embeddings-retrieval.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Retrieval vor AI with chroma\n",
    "\n",
    "## Understand the embedding model\n",
    "\n",
    "The embedding model - i.e. sentence transformers -  has a limited context window width. It uses 256 characters. That's the maximum context window length of the embedding model. \n",
    "\n",
    "Note: typically an embedding model will simply truncate any characters or tokens that are beyond its context window.\n",
    "\n",
    "The Sentence Transformer Embedding Model is essentially an extension of the BERT transformer architecture. \n",
    "The BERT architecture embeds each token individually in a dense vector.\n",
    "\n",
    "Sentence Transformer allows to embed entire sentences or even small documents like we have here by pooling the output of all the token embeddings to produce a single dense vector per document or in our case, per chunk. \n",
    "Sentence transformers are great as an embedding model. They're  open source, all the weights are available online, and they're really easy to run locally.\n",
    "\n",
    "In essence with the RAG loop, we're turning GPT from a model that remembers facts into a model that processes information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import\n",
    "import chromadb # chromadb is a python client for ChromaDB\n",
    "import openai\n",
    "from openai import OpenAI\n",
    "from langchain.text_splitter import RecursiveCharacterTextSplitter, SentenceTransformersTokenTextSplitter\n",
    "from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunction\n",
    "import numpy as np\n",
    "from pypdf import PdfReader\n",
    "from tqdm import tqdm # progress bar\n",
    "\n",
    "\n",
    "def word_wrap(string, n_chars=72):\n",
    "    # Wrap a string at the next space after n_chars\n",
    "    if len(string) < n_chars:\n",
    "        return string\n",
    "    else:\n",
    "        return string[:n_chars].rsplit(' ', 1)[0] + '\\n' + word_wrap(string[len(string[:n_chars].rsplit(' ', 1)[0])+1:], n_chars)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 Dear shareholders, colleagues, customers, and partners:  \n",
      "We are\n",
      "living through a period of historic economic, societal, and\n",
      "geopolitical change. The world in 2022 looks nothing like \n",
      "the world in\n",
      "2019. As I write this, inflation is at a 40 -year high, supply chains\n",
      "are stretched, and the war in Ukraine is \n",
      "ongoing. At the same time, we\n",
      "are entering a technological era with the potential to power awesome\n",
      "advancements \n",
      "across every sector of our economy and society. As the\n",
      "world’s largest software company, this places us at a historic\n",
      "\n",
      "intersection of opportunity and responsibility to the world around us.\n",
      " \n",
      "Our mission to empower every person and every organization on the\n",
      "planet to achieve more has never been more \n",
      "urgent or more necessary.\n",
      "For all the uncertainty in the world, one thing is clear: People and\n",
      "organizations in every \n",
      "industry are increasingly looking to digital\n",
      "technology to overcome today’s challenges and emerge stronger. And no\n",
      "\n",
      "company is better positioned to help them than Microsoft.  \n",
      "Every day\n",
      "this past fiscal year I have had the privilege to witness our customers\n",
      "use our platforms and tools to connect \n",
      "what technology can do with\n",
      "what the world needs  it to do.  \n",
      "Here are just a few examples:  \n",
      "•\n",
      "Ferrovial, which builds and manages some of the world’s busiest\n",
      "airports and highways, is using our cloud \n",
      "infrastructure to build\n",
      "safer roads as it prepares for a future of autonomous transportation. \n",
      "\n",
      "• Peace Parks Foundation, a nonprofit helping protect natural\n",
      "ecosystems in Southern Africa, is using Microsoft \n",
      "Dynamics 365 and\n",
      "Power BI to secure essential funding, as well as our Azure AI and IoT\n",
      "solutions to help \n",
      "rangers scale their park maintenance and wildlife\n",
      "crime prevention work.  \n",
      "• One of the world’s largest robotics\n",
      "companies, Kawasaki Heavy Industries, is using the breadth of our tools\n",
      "—\n",
      "from Azure IoT and HoloLens —to create an industrial metaverse\n",
      "solution that brings its distributed workforce \n",
      "together with its\n",
      "network of connected equipment to improve productivity and keep\n",
      "employees safe.  \n",
      "• Globo, the biggest media and TV company in Brazil,\n",
      "is using Power Platform to empower its employees to \n",
      "build their own\n",
      "solutions for everything from booking sets to setting schedules.  \n",
      "•\n",
      "And Ørsted, which produces a quarter of the world’s wind energy, is\n",
      "using the Microsoft Intelligent Data \n",
      "Platform to turn data from its\n",
      "offshore turbines into insights for predictive maintenance.  \n",
      "Amid this\n",
      "dynamic environment, we delivered record results in fiscal year 2022:\n",
      "We reported $198  billion in revenue and \n",
      "$83 billion in operating\n",
      "income. And the Microsoft Cloud surpassed $100  billion in annualized\n",
      "revenue for the first time.  \n",
      "OUR RESPONSIBILITY  \n",
      "As a corporation,\n",
      "our purpose and actions must be aligned with addressing the world’s\n",
      "problems, not creating new ones. \n",
      "At our very core, we need to deliver\n",
      "innovation that helps drive broad economic growth. We, as a company,\n",
      "will do well \n",
      "when the world around us does well.  \n",
      "That’s what I\n",
      "believe will lead to widespread human progress and ultimately improve\n",
      "the lives of everyone. There is no \n",
      "more powerful input than digital\n",
      "technology to drive the world’s economic output. This is the core\n",
      "thesis for our being as a \n",
      "company, but it’s not enough. As we drive\n",
      "global economic growth, we must also commit to creating a more\n",
      "inclusive, \n",
      "equitable, sustainable, and trusted future.  \n",
      "Support\n",
      "inclusive economic growth  \n",
      "We must ensure the growth we drive reaches\n",
      "every person, organization, community, and country. This starts with\n",
      "\n",
      "increasing access to digital skills. This year alone, more than 23 \n",
      "million people accessed digital skills training as part of \n",
      "our global\n",
      "skills initiative.\n"
     ]
    }
   ],
   "source": [
    "reader = PdfReader(\"docs/microsoft_annual_report_2022.pdf\")\n",
    "pdf_texts = [p.extract_text().strip() for p in reader.pages]\n",
    "\n",
    "# Filter the empty strings\n",
    "pdf_texts = [text for text in pdf_texts if text]\n",
    "\n",
    "print(word_wrap(pdf_texts[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "increased, due in large part to significant global datacenter\n",
      "expansions and the growth in Xbox sales and usage. Despite \n",
      "these\n",
      "increases, we remain dedicated to achieving a net -zero future. We\n",
      "recognize that progress won’t always be linear, \n",
      "and the rate at which\n",
      "we can implement emissions reductions is dependent on many factors that\n",
      "can fluctuate over time.  \n",
      "On the path to becoming water positive, we\n",
      "invested in 21 water replenishment projects that are expected to\n",
      "generate \n",
      "over 1.3  million cubic meters of volumetric benefits in nine\n",
      "water basins around the world. Progress toward our zero waste\n",
      "\n",
      "commitment included diverting more than 15,200 metric tons of solid\n",
      "waste otherwise headed to landfills and incinerators, \n",
      "as well as\n",
      "launching new Circular Centers to increase reuse and reduce e -waste at\n",
      "our datacenters.  \n",
      "We contracted to protect over 17,000 acres of land\n",
      "(50% more than the land we use to operate), thus achieving our\n",
      "\n",
      "Total chunks: 347\n"
     ]
    }
   ],
   "source": [
    "character_splitter = RecursiveCharacterTextSplitter(\n",
    "    separators=[\"\\n\\n\", \"\\n\", \". \", \" \", \"\"],\n",
    "    chunk_size=1000,\n",
    "    chunk_overlap=0\n",
    ")\n",
    "character_split_texts = character_splitter.split_text('\\n\\n'.join(pdf_texts))\n",
    "\n",
    "print(word_wrap(character_split_texts[10]))\n",
    "print(f\"\\nTotal chunks: {len(character_split_texts)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/dev/miniconda3/envs/llm/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n",
      "  return self.fget.__get__(instance, owner)()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "increased, due in large part to significant global datacenter\n",
      "expansions and the growth in xbox sales and usage. despite these\n",
      "increases, we remain dedicated to achieving a net - zero future. we\n",
      "recognize that progress won ’ t always be linear, and the rate at which\n",
      "we can implement emissions reductions is dependent on many factors that\n",
      "can fluctuate over time. on the path to becoming water positive, we\n",
      "invested in 21 water replenishment projects that are expected to\n",
      "generate over 1. 3 million cubic meters of volumetric benefits in nine\n",
      "water basins around the world. progress toward our zero waste\n",
      "commitment included diverting more than 15, 200 metric tons of solid\n",
      "waste otherwise headed to landfills and incinerators, as well as\n",
      "launching new circular centers to increase reuse and reduce e - waste\n",
      "at our datacenters. we contracted to protect over 17, 000 acres of land\n",
      "( 50 % more than the land we use to operate ), thus achieving our\n",
      "\n",
      "Total chunks: 349\n"
     ]
    }
   ],
   "source": [
    "# Chunk the texts into smaller pieces - i.e. 256 tokens\n",
    "token_splitter = SentenceTransformersTokenTextSplitter(chunk_overlap=0, tokens_per_chunk=256)\n",
    "\n",
    "token_split_texts = []\n",
    "for text in character_split_texts:\n",
    "    token_split_texts += token_splitter.split_text(text)\n",
    "\n",
    "print(word_wrap(token_split_texts[10]))\n",
    "print(f\"\\nTotal chunks: {len(token_split_texts)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
      "To disable this warning, you can either:\n",
      "\t- Avoid using `tokenizers` before the fork if possible\n",
      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "# Load the embeddings into ChromaDB\n",
    "embedding_function = SentenceTransformerEmbeddingFunction()\n",
    "print(embedding_function([token_split_texts[10]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chroma_client = chromadb.Client()\n",
    "chroma_client.list_collections()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# only run if collection already exists\n",
    "chroma_client.delete_collection(\"microsoft_annual_report_2022\")\n",
    "chroma_client.list_collections()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "349"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a collection\n",
    "chroma_collection = chroma_client.create_collection(\"microsoft_annual_report_2022\", embedding_function=embedding_function)\n",
    "# create ids for each chunk\n",
    "ids = [str(i) for i in range(len(token_split_texts))]\n",
    "# add the chunks to the collection\n",
    "chroma_collection.add(ids=ids, documents=token_split_texts)\n",
    "chroma_collection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "revenue, classified by significant product and service offerings, was\n",
      "as follows : ( in millions ) year ended june 30, 2022 2021 2020 server\n",
      "products and cloud services $ 67, 321 $ 52, 589 $ 41, 379 office\n",
      "products and cloud services 44, 862 39, 872 35, 316 windows 24, 761 22,\n",
      "488 21, 510 gaming 16, 230 15, 370 11, 575 linkedin 13, 816 10, 289 8,\n",
      "077 search and news advertising 11, 591 9, 267 8, 524 enterprise\n",
      "services 7, 407 6, 943 6, 409 devices 6, 991 6, 791 6, 457 other 5, 291\n",
      "4, 479 3, 768 total $ 198, 270 $ 168, 088 $ 143, 015 we have recast\n",
      "certain previously reported amounts in the table above to conform to\n",
      "the way we internally manage and monitor our business.\n",
      "\n",
      "\n",
      "74 note 13 — unearned revenue unearned revenue by segment was as\n",
      "follows : ( in millions ) june 30, 2022 2021 productivity and business\n",
      "processes $ 24, 558 $ 22, 120 intelligent cloud 19, 371 17, 710 more\n",
      "personal computing 4, 479 4, 311 total $ 48, 408 $ 44, 141 changes in\n",
      "unearned revenue were as follows : ( in millions ) year ended june 30,\n",
      "2022 balance, beginning of period $ 44, 141 deferral of revenue 110,\n",
      "455 recognition of unearned revenue ( 106, 188 ) balance, end of period\n",
      "$ 48, 408 revenue allocated to remaining performance obligations, which\n",
      "includes unearned revenue and amounts that will be invoiced and\n",
      "recognized as revenue in future periods, was $ 193 billion as of june\n",
      "30, 2022, of which $ 189 billion is related to the commercial portion\n",
      "of revenue. we expect to recognize approximately 45 % of this revenue\n",
      "over the next 12\n",
      "\n",
      "\n",
      "that are not sold separately. • we tested the mathematical accuracy of\n",
      "management ’ s calculations of revenue and the associated timing of\n",
      "revenue recognized in the financial statements.\n",
      "\n",
      "\n",
      "82 in addition, certain costs incurred at a corporate level that are\n",
      "identifiable and that benefit our segments are allocated to them. these\n",
      "allocated costs include legal, including settlements and fines,\n",
      "information technology, human resources, finance, excise taxes, field\n",
      "selling, shared facilities services, and customer service and support.\n",
      "each allocation is measured differently based on the specific facts and\n",
      "circumstances of the costs being allocated. segment revenue and\n",
      "operating income were as follows during the periods presented : ( in\n",
      "millions ) year ended june 30, 2022 2021 2020 revenue productivity and\n",
      "business processes $ 63, 364 $ 53, 915 $ 46, 398 intelligent cloud 75,\n",
      "251 60, 080 48, 366 more personal computing 59, 655 54, 093 48, 251\n",
      "total $ 198, 270 $ 168, 088 $ 143, 015 operating income\n",
      "\n",
      "\n",
      "47 financial statements and supplementary data income statements ( in\n",
      "millions, except per share amounts ) year ended june 30, 2022 2021 2020\n",
      "revenue : product $ 72, 732 $ 71, 074 $ 68, 041 service and other 125,\n",
      "538 97, 014 74, 974 total revenue 198, 270 168, 088 143, 015 cost of\n",
      "revenue : product 19, 064 18, 219 16, 017 service and other 43, 586 34,\n",
      "013 30, 061 total cost of revenue 62, 650 52, 232 46, 078 gross margin\n",
      "135, 620 115, 856 96, 937 research and development 24, 512 20, 716 19,\n",
      "269 sales and marketing 21, 825 20, 117 19, 598 general and\n",
      "administrative 5, 900 5, 107 5, 111 operating income 83, 383 69, 916\n",
      "52, 959 other income, net 333 1, 186 77 income before income taxes 83,\n",
      "716 71, 102 53, 036 provision for income taxes 10, 978 9, 831 8, 755\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# query the collection\n",
    "query = \"What was the total revenue?\"\n",
    "\n",
    "results = chroma_collection.query(query_texts=[query], n_results=5)\n",
    "retrieved_documents = results['documents'][0]\n",
    "\n",
    "for document in retrieved_documents:\n",
    "    print(word_wrap(document))\n",
    "    print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.10.0\n"
     ]
    }
   ],
   "source": [
    "print(openai.VERSION)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "_ = load_dotenv(find_dotenv('.env')) # read local .env file\n",
    "openai.api_key  = os.environ['OPENAI_API_KEY']\n",
    "openai_client = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rag(query, retrieved_documents, model=\"gpt-3.5-turbo\"):\n",
    "    information = \"\\n\\n\".join(retrieved_documents)\n",
    "\n",
    "    messages = [\n",
    "        {\n",
    "            \"role\": \"system\",\n",
    "            \"content\": \"You are a helpful expert financial research assistant. Your users are asking questions about information contained in an annual report.\"\n",
    "            \"You will be shown the user's question, and the relevant information from the annual report. Answer the user's question using only this information.\"\n",
    "        },\n",
    "        {\"role\": \"user\", \"content\": f\"Question: {query}. \\n Information: {information}\"}\n",
    "    ]\n",
    "    # create the completion request to OpenAI\n",
    "    response = openai_client.chat.completions.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "    )\n",
    "    # get the response from the first choice\n",
    "    content = response.choices[0].message.content\n",
    "    return content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
      "To disable this warning, you can either:\n",
      "\t- Avoid using `tokenizers` before the fork if possible\n",
      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The total revenue for the year ended June 30, 2022, as stated in the\n",
      "income statement, is $198,270 million.\n"
     ]
    }
   ],
   "source": [
    "output = rag(query=query, retrieved_documents=retrieved_documents)\n",
    "\n",
    "print(word_wrap(output))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pitfalls\n",
    "\n",
    "you need  `umap-learn`\n",
    "\n",
    "In the example embeddings have 348 dimensions. In order to visualize for humans let's project them down into two dimensions, and this can be useful for reasoning about the structure of embedding space. [UMAP](https://umap-learn.readthedocs.io/en/latest/) is Uniform Manifold Approximation. This is \n",
    "a similar technique to something like PCA or t-SNE, except UMAP explicitly  tries to preserve the structure of the data in terms of the distances between points as much as it can, unlike for example, PCA, which tries to find the predominant directions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# helper functions, see section above how to handle embeddings\n",
    "\n",
    "import chromadb\n",
    "\n",
    "from langchain.text_splitter import RecursiveCharacterTextSplitter, SentenceTransformersTokenTextSplitter\n",
    "import numpy as np\n",
    "from pypdf import PdfReader\n",
    "from tqdm import tqdm\n",
    "\n",
    "\n",
    "def read_pdf(filename):\n",
    "    reader = PdfReader(filename)\n",
    "    \n",
    "    pdf_texts = [p.extract_text().strip() for p in reader.pages]\n",
    "\n",
    "    # Filter the empty strings\n",
    "    pdf_texts = [text for text in pdf_texts if text]\n",
    "    return pdf_texts\n",
    "\n",
    "\n",
    "def chunk_texts(texts):\n",
    "    character_splitter = RecursiveCharacterTextSplitter(\n",
    "        separators=[\"\\n\\n\", \"\\n\", \". \", \" \", \"\"],\n",
    "        chunk_size=1000,\n",
    "        chunk_overlap=0\n",
    "    )\n",
    "    character_split_texts = character_splitter.split_text('\\n\\n'.join(texts))\n",
    "\n",
    "    token_splitter = SentenceTransformersTokenTextSplitter(chunk_overlap=0, tokens_per_chunk=256)\n",
    "\n",
    "    token_split_texts = []\n",
    "    for text in character_split_texts:\n",
    "        token_split_texts += token_splitter.split_text(text)\n",
    "\n",
    "    return token_split_texts\n",
    "\n",
    "\n",
    "def load_chroma(filename, collection_name, embedding_function):\n",
    "    texts = read_pdf(filename)\n",
    "    chunks = chunk_texts(texts)\n",
    "\n",
    "    chroma_cliet = chromadb.Client()\n",
    "    chroma_collection = chroma_cliet.create_collection(name=collection_name, embedding_function=embedding_function)\n",
    "\n",
    "    ids = [str(i) for i in range(len(chunks))]\n",
    "\n",
    "    chroma_collection.add(ids=ids, documents=chunks)\n",
    "\n",
    "    return chroma_collection\n",
    "\n",
    "def word_wrap(string, n_chars=72):\n",
    "    # Wrap a string at the next space after n_chars\n",
    "    if len(string) < n_chars:\n",
    "        return string\n",
    "    else:\n",
    "        return string[:n_chars].rsplit(' ', 1)[0] + '\\n' + word_wrap(string[len(string[:n_chars].rsplit(' ', 1)[0])+1:], n_chars)\n",
    "\n",
    "   \n",
    "def project_embeddings(embeddings, umap_transform):\n",
    "    umap_embeddings = np.empty((len(embeddings),2))\n",
    "    for i, embedding in enumerate(tqdm(embeddings)): \n",
    "        umap_embeddings[i] = umap_transform.transform([embedding])\n",
    "    return umap_embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/dev/miniconda3/envs/llm/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n",
      "  return self.fget.__get__(instance, owner)()\n",
      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
      "To disable this warning, you can either:\n",
      "\t- Avoid using `tokenizers` before the fork if possible\n",
      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "349"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunction\n",
    "\n",
    "embedding_function = SentenceTransformerEmbeddingFunction()\n",
    "\n",
    "chroma_collection = load_chroma(filename='docs/microsoft_annual_report_2022.pdf', collection_name='microsoft_annual_report_2022', embedding_function=embedding_function)\n",
    "chroma_collection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/dev/miniconda3/envs/llm/lib/python3.10/site-packages/umap/umap_.py:1943: UserWarning: n_jobs value -1 overridden to 1 by setting random_state. Use no seed for parallelism.\n",
      "  warn(f\"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.\")\n",
      "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n"
     ]
    }
   ],
   "source": [
    "import umap as mp\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "\n",
    "embeddings = chroma_collection.get(include=['embeddings'])['embeddings']\n",
    "umap_transform = mp.UMAP(random_state=0, transform_seed=0).fit(embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# project the embeddings into 2D  \n",
    "def project_embeddings(embeddings, umap_transform) -> np.ndarray:\n",
    "    # create an empty array to store the projected embeddings\n",
    "    umap_embeddings = np.empty((len(embeddings),2))\n",
    "    # loop through each embedding and project it into 2D\n",
    "    for i, embedding in enumerate(tqdm(embeddings)): \n",
    "        umap_embeddings[i] = umap_transform.transform([embedding])\n",
    "    return umap_embeddings  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 349/349 [01:41<00:00,  3.44it/s]\n"
     ]
    }
   ],
   "source": [
    "projected_dataset_embeddings = project_embeddings(embeddings, umap_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
      "To disable this warning, you can either:\n",
      "\t- Avoid using `tokenizers` before the fork if possible\n",
      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-4.14157487154007, 7.448055040836334, 5.867360353469849, 11.475993871688843)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10)\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title('Projected Embeddings')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Relevancy and Distraction\n",
    "\n",
    "Evaluating the quality and performance of a retrieval system is about relevancy and distraction.\n",
    "\n",
    "The embedding model that we use to embed queries and embed our data does not have any knowledge of the task or query we're trying to answer at the time we actually retrieve the information. So the reason that a retrieval system may not perform the way that we expect is because we're asking it to perform a specific task using only a general representation. And that makes things more complicated.\n",
    "\n",
    "Query: \"What has been the investment in research and development?\"\n",
    "Here there are also distractors in this result. A distractor is a result that is not actually relevant to the query. The problem is that information is passed to the large language model which is not relevant to the query. In effect the model tends to get distracted by this information and output suboptimal results. Distractors are very difficult to diagnose and debug, both for the user, but also for developers and engineers building \n",
    "these types of systems. \n",
    "\n",
    "An exterme example is the query about Michael Jordan: the query is totally irrelevant to any of the data that we have in our data set. \n",
    "\n",
    "So it's very important to make your retrieval system robust and return relevant results and no distracting results to the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "revenue, classified by significant product and service offerings, was\n",
      "as follows : ( in millions ) year ended june 30, 2022 2021 2020 server\n",
      "products and cloud services $ 67, 321 $ 52, 589 $ 41, 379 office\n",
      "products and cloud services 44, 862 39, 872 35, 316 windows 24, 761 22,\n",
      "488 21, 510 gaming 16, 230 15, 370 11, 575 linkedin 13, 816 10, 289 8,\n",
      "077 search and news advertising 11, 591 9, 267 8, 524 enterprise\n",
      "services 7, 407 6, 943 6, 409 devices 6, 991 6, 791 6, 457 other 5, 291\n",
      "4, 479 3, 768 total $ 198, 270 $ 168, 088 $ 143, 015 we have recast\n",
      "certain previously reported amounts in the table above to conform to\n",
      "the way we internally manage and monitor our business.\n",
      "\n",
      "74 note 13 — unearned revenue unearned revenue by segment was as\n",
      "follows : ( in millions ) june 30, 2022 2021 productivity and business\n",
      "processes $ 24, 558 $ 22, 120 intelligent cloud 19, 371 17, 710 more\n",
      "personal computing 4, 479 4, 311 total $ 48, 408 $ 44, 141 changes in\n",
      "unearned revenue were as follows : ( in millions ) year ended june 30,\n",
      "2022 balance, beginning of period $ 44, 141 deferral of revenue 110,\n",
      "455 recognition of unearned revenue ( 106, 188 ) balance, end of period\n",
      "$ 48, 408 revenue allocated to remaining performance obligations, which\n",
      "includes unearned revenue and amounts that will be invoiced and\n",
      "recognized as revenue in future periods, was $ 193 billion as of june\n",
      "30, 2022, of which $ 189 billion is related to the commercial portion\n",
      "of revenue. we expect to recognize approximately 45 % of this revenue\n",
      "over the next 12\n",
      "\n",
      "82 in addition, certain costs incurred at a corporate level that are\n",
      "identifiable and that benefit our segments are allocated to them. these\n",
      "allocated costs include legal, including settlements and fines,\n",
      "information technology, human resources, finance, excise taxes, field\n",
      "selling, shared facilities services, and customer service and support.\n",
      "each allocation is measured differently based on the specific facts and\n",
      "circumstances of the costs being allocated. segment revenue and\n",
      "operating income were as follows during the periods presented : ( in\n",
      "millions ) year ended june 30, 2022 2021 2020 revenue productivity and\n",
      "business processes $ 63, 364 $ 53, 915 $ 46, 398 intelligent cloud 75,\n",
      "251 60, 080 48, 366 more personal computing 59, 655 54, 093 48, 251\n",
      "total $ 198, 270 $ 168, 088 $ 143, 015 operating income\n",
      "\n",
      "software assurance ( “ sa ” ) and cloud services. unearned revenue is\n",
      "generally invoiced annually at the beginning of each contract period\n",
      "for multi - year agreements and recognized ratably over the coverage\n",
      "period. unearned revenue also includes payments for other offerings for\n",
      "which we have been paid in advance and earn the revenue when we\n",
      "transfer control of the product or service. refer to note 1 –\n",
      "accounting policies of the notes to financial statements in our fiscal\n",
      "year 2022 form 10 - k for further discussion. the following table\n",
      "outlines the expected future recognition of unearned revenue as of june\n",
      "30, 2022 : ( in millions ) three months ending september 30, 2022 $ 17,\n",
      "691 december 31, 2022 13, 923 march 31, 2023 9, 491 june 30, 2023 4,\n",
      "433 thereafter 2, 870 total $ 48, 408 if our customers choose to\n",
      "license cloud - based versions of our products and services rather than\n",
      "licensing transaction -\n",
      "\n",
      "productivity and business processes $ 29, 687 $ 24, 351 $ 18, 724\n",
      "intelligent cloud 32, 721 26, 126 18, 324 more personal computing 20,\n",
      "975 19, 439 15, 911 total $ 83, 383 $ 69, 916 $ 52, 959 no sales to an\n",
      "individual customer or country other than the united states accounted\n",
      "for more than 10 % of revenue for fiscal years 2022, 2021, or 2020.\n",
      "revenue, classified by the major geographic areas in which our\n",
      "customers were located, was as follows : ( in millions ) year ended\n",
      "june 30, 2022 2021 2020 united states ( a ) $ 100, 218 $ 83, 953 $ 73,\n",
      "160 other countries 98, 052 84, 135 69, 855 total $ 198, 270 $ 168, 088\n",
      "$ 143, 015 ( a ) includes billings to oems and certain multinational\n",
      "organizations because of the nature of these businesses and the\n",
      "impracticability of determining the geographic source of the revenue.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "query = \"What is the total revenue?\"\n",
    "\n",
    "results = chroma_collection.query(query_texts=query, n_results=5, include=['documents', 'embeddings'])\n",
    "\n",
    "retrieved_documents = results['documents'][0]\n",
    "\n",
    "for document in results['documents'][0]:\n",
    "    print(word_wrap(document))\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  3.74it/s]\n",
      "100%|██████████| 5/5 [00:01<00:00,  3.53it/s]\n"
     ]
    }
   ],
   "source": [
    "query_embedding = embedding_function([query])[0]\n",
    "retrieved_embeddings = results['embeddings'][0]\n",
    "\n",
    "projected_query_embedding = project_embeddings([query_embedding], umap_transform)\n",
    "projected_retrieved_embeddings = project_embeddings(retrieved_embeddings, umap_transform)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-4.14157487154007, 7.448055040836334, 5.867360353469849, 11.475993871688843)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the projected query and retrieved documents in the embedding space\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10, color='gray')\n",
    "plt.scatter(projected_query_embedding[:, 0], projected_query_embedding[:, 1], s=150, marker='X', color='r')\n",
    "plt.scatter(projected_retrieved_embeddings[:, 0], projected_retrieved_embeddings[:, 1], s=100, facecolors='none', edgecolors='g')\n",
    "\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title(f'{query}')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "culture of trust can help navigate the challenges the world faces\n",
      "today. organizations of all sizes have digitized business - critical\n",
      "functions, redefining what they can expect from their business\n",
      "applications. customers are looking to unlock value while simplifying\n",
