dDR6Ph3379kFPT49kXjBSEUpKSkhLS6N8bCZoybRJWloaWCwWnJychCQiampqsGHDBpiZmcHHx4cU8gT4+8z8+fMpUsGHDx/AZrPJ+sLMQUbDnbGemWjfvn3DnDlzhBixmzdvxuTJk4WCXgDf19fQ0CDnLoC/Xjg7O2Pw4MGoqKhAdHQ0NDU1IScnRzKImOeorq6GkpISMjIy8PLlSwQFBVEkll4gttf+G+sFYXut13qt1/4vbeDAgZS2K8DXmetZ/GTz5s04dOgQ5OXl4evri2fPnuHChQtITExEa2srpk2bBn19fbS2tqKlpQUrVqwAi8WiBPQFN3vGAejq6sKnT58QHh4OeXl5Ic3Ez58/48SJEwgLC8Po0aORkpJCVUxWVVXFwoULMXHiRPTp04ewfn7+/IlVq1YhODgYoaGhBBwrKiqCsrIydHV1YW9vTx3CWltbkZWVBTc3N0yaNIlyMs+dO4e+fftCXl4eYWFhePPmDfkbA8QqKytj4sSJQkU+LC0tIS0tDX9/fwJMA3wgNiIiAn5+fkLSBCUlJdDV1SXOZklJCfr27UulTDG6ch8+fCD3vHbtGhwdHUmhnwsXLkBaWhqmpqZQUlJCSUkJAd6+fftGGGpmZmZgsVhUNWjGXr58CRcXF5iamlJpX4wlJyfDwcEBc+fOJQfXmzdvwsDAACNHjqRSvBnjcDhobW1Fbm4u3N3doaenh+TkZNy+fRtjx44lYPyzZ88II23OnDmoqalBY2Mj5s+fTzETuVwu0tLSEBAQAFdXV8TExJAD0vv37/HixQsCqDDfB/iFVjQ0NKiDXE9H+MSJEzh48CCMjIwwbNgwcljr6Swz43vlypVQVFTE6dOn8fDhQ2RnZ8PU1BSzZ88mzGsm5S8/P5/81ufPn+Hq6koOaKWlpZCQkKD0ZgH+gV+QhdzZ2UnJNBQWFkJeXp6kczKWm5tLsazv3LmD8PBwFBUVUe/CVIQWBGi5XC5hQzPPm5ycDDc3N/IZ07alpaXo378/SVEF+AeBuro6wtDo7OzElStX4ODgAGdnZwLExsXFUemq3d3dWLp0KdTV1cnBaebMmZCWlkZcXBwBYq9cuQJPT0/861//IvqRPQMplZWVcHR0hLe3NwHqurq6KKan4HrQ0tICW1tbsFgsKp2yo6MDYWFhiI2N/ccqwh0dHdi+fTuUlZUpIBbgA6rMdZ8/f8bnz5/x9etXAHwQwdLS8o/s/6ioKHJdSUkJPn36hKamJjg6OhIQRTDgNX78eMTFxQk92/nz5+Hj4wMJCQnCHmLGT2NjI1RVVXHmzJk/prXyeDy8evUKTk5OMDAwIEDskydPcPHiRSxZsoRo9pWVlUFTUxMBAQHk+r1790JdXR0hISEE6P3y5QtCQkJgbGwMFotFWFiCgDLAZywpKCiQAAPDdmXmQnJyMuzt7bFkyRLSv0xxLMG50NraitDQUPj7+5N7MJXCmTGbkZEBW1tbZGVlkTXt7du3uHfvHrWecTgcbNy4EXZ2dmhqaqLGz6hRo2BtbS3UhgBfikFRURH3798nRQdzcnIgIiJCUq1v3LiByMhIwuYC+EWN1qxZg6KiIjL2ORwOlixZAhcXlz8CsQB/X5gzZw5hqDc1NSEnJwcODg4UK3/9+vUYPHgweb/s7GxYW1vDwMAAZmZmZJ/69OkTEhIS4OLiQnQbBedCUVER5OXlcfDgQezZswexsbHo168fmdvV1dVYvXo1oqKiMG3aNEqyZ9q0aWCxWCQ74+3bt0hISICBgQHGjBkDW1tbmJiYUMD0w4cPoaioiI6ODiHNy9bWVmzcuJFiSTNWV1eH2tpaaq9//PgxVFRUqCJ4TIEpxp49e4a7d++iubmZrHvPnz+HhYUFgoODCRArWGz09+/fyMrKQkpKCmxsbDB9+vQ/jo2qqiq8fPnyj0Axh8Mh0gSCvhXAD3A2NTWBy+Xi6NGjFCA1duzYPwKxv3//xtevX4Xe79KlS9i7dy8OHDhA5nhJSQlEREQwefJkCogVvK6qqgqqqqpQV1enQEpBO378OPbu3UuCcxs3bkR0dDTCw8MpdnZDQwOGDh0KeXl5wgIV9CHz8/MREREBf39/TJw4kXyem5sLTU3NPwKxAH/fk5KSwvbt2/H27Vs8fPgQI0aMgKysLPG3KisrcezYMRw8eJBiFTJg27lz5+Do6EjY/wB/D1q4cCFmzpyJTZs2kX7r2QaTJk2CoaEhWXO5XC5+/fqF27dvk8Dc5s2bSXFYHo8HOzs7uLi4UH5nR0cHwsPDMWPGDGruPX/+HPb29njw4AFu375NQD8m6PXr1y/cvHkThYWFuHXrFmnTt2/fYuHChZCXl6d0vgXt5s2bKC8vp/R0q6qqYG9vj7KyMjx58gQpKSno27cvmb+NjY2orKzE7t27cfv2bXK/48eP/2OmSVNTE8rLy8Hlcint5X379hFW6MmTJyEjI4P9+/dj/fr16NOnD+bPn0+Y/D0lUc6dO4eDBw9i2LBhFPmhZw0FwTF2/PhxBAUFISQkBDIyMsjIyCB+yJQpU+Dr60u+yxSiA/jj9OLFi2CxWBR4DvD3O0YeiFlPmWKJubm5SE1Npa55+fIl3NzcyNopWOCLud/ixYvRp08f2NnZUTrPjBzRsmXLoKioCG1tbTg5OVHB+17rtf/GekHYXuu1Xuu1/0u7du0accoFnf3GxkY0NzfDw8ODAHPt7e2wsbGBmpoaJk+ejOXLl8PKygqOjo5QUFAgbD2Af6hftmwZWCzWH8XtGWOcgYcPH2LMmDFQUlKi2ED/ZE+fPkVubi7FIt2zZw/69OlDqvAyJuhUPX36FO/fv8fTp09JwY2eeqjJycmYNGkS5aA0NDSgpaUFnz59goqKCoKCgijn/OfPn1i5ciVVRTcnJwfKysq4fPkyPn/+jLi4OMjIyFBFTa5cuQIPDw8hkfzCwkL4+PgA4B9oezqo9+7dA4fDoZ69q6sL9fX15HuXL1+m2tPCwgI2NjY4evQo6XMGhAoPD8egQYPg4+NDVYRl3uXly5fQ19fHiBEjhPqCx+MhKysLzs7OSEtLI2zJsrIyGBsbw8fHhzjGly9fxpEjR8gBA+CzAo8dOwZ9fX2Eh4dDTU0N//rXv1BUVAQlJSWsXbuWOK2MHEB9fT3RmRMEYpn3YZ7hyJEjMDIygqamJjQ1NTF+/HiKQVldXQ1DQ8M/6o+uX78e2dnZhJF1584dGBoaYtiwYVQaN8No4PF46OjoQEBAABYtWkS10YYNG6Curk7e++vXr0S/krHv37/DxsYGra2tKCkpEQISduzYIaTvuHz5cowaNQpGRkZYuXIlea7CwkKoqalRh6nJkyeT9uvu7kZJSQni4uIgKiqKyMhIAqacO3cOgwYNIkCC4CHyxIkThN1x+/btP2ronT9/HpaWluSgvnDhQlhZWcHAwAAWFhbkkMDhcFBaWgpHR0coKSnB09MT2traVOpffX09IiIiSPDh9OnTkJGRQWxsLDQ1NTFmzBjU1NSgtbUVYWFhMDAwwL59+yi9VkHbt28f+vbtS8aA4BzfunUrpkyZgvz8fMIGP3r0KCwsLBAYGIh79+7hyJEjRN/2T8xEQWtqasKOHTugoqKCCRMm4Nu3bwgICCCsHqbataamJoYNG4bDhw+jra3t37L/uVwuamtrwWKxSEXu69evQ0xMDHPnziVMbw6HA2dnZ6Snpws9V3d3N27evAlLS0uYmJhQxVzevn0LTU1NSn+wtLQUR48exeXLl8m8YpiHgkDsn+7DALGCGqKrVq2CsbExrK2tMXDgQDg7O8PW1hYODg7Q19fHrVu3SJv2ZOts2rQJAwYMoLRLBft6xowZcHBwQG5uLn7//o22tjYkJycTjcn4+HiSIsvsPUwKbs+CPxkZGbCzs8OCBQuoAARj69evR0NDA1atWgUDAwPyrAy4UldXhwEDBlCgO2MbN24kmqSCf0tLS4OGhgY+f/6MtrY2PHv2jIzh1NRUaGlpwcXFBe7u7vD09CTsUgacc3d3x+jRo6kAyvnz52FhYQFtbW1q3fr58ydycnLg6OhIMWKZ52G0ho8cOYL9+/dj+vTp6NOnD2Gfvnv3DtOnT4e+vj7RSQb4cyYzM1No3587dy769etHpVULssvy8vLIfp6SkoJ+/foR4OjTp08oLCyEra0tNDQ00K9fP8KY6+7uRmNjI8LCwpCVlQVJSUkKzHv06BGGDh1KdL4ZW7hwIUxNTaGrqwtdXV2UlpaS9O7Hjx9DTU0N4eHh+Pr1K9VH8+bNg7GxMeTl5WFra4t169aROfD8+XNYWloiLCxMCHxh7Pfv31i5ciUsLS0pIJZJdRcESYuLi1FUVETJjbS1tWHp0qUQERHB6tWrybtHR0cD4AdXJSUlER0dTRW8i4uLg7S0NPbs2YN3794hNDSUZCwAf6+VaWlpMDIygp2dHfz8/KCgoICamhoA/KBu3759kZCQgI8fP1LtWVlZiW/fvqG9vZ3sq25ubkIgpOD6PmfOHGhoaGDGjBlYtGgRWCwWFi9eTNqgoaEBw4cPB4vFopiAc+fOhaqqKlauXImDBw+iT58+CA0NJb+9ZMkS6OjoID09ncreAPh7o6enJ/UcHR0dGDZsGPT19akUc8YEs4gA/n5sZWUlFOjsaWvWrMHixYspJm1dXR0cHR1JcJXD4VB+QHNzM8LCwmBkZERAuvfv30NPTw82NjZYtGgR1q9fD29vb1hYWFDv0d7ejoqKCqSkpJDPmpqaMH/+fLBYLMKa7bkvMvdvbGxETk4OdHR0KBkTwXsIAo3t7e2oqqoiBS4Zy8zMRN++fSmpMsa6urrQ3d2NHTt2/NtMk5iYGDKvduzYgU+fPpH/1dfXw8HBgTDxv3//DiUlJYiKimLz5s1CPtK8efNI/127dg0RERHw9vamGL979+6lxkpOTg709fWJruqhQ4dgb28PGxsbjB8/nswFpk0F14jjx4/j1KlTGD9+PJSUlMg6zXyHAWhZLBaVWZefn4+BAwdCT08PMTExpB4Dk1n1pz7gcrkoLS3FyZMnMWbMGLi7u1P+NcAPKL99+5ZaA3tmAfRar/1PrBeE7bVe67Ve+y/tyZMnFPsjLy+PKnwE8FN01NTUyGHi/fv3GDlyJI4fP0428sGDB4PFYiEmJkbI2W1vb8fy5cvRr18/If04gJ/ua2trS0Cux48fY/To0XB3d6cOHT3lEm7dugUWiwUpKSmhg/OePXsgIiKC+fPnCzGCeqZx3r17F2ZmZkJArGAl6T8BLDU1NQSIff/+PflcMBWzsrISTk5OhJF66dIlDBgwAMOHD4e+vj516GUi/sxzAfxD+tChQ3Hjxg2hQgpFRUVCh4tx48aRqDyTSh8REYGUlBQCDoaGhkJCQkIo/Z6xxsZGDB48WKjABwBSXZZ5vvv371OHKx6Ph/nz54PNZmPOnDkkdbW0tBQjRowgBRCMjIxga2sLKysrGBsbC6WPFRYWIiIiAkZGRoThxRRyYlJNmTZmgFhpaWmSqlpZWQlTU1NUVlaSQjxr1qzBw4cPkZ+fj4CAAAwaNIiAbG1tbZCQkBDSxEtNTYWamhq2bNlCPWNZWRmMjIwQERGBgoIChIWFQUFBgbBnOzo64OrqSopOCB6oR48eDRcXFwAgoC/ABwZfvHiB7u5uWFpaYsiQIZCRkaEYsLW1tRg0aBBVJTwjIwNKSkrYvHkz8vPzYWhoiICAAPz+/RvNzc3Ys2cPNDQ04ODgQBX+KC0txf79+0lfVlRUYNKkSTAxMYGLiwu2bt0KFRUVoUDEnDlzoK2tjQULFhCwYtmyZRAVFUVeXh5ev36Nuro6hISEwNfXF1wuF1lZWVBWVsbZs2fx5MkTDB06FCwWi4CqTKXxRYsWYf78+VQa5t27d/Ht2zdcvnwZP378wP3796GpqUlA39TUVMjJyWHw4MGora1FTU0NJk6cCDabTclZCLK8njx5AjExMVy/fp16t+zsbEhLS2PIkCFQUlJCaGgoAYROnToFNpsNeXl5ODo6IioqSijN9J+sqakJ+/btg4KCAvT09GBvb4+uri5kZWVBQUEBZ86cwbVr1xASEgJxcXF8//4dnz59wokTJ0iacGpqKjkwMf+fmJgId3d3wiY9ePAg+vXrBy8vL4SHh8PT0xNmZmbk+6dPn8bWrVuxY8cOMvaY1FgDAwMcOHAAR44cQWhoKKV1mpqaChUVFZibm6Nv374IDg4m4G9dXR3YbDZhyP9pzWSAWA0NDYo1dPHiRWzYsAFz5sxBQUEBOBwOPnz4AFdXV3h6ehLJAeb3mN8sLi6GqKgoFUgBaJCAAWLz8vLION23bx/CwsIwduxYZGdnk3a5evUqtLS0ICsrS9ZqwTnLSBPMnDmTKky3ceNGAgx9+vQJioqKQuyx8vJymJiYCEmYAPzUf2lpaQIyMOPz2rVrUFVVpbSnAX6KtLa2Nqn6vWLFCoiKisLMzIysCRwOB3PnziVprYy9f/+eSDIIFnQD+Ky4JUuWQFtbm7CveTwempqa4OHhQdLeGWMCqwwD8M2bN1i5ciUZL48fP4aVlRXExcXJPBXsG29vb6IZ++LFC1hYWGDMmDFISkqCiIgIJYUza9Yswp4VnGdv375FcnIypKWlCRDb2dmJIUOGCBWFZArZhIaGUr+RnZ0NNTU1HDt2DD9+/ICXlxcBkxkf6MmTJ2CxWJQWb05ODtTU1HD27FnweDyEhYVBV1eXAuqfP38OJSUlAoStXr0aY8aMwahRowgA/f37d6xatQrW1taYNGkSfv78CX9/f0qmYO7cudDR0SHAc1BQEAlstbe3Y+3atWCxWDA3NydBhTlz5qCiogLXr1+HgYEBYmNjKSB24sSJkJeXh4mJCWxsbIR8K4a9z2R7bNmyBSwWi9IYP3fuHFgsFikCCvw9T06ePIn29nbweDxUVFTA0NAQnp6eJNATHx9Psj8OHDgAfX193L17FwANTM2YMYOMm48fPyIjI4PM2adPn8Lc3Jz4A2fPnoWkpCQlV8HlcpGamoqIiAghsGnNmjWQkZER8rlu3LgBbW1tIemBO3fuQF9fH2pqali7di0JHJw9exbm5uZCqe2ClpCQAB8fH8jKymLx4sXk2rFjxyI0NBQAfzwLZtF8/vwZDx8+xPjx42Fubk6A2ObmZowaNQru7u5wdXXF2LFjqX1o4cKF8PPzg42NDQYNGkT5v83NzViwYAH69etH+ZKFhYVYsGABpk2bRtaWX79+IScnB6ampkR/mGlTQcvOzoafnx+0tLQwcOBAoSypefPmUbJRAH8dY/zP1tZW2Nvb/zHThCkUWVtbi+TkZCgpKeHt27fkO4w+PiNjVVtbi6SkJOzatYua50xQa/Xq1dT1V69exZAhQ+Dm5oZ169YhJCQEBgYG5B1fvXqFKVOmCJ0vPn36hIsXLxIZI2asCrZNTk4O9PT0UF1djZqaGsTHx0NOTo7a0x49eoTJkyejsLBQaHx++vQJly9fhr29PZycnDB48GCUlpZCU1MT+fn5QvrW7969I774kydPMGLECHh4eFDF67Zv307J+/RKEPTa/631grC91mu91mv/hWVnZ0NERIQqHHX06FH06dMHSUlJZEOvr6+Hu7s7RowYgbNnzyIgIACBgYHgcrno7Owk6fupqamETcM4OoIFmzIzM+Hu7k4dznk8Hoks+/r6EgehoqICo0ePhoeHBwUc9TTmALJ48eI/st1YLJZQGndP4/F4uHv3LszNzeHg4PCPemiCxnynpqYGqqqqCA0NFdJ9Yq7btGkTvn37hmvXrkFFRQXbt29Hd3c3goKCICYmJqQvJ3j/d+/eQUZGhqrGDvDbMzg4GOPHjyf3qampgZeXF65cuUK+19TUBDs7O3IQ5nK5GDt2LN68eUPus3PnTsyePRsxMTEkGs8wD319fbF9+3Z0dnZi4MCB1OH91KlTMDY2xurVqynAgsPhICkpCUpKSlRhG6YtFBUVCRNr165dVKpWz7YW1G5TUFCAiooK1qxZI5ReWF9fj8zMTJLa379/fyKlMWfOHAwfPpz6/rlz5+Dj44PExES0t7fj58+fGDZsGMWy2blzJ1RVVSldVB6PR1Kcy8vL4eXlBUdHR/j4+AildsXHx0NXV5ccIpm/Z2dnIywsDOXl5dDR0cHBgweRmpoKSUlJAvTu378fampqGDx4MLl3W1sbQkND4efnR8ZLeXk5zMzMyMHp1q1b6NevHwWeM/rMioqKcHFxIelsMTExUFNTw759+8i8a25uRn19PWJiYhAWFgYWiwVpaWn8+vULPB4PK1euhIKCAsrLy6nD3Y8fP7Bx40ZIS0tDQ0MDhoaGcHZ2RldXF+7duwdPT09yWD5z5gxkZWXh6+srNK4Bmt0xe/ZsaGtro76+nrD6MjMzMWzYMNKuixcvhqurK6ZNm0auZYq6uLq6Uodypt327t0Ld3d3ir1ZWVmJmJgY3Lp1CwC/ijsDJAuyVKqrq0nVYeA/Z5JwuVw0NDSQQhj19fXw8PAgY//8+fOQlpb+43oluCZ0d3eTe547dw62trZUMbpnz54hOTkZkydPpkCL1NRUqKurIzw8nGQuMCD49evX4eTkBBaLhXHjxmHlypUEuNy5cyeUlZVx+/ZttLW1oaKiAkOGDKHa5U8MeUZ2gpkv/wTEAvS8r6mpwa9fv+Dk5ARvb2/q0CrIhPXx8UFBQQG2bNkipL/J2IwZM2Bvb4+8vDwyXnvqYXZ3d+Pt27eYP38+ZGRkKFaiIHA4ffp0xMfHk2ctLS3Fpk2bcOzYMfKdI0eOQE5ODiNHjsT9+/dx7949hIWFUYWVBO3FixdwdnZGUlISVUToxYsXMDExodaeX79+ITo6mgQWzpw5A2lpaaSnpyMoKAgmJiaEadXV1UWlwAtqsScmJsLR0VGoSNOPHz+we/du8l0ej4evX79CTU2NZEUw6bIAEBwcjNjYWCr9lmnPzs5O7Nq1i2SZMOAbMxZHjx6NMWPGkP7Yu3cvFBQUICEhQVLBBQPBs2bNgpiYGHbt2kWBCO/evcOMGTMgJSVFgNjW1lbY2NjA2toaiYmJyM3NxcCBA6Grq0vJHZSXl8PNzY3Mv5KSEsjKysLJyQkSEhI4ePAgWXNevXpF2uXZs2dwd3cnoPfFixchJSUFX19faGtrIzs7G58/fybaqN3d3cjOzoaSkhLGjh0LNzc3iIqK4vTp0wD4QOyGDRugq6sLTU1NODg4kOdcuXIlVFVVCYC6bds2sFgseHt7U+Pl0aNHOHPmDLq7u3Hs2DEoKCgQP+Dy5cvQ0dERAmLPnj1LrhEs7sW0NxNAPH78OCQlJcm69Pv3bzKX7t69S66bP38+VFRUcPbsWaHA98OHD2FoaAg1NTU4OzvDwMCAXFdQUEAkFYqLiyEjI4MdO3bgwIEDYLFYyM7OFmLRcjgcXL16FUZGRgD4voggAPv7928SwH/58iVmzJiB8PBwrFy5kgSsqqurYWVlhezsbIox/uLFC+jq6hL2IWMdHR349esX5s+fT9LS586di40bN8Lb25titDLWk9m6fft2WFtbw9bWFklJSTh79iz69OmDnJwc9OnTB+fOnUNSUhLExMSIL1JRUYG4uDiYm5uTtYbH45FCtIKMxr/++guqqqpIT09HXFwcWCwW1q5dS62vzc3NmDlzJtzd3QH8XXMgKCgIrq6u6NevH3Jzc9Hc3Izv378jNzcXlpaWRBpKcK5v3boVysrKmD9/PmJjY8FisbBq1SpqjgL8YKGXlxf599mzZ2FiYkKA64MHD8La2loo08TCwgKDBw+GgoICpKSkSFCKeZ+bN29CQUEB69atw/Xr1xEWFobw8HCq/fft2wdlZWUKVG9vbydrEgN0W1paIigoiMw9ptAaU8CMuW/PdbyoqIgK6AH8vW/ChAlUsLy2thbjx4+HpKQkdu3ahXv37mHw4MEYO3Ys+c6ffImOjg6cOnUKERER5CwgmDGXnZ0NKysr6OnpQU9PD9u2bQOHw8GjR48QHR0NZ2dnLFy4EKGhodDW1v7jPtRrvfbfWi8I22u91mu99l8aE8G+fPkycT6Ki4shJiZGabRt3boVLi4u0NbWpgpF9Czos3TpUtjZ2VFALMDXCBPUKRR0CjkcDk6dOgUnJycMGjSIOHCVlZWIjY2FsbExBYL0TP9lHFhBsIX5+/nz5/8jkITH4+HevXuQl5fHuHHj/oOW+9sZffnyJVgsFlVIp+dvA3ztqKSkJNJ2KSkpcHFxwdSpU8lv7d69G+np6di9ezeRddi3bx9kZWWRkJCABw8e4OLFiwgMDKQq527fvh1+fn4YMWKE0KE4MDAQRkZGWLx4MTw9PWFlZUUVhWHS82fOnAkWi4WVK1cC4BcdGDFiBMzMzKCnpwdra2sKlGhtbSWHyrVr11LgRmNjI1RUVKCtrU3SVnk8HmbNmkXY0EePHoW0tDRhSAiOJcE+Y3T0mpqakJubCy0tLeTl5VGMCy6XS4IBMjIyFON69uzZcHNzEwJfGOYXAzb1PDjMmjULMTExAPgH782bN8POzg56enokzevz588kHfPx48d49OgRAeO/fv0Kc3NzODk54efPn2hvb0d3dzcGDRqEcePGobq6GrNnz4aCggJkZWUpWYuGhgbMmzcPcnJyCAsLQ0xMDAYOHAgrKyuK9cIUNgP4hwZB6YKWlhacOXMGbW1taG9vx6dPnxAVFQUvLy/Cjhg3bhxMTU2xZ88eobn89OlTbNmyhRx8Ojo6EBkZSVL/mDHUk5Fx5coVXL9+ncz12tpaLFmyBFwuF5cvX4aqqio2bdqEnz9/wt3dHSIiIpT+K2Pfv3/H5MmTqaACACQlJSEgIAAfPnwAwK+2fejQIfB4PKxZswa5ubkA+Ew0BogVZMT+/v0bwcHBmDp1KpmbhYWF8Pb2hqenJ9F/BPhM75CQEPj7+xPmJ0BrPP639ubNG2hoaODNmzc4c+YM1Xft7e3YuHGjEHuytLSUYt0D/PnNpLT3fD7GCgsLqaIzW7ZsgZiYGGFX8Xg8XLt2jRQ3ZEBmJo2fCQYwv/vo0SN4eHggPj6efC7I5Fq8eDEsLCxgbGwMPT09CkxkpAmCgoKEnnXevHkwMjJCW1sbPn78SLR7L168SNqa6b/4+Hj069cPYWFh8Pb2RmxsLO7evUuBdwAI6JiXl4cfP378Y581NDQgKysL2traBIACaCCWedZ79+5BREQEoqKi1Lhoa2vDxYsXYWxsDDU1NcIAZObs9u3bMW/ePCxfvpzMt7Vr18LFxQWjRo1CWVkZHjx4gKCgILi7uws964sXL/D69WtUVVVBV1eXBNc2b96MPn36QEFBgVRrB/hM3cTERMydO5fo/r579w7Tpk0Dm82mgNieQCpjkZGRcHd3J/OCWZtjYmIQGxtLXbdlyxYyFzkcDvbu3Qtra2sEBweTfuHxeHB1dcXkyZPJdRcuXICGhgaMjY0RFxdH2lxwzU5JSQGLxUJxcTHVJu/evcPMmTMhJSVFJGEYoMnPzw+hoaFgs9lEu5l5/hcvXpC9p7S0FCoqKsSHcHNzg76+PgoKCqhn6O7uxo8fP3Do0CG0tLTgxo0bUFFRIb/j5+cHHR0dJCUlEX3nhoYGZGRkkEBZc3MzEhMTISYmRhh2bW1tePfuHc6dO0dpc44fP56wTxnty9zcXOjr68PX11doLSgpKcH06dOpgl3A30Ds2LFjKSkKhl3O3PPq1atoaWnBxIkTkZmZKbQu8Xg8bNmyBcuXL6fmRWVlJYyNjUnA5OfPn3j+/Dm2bt1KAgM/fvxAcnIylixZQnT5a2tr8fXrV9TV1ZEioYz/8eLFC8jJyYHFYmH16tXoae/fv4eXlxdycnIgJSVFMS3v3LmD4OBgFBUVQUVFBWFhYYiIiICIiAiRgWpra8Ps2bPh5eVF0tR//vxJ1qCe2ueC1tjYiBMnTsDLywtBQUFgsVjQ1tYmexLADxRNmzaNZMsISrgUFxfDwsICVlZWYLFYSElJwcSJEzFgwABISEhQYDnwNxBrYWEhxMpknq+iogKZmZkE3Af4IH6fPn2EpILa2tqIf6yiooKHDx+Sd1y1ahXk5eWJ31ZfX4/09HSMHj2aaofy8nLMmDGDep7c3Fz06dMH+fn5xJ/6U2bE27dv4ezsjOzsbAB83+vYsWNwc3ODvLw8HBwcSKbJwoULSdEtQX15xjIzMyEvLw9dXV0oKyuTscJkJS1evBijRo0CwPdp1q1bB1NTU5iYmJB3bGlpIbURgL/XOAbIXr16tdC+8icWKYfDwf79+8FisaCnp0fmvOB7p6eng8ViwdjYmCps9u/IHoydPn0aOTk55Plyc3OhrKxMCi/6+vpCS0uL+A2PHz/GzJkz4eTkhLCwMCoI1Wu99r9hvSBsr/Var/Xa/9AEmQV+fn4wMDDApUuXiGN95swZiImJYerUqeR7P378oCp5L1u2DL6+voiJiaEqXC9btgwODg6YOnUqysrK4O/vD2dnZ/J3Ho+HU6dOUY4Ah8PByZMn4ezsDB8fHxKlvnv3LrKysojDs2HDBsTFxWHIkCHIyckhABrj/DGOeE991/8EiOVyuaiqqvofpegw9xEEIC5cuIAjR45QrEqA385MwbHu7m6YmZnBxMSE6Bqmp6dDQUEBbm5uRAuSAS8OHDgALS0tqKurw87ODuHh4RQYl5aWBi0tLTg5OZH7MYdHhkHp7e2NoUOHUmC7lpYWcfjLysqoFHGADzKWlJSQVGEAlAZta2srxo8fDycnJ6xdu5Zi3f3rX/9CWloalQYeGBiIBQsW4PLly0I6rkuXLsVff/1F9V1TU5NQetv8+fOhpaWFFStWoKGhAVwuF1FRUTh9+jSkpaXBYrEocGHdunXQ0tLCvXv3KEf36tWrMDY2FjrIMlWYV69eDWVlZcyaNQu2trYYNmwYsrOzMW3aNEhKSlIsypSUFOjq6kJKSgr29vaEhVtZWQlbW1vCQrWzs4O5uTnpA4bJraOjQwAExr5+/Yrz589jyJAhmDRpEhYvXiyUjn79+nUYGhqisLAQsrKyVJGWy5cvIzo6Gs+ePSP3q6qqQnBwMNhsNjk8xcbGEiC250FD0JqamqClpUUOTsDfB4e2tjbSF4LGzAmGGcWkHDOfMwdLDw8Pqm8KCgogLi4OW1tbSmMa4DMzDQwM4OLiAktLS5iamlLjTllZmbAvmTRAFxcXookcHh4OW1tbKphz6tQpWFtbQ15eXkjD8cGDBxg8eDDs7e1x/fp1oXXrPyluwYAdPfWlfX19kZ6eDllZWQoorqqqwtChQwmAAfD72tLSEioqKtixYwdh9jx69AjW1tYEWP9TsGv+/PmkONfhw4chLS1N7tfc3EwCZqWlpXBycoKzszMBFFJTU+Hr60uen3n/AwcOQExMjAIeAD6QqqKighMnThD5DBUVFeqwfvv2bfTt25fME8F2FixyU19fD0dHRwwaNAilpaXg8XgIDw8nxRQjIiIwbNgw1NXVYfDgwQgICICnpydu3bpFPdfs2bOhoaFB6Vxv27YN6enpmDZtGgGmvn//jqysLJiamlJ6zoLp2kzxvPz8fCgoKFDa3ox1dnbi0aNHqKqqIu01b948DBgwAGFhYRAREcHAgQNJ2v22bdvg7+8PFosFa2truLu7/1upi40bN8LX15fsf0eOHMGQIUOwZs0a8n1GpiQ4OBh2dnZQVVUlaxuj4+rm5oYFCxZQY/rDhw+U9MqFCxfg6uqKuLg4si8zwSTBwGN6ejpUVVWRn59Psh+6urpQWFgIAwMDaGlpISgoCKNHj4axsTG1Jj19+hT19fUoLCyEvb09Ro8e/UfAYPPmzX/cy/8ExDLa4FwuF8+ePQOHwwGHw6GkDpg1fOTIkUhKSiKM0BEjRkBVVZUUDOppzPoyYcIEJCQkkDafNGkSzMzMMG3aNPB4PBw9ehQsFgsmJiYUE6+jowOJiYkQFxcnoFlPEJwprPXlyxc8ePAAurq6ZH3Pz88Hi8WCjY0NaeuKigrY29tDRkaGgLDM7wB83Xl9fX2EhYURQF6wn+fNmwcbGxu8fPkS+fn5sLGxgZSUFLWnfP/+HcHBwUJa52/evIGVlRVOnTqFmzdvYurUqbCwsIChoSG0tbVRVFSEu3fvQlxcHOXl5WSsCAYeHz58CDMzM9I/b9++RWJiIq5cufLHPmcK+fXr14+SnmhvbycZDFJSUlQq/aRJk9C3b18iB9HU1ITU1FRYWlpCTEwMTk5OUFZWJmzsntYTUGxsbERVVRWmTp0KbW1twoZNS0uDkpIS8vLykJCQACMjI4wYMUIoELx7925kZmaCw+Fg7dq1RHLp9OnTQntxRUUFxo8fDwUFBZJ+zzxLRUUFWCwW+vbtS0l4AXxQVUREBH/99ZfQHnXo0CFYWFjgx48fVBszwDbDtv7x4wf17mVlZRAXF4eUlJTQ/XJzcyEiIoL169dTurqtra3U/bdv344BAwZQ2tAAf89mgoAdHR1obGzE06dPERkZCRUVFSJb0ZN5evfuXaxbtw5dXV0UY/+vv/4Ci8VCRkYGzMzMMHz4cKxevRoJCQlQVVUlsl2M9SzIGhUVBWlpaZw6dUpItuOfbNiwYUReQTBYwdjz58/x5MkToaKT/2RcLpfSbOdyufjx4wd8fHxI+5eUlEBGRobs68xvM6zf/2nmTq/12n9ivSBsr/Var/Xa/8AEHY5Tp06hoKAALBYLlpaWuHz5Mtmkz5w5g/79+2PatGno6OigrluxYgXk5eWRmppKUiEFnd01a9bAxcUFOjo6cHNzE2JN6OrqYtSoUdRvdnZ2Ys+ePZCTk0NERIRQYYTU1FQoKSlh+fLlyMrKIoc6xtnIy8uDqKgoYeoBfKd75MiRf6zO++/a5dmzZ0Latv9kgofkOXPmQEJCAoaGhhAVFcWWLVsIALVq1SrY2NggJCQEHh4eUFdXx6BBgzBs2DBcvHgRMTExBHQtLi5GWFgYPDw8SFrc79+/UVVVhYsXLxJdwvT0dFy+fBlfvnzB4sWLISEhQR1IBJ27nkzTPXv2EFD40KFDFOPl58+ffyxStX37diQmJiIhIYGwQdvb2zFx4kTC6r106RK8vb2hq6sLWVlZPHjwgLTR1q1b4erqiv79+1Og048fPxAaGkod7nJzc+Hj4wMFBQWkpqaSlDAAWLBgAXR1dTFs2DB4enpCTk4OkpKSmDFjBtavXw8ZGRksXryYfN/NzQ3Gxsa4ffs2YWjMnDkTdnZ2VOrkjRs3wGKxUF1djfr6emRnZ8PW1hbr168nRcVu3rwJT09PcoA/efIkdHR0cPnyZVy8eBHr1q2DrKwsxRLMz8/H0qVLCVDNMLIqKipw7do1pKSkwMTEhApmCFrPoIKgMbIBjJYj0yehoaGIjIwkbX/o0CGMGDECrq6uGDBgAHR1dUkFegaI3bdvn9DvM9bZ2YmoqCiMGTNGCBi/ffs2oqKiSJvcuHED58+fp9glv379goWFBXJycsh7REZG4uLFi0KH2ydPnsDf3x9iYmLkQCx4eCgsLER2djY5wDIp13V1dXBzc6OK+jFpgB4eHtDU1KQAIMG5e+3aNTg6OmLo0KHUIRfgByhSU1Opfli6dCkiIyPh7e39j+nwAH2oa2lpwYkTJ4jO7Ny5c8FisUiqJ8AHRUNCQuDn5ycEaldXVyMnJwdGRkZgs9nIzMxETU0NfH19MXv2bKF7M8y02bNnIzc3F7dv36bmOZfLRUFBAdatW0eCJTdu3ICSkhKMjIzA4/Fw5MgRIT1IgH/oc3BwIIw/gM8QdXd3J7qqp06dgqysLJnzghWbnz59Stq/sLAQwcHBGDRoEDlsMn1UX18PJycn+Pr6wsbGBsbGxmQ9ZzT9vn37RtizkydPRr9+/TBo0CDyXgCfmSaocSsrK4ugoCA4OztDXFwcK1asQGtrK758+YLs7GxYWFggJSXlH1lDP378wJo1ayAmJob58+eTz/906H716hXCw8PJ+v7lyxcYGxvDw8ODAiEqKyvx8uVLcs9169Zh1qxZyMjIoJj669atg7q6OqlQPnjwYCxYsICMs48fP2L27Nlk7lRXVyMyMhISEhIUEDtmzBhK83nOnDkwMzODuLg4QkNDiW5kYWEhnJycSPE4BwcHmJubkzm5bt06KCkpUe8iGJw4fPgwbG1tYWJiQmW1zJ07F46OjoSR3draiq1bt8Le3h6xsbGkv6ZNm0Yx4v8dECsjI0P2puXLl1PgxYkTJ2Bubo5du3aRz5qamuDk5IS8vDzy2ahRo1BbW0tpEJeUlAitC0OGDMG4ceNIn0dHR+PcuXPkunfv3mHcuHHo27cvmYtM33Z0dJDsE8H1Y9++fUL6omvXrkVISAjZ9wsKCjBhwgTExMRQa9i2bdtgZmYGOzs7ArAKArElJSUYNmwYuFwutmzZAhsbG7S3t+P169cICwsjsiYtLS0YOHAg1NXVcenSJXz9+hWvXr1CcHAwnJycSPtv3rwZ69evR2trK1xdXeHo6AgREREkJiaiuLgY79+/h6urKzZs2IDa2lpMmjQJUlJSkJWVJZJCTFtVVVWRdHYmAyEgIID8fc2aNZgyZQoiIyNx7tw5cDgcPHv2DEZGRggMDMTixYuxbds2eHt7w8zMDHJycnBycqLmb1xcHPr164cHDx6QjBUul4vv37+jsLAQp06dojK4/icWFxcHNzc3XL9+HUZGRsRvO3PmDMTFxYX09QWBvqysLISEhODTp0+YOnUqJCQkUFRUJOS3vnjxAosWLfrj+C8sLASLxcLUqVOpNZlpuz+t4fv378eAAQPI95n7ffr0CaqqqqRg1Z/YrPn5+ZCWlsaECROEAtl5eXlgsVgkMLhy5UqMHTuWSIYA/LkeFBSEBQsWoKuriwRMmHusWLECSUlJJBOnra0N4eHhUFVVpdjcubm5RGIC4I/3nTt3Yvr06WQNWrhwITw8PLBhwwYSgKipqYGTkxP5N8AP8CYkJGDq1KmEJQvwQVV5eXmcPn363wKmgv0SGhoKJSUlXLx4kQqKCmba3Llz5z9ipQ4dOhQJCQnkWiYQaGhoiM+fP6O0tJTa19va2rBmzRqhfullwPba/7b1grC91mu91mv/hWVmZkJBQQGbN29GdnY2HBwciDQB40wUFxcLpYPduXMHubm5hKXV0NCApUuXQktLC5mZmeR7z58/R0VFhRB7r7m5GRs2bICjoyNiYmIox+Dbt28wNzdH//79kZCQAOBvzVZTU1OS3nPy5ElKp4yx9PR0wqp79+4dHB0d/23BBMYEnyElJQU+Pj44duzY/xG8Za7j8Xi4c+cO3NzcUFZWhq9fvxJHdMWKFaRy8+rVqzFixAhMnjwZXV1dKCoqgo+PDwIDA+Hj40MdtC9cuICwsDB4eXnh5s2b4HK5qKurIzppjLPOOKmNjY2k0rMgW7EnKMA4uTt27ICLiwsOHToEaWlpqijCnj17EBUVRRg/wN8sw2HDhiE0NBQsFovocLa3tyM7Oxt2dnbQ0dEhmnUjRoyAtLQ0Ydu+ePEC7u7usLGxIamXr169QkhICHW4mzdvHpSVlbF9+3acPHkSRkZGCA4Opth0f/31F6ZNm4bo6GiwWCwCyH39+hXLly+HjIwMSSvu7u6Gh4cHtLS0YGFhAX9/f8jKyhJAgrFfv37B19eXYtIKgpIcDocUeOHxeLhw4QImTJiArKwsqr1Pnz4NBQWFPxaiY55H0F68eIHExESYmJiQKrsA//DNMKWZdPuQkBBMmTKFHKiqq6vh6uoKTU1NFBQUYPXq1fD394eFhQVpz9u3b2PAgAEoKChAdXU1YSg6OTkRAGTcuHFQVlYWKk4maHv37oWYmBgWL15MDqvfv39HREQEAgICSCEUVVVVDBgwgGjQMgyg2bNnQ1xcHCkpKWCz2bC3tyd/EzzgcblcPH/+HM7OzjA2NiYBkT8dgAT1DBlW9KBBg6jv1NbWYujQofDz8yO/0VPWBODrsrq4uCAqKkoIcBGUX8jLy4OSkhJmzpyJwMBAiIqKYseOHX98Pub3c3Nzoaenhz59+iAoKIiA/8w8Hj9+PCZOnIiBAwfCwsKC/NbNmzdx8eJF6mBdUVGBHTt2QEVFBYMHD4a5uTlYLBZ1OM3IyEC/fv3w/ft3FBUVkWI3goU6mpub4e/vTxjrzPsFBQVBU1OTPENaWhrExMRQUFCAFy9eoKGhAYGBgRRIAvDXfCYYcPnyZaioqGDDhg3gcDhgs9lQV1cXqtjc3d2NLVu2QF9fH3JycpQWoyAQa2RkRBURYop4WVlZEQCNx+PB0dER7u7uyM7OhpSUFHR1dSl2/8ePHxEbGyt0kJeXlydr4Pv37zFr1ixER0eT99u4cSOSk5MRGxuLsrIytLS0oKurC2vXroWsrCwFxAq2yYoVK2Brawt/f3+KPf/p0yeYmJjA09MTd+/eFWKpMWy0kSNHQk5ODg4ODgTEraioQGBgIBQUFGBiYkIBovv374eYmBjs7e3x5s0b8ntv3rxBZGQkpKSkyLr36dMn0u/bt28n/XP8+HHExsbC1taWrKHPnj1DVlYWjIyMEBcXR+7X2dmJKVOmkCrqr169woEDB4gEACMfsGvXLnh6epJsjEWLFkFZWRnnzp2jgIm2tjZs27YNdnZ2sLOzQ0BAANTV1f8jBte7d+8wa9YsAubp6upi+PDhhFV47949jBgxAl5eXpTWfHR0NJSVlZGamgpXV1dYWFiQNTo9PR1SUlIwNDSEjIwM5QvNmjULVlZWiIyMBJvNhpmZGbmOaddv375h6NChkJGRIWxYpq87OjqoDBImo2XOnDlEhxvgrxHm5ubgcrloampCeHg49RyCe/zOnTvBZrMxatQo0v+CQCzAD4ayWCycPn0a27dvh4GBAdzc3ChmKqPLbGlpCUlJSbi6usLNzY3MP0ZHnSki9vnzZxQXF1NMdgBwdnYmYD5T0E1GRob4coKaxQzD18DAgErVnjt3LuTk5BATEwMfHx/Iyclh5syZ+P37NyorKzFlyhTo6+sjICAA8fHx4HA4WLVqFcTExEgBsOXLl0NUVBT29vYYO3YspKSkEB0djSVLlqC6uppinv67jJCexvTdgwcPYGpqiq1bt8LOzg4An6EuJSVFSQSdO3eO6q8rV67A3NycMDwBYPz48ZCQkMDRo0fJ/jhjxgx8/vyZXNvd3S0UMGUKqC1atIgqIAjwdVd7zqHW1la4ubnB29ubIj3U1dXB0NAQN27coMZNe3s71TYrVqyAuro6Fi5cSGkU83g8qtjUrl27EB0dDUVFRQwZMgSHDx8Gl8vFmjVrqKAaM97T0tKgqKiIoqIi6ne7uroQGhpK5BIGDRpEzVXmO4wWOOMTMm3PWGdnJ4KCgqj9Ky0tDerq6pgxYwYyMjLAYrGowrlRUVFQUlLC4cOH/+1aJPi3gIAAqKmp4dKlS+ju7sbp06cxbtw4NDY2IikpCX369PmPyB6bN28mPq7g95nApaSkJCXp9OHDB3h4eAjttb3Wa//b1gvC9lqv9Vqv/Q/t7du30NHRoQAXDoeDgQMHQltbG5cvXybOXllZGXEsGE1HDQ0NivXy+fNnLFu2DDo6OtRhtGflWcbZYg5aNjY2iI2NJd//8uULYmNjcebMGcr5u3jxIkxNTQHwC0UIOrbNzc04duwYFW1evXo1wsPDMXbs2D8ykwRN8PDLFMs6evQodTD8kwk6fqtXr0ZYWBhmzpwpxBgWBGIBPmh25coVVFVVEUYqm82GnJycUOr1hQsXMGTIEJiZmRGw9eTJkxAVFUX//v0JwMy8w6dPn7Bw4UKYmZkRVuk/Rb9fvHgBDw8P9OvXjwILW1tbMXjwYKro1/Xr16Gqqkqq+gJ/awenp6cD4I+f79+/o6amhtyTAWKlpKQIuFJeXg5XV1eYmJhASUkJTk5OcHV1JQeus2fPwtTUlBzm7ty5g759+8LY2BiDBg1CSUkJeQZBaQVB51cQiBVk1+7atQtLlizBsmXLhNqaseTkZJiZmVGftbS04NixY0Qzs6urC3V1dTA3N8eAAQMwZcoU6vsdHR2YOHEioqKiqNS4f2fV1dWYMWMG9PT0kJaWhpCQEOjp6ZFxs2LFCsjKyiI5ORlOTk5gs9lEP+/9+/eIiYmBhYUFvL29MXnyZCr4sXXrVpibm1MHqI8fP8LDwwM6OjokJXbq1KmEAf1PtnHjRqiqqoLNZsPNzQ2Ojo5EL/jx48dwcnLCnTt38PLlS4wYMQIuLi7Iz89HV1cXvn//jvT0dHh7e2PUqFEUI/XEiRPYsmULYVECfLaKnZ0dzMzMhDQpAT7gMGLECNTV1RHGW11dHdTV1UnqOdP279+/F9J8Y6wnEOvq6oqRI0cK6dECfKAnPT2d0t7MyspC3759sW3bNiqNmrlffn4+xMXFIS4ujuHDh8PAwAAmJiZkDV21ahXi4uIwcuRIiuk0a9YsaGpqQlxcHJ6enti4cSP1rE1NTVi2bBnCwsJgampKxkpdXR3mz59PtWVGRgbExMRw5swZfPjwAc+fP0dgYCBJ7Rdsl5qaGrDZbBLkamtrw6JFiyApKQl1dXWYmJhQBYR6BtIA/qE1KSmJsL6joqKgqamJgQMHCrUpwJdJMDU1RXR0NB4/fkw+Z57p+/fv5P1KS0sJiL1//344Ozvj8ePHsLW1hZeXFwEgXr16hWXLlpHrdu7cCTk5OVhbW6Ourk5Ij1ZWVpZoQTY2NpK/M5IRw4cPh5OTEyk62NDQgI6ODlL4jklpF7QnT55AXl4eEhISBERlfrehoQHm5uawsLCg0uQBvoY4w/5va2uDtbU1zMzMCHhcWVmJPXv2YP369aSNuru7cfPmTYSHh2PAgAGoqamh7vfmzRtERUWBxWJRDLArV65gwYIFVHbC169fsWTJEtjY2JD1oaamhjDXmPsBfNaXubk5tm7dioEDByIoKAgTJkyAp6cnqf7e0dGB3bt3w9XVFR4eHrCxsaHAccHf6+jowPnz5zF16lRMnTqVer//k9XV1SE/Px8tLS3YtWsXXFxcEBkZSUCYyspKjB49Gu7u7hQjNiYmBsHBwRg5ciQpbPbmzRu4u7vj4cOHePbsGdatWwcRERFKMzgtLQ1xcXGYMGEC2c8zMzORmppKAOimpiZERkZSgb+e44SRt6isrBRKW6+uroaCggJ0dHRgZGQES0tLcDgcbNiwAaNGjcLw4cMpJu+OHTvg4eGB0aNHCxVJZQIyTJ/W1dVBU1MTLBaLsHUFZWbu3r2LAwcO4M6dO6T9mf44e/Ys+vXrJxSwam1txfv37xEYGEikX37//o0nT57gxo0bmDx5MuTk5Mj6JBi8ev/+PR49ekSet6GhARMmTKD0NTdv3gxLS0sC/Hd1daGlpYUaHxwOB/n5+ejTpw/8/f2hoqKCCxcuELmWO3fuIDU1FZqamtDW1ibM3EWLFmH9+vX/EWtQcP2YMmUKNDQ0cODAAQQHB+PEiROU5BLwt2Yvw1A8ceIE4uPjSaElwaD/hAkTIC0tjZSUFAwcOBAqKirUvsX4uHFxcUQTFODvz/8ExDLtIvj8Z86cgZubGxwcHFBaWoqzZ88iLCyMFNZkLD8/H+Hh4fD19UVcXBxpnxUrVkBDQwMLFy5EfX29EGgrCH4+fPgQQUFBcHBwgIuLC86dOwdJSUnSjwB/fGpqalJ7QHNzM6WPHhsbC1dXV4SHh5O5InjfX79+Yd68eXB2dkZ6ejpFACkoKICPjw9sbW3J+125cgV6enrE5zx+/DjExMSE6kwMGjSIaJn/OxNs48DAQGhqauLMmTM4fvw4lJSUYGNjAwUFBfJO/84/ZJ6RKTQcGxtLmL979+6FgYEBAgICqLYKCQmBt7f3/0hardd67b+xXhC213qt13rtf2hv376Furo6ST9jgMpfv35BV1cXzs7OKC4uFnJqnz17hhkzZkBCQoIAQIw1NjZixYoVEBUVxfbt2ymnKD8/H6NHj4aLiwtWr16Nd+/egcvlYseOHbCysoKrqysKCgowcOBABAcHk2vXrl2Ly5cvk4Plrl27qCq4AD8ldfz48eRQ2draivnz50NOTg4uLi7kez0dEsEK0jwej+jK9kzr/ZODJPhZcHAwWCwWJCQkYGdnJ6QFu3LlSvTt2xdZWVnYtm0bnJ2d4enpSUWuDx8+DEdHRwwePFioGM+pU6eII8nj8XDp0iWIi4sTRiyjCcfYp0+fsHjxYsjKylJp2YWFhcjLy6OYlqtXr4aZmRkmTJiAe/fu4ezZswgKCqKKfjGOupGREWHnMG158OBBiIuLUywOxpg+/Pz5MwFime+9e/cO9+7dw44dO6giThwOB48fPybslXPnzkFOTg6FhYWoqqqCtLQ0AgICSIRfEDT6+vUrNeb+xIj9k9XW1lIpq83NzdDT08OyZcvIZ0wa+JQpUyjA6saNG2Cz2TAwMCAp5owtWrQIbDb7P5LCYOzVq1dYsmQJnJycEBkZSRzwsrIypKSkkEPrx48fkZKSAhsbGwpAFwSOBNtnz549MDExobQaAT5AJCkpCTMzM8KI/ScTbNurV69i8+bNSExMJEzHrq4uVFdXY9KkSeS7LS0tGDduHJydnbFhwwZy3/DwcKSkpODXr1/gcDiYO3cuBgwYABsbG1Lkjjmo1tTUwN7eHpaWlhSTkMvlYtmyZfD09ISqqiri4uIIez0mJobM4+3btxOGuSAw2tME2+3ChQswMDCgAkoAP7WUqZjck2GfnZ2Nfv36Yfv27VTgp7S0FCEhIejfvz8p4tTW1gY2mw0rKyvyve7ubuoZLl26BDs7O9y6dQuVlZUYM2YM3NzcsGLFCup7DMjJvBdT1VlXV5c6yNbW1iIxMRGioqLQ0NAggOWfpBna29sxYsQIoQPnw4cPceXKFZw/f14IkBG0pqYmWFpaYs2aNQD4423YsGEoLy8nz37mzBns27cP69atI7914MAB2NvbY/z48RQoKXiPuXPnwsHBgaz3tbW18Pf3h4SEBEnpBYRBLg6Hg3PnzmHQoEGQkpIi6cgMm6yhoQEqKipUkAfgg8qjRo2i1rhly5bB0tISS5YsAcBfa3JzcxEYGEjer7Kyksy3ly9fQlZWFiEhISRNXFA6IDo6mrTB/fv3cfXqVUycOJGw4Jn+YYBYRmbgn4pp3b17F15eXtDW1ibsRuZ+r169wrx588iYYbIrWCyW0DrJsCEFGWGMbd68maQXf/v2DR4eHjA1NUVeXh7JfCgsLISnpydh2XV1dWHLli2kAA/Tpj2BG0EZE8b+J1qGgiDirl274OzsjKFDhxJAqKKiggCxgmnigvvAt2/f8PDhQ0ydOpUqFLZ582aIiIhQ2SaMpaWlQUVFBdOnT8eQIUOgr69PsoM+ffqE4cOHQ0FBgWJ7M+8fHx9P1puebFqAP86zs7Oxbt06cDgczJkzB0pKSkhISEB8fDz69++P4OBgEkTYsmULAY0Y+RiGASslJYV3796R+9TX10NNTQ0eHh5EdudP7ck8k6C+ZFRUFBISEtDR0UHWsNWrV8Pd3Z2sL0uXLkVaWhrxjaqrqzFu3DjIyclRMkPr1q2jdGoLCgogIiJCBawYy8/Ph5SUFMX2/tPzbtiwASwWCxMmTPjj3xsaGmBsbAx7e3tSMI0JeP87E/yN7u5urFixAmVlZfj16xfU1NTAYrEo/6u9vR3BwcEYM2YMeDwempqaMGjQIPTv359aZwX3joyMDAwdOhRWVlYwNzfHnj170N3djfz8fMjIyGDOnDkwNzeHm5sbFWzatGkTREREkJKSIlRwtKd1d3fj2rVrCAsLg4yMDMkUEtwX5s6dCxUVFaxZswZHjhxBv379EBgYSHybFStWQEdHB7NmzSIZGytWrMCIESNgbm6OhQsXkgB+R0cHHj16hJiYGJiYmIDFYmHMmDFUf3l6egLg7/2rVq2CoaEhdHV1qaK5jY2NBIDlcDi4d+8enjx5QoLIv379wty5c8FmszFnzhxwOBw0Nzdj3bp1VGCHKSDIFLc8fvw4JCUlSX2J379/E534v/76S6ho2j+Z4Hplb29PiluOHj0affr0QWRkJCV98adzhuCazpwjREVFsXDhQrS0tKClpQXz5s0jRb5GjhwJV1dXWFtb/1tN8V7rtf8t6wVhe63Xeq3X/guzsLCgWKhMepOvry/69OmDiIiIP173+vVrJCUlQV9fn4ryA/yDxr59+4R0UhUUFJCcnIyEhAQoKioiKioKDx48AJfLxfnz5+Ht7Q17e3uEhoYS52Hjxo2QlJTE8+fP8fnzZ+jp6YHFYpGDPcB3bIOCgjBy5EjKifn06RNJfWMOysDfh5oxY8ZQ2nRbtmyBhIQEZGVlyQFJ8Pc6OzvJgVrw3caPHw8Wi4X4+HhMnz4dAwYMwJw5c4S0mJg0TklJSRw6dEiomA3Aj2p7e3sjMjLyjwchwXsLFv3IyMgQ0gBjIv7M97OysjBgwAD4+PiAxWJh2LBh5GC2YsUKDBo0CH379gWbzcbgwYOFHLjr16+jT58+hMklWMFZW1tbCLjoaYJArOABVPCQ+ebNG7S3t6O7uxvfvn1DS0sL/P39kZubS/qCzWZDRUUFc+fOJde/f/8esrKyBKAU7B8GiFVUVCRsi8+fP5P7Hjx4EFpaWvDz88O1a9dIO86ePZuwWBkTLE4h+PmNGzfg4uKC8PBwwi769u3b/4+9vwyoav3Wh2EXAko3SHd3d3eDGIgBCBYGKgrYhY0iqGChgomC3bFt3RYqJtiKomKgNCy4ng/rnfdv3iz0t8953v85/+ccxpe9Xay55px3jvsa17gGPDw8MHjw4D+2y++stbWV3OvgwYMwMzODgYEBYbYBvJSzadOmwdramhrjjLHH7/Pnz9G3b1/MmTOH+s6dO3fg6emJ2NhYKhX1d/Y7xsbChQtJOq6Pjw/1t4aGBiQmJsLZ2RlZWVloa2vDqlWrSBDh5s2bcHd3x82bNwkjVlJSEuPGjSPPVFlZCTU1NZL6euDAAepQXlRUhJSUFPTp0wcpKSnw8vKCmJgYsrOzoauri9TUVALA/InhxH4/5nnY1tHRgcmTJ4PD4RAWHfuaBQsWgMPhEO3TS5cuQUZGBr169SIAC3PIrq2thbKyMkkrZhfuOnToEEaNGkXJu3z79g2jR4+Gs7MzVq5cSb7btajI3bt3MWzYMAgLCxMmb9eq1mfPnsWtW7fItdu2bcOUKVPQ0tJCvltZWQkJCQkqWNTV/nTAS0hIgKysLGbPng1HR0dYWVlRmqxaWlrw9PSEmZkZtLS0CNOtqKgItra2SE5O5iuQ8/LlSwQHB1MsZKbdBQUF/62eI5fLxV9//QUzMzOYmppSzPDXr19DVVWVsAEBnsamhIQELC0t+Zjz8+fPh7y8PFkz2Onjhw8fhqqqKgoKCggb7fHjx5CUlER4eDgFxLL7ZsqUKVBQUICioiI4HA7Wr19PrTVcLhfW1taQk5OjgKIHDx7gyZMnVADv77//hq+vL3R1dSkgtjt96StXrkBMTAweHh58QcQJEyYgJCSEYsV9+PABMTEx0NfXJ4GFzs5OKiDY3t5OCnGx37OtrQ1v376FgoICtW4xY+Py5cvYuHEjAUSfPHmCa9eu4cuXL+R5f7cOsQMZzLO0traisLAQ9vb2fEDs0KFD4eHhwefHzJo1C/b29rCwsICVlRUBNgEeiLRhwwYICwtj2rRp5PPjx49DS0uL7G9MgJIte/D161d4enoiMDCQul9bWxtsbW0xcuRI8hkbSO7qD5SXl0NNTY0E0QEesKmsrIz+/fuTz1avXo1x48aho6MDBQUFEBQUxK5duxAUFARtbW1UVFRQmQKKiorw9fWlxjq7rZcvX45du3ZRYyQ3NxeamppUmvS3b9+wY8cOUjS0X79+KCwsJAESgBcMiI+Ph6ioKHJycuDn5wczMzNqTamqqiKF7Biwllk/29vboayszJfxUFtbi1evXuHnz59k7uTk5EBAQIDyHYF/yTTcvn2bFMVi+u9PGVTsNmG0/tva2sizX716FYqKihgwYAAOHjyI0tJS8n7s4PaHDx8wePBgaGhoUMQC9r3r6+vx+vVrREVFwcPDA1u2bMGYMWOIv1NfX0/2haVLl1KZMy4uLn9kWXb92/Pnz1FTU0MBlI8fP4apqSkZaydOnICEhAQfS3TmzJmIiopCZ2cnMjMzIS8vj61bt2LNmjWwsrKCg4MDFUQFeHOdXWyvs7MThYWFMDMzQ0xMDAwMDDB06FBkZWVhy5YtkJeXx+3bt5GQkEDY152dnaQQmrq6OoyNjYlv/+PHD2RmZsLJyYkKPDHGLqYbGRmJwsJCPpLH6dOnkZiYiCNHjkBYWBgjR47kCwj8ztj3Y/67adMm5OXlQUNDA8nJyXykC/a1jDFnMh8fHzg6OoLD4SAjIwNtbW1obGzE+fPnkZSUhIkTJ2LFihV8mS091mP/p6wHhO2xHuuxHvsPGLtQj66uLqZPn079LT4+Hs+ePSNOQ0lJCXJycjBv3jzCOnj37h1SU1NhYGBApTB2vU95eTm0tbWpwhOXLl2Cg4MDhgwZQqUqffr0iTiFFy5cQHZ2NlV59fHjx5CRkUFUVBQ2b96MPXv2wMfHhzi2Dx8+xIULF/Dhwwe0traivb0dCxcuhLi4OKXx+evXL2RmZpJD5YYNGyApKYm1a9eib9++pLoy+0B37do1bN26lXreqVOnQlhYGJMmTSKf5eTkQE1NDbNmzaKA2Hv37kFPTw/5+fl8rBK2U8gAsQMHDuRLT2X3HfMbxcXF4HA4mD17NnFwBw0aRBzmzs5ONDQ0YMCAAbh27Ro6Ozvx8OFDSEtLIzAwkACxnZ2dqKiowNevX6nDMmOtra2IiIiAr68vVeW5trYWRkZGOHr0KN+zdrVPnz4RfcPr169T7z1v3jxSGIR5xx8/fsDMzIwckOvr65GQkIDDhw/zAWkDBgyAp6cnxWRi7OvXr5g/fz40NTWxfft2+Pn5UVXSd+3ahVGjRpGxtX37dly9ehW9e/fmY7ey255t58+fh6OjI9HO69+/P1xcXPj0Tv9JiiP7ENrZ2YkHDx4gLi4OEhISfIfI6upqZGRkQFVVla/wR1fbsWMHhISEMHPmTLx+/Ro/fvzAnDlzEBERQdLbZs+eTYFQvzM2G2rr1q2QlJTEsmXL4Ofnh379+lEpgAAPiI2MjKSKAG3atAkcDgejR49GfHw89d4MEJuSkkJY8+/evQOXy8XTp08hLi6OIUOGkKAAY+Xl5UhNTYWfnx/RLF6wYAGcnJwwYcKEfwzEsudld0BjUlISxMTE+MYHw+5n3v38+fNQUFCAqKgoUlJSyPe4XC6amprg4uKC+fPn4++//6Y0dt3d3SEiIkIBKszfxowZAzc3N8ydO/e3B+yHDx8iIiICUlJSJP25K9OWed5fv35hwoQJMDExgaamJsVkHD9+PBITE1FXV/ePi3ow9/j+/TtGjRoFHx8fxMbGkvVk06ZNUFRUJAfZw4cPg8PhUIGc7du3Q11dnUqxzs7OhomJCTw8PMh4Zfrm48ePcHZ2Jgz6P1lHRwcuXLgAMzMzGBoaoqSkBAcOHEBoaCisra2p/i4vL4enpyeEhYVJmzAASWNjI+Tk5LB3716qXbds2YKVK1dCSEgI6urq2LRpEwXESktLIyoqCpWVldR1f/31FxwcHHDy5EmUl5fDw8MDtra2OHToEDWX2tvbqaJVc+fOhbGxMbS0tKCvr0/tx3///Tf8/PxgYGCAV69eUX3IFGRjWKqXLl2CoKAghg8fTgDe+vp62NvbY/To0WhubqbS5MvLyzFy5EgYGxtTOsN1dXXYuXMnQkJCYGZmRhXoYu8tGRkZsLS0pDIzuFwu/P39CTOOqWiuoqICOzs7jBo16rfBIjbAzBSQZAByRgqBKbzHliYICgqi5GQ2bdoENTU1LF68GGlpaRASEkJaWhq1H7a0tCA7Oxvu7u7knfLz8+Hr6wuAXwu0vr6eMAG7Y/m2trZiwoQJ8PHxoQJtAG/MBAYGUmDN5cuXoaqqSvQy2bqkoqKipOAi0y4HDhyAsLAw+byurg5eXl7Q1tbGw4cPKSBWSUkJAQEBePToEfWcLS0tSEpKQr9+/eDs7IypU6cSf8HX1xdjx44l92Ns7969UFJSohj5P3/+RHV1NbhcLn7+/Im0tDSYmpoiKiqKtPGWLVsIa76yshKenp7Q1NQk7HWAN+c1NTVRVlZGBSyZAnI+Pj4YN24cGd+M3iy74BKbta6jowN9fX24uLgQsL87EIvdJhs2bICcnBzxGdnfuXbtGiwtLaGrqwt7e3sMGjQIbW1txDdl7P3794iMjISnpye1h3eV4Hj37h3Cw8Ph5eUFExMTiiXP7AsMI5Y955j//hMwNj4+nsx95v6XLl2Crq4uAODIkSMUSPnz50/qmTs7O3H//n2Ym5uT1P5z586hb9++JGj5u32EuV9LSwsp5LVt2zayL5aXl8POzg6XL18mfsadO3fw/PlzIiVw+PBhjB07Fr179yYB8R8/fmDmzJnQ1tYm2sQAb99hWLP379+Hvr4+BAQEqMK+TU1NCA4OxogRI9DZ2UkCLQkJCd36512to6OD9EV+fj7y8vLIGnro0CGoqanxZTwwrFvGJk6ciF69emHZsmWknxiN2MzMTKqwLNt6GLA99l9hPSBsj/VYj/XYf8K+ffuG1atXQ1VVFZ6enkhNTYWzszOMjIyIozR58mQoKSmR6vKysrKEYfnmzRtMmTIFJiYmfNIEjN27dw+qqqpEx4753YsXL0JISIjP4QB4WqVMeiTjMLOdZTc3NxgYGMDV1RVDhw5FW1sbZsyYAUNDQ6irq8PKygoJCQl49+4d6urqsGTJEkhJSZG0JrbcwODBg8HhcEha5YQJE6Curk49V1tbG/z9/TF69Gjy2Zw5c8DhcCAqKop169ZRz88AsXPmzCGHhh07dsDa2vq3B0i2U15SUgJTU1OKBdfV2A71jh07ICgoiMjISNjZ2UFXV5c4fs+ePUN5eTkmTJhAVbSvrKwk6bGMI8r+zbVr12LcuHFITk7GkSNH0NLSgmvXrhGNt6KiIpSVlRFNyX/q8H3+/Bn+/v7w9/cnnzFFuEpLS/kK17i6umLIkCFYvXo1AgMD4ejoSJ6Ty+VSmrCOjo6EIdfV0f/27RvWrFkDGRkZLFq0qFutz7NnzxIZh4iICPTp0wcxMTGor6//R5quV69ehZ2dHRwcHJCXl0c+v3//Pm7evIlPnz79sbIu806MsZ3rZ8+eYfjw4XBwcOBjJr59+xbr1q37t33Q2dmJ3bt3Q1xcHNra2tDR0YGUlBQ4HA5WrlyJlJQUiIuL/5aZ0fW3AF67z5kzh7DhGhsbkZGRAScnJ8yYMYMvxZ0Bb7sCsQYGBlQBDoB3SJGVlUVsbCxhos2aNQuTJ0+GpqYmhISEEB4ezpce2NLSgl+/fmH8+PHQ1dXFr1+/sGDBAri7uyMtLY2wH/8kS8D87dmzZygtLUV2djbWrVtHgb7x8fEQFxcnQCz790pKSgiL8/bt25g9ezZZE9j3MTc3x8SJE2Fvb4+YmBhy4Hz79i0GDBgAQ0NDSrcS4I3lQYMGYcyYMXzjkv3vR48eITo6GsrKygSI7coE6srSmTFjBoKDgyEtLY01a9YQFhubNfsfNXZgpL29HbNnzyas9L1790JSUpKAVewxz9Y5BHj7goKCAsWKY6ytrQ3Dhg2Dg4PDP5L/YIBYGxsbksmwbNkyAr6wg10VFRWwsbGBqakptT69ffsWGhoaVEbF3LlzISMjg127dqG4uBghISFQUVGhgNgnT56Aw+FQwc8DBw5gxIgRFLOyvr4ePj4+sLe3p4BYdh/PnTsXCgoKOHfuHF6/fk0yM9hAws2bN2FlZYUBAwaQz5giNFu2bKHYw2fPnoWgoCA0NDQQGRmJqKgoGBgYICMjA0ZGRiTllWHyPnr0CAkJCTA2NiYA39u3bzFq1Cgqk6CwsBBz5szBmDFjyH7z7NkzJCUlQVtbG0OHDsXkyZPh5uZGgNtVq1ZBUVGRBBRHjBgBeXl5XL16la8/2W2yceNG9O7dGy4uLggKCkJBQQGamprQ0dGBoqIi2NnZURqxbA3zCxcuYP78+VRBm71790JQUBDp6enU+s3IGTEZElu2bEFiYiLRuWSD4WVlZcjMzKQyVl68eIHXr1+TMX/nzh1ISEggMTGRrB01NTUIDw8n+o7Me758+RJ9+/alqs0zTGR9fX2+gNz169fJ3sj0yc+fP38LxHI4HKJTCvB0spkinQ8fPsTWrVuhqakJFxcXDB48GOPHj0dISAhVvR3ggUWMJvCTJ0+wYsUK6OjowNLSEmPHjiVzlWnDzs5OvH//Hn369MGpU6fI/Z8/fw5XV1eoqakhOzsbRUVFCA0NpWSTzpw5A1FRUaxZswYfPnzArFmzICAgQLVRbm4uOBwOn88G8ALKDHDq6OjIV/SKHYAH/hW8Z/a+7qylpQXv378nYHVOTg5iY2Ph6emJwsJCEqh/8+YNIiIi4OXlRREPuq65b9++RUxMDERFRak5zrRhSkoKdHV1yW/s2bOHFPD8d/b161eSacQmYXz48AGenp5YsGABJCQkSJo+wNvbgoODqSKHt27dgp6eHjo7O1FWVkbNhcbGRuzbt++3xajY78sutskUo/Pz80NHRwceP36M2NhYKCkpYeHChVi4cCG5rqamBikpKRAQECBA7Pfv35Gfn0/W9RkzZkBVVRWFhYWkX3fv3k2Kce3btw+nT5+Gn58fFBQUsGDBAjQ3N6OzsxPHjh2DhobGPwJimXkwbdo0yMvLY/Xq1VQgoaysDJqamhgxYgQJBCorK5PrNmzYgL59+0JFRYUiSAA8lrugoCCWLFlCgpI91mP/1dYDwvZYj/VYj/0n7devX7h27Rqio6MRExOD+Ph4ctAoLS2FoqIiHjx4QJzl8ePHo1+/flRl9sTERErTjm3l5eWQkJAgVe3Zadbm5ubIycnpFuA6evQopKSkMGjQIMJkYL7HaMYxn+fk5EBJSYkczJOSkiAjI0PYt7W1tViyZAl69eoFDQ0N6j42NjakIjTDshs2bBgkJSWRnp6OjIwMeHt7U4ye2bNnY8yYMUhJSYGenh4fSwUAKeDBOKxTpkyBlZXVH/vi7du3hGV68uTJfwSqMXb48GGMGzcOkyZNIs7r1KlToampCSkpKYiJiZE+YKyyshJycnJwcnKi5BHmzp0LMTExJCUlwcLCAubm5oiPj0dzczPu3r2LUaNGQUxMDLa2tggODibsjn8KxH779o042w8fPoSBgQF14GK/25kzZ+Du7g4bGxsEBgaSPnj58iUFtjDV16Ojo7u95/Hjx6GgoPDHAxNjTEGawMBAiImJ8Wk4djX25xcuXICLiwtiYmJw9epVotelo6MDbW1tTJs2jS/dl7GuEh4DBgzA9evXCWhYUVGB4cOHw8XFhWKP/e43fmevX7/G4cOHsXfvXrx+/Rrbt2+HsLAwREVFuwU4fve+t27dgoKCAilkxxijxcakAHbVN+x6sNy2bRthc3dX0TkgIAAdHR2kCv3169fx6NEjnDx5EgoKCujfvz+Vts4GK3R0dBAbG4tRo0ZBRUUFYmJiSEtL+y0jtmsgQkhICDIyMvD19YWCggJsbGwoIDUxMRHS0tIU8ywzMxPKyspYv349WaOqq6sxe/ZsSEpKIiwsDCkpKfDx8YGuri7a29tJpee4uDgy3t68eUMAGPbBHOCt28yz/ylA8PDhQ8TExEBVVRW3bt2ivrt582aMGTMGq1evptIr379/j8LCQpibmyMoKAgcDgfjx48nf8/Ly6OYO78zNtje2fkvHeno6GhMmjQJly9fpgrXdHZ2Yv78+ViyZAlfyihbz1RWVha+vr588+jatWvw9vb+x2BxR0cHzp07B09PT9jY2BDQpbvK6A8fPoSFhQUMDQ2xYcMG7N+/H6GhobC0tCTv9enTJxgZGVE6kABPA1BeXh6bNm0iINXLly/JOv3ixQsEBQVBTEyMCk4BPCDW19cXzs7OmDdvHl+RGx8fH5KWfOzYMUhLS6N///58sj2PHz8m7ZKfn49+/frx6ZIyYPnFixfRp08fmJqaYtKkSdDV1UVcXBwmT56MpKQkqKqqQltbmzCXHzx4gMTERJiYmJA9hi3dwgC+AwYMgL+/P7UOV1dXY/v27XBzc0N0dDQmTpyItrY2NDc3IywsjIBlx48fpwCglpYWag4z78bIBIiJiWHMmDFITEyEkJAQhg4dilevXoHL5ZLiYB4eHlR7fv78mQR/2UE0gAfECgkJITMzk0oVz8nJITq6t2/fhoCAADgcDpVp0dTUhMDAQCQnJ5M2mT17NgkaKysrE2bh9evXoa2tDQsLC2hra8PGxoYUEFqzZg0OHz5MAOUxY8bA0dGRFP8CeCCXmZkZiouL+diP3WmnMrqkXYHYT58+kXE9c+ZMIq3RNU2eqXrP4XDQq1cvCqADePqeQkJCGD16NFmLs7OzkZWVReR12OsY8/9OTk58QDKj/czhcJCcnIycnBwCjDU3N2PUqFHIyMgAwNvD1dXVMWHCBHI9M9/WrVtH1q/jx49j3759RAqFy+Xi/PnzsLKygrOzM1kTkpOTqXm9YcMGSElJ/RHg7LoOMSn6S5cuxdixY2FjY4OEhARqvY+OjoapqSlOnjxJXb9nzx6in/zx40dER0fDzc2Nb1+ora0lRWCnT58OTU1NbNiwgZKB6G6/YD6rrq6Gra0tZGVliQRGTU0NwsLCICwsTIqwAjw/PCQkBNHR0dSz3rlzB7a2ttiyZQukpKQo9umlS5cwdOjQf6S5C/CA740bN5LgPzP+GCB22LBhEBISwrhx46j3qKmpwfjx4yEkJESx9AGejIyioiJu3LjBlzm1c+dOuLm5QVxcHK6urggPD0d4eDicnZ2xevVq4nP+EyCWDaRKSEigT58+VHE5ZjweP34ctra2sLCwoDTaHzx4ACMjI8yePRuCgoJ49OgRgH9lYjx58gQSEhLgcDh80hA91mP/VdYDwvZYj/VYj/3/2ZiK6vb29mhsbKSYmomJidDQ0CAOSXV1NcXS2bhxI7Kzs4kTn5qaCgkJCQoo+fnzJ4yNjSmWV0NDA9rb24mTUVZWBmFhYaSmppLP2NpoXC4Xra2tiIqKQk5ODgCec9T1sNba2opv374hMjKSFMKZM2cOOeD1798fZmZmKCkpQWdnJz5//ozVq1cTkJFdaf7YsWPo27cveZetW7fCysoKY8eO5dNtKykpIW2wevVqiIqKkih4V0eYy+UiKSkJy5Yt+y0A0Z2x/8Zm6Rw9ehQmJibYv38/ysrKoKWlheDgYD6QjUl1ZO756tUrhISEUPIRBQUFcHV1RUpKCrnH+/fv8ePHD3R2dmLZsmVYtGjRb5+RscGDBxNHkrG///4bKioqFDuAMabPf/36hZ8/f5J3raiogK2tLezt7XHjxg3CAmAOsF3BZoAHSLP7EeABK1u2bMG8efP4DlNMe3h7e2P48OF8Wop/svPnz8Pd3R36+vqQlZUlrNvhw4dDXl7+j0XMACAoKAi9evWCpKQk3N3dMXLkSALmVVRUYMSIEXB3d8fatWv/0fP8zph7Hj16FEJCQoQRywBF3Rl7vOXk5KB3796Qk5PjA79//vyJmTNnQkdHBxs2bKDe7/79+7h+/To+fPjAV9F53rx5hHHVFWQcNGgQVZgD4LGPJSQkEBkZSTFimX5WV1eHiIgIdu/ejZMnTyI2NhaWlpZITU0lB+zuQIANGzZAXFwcMjIypL9qa2sxe/Zs2NnZYenSpeReMTEx8PPzAwAsWbIEioqKuH37Nlkf2en5s2fPhpKSElRVVaGpqUmKobW3tyM/P59UNGcO5q9evSJALJPyyu6DfwK6P3z4EF5eXggLCyOfzZs3D5KSkoiKioKCggLCw8NRVlZGXffq1SusXbsWo0aNIkUBnz9/DnV1dT5tv+6MPdfYY+rQoUOwtLSEoKAgNm3aRD7/9esXwsLCqIP+kSNHkJubi/z8fJLS/PTpUz4Wf9d2+adzlQFdbGxs4Ozs3K2cCWMPHz6Ek5MTOBwOxo0bh6ysLNLHjI61gYEBAeDYQSIbGxsYGRlhy5YtZC4DvIrqo0aNwosXLzBy5Ejo6elh7dq1fFIe/fr1I8xH5ndramqwYsUKtLS04K+//oKysjIKCgoIgNldoS0ul4uEhAQCTlVWVqK4uBju7u5kPQV4wSQOhwMBAQFs2rSJPDOXy0VVVRXs7e2hrq5Ogoa3b99GUlISZGVlKb3eDRs2QE1NjXzv0qVL4HA4kJWVxc6dO3+rWdjc3Aw/Pz/cu3cPZ86coVKgW1tbsXnzZly4cIEvNVxcXBwxMTFU0bxLly6hX79+pDBTS0sL1q1bh+TkZHJ9cnIyzp49i+vXr6NPnz7o378/n247U/COrR+7YMECSEpKEhZ/cXExKZxz9epVXLlyBQEBARRjc+nSpZCTk8Phw4dx4cIFEpxhgjtVVVU4evQoFi1ahN27d4PL5eLHjx/Q1NSEqakpkYu5e/cuBg8eDH19fVL008/PDxYWFnyBr2XLllFMaLb9+vUL3t7e0NPTo6SGAB5YrKCggOvXr/MFyNh29uxZJCYmwtvbGxUVFVTWzeLFizF8+HAUFhYS1nVlZSUsLS0pf4DtA0RHRyMxMZHvPk+fPoW/vz90dXXJPZj07piYGBQWFqK6uhqqqqpU5tLhw4dx9OhRao3IyMiAuLg4KQ7F6JV3dnbir7/+gpWVFZSUlODu7g51dXXSf7t27UKvXr341svujLnf7t27oaenRxijZ8+eRe/evWFqaoohQ4YQgPzly5ekiBRj6enpUFNTw9KlS8ne+P79e0RERMDT05MPiAV40i0M0NidsedN132vT58+cHBwgIKCAgGrb968CSMjIwQEBGDu3LkoKCjgIyewfzMwMJCPkd/U1ISQkBBERUX94/W5vb0dK1asoOSN2G1TUVGBuLg4iIiIkH2aHUiIi4sjBbc6OjpQV1cHHx8fbNmyBQCP5Xv58mUkJCRg48aNqKurQ2trK968eYPa2loi5xUfHw9HR0cC/AO/B2K7Bh/d3NwgLCyM0tJSPH36FIWFhXBycoK1tTUhjrx9+xbPnz/n83levHiBjo4OREVFwcrKitrv3r59i/T0dJSWlvZov/bYf5v1gLA91mM91mP/P/vPpIyyWUrs/1+5ciUUFRXJ9xiGUGVlJeTl5YnmE/ve06ZNg5qaGtauXUul1g4cOBBCQkKYP38+li9fjsDAQKoIw8qVKxEdHQ1HR0dMnDiROH8MEDtlyhRMmzYN/v7+VDS5ra0NgYGBuHXrFs6ePct3WNu4cSMGDx6MlpYWnD59Gh4eHjAzM4OEhARVhTcyMhKmpqbYu3cvceq7MqI2btyI/Px8UkiH/bm1tTXGjh3LV7yFac9r165BXV0dQ4YMIQAGGzStr69HZGQkxaB58uQJn6bo74zt9B09ehTJycmUnuLDhw9hbGyMsLCw37Idc3JyoKmpCVtbW8rZa2lpwfLly2FmZkaqZHd2dhKQ1MnJiUrf/J2NGDGCXHPx4kW8efMGt27dgoCAAEk5ZWuNnjt3DsePHycHI4DHsmxvb8fx48cRGxsLVVVVhIeHY+fOnfj06RNCQkIwd+5c8lsAz2n38vKiALwFCxbAx8cHioqK0NDQgL6+PjkwsJ9hxowZ8PPz40tF7M7Yc+jYsWNQUFAgaXJHjhyBpKQkNTa7gnQAEBUVBQ6HQ66bMGECREVFERUVRQ5gFRUVCAsL6zYd/Z9Yd2tER0cHNm/eDA6Hg0WLFvEduLtqF+fn50NSUhI7d+7EunXrYGxsjFGjRlHX/PjxAwUFBRRQmJaWBg0NDYiIiMDW1hbDhg0jY4IBYhcsWECBdmfOnEFHRweio6MRGxsLgJaiyM7OhrCwMEaMGEEY6Z2dnTh48CB69epFyXo0Nzdj1qxZ0NbWRnp6OpnjkyZNIvdk0kwTExMJC42xmpoajBs3Dt7e3lS6akdHBxobGxEWFkbA8Xfv3uHs2bMYMGAAli1bhufPnxMdXh0dHZiYmMDb2xtlZWUUS7E7IDYyMhJmZmYUY7y78fM7q6qqIvcoLy/HsGHDyDpw+/ZthISEwN/fn2L0Lly4EBwOB2fPniXtXVlZiX79+lEAeldjz1cASElJgaysLGHbVldXY8CAAbCwsMCOHTtI8ZeQkBDY2tqSA+X06dOhra0NLy8vREVFQUBAgLA+q6qqICsri/DwcDx9+vQfF1vrzrhcLi5dugQDAwN4eXn98bsPHjyAi4sLLC0tSdVxtk6qh4cHVZiOGduxsbEwNDSErq4u2Tffv38Pe3t7chCvq6vDkCFD4OrqioKCAuqdmpqa0L9/f1hYWGDXrl1k7DHr0qhRozB69Ghyv4kTJ8LFxYXSLGVs+vTpsLKywrx58+Dq6oqIiAikpKQgKioKampq+PnzJ2GnCwsLY9CgQRSoBvBYe4aGhlR73bx5E4sXLybjor6+HsuXLyeAB6PzvGPHDiQmJhI9XWZdY4x53pCQEBgaGkJSUpJi/n/48AHe3t7kdwFeMLRv377gcDhQVFQkbcw8y9mzZyEgIEAATPYYvXDhAuTk5IisyOnTpyEgIICxY8fyMQjPnTtHSXp8/PgRPj4+RK+xsbERW7ZsgZKSEpSVlWFqakqKmjFrhK+vL7U3AzzWvbCwMEmfZltaWhoiIyPh5+cHeXl5qnjc48ePkZWVBTU1Nbi7u6N///6YPn06FQQHeGxWBuTtbq78+vULZmZmFFD76dMnuLq6Etbyp0+fcPPmTaSmpuLQoUN8Y+Ls2bMQExODhoYGjIyMMGTIEPI3th/DgHFMajnAY6cqKirC2toavr6+CAwMREREBK5cuYL6+npqjr158wbOzs4wNDQkfiKXy8WIESMQFhYGHR0dSnv858+fGD58OFauXEnWlsePH8PW1ha3b9/Ghw8fsG3bNggICCAjI4PMoefPn2Pu3LmYOXMmuW7NmjXw9fWFtbU1srOz/xi0Yc+7OXPmEPmRQ4cOQUZGBhs2bEBOTg4kJCQwfPhwPt+Ry+Vi7dq1kJeXx927d/lkdN69e4eoqCh4e3sTv4IZg6GhoVi+fDkAHrB74MABREZGIjY2lsosYz8js++VlZWhuroawcHBkJeXJ3vq1atXMW7cOJL9lZSUxAeMMs/2/v17uLi4QFdXF7m5uVi5ciWcnJxgbGyMtrY2rF69ultmdnftxx7H3YGNT548wYABA6CgoMBXVJeddQXwAqkqKipYsGABjh07htjYWDg7O8PGxgb6+vpYunQpX5CTAWITEhJ+C8QmJiZSTHI2C1ZYWBhycnJYtGgRKXybkZGBqKgoqKqq8sledPW1AJ6/HBwcDB0dHezfvx8HDx5EYGAg0aD+Xdv0WI/9n7YeELbHeqzHegy0c/3s2TO8e/eOcl5/dxhlOzl79+4l6W2fP3+GgYEB5UwDPCabnp4eX4XQgoICKCoq8hXLAXiAwbJly2BjY0N0PhlwIz09nVRS3bBhA8zNzWFsbEycxYMHD0JERATe3t5wdHREbGwsBSRGR0dDW1sbkpKSFLO2pqYGcnJykJWVJZ8x6bWhoaF87REZGQkLCwvs3r2bzzFiClAxmlEA7fRs2rSJ6OX9zrmcPHkypKWlkZycTDHJ3r17h9DQUDg7O5O+2Lt3LwwNDbFnzx5yKPgn6fD37t2Dra0t+vTpw8cafPjwIUxMTBAZGUlVVWbs06dP0NPTA4fDwcGDB6nf/f79OwQFBSEuLk6BDC0tLTA2NiaMvu7MxMSEOnQOHjyYjJPm5mZER0fDw8ODSo9tb2+Hr68v0tLSyHOcOHECcXFxFEv3yJEjSE9Ph5CQEJKTk+Hg4AAOh4OnT59S43rLli3gcDgYM2YMbG1toa2tjaVLlxK208CBA+Hr60sB7wsWLICCggKEhYWho6ODAwcO/PbQxW6r3NxcHDhwAA4ODnj48CEuXbpEBQdaWlqwdu1avnTghQsXonfv3sjMzATAAwPExMQQHx8PExMTDBgwgMwJhiHR9d7/zthrxLVr13D69GnU1NSQ32A085YuXUpAybi4OAIUbd68GT4+PhASEkJ6ejpJBV27di3Mzc0p9hH7flwuF2VlZdDV1cXZs2dRXl6OnJwc2NjYwM/Pj4zxjRs3olevXkT3dsaMGRASEsKvX7+wfft2Agqy3zs/Px8RERFQVFQkcxPgAVfW1tZEf5TdTm5ublBQUEBCQgJOnDiBhIQEtLe3Y8OGDZCWlkZpaSm2b98OMzMzEkxiyzBwOBy+/qurq4Oenh7Gjh2LAwcOIDo6Gu7u7vD09ISRkRFheL569YoAsaampvDx8aFSitlALMMOq6qqQnp6OhnTRUVFpNDLn2zjxo3UexcVFcHb2xvu7u4U0H3r1i2EhoYiICCAYpIHBQVRoE9VVRX09PTQ2NjIxw7v7OzE4MGDkZ+fT/YdJn1YXl4egoKCyMvLA5fLxbNnzzBw4ECoq6tDVlYWVlZWcHd3J++zY8cOKmW+qKgIHA6HKoBTWVkJDoeDtLQ08tnFixdx9OhRnDlzhprL3c0RdpbBvXv3cPz48d9qdrPtwYMHMDc3h52dHWpraynG6927d6GgoECCBczvx8XFoby8HK6urvDz88OSJUsQHh6OuLg4NDU1UWxpBojduHEjuFwutc9ERUXBzMwMO3fuJO/X2NgIOzs7wm5tampCdHQ0BajX19eTtr137x6Sk5Oho6ODFStWkH2ckf6oq6tDZGQkBAUFsX37dsjLy1NgJNN2OTk5kJKSIoWkuqs6fufOHVRXV6OqqgomJiakcNrff/9NUtiZsVVRUYG3b9+SAFBVVRXMzc1hYWEBgOdDfP/+HcHBwXBzc6OCXpmZmcjNzcWoUaMgLCxMUpAZ8LO5uRnGxsZ8abvbt29HamoqsrKyqOc+deoUBAQEMG7cOGp9ZH6TYYYDPImmrlJDHz58QFxcHBwdHQkbsb29HXV1dTA2NiaZO2z/LDY2lgCTTFsyKd3l5eWoqanBp0+f4OvrCyUlJaqAYkNDA1paWkiqurOzM/WuQ4cOJevg76yxsZHaMz98+EDAwmvXrmH48OGwsbGBsbExFBUVsWPHDnR0dFBrkqCgIJKSkrBq1SqoqKjA09OT7FmNjY1YvHgx/P39qeBWR0cHbt26hVu3biEnJwdpaWlwc3MDh8OBnZ0dFBUVYWVlhfDwcBw6dAidnZ148eIF1NXVISEhQZjXVVVVUFFRgZ6eHjVnZs6cCS0tLSJfsnTpUowZM4YUEmNs165dEBAQQGZmZreSJIysxowZM7Bx40ZwOBxMmDChW5+gK7jZq1cvHDt2DLW1tXBwcCCFYhsbG6GrqwsNDQ0SPGZfm5CQQPqtK7sZ4IGdrq6ulFwM8K+xtGXLFgQEBMDX1xdxcXEwNDQk/lt3DNiQkBCyF3cHxLa3t6OpqenfAqMA8OXLFwwbNgyOjo6wtbWFnJwccnJyMHHiRHA4HL4CdN0Z+z5/CoQ/fvwYgwYNgpKSUrfnD3abrV+/HrKyspCSkkJmZibJVBoyZAhGjhxJ2oYx5v//xIjV1tZGZGQkIS/U1dVh9erVkJaWRn5+PtHqXblyJWHNnjhxAj4+PnxBqN/ZnTt3kJycDGlpaRgbG8PT0/Pf7v891mP/p60HhO2xHuuxHmNZRkYGDA0NISEhgXHjxlHpgV0Po+x/+/n5QUJCAgsXLsSXL1/Q1taG4uJimJubIywsDI8ePcL169cRHh4OV1dXvgIvSUlJmDx5MgBe2ti2bdvg6OgIR0dHApoOGjQIFy5cIPd98OABLC0tceXKFQD82m/MPYqLi+Hp6YkTJ07A3d0dcXFx5DffvHkDW1tbGBkZAeAdQr99+wYXFxcICwsTmYDNmzcjKCgIs2fPhpubG4YOHcpXWbR///7o168fX4X4zk5egRY/Pz9oaWmR9EO2E5STk4OEhATyzHv37kV2djbmz59PWA4TJkyAvLw8NDQ0MH36dAwaNAhubm6wsbEhv7V3714sXboUvXv3hpmZGUpLS38LxLL/nZ+fDz09PVy5cgVBQUHkWrY9evQIsrKyVFEYttXW1kJTUxN2dnaUfERNTQ0MDAwwb948mJmZwdvbm/zN1NSU6AO2tbVRjvPUqVNhaWlJ/r1hwwYICAhAWVmZpI+fPHkSISEhMDY2Rm5uLnJycuDn5wdzc3Pi4JeVlUFERATLly/vVk/swYMHGD16NAFh2QDZqVOncO/ePeTm5iI4OBhDhw7Fy5cvqYPWwoUL4e3tTRzrBQsWQE5ODp6enjh37hy8vLygoqJCsacZYzv9gwcPRq9evbBv3z4MGjQIenp6EBMToxjOnz59gqenJ5WKXVBQAElJSUydOhUfPnzAtWvXoKysTOZBfHw8BAQE4ObmRhh4wH+O+Q7w2FVqamro27cvPDw8sH79ejKW8vLyICgoiMGDB8PR0ZEUeps2bRokJCQgKCgIGxsbCAgIYPLkyfjy5QsaGxuRl5cHa2trDBw4kO9+R48exeTJkyk91dbWVhw+fJiw8pj7Hz58GO3t7Xj16hVmz55N2I8tLS0YM2YMREVFceTIEfz48QM/f/5EeHg4SkpKSGGNFy9eoLOzEy0tLRgyZAg8PT35gJRJkybBzs4OU6dOJaDH6dOn0atXL6L9d//+fYiLi1OMWeBf+qBdpTUAHsupX79+kJeXx6xZs8jaO2HCBAwcOJAqdhITEwMFBQXIysrCzs6OzCGAN5c9PDwwbNgwVFVVUfdob2/HggULYGlp+Uem/Pr16zF06FByz5s3b2LTpk2wsLCArKwsX1HE27dvIyIiAtbW1lThOn9/f/Tr1w9nz57FhQsX4ODgwHcvgHdgHjp0KERFRVFcXIy0tDQICAggKysLdXV1WLhwISQkJIjm68+fP1FZWYm9e/fi9u3bFHN9/vz5pDAQU9yFmS8/f/4kwPi7d+/IGjFt2jT069cPhoaGEBAQQHh4OFU0q+uzMpaSkgIzMzOK/f87Y57x8ePHkJGRgaysLIyMjFBQUED66dChQ1BUVIS5uTkGDBgAW1tb6OnpAQBhn+bl5UFUVBQmJiZkzWHW/+/fv2Po0KHQ19cnwS32PsMAsbt27SLjcvny5ejduzfi4+Nhb29PadUuX74cUVFRsLW1xYQJE8h7stnunZ2dCAoKwoABA9DZ2Ylfv37Bz88PGhoafCnNzFi7cuUKOBwO7t27R61DGzdu5NPzPHHiBGxtbUkbXbt2DbNmzcKyZcvQ3t6O9PR0aGpqQlpaGklJSSRIWFpaCnl5eRgYGMDJyQnOzs6wtrYm474rAMQU7Onbty/l99TX10NbW5vS9Xz16hV8fX0hJiZGAiTt7e0UECssLIzY2FgSsNi+fTvi4uLw5s0b8r2GhgbCrmPb1atXYWhoiJiYGCp7Z8SIETAwMCDgC9O3gYGBfJrA8+bNg7+/Px87zsPDAzo6Ojh9+jQF5AI8MDIpKQnOzs5EOmHgwIF/LPTZHYAO8PZBMTExiIuLIy0tjTDxAwMDKeDv2LFjSEpKQp8+fcj4qqiogI6ODry8vMielZ+fj3HjxlHFwboGvAHeeJGRkcH9+/exf/9+rF69GmPHjiVtdejQIYiIiGDKlCmUhAITsPfy8kJkZCQGDRoEGRkZ6jvz588Hh8OBk5MTAfbYsgFCQkIYP348BfrduHEDurq6xOe8evUqBAUFu9Vm7wrAMkE9pk3U1dVJILmqqgqxsbHYvn07317e3NwMExMTpKSk8P12S0sLyW749OkTOjo6UFZWRvaQXbt2ITo6GlJSUpg/fz5J1V+1ahViYmKo8ZSXlwcJCQmEhISQTBhmDDBArKKiIgls/0dlX379+oXW1lZST0JcXJw8z5/kdNj32b59O9LS0vjGOtseP36MIUOGgMPh/FvN8srKSj5NcX9/f2RmZlLv1NjYSNWxqK+vx4gRI/iA2H379qF///7o6OjAihUryNnDxcWFnBXYZ42Ojg4EBAQgKirqH2e5Mfbu3Tt8+fKF2i97rMf+u6wHhO2xHuux/9XGdhoOHDgADQ0NHDt2DHl5eXBzc0NoaCiVxto1ZQYAKa6wdOlSvujzwYMHYW1tDUlJSRgYGMDDw4OAguzvZmZmQl1dHUuWLIGTkxPCw8ORnp6O0NBQaGpqYsiQIdDU1KT0Y69cuQI1NTV0dHTg0KFDfJVUt2/fTlVSvXv3LkaOHAlFRUVKB/Lw4cNQUVGBtrY27O3t4eTkBHNzc9jY2GD06NEYP348HB0diUO0du1aODs78wGxnZ2dyMjIIO/V3t5OMR0qKythZWUFExMTcohlH5CZNmUAgfj4eJKGxYAIu3fvRnx8PKysrNC/f3+sWLGCtElmZibk5OSwceNG5ObmwsrKCoaGhti/fz+5T3f9xxSKYBhAjx49gq+vL4KCgvhYqi9fviTvd/DgQeTl5aG8vJy086dPn6CqqgoTExMsXrwY+/btQ1hYGAEMTp48CSMjI3h6epLD+9GjR0l7Mfbt2zdMmjSJVEeOjo6GiIgISkpKYG1tDSMjIwL03rp1C2lpaVBRUSEgO7tAgaamJpV+CoCvIEJTUxM+f/6MsrIyGBoa4uHDh5g6dSpUVFQI87g7h7WxsRGBgYGYNGkSAJ6z7O3tjX379qGxsRFHjhwhjAZ2u3d0dODp06cwMDDAhAkT4Ovri169eiE3NxcAD/RydHQkLKnOzk78+PEDwcHBcHV15Zs7bMB8+vTpGDlyJJlnS5YsQUBAAKZNm/aflhxh7K+//oK1tTWuXr2K8vJyDB06FC4uLiSlFuAFPZKTkzFu3Di0tbXh4sWLUFZWRkJCAnnOPXv2QFZWFrNmzQLAkx9YvHgxRowYQbF0v3//DnV1dXA4HMIQZD9XYmIigoKCqPYoKysDh8OBlpYW0QIFeAeQKVOmQFBQEAYGBtDU1ISRkRFaW1tx/vx5qKmp4ciRIwSE//DhAxQVFREdHY2XL18SFltMTAy2bNlCzd179+5BU1MTPj4+JNV2z549EBAQwPjx43H06FE8ePAAgYGBcHJy+m1Rrw8fPlAV55kDV2pqKkkBZcb6tGnTkJqaCi0tLbi7u1Ms1IKCAhgZGWHevHnk95l7NDY2QllZmfytO/v16xdp04kTJ0JLSwuPHj3CuXPnYGdnh+joaBL8YuzatWtIS0vjezd/f3/o6elh0aJFkJOTw6BBgzBy5EhkZGRg0qRJGDBgAAF1J0yYgD59+qBPnz5k7jO2ePFiSEhIYNmyZVSleHZbAcCsWbOQkpKCAwcO8FWaLyoqwqxZs6hgxKZNmwi7/tu3b3j06BFcXV0RHBxMMefZ92DeS0BAAMnJyb+t2M1cw27/xMREyMjIYObMmVi4cCG0tbWRkJBAAkTv379HSkoKkpOTMWnSJDLOhgwZgtjYWPz48QOFhYUQEhKiwDFmffr69Svmzp37W5AiIiKCMGJbWlrw69cvrFq1isiUdM0y2b59OwHgDQwMyJ5XX1+P48ePEy1RJk2/s7MT9fX18PHxgaamJjUHAd6+v27dOnh6elIBCqYY0KJFi/Dp0yfSXlu3boWIiAiuXLmCly9fIjQ0lLDm//rrLxgaGuLixYtYv349AgMDqYJjnz59wrx587BkyRJs3bqVSoEuKirCmjVrqIBWVVUVBg8eDGFhYcyaNQsrV65EeHg4jI2N+db/EydOwN/fH3JycmQv4nK51P7IsG47Ojowf/58eHl5QUpKClOnTiX73pw5czBo0CB8+vQJ+/btI2P71q1b0NfXR3R0NJFIuH//PpydneHn50eA2JMnT6JXr16wtLSkMmmmTp0KfX198m8G9Dl+/Dg4HA6MjY3JWsd+t+fPn2PkyJFwcHDA1q1bMWXKFOTl5eHp06eoqqpCdXU13r17xzc3urMHDx5QgU9G55LJbnn58iV69+4NDodD2JyMMUCst7c36uvrqbm3ZMkS9O/fH3p6epg5cyaVnfPu3Tvo6enxpegDvLllYWFB0u272rNnz5CSkoL4+HjMmzevW8blmjVrui3ABvBkMOzs7Kg98+TJk3BxcQHACwywM1t+/PhB1tHu0vvZ+3pFRQVsbGwwbdo0XL58GaGhoQS8A/hBybS0NHh6evLNv4qKCgwYMIAENdLT06GhoYEtW7aQMVVfX0/8Xcb8/PyINjLA82cVFBSgoqKCcePGwcnJCQICAlTWRXV1NcLCwtCrVy+SKcAEQf9kTFsw43L79u2QlZWFiYkJcnNzyfrdnT/TtR379OlD5tqf7MGDB5gzZ84/LhL769cvXL16FWFhYTAzM6MKz61YsQKRkZEwMTHBqlWrSB/U19cTv37NmjVUEGHGjBmQl5dHbm4ucnNzoaenBx0dHfKuDQ0NOHLkCHx8fGBqakrW6UuXLv1x/2G3ye8CJj3WY/8d1gPC9liP9ViPgVcQaOLEiVThiIsXLyIgIAAhISEUEMtO5cvPz4eQkBAprvO7COutW7dQVVVFHYJ+/vyJ1tZWcLlcvHjxAmPGjIG2tjZWrFhBnJZjx47Bzc0Ntra2BCRknN+qqir4+/sjLy+P0swEeCmLcXFxuHfvHgBgypQp0NbWRmpqKoYOHUqKcDDFDr59+4YlS5Zg5cqVKC4uRnt7O4qLi6GqqgpBQUGKsdje3o5169bB2dkZw4cPJylzbAdn6dKliIyMhJ6eHmbNmkUOLM+fP4elpSVMTU0JEMtuq3379kFdXZ08F8OuKCkpodqza3rVixcvoKWlRX2vra0N3t7e0NHRIYxYtm4vwO/sM85aRUUFAWK7K1aVkZEBGRkZ6OnpQUlJCTNnziQHlk+fPkFXVxccDgfx8fGYOnUqOjs7CVPo1KlTMDQ0hLm5OeTl5WFkZAQrKysYGBjA2NgYRkZGSE5ORkFBAVxcXKCjo4NevXqRSrlcLhcWFhYwMjIi7dTR0YEfP36goaGBgATt7e24fPkyDAwM8P37d3C5XGzYsAGenp5QVFREQEAA33tduXIFgwcPhrKyMmRkZMjBoavD2tzcjLdv3yIwMBDW1takD9+8eQMlJSXU1NTg/PnzfIGBhQsXkn7/+fMnCgoKICYmhl69epE0U4aJWVhYCCMjI2hoaMDT05OAsozzXVJSgo0bN/LJQzDAKNOXMTExpJAc01b/GTt06BBGjRpFAT/fvn3D6NGj4ezsjOXLlxMQgp1mffjwYVIMhc2G2bZtG4SEhMhcZ9LUuz7jmzdv4OTkBF1dXRw7doz627p162Bra0sd6u7cuYOhQ4dCWFiYsDLZB7MrV65g+/btZJ4DgIODA6nqLiEhgfj4eFRXV+Px48dQVlaGtbU1SY00MDDAly9fyHMyRVZKSkrg5eUFf39/AsQePHgQxsbGUFZWhqGhIVXB+HdALMA74J07d44c8JjnvH//PjQ1NYmsAsBbu0NCQuDs7Ey0KQFeUO13B62lS5ciKCgInz594vsb+7kmT54MAQEBREZGks+PHTsGJycnDBw4kAJi2dft3buXYpIGBweDw+HA29sbiYmJSE5OxsSJExEfH4/ExESKFdSrVy9wOBx4eHhQYCnAA19kZWUxe/bs3xaB2759OwwMDCAmJkYVoKurq0NwcDCpgs60d2pqKt/+VVlZCRMTE5Jiyv4+AAwYMAAcDgeLFy/+I8Oq63VJSUkQFhYmxfyY1Hqm+jtbpod5lm/fvmHkyJGQlpZGRUUFJaUhICBAsSi7auoWFRUhMzMTa9eupcZMREQETE1NsWfPHvL87PeoqKiAlZUV2beYLBM2YFlZWYnx48djxIgR3Ra+aWpqgpeXFzQ1Nan3+vXrF0JDQ0ngCuBJmTD6ld1ZZGQkOBwONDQ0qDXwr7/+wpQpU8j3Ll68iIiICHh5eVHscLZxuVzMnj2bVDHv06cPBgwYQMZaVVUVhg0bht69eyMsLAxlZWVkfDY3N1N77+XLlxEQEAA7OzvyjmzNaaZdu2piDxo0iGQvzJ07FxISEpgwYQLU1dWxaNEiMrbZQCyz1zHzT1ZWlmiMKisrQ11dHenp6YRN+vz5cygrKxOpCcYuXLiAtLQ0eHh4wNLSkno2Rjri1atXGDlyJBwdHcHhcEgRKiUlJSgoKEBRUbFbWabfWUNDA27fvg1XV1dwOBwSdGH8AR0dHar4H2MPHz6EqKgoxeicMWMG5OTksGPHDmzatAm2trawsrIiwdKWlhaoq6tTvizznFVVVdDW1ibjjJ1Wz9572G1y9+5dnDt3Dnfv3iVA26JFiyAgIEDdo7a2FlJSUnB1dUV1dTX5vevXr8Pc3By5ubmQlJSkgkKnTp2Cr68vVVhs7dq1kJWV5ctEAoC5c+fC3NwcqqqqcHV1pbIZ6urqqH33yJEj0NHRwfjx4wnhoKamhswPhnmppKREsa3ZbfH9+3dcvHgR/v7+VHYRABLkYq5lNI0FBQWRmZlJvltcXAwZGRlwuVxMnToVBgYGfBIlXY2trQ/w/NsXL15gwoQJsLW1xYoVK7qVGGD3HUMu6K4d/539E4bopUuX4O3tjaCgIDLfuVwuAVPXrVuHBQsWwMbGBlFRUeQMUV9fj8TEROjo6JB6CM+fP4eNjQ2RbmKC94zPy3wnIyMDgYGBxOdJTU2Fvr5+t0HJrvanTLge67H/DusBYXusx3rsf709efIE+vr6EBMT46tUf/HiRQQGBiIsLIwPjNu4cSMkJCRgampKRciZzb2pqYmq5s44Rx0dHVi5ciWCg4MJo5QBA9hgSmdnJwIDAxETE4MhQ4ZASUkJEyZMAIfDIandXl5e5DDMWFNTE4KDgwlwcOPGDSgpKVFasGVlZbCwsKCco67Pn5WVBXFxcZiZmWH8+PEUa6e9vR3r16+Hm5sbgoKCKIdw5syZREx/xowZMDU1hb+/PwFrKisrYWdnB3l5eT6QITs7mwACJSUllNNeX19PAKuuAE51dTW0tLQIc5WdpqqhoQEHBwcUFhZSh/Su6W5d3//hw4cICAiAra0tcQ47OjpQU1ODgIAAwqJZvnw5rK2tMWnSJALEMtIEgYGBePToEXJzc7Fs2TK8evUKXC4Xx48fh4eHB0RFRbFv3z4cP34cO3bswPjx46kK34zOLFNBnjEGiDUxMcGNGzfA5XJRWVmJYcOGITAwEMuWLQPAKyRkbW2NsLAwmJqaIiIiAlOmTMG5c+fQp08foh/KtszMTHA4HBgaGlKHNcYaGhowZcoUuLq6Em2t2tpaAnhFR0cjKioKYmJi1O+/ffsWrq6u2L9/P/m9kSNHgsPhoF+/fhQoAfBS7l++fIn58+djwYIF2LJlC7lHZmYmREVFYW1tDQ6Hg8zMTDKHiouLYWNjAxsbGzg4OFAsrv+s411XVwcPDw+IiIigf//+1N++ffuGMWPGwM3NDZmZmZT+aXNzM86ePQtBQUGiDcccHL9//w4NDQ2+StFdi1sAPFDA0tISPj4+KCkpQXNzMz5//gx3d3dER0fzvdezZ88QEhICKSkpEojpmg4J8A53zs7O4HA42LFjBwBeGq+QkBBZL2pra5Gbm4vp06dj3rx5OHToEKytrfH+/XtMnjwZIiIipBpySUkJ3N3d4e/vTw6aKSkpOHToEO7fv98tWNWd3bp1C8HBwQgNDaUOeFVVVZCTk+MDmM6dOwdxcXE4Oztjz5491N+WLFmCQYMG4cyZM6Q9b9682W3wpSuLSEJCAuHh4XBxccHMmTMpINbZ2RmDBw/G+fPnqeumT58OXV1dLFy4kCrAExkZCWVlZbKWAKD2h8WLFyMnJwdnz55FRkYGOBwOtm7dyqexOGPGDPj7+5N7Hjp0iKwhjMXFxUFcXBx79uzB8+fP8ejRIwQFBcHGxoa0PcP0Sk5ORlBQEADe+sYALfv27YOEhASuX79OtU9ubi4EBQUxfPhw6rm60wlnAF+AB76JiIhg2LBhAP510C4qKkJJSQmEhYUxfPhwXL16lfzW69ev4e3tDWFhYUhKSkJXVxfz58/Hhw8fyG8KCgqSfZv9DBkZGZCUlISXlxesra0hKytLMQCjoqJgYWGBzZs382ngPnjwAKqqqmhvb+82y6SoqAgtLS2UVMeBAwewevVqbNiwgQAzLS0t8PHxgYaGBpn/ISEhVD80Nzdj2LBhWLp0KQDe/rh79264u7sjMjKSgJtHjhwhY3j16tWIjY1FdHQ0kZ5g7NKlS6QYFbO2sIG2xsZGREdH49atW6ivr8etW7cIqMgEVJ88eYKkpCTIysri0qVLAHiBi8DAQNjb22P06NGEsX7p0iWEhobC3t4e9+/fp4C9vLw8DB48GGlpaRRztLa2FufPn4eLiwtCQ0MJ03/KlCmwt7fHwoUL+YDYyMhIspZ9+fIFK1aswMyZM7F8+XKiSa2iooL09HTCiF2/fj0MDAyQlJSEmpoaPH36FMHBwUhPT8eTJ08gKipKgiULFixAREQE8YeqqqowcuRIODk5YcKECWhoaMC3b9/w+PFjvH79mgrG/8k6Oztx6tQp+Pv7w9fXF5GRkVBQUCBBgY6ODpw6dQoyMjJUtgPzu+zsm0ePHlESVOfPn4eIiAhJ7WfWSrZ2Kttev34NGRkZao1k+urKlSu4fPkyNdczMjJgamoKVVVVeHt7U0UVly1bht69e1Og6tu3b2FkZARnZ2eyvtTU1CA8PBx9+/YlmR8Ab9yHhYUhNjYWHR0daGhoQGVlJcTExPiKlbL9vVevXuHhw4fUXpKdnQ1vb2+iB858f+fOnbC1tYWOjg6MjY1haWkJS0tLtLW1oaGhAf7+/li5ciVpm+PHj2PIkCFISkpCU1MT7ty5gxEjRiAmJoa0LXNfpvZAV0mIvLw84pNzuVw8fvwYpqamUFNTg5SUFJ9ETldjA7C3bt3CwoULiZ53W1sbUlJSYGdnh1WrVhE/d8qUKXj37h0FwEpISJDvdC3+1dXY+zE7C+RPxuVyUV5eThFPysrKoK+vT0Dvixcvonfv3jA3N0doaCiRtvj58yeysrLIfW7cuAFFRUVwuVwcPXqUWm8bGhqwadMmtLa24tu3bzhy5AgCAgKgqakJGRkZKnPmd8aeozt37uSTiemxHvvvsB4Qtsd6rMf+11l3B+5Dhw7BwsICbm5u1MEY4B0ybGxsqCImmzdvRu/evbFv3z4kJiYSp5Pt5Lx+/RoxMTF87BYmUrx161aUlJRAW1sb+vr6JHW/oaEBR48ehY+PD8zNzdHW1oafP39CUVERwsLCFPOvvr4eFhYWsLCwQFZWFlavXg1vb28qXefu3btUoRbG9u/fj969e2PQoEGUjiFj58+fx4MHD7Bu3TrY29tj1KhRFFuovb0dGhoa8Pb2pvT+jIyMKF3YO3fuYODAgQgKCiIslQcPHiAhIYHP2Zs/fz4mTZqE69evQ1xcnGJaFBUVYenSpXzALfCvIlfx8fHkMwZwDQoKgqSkJCQlJcnBp7S0FBwO57csAWZslJeXY9KkSZQeZXV1NeLj4ymphdWrV8PKygqpqakUI1ZVVRVqamqQkZFBUVERKWbV2tqKY8eOwcrKijBgNm/ejICAAMJmePv2LTQ0NBAaGgoXFxfMmTOHAgu4XC6srKwgLy9P9DTT0tJw8uRJihFSVFSEcePGYfbs2eTZ2tra4OHhgaNHj5J3ZdJGz507hz179mDo0KGwsLAgh3Cmrz5+/Ig9e/YgPz8fXC4Xy5YtQ0pKCjkYrlixAqqqqoiJiSHP0NDQgODgYPj4+BAwsK2tDQMGDEB2djbWr18Pc3NzvoIfjLFBBAYEv3HjBpqamkj6fUpKCn79+oXm5mbs2LEDEydOxNSpU8kB4z+SftbdYeXt27cYMGAADAwMqCJ2AA+I9fT0hIqKCjo7O5GamgorKyt8//4dHR0dCA8Ph5WVFcX4+fTpE/T19X/LWGOMee4XL17AysoK4uLisLa2RlRUFLy8vNDS0oKdO3di8eLFSE9Px82bN9HZ2YnXr18jKioKysrKBLxgH7bq6+tRVlYGTU1Noke9b98+Sj6iO7bNz58/oaysDA0NDUhKSlIsPzYQGxAQgHPnzsHR0RFOTk5EB/af6rA9ffqUL7Pg5cuXMDMzw5o1a/jYQu7u7jAwMKAKjAG8uW5nZwd7e3vY2Njg1KlTaGxsxIoVK+Ds7Nwti6agoAASEhIoLS1FXV0d0tPT4ejoSAGxx48fh66uLmbPnk2uYypy37p1q1vA2d/fn8g+PH78GCYmJkhISEBqaip69+5NpS5PmDABffv2RXFxMZnPMTExmDlzJnnvqVOnQlJSEkZGRhASEsLUqVPJ9UzavaCgIJycnGBqakrW+bS0NNLnR48eBYfDIexUxsrKyiArK0sVJTp48CCkpaWhpqZGmOvsedXa2ooHDx6gqakJJ0+eJIAuk3Gwbds2fPnyBd++fYOrqysBirhcLvT19SErK0sKPQHAypUrISMjg23btqGiogLTp0+Hk5MTxowZQ5h/TKEftsbkzZs3ERQURMDQ6upqrFy5Er179yYFrgDA09OTApOzsrKwY8cOPHjwAP7+/lizZg1flsnNmzcRGxtLaWVOmzYNqqqqZE4aGBgQTer6+nr4+vpCR0cHjo6OMDAwoAILAI+9r62tjZ07d8LDwwP+/v6YPHkyjIyM4OHhQa1HixYtgpSUFAYPHgxDQ0OIiory7WOXL1+Gu7s7Jk6cSF374sUL3LlzB6NHj6YCBPfv34eSkhLCwsIIEPv06VMMGzYM/fr1Q1xcHOTl5TF//nxkZWVBXV0djo6OZM0/d+4cIiMjoaGhQUCmJUuWQFJSEqNHjyZ+AtMmjH3//h3Xr1/HrFmzyDyZPHkybG1tfwvEdg0as9PRCwoKoKKigunTp+PTp09oampCUVERNDU1ISUlBTU1NVhbW4PL5eL58+fQ0dHBnTt3MHPmTCgpKWH37t0E4Ad47LvExEQ4OjpSmriM/dM95evXr7h69SrJlIiNjYW0tDTx5RigVkZGhq+YK/teDx48IMWzGL1ndnBgz549+PXrFw4ePNht4aHa2loEBARQzGLGUlJS0L9/f7LW5OTkQF5enkhBzJgxAxwOh/Ltli5dCg6HQwUS37x5A319fTg7O5O2LC0thZWVFYKDg1FUVISioiIEBAQQdun8+fOxfv16NDU1/RZU625PZpiX/fr1Q25uLoqLi6Gurg53d3cyjsvLy3H06FHMnz8fO3bsoPSIo6KiMGzYMGzZsgVhYWHw8fFBaGgoTE1Nif/y5MkTSmKLsQsXLoDD4RBAj3m+Bw8eQEJCAhwOBwsXLgQAjB07lgS2//Q+bNkWZkz26tUL4uLiGDVqFOrq6tDe3o5x48bB3t4esbGxCAgIgJycHOnvrVu3onfv3tDW1oaMjAx8fHyQkZFB2uNP7Tp69Gikpqaiqanp32YMsfdf5rvnzp0jshpHjhyBjIwMtmzZgj179pCAJjtb5eDBg+ByuaitrUVoaCgWLFgAcXFxap24d+8eoqKiqHPZ6NGjweFwYG1tTYK9v3veroFVERGR3+qd91iP/VdaDwjbYz3WY/+rjL1Rt7S0UBt0aWkpbG1tMWzYMD5H//79++TaX79+YdGiRYR1+fr1a8jKyiI6OhpPnz5FY2MjPn/+jNDQUPj4+FD3rKqqgrW1NZV2IyUlRaXdVFZWYvr06VSaI6NXa2VlBXV1deoA9ePHD8TFxcHV1RW+vr6keEN6ejry8vJw/fp1KCkpkYMaOx2YqdbL1kfsCm7U19dj5cqVcHBwoIDYSZMmwdjYmPy7o6MDL168QL9+/ShHC+A5wjIyMkQugN0mBw8eJKwJpmAJh8Mh8gvAv7RH2QUtKisrUVtbS9Lbjx8/DhEREYp9BfCKeaSmpqJv377Q0dHB27dvcfr0aYqR1p11ZbhkZGRAT08PsrKy0NbW5is0lZOTAzs7O8THx5M0fqYqvYuLC1+BsNbWVpw8eRKmpqYwMTEB8K9D3bVr1yiHf/LkyXB0dMTcuXP5GMkxMTHQ1dWlggTM37p7Fy6Xi7lz50JdXZ16h8+fP1OO+sWLFzFw4EBYWFhQadd79+4lYHJGRgbk5OSwf/9+vHv3DgCvr0aPHk2CGomJiXBxcSEBBYAHZjc0NJD71dbWYvXq1TA3N6f6eNq0aaSfOjs7UV1djSdPniAtLY0CCI8cOUIBsV3tP1KAgT02KysrUVVVRfqzurqapDMWFxeT73V2dqKwsBAuLi4wMDCAjIwMBbheuHABgYGB0NHRQUlJCfbu3UsYcf+UdQLw1hoHBwcYGhqiqKgIHR0dmD59OpSUlDB69Gh4eHjA2NiYMKErKioQExMDVVVV3Lp1i+9enz9/hqWlJQ4fPoybN29Sh/q2tjYsWrSICtAw7ZiWlgYOhwMLCwu8evWKajMGiPXy8oKtrS3KysoQHBwMBwcHAjL+uwMeu79qamqocTlz5kz07dsXZWVlZDz9+PEDgwYNIm0C8KqjM2OntbUVN2/eREJCAszNzWFvb4/Q0FBYWVmRIBlz3ZkzZ6CoqIj9+/eTz+rq6pCRkcEHxF6/fp0KKgwdOpQcQtmZD2yztrZGREQEmpqasG3bNsjJyUFMTIwA5ez5PX78eIiIiGDnzp349esXli5dCkFBQSxbtgxfv34l7MM3b95g7969EBERIXqhAI85d/LkSfz9998YPHgwREREyH+Z+3V0dGDatGno06cPtm3bhurqatTU1CA4OBjW1tZk3aqtrcXdu3fx119/EQZjV3v69CmSk5Px8uVL8t4DBgyAoKAgBRS+evUKenp6JLukuroaMjIyRC+Yy+Xi58+f8PPzIwxRxtauXQtTU1PC3G5qasKhQ4fImCkqKkJYWBg8PDyoQNmvX78wb948mJqakmAUO313z549kJSUJNkWfn5+pNgOY0yWSUREBLmupKQEqqqqBIxhdBjZbL6mpia4u7tDX1+fjFn2+vXo0SOEhoaiX79+WLRoEfE/9u/fDz8/P7KmVVRUYMWKFYRVeu/ePSQkJMDExAQHDhyg2ontswD/0pxlGHld97/79+9DRUUFoqKiBBx/9uwZfH19ISgoiLKyMrKP1NXVwd7eHi4uLgS0O3ToENHDLC8vR1JSEinw9f79e8TGxsLd3Z0PiGWMy+WSPkxNTe0WiDUwMMCAAQP4JGjYlp+fDxUVFaSlpRGApr29HadOncLNmzdJm2RmZsLCwgJnzpyBrq4uX0FR5nsvXrxAcnIydHV1+bIWun63O2MDa8x3Ozs7CRDLXl9Pnz4NBQUFviJjjN2/fx9WVlbIz8/nS9e+evUqBg8ejHv37pH7nT59GrNmzUJqairZw86ePQtDQ0NERkZi06ZNOHfuHMaPHw9paWmyPre2tmLo0KFkL2DYiQwQ3djYSKXbM//PsEIZINbR0ZFkqJSUlGD48OGQlJSEp6cn0a4/dOgQZGVlfyvF0bUtGWtqasLRo0dhbm5OgOIjR45AQkICsrKyMDMzI9JMXfuH2QcLCgpIUd158+aROTxr1izExcVR13Z0dFDBbYZR7uPjQ5ifAG+sjxs3DgUFBRAQEMBff/2FS5cukUKaFhYWZD/rCpQz7ZidnQ1xcXGIioriwIEDpCAa83zt7e3IysrCsGHDMGTIEKowoZOTE6SkpHDq1Ck0NzcjPDwcqqqq1DN2bQcAmD17Nnr16gVra2sS4Pqdb8Luhxs3bqCkpISstbW1tairq4Obmxu1dltYWEBRURFqamr49u0bUlNTISkpiY8fP6KlpQXh4eHgcDhU0K+xsZFkxDD7QltbG/bv34+CggKEhITAxcWFBH66tie735lA4O/mcI/12H+19YCwPdZjPfa/xtgbck5ODiIiIhAaGopx48YRZ4NhTQ0bNqxbp4X5DeagzFxXUVEBVVVVmJmZQUtLC/b29rCysqIAyvb2djx8+BCKioro7OzsNu2GKXjz5csXiqH48eNHUrTGxcUFqqqqxFFijKlGCvDYu9LS0oT9OnHiREhJSVHgcm1tLUaMGEFVl83Ly0NSUhK8vLxw+PBhAo42NDRg5cqVcHR0xJgxY9DS0oLg4GDCXJw9ezYuX76Mt2/fQlVVlWhwtre3k/dgUnq7poxqampi3rx5pE1XrVqFvn37Yt26daiqqsLt27cRGBgIKysrqgiXvr4+1NTUMHr0aMLq2LRpE/r27QsfHx8kJyfDycmJsA+8vLwgLS1NKjQDf04lZDugp06dQr9+/bBv3z5MmzYNxsbGiI6O5itcsWjRIiQkJJCDVk5ODhwcHEiaZnf3PHToEAYPHkwBsMLCwli8eDFp/6amJkyZMgWOjo5UWwE85oOTkxM5ZP3JDhw4gOTkZCgqKlJMrjlz5sDY2BgmJiYUiHPlyhUMGjQIhoaGKCwsRFBQEMzNzdHR0YG//voLOjo65AAE/Gt+NDQ0oKSkBAkJCRg9ejQWLVpE+m7x4sXw8PCAhYUFhgwZQtJ0v379ipycHJiamsLT0xNBQUEkJRjgjRUTExNISEhAXV2dT8ft6NGjEBISwtChQ/9toYbfGbtv5s6dC1NTUxgZGUFBQYEw6N69e4fw8HB4e3tj586d1DVxcXHgcDhwc3Pj08q8ffs2Ro4cCXl5eVhZWSEkJIR85z8CxL569QpmZmYIDAzE4sWLoaGhQcZ/aWkpBAUFqQDGs2fP4OnpSWkObt68mRya5syZA21tbQgLC1PA8vfv3+Ht7Y3s7Gy+Zzl58iSuXbsGbW1tODo6UlqdTDvu3LkTo0ePRkdHB0pKShAQEAAXFxcKAOvO2L8THx8PfX19ODg4YMyYMeTzsWPHom/fvhg1Tn7z6wABAABJREFUahRmzJgBDw8P2Nvbk9+8c+cOPDw8iFwH227cuIH8/HxoamqCw+EQ+RPGPn/+3K2MDAPEOjs7Y/z48XyBjY6ODri4uFBsbuY7zc3N1NrL9OWJEyegpKREUqaZz9mH/YkTJ4LD4eDUqVNobW3FunXrwOFwkJCQgKSkJOrgyVQ+745RXlNTAx0dHfTu3ZuwRpm5VVNTgwULFqBPnz7Q0NCAnp4ebG1tyW8XFBRg8ODBBKC8cOECxMTEMG7cOAA80KahoQGGhobo1asX2TsZUERKSorIEAA8MMnMzAzTpk1DWVkZTExMIC4uzleQxsPDA5mZmdRnAI/l6+3tzfeO7e3tyM3NhaamJiQlJfmAnQsXLkBGRoaPBVhaWorc3FxKQ7exsRHW1tYwNTXFggULsHLlSvj4+MDExARtbW0EwJ0/fz5hL5aWlkJCQoIwZxsaGgiw1djYSMbSypUrERISgtGjR+Pw4cNUHzHW2dkJf39/DB06FAAvOMDhcKCiokI9f3l5ORITE2FiYkIVkmSDRwcOHICRkRF27tyJ3bt3Q0VFBZ6ennj69CnVDjExMZCSkqLa+ty5c1BSUiJ9yqxZjAZoZGQkFfjatWsXHBwcYG1tTQJzAC+ANGTIEHh4eBAw70/g5aRJk7oFYiUkJAhQs3//fmRnZyM3N5eq2M4AsdOnT+er5H7//n2MHTuWSLWcP38eGhoalD/FjENm/FdWVpL0coAXXJ03bx42btxIgN7u1nA2yF9TU4MjR45Q4PugQYP4gNgjR44gKCjot23Tv39/UgiWsaamJoSEhFDBgWPHjqFv377w8/MjweNjx44B4PmHgwYNgry8PAwNDeHg4ECCMowFBgZi9+7dOHbsGOWntre3o6CgAHv37qXWwBUrVmDOnDmkHRkg1sHBgdLerqmpIeNr586dyM7OJqD/n/wx9t+Ki4uxZMkSHD16lARJTpw4ATk5Oaxfv54EFL29vSlfYNeuXVi2bBlmzJhBMjOam5upgm4AL2Nh7Nix1D0ZCZARI0aQuXDhwgUSrNqxYwdOnjyJgIAABAUF4ePHj9DU1ERWVhbpk6dPn8LU1BQWFhbUONi6dSslRebo6Ii+ffuitLQU+/fvp7JTGKC7a32DtrY2/PjxA15eXiRAdebMGYiJiREt69bW1m4zg6KjoyEoKEhqQAQGBv52XLPbZP369RAUFISRkREVBHr9+jXU1dVJkO39+/eIi4tDbm4uJCQkoKurCykpKapo2q9fv2BmZgZra2tMnjwZy5cvh5eXF8zMzKhgK9uvOnz4MPEr2PP8yJEjVL9v3LiRr9Bbj/XYf7f1gLA91mM99r/OmMIGc+fOxdixY6GnpwdjY2PC7ispKYGjoyNCQkL4DindGbuAyN69e7Fq1Srs2rWLSmFavHgx8vPz8fbtW4SGhmLRokV8aTfl5eV8aTeXL1/G2bNnKebHs2fP4ObmRgGx7EPT+vXrsXr1akontr6+HrGxsejbty/mzp2L7Oxs+Pr6wtXVlThV6enpUFBQwKxZsxAfHw8DAwNMnz6dsCUbGxuxatUqaGlpYfny5diwYQMUFRURGBgIMTExPHnyBAAPZBMWFqbSrOvr62FpaUkVSFqxYgXk5ORw+/ZtygH98OEDlixZAnFxcSgrK8PCwgJ+fn7EETt48CBUVFRw7NgxLFq0CEFBQfDw8CAgx927dzFw4EAMHDgQycnJxGmLioqCq6sr0Q1jQMvuHH/2Z8OHD4e7uzt1QN+2bRu8vLwwcOBAPo0vRhOvo6MDEyZMgJWVFfkbMyY6Ojpw5swZvHnzhnJyGcbp7Nmzoa2tjWXLlpGUvubmZkydOhUuLi6YMmUKeS+m2mx3xtYnBniH1smTJxPgE+AxBpWUlLBhwwYsXrwYcnJyCA4OJoD+zZs3MWrUKOjo6CA4OJj0w549e2BgYMAHHPzJMjMzoaCggB07dmDHjh1wdXWFnp4ecca/f/+O0tJSDB06FImJieRepaWl0NbWxtatW5GdnQ1paWkkJCSQgxRj+/fvh5ub23+6+BZjixcvhoKCAs6dO4eWlhaisVlRUQGAJ00QGRkJU1NTqmhfYWEhVq5cCS8vLwQFBZFUd3a7fP78GT9+/KAAJyZF/t+1H1uawMbGBpqamqTy9N69eyEpKUkOa/X19QQAevHiBWmTefPmgcPhYODAgQB4a4yPjw+srKwIaPLp0ycEBwfDycmp27RWxhjtY0dHR2pMsVN3lyxZgujoaFhYWIDD4cDZ2Zn02+8YSgCPwd6rVy/MnDkTGRkZpFI4Y7m5uRg8eDDc3d0pNtDcuXMRFRVFio1ZWFhQetiMff78GXl5eXBwcCBg3e8Y02wgduzYsUhOTubrK2aceHp6oqamhi8NfODAgRR41tHRgY8fP+LVq1coLCyElZUVRowY0S2DNi8vjzo8r1u3DuLi4rC1teV7VkbDlAHvmOf88OEDQkJCEBwcDHl5eYphzlhFRQWOHTuG48ePk75oaWlBUVERzM3NMWbMGLInFhcXQ1JSEtbW1vDw8ICTkxOMjY0xcOBASEtL49atW6SoT0lJCdTU1CjNy+zsbJiZmUFPTw96enqQk5MDl8vF9OnTicb60KFDYWZmRgIGTJtkZWURdlR3tnv3bujr6yMuLo466L958wY6OjoU6PX161eSPpyenk61ya9fv8j67+fnh/Hjx/Np6mZlZWHWrFk4c+YMBVZ1dnZi9+7dWL58OcXkXr58OaSlpTF58mTY29vDwcGB2qt//vyJw4cPw9/fHxYWFmRcV1VVIS0tDX369MH27dup97137x6SkpIgJydH5GMYO3r0KKZNm4ZVq1aRz969ewclJSX4+PhQPs6QIUOQkJAAgAc6HT9+HHV1dZCTk6Oesa2tjUhIWFlZUfP277//hqenJyQlJfme882bNxg2bBiMjY0pwPjMmTPYvHkzzp07R2UQMEAsu1gXkx6enp4ORUVFhIeHQ1NTE0FBQZTWaUFBATQ0NDBmzBiqENL58+cxffp0sgZdu3YNffr0IWsEW9P25MmTuHLlCjVH0tLSoKCgADs7O5iamsLV1ZXILLHbgc2AnTNnDimwGRQURNLUAd4Yl5GR6Zbdyx7fzP9/+vQJPj4+UFVVxYoVK5CVlQVfX19Kgurnz59IS0vDli1bAPDWtfj4eIiLixPQv729Hd++fcO7d+/4UtXb29uRlJQEBwcHCgAEeHJEQUFBFAuXeUcREREsX76cD4h1cnIi84Wx+vp6Egj7nQwRuy0Z2ZsNGzZAQECAjOf379+jsbER7u7uJKPr69evsLKyAofDIYzWtLQ0yMnJISwsDKqqqjAyMsLs2bNJAKGurg7Xr19HYGAglbXT2dmJZcuWQUJCApMnT4a2tjbMzc3J2P77778xevRo9OnTB0ZGRnB1dSUSCwybNSEhgQChT548gZWVFYyMjHDq1Cn4+PjAxcWF9O/y5cshICCAadOm4dq1a3zZKdOmTaNkLNj/bWhogIuLC9G3ZV/b3NyMrVu34vbt29R47t+/P3r16oXZs2fj0aNHWLZsGRwcHODr68sHxLLnxoYNGyAjI4Pdu3cjJCQEgYGB5DcrKyvh6uqK5ORkkgnD6JinpKSAw+GQMcF+lrq6OkyYMAGenp4IDg7GxIkTyXo7b9482Nvbw97enlqLjh49SvTOT58+jcDAQDg7O1PEkh4GbI/932g9IGyP9ViP/a+yZ8+eQVdXlwII3717BycnJ5ibm5PPduzYgaSkpH8M5nSNFrN1ynbv3g0lJSXcu3cPjY2NCAkJAYfDoYoUMGk34eHhVLqclpYWbG1tISkpiQEDBhD24qNHj+Du7g5NTU0KBKurq4OTkxM4HA5VLIyxRYsWwd3dHba2toiIiCCOZnFxMVU1l5EF0NfXR2pqKmGO1tfXY+fOneByuWhqaiKFkdgV45ubmzFp0iTiXE+bNg1+fn5UlfOmpiZERkYSXcGuFXoBHnBx48YNPH78mPz90KFDmDx5MnUAOH36NMLDw+Hm5kYdpJjfqq+vJwenp0+fIj8//49ALPv/Fy5cCA6Hgz59+vAVumCA2MGDB/OBgcxvXLt2jUrvZOzr16+IjIxEZmYm3N3dAfCKK1hbW1MMRXV1dT4gduTIkRg1ahS5x8SJE6kUt+4sJSWFtBmbZXfmzBkUFRVRh9dbt25BRUWFr+rtp0+fCLjc3t6OdevWQUNDg4DBbLDu+PHjVCEWgHegtbS0JMxEhmFjYmICFRWV36aqnz59GmPGjKEOgkeOHIGGhgaSk5Mp8I9t/1kgtrm5GaGhoYQVeuDAAcjIyJD7M+D08+fPSfptVlYWVTl9x44dpGgdu4r9uXPnSIokAKJNyOFwCEvpT8a0PZfLxdu3b0lVeeawxm6jHTt2YO7cuRRLbeLEiZCTk0NUVBQGDRpEfZdhitva2sLa2hr29vYUU3fDhg1ITU1FdHQ0rl+/Tt7r+/fv0NbWhr29PQoLCxEcHAwtLS10dHQgLy8P4uLiOHv2LF6+fImCggJ4enrC0dGRBG26m/vjx4+HqKgoqfze1taGc+fOQVVVFV5eXuR7TU1N1Nqbl5cHMTExXLx4ETU1NSgpKUFwcDAsLS0Jc5pJawRA2EpsXdc/tT3AAziYZ62qqkJ1dTWZn0+fPoWkpCRiY2Px/PlzNDc3E707X19fSlu6rq6OzNm6ujqsX78e1tbWSExMJPecMGECNm7cSFg+06ZNw5kzZ9DU1ISNGzdSRanYtnfvXkqrm7HOzk68e/cOcXFxkJWV5UtJ//z5M06cOEEkXjIyMkjbbN26FdbW1khOTibP8+rVK6SnpyMzMxMrV64kwM6IESOoonD19fXYs2cP1NTUCPgP8ObQ27dvUVVVhcDAQKirq0NKSoow075//w4dHR34+fmhpqYGDQ0NRM+a3U5d+wjgBZesrKzg5+eH/fv349SpUwgJCYG5uTnffv306VOYm5vDxsam2z2hubkZ+/fvJ0GYadOmkYyBffv2gcPhoHfv3hToWF9fD39/f0qn98aNG0hLS8O5c+cA8IDctLQ0WFtbY8mSJQB4BSEnTpyIgQMH8ukKv3jxAikpKRAREeHT8L158yaWLFlCvdv379+hrq4ODodDMckBHnjVr18/+Pv74+HDh2hra0NWVhbc3Nzg4+MDaWlp0g+rVq2CmpoaFTTmcrmwtLQkYNjx48fx5csX8g6+vr7w8/PjK2j64sULzJ07lzxneno6VFVVYWVlRUB8RsYA4EkTODg4YPr06WS+5OXlQV1dnTASGdkfd3d3wgIEeIzjyMhICjwCQLHpvnz5Am9vbwwcOJBiTre1tcHb25sA8wBPkzo+Pp5ktpw6dQqBgYGwsLDgA2KZ8bNgwQKIiYlBXFwcq1evRnh4OBQUFKgio0OHDgWHw/lHKfkAjxHIFIP08/PDhAkTyBi5ceMGlJWV4eTkRMYZYwkJCRAXF8fRo0cJm5uxO3fu4Pnz52Qte/HiBVRVVWFubo7q6mo0NTXh8+fPpKBsd8zf5cuXQ1JSEkuXLiVjgSnWpaury6e/XV1dDXd3d+jo6JD9oKt1dnbi0aNH0NHRQWhoKISFhSEoKEhlIb169QqampokK6e2thZxcXG4c+cOOjo6cOzYMaiqqlLtO2PGDLi5uZE5c/LkSVJUlO33PH36FPHx8dSYjI2NhbW1NbZu3Ura/e3bt6RA5dy5cyEiIgIlJSXs27cPvr6+UFVVJWPk5cuX8PT0hJGREXx8fNDW1oaPHz/i3bt3MDY2Rv/+/eHo6Ig+ffpQWtdfv36Fr68vcnJyqL5j1uvW1lbY2dmRvZw9X1+9ekUKezLtmp+fj969e1P6/QCPMWxkZITg4GACqLP9uw0bNkBUVJRkB9XU1EBeXp460+Tm5sLJyQlaWlrw9vYm1+/bt49I/vj6+uLZs2ekrZnnAmg/dfXq1VBUVMTSpUuRmpoKISEhKmPrzJkziIiIgKqqKmlPpp09PDz4inX2WI/932A9IGyP9ViP/Y81T09PPp2vmzdvQlpamjhDzIb/5MkTqKurk4I73TEQ/ol1/e6RI0eQlZVFwEaA5zAZGRnB3t4eaWlpyM7O5ku7ycvLo1IAV61aBQ6HQwFbjx8/hqGhIaKioqh7VlVVoX///pCXlycAFdth/vXrF+rr6ymWZGlpKakczRRfKSwsxOLFiyEiIoIpU6bg2bNn1MF027ZtCA8PR0JCAtTU1CiWK8A7BIeHhyMgIADJycmUY/vjxw8oKyuTgydAszZra2sRGxtLpUeXl5fD3t4eMjIyVHsCPKAuIiICnp6eOHfuHOmH58+fY8qUKdDS0qKc6PXr1/MBsWxwBviXhlRGRgbc3d2hpaXFJz9QVFQEExMTAlRcvHgRu3btwrVr1whwnZGRAXV1dcydOxfv37/HrVu3EBoaCmtraxw+fBi6urrQ19enxiVjDBC7fPlyqqgXW192w4YNEBQUxOnTp9Gd/fjxA/Hx8XxMgMrKSqK/W1hYSP3t1q1bUFVVRWhoKF9xJnZ6pbS0NEaOHEn9vb6+HmFhYRRzGOAdDpkD7fHjxyEvL4/8/HzcvHkTKioq0NXVpartArw+NzY2hoiICAX0A7xUNA0NDYwePZoqDvX/xjo7O1FbW4t+/frhwYMHuHTpEh+bZMaMGdQ4aGlpweTJk8HhcAgDlMvlkiI7Xl5eKC8vR0BAAHx9fbtluyYmJmLIkCHd6tkC/DrNK1asQEFBAe7cuYPevXvzaSg3NTUhKCgI48aNI9dNnjyZAFxlZWWws7Oj7vH8+XMUFxdj1apV2LdvH8Xkz8jIgJKSEsaMGYP+/fujX79+WLNmDWE3/fjxA66urnB1dSWHoPb2dsTGxiIlJYW6z+HDh2FhYQFXV1fCImczUOfOnYtevXqhd+/e5MDIfOfcuXNQV1eHn58faRd2340YMYIqzgfwgG8nJydYWFiQ9ZSdymltbQ0NDY1/tM6zD6KzZs2CiYkJNDQ0oKGhQcbInTt3oKioCAsLC+jp6cHBwYFiNGZlZcHV1RVGRkaIiYkhDP6fP38iPz8flpaWsLe3R2BgIBQVFWFiYoKJEyciKSkJHA6HAIEtLS1Yt24dBAQEqHW0a7vs3r0b69atw7p160iK5rt37zB06FDIy8uTYoUxMTGYPn06LC0toaWlhTFjxkBUVJRKUy4sLCRALLuIWFfwc9myZeBwOFBSUiLsXwaI1dDQIIxY9nobHx8PDodDMV8BXvq4vr4+tLS0YGNjA3t7e4r113U+sZ9l69at0NTUhJCQECIiIpCWlkbWzq4gEuMD+Pv78zHYGxsbERYWhj59+mD48OEQFRWl1pz58+dDUFAQ+/fvx+PHj/Hw4UMEBATA2tqajO0jR47AzMwMBgYG1Prx/v17TJs2DTY2Nli1ahU6OjoImHPp0iWcPHmSWttfvnyJiRMndptey5YwYuz169dwdHSEtbU16WvGqqurweFwMGHCBHK9qakpBAUF+cDH9PR0koEwa9YsUgC0vb0d169fh5GREZKSksgYu3v3Lnx8fBAYGEhJLrBt5cqVUFNTI8HTefPmQVRUFL6+vtSzxsfHY+TIkejs7ERDQwOmT59O9peysjJIS0tjwYIFcHJygpmZGXbt2kW1CXv93LZtG+bOnYtx48bh6tWraG9vx7Fjx+Ds7AxPT08UFBRg69at8PX1hYWFBem/Xbt2wcDAAJ6enlTmzoULFxAQEABLS0uyfzNjs6amBvr6+hAREUFpaSnOnTsHUVFRwlBlg8Fz5sz5rY7776yhoYEa7+3t7WhoaEBoaCg4HE63GvzMOsLW7c/IyICCggI0NTXh5uZG/Mzr169DRkYGlpaW0NPTg6urK2xsbMj73b9/n5JGAnjFusTFxbFkyRICxD5//pxILrW0tJCUeoAXCDM1NYWNjQ1fUS6mDb58+YKYmBj06tULoqKifPtGc3MzjIyM4Ovri4SEBNjZ2cHT05PMg82bN8PIyIjKQGlpaUFKSgqsrKzIZw8ePCBt1d7ejqKiIujp6cHU1JQKtLe2tmLIkCGwsbHB5s2bKR+prKwMSkpKkJKSQnl5Oc6fPw9RUVHiY7GzoRifeuHChRg+fDiuX7+OHz9+4NixY7CxsYGHhwdhhn/+/JlooLL3oezsbCQmJpI15fLly1BTU4OPjw8A3lj89esXQkJC4OXlRUnejBw5Eg4ODnwgLACMGjUKHA4HwcHBFNGjoKAAYmJi4HA4sLOzI2Ns8+bN8PT0pNYqRkKN3aaMvXr1CgoKCvD19aWkBJi5wdjff/+NzZs3U2vIkSNHICYmhlGjRpHPmpub8fz5cyqTpKWlhWLB91iP/d9kPSBsj/VYj/2PtezsbD5dxvr6emhpafEdWn/8+AFDQ0Pk5uZSDuvly5dx5swZvsNLd8Z2mr99+4bv378TkIvNhgF4Ee1x48bB1dUVQUFBSElJIfqpTCoYk7JWUlJCpYQxTm9HRwdevXpFHFv2waC6uhpeXl5QU1Mjji3jAHVlep44cQLv37/H58+fUVNTAzs7O8Ju+fnzJ1RUVKCsrExVlZ48eTIkJSXx9u1bfPnyhbBZugKxLS0tfIcEgHd4iI6ORmJiIp+27ZUrV9C/f38sXryYLxW6uLgYNjY2sLa25mOfnjlzBq6urlRq27x582BpaQlZWVnExcVRoM769evh4eGB4cOH8xUXYldHZ37bx8cHrq6ufEDsiRMnSBqtqqoqdHR0oKmpCVtbW1IRefXq1ZCVlYWCggI5yDHvFhsbS9K0GWOzABjNzlmzZlHasocOHcLGjRvx8+dPuLm5QV1dHTdu3OBLqZ47dy4sLS35DjhtbW04fPgwVFVVKVYkY3fu3AGHw8G0adMA8ACYiRMnIj8/nwAQTEpyTEwMLly4gGPHjiEoKIhiPbPt8+fPaG9vR2BgIObMmQOANya8vLygoKBA6ZZOnToV27dvx6FDh2BnZwdHR8duU22FhIRIIar/qP0OeEtKSoKfnx9ERUUpJkpNTQ3c3d2xbds2im39/ft3UjyDYcRyuVyUlpbCw8MDysrKcHd3J+tR16rChYWF0NLSogICjLHvs2fPHkRFRaFPnz7Iy8sDwAvYiIiIYMmSJXjy5AmuX78OeXl5KCsrkzXl+PHjkJGRIeyrvXv3QlFRET9//vxj0TIul0uALIaFf/PmTXA4HKipqWH58uXkkNPS0kKlFzLrmJ+fH989pk2bBg6HA11dXeoAtn79ekhLS2PChAlQV1dH//79+Z7n/PnzEBQUxMSJE8nnBw4cwIcPH5CWlgZ3d3e+wMGSJUvA4XBga2tLacQeOXIE4uLi4HA4vwWK2P3AWGJiIqSlpXHs2DEcPnwYCxYsAIfDIWO6uroaxcXFWLp0KYqKisjBd8aMGVBQUMDevXtRWloKb29vqKmpEQZXfX09jh49ilGjRmH06NFob2/H1q1boaSkhD59+uDIkSPUszAasUyxrq7PmZaWBgkJCTg6OhLpgOLiYsKkTkxMJFWmdXV10dbWhtraWsjIyEBERIQErtj7aGFhIWxtbTFmzBg+HcmMjAyyD6Snp8PR0ZHSIq+vr8fevXshJCRECpgx/TNu3DgUFhbC19cX9vb21OG5vb0deXl5WLx4MVavXs3HEO1q7Pmzc+dOWFhYUDIsv5PYePLkCdTU1BAYGMjH2mtpaYGqqiqEhYUJC5UBdL99+4YpU6ZAQkICioqKsLW1pdhfTGX7uLg4SEhIYPXq1dRvV1dXIyMjA8rKyoTJOWPGDOjp6UFHRweGhoYYPnw4+f7Lly8xadIkyMjIkEAl+53r6urQ1tZGwK6qqipYWFggMDCQL+398+fPVKEiPT09REZGwsPDg9rzP3z4gL1798LJyQmhoaGUXExbWxuWLl0KNzc3jB49mgJifX19ERISQhUqA3hsxcGDBxPQhSlSOmHCBNja2sLDw4MKnLIZ8w8fPsTnz5/x9OlT6Ovrk6DsqVOnIC4uDktLS5JZwF4/mZT0gQMHwsjICHp6ekhLS0NzczMuX76MUaNGQVpaGi4uLoiJiaH6b9u2bXBxcYGCggLlawG84GtwcDCUlJSotPtVq1ahd+/eWL9+PQ4fPkwF9FpaWlBYWIjy8nIKlNy/fz8BL39n3enLd2VuBwUFQUVFpVt27bhx4wgD8fr16zA2NsbVq1exY8cODBs2DAoKCoQlX11dja1btyIwMBBTp04lY+Xo0aPgcDjYtm0b5a8AIPrSq1atonSBly5divDwcOjq6mLmzJmEJPHx40cYGxvDzs6O0rZn+nzz5s3o06cP+vbtCy0tLSI7APxrLp85cwY6Ojro06cP5OXlyZrT0dGBrVu3QldXl2jTsguE9u7d+7dF2erq6hAQEIA+ffpg06ZN1HrT3t6OYcOGQU1Njdo7bt++DSUlJdy4cQMHDx7kC+Ju27aNyt5hZDX27t1Laedu3boV9vb2UFVVhYODA2xtbWFnZ0eNyWnTpkFRURE7d+4ksmH19fVYv349hIWF4erqioCAALi7u1OBQOY9WltbsXDhQlhbW+PSpUvU++Xn5yMyMhLBwcFITU1FS0sLrl27Bg6Hg/z8fHh5ecHHxwcSEhKYNWsW1q5di9DQUCxcuBCtra1U4GPz5s2YPn06hg0bhgcPHhBG+5s3b6CoqAhvb2/s3r0boaGh0NPTo7TdmUy0rgEnZu/uTsri/60cVY/12H+F9YCwPdZjPfY/3pYsWUIOKi0tLZg4cSI8PT0plmVzczPs7OxIQQ2Ad6DU0tKCnZ0dAZrYxVXYxnaA16xZg+joaPz8+RNv3ryBhoYGLCwsCIOJMSa1mO34MACBk5MTiouLcfv2bb6iCAsXLqT01JYsWYKAgACoqalh/PjxRKPy48eP8PT0hLq6OgHg2AyZffv2QUhIiCrQVF5eDl1dXQIKPHnyBAkJCSgoKCDXPn/+HEOGDCH6pQDPmWIO4OyUaOaQCvAOjmyHfOPGjejTpw+WLVtGDi7fv39HZGQkVZgiPz8f8+fPJ9ft2rULnp6eiImJ4UtFv3XrFrlu9uzZkJOTw8GDB3H69GmSJs0G1QoKCmBkZEQBApGRkejduzcMDQ0xdepUAgacPn0afn5+FIOPsaKiIsjJyeHKlStoaGjAhQsXkJCQAHV1dSpF7vLly7h37x5J629qasLOnTuxfv16mJiYwNfXl/wm+2CWnp6O0NBQODk5wcXFBSUlJeBwOAQMuHr1KqytraGoqIhFixbh+vXr2LNnDylAwj6INTc3U4emAwcOQExMDMnJydQ7dXZ24unTp+ByuZg1axZkZWXh6+sLfX19+Pn5EUD0/PnzMDY2hrq6OkxMTBASEkKc/QcPHuDvv/+m+un169dQVVUlgPjXr18xcOBAnD59mvTd33//DTk5OZJCfubMGTg4OGDw4MF8+p4M0P0fNbajXl1dTZjGAA9o0tbWRkhICJmfdXV1CA4OJgybrgVfvn//jrlz51KM2M7OTvz48YOqVN7e3o5r167xFQNxdHQk+nWMsQGE6dOnQ0JCAgICAlBRUcGAAQNIFfrVq1dDWloaysrKMDc3h5WVFQEimbZhgwM3btyAlpYWkUbo7OzE+PHj+dL7Ozo6sHHjRsI6O3DgAKSkpFBcXIxp06ZBREQE2dnZfEXh2LpxBgYGOH78OB+QFxwcjPnz55P73b17F7169cK+ffvQ3t6OnTt3Ql5eHiNGjKB+u729Hbdu3SLXLVy4EFpaWnj69Cm2bt0KHR0dlJSUUPOntLQU/fv3R2xsLIYMGULeu66uDm/evEFKSgphIv87jei1a9eiV69epCgVY0xKdNcq9YydPHkSVlZWZEwfP34cEhISsLa2hry8PFn7uwL0Z86cgb6+PgwNDZGamsqnU97a2or169eDw+FQe9rHjx/h6OiIO3fuoLW1FU1NTRgwYAAcHR3JM37//h2HDx/GunXryDivqqqCnp4eDA0NYWxsTIJk7LV869atUFFRoYIfb9++ha6uLsXIfvHiBaKioiAtLU32mZ8/f+LMmTOk/1atWgUBAQHCUj558iQ8PT35gNiu9u/mfNegmo2NDcaNG0dpxHZnT548gaamJmxsbCjpkNraWri5ucHDwwOysrLkfdhjo7y8HFeuXCFp0AANFD979gzDhw+Hg4MDX/bB27dvsW7dOnC5XCxduhSKioq4fv06WltbsWjRInA4HIqx9urVK4wYMYJoLTK2dOlS+Pv7w9LSEsOGDSMa85WVlTA3N0dgYCABN9nXzZgxA56ennjx4gXq6+sxYsQIuLq6Ijc397ftCvxrXHR0dGD58uVwdnamgNjy8nJYWFjwBaIBHmD14cMH3Lt3DxoaGuReK1asgKioKDVf2Pdm/rt9+3Y4ODiQe+3fvx9RUVHIzMzsVtZGTU2N0mVeunQpXFxcMHfuXNIW3759ozKFmP7r6OhAaWkpTE1N4evryxc8PnnyJKZMmQIul4v29nZcvnwZvXr1gqamJkaOHAlZWVlKRunx48cICQlBVlYW1NXVAfACj7q6ukQS4E/G3htu3bqFDRs2IC8vj/h/XC4X/v7+UFNTI/t/V1kGgFekKyMjg/z76dOnGDZsGOTk5Ahg/+rVK1haWiI4OBiHDx8mc2/MmDEQFxdHUVER5VN8/PgR0tLS4HA4JKgwc+ZMyMrKYsWKFZg6dSrc3d3h4OBA/ICPHz/CwsIC6urq+PTpE8rLy/H161c0NDTA2NgYQ4cOxdOnT7Fy5UoYGxuTgn1sa2pqQkFBAfz9/REeHk789a9fv0JWVpYKZAA8WS8TExPik3Vnv379gre3N+zt7XHkyBEqbZ7RfuVyudi0aRMePnyIt2/fwszMDNOnT4eMjAzV5/fu3UNERAQBuBmZBCaY1dnZiZqaGty/fx9cLhfv3r0jGWl79uyhslNKS0uhpqZGFRBuaWkhe3FFRQVSUlKQnp6ONWvWkHF88uRJnDp1iqwLDQ0NsLW1haOjI9GAbmhoQFRUFFavXo2MjAwYGhqirq4Or1+/xoMHD9De3o6srCykpaXh77//xpgxY5CUlAQFBQVISUlRZwMmiyYhIQG+vr7Q1NTExo0byfx5+/YtrK2t4ejoCHd3dyrDoa2tDZs2bYKkpCQhA7Dt2LFj4HA4WLlyZbd912M99n+z9YCwPdZjPfY/3saNG0el6758+RIDBw6EjY0Nhg0bhry8PHh6elLsvXXr1lGplDk5OeBwOJRzwRj7IMNU4dy9ezf5rVevXkFOTg5BQUEUcMN2ogEeyMKw17Kzs6GhoQEhISHqYF1XVwdfX1/C5GWAxpUrV2LFihWwsbGBl5cX0aZ7//49/Pz8ICgoSKUUlZSUYMuWLQR0Zp7j6tWrMDAwwIoVK3D16lWEhYVRLMni4mIYGRnB2dkZ3759ow6Yb968QWZmJjQ0NPicopkzZ0JDQwO6urrw8/MjDnt2djaUlJRIKqCDgwNVFOH79+9ISUmBrq4uVaV9+/bt8PLyQkxMDJ48eUIBaAAvBdnc3Jwc4M6fPw8RERF4enpCV1eXatMDBw4Q5zYzMxMiIiKIiIjAzJkzIS8vD09PT+LoHj9+HMHBwdDX18e7d+9ItH/q1Kl8bNLHjx8jJiYGgwYN4issw/w/+9/Hjx+HgYEBBcQCICyN1tZWXL58GSoqKhAWFqb0Bzs6OvDkyRMMGTKEFJnR09NDSEgIBTosX74cAwYMgJGREebMmUOAH4ax0RWIBXgph4mJicRpP3/+PPr3709pzrW2tqKyshJv374lYykjIwOWlpZE+4sBEDo7OxEWFgZbW1sUFxfD29sbHh4epC1Wr16NJUuWUMA4wGMcOzo6YvDgwQTYZtt/BogFeH1uZGQERUVFTJo0iQAvc+bMgYWFBUxNTREZGQkHBwdYWVmhra0NJ0+eBIfDIcxExr5+/YrU1FRwOBw+5hfzjOfOnYOenh5UVVWxfv16ssYw8gXMGsEeGxUVFbCxsYGYmBj279+PHTt2wNfXF0FBQSQF9t27dzh16hSqqqrIvFyxYgV18GTmFaMHyQQTQkNDIS0tTc3nRYsW4f79+6iqqsLHjx/x5s0bWFhYEBbf+/fvISkpCXFxcZL+e/jwYRQWFmL9+vVEMzYiIgKGhobYs2cPqqurUVdXh8jISAr4WLZsGWJjY6GhoYHly5eTw/OOHTugoqJCigV1tRcvXiA+Pp7S+B4yZAg0NDSwZcsWVFVV4du3bwgNDUVWVhYKCgogLS2NmzdvUr+zdetW9OvXj6R+/o5htn79ekhJSUFBQYG0A5fLJWMvLi6OaAp2HY/37t0jKd4nTpyAgoICCgoKcP/+fWhpaUFFRQUXL17ku3dDQwMaGxuxefNmWFtbUyw2xhjWNdN/S5cuhaenJ8LDwykN24aGBsKMYow9zphnbmpqQk1NDaytrWFoaNgtM+/ChQvUOz579gyioqKUzmxnZycqKiqgoqJCmPpsu3jxIubOnYsTJ05Qn58+fZpoBzP7FhsEZtuf0rbZbKwtW7ZAS0sLU6ZM+e1vMVZRUYHIyMhuAcfv378jKioKMjIyfEzgrgXZbty4gZMnT1Jp2xUVFRg+fDhcXFyogCBjz58/R1RUFGFyHjt2DFJSUpg8eTJkZWWpfebDhw/U/WbNmgU5OTnk5+cjPT0dEREREBMTI31SVVUFa2tr2NraUsHXW7duITAwkAI8P378iPj4eLi6uhLWPcBffAqgwVEGiB0zZgwBRysrK7sFuZjfWr58OYKCgohfsGnTJvj7+2PhwoV/ZLUVFBTA3Nwc58+fx69fvxAREUF8Iy6XyyfLoa2tTflBwL8Yx4wUTNf+u3btGtUupaWlcHV1RWBgIJkX7GtWrVqFlJQUfP/+HeXl5SguLgaHw6HW4fr6eoSEhBBNTAcHB/Tr1w9SUlJ8kkTdGXvMT5o0CZKSkggPD4evry90dHTIOtPY2IjAwEBoa2vzrXnLli1DXFwcfH19MWzYMOpvT58+xfDhw6GoqEiywCoqKuDn54fQ0FAqoyglJQV9+/ZFUVERGeNOTk4ICwvDxo0b0d7ejmfPnsHMzIwqYnn79m0kJyfDzc2N+CiMTMqrV6/A4XCQkZGBMWPGQEpKimQ+ffr0CVlZWTA2NqY0SGfPnk3A5v3798PX15cCYs+dOwcpKSlER0fj+PHjuHr1KkJCQuDk5ETte3fv3sWZM2fw/v17qmiXh4cHHB0dceTIEaqwJJfLRXl5OVRUVAh7funSpeBwOFS2RkNDAylgxYyXAwcOwMnJCV+/fsXjx48xb948aGlpkSKUzPxhGzt45erqCoDna65YsQKGhoaQkJDoFqAGeExwSUlJwhhmGOT19fVwd3eHubk51NTUYGZmBn19fQA8/1NPTw87d+4Eh8NBVlYWPn36hMbGRpiampL5duXKFQwYMAAcDgdDhgwBwGPAamhokHXy+vXr4HA40NbWxtq1a0l7/fr1i5ItyMvLI/5mW1sb0a7NysrieydGUqTHeuz/a9YDwvZYj/XY/yi7c+cOYYAtW7aMgDXTpk2DsLAwEWh/+/YtcnNzYW9vD19fX8TFxVFpPmPGjMGCBQsA8FJ32XIALS0tlK4TY4yGKFt7k13NXFZWFsHBwXwMOoB3QB80aBBh+d29e5cUEWG096qrqxEcHAxHR0e0t7fjxYsXMDU1pQr6VFZWYvjw4fDy8iKO4vPnzzFhwgSKESclJQUOh0Peke3UT548Gbq6ulBTU6Oqo3d0dGDTpk1wdHSEnJwcScljp3a+efMG48aNQ0REBPnN0tJSqKioYN++fdiyZQvMzMxgbGxM2B6nTp1Cbm4uxo0b122q6fPnz5GZmQlDQ0OqwFVRURF8fX3Rr18/qjIrwDuczpw5k1SeV1BQwJYtW1BZWQkjIyOoqqpSB0uAV0xEW1ubT9PKzMwMfn5+pP327t1LGC/MoXHGjBmws7Pj0/Rcu3YtlJSUUFtby1ftfMSIEXBzc8P69esJe+HkyZMwNDSEm5sbnjx5An9/fyqd+/Hjx5CXl4eCggICAgLI77H77/nz5ygvL0dtbS2lrThjxgzIy8tj+/btpAiQra0tvn37Bi6Xi0OHDkFKSopiW5WUlMDe3h5ubm6k+APAY8/ExMTA2dmZOlgxtnz5cooZzGimMlpzZ86cQUhICCn+wK7qHBgYSDny7EP/iRMn4OLiAj8/Pz5m+X/G9u/fD21tbRQXFyM/Px+SkpIIDQ0laYFnzpzBjBkzMGXKFKpC/ZMnT5CcnAw5OTkcPXoUwL/64MKFC0SG5PDhw92CCBUVFVi5ciX09fXh4OCA8ePH49KlS5CUlOTT0t2zZw/09PQgICBAFZjYt28ffHx8EBQUhCdPnmD+/PkQEBAgQGJDQwNyc3NJJXbG2tvb8f79e8jKyuLKlSsYOHAgDA0NqSJce/fuBYfDoVg2V69ehampKQFv7t27hwkTJmDNmjVEjkNFRYWkm9rY2BBwNDo6Gubm5pCVlYWJiQkMDQ1JW2ZmZkJBQQEbNmzA2rVrCdO6rq6OFAJUU1NDREQE1S5FRUUQFBSEvr4+9ZwAMHLkSJibm0NKSgqysrKQlZVFU1MTHj16BCUlJUhLSyM7O5sCovz8/BATE0ONt5s3b5JxHxkZCVFRUZSWlmLs2LEwNzcnbGbmmpSUFERHR/8WOKqtrQWXy0VoaCgBEDo7OxEQEABVVVUEBQWR79bU1BC5GcbWrl0La2trTJw4kQCxjBQIu38LCwshKysLdXV1cpBngMf79+9DWFgYd+7coX67rKwMK1asQG5uLtk3X716BTs7O5iYmKC6uhpcLhdxcXFYunQpuY79G15eXkhISKDkINra2hAQEABpaWmi5QvwgjkqKiqQl5cnIBf7MH369Gn4+PhAW1ubAoEPHTqErVu3Ijs7m092oqu9ePGCPN+OHTuwfv16krb7J2P339WrV3Hjxg0CCgA8gDIqKgry8vK4efMmWlpaMHjwYKSlpQHg9SmzZykoKMDd3R0jR44kabgVFRUYMWIE3N3d+ZimXC4XhYWF+Pr1K65duwZ1dXWSCTN16lRwOBx4e3vzPe/79+9haWlJMbHfv3+PpKQkyMvLE3/g2bNnGDFiBHnHoqIihIWFwd/fH01NTZRe8sePH5GQkAAPDw+qz//UZh0dHVixYgXc3NwwaNAgqmDk7wJlWVlZsLCwIL5OVFQUcnJy+EDerlZZWQlra2vo6OhAXV2dSrlmB5YBnh+irq5O5ix7z+nbty9fQG369OlQV1eHhoYG0QJmfLf9+/fD3d0dISEhVAr59OnToaamhry8PKpQ17x588DhcDBw4EDExMTw1QBg9kdNTU1Kbqo7Y+/18+fPR69evYju9t27dyEmJkat9y0tLXBwcICJiQlZ45csWQIFBQUMHToUXl5eEBQU5NvHnz17htDQUMq3OnXqFFxcXODv70+1V0pKCiQkJDB79myEhYVBVFQUkZGR5O+PHj2CrKws2SsZ+/vvv6GlpdVt5foTJ05AWFgYIiIiZH1j3v3z589YvHgxDAwMEBkZiZCQEKipqVHrBxuIZUDAW7duwdTUFFpaWtDX14ePjw+lET1jxgxoaWlBTU0N2tramDdvHglU1tXVwdPTE1paWnz1GaqqqqCvr48vX76go6MDzc3NGD9+PClOm5ycTPX5169f0dHRgdOnT0NFRQVhYWFQVFREQkICNm7ciNLSUujq6lJyHF37/+jRo1BWVkZERAT09PQwdOhQrF69mmRkPHjwgJKteP78OczMzHD37l08evQIOTk5EBAQIGeA5uZmnDx5EqtXr8aWLVvI2Bw1ahQ8PT3x4cMHEsgKDw/Hnj17UFVVBUdHR5w9e5b4AoWFhWhvb0djYyPWrl1LJMqYLJpt27YhOTkZkpKSWL9+PTV/AN4eYGpqCg0NDQKqc7lcrF+/HgICAt0Cscx1PdZj/1+yHhC2x3qsx/7H2OPHj2FtbY3U1FTiALErrk6dOpUCYhljp1G1t7ejpaUFzs7O2LZt22/lALrqB27atInSEGUbG4hVUFCAvb09xdzcu3cvXFxc4OrqSqU/lpWVISgoCOLi4jA1NYWVlRUcHR2Jc/Tu3TuoqakRB5Zx2pn7MCxXdmrb0aNH0d7ejqtXr8LKygoODg4kbZcNpj58+JAqksQGRvfv3w9dXV34+PgQgILtANXU1FAalsXFxSQ9G+ABtXZ2djAyMqLSTdmHjkePHuH169fEQa6qqkJ6ejofEJufn49Ro0aRwwW7En1jYyM6OjoQHR2NWbNmkX7o378/SdVks5EZxhbDymDu/ebNG1JY4ejRoyRFb9KkSaQo2p49e6CtrY3du3dTwMBff/0FKysrqr/T09MhJyeH8ePHIzExkejVMozIv/76CxYWFtDQ0ICrqyvplz179hAZiPPnz5NCFIwx47irDjLzbubm5uRAeu7cOYiIiPAxsXbv3g0/Pz/SFzt37oSzszOkpaX5gK7Lly9j0KBB0NXVpVg2LS0tiI6ORlFREYB/pV2zi1Yx9uHDB760z/fv32PEiBEQFxcnzDn2+Dpw4ABGjRr1n9L96nrN+fPnKdDzyZMnkJKSQkhIyP/D3l+HVbWt7+OwUxGQ7m6Q7u4GSVFBMbBbUUQJOxALOxG7E1RMDOzE2BYgiluxA6RzwbrfP9Y7x5mDhXvvc77v+/t9zufLc13n2sfFWnOOOeaIZ9zP/dwPeWftf8O2//Xr14Slwz2QvnjxAuPGjcPBgwcpxt3jx4+Rl5eHp0+fkndVWFiIs2fPwszMDL1790a3bt2grKxMpd6lpaVBUVERioqK1PgGBEBscHAwHB0dcevWLQQFBUFbW5sAsRUVFdi+fTuUlJQoVk5NTQ1MTU0hISEBc3NzSisuJycHmZmZFNMaEKwdSkpKOHjwIP744w9ERkYSdtfevXuhoaFBQM2DBw+CYRiqMvqDBw+wd+9e7N+/n/RhQUEBzM3NCQh3+/ZtdO/enYwdtk3btm1D7969hd5FSEgIGIahDo2sPXr0CEePHoW7uzucnZ2xatUqTJw4EWZmZkhLS4OJiQmcnZ0xePBgFBcXExkZFjwpLi6Gg4MDxo0bB09PT3Tp0oWwX69cuULY3azESnNzMwICAiiNuqdPn+LGjRskvRQQjG9tbW0y9379+oX+/fvj/PnzZC4sWLAAbm5ukJSUxMiRI3Ho0CFyzU2bNsHJyQnu7u5wdXWFuro6efbVq1cTmZBjx45BUlJSSDPv/v370NfXp/ZGFkDv378//P39YWRkRIKOr169gpubG6SlpeHk5ES0YzuylStXws3NDUuWLCHvqra2Fn369MGNGzeo91dUVIRp06ahR48eBAhg3zdrubm5mDx5Mum75ORk6Onpwd/fHw4ODtDQ0EB+fn6HbNi7d+/CwcEBR48ehY+PD7p06fKPAjftmaUGBgbo2bMnpKWlsWTJEtK+r1+/YsCAAURTt2fPnqRfli1bBjU1NfIu4uPjISEhgT59+pDg5fPnzxEREYHx48eDz+dTxRzZ55k/fz4GDhxI9pRVq1ZhwIABQsECQDBexcTEhMA0FijZsmWL0Pxpa2vD6tWroaOjAyUlJarYGnv9r1+/IjIyEhMmTPjbYlFcIHbevHkYN27cP1qnz58/D1dXVxgaGsLU1BRmZmYdathzjf389evXOH78OPbu3UvWL5bZOW3aNLi4uKCurg4tLS0wMDCgJGYAQdCSuwYBAsY7KxHy+vVr3LhxA5qamoiMjCT+zZEjR2BmZobExEQAgjVPTU2Nkqzi8XgEhD537hxGjx6N0aNHY9myZaQNFRUVePr0KS5dugRPT08YGRkJaZdyr8caW6He2NgYgEDmR0dHh5rvLPjY2NhIAr1sUJsdm1+/fsWYMWMgLi5OMltYKysrI+8vNTUVQ4YMgYWFBbp37w5XV1cKPF2wYAEsLCwgISEBTU1NtLS0ICkpCc+fP8eXL19gaWmJdevWCRWZdHFxofY7Nghw7do1SEhIEEZse7CuvLwc+/btI/sQl0TBGheIZQG9+vp6vHnzhmJn83g8LF26lKwnADBixAgoKysjPj6e1AGoqqqCgYEBjIyMoKKiQjLjCgsLYWFhgerqamoObNmyBTExMRgwYADmz59P0vhHjBhBJJoOHz6M+fPn4+jRoyTY9O3bN9jY2ODmzZu/9T9+/vyJvXv3om/fvti9ezd5v69evYKjoyMlmbV06VJMmTKFAucBAZO8a9euWLx4MfV5W1sbHjx4gClTpkBWVhaXLl2iAkjJyckwMDCAh4cH+vfvjwkTJmDQoEEwMzMjGs88Hg8vXrzA169f8fbtW1haWhLm7du3byEpKQlFRUVKvoa1lpYW+Pj4wMDAgPjFra2t2LJlC0RFRSn5jE7rtP9W6wRhO63TOu1/jbW1tZH0dklJScLm4Tqy06dPh5iYGNn4uQ7O06dPyWFn7dq10NbWhoiIiJAcQGBgIHXIZCO0v9MCBP7lOL169YrSOwUErEhbW1vIy8sLpaKVlZUhNzcXmzdvpvSoeDwePn36BH19feJAcdPvgoKCMH36dOTn5yM4OBh3794lbIvv37+TQ5+Ojg6CgoLI/bisV9bOnz+PI0eO4MiRI4RZefz4cZJy1hEjFhAAbIqKimAYBitWrADwr4PT+/fv4eTkBCsrK0onFhAwNlVVVdGzZ094eXkRYLq0tBQpKSkwNTWlpAnYa27btg1qampU4ayamhoYGxuTQ351dTViY2Nx6NAhKkWXba+0tDQFyrGavU5OTli1ahU8PT2hpKSEmJgYyMvLU4f64cOHQ0tLC1u2bMGLFy/w6dMnBAUFISgoiLy3hw8fQk9Pj9I1vXTpEhwdHTFixAgCHDc2NlJMte/fv8PFxYWwd3k8Hs6dOwczMzOKXbZ582Zs2bJF6OD65MkTUvAgJyeHCizU19fjyJEjQqlv7Bg4ffo03N3d0atXLyEg9vLly5g9ezZp559//onm5mZ4enrizJkzOHv2LHWvlpYWbNq0CWfOnKHG2IcPH1BUVETeRVVVFSIjI6liUh0xHf4dIJbbJ1u3bsX06dPh4OBA6Q0DAnBITk4OUVFRFFB18eJFnDhxggrivH37llSRz8zMxJ07dxAZGUkAfrbdqampsLCwgJaWFpFf4LKUWSZyYGAgunTpQg6l7DU2bdoEc3NzDBkyREgvcO/evUhISEBbWxvKysoQEBAADQ0Nwvj79esXtm3bJgTEhoaGwtzcnAqwFBcXQ1lZmRTfYD9nLS4uDvLy8tDS0oKjoyMBmefMmUOkLA4fPgxZWVny+5qaGnK45FbSbm1txePHj2FtbQ1AABpyx0pdXR1Onz6N+vp66nftD/G+vr5QV1fH1atXO0yVbm5uRlRUFJSUlCAhIUEYjW/evEFubi6pQu3k5ASGYaggz6ZNm6CsrIwuXboIyWPs378f/v7+UFBQQFBQEGxtban+TE1NhZWVFdTV1QljmV0jY2NjYWlpiczMTPj6+sLDw4O0fe7cuVBWVkZ2djZu3LgBb29v2NraUnrlx44dw8KFCzF16lRyv58/fyIwMBAJCQkABMGQQ4cOQVxcHCNGjMCVK1dIhoWTkxOZO8ePH4eWlhYJeGzfvh3i4uLUOG9ubsbq1aupTIWOWI3Nzc1ITEyEg4MD3NzcMGvWLDg7O8Pe3r7D7JGPHz9i6tSphD3IWkdzfefOnVBVVSVFAc+fPw+GYSgpCi7zq6ioCMOHDyfalGyxyb+SLeG2rV+/fpCSksLNmzfR1NREisklJydTe92hQ4dI2jUgWBPc3d1JYObixYuQlJTE8OHDYW5ujpiYGALWlJaWoq2tDdevX4ecnBwWL15M0uX5fD6io6NJynFDQwP69OmDzZs3U0APG5jh8/nw9fXFjBkzhDIynJ2dMWPGjN+ul2wV+GHDhlGaw+wzscw9rtzM3/Uhd57+k3X64sWL2Lx5M5YvX04VDvora98Wdn/r1q0b7O3tISMjQxXwfPz4MTQ1NeHt7Y1jx44hLy+PFD3ijotRo0Zh9OjRVNsLCwshJydHrc35+fnkd/Pnz0dMTAwAAVC1fv16mJubQ0NDg7ABeTwe1RfLly/H1KlTCdD06tUruLq6wsjIiNqPs7Ky8OPHD0rqR1JSEvPnz0dYWBhevHgBbW1tjBs3jrTn/v378PDwoFjyeXl5YBgGysrKVLHZ8vJyjBkzBj169CAgJNe2bNkCWVlZ3L9/Hx8/fsT9+/fh6OiIwMBAKtBWVlaGlStXgmEY9O3bFwzDEGB/zpw56NGjB3Jzc8n8qaqqgr29PTZu3NjhuGpra8O5c+fAMAwSExOFdHjbW0fAPQvE9u7dm9ID5o7TN2/eIDg4mGjsnzt3DjIyMujXrx80NTUxefJkAmrW1dWhsLAQw4cPh6KiIm7cuIGSkhKYmZlR+1RHlpKSAjU1Nezdu7dD3V8ej4eqqiqEhYXB09OTWmc2btyIsWPHwt/fH+fOnSPkCfZ9t7a2ora2FqqqqlBXVyfP19LSQhj03Owp1rZu3QpRUVHMmjWL6ruDBw9CS0sLpqamMDU1ha6uLpGhqKurw7Nnz+Dr60uyfo4fP46EhASYmJiQ4qSsXblyBZaWlgR4vn//PiZNmoRly5aR9rNrFnv/lpYWeHp6CgGxLMv+79ahTuu0/+nWCcJ2Wqd12v8KYx0Ottq7paUlEhMTCUDIdbDZwxQ36j937lz4+vpi165d4PP5ePz4McLDw2FpaUkOfR8/fkRoaCicnZ2pQ+KAAQN+q1nItfYOOPcaBw4cgKWlJSIiIoR0Y9sb91m2bt2Krl274sCBA+SzhoYG2NnZYdWqVcQRNzQ0hLy8vFBRl7t370JLS+u3qe0pKSnQ0tKCv78/NDU14evri8uXL4PP5+PAgQNwd3dH7969hRh67HXu3bsHe3t7ODs7C1WGLysrg46ODqVHdvHiRRgZGeHcuXPYvXs33NzcoKurS1iJpaWlmDlzJuTk5EjBB/aaP3/+hI2NDaysrIjD3NDQgLFjx8LFxQVz586Fv78/HB0dyXtYu3YtJk2aRIDgtLQ0aGtrU8yzlpYWWFlZkQIL2tra6N69O1V8ibUJEybA2toa4uLisLa2pvRt29ra8PDhQ2hqapIxxf72woUL6N69O2GncO3ChQsYN24cBgwYQDGHm5ubCRBrYmKCcePGUYce7vUfPXoEe3t7ZGVlQVZWlioWcfPmTQwcOJAAym/evMGrV6+oex07dgxBQUEIDw+nDjLcZ09ISEC/fv3w/v17DBw4EIGBgZCXl6cKtX348AGhoaFUUZq5c+fC1dUVUlJSiIqKwuzZswEAP378QJ8+faCoqEja9p/qvnLbmZ6eDlFRUfTr1w/du3cnjBOuFRcXo0uXLkRbb+bMmdDV1YW1tTXU1NQQFRVFDskfP37E/PnzSTE3JycnKiV27dq1UFJSIkGh2bNng2EYInvBLWLVrVs3hIaGws7OTojRvHHjRnh4eGD48OG/LVjU1taG9+/f/xaIVVFRIUAsW8EY+NdaVFdXhyNHjsDY2JhKeeZmC9y+fRt3795Fa2srzp49Cx6Ph9GjR2Pu3Ll48uQJpKSkyDvn8/kkJfHcuXNIT0+nxvidO3dgaGiI3bt3Q05OjoAVgIClHBsbS43n/fv3Y8aMGUhOTqaCY97e3tDR0aF0Srlp1VevXoW2tjYsLS2RkZEhlMZ+8uRJzJ07F7KysrC0tCSp/ufPn4eOjg5MTU0xceJEIRDg1atX2Lx5M5KSkpCRkUFp8SopKZGiccnJyWAYhgAc169fR0xMDCwtLREZGUnGy7Vr12BpaUkYVjdu3ICYmBjc3d1ha2vboYYo9/0tXboUurq65EDb3NyMQ4cOESAyMTERAwcOpKQnli5dSsCj7OxsSEtLE8C3traWrFVc62gecg/9OTk5GDFiBEJCQjBs2DDyfJs3b8b06dMREhKCCxcuoLKyEj9+/MD06dNhYmJCBcDa32PRokUEADty5AhkZGQIYM8NaHD31X79+qFLly7Q09OjQOX2oODevXupayxcuBAiIiKYN28eAIEEgpycHMaMGYPu3bsjJSWFjCHu2sKyfXNycvD582fcuXMH6urqyMrKAiAI1HXt2hUeHh7kHa1duxbLli2DpKQkZGVlkZaWRub3pUuXICkpCTs7O1hbW8PS0pICJpctW4bExEQSWJg1axbs7OyQlZVF3nF9fT3c3d1JIBQQ7CnHjh2jwJIdO3bAzs4OEyZMoAKZXJ3h/v37458Y9x380wJq3H5cu3YtWSf+DsDlBltYCwsLI0Bg+++9ffsWnp6e6NmzJxQUFKCqqkqlpLPyGUOGDCG/Y/++ceNGGBgYCK0Dra2tJA18ypQpMDMzQ//+/bF27VqkpKRAXFxcaM1mM2KOHTtGBaJfv34Nd3d36Orq4uTJk/D394eLiwvph3HjxqFLly5YsGABHjx4ABUVFYiLi2P8+PHU9UeMGIEuXbogPDycZEYAgv2WYRhs2rSJ6vOKigqMHz8eDMNQezwgkBuIjIykPnv8+DGMjIyITirXbGxswDCMkITFxIkT0aNHD4waNQozZsxAQECA0Jj++fMnkYxg23fs2DEwDIOkpCQSpOjfvz/FxG3vK7cHYoODg0lRVe74ZPe2M2fOoKqqCvfu3YO6ujrxkYYPHw5VVVUMGTKEtOv27du4du0a0c1dvHgxHB0dMWDAAKSkpGD27NmYOnUqRo0aRfb506dPQ01NjZLAqaioQFFREdFGXbRoEYKCguDo6Egxe2fOnAlVVVVMmzYNY8eOhby8PNLT08m4qa+vx8GDB+Hr6wsLCwuyNnGD2unp6WAYRijDBQAhGHD7LC0tDUpKSjh79iwqKiqI9Fd7ObWVK1diyJAhaG1txatXrzBlyhSYmJhQ2W9HjhyBqqoqTp48ieLiYkRGRmLcuHHk71u2bIGJiQl5HrYdTU1NcHFxgZWVFSEAcIM7nUBsp/03WycI22md1mn/1dZ+Ey4rK8OHDx+wcuVKuLq6YvLkyVSKP2ubN28mjtj8+fOhqKiIK1euUM71qVOnEBYWBikpKZiZmcHGxgYuLi7kcMPj8XDixAno6elRqWy/M+5h5Nq1a7hx4wbFUtizZw+8vLwQGxtLGLH/5ACycOFCMAyDwYMHY/z48fD394eFhQVx4lJSUiAiIgJvb+8OQb67d+9CT08PdnZ21Oc7duyAuro6cchZcfwLFy6Q52H1KttXLuVGsx88eAA9PT34+vpSAAkg0Jxr3y9clmtpaSm8vLygq6tLqru/evWKVJEGBAdK9hBaUVEBJycnmJubEyD29u3bGDt2LBwdHdGvXz/SL0lJSVBTU8O2bdtIf7958wZTpkyBnJwc4uPjsXjxYnJQaGpqQnV1NVxcXODg4ABtbW1cvnxZ6JBZVFSEc+fOYc2aNXBxccGRI0fIWHvw4AGkpKSIY84F2kxNTYX0QIF/HUCkpKQIM5PLsnz06BGGDRuG/v37U4BJexYRm7rNZfo1NDQgNDSUFKGZN28eYRD17t0b69atI989evQogoKC0Lt3b6ECO69fv4a9vT1h+D569AhSUlLw8PBARUUF2traUF5eThgebJ+lp6dDSUkJly5dQllZGfr160cVvPn69Sth1PyTgiV/Z48ePcLw4cNJO1+9egUTExNERUUJFft6//49eDweMjIyqDTTLVu2gGEY9OrVi1ovSktLUVhYSIFRTU1NGDJkCAElz5w5AykpKXJAqa+vJ+n24uLiOHnyJEnN/fXrF+Li4qgD7oYNG+Dp6YmRI0fi48ePv10f/vzzzw6B2O3bt4NhGKxZs0ao0jj7TpqampCdnQ0VFRX069ePXLOxsZG637x588AwDH79+oXTp0+jR48eYBiGCmCwhWFCQkKgoaGBxMREobHTr18/iqnI3isiIoLSV01OToampiZGjhyJKVOmkCIhrPn6+kJfXx95eXkdMikrKysxZswYODs7Y+XKlR2yli5dugQ9PT2cPn0a7969Q2VlJb5+/YpNmzbBzc0No0eP7rBI1eXLl8nhtKqqCgMHDiTvmGWDs//mtu3nz5/UXP706RNWrVoFHo+HixcvQlFREbt27cKHDx+gq6sLc3NzrF69+rfvvaWlBXZ2dkhOTqY+O378OOTl5TF16lSqjwGBfnNycjIuXbpEMZH5fD4OHz6MpUuXdriHdmTt28Vlcs2YMQNqampITU3FmDFjoKCggOnTpwMQzJ2kpCSYmZlh2bJlHT7f4MGDMXbsWFy/fh3S0tJUcCc9PR1paWkU8zIrKwuSkpKYN28eRo0aBTc3tw5B7LVr12LgwIFUMERaWhrjx49HfX09bt26BS0tLRIgYINdEydOpNbvWbNmwd7engA1gGDMjho1iqzFS5cuRXBwMJKSktDW1oa0tDQiZ3Lu3DlMnTqVMGLZcZafn49JkyaRdGZAMFdTUlKgpKSEQ4cOkb0RELA4ra2tERQUhJSUFHh6esLCwoL8NiUlBfr6+vDw8EDPnj1hbm5OgKGtW7fC3t4eDg4OBIBmLTU1FWlpaQD+Gvzgju+cnByyN/9dATUu49Td3R3KysokC+Lv9FHPnz+Pfv36kWKImZmZWLt2LWRkZKgAOTc49v37d7x9+5Z8xi2etmPHDvTo0YP4Oqxt3bqVCihzraqqCitXroS7uzu2bNlC1oPi4mK4ubkRqQlAwAzU19f/rd/48eNHhIeHw8LCAsHBwaSNr169goaGBgYOHEi+u3v3bgJ4FhYW4s2bN5g6dSrk5eVx8uRJyMnJoXfv3tT+yUpzscxP1n7+/EkxkbkyIAEBAQQAYz/fu3cvJCUl4erqSvRLHzx4AHd3d4wYMQIMw1DBMkCQXTB48GAEBgZi/PjxVEAoLS0Njo6OUFFRQWRkJG7dukXmzrFjx9C9e3eEhYXBwcGBkv/4nXHH3L59+zB16lScOnWKBMO4klIsYJmQkEDJG6SkpJCCiG1tbUhOToa5uTnev39PGLHdu3eHoaEhZs2ahaioKPTt2xcxMTEYOnQo6ctDhw7B19cXTU1NePHiBdLS0qCvrw8TExPExMSgvr4eubm51Dzn8XjYv38/9PT0iJzCo0ePwDAMVFRUMHv2bHz58gU1NTXIzMzEzJkzyW/XrFkDR0dHAvDW1dWRADCXtMEa1x+orKyEn58fYb7m5uZSdTF+N5fZImwdAbFhYWFQUFCAlpYWHBwcqHf37t07GBoawsPDQ0gGKjc3FwzDQE1NjSpI2QnAdtp/u3WCsJ3WaZ32X2tcx/z79++orKwkKTrNzc1IT0+Hq6srpk6dSlgukydPpjS7SkpK4ODgQKVUcTf3jx8/4vTp09iyZQvOnDlDyQFcuXIFEyZMIAyTvwJMuX8LCAiApKQkNDQ0IC8vj5iYGALm7Ny5Ez4+Phg0aJBQBey/spMnTyI2NhZRUVGYNGkSWlpaiLOcnZ2N7Oxs+Pn5ITw8XOhgAQiYWX369KHaOWPGDHJoP3r0KJViXFdXh5qaGrS2tuLChQukX/bt24c5c+Zg6tSpVCr3gwcPoKurCz8/PyEgFhBE4uPj42Fra4tJkyZRfystLYW3tzcMDAzw/v176m8zZsyAqakpVq9eTdi45eXlcHJygqmpKTl48Hg8NDY2kt+ePXsWWlpahHHGtY8fP2LHjh2wsbFBUFAQccjPnz9PHbD9/f2hpaWFK1euUAdP1pn/9OkT3N3d4e/vTx12Ro8eDXl5eap/KisrYWZmRqrMt7fTp09DVFQUkyZN6vAACNCAbkZGBnr16oWJEycS6Y0fP37Azc0Nenp6WLNmDZYvX46AgAAC2C9cuBDKysq4cOECnj9/jpiYGMLyYO3YsWOws7OjQHeWSTdo0CCKMXn27FmIi4vD1dUVtra28PT0hK2tLRmb3759g7+/P2GzXL58GZKSkkRTjHXSv379ipkzZ/7HLFjWDh48CBcXF9ja2lKgxdOnTwkQ2/5Q/PHjRwwdOpRoPbPFyxYuXAhtbW2EhoZSaYUdpd+GhITg4MGDQtIMPB4PW7duxYYNG9C1a1fCMps1axYUFBQQGRkJMzMzIbmOTZs2oWfPngQQAQSspCdPnlDyGO/fv4e/vz8FxJaXl1PpoIAgIDV+/HgEBwfj4MGDhGmUnZ0NHR0dwpIE/nUof/r0KZKSkkgQ6devX5g+fTrU1dVx5MgR1NTUoLCwECEhIdDT04OEhASOHDlCFelhraioCB4eHtDQ0MC2bduwcuVKBAUFUYEklpHKvp/jx4+jW7duQmmPZmZm5FANCA6sr1+/JvO2qamJALGrVq0ioAs3S2Ho0KEwNjaGjY0NWR/4fD5Wr15Nqr6zB9uxY8fiypUrUFBQQGxsLLmvj48Pjh8/3uE737x5M3Jycqgxwv3/NTU1REJh3rx5pM8jIyNhYWGBKVOmUBIsd+/eJXqJPB4PCxcuhK+vL9kLAcF+eODAAYiJiZHiUaydPHmSpJRytXjr6urI+seuLWvWrCHag39l7Q/IeXl50NPTI2Df/fv3wTAMxU4tKyvDmDFjEBsbS37/7NkzMh4vXLgAOzs7iIiIUNIMNTU1iIiIoJ6L1SRm5+3Tp08xdOhQuLu7U0ywTZs24fPnz2T9Tk5OJtru7Do+ffp0DB48mIyVOXPmoFevXvD19aV02ENCQoQK6cTFxcHd3Z08T3R0NAFza2pq4OTkhOXLl1O/mTdvHsTFxZGWliakgwkI3nF+fj709PSoYmHc9XHnzp0YOXIkwsLCMHnyZDKPMjMzoaKiQoJcx48fB8MwlE+wcuVKiIqKwtDQkALQ4uLisGDBAqH2sMZNlweAgQMHokuXLujTpw9V1LEjY383b948ODo6wsHBAaKiolBVVSX+Wnv/iv3Nzp07SaFRboYHIFivpaWlhTKV8vLyqP46dOgQtLS0cODAATQ1NaGiogIjRoxAz549iY7+r1+/EBISgn79+oHP52Pbtm2YPn06hg4dirt375Lxwf6XZdCGhoYiKCiI6psDBw7AzMyMCuKxf+e2q7S0lNKsFxERofSkWVu5ciUUFRWhoqICRUVFqKmpkbX55cuXkJGRQWRkJAXEJiQkQExMjPJNfpepxUp/cNcH9jmCg4Mxffp08ls2WN3Y2IiUlBQwDENlLbH3aX+vefPmQV1dHXv27MGrV6+gr68PHx8fnDhxggCxFy5cwJQpUzB9+nRKx/yvfO/2a5GXlxcUFRU7lJQCBAziPn36EH8yJiYGp06dAp/Px9evXzFw4EBKyuHFixeYMGECFBQUSKZZe6Zma2srWWcHDBgANTU1xMXFYevWrcjKyoKurq5QxkFrayt4PB4OHDhAgvOs/3HgwAFkZGSgW7duWLBgAVWHgf3tixcvSNFaLhA7a9YsdOvWjfI1uWz0X79+ob6+HioqKvj8+TPy8/OF5KsWLVokJF/FNS4Qyw2WXbx4EVeuXKHOUax9/PgRPXv2hIuLC+XzXLhwAcnJyZQ2eKd12v8G6wRhO63TOu2/0rhOV3p6Onx8fKCrq4sJEyYQ57OlpQVLliyBq6srPD09ERgYCBUVFWrjf/XqFRQVFSmnirXm5mbqIMsam3ZjbGwMCQkJoqUEdByd5bZ19uzZ6Nq1K1asWIHCwkLcvHkT6urq8PPzIwfdHTt2wNzcXIiJ8jvjsk651p4Ndu/ePXh7eyM8PJwwMQHBAYTbRvY6/fv3x/r16/H48WPKCWttbcX69euFDgJJSUnQ1tZGVFQUevfuDQkJCUqv78GDBzA0NISlpSXVtqVLl0JGRgbR0dGwtbWFiooKBZQDghRCMzMzipm3evVqUlmbC/4BArDJ2dkZFhYWFNjJ9tfGjRvh7OxMsUXbO3hcplxqairMzMyQmZlJHYx9fX2hq6uL8+fPo7y8HOHh4RgxYgR4PB74fD6+fPmCgIAA+Pj4EDD0y5cv6N27N3r06IHly5dj7dq1CAkJgbW1NaUrePfuXTx9+pQ4u4cPH4aIiAiSkpKod93+ALJ27VooKysjISEBXl5esLOzIwWFqqurMXToULi5ucHPzw+TJk0Cj8dDQUEBrKysSFp+fn4+JCQkEBYWBj09PSqt8PLly+SeNTU1JA2zZ8+epG/YMVlUVIT169djwYIFOHDgAOV819bWwt7eHkVFRcjNzaXGWFNTE7Zv3y6kQft/UgH34cOH8PHxgbS0tFBK3vPnz2FhYQFPT0+h4jTHjh3Dz58/UVBQAD09PQKisNp3zs7OKC8vp+b+smXLsHHjRvB4PIwZMwZOTk4UkwQQjIOQkBCitSkqKooVK1Zg0aJF8PPzg6WlpVChHtaOHz9OaYgaGRnByMgIMjIyVJppWVkZAgMDoaWlJRTU4fF4SE5OhqKiIkaPHo3o6GjIy8tj9OjRRLstOzsbBgYGlDRBbm4u1NXVYWBgQBX/ePbsGaZOnQpRUVFoaGjAysoK7u7uCAgIwObNm6n5VVlZibt37xLQiq3CbmlpCX9/f4wfP55iA23btg2hoaEAQDSN2RTv6upq3Lp1C9OnT6cOeGyxKVaTlS2myAKxLi4uWL16NVnj2TFtbGyMHj16IDs7WwhwXL9+PVxdXeHk5AQ/Pz+yn+zduxdaWloEbBgxYgQ8PDyE5Dg+ffqEkJAQCkR8+PAhLly4gKKiIgJWNTY2wsbGhujQNjY2YtCgQThy5Ah5t/fu3SMZGo6OjsjOzkZ1dTUqKyuhoKBA5hI7ftjMhS5duiAkJAQ5OTlk/Vu8eDG6deuGffv24dmzZ3j69CmCg4NhYmICKysrbNiwAfHx8WAYhkpV/51xx2tDQwNOnjxJiggeOnSIYrLW1NQQcPbjx4/kt7Nnz4abmxsBwT5+/IghQ4bA0tISWVlZaGhowLNnzxAWFgY7OzsyXjZs2IDw8HC4urpi9erVJO3/2bNnGDZsGJycnJCUlITw8HBoaGiQ8ZKYmIguXbpg4MCBJFjQ1NSEwMBAwjxkwfGTJ0+S51u5ciUsLCzg4+NDUs7ZsbRnzx44ODgQSR624BSfz0dtbS3s7OxIZgJ3D+vduzfU1NSwfPlyAqBw7ejRozA1NSX67u37nDXu/sZqU7N+xZEjRyArK0vGSXV1NQXu9+nTBz4+PmSt7N+//299ksTERGhqapL1Kjw8HF26dIGrqyu0tbVhZGREFW/kGnvPrKwsiIqKQk5ODpcuXUJeXh6pGs9NReb+5tixYxAXF4ekpCTFwOdemwVi2QJ8ISEhCA0Npfqrra2NjCN2jr169Qrjx49Ht27d0LNnT5iYmMDGxgYtLS1ITU2FsrIyJk+eDD8/P9jY2GDFihVE/qq2thYHDx6Ej48PCTwC//Kt1qxZA319fWqNY+3s2bNUVgafzyfPzUppzZ8/v8PCbDdv3oSvry+MjIywfft2AiSyQGx7Ruy0adMgKSmJffv2UX7E4cOHkZGRgRkzZpA1fvHixejevTs2b96M4uJifP/+HREREVi+fHmHADIg8MNmzpxJsS+5TFr23zdv3oS1tTXx3W/fvg0JCQkYGBjA3Nwcp06dIvI57Jiuqanp0D/vyLj929LSAh0dHXTv3l0oiAcICAE9e/aEv78/7OzsYGpqCh6Ph6ysLMjLy8PW1lZI1quwsBCDBg2CqqoqFdBoaGig+nXPnj1ISEiggp3fv3+HtbU1bt++3eEcfvv2Lb58+YJPnz7Bzs6OZIz8/PkTioqKEBMTI3theysuLoampiYCAwMpIHbOnDlEEol7z+TkZAwaNAiAAHzu3bs3JCUlKfmoDx8+wMPDo8OCWlxjgVhTU1Oy33H74uzZs8jMzERubi5hvH/48AHGxsZwdHREfn4+Xr9+TYKRrHUCsZ32v8U6QdhO67RO+6+2OXPmQFFREYcOHcL+/fvh5+cHKysr4gi1tLRg7969mDRpEkaNGkUOQFxGl5qaGmHMcDf4/Px8rFmzBs3NzR0edM6cOQMbGxvY2tpSjErud7j/f+jQoejevTtV0R4QACXy8vKIj48nvzl79izVln9S2KKjojTt7cGDB/D19UVwcDBWrVqF8PBwqKiodHh9tkBL165dqQNObW0tgoKCMHfuXPLZtm3boKWlRaQLzp49C4ZhIC0tTVKaAODWrVtUZec///wTo0ePJoeOiooKBAUFQUdHh7B1WPv8+TNaW1vB5/NRV1eHiIgI4pB2xECsqKiAjo4O0Xbj2vr162FlZUUdcLlABRd8SUtLg7KyMm7evNlh+ltQUBDU1NRgYmICMzMzoe98/PgR/v7+8PLyIof32tpazJkzB9bW1nB3d8eAAQPI4eL48eMwNjZGz5494erqCldXVwJ8HD9+HN27d0dqamqHRdQAQZXi8+fPAxA48CkpKTA2NqZkHioqKsg7KC0tRX19PVasWIHa2lpcvnwZKioq2LFjB8rLy+Hi4gJZWVmSQsvaypUrMXHiRBQXF+PIkSPo2rUr5s6d22EBHu78Yd/hr1+/iI6agoICBVaVlJQgJCTkL4vd/ZX9br48f/4cAQEBQgVFAAFrctCgQUIHffa/K1eupArRZWVlYeTIkVTRoZaWFjQ2NsLW1pYEOsrKyoge6cePH9HQ0IBv374hNDQUbm5uaG1tRVNTE9atWweGYWBkZAQHBwchXTxAwFrl6pkuXLgQqqqquHbtGmprazFx4kQwDEOlZpeVlcHW1ha9e/emnvfu3bvQ0dGh2HTHjx+Hra0tYc/V1dVh3759iI6OJv1y9epVDBgwAN27d8eZM2eoa/J4PBQWFuLs2bN4+PAhKioqYGFhgd27d1PPEB0dDYZhICMjQwG87dk17OH52LFjiImJwb59+yiwHhCwxAcMGAAPDw/Y2dnh3r17ePLkCfT19XHr1i3s378fo0aNgo6ODjk4NjU1Ydy4cdDX1ydrW1tbG86cOYMuXbqQw3ljYyM+f/6MnJwckh6ek5OD6dOnU0BxaWkpwsLC0K9fPzQ3N6O4uBhKSkpwcHDAt2/f0NzcjB8/flDvHBBoDRsYGMDExAQWFhaIiYnBo0eP0NjYiCFDhpCU8sDAQNjb25N3EB8fT8D//Px8kpoeEBCARYsWYfr06QgNDRUKDkybNg0yMjLQ0dEhQS02+JecnAwZGRmoqKjA3t4eAQEBaGpqwuTJk6GmpgYpKSkyVv7qIMy93+7duzFjxgxkZmbC0dERV65cgYyMDMVYPHr0KMaNG0fJPMyePRuqqqo4d+4cmW+AYD2Li4uDjo4OZGRkYGdnBx8fH7IWJicnQ0lJCenp6YiPj4e9vT0GDx5MQNWXL18iNTUVnp6eiIqKIr87d+4chg8fjrCwMLi4uCA9PZ1IMOzbt4/Ij1hZWcHKyooqHFVSUgJFRUWIiIgIyf2w82fq1KmYPn26UJr3sGHDYGhoSD5n2xMfHw8HBweoqqqSTIH2xTyVlZWFArB8Ph+XL18WYvSz3wsJCUFqaipu375NAeF8Ph/z5s3D6tWryXc/fPiA3r17w9PTE4cOHcLo0aOxefNmvH37Fm/fvsWHDx/w8eNH3L17F+/fv4eNjQ3s7e2xcOFCdO/enTB8m5qa4O/vDx0dHSEpEu4a6+Pjg+7du1P+wpMnT+Dj4wN1dXUC1LDPWl1dDXNzc4iJiRH/DRCw8q9fv44HDx6Q1OaLFy9CSUkJJiYmlN7myZMnSV/x+XxERUXB0tISR48eJf19+/Zt7NixA8eOHUNrayt27NhBsbovXboEhmFgaWmJ9PR01NTU4OfPn1i3bh0JcgI0EPjhwwdISUlh4sSJVH/U1NQgMjKyw+KarE2bNg2ioqJCIBh3fIwePRo9e/bEtm3b/haIHTFiBHx9fcm/k5KSoKOjgz59+qB3795gGAZHjx5FXV0dVq5cCSkpKWhra0NXVxeWlpbU2OvIWCC2o8wF1l6+fEn+dvnyZSgqKmLPnj1obW2FhoYGvL29qSDu4sWL4eTkBDc3NwwZMqRDxjhr3HZt27YNO3fuhLOzM5ycnH4rKbV27VpMmzYNCQkJ5L2VlZXBy8uL0vbm2qtXrxAaGoqwsDAAgjnK9iGrcw/8K7jf2tqKuro6hIaGwtvbmwr6//r1S0i3/PHjxzAzMyPjlQU5t23bRklz7dmzB6WlpaTdRUVFQkBsbW0ttm7dSgVprl27Bnt7e9y9e5dkfmhpaVHEB7a9AQEB/wgMLSkpQUJCAuTk5ChZpaSkJKiqqsLW1hY6OjqwsLAgQG9FRQUcHR2hqKgITU1N2Nvb/63sRKd12n+jdYKwndZpnfZfa+fPn4eFhQVhWFy5cgXi4uJwdnaGubk5Ll26BIBmEgACB4f778GDB0NFRYViwNXX1yMsLAwTJkygvstNaQcE6UEODg4YNGgQxfRo75CuWrUK3bt3h7S0NMLDw8nn7AF4/fr1sLS0pFKb3759i9LS0r9M+/nd/f7qO48ePcLAgQPh7OxM6Y3du3cPFy9exNu3b1FfX4+WlhaMGDECGhoauHHjBhobG/H27Vvo6OjAyMiIOHnV1dVIS0sjzNjTp0+T4i4TJ06EjIwMYaFx7cCBA4RByWW+smmwHaVoAQLntbGxEVZWVpQmJGuNjY3kXVZXV3foLF65cgWioqLIzMykDkfse2cPp58/f4azszM5CH/+/Bk3btzAlClTKFDz4MGDmDBhAhiGwbBhw5CcnIx3796R9/n9+3f06tULHh4eVPpfeXk5Sc8HBI4wt7ARm1bLvRebQjp//nwhZsGVK1fQq1cvitn97t07pKSkwNTUFCtXrqTGSkpKCnr37o3KykrSD3FxcRTbdvTo0XB1dcXIkSPJb7l6hGzRj+3bt6Nr165YsmQJ1S5u/3/58gUNDQ3kgHHixAmIiYlRjn5NTQ3CwsIo6Yp/x7jPl52djc2bN2P//v0k9fOPP/6Av78/evXq1eG4BDoGcUePHg1bW1sAgkNM7969MWPGDDAMgzFjxpC2Njc3w9TUlDqoPXz4EIqKirC2toaRkRHc3d2pwwU7pjdv3gwJCQnMnDlTqB1BQUHQ1NSktBNDQ0MJ2/zUqVOQl5fHkCFD0LVrVyxevJhc/9u3b0LPdOvWLWhra6O4uJjqs8OHD0NMTAxPnjyhmEfc9jx58gQREREwMDCgChy2trZiyZIl5OBfVlYGMzMzjBs3DqdPnybFqOLj43Hx4kXk5+dDRUWFZBNwD1vcNl27dg0GBgbo3r07YXUDgvkaGhqKcePG4ebNmxgwYADs7e2RnJxMyTUUFhZi3Lhx0NLSIvOvsbGRqs4MCAAANTU11NfX49GjR0hKSoKJiQnExMTg5eVFgPGcnBzC7mHnTW5uLkRFRYmcRn5+PqSlpeHg4AAzMzN4enpSBdfWr18PNTU1wj5PTEyEjIwM6c8HDx6QdPa+ffuSvikvL0e/fv2EgIDHjx9j27ZtMDQ0RI8ePSAiIkIO7G1tbXj37h0iIyPx4sULlJeX48CBA7C3t0dISAhp0x9//IH79+/j+fPn5H47d+6EgoICzM3NsX79esIs7WiOtC8aKSYmhjNnzqCmpgZWVlZgGIZiATc1NSEiIgLDhg2jJAiMjIzI81VXV6O4uBg7d+4k+0FZWRlOnDiBZ8+ekXbs27cPJiYmhDWZm5sLMTExGBoaIioqigCx9fX1OHz4MGF8TZ06Ffb29oSZlpCQAAcHByxevJgAwIcPH8bw4cMRExNDAg/Tpk0j47a0tBTy8vIIDg7+W+1qbvp0WVkZrKys4OzsjNraWjKWYmJiUFBQQKQx2vf1ly9foK+vTxW1BARrZ0hISIfa4oCA/WptbU0VlmT7OCwsDHPmzCHXBwQBxN69e8PDwwMSEhIEbFRVVYW8vDzU1NQQGRlJUrXV1dXRtWtXGBsbCxUYDQgIgK6uLhX0YY2t0K6trS3EbtywYQMYhoGWlhbRxQQEkjtdu3alAK4NGzYgIiICDMNAUVERAQEBJN38169fuHPnDsUqZYOTLDjF5/MRGRkJS0tLHDlyRKgtPB4PGzduxMqVKwEI1gE5OTls3rwZY8aMgaKiIpYvX06kmljbtWsXEhMTMWHCBAIY79y5E9LS0hgyZAhu3bqFvLw8khHDzr1bt25hyZIlSE5OpqQApkyZIgQ+A/T8Gzly5G+B2KioKCJRA/xrLh87dgzq6uokAH79+nUwDEMVwHr69CkuX76MkydPdphW3pFVVFRg4sSJcHd3J/3cvl+/f/+O5uZmMg5Z/VlfX1/06NEDEyZMACAojiYrK4sVK1YgLS0NZmZm6NmzJ/G/25Mg2GfLysoCwzAUGOjr6wtNTU1cvnyZeob2euHs375+/Qp7e3tYWlpS/cdaWVkZ2trakJqaClVVVaSnp2P+/Pno2bMnJetTW1uLRYsWkUwqbkB90aJFsLW1hZeXF5Vld+nSJSgqKiIzMxN37txBREQE5TelpKRARkYG+vr6kJCQwJo1a8g8Lioqgra2NoKDg/H9+3dKn5jH4yEnJwfDhw+nggINDQ2k0Ky7uzuGDx8ONzc3anz+E//s5cuXWLt2Lfnu0aNHoaysjNu3b6OtrY1IG2loaFDyJ1evXsW1a9f+8RjrtE77b7NOELbTOq3T/mutqKiI6MCdO3cOSkpK2L59O+7evQttbW2YmZkJsd2WLFkCNzc3REVFEWCrtrYWISEhkJSUREpKClJSUuDn5wcLCwtyOOXz+VizZg0iIiLIoZ8FJ06ePAknJycMHjy4w5S7zZs3Q1xcHGvXrsX48ePRvXt3clBnjZUgYNk3CxYsgLW1NUxNTaGpqYk9e/b8tjgK1+ncuHEjVUzpd1ZdXU2xpKZNmwZ1dXXIyMjA3Nyc6LiVlpZi4MCBEBERgb6+PszMzKCmpkZF8wEBsPv+/Xu8fv0aJiYm2LBhAwABEMHqDXLBGtb69+8PhmGwe/duCuypq6tDSEgIREVFO9TGraurg6enJ6Kjo4X6oLi4GBMnTqQOwx05i2xF+6VLlyI/Px8FBQUICgqiUlvr6+vh6uqK6dOnk2rtjo6O8PPzQ9euXYlGHp/Px+TJk8EwDBwdHWFrawsDAwMYGBhg3rx5uHLlCsrKyuDr64u+ffsKsVj4fD74fD6WLFmCsWPHAhCkLmtra2Py5MnkeywAcvLkSZIyDgi0cSUlJaGpqQkxMTGkpqZS13///j1mzZoFOTk5osP4xx9/wNHRkWIntba2wsnJiRx4GhsbMWDAAOzfv5/08eXLl6Gvr0+KW3EtKysL3bp1EwJi2f62srKCpaUl/Pz8yEFvzZo1YBgGERERCAsLg4+PD6ysrP4tR5/bj6wlJiZCQUEBJiYmpBI2m+74+PFjBAQEICwsjBRz+Tt7/vw5ZGVlYWRkBBMTE1LVOTc3F7Kyshg9ejT5rqmpKa5evQrgX4eH79+/Y8+ePcjIyMCJEyfQ2tqK169f486dO6iqqqJSVRmGoaqZh4aGUizrtrY2fP/+HZmZmWhsbMSNGzegqalJpBLi4uLAMAxSUlLI2OK2BfgX4M+uWWw6NJ/Ph76+PsVaYjXoEhISUFRUhLa2Njx//hwDBgyAtbU1edYbN26gZ8+eiIiIIAf/U6dOkZRke3t7XLt2jfyturoaHh4emD17NvXudu3ahRUrVhCwAxCAlgzDYMGCBcjLy8ONGzcQFBREyXg8fPiQaP2xRZ9YKywsxPjx46Grq4u9e/d2GChoaGggQSY5OTmMHz8ex48fR1lZGSQkJHDw4EF8/vyZrGkzZ85ETk4O2ScSEhIgLy9P5uaff/6JrKwsLF26FElJSeTzxsZGDB48mOgt5+bmQkZGhgCU9fX1RBOQG6RZs2YN9PT04OPjQ3SN2wMajY2NOHToEPz9/REYGIimpibs2bMHzs7OiIqKImt3S0sLsrOzYW9vj+DgYPL+22vVlpSUoLS0FJMnT4ajoyMyMjKEWFrcPgQEAJCYmBjGjh1L2KHHjx+HmZkZwsPD8ejRI+Tk5CAkJISSp+Hz+SgqKoK1tTXy8vJw584dTJo0CWZmZjA0NISOjo7Qns6288CBA8QfyM3NhYKCAjZs2EBAm0GDBqGqqopkmoiKisLW1hYyMjJ4+fIldT0WiF2yZAkBYr9+/YrY2FgYGxsjJiYGYmJiVJCwuLgYsrKyiIyMJABNe+3L9sbn83H79m3Y29tDVVWVFIE0NDQEIPAd7OzshNbAlpYWbN26Febm5ggPD8fDhw+Rm5uL0NBQaj4UFBQgPz8fX79+RWtrKz5//ozIyEjY2NgQYK2kpAShoaFwdHQEj8fD4sWLERISQtbnjx8/ol+/fnB2dkZSUhJ+/vyJHz9+4MWLFygrK6OyWliwvmvXrgRs5WYWBAcHo3v37lR/Z2ZmQlpaGjNnzoS1tTU2bdpE+ToXLlzA0KFDMXToUPj7++PLly94/fo11NTUYGZmBicnJ1y/fh3h4eEwNzdHQkICnj9/jtzcXNja2iIjI0NojqSlpUFRURH37t0TYtnx+Xz06dMHtra22LFjhxDT8927d/j69Svev38Pa2trEhR6//49FBQUoKOjQ0k1JScnQ1tbG6NGjSJBu40bN6K6uhp5eXkwNjaGlpYWzMzMEBoaSu53/PhxyMjIEPDf3NycymaYNm0apKSkcPDgwd8G4YcPH94hECsvLw8PDw8q6N/W1ob169djzJgxAASAvbS0NMk6qKysJP4H1/7p/syVu/hde+vq6uDs7Iy1a9eSNo0aNQoPHz5EW1sbrly5gnnz5lGgcEtLC7y9vWFmZkb5kNx9b+vWrRAXF0dERAR2795NjT8/Pz/o6Ojg3LlzpHjo8OHDAQj0Xp8+fUoxbb99+wZra2vY2tqSADTXWKkQdvyfOHECEhISUFBQQFBQEPW9mJgYMAyDxMRE8Hg87NixA0pKSlizZg2mTJkCDQ0NCryNj4+HgoICdHV14eTkRPaG9+/fw8fHB3fv3kVLSwsWLVoETU1NLF68mLzj4uJidOvWDba2tmSdbGtrQ11dHYKDgyEhIUFlpQCC/fDYsWMYM2YMxo0bh2XLllHM7n+Soce1trY2LFiwgOoHQDCnxo4di9DQUDJOudYpQdBp/xutE4TttE7rtP8K+91mX11djZaWFoSEhFBFIwICAmBsbEwxRTZu3AgFBQWkp6cTp5Yb+Z0zZw7CwsIQFBQklEY2a9YsKCoqYuHChZg0aRKMjY1hbGxM0taPHz8OV1dXhISEUOBYeXk5xo8fT0C3kpISAgRkZmaipqYGnz9/RlBQEIKDg8Hn87F48WIoKysjLy+PMO4UFRU71OLj9su2bdsgKiraoTZae+M6Nbm5uTA1NcX169fx559/YteuXfDy8oKbmxs5gN64cQM7duzAtWvXiKO7Z88eKs0YELCTnZycSL/cu3cP06ZNw6ZNm34byQ4LC4OysjIuXrxIHYhqa2uRkJBA2lpYWIgvX74Q1sq1a9cgKiqKpKQkNDU1oaWlBdXV1QgNDUV4ePjfVlQGBKBGz549ISsrC2tra/j5+QmxE+fMmQMXFxeIiIhgxowZBEweNWoUJk2aRDEgJ0+eDBkZGdy6dQt37tzB6tWr4evrC3l5eQQEBMDe3h6ioqIwNTUVSl0FBEVgEhIS8OHDB2hpaWHcuHGkvWfOnMGGDRuECnN9+vQJLi4u+OOPP/D48WOkpaVBQkKCKqgFCNhaW7ZsQWtrK5YtW4a4uDjExcWR99LW1oaWlhbMnj0bdnZ2GDVqFHx8fGBjY0MVU9u1axcsLCyoNGFun7LsXe7Y2L17N+Tk5LB7926sXLmSaI2xbPXLly8jPj4e8fHxWLt2bYcpnH9n3Pf9+PFj+Pn54dGjR6ipqcG7d+8wbNgwSEtLE8mMJ0+ewNramgLr/o5RXlRUhLlz52L16tVUCnFubi6kpaUxbNgwtLW1wdHRkZIo4erYsTZ79mxYWFhARUUFrq6uiI+PJxqP69atQ7du3bBq1SpER0dTlaC5fcJeLz4+HsOGDSNjY8aMGfD29oaXlxd1MG0POPTt2xcaGhrUYfzHjx8wMTEhUhDJyclQV1fHqFGj4OHhAX19faxfvx4AcOfOHQwcOBC2trY4f/48WlpacOjQIbi7uyMkJISw+D98+CBUYAwQHOw9PT2p9PSUlBTIycnB3d0dCgoKcHFxIWNt6dKlcHZ2hpiYGCl6xz7fxo0bUVNTg3v37iEyMhKKiopCc6yoqAgDBgxAVFQUAMH7vnHjBq5cuUIYUh8/fsTq1atx4cIFAja2trbC3d2dyImsXr0aBgYGiImJIXq6lZWVeP36Nfz9/TFp0iQqg6GmpgbOzs7w9PQkuq9RUVG4fPkyAcNZAJYF2E6fPi0EKly7dg0WFhaQl5cna+zvWOc5OTmwtrbGmzdvsGLFCpibm8PY2Jjqj5aWFuTk5MDJyQkODg7U2lJQUIDi4mJyH1bCwdHREatXryagbWJiIiXfEhISgi5dusDKygpGRkYwNjYmAQU2c0RBQQGOjo6Ijo4WCrawbDNnZ2eIiIhg8uTJOH36NN6+fQsnJyds27btt/P048ePJJ2VTYf//v07DAwMICIigqFDh5LvsoxJLrDFnR/Tpk2Ds7MzUlNTSWHPoqIi9OzZE127diXZCq2treR3xcXFkJOTg7e3N9mv/0mWSl1dHVasWIGZM2diwYIFBFwZNWoUwsPDhTJwAMH+ePr0aTg6OkJJSQnm5uYICwsjbUlKSoKCggJUVFQgJyeHCRMm4M8//0RJSQl69+4NDQ0NkhLs6emJlpYWzJo1C2pqajhw4AD1Tj99+oTevXvDx8eHFPS5cuUK0aKcMGEC4uPj8evXL/L+rK2tCUjF1Qxl9/SjR4+SNrKMzvHjx8PW1hZLlizBmzdv8OXLF0RGRiIpKQkHDx6EqqoqYbZevXoVV69ehZOTE4yMjODi4oJbt25RII6bmxsmTZpE9du3b9/g7e1NfLIPHz7gypUrGD58ONE+5/P5cHNzw7Bhw8i/uXMREOxZJiYmRHP+3r17iIuLw4oVK8hYvnjxIrS1tUmg88KFC0J7Y0NDA5YtW0bpc5aUlMDQ0JCMsZKSEkqyirWRI0dCVVWV7APv37/Hx48fCasbEEhetAdi//jjDwQFBQn5SLNmzUJERAQuXLhAyVUAghT9iRMndpga/v8rkKy+vh5ubm7w8vJCWloa/P39YWNjg7a2Nty6dQs6OjqQkpLC2bNnAfxrX62qqoKWlhZVJJcLwIqKikJCQgIBAQFQUlJC//79Ke3W4OBgqKmpwdjYmASA582bB0NDQ+jr65NiWOw+9O3bN9jY2MDBwYFifAPA/v37CaP8zJkzUFBQwPr163Ho0CGIiopSoGplZSWysrKgoqKCadOmYfv27WTfbWxsRG5uLuTl5dG3b1/ym/v37+Px48ekz799+4aysjIkJCRQYzQ9PV0IiD148CAOHDhA3iHrS//48QPDhg2DtrY21q9fLzQuuNctLCxEUVER2Sv+CojljhV231u7di0sLCwIS5e1I0eOQFJSskNgu9M67X+jdYKwndZpnfY/3ribfElJiRBr5du3b9DR0SEHgvLycsTGxiI7O5tK816+fDlx3qqqqrBlyxYYGBgQ5iEAIYYPj8dDSUkJjIyMyG8BwaHEw8MD5ubm5LNDhw5hzJgxQk5JewZrUVERxo4dC4ZhoKmpiREjRsDf3x+NjY0kFZ8FUk+ePEkVd2Gv3dbWRjm+ixcvhpSUlFD12o6Me5g7fvw4EhISqMrSfD4f+fn5cHFxwYwZM8Dj8TB79mxERkYSx+nbt29wc3ODj48PpeG2f/9+MAyDBw8eoKysDJGRkdTBNycnB6tXr8a+ffsokCo4OBiqqqq4ePFih8BbamoqdHR0oKenh6ioKAKkHTx4EKKionB2doabmxvc3NwoFuU/idSXlZXh5cuXePnyJfk+tw11dXV4//69UIEvT09P4mwD/2ISDhgwACoqKgSsbWxsxLdv37Bu3TokJCRAVlYWXl5e5P09ePCApLiuWbMGjo6O0NbWxrhx48j7aGlpwbhx4zBt2jSqgMvSpUsRERGBkSNHEkf558+fyMjIgKysLJFraH+AX7x4MRiGgaGhoVDxocLCQsyePRtBQUGIi4sTAkk2b94MU1NTciBhGSd8Ph/Hjx9HcXEx9R4vXbqEyZMnU8UdGhsbMX78eEhKSlKsMa7904MdN0UVEKQOBwYGolevXlRfNTU1oV+/frC0tCSpyW/evEFbWxslRfI76whM4QLYubm5kJCQQEhICAwNDaGpqQkvLy+Svmhra4uUlBQAAn1Z7hgZOHAglJWVSfp4c3MzYX4aGhqSd3DixAns2rULN27cIIzG+vp6eHl5EQZTS0sLoqKiCFDKtn3dunWIjo7G8OHDSTGgL1++wMfHh6wxWVlZCA0Nha2tLVpbW5GdnQ0tLS3C+GP1D7lpsCyDnKu9vHv3bri5uaFfv35knLTXrP727RvCwsLg7OxM/lZVVYW+ffvi2bNnqK+vx8uXL2Fubg47OztyiPv27RuKiopw8uRJSEtL4969e4iPj4eYmBiRC7h79y4p9MddZwAB64YdazNnzoShoSHs7OygoqKCiIgIcg3gX3M3PDwcDg4OZI69fv0aU6ZMwcqVK4nOtYGBAY4fP44hQ4bAwcGBAC/sGMnKyoKVlRVhoo8dOxYKCgqQlJSkqof//PkTfn5+RO8aEAA8bLvu3LkDXV1d+Pv7k793BMTW1dVBVVUVeXl5qK6uxtatW6Gurk6AJdZaWlqwf/9+jBw5klwnJSUFGhoaUFNTg6+vLwEGmpubMX78eDg5OWHgwIEIDg6GoqIiecb58+eDYRgsWbIEgGBtXbZsGTQ0NKjxWFJSgoqKCjKn3rx5g69fvxLGWVlZGU6ePImbN29S887Z2ZnSA/7x4wc+fPhApQ8/ePAAWlpaRLOzpKQEMTExiIyMpL63fft2rF+/HnJyctQexV0zxo0bh+HDh5N+efv2LcLDw0naOCsFwufzCSgRHx+PLl26EKCf/fs/sfXr16OgoABfv37FlClTIC8vL+TvdHS94uJifP78mXx+4cIF6Onp4cqVK/j27Ru2bt0KLy8vxMTE4MuXL/j16xeePXuG/fv3486dO2htbcWTJ09gaGiIvLw86trseGIZsebm5sjOzsbgwYPh4uKC0NBQSElJUWvo169fiV4+O265Y3TmzJmQkpKCk5MTGIZBXFwc6fdp06bByckJIiIiRGcdEKTvy8jI4MmTJ4iPj0efPn2IhENHqeHl5eXw9fUlWTmstbS0wMHBAaNHj8a1a9cIyzcsLAzdunXDqFGjSB+3tbUhIyMDERER8PX1RUZGBgE4L1y4ACMjI+zatQslJSUwNjYmGSRsv+3evRuRkZEABNI43IKCVVVVePz4MebOnQuGYUiQqq2tDTdv3oSFhQUAAbCqra2N8ePHk2uzEibsOgoICjTa29tDQUEBnp6elFTTsGHDYGxsjO3bt+Pnz5+Uf8N9L/fu3YODgwNERESofqutrUVkZCQmT54MPp+Pw4cPIysri1q3fhcw5Y7V169fC6X6t/8euyf5+voiIiKC7H3v37/H/PnzIScnR/Y69r6NjY3w9PQUKhy3evVqyMjIwMPDg+ytly9fRkBAAMLDw4l2PiDwJQ8dOgQej4dFixZBXV0deXl5aG1tRWxsLOTl5bF27Vriz3/79g1qamoYMWKE0LN8+PABlZWVcHZ2xtKlSwEI5o+BgQEYhsGkSZPI81ZVVZG1WVJSkpJLaGlpwenTp6GoqEiyvrg2c+ZM2NjYQFpaGhYWFkJSKEuWLIGuri5SUlJgZWWFsLAwcnbYvXs3goKCyLz9/v07+vfvD09PTxLomjJlChWgnTlzJlRVVaGrqwtra2sh35Fr3P1+8uTJGDp0KCorK3HlyhXo6Ohg48aNVCD/0aNHsLGxoYp9dlqn/W+2ThC20zqt0/5rLCUlBZqamlBQUEBISAiKi4tJOk10dDR8fX2xadMmBAYGwtPTkziX169fh5aWFpSVlamqs1VVVcjMzISRkREBvLjGOkkPHz6ErKwscQ7Yz1+9egUdHR0KXGLt78C/kpISTJw4EUZGRoSxAwgOo6qqqigtLSUMKfbQ2dDQgHnz5lGHLUDA6OnatSs0NTX/LemCNWvWQF1dHQzDICQkROi7LBOopaUFy5Ytg6enJ0aOHEmlN4WHhyMgIIAAC4CAXccwDAwMDCj9qKSkJKioqMDDwwN6enowNTUlDiogYFBpamoiNzeXcugvXboETU1NXLx4EWvXrkXfvn1hbGxMtP9KSkqwaNEipKam/lssyt8djP+qwFl9fT2ePHmCXr16QV9fn6R/jxs3DrGxsQAE737w4MGQlZXtsIBDaWkpYWrU19fDxcWFMLZbWlrg4uICSUlJosvY0NCAWbNmQV1dnarK29rais2bN0NKSgq2trbUmPv58ydWrlwJBQUFAvwBoH6/bds2oi3bfrx0pNnGWlFREbp160Yxz4F/6aRy9QivXbsGa2tryMvLEwYV++y/fv2Ci4sLSUX/TzS/5s2bR5glbPr29OnTYWBgAF1dXSE9sVOnTkFPTw+ZmZlISEgAIEg9DgsLI8DsX1l7YLh98bzTp09DX18fSkpKOHLkCPbu3YstW7Zg69atyMrKIsWuQkNDyWH8woULkJKSIun/zc3N5H/cuZCYmAhVVVVoaGjA0tISEydOJO+N1U2MiYmBjY0NKa506tQp8Pl8LFu2DFJSUpgyZQoiIiKgp6eHwMBAAAKwbuLEiTA1NYWjoyOlP7px40Zy+Dt48CBkZGSoqvYsa+X58+dk/K1duxaDBg2CoaEhGIZBnz59qMPWjx8/kJGRgdDQULK+AIL1yNjYGKGhoUS/FxAc3C0sLODg4CCkjx0REQE5OTlISUkJgfG3bt1CTEwMbG1tO5TOWL9+PZSVlUlAZ8uWLWAYhgAcPB4Pe/bsgZubG0xMTHDr1i00NTWRd56WlobQ0FDCQlu0aBGGDh2KgQMHgmEYBAUFCekT+vn5wcHBAYAgi8Pf3x9aWlpoaGhAbW0tvn//jpCQELi6upL7pKamwt7eHtu3b0d9fT1JYdfU1ESvXr2o8dce6JKQkMDRo0fR2tqK1tZWZGZmwsbGBiNHjqT6gstYun37NpEbYQOL2traZI1vaWnB4sWLERcXh0GDBpHfZmRkQF9fH7a2tlQw89u3b5g5cyY8PT1JoSTuXE9LS4OtrS1MTExgb29P9mj2Werr6/Hp0yeEhISQ4AAgkOzx8fGBjIwMhgwZQkDr0tJSWFlZYfLkyXj8+DFCQkIQHR1N3kVGRgaRzwAEGuYyMjIUEMuOH/a9sf9ta2sDj8fDs2fPMGTIEFhYWBAglm3zH3/8AR8fHwQFBVH6338FxPL5fDx9+hRiYmKIiYlBamoqyW74q9+1LyIIAJs2bcKSJUsoPUlAEHC1srKi/A2unT17Fjo6OmSOcdO52eDDu3fvkJycjNbWVnz8+JHo/C5cuJBch8totrW1hYODAwWsvH//Ht7e3nj8+DFqampw9+5dyMjIoG/fvmTcfPjwASdPnsSVK1dI4UIPDw+IiYnB3t4esrKyQhXquX1SXl6O8PBwuLi4kLGWl5dHfIZNmzbBzs4OYmJiSElJIfu0n58funTpQiQvFixYADk5OSQkJCA+Ph49evRAdHQ0ioqK0NraiujoaOjq6kJJSQlSUlIEYGT77ciRIwgICMCePXuo1H5AEFDr06cPHB0diSQOW3zs2bNnCAwMxP3790lAlltMdtKkSVTGVXp6OhQUFJCbm4tDhw5hwYIF6NGjBxVcHzVqFKSlpYkOOp/PR05ODjZt2kRYoY2NjZgxYwZMTU0xf/58fPr0CREREVBWVoatrS14PB6mTZsGBQUFmJmZQVtbm4DMgLDPxR2X69evh7a29j8C7hoaGtDQ0CAko/Pt2zcsXLgQWlpaQpJL1tbWBIRl52nPnj1hbW2NoKAgwmYHBCzuwMBARERECAUdXr58CX9/f0K6YNmoYWFhYBgG69atI4xiboHT9s/7xx9/QFtbmzC33717h0GDBiE/P1+ITVxfX4+srCwoKChQskaAYL09c+YMGIah9I9PnDgBVVVV7Ny5ExMnToSmpqaQDBcg2AecnZ1hZmZG+qC5uRk5OTnw8PDAgAEDSKDn27dviImJgaenJ1atWgVdXV2YmZmRYnfa2to4f/48srOzERgYCDU1tQ7rNnD3oV69eqFLly6UvzJnzhySlXjz5k2UlpYiODgY3t7e/7bEQad12n+rdYKwndZpnfY/1rgOzcWLF2FiYoLc3FxcvHgRZmZmsLa2Jk71+fPn0bdvX6I5x2VClpWVYe7cuR3qBFZVVSErKwtSUlIdaocBAgdJX19fqAhUVVUVTE1NsXbtWspx6EgvryN79uwZJk+eDFNTUwooGzx4MEJDQyEhIUEBvJ8+fYKnpycOHDhAPgsNDQXDMJg7d+7fShdwny0rKwuioqLYtWsXwsLCoKmpicOHD1NpR4cOHYKlpSUBRDZu3AgPDw8MGzaMHKZfvXqFkJAQ+Pv7U0Ds6dOnceHCBeKgZmdnQ0VFhYAhpaWlWLRoEbS0tCjGl4uLCyIiIsi/Dxw4gDlz5lA6t/fv30d0dDSMjIwIu6G1tfW3abl/Z/+UpcS2Jzo6GgEBAYiKioKbmxt69eoFOTk5irHEArFycnLkwN/+Pmx7z58/Dzk5OXIY+Pz5M5G7MDc3R0hICNTU1AhYxDVW77F79+5Ch+7y8nLMnz+fyFwcPHgQtra2lAYqqz+6bNkyCoTk9mVH/ZOVlYXu3btj6tSpuHTpEq5fv47g4GBKjxAQOPtLly6FhoYGAgICyD3YA36vXr0ohs+/a0+fPiX3YwFBNr1TQ0MDY8aMoSQAWJYcC1C5ublBWlqaOtD+zrj90JG+MSA4MJ09exby8vKYNm1ah9+pr6+Hr68vCgsLkZeXRwVampqasG3bNty+fZu63+PHjxEcHIwnT57g58+fWLVqFdzc3DB48GBysMnMzMTAgQMxdepUPHjwAEFBQQgKCsLevXsRGxtLpB94PB6uX78OPT09aq59+/aNgHzs92bPno2BAweioKBAKD11+/btmDdvHpXCvnz5ckhLS+PMmTMoKCjAnDlzYGdnh4iICALE3r9/H6GhoYRlz94rPz8fpqamUFVVJYdcdhy+efMG1tbW0NXVRVVVFfnd2rVrSRGeGzduCKUM37p1CwMGDIC6urrQYXHs2LGEEXz06FHIycmR98Cy8p49e4bVq1cjICAADMMgISEB169fJ9dwdnamiqPcuXMHmzdvBsMwUFNTw4IFC6jiPm/fvoWsrCySkpIACAKElpaWUFZWhqWlJZydnanq7YsXL4aSkhKuXbsmpMd4+/ZtaGlpkWrcXJs5cyaUlJRgYWEBVVVVREdH4/Hjx2hoaMDGjRtha2tLsclY2717N6ZOnYpFixaRz4qKijBx4kRoaWmRtYPP51NrLI/Hw7Zt2yAlJQU5OTmh4kvXrl1D9+7dhTTT586dCxUVFZw4cQL37t1DQEAApKSkyPzi8XhYsWIFvLy84OXlRfpl/vz5UFRUxLlz5/Do0SOEhIRAXV0dr169QmNjI5YuXQoTExNoamrC3d2dkvIICgqCrKws2YtYjVg5OTnExsaisLAQISEhFIje0RpYUFCAuLg4WFtbk0yGyMhILFu2DG/evCGV0lkW8e+uw/08Pz8f+vr6GDp0KDXO/g7AZa21tZVUcI+MjBQCe6ZPnw49PT2K7cvanTt3IC8vT0l4cPdvrnY4IJj/gwYNQmRkJLy8vEhQCfgXqH/58mWKfb1s2TKEhoZiwIAB1Lx49OgRZGRkEB0dTVKkWbt27RrGjx8PeXl5uLi4gGEYDB48WKiNgMAnW7RoEXr16gUHBwfSjuTkZJibmyMzMxPNzc2ora1FeXm5kN68k5MT7OzsIC8vj+zsbMyfP58KpP7xxx/Q0dHBgAEDyHPeunUL+fn5ZE3iAu8FBQVwdnaGuLg4BX7X19cjPDwco0aNgp2dHXr37o3z58+DYRg8f/4cnz59gq6uLhiGoTK1AEEwzsfHh/RTXV0d/P39qbW5vr4ee/bsgYyMDPEh+/btC1dXV/K7WbNmQUJCAg4ODmAYBhMnTsTPnz9RW1uLxMREWFlZQUREBDo6OhATE8PQoUNRW1uL0NBQvHjxAt+/f8e5c+egpaVFsfK5+s7s+r1161YoKCgQH/GvxnNrayv5+759+7Bw4UJMmTKFFG/99esXFi5cCDk5OQQHB2P8+PGIiYmBoaEhlZkCCGot9OzZEyoqKkJrUn5+Pnr16gU3NzeqMOzHjx+xa9cu8Hg83Lx5E+rq6iTY3rdvXygqKiI9PZ3y8zvyNz9//gxDQ0OMHDmS7N8RERGkja2trdi5cyf27t2LX79+oba2Flu3boWsrCwJELPW3NyM27dvk/ucPXsWU6ZMoYrrrVu3Dvb29pgyZYoQMzwvLw8Mw6CoqAhTp06Fl5cX6V8fHx9ER0dTQGxsbCxMTEywZcsWuLi4wMLCArt27aL88PLyckREREBVVZUEDwD63bI1H5YtWyZU5C4tLQ0ODg4QFxeHlZUVXFxc/q0Mtk7rtP926wRhO63TOu1/pLXfhB89ekQVqmlqaoKFhQUsLCzI4ZrH4+HHjx8dFqH59OkT5s+fDyMjI+qACQh0mU6ePEkdWFpaWgi40NraimnTpsHLywt79uyh2uDk5ESxGxITE7F48eK/BWK5Fc6dnZ3RpUsXks67YcMG6OrqUlp1NTU1CA0NpSrGV1dXQ0dHhxRu+ivpAq5jtHXrVsjIyJDDQlVVFby9veHk5ISsrCxUVFTg06dP8PX1RUhICOVgbtiw4bdAbEBAQIdFjlpbW7FixQq4ublRn3/+/BmJiYnw8/OjCh+w7X79+jU8PT0hKSlJvXtAAKbFxMQQhhp3vOzatQtz587FkCFDcP/+/d8yHLlMHz6fjydPnlCMvY6suroa165dI0wLe3t7MAxDpcGx/dXW1oa4uDgoKiqStLf2zDiWtdO3b18kJydTcgjbt2/HokWLsG/fPord8PDhQ5w+fRrPnz8nYFVWVhZEREQwd+5cqr1sIRrgXwykgIAAqjDY6tWrSSGov3t+bttPnToFHR0daGpqwsLCAsHBwZR0AfdZMjIyYGtri7Fjx1LfcXFxEQqM/CeWk5MDLS0tXLx4EYAAiF24cCEcHR0RExODoqIi3L9/n7AMm5ub4evrC4ZhSBEOtk2/e17Wtm7dSiQ3OrLW1lbk5uZCTk6OAjm55u/vD1tbW8jKylJF+j5+/Ag/Pz9qnTl8+DBCQ0MxZMgQitm7efNmuLq6YujQoQSIbWpqIm39448/EBAQgODgYJiZmVFsNB6Ph9OnT8PY2Jj0GXvtu3fvErbSixcvoKSkBIZhqNTTxsZGhIWFYeLEieR+9fX1CAsLo1hxPB4PO3fuhKGhIWJiYsj44jJduXrDt27dgrq6OsXMZ69fXFxM9QEgCOZ8/vwZUVFRUFFRwYULF4SAp4KCAqSkpFDPBwAODg7YtGkT7t69SwHhra2tSE5OxokTJ6j3vnPnTjg4OMDQ0JCk2xcXFyMgIEAoG+LJkydQVVUFwzCws7PDnTt3yBqXnp4OCwsLAnY1NjYiKysLmZmZyM7OJiDE58+f4eHhQY0FgN4b79y5g65du1JzaPPmzVBTUyOg2aJFiyAuLk6Azbq6OmzZsgXq6upUJsKHDx8QEREBaWlpJCYmUvdkix3q6uoKtYfbRydOnICysjJGjx5NBTb+/PNPGBsbE5YxIACRXV1dCdh45swZyMnJEc1ftr2fPn3Crl27yPsrKyuDu7s7WVPz8/OFApZ8Ph9fvnxBQUGBkMRMS0sL+vfvD0VFRYrtmp+fD1VVVZiYmJCiNx0Z93kLCgowcuRISEpKwtramkiHXLt2DVOmTIGCggKcnZ2pFOP2ABR3D1q9ejX09PSgo6ODoUOHUoGDjoAr7mfnz59HXV0d6urqEBcXBxkZGYrxCwB79+6Fk5MT2RO3bNlC9pa3b9/C0dERo0aNIuw9tt/8/f0pVuXcuXPRo0cPfPnyBe/fv8ewYcPg5uZGFfObMGECAgICKLbgkSNH0KNHDxgYGJD5wL6fx48fQ0FBgfyG/dv169cRHR2NO3fuYPHixUhKSoKNjQ2lj8oGX+7du4ekpCQkJSWR971w4UIoKyvj5s2bQkEaAISNy0pMvH79GhMmTICsrCwUFRVx7f9bzJEdDwUFBejWrRtVHIq1169fg2EY9O/fn3yWkZEBdXV1JCYm4sqVK7h06RKCg4NhZWUFHo+HoqIiSElJQVxcnApk37lzB2JiYhg9ejRu3LiBgoICJCYmQkZGhryfwsJC8Hg8aGpqUusu+1wxMTGYPHkyYcEzDINZs2bh3r178PHxQUFBAfh8PvLy8iArK4sRI0bg58+faGtrQ01NDa5du4bi4mLs378fGhoa8Pb2Rr9+/UhAqLW1Ffn5+dDS0kJAQAC5d0tLC+mvrVu3QkJCAsuWLaPWhL8LSMyYMQPKysoIDg4ma8Ly5ctRV1eHiooKLFy4EJqamrC3t8fFixc7lJICBH6xlZUVBg8eLJQtcebMGSQkJAidN1g2+OjRozF69GjweDzw+XxMmDABlpaW8PDw+NvgfXNzM7Zu3QoDAwPo6elRwaC2tjaSGbZz506SXcbKxigpKf02iPv48WM4OjpCTk6OyjoCBGxje3t7TJ06VUiTesKECRAXF6f0xAEBEOvr60sBsZ8+fcLcuXNJ8VA3NzdSiJJ7zYqKCkRGRkJTU1OIJJCZmQkREREhGQXuuvr582fcv38f9+/f/+3767RO+99qnSBsp3Vap/2Ps/Yp82yF1/aMuebmZlhaWsLa2hp3794VSmE/ePAgTp8+TQ4cZWVlWLBgAUxNTSkglus8tLa2Ij09HWFhYTA3N8fKlSuJfh1bgGbQoEFYt24dfHx8YGFhQe776NEjqKurk0P+74xNDQWAKVOmQEpKCgoKCpg6dSoAgROSmJgIGxsb2NvbIzY2Fq6urlRqf2trKz58+PCPpAu4lpWVBRkZGaLpyLajsrISvr6+EBMTg7GxMfr164fg4OAOxffXrVsHd3d3ISA2PDwcNjY2BNThvsvdu3fDxMREKEJ//vx5iIqKCunesffLzc2Ft7c39PT0hNi9BQUF8Pf3J6wUQMB40dTUxJgxYzB48GCIiIhg1apVQswfLgC7bNky9OnTB9LS0kLMmPa/4RpbSTg8PBze3t7IzMwUciTb2toQGhqK4OBg8ruHDx+Sgx1ra9asgby8PKl4/rv7pqamwtjYGAYGBqQwEQuu7dixA927d8f8+fOFDhXsNT59+gQ/Pz/4+vpSQCzLKOQCbf/Efv78idLSUrx+/bpDJ5r9rKWlBUuWLIGRkRHMzMwwZMgQ9O/fHyYmJv+R090+DffKlSsk9ZxlfDY0NGDx4sVQVFQk6a4TJkxAQ0MDqqqqsHz5csIY5IJY7cEXLqC8detWyMnJdXgAb9++w4cPk+InbFE5Fix9/vw5TExM4OjoCEAAnlZVVSEsLAze3t5kXra0tCAhIQG6urqwsbGh7sECsR4eHggNDaXSLdl+ef78OYKCgkgaJdc+f/5M0hlZu3r1KuTk5LBkyRICkmRkZEBbWxtz587F58+fcefOHaEq7Oz9QkNDMWjQIKH+YFP03d3dKaD/0qVL2LFjB3Jzc8n8vnnzJtTU1CiGJ5dVBQjA4bdv31LzOjQ0FCoqKrh06RLpv9mzZ1MM0lmzZsHMzAzV1dXYuHEj7OzsSEYAa5WVlejVqxfFLM/KykJlZSWePn2KhQsXQkREBCEhIcjKysKcOXMwa9YsUlSNvXdWVhaGDRuGfv36wc/PD1OnTsXt27dRWVkJc3Nzqvhje2ttbcXPnz+ho6PTIXussbGRaEg+f/6cAqbHjBlDgjHHjx+HrKwsCczV19ejpaUFtbW1OH78uFDQ4caNG+jTpw8UFBSEALxXr15h0KBB6NOnj1B7uW1jAZu+ffvi4MGDuHbtGsLCwmBlZUXdr7CwkBQPvHTpElRVVbF582ZSfVxWVha5ubnUe6+vr0d5eTksLCzw4cMHnDp1itr3GhsbsWPHDhQWFlK/e/PmDVXwhc/nE1YbVzO4srIS9+7d+1tAgPu87969w8mTJ7Fq1SrweDykpKRATU0N6enpmDNnDjQ1NSldXe7vudfJzMyEgoICDhw4gCtXrkBXV/cvgdj2gSFxcXEi5dDQ0IDw8HCoqakhNzcX79+/R3l5Ofz8/EhmRG1tLSwsLKCrq0t0Ww8dOgQTExOiKX3o0CH4+flRc/3t27eYM2cOlQ3w6tUrDB8+HF5eXqTIXmBgIMnwKSsrI77E2bNnISYmhvj4eAKKss9y7949BAcHC0lrbNmyBTk5Ofj58ycaGxuRkZEBS0tLoUJVqampeP/+PblmWVkZnJ2dib/z+fNnXL9+HfHx8WQ9PH36NGJjY6kg4qtXrzB9+nR069aNsA15PB4pwmZjYyO0ngKCeXv+/HkoKSlRfglbZKpbt27w8PCgWMpXr15F165d0aNHD6G189y5c9DT04OmpibMzMzg5OSEP/74A4CA7e7v74+vX79i0qRJ6N27t5BEw/jx4xEREUH6l9XsHzlyJKX3DghkceTk5DBq1CgimcRaQ0MD9u3bB1NTUxgaGgo989WrV4lOaFxcHNkf2YwraWlpaGlpwcDAgMgScd97+3+fP38e0tLS8Pf3J/vFsmXLoKCgQMbXp0+fsGjRItja2lJB8JMnT2LPnj2U35ednQ0HBwcMGzaMaEVz73327FmcPHmSYsvW19fDx8eHCkj17dsXL168+EuGPNeam5vx8+dP/PHHH9Sawq6RHWU3sdl5KioqHerNAoL3yEp9tK9VsHHjRmhqamLNmjXU5zNmzADDMBATExPyt/ft2wc/Pz/079+fqn1x6NAhVFdXo6ioCAEBAdDX1yeayFwg1s3NjQo4Z2ZmQlpaGqqqqli1ahUA+gzR2NiIwsJCIV+rkwHbaf83WScI22md1mn/o6w9ANujRw+MGzcO2tra0NLSQk5ODnUwamlpgbKyMtHUBASOuKGhIYyMjODp6Qk/Pz8S2X7//j0WLFgACwsLzJgxg7DaWMdjyZIlUFRUxPz58zFp0iSiUfjw4UNUVlZi06ZNcHV1RWBgIOXEZmRkYNGiRZRm0989Y2JiIiQkJAhzg5tix+PxcOrUKaJFlpGRQZ6bTX0E/j3pgrVr10JKSkoIQOIya0NDQ6Gnp4edO3eSA9L169dRUFBAMf82bdpEqgezQOyLFy+QmJhIHKkTJ07gzp07aGpqwv3796Gjo4P09HT8+PGDXOfly5ewtram0pna27lz5xAYGAgPDw8hILaoqIjc78yZM1QRoYcPH4JhGCo9kHUI+XxBsSsejwddXV1ISUlRBcY6Mi6AMHr0aHTt2hUlJSWor69HbGwsPDw8KCAWAEnBYj/7/v07oqOjSWozW20dAIKCgjB69OjfMrA2bdoEFRUVAhqkpKRATEyM6LnxeDzs2LEDDMOQg+OxY8eEwBSWbens7Ezd//Dhw//HLISOnGju4WPlypXQ1dWFq6srNTb/0/ty23/z5k3ExsbCysqKALGNjY1IT0+Hs7MzJk2ahNraWuzevRu7du3Cjx8/0NzcjE2bNkFRUVGIkXvv3j3CqAP+xejhFqX6K2OfOzU1lejETpo0iQAlBw4cgIyMDKysrODl5QUPDw/Y2NgIFUKrra1FWloa9PT0kJiYSKX/s+na48aN+20fFhUVISgoCJ6enhRTvba2FmZmZmTdWL9+PZYvXw5JSUnIyckhPT0d1dXVRF9YWVkZioqKsLa2Rq9evYTa2drainnz5sHFxQX379+n5ktGRgaCgoIotndKSgp0dHTg6ekJd3d3WFlZEXbjzZs3oaGhQekNssYGIqSkpDB+/HjyrgEgLCwMqqqqWLRoEfz9/aGjo0Pa8fDhQ0RERJD+v3fvHry9vUl7AQEblA3AiYuL49mzZ0QDkVuw6/nz5/Dy8oKnpyf09PSgpqYmlAXw7NkzhIaGIjs7G48fP8bMmTOhpaWFXbt2YePGjejWrRsJxnR0mK+oqICuri7ZU7hz6/Hjx0hLS6NSt1mAKCQkBNnZ2SgoKKAASh6Ph7Vr1+LkyZPUtb58+UIx7Z8/f45+/frBxsaGSokHBGDa7w7K3Gc4ePAgFBQUwDAMBgwYgPHjx1NpuKyxe0F0dDQBO9ra2hAdHQ0dHR14e3uTa0+bNg0LFizAmzdviOarvLw8AWUAwR4UERFBjYnU1FSYm5tDUlISkyZNooCWvn37QllZmZImYI0b1Pi752WtsLAQOjo6VOX1Z8+ewdPTE25ubtTezePxqOAONzgKCIDp3wGxHWW2tF+XGhsb0bt3bzAMA21tbQwdOpRi47Fsa29vbxgYGJDxfebMGQwbNgwKCgpwdXWlNKKzs7PBMAx0dXVJm7ga+ePGjYOioiK0tbVhbm6OlpYW7N69G5KSkrh69SoZAydOnICoqCimTZsmBMSyxvZNcnIylJWVsXXrVgIA/fr1C6tWrYKNjQ3GjRuHyspK2NnZQU5OjmLWNzY2wsXFBYmJicjPz8eAAQPg6OgIPz8/dO3aFStXrkRzczMePnwoBLyXlJRg7NixEBERITqqgACQNDIyogrNtTcW0OQyYquqqlBUVITy8nLyDtmU97y8POTn50NeXp5onLP248cPFBYW4s2bNwSQfPDgATw8PMhYPnnyJMzMzDBjxgwCsNXU1MDX15cE91nbvXs3GIaBvr4+YUSyfZ+Xl0eKQLEB4efPn6OyshItLS04cOAA5OXlKV8V+Bf4HBISgpiYGMjLy2Pu3Lno0qULNDQ0UFBQgPz8fMycORMMw2D37t3kt2zgivv+Wf9q+/bt1L42f/58yMrKknHw5csXLFq0CJaWlpgxYwaSk5Ohp6cHPz8/2NnZQUNDg2QcHDlyBE5OThg5ciTlyyYnJ0NJSQnKyspwdHSkiq2mpqZCTEwMw4cPh4ODA8zNzcHj8XD58uV/S8aKHVvsWJ8+fTr69etHZam1BylXr16NkJCQ3663+/fvh7e3N2JiYoTIA9wAG5/PR0NDA9auXYurV69i+PDhEBcXF8rk2b9/P/T19aGlpUXOHtyCca9evYKTkxNMTU3JvsO2vaqqiipeOGvWLFK8z97enqzz7HeePXuGxMREEjDptE77v9E6QdhO67RO+x9pBQUFGDNmDNHjam5uho+PD9zc3JCbmyukR8f+e+XKlVBXVyepmEuWLAHDMLCxsSEpsGVlZUhMTMSgQYNIipG0tDTOnz+PhIQE6gB19epVREREICoqigIPuWltVVVV6NOnDxiG6bCCKWtch2vnzp1gGAZdu3ZFTk4OZs2aBQ8PDwCgQBb2d6wtXLgQDMMQHdV/Kl3Q2tqKKVOmUCwErnGrk7u7u5N0z4SEBCgrK0NdXR3y8vIYO3YsYZaxGrEjR47E+/fvKac0KSkJmpqa2L59O0ktXLduHWRkZJCSkoLz58+jsLAQwcHBcHNzI8+4b98+JCQkYM6cORTAlpubi+DgYHh4eAgVSGP7aN++fejbty8AQQSfq2FZU1ODc+fOEVCAtc2bN6Nr165/C55z7zVz5kxISkpSGmzl5eWIjY2Ft7c31q9fTw5A3IJv7DNWV1fj3Llz8PX1haWlJQICAnD37l3Mnj0bUVFRQmxY9pAydOhQkj58+vRpSEtLk/TPhoYGVFdXg8/n48yZM2hubsaPHz+gqqqKkJAQqiAdAPI3X19fofTi/3+kg3EPuOnp6QgICEB8fPz/kQZYSUmJUOrnjRs3hIBYlhXu6uoKR0dHKCkpUSmAVVVV2LJlC5SUlBAfH4/KykqEhIRgyJAhuHLlCsLCwpCcnAwxMTF07dqVHAD/yfNeunQJPXv2RH5+PlatWoXAwEAEBwcT0Of9+/dITU3FwoULsXXrVjIPCwsL8e7dO8Leq6urw7x58+Ds7Izk5GQKqOcy69va2vD8+XNcu3YNX758IUGAp0+fIjAwEGZmZpg6dSo2bdqEqKgowkROS0sjzMMzZ85g0qRJkJWVRXp6OpnvlZWVuHPnDsV6vnz5Mq5du0aCKD9+/ICZmRl8fX1x5coV1NfXo76+Hn379qU0t3ft2gV1dXUyLleuXAkxMTEqQHTr1i0wDEOlQZ88eRK6uro4d+4cNm/eDC8vL4SFhZFCOoDgAB8aGoqoqCjST7t370ZYWBj8/f0pcO3UqVPw8/ODmpoajI2NYWdnR7Tp4uLiICcnB2lpaaryO9vXP3/+xPbt24kut52dHbZs2UKtFbt27YKsrCzevHlD+ovVCWQYBoaGhgTk5xp7jaysLAJGsJ83NjaiV69eiI2NJd/jsjwXLlwIGRkZiIqKUut9VVUV/P39KQmChQsXwsnJCSoqKvDz88OOHTvQ2tqK+/fvY8CAAbCxsSEgBneOtpe4ad9uQCARoqqqilmzZpE1++bNm7hw4QKVLfHjxw/07NmTrKdsoc3r16+T6z158gQaGhpkvLC6u1y9zNraWoSHhyMwMJC8o8OHD0NXVxfHjh3Dtm3b0LNnT/Tt25fS+YyJiQHDMIRhCAgkI7Zu3Sr0fB0Zt18+fPgAbW1tIj/AlR2SlpaGr68v9u3bR/0tKyuLFHyaNm0aHj9+TBh8Fy9ehK6uLoYNG9ZhAZzfAbCsNTQ0YPjw4ejWrRt5ZraAIdu3rOwFF4jl8wWFE7lyNjweD48fP8awYcMgKipK3iH3WocPH0bXrl0REhJCgH0ejwdXV1cYGBjg+vXrFBArJiaG6dOnC/k8rO3duxfq6up4/PixEPvw169f2LRpE/T09KClpQUHBwdynfz8fHz//h08Ho+smyIiIpgxYwZh8I4ePZrKrrp16xauXLlCjY03b95gzJgx6Nq1K6ZNm4ZFixahd+/eMDU1Jc+xY8cOpKSkYPDgwcjPzyf+DgvEcv0Nbvu/fv2KpqYm4kvW1dUhNzcXCgoKFBDbfm/MzMxEXFwc+vfvT+3VO3fuhLW1NSwtLUmQlZupde/ePdI/R48eBcMwSE5OJu1l7eTJk+jVqxfa2towe/ZseHh44MiRI2htbUV9fT0OHDgADQ0NoUJ2XBBu/PjxkJOTw8CBA6mMgoqKCsydO5cCYrn71/Pnz7FlyxaIi4tDXFycgM7sfPj8+TPU1NSoIMvXr1+RkpICAwMDKCsrk3ly9uxZMAxDBT4OHToEbW1tLF68mDClfXx88Pz5cxQVFSEtLQ2WlpaYMmUK+c3cuXMxYMAAjBkzBi0tLTh69CjMzc3xT4wbMGlrayMB8aioKKIlzs3y4PF4uHbtGqqrq6nCZAcPHsSsWbOQkZGBy5cvk+vv2rULPj4+HQKxbN+2t/fv32PQoEEUEMtmvezfvx8RERHQ1taGrKwskb1g21FSUgJnZ2cKiOXeY8GCBejduzdh/Z88eZIUnv316xcAgS8eHh4Of3//TuZrp/1fbZ0gbKd1Wqf9jzDuRp6dnQ0bGxsYGBhQB4/q6mr4+vrC1dUVp0+fppgkgMCRiIiIIAeS8+fPQ0pKimiI2dvbE0bst2/fKKd+7NixEBUVhYKCAlXtGBCkOsvLy5NDR0cpgV++fMHYsWPRo0cPwm76XUp4cXExtm7dSrFSt2zZQmmm8vl8bNq0ieqXKVOmQFZWFiYmJqQy/T+VLmjf7t+9Az6fj6qqKvj5+UFbW5sAJU+ePMGZM2cgKyuLqKgo8psNGzbA2NiYpJWy7VZVVUVBQYHQ4Yp9TklJSVhaWlLMHFZKIDY2FoMGDYKWlhalt5ubm4vQ0FAYGxt3GEFfsWIFPDw8cOnSJaqKOyAAYcaNG4fc3FwoKytjwIABJLVcS0uLAO/t0yDZz1iLj48HwzBQUFAgDirb/vLycgwfPhzm5ubQ1dWFra0tef6nT5/i+PHjePz4MZHH+Pr1Kx48eABvb294e3vD0dGRAOwdvavY2FhkZ2fjwoULQgy3HTt24PDhw+R3NTU1pIq3lZUVIiIihCrEh4SEQF5eXkj/8Z/av+tAc9kg6enp8PDwwPDhw/+WccZa+z5pbm5GdnY2FBUVMXDgQPL5jRs3iHQIewBrampCdHQ0REREOkzxq6ysxK5duyAjIwMDAwPY2tqipaUFN2/ehJWVFbp27QopKSly0Pnds7cHp+bOnUuxOS9evIiwsDAEBgZSh/32IL+JiQm0tLSgoaFB2NsNDQ2YO3cuXF1dkZqaKsQg4/P5mDVrFkxMTCArKwt3d3fMmjWLrHnPnz9HcHAwRERE4O/vj2XLloHH46G6uhqOjo6kSBVrs2fPhri4OJYsWdKhTEZSUhJkZWWhp6cHCQkJktL/7ds3ODo6wsbGBnp6erC2tqZkJ/h8PhITE4mW9YkTJyAtLU1Ar7q6OsK+efr0KVm/8vPzMWXKFIr5eOvWLYSEhCAkJIQCYn/9+kWBRyxYo6CgIKQLWFJSgosXL2Ljxo04d+4cud/ixYvBMAzk5ORIAUjue2b/29DQgBUrViAuLg4MwyA2NhY3b94k15k0aRL69+9PwPt3795h6dKlMDAwgLOz81/Oo58/f2L+/PlgGAb9+vUjgR4LCwuy7uzatQtubm6ERfzx40f06dOHpJnzeDx8/vwZISEhcHZ2Ju8hLS2NFMWqqKiAg4MDTE1NyRi/c+cOYmNjoaamRlJ4AfxtETvuWN69ezc0NTWRmJiIMWPGwMzMDEZGRnBzc4O9vT0JEowYMQLy8vJYunQp3N3d4eTkRPovIyMD8+fPJ3qEgGDup6amEk3nIUOGQF9fH8bGxlSad0pKCqW5/ODBAzg4OCAqKooAIuvWrcOkSZMoMMjJyYkKxv6TZ3306BEKCgqgr69P9kOulImnpyfU1NSoIpwHDx5Ely5dICMjg5EjR8LBwQGurq7YuHEj6ZtLly7BwMAAERERBMwHBHsvW0Dqr4wtpqShoYEFCxbAyMiI7EtcmRpHR0dYWlqSvfV3xRlLSkoQGRkJGRkZkk7NBWJ37twJLS0tzJgxgwpeeHl5QUdHB9euXSNj8NSpU0Qq5d69e0KgUWpqKmJiYqh+5LaLx+OhrKwM58+fJ995+vQpGIbB9OnT0dLSQqQ72o9bT09PItsxe/Zs9OzZk4whbtG60tJSTJo0CRISEvDy8kJubi5p//Tp06GkpIT+/fvD09MTioqKSE5OJkGRCxcuQF5enpIZaG1txalTp2Bubg57e3tERkaSgGB9fT1Onz4NBQUFak/j2rx589C1a1fo6+tTDHZAoHe9c+dOTJgwAStWrCDtnDVrFhwdHbFlyxYq4M1qxLYHYgGBlrSysjLy8vIIgMa28cCBA9DU1KT2Uu57+fz5M/GH2VoHrLFAbLdu3RAfH0+ec+rUqTA2Noa0tDQOHDgAFxcXBAYGUvUVSktLYWhoKOTLfPv2DcnJyUhOTgYgYL3KyMgQH4mVAWprayNyNdXV1SgsLERUVBS5R3l5OTIyMmBhYYGpU6di8ODBiImJofzYPXv2wMfHB4CwdBHXuODqzp074eTkBIZhUFdXh507d0JcXJwKRgGCeTho0CAqeykpKQnq6uro27cvAgMD4eDgQGkv7969G/7+/vD396e0XjtqD2tlZWUYNGgQevTogX79+mHmzJlk7i1btgw9evSAg4NDh2tLSUkJXF1dIScnR/oVEMwhtlgimx3H5/ORmZkJDw8PqKiowMvLC9bW1lTGTycQ22n/t1onCNtpndZp/6Ns3759uHr1KgYOHAgZGRksXLiQ2qRramoQEBAAAwMDqsjHqVOn0NTUhLy8PJSVleHhw4fQ1tYmTtiCBQtIxWquQ9ke/GAYBitXrhRKj7K1tcXcuXOptpSVleHFixcEVKuvr0f//v0hLS1NIsztgaPs7GxoamoS9grrJOfl5ZHDEZ/PR1hYGAwNDcn9EhMTIScnhw8fPmDevHn/WLrg6dOn+Pjx42+fmWtsehwgYBqxqZBce/78OcTFxSkNLraYDGuDBw8WAva4jI3y8nK8fPkST58+pdIx9fT0SHrd3r17ISIiAnFxcQocOnr0KKZNm0bul5qailGjRgEQRPhZIJNbsKChoQEREREYPXo0WltbcenSJUhLS6NLly7Izs6Gm5sbxS7gsoK5xqaj+/n5oXv37pSOJOtQVldXIz8/nzBH2DYrKipCU1MTRkZGGDNmjJBW74kTJzBr1ixISUlR0gzcYkqjR4+GhoYGZGVlqaq4379/h7+/P9EAy8jIwKBBgwjDrrCwEGZmZoiIiCBzprW1FePHj8fVq1f/IyeY+5vMzExK8uGvjHtomTVrFnr16vWPmKW/s+bmZpw4cQKysrLUofXmzZsIDg7G0KFDyXtISEiApaUl/vzzzw5TAAHBnD537hyVOj1x4kR069YNvr6+lN7zXzEB161bBzc3N3Tr1k2ICXXp0iWEh4ejV69eVMCHz+djxYoVUFRURF5eHi5cuIA1a9ZQhZdqamowd+5cGBgYUGAkIGDvqamp4cqVK+Dz+Rg8eDDU1NQwfvx4wlopKiqCra0tFi5cSFg6VVVVsLW1JWAvV2c1IiICGhoayMjIoA7qRUVFMDMzQ0FBAZ48eYK0tDR07doVa9euBSCYO2fPnsWKFSuwceNGoVT06dOnY926dbh06RKkpKQIANvW1oa9e/di8+bNVLZBYWEhjI2NISkpSQJQrLFAbHh4OKVz3P4dHTlyBCYmJhgyZIiQJh57b9ZaW1tRWVmJwsJCDB06FPLy8iQ1v30Qjv1dbW0trl+/DmNjY9jb22PChAlobGzEo0ePEBsbS6U0Nzc34927dx0CS+2ttbUVFy9exODBgzF8+HDMmjWL9Oe5c+cwf/58dOvWDT4+PoS1mp+fj8DAQIiLi8PCwoKqPs1KbLi5uZF5e/XqVUhKSlKHe0AgRTNnzhzy3pKSkqCrq0sVVuvIuMGIvXv3olu3bujRowfFfGYYhgCdb968wahRo+Dm5oYBAwaQdYItLsQwTIdatAcOHEBcXBz69OkDKysrApb8+eefkJCQAMMwBBBljQVi+/Xrh/T0dJiYmGDo0KH4+PEjeDweamtroaWlRUDtv3u+trY2bNy4EWpqaiTA2rVrVyrlurGxEUOHDkV2djZ512x2ioqKCgkMnDlzhrCq16xZg4aGBgCCzAc2fRkQ7Os6OjodFsLkGttGNi1fREQEurq68PDwIPOcvSabpq6qqkrtT/v378eSJUswY8YMopf7/v179OvXD6qqqgSIZdsKCPwHHR0dpKamUhJCHQGxN27cwPTp0+Hr6yvUx2FhYQgPD6c+AwT+xJ07d0hqP2vsON23bx9ERESQlJRErVu1tbV48uQJevXqRXRuly5dChUVFdy9e5cUdGQYhvKxSkpKMHz4cPTq1Yt8dunSJWhqalJBnQ0bNsDKygoLFiwAj8dDS0sLAWLZApBsIa7ly5dj0aJF8PPzg7q6Ogk81dfXExbnsGHDOnyvGzZsgIKCAlJTUzsMkHFt3rx5UFRUxPXr14X22r1794JhGMydO5dKMX/37h1sbW2F1lO2/+vr63Ho0CEyv16/fk2CqYsXL8bPnz/x559/kr2TqzMKCIJk8fHx0NfXJ6Bcjx49wDAMTpw4gba2Npw6dQqurq5wdnYmkg0RERFwcXHpkOE5cOBATJgwATdu3KCyoNg2cetAzJ8/H+bm5vD09CS67KxVVFQgIyODyATJyMhQGU2rV69GaGjoX/Z5e7mQHj16IDIykuwhHz58wKBBg2BoaIjc3FzU1NTg7du3CA8Ph7OzM3m+LVu2QF9fn2T2sRq7enp6lCbxpk2bEB8f/2/5ch8+fMCQIUPQpUsX4nM2Njbi5cuXuHHjBvr27QsfH58O6wQUFxcTfxoQyAtYWFhQDGVuW4qLi7FmzRrMmzcPmzdvJnO/swhXp/3fbJ0gbKd1Wqf9v2pcZ2r9+vVgGAafPn1CeXk5hgwZAldXV2RlZVEbelVVFan4CggYPQYGBpRAfUZGBmJiYsjBYOfOnYiNjRVK5eVaW1sbJk2aBHFxcRw/fpyAAFVVVTAxMaGcnjlz5sDJyQnS0tKIiIggKbNsAS8ZGRkUFBQAoB2yxYsXo0uXLpRTB4DogbEsJi6jZ/v27WAYhjhKfyVdwLXk5GSSojV06FAquv67ggiAIKJtamoqlErH3mvJkiVwcHCg9AgBENaJubk5YZhw31tTUxOePn1KHdYAgeM3c+ZMIrFw+vRpyMrKYsWKFUhKSoKIiAgB07nXmz59OmGqff36FfX19Vi9ejWsra0xYsQIlJSUIC8vj1Q95vF45BlY8MfHxwcGBgZQV1eHm5sbLC0tYWpqCisrKyQkJJB7bdq0CXJycsjOzkZxcTEGDx4MHR0dCnzkOpRsf378+BGRkZHYtWsXvn//jjVr1pAKwx2BjyygDwiY3A4ODgQMaGxshIeHB3R1dfHjxw/8+vUL3759Q0hICFxdXcHj8ZCcnAwNDQ1kZWVRrKnnz5/Dzs4O7u7uiImJIcVWuIDAf2IpKSnQ1NTEkiVLCOPyd8YdY/n5+bh3757QGPo7W716NSZNmkR91tzcjJycHEhISGDkyJHkcxbkb2trA4/HQ2RkJEnz5KYJ8ng8XL9+Xahad2trKxobG3HixAkcPnwYPj4+6N27NwXYs8ZlUC9cuBA9evSAiIgIVFRUICUlJcSqu3z5MlxdXakx1tLSgrCwMCHQ6MSJE1TRtJqaGiQkJFDvrLi4GB4eHiQNmh3fffr0gYmJCSZNmoTy8nK0tbWhpKREqLDZoEGDYGxsTBVSAwQsTnt7e6iqqhJ5kKVLlyI1NZWwjtjnz8jIAMMwv9VK5LZ3zZo1EBERQY8ePSiwqrKyEoGBgWT94I6ZM2fOwNbWFu7u7kLFD2/fvg1HR0chXV+2bazt2rUL9vb2GDt2LMWM436ntLSUSu3k8/kYMGAA5OXlqSJO8+bNozRTd+zYgTdv3qC8vBxz586Fubk5jI2Nce7cOURHR5NCY6y8SEf98lfW/oCdnJwMVVVVZGRkYPbs2VBTU4OrqysJtNTX1+PIkSOwtbXFlClTyH14PB6+f/8OGxsb1NfX49y5cxSzvr6+Hrt27SJsJtYePXqEfv36/W3hyQ8fPhDNbfZ5IyIiSODu1KlTkJGRIYAvF/TnriHsevrp0ydMnjwZYmJiZO61B8zZ+7DXLy8vx8OHD6Gjo4Pg4GBKagAQyB1paWlh5syZyMzMhLe3N+Li4sgzGxsbk+dsbm6m1gTuXM/MzISXlxe6d++O6dOnEyCKDfrGxcVh6tSp8PHxgY2NDRWM4PP5WLJkCdn3cnJyICcnh7Vr1yI6OhqamppYt24damtrqed9+/YtHjx4QAXofhcQYn83b948WFhYYMCAATh58iSMjY3h6upK9f2ZM2cwefJkam1hx9iECRPg6+sLU1NTLFmyBIBAf7d///6UTAQgYNLNnz8fcnJy6N69OxISEqi2ent7Q19fH3l5edTYZ5m/paWlxPfavXs3lJWVqaJmgGCMxcTEkKADAIoxCfyL6Zmamkr2mUOHDqFv376kCFdpaSkiIiJIMOzs2bOQlZUlWUfcWgPv37+n1s0zZ87AwMAAHz58ENK/lpOTI0A2n8/H6dOnISUlhaVLlyI3N5da44uLi+Hv7w9VVVUCxNbV1eHcuXNkHbpx4wauX79O+bhLliyBlpYWFi1aRIHm3LHw8eNHuLi4CIGpXF9l79696NKlCyW/8eHDB6ioqJC1hHvNpqYmVFRUoKWlBRcvXsTdu3ehqamJvXv3kkwhtt1//vknxowZA1lZWaEMs5qaGrI2MAwDZ2dnqp08Hg/5+fno1asXZGRkYG5ujsDAQKEML9bOnj0LW1tbiIiIICsri7pPeHg42a927doFZWVlrF69GqNHj4aEhIQQ2F1RUYF58+ZhyJAhOHHiBCQlJTF69GgAgmAnK//1d5IsbOBeQUEBJiYmlK7448ePMXnyZIiIiEBHRwcmJiYkUAYI1sWEhAQsX74cgCATTE5ODosWLcLw4cOhpqZGBc1+F1j+nfH5fPz5558kYLBr1y707t2bMOHfvn2LyMhI+Pj44NChQ+R3a9euJXMVELyH27dvQ1lZucPaDr/b3/5Tn7PTOu1/i3WCsJ3WaZ32P8Lu3bsnxKirqKhAbGws3N3dhYBY1p4/f47+/ftTlXoBAXNUV1cXzc3N4PF46Nu3L9LS0qjD1PXr13HhwgUqLRgAxo0bB1FRUQwbNgxpaWmIiIiAlZUVcVyXLFkCJSUlXL58Gd++fcOAAQMgKytLGBE/fvzAoEGD0KVLFxQVFRHnqKWlBdOnT0d0dDQiIyPx8+dPSkdLX18fPXv2pABYNp2P67z9TrqA6/zl5eVBR0cHly5dwvr16xEVFQU3Nzfk5eVRv2P7grWsrCzIyspiwYIFiIuLg5iYmFBK0vr162FnZyd06GFt8uTJMDY2Jqly7H0KCwsxYcIEoeJabJ+9efMG7969g6mpKWF15ufnQ1RUVKiYw7Rp06CsrIxjx45BX1+fOP01NTVYu3YtHBwcIC4uDjs7O1KJePPmzViyZAlJFbx06RIBm48fP45jx45h586d2L17N3bu3Ene9+zZsyEjIwMfHx8isVBaWoqRI0fCzMyM6p/26alxcXHo168fBTbu2rULXl5eFBDLSmuwvz9z5gxGjRoFOTk5uLm5ERDvyZMnMDIygra2NgwNDYnOaUtLC3JycqChoUEVXGhsbCRjp6ysDKmpqYiOjsaoUaP+j9PB1q1bByUlpd9W7+Za+4MJwzAUk/131h7EX7lyJaSlpZGamkp9r6WlBRMnTgTDMELFnLjai+Li4kLz/dOnTxg8eDBu3LhB3W/p0qWYOHEiYRrduHEDHh4eiIqKoq7BlYEoKipCVFQUKeD14MEDDBo0CFZWVtTcAwSMPO79qqurYWhoSKUys2NwzJgxCAsLQ319PXJycsAwDDIzM8ncbWlpwbFjx1BRUYFbt25BVVWVHER79+5Niq2wjPh79+7h4cOHZC58+vQJJiYmcHNzQ319Pblv//79UVBQgMGDB8PMzAyNjY0YN24cGIahdKgBwTteuXIlunfvjhUrVgi9y/Y2ZswYSEpK4sGDB3j//j3evn2LXr16wcHBgdy/sbGRGjsnT56Eo6MjBg8eTBVYAgRsnL+SiWBt586dcHBwwPjx44V0NlNTU2FqagoJCQmMGzeOAhxjY2MJg83HxweGhoYQERHB/v37kZqaCjk5OQI2tbS04NWrV4iOjoaRkRGRKkhNTaWCIzt37vxbUJM1Ltj4/PlzqKurU+B+WVkZTE1N4ejoSCRxAMF+wYJarL5vS0sLLCws0KdPH8jKylKH+Tdv3sDX15cA+oCARezl5QVfX1/U1dX99gC9bNkydOvWjTCNV69eDWlpafj4+GD9+vVESoVlqbW2tmLNmjVUUUlAAHhxU60rKiowZMgQSEpKEsCPq4PM2tevX6Gjo4Phw4ejoqICd+/ehba2NkaMGEHkY1h7+fIlxTjz8PBAXFwcSkpKEB4eToBb7vjjsipTU1MhJSUFUVFRODk5wdHRESkpKQSIzcnJQXR0NEJCQhAXF0cA5ra2NgJI/fnnn/j27Rvevn0LCwsLsu+9fPkSsrKyMDIyIrq+fD4fKSkpJGU7Pj6eSvf/XWD1xYsXsLGxQWRkJAlCPnnyhIA+z549w9u3b9GvXz9KGz0nJwe6urqE6ZqTkwMRERGqgGVJSQn8/PxIZfRly5ZBVlYWFy9eRH5+PpYtWwYpKSkkJiZSQKyZmRn69u2LrKwsCiA/fPgwGIbBuXPn0NbWhtLSUkRHR8PDw4MUjnzz5g0iIyMpRmRGRgYiIiIwbNgwXLt2jYx3LhDb0NCA+vp63Lp1C21tbaQw444dO1BRUYHbt29TEkhTp04FwzAICQmh+nXevHm4f/8+cnJyIC8vT1LA2eByQ0MDVFRUKECxsrIS9vb2MDIyAsMwQoFEFojV1NQU0tefMWMGNDQ0IC0tDW9vb6xcuZL8LT09nWicfvjwQWj9e/XqFWRkZISYqIAA9GZ9ADb7Y9SoUVi2bBl+/vwJaWlpkm3BDVrevXsXmZmZhGQAABMnToSioiIkJCSE9Offvn2LcePGQV5eHufPn6fa2NDQgFWrVmH+/PlwdHREXFxchz7E27dv8enTJ6HiaVxj2aXW1tbYuXMnmpqa8OLFC4SFhZE95ezZs9i9ezdhkNfU1BDdYW4At62tjWjsA4JsL0lJSSQnJ2Pr1q0IDQ3F0aNHcezYMdy8eRNXr17F1q1bUVlZKVRsLzU1FZGRkRATExPqGx6Ph4cPH+L48eNUUIJ9vvLycpSWlqK0tBQ9e/Yk68O5c+fQo0cPSEpK4sCBA5Qk0T8FY9v/ff369XBxccHQoUOJX/Dnn3+id+/e8PT0RFJSEiIiIqCgoCC0/l+5cgVqampkreBmEp45c4YqwtppndZpAusEYTut0zrt/3EbOHAgifgDgogwW6SKZXtxnZCBAwfCy8sLa9asoRy07du3w8rKCtbW1uRgyzoHt2/fhr29PTQ1NWFrawszMzOKmTNr1ixoaWnBysoK3bt3x9SpUymgc9q0aWAYBqGhodi1axfRPPv+/TsCAwOJg33p0iVISkoS3bmWlhbU1NQQLT8ej0ddFwApvsAFEWpqaqCpqUlp/R09ehRWVlbk3/9UuiA3NxdTpkwhDhsgSM/u378/XF1dKTCIywpevnw5pVPLgoj6+vo4evQoGhsb8fPnTwQGBiIsLIy8i2fPnqGgoIC07+bNm/Dw8EDfvn3x9u1bAILDa0REBLy8vKj03fZ2+vRp2NrakgPrgwcPSH+z7zY+Ph5ycnJ48uQJ6uvroaenRwG77PcePXqE79+/g8/nkwrLe/fuJYcmtsqtiooKYTm0N/Z3sbGxCA8Ph4aGBtLT0wEAf/zxB0aPHg1LS8sOU7bS0tKgr68PHR0dijkACIBYPz8/BAYGEgYma0lJSdDR0UFaWhoSExOhp6cHb29vArjw+Xzs2LED27Ztw6lTp8jzrlixAv7+/uSdZGRkwMTEBNLS0oRZ2P7w8p+mg7W0tGDUqFEEMHz9+jUOHToENzc3DBs2jEpLaw/AysnJUQWY/omxDDW2iJaCggLFxASAVatWISoqCpGRkWhra8O3b9+oufflyxf0798fRkZGOHv2LP4/7P11XFTd2z2Oe6RBQLq7u7s7RUJBUBEVBQMbBFQU7FZULOzb7sQusLtuGwQ7MFCJgZn1/WN+Z79nM5jv53l+f3xYr9f9umVmTu2zzz57r2td6/r69SsqKyuFUgABvsJXQ0MDJSUllP/w2bNn4ePjg4iICERERJB0fZZYYRiGKpwHABcvXkRKSgpsbGyIB5zgAqiyspLyGDQzMyOKJ0E7EjYtt76+npBdgimXrKpt8ODBVDX67OxsuLq6YsyYMeByuRgzZgy0tbXRqVMnhIWFkcJsFy9ehLW1NTQ0NBAcHAwbGxsYGRkB4C/QHB0d0dLSgg8fPiA/Px8iIiJEoSa4CCwoKIC3t/cvCXlW9S8vLw91dXU4OztTHtFz5sxBdHQ0IiIiMHDgQEKs7Nq1Cy4uLkhJSRGq8Ny6bX/0+erVq6GtrU0VqdqyZQv09fWxfft2rF69GqampkLK5yFDhsDb2xtxcXGoqanB5MmTISUlBXl5eWL/0TrTYunSpejRowcYhoGfn58QcStYVOtHaN2WDx8+hLa2NlHism1TVVUFWVlZhIeHC/kNLliwABMmTCBBhX/++Qfq6uoUmV5fXy9U3Argjy1WVlZQUVEhgaO22vny5cvo2rUrdHR0UFBQACUlJWzcuBETJkyAt7e3kFf327dvYW5uLlSRnPU17t27NxnbP336hJSUFHTq1IkQ1231sWvXrsHJyQn9+vXDx48fUVFRQYhYlrQUDECy17l48WL4+voiODgYDMPA1tYWtra2cHBwgJOTE8zMzEjGy5o1a6CsrAwZGRns2LED+/btQ8eOHWFpaYmsrCzKogjg99mQkBDU1tZixIgRkJeXx7t37yiiwsrKioxXJ06cQI8ePTB58mTSzvv27YOxsTF27tyJ1atXQ1NTEwkJCSRVmb0uQSKmpKQEhoaG6NixI2WfA/ADRq6urpCWloauri7l0wjwLQXYMYf12GTv3devXwmpzdpqcDgcBAUFUd69AL//i4mJYeTIkZTCvLy8HCIiIhg8eDD1/g4PD4e6ujp53129ehUDBw6EjIwMNDQ0YGpqSikG58+fD0VFRYwbNw6mpqbw8PBAcXExIZw3bNgAERERhIeHE1Jx2LBhGDRoEID/9ONx48YhJSWF3LOZM2ciISEBXbt2Jb9hA2As2eTl5QV7e3vqWamuroaJiQklDDh37hzU1NTIe19PT48ERFg8ePAATk5OMDExIfPNS5cuwcHBAZcuXcK5c+cwdOhQODo6YtKkSWS7adOmQVRUlPI+3rVrF549e4bnz5/DzMwMK1eupMZogO9XW1RURN4TFy9ehK6uLmn3/Px8aGpqUsIIDoeDkJAQmJqaYvTo0eQerF+/HjIyMtDW1saaNWso+yuAr27OzMxEhw4dSH8tLS3F8ePHSWHdJUuWwMHBgbLA4vF4uHz5MpU91da4IxgETU5Ohr6+PuTl5WFvbw8/Pz9wOBw8ffoUIiIiYBiGUv1+/foV69evh6amJvr370/t//r162R+tmvXLigoKIBhGHh4eMDZ2Rl6enqwtraGmZkZfHx8SD8oLS2FiIgImeecPHkSgYGBMDc3J/7igkr11sS0oMcywFdwOzo6knY9ceIEEhISsHr1auqZ/fr1q5C/74/ew+y5/vPPP+Scli5dCm9vb6SkpJC5+7NnzzB48GCEhIQgOjr6h8F7tqilYDYX+z5pPSa0ox3taCdh29GOdvwf4+3bt0hPT6f8/hobG7Fy5UrIy8tj6NCh5HN2clhbW4vQ0FBkZGRQE4rHjx/D2dkZoqKiQgsMDoeDiooKTJkyBVOnTiXHa2lpwfTp06GhoUEWcjNmzCAFPgQJl9TUVISEhJC/2eqwLi4uuH37NkkxY5UTjY2NCA0NRVJSElE+btu2DbKyshg5ciSl/OvVqxcCAgKoifj169epSHhlZSUkJSWFqjS3ti4wMzMjE6N79+7Bw8MDnTt3RlFREbVdeXk5EhMT4enpSRWxAUAqfOvr61OKgMuXLxMCwcDAAGlpafDy8iILnNGjR0NXVxeSkpIICgoiBO+OHTsQFBQEOTk5ODo6wsrKilrkTZ8+HV26dEFoaCiOHTtGJm5HjhyBhIQENm7ciA8fPsDCwgKqqqokpZz13WUVbI2NjTA2NqbSFVtPOnfu3Altbe02CRvWI1ZFRQUBAQHUd3v37oWuri451pkzZ8AwDKVwuXv3LuLi4ij/OBYcDgdz5syBnp4e+vfvL+QxW1JSgsjISCrt98aNG9DR0aEWcMeOHUNERAS8vLxI+7a+xpaWFkICsl5jKSkpKCkpweLFi6kUwR+108/Q1m+7du0KExMTbN68Gb6+vggNDcWgQYNgbW2NLl26CPkq/6qStyAEJ/j79u2DmJgYKcbx+fNnLF68mBRBAfgq0u7du5NnpbCwEPb29lBVVUVgYCBJW7179y4GDhxIvBFbpwByuVycOnUK2traVKprayVQQEAAOnXqhMDAQLLtoUOHoKWlBVFRUSGS+dKlS+jduzdUVVUp0qSwsBA9evQgpPXp06cRFhaGmJgYQkw0NDQgODgYdnZ2JHjV0NCAadOmgWEYIW/YxMREarHUrVs3rF+/HjweDxUVFbCwsMD58+dx4MAB9O3bFw4ODkQ129jYiKKiIuTk5CApKYl4vKalpSE6OppUbP748SOGDRsGUVFRophs7ZXa+rMf4fjx49i/fz9RqAF8Ik5JSQmTJk3C4MGDYWpqClNTUxJA2b59O9zd3REeHv7LQlGCEOxXBw4cIOPt6dOnkZOTQylCr127BmdnZ3Tp0oUiYgXJs6VLl4JhGEhLS2PdunXUcQSJmaqqKuzcuRPPnz9vk7j9WWqmYBvOnz8fU6dOxZs3b6CmpkYVRGxubkZzczPc3Nygrq6OsLAw0l94PB7Gjx8PdXV1zJw5E7W1tfjy5Qvy8/PRuXNnREdHo1evXvDz84O1tXWbKb8rV66EmZkZEhISyJjVVvGmW7duwdbWFgzDUMpOQ0NDWFtb48aNG+BwOHj+/Dn8/PzQoUMHJCYm4uXLl9iwYQP09PSwceNGbNy4Eerq6ggJCSFZJp8+fULv3r3BMIyQslUQ169fh729PUXE6uvro2vXrpQSubGxkUrJX7RoEby8vGBlZYUpU6Zg79692LJlC9auXYuSkhIyJxkxYgRERUWxY8cO7N69GwoKCli4cCGys7OhoKCAUaNGUeP948ePISEhAVNTU8jLy5O0XUHfcDMzM2zdupVY2Aj6qre0tODs2bNU0ODq1aswNTVFfHw8FdBl9/nt2zfk5+eDYRiIi4tTymZB7N+/nxQrYtsE4JOQffv2xblz5yj1MsAnNgsKCkg2DI/HQ2NjI/z9/UmWgqBVUv/+/aGkpITMzExqjrV161bo6Ohg8ODBlCo9KioKSkpKhBD89u0b7ty5g3/++Yc61+bmZuTn55PxtrGxEb1794aHhwcWLlxIzmH+/PlQU1ODgYEBIiMjIS0tTfUfHo+H2NhY4ktbX1+P2NhYKq1906ZNWLJkCUV2XrlyBba2tjA1NcWOHTuwfft2REVFUWp+9p68evUKXC4XFRUVsLOzg729PUVYAfxgJts+27ZtQ0pKCiH+AX7GQk5ODhwcHCgids2aNaRN8vLyoKWlheLiYgD8eayqqioqKirIM1pfX48uXbogLS0NPB4Pq1evxsCBA5GXl0f2yWYuycrKYtCgQRg2bBj8/f1hbW2N8vJy4i/97t07fPnyBe/fv8fgwYNhZGSEkpISfPr0ibq2N2/eYOrUqWhubkZOTg7U1NSwcOFCMlf+9u0bli5dCkdHRyQmJuLFixcICQlBfHz8b71H2N/U1taisrISu3btwo0bN8gYxdaMMDQ0FMqW+fbtGzZs2IAOHToQuw3W9mvt2rVoamoCh8PBvn37oKmpSWyNAH6g5fv37+T479+/J5kPGRkZ5HfHjh1D165d4eTkREj81oVgZ8+ejeTkZDg4OGDKlCmkIOKuXbugrq6O7du3E3uF4cOHU5l906ZNg7+/P4yMjBAfH48zZ8780HqNnc80NDRATU0Nfn5+VOCGJWLZAOH379/x9etX8pt9+/Zh0aJF2LNnD5lX3r17F6amprCwsEBxcTEWL16MoKAgWFlZtXu/tqMdbaCdhG1HO9rxfwYfHx+KGCwpKSFEQ2NjI5YuXQoRERHKL4t9eX/58oVMOA4ePEi2q6mpgZOTE7y9vYUsCQD+Ivndu3dkX2zKEkuksSllY8aMgaSkJPr06UPSIAUnSOzk4/Pnz3Bzc0NsbCwUFRWphcnjx4+ho6MDQ0NDFBQU4MuXL6iursamTZtgb28PFxcXBAUF4eLFi1iyZAm6dOlCFmOCx2lpaSGTJ7a6+o+sC0xMTISUsrt27YKXlxcsLS2FUnYrKioQFBSEAQMGkM/S09PRoUMHZGVlYdq0adDR0aEIyevXr6NPnz4wMjKifHF37NgBCwsLlJWVoaKiAj4+PvDw8CCE6KtXr7BmzRpMmzYNpaWlZJEwe/ZsyMvLo6CgAK6urjAxMcGcOXNQW1uL79+/IzMzE+Li4jA0NCQp0ADIoklQPdDQ0AATExOy4AAAd3d3qp+xk1PBRWHrSf2oUaPg6+tLTYjXrl1L0iw3btxIFXuoq6sjk8/Hjx+Ta3vz5g1qa2sJ+cHhcDB9+nS4u7tjyJAhQuqX1sTsv//+CyUlJSEVG+vx6eHhQaUWPn36FF++fCFKkbVr1yIyMhKrVq0ii7mamhq4u7sLkbC/i9b+i+yxampqEBgYSNIh2fTETZs2wc/Pj7rWhQsXQklJ6Y8J2DVr1mDRokVgGAampqYUEbtixQrIyMhAV1cXpqamxDKkoKAAGhoa+Oeff1BdXU2I1p07d1JE6rZt29pMAfznn3/g4OBAlOaAsHXH/v378fbtW3C5XFJIBOArZdPS0iAjIyNkP1BeXo5JkyZRReWUlZWxe/duyh949+7dJIDh6+sLW1tbogz09PQkSkZBIpbtl1wuF9OmTYOzszMCAwPh7u4OCwsLtLS0YMeOHUhLSyOqaIC/6B88eDDs7e2xePFi8nllZSUYhiFktaSkpJCnX21tLbKysiAmJob9+/cL3cdfLZx/pFj9999/iVqZxYsXL8iYxmLTpk1CyqXfOXZr4vDRo0fo1KkTGIahiA2AT8S6uLggNjYW+/bto8ZpHo+Hly9f4urVqygsLKQKjP2MhP4Zcfuz61i+fDmkpaWJ6n758uUQFRWlivRxOBz0798fc+bMIbYyRUVFRO08adIkaGtrY/r06fj69Su+f/+OsrIydO3aFQMHDkRhYSGljLt+/TqVdrx06VJ4enoiNTWV9MPW78hly5ahU6dOcHZ2hqamJiHXrl69Cm1tbdjZ2UFbWxvu7u5wcXHBpUuX0KlTJ6SlpWHWrFmUNUFlZSUMDAwoIra2thaTJk365cKeJWL79++PT58+4eTJk4iLiyPnO336dAQGBiI2NpYi34uLixEQEIC0tDS8fv2augfstrW1tTh48CBevnwJOzs7UtTuxYsX0NDQgI6ODkkbZ89zwIABYBgGvr6+ePPmDbXfz58/IyQkBHp6etDU1ISDgwN5rxcXF6N///7w8PAQUv9fvXoVZmZm6NatG6ZOnUoCR2PGjEFgYCDk5OQwa9YsGBsbo0uXLlQgsnWxvNb/vn79OkRFRYUCj/X19QgLC0NmZqZQ/x47diwUFBQomx32cwcHByQkJFB+wQDfk1RHRwfDhw+nCuZFRUVBWVkZZWVl5N0teLx9+/Zh37596Nu3L3kvAPy5IkvEFhcXk/nD8+fPSXBAsEgTe82HDh2CtLQ0XF1dYWdnB2tra3L+Dx8+hJaWFhiGoeZAXC4Xjx49Qnx8PPT19WFtbY3IyEgS9D9y5AiGDh2Krl27YsGCBYTUOn/+PJydneHg4CA0JwD4GWBxcXFQVlZGfHw89d3Lly+Rk5PTpgf2pEmToKysjMuXLxMSlPW0VlVVxcCBAzF8+HD4+vqSrKvnz58jJiYGsrKyQrUKXr58idWrVxMbnqFDh1JFlVhlr6D9yYABA2BkZIQVK1YQkjk9PZ0oNOfOnQsVFRXKhoLdJ4fDwYYNG2BhYQFNTU24u7v/kEj8EwiSlYcPH4aCggKSk5Op39TV1aGsrAwtLS0oLCyEsrIyjh8/Tql6ORwOdu/eDWlpaYpgZcH2z7dv32LNmjXo1KkTZT1x5MgRxMbGwsXFRciGJjc3F8rKyli5ciVmzZoFW1tbeHp64suXL3j06BFSUlKgoKAAfX19KkOOx+NhwoQJUFNTw6pVq3Dv3j2oqKjA19eXyjhk20HQrmD58uXo0KED9e4CQPlkP3nyhHru2LoDHh4esLCwQNeuXcna69OnT4iPj4ezszNcXV3Rs2fPH3r4tqMd/6+jnYRtRzva8X+CrKwsagH99etXWFhYUN6hrG9nx44dSco3QL+8L168CDMzM/Tv35+ky1RWVsLe3h5BQUGUV+Pu3bthbGyMjIwMMgH8/Pkztm3bhi9fvuDSpUvQ09MjBF5hYSEYhkHXrl2pQgePHz9GXV0dUX2wk3U2ms7lcvH582dERkbC398fubm5cHBwQEFBAYnyv3nzBqdPn0ZERATc3d3h5uYGhmEwZMgQqp3+xLrA0tKSTHC+f/9OqYv37duHwMBAREdHU4toAJQ6oKGhAX369CETypaWFly4cAF6enpUteIjR46gX79+sLS0xMGDB7F//37k5ORg1qxZ5DcfPnxAZGQk3N3dKfsAQdy5cwcDBw6klGXDhg2DtbU1Zs+eTXzbKioqsGvXLrKPI0eOgGEY4uUlWNwmKiqKLHjDw8NhYmKCpqYm8v2wYcPg7e1NthOckB84cABr165Fx44dkZ+fj+rqamqRHh4ejvPnz1P+aACf7Bw9ejQpLgHwCX0HBwcYGxsLeXtOmzYN7u7uGDZsmJD6hQVLCJmbm2PRokXUhBngFzRxc3NDTEwMbt26hfHjx8PCwgJGRkYYMWIECUwIqr7r6+tJv/wb71fBbebPn4+uXbvC09MTI0aMIM+UYPobl8tFaGgoKWjC4/ErscvLy2Pz5s1/dOy8vDyoqalh6dKlGDduHLy8vKCiokIW3FwuF48fP8bUqVOJSu3cuXOwt7cn48CZM2cgIyMDU1NTGBoaYufOnZTyjYVgX92wYQMUFRWJ6pIl3NiKzSzxeevWLTx58gQMw1DKmEePHqF///7o3LmzEBHL4tChQ9DR0SEL0ebmZrx8+RLl5eVobm5GXV0dVq5cifz8fCxYsADNzc3E89Pd3Z2MT4JELEui1tfXY+bMmcjIyMCgQYPIvkNDQ6GgoIB+/fpR5/Lo0SMMGTIEzs7OpAhIXV0d+vTpg/T0dBgaGiI6OhqysrIoLCwkBboAfl9ji7EIKocF8btkLPu7K1euQF5ennhIsp8/ePAAurq6hKQT7Ju7du1CaWkpZs2a1Sap8aPjsUTiyZMnYWBggODgYKraOcAno3R1dSkC7P79+7h48SKpzv7t2zfk5uZCVlaWIkWnTZtGxm72On5F3LYFVkUuqLD+9OkTKQDVp08f5Obmws/PD2ZmZjAwMICKigpMTEwgISFBqQwLCgoIEcsGKFsff8yYMTAwMICGhgYUFRXRr18/Mm4tWbIE3t7eSEtLo8ZLgP++YhgGO3fuxL179xAZGUkRsU+fPsX+/fuxYMECHDhwgIxVV65cgYyMDBiGIUo09nwqKythaGiIsLAwoaDi7xCxTk5OiI+Pp8bdGTNmECV9YmIiZGVlUVBQQL5ftGgRfH19ERERgbdv35LPGxsbqbHi9OnTMDAwIGrs69evo3v37lixYoVQwbD169dj37596Ny5M6KioqhgL8Cfm5w9exa7d+8m206ZMgWSkpLo2bMn5OTkYGZmhr1791LXeO3aNVK4SEpKCj169IC4uDiVDn3x4kUYGRkRj2cAlLIN4Bc0Ky4uxu7du4laePHixZCWlkZRURHu3buHiooKhIaGkiJjHz9+JM8QwB83fHx8YGhoiMrKSpJaHRsbiwMHDgjZJRQVFSE/Px/KysoQERFBeno6RcRGR0dDXV0du3fvpu71iBEjoKCgACUlJTAMg379+lH9sK6uDmlpaTAyMiIeti9evEDv3r2RmJgIS0tLStHK4/FQX1+PI0eOYNCgQcjLy6NI6vr6euzcuRPW1tZwc3OjtmNRU1OD9+/fUz6iEhISSEpKQnJyMhQUFBATE0MKpJaXl8PT0xP6+vpCwViAr0RNS0uDlpaWUDbUy5cvkZGRQZSsAP89HBwcTPw3X7x4gVOnTmHgwIHYvn07+vbti969eyM8PBwjRoygyNTy8nIkJCRARkZGKADM/kbwetm/y8rK4OzsjKSkJGruPXDgQJiYmKBv374IDAyEgoICsR3o06cPIcErKyuxfft2+Pr6IjMzk5C5b9++pZScgvf+d+YxrcfS1oE3lohtncHE4/FQXV0NZ2dnoWJmgu+N3bt3g2GYn3qfNzQ0YN26dZCUlKSI2KNHj8Lb25t6D1+/fh1WVlbEM/bYsWOQlJSkMvxevnyJ48ePY+PGjUIZc/b29qSAa3l5OaSlpan3UOt2KSkpwYABAyArK4udO3ciLy8PUVFRVGGtFStWwNzcnApMzp8/Hzo6OuQ8p0+fDklJSXh7e1OB2I8fP1LjS7sSth3tEEY7CduOdrTj/wRDhgwhE54FCxZg3759ePv2LVxdXWFlZUURsSUlJRAXFxcqvsNi7ty58PLywsCBA8l2lZWVcHBwQGhoKJmM8Hg8zJkzB15eXhgwYAAhRFnPr4kTJ6Jr167Em3TWrFno1q0bAgMDKZ8wQ0NDWFlZYfDgwYQkLS4uBsMwCAsLQ2hoKHx9fanoNKv8GD9+vJDn5/Hjx7Fw4ULIysqic+fOJIr8J9YFV69epZSlkZGRCA4OxqBBgwhZvHfvXgQHByM6OpryoWJRUlKCoqIiODg4UMoQHo+HCxcuQF9fH0FBQUhLS8PChQtx7do19O3bF6qqqlBRUQHDMJSiFvgPEevr64uuXbtSqcLbtm2Duro6DAwMhAoUDBs2DFZWVpg7dy61kAH4HrhnzpxBVlYWFBUViUcZ+5u0tDSkpaUhJiYGxsbGQhP3AwcOgGEYUuCERW1tLRISErBjxw4sXrwYOjo6yMvLowpZ6ejoCBUFa2hoQFRUFNLT08k5HDt2DBISEli4cCE2btyIBQsWQFRUlEy0ORwOpk2bBnNzc2RnZ/9UFTB27FhISUlhz5495Bo+fvyIxMRELFy4EAYGBsjIyIC6ujp27tyJ7OxsBAYGIiQkhEyiv337hvXr18PX1xeOjo7/dRGuvLw8aGhoYMaMGdizZw8hHtnF47dv37Bt2zZERERQzwF7PMHCZL+DmpoaGBgYUFV5a2tr0aVLF6ipqZH+I3g9379/x8OHD8ni+vjx41BWVib3zsDAAO7u7sRH7UdtceHCBVhYWFD+mQCfgDExMUHHjh2JnUdLSwsOHTpEfINZPHz4EOnp6VBSUsKePXuECnCdOXMGNjY2ePnyJf7991+MGzcOenp60NLSgo2NTZt+yS0tLaiuriaVzdsiYhctWgRAeBHKFgBJSEiArq4uVVwH4AeaUlJSqEV9fn4+rK2tCVF3/PhxpKWloWPHjujfvz927tyJ5uZmNDU1Yd68eaSv7tmz548JUeA/vr/fv3+HgYEBFYgD+CSVubk5sUhgkZ2dDT09PQQHB8PV1RXq6uo4fvx4m/dX8LmbMmUKNDU1iWL8yJEjpKhT64JdDx48INvm5+fDwsKC+NhmZmbi7du3+PDhA8aPHw8JCQlkZWUhODgYJiYmZLs/IW4FA2fLly//oY1HY2Mj9u7dC39/fwQHB6NHjx6or69HeXk5REVFISoqSsYEQV/FgoIC6OrqYubMmZQdCo/Hw4IFC6CkpISKigpcuXIFBw8ehIKCApXCu3jxYpiZmVHvjU2bNmH48OHo3bs3SbdliyhpamqS8+DxeELKbx6PR4pRBQYGkgCrIBErLS2N4cOHC7XBr3Dp0iX06dOH9Idr165h8eLFxALk06dPKC4uRseOHTFhwgSyHVuYj8vlYt68eejevTucnJwwbdo0kpVx6dIlmJubY8aMGbh//z6io6ORlpZG7nlLS4uQmvbevXuQl5dHVFQU5QfMBhhZVFRUICsri/j+3r59G35+foiOjhZSnj948AAvXryAoaEhREREEB0djX379oHD4ZBzuXDhAoyNjQkpOHLkSKLyGzlyJKngbm5uDi0tLZSXlwPgZzEoKChAQ0MDdnZ2iIiIAIfDQVFREby8vCAvL4+MjAwyj7l//z6Cg4MhIyMDV1dXmJubw9TUVIjImzVrFuTl5XHixAlUVFSgpKSEqDEF5w0eHh7Emxbg96mwsDBcvXoVT58+xciRI+Hk5IQJEyZQ7fzp0ydMnjxZ6F37+PFjDBkyBGZmZhQRC/ALuwmOG+z4BvDf4QcOHICOjg5CQ0PJb9pS6b58+RK2trZYuHAh+ez69evw8fEhQX4ul4ujR48iMDCQ9IPHjx/j3r17JLD57NkzpKamwtPTU4hUE5wnsRYxmpqaGDduHM6cOYOkpCS4urrCyckJWlpaKCkpIbZOAKh/A3x1bvfu3WFtbU0IVTbY3ZrEnD9/PrGKOHToENzd3dGtWzeKiJ04cSJSU1ORkpJC5gMcDgcBAQHw8PDAmjVrEBwcjJCQECQnJ8PFxQVJSUmkvQWzTw4cOIANGzZQ6tkfQfA+3L59u83gFkvEKisrCxVeq6mpgYaGRpvFzBobG8lc5syZM1T7zZkzhxo/gP8QsaKiopStxIULF6g2vXz5MkxMTADwyXtZWVlic/b161fs2LGDzLUERQQAf65hYWEBAEIWaV+/fsWmTZuoLLCHDx9CTEwMDMPA3d0d58+fx5MnT+Dg4EBl9gGgag58+vQJqampZN979uyBvLw8Ro4cCQ8PD7i6upK1V+u2bkc72iGMdhK2He1ox/86uFwupk+fDgcHBwQHB0NcXJykybx79w5OTk5CROysWbPg5eVFXuCt1Wvz58+Hu7s7Bg4cSFXy1NLSorySeDx+xW4PDw8MGDCAFHxqbm5GcnIyQkNDSZXYLl26UL5pu3fvhp6eHvbs2YOxY8ciKCgI/v7+ZNFeXl6OESNGYPjw4SguLqaUBQCfTHN0dMSECRPaJKGSkpIgISGBqKioP7IuEASb0jx+/HhkZ2dDW1sbtra2pLDPjh07EB4eDnd3d2phM2nSJEhJSSEoKAiampqwt7cnyj+23S5evAgJCQlS2ADgK8YGDx6MM2fOwMPDA3Z2dlQRJoBPxJqZmcHY2FhoAdSzZ0+Ii4tj5syZQsWqRo4cCRUVFarIVX5+PvT09FBVVYXKykpkZWVBTk6OImIzMjLQoUMHODs7g8PhYOfOnZgzZw6mTp1K+saIESMgLi5OLDBu376NiIgIqqjG4sWLoaWlhby8PHKPS0pKYGBggMzMTDx58oT4s7Kp76yqZ9CgQUKqilOnTqFjx45ELdHU1IS5c+cSggHgV0fPzMzEsGHDKMJx4MCBkJKSwqBBgzBhwgT4+fnB3d0dAGBvb0+KbbDYvXs3wsPDERQUhNu3b6OlpQWrVq1Cdna2UL/8U9y6dQvm5uZEwXPmzBlISUlRx79//z6GDh2K7t27/9fHA/iFPBQUFEgwgn2ea2pqoK+vD3NzcyoFNT09HSkpKfj69Svevn0LDoeDmJgYjB07liiKQ0JCICcnh/T0dGoBVFFRgVOnTlEplePGjYO5uTkyMjJQVlaGo0ePwtbWFh06dCCp3Sx4PB7KysqgoKBAEbGPHj1CQkICwsLCyGd5eXkYNmwYduzYATs7O/j5+UFZWRn9+vXDihUrcPbsWejo6BCSpa0FzLNnz2BiYiJExE6fPh2ioqKYPn06+W3re3Dp0iV069YNfn5+VMEVgE+Csm3Ftk9QUBBVjdvY2BjBwcEICwuDs7MzFBUVCeEG8D2i/4YQnTVrFrS0tPD27Vs0NDSQlFnBtm5sbISLiwtZBAL8VGY1NTVCmpaVlYFhGGoBLZh+ySI2NhaioqLQ19eHu7s7Kdh07Ngx6OnpITU1tc3xdtasWVBVVSVkQ69evaCsrEyCAh8+fMCSJUvg6emJ5ORkMm7m5eX9FnEbFBREEbeLFi2CpKTkLwvZCRIXTU1N6NWrFzp27AgtLS2Ehoa2+R6dNGkSREVFsX79empfvXr1wogRI6jP7t27BykpKaqA1s6dO8l5ZmdnQ01NDf369SO2EWyK/s2bN9G1a1fo6urixo0bOHfuHExNTXHjxg2MHj0aampqZD5w48YNSEtLo3v37mQMZs/99evXf53Syu7j5MmTYBgGysrK1Pjx9etXFBcXQ1RUFBMnTqS2y83NJarZkSNHQk1NjfJcHDRoEIyMjKChoQFXV1cqTbiwsBDu7u6wt7dHSUkJecf++++/UFBQQHh4OLZv347o6GiYmJhQxTVtbGxgbm5OZcdcuXIF/v7+iIqKIvYg7LW9evUKkZGRiIiIgLKyMhnPmpubyTldvHgRsrKycHR0hJOTEyZOnIijR4/Cy8sLly5dQkNDA27evIl+/fpBQkKC+Fe/fPkS165dw+PHj8HlcjFhwgSoqqpi3bp1OHXqFCwsLODv70+p5FetWoXZs2dj1qxZQtYHXC4XkZGRQv1s06ZNEBMTw8CBA8kzyf4e4NvTsIQf2+c/f/6MsWPHwtXVFePHjxfy2ayoqMC+ffuowPbt27cxdOhQWFpaEpVpREQEVUBo1qxZSEhIgKenJ5YvX0766IEDB2BsbIyIiAiKEBMcq9+/fw9jY2MyxrLXff36dSroImjvM2HCBFhaWpK+NGfOHNTX1+PRo0dITU2Fl5cXZdXBQvC4paWlUFBQgJycHHJyckjGUc+ePamCVytWrEBqairS09OpDJ+zZ8+iR48esLW1pQjV1oiLi4Oenh5VLNbDwwMJCQnUdoLkH9sHq6qq4OjoCENDQxQVFRF1++LFixEYGEhtA/DHTmlpaVhYWIBhGMyaNUvIb7attigpKYGjoyNZV7T12z179iA8PJzqL1VVVVBWVibvGcF36IULFzB37lwqSNrc3Iz6+noUFBRAWlpaSB1bX19PfKwF6y0AfCV4WVkZzp49C1dXV6xduxby8vIUGXrq1Cn07t0b//77L5Whd+TIEdTV1eHLly8wNzfHoEGDICcnR6mmb926BR8fHxJQAfjqVQkJCZiYmGDBggWQkJDAunXrkJqaCkVFRaFsPOA//ff27dt4+fIlbt++DX19fWLNsWzZMsjIyMDKyuqHGTHtaEc7aLSTsO1oRzv+z2BkZAQZGRnk5ORQn7NErLW1NZkwCVYHLS0txZgxYwiBymL+/PkwMTHBoEGDyILt1atX1EQf+DERyxYyYtUarQ3kt2/fTtJzAX7kNzAwEL6+vuQ8BSeMnz59orxbgbaJ2ObmZvIbd3d3dOrUCfn5+b+0Lhg2bBh1/Q8fPoShoSHl1fjlyxc4ODjA2dmZfPbPP/9gxIgR5JhVVVXo1q0brly5goaGBjx48ADGxsbw8fGhJnlcLhf37t0j7bly5UoMHTqUpCo+ffoUdnZ2CAkJoSbe/v7+KCsro5RxggvexMREWFhYYMOGDZQ6C+CrpNnjvXr1CgMGDKBSup89e0aIWDZdjK2I29zcjOzsbBgYGCA0NBRdunQBwzA4ceIEXr9+jZkzZ1IVln19fYlSSJCI1dTURG5uLt6+fYuvX79ixYoV0NfXh4KCAuzt7dGlSxeyAGRTXMPDw4nHGEuEAMDUqVNha2srpIYGgJycHKiqqmLQoEGIj4+Hvb09paSYO3cutLW1YWJiguTkZDQ0NODKlSuQlZUVIkGB/xCxoaGhQkVrfpe8aF0gBeAvzGxtbckxBFOoP3/+TNQPgsqcPyFLfqSUcHZ2Ro8ePajP6uvrERISAh0dHUKksOmDgiRqfX09PDw8qAVRWloarl27Rp1bfn4+TExMiMdyeno6+W7u3LkICwsDwzDQ0dFBhw4dwDAMUWu3vgY2xVHwnAXTtU+ePAkjIyNSbGPv3r2YOXMmdu3aRZRPb968gb29PU6dOkWNI01NTRSB9uzZMxgbGwsRsbm5uSR4tXTpUvTu3RspKSlYtmwZ2d+5c+cIEdsWuceSGM3NzRgzZgxRu9va2sLLy4uowy5fvoycnBzynP8JISp4z6Ojo4n3LKswrqmpQVJSEhwcHJCcnIwFCxbAz89PaIwuKioivohsBXd28SyowhXcJjIyEgzDYMSIEbh48SLMzc1hYGBA1JnHjh0jxVvYsY7L5eLbt2+Ijo4mC+RDhw5BVlaWFO9pamoi7wNBP+E/IW67dOlCyIrFixcjOTlZSCHZFtjru3fvHnJycqClpYWjR4/ixIkTMDc3R1BQEHV/Wfzzzz/keWhoaACXy4WbmxvS0tLIb9ixbPLkyXBzcxOqvr1t2zbo6uoSMn7r1q0QFRWl0nnv3bsHT09PdO3aFefOnUNKSgrU1dWhoKBAyC32ONevX4e0tDQSExOpwCCL/4aIra6uRkFBAaSkpEjRMBbfvn1DUlISOnToQMbWmzdvwtDQkBpbLl++DE9PT8THx6O5uRnfvn3DrVu3cPbsWSoLo7S0FEpKSli+fDm6desGJycnEswD+OpVKysruLi4wMfHhyJvr1y5gu7du1OqNhZXr15FUFAQ3NzcqIwS1mu1uroavXr1gqKiInXeAP/eP336FC0tLcjNzYWnpyf69u2Lrl27Uu365s0bJCcnw9vbW2isY0lXltg5f/48xMXFYWFhATc3N4qIFYTgvKy5uRmhoaHIysoCwL/3bL8cPnw45OXlKX9+gN8/p06dCjMzM8raCvgPEevh4YGhQ4eSZy8vLw9mZmbQ0tKCh4cH5QN6584djBo1CrKysjAzM6MKnBYUFEBRURFZWVlIS0uDoqIievbsScbu/fv3w8zMDM7Oznjy5AkmT55MikkBfNJaS0uLWMQI2iNFRERQ7xmAT4ypqqqSgHZcXBxUVVVJIOjBgwfo27cvTExM2vTfFkR1dTWxcmHbOygoiARQcnJyoKGhgaysLAwePFjIauXs2bNISUmBmpoarl692mYA7c2bN/Dw8MCYMWPI90ePHoWnpycSExOJSpZF60BYU1MTZYXS3NyM8PBw9OnTh3pHsMX7Lly4gM+fPxM/7QkTJlBerYIWFwA/e6BTp05CgUZBtCbrBfv/+PHjISYmRlkzNDY2IiwsjFK6C4KdY8rKylKBUID/ngoPD0dISAg55tatWyEmJkbusZ+fHxiGoTI9GhoaEBkZibi4OJw+fRre3t64cOECRo4cCTk5OTx//hw8Hg8FBQXo3LkzNW43NDQgOjoakZGR4HK52L9/Py5dugRjY2MsXLgQampq2LJlC65du4bo6Gj06dMHDMMgOjq6zUwcts0A/jw9MDCQCCnWrVuHsLAwTJ069a+zrdrRjv/X0E7CtqMd7fhfR2NjI6qrq4knloODAxYuXEgtkt+9ewdXV1eoqKhQZvKsytDW1haFhYVCRGxqaiqUlZWRmJhIpVX+jIhNT08nE8CjR49i9OjRVEGSRYsWIT8/H3FxcVSRMIBPKAYHB8Pf358qdDRlyhQEBwdDTU0Nubm5FCk5duxYojph/eXYYyUlJcHExAT29vY/tS6QkJCAhoYG5Vd4/fp1qKio4P79+wD+ozR4+fIlFckXxOLFi6GmpgZXV1cqFbKyshJGRkbw8fEhFbsF0dLSguzsbNjY2CA/P5+09ZMnT2BnZ4fQ0FCcOnUKmZmZMDY2JmTEs2fPoKenh5SUFCrFNj4+HlZWVm0SsQDfP69jx44wMTGhlHbsPocNGwYFBQVKKbd582aoq6uT37Np84IT8QcPHqCiooL4arW0tFAph2wbaWpqYuzYseR+cTgcXLt2DS9evCB96vDhwxg1ahSqq6uxdOlSqKurC9k+lJSUwM7OTugaS0tLYWxsTNpk48aNEBcXh66uLqmKXV1djcLCQtKW9fX1GD9+PGRlZWFiYgJPT882PYSdnJyECPvfQX19PczMzGBiYkKppp88eQJbW1sUFRUJKS0qKirg7e1NqZb+JP2stQLlyZMn5Plfv349HB0dqaBNY2MjunXrhuvXryMhIQGysrKkUJDgPWxqakJgYCBcXFwwbtw4+Pv7w8bGRqiasKqqKs6dO4fv37+joKAADMNQiuaGhgZMnDgRIiIiqKiowLp168AwDIqKioTUOIIpjoLpqgC/T+Xn5wsV1mHR3NyM9+/fIzo6Gl5eXlQxkpkzZyIuLg5mZmaYOHEiIVZYItbDwwMvX74k5D+Px8PYsWOhoqKCvLw8pKWlwd7eHpmZmWRcPH/+PJKSkmBhYfFTxVNlZSU6deoECQkJ+Pv7U4RM6wXs3xCiKSkpYBgGycnJSE5OhoiICKkA/+rVKyxatAju7u4IDg5Gr169qLRWgD/+9+vXD6dPn6YK5wH8AIigqhHge4GKiIgQQoL16BQsbAbwnyPBIk4s/P39cevWLRw5coQKRjQ1NWHFihU4c+YMVTjw69evv03cXrlyBaKiotiwYQOys7PRuXNnMrb/DIKEwNOnT3HkyBHynqivr8eBAwdgbm6OkJAQ8rv09HRMnDiRjFejRo0ixOPSpUuhpaUlRKTMnTsXHh4ebWalxMTEAOATC3JycuR6v379SsaSJ0+ekLbJz88HwzAwMTEhxaIECzZdv34dcnJyCAwMbDOA9Tv4ERlQXV2N3NxcSEpKUgW52EwaQVuXO3fuQENDg6j12La+dOkSxMXFSRFKQbS0tODixYsYNmwYFeSYN28e3N3dkZGRQbIh3r9/T9SlAP1s3L59G0lJSXBzc6OyQwC+Im/o0KE/vMaHDx+SuRGrhoyPj8e4ceOoMZCtUq+jo0MVcgL4BL22tjYJcAN8svPBgwdEPXn48GEoKipi3bp1qKmpgZKSEnx9fSkvyx+d4+TJkyEpKUm8zNm2nTRpEtzd3REfHy+0bW1tLRYtWgQ1NTX079+f+u7z58/IzMzEgAEDwOPxMH36dGJdw+FwSJ+LiIgg27x48QLl5eWUh29lZSVycnJI5gfAf24dHR3Rr18/4lu/detWhIWFwdDQEEOHDkVubi71bEydOhViYmJCRHhwcDAVbK2vr0d4eDixRti3bx/k5eXJ2Mk+E7dv327TXuFH+Pr1K8rLyxEdHU0yd9avXw9jY2PSn7ds2QJJSUlISUlRRbmOHz+OgoIC6ljTpk3D7Nmzyf1asGABAgICqPnZ8ePHYWxsTCnmW6O1d++2bdsQFRUFa2trytrh3bt3ePjwIXJycqh3e2lpKRiGQUFBAT5+/Eh559fV1WHevHnE65TdV1vnIKiuzs/Px7Bhw3Dt2jVwOBx8+PAB/fv3B8MwyMzMREZGBgICAoTO8datWzh37hyxAGtsbMS0adMgJydHBBxfv35FUlISNVfdunUrVq1aRd4DAH/+4+TkBEtLS5SUlGDhwoUIDg4mgcdTp06hS5cu0NfXh6KiIpVRde/ePSQnJ8PQ0BCZmZkYO3YsOV8Oh4M7d+7A19eXFO8C/lM34smTJ3j16hU2bdoELS0t+Pj4/HION2/ePFhZWeHSpUvg8XiIiYnBzJkz/yoI3452/L+KdhK2He1ox/8KfhYN7du3L+zs7FBcXEwtzt+8eYO+ffuSF7ggEZSXlwdHR0dMnDiRIgKmTJkCNzc3jBw58ofH/JEiliViBQmP3NxcKCgowNvbG3p6elBVVaXIXYA/ebG3tydm++PGjYOysjLWrVuHtWvXwtXVFX5+fpS1QV5eHrS1tcmki8vl4uPHj9DQ0MDly5d/aV2QlZUFIyMjLF++nLRPXV0dVFRUCGkB8Cc/dXV1sLe3F1L6APwJIVsh+PDhw9Rkq7KyknjCtSa7WbAesrm5uRQR6+joCDs7Ozg4OJAFxpQpU/D27Vts374dbm5uSE1NpaozJyQkwNbWFsuXLxdKQfvy5Qvi4+PBMEybC93q6mqkpqYSYoHH42HmzJkYOnQoAL6KuVOnTqS9P3/+TNp1//79YBgGWVlZyMrKarO9i4uLoampiby8PGqyy2L79u2QkpJCUVERrl69irt376JLly6IjIwUSs/29/cX8sacNm0aaac9e/ZAQUEBM2fORHZ2NhQUFIS8xdh+rq2tjRs3bmDFihXw8vJCz549qUUywFey/KkagVX0fv78GX5+fjAyMiLP38ePH5GcnAxpaWnK16yxsRFdunRBQkLCX6kfBPvehAkT4O7uDhUVFYSHh5M+PXnyZNjY2MDFxQXZ2dlwdXWFjY0N2d7AwAAdO3aEq6sr2ZdgmiqrPomNjSV9jMvlorKyEpGRkURFfuDAAcjLy2Po0KGQk5NDamoqAL4STlNTkxD5XC4XJSUlPyVi20pxDAoKAsMwCAkJESKxGhoaMG/ePISFhcHFxYWqJpyXlwdFRUVMnz4dQ4YMgZeXF6U2Y4t1GRkZkX68bt06mJqaEoJtx44dEBcXh76+Pnr16kXGj1OnTmHcuHHk79ZeroLesA4ODm0+B2ybAL9HiAq2yfLlyyElJUWlJM+fP58UZxIkpI4dO0YUYAMHDiTPx+HDh+Hg4ABRUVEqOFBXV4fo6GiqevimTZtIJej6+nqUlZVRSsNv375h9uzZ1LUD/AAJ67UbGxsLMzMzyMvLU6nBL168QEBAQJvpwr9L3L5+/RqTJ0+GlJQU5OXlSTDsZwtawe/Cw8OhqakJU1NTODg4EKViQ0MDDh48SBS//v7+0NTUhK+vLyIjI9G7d2/KO/bu3btISkqCv78/UTHX1tYiPDwcPXr0IG2zdetWcDgcTJkyBYMGDcL58+fRqVMn6r6vX78ehYWFRDHF5XLR0tKC48ePY8eOHejVqxdsbGwI4SWYAcMqPv/bgoInTpzA3r17icoa4Cut8/PzISsrSxGx169fh7OzM9LT00nqrZycHCl2JOgl7ejoSBWmZHHs2DEYGxtDTU1NSLU4f/58eHh4YNCgQURlzaK0tBSTJ0/G3LlzSXtdvXoVycnJ8PLyIufws2sVxMOHDwmR5ODgACMjoza9wQsLC6GpqYlRo0ZRXr1Xr16FgYEBUbZnZWVhzJgxePfuHWpra9HQ0ICIiAgUFhaS/fn6+kJDQwNjxowROs7Ro0exbds2QkbxeDx06dIF6urquHHjBr59+4bGxkbExMRgy5YtpB9cv34dt2/fJsG579+/Y+HChbCxsaGIQ9ZnmcfjF7gMDQ0l4zv7rLPKz+jo6DbbbOfOnWAYBmpqakLk6f79+yEuLk5sDe7fvw9VVVUqG0Dwmt+/f48BAwZAREQEM2bMwIoVKzB69GjIycmR4Arr5coWqD1z5gw1RjQ0NGDmzJmE+GTxK5KLx+Ph1KlTiI6ORlhYGDgcDng8HmbNmkWEBWwAat68eZg3bx4YhmkzSNjS0kKC6TIyMujfvz8WLlwIHo8HJycnigzncrm4cuWKkAjiR3jy5AlSU1ORkJBA2Rjl5eXBwcEBcnJyMDc3F8rsWbVqFURERDB8+HAyd5kyZQqsrKzAMAwiIyN/auHC9q2cnBzIycnB19cXzs7OcHV1RUlJCZlDlJaWEiVq62JmbCYT65eck5OD6upqtLS0YM6cORAVFYW5uTnMzMwICQ7wxx5ZWVkwDCMk8nj58iVRzfv5+WHAgAGUuj4nJ4dk7wnaawD8jLDFixfDyckJCQkJGDVqFHW+bBFTGRkZDBgwAPPnz0deXh5lR9HQ0PBb9+706dPw8vKCvr4+TExMYGlpKeT53I52tOPnaCdh29GOdvyPQ/AlvHfvXixcuBDnz5+n0hhZInbRokWEoBJ86U+YMAE2NjZExQHwJ0xOTk4YN24cSfNNSkrCpk2b2vT9E4Tg53PnzoW3tzdVWAjgV2QdPnw4IdEqKirg6+sLExMTISK2vLwcXC4Xhw4dgrm5OVEWnD17FmJiYnB0dISXlxelJlqyZAmZ4Hz8+BEfP36kFJK/si5gU+2XLFlC0oUmTJgAR0dHKjW9ubkZjo6OKC4ubrMtvn37BlNTU9jb2+PGjRvU/Xr8+DESExOFJvmC7Tdp0iQhIvb+/fvo06cPpk6dClVVVcTGxkJCQoIsHrZu3QpnZ2chItbf3x89e/b84XkGBwdDS0tLKEUe4JP2gueVm5uLHj16YO/evUIk0PLlyzFy5Eg0NjZi3759kJKSwsyZM0iaKLYAAQAASURBVJGWlgZdXV0UFBQIVQVesGABdHR0MHjwYEqN9fDhQxgYGLRZxKBLly5QUlJCZGQkwsLCICcnR1IYBdHS0oKqqiq8ePECVlZWxD/x+vXrUFJSgrS0NCHRa2tr0adPH2hra1OEe0lJCby9vdGzZ88203Z/l7xwd3cnJBPAJ2S9vLwoIvbUqVNwc3ODj48PZsyYgcWLFyM4OJgoLf7keK1RVFQEJSUlHD9+HA8ePECvXr3AMAyqqqpQV1eH48ePIykpCQEBAUhMTASHw8HIkSNx9epVvHnzBvn5+ejYsSOpqg78xyakubkZjY2NlNKM9SxbtWoVPn78iIqKCmhraxMybujQoejQoQNUVFRQX19PWaSw+BkRK9gOgv/u3bs3xMXFsW3bNkrZAwC7du3CzJkzqUXT/fv3YWlpSXkuX7hwAWlpafD19cXdu3fRrVs3FBQUoEePHuSZXbp0KVEPswT//PnzMW3aNFJEp/Xz3drLVU1NjRTaOXToEOTl5Yk/5KlTpwi5lJmZ+VeE6JgxY9ChQwc4OjpSXsjAf4jYGTNm4P3796itrYWnpyciIiJIBW+WMHz16hV69+4NGxsblJSU4Nu3b7h58yYiIyPh6OhI2nPChAkYOnQoDh48iOjoaAwdOhSdOnWixs0HDx4gNDSUjANssSgHBwc4ODhg9+7duHfvHhUIaGxsxKdPnxAREQFvb2/Srps3b/5t4lZQNbhixQowDANpaWmsW7euzX7EQnDcjoqKQocOHTBy5EhcunQJISEhkJaWJu+fpqYm3L59G6NHjyak0ZEjR6CjowMxMTFyD9h9njlzBr1794a0tDRJ/xYsuDd58mQwDIOXL1/i4sWLEBERAcMwlAVBfX09wsLCMHjw4B8uzCsqKpCUlAQbGxtSgAoAVq9e/ccV0dtql9zcXBgZGcHExARWVlZUcbGamhqMGzcOnTt3plKAr1+/DgcHB/Tv3x81NTWYNm0aJCUlKa/Db9++wcrKCqWlpW1eW15eHlRUVNCvXz+hgOaCBQsgLy8PNTU1su2oUaOgrKwMV1dXmJiYwM7OjsyLrly5gpSUFPj6+lLP1e/g8+fP2Lt3LxYvXizk1d363Wlvb4/U1FTcuHEDV65cQWhoKNzc3IgtkYGBgZCPrr29PXl3NTQ0IC0tDQcOHBC6Xzk5OTAxMYGTkxMcHBxgaGiIhw8f4v79+0hMTISEhATs7e0hJycHfX19co5jxoyBmpoaNDU1IScnh6lTpxICeOHChbC1tcWgQYOErpvH42HNmjV4/fo1zp07By0tLRKQHTx4MCGyWuPVq1cYNGgQGIYhXsmCQXoLCwvMnj0bXC4XI0eORPfu3YW87QVRW1uLOXPmwNTUFHZ2dvDx8WmzuFRiYiLc3NwgIyNDFQF99eoVfHx8hHzIfwcNDQ24fv069e7jcDh48uQJXr9+DVtbWxJEuHXrFpSUlMAwDKZMmdJmn54xYwZkZWWxfv16uLq6om/fvli5ciU6duyIrVu3UnPZAwcO/LYa8u3bt1Tf3Lp1K7S1tVFSUoK8vDzIyMggKytLyNu1uLgYnp6e4PF4GDduHOTk5NCpUyeMHj0anp6eMDU1pbLqWLDXtmzZMigqKkJSUhLHjx8nwXk7OzvMnz+fXA/7f0EF+b59+6Crq4uysjJUVVVh6tSp8PDwQGpqKrEHunbtGiZMmICJEyeS6zt48CBaWlqIxZOHh4fQ/gH+cys4R2ADt7t378bGjRsRHx+PgIAAYtUleL/aKsopiCNHjqBnz55wdXWFvLw8qcchKFb5nXt39uxZrF27FvPnzxfyfG5HO9rxa7STsO1oRzv+RyE4ARg7dizk5ORgaWkJCQkJZGdn4+7du+T7fv36wdHREdOnT6cmsrm5uVBXV8e+ffuEJlETJ06Es7MzVFVVYW9vD3Nz8zYXFW2hNZGYkZFBPtu4cSOZgLFFrQB+IYuAgACYmppSldJZ3Lx5k0SzDx48CEVFRaxevRrnzp2DkpISPD09sWXLFurYRUVFxLpg7Nixv7QuYNs0KSkJurq6EBERIemJlZWVyMjIgJGREfr06YMZM2bA39+fikyfOHGCFNBgFRh1dXUwMjKCo6OjEBHL4ldErKOjI/Lz84XSFa2trdGxY0eyOGOxZcsWODs7o0+fPoSIFUwLKysrQ2lpKfbu3UusHhobG+Hv7w89PT1CvPzovPbv3w9HR0dISkpSVYnr6uoQFRVFSKCmpiZkZmYSAqakpASTJk2CjIwMBg8eTJEfCxcuRJcuXaj2OXbsGExNTcl1C7bL/fv38c8//yA1NRX5+fmUmptV+giirKyM6luXL19G9+7dsXnzZuo679+/j+HDh8PMzIxKYSspKYGfnx8iIiL+Km23qqoK5eXllOUBwCdivb29YWBgQK7h+PHjGD58OLS0tBAWFoZ+/fr910W4amtrERoaSlRqZWVlVOES1uvtwYMHUFRUxOTJk5GRkQGGYUh/eP/+PaZMmYJOnTpRyjRBj0X2/wUFBTAwMCDVqQG+0jMlJYWMQdOnT4eHhwfExcUpf9fWHnIsETt58mShysUAX8l/9+5datHdtWtXKCkp4cCBA9TiXvA82ft+//59KCgoUJ7IAD8ApK+vj/3792P06NEQExMj5B67bU1NDd6+fQt7e3vSJmy6taysLCFOeTzeD71cBZX8iYmJcHBwwLNnz/6KEHVwcCB9JC8vD+Li4jAzMwPDMOjRowdljQLwnzuGYcg49/jxY6J6FgwYsN/16tULhoaGkJWVhYODA1VMcNeuXTA0NMTly5fR2NiIjIwMSElJITMzk+zj+/fviIyMpBTMY8aMIYV5FBQUYGZmhqVLl2Lz5s3Q1taGqakpPD094enpCXt7e3K8W7du/TFxy977ly9f4urVqygsLKQUcT9TF2VnZ0NERARFRUUA+ONg586d4e7uDjExMar/CPbPy5cvw93dHa6urujatSsJJLJ4+/YtKioqMH/+fMo79tq1a5g9eza13+LiYkhJSWH27Nm4f/8+Ll68iNDQUNjZ2bWpkBL897lz55CcnAxTU1OsWLECERERsLa2/q+9BWfOnAk1NTVyXbNnzwbDMAgKCiLn9Pz5cwwdOhTBwcHUObFE7IABA3DkyBEMHz4cDMNg7NixmDx5MkJDQ2FtbS0UTBEkosaNGwc7OztMmjSJCkBzuVyMGTMGNjY2CAgIwPv379GrVy/cvn0bDQ0NuHDhApydnWFoaEhUflevXkVYWBjps4cPH25zPvIrtB6nBdt43LhxUFBQQOfOnRETE4M+ffqAw+Fg+vTppACpIN6/f4/AwEDExsZiypQpCA0NhZOTE2XHAfDJLhUVFWKRsX79ejAMQwWXtm3bhkmTJkFXVxcGBgaoqqrClStXoKGhgePHj+PatWtYtGgR5OTkMGzYMDQ0NODLly9YuHAhVFRUkJWVhdWrV+PixYtk3sRi/PjxSE1NJUTWnDlzEBcXh/T09B96e/bu3RsyMjJUYODz588wNDQkyml3d3ehwmIs2P2y/3/79i3q6+uFMmLYNtq+fTusrKzg7+9Pvvvy5QsiIiLg5+f3x+SW4H398OEDPn78SAkOTp06BRMTEzK/vnfvHnr27ImysjLqWHv27MHWrVvJ31FRURg4cCC+f/+O7t27IyYmBpKSkjAyMoKnpycAfhFUQY/t3z3PlpYWnDp1CoMGDaICU6tXr4a2tjZGjhwplI3Bqp6dnJwwf/58lJeX48SJE5CSkiL7ELwX7PFYWyNJSUls374dO3fuROfOnbFgwQJ0794dGhoamD9/PrEZEDze6tWrMXv2bDLesli1ahWsra0pG7ATJ04gPDyc2JMwDIO3b9+Cx+OhvLwc2traCA8PJ78XnBP8jBQ9evQoYmJiEBAQQD1HGzdupLxyf4Tnz59j3759cHJyAsMwJIMMQJvEdes2aAv/TSHWdrTj/0W0k7DtaEc7/ldw+fJlBAUF4fz58wD4aT1mZmYYMmQI5R8ZFxdHmfHfuHEDJiYmJBXs+/fveP78OTZu3EgmdWfPnsXChQsxZ84cKnW3raIvrSE4sRFUzz5+/BgJCQkQFxcXWoxeunQJwcHBkJWVpYoJAPxJ06dPn/D9+3eEhIRQ6UU+Pj4wMTGhJup/Yl3AVurlcrmYNGkSFBUVcfnyZWRlZZGKpgBfUbVq1So4ODggLCwMvXv3Ju0yevRoUohKV1cX9vb22LFjBwA+OWlsbAxXV1dKnfoztCaTBRWEPB4PJ06cgJWVFbp37w4dHR1KGQXwFbFubm7o0qULRVCOHj0aKioqcHR0hLy8PDw9PYnStLGxEYGBgTAwMCAp1gB/gbBu3TpCBnA4HPTv3x+6urooLi5GdXU1rl27hvDwcIoE4vF4GD9+PKWEaWxshLKyMiwtLWFrawtHR0csWbKEul62v+zevRs6OjoUCSuY4t1WddnJkycjPDwcjo6O2Lt3L1lcnzt3Djo6Opg7dy5evnyJyMhI9OvXr01vrQcPHiArK0uIiJ09ezYGDRr0x6SFi4sLXF1dyXZFRUUYPnw4UW7V1dXBx8cH+vr61L1qvZD8bybfnz59Ir6/Bw4coNLDm5qasGjRIlJ8pqSkBJ07d4akpCRZeLDt9O7dO0ydOhXy8vJC5D+Lq1evIj4+nqoUzPqZBQYGAuCTKLGxsVi+fDmOHz8OZWVlxMfHU78XbOelS5dCREQE2dnZVLuMGzcODg4O0NHRIQV5WMTFxUFFRQUHDx5sU0XMEjnV1dXEH6514RFWiQ7w+1bHjh2F1IMVFRXQ09MjAY27d+8iMTERW7duFXqOf+Tlyi7cV65ciaSkJPB4vD8mRP39/cl1XrhwAbGxsTh//jy4XC6WLl0KDQ0NoWAOwB8r2EyABw8ewN/fHy4uLoiJicHevXup337+/BnV1dXYu3cvbt++Ta5v165dGDVqFAoLC8lvP336hODgYDg6OiI5ORn5+fnw8fGhlJ6rVq1C586dce3aNXz8+BGvX79GSEgI/Pz8sHr1ajx//hzTpk1DYWEhSktLyXM6atSovyJu7969i4sXL+LDhw8krTo3N5cKSAB8GxNBb+3ly5dDRkaGBAuOHj0KNTU1lJSUEBJeVlYWe/bsoe55eXk5nj59iu/fv6OsrAwhISGIjIyk3gNtvUdZgl5JSYlKh339+jXmzp0LeXl5aGhowN7eHmFhYYT4aotEEtz/lStXiJ94RESEUADlT/Hs2TN0796d9JMDBw5ATk4OY8eOhba2NkJDQ8mzwpIirY/HWhNkZGTg3LlzWLNmDXlf9+rViwSuWlpaUFxcjMTERPj7+2PcuHHk/NnsltZELIfDQVlZGSwsLGBlZYWgoCBqbnHjxg04OzvD2NgYdXV14HK5uH//PrhcLsaNGwddXV08evTol+3zO+8Ewd9MnjwZKioqROHb0tJCLA0EPYXZ4164cAEhISHw8PBAVFQUsWsQ3OfIkSNJBseOHTsgJydH3l+t3yXXrl1DREQEDAwMMHnyZCFP5y1btkBcXJwQbGvWrIGdnR20tbWhrKwMhmHQpUsXqhhgYmIiKVTK4XAQHx9PKZ/b6ptv375FSkoKpKSkMHr0aMyePZv4lrIe8vr6+kK2Qa3btX///r9Fljc0NGDy5MmwtraGubk5YmJi4ObmRo0Rv0vECvaJyZMnIyQkBEZGRkhJSSHBztu3b0NBQQGTJ09GVVUVIiIikJiYSM07nj9/jtDQUFhYWCAzMxMcDgcnTpxAamoqmSPv2bMHXbt2hb29PZSUlGBmZgY5OTliH/Cz/in4TmPJXmNjY8jIyFAFNYH/ELGjR48WsmZ4+PAheU527dpFzSHq6+uxYcMGKlNo6dKlmDBhAmRkZFBaWoqnT5/CysqKZB7du3cP8vLyMDY2xsaNG6ljNTQ0wNLSkviYt76+1NRU2Nvbk7/PnTsHT09PGBsbQ0FBQcjju7y8HJqampRPces5xsqVK5Geno6BAwdSiuhjx44hNjYWXl5eWLRoESIjI2FkZPRH88Dv379j1qxZZCzctWsX3Nzc2rToao1224F2tOO/QzsJ2452tON/HEuXLkWfPn3Qu3dvakKwevVqmJmZYejQoRQRK0iMnj59GioqKqitrcXVq1cxatQomJubQ0pKCq6urlQxLMH0oMbGRkJssfjRJEFQvcJObNnKyUFBQdDQ0BBSZp05cwZZWVloaWnBw4cPKUUvwFcbGBkZkclfbW0tUlJSsHnzZnKef2JdUFhYCEtLS6SlpWHYsGEQERGhinINGTKEELE/Sn9eu3YtlJWVUV5ejoaGBpw7dw4ZGRnQ1tYmi9OvX79CTk4Offv2bbOt2oLgMVatWkUtDliVV01NDTlW6wq1a9asQb9+/ch+tmzZAjU1NZw/f56kAA8ZMgSOjo4kNa9r165QUVEhhNjYsWPRqVMn2NjYgGEYjBw5EjweD42NjejVqxfs7OwgIiICNzc3BAYGUr5a7DVYWVmR/dva2iI4OBiVlZV4+PAhwsPDqcI8rb1zpaSkkJ+fL9Q2w4cPR0FBAeX7OW/ePCgrK2PSpEmIj4+HpKQkZs6cidraWnz+/BlZWVlQU1ODtrY2HB0df0pAsESsubk55WX4KzuO1lixYgX09fXJ39+/f8eGDRtIwYvWRKyhoSFFxLY+7t+irq4OERER6Nu3LxQUFCgVyaNHj9ClSxcSNDh48CBUVVWhqqqKKVOmCFkwvH37FtOnTwfDMNi4cSN1bmvXrkVgYCA8PT2JUoRtqwMHDkBKSgru7u6ws7Mj/m08Hg/Hjh2DsrIyEhISqGsWbOfZs2eTtEiAT5QpKiqivLycWJwwDEMFd+Li4sAwDCEjWbC+wCwhOXLkSMjKyuLw4cPkOfv8+TPs7e2JSvLZs2dISUmBjIwMSaEF+AttExMT5Obm4v79+4iIiKAWjr9T3GrKlClkQcySK//+++9fEaKrV69GVFQUoqKiqDF40aJFxH+ZvaeCbSJILN+5cwf+/v6IiIigAlcsBLd7/fo1DAwMwDAMevXqRf2utrYW06dPR2RkJLp160b5OjY3N2PcuHHw9vamCKXnz5/D1dUVRkZG1JjGtuefELcrV64k9zM3NxcWFhZQV1eHs7MzMjMz8fbtW3z48AHjx4+HhIQEsrKyEBwcDBMTE7LdokWLICkpiZ07d5LntVu3bmQs5PF46N69O/T19eHt7U3ONzc3F3p6eli/fj25D7t370ZISAhiYmKI7URcXJwQCfH48WOMHj0aEhISbabGP3/+HHFxcXB3d6dUZz+C4DPK5XLx7t07Kn36v8E///yDt2/f4uLFi9DR0SFjy4QJE8AwDOzt7dsMsgni2rVrcHJywoABA0gQWPB3zc3NyM3NhYaGBiZNmkTG0D59+pD7lJOTAxcXF4waNUrIuuTEiRPw9PSEkpISeWcIBqRdXV0hIyNDVPqvXr1Ceno6pX77EVqrjX/k6Qz857m5ffs2Zs6cCS6Xi6lTp+Lu3buora3FuHHjICIiQlSRgs9FXV0d6uvrSZ9j79uxY8fQ0tKCuLg4jB07FseOHaPGF9bHfc6cOdQc4urVq4iJiQHDMEhPTwfAn7Oxx8vKyoKDgwMWL14MBQUFzJ07F+Xl5Xjz5g15r9nb2xMv+QMHDsDY2Bh2dnZwdnb+bf/Kt2/fEgI6MTERW7ZsQWNjI7nGuLg4ODo6UplTgv3p2bNn8PHxIZkCv7pP7Bxt9OjRyM7OxsKFC/+rTJPx48dDSUkJu3btwoEDBxAYGAgFBQW8ePECX758QVFREeTl5aGvrw8nJ6c25x01NTXYt28fNDQ0EBgYiJkzZ6J79+6YNGkS+Q1bDDI5ORkMw8Db21tIId7WNQvaAjAMgzNnzmDLli2wtLSEv78/Nd8F+O/wjh07ori4mDrHBw8ewNraGtOnT0fnzp0pj9PLly8jPj6evHsXLVoEhmEgKSlJBAIHDhyAlZUVmfOfPHkSycnJmDJlSpvzqffv3yMiIoIqAstiyZIl8PLyohS0o0aNgqioKPz8/KgAMIuKigro6urCxcWFtA0L1nd2+PDhSEpKgr29PeXbe/r0afTr1w+WlpYIDw//I2uo1qR+c3MzNm/eDE1NTeJX/aP9CJ7j8ePHKXFEO9rRjt9DOwnbjna0438c48ePR8eOHWFpaSlElKxZswaWlpbo1asXVZhCcOFlamoKPT09yMvLY9CgQdixYwfev38POTk5EgluTVyEhYXBzMwM6enpuHLlyg8n14ITjwkTJqCwsBB79uwhqdyvX78mhUtaE7EAfwGrqakJNTU1eHp64uHDh+Dx+JVcw8PDkZCQgOLiYoSFhcHLy4tKzbtz585vWRcA/Aj+2rVroaSkBBkZGWIZIJjuOGTIEEhJSWHDhg3EI5YFj8dDTk4O4uLiqM8fPHiA5ORkxMfHE5Xb9+/fSbssW7bsjytys3+3nrDdv38fmZmZ0NbWJkRaa3C5XEyYMAFBQUHU5w8fPkRSUhLi4+PR3NyM+fPnQ1RUFFOmTMHDhw/h7u6Oa9eu4f3799i7dy/ExcXJgq2lpQUvXrzA0aNH8eDBA6FFPauumzhxIlJSUmBiYgIfHx+hdP6fKatXrVoFMTExZGdn486dO/j333+Rk5MjVNH80aNHGD16NOU3O336dMjLy2PatGloamrCly9fcOvWLRw6dIi0688WXQ8ePMDw4cPRuXNnqtjMnxCiu3fvhpmZGa5evYr8/HykpaUB4BNlDMNg/PjxFBHr5+eHTp06tflM/Ldgj5mUlESu+/Pnz4iIiEBAQABpk6amJnA4HBQXF0NLSwvjx48XSp3jcDhYs2YN1X4NDQ04dOgQLCwsICsrS/lMA3ybiLKyMgwYMIBSsbW0tKC5uZkoYn9GxLJt//37d8TFxZHnmK10zSq/BJ/T3Nxc6jnKycmBuro6li5dSnlQp6WloVOnTsjIyEB+fj7x4m1ubkZ2djbs7e2RkJAAXV1diImJkSrbX79+xbhx42BgYAAtLS1YWFiQgl4ZGRm/7eUqmIYs2Md+RYgKgsvlYvHixdDX14empqYQMbF48WLo6upiyJAhpCAVwFeInj59Gu/evSMk1eXLl+Hv748uXboQoiUwMJCyokhPT8eUKVPw+PFjeHp6wszMjBTp+RnYflNUVARnZ2dyTLZPnDx5EtLS0ggICMDmzZupNvkb4nbWrFlQVVUlljS9evWCsrIyUX9/+PABS5YsgaenJ5KTk8l5nD9/HikpKdT9evfuHUxNTYk6+du3b0hISMDp06fJ8WbMmAFVVVVUVFQIEYK7d+8mKkQnJyfo6OgIWWYAfHJpyJAhEBMTI9fEElMcDgfr1q2Dvr4+EhMTqUDpr/CjYOKv8CuCatq0aejWrRshRkpKStCzZ0+qSN3PcP36dVLsRnDOwuPxcPXqVZiYmBC/2LNnz0JcXJw8gywGDhyIiIgIoh7u168fJk2aBC6Xi7KyMhgZGcHLy0toDL98+TL69euHlpYW/PPPP+jYsSPJHPgZBK9r8eLF0NbWxq1bt376jrh27RqsrKwwbdo04pvKvss+ffqE4cOHQ1RUlDzrXC6X2p/gmDhhwgRCbJWWlsLd3R2SkpJUkO3Tp0+IioqiVOosLl26hC5dukBeXp4oH9lrmjJlCkxMTCAmJka9/1iUlZXB0tISvr6+qK6uxtevX7Fv3z54eXlRxZV+596zpLesrCwuXrxIAr0An+RnC3y2lf1SUFAAHx8fyhP4d0it1vgbn83q6mq4u7uTceXw4cOQk5OjArdcLhePHj3CqVOnfjnv+PbtG/r27Yv4+HhoaGiAYRghL+/du3dj+/btxK6IVVO2vjbBMWXZsmWQkpJCZGQk+WzTpk1wdHREWloaZeXT1NREPFVbF7fMzMwEwzAYN24c+Yy1mImMjASXy0V5eTmmTp0KW1tb7Ny5k7KCMDMzw5YtW1BTU4MuXbpg5MiRZD9ttf+HDx/g7u4OU1NTnDp1Cm/evMGXL1/g6+srVPTt8OHD2LJlC3lnta49APCDMTExMUKiFWNjY5L5wKrA9fT0KB/k2tpavH//HlwuF7du3RISo7SFqqoqKnAv+CwHBgYiJibmh9sK3s8lS5ZAQUGBys5oRzva8XtoJ2Hb0Y52/Ff40aRy/vz5UFFRQUFBATGqZ7F48WL06NGDbHvy5EmcPXuWFDCqra3FggULcOzYMcq03tvbWyi9fdy4cVBXV8eSJUtQUVEBaWlpREZGUgt5FoKTh5CQEHTo0AHGxsYQExNDQEAAUZG9fv0aQUFB0NHRoQi1Xbt2wcDAAHv27MGhQ4fg4eEBIyMjEgVmq6JbWVmRirSCbfQ71gWChMeBAwegqqoKU1NT9O/fn0wGBSegWVlZYBgGS5YswZ49e7B7926iQigsLISDg4PQYnv58uVQUlJCWVkZpQx9/Pgx1NTU2my7n7Vl6/0L4v79+xg0aBBRXrXVX2bPng1XV1ehAia7du1Cx44dySJsxYoV6NixI/r164e0tDRqwXD48GGIi4tj4MCBZBIqeKzKykrcvHkT9fX15L5cuXIF0tLSlG8hQE+6f9S/uVwutm3bBgUFBWhra8PY2BhmZmakD/N4PJK6q6amJuTrOWPGDMjLy2P69OlCFhe/s+i6e/cu5s2b99eFEO7cuYOuXbvC3Nwc4uLiVNELQSKWTaH9/PkzBg0a9D9aeEGwD82cORMiIiKIiYlBdHQ0fHx8YGtrCw6Hg1OnTuHgwYPUszhr1ixoaWlh0qRJJNDTpUsX3LhxA3v27MHDhw9JNeEhQ4YA4BeksLe3R9euXYnaj4Xgfa6pqUF1dTVRn7FErJKSEkXECi5cWGXP169fYWhoiLKyMhw5coRKjeRwOJgxY4ZQX2CLJGlpaVFqWcFzmjNnDrp16wZ/f3+kp6eDw+Fgx44d6NSpEy5duoSGhga8efMGY8eOhYiICElh//btG548eYJDhw4RL9f4+Pi/8nL9W0JUEJs3b4alpSX69u0rlE0wY8YMxMTEkDbNy8sjxLmvry8KCgrIs3358mWEhYXB0tISZmZmMDU1JePeo0ePYG5uTgqLVVdXw97eHiEhITh58iQ53s/68u3btyEiIkIpvgD+OJOQkIDAwEAEBwcTFRjwZ8RtS0sLvn37hujoaKIMPHToEGRlZQlh39TURAgfVoEH8NXRenp6kJSUhIuLC/r370/6SmpqKjp37owpU6bA09MTzs7O5Dq/fv2K4OBgknbLQnDsu3jxIpYsWYLx48f/VIVXXV2NrKwsyMvLU0Qse67bt2+Hqakpunfv/lvtLTgWCAYaf4bW3oc7d+7E7NmzsXPnTqqQI9u32X3HxsZi7ty5v3VeLC5duoS+ffsKvQ+OHz9OUt137txJ+fh++vSJZLfU1tbCyMgIkZGRSE5Opgo2Njc34/Dhw7C0tISfn98PCbmPHz8iPj4eDMOQZ60tCF7PiBEjICMjQxXF+xF4PH6BIzU1NUhLSxPCmL3mz58/Y9iwYRATEyOF+drC7du3ER0dTYjpqqoq+Pv7w8bGBvv27UNTUxMePXqEyMhIODs7k/41Y8YMZGRkkP1cu3YNgYGBUFVVxc2bN/H582fU19fD3t4eHTp0QF5eHnXugte9fft2MAyDf/75BwBfwc0wDCnG+ifK0jdv3qBHjx7En1swkDZlyhQwDIPU1FQy3ly5coUESdm0/DVr1lBZVz9Ca5us3w2stu6XDx8+hIaGBt68eYN9+/YJpegvXbpUiDj+0XPAfs7hcHDkyBFSuLJ3794A+MGfjx8/knHv1q1bUFdXR1hYGPWMCnrtA3wCVlZWFlFRUbCxscH48ePJd+vXr4eTkxPS0tKECqDOnDkTQUFBiImJIWRpQ0MDunfvDhkZGeTl5WHMmDEICAiAlZUVOBwOLl26BIZhwDAMZUUB8L13Q0NDoaurC01NzV9mI7H48OEDPD09ISEhAQsLC6SkpMDFxYW8h2bPno0xY8aQMfzcuXPw8fFBly5dqEDwli1bkJSURPzP2Xs5Z84ckm3FFticPXs2xo8fj86dOyM7O5u67xMmTEBgYCC2bt1K2bO1RkhICGXz0bro8ObNm+Hp6Ukyn37k5b1s2TJ07txZaE3Wjna04/fQTsK2ox3t+GsITgD+/fdf3Lp1iyJzWM/QoqIiitgTnGiOGjUKampqxA9UcHEE8CdXL1++RFRUFBwdHYWKFVlbW5MJzYULFyApKSmkQmGPyaJv376k+ja7IEhKSoK/vz9RbD579gwODg4kIrx582YsWbIExcXFZD8cDod4ZrKpU3V1dXj//j05HlucRxC/Y13AToyePHmC0tJSUrm4ddELgK+esrW1RdeuXSlfyJ07d0JfXx/r1q2jFg7l5eVQU1ODjo4O9u7dS9r07t27UFZWxps3b365UGAxf/58ODs7C3m7CYJV33bt2pV8JuhRWFZWBklJSSxZsoRaHJ0/fx52dnYkNbu+vh5btmyBiIgIrKysCPnLns/hw4chJSWF5ORkSg3AFkhRUFCAv78/srOzCblYWFiIiIgIoWIev4uXL1/i/PnzuHDhQpuFsfLz88EwDKZPny5U5GHWrFno0KEDmXyz+FNv178tYNO1a1dISEjA19dXiJRctWoVsSb4G5L4dyHYl3bv3o2cnBwMHDiQpGKOGjUKmpqakJWVhZeXF/EWBPiLHD09PURHR8PDwwMaGhr49OkTQkJC0KlTJ6SlpUFaWppS0+zbtw8uLi5ITk4mhKegcnHy5MmwtbWFmZkZLCwsKAuG48ePQ0VFhRBLbbV7c3MzBgwYgG7dukFOTo5SKtbU1CA6OpqyDGDB+kM3NDT8cLHO5XKp56OkpASurq7U/eDxeMjKyoKkpCQhIFj8N8Wtxo4d+9uEqJmZmVA6amsLE0dHR6SnpwtZXAgSmurq6jh27BgaGxuRlJQETU1NDBkyhDz3//77LzZv3owFCxaQdpk1axb69OmDIUOGUKnRlZWVsLe3R2hoKE79//zGf4U1a9YQtfvVq1fx9OlTREVFYerUqfj333/BMAy1mP4VcRsQEECIWxb+/v64desWIezZ/tLU1IQVK1bgzJkz1D3fvn07DA0NcfToUVy+fBmzZ8+Gvb09IiMjwePx8OrVKwwcOBCenp5ISkqiVN1v3ryBkpISIYIF70lDQ0ObhXR+9qw/e/YMw4YNg4KCAtavX0/99tChQ2Ts69ev30/3J9jPV69ejblz5/7UwgAABgwYgOzsbHLOOTk5kJOTg6OjI/T19WFlZUXmARcuXICCggJMTExgY2MDKyurv0rvbsvy5datW7CxscGsWbMoL2WAT76bmpqSsfX169dQV1eHqKioULX75uZmlJWVwdraGoGBgT9VJAYHB0NLS4simlufIwCEhYWBYRgYGxtDS0sL/v7+hBRsDfZ427Ztg6ysLKSkpDBp0iShsf/z588YMWIEGIZBRUWF0H6WLFkCX19feHl5Ue/Ue/fuwdvbG+bm5lBUVISLiws8PT2p/rl27VowDEOlW1+7dg0BAQGQkpKCubk5MjMzYWJiAkdHRyQmJuLQoUPUtQuqcT08PDBgwAByfVeuXCGWRj8LHLfVph8/fiTFGu3t7eHo6Ig9e/agvr4eCxYsgKKiIkRFRUk/c3JyIvfnzZs3UFVVFfI5/dGxWPxuMEKwP+7atQvPnj0jRdMmTZoEeXl5ql/evHkTCQkJmDVr1k/nbT86Lx6Phx07dqC5uZl4zhoaGiIlJYVkWty5cwfa2toICAjA4cOHER4eDhcXF9LPiouLoaSkhB07duDt27eYMGECHBwcKIun9evXQ09PDzIyMqQI1ty5cyErK4u8vDwMGDAA2tracHV1JX0tPz8f4eHhxKO4ubkZmZmZSEtLw+rVq6GoqEj6BPCffl9XV4cTJ04Qpa3gdz/Dhw8fEBUVBWlpaep5GDVqFLS1tbFgwQJqTXT27Fn4+voiLCwMCxYsQFRUFNTV1dGnTx9ISUlh586d1P6fPXuGV69ewcbGBrNnzwbAn6erqqpCRkYGM2bMAMAPWCorK+PIkSNCYobWxfe0tbXJ3927d4eYmBjmzZtHVP7s+qR14KY1ASsnJ/fDDLd2tKMdv0Y7CduOdrTjryD4Qs7Ly4OlpSVkZWUJWciisLAQOjo6xMNRcLvbt2/D1tYW165dw9mzZzF+/Hjo6upSVUfXrl0LDw8PeHl5CRX5uH37NlG47N69m4r219XVYffu3VSaPI/Hw7JlyyAuLg5bW1vqOh49eoSgoCBKufPmzRtwuVzU1dWRFKycnBxqOw6HA19fXxgZGRFPUxZjx479K+uCvXv3gmEYkkr2+fNnLFmyBA4ODpR369ChQ5Gfnw9paWls27atTRJw4MCB0NDQwMKFC3Hjxg3U1NQgNDQUfn5+CAwMhIeHB5k4P3nyBGZmZtTCqLUnauuJmIKCgpBvYFuoqqoi+7p27Rr09fXRv39/sj+2uNCMGTNw7tw5VFVVISQkBL6+vuByuZgzZw4GDRqE+/fvY9OmTejYsSMKCwuFzm/Pnj3w8/Mjn7Ppt0eOHEFTUxO6du0KTU1Nkj61Z88e6OrqkvTfv8XPiNDhw4dDXFwc69atoxZWXC4XGzZsQHNzM+7du4dLly7hzZs3baYAC0KQyPiTxWTrc83MzMSyZcsQFhaGqKgoouRhsWbNGjAMQ6Uw/m9DsH9dvnwZzs7OuHz5Mi5fvowRI0bA0dGRSjlcs2YNRo0ahcGDB5NF05cvX6CmpgYJCQmSripIfO3duxdubm7o2bMnVVxo/PjxUFNTw7Zt23D37l24urpCX1+fItpOnDgBhmEoFdbLly8pAmvHjh0QExNDVFQUITHev3+PyMhI+Pj4tElELVy4EAoKCkJjHJfLxbFjx4SKVvF4PKxbtw6SkpJkAcpuw54jwzBU6vDfFrcqLCz8K0L0Z5XYV61aBScnJ2RkZODmzZtCHn9ubm6kuM6xY8cgIyODmJgYmJmZYcSIEW2q3T9+/IhBgwZBUlKSqjjN3vuqqio4OTnBwcFByG/wR9ixYwdUVVWhra0NLS0tODg4oKGhAc+ePYOJiYmQrcKPiNspU6YQ4jY/P5+Q4LGxsTAzM4O8vDxWrVpF9vPixQsEBARQVcIPHjyIESNGUCqmxsZG7Nq1C9bW1mRBDoCqhC54HwICApCYmEiCcmyfqaiowMSJE38rlVUQ1dXVSE1NpYo2jR49GtbW1hg8eDDxNE1MTCTftw4asFi+fDk6duwo1C/bQm5uLnR0dFBUVIQjR47Aw8ODjOG3bt3CmDFjoKGhQVKmL1++jJycHEybNu2P0tFZCL5nBPvc27dvER8fDykpKYwdO5Z83tDQABsbG2LpwOVyUVlZCWtraxgaGqJr165EKcqCw+Hg8OHDUFBQIOr9srIylJaWYu/evcQPv7GxEf7+/tDT0/uh32iPHj3AMAxRpLNj+enTp8lv2nqns1Y5sbGxcHR0xMSJE4WK9Hz9+hXz5s0jtj6COHHiBHR1dSEpKSlk//HmzRtcu3YNa9euRXl5eZtk19atWyEuLk4RQFevXkVSUhIhfnk8Hs6fPw9vb2+h9G72fL5//w5TU1OMHz+eOseLFy9CRkYGGRkZv6wiLygWmD59OiQlJZGXl4fbt28jJiYGioqKpPDs9evXceDAASxYsADnzp2jCOjGxkakp6cjKSnpl8djsXLlSqSmpv4yGNF6Hq6lpUWEAgMHDhQitb99+4bIyEjY2tqSDKrWweHfPV5rz9mAgAAoKCgQAcHTp09hYmICW1tbeHl5kXlNdXU1pKWlSTAI4D9H+fn5cHR0pBSxEyZMgImJCTw8PDBv3jxkZGRQRdceP34Ma2treHl5kfN7+/Yt8eJmLS3u3bsHHo9HbKQEjyHY//7EPoXF+/fv4eLiAgsLCzx58gT//PMP1NTUKJ9UDodDxtbr16+TYnGhoaHk/TR8+HBISEhQVgkAP/hrZGRE5gDbt29Ht27dsGXLFnC5XFy8eBEmJiYkqFxXV4cnT55g1apVRO3MWisNHjwYPXv2BABERUVBUlISfn5+8PX1haqqKqZNm4ZHjx7h4MGDsLe3b3N8Wbp0KWRlZYUI43a0ox1/hnYSth3taMd/hdmzZ0NRURHHjh3D6dOnsXz5cmhqalIeT1OnToWoqCgpggQApaWlSElJodLvX716hSlTpkBbWxtTp04FwE+rWrlyJSE5mpubcfbsWTQ0NODFixcwNDTE2LFjhaL9bJqs4ESooKAASkpK6NatG7y9vUnxHXbCdeDAAYiIiAhVX+VyuaipqYG7uzssLS2JLyY7IW1uboa5uTm6detGtvkT64LWhvrPnz9HamoqJCUlCTH25csXlJSUwM7ODi4uLggLC4OqqiqsrKywYMEC6nxbp+YNHz4cdnZ2kJCQgK2tLSnCwHp9uri44MCBAzh16hQ8PDzavM+CakGAjoT/bnodwFfOpqWlQVtbG+Li4khLSyP7nTVrFvT09KCkpAQLCwu4ubmBw+EgJycHysrK2LRpE2l71ppAsHhC61S+2tpaBAUFkTS4o0ePolOnToRUZLdzdHQUKtzzJxBsl2PHjmH79u04cuQIZRshWEitoaGBapNx48bB1NQUhoaGMDAwwJgxYyjvwdbtyWLZsmXIzs4W8gP+FVrfr6NHjyI4OBjR0dFCROyBAwf+SjXWFin9O4pd9jdbt25Fjx49MGLECPLdmzdvkJ+fDwcHB2oRxZIcAP9ZfP/+Pby8vODu7g5VVVWithQkt/fu3Qs9PT0UFBQA4Kuu3dzcSOBj37596Ny5M+zt7SEvL0+1y9WrV8nzNW7cOBgbG0NfXx8ODg6kYM7q1ashJycHb29vogxzcHD4YaXra9euwdraGrm5uRQ58PXrV/j5+RGFpOC9eP/+Pby9vZGQkEBV4L59+zaysrKwatWqNu/dr7xcBfvH/fv3f5sQFcSPFrGtPe+0tbUxffp06ty/fPmCbdu24ePHjzh79izU1NTIMxsWFgZlZWX07NmT6vdsuz59+hRjx44FwzBU+iv7/ePHj9GnT58/Uo+/ePECFy5cwNmzZ8l2ubm5MDc3b1M92pq4tbe3J8Strq4uzM3N4eDggN27d+PevXtwdXUlwUS2sGFERAQh7Hk8Hj58+EACga3HKi6Xi969eyMqKkqojV+8eIGHDx+Se7RkyRLY2dmhqKiI3KP6+npERUURNe2f4vXr1+SYp06dgqKiIglufPv2DaWlpdDW1kaPHj3INuy7lwX7PvnVwr41Yaivr4+MjAzExcVRfb2qqgoDBw5EaGhom4GqPxnTWr+/MjIykJGRQYi2I0eOwMnJCUFBQViyZAlWrlyJkJAQ2NjYEBLt1KlT5N+VlZWwtLREVFSUEBEL8EmalpYWjBkzhmQIycvLw9PTk6RmNzY2IjAwEIaGhkL+sKdOnYK0tDRSUlIA8MdSwfmRYCBQ8DldunQpdQ/Gjh0LR0dHFBUVkcyRzMxMPHr0CACtzH/8+DHx53769CkMDQ0RHR39y4I9gvYrLFjvyzFjxpDPysvLMXr0aEJY8Xg8nD17lqR3t/bZvHXrFgICAogdBI/HQ0FBAYYMGQItLS0wDIMePXpQwQpBCBLU8+fPh5SUFPGcf/fuHYyNjZGZmSm03Y/GlStXrkBMTIwEvH90PID/LMjIyPzwt22hqKgIysrKuHz5MnVNPXv2hJqaGoYOHYoRI0bA398f1tbW4HA4mDRpEsTExLB48eLfJmLZ82Q9Z9kAZWvPWfY+NTU14cGDB6SfcDgcHDx4EIaGhkLZGK9fv0ZGRgY0NTXh5eVF3oOPHz9G37594evrCx0dHdKn2La+ceMGNDQ0SIYJO/czMzMjWUgsGhoaUFpaClFRUeKJ3hZa+8b/Ch8+fICHhwdUVVUxePBgMtbduXMHxcXFsLa2hra2NrGa+fjxI96/f08VjH3+/DliYmKgrKxMBaIuX74MfX19TJs2DVlZWejYsSPCwsLIs3v16lUiJLh79y6GDx8OY2Nj6OnpoVOnToS85XK52Lx5MxiGgaWlJTp06EDmFVVVVVi+fDlcXFzg6OgIW1tb6OvrE297tq2vXLkCAwODdgVsO9rxP4B2ErYd7WjHX6OxsRHdunWjUoQ5HA6OHz8OTU1NMslJTk6Gv78/UVa+e/cO/fr1Eyp2A/yHiNXT0yNqs9OnTyMwMBB3797FiBEjoKKigtevX6OlpQWjRo2CjIwMZVTf2NiI6OhoODk5kXS1wYMHQ0JCAps2bcLJkyfBMAzxTWRx4sQJ2NnZEeuEY8eOYffu3WRC9Pz5c1hbW8PFxYUsONhJaUtLC5kU/Yl1wYcPHygyl/33y5cv0a9fP4iKihICqK6uDvv378eAAQMwcOBAHDhwACYmJm1WrWePyaKmpgbHjx/HyZMnKQXK58+f4efnh6CgIIwZMwZSUlIYOHAg0tPTMXbsWOTk5CA5OZlSHwwePBiSkpLo3bv3L9PZBBcX2dnZkJOTw+7du3HixAkMHTqUFGljJ3n//vsvrly5gvLycnC5XBw/fhwGBgZtpj4uX74cIiIimDp1qhBJ/O3bNzQ3N8Pb2xtPnz7FwYMHKaV0Y2Mjli9fjitXrlCk2p9C8Ppyc3Ohrq4OR0dHiIuLY8CAAbh06RL5fujQoZCRkcHSpUvJImXOnDlQU1Mj5F/v3r2hrKzc5uK0tWpMXFz8v5oMtyaPg4OD0aVLF3IugvgT0kJwv0+ePMH9+/d/uNgVBHt9rPehiooKunTpQv2GJWKdnZ2pAA6LZcuW4cKFC2hsbMSHDx8QEREBFRUVqoI1e6wbN26Q+37z5k3ilXns2DGoqqpiyZIlqK+vh62tLQwNDXHgwAHq2tatWwcFBQVs2LABu3btQlxcHFRVVYmi8dixY5g/fz5GjRpFEaJttSWPx0N2djY8PDzQr18/3LhxA8eOHUN4eDgcHR3R3NyMZcuWYdCgQZg0aRKpdL5p0yb4+voiMDAQFRUVOH/+PCIiIqjCGjdv3vxtL1fBlNm/JUR/BcE23L9/P7kHo0aNgp+fH2pqash5Dhw4kFI5jxgxAq6urhg1ahTZT0lJCaytrclYVFNTg+HDh0NGRoZS6f/MIuF3cffuXfTu3RtKSkqUzUVrtEXcurq6QlZWFi4uLlBQUICZmRmWLl2KzZs3Q1tbG6ampvD09ISnp2ebhP3jx4/h7OwMExMTlJWVUePBggUL4OzsTD1n48ePh4eHBzp16oTY2FhCRuTk5MDR0RE2NjZITEyEk5MT8U4EhIM0f0LMbt26FZqamhQx/+XLF8yZMwcMw1Cenyz+NLVV8L5NmzYNEhIS0NDQIOQgi+3bt0NGRkYoqPq3YFWiffv2hY6ODgwNDQnZfOjQIQwYMABKSkoICgpCz549SZ89d+4c1NXVMW7cOELa3717F5aWloiJiSHjrbe3N0k53rJlC9TU1Eh2zd27dzFkyBA4OjqSYPa3b99gZ2cnVHzzw4cPsLGxwcyZM3Hu3DnqvdfS0oLc3FwhS5QVK1aQeyDYvmPHjoWTkxOio6MRGBgIJSUlIQJ97NixMDc3h5KSEnx8fLB7925UVlbC0NAQ3bt3p0hiwe0uXLjQpkcnwFeCMgwjVKH+w4cPqK2tJeODIBHLEq4AX+UXERFBtp05cyYUFRVx8uRJnDlzBuvWrUPnzp2JR6wg2goOsMXQPn78CA0NDQwcOJD8ZuvWrUJ1D44dOyY0L+vfvz969+6N79+//9RnU15e/o/e67W1tQgODib2My9evMDJkycxYMAAbNiwAb169UJycjJiY2Ph7u5O7DGam5tRUFAAERGRXxKxrf1p9+zZ81PP2WXLlpE0fMG6Dnfv3sXHjx+RlpYGb29vLFmyhDrO9evXISsrCwkJCWr+fOfOHaSlpUFUVJQKwLLXb2ZmhoULF5LPPn36hMjISPj6+iIkJISyfKqvr8eqVasgKSmJYcOGUdcI8O+npaXlr5pdqF1ev36N2NhYTJs2DQzDYMSIEbC0tES3bt0wd+5cjBw5EtLS0kIZa1wuF9nZ2XB1dUV0dDRUVVUhLS1NvLY/fvyIUaNGQUtLC1paWujUqRMMDAxw6tQpcDgcVFVVITw8HJaWlqSA56ZNm/D27VuYmJhQWQgAoKuriw4dOlD2YCyqq6tx6tQpREREQEZGBqampiQAw+JH6412tKMdf4Z2ErYd7WjHb6P1Yqy5uRn29vaksrrg55mZmYiLi8P3799x9uxZoQXl7du3MXToUHTq1IlEh1m8fv0aY8eORWxsLHg8Hvbt24ewsDAYGRlBUVGRqtB+5coVxMbGwsTEBOPGjUNRURGCgoJgaWmJ/v37g2EYJCQkQEZGhko9njZtGkRFRTF37lzcvHkT1dXVCAsLQ2BgILhcLnJzc0n6qaSkJPr06YPnz5+jpqYGVlZWcHV1FTK0B/iTv7+xLliwYAFV1AngE7F9+/aFmJgYUcwITvoWLFgAHR0dUkCoLVRXV2P79u2UtQDAr+zLptJ9+fIFAQEBkJOTg5OTE/r27YtevXphwIAB6NOnD1W1PjIyEh06dICtrS1cXV2hrq6O48ePt0loCF7ftGnTIC4uThUj+/r1K+bPnw99fX2kp6e3udgvLS2l/F9b73fjxo1gGIZSWbOenHV1dXBzc4OPjw86d+5MpdVXVVUhICCAqlj+33idsoWiWPKUJR169OhBEbG9evWCv78/uFwumpqaEBMTQxYb+/bto3xEm5qayGLzb1RjvwPB/R4/fhyhoaHw8PD4ZfXt39nfhAkTYGlpCSMjI2hqamL+/Pk/LJgnqGIuKSnBmDFj0K9fP2hpaQkpZt68eYMhQ4agb9++lGLp06dPkJWVxdatW8lvnz9/jsjISKirq+PmzZtoampC9+7dkZubS37D3nf23GJjY0nBj6amJnTp0gXKysoIDg4m22zfvh2LFi0SCuRkZmZCSUkJd+7cabN92upjgj7Ps2bNgo+PDxiGgY2NDYKDg8HhcFBYWAgZGRkkJyejU6dO8Pf3JwW+9u7di6ioKFI53cXFhYy3ubm5f1Xc6k8I0ZEjR/7y+f/RNbN49uwZ/P39qTEaAOLi4hAXF0f2lZiYiA0bNlCK95s3b0JXVxf+/v6EiK2ursbIkSMhJycnVMX7b9Hc3Izr169j9OjRQj7fP8Pdu3fh6elJKop//PgRr1+/Jimzq1evxvPnzzFt2jQUFhaitLRUKFWb/fvRo0ewtrZGSEgIduzYAQ6Hg3fv3sHHx4cKaE6ePJl4BFZWViIuLg7y8vJ4+vQp8R8dOXIkBgwYgMLCQsqrcdiwYQgPD8f27dvbfMexELyHZ86cwd27d3H37l3o6uoKqfgePHgANTU1ISuPJUuW/DHp1PrYxcXFUFBQQHZ2NmXbcefOHZiYmJD36p+idR8dNWoUUboDfD9fTU1NKsX/w4cPQucG8L0qXV1dMWHCBELC3L17Fw4ODrCzs4O5uTksLS3JszZ+/HgEBQVRx3/48CGSkpIQHx9P7te3b9/I8YqLi8k8YeXKlbC3t4eYmBhlc/H582dERESgsLCQfMZaFQgW+2p9DZmZmejTpw+xIBAMOKurq2PPnj1Yu3YtxowZg44dO2LdunV4+vQpjIyMkJycjAsXLlD7ZOcx06dPh5iYGEWgAfxgrLKyMjp06EC+mzFjBnx9feHk5AQvLy9SqPH8+fPw8fFBbGwsjhw5gpiYGFhYWFDZRXFxcVRWBcDvs7KysujTpw8hmgTHrIkTJxJiOiwsDCkpKTAwMMCgQYPIOPn582dERUVRc4uHDx9CQkICHh4e6NWrF549e0aKWikrKwtlUrFYvnz5X/lsfvz4EZqamhg3bhzOnDmDpKQkuLq6wtnZGVpaWoQcffr0KWJjY9Hc3Ey9hyZMmPBTIlZwzrlr1y5MmTIFBgYGcHd3/6nn7NmzZ7F161bS7sOHD4empiYAfnC2f//+cHd3p4jYmzdvokePHli5ciW4XC42btxInpdHjx4hLS0Ntra2QgIHKysroXoSAH8tERkZiYCAAMojncPhYNasWVBVVaUy2ABgw4YN8PPzI7/7EQTvX2lpKXJzc8l4PGvWLLi5uWHJkiUkOHTv3j14enqSQqIsNm3ahE6dOuHy5cv48uULampqkJGRAQkJCVL06tOnT7hx4waOHz+OlpYW+Pn5wczMjPib37