      "security and management. from infrastructure and data, to business\n",
      "applications and collaboration, we provide unique, differentiated value\n",
      "to customers. we are building a distributed computing fabric – across\n",
      "cloud and the edge – to help every organization build, run, and manage\n",
      "mission - critical workloads anywhere. in the next phase of innovation,\n",
      "artificial intelligence ( “ ai ” ) capabilities are rapidly advancing,\n",
      "fueled by data and knowledge of the world. we are enabling metaverse\n",
      "experiences at all layers of our stack, so customers can more\n",
      "effectively model, automate, simulate, and predict changes within their\n",
      "industrial\n",
      "\n",
      "every organization turn its data into predictive and analytical power.\n",
      "with our new microsoft intelligent data\n",
      "\n",
      "4 our commitment to responsibly develop and use technologies like ai is\n",
      "core to who we are. we put our commitment into practice, not only\n",
      "within microsoft but by empowering our customers and partners to do the\n",
      "same and by advocating for policy change. we released our responsible\n",
      "ai standard, which outlines 17 goals aligned to our six ai principles\n",
      "and includes tools and practices to support them. and we share our open\n",
      "- source tools, including the new responsible ai dashboard, to help\n",
      "developers building ai technologies identify and mitigate issues before\n",
      "deployment. finally, we provide clear reporting and information on how\n",
      "we run our business and how we work with customers and partners,\n",
      "delivering the transparency that is central to trust. our annual impact\n",
      "summary shares more about our progress and learnings across these four\n",
      "commitments, and our reports hub provides detailed reports on our\n",
      "environmental data,\n",
      "\n",
      "5 platform, we are helping customers focus on creating value instead of\n",
      "integrating a fragmented data estate. cosmos db is the go - to database\n",
      "powering the world ’ s most demanding, mission - critical workloads, at\n",
      "any scale. with azure synapse, we ’ re removing traditional barriers\n",
      "between enterprise data warehousing and big data analytics so anyone\n",
      "can collaborate, build, and manage analytics solutions. and we ’ re\n",
      "creating an entirely new market category with microsoft purview, as we\n",
      "help organizations govern, protect, and manage their data estate across\n",
      "platforms and clouds. when it comes to ai, we ’ re seeing a paradigm\n",
      "shift as the world ’ s large ai models become platforms themselves. and\n",
      "we are helping organizations apply the world ’ s most advanced coding\n",
      "and language models to a variety of use cases, such as writing\n",
      "assistance, code generation, and reasoning over data with our new azure\n",
      "openai service. digital and app innovation\n",
      "\n",
      "• technology and research, focuses on our ai innovations and other\n",
      "forward - looking research and development efforts spanning\n",
      "infrastructure, services, and applications. • linkedin, focuses on our\n",
      "services that transform the way customers hire, market, sell, and\n",
      "learn.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "query = \"What is the strategy around artificial intelligence (AI) ?\"\n",
    "results = chroma_collection.query(query_texts=query, n_results=5, include=['documents', 'embeddings'])\n",
    "\n",
    "retrieved_documents = results['documents'][0]\n",
    "\n",
    "for document in results['documents'][0]:\n",
    "    print(word_wrap(document))\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  3.78it/s]\n",
      "100%|██████████| 5/5 [00:01<00:00,  3.51it/s]\n"
     ]
    }
   ],
   "source": [
    "query_embedding = embedding_function([query])[0]\n",
    "retrieved_embeddings = results['embeddings'][0]\n",
    "\n",
    "projected_query_embedding = project_embeddings([query_embedding], umap_transform)\n",
    "projected_retrieved_embeddings = project_embeddings(retrieved_embeddings, umap_transform)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-4.14157487154007, 7.448055040836334, 5.867360353469849, 11.475993871688843)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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m8b5rrrlG8e+8+uqryMnJQbNmzdzXdN26dZLX87LLLkNcXFyQRxKalStXomfPnhg6dGjQnw3mmMLhfd6zsrIAwOMayVm+fDn69euH/v37e9wLF110kSozmzZv3owTJ0743EPnnnsuunbtGta+BMrDfvvtN5SUlGDcuHF+xzEsX74cBQUFSE1N9fjdESNGAGgsS/zZu3cv2rdvL/laUVEREhMTMX78eABAy5YtcdVVV+HTTz9FVVWV3+91cX230jz06aefxrfffosVK1agd+/eij4TCbquM1BQUICdO3di79692LBhA84880y0bNkSQGMwsHXrVhw5cgQbNmxAbGwshgwZ4vMdKSkpPtsSEhLw+++/u/++99578be//Q2jR4/GsmXL8Pnnn2PLli3Izs72eF+4bDYb1q1bh4suughPP/00cnJy0K5dO9x55504duxYWN8d6Dhra2tRX1+PF198EXFxcR7/XXLJJQCAgwcPyn5/Xl4elixZ4i50HQ4H+vXrhw8++EDxPjZv3hytWrXy2Hbq1CkMHz4cixYtwgMPPIB169bhiy++cAcmSs7//v37ATQGLN7HNn/+fPdx1dbWAoDHoBwXqW133HEHjh07hvfeew8A8NJLL8HhcODyyy/3uz8//PADzjvvPOzZswezZ8/Gp59+ii1btuDll1+WPCapkdq1tbWS21NTUz2OJVjNmzdHs2bNPLYlJCTg+PHjHr8tdT46duyo6Deee+45TJkyBeeccw4WLlyIzZs3Y8uWLbj44oslr6eWI9V//vlnn8GHSgR7TOHwvpcTEhIAKL8Xtm3b5nMfJCUlQQjh9x5XIph7KNh9CZSHHTp0CA0NDQGv3/79+7Fs2TKf3+3bty8A//kc0Hieve8RAKiurkZpaSkuvfRSCCFw+PBhHD58GFdeeSWA/80wCMT13UrTzbfffovU1NSQB8OqRZfZBC4FBQV47rnnsHHjRmzcuNFdaAFwF/ylpaXYuHEjzj77bHegEKx//vOfmDBhAp588kmP7QcPHsRpp50W8v5L6dKlC4qKigA0zjv96KOPMHXqVPzxxx949dVXVf2tptq0aQO73Y7rr78et912m+R7unXr5vc7Lr/8clx++eU4ceIENm/ejJkzZ+Kaa65B165dMWjQoID74D03HGgcBV5RUYG5c+di4sSJ7u3V1dUBv8+lbdu2ABrXp3C1KEhxZTau4KGpffv2+WxLT0/HiBEj8PLLL2PEiBFYunQppk2bBrvd7nd/lixZgl9//RWLFi3y2B+5KZdS5yUlJQU//fSTz/a9e/cC+N8xuzKWEydOeLwvnEw/JSUFX3zxhc92qXMk5Z///CfOP/98vPLKKx7b5QJeqeOPlHbt2sHpdAb9uWCPSS9t27ZFYmKibMHkSjehCnQPNW0dUHtfkpOTYbfbA16/tm3bIisrCzNmzJB83RVQ+/t8XV2dz/a33noLQggsWLAACxYs8Hn9nXfewRNPPBEwf3B9t9Lj79SpE3r27KnovZGkazCQl5cHu92OBQsW4JtvvsHTTz/tfq1169bo378/3nnnHezatSuoJkxvNpvNHX27fPLJJ9izZw/S09Pd24KJ0JXo2bMnHnnkESxcuDDgQhRNfzsxMTHo32revDkKCgqwdetWZGVlIT4+PqR9du1Lfn4+TjvtNKxevRpbt27FoEGDQjo/roLA+/y/9tprkr8r9f0XXXQRYmNjUVNTI9kN4dKrVy907NgRH330Ee6991739h9++AFlZWWSmcRdd92F4cOHY+LEibDb7bjppptCOiYhBN54442An3W58MILMXPmTJSXl3usUzFv3jzYbDZ3l5gr8922bRsuuugi9/uWLl2q+Le8FRQU4KOPPsLSpUs9mqzff/99RZ+Xup+2bduGTZs2oXPnzoq+Q+17zWXEiBF49NFHsX79ep+uGX/UOCY1ebduuowcORJPPvkkUlJSAgb3oTjnnHOQkJCA+fPnY+zYse7tmzdvxu7duz2CAbX3JTExEfn5+fjXv/6FGTNmyBamI0eOxIoVK9CjRw+0adMm6N/p3bs3ampqPLY1NDTgnXfeQY8ePfDmm2/6fGb58uV49tlnsXLlSowcOdLv93/33XeIiYlBr169FO2PdwCqF12DgVatWiEnJwdLlixBTEyMT79ufn4+XnjhBQDhrS8wcuRIzJ07F71790ZWVha++uorzJo1y6c5qkePHkhMTMR7772HPn36oGXLlkhNTQ0Yabps27YNt99+O6666ipkZGQgPj4e69evx7Zt2/Dggw/6/WxmZiYA4KmnnsKIESNgt9uDLtRnz56NIUOG4LzzzsOUKVPQtWtXHDt2DNXV1Vi2bJnffuhHH30UTqcTF154IRwOBw4fPozZs2cjLi4O+fn5AEI7P71790aPHj3w4IMPQgiB5ORkLFu2DMXFxbLnYPbs2Zg4cSLi4uLQq1cvdO3aFdOnT8fDDz+M7777DhdffDHatGmD/fv344svvkCLFi0wbdo0xMTEYNq0afjzn/+MK6+8EpMnT8bhw4cxbdo0dOrUCTExvr1iw4YNwxlnnIENGzbguuuuk+1L9P5MfHw8/vSnP+GBBx7A8ePH8corr+DQoUMBP+tyzz33YN68ebj00ksxffp0dOnSBZ988gnmzJmDKVOmuGsKHTt2xNChQzFz5ky0adMGXbp0wbp167Bo0SLFv+VtwoQJeP755zFhwgTMmDEDGRkZWLFiheSqn1JGjhyJxx9/HI899hjy8/OxY8cOTJ8+Hd26dQu4hoBLuPeanLvvvhvz58/H5ZdfjgcffBADBw7E77//jpKSEowcOVI2H1HjmNSUmZmJDz/8EPPnz0f37t3RrFkzZGZm4u6778bChQuRl5eHe+65B1lZWTh16hR++OEHrFmzBvfdd5/iOfFSkpOTce+997rT25gxY+B0OiXvoUjsy3PPPYchQ4bgnHPOwYMPPoj09HTs378fS5cuxWuvvYakpCRMnz4dxcXFGDx4MO6880706tULx48fx65du7BixQq8+uqrfrsazj//fEyfPt1jvY+VK1di7969eOqpp3D++ef7fKZfv3546aWXUFRUFDAY2Lx5M/r37684ULnwwguxe/fuoFpLI0K3oYv/9cADDwgA4qyzzvJ5bcmSJQKAiI+PD2qep/co2kOHDonCwkLRvn170bx5czFkyBDx6aefSs6b/eCDD0Tv3r1FXFxc0OsM7N+/X0yaNEn07t1btGjRQrRs2VJkZWWJ559/XtTX1/s9DydOnBA33nijaNeunbDZbJLrDAQ6TiEaRwxPnjzZPf+2Xbt2YvDgweKJJ57w+/vLly8XI0aMEGlpae71ES655BLx6aefKjo/cqO9hRDi22+/FcOGDRNJSUmiTZs24qqrrnLPEPE+vw899JBITU0VMTExPqPolyxZIgoKCkSrVq1EQkKC6NKli7jyyivF2rVrPb7j9ddfF+np6SI+Pl707NlTvPXWW+Lyyy8XAwYMkNy/qVOnCgBi8+bNfs9RU8uWLRPZ2dmiWbNmIi0tTdx///3u+fNN99m1zoCU3bt3i2uuuUakpKSIuLg40atXLzFr1iyPdQaEaJxKdeWVV4rk5GTRunVrcd1114kvv/xSdp0Bb1Kj851Op7jiiitEy5YtRVJSkrjiiitEWVmZotkEJ06cEH/5y19EWlqaaNasmcjJyRFLlizxWMtBiP+NXp81a5bk98ilpXBmEwjReL/fdddd4vTTTxdxcXGiffv24tJLL3VPIxbCd6S/0mOS+qwc7/e5Ru57j76XmjGya9cuMXz4cJGUlOSzzsAvv/wiHnnkEdGrVy8RHx/vnk58zz33iH379smem2DWGXjiiSeEw+EQ8fHxIisrSyxfvlxkZ2f7zKxQui/B5GHffvutuOqqq0RKSoqIj48Xp59+upg0aZLHOgM///yzuPPOO0W3bt1EXFycSE5OFmeeeaZ4+OGHfdY48FZdXS1sNpvHrJvRo0eL+Ph4v7MYxo8fL2JjY93HJXVMx44dE82bNxfPPvus331oKj8/3yeN6cEmhBDahB1E+jh8+DB69uyJ0aNH4/XXX/d5/ayzzoLNZsOWLVt02Dsi4/v+++/Ru3dvPPbYY/jrX/+q9+6EbdSoUaivr8fKlStV/d6ioiLcdddd+PHHH0PqwtCTrt0ERGrbt28fZsyYgYKCAqSkpGD37t14/vnncezYMdx1113u9x09ehT//ve/sXz5cnz11Ve6rQdOZDQVFRX44IMPMHjwYLRq1Qo7duzA008/jVatWqGwsFDv3VPFzJkzMWDAAGzZssU9rTpc9fX1eOqpp/DQQw+ZLhAAGAxQlElISMCuXbtw6623oq6uDs2bN8e5556LV1991T31CADKy8vdAcNjjz2G0aNH67fTRAbSokULfPnllygqKsLhw4fRunVrnH/++ZgxY4bklEMz6tevH95++23FM2iU+PHHH3HdddfhvvvuU+07tcRuAiIiIovTddEhIiIi0h+DASIiIotjMEBERGRxDAaIiIgsjsEAERGRxTEYICIisjgGA0RERBbHYICIiMjiGAwQERFZHIMBIiIii2MwQEREZHEMBoiIiCyOwQAREZHFMRggIiKyOAYDREREFsdggIiIyOIYDBAREVkcgwEiIiKLYzBARERkcQwGiIiILI7BABERkcUxGCAiIrI4BgNEREQWx2CAiIjI4hgMEBERWRyDASIiIotjMEBERGRxDAaIiIgsjsEAERGRxTEYICIisjgGA0RERBbHYICIiMjiGAwQERFZHIMBIiIii2MwQEREZHEMBoiIiCyOwQAREZHFMRggIiKyOAYDREREFsdggIiIyOIYDBAREVkcgwEiIiKLYzBARERkcQwGiIiILI7BABERkcUxGCAiIrI4BgNEREQWx2CAiIjI4hgMEBERWRyDASIiIotjMEBERGRxDAaIiIgsjsEAERGRxTEYICIisjgGA0RERBbHYICIiMjiGAwQERFZHIMBIiIii2MwQEREZHEMBoiIiCyOwQAREZHFMRggIiKyOAYDREREFsdggIiIyOIYDBAREVkcgwEiIiKLYzBARERkcQwGiIiILI7BABERkcUxGCAiIrI4BgNEREQWx2CAiIjI4hgMEBERWRyDASIiIotjMEBERGRxDAaIiIgsLlbvHSBjcDqdqK2tRUpKChwOh967Q0REGmIwYDFShX5xcTHKysrc7xk8eDCGDRum1y4SEZHGGAxEMe+CX6rQ79Onj8c2ACgrK0OfPn3YQkBEZBEMBqKUd8GfmZmJ7du3e7ynrKwMsbHSSaC2tpbBABGRRTAYiCKuloCGhgaf2r53IBBISkqKmrtGREQGxmAgSni3BCiVkZGB+vp6j8/m5uayVYCIyEIYDEQBp9OpKBDw7ipwFfoOhwN9+vThbAIiIouyCSGE3jtBoXM6ndi6dSvKy8v9vi83NxdDhw7lFEIiIvLBYMDEAnUNjBo1Cna7XbWC3+l0oqqqCkBj9wKDCSKi6MBgwKScTieKiopkX3e1BKhFKvDgegRERNGBYwZMqra2VnJ7Tk4OBgwYoGqtXW5MAtcjICKKDnw2gUnJTf1TOxAA5AOPQK8REZE5MBgwKYfDgcGDB3tsi9SUQH9rDnA9AiIi8+OYAZPTanaA1JgBtcclEBGRPhgMkGKcTUBm4i9Q5hRbIk8MBkyEGRiRMv6exMmndBL54mwCk2AGRqSM1OwX18wX17+lXmOATVbGAYQmIJe5OZ1OnfYoMKfTiYqKCkPvI0UnuRkutbW1fl8jsjK2DJiAvwzMiLUZtmKQnuRmuHBWDJE8tgyYQCiZm17M2IpB5ubdCuVv2q2WU3KJzIQtAybgcDhknzhoNGZrxSBzk2uFGjZsmOyTOP29RmRVDAZMoLi42CMQyMzMNOz8fjO1YpB5SM2k8TdQ0NUKIFfQ+3uNyIoYDBicVIa3fft2DBw40JCZmasZtuk+G7UVg8xBrvbPVigi9TAYMChXTaiurk7ydSNneGyGJbWUl5fL1v7ZCkWkHgYDBiS19K83o2d4bIalcPm7D2pra5Gdnc1WKCKVMBgwGLnHBTfFDI+iXaD7wBUMsxWKSB0MBgxGrh80Ly8PycnJzPDIElzPwJDiHQyzFYoofAwGDEau+Z8PBiKrWLRokcfsmaZGjRqFnJwcjfeIKPpx0SGDkVoUJSMjw+NvLvVLZqQk3foLBHJzcxkIEEUIn1poUE6nEyUlJaiurnZvGzx4MI4dO+aRWXKpXzIDJUtUO51OFBUVSX4+Ly8PBQUFEd1HIitjy4CBNQ0EgMYpVd61JqMv9ctWDFK6RLW/hwV5t44Rkbo4ZsCg/A2g8mbUNQf4wCIClC9RLTdeJisry2PVQc4cIFIfgwGdOZ1Od8Ef6iBBI645EGip2Ej8HgsJY1K6OFBlZaXPe7KysjBmzBgA5gsumSbJTBgM6Mg7cystLXVncBkZGSgtLQ34HU1rTUai5VKx4RYScpl20+0AmLGHSMkS1XLrCpx99tmyr0cyuAyX2QIXIgYDOpHL/JpmcN4ZaGpqKvbu3ev+u2mtyWi0Wio23EJCLtP2t/odM/bg9enTB7GxjdmNq/+/oqLCHVwFCh7N9BwCswUuRACDAd34GyzlyuCkVlczS9OjGg8sUnKs4RQScpl2SkqK39XvmLEHxzuwqq6u9ghqMzMzMXDgQMnPuoJHMz2HwEyBC5ELgwGd+MvEmr7mvbqamVZbC2epWKXNrOEUEnKZ9p49exR91izXQQ2hBqFSAVfTQACAe4aMv+DRTE/DNFPgQuTCYEAnDocDmZmZPlMFjZrBhSqU4CWYZtZwCgm5zDktLQ3l5eUhfTYahdP/7a8FrKnt27ejsLDQb/BolucQmClwIXJhMKADqQWFHA4HLrroIt0zDCN0QwTbzBpqISGXaefk5KC2tla2q8BKGXu4/d/BBE2uJxH6+16ztIyFkiaNcO+RdTEY0JjcwDQjLMpjlBHQoTSzhlpIyGXa3tsB884mUFrISL0v3P5vqYCrbdu2OHjwoM97o621JZg0aZR7j6yLwYCGAj2WVc9+6HBqgGrXaLRuZpXLtKXGa5iN0kJG7n0NDQ2S3xtMwS0VcHk/g8BKrS3eonn2wf5f9mP3kd2oP1WP9i3ao0ebHrDZbHrvFklgMKChQKsK6lkzCrUGGKkajVn6h41MaSEj9z7v52C4hFJwewdWY8eOxcCBA3l9EX2zD4QQWFOzBnO+nIPlO5fjlDjlfq1/x/649axbcW3WtWge11zHvSRvDAYMQu9HFCtpmvduAYh0jcYs/cNGpbSQkXufVCCg5iOEeX0bRdPsg99P/o7rF1+PhZULkdUhC3MumYNzHeciNiYWNYdq8Gb5m/jz8j/j6bKnsfLalUhPTseR40ewdMdS7D22FzG2GHRu3RmX9bqMwYLGGAxoyN+qgnl5eRrvjadATfNSLQDt27eX/C6z1miijdJCJphCp7Ky0m8wwEFwwYuW2Qf1p+oxbsE4rK1Zi2fOfgbjMsehc+fO7tf7tu+Ly3pdhh0Hd+CyDy/DeW+fhwu7XYgl/1mC307+htbNWkMIgSMnjuC0Zqfhhv434C+D/4LUpFQdj8o6+AhjjUkNIMzNzcXQoUN12iNPUpm53KNlR40ahWXLlvlsLywsNF1GFgwlyxcb5fi905tcWvN+X1ZWFrZt2yb5nXLXl4PgwmPE9OOP9/6+/MXLuHPlnbgG1yAd6QAa04BUd9+S/yzB2PljEW+Px1/P+ytuyrkJnZI6AQC+P/Q9XvvqNbxZ/iYSYhOw6tpVyOyQqdtxWgWDAY25Hkx09OhRtGrVSvfuASUqKiqwZMkSn+2jR4/GgQMHFBU20ULp8sVGKghDnU3w3nvv+TxGG2i87tnZ2T6flQoYoz0wjBSjBwbeA0AHDRqE2ytvR9zhOIzDONnPDR48GKnZqRj81mB0atkJO2p34Ls7v0O3Nt183rvvl30Y8d4I7P9lPz6/8XN0bt1Z4htJLewm0JBUgWHEG92bv+bm7Oxsywz0kxsjERMTY+jR4Er75r3fl5+fLxkMSKUHucGxVVVVqi9BHe2MGFg2vS5ffPGFz3iSDzZ9gCpUYSIm+v2esrIybPxhI1KTUrFx4kb0eqkXXv/qdcwcOtPnvR1bdsSqa1dhwGsD8NjGx/DW5W+pekzkicGARsw8fShQn6ZVBoLJDbT77LPPZN9v5vOidV+2EQtBrUUqn5Dr/lMSePl7aJfLT/gJzWKaoeuprn7fV4c6bHRuxFuXvYUOLTvgwu4Xonxfuez+dGjZAbedfRtmfDoDzw5/Fm0S2wRx1BQMBgMaMfv0oWCm+kVr7S7Y0d1mHA3uTel1lxsc63pCYSBmDpbVFIl8QirIAqAo8Aq0NorLH/gDcYhD7uBcv+//Gl+jZWxLXN3vagBAy/iW2P/Lfr+B4I05N2JayTR88O8PcOvZtwbcFwoNgwGNRMP0ISUtANFcu5OqKcsx42hwOUque6BWhEABolmDZbUDX7XzCbkgy5vc+hNbt25V9DvN0Ay/nfoNPXr2cAePDQ0NPgOM61CHzHaZ7mmDB349gASR4DcQ7NCyA7q16YbvDn2naF8oNAwGNBIt04f8sULtrmlNWSqzA4AhQ4agbdu2cDqdUXPcSsi1IigJEM0YLEci8FU7n1D6oCjXe+WuWSDd0R0NaMC//v0v/N+l/+exnHXT72mT0gYJiQkAGgcIrvtuHe48405AYjX22tpadOjUAYeOH4INNhyvP654fyh4DAY05MosXYOtlDahmoVZa3fBalpT9s7s0tLSPMYQRFPLiBLerQhKA0SzBcuRDHzVXH0zmGDK9d5AXQO5ubnYt28fampq3NvaoR26oisW/rgQD4gH3EsOex/LgYoDWFWzCkIIvFn+JmJjYjGp/yQs/PdCj9/4CT9hVuUsLPlkCX49+SsAoLquGoePH8atZ9+KQY5BXNZYZQwGNFZZWem+0UpLS01dWHg3kZqxdheuQC0F0dYyEqxgAkQzLUEd6cBXrUG5ckGWEEI28JI7tpycHAwYMMD9Pu/phZP7TMajlY/imbJncH/u/ZLHclX9VZjz5RzM2TIHT376JCYPmIx+Pfrhp8E/oaysDPWox3Isx9f4Gml703D/4Ptx5PgRPP/587j7nLuxZMcSvLf9PYzqOQrvX/E+Wsa3DPscUSMGAxqKpmZ0uSZSM9Xu1OLK7CoqKiRfj7aWERcl/eXBBohmmZmiVuCrxWBbuSBLLvCSO4amgQAg/XyJE+tP4IG1D2D/r/vx0JCHkNLc87sGOQYhNSkVd626C+c6zsUzw59x72PPXj1xw6ob8O3+b/HmpW9iYv+JsMGGQUWDcGG3C/HMRc/g6eFPY1HlItzw8Q245L1LsOb6NWgW20ztU2ZJDAY0VFJSIrndSIWFkszJX1Bjptqd2qzUMqK0v9xszf9KqXFcaow5UBpMSAVZagRe3t/xeMHjaJ3QGo9seAQvb3kZ4/uNxzlp5zQ+m6CuBnMr5mLfL/sAAHld8pBgT3B/dtGeRSjZV4KPx3+MkT1H4pQ4hVs/uRXlP5Vj7YS1AIAYWwyuPONKpCal4sJ5F+KxDY/hqWFPhXUM1IjBgEacTqfkAi6AcQoLpZlToCZSs9Tu1BatBZ+3QC1c3gVUtAaI4RyXGq2EkZq5E04XiM1mw/2592NS/0l4a+tbKNpahHcr3kWDaEDb5m0x7oxxmHL2FCzbsQx/Xf9XfHfoO9w/+H7079gfL37xIq7NvBaXZlyKT3d/iic/exKrq1fjzcvexPldzwcA7D22F2989QYWVC6A3WbHrLJZ2OzcjJvPvBlXnnElEmIT/O4fyWMwoBG5G8woyxEHkzlZqQYcrGgt+JryV1g0HRMD/K+AitYAMdjjcgVKdXV1kq8rbSWMZJejGvd3uxbt8H9D/g//N+T/IITAKXEK9hi7+/V+7fshrVUaHln/CM564yykJ6fj+8Pfo2dKT2S+kolvfv4GPVN64uPxH2NAiwH4cuuXmL1zNj7Y8QGaxTbDVX2vwtDuQ/HC5hdw4LcDuG7xdbhn9T146ZKXMK6v/HLIJI/BgEbkbiS9n1boEkxtQO0acLQtUhSogDD78cql5YaGBkOPidH7vCuZrqe0wPV3v7r+H+pxqn1/22w22G12n+0TsifgmsxrsKJqBR5c+yAS7Ak4Xn8c/Tv2xwsXv4ALu12ItWvX4vWy1/EBPsD3+B6FXQrx9Pin0bpZawDAZz98hn7t+2Hx1Yvx6IZHcfWCq3H0xFHcmHNjSPtqZQwGNGL0JuRgawNq1YC1XqQonAJBjcIkGhZlkkvLdrtvhg8YY0yM3uddyUp+/vIDpTN3ampqPB4qFupxRryFa/164JNPEDtjBi7rdRnW1KxBnD0OGydtbHz9+HEc+/OfsffECaztXoXv8B2uwTVI3Z2KYwePobWjMRhITkzG0RNH0bttb8y/cj7armiLW5bfgr7t+mJQ50Hq7nOUYzCgISM3IYcSrITb9Kv17IpwCgS1BnsZueYcDKm07HRKrBwD/buPjHDe5WryeXl5SE5O9psfKJ25I/XY6XCOM2JdO2vWACNHAidPAt9+CyxejKT4JBw+frjx9ePHgTFjkLRqFUYl2nDz/TE4L+Y892ORmwaXh48fRqeWjY8+ttlseHHEi9i4ayOe3fQsFnReoP6+RzEGAxozct+p1sGKlosUhVMgqFWYRNuiTN5p2aitX0Y473IBUaAxQ8HM3KmtrfUJBgCDpS9XINDQ8L+/x4zBoKcL8ff/93d8tasMZ055vHE7gH9mCpwSDRj7fQoO/fcpx65zublyM77c8yXGdh3r/np7jB23nn0r7l51N/Ye24vUpFRND8/MGAwYjN79mloGK1oORAynQFCrMLHCwEsjtn6Fc97Vuh9DDZTUmLljmPTVNBA4dapx26lTwJo1uBQCpw9zYM6scSha85P79U96AkO/A277YAnev6Y5Ok2cCIfDgeLiYjxe9jjiEIcj/+8IikWxu6VuQvYE3LHyDqyqXoXJAybrdbSmw2DAQPTu19SaljXJcAoEtQpxo9ac1Wa01q9Qz7va96P3apV2uz3g8yuCSXuGTl/r1/sGAi6nTsG+phi31sfjkUHHMb4rMOy/zySqSwQG7ANihMB18+fDdsMNcDqd+FfZv7AZm3EmzkQCEjxa6loltEJSfBLqfpeesUHSGAwYhBH6NfWgVU0ynIxSzUzWKDVnvVugtBbseY/U/ehwOGSnX8q9P5i0Z5T05eOTTxrHCMg5dQr3bTiBkg7A5X8C3lwKjP830Kwe+D0WsAkBnDwJ8clyLDnZHfMwD+3RHhfgAvdXuFpLhBA4Xn8cibGJGhxY9GAwYBBG6NcMhpqFiVY1yXAySjUzWb1rzlZrgXIJ5rxH6n4MJcgINu3pnb4kzZjROFhwzRrfloH/im0QWDgfmDQauPYK4NECoO1vwKp0YHU6sDO3D17rvhrfbP4W3dEd4zAO8Yh3f97VWvLpD5/i5KmT6Nu+rxZHFjUYDOioaYFqpv5kMxcm4WSUhsxkg2TVFqhgRep+DDXIMH3aa9YMWLwYGDPGb0CQWA98uAC4ezMw52zgw75AfSxw8XWA3bYTl7e7HLNH/AMN1Q3YtGmT+3NNW0vmbJmDXim9kN8lX5NDixYMBjTUtPCXair0bg4EGp9yaKRMgIWJuZmtBUovkep/N1PQrzqFAYENwCBn43+vfWLDeXcm4dfTO2LDpI3olNQ4jRDdgTPOOMNnauvanWux8NuFeGb4M3zEcZAYDGgk0OpjZWVlGDVqlOR2IxW0LEzMzdKFUZAi0f9u6EF+WmjWDPjwQ6BrV+DoUdmAAAAQE4PmzVvhnVtWIPdfF+Oqf12Fj8d/7H4SYtPWkuLiYrxf9j4+xIdwwIH0I+kaHEx0YTCgASWrjwHAnj17JLdXVVVpllkEGgvAwsTcLF8YBcm7eV6NsTKGHeSnhePHgfHjAwcCQOPrR4+i3+3TsfqlpRi16Ep0nd0VE7ImoDCnEN3bdMfJhpNY+vVSzCybiRrUoBu64WpcjS83f4nsvtnWOrdhYjCgAbnatLe0tDSUl5f7bC8tLUV9fX3E++WVjAUIpjCx2oh1szBCYWTGtKHmWBnTjwEIxX9XFvTXReDjv+sQnHs7sO3dL/DK9rfx+levY86XczzeloY0jMZoZCITdjQuix1Ka2Uo6dKMaVkKgwENKKk15+bmIicnB7W1tZKtCJHuLghmLICSwsTMgwytQM/CyIxpg2NlwhRKIODy34Cg0/W3YvrixXgk7xGU/ViGn3/9GfH2eDT/oznKFvvmmcG2VoaSLs2YluUwGNCAXG26d+/ePgXqsGHDEBsbi9LSUp/viWS/fElJieR2ud/0V5gw4yQ5Zk0bgcbKREvtMGIefhhYtcr/e2Ji5AOFU6caP//ww4h/9lmc3/V8z9f3I6yur1DSpVnTshwGAxqRq01LJZqMjAzJYCBS/fJOpxPV1dWSr4XymxxkSHIi+ejdSHE6nairk17Nrq6uDosWLcL27dvd28xcO4yYSy8FXnxRegVCoDEQaNVKfixBTAxgtzd+j4Rwu75CybOiLZ9jMKAhpU2zWg/ykkvUgR6iIoeDDElOpB+9q7ZAs4CkgnYz1w4j5oILgOXLG5ckBjwL/JgYYPjwxlkG48f7diW4AoHlyxu/R0Y4XV+h5FkNroctBfEZI4vRewdI2rBhw1BYWIjRo0ejsLAQQ4cOjdhvySXevLy8kL7PFcw0xRHrBEinjaysLI+aNdBYoMo9ElkrcrOA+vfvH/CzSgcNW8rw4Y0Fut3eWMAD/wsEFi8GWrdu/P/w4Z6vuwKB4cMlv9bpdKKioiKs9BJsnrVo0SIsW7bMZ7uZ8zm2DBiYVoO8ItESYYQR62RMZnn0rlyBHhMTuA5l1tphxLkCgpEjG2v/rkCgWbPG15suTLRqVcBAQM0BfErzLO9uIZdRo0YhJycnpN82AgYDBCByC6wYKQjgIC/jUJI29C5Q5X5fbgqwixq1w6hOq8OHNxb0n3zS+MwCVyDg4goIHn64cYyATNdAJAbwBUqXTqdTMhAAALvdHtJvGgWDAXJTq/A2YkYWTVOAoo1RF0KS2y+pKcBZWVno3r27KmneEmn1ggv89v+jWTPg2Wf9foUeA/j8df/oHbyGy/LBgBELLjMzYkZmlClATGvy+vTpg9jYxuwo1IGrkSDXYhapbjCjpFUz0GOgsr/vNtpzZIJlmWBAKiM2YsFlZkbNyIwwBYhpTZ73uamvrzdUpirXYhaJbjAjpFUzSU9P95gWHekWJanWIhcj5HXhsEQwIJUR9+nTx5AFlxEprdEaNSPTe6qjUYMktYTT4hHt5yZYeqdVs/DO09PT05Gfn69JmtFrYbhIi/pgQC6zcTVJejPzxYyEYGq04WRkkWxC17tP2qhBkhrCbfGI5nMjJVA61zutmoFUnl5dXY38/HzN9kHrheG0EPXBQLDzfc18MdUWbK0t1IxMiyZ0Vx9vVVUVgMabWSvRWttTo1YfredGitJ0zmm5/hkhgIzGoC3qgwG5TCUjIwP19fVRdTGbUqOmHcpNN2zYMKSkpGDPnj1IS0sLOO9Wy2biyspK92+VlpZq1m8fjRkHoE6mHK3nxlsogXW0nQO1GCWAlArazDxIOCqDAe8LIpfZOBwOw0bg4SQqtWraSm467/1s+tvl5eWora31+9taRfl6901HY21PrUw50ufGCBm0EWqzoTDCufNmpACyadBm9kHCURcMyF0QuczGiBF4OIlKzUIv0E3nvZ+ZmZmSy8r6+221o3y5zMsImbER01o41MyUI3VujJJBG6U2GwyjnDspRguu9a5sqCGqgoFAF8QMFyXcRBXso4gDkbvppPZTbmUuf7+tZoHiL/MyY2aslJ61N6Nlyk3pkUG7rkVDQwPsdrv7nBipNquEGQo3I+XpRqhshMs0wYCSDC8aLkg4hbnajyJ2kbrpghmYGei31ShQlASCZsqMlTJC7c1ImXJTWucHck84dF0TowROVslLtRQNlQ1TBANKMzyzX5BwC3O1H0Xsj9JzmpWVpei3wy1QlGReRsmM1aJW7c2I/cJq0DI/kHvCIeAblOp5jq2Sl2otGiobhg8GgsnwzH5Bwi3M1X4UsT/+VuJqqnv37kF9b6gFk9LMS+/MWE1q1N6M0LIQKaHmB6GkwUAtZUaoUVspL9WD2Ssbhg8Ggs3wzHxBwi3Mtb6Bm57rhoYGyed7B1OTCKdgsmLmFW7tzQz9wuEKNj8INQ02NDT4fT3YGnUkWmuslJfqxcyVDcMHA6FkeGpcED2aTtUo0LS+gZuea+8nuQWz72oUTGbNvEJNa+GmF6v0CyvND0JNg3JjBVxyc3MBABUVFRENSAKpqamR3B7pvNQKoqGrzfDBgB41Pj2bTtUo0PS6gcPZd7UKJrNlXuGmNSXnXC6jYr+wp1DSoNxYgSFDhqBt27ZISUlBZWUlioqK3K9lZmZi7Nixir8v3NYap9OJqqoqydk+PXr0MNX9YkTR0tVmqGCgvLxccuU6LWt8Rmg6bVqgmS3iDLUwtmLBpFZa83fO/WVUoQTaZkuPwQglDcoFEG3btkV2drbfKbhSAYHarTWBWi1qampQXFxsysLLCPw9+8ZIj+JWwhDBgNPpxPz58/HLL78AaAwKvvrqK9x0003u92hV4zNS02m0RJxKOBwOn0WLor3PX+01IbwpCTaCCbSjPT2GEhwFCiDk8pPt27dj4MCBPt+tZlDsb4ZDU9E2TkRLcte3tLRU0yXP1aB7MCAXue7duxcff/wxzjzzTE0TqVFqqEZoodBScXGxRyCQmZmJoUOH6rhHkRWpNSGaUhrYKgm0ozU9erd0BNsKGSiACNSqEMlR/HLBptJ9IWlN00yge9VM94iuwUCgyPXrr7/G119/rWl0ZZRR6UZqoYg0uaZUqZpTtNBiTQg1A1sjpsdwuyzkWjqCbYUMtNy51DLdgPx1UGsRLrlgU0o0d8epSSrNBJpibZY8W9dgQGnkqnV0ZYRR6Xq1UOjRJ2zEgibStFgTQs3A1igtZkBjGi0pKfEo7IKtMKjd0uEvgHCNDQimCyzcbtFgVgjVqzvObONP5NJMYWGh+/HopaWlPp/zd48Y6RzoFgwEG7lqXTBoOSpdKkFYaRaFkQoarWh1fdUKbI3SYibXrRhsQa51ADp27FgMHDhQs4w/0L2Tl5eH5ORk3QohM44/8ZdmsrOz4XA4UF9fr/geMdo50C0YCCZyBaK3YPCXIKwyi8IoBY3WtLq+agW2ereYBepWDKYg1yMA1bKCIXVPNaXnSHezjj9RkmaU3iNGPAe6BQNyJ3bUqFFhLV5jJnIJIiUlxT210iqzKPQuaEgZPddxCFSBCKYgt0IA6rqnvLtU9D5OvfOaUClNM0ruEblzUFJSgmuvvTb8nQ2BbsGA3Il1FYJWKBjkEsSyZctQW1urSZNR00euStGyRcZ1nV3nJVqvu4vRmgmNzl9aDKWAGzZsGFJSUiTXNokWDocD1157raH6ps3cLahWpUXuWKurq+F0OnW5RroOIAw0ClfvRBtp/hK/Fk1G3oVRamoq9u7d6/5b6xqElQpHIzYTGp1UBSIjIwN5eXlhzyYoLy/XLADXgys/dTqdipdFjuS+mLlVRo2yyeFwID09XXLcnF4tJLqvM2CFQt9b0yjdX79eJBOFVGG0d+9ejBo1Cna7XfPMwmqFo1mbSvWmVs3MaukNMFawzW5BID8/XzIY0KuFRPdgwGqkbshRo0ZJPvEv0JPQwiFXGNntdmRnZ0fsd+VYrXA0c1Op3tSoQFgtvRkx+LFiRbApo7WQxOjyqxYld0O2b98egwcP9nn/smXLUFxcHJF9MVphZLT9iTRXRtCUmZpKzc5q6c1f8EP6GTZsGAoLCzF69GgUFhbquuoqWwY05O+GdA1m8m4hiFT0brSo1Gj7owU2lerHaunNasGPmRilhYTBgIYC3ZB2u13y9Ug1XRqtMDLa/mjBKBmBFVkpvVVWVvps0zP4MdLsBmrEYCCCvBN8oNpItC+EooTR9oeimxXSm9xiTXa7XZdpbEYayEj/YxNCCL13Ihr5S/D+omLvz+Xm5kb10/uIKLIqKiqwZMkS2de1LIydTieKiop8thcWFnrkheG0HLDVITRsGYiAQCN3/dVGrNR0aVTMTCiaGOkxu0pmcYTTcsBWh9AxGFAg2MIh3GlLVmi6NCpmJsajdXAWbcFgoOcUANpNqQzUFRrOFEgjTp80EwYDAYRSOHDkrjkxMzEerYOzaA0GXS2OoTxmV02Bxk2FUpFyBW91dXVBf5b+J2qCgUhE86EWDlabthQtrLYQjdFpHZxFezDoanEM5jG7keCvKzTYipTcI62VfJY8RUUwEKlofvXq1ZLbq6qqAt487Ps3H6O16ERbc3WwtA7OrBIMGiFvkusKDaYiFeiR1gCQlZVlmQefhcv0wUCkovlFixbB6XRKvlZaWor6+vqAAQf7/s3FSC060dpcHQytgzOjBYOhUhJEGjlvUhqs+Fs9MT09HYmJidi2bRu2bdsGwLj3UHl5uSGenGn6YCDcaF7qxnE6ndi+fbvfz0VT8yH9jxFqTcEGuNHagqB1cGakYDBU0RJEKglW/AVpUg8AMmKe/cYbb7ifFFteXo6vvvoKN910ky77YvpgQMnoVKVz+l03jtL1urVqPjRK5GgVeteagglwoyXzl6N1cGaEYDBU0T7mwZuSWRLejNTlU15e7vHIeKDxybHl5eW65POmDwb8RfOBFv6Ru3GUNgtq0XxopMiRtKG0uVouDcfGxiIjI8MwmV64tA7O9A4GQ2WWMQ9qtmTJPdNFjpG6fPbs2SO5/fPPP2cwECqpaD5QlFxVVSX5XbW1tcjOzkZmZqbfrgItmg+NFjmSNpQ2V8tl/qWlpSgtLY26VgLyzwxjHiLRkpWTk4Pa2lqf+0UIYegun7S0NJSXl/tsP3DggC7LREdFMAB4RvNOpxNbt26VfF9tbS0qKytlm5ZcN87YsWMBwCMgyMrKQvfu3TVrPpSLHPfs2cNgwI9o6ENX0lxtpJXlKDxqpFmjj3mIZDeG3P1i5C6fnJwcfPrppzh8+LDPa3q05kRNMOASaN5pQ0OD7OveN87YsWMxcOBA3RKTXOSYlpYW1vdGQ2EpJ5r60AM1V6u5spyeacJs6VHt/VUzzRp5zEOkuzGk7hejd/mcd955kl0cerTmRFUwoGTe6ZEjRyS35+XloaCgwGe7nokpJycHmzZtwsGDB93bwh1EGErGY5bM2moDqAB1VpbTM4AyW/Cm9v5GIs0atQA0QzeGluQqrnq15sRo/osRpHQWgJSMjAwV90QdxcXFHoFAjx49cOONN4b8fXIZj9x6Cq59KCoqwpIlS1BUVITi4uKQfz/S/NU8tOZ0OlFRUeH33KrF4XCgoKAAgwcP9tiuJFMJJU2oRc/fDkUk9tdIaTbSXC1ZTRmpG0NL/iquej1IOKpaBpREmBkZGbovx6mEVGKpqakJa2BJsM10ZqtpG6XmoVdtN5QmYj1HoJtl9LtLJPbXKGlWK0buxtCSv2BPrzw2qoKBQH2orkLf4XAYPkEaIeMxW2ZthAFUegdQwTYR61kYma0gjMT+GiHNuvjrDlSzq9Co3RhaCpRmOIBQBd6RJwDJRGz0BGmEjMdsmTWgf82DAZQ5fjsUDofDZ8qxGvurd5oF/LdmhdrSZZaxRnqQSktNcQChSrwLejMmRKmMUo1xDcFkPGbLrF30DPQYQJnnt4NVXFzskXlnZmZi6NChqny3nmnWX2uW699Sr/nbX7MNDNWad1pqSq88NiqDgWjhyihLSkpQXV2NqqoqVFVVhX1jBZPxmCmzNgIzBlB61+Bcv2nkp8tJFZjbt2/HwIEDI9qkroVQBjH6a+mKZFeZ2c6tFLnBg3l5ebquHMpg4L+MnMi8H7qhVR9003OSnZ0d0d+KJmYKoIxQgzPCPgS6/5V2/xjhWIIVSmuWv9ci1VVmxnMrRe78JCcn65pXMBiAsROZXn3QRj4nZmD0MSmA/oMdjbIPStK6kgLTCMcSCn+tWVJTiQO1dEWiq8ys51aKUbsSo2qdgVAYca5z0znqeiQcI54To9By/YBIM8Icd7lnhMhtV5vStO4a8NWUd6EY7Pk0UloaNmwYCgsLMXr0aBQWFmLo0KGyzdm9e/f2+12RWE/ACGlVLUZdb8HyLQNGG/0tVUvRug/aaOfEKKKttcSoNRQtBdP8H2jwYDDn04hpybs1K5x8QO2usmhLq0bsSrR8y4CREpm/pjDvqD2SjHRO1BJuLSwaW0v0qqE0vRZyM2S0WhE01Ob/7du3S7YeKDmfZklL4eYDDocD2dnZqj13wIi16XCoeX7UYPmWASON/vYXiWuZaIx0TtSgRi3MKK0lag901bqGYoSWr6bkFiqrrKz0meXgTeraKzmfRklLgYSaD0RqMLYRa9PBMvJAdcsHA4BxEplcxF1TU6P5aH6jnJNwqTXwyAitJZFqWtZqsKPctSgsLNQ1rfXp08dvGgn22gc6n0ZIS0oFmw9EuvvDDANz5Rixa6gpy3cTuBihyUZqkBIg3SSp1f7ofU7CpdbAI72bKc3StCzF1S2wevVqydddNWK90lqgNKL2tdc7LQVL6bVRI40aaVClmsxw/7JlwGB69OghuTKV0ZoQzULNWpierSVmaVr2JveY1qYCXQtX02pDQwPsdrvsMuOhNsEqSSNqX/toaXlrKtw0avSaczjMcP8yGDAYMzUhmoHa4x/0aqY0Y7rw95hWl0ArrikJJly17FALEqVpRO1rb+YmbynhpNFoWkdAihnuXwYDBhNtg/eMIBpqYWZMF0q6YvLy8mRfUxJMAL5r57u2BVOQREMa0Vs4adQMNedwVFZWym43yvExGDAgZkzqi4ZamNJ0YZQRy4FqPYEKinAXlAm2IImGNKK3UPMuM9Scg9W0e0suqDVS6weDAZ3JZdzMmEhKoHRhpH5XqZpiVlYWunfvrqigCLcgMHNBYmah5F1mbPnyR0n3lotRWj8YDOhI74zbKDVIUocR+13DaeVyOBxo27YtDh486Pd9ubm5EEJETUFiVdHSIqq0e8vFKEErgwGd6J1x6x2IkPqM2u8aaiuX0+mUDATS09ORn5/vU2hEQ0FiddHQIhrMczWMFLQyGNCJnhm33oEIRUa09bvK3SP9+vWTLDSioSDxhy15xrdo0SLJqeEueXl5aN26tXuKrJGuI4MBneiZcRu1BknhibZ+12gLbvwJVNCzJc/YnE4nVq9eHXARoeTkZM1Xk1WKwYBO9My4rZTJWo2R+12DrdlGW3AjJ1BBz5Y8YwtmsKCR81gGAzrSKuP2zoStkslaidQ1lntND6HWbI0c3KhBSUHPljxfaqXpcL8nmMGCRs9jGQzoLNL9nHKZcLRnslbir6A1QvNyeXl5WDXbaB4LoKSgD6UlL9hC7veTv+Pw8cNoFtsMrZu1RozNuI+tUStNK/0ef+cy0GDB9PR09OvXzxR5LIMBjWlZSwtU64jmTNYq/F1j17+lXtPquvtrQrVyzdZFSUEfbEue0kLuZMNJLN2xFHO+nIP13693b09NSsXNOTfjpjNvQmpSatDHFElqdZko/R7vc5mZmYmxY8dKvuYtKysLY8aMUbxPemMwoCGta2lsXox+oTyVUavrH6gJ1cj9p1pRWtAHs/qkkkKuuq4aI98fiR21O5DbORevjXwNaUlp+L3+d6z9bi1mlc3CE58+gdkXz8atZ9+q4hGHRy5dV1VVBZWmleSNUufSNVNg4MCBsmk7IyMDeXl5pstjGQxoRI9BQBwoGP1CucZaXX9/AYnR+0+1pLSgV9KSp6SQ+/7Q9xjy1hCc1uw0lN9cjgGdBni898ozrsRTQ5/C3zb8DbetuA1/NPyBu8+9O/gDiwC5tFtaWor6+nrFlSsl941cF8D27dvRpk0bydfy8vJQUFCgaB+MxrgdQ1EmlBpcuFy1jqaYCUcXf9dY7+svl+GOGjUKQ4cO1WQfzMLhcCA7OzvsaxOokBNCYPzC8WgZ3xKlN5T6BAIurZu1xj9G/AMPDH4A966+F1/u/TKs/VKLVJp2KSsrCzi1z9/3qHFvZGRkhPV5PbFlQCN61dI5UDD6+bvGel5/uSbwnJwczfbBagJ1O3y+53N8secLLP/TcrRv0T7g9z154ZOY/818vPTFS5g7em6kdjsow4YNQ2xsLEpLS31eC6YLLNC9kZGRIfkbrtfq6+ujakaWTQgh9N4Jq/AeM5Cbm8saEkU9I0xttBq5cz5h8QR89sNnqLqjCvYYu8f7Xc3iGRkZHp/5+2d/x9SNU7Hn3j1IaW6MLkan04mioiKf7YWFhaqmMalBgk3z7WhK2wwGNGakxGOkfSGiyOs+uzvG9hmLZ4Y/494mVeA1HdxcU1eD9BfTseraVbgo/SJN99cfrSpX/gKlaMJuAo0ZZTqfEeafE1FkeQf8R08cRXJissfrUqPimw5udr3/6Imjmu23Elp1gRklz440BgMWpOfypmyNINKGVMCflJCEI8ePAGi8F7du3Sr7eVf/++HjhwEASQlJEd3fUFiloNYCgwELUnv9AaUFPFsjiLQht+pjdvdsLP7PYlwgLsDmTZv9fodrcPOiykWIi4lDTicO/IxmDAYsqKGhIajt/gSzpKfeq+FFEls8yCj8rYx3eerl+Pi7j/HepvfQAz1kv8M1Mv6UOIVXvnwFV/W9StHsAzIvBgMWZLfbg9ouJ5gCPppXQ2SLBxlFoFUfh/Ycil7be2HlkZUoRCESkeh+rVevXujQoYPHILknSp9AzaEavDvm3YjvO+mLiw5ZkFprHsit0CW1PVpXQ5QLiJQufkKkpkCrPnbu3BmvD3sdv+JXzMVcHMRB9+tDhgxBQUEBHA4Hfjv5G/667q94bONjeKLgCQzqPEiL3ScdMRiwID1WptN7NbxICXZlSafTiYqKCgYLFBFKVn3M65uH2f1n4ziO4yW8hHfxLo5nHEd1fTVWVq3Efavvg+M5B/7+2d/x1NCn8Nfz/qrlIZBOuM6AhanxLO9gF/6Itr71YM6Bku6EaDs/pD2l8++rdlVh/vb5WPjjQnz989fu7cmJySgcUIhbzroF3dt012KXyQAYDFBYuKqisnOgJGjw/p709HTk5+czKKCgBRtUHvztIA79fgiJcYlo36I94u3xGuwlGQmDAQpbNNRm1Wgl8ff5iooKLFmyxGf76NGjkZ2dLRssAByQSESRx9kEFDazL/yhxmyAQOcg0ABKfwO/omkKJhEZEwcQkqVpNRsg0ADKQLMqIvmoayIitgyQpWm5/oG/tdSlHj3blNmnYBKRsTEYIEvTev0Df90JrmChpKQE1dXV7u3eUzCjYYwGERkLBxCS5RlxRoRcgc/VDokoEhgMEMF/bdsoNfFQ1nUgIlKC3QQ6MUoBQ43kmu+NVBOP5uc7EJG+GAzowEgFDMkz2pMWo/X5DkSkP04t1JhcAVNeXq7THpGcYJ87EGnR+nwHItIfWwY0JleQLFu2DJWVlVx+1kCMWBP3Nz2RiChUbBnQmL+CpLq6GkVFRSguLtZwj0iOUWviDocD2dnZuu8HEUUPzibQgfeYASkcIW4cSgZ7ckAoEZkZuwl0MGzYMOzfvx81NTWy7+EIceMI9NwBDgglIrNjN4EOnE6n30AA4AjxSHI6naioqFDl+QNaPduAiCiS2DKgg0Cj0bOystgqECFq1+I595+IogFbBnQQqNa/bds2DiKMgGBq8UpbD4w444CIKFgMBnQgNUrdG5ua1ad03YDi4mIUFRVhyZIlAWd3GHXGARFRMNhNoJOm88Xr6upQWlrq8x42NatLSS0+lFUHOfefiMyOLQM6cs0Xz8jIkHz9s88+03iPopuSWnyoqw5y7j8RmRlbBgzA4XCgR48ePjMMDh48iPLycuTk5Oi0Z9EnUC2eYwCIyIrYMmAQsbHScdnOnTtV/R01p9WZlb9afDSOAeA1J6JA2DJgEImJiUFtDwUXx1EmmsYA8JoTkRJsGTCIM888M6jtweLiOP+jpKYcDWMAeM2JSCm2DBiEq3m6aebtap52rXvf0NAAu90eUm2Vi+M0slJNmdeciJRiMGAgUs3Tcg81CrYQ48C40KYNmhmvOREpxW4Cg2naPC1VeLkE29wbjQPjghXqtEGz4jUnIqXYMmBggQqpYJt7m7Y8uLocnE6nZQoHK9aUo2kwJBFFDoMBAwtUSIVSiDkcDlRWVlqm37wpf+MyolmgRzATEdmEEELvnSB5cmMGcnNzMXTo0KC/z+l0oqioyGd7YWGhZQoM14BM1pSJiBqxZcDgpJr2wynEOMKcNWUiIm8MBkxAzcLLiv3mRETkH2cTWAxHmBMRkTeOGbAo9psTEZELgwGKSgx2iIiU45gBijpWWnKYiEgNHDNAUYUP54kMPgaZKLqxZYCiCqdOqo8tLUTRjy0DFFX8TZ1k7TZ4bGkhsga2DFBUkVty2KpLMIeLLS1E1sBggKKO98N5APgswRzNjy5WExepIrIGdhNQVGr6KOiqqirJ98htD0W0dkFwkSoia2DLAFmaGusRRPsAOz4GmSj6cdEhinpyT2rMzMzE9u3b3X+HUojzKZBEFA3YTUBRT6qpOysryyMQAEIbJe9vgF2kRWvXBBFpj90EZAneTd21tbXYtm2bz/tqa2tx4MAB7NmzB2lpaWjfvr3f5nG5gXR1dXVwOp0Rax2IVNcEl3EmsiZ2E5AlyTXvt23bFgcPHpT8THp6OvLz830KSe+CualIjB8ItmtCaQEf7WMfiEgeWwbIkqTWI+jRowdqampkP1NdXY3q6mqfQtLV6lBVVYXS0lKPz0RiCmMwc/+VFvByiwtx+iWRNTAYIMvy7jrYunWros9JFZIOh0OzBXqUzv2XK+BTUlJgt9s9Wgq4uBCRtTEYIEtzOBzuwu7AgQMoLy9X9DmpQlKrBXrkVln03h+5An7ZsmXuf7taCri4EJG1MRgg+q+cnBx89dVX2Lt3b8D3ShWSSgtpNfib++8aI9DQ0BDwe5q2cmi170RkPBxASOSlvLzcYzZBSUkJqqur3a/n5uZi6NChsp/Xc0S+9xiB1NTUgMHN6NGjkZ2dDYCzCYisisEAkQJGLySdTqfkAEYAGDVqFOx2OxoaGjy6CFy4QBIRsZuASIGmYwu0EEzw4W9qIwDY7XZ3zb+2tpZdAUTkg8EAkcEEM99fasaAt6bjG/icASKSwmCAyECCne8faNljqZq/1q0cRGR8DAaIDCTY+f5yU//y8vKQkZHBQp+IFOGDiogMJNj5/lIPYcrNzUVBQQEDASJSjLMJiAzGe8xAoKmMgPFnOxCRsTEYIDIgFu5EpCUGA0RERBbHMQNEREQWx2CAiIjI4hgMEBERWRyDASIiIotjMEBERGRxDAaIiIgsjsEAERGRxTEYICIisjgGA0RERBbHYICIiMjiGAwQERFZHIMBIiIii2MwQEREZHEMBoiIiCyOwQAREZHFMRggIiKyOAYDREREFsdggIiIyOIYDBAREVkcgwEiIiKLYzBARERkcQwGiIiILI7BABERkcUxGCAiIrI4BgNEREQWx2CAiIjI4hgMEBERWRyDASIiIotjMEBERGRxDAaIiIgsjsEAERGRxTEYICIisjgGA0RERBbHYICIiMjiGAwQERFZHIMBIiIii2MwQEREZHEMBoiIiCyOwQAREZHFMRggIiKyOAYDREREFsdggIiIyOIYDBAREVkcgwEiIiKLYzBARERkcQwGiIiILI7BABERkcUxGCAiIrI4BgNEREQWx2CAiIjI4hgMEBERWRyDASIiIotjMEBERGRxDAaIiIgsjsEAERGRxTEYICIisjgGA0RERBbHYICIiMjiGAwQERFZHIMBIiIii2MwQEREZHEMBoiIiCyOwQAREZHFMRggIiKyOAYDREREFsdggIiIyOIYDBAREVkcgwEiIiKLYzBARERkcQwGiIiILI7BABERkcUxGCAiIrI4BgNEREQWx2CAiIjI4hgMEBERWRyDASIiIotjMEBERGRxDAaIiIgsjsEAERGRxTEYICIisjgGA0RERBb3/wFBXX5r7TN8kgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the projected query and retrieved documents in the embedding space\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10, color='gray')\n",
    "plt.scatter(projected_query_embedding[:, 0], projected_query_embedding[:, 1], s=150, marker='X', color='r')\n",
    "plt.scatter(projected_retrieved_embeddings[:, 0], projected_retrieved_embeddings[:, 1], s=100, facecolors='none', edgecolors='g')\n",
    "\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title(f'{query}')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "• operating expenses increased $ 1. 5 billion or 14 % driven by\n",
      "investments in gaming, search and news advertising, and windows\n",
      "marketing. operating expenses research and development ( in millions,\n",
      "except percentages ) 2022 2021 percentage change research and\n",
      "development $ 24, 512 $ 20, 716 18 % as a percent of revenue 12 % 12 %\n",
      "0ppt research and development expenses include payroll, employee\n",
      "benefits, stock - based compensation expense, and other headcount -\n",
      "related expenses associated with product development. research and\n",
      "development expenses also include third - party development and\n",
      "programming costs, localization costs incurred to translate software\n",
      "for international markets, and the amortization of purchased software\n",
      "code and services content. research and development expenses increased\n",
      "$ 3. 8 billion or 18 % driven by investments in cloud engineering,\n",
      "gaming, and linkedin. sales and marketing\n",
      "\n",
      "competitive in local markets and enables us to continue to attract top\n",
      "talent from across the world. we plan to continue to make significant\n",
      "investments in a broad range of product research and development\n",
      "activities, and as appropriate we will coordinate our research and\n",
      "development across operating segments and leverage the results across\n",
      "the company. in addition to our main research and development\n",
      "operations, we also operate microsoft research. microsoft research is\n",
      "one of the world ’ s largest corporate research organizations and works\n",
      "in close collaboration with top universities around the world to\n",
      "advance the state - of - the - art in computer science and a broad\n",
      "range of other disciplines, providing us a unique perspective on future\n",
      "trends and contributing to our innovation.\n",
      "\n",
      "our success is based on our ability to create new and compelling\n",
      "products, services, and experiences for our users, to initiate and\n",
      "embrace disruptive technology trends, to enter new geographic and\n",
      "product markets, and to drive broad adoption of our products and\n",
      "services. we invest in a range of emerging technology trends and\n",
      "breakthroughs that we believe offer significant opportunities to\n",
      "deliver value to our customers and growth for the company. based on our\n",
      "assessment of key technology trends, we maintain our long - term\n",
      "commitment to research and development across a wide spectrum of\n",
      "technologies, tools, and platforms spanning digital work and life\n",
      "experiences, cloud computing, ai, devices, and operating systems. while\n",
      "our main product research and development facilities are located in\n",
      "redmond, washington, we also operate research and development\n",
      "facilities in other parts of the u. s. and around the world. this\n",
      "global approach helps us remain\n",
      "\n",
      "when the world around us does well. that ’ s what i believe will lead\n",
      "to widespread human progress and ultimately improve the lives of\n",
      "everyone. there is no more powerful input than digital technology to\n",
      "drive the world ’ s economic output. this is the core thesis for our\n",
      "being as a company, but it ’ s not enough. as we drive global economic\n",
      "growth, we must also commit to creating a more inclusive, equitable,\n",
      "sustainable, and trusted future. support inclusive economic growth we\n",
      "must ensure the growth we drive reaches every person, organization,\n",
      "community, and country. this starts with increasing access to digital\n",
      "skills. this year alone, more than 23 million people accessed digital\n",
      "skills training as part of our global skills initiative.\n",
      "\n",
      "also increased the number of identified partners in the black partner\n",
      "growth initiative and continue to invest in the partner community\n",
      "through the black channel partner alliance by supporting events focused\n",
      "on business growth, accelerators, and mentorship. progress does not\n",
      "undo the egregious injustices of the past or diminish those who\n",
      "continue to live with inequity. we are committed to leveraging our\n",
      "resources to help accelerate diversity and inclusion across our\n",
      "ecosystem and to hold ourselves accountable to accelerate change – for\n",
      "microsoft, and beyond. investing in digital skills the covid - 19\n",
      "pandemic led to record unemployment, disrupting livelihoods of people\n",
      "around the world. after helping over 30 million people in 249 countries\n",
      "and territories with our global skills initiative, we introduced a new\n",
      "initiative to support a more skills - based labor market, with greater\n",
      "flexibility and accessible learning paths to develop the right skills\n",
      "\n"
     ]
    }
   ],
   "source": [
    "query = \"What has been the investment in research and development?\"\n",
    "results = chroma_collection.query(query_texts=query, n_results=5, include=['documents', 'embeddings'])\n",
    "\n",
    "retrieved_documents = results['documents'][0]\n",
    "\n",
    "for document in results['documents'][0]:\n",
    "    print(word_wrap(document))\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  2.62it/s]\n",
      "100%|██████████| 5/5 [00:01<00:00,  3.53it/s]\n"
     ]
    }
   ],
   "source": [
    "query_embedding = embedding_function([query])[0]\n",
    "retrieved_embeddings = results['embeddings'][0]\n",
    "\n",
    "projected_query_embedding = project_embeddings([query_embedding], umap_transform)\n",
    "projected_retrieved_embeddings = project_embeddings(retrieved_embeddings, umap_transform)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-4.14157487154007, 7.448055040836334, 5.867360353469849, 11.475993871688843)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the projected query and retrieved documents in the embedding space\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10, color='gray')\n",
    "plt.scatter(projected_query_embedding[:, 0], projected_query_embedding[:, 1], s=150, marker='X', color='r')\n",
    "plt.scatter(projected_retrieved_embeddings[:, 0], projected_retrieved_embeddings[:, 1], s=100, facecolors='none', edgecolors='g')\n",
    "\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title(f'{query}')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we use metrics in assessing the performance of our business and to make\n",
      "informed decisions regarding the allocation of resources. we disclose\n",
      "metrics to enable investors to evaluate progress against our ambitions,\n",
      "provide transparency into performance trends, and reflect the continued\n",
      "evolution of our products and services. our commercial and other\n",
      "business metrics are fundamentally connected based on how customers use\n",
      "our products and\n",
      "\n",
      "our success is based on our ability to create new and compelling\n",
      "products, services, and experiences for our users, to initiate and\n",
      "embrace disruptive technology trends, to enter new geographic and\n",
      "product markets, and to drive broad adoption of our products and\n",
      "services. we invest in a range of emerging technology trends and\n",
      "breakthroughs that we believe offer significant opportunities to\n",
      "deliver value to our customers and growth for the company. based on our\n",
      "assessment of key technology trends, we maintain our long - term\n",
      "commitment to research and development across a wide spectrum of\n",
      "technologies, tools, and platforms spanning digital work and life\n",
      "experiences, cloud computing, ai, devices, and operating systems. while\n",
      "our main product research and development facilities are located in\n",
      "redmond, washington, we also operate research and development\n",
      "facilities in other parts of the u. s. and around the world. this\n",
      "global approach helps us remain\n",
      "\n",
      "17 as of june 30, 2022, we employed approximately 221, 000 people on a\n",
      "full - time basis, 122, 000 in the u. s. and 99, 000 internationally.\n",
      "of the total employed people, 85, 000 were in operations, including\n",
      "manufacturing, distribution, product support, and consulting services ;\n",
      "73, 000 were in product research and development ; 47, 000 were in\n",
      "sales and marketing ; and 16, 000 were in general and administration.\n",
      "certain employees are subject to collective bargaining agreements. our\n",
      "culture microsoft ’ s culture is grounded in the growth mindset. this\n",
      "means everyone is on a continuous journey to learn and grow. we believe\n",
      "potential can be nurtured and is not pre - determined, and we should\n",
      "always be learning and curious – trying new things without fear of\n",
      "failure. we identified four attributes that allow growth mindset to\n",
      "flourish : • obsessing over what matters to our customers. • becoming\n",
      "more diverse and inclusive in everything we do.\n",
      "\n",
      "32 services. the metrics are disclosed in the md & a or the notes to\n",
      "financial statements in our fiscal year 2022 form 10 - k. financial\n",
      "metrics are calculated based on financial results prepared in\n",
      "accordance with accounting principles generally accepted in the united\n",
      "states of america ( “ gaap ” ), and growth comparisons relate to the\n",
      "corresponding period of last fiscal year. in the first quarter of\n",
      "fiscal year 2022, we made updates to the presentation and method of\n",
      "calculation for certain metrics, most notably changes to incorporate\n",
      "all current and anticipated revenue streams within our office consumer\n",
      "and server products and cloud services metrics and changes to align\n",
      "with how we manage our windows oem and search and news advertising\n",
      "businesses. none of these changes had a material impact on previously\n",
      "reported amounts in our md & a. in the third quarter of fiscal year\n",
      "2022, we completed our acquisition of nuance. nuance is included in all\n",
      "commercial\n",
      "\n",
      "have been possible without your commitment to the company and belief in\n",
      "its mission. the opportunity to apply technology to make a real\n",
      "difference for every customer, community, and country has never been\n",
      "greater. and i truly believe if we continue to live our mission,\n",
      "embrace our responsibility, and grasp that opportunity, there is no\n",
      "limit to what we can achieve for the world in the year ahead and\n",
      "beyond. satya nadella chairman and chief executive officer october 24,\n",
      "2022\n",
      "\n"
     ]
    }
   ],
   "source": [
    "query = \"What has Michael Jordan done for us lately?\"\n",
    "results = chroma_collection.query(query_texts=query, n_results=5, include=['documents', 'embeddings'])\n",
    "\n",
    "retrieved_documents = results['documents'][0]\n",
    "\n",
    "for document in results['documents'][0]:\n",
    "    print(word_wrap(document))\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  3.66it/s]\n",
      "100%|██████████| 5/5 [00:01<00:00,  3.53it/s]\n"
     ]
    }
   ],
   "source": [
    "query_embedding = embedding_function([query])[0]\n",
    "retrieved_embeddings = results['embeddings'][0]\n",
    "\n",
    "projected_query_embedding = project_embeddings([query_embedding], umap_transform)\n",
    "projected_retrieved_embeddings = project_embeddings(retrieved_embeddings, umap_transform)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-4.14157487154007, 7.448055040836334, 5.867360353469849, 11.475993871688843)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the projected query and retrieved documents in the embedding space\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10, color='gray')\n",
    "plt.scatter(projected_query_embedding[:, 0], projected_query_embedding[:, 1], s=150, marker='X', color='r')\n",
    "plt.scatter(projected_retrieved_embeddings[:, 0], projected_retrieved_embeddings[:, 1], s=100, facecolors='none', edgecolors='g')\n",
    "\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title(f'{query}')\n",
    "plt.axis('off')"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Query Expansion\n",
    "\n",
    "https://arxiv.org/abs/2305.03653\n",
    "\n",
    "![image.png|width=200](attachment:image.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if not already active in the notebook, run the following to initialize the openai python client\n",
    "import os\n",
    "import openai\n",
    "from openai import OpenAI\n",
    "\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "_ = load_dotenv(find_dotenv()) # read local .env file\n",
    "openai.api_key = os.environ['OPENAI_API_KEY']\n",
    "\n",
    "openai_client = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/dev/miniconda3/envs/llm/lib/python3.10/site-packages/umap/umap_.py:1943: UserWarning: n_jobs value -1 overridden to 1 by setting random_state. Use no seed for parallelism.\n",
      "  warn(f\"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.\")\n",
      "100%|██████████| 349/349 [01:40<00:00,  3.47it/s]\n"
     ]
    }
   ],
   "source": [
    "embeddings = chroma_collection.get(include=['embeddings'])['embeddings']\n",
    "umap_transform = mp.UMAP(random_state=0, transform_seed=0).fit(embeddings)\n",
    "projected_dataset_embeddings = project_embeddings(embeddings, umap_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def augment_query_generated(query, model=\"gpt-3.5-turbo\"):\n",
    "    messages = [\n",
    "        {\n",
    "            \"role\": \"system\",\n",
    "            \"content\": \"You are a helpful expert financial research assistant. Provide an example answer to the given question, that might be found in a document like an annual report. \"\n",
    "        },\n",
    "        {\"role\": \"user\", \"content\": query}\n",
    "    ] \n",
    "\n",
    "    response = openai_client.chat.completions.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "    )\n",
    "    content = response.choices[0].message.content\n",
    "    return content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
      "To disable this warning, you can either:\n",
      "\t- Avoid using `tokenizers` before the fork if possible\n",
      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Was there significant turnover in the executive team? During the fiscal\n",
      "year 2019, there was a notable turnover in the executive team of XYZ\n",
      "Corporation. The Chief Executive Officer (CEO) retired after serving\n",
      "the company for 10 years and was succeeded by a new CEO who was\n",
      "appointed in the second quarter of the year. Additionally, the Chief\n",
      "Financial Officer (CFO) stepped down from his role and was replaced by\n",
      "a new CFO with extensive experience in financial management. The Board\n",
      "of Directors also witnessed changes with the departure of two\n",
      "long-serving directors and the addition of three new members, including\n",
      "a renowned industry expert. These changes in the executive team reflect\n",
      "the company's commitment to refreshing its leadership and bringing in\n",
      "new perspectives to drive growth and enhance shareholder value.\n"
     ]
    }
   ],
   "source": [
    "original_query = \"Was there significant turnover in the executive team?\"\n",
    "hypothetical_answer = augment_query_generated(original_query)\n",
    "\n",
    "joint_query = f\"{original_query} {hypothetical_answer}\"\n",
    "print(word_wrap(joint_query))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the company engaged deloitte & touche llp, an independent registered\n",
      "public accounting firm, to audit and render an opinion on the\n",
      "consolidated financial statements and internal control over financial\n",
      "reporting in accordance with the standards of the public company\n",
      "accounting oversight board ( united states ). the board of directors,\n",
      "through its audit committee, consisting solely of independent directors\n",
      "of the company, meets periodically with management, internal auditors,\n",
      "and our independent registered public accounting firm to ensure that\n",
      "each is meeting its responsibilities and to discuss matters concerning\n",
      "internal controls and financial reporting. deloitte & touche llp and\n",
      "the internal auditors each have full and free access to the audit\n",
      "committee. satya nadella chief executive officer amy e. hood executive\n",
      "vice president and chief financial officer alice l. jolla corporate\n",
      "vice president and chief accounting officer\n",
      "\n",
      "89 directors and executive officers of microsoft corporation directors\n",
      "satya nadella chairman and chief executive officer, microsoft\n",
      "corporation sandra e. peterson 2, 3 operating partner, clayton,\n",
      "dubilier & rice, llc john w. stanton 1, 4 founder and chairman, trilogy\n",
      "partnerships reid g. hoffman 4 general partner, greylock partners penny\n",
      "s. pritzker 4 founder and chairman, psp partners, llc john w. thompson\n",
      "3, 4 lead independent director, microsoft corporation hugh f. johnston\n",
      "1 vice chairman and executive vice president and chief financial\n",
      "officer, pepsico, inc. carlos a. rodriguez 1 chief executive officer,\n",
      "adp, inc. emma n. walmsley 2, 4 chief executive officer, gsk, plc teri\n",
      "l. list 1, 3 former executive vice president and chief financial\n",
      "officer, gap, inc. charles w. scharf 2, 3 chief executive officer and\n",
      "president, wells fargo & company padmasree warrior 2 founder, president\n",
      "and chief executive\n",
      "\n",
      "84 report of independent registered public accounting firm to the\n",
      "stockholders and the board of directors of microsoft corporation\n",
      "opinion on the financial statements we have audited the accompanying\n",
      "consolidated balance sheets of microsoft corporation and subsidiaries (\n",
      "the “ company ” ) as of june 30, 2022 and 2021, the related\n",
      "consolidated statements of income, comprehensive income, cash flows,\n",
      "and stockholders ’ equity, for each of the three years in the period\n",
      "ended june 30, 2022, and the related notes ( collectively referred to\n",
      "as the “ financial statements ” ). in our opinion, the financial\n",
      "statements present fairly, in all mat erial respects, the financial\n",
      "position of the company as of june 30, 2022 and 2021, and the results\n",
      "of its operations and its cash flows for each of the three years in the\n",
      "period ended june 30, 2022, in conformity with accounting principles\n",
      "generally accepted in the united states of america.\n",
      "\n",
      "88 report of independent registered public accounting firm to the\n",
      "stockholders and the board of directors of microsoft corporation\n",
      "opinion on internal control over financial reporting we have audited\n",
      "the internal control over financial reporting of microsoft corporation\n",
      "and subsidiaries ( the “ company ” ) as of june 30, 2022, based on\n",
      "criteria established in internal control — integrated framework ( 2013\n",
      ") issued by the committee of sponsoring organizations of the treadway\n",
      "commission ( coso ). in our opinion, the company maintained, in all\n",
      "material respects, effective internal control over financial reporting\n",
      "as of june 30, 2022, based on criteria establis hed in internal control\n",
      "— integrated framework ( 2013 ) issued by coso. we have also audited,\n",
      "in accordance with the standards of the public company accounting\n",
      "oversight board ( united states ) ( pcaob ), the consolidated financial\n",
      "statements as of and for the year ended june 30, 2022, of the company\n",
      "and\n",
      "\n",
      "officer, fable group inc. board committees 1. audit committee 2.\n",
      "compensation committee 3. governance and nominating committee 4.\n",
      "environmental, social, and public policy committee executive officers\n",
      "satya nadella chairman and chief executive officer amy e. hood\n",
      "executive vice president and chief financial officer judson althoff\n",
      "executive vice president and chief commercial officer bradford l. smith\n",
      "vice chair and president christopher c. capossela executive vice\n",
      "president, marketing and consumer business, and chief marketing officer\n",
      "christopher d. young executive vice president, business development,\n",
      "strategy, and ventures kathleen t. hogan executive vice president and\n",
      "chief human resources officer\n",
      "\n"
     ]
    }
   ],
   "source": [
    "results = chroma_collection.query(query_texts=joint_query, n_results=5, include=['documents', 'embeddings'])\n",
    "retrieved_documents = results['documents'][0]\n",
    "\n",
    "for doc in retrieved_documents:\n",
    "    print(word_wrap(doc))\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  2.40it/s]\n",
      "100%|██████████| 1/1 [00:00<00:00,  3.38it/s]\n",
      "100%|██████████| 5/5 [00:01<00:00,  3.27it/s]\n"
     ]
    }
   ],
   "source": [
    "retrieved_embeddings = results['embeddings'][0]\n",
    "original_query_embedding = embedding_function([original_query])\n",
    "augmented_query_embedding = embedding_function([joint_query])\n",
    "\n",
    "projected_original_query_embedding = project_embeddings(original_query_embedding, umap_transform)\n",
    "projected_augmented_query_embedding = project_embeddings(augmented_query_embedding, umap_transform)\n",
    "projected_retrieved_embeddings = project_embeddings(retrieved_embeddings, umap_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-4.14157487154007, 7.448055040836334, 5.867360353469849, 11.475993871688843)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot the projected query and retrieved documents in the embedding space\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10, color='gray')\n",
    "plt.scatter(projected_retrieved_embeddings[:, 0], projected_retrieved_embeddings[:, 1], s=100, facecolors='none', edgecolors='g')\n",
    "plt.scatter(projected_original_query_embedding[:, 0], projected_original_query_embedding[:, 1], s=150, marker='X', color='r')\n",
    "plt.scatter(projected_augmented_query_embedding[:, 0], projected_augmented_query_embedding[:, 1], s=150, marker='X', color='orange')\n",
    "\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title(f'{original_query}')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Expansion with multiple queries\n",
    "\n",
    "we generate multiple related queries using an LLM, gives us a better chance to capture all related informations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def augment_multiple_query(query, model=\"gpt-3.5-turbo\"):\n",
    "    messages = [\n",
    "        {\n",
    "            \"role\": \"system\",\n",
    "            \"content\": \"You are a helpful expert financial research assistant. Your users are asking questions about an annual report. \"\n",
    "            \"Suggest up to five additional related questions to help them find the information they need, for the provided question. \"\n",
    "            \"Suggest only short questions without compound sentences. Suggest a variety of questions that cover different aspects of the topic.\"\n",
    "            \"Make sure they are complete questions, and that they are related to the original question.\"\n",
    "            \"Output one question per line. Do not number the questions.\"\n",
    "        },\n",
    "        {\"role\": \"user\", \"content\": query}\n",
    "    ]\n",
    "\n",
    "    response = openai_client.chat.completions.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "    )\n",
    "    content = response.choices[0].message.content\n",
    "    content = content.split(\"\\n\")\n",
    "    return content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "What were the key factors that influenced revenue growth?\n",
      "What were the main drivers behind the increase in revenue?\n",
      "What product or service lines experienced the highest revenue growth?\n",
      "Were there any significant changes in pricing strategies that contributed to the increase in revenue?\n",
      "Did changes in market demand or consumer behavior play a role in the revenue increase?\n"
     ]
    }
   ],
   "source": [
    "original_query = \"What were the most important factors that contributed to increases in revenue?\"\n",
    "augmented_queries = augment_multiple_query(original_query)\n",
    "\n",
    "for query in augmented_queries:\n",
    "    print(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Query: What were the most important factors that contributed to increases in revenue?\n",
      "\n",
      "Results:\n",
      "engineering, gaming, and linkedin. • sales and marketing expenses\n",
      "increased $ 1. 7 billion or 8 % driven by investments in commercial\n",
      "sales and linkedin. sales and marketing included a favorable foreign\n",
      "currency impact of 2 %. • general and administrative expenses increased\n",
      "$ 793 million or 16 % driven by investments in corporate functions.\n",
      "operating income increased $ 13. 5 billion or 19 % driven by growth\n",
      "across each of our segments. current year net income and diluted eps\n",
      "were positively impacted by the net tax benefit related to the transfer\n",
      "of intangible properties, which resulted in an increase to net income\n",
      "and diluted eps of $ 3. 3 billion and $ 0. 44, respectively. prior year\n",
      "net income and diluted eps were positively impacted by the net tax\n",
      "benefit related to the india supreme court decision on withholding\n",
      "taxes, which resulted in an increase to net income and diluted eps of $\n",
      "620 million and $ 0. 08, respectively.\n",
      "\n",
      "independent recalculation of prices where appropriate. cash flows cash\n",
      "from operations increased $ 12. 3 billion to $ 89. 0 billion for fiscal\n",
      "year 2022, mainly due to an increase in cash received from customers,\n",
      "offset in part by an increase in cash paid to suppliers and employees.\n",
      "cash used in financing increased $ 10. 4 billion to $ 58. 9 billion for\n",
      "fiscal year 2022, mainly due to a $ 5. 3 billion increase in common\n",
      "stock repurchases and a $ 5. 3 billion increase in repayments of debt.\n",
      "cash used in investing increased $ 2. 7 billion to $ 30. 3 billion for\n",
      "fiscal year 2022, mainly due to a $ 13. 1 billion increase in cash used\n",
      "for acquisitions of companies, net of cash acquired, and purchases of\n",
      "intangible and other assets, and a $ 3. 3 billion increase in additions\n",
      "to property and equipment, offset in part by a $ 15. 6 billion increase\n",
      "in cash from net investment purchases, sales, and maturities.\n",
      "\n",
      "37 general and administrative expenses include payroll, employee\n",
      "benefits, stock - based compensation expense, and other headcount -\n",
      "related expenses associated with finance, legal, facilities, certain\n",
      "human resources and other administrative personnel, certain taxes, and\n",
      "legal and other administrative fees. general and administrative\n",
      "expenses increased $ 793 million or 16 % driven by investments in\n",
      "corporate functions. other income ( expense ), net the components of\n",
      "other income ( expense ), net were as follows : ( in millions ) year\n",
      "ended june 30, 2022 2021 interest and dividends income $ 2, 094 $ 2,\n",
      "131 interest expense ( 2, 063 ) ( 2, 346 ) net recognized gains on\n",
      "investments 461 1, 232 net gains ( losses ) on derivatives ( 52 ) 17\n",
      "net gains ( losses ) on foreign currency remeasurements ( 75 ) 54\n",
      "other, net ( 32 ) 98 total $ 333 $ 1, 186\n",
      "\n",
      "product revenue includes sales from operating systems, cross - device\n",
      "productivity applications, server applications, business solution\n",
      "applications, desktop and server management tools, software development\n",
      "tools, video games, and hardware such as pcs, tablets, gaming and\n",
      "entertainment consoles, other intelligent devices, and related\n",
      "accessories.\n",
      "\n",
      "• windows revenue increased $ 2. 3 billion or 10 % driven by growth in\n",
      "windows oem and windows commercial. windows oem revenue increased 11 %\n",
      "driven by continued strength in the commercial pc market, which has\n",
      "higher revenue per license. windows commercial products and cloud\n",
      "services revenue increased 11 % driven by demand for microsoft 365.\n",
      "\n",
      "----------------------------------------------------------------------------------------------------\n",
      "Query: What were the key factors that influenced revenue growth?\n",
      "\n",
      "Results:\n",
      "engineering, gaming, and linkedin. • sales and marketing expenses\n",
      "increased $ 1. 7 billion or 8 % driven by investments in commercial\n",
      "sales and linkedin. sales and marketing included a favorable foreign\n",
      "currency impact of 2 %. • general and administrative expenses increased\n",
      "$ 793 million or 16 % driven by investments in corporate functions.\n",
      "operating income increased $ 13. 5 billion or 19 % driven by growth\n",
      "across each of our segments. current year net income and diluted eps\n",
      "were positively impacted by the net tax benefit related to the transfer\n",
      "of intangible properties, which resulted in an increase to net income\n",
      "and diluted eps of $ 3. 3 billion and $ 0. 44, respectively. prior year\n",
      "net income and diluted eps were positively impacted by the net tax\n",
      "benefit related to the india supreme court decision on withholding\n",
      "taxes, which resulted in an increase to net income and diluted eps of $\n",
      "620 million and $ 0. 08, respectively.\n",
      "\n",
      "34 net income tax benefit related to an india supreme court decision on\n",
      "withholding taxes in the third quarter of fiscal year 2021. refer to\n",
      "the non - gaap financial measures section below for a reconciliation of\n",
      "our financial results reported in accordance with gaap to non - gaap\n",
      "financial results. see note 12 – income taxes of the notes to financial\n",
      "statements in our fiscal year 2022 form 10 - k for further discussion.\n",
      "fiscal year 2022 compared with fiscal year 2021 revenue increased $ 30.\n",
      "2 billion or 18 % driven by growth across each of our segments.\n",
      "intelligent cloud revenue increased driven by azure and other cloud\n",
      "services. productivity and business processes revenue increased driven\n",
      "by office 365 commercial and linkedin. more personal computing revenue\n",
      "increased driven by search and news advertising and windows. cost of\n",
      "revenue increased $ 10. 4 billion or 20 % driven by growth in microsoft\n",
      "cloud.\n",
      "\n",
      "• windows revenue increased $ 2. 3 billion or 10 % driven by growth in\n",
      "windows oem and windows commercial. windows oem revenue increased 11 %\n",
      "driven by continued strength in the commercial pc market, which has\n",
      "higher revenue per license. windows commercial products and cloud\n",
      "services revenue increased 11 % driven by demand for microsoft 365.\n",
      "\n",
      "35 reportable segments fiscal year 2022 compared with fiscal year 2021\n",
      "productivity and business processes revenue increased $ 9. 4 billion or\n",
      "18 %. • office commercial products and cloud services revenue increased\n",
      "$ 4. 4 billion or 13 %. office 365 commercial revenue grew 18 % driven\n",
      "by seat growth of 14 %, with continued momentum in small and medium\n",
      "business and frontline worker offerings, as well as growth in revenue\n",
      "per user. office commercial products revenue declined 22 % driven by\n",
      "continued customer shift to cloud offerings. • office consumer products\n",
      "and cloud services revenue increased $ 641 million or 11 % driven by\n",
      "microsoft 365 consumer subscription revenue. microsoft 365 consumer\n",
      "subscribers grew 15 % to 59. 7 million. • linkedin revenue increased $\n",
      "3. 5 billion or 34 % driven by a strong job market in our talent\n",
      "solutions business and advertising demand in our marketing solutions\n",
      "business.\n",
      "\n",
      "36 • search and news advertising revenue increased $ 2. 3 billion or 25\n",
      "%. search and news advertising revenue excluding traffic acquisition\n",
      "costs increased 27 % driven by higher revenue per search and search\n",
      "volume. • gaming revenue increased $ 860 million or 6 % on a strong\n",
      "prior year comparable that benefited from xbox series x | s launches\n",
      "and stay - at - home scenarios, driven by growth in xbox hardware and\n",
      "xbox content and services. xbox hardware revenue increased 16 % due to\n",
      "continued demand for xbox series x | s. xbox content and services\n",
      "revenue increased 3 % driven by growth in xbox game pass subscriptions\n",
      "and first - party content, offset in part by a decline in third - party\n",
      "content. • surface revenue increased $ 226 million or 3 %. operating\n",
      "income increased $ 1. 5 billion or 8 %. • gross margin increased $ 3. 1\n",
      "billion or 10 % driven by growth in windows and search and news\n",
      "advertising. gross margin percentage was relatively unchanged.\n",
      "\n",
      "----------------------------------------------------------------------------------------------------\n",
      "Query: What were the main drivers behind the increase in revenue?\n",
      "\n",
      "Results:\n",
      "engineering, gaming, and linkedin. • sales and marketing expenses\n",
      "increased $ 1. 7 billion or 8 % driven by investments in commercial\n",
      "sales and linkedin. sales and marketing included a favorable foreign\n",