lzB9u3b8eJEyeI4v7bt28wMTGBoaEhmf+vWLECHTp0QFRUFBiGwbx586iMLUHs378fnp6eJFvmVzZZ7WhHO/4M7SRsO9rRjt9C6yJcbCpeUVER/Pz8hJSKU6dOhbe3N/WCX7p0KRwcHKj9DB06FObm5kLFtAQVojweD0OHDgXDMPDy8hLyKbp69SqmTp0KU1NTREdHY8iQIWSRYmxsDBERETJJFFSjFRcXQ15eHhoaGjA1NYWrqys4HA5mzpwJDQ0NQp4tWrQIDMMgPj4ez58/x/Pnz0m6TlvpqL9jXSDoPfvu3TsEBARARUWFkDfs758+fQorKyvIyMgIpUht27YNDMMIpWex4PH41Y7Hjx9PTRhzcnKgo6OD3NxcsvhgK2d7eHjg0KFDbZIq69atg6KiIpkAl5WVgWEYSiX7M+9YQ0ND4nXHgsPhIDIyEgzDUEQsu0hYsmQJzM3NqSJc7H/bt2/H/fv3ceTIEXJfa2pq4OrqSqqgnz9/Hnp6etSkuq6uDpGRkUSd/TcQJM7evHmD1NRUoi7auXMnOnfujFGjRkFBQQFdu3alCl9xuVxwOBw0NzfD3d0dd+7cwZkzZ6jCPI2NjVi0aBFF4LJt+Tekxc8geK8OHjyI4cOH/3WxLxbTp0+HqqoqIS3i4uKgpqYmVBimtZJk3rx5EBUVxfbt2/H06VP069cPHh4eQhWSP378SPmmsggICBAibZ8/f46uXbuiY8eOcHBwgLGxMTgcDsrLy3Hs2DGq0venT59gYWFBEeGJiYm4ffs2OU9BQmnOnDkAQI1zrq6uJGV8/vz5v1X8pHV7s/7NXC4X9+7dQ/fu3Ynn5Zs3b+Dn5wc/Pz+qMM3Nmzfx6NGj/9rLla1m/juE6Lp166gFemlp6W8VfGltx+Hh4YHw8HBSVIT13iwqKoKrqyvCwsLg6ekJCwsL6r6z+7l37x6MjIzg7e1NEbGjR48GwzAUefbf4k8Woyxx6+bmBkdHR0qx//z5c7i6usLIyIgKBrUeA1mw292/fx82NjaQlZWFs7Mz4uLi4Ofnh8bGRuKJGBAQQEg11kKirYKVgmDT3ydPnoz09HQYGRmhb9++bQb5BM+tuLgYKioquHbtGj5//ozQ0FDExcVRc4Kqqip0794dhw8fpu5fjx49qGv/Ewg+M9OnT4empib69+9PipaFh4fDycnpr8YywW0qKipQVlaGtLQ0IS/hgIAAaGtrE1Wa4HZLliwBwzCEsM/LyyOel+y84enTp1i6dCl5/mpqatDc3IzZs2fD1dVVqMjOrl270LFjRzx+/Jg6Vl5eHhiGIQr4S5cuISgoCC4uLuRdWFVVhcjISLi6ulJq/FOnTrVpS/KjdmO3PXXqFNLT00kGAcDP1lm4cCEkJSVx7tw5XL9+HdLS0lTq94YNG7Bp0ybU19eDw+Fg9uzZYBiGImJfvXqFrKwsHD9+HM3NzRg3bhxUVFSwceNGnD9/HiYmJjAxMSEE3blz5+Dv708q1bPPKDs+enl5ES9MAJT6nmEYREdHU2r+6dOno0OHDqSI06ZNm6Cvrw9HR0eqLfLz82FiYkIJAwD+eLR7927Y2trCzs4OsbGxuHz5Mjw8PNC/f3+htl27di1ERUX/OrBaWloKBQUFyMnJIScnh8wVe/bsidTUVCHCd8uWLdR88kdErGBwNC8vD507d4aEhAR27NjxU8/Z8PBwcLlcbNmyBQzDwNXVFZ07d6be/ywR6+rqijFjxuDatWsIDQ3FwIEDwePxSM2H4OBg4kt8//59YmfVu3dvTJw4EXFxcTAxMflhtk5lZSWioqIQEhKC1atXo6WlBUFBQRg1ahQ2btwIOTk5qljX3LlzERER8dP2FmzPpUuXQkZGRsjLmiVDeTwempqaEBERgdDQUKF7sWDBAvj4+FCfczgcpKamQk5ODnv37qX6y4EDB4hS3NbWFmfOnKG+b2xsRFVVFaKiooj1GMC3nTp69Cix7pg1axZRogt6D7PtyOPx4OvrS6m+29GOdvzPoZ2EbUc72vFLtF4w+/v7ExLo8uXLsLe3R69evUha3adPnxAUFEQpZLlcLnbt2gVjY2NKUXbnzh1kZWXB3NycUmywYBc2GzduxPLlyxEVFYXw8HCi4hQ8t6amJmoy8vnzZ3Tv3h2xsbEQFxcnE3LB4hoPHjxARUUFTpw4gZaWFrx8+RK9e/cmXkg7d+6EgoICJkyYAHl5ecTHx6OqqgpVVVXo2bMnmcz/iXVBayUCwE/DiouLg6amphBRlZSUBB0dHfj4+FD7efHiBaytreHs7EzSkwVTbuvr6xEXF0el+y1cuBBKSkq4fv06SRNjz6Wurg7+/v7w8PDA5s2bhdJ3i4qKSMGMLVu2UNWgBUkXwe1Y1ebmzZuRlZWFwMBA3Llzh7pvkyZNQlRUFHx9faniMgCfJBIREaGK0QB80jgmJoYi3GbNmoWoqCj06tWLTCq/f/+O5cuXQ1JSEh4eHggJCYGPjw/s7Ox+6M/5K2zZsgV9+/Yli7avX7/iyJEj+PTpEyk6xi4oi4uLISUlBU9PT3JfFy5cSEihxMREGBsbQ0ZGhqqYzRJtggob1rPvdwjYtsjwX3n3tsbfENQ8Hg/fv39HWFgYeZ737dtHqWXY/Qou8AoLC6Grq4uOHTvCwMCAjCWVlZWEiGWJ0dbHYwvWAEBaWhoSEhKErofL5WLNmjVYtmwZmpubMXbsWJiZmcHKygrGxsYICAgggaWEhARoaWlh2rRpJDVckDiqr6/Htm3bYGFhQQqCAP8h5/r06YNevXqRQky9e/f+rXT9tu7B0qVL4ebmBk9PT0pFXF1dDX9/f/j7+xOy7X/Cy3XGjBm/TYhaWlqSdhkzZgz09PQQHBz8Rwr5BQsWQFlZGYqKilBSUhJKHf/69SumTp2Kfv36YeDAgWSBKPgMsPu7e/cuDA0N4evrS67t6dOnKC4u/itf4/8JsOc2ceJEODs7E7Ke7SsnT56EtLQ0AgICSKGa31EQP378GA4ODjA3N8fatWvJNk1NTairq4O9vT0ePHiAvXv3CtmwlJaWkuAOu93JkydhZGREFPAnTpyAqKhomypiwXEhPj4eYmJi0NDQwOzZs/Ho0SPcv38fdnZ2iIiIwJQpU3DkyBEEBwcjMjKSnL+gSvG/geD2M2fOhIyMDCQkJJCQkIDevXv/1XEE23/06NFQUFAgPqIzZswQqlofHBwMMTExiqA9ceIEioqKSGFAFiwRyypid+zYQX4zatQohIWFgcfj4ejRo5CUlMSSJUuovnv+/HnY2dmR9z3AVxiqqqoiPT2dBBsBvldtaGgoNDQ0oK+vDzs7O3h4eAi9935lN9HWO+T169cwMjKCrKwspkyZQv3+48ePiImJIQFX1uMW4FsSaWhoYPXq1WQ8q6+vx8yZM8EwDIYPH45NmzYRIo/H46GmpgYuLi7EboD162YDc+y9PX36NDIyMkh7jR8/HrKysvjw4QPWrFkDbW1tIYX2/Pnz0a1bN0RFRZH9VFRUQE9PD76+vhg8eDAAfqB89OjRMDc3R2xsLCZMmICUlBTIy8sTW5Jr167h4sWLQtkemzdvRnp6OuTk5KCmpgZjY2NiX9DS0oJv375h0qRJVDDwb1BdXU1ZcnC5XAQFBVGFLHk8Ht6/fw81NTWEh4dTnsRtEbHs/S4qKkKnTp0gIyNDWVn8zHOWfW+wWRp9+vQRKjRWVVWFwsJCaGpqwtDQEJ6enuBwOFi8eDHOnTuHdevWwc/PD+Hh4aTI5YMHD9C3b18oKCjAxcWFsvr50ZylsrIS8fHxsLCwgIGBAaytrcl6Yffu3ZCRkUH//v0BAFOmTCHBjLaejT+xj6ivr8emTZvg7+8Pe3v7NsejRYsWQU5OjgS72Gs5ePAgKbDJBlLy8/OhrKyMkpISTJgwAXZ2dtDT08OpU6eITUhJSQnCw8Ph7u5Ojnf79m1ikSAINmNrwYIF1L1hz69///5ISUlpV8G2ox3/C2gnYdvRjnb8NiZOnAgVFRUcOnSI8gk6c+YMPDw8YG5uDlNTUzg5OZGJGABqgXj48GGYmpoiICCAbH/nzh0MHz4cnTt3xv79+6kJSutJ0K5duxAWFobw8HBKXbhnzx4qZf3gwYO4efMmOBwOOBwOMjMzKSKWheBiBuBH8nft2oVPnz7hypUrFKE2d+5cMAyDgIAAytcpJyfnt60LBK/t5cuXVPrk48eP0aVLF2hqahLfpcbGRiQnJ+PIkSNtTghLSkqgrq4OX19f6loeP36MyMhIuLm5kYlpS0sLevfujUmTJpG/W5/Tly9fYGVlRSkD2O9TU1PRr18/nD59GrKyspQ6cerUqZg4caKQn5y0tDQhVmtqaqCjo4OEhARcvnwZPB4P9fX1iI+Px+LFi5GamoqAgAChifry5cshJiaGYcOG4ejRozh9+jRCQ0NhY2NDJqzfv3/HxIkToaioCFdXV2r75uZm3L17F1lZWcjNzcWiRYt+6s/5Mzx58gTS0tKQlpZG3759CdnDLlqmTZuG8PBwQkqzKgdZWVkMGTIEI0eOhKioKLm/ly5dgpubG+zt7QH8J60+IiIC3t7e1KIiNzf3twjY1t64glYUP7ve1guYvynSw+Vy8fnzZ5iYmODp06dCCt+GhgbMnj2bKjzGptpLSUlh8ODB6NWrF8TFxUll+IcPHyI9PR3GxsZCi+hly5ZBSUkJJiYmcHd3R1BQEAICAnD06FG8e/euzfTKBQsWQElJiSjIWaU7u9B5+/YtEhMTSYp3WwunhoYG7Ny5ExoaGggPDwcAsvB0c3Mj6pHy8nJ07twZKSkpv6WIBeh2v379OszNzSErKyukVqupqUFQUBBsbGyolOj/xsv1yJEjUFJS+iNCdM2aNVBTU8PNmzcB/FwhL9jHli1bBkVFRWzatImkBqekpJB7JlhwjyUXAX5aKpuZ0Hr/Fy5cgIyMDBISEoQKMv3/i4gF+PdERESEjL0sDh8+jPj4eAQEBCA4OFgo8NUW2HZ5+PAhLCwsEBUVhfPnz5Nx88OHD3B0dERKSgoUFRWpdN8HDx7AwsKC8v4F+MSWu7s7AH6QSXB8//btG86cOSM0LoeHh4NhGAwYMAALFiygAqxXrlxBZmYmdHR0YGVlBT8/v/8x4vVH7QH8R326adMmKuj5uxB89s6cOQNvb28cP34cT548QdeuXWFpaYlNmzYJpfBmZWWRvn327Fno6Oigc+fOxM9dsO3y8/Ph4uKC4cOHo0+fPmAYBrGxsZCVlaWyfKZPn46OHTtixowZOHfuHKqqqhAcHAxfX19yzaz9yb///ovjx4/DysqKOq/KykqcPXsWS5YswbFjx9DS0oITJ05g//79fxTMAyAUtLl16xaMjIzg6OgoZPnQv39/hIWFUZ/NmzcP6urqQtkdbJ9fv3491NXVYWtrC19fX3A4HFLQTlFREY2NjSgrK6OCCt++fcPcuXOFxvmLFy+ib9++RM3/8OFD9OrVC76+vkR5XVtbi6ioKKHg3ps3b3Dz5k1s374d4uLi5HzfvHmDjRs3IjQ0FJqamkhKSiJe42PHjoWSkhI0NDQgIyOD/Px8oYyts2fPYubMmVBQUBDyNW1N7P83+Pr1K8rLyxEdHU3NkQRx584d2NjYIDo6mnp3FBQUQFxcnAo21NbWwtzcHNLS0tixY8dPPWfz8/PJcy5orTFjxgwwDIPRo0cTVSvbhxsbG/HmzRtcvXqVpMwzDIOHDx+iubkZmzdvhpeXF0XEPnr0CLGxsRg9evQPMwda49WrV9i/fz9KS0tJn2PbZteuXZCRkUF2djaWLVuGiIgIbN26Fdu2bcPZs2dx8uRJLF26lFKm/459RFVVFRYuXIjBgwcLHVPwvJycnNC7d29qXXXlyhUMHToUixYtAofDwePHj6Grq0tlDjQ1NcHLywuGhobEmuDq1atYu3YtaY/S0lKcPHkSGzZsgIyMDFXwDuATsWJiYpg8eTJFtl68eBE6Ojrkvd6OdrTjfxbtJGw72tGOX4LH46GyshK2traUbxjwn4nPkydPcOzYMRQUFGDlypVkolFWVob169dj165dpIL34cOHYWZmRhGx169fx7x586hJwNq1azF06FBkZ2dTE53du3cjIiKC+DxFRETA0tKSTMbGjh0LPT09/PPPP2Qh/vHjR2RkZEBSUhJ79uxBXV0dEhISSEGv1qlAAH8RFBUVRQo3LFq0CL169SKpVgB+27pASUkJVVVV5Bj5+fmwtLSEnJwcIiMjic8h69slKiqKnj17wsHBAU5OTtSEKjs7GxkZGYTkWLRoEfT09CAmJoaEhAT4+fnB3d0dbm5ulOqlqakJtra2VFVf9rrr6+uJovDIkSNEnZOZmUlSCQ8fPgwHBweIiopSC5e6ujpER0cTlSzAT13u0KEDDAwMoKamhqSkJNTU1ODff/+FiYkJnJ2dYW9vD0dHR5iampJrs7CwaLNQxp49e6CrqwstLS1YWVkhNDSUXBtbRff169eYPXs2OnbsSHne/Why/jdKz+rqatjZ/X/sXXVYFd3edQgJ6RZQpLu7u0tCURDFbgURAcXuwA5EEBVbbLA7XhvF7kAFQVEJAYmzvj/OM/ue4aAC+r73u/ee9Tz3ua+HM2dm9szs2Xvt9VvLFI6OjggPD2eQa83NzYiPjydemk1NTQgNDUVWVhbWrVsHGRkZiImJkfJUFouF+vp6ZGdnQ09PD927d4erqytsbW0ZwTztUSFwEhJLly5FSEgI3N3dERcX12pKOI2WPru/SrWmwel9um7dOjIp7dWrF2xtbdGlSxeGX29JSQmcnZ2JmubLly/o3r07hIWFGaWYqampEBQUJOrhhw8fYt68eVxt8eLFCzx8+BBbt27F1KlTCTFkZ2cHCQkJ6Ovrw93dnaHeGT58OFFQ5+XlQVJSkvhSc06GOdurtYlsfX099u7dCyUlJejo6MDPzw8xMTEMb1WAPfmmQ0BaU5/SaBl+cvbsWbx9+xb379+Hvr4+/P39iSUBjVevXmH06NEdCrf6kZfrrwhRzm0aGxs7pJCPj4+HsLAwUlJSyOIRrdZtWQJ/6NAhDB8+HG5ubrhz5w5YLBaOHz8ORUVFhq0LwCbQTU1NfxgC9e9ETk4OBAUFkZSUhJs3b+LFixcIDAzEhAkTiGo6MTGRVHn8DLStAa06VVNTQ3BwMOk78/LyICAgwAhlqaqqgp2dHYSFhdGvXz+G7/O2bdvg7OyMEydOQEJCAqtXryZ/279/P0aNGsVQ+KWkpICPj4+Ecl66dAmCgoIMNT+9z+Li4g4Rou0B5z2Zk5PTZpXnj7Br1y7069ePyz4nLCwMRkZG2LZtW6teik1NTXjz5g3S0tIgKSnJ2J6+/6dMmYK4uDjiaa2hoYHOnTuTxV7O99KyZcugpqYGWVlZSEpKQklJiVjZFBYWQkREhCgxL168CDk5OXz48OGHZH5ycjI0NDRgbW0NFRUVuLm5cVXe0OBsu2XLlsHZ2ZnLmqKoqAimpqbo378/OY6qqio4ODhwLeT27t2b+OQ/f/4ce/bsgY+PDwIDA8miZHl5OcrKysBisTB16lRMmTIFNTU1CAwMxNixYyEmJsbw4X706BF8fHwI2Q2w/botLS1hYmLCuGevXLmCwYMHQ1xcHLq6utDU1GSQlKWlpVwLZXQlFeeY5OPHj7C0tISysjJevHiBq1evQkVFBSdPnsSLFy+wZs0a6OvrY/jw4YzFRrpNV69eDUdHR5SXl//xBQkWi4WzZ88iKCgIvr6+hPxvbaxz9+5d6OvrcxGx48ePZ5TH7927l4xpf+Y5y/luaGpq4hrHbd26lfRxnGQmTR4CbF/69evXM/xbm5ubsX37djg6OsLf35+QuC9fvmTYQrUVnMdYWFhIKmD27dsHaWlpUBQFe3t7WFlZQU1NDUZGRtDV1YW1tTVpx8GDB7fZPqKqqoqRC5Gbm4uZM2dixYoVpA/OycmBvb09goODcffuXdy8eRP+/v6M/rusrAxdu3Yl6mX6Gf/8+TO6desGOzs7HD9+nNEWixcvhqKiIu7fv4/v379j69atEBISQmJiIuMYZ86cCScnJ67+km4bHnjg4c+DR8LywAMPbcLTp0+hqKhI1KecL+u6ujou7zKAXaKqqqoKd3d36OnpwcnJCQUFBWCxWCgoKIC+vj7DmoBGU1MTJk2aBEVFRQwaNAghISEwMzPD3LlzyXfy8/NJKTcdXgOwA0mUlJRw4cIFLuVOQ0MDRo8eTbyUdHV1WyW46HMbOHAgnJycUFlZibq6OgQFBRGbAoBtOTBgwIBfWhccOnQInTp1wsiRI9Hc3Ix169ZBUVEROTk52L9/PwICAmBnZ4eFCxeCxWKhsrISCxcuRFRUFMaMGUOOceLEiVBQUMDEiRMRFRUFNTU1JCcnA2CvWk+fPh09e/bEkCFDsH79eq5wl/r6egwbNgy+vr4kuZbG3bt34e/vjytXrsDBwQH+/v4IDw9Hly5diKKjpKQEsbGxMDY2xtq1a1FTU4M7d+4gICCAJLgDwOrVqyEvL0+8Y6dMmQIREREyUSouLkZubi4SExOxaNEisl1cXBxCQkJ+GBTw8eNHPH/+nOF7mZ2dDVlZWaIo/vjxI+bNmwcxMTGSBk63QWsl+h1BZmYmevTogZSUFDg7OyM2NpZM3o4dOwZRUVHiPWpgYIDGxkYcOHAAMjIy0NTUZCTyAuzB9IsXLzBjxowfBvO0FykpKZCXl8e6deuwefNmotRurW1blteJiIgwkqZ/hMLCQpiZmWH+/PmIj48HRVGEyN+zZw8MDAzg5uZGvl9VVQU/Pz+4urqS83v37h1ERERIm3A+j66urhg2bBjXRKupqQk5OTlISkrCuHHjGMd68eJFSEtL4+bNmzh69ChycnIQHx9Prn9zczOsra2xbNkynDlzhis5fMaMGVxE0s/uF5qINTMzQ7du3RjesY2NjZgxYwbGjx9PPGTj4uJatSbgJGD37NmDnj17Msoc7969Cz09PQQHB3MRsTTaE27F6eV68uRJbN68GYcPH/4lIcrZFvQ1bItCnhM+Pj7g4+ODhoYGvL29oaamRiajZ86cgbi4OAYPHoyamhpkZWVBWVkZixYtYnju0SXbsrKyjInqt2/fMGTIENy5c+e3gvb+LuTl5UFBQQGqqqpQUVGBnp4eBAQEsGzZMkhLS0NcXJzLX7I1cIYjDRs2DJ07d8asWbNIv97c3EzUZyEhIQgODoarqyuMjY2xdetW2NjYICYmhiy21NbWQkNDAxRFMRYs6urqEBAQgL59+5Jrf/nyZSgoKKBHjx4A2N7knM9RdXU1Dh8+zDUm6AhR0hI/u6Yt/9bRElraq1ZMTAz29vZcz394eDhMTU2xYcOGH76rSktLMW3aNHTv3p2hfr5//z5ZHKXtWPz9/dGzZ0+IiooylP70fp8+fYrLly9j7ty5ZEzDqVKkcevWLUhKSjKqa+Li4oiSbc2aNcS7F/hXIBcnAfczT/dt27a1eq6FhYUwMDCAkpISgoKCEB4eDnNzc0IS0f3uwIED4e/vj4ULF8LT05PcV97e3rCysmKQdvv374e6ujquX7+Ouro6DB06FCIiImTRHGA/6wEBAfD392fcL/v27YObmxuEhYWJ/yWNT58+4caNG1i8eDGysrLIPfLXX39BQkICAwcOJLYgAHtRycjIiISA0edUXFwMPz8/KCsrIz09neF5C7A9ZFVUVEhfyHlvXrhwAd27dyc2VX8a9fX1KCwsZFT7ZGRkYPz48ejTpw/Onz9PFq5pIjY4OJhhTcB5/S9fvozU1NSfes623GbRokXw9fVFeHg49u7dS+7Xbdu2gY+PD+PGjcPFixcRHBwMMzMzsFgsPHjwgJTft2y35uZm7NixAy4uLrC2tmYskHbUaiQ1NRWOjo7YtGkTvn//joaGBhw6dAjKysqMsK5v377h0qVLEBAQwJEjRzB27FgICwszrKJ+tr+W+xQVFYWPjw8UFRVhbm5OKsV2794NFxcX8m60srJCQ0MD4uLiSNWHrq4uBg0aRH6vqakJ3759g5ubG1d1yIMHD5CYmEjCvQD2vfAjIpbz2f/TiwM88MADN3gkLA888NAmvHr1CiIiIoSg4CQNLl26hOzsbAa5sHHjRigrKxPSNj09HcLCwqSklk5olpaWxtixYxn7yszMhKamJlGXbtmyBZ07d0b37t0ZycqfPn3C27dvyYChrKwMjo6ORNX27t07nD9/HqNGjWJMYI4dO4Zt27b9kui6cuUKBAUFYWRkBG1tba7Srrq6ul9aF7i5uaGsrAxHjhxBly5dMH78eCxatIiUWgNsxV18fDysrKwYA2HOSeSRI0egrq5O2iQvLw/CwsJchFFLX9yXL1+iuLiYKNouXboEUVFRjBgxgpCrZWVlCAkJgYeHB5qbm/Hs2TOoq6uDj4+PK+To2bNn6NevHzQ0NCAuLg5zc3O4ubmRSWVTUxMGDBhAJp600pCeoH/79o1LpXP37l1MnDgR0tLSP1TltIbm5mbiF6enp0dSZ8vLy7FgwQJISkpyecx2BC2tC54/f46YmBgcOXIEmZmZsLKyQmxsLJlEnjx5EvPmzcOCBQvINXz16hWePHmCNWvWwNjYmKFG/hE6SiI9evSIBDYA//Jk5SxLBrgnCLR/b1vDQT5//ozk5GQoKSlxldLW1tZi9uzZMDIygr6+PkJCQmBjY0N80d68eUPaxs/PD97e3gxPNBaLhYiICAwZMoRrv0lJSVBUVERCQgJ69eoFDQ0NjBs3DiwWCx8+fICuri5u3rxJrsOIESPw5MkT0p5LliyBi4sLRERESF8BsPuTwMBALF68uE3nz3mueXl50NLSQs+ePcnnc+fOhYyMDE6dOoXTp09jw4YNEBMTQ0xMDJfiir4OEydOhJycHAQEBGBrawuKoggxQ0+Ye/bsSawTaCxatKjDXq50SfGvCNHz588T38L2KOQ5J3ujRo1Cp06dyAIJ3U9ylliePn0aFEWhX79+kJSUZCx8cbYVTcTKy8vDyckJc+fOhbu7OxwdHRmE/f83vHv3DleuXMGFCxfw/v17zJ49GwICAuDj4yOE2c+Om/OZpX0pr1+/Tj5raGgg5NzZs2cxcuRImJubw93dnfRhW7duhZWVFfr160feKceOHUO3bt3g7++P06dPY/fu3fDx8YGhoSHZ7ty5c/jy5Qs2bdoELS0tbN68GVJSUgzl7KlTp9CnTx9CXLUXnO+vkydPIi8v74cE4I/apaUKr637o/H9+3eMHz8empqamD9/Ple5u6urKwnfA0DUbePHjyfPT0VFBaZNmwY9PT3MnDmTyw93165dDBJ1+PDhEBER4bJcablgumHDBnh4eJD+kv69jx8/Ql1dnbS7v78/1NXVybUbO3YsUS7v2rWL8V7mrABoaRnSlnfCvXv3oK6uDmdnZ/KbnMcGsC2jOP226XZasWIFQkNDSfscPnwYiYmJmDVrFtm2oqICHh4esLS0RExMDKZOnQpnZ2eG7VXL+8bV1RVOTk6MMVVrz9WePXswa9YszJs3D6NGjUKXLl0QFhZGyCsXFxdER0dzbffmzRsEBweDoihERUVx/X58fDy0tbW5xjtr1qyBhIQEl3fs34Hm5mYkJydDXl4e48aNg4+PD0xMTDB37lyicrx79y6MjIxgb29P1MytEXE/85xtqZqWlJTEjBkzYGlpCVtbW8yYMYPcrzt37oSioiIMDQ1hbW2NhoYG0kZ5eXlQVlZmLKzR929zczOys7MxYsSI3yYJZ86cCTk5OZw6dYoQ0gD7ft2/fz9ERUUZlRTFxcWYNGkSREVFISUlRdrhZ8fR0vt86tSpcHR0JJUO5eXlmDJlCszMzLB8+XLy3WvXruHevXtobm7Gw4cPYW1tTRYTtm/fDg0NDcY8qLGxEXFxcUScwGKxcObMGVAUBTExMa7gQ5qIFRUV5Rpf/a5AgQceeGg7eCQsDzzw8EvQL+aEhASoqqoyfFUbGhrg7e1NXub0oCQhIYGEGuTl5TFKVGtqalBaWorm5mb89ddfjIEri8XCtGnTCIl34MABSElJYf78+Rg/fjxkZGSIIpZzANTc3IyKigo4ODhg2rRp2LlzJ3r37g0nJyfY2trCyMiIEDWc+NUk/datW5gyZQoWLlzYqo/oz6wLVFVVYWdnR44zPz8foqKioCiKTIbo46mrq4Oenh4xzm85uMvOzoaTkxMA9qRBXFycoTyiS7o4z2/q1KnQ19dH9+7d0b17d0LYnjlzBt27d4epqSl0dHRgZWVFgqrogZ+bmxusra0REhLClfr69etXvHnzBgcPHsTdu3fJsdKl1l5eXsjPz8e1a9cYfqANDQ1YtmwZUUPT7b9kyRKYmppyeai1RMs24Qwos7e3h7a2NoOIpcM+cnNzf/q7P0NeXh569+6NoqIixsQ+OjqaJOiuX78etra2hIjlPM4PHz7g69evZBL/8eNHLF26FMbGxoxS1YkTJ5LJYnsHwi3b5dy5c1BRUQHAJmBbeuht3LiRSyVGT7bb4hPIuc9NmzZBSkoKhoaGmD9/PuPYa2trcenSJUyYMAETJkzAihUr0NjYiDlz5iAyMpL0Izt27IC9vT1RitO/7+LiQspXaRw9epSxGLF7924ICwszyhdNTU0RFhYGRUVFeHh4oHv37lBQUMDVq1cBsFVPxsbGsLOzI4tEb968aTU5vK2ora3F3r17oaWlBTc3NzQ3NyMsLIzLf+3EiRMQFRXF0KFDyf1Et9muXbsgISGBLl26IC8vD4cOHQJFUQxlVlFREaSlpbnapSNerhs2bGBUN/yIEO3UqROmTJlCFPIREREdUsgD7OqCvn37AmD37WJiYkRRVF1djdLSUrBYLFy9ehV9+/Zl3BM/wsOHD+Hk5AQ3NzcEBwf/bd6jfwfu378POzs7dOrUCcLCwti8eTP5269CzWivbHNzcwBsMmXp0qXQ09ODvLw8WUyoqKhA//79YWdnh7lz55J33o4dOwgRS5O/Z8+ehYWFBbp37w5ra2s4OzvD2toaALtM2dzcnJAWoaGhJF2bRl1dHQIDAxEeHv7b7T9p0iRoa2vD3Nwcpqam0NbW5irvbq1d6BL+toThcR7jzZs38fTpU2IbVF9fjyFDhsDGxgaLFy/m8u2kt01MTISCggJRdAoLC5Pvl5eXY/r06TA0NCSLEc3Nzfjw4QMoikJoaChD+TxixAiIiYlh165dKCkpQXh4OHleaGJs7dq1sLCwQO/evQmxxWKxUFVVBVVVVeTl5SEsLAw6OjoMf0662uby5ctcFQApKSkMBTTAXgxvzzvh9u3bsLW1xdChQ394naqqqkg5OQ0/Pz/069ePjOFUVVVBURRRWNL4+PEj5s6dC19fX0RERGDixImkbzlx4gQOHTrEIItPnDgBPz8/+Pr6clUH0PfLy5cvIS8vj6ysLABs8v3u3bsIDQ2Fubk57OzsMGLECEY/yYmXL1+id+/ekJKS4vLFXbVqFRwcHBgVWd++fcOCBQt+Odb5U8jOzkaPHj3IsZ06dQoURcHAwADTp08n1+LWrVuIjo5u0zP7M8/ZmzdvYuTIkYQ0bGpqwvjx42FnZ4fp06eT+/XBgwcoLCwkHrBLly7Fhw8fwGKxsGfPHoiKipL5A/CvMTfnc96R/oXFYuHNmzewsrJiKEQ5f4/FYmH//v2gKIrhnb1y5UpQFIUuXbow/Nl/FN5Ff56ZmQkBAQEYGhrCz8+PYUlUWlqKUaNGwdXVlcuqKDs7G4GBgejfvz/psz99+oTFixdDWVkZnp6emDBhAhwcHKCnp8e18Dhnzhxi/9CaP3pmZibc3Nx4xCsPPPybwCNheeCBhzbjzp07GDhwICQkJJCYmIikpCS4u7vD0NCQDPbpUtnhw4dj7dq1rQ74N2zYQHy9OAcO9KSpvr4er169QnFxMfT19bFkyRIA7JJ7KSkpiIqKMlR9e/bsISvpycnJMDc3h5CQEFJTUwmxNWDAAIwZM+a326AlQfMz6wJPT08uM/6TJ09CSkoKgYGB+PTpE2MANGzYMPTq1YvxGe2VtnXrVvTp0wcFBQWM9gTYZEZSUhIjLGzevHmQlZXF3r17ceLECSQkJEBSUpIkGd+/fx979+7F9OnTsWnTplYJ5nv37sHNzQ3+/v5coUAA2zuSJpJmzZpFyKIpU6ZASkoKQkJCDHLsy5cvcHd3x6JFi7h+qzU7ix9h8+bNZGLTkojV0dEhRGxpaSlyc3M7XNL/4MEDSEpKgqIoGBkZYejQoUTpXFZWBk9PTxw5cgQNDQ1YuXIlHB0dERgYSCYa8+fPh4uLC0xMTNC3b19yLT99+oRly5aRwBo/Pz+oqKh06Dg5FZX0xOft27cICAjA/PnzISYmxlB73rhxA5GRkYwk75UrV0JSUrJNCtiW5ar37t3D3bt3kZycDBsbG67goZZITU2FrKwsDh06RK5TfX090tPTYWlpCW1tbcTGxsLGxoZYOXAiOzsbLi4uALgXIyorK3Hx4kVoa2uDj48P+/fvR01NDe7duwdJSUmSPA6wleX0IgTtkUircgD2RLOl/+GPwLmQQ5d6v3jxAlZWVlylgwAwZswYUBSFyMhIxj7CwsLQuXNn5OXlYc+ePYxr9/XrV6Kc4lT1cuJXXq6caGxsxPjx45GSkgLgx4QowJ5YNzY2dlghz3nuo0ePxsKFC3H48GFGP9bc3IxNmzZhxYoVqK+vR2VlJVRVVRkEHyfo86InlywWi9GW/84Qrl+BUxFZWFiI4cOHY9euXZg5cyZj0epnk2N60WTChAkkHEtXVxdRUVFYsWIFZs6cCQEBAfKMlZWVYdy4cXBxcWEoDGkiNiYmhqjgALbX8qdPn3D06FHo6+tDQ0MDUlJSDMLwzp07cHZ2hqqqKrKzs5Geng5vb2+GcrajROy6desgJydH1JKbN28GRVE4duwY+c6PSudlZWXbpJzlxKRJk6CsrIyuXbvCw8ODLDzSRKytrS3S09O5+oTDhw9DUVERt2/fZpAfMjIy5DoWFxcjPj6eYekAsIkvCQkJREREMPzix40bB4qiYGhoCH19fa4Fs7q6OmzcuBE2NjaIiIggx1RZWQkjIyN06tSJKERXrlxJFmg3bNgAMzMzCAoKIjs7m/ze169f4e/vz/BRp60KWmYA/AqFhYWwsbHhUkK3vJerqqpw8uRJ+Pr6wtjYGA0NDaisrCS++La2ttDX12+TLQ4tDujRowcUFBRgZmZGvMqPHj0Kf39/+Pv7kxJ6GmfPnkVWVhbGjBnDdb/W1NTgwYMHGDhwIGRlZSEtLU0yDVrizZs38PPzg6KiIlG3V1VVwcPDA4GBge1e+P9TaGpqwvr168lizL59+yAlJYV169Zh1KhRkJaWxsyZM7kUub9Sd3J6znL273v37oWRkRE0NTUZhPS3b98QHx8POzs7hiIW+JfF1saNG4k9Q1NTE3bv3g0RERHGQvWfWlQrLi5G165dGcGRNOrr6wkxfe7cOTQ2NhJ16YsXL3Dx4kUkJSVBXFwcu3btIsf7I2RkZEBcXByzZs0CRVEQERFheHED7DEZRVEMm6GvX79izJgx6Nq1K8PSCWA/5xcuXEBwcDDCwsLQr18/ch2+f//OOJ7JkyeDj48P69at4+q7WopYeOCBh38WPBKWBx54aBeKi4uxevVqWFtbIzAwEMOHDycD2ISEBIiLi6OqqooEVAkICDDKSSsrK+Hp6Ym0tDSuVOMFCxYwSu/y8/Ohr69PyIArV66gV69eDCuB9+/fQ0BAgCSUA+xybM6yKQDw9PTkUqX9SXBaF2hpaTEUAunp6Thy5Aj595EjRyAiIoIhQ4YQO4W6ujpYWFjAx8eHlHYmJCQgICCAECAiIiKgKIoRdFRbWwsXFxcS8tHc3Ixv377BxcWFq6x64cKFEBYWZkxGOK9BUVERzp07h/LycuJ1d/36daIwoydkHh4eSElJgZWVFfz9/TFy5Ejw8/MTK4Fnz54hJCQE6urqKCkpQVNTE0pLS+Hn5wdbW1su5XN78OHDB0hLS8PGxobhOQewk7+VlJTg6OhIvC1pdISUKSkpweTJk+Hm5gY3NzdkZ2dDU1MTwcHBSEpKQs+ePQmh0dDQgPnz5xMP08mTJ0NeXh65ubnIzc2Fo6MjtLS0iALm8+fPyMvLQ0xMDAYNGsRFVrUFe/fuRWhoKGpraxEfHw8ZGRmUlZWhsrIS7u7uoCgK06ZNI9+vra0l/oP0dX/58iUcHR0ZassfgfNe+fLlCxobG8lxf/jwAQkJCbCxscHs2bPJ96ZMmUJ8Ym/cuAE9PT1GKT39m9+/f8fVq1cxfvx4DB48GKmpqeSacbbJ5s2biRVEy8WIffv2YdSoUaAoimH3UV9fD01NTTg5OZFAI4A9eT527BhGjx6NgoICsp8ZM2bAy8sLFhYW2Llz50/vUc6yzYKCAmzatIkoWtatWwdVVVUUFBQwtlm0aBF69uzJCPi7cOECJCUlYWdnh/3793N5q2ZlZWHs2LEMtcyJEyc65OVK/3dbCVH6s/v377dZIX/nzh1ybpzP3qxZs6CiosIgzwG2WtPHx4c8TzU1NVBTU/spqU9v01JV9v9Z2cP5DD169AhXr14l6t+amhqkpKRAXFycET40b948ht0AZyr358+fsWbNGri5uWH9+vXkPnj27Bns7e0Z78FTp04RH/X09HTyOU3ExsbGciXXA0C/fv1AURQsLS25zuXp06cYMGAADA0N4ebmxlBat6fPbXnNEhMTiWUFXUlDL0hwKlxbK51vi3Kzpedljx49cPHiReTm5mLQoEHo3r07UcrRXurq6urYvn0743e2b98OY2NjfP36lXG+kydPhrS0NMrKytDc3EwWXD9+/Ijm5mby3Zs3b0JUVJSLiD169Cj27dtHzu/kyZO4ePEiecfW1dUhOzsb1tbWCA8PJ896QkIC7O3t0djYiClTphBPYIBd5uzp6Qlra2vSB7969arVCoCzZ8+2uvD6I3De19evX4erq+tPy+2vX7+O6Oho9OnTB42Njdi0aROio6NJGzx79gwmJibw9fVlBDe1fD9mZWVBVlYWt27dwps3b/Dy5UvY2tpCS0uLkHr5+fkkiJATMTExoCgK5ubmjH615b145cqVHxKwNN68eQN/f38ICQlBU1MTw4cPh6WlJXk//hN9Umv7ePPmDT58+IDi4mKYmppi6dKlANiL1nJycujevTvpa9p6jLTnbMv+vby8HNHR0ZCQkMCMGTMY90RtbS0SExOhoaFBFgB27twJFRWVVvucxsZGshAZExPTjlb4NV69egU5OTny/uG8769cuYL09HTG/fDhwweGwKG0tBRjx46FuLg4o69ZsmQJqSgA2P20sLAwnJ2dUVlZiZs3b4Kfnx8xMTEM3+YnT55AW1ubVOrQePbsGZKTkyEsLMzIN+AEZxuvWrUK0dHRiIyMJFkRAHvhm7YKauvCMg888PD3g0fC8sDD/zhoH8+2fI8TLX2uXr9+jQkTJpDBfUNDA0aOHAlRUVFcv34dZWVlePHiBXx9fWFlZcUY+CQlJUFeXh5btmxhhBWcPXsWqqqqWLNmDcrKyhAQEIChQ4cyStkBdnmxiooKAgMDGb9bWVmJ27dvw9/fH0ZGRn+7Ooq2Lpg/fz5jIuru7g45OTmcPn2afE5bExgaGiI8PByhoaEwNjbGzJkzQVEUfH19ISYmxhjUHThwAF26dEF8fDxOnTqFkydPQlVVFWJiYmQgy2Kx8PnzZ+jo6JBBJmc5XGhoKAICAgAwJzSpqanQ19eHuLg4XFxcMG3aNDIQvX79Onx9fWFgYABdXV3o6uqivr4eBw4cgIKCAkREREi5H6evm4eHB0RFRWFiYgILCwvY2Ni0m2zkvO/oe+7WrVvQ1dWFvb094z6srKyEi4sLKIriSk1vDzgHtu/evcOMGTNgamqKRYsWoaGhAatWrUJUVBQoioKKigpR4zU1NYHFYuHo0aMwNTUl5Yv5+fkQExODgYEBlJWViUqnpfqgvffnnTt3SGmhpKQkg4x6//49unfvDmdnZ0yZMgVr1qyBu7s7UR3RqKurw/v379vVJosWLYK/vz/MzMyQkpJCFE9lZWWYMGECrKysEBERgYCAACgoKJBrffz4cXTt2pVrgQT48QSwZZs8evQInTt3bnUxwsfHB6GhobCwsICpqSlRCdPl84aGhujVqxd0dXWxfPlyXLlyhSQ207+1aNEiKCoqYurUqejfvz/4+Pgwe/bsVicvnATsunXrwM/Pj9mzZ5OyylevXqF3795wdXUlXqqfP39GYGAgQ4kGsK/XmjVrYGlpCWFhYYYCtKqqCoGBgcSqBGD3mW31cv2RyuVXhOiPCNBfKeQ593f06FGcPHmSofLx8fGBlJQUrl69infv3uHVq1dc7wUWiwU7Ozs4Ojoyypc575Pr168jPDy8Tffv/wdwHvvkyZOhr68PJSUlWFlZYcSIESgrK8OnT5+QlpYGISEhjB07Fl5eXtDR0SHP0KpVqyAsLMylWucke+rr6+Hv7w9PT09yLSZMmABPT094e3tDXl4eampqjKDLnTt3wtbWFoGBgWTRhCYLd+/ejfXr18PMzAxOTk6teqnX1NQw+vTfIWABICAgAJMnT8bJkycZCxIsFgsLFixgeCgCbMKDM8iurcjJycH48eMZC0cPHjzAsGHDoKqqSqw56urqGFYONLKzsyEmJkbelbRlwdu3b6GoqMhY8Jw9ezYcHR1hZ2eHDRs2EJKSJmIjIyO5Fg8B9rMuISEBdXV1yMvLk0Xt+vp6ZGdnw9bWFhEREaiqqiLe7OPHj4eCggKGDBkCV1dX8lvHjx+Hj48Punbtih49esDMzAz29vYdWgRsDevXr8eZM2d+GFjGiZcvX5JrP336dFhaWmL06NGEoHry5AmMjY3h5+fHCA/jRHJyMvFjpX+rubkZRkZGxC4IYJNrLfvBpqYmjB07FoKCglw+vPTf24PXr1+jf//+oCgKhYWFjIDGvxuc51ZXV8fV/ufOnYOOjg4Ze1y/fh2xsbFIT0/v0DVvGZZJ4/Pnz+jbty/s7Oywfv16xt+/ffuGlStXkv2lpaUhICDgp4rMTZs2wd3dvUNKzZ9tk5aWBkFBQUZwW319PXx9fTFgwABy7Whf265du8LR0RF79+5FfX09Pn36hHHjxkFISAhpaWnw8vKCvr4+ObeVK1dCVFSULN6MGjUKNTU1uHTpEvj5+REcHIxt27bhwoULCAgIgImJCZqamvD+/Xu8f/+e3DMlJSVISkqCtrY2Y+GspTqe9smfPXs2lixZAmFhYbL4ArAXw4WEhJCent6mZ5MHHnj4+8EjYXng4X8cnCv8Bw8eZKgxfoaWJbhCQkIwMDBg+BHeu3cPffr0QefOnaGmpgZzc3M4OjpylTCpqqq2uhr+/v17DB8+HPLy8ujWrRvMzc1/qCy4cuUKFBUVERISQkjHffv2wdnZGQEBAX9sktEecIZL+Pr6QllZGadOnSIDrGPHjkFBQQEqKiq4cOECOTZzc3NQFIUpU6YAYKoF9+zZg+7du0NVVRWWlpawt7eHpqYm+vbty2jDyMhIGBsbk0khTVaOGjWKEXoAsMsnlZSUcPLkSdTX1yMqKgrKysoYPXo0IRgfPnyIHTt2YPny5eS3zp49S1S/ISEhXJYCFRUVyM3Nxdq1axmqnrZOSjgH0XPnzkVaWhrxIywsLISmpibDc62hoQEDBgxAUVHRHymvGjlyJNauXYvXr19jxowZ0NLSYlgpbN++nUFY0Pjrr7+IZ2dBQQHk5OSwdu1aXLt2DcrKylzlekD7lTJ0Gw4YMAAURcHb25sRyASwVTBxcXGEqOuoSo0TtJ1AZmYmFi5cCHt7e7i4uBCF1sePH7Fs2TL06tUL0dHRDH9OOnmYs83oYz1w4ECrE+HWsGfPHoiIiGDSpEk4e/Yszpw5A29vb5iYmKCxsRFPnjyBpaUljIyMEBQUBAsLC9y9excfP37Eq1evkJaWBm9vb1AUhUmTJmHGjBno3Lkztm/fjpkzZzImZhs2bABFUZg1axaDiOW83hkZGRASEoKEhARkZWXRvXt3rFu3jpSb9+vXj5DALVXynN5xzc3NGDFiBLp374709HQ8f/4c169fh5+fH8zMzMg2WVlZbfJypSiKQS4dP368TYSon58fgxC9f/9+mxXynB56iYmJkJGRQbdu3dCtWzdyLFVVVbC1tYWamhqkpaVhZ2dHAtvo9nz8+DFOnDgBISEhDBkyBJWVlQxrhdraWuKX+f9Z+doalixZAgUFBZw+fRoAW2kqJydHrsunT5+wZs0aODg4MJ6hyspKJCYmcgWV0aitrcW2bdvg6urKeFdu374dUlJSJGm+rKwMAwYMgJWVFSO4cOPGjRg0aFCrfWdzczOOHDkCIyMjODs7M/526NAhhl92e67HX3/9RWwQhg0bRsjVDRs2wM7ODiIiIowFAnoRg9NSYdeuXaAoqs2BgjSKi4sREBAAcXFxrqTwBw8eYPjw4VBTU2P49ALA/v37ybX69u0bLC0t4ePjw/CMffbsGTQ0NMj31q9fDxkZGaxevRpBQUGwtLTE2LFjyaLzzZs3ISEhAQ8PD8aiwsOHD2FpaYkbN27gypUrSE1NBUVRZBGnvr4emZmZUFNTI+OFESNGQFZWFg8fPsSpU6dgaGjIOP6XL1/iwoULWLduHU6ePNnu9zInOO+VFStWQEFBAUVFRT+9B+jFypZYunQpbG1tMXLkSAYRa2ZmBktLS64yboCtZqU9iwGQ/mnXrl0Mj3h6f2VlZXj//j3Ky8vJNn369IGkpCR5Hml0pF95/vw5EhISSJv+033T7Nmz4erqCn9/f4YVVEFBAbS1tZGZmYkHDx4gODiYEcrUnnFxy7HO3r178eDBA9Km5eXl6N27NxwcHAgR29qC8+DBg0kFG+dYoLGxEUeOHCHBYa3ttz3HmJOTg8mTJ2PcuHG4desWGhoa8OnTJwwePBgURWHEiBEYPnw43N3dGUFvM2fOhKysLLKzs3Ho0CEEBgbC1NSUeNvTAbCWlpbo1asXGYd++fIFI0aMINVFmzdvhra2NoYPH45v374RIpaiKAwcOBBxcXFoamrC9OnTYWxsjB49ekBPTw/79u1DY2MjSktLMWnSJOjp6bVqz3Pt2jXo6uri4sWLAP5lLcRZSQOwx7POzs7/ce9LHnj4bwWPhOWBh/9hXLlyBZqamrh8+TJJ5W6LqqjlS/zixYsICQmBiIgIUeNxfuf06dM4ePAgzp07x1XCNG/ePLi5uTHUmpzbfvnyBTdu3MDBgwfJQHH+/PmMZGIaf/31F2RlZUmJG8AuNWytLPbvAOdxHz16FHp6eoxACC8vLy4i9sCBAwxz/Pr6eowZM4aUVXOmTnOa8798+RKvXr0Ci8XCpUuXoKGhgT59+hAi9saNG7CyskJgYCCZmLBYLJiammLkyJHkNx88eAB7e3vij0WXM4eEhEBXVxfx8fFE5cN5fk1NTfj8+TPKysqwZ88eODg4ICAg4Jferm0d7HMOoouLiwmZv2TJEqJwLCwshK6uLrS1tTFx4kQ4OjrCxsamw8noLf36lJSUiAKntLQUM2bMgK6uLtLS0hjH2drkoKysDI2NjfD19SUp8o2NjXBzc4O8vDyCgoLadWwtj5He54YNG7Bz50506dIFERERZPLKObFuampiEAQdfQ727dsHfX193LhxAwB7EUFISAhGRkawtbXF/fv3AXCrNOj9ff/+HRoaGsRig0ZtbS2CgoIwffr0Nh1HU1MTtm/fDhUVFaioqMDCwoIRyNTU1IRHjx7By8sLFEUxvC5p1NTU4Nq1a+Q40tLSwMfHBxkZGaJapbFhwwaiiKW9Vun2zcjIgKioKLS0tHD+/HmUl5djxIgR0NfXx+LFi1FfX49v377hwoULmDdvHjIyMlq1WeC8Z+Pi4mBpaQk+Pj7Y2trC09OTcW5t9XK9ceMG2Vd7CFE7Ozuyv+Tk5DYr5HV0dMgCzatXr2BiYoLbt2/j1q1bWLp0Kfj5+cmzALBJ4by8PGzatAkCAgLIzc3FpEmTiPfo9+/fsXjxYnTu3Bk9e/bEnj178PbtW+zZswc+Pj4MMvs/wdOuubkZNTU1CAoKIhPkI0eOQFxcnJTaf//+HfX19cTjtmXVx89UTG/fvkVGRgbGjx/PWGxZuHAhg8SnvxsUFISuXbuSEmXONszNzUVqaiqmTp1K3infv3/HsWPHYGJiAmtra9y+fRve3t7w8vJq98SexWLhw4cPUFJSQr9+/dC/f3+IioqSZ/X58+dwdnaGiYkJCgoKiCVPQEAArK2tGdf9/PnzOHHiRJv22RJnzpxBaGgoZGVliX88jYcPH6J3794IDQ0l2z948ABdunRBbGwsOdZDhw7B2toa9vb2uHTpEk6cOIGgoCBivXPt2jWMHTsWBw4cIL89f/582NraYsyYMYSIvXLlCkP1V1dXh1u3bmHChAlku+rqakyfPp0QsYMHD8a4ceOQn5+P+vp63LlzByIiIuTYLl68CDk5OXz48IGreokTv7s4XVRUhOTk5DbZ2tDXgbZ/4LRrWbJkCezs7DBq1Ci8ffsWAHuMQgd3AezxJL3od/bsWXTr1o3cwzT2798PAwMDUpUAsPtKZ2dndO/eHQEBAYzKgn79+kFKSopUcnE+C/TCb3vR8j34d2P16tXo2rUrpkyZgujoaPDz85MydhaLhaioKKipqUFZWZnhf96eZ5fzu8nJyejRowe6desGExMTDBs2jFTFlJeXIyoqCs7OzliyZAnZ7tq1a6QP2759OyiK4vLqpUnc1jxb24tJkyZBXl4egwYNgpWVFWxsbLB27VryLGRlZSEgIABhYWGIj49HY2MjWCwWSktLYWlpybA1AthEpp6eHmNBoKamhtFPX7x4kavaJycnB9ra2hg6dCjq6uqINUF8fDxKSkowZ84cyMrKYseOHTh06BDxIqYzCF6/fo2UlBRISUlxPWOnT5+Gnp4eAPZ9z+krXlVVxQgga81HmwceePj3gEfC8sDD/zCuX7+OuLg4KCoqQlpamkwGfmXMTyMrK4sk6l67dg1OTk5QVVUlg+cfkT3Nzc1k0D9u3Dg4OTmR3+YkI/Lz8/H69WvG8TQ1NWHr1q0QFBRs1bR/xowZoCgKHh4e/zbj+cOHD2Po0KFITU0FwJw4e3l5QUVFBadPn0ZDQ8MPj7GhoQFz584FRVGMEDIADD8umgS8cOECNDQ00KtXL0KE79u3DxYWFlBSUoK/vz/U1dXRqVMnoqKhS1e3b9+Oz58/48KFC1BUVCSEjq+vL+Tk5BATE8PwyHr16hVKSkqIT1ZDQwNyc3Ph4OCA4OBgMmkZMmQIUTd2dNA3YcIEGBsbY/DgwbC2tgYfHx/mzJlDiNiysjL07t0bgYGBiIqK+iPJ6MuXL0dycjIhW+ljLykpwYwZM2BgYMDleXb//n1cvXqVhG8B7HZSUVEhAQ6fPn1Cr169cOLEid8urysrK0NdXR3xR7x27RrxFuS09Gipmvudwff58+fJxPXw4cOQlZVFRkYGDhw4ADk5OTg5Of1Q4Us/75cvX4aysjIcHR2xceNGbNmyBV5eXh2yCykvL8fjx4/x5s0boo6kFXk0YUIHfNGLA60p4un9Llq0CBRFYcGCBVztlJ2dDYqiGN5stAI2KCiIy286Pj6eELEt08Bb7r/lZywWCyUlJTh79ixevHjBtYjUFi9Xzj6H9ldsCyF66dIlsr+ZM2e2SyHP2Y6xsbEYO3Ys+f3q6mqsXr0a/Pz8RLFHo7S0FLNnz4aIiAgkJSUZC4Ffv37Fjh07oKqqSjyxTUxMEBkZ+W+pbmgvWnve3NzcUFRUhOPHjzMmzN+/f0dmZibOnz/PqCjJysrCX3/91ab90YsEwL9saHJycmBiYkIWaOjr+9dff0FSUhI9evRgvBMmTZpEiKrIyEh06dKFqMO/f/+O8+fPw9ramtid/I7v5e3btyErKwtBQUHST9K/c/fuXTg6OkJPTw9ycnKwtraGg4NDh657S39KzkDDa9euISwsDGZmZkRNRuPly5dk27S0NEycOBHdu3eHoKAgQkJC8PDhQwBsMtDDwwMSEhIwMDAgCyfHjh2DtrY2lJWVGQp7gE3E2tnZYdy4cVwVSNOmTYOnpydMTU3h6urKUBrTRKyAgACGDBlC2qOhoQFNTU2oqKgg37116xYkJSUZHpRxcXEMm6PfAYvFwuXLl0FRFISEhJCbm/vD73KqHc+dOwcZGRkICQlxLXrNmDEDUlJSGDt2LJ4/f864r5KSkmBsbIxly5ahpqaGeJHb2dlhzpw5qKurw6tXrxAYGIiAgACy7dGjRyEsLIwVK1bgzp07ZJxIj0+am5sRGxsLiqIYHrQLFixAUlISIX1/hpb32N+NlmOItWvXEqK/uroaq1atAh8fH1GNs1gs/PXXX4yqq44uyC5YsADKyspk4WLs2LGQkpJCREQEWYwtLy+Hl5cXRowYARaLhbS0NFhbWyMnJwdNTU349u0bBgwYAFFRUezZswevX7/G06dP4e/vD0tLy9/u1zMyMqCmpkZCSA8fPgyKomBqaoply5aRa9TyWtECA11dXWJTxCkSMTIyIirill7rxcXFEBERwfTp07k8kTds2AB+fn6MHDkSFRUVOHv2LPj4+DBkyBBYWlpyhV2mpqZCQkKCeMU+efIEa9euJe2Sk5ODtWvX4s6dO/D398eqVasY7xOA7TUfHR1N+inOyhseeODh3wseCcsDD//joAejmpqajMFnay/qlinEYmJijBLi69evw93dHdra2oSI/RUpVlBQAIqiuAIvKioqEBERwVjFvXjxIiGY9u7dC1FRUYwYMYKxXUZGBmJiYhAWFvaPEK8tPXW/fPkCCwsLCAsLM9S6nIM4X19f8PHxMewDjhw5gl27djEmMbW1tZg3bx74+fmxdOlSlJeXIyQkBH379iXfefr0KUMxoqGhgfDwcDIQfv/+PWbOnImkpCRMmzYN06ZNAz8/P7Kyshj7AdjloKNGjSID8/j4eBJowUnM0BNwPz8/Es7T2NiIrVu3wtHRERoaGnB3d4eKispvqY8PHjwICQkJ3Lx5k7QxTZTNnTuXMdnkVPn8zj4/fvyIkJAQUBSFAQMGAGAPyunzLykpwaxZsyAtLU3aMDU1FaamplBQUICnpyciIiIAsO8NuvR0y5YtcHd3h4uLyw/91H4Gzmdv3rx58PDwgKmpKXx9fUlZemFhIcTExNCzZ08cOHAAwcHB0NXV/aN+ah8/fsS3b9/g6uqKOXPmAGC3t6WlJVRUVDB48OBf/vbr16/h6ekJIyMjmJubo1evXu0mVjjDvQC2v6mnpycsLCwYSpHHjx/D0tISBgYG5H5paaWyadMmxv3Nz8/P8JulYWNjQxZWXr58CRsbG5iamoKiKPj4+HApn+Lj42FiYoK0tLSfBr9w4keLMpz/3dZwK4CtLGsrIcp5XI8ePYKtrW2bFPKc+Pr1KxITE9GlSxeGJyPnfjt37swVkpOZmQmKoiAqKspV/g2wS/ELCwtx/PhxvH379h/1W+woONtzx44dZJLds2dP6OrqQlJSkuEN/O7dO7i7u2PmzJlEGZycnEyUwb/Cj56d+/fvQ1xcHAkJCQxLjfPnzyMoKAgrVqwg99f69evRrVs3EgS2Y8cOUBQFfn5+YnfBYrHw/ft33L59+7eqTJqamnDr1i3o6OhARUUFAwYM4Co5f//+PW7cuIGsrCxcunSpQ+QR57OzYMECuLu7w9TUFH379iXWKNeuXUN4eDjMzMxw6dIlru3S09MhJSWFy5cv4+7du2QRKjw8nLHw9uDBA7x7947RLomJiZCVlcXw4cMZZCrAfp9paGiQEM3m5masXr0aSkpKSE5ORlxcHCiKQnp6OuN+qq6uRkJCAhwdHcFisZCdnQ0PDw9yfem+6OPHj1BXVycKRXox9neem9b6r5UrV5LS7taqYTgJ2KdPn5IFLC0tLcycOZMs6gBsiwcNDQ1069aNtAuLxcLChQshJyeHS5cuMRYbXr58iSlTpkBJSQlSUlLQ1dWFlZUVaYO6ujoMHjyYeFyXl5dDVVWV0SfSGDp0KLkn6KyCrVu3MoKZ6PP5UZts2rQJSUlJjDHfnwbn/vbu3YutW7fCzs4O27ZtI5/X1dVh9erVEBAQIO9qTnSU5CwuLoavry95z9Jq/v79+8PAwAARERHkfvvy5Quam5uJjdHZs2cZVhCfPn3ChAkTICQkBGVlZejp6XV4oYXzu/X19Vi6dCnxUd27dy+kpKSwfPly9OrVC127diVEfmuhlSwWCzY2NkQFD/xrjDlw4EAMGjToh8dx/vx59OjRAzNnzmQsKDY2NkJLSwtdunQh9/WxY8fQqVMnSEpKYtOmTeTYaXh4eLSab1BTU0NCVr98+ULGIfPmzSPfoYNY+/TpwyNeeeDh/yF4JCwPPPyPgVOZRiso9+3bh0GDBsHAwICUhv1skJmRkcEIweD8G53Aq6ury6W8AdgDlLy8PJw/f54oxMaMGYPOnTtj7dq1ePLkCe7evUuCf+iBVUpKCszNzUlid2NjI/Ly8tClSxcMHz4cZWVlhLjl9EL6u4lYmgAF2BPYN2/e4MGDB/D29oampiaDROYkCseNG8c4NzU1NZiZmUFFRQX+/v5k0F9XV4elS5eCoigoKSlBQ0ODDFBpnyhZWVk4OTnhwIEDePHiBTQ0NBAREcGlSgTYg7e0tDSuYCMACAsLQ1hYGLmevXv3Rm5uLvl3Wloa5OXlcfDgQZw5cwYhISEQFxcn59jY2Ihz585h8uTJpLQLaNtAOiEhgSgWaGzbtg2GhoYMP0iATUIJCgpi6dKlXBO+jpTFtsSdO3fQr18/CAkJEQUap4/d27dvkZ2djaamJixatAiysrK4ePEiampqEB8fD4qiiA3FiRMnEBAQAD09Pfj7+/+2UnfKlCmQlZXF7t27cezYMVhZWUFaWpqUoN+5cwfa2tqwtLRk+C+3p104j+3t27cMFRXALhXu2rUrCWV6//49oqKisHfv3nadV0VFBSoqKtpNqO3cuZNx/y5ZsoQrTGvWrFlEDfrkyRPY2NhARkaGQRxOnDgR3bp1w4oVKxjP8fTp07mIWCcnJ5ibm5O+5+3bt6TNBw4cCFVVVWzcuJErwGvgwIHo168fWCwWo+zyV9eD85lpj5crZ6l2dXV1mwlRzuO5e/cuKisrsXv37nYp5GkUFxdj2rRpoCiKy5eupqYGCxYsgJOTE0OV8/79e9y8eRMzZ85kqHl+ptz5/2xB0FIlb25uDnNzc+zfv58otI2NjQGwJ91fvnyBv78/nJ2d8e7dO4YymFZU/awf5dxfr1694OjoiGnTphFPzLy8PPDz82P48OEoKCjAgwcP4Ofnh5EjR5L2/fr1K5KTk8ni0uHDhyEhIYGlS5di2LBhEBQUxJEjR3667/a0CyeuXr2KHj16IDo6mus90BIdJY/S0tIgJyeHBQsWYOnSpdDV1YWJiQl5Li9evIjevXtDWlqakMH0vnr16sW1wHTu3Dl06dIFYWFhuH79Ote5cf47ISEBZmZmmDt3Ltczs3XrVrKfW7duYfLkyYzAu/T0dPDx8WH58uWMZ6Guro5UD61ZswYWFhbo3bs36YNYLBaqqqqgqqqKvLw8hIeHQ0dH57cU5Jzn9P37d8ZvLFiwABRFMSyD6G3o4549ezaUlZUhJiaGvLw8JCQkwNLSErNmzSLbPH/+HAMHDkRGRgbZ9suXL/Dx8WEEtHGeQ11dHT5+/Ihdu3bh7NmzXGS9u7s7CUNTUVHB0KFDyfHt3r2bYYkAsN8xysrKDAVsVVUVo8yc06OaBk0ut1T3/klw7i81NRWCgoKwtLQEPz8/hg0bxqiCqK+vx9q1a0FRFKlaay9ae2ZPnDiBDx8+EJ97ulpr9OjREBcXh5ubG549ewaAbVVhZGREVOZfvnzBw4cPsXz5cqLQvHHjBk6cOIGzZ8/+tn3YunXrUFRUhKdPn+LDhw948eIFDA0NiWXFgwcPICkpCS0tLYboobS0FF++fCGVXBcuXIC4uDix76KPy9bWFklJST89hosXL0JVVZVBxJaUlGDMmDHYvHkzGhsbycLaqVOn4OTkBAcHB7I9J+EbGxvL+G36+t++fRuioqI4f/487t27B1FRUfTu3RurVq3Crl274Onp+R9n2cMDD/9L4JGwPPDwPwTOl/CnT59IKTPAHvzHxMTAwMAAx44dI58PGTKEkDAsFgvr16+HhIQEVwpxy9RqExMTklpLIykpCWpqalBRUYGOjg709PTw/PlzAOxwqC5duqBr167Q1dWFi4sLmSzMnj0bcnJyuHDhAkNJ0tzcjPz8fMjKykJZWRk9evQg4Tz/BG7dugWKonD+/HmimqDP5+7du3B3d+dKEG+pjli4cCGUlJSIzyatCGsZ0EEHPA0ZMgTPnz/Hnj17oKSkhAMHDmDTpk2YOHEi+Pj4sHnzZrx48QKampro06cPo7yYRl1dHaZOnQqKosjqe2NjI1G5+vr6wsHBgZH2evbsWVhYWBCV0NGjRyEuLg5XV1cyoWoNbZnolZSUIDIykuu67dq1C4KCgoRIoNuO9uUTFhYmnrm/q/YsLS0l6g2ATSSFhoZCTk6OKJY5FbH08fTs2ZMo9woKCiAuLo4NGzZwnXtJSUmH1Xv0Pt++fQs7OzucOnUKANuLUEpKikxM6YF7WVkZnj179tuTmZSUFOjo6EBeXh4jR44k9+PHjx/h5uaGnj17Yv/+/fD29oa3tzeZMHNOun92Pr/67GdoS5jWzJkzyT1z//59DBo0iFyTjRs3QlFRkZT6tcT06dMhJCSE1atXY/r06TA1NSXntHXrVvTq1YtRIh4ZGQlDQ0Ns2bKFKMs5Fc9Pnjwhx0SjLeRibGwspKWl2+3lSp9newhRgG3/4erqiuLiYjKZb4tC/vHjx7h8+TIqKirQ1NSEuro6pKSkcJVHAmB4nT58+BBXr17Fp0+fwGKxUFNTg5SUFMZzBLDV33Qf+Z+EiRMnIiIiAg4ODpCWloauri7WrVtHLBZ0dHTg4OAABwcHRphWRkZGq8rg1p4Tzn7G19cXnTp1gpGREUxMTKCqqkqUfQUFBTAwMICqqirU1NRgYWHBtUhz7949vHjxAk+fPoW2tjZWrlwJAMjPzwdFUaAoikuF3lZwHvvr169x+/ZtsFgscl+dPn0a6urq6N+/P+lz3dzcGFUb7QGnqu358+fQ1dVlVO40NDTAzc0NpqamZFwxatQoSEtLY8WKFYwy/5CQEFLZ0tjYSP42f/58CAkJIS4ujrTzli1bkJiYiLS0NEZY3rhx42BpaUmI2FGjRpGFlebmZly7dg0URUFAQICLMEtPTwc/Pz8jXZ7zPOvq6rBx40bY2NggIiKCELGVlZUwMjICRVGM0KHfDeFatWoVevXqheDgYIailCZi09PTUVVVxTjW+Ph48PHxoVOnTowgtMTERNjY2CAmJga7d++Gn58fevXqxSBaq6qqoKWlRYLbOFFbW8uw76C3o/vhxsZGEr6krq7OIGC/fv2KQYMGMexU6PPz8vICwF7EW7x4MTQ0NGBiYsIgxX4mTvi78fDhQ7i5ueHmzZsoLi7G5s2bISAggMmTJzOqMurq6rB3797fHhdzerTSv5+SkoI+ffqQfy9YsAAuLi6YPHkyuV8ePXoEeXl5nDp1Cvfu3cPIkSOhq6sLNTU1iIqK4t69e1z76qjVCG3B8ODBA/Ib+fn5MDQ0JKTnmTNn0LdvX8yePZthY+bg4ABVVVX4+fkRG6fc3FyIi4vD2toa4eHhcHR0hL6+fpva8uLFi9DQ0ED//v2xcuVK+Pr6wsfHBwB7TuPl5UXmBmfPnoWpqSlXaK6zszPGjRvH9dv0Mz9o0CBSsXX69GkEBQWhW7ducHV1ZYQ6/n+27OGBh/9V8EhYHnj4H8T06dNhYmICHR0d+Pn5EeVJUVER+vXrB01NTaxYsQK2trbo1KkT8TtctWoVREVFf5hCzDkgffDgAWNwlJ2dDRkZGfz1118oLy/HxYsXERwcDDk5Obx48QIAeyJ/6dIlXL16lRA5JSUlcHV1JWQhDc7ffv/+PdatW0dWmIF/ZtBRVVWFpKQkCAsLM3zX6H3fvn2bELGtKSPev3+PgQMHkonagQMHICkpidmzZ0NdXR1eXl4Mf8/bt2/D0tIS48aNw4gRIxhhFFVVVVixYgWEhYVx+fJlFBYWQlRUFNOmTSPf2bhxIyEaOYlYOnygsrISc+bMwcCBAzF06FDSll+/fkV5eTkmT54MFouF48ePQ0FBARkZGXj58iVMTEwgKiraIaWFnp4eI8V327ZthGRsbm6Gh4cHbG1tGYT0ixcvSKq9kJAQsV5oDzjv1alTp8LGxgbi4uIIDAzE/Pnz0dTUhKdPnyIqKgqKiopE6UTfd3RwkJOTEw4fPoz8/HyGP2dDQwNWr17Ndd3bSjZGR0dzJeE+ePAAMjIy+Pr1KwoKChj7+/btG5YvX/7Lssm2Yu/evVBXV8e2bduQlZUFGRkZ+Pv7E3XL5s2b4ezsDDU1NeJ/SE8M2oKOlsdxbteWMC1aEcsZaNbU1IQRI0Zw+bq1bKv4+Hg4OzsjISEBFhYWAEAIWUtLS8TFxTFI3IiICBgZGWHr1q2MctmFCxdi/PjxkJSUBEVRxNKgtXbgPAb6/t6/f/8vvVwvXLhAtr1//36bCVHOtikuLoabmxsjTBBoXSG/ZcsW8u/U1FTo6+tDSUkJVlZWGDFiBMrKyvDp0ydMmTIFEhISREXbUsX1o+3S0tIgJCSEsWPHwsvLCzo6Ov9xE8mcnBxISUnh1q1b+Pz5M0pLS+Ht7Q1XV1ds3LgRb9++xbx58zBz5kxkZmYStX1jY+NPlcE/wqJFi9C5c2dS6nr//n0EBARASkqK9Pvv3r3DkydP8Ndff5H7hVO1SOPAgQOwtbUlFh6XLl3C8OHDkZWV9dsE3tSpU2FkZARxcXG4u7tj48aN5Hk5c+YMdHV1YWtrC2NjY2hra/80UKot+wPYi2xKSkpkEZFenKmtrYWioiIp462qqkJcXBwcHBywfPlysm96cZT2wKR/f9WqVQgKCoKcnBwmTpyIiRMnQkFBAcHBwXBzcwNFUYxgrbFjx8LGxgbjxo1jeJjT2Lx5MyiKwvDhw7m8pJctW4ZOnTqRypMzZ87g4sWLRK1ZV1eH7OxsQhjRROyECRNgb2/PCGv7HSQnJ0NBQQGLFi3C6tWrISEhwfDgX7RoEQQEBDBjxgxyDPHx8ZCUlISJiQlMTEy4LEeWLVsGV1dXaGpqwtvbm2tx4NOnTzAzMyMEKuf1LSoqQnx8PMOm5OjRo4iLiyPjhhMnToCPjw8mJibE+oDFYmHy5MlQUVEhisxFixahtrYWGzZsgJqaGvr16wctLS1ER0dj/vz5WLFiBbS0tLg8Yv9pAnbevHnw8/NDZGQkY2F/27Zt4Ofnx+TJk1u9zh299i9evGBYNNEYM2YMHB0dybgjLCwMmZmZjHfqp0+f0KdPH6ioqEBUVBSjR48mY14DAwOGz3p7wXkfXLx4ERkZGcRbmv7bnj17oKuri507d6K4uBjBwcEMO5ypU6eSUKwVK1Zg5MiREBAQIOPiJ0+eYPjw4Rg5ciRSUlLa9RzdunULfn5+MDQ0RGBgIBoaGpCamgo5OTnk5+cTYriurg65ubkwNDSEuro6wsLCYG1tzSB8V65ciTVr1jCU9Lm5uejSpQuxj6murkZFRQVj/PH/2bKHBx7+l8EjYXng4X8AnAOVjIwMSElJYfXq1WTArqWlRQz979y5g/Hjx0NXVxf+/v7IycmBsLAwhg0bhqioKOzateunE0EWi8Uo7eJUWMXFxTG++/r1a/j4+CAwMJAxaOA87o8fP5JS35aoq6sjKklO/N2Tdc7zX7NmDVGvcJKHdJvfvn0bXl5esLKyIhNAzt/Jy8tDeXk5bty4gR49ehBl5/Lly0FRFMzMzBgeWrdu3SIl6LQqjsbnz58REhJCAstu375N2qK2thZycnIwNzcnRBonEUurjTiPHWBPSkaMGIE3b94Qgq1Xr16YNGkSaYdevXrBwMCArPK3FePHj4epqSnZ37dv36CqqgofHx9Sunb27Fm4ubnBwMAAx48fx7Fjx+Dn54egoCBUVlaScvKOYs6cOZCXl0d+fj4+fPgAT09PqKmpEXXGw4cPERUVhU6dOpGJWkJCAsLDw/H69Wv06dMHXl5ekJaWZigNi4uL4e/v3+p9+yt8/vwZY8eOhaSkJElNB9jl+yEhIUhNTWUkqgNsBVvPnj1x7ty5DrVDS9Li3LlzjHZ9/vw5ZGVl4e3tTRYGKisrSXDNihUrEB4eDmdnZyQnJ7fqC0iD8/k5ePAgV4BFW48RaFuYFuc1oEmVyMhIxMTEcP3e9+/fSXAaXQp/8eJF6Ovrw9jYGFJSUvj69Sv27t0LKysrxMbGMojYXr16QU5OjlQTzJgxA7Kysjh8+DD279+PtLQ0CAgIMIK8WkssjoiIgKCgIPz8/MhnbfFybQ8hyomFCxfC3t4efn5+5NrRquZZs2bBxsaGKOQNDAxIv7J48WIoKCjg9OnTANgp43JyckThV1paSuxPONPhlyxZ8tPtPn36hDVr1sDBwYGh6PlPKqmcMmUKnJycGH3q27dvYWNjA01NTUJEcCrH6YC/tiiD6Yk3wC5b7dSpE7S0tBgLd8+ePUNAQACkpaWJUpMTixYtQmhoKIYOHYrLly+T46STy69fv47y8nIEBwdj4MCBZLuOTuxnzJhBKjg+ffoEFxcXGBgYYPHixaQy5/r160hPT8fs2bM7RBxyPg9xcXEYNmwYGhoaoKKigkmTJpG/ff/+nSz0TZ06ldzT1dXV6N+/P+zs7BhE7IABAyAmJoajR4/i69evqK6uRnBwMPbt20fIU857uK6uDjt37oSwsDAJeaR/Z9CgQeQ4N23ahP3795O2pwnfGTNmkNJoGjt37kRjYyOSk5MhISEBdXV1yMvLE+VefX09srOzYWtri8jISHz79o0skLW3HWlwjqdu374NfX198n4+ePAgxMXFucJDJ0+eTPxqFy9eDD4+PhQVFeH169fw8/Mji8MtS+dfvnxJjvXx48d4+fIlIfj2798Pfn5+LFq0iHynurqaeGPSn+Xl5UFSUhITJkxgWDLl5uaCj48PPXv2RGRkJKKjoyEmJgZVVVXs27cP48aNA0VRZDF93rx5GDhwIDZu3Eg+u3fvHszMzBhVMxs3boSQkNAPxQl/B/bt2weKoqCsrMxQAQPsZ1dISAhjxozp8Fi4tTH+kSNHIC0tzbh3N27cCEtLS5iYmMDMzAx6enpobGzE5cuXcejQITx79gzfv39HVVUV8vPzGYuFdXV1sLOza9UDvL3HSKvIW7PZqqyshI+PD7p37w5lZWVGBcDHjx/h6OjIEBB8/vwZc+fOZQQStkR72rW+vh6fP38Gi8XC3bt3oa+vz6g2pM/j+/fvePbsGRITEzFu3DhMmzaNPK+VlZWIj48nQaAt+xM/Pz9GZWNrbcQDDzz8/wKPhOWBh/8hHDt2DKtWrWIE1wBAcHAwtLS0GN5z9CQQYA/q6NV1Gj96udODw1WrVqGwsJBM6EePHg0TExOu769cuRK6urqMkCVOlJaWQltbm6i/OAc/N27cQEpKSqvp438XOEmAiooKlJeX49GjR0hKSoKAgAApL+JUuNy/fx9jxoxplUCg23Hp0qUICAggk67s7GwMGTIEMTExXAO+u3fvokePHrCwsODyfR08eDB8fX0Z14fevry8HPr6+rC2tibeZnV1dZg2bRoEBQUJAUyDtljYvn07SW/++vUrNDU1iXqhqqoKvXr1wqFDh9o94IuOjkZkZCQAdnnW5cuX8eTJE5iYmMDPz4+QW9evX0dkZCTExMSgpaUFR0dHNDY24vv37zAyMiLKh1+BbluaXCovL4ezszMhQ06fPo0uXboQsoNTWZiWlkbUsZy2DDdv3oSYmBgcHR1RUVFBlB8BAQFwcnLq8CSopKQEaWlpEBcXZ6gXY2JiuNRVdEiDv79/h0gqzuu2du1ajB8/Hubm5oyBPsBWw8jJycHPz48xCU1JSUHXrl0xZ84c7N69GxRFITY2liuEpuW+1q9fz1CX/Qyc59WeMK05c+aQZ3H69OlE8ZaSkgIFBQUGYQWw+5s+ffrgbIuQQl9fX1AUxSBFt23b1ioRO2XKFDQ1NaG6uhpubm5YsmQJ+VtNTQ1R6XK2Lyc5snz5cnTu3BnCwsLtCrf6FbH5I0IUYCtqZWVlISsryzWpr66uxty5czFo0CAMGzYMjY2NaG5uRmVlJYKCgsjiAx3QQi8OfP/+HY2Njfjw4QPWr19PtqupqfnldrS6q76+/j8ihIsT9PHOmjULVlZWhGii78MzZ85AVFQU7u7uJJCSVuV1RBm8atUqCAoKwtzcHGJiYmRhkj6O58+fIzg4GBRFMbyPly1bBhkZGUyaNAnq6upwdHRERkYGmpqa0NjYiMjISFAUBW1tbRgbG3fIX5rzu3QlB01snD17Fl26dIG9vT20tbVJUE7L7drah7a0QSkqKoKxsTEhPDIyMtCtWzfG88hisWBpaYkFCxYw9kUTsba2tli1ahWamprw8eNHopLT09NDjx49oKenh4aGBpw4cQKKiorQ1dXlUu5mZmYSn1kWi8WwtamrqyNhREePHiWfr1u3jkHEcp7Xw4cPYWFhgRs3buDKlStITU0FRVEk5K2+vh45OTlQU1P74WJNWzBs2DASOka3y/Hjx6GlpQWArZbmVGlXV1czyCxa1X3gwAHGAkBoaCipQgDY1+2vv/5iHN+0adNgbGwMPT09dO3aFRs2bMCnT5+Iv6mnpye8vb3h6OjIuDeLioogLy/PtdBEjxEvX76MMWPGICwsDNOnT8fjx4/Ru3dvKCgoQExMjBGWCoBxz9fU1CAwMBCenp4MFfnIkSNJQOnfgR/lMxw7dgx8fHwYPnw48SenkZWVBWdn5z9OwtE2VJwLMgEBAQgLC0NSUhIaGxuRkJAARUVFSEtLQ0dHB/7+/mT8CLDv+SdPniAoKAgWFhYd6tfPnDlDKqhGjBiBQYMGIScnBzIyMgy7Cfq3q6qqcPr0aRQUFDD8gktLSyEhIcFY0AbYlk4+Pj6YPn06gD8n7Dh16hRkZWVbXRD70T44P3/27BlSU1Ohp6cHTU1NLF26FFOmTEFISEirtg488MDD/1/wSFgeePgfwe3btyEiIsJQPXKqENTV1Yk6i/Olv2jRIsTHx0NcXPyXpbR0OfKiRYvAx8cHRUVFMtjYs2cPTE1NucJrjh07BmNjY8bksCXWrFkDPj4+hok+TTxFRUX9Y6u9nIPhOXPmYMSIEYQE/fz5M8aNGwcBAQFGeMn06dMZA9CsrCxMnDgR27dvJzYMAHvCY2hoiObmZlRVVSEkJIRhN9BygFZUVARTU1P0798ft2/fBsAeaDo4ODAGoTSZQbdReXk5dHR0uIjY+Ph4olwB2INFdXX1VtW7o0aNgrq6OqZPnw4XFxfY2NiQ42sLCUgrDDds2AAzMzM4OztDUlKSKHQfPXoEQ0ND+Pn54cqVK2S7x48f48OHD4wyaC0trVbV0C2RmJiI4cOHM2wNvn79Cmtra3z48AEHDx5klPfTHnucVgfz5s1DREQE+vbty3h28vPzISwsDDs7O5iZmcHJyQlmZmYd8uPivJffv3+PKVOmcCmNnJycoK2tjcGDB2Py5MlwdXVlTETbQ8Ry7m/evHno3LkzevfuDRERERgaGnL5P758+ZJBAhcWFkJXV5cocC9cuAAhISEuH8eWAUu0Ir+96qH2hGl9+vQJKioqsLOzw+jRo9GlSxcUFRUBYD8XVlZWMDIywt27d1FSUoKSkhL4+fnBwcGBcc0qKioQFBSEWbNmwcDAAH369CF/27ZtG6ytrREXF8dVxv/161d0794dycnJjM+rqqoQEREBiqIwdepUxvVat24dJCQkkJGR8UsvV3qS3VZikyZE161b1+rE9/z58xAXF0d0dDQhwzjDZzivH729m5sbioqKcPz4cQYh8/37d2RmZuLChQsd2u78+fOMdvlPVPTcvXsX/Pz8JJWdxrFjxxAREQEPDw94eXnh+/fv7VIG9+3blzzrlZWVSExMxPbt23Hp0iXY2NhAW1ubVE9wqgoTExMZ133SpEnEI7W6uhp9+vSBg4MDMjIyyH11+PBh7Nu3jyvoqC3gvH7v3r1DSUkJcnNzUV9fj7Nnz0JeXp70E+bm5tDX18e0adPabGnyM2RlZaF3794YMWIE+aykpIQo08PCwjBhwgS4ubn90OOxqqoKsbGxsLGxwerVq8l3Tp06hQ0bNmDTpk3ks4SEBOjr60NERIQQeXTbFxUVQVFREefOnSPvOIC9CEUrPe3t7eHi4oKCggLSbhkZGeDn50dCQgKxjKirq8OtW7cYi3DV1dWYPn06g4itq6tDfn5+h8mjly9fwtbWFj169GCEUT169AgBAQFYtmwZxMTEGOTVX3/9hbCwMFKqT/cZLRdR4uPjSeJ7c3MzvL29ERMTw1i8kJeXx/Hjx1FTU4OwsDBIS0uTxaFr164hKSkJo0aNwvz58xlq6YMHD8Le3h4Au9/etGkTfHx8oKysjJSUlFZVwWvXrkWXLl2goaGBPXv2EEUh/b2amhosWbIEfn5+rb7XW4Yx/klwPkOnTp3C9u3bsXPnTiJuOHDgAPj4+DBq1CguKyIaHe0758+fz/DupXHkyBGIiopixIgRaGhogLm5OaytrbF//34cPnwYBgYGOH/+PN69e4dt27bBy8sLJiYmZMFz8+bN8PPzg5OTU7vHSCwWO2yOtnUJDg6GpKQkHjx4ABaLhezsbAgKCra6wMnZlvT+mpqaEBUVhdjYWLx7946xr7CwMOID3RFwtju97wsXLkBNTY0oyTn/tmvXLoaH9I/Q2NhIxuyhoaHE5mjhwoUdPlYeeODhnwePhOWBh/9StBx4VVRUYP369VBWVmaYv9ODoJ49e5IydhozZsyAnJwcDh48iLy8PKSmpv6wlDYpKYmUbK1atQrCwsKgKIqUNNfX16NXr16wt7fHsmXL8P79e7x9+xY+Pj7w9/f/6UCxvr6eTDLCw8MREREBZ2dnRtDE3zlJb/nbkyZNIgpRTgVCdXU1Ro8eDYqikJaWBhcXFxgaGpIB37Rp0yAjI0O8NDnDfR4+fAhpaWmoqalBR0cHRkZGv5zwFhYWwsDAAF27dkVwcDAiIyMZ4S5Lly6Fq6srQwEKsFf5NTQ04ObmRkjy79+/M8qiN27cCENDQ+Kfxrn9lStXMHHiRFhbWyMyMrLDpcLNzc2wtrYGPz8/Ro0axfgbTcQGBARwldhfv34do0aNgoyMDJcS+EdISkqChYUFkpOTyWC7srIS+vr6ZJJHE7AA2wfM09OTKAarqqqwadMmogyjJzycAUMrVqzA9OnTGWnXHSUtaLx//x6TJ0+GmJgYVq1aRT5PTU1FaGgoQkNDkZyc3KGyXc793bx5E3FxcWRy8PLlSxgYGCAwMJBBLjY1NeH9+/fk/M6cOQNzc3MAbBU8J6H25csXHD16lGu/GRkZrYb7/QrtCdOi8fLlS3Tp0gVdunQhiee0Uu3ly5dwc3ODvLw8VFRUYGZmBktLy1bvZ9qvMzs7G3p6eujbty/52/bt29G9e3fMmjWLq69IS0uDra0tYzEBYPvQBQUFQVhYmIQfrV+/HpKSkti4ceMvvVxra2u5bAzaQohyntOJEyewefNmHD58mCwInTx5El26dMHAgQMZ5ALndtu3byf3Ys+ePaGrqwtJSUlCAAFs0o1OJKexY8eONm/XERuP/4/IycmBoKAgkpKScPPmTbx48QKBgYGYO3cuHj58iE6dOuHQoUNtVgZzXnc6AZxWQDU3N+PSpUtwcnKCgYEBysrKAHAT6AUFBTh69CgGDhzIeJYqKirQp08f2NvbY/369VzESEcXk0aNGoXQ0FCUl5fjy5cvYLFY6Nu3LxITE8lvRkVFQUNDA2PGjGn3uzwqKgrDhw8nbVBWVoa4uDjIyckhODiY8d2KigoUFBTA09MT4eHhDO/zs2fPYufOnSgsLCRVQZWVlYiNjYWtrS1WrlyJ+vp6Lq97T09PSEhI4Pz58/D390dMTAxZGAXY5K+BgQEyMjIgICCA3NxcJCcnQ0pKihCLHz58gK2tLRcRu3TpUjg4OIDFYmH69Onw9PSEqakpXF1dGZUGNBErKChI+hMaHSFiWSwWbt++jYCAAKiqqpLjfPv2LSwtLUFRFObMmUO+X1tbCxMTE/Dx8SE9PZ1rcY2zzebOnQtbW1s0NjbC398fGhoajD43KCiIqBz3798PaWlpsgjZGmlHq4sBtncxRVGYNGkSrKysEBISgvHjx2PhwoUQFBRkeCHTePToEV69eoU+ffrAwMAAW7Zs4SJWs7KyMGbMmD/mq9teJCUlQVtbG6ampvDw8ICCggIJgc3Pzwc/Pz/Gjh3LWGRuL1q2y4oVK4gamwanvVinTp3Qt29f1NbWwtfXFy4uLkhKSuIKkrpw4QJcXFzI/KKwsBB5eXkdGiPRqKiogK6uLiiKYnjK1tXVISsrCwICAgzvdM5ze/PmDUMAkZGRAT09PcyZM4e0X01NDVxcXBhK8vagZVvS/XddXR309fXh5eXFsGGqr69HUFAQY271I3D2jy9fvkROTg6CgoL+YypFeOCBBzZ4JCwPPPwXoqWCiLO0MzMzE6Kiohg2bBjju0ZGRgx1xbdv3+Dp6YlFixaRzzhLaTkHOGVlZZCRkYGtrS3mz58PCQkJ7Ny5EwsXLgRFUUTRWVtbiwEDBsDMzAwCAgIwNTVl+DP9isTLz8/H8OHDERsby/BL+icHH/v27YOysjJR1AHsAeG9e/cIuTN37lw4ODiQ1FgWi4Xa2lpER0cTlcy+ffvg6+sLPz8/ojZ9+vQppk+fzkjq/dUE6t69e9DS0oKRkRFycnIYA9tr165BSkoKYWFhhIil25j2sDMyMmKUZNN/X7NmDfT09BghFvTf9u/fT/xmO1oq3NTUhJs3b8LQ0BADBw6ElZUVIzkeYE+OTExMYGtrizt37pDPHz9+jDVr1nCVTbeGlkpPOzs7JCUlERUlPckLDQ0lx1VTU4OAgAB4enqiqakJS5YswciRI/Ho0SPs3LmTlJL/Sv3b0YTflknz3759I76QnERsR0mS+fPnM8j17du3w9raGiYmJgxV8cOHD0mgxMWLFxnb3L17F42NjXj48CGMjY0xb948SEhIMIjs8+fPw9XVlXjpAuyJnYyMTJsI2JaBWe0J06L/fu/ePcjLy6Nr165wdXXlUoYDbF/D3Nxc7N+//5cTw5qaGmzcuBF6enqIjo4mx3DixAk0NTXhy5cvDHLk1KlTcHV1RUxMDCFiq6qqEBoaiqysLCQkJMDZ2RkTJ06EpqYmZGVl2xVu1R5ClFOdnJSUBE1NTVhYWMDb2xtqamqEpD5z5gzExcUxePBg1NTUMNr4/v37MDc3h7m5Ofbv348HDx7AxsYGxsbGANjvmC9fvsDf359hx9Ge7Zydnf/jQrh+hry8PCgoKEBVVZWQ/XV1dXj9+jW0tbVRVFTUJmUwZ5tMmzaNhLjo6uqSMnAWi4VLly7B2dkZxsbGKC0tZdwv8fHxkJaWhpSUFCiKwsiRIxnH+vnzZ8TExEBbWxv79u377XMvKSmBnZ0dYyGHxWLBy8uLQdbExMTg+PHjDOV1W9DY2Ijz589zBVwVFRVh1KhREBIS4io15jwOGklJSVBTU4OGhgaMjIwwcOBA8s6prKxE//794ejoiHnz5pG+YcKECRASEoKYmBgEBASQk5ODdevWwd3dHb6+vtiyZQtOnjwJHx8fWFlZ4d27d5g9ezZEREQgKSlJSBi6T6KJWFdXVxw5coTsh8ViYfXq1VBSUkJycjLi4uJAURTS09MZ51BTU4OEhARGRUtHwNmWp0+fhouLC3R0dAjpV1hYCCkpKQQHB2PRokXYsmULPDw8ICcnBwkJCYwaNQpubm7w8PDAiRMnuBYs161bB2NjY/j6+kJbW5vsLy0tDQsWLICKigqePHmCs2fPMqpTamtrMWXKFPLupn/v06dPqK6uJu+n7OxsODg4ICEhgRGgZW1tzVgUvHPnDp49e8aws4qIiICBgQG2bdtGFNmTJk1itMk/3TdlZmZCXl6eeEDTVhWc79DDhw+Te+J38fLlS3KOGzZsAD8/PyPgFWBb3/Ts2RM+Pj5obm5GbW0tvLy8QFEU3NzcuH4zOTkZJiYmXM9pR9vyy5cvCAgIgIuLC7y9vRlVcrW1tcjOzoawsDDs7e0ZmQopKSlQV1eHkpISQkNDybWfO3cuDAwMYGVlRRaiDA0NfzuEcPny5YiOjoaVlRXmzZuHr1+/4unTp+jatSscHR2xaNEiZGdnw93dvU3CCxo/er55RCwPPPzngEfC8sDDfxk4BwBLlixBbGwsDA0NsXLlSjIgzczMRJcuXUhpo66uLvj5+Rk+jzU1NVBXV0dSUhLj92kCgaIojBkzhnz+9u1bdO3aFXx8fGTSU19fz0XENjQ04NWrV9i7dy/OnDnT5tXw1sJrgL93QOzv789VjrV161Y4OzujtrYWjx49wpw5c4g3XFBQEGprawGwiVn6WAsLC/H8+XOEhoYyCM9Dhw4RJTBddtqRc7t+/TqGDh1K9nf48GGijrp9+zYUFBQQEhLC8N3dvXs3xowZg+jo6Fb38/DhQ/Dz8xNPLBq0VQKn2qatE74fkZWfP39GUlISzM3NMWvWLMbf7t27h379+nFt2x6fQBr3799HeHg4NDQ0kJycjA8fPqC5uRlz584FRVEICgpCWFgYo7x/0qRJkJOTw/bt20mSLb0QMXfu3N8umW6pUvuZLyRNxrVURbYHO3bsQGxsLKP9CgsL4enpCXFxcS4vPZoI19XVRc+ePVFeXo6xY8dCQUEBFRUV+PjxI3r37g1RUVFGX1FfX0/U2XQbvX79GvLy8lye1L9Ce8K0OH0h6f+vqqrC48eP0aNHDzg5OXF5Nrb896/urZqaGuTk5MDQ0JARRkeHW5mbmyM4OJj0Bfv27YOXlxdUVVXh6OgIQ0NDQj6mp6dDSUkJ8vLybfJy5STGOkpsZmdnQ1FRkZDC6enpoCiKUQp5+vRpUBSFuXPnks8mTpyIiIgIODg4QFpaGrq6uli3bh127NgBVVVV6OjowMHBAQ4ODgxF/oQJEzq03X8TEfvu3TtcuXKFYbMQEhICRUVFlJaWtksZPH36dMjLy+PEiRN4+vQp8YmmlbQsFguXL1+Gnp4e43l5+vQpvLy8cOPGDTx+/BhjxoyBpaUlV5/76dMnTJ8+/bfbf/78+fDz80NUVBQjeLOhoQFxcXGwtbXFoEGDuCpGOhq+tnr1alhZWZF/P3jwACNHjoSOjg7DpqQlEbRgwQIoKysTonjChAmQkJBAcHAwWZiorKxEYGAghg0bhubmZrx69QpOTk44c+YMiouLsWjRIggICGDNmjXIycnB4MGDISQkBHNzc3h5eZF90j7YoqKijEAiug/68OEDHBwcoKenR6pkbt68idTUVOI3D7CfWT4+Pixfvpzx/qirq/vhWKm9mDlzJvz8/GBtbQ2KotCjRw+yoHb16lVERERAS0sL7u7u6N+/P65du4ZBgwbhwoUL+Pz5MyIjI9GnTx/o6ekhLy+PWPtcuHABFEXB1NSUtMu2bdvQrVs33L9/H/369YOvry9ERUUZz8L79+/h7OyM3NxcxljH0dERFhYW0NbWJu+Wln16amoq1NXVSRXMpEmT0KNHD8jIyCAqKorRtpGRkTA0NMSYMWPg4+MDCQmJfyu5lZCQQEJY6WoT+j1dWVlJrCouXbr026Th7t270aVLFxw5coQ8j5mZmURZ+vXrV1RVVSEyMpLcv+/evUNzczPq6uoQGhoKJSUlbN68mbz/AGDv3r0wNDT8LaVuaygtLUVAQADc3d2JehpgP+Opqano1KkTgoODUVlZiW3btqF79+7Yvn07tm3bBi0tLVhYWJBx3ZEjRzBr1iz07dsXaWlpvy3yoL3yZ8+eTUJC4+Li0NzcjJKSEoSGhsLc3Bw2NjYMi5mOKtd54IGH/yzwSFgeePgvRUpKCuTl5bFq1SrMnz8fmpqaCAwMRHV1NSorK5GZmUnIw9OnT5PJOycRO336dFhbW3OV0qakpMDDw4MRUFBQUABpaWmoqKjA2tqaqBXq6uoIEbt8+XLyG60Fb7Rl8tWyDO3vxNWrV4lKhcbWrVuhoqKCiIgIdOvWDbGxsVixYgVycnKgoaHBVSo9ceJEyMnJQV5eHpKSkozAH4A9ifD394e1tTVDtdEecBJ5SUlJ0NXVxezZs8ng/Pbt21BUVERgYCCuX7+O9+/fIzQ09KeeswB7wigoKIhx48bhxIkTOHfuHHx8fGBiYtLugSnntdq7dy9WrFiBkydPEoVucXExJk2aBHNzczLhaInfSUYfN24crK2tER4eDnNzc4iLi2PSpElECXHmzBn069cPo0ePxqJFi9DY2PhDX1yA3Tb8/PxcRGxHQLfN7wQrtQf0tT58+DBRYz169Ag+Pj7w8PDgKiW9d+8ebG1tSQJyy/Cm48ePw8bGBm5ubli2bBkyMjLg5eXFUHbQbcRZgvcjnD59mrRJe8K0Tp06RT7Lz8/HmjVrsG3bNvJcFRYWQkNDA66uroQUGjRoELFMaU9/UlNTg1WrVqFv375obm7G5MmToaSkhDVr1pCQHjc3N6Iee/DgAXbv3k3uLzqZfeDAgVBSUsKyZcsAtC3cCug4IdrU1ITx48cjJSUFwL/CdehJfXV1NbFYuXnzJtlfTk4OpKSkcOvWLXz+/BmlpaXEl2/jxo14+/Yt5s2bh5kzZyIrK4vcY1lZWR3a7r9R0cMZ9BccHAx+fn7o6em1i0C/efMm3NzcSB+Rn58PKSkpBAUFgaIoskDT3NyMu3fvku1ycnLg5OREqjMANtk6YcIE2NjYcBGxNDqq5mexWMTfWFdXl5R307/35csXDBkyBOHh4YiOjv5tP2uArWjv0aMHfH19yWdFRUUYPXo09PT0sGnTJq7feP/+PQIDAwmBk5+fDwkJCQwaNAhGRkYIDg7GnTt30NzcjG/fvqG5uRkVFRV4/PgxUlJSGO2zdOlS8PPzk4CxDx8+oKSkhFSRNDY24t27d7h27RpmzZrFUDzT3xk1ahTy8/OJ3+bNmzdBURQEBAQYoVcAm4jl5+fHypUrW/Xn/x2sWbMGXbp0wblz5/D69Wvs2bMHbm5u6NatGxkj1tTUoLKykpBtVVVVcHFxYQQG3r9/HxRFQUNDA46Ojpg2bRpOnTqF+fPnk7Y7ffo0RowYQcaHq1evRo8ePRhWElVVVfD394ebmxvZrqCgACIiIkhPT8fdu3eJFdSlS5fI+R88eBD9+/eHnJwcsS46efIkevTogdOnTyMzMxMRERGwtbXF7t27yf7Gjx+PyMhIht3Sv2tRKDY2FlOnTkV+fj5DGdzc3Ix169Zh8eLFDNK5o5ZE27dvR05ODiiKgqGhIY4dO8aonBIREYGmpiY0NDTIGHDLli0ICAggKt3a2lp4e3vDzMwMK1euRGlpKd68eQN3d3d4e3v/LWP2ly9fIjAwEN7e3sTKx9PTE4mJibhz5w6UlZURGRmJdevWMexxPn78CD09PZibm5P3NMB8djr6Hrp69Sq0tLQYCyn8/PyMPoiuuqLHwL+zPx544OE/DzwSlgce/gtx7do16OnpEULw4sWLEBQUZCgvamtrsWHDBigoKGDMmDH4/Pkz7O3tYWZmRgiWc+fOkVJaejBRWVmJ4OBgRjo5wE5gvnTpEt6+fQtdXV1YWVkxiFhaKTJ//nzGdi9evMCrV69I0MDP8E+t9nJaDQBscszLy4v8e82aNYiPj8fWrVvJyv6rV69gamqKGzdukO/dunWLDPbXr18PLy8vGBgYcAX47NmzBwkJCe0m81q2x6JFiyArK4urV68ylEcA2+NUXV2dlMVyEjM/+/0DBw6ge/fuUFFRIcq/joQp0Jg4cSIUFBSgrq4OfX19DBgwgLRhcXExkpOTYWVl1SZvrLYiPz8fsrKyKCwsJIPclJQU6OvrIzk5mZBOLds/Kyvrh764AFu9Q1FUq5P7X2HKlCkMNXF1dXW7k+bbC87rXVhYCG1tbQwYMICUi969exfe3t7w9vYmRCzn+fbq1QsURSEyMpKLCD1y5AhGjx4NRUVFeHl5IS4urkNKEs4wrbFjx7YpTMvDw4MRpjVp0iR069YN3t7ecHJygr6+Pplg37x5E9ra2lBVVYWtrS00NTXb3Za0coZWnZ04cQLGxsbkuaavnaKiIgwMDFqd4L1+/RoTJ06EpKQkrK2tf+nlyonfJTZHjx6NhQsX4vDhw1yT+k2bNmHFihWMxafGxkZMmTIFTk5ORG0MsKsfbGxsoKmpyVDR0ufY1NTU4e3+W9HY2IjY2Fhoa2vDzMzslwR6yyCgt2/fYsGCBaivr8fp06fRtWtXrFu3DjU1NfD29gZFUVi8eDFjnzU1NZgxYwa0tLRgZmbG+BtNxNrb2/+xPpd+l9fX1yM3NxdCQkKMipIfvT86SkBkZGQQgjI/Px86OjqM9/Xdu3cxduxYSEtLo6CggGv7c+fOobS0FDdu3ICKigrxlJ44cSLExMTg6OiIBw8eAGBXKlhbW0NSUhImJiZcKefLli2DgIAAUlJSSMATwB4f0J75ALtSJjU1FWJiYoQYqqiogImJCWMhvKmpiVgHDR8+nFE6T++PoigGgdgRtHz3DR06FIMGDWJ89tdff8HS0hJaWlqkD6RBLwRfvHgRmpqaZAxpbGwMf39/nD17FuvWrYOgoCBGjBhBnvV3795BU1MT4uLixNuzqakJCQkJMDU1hZmZGXr16gVbW1uYmpoSsrGpqQmxsbEkKPbNmzfQ1tZmhJI2NTVh+/btiI6OJtdv//79GDVqFMNm6+rVq4iOjoa1tTWjP+L0hf13kmPLli0jC8ecfuefPn2Cv78/w5u3o5g8eTJkZGSQmZmJ2bNnw87ODkpKSjh+/Dh5Th88eID09HRGsGNWVhbs7OwQExNDxr7fvn2Dr68vhISEoKGhgfDwcPj5+XU4O6AtePnyJcLDw6Gvrw91dXUYGRmRe4UmYimKIgv8nFYWBgYGsLa2JtVjHUHLczp//jxsbW0BsNXFnO/ZyspKLjEG5zHxwAMP/xvgkbA88PBfiCtXrpDJ1q5duxgDgJqaGhQUFKCurg5fvnxBZmYmunbtCg8PD6xevRoURcHBwYEQB/v27YO3tzeUlZXh4OAAQ0NDmJiYkAEOTULs378fBw8eBMCeZBsaGjKI2Pr6ekydOpWETABslZuJiQn09PSgoqKCTZs2MfwUOcE5QFm1ahVDVfsnQYcRcKrqjhw5AklJSYSHh5PP6PNvbm5GVVUVAgMD4erqSgZjy5Ytw6RJkxgKo4sXL6JXr14wMTHhIlZotHWASpOs9AC5uroawcHBpF3o3+H8vaqqKhw8eBCHDh1ql+Ls48ePeP78OZ4+fUp+ryOTkqKiIgQFBaGwsBA1NTVYu3YtnJ2dERYWRojYt2/fYsSIEYiLi+vwoLTl5H7v3r1QU1PjKoUbP348REREkJKSwpgg/8wXl/7fnj178OjRIxw/frzdbfHlyxe4ubnBxcWFUWbclmAlTrRnv5ylgcePHwfAVm45Oztj0KBBhIi+d+8efHx84Ofnx6W8WrlyJWbMmAFra2sMHTqU4fXKeW4dPUYa7QnTEhYWhpKSEpngbdq0CcrKymTRaMWKFRASEmKQFLS1w5w5c9rsvUwjLi4OwcHBuHXrFvnsxIkTRFV+7NgxyMrKIiMjg9gveHp64uHDh4y07bCwMGhoaODOnTvt8nIF0GZik9OagfP8Zs2aBRUVFYiLizM8fCsqKuDj48PoszgTy62srIhPIt3eZ86cgaioKNzd3UkpMKcyv73b/beDVhRfu3btlwR6ZmYmuW6PHz8miyX0NR8wYABGjhxJ2nT48OGwsrJq1RO0vLwcS5cuhZycHFcI4qdPnzB48GCGpU170FJNp6ioSEivxsZGbNy4EQICApg8eTL5XsvnraPX/uvXrwgJCSGEYW1tLQ4dOgRdXV0GEXvr1i2kp6e3+pzTfcDUqVMRERFB+pr09HS4uroiLS0Nzc3N2LFjB7p27YqVK1ciPj4eoqKimDhxIuPdAfzLE54+p8mTJ6NHjx6Ql5eHsbExtmzZgurqalRVVWHy5MkQEhLCmDFj4OXlBR0dHTQ1NWHTpk3Yv38/advMzEwSksSpnAOAnTt3/hZJyNn2u3btQnl5OeLj42Fubs41HpkzZw4oioKIiAjDPxz4VygaXWVjbGwMJycnhidnVVUVuQacAXNaWlpwcHAg/X1TUxMOHjyICRMmYOzYsVi6dCk5x7y8PGI9ceLECVRXV0NZWRnDhg1j+M7S1gM0mfrs2TM4OTlBSkqKcS8CbOFCTEwM7OzsGGXtLdvn34GvX7/C0dERqqqqOH36NCoqKvDixQtSQfW7BHFxcTHU1dWxfft28hmLxSLj/mPHjhEVOCfo67hjxw6isqeJ2NraWkREREBYWBgHDx78rXFjW1FSUoLDhw8jMzOT7KeyshIAe1yjqakJZ2dnLo/iiooKyMjIcC06dASpqak4duwYbt68iR49emD16tWQlJQki+sAe7wQEBDAWJzlgQce/vfAI2F54OE/HK2RdidPnoSenh527NgBSUlJxur5iRMnEBMTg6dPnwJgD4q9vLzAz8+PqVOnYtiwYdDU1ISBgQFJEH306BH27t2L+Ph4LFiwgKFkSUlJgYqKCszNzSEsLIwBAwbg7du3KC4uhqGhIcOagA6pAtiTc3l5eRw7dgzV1dUICQnhKnOmwTkIzszMROfOnbFz584/1IJMNDc3Y8CAAZCWlsbJkyfJ56dPn4asrCyDiK2ursa8efPg6+vLCBgrLy9HREQEKIoiAWg0aCLWwsKCQfS2B6mpqbC1tWVMxmpqaqClpdVqWWltbS2ePXvG9XlHFWcdUTLs2LEDXl5ejPI+gJ147+zsjPDwcEKSlpWV/RFfu3nz5uH06dPYvXs3I+GZnmSXlZURZTCdvsyJH/ni0vcrZ0hWewMVysrKEBkZCQ8PD6KEai8Z11YcOnQIHh4eANjBPN26dSOTEzp9uyURa2Fhgfj4eABsD1zOBOK1a9fC3NwcQ4cOZai2Wto2dPTatTVMKzw8HD169CD3U2NjI6ZNm4aBAwcCYJPv4uLihMyurq7mUq4BbX8OHBwciFdv//79SQkmwJ7I1tXVwd3dnYQWfv78mfgp9u3bl3z3/v37MDExgbGxcbtK0dtDbG7bto1sc/z4cZw8eZLhO+3j4wMpKSlcvXoV7969w6tXr4j/Y2v38t27d8HPz89IygbYpHNERAQ8PDzg5eXF5cXY0e3+W9EWAn3t2rW4ffs2ud6TJk2CoaEhZGVlkZSURO47MzMzol6tra1FeHg4w9vyyZMnePbsGSEdqqqqsGTJEhgaGnIlmH/9+rVDfW5LP8k1a9aAoijY2tqSRZrGxkZkZ2ejc+fOSEtLa1d7tQX79u2DoKAgqfypr6/H4cOHoaenx7AmoPGj5z0pKQk2NjaEXAwLC8PatWvBYrFw7tw5jBw5klFNtGbNGqiqqiI5OZlrEY9uw9zcXOKDfe7cOURHR8PQ0BDz588nC+Fr1qyBvb09sWWor6+Hnp4eHBwccPToUdLGdCBTa0Qs0DGCq2VwpZqaGoqKirBnzx6YmZkhOzuboQjdvXs3evXqhRkzZqCpqQm1tbWMvwPsMCKKouDi4sL4G2e7t7wGRUVFMDMzw5AhQ7gqkThx7do1yMjIYN++fRg0aBCioqKgqqqKUaNGkX7w27dvCA4OxuLFi7nu5fz8fLi5uUFbWxvnz59n/O369evw9/fH4MGDf9VsfxQ/e97odvr06RPMzc1hZGQECQkJ2Nvbw97e/o9YJRQXF0NFRYWMd+m+uKamBhoaGjA1NcWxY8fIvk6cOMFFIG7btg1OTk6IiooigXbfvn3DmDFjWhUE/F3g3MfatWuxYsUKMq68e/cuunbtisDAQKLWp9u+srLyt71Y8/LyICcnhzNnzqCmpgZ9+vSBgIAApkyZQr5De+X36tXrH2kPHnjg4f8veCQsDzz8B4PzJb5u3TqGqsnHxwcURTEI2Lq6OgQGBjLCch49egQlJSUyaQfYFgFmZmYwMjJqlbwD2AP+hQsXomvXrrh27RoAtkKVoiiEh4fj7du3ePv2LUxMTNC9e3eGGqK6uho+Pj5k5Z1OqKdXizkHbZyDnIyMDEhISPyR1ObWwDkIGzx4MGRlZXHmzBny2alTpyArK4vIyEjy2YYNG5CcnMxVel1UVIS4uDh07tyZS8F46dIleHp6YsCAAe0+RhaLhaysLDg5OSEoKIhMxr58+UJ+s7q6mtFut2/fxsCBA7lKyP8pNDc3IzU1FZqamtDV1eUa7G7cuBFubm5wdXVllFu2l8TjfB62bdsGAQEBEgZibm4OBwcHhk3Dw4cPER0djeXLl/9wAP4nfXEB5j32119/wdXVFdbW1ti3b9/flhj/8OFDyMnJQVdXFxISElzewzQRO3jwYELYvHjxgqi8R4wYASMjI0ZI07p16wgZeezYMfj5+cHIyOi3lXQ02hKmNWHCBFhYWABgh+msXLkS06ZNw7x583DixAmGmri5uRm5ublYvnw5o0y4rZg+fTpMTU0BsAlEZ2dnDB48mEHEvnv3DlpaWsjPzwfA7uf69++PR48ekXP8HS9XGr8iNt3d3QmxmZiYCBkZGXTr1g3dunUj5ZhVVVWwtbWFmpoapKWlYWdn98tJfU5ODgQFBZGUlISbN2/ixYsXCAwMxNy5c/Hw4UNQFMVYuPrd7f6b0FYC3c7ODjIyMhg6dCiePn2KgwcPQkVFBfv378fMmTNha2uLsLAw3Lp1CytWrICgoCCGDRsGGxsbmJmZkeuWmppKbDdkZWWxdOlSVFZWoqamBkuWLIGRkRFZZOFER4kBOoRmxYoViI+Ph76+PnR0dBhELO03SVustBct+xbOY42KikJsbCzxQf/+/Tvxyx0/fnybfn/79u2wtrYmwXl6enpobGxEaWkpNDU1ISYmxlWBs3r1aqiqqmLy5Mlk0ZrGnj17sH79eoYKDmCTvZqamoQEfPbsGb5//w4Wi4UNGzbg6dOn+PDhA+zt7eHi4oKCggJyrhkZGeDn58eECRPIuf4JPHjwANHR0Th69CgA9vPft29f2NraYunSpXj37h3KysoQEhKCCRMmAABmz54NZ2dnODk5Mbw2v379iuDgYKSlpbXrfVBYWAgLCwsMHTqUvLc58ezZM0ybNg2TJk0CwA4Y1NLSgo2NDaPSgx5r0Nfj06dPRBULAGfPniXVHhcvXmTs4+HDh/8YOcY5tvxZO9HjjOrqaly+fBm5ubm4fPnyH/XPNjMzQ1RUFGOfdXV18PHxgaKiIpSUlHDs2DHcuHED3bp1w5gxY/Dq1SvGb+Tk5EBcXBx9+/blCpr9py1mkpKSoKCggM2bNxMRCMAelysoKCAoKIgE1baWT9FeFBQUYMyYMYz5VkFBAdzc3GBhYYFNmzZh7dq18PHxadUrnwceePjfA4+E5YGH/wJMnDgR3bp1Q1paGhlw3Lx5k3ge5ubmYuXKlfD29oahoSGjBPf27duQlZUlkyV6UFBUVARpaWlSStsS79+/x4ABA4gide/evZCWlsbUqVNJ6f6rV6/w6tUrxMTEMAY3xcXFUFRUxPPnz3H27FmGXUJtbS2mTp3KVTq+fv16SEhIIC8v7w+3HhjnDbB9rlauXAmKohgKAYBNxMrLyyMiIoJru69fvzJIxFevXiEqKgqysrJcRGxRUVGHB2DNzc3Yvn07HBwcEBAQQAaTeXl5oCgKM2fOJMfx5csXBAUFISgo6B8b8LW2n4aGBixZsgSampoYPnw4UWLSWLVqFUaNGvVHjnH//v3Izs5mKEcfP34MHR0dmJmZYfv27SgoKICvry969er1Uy/KP+WL2xITJkxAaGgobGxsIC4u/rcnxvfp0wcURTEITc7Jx7Jly+Ds7IyePXuS+wlgX0vO0DRO/7ns7Gy4urqSMr9feQy3Bs7zKSgoaFOY1sCBA7FixQpcvHgR+vr6MDExgYSEBN69e0dSiDt37szw6q2srISXlxcJpGovJkyYQCxeFi5cCBsbG9ja2iI2NpZYE7BYLOjp6cHNzQ1bt26Fu7s7bG1tyT2dnZ39x0KqfkRszpkzhxCbubm5MDExwe3bt3Hr1i0SHEQrdQG2NUVeXh4uXbrUppLRvLw8oh6nKyDq6urw+vVraGtr/1DF1tHt/tvQFmWwra0tUaJPmDCB0Y8dPnwYbm5uCAsLw65du7BmzRr4+vpi0KBB5PlbsGAB5OTkcOTIEVy6dAkLFiyAhIQEJk2ahMbGRnz+/JmEANKBcL+Dx48fQ1lZmREWWFxcDFtbW+jq6pLxQ0NDA/Lz83+bNFq2bBmOHz/OWNhdu3YttLW1GYrU79+/4+LFi+3qM3ft2oX58+cz0tGbmppQVFQEHR0deHt7cy1irV27Fvz8/IxF8Ldv30JMTAwURRH1L+d5Ozg4ICwsDEVFRRAQEEBubi6Sk5MhJSVFKjY+fPgAW1tbLiKWXjT7U2XymzdvJguknM/h9+/fMXjwYFhaWkJISAh6enowMDBAY2MjuX+mTZuGQYMGgaIoRon/hAkTYG5u3u5rXVhYCGtra0RGRjJ8ZysrK2FlZQV5eXmyeNDU1ITExESYmprCw8MDCQkJiIyMhJSUFG7fvg2ATRTb2tpCXV0djo6OOHLkCACQhUM/P79Wgzf/7rHSli1buPzkf3Y9f3Q8v0tu0tvv3bsX2trajAWLpqYmxMTE4Pnz5wgICICsrCx27NiBpUuXwsrKCuPGjeMiYk1NTaGqqkr6t3+HlcP69euhrKxMgtgAdvvR/cWdO3fQtWtX2NnZcY1DO4Jbt27BwsKCq+oQAI4ePYphw4ZBVlYW7u7uGDBgAKNyhwceePjfBY+E5YGH/3DQ5W60lxaN5uZmPHjwAFFRUdDT04OLiwtjosY5wejevTuSkpIY21dUVMDCwgIURSEmJoZrv3V1ddi3bx++fPmCGzduoEePHiRlPD09HRRFwd3dnZQ4A+wJJI3o6Gj4+/tDVFSUq/TaycmJ4cu1bNkyiImJcaW2/x2YPHkyFBQUkJWVhVmzZsHLywuSkpI4ceIE+c7p06dBURSSk5PJZ3PmzIGTkxO6d++Onj174tSpU2hubsabN2/Qt29fyMvL/5HBPj2obW5uxrZt2+Dg4AB/f39CumZlZUFQUBCurq5wdHSEvb09jI2N/9ZQBE5w/v79+/fx5MkThhpq/vz5sLW1xejRo7mUPJzn1pH9sVgsvH79GsLCwqAoCgsWLGB8t7S0FH5+ftDV1YW6ujpcXV1Ju/xqsvCnfHEB9qRXWloat27dwqdPn/D+/Xt4eXn90cT4lm148uRJ7NmzB6qqqvD19SX3C+dvLlq0CEOGDEFzczMXKfb27VskJibC3Nwc8+bNI58/f/6coR5q6zG2DOLraJiWr68vKIqCv78/+a2xY8dCSEgIJ0+exLNnz/DkyRP4+PjA0tKy3deMvi9owtfIyAhSUlL48uUL9uzZAysrK8TGxpJqgDt37sDIyAjm5ubw9vZmPHd/OqTqZ8SmnJwcgoKCMHbsWPL96upqrF69Gvz8/IwSSU605dl79+4drly5ggsXLpDvp6SkQE9Pj9Hf/6nt/tvQFmXw2rVrYWVlBWlpaS6i9NChQ/D09ERERATjncJisUgoTkuSNycnh2HjU15eju3bt/8RhdqdO3cgJSVFyEnOKht5eXk4ODgQYvF31XsVFRWIjIyEuLg4QkNDGcpUV1dXRpUKZ59eUFDAUEO2xI/ue87jvHPnDrFhaanU3LNnD1dbXrhwAebm5rC0tCQLSPR+EhISEBYWhtLSUsyePRsiIiKQlJRESUkJABALFpqIdXV1xZEjR8j2f8Kuh8bnz5/h5eUFPj4+rFixgnEezc3NePHiBXbt2kW85IuKirBq1SpCaNJVBoKCgmRMVF1dDYqiyJiwPbh27RoGDhzIdU3oMEkzMzOy8NXY2IhNmzYhLi4Ofn5+SEhIIBY5M2bMgKKiInbu3IkPHz5AR0cHJiYmhKg/evQoAgMDYWlpSUro/ym8evUKycnJkJSUZPjC/+p6/l3jty9fvmDlypXo3r077O3tMXr0aNjY2EBXVxcAW10sKCgIRUVF1NTUID09HWZmZhg/fjwhYktLSzFkyBCu0N5/GuPGjUNsbCwA4OnTp9i4cSOsra1haWlJ/Mdv3ryJ4ODgP3acGzZsgL6+PiwsLLhC6wBwBerxCFgeeOCBR8LywMN/OFJTU9G/f38AP57gfPjwgVHOe+zYMezfv5+U9S9YsAA2NjZYsmQJ+c63b98QExODu3fv/nCgQhMM8+fPR2BgIAnVWrVqFfr16wdfX1+y7axZs0BRFNLT0wGwQ37U1NQQEhJCfq+qqgr+/v5wd3cn59LU1ISxY8cy7BL+LpSUlEBbW5vh+1ZZWYm+fftCSkqK4eF68+ZNcozTp0+HrKwsVqxYgZycHKKSo3/n2bNniI2NBUVRHVZ8tTY4b2pqwtatW4kilia2Lly4gMWLF2PcuHFYvnx5h1Lqf/cY6XJYZWVlKCgoYMqUKWhsbERjYyPmzp0Le3t7jB07liuI7U9MKk+fPg1dXV0Gyco5sXz37h1ev379W2Tq7wzep02bBkdHR4bdxtu3b2FtbQ0tLa1W1d7tIUta+qItXboUZWVlANhKPGVlZfj6+jJ8Bel9slgsHDx4EPr6+ozFEYCdQD1gwAB069at1WC8th6jsbExQ5G6ZcuWDoVplZeXIygoCLNmzYKBgQH69OkD4F99l7i4OBQUFGBpaclQ6naUeKIJXz8/P/LZtm3bCBFLK2+amprw/v17cm3p/f4dIVWtEZsTJkyAjIwMREVFGeQ08C8itnPnzkhISOhQO3Di/v37iI2NhaysLFGf/Z3b/begLcrgu3fvQkNDo1X1ZX5+PoyMjBgLgd++fUNjYyOMjY2JhzNd5g4AgwYNgrOzM5e1R3ueh9buSxaLBXV1da6y/8rKSjg4OEBGRgb6+vpc3sZtwY/62RMnTiAtLQ3i4uJwd3fH8uXLsWHDBnh7e+PWrVuM7aZMmYLu3bvj6dOnv01ycZbM0+FjnNvs27cP69atQ1ZWFp48eYILFy5AW1sbHh4eKCsrw7dv39DQ0AA7OztiR7RhwwZQFAVRUVHG2IO+Th8+fICDgwP09PRIH8kZftce/Oj8vn79SkqnDx069MPvXb58GRRFQUJCgtiu0MjNzUXnzp2RnJyMpqYmZGVldXjM8aMF2aKiIpiYmHB5x9KkNb1taWkpbG1tyRj39OnTEBcX57LC2LdvHyZMmPCPkob0uX38+BEzZ86EmJhYqwtwP9oOAF6/fs045z+BmpoaXL9+Hb1790bv3r0xcOBANDQ0YNasWZCTk8P169dx79498v21a9fC3t4eAQEBWLJkCXx8fODj49OhxfSOomVbsVgskpmQkJAAOzs7hIeHY9SoURgxYgTU1NTIQgeN3zlOzm03btwIOzs7REdHE6KfHuO1FAvwwAMPPPBIWB54+A9Ca4OF2NhYODs7k3/TL/i6ujpSRs/50k9OTmYEaY0ePRqnTp3C+PHjYWBggJ49e2LBggVwcnJipOP+qFQbYJcHOzk5obKyEnV1dQgKCmIkrY4ZMwaSkpLQ1dUlIUeNjY1ISEiAqakpLCwsEBUVBTs7O5iamnKRJf/UoOX169eQkZEh6fH0uZeWlkJPTw8aGhqMiQeLxcLLly9hbGzMIIyqq6sRFRUFS0tLEoBWVFSEmTNndogA4rzur169QklJCVGONTY2Ijc3l0sR+6Mk238CixcvJn66Z8+excaNG9G5c2cSeNHQ0IC5c+dCU1OTkPIdwfHjx5GamgpPT08EBQVh8+bNJDDizJkzkJeXR8+ePcn3WyuX/3dMvubPnw8rKyviY0cf16lTp9ClSxcYGhqS0t7fufd/5It27949KCsrw93dHceOHSPBcnRb3Lt3D3379oWzszNycnIYv3n58mVISUlBXl6e629twcyZM2FiYsJo998J02pqagKLxUJ2djZ0dXWJAgYAzp8/j5MnT+LatWu/rV6uqKholfAF2ESstbU1BgwYwOWFx3mef1dIFb0PTmLz6NGjmDZtGlFVcqKmpgYLFiyAs7Pzb91fjY2NKCwsRGJiYqsejn96u/82tEUZ/DP15dq1a4m/8dy5cwmRM2rUKKipqZHfoPuX5ORkBAUFdfh4Oe/lkpISlJSUkMUdWhnHWX1QV1eHmJgYXLp0Cerq6khMTGzX/jjvzdzcXKSnpzNK/puamvDmzRsMHToUbm5uoCgKFEUxFo9KSkowdOhQRiVLW/Z3+fJlLo9XGj8qmU9MTIScnBycnJzQpUsXODg4ID09HRcuXICOjg66desGDw8P9OnTBwYGBoREe/v2La5du4ZZs2YxfKw5yZvy8nKMGDHit97jnNcvPz8fK1euxK5du4iqtKKiAk5OTrC3t8fhw4e5VLcAe6F86dKlEBERYVjT0Ni2bRtXmf3vErEtQRPhQ4YMwf379xEZGYn09HRGCNirV6+go