      "currency impact of 2 %. • general and administrative expenses increased\n",
      "$ 793 million or 16 % driven by investments in corporate functions.\n",
      "operating income increased $ 13. 5 billion or 19 % driven by growth\n",
      "across each of our segments. current year net income and diluted eps\n",
      "were positively impacted by the net tax benefit related to the transfer\n",
      "of intangible properties, which resulted in an increase to net income\n",
      "and diluted eps of $ 3. 3 billion and $ 0. 44, respectively. prior year\n",
      "net income and diluted eps were positively impacted by the net tax\n",
      "benefit related to the india supreme court decision on withholding\n",
      "taxes, which resulted in an increase to net income and diluted eps of $\n",
      "620 million and $ 0. 08, respectively.\n",
      "\n",
      "independent recalculation of prices where appropriate. cash flows cash\n",
      "from operations increased $ 12. 3 billion to $ 89. 0 billion for fiscal\n",
      "year 2022, mainly due to an increase in cash received from customers,\n",
      "offset in part by an increase in cash paid to suppliers and employees.\n",
      "cash used in financing increased $ 10. 4 billion to $ 58. 9 billion for\n",
      "fiscal year 2022, mainly due to a $ 5. 3 billion increase in common\n",
      "stock repurchases and a $ 5. 3 billion increase in repayments of debt.\n",
      "cash used in investing increased $ 2. 7 billion to $ 30. 3 billion for\n",
      "fiscal year 2022, mainly due to a $ 13. 1 billion increase in cash used\n",
      "for acquisitions of companies, net of cash acquired, and purchases of\n",
      "intangible and other assets, and a $ 3. 3 billion increase in additions\n",
      "to property and equipment, offset in part by a $ 15. 6 billion increase\n",
      "in cash from net investment purchases, sales, and maturities.\n",
      "\n",
      "• windows revenue increased $ 2. 3 billion or 10 % driven by growth in\n",
      "windows oem and windows commercial. windows oem revenue increased 11 %\n",
      "driven by continued strength in the commercial pc market, which has\n",
      "higher revenue per license. windows commercial products and cloud\n",
      "services revenue increased 11 % driven by demand for microsoft 365.\n",
      "\n",
      "37 general and administrative expenses include payroll, employee\n",
      "benefits, stock - based compensation expense, and other headcount -\n",
      "related expenses associated with finance, legal, facilities, certain\n",
      "human resources and other administrative personnel, certain taxes, and\n",
      "legal and other administrative fees. general and administrative\n",
      "expenses increased $ 793 million or 16 % driven by investments in\n",
      "corporate functions. other income ( expense ), net the components of\n",
      "other income ( expense ), net were as follows : ( in millions ) year\n",
      "ended june 30, 2022 2021 interest and dividends income $ 2, 094 $ 2,\n",
      "131 interest expense ( 2, 063 ) ( 2, 346 ) net recognized gains on\n",
      "investments 461 1, 232 net gains ( losses ) on derivatives ( 52 ) 17\n",
      "net gains ( losses ) on foreign currency remeasurements ( 75 ) 54\n",
      "other, net ( 32 ) 98 total $ 333 $ 1, 186\n",
      "\n",
      "36 • search and news advertising revenue increased $ 2. 3 billion or 25\n",
      "%. search and news advertising revenue excluding traffic acquisition\n",
      "costs increased 27 % driven by higher revenue per search and search\n",
      "volume. • gaming revenue increased $ 860 million or 6 % on a strong\n",
      "prior year comparable that benefited from xbox series x | s launches\n",
      "and stay - at - home scenarios, driven by growth in xbox hardware and\n",
      "xbox content and services. xbox hardware revenue increased 16 % due to\n",
      "continued demand for xbox series x | s. xbox content and services\n",
      "revenue increased 3 % driven by growth in xbox game pass subscriptions\n",
      "and first - party content, offset in part by a decline in third - party\n",
      "content. • surface revenue increased $ 226 million or 3 %. operating\n",
      "income increased $ 1. 5 billion or 8 %. • gross margin increased $ 3. 1\n",
      "billion or 10 % driven by growth in windows and search and news\n",
      "advertising. gross margin percentage was relatively unchanged.\n",
      "\n",
      "----------------------------------------------------------------------------------------------------\n",
      "Query: What product or service lines experienced the highest revenue growth?\n",
      "\n",
      "Results:\n",
      "35 reportable segments fiscal year 2022 compared with fiscal year 2021\n",
      "productivity and business processes revenue increased $ 9. 4 billion or\n",
      "18 %. • office commercial products and cloud services revenue increased\n",
      "$ 4. 4 billion or 13 %. office 365 commercial revenue grew 18 % driven\n",
      "by seat growth of 14 %, with continued momentum in small and medium\n",
      "business and frontline worker offerings, as well as growth in revenue\n",
      "per user. office commercial products revenue declined 22 % driven by\n",
      "continued customer shift to cloud offerings. • office consumer products\n",
      "and cloud services revenue increased $ 641 million or 11 % driven by\n",
      "microsoft 365 consumer subscription revenue. microsoft 365 consumer\n",
      "subscribers grew 15 % to 59. 7 million. • linkedin revenue increased $\n",
      "3. 5 billion or 34 % driven by a strong job market in our talent\n",
      "solutions business and advertising demand in our marketing solutions\n",
      "business.\n",
      "\n",
      "revenue, classified by significant product and service offerings, was\n",
      "as follows : ( in millions ) year ended june 30, 2022 2021 2020 server\n",
      "products and cloud services $ 67, 321 $ 52, 589 $ 41, 379 office\n",
      "products and cloud services 44, 862 39, 872 35, 316 windows 24, 761 22,\n",
      "488 21, 510 gaming 16, 230 15, 370 11, 575 linkedin 13, 816 10, 289 8,\n",
      "077 search and news advertising 11, 591 9, 267 8, 524 enterprise\n",
      "services 7, 407 6, 943 6, 409 devices 6, 991 6, 791 6, 457 other 5, 291\n",
      "4, 479 3, 768 total $ 198, 270 $ 168, 088 $ 143, 015 we have recast\n",
      "certain previously reported amounts in the table above to conform to\n",
      "the way we internally manage and monitor our business.\n",
      "\n",
      "productivity and business processes $ 29, 687 $ 24, 351 $ 18, 724\n",
      "intelligent cloud 32, 721 26, 126 18, 324 more personal computing 20,\n",
      "975 19, 439 15, 911 total $ 83, 383 $ 69, 916 $ 52, 959 no sales to an\n",
      "individual customer or country other than the united states accounted\n",
      "for more than 10 % of revenue for fiscal years 2022, 2021, or 2020.\n",
      "revenue, classified by the major geographic areas in which our\n",
      "customers were located, was as follows : ( in millions ) year ended\n",
      "june 30, 2022 2021 2020 united states ( a ) $ 100, 218 $ 83, 953 $ 73,\n",
      "160 other countries 98, 052 84, 135 69, 855 total $ 198, 270 $ 168, 088\n",
      "$ 143, 015 ( a ) includes billings to oems and certain multinational\n",
      "organizations because of the nature of these businesses and the\n",
      "impracticability of determining the geographic source of the revenue.\n",
      "\n",
      "highlights from fiscal year 2022 compared with fiscal year 2021\n",
      "included : • microsoft cloud ( formerly commercial cloud ) revenue\n",
      "increased 32 % to $ 91. 2 billion. • office commercial products and\n",
      "cloud services revenue increased 13 % driven by office 365 commercial\n",
      "growth of 18 %. • office consumer products and cloud services revenue\n",
      "increased 11 % and microsoft 365 consumer subscribers grew to 59. 7\n",
      "million. • linkedin revenue increased 34 %. • dynamics products and\n",
      "cloud services revenue increased 25 % driven by dynamics 365 growth of\n",
      "39 %. • server products and cloud services revenue increased 28 %\n",
      "driven by azure and other cloud services growth of 45 %. • windows\n",
      "original equipment manufacturer licensing ( “ windows oem ” ) revenue\n",
      "increased 11 %. • windows commercial products and cloud services\n",
      "revenue increased 11 %. • xbox content and services revenue increased 3\n",
      "%. • search and news advertising revenue excluding traffic acquisition\n",
      "costs increased 27 %.\n",
      "\n",
      "commercial and consumer businesses. as we have diversity of target\n",
      "audiences and sales motions within the windows business, we monitor\n",
      "metrics that are reflective of those varying motions. windows oem\n",
      "revenue growth revenue from sales of windows pro and non - pro licenses\n",
      "sold through the oem channel windows commercial products and cloud\n",
      "services revenue growth revenue from windows commercial products and\n",
      "cloud services, comprising volume licensing of the windows operating\n",
      "system, windows cloud services, and other windows commercial offerings\n",
      "surface revenue growth revenue from surface devices and accessories\n",
      "xbox content and services revenue growth revenue from xbox content and\n",
      "services, comprising first - and third - party content ( including\n",
      "games and in - game content ), xbox game pass and other subscriptions,\n",
      "xbox cloud gaming, third - party disc royalties, advertising, and other\n",
      "cloud services search and news advertising revenue,\n",
      "\n",
      "----------------------------------------------------------------------------------------------------\n",
      "Query: Were there any significant changes in pricing strategies that contributed to the increase in revenue?\n",
      "\n",
      "Results:\n",
      "36 • search and news advertising revenue increased $ 2. 3 billion or 25\n",
      "%. search and news advertising revenue excluding traffic acquisition\n",
      "costs increased 27 % driven by higher revenue per search and search\n",
      "volume. • gaming revenue increased $ 860 million or 6 % on a strong\n",
      "prior year comparable that benefited from xbox series x | s launches\n",
      "and stay - at - home scenarios, driven by growth in xbox hardware and\n",
      "xbox content and services. xbox hardware revenue increased 16 % due to\n",
      "continued demand for xbox series x | s. xbox content and services\n",
      "revenue increased 3 % driven by growth in xbox game pass subscriptions\n",
      "and first - party content, offset in part by a decline in third - party\n",
      "content. • surface revenue increased $ 226 million or 3 %. operating\n",
      "income increased $ 1. 5 billion or 8 %. • gross margin increased $ 3. 1\n",
      "billion or 10 % driven by growth in windows and search and news\n",
      "advertising. gross margin percentage was relatively unchanged.\n",
      "\n",
      "• windows revenue increased $ 2. 3 billion or 10 % driven by growth in\n",
      "windows oem and windows commercial. windows oem revenue increased 11 %\n",
      "driven by continued strength in the commercial pc market, which has\n",
      "higher revenue per license. windows commercial products and cloud\n",
      "services revenue increased 11 % driven by demand for microsoft 365.\n",
      "\n",
      "( in millions, except percentages ) 2022 2021 percentage change sales\n",
      "and marketing $ 21, 825 $ 20, 117 8 % as a percent of revenue 11 % 12 %\n",
      "( 1 ) ppt sales and marketing expenses include payroll, employee\n",
      "benefits, stock - based compensation expense, and other headcount -\n",
      "related expenses associated with sales and marketing personnel, and the\n",
      "costs of advertising, promotions, trade shows, seminars, and other\n",
      "programs. sales and marketing expenses increased $ 1. 7 billion or 8 %\n",
      "driven by investments in commercial sales and linkedin. sales and\n",
      "marketing included a favorable foreign currency impact of 2 %. general\n",
      "and administrative ( in millions, except percentages ) 2022 2021\n",
      "percentage change general and administrative $ 5, 900 $ 5, 107 16 % as\n",
      "a percent of revenue 3 % 3 % 0ppt\n",
      "\n",
      "independent recalculation of prices where appropriate. cash flows cash\n",
      "from operations increased $ 12. 3 billion to $ 89. 0 billion for fiscal\n",
      "year 2022, mainly due to an increase in cash received from customers,\n",
      "offset in part by an increase in cash paid to suppliers and employees.\n",
      "cash used in financing increased $ 10. 4 billion to $ 58. 9 billion for\n",
      "fiscal year 2022, mainly due to a $ 5. 3 billion increase in common\n",
      "stock repurchases and a $ 5. 3 billion increase in repayments of debt.\n",
      "cash used in investing increased $ 2. 7 billion to $ 30. 3 billion for\n",
      "fiscal year 2022, mainly due to a $ 13. 1 billion increase in cash used\n",
      "for acquisitions of companies, net of cash acquired, and purchases of\n",
      "intangible and other assets, and a $ 3. 3 billion increase in additions\n",
      "to property and equipment, offset in part by a $ 15. 6 billion increase\n",
      "in cash from net investment purchases, sales, and maturities.\n",
      "\n",
      "34 net income tax benefit related to an india supreme court decision on\n",
      "withholding taxes in the third quarter of fiscal year 2021. refer to\n",
      "the non - gaap financial measures section below for a reconciliation of\n",
      "our financial results reported in accordance with gaap to non - gaap\n",
      "financial results. see note 12 – income taxes of the notes to financial\n",
      "statements in our fiscal year 2022 form 10 - k for further discussion.\n",
      "fiscal year 2022 compared with fiscal year 2021 revenue increased $ 30.\n",
      "2 billion or 18 % driven by growth across each of our segments.\n",
      "intelligent cloud revenue increased driven by azure and other cloud\n",
      "services. productivity and business processes revenue increased driven\n",
      "by office 365 commercial and linkedin. more personal computing revenue\n",
      "increased driven by search and news advertising and windows. cost of\n",
      "revenue increased $ 10. 4 billion or 20 % driven by growth in microsoft\n",
      "cloud.\n",
      "\n",
      "----------------------------------------------------------------------------------------------------\n",
      "Query: Did changes in market demand or consumer behavior play a role in the revenue increase?\n",
      "\n",
      "Results:\n",
      "36 • search and news advertising revenue increased $ 2. 3 billion or 25\n",
      "%. search and news advertising revenue excluding traffic acquisition\n",
      "costs increased 27 % driven by higher revenue per search and search\n",
      "volume. • gaming revenue increased $ 860 million or 6 % on a strong\n",
      "prior year comparable that benefited from xbox series x | s launches\n",
      "and stay - at - home scenarios, driven by growth in xbox hardware and\n",
      "xbox content and services. xbox hardware revenue increased 16 % due to\n",
      "continued demand for xbox series x | s. xbox content and services\n",
      "revenue increased 3 % driven by growth in xbox game pass subscriptions\n",
      "and first - party content, offset in part by a decline in third - party\n",
      "content. • surface revenue increased $ 226 million or 3 %. operating\n",
      "income increased $ 1. 5 billion or 8 %. • gross margin increased $ 3. 1\n",
      "billion or 10 % driven by growth in windows and search and news\n",
      "advertising. gross margin percentage was relatively unchanged.\n",
      "\n",
      "35 reportable segments fiscal year 2022 compared with fiscal year 2021\n",
      "productivity and business processes revenue increased $ 9. 4 billion or\n",
      "18 %. • office commercial products and cloud services revenue increased\n",
      "$ 4. 4 billion or 13 %. office 365 commercial revenue grew 18 % driven\n",
      "by seat growth of 14 %, with continued momentum in small and medium\n",
      "business and frontline worker offerings, as well as growth in revenue\n",
      "per user. office commercial products revenue declined 22 % driven by\n",
      "continued customer shift to cloud offerings. • office consumer products\n",
      "and cloud services revenue increased $ 641 million or 11 % driven by\n",
      "microsoft 365 consumer subscription revenue. microsoft 365 consumer\n",
      "subscribers grew 15 % to 59. 7 million. • linkedin revenue increased $\n",
      "3. 5 billion or 34 % driven by a strong job market in our talent\n",
      "solutions business and advertising demand in our marketing solutions\n",
      "business.\n",
      "\n",
      "• windows revenue increased $ 2. 3 billion or 10 % driven by growth in\n",
      "windows oem and windows commercial. windows oem revenue increased 11 %\n",
      "driven by continued strength in the commercial pc market, which has\n",
      "higher revenue per license. windows commercial products and cloud\n",
      "services revenue increased 11 % driven by demand for microsoft 365.\n",
      "\n",
      "and crm applications. office commercial office commercial is designed\n",
      "to increase personal, team, and organizational productivity through a\n",
      "range of products and services. growth depends on our ability to reach\n",
      "new users in new markets such as frontline workers, small and medium\n",
      "businesses, and growth markets, as well as add value to our core\n",
      "product and service offerings to span productivity categories such as\n",
      "communication, collaboration, analytics, security, and compliance.\n",
      "office commercial revenue is mainly affected by a combination of\n",
      "continued installed base growth and average revenue per user expansion,\n",
      "as well as the continued shift from office licensed on - premises to\n",
      "office 365. office consumer office consumer is designed to increase\n",
      "personal productivity through a range of products and services. growth\n",
      "depends on our ability to reach new users, add value to our core\n",
      "product set, and continue to expand our product and service\n",
      "\n",
      "( in millions, except percentages ) 2022 2021 percentage change sales\n",
      "and marketing $ 21, 825 $ 20, 117 8 % as a percent of revenue 11 % 12 %\n",
      "( 1 ) ppt sales and marketing expenses include payroll, employee\n",
      "benefits, stock - based compensation expense, and other headcount -\n",
      "related expenses associated with sales and marketing personnel, and the\n",
      "costs of advertising, promotions, trade shows, seminars, and other\n",
      "programs. sales and marketing expenses increased $ 1. 7 billion or 8 %\n",
      "driven by investments in commercial sales and linkedin. sales and\n",
      "marketing included a favorable foreign currency impact of 2 %. general\n",
      "and administrative ( in millions, except percentages ) 2022 2021\n",
      "percentage change general and administrative $ 5, 900 $ 5, 107 16 % as\n",
      "a percent of revenue 3 % 3 % 0ppt\n",
      "\n",
      "----------------------------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "queries = [original_query] + augmented_queries\n",
    "results = chroma_collection.query(query_texts=queries, n_results=5, include=['documents', 'embeddings'])\n",
    "\n",
    "retrieved_documents = results['documents']\n",
    "\n",
    "# Deduplicate the retrieved documents\n",
    "unique_documents = set()\n",
    "for documents in retrieved_documents:\n",
    "    for document in documents:\n",
    "        unique_documents.add(document)\n",
    "\n",
    "for i, documents in enumerate(retrieved_documents):\n",
    "    print(f\"Query: {queries[i]}\")\n",
    "    print('')\n",
    "    print(\"Results:\")\n",
    "    for doc in documents:\n",
    "        print(word_wrap(doc))\n",
    "        print('')\n",
    "    print('-'*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  3.86it/s]\n",
      "100%|██████████| 5/5 [00:01<00:00,  3.49it/s]\n"
     ]
    }
   ],
   "source": [
    "original_query_embedding = embedding_function([original_query])\n",
    "augmented_query_embeddings = embedding_function(augmented_queries)\n",
    "\n",
    "project_original_query = project_embeddings(original_query_embedding, umap_transform)\n",
    "project_augmented_queries = project_embeddings(augmented_query_embeddings, umap_transform)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 30/30 [00:08<00:00,  3.56it/s]\n"
     ]
    }
   ],
   "source": [
    "result_embeddings = results['embeddings']\n",
    "result_embeddings = [item for sublist in result_embeddings for item in sublist]\n",
    "projected_result_embeddings = project_embeddings(result_embeddings, umap_transform)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-4.14157487154007, 7.448055040836334, 5.867360353469849, 11.475993871688843)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10, color='gray')\n",
    "plt.scatter(project_augmented_queries[:, 0], project_augmented_queries[:, 1], s=150, marker='X', color='orange')\n",
    "plt.scatter(projected_result_embeddings[:, 0], projected_result_embeddings[:, 1], s=100, facecolors='none', edgecolors='g')\n",
    "plt.scatter(project_original_query[:, 0], project_original_query[:, 1], s=150, marker='X', color='r')\n",
    "\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title(f'{original_query}')\n",
    "plt.axis('off')"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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1wNg9gKWtMYcESIAESIAESIAE1h8BipP1905XekadlTpW7YjQ0JYTrMK///3vQ2O80NHAtQkHjyD6AhXhcIVAjk77L7SpReWx1u9e7muNAb0BDytIDiS6ny6qi1sMAwXwra/uAsiBhxhOS9Rt4rb7qU6jLsrg0reIzNGCRxfGU9iacEGZQMNAlS3byNJmmUMCJEACJEACJEAC64kAxcl6epurPBesp7HK16tqBHzDT0k7KZ12WB1VgLoIOv/7v/97SBTUQtQKjh/pLNOXJha1rMWDzoTYwM6/3eoIg+mIB52GVLjuuute+cpXQkp1xtBpE4WRRgudftEmMpce2Y66uDB3lO8U7rSjEzof2xb/6I/+KI5ZRFOIPAEiHSUP17KHHnoImXBj+7Ef+zFsSbyoOm9JgARIgARIgARI4EIgQHFyIbzllZsjluA7d+588MEHYRlAOMfBgwex2sZ15iOATxeOZteiAl5SCGLp1IUwgGEBYfednEWJbmEAtdAddI5Hi56iLspgtNgsWO8wtmxrEAy6pNIfqd8XNiJbVFIXWJq5NAfnS77xjW+EOMEjCBI4rWlxcuedd95///3IhF7CCSd9fX1L6zKHBEiABEiABEiABNY9AYqTdf+KV3qCOKDjmWee0a5ZX/va17DORmQFhAFW9t3yoDMsna/X/TCb4KwPeDdBh8CnC95NnWJIYH9hRJxDSEAw6EsbN7rLLJvW/erCSCOBptAjQtuhdmDN0L2jbifRaQflMZ5ms4ndtPAUfmsIrek81Qnk40J62QkiH0/1I9iCoD2g1tD1PffcgyPp3/Oe96AADqFHzD3iTG6++ebufY07FXVH/CYBEiABEiABEiCB9U2AWwmv7/e7CrNDyASONsdaHCri93//9+G8pJ27TrZw10PEU+iNf//3f//VX/1V5GBR/vM///M4Kr57AlAUiDtHDgpDKmA3sO6nOq1FAr7RqU53yqB9nQP/K+2apRUOrDTIgWJBs/jWFyJncCGNTAT3w+cKAes4JB6no0CrILPT7JkkOuXRILQHAmm0CQgSBePEAJDAYLAZ8ac//Wns4tVps1Oxk8MECZAACZAACZAACaxjAiaWj+t4epzayhPAQh+eVzA1PPHEE1h2IyweBgF9OPqyS21kQjPgG8er/+M//iNW/0hv2LABoRdXX301FEKnFpbvaBzHFGJBf+TIEQSUv+pVr1o0QV0Y5pe//du//fa3v63dw2CsQKSH7gXfaGTHjh0wViCyBZH3CDjBvr1QC6g7L01STYJbXOj0wx/+8D//8z/DFoRDVzonNuIRpomtgb/73e8iHw2+973vReai8Sy9hTi54YYb4NOFsyAxEgTnoOWvf/3rGMyePXve+c53InNpLeaQAAmQAAmQAAmQwIVAgJaTC+Etr+gcsUCHqLj99tt1bAaW79AJn/rUp/bt2webA7QBru4BYfWPyPWPfvSjEAAQDHiKuIsPfvCDcHlCzEn3ch8N4iwRZKI6WvvKV77yxS9+ETEq3a0h/dxzz8Gd7D//8z8XRadoMwgKwDULvmfQP2gcUTHYSvgzn/kMEtA8GIxuDcNAGmdK/sEf/MF//dd/IYoGPcJcA+uNFg9qGidOpHuoi4bUfQufLoSawD8N5SGiPvvZz/7rv/4rtNaVV14J0QIx1l2YaRIgARIgARIgARK4oAhwJXRBve4VmixUBA44f9/73nfHHXfo+BN4RsHLC5tQwUABdaF3HIatAHIFkgBPP/7xj8OCgfU6AsRxBCGOSId4gJzoHjEW9Lt3737LW94C9yoUhpKB7IHpY2BgAHHzsEhA5MA/Cvk46BAbYUHkQD/AeKJVREc8QGDgIJG3vvWtsFo88sgjGCH2B4PIQXA8mtqyZQvKI5p/ZmYG4uFjH/sYNAkGidAUVEGbHZHTPTakUavTxaJH3bcoAwjgg/McoYgwAORgkLDeQHp1l2SaBEiABEiABEiABC40AhQnF9obX4n5YvkO48Av/dIvwaELoRrf+973IBhggkDfWIhDdUAGQEsgkANyAgYKXPDRwuIe+fC/+q3f+i08XaRMdF3EnPziL/4iCsPcAWkB4wl0CEQLlAPC7h944AGICsSiwDpxySWXoMG9e/d2xImeeUc//OzP/iz6hSZBJDp2yoKFB8oE5ovXvva1qIimMDyIB/QFMbNp0yYok5/+6Z/GwDotLErAUIOSncxTgEYZOK3BLAMfNu14hhwQu+qqq05Ri49IgARIgARIgARIYN0ToDhZ9694dSYI9yTYT97//vdj51wEeSOeBKt8PRT4R2HRD+0Bswnkgc7UZgcs2REQv6wy0cVgc4DPGHQFqsMbCnoAi3u0DCPMvffei1vdIILyf+3Xfu1DH/qQVheLEGj9gF5+7ud+DpHx+EYjMI/Atwo2HMSQoDxiZmCEQT6cuHCUO/TS29/+dphNTqY9MH60gMK4FnW39BaNIAwGIg219FOoGjROn66lrJhDAiRAAiRAAiRwQRGgOLmgXveKThbLdLhvwRHrF37hF+CLhbX+Jz/5SeyfC0csHQ2Cpbn2yEIOLuiKL3zhC6jyG7/xGycbKDQJ1vHY7Qqi4g1veAPcxr785S9DnGiVggZxaMmrX/3q66+/Hi0jE+5YaAr52kCB6riQA3mATGwKfNtttyGkBE8xNhw2AqsLjDm6CkaCjX1hqIEiwlmQMNroukvHpltDd2hz6dOlOSiGWaBBdAHTDap/5CMfedOb3rS0JHNIgARIgARIgARI4IIiQHFyQb3uFZ0s1tzQJzBQ4ORBbGYFOwkW94gngQDoLOLhkYWlPwJIYF1BDMZTTz2FAHFkQmMsOohQV0GbuLCsR5AJ4kbgbYUNuyBO8FQ/Qhg9HLpwnAjsGD/xEz+BFT80A3qH8kHvKNONADkw78AwguoogJ18dVMog5FjGDhrBe2jFrTEUmWCkSNQBCVhb9HhNIva7+6rO62LQThhbEijZZiDEOvSXYZpEiABEiABEiABErgACai/H1+A0+aUV5gAfs2wFoeBQpsyFvUOp6xPfOITMJsgNh0lIS3+5E/+BBtqQTl0lvtLf1GRgwYhKnDpBlEYUgHOUVju46neHAyZ+sKjpQKjMxKIGW1d0TkorMvjG9U7xZYmYPrAAOCUpQXMqQt3qkOPwesM3m5QOC996UuRgD7pPGWCBEiABEiABEiABC5MArScXJjvfaVnjSU7NAMudLxIZuAR4texdzDkwec+9zkEfuDYkJ/5mZ+BXHnb294G84Ve7i9d9CMHK/vumXRa1gmohc5TFMbVuV2agLpY1Jouf+paaAeuWUtbO3UOhocIGWx5jAT8037lV34FJiBdBTmn7fHUjfMpCZAACZAACZAACfQuAR7C2LvvrldHjsV394Vp4BZCAjtl4Ru7ZiEYHUYM7PEFwYCjP06xXofJAnU7ILqbXZruFDtZorsKbCz69mSFzyYfw4bZBAcvwq0L3ly/8zu/g1PhtVUHnZ5Ny6xLAiRAAiRAAiRAAj1NgJaTnn59PTl4iI3ucXeW43Diesc73oEYlT//8z9HFMfRo0f/4R/+Aa5ZH/jAB06mTzp10WB3s9353X2dIv0iqpyitdM+gnUI8S048mXz5s2In9E2JdQ62UxP2yALkAAJkAAJkAAJkMA6IEBxsg5eYo9NYVkZgExEd2BTLOzrBRsCAjmwdsfEEK2OR7iWnWR3vk53S5Rlq6x6JnYDwwH2OOQE9hPEmSD0Hwaizqi6Z9TJZIIESIAESIAESIAELhACDIi/QF50z0wTEfM6kF3LDAgVRKT0zOjPYKA4j/JHfuRHcDokpokjVj7+8Y/DfkJNcgbkWIQESIAESIAESGD9E6DlZP2/496aIdRI92IdEgXXulm7w1qCiJqnn34aCcwUNpPuyfbWm+JoSYAESIAESIAESOCcE6A4OedI2eBZEVikQ/TtutEnjzzyyOc//3koEzCC/eTNb37zWcFiZRIgARIgARIgARJYXwQoTtbX++Rs1jABSCxsl4xvHA0JfYLzKPfs2bNIjK3h4XNoJEACJEACJEACJHDeCTDm5LwjZgdnT2B9WE4wi3379j366KPYQRhpRMNjAwA4d509H7ZAAiRAAiRAAiRAAuuDAMXJ+niPnEVvEEC4Py6ttfQJ9Bg3jSe98fI4ShIgARIgARIggfNPgOLk/DNmDxc8AagRMFhWhGihcsETIgASIAESIAESIAESUAQoTvh7QAIrTYCCZKWJsz8SIAESIAESIIEeIUB/9x55URxm7xPQ9hPMY1kTSu/PjzMgARIgARIgARIggbMlQHFytgRZv0cJKEerlbpO4da1UkNgPyRAAiRAAiRAAiTQAwQoTnrgJXGIL5aAOk6k64IeOS5JEAZy/ObEQl135yZJU8m54chWSIAESIAESIAE1jsBipP1/oY5vyUEtEaRUj1Q6TRafUkpZpAACZAACZAACZAACaw0AQbErzRx9re6BLQy6YwBCgUfRqh3gDBBAiRAAiRAAiRAAqtIgCfEryJ8dr3SBODmtf/Q9DPPjWdy2SSJZeyNDRUu3rVNKoXCiwRIgARIgARIgARIYJUJUJys8gtg9ytJIEzEY89M/OPnvzcyMhhFgQxmbrxm826IE2qTlXwN7IsESIAESIAESIAETkKA4uQkYJi9fgiouPcktY0EQkw0sg88P7ShWfbDlhPM7Njqq8fauStN6PRCkj9JgARIgARIgARIgARWjgDFycqxZk+rSwAiJBTCk4W2tdl3ypHRTmQ7sXIYlQqJp/FkdV8PeycBEiABEiABEiABIShO+FtwARGIpYiEFRo5YeakMGWckcJW80+VCeXJBfSrwKmSAAmQAAmQAAmsSQLcSnhNvhYO6rwRSKSMhZlIU0hL4NtQkgT/U5mcN+RsmARIgARIgARIgATOlADFyZmSYrl1QADeW7GQiTQSYajEOpgSp0ACJEACJEACJEAC64gAxck6epmcypkRiOaLYS/h9BDG9JZHMZ4ZPJYiARIgARIgARIggfNIgOLkPMJl02uWAA480VcilUThRQIkQAIkQAIkQAIksBYIMCB+LbwFjmGlCSSwmVCTrDR19kcCJEACJEACJEACpyFAy8lpAPHx+iagA1DW9xw5OxIgARIgARIgARLoFQIUJ73ypjhOEiABEiABEiABEiABEljnBChO1vkL5vRIgARIgARIgARIgARIoFcIUJz0ypviOM87AW7Ydd4RswMSIAESIAESIAESOCUBipNT4uHD9U6gs1uXPvOE+mS9v3DOjwRIgARIgARIYE0ToDhZ06+HgztXBNLjF483hvMXcRAjrnlNkj5Rack9vFIW/CIBEiABEiABEiCB1SBAcbIa1NnnihKAEpE42ETrEN0zfu+xlbA6Ij7dUbj7qcpb0eGxMxIgARIgARIgARIggXkCPOeEvwrrkwAERrcRROsN5JhCGFJYlikCGSVJFCdx+kyXh2hBmW7JrhvR1VNSStSsT2ScFQmQAAmQAAmQAAmsNgGKk9V+A+z/PBCAlsAnSlvW6VAImEcC5JuG41hhHAlTmpYdGXY7EkYqSqA68BP/JDpSBEoGQqRzu9Aexcl5eGdskgRIgARIgARIgATSlRgxkMD6IaCFxFylsf/IrMz0qSASmbp1SRkkSew6labpumYsY8NIEttteOb+cT9JwhgOXioQJcEHQiYIvL5SZuNIyVmsRBbfrx92nAkJkAAJkAAJkAAJrDYBWk5W+w2w/3NKQCkLIQ4fq/x/d34/zGwzpGUYEjaSWJpBmGT7S88dNk3HjIxEmiIynCMz0V0PTjWbLeXglcQCPl4xvL08z6vuuWLD8HDJToeHOPkFEwrFyTl9YWyMBEiABEiABEiABLoIUJx0wWCy9wno3bYSYc823W/dszeIpG0apmlJwwqD2MgOtc1+aWW8KDRMGcvMM0emjow/1my3DESjQNlEURL6IpnbNObu2l6CEEGASoSAemie4/qk9zFxBiRAAiRAAiRAAiSwJglQnKzJ18JBnQUB6IjRjX23vPolX7z3iVyunCnkTdOUSSLjMDCyseGa0sI9/LgMoxCJxJMFmVF2ExnHyq0rDubGJ1/ztqtvfOnFdmomgT7BlcoTKBT98yzGx6okQAIkQAIkQAIkQAInIUBxchIwzO5lArmcvWlTuVQqRZAfRiExbKVO4hC+XNIwjTQMJUb4u3QioxiIjGHi9MVEGhAscRx5UlqbR8tjQwUtS3qZBMdOAiRAAiRAAiRAAr1EoHvT1F4aN8dKAqcggN23Clnr6stG8hkRBFEYW6FwIpGJhQ1NAp2CutiJS8WdSCeU2VBkI5mLjFwk3DAyt23Z1F/K2+bCnsKquIo5Sa+Fn/O3/EECJEACJEACJEACJHDOCFCcnDOUbGjtEICAyOfMN96yaajQjoOmiXAROG0JM1abBmO/4BgfAScuRJno3YMl4t4tmZhRmPhBePONV48OD+rpKC+uNNpk7cyOIyEBEiABEiABEiCB9UqA4mS9vtkLd15QJrCK5B1xzWWiP98I/HochFIqWWKmrlv4pYcDF5SJEir4UsVVTEoYhW2vEYaVq6/qHxzMoB0cjcKLBEiABEiABEiABEhgxQhQnKwYana0EgSgKPDBr7UrRH9GbBzIFbNWOwxj7BGcKBOIicNMlDJJXbaQRgKKJVFxKDjdxJSNgUJ7qE+6DjLVU7TGiwRIgARIgARIgARIYGUIYPXFiwTWGwH8WltSZA1x2e7RTSMF3/Ph2WXApwubAgtpKTWCbbdSIYMtu1IBgoD4KGz1FaJXXre5lLdQXYuc9YaG8yEBEiABEiABEiCBNUyA4mQNvxwO7cUS0LoCGwHvecnIjk25yPMgNrSXlraTpIYTeHPhAzuKunAIYxA0R/vE62/eVcjYap8uVYUXCZAACZAACZAACZDAyhHgVsIrx5o9rSQBLS62bRabhhIzDsMwiISF2HZYUNSJisrJCyYTGSFOPg0tiaNIRM3+vH/lbjuLQpTtK/m22BcJkAAJkAAJkAAJpAS4BOMvwjokAGWC32z1nYjNY8XLd5XazZk4xtHvaocuTBjh76qI2sILlhOkY8uKRvqdjUOFgjorXlXkRQIkQAIkQAIkQAIksMIEKE5WGDi7WyECEBzQGPDm2r0te8OVVtAaj+N2kgQwlqgDTJLIMgycHI8jGSNlTQnrjand24o3XrsTteAPBrcutMCLBEiABEiABEiABEhgJQlQnKwkbfa1ogSgLnB8yaZhY/e2JA5mhPCFCEUc4ax4dQBj+g37Co5AEbEfBpXNY/ZFO4fg9KWtLis6VnZGAiRAAiRAAiRAAiSAvywTAgmsVwLKeCJFKSOG+42hPrsSh3DjkvjE6tiTKA5jRKNIhKDEvlct54L+kshlRIQdvWA5YTz8ev214LxIgARIgARIgATWMAFaTtbwy+HQzoKAdsqC+MZnqNR3683XeWHS9uNEmtIwIU4seHVhW+FY2FFSr85sGXNx8CKOZAxhXDmLflmVBEiABEiABEiABEjgRROgOHnR6FhxrRNIsCVXGnYyNmS95sZiKStVFIph2LaKNzFwpQoGB5xEXu22Gzdf/ZJh1xKWpewtWtus9RlyfCRAAiRAAiRAAiSwvghQnKyv98nZLCKgtgwWmYwcG7H6shYi3eM4CiO1QVeEVJKEcegF7bwd7hjLjpbdjBS2PpRxUTu8JQESIAESIAESIAESOP8EKE7OP2P2sEoEtPVDB7jnHHnpjkI5F/uBF4SRkiVQJ3Hghy0/al6ybWCoaGdNtbsX9+lapdfFbkmABEiABEiABEhAxf3yIoH1SkCdtohfcYSdZG3jdTcObxoMg3YdygQTjhEInwRRWHfNxi2vuHi4XMDWXvD74kUCJEACJEACJEACJLBaBChOVos8+z3fBGJ91CK6geTIGuKaS8VQYS5ozeG8eMsyHBsx8YElKv256o3Xl/rL8OfiRQIkQAIkQAIkQAIksJoEuB5bTfrs+7wRSA94l+lp8GkfiDbpd8WGAXeg5CDWxPf9MMK2XF7Obo71BX0laVtqB2HGwZ+3N8KGSYAESIAESIAESOD0BChOTs+IJXqQAFQGgk2U1lCuXWkkiWOIKy4d2b1zoNH220EIj662Vx3Ix9ddNppzYUXpwVlyyCRAAiRAAiRAAiSwvghwRba+3idnc5wA7CA4/B1nLqos/KLjc9mlQ7t3FpvtNg6Jx2ZdvtcY7Zc3XrMta+Hkk+M1mSIBEiABEiABEiABElgVAjwhflWws9PzTiD161K9dPQ3EoMlfELb8DI2zoePM1a4edi+ZEfWSQPhcfaiMric96GxAxIgARIgARIgARIggeUJdFZuyz9mLgn0KAEtM/D7jU9HciDmffNI/trdfX5zMgobY4OZTSPlXHrqYo9Ok8MmARIgARIgARIggfVEgOJkPb1NzmV5Ah1xgl/3i7Y4t73cbVeP1qoTF+8oXX7pBjyNwjhJ9xdevj5zSYAESIAESIAESIAEVoQAxcmKYGYnpyfQ8cM6fdEXXQJejBsGzMt3xmHzoNc6tmXM3ra5BHECry58n9NLxeEv9znzTpYCWZpz5q2xJAmQAAmQAAmQAAn0AAHGnPTAS7oQhpioLbXOtUBYAg4bChdtMZCLh/P1qukOFMNSPj0V3jK099eSGucmo0tVnDjNzoPFU8cD/Wzxg3MzILZCAiRAAiRAAiRAAmuSAMXJmnwtF96gzs8aHOv7hYbTpT625DJx4Ekh87qbdx+cMwbLLmwmZiKMcy+MFvo9l6/yfLR5LsfHtkiABEiABEiABEjgLAlIutqfJUFWP0cEsFdWt5Nhl644Jx0ocaLahOVirhE8+MREPcxctK2wfdTF4fFpx6l8gZiZ71nfLtv3GYiEhcaWrc9MEiABEiABEiABEiCBZQlQnCyLhZkrTyDdyBfSAReOTzyHTk26TdWgUgz4P4iS2VrkCzuflUU3sdFdgt6jhZ29Tjd3dSSK/pykpOqn6zoDLfOiS3dVZJIESIAESIAESIAEep4AxUnPv8L1MoF58aDUw3FxAjGxaGmvF/5ppvrqPO3KRxP6bh6NNobESoHE+FZPY2GE0CIyMdFBgmQoIj+JUc2QCD8xTBzgqD4ntIOb9Kh5aQn16bLzKLnSdZ1QayEfRY7nd1JpxeO10SNuzr2T2cIg+JMESIAESIAESIAE1jQBipM1/XoujMF1VuqRUg4QDmoVDwmRfncQKFEBVYErTSl/RKzjDRz0jiK4w5nvSk6kN51K6a2+i7FhsAgDGaW9SJkaSqBVIogTGQeRV1cFIDlM23QyiWEvK04S25IWnjpKwHQu1W/atQ7rXxAXhgqzR5PqUloHYkjiUnmdqspcc1zbQJxo2bPQRFe5NAkm3XUXP+Y9CZAACZAACZAACfQ0AQbE9/TrW/uD1xoDK+qFJTVW18ctCOomvY2UtSQOksRL7RgwcYSpONEVoSsi9fG8uNVsVqu1arXV9qII+sSYm5uNk9hre416I4YEUIt3rQBM2ETwn6EEQ/qB2UMkCIiXSv/AShKjNMYlRWTEgYmu1VBkEsvIsGLppOJHjU/rCZXSY5VmmFhhGqiCMql5JZVKEnWjjGPb+JiGaRj5QgE3Gdctl8vQJ9l8zsoXRC4nHEe3ppSJEhuw1aTmGmELfBInbbVLtCivM1UQAkzK1KqzUD+tfvyGKRIgARIgARIgARLoaQK0nPT061v7g49EatlQq21cHePG/MBh64B6gRTxRKsqmjPt2UPezJGkVQsas5HfNuIEJgcIC/VrigvVYSiJgiiM4JcVCTMWZhD6EB1YvIchFI6pzCpCot10xa+0d9qxMJBtxMqQoQoorYIgE3SeihPchkYCUwoUi4HVv2o5MWDlUMNMu0dlNVI0rPQJCqBHFMAdFImqiFmgpoxDqAxLRdgrQ41tY+9i1QUkChSRYUrDshPTxFRUs6oFmRimlSuY2ZJTHHSKI3ZhVOaHRSYvTAiY1HNMDUPblFR/6YjTfHWDBD5pvrrlRQIkQAIkQAIkQAK9TYDipLff39oYPRb6iy4lAFIZ4IvYV2lcECFQFa2m32y1Wu1Wq9lut6E1sKI3hW96NceblrVDceWI7dVley4J2zKOTBg78J/SEGYqEAzDhMOVGUs7MdxI2DHUANLqo80dkA3QEVYknATre9RSFhC1fNdaQw0EQkIZT1RSDRK2EgmhksoflJKWqoFFP+qqItpqofUA0qmiUA/Sgaly8ArzjcQ3RWQmoSECI/HM2EuQCd8x5YWmGweKQBlt0CNmrYSSGmpo2dLNhnZRZAZlYTTKjUWZ4djOR/ArE9AyMMAYpWIBlwV7i+sKy1JmFi1LJMpgjifTJxQt6XviFwmQAAmQAAmQQO8QoFtX77yrNTtSvXw/YXhhEgciaIfN6bg9FwfNOMKSPYZhIZirtCqVWq1WqdbgnRXGMQwJNj4yyst6Pq5mk6Yjw4zdljZ0SwiDBS5Ea0gDPy1EnCjHK4EY9kSJnhi5bhCbXuwGwvWTLGwaobADkQlE1pO5JDFRAw2grJIoqUBJvbzUcKFS8BEww6QKBiUgHNATqkADIaFEihJWKlcltchSa35lVjFNWG9iJ265su3IlhU3smbkiJYrIleGprAgVyxTqRAYSFJ3tQDf8CtLBZcWJwayfBFCrLW9mleZbIrn20kpSKwINYR0XdPEfEeGjYFBJ5uTuWxiO/A6g13FyRSN7ICRGZBWLp0XGly41AhxnUy06Kf8JgESIAESIAESIIE1R4CWkzX3StbkgLSdAUPDsnd+5YsbrNVTU4Cvlu3pB55XcHKCJUH41Wj2WGXv94Lx77enDwT1SgaGDbXmh0HCFmbGsNwQtg7DRV7aqHRk2xItO/FgcDAk1AdCUNrQJ1K5Q0FEWLCjJJEVxnYY2UHituJM3bNCq1zzZcVzqkGu4rl1T7ZlthXnKkF+Lsi1Q+kHIoTRAgJlXpkow4q61A9llYEhQ91hKX98ZspFCyt+pWvg6qVEiba+pBWx6pfCcY1C3oWPWVZW+51mn93KxZWRQpyXlZLdGMqGjtHKmB5El21GlhGbRsuyPMuMDCgaZT9JxUlsRtgwzHACmICEEyt95cYig6foE8EwZtIWYUOG7ST0EM2PIUHOtWNL5ocGt16a3XilvXmPURpWSKUpIWQAU00znYmyq3Qplvmx6x/p3FVyofAJT3lDAiRAAiRAAiRAAqtDgOJkdbj3Wq8dcYKBp/Ea6idW7YFIPBG3lCXD94K5mWP7Dxw8dCj0G64R2VE72zpcFpNuVIPkcESoWlFeWNjtKhuKjG+V27IcGgVolShx4siLIz8O22HoNVv1en263a4EPowKNc9vJZEJK0WCVoWbiGwgcoGRC2XRM/LN0G0lhZYst8w+Tzhekm0bhbosN0Q51iHmQu+s1VmIq6U5FvF65a7MKvOr+DSl7nCp+BKlSvClvrsvGEOgdRAPE8Wx7ya1fFLJi0ouqvQZjWw8l01ms8mcI5pO0jAT5dxlQ2LJGj5C+pAPrjKI2I6by2ZLuXx/vjRg2q5hqo9lZQwzYyPIJPbNsJ4VM244Ycc1I24ZcRuDAMQ2LEUyHzkDdWdDxR71RB5CBpaUiy+5tDQ2ahVLiZuFXQd2F2TD5y2Nb0HVE/SVEmbq02HSPUGmSYAESIAESIAESGB1CNCta3W491qvetWeLtJV/DeuNEQ7aCTVg3PPPeDNTYqgaYR+VG0U602Us0zDkpGbzNpG27ZhRkhsrOhhKokNbHXlRW49sA5MJhNhZjYqVFq2L0oR3L4Qn5FgF67Yj4LAb8dRiIzQD5FjQAtgwQ3PLpwxIiBRHJhQsKeWEjkSlgcXWsWX2VDaAW6l68t8S+YwEASoLxgQurWH8suCPlmqPBZezXGbw5IyelmP7wiWj0j0RclAK25mZbuaNF3ZskXDThqW8G3EnxgQVYgwgYuaL2Q7QRQKgu49zFSYLcus29as7boZRMojEB9yyUCgSywKbliw/bJtb820txXyRSt0TMSrJKbloCkVex/LIPEywTT2QM4mMCgFoNuK9kf7nMByIrtQHt2a33KZWdoorHw6fcwWCq2bgE535yxMnT9JgARIgARIgARIYJUIUJysEvje6zZdkatwDzhxBY2ZidrcTFSbytaf9579dlg7pqLALTNvFrJGFvHcsVmIZFEkdjPKVLxK0K4kke97fhRZfmI0o7DhO89WskfFwGQ0Ot3IevZICAEC/y0De3CpEHX8XR8LdpyJCOMHfJXgtKQclpSZQzlEwVaA8JIEzlESse+23kErUHHwRoygkTQ4HrtkYTmu3KPSRXm6hZfmjrmoVlRjWLSru9S1Sz88/o3H6YWfaZmFJzClqHtlQlJ7deXaohBCmSHCJA5gJzFVTLxvwhENPcDAopy4UF6F/sdQQ0rYweSitjJGYE4SxKKl5M98DygbBUXbK1mtIXt2p1ufyc+WrdiVvp20EIdjuZbp5B2nz3YHDJnJSRhJQitqW2FVzo0nU80oitpGUczuaNXnkuJWKz/SNzRoFUowT6no+XnvNT21hQkuTIw/SYAESIAESIAESGB1CVCcrC7/nug9DbpQ8RcRQtvDxkTSmp19+vHx559r1SZGrWo5OlpyfERW4K/+0BetyGqG+WowXEv6wyRseI3K3BQcvtoNnE/SRAB8JPO+KPuyNGNtm3N31ayNzUw5dkcChJlIyzBN7OGlTAjpgh1RFGCEvXm1M5lawyfYwUtdC25X2j9LeWGhGiop57FUwOjdfnVhZClZ0HWpYmmO0kFLnnYVTJ8uuu/cwrKjAt+dSDUSSzMNFklFCzRJ2jX6ADpooHRcqpAaIaSWHo8SXGpHAaVP0jliAnErbszG1enm1Mxc+2BUy0a+JWJE6sBolS+XSqXBcv9of9+obUIPmjmz2Sdln9lybM92sMty2Izbzdl9k9NTTdmf7dtkX3ypM7zBKY8a2SGJbcGUVIPTV2cOTJAACZAACZAACZDAWiFwCreWtTJEjmNVCaTKBCEl6kT1qHV079QDd3j77sUaG0ETOC3dtbA5VctQoRQhzBe1cGSqUXpiou+h8aEnKyPYiitAODvW0PBbgluW2nYL5hC4Y7n4NMxSQxZbsoAwEuyvBXendN2sVvFRqknMBTmhjhRJQ++BAoXUoSXpKr+bTLr210oE6+5Uq6SPVeS5vu8qrct1ZZxtcqHBVJAsDBumkYX8E9pPh4ocrQ9S9ZI+7xSG7cVSUTqtYjKTi6awIZgh2iaOcpHCD4M4gvubCnxPonbGEtvLtT1Dx64cOjZYaJTMaVM0gygTx9kgwSEwMorwSdqeP7bntvLltxhjl8DWJLAPgTIbQQ9Ro5zwanhDAiRAAiRAAiSwugRoOVld/mu/d8RItBHyXjv0/Pi+pxpHnyk29pWNOWmXI6cQmnlPGvVETkwemTx2aK46W0+yjbg4Hg8eiC+dKFwUGrCTWAnUCfbdVWYNrIW1ocOEmaUtLA9CJXXKgpWjy+0K625lXghTPFiyq7PcFy7kq0V8an9YyFv0s6v0oifn7XZBb2AW0A1q2Z+OGS5q6Wjnb0/WvY7X1zYfVQaHS0bS8VXcf7ZhDuFI+vRgFliU4MKFHdGgGNONjtMo+XbraPuQf+TweN6o5Y2Z4YH8ps3byoUhVzQzZtUMqyL0oqTZPPDg+NSM3Hj5pTe9XvWg9vJaFIVysuExnwRIgARIgARIgARWiADFyQqB7tVuEBLRmmjsfbBy4JloYn+mNZ2125ms0TJL463ywbnMsabVSPrmakO1+q6WlwRGfyD7K8amOXNr09yIQ9EjuDpBSShfrOOaAZElkBfpOeswcSBffytI86v5dE2/sOJfAm9BmXQKLylxPEPZUFbqSrtKp7kwQt2zmm1qTlHmijO6oGpQyWxLC/uSpcpE1VcuYWCJJxAn0HmGOvxxKs5ih+VKVLSTihVXioEc9Er5jDsgDlxUNreUM1kryZjtKJw2Zlvt9sxew9902Svc8oiwsmkUih7QmY7sjIbPQiRAAiRAAiRAAiTwoghQnLwobBdKJfyFPogax6oP3xHVp0o4XtA2Y8uZaFiH284zc7mnpvoOVAsVc1Nk5NTB7VlHGhn4aHmi0BSFQBawhIaDFk4gVPIEm++qJbtaZKuIB7VOV5tW4UqNDGlCfakLy+9lNYV26OqSObr4/Ddqda7T6hZVOO29U6WT6Iynk/OCEp2RQ0Uo1QV3twSOaqo3pE+rTxac1rRawL9QhJqg6vxY0XgqTFIVJ20Dh7pIe8bIt61NOJw+wnbDkW9MIhzf3xC2pge9ueFgwBUb+0u2LcpG027unXxoLmvbA7uvcfs3CZxDf1yVHE+9oPmyMAmQAAmQAAmQAAmcKwIUJ+eK5PprR62xEQHvV8f9Y48WMmbexXHmhcON/P3PGU9MxYdxyqG5ve5sadqbIhN/g1eHmqeyAotp/OE/3fMX7kzdAiB11kKzyFO+T2nqLJVA2srir448WPxg6f3CMNQaHcPSt0uLnUUOqHQYnLEy0f2lVp+usBDMS98pqaMaVW5joTQRsdOUg1BCMU50tCKYU4wkkL754Iyxf+rZPqt1/WWjW/v9QWeibM+GoXXsoa9a+dxwqV8YeHHdmu4s5smqJEACJEACJEACJHDWBChOzhrhemwAW0epsI8krhzcN3nPNwZsnFKi4t0PTja/+LDzpLypam5rZjZ55mholD1ZwKIYvlvYKxfGkfRsQ2zmqxbWMAIoG8hyK/55/XDio84yWT/t3HYYL2pqUYH5NjulT5lQhTu960Tn9pQVT/Fw0Xg61h/0tWjkp2hEPzrZXOb3+OoaO45/Ae0wlYGw0yhDlYwMEVXcy2JnaC6+wvKnn3u6eu3Q3hs3TF08EPeJmqhM29PPitpFor+M4BO8JWXb4kUCJEACJEACJEACq02A4mS138Ca7V/9YT72m/XG9PhGF/Hsphd4M/X4cKP/SPmqwN0UGoMBzvfAye7CwS5cev2NFS6Wxp2VM1bki9fra3a+53NgZ65MFLGOnSUdEsCejiF0IIqoVwDLDHZVg1zBNnx1xJ7IjGMMmrJ6tD3pHj20I9u+ZNDPyKBsVM3akag2bfbvSnXT6Xo4n3DYNgmQAAmQAAmQAAl0CFCcdFAwcZzAvCcRIiWiMPBaFg76w2oXG2xli7mBzfWwz4/yhoQmwabAajMu/MEeq2r1x/4z+Pu7XgifwZr7+HguqJRWMqCkeJ7BlRZLHcAWCkMfIjNJbD/JeFGMtwjnL7e8MZs/IJMZHF0PfWIEjcRvK1c2aCEVrX8Gb26hff4kARIgARIgARIggfNEgH8xPU9ge73Z49YP9Yf4xMDJGqZl9fX3X7RjbFO/WZINM5g2gmkZ12MR4uBzHemuFrvHIywUhEUr7I4y0ceP9Dqm8zp+sNIf3csii0pX15q5+lZHOSr+eF2hiJpmULWTar/rbx/OXLJr48jQIFz14MIFw0rq/YU2UFh/60R6xy8SIAESIAESIAESWCUCtJysEvi13y2WufPxDWpVHOHgPyFLWfOq7XZuW+ahpyYPHK3MeZmasSnJbo9VQLza/daaX+xqbaP+GA9xovVJRwfrW/xtH4lO5trnsQZHCNWYqot5XZGiTsw49e0K205wZEAe29gXXrx1ZOuGvh2JKPqeDBErr+JSbNvC8fILk6LZZIEEf5IACZAACZAACawqAYqTVcW/xjtPt5lKNQrOd8eviiyEsxvld0tuZddFTmObdaxZemAye/dEodJ0fWEbhpPFitcw8JUYJvzAcDR8tLBDF8SNViP4hhsRZAlysI7ubEaFtMrUTkZrnMw5HR4IdJQgGu4AWdQJ3L26SxoKVmQrB64ojHFFQRy3k8iIo5wISnZ8zeY5nBy/vTRTsJ7GcfGDyb5yfMjCtgYi9nDIvD7Kcb6PbkPZom55SwIkQAIkQAIkQAIrR4DiZOVY92ZPWDhjFYwdajM4yh0OQWVxrBDP9hlumCmMZDeamXJheFslsKoNb2J2Zm62grM9QpkJjGJkFBIzGxuuQFCKibW0OjcQf+RXC2Ecga70ifqTf/pH+zQvfYbOdJY22/QmtBc26nkD1cK5jWABMmCFMJ8I3nRqC7R56xNSqZUErwSRJLETVa2oZkR1J2kjksTJZQrFwkA5P5y3cjK5KFvdkX1+zHreiSI3SXLxVEbM2jJIsLXafDsvbJwsTQIkQAIkQAIkQALnmwDFyfkm3OvtYzUM5x/HT4rVwGp5npnMDPRJ03ASA2cuhkG+VC4X/dhttLzZQmWmUIVzVyUsTXhD497ArJ/zoyKOZVQh2oapNqyVEicwokVrPgpbWU9iqfSPOq4wPagRyHCvjCoLVhed0+soO+OHsWPZSwkzNfcYH0Tx6A9EHaxPsK3A1IGTZJBGvikiVwRFcXQsOzuYqRXtesaoZLLZQqnYV8yXszknSXBC/IA4WEyO2sDrRZWZg6FTyZTRkoU9vcBWC51UCqa6cNkxMZMESIAESIAESIAEVpAAxckKwu7JrhBwAlcgqyWK4y17YmpatKu7zEIuI2wbsQuNfvFcLm7AwcjIeGJDEG7A2YvOMW/suZr5xKx5qBLMhFYzVhErAawAuKLYUNYA4WBRrByYoEzMUGI/4oyUqIsDHFN/JfVI4LQO5bWUXvipLS3z96f5oaqv7JWaNM6oy2XGhu0EIBUiEVtKluB8d8+M1SnvSjRIZT9R8gTHl4CcZTlSZIw4bwYbjInLR2Z3DdaHC7P55AiAQt4AbRLlDIlXdMyK634o2l7cqPqHnzy0abgxODiEbtQhNvPRQWrE6dCVGDyj4bMQCZAACZAACZAACZw3AhQn5w3tOmoYDl2xkQ+s3JQfHNyXPD0+Wy6JzVvGNm7c4rhWRjRcMWdH44Y/FcKJy8q6zs7ckL1xbKAeZZpGoZ049VZzema2Wq1W5qr1ej1se1hGR7EVRUaQZFr2QGANCjOXmHlhQqUony/sJwVlooqlBgVIGrXTVNeSGoDTJ0tAY5mdbm285AEy1KNO/oLw6WSoRKfNRU/T/BPW9Kpwuq6fr98RUvP38z9ObAeFsFWWakzPDrIkUcE3cRLDmgGfq0YS1s1wOhfNuHFdmJFlxAjiyeVz5XLJcXMjI2PlQj5vm50LR98AAEAASURBVBkjLMe5IXGwLPbl5cFc8jwaALVY9nnmVk9mA9E3104mx8WBvfu9emTWwvKAskbB+gKo3eJkEZYTh887EiABEiABEiABElg5AhQnK8e6V3tSJ47HhiENwwyMgXHjhtDeKQP3oYOue1Tk5MzGQbF7KNiaz/fZczCJCOmXkikZP5lrz0VGMYjzcWLiyI1o2PP7WuHmEGenRFFkSiOICn6UmW7m9tWiI7480mhNBoEf5XxhhYiqgLkAO+LiQqSLIS1TOjhoJQ2aT0+hR3y4CszABfuKZqtcxtSaXy3A1YIbhoQ0niM1wKjgDfUIxeFIplynljcVLIgTLTtQUsuV1CiBuwTLeqWQUBn2B+xOpi9kIjAEgSBQHhgWGgnjeQGQ9m5EiEFPRBArawiGgaLYnhnFVCtJbBuJY8Ee4hfM2bGyf3G5uTNXGXImpeEZ6oNDMA1s5Syla1kZSzpWbJuJ6UZH8/JYJpm05IwtPWnm49iei8p762N3P5dvxYVWOOj7W6PoajublIP8JfbToQn1ggEE8+xScPP4NER+kwAJkAAJkAAJkMDqEaA4WT32vdOz2k1KLcZFYBRmzdGq/XJfZqLAkO1WLj56NJybgteQEw6ZLcdxC0U3iy2HHRtLbcucFvGkKVpmUrONRmA3YQpQNoI4tiw7jPqCpK9aHBruS8ajwrTvVmKjkdjQD9gOFzEWKBcEYcNro0YYBqHXDnxf+SRBtGDpD0MKTA46Vhw/1OGF0B4Wgu0jaQXSTgwHj1PpolQFLDESsgenRuKcD8BPJQS0hxIy6ZUKF51UFhIoh0j5P+GT/q/sNgFcrea1iYjNODRFKJUIUSYdKUJ4ZqEGelTKBke/qC5TOwk274XXmm1KbGYGv6xM1rWdjO06JhQTLoTjQIAJx4iKQvbZ7e2Z6a32gQHzgJQNKZsSh5ao8UL/ZJLEjWUxlH2xKEmjJYXdjot+q9WsVSv1luf7c0n0bJR9cHZrW0LmZQDAsX2YWXz7+YY5HcsGFFQq3tSI1dTnf+iJ85sESIAESIAESIAEVpMAxclq0u+ZvtViW6234d/VkgMVc4sn8yE2FzaCVtLf8idnm87BOC4nWce1y+V8uTyYzZVc08qZtaLlFa16nzmVc6Zi0ZTCwwo+lpEhXSyvQ9mfc5qZjByTVlMEnsSnrhy41H8wb0CSeM1WM4qgSlrtdrPdbuMBFtc4eAUmC1VKHf8IvQNzgIFg8VDm/chqJa4vc43IUWYP2AhUnL1ah4cyqx4hsgO3nWj7BXGCnPkrFRfpfJGHMH4VEGLLKA+5FdcN2JFgzElCM2zm7cgSoSFC24AtA3qpZUEwpUt+nCWiZApUSWr4gKXIdmxIslSb5LNuNuPkLROhN6pEKlFgh2lnkjknnukXB/rj/QVxQIgaxIkQgTIBKbmUw7ZbtWC0GrgzfrEVumFS9MO+ZrNcrfRPzTb9QNbNTceMDRPm9tiChsEea8KRoOYVjMFA5KH+FibJnyRAAiRAAiRAAiSw5ghQnKy5V7JmB5Su4WGCsAORC418mDhYpCciG8oRz95ciy934noEOTEdyqkQC3pbBINmuKM/2V60t+WN7SVlqoDdwjDg1mTAghJHECpNW872CSMnm0GyP5JZIWHu8EWCFny17rejxEE6VK5YMkLIOISIMp5gsY4fCLJQARv4YHtc9fFFuRY4tSDXSkoTDZWjLANY1hvqcEJfhrUorAUQJ0ao1E1HjpxAXUWJaH2i9ADmjWJJ3ooHMp4bzppKWWF2bTeuDeWFbQbYtcw1o0ImMuOqYcB4ggZgNoFWgolCySKlT2JssaUUUWq1gDuYIxM3wW7A0o4Fts8y1dGIIkazRlJzxYybzMVJiA26lJ1DqS/1DUUGEAfr5uNzmScrhYmKbCblUGKz5tT4gtNosiZ2cG4Yw6EcirDds7RgZkIAfAArUGKnfmQnzJQ3JEACJEACJEACJLCmCFCcrKnXsfYHA1WgAkKC2PbhN4WNtqBVzBLMKVXpmQhuV+t4LM0jA4aFpN2KDtRnjx6ZDp6Ojo4ks8oNyaxj+e5mMsMjG4XIDvSPlcpjplGIZR4RIzaObUTduIFVvpNU3aRmxrVEeBAqsfATGcY4YjAM1IZeaimPvizoCxWKomLoLUM67aQ04PZ7brmV9G0u9CkxBH0AY4YSJ6Yv/ZZR8hEpo1SNqr/speYwbzwxEEGCNISBI728qLvhnEgCU0JbeE5czZtNM2kZiW9jiy1RNWUF0kXtqgVHLKUjkMBHiRK1XzLCXlSXGLmD49qVd5YoeAjLkX0J7EhGNpE2tEwQYqhuLcy1Grlqfaoyd7RWafntNgQYdj0LRTQRjRwwy+PODs/pa8t+pehw5KWSaqofTDmG0x0kHWCpvMjEfgawvajdm6G1eJEACZAACZAACZDA2iVAcbJ2382aHZlau6emhRCB3Vj04wbmEISsq2x8cCkrhykQH2KF8UA7HqvI3ceSGSlhKvGTOJRtaR7FH/UNZyrj2C7CMQzDxTmNMKpkTH/Q8Yaz9qAlRtxoMIPzG1VoB6LxhYEGY7UJsTJKwAQBKeShawTJQzJBKUkc/6ieR9mknRfVyJiFtUQdooIiKvbEiIQTwNQjXHQNUwSycC0VKUpipdJHzUbJCVyIc/cd0bYMeKZBAcCbKzKNppO04HNlyNAyQkM2jKQpYaWAPlEEVOdwJUNTSjtBDKnQerh94YiYpBnKmi9nfHPSy0zDzhMVqr7b8I0Q4gNVYSmKh8Jwix96YdjGDgIYBgJWEhOCMFO3h2aNTQ1zUwARAiuWtNEydAhGiRmpr0QdGpPafGABgoyDxMKYVRYvEiABEiABEiABEljLBChO1vLbWctjU2vt9FILcKz74cYUSiyKU9MAwkJwOodwEYwdylLbGK1angMhoXawxUJbuWYFyq0KQSuqfLpsV+IGkd8Z0Ry17TFXDInGqCWGncCSvm20pfSF4cF4gJ27YIOAfsCi27YzsHHg2zBsCCHLxjbEOcPKGUZGGkqBKF2Qrtq1ajIhJGADgWpSblt4nC7m5+WHno76hq0lnYeSKPgPsS+qO3UICRSImi7kDtQCDBQe8jCjyItCDx1FPhQT9JgPRQFVAEkRYdMuWDvQJkwXygSD/cSwJUBUi7LVKJkO7WNBfioZbCR9tbDQCBwPofUwcczbONRBjEpbWRBekH8QF2BkhCLXRGiNxDZo2DwAOkRvwKWkh1JhqQzpmEjShH5XmOeSqaIOLxIgARIgARIgARJYMwQoTtbMq+i9gcyvdLFcxzI/Xf+q5TNWw0hjGR7CIyqx4HTkwb4CM4VyaVL2BCyR4fOkrBP4SoUAGkDSVA1FVtRo+dnZdrYYWuXQLoo8zAy2Cprw1Gof7UEuqONFEtMys9kc1u+umzNxMiEECuLxrYxtZW3LtU3HUMfYqw29YCQB3VSlqAGm2xEjFERdy1JXrat4fGVaQfk4DtXsoHWUsQX6Sg1BVVQNK8ctP/A9rwU51vbqKByGvu83sdkYHgW4wgD9x3CGg0EFbaj9xKxm0t+WA3VjeE6O1dxNvtHnyVJgZdUxixBaqcpQPeCTDhJUlcxQMTDQOAi9hyZZxk1LkU8/asDzl2pDaSn1WniRAAmQAAmQAAmQwJomQHGypl/PWhvcwlr+hJWuUiPYvnfxWFXZdDmMJ9jbNz2vUOkTfJCvvtMVPqwT8zJAGV7g/GQWm0kxTMYa9kWVpOEkbZgaYLXARlwwOCCMAvVSF6nUqwtaAD9r6rHaSTjVO2p3XqzoVQ8mFvlKGKAC9MT8Kl8/SuBFpppamBLSnQtVlR9VanWBYorhoKV0SHqKihInuLAZsQrgSLc7xqH2uJkXOiiHWxxLAumCbKVjlLua8q2C+xV6g/iAKSRQDmaZQObaMt+WxUg6vnQShNnDBtXlgdXRE+hVDTcdrXbZgsEkHYn6guI5ftPJ7Uqkrmgp865MJkmABEiABEiABEhgrRGgOFlrb6QnxoM18vxiGH/Ax4UbvYzuLJHTW7WU1n/4RwIKQ6mH9EotGSqly2MFrxffqQrBQedOWxQaZmAjrgPKAjpDxbUoIwvUR9rA/BdEjhINqY8W0rhSmYBmoQpUo3AhSyum5bV8UOt4NKLc0lLjhjKhdLeJNB5BnKBbKA7LxI7J6Fg3rgwfui0tFNJweVVeZWN0SrDMCx6kdMsprHQ8aWw+ekOOEjSwfiRQKTaCRlJBAhWXumWpJlTzauhdV9etGjBuNT2V1tqvq7DOPDHjZHfzUzrZY+aTAAmQAAmQAAmQwIoRoDhZMdQ925HSBHr9ijWxWlljJaxX//juzKqzUNY56latppWe0FeqIVJrw3zG8R+QAWhIF0yDKNCHOpMQ3l9aDCihkC76Fxo7XlcJk/SChUMn1NhUSp0Xr00087YS/fj4tzrEUdlUUkVxPFuNJB1OeqQiHit9BdODUj6LLviXpf5saX8qTOXEprrLz4NTbatJwfqhekEIP9zG0oS6R1/qUao6VGuLujvVrTIcLbnQlIaielXNpazgHaeg4YOHac6SiswgARIgARIgARIggVUhQHGyKth7rNN0q6d0zGoFrJbUCNOGc5Je+J7hZNR6GGthfC8so9XavbM2XshEHhyWVIRKGiiR2luOV1FNLH91Gppfjqfj1EXnRYUerf5OZYNWB8s0p4QErvRLlV9ouzPfTiN6jywUUTnzUzg+k055PMSFTmGQgTLRnmGokNaaLz9vAEI52ExSS4jSMMcbS/3i0qf4QsVu5YOck19oAh11GtKDWjS0k9fmExIgARIgARIgARJYQQIUJysIe310pSIicHUWuy9sVvO100pqhX2SZrQxAUrmjJfgpxvGwkL/nKzKX2gjaqbzAgYmmBOHitsFCEh2+ECWaDmH0trq0V1tvrXurFOkl5p8TlGYj0iABEiABEiABEhg9QhQnKwe+3Xd89Llu14h42/4Wm9os0Cn2LwIWZAQ55aN1ga6x/mOzm0HS1pDX/rSpo9TdIpHHRQdZaLrLrqdb1G3vKBn5jP5gwRIgARIgARIgATWBQGKk3XxGtfeJLDmjtSSXBkDUtOAOuwQ10mW6SiTPl6I/0gDJM7pAhyNzYfCoyN0pw5medHYTl0TYuN4ARXUgu66rtRlK/UH01YUFdOjYvTnp4sfx2vPV+smcWJjXe0ySQIkQAIkQAIkQAI9T4DipOdf4ZqcAI7/iH0/DEIvjnAEoWGYmaydMU/cb1gv2lXMepL4SYDTQsIIpxxKHFpima6hTnyfj/44yznqxX4ayIFwD4wHh5PgRHkcJ6I20dIGikUK4oX3iIB5deAJTpeMIxxBqbYRU1HvyE338UWDhmm4lumYhq0ECA66t7CtME5VxIZkYRx6qB3hjBRlPErj+FFVjQJbEGOYqGuZqJt+6U2Q9dNu3fLCB80aJEACJEACJEACJLCmCFCcrKnX0ZODUUt//ef8rt1vsSYXwt8yFhczkR+K2Wo4PefnsDaH+IDk0AvrdLqwM0RJ2Paao0Oir4iFfTIxk3i+mYarn6hmXiCejm9VapTAWh+N1yxRMw1IgEKSlKBP1LJfP36BjUPMdLtdpRsZh4bwN4xGA3kcZI8ZKgTzH8w4Fn4Q+m2/1Wp67bZpDcZmP06y1waTOKwNFOKBkuU4EdQcxpoSwpfSTmFkNH2v0QoaTRnEBWFmDBPKSsHRHmtIaN+wFzgJFicBEiABEiABEiCBtUWA4mRtvY+eHE26jlYjT92ZVCS3MkNEGdu/8Sp3zyWZlmc/8Gj0xTtrjpmXtgODSLffkvL3SvxWe/amq8euuixTbzS/fGd1/1FsCKwOLzy+UdhZocF4cMy7b0QTpdzhcsGfrI3Uw22JKKa7IcO+cVatozL8snBMZCabvPaG/LWX2mbgGThRMrWZwHICc0gUiemZ+qGDM/ufP3T0yMRMe4uX7I6MIVg+bNM0w2NXbsm/8rrRDWMomZ6/ogwmSrlgh+JaMzk6Wdm7f/rJ58OjM4UwLJmybJg5dHCcJE0oZ/sOWZ8ESIAESIAESGD1CVCcrP47WH8jSM98D0Ov+tyTj996ZXlky06v1f/v35hVewTj5EGs5LsODYzjwPcqrdbE9g0DV+xsHDr4zMyxfTK52bLcRFrwkHrRfHQwOoRSareIgqC1c3D69pe3Ltlp/P2/731+djCIM1KdhPhieug2m6A+phyFrVi0BnImenG9h6UM4MiG81oQc5LgxHgjDrdF8ZWJX48mx+U/ffnZRw9nGqFtmJYhXTt4dsRq7SwObSzahjGHY+IFsrWZyTCC2PB3yda12cn6ZV/4SuX+JyqVZuwaGXjLdWRVGrLzYibCOiRAAiRAAiRAAiSwdghQnKydd9H7I1lw64IpxISmkPHRQ0+0KkV31B7KJ9v7jtU8P0k2C4HfunnJgQCLOK674sjNl/gbB1pBc3L86NON2pzMw7EpjNUOX0t/RVH3uMFggRoUhgor12H1C5n4iWMS1Va8hgh9r7pri3H5ruZQ6YgIayK6SIiigGdXAv8obaFZJFPUbdoTjDtqPl3Nxt0jQKdxgon4Im650somB9qzX//G/90bSTuxnFiakToW0i8WCxdt237xti2jW+X/c/tO5/8a9z35jIwHZDzkiqmcmCgY01kj+/Cjd+4/dLDehj7JggLsTLG0Rsa2Xnzpy0f6xt54S38Uj//vA+NRPChV2AwG3z2wrjEySQIkQAIkQAIkQAK9RmDpyq/XZsDxrjYBbaA4cRSI4sZ/VrshDh+a3Tw6u7Fcfs1l1W8+NNcIs9KAvcKKEsOUsSkCEc2Ujad/4Ib+zQPekSPNR74fB8lIxshEMeIr/Dj2whgeWUp0WIYBDyjDcIw0VuTEHrGMD6LIb4Uoq4QEtsNCOdN0LQOx77GIvNCvlzJeOVtx5f7Ia/j+dGQMOhaiPmxVPImCJEIwux/F8KuCXFHdoL4Ja4+FAScSNh8VRIIIGZn4KI9eEPcfpZYXAw8wWhMB/YElmrE3+fAjTzeMK2J7IDCcWNhx3My4xvOHpmtTtddcO3bp1h03X9n2m7OP7Z2TVt4UDZlUpXAi2X/wWPzdJ4LJWs50hiGOYGhCH30lY3ymcuuttYs2ti/dPP7Yk3LGayZGPnWRozg58XeBdyRAAiRAAiRAAj1LgOKkZ1/dGh54ugEWQktcaY49+eyhbRsbl+xovXpP/eHHx9vtEWENqfPlsYWXwK5WvhlOFTNPvvLy3cWif//D1nefGjCcjVHs+mEzSZq2GeZzlptx4jDyfISUJ20/a5l9qWpASApUBcwluFpxVJHJXF82l8kofycvCFstzw9dP85jKFYyN1xsFNyKHU9b0WQpEwxEtZpfiWMtdZpRWJdx2zSTvryTdR3ok9D3I99L/EgYZWH2SZGFCIBUKmYC22gEfq3aqBfz2UJeKYRmy5uqzLg25hVDPxlGttLaWnFeGxoXBXEuFBkRNcNm89jUk/Vjjw9no12X7Lh2d646M/vUs16Q7EK8CgLsUSwQGxriislg47g3Zhs7pLAjYcVB+8CB2uFZ/6VXNweLB0ZLlZHy6PSxtkigrBZZe9bwrwWHRgIkQAIkQAIkQAKnI0BxcjpCfP6iCCCWQ8qMtDY9/PTExdv9Ky5uXrajOpg7Nt6qRRAkiJeAq5UUvucZcaXkToyUMu3kJdMV8/DMwEB5qOZ7IjjWn5vatiHZsX3j7p2D9Wbz4MHpvQcmnz5kB8F2mQxatqtsGrB4hO0onHDF/r7csRuvvXrn9kHHsSemK089N/HEXn+i2hcLJ+ceetmVxq6NlaI9kTFmr9rdt02Kx/fN7DsSR9KyoiNWcChrN4aGCpdftmPX9oG25x05NP3cs/sPHDjiG7viZHdiwY4hfb990UXOWKldmd73yFNPXLvrsiuvuEya7hNPT3ztruekO2qIPGwtpgEbyJa2cZkvXuKLYmwgM4hkyw+HDsz4f//5r/+/v3Tt5g3xltGpQi6YTO0wakNl6JCkGJmbAtnvGVtj4+IksWF1MZ0o9KarrfHZuUYy9rxrNF2rACNOLGJLOX69qDfESiRAAiRAAiRAAiSw9ghQnKy9d9L7I8ImUmkUelZa2441W8eaVjNqDhYOb9gon6pHrSC0saaGj5QpW0GwZbB00yuvdbIH73nk/sf3bvHlmI/Y8vbsG16efdW1/bs2z2bco1l3HMeGtPdElYbx5IFN//KV9r7xaWH0OWYRYeiN5vTlW5tveEXxusu9Qn486xyD7PGi5LXXxoent335//xv3vPUcP6xH339pdv6p/qsKUf6P/iaIc/1/uPOgxOTszMN02rf97Zbslfv6Rvd6GZy+7PuIfhuRVcEbdhWpjIIXn/4iN30DeyqVW/Xbtqz8ertldrUk1dueviVNxUHhuCA5m4fqj77xNP1MGcmiCHxYc5B6H8icrEoRCIXiLyFHCPvmeFk5E9Wi+OtrWPG4XKft2GscPhQgL3EEH6DN4/jUeDIJeEqpkLdlVUkCiG/Aq8dFvLWUH9fJpf3g2q90cAjSx3SMi9NQHw5/7re/2XiDEiABEiABEiABC4kAhQnF9LbXrm5YsUMhysL+iE0tzxzaN9jT+697frqy152zdOzxcexFk8X4gG8psJWf1/2yssvdZzxvfv2Hp0sZpzNIhp/3fWbbrnO3bFhrlV5/O7v3ZVEDazCB4c27tp9/dWX7Jqt2t+6v/bswbqd3Ra0nn/JpuhV1+Su22MPFg/d953/mZ46grNCLCe3a9dLRrcM3PKyIRFa33/o3m9+8zs3XJpcsaOdtWp33/21mjy8b+8Wr325aY7efF355muCLZurk5Vnv3bXN5PYg7oYLpd3b9m2Z/dFrTdsib7h3/vUvsQpIqy+4Nobins3Z/cPl/LN5ve/+8B3TKvPi4Z9b1oaPsRCqhegFCBObHyEdKRhI7pfBfebI5GVVGLzwGS0c2MlXwg3bxm+91CM2JXUBIJQlrm4vT9uTfm1mbY/J2NHCCdrGVftHLzxmktGhoLJCfPg4WSupk5jhDsZnbpW7peaPZEACZAACZAACZx/AhQn55/xhdsD1ukZ0+k/Ovn9Z57d+7prrYsv2jl0Xz464EUx9EkmDJuW0R4o22PDo2HbmpqsNOutjNUqyGduvSZzydaByYnKd+459NCjs1HswYowNGBPzR159S2zL7/crM2Mjx/FkfJ54T/6sov7b7hia8Z177pv5q7vVGenENMuLbu970jlLW/1L90et6vhY9+tf+v+xkBuYPtGbATmP/Dok0fam6ZbO4LEKRXEza+4aOe2Jycm9v7fA/u+eX8dJguoq+Hi1NzuaKy//7JdV77iaHNudmLvREVGBSuuusaEbVWFGL37/pln9jesDOwtsuFvMNyM2j5r/vQRdXxKus2XsoVAXEG0xCIbGP0NsfHo7N56q+bmzMHhAcSxIF4+kYiwbzrm+KVbq6YVz7baoTmtNiGWrmtaW0ati7f3Tx+bePz79UeeLDTbw1YefeHf7//P3pmAeXKU9b/v3zn3zM7O3rvZ3RybEI5ACAYIkUtQQJBTUQQRFfHx0QcvFNFHxQtURPmrCB7ggUYQRYRwCQohBEhC7mST7H3P+bv7+n+q35ne3v7NzE52Z7Mzu9WZ9FZXV7311reqf/19+61j1nOirZSL9znTNdcIaAQ0AhoBjcAFhIA2Ti6gxlxxVVGMvOB5jVZ89Ghjenqgt6dvoDequPUgmHGccuBPjQ34m9aWPdt7ZHdzasJiSnipOLNp4JEnbGFZ4JG77z70qS+0ypWnxXbBiMJjexr7j0xt23j31VeYuzZO3tHnPXR8uNe554nbRreOle7b3/+XH2+F/nWe0+tant9u7729tvPKaJf9aMHeUyxvODy1biYuhc5U5Dw6E116tPnserjNcoeHB0uXXrres+64454HPv3l9rTz8oJXjCN76tjeZuOBgZ5Dz3hW58mX2hMnGvsPHPaMnaxKbJtBsxHfea/9mVs2zrSvcorMmO9h2JfD9BJcJWptYowpRq4xISQ5M8pNDdoyQssMDLdtFqfrTNYPKpViBe9JwAJlGCeg1fScY0+60r3qqr7A7gtt7CiWDbDMkBXHpoLWXbfcMXXPA4WDR9cG0dooYiExDKE542T23xXXCbRCGgGNgEZAI6AR0AhoBJaOgDZOlo6VTnkGCFhMDY/jvhPTI3c/7G69zNy0pr1leHLP0ZbllNuNh5967dB3PWWg0a798ycf2HN4QxD39JWsa5/QN1S865t3HLvnjubMhIN/JLaZQB/5rP9rTNz5jb2Xrh0YKQ+ODW68+8DkrnWt0b59Rqe8/+C2hw5vGBneVHaGQ5PRUO2GOfEvn7r7c8WvRv7+6faV09GVTSP2rT2BcaIVb2qZV7SjwZ6SMzbo2VZwYnLy+KRRjy4xStcHViGMXNfYd6xVuunmW3c9sbN+JNo6Ou6Eh51oE6tqUatmx/jOg41G/Iy4OBZ6vWxKEtuTTJhnw/fUmzEfXhgpthk7LT9gyWK13rKaPu8YPpE4XFjsy5lpNKebDd9oxW6VsWG27VQK5b5i78BA77Ovv+qyKwc//rnD//6/zVY7KBRdbBPZcQXbRwLzFarjNAIaAY2ARkAjoBHQCKwOBLRxsjraaZVqCRG3zCLTTh6ZvOqmLx15y2bn2l3N2olH9u1rR3ZPOb5jy1DfxuFour72zuNPH4/Xt6z1QwVz68YxJ75z19Zw+BVjr/6eYcstxlg4LBccts2oPth3fGQwaAbl0eFBNiUZGigXCtPN9vj45BgzOmxryDD7ItOLrbBQqTbZAL7TE0fTUWEkbJZCoxYZR5iqzkSOOCpaYdTrdNb2Ra7pHjzuTE71xcaoaQ6EsRcaHrqzr+KJGbMRD7vuo2XnsBkdZ+1jxmrhyWgE5r6j07Fdtdw+w6qykz0z9nGNMJQtMRPw/GAsWKY6m+I2oREJsPZvHIbVUslz3cDv1Gp12+pnO0UzLhjxYDPY9uVvHbv9volj0xEmGZuckMk1mkW7vm546vteWFk7dOCGp/fVzdF/+NKMW3Ac5CfOE22ZrNJnRKutEdAIaAQ0AhoBjUAWAW2cZNHQ4eVFgMWkmBTOaWSqc8mde73pmWD7muNbR/f12M3J9vFNI7WNw424Xbrzvvq+xqWGt64TlWynMTQ46BhB2QtGh7w1I/1GsmQwngETV0NYjc1CxNq79sZKZcyyw1Kp6DqTfqcxU8c26AlNFsgqGrGDCWA5Baa2BFHFMFqh7flxM1LbidhMKEnsE8ZfsVFjWPFix3RnZsxaq6D2jDdKYVxkDd/AMJrx2PH2dJudUqyO5046dgM7Qy2kZVp+ZE7X/cjxTIMVjQuJhYBAa25lX7UBS/eByWLH7Bfvjw4Pl8t99frRg4cOW8a6xMJQq3uFxtqJ1rZHjo4fmhyxipujUAFoxC07qu89NmEYn3nNi73Na6/bvmV9bDLHHh3xEelDI6AR0AhoBDQCGgGNwAWCgDZOLpCGXKnVYJtE1pSqdqxRJng/vPfgtsEDawamR4fMA3tPXHXt2g3rpien937tm5ON+OkFZ1gNdYqZLk8e58jR+iOH6g2/Y7huspUH08kdI8LrULZdZ6pT3MfWJnYUBCZr7WIiWBa7ztOfIet2YGAkMI0jZJ/3OK7GcYG56YFaEYvls9joHe8FKdmJxWWzRSZ/sAG8bRUsBoPFDK9Sw65IgPMkiMqh2ReqXIFpdhyLmSEYNpgd+EnMIGSDxGSye+LfUMOykunpFI0Bk7SImkeC4ZG2Toz6bPVotIaGBkrlvqPH9u3bf9CxnugoWwb7i33oq6YzGtvl2NlgF3YakRXiwTFaRjQ11dn9pa/+/YufMTI8umuw1ywVsP1k3TM1xUUfGgGNgEZAI6AR0AhoBC4ABLRxcgE04gqvAnaDZztV3+y59fYvXr3x0OBgYfvWgS/cNX71VVetWbv/vvvvuuvBKdf9boOlh42w04kOHp4IxyoP7Kv9xxfb39nTcoql0HYsjIpQ7T7iWna5ZIdWeyJshObAsckGZk9PX4U9QBjCxWx1ZpYzFz2Ig0a72VcOXLujRk812D8Ey4IhUIm1oKwHM7Lcmh8cmcQmMkcG+/orRTMOGD6mVjrG+lBLinX6KsxJZ3t60w/sIMb+Ua4TjBBldCgLhMTK1pk1Rvh31jJR8YnzRJWpkiqDJQ7UfpHTg9VOT2+v4fZN1Z0jxyeLnum0RVSYGDJkYQFixnSV8f5gOClTyorsuNoJWHO4aRkdzzaqOH2wjpgyn5g1Z9oJThpOZypB59MIaAQ0AhoBjYBGQCOwbAho42TZoNSCFkbAsizP8SoPPnTgxLGpK3dd8dQnXfr/brqnUhlpdsIjE4frrbbd04vjwrM6TBTff/Bo8OTilh3PWr93zS17q73VDaYzgIkTdRpm0LjmSYNPu2rw+LT/1btq39o9ffRYrdMu9vWMbRgdNsPDhl9lNFdoulHInvLjL71h7KlXDTSbzU/894lv39/A2FD7FmI2RLhMGF7lslfj+IzFPJKBwUKlzMYrNSvoWI6tFs8KpwvG/q2jJzx3UyvorQdjgTHFQDDDZGDYLKdXhlBql8zVP7F/cL9EFiO4mD2v1uiKWJGr47cbjQNrqkdf/vxNw0PeTGv4yOTa8VrN6WFeu8wZQRrmBt4ZLvlDunIJYS61252o1Rwrl13XY4o8qZrNdqVUYUY95UvmeQeSzSnV/S9VkHzdt3SMRkAjoBHQCGgENAIagfODgDZOzg/uF0+pCb82XNNyHNef8SZPuH6zwoyLZz9tfana9+37Jr7yraHQ7rcteLZddMJWs3Hn3ffM3OAMj2zYvHVD752do7V2bPtw/Sisr+kJrr928LKtk9+550Dst4r2QNSxTxyOmpvMtQPFZ+5y79+//3ijHdqlKK47Tn3HhpFL103s2/vQ8YP3mvElRtiM/GZkhlgfjcZMO+7xO/ahCevYxOTW/tamzeWNY6Xb9h8qlap4SMzgkcvXPfATL98wMhje9WDna/eVm/ZgB2+GWgqMqSCJ0yRpyMTVkoSS2ob4R5jnPjN9fOZYwzkUGVOhWWzHzUohfsrO+ManDl575fH+nnVf+0b0uW8wGX+LbfcYJhNXGIpmsKzwdK05Pl0/Nj5u1g7jBmI9rzCqF73GjrHqa2543cjoXePTzYNHJpttr1i0MYSwZdiLcdY+uXg6lq6pRkAjoBHQCGgENAIXIgLaOLkQW3Ul1slyLPwDa+59YGpkJBi9pO8FN2zq7avcdmflrj2jhrvONMu4ABwrNAPv6An7tjsmrnxyge1HXvYCY/f+9uEJbhkD1d7NY4VLtuLbePjosd2TE8WCPWJGa+6+b8/wcHvDjvIrX7DxzgdrjxyNGn67t2KPjY5escVqTj/4yANf7TQanrOl02p0Gs3e/tKzn7Zj09TGex8t7t7fOToRfeWWuwdviLdfuvMFwdqh+/snZ+qu6470VK/avPbqnfZ0p3XnbuOuvUNxYU1cL7CTSYTzRI3aSvwmcwOjEhOFXU0YEmZUqqUXPu8pRwwWLB6KGKNl24blFgrmjk32E7a3x/r33HLng1/5ZnDfoS3INK1ysq4X26IwHaW+Y2uf6QxPN7HZKjhwLEvNwCkVesZG4ic9Af+Of+/9we33HLLsS4lPfTiqzdFpTpmV2AW0ThoBjYBGQCOgEdAIaAROh4A2Tk6HkL5/1ggwTimZhl6IvEu+tXt8ZGNh69XF655S6pito5Pe0fqaamWNpWaoMxW9YNn9fnjF5279VseduPSy2ouuHzo6Ye89NG478chAZXDAazb33XvvnjsfmJms91pFFtfafsfDzUKl+ey+I0+9bGjbpt79R2u1VqOvtzi2xvM7h27/zgO33nHELmwpGeWp8ZmpE5M9W4rPe8a2KWPgc1/r1Ovm7kPWZ7+2d+1I6YpLR659yrodO5yDhya8orl2cGC4xx4ff+iuvQ6btBypbzQKw7EdWQ6rDLvMBrEdNRyLkVdqoBhDsZhK7+DniKxCPLyu+rKX7Jo2h32zSALGXjGrngkjYdBp1qbvPVH71BeP3r1nXSteX3aYr48go+BEBadeLRx72q7SEy7v99nPEeG4RPAoqZn65G03ao17j/V+/c6pux/qFKm7vfieKmfdclqARkAjoBHQCGgENAIagccXAW2cPL54X3ylqYnhDDtiXSzWoSrsPFCzDjSqbOQ+UHnglrvbB49VY3b5cCrM/0i2BCmY9mhQeMZdB3uP/Mfu5x06+MLnXHLl2tLOsSYmAEx9aqbz8c8fvuWuwrGZrbG33bJH2uaVh9u9N9/2wJ4D//ral2zZuHl43WXME/ft0G7VWzd9cf//fsc7PPNkp7jZi4b27pt6+P4DT9lcGFlzpGh+Y8tIz6Y1gwdPDB+pr//Ax/ffeM3e5103tWNDa/s65QUJw9Lhw+anb3706/cdP97eZXhbsUvsQs1win7IDHa3VHanA54g5a1QY6sMo+i5EXP641a52O4tPlo0GqFRjiInCIyZGXt8MnzgkdZt97W+s8+a7myIrc2OO6gMmzgsOFbB5Txdsh90KlFgFEKjEpksbaymlERtu16LDxyY+cKtR+/ai5m0oWluKngVG8+JmqWSzLwnmXabKDD0oRHQCGgENAIaAY3AKkZAGyeruPFWj+oslAt1d0NrbbvgfvmO3Q/v+VjZ+OSJzvcdrN3oFjaw/q9aIksxcSuAzRsbrEJ1JnD+75tfffCeTxtu06v4kWWyanCjUzk4df1k51mhu91wBkOjZFhrzUKPH3oHx2v/9C83m96EU5xy7HYcunHb3l+7dsp/ZuRdGTs9dsQGKetv+45x8JEvmuVvsQrY4Zmn7p/5bsvd5Nhb6vHA/9x+7wP3f3Kk+LVKkaWHw3p7eKK+faqxrWnscIqXBOZwFPvVovHRf/v6F/77v6LO3onGcw2vqNb/ZXAVi2a53vjU5D/8+zf/5+ZP98b/FduM/mLFLdeMHDajjIORwB+a8rcd969qmFdb3qBhD1lMNYn92GhHzvCtd3x794Nfjp2ZyJ5mwFhkqlxWxFJdLCvWawS97c7QkeApx8InNO1NpjVi2bZYJtINtGWyeh4HralGQCOgEdAIaAQ0AgsioI2TBaHRN5YFAYySxO5QX/VDs2S5w/WovX9iumh8T8vcFRmjrsOMC7X+FdM1cEIwviuyenFCdKxdJyJzZmYsNBp2Ta2xG0VsaVJuGFcFznamrxhmiUFP2Ce2hVtmcy1q721Uw8a0adcxZCzGiEVWw7gisC41rVF2JGGpYt+59Fj0/NrU5qhmBrZZjy7pmJtdr8e0inbU0wqjw9PRTK3fJasRdcLeTrghsjaF1lhsDcRG0TGcnoI9Wd/QblxrW7ti72rD7DfYgZGxV2wGb1Vid2iytbXTvr5kjcwt6MWQNjBwrLg3jnvb8dq2tdWxNgAFpktssumKWvzYd3eciPzp+paAPewt3ESzoFns6ggqccmMK1HU13R2Rs4ltjkYmcSc4iiZw3lZGk0L0QhoBDQCGgGNgEZAI3B+ENDGyfnBffWUCnlOjIuz0FjxZiZ7s56uaRsOrBp7o9AyN4XxiGEOWcwvxzcABU/ItprhrfaAd9vWRsOqtOKdscFKv+RX/gnD9CJzTRwPs4+72vSQXUfg/ey6aA417ctDA8nKEUGB7LCIxdA2h0JjxDCY1wGZNzv2hhmz0LIuY4lfzI/Q6g/MNSbuF6NgWSULZ4Xd3zQua7BPCuXZBcNiHa2+wCjhz0k2bTQdh0dma8fsYZf30BwJ4x42dlS6Y1yZBdsZCI0dbXMgNq9O5qeravFHBS0DL4raETIyes24V0VgkqmxWOxkYnXsjTW7YhuXU1lMsCQviKfmB7tPskRY0beQ32saRTPJq1KoxYaTI00rl8mZMvShEdAIaAQ0AhoBjYBGYBUhoI2TVdRY50lVtSRV3j6B9YZqFNZSD0mvPAzshWhU24ZnxUOKrBsuG6jD0RWFx/RQ8lQwYnxX3McuhKa1JmHqagfDZHoFqTAVYPnsPaiyRGoPdSh+WW3obg7GzDxXLhjliUEWe8MHauZG0s9NDJdeXBaOuRbbg8khjDSLYyasM4AK60ltdxiYPYExhlhKQwfTwPDAdrKwPJCIFYTMyBygCpgVkdp+3qMwtXQXeZT/B0/IkG/0+spAUjor60FVkLOSr8aAJed0ZS2sJuR3jH4mmSQ7SKJJHm3GjKn9TFCPoXEx2irgEyXVXJekBCLUgsLdg7tO30YJ6Cq/PjQCGgGNgEZAI6AR0AicbwS0cXK+W2A1lK9W24INK5adqMsWgbKxxmPZm1wNYJo9YNHKLElMklmerVj/3CFWCFxfLcqr/BIncyotYtLiqFCpFfknQtkBirtH6paKTgyDJIivJrWhsEiUHWH6yt4QmeQSvfCyEIUs/nWVXCWE6s4lSIrDo8E1BZGL+4n+ymjAQiB18j9CuKtWRU6Kn41MwklWJUAFslZEooqSyX7vkbKs5jkw4dAnUqZdogqCVZHqSEVhS0kZooncleSSRonIaqSulPdpTuRsDv2PRkAjoBHQCGgENAIagfOFwByFOl/l63JXCQJq6kNyzFLjs1JbceI5Dr6gvISFC9nOWi4LaaH8DwsodbIIZM4lS2WevKvY/4JCZmUnLJ+CBI5s3rRwEbKQMkmyrnyUq0wndaSKJVdzp9PCNZtwrpnm8ul/NQIaAY2ARkAjoBHQCKwmBLRxsppa63zpKpZJSrfTwBxjPgO9uuj5/DKWmEwyLzHx4skWv5tquXiyxe+mQnKBM8uVE3LqZUakuHcwXk61XxL3z6mZ9JVGQCOgEdAIaAQ0AhqB84VAyjPPlwK63JWOAPw2+TuV06J1hviu9DpcHPrlbcV00N1cS9GEp6bBMumyVi4OrHQtNQIaAY2ARkAjoBFYmQho42RltstK0UqZJbNWCbT2VPvk1KuVovHFrUc6/wQYxA7hPDfBZs5GURDpB//i7ii69hoBjYBGQCOgEVipCOhhXSu1Zc6rXhFrYAmVNS21SG4Uqg/sTJxOIlPWK3OyJfK86qsLP4lAap9I6zBvPyKkJvyrPyti/eKQXVmYUE80a5BpD9hJ7HRII6AR0AhoBDQCGoHzjYD+gHq+W2BFlo9FInqxhK3jOkYYmGGrYLaLVssMG2bss5KwZUT82dnP8SuyLhetUjSNrYwP1iYOO0EnilkMDEuFdY3dDlFqJ5eLFhtdcY2ARkAjoBHQCGgEVigC2jhZoQ1zntWaNU7Mcrk0ODgc+G07nOlxpocr7aFq5Lfrkd8wo7ZpBJbaLUQfKwiBZBxXYnYoa8Q3onbgN/gbHOjprfZHke0bVpONHsu9Vrmi9FZptZmyglpQq6IR0AhoBDQCGoGLGQE9rOtibv3T1d00yn0DxsYt9YNf9gqNquuM9fZctsE7OtU83gzavhdZpcBmn8Sq2qw9PzxIu1ROB+9y3p+1LpIRd2xLo9bgMsO6HdYco1l0Wn29xo7h/qGB/jCw24Hdcvp7eteY1b45FcjOn26yOTz0vxoBjYBGQCOgEdAInCcEtHFynoBfFcXGljMwXNh2xZGvV3rYDj2qrSm1rtvp9LTC2+87tP9Ysx5X6u76mrMusksGs1OSadZqg0aTvT5gunJeFVVdrUomrk9MktiKo0Atz6UsE3a3j4OgGBzujw6MFOqb1la3bxna4TpDoe371ozvWkM7rN51hoPnRHyn2ixZrR1A660R0AhoBDQCGoELDAHFZC6wKunqLBMCyVf4qBbX9wa7v7bv1s85M/sLxf5WeeektX6i4U11iofqvbceHrltYtNMjP/ENW3PsYyCbRJmo/SQ7cxNtcs7gmTJLwaLpeMICUvXI4aJERzz9kTuJnrM1ikblqhU4GyKU9MTmUsgErKRxGQvmUyT2cw+lbqkAHK6NSRnNjJb1mmFdmdMY4CLWSWWmt3OXxAHnY5pNEMmlwSuEbpxcP3aI08b3r+t51iv26l4nUq4r9B6MG4fmbTGLnnej1Q27DLLY6bVq3RQo/i0fXLa1tAJNAIaAY2ARkAjoBE45whoz8k5h3jVFgCLxgfimsUBd/OTRkKjcd8t/rFH7fr9o4X9A95A2+tfWxotlyvrQ+d4PZiozUxON2dqTTL5Zsm3eiOrx3bKoVUwTewVvu2bybbwsZLLXG1li8wS9Sg2w4VWjcqMNkp5+TJC2i1ziZYJqnfnXUbF1NCsxGrDFTILk7Lf5lZM41YU2nHLChpOWHfjGTeqe2XPrXp9PaXB3mLZs3eVapd6e9daD7txzWrP+O1pjMfKpmt6tzytvG6XVVxjmIXZ9de0ZbKMLadFaQQ0AhoBjYBGQCNwFgho4+QswLvws/I13THsqtGzvmebazul1v67jan9naP3FZzxottXcGpuf2HMKU41o6l6faavUasHfmCO+71H/DVH2/6434iNnsD0WI/YsqH9scPHfi4YBKbQ44TBoj7bw8Dh+sLCU9LPZdavx2V6a4nYdwvMCcldZsUuVFZOpmTJJs6GJXEqNs2bi08TJAGskchRdVVra0WxChAfxnEQWSzqrNydUWhFfp9bGyjMDHmTI+7EgHO8WHZKJadaLfVXq0XbGoofHPIfLLYfCcNaFLeLQ9sqozsrY5e5m642CqOGVTQMVztMTkVeX2kENAIaAY2ARkAjcJ4R0MbJeW6AlV68aRtG0bAdo8cp7+wpj20NDt5xrDlu+b4Zznh+e9BtVKI9sWPEA6E5CHUud0L3QGvNQzX3oSlv70x7IrSarGQbsVWK4tRWBO02bPXF3oxMNzbcwHQM04sxYPARJNuqgAn0nNFgsPLZ7VbmYMpwesXZuw41Nok0ciu1BHLJMkLUne5Lss8nPCfm5GVX4lmTSrk8knuZIpSGafxJEVgJahI7GdmVJLDjjht3bMOPzDCOfFYAVgO42KSEP8PCD+UasWeGm6q1DZWprb2Tm6tHR929BQf/U9tUi3Q5Rtuw/aNF44Rl+YFXjL3e/l3XVdY/0SivM4r9hlFSZme+6ll1dFgjoBHQCGgENAIaAY3AeUBAGyfnAfRVVSRGBN/X+cOOcIwBBgYVxkZHjeOHJh+8a+rh+9rTJ4rFR7yi4TmBazE6qxoalXLpkr5qYeuGwabZPx2Vplvx+HT9xPh4u9WYmJhs1hqKP8dGx+oNrd7A7mnZ/ZbdFzPKyHYtDCG8BIrBK48Km3TA7DPknpnfCfXHpTDnVlFT8NWBOTObMPlHnTANkruzCeZ1FJAutS5m859SYiK763RqLuSrIiT7XIlzO7MnrqFEgKoRBgSHGp8lSqlcKp5IvCVW3Gq3pqxwygsnvWjSjBtx1LBto1Qq9fb2VqvVSk9fX0/PQKXaW3Z7onpP3Bkwjg/FD/f6d9t4VqKZIAjbvlNvxY12qzQyNrz9msK2nQYtVFxnlNYb3gim4JzPJFEl0UyfNAIaAY2ARkAjoBHQCKwEBPSE+JXQCitZh1narXbMgMPHHSOsG+G00W6EjZrfnIo7U+aBB6YP3Nsc3236047NZIdKx13b9DY1nDHfrPhGCUsjCH0/aoURzDlgoJLJbhuBMRWMnGj3H2r07W30H+2MHG/a0x2nHTmBEbmurfZPiRj9ZbqO5dkWNgmOF6aAF2z2Ocd5ALtXm5+HcehYiuczBMqwLeWgwS2jHD5WoFYQg3+TivtMeSFS2SFqIFmkvBfJzThi7w/HEZNHEiTtQYI56yG5zpyUKmr+RzJAjfjEXorU0DSMDrRUrhFVTmo+kVYNygqVKySQBKRG+SDylSvJJiPKVdxouOyXrNr6wvEt1RNj5QnPOtFXbbusLGCYtuXYlsufwx9XDMwy604wWQiOFaNDXrCn7bf9oGmXh6prLy+v3RkPrHWrw06lX+1nYntqeB7T3y18JhTFX9YykZpmYzLV1UGNgEZAI6AR0AhoBDQCjxcC2nPyeCG9WssRwgrhl67CUla2wcLBTmCXQjtqG+GEUemNh9cUp3earQmz0bRrM0bdbzb3W9Gxkm1XsCTsyLJD2w5wDWCXMP3EYl3i0J4yNkxGa4+1g80dbzyOpsNCI/QwTpTFwfpTQdhsc3SiENMGkyaMA9/3O7HPSCfl6sBACJmBgW2APDwSmB+OG4T4T9zYKsSMGYttDBIqkIwRc1gYmVqYtsPsGdOxME64x6ApP/Tj0MY6EP8JZzwYJl6IzMAxcYkkpg3SMDowMcKE3qs1fNWSWZFvGW3HwLBiRV/EcRdJ7MOOgWU5jqcWKjOd2AVAq+C5Ba/gYoGpYWtmuei42B2GUbCCPi8qmf4aa2bMPTLiHHDiwz2lGcv0MZQSCwzZZuTbEeO9WKMLpHyfddHcitkzuK1U6Q0LnlUaKA5s8gY3mz0jhtenrJGk4sk4rsKcWaLtkNX6QGq9NQIaAY2ARkAjcGEjoD0nF3b7LlftUh8CHgPFuTENlHGAOyWuGeGM4c8YQc3o1IyZKWNqcmZqulZvdDq+409bnWkrmImjqcgfjxNCnXz7L1iG17DXN6x1/NXMdQ17A26WjlkIYyfE58A+HexL3+m0Wy0/aHfabbbxCEOfCCwUnBDKGxIq4yRZCsz2Y7sdupFVaPhuYBR9s9yKirWgYOFCsazQ4C4OmUJoe6FdiC3XstRccNsI7LBlhO1O6HRiYpLlxBR/b7umbyvvx8kjmRCicOBuwfIZwobLxbTikuV7hl8wWkWr7cUtO254VsdzfJMBXDhvMMcozKVE7CGXCSO2YxcKRc/FOik4DGOz7FKh5CTGiRUHBaPB0lvVYH9ftKcc7TPDI445ERtt5axRXhkEeBY+EKffdHtDry8wy16hXO2t9vb3GgODRrFkuGXDrRpur3KV2JVkEFeiNQbfPHtlSgWplzZXTra1DmkENAIaAY2ARkAjcL4Q0MbJ+UJ+9ZaboezYB8y8ViO+sFICFQg5w3TjxL5omyf2RBN7OlP7m5N7a+O7g2aDCfGe5cCvPdNtReUOa3nZfaE1QCDGbDAwJJSNoCwByD0z5OHMOEUSL4QaD0UA+baNGwH/CiZKhFFheq3AabTdtlGebhcaUbUZ90z75fFWiaTQ+SC26x2vERd9uzITFqfbZltNerFZh7fPbQxXzFrHbYeFZKgXJJ3p5M2S6xdmTZW0pZgnoowT16hVXb/ohoxScxyrx/WrdrNiNwcKnbJR9+KpklsrF3zTCi0rwHpRrD9h/mohYHWlzjiQVBVxp6Ahfhq1BBdju1jNjHFqzUI0U4yZczJlmvU4bvrKHRMFDB8z7VKlv9S3vjSwqTSwwRjYYpRHDa+s3FlYPjLUTSbM4/5hshDTeJBPSZQrC6SltVEBVR1tliQg6JNGQCOgEdAIaAQ0AisCAW2crIhmWF1KYHmoCR/qD9aLrTLnS1HjnTAu5uKxVYIJoz0RB5OGj+dkwgiwYUyz0TCnJox6vV1vTk5MsTVKEFqtDrZCxJ9jxjYjsMwAy8S2Q0dNjlDrVCWbzjOZHGeFHWHEmBgojGvCf8GMD5dVwhLHS2/b6O0YfS2rv20NtYyBiP1UlHHDKLRqIyo37cH9tcJ9h1r7j8yEVqnQOXL5mtZ1u0babTc0mYyh3ClUyjWartlQQ7NOORKjSyWq499wzHYUdUhcMJtFo1aIa4VgvGo1vHjSNSZdawazLY7bESsAmwZOE0adJZNNqBYOn8CMmeWSjAiL7SBgLooFCKwUzGCygMoUnJ6S11Mp9Pb3W9Wq0ddrVPviAov/Ymo5hoNjpM90+4zCEC6U2CQeu4Ql0LgvLUOIgWqcxVtySjUyF9o4yYChgxoBjYBGQCOgEdAIrAAE9JyTFdAIq02F5Hu/KC3f4xMSrD7D84ehgjcg2bwk9mLXNu2yGQ8ZjHcK8bEkbJiJ4Ws7zCnxgnBnW9D5AABAAElEQVSw0+kN1BitKGJixYw5c9RojjMayp86FrRroT/NOejUiAmDVuS3EM3MEii4w+x2NS/eYYVdeLnNamFmyTMnilYJKyUwKoFVCRy2P2c6Cmq5fljumJUJY1MtGMCr4Ya+a/WXw71rgr3brSIz4plpj8GAZAwspo44UZvpHae2jKod/1tRi5V6TaMTRozdIkPLiRvsh+iGtYLZdqKaHfPXiOIOU0I4Y53gQFHz4NVqWhhnllcqe16PmgCDD6nQ4/DXM2qVhuPiQFRm80qmvDP4Sw0Asz3XdBzD9dRfso6ZMkOUk6SgJpNgUJlFmf2fwJ7VF81oF/4WORa/u0hGfUsjoBHQCGgENAIaAY3AOUFAGyfnBNaLSagQXDnjpcDTwZGcId+sQWV5iTuF2fCK2c8dzJ/AiIm8mD/cL2qEk9FhJv0Joz3OILGgdiJkQbCgFviNqNMwjSAKmBnP+LFYbUMYxbYf2qGvlvCKQpMp8mqSvKWmn+OwCGt+2PTDKcs/khSHc8exjKJlVzwvNNqtTstjuTDTrLLUldveXWh2oiYz2m3sHNi8Mj+UUwMnT0ZfbmAUWCz5xUAt31TD2NTEGK9QYDwbs+ddO2IuOo+TZ1VsDAamwrvKAaScPo4b254agObYOICQ4BaKlsusG6aglGyvYhXZRGbEKjJjpN8osaCW8oSo8mSKSGJjYNOQMwEKpHCSgDB/aop/YoEI/nPozv47b2Qujb7UCGgENAIaAY2ARkAjsIIQ0MbJCmqMVatKSoLTQFoV6D4EGpMh4dvKCJlLw79qDBi3sAGSP7tgFMpGNMKCxc5Qx2HZYuaxYAZgkxBQC/MmcnC8hNgYbaPFWmHcZYFen/nzUchoKUZFmVanw0gpjynyHTIq7wczTyLTY+BW5A1WzGp8hPkbyhDB3DEcp2ekL2i0sHkYAkViymAoWFLWSeNE2QqYJngz1CpforNSplBkUodacosZ7YVCgVFnBbXwFpJio1BSSwQ7HokMB18HA8KwUpLFjdUWLpgWRDqx7ZpYI2pNLRb8JeAlU9jnjBOZo5LYHxQkplPiJEkSKCeV0lkfGgGNgEZAI6AR0AhoBC4MBLRxcmG040qthTJF5gg0VD8l0hKYnaKdWCZYEWrFW9g525OIHZLYAMqTgWUiI6wSHwt1VTkkTEgdpFLeBCItBmmRXc1KSQZhKRMicUGwjLHbtIYmH4i/PnGsdeKIG9lRWCqMXX3pjc9OrKCkuFl5YpyorCcPdBaFEa404DKZIT9bF66pKZH8r3w7iQJJGkmgrBq8HyqJWEDJhHW05D9uMd1FLRemBCuvCOZNklSdZvMkGbOXxOduzSXR/2oENAIaAY2ARkAjoBFYnQho42R1tttq0nqOQ3cRabU47mxkYkyocOJhwNRIPB6JDQBbZ1q7pJszTsimNlZUq/QqJJS1IAdEn2gVlfxJJGGyM0GcafWFVtwab5gs2NXrOPWOU/ddwx1mcWS1ActcTrKpVXtTqXOyZ42TufKUTvwvyVCJAV84bjIGw6yfSKVBGvvXY0BRyJy9JF4RFYOIxCAhr9rvJFewFK9iM7N9ZiP1PxoBjYBGQCOgEdAIaAQuJAS0cXIhteYqq0vqR0Dv2fAs14fVJz4EVSE4eTIjBWae0PPZSqoxWBI/G6H+UeaCnHGeJGE5KdeEbNTIBu1WEDBCy2VZXoyegLW/7CK7tbMtyWxa+eekwZPKSQZrqStlVZw8Tl6o9cOSYzbq5B1CCMQOQUXlC+LIWDEqJrmVnJNanVpEJkO2Wkn0ydPJ4k7G6ZBGQCOgEdAIaAQ0AhqB1YSANk5WU2tduLpmePVsULi7sHapd4bNnwQi4eqZ3HN3cETMHcldGD9/+CyYohJinKh55DhSkr3rWZxYmQpqv/i5PIv/K8lyiSlG9EjOEpQkmehZudms6i56YdZIOkmSDS+ujL6rEdAIaAQ0AhoBjYBG4MJBQBsnF05bXkA1yVHz3OXJiooz4uR1NkQmbIAkK//iFhGLgMkg7CsyN4wKd0qy1aKpjJVTzIMFy5QyugZ9pdmzGbNhySfnfDzXJ6NOhrJZdFgjoBHQCGgENAIaAY3ARYCANk4ugkZexVVMibpYFhnfRnKHqSeLVU6lkX1OZK76nAWgtm1XA72yJsFicua5N68b52S6OXVPxpwaErXRL61g9j65UwH5BPnrbD4d1ghoBDQCGgGNgEZAI7DKEZgdI7/Ka6HV1wh0IwCNn7VMuIc1wER0KD+LDbcDJuK7aqKHmtmhJrcoxi/mQLeYs4iZT6Qq9SxE6qwaAY2ARkAjoBHQCGgELmQEtOfkQm7dC6tuic8gOWXqlb3Okv5sPJYJmyoqXwcbmLAMWOAzv4QZJmpDRda/UlPfSX5KjkwJZxRcWBh3pDzkpqnSQFqYxHTHpwl0QCOgEdAInAcE7rrrrptuuoltnaIoeuYzn/ld3/VdLDByHvS4iItkTy+1Ka+ldiHOritz0UIiONAhQWNeQDRQ9I1arfbQQw994QtfILBt27anPvWpl1566YrtM9o4WbFNoxXLIrAQTc/Fz2ufzEbOjuJizkmyTzu2ActvyaJfj++rNacz1czF5C6zOOiwRuAiQgBKQW2FbRw7dmz37t0zMzOdTieNL5VKa9asWbdu3eDg4EWEy7mpqu/7gAy2oFoul4vF4rzlPPLII+9973vHxsZoiIGBgWc84xnzJtOR5w6BI0eOQMQ9z3Mcp6+vj82Bz11Zyyv54YcffvDBBzGruk0IqkOv4+jp6RkZGVmo++X0ufvuu0EjSJbgxGZDMgdpwIezmxzI3LhxY29vL1dE0sMlTU7UBX/Zbrf37t37t3/7twcPHnzRi160YcMGbZxc8I2uK7gSEFiQ08+aJYmOkJ1k2S41qiudsKJW8low90qomtZBI3DRIQCH4IBkwJjhzd/+9rf//u///oEHHjh+/DhcBHID1eD9ysf75zznOVdddRWXQ0NDwj8uOrDOusLgPD09/fnPfx6GB6o7d+7ctGnTQlIBH06McQKhJEwzdXPNhfLq+LNH4LbbbpuYmOjv74fEP+lJT4LHrxb8/+d//ucP/uAPUBjzgC5Hz0nR4PvC+vXr6Xt81H/yk58szzIWBabyQtYX2f/t3/7tM5/5DK4A7DQRCBQcdE6KwM7Bfkbs933f99GfgYsY6bSkSYu+SALAWK1W+YXE7YnBBrArueLac7KSW0fr9lgROOXnhp89rmejkt9AxnaFpuHbbGti+Mo4UbF8dFI/U/IjeYqAx1q6Tq8R0AgsGwKwB4jyiRMnfvZnfxafCcyj2Wxy5rWKcQIv4V07NTX13//937ATIuHTv/3bv80n0mXTYDULeqwGQ6vVwiXy+7//+5