6ODpqYmHD16lGF5VVNTg/Xr13N5g//TpGF2djYSExMhICAAAQEBRvVXa+QijZUrV8LNze0fqR6oqKiAp6cntmzZAoDdZ505cwbDhg3D7t27MXfuXMTExMDIyAg9e/Zsc2XRnwDn9aqpqSHWAs+fP8fw4cNhbm6OZcuWEeJ4z549cHd3/6Neyi2PY/369XB2dkZMTAwJ+OORrjzwwENr4JGwPPDwHwLOF/3NmzdJad2KFSugq6uLM2fOMCbvZWVlcHJyIiVjAH4YpDVo0CCcP38eu3btgqurK9zd3REREdHmEvYrV65AUFAQRkZG0NbWhrGxMRl4JyQkQEpKCsXFxZg6dSqio6PJdo2NjThw4ADGjx+PMWPGYMmSJf+YavNHcHd3R0hICMM38/v37wgKCoKMjAw8PT0Z3//48SPU1dWJVQK9XX19PVRUVFot++1oWfnMmTNhbW0NNTU1+Pn54eDBg+T3cnNz4ejoiKCgIK7Sp78bnIPM5uZm9OzZk+u8z5w5A4qisGrVKgDsdtq8eXOHJ5UbNmyAjIwMBg0ahMjISLi7u4OiKLi5uZHAkzNnzkBOTg5hYWGtHuu/C/fv34eAgAAXGVdQUICQkBBMnjz5tyeEmZmZrfqi0aTJs2fPoKWlBWNjYzg6OqKhoQG5ublkkeHx48fo168fHBwcGOWSN27cQFRUFDIzMzt07TjDtCZOnPjHwrRqamqwceNG6OrqMvoYTvxum3ISvnp6eujbty/52/bt26GmpkaCr36EPx1SxUku79u3D3369CGhLXV1dUhJSWG0KY26uro/VtLcES/g39nuvxE/Uwa3pr58+fIlzM3NERoailGjRoGfn5+oZYuKiuDu7g4nJyei+mpsbISnpycGDRrUoePjvEdmzJgBFxcXdO3aFaGhodi0aRMaGxsxceJE6OnpISgoCPPmzYODgwMsLS1RX1+PgIAAstDS3v0lJiZCVlYWpqam6NGjB2PRGWC/S8rLyzF16lQEBQWR9+vWrVvBx8cHbW1tLrumn+2PDtv6WdVKy5L5PXv2oGvXrrh58yZYLBa+fPmCIUOGwM3NDRkZGbhw4QJMTU2hqKhI7HnevHnDSJmvqKhAamoqxMTEGEFXM2fOZHzvdxdUJ06ciK5du8LU1BQGBgaQl5cni+YVFRVwdnaGo6Mjdu7c2WqfWV9fj3nz5rW6wAOwF5X+7vFbYWEhbGxs0KdPH/Tt2xedO3fG+vXrCRHLYrFgaWmJqKgoSEhIIDMzk2z79OlTrrHxP42UlBQoKSlhw4YNWLRoEQICAiAmJtaqRyznvUlnI9AVEz/Dj/r1n70HORXWLBYLnz59grKyMqZMmYLz588jKioKNjY2sLKygpKSEtasWYOmpiZUVFSQ7f6JsTvnuc2dOxfBwcFQVVXF+PHjSf4C55ihoaEBQUFB+L/27jyuprWLA/g6DSSKUJlJCg2oqIRCpRSZxxARMkuJTNc8Zh5CZCwZwjWFUDIPZSbzcJFQUikN5/f+0efs9xzlXqLR+n4+7+e+9tmd8+x99tn72Ws/z1pdunTJlz7gt4FYKysrtG/fXih0yhhj3+IgLGPFwLfTvCUjL7OyspCamorGjRujWbNm2Lt3L96+fYtHjx7B0dERFhYWQof9e4W0pk6dClVVVfTp00d4civdofjRDtX169cxZcoUzJ8/X/ibDRs2yEzBnzx5Mlq0aAEA/zqVqqArqQL/3+Zt27bBzMwMY8aMEV77+vUrunbtiv379wvrbd68GZcuXUJKSgp0dXUxYsQIYX1JcKFLly4y7/Mrpk2bBnV1dRw8eBCnT5+Gk5MTVFRUEBwcDCD7e9qxYwd0dXXh6en5Wz7zR0gfK5Lgr56enpBjWCwWC/tj3LhxaNu2bY6RCD/7ff/9998oX768MNVQYsOGDahTpw6aN28u5Hg7ffo0qlatCktLy5/bsHwmCcZ5enriypUrQvEL6Wn6eQkaSs4VY8eOFYKRDx8+xKZNm9C0aVMYGxtj+/btALKP6wcPHiArKwteXl6oUqUK/Pz8hEDt3bt30b9/f5iZmeGvv/7C7du30b59e4wcOfKHcpbm1q78LKaVnJyMgIAA6Ovrw8HB4Yf+Ji8kAd8GDRrIBHxPnDjxQ/vjdxWpkr4u+Pj4oGHDhqhSpQqaNm2K4cOH4927d0Iah28DEbm9ByscPzIy+NvRl5mZmdizZw/U1dWhrKwsM00dAI4ePYo2bdpARUUFlpaWaNy4MfT19X95pNqMGTNQsWJFHD16FJcuXUKnTp2goKCAd+/eITY2Fnv37kXr1q1hbW2Nnj17Cg8lnZyc4OXl9dPT6D98+IDu3bvj9u3bSExMxJkzZ1C/fn3hQQ6Q+zkoIyMDiYmJ6Nq1K0QiUY5rhTTp9vj5+aFChQrCdfXfSE+7XrhwIczMzJCeni6ct2NjY9G1a1fY2dkByD73VatWDQ4ODvDx8UGdOnWgrq4OQ0NDbNu2DUlJSfj8+TN8fHxQunRpjB49GjY2NsKIzt9h9+7dqFy5Mi5evIiMjAzExMTAy8sL8vLywkjqhIQENGjQAEOHDgWQ3SeaNWsWxo4di0uXLgn5befMmfPdQCyQ/8G4y5cvw8rKCm/evIGPjw8UFBSwYcMGobDk0qVLoampiR49egh/8+XLFzg6OqJdu3aF0s8EskdnSwqESjx69Ahjx46FsrKy0EcHZI9tPz8/qKqq/lBtBOm+w927d3Hnzh2Zc8v3+ha5/Tb9/f2hpqYmFPeTPCR0dnYWUqH91/v+Lt+2z8fHB5UqVcKuXbsQFBQEMzMzNGjQQBik8vnzZ+zZswd2dnZo1KhRvtZGkH7PpUuXwt3dvVBz4zLGijYOwjJWjMyZMwcaGhoICwtDQkKCsDwlJQU2NjbQ19dH6dKlYWRkBFNTU5lp/f9WSGvJkiUQiUSwsrKSmbb8KzfokilA0tVTJTmkpN//22qihS0lJQULFiyAkZERDA0NMWrUKDRt2hT16tUTqhhPnDgRFSpUEFIN7N+/H6VLl5aZnpeVlQUTE5Mcox1/lPS+j4iIgLGxsVCE5dixY1BRUYGVlRXKlSsn5PNMT09HaGhogd1cSHcwfX194e7ujn/++Qdz586FlpYWrl69KrMtU6dOhY2NTZ4/TzI9093dXchnmZGRIbOvNm/ejDJlyggV4CXTER0dHYtch1g6GFejRg0YGRnlKUiS23b5+PjAysoKo0aNgpmZGbp27YqRI0di5MiRqFWrFl6+fCmsu3HjRlSpUgXXrl3LceN8//59TJ48GRUrVkTdunWFQMPPtlFafhbTSk5OxurVq9GnT598/b6lA76SIIvEj/z+fmeRKkml8lOnTgEA+vXrh8qVKwupEd6+fYupU6dCJBLJVLBnRct/jQy+fPkyBg4cKBwvp0+fRq1ataCvr4/u3bvLVPoWi8WIi4vD2rVrMWPGDCxduvSXZ5m8ffsWVlZWOHbsGIDsEY8qKir/Gdz39PSEhoaGUJzrR61duxa6urpwdHQU8ldnZWXh4sWLqF+/PkxMTIR1v80JKpGcnAwbGxtUr1491+JL3wZgVVVVc83J/T2S78LX1xeNGzcWApSSfXz16lWIRCLcuHEDYrEYkZGRqFSpEhQUFBAUFITw8HD07dsX+vr6mD9/PlJTU5GQkIC1a9fCwsICffv2/a2Bo/nz56Ndu3Yyyz5+/Ah3d3eYmpri9evXALJHEWZmZgqjkLt27QptbW3Ur18fnp6ewvcxb948KCgoYPHixb/ctp8lGYQAZAdXnZycoKGhgY0bN0IsFuPNmzcYOnQotLS00KVLF4wYMQKWlpYFWqg0N69fv4aKigr8/f1llt+/fx8NGzZEqVKlcvymfubYlD6mp0yZAiMjI9SsWRMmJiYyhRr/7e/Wrl2LgQMHCv9+8eKF0N8FsvebtbX1dws85ifJd/bgwQMYGRkhPDwcQHbe3zJlyggzd8RiMWJjY+Hu7o7Bgwfn6fwnvU9+JNdtbrlfi1q/kzFWNHAQlrFiQDItyMzMLEfHTTLSJD09HXfu3MGuXbsQHh6ea5Gufyuk1b9/f9jb2/+WDsPevXtlOrqSNoSGhqJevXpIS0uDWCyGg4MDtLW1i0wnRTqf7tmzZ+Hm5oYePXrAzc0NL1++zLWKcVZWFpKTk7FixQooKirC3t4eLi4usLKyQsOGDX+56FNSUhLi4uLg4+MDsViM48ePQ0NDA35+fnj69CkaNWoEZWVlmRGEQMGOJp44caIwpfHFixe4fv06OnbsCHt7eyEQm5ycjHbt2sl07PMiLS0NDRs2xLhx42SWS3eWXV1dUbt2bZmghERROdYkXr9+jStXruDMmTN5qhwuvT0BAQHw9vaGj48PZsyYgWHDhqFNmzZYtmyZMApm3759aN26tcxoZHd3d2Gacm4jXDMyMoS8hfmVW/V3FtOSnmqf34HY3xHwzWuRKsm5p0OHDsJotKNHj8oUoPn69SsyMjIQGxuL9evXc1XmYk5yXEsqwL9+/VoYAda5c+dcz3nS8lrgD8h+cFCrVi3ExMTg0KFDMnk2U1NTsXr1aplA561btzBmzBhoa2vLpEX5EZmZmQgMDIShoSFq1qyZo10XL16Enp4eatasKdPOY8eOwd/fHwcPHhRySaelpaF169aoXbv2d0eZr1u37qcDsNLu3r2ba77nS5cuwcDAQEgnsHfvXnh4eKBKlSoyD8K8vLygra0tpNIBZIuq/a7f7cqVK1GjRo0c06T37dsHdXV1mTy4x44dQ40aNYScsUB2aoSWLVvir7/+QkZGBlJSUuDj44MWLVoU2qj6sWPHwtTUFN26dYO2tjZKly4tHJdv375FYGAgbG1tMWDAAKFAKFAw0+Zzuy5kZGSgV69ecHFxkRn0AAB9+vSBoaEh7OzshP25fft2lClT5odGwEqbN28eKlasiMjISLx79w5jx46FSCSS+T4lvn0YUb58eZliYRJJSUmIjIxEhw4dZNKO5bdJkyZh4cKFMssePHiAevXqISUlBSEhITLnoy9fvmD79u1ISkpCQkLCT8/cAXL2wyUjrCW+d7xL75PCGm3NGCv6OAjLWDHx8uVLqKurC6OdpDsIX758EUYwSPu2A/BvhbSkp0D9auDi6dOnUFJSypGH8NSpU1BTU8OrV6/QuXNn1K9fv8BGJPxboYN/Wy7drnXr1uVaxRjI3tcXL15Er1694OzsjLFjxwqdsbx2/JYsWYLhw4fjxYsXwoiPHj16YOLEiUI7e/ToAT09PaEqbUHfCIWFhUFLS0sYpStx8OBBODk5oWzZsmjatCkMDQ1hYGDwy6MoP3/+jKZNm8Ld3R2A7Ogxyf4OCAiAurq6UKG2OMlrp93LywuampoYP348unbtCmNjY7i7u+eaF61z587CqOKMjAw0b95cJlek5LtJT0/HlStXcgR2fmdu1fwsplUQv4VfDfj+bJGq3LapdevWuHnzJo4fPy6T//Xr16/YsGGDkCNP+jNZ8XXy5EmIRCJhOnNqaioCAgKEEe+S3/ywYcNw6NChPH2GJCUJkJ3j8OnTp0hMTIStrS3GjRuHChUqyBTJunfvHjp16oTQ0FCZ9zlz5kyOQFNucvvtpKSk4MCBA9DU1MyRXkQsFiMiIgJ9+vQRzpmenp5QV1eHsbExypcvDwsLC+HhRFpaGtq2bYu6devmyA975swZVK1aNdeg08/YsmULFBUV4eHhgfPnz+PevXto3749WrVqhaysLLx69QrlypWDSCSCt7c3ANnfooWFhZC/PL+qqUdGRqJx48aYN2+eTCC2X79+qFu3rjCDCcguslWvXj3ExcXJBLEmTJiABg0aCIUlJQ/Vf3dbf8SePXugqqqKqKgoJCcnIy0tDePGjYOCggLWrVv33SKHBREck/4Onz9/LpPXd/369ahfvz5mzZol/D4+f/6Mzp07Izg4WGY/njt37qfz16akpKBLly5Cv16SwknycE565HhuKQ9yexghFotx5swZdOjQAXZ2dnl6QJoXsbGx6NatGywsLLBmzRph+e3bt2FoaAhfX19UqFBB5rVLly6he/fuuHLlikz7f5T0uvPmzUPr1q2hra2Nrl27IiIi4ruzFqT/LigoCGFhYZzyhzGWKw7CMlYEfe/puZaWlkyOUUnn5/z581i5cuV/joKR+LdCWnltq3TgBsieet6xY0e8f/9eWOfJkyfQ0tKCjo4OdHV1c4yUzS/S+/NHp/p+Ow0pOTkZsbGxuHbtGmbNmiVTwf3fOll53Tbp0aWSlA6fPn2CtrY25s+fDyC7096jRw/8/fffhdbR27x5M/T19YX0GNL7+smTJzh27BhmzZqFdevW5XkEyre/B0nuNMn0VsnvQPLfjRs3okWLFv9ZzKmkOHbsGLS0tISCe8HBwShdurSQ+/Xz5884ePAgbGxscs2LNnfuXFSrVk2Yvi7x+PFj9O/f/6dGZ/6MgiimVVAKorjVtzd4kiJ3kgda5cuXl6kM/88//6BNmzY5Zk+w4i0uLg4eHh5QUFDAzp07AWQHVbZs2QJzc3Po6urC2toa1atXz9P159y5cyhbtizu3r2LcePGQV1dXbgGzZ07FyKRSMgXCmSfXxwcHGBjYyOcg3/mdyu97unTpxEUFITjx48LgeADBw6gTp06cHJykvk76d9DYGAgNDU1ceHCBYjFYty5cwcjR46EsbExAgICAGSfbxo3boyuXbvKvE9iYuJ/Fu76Ufv27UPVqlVRrVo1aGtrw8LCQiZYdfbsWRgZGcHExERIXSDZ/vHjx8sUkcwvPj4+MDAwgKenJy5cuIAdO3agZs2aaNmypcx3sXPnTtSuXVsIEkq248OHDyhVqhSOHDki876F0Qfx9/eHsbExkpOTZdo+fPhwqKqqYvPmzULqhMIyefJk1KlTB5qamnB0dBSO6wULFkBfXx/m5ubo378/mjVrBiMjI5nf0I/u02/XS0xMRN26dXHs2DHh4ZzkoUl6ejoWLFggDOiQkBT9+rfR4GlpaYiKivrlB6Q/68mTJ3Bzc4O5ublMCjMXFxeIRCKZEegpKSlwdHT8LSmopk2bBk1NTWzatAl3796Furo6LC0tZUaxS3xbQE0kEuV4KMUYYxIchGWsiJHuNJw8eRL79+8XikrMmzcPRkZGMvm3MjIyYGdnh+7du/9UJ1hSSGvhwoV5Co59W1xJOvcrkD0SsmLFirh06ZLM31SvXl2mQEhBBmDnzZuH4cOHy7Tpe76tllyvXj2h8NQ///yDKVOmQEVFRaaK8Zw5c4RA2K/43uhSsViMESNGQEtLCzNmzIClpSVMTU3zdOP7qyT7Z82aNWjQoIEQhBWLxUJ7du/eLTP6A/i5URPfHs9BQUFITEwUcgLWq1cPjx49klknKysL7dq1y3MV8OJo06ZNQuGxPXv2QEVFJce0PHd3dwwdOhQZGRm4cOEC9u3bh4iICCQkJODFixewsbGBjY2NMGry9evX6Nixo0xxv/xQUMW0ijvp3/adO3dgZGQEIyMj7N+/H3fv3oWpqSkMDQ0BZN8oJyQkCKPweEpk8fW9GRwfPnyAp6cnRCKREIj9+vUrTp06BS8vL4wePTpPMzEkn9GrVy+oqalBRUVFZnQkkF1gUUlJCf369UO/fv1gZWUlM8shr9chb29v1KxZExYWFqhfvz7atGmDU6dOISsrCyEhIdDW1kbnzp1l9oPks6ZOnQpra2uZ94uJiUGvXr3QtWtXYV98+fJFpn35cc18+/YtoqKicOXKFWRlZeHAgQNYvXo1/P39ERMTg7Nnz0JHRwdt27bFu3fvkJKSgvT0dJibm8PFxeW3t0dCeltnz54NKysriEQiNGrUSMj1HRgYiNOnTwPIPjdXq1YtR0X5Bw8eQE9PT2aUYUHI7buSBA4lD1wlM4YuXrwIOTm5QsmDLd3OwMBA1K5dG7t27cKuXbvQoEEDNG7cWOi3HDt2DDNnzkSXLl0wduzYPI0uffjwobDdM2fOFPqgQ4cORY8ePaCqqiozK+3ly5fo0KEDtm3bJizz9/eHvLz8T6U8KKj+puTYe/LkCQYPHgxzc3OhnkVycjIcHR2hpqaGGTNmYPLkybC2tpa5x8hrO58+fYomTZoIo5AjIyOhrKws0+f/to3A/9M5/Gz6CMbYn4WDsIwVIdIX8kmTJgmVs5WUlDBy5EicOHECY8aMQf369dGuXTsMGTIEzZs3/y3TvH8mGOrp6YmxY8cKQcndu3dDRUUF48ePl5n62q9fP7Rp00YmYBsVFZWn3Je/ysvLC5UrV8aePXuEfK4S30vbAGSPquzcuTN0dXXRrFmzHIHY/Khi/O3oUuk2Xbx4EZ6enkKl7MIsMAFkT0OVl5fHjBkzZJYnJSXByckpz4XXJMeGZLuOHz+O2rVrC69v2rQJ2tra0NDQwLp163Ds2DEcPnwY9vb20NPTE/7+T5gKtnXrVjg7O+Po0aMyI16A7JFZc+fOxf379yEWizFx4kTUr18fOjo6aNOmDYyMjBAfH48zZ86gV69eKFOmDOrVq4cGDRrAxMSkQI6vgiqmVRJ4enoKUzPV1NRQv359rFu3DkFBQahRowZ0dXVhYWEBCwsLmUJvHIgt3nx9fXOMqnr//r0QiP3eVPq8fu+zZ8+GSCRCxYoVhXyu3wYahg4dCmdnZ8ybN++X82z6+/ujatWquHDhAoDsB6ZlypTB4cOHAWQHmA8cOABlZWV4eXkJfycZkbZ48WKYmpriw4cPMu8bEhICOTm5HA/rCur3MGHCBFSuXBktW7ZE2bJlYWFhAV9fX5w9exa6urqoWbMm2rZtiz59+kBPT++X+3H/RXq7ExIScPHiRdy4cQOZmZmIiYmBqakpbG1tERkZCQC4cOEC1NXVYWtri5CQEJw6dQoODg4yD38L2t69e4XfwpcvX2BsbAw7OzshPQKQnY/Y29sbK1asKLT0KwcOHMDatWtlimzFx8dDX18fjRo1kil09W0O9h8hFotx69YtiEQibNmyBaNGjYKysrKQL3rXrl0oVaoUOnTogLi4OADZ5wwHBweZh3NJSUmYP39+kSvaKOkLSPcJHj58iMGDB8PMzExIP5CVlQUPDw9YW1vDwcEBHh4eeToffdv3iImJQcOGDQFkp3OQ7lslJSUhMDBQJq0DkLfifoyxPxMHYRkrghYuXIiqVasKT7RXrVoFkUgEV1dXREZG4sCBA+jSpQv69OkDLy+vAi00AAAjR46EiYkJpk+fjsTERLx48QKBgYFo0qQJmjVrBmtra1y6dAlr1qxBx44dcy2GUZAd+JCQENSsWVOmHQkJCTIFCr6d0g5kd6iUlZWxf/9+PH78GPr6+jA2NhYCsXFxcVizZs1vq2L8b6NLJe+5f/9+REdHC3k1gcLP8bh+/XooKipizJgxOHHiBMLDw9GuXTs0atQoT20bNWoU6tatK9PBDQ8Ph6GhoUyOt0OHDqFbt25QVlaGgoICmjdvLhOYLuz9UlDu37+PUqVKQSQSCVNvgewb1Hbt2mHQoEEQi8VYs2YN1NXVcfHiRQD/D7RIRnrExcUhLCwMa9euRUhISIE+LCmoYlrFWUBAACpUqIDr168jPj4eb9++ha2tLaysrLB582a8evUK8+bNw8yZM+Hv718oD7vY7xcfH4+uXbtCRUVFGKUo8fr1azRv3hwikUhmZNvP+vY39+HDB9y+fRu9e/dG5cqVhaDcv123f+WaPnLkSKHY4r59+6CqqioEPJKTkxEXF4eMjAzMmjVLmBnk4eEBe3t7iMVinDhxAkpKSlizZo3M8X7hwgU0adKkUPKD79mzB1WrVsW1a9cgFouRkJCAIUOGoHXr1vDz88PZs2fRuHFjVKlSBffu3RP+Lr9/r987z2ZmZuLAgQNwcHCAvb29EBC/e/cumjZtirp160JXVxc2NjaF9nDnzZs3qFOnDjp27Ijw8HAA2QGypk2bwsLCAleuXMHZs2dhb2+PHj16CH9X0OfA9+/fQ1lZGSKRCDNnzgTw//2ekJAAAwMDmJiYfLdQ3M+YM2cOlJSUoKysLFzbJZ+1bt06lC9fHq1atYKlpSVatGgh83BOcgxIRtIWFdJ9v+fPn+P9+/fCYI7Hjx9j8ODBMDU1lXnI/+3svJ/5zqVrahw/fhyfP39GYmIiGjRoAHd39xyjiW/evAlLS0vhvAgAy5YtQ6VKlTgAyxj7IRyEZayIef36NVxcXISE+vv27YOamhqmTp0KVVVV9O7dO9d8RAXRGZYeneHj4wMjIyNMnz5dCErGxsYiPDwc7du3h7m5OczMzCASiTB+/Ph8b9v32glkjxRs1qwZsrKyEBMTg7lz50JLSwu1atWCo6OjsJ70TcmQIUNQvnx57N27V3i/R48eQV9fH02bNhW2Gfj9VYy/N7r08+fPcHJywsqVK7+7rYVBLBbjwIEDqFWrlpBuol27dnm+Ubt8+TIaNGgACwtjajwiAABcRUlEQVQL4eZg3759aNasGYCc+TPv3buH6OhovH37tsgEpgvanj17UKZMGUycOBFnzpzB6dOnYWtrK+SAzcjIwODBg7FgwQIA2elCypUrJ0ytS0lJyTWndEHfZBeF47momjJlipC3UXKuevXqFUxNTaGtrS0zGjIv1aBZ0ZDbb+DevXtwdXWFmppajlyOQ4YMgZ6eHlq0aJGnz5O+7j19+jTHCL0uXbqgcuXKQoAHAGbMmIEXL17k6fOkSRcL3bJlC86dOydTXC4zMxMbNmwQCmEOHToUIpEInTp1goqKikwQa/78+ZCTk8OCBQtw/vx5PHv2DO3atYOlpWWhPNhZuHChMM1f8vmxsbHo2rUr7OzsAGRPca5WrZpMKpafPQf+27Z97zXpc8jSpUsxa9Ys4XMPHTqEdu3awd7eXkiJlJ6ejmfPnuHp06cFmg80t31x8eJFNGvWDJ06dRKOyTNnzqBNmzYoV64ctLS0YG5u/kN5tvOznXfv3hX6MZJaBNKBWHV1dQwcODDPnyk5twcHB0NeXh7y8vLYvHlzjmDkiRMnsGzZMowfPx6bNm0q8EEbP2P+/PkyM8B8fHygra2NevXqwdDQEMePHweQHZgdPHgwmjdvLuRGl/Yzv6GzZ8+iZcuWuHjxIsaPHw9VVVW8evUKYrEY06dPR4UKFWS+J0kxYwcHB+G38PnzZ9SrV09IDcMYY/+Fg7CMFTGpqakICQlBQkICrl69ijp16gj5j5YsWQKRSITWrVvnGogtCNI39ZMnT4aRkRGmTp0qU2kXyM5rumLFCtSqVQs6Ojoyo07zk/RNh2RqYkhIiJBzsnbt2hgwYAB8fX2xd+9eaGho5ChItGDBAhARGjduLCyTdOqio6NRoUIFtG/fPkeRr98ZQPrdo0sLwvv37/H48WM8fPjwl2/UoqOjhYB3WloagoKCfjjI8CeOpMzMzERgYCCqV6+O6tWrw9jYGB07dpQJhPfq1Qvr1q3D4cOHZabWZWZmYuPGjTKjJ1nRITmvzJo1C02bNhUeTEi+29OnT0NZWRlt2rRBUFCQzN+w4kX63JWWliYUbwKyc3G6uLigYsWKiIiIENbp3bs3jhw58svfube3N/T09FC2bFmMGDFCyJ0uFovRtWtXlC9fHosXL4aVlRX09fV/67li4cKFkJOTQ6lSpYRjGMguRlmnTh14enoKy+rWrYtSpUoJ/SLpdixbtgy1a9dGpUqV0LBhQyEIChR8DktfX180btxY+A4l18KrV69CJBLh1q1bEIvFiIyMRO3atWFhYfHTnyW9TRs2bMDEiRPRp08fHDlyBB8/fvxu2yT/9fLygrq6Ory9vYUCXED2QzpbW1u0b99eZrRfbp9bEKQfegPApUuXYGRkBCcnJ5kc/zdu3MCjR48KNFD8bZ/z06dPwgPN27dvo0qVKrC3txe2QbLvk5KS8vQb+vZ3/vXrVyQnJ2P27NmQl5fH2rVr/7MoaVG8zoeHhwt5n79+/YrDhw+jUqVKCA4Oxo4dOzBo0CAoKioKD44fPXoENzc31KtX75fyr545cwZOTk6oU6cOKlasiCdPngiv3b17F3369EHdunUxfPhweHt7o02bNjIp4CTHWEpKyi9sPWPsT8NBWMaKIMnFff78+XB0dMSnT58AZKcl6N+/P+zt7Qu8E/y9Gzxvb28YGxtj2rRpOTrKQHanuF69eli/fn1+N1Fmn8yfPx/jx4/HgwcPAGSnFhg7dix27twpTD2KiYmBkZGRkPMOALZs2QIFBQXMnj0bNWrUgL29vcxnfPz4EaamphCJRL80iuG//O7RpYXhZ49R6fWvXLmCy5cvo2HDhrC2tkZAQAAsLCwwY8YMLF++HDt37sTGjRsxbdo0PH369Hc3vdiKi4vDw4cP8eLFC4jFYmzYsAGnTp2CWCzG+PHj0aBBA5QvXx5r166V+Rs7OzssWbKkEFvO/sutW7cgLy8vUwkaAEJDQ9GtWze0bdsWNjY2Mik7WPEhff5bunQp7O3t0bJlS2GaPpAdeHB1dYVIJEKHDh3QqFEjGBsb56k4o/Q1JCgoCLVr18bu3buxYcMG6OjooEuXLjKjbocOHYoWLVqgc+fOvz2wmZqaioEDB0JVVRX379/Hhw8f8Pz5cyGXqiTfp1gsRvv27dG5c2chVZCEpI/y8OFDXL58GREREQVexV3a3bt3c/29Xrp0CQYGBjJFK0+fPo2GDRvm+eG6l5cXNDQ04OPjgx49ekBHRwejR4/O9Vwg2U+bN29GuXLloKGhIYwo/vr1q7DPwsLCYG9vj2bNmuUozpbfpPubq1atQrdu3XDr1i2ZdS5evIhatWrB1tYWZ86cyfEeBdFHlm7n7NmzYWtri7p166Jv377CsXnnzh1Uq1YN7du3FwYGSP/dz/TlpLfpy5cvQq5XCR8fH8jLy2P9+vVCINbV1RXR0dE/u2kFLj09Hdu2bUPz5s3RqVMnTJkyJcco16lTp0JBQUHosz948ADz58//5f7wxIkTIRKJYGpqKlPXAsiehbB69WqYmJigW7duec45yxhj0jgIy1gRJD1Fr2XLlkhMTBSmwEjSFAAFNxpB+nMSEhIQHx8vsyy3QGxmZqawjpeXF6ysrAos75RkdMeOHTvwzz//5Hg9MzMTCQkJ6NixI6ysrIR2Hjp0CD179hTSAERGRuYIxKampsLV1RU3b94skEDo7xxdWpRJ35RMnDgRbdq0wdOnTxEVFQUDAwOIRCJYWlqiY8eOaNasGaysrGBmZob27dsXi4B0QZPkIFRRUUFwcDCA7NyKRkZGqFWrFu7fv4/4+Hj8888/aN++PczMzErkcVXSBAQEQFFREV5eXrh27RqePHkCR0dHzJ07F/fu3YNIJMLJkycLu5nsF0yaNAlVq1bF7NmzsWXLFigqKsLFxUUY2fj582ds2rQJAwcOlMkJ/6Pnwfnz58uM9goPD8fEiRPh7+8vLLt8+TJMTEzQqVMnmUDsu3fv8i3lS1RUFDp27AglJSXUrVsXRkZGaN68uRDwDQoKQnx8vLD+sGHDUKZMGZlALACZbQMKd2aE5Pvz8PDA+fPnce/ePbRv3x6tWrXK0S7pwlI/IzQ0FFpaWsJso9DQUCgoKMj0FYcMGQJ/f3+ZfLB2dnYoVaoUgoODcffuXaxduxYGBgZo1qwZtmzZAiC76Or48eMLbR8mJiYiLCwMVatWhZubW45gcEBAAMqVKwdra2tcu3atUNoIZAcHK1WqhJCQEBw+fBht2rSBmpqaMLr4zp07qFmzJpo1ayYMqvhZ3w4ysLGxQa1ateDp6SmzXyQFY4cMGQILCwvUrVu3yF/bpfOXb9myBa1bt0bZsmWxfPlyAJB5mGBtbY3+/fvn2Ka89AMl77F//37s3LkTXbt2RZs2bYTCb9L90m8HonC/kzH2KzgIy1gRdvHiRSgqKsLAwAA6OjowNDQs8M6UdMdvzpw5sLGxgaamJiZNmiRzc+bt7Q0TExPMmDED7969A/D/TkuvXr3g5ORUICO0du/ejWrVqsmMmkhISMCDBw+E9ixfvhx2dnYyBQomTpyI6tWro1GjRlBSUsLgwYMRExODyMhI1KlTB02aNMH06dNhaWmJ5s2bC/uloDtiJX2q/YMHD9C6dWuZ0QjXrl2Dubk5GjdunGM6pQR3iP9/bEjvmzZt2siMJnn69Cm0tbWhq6uLqlWrwsLCAs2aNStWI6z/dJI0KjVq1ED16tVhZGSE1NRUPH/+HDo6Or+l2AsrHAcPHkT9+vWFFDnHjx+HkpISypQpIzOSDpANgv5ovyAmJga9evUSfucvX74UCgjNnj1bZl1JILZr1644cuSIzGv5me7iyJEj2LNnD8LCwoSHuf/884+QC1Z65sPw4cNRrlw5BAcH482bN+jatSv69OmT7238Gfv27UPVqlVRrVo11KtXDxYWFr90vv32bwIDA2FpaQkA2LVrF1RUVISZDsnJyQgNDcW8efNkcqT6+fkJxRwXLFiAxo0bo3PnzpgzZw66d+8OHR2dHFPaC6LvsXfvXiHVxoQJE9CvXz8A2cdErVq14OrqKtO327p1Kzp27IghQ4YUWt/oxYsXMDc3F/rDoaGhUFVVxYYNGwD8f2ZbdHQ0nJycfrqd3x7HU6ZMQZUqVbBs2TIcOHAAFSpUQO/evYX9BmSPpO/bty9cXFyK/LX92+1LS0tDQEAA6tevD0NDQyG1g+Qc169fP+E3nhfS+//bfXLixAk4OTmhTZs2OHHihLB8586dMg+AGGPsV3EQlrEi7vr165gyZQoWLlxYqFNgpkyZgsqVK2Pr1q3YsmULTE1NYWVlhb///ltYZ/LkyahRo4bQ+czKykJ8fDyqVq2KK1euFEg7/f390bZtW4jFYjx48AALFy6ElpYWDA0NhY6bZBq7ZD/Onz8fVatWxeXLlwFkT38TiUTo2bMnHj9+jGfPnsHR0RHW1tbo0qVLgeeY+1PMmzcPrVu3lknBAWR30qOiolCvXj20aNEiR+6tonKzXVRIUnAAwMCBA9GtWzeZfZSWloY9e/Zg/fr1OH78uMwoFFY8/PPPP7h48SLOnj0rnIcmTZqEBg0a5MhVzYoHsViMkJAQYfTX0aNHoaamho0bN+LSpUsoXbo0Bg4c+Mvfr3QBpg8fPuDq1auoVasW2rVrl2Pa8pUrV1CjRg1MmjTplz4zr20E/h8ouX79OlRVVdGtWzc8e/ZMeH3MmDEQiUTQ19eHnp5egRZk+lFv377FjRs3cOXKld82o2XNmjV49+4dNm7cCAcHB5w5cwYqKipYs2aNsE5wcDA8PDyEGUr+/v6wt7eHqqoq9u7di5EjR8LY2BjLli3D3bt3AWQ/9DQzM/sthdd+RmpqKvr16weRSIRevXqhbNmyMqmipAOxR44cwadPn9CpUychRyhQMH2ybz8jJiYGVatWRWxsLP7++2+ZfOtfvnyBn59fjpRJP9pOST9I8hs4evSozEOaK1euQEFBAerq6rC1tRUKqQGyOUqLw7V97ty52LRpE4Dska/bt29HkyZN0K5dOyGvclZWFiwsLODm5panz5De7xs3bsSQIUMwdOhQYeQ3AJw8eRKdO3dGixYtsGrVKjg4OEBbW5v7+4yx34qDsIwVM4XRmTp69CgaNGggFEA4e/YsFBUVYWxsjBYtWuDYsWPCuuvWrRM6jJIbqbS0tHxpV27Bt40bN6JGjRpCMn1nZ2csWrQIa9asgZaWlkyACsgeCeTi4iJM3du3bx/U1NQwbdo0lC9fHl27dhVSGkjf3BWHTm1xExoaCpFIhPLly8vcfElIiqINHTq0EFpXPPj5+aFSpUrQ0dGBubk5rK2t0aZNGxw/fhxxcXHfnQpZVEfJsP92584d9O/fH5UqVSoWuf/Y90lGNH/69Anm5uaYM2cOgOygu7a2NkQiETw8PH75c96+fYtatWoJaQ4uXLiAmjVrYuDAgTlyb967dy9P54fvBS3+670kr2dmZuL9+/cQi8XC9fbatWtQVlbOEYg9duwYDhw4UGweKOUloCP9N5IHxQ8fPsTbt2+hqakJkUiEwMBAYZ3U1FS0b98eAwcOhFgsRnp6OhwcHKCgoCCMMAUgjDQEsvebvb09OnToUCgPN7OyslCnTh0oKChg8+bNALL7XZK2hIaGwtzcHFWqVEGdOnXQuHFjoV9WEO2V/g5CQkLw/PlzvH//Hm3btsVff/2F8uXLCwFYILsmQrdu3WRGqf6oKVOmwNjYWCh6m5GRgXPnzglB9mPHjkFNTQ07d+7E/fv3UapUKfTs2VNmBCdQPB5Sf/nyBe7u7jLH8NevX7FlyxbUr18fNWrUQLt27dC/f380aNAgT9/5tymvNDQ0MHbsWPTq1QtNmjSBl5eX8Hp4eDhcXV2hr68Pe3v7Aj3GGGN/Bg7CMsb+0+3bt4WpikeOHEHFihWxefNmnD9/HpUqVYKFhYVM/jFA9kYrPzou0p3h169fC6M4gOxAsKurK7Zs2SKM5rh37x6aNGmS4wYzNTUVISEhSEhIwNWrV1GnTh2h6rKvry9EIhFat24tUzmYO2K/7ns3oWfPnoWCggKcnZ2FAmrSHj58yAFDKd/uxydPnuDevXvYsWMHpk2bBnt7e4hEIpibm0NVVRUNGzZEmzZtsG3bNgB8LBd3GRkZiIqKwoQJE3Dnzp3Cbg77BdK/xcePH0NHR0cY2fbhwwe4ubnhxo0bv+38d/36dZiYmMDV1RXx8fE4d+6cEIjNrRBTXgsIHTlyBFu3boWfn99/5oX/NlDSokULmJubY+PGjXjz5g2A/wdiu3fvniP/68+2szgKDw/HmjVrZHLhSlKUDBgwABcvXsSRI0dgZ2cnpLDas2cPXr58iUePHqFPnz4wNTUVAvxAdp7hLVu2wMbGRiawWdAjSxMTE+Hk5IT27dujTJkyQsGtjIwM4XuNiYnByZMnERQUVKBBd+ljc/LkyahevTpWrlwJILtonUgkkgnkJScnw8HBIc+FdLds2QIrKyvY2dkJgdj4+Hi8ffsWiYmJsLKyEr7D9PR0GBgYQE5ODpMnT/6VzSwQuaVOev/+Pby9vSESibBz504A2YHYHTt2wMzMDJUrV8aJEyd+eST55s2bUa9ePWF23q5du1CqVCnUrl0b7u7uwnoJCQl4//59ia7FwBgrPByEZYzJyK2zmJ6ejoSEBKSkpMDW1lYmd1yrVq2go6MjU8E5v0l33KZOnYqmTZtCVVUVtra2WLBggcyIVbFYjKSkJDg6OqJt27bf3T4gOy2B9FT4VatWoX///nnuRLPcSe/L6OhonDp1Ck+ePBH2+/HjxyEvL48hQ4YIN97fKuk32j9Cej8GBATAy8sLY8aMkRmZHhkZCTU1NVy7dg3Hjh1DQEAAxo0bxzcUJUxRnILN8u7jx49QU1PD4MGDERoainbt2qFVq1bCte93nf+ioqLQpEkTmUBsnTp10KlTp1wDnD/Ly8sL2traaN68OSwsLP51tLb0+axXr14QiURYuHAhOnToABMTE4wePRovX74EkB2IVVVVRdu2bb97jSiJLl++DDk5OZQuXVomCJuYmIgDBw5AR0cH1atXh7GxMbp06YKvX7/i+fPnqFChgpAm6vXr1xg9ejTMzMwwb948ANkBsLlz52LQoEEFmvZK+jsPDQ3FnTt3kJGRgdTUVAwcOFAmECvxbZqEgu4LzJo1C5UrV8aVK1dkZpY4OztDU1MTo0aNwrhx49C6dWsYGBj8UkB7z549aNWqFWxtbWXSkLx79w6GhoZCsPLz588YPnw4zpw5U6z6Rs+fP5f59/v37+Hl5ZVjROzq1asxatQoYR/+6L7s1asXtm/fLrNsyZIl8PHxAQAcOHAAampqWLx4MaZOnYoKFSrIBNIluP/PGPvdOAjLGBNIdzRiYmJyjKz68OEDtLW1helWHz9+RN++fREUFFQonZS5c+dCXV0dR48excePH9GuXTvUrFlTuMn78uULFixYAHt7e5kiXN+2VXJjO2jQILRs2RKJiYlITU1Fhw4dZEb4ckfs13070qlu3booX748GjZsiPbt2wud8tDQUCgqKmLo0KEyo5BZTl5eXtDU1MT48ePRo0cP1K1bF2PGjIFYLEZsbCzq16+fa+Xo4nSzxtifQnKdOXz4MCpXrgw9PT20bNky36bESgKxgwcPRkJCAk6fPo0uXbr88vVu06ZNUFdXx/Xr1wFkjzgTiUQyeeRzK7To7e0NJSUlTJgwQVg2f/58mJmZYdSoUUIg9uLFi999sFpSxcbGwtfXFxUrVsSYMWNyvJ6WloaYmBi8fftW2KcZGRnw8fGBtra2sO/evn2L0aNHw9zcHIsXLwaQfT343UH+fyP9nU+aNAlaWlrYuXMnEhISAGQH5FxcXFC2bFkcP34cycnJ6N69O0aNGpXj7wvKx48fYWNjgx07dgDIThNy+vRpuLm5Yfv27ULRqM6dO8PHxydPAW3p41ksFiMoKEgIxEpGxD5//hxaWloYMGAANm7cCHt7e5iZmRXo9/erDh06BJFIhJMnT8osj4uLw/DhwyESiXDw4EEAsikpfmbbJIH8ffv2ySx//vw53rx5A0NDQ+H4v3PnDjQ0NFC2bFksWLDgVzaNMcb+EwdhGWM5TJo0CdWqVYOmpiYsLCwQExMDsViMuLg42Nvbo1u3bli5ciXs7OzQokWLn346/avEYjE+fPgAKysrIUgaFhaGsmXLCkUaJDes69atg4eHxw91hi9evAhFRUUYGBhAR0dHmMrHfg/pzvPq1atRsWJFnD59Gk+fPsXWrVthbW0NIyMj4UYxLCxMqN7Mcnfs2DFoaWkJReV2794NJSUl4SYRABo3biyMeAI4BQFjBU0sFufpdxcfH48nT57k+5TYqKgomJiYoGvXrkhKShKW/8o1fcqUKZg+fTqA7BF9KioqWL9+PYDskXuSbZG+LowePRpycnKoWLEijh8/LvN+8+fPh7m5OcaMGSOTD/ZX21lUfW+bYmNjsXjxYpQuXRp//fWXsPzr16+5VpoHsnOTNm/eXEhDI3mfcePGQUtLS2a0YEFfH2bPng1NTU1ERETkSFfx5csXuLq6QiQSoXHjxtDV1S3UUf/x8fGoVq0apkyZgoiICPTq1QumpqZo2rQpqlevLgxQyK2w3M+6evWq8F7SgVjJyO8TJ05AR0cHRkZGaNu2bbHLW3r37l30798f6urqCAsLA/D/tp84cQIikQgikUhmZk9ecsCOGzcOpUuXxr59+2R+U2FhYdDW1hYe/EdFRaFHjx7YtWtXiTyfMMaKFg7CMsZyFBvQ0tLCgQMHcPToUTRv3hza2tpCh/DAgQOwt7fPkbA+vzst33a+Pn/+DDMzM7x+/TpHRdrU1FRs2rQJ9+/fl/mbH+kMX79+HVOmTMHChQsLdFpeSXfw4EHs3r0bQPb3079/f3h6esqsEx4ejpYtW2Ls2LHCcXXt2jXe//9i06ZNsLS0BPD/QIfkd5CYmIjIyEhYWVlhxowZhdhKxv5s0rnI16xZk6N4Tm6+vebl93nw8uXLcHFx+eWiURLOzs4YNWoUQkNDoaKigrVr1wLI3q6lS5dizpw5Mtvo5+eHChUqoGPHjqhUqRKGDRuWo5DgokWLULduXfj6+n73c0sC6e06evQotm/fjh07dgj76927d1iyZAkqVKiAmTNnCutKXt+/f3+OQHWvXr3QtGlTmWWvX7/GsmXLCm3k5Pv372Fubo5NmzYJ7YmMjMTYsWOxePFiYT/8/fff2LZtW5EovObv7w81NTWoqqpi4sSJwkhOZ2dnDBgw4Ld8RmRkJEQikZBzVjoQa2NjI+TLf/PmjVC8Dii6fdXv/U6fPn2KAQMGQE1NTWZE7I0bNzB06FBs2bIlT9skfTy/evUKTk5OqFy5sjCyFgCuXLmCOnXqYN68eXj+/Dnat28PFxeXYjWamDFWfHEQljEmCAoKwpo1a4SOH5A9orRVq1aoU6eOMK3w8+fP+PjxY4F1/KQ7cJ8/fwaQXfTA0NAQjo6OUFNTg5+fn7DOo0ePYG1tjb179/7yZxfVTm1xY2lpCR0dHeHfXbt2haOjY471xo8fj2bNmuHr168yy/l7yN3WrVvh7OyMo0ePyjyIALIfqCxatAiHDh3i/cdYIbl//z5Kly6NuXPnwtvbG+XKlcOjR4/+8+8KY0Sb5DPzGtyU3q4dO3agWbNmUFJSEiq6A8CnT5/g6OiIKVOmCMv2798PkUgkTBseP348mjRpgrlz5yIxMVHmM3bs2FGiAyTfpmaoW7cu9PX1YWxsDHNzc2GksiQQW6lSJZkHmpKCa8rKyli8eLGQU/XVq1do2LCh0L/79jsujH364cMHNG/eHHPmzMGePXvQu3dvWFhYoGnTpmjYsGGOB7WF1c5vvXjxAg8fPhT+nZWVBWtra5lj+lfEx8djxowZUFBQwOrVqwH8PxBraWkJOzs7/PPPPzJ/U1QfSEi3KygoCIsWLcK0adNw69YtZGRk4O3btxgwYABUVFSwZcsWXL58GU5OTnBxcRH+Lq/9Fy8vL5iamqJDhw7Q0NCAsrIy9uzZAyB7H3t4eKB69eqoXr06mjZtWuxGEzPGii8OwjLGAGQHN6tWrQqRSISJEycC+H9HJD09HZaWltDW1saFCxdkOij53fGTfv+lS5di2LBhwgiP0NBQaGhowMHBAUB2Ry0pKQkODg5o27Ztkeis/+kk39+DBw9Qu3ZtjB07FkD2d9m4cWNERETIdLC3b98OMzMzIS8c+3f3799HqVKlIBKJEBAQICz/8uUL2rVrh4EDBwrL+PfAWMGLj4+Hn58flJSUoKqqKuS4/rfAgvQ11tfXV8iDWRB+JgAhfX0+e/asTI7HN2/ewMHBAQ0aNEBQUBA+f/6Me/fuoX379jA2Nha2f8uWLXB2dkb//v2FAAkAjBkzBiYmJrkGYoGSfz7z9fVFlSpVhCruq1evFqblf/jwAUB2IHb69Olo166dzPeWnJwMX19fWFpaQktLC8OHD8e5c+fg4uKC4cOHF6kg07hx42BkZARFRUVMmjRJCBr37dsX48ePL9zG/YekpCRERkaiQ4cOeU5f9b3vIiEhATNnzoRIJBIeYojFYuzatQsNGzYs0GK4v8OECRNQqVIlODg4oGrVqtDX18dff/2F1NRUvH//HhMmTIBIJIKuru5vCYgGBgaiXLlyuHLlChITE/Hy5UsMGzYMpUuXFmZlJSQk4N69ewgLCysSo6wZY38ODsIy9ofKLXj68uVLmJubQ09PD0+fPgUAmdGuDRo0QI8ePQq0nRKenp7Q1NTE1q1bharNiYmJWLx4MUQiEWxtbdGxY0dYWlqiUaNGQgeupN+oFRfJycmYMmUKTExMcP36dXz58gUmJiYwNzfHoUOH8PHjR8THx8Pa2hrdunUr7OYWK3v27EGZMmUwceJEnDlzBqdPn4atrS0aNWrENxSMFQGSolTlypXD3LlzheW5XZ+kgw7r16+HqqqqTI7nokK6D7Fu3TrMnj0bIpEIKioqOHToEADg2bNnsLW1hZ6eHsqVKwdTU1O0atVKuD57eHhAQ0MDHTt2ROvWrSESieDh4SG87+jRo2Fqagpvb28kJycX7AYWotevX6N///7CyODDhw9DVVUVM2bMEEbFfvz4EVlZWYiPj4dYLEZ0dDQiIiLw4MED4X1iYmJw+PBh6OrqwtHREdWqVYNIJMKFCxcKa9ME0sfP3bt3ZdoNAG3btoW3t3dBN+uHicVinDlzBh06dICdnd0v9zmXLFkiUwgWkA3E+vv7A8jebydPnixWfdu///4b1apVE2bTAdmFWS0sLGTSTjx48AC3bt36LTmwly9fjlatWsmcT9PT0zFgwACoqqrKpCaQKE77lDFWvHEQlrE/kHTn9+TJk9i/f7/QIXn16hUMDAzQrFkzoUCSdI6kwuikBAcHo1q1akJeWiC7M/X27VsA2QW1Bg0ahLFjx8LX15dzuRYBO3fuxMCBA/Hs2TOkpKQAyB61Wbt2bQwaNAhAdhC9ZcuWMDAwQOXKlWFiYiITQC9Ko3WKsszMTAQGBgrT6kxMTNCxY0d+EMFYIfn2IefHjx9x69YtrF27FuXLlxcKVv0bPz8/qKqq5qjsXdRMmjQJVapUwZYtW7Bw4UI4OjpCUVFR6FN8/PgRd+/eRXBwMK5fvy7smxMnTkBTUxPnz58HkJ0rfNeuXVBSUsLUqVOF9x84cCBcXV3/uOvB/v378fr1a1y7dg21a9cWUs1IHjxXqVJFGCHs7e0NXV1dqKqqQl9fH+3bt5d5r4SEBOzcuRM9e/aErq5ukekbffs7SUxMxM2bN9G+fftiURg1LS0NUVFRvxw0/PTpEwYMGIAyZcrgwIEDMq/FxcXB2toaIpEIy5Ytk3mtqF7bv23Xpk2b0LBhQ3z69En4HX/58gVDhw6FkZFRrvvtV2fZrVq1CqqqqkL/U/IZR44cEYp+nT59+pc+gzHG8oqDsIz9YaRvZCZNmoTq1avDyMgISkpKcHFxwatXr/Dy5Uvo6+vD1NRUmDopLb87fpI2Sv47Z84cWFtbAwDu3LkDX19fNGzYEGpqakLV929v0Ipq57SkE4vF+Pz5Mxo1agSRSISRI0fir7/+EirQ7tu3D3JycggMDASQ3REPDw/H+vXrERwczFPCfkFcXBwePnyIFy9eFPlCHYyVVNLBgxs3buD69evCA5GPHz/C19cX5cuXx6xZs4T1pk2bJkzDBv4/AvZ35DXPT69fv4aenh62b98us8zNzQ2Kiooylc2lZWVlISgoCHp6ejnyf2/YsAFqamq4du2azPpAyXww91/BphUrVqBjx45CPvxt27Zh0KBBGDlyJDIzM7F8+XJUrFgR4eHhiI6OFqarm5qa5vp+RfnasGfPHrRq1Qrt27cvdg8RfyZomNu6jx49wujRo6GqqoqQkBCZ10aNGgUTExO0bNkSYrG42PwO1qxZg1u3bmHjxo3Q0dFBXFwcAAjf7YsXLyAnJydz7vtZ39vvb968gYmJCfr374+PHz8Ky69evYrRo0dj1apVRfI3wBj7M3AQlrE/1MKFC1G1alVcvnwZQPZTY5FIhK5du+LVq1d49eoVGjVqhDp16uDdu3cF1i7pDpUkL+ju3buhqamJXr16oX79+ujTpw8WLVqElStXQiQSyUxjKy6d05Lu5MmTqFSpEtzc3ODl5YXatWsjPDwcsbGxGDFiBFq2bInbt2/n+rfF5aarqCuqhToY+xN4e3tDXV0dmpqa0NHREa61nz59wtKlS1G2bFn06NEDNjY2qFu3rnDeW7t2LRQVFYv8CFggO92AsrJyjrY+ffoUenp6UFZWRlhYGLKysnKcj06ePIkyZcoI+0Vy7b558yY0NTURHh4us35JPJ9J91cCAwMxY8YMbNy4EefOnROWjx49GjVq1AAApKSkwMnJCTNnzhRe79Onj0xBqKysLFy5cgX169fHmDFjcv2sotxPOnv27G+Zjl5USR/H9+7dQ3R0tPDvly9fwt3dHeXLlxdGkqempqJ3794yI2SL6vcnvW2rVq2CnJwcHj9+jNjYWKipqcHV1VVm/du3b0NPTw83b97M0+dJ74ft27dj5syZWLFihfAAJyAgAM2bN0fHjh1x69YtXLt2DQ4ODujZs6fwdyXxGGOMFX0KxBj747x584bu3btHy5YtI1NTUwoJCaHp06fT1KlTaeXKlTR27Fjy9fWlgwcP0rRp06hSpUoF0i6xWExycnJERLRy5Up68+YNjRo1ilq3bk2zZs2i/fv3k6enJ1lbW5OWlhbduXOHzM3NqXTp0sJ7iESiAmkr+3dt27al0aNH05s3b2jEiBFUoUIFGjZsGPXp04cAkEgkosjISDIwMJD53omI5OXlC7HlJYf0PmWM5S/p89jx48dp3759tGPHDipbtiwtWbKEHBwcKCgoiGxtbWno0KFUo0YN2rx5M9WsWZOOHj1K8vLylJKSQgkJCRQYGEhdu3Yt5C2SJTlvS///OnXqkK2tLQUGBlKrVq1IXV2diIi0tLSoUaNGJC8vTw4ODnThwgUyMTGh0NBQSkxMJENDQzIyMqLWrVvTypUrydPTk5o0aUJEROrq6lSpUiVKT0+X+fySdj6T3p+TJ0+m1atXU9OmTenVq1ekqKhI/fv3Jx8fHxo1ahQdPHiQNDU1qXLlykREtG/fPjp16hRZWlrSx48fKTk5WXhfOTk5atasGTk5OdH169cpIyODFBUVZfpG+d1P+vaa/iOvSZa3atVKWKagUPJuUyXb7u3tTdu3b6evX7+SoaEhrV27lvT09GjKlCmkqKhInTt3ptatW9P79+9JQUGBOnToQESyx01RIv29njt3jhQVFSkoKIi0tbWJiCg4OJi6d+9OSUlJ5OrqShUqVKDZs2eTqqoqGRgY/PTnSe8HHx8fWrFiBbVs2ZJu3rxJ1apVo169epG3tzeVLVuWVq9eTU2aNCEtLS1SU1OjAwcOCO9TEo8xxlgxUJgRYMZY4UhNTUVISAgSEhJw9epV1KlTBytWrACQXZFXJBKhTZs2MiNgC3J0oqenJzQ0NLBjxw48e/ZMWC49Pe3Lly9wdHSEtbV1iRwhU9wEBwdj4cKFePTokbDs4MGDaN++PSIiIgBkF2eYOHEibGxsIBKJoKGhgffv3xdWkxlj7Lfz9/fHihUrsGDBApnlPXr0QMWKFXHy5Mlc/05yjf12en5RIH2NzcrKEq7FQPbIXXNzc0yaNAmfPn0CkD1is0uXLti/fz/at2+P/v37w9PTE2XLloWOjg4UFRUREBCAdevWoU2bNrCzs8O2bdtw8uRJtGvXDk2bNv1jZkRcvXoVVlZWwujXp0+fYvbs2ahevbrQL4uJicGcOXOwfPlyZGRkYNq0adDX18ejR4+wYsUKmJmZITQ0VOZ9161bh2bNmgl5YwuK9LGyYcMGTJw4EX369MGRI0dkpoV/S3pU44ULF4QCrCWF9PaFhYWhQYMGOHToEM6cOYMmTZqgfv36uHTpEoDsc8DevXsxfPhwTJ06VRitWVR/E9LbdvnyZSHnakBAgMx6ly5dQsOGDVG7dm3o6OigdevWwrkkr/34e/fuoUWLFkKxubi4OEyZMgVNmjTB8uXLhfWuXLmC27dvl+hR1oyx4oODsIz9oSQdn/nz58PR0VG4eVq1ahX69esHe3v7Qglubt++HdWrV5epopqZmYkXL14AAJKTkxEYGIjWrVvDyMjolztw7PeYMWMG5OTkYG9vj1WrVgnLx4wZA21tbaGT/vbtW1y4cAHa2tqoX79+kb2pYIyxn5WWloYmTZpAJBJh2LBhOV7v0aMHNDQ0cPjwYZlzX1GdXgzknGLcrVs32NnZYdGiRcLyWbNmoVmzZmjUqBHc3d1hYmICY2NjAICLiwssLS3RsmVLXLhwAR8/fsSiRYugoKCANWvWICAgAIMHD0bp0qVhZGQEGxubYpcPNK9Wr14t7E9JASEgO5+lp6cnWrVqlSMd1K1bt+Do6Cg83Hz69CmaN2+OTp06Yd++fcjKysKHDx9ga2uL3r17F9qx5eXlBQ0NDfj4+KBHjx7Q0dHB6NGjc33IIN3G1atXo0aNGnmeol4Ufds/jY6OlnlIIxaLYWxsDF1dXVy6dEk47qWP/6IaNDx9+jR27NgBABg+fDhcXV0REBCAihUrws3NTVhPsg9SUlLw6NEj3L9/P08BUeljZd68eWjbti3s7e1lHja8ffsWI0aMgJWVVa4PIUr6eYUxVvRxEJaxP5SkIzNo0CC0bNkSiYmJSE1NRYcOHbBr1y5hvYIObs6YMQP29vYAgAcPHmDVqlUwMDBAtWrVsHz5cojFYqxYsQKenp5Cx62odk7/NOfOncPAgQNRoUIFODk54cGDB8jMzESXLl0wcuRImXWTk5OFY4s7xIyx4ii3AFdCQgIcHR1RvXp13LhxI8d61tbWOarXFweTJk1CtWrV4OXlhSVLlkAkEsHT01M4jx87dgweHh5wcnLCiBEjkJaWBgDo3r07evfuDS8vL5lr9dKlSyEvL49ly5YhOTkZsbGxiI2NLdKFo3631atXQ1lZGRUrVpQpRAZk58wtVaqUzPI1a9bA0tISLVq0kAnO3rlzB9bW1mjQoAGqVKkCIyMjNGrUSAhmF3QgNjQ0FFpaWsLD9NDQUCgoKMj0LSWk2+bn54cKFSogODi4wNqa36S3b8mSJXB2doa2tjYGDx6cY10TExPo6ekhPDy8yA8skBRhtbW1hZWVFTp27Ijy5cvj7t27EIvF2LRpExQVFTF16lThb3L7Ted1OzMyMnDmzBmIRCKUKVMmx+/n6tWrEIlEOH/+fJ7enzHG8hMHYRn7w128eBGKioowMDCAjo4ODA0NC+zmJ7fO1/r166GrqwtnZ2cYGhqiV69emD59OubPnw95eXm8fv0aycnJwvocwCs8uVWsjo2NxYkTJ6Cjo4MGDRrA09MT69atg7u7u9AZlj6+ivqNBmOM5Ub63PXixQs8e/YMb968AZA92qtFixbQ1tbGnTt3AMieJ4vbeW/Pnj3Q1tbGxYsXAQAnTpyAgoIC5OXl4eLiIjO6UbJtSUlJMDc3h7y8PFRUVNCoUSOZIpoAsGzZMigoKGDSpEkyI0GL2/75Ed/bpp07d6Jy5cpwc3PD/fv3heWPHz9GvXr1ZIp0nTp1CrVq1YKSkhKOHDki8z5v377F5cuXsXTpUuzatUvoGxVEf+7bIG9gYCAsLS0BALt27YKKigrWrl0LIPsB7IULF3K0y8/PD6qqqti7d2++t7egSO+XZcuWQVlZGe7u7tDW1kbVqlURHBycY2RwzZo10adPn4Juap59/PgR9evXh0gkwvz584Xlqamp8Pf3h4KCAqZNm/ZbP3PdunVwdnZGYmIirl27Bnl5eTg7O+P58+fCOjExMcLIYsYYK2o4GzVjfzhzc3O6dOkShYSEkKqqKnl4eJCCggJlZmbma8J66ST+YWFhlJycTGXLliUnJyeKj4+niIgIcnd3JxsbG9LR0aHz58+TqakpiUQiKlu2rPA+XMSpcEh/f/fv36ekpCSqXbs2aWhokK2tLd26dYt8fHzo4sWLtG7dOlJQUKBSpUqRhYWFzHFV0oqtMMZKPgDCuWv69Ol06tQpevz4MTVr1ozMzc1p6tSpdOzYMerQoQN17tyZDh48SHp6esLfy8nJ/WvxoqIkKyuLUlNTady4cWRubk5Hjx4lZ2dn8vPzIw0NDercuTNpaGjQlClTSEVFheTk5Oiff/6hQYMG0bVr12jChAmUnp5OGzZsIH9/fxo1ahTVrl2biIjGjRtHX758oSNHjlCZMmWEzywO++VnSH/XJ0+epE+fPlFKSgoNHDiQ+vbtS+np6TRlyhSKj4+nHj16UNWqVWnBggWkrKxM5ubm9PjxYypdujS1bduWzpw5Q7a2trRu3TrS0NCgpk2bEhFRlSpVqEqVKmRqaip8blZWVoEUHpIUSEpKSiIVFRVKSkqicuXKUXh4OLm5udGCBQvI3d2diIiOHj1Kly5dIh0dHaHQmJ+fH3l7e9PmzZupW7du+d7egiLZL1evXqV79+7R33//TdbW1gSA7OzsaMmSJaSgoEAdO3YkRUVFIiJ6+fIlZWVlFWazf4qcnBxpa2uTpqYmnT59mmrUqEH9+vUjJSUl6tu3L4lEIho5ciQlJibSihUrftvnXrhwgSZPnkyLFi2iiIgIsrKyos+fP1Pv3r2pZs2atHDhQlJSUhJ+H4wxVqQUdhSYMVb05PfICenRAZMmTUL16tXRpEkTlC5dGiNHjsTDhw+FqYySIlwdOnSAnZ1diRwhU9xIf39TpkyBrq4u6tatCy0tLXh6euLevXsAsr+7q1evYvz48RCJRGjSpEmRzn3IGGM/Y+bMmahYsSJOnDiB27dvo3fv3hCJRLh9+zYAIDExEVZWVihXrhyePn1ayK39Mbmdoz9+/IinT58iLi4OxsbGWLhwIYDs0ZqampoQiUSYM2eOsH54eDh69+4tUxhnzZo1qFGjBry9vWVGrEl/Zkm/PkycOBE6OjowMTGBkZERatWqhZiYGADA1q1boaamBpFIhB49emDo0KHIyMiAt7c3GjRogEqVKqFVq1bYv38/nj59irp166JHjx4y07ALc/8tWrQIQ4cOBZA9I0ZdXR0ikQiBgYHCOqmpqXBwcMDAgQOFtp45cwZVq1bFnj17CqXdv5u3tzcePnwo/Hv//v3Q09NDnTp1ZL6rlJQU2NraolmzZggJCZEpdgcUv1leb9++hYODA9q0aSPkiAWy608sWrQIrVu3ztPx+b0+/9atW6Gjo4Nhw4YhJSUF586dg7y8PEQiEVxdXTFw4MBcc+syxlhRwEFYxlihWbhwIapWrYrLly8DyC76IRKJ0K1bNzx58gRJSUnYs2cP2rRpgyZNmnARriJmyZIl0NTUxKlTpwAA/fv3R+XKlXOd/nXixAkhuF/Sb7QZYyXf+/fvYWNjg0OHDgHIzomqoqKCjRs3AoDwIDExMRHu7u7FIhAgfW199eoVvnz5gtTUVGHZ7du3Ub9+fURFRQEA/vnnH4wYMQIXLlwQtu/t27fQ1tZGuXLlZIKwwP+LLvn4+ODJkycyr5X064Kfnx/U1dWFPKnbtm2DSCTC4cOHhXWCgoKgrq6OqVOn4tGjRwgKCkKVKlVw4MABbNmyBZ6enpCTk8PWrVvx5MkTaGtro0+fPkKaiMIUGBiIihUrCv25vXv3QkNDAwMGDMDFixdx5MgR2NnZ5Uh5JZlSXhKEhYVhyJAhMtv38eNHDBgwAKqqqpg6darMa1++fIG9vT1q1aqF8PDwwmjyb/X06VM4OjrC1tYWmzdvRmZmJqytrTFhwoRfftASGRmJV69eySwLCAiAjo4O3NzckJqaKqQmGDdunJAahu8XGGNFEQdhGWOF4vXr13BxcREKNezbtw9qamqYNm0aKlSogB49euDUqVOYNWsWPDw8uAhXESIWi/H161c4OTlh5cqVAIC///4bqqqq8PPzAwB8/foVX758yfG3/P0xxkqCjx8/om7durhx4wYOHz6McuXKYd26dQCyA7CrVq3ClStXZP6mOARiAWD69OkwMDCAgYEBJk+ejBcvXgAAHj58CHl5eUyfPh3nzp1D+/btYW1tnaOY1s2bN6GrqwtbW1vcunVL5r3Xrl0LeXl5YV+VVN8Gf8aPH4958+YByA5QqqqqYv369QCAT58+CeutX78e1atXR8+ePdGjRw8sXbpUeO3z589YsWIFlJSUcP78eURFRUFZWRnTp08vgC36v28DaWKxGM+fP4eNjQ0WL14MIPv3ceDAAejo6KB69eowNjZGly5dhIfpmZmZJTJAJtmm4OBgISCdmJiIAQMGwNTUFGvWrJHpB6WkpGDcuHHF5tzwX54+fYquXbuiYcOG0NLSgoGBgZD3Nq8B2JcvX6JMmTKYMWOGEFyV2LhxI+Tl5eHu7o6PHz/izJkzkJOTw4gRI3IEbRljrKjgICxjrFCkpqYiJCQECQkJuHr1KurUqYMVK1YAAHx9fSESidCpUydhajtQfG5gS7r09HRkZmbC3Nwct2/fRkREBMqVKycEYCUBCMkNCGOMFWe5BYvi4+NhZ2cHNzc3qKmpyQQVY2Ji4OTkhIMHDxZkM/NMOjgiGY25c+dOuLu7C5XPHz16BADYsGEDFBUVoaurCzMzMyGo9m2A5caNGzAyMoKbm5tQnExi3759Jfp6Lr0vTp48iczMTHTp0gXe3t44efKkTKEqsViMhQsXCsFLAFi+fDlEIhFKlSqFmTNnyrx3fHw8nJycMHLkSABAdHR0oe1L6SKpADBjxgxUqlQJHz58EJalpaUhJiYGb9++zRGsL0mkt+nhw4do0qQJOnToIIwaT0hIQN++fdG8efMcgViJkvKbePPmDQ4dOgR/f//fNoAiIiICderUwcyZM/H69WtheUZGBurVq4dy5coJv6HQ0FCIRCJ4eHiUmH3KGCtZOAjLGCs0kpu3+fPnw9HRURgNsmrVKvTr108mB2xJn6pYlF29elX4/ytWrEBYWBgAoGfPnqhXrx7Kli2LLVu2COvExsbCysoKGzZsKPC2MsbY7yQdgH39+jWSkpKEf69YsQIikQj9+vUT1ktMTISDgwPatm1b7AIAoaGhmDhxIrZt2yYs27FjB9q0aQNHR0c8e/YMQPZotzt37gjb/L0AS1RUFIyNjeHm5oa7d+/meL247Z8fId1XmTZtGvT19fH06VP4+/vD3NwcSkpKMgH7hIQEODo6YubMmTL7Y968eahVqxaMjY2FQJ7E4MGDYWdnJ7OsoPflunXr0L9/f5w5c0ZmuZmZGSZOnPjdka4lefQrABw8eBAfPnzAnj17YGtri06dOgkpKOLj4+Hs7IyWLVti4cKFJfL4z83v2s7IyEjUqFFDJhD75s0bjB49Glu3bpU5D4WFhckM4mCMsaKkZJUfZYwVK5KqvQ8fPqTExEQSiUSUlpZGx48fpw4dOlBoaKhQRVpSZZYVrJiYGHJ2dqbRo0eTh4cHTZgwgapWrUpERBMmTKBKlSqRjo4Oubi4EAD69OkTDRo0iLKyssjV1bWQW88YY79GUtV++vTp1Lp1a7K1taWRI0cSEdGYMWNoypQptGvXLurRowd17dqVOnbsSK9evaLQ0FCSl5cnsVhcmM3/YZcuXaKJEyfSpk2bhErtRETOzs40ZMgQ+vLlC40ZM4ZiYmJIS0uL9PX1heuz5Fr+LSMjI/L396cbN27QjBkz6NmzZzKvy8vL5+s2FQZJX+X27dsUHR1Na9euJS0tLbK2tiYlJSXS0dGh6tWrU3p6Oj169IicnZ3p3bt35OPjQ/Ly8pSVlUVERJMnT6ZDhw5RVlYWLV++nG7cuEFERElJSXT//n2qVauWzOfm974EIPPfxMRESktLo3bt2tHw4cMpKCiIiIjat29P0dHRlJaWRnJycsL6EpLfU0kBQNgmHx8fGjZsGO3evZu6d+9Orq6ulJSURLNmzaLr16+TmpoarV69mlRUVOjJkyclbl98z+86Nlu2bElBQUG0detWmjx5Mq1atYpcXV0pJiaGBgwYQAoKCpSRkUFisZisra2pYcOGv+VzGWPsdxPh26sjY4wVsEuXLpGlpSXVr1+fvn79SkpKShQVFfXdGztWcD5//kyBgYE0ZcoUSk9Pp0uXLpG+vj4BoPT0dNq5cyctXryYvnz5QlpaWpSWlkbp6el0+fJlUlRUpKysrBJ5o80Y+3MEBweTl5cXzZkzh27fvk0nT56kSpUq0alTp4iIaMeOHRQVFUWfP38mPT09GjNmDCkoKFBmZmaxuo4tX76c1qxZQ1paWrRjxw7S0NAQXtu1axfNnz+f2rVrR4sXL/6p971y5Qr5+fmRv7//HxF4Wrt2LQUHB1NWVhaFhIQI+/HevXs0bNgw+vDhA8XFxZG2tjYpKipSeHj4d6+X0dHR1K9fP4qPj6emTZtSqVKl6NmzZ3Tp0iUqVaoUAcj3h9RisVj43lJTU6lMmTLCa0eOHCF/f3+6ffs2NWrUiLp06UIuLi7k6+tL48ePz9d2FSWzZ8+mlStX0tGjR0lXV5fKly9PREQHDx6ktWvXkrKyMk2bNo2MjY0pOTmZlJWVhSA1DzL4OVFRUTRlyhR69eoV1alTh/bv30+Kioq8LxljxQYHYRljRUJUVBSFhISQqqoqeXh4FMsb2JJG0qE9ePAgubq6kpqaGjk6OtKKFSuEddLT0+mff/6h7du3k0gkourVq9PAgQNJXl6evz/GWLEkHXQiyg7CJiYm0tChQ+nr168UFhZGnp6eVLVqVTp9+jQREWVkZMiMIC3KD6C+3T5pK1asoF27dpGBgQHNmzeP1NXVhdfCwsKoTZs2edouyfXk3z67uPp2m06fPk2DBg2iuLg42rdvHzk4OAivvXv3jl6/fk23b98mHR0dMjMz+8/r5Z07d8jJyYlq1KhBffv2peHDhxNRzmMuv7dt+fLldOnSJXr37h2ZmZnRqFGjqEaNGvTx40d68+YNjR8/nrKysigiIoJ69eoljI4t6eLj46lXr140cOBAcnZ2ptevX9PDhw8pMDCQbGxs6NmzZxQZGUlJSUnk7+9Purq6RPTvv0P2775+/UpfvnyhChUqkEgk4v4mY6xY4SAsY6xI4g5V4ZHcLEv+++rVK0pNTaWwsDDy8/OjFi1a0Lp16/71PYpyAIIxxr5HejSVv78/ffr0iY4ePUp2dnbk7e1NRNkPn06ePEkTJ06katWq0cmTJwuzyT9FOvBz8OBBevDgAVWpUoUMDAzIxMSEiIiWLFlC+/fvJz09vRyBWKK8n99L4kg16f35+PFjKl26NNWsWZOePn1Ktra2pKenRzNmzKCmTZt+9z1+ZH/euHGDhg8fTo0aNaKJEydSvXr1fut2/JdJkybRpk2baObMmfTlyxfasGEDVahQgSIiImRGxp49e5aio6Np5MiRf0wfLiEhgQwMDGjQoEHUrl07Wrt2LT179ozEYjH9888/NGvWLCpdujRduXKFVq5cyYHX34yD2Yyx4oaDsIwxxgTSndl3795RuXLliIiobNmy9OHDB9q+fTsFBASQpaUlrV69moiIvLy8qGPHjmRpaVkib7IZY38G6fPf1KlTacWKFaSnp0dv3ryhypUr07lz56hs2bJElD0KMSwsjPr160f9+vWTmSFQVEmfn729vSkwMJC0tbVJLBZTVlYWTZo0iTp27EhERL6+vnTw4EHS0NAgf39/qlChQiG2vGiS3p+TJk2igwcP0vv370lPT488PDyocePGZGNjQyYmJuTt7S0EufN6nYyOjqbhw4dT3bp1acaMGdSgQYPfuj3fc/PmTerXrx+tX7+eLCws6PDhw9S3b1/y9fUlNze37/7dn/QwfdOmTeTl5UVZWVk0fPhwsrW1JRsbG3J2dqYyZcqQv7+/sC4HDRlj7M/GVwDGGGNEJHtjsGDBAurZsydZWFiQm5sb3bt3jypXrkwDBgwgV1dXCg8Pp9atW1P79u0pKCiILCwsiIg4AMsYK7Yk57/Y2Fh69OgRRUZG0qlTp2j37t2UkpJC7dq1o69fvxIRkaKiIllbW9Phw4dp6dKlhdnsHyY5P69atYqCg4Np9+7dFB4eTl26dKFr166Rp6cn7dmzh4iyCy9aW1tT5cqVSVVVtTCbXSRJFwzdtWsXbd26lRYsWEC+vr5kZmZG3bp1o8jISDp58iRFRUWRr68vXbp0iYjyfp00MjKi1atX09u3b4Wco79b//796cqVKzLLEhISKCUlhSwsLOjAgQPUp08fWrRoEbm5uVFKSgoFBQVRampqjvf6UwKwRESDBw+mGzdu0LVr12jhwoVkY2NDYrGY3r17J5NbmajkFSdjjDH2c/6cqyNjjLF/JbkxmDJlCm3cuFEILPj5+VGnTp1o37591KhRI3JxcaGaNWvS/v37qXTp0vT333+TgoICpyBgjBV769evp2nTplG9evWofPnyVK5cOTI3N6ddu3ZR7969ydramk6fPk2lSpWiUqVKUfPmzYmo+KRgSUpKEgKuzZs3p0OHDtHMmTNpwoQJdPfuXZo0aRKVKVOGOnToQDNmzCjRuVx/hWRfhIeH06lTp2jixInUqVMnIsrexzVr1qRhw4bRqVOnaM+ePdSyZUvS0dEhc3PzX/rcZs2aUWhoKCkpKf3yNnzrzp07VK1aNTIyMpJZXr58eapfvz6tX7+evLy8aMmSJTRs2DAiyk6TEBoaSo0bNyY9Pb3f3qbipFatWkRElJycTDdu3KCFCxdSXFwczZo1q5BbxhhjrCjhdASMMcYEoaGhNGnSJPLz8yNzc3M6cuQI9e7dm2rVqkWfPn2i48ePk4GBQY4b8j9p2iFjrOR6+fIl9ezZk27cuEGRkZHUrFkz4bWoqChydnamrKwsunfvXrE45+UWPH306BHJy8tTWloadejQgcaNG0djxoyhLVu2kJubG5UrV46Cg4OpXbt2RFQyc7n+DrGxsdSyZUuKi4sjb29vmjJlivBaQkICDRw4kGrWrEmrV6+mGzdukKGhYbEI1BMRbdiwgWrWrEnt27enL1++kIWFBd26dYsWLlxIXl5eRESUlpZGXbt2pTJlytCePXs4SE/Zv5WIiAjy9fWljIwMOnToECkqKhabhzSMMcbyH18tGWOMCSpUqEB2dnZkbm5OR48epYEDB9KiRYsoICCAiIg6d+5M0dHRMjdbAIpFMIIxxqSJxeIcy2rVqkUhISGkra1Nw4cPp5cvXwqvGRsbU0BAABkbGxeLoKR0ADY0NJSCg4Pp3r17pKOjQ3Xr1qXz589TjRo1aPDgwUREpKamRh07dqQ5c+aQtbW18D7FYVsLQ5UqVSgkJIQ0NDQoJCSEoqOjhdfU1NRIXV2dHj9+TERETZo0IXl5ecrKyiqs5v6rzMxM4f8/ffqUDh06RBMmTKCwsDBSVlamI0eOUI0aNejQoUO0bNky2rhxIzk6OtKrV68oODiY5OTkcv09/WlEIhE1b96cZs2aRUePHiVFRUXKzMzkACxjjDEBj4RljLE/1Peml8bFxVHFihWpQ4cOZGpqSrNmzaLMzEyytbWlu3fvkpmZGR06dKgQWswYY7+H9PnvwIEDFBMTQ2XLliUDAwNq3bo1vXnzhmxsbKhs2bK0b98+YaqxtOIyum3y5Mm0atUqqlatGj179oyWLVtGw4YNo507d5KPjw8FBweTmZkZde/enQwMDGju3LkkEomKzfYVtlu3btGAAQOocePGNH78eGrSpAklJSWRvb096evr04YNGwq7iT9sxowZZGxsTCoqKrR582a6desWLVmyhNq1a0fPnz+nESNGCDlptbW1yc/PTwg08sPYnDiNB2OMsW9xEJYxxv5A0jcGd+/epeTkZFJRURFyuj1//pxatmxJS5cupZ49e9LHjx/J3d2d3NzcyNramm8qGGMlwsSJE2nXrl3UpEkTUlBQoPDwcFq6dCkNHDiQXr9+TXZ2dlSuXDkKCgoiLS2twm7uD5GkDwBAL168oP79+9OiRYuofv36FBAQQF5eXjR//nwyNTWlVatWUUREBFWsWJFKlSpFN2/eJAUFBU5B8JOio6OpX79+FB8fT02bNqVSpUrRs2fP6NKlS1SqVKkiuz+l+wJHjx6lbt260fnz58nY2JguXbpEy5cvp3v37pGvry/Z2tpSZmYmpaSkUKlSpahMmTJExOmIGGOMsZ/BQVjGGPvDSN8M+vj40NGjR+nt27dkaGhIFSpUoL179xIAcnJyordv39LYsWMpICCAsrKy6MyZM8K0Qw7EMsaKG+nRnXv37qVx48bR3r17ydzcnDZt2kTDhw+nTZs20YABA4iI6M2bN2RoaEhdunQhf3//wmz6D5E+N8fHx9PHjx9p8+bNNGfOHGG7V6xYQR4eHrR8+XIyNDSkT58+UWxsLA0ZMoSLLP6CO3fukJOTE9WoUYP69u1Lw4cPJyKijIwMUlRULOTW/buAgABKT0+n1NRUGjdunLD84sWLtHLlSiEQa2NjI/N3RTW4zBhjjBVVfAfNGGN/GMkN0+LFi2nDhg20evVqevr0KRkaGlJISAhFRkaSSCSiMWPGkKamJs2bN4+UlJQoLCyMA7CMsWJp27ZtREQkLy8v5L98+PAhWVlZkbm5OYWEhND48eNpzZo1NGDAAEpKShKqxcfExND69esLs/k/THJunjJlCtnb21OzZs3o6NGjQm5SIqKxY8eSr68veXp6UlhYGHXu3JmGDx/OAdhfZGBgQCEhIZSenk5RUVHCPi+KAVjpMTgfP36kOXPmkLu7O/3zzz9ERELu2ubNm9PYsWPJwMCA+vXrR9evX5d5Hw7AMsYYYz+H76IZY+wPIX3T9fXrV7p48SItXbqUWrZsSREREbRp0ybasGEDtWrVirKyssjW1paOHDlCp0+fpiNHjgh53zgAyxgrTkJCQsjDw4MmTpxIRCRMnVZSUiJNTU06cOAAubi40KJFi2jo0KFElF3Ias+ePfTp0yeqXLlykS6qRCRbZGzXrl0UEBBA/fv3p0GDBtHjx4/J39+fXrx4Iawzbtw4mj59Op05c0bm2sAB2F/TpEkTWrduHd28eZOmTZtGDx48KOwm5fDixQsheLp7925SVlam/fv3U+vWrengwYMUGxsr87DC3Nychg4dSsOGDaMmTZoUYssZY4yx4o/TETDG2B9AevTqs2fPqHr16mRtbU3e3t4kEomod+/etHjxYho+fDhlZGTQhg0bqHbt2tShQ4dc34MxxoqLuLg4CggIoB07dpC9vT0tXryYiIgCAwNp2LBhlJ6eTitWrBCmjycnJ1P37t1JT0+Pli5dWphN/2kRERG0e/duMjMzE1IqrF27lubPn0/Ozs7k7u5OtWvXFtaXzh/Loxp/n6tXr5KXlxcFBQVR1apVC7s5grNnz9LUqVNp8uTJdOLECVqxYgW9evWKqlevTnfu3KF+/foREVFkZCSpqKjkmu+VR0szxhhjecdZ1BljrIQDIARPPTw86MWLF7R06VKqUaMGrVixgq5fv06LFi0SAhCxsbF05MgR6tGjh8z7cACWMVbcACANDQ0aPHgwAaDt27cTAFqyZAn17duXbt68SYsXLyYVFRWKjo4meXl58vLyovfv39Phw4eF9ygOAcrY2FgaPHgwvXv3jnR1dYXlI0aMIAC0YMECkpeXp8GDB1PdunWJiDgAm0+aNWtGoaGhpKSkVNhNkVGtWjVSVlYmd3d3SkxMpNu3b1P16tWJKDudws6dO6lv375kaWlJZ8+eJRUVlRxBVw7AMsYYY3nHd9SMMVbCSW6uHz16RBEREeTh4UG1a9cmT09PunTpEunp6VGvXr1ILBbTx48fafjw4ZSUlCSMomKMseJKEmSsXLkyDR48mPr160fHjh0jDw8PIiJauHAhubm50aRJk8jS0pLc3NwoIyODLl++LORILS4ByipVqlBISAhVq1aNjhw5Qrdv3xZeGzlyJPn4+NDChQvpxIkTMn9XXLavuClqAVixWEz16tWjli1bUmxsLOnq6tLTp09l1tHX16fAwEASiURUv359+vLlCwddGWOMsd+I0xEwxlgJJT26af78+RQVFUWKioq0efNm4ebwyJEj1L17d2rSpAmlpaVRuXLlKDk5ma5cuUKKioo87ZAxVix9mz5Fcj6Mi4ujzZs307Zt26h9+/bk6+tLREQ3b96kL1++UIUKFah+/fokJyeX61Ts4uDmzZs0aNAgatq0KY0dO5b09fWF10JCQqhTp058Xv+DSH4Lkv+ePn2asrKyaOXKlZSSkkLDhw+nnj17yvzNrVu3aMmSJRQQEMDHCmOMMfYbcRCWMcZKIOkARFJSEoWEhNCgQYOoXr16FBkZSZqamkJQ4v79+3Ty5EmKj48nHR0d6t27t1CUozgGIBhjfzbpB1Dr1q2jBw8eCKP7W7duTZ8/f6a1a9fmCMRKK+45sKOjo2nIkCFkYmJC48aNIz09PZnX+QHbn0H6OH706BGVLl2alJSUSENDgx49ekRjx46lr1+/kru7O3Xv3p2IsnMIDx48mEqXLk1EfKwwxhhjvxMHYRljrISRvuny9fWlJ0+e0JgxY+jmzZvUt29f8vHxob/++ovk5eW/G2jgmy7GWHEkfU7z9vamjRs3kqWlJSUmJtK5c+do8uTJNGHCBCIi8vPzo507d5KZmRlt3LixMJudL6Kjo2nYsGFUu3ZtWrRoEWlpaRV2k1gBkn4Y8ddff1FISAilp6dTYmIizZo1i9zc3Ojx48c0duxYSklJoZYtW9LNmzfp4sWLFBcXV6wfQjDGGGNFFV9dGWOshJEOQCxYsIBatWpFpUuXpl69etH69etp3rx5tHDhQplgxbfP4zgAyxgrjiTntDdv3lBCQgIdP36cDhw4QGfOnKHly5fT6tWraf369VS+fHkaOHAgOTk5UWpqao5zYElgZGREq1evJhUVFapdu3ZhN4cVMEkAdvbs2bR27VpasmQJXb9+nZo3b04TJ06ke/fuUb169WjlypWko6ND58+fJwD09u1bIX0BY4wxxn4vHgnLGGMl0KlTp8jNzY22b99OLVq0kHltw4YNNGLECJo1axZNmjSJR7swxkqUHTt20LBhw6hmzZp08OBB0tXVFQJSvr6+NG3aNLpz5w7VrVuXEhMTSVVVVSjgVRKLVEm2q7inWGA/Rvp7FovF1KlTJ+rduzc5OzvTgQMHyNXVlebOnUvu7u6UkZFBioqKlJycTEREZcuWJZFIxOmIGGOMsXzCPTHGGCuBXr58ScrKyjIFWSTP3IYOHUrbtm2jqVOn0vbt2wuriYwxli+qV69OVlZW9PLlS/r69SuJRCJKTU0lIqKBAwdSxYoV6caNG0REVL58+RIdgCUiYfs4APtnkHzPM2bMoMWLF1N0dDQ1a9aMwsPDqX///jRv3jxyd3en1NRUmjlzJr169YrKlStH5cqVE4L1HIBljDHG8gdfYRljrASRBBJSU1MpKytLZrnkv/v27SNjY2MKDQ2ltm3bFlZTGWPsl+U2utPKyopKlSpF8fHx5OTkRFevXiV1dXUiIkpLSyORSESKiooyf1NSA7ASJX37mOxvITg4mAICAujYsWN0584dGjNmDEVGRtKqVavI1dWViIgSEhLo7Nmz1KBBA+rXr5/wPhysZ4wxxvIPX2UZY6wEkdxot2nThh49ekTLly8XlotEIkpJSaHt27dTWFgYtWvXjhQUFCgzM7MQW8wYY3kjPbrz4MGDtGvXLjp9+jTJycmRhYUFLV++nDQ1NcnIyIg2b95MgYGBNGzYMKpUqRI5ODgUcusZ+70kv4WIiAgKDw+nCRMmkL6+Ppmbm1NMTAxZW1sLAdikpCQaMmQIycvLU58+fQqz2YwxxtgfhXPCMsZYCbVhwwYaNWoUubu7U4cOHahUqVI0b948io2NpevXr/N0Q8ZYieDj40MrV64kLS0tunfvHs2YMYOmT59ORESXLl0iLy8vOn/+PDk7O5OZmRm5urqSsrIyZWVlcRFCVqLExsZSy5YtKS4ujnx8fGjSpEmUlZVFXl5edPr0aRKJRKSjo0MvX76ktLQ0unr1KikqKvJvgTHGGCsgHIRljLESCgD9/fffNGbMGMrKyqIKFSpQ9erV6fDhw3zTxRgrtiRpVwBQbGws9e3blxYvXkzVqlWjU6dOkaurK40bN44WL15MRETnzp2juXPn0vPnzykiIoI0NDQoNTWVypQpU8hbwtjvd+vWLerWrRtpaGjQypUrycTEhLKysujIkSMUERFBGRkZpKWlRaNHjxZmw/BDWcYYY6xgcBCWMcZKuA8fPlBiYiKJxWLS1tYmOTk5vulijBVL0nkv4+LiKC4ujjZv3kxz584VgqrBwcHUr18/Gj9+PC1atIiIiC5cuECTJk2ixMRECg0NpapVqxbaNjCW327dukUuLi7UtGlTGj16NDVq1CjX9fhhLGOMMVawOAjLGGN/mNwK2TDGWHEyefJkOnbsGH348IGUlZXpwIEDpKenJ7y+e/ducnFxoQEDBtD69euJKDs1wdChQ6ls2bJ0/vx5IVc2YyVRdHQ0DRkyhExMTGjs2LGkr69f2E1ijDHG/nh8F84YY38YDsAyxoqbrKws4f/v3LmTgoKCyNXVldzd3enZs2e0bNkyio2NFdbp2bMnrVu3jh48eCD8rZmZGfn7+9OuXbtITk6OA7CsRDMyMiJ/f3+6ceMG/fXXX/Ts2bPCbhJjjDH2x+ORsIwxxhhjrEhasGAB9ezZk+rWrUtE2ZXfDx06RIaGhuTi4kJERKGhoeTo6Ehubm70119/UZUqVXK8D6dgYX+qK1eukJ+fH/n7+/NDWMYYY6yQ8ZWYMcYYY4wVOQ8fPqQbN25Q7dq1iYjo1atX5ODgQEuXLqVXr14J69nb29ORI0do06ZNNHv2bHr9+nWO9+IALPtTmZqa0qZNm0hOTo7EYnFhN4cxxhj7o3EQljHGGGOMFTm6uroUFBRE8vLydPjwYVJWVqaIiAiqWbMmRUZG0o0bN4R1JYHYdevWUVBQUOE1mrEiSCQSEQAeCcsYY4wVMk5HwBhjjDHGiqzY2FgyMzOjNm3a0NKlSykmJoZ69epF1tbW5OHhQYaGhsK6ly9fJhMTEx75yhhjjDHGihwOwjLGGGOMsSItKiqKhg4dSo0bN6YlS5bQvXv3qE+fPmRtbU0TJkwgAwMDmfU5ByxjjDHGGCtqOAjLGGOMMcaKvOjoaHJ1dSVjY2MhENuvXz9q3LgxLV26VCjexRhjjDHGWFHEiYEYY4wxxliRZ2RkRJs3b6aoqCjy8vIifX192rx5M8nJyVGdOnUKu3mMMcYYY4z9Kx4JyxhjjDHGio3o6Ghyc3Oj2rVr09atW6lcuXJERCQWi7nwEGOMMcYYK7K4p8oYY4wxxooNIyMjWrt2LamoqJCysrKwnAOwjDHGGGOsKOORsIwxxhhjrNgBQCKRiEfAMsYYY4yxYoGDsIwxxhhjrFiSBGIZY4wxxhgr6njYAGOMMcYYK5Y4AMsYY4wxxooLDsIyxhhjjDHGGGOMMcZYPuIgLGOMMcYYY4wxxhhjjOUjDsIyxhhjjDHGGGOMMcZYPuIgLGOMMcYYY4wxxhhjjOUjDsIyxhhjjDHGGGOMMcZYPuIgLGOMMcYYY6zIGzhwIHXu3Lmwm8EYY4wxlicchGWMMcYYY4yVOGvWrKE6deqQkpISmZmZ0ZUrVwq7SYwxxhj7g3EQljHGGGOMMVaiBAcHk4eHB82YMYOioqKocePGZGdnR3FxcYXdNMYYY4z9oTgIyxhjjDHGGCsQYrGYFi1aRPXq1aPSpUtTrVq1aO7cuUREdPv2bWrbti2VKVOGKlWqREOHDqXk5OQ8fc7SpUvJzc2NBg0aRHp6euTn50fKysq0efPm37k5jDHGGGM/jIOwjDHGGGOMsQIxefJkWrBgAU2bNo3u3btHgYGBpKmpSSkpKWRnZ0dqamp09epV2rNnD4WFhdGoUaN++jPS09Pp+vXrZGNjIyyTk5MjGxsbunjx4u/cHMYYY4yxH6ZQ2A1gjDHGGGOMlXxJSUm0YsUKWr16Nbm4uBARkba2NrVs2ZI2btxIaWlptG3bNipbtiwREa1evZo6duxICxcuJE1NzR/+nA8fPlBWVlaOv9HU1KQHDx78vg1ijDHGGPsJPBKWMcYYY4wxlu/u379PX79+JWtr61xfa9y4sRCAJSJq0aIFicViiomJKchmMsYYY4zlCw7CMsYYY4wxxvJdmTJlCuRzKleuTPLy8vTu3TuZ5e/evaMqVaoUSBsYY4wxxr7FQVjGGGOMMcZYvtPR0aEyZcrQqVOncrzWsGFDunnzJqWkpAjLzp8/T3JyclS/fv2f+pxSpUqRiYmJzOeIxWI6deoUNW/ePO8bwBhjjDH2CzgnLGOMMcYYYyzfKSkpkbe3N02cOJFKlSpFLVq0oPfv39Pdu3fJ2dmZZsyYQS4uLvTXX3/R+/fvafTo0dS/f/+fygcr4eHhQS4uLtS0aVMyNTWl5cuXU0pKCg0aNCgftowxxhhj7L9xEJYxxhhjjDFWIKZNm0YKCgo0ffp0evPmDVWtWpWGDx9OysrKdPz4cRo7diw1a9aMlJWVqVu3brR06dI8fU6vXr3o/fv3NH36dIqNjaUmTZpQaGhongK6jDHGGGO/gwgACrsRjDHGGGOMMcYYY4wxVlJxTljGGGOMMcYYY4wxxhjLRxyEZYwxxhhjjBUbL1++pHLlyn33fy9fvizsJjLGGGOM5cDpCBhjjDHGGGPFRmZmJj1//vy7r9epU4cUFLj0BWOMMcaKFg7CMsYYY4wxxhhjjDHGWD7idASMMcYYY4wxxhhjjDGWjzgIyxhjjDHGGGOMMcYYY/mIg7CMMcYYY4wxxhhjjDGWjzgIyxhjjDHGGGOMMcYYY/mIg7CMMcYYY4wxxhhjjDGWjzgIyxhjjDHGGGOMMcYYY/mIg7CMMcYYY4wxxhhjjDGWj/4HoE7U1aHV8nAAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "function_matrix = pd.crosstab(df['category'], \n", " pd.Series([f for funcs in df['called_functions'] for f in funcs]))\n", "\n", "plt.figure(figsize=(15, 10))\n", "sns.heatmap(function_matrix, cmap='YlOrRd', annot=True, fmt='d')\n", "plt.title('Function Usage by Category')\n", "plt.xticks(rotation=45, ha='right')\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "# Task Complexity Analysis\n", "df['task_length'] = df['task'].str.len()\n", "plt.figure(figsize=(10, 6))\n", "sns.boxplot(x='category', y='task_length', data=df)\n", "plt.xticks(rotation=45, ha='right')\n", "plt.title('Task Complexity by Category')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 46, "id": "b8a179ab-b3e1-4e41-8294-4bdd18b26bc7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Sample Conversation Analysis:\n", "\n", "Category: Services Industry Software\n", "Task: Generate client invoices.\n", "Available Functions: []\n", "Called Functions: []\n" ] } ], "source": [ "print(\"\\nSample Conversation Analysis:\")\n", "sample_idx = np.random.randint(len(df))\n", "sample = df.iloc[sample_idx]\n", "print(f\"\\nCategory: {sample['category']}\")\n", "print(f\"Task: {sample['task']}\")\n", "print(f\"Available Functions: {sample['available_functions']}\")\n", "print(f\"Called Functions: {sample['called_functions']}\")" ] }, { "cell_type": "code", "execution_count": 49, "id": "12d38002-9d07-4ccb-a8ab-75397b6df11d", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 6))\n", "sns.scatterplot(data=df, x='human_msg_length', y='num_tool_calls')\n", "plt.title('Relationship between Message Length and Number of Tool Calls')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 50, "id": "c11994d8-2177-4fc3-9e6c-fe339cc56465", "metadata": {}, "outputs": [], "source": [ "numerical_cols = ['num_tool_calls', 'num_available_functions', \n", " 'human_msg_length', 'conversation_turns', 'task_length']\n", "correlation_matrix = df[numerical_cols].corr()" ] }, { "cell_type": "code", "execution_count": 51, "id": "c8d2b515-086f-44e4-8074-971c8b89a43a", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 8))\n", "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', center=0)\n", "plt.title('Correlation Matrix of Numerical Features')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 52, "id": "a604d62e-4059-43fe-8ebd-d1035d76f941", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Summary Statistics by Category:\n", " num_tool_calls human_msg_length \\\n", " mean std mean std \n", "category \n", "AI Model Integration 2.08 2.15 1175.25 264.97 \n", "API Call 1.58 0.99 917.49 334.36 \n", "Accounting & Finance 1.50 0.71 983.00 130.11 \n", "Algorithmic Trading 1.87 1.22 1493.77 416.28 \n", "Annotation 1.25 0.50 1192.00 654.47 \n", "... ... ... ... ... \n", "Use Apps 1.43 1.50 793.14 231.93 \n", "Utilities Software 2.02 1.16 1622.67 420.90 \n", "Voice Assistants 1.50 1.08 935.90 266.69 \n", "Web APIs 1.33 1.12 999.67 212.40 \n", "Web Browser Agent 1.27 0.90 1016.27 318.25 \n", "\n", " conversation_turns \n", " mean std \n", "category \n", "AI Model Integration 3.0 0.0 \n", "API Call 3.0 0.0 \n", "Accounting & Finance 3.0 0.0 \n", "Algorithmic Trading 3.0 0.0 \n", "Annotation 3.0 0.0 \n", "... ... ... \n", "Use Apps 3.0 0.0 \n", "Utilities Software 3.0 0.0 \n", "Voice Assistants 3.0 0.0 \n", "Web APIs 3.0 0.0 \n", "Web Browser Agent 3.0 0.0 \n", "\n", "[63 rows x 6 columns]\n" ] } ], "source": [ "summary_stats = df.groupby('category').agg({\n", " 'num_tool_calls': ['mean', 'std'],\n", " 'human_msg_length': ['mean', 'std'],\n", " 'conversation_turns': ['mean', 'std']\n", "}).round(2)\n", "\n", "print(\"\\nSummary Statistics by Category:\")\n", "print(summary_stats)" ] }, { "cell_type": "markdown", "id": "fb840196-acea-4030-9102-8c68daa204ad", "metadata": {}, "source": [ "### Pandora Tool Calling\n", "\n", "- Based on glaive-ai function calling\n", "- BSD-3\n", "- 100k examples\n", "- \n", "https://huggingface.co/datasets/danilopeixoto/pandora-tool-calling" ] }, { "cell_type": "code", "execution_count": 53, "id": "7d0a7431-019a-454d-8d90-10ef5824e60d", "metadata": {}, "outputs": [], "source": [ "d = load_dataset(\"danilopeixoto/pandora-tool-calling\")" ] }, { "cell_type": "code", "execution_count": 54, "id": "e10dee89-26dc-406d-a595-7ee1a19fbef0", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'messages': [{'role': 'system',\n", " 'content': 'You are a helpful assistant with access to functions and tools. Use them if required.',\n", " 'tools': None,\n", " 'tool_calls': None,\n", " 'name': None},\n", " {'role': 'system',\n", " 'content': None,\n", " 'tools': '[{\"name\": \"generate_random_quote\", \"description\": \"Generate a random inspirational quote\", \"parameters\": {}}, {\"name\": \"calculate_loan_payment\", \"description\": \"Calculate the monthly payment for a loan\", \"parameters\": {\"type\": \"object\", \"properties\": {\"loan_amount\": {\"type\": \"number\", \"description\": \"The total loan amount\"}, \"interest_rate\": {\"type\": \"number\", \"description\": \"The annual interest rate on the loan\"}, \"loan_term\": {\"type\": \"integer\", \"description\": \"The duration of the loan in months\"}}, \"required\": [\"loan_amount\", \"interest_rate\", \"loan_term\"]}}]',\n", " 'tool_calls': None,\n", " 'name': None},\n", " {'role': 'user',\n", " 'content': \"I'm feeling a bit down today. Can you share something inspiring?\",\n", " 'tools': None,\n", " 'tool_calls': None,\n", " 'name': None},\n", " {'role': 'assistant',\n", " 'content': None,\n", " 'tools': None,\n", " 'tool_calls': '[{\"name\": \"generate_random_quote\"}]',\n", " 'name': None},\n", " {'role': 'tool',\n", " 'content': '{\"quote\": \"The only way to do great work is to love what you do. - Steve Jobs\"}',\n", " 'tools': None,\n", " 'tool_calls': None,\n", " 'name': 'generate_random_quote'},\n", " {'role': 'assistant',\n", " 'content': 'I\\'m sorry to hear that you\\'re feeling down. Here\\'s a quote for you: \"The only way to do great work is to love what you do.