OTk9h7r371q0FyXgKHZA4hxDQBabicN+Vqxu8U3Zelglkh2fApJS3t4p/+6Z+++tWvbtmyhZbi4zdcc1XgT63FfqDbEOBDPr2OZ5nHHP3peHv27MGigD1zSeCKK6740R/90euvv75SqcwLjNQas4SD7xfIRyYHAsGEy0ajwbcMOjZwkeB7v/d7X/va12L5zCvtLCPTNk0DZylw2bMDF8gDrJyXXf7yCtTGyfLiqaWtFASwNebMDbXGF2EsEFwlyR/GibpPOOScrAF20j5ZKTXQemgELmoEoBRf+cpX+JZ/zz338FGfFyqfUXfs2AEnYygX5IYEjFKA0DDWi0+nkJJf/dVf/aEf+qHrrruOD4QXNXZJ5R8TSQJe+BwEjqxQPRjMQtmJB3xoJR+nYYELJbvA8D/7aqYSCJwlOIAvLYWcVUE0pb6QYw4hx7gvnv3sZ4+OjmI/cJcexVM8Pj6OLXH48GE+SdC1mN30gQ984FOf+hQmyhOf+ETyzoubyETgDTfcwFmsFIxnAghk0NfRo0cZyARQmCjYQhT0tKc9bYX7Deat6VlGCoCc08BZCjyn2bVxck7h1cLPNQLK6DhZxtwV/7KxCbaHGtDFRTJqK2AqvGXgSFZ7MSaWS7HouUU3jI1OZDA1XrlQYpUr3Y5RiZ6TebIUHdIIaATOMQLwki996UtYJt/85jdhFd/93d+9a9cujBPYDJYJY4pgM3AOqAz8A7/KHXfccd999/3f//0fxBorhfTzkg/hhfJuXqQGKX08bUqELFHmQsWRfaFSzkbyImLn1QTKCLEDPc4c2dFxiOIggWQkDPjozCFhcqU4EIBW0mTclfSSmHAaI/Er8Iyq1Ag9pbLZai5FefIuUs2cBCmI9AQ4UniXAguAY0lyZHFGCAojJ1fQQgJJ351y3shlb0HKRfmnPOUpmByYuKIhVgqfGDhwhxLmkwTP/u23387TTTWJx000b12Qhh2CHIZ38uNAFTjAgX5Yr9f5rsGBiYJ/dd++fV//+texT/DJyO8DKbtBmLcUIrsTE0P8vBJS0ESZ7rzzCuwumoySt7sU4tP03XfTW2kgkTSbZSnp04znJaCNk/MCuy50uRDgSTtpnKjHLrFDJqdmHtl3pBkajmVbMXaHyadAP7KbbvHQ4SgMIofVukyjWKj4YfzI/skwCBzHdm3LMU3eTq4Vh5FfrRaH+3sQebKA5dJay9EIaAQWQIA3KB+GsUz+/d//Hd8IRJnPnK961auuvfZaGaqeEjLGccmXe6bYMgYJiwX7hLVoiGQ4PhO1U8Inb3fOMAYOSobeLf56lhe5nCkxFZXVmrvpJWHKhUJhGiEZ1w30K2WK3JXi0oBk5BJeRbI0pSQDARgVLI16SX05Q6pSTXJyUjUkIHUkPdLEcsglSC9FDmc5QJtcAg5CUp3lLpdzCRX5y2FIRYRfwgiZP4AlCQIURBaRkxa6SIDEAIgchvBBH2WIvKRfohAkkF5UFRwIy7FIuXJLakcuQBDzTKRxRkIuDW3EQUoGHdEzQSMtevGCECUFESA7cNFtwEoqKwVxlkBWJh2Mg4I4UC/pNcrBJWlQG+hkuF1OARKk0iDxwMsBvAyGpMWRk1YtlzG9RE/CafcjjExKFKclmvPEpaWkueYNkIyDW6ypcNlll0kY9QggUN1LAlgm9CKME1yjTCyhajzgT3jCE+aVSd8DQ9yqzFcRUSKHM+k5c5dvGZwZPMZPxI//+I/TP6m73BVw5pW8UCSqUihPKAEwpw9Ic6SiQAy4yE6TpX0pvSt15ExTpkWQkqeepiEZrYOGyEyrkOZN02cDkkyKQwLtQqG0C02cTUY4TZmLX2mXJ3FZaZppfTQCjxUBXh+ymcmDu/f/yV99Ys8xBkZXC67n2Oo7k+u5cXnLodZQq11gkh0UJbDKjxya/sRnHzwxOaV+qUljW7YR2WYzCKeeeMXGZz/jalebJo+1GXR6jcCZIsCLk5c6Nsk3vvENVr3klc8E2Xe84x3QDmESWcG8++Wtj1Nl8+bNz3rWs37t134NQ+VrX/saFOTDH/4wb3fhB/Jeh0ry2uYMP2OObLfAVDjp4RzwY+SQeHh4mHm03eQAbYkkASkhFrBMdD506BBawbqYfUsRhIW4IJz0kkUKIgzlYhALSiKfZATgT4gi8s477/zWt771cz/3c2hCEfxAQThwHBFI2WSqcDYAZ2K2NGmoLKVDAbN3u8OkR3/KZSwNwtGKErnEJSXoEUMA9il5JQFKcgm1AgFF0lstmTMA/rDAK6+88vLLLwcBMsKQuqHLqoFApFFH0CCAGnSARx99lBnM2J8wVOqCHGiW6JPN2x1Oy0IgLYJMYqCPVE2Mpe4saQyJRQ2go4eAHnlRTxIQEKxIw0FD8yWeRrnkkktITAuSnhbn6G4gAU30T+UQgIwyNJHK0vpSWUnDNG7BNq0OOtAouArp1QI+Twr6IIFLknGJMlizKJDWSAI0qFSNEoH34YcfpkQemS1btgAvanMAEUWTIJeXSyLpDDQxGNINUAxpSZu38HDS4ixHgVsjq2q3kDQGaaiKBALZEnPZn/70pwMsJsof//Efk/jmm2+mV//1X/81enbDS940expGfhrJ9Hq+buA/YS0BSmeNLzrn2rVrU62WEhBpPCzUHeSxTHhI6QnIwSgSSw/1wF8QE00IU5boTJiC6F0IISNIcotIuSQePOn8JN66dSsPEQnoGPRb6RU5JdPaIQFpaEXVEELj3nvvvbQUP5u0MsnQjSYm0A1dTubKudTGycppC63JMiCgdn7nk8y6LTc8/7V/fdPdTa/iOy52iNU2zI4RNKs1s2C55ch0Omx+4gwcnDYnbq/5RrXlh7bRLuASj/1W49G1I8HoxpFObOSME35atLWyDO2kRWgE5kOA1ycM7Ld+67cY1AGj4g0NNRGaSHLewen7OJubNy4MePv27S972cs+8YlPyOqi8Bgmv5JXUiKNL6aMX+dbLK/8v/u7v4OZZYXkwnyv/dznPveP//iPENxf+IVf+J7v+R5YQi4N5cJR/uu//utv/uZvYCrchSbCD9BTqAAF4cD5sR/7MUwswiif1R8+QTV/5md+Bu71kpe85Pu///sxJN75znfCHeVrOjzjzW9+Mx6k//iP/6AgkrHSEYNhFqL7lEs1GQbzkz/5k6hBlhe/+MUYbDm1s5foA8H62Mc+xnAXqCfZYUJoxapo73//+6kOMqnm1Vdf/Ud/9EdZhkQy4qkmdBlgWZ+UhkMa5XKwSgGlkIbxM+9+97uRLIVmq59VA4L+n//5n9SU4jioKcqTHdC4pL5MYqZSrBmdzbV4GBsJRotiSGNJKyZDs3zqQgqIKPrMF7/4RTJC2X/v934PYocOZKHiIIMmdJ4PfehDdDAqLjUVgegJGvSo173udbBqDJVFdKPd4aDvete7sCWopkgGajoYYeTQ7X/zN3+TziDVJxJpFMSoReIxlZlBgYkCo6WLfuc736GfIBN90BObnOyiVarD/v37gZdeRClEAgiNpayoxI6iXLa8eNOb3oRhk8tIYsTSOn/1V39FKwPIW9/6VtwXSPvnf/5n9KdcYHnLW96y0JirVAcJIB8lqWNaUBrIpaTuEHfmj/E48Ihh9lNrCqUdic8lzl2KzJxkLCiaj2lsKEATQ+Ull2Cek9B9STURCIAf+chH2OeH7NQCJIkhgLYARW9/+ctfzm8FiXnu6CfYKqxY8J73vEc8GMQDGl2IVcswboH9T//0TzH86Hif/vSnkYM0JFMQjwztQhO/5jWved7znrfQjxUCUZVexGKGH/3oR+kMoiTtQgCtqCwV/Pmf/3n2I0IZxFJKd+1WYIw2TlZgo2iVzhaBvv7izktHZoJ+2+opulXT4YMQ896NyPQMu+hZHj8zjPeK43IrZriXslV8fi2NuM2cFL8+Ob3vec/bccUV23nu1aPPi+FsNdL5NQIagdMjAM3iwyEH5AlCyQKg8CHer+SU1/BCInjj8t698cYbITHYFZB7CMTzn//81DjhVQ2TwISAE/C2hkksJEriYQnogCY4BHj3Q+NQACFpLl7/kA9IBnSH75Rojg5QEM4IJwsHmlMoysBCmK2b5dZI4y6J+fAMA+aS752f/OQnMRJQEuGUjp6oAT/jC/2//uu/QjXglzB17JNUjWwAIeSCicLnKBc6AlvKJugOkwUyRBaqAFZwbg40p9aIQggJKJdvw9m6IwfdAJyCqB2jbsSYBCUScwu+RUZEAQss/I1vfCNfwamsNGVODSYDYMyAA2hTX+6SESShcQgnhjDK8Mn/h3/4h6H+uey5S8oVVflyjL1Kc1MdHHFUAeMklzh3ybBA2pTslAg1pDqEOagRDgooMnoCFNSWunCQAMIHVgBFMmpN4NZbb33pS1+KN4+YVD5h0nNJdpT53//9X8oSeJFAB6AVaHcKIg1l/e7v/i7zxRnQCCuVjNQCOxCrBqccycCZbga89A1xa5BAOl5aqAQwYLDJaSmeCyG+UiPuIoeDdoQEs2A3vB9bmtFTWQmUTnOgEp1E3CbYe3R7zFdKpI1QnmZKYc/mXSRM+kXucgslqSMl0mr0DQwkcMb04nHAPMti2y0nJ1wSS3vRZPQocXNJxsVFpcKBCLOfvkrd6aggSfWBji6NQJqStqCBUBIj6g1veAONQj+hI+HtRB8OKYgAovACkYAWB1WsHYw9+gM4Y3Miikah7nQMEmOx40fl14NVy+ZVVX436BgclIgy5CI7mqMhetIrMH6Qz7PDM45Y5JAmrdrKDGjjZGW2i9ZqiQic/PXPZigUzMFhb3jNmvG6HZglzy0kK3YlJgnzSpKXhNot3uSzXCmyCkxOYYCCpfgP6xFahWLpsq3rN40Nqcn085eQLU2HNQIageVBgNcw/A9qzsEoF/iZvGUXly7vWsgHn36h4/BL3sSwUngb3I73vWQXmgUD4IW9uEDuSmIkc6BDjlXzvofMwRuYsg8XgULBmbCjxKcBP4BeQEHQBDIqM3G5RZrsR9+0CDSE1jAajY/TsD0ZJkQkNAKmiEkDEaQsJHz5y1/G5MA44acKxXK1IAZlGLgidSTZNddck0uTuyQLX+ix4uDx6AP/pmr4eagLqhImPXUH2FxGuaSCLEUAV/uBH/gBYa4IQTeqD1W6//774WpYXAxSws5koBcCsw1KSrwBWFzUizBjbyDHlEuJUF6oFd2ARsTyoV5wawCh3MXtkxQW4KL1GRsDr4ULIgcLB5MDDbvrgmI0AXyREqk+uJEybXSq89nPfhYbjO/T6MBoGSxnKkUCoKahURWrGChkOCKRqIF9QkFpSxGgCKgtPVyYKBO4AV8ILgqQBRsArokcvqMzBglluAu7FTmMHcLPxpxvmonuR9+ggswpRz3pcqgB7c6WiBX08Y9/nH5FrWkg6kX2FAEyAiwtxZlGpCLoQGfgzJEqT5WpEWci+TYPk4ZSYyGgDyCgBiB3Q7pQDOrJsVCCNJ7i6C04grDH6AMUiomFkiRAgmiYJpaASM7dksTUEftW6o7M1LuVS5wTKJcAe+DAAfyozIWjk9A3+HXCFYMQ+gDg03ykYRAaYPIIYwPQdjzC4Jbt8JTFQSTdm/6JUUfnx3REIIt30zQ0NxlpF4TIdxb6A/2WGCxVsZazGvJQ0Lj8OFA1FOCxpXPSgaXrohhwUXEUE8OJXw8QQCXUyMpZgWFtnKzARtEqLR2B+R8wnrty0X76k9b/37eP1lqxYbEvbITtwY7wbAkvnwywTbgOTYsxX4zeMmI3NKAUnSAOt6wbGu4tlG3DIcWpuuQuT72przQCGoGzQgCL4l/+5V94ccInGFoDh1iiOHnX8kqGEcL8GKrEa54Ar2oxToS1iDTe2VwuLplXOAdp5n2LQ1BYlhROwLdPiAiOEcZyQFj5UCqSyQXzwCyBGsLg0QdKCjvMGieiACmhfXAatOJAFCyEkTPwTjSH+aEGrB3iAs+AIcFKCQhTzFUBURBx7CXIh6AHTcml6b6kIOwfmA0kBt6J5YYpgi0hNgAy5UgBlAoCNSwKsgjTgmT/1E/9FByaSBJTBGmg19SdenH5D//wD1QBo4sEkp1ISoQwMSIOxk88CRg8xqKxUN6skkiAvYE26iEQFoh6cHppnWzKXBhNAJDv7vQoCoL3Y+NBo+GFuZRc8tkb45DWRD2gZrW3NBm3+GTON3sqS/MBF1YfAwjRIa0LErCyqAUNjRDsMRqI+nLmFslQBrhuueUWWocaQWrpLTiC4Lh0VJFDjWhcbEsCnPHAQEbpALQFQohkbBsQEcAEgqnDaAUx6eGkkQMiK8XRW1CbQonHcUTi17/+9VihcwnVvxjPNDrF0XMwEek54E8dadY0GSUikBigwIOHwcljhVGEqcO3ABoOTUiQpl8kkEVskWRyS3ADVR4HDF1agUYBXvo/D1o2O6WjOXoSmYKZCgEQcjGDiw5AGtqXHxZsg6yExcN8NMFBiouDxqIP0Gp8aMA/Jsjz2Eq5jCml6SmFwVo8/mnL5oRLvdAERwf9n6ePXw/GxQE7laWHkwDTlK6CScxPovQKzELQzlaclPQEHgoSgwANh23PBx0aWpoDOfhh0IdHgO6NZYUo0Mg2bk63lXOpjZOV0xZak2VDgJ/Jasl67neV77pv+vhEyXErbb9TLqpf2zlKov5lE0ZloKhfVdiQEcZ+uzXTap249pk7xob6Sc2awvrQCGgEHjcEhLBCpHivQ0R4VVO0vMuXqAOfM3kZQ1/4sguhgejDJNRzPndkw3Nxi/0rr/lcCjgoW0PCb3jTMxiG6RAoDD3KJoNGvOIVr4DKMIUGcgzD5gNw97xhmA0ZoX1IYFja2972NpmjLEwLgRQBD+aTJ1/uKRGyAkuTr/LZ4iQlH1AhMXBi6DUTygFwEfQECgoiPSkpCNxkgApnmHFWPjhwiDQC5CIN7QVDZSIEHDpXfWCBgrOrIypBZyHKUCjoFzIRwgEmzHXhizhuDcgiA+uZ9iBy0rqTGEsAawR6ypYXfCfGq/DBD37wF3/xF4X3ZzXsDiONfW/g3HQJaBnEEQInVgcKUIs0C+SVoS9wUCJpMhZXkL5HAtCG08v3bBj5T/zETyAEOp4mECGyju0f/uEfYouiJ4YxVaZeaV34/s00HowKqCHVARmECKUmDd0AgbQvti6loDYaYp8QycQhAZzEXKK/NBPlQk/BgSNbF9pR4GWqA/CSGFuC+VeQaQDJqY3Bg5IYJ+973/v4VA/ZpTXRE0Na6oWoNAAINCK8/Ad/8AfhwfQQpEnRFEpAwpL+7M9Ik9Kxk3EgwLBBDA1h8zzUWfkgg52AMiCJJvJMpQmwE5hKxNcBOg/m+g033EDPTNslTbZIAMvkN37jN8hFnyc708NwA9IQqRCpOP5DfruwYbAE6EVohTI5saQkl1SNDwE8HX/+539OfyAxlaUK8tzxpLzyla9ECBtu4kXhqecHhwF1WLypQB4cOjb9jZ8a0jC3TYxqJKStxi2eUGxyJrpgqTLrhlrk+kAqcEUFTvkxXVGaaWU0AmeMAO+cim3s2mSMlBsP+UGn3WfZst+J8p7wEQrJyY4m/Ms3D5wqoZpyEjbjYLJkTz716kuHBxkJhslyxirojBoBjcBjRgBWAZeCckHR4Ojk5y0rL/4lyhK2hBze0BAp3tlkFAnZ82mlUS7HvMngBHzy5BZcja/acDUYAMI5JAsByQh9gVuz2hi7Q0JroBGM6oHcZMVKYlg+NBHii00FTVGy5oTAb/jaTUGMKkEgH1MpDhssK0TCuCAgH1Afag2jxRYiHjk5rdKMUgR3JQ0BcKM4DsIp8UrTpwFJCbV67nOfC4XK0R0RSHYoF6uN/fIv/zJqY87xJRjHiIilRCgjfBHKTnVwI8Ceuy0TSqRBwQRrgQEwOKxAHlcAPYRbUlCqVXeAUiiaL+X0JTLy5RiEydWdkorjOqBGMHVmMEsTSEpuYUdhNmCT8E1aLJPu0skCcfylX/ollk9ADqwRWvn2t79duCYcFLWRQ5/h+zemZmonoCSH9FvEIoexUrQvBJcODCul2zBcB16efvBGPt0JxcCBvKJMWqlEnlpCjflLJENzmPQLXvACAt1tSgy0Xvx1PHqUyAFW8nUglSkBOgZiaXH4LhYRkVKWBHKJl+VSakfF0ZP6ohVWCg9gTjh3eYIg3zS3mJHgSYDexYHlD/6YhVTzhS98Ic40eqxIkCaWUnIy00tMaw4uaUpsG55TekjWICS7dEUScJdyaTuAQpluwElMExNP29EifD1JewLwSkU4oz9K4gbBLuIjC7foCdLtU8XwYtGp0IRymaRE7XiUciXKJfGYpsDIshaE530EUrErJKCNkxXSEFqN5USAz62eZfQWjEvW9+8+FJ/oxK7D8C2xTHCYqF9zJshjr/AVQ3lQjDi53y5Ztb5ya3TILqk1WvJjupZTRS1LI6AR6EKAtyYvdVgIvgIxThbnDV0CFFvi3Q8t4O0OzYKm597EXOZiuoVkYxDIkY3h2y2TjKF0kB4IATYAZUmCXEqYAUSTBCSGizOvl7w544S8cA4YBt9ccRGQpVsIxJRBU9yFPjK6iU/yULGUqqa6MV6IAwJHeqy7lIGRICczzZLeShMIPpzTmGziNAxbYqAUvB+ihibZxBKmXgz44S76EAMvZ9aHIM8lTQxr5FM99cX0AiKqjxwSCEVLCyIx3AtREHpK5OM3Z3E0pbCnibsDZIcv4spg2D0UE2oLLOCTTQlzxd0EpBwkxhAiFwk4ozMmHz0KxomvAB2kOlKRrBASI5a68F0fI4qDtqAukhKfDBNFaGhE8Rkb0plrPrKTmDOAwFkx1egnQIQHgwMEsh2DZIgFQ7IgUzJmlQFtaoQOZGQJXWokRm82jYQRiyb0UkYWgQMMGGzp3hjD9Lc0vdQCaRhveOSka6EGR5rm3AUoBT1pbh4T5saIqZAtTnoCjibQwB4T2AUiUCJADOwcDwyWIfXK9pzTVoGeg2lNFh5hfCP0EBpaciFZAnJGSSwNvJoM2OMjAk8riGX1lLA0JSqRGNhpX2K4RRHISXWjq9AuOE8wJ6gy7UKWrDSsVvoneVED854mFjWyaQiLcLolNirPEUJycnLpV8ilQkQfGoELDwF6Npb3rstG16/rrbUDfvUDM454ii38JlGM75fvbkyTN7lkl0Z+YphsUhuqBjdcs2Gg6rgqmT40AhqBxxUBoRG8O+Vz4JmVnb7gsXMgK91CKKU7sjsm96ZPL+EETIGAUkAiITq878mb3hU5FCEHzAA6C8mAYUD+IBOSgPRpFugUCWTORrcaSOCAx0BYMdgABznoAJPOJiaeb/+Qb1IyRAqtUpaTFpRNf5ZhqR3NlBK1nEB0hl1Bzjigv5B7uFqqCUwLAs2ZXHAmMfC4i1hiZrFL/hGxSIMUgjYBkvFpH4G5Ehe6xHmFT4OeQEYmiJOXAEeankaBjiMZPcVS4pZowi3sSbg46TG0GE1EMu7KOZVAgAQiAe4OTaQ4bAMRwl3IJXJIABoY3uiTzZsLY1pjCDF2iNFTjI6jYxCTVRg5XIrwtIisEOqID01sKtSGuaadoTs90riLrwbFQBU2j3+PPiYCSS9ZqBHJaCxanCzZ4s5dWIoW+VSZGmGa8rzkSpRbPGI8a5zRMA0ToJeiPI3LDwINgZAsmDlR3ZcgKTY/4PAxgk6YZk8D5BJVQQZzgrZDh4W6KLk4wJk0+F2ldxEjqAJyCi+RGO18AuDpRloWDUrEg8THF4TQ5fgBoYKkF/0JyJFWh47HbwLNhyiKTuNXbEB7TlZs02jFlgGByy8fGLs3nPn2TLWvhI8EIwTLhPeIEq3GpnKpwkTyvPrtmbEx8wde+KSBipptcvLdtQyKaBEaAY3AkhDgxczBS1eY65LynJpIXuSceevDS3hJy30JqMd+CcaJJE5TpkIQxQdUGBKuCdGT4SJpslMVmb2CD8EMoE3k6uYr0CbIFnQWFrKQHEqHoDCzBYJLcfgBGH8PjYaOSBlUCj7KtApRjBkLC5k682q4SGRWJdSQQ9Jjm807cCWVRl75bi0BwiAmd5njAe+HhyGBqgEOl9yV4iglFZIGiCQxB2mYmw6TJld6d5EAQMHeIKmgxORv6CBDs9KCiKRoBpghnyaAwIlY4tEHA4NP9RKDcQXIZOSYV0PiaU1gwT7Eu5Xl0NQdNwg6IBNyTMW7FU7BQfhSqkYySqQPpBlFJvE8PnQSaCvOQ6xosKJEEkuCefWnRDKKxUsfg8eTmJTpQXWoBdNXeKYokfjuKix7jNRRzrQICoAtfSBXELeIwUEEGlRB0tNePA4coIHdziAotknBZ8XQLOwHWiEnZKFLvEk8WTg/aVzqPm/bpXkpGiRBCfmkz6HEXQ6BlLogip8RfhzS7BIgTRpDn8TpgY8RaVSTvCKBMD8mVJafDhx68kOXzZhKSAP0BKYzsQQCotLIFRtYavOs2ApoxTQCCyHAAz7Qbwz1maWCMj8SV4panCs5lOdEvShnL3mpdFzTH6pGo4OGZ89aJid/IRYqQ8drBDQCy4cAb2sIHOQDbseX9cckWF7bZCHAi5+D9zpMMY2XNzeXSxRLSghZd3rkcEAOsFLYqo8ANGghmbAleAP0iDNpcu4OEQVXwCUCYUpVzUkjGcjACOUzMCO7mD7BxmoULRKgKayIxSRsiA5pGDjEOSfkfF2KhjkYAYSRTlIdFj2TZbhICRS5lFJHYITzCe+ksjBv/CFLrBHQMRgJWsb4HMg6RgIZKQvJBGDhKAOFBTr8Ffg0slyfxKInKf86OWh0FOg2CURt4ul4dGDOIl+U5C65KAKDgTQSee7O9FvMP3ER0PGk71Fl1OA8b7nEozbqEaDWQE0VcimRg10n0ri1kKhcrrO8TEtBH+qFAngJcjJFW6aDi1tDsoA/B7kkI7MyeGqYh8OkINYtwHpfYhVAgx5CofyYpMrkFOgWBdRy5FJmJcjPXba/5RKjv/QWeimdh/Rp1aQbUwRNxli1pXQqniAMMySQK1fQCrzUxskKbBSt0vIggOlRsI3Na3uu3mQ8dGSqbA9Y7GVimHZsBsr6SOwTNbBLmS71Zn3rSPXy7dWKazimwXet+X/Cl0c1LUUjoBGYBwHe07xBuQGJhC/Ok2LhKHlt86kbTwWvagwGvjjysTB9Gafv9UXYQFY8VABCAF2WjOktXu2QBi4pBVZEQUIU0gTZAGVxkB56AT2VjNkEEqYIknXHpzEk4IA9w5UZAY8OfNFnNBTUhDQoyYB7xnThIuAzKqR/cWmp2LMJiEqnlUCy7jTozyG3wATSCYYSKedsFklJc8C2SUn6eWVms+TCjFmCubLaL/ybyRhYIHzbFv0Bk0VmIdxIZk4C3FfyAiAJUmUI04KiJ2c6Rg5hSc8tiqBjYBvQNGlzZ+U8VuVzdeFSNE/j5xUooOVu5S5TCRJI75I3d0suqaOQYEkA6adR5k25vJH0eXwXYE4noe3wbuXkowmtQ7fHfuAW6knrgD8HlxxvfOMbkcCSd7L1EP0Br0VOzryXkp1b4JNCNG/KxxqJtFwvyklAeelXKdQoI2kSXWafLGmFpei2eHG50s/vpTZOzi/+uvRzhQDveegD7tKdG91rLrfu3T1uVXutyMUyUcZI4jHBi8JWjFgmpsFuXzOXbKo88apR7JfFOMK50lfL1QhoBAz4HIQbnwk8nvexvJuXiAuvbV7PrJKEAwGuCY9htSj4h7zO5S6i0sDiYjE54JdCxXIpkSCMB67DIkj4ZzBRcmmyl6IAuhHgy2X3rZQ/ZQlHNlkaxjiBTDMpHHxYGBfTC67G+DeWu8WdgsKMbIF1QVaWwlRSsWcQEPlnXAomKMpD5WkpxlkxLyIVJXDlVJJIqBVmGCYKq0UxzCaXZpFLRo5t3bqV3kWn4ts5U0cwTiQ90wkYLIcamLJ8d8+JJZ5xROgJ4DfeeCN60tYpZcyWiP4c3BXwhSvTf4gU5QmjPwmoQjbjuQgDEUydylK0HKhx2oLQjWqSnlpTC7SVvNmMRKp6zlUqe+vchenzrImMVnywoOEYyNRdFqoK8gRQkoM06ElAaoF7gQF+mI60pqzrvUTjhHI5aHTalHN30QvFdKMnKYlfKEsuPsVZAmlGKsWPD5fEUx38zLR1Lm/3JY0r86DI1X13pcVo42SltYjWZxkQkCePHyf695Y15lXbQtOfCP11tuUYpsOALpuPKfxyqXWFYysOTaPl2a0NY/1bNvVoy2QZGkCL0AicEQKQSNb6/OhHPwq7wnnCN04oBZKW+DblbQ3XhMoIBcHOkcEbIkE+aRNGuAzO4QW/kJq4X5iKQBYSpJxAEsMyyShMDmOA1ZByCeaVKVXorgh5hfF03+qWA7vasmULdBmexDdgsOJLP4SDrTyoEYyfu4zpQhRilyIwLWKhKoioNFk2IPIXKYVb2bvZIqgCdhq1gPZhErAksQzIQX42mRSHEKkOZwnQBDRiVpmFwpKe9oLRshAw3QPPCVNWxIrArsPdhGmHhckqAqQRLptKw4LCGUUuUrLqK2tYZWuUJpOA6ClhyCLNip5yiVj6EgkgiMIjRbGchOW6pCdQF2grAtEcQz1ndHUXhGJgwoFiuCZADG05sqyXW2QkUrKngW5pi8TkhCySMr0F/qwAISphQ8paYXJXdEg1EeGgnd6VW9QCTACB8ZPUkXURfuRHfiSVv3gAJAEEfEASw5JmTeXPm5E0PJKUSDJKFwWyKVFSjtOaOpJdzmSRgIgSNLDHMNhYUO7lL395toh5w/xEsGAgQsg1b4IVFamZ2IpqDq3MsiHAzyedmzdDX8kY7YsGyh0GDvhhOzL48fWNOMQ+Yd1KN8JQCeNOfe2gMdCjFulaBZ8Ulg0kLUgjsLIQgLC+6lWvgrBCPdk37S//8i/layUv5m5FuyMZGg7XZEICb26+jsMsYYe8jMnLmVHjsBMYA1/QoaeYH6lM4QpZgQwjgbPy+bn7Rc7kEJg0hI/RJhAdiiCZHBCgueDsv1BSJMBsqAiJ0xIlIGxDyhUqk0uQu0QUXBmjCwKEqwQdCOBoYg8Q6o5lAnUTQgzvOS31yQlfKL0oKTCSJXuZRuZEpZdppbLYcpemYe8OAugP74QzgRfodQMo8Zxhe8DIAYx0Dyk6JzYtNw2kGmJ+vOQlL6Fr4V8CMVY64hZdhQBC6Bivec1r0nkI3OJACDEscAS2eNIompiFlBQ9kS96ck57DqLokHQ/EEZ58cNQKEeqZzZAPDyS/gnHhXoiqjulypwc2YxpGNuPzgCZpjMwFxx4uUXyNEF3gOW5UIz0tAjeCZ4RSSM4yBn9U2WIoXG75SwlhrwcS0mJznRypqSzFAG64ScE/2y5yOGSZLQOZzBPYc/Kl0geRgwbwlRWWpM0i8NCAvkiQIuADBnpCZIrl5FLOVCYMZY0NMVJ/0+qe7K+wEhKkOTIKtkdJju1JjtF5+4SSWejX6ES26rQ1iIWybmUckk8XZ1pV8hcomE/r5zHLfIM+9bjpp8uSCNwNgjQv/m8Ntzf+9xnPqHgmPwesBmj+moQhfyecYtfSD/wjx/f/8Sdg9s3DaRT4c+mUJ1XI6ARODMEeHFCPtgoALIIiYRUscYrL3vexKcVyPubLcaYV8ArHwrCtFeYuuSS7Hz+RCykgZc6Y3swLbgr73ISyJG+2qGGMFdSolKuaIZyveENb4CwwnL4DI85lEuQvYQQfP7zn//pn/7pV7/61ezQ95nPfCZ797GGqRrLDb3sZS+DKlFHqAYQwUsYzMaZPRPYgV4U5kyNHpN8SU+lziDvvAUhMBUFsIKtnImHV2HmQeDwj3FI/LxyiKTirD3w5je/mdV13/a2t1FZSbn0OtL6DIqDllEuu9p94QtfgMwxvIeiIeJYDlgv3MopgGOKOTw0IrfoijQlCSh0Xm1REsV+/dd/HSXZrvu9730vnU0E0hVf8YpXgC0GAH0GT1eKTK5ELunwf/Znf/aWt7yFz+Ese4AhnTJpSYwCHBKeVxOMfHx6VJCnCaLMRPBFEsstliVgzVxpfbbpwPyW+GxB85YlyZZ+FoGLiMrewqT/nd/5HVbuBkncqjzgVG3estJcBNJwNiXl0jrYpcDC1BRqKnfTCmYTZ8PXX389Kwhjk/DEsUc7gyq5S65cRonhzHeNP/mTP6ERu7tTVuzZh/lOQa+mOvRqOgm/SKnMHAhc8ouBgcePHh2PI025YgOrQMUVi51WbGUjwPcD9QmBn/ChQe9Zzxj23DgMQkM2O0l+WGI2OMFOiQPXbFyzq7JjY8lLpsLzo/XY3uorGwitnUZgtSDAcwlveNOb3sR0Ed64vEpZhIrlX/n6210FEqeRjLp+3/vex2gNsvC1G47O3g4yO5Y08qqGCsvXay4xTvgcC5tMJUgAmbzsmSHNGHfoi3y2zKWBJDFaHZZJAgirkJU0ey4xq7Ky7C/jUiDBmEaMucoleEyXsAo+ilNBRqfAO6kFdBlVqRF12bJlSzrHBrFZfE5bCmjz7Z+6UwQ8LEt0Tpv3zBKABq4MCoX6Q4tZzDel8jmBeA9oWcauMGAPckkjPqaqiTQqiLsG/Bmlg9mJNCpLu9BzAI2p8PMaothOFIeTh54AzliDNCgZ51WAgYgf/OAHSYNYEjAxJmWBFEqfpMnoM9iTbOydq2P2EhwQwtQpfHd8F6ffonw2AVpxkIy7KJO9JWFoMbSVBcqoFGnEHILo51LKcwFtBV6+vjOOkfSggQGAqrnEy3sJMvNiSClpPM0Ey0cx6D7GEmY5zdetmNQihZrsqYSsztB3Kshjy5PCnjk0q9wlezZZd5jnnSeODsAtkKTtxBPVnRJR2L2YeXQS7qLSvK3TnfHMYjB3GVPK00pP+NCHPsRywyggdU8wOPnzyCVqf+ITn6AgwoLYmRX6uOU6pcc/bqXqgjQC5xgB+blRDycEpqdsbd3sFd2w3vLDwHVstjGxYSUR3+Nixti2h/vNjWu8wYp6A5x8oM+xilq8RkAj0I0AJAC7AucAt+Alt912Gy94CBaRDOpgxwZ5+6YZIQr4LmByLEcLc4W7sMjsi170Iuhg+nFUEsODYZlMYoGj8A2Vr9cwPEZ/pTJ5Z/OJGsaPyQG/FLJO3lyJML+tW7e+8pWv/PSnPw0XwTzACkI3+BMCU8UoAt1uvvlmiCb8T4qWsUxpmjMIwHhgqzgB8BHBgfguTpUhryxIBa1MqVtO59MWhFiE4H0CNNBmzNhps5xxAqFQmAovfvGL8fkANUAxhQaOhZsCVp2VDDHFdMHFgdkJvYZwk0uYYjbZacMAAvN+/vOfz/djzAx4P12LatJMGHU33HDDvDLJBTfFWv7IRz6C7YHVyjoE6ADaGFfZQumEDERkfB0K44ph6jyf29MeSLtQCmsV4LGhIhSNHCxwWC+3Uk7J53bscCboI40+Q+fEpKGglHlLiVSETggrRRQORrpfTnnUBt7Xve51fOmnptBW4MXGQyU6TyoNmg4CVIpdF2kISmcMG5ug4yJI02TruFxhhKP/vEXwsKMnhgRV46FGbXyYPIlM+MFjSU27O7agx6PXfUsUptvQx3iuOUsP5/eBh2WJ1UFVfLkY0jQZXRSWT7OyigMWTmo0ogNmDwMU+emgG/CTArYcSyzizJKhFdOo6C387lE7PuLQGfghyv7IoDBI0uExmTgzIlT26lkIqzPT5Fzk0sbJuUBVyzzvCGBizH4OwTjB5qgUjA3Dbr3ZDjuWXSibGCixEcZhK6ibcf2qK9b2Vxn2NbuCMF9SWNNLWynnvRW1AhchArw1eeVDRGAA0BReqJAnbAAYIdOmIYXclTcrhIAD9s93X9bVhavBCWBXJONDeMoLwVDSc4btQU8//OEPE8m7HHLPnHJkkhhRQozYzYJCYYSwSb7dzvvtEwbAqBsYJKwaLkIAsfCVlNUhDRLAIC7ICtwIpvic5zwHuyir1Rk3LtUEH0gSumFoYVDB85irzTCPM5ZJRoTAleE3sBn8PDC5VBpsG3ssvZSAoJqLXOIl+MA4MSOxCsCH9sVWFLSZ8IAmHNIiaPLZz36WgUlQPWDn8/lChsRpi4a/0gqIon0xIW666SYcRPBdqkbvWqhpwITJ01D8r3zlK9BlwIGV8tEa9wIIoCetwMHdj33sY/Qo+icJcJtgHqcQEaAgcuEmoqbIYZTa61//euwT+oYko74Ip1mRQytgRdCTaVaKyFWNhsbeQBTeP0xfuCnmCtk56OGESY+H7aUvfSk9E9JMJwFDwlhiWE1oKPByCw8SVj34E4NYViTDOIGO50pEci7mzC6pKQdQUxw+KxoX6FJRlAKZplKYcCiG4cQlNj8sHLuO3kLebOL0EmnUmh8BLLpUVe5KGDDZgRGBPJL0Oobq8bSmYz5TgQsFkMNPBBub4iPFbue5oJnoDxSKYcmZjHROKYXeBXogT38gRu7mJKdq5+IXulwoPRYpPymM3+MrCQ8RHlr6FUDxQ0QWDqoPIKhNjwJV/E7YuiQ711bTQhV5TPHaOHlMcOnEqwiB2V8x+U0tePaN122fqd+/5/CMVygxH03NMbSCZjBTtKd+4OXXj66dXVaFGmZ+AFdRfbWqGoELBAFeq1ANCAQs/F3vehcGAK95HAXwNrkl5AlqBS+H6JCYGB5oSCSvalgj9GteLKBufDTluzXfODFm+OgIt4NhkJ1PqrzgeZdDWGGrrN0EV3v3u99NvFAczvK+5wzNxXRh8sNf/MVfII2vzjA/vlIjSpwn6IbOMuICVgqlhvPBJFIJqEc4q6SUko3pDosO0FaIGgVB3eB2oiG0e+kfg7slEwNvwx0EVYVhQ6AZ6E8kPAaEMfZYnCCn8LxCJDJbF8nFOQ1IGi6B/Y1vfCPymfmNxwDC9453vIPWBEYOakdzwKeBkYamTZnqg4YLNe4i+sgtmCIGAwc2JDIZJEYz0dbQ30Vkkgvb7O1vfzsqwXEhuJijdEWoIaoCGt0GKxo9UZiK021e+9rXwhGlvqlWFIHljLFBoZgKEFzGLCET4cgBZ+Tgu0AxwtQXBxEHTDqVkAYwTeGaCCElD4jEkx3J0HomcBND6fSQt771rWjImB96IybZO9/5TjCnOG7RbSiOgkiM5hgzeFown7iV05wE1ItDApzP5kA4orCsPvCBDxCgviJZejJaoRJn6Xh0darA4CVMRPpJttyskrQFWYACBKRGpKThRA6SiUQgkdiNPLa0EThwKUVnxc4bBjFs5l/5lV95z3veg1cHHxrg892BtgMuhND69AG6K10Lk5IiGABGV5G78xZELo55i+uOTCsrWbjkIEx1qDv64GSmEfEx0qvf//73o7BUH3j5QUMxtOLZwRimD5OSIpCQFoSo7GUafx4D8/+Cn0eFdNEagWVEgEdfPssUbeOZ1xjf+FZt9/6QqSas8siGXmEUFJz22kFzeMDwWGQ4SZz/SLWM2mhRGgGNwJIR4KXLV14+MMPD+DTIJ0k+tcIwYBW8dxED5+CdCj/gEub3/9m7DwDPqup+4PMrU3bZZWGpisiOgIgoKipgJLGRoFiiImKLijGKGk0s0ST+NZYktsQYYzTFltiN2EusqNhAwB6UtkgvC+yyfWZ+8/t/7jszl8fvN/Ob2dnZ3ZnlPYa393ffueeec277nlveM7hCBqCYhN1jbcSgBEZBNCcc4rQGNIMh3IOzC5iwf8xpZh4O1wVcNpADdsCHjGSah3CUkIHTz1iZgzc5bf8JMVzyksoF8Nmn5FizOUsztfEoc5C1JC4xJr8hxRltE2ndgVrzo1wskIj8JAFHMucZ+UxJwHrgC+EBL1Pp5Id3oTr2JGQ5Ccxn5t6dWcrx5XAIw6QmmxkHW4YtE0SJED7WfEA9Fy+FtRWHkgozKmUbqxxKtq/G+gazR+mXWc0+LC18BsPxvpSO7PiNYnqbzlMuzfOe9zy7Ykw8Mzs4iBXLKFN2YCiKqK5PeMITrJkAsn52SIUJYk8BbqbgMFi9ARzxEY84ALRqZqFAXjwZiHxKwUzkq1RSKamA4wpLgMWiUUTW0qonKGFx64TwK33RkI2FUUoi4E0A5EFmj5A60JEjeqXPl1COHCoc6Bv8Peog7lC5+yeUzI2no7QUJ4Magix+smeYlJutxF12KGmJljHFT5mX+m/BLdaOFEpqw5MMg14u9JWjiQnOHqdRS2SWeDolz26xxZhisCnO6Xw7zXRHOiWcqROW5ANEh+ClFBZjNUYimbOQKs6s54xoGi0CB6XPmDjE0yntiYZeLE+GKGL5BqVUwpYTX/rSl/LfrNPyTNCzFZ7oMWcNur/gBS+gOCecrVyWpNQ9pptS0wUSWTknC6QgKjHm2QLckpgWgGL4J/01LxTu23dFbbC/vXW01ez31q722JYNey8du+9h+y3t9wGUYiOY755MJpxngSp2lQUqC2yLBQy9PA3TwMAEdGL0Bd+hmYBKkJxBN3CGfV82dxmGgQajNUrxHVnF8O8Ol4ApBm/gz6iPmztwiRsACjjmk8TAn5UTbGN6soOhjKBbqbDi8IDULnOlAQ5Cl24IfAAAQABJREFU5pDQgonz67iFDJmPhICXLASoCWTkRz0CcImnuMGU1pTAIwDOa3Dz7qAeaXs/wtNSFWgFZMNPARypL8A9yGk9JbPsFAG4NiWiysRM9Gd/9mfMi4ycOV4grMGMIDg+jO9cAXXgYGZ0lwV5FD2EB14rL2H0ZSZzCMtLHaCmuxrF4VF8vfkQFcCF7SxPMQXcqazBdFbinkHShA8YynshM85TyokPg6h+fABJpKUmmKgSoldnPI1HhBTorjMhJztYOmMf8D0KiHkVB4ZqGppc08K8/Fjx4Ck8mnMUo7Y7Fy5TdUktFVAVO0yBlRbhBd9yjHzV6qDJuXQk6fFT23zzm98cjjSZXZmJgIsAZNbwlbgKQ6QwgkdTsrWIxJ5QOESOAMNuMjw9pSlKPP2cjlt32hxDDMLE4qc6owKEt8YtVFIsyZ5qsoasOsni9NNPd3BOvopJ5cl8hK0JI1PoHc7nlFJpbl7+5oyZZog++GRKtlLxcGMxa7l8GIKpUS7OUnRoyos3y55iJHzVq17FlUJc7nAywyznLg+khaFdLkQlQGWBebeAaq0zc/dnZsZUj8CHPn/FZ8/edPnNWquZm9qGdZfea3jrMx5/jwfcc+Xe/TWv6pKElzJNNzjvMlYMKwtUFuhlgRie3CGwAGGoYQIACybQiuE5w79D4Z/4xCfMu6ME12zcsrkLiOwx4uIG0MBzfAkjOlRnjA+EYbzHU1pPYWU8ZRTjeresIVvMUEJ+ULW75AArKCOAG1gDrHSnFUMLGAUB/q7pyMppYRQ/WYCHYE+aLVgwvQ1CMFAk76F1mc904bBM5IKGgrQTgMCCM0+DjszFPmQGxKdjJR43xATD0B2TKYmzGeXFIB3OiYRM5NpO1SJrIpmBZnmlIwAo00IxTSlYRyQtJCStCqMegoACPEw1BzqMsnbvLWdWViCgpNKUSp1RiOQRBmF7MyFJlBQmISTTEYYjQa9usRG7FJm8mJeRgWltRC2VV1h4uhxloSFIi4ya21MQYDGbh3YheXemESMvF1N06JJ/RnIqMwWyHpSRBAHJ8fRT2pxvOZyZTxdAHI1dNVABrH4IqNW8O55bqqNFFshYuBAqrQ55hGHk6FFUPwnFKPEsyZSZyo7lJVF82VXroMSzKN7UpzGI2RY1U0VSLV2srUqE4sj0eJKLRBCRHdwWyM/KOVkgBVGJsaMsoOc2tBrPOR7n/mb8U2et/eIP1u25155eK7x1/UWPPLb5ijOOX1rvW+LcfC19txFZ8YbhHSVPxbeyQGWBbbKAobc8fhvsXTjE2C9gmHdK1Q6rOBZv54yJXkd7gYYZR98Y192DWzkjnGUkvlta9CI7iEUWot1Otg6ablaSoJmRrJxQEj6J49QgCNhhN/nb3va2kGeb+JR59g5TDee4o8yB3ql6P52OiXgKxtNkl2KuKO69Gc7+KeaZeDacu0UNIUNONUQ1Cz7dlDmjHIjcMz0mLj9dWLnPhknmlgNSuaasrh00skMZ2fWmLyfMYQFpyz9nH5ZvEHdwCHlmzycos922NWE5O0xmY4RI0pGwbMnQKO7IyiJ1KBuP0Lg8mvJpOTmy/DMTR9oyq9BCfEjlkZiC/e0Kq5wws12AgWpb1wIslF0j0mKpsnOzjtbN5Tj8sPohF42tvXXD8uVDm7ZsXrlH/YC9l5r326Oe3BIzKnPtcucmVJWqskBlgZktkMfjIDXiusrJAHTb9H237iUveYld106om9RE4DiBieQyZXcYc5Od3fER05FRJusQKeJFFqLNMHGemfTOooMsfgYaM43t+LhJd/PQsVIkX3OiOcmU4uWncwgEw8w2B+bAKieZjon4GV3KzGRugemyno5bN30I2S1nN2U3zzKNsLKLe6YsE+TIGQNSzZgwaKar1T2ymJFzj7TlR9PxmS6+nLY7PAdFgkk5u1kyiSQdCadLWybrFjvLMBsyxFOSlSOF80+B7mpZliFTliMXYLiRX/WwAIWrRNppFthdPRN6pTkH+7W0WHsM6n2XXbX5l7/eUK+Prt1w84OO2vfE4+5y+J1txJzwTGKG4XbzDDutDKqMKgtUFpirBaAE+4vsKXcewHFnJz4vK76rbdeEjQ1z5brN6fQzrm1Oti0JdGleGOo4tYPFdlg94hGPsI3NZhv5MkKR/44VYFuErWhntkBVZDPbqKK441lg2hmjO54p7tAa7+gBdRcY17dK+CWTw7R//anuBx+wx3H3Wv7dn/xmYHz88LseeNghy/vrfbV2ehq0cd8FAldZVhaoLDBXC+jBrJ943ZC3uDq0aou26UNHk0XOleVCTBcdtXUh7/m1VOKUglPaDg+QdTfswxdiCVQyVRaoLLAzLFA5JzvDyoslDyO6bQOLRdqeciYXY7zVN7RkoNZIO0D8z1VxX3XnJcffZ+nXz7rkwDvf6S4H9K1cUROZ5jr5JyVnpifz6mFlgcoCC9ECTnn6ypiPcujHXBYWnNsm6O60Muy0qzUTx20pS1OLRdywWCFeiEVSyVRZoLJAZYFtt0DlnGy7zXaLFDFyewuEQB7YHK80nPfesLhItOdtpOWQfffZe2BokL/FA6FXc8nS/fbqP+KQkcbI1fc85G4H7DXYqKWz8sWbdIrVk6ReeDGLRNFKzMoClQUKC8TSQXrp1eCgCN2al+TsZusJlPL5P+9NdtbfmRN7unyjI3fgVUWoLFBZoLLA7mGByjnZPcpxZi0MYHmcFrYz24dCfenWu/C8fi5clAggy5Qz812QFNwLf+O1vgHviPQeFRu6Go17HH7Ec894wb3vd8we/bXDD6w97uFHHrFq33hDlw1gO3ij+II0UyVUZYHd1wLlfmyxd2jlUnIU3kcAaWTlxFETd+HKPymbqApXFqgssNgtUDkni70EZyt/Hp599th+ZcObr/bak+3jPnYt737DG+dkrO1jiwM+kbpp40afy/rKl778z+94+6q7HbrP/nd+wknH3t33nZY20yn5FtfFgRMpXBwZqyzVVVmgskBlgQVngf8rLu8R9oWK0047zRc2douF7gVn50qgygKVBXatBSrnZNfaf6fmbhOXLyh/+9vf9lUsJyl9VdQ3dx0e9dnRmHjL0285sFPlm9fMuBqtvvFms9+2ta0jI7euW7t0aOjGm9Zcd/31l15y8arhI46535F9+yyt9w+m8yZO2jgWP68CVMwqC1QWqCwwvxZwvt/Xvr0f2Y41e7rMLsWsU557mt/sKm6VBSoLVBbYJRaoloN3idl3dqbe62KDskm3V7/61V7qf2px2Q9g1s3FFUFQ9k92A+eEiR11T2/XbDS995sDMrJl8/j42E8uuOBTZ5553gW/ePofnf67Dz7+sLutWr5sGfUbxUs408oJt6ZyU3Z2Da3yqyxQWWBmC+ipzDHZf8sb8d36yieZ2WQVRWWBygKL0AKVc7IIC23bReaZWDB57nOfu2rVqte85jW///u/bwbO2ffwSXYPV6TbKs1mfazVdt6fv+FIiY3ZS5YMtdtj1113/Y/O+fE7/vlfjz32gU976lOPO/ZYjklxSgWPyjnpNmQVU1mgssDCsoBOu/JMFlaRVNJUFqgsMH8WqJyT+bPlwuMUA5jD7p8689P/9V//dchdD37KU57iU8q2BIyOmn0btZ0JTXHYosdiwcQomCgL2sUyKJJzQuLJtRBn432njEE2b976o3PO+dxnP+sbbX/+539u6/Z0n3pdeKVaSVRZoLJAZYHKAgvLAt2Do5g5j5Xbk3Zh2aWSZldYYDeoP9UX4ndFxdlZeUbP+IUvfPGzn/u85YMXnHEGz2RoaEl6K1drPB20iEPgSZ4ezok1h4mnAjmclYhOOf9cUIGybCQv3splk1eTEfbdd19rR6tXr/Yl6fvf//7x0psFJXwlTGWBygKVBSoLLAoLxMhYHh+LEWeO/kmZz6JQvxJyl1ugwyFZ7FWoejHRLq9RO1AASwS+JfzlL3/ZCfjHPfYPjznm/oODQyOjY5ZNPOKZxH/p44PTXumZSu/KJPEz33P8Qgt0yBxt1VpRqzVuP5vPKp9wwgmHH364jwb88Ic/9FGzhSZ/JU9lgcoClQUqCywKCyz8AXFRmLEScnsskDFP1MbtYbXL01Zv69rlRbADBfDFd1/suuqqq301+ZQnPtHOpc1btjqEkQ5YcDZK/kZaU5jqSqQ+GDI+DtnH5adAB213TAfBQvjp6D9FovUKuA455JDjjjvuggsueO973+u9N3vvvfdCkLOSobJAZYHKApUFdrQFjAXzOHLhZkyJ7cGjo6Pmv7x7xtnOOWuBm5cf4OPNB3NmUiW841ggsE1U6fmt27vEhpVzskvMvpMytWDyhje84bDDDr/Pfe4zONC/ceNmHgl4nr6dnk6Ic0hu52bcfgllwl1Ry1363OhqQfyO4xnz2L/vBLvQJXKhhbANXS9/+cuf9KQneWfATsi9yqKyQGWBygKVBXY/CxhQYkwxrPz2t781oNg5fNe73lXk3JTdsGGDLccbN2588IMfPDcOVao7lAXKNQ1OW+y6V87JYi/BaeW3bHLjjTdec801z3ve8+97v/uNOWPSatXqxYnwtm+A9A0006ROsYoywUT49s5KWiLxQt6BgX4eiMvep4suuug3v/mNzveWW24xP5Sx/rRyLNQHaSTxnuFGY9OmTQz1lre85UMf+pCTJ94WsHz58uHh4fve975HHHFEWXzKMkI5pgpXFqgsUFlgd7VAdO/dnd5i6QmznAYse3fPOussCxGPecxjjj/++AMPPHB7Su1tb3vbpZdeumzZMtuDX/SiF61YsSK4We54//vfb8OCMcXnaE455RSL8wLGGgRle2bZusUgpIHbO2zOOeccZN7X8trXvvbOd75zN+XuFxNmofj3v//9X//610NDQ6961avsawgD7n76zqNG//3f/33++edrrWz1ile8orvClKvfPOa7g1hVzskOMuyuZ8uR8Bl4UHvVqkP23mvFyMgoz8OyR1+92VdrWEIZ7bN2UMg5ibeTK1IS3LutGvW2D4A0m42vf/1rl19+uQ5XL+8ciy54yZIlS5cuXbxdhjbssuxOEcMVXSi1fv36q6++2qQX/8Rgdre73U3gcY97nNGFYdCXzFMFKwtUFqgssDtbYLfp8WIV4pvf/KaNUkcffbSJp+0sNuj5vPPO23///eHmP/mTPwluwJ9B5Oyzz7ZV2NtWjCy8FzNcMXx05NjDtoTE4Qc/+IFPk9mwAHFa3u9Ivnv/hDR++tOf+v6BcdnrNHvYave2wzZpd+GFF6rhsWbyghe8oDvt4jJj5Zx0l+BuEnPzzTfr4Ey66B91mq2xUW+rajYaG0drt24ZWb9FBE0n4HZs8DK3E4dMVOJGrW+gv94a3bhh7Y2b1t343ve+D3Dfd9999JV46pH55SaNOCeLq8bn0k0zNH38M28XrnlFgDUUP62hX3nlVVdceQXXbs2aNVdeeeV11103ODhoIYXKq1atysmrQGWBygKVBXZ7CwDZ5muuuOIKmjqkd8ABByzqjz+mbr+4BLan7Owa8NJLHNyDlXsEDJECVj/iLrfyFB7Yfe2119p3AETe6173MnsYTzuGUclxdjd9Vk6+PTIvurQ8PUagfodxFp0iO0dgtgpzuUdVLOdri6CZ5YhR8fbbb7/y0wUYrpyTBVgo8yOS6X/7rw466CDzN8VJkxZPpNFs3nDt+l9cdsvl121x8AQ010Wrx3D6xCpKsT7QaNYH/DX6rrni1+ed/eXLfvXdkZEtL3rRC0455Yk+DBK9rS5Y92qmqEfHUe7+w+1Jusl4UsUcmIzYef/q+JoNi0hpdEliJDUcukmDSsuz4jDixRdf/I//+I//8A//wIbWT8xGWEjpoe/Ok77KqbJAZYHKAjveAia5PvOZz7zpTW8ySviAr27w0EMP3fHZ7qgc0lhXzMgJBOgXkNm29uqGP3uAYxAsp8XT62dMaf385z83eec0YxkFyusnP/nJxz72sa9+9avGFIF73/veaYC+/WUv06Mf/Wiz4PY+GGQdjDRBdnuS3f8XS7Kwa/dXdZ40ZDGurAt6KdfJYP+5z33u7//+74WRffjDH/Yl7nnKdkexqZyTHWXZXc538+bNprssYVsYBcHNPjQaA2Oj49dcc+MNa0YGlx5QqzfH04pJgPIkb3Egvs3jGBxs7r188Mfn/vC73/z2xhuvBsqPPfb+d7vb8IoVe6r3Jo3ibm4nv494an2L763Ho7Kjkn2SFCg/mJrLjoodrY0m+dvxihW+SfKais9S2sxWX75sGevxTEwc/sd//IcdwMbp173udd1jyY6Sr+JbWaCyQGWBXWSBQO26O5dRAmJ2smKxg0VK0cUVRg0dZ2/goA8OQJ6EhkKRER8xj3/84/knjjKylfV2OxeCP0oEYUaWRGBoDntmeYLST/F/9Vd/FZtz2H87T8jMXsEFRcmqpgqJJNBhogUl50ITZkpb8W/5yVwXp5Fj69dCE7tDnso56TDI7vOTC+FtXVaNze5A3WlppF233Ld1a/IpGkNNyyaWS9P3TjxQnV1th1L6hgZrA/3tH37/W+f+4JuHHbTHU/70Ffc8/KB99tl7YHDAUrOvpKSVD51F6o+LLr7n+jjX47Y1k6Bn40mHJIaIwimYGC12cgHwTQr/JIk5IV2STeT4WDstKB+w//5eMWyQ+N///V9TWXyVP/qjP1q1atVOlrPKrrJAZYEZLZBBTOqcikuvNmOqWRJk5rOhDyQaYswoA+LU/U4v6o5QJ2vRQy8iwTEuPaFxxBX4O9LOUrucUQ70SNj9qDsGH5FhrhzIzMsBNEFABbDMvfx0ynBHdmX+5Uc5HGJERhFpzLXzLco0W8yjqBKFFRPuEhNPg0PEuGeGHBJnWpCF8aeUNiJnrD8daUPOkDlzkEtk7WkWqSPhLH/i4CpXlRkTokcj38g67mIifsbkZcqcdjappqTJwpSfThlZJugRlnY6qTyKpwgi0IOPR8ranW1nJEaAMucrEK2Av5eLpoOmd9Y7+WnlnOxkg++87FRi/okJmMmKaJA2wDhbUa+1R8fHRure1mU4nHAdJtY4BpqNvvEtV/72t2d/68v3uOueT3rcQ0582PF18xfj9r+mLbDj41751Sj6DFV/AgH00CpR3EbVCRQmntyeqAe3HfQommhJTusn5sPGW+OpPQ8NDjpAafrKBrBPfvKTAo997GM7XuS1gwSr2FYWqCyQLaABehuHyQJAU2QedzNBDmjRJghz79eDspykg6fuDhNT3ZNdaKbdZQF60YVgzkwTTHhu8IJe0sa0/XTKhNHQ6PFcbG5T6zzuLwpd3ANvZc8h8iVVEGQdy3JmmkwWT7Eql3tw8Cjop9yLX2YblFJFQgOohFyIoOnINGgyc0/F+Km25AqTaTJnqyWMiZhhSRtJgn/HPefbEd/9MwuGmzNCSqp32kzfzSrHYKWOMaZyIXDWKBPMMqCuYjWdPKF+lsfPHM6BWWY0GzKrVco0v1qtRxJkhMm1vUPOHgnzI1tXaB09lciyaplmZwZIEl3ZtpamWqoQi0q9Uw//VM7JzqweuzYvXsi4XbJ777XHnmvHbx3Zqsa1LafwNFKvmlwIZ1D6G7UNa9d8/9tfrY+sPfVxTzjpESeYbBrZMso5ST1p6uX5NgHjOz2Nuao3X3zmmv/U6WKk8SKBlgHEQHLkkUeefvrpdhJ/4hOf0Ls5G6qpT520iq0sUFlgrhYACxyWA4xAYV+KcMjNdkoHiL2swnjv/a0nnniiGeUO9uiROWgHnOmpXF7QZAI7JgttrfEaD+EZEQ/86i2uXv5BDBcmxAAyXALeAiKAiRdmXHbZZWQQabMEIbM83Kc4Pm44R18+cpBpcoBGl1xySYBmTpcl2SklpA5cdf3117sDCgST0Aw9PpSCdx1v0CkJZ87dgXjJBzPCSe4yAlOQQS3sjEPZV4FK2dPpbQSsGnuTBEh71VVXicREdnl2f0qxu2WIGObF3MI+xcXQyD0gNS1IouA8cuRPaXrk593vfvdI617GecJonPGgET5SKTIGwc1FbF8aiSRsqJJkJuVAWXg6ehUKCRGUXTjGIZiCBliDvpwquImRi+TqgAJiXgWKXk1QcLYHk82dwCKJR0EieSoVRajpfQO5LqlgioyRxdOiXDpZeKlUhhtuuIHYWPkpC8wRE8ZdpcIwCjqnigBiCpJWcmFtylvFpCK8fKPys6oKjwNW6pt6knepdXAr/5RKzWFDeskCc2OlOybKl0gKSEbx5k8BWXgxpsgyk20N4yMLd1l7k43kMrWtTgtlEzUklGX23/u93+tmTmZah+L4KD7VSdoQXtEzDjm7E+YYlLoOPVU0Z9WbviyvBN11Bd0KykLFIK0qIS+tiXmpkHl2BNCrPwqIJDqWjjbbQRx8cPZGZnWMWVQMNOTUQf3sZz8TiMvJZCVLTj8jlbpEEY1UwEUjT2XqTgv5unrI2SHJ3H72svXcOFapFqAFVCPDcqttU1b90LsdVFu65cLVt2zYtLXVtms2/SXfpD0+NLC0Wd968w2/PetrX/i3t7/u2AfezyrLlk0Ge26M/0qNpggmX8X/Pa9p29lEqonnpa1fPdntlIeUSkunafdactnarfHNWzb19w8Yaf7t3/7tec97nnf2GaEdDN3R7XOnqFtlUllgoVjA6GhEfM5znsMJ+YM/+INnPvOZj3jEI771rW99/vOf9+ZW0MFY/vWvfx2GK0sMAwFYX/jCF7785S97+2rgM6zEG1AN+b/zO7/zl3/5l+CFwVWbzWNwmYkwerm/5z3v8UEMIMBPg7p49Jg89KEP9UZXozLM8eMf//jJT34yVieffPKzn/1s/lJmJe0LX/hCSeAw38B96lOf2qOX0I3YJsrrgJye8Yxn/PM//3PmkwPEgPOcjSaYt8oCPaQKJAGsAI7HHHOMg9cglxynywvlueee61NO7oBXKCWSnGDTH//xH1sNFsA28gVlzjzzTDnKC2CCSIjxrne9C9ZRBKSFV2THqgorizqbgIReI6mw7JIFGYFFMoepFeujHvUoZ+7vd7/7KUTvkKW1vKhGmMwcfZSgO1284/5f/uVfvNuXzGiCmzI6+OCDFdlf/MVfEF6kmuCisrAruOUAVi5iKFnTT14HzOZRWyQRr7dXlOrk8PBwWAl9FikHUH7jG99wQJGdH/CAB/j0BBDJhuqzT6OoGzwNKD9wqretUFOBuoOATqr86Z/+qSxww9wW4o9//ONQo9r7d3/3dxBkziUCaLgQKs8HP/jBr3zlK+wgBgAlMCOzgBm0Jz7xiRha588lm5nQnf0p+9a3vlVCddtpGWRivvSlLzEm5ojDRDwKLfG0006jFHVERnzmlgNyV2of/ehHKRtIHb2LSORRvl7cbyeCmHe/+93ve9/7yMlE6I866ihiZD5zCIRIX/va11784hdLLhef+zj22GO1mne+851cQfJosCeccILcy/zJBsHbua0DYcaojUFDpHve857aF+PoQER2K47GpaJqXyoqqzKCyoYPYi2UJL7Wgk9HvmrvL3/5S49YTDG95CUveeADHyhhWbZyGD0E8p//+Z8qg63mWgrvq0xQDhPJT/3YE57wBEZWMVxcIL6NqqUhq3UkVPHe/OY3681Uy1BNJBVUY9WPhyxTYuMmXr0loUqlu8At6D3qtklZkrmFp7XC3NhVqRamBexRSj1s6mfGGvXGXQ4YWrnv/uZqxhw4Ab7TEZK+enFo/vxzfnrBOd/dZ8n40UetWrF86cjIqI6u6DDSuZXo0d0n1k5SIJ8jmbvq29UhzT3baVMWStEyqUvpds3EXho+2VA36v0qcJIe/NWvfvW0LKoHlQUqC2y7BTQ3AyFUFHONkKsXy/BMgHjxfkLGWmIHYzAIPjOOmj+WFgFkaciMYZ6/8b3vfe+MM87wgpqHP/zh97jHPSZ7stuxkQVI+qlPfQragxehNKxkFwOzOVGgB4IxMD/sYQ+T0ngfQFOgzAg9NE9+8QSYMq9M76nxHugJKJzjywHC88eAZoKFduACHcMgZnxNghIerjJvwlEpp81h4Az28hLbNBGqWy+sREcqUPYjH/mINWHGAXfygjADekRCiohkfELKLpwTUAwBVrLorWOWQUDyt7/97cAiSXDAFkgiDFaEAYiVNaD2yEc+EloCiGEvWkuVmaDMOf7iF79QKN/5znfQ4IMDnnppNO6rV69W9IoM7NZvZ9c0s8oB9HFxDn1bAzLzCLdsKKaGWSFpLhCMzksheUe5B7co0FisUExopFVYBONas2dUCfG0Vl0BRNq5I6ACsfEhDD7CyLBSRphkaXOASJ/97Gd9j0vp05TAcsQEgYQ4gKH2IfsiJHtyoXPCHFBLVT8iAaY8Q19W4VOhJxipCOCRckdDBfHm+DmKp556Kl89MykHCACg823YEOKX3J1qkpMHUCawqb2HPOQh/BxsLdfgT0FPaV1mNedw5EUdi6WsoXP493//d6ZgH49I2G1Mzq1vPhKP9yJfRUN3IqFkIlpTStET21vUVKQO2ZQsf5sjqrIJy0W+1JEjBC+sSnOSzT5oX9yDnJx9VHIWkJEaFXbIT7sDaFDiLKCTwb+bJseQX5gwREKvIrn7KdOochoyVu6hrHAk4ZZwsczyqFTRBBRiZIpSPGPqkV75ylcedthhsohUOd/5ClTOyXxZcuHzSd6FTrtRazkMP2DTdt16+oTYegXuus8zrrvx8rU3XP7SF//xXe68vw1cGin/RR0vdnQJ2QSWPBK8JjqSVP9nuiYrL3couUGla/JJKWohBJNS6f8QNmEhW+JaaZ/3sj32gE50YT4Rpc8ydkYHsUAVWQjGrGSoLLAtFtCUYiAEhcFuYNFwCMeYCAdljI6G8zI/cBbigXeNspY1gJ6YJ8ZE27SiAnZ/97vfNdDCJWCH0b28RyhYQbcm8r1tE3IyEpuu5oHc5z73AfIQiLERAjqBz4RF4gwcQBVGegzL8viJAA5AM2O3gAAHxACcsKvMSl7U53WAjNA8Bc3gEl7WyBBL5dW0MGUAcUgIrAzfKfNhRu8CtvrEebPWYZHH5DdK9sEfPQNiLgsoiukADiAJlLHsALPCMSCXLMjJe/FUJDPqDGlqGjVnNGPANh5YmUbhZQF55nTNpmcjQ4eAEY1AKKCQgpCcztbPzDybyAyRF/LiBpqzw6pVq6y32HyLG9VIaLFCuSu1D3zgAx6xA73oiBUmmU9wtruJfyt3vbrk6piKZCkpDIWGEfiuHEUGUQ+VhVLLUuUAtgylYih9AcJERqa6LTHRl6nVMRsXGf/pT396rAEyJsHQsL/cs2w4EAC3zD8HDEDUV2m5KJS17GCJgDHZSnJVXY3ljvL3FDH+TAQcs0DmIBBC4q9iYIiYYH5asxLjKRpyqhsm+JmI1rgxy4Mf/ODuOXtZvPe97yWVvX/E0GbNrysXAUq5rF1gxc2GbtlQk1S+4qmZVS6LJzxdfAdZx081UxvBWXlxk5Qd75RttegO791TnjmorXLqWxSBxSsCR6OmBQJtR12iOAuwCfdMX1TOUQ20msFEClFNszKj+cid8JKoz1Qmg26KpupVTotADcHTFbUlP5oygIxgUgkophBySsocqSZ7A7jS1JfqJEklR/XQRkHVBiuui1acK7MKoLFrNXTRnfLDUbKDS3Y8YUzYSr+q3+CqsWrOa34DlXMyv/ZcsNwCbluZ02JGuN6ckXqzVi/6fPUVDh8aNDG27sarL2/2bXri4x+zbI+l2moiT5d1lYahvs5f0aNto5Y8meK/9JbeDuckof4Yjm/ns2xjBjuCnM7hlBFsnMHMxqXFcu35vve5j5HAMroGbEaqo7vfEbJUPCsL3KEsoMcxWIJxgClAAxObBDVZ64JZwZqwBsgFUX3605826wlPHH/88TZO2B0BoWY8BwdD80ZZOBVmgj41WAi7Y1yHOyE5M/H4+6wEDvbSwBkxZmv1xmMwS0JoOPaVwVUESJ1j15W6zMmr62FnBEnikqL8TPcLN3zxi1+EFdgBuqLgH/7hH5KNe4ASPQxquxEkZOIWqiYY7SBUO/gRFB17WqywZwbuB1Cs+nJvOCfUREAvMBH8BSh5gOZ3acdWmLh8qQ1zmIzPhjOT2p1i8lgppKGhWElmnwBhZcmnDFt6UgQ2ipBZ7gGmcRseHs7CAHncQishAhwq5oXY4LAOy8gRciIq1EhrgqkhXvtOLxWAOgQAlDljALQaAh3CUnwhgJUlu8VT08yvW6OTCphjPRDWOptaR7YwI3Dpp0wDZXJ1Mp7rYBjSupM8C6/4LLkoaMIwKaQI9FNfadKRPV0CIXwwxKF8lXMhsBrLa1W9JYGGbQnjnES5o7QUw2lRRVUMASXLEwCpjzvuuPLEf/CXr+bDhyeSSo6VtRGVivB0ZxOKQ+1Q6UUXXcTgWoo60OGcqEia4f/8z/9A89KqhEpEYyRS+NIqjLasuEnOyTeAEknZUTyrGabOmorP4dkHpCK50mFnTrssrFdwqKivCVAks1IryMx3VdNUvMMPPxxMP+WUU9gNB2Rk03BYTE1jH2bUFkJ3Rgs+cqGX+qNV6jrgdQWtEcVTWciX7jxSVVEuJ510Eko1IQhy289GiPgp79kgQTwlTUekvLhDNKKLEnRnZD3Jgx70IFLhw+FUQFkd7gc5NVK2sgGPG6NK4IlYQmZkT9ZgMdVPf1g5Jx0Gr37OxQImJIv3Bhu1HEEZb7Sb6chJ6g98rmR8SbN50W8vv/GaK/ZaPnDwXe5k3DIA6Ry0dF9R39pqtmB0dXnSi4i2dduMVl86vBJXOTI8GYkKVpO+SDSy1PNE75OYJi9ggsGu/yf1iuntyw1SNfsHau0R7xZO7xceGzMYmEswhhmwTaJEzxsSs2VotusVqCSoLLCYLWAINI9rRDTZaVsOeGQUD6jnUWgGdtuBDTRodMCQAyrgqYYZBNEYxRtQgQZjsEEXBNdgTegCHDEeG63xAYWhRhANejDBDIUjwCeas7lGm8GMxEZrWA0fCBV810kiCJp5NzZ8yVmSF9gH2upq/vqv/5qEWSo5gs6B7x3hgAtBVfQ8DXvYQjAGJDCvjPVgL4jEukoojgA31nDgBEyUUI6wF2wKTnmKzFMJ9XgeuQN8koQvsa1aQ8mMDNOHJCCg4wd4yiWzAqFgWR5RbEaC8OSIvsO2gFHMwQPK5FG+L3rRiyQUDkwpiSLj/4DC1HFUBqw0h42bvHJ2wVYFUIXQqDCEkUr14JmQLbilEbKvTz3k+YBiNsiB1/C3LKTtkG26n1ixm6xDX+UirSpEZtLKItQspIsxcTpOKd76g6kx/h6NuNDPf/7zeQIqBuaRjPAkJLDpbVfUIpK//vWv10A6TCpTadUBlTzwqOT4hDDCfD9OFIacEzLzHtUiHlE0MZQCXKDXve51KhsZtBQnNJQv8ULfsCF3lwE1LmTRbD1lGRmF2PN1xxBnDUe+gDj75OYcuofkHAathqNLBu4oz9+UhGIq20dt1By4NL51pvewBmLViDXUupCW94IPK8EGVDZfqbVmjaTlHrCDnopvoMZiIi8x86VsDz7UZAfeFI2IFKXD8ci1EYEa6JFL2MU5sUyklFlMT0hxxDkLq6nU1C/patw5oqpxMM808xWoVk7my5ILnI/utVgDKToc/cFAY2C8Nh7+hO0PNV8drPVdftnF69eu2X+/lTZvjW0egcX5JY1mw3rJhZdee/3a8a0tLxHO7kTqsstX9lsmSIpniPQ8moYhJr3HWP+psqfQ7bqkcHrGM4sy310S9umXNt9sXLs8/JAVy5cM9tcG07JR8llqhnmDAedEQy1Lp4XHT418yvhyZBWuLFBZYDoLGPA0LijHdnBwKgbI3L4iFQKbEOBmo6/xHmACEcrAApmfIhH8v//3/yAzE5xmnc2RP+tZz+KHIOCZmAiMCXVrMkZfs6c5RwTaMiYuwzxW9kjYwgHES94hT0g1X3drNb7obF6WmqSyw7s84UqqyB2s5IDZfQH6gB1Qu34JGoun3CfnHIhEeDgDgg/fJndQ9ILGABQgA3Iy04w+M5dQfL5IAlXPTWtmB8sio6c85SnQf6CisrlCGMoSkjNDeA5AmSDCCsvhEPYhjK7YHiSQN6B/JlZhXJIDxCbOsYKG4S0E5JdRaEFTFobyXcA3d0gt6pAtKKMCcHXUDQsLssM/ZzdjABNKyS7cRa4yY+KAbeYThVI2/nRsLQDaROQpno4+rireCVYmxtal0OnOIQSgIXUWcGcK1bhMLEwYlYflAXTlUn6KiZ9mB5haO9LcNBlMQtqgVEMkVy7cS5c1HAsIHeXLAjR1GTrf8pa32D1lVcFP8XGVM93+MJ5Klq9lG3Y422KCbZZcoVuW1Ky0ZcsdCpdlkJWLgPou7hm9LEEgdszJ/fTTT8cNJZMyL0XYhFuijuWMEAhbgrCX0voMSoDeSq/qunOcE7m7QmtlFFVOIARzV0myskEZm/f0Feq5EqRXJFdvEWtQKhtD/eu//qtqoMTdWSNo5vdeOSfza8+FyS15Jj6aqKGkvqDe7zjldetu2eJtwmmtwvJJ2rG178plP//pT7du3nTM/e8PgKc1vJSivn7j2E9+8esbbm1vbi0br5l5inksPGOdY6LqJ9BeXPIpnJOUaWJer/U3a4MDfYMDjTU3rNmwaZPjf+tuXbd23dq0jpMkc5PRBLv0Y2FcaV9Xe6w2NrbX0tb+ey1ZvqTZ127pt5oD/TpoewZ0beYCjVJau3ZrnLCBWPdtvTvvPFkYqlRSVBZYZBbQpgyW2hS8qHEJR0eR1YCkTQkDeebRLZiAIDHeI4tRNicR0O9pmCAIhAGy2JBg5j6cE+Mr3GBIRmbchfKBiRizI6/glsP4QLHEMw0pr7iyVPMYMKFrotrAD+7oT0KqzL8sFfDkKXSlX4oFEMDdzC4k4RGEATaht34C0cJJmOTkEWA9Ngzfw9JB5EK1eAqXuITnrKxdTHQJWGxbi9no8CUwLAsT+SpH6M3LiJwwliQiy3eWx9AjxUpxAkuSNSpTimQBe5mAQnPekkSOmQaBFTOPTBWDWRaRTLSTDUFWPxMLyIhhLQtIpYDUz/LTWYZD1FCtLHYOT5l1MFdGljjMWHM5IEhLYQAxMaZMgiFdrAZYhFTJCW8XkwrMky+LqnCZlIvrUYdnksm0CHZ2SOYd73iH7PjAFqM4fpEvA3pDjPpGKm4/jyjKNycP1dzRS65Kk4FjYOMifyDk9yjTz0uAMJSyqzMj7DJbi5/qpBhule1nqlx4JmJyQQiHgkynu+DksD8H3pVZaZvDw8Pi0ZggsKvC5slIFTRM55HJEVMGskCvF8rJd2aAVC7FLdOsYw54JJ6a2oKeRJcYMSEhLSJAQWvUfHgqa8jTVZgg3p575Zxsj/UWT9rkmaQ/yxbX3Lj+6us23mQ+zokSqwCpRrb6m30jrdqlq6/kPOjuQzEJxtuNjSOtS68ZHW8uG28MtetDjYndW4W3kxyK9CoSHkvhtKSux2uJ0/ax+jiXu99ff33NDddcc8Ulm9evueaqa8ZGvShm69bRLY3BZn28qO55nYV/kj2d+TCtAzbbxyZZptYaa7a37rmksdTernYrrSb5TmVfn/lFXYzldY1WK6W4S9djIwTsovMFqkw1ab0GD49yF7B9IlWpKwvs5hbQWGgIupm6g5amBBYIQDQ7EEBPyMZ0gLbW3cRyjAAyvgewYv9JAOXUYtvp9IIZZT6AZgvtISjnmDlko2vjwAdQGBu4c/z8BoBF+MCdADZu2ZaWwcGUGdHObhOImfvBceKc6IJESg4mwmdmUszvOh+sX4otavTFKtjS2tQ4a4iRKuBLOcd45Gm3QaaUpyOSVMzOsJJbl4hNesEtc85J0OgzbWP72Mc+xgIdBIGkeZjk1LvabaXsyqJmPjmAmyUjoEqqDm5o+Gy25eAmLwhVlQsdp9RUpGrJgzU5xa2VKufSO5B5ZrY50DthPM1i88Yd2FA3xMDKjgSAkj1YsYzCpZdByoDFqbMNrMM5kYXmRnGWLLOKTCPGnRltZ5I1re3qcS6IcxJP2dBWN2Ofp0ydy7dbNfQuddLeOXXS5jQNqptsO2NIHo4olV1+yrSDJ5kVog5EjeKZ8znL+mbiSMiM+GiJmphdT/zYTGBGkoXhAQbkpOGmoWmw2hdDSR656zSiWckx9zCeBsGUWecsygGU+Lj3rvPlJDkcueSfHYGQxG49rizPk6vpHWW6DpsDlWkmVt/8pDJuoYuAtJlgvgKVczJfllwMfIrvdlx93Zr/u3zj5tbyWtqwZZtWeh3XULO994r2Les2NhtpEm5CGS8e7qttHW/cOrJs6eBefc2hPsfi08qJilh4O2nlwy9Vs+4Ljims2Ri/6l5Xp/GM3XLLTZvXr738sguvWv2r/r7NzXbfPsuWDA0u6R9avs/++xZbveyemqjW6d+CX+IzD1cx0m4Pw7QGJL29Zk7bjBVLOzqFWC9K8uUuXuMECMzgmqrRbZlyAHd0TBqwkcBlENXUowHvoJY8DwarWFQWWBgW0FJgC/B6eHh4OonMd4JHWhmgY7+EFQPwazpi8cZyyCk2KnBINEOR7kZ6LVf7BTrBr4wberCCM2Rt5z2ewacH8dweEZVSxn5ZQDl+mvPuzitimMsVijCIAOfEPDewKHcqg7AWi7hkrAQ5wR/AE08MAV8FqAIQ5YVb8MFhSrE9nTJ+xkieCcRDNhegfNsQM01KM80cTiIp5Q5hlB2/VDEpNR6p3nUaHhPRlGJD3NQlULjbhrprKJkpGAo6l3Vvhshs/HNXRXtTdjwN86aiKsxIqjJBPC3HlMNZbM4Jn5wRJFdjjUFMijJ4lpPkMNVQIlPKKoaCyI8iIeZ0iSnz/CjnmAWTHECXtYByUSczMa9Pi+D0aoOxXhePctpMGQEly4b2RipcivQQviPhLH9iq3qoZkoT/6xLOTn/yr4y0iJWo6ytCZAkl0tOFeIZ3DGkOybUdNFCmE3sPrVuydtx4cnn4bjqTLRcSRg/OypZgA7L5LwywXQBlHGRKgSbjjLHo0fpnmOmCyAzx6E5WJrT/3gFs77OZj/HhCirdVCKRupS6B58ZsN5uhx7xFfOSQ/j7E6PDCrJqTA5dOuGLZt8SXZoebMx0K41fWLQ5qV6/3it4Xhffb9997vLXSZekxf+R6uPizLozwq5mOK7jWp5cnTSvfifR5JqfkqQdoj19/N7RjZuWPv9753185/+ZFmzddx9h0/8vRPvdc8jD9h3H+Ng8mea6U0g6euPBZP5tzWR5s3XibMwhYbTCEoXl97NZRLF5IqB8Jvf/Kbt7DZo2l9rYgaKyh3fNGyq6MoCd2gLaEQxjkJLcDP3fjpzcCcANcOkZsVPcBlNpyPW7oys2iZQK+wul7jkaKCVHdgRk9BipuMT8TZmALvAGZ6IZ6TvzW3Kp9CeQxrxyHuNfDgCKAwnqkwPIdGCEVzZrQIcvUY2Vl0QA0/2x4sUA3bonXzLxaIEMMqBgREd4aUR9VkSPSvhmbmJCUOV893WMGBHAELKJYwfHOZgOvJzdbAyDcR9tR5CvLI8eJZjIqxkAUQWKFNGWC3CCoLkb8CyZcW7ibc/JuQpSzgbnnngUFEVrpqgmGhaxojT8ZEXc8GUVFOvFESZEhMXhpobC5Qf5TACTCQH5XNkdwBZd+SuimEfjVS5E2BKayt3WqvzKP/pn/5JU1I93KkZts3qSM7OdHeJDEpmDOffU2sLPmv4spe9jIeGiTVVSyjIOC3WZJzA4UMilhcOZYPgFpfynVLIMnGEkUUPFkJ2E2xnjAbFG7HdztkYWZjOsNqm/mg+tOCDOTKk3WkpdIlqOUvJt1WwyjnZVostRvp0esLpd29/TNLbzJX2O2kUBiExqUOxvcurhet8lb6G4+sTSqZ9Ue3mYP9BB+93w00bjI7OVaYNXBOPU530X1Cn8yO1dIp8qa91Nfquu+qiL3/pM7/65c8ff9LvPvakh97/6CP3XOZlL4PJYxhP306xvwsbaYr8d4iDQsMJSbf3H+abgUXuYnRtZhcM/Nqwc5/eumh+yMfRfEpZP2UACEbod1CTnkHQ6nFlgQVsgdwoDO1GvkADObIsuBYEqBk1BQAFUMNsJQI/O8jip8lRxHjqxxBLi9LFyRGOgVbjzWmnzDSeeoSPtH4Ku3Kq7Q8EWxLCkSARNA/uQM/EZhPSyiLJPalmBOJOKjQgF3qUEUkpSMJ36G0TtykF5oCc0OADeZjrdXRHfwWR2K3Ek4FIPKIUbtuvTnAgFbYYusiTLSaQFZllXlgxDm5KLfuTOS1umXlE+ok4LJltkukFROJJKjTEy6m6WZVTbU+YSHFlJrM3Al1CfUlcIbBAZjVlAJk64JG6xG5lGmlZgPqaAAsQrPw0h5HFo8jLPQKZYKEFSEsdUpFzSqWiMugTlD6PV/sKy0jFSvFUwrhCO2FPNcx4KlKMO9PZyebrol754HUUphL0NiqnkzmmGMxRcktsBLWTzVxArmPBEyuXyB7GD0r30EVhRTjHb38gSpM6KpjdesPDw9457h2AdDHTKke1jpX4Xfw9DozTR7F1bfuzno5D5ZxMZ5ndMN42qv7+gT2WLOlvrt+0db0VjvF6Okhhz5KBozXa0EhiwKW8TVbOg7stHazf58hla24Z3Or1XSKi84pVieRbFPvCJKj7olNff7O95/LauT/88Xe+9b+3XHfpXzz/yScc/4BD73bI3nvu0W6N2R9leB0fL05oFE5J3j0wdY/Y02cpBJkmXVF689d76vonMorOqLtyiHdp2O7JGMU7cEyseregKQdzn97wY6rVKopJyu7kVUxlgcoCHRbQiAyK0aA8yoEg88iQr8uCswHrhz/84cZOj7T6csPPYYEY1CEPE/lmEIJnYAIYJVhFZGIxDaZBgNIViwCE7BAMwfZcuMmak6CjkAvtHGE302FWm9iZcznTQtgETykYONvWKfMgZRqTnVAFJ8RsrmlRe3tsPnEUxOZyYXtR9E42OPFPzDcDsuW0OdM5B2LOWBbwH2nLfLY1I6xYBpSUkA8GKVKtzLA7jJIZoatydcpkil5RZtAf8vQo/ZxwOwMyiry2iQ8VlKySilRqiBo4IwdkjE9N8/fhpeQk0crYBw0juKZj2FFwmYPA3HQpc5jfMFGpQ6oezVO5u+irQ/DCNx0CI6ifkojskCd0D1tpPk775DYShagbEamR2iLheL2a6Y0ddndrXwK8FxMo9krZVvfkJz85M5dWwqiWBO5uHZkyB7KpiRRS5UfbE8A2uJGHWbQyVUWYT2VFWv/gvYheoEcFZGL0Rd5soeO1ZT0ssD25T5m2ck6mNMvuGcndVo0OOnCfkb6lazZC0tY5VADOSTrtvc/eg75V6lSJBk3/1AbScYuxwXrzgBXNFYOacbE1rLCN8SUPMU6JO8guUaO/b6DZd9FvLvzled9tr7/uuU997KNOOvGA/fcbGmi0W17rzgXinqRjG7eBfRkVnG43Xt1m/tuiuxtAIcBtBLcl6gptaxueKq8ZMspJ5KWXARF0ZNq2rsrJTk3d12Ft8RIDasRac5eYVURlgcoCExaYsc0a0Q2fZiiN+mbyNCuAVeKcMAeibQIcEYAAJLHLJX5qp4FjDLdgR7kAcAiaDlarV6+Ot+IiRhA0OWHEuMsxJ8xPOwIIAmd3MAFAnQnxCHIyx2H/lZOp4HWZLDLCUEYuioQuwrGHpIMYcoKo+CfIaAozOU1uixTAYQkF+AD04RLrvd276SSJjGbUqEPB+Ml/4G5Z2oL/4Dbdo55wSkqRsohc4l7WwlOdp0MydKQL4R0VyKd1c6qOJH7K2pa2KTNlK7KxswvbEGA62cSrLeElqoE9yLofhVTurhAVjUAOdyfpjgFz6Wsym6jMqMhyTca2mz6yyJQKgr4dZATAzSUwHZNIEpTBsyw2U/B8WCZs6JErWOVApArdUQK4mqF6haBDnvn6KS/XdNwUurpkZYNxLGhw2knVYYSybMGNwCpwcmu63oWgdmlcWq5dXjoZZ1osQaii4aXoNBwbw8RLBcwdRHJ2I4aEAlq3lqiZTycwYfg2pmDUgaDpod2UTHBwUWHKhBEZLV0YaCEnebRZ3Sz5nTxRajoKW9atwSo+8Ibdpsxr+yOn7SC2n3XFYSFZQPvXB9T0Zwfuv3LpnvU160wSFBu70tas9kCzfdCdve1+kJPBOUHtX52VBI32iC+UDKYNEZNbuCYVy70KejvCGt61Ozryna/87xUX/erBxx1zxnOeYYN3avDFmn5x8J53MrH44p+JTV3Tdx8a0mRWqROfskVlgukCZSbT0XTE98hrOm7leGGXbk6rZjW9lZ2ahtIPfvCDllDM0Hi3Y84R5dz0yhyqQGWB3c8C0YLcp1MNsHAe2uFgrcyF0rEBTUkgLgn9jEtYR2S+2YAqHLASmaeQgYRiDMDWEBCAWeJzvplbMHQH5X3sHNbnPJSfRhKsNHbxQI9MBSI+eMbPzF8vIUesQiSUCDyFIPUbnuJgcwhgbcN3TGqUGaL00wUMwalYyVSfA764i5eccdxd9HJBRVS2+ACnWpCREOzw4XagB4f3ve99Xkm0atWqLEkI7x4M8cwxsw9AObwIkJpgXo1FNTBuyuRJmXYbULN9n8wyzbYKeiooLxZmMUf87TPxaY7MStoIl1MxI6QIJsq9HI8SvZUizu1ll13GFGaIOR7d8L3Mn5Flquhxy/GzDIR47kRyD2FyoAcTNEEGMtoe7IQVDjxM5wHMbXdIghKrrKmSVbFVA5JDxvQtZ4QYKzHBP6cq05TDwTzoc7zqpIi1L7m4EywaYxAE53ISpmZDUqmK5fjMcDsDtOiuOR08LXTwclVLFSkWXbl5UcmDMmsaP6lG4IhU/bKhWFVlwMQjDVn7ElAifEiXOiyVcd/XHtV/uyiFZS0vbKUy9cAIUml9cL+XVXTImX9iyyVQRdUB4SxAJugdkKRc66YjtsKGjGBE0taQUZYHFe+tZgQvi3O3KEQY6mgvnk7HbXviZ14Q3B7uVdqFYwH9ldqZ9lK128uGagcfOHTYXZfcfXjI32Grlhxy56VLBpx4S+dNuA32NUcfb/GEc9Ic39wc31Qf21IbmfjrG93srza2uW9sy/jYlnZrUz+y1ujVV1z5w+9+9b5HrXrSEx410F8b3brFn13QBtkOU6Q3G3dEdf3U/MpX1/OZI5LKc7oknMOlVbskJLZsdUx6YTFQhRdoPvShD7WP4m1vexsA4Sky96Cck4xVosoCd1wLGCy9hMogqgWBnhB8R1OCM1wRqa0ZUC1dvv/97zdH4PNE4IhIbdPQa20TVjDpyz/xMivNVqpIyL4CwcodvaemQsEICSMmGnIuCdDB20VlZ4YVT/QeoQmygvFEzxfcxNAiFEEj0iUSOIDwoBwwzuaQiMy5BE+RBePkhPg2nFd/+hA1T0O3E6xAB76HbodDxcNBHzZxxx9zd8sydmgwAp5mRkkebMkQ2QUrEMolMnIsSzJjGHOzyGFYQsI0mHSnEom/i2fCTYL5wCOilik9JbYpHo+AYMhPd1rmhqBMLww+gnQqiaLpfmo+GNznDsnIgQG+ExpXmWdmKBKrN73pTSa5ccvxswxgS1qlE6aQo3J3F9+bQxaG4/Swhz0sptu5Wz5brpp1pE3Sl+TnwJizl5AdvIvJvH4H/fb8DMEY0G4llUd1ktd5553XUWqRBeKgp76TTtqsGuVRRJJ5eyTZ1rTKXZ1kE0Xw7W9/mzFDksJ46UaFuIRJqMTtzVYtfX7HnIg2Ejl6P4EvCvhqCjvHsbeyJBTkAtkt6VVmSg30t+wg06BJ5ijqPLupzJiwjBjMXQJlVn5qyIys5hOp/Gg24WDrHp1Dd5IgIAOvQ/+mvRAGWQij0anw+knVzwHasIyGrNWuQUwAAEAASURBVGuSsJvb9sfcrtlvP7uKw8K0QFozKf7GUrXfOt7a0je6FXZuj46PbmmNmm4b9QUPbQKSTiQTWqTVjaINaJuWVxx4n/xLe8H66i1fMylinNvk+1977XV/8zevGz7sbo94xMN8UUAvbOawqLYTTLA1+CRWiWH8TXhB09ktJMj3YvEm3ls8wz2SzJ6+B6WOIF89yDwyzqShphhschItXGck0qe7vBhHH2fvZscOjenUr+IrC1QWmNICRnpbDozT+i3rGL4Bp6Hp3TKxBphHTc3tIx/5iLdUnXnmmcCTRYNwBrRKDsCzn/1s85eSG5i9tweAiITBIcLumIv56Ec/CprwTOAJP6Ox50wFbML2EToQHy5xFvaLX/yiSGTuWZ4QFQgAdwKeeuQqM3RWzYwGJvrRyy67zBfrEJQzEkbvIhhfC9qjoBwhhoAv6KElCd/4xjf6Bpy8AjWiB1CwlRbmIJu7JB3M46dHLpTIuDr0Ep6SskckcwHH5mhkbf7YtCv3I9MnzQvV4q6wAD4TtCwMDwV+zcQC5qd9+RtOYkYz33/zN3/DYcA5aIhXlhANj/Sss86acn4XpeltW1M4QsQDHMEyYawwDHnKWUNsBJMdaxCv/Gi6cAcT9Y0pGJ/B1TRDQ5Y8OKAvyx+RtMh8VBh4V41V6CA1wGrSPT/NYgQTRcYvVQfEK7tVq1ZJm2m2PxC54MmGxGAW8rBhuLgd/D11gdccabVUJYyq1WGBjlTz/pOt2FMt0sTUCmXh2LdVuGgRhOm4CMCP0rgsenjNHcnLIqkPr3vd617xileA7HSXtvw0SlP9F89Wyk7t6igsMqjkmqpZD+VFDBw66kAk0Q+YQMHE1UFQznTKsPpGZWLQvUPIoJeFyZRPfvKTr3/962n07ne/OxaUIrvMM1pl6IVVGC0/ncdA5ZzMozEXMCvDSTGiFPNs/JDRvvbW9vhI3/horT1a6xur1yygG0GNn0halk8MxcVImCB3s39JY2CoOTTQXDrQn/+8Fm/JoL+mA/YD/SOjLa/G/vZ3vve7Jzz43ve+lyk53VOyyGTWE8HbjNQx0E4x4KUoVMUaS3I2igGyaCppwslGzR5/ae9Cev/KHK4ih3Licj69+RU5pqwnLy0ZO3poxta+7W2FqLw+XAd9myWqUGWBygLbaAHNyu4gL6ECLg3Y3kBl0QDwNfZHR4FfjN8m10H2r371qxAGOAjV+WR4nkQ3ZtvrYjqZxwIfWKZ4z3ve40gJPoEnMgjwlGfi8Jh96pBxTEACW5kgNNDMfRxAe/dTjt/4xjdswgm8K8agHuM6VO1VfgHBxctLfHAIMnxOO+202P5EHm7V2WefHXAhkwkQQy5kXr16NU29NcjxG8YJI4DCnCWegDkR87tmiFmAbAVKTKM/Mvnay27FQIBeuqz8FIGeDDdJ4Ehzw9B5pHKf/YWhrs9Kl9wBINiUGSG5Dg6EIYlHH/7wh2mqaKLz7CAD7k8++WQ4G+YD5tjQahjcJrmrTKzIrC34xktsNIoiKxMIQ2zWjrybiI7gtcUTji7Q72cHN5ibB6ggAmsGiOzg1vsnnqoZTMzUtCN5fmF05FWuA2VWSbFJ1RjTTLw1ENzY00qU6q2IowplDtweTqBpfo4Z9WX3whe+0Py9QJnztobxj6ucUN1wTum5z30uy7ChiqpE2FBZl8mE1VKegJkCLuh05duRZN5/siQbqloWT0xMEFIpmETwcqpYLphUceJfvYqGoyHrZ9Q33YUGnovDHi1b2tDwqL2ZU5l2CKztqzmqIpXlq7+SNdbIQhLbvDFBJnfV1VqEsgv+QUZCvtNb3/pWd4WOibIWiKcd2U33U9Fwv6MJwGYCHZRyJJgapa+gjp6Qr05luWRlJdHbWHkWg4Pla+p08Jmvn9WZk/my5ALnU2D8GK1t3UqNM9W3eqyHQP/ChqrUsXvNr7UNbxtOSWr1Rquvf/NozfcZN1ntT2sprok3EE/+6htq1m698dof/vA8LyQ88oh7+Dq6iTnuOcdGVol5yrpgn5pkyiD5HLEsUzAU1fY59iAjmlQpvrjShjSzEYXMIXeRNPhNEk35b8psDldS/fbcg9FtIvVmaryfJEhWLhCJuz4FBvLCrje84Q0vf/nLO9p87mgiySSD6t/KAnc4C0RbcI/AdPobbu1HAsvsbHE3qSngIApAbzIS6IQGYAKw1cwxfG80tf/Esga8rjEGcwHEDy9e9oUMjIM+tUEwzlgO3COAG4zZdnyBrdAVMCELCHtKwbg9gBrB+Eu4cUJwsxE/pswN/2A3wSy/mNLGQe4xj9PR8MV7WaflVrAJKLE6RGAy2DPmEYAOsmAlC36FaV1Cgk08E9vWgxXJORuQE60hHgiMgs5XEN4V06jAFhNBkzAH2fROoHNZEpHcFaYmKhvaGidHMYTxCDSh7JR2KEdiqFwcvbNoDMOxSRQN/MpXDEeR/DgTA9SG0ihOa2RwmIzK3EBhSnknErthBT/BuyL1ruRkGbJJqDJQ+b3vfS//CppUmtRkE6yi6CMgZnh4WK0AyOSrUNiEYeFFRcZKhMcN5o79UeT3HlWsYhdTWbDMWRJsXWFJ2UUAgRLBNlTmtYpRGylITZZnTE5p8OwQMnMQ8OkMoro4eHAzNwmgVBY44Kye012VU16yuPLKKxk56tKUB05kjScZchYhwHT3UKeDWLXkS8tLCaqQihLC5iqbQWBDFUb5siGBLV0qNf4VR1QFKJdv5ikLl0fTydAdj76cPJTKMR304pWOcvc6TcWqqWqPGpS6xETMqBapNlRQyszoqdpIC/XEHkV1I3NW66xwWpNUG7UvZqQmF1R9k2lUQhy0XPy1OzlGpQqR8NHo9CoIGA3uJ7mGzG5k4IFEu2DSD3zgAxqyyml/5pTGCaWi1iHoUJleVrfUFhLSVyUhBh3VbdmFRn5yes1xxDSEnsciISsRRstCyRrSipeclaSa34W4ssyVc1K2xu4bThU11dZG3cu4Gq3x9sio/sh7G9JOraIZ9zW2pu+e1utprwJA7Q99G3GrccU1a3+zes2aW1ubR/WhydHwyBu63JE5qLLfitrl/3f+WV/98u8c96C9Vuxl9WVs1Mflk8cz7tMoya6tRnHgpQinW7EckkgKHjWfeiQfkfq94bjZ4CLZarZ50+aNmzZqBrihTN7JhD8j5xmvQo0ZqXYAQeojC8Wm5K0TZ2f9sp4uyNwNHnqiPKfVI/mUPKvIygK7hwWMqS49kjZiYBagl5jQrqNdGGWhH3ugYQhg0ZhqK0IgvOHhYQ0NYgMLACDJjbsiTd6feuqpEmaeHhnOMYFHjcRQgjHYbLTmCUQCjgI4Q12QrrABHm42VPNhjO4hWPlOSCciXvCCFwArsLi0JuN5MmYZQU8JTaMCIjCHRVQoE2f50jdpXtIUH33Cc57zHHwgEkjUCgDfgF4UAQtgIPvQsCKwhFCvXaO8LLlneTDhyTzxiU8MHI/eng1Gg6jwEck4ASXZh99iAUF8Ti6AA7jsvV4sQ04z8Y72yovA1DdZPhvnBB+gmemcTGA3vR8Iyw5Wojgt3vmjCBQWzArAYfvoRz/6xS9+8Wtf+1qOk/7f0xAp24e0YKKfSo1fiowTIiHhWUbNYRZeBKxJfpRO+bOSglCjXJkPtsIK2pfm+U7f+973JLRvxyVfAoN0cgcHySYGpWW35z//+eRH6RFuwSQkjJ8pj+LC3BWPSKLiufBU9IzAEeI0ElutUIf5D894xjOy/WkhR3eXtMEk8lIPiaEKwb7UtyYGFuMTxcomdFevJJSdwqKdklVtZBQc3PEko3JkczUNZbZzzqs7QB1sJex4pJpZiHjoQx8q3nQAqWwQkIXKpuYrfc6S6gfdoqSpiq30NU8M5R7cwlYhGN1dNM0G7Mix/BONK6wkQEJ1u0zQHaYsqdReiyfoyaa1uojHzdMW2FOFD2eVlSJeu+YYR0bBU3lpHRYGceBdWPfTSBmc1gjUHP6Y+kkROB6ZRb+yMFgpNW81UJ1QqqXMgpgbQzYW0O1o+8qah6D74ibxokleZhJhrOiuaJItiqsspyonF8kR6N80QxWDjnoAGyNpwb1XB7xeIiZilJSlXctuWigJuVtaKKcl/EkViS7a2mzqTLeos4mpnJPZWGnR06ij0Y32D/SPtmrXrVl76eqrNmzaVCim67TE3Dz0rget37Bxn5V7hbaTXkTdJ1F+dMHF7YGVtcF9iyahAaTXedm1kDyb2phxYw8efvoKY/tZz3z6fvvuo/bzf6yb1vv3GGl5G/3mjeu3ON1SuB9WUWocGymLjAo/xw6yBqSuJ+0bGmwuX9K//uY1V111xbnnnPutb37j0osvSb1hOqiSlnVSqthxFoL2uJdWX3pQze+jJB9zl8aSDv56GXhF16wD8ki56BT0jxCPLkCMXiWSCPTg08G2+llZYPewgGpvhAawjJFgU2+lgFTrGHAAHPmWt7wFwgMjQHnAV0KsNDeRyMwIvuhFLzL1qLnFo3LjQmBGE3qAqKxRIEBGjJik1P/go8Eaj30SwTQ8LEi8gHrdEpplgGDgGJtbgBViSIsVkIEVeXBDcMopp4ALr3rVq+AAl0giIc4M/ZTFs571LHDWpjVAVncBcAN/xEPJPkAYSAEC8hNiTjc6lmCiK6YaaC7S6gq0UUC+9J5TjySXhYBIqp1++umcJZAlCxABM7uQGf6EFEN+fhHjmBtWTB3EU/4kqowAINAH5Hr/+9/PyDKlDl3AnTALbvTlwDzzmc801tBUVymvXA2QuejrYmQ+jCJ75zvfaQsKLYgEHfIrZEdIwB320q+SXEZcO0WAVdQr9ERyhcCwoPJSi0xdA3DiJYECiYcbUYnB6wPx1SIOMLgJq8WMMlbBBKVLOVIEFsdTQiWFVTYL+QOav+Y1ryGJ0iG2SiusEIVxCKmkxUdGFMlZBB8EqgTV1GenHcKpUxNga2bBTVoXSUjI4QFqGV9eIUnOgjBo2ErurhkBPTEYkJBEyoWCW0hF06c97WnDw8M+9GktS1HKkZfCUDKSRELTcPznV7/61cCuHD0iMKlwduETEpIEPZtLGPHZgFMGGMQVjySRkcrD/sLEc+UiEM6U6PlF2iCZNVXHLRicXmqRHXGSsCT7EIb/bKVO22dPSpVlwA3u5/O/613vsvWLzJ7qH9g/DB4Ww8Ee1PJHToKJ5Cqzzoe0Ttvzn8Wo/Fpo2E3pEIOHYFeelqiIuZ3Ssh7typLISG3BjY7dRlNhtHGzMDa46iGjEHULCoipw0RSKTW1hZp2kWl9DMIh4Xdh6ylTkAeNjuIlL3mJJZeyAPMbvp2V55d1xW3hWEDNs5qhehHp4tXXXPzbdWu39PfV9uJOAPCWNka31jZt7R9r9ftIvHcJG9bT0XXjlp2F4/VbtgwuH1peb5p0KZbXNW+hNi8j/Tfg4yZ9oyNbNg30te579D2XDKYtrQPN/natf+t4309/feO1N6TPFffXuDTpQycJM9T9g0f64+b7CIrDGo6Yev3mzTde+5uf/eiqi38yNrJx6ZKhw+5+90c+6mRD494r93af6Bcme8NeFiZ9elzcetHN/7NiiWhatoqCNZSFXszEjHkRvYO+zGqpMQ/MetnLXqZrSKIXSGVCj2n5VQ8qC+w+FlDbQRzbJOADE7EGVLr1bgLAjWlOJ6SdHDAbDcEDlAZpg6jxHqA0roOD5rzB4jzj2MFTewRkvb3nla98pXlx7dF6AnxpbAanMOGQAIKYDA8Po9SKjdPuU5oecz0VpIuV+XieEm6QPbxiXLcQwVsgswsA8o5g4AbUkHsHw/jJW0BPeMLAzbQDGtDrLrDSY6xatYqrgxvAx3pZJMlJwj5iWIAxWQnOYCKqQSfQBoN4BGSQwYQxZTP2iuTS4omA2xaLPNIqHbowmkxDyA57ZhkiEE/Rw4KmmW1qBayZxVQxbkAVsxBPiZOBJLH6weYgnXKE2kMYHDLKFOAdmaJ23B+SizcmRZEZKWBx9qQa74WJ1AcFB3XJC39qEikrSEjcyGZHnLUyFoZNOTm4wYXi2VlGZPNUHUCMs3LBx08IL1jhSULZcZg9JQPji2FnVzx1l0SB2qWj59f/y8VYoDjsJJSEMMFNxTBSqMMEZp8Ok5JBJMtYX1IxVDBz/NR0KS91gw055PJScxiBkKFyuUSIxyy+XI5M7tTpyKXjJ1OY+HcnUi76TIM/rY8//ng5Kl/ve7CAo9qzuUpFJKs9DMg+shMjDPHjphLGJqhgRX3ljg9uJNTcchazCeCvoKMOsB6pyqniZxSHsNLBn624cMxl+ULbJzO8LhU5mQ6mJ6qiwQ19mVuE6aKLMOHIknZ/UVxLwUQZUUEZqTx6Ax2Rn93JxVBTddUuzEQ4tWJdTq3gF9FC69azeSpAHjOYcoEQGFmqMjclaDcpCelVtmfQiCfDS1/6Ug6SVVCOulqnFcsIZ3WGtChZRjXQEIitftJFQ+DpEQbP6AkZRCBSlRtRWZjtD1fOyfbbcHFwMBPUaDRNQ9x088Yb142OD+7n/Vp+Fg5I33izPtYeTFuw0hGRYsPWpFp887H2wMh430ByZbgl/jgYqGJgdm+1xkZswmrW+/bff1/OjaXolLpdu/nm0auuH71xrT0VQ45V2u0VyYMFJgYFfOrNvoG+xrq1Gy31//Jn59967UX3OWzlEYfd95C7HnynOx2onxoaGtxjD5+2HZzc1jUpXI9/U49Ek11zabG9M2Y+rd2gYpg3nOjEYxrJLIWzrRq/zojiqSyqq7LAHckCkIrvAIL+oLYBckbVtZGAthAkDGGEDuwesNJAC1UYyI3NMEQMwHim/qvUSP1EAD9BA+KhEK6I+UW4CgIQCb4YjINJiIRbD9kwMZaDIzB3eEe4EQlGlEsAQWHI2/Q/DOqR8T4Ey2yj+cuUauAIGtzMaGTBZCHeUxd5UEaSzEFApDtYwxS0IIzuBS6hGmKpoMzAi+RhnzIHWvgpkgWkklaXJfeYasWWYcv05Xy7wygJA59xdeSIG9CGYZq6KszCwiwPLJJKBYC0PHKpEpGLuysKLvAlbvTiNrAAh4FgUWQiVZ4od5lKIi/M2VC+1CFesCpYxmiR9uMxlITDw8NqEW5yh9twI5sKSbawJ9l4IMT2VGRmwlbSilR/VEsE5Iy8wiAoPZURbiTR/7OAsYBgKgazhFSIOTBQqepHxw6sGRaQF8tw4WRBPFZVnYwjMiWSioE/AtmFzCFA+Y6MWWiHxnBD9/LT7jACy2tEIqqq2E0go1zT1CsAnTxUE88JISTFmYXk0lqyAJdJ6yItxTNDac1QcGZoSrzyo0zTHYgqwXEiJI1kpMIj652cbC5dBwtoF+oSmZWIhMxOHQVKPHXSJTKMX86dOmyCAwVdBIDmVR75sr+01FH3hGVUTpjDKJUyE7GVmszZ1sp4DtiymAqpE5O7jNhEJRFPKsWXOQiokOwZtiV2t9boEbCJOwn5w1JR1tRGqOan5ExHBmIjo5QFHGbxSLyGE60j2WLyxeIe7Yjrdh30jsig4rmrLGAF37xdzFHtv98BW7ek2QtLpN/58SUXXdtqLr+LHsGSRd94q9k3vmywceiBQ2/46xfeef9lL/rT5x1z//utv3WD4+/t/oGbNta//oPrNo3Yx+VwvE/ITzgnya9IurWttuzZXH/etz998U++/dWvf6E9Pja6ddQrhFt9A7+5YvQnl2y4dUufF1Ua4uyhlSYtzKQTJtZP0hYvLW6gf/ymNddcfunFl1120djGW44cXvnoEx94zyMOX7nSx9HSYIk2WprtYrO1Z7GqM1vi+aO7nWM3PdvoQTzXn9LOEChsusVRM9tw9VOmzfQ1urnpeVRPKgvshhbQHIzKFNPkNZPphnMEuVsQCHrtSFibimYleb66h+rg4O6Kp5mh5Fi5PBKJic4zSyLG7gtTrcZv+zFs9THnWrC57ZZZCRTiTNxkFKxyjlB4hCOX21hMFQqp8PQwdCSVnlzabvIgC+aII4ADYhhITCTBweVp0GRW5eRBGUlCo4hBLG131jPGYBVXGFnuWLGMO/4uHFQDMQJoAKPMM55KLpVLvDtiMcLxNARzj6cTmRXFilWOzzzLARzYJ2KCG/7UjFQRL7t45I5hiBGPsl4C8HEYXFqUZTLECES6BPxEE1fOQrwkCHIWwvHUPR5FQC5kFiPgHnyiWDO9tB7lnxGIhB4hdkkY8eWMchLy8P0mpJyq6LNIkuDsikzFuySMgMh85fjIxU+PmDcoBQDxLFWWZMpAmMtdKrqgKWtUTiIL/MsxEY6s3TERI9+ok8IiQwwBP6dMLl7CUDw4hACIBaZLIlW+wmIhQGQkoStbAAHOfro6GOY6iZs+IT/FR9jdJZWnIaQ7MqmiR8oy5EAkQRA04iUPeTLNjgv0mvvZcblWnHeyBQB1DWrUsXKnzZ2Jt7YxZtqsZZkkbapKp+I8V4Nz+xGvcfrd3ntZ/3H3PvjCy66+9uYNmy2gcE6K4SCdN0l/7cYAn2fz6NjIFpDCo7QWU+CG1IbbRhsrKqlpWG9Jh1TSF+ipr/U7++4a6O8bH1n3za997v9+dv7Djj/6qc889YH3O2rZkIbHb2r5AIvGHn24RNtmt9w6ty0Z6im6rVnz4LxN3fFNx4GY0Tsceuih9pVa6H/7299uE4VtD16dbjZFdzBd2iq+ssBuZgHNoYxEe2iX23cObGtLyQk7ckkdU33aD1lEKt1mDN4daeNn5izQYzj3FPaaksOUkT1YddNjTsIsT4gUcL/bwigRBE1O0sGTTSJmW+3cwcfPwsAT3DqeZjGyZSLfkBBxCNkhA5jVwaf8s0d2ZbII49+bG7IeBJFX2BllDpRtGxmFXhHuvk+ZRQeT/HM2FSMTl/OaTcJMT2DT//lndyDXN496cCbJlMJkhln3KOVc9JlgykDYs0e+OdV0uYvvbhqRKicRKKuZeUYgSj/L3/F0xp+hbw+yHtpNl2lI7h4BzEPIyCW3su5MIwmCHjTdqeYrpnJO5suSC5oPH9vEH5e72d+4y0EH3rJ1zerrrks1r95IR0za461N4xtX7L11dFO7z97WwvnQAsfTVxk9PviA2v77HbipNZ58k8kBpTg0gjSdWlnS19507cEXXsDj0GyLSwNotPfbd2n/5Tdv3bylMdofMzPpW4/x+ROuRss236Ujm9b/5pfnnnP210951ENOe8JJx97vCKssjrDgUkjSw0/YRl9l24qoR77bxmhGaijHzIQZEf2OkcwS8BlnnPHhD3/Y0UzTVNa+LOPOyKQiqCxQWaCywJwtkIHLnDns6IQLX8IOCxRD2IQr1fGo+rmbWUBZL7r6ucCLoHJOFngBzY94vAxbqtIJk1bfviuX3H/woCOGfYikbc2V3+KTi/Xa+IH7LF2xvGlBO61vuNL6CGcD0Zb+hq1bFkCa41ZaLIOkRZD0KmGXe79XbNW8ZQubkXSQ3spBcmy4KWN7LR88+p777nP9hptvHRmvp7VvsYRBZpPEHkuXQuS/uPjS75z1tSc/+ndP+cNHHn3vI5YMOZc/Jod0rByr5Clp9kSanANM2bpSTISmucutN8E06VJ0yrTH4x6PklWSEbYhefRr7rHXwvzH8PCwvSJ2iH784x9/2MMeFvtWE+OqB+xh+upRZYGdawHtMa6dm+025JYBUw5sQ+IFQ7pIhV+kYi+YYl+4gnSXbHfMwpV+kUhWOSeLpKC2T8y0hbLdcsLDBq6h/ubSlU6ALE0bptLeLZfdVq0Vy/fgYCDjP0Ru/kk7lHw/3tbrWkMwbcFOKRLqT3u3PE/OieWXPgdXimcciURQAOnxRn30oP2X7LGksW7DiFXeVjs5J9LycWzp8l6vH577iwt/ft4ezdaTHv/I+937iOXLuCujHCksCsLk6IQ02KYMJy78UzbFlSMnIyb/3e7+ImcxyXFH/ktfAscqipVlpxv5Kl5B4+yQ02mOwcl8uzXakQpUvCsL3PEsUHRTu4naVfeymxRkpUZlgcVvgco5WfxlOCsNIPh0FqoYSke5CPZ5Dfgnfeo9TfS7J+cjhZNXkO4F/OcS+Mai3V3NRJnSJ4ScPt1YnCBJ6L022LCoUms43e6n8S0dRkmuhI2ZPiI10Kztt6K59wpvEpZfuDYY9Q00aus3brrkVz+67vILH/+Yhxz/gPsMDfSPeevXmLOwhSMSUqR1neJ3Sc1iSSRl5knxXfkkRyLKV/xwn/uV+M8xdZJ8jhcNAu5YNvEODYduvcXfO8WPPvpoZyuTXYsLTYSDuDs8x+yrZJUF7sAWyO1r9jaYQ5LZM68oKwvsKguo2DG47EwBqta0M629wPOqnJMFXkDzJF4B561IOJzppHlaSBkd8c2RwgeRhVcwOHiSHBVP4x0QUHDhtKQPkrjsxEovzpo8EMmP8Z6vJFzNJ00SipfKEko6kOIgS4GhE4D2FmLvULEVrK/esljSSCfuvcjLGs7S5c1fXrT6t7/++WEHLzvjj5+2dKjuW1Ct0eJgfvrAY3Hhk5hwhiZBecqwWJxJHSdxao7yp39k75Bic6Bhuxhlkpy7oG+dEHs+/rGE4hWK3mj++c9/3hH5yy+/3Hv9HEpJZVGUVJycy2H2sNISBPORf8WjskBlgV4WiKaXOsfJKYNe1NWzygKLzQK7qmLvqnwXW/ns5vJWzsluXsAl9YBaDkZyNRrJleAnpPcUBkF+ewOM6yqn8hWSRv/glhFvCHYQBOJPu6vSxxTTv37Utoz29ddbm7c6PJ9SWj/h/LTa43A0FyHRpj9LLYnYko1vMdZ9wnG8efa3vrZ5w5r7HvWAJUP1ka1bxtNRk+R8pP+SB5KcJ+mLRZqJVZn0PEmQTskkNt4+1t/vEHnTSX/+Vbvthdzr13tJude9b/IlI2daJFlcF9BDESUSqjkff/bZZ/u63OMe9zivxvfyLpfXjbtHqSVDJXczfQpaeHEpW0lbWWAxWsBEQHwMwVdHfFxiMapQyVxZoLJAZYEFa4HKOVmwRTOfgnEa/MGy1hRAWJuwAvgHlIX/E6QtnAHhyT8k/hpbRuvXX7v2hjXrN6VvD/iavDpTH09bwhJXnsjQQHOovvXKa2/yYi+uSTrI4knyIVwWNdJqjQt+LjwPizAR33fhr3910J32e+ADjkEzZs2Ex0G0dKV3ghXuiFfopn1dhbTJILwdazgJjadv1ScJXdySa6659oILzndCY+Omjb4b4OXDXrAONNze0UocFv5l9SN8quRy9ff7UpLPOV1yySWf+9zn7OyCiqgs3vehfAXFZ3R9FMkZlWSIyjNZ+KVbSbhbWMAX6J75zGdqhr53PuXX6HYLLSslKgtUFqgssGssUDknu8buOz9XyBXwt+nJ17fWb9i8bt1Gbkhag0hX+tKTLwhv2bzVF28BflFpxSI5IY1NW/t+dcmNN68H+Qdq9cG+9BWTRrEUgkTC1pLB9tLGxpvXbUng2CpJ4YVwG9LJklpzZKxv08YtW7duSV9lTGwxtxbTdKbimquvf8RDT7jnkUemD5k4j5JcmKZdYLeuW7dhw8bEgGPC9yAmZySJi7VNXIUmaAswfsMN1/vW6erVq3/5y1/a+7Rq1Sqcwfpmc+LDvUmPRXUVjlzSNaT2inHfZmYgrxvmmfC4eF8+H0tlH200ceszwMPDww7Qs0dhkkWlbSVsZYFFaAFfWeacmEfw4Wcfb16EGlQiVxaoLFBZYOFaoHJOFm7ZzKNkMGsB6ev99cYNa9ZddNn1V1x9Y1rHSFfyMXxiePiuB9gPteeKFcWuqvTMA36Br71fdf2GwSV7NYeWt2v9hRfh7cHFukVaORl31qReH683HHFPqx1pkUZKe8dq/aPtgevWbrr66pvW3HRDHIYv/KGa93QZ0dfcvGXlygO8impsrFWslTS3tOo3rdt8ySXXXHXVtZwcKz1pmaRvvFEAda6JJQUOS2Ogf7BZa7e23nrz9eee86PfXnH54ODQPY444mlPf/oJJ5yw9957FyDdKktaWEkaTgJ94YV/0TGfJxGO9RNi80yS+sV10003nX/++RdccMGPfvSj73//+0cdddRTn/pUjpmXDofKC1/NSsLKAovXAr4N/6AHPcg8AhXivnh1qSSvLFBZoLLAQrNA5ZwstBLZMfIkXJ/OfrTqjdWXX7/6mo21JYfUnVO3/JBeuzVWb4w3B/fs71/eqDWdCSk2bZEkbcFKB1UaK9p132zn4BQrH+mxHVbFgoaz6rC/0yvOo9f73ZM3kDZ1Ncbb/bdurv/8N2uvXTNaa+zdHEiuiyPxztWPtuqttfWR1nIuDbfEJiyHR3xq/oYb11+4+qarrx1rDB5iDSc5J+lKrklwTnm1x4aWDC4dGLvq0p9/4P0fuHntzU897bTHPPpkSwf9A5KkVRYLLOEkZbckBwqGM9+2lX5mjttCwQkJcrjHmolPMfrJ6/AznJP99tvvpJNOOvHEEy2knHnmme94xzs++clPfvrTn471E8JXLsq22LuirSywbRbQEl3blqairixQWaCyQGWB2Vmgck5mZ6dFTgWq8jCcgx8d8Z/vLC5tDqwsdksB8T7avrVV47v0J0zLHeGAgLdeCVXz7qvaYH/beffW6JaWB41m2rVlScNqRGETZ05ajn80Wn2+j2IBZCLS6gsPpH3NDRtu3dxo1Vd4jdZYvW1phddgt5ZUa27ZvGXE6F53hsTXIdPZ/Hptw9axm9c5VLG83txzrOZ8S4LihXNSuDxpLaVvYKBda7bO/8k53//Wl0jylje9+eij7wWsDwwOytzCDsmTcCFfCLQb3cNrSnaxSa/ZNIProLy9JR/60Ife+MY3nn766Q95yEMcTan8k92ozCtVKgtUFqgsUFmgssAdyAKVc3IHKmyOCAfA/5CrqXmehCMd6dZXHys+Fu8o+zh4P2kSLoSPnOy5tHHMUfutvnrthpER/kmrbqmk2Cw1uZrhLVnNhrdncU/GJlwCbgyGVmSKDVvpu/Jpx1e6py1WwnWblDYJJR72e/m8Y1rvsIjSrPUvGbem0jeQvsXCOUmp0KT/7eTyucdlS2s//dkPz/3xD/qbfS99yYsf+pCH7LnnMs5NnBTH3oWeEuD7pCpz+Pe2tInhzrsK0afIjjwTcpAnq0ZxG+R8Rd7RlI9+9KOf+cxnrLqcfPLJGJTJpuBXRVUWqCxQWaCyQGWBygKVBRaeBSrnZOGVyY6QqFgMsWrh9TIrV+6114Yta0c2Qe8J5KbPvo8WH3/nIMSiAwkKvyCh/LGlAwP3uvvKZnPslk2cj3QUfmJ9JKVPzs1As7G0Ud9zxdCYhYuEn8FrjG0aG/ftxcHBDes3j7ZG056kcdvIuDaYcETaIzVLOIXbkTjJu9VeumzJ/vstW7/x5tHR5Lok10SKwoPCLZ2j72+uueG6H//wW32j6x538iNOe/Kpvp3Sao21eEFjY8VGi9s5FRnEz9GoyWMqrBH/zpHLNiab0hVK/l7yN4qiiUBi63C8V3Xts3LlIx/5SG/1+sxnP+u7KNwVLxGKgyvbmHdFXlmgskBlgcoClQUqC1QW2JUWqJyTXWn9nZw32A6wHrrqoPHGhl+vvtEiSZpc73PGenxooL5kYLzBayhwL7/A6sZ421rImIWWwf4lRx6632hfrWWVpdGXvqI4eYlI/km779fn2yeWtmelJ2m9o93faN/pwKX7X3vLlo2bxlrjdcfa7cuyVYyX4YuMtS21tu8DOAqfXBbLLpyTffYc6Dt4j1vW3Lxu/YbRMfvKJvwfuXJOBgeWNNuNb37lC1de8n/PecYT/ujppw0ODaxff2vaaAa137ZOUvZPStGTMse/ocQEaXKABPMvJBOuQArsxIsPMvU14Salh4WHkkqKwApwa3p1cmvJ0NCpp546Mjrq8Mnf/u3f/tf/Z+88wOw4q7t/p922d3e1WmnVZUmWC9jGBeOGMWC6MdhgqiEJhHyEloTwkRACT0iDQApxIKE5H70+GDDYxmBiIAZcwIC7wUVWl1bby91bZ+b7nfe9d3a1K613Je1qV5zxau7MO28573+un+f872mf+xy1UA48lbYqAoqAIqAIKAKKgCKwUBFQcrJQ38wRlks0b4wepUqVePQTjyscv6Fg1V3rRYT7ViHjdrTlyLFlC4j4rkcUCVo/im8tKkZUOCHGQR5CT5qKvajHqUyGfF2pNMSGgBU8uCQYXQ7C752oesbJXadsXiH1FanLSHfHkah1N+zuKbW3IVXNsAA4TV1cw8LU8nz24nOPFy8vSSNs6IKttkiSLtfZs2fv3/7i5mc/49zznnx6LhNIJRNjqEEqiWTZ/xAl3qry+7fbOyM7XSwAkrQ46WW3J8PH22SmpMM8XOAAl6wohA9JRFJJSSD48gfaYlxyMXfVaCgW4X3PuvhiEit/8YtftBXlyao8D6LqEoqAIqAIKAKKgCKgCBwpBJScHCkkF/48otpCNohU970wwFwimrfVgHHBcgI/SwQ6LXhtoQYbhyjueSSasJuqQTukVSogWjVdenMEsS+avTRKO63Sias4clPVPNm/YBUUCaQZUoJFJcBZyysX8THDbGJH0ZMl6qnQ2GaEHgkvQVYeY1bxTbn0PXv3/uRH/9O3d/uF5775pBM3C2uqSWFIWbMhC2NMQ0MKe32AM71ETvNnHmMmakzR7G12KtMxuZ10UodmxyP9aZYRNBO+1FhYPiQOxyMuyHYSlGxkjsQM4d/WuWzZ5s2bKR7/2c9+9m1ve9umTZuOtHQ6nyKgCCgCioAioAgoAnOIgJKTOQR3IU6NUgtDEe8rUbjlV3jzg7zNvyWuQsJERDOmi/RAMSfTF4o6mrKp2o4+LI/lkA9Ueuwp4gRGhyZHaCjT8A3qxUd1o0Fj2ECNRtMnrj0gR7Dv1iA8ZkE7jTySHMCSC6zho2XkkdVoYkBf997bf/bTc8467aQTT2hva61WKdgoMkiOY/lPTtxyGAFZzXzapgnnpNXIaUkJjIveIqDdREJV6Gwo0oTxc3kJD2pKlYiJqaqxE0FSngMMO8UPDqTINQxmYuViDxk/AzkhYRdpha+88kolJ3P5rnRuRUARUAQUAUVAETjyCCg5OfKYLtQZRelFA+cDvmGFRBO2nMKo9cIJ+EmeHujFddHWTaYsuInv1UOC2qEZsUtyrgZvkTkwptQi+IZD+XLUeBiCaNcy1po9WAxN2ij8JiRFNG66i8ZfJSYerzHurVRGJnMS+Vga1VsUbllGzvHQ4MDWRx++8tWvWrVqBQSK9Fw0Sy0UlyKN2HWMtNJbDrzKrHnB3h7wLFSGie2a4iZFg3Ac0xkRmjDRyfQ54CRHsJFF7Npmw/Y9NKZvSgAPQT52ZkBm91L5RPCDn8heXOe444571rOeReWT0dFRICLd8BGUUKdSBBQBRUARUAQUAUVgThFQxWVO4V1ok1t13fFgGGKeIH2WHASccA+xEAaA2ouCjJqM9isNfuT4dcfb2ze6r6+vXB7LpimHIqPQiY35xSUDWDZw9u4bkMHjBxqzaPomtZfo2cYkwUj6iEUlgAdBB0ShlsMSAfpL6LvYQETjNkXlpYPvB0TSjxXHBvp7zzvv3I6OJda1DGYSZAqVulMq18vlWli3Xl4yKcNldxMlknX2O5AKRZ8meA2LSu+Y/yNk/yKByDTt+P0mOyI3ApSBX3ZwwLV5beaRsEiELrR6mZwfSG1LOGOd91gI0mvWrEH2gYGBsbGxtra2IyKZTqIIKAKKgCKgCCgCisA8IKDkZB5APvpLGE0dMkARd9T5NOURh4bLlTpRGzTikeWSxWtFV6shA5JQmB/hyeWFZg6LGa2Ed9yxa7hYrpOly81S4J3MWoZUoCbTR0o05rxyT88YJgzhBOaZKPqi3Tv5XI4GFGeWwceL1XyqolBBRZzEOCw4zQ+hTTiRuTUWYyKivVHWxWMM001EWioaV69e7XlBvUaSMcT2R8vOXQ/s3blvWFYUVsFZLoRzmAv5nHAwl2j90kU+fdchYsbLen42wCBE4qtU5JXLFaAx5poJI+fl0iFjclNufOKmrClY0BhJPmcA8qJ6uHx5fsOGjq5lGT9Vd8N6Jk365gyphHt6egiOJ2eXOPFBuUx1+SkTaoMioAgoAoqAIqAIKAILCAElJwvoZcydKKKyyx8x6Onu3qHd3QODwyUchIQsoOsSr54OyuWOYrGUSbfRJHYLVGRMG2SBKqe2dZcdN42RQjT5EP3ZRo8LRREfL9f1xYaS9imhKENMYl9x8aJyfLCzu7+vr788NsbyPOKnfSwtpCkeHhoaGRkTBRuxrJHA8aj9PjRaemTLtlolxH0J0w3khDlz2QyrPrZ1F7Km01SC5wHtsBt/557B7oH6UBl6Qaax5j7pIEq86PHjh6wl/2Q07ChwMyJvXKqM7d6x68GHfoOgkYT9Q40oSml3MT56fq4a9E4WAxQjbeNMi3lVsUSgGKOWbLIWhq35uHNp1JovBW4URPXAcyuVyp49e6699tq77rpryZKGlYmtcthddHR0nH/++aeeemp7e7tt0bMioAgoAoqAIqAIKAILAQElJwvhLcyDDCjyYqhA497b3f/o1r6xKsYSH4sEtAKFOJOOCtlSpSJ+X8StS8Jgc9Qpo0Ei4Uoq35IN/JwUKTHBJEJGhMCg5UdBwK/5VSLWsWTIIBR/YQYYKLyxirdlZ3H3nuFqpSKKcUgpFS8tLCY1Oloqln0ScRkWYZyV3GBorLZ91/BvH+snpxc/9ZO6S+K8U6mWbBRVR7bt6pGZ4RMsgarOAyc1MDharqVcP+/hb9bQvkWrFyomf+OHDDGjGBg5YSbjl4uD/Xt37tz2yO6e3fv27elsb1u9cmVAfZZmmcn9xo/PNFdXhhI2hWaTskskNmcuGhYfLCsTD7ZadZwRJ1XxeZWeUBcsJ5dddpk1lVClcWJv6scTi/KrX/0K9vLggw+uW7fu7LPPhqJoaMpElPRaEVAEFAFFQBFQBI4WAkpOjhby87ouSraHIcLlN/Va/1B5qOh5+eX4V1GUUTT9iBKJkJI8hgh0epRhORuWgWaMIxHOYOLrhU0hRrkNYRImUN38tO9QwsSpp4iKx9YgmxICIMyEib3u/srOfne4tjSbC0TRx4uMQo9pTBz1MMjG7jLqN9KMyxd0A4+u7v7iQzuGSs6SfK49dNwQyTBxMC6bHivVRkvMakJimgQIpoQXGLKJJxrhMRAnESHR4+3N+FkompAyjC5Rsdj/6EP3P3TPz3dvfbCrq/0Z5zzxmRc97UmnngZpianKYmiMZQfj4+f4ykAnMSePdzRtKma34jNHlRi/DgiUoKHNBuRMnQTuBlfB3euaa665++67b7nlllwu9453vOOss87q6urKZrNTh2iLIqAIKAKKgCKgCCgC84mAkpP5RPtoriU5fesUXYeIYBhI+z7aP5ElosoSDOL7BJnAH9D0xZWLwzhvEYmOv5Db1ZHpHx4ZqxYJGLF7kHGiueMWFjoxAdlj5VqFfF4wnUZsgxRdjPf1jozVsnWvEEIICObwJAqenF8kA6tT1cRpMSUf7ZTiBwbFKTOHk6ulWqAd+I3BiCgdnwoKfrbopxslBcWoYDMi12urVizb0b13YGggjHJQHztXYwdClCYeMQEzOLDBT9Kp+nXXfeOBe35x3ilr/+3973zCSZtaWjLZbNr3/FolVXHw7hq3WEycYk6vEZd3YoRmB2YT+6/X3BemKuGaYvUCtHolrFXwgZPMa9ybIQ0b0v7DeTXEx+PT9fa3v50SMZATknq95S1v+bM/+7PLL7/8pJNO2r+73ikCioAioAgoAoqAIjDfCCg5mW/Ej9J6ouxCENJBkG/N+0G1OFb2g0A8utD0MXoQC15ziZCnH8YJE++A7YO46zCfDi46Z8XAUDg0Wq+QvFdCQSYUcHSiXJp48vJj93U8YLJ/iY6MYo9Nw/XaWtvj1FClVncpOO85VVNjkVWxxBCUT5kO7DUAQmfhRHHc0dqyaln7I9v6Qifn+GnWklbYSS2kqgnxFSnHfmPhDqKF+57btTQ4+7SVu3qLvYPwmkBmkz/xhRI7C6LYs6wU5/O5wPd27d7x0Y99NOOW3vp7lzz/medtXLsil0uzSFSrEnMPFUJ6Rlotf37fl7wMJH+8gxeEWUn2acxVYYCDHrQSi1YE5RTwD0hODJYWGIfi8YSdrFy5csuWLdddd91DDz10ySWXXHHFFY+3tD5XBBQBRUARUAQUAUVgDhFQcjKH4C6cqY2+a5XeaO3qzloq3jsAFSGuHQ1clNq0H7cvyaUzhG2YbkJQONBmQ9+pd7a5hWx6+VJSQ4naG0rSYZOoV1T/FHmEg1Sms7PAGPktH71Y+AmX0fLOzKpluWhfsVYdxRtMrCdMKbmL0aArpgijJJLCXgM9goG0FdKb1nfUanHvMDHp4qpFtmFCWjxoiFMXBy7LGBrWBYbFgZfqWprJ5byu5VmC6JlNMoihvSM9oogCL/8kXbKTwmzywINbbrvlpsF9W9/2+pdc8twLjt+41oWSsX5YE6MSnYWWyDz22jTM52mGy1ogkFLeoezTHrwYu+MDcRzBXv5J5A9mNBJ5ERNPoUZc9b73ve/ddNNNp512Grcaf9JEUz8VAUVAEVAEFAFFYL4RUHIy34gfnfWMk5UopvV42dI20ua29dWr9SqKsNFrY7L7rlzRks/K96Gh3RrtXEobpiqkt80FqXzaJTEXhAHakWjQKMaZNFm60gV6wApEWzaUR6YJ2wvB5jX5QjYcLUIcIBIeTylZAtUYzmYyQTkVS2FHoRLYR2o1iqhAZjxnxe59Q1XoCr3jmNTD+WwwlM52tJKnC7sGvYXScDYMqe677pKC09aKW1dDSUdohBCKRDfDOLDbEOqyZ0/3w/ff9uA9t//+Fc9+2WXPXbtqeRzVq1WC9aWUvVlNxhlYEn1fJll4R/IGZiGaeW2yQTbLgQELHtLZ2Xnpiy4lFuWnP/3pd77zHfy71q5dq/Ens4BVuyoCioAioAgoAorAkUNAycmRw3IBz4QWzyFaKaHvXthRCNrbiHIPRLk3v7ujiefTThBIKRNjNhDGYGgAhMOQkbASpUj1a5+akBN5zh8qbhrVn9olRKCYNolPh1ngRuWG4YYub33XkthZYiLXcRNL4YMEx+nZ19LeUoP52HUM46jg7JUJsutWZNav6kI0kQ7xXGJFnH176g/d3Y6txMAsFgCWpoxkFNfE7IJxRaL5jZMYg7jCUYyxiB8TJp4KMkHaDW//ya2/vv22M05Y8d6/eFsmnapQ0KRSwW+MAfZI3iFEhZbk9li5EEqDux27kzfEywDkKCoUWi+99FLMKR/60Idspq/169cfK1vWfSgCioAioAgoAorAYkJAyclieluHLKvESUtReLRt+AJlPLAmoM1LODW6O6oqKbm8oOCRzMp4Zdmf5TmLes6H3GOykELqKLYm5tp2ERYA16Cwuhgo0OfFTMGcovNiKnGiEpMzWFR/E+DCFw4vMCotZr2q59bt1Pbsk4tYlig5US0iuEVazeCUm2nJxWE5rBdFjMaBoQOqxc//dmoSbEltSHOI3YSLuB7yFOEkf7GbGugbvO2WH65amvvTP3lzPuuWyqW6qSjPeIEGAc1q9tyY6Vj8sDSVLdvNSZqEUqmtvf2JT3ziKaec8ulPf/pJT3qSkpNj8c3rnhQBRUARUAQUgUWAgJKTRfCSDl/EhpZPfLkUC3eowW70eLGDRGJtIIpETCKJXi6qvZgdOCAcHs4/fuDzlN/bIRBo/sI/zGPzQ7woutRZJ9+wDOCPjhLxwQVcwhogaJJxGFWoxCgVUehschbLIjKXNcogIO1QE0kubGaSSHZ6M7mZVRbgP1PAnugS/uA6Em4vEfJCm+w8IohdUiRlv/Xa9d/+Zn/P3gsuuGDN6lWl0hgB9mxHpjNd6W0vONvDtjTvFsEn25xeyqkdBG5gIlFBOn3CCSe84Q1veOtb3/rwww9DVJYvXz79bPpUEVAEFAFFQBFQBBSBI46AkpMjDulCnFDUfGEDnDEToMdTOJGDFqErVEIkCAQ9nSujrKKvGmogxAKXqEwt9Hr6B0qlUhjWUYBlImEo5kDh9XzCOXp7+5kDA4RYTOxjY0ExthhIA/2EOUgBdjFTwCMCyqpIC//kz3AezpAR2gljMYUZkYQZxJ2MMiiSyFg6CEsxpII23wuqNWd0aGy0NCpJkoWgIKJ0lPB7kQXm4obl8o3fvWHz8ZvPecqTCYsvFovC08RmAlOTjcimhGnJedEeZidm8zPegsDJHy5ehULhjDPO2LBhAyVQSCus5GTGGGpHRUARUAQUAUVAEThiCCg5OWJQLtiJjNZtAkeiCBND5AS10KlUcKnCLQo2guCOHzhEo1TrMQYS+2u6MBVhFEGl7nd3l7bu6BkZGW5EKRh1VqwW9Eg56Uwm60W79/QKLRAzjPAWw0WEV5gmYSxO7JlcX74beSxao7yisJLmYS4hC9AWUnCViHAxszAFI8lxPFaJaohshkA+JDEYtMjzq1F6b29x556B3v4eK54sbiQ0H7Eb+Gk/VR3tv+ee+19y+UvwWYLbCDMRHgPhgZzI2sLHzEjOi/ewFGt6+Zu00gDMxgWMEOcucICfXHzxxbfeeusDDzzwtKc9bfp59KkioAgoAoqAIqAIKAJHHAElJ0cc0gU4ofw0bv+8wK+F7u6+sUe39ReLFQwhkAccsNKBd8qmjmIpbs1hRJFUv4YGUPrdGyzWfnjHNj+ddr0u1HnsHrhsQWwopMhZHMO8jJsqRnGaR2aYOHRReIPAEkqr1MOoVK6VSyTfYjbsH8ZDLIr7+gZLlZoQAuEFTAnZgClQ5d0dGKw8tmOAqiViP4HLhPW29vzAvoF9vcOkHbZLcBZLip/eurN0z295WPW8Dj9NxjCjezMvOxPzT+hHXrFU7N6+JYz8pUs7c7k8QfAiKnnDqD3pePA0MSuJKMJYFvUBtXsc+YXVNQ6YKlVfvCBVq0lWAFopGP+KV7zizjvv3Ldvn9isDG1rdtdPRUARUAQUAUVAEVAE5hwBJSdzDvFRXwCmgfWBNL7GM8p99KEdv90+PFLOOE6aMoZiLRBLhDtaJC5DbB2Ej3Pmj1D5MCSBllOO8nmvxaFcPEVOhOWgyVLfPeQOElIJcbcq101UiN2s+FJxkDjYyTzw0CMYVco1vLkCKIj4WAUB7Kc4MjpSFLYiPmDGWQu6MVpJ7esdvOeB7aVaNnbTseuLdcWJCmPxyEBxaKTatG3AQIR58Jv/3u7+Yg121QFTga8I1eGBCClP8UojS1e1GHb3DXd2Ls9mcjRSHB1yEgQBNe137e175NFdUn1SCIqI38hEZneyuM52A0ZmS7YOLj5b5X36nR3tTz7zJAxQUmUmDMFk3bp12E8eb/jBJ9YnioAioAgoAoqAIqAIHAYCSk4OA7yFPRR2gK6Ju45RWUWZJwqjXq0NDI4ODldSQRsZs+jS0OYxdohRwiVenXqERrfnh3OMGZJkC6NGKE89+XWdRhy6aGWE/LIuleDpZFJeiVkDfiADIS5Rau/A6Laeen8xI+EiBIh4EB4mgvqkSnVqxLcQ7sKcmEgktVfg9w+Ut+wYGxiDUuSoDEkSMGMKCEv1oFoPwkgkhMqIEOafcBHxIxMJJW+XzMN88lS4BvyKJ54XpqK+wYH2jo40+YN5ZBFxnZ17eh95rH+wmCbMnz8GGnpCF7G/cL+4Dnk7zWN8J80WYYaN7QGABNzElXi0Hnbs6N+wMu+TKM0kF6bCCeyUQbzB5lD9VAQUAUVAEVAEFAFFYJ4QUHIyT0DP/zIwk/b29sHBQQwFosKjnBJHAj+hEnro+dlsCtOEhKSjxovdAHUUiwn6K0qq9JcGoRmZwO1a1lqskIAYwwU1QSAtzAOBwY5CvzgIUO6lZKIkfqJB7DAvrfzoAABAAElEQVT80SnVO1gZKqfLTjabyaI6C33guXh/RVJ80S1EDuQEE4zQHsf1i+WwbySspfK+VyC3sRh2TBQLEfuxh8Bi52EGWdVc8LlsWevuwdHR8liq6oW2s4gucspHLIVT6rVicXQok6Uey7jajfGkf2B0b2/Zb1mdwnQA9TL7kdFmGSFni/aQze9/8Goa71VeEq9PvglDlfL23YOrlmWDLAnNJPxEOcn+sOmdIqAIKAKKgCKgCMwrAkpO5hXu+VyM+IFVq1bt2bOHLFto2fxhFSHKIptOU1EELVSohMnRRWVDsuqSTlbEk4ATq5Qb96gozqb9J27u3LZzd7FUsU2i80uIgjhAkeQ3m45zXiodxMZKI8RB/vFH1IkfUFwe7lF3MgxAAFlDzChkCx6L8SsTOiGrykdEfcYgnU3XRlCT4Q6EqhMZgohOpsFSrGBmgCwDG4rWrVrSM1Sp1UphVDXWDru4jLMbpHJ93S97qXIcEcXCUzkQEV8mDEf1OB3HKOY+xAY2ZQJWpINZaXw5aVoEx7QCy+bt9qFdXDh1jFtxqhKWje+cYaKLYI8qoiKgCCgCioAioAgcywgoOTlm3y6RAxs3bty6dWu5XIIWiHMWOX8Dv2v5sr0jxe19JfgJhRUxYJACOEpH1WpcoSghhMCzBgrYS0iiLKwYJ6331y1bQT1xTB/2l3UbmMFgLBFBIEVO9my98/af1euE2Hu4SJmi677ftXJJZlulf7gqej9sg/HCa6AtuGfBUAjGF1riyA/5Ee5ZKzpbS+Vox87eepQLxRAiho4wJH69hSj2Ghm+jLOV0cHlZ/6wUs9k/TNPWn7icZ3VWuS5eG2ZcBSZjnWwA6QIl9m927nvtpbHeqrizSS+W3AeSVOWbym0FFLDldAPMJtAWGBrCbdBqml1/YX4xZlOYLsxYSeyUfkPMpn23XWr1wRSxAazmB6KgCKgCCgCioAioAgcZQSUnBzlFzB3yy9btuycc875/ve/PzIyIuEenkfYd7VeXb6scEa+dVNFkvmSpgr1ncCOwE2t6XCXtGfF2iDxCFYuVNkaBgVS7rakbRNnoSdiHBHTiVCLLI5fYjkR3mLoBMq/lEzEFtOS9U47ubNjz1j/ED/PywiG+0SUuHHWTQVeDeoh7IjOPIrCbOCuX1V45lNP6i+S5oty8RzCJtoK7mBPx45lbWjWMg3yNWwccVQtBY7bSsKwDNHzDWZi+pi9UaUlkxpJu61ZeA5jjTsYc8Yx3m5rVnfUncJvtlH1ZFja7HDjD2aoCW2L60B0wWt/oc2uTSt0y3RodFrSll+9smPNat8liXREjZr9x+mdIqAIKAKKgCKgCCgC846AkpN5h3y+FlyyZMkpp5wyOjra09MzNlZKp9NRpUJaXnJldbYFS1KeZAI2qj5h4/CTjtZUNoBTSF5dZBQjCfYR6VEnRh42YAQX3VeUWO5Ix2XOqLzGoGI68Az9l0ucqnCncv3VHUEhnS9VAqMzS9w7nXk8Npoq5MpOqiYzMkboTg1Jcmlv/crCskqD/7AUZhYCZPal0ktbiUJBamkT6wfGD1mLsaEvkTDiyNWUU0w1RkocwuBNMe5nso5ZSoYQ6BKG+Ux67Yogm/HKVXIDQE2s6m4e01NczRbVITEl7HG/w9yzXwOHeXWmkzSng3RrIZ1Lk2+ZoCONNtkPN71RBBQBRUARUAQUgaOCgJKTowL7fCxK2qWVK1d2dXXde+99J5148hNPeYJTw70qcuNaGiUVDV1KXojaik5OoElWYjDwmxLGIeq50eVF1xX3KPG+smqvqL8Nq4Xtw1QyyjIBM0oojSi70JeonveilnauAslnbDqRqZjPgf5aLo2/mSEnZmqcu2ShlEtJx2xBfsfnTzINkyg469ZyqTxqtDiAWe1aNiAJuUR8lmMgTmg8NaLLWQpMGtNLIM9JQSZmHjOamdmEGIjqrVm/sDpDVItk9mqyEew7i+6wsjclN4A2oBjfioWGuja2iWqZ5Io2zCQUU1fjDY/31ytFQBFQBBQBRUARUATmGQElJ/MM+Pwth16eyWTOP//8W265Ze3atZATjCeVWsUVewPRFxIdTmC0oRomT1eqgEorir7o9UZllXxVeGqh2Ud4hRlyIR2sTYFu/LEKges85GBvVik2m5TnXkykPUxFLBw0wgYgEX4mTUH6VH0kFWE5aarTMoa5xTBCoAvVHWVpEUB6eOksjU5MyDvTyj/5gO5ATSQFGCLRBFMx63OScRL4IlVbbKP0l0FCV5iaa5kFEGoswI2QnuZhI2qad4vjM6EWBgu2bzabZOgymxAiJ/E9lqXxviycbN2kazPgLY7dqpSKgCKgCCgCioAicIwioOTkGH2xZlttbW3vfOc7//Iv/vKRhx7au3v3uvXrUcvLlUoYUkKRComioBstn94YDpJrYRJiihDN3w184R5ouaK7whcgL+YRdzLEMIjGWBlh7BiczEMmMPqvPJA/eYqGbNiBuHfJtZE0mcxQB7mz/UWBliv6NnpCVXgmf8wHJyJjMlXOkQnbiI23l6FyIGlMOXpShrGLDOU7mkvZqRu5hm1fOY+LIlgs2kOwNzTQYJhYgxr7aTyVO3CyW8bA1HiqH4qAIqAIKAKKgCKgCBxdBJScHF3853Z1SoBjM7n8sstu+9lP//tTn3rD//k/K1asSJNdS+wiQhfs0fDyad4aEiFPIRLUHqnWU3t3E7eyr1Qpo9pCEiTllRktlhA3xiBDErBHH9vOEAiAzCyTN/iJh5WEqBES9cJTTCvR+fxQ76VbYy8HKTLL2s4yq4TUS2lIfMxQnY2MnrGjuJCkjFnXNIqdxPU9YvGDrTv39fT0V6vkHzNOX2YVYySgu5fN5hF+264eCrXInozLmijmMjn8CC8nqp8wmRAgi4Hd36JjKEAZ1SmhKZYQYyCBScqG2ZTZtN1cchaCZ/doGEvSrheKgCKgCCgCioAioAgcNQSUnBw16OdhYbRtiMOFFz1t166d/3PTTblc/vWvf33H8mVpx0VTr0MjiLywckiIiNXWzZlGlPeYTF3eaKV+3yODwyMVBtBorBN2DCMka7CfruX8ysAgPlpUJsE4wlSNsAasFrWaM1Isj5aoBElFRanM6JuMwsNDIyUhO0JOjAJNWAu+Y36lFu/rHy1W6NmQyPXgP35v92jvwNgEMmMEjN19vaUtO4p7esqmsL3sxhRvka2ZmWstLf7wQDQ8JsYiQz8MP5G5WdCvR87YWL1UqpmyKiQUZhjPOMRYZC4WzYnczORIJr6/JZdOxdXIvF8cuSw/MbsSNmK3Z3fF9aSWRbNbFVQRUAQUAUVAEVAEjkUElJws7rdaLpf37t07PDxM0Q9+++dcrVaf8IQntLa2Jhs77rjjzn/qUx9+5JEvfunLGzdvPuecc5d3Lcd+4jjkjyVfr9HjjReX73t4fFWoiyKqu0R88HC0knp0b5TJdgYZ/KOIWJBAENPd+FoRC+JS4r1ISmEJaTCqPR0k0EOyeQXdfYO79g71DNaqKYrEU/YvRchJNp0aGeovjqIai0eWiMoQzw8jt3+49OCj+waKQZXQfRiCeHRFhXy2ODDY3TtqyYwlHgxCjG27h3cPeiNhhzhwER4jqjf6ONYdqAUXcdVvqQeQrIKpumge0w75cN16PRoYqe7ZNzw0XMJcE7skI4ZuiejmT+RaRAcRPlSc7GzPrFheaG/xyMzWNI2Mb0L2v/9hWuQ09dH+HfVOEVAEFAFFQBFQBBSBOUdAycmcQzynC3R3d3/uc5+7+eab4SQYSThv3779hhtuOPPMM+26xlaQuuCCC6jJuLe7+6/f8543vOENl19++aZNm1ryefpjQYHSoJDzVyi07N69Z+fOnTIWPZ/sXY5TC51ylHecFtR3+lCZ0YStk5tXyrfzQcF5SdhFUUUOiqIYBynxlfKCobHwgYd37+4tx35b5FPOhMNNh6lyLVWu+mFMzURJDibx8pAQN90/hBmkf2fvWOQvp6NMD4kgcD6VqaQydWwv8sdhlGncxXxvdKxeCTORl4kCj8LyTGaMH2ZWTk6YpkS9m48bLmFmtLEW+IG/q7v/N4927+ouukE25aSJnydvmWT4ahhtbOdFc/ZSFadWzgX1dataLjzniUTi1CGLxnVLiceieYsqqCKgCCgCioAi8LuNgFX1frcxWMy7R9nHeDI2NgbBIMIEstHX1wffmLgnlG0enXTSSf/yL/9y6623wmTI30UWr3e84x35fB5KYzvTbdOm43t6erdt2yYt6LMxIea+G6Sq9TAIQy8mNkPMChwYScS2Irei/lr3LPy1oBiS20tYgYPb2LbdA/1jXtVtc/3WMEWSLok7cXwKqNSrkUcLthTct6AEQiNcr3+0tqOvWomzvpdxPFJ6iR1D3LRIc8yfy9c1CZBhlKQDLhTy3kAtrNUloTGGFiMeJ7G6CAmZ0L/5EJnlL457egf29JTc7Eo/lwtFDuaUIH2GG36SjG1OurA/KRqTcivFyuCenuFRKtv4VK+RVGtAKFxThE/gWdg7UekUAUVAEVAEFAFF4HcVASUni/vNw0lKpZLEj4Sh5ScH3A88oqWlZfPmzZzXrVv3k5/85I477njf+95HrmGOpUuX0tjR0TE4NEix9H379tlJ0GsxRLTkg6ecuXLvvtGR4khYoSwJOj/tKPHCKCQXcCYduqNRvWLi0Y11xOjCdKrWnWqcCZ00sewwEMI+JOxcbCukH6baClHvxjfM+IOhPkeYStyAyvUSQY87l8gxSbEWRdso2eJCFsX1tata+0vF0p4RTia3sPQ39ALhCDKJQj9fr4zUS2NJfI0ZLhaeWi2u1L10vi2MfQmWb6juJgzGaPSy1CI5kJ1SkzHJBpyxSq1YqdVwwmtsyEK22Ha0SIBXMRUBRUARUAQUAUXgSCKg5ORIojn/c+Gsde655y5fvvwXv/gFLl6i9pt6I1MlgZ9gJIGEUJlx2bJlZBnu7e2t1Wo7duwgZKW9vR2Ksn37th07dyxf3sVwSR8cQXjq2cA/ZfOSpS3O0Kgb1uv4csFYzPxSdR2ukM74Wdd7pLNFijU2D7lyU+1LC8Geeo3C9BhfDNcQfTnyIs/BuoPFxU5kGEhEQcAlhezq5a2DI73VWpnFoC64i1G0Pu2latUqBEyYh/2jWZZLtbfmNq7O5bLhWAlrB5TJPodpGBJEKEzW3+f7bS3u4FDDx0nIicTGOPlcaz5LCL5XofzjeMkVEcpYThq6/VQwF2aL7D2MvZSXy+bEIMYubUCRiCtb5qSHIqAIKAKKgCKgCCgCCxkBJScL+e08jmyo552dnS95yUvQ2j/84Q9ff/31jzMAJycqfmQyp59++sknn4ylBXLy85//HC8vIlXIFkxLtVKFtAwNDdENTT+F4SFV68gGHRsLKao0Gu1WIuKbB1eYOAhGefieLjRhYQbiGwXxkF6rVhS6eqqVqFQWViNlHFmCH/fTRN5jI7GV5MViwTisILXO1ky8tq1vYHCwUmcySSuMu1e9lg/8VBBRcUUYRGNx8VOCDpEzd21XevXKzqZEzMUTDnE74xJ3sO2FsV91tRb3cssjEVmsLmFqWWfH2mJhZ58IQvJd8iAjtuE+i1KPR3y86gotmZXLc4V8rg7wJDwAJYOGwcQiYy71pAgoAoqAIqAIKAKKwMJDQMnJwnsnM5YI7Zuocw5GoPTj3wWjmMloQlDsKDo/85nPJFweesM1tohPfvKT3/jGN3/0ox9dfPHF0ies4RgV1So8FNXdzG7ICUovf3J4mayUam+YU4QZoOKLVQO7iJM649SlJ5zglCpmLL/s151cOs4ETt++uL2NeiaiOYtFI6YOCnm/3BUd2WdfePJYLCErTCVeX3HMtnp3p3u3rP55ar9wGsY6cZmqHlhYmKiZ/FfENDExUlAlcNOBlGOpynORuSE5kTErl7fm2/01w6l9/RJ7n7hBMXyRHvlc3NGa6szBSspYoqwPnNmyvD9zIeDooQgoAoqAIqAIKAKKwMJEQMnJwnwvhy6V+e3/8Ycbs4J0kwrrJo+WuESlUpdc8kI4wX/910fPOuvMNWvWEBtSqVRx8OKR5SJGt+WEui/DmcePI1JuGeuHNBGELZElkssX5biediBCqdacLChsI0qZkvNxPVv1XRIQm1gPUv9ivGAAcfJx3YnTWXJ6CS2xizotXmrMrXqpspQXNI0ijHAgkUS4DVzEumKJUPagi0S9y19DeDZoN0GHOKrXSCmW9bwVbc7SnLhxiaUled6cZXF9YpwKXNzm6mQIsOiwJfOiFtc+VFpFQBFQBBQBRUAR+B1FQMnJsfPijaZunZlmsSkcvawbliUnxx9//KmnnvqBD7z/S1/64stf/vINGzeK9xcBI9bsYPRc1H25a2ryovILN4CUmHXlWq4IWXFSZdchYESYifh0CZdIpSkR71IVpey6ZclBzGEGmCUiiIabgp+QmctMh3BxnHX9tFv3Uxhw8OOacAhrwvtL3NVMjUXhV43JRCqaKf/ijfOZiUNJ9RVWWZRo/XR2PKsXE5pe+60zYdyCvpS9g0ksViepCcOd3Q1Sc3HgPSU9FvTWVDhFQBFQBBQBRUAR+F1AQMnJMfWWhQTM/pAxzYE2qdeLXvQinLva25dceumlq1evkrRbJoBd1FvRdo06axiKWc94DDX9utCPxZQhVIn/6ia7r5ELmgGzMBzIp+Jiqka2YTuVFRpPMKTwRKPGk0wMJ0abpjEO8F+TcHe7dFOZNiYBjDSUVMHsIkHtRhBZQ9Rw88csLqVaJLQ/MaAwnh7QGqw04n3mBklg/v7gWbn2b1vgd7JJQzaFbVm8mnAhuWUqAmzjlUmbIDWhzwLfoIqnCCgCioAioAgoAsc0AkpOjqnXa40ns9/SuBaOMn/iiSf++79fRa3Ga6/9NlXVX/WqVxQKrcWwSFiImVnOxlWqsY7o94aKcCF9MGRIkl/LXaAGwhJQflGHSXSL/QRzBuoxAS3iGCZ2ElGWCVGnvCM8Q/4cT6iEOIfxBInQtoVkiHlk/0O6ux4CDRfLg8PlWpyBdBhLkDHnyPAw35IZKVaKpQoGBauGG8nMRGJzIbsVy9lR9Jej8WFvFtlZELOIWsEFg+ZhNm5NTwIF/0mLlKWRuHk9FAFFQBFQBBQBRUAROOoIKDk56q9gwQkAbSAJ2L//+79/8IMf/MxnPkOi4f/7f99RaClUqhXy+TZVd/nBXQiI/TFe2Ic9hGQY9RiOEPvpHHXixb0IkmIiV6S7kyIVl5dZ4jgZ3LdkColkh4pAE3wvTbn3rPFLaijMjEB3plKK6+dgMYkAkBboylg1uue+h7bv7q+n0jHOYviPSQ/GWmpTz+eDgYF9e/tHrO2kKSdJd+MUZQr9jMuinlgSMPIkOvoxYEyQ13CAAyoHQnBIYZTkQQgr1TgimCd5gwcYo02KgCKgCCgCioAioAjMDwJKTuYH58W0CkYK0nkdd9xxb37zm7/5zW9+7Wtf7evr/aM/egM1UrLZLDvBxUv0WswNlFXHIgIVkH/m93pR70XNFVOH44VxsGvvaG//6MhYrRbhmIVa7FK5nPxixdHSwDBGksAME4OKWEo8HwPIvQ9vHalmwtiFschccdzakh3u3fXQY91MbBySaJZ1+di2s3/voD+W6nS9XExOY3HXotkKhD2m5rpBza+mvAIJudDXGSQ6uyFCkRcMjNS27+ktlUPMOoYpCZOyW6DXYj/2D9BJdiMQUU4+l/O7lhbWdLUQVER+gOSxXigCioAioAgoAoqAInC0EFBycrSQX9DrQixsORTLQ7Zv3/r1r3+9q6uLao8bN2484YQTsK5giBCTB0o9zlo4V/EnXluuRHfYBFmuN1qNt+8Z2t1TLFU9arFLSXhXMvum3bg4Wi5X8cLyhdaIbxfMJD00Wtm6q+/R7UOl1NLISUfGowsO1NbilIbioaKUmGfJJnkQStM3VBmp5epuJgjyYvzAocwE2RMOLhHhcbXupyNvTKwxYjGwh1gPXN/rHRjZsru4rbtcrZFyLE1WZJFDCrWIYeGAdofmDAv0U8CRl2IOcBW3rfEDRgIiUUoqaTqpatovDgyVW7J+W06QbLrtjffXK0VAEVAEFAFFQBFQBOYZASUn8wz4XC1HOUXqnMAKsGccqTWoMv7kJz8Zg8mPfvzDn/30p7ffcXs+lz/p5JMuvvhZ6YC6i3KwFotCTh7bulWsH1alRymGVzju0Gh130BlqITnVEscpLGlSPQ5hhMKkDillEOLEAajQMMLgp7BgS07h8pR1sm0etSdJ9kWBhLKJVJKJdMiSbVSUtRF7CdiqWE5z/Gz/OZfiXgE1UEeQksEATqY0i2pWpyuRX4tNMXmzWAeorf7rru3u//RbYOleAkphWMnIzUMZQHoiZlhEdIT8bSbQKqwnEwkJ+YJPSJPEPArY6PFsaGlreknbFqa9d0wPGLfnAbM+qEIKAKKgCKgCCgCisAsEVByMkvAFmr3arU6MDCQyxHjgYFign56eALDT1avXv3yl73s0hdeevvtt33nO9/50he/+MUvfGGiyssK2UxmYGBo06bjhag0FqfSidPTN1iueZFDXEeGnMKEnwuBMRJCXawuLN2xnKR8KM5YzR8pZ90gF7lwB2EXUrpdHhr7CquiVBviYflJ5HjLl6/YPjAyVAndmk3wxazSTzqIBSSs19G6kQva1mgWeCQQP1UaHRsdraSX5CnVCCtBAJ5Am7DYMHgxqurm3QtE9jsgzG/CIXYU7EfGMw4rlovjXM3ZsbN387rWfNrnfU3oq5eKgCKgCCgCioAioAgcBQSUnBwF0OdiySuuuOLcc88lJqSvr2/9+vVHcAnMF5kMtQr98847/6STTvqjP/qjSZNjq6GS4w033HDjjTeWy6VsNoeHV0iSXidVaGuLnUo9jFx8vSAjjhNCFpyIAHQog9H/Dc1BKyZ6JZVqa23vXBpv2dXrZyl170jReFRm4kgieou72MSlpQh9GK1akT7d79zdUxscqtTrNcM/WEfUcqOke21tmWE3k6VOigxmBruipPlyCYh3/WropClDySAJaLEKuqSx2t/qMHHlBXqN6IKQ7M/uYoqcZovynO0RjsOV4+ZaC7i4MZCWKQO0QRFQBBQBRUARUAQUgXlFQMnJvMI9d4udfPLJGzduxGxSqVSWLFlyZBdC1ydEvr29vbW1dfXqtQ39vrkGKi2hJnfddTfM5N577z3llFNdL0DTxTTS2ZHuWtYyWh4eGenHHiKkJUzBBGq+U63WoByiE0MDHNJx1VNhrbPdP2lTGwaP3b3lejXEFEKgOqtHVf6qEJoJajcxEjhwxZhjVrd7bRmnvAJ3rMwEW4HExqN1ZzL+7p3e8iV+pdvyDeMSlnIqYbh85aoVYy0P7xr1fco78v8CrmUNtV4CTxbbYcNxDEQHJieNzRmrESVo4lStNe9s2Lg8CHxKvlhGt9g2rfIqAoqAIqAIKAKKwDGFgJKTuX2doqM39d05XamtrS2Zfw5WlF1wYEWBpSQLNS/kJ/uOjiUUbfzhj360bt36jqXLeAT3KOSyG9e2Bpl4eLTkBuk49uAXvuem8eBqbcUHrfk7v5TaSEW1fJBa1ek7Tkdb+2iZDFIuxhMmcrKZoJhr3bY02aNVvh3ISSquZd16toVUW0Sg4P4lK8No4BawF9eLA9+pDMaFDE5LiaMWvZxqrd7RUdi8KRMFg1HkNVIQi7lGplh0ZhNkFnLCS5qeV8m7EsMKMSeBF7S3Bl2dra5DNuEEHNm+HoqAIqAIKAKKgCKgCBwVBKYqmvMqxhzp7rOals7sGaXO7nxWY+cVrGkXS+SftteBH+KXRcjK2NgYk5CkC98wSMikrsbCMamtcWuXXrV69amnnvr97930kstfurxrBZEeUT10wmh1V2ZF13J+pccsQZX5sE4xEwl7GO5LtbXhSAWRMBYQAj2o116P0q6/dmV+5cqcOB2RVcqjXHwq8FID3fHWe+A8dGuuKy8OTRzjik2u5RKfQhO8ghntW43q0KqMT1BLWJW6Hs2xTIGDWTpIH7e6ZeXKlgqGE/sIBmO+CJwmQ3Dg3S+wVruLCdtM5KPNNtt98X0nMUE2SAVhhLMdNM+4wiXd9UIRUAQUAUVAEVAEFIGjgMDhkpOGDmg0e65npSLTH7UYT6RZ7ZtRHFO152QSnpK6ih/46cP1JJFooefExlC8h8QmwJlr+/SA8yMtfTimTpusbi/owJEsNPF6Us+FcAst2bZt269//Wt2TVQJHmLwk/3fCy9Y/jv44WzaePzTnvb0T37yamYL/CCVQfsvxbWKG2U83LwYa2gILIWUvajFdafihUNOXGmyQvgEHAOiEYbVSpwK/JSk6gq58lKFfGokHItrQ3h/MRO9xAxi5LFatfzsT/GVRqgJT0URxxgQBFJwXswgzG5eiIw2w8UtLKz7LOS4eIMRC28lkcGmk/k8+I4X5hPZY+OYyMSabeOf0Di+x5hMvFQNDmh2PWHweEe9UgQUAUVAEVAEFAFFYP4QOCxygs4til/zSK4ntTefH+AzGXKAZwdvmn4UT1Gskz4TiQHXHMkjuwKdk3bLSSZ1SASxT+kMhzmQd1PSUS7sJHSG0nC2LdPPv9/4Ob6xu0Ce66+//rrrriPT1+joKKJiOaGeyROf+MTXvva1y5Yto8PB0JgkIBEp1G0sFAqf+tSn/vAP/5AcxB7ptijtZ+LeXcnQizlGqmlQMZ6vXeAUvRSFyRveROKMZL5LsA4vrpDYFibIu6Iz3koBzllU54iJd9/f+whGgYQeHko+NeStvcd+I42ijcrtGHbi+ek8l4nMbJ+bOKrxZlwnCFibxWg17mCmGxtPui+WCyv+VI4xuQVoSdXFrowZqk5OM64IHFos+1Q5FQFFQBFQBBQBReBYReCwyMnB1NaDtU8EET2YW3omivvEp4d5bTmAndlOxfXE24nzJ9ImHaxsTMJF8tQOsbe0j4yMkGaXLFV2rYkTJtdmTeFCHBhzoDSk+uU66XB0L5Dk2muvJTvwnXfeSRg9twjMeevWrTt27KDSIum/ICozFBK2tnbt2re//e033XTT/fffD73JZNJMG4Y1sZk45OhCH2YNVGDfGCqqFCk3Ng2jIpvqimKdgVtCZTzhFRi0+EMqn3Im5o/f+JFHEJTsWqauipseK9eHiyPFMiawYIJ+bTXyKJvxu3tKg6NVSfbFehx2Blms8dfwLjPmFmN0sS9pobypGb4Cw9wMxZss+GRyYngJbwUMAUQQnTxixktqR0VAEVAEFAFFQBFQBI4gAodFTpBjz5493d3dw8PDVrvld/cVK1Zs2LABxd1KyU/yv/3tb1HieUR9cZ4m0pP0dvv27Sj35XIZvZZif8mjSRfok/R57LHHWIXoCHJGoftO6jPplpl7enqKxSKsAC0WATo6OlauXNnZ2Tmxp9FUGw2Qh97eXraDY1KyBB3YAksjLVmwMA6ghT/wwANMi5UAmSkDMnFCe82KE2dmOEAhfEtLy5Oe9CQoCt3oM3Xg/LQgmz2++c1v3nHHHdZacuaZZ4IS/l0PP/zw7t27/+d//ofdzZycsJ2lS5e+5jWvwT2MA27z1Kc+1dA8sgHDC+QPZiIbl62zeRuhnujNPCIoXdhIFEfFIp5dku2XJoZTRrFYLPPyDWRGmzYKNUaTcj21p5si9MNDY3Ho5pPpDMdgiXqhkB3pH+sbLhll3Dxn8yIApgLsLVST9OSRFFvh7PHmjIxG0vl5H0dsFc+aQqb/YgkE8vW0diZSoxG0U5e4HWFqeigCioAioAgoAoqAInA0EThEcoJqjukAbRsVloMEsqizBCqg/T/nOc951atehR6PUxBaL3r53/3d36Hro+Y+//nPv/TSS+124SQPPfTQRz7yEUahuL/uda+78sorD4YEmhQM4TOf+QzMAf6Ay9A//MM/HLAzHGZwcBCagavST37yE5aAVMCU4EXYAS6++OKzzjoLYfL5PBxDFFR0UqOpcl2v17EhfPe730VmNHWWYDaIyi9+8YsvfOELP/rRjy688EKqfMBJ/uZv/mbVqlUkyHrhC1/4ohe9yM4zSR4aOZgcNoWB4n//93+5YN2rrroKJkZnnk4aMp+3aPxsrb+/nzOvBlje/e53876++tWvQk5A7Pbbb+dlzURICyDCM5wSKxdddNG3v/1t5jnxxBMhhMwAsCzHYfE2CnSDDOCyBQrwBAm457Hj12JnaLiya09fzZThEEzimFfW093f3TscSpi6xc2YpFynf2D0ocd6qEPv5dpCsnvJANtBLDWEtROkMlqKSzUJNDHGEunBjbHKpGuxVyJncSgFGFnfyCPDG6KavovlJKxj/LAgjN8nVxYimJg4xJE5DY84fOgiUqMlXfRCEVAEFAFFQBFQBBSBo4PAIZITPH8+9rGP3XbbbXCSoaEhlHgUUPjG3r17H3300WuuuYZruMRTnvIUjCqQBDaHvouRAW3e6rsoQzANAh5QbdENaZ8GAIaUSqWvfe1rMBMGTrJ+MDDRj1Gp3//+99MNMgMtQTDRulwXOdG5YSywpje+8Y0wqA0bNjAtB2M5mATG9atf/epnP/sZPbEh8OgHP/jB17/+deRnKoRElWdCOv/85z+HZnCxadMmJN8/dny/fTAKFyk4z8033wxBeu5zn0tn5Nmv07zfsDW7HSgWm8LKAW2DSLBrxCP4hDcF4EA3E9GYLenG8N/7vd+DpcBP3vrWt37wgx9cs2YNtywHN7MT0p+DnpYA4OLl+RRtrFNFvhLGu7v777hrSzXV4rhZGyWCGt0yXB/uq/WN8J7ScAwJb5eAbkY6O/b0D5a8utfheK0pN40oVkdncpTvOKqmPD9yszFB+DQZSZmFR0E6M1pxHt0xeNdDu0gjhieZcTZrMJsmw0l2tjgu2JrZPvt8nO8YNqWWjLNqRdtTTl/lpXyblXlxbFKlVAQUAUVAEVAEFIFjF4FDISeYSj73uc+hxGPxgJOgo6Nto9qi9+NJhbKL7QLEsDy85S1vQTG1Cj3dONBKEzBRVVFYbfvj6sF0Q2nGVsNwNN1kEnvBtMwAkUAwmIPlJDwiSpvcUxAkjCFIxQX06bOf/ex99913ySWXvOAFL2DURKmQh7H2zFpo2GwWZkIf9shYVHacnZ797Gf/8Ic/pCc+UXR4xjOeYSlHsjt7wShW/PjHPw5lYjYGvulNb8L3aZLw83+LYAiMaevNb34znm/YJWApsEfaEYYz5hTsQnCVQ5CNrwEmMmaDTL7vfe8DKyxOsDhMVbw4vjCAwxJc1PDf4kpSBvAp7KG/d2jLtr5qlA+DpbGbJsYdkkBmr7pHNZKW2KNsPLYNkdEIRoH4qFanfGO27uU9Nxs5FHpvHHzP8CIzpeWDFMUZ3SDEZctQD/sdBIEdu7t/s3WwWM+6HmuxWZ7EzSlkguZki+MTJza2b97hwYQf3xFJukYq1bCn3PFY38bVhYzvRaR51kMRUAQUAUVAEVAEFIGjisCsyQlGAJyUvvWtb1kC8PSnP50gCtRcoikwJuDrBYXgTJj1j3/8YxrRei0BQLnnSDabqO9Jy+FcoOEiEswEzsA1+vGLX/xifv63ajf6N5QJqQhE+cpXvoJ5BGsGuunxxx+P0mx1ZSsPMqBAIzCmoauvvhpfLGZAt8ZDCfczS3WY9pWvfCVWIzT4X/7yl5hEMDscTHg4Cf5gu3btQjXH5w2sWPdgneeznXfB2zn99NNZlL3bV/PTn/70nnvu4ZqX+/u///sbNmwAzASZGYrHcGgYhA0YYWXggzHtjDPOgCUCOKTFToh3HAYTwlCI9yChF+sQAzJWjgeHyfCVdXwyB/DllJLtccqL3YzjpiGITVoiyrdYT6JU14qlu4bLQ0OpsEJNE2LvsfaYRFRidiHnV80NnHK1VuWtGoOLoRyio7Pk4NDIwFDRzXVIgUiWYyX8vZhFjnE93twugpNBxxCU6eQX6HhO1Zmw7o6MFXfsHli3Ip9Pu8QELYJNqoiKgCKgCCgCioAicEwjMDtygj534403fv/730cvR8kmuuAP/uAPnva0pxHmbhVcOqCSwgRQPW+44QYSN6HmWgDpwDEXYOKOhXHjE5/4xC233MLqRFBcfvnl+G5t3LiR5WAF9td6uj344IN4fOGmhc0HRXzz5s10m8QWRE02Gave+973orvDTNCzCckgip2e1t2LLWMAwXMM1oERhkUnTWK3iZmFDvv27UMAIviZBGHmAoFDm5NtJrYRjEXwsW984xuQLoxdsDsCToj+t2jMdn7QYOzLXvYyHMZwpYPQwnmIFLrgggv4YsBewIGlwYeZhQtAjkiYheEjyAbZtkpx1PdrrlhNaEaNFoAj6ilSb9HkvjXqNf1hE/HqVR17CH9KVQlWaVKXhrz4g0UpjxopUYVoFMfEq9hH8j1kUuMEJcubEiiis1M8RUIvjEyNWRbRh0jeKCI5CYpkE1A6iAkWJLziMAdCSKIQQicGpzn63zNZWi8UAUVAEVAEFAFFQBF4XARmoSujp2IHIPb9scceQ4+BA3z0ox9F+0TLRN2kJVFkMaG8613vwi/oS1/60t133520H1Aanh6wfeaNBL1gMNm5cyfqJovCHAjBR722ypalDdYT7Lzzzvvyl7982WWX3XrrrajL6OIESGBAQH67HEPoj+rMBbSK8BX4CTYTu8dEVFo2btwI8YCk4bjF0phTaLQrJpLTgXRYuJMx8HnPex7B9Mmjo3uBPGCV7BruRPwP7mfYlCAMeOidf/75IEkH25N9Tdra48oPjBiaSNhFagEID1CTVACHOgZCflgC6woWFZNBi3APD089skZ1LmlbvybevrcnLg35Ad5WvjBFaAUR9fVyTFZiKnI0D7437CJIp045sX3NmlQRFtwIKmn2MJ+FQqq3e+SeZW17h8a/7TKr2I6y+VxloFL0ItYiyki+BsZvTBjLfrMskhsSbz2upC6YyvZwqqtmfWft6hWE7uBvx5ciRdyNHoqAIqAIKAKKgCKgCBw9BMbVtceVAUMB1gmyxKLo4w31+te/HpctFE3UPDs2uUCpxc5AVlnMFHfddRdP0XHtMWkV25gMnPR0+lsUUwZyEAryT//0T+TApQUO8Pd///cwE/RdHiUzcGuvcdPCWkJPNGYGwlLOOeccdGX7FHnYHTYW+Am2ESLv+aXfLDJOveiJ2v2P//iPmFYwIsHW3vnOd374wx/esGGDnSQ5E4UPPYPk4MvEbBzJo6N7YXeUyECu5//+7/8GCl4xnARGQbkSiwk9Ew6T9J/hBWOBHaZKnjR8uv70T/8UeHGogwhhqGGhLVu29PX0du/tXr1qNYE+Ub3eEqROWF9obz2lu79WrklpQLN8hNfRgN/+29YWQkLsS0UHF3LCTRjlXCfT4kT5hlyNt24+6EBS69pgqjUT7ZMIF9tHvne1WnXtmhX1zLLfbBvtHxyp4U3GcuNzCEgz3OmC6Wa215C6sdVENpMXTe4wmkBBiORpawmOW9G5fk0hG1TFfjIDYpPMpheKgCKgCCgCioAioAjMBQKzICdYCUiuhZUAOTZu3PjSl74U/fJgChwaLaYVIg1I2IVXD7rgJOkPNnBSt2lumcFOi6ZLymBIBfYN+BIkYRrvKdRllG+i2NHFce7CkIIDUkJOWM4KBpF4+ctfDgmZqJonu2B+3LTIvsVTAlrIDQA4yVNmgPwwFbQEfkI7xpwnPOEJE6eaZl/z8whhEAzQyB+AAx7pktnIaaedBjhIC4yJGOzlkCUHCgDnewInZDkOknexELYa2n/wA5JQ3//jH9/y6le+SjyqpDZ8lCM4pzNfKIR1ftlHCHkfcTbt7fMLyzoKExVorC4SRRKWqdmItg3qkiBY+sswSVslvkue73gZN854Ee5h42yD704U5TKZtSuy+YJfquRDXLnEm6t5iHvX5C9t89mC/ZT9YxMxch9Q+MYGAcZPRVnPa81msgGoQ9t4yxO2v2C3qIIpAoqAIqAIKAKKwDGNwCzICQolOXbx7EIBQmsnRnwaDgBoaJ/4RJEUC3JyZDG0aq7VQlGdMXQgG0tYKwf2EKjCNCsy3GrbaMnf+973SCk2tTM69BVXXME2pz6iheGYhk466SSIDRYb/MrwUMKzC4uN7c8S8CVyeaH9I+czn/lM9P4DTnVUGhEJCVmaiH/qusBM8OaCQhAWQmAMVI3t8KIBgWtLtA5ZTtbiSIYzIYddnSzMX/nq1+6++54rX/XqIONXqzVeJgEgaddpb3Gxixn9mrFxPuNUR91chmvr1iWsBEIiNxQQtI3SIop54ttl6qpI5Ud4GNEVpuwJT+VPxtGSCguBn1tKTcycDTsxT8wpmWW8aXFcCWjGOUuoXfMwDY0b2oXL4cMFLBF/9UjS3zHOAtMco5+KgCKgCCgCioAioAjMOwKzICfIhqptNXtoyfTMxG6EiBTCPKwmOhdbQ+vFbEIaLrsElhOYCVH4xKBPsyhBJgR/Iw+UBsczuM1E2awuTv4xJLdOa8lUE5VsuhHejUMUGcDogCmGIAosRbYPZ8LuP//5zzMzQEHSNm7cOHGVo36N/Bh28ObC7w5Sh/MVB/YNoHvkkUfw74JxQc8gEhN3ffhiJ/gwFVVffv6LO7dv37Fj1451FKaUPGl8wepSSj5OcpoJ3/AyFOKoOTGJpGuGs6BJi5mDtL9E0WM0EQOLTE1n0m2JKi6FUKAk5kou5coo39KXW5khxZyR6zsBd5P/T1ic5ER2xWbMRrlO+Mn+5EQeG4zoSgoAylSaTGaCiR6KgCKgCCgCioAioAgcTQQmq2QzkQVtG619hj0Jt5hJz1n1sYooShgXxKPjOsUF2jY5u3A8wxow0clq6sx0Jt+xUU+nPpQWDCOITYB78pghybW9oAUPKKLqiSqhP6HeRFaccsopgGPNMmj5ZA7gGtKC0k9/qN1MGN2khebiFqwwlSAejm1YSGAgrEKONZzcoGoYlDhzC9eCVtntHLIYCc5TMWxtLWCbuuOOb7z73X/9iY9/PJvJ8BM+CW4dp+aKPQRlWf5zJFYd7yzYiPHzMqLY2UTD5mGQcaWyZVO3Np+imkNQIDYeL9RzvJzJRCxUxx4yQxi6KdKCkZI4hIwkGrzwG/l6Nbs2RiyCDwOZ0C4Os3v53sqeAU/AsKxFrFKkMuM/mJ4Ti3EP89LUF7QINqwiKgKKgCKgCCgCisCxhcChkBMMDvzobrnB4aBhlSGrvFrXrIPp7ran9d1iRS4wmGAnseo+lhC0bduOzs1TFO5EJ54qIaswkHam5ZrzpL0wm+1gx9oOyXVyAYHBwLJ27VricKBDbIGeVpXHnELYN/MQUv+Rj3wEny4e2YEL4YyQON0hEiSTa+BCKrtroAATrjGkWHAOR+CJwNo3MgmHl770JfCRr3z5y7fdfuvZTz670Fpwa8LiEIB1LZMwsSL8xE9IScMSYLTt2BWwPTcdbNtT3L53qH9oLIqlkKIEe8vLJfGwhFK0ZNMDfT2/2d5TwfdPFHQhLXQQVV2qyMeen/LT4jE2fjhEp9Bx8ZET+JTBSISfKD27Y7uYpYx1KgQGuIjgK1CYAicGjXEE9EoRUAQUAUVAEVAEFIGjgcChkBMUR45JWuYBhYcqYNmgp1VMp/ax7ZxRM6efkKcctj+dOZiNFmI/ksgQIkAI5ib7VkJjpq5IC3o56q9dlNv169czz6SebHBSy9RbRpEn93Wvex0Zh3lK4RSKDGJOYWZCzKk/iJAEchA6z5nGqatMnXPeWqB2BPT/8R//MS8IEmKBTVZHVPgnkicth3YxccsTr5PZjjtuPZEnnutcc801yCARL0uWYM8gVxfVN5qmDH7j5wjRrJOBvDDRrh2nu6e4Zefwjn2VctUNU5ATBhm9m+IlxFWkorF6MFpKl0PXBNAnE8hYz09HsT9aIj9bRbja+NcAxf7xvwDjcy2MK+EZhmwIE5nCrGAfbhBk0mkxUNWq8g2XopOSRmBhiK9SKAKKgCKgCCgCioAiMMXTfoaQTNJlDzZqy5Yt00TDi8LZ/HlXNEWPAN3pNHhLSFjLdrYX/PaP5cRec4EnEmxhgpZ5YNHsunRDRZvkova4YyfOSFDNxRdfTCJjGol1oaojgShQI6rC4/EFayJZGfSJOWc17cQl5ugatLHqQAxAgGPiKuAMXcGcAjJzKjZKMZryE55wcqFFCuP84Ac/wPp09tlnr+jqQmWGQIYm+qShPIsXkhzW4iEGErF7uLv2Du3tLY9V0366JeWkxflLviDWqUlMBV4656VHgnSuarNRicFATCrUp69F7sBwfXf3WKValTfEAzlAA03+APq9fbxgz8YZzRI6s4X9BWVLQTrd3taydkUuSwGZmPQDBJxM3GZj//uP0ztFQBFQBBQBRUARUATmD4FZWE5QZ3FhIiABlypMIoSe49SEFjuNsNQSIRgjYSCTeqIMMicaEh3QSq02nNCGiZ15mkSJ0IGDsQy0M9j4EPoQyU3uLOacWg8xmY2xPT09dKYF4cmvlXAeWqx+alawmnAy7sAXLA0DIWkyc1JykRAONGoC9Cm8CEokv7ryyisJN0ckxjPtgWeZ91YrCdtP8J8EAjjQYhvpbGGZiZh0tmYrxtpdTz+KmaFAK1asfNlLX3bNN68haogXTXKz9tYlXhDwjnHwMnTERbEWssR0cYQrXl2iKIg38cdKlTIR3W4aMwiMwwaeGHICwzB0100RVYJlzgTOCzMR7kHaYt/d11N6YMvow9uL6Uxg8lVZTd1q9vZ6evEX2lOPHAAmUib5prFds2MjaT0qtrWMRnHX5lUUneR/IAOu8WBbaDtReRQBRUARUAQUAUXgdxOB6ajFJEQIm/7ABz5AiUMyz5KKinrnV1999cSCGJP6c4vLEKEXU9tpQS9Cs0etRx9FoSdIg9y7p556KtoqzIHzRNpDUAfpsJJIEjRghljdF1WYeZ71rGchEoEfkATivDFoWMV66tIM/JM/+RNKSeLXRDZkaslTUJL4Cttz5lq47Y8kbOEv/uIvKMJIXD7CwNkoVw9LQQAcxi666CIsJ4c2+VThj1SL3SbCc3CNqJM2Trtdyyiw0cR3MY0MdIaSgQMgw9lwG5s07dSxVnFuyedf/OLLzj7n7C9+8Yvvec9716877j3vec/ZZz95SccSBMHgQbT2ihUr1q1dJ6q2sY2QNVgqnNeqmXzWdctV6maGdZ7AMaR/QyOXmBPrEwYFDido7DKl6+3cs3vbrjEvu8rJYHJBOv7Zv/1MSVPFXqgtgEOg+zgbMcwkuZWswaV66TePbl+/4vis4cv7byQBaP9mvVMEFAFFQBFQBBQBRWC+EJgFOUHJJpwDXRyNExpAEQ8SVZFtduPGjUhr1dyJYv/nf/4n2Z/QUyc2JtcoxBgWcIh661vfChvBJwqeQ7YrJp/6izvuYTaR1MTh9pp5SIf1V3/1V9Cb+++/n9KKn/rUpyBRCSVIhnBBelyYFd0gMNzSBwXaOi9ZNZqzvZg4iusDNtp2nKOo5fKZz3wGBgVBAgebX5h2yAl5upBw0mwL5NbsNdFc9xOKRwljmfo69utqbmBl+O9961vfAmG+G7TBZ6xXG25vK1eunDqElsbavHHfK7S2bMhseNWrXkVxlRtu+O7HPvax1rZWgoj4Spx22inwT94UxpMwCkeKo/mWPOET9Rrmk/i4dZ295eHS7uLI2GAdywnTGu3c+mjVKeIR18bGSiWKqKQIO5EwFMs/EIDECrWwGhi3O8Lrm7q5MJMkVVez8YA7OEDjgQE9QMeDNs12xWQiGJdsb78DcUAC5sV/YqJMRWGlUsK+JejD78xLaMrc/NxvBr1RBBQBRUARUAQUAUVg/hCYBTlBScWP6xWveAWON6TrxXOJIGbsHs94xjOIY0Z3RGqoCKaS++67j0Iin/vc53BwetKTnnT33XcfcEP8Fk4tEYLFcRKj/3e+8x20WIJGNm7caKsZ8jM8lOOBBx6gUCBzihOKOSZq1ejQzECgAgwBwej/7W9/e8OGDVRk58APzXID1DIqSCL2LbfcsmPHDpRpZH7961+POQg1OuEeyYWocTM74DaQEAgSlh+WIIMwuyaanHCO5z3veTPR7Ge2znz3slAkgEyzPFgR/Q/s3//+99k7PS3mMApIIG8ZwxTvaJoZZBUnlclmqGtJT3jdju07Hn4YN72Hd+3cceedP+cdLV26lNKQfFX4JhTOOw9iCeuIw4gaLcevd1rb02MVeIgkyEXFhqLwXYGlkLALl62+fZnOJW19w9646g77cpxCPlvI14q1osdEjm81dUNeEJYvgHwJMC1N/CrMRH8nDfE0m53+kV1x+j4He4qgIl5jcT64kz8O+T7H9TCseG5t6ZKCCy2Rbo2uB5tQ2xUBRUARUAQUAUVAEZhnBGZBTpAMpfPyyy/np3Gcl7AP/PKXv4R4QB5e/vKXk6iKDthAUNDJVfXjH/8YooJdBb5BaPgBdX0Ud35ch1Rcd9116PS4Wr33ve999atfTcEQrCjoo8S3/OpXv7rxxhuxnJA5iplR+qeaYtC9YAiXXXYZfIkf7+EnOAXh6PX85z8fPzHLPSA2mDUw9TAJQp588slEg0BOrNnkcEBndZbAPgDnuffee/ErY7McWJkuvPBCnh7O5ItiLBwSWnLttdciLawSbEEV1gqX4J3CW/gOYACZyV5AEsvJi170It4yJIRvF++LYB5uiSbCS5CnJBvAbW8dOdZcV/hqGK3qzHYtlxLvia5tdXS5laD51PbcyF0ducGdNDS6mA7x8s4la4rBzp56Pa5QLV6SV40feLw1SEYyrZlvvMdBr4RqHeIxca1ZT2HXtZuXnUJKXMiVuMBB1OJqxgs7WtMb1rbjx4dr5Kzn1wGKgCKgCCgCioAioAjMMQKzIyfo3PgpofSjj7773e8mCIQD8oC+aE0EdMAowYFSjnb+ghe8gB/CP/ShD03dBT1pxEmMaA1+bud3d0ZRrx2nrE9/+tOwIDpwoJVyxgQBKfqP//iPBx98cCo5YR6Ww3gCdUFbhYFwgbpM7AfKLk/tbIgKLeGWcHnCTmBBSagJjfZgOMs172b6yd7f9KY3waASGobRgJ/2Oc90ikXbD7h4fbw4ijZiJIE24GKH6ePmm2/mvZM/DUc7TFhwyxnyNF4WL4hp8frD7Ma3QhiIOaB/uP99/vOfh4ji8ZX2fV5oVK+4ITjj0LXfCqjoHv/cVNpz2ty6Vx/0wpJLwUFqyps0wfVadfnyNi+3pKVtrH+QGikwEwnY4PUbvzD5GtCVY+IXwjQYaQ52IkjmYI9m0C5bffw1DjpR4pqW9JDJCEUxRpUlbdk1XW2rl5I2oBjV2Zb1+Er66oUioAgoAoqAIqAIKAJHGYHZkROr/WHWwLmLEh8Ex5OPC0MKJo6ETrAhvL+IEafkCKoqv50fUN23U3EmmRV1Qs4///yvfOUrBIQYvlOxT+3AN77xja95zWsgRUSZQ4oOBhg8BHUWhy5ozF//9V9j2MEFiM52Ki6YDab07Gc/+w1veAPCMyEtyVM62J/niZo42BIHa2cS9GlrhLFz/vmf/zkFTyZOfrCxx0A7GwdzwMe1DwvJ6tWrSTaAtcR+JQ4BBIshlI8ZmByIaOGMdQ4L1b/+679iT8Nhj+9hrV5345oThR5MRIqe76fXEw3P+/c9P5OKM26NQvA8xrogIjFjPUzFYWsu2LyhkIpaWCFx+qKfJSSWnMzqHU2lB7MaTudDWDRZYqLpxzYaRDixIZze3LRra1zWXSxNh0ODkiX1QhFQBBQBRUARUAQUgSOHwOzIiV3XRiej3GM8wR0LOoGlAt8bfi/nl3IUU86nn3466ikXKIJWszyYzCigMAo8eYg3wCeKn8kJHeH3claBtzAWfReSw8VVV13FmR2KmAAAQABJREFUWsxDjMfU2ViI/hhDcBWD7eDixSSwJuakhUcIBoXAL4gJYSmsK0rqhANbB45eWHtYBSMAK07qMKHv5EtmS5oYSCwNm0pajuELIAJVIoXw5uICYPkmEH5DbA/fCsgkhV94NCsELOyc7UUylvl5L895znOYHHICI0LhLleq5Bs2Ll28ThP5bQdYeoECLtl1MYjVw7hu0xJjIeGh1PiQ2uhV4uFJSUzJRviJqPANZsJrbE6RSDCDi/2+UjPoP7WLUKhDWZmZGoiJe5fBzkwjuzL/mYgcvLmimmF78u1vrjPhcqpA2qIIKAKKgCKgCCgCisB8IXAo5AS1h1+1IR7EVFi3K3RQzBoEl8MN4ABo6tgxpmr/B9sUnVHloQ2iD8YxjAJ3nYSc8JSDdpx5ODOJdSGbOhsrciAG5hHroIXxBHcjeJQVzErObEZzmzwBP9Jj7oDSsApLHLDP5DHNe6uIM5DJCY5HdWbR5sNj/JMtYytjk6BNABLhRuRDI8MBL4KsA+RLgEzOCsyD4cUkkB8yeuH4RwQRlpNzzz2HbwQJhUPMIE2TSEPlbrAE1HRjEYGISFUP5oZ8wCTlmxRHdQwJeDw5ceiSaBcV3ozCBMPRNJ8cTJwDtzPBfhH0B+41XethWE6EnpEkWaAwVpEG5zB7Ndth00xfP9DyDbwO9EjbFAFFQBFQBBQBRUARmCcEDoWcJKIlMRXYHNDF0R3tYTug3iU9H/fC+vDQjRn4gVxUQ5PNNhlo25PbaS7oiWCc6YNgqMj22p6nGcgjmBXH9H2mPkXrJRjGVnRBeyYNAEYkutldTO1/jLUArKWLsEqYCbVKiFzHWoWVg7QE+GLBY4/UliGZME+yNl9//fWf+tQnly+XfM3pwK8K9+ALJ4zDkoom0eDONhpt3TAHFHeeyvdTrCqSNJmswtxRpZHBUBlXKsjP4ts7cXeHyUyYyhKkiXPO4loGYwKCbonFUvbQIB0CgrmxF1OntE+ntmuLIqAIKAKKgCKgCCgC84fAYZGTiWIezJoxsc/01wl5MMqi9EW5so3JxfQzJE+TqbhIrpOnM7+Y4bqYjwi/IVabtdCV//Iv/xJGNPNVjpmeFmqc4nDM4/vAxT//8z8TuQ5LOVJ7ZAnY42tf+1oMYv/6L/+yd/ee//70/1uzZrXvB+JEZsp3Gu1cVG2hIE17ANf4conaLnYTbCSRkBIPE5/rI6sYyiSiHjnNEEnDcMgyHyY/SWSevQAu+SNCMgjUo5opAmM2ZKex27FwTN6aJXCzX05HKAKKgCKgCCgCioAicIQRODLk5HAIwDQbYtrD0REPOPNM+EbSZyb7ojOWEzLnoovTH1sNv+4bZbepFx9QjmOxkTzCJJXG2Q/XuLvuuuujH/0oLOXqq6/GokIg+5HaMYBjGXvlK1+5fNny/3f11W9769te89orn3rhhcuWdaWzmRCtvE5BD4LdRQXnHSSvQbydRAja5ZHrUfwxPVKs7Ny9B1MPdU+SxzzFA+zQOEaynCx1SMdk6jDjSVg6CNLLli5ds3JZxo+rJDozOzUTHPKsM15eOyoCioAioAgoAoqAInDYCBwZcjJDMWai60+ayvKT6QdO/3TqhJNapt7OasKBgQHis3fv3g1FIcSCH/UTp7KpMx97LdAA4kw4oGdEnuBzRf5fbBLEn+DZRTASLAW6cgQ3ztuB+xHV85znPJvS8vh3fec71//613eRr/iFl16az+WIHYLACDnhj87ExHh+S0ueM/SENhOD4rie1zMwsnXn6M49pVooFUF4KHIay4XMsNgOKiu6bnnfQC9VQE/dvJpsZ9SWBAWzD84H5U2Lb6uL7dWovIqAIqAIKAKKgCIwQwTmlZwcmsI3K6oww20fwW5kA/vsZz9LVUrmpObji1/8YpThIzj/Ap+Kdwot+e53v3vnnXeeeOKJEBIylWE+gqpBIeBpGCXIFnDEdwHIq9esIWEXa1Fe5je/+c19993PolhveAQ7CvwgHQSZbBY3sO593WRvI1LcfpdQ2PHhok93z8gj24eHK7l0pk0iVkwwCgYWSerVVNiFzczyIOR81mPMErCHw8lEzLJRvT5SHKkW955wXJfJ6TAL2yN7BkC71/H9z3Lv2l0RUAQUAUVAEVAEFIHDQWD+1GjUHXugIHKxwCnHDDHFboBqThlK0ouhBBNcwS/6Mxx7bHRDxd+8eTN7J6k0rACeBj2Aojz22GPYlGgniXOS4eDIbhnyQxoG+Mkll1zys5/97Atf+AKOZNZog5bdVii0tS9ZurSj0NpKLMr2rdso2pgElmBG4HqkWB0ai9zc0hBFnpATka9BK7i2rOQQaMaESI9Z73j2VGh8CYL5sZWEUThWLZcrlVxWSsQ0j4OaTZodJn8eM/+TTt6Y3isCioAioAgoAorAAkZgvsnJscRMeK38Hr9t2zaYCZocJeqpoLKA3/WciAYZgJKRPZkEZcSW4N/1rne9i0asJbxr8CEKZebl4WcrIgthnIEU4Tl22mmn2Rqd4mR2//19vb0YtSBIYrcxdEHigqoSFwSrMS0SPl6P4jSzUAqFio1S9qRJTug3W2ma/bE+HPJYRh6O8QTrDwVbMA0F6Yy4qcmOZEtiFTqQVElcDb5sFkzp1jyaG9JPRUARUAQUAUVAEVAE5gmB+SMnaPAcbAvN55j5Ufa222772Mc+xnbY1/Of//ynP/3p8/TeFtIycINXvOIVWEi+/vWv79ixgzy/hKTT2NXVRcHEF77whbh7zam8aNU4dzVCTVIpMhdT0LNarvBfrcpXLsaOsHXrY//1Xx/jG4jrFn8SMh9GK7uWri0Gu3v6alJLHv1d1Hg5o8lLtRB7zI5o2Fxb8oU4pENWPtTBEsIfhbl0nX2l00EUkbprXIjH3YalJGNjY/b/0/GReqUIKAKKgCKgCCgCisB8ITCH5ARdh12QSfZv//ZvuUCDPP/88+2+7CN7vajPGA3wKSIKnF1QWv53zacreZt4drH9pUuXYp3AfGEDTvC5giRg0MDLa67fMt8uDrsKNhwkoSi8GAyMok+VxpWrVl111X+IaQUTAXmDUeSjcHln26lurmtJqVq33aWGOuxClHzmOlTbieE3h7Ljw2EmZr3Ic1OFnLuiI8AUFJlNWKbTZCZCo9lfIpxQqYYnmXATXtxvf/tb8s7B9JI+eqEIKAKKgCKgCCgCisC8ITCH5MTuYcOGDe985zutqYQIhHnb2PwsdMYZZ+CzZC0n6HPiL/Q7eWAnwTyyadMmoEiCqlF2aeeYZy7aYCkTXoWfDjDj4NOFq1dxdIRkzwRmIGprzi1kC+tXFCohthRR2eWfMBqr0su7lJdrKjPKzYyP8fEzHmI7jvOGWQ6kO8wq7acCP+U71DqBIoaJGELGMFjKnLZtfB17b4tRQt5uvvlmDF+wu9mvryMUAUVAEVAEFAFFQBE4XATmnJygKeJmg4aXaKii7cmv0uPq0eFu4uiNh26hfB8z2zlkIC0PgZtNfK0TX/ohz3ykBiJYW2vbfffeiyXnrCc/uVIpC40Kq6m46jpejqy7JBoW6RtfS/P1tNezdrM6ZMsJmz2cgBM4VBxjAyKOBuplmQlbwEw0CcXJ/IR98+44RkZGvvrVr8K3+U1h0hi9VQQUAUVAEVAEFAFFYB4QmHNyYrVVe2Y/C0phPSL4Jls7IrMt6kkmQTHp9uhuLZvLvvvdf3XNNdfceuttZ5315Hy+UCyOYeRByCiuO2I2qYs/V5MzN/V54+41W9GTsPrZDpT/QWY/JhnhRIaH2Dmsk5slSuxO5uWjeXBrVpKoeYd8ANBsQk22b9/e29v73Oc+9ylPeUqzp34qAoqAIqAIKAKKgCIwfwgkUb/zsaS1mczHSrrG0UZgob1rlO/zL7iA8+233Q4/8SgOH6SlTKFYGwgblyS8Diwlqk38wxAhjbP5g+Sk4sP4Yzg0aTYrTugsBhMYF+zEpud6nG+BoSdUf8EjEWTI/nz11VcTPrRx48a2trbHGauPFQFFQBFQBBQBRUARmAME5pWcLKif0g8ZzIWmdh/yRuZ04EJ717gXUsD+oqc/nbKM3/72tx955BHCTibEw1hLgpxNHLlcSPIrUfJn+ScWCbFXHNqfHTvrRa2Q5o2Ka1rTO818Nk72dSMcFhR7ph+wCDNJp7c8+uhNN91E9rmXvvSl69evb8Tt2DF6VgQUAUVAEVAEFAFFYL4QmHO3rkkbWWg66yTxLPGYRsiJzITraXpOmllvjz4CjvOiF7+Ygoxf+tKXuq7tIv0xUfJYDIj/Jq8w+rp9m5gdpDiIHE0d397N7DzBdWpmA45or6ZXmp10P1m4EX8vs097hoFAz0gPsGfPnuuuv/673/0utXogJ8ByRIXSyRQBRUARUAQUAUVAEZgpAvNNTmYq11Hq97hkI+kwkaUcJWF12dkhwLvr6Og499xzt2zZ8oEPfOCEE0646KKLaCFFFeUjRWlvztfkqEaVbzYeG5/2C8yZA2JGfRj29clPfvIrX/nKmWee+W//9m9LlixRs8mx8a51F4qAIqAIKAKKwGJEQOohLka550JmC8VVV111yy23oLrh7vKhD30IF5epa9GTDlPbtWXhIzA6OopPF5Hx99577znnnEN5FvJBYznBfsJBwAbHwt/FoUkojMQc2WwWBsIldWk+/vGPX3fddQTBv+Y1rzn55JPJ2XVok+soRUARUAQUAUVAEVAEDh8BtZyMY4iuBut48MEHb7zxRtxdKB9JNbrxx+YKBxj0OXgL6h3F/vL5/KQOervAESCxNTHfV1xxBbTz7rvv/sQnPnH66ac/73nPW7lyJa+VLwDHAt/C4Yhnycn/Z++9o+y6zvvs026fXtABEgABECTBAoKkqGJRonq1LcmyYsm2In8pTpyspSylLNtZdmLH+cNOPtufE8dFjprVrGpLVqckqlMkRYq9g+gg6tRbTvmeffbMwZ2LmSGA6Xd+R8M7+56zzy7PuQO9v/u+7958vH/4wx/ee++9Bw8evOeee9785jcj0tipRspkLmx1rwiIgAiIgAiIwNwJSJxMYYjpRpAPmoSC/Xa5+TJm6wMPPIBfBU3CckbYc2w72FxB5eVPgCeLPrnmmms2bdqEGvnyl7+M36BaraJVOJ/P53llb/uOjg6intpGqPCRZo58tsfHx8+cOcO8vvrVr7IZPJLsBS94wdvf/vatW7cy3+X/+DRCERABERABERCB9ibQKk6wWrDe7JybyxmFzFyz1bI6tmCvZi1kd63EQnPkvZ0XAT933303cflcImmYveokTlbik+XziSGO44uceFTKZz/72S984QtY7WSecH779u0IFfxmSBT73FfiHLMxM1lmcerUqePHj7PHIn6/+++/n6kx05e+9KXvete7EGmIbflMMmIqiIAIiIAIiIAILCGBVnFiTRmrLuxry+CmPUmdWW5paeGi3i4TtWNnhwGHPuFLaKJiuru7L/CbZqZgb88KlkDL24vCospzJ4DCxDmGOLn88sv/2T/7Z6SdfPOb38SfwCP+3ve+h0eFFJS597IcWmCmfHT50KJDWAbghS984ctf/nI+wGTDk/7O+Zn+qJfD4DUGERABERABERCBVUWgVZww+WZL5Xm1QXPlacE9bwvT3pWdfN72s5oLXci0BAUO4n8ucGxZtaxgh9rydqHHr/bPJ8Aj4DmyYJfdc/AVr3jFnj17ECe4UGxy/Pm3rNAzzBQRghohXI24tbVr19oPsBwmK/SBatgiIAIiIAIi0K4EphEndqp2/SLK+AeazWgyaE+cOEGw/u7du2eCgu1OgPvRo0cJI6Hm+vXrMYmao6RmujE732g0zp49S180hSE1ODg4i5uCOpiS2F6E1NMCPWbtTFvA+uQ8t9ALAS3Ns5u2PifpAiBYchRsnZbvm+maqxzTtvBcelCnr6+PKP8WpNPeopOLQ4Cnbw+644PKh42C/YQszgAWupfsE2unyZ8hhZk+qAs9GLUvAiIgAiIgAiIgArMTaBUnmDLYLogKhMGBAwe4mbgXttZGKjz22GO8JSP86aefJigfcWIrZx1g7nPp2LFjnGfBVtJtkTF8TUtNjHLsIfI0Nm/eTCxNdktLgRaefPJJ+mIAaBv6QhKwiBCBN3zpi11FU4SjMMLmG4eGhn784x9j8aOI6IKVYZuvtpQZG81yCzkGDImdLpAZLXVa3jIG6hOpzwCeeeYZWuBghKxFS4HKvNIaYyNsJrsXKcL0AcIZ7mJvDb6PhxtxNfYLbOxghErLXLLbVVh8AnweOBa/X/UoAiIgAiIgAiIgAiJgCbTa5dZWxqRmF21WWcUu/+u//utbb72VhUeJy+cbZc5w/NzP/dyv//qvZxA5jxcC9wB7JlCf89jrVLMVMpvvne9857/+1/8aAx3nxvmOFJQJObt/+Id/yHJYrNhLm9b0Z0gcNIJN/4EPfOAlL3kJBdsF5ylg97/1rW+lPse/+Bf/YnZxwqjYveSOO+5AXbDrHLti49Wx45zplSSTRx55hF0gUFzoH6rRyEMPPfTv/t2/Q9jQKcPglYmTYG0boQJzIc36P/7H/8gsODjDK7Mwk3Hdm2666Rd/8RdZ0JbUZBnEM5FftPM8kUXrSx2JgAiIgAiIgAiIgAjMRKBVnGBAY6hhMaMfsMW5DdsdofJ//+//xXuQtYIUoUxle4YlgP7hH/7hM5/5DBrG3kUj2dXsro9//OO4X1784he/5z3v2bBhQ3beFth14d/+23/LBnl4ThAqzVet7Yjn4b3vfe9v/uZvvuMd72i5itQZGxtDACAkmi+dX6YpZoSWoD5DtS2fX63lDPUZFe4RK0W4iwJChQLTtDPFVcJJK7rYLOVjH/sY80UC2avNHXHm+9//Pq4hNNJ//s//GddQS3d6KwIiIAIiIAIiIAIiIAKrkECrOLE2tPV1WKv6gx/8IKFWHHgJbrzxRixpgpcocNVWZpVSoqr+5m/+5ic/+QkWP6rjZS97GauU2iwR6qAZcMV86lOfwmT/7ne/i1eERqhAUFNGnBAptA3tYN8TA/a6173u9ttvz64SFvWVr3wFg55Qsb/4i79Agfzqr/6q7d0OkgFzoz2yu2Yq2HSRC6xMI6QOs20f/SKZWHb205/+NN2x4CyuD2K0GIAdA/tF2CFxC3PhYNjEsP3Gb/yGDUvjqq38oQ996Bvf+AY6jRA4nC2EorFo0kyj1XkREAEREAEREAEREAERWCUEWsWJnXZmZPOW2CQcKSw/ynHllVcSlIWoIEM90wb4OhAeP/jBD7DdkSWvetWrkC6ELWXiBBlA+gomOGY9q7UiUai/cePGFnFChJV1mLz+9a9n+wViyazRT0ckwKBYEEhEjiFvSFz55V/+ZeujaB6qrf+8T+5ib0HMMN+f/dmfpWXGwCxogV0ybrvttltuuSXrzi5/xBiYBduhoKNQJsyC2C22Q8kybahATeQNcguPEzsAQgZhk7WjggiIgAiIgAiIgAiIgAisTgLTixPLAjMaKxxnCBY2aoE8E/QGVjWqILPviYy65557/vZv/5ZAL4xsqr3tbW+jGgeNZNXwMLCrHf6BZ599FjHzuc99Ds/Jtddea5dwpSbulAcffJD6dMrO64R+YcFTto1g3HPy61//OnFQ7G9NrBRBVmTGN+sTW5lXjqxfO5G5v9KRTXSx86ILu9sJkqOlL5QYxDjwFyHAUGv4WDLHiK0MSSLE2FKDdj784Q8j5CRO5v6M1IIIiIAIiIAIiIAIiMBKJ+DNPgGrFjCmiT7Cf4ItjnVu9Ym9kTWs7rrrLkxt3pLvToo5i/OiK3jbbLVzC/fiavj3//7fc4n0DBwgBHHZRnjFlMfhgGXPXaS7ZC3YRrgdTwWyB4VDZbvLdXN6CdVszayQtXx+wciXyWwZe9f5dWY5Y29hwNQ5/3amQHKOdQEhvbZu3cp0mkdF15yBEg4ZDmYBjVm606WLIpA92WnvMg8+Paa9qpMiIAIiIAIiIAIiIAJLS2A2zwkjw9RGD7CUsPVjnG+LkzvBXtrU5NKrX/1qvAS2zvk1OUM7WfI3NxIkhmPB1kTz0AVmOqYjagdPy1VXXdWMhiWJyULhPE4JZJI1+psrLIcyg8fHQgwY8oPxEMBGxg7DRorw1s7UvjJxCFhDmbksh8G3xxjAC3Y8bKz5hqYlpo5XnHL461CMfMbwU73yla+EuX0Q7TFrzUIEREAEREAEREAE2oPA84gTJknwFda2DaA6f84sOUVWN+cx9aiGhDi/TnYG0zBbt5fsERbbzS6x38i//Jf/8o//+I85QzIGO4TQL8FdqBEbT4WTAW1DfBR6icHwdqYhZW0ufgEIjIppMlSGjUOJ5ctYHJmE+Jtvvnnv3r3ZmO1c7AiZy+IPtY17BDtJSiRBWV8fipdMIT6lCGBEIwViEfmw4crLHkcb09DUREAEREAEREAERGAFEXh+s3jPnj0kk8w0JVJNCHDCKOf4zne+c+jQIWpSnqk+X2DbS2gMGxmF94AzSBEWv2IBK77zZtUvFu8i8x4T87rrrkPP4Hlg926ECvblTC0vq/M4RjCCCV0jQ+ZP//RPmQtZ/uTVYA0jRfjannSU2YXcsprOyhoMrhIg84o+JOwQHYiPDmWIR4XHwScQucKaDRyol5U1NY1WBERABERABERABNqbwPOIE2QGkVq9vb1QQEW0qA6rK+wlxAYbDmIR2mrUpMDRgs8KkuykrYDJjuq4+uqrf+u3fouvvTEfWZ6YVxwptMNVVvIlIZ7lgzE3yYPHpjy/5azNpS1YRG9/+9uZEWVmgSZhJeX/9b/+11/91V9xhkSUX/u1X3vNa16DYmEu2ff3zMjeu7Tjb4PewWj1iXVJsfQCSVN8hv/yL/+SWC8UL58uVr7GnSVx0gaPW1MQAREQAREQARFoJwLPI06wmLHzbPTL+aYzZ+xJXqlp0+IvkE56qxEeWX08CXyZzepVeE4++tGPsgJY1uADDzzANvB/93d/R1o8GzVi+tsebe90jebhNWtq9sKF15y9nZmuMipcPW9+85tf/vKXk7v/3/7bf/va176GQcwX9lxiK8k/+ZM/YasTFNf73ve+ffv2IVFoys5lpjZ1/mIJoJZZbIBwQZbAZrU3PsaEcuHOQijyqePVbiR6sc2qvgiIgAiIgAiIgAiIwMIReB5xcoEdY1jzLTXJFQQscQtvMQ1b7s2M76zAZo7UsVKBk5iMZGusXbuWzUPYyREFwlVsehLuWXWXAmY9+6Vg2ZOR8q/+1b/ilkxmNIucln5b3nILt7MYccv5+X3L2Gw0Gl/Yo0De/e53YygjVO688042Z2QdZFb0IuXmD/7gD/7Tf/pPpGhnSyrP7zBWc2t8AhG3RCQiaPlw8twRgTwXNAmv1Wr1/I/oasaluYuACIiACIiACIjAciAwV3Fi5QGvHGzWQerIhc+KL7ObK9MCb7Ej2W8RO3L37t28RUUgVJArbJDyiU98gm++f/SjH5F/wpaIyBhawNAkgIozmPvWf0I7nGxuuaVsnRgtJ+f9LXqJgxHCxA6MuSDeeEsB7xAqhSgjFBpZ2qT+z/sAVnmDfAxwVcHWxtdBg08FD4KDgpTJKv94aPoiIAIiIAIiIALLk8CcxAn2H6qARbpYest+Uc0kSaKYaaoY5agLFvjiRsL9URfZJvFk0nMJUxLnCSe5ik1JO7wlZ+BFL3oRfgYM/Y997GM4Tw4fPnzfffexa4pdope7WKGYQB28E0gUrjIqhMFMw+ALdbsPyUwV5nIeg5isBrsJIxKLhZiZiJ0LZJgIy3bBihC1z3/+83yLz4zY45LzdDq7pprLqFbnveiQFqqQ51idNDRrERABERABERABEVj+BGa04C9k6BjTxPS/4hWvoDJ6g63iEQYUOOwZW85eH3/88f/9v//3G9Pjd37nd1jMimrWImf54Pe+973//b//dxLHSS+xvXMjGgN9ggghffy3f/u3WbyL+mihu+++GyliWyZL/vrrr7fJzY8++ug//uM/zqQ9sFYRSPOSbICNS+92nM2vrAfF3ia/93u/x/IA5M+gVewg7UxRKcyFiC/iuCgwF2Zhx2M5NDel8hwJNCOlbN/aBzfts5tjd7pdBERABERABERABERgjgTmJE7oGz8ABwWsPbJB0CeUrRWYWoMmvMoWeEU5fOQjH8G5gULAH8LuhFnN06dPE6/1hS98AU+CVThZOxTsYZ0hdEToF1KEt7ZlXDe/8iu/greEaqxB/OlPf7pZfjSboXhXyIp+5JFHJpucyHjJ3lKwQ6LAjc33ZnU4iYFLAklzL9lV9A8uILQTCyuTKvPxj38cL0pzm7YmooUUGpo6/1LWlApzIWDB8mqeYpOMtB+bubSse0VABERABERABERABBaIwFzFCU4AEkJY5JfxEXDFaq1s64FEyXwX1jok/xg3wvvf/34bAIYbZPPmzXaVKjsxQp5wgKBbqPAXf/EXeD9aJowY+C//5b+QqsF54r5YgoloLlsHdwR5z0gUfCwY/WwwT5Y5Y8gW+7LVUAu///u/z8JZqAV7JhMG9u2Fv2LsMh7ayaaZ3cuk3vnOd7K3BlfZZAOt9f3vfx/plVXgXtYXZs8NG19k7WZGcsmDyVpWwRLgwwZwJCKhgBTwTWVkYI5rixhC8o5s0Fd2SQUREAEREAEREAEREIElJzCnnBNGj0lNvsdb3vKWBx98EK/FN7/5TVJKcFAQf4V/w04P+xvNwNLArFVFfVZPwnxnX7zME0I16rMZBeqF8pe+9CVkBuajvd2+IlpQPqgXNMzWrVt37dpFHXuJNunr53/+5637hRupSYIKG6fYBBgqYJWSfU5KPYNh5xYsV5bMam4/K1u1wFvu4sjO2wK6iCWA2XEckxfHCAt/0ZG9ROoIlxgeq2+xiDBd7N+/H0WESwcpQpY/1RgGbSJOvvWtb9mOfuEXfuGaa65p6UVv50KADxiPAN0Iaj5XPT092XNkzQY+NjwjHoRWSJsLZN0rAiIgAiIgAiIgAgtBYHpxgmHHYftDV8z+HTNmN5t14Dz54he/SGjWQw89RG6JFR7NI8aaZycTNAma4V3vehdbT9ir2OjYjsSGYS+ynwmhXyMjI6xkRYhX8+1c5Rtxornoi8pYlpnFSQt0h+BBuqBPSFmh5p//+Z8jG7I63M7BXZitLO+LdwVxkumQ5o6yUTHx8ysgJF73utchonCM/J//838yZUJHf/3Xf43soYAnh/3gGcNnP/tZdBqRbPhPbDQRY6ACPMGL5+eGG24g04ZX21E22vPHozMXToDdFVlrAX0IT5548woNPJdXv/rVkB9jleHBwQtvUzVFQAREQAREQAREQAQWgcD04oScEA5sOw4bvzSL9UwdbMH3vOc9b3jDG4ibwmuRiZmWu9gW/d/8m3+DfU8uuDXrqYDVzisGPd9qf/KTn/zN3/xNPCd4JGjE3p5RoKNXvepV//Sf/lPW6eISb7NLvOXr8F//9V/fuHEjuzRye3Mwj61GBNorX/lKdp3/D//hPxDbw+32yBqxBasiEA8E/5yfVbJ3714GhueE8DDUS/O93EKD9gwSCPcOSuyf//N/bqs1z8VW40t9NBgBYJmLqbk1lS+NAJx5gsjgdL0BohanfE4GBgZZxICn1JOYVx0iIAIiIAIiIAIiIALLisC5fQybh4Xvgq/8cUEgIdhvhMAkTL3mCueXMQox5Z955hnCmRAG3P7jH/+YMsY3SSn4Sfi6mngbNi1BJFgB0NIILXAjoVDWAUJThIGxvQn12RuERvB40BqBVRRooeV23uKXQJZwI3qA9Xzx4TAMTiIVCLjCw8ONO3bswDlDNdQXjSBX0EXNTZEiQgiZXUoLF41dBCyrQGsMj8Z5ZcD2QK6Q3Y7oYuFgW5Pz0KAXZAxlkk9Y+5i5IGBQLASAURMDes+ePSiTTNJkvagwLwSMDjmvIRYSztYStgF51OEZNT2Fae87ryGdEAEREAEREAEREAERmG8C04sTbDWikjiw2DDTMd+bTLfZhoDxjaXOK/4WLHhMdkxw0t8RBugcxMDstjj9cjsCAHVBgBbSguAresczgzXPSGjEtjPTILjXtsCNSCMaoU02OkTVEN7DAGgNCUQdxAPjPF/noDq4SjVutD0298VJDnrhoGAvUYAVrhsEWHNl2qELzrD+2JEjRxgSZ0jcZy70C9Isbab5LpXni8D5IgNZwvMwu5+gWxLHdx30iXGvTBEn1JpG+s7XqNSOCIiACIiACIiACIjATASmFye2NhabNdouUJk094EVzsEZ7m0RJLRpzzfXby7bCrzSAhqAS8+rappvt+VUPhj9wGH1TPMsOJnd0nyek7Ncym45v0B3tNPSVFaNq81zseOho5nqZzeqMBcC54uThuOcHGocPDZy+uwQO+i44fi63sJVOzbycWiK8pI4mQt13SsCIiACIiACIiACl06gNeckM81TS9sExWQG9EUZ08gJTPDzx3Uhjdge7QCae5/l3vMvMQAOBsAlO4zz62SNN49z2pPNFWybWTXbPm+zM+dXbhnMTDVbbtTbORJoienicxAlzv6jY//w9QPfvevhcnmgPvzsK2/u271jY1P41znVOsfedbsIiIAIiIAIiIAIiMDFEmgVJ9jNmRGfFWyjF2hSW2M9G0dLI/b8tCe5NNN5LtmBzXR787BtnezVDrt5VC3l8+dFBQ7On3/