\" - Steve Jobs. I hope this inspires you!',\n", " 'tools': None,\n", " 'tool_calls': None,\n", " 'name': None}]}" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][21313]" ] }, { "cell_type": "code", "execution_count": 55, "id": "489b9055-e71f-431e-9bbf-9b2fc6d92122", "metadata": {}, "outputs": [], "source": [ "def safe_json_loads(json_str):\n", " if not json_str:\n", " return None\n", " try:\n", " return json.loads(json_str)\n", " except json.JSONDecodeError:\n", " return None" ] }, { "cell_type": "code", "execution_count": 56, "id": "194affe8-c89b-4c92-9273-b655d02c67a7", "metadata": {}, "outputs": [], "source": [ "def extract_tools_and_calls(messages):\n", " tools = []\n", " tool_calls = []\n", " conversation_flow = []\n", " \n", " for msg in messages:\n", " # Track conversation flow\n", " conversation_flow.append({\n", " 'role': msg['role'],\n", " 'has_content': bool(msg['content']),\n", " 'has_tools': bool(msg['tools']),\n", " 'has_tool_calls': bool(msg['tool_calls'])\n", " })\n", " \n", " # Extract tools\n", " if msg['tools']:\n", " parsed_tools = safe_json_loads(msg['tools'])\n", " if parsed_tools:\n", " tools.extend(parsed_tools)\n", " \n", " # Extract tool calls\n", " if msg['tool_calls']:\n", " parsed_calls = safe_json_loads(msg['tool_calls'])\n", " if parsed_calls:\n", " tool_calls.extend(parsed_calls)\n", " \n", " return {\n", " 'available_tools': tools,\n", " 'tool_calls': tool_calls,\n", " 'conversation_flow': conversation_flow,\n", " 'num_messages': len(messages),\n", " 'num_tools': len(tools),\n", " 'num_tool_calls': len(tool_calls)\n", " }" ] }, { "cell_type": "code", "execution_count": 57, "id": "2cf833af-0214-4bb5-94fe-249d35e0421b", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████████████████████████████████████████████| 101114/101114 [00:14<00:00, 6898.85it/s]\n" ] } ], "source": [ "records = []\n", "for item in tqdm(d['train']):\n", " messages = item['messages']\n", " \n", " user_messages = [msg for msg in messages if msg['role'] == 'user']\n", " assistant_messages = [msg for msg in messages if msg['role'] == 'assistant']\n", " tool_messages = [msg for msg in messages if msg['role'] == 'tool']\n", " \n", " conv_analysis = extract_tools_and_calls(messages)\n", " \n", " record = {\n", " 'num_messages': len(messages),\n", " 'num_user_messages': len(user_messages),\n", " 'num_assistant_messages': len(assistant_messages),\n", " 'num_tool_messages': len(tool_messages),\n", " \n", " # Tool information\n", " 'num_available_tools': conv_analysis['num_tools'],\n", " 'num_tool_calls': conv_analysis['num_tool_calls'],\n", " 'available_tools': [tool['name'] for tool in conv_analysis['available_tools']],\n", " 'tool_calls': [call['name'] for call in conv_analysis['tool_calls']],\n", " \n", " # Message content\n", " 'user_query': user_messages[0]['content'] if user_messages else None,\n", " 'user_query_length': len(user_messages[0]['content']) if user_messages and user_messages[0]['content'] else 0,\n", " \n", " # Store full conversation flow for pattern analysis\n", " 'conversation_flow': conv_analysis['conversation_flow']\n", " }\n", " \n", " records.append(record)\n", "\n", "df = pd.DataFrame(records)" ] }, { "cell_type": "code", "execution_count": 58, "id": "fdaa0f7b-ea8d-4c15-a92c-f7af7b5e87f1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Dataset Overview:\n", "Total conversations: 101114\n", "Average messages per conversation: 7.46\n", "Average tool calls per conversation: 0.74\n" ] } ], "source": [ "print(\"\\nDataset Overview:\")\n", "print(f\"Total conversations: {len(df)}\")\n", "print(f\"Average messages per conversation: {df['num_messages'].mean():.2f}\")\n", "print(f\"Average tool calls per conversation: {df['num_tool_calls'].mean():.2f}\")" ] }, { "cell_type": "code", "execution_count": 59, "id": "4a9f155a-2709-4f67-9d01-6cbe4b9bc2aa", "metadata": {}, "outputs": [], "source": [ "all_tools = [tool for tools in df['available_tools'] for tool in tools]\n", "all_calls = [call for calls in df['tool_calls'] for call in calls]" ] }, { "cell_type": "code", "execution_count": 60, "id": "a666c621-a55a-4108-8dac-ae0e9dcbfee7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Tool Usage:\n", "Available Tools Distribution:\n", "calculate_bmi: 4157\n", "convert_currency: 4055\n", "calculate_distance: 4010\n", "calculate_age: 3980\n", "calculate_tip: 3819\n", "calculate_discount: 3529\n", "get_stock_price: 2618\n", "generate_qr_code: 2497\n", "generate_password: 2396\n", "search_books: 2274\n", "calculate_loan_payment: 2206\n", "generate_random_number: 2130\n", "search_recipes: 2127\n", "get_movie_details: 1999\n", "send_email: 1950\n", "calculate_area: 1865\n", "generate_random_password: 1754\n", "create_todo: 1385\n", "create_calendar_event: 1376\n", "search_movies: 1250\n", "calculate_mortgage_payment: 1046\n", "translate_text: 958\n", "analyze_sentiment: 954\n", "search_recipe: 942\n", "get_news: 841\n", "get_definition: 797\n", "calculate_tax: 777\n", "create_note: 737\n", "search_restaurants: 691\n", "generate_invoice: 674\n", "get_news_headlines: 668\n", "search_movie: 597\n", "play_music: 561\n", "convert_temperature: 550\n", "get_random_joke: 540\n", "calculate_gpa: 479\n", "create_invoice: 478\n", "calculate_shipping_cost: 474\n", "generate_random_quote: 471\n", "calculate_average: 449\n", "get_random_fact: 444\n", "calculate_interest: 418\n", "calculate_discounted_price: 412\n", "create_user: 411\n", "generate_barcode: 406\n", "search_jobs: 406\n", "generate_random_color: 399\n", "calculate_mortgage: 347\n", "search_news: 335\n", "generate_username: 330\n", "search_book: 326\n", "create_event: 289\n", "analyze_image: 281\n", "schedule_meeting: 270\n", "get_current_time: 256\n", "check_email_availability: 251\n", "search_product: 227\n", "check_palindrome: 223\n", "calculate_profit: 223\n", "get_random_quote: 196\n", "calculate_fibonacci_sequence: 191\n", "find_nearest_gas_station: 186\n", "check_word_count: 184\n", "create_user_account: 178\n", "create_task: 178\n", "search_images: 176\n", "find_nearby_restaurants: 162\n", "calculate_sales_tax: 157\n", "calculate_age_difference: 153\n", "create_contact: 152\n", "get_movie_recommendations: 151\n", "get_recipe: 147\n", "create_reminder: 146\n", "encrypt_text: 141\n", "check_flight_status: 132\n", "execute_program: 131\n", "get_random_number: 130\n", "generate_random_fact: 129\n", "calculate_loan_interest: 128\n", "track_package: 127\n", "calculate_square_root: 121\n", "create_todo_list: 119\n", "search_music: 112\n", "generate_uuid: 110\n", "count_words: 109\n", "get_news_articles: 103\n", "create_account: 103\n", "create_user_profile: 102\n", "search_hotels: 101\n", "search_song: 101\n", "generate_random_username: 99\n", "calculate_gross_salary: 98\n", "get_translation: 97\n", "calculate_loan_repayment: 96\n", "calculate_factorial: 95\n", "create_playlist: 95\n", "find_restaurants: 94\n", "search_restaurant: 93\n", "calculate_rectangle_area: 92\n", "find_shortest_path: 91\n", "calculate_tip_split: 91\n", "check_spelling: 85\n", "calculate_route: 85\n", "generate_random_name: 83\n", "track_calories: 83\n", "calculate_fuel_cost: 82\n", "calculate_percentage: 81\n", "get_lyrics: 81\n", "calculate_fuel_efficiency: 80\n", "calculate_gcd: 77\n", "find_hotels: 75\n", "book_flight: 74\n", "add_numbers: 73\n", "send_sms: 72\n", "calculate_salary: 72\n", "get_song_lyrics: 72\n", "find_nearby_places: 69\n", "make_note: 68\n", "calculate_fibonacci: 68\n", "calculate_profit_margin: 66\n", "find_nearest_restaurant: 61\n", "calculate_volume: 61\n", "check_website_status: 60\n", "track_expenses: 60\n", "generate_qrcode: 60\n", "check_email: 59\n", "calculate_route_distance: 57\n", "calculate_fuel_consumption: 56\n", "check_website_availability: 55\n", "search_events: 54\n", "find_movie: 54\n", "get_exchange_rate: 52\n", "create_poll: 49\n", "check_prime_number: 47\n", "generate_quote: 46\n", "analyze_website: 45\n", "search_wikipedia: 44\n", "calculate_loan_payments: 44\n", "validate_email: 42\n", "search_products: 41\n", "upload_file: 40\n", "get_quote_of_the_day: 40\n", "get_sports_scores: 40\n", "calculate_fahrenheit_to_celsius: 40\n", "calculate_tip_amount: 39\n", "get_directions: 39\n", "get_movie_info: 38\n", "calculate_carbon_footprint: 36\n", "check_stock_price: 36\n", "book_hotel: 36\n", "play_sound: 36\n", "add_contact: 36\n", "generate_random_joke: 35\n", "calculate_square: 34\n", "calculate_triangle_area: 34\n", "calculate_future_value: 33\n", "detect_language: 33\n", "calculate_sum: 32\n", "calculate_time_difference: 30\n", "calculate_body_mass_index: 30\n", "calculate_tip_percentage: 30\n", "analyze_text: 29\n", "check_stock_availability: 28\n", "calculate_car_emissions: 28\n", "convert_units: 28\n", "search_definition: 27\n", "generate_anagram: 27\n", "calculate_median: 26\n", "generate_meme: 26\n", "find_common_elements: 26\n", "encrypt_message: 26\n", "search_articles: 25\n", "analyze_social_media_sentiment: 25\n", "generate_fibonacci_sequence: 25\n", "check_username_availability: 25\n", "analyze_customer_reviews: 24\n", "analyze_website_performance: 24\n", "order_food: 24\n", "generate_random_string: 24\n", "play_song: 24\n", "calculate_duration: 23\n", "analyze_product_reviews: 23\n", "get_time: 23\n", "check_movie_showtimes: 23\n", "get_recipe_details: 23\n", "check_email_validity: 23\n", "generate_unique_id: 23\n", "add_task: 22\n", "encrypt_data: 22\n", "get_stock_prices: 21\n", "analyze_customer_feedback: 21\n", "generate_random_numbers: 21\n", "calculate_loan_emi: 20\n", "calculate_calories_burned: 20\n", "fetch_news: 19\n", "reverse_string: 19\n", "get_user_profile: 19\n", "find_restaurant: 19\n", "add_contacts: 18\n", "get_traffic_info: 18\n", "get_joke: 18\n", "calculate_loan_emis: 18\n", "calculate_speed: 17\n", "find_recipe: 17\n", "search_songs: 17\n", "calculate_calories: 17\n", "search_movies_by_genre: 17\n", "get_upcoming_events: 17\n", "get_note: 17\n", "get_currency_exchange_rate: 17\n", "find_movie_recommendations: 16\n", "analyze_website_traffic: 16\n", "validate_credit_card: 16\n", "get_word_definition: 16\n", "recommend_books: 16\n", "generate_password_strength: 15\n", "calculate_rectangle_perimeter: 15\n", "get_horoscope: 15\n", "create_new_user: 15\n", "create_event_reminder: 14\n", "search_news_articles: 14\n", "get_quotes: 14\n", "calculateBMI: 13\n", "search_lyrics: 13\n", "convert_length: 13\n", "get_movie_recommendation: 13\n", "search_tweets: 13\n", "calculate_taxes: 13\n", "get_calendar_events: 13\n", "get_sunset_time: 13\n", "calculate_hypotenuse: 13\n", "get_word_synonyms: 12\n", "delete_note: 12\n", "get_movie_reviews: 12\n", "check_word_anagram: 12\n", "search_job: 12\n", "calculate_body_fat_percentage: 12\n", "get_book_details: 11\n", "get_quote: 11\n", "create_survey: 11\n", "get_notes: 11\n", "search_hotel: 11\n", "check_prime: 11\n", "generate_random_password_strength: 11\n", "send_notification: 11\n", "search_flights: 11\n", "calculate_age_in_days: 11\n", "shuffle_array: 10\n", "calculate_pace: 10\n", "analyze_customer_sentiment: 10\n", "create_todo_item: 10\n", "analyze_audio: 10\n", "analyze_social_media: 10\n", "get_current_date: 10\n", "analyze_stock_market: 9\n", "calculate_emission: 9\n", "calculate_car_loan_payment: 9\n", "create_post: 9\n", "generate_hash: 9\n", "calculate_circumference: 9\n", "generate_password_reset_link: 9\n", "search_image: 9\n", "generate_random_word: 9\n", "calculate_trip_distance: 9\n", "calculate_perimeter: 9\n", "find_nearby_hotels: 9\n", "add_to_shopping_cart: 9\n", "add_note: 8\n", "identify_language: 8\n", "calculate_car_loan: 8\n", "calculate_retirement_savings: 8\n", "generate_invoice_number: 8\n", "generate_password_reset_token: 8\n", "search_movie_reviews: 8\n", "check_word_definition: 8\n", "check_anagram: 8\n", "calculate_shipping_time: 8\n", "find_median: 8\n", "get_flight_status: 8\n", "check_stock: 8\n", "count_occurrences: 7\n", "get_user_info: 7\n", "find_movie_showtimes: 7\n", "get_holidays: 7\n", "calculate_mortgage_payments: 7\n", "find_hotel: 7\n", "find_nearest_coffee_shop: 7\n", "generate_password_hash: 7\n", "generate_report: 7\n", "generate_sudoku: 7\n", "check_word_similarity: 7\n", "find_book: 7\n", "solve_equation: 7\n", "scan_barcode: 7\n", "get_news_feed: 7\n", "calculate_circle_area: 7\n", "check_availability: 7\n", "analyze_stock_performance: 7\n", "encode_base64: 7\n", "find_route: 7\n", "get_random_quote_of_the_day: 7\n", "get_pokemon_details: 6\n", "create_new_note: 6\n", "get_latest_news: 6\n", "calculate_emissions: 6\n", "search_contacts: 6\n", "generate_phone_number: 6\n", "create_blog_post: 6\n", "roll_dice: 6\n", "track_fitness_activity: 6\n", "search_quotes: 6\n", "calculate_age_in_months: 6\n", "create_new_task: 6\n", "generate_random_date: 6\n", "recommend_movie: 6\n", "make_notes: 6\n", "calculate_area_volume: 6\n", "add_to_shopping_list: 6\n", "search_videos: 6\n", "get_top_news: 6\n", "fetch_news_articles: 6\n", "get_random_recipe: 5\n", "execute_command: 5\n", "get_traffic_status: 5\n", "find_closest_gas_station: 5\n", "analyze_sales_data: 5\n", "get_daily_quote: 5\n", "analyze_health_data: 5\n", "calculate_premium: 5\n", "calculate_rental_income: 5\n", "find_song_lyrics: 5\n", "make_payment: 5\n", "get_song_recommendations: 5\n", "get_daily_horoscope: 5\n", "reserve_table: 5\n", "create_schedule: 5\n", "search_parks: 5\n", "set_reminder: 5\n", "send_message: 5\n", "generate_id: 5\n", "get_road_traffic: 5\n", "analyze_twitter_sentiment: 5\n", "analyze_text_sentiment: 5\n", "find_highest_number: 5\n", "get_random_dog_image: 5\n", "sort_numbers: 5\n", "calculate_rental_cost: 5\n", "generate_thumbnail: 5\n", "search_for_books: 5\n", "record_audio: 5\n", "search_movie_theaters: 5\n", "calculate_square_area: 5\n", "play_game: 5\n", "check_word_availability: 4\n", "get_recipe_ingredients: 4\n", "track_fitness: 4\n", "take_screenshot: 4\n", "post_tweet: 4\n", "check_password_strength: 4\n", "calculate_rent: 4\n", "take_notes: 4\n", "calculate_distance_traveled: 4\n", "check_email_spam: 4\n", "search_for_restaurants: 4\n", "generate_fake_data: 4\n", "find_nearest_parking: 4\n", "calculate_cylinder_volume: 4\n", "post_social_media_status: 4\n", "get_daily_news: 4\n", "post_to_social_media: 4\n", "calculate_total: 4\n", "get_product_details: 4\n", "generate_recommendations: 4\n", "check_visa_requirements: 4\n", "calculate_total_price: 4\n", "get_recipe_instructions: 4\n", "calculate_rental_price: 4\n", "analyze_text_language: 4\n", "find_prime_numbers: 4\n", "calculate_pension: 4\n", "get_movie_showtimes: 4\n", "calculate_fibonacci_series: 4\n", "analyze_text_similarity: 4\n", "calculate_area_of_circle: 4\n", "check_email_existence: 4\n", "calculate_lifespan: 4\n", "calculate_grade: 4\n", "schedule_maintenance: 4\n", "analyze_tweet: 4\n", "get_restaurant_reviews: 4\n", "track_sleep: 4\n", "rate_movie: 4\n", "search_places: 4\n", "get_word_count: 4\n", "schedule_appointment: 4\n", "create_new_contact: 4\n", "calculate_savings: 4\n", "recommend_movies: 4\n", "calculate_net_salary: 4\n", "search_stock_price: 4\n", "get_stock_info: 4\n", "track_fitness_progress: 4\n", "find_closest_restaurant: 4\n", "sort_array: 4\n", "get_nearby_restaurants: 4\n", "check_email_domain: 4\n", "check_email_format: 3\n", "find_similar_images: 3\n", "analyze_video: 3\n", "analyze_stock: 3\n", "play_video: 3\n", "search_photos: 3\n", "generate_quiz: 3\n", "get_sudoku_solution: 3\n", "get_music_recommendations: 3\n", "find_nearby_gas_stations: 3\n", "generate_random_song: 3\n", "get_bus_schedule: 3\n", "generate_calendar_event: 3\n", "find_nearest_hotels: 3\n", "calculate_tip_share: 3\n", "get_synonyms: 3\n", "calculate_discounted_percentage: 3\n", "search_for_movies: 3\n", "schedule_event: 3\n", "calculate_gas_mileage: 3\n", "get_recommended_books: 3\n", "get_current_news: 3\n", "get_contact_info: 3\n", "schedule_task: 3\n", "count_characters: 3\n", "find_nearest_parking_lot: 3\n", "calculate_payment: 3\n", "check_spellings: 3\n", "convert_weight: 3\n", "convert_image_format: 3\n", "get_upcoming_concerts: 3\n", "buy_product: 3\n", "check_word_frequency: 3\n", "create_folder: 3\n", "save_note: 3\n", "analyze_stock_data: 3\n", "get_location_coordinates: 3\n", "evaluate_expression: 3\n", "find_longest_word: 3\n", "send_push_notification: 3\n", "check_word_spelling: 3\n", "generate_random_sentence: 3\n", "generate_random_password_complex: 3\n", "generate_recommendation: 3\n", "find_nearby_parks: 3\n", "generate_riddle: 3\n", "calculate_score: 3\n", "find_movie_details: 3\n", "execute_shell_command: 3\n", "get_definition_of_acronym: 3\n", "search_song_lyrics: 3\n", "calculate_power: 3\n", "book_appointment: 3\n", "parse_csv: 3\n", "book_table: 3\n", "perform_sentiment_analysis: 3\n", "get_sport_scores: 3\n", "calculate_celsius_to_fahrenheit: 3\n", "get_random_quote_author: 3\n", "calculate_gas_cost: 3\n", "analyze_tweet_sentiment: 3\n", "get_location_details: 3\n", "generate_credit_card_number: 3\n", "calculate_earnings: 3\n", "calculate_roi: 3\n", "check_lottery_results: 2\n", "calculate BMI: 2\n", "search_database: 2\n", "upload_image: 2\n", "find_movie_info: 2\n", "create_recipe: 2\n", "get_dog_breed: 2\n", "search_podcast: 2\n", "decode_base64: 2\n", "get_random_word: 2\n", "calculate_discounted_price_with_coupon: 2\n", "generate_mnemonic: 2\n", "calculateLoanPayment: 2\n", "get_hot_deals: 2\n", "calculate_discounted_price_range: 2\n", "calculate_percent_change: 2\n", "calculate_car_mileage: 2\n", "generate_quote_of_the_day: 2\n", "get_recipe_suggestions: 2\n", "create_journal_entry: 2\n", "get_diet_plan: 2\n", "search_movie_by_genre: 2\n", "play_sound_effect: 2\n", "get_language_translation: 2\n", "search_hiking_trails: 2\n", "get_fact: 2\n", "get_user_details: 2\n", "create_new_account: 2\n", "calculate_mean: 2\n", "calculate_total_expenses: 2\n", "create_todo_task: 2\n", "get_driving_directions: 2\n", "create_new_event: 2\n", "record_notes: 2\n", "calculateMortgagePayment: 2\n", "generate_license_key: 2\n", "fetch_news_headlines: 2\n", "get_random_fact_of_the_day: 2\n", "perform_translation: 2\n", "calculate_daily_calorie_intake: 2\n", "search_for_recipes: 2\n", "calculate_vat: 2\n", "check_grammar: 2\n", "generate_lottery_numbers: 2\n", "check_text_sentiment: 2\n", "calculate_commission: 2\n", "find_nearest_store: 2\n", "get_sunrise_sunset: 2\n", "find_nearby_cafes: 2\n", "find_books: 2\n", "identify_object: 2\n", "get_fuel_price: 2\n", "calculate_bill: 2\n", "generate_resume: 2\n", "get_population: 2\n", "generate_unique_identifier: 2\n", "generate_short_url: 2\n", "calculate_total_cost: 2\n", "analyze_social_media_mentions: 2\n", "find_hotel_rooms: 2\n", "calculate_loan_amortization: 2\n", "find_nearby_parking: 2\n", "get_time_zone: 2\n", "calculate_shipping: 2\n", "get_person_details: 2\n", "get_poetry: 2\n", "get_holiday_dates: 2\n", "get_forecast: 2\n", "calculate_age_in_hours: 2\n", "create_resume: 2\n", "search_files: 2\n", "find_nearest_hotel: 2\n", "calculate_car_emission: 2\n", "analyze_social_media_post: 2\n", "find_nearest_pizza_place: 2\n", "get_country_info: 2\n", "add_calendar_event: 2\n", "read_file: 2\n", "search_restaurants_by_cuisine: 2\n", "calculate_exchange_rate: 2\n", "suggest_book: 2\n", "get_file_size: 2\n", "perform_google_search: 2\n", "generate_random_password_special: 2\n", "find_word_synonyms: 2\n", "analyze_customer_churn: 2\n", "add_todo: 2\n", "get_facts: 2\n", "find_nearest_park: 2\n", "find_nearest_hospital: 2\n", "find_music_recommendations: 2\n", "find_similar_products: 2\n", "calculate_car_fuel_efficiency: 2\n", "calculate_nutritional_value: 2\n", "delete_calendar_event: 2\n", "search_cities: 2\n", "find_closest_store: 2\n", "search_in_database: 2\n", "check_vowel: 2\n", "classify_image: 2\n", "check_movie_schedule: 2\n", "track_calorie_intake: 2\n", "get_temperature: 2\n", "search_holidays: 2\n", "analyze_customer_demographics: 2\n", "get_sunrise_sunset_time: 2\n", "perform_spell_check: 2\n", "generate_daily_schedule: 2\n", "calculate_car_loan_emis: 2\n", "search_book_recommendations: 2\n", "find_distance: 2\n", "find_similar_movies: 2\n", "perform_calculator_operation: 2\n", "get_traffic_report: 2\n", "identify_objects: 2\n", "search_museums: 2\n", "retrieve_user_profile: 2\n", "get_github_repos: 2\n", "calculate_cagr: 2\n", "calculate_combinations: 2\n", "create_task_reminder: 2\n", "search_location: 2\n", "calculate_rental_profit: 2\n", "get_word_definitions: 2\n", "get_book_recommendations: 2\n", "calculate_vehicle_mileage: 2\n", "write_note: 2\n", "query_database: 2\n", "generate_checksum: 2\n", "random_number: 2\n", "calculate_discounted_tax: 2\n", "get_recommendations: 2\n", "timer: 2\n", "find_hotel_deals: 2\n", "random_number_generator: 2\n", "create_email: 2\n", "calculateDiscount: 2\n", "find_max: 2\n", "generate_random_number_sequence: 2\n", "analyze_social_media_posts: 2\n", "check_bus_schedule: 2\n", "verify_credit_card: 2\n", "calculate_pizza_cost: 2\n", "search_stock: 2\n", "get_song_recommendation: 2\n", "search_nearby_places: 2\n", "find_lyrics: 2\n", "get_poem: 2\n", "search_product_reviews: 2\n", "analyze_sentences: 2\n", "calculate_roots: 2\n", "set_alarm: 2\n", "find_events: 1\n", "randomize_list: 1\n", "find_closest_pizza_place: 1\n", "generate_license_plate: 1\n", "submit_feedback: 1\n", "calculate_invoice_total: 1\n", "find_bus_route: 1\n", "get_current_exchange_rates: 1\n", "get_live_traffic_info: 1\n", "generate_schedule: 1\n", "create_alert: 1\n", "analyze_fraud_activity: 1\n", "calculate_paint_required: 1\n", "search_documents: 1\n", "schedule_social_media_post: 1\n", "create_new_post: 1\n", "searchRecipes: 1\n", "check_fuel_price: 1\n", "generate_birthday_card: 1\n", "sort_list: 1\n", "calculate_delivery_cost: 1\n", "calculate_shopping_cart_total: 1\n", "analyze_traffic: 1\n", "send_text_message: 1\n", "record_expense: 1\n", "get_recipes: 1\n", "find_hot_restaurants: 1\n", "check_internet_speed: 1\n", "simulate_dice_roll: 1\n", "solve_math_equation: 1\n", "get_stock_history: 1\n", "locate_nearby_places: 1\n", "check_ip_address: 1\n", "retrieve_news: 1\n", "detect_face: 1\n", "search_dictionary: 1\n", "search_artist: 1\n", "calculate_fitness_level: 1\n", "getNewsHeadlines: 1\n", "calculate_route_duration: 1\n", "get_definitions: 1\n", "search_music_albums: 1\n", "make_hot_coffee: 1\n", "generate_prime_numbers: 1\n", "get_random_trivia: 1\n", "find_file: 1\n", "get_recipes_by_ingredients: 1\n", "search_website: 1\n", "calculate_tips: 1\n", "create_thumbnail: 1\n", "find_music: 1\n", "estimate_delivery_time: 1\n", "get_nutrition_info: 1\n", "post_comment: 1\n", "check_word_palindrome: 1\n", "get_currency_conversion: 1\n", "calculate_net_pay: 1\n", "generate_nickname: 1\n", "detect_faces: 1\n", "find_cheapest_product: 1\n", "get_word_meaning: 1\n", "generate_username_password: 1\n", "calculate_days_between_dates: 1\n", "check_route_traffic: 1\n", "flip_coin: 1\n", "compute_fibonacci: 1\n", "getRandomFact: 1\n", "save_contact: 1\n", "find_largest_number: 1\n", "suggest_friends: 1\n", "add_two_numbers: 1\n", "get_pokemon_data: 1\n", "search_contact: 1\n", "get_traffic_updates: 1\n", "calculate_discount_percentage: 1\n", "create_guest_list: 1\n", "get_daily_stock_price: 1\n", "verify_email_address: 1\n", "calculate_quadratic_equation: 1\n", "searchRestaurants: 1\n", "create_purchase_order: 1\n", "get_top_headlines: 1\n", "calculate_discount_amount: 1\n", "analyze_movie_reviews: 1\n", "calculate_miles_per_gallon: 1\n", "find_song: 1\n", "find_friends: 1\n", "validate_password_strength: 1\n", "search_vehicles: 1\n", "search_shoes: 1\n", "check_word_meaning: 1\n", "create_ticket: 1\n", "get_public_transport_routes: 1\n", "search_venues: 1\n", "get_relevant_articles: 1\n", "check_horoscope: 1\n", "get_random_quote_category: 1\n", "generate_random_id: 1\n", "calculate_recipe_calories: 1\n", "create_password: 1\n", "find_smallest_number: 1\n", "identify_plants: 1\n", "check_word_spell: 1\n", "calculate_payment_due: 1\n", "calculate_seconds_difference: 1\n", "find_word_frequency: 1\n", "get_public_ip: 1\n", "analyze_text_complexity: 1\n", "find_cafe_nearby: 1\n", "generate_email: 1\n", "calculate_discounted_amount: 1\n", "run_script: 1\n", "check_blockchain_balance: 1\n", "analyze_tweets: 1\n", "search_place: 1\n", "validate_email_address: 1\n", "check_internet_connection: 1\n", "search_albums: 1\n", "fetch_stock_price: 1\n", "search_books_by_author: 1\n", "get_current_weather: 1\n", "get_traffic_conditions: 1\n", "calculate_delivery_time: 1\n", "find_parking: 1\n", "find_nearest_restaurants: 1\n", "check_word_spellings: 1\n", "generate_anagrams: 1\n", "search_nearby_hotels: 1\n", "create_random_password: 1\n", "analyze_stock_portfolio: 1\n", "analyze_market_trends: 1\n", "get_email_count: 1\n", "create_random_username: 1\n", "find_factorial: 1\n", "search_recipe_by_ingredients: 1\n", "search_health_symptoms: 1\n", "create_file: 1\n", "get_definition_by_language: 1\n", "get_distance: 1\n", "generate_birthday_wish: 1\n", "create_password_hash: 1\n", "search_flight: 1\n", "add_notes: 1\n", "find_mismatch: 1\n", "start_timer: 1\n", "perform_stock_analysis: 1\n", "calculate_discounted_total: 1\n", "get_random_name: 1\n", "get_detailed_stock_info: 1\n", "book_movie_tickets: 1\n", "check_road_conditions: 1\n", "analyze_user_sentiment: 1\n", "calculate_resistance: 1\n", "search_in_array: 1\n", "analyze_text_length: 1\n", "find_suggestions: 1\n", "identify_face: 1\n", "generate_word_cloud: 1\n", "find_nearby_hospitals: 1\n", "check_if_prime: 1\n", "validate_password: 1\n", "find_movie_reviews: 1\n", "play_youtube_video: 1\n", "delete_folder: 1\n", "calculateDistance: 1\n", "record_note: 1\n", "check_vehicle_registration: 1\n", "calculate_returns: 1\n", "find_music_albums: 1\n", "calculate_stats: 1\n", "find_shopping_mall: 1\n", "retrieve_contacts: 1\n", "analyze_data: 1\n", "search_coffee_shops: 1\n", "read_text_file: 1\n", "check_url_status: 1\n", "get_meme: 1\n", "calculate_apr: 1\n", "calculate_percentile: 1\n", "generate_sentence: 1\n", "search_online_store: 1\n", "get_route_directions: 1\n", "calculate_triangl\te_area: 1\n", "find_max_value: 1\n", "generate_unique_code: 1\n", "create_roadmap: 1\n", "calculate_mortgage_repayment: 1\n", "randomize_array: 1\n", "estimate_car_value: 1\n", "track_fitness_goals: 1\n", "get_current_temperature: 1\n", "generate_random_password_with_constraints: 1\n", "check_license_plate: 1\n", "get_exchange_rates: 1\n", "calculate_squared: 1\n", "post_note: 1\n", "calculateTip: 1\n", "get_forecast_weather: 1\n", "solve_quadratic_equation: 1\n", "get_city_population: 1\n", "capture_screenshot: 1\n", "search_offices: 1\n", "get_complementary_color: 1\n", "analyze_tone: 1\n", "add_task_to_todo_list: 1\n", "check_file_existence: 1\n", "get_random_pokemon: 1\n", "get_dictionary_definition: 1\n", "create_to-do_list: 1\n", "analyze_email: 1\n", "create_social_media_post: 1\n", "calculate_recurring_payment: 1\n", "check_webpage_status: 1\n", "get_road_conditions: 1\n", "generatePassword: 1\n", "get_movie_information: 1\n", "get_defect_count: 1\n", "calculate_battery_life: 1\n", "find_venue: 1\n", "find_recipes: 1\n", "encode_url: 1\n", "search_for_hotels: 1\n", "add_item_to_shopping_cart: 1\n", "get_available_flights: 1\n", "receive_payment: 1\n", "get_random_cat_fact: 1\n", "check_news: 1\n", "search_flickr_photos: 1\n", "get_earthquake_data: 1\n", "make_reservation: 1\n", "search_twitter: 1\n", "generate_jwt_token: 1\n", "create_to_do_list: 1\n", "calculate_car_lease_payment: 1\n", "recommend_products: 1\n", "update_calendar: 1\n", "check_movie_rating: 1\n", "search_movie_theater: 1\n", "check_file_exists: 1\n", "get_length: 1\n", "delete_file: 1\n", "get_contact_details: 1\n", "get_next_holiday: 1\n", "create_image_thumbnail: 1\n", "get_historical_data: 1\n", "convert_celsius_to_fahrenheit: 1\n", "calculate_days_until_event: 1\n", "get_sunrise_time: 1\n", "get_conversion_rate: 1\n", "calculate_percentages: 1\n", "calculate_loan_affordability: 1\n", "get_movie_data: 1\n", "get_file_contents: 1\n", "calculate_distance_between_cities: 1\n", "calculate_correlation: 1\n", "rate_product: 1\n", "get_nearby_events: 1\n", "calculate_tip_percent: 1\n", "mark_todo_as_complete: 1\n", "purchase_product: 1\n", "check_movie_reviews: 1\n", "convertTemperature: 1\n", "make_todo_list: 1\n", "calculate_triangle_perimeter: 1\n", "solve_sudoku: 1\n", "book_hotel_room: 1\n", "search_repositories: 1\n", "find_hotel_availability: 1\n", "encode_image: 1\n", "find_nearest_pharmacy: 1\n", "calculate_age_in_seconds: 1\n", "compute_average: 1\n", "calculateInterest: 1\n", "check_brackets: 1\n", "check_phone_number: 1\n", "calculateAge: 1\n", "get_stock_quotes: 1\n", "calculate_profit_loss: 1\n", "calculate_quiz_score: 1\n", "make_todo: 1\n", "analyze_sentiment_tone: 1\n", "calculate_car_fuel_cost: 1\n", "calculate_car_fuel_consumption: 1\n", "get_random_dog_fact: 1\n", "store_data: 1\n", "generate_pdf: 1\n", "generate_greeting: 1\n", "play_playlist: 1\n", "check_traffic: 1\n", "find_sports_scores: 1\n", "create_employee_profile: 1\n", "get_current_stock_price: 1\n", "check_domain_availability: 1\n", "search_recipes_by_ingredients: 1\n", "post_social_media: 1\n", "get_social_media_posts: 1\n", "calculate_elapsed_time: 1\n", "generateQRCode: 1\n", "get_random_factoid: 1\n", "search_recipe_by_cuisine: 1\n", "calculate_bmi_category: 1\n", "find_shortest_route: 1\n", "add_event: 1\n", "generate_fake_name: 1\n", "download_file: 1\n", "check_if_palindrome: 1\n", "convert_time_zone: 1\n", "calculate_weight: 1\n", "add_to_cart: 1\n", "get_social_media_stats: 1\n", "check_isbn: 1\n", "get_local_news: 1\n", "calculate_body_mass: 1\n", "update_note: 1\n", "predict_stock_price: 1\n", "analyze_stock_price: 1\n", "get_location_info: 1\n", "find_movie_rating: 1\n", "book_tickets: 1\n", "get_exercise_recommendation: 1\n", "analyze_user_behavior: 1\n", "get_definition_synonyms: 1\n", "calculate_rectangle_diagonal: 1\n", "calculate_pizza_area: 1\n", "get_shopping_list: 1\n", "multiply: 1\n", "search_for_jobs: 1\n", "parse_email: 1\n", "calculate_sale_price: 1\n", "search_for_product: 1\n", "detect_object: 1\n", "track_order: 1\n", "check_if_website_is_up: 1\n", "verify_email: 1\n", "get_user_data: 1\n", "find_average: 1\n", "get_definition_in_language: 1\n", "add: 1\n", "calculate_trip_duration: 1\n", "complete_task: 1\n", "find_jobs: 1\n", "searchMovies: 1\n", "search_flickr_images: 1\n", "get_stock_details: 1\n", "retrieve_movie_details: 1\n", "find_closest_parking: 1\n", "calculate_shipping_distance: 1\n", "calculate_shopping_discount: 1\n", "get_next_prime: 1\n", "retrieve_contact: 1\n", "calculate_discount_percent: 1\n", "get_random_quote_by_author: 1\n", "find_nearby_events: 1\n", "calculate_conversions: 1\n", "play_audio: 1\n", "calculate_biorhythm: 1\n", "find_songs_by_artist: 1\n", "search_nearby_restaurants: 1\n", "calculate_lease_payment: 1\n", "check_string_palindrome: 1\n", "calculate_statistics: 1\n", "retrieve_contact_info: 1\n", "generate_email_signature: 1\n", "searchBooks: 1\n", "find_nearest_parking_spot: 1\n", "retrieve_user_details: 1\n", "register_user: 1\n", "get_exercise_recommendations: 1\n", "find_max_number: 1\n", "calculate_exponent: 1\n", "search_exercises: 1\n", "calculate_repayment_schedule: 1\n", "find_gcd: 1\n", "check_movie_timing: 1\n", "get_currency_conversion_rate: 1\n", "generate_random_number_list: 1\n", "get_concert_info: 1\n", "search_movies_by_actor: 1\n", "make_appointment: 1\n", "get_quotations: 1\n", "find_movies: 1\n", "generate_payment_invoice: 1\n", "calculate_income_tax: 1\n", "get_tv_show_schedule: 1\n", "bookFlight: 1\n", "calculate_loan: 1\n", "shuffle_list: 1\n", "track_daily_calories: 1\n", "calculate_circle_circumference: 1\n", "check_credit_score: 1\n", "search_nearest_gas_station: 1\n", "calculateTax: 1\n", "transfer_funds: 1\n", "analyze_social_network: 1\n", "check_email_syntax: 1\n", "check_word: 1\n", "check_moon_phase: 1\n", "retrieve_book_details: 1\n", "calculate_sleep_duration: 1\n", "search_artists: 1\n", "convert_currencies: 1\n", "calculate_fitness_goal: 1\n", "get_github_repositories: 1\n", "get_exercise_plan: 1\n", "calculate_lcm: 1\n" ] } ], "source": [ "print(\"\\nTool Usage:\")\n", "print(\"Available Tools Distribution:\")\n", "tool_dist = Counter(all_tools)\n", "for tool, count in tool_dist.most_common():\n", " print(f\"{tool}: {count}\")" ] }, { "cell_type": "code", "execution_count": 61, "id": "a58fbf62-d2e1-45f7-8fe5-317fdb44d138", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Tool Calls Distribution:\n", "calculate_distance: 4591\n", "convert_currency: 4224\n", "get_stock_price: 3408\n", "calculate_discount: 2960\n", "calculate_bmi: 2943\n", "calculate_tip: 2809\n", "calculate_age: 2729\n", "generate_random_number: 2690\n", "calculate_area: 2599\n", "get_movie_details: 2288\n", "search_books: 2200\n", "search_recipes: 1873\n", "generate_qr_code: 1774\n", "generate_password: 1628\n", "calculate_loan_payment: 1502\n", "search_movies: 1360\n", "send_email: 1334\n", "generate_random_password: 1210\n", "translate_text: 1175\n", "analyze_sentiment: 1149\n", "get_definition: 1057\n", "get_news: 1002\n", "create_calendar_event: 957\n", "create_todo: 955\n", "get_news_headlines: 790\n", "calculate_tax: 760\n", "search_recipe: 745\n", "calculate_mortgage_payment: 742\n", "search_restaurants: 639\n", "search_movie: 605\n", "play_music: 579\n", "convert_temperature: 573\n", "generate_random_quote: 498\n", "create_note: 496\n", "calculate_shipping_cost: 491\n", "generate_invoice: 463\n", "get_random_fact: 462\n", "create_invoice: 375\n", "search_news: 371\n", "get_random_joke: 370\n", "search_jobs: 365\n", "calculate_discounted_price: 343\n", "generate_barcode: 332\n", "calculate_interest: 317\n", "calculate_average: 315\n", "check_email_availability: 313\n", "calculate_gpa: 313\n", "check_palindrome: 297\n", "create_user: 291\n", "generate_random_color: 290\n", "search_book: 274\n", "calculate_mortgage: 268\n", "generate_username: 221\n", "calculate_fibonacci_sequence: 215\n", "get_random_quote: 214\n", "schedule_meeting: 214\n", "search_product: 210\n", "analyze_image: 210\n", "get_current_time: 209\n", "create_event: 194\n", "search_images: 181\n", "calculate_profit: 175\n", "execute_program: 154\n", "get_random_number: 153\n", "find_nearby_restaurants: 132\n", "check_word_count: 131\n", "find_nearest_gas_station: 131\n", "create_user_account: 129\n", "search_music: 128\n", "encrypt_text: 127\n", "create_task: 125\n", "get_news_articles: 124\n", "get_recipe: 119\n", "generate_random_fact: 114\n", "create_contact: 109\n", "find_shortest_path: 107\n", "calculate_sales_tax: 106\n", "get_translation: 106\n", "calculate_factorial: 105\n", "calculate_age_difference: 105\n", "get_movie_recommendations: 105\n", "calculate_percentage: 102\n", "calculate_square_root: 101\n", "track_package: 96\n", "find_restaurants: 93\n", "create_reminder: 91\n", "calculate_fibonacci: 89\n", "search_restaurant: 89\n", "calculate_route: 89\n", "search_hotels: 88\n", "check_flight_status: 87\n", "count_words: 86\n", "search_song: 85\n", "calculate_loan_interest: 83\n", "track_expenses: 83\n", "create_todo_list: 81\n", "find_nearby_places: 79\n", "add_numbers: 78\n", "track_calories: 77\n", "generate_uuid: 74\n", "find_movie: 74\n", "generate_random_name: 72\n", "create_account: 72\n", "calculate_rectangle_area: 72\n", "create_playlist: 71\n", "calculate_route_distance: 71\n", "check_spelling: 71\n", "create_user_profile: 70\n", "calculate_gross_salary: 69\n", "calculate_gcd: 69\n", "calculate_loan_repayment: 68\n", "check_prime_number: 68\n", "generate_random_username: 67\n", "get_exchange_rate: 63\n", "check_website_availability: 62\n", "calculate_tip_split: 59\n", "search_wikipedia: 58\n", "calculate_volume: 58\n", "check_stock_price: 57\n", "calculate_fuel_cost: 56\n", "find_hotels: 55\n", "send_sms: 55\n", "book_flight: 55\n", "calculate_fuel_efficiency: 55\n", "search_events: 54\n", "calculate_salary: 53\n", "check_website_status: 51\n", "make_note: 49\n", "calculate_profit_margin: 47\n", "get_sports_scores: 47\n", "search_products: 45\n", "calculate_square: 45\n", "find_nearest_restaurant: 45\n", "generate_qrcode: 44\n", "check_email: 42\n", "generate_quote: 42\n", "get_movie_info: 40\n", "search_definition: 39\n", "calculate_fuel_consumption: 39\n", "analyze_website: 38\n", "create_poll: 38\n", "generate_random_string: 38\n", "calculate_fahrenheit_to_celsius: 37\n", "analyze_text: 36\n", "check_username_availability: 36\n", "play_sound: 36\n", "calculate_loan_payments: 35\n", "generate_anagram: 34\n", "calculate_future_value: 32\n", "calculate_triangle_area: 32\n", "calculate_carbon_footprint: 31\n", "check_stock_availability: 31\n", "get_quote_of_the_day: 31\n", "upload_file: 30\n", "validate_email: 30\n", "get_directions: 30\n", "book_hotel: 29\n", "calculate_tip_amount: 28\n", "calculate_calories_burned: 28\n", "analyze_social_media_sentiment: 27\n", "calculate_sum: 26\n", "detect_language: 26\n", "convert_units: 26\n", "generate_random_numbers: 26\n", "calculate_time_difference: 24\n", "calculate_calories: 24\n", "search_articles: 24\n", "get_stock_prices: 24\n", "add_contact: 23\n", "generate_random_joke: 23\n", "find_restaurant: 23\n", "fetch_news: 22\n", "calculate_duration: 21\n", "get_currency_exchange_rate: 21\n", "generate_meme: 20\n", "analyze_website_performance: 20\n", "get_word_synonyms: 20\n", "get_word_definition: 20\n", "generate_fibonacci_sequence: 20\n", "calculate_tip_percentage: 20\n", "calculate_speed: 19\n", "check_movie_showtimes: 19\n", "encrypt_message: 19\n", "calculate_median: 18\n", "order_food: 18\n", "add_task: 18\n", "find_common_elements: 18\n", "calculate_car_emissions: 17\n", "search_movies_by_genre: 17\n", "check_email_validity: 17\n", "play_song: 17\n", "add_contacts: 16\n", "calculate_loan_emi: 16\n", "search_tweets: 16\n", "calculate_body_mass_index: 16\n", "reverse_string: 16\n", "get_horoscope: 16\n", "send_notification: 16\n", "get_traffic_info: 16\n", "find_movie_recommendations: 15\n", "get_time: 15\n", "calculate_rectangle_perimeter: 15\n", "get_recipe_details: 15\n", "get_upcoming_events: 15\n", "check_word_anagram: 15\n", "search_job: 15\n", "get_sunset_time: 15\n", "encrypt_data: 15\n", "get_job_details: 14\n", "analyze_customer_reviews: 14\n", "find_recipe: 14\n", "check_prime: 14\n", "get_user_profile: 14\n", "search_news_articles: 14\n", "calculate_loan_emis: 14\n", "get_quote: 14\n", "analyze_product_reviews: 13\n", "search_songs: 13\n", "search_hotel: 13\n", "get_movie_reviews: 13\n", "recommend_books: 13\n", "get_note: 13\n", "get_joke: 12\n", "get_calendar_events: 12\n", "search_movie_reviews: 12\n", "generate_unique_id: 12\n", "get_book_details: 11\n", "convert_length: 11\n", "analyze_customer_feedback: 11\n", "calculate_taxes: 11\n", "get_movie_recommendation: 11\n", "get_quotes: 11\n", "calculate_pace: 11\n", "calculate_perimeter: 11\n", "calculateBMI: 10\n", "shuffle_array: 10\n", "validate_credit_card: 10\n", "generate_random_word: 10\n", "calculate_shipping_time: 10\n", "calculate_body_fat_percentage: 10\n", "create_new_user: 10\n", "find_route: 10\n", "create_event_reminder: 9\n", "analyze_customer_sentiment: 9\n", "analyze_audio: 9\n", "search_image: 9\n", "check_word_definition: 9\n", "delete_note: 9\n", "generate_password_strength: 9\n", "find_nearby_hotels: 9\n", "calculate_hypotenuse: 9\n", "get_top_news: 9\n", "get_pokemon_details: 8\n", "generate_random_password_strength: 8\n", "create_todo_item: 8\n", "analyze_stock_market: 8\n", "search_contacts: 8\n", "search_flights: 8\n", "search_quotes: 8\n", "calculate_car_loan_payment: 8\n", "analyze_website_traffic: 8\n", "calculate_trip_distance: 8\n", "get_song_lyrics: 8\n", "create_survey: 8\n", "add_to_shopping_list: 8\n", "find_book: 8\n", "add_to_shopping_cart: 8\n", "find_hotel: 8\n", "check_word_availability: 7\n", "add_note: 7\n", "count_occurrences: 7\n", "get_user_info: 7\n", "calculate_car_loan: 7\n", "post_to_social_media: 7\n", "generate_password_reset_token: 7\n", "generate_report: 7\n", "generate_sudoku: 7\n", "analyze_social_media: 7\n", "solve_equation: 7\n", "get_news_feed: 7\n", "calculate_area_volume: 7\n", "check_anagram: 7\n", "check_availability: 7\n", "analyze_twitter_sentiment: 7\n", "calculate_age_in_days: 7\n", "search_videos: 7\n", "get_notes: 7\n", "get_latest_news: 6\n", "take_notes: 6\n", "get_daily_news: 6\n", "calculate_circumference: 6\n", "generate_password_reset_link: 6\n", "create_blog_post: 6\n", "get_holidays: 6\n", "get_synonyms: 6\n", "check_word_similarity: 6\n", "roll_dice: 6\n", "find_prime_numbers: 6\n", "recommend_movie: 6\n", "sort_numbers: 6\n", "search_places: 6\n", "check_stock: 6\n", "schedule_appointment: 6\n", "calculate_savings: 6\n", "generate_invoice_number: 6\n", "generate_random_sentence: 6\n", "find_movie_details: 6\n", "get_random_quote_of_the_day: 6\n", "record_audio: 6\n", "find_movie_showtimes: 5\n", "find_closest_gas_station: 5\n", "calculate_premium: 5\n", "identify_language: 5\n", "calculate_rental_income: 5\n", "calculate_distance_traveled: 5\n", "analyze_stock: 5\n", "make_payment: 5\n", "calculate_mortgage_payments: 5\n", "post_social_media_status: 5\n", "find_nearest_coffee_shop: 5\n", "get_daily_horoscope: 5\n", "reserve_table: 5\n", "generate_hash: 5\n", "generate_phone_number: 5\n", "search_parks: 5\n", "track_fitness_activity: 5\n", "set_reminder: 5\n", "scan_barcode: 5\n", "calculate_circle_area: 5\n", "get_current_date: 5\n", "convert_weight: 5\n", "get_lyrics: 5\n", "find_median: 5\n", "analyze_text_sentiment: 5\n", "get_flight_status: 5\n", "calculate_emission: 5\n", "get_location_coordinates: 5\n", "make_notes: 5\n", "evaluate_expression: 5\n", "search_stock_price: 5\n", "send_push_notification: 5\n", "track_fitness_progress: 5\n", "search_movie_theaters: 5\n", "calculate_square_area: 5\n", "get_sport_scores: 5\n", "get_road_traffic: 5\n", "get_random_recipe: 4\n", "get_product_details: 4\n", "create_new_note: 4\n", "search_podcast: 4\n", "play_video: 4\n", "search_for_restaurants: 4\n", "calculate_emissions: 4\n", "check_visa_requirements: 4\n", "generate_password_hash: 4\n", "search_for_movies: 4\n", "get_recommended_books: 4\n", "get_current_news: 4\n", "perform_translation: 4\n", "get_contact_info: 4\n", "create_new_task: 4\n", "generate_random_date: 4\n", "send_message: 4\n", "analyze_text_similarity: 4\n", "generate_id: 4\n", "analyze_stock_performance: 4\n", "calculate_lifespan: 4\n", "find_highest_number: 4\n", "rate_movie: 4\n", "search_files: 4\n", "calculate_age_in_months: 4\n", "recommend_movies: 4\n", "find_word_synonyms: 4\n", "get_movie_showtimes: 4\n", "calculate_rental_cost: 4\n", "sort_array: 4\n", "get_traffic_status: 4\n", "perform_calculator_operation: 4\n", "get_definition_of_acronym: 4\n", "get_github_repos: 4\n", "execute_command: 4\n", "get_word_definitions: 4\n", "play_game: 4\n", "get_stock_info: 4\n", "generate_random_number_sequence: 4\n", "fetch_news_articles: 4\n", "get_recipe_ingredients: 3\n", "analyze_sales_data: 3\n", "get_daily_quote: 3\n", "take_screenshot: 3\n", "check_password_strength: 3\n", "track_fitness: 3\n", "calculate_rent: 3\n", "find_song_lyrics: 3\n", "generate_quiz: 3\n", "get_sudoku_solution: 3\n", "generate_fake_data: 3\n", "get_song_recommendations: 3\n", "calculate_cylinder_volume: 3\n", "calculate_retirement_savings: 3\n", "find_nearby_gas_stations: 3\n", "create_post: 3\n", "calculate_total_price: 3\n", "create_schedule: 3\n", "calculate_vat: 3\n", "get_sunrise_sunset: 3\n", "find_books: 3\n", "check_email_existence: 3\n", "create_folder: 3\n", "analyze_tweet: 3\n", "track_sleep: 3\n", "get_word_count: 3\n", "find_longest_word: 3\n", "analyze_text_language: 3\n", "encode_base64: 3\n", "get_file_size: 3\n", "generate_recommendation: 3\n", "find_nearby_parks: 3\n", "calculate_score: 3\n", "search_in_database: 3\n", "count_characters: 3\n", "check_movie_schedule: 3\n", "create_to_do_list: 3\n", "search_for_books: 3\n", "create_task_reminder: 3\n", "perform_sentiment_analysis: 3\n", "search_location: 3\n", "generate_thumbnail: 3\n", "calculate_gas_cost: 3\n", "find_max: 3\n", "check_bus_schedule: 3\n", "calculate_discounted_percentage: 3\n", "search_nearby_places: 3\n", "get_poem: 3\n", "get_next_prime: 3\n", "analyze_sentences: 3\n", "calculate_roi: 3\n", "calculate BMI: 2\n", "search_database: 2\n", "find_movie_info: 2\n", "create_recipe: 2\n", "get_dog_breed: 2\n", "get_live_traffic_info: 2\n", "get_random_word: 2\n", "get_music_recommendations: 2\n", "find_hot_restaurants: 2\n", "check_ip_address: 2\n", "generate_random_song: 2\n", "search_lyrics: 2\n", "calculate_total: 2\n", "search_artist: 2\n", "generate_calendar_event: 2\n", "getNewsHeadlines: 2\n", "calculate_route_duration: 2\n", "get_definitions: 2\n", "search_movie_by_genre: 2\n", "generate_prime_numbers: 2\n", "find_file: 2\n", "search_hiking_trails: 2\n", "create_new_account: 2\n", "get_recipe_instructions: 2\n", "calculate_mean: 2\n", "find_music: 2\n", "get_nutrition_info: 2\n", "check_word_palindrome: 2\n", "generate_license_key: 2\n", "fetch_news_headlines: 2\n", "calculate_daily_calorie_intake: 2\n", "compute_fibonacci: 2\n", "getRandomFact: 2\n", "generate_recommendations: 2\n", "save_contact: 2\n", "analyze_video: 2\n", "check_text_sentiment: 2\n", "add_two_numbers: 2\n", "calculate_commission: 2\n", "calculate_payment: 2\n", "get_pokemon_data: 2\n", "search_contact: 2\n", "find_nearby_cafes: 2\n", "identify_object: 2\n", "check_spellings: 2\n", "get_fuel_price: 2\n", "convert_image_format: 2\n", "get_daily_stock_price: 2\n", "generate_short_url: 2\n", "calculate_total_cost: 2\n", "buy_product: 2\n", "analyze_social_media_mentions: 2\n", "get_random_dog_image: 2\n", "find_hotel_rooms: 2\n", "calculate_loan_amortization: 2\n", "check_grammar: 2\n", "get_time_zone: 2\n", "search_shoes: 2\n", "check_word_meaning: 2\n", "calculate_shipping: 2\n", "get_person_details: 2\n", "get_holiday_dates: 2\n", "calculate_age_in_hours: 2\n", "schedule_maintenance: 2\n", "analyze_stock_data: 2\n", "check_word_spell: 2\n", "create_new_contact: 2\n", "calculate_discounted_amount: 2\n", "search_place: 2\n", "search_albums: 2\n", "get_current_weather: 2\n", "add_calendar_event: 2\n", "calculate_exchange_rate: 2\n", "post_tweet: 2\n", "check_word_spelling: 2\n", "find_nearest_parking_lot: 2\n", "check_email_spam: 2\n", "get_language_translation: 2\n", "analyze_market_trends: 2\n", "analyze_customer_churn: 2\n", "find_nearest_park: 2\n", "calculate_area_of_circle: 2\n", "get_distance: 2\n", "add_notes: 2\n", "find_music_recommendations: 2\n", "calculate_car_fuel_efficiency: 2\n", "delete_calendar_event: 2\n", "generate_riddle: 2\n", "check_if_prime: 2\n", "validate_password: 2\n", "calculateDistance: 2\n", "search_coffee_shops: 2\n", "calculate_apr: 2\n", "calculate_discounted_price_with_coupon: 2\n", "search_cities: 2\n", "search_holidays: 2\n", "get_sunrise_sunset_time: 2\n", "book_table: 2\n", "get_current_temperature: 2\n", "get_exchange_rates: 2\n", "calculate_car_loan_emis: 2\n", "calculate_squared: 2\n", "get_nearby_restaurants: 2\n", "post_note: 2\n", "book_appointment: 2\n", "get_complementary_color: 2\n", "analyze_tone: 2\n", "find_distance: 2\n", "add_task_to_todo_list: 2\n", "check_file_existence: 2\n", "get_dictionary_definition: 2\n", "create_social_media_post: 2\n", "calculate_recurring_payment: 2\n", "get_road_conditions: 2\n", "get_movie_information: 2\n", "get_defect_count: 2\n", "execute_shell_command: 2\n", "search_for_hotels: 2\n", "get_restaurant_reviews: 2\n", "check_news: 2\n", "get_traffic_report: 2\n", "recommend_products: 2\n", "calculate_rental_price: 2\n", "check_movie_rating: 2\n", "check_word_frequency: 2\n", "calculate_celsius_to_fahrenheit: 2\n", "check_email_domain: 2\n", "get_sunrise_time: 2\n", "get_conversion_rate: 2\n", "get_movie_data: 2\n", "get_nearby_events: 2\n", "save_note: 2\n", "check_movie_reviews: 2\n", "convertTemperature: 2\n", "search_repositories: 2\n", "parse_csv: 2\n", "get_location_details: 2\n", "calculate_rental_profit: 2\n", "check_phone_number: 2\n", "record_notes: 2\n", "analyze_sentiment_tone: 2\n", "check_domain_availability: 2\n", "post_social_media: 2\n", "create_email: 2\n", "get_random_factoid: 2\n", "analyze_social_media_posts: 2\n", "verify_credit_card: 2\n", "convert_time_zone: 2\n", "search_stock: 2\n", "check_isbn: 2\n", "perform_google_search: 2\n", "analyze_health_data: 2\n", "predict_stock_price: 2\n", "random_number: 2\n", "analyze_tweet_sentiment: 2\n", "random_number_generator: 2\n", "get_definition_synonyms: 2\n", "get_temperature: 2\n", "calculate_rectangle_diagonal: 2\n", "multiply: 2\n", "check_if_website_is_up: 2\n", "add: 2\n", "search_product_reviews: 2\n", "find_closest_parking: 2\n", "retrieve_contact: 2\n", "find_nearby_events: 2\n", "calculate_conversions: 2\n", "calculate_biorhythm: 2\n", "retrieve_contact_info: 2\n", "searchBooks: 2\n", "calculate_exponent: 2\n", "search_exercises: 2\n", "get_facts: 2\n", "get_currency_conversion_rate: 2\n", "get_concert_info: 2\n", "search_movies_by_actor: 2\n", "make_appointment: 2\n", "get_quotations: 2\n", "get_tv_show_schedule: 2\n", "check_word: 2\n", "find_closest_store: 2\n", "find_closest_restaurant: 2\n", "search_artists: 2\n", "calculate_lcm: 2\n", "find_events: 1\n", "randomize_list: 1\n", "find_closest_pizza_place: 1\n", "generate_license_plate: 1\n", "search_author: 1\n", "submit_feedback: 1\n", "find_bus_route: 1\n", "get_current_exchange_rates: 1\n", "generate_schedule: 1\n", "create_alert: 1\n", "analyze_fraud_activity: 1\n", "calculate_paint_required: 1\n", "schedule_social_media_post: 1\n", "searchRecipes: 1\n", "generate_birthday_card: 1\n", "sort_list: 1\n", "analyze_traffic: 1\n", "send_text_message: 1\n", "record_expense: 1\n", "get_recipes: 1\n", "simulate_dice_roll: 1\n", "generate_quote_of_the_day: 1\n", "get_stock_history: 1\n", "locate_nearby_places: 1\n", "create_journal_entry: 1\n", "calculate_fitness_level: 1\n", "search_music_albums: 1\n", "play_sound_effect: 1\n", "get_random_trivia: 1\n", "get_recipes_by_ingredients: 1\n", "calculate_tips: 1\n", "create_thumbnail: 1\n", "upload_image: 1\n", "calculate_tip_share: 1\n", "schedule_event: 1\n", "create_new_event: 1\n", "get_currency_conversion: 1\n", "calculateMortgagePayment: 1\n", "calculate_gas_mileage: 1\n", "calculate_net_pay: 1\n", "generate_nickname: 1\n", "detect_faces: 1\n", "find_cheapest_product: 1\n", "generate_username_password: 1\n", "check_email_format: 1\n", "calculate_days_between_dates: 1\n", "check_route_traffic: 1\n", "calculate_fibonacci_series: 1\n", "find_largest_number: 1\n", "suggest_friends: 1\n", "find_nearest_store: 1\n", "get_total_expenses: 1\n", "get_traffic_updates: 1\n", "calculate_bill: 1\n", "create_guest_list: 1\n", "verify_email_address: 1\n", "generate_unique_identifier: 1\n", "get_upcoming_concerts: 1\n", "calculate_quadratic_equation: 1\n", "searchRestaurants: 1\n", "calculate_discount_amount: 1\n", "get_driving_directions: 1\n", "analyze_movie_reviews: 1\n", "calculate_miles_per_gallon: 1\n", "find_song: 1\n", "validate_password_strength: 1\n", "create_ticket: 1\n", "get_public_transport_routes: 1\n", "get_relevant_articles: 1\n", "get_random_quote_category: 1\n", "get_random_fact_of_the_day: 1\n", "calculate_recipe_calories: 1\n", "get_forecast: 1\n", "create_password: 1\n", "create_resume: 1\n", "find_smallest_number: 1\n", "identify_plants: 1\n", "calculate_discounted_price_range: 1\n", "get_public_ip: 1\n", "analyze_text_complexity: 1\n", "find_cafe_nearby: 1\n", "analyze_social_media_post: 1\n", "generate_email: 1\n", "run_script: 1\n", "check_blockchain_balance: 1\n", "analyze_tweets: 1\n", "validate_email_address: 1\n", "fetch_stock_price: 1\n", "search_books_by_author: 1\n", "get_country_info: 1\n", "calculate_delivery_time: 1\n", "read_file: 1\n", "find_parking: 1\n", "find_nearest_restaurants: 1\n", "check_word_spellings: 1\n", "search_nearby_hotels: 1\n", "create_random_password: 1\n", "analyze_stock_portfolio: 1\n", "generate_random_password_complex: 1\n", "create_random_username: 1\n", "find_factorial: 1\n", "generate_random_password_special: 1\n", "search_recipe_by_ingredients: 1\n", "search_health_symptoms: 1\n", "create_file: 1\n", "create_password_hash: 1\n", "search_flight: 1\n", "find_mismatch: 1\n", "start_timer: 1\n", "perform_stock_analysis: 1\n", "calculate_discounted_total: 1\n", "find_similar_products: 1\n", "get_random_name: 1\n", "generate_expense_report: 1\n", "book_movie_tickets: 1\n", "check_road_conditions: 1\n", "analyze_user_sentiment: 1\n", "search_in_array: 1\n", "analyze_text_length: 1\n", "find_suggestions: 1\n", "identify_face: 1\n", "find_nearby_hospitals: 1\n", "find_movie_reviews: 1\n", "get_recipe_suggestions: 1\n", "delete_folder: 1\n", "record_note: 1\n", "calculate_stats: 1\n", "analyze_data: 1\n", "read_text_file: 1\n", "check_url_status: 1\n", "classify_image: 1\n", "add_todo: 1\n", "calculate_percentile: 1\n", "track_calorie_intake: 1\n", "get_route_directions: 1\n", "find_max_value: 1\n", "generate_unique_code: 1\n", "create_roadmap: 1\n", "calculate_mortgage_repayment: 1\n", "perform_spell_check: 1\n", "calculate_grade: 1\n", "track_fitness_goals: 1\n", "generate_random_password_with_constraints: 1\n", "check_license_plate: 1\n", "calculateTip: 1\n", "solve_quadratic_equation: 1\n", "capture_screenshot: 1\n", "get_random_pokemon: 1\n", "find_similar_movies: 1\n", "analyze_email: 1\n", "search_museums: 1\n", "check_webpage_status: 1\n", "generatePassword: 1\n", "calculate_combinations: 1\n", "calculate_battery_life: 1\n", "find_recipes: 1\n", "encode_url: 1\n", "receive_payment: 1\n", "find_similar_images: 1\n", "get_earthquake_data: 1\n", "search_twitter: 1\n", "create_todo_task: 1\n", "generate_jwt_token: 1\n", "calculate_car_lease_payment: 1\n", "calculateLoanPayment: 1\n", "update_calendar: 1\n", "find_nearest_parking: 1\n", "find_nearest_hotels: 1\n", "get_book_recommendations: 1\n", "calculate_vehicle_mileage: 1\n", "search_movie_theater: 1\n", "check_file_exists: 1\n", "get_length: 1\n", "delete_file: 1\n", "get_next_holiday: 1\n", "query_database: 1\n", "get_historical_data: 1\n", "convert_celsius_to_fahrenheit: 1\n", "get_bus_schedule: 1\n", "calculate_days_until_event: 1\n", "calculate_percentages: 1\n", "calculate_loan_affordability: 1\n", "get_file_contents: 1\n", "get_hot_deals: 1\n", "calculate_correlation: 1\n", "rate_product: 1\n", "calculate_tip_percent: 1\n", "mark_todo_as_complete: 1\n", "purchase_product: 1\n", "calculate_triangle_perimeter: 1\n", "solve_sudoku: 1\n", "encode_image: 1\n", "find_nearest_pharmacy: 1\n", "calculate_age_in_seconds: 1\n", "get_recommendations: 1\n", "compute_average: 1\n", "find_hotel_deals: 1\n", "calculateInterest: 1\n", "check_brackets: 1\n", "get_stock_quotes: 1\n", "calculate_profit_loss: 1\n", "calculate_quiz_score: 1\n", "make_todo: 1\n", "calculate_car_fuel_cost: 1\n", "calculate_car_fuel_consumption: 1\n", "get_random_dog_fact: 1\n", "store_data: 1\n", "generate_pdf: 1\n", "generate_greeting: 1\n", "play_playlist: 1\n", "create_employee_profile: 1\n", "get_current_stock_price: 1\n", "get_social_media_posts: 1\n", "calculate_elapsed_time: 1\n", "calculateDiscount: 1\n", "generateQRCode: 1\n", "generate_resume: 1\n", "calculate_bmi_category: 1\n", "find_shortest_route: 1\n", "calculate_power: 1\n", "download_file: 1\n", "search_for_recipes: 1\n", "find_nearest_pizza_place: 1\n", "calculate_pizza_cost: 1\n", "add_to_cart: 1\n", "get_social_media_stats: 1\n", "calculate_body_mass: 1\n", "get_song_recommendation: 1\n", "analyze_stock_price: 1\n", "get_location_info: 1\n", "find_movie_rating: 1\n", "get_exercise_recommendation: 1\n", "analyze_user_behavior: 1\n", "calculate_pension: 1\n", "calculate_pizza_area: 1\n", "find_nearest_hospital: 1\n", "get_shopping_list: 1\n", "search_for_jobs: 1\n", "parse_email: 1\n", "calculate_sale_price: 1\n", "search_for_product: 1\n", "search_restaurants_by_cuisine: 1\n", "detect_object: 1\n", "track_order: 1\n", "verify_email: 1\n", "get_user_data: 1\n", "find_average: 1\n", "complete_task: 1\n", "searchMovies: 1\n", "search_flickr_images: 1\n", "retrieve_movie_details: 1\n", "calculate_shipping_distance: 1\n", "retrieve_user_profile: 1\n", "calculate_shopping_discount: 1\n", "calculate_total_expenses: 1\n", "find_nearby_parking: 1\n", "calculate_discount_percent: 1\n", "calculate_net_salary: 1\n", "get_random_quote_by_author: 1\n", "get_user_details: 1\n", "play_audio: 1\n", "search_book_recommendations: 1\n", "calculate_lease_payment: 1\n", "calculate_statistics: 1\n", "get_fact: 1\n", "generate_email_signature: 1\n", "retrieve_user_details: 1\n", "register_user: 1\n", "write_note: 1\n", "get_exercise_recommendations: 1\n", "find_max_number: 1\n", "calculate_repayment_schedule: 1\n", "check_lottery_results: 1\n", "check_movie_timing: 1\n", "calculate_earnings: 1\n", "find_movies: 1\n", "generate_payment_invoice: 1\n", "calculate_income_tax: 1\n", "bookFlight: 1\n", "calculate_loan: 1\n", "shuffle_list: 1\n", "track_daily_calories: 1\n", "calculate_circle_circumference: 1\n", "check_credit_score: 1\n", "generate_credit_card_number: 1\n", "search_nearest_gas_station: 1\n", "calculateTax: 1\n", "find_lyrics: 1\n", "suggest_book: 1\n", "check_moon_phase: 1\n", "set_alarm: 1\n", "retrieve_book_details: 1\n", "calculate_sleep_duration: 1\n", "generate_checksum: 1\n", "convert_currencies: 1\n", "calculate_fitness_goal: 1\n", "get_github_repositories: 1\n", "get_exercise_plan: 1\n" ] } ], "source": [ "print(\"\\nTool Calls Distribution:\")\n", "call_dist = Counter(all_calls)\n", "for call, count in call_dist.most_common():\n", " print(f\"{call}: {count}\")" ] }, { "cell_type": "code", "execution_count": null, "id": "8703e34d-aede-48f1-8872-e0ba40f31b1e", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "fb81043b-f022-43cc-bf29-44115cc1f41e", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 62, "id": "c6e318c0-fb44-4bd5-996e-1d0e93f8f0b3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Frequency')" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(12, 4))\n", "plt.subplot(1, 2, 1)\n", "df['num_messages'].hist(bins=20)\n", "plt.title('Messages per Conversation')\n", "plt.xlabel('Number of Messages')\n", "plt.ylabel('Frequency')" ] }, { "cell_type": "code", "execution_count": 63, "id": "6b87cc2d-8ff6-4a78-81c8-d046121dac6e", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.subplot(1, 2, 2)\n", "df['num_tool_calls'].hist(bins=20)\n", "plt.title('Tool Calls per Conversation')\n", "plt.xlabel('Number of Tool Calls')\n", "plt.ylabel('Frequency')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 64, "id": "db7c79e2-d835-417b-82c7-3e2dd3d00f85", "metadata": {}, "outputs": [], "source": [ "def analyze_conversation_patterns(flows):\n", " patterns = []\n", " for flow in flows:\n", " pattern = []\n", " for msg in flow:\n", " if msg['has_tool_calls']:\n", " pattern.append('TOOL_CALL')\n", " elif msg['role'] == 'tool':\n", " pattern.append('TOOL_RESPONSE')\n", " else:\n", " pattern.append(msg['role'].upper())\n", " patterns.append('->'.join(pattern))\n", " return Counter(patterns)" ] }, { "cell_type": "code", "execution_count": 65, "id": "181a9a6c-6e20-4255-9574-841535679600", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Most Common Conversation Patterns:\n", "SYSTEM->USER->ASSISTANT: 6819\n", "SYSTEM->SYSTEM->USER->ASSISTANT: 6738\n", "SYSTEM->USER->ASSISTANT->USER->ASSISTANT: 6353\n", "USER->ASSISTANT->USER->ASSISTANT: 6151\n", "SYSTEM->USER->TOOL_CALL->TOOL_RESPONSE->ASSISTANT: 5959\n" ] } ], "source": [ "conversation_patterns = analyze_conversation_patterns(df['conversation_flow'])\n", "print(\"\\nMost Common Conversation Patterns:\")\n", "for pattern, count in conversation_patterns.most_common(5):\n", " print(f\"{pattern}: {count}\")" ] }, { "cell_type": "code", "execution_count": 66, "id": "cbf49a65-a93b-4b51-85a1-0dba42c5da4e", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 5))\n", "sns.histplot(data=df, x='user_query_length', bins=50)\n", "plt.title('Distribution of User Query Lengths')\n", "plt.xlabel('Query Length (characters)')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 67, "id": "6f9249df-b5e7-4e8c-9654-7e950bead9fa", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Most Common Tool Call Sequences:\n", "tool_calls\n", "[calculate_bmi] 2701\n", "[calculate_age] 2665\n", "[calculate_tip] 2363\n", "[calculate_distance, calculate_distance] 1882\n", "[calculate_discount] 1837\n", "Name: count, dtype: int64\n" ] } ], "source": [ "tool_sequences = df[df['num_tool_calls'] > 0]['tool_calls'].value_counts()\n", "print(\"\\nMost Common Tool Call Sequences:\")\n", "print(tool_sequences.head())" ] }, { "cell_type": "code", "execution_count": null, "id": "4ae94662-c5cc-4710-ad0e-09d0924b013c", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 68, "id": "6f8638ae-393b-47a1-8d72-3fd9c6590c2f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Sample Conversation Analysis:\n", "\n", "User Query: Hi, can you tell me the current stock price of Apple?\n", "Number of Messages: 11\n", "Available Tools: ['get_stock_price']\n", "Tool Calls Made: ['get_stock_price', 'get_stock_price']\n" ] } ], "source": [ "print(\"\\nSample Conversation Analysis:\")\n", "sample_idx = np.random.randint(len(df))\n", "sample = df.iloc[sample_idx]\n", "print(f\"\\nUser Query: {sample['user_query']}\")\n", "print(f\"Number of Messages: {sample['num_messages']}\")\n", "print(f\"Available Tools: {sample['available_tools']}\")\n", "print(f\"Tool Calls Made: {sample['tool_calls']}\")" ] }, { "cell_type": "code", "execution_count": 69, "id": "9ec1f9dc-ae4a-4ccc-8764-89e2e6c3b10a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Tool Call Success Analysis:\n", "Success Rate: 100.00%\n" ] } ], "source": [ "def has_error_message(conv_flow):\n", " \"\"\"Check if conversation has error patterns\"\"\"\n", " tool_responses = [msg for msg in conv_flow if msg['role'] == 'tool']\n", " return any('error' in str(msg.get('content', '')).lower() for msg in tool_responses)\n", "\n", "df['has_errors'] = df['conversation_flow'].apply(has_error_message)\n", "print(\"\\nTool Call Success Analysis:\")\n", "print(f\"Success Rate: {(1 - df['has_errors'].mean()) * 100:.2f}%\")" ] }, { "cell_type": "markdown", "id": "d382beb5-785b-44ed-978a-315e1636d9e6", "metadata": {}, "source": [ "### Reflection-v1 Glaive ai\n", "\n", "- Apache 2.0\n", "- 60k examples\n", "- https://huggingface.co/datasets/glaiveai/reflection-v1" ] }, { "cell_type": "code", "execution_count": 70, "id": "9445c17d-88b6-4543-bc5a-977d74701024", "metadata": {}, "outputs": [], "source": [ "d = load_dataset(\"glaiveai/glaive-function-calling-v2\")" ] }, { "cell_type": "code", "execution_count": 71, "id": "3a946d48-b9b5-4a54-bb86-9a46d9404a13", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'system': 'SYSTEM: You are a helpful assistant, with no access to external functions.\\n\\n',\n", " 'chat': 'USER: How can I write a C# program that calculates the difference between two given dates in years?\\nHere\\'s a starter code:\\nDateTime givenDate = new DateTime(2015, 8, 12);\\nDateTime currentDate = DateTime.Today;\\nTimeSpan difference = currentDate - givenDate;\\nint years = (int)(difference.TotalDays / 365.25);\\nConsole.WriteLine(\"The difference between the given date and today\\'s date is: \" + years + \" years.\");\\nYou can replace the given date with any date of your choice. How can this code be optimized for better performance?\\n\\nASSISTANT: The code you provided is already quite efficient, but there are a few optimizations you can make:\\n1. Instead of dividing by 365.25 to get the number of years, you can use the TotalDays property of the TimeSpan object and divide by the average number of days in a year (365.2425). This will give you a more accurate result.\\n2. You can use the TryParseExact method to parse the input dates, which will improve the performance and handle any formatting issues.\\nHere\\'s an optimized version of the code:\\nDateTime givenDate;\\nDateTime currentDate = DateTime.Today;\\nif (DateTime.TryParseExact(\"2015-08-12\", \"yyyy-MM-dd\", CultureInfo.InvariantCulture, DateTimeStyles.None, out givenDate))\\n{\\n TimeSpan difference = currentDate - givenDate;\\n int years = (int)(difference.TotalDays / 365.2425);\\n Console.WriteLine(\"The difference between the given date and today\\'s date is: \" + years + \" years.\");\\n}\\nelse\\n{\\n Console.WriteLine(\"Invalid date format.\");\\n}\\nYou can replace the input date and format with any values of your choice. <|endoftext|>\\n\\nUSER: Can you explain the difference between supervised and unsupervised machine learning?\\n\\nASSISTANT: Sure, supervised learning is a type of machine learning where the algorithm learns to map inputs to outputs based on labeled examples that are provided during training. Essentially, the algorithm is given “ground truth\" data to learn from. For example, given a dataset of cat and dog images, each image would be labeled with the corresponding animal.\\n\\nOn the other hand, unsupervised learning is a type of machine learning where the algorithm learns patterns in the data without being explicitly told what those patterns are. In other words, it tries to find structure in unlabeled data. This can be useful for tasks like clustering or dimensionality reduction.\\n\\nIn summary, supervised learning requires labeled data while unsupervised learning does not. <|endoftext|>'}" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][1455]" ] }, { "cell_type": "markdown", "id": "4dc94e2a-8ca4-4d46-928f-20c849feb82c", "metadata": {}, "source": [ "### Glaive-Function-calling-v2\n", "\n", "- Apache 2.0\n", "- 113k rows\n", "- https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2" ] }, { "cell_type": "code", "execution_count": 97, "id": "8393b2c2-4a96-44a1-af66-a2ca2f675e53", "metadata": {}, "outputs": [], "source": [ "d = load_dataset(\"glaiveai/glaive-function-calling-v2\")" ] }, { "cell_type": "code", "execution_count": 98, "id": "9f1c896e-f6b1-4299-afd9-e8e0e0461b42", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'system': 'SYSTEM: You are a helpful assistant with access to the following functions. Use them if required -\\n{\\n \"name\": \"generate_invoice\",\\n \"description\": \"Generate an invoice for a given product\",\\n \"parameters\": {\\n \"type\": \"object\",\\n \"properties\": {\\n \"product_name\": {\\n \"type\": \"string\",\\n \"description\": \"The name of the product\"\\n },\\n \"quantity\": {\\n \"type\": \"integer\",\\n \"description\": \"The quantity of the product\"\\n },\\n \"price\": {\\n \"type\": \"number\",\\n \"description\": \"The price of the product\"\\n },\\n \"discount_percentage\": {\\n \"type\": \"integer\",\\n \"minimum\": 0,\\n \"maximum\": 100,\\n \"description\": \"The discount percentage\"\\n }\\n },\\n \"required\": [\\n \"product_name\",\\n \"quantity\",\\n \"price\"\\n ]\\n }\\n}\\n',\n", " 'chat': 'USER: I need an invoice for 5 units of \"Smart TV\" each priced at $500. I also have a discount of 10%.\\n\\n\\nASSISTANT: {\"name\": \"generate_invoice\", \"arguments\": \\'{\"product_name\": \"Smart TV\", \"quantity\": 5, \"price\": 500, \"discount_percentage\": 10}\\'} <|endoftext|>\\n\\n\\nFUNCTION RESPONSE: {\"invoice_id\": \"INV12345\", \"product_name\": \"Smart TV\", \"quantity\": 5, \"price\": 500, \"discount_percentage\": 10, \"total_amount\": 2250, \"discount_amount\": 250, \"payable_amount\": 2000}\\n\\n\\nASSISTANT: Here is your invoice. The invoice ID is INV12345. You ordered 5 units of Smart TV each priced at $500. The total amount is $2250. You have a discount of 10% which amounts to $250. So, the final payable amount is $2000. <|endoftext|>\\n\\n\\n'}" ] }, "execution_count": 98, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][12312]" ] }, { "cell_type": "code", "execution_count": 99, "id": "dc73721e-76ed-40f5-bee2-a552a9169479", "metadata": {}, "outputs": [], "source": [ "def parse_system_functions(system_text):\n", " try:\n", " # Find the JSON object in the system message\n", " json_match = re.search(r'\\{.*\\}', system_text, re.DOTALL)\n", " if json_match:\n", " return json.loads(json_match.group())\n", " return None\n", " except json.JSONDecodeError:\n", " return None" ] }, { "cell_type": "code", "execution_count": 100, "id": "c8386fb0-a174-4f96-be37-83f1e6ebe1ec", "metadata": {}, "outputs": [], "source": [ "def parse_chat_content(chat_text):\n", " messages = []\n", " parts = [p.strip() for p in chat_text.split('\\n\\n\\n') if p.strip()]\n", " \n", " for part in parts:\n", " if part.startswith('USER:'):\n", " messages.append({\n", " 'role': 'user',\n", " 'content': part[5:].strip()\n", " })\n", " elif part.startswith('ASSISTANT:'):\n", " content = part[10:].strip()\n", " function_call = None\n", " function_match = re.search(r' (.*?) <\\|endoftext\\|>', content)\n", " if function_match:\n", " try:\n", " function_call = json.loads(function_match.group(1))\n", " # Parse the arguments if they're in string form\n", " if isinstance(function_call.get('arguments'), str):\n", " function_call['arguments'] = json.loads(function_call['arguments'])\n", " except json.JSONDecodeError:\n", " pass\n", " \n", " messages.append({\n", " 'role': 'assistant',\n", " 'content': content,\n", " 'function_call': function_call\n", " })\n", " elif part.startswith('FUNCTION RESPONSE:'):\n", " try:\n", " response = json.loads(part[17:].strip())\n", " messages.append({\n", " 'role': 'function',\n", " 'content': response\n", " })\n", " except json.JSONDecodeError:\n", " messages.append({\n", " 'role': 'function',\n", " 'content': part[17:].strip()\n", " })\n", " \n", " return messages" ] }, { "cell_type": "code", "execution_count": 101, "id": "7d3bbd7a-607e-4428-ad4a-ba024dd7e0b8", "metadata": {}, "outputs": [], "source": [ "def get_function_params(func_def):\n", " if not func_def or not isinstance(func_def, dict):\n", " return [], []\n", " \n", " params = func_def.get('parameters', {})\n", " if not isinstance(params, dict):\n", " return [], []\n", " \n", " properties = params.get('properties', {})\n", " required = params.get('required', []) if isinstance(params.get('required'), list) else []\n", " \n", " if not isinstance(properties, dict):\n", " return [], []\n", " \n", " optional = [p for p in properties.keys() if p not in required]\n", " return required, optional" ] }, { "cell_type": "code", "execution_count": 102, "id": "794d29d6-7811-491d-a73a-33897a4880e1", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████████████████████████████████████████████| 112960/112960 [00:13<00:00, 8629.64it/s]\n" ] } ], "source": [ "records = []\n", "for item in tqdm(d['train']):\n", " system_functions = parse_system_functions(item['system'])\n", " \n", " messages = parse_chat_content(item['chat'])\n", " \n", " function_calls = [msg['function_call'] for msg in messages \n", " if msg['role'] == 'assistant' and msg['function_call']]\n", " function_responses = [msg['content'] for msg in messages \n", " if msg['role'] == 'function']\n", " \n", " required_params, optional_params = get_function_params(system_functions)\n", " \n", " record = {\n", " 'system_functions': system_functions,\n", " 'function_name': system_functions.get('name') if system_functions else None,\n", " 'required_params': required_params,\n", " 'optional_params': optional_params,\n", " 'messages': messages,\n", " 'num_messages': len(messages),\n", " 'num_function_calls': len(function_calls),\n", " 'num_function_responses': len(function_responses),\n", " 'has_function_call': bool(function_calls),\n", " 'function_calls': function_calls,\n", " 'function_responses': function_responses\n", " }\n", " \n", " user_messages = [msg['content'] for msg in messages if msg['role'] == 'user']\n", " assistant_messages = [msg['content'] for msg in messages if msg['role'] == 'assistant']\n", " \n", " record.update({\n", " 'user_query_length': len(user_messages[0]) if user_messages else 0,\n", " 'avg_assistant_response_length': np.mean([len(m) for m in assistant_messages]) if assistant_messages else 0,\n", " 'conversation_turns': len(messages) // 2 # Assuming turns are user-assistant pairs\n", " })\n", " \n", " records.append(record)\n", "\n", "df = pd.DataFrame(records)" ] }, { "cell_type": "code", "execution_count": 103, "id": "fb059be4-84f3-4775-ad47-5940e05e2513", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Dataset Overview:\n", "Total conversations: 112960\n", "Unique functions: 938\n", "Average messages per conversation: 4.40\n", "Conversations with function calls: 2.0%\n" ] } ], "source": [ "print(\"\\nDataset Overview:\")\n", "print(f\"Total conversations: {len(df)}\")\n", "print(f\"Unique functions: {df['function_name'].nunique()}\")\n", "print(f\"Average messages per conversation: {df['num_messages'].mean():.2f}\")\n", "print(f\"Conversations with function calls: {df['has_function_call'].mean()*100:.1f}%\")" ] }, { "cell_type": "code", "execution_count": 104, "id": "4428fc49-9b16-49c9-b538-deacf0a9e001", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Function Distribution:\n", "function_name\n", "calculate_bmi 3146\n", "convert_currency 3068\n", "calculate_age 3024\n", "calculate_distance 2979\n", "calculate_tip 2855\n", "Name: count, dtype: int64\n" ] } ], "source": [ "print(\"\\nFunction Distribution:\")\n", "function_dist = df['function_name'].value_counts()\n", "print(function_dist.head())" ] }, { "cell_type": "code", "execution_count": 105, "id": "6063727d-6323-4c5e-87bf-79a35054d6dd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),\n", " [Text(0, 0, 'calculate_bmi'),\n", " Text(1, 0, 'convert_currency'),\n", " Text(2, 0, 'calculate_age'),\n", " Text(3, 0, 'calculate_distance'),\n", " Text(4, 0, 'calculate_tip'),\n", " Text(5, 0, 'calculate_discount'),\n", " Text(6, 0, 'get_stock_price'),\n", " Text(7, 0, 'generate_qr_code'),\n", " Text(8, 0, 'generate_password'),\n", " Text(9, 0, 'search_books')])" ] }, "execution_count": 105, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15, 5))\n", "plt.subplot(1, 3, 1)\n", "function_dist.head(10).plot(kind='bar')\n", "plt.title('Top 10 Functions')\n", "plt.xticks(rotation=45, ha='right')" ] }, { "cell_type": "code", "execution_count": 106, "id": "d849d61d-e97a-417d-b966-f4ac1485744b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 0, 'Number of Messages')" ] }, "execution_count": 106, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.subplot(1, 3, 2)\n", "df['num_messages'].hist(bins=20)\n", "plt.title('Messages per Conversation')\n", "plt.xlabel('Number of Messages')" ] }, { "cell_type": "code", "execution_count": 107, "id": "9dd873ea-1942-49db-8620-06e621763577", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.subplot(1, 3, 3)\n", "df['user_query_length'].hist(bins=20)\n", "plt.title('User Query Length Distribution')\n", "plt.xlabel('Characters')\n", "\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 108, "id": "4e0ca145-c0e1-4638-9278-4c047cb67d95", "metadata": {}, "outputs": [], "source": [ "def analyze_function_arguments(function_calls):\n", " if not function_calls:\n", " return {}\n", " \n", " all_args = []\n", " for call in function_calls:\n", " if call and 'arguments' in call:\n", " all_args.append(call['arguments'])\n", " \n", " return all_args" ] }, { "cell_type": "code", "execution_count": 109, "id": "35d02497-4b3c-4ca6-b37a-f57bdd29a5b4", "metadata": {}, "outputs": [], "source": [ "df['function_arguments'] = df['function_calls'].apply(analyze_function_arguments)" ] }, { "cell_type": "code", "execution_count": 111, "id": "3ab7b8f6-22af-47ea-ab31-3828cfb1c0fe", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Function Call Success Rate: 100.0%\n" ] } ], "source": [ "def check_function_success(messages):\n", " \"\"\"Check if function calls were successful\"\"\"\n", " has_error = any('error' in str(msg.get('content', '')).lower() \n", " for msg in messages if msg['role'] == 'function')\n", " return not has_error\n", "\n", "df['function_success'] = df['messages'].apply(check_function_success)\n", "print(f\"\\nFunction Call Success Rate: {df['function_success'].mean()*100:.1f}%\")\n" ] }, { "cell_type": "code", "execution_count": 112, "id": "ca005610-cbc1-483a-bc5f-530aaad80cf8", "metadata": {}, "outputs": [], "source": [ "def analyze_conversation_flow(messages):\n", " flow = []\n", " for msg in messages:\n", " if msg['role'] == 'assistant' and msg.get('function_call'):\n", " flow.append('FUNCTION_CALL')\n", " else:\n", " flow.append(msg['role'].upper())\n", " return '->'.join(flow)" ] }, { "cell_type": "code", "execution_count": 113, "id": "80593373-4dd2-4eca-a2af-8e842a7cc83b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Most Common Conversation Flows:\n", "conversation_flow\n", "USER 33976\n", "USER->ASSISTANT 15590\n", "USER->ASSISTANT->FUNCTION->ASSISTANT 12321\n", "USER->ASSISTANT->USER->ASSISTANT->FUNCTION->ASSISTANT 12224\n", "USER->ASSISTANT->FUNCTION->ASSISTANT->USER->ASSISTANT->FUNCTION->ASSISTANT->USER->ASSISTANT 9359\n", "Name: count, dtype: int64\n" ] } ], "source": [ "df['conversation_flow'] = df['messages'].apply(analyze_conversation_flow)\n", "print(\"\\nMost Common Conversation Flows:\")\n", "print(df['conversation_flow'].value_counts().head())" ] }, { "cell_type": "markdown", "id": "55a0b012-747e-4254-94ab-89939360d282", "metadata": { "jp-MarkdownHeadingCollapsed": true }, "source": [ "### Glaive-Function-calling-v1\n", "\n", "- Apache 2.0\n", "- 52k rows\n", "- https://huggingface.co/datasets/glaiveai/glaive-function-calling" ] }, { "cell_type": "code", "execution_count": 3, "id": "d81b5004-2af4-43b7-90b3-e9622b6decfc", "metadata": {}, "outputs": [], "source": [ "d = load_dataset(\"glaiveai/glaive-function-calling\")" ] }, { "cell_type": "code", "execution_count": 4, "id": "c806f8ab-39ef-4430-951e-e4f9e4a90c91", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'sample': 'SYSTEM: You are an helpful assistant who has access to the following functions to help the user, you can use the functions if needed-\\n{\\n \"name\": \"calculate_age\",\\n \"description\": \"Calculate the age based on the birthdate\",\\n \"parameters\": {\\n \"type\": \"string\",\\n \"description\": \"The birthdate in YYYY-MM-DD format\",\\n \"required\": true\\n }\\n}\\nUSER: Can you help me calculate my age?\\nASSISTANT: Sure! I can help you with that. Please provide me with your birthdate in YYYY-MM-DD format.\\nUSER: My birthdate is 1990-05-15.\\nASSISTANT: {\"name\": \"calculate_age\", \"arguments\": \\'{\"birthdate\": \"1990-05-15\"}\\'}\\nFUNCTION RESPONSE: {\"age\": 31}\\nASSISTANT: Based on the provided birthdate, your age is 31.\\nUSER: Thank you for calculating my age!\\nASSISTANT: You\\'re welcome! If you have any more questions or need further assistance, feel free to ask.'}" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][12312]" ] }, { "cell_type": "markdown", "id": "f7d91ae8-2a5e-4164-bbb9-d3546309888a", "metadata": {}, "source": [ "### Salesforce-xlam-functioncalling-60k\n", "\n", "- CC-by-4\n", "- 60k rows\n", "- https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k" ] }, { "cell_type": "code", "execution_count": 124, "id": "8151e97d-8324-4c0d-ba02-563149ccb108", "metadata": {}, "outputs": [], "source": [ "d = load_dataset(\"Salesforce/xlam-function-calling-60k\")" ] }, { "cell_type": "code", "execution_count": 125, "id": "c3315391-36db-46c5-869a-691962bd4e3d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'id': 555,\n", " 'query': 'Determine the area of a triangle with a base of 7.5 cm and a height of 3.2 cm.',\n", " 'answers': '[{\"name\": \"triangle_area\", \"arguments\": {\"base\": 7.5, \"height\": 3.2}}]',\n", " 'tools': '[{\"name\": \"triangle_area\", \"description\": \"Computes the area of a triangle given its base and height.\", \"parameters\": {\"base\": {\"description\": \"The length of the base of the triangle.\", \"type\": \"float\"}, \"height\": {\"description\": \"The height of the triangle.\", \"type\": \"float\"}}}, {\"name\": \"batting_average\", \"description\": \"Calculates the batting average of a baseball player based on the number of hits and at-bats.\", \"parameters\": {\"num_hits\": {\"description\": \"The number of hits.\", \"type\": \"int\", \"default\": 3}, \"num_at_bats\": {\"description\": \"The number of at-bats.\", \"type\": \"int\", \"default\": 3}, \"precision\": {\"description\": \"The number of decimal places to round the batting average. Defaults to 3.\", \"type\": \"int, optional\"}}}, {\"name\": \"fibonacci_numbers\", \"description\": \"Generates the first n Fibonacci numbers.\", \"parameters\": {\"n\": {\"description\": \"The number of Fibonacci numbers to generate.\", \"type\": \"int\"}}}, {\"name\": \"investment_profit\", \"description\": \"Calculates the profit from an investment based on the initial amount, annual return rate, and time.\", \"parameters\": {\"amount\": {\"description\": \"The initial investment amount.\", \"type\": \"float\"}, \"rate\": {\"description\": \"The annual return rate expressed as a decimal.\", \"type\": \"float\"}, \"years\": {\"description\": \"The number of years the investment is held.\", \"type\": \"int\"}}}, {\"name\": \"california_alimony\", \"description\": \"Calculates the total alimony one spouse would have to pay to the other in California over a given duration.\", \"parameters\": {\"payor_monthly_income\": {\"description\": \"The monthly gross income of the payor spouse.\", \"type\": \"int\"}, \"recipient_monthly_income\": {\"description\": \"The monthly gross income of the recipient spouse.\", \"type\": \"int\"}, \"duration_years\": {\"description\": \"The duration of the alimony in years.\", \"type\": \"int\"}}}, {\"name\": \"potential_energy\", \"description\": \"Calculates the electrostatic potential energy given the charge and voltage.\", \"parameters\": {\"charge\": {\"description\": \"The electric charge.\", \"type\": \"float\"}, \"voltage\": {\"description\": \"The electric potential difference (voltage).\", \"type\": \"float\"}}}]'}" ] }, "execution_count": 125, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][555]" ] }, { "cell_type": "code", "execution_count": 127, "id": "af6e9ff0-6418-487d-bcf5-962dfa5d95f6", "metadata": {}, "outputs": [], "source": [ "def parse_json_field(json_str):\n", " try:\n", " return json.loads(json_str)\n", " except (json.JSONDecodeError, TypeError):\n", " return []" ] }, { "cell_type": "code", "execution_count": 128, "id": "8f685ea5-3474-44e7-a2a5-830924ee000c", "metadata": {}, "outputs": [], "source": [ "def extract_parameter_info(tool):\n", " params = tool.get('parameters', {})\n", " param_info = {}\n", " \n", " for param_name, param_data in params.items():\n", " param_info[param_name] = {\n", " 'type': param_data.get('type', 'unknown'),\n", " 'has_default': 'default' in param_data,\n", " 'default_value': param_data.get('default'),\n", " 'description': param_data.get('description', '')\n", " }\n", " \n", " return param_info" ] }, { "cell_type": "code", "execution_count": 129, "id": "3c111217-7135-4614-b61f-e11e448afa1a", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|████████████████████████████████████████████████████| 60000/60000 [00:06<00:00, 9669.40it/s]\n" ] } ], "source": [ "records = []\n", "for item in tqdm(d['train']):\n", " tools = parse_json_field(item['tools'])\n", " answers = parse_json_field(item['answers'])\n", " \n", " tool_info = {tool['name']: tool for tool in tools}\n", " \n", " used_tools = []\n", " used_args = []\n", " for answer in answers:\n", " if isinstance(answer, dict):\n", " tool_name = answer.get('name')\n", " if tool_name:\n", " used_tools.append(tool_name)\n", " used_args.append(answer.get('arguments', {}))\n", " \n", " record = {\n", " 'id': item['id'],\n", " 'query': item['query'],\n", " 'query_length': len(item['query']),\n", " 'available_tools': list(tool_info.keys()),\n", " 'num_available_tools': len(tools),\n", " 'used_tools': used_tools,\n", " 'num_tools_used': len(used_tools),\n", " 'tool_arguments': used_args,\n", " 'has_numbers': bool(re.search(r'\\d+(?:\\.\\d+)?', item['query'])),\n", " 'is_question': item['query'].strip().endswith('?')\n", " }\n", " \n", " if used_tools:\n", " main_tool = used_tools[0]\n", " if main_tool in tool_info:\n", " tool_def = tool_info[main_tool]\n", " record.update({\n", " 'main_tool': main_tool,\n", " 'tool_description': tool_def.get('description', ''),\n", " 'parameter_info': extract_parameter_info(tool_def)\n", " })\n", " \n", " records.append(record)\n", "\n", "df = pd.DataFrame(records)" ] }, { "cell_type": "code", "execution_count": 131, "id": "0e480a2c-2b39-40ad-ae98-551ee2cc6b31", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Dataset Overview:\n", "Total samples: 60000\n", "Unique tools available: 3605\n", "Average query length: 111.89 characters\n", "Questions in dataset: 36.6%\n", "Queries with numbers: 73.3%\n" ] } ], "source": [ "print(\"\\nDataset Overview:\")\n", "print(f\"Total samples: {len(df)}\")\n", "print(f\"Unique tools available: {len(set(tool for tools in df['available_tools'] for tool in tools))}\")\n", "print(f\"Average query length: {df['query_length'].mean():.2f} characters\")\n", "print(f\"Questions in dataset: {df['is_question'].mean()*100:.1f}%\")\n", "print(f\"Queries with numbers: {df['has_numbers'].mean()*100:.1f}%\")" ] }, { "cell_type": "code", "execution_count": 132, "id": "30185c32-2fd0-4a56-8a35-845d374cbaae", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Top 10 Most Used Tools:\n", "search: 1469\n", "loginuser: 458\n", "calculate_standard_deviation: 408\n", "calculate_investment_return: 383\n", "is_perfect_square: 369\n", "is_sum_of_cubes: 366\n", "is_power_of_two: 362\n", "find_n_largest_numbers: 354\n", "sort_numbers: 352\n", "get_ip_zipcode: 352\n" ] } ], "source": [ "all_tools = [tool for tools in df['used_tools'] for tool in tools]\n", "tool_usage = Counter(all_tools)\n", "\n", "print(\"\\nTop 10 Most Used Tools:\")\n", "for tool, count in tool_usage.most_common(10):\n", " print(f\"{tool}: {count}\")" ] }, { "cell_type": "code", "execution_count": 133, "id": "ee8c76f4-5609-4ca0-856d-1a8f87331e5a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),\n", " [Text(0, 0, 'live_giveaways_by_type'),\n", " Text(1, 0, 'web_chain_details'),\n", " Text(2, 0, 't3ma'),\n", " Text(3, 0, 'list_titles'),\n", " Text(4, 0, 'stagecompetitorstandings'),\n", " Text(5, 0, 'product_id'),\n", " Text(6, 0, 'get_id'),\n", " Text(7, 0, 'search_torrents'),\n", " Text(8, 0, 'time_zone_api'),\n", " Text(9, 0, 'find_peak_element')])" ] }, "execution_count": 133, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15, 5))\n", "\n", "plt.subplot(1, 3, 1)\n", "pd.Series(tool_usage).head(10).plot(kind='bar')\n", "plt.title('Top 10 Tools by Usage')\n", "plt.xticks(rotation=45, ha='right')" ] }, { "cell_type": "code", "execution_count": 134, "id": "311edf00-2f28-43ad-b0e3-abac0dd2bddc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 0, 'Characters')" ] }, "execution_count": 134, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.subplot(1, 3, 2)\n", "sns.histplot(data=df, x='query_length', bins=30)\n", "plt.title('Query Length Distribution')\n", "plt.xlabel('Characters')" ] }, { "cell_type": "code", "execution_count": 139, "id": "80449134-cb6c-4e7f-9e79-185e90b481f1", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAASIAAAHWCAYAAADTvYS5AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAQ8FJREFUeJzt3Xl4TPf+B/D3TCKTRSaL7EQSUksspZZIKaqpIFVat9YSxNYm1Uhr61X0tpWgCxflamupi6JKW3tqLWILsUsVaRST1JZJLEkkn98ffjnXSEIIvlrv1/Oc53HO93PO+Z6ZM++cbYZORARERArpVXeAiIhBRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlLubxNEmzZtgk6nw3fffae6K6WSnp6Of/zjH6hQoQJ0Oh0mTZqkuksAgDlz5kCn0yE1NVV1Vx6K3r17w9/fX3U36Db3FESFO6mtrS3OnDlTpL1ly5aoXbv2A+vc39mQIUOwdu1ajBw5EvPmzUObNm2K1PTu3Rs6ne6uQ+/evR/9BpSCv78/XnrppWLb9uzZA51Ohzlz5jzaTv3F5OXl4d///jcaNWoER0dHlC9fHo0aNcKUKVNw48YN1d17YKzvZ6acnBzEx8djypQpD7o/T4wNGzagQ4cOePfdd0usGThwIEJDQ7XxU6dOYfTo0RgwYACee+45bXrVqlUfal9JjStXriA8PBybN2/GSy+9hN69e0Ov12PNmjUYPHgwli9fjp9++gn29vaqu1pm9xVE9erVw5dffomRI0fCx8fnQffpsXblyhU4ODiUeTkZGRlwdna+Y01ISAhCQkK08T179mD06NEICQnB66+/XuY+kFo3btxAQUEBbGxsim2PjY3F5s2bMWXKFERHR2vT33jjDUybNg3R0dEYOnQopk2b9qi6DAC4fv06bGxsoNc/uCs797Wk9957D/n5+YiPj79jXWpqaomH3zqdDmPHjtXGx44dC51Oh19//RWvv/46nJyc4O7ujvfffx8igtOnT6NDhw4wGo3w8vLCp59+Wuw68/Pz8d5778HLywsODg54+eWXcfr06SJ1O3fuRJs2beDk5AR7e3u0aNEC27Zts6gp7NORI0fQvXt3uLi4oFmzZnfc5pMnT+K1116Dq6sr7O3t0aRJE6xcuVJrLzy9FRFMmzZNO70qiyVLlqBBgwaws7ODm5sbXn/99WJPnTds2IDnnnsODg4OcHZ2RocOHXD06NG7Ln/Pnj0ICwuDm5sb7OzsEBAQgL59+5apz8UxmUzo06cPKlWqBIPBAG9vb3To0KHI9arVq1dr2+Ho6Ijw8HAcPny4yPKWL1+O2rVrw9bWFrVr18ayZctK3ZfC08p169ahXr16sLW1RVBQEL7//vsitZcvX0ZMTAx8fX1hMBgQGBiI8ePHo6CgQKsp/Cx88sknmDRpEqpWrQqDwYAjR44Uu/4//vgDX3/9NVq1amURQoWioqLw/PPPY+bMmdp7fS+fNwA4c+YM+vbtC09PTxgMBtSqVQuzZs2yqCm89vrtt99i1KhRqFixIuzt7ZGcnAydTofPP/+8yLq2b98OnU6HhQsXFrttxbmvI6KAgAD06tULX375JUaMGPFAj4q6dOmCmjVrIj4+HitXrsRHH30EV1dX/Oc//0GrVq0wfvx4zJ8/H++++y4aNWqE5s2bW8z/8ccfQ6fTYfjw4cjIyMCkSZMQGhqK5ORk2NnZAbj5gWzbti0aNGiAMWPGQK/XY/bs2WjVqhV++eUXNG7c2GKZr732Gp566imMGzcOd/rVlPT0dDz77LO4evUqBg8ejAoVKmDu3Ll4+eWX8d133+GVV15B8+bNMW/ePPTs2RMvvvgievXqVabXa86cOejTpw8aNWqEuLg4pKenY/Lkydi2bRv27dunHXX9/PPPaNu2LapUqYKxY8fi2rVrmDJlCpo2bYq9e/eWeAE3IyMDrVu3hru7O0aMGAFnZ2ekpqYW+4Esq06dOuHw4cN466234O/vj4yMDCQkJCAtLU3r37x58xAREYGwsDCMHz8eV69exfTp09GsWTPs27dPq1u3bh06deqEoKAgxMXF4cKFC1rIldbx48fRpUsXDBo0CBEREZg9ezZee+01rFmzBi+++CIA4OrVq2jRogXOnDmDgQMHonLlyti+fTtGjhyJc+fOFbkJMXv2bFy/fh0DBgyAwWCAq6trsetevXo18vPz77h/9OrVCxs3bsSaNWsQGRlZ6u0Cbu6rTZo0gU6nQ3R0NNzd3bF69WpERkbCbDYjJibGov7DDz+EjY0N3n33XeTk5KBGjRpo2rQp5s+fjyFDhljUzp8/H46OjujQoUPpOyT3YPbs2QJAdu/eLSdOnBBra2sZPHiw1t6iRQupVauWNn7q1CkBILNnzy6yLAAyZswYbXzMmDECQAYMGKBNu3HjhlSqVEl0Op3Ex8dr0y9duiR2dnYSERGhTdu4caMAkIoVK4rZbNamL168WADI5MmTRUSkoKBAnnrqKQkLC5OCggKt7urVqxIQECAvvvhikT5169atVK9PTEyMAJBffvlFm5aVlSUBAQHi7+8v+fn5FtsfFRVVquUW2r17t8XrmZubKx4eHlK7dm25du2aVrdixQoBIKNHj9am1atXTzw8POTChQvatP3794ter5devXpp0wrf41OnTomIyLJly7T3/F75+flJeHh4qbbl0qVLAkAmTpxY4vKysrLE2dlZ+vfvbzHdZDKJk5OTxfR69eqJt7e3XL58WZu2bt06ASB+fn6l6jsAWbp0qTYtMzNTvL29pX79+tq0Dz/8UBwcHOTXX3+1mH/EiBFiZWUlaWlpIvK/z4LRaJSMjIy7rr9wX9q3b1+JNXv37hUAEhsba7GO0nzeIiMjxdvbW86fP29R17VrV3FycpKrV6+KyP8+V1WqVNGmFfrPf/4jAOTo0aPatNzcXHFzc7P4bJbGfZ/kValSBT179sTMmTNx7ty5+11MEf369dP+bWVlhYYNG0JELBLf2dkZ1atXx8mTJ4vM36tXLzg6Omrj//jHP+Dt7Y1Vq1YBAJKTk3H8+HF0794dFy5cwPnz53H+/HlcuXIFL7zwArZs2WJxSA0AgwYNKlXfV61ahcaNG1ucvpUvXx4DBgxAampqiYfh92vPnj3IyMjAm2++CVtbW216eHg4atSooZ0Snjt3DsnJyejdu7fFX+C6devixRdf1F6b4hQeUa1YsQJ5eXkPtP+3srOzg42NDTZt2oRLly4VW5OQkIDLly+jW7du2vt2/vx5WFlZITg4GBs3bgTwv+2NiIiAk5OTNv+LL76IoKCgUvfJx8cHr7zyijZuNBrRq1cv7Nu3DyaTCcDN0+LnnnsOLi4uFn0KDQ1Ffn4+tmzZYrHMTp06wd3d/a7rzsrKAgCLffl2hW2FtaUlIli6dCnat28PEbHod1hYGDIzM7F3716LeSIiIrQzikKdO3eGra0t5s+fr01bu3Ytzp8/f8/XMMt0tWnUqFG4cePGXa8V3YvKlStbjDs5OcHW1hZubm5Fphe3wz711FMW4zqdDoGBgdp1huPHjwO4+cK6u7tbDF999RVycnKQmZlpsYyAgIBS9f33339H9erVi0yvWbOm1v4gFS6vuHXWqFFDa79TXc2aNbUgLk6LFi3QqVMnfPDBB3Bzc0OHDh0we/Zs5OTkPJBtKLw+ZjAYMH78eKxevRqenp5o3rw5JkyYoH3ggf+9d61atSry3q1btw4ZGRkW23v7vgAU/xqUJDAwsMj1u2rVqgGAxf60Zs2aIv0pvNtZ2KdCpd2XShMyhW0eHh6lWmahP//8E5cvX8bMmTOL9LtPnz6l7rezszPat2+PBQsWaNPmz5+PihUrolWrVvfUp/u6RlSoSpUqeP311zFz5kyMGDGiSHtJF2Hz8/NLXKaVlVWppgG44/WakhQe7UycOBH16tUrtqZ8+fIW47f/JXiSFD4kumPHDvz0009Yu3Yt+vbti08//RQ7duwo8lrdytbWFteuXSu27erVq1pNoZiYGLRv3x7Lly/H2rVr8f777yMuLg4bNmxA/fr1tfdu3rx58PLyKrJMa+sy7c73paCgAC+++CKGDRtWbHthcBUq7b5UeOR24MCBEvfTAwcOALj5OQRK/3krfB1ff/11REREFDtP3bp1S9XvXr16YcmSJdi+fTvq1KmDH3/8EW+++eY931Er8zs3atQo/Pe//8X48eOLtLm4uAC4eVfhVg/6yOBWhX81C4kIfvvtN+2FLXzmxmg0Wjyj8yD4+fkhJSWlyPRjx45p7Q96fQCQkpJS5C9QSkqK1n5rXXF9c3Nzu+sjCU2aNEGTJk3w8ccfY8GCBejRowe+/fZbi1Pp4vpX0uloYV9uf02qVq2Kd955B++88w6OHz+OevXq4dNPP8V///tf7b3z8PC443tXuMzb94Vb11sav/32G0TE4gP+66+/AoB2Ubxq1arIzs5+4PtS27ZtYWVlhXnz5pV4wfqbb76BjY2NdlG4tJ83d3d3ODo6Ij8/v8z9btOmDdzd3TF//nwEBwfj6tWr6Nmz5z0vp8wPAlStWhWvv/46/vOf/1gcRgM3P+xubm5FzpO/+OKLsq62RN98843F4ex3332Hc+fOoW3btgCABg0aoGrVqvjkk0+QnZ1dZP4///zzvtfdrl077Nq1C4mJidq0K1euYObMmfD397+n6xOl0bBhQ3h4eGDGjBkWp0qrV6/G0aNHER4eDgDw9vZGvXr1MHfuXIud9NChQ1i3bh3atWtX4jouXbpU5Miz8C/03U7P2rVrhz/++APLly+3mJ6Tk4OvvvoKHh4eeOaZZwDcPEK6fv26RV3VqlXh6OiorScsLAxGoxHjxo0r9npV4Xt36/beepqdkJBwT9fpzp49a3HL32w245tvvkG9evW0I7LOnTsjMTERa9euLTL/5cuX7/vp50qVKiEyMhI///wzpk+fXqR9xowZ2LBhAwYOHIgKFSoAKP3nzcrKCp06dcLSpUtx6NChIsu+l8+AtbU1unXrhsWLF2POnDmoU6dOkaOpUi3nnucoxj//+U/MmzcPKSkpqFWrlkVbv379EB8fj379+qFhw4bYsmWL9lflYXB1dUWzZs3Qp08fpKenY9KkSQgMDET//v0BAHq9Hl999RXatm2LWrVqoU+fPqhYsSLOnDmDjRs3wmg04qeffrqvdY8YMQILFy5E27ZtMXjwYLi6umLu3Lk4deoUli5d+kAfAAOAcuXKYfz48ejTpw9atGiBbt26abfv/f39LW6rTpw4EW3btkVISAgiIyO12/dOTk5Fni+51dy5c/HFF1/glVdeQdWqVZGVlYUvv/wSRqPxjgEGAAMGDMCsWbPw2muvoW/fvqhfvz4uXLiARYsW4dChQ9pfdODmkcYLL7yAzp07IygoCNbW1li2bBnS09PRtWtXADc/aNOnT0fPnj3xzDPPoGvXrnB3d0daWhpWrlyJpk2bYurUqQCAuLg4hIeHo1mzZujbty8uXryIKVOmoFatWsX+ASpOtWrVEBkZid27d8PT0xOzZs1Ceno6Zs+erdUMHToUP/74o/bkc4MGDXDlyhUcPHgQ3333HVJTU4tc3yytzz77DMeOHcObb76JNWvWaF8DWrt2LX744Qe0atUKEydOtJintJ+3+Ph4bNy4EcHBwejfvz+CgoJw8eJF7N27Fz///DMuXrxY6n726tUL//73v7Fx48Ziz4xK5V5usd16+/52ERERAsDi9r3IzdvikZGR4uTkJI6OjtK5c2fJyMgo8fb9n3/+WWS5Dg4ORdZ3+6MChbcZFy5cKCNHjhQPDw+xs7OT8PBw+f3334vMv2/fPnn11VelQoUKYjAYxM/PTzp37izr16+/a5/u5MSJE/KPf/xDnJ2dxdbWVho3biwrVqwoUocHcPu+0KJFi6R+/fpiMBjE1dVVevToIX/88UeR+X/++Wdp2rSp2NnZidFolPbt28uRI0csam6/fb93717p1q2bVK5cWQwGg3h4eMhLL70ke/bsKVWfL126JEOGDJGAgAApV66cGI1Gef7552X16tUWdefPn5eoqCipUaOGODg4iJOTkwQHB8vixYuLLHPjxo0SFhYmTk5OYmtrK1WrVpXevXsX6dPSpUulZs2aYjAYJCgoSL7//nuJiIgo9e378PBwWbt2rdStW1cMBoPUqFFDlixZUqQ2KytLRo4cKYGBgWJjYyNubm7y7LPPyieffCK5ubki8r9b63d6PKE4ubm5MmnSJGnQoIHY29sLAAEgERERFo+DFCrt501EJD09XaKiosTX11fKlSsnXl5e8sILL8jMmTO1msLPVXHbfatatWqJXq8vdr8rDZ0I/18zotv5+/ujdu3aWLFihequWDCbzWjRogVOnDiBLVu2lHgh+1GrX78+XF1dsX79+vua/2/zMyBETwKj0YjVq1fDzc0N7dq1e6g3fkprz549SE5OLtO3BB79/U4iKhMvL69iH+Z91A4dOoSkpCR8+umn8Pb2RpcuXe57WTwiIqL78t1336FPnz7Iy8vDwoULLZ4Ju1e8RkREyvGIiIiUYxARkXK8WP3/CgoKcPbsWTg6Opb5h8qI7kZEkJWVBR8fnwf+oOtfEYPo/509exa+vr6qu0FPmNOnT9/Tj7X9XTGI/l/hzy6cPn0aRqNRcW/o785sNsPX1/eOvzf0JGEQ/b/C0zGj0cggokeGlwFu4skpESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyvH3iIrhP2KlxXhqfLiinhA9GXhERETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUs1bdgb8i/xErtX+nxocr7AnR38N9HxHFxcWhUaNGcHR0hIeHBzp27IiUlBSLmpYtW0Kn01kMgwYNsqhJS0tDeHg47O3t4eHhgaFDh+LGjRsWNZs2bcIzzzwDg8GAwMBAzJkzp0h/pk2bBn9/f9ja2iI4OBi7du26300jokfsvoNo8+bNiIqKwo4dO5CQkIC8vDy0bt0aV65csajr378/zp07pw0TJkzQ2vLz8xEeHo7c3Fxs374dc+fOxZw5czB69Git5tSpUwgPD8fzzz+P5ORkxMTEoF+/fli7dq1Ws2jRIsTGxmLMmDHYu3cvnn76aYSFhSEjI+N+N4+IHiV5QDIyMgSAbN68WZvWokULefvtt0ucZ9WqVaLX68VkMmnTpk+fLkajUXJyckREZNiwYVKrVi2L+bp06SJhYWHaeOPGjSUqKkobz8/PFx8fH4mLiyt1/zMzMwWAZGZmit/wFRbD7e7URlQat+5vJPLALlZnZmYCAFxdXS2mz58/H25ubqhduzZGjhyJq1evam2JiYmoU6cOPD09tWlhYWEwm804fPiwVhMaGmqxzLCwMCQmJgIAcnNzkZSUZFGj1+sRGhqq1RDR4+2BXKwuKChATEwMmjZtitq1a2vTu3fvDj8/P/j4+ODAgQMYPnw4UlJS8P333wMATCaTRQgB0MZNJtMda8xmM65du4ZLly4hPz+/2Jpjx46V2OecnBzk5ORo42az+T62nIgehAcSRFFRUTh06BC2bt1qMX3AgAHav+vUqQNvb2+88MILOHHiBKpWrfogVn3f4uLi8MEHHyjtAxHdVOZTs+joaKxYsQIbN25EpUqV7lgbHBwMAPjtt98AAF5eXkhPT7eoKRz38vK6Y43RaISdnR3c3NxgZWVVbE3hMoozcuRIZGZmasPp06dLsbVE9DDcdxCJCKKjo7Fs2TJs2LABAQEBd50nOTkZAODt7Q0ACAkJwcGDBy3ubiUkJMBoNCIoKEirWb9+vcVyEhISEBISAgCwsbFBgwYNLGoKCgqwfv16raY4BoMBRqPRYiAiNe771CwqKgoLFizADz/8AEdHR+2ajpOTE+zs7HDixAksWLAA7dq1Q4UKFXDgwAEMGTIEzZs3R926dQEArVu3RlBQEHr27IkJEybAZDJh1KhRiIqKgsFgAAAMGjQIU6dOxbBhw9C3b19s2LABixcvxsqV/3uoMDY2FhEREWjYsCEaN26MSZMm4cqVK+jTp09ZXhsielTu93YbgGKH2bNni4hIWlqaNG/eXFxdXcVgMEhgYKAMHTq0yO3K1NRUadu2rdjZ2Ymbm5u88847kpeXZ1GzceNGqVevntjY2EiVKlW0ddxqypQpUrlyZbGxsZHGjRvLjh077ml7ePueHiXevrekExFRF4OPD7PZDCcnJ2RmZqLuuF8s2m7/Gge/4kFldev+xssC/NIrET0GGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJS7r6DKC4uDo0aNYKjoyM8PDzQsWNHpKSkWNRcv34dUVFRqFChAsqXL49OnTohPT3doiYtLQ3h4eGwt7eHh4cHhg4dihs3bljUbNq0Cc888wwMBgMCAwMxZ86cIv2ZNm0a/P39YWtri+DgYOzatet+N42IHrH7DqLNmzcjKioKO3bsQEJCAvLy8tC6dWtcuXJFqxkyZAh++uknLFmyBJs3b8bZs2fx6quvau35+fkIDw9Hbm4utm/fjrlz52LOnDkYPXq0VnPq1CmEh4fj+eefR3JyMmJiYtCvXz+sXbtWq1m0aBFiY2MxZswY7N27F08//TTCwsKQkZFxv5tHRI+SPCAZGRkCQDZv3iwiIpcvX5Zy5crJkiVLtJqjR48KAElMTBQRkVWrVolerxeTyaTVTJ8+XYxGo+Tk5IiIyLBhw6RWrVoW6+rSpYuEhYVp440bN5aoqChtPD8/X3x8fCQuLq7U/c/MzBQAkpmZKX7DV1gMt7tTG1Fp3Lq/kcgDu0aUmZkJAHB1dQUAJCUlIS8vD6GhoVpNjRo1ULlyZSQmJgIAEhMTUadOHXh6emo1YWFhMJvNOHz4sFZz6zIKawqXkZubi6SkJIsavV6P0NBQraY4OTk5MJvNFgMRqfFAgqigoAAxMTFo2rQpateuDQAwmUywsbGBs7OzRa2npydMJpNWc2sIFbYXtt2pxmw249q1azh//jzy8/OLrSlcRnHi4uLg5OSkDb6+vve+4UT0QDyQIIqKisKhQ4fw7bffPojFPRIjR45EZmamNpw+fVp1l4ieWNZlXUB0dDRWrFiBLVu2oFKlStp0Ly8v5Obm4vLlyxZHRenp6fDy8tJqbr+7VXhX7daa2++0paenw2g0ws7ODlZWVrCysiq2pnAZxTEYDDAYDPe+wUT0wN33EZGIIDo6GsuWLcOGDRsQEBBg0d6gQQOUK1cO69ev16alpKQgLS0NISEhAICQkBAcPHjQ4u5WQkICjEYjgoKCtJpbl1FYU7gMGxsbNGjQwKKmoKAA69ev12qI6PF230dEUVFRWLBgAX744Qc4Ojpq12OcnJxgZ2cHJycnREZGIjY2Fq6urjAajXjrrbcQEhKCJk2aAABat26NoKAg9OzZExMmTIDJZMKoUaMQFRWlHa0MGjQIU6dOxbBhw9C3b19s2LABixcvxsqVK7W+xMbGIiIiAg0bNkTjxo0xadIkXLlyBX369CnLa0NEj8r93m4DUOwwe/ZsrebatWvy5ptviouLi9jb28srr7wi586ds1hOamqqtG3bVuzs7MTNzU3eeecdycvLs6jZuHGj1KtXT2xsbKRKlSoW6yg0ZcoUqVy5stjY2Ejjxo1lx44d97Q9vH1PjxJv31vSiYioi8HHh9lshpOTEzIzM1F33C8Wbanx4Rbj/iNWlthGVBq37m9Go1F1d5Tjd82ISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkXJmCaMuWLWjfvj18fHyg0+mwfPlyi/bevXtDp9NZDG3atLGouXjxInr06AGj0QhnZ2dERkYiOzvboubAgQN47rnnYGtrC19fX0yYMKFIX5YsWYIaNWrA1tYWderUwapVq8qyaUT0CJUpiK5cuYKnn34a06ZNK7GmTZs2OHfunDYsXLjQor1Hjx44fPgwEhISsGLFCmzZsgUDBgzQ2s1mM1q3bg0/Pz8kJSVh4sSJGDt2LGbOnKnVbN++Hd26dUNkZCT27duHjh07omPHjjh06FBZNo+IHhHrsszctm1btG3b9o41BoMBXl5exbYdPXoUa9aswe7du9GwYUMAwJQpU9CuXTt88skn8PHxwfz585Gbm4tZs2bBxsYGtWrVQnJyMj777DMtsCZPnow2bdpg6NChAIAPP/wQCQkJmDp1KmbMmFGWTSSiR+ChXyPatGkTPDw8UL16dbzxxhu4cOGC1paYmAhnZ2cthAAgNDQUer0eO3fu1GqaN28OGxsbrSYsLAwpKSm4dOmSVhMaGmqx3rCwMCQmJj7MTSOiB6RMR0R306ZNG7z66qsICAjAiRMn8N5776Ft27ZITEyElZUVTCYTPDw8LDtkbQ1XV1eYTCYAgMlkQkBAgEWNp6en1ubi4gKTyaRNu7WmcBnFycnJQU5OjjZuNpvLtK1EdP8eahB17dpV+3edOnVQt25dVK1aFZs2bcILL7zwMFd9V3Fxcfjggw+U9oGIbnqkt++rVKkCNzc3/PbbbwAALy8vZGRkWNTcuHEDFy9e1K4reXl5IT093aKmcPxuNSVdmwKAkSNHIjMzUxtOnz5dto0jovv2SIPojz/+wIULF+Dt7Q0ACAkJweXLl5GUlKTVbNiwAQUFBQgODtZqtmzZgry8PK0mISEB1atXh4uLi1azfv16i3UlJCQgJCSkxL4YDAYYjUaLgYjUKFMQZWdnIzk5GcnJyQCAU6dOITk5GWlpacjOzsbQoUOxY8cOpKamYv369ejQoQMCAwMRFhYGAKhZsybatGmD/v37Y9euXdi2bRuio6PRtWtX+Pj4AAC6d+8OGxsbREZG4vDhw1i0aBEmT56M2NhYrR9vv/021qxZg08//RTHjh3D2LFjsWfPHkRHR5dl84joUZEy2LhxowAoMkRERMjVq1eldevW4u7uLuXKlRM/Pz/p37+/mEwmi2VcuHBBunXrJuXLlxej0Sh9+vSRrKwsi5r9+/dLs2bNxGAwSMWKFSU+Pr5IXxYvXizVqlUTGxsbqVWrlqxcufKetiUzM1MASGZmpvgNX2Ex3O5ObUSlcev+RiI6ERGFOfjYMJvNcHJyQmZmJuqO+8WiLTU+3GLcf8TKEtuISuPW/Y2XBfhdMyJ6DDCIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpFyZgmjLli1o3749fHx8oNPpsHz5cot2EcHo0aPh7e0NOzs7hIaG4vjx4xY1Fy9eRI8ePWA0GuHs7IzIyEhkZ2db1Bw4cADPPfccbG1t4evriwkTJhTpy5IlS1CjRg3Y2tqiTp06WLVqVVk2jYgeoTIF0ZUrV/D0009j2rRpxbZPmDAB//73vzFjxgzs3LkTDg4OCAsLw/Xr17WaHj164PDhw0hISMCKFSuwZcsWDBgwQGs3m81o3bo1/Pz8kJSUhIkTJ2Ls2LGYOXOmVrN9+3Z069YNkZGR2LdvHzp27IiOHTvi0KFDZdk8InpU5AEBIMuWLdPGCwoKxMvLSyZOnKhNu3z5shgMBlm4cKGIiBw5ckQAyO7du7Wa1atXi06nkzNnzoiIyBdffCEuLi6Sk5Oj1QwfPlyqV6+ujXfu3FnCw8Mt+hMcHCwDBw4sdf8zMzMFgGRmZorf8BUWw+3u1EZUGrfubyTy0K4RnTp1CiaTCaGhodo0JycnBAcHIzExEQCQmJgIZ2dnNGzYUKsJDQ2FXq/Hzp07tZrmzZvDxsZGqwkLC0NKSgouXbqk1dy6nsKawvUQ0ePN+mEt2GQyAQA8PT0tpnt6emptJpMJHh4elh2ytoarq6tFTUBAQJFlFLa5uLjAZDLdcT3FycnJQU5OjjZuNpvvZfOI6AF6Yu+axcXFwcnJSRt8fX1Vd4noifXQgsjLywsAkJ6ebjE9PT1da/Py8kJGRoZF+40bN3Dx4kWLmuKWces6SqopbC/OyJEjkZmZqQ2nT5++100kogfkoQVRQEAAvLy8sH79em2a2WzGzp07ERISAgAICQnB5cuXkZSUpNVs2LABBQUFCA4O1mq2bNmCvLw8rSYhIQHVq1eHi4uLVnPregprCtdTHIPBAKPRaDEQkRplCqLs7GwkJycjOTkZwM0L1MnJyUhLS4NOp0NMTAw++ugj/Pjjjzh48CB69eoFHx8fdOzYEQBQs2ZNtGnTBv3798euXbuwbds2REdHo2vXrvDx8QEAdO/eHTY2NoiMjMThw4exaNEiTJ48GbGxsVo/3n77baxZswaffvopjh07hrFjx2LPnj2Ijo4uy+YR0aNSlltuGzduFABFhoiICBG5eQv//fffF09PTzEYDPLCCy9ISkqKxTIuXLgg3bp1k/Lly4vRaJQ+ffpIVlaWRc3+/fulWbNmYjAYpGLFihIfH1+kL4sXL5Zq1aqJjY2N1KpVS1auXHlP28Lb9/Qo8fa9JZ2IiMIcfGyYzWY4OTkhMzMTdcf9YtGWGh9uMe4/YmWJbUSlcev+xssCT/BdMyJ6fDCIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpNxDDaKxY8dCp9NZDDVq1NDar1+/jqioKFSoUAHly5dHp06dkJ6ebrGMtLQ0hIeHw97eHh4eHhg6dChu3LhhUbNp0yY888wzMBgMCAwMxJw5cx7mZhHRA/bQj4hq1aqFc+fOacPWrVu1tiFDhuCnn37CkiVLsHnzZpw9exavvvqq1p6fn4/w8HDk5uZi+/btmDt3LubMmYPRo0drNadOnUJ4eDief/55JCcnIyYmBv369cPatWsf9qYR0QNi/dBXYG0NLy+vItMzMzPx9ddfY8GCBWjVqhUAYPbs2ahZsyZ27NiBJk2aYN26dThy5Ah+/vlneHp6ol69evjwww8xfPhwjB07FjY2NpgxYwYCAgLw6aefAgBq1qyJrVu34vPPP0dYWNjD3jwiegAe+hHR8ePH4ePjgypVqqBHjx5IS0sDACQlJSEvLw+hoaFabY0aNVC5cmUkJiYCABITE1GnTh14enpqNWFhYTCbzTh8+LBWc+syCmsKl1GSnJwcmM1mi4GI1HioQRQcHIw5c+ZgzZo1mD59Ok6dOoXnnnsOWVlZMJlMsLGxgbOzs8U8np6eMJlMAACTyWQRQoXthW13qjGbzbh27VqJfYuLi4OTk5M2+Pr6lnVzieg+PdRTs7Zt22r/rlu3LoKDg+Hn54fFixfDzs7uYa76rkaOHInY2Fht3Gw2M4yIFHmkt++dnZ1RrVo1/Pbbb/Dy8kJubi4uX75sUZOenq5dU/Ly8ipyF61w/G41RqPxjmFnMBhgNBotBiJS45EGUXZ2Nk6cOAFvb280aNAA5cqVw/r167X2lJQUpKWlISQkBAAQEhKCgwcPIiMjQ6tJSEiA0WhEUFCQVnPrMgprCpdBRI+/h3pq9u6776J9+/bw8/PD2bNnMWbMGFhZWaFbt25wcnJCZGQkYmNj4erqCqPRiLfeegshISFo0qQJAKB169YICgpCz549MWHCBJhMJowaNQpRUVEwGAwAgEGDBmHq1KkYNmwY+vbtiw0bNmDx4sVYuXLlw9y0EvmPsFxvany4kn4Q/ZU81CD6448/0K1bN1y4cAHu7u5o1qwZduzYAXd3dwDA559/Dr1ej06dOiEnJwdhYWH44osvtPmtrKywYsUKvPHGGwgJCYGDgwMiIiLwr3/9S6sJCAjAypUrMWTIEEyePBmVKlXCV199xVv3RH8hDzWIvv322zu229raYtq0aZg2bVqJNX5+fli1atUdl9OyZUvs27fvvvpIROrxu2ZEpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRcgwiIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXIMIiJSjkFERMoxiIhIOQYRESnHICIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREpxyAiIuUYRESkHIOIiJRjEBGRctaqO/Ck8R+x0mI8NT5cUU+IHh88IiIi5RhERKQcg4iIlGMQEZFyDCIiUo5BRETKMYiISDkGEREp97cKomnTpsHf3x+2trYIDg7Grl27VHeJiErhbxNEixYtQmxsLMaMGYO9e/fi6aefRlhYGDIyMlR3jYju4m/zFY/PPvsM/fv3R58+fQAAM2bMwMqVKzFr1iyMGDFCce9Kj18BoSfR3+KIKDc3F0lJSQgNDdWm6fV6hIaGIjExUWHPiKg0/hZHROfPn0d+fj48PT0tpnt6euLYsWPFzpOTk4OcnBxtPDMzEwBgNptRkHPVotZsNluM39p+p7aH0V57zFqL8UMfhIH+egrfVxFR3JPHw98iiO5HXFwcPvjggyLTfX19i0xzmlTycu7U9ji00+MtKysLTk5Oqruh3N8iiNzc3GBlZYX09HSL6enp6fDy8ip2npEjRyI2NlYbLygowMWLF1GhQgXodDqYzWb4+vri9OnTMBqNFvPeqe1xb3+c+/Yk9V1EkJWVBR8fnyLLeRL9LYLIxsYGDRo0wPr169GxY0cAN4Nl/fr1iI6OLnYeg8EAg8FgMc3Z2blIndFoLHanu1vb497+OPftbu2Pc9/u1n5rG4+E/udvEUQAEBsbi4iICDRs2BCNGzfGpEmTcOXKFe0uGhE9vv42QdSlSxf8+eefGD16NEwmE+rVq4c1a9YUuYBNRI+fv00QAUB0dHSJp2L3ymAwYMyYMUVO3+7W9ri3P859e5L7/qTTCe8fEpFif4sHGonor41BRETKMYiISDkGkSK8NEf0P3+ru2Z/JQaDAfv370fNmjWV9uPcuXOYPn06tm7dinPnzkGv16NKlSro2LEjevfuDSsrK6X9oycDg6gUjh8/jpiYGEycOBFBQUEWbdevX8ekSZPg6emJkJAQ1KhRA8eOHcPkyZORk5MDs9mMypUrF1lmfn4+4uPjUaFCBQA3f8YEAK5cuYLFixfjt99+g7e3N4KCghAQEICAgAAAwLx58zBjxgykpaXBz88PDg4OGDVqFJ577rli+z516lTs2rUL7dq1Q9euXTFv3jzExcWhoKAAISEhWLZsGQIDA2FnZ4fjx4+je/fuyM3NxbvvvotZs2ZhzZo1cHR0fJAv5wO1a9cuJCYmwmQyAQC8vLwQEhKCxo0bQ0SQmpoKX19fWFtbIzc3F8uWLUNOTg7atWsHNze3Istr1aoVZs+eDS8vL+j1epQrVw4AcOLECcyaNUt73SMjI7X3hB4AoTtKSUkRb29vASB6vV6aN28uZ8+e1doXLFggAMTV1VVsbW1l9erV4u7uLqGhodKqVSsBIIGBgdKyZUuLQafTSaNGjcTe3l6aNWsmIiJpaWni7+8vTk5O0qhRI3F1dRVra2v55ptvRETkyy+/FDs7Oxk8eLBMnz5dYmJiBIDodDp56qmnJD4+Xs6dO6f17cMPPxRHR0fp1KmTeHl5SXx8vFSoUEE++ugjGTdunFhbW0uLFi20+nnz5klwcLCIiFy8eFHq1asngwcPlpycHFm0aJHExMRI165dpWvXrhITEyOLFy+WnJycEl87k8kkH3zwgZw+fVqysrKKtOfm5srmzZuLTA8ICJBff/1VRESuXr0qX3/9tfTp00fatGkj7dq1k+joaFmyZIk0a9ZMdDqd+Pn5SePGjaVx48bi5+cnOp1OnnnmGfH19RW9Xi+BgYFy8uRJadCggTg4OIi9vb04OjrK9OnT5YcffrAYrKysZOrUqVK7dm0ZNmyYiIhs3bpVDAaD1K1bV7p06SL169cXe3t72b59u+zcuVMmTZokI0aMkBEjRsikSZNk586dIiKSn59f7OuSn58vv//+e4mv25OIQSRSZGe8dQgODpagoCDR6XRy/PhxCQ8Pl4CAAG1HatiwoRTm+cKFC8XFxUXee+89bdktWrQQOzs7Wb9+vcU6ra2t5fDhw6LT6SQ9PV1ERHr06CHPPvusXL58WUREsrKyRK/Xy8svvywiIvXr15eZM2daLEen00nlypXl7bffFjc3NylXrpy8/PLL8tNPP0nVqlVl6dKlIiKSnJwsVlZW8t///leb18bGRvz8/LTx/Px8KVeunJhMJhERWbdunXh4eEiVKlXE1tZWWrRoIZ07d5bOnTtLixYtxNbWVgIDA+X48ePFvq4JCQlagFtZWUnPnj0tAumjjz4SnU4nkydPthisrKxk5MiRMmrUKHF1dRUPDw/x9fUVnU4n4eHhEhwcLACkQoUKcujQoSLrPXbsmLi6uoq3t7ccOHBAYmJipGbNmtKhQwfJzc2V69evawFe0lDYXvgeDhkyxGIdQ4YMEaPRWGwQAhA3NzextbUVDw8Pef/99+XGjRvavCaTSfR6fbGv2ZOKQSQ3P8x6vb7EHbLwwyQiUlBQIIMGDZLKlSvLiRMnxNHRUdth8/PzxdraWvbu3ast++DBg+Lq6irVqlWTd955R3Jzc0Wk+CCqUqWKrFu3zqJvTk5O4unpKSIiHh4ekpycXKTvtra2InLzCGPRokUSFhYmVlZWotPpJCoqSguKcuXKWXxwK1asKAaDQRs/e/as6HQ6uXr1qoiInDp1SvR6vXTo0EEyMzOLvG7btm2Tli1bSkhIiOzfv7/I0Lx5cwEgu3fvloSEBGnQoIE0bNhQLl68qPUdgPj7+1sMOp1OKlasKHZ2duLo6CgFBQUiIhIfHy9t27YVEREHBwfx9vaWMWPGFPueuri4iJ2dnYiIZGdni06nk19++UVrb9Kkidja2mqvfaHC98XBwUGOHj0qIiKenp5FXvewsDDR6/Vy7NixIuvu2bOn2NraSpMmTeTLL78UPz8/CQ8P144eTSaTts/QTQwiEfHx8ZHly5cX2+bo6ChLly4t8hcsKipKKlWqJA4ODhY7Vfny5eXEiRPaeGpqqtja2kpWVpb06tVL6tatKwcPHpRy5cppQZSRkaH14+DBgxbreeWVV8TKykpERF577TUZNWqURbtOp5OaNWsW6ffvv/8uzs7O4uHhIXq9Xn799VfR6/WyePFiraZDhw5Srlw5Wb16tWzYsEGef/55admypda+Zs0a0el0Rfp067r1en2xRxe3Ti90/fp1ad++vdSrV08uXLggvXr1EgBy5MgRi+UWhoG9vb12iiYikpOTI+XKlZPz589rp5j+/v7F9s1gMIizs7M2Xr58efntt9+08bS0NLGyshJfX1/56aefiqy7VatWMmHCBBERefbZZ2Xu3LkWy7e1tRUvL69i1125cmWZMWOGlC9fXkRE/vzzT2ncuLG0bt1arl+/ziOiYjCIRKR9+/by/vvvF9vWqFEj7RTidlFRUdqRVKGDBw9KXl6eNr5lyxYJCAjQxhcuXCienp6i1+u1IKpTp47Ur19fypcvL999953FOpYuXSpWVlbSvHlziY2NFTs7O2nWrJn0799fO+KYP39+sX0fNWqUuLu7S9u2bSUgIEBGjBghlStXlunTp8uMGTOkYsWKUq1aNbG2thadTifPPvusnDx5Upt/7dq14uLiYvFBvVWFChXkrbfeEnd3d0lNTS0y2NraFnnd8vLypGPHjlK3bl05cOCA6HQ68fX1lSlTpmg1hWHg4+MjSUlJ2vRLly6JTqcTs9ksb775plSsWFGsra0tjtYyMzPl+++/F2tra3n11Ve16V988YWYzWZtPCkpSby8vGTfvn0SFBQkAwYMkCtXrmjr3r59uzg5OcmYMWNkypQp4ubmJqNGjZL58+fL6NGjRafTycCBA4t9Xezs7GTBggVSoUIFbZrZbJaQkBBp1aqVnDx5kkF0GwaR3AyL1atXF9s2btw4ad26tWzatKnY9sIwKMnIkSMlMjLSYtrp06dl+fLlkp2dLWPHjrUY1qxZY1H77rvvyquvvirDhw+XoKAgsbW11a7tdO/eXXx8fOT8+fPFrjs/P18+/vhjeemll2TcuHFSUFAgCxcuFF9fX6lQoYL07t1bsrOz5dq1a8VeTBYRef/998XFxUU+++wz2b9/v5hMJjGZTLJ//36pXr262NnZlXh69NRTTxX72hSGUeXKlUWv18sff/whrVq1kjZt2si5c+e0MIiIiJAWLVrI0aNH5eTJk9qFYpGbR1cvv/yydtpsa2srtra2otfrxcbGRoKCguSLL74o8X2Ji4uTdu3aicjNC+IDBw6Up556SqysrOTw4cMiIrJ9+3Zp0qRJkaO9ihUrSrNmzcTPz0++//77IkFYsWJF8fDwkOjoaIt1ZmVlSUhIiDz99NMMotswiOiu4uPjxdvbWzvlKjwKdHFxkS5dupQ43+DBg6V27drFtuXl5cnLL7+sHTEVFBTIuHHjxMvLSwuD9PR0LQj0er34+flZXH9bsmSJjB8/XjZs2CALFiyQBQsWyIYNG4q9nnW7kydPWtz9FLl50yImJqbIdaOMjAzZsWOHbN++XU6dOiUiN4Nw0KBBYmNjUyQI9Xq9VKlSRa5fv15kvWazWYKDgxlEt+G376nUTp06ZfG8zt2eo7lx4wauXr1a4q8V3rhxA2fOnIGfn582LSkpCVu3bkWvXr3g4uIC4OZzXDk5OahRowasrR+vR9/MZjOSkpIsXpcqVaogOzsbtWrVKnaerKws7N27Fy1atHiUXX28qU5C+mtLS0uTPn363HPbg2j/9ddfpV27dtqp1K2uXbsmX375pfzyyy8PrT0uLk5mzZql3V07evSoDBo0SPr06WPxuEZ2drbMmjVL3nvvPZkyZUqJp9JPMgYRlUlycnKJpxl3aitre3EPmp45c0Zr37Ztm3bXrrgHUcvafqcHWe3t7UWv18v69euLfUjVw8PD4qYAiTxex7n02Pnxxx9LbNu5cyfS09MhIsXW/fjjjyW2lbV93LhxcHFxgclkQkpKCmJiYtCsWTNs2rQJlStXxkcffQQAyMjIwOXLlxETE4OmTZs+sPbCr+RcuHAB3377Lbp374433ngDH3/8MfR6PaKjoxEfHw8PDw/4+PggOTkZTk5OyM7OxiuvvIJ//vOfWLBgwR1e+SeM2hykx11pHvZECU8p36mtrO24y4Ombm5uFo8OPOj2Oz3IqtPpZNOmTeLp6VnsQ6rbtm0TX1/fh/ae/RUxiOiO7vSwp4+Pj3z22Wclnj65u7vf8QnisrTf7UFTe3v7Ep/9ehDtd3qQVafTSVJSktja2hb7kGrhM1b0P/w9IrqjBg0aICkpqcS2Y8eOlfjbSkFBQXf83aWytNeoUQNHjx4t0j516lR06NDB4r8Tfxjt165ds5iemJho8SsLr732GgoKCmA2m5GSkmJR+/vvv2u/ukD/T2kM0mPvTg97btmyRZYtW1biw55r166V8ePHl7jssrTf7UHTwi/GlqSs7Xd6kHXs2LHSrFkzqV+/fokPqXbt2rXEZT+J+BwRESnHUzMiUo5BRETKMYiISDkGEREpxyCiB27Tpk3Q6XS4fPmy6q7cF39/f0yaNEl1N54oDKInWMuWLRETE6O6G0QMIiJSj0H0iLRs2RKDBw/GsGHD4OrqCi8vL4wdOxYAkJqaCp1Oh+TkZK3+8uXL0Ol02LRpE4D/ne6sXbsW9evXh52dHVq1aoWMjAysXr0aNWvWhNFoRPfu3XH16tW79qd3797YvHkzJk+eDJ1OB51Oh9TUVADA5s2b0bhxYxgMBnh7e2PEiBG4ceOGNm9OTg4GDx4MDw8P2NraolmzZti9e3eJ6/r999/Rvn17uLi4wMHBAbVq1cKqVavu2sc5c+bA2dnZYtry5cuh0+m08f379+P555+Ho6MjjEYjGjRogD179mjtW7duxXPPPQc7Ozv4+vpi8ODBuHLlitaekZGB9u3bw87ODgEBAZg/f/5d+0UPHoPoEZo7dy4cHBywc+dOTJgwAf/617+QkJBwT8sYO3Yspk6diu3bt+P06dPo3LkzJk2ahAULFmDlypVYt24dpkyZctflTJ48GSEhIejfvz/OnTuHc+fOwdfXF2fOnEG7du3QqFEj7N+/H9OnT8fXX3+tfRsdAIYNG4alS5di7ty52Lt3LwIDAxEWFoaLFy8Wu66oqCjk5ORgy5YtOHjwIMaPH4/y5cvf03aXpEePHqhUqRJ2796NpKQkjBgxwuI/RWzTpg06deqEAwcOYNGiRdi6dSuio6O1+Xv37o3Tp09j48aN+O677/DFF18gIyPjgfSN7oHqR7ufFC1atND+I8VCjRo1kuHDh8upU6cEgOzbt09ru3TpkgCQjRs3iojIxo0bBYD8/PPPWk1cXJwAsPhfQwYOHChhYWGl7tPbb79tMe29996T6tWra/+Fj4jItGnTpHz58pKfny/Z2dlSrlw5ix/sz83NFR8fH+1/vSjs66VLl0REpE6dOjJ27NhS9elWs2fPFicnJ4tpy5Yts/hqhaOjo8yZM6fY+SMjI2XAgAEW03755RfR6/Vy7do1SUlJEQCya9curf3o0aMCQD7//PN77i/dPx4RPUJ169a1GPf29r7nv763LsPT0xP29vaoUqWKxbSy/EU/evQoQkJCLE5/mjZtiuzsbPzxxx84ceIE8vLy0LRpU629XLlyaNy4MY4ePVrsMgcPHoyPPvoITZs2xZgxY3DgwIH77t/tYmNj0a9fP4SGhiI+Ph4nTpzQ2vbv3485c+agfPny2hAWFoaCggKcOnUKR48ehbW1NRo0aKDNU6NGjSKng/TwMYgeocJThkI6nQ4FBQXQ62++DXLL1/7y8vLuugydTlfiMh8n/fr1w8mTJ9GzZ08cPHgQDRs2LNXpo16vL/Lt+ttfl7Fjx+Lw4cMIDw/Hhg0bEBQUhGXLlgEAsrOzMXDgQCQnJ2vD/v37cfz4cVStWvXBbSCVGYPoMeDu7g4AOHfunDbt1gvXD4uNjQ3y8/MtptWsWROJiYkWAbBt2zY4OjqiUqVKqFq1KmxsbLBt2zatPS8vD7t370ZQUFCJ6/L19cWgQYPw/fff45133sGXX3551/65u7sjKyvL4uJyca9LtWrVMGTIEKxbtw6vvvoqZs+eDQB45plncOTIEQQGBhYZbGxsUKNGDdy4ccPiZ05SUlL+ss8//ZUxiB4DdnZ2aNKkCeLj43H06FFs3rwZo0aNeujr9ff3x86dO5Gamorz58+joKAAb775Jk6fPo233noLx44dww8//IAxY8YgNjYWer0eDg4OeOONNzB06FCsWbMGR44cQf/+/XH16lVERkYWu56YmBisXbsWp06dwt69e7Fx40bUrFnzrv0LDg6Gvb093nvvPZw4cQILFizAnDlztPZr164hOjoamzZtwu+//45t27Zh9+7d2rKHDx+O7du3Izo6GsnJyTh+/Dh++OEH7WJ19erV0aZNGwwcOBA7d+5EUlIS+vXrBzs7u7K/uHRvFF+jemIUd2G4Q4cOEhERISIiR44ckZCQELGzs5N69erJunXrir1YXXgBWKT4i7ljxoyRp59+ulR9SklJkSZNmoidnZ0A0P7Prk2bNkmjRo3ExsZGvLy8ZPjw4Rb/e+21a9fkrbfeEjc3NzEYDNK0aVOLC7639zU6OlqqVq0qBoNB3N3dpWfPnqX+nyyWLVsmgYGBYmdnJy+99JLMnDlTu1idk5MjXbt2FV9fX7GxsREfHx+Jjo6Wa9euafPv2rVLXnzxRSlfvrw4ODhI3bp15eOPP9baz507J+Hh4WIwGKRy5cryzTffiJ+fHy9WP2L8PSIiUo6nZkSkHIPobyotLc3itvXtQ1pamuouYtCgQSX2b9CgQaq7R48QT83+pm7cuKF9ZaM4/v7+yv/75oyMDJjN5mLbjEYjPDw8HnGPSBUGEREpx1MzIlKOQUREyjGIiEg5BhERKccgIiLlGEREpByDiIiUYxARkXL/B6bLD6Ub1GcbAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.subplot(1, 3, 3)\n", "df['num_tools_used'].value_counts().sort_index().plot(kind='bar')\n", "plt.title('Number of Tools Used per Query')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 140, "id": "05fa2f84-4f22-4ddd-9915-7e348864283e", "metadata": {}, "outputs": [], "source": [ "def analyze_query_patterns(query):\n", " return {\n", " 'has_numbers': bool(re.search(r'\\d+', query)),\n", " 'is_question': query.strip().endswith('?'),\n", " 'starts_with_wh': bool(re.search(r'^(what|where|when|why|who|how)', query.lower())),\n", " 'has_comparison': bool(re.search(r'(compare|versus|vs|difference|between)', query.lower())),\n", " 'has_specific_value': bool(re.search(r'\\d+\\s*[a-zA-Z]+', query)), # e.g., \"5 meters\"\n", " 'has_quotes': bool(re.search(r'\"[^\"]*\"', query))\n", " }\n", "\n", "df['query_patterns'] = df['query'].apply(analyze_query_patterns)\n", "pattern_df = pd.DataFrame(df['query_patterns'].tolist())" ] }, { "cell_type": "code", "execution_count": 141, "id": "6e271926-1521-475b-ab1d-9470a235dc62", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Query Pattern Analysis:\n", "has_numbers: 73.3%\n", "is_question: 36.6%\n", "starts_with_wh: 18.6%\n", "has_comparison: 3.4%\n", "has_specific_value: 45.6%\n", "has_quotes: 0.0%\n" ] } ], "source": [ "print(\"\\nQuery Pattern Analysis:\")\n", "for column in pattern_df.columns:\n", " print(f\"{column}: {pattern_df[column].mean()*100:.1f}%\")def analyze_tool_parameters():\n", " param_types = defaultdict(list)\n", " param_defaults = defaultdict(list)\n", " \n", " for _, row in df.iterrows():\n", " if isinstance(row.get('parameter_info'), dict):\n", " for param_name, param_data in row['parameter_info'].items():\n", " param_types[param_name].append(param_data['type'])\n", " if param_data['has_default']:\n", " param_defaults[param_name].append(param_data['default_value'])\n", " \n", " return {\n", " 'types': {k: Counter(v).most_common() for k, v in param_types.items()},\n", " 'defaults': param_defaults\n", " }" ] }, { "cell_type": "code", "execution_count": 142, "id": "57604560-835f-4b44-8218-3841c0c3f8ef", "metadata": {}, "outputs": [], "source": [ "def analyze_tool_parameters():\n", " param_types = defaultdict(list)\n", " param_defaults = defaultdict(list)\n", " \n", " for _, row in df.iterrows():\n", " if isinstance(row.get('parameter_info'), dict):\n", " for param_name, param_data in row['parameter_info'].items():\n", " param_types[param_name].append(param_data['type'])\n", " if param_data['has_default']:\n", " param_defaults[param_name].append(param_data['default_value'])\n", " \n", " return {\n", " 'types': {k: Counter(v).most_common() for k, v in param_types.items()},\n", " 'defaults': param_defaults\n", " }" ] }, { "cell_type": "code", "execution_count": 143, "id": "ef73a967-ed64-4e64-94ee-37b7a0cba617", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Parameter Analysis:\n", "\n", "Parameter Types:\n", "type: str\n", "chain_slug: str\n", "symbol: str\n", "interval: str\n", "format: str, optional\n", "v_factor: int, optional\n", "series_type: str, optional\n", "outputsize: int, optional\n", "time_period: int, optional\n", "genres: str, optional\n", "limit: int, optional\n", "source_ids: str\n", "source_types: str\n", "types: str\n", "regions: str\n", "sort_by: str, optional\n", "page: int, optional\n", "network_ids: str\n", "release_date_start: int\n", "release_date_end: int\n", "is_id: str\n", "locale: str, optional\n", "currency: str, optional\n", "country: str, optional\n", "q: str\n", "nums: List[int]\n", "url: str\n", "timestamp: int\n", "callback: str, optional\n", "domain: str\n", "query: str\n", "day: int\n", "year: int\n", "month: int\n", "location: str\n", "items: list\n", "quantity: list\n", "aweme_id: int\n", "locale_info: str\n", "lang_id: int, optional\n", "time_utc_offset: int, optional\n", "present_value: float\n", "annual_interest_rate: float\n", "years: int\n", "latitude: int\n", "longitude: int\n", "from_date: str\n", "to_date: str\n", "elevation: int, optional\n", "time: float\n", "a: float\n", "b: int\n", "experiment_id: int\n", "identifier: str\n", "choice: str\n", "count: int, optional\n", "currentcountry: str\n", "purchasecountry: str\n", "homecountry: str\n", "username: str\n", "lang: str, optional\n", "evt: int\n", "principal: float\n", "annual_addition: float\n", "return_rate: float\n", "inflation: List[float]\n", "inflation_adjusted: bool, optional\n", "profile_id: str, optional\n", "uid: str\n", "player_id: int\n", "ticker: str\n", "caid: int\n", "gl: str, optional\n", "cr: str, optional\n", "tbs: str, optional\n", "num: int\n", "start: int, optional\n", "hl: str, optional\n", "quotes: str\n", "securities_code: int\n", "strs: List[str]\n", "sort: str, optional\n", "offset: int, optional\n", "price_max: int\n", "city: str\n", "pid: str\n", "cursor: str, optional\n", "user_id: str\n", "board: List[List[str]]\n", "language: str, optional\n", "keyword: str\n", "filters: str, optional\n", "curpage: int, optional\n", "itemsperpage: int, optional\n", "sortby: str\n", "name: str\n", "week: str, optional\n", "difficulty: str, optional\n", "charge: int\n", "distance: int\n", "permitivity: float\n", "total: int\n", "extroverts: int\n", "introverts: int\n", "size: int, optional\n", "text: str\n", "status: str, optional\n", "phone_id: str\n", "cnt: int, optional\n", "units: str, optional\n", "login_id: str\n", "api_key: str\n", "survey_code: str\n", "tanggal: str\n", "source_id: str\n", "region: str, optional\n", "nested_list: List\n", "is_from: str\n", "to: str\n", "adjust: bool, optional\n", "target_sum: int\n", "num_dice: int\n", "num_faces: int, optional\n", "period: str\n", "season_id: int\n", "s: str\n", "od: float\n", "dilution: int\n", "factor: float, optional\n", "base: str\n", "height: float\n", "cast_name: str, optional\n", "product_id: str\n", "time_bucket: str\n", "pair_id: int\n", "end: int\n", "event_id: int\n", "weight_kg: float\n", "height_cm: float\n", "age: int\n", "sex: str\n", "activity_level: int\n", "goal: str\n", "seasonid: int\n", "tournamentid: int\n", "points: int\n", "tconst: str\n", "zip: str\n", "target: int\n", "date: str\n", "sign: str\n", "n: int\n", "continent: str\n", "fields: str, optional\n", "ids: str\n", "amount: float\n", "lst: List\n", "chunk_size: int\n", "sname: str\n", "fname: str\n", "numbers: List[float]\n", "descending: bool, optional\n", "connection: str\n", "content_type: str\n", "hash: str\n", "match_id: str\n", "store_location: str\n", "item_list: list\n", "order_size: str\n", "market: str\n", "crypto: str, optional\n", "fiats: str, optional\n", "lat1: int\n", "lat2: int\n", "lon2: int\n", "lon1: int\n", "unit: str, optional\n", "source: str, optional\n", "total_dividend: int\n", "num_shares: int\n", "vin: str\n", "mileage: str, optional\n", "search: str\n", "string: str\n", "word: str\n", "continent_code: str, optional\n", "password: str\n", "hotel: str\n", "checkin: str\n", "checkout: str\n", "lang_3: str, optional\n", "iso_a2: str, optional\n", "email: str\n", "hour: int\n", "minute: int\n", "ds: str\n", "asset_type: str\n", "market_venue: str\n", "data_type: str\n", "asin: str\n", "manufacturer: str, optional\n", "vertices: List[Tuple[float, float]]\n", "voice_name: str, optional\n", "l: int\n", "max_rank: str, optional\n", "min_rank: str, optional\n", "max_waist: str, optional\n", "max_cup_size: str, optional\n", "min_cup_size: str, optional\n", "min_weight: str, optional\n", "max_weight: str, optional\n", "max_age: str, optional\n", "ethnicity: str, optional\n", "min_age: str, optional\n", "nationality: str, optional\n", "tattoos: str, optional\n", "eyes: str, optional\n", "hair: str, optional\n", "min_waist: str, optional\n", "date_of_birth: str, optional\n", "std_dev: float\n", "sample_size: int\n", "mean: float\n", "confidence: float, optional\n", "ordering: str\n", "language_code: str\n", "id_detail: str\n", "range: str\n", "fontstack: str\n", "min_strike: int, optional\n", "min_expiry: str, optional\n", "max_expiry: str, optional\n", "max_strike: int, optional\n", "strike: int, optional\n", "expiration: str\n", "site: str, optional\n", "tm: int\n", "m: str, optional\n", "first_name: str\n", "last_name: str\n", "matchtype: str\n", "collapse: str\n", "fl: str\n", "filter: str, optional\n", "timezone: str\n", "useragent: str\n", "auth_id: str\n", "signstart: str\n", "signend: str\n", "sess: str\n", "xbc: str\n", "apptoken: str\n", "show: str, optional\n", "beerid: str\n", "number: int\n", "radius: float\n", "symbols: str\n", "end_date: str\n", "start_date: str\n", "input: str, optional\n", "season: str, optional\n", "guid: str\n", "skip: int\n", "p: float\n", "label: str, optional\n", "subaccounts: str, optional\n", "group_by: str, optional\n", "zipcode: str\n", "address: str\n", "valuta: str\n", "category: str\n", "from_to: str\n", "product_sku: str\n", "since: str, optional\n", "start_value: float\n", "end_value: float\n", "from_symbol: str\n", "to_symbol: str\n", "code: str\n", "nrds_id: str\n", "advertiser_id: int\n", "initial_velocity: float\n", "acceleration: float\n", "lower: int\n", "upper: int\n", "divisor: int\n", "dividend: int\n", "dict1: Dict\n", "dict2: Dict\n", "sentence: str\n", "airline: str\n", "voltage: float\n", "make: str, optional\n", "street_address: str\n", "business_name: str\n", "artistid: str\n", "width: int, optional\n", "theme: str\n", "arr: List[int]\n", "phrase1: str\n", "phrase2: str\n", "initial_population: int\n", "growth_rate: float\n", "doubling_time: float, optional\n", "brand: str, optional\n", "title: str\n", "price: int, optional\n", "length: int\n", "uppercase: bool, optional\n", "lowercase: bool, optional\n", "digits: bool, optional\n", "special_chars: bool, optional\n", "lr: str\n", "state: str\n", "pagesize: int\n", "startindex: int, optional\n", "total_cards: int\n", "desired_cards: int\n", "cards_drawn: int\n", "iata: str, optional\n", "icao: str, optional\n", "lat: int\n", "lng: int\n", "origin: str\n", "destination: str\n", "avoid_routes: str, optional\n", "arrival_time: int, optional\n", "departure_time: int, optional\n", "distance_units: str, optional\n", "race_no: str\n", "chain: str, optional\n", "platecodeloc: str\n", "input_format: str\n", "output_format: str\n", "tp: str, optional\n", "num_of_days: int, optional\n", "id_horse: str\n", "awb: str\n", "str1: str\n", "str2: str\n", "fresh: int, optional\n", "isin: str, optional\n", "alias: str\n", "model: str\n", "sedol: str, optional\n", "companyname: str, optional\n", "lastprice: int, optional\n", "term: str\n", "color: str, optional\n", "sample1: List[float]\n", "sample2: List[float]\n", "alpha: float, optional\n", "dataset: str\n", "subset: str\n", "passport: str\n", "goverlytics_id: str\n", "region_code: str\n", "country_code: str\n", "target_value: int\n", "num_rolls: int\n", "num_sides: int, optional\n", "channel: str\n", "resort: str\n", "el: str, optional\n", "province: str\n", "protein_in_grams_lt: int\n", "protein_in_grams_gt: int\n", "playlist_id: str\n", "lon: int\n", "hours: int\n", "k: int\n", "starid: str\n", "function: str\n", "x: float\n", "words: List[str]\n", "data: list\n", "bins: int\n", "vector_a: List[float]\n", "vector_b: List[float]\n", "blockchain: str\n", "end_time: str, optional\n", "start_time: str, optional\n", "configuration: str, optional\n", "token: str\n", "host_name: str\n", "immatriculation: str\n", "c: float\n", "rating: str, optional\n", "location_id: int\n", "matrix_a: List[List[float]]\n", "matrix_b: List[List[float]]\n", "team_id: int\n", "point1: List[float]\n", "point2: List[float]\n", "message: str\n", "trim: str, optional\n", "direction: str, optional\n", "make_model_trim_id: str, optional\n", "rgb: str, optional\n", "verbose: str, optional\n", "json: str, optional\n", "make_id: str, optional\n", "make_model_id: str, optional\n", "ingredient: str\n", "sticker_ids: str\n", "ticker_slug: str\n", "page_number: int\n", "item_id: str\n", "lan: str, optional\n", "network: str, optional\n", "keywords: str\n", "includesource: bool, optional\n", "rtype: str\n", "from_unit: str\n", "to_unit: str\n", "item: str\n", "intervals: List[List[int]]\n", "fitness_level: str\n", "body_frame: str\n", "gender: str, optional\n", "formula: str, optional\n", "search_type: str, optional\n", "exchange: str, optional\n", "quoteassetid: str, optional\n", "baseassetid: str, optional\n", "fast_dma_type: str\n", "fast_d_period: int\n", "fast_k_period: int\n", "image: str\n", "cat_id: str, optional\n", "table: str\n", "conditions: list\n", "publish_time: int, optional\n", "sort_type: int, optional\n", "category_group: str, optional\n", "dir: str, optional\n", "order: str, optional\n", "bot: str, optional\n", "category_group_id: int, optional\n", "bot_id: int, optional\n", "postcode: str\n", "point_a: Tuple[float, float]\n", "point_b: Tuple[float, float]\n", "building_id: str\n", "floor_numbers: List[int]\n", "analysis_mode: str, optional\n", "length_m: int\n", "area_sq_m: float\n", "material: str, optional\n", "game: str\n", "scores: List[float]\n", "weights: List[float]\n", "userid: str\n", "upc: str\n", "ip: str\n", "species: str\n", "cookie: str\n", "host: str, optional\n", "referer: str\n", "initial_amount: int\n", "interest_rate: float\n", "num_years: int\n", "word1: str\n", "word2: str\n", "birthdate: str\n", "website: str\n", "arr_lat: int\n", "arr_lng: int\n", "dep_lat: int\n", "dep_lng: int\n", "max_cursor: str, optional\n", "tour_id: int\n", "info: bool, optional\n", "sdate: str\n", "edate: str\n", "fat_in_grams_lt: int\n", "fat_in_grams_gt: int\n", "req1: str\n", "req2: int, optional\n", "req3: str, optional\n", "req6: int, optional\n", "info3: str\n", "info1: str\n", "info2: str\n", "creator_id: int\n", "cat: str\n", "getdata: str, optional\n", "popular_only: str, optional\n", "nexttoken: str, optional\n", "hero: str\n", "regex: str\n", "current_pop: int\n", "annual_growth: float, optional\n", "song_id: str, optional\n", "created_by_id: str, optional\n", "text_format: str, optional\n", "per_page: int, optional\n", "web_page_id: str, optional\n", "place_id: str, optional\n", "postal_code: str\n", "synaptic_input_rate: int\n", "synaptic_weight: float, optional\n", "decay_constant: float, optional\n", "tournament_id: int\n", "mailid: str\n", "start_id: int\n", "time_out: int, optional\n", "aqiindex: str, optional\n", "county: str, optional\n", "event: int, optional\n", "image_id: str\n", "src_attr: str, optional\n", "kinds: str, optional\n", "src_geom: str, optional\n", "rate: float\n", "showid: str\n", "conversation: str, optional\n", "conversation_id: int, optional\n", "output: str, optional\n", "matchid: int\n", "studies: str\n", "country_iso2: str\n", "page_size: int, optional\n", "population_min: int, optional\n", "next_token: str, optional\n", "population_max: int, optional\n", "sid: int\n", "ppn_bundle: str\n", "convert_currency: str, optional\n", "perpage: int, optional\n", "latlng: str, optional\n", "time_interval: str\n", "gallery: str, optional\n", "newspaper: str\n", "goods_spu: str, optional\n", "sku: str, optional\n", "goods_id: str, optional\n", "iso_code: str\n", "coin: str\n", "market_type: str\n", "did: int\n", "topk: int, optional\n", "countrycodes: str, optional\n", "json_callback: str, optional\n", "polygon_text: str, optional\n", "namedetails: str, optional\n", "viewbox: str, optional\n", "polygon_geojson: str, optional\n", "bounded: str, optional\n", "polygon_svg: str, optional\n", "polygon_kml: str, optional\n", "polygon_threshold: int, optional\n", "accept_language: str, optional\n", "addressdetails: str, optional\n", "minecraftversion: str\n", "end_cursor: str, optional\n", "resume_key: str, optional\n", "die: int\n", "shape: str, optional\n", "song: str\n", "artist: str\n", "include_special: bool, optional\n", "linkedin_url: str\n", "player: str, optional\n", "team: str, optional\n", "city_id: int, optional\n", "mac_number: str\n", "min_rating: str, optional\n", "product_condition: str, optional\n", "max_shipping_days: int, optional\n", "store_id: str, optional\n", "on_sale: bool, optional\n", "free_returns: bool, optional\n", "free_shipping: bool, optional\n", "max_price: int, optional\n", "min_price: int, optional\n", "no_of_save: int, optional\n", "min_sales: int, optional\n", "provider: str\n", "webtoon: str\n", "case: str, optional\n", "extra: str, optional\n", "related_keywords: str, optional\n", "drug: str\n", "breed: str\n", "list1: List[int]\n", "list2: List[int]\n", "line: str\n", "user: str\n", "start_lat: int\n", "end_lon: int\n", "start_lon: int\n", "end_lat: int\n", "distance_unit: str, optional\n", "cache_key: str, optional\n", "countrycode: str\n", "admin2: str, optional\n", "admin1: str, optional\n", "admin4: str, optional\n", "admin3: str, optional\n", "rank: int\n", "record_type: str, optional\n", "response_type_seperator: str, optional\n", "response_type: str, optional\n", "federation: str, optional\n", "tour_code: str\n", "directory: str\n", "extension: str\n", "int: str, optional\n", "until: int, optional\n", "state_code: str\n", "license_plate: str\n", "topic: str\n", "x_values: List[float]\n", "y_values: List[float]\n", "target_x: float\n", "counter: str, optional\n", "after: str, optional\n", "platform: str\n", "gameid: str\n", "number_of_puzzles: int, optional\n", "round: str\n", "hotel_ids: int\n", "languagecode: str, optional\n", "func: str\n", "section: str, optional\n", "pair_slug: str\n", "exchange_slug: str\n", "columns: str\n", "screenername: str, optional\n", "include: str\n", "slug: str\n", "dtid: int\n", "reference: str\n", "aqi: str, optional\n", "alerts: str, optional\n", "request_id: str\n", "page_id: str\n", "imdbid: str\n", "currencies: str, optional\n", "num_hits: int\n", "num_at_bats: int\n", "precision: int, optional\n", "t: str\n", "room_facility_type_id: str, optional\n", "facility_type_id: str, optional\n", "cycle_length: str\n", "last_period_date: str\n", "localite: str\n", "tickerid: int\n", "trip_uid: str\n", "company: str\n", "hashtag: str\n", "include_humans: bool, optional\n", "geo: str, optional\n", "teamid: int\n", "brandid: int\n", "job_title: str\n", "kem: str\n", "h: int\n", "co_uasg: int\n", "numprp: int\n", "cnpj: str\n", "searchterm: str\n", "downpayment: int, optional\n", "home_value: int, optional\n", "monthly_hoa: int, optional\n", "annual_property_tax: str, optional\n", "duration_years: int\n", "loan_amount: float\n", "annual_home_insurance: int, optional\n", "fragment: str, optional\n", "nconst: str\n", "id_race: str\n", "mot: str\n", "limite: str, optional\n", "s_amount_usd: str\n", "t_blockchain: str\n", "post_id: str\n", "fmt: str, optional\n", "part: str\n", "video_id: str\n", "zip_code: str, optional\n", "spotify_url: str\n", "daylights_offset: str, optional\n", "daylights_code: str, optional\n", "daylights: str, optional\n", "mlemid: int\n", "expand: str, optional\n", "country_name: str\n", "mass: float\n", "volume: float\n", "town: str\n", "aid: int\n", "version: str\n", "os: str, optional\n", "energy: int, optional\n", "consumption: str\n", "x_cachebypass: str, optional\n", "timestamp_first: bool, optional\n", "remove_dash: bool, optional\n", "block: str\n", "num_draw: int, optional\n", "quantities: List[int]\n", "prices: List[float]\n", "petid: int\n", "weight_lbs: int\n", "height_inches: int\n", "activity: str\n", "station_id: int\n", "sortorder: str, optional\n", "country_id: int, optional\n", "state_id: str, optional\n", "state_name: str, optional\n", "d: str\n", "logotext: str, optional\n", "fgdcolor: str, optional\n", "qrsize: int, optional\n", "e: int, optional\n", "addtext: str, optional\n", "txtcolor: str, optional\n", "bgdcolor: str, optional\n", "profile_display_name: str\n", "canonical_term: str\n", "search_value: str\n", "min_height: int, optional\n", "min_net_worth: int, optional\n", "max_net_worth: int, optional\n", "max_height: int, optional\n", "barcode: str\n", "series_id: int\n", "style: str\n", "app_id: int\n", "price_range: str, optional\n", "yelp_domain: str, optional\n", "author: str\n", "control: str\n", "pokemon_name: str\n", "move_name: str, optional\n", "track_url: str\n", "chapter_number: int\n", "recitation_id: int\n", "business_id: str\n", "flag: int, optional\n", "start_year: int, optional\n", "max_imdb: int, optional\n", "min_imdb: int, optional\n", "genre: str\n", "end_year: int, optional\n", "range_highway: str, optional\n", "range_city: str, optional\n", "combined_mpg: str, optional\n", "epa_highway_mpg: str, optional\n", "epa_city_mpg: str, optional\n", "lastid: int, optional\n", "uuid: str\n", "message_id: int\n", "template: str, optional\n", "protectiveness: int, optional\n", "trainability: int, optional\n", "shedding: int, optional\n", "barking: int, optional\n", "max_life_expectancy: int, optional\n", "min_life_expectancy: int, optional\n", "vehicle_make: str\n", "rows: int\n", "minrounds: str, optional\n", "timespan: str, optional\n", "map: str, optional\n", "agent: str, optional\n", "minrating: str, optional\n", "event_series: str, optional\n", "payor_monthly_income: int\n", "recipient_monthly_income: int\n", "max_length: int, optional\n", "min_length: int, optional\n", "min_speed: int, optional\n", "min_range: int, optional\n", "max_range: int, optional\n", "max_speed: int, optional\n", "tag: str\n", "start_month: int\n", "number_of_months: int\n", "enclosuretype: str, optional\n", "sample: int, optional\n", "analyzed: bool, optional\n", "subcategorization: str, optional\n", "polysemous: bool, optional\n", "pos: str, optional\n", "monosemous: bool, optional\n", "morph: bool, optional\n", "get_dash_url: str\n", "edinet_code: str\n", "article_url: str\n", "author_url: str, optional\n", "author_name: str, optional\n", "currency_code: str, optional\n", "siteid: int, optional\n", "link: str\n", "delivery: str, optional\n", "repo: str\n", "path: str\n", "key: str\n", "content: str\n", "category_id: str, optional\n", "sequence_id: str\n", "file_format: str, optional\n", "upstream_bases: int, optional\n", "code_com: str\n", "image_size: str, optional\n", "next: str, optional\n", "terms: str\n", "cid: str\n", "artist_id: str\n", "skin_name: str\n", "genre_id: int, optional\n", "langs: str, optional\n", "details: bool, optional\n", "categories: str, optional\n", "iso3: str\n", "iso2: str\n", "https_only: str\n", "wmid: str\n", "songid: str\n", "song_preview_kbps: str\n", "currency_base: str\n", "currency_quote: str\n", "stockcode: str\n", "ident: str, optional\n", "localid: str, optional\n", "frequency: str\n", "statement_type: str\n", "bl_lng: int\n", "tr_lat: int\n", "bl_lat: int\n", "tr_lng: int\n", "speed: str, optional\n", "altitude: str, optional\n", "airport: str, optional\n", "reg: str, optional\n", "match_value: str\n", "zoom: int, optional\n", "match_type: str, optional\n", "grid_size: str\n", "uri: str\n", "job_id: str\n", "exclude_job_publishers: str, optional\n", "employer: str, optional\n", "job_requirements: str, optional\n", "remote_jobs_only: bool, optional\n", "job_titles: str, optional\n", "company_types: str, optional\n", "num_pages: str, optional\n", "date_posted: str, optional\n", "employment_types: str, optional\n", "league_id: str\n", "distance_in_light_years: int\n", "speed_of_light: int\n", "start_with_lorem_ipsum: str, optional\n", "random: str, optional\n", "paragraphs: int, optional\n", "tcin: str\n", "challenge_name: str\n", "verbeconjugue: bool, optional\n", "minlong: str, optional\n", "maxlong: str, optional\n", "avecdef: bool, optional\n", "contingency_table: List[List[int]]\n", "significance_level: float, optional\n", "by: str, optional\n", "area: str\n", "hotel_id: str\n", "airport_limit: int, optional\n", "check_in: str, optional\n", "promo: bool, optional\n", "photos: bool, optional\n", "videos: bool, optional\n", "guest_score_breakdown: bool, optional\n", "reviews: bool, optional\n", "city_limit: int, optional\n", "important_info: bool, optional\n", "recent: bool, optional\n", "poi_limit: int, optional\n", "plugins: bool, optional\n", "id_lookup: bool, optional\n", "check_out: str, optional\n", "nearby: bool, optional\n", "numberoftopresults: int, optional\n", "listing_id: int\n", "outcome: str, optional\n", "sport: str\n", "fighter: int, optional\n", "postid: str\n", "resolution: str, optional\n", "sp: int\n", "ticket: str\n", "recipe_id: str\n", "domain_id: str\n", "dice: int, optional\n", "sides: int, optional\n", "airportiatacode: str\n", "sum: int\n", "maker: str\n", "bodypart: str\n", "tweet_id: str\n", "sec_uid: str\n", "target_lang: str\n", "ip_address: str\n", "slow_limit: int, optional\n", "fast_limit: int, optional\n", "left: int\n", "right: int\n", "league: str, optional\n", "polygon: str, optional\n", "force: str\n", "hex: str\n", "group: str, optional\n", "days: int, optional\n", "abbr: str\n", "leagueyear: str, optional\n", "fill_char: str\n", "add: str, optional\n", "generator: str\n", "loan_term_years: int\n", "params: str\n", "hotel_type_id: str, optional\n", "dt: str, optional\n", "proxy: str, optional\n", "background_color: str, optional\n", "eye_pattern: str, optional\n", "error_correction: str, optional\n", "data_gradient_start_color: str, optional\n", "data_gradient_style: str, optional\n", "data_pattern: str, optional\n", "eye_color_outer: str, optional\n", "data_gradient_end_color: str, optional\n", "eye_color_inner: str, optional\n", "climate: str\n", "position: str\n", "collection: str\n", "short_code: str\n", "ipaddress: str, optional\n", "kun: str\n", "northing: int\n", "easting: int\n", "datum: str, optional\n", "coord_unit: str, optional\n", "vehicle: str\n", "dial_code: int, optional\n", "iso_a3: str, optional\n", "currency_num_code: str, optional\n", "i: int\n", "unique_id: str\n", "isbn: str\n", "ayah_key: str\n", "language_id: int\n", "symb: str\n", "tech: str\n", "client_secret: str, optional\n", "client_id: str, optional\n", "sticker_id: str\n", "competition_id: int\n", "notfound: str, optional\n", "property_id: int\n", "order_by: str, optional\n", "browse_id: str\n", "character_id: str\n", "session_id: str\n", "job_url: str\n", "include_skills: str, optional\n", "class_name: str\n", "social_networks: str, optional\n", "document_id: str\n", "center: str\n", "rpos: str\n", "max_lat: int, optional\n", "min_population: int, optional\n", "min_lon: int, optional\n", "max_population: int, optional\n", "min_lat: int, optional\n", "max_lon: int, optional\n", "restaurant: str\n", "muscle: str, optional\n", "long: str\n", "protocol: str\n", "filter_language: str, optional\n", "filter_customer_type: str, optional\n", "user_sort: str, optional\n", "pageindex: int, optional\n", "scientificname: str\n", "compounding: str, optional\n", "in_currency: str, optional\n", "to_currency: str, optional\n", "cmd: str\n", "orig: str\n", "article: str\n", "room_type_id: str, optional\n", "weight: int\n", "ingredients: str\n", "book_name: str\n", "currentpage: int\n", "qualities: str, optional\n", "fits: str, optional\n", "sizes: str, optional\n", "colorwithnames: str, optional\n", "contexts: str, optional\n", "functions: str, optional\n", "concepts: str, optional\n", "descriptivelengths: str, optional\n", "hateoasmode: bool, optional\n", "division_name: str\n", "phone: str\n", "freq1: int\n", "freq2: int\n", "bpm: int, optional\n", "refresh: str, optional\n", "abn: str\n", "startdate: str, optional\n", "tickername: str\n", "enddate: str, optional\n", "max_elevation: int, optional\n", "min_elevation: int, optional\n", "route: str\n", "formstyle: str, optional\n", "freq: str, optional\n", "corsenabled: str, optional\n", "nextmaxid: str, optional\n", "uname: str\n", "sellerid: str\n", "captcha: str\n", "with_genres: str\n", "source_coordinates: str\n", "destination_coordinates: str\n", "return_route_coordinates: bool, optional\n", "arrival_timestamp: int, optional\n", "housenumber: int\n", "housenumbersuffix: str, optional\n", "fontname: str, optional\n", "noise_number: int, optional\n", "y: int\n", "z: int\n", "cci: str\n", "brandname: str\n", "family: str\n", "channelid: str\n", "maxresults: int, optional\n", "pagetoken: str, optional\n", "shipid: str\n", "image_url: str\n", "fullscreen: str, optional\n", "cache_control: str\n", "secret: str\n", "e_mail: str\n", "action: str\n", "max_id: str, optional\n", "fg_color: str, optional\n", "bg_color: str, optional\n", "video_url: str\n", "vat: str\n", "location_name: str\n", "max_period: int, optional\n", "max_temperature: int, optional\n", "max_distance_light_year: int, optional\n", "min_distance_light_year: int, optional\n", "max_mass: int, optional\n", "max_semi_major_axis: int, optional\n", "min_mass: int, optional\n", "min_semi_major_axis: int, optional\n", "min_temperature: int, optional\n", "max_radius: int, optional\n", "min_radius: int, optional\n", "min_period: int, optional\n", "batch_size: int, optional\n", "next_cursor: str, optional\n", "timeframe: str\n", "album_id: str\n", "search_term: str\n", "exclude: str, optional\n", "ig: str\n", "side: str\n", "question: str\n", "chathistory: str, optional\n", "localauthority: str\n", "rid: str\n", "max_deviation: int, optional\n", "min: int, optional\n", "max: int, optional\n", "colorname: str\n", "movie_year: int, optional\n", "idd: str\n", "msg_id: int\n", "movie_id: int\n", "with_cast: bool, optional\n", "with_images: bool, optional\n", "playerid: str\n", "veiculo_tipo: str\n", "id_marca: str\n", "tilerow: int\n", "tilematrix: str\n", "tilecol: int\n", "rotationangle: int, optional\n", "mapstyle: str, optional\n", "landmarkicon: str, optional\n", "contour: str, optional\n", "bldgname: str, optional\n", "logo: str, optional\n", "video: str\n", "pairs: str\n", "langid: int, optional\n", "sporttype: int\n", "payload: str\n", "ruleset: str\n", "sic_code: int\n", "videoid: str\n", "periods: int\n", "values: str\n", "dates: str\n", "uetr: str\n", "lastname: str, optional\n", "firstname: str, optional\n", "that: str, optional\n", "pattern: str, optional\n", "score_id: str\n", "scale: int, optional\n", "postal_fsa: str\n", "bin: int\n", "level: str, optional\n", "value: str\n", "description: str\n", "packages: str\n", "sekolah_id_enkrip: str\n", "start_x: int\n", "end_x: int\n", "method: str\n", "x_funtranslations_api_secret: str\n", "bgimg: str\n", "rmber: bool\n", "tags: str, optional\n", "mnemonic: str\n", "duration: str, optional\n", "chips: str, optional\n", "ijn: str, optional\n", "html: str, optional\n", "uule: str, optional\n", "device: str, optional\n", "safe: str, optional\n", "nfpr: str, optional\n", "adp: str\n", "mobno: int\n", "nome: str, optional\n", "cpf: str\n", "zpid: int, optional\n", "property_url: str, optional\n", "searchtopic: str\n", "list: str\n", "track_id: str\n", "nom: str, optional\n", "filter_zero_volume: bool\n", "search_filter: str, optional\n", "playlistlimit: int, optional\n", "artistlimit: int, optional\n", "securityid: str\n", "penalty: int, optional\n", "outputformat: str, optional\n", "reqid: str, optional\n", "tabname: str, optional\n", "country_auto: int, optional\n", "date_from: str, optional\n", "date_to: str, optional\n", "rego: str\n", "exact: int, optional\n", "steamappid: int, optional\n", "suit: str, optional\n", "employers: str, optional\n", "pair: str\n", "meta_property: str\n", "property_value: str\n", "meta_property_attribute: str, optional\n", "trend_type: str\n", "x_user_agent: str, optional\n", "last_days: int\n", "brightness: str, optional\n", "maxheight: int, optional\n", "minwidth: int, optional\n", "minheight: int, optional\n", "maxwidth: int, optional\n", "orientation: str, optional\n", "timeout: int, optional\n", "quality: str, optional\n", "asset_contract_address: str\n", "orderid: int\n", "cgeo: str, optional\n", "cringelevel: str\n", "search_query: str\n", "vsid: str\n", "forbiddenwordlimit: int, optional\n", "wrapper: str\n", "filler: str\n", "strength: str\n", "chain_id: str, optional\n", "number_results: int, optional\n", "telephone: str\n", "port: str\n", "service: str\n", "channel_id: str\n", "iso_3166_2: str, optional\n", "languages: str, optional\n", "only_verified_guests: bool, optional\n", "id_modelo: str\n", "tlds: str, optional\n", "valves: str, optional\n", "valve_timing: str, optional\n", "fuel_type: str, optional\n", "cam_type: str, optional\n", "engine_type: str, optional\n", "drive_type: str, optional\n", "cylinders: str, optional\n", "horsepower_hp: str, optional\n", "transmission: str, optional\n", "raw: bool, optional\n", "methane: str, optional\n", "show_slug: str\n", "coord: str\n", "after_datum: str\n", "increment_time: str, optional\n", "plates: str\n", "filetype: str, optional\n", "twitter_account: str\n", "chapterid: int\n", "verseid: int\n", "admindivision1: str, optional\n", "admindivision2: str, optional\n", "accuracyradiuskm: int, optional\n", "plate: str\n", "upload_date: str, optional\n", "features: str, optional\n", "system: str, optional\n", "backtracks: int, optional\n", "factid: str, optional\n", "eid: int\n", "min_wingspan: int, optional\n", "max_wingspan: int, optional\n", "fov: int, optional\n", "spans: str, optional\n", "pageno: int\n", "searchquery: str\n", "seriesid: int\n", "naics: int, optional\n", "accept_all: bool, optional\n", "smtp: bool, optional\n", "cod: int\n", "min_apparent_magnitude: int, optional\n", "constellation: int, optional\n", "max_apparent_magnitude: int, optional\n", "max_absolute_magnitude: int, optional\n", "min_absolute_magnitude: int, optional\n", "millis: int\n", "music: str\n", "asn_number: int\n", "invite: str\n", "orderby: str, optional\n", "yyyy_mm_dd: str\n", "rounded: bool, optional\n", "font_size: int, optional\n", "background: str, optional\n", "domains: str\n", "name_brand: str, optional\n", "user_name: str, optional\n", "asset_class: str\n", "ext: str\n", "max_size: int, optional\n", "delimiter: str, optional\n", "include_variations: bool, optional\n", "company_id: str\n", "winner: str\n", "randomizer: str, optional\n", "text_color: str, optional\n", "productcode: str\n", "god: str\n", "newspaperid: str\n", "subregion_id: str, optional\n", "timezone_id: str, optional\n", "region_id: str, optional\n", "shortcode: str\n", "variable: str\n", "datetime: str\n", "gov: str\n", "twttr_proxy: str, optional\n", "twttr_session: str, optional\n", "x_rapidapi_proxy_secret: str, optional\n", "source_name: str\n", "account_id: str\n", "bounds: str, optional\n", "geojson: str, optional\n", "maptype: str, optional\n", "delta_zoom: int, optional\n", "kml: str, optional\n", "marker: int\n", "radius_units: str, optional\n", "max_results: int, optional\n", "music_id: str\n", "callback_url: str\n", "estado: str\n", "ano: str\n", "champions: str\n", "x_units_pressure: str, optional\n", "x_aqi_index: str, optional\n", "x_units_temperature: str, optional\n", "x_units_distance: str, optional\n", "x_user_timezone: str, optional\n", "x_user_lang: str, optional\n", "woeid: int\n", "cards: str, optional\n", "character_name: str\n", "match_email_domain: bool, optional\n", "lens_id: str\n", "mmsi: str\n", "referencecurrencyuuid: str, optional\n", "utc_offset: int, optional\n", "namespace: str\n", "sport_id: int\n", "page_num: int\n", "league_ids: int, optional\n", "subtablename: str, optional\n", "themes: str, optional\n", "theme_search_type: str, optional\n", "number_of_moves: int, optional\n", "opening_variation: str, optional\n", "opening_family: str, optional\n", "zone_type: str, optional\n", "active: str, optional\n", "point: str, optional\n", "zone: str, optional\n", "urgency: str, optional\n", "certainty: str, optional\n", "severity: str, optional\n", "creds_datetime: str\n", "creds_uuid: str\n", "creds_checksum: str\n", "socket_id: str\n", "catalog_item_id: str\n", "mode: str, optional\n", "movie_director: str, optional\n", "binnum: int\n", "domainname: str\n", "doors: str, optional\n", "nitrous: str, optional\n", "productid: str\n", "pricerange: str\n", "food: str, optional\n", "restaurantname: str, optional\n", "property: str\n", "apikey: str\n", "performance_rating: str, optional\n", "fund_type: str, optional\n", "fund_family: str, optional\n", "risk_rating: str, optional\n", "strategy: str, optional\n", "stars: int\n", "tcins: int\n", "bedrooms: int, optional\n", "maxguestcapacity: int, optional\n", "app_key: str\n", "domain_key: str\n", "tweetid: str\n", "inn: str\n", "tracking_number: str\n", "n_player: str\n", "next_max_id: str, optional\n", "task_id: str\n", "search_radius: str, optional\n", "max_bedroom: int, optional\n", "furnished_type: str, optional\n", "min_bedroom: int, optional\n", "has_garden: bool, optional\n", "added_to_site: str, optional\n", "property_type: str, optional\n", "has_house_share: bool, optional\n", "has_include_let_agreed: bool, optional\n", "has_parking: bool, optional\n", "do_not_show_house_share: bool, optional\n", "check_word: str\n", "r: int\n", "titleno: int\n", "all: str, optional\n", "g: int\n", "input_weight: str, optional\n", "seasons_id: int\n", "unique_tournament_id: int\n", "lid: int\n", "cut: int, optional\n", "sstart: str, optional\n", "send: str, optional\n", "intensitylevel: int\n", "xid: str\n", "filmid: str, optional\n", "orderdirection: str, optional\n", "eventidentifier: str\n", "tz: str, optional\n", "street: str\n", "apifeedtype: str, optional\n", "authorid: str, optional\n", "newspaper_id: str\n", "verse: str\n", "performanceid: str\n", "header1: str, optional\n", "query2: str, optional\n", "datestring: str\n", "reason: str\n", "id_restaurant: int\n", "uppercase_mode: bool, optional\n", "text_mode: str, optional\n", "chapter: int, optional\n", "geography: str\n", "highlightid: str\n", "profile_url: str\n", "dimensionvalueid: str, optional\n", "sortid: int, optional\n", "verified_purchases_only: bool, optional\n", "star_rating: str, optional\n", "images_or_videos_only: bool, optional\n", "bookname: str\n", "versestart: int\n", "verseend: int\n", "flnr: str\n", "aptfrom: str, optional\n", "aptto: str, optional\n", "pincode: int\n", "pollutants: str, optional\n", "profile_name: str\n", "extended: str\n", "offsettoken: str, optional\n", "collectionid: str\n", "globalid: str\n", "area_uid: str\n", "litres: str\n", "locationname: str\n", "fhir_id: str\n", "group_id: str\n", "maxage: int, optional\n", "simpleshistory: bool, optional\n", "registrations: str, optional\n", "simples: bool, optional\n", "topics: str\n", "webcamid: str\n", "domain1: str\n", "domain2: str\n", "maxcursor: int, optional\n", "mincursor: int, optional\n", "codigo_postal: str\n", "rs: str\n", "lonlat: str\n", "icon: str, optional\n", "centericon: str, optional\n", "routeresultid: str, optional\n", "routeicon: str, optional\n", "scaler: str, optional\n", "place: str\n", "within: str, optional\n", "prefix: str\n", "tv: int\n", "videoduration: str, optional\n", "videodefinition: str, optional\n", "videocaption: str, optional\n", "videolicense: str, optional\n", "eventtype: str, optional\n", "videotype: str, optional\n", "validate: bool, optional\n", "captchasid: str, optional\n", "vkhash: str, optional\n", "audio_lang: str, optional\n", "speaker: str, optional\n", "publish_date: str, optional\n", "subtitle_lang: str, optional\n", "max_duration: int, optional\n", "to_publish_date: str, optional\n", "from_publish_date: str, optional\n", "min_duration: int, optional\n", "record_date: str, optional\n", "to_record_date: str, optional\n", "from_record_date: str, optional\n", "source_language: str\n", "target_language: str\n", "x_rapidapi_key: str, optional\n", "x_rapidapi_host: str, optional\n", "setlabel: bool, optional\n", "forecolor: str, optional\n", "labeltext: str, optional\n", "labelalign: str, optional\n", "backcolor: str, optional\n", "store: str, optional\n", "sizeschema: str, optional\n", "media_id: str\n", "mediaid: int\n", "series_ticker: str, optional\n", "max_city_mpg: int, optional\n", "min_comb_mpg: int, optional\n", "max_hwy_mpg: int, optional\n", "drive: str, optional\n", "max_comb_mpg: int, optional\n", "min_hwy_mpg: int, optional\n", "min_city_mpg: int, optional\n", "rolls: int, optional\n", "linecount: int\n", "statecode: str\n", "transactionid: str\n", "temperature: str, optional\n", "min_kw: str, optional\n", "max_kw: str, optional\n", "available: str, optional\n", "tbm: str, optional\n", "search_engine: str, optional\n", "order_by_date: str, optional\n", "class_to: int, optional\n", "distance_to: str, optional\n", "distance_from: str, optional\n", "course: str, optional\n", "class_from: int, optional\n", "optifineversion: str\n", "answer: str, optional\n", "speech: str, optional\n", "dialcode: str\n", "date1: str\n", "date2: str\n", "cointicker: str\n", "asciimode: bool, optional\n", "currencycode: str, optional\n", "nameprefixdefaultlangresults: bool, optional\n", "nameprefix: str, optional\n", "menstrual_date: str\n", "company_prefix: str\n", "lot: str, optional\n", "qty: str, optional\n", "firmware_hash: str\n", "trainno: int\n", "startday: str, optional\n", "lang_to: str\n", "lang_from: str, optional\n", "breedtype: str\n", "tostationcode: str\n", "fromstationcode: str\n", "states: str, optional\n", "room_type: str\n", "nightly_rate: float\n", "checkin_date: str\n", "checkout_date: str\n", "guest_id: str\n", "promo_code: str, optional\n", "trackingnumber: str\n", "back: str, optional\n", "pulls: str, optional\n", "exclude_sources: str, optional\n", "from_sources: str, optional\n", "has_image: bool, optional\n", "weapon_name: str\n", "expression: str\n", "screener_id: str\n", "filter1: str, optional\n", "filter2: str, optional\n", "default_country: str, optional\n", "visa_type: str\n", "specs: str\n", "pjpage: int\n", "pjlocation: str\n", "pjkeyword: str\n", "field: str\n", "countryid: str, optional\n", "tok_proxy: str, optional\n", "maxlinks: int, optional\n", "includequery: bool, optional\n", "sm_uid: str\n", "skill: str, optional\n", "token_id: int, optional\n", "order_direction: str, optional\n", "minimportance: int, optional\n", "countries: str, optional\n", "finish_instruction: str, optional\n", "voice_instructions: str, optional\n", "filename: str, optional\n", "weighting: str, optional\n", "routetype: str, optional\n", "scheme: str, optional\n", "book: str\n", "media_type: str\n", "keywords_in_image: bool\n", "includenames: bool, optional\n", "ks: int\n", "startyear: int, optional\n", "titletype: str, optional\n", "endyear: int, optional\n", "on: str\n", "locality: str\n", "dp: str, optional\n", "explorers: bool, optional\n", "community: bool, optional\n", "contracts: bool, optional\n", "news: bool, optional\n", "flags: bool, optional\n", "exchanges: bool, optional\n", "links: bool, optional\n", "channel_name: str\n", "sources: str\n", "category_name: str\n", "required_props: str, optional\n", "h3ndex: int\n", "act: str\n", "pretty: bool, optional\n", "company_name: str\n", "airportcode: str\n", "carriercode: str, optional\n", "pull_type: int, optional\n", "months: str\n", "text1: str\n", "text3: str\n", "text2: str\n", "o3: str\n", "no2: str\n", "pm: str\n", "hashtag_id: str\n", "prefix_match: bool, optional\n", "bmi: int\n", "authorization: str, optional\n", "accept_charset: str, optional\n", "state_hasc: str\n", "geonameid: str\n", "timezone_offset: int\n", "playlist_url: str\n", "product: str\n", "time_period_1: int, optional\n", "time_period_2: int, optional\n", "time_period_3: int, optional\n", "stateisocode: str\n", "watch_id: str\n", "propertycode: int\n", "connection_string: str\n", "book_id: str\n", "searchstring: str\n", "fill_text: str, optional\n", "productgrouptypeid: int, optional\n", "parentproductgroupid: int, optional\n", "txt: str\n", "fix: int, optional\n", "agentname: str, optional\n", "photo: bool, optional\n", "tsym: str\n", "fsyms: str\n", "regioncode: str, optional\n", "dur: str, optional\n", "media: str, optional\n", "advantage: bool, optional\n", "modifier: int, optional\n", "statename: str\n", "zuid: str\n", "extended_publisher_details: bool, optional\n", "sec_user_id: str\n", "quizid: str\n", "datastring: str\n", "ein: int\n", "schemaname: str\n", "iniya: int, optional\n", "questionid: str\n", "peopleid: str\n", "time_published: str, optional\n", "codepoint: str\n", "domain_name: str\n", "ne_lat: int\n", "sw_lng: int\n", "sw_lat: int\n", "ne_lng: int\n", "swift_code: str\n", "colisid: str\n", "leagueid: str\n", "modelid: int\n", "wikiurl: str\n", "withname: bool, optional\n", "straintype: str\n", "iso: str\n", "club: str\n", "singleav: str\n", "msg: str, optional\n", "glanguage: str\n", "gcountry: str\n", "gkeyword: str\n", "slow_period: int, optional\n", "fast_period: int, optional\n", "joburl: str\n", "with_rt_ratings: bool\n", "query_term: str\n", "minimum_rating: int\n", "safesearch: bool, optional\n", "fifacode: str\n", "getmusic: str\n", "w: int, optional\n", "gstin: str\n", "variables: str\n", "subreddit: str\n", "accept: str\n", "authority: str, optional\n", "search_keyword: str\n", "have: str\n", "want: str\n", "private: bool, optional\n", "stock_country: str\n", "index: int\n", "uniquetournamentid: int\n", "minapps: bool, optional\n", "accumulation: str, optional\n", "dietary_preferences: str\n", "body_composition_goal: str\n", "block_id: str\n", "collection_slug: str, optional\n", "auction_type: str, optional\n", "collection_editor: str, optional\n", "occurred_after: int, optional\n", "account_address: str, optional\n", "occurred_before: int, optional\n", "only_opensea: bool, optional\n", "event_type: str, optional\n", "skinname: str, optional\n", "increment: int\n", "include_start: bool, optional\n", "business_type: str\n", "business_brand: str\n", "avis: str\n", "bookmakers: str, optional\n", "fixedrate: str, optional\n", "heightincentrimetres: int\n", "weightinkilograms: int\n", "comp_id: int\n", "municipality: str, optional\n", "level_of_government: str, optional\n", "rentalid: str\n", "athleteid: int\n", "imageversion: int\n", "pk: str\n", "phonecustomid: int\n", "listid: str, optional\n", "startfrom: int, optional\n", "department: str, optional\n", "debug: int, optional\n", "namefilter: str, optional\n", "tradingsymbol: str\n", "idmessage: str, optional\n", "phonenumber: str\n", "typemovie: str\n", "addressline1: str\n", "addressline2: str\n", "clabel: str\n", "idv: str\n", "secuid: str\n", "pagenum: int, optional\n", "top_right: str\n", "bottom_left: str\n", "max_alerts: int, optional\n", "max_jams: int, optional\n", "country1: str\n", "country2: str\n", "state2: str\n", "city2: str\n", "city1: str\n", "state1: str\n", "x_api_key: str\n", "training_uuid: str\n", "from_tzname: str, optional\n", "to_tzname: str, optional\n", "hash_tag: str\n", "pbpage: int\n", "pbkeyword: str\n", "pblocation: str\n", "langpair: str\n", "onlyprivate: str, optional\n", "mt: str, optional\n", "de: str, optional\n", "chainid: int\n", "endblock: int, optional\n", "startblock: int, optional\n", "itemid: int\n", "spanms: str\n", "intervalms: str\n", "regionid: int\n", "lasttime: int, optional\n", "storeid: str\n", "juz_number: int\n", "id_modelo_ano: str\n", "meta: bool, optional\n", "breadcrumbs: bool, optional\n", "x_traceid: str, optional\n", "orderful_api_key: str\n", "ref: str\n", "updatedlt: str\n", "updatedgte: str\n", "deaths: int\n", "assists: int\n", "kills: int\n", "watchid: str\n", "characterid: str\n", "dna: str\n", "selector: str\n", "stock: str\n", "releasedate: str, optional\n", "resource: str, optional\n", "rp: str, optional\n", "blueessence: str, optional\n", "attribute: str\n", "hq: bool, optional\n", "contractaddress: str\n", "tokenid: str\n", "history: bool, optional\n", "tempunit: str, optional\n", "alt: int, optional\n", "windunit: str, optional\n", "beds_min: int, optional\n", "baths_max: int, optional\n", "year_built_max: int, optional\n", "year_built_min: int, optional\n", "list_date_min: str, optional\n", "open_house_max: str, optional\n", "has_tour: bool, optional\n", "list_price_min: int, optional\n", "hoa_fee_optional_max: int, optional\n", "list_date_max: str, optional\n", "list_price_max: int, optional\n", "baths_min: int, optional\n", "open_house_min: str, optional\n", "beds_max: int, optional\n", "lot_sqft_min: int, optional\n", "lot_sqft_max: int, optional\n", "hoa_fee_optional_min: int, optional\n", "sqft_max: int, optional\n", "sqft_min: int, optional\n", "google_place_id: str\n", "geo_text: str, optional\n", "geo_ref: bool, optional\n", "geo_type: str, optional\n", "stationid: str\n", "access: str, optional\n", "cards_accepted: str, optional\n", "owner_type: str, optional\n", "federal_agency_id: str, optional\n", "ev_network: str, optional\n", "ev_charging_level: str, optional\n", "world: str\n", "series_slug: str\n", "livestreamid: str\n", "ridet: str\n", "engine_icontains: str\n", "zoneid: str\n", "imgc: str, optional\n", "hitsperpage: int, optional\n", "email_string: str\n", "exchangecode: str\n", "fastav: str\n", "pricemax: int, optional\n", "pricemin: int, optional\n", "issale: bool, optional\n", "isfreeship: bool, optional\n", "isfavorite: bool, optional\n", "phrase: str\n", "stageid: int\n", "rating_change: str, optional\n", "cityname: str\n", "list_id: str\n", "degree: str\n", "skills: str\n", "university: str\n", "nombre: str\n", "orgid: str\n", "tournid: str\n", "roundid: int, optional\n", "nft: str, optional\n", "fileid: str\n", "mileage_year: int, optional\n", "mileage_start: int, optional\n", "maximum: int, optional\n", "qintitle: str, optional\n", "h3index: int\n", "playlist: str\n", "sign1: str\n", "sign2: str\n", "exam: str\n", "sfchronicle: str, optional\n", "measure: str\n", "grayscale: bool, optional\n", "rotate: int, optional\n", "blur: int, optional\n", "resize: str, optional\n", "currentnewsid: int, optional\n", "momentum: str\n", "growth: str\n", "getcountrycodes: str\n", "pair_interval: int, optional\n", "time_zone: str\n", "imdb_id: int, optional\n", "languageid: str, optional\n", "take: int, optional\n", "shortperiod: int, optional\n", "mediumperiod: int, optional\n", "longperiod: int, optional\n", "emailsimple: str\n", "latin_name: str\n", "results: str\n", "nation: str\n", "movie_name: str, optional\n", "comment_id: str\n", "backgroundimage: str, optional\n", "brandowner: str, optional\n", "pagenumber: str, optional\n", "district_id: str, optional\n", "vendorid: str\n", "monitoraddressid: str, optional\n", "requestedsymbols: str\n", "artist_name: str\n", "lyric_title: str\n", "sm_lid: str, optional\n", "parent_id: str, optional\n", "page_order: str, optional\n", "page_sort: str, optional\n", "gamepk: str\n", "subject: str\n", "top_n_keywords: int, optional\n", "max_articles: int, optional\n", "last_n_hours: int, optional\n", "phoneid: int\n", "param: str, optional\n", "stop_address: str\n", "start_address: str\n", "coordinates: str, optional\n", "common_name: str\n", "documentid: str, optional\n", "episodeno: int\n", "h3index1: str\n", "h3index2: str\n", "routingnumber: str\n", "paymenttype: str, optional\n", "access_param: str, optional\n", "ev_connector_type_param: str, optional\n", "ev_network_param: str, optional\n", "owner_type_param: str, optional\n", "substring: str\n", "authoriza: str, optional\n", "todos: str\n", "time_start: str\n", "time_finish: str\n", "ftext: str\n", "stext: str\n", "nftaddress: str\n", "nftid: str\n", "targeturl: str\n", "islandscape: str, optional\n", "proxycountry: str, optional\n", "isfullyloaded: str, optional\n", "clickcount: int, optional\n", "fullpage: str, optional\n", "clickselector: str, optional\n", "hastouch: str, optional\n", "clickdelay: int, optional\n", "clickbutton: str, optional\n", "devicescalefactor: int, optional\n", "ismobile: str, optional\n", "pagewidth: int, optional\n", "pageheight: int, optional\n", "removables: str, optional\n", "uniqueid: str\n", "cep: str\n", "whitelist_ip: str, optional\n", "feed: str\n", "checksmtp: bool, optional\n", "suggestdomain: bool, optional\n", "bathrooms: int, optional\n", "accommodates: str, optional\n", "sourceid: str\n", "coinname: str\n", "musicid: str\n", "callerid: str\n", "report_mask: int, optional\n", "report_url: str, optional\n", "equipment: str\n", "matchmode: str, optional\n", "properties: str, optional\n", "withpictures: int, optional\n", "api: str\n", "anonymity: str\n", "subtypes: str, optional\n", "portfoliotype: str, optional\n", "txid: str\n", "trimid: int\n", "active_mer: str, optional\n", "latitude_range_end: str, optional\n", "active_smop: str, optional\n", "active_vmer: str, optional\n", "longitude_range_end: str, optional\n", "active_bkg: str, optional\n", "hotelid_ppn: str, optional\n", "property_type_ids: str, optional\n", "cityid_ppn: str, optional\n", "hotel_address: str, optional\n", "active_agd: str, optional\n", "changes_since: str, optional\n", "player_input: str, optional\n", "verse_num2: int, optional\n", "verse_num1: int, optional\n", "dest: str\n", "src: str, optional\n", "commentid: int\n", "min_id: str, optional\n", "tenantid: str\n", "mkt: str, optional\n", "cp4: str\n", "cp3: str\n", "profile: str\n", "overview: str, optional\n", "roundtrip: bool, optional\n", "geometries: str, optional\n", "steps: bool, optional\n", "tzname: str\n", "pets: str, optional\n", "amenities: str, optional\n", "laundry: str, optional\n", "propertytypes: str, optional\n", "activetypes: str, optional\n", "deactivateddays: str, optional\n", "activateddays: str, optional\n", "distanceinmiles: str, optional\n", "fi: int\n", "customer_a_id: str\n", "screening_a_id: str\n", "fooid: int\n", "sunsign: str\n", "time_range: str, optional\n", "queryid: str, optional\n", "nftnews: str, optional\n", "district: str\n", "command: str\n", "person_id: str\n", "exclude_tags: str, optional\n", "include_tags: str, optional\n", "by_state: str, optional\n", "by_name: str, optional\n", "by_type: str, optional\n", "by_tag: str, optional\n", "place_unique_id: str\n", "ingr: str\n", "nutrition_type: str, optional\n", "set1: set\n", "set2: set\n", "translation: str\n", "verse_end: str\n", "verse_start: str\n", "edition_currency_id: int\n", "total_volume_min: int, optional\n", "chg_24h_min: int, optional\n", "total_volume_max: int, optional\n", "chg_7d_max: int, optional\n", "chg_7d_min: int, optional\n", "market_cap_max: int, optional\n", "market_cap_min: int, optional\n", "chg_24h_max: int, optional\n", "volume_24h_max: int, optional\n", "volume_24h_min: int, optional\n", "max_tweets: int, optional\n", "posted: str\n", "subcategory: str\n", "commonname: str\n", "speciename: str\n", "consistency: str\n", "cropcycle: str\n", "fruittype: str\n", "appid: str\n", "radius_km: int, optional\n", "disaster_type_number: int\n", "activity_type_number: int\n", "calories_lt: int\n", "calories_gt: int\n", "idea: str\n", "user_agent: str\n", "fulldata: str, optional\n", "starttime: str, optional\n", "endtime: str, optional\n", "recipeid: str\n", "second_date: str, optional\n", "first_date: str, optional\n", "ai: str\n", "data_id: str\n", "next_page_token: str, optional\n", "topic_id: str, optional\n", "daysfrom: int\n", "datefrom: str\n", "inpast: bool, optional\n", "first: bool, optional\n", "last: bool, optional\n", "prep_time_in_minutes_gt: int\n", "prep_time_in_minutes_lt: int\n", "dateid: str\n", "tolanguage: str\n", "fromlanguage: str\n", "teamids: str\n", "projectid: str\n", "timezoneids: str, optional\n", "minpopulation: int, optional\n", "maxpopulation: int, optional\n", "includedeleted: str, optional\n", "taxid: str\n" ] } ], "source": [ "param_analysis = analyze_tool_parameters()\n", "print(\"\\nParameter Analysis:\")\n", "print(\"\\nParameter Types:\")\n", "for param, types in param_analysis['types'].items():\n", " print(f\"{param}: {types[0][0] if types else 'unknown'}\")" ] }, { "cell_type": "code", "execution_count": 144, "id": "c523a30f-c788-488d-b383-2488c10a2534", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Argument Type Patterns:\n", "is_id_string: 5686\n", "symbol_string: 3233\n", "is_id_numeric: 3034\n", "page_numeric: 2494\n", "q_string: 2383\n", "num_numeric: 2285\n", "limit_numeric: 2186\n", "date_string: 2074\n", "country_string: 2026\n", "text_string: 1889\n" ] } ], "source": [ "def analyze_tool_arguments():\n", " arg_patterns = defaultdict(int)\n", " for args_list in df['tool_arguments']:\n", " for args in args_list:\n", " for arg_name, arg_value in args.items():\n", " if isinstance(arg_value, (int, float)):\n", " arg_patterns[f\"{arg_name}_numeric\"] += 1\n", " elif isinstance(arg_value, bool):\n", " arg_patterns[f\"{arg_name}_boolean\"] += 1\n", " elif isinstance(arg_value, str):\n", " arg_patterns[f\"{arg_name}_string\"] += 1\n", " return arg_patterns\n", "\n", "arg_analysis = analyze_tool_arguments()\n", "print(\"\\nArgument Type Patterns:\")\n", "for pattern, count in sorted(arg_analysis.items(), key=lambda x: x[1], reverse=True)[:10]:\n", " print(f\"{pattern}: {count}\")" ] }, { "cell_type": "code", "execution_count": 145, "id": "5daa6c10-296f-447d-b1a1-d345add9a188", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Sample Queries:\n", "\n", "Tool: search\n", "Query: Find articles from the last week about COVID-19 in the UK. Also, suggest keywords for 'healthcare technology'.\n", "Arguments: {'q': 'COVID-19', 'gl': 'UK', 'tbs': 'qdr:w'}\n", "\n", "Tool: loginuser\n", "Query: Attempt login with 'frank' and 'frankpass'. Retrieve reviews for the product with 'goods_id' as '10196865'.\n", "Arguments: {'username': 'frank', 'password': 'frankpass'}\n", "\n", "Tool: calculate_standard_deviation\n", "Query: Find the standard deviation of the scores of a test: 80, 85, 90, 82, 88.\n", "Arguments: {'numbers': [80, 85, 90, 82, 88]}\n" ] } ], "source": [ "print(\"\\nSample Queries:\")\n", "for tool_name, _ in tool_usage.most_common(3):\n", " sample = df[df['used_tools'].apply(lambda x: tool_name in x)].iloc[0]\n", " print(f\"\\nTool: {tool_name}\")\n", " print(f\"Query: {sample['query']}\")\n", " print(f\"Arguments: {sample['tool_arguments'][0] if sample['tool_arguments'] else 'None'}\")" ] }, { "cell_type": "markdown", "id": "3447d93f-da35-4516-9819-22a2442d80cb", "metadata": {}, "source": [ "### Argilla-Tool-Calling\n", "\n", "- Apache 2.0\n", "- 60k examples\n", "- https://huggingface.co/datasets/argilla-warehouse/apigen-synth-trl" ] }, { "cell_type": "code", "execution_count": 33, "id": "2b020f22-2fd3-44a6-a463-4d31bc4195ad", "metadata": {}, "outputs": [], "source": [ "d = load_dataset(\"argilla-warehouse/apigen-synth-trl\")" ] }, { "cell_type": "code", "execution_count": 34, "id": "a433c577-e282-40e3-9607-11c6d5a7cd3d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'messages': [{'content': 'You are an expert in composing functions. You are given a question and a set of possible functions. \\nBased on the question, you will need to make one or more function/tool calls to achieve the purpose. \\nIf none of the functions can be used, point it out and refuse to answer. \\nIf the given question lacks the parameters required by the function, also point it out.\\n\\nThe output MUST strictly adhere to the following format, and NO other text MUST be included.\\nThe example format is as follows. Please make sure the parameter type is correct. If no function call is needed, please make the tool calls an empty list \\'[]\\'.\\n```\\n[\\n{\"name\": \"func_name1\", \"arguments\": {\"argument1\": \"value1\", \"argument2\": \"value2\"}},\\n... (more tool calls as required)\\n]\\n```',\n", " 'role': 'system'},\n", " {'content': 'You have access to the following tools:\\n[{\"type\":\"function\",\"function\":{\"name\":\"remove_dir_recursively\",\"description\":\"Recursively removes a directory and its contents, including subdirectories and files.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\",\"description\":\"The path to the directory to be removed.\"}},\"required\":[\"path\"]}}},{\"type\":\"function\",\"function\":{\"name\":\"pair_with_next_value\",\"description\":\"Pairs each element in the list with the next element, returning a new list\\\\nof tuples. If the last element is paired with a value, a None value is used\\\\nas the second element in the tuple.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"numbers\":{\"type\":\"array\",\"items\":{\"type\":\"integer\"},\"description\":\"A list of integers.\"}},\"required\":[\"numbers\"]}}},{\"type\":\"function\",\"function\":{\"name\":\"convert_list_of_objects_to_dict\",\"description\":\"Converts a list of objects into a list of dictionaries.\\\\n\\\\nEach dictionary has keys `type`, `color`, and `brand` corresponding to each object\\'s attributes.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"obj_list\":{\"type\":\"array\",\"items\":{\"type\":\"object\"},\"description\":\"A list of objects, each with `.type`, `.color`, and `.brand` attributes.\"}},\"required\":[\"obj_list\"]}}},{\"type\":\"function\",\"function\":{\"name\":\"get_cnn_dict\",\"description\":\"Creates and returns a dictionary with predefined key-value pairs for a CNN configuration.\",\"parameters\":{\"type\":\"object\",\"properties\":{}}}}]\\n\\nPlease answer the following query:\\nRemove the directory \\'/home/user/documents/old_projects\\' and all its contents, including subdirectories and files.',\n", " 'role': 'user'},\n", " {'content': '[{\"name\": \"remove_dir_recursively\", \"arguments\": {\"path\": \"/home/user/documents/old_projects\"}}]',\n", " 'role': 'assistant'}]}" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d['train'][43123]" ] }, { "cell_type": "code", "execution_count": 1, "id": "2d915991-d590-4571-9136-382e1492603e", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "63f30928122b412ba8612f4774de79aa", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Loading checkpoint shards: 0%| | 0/30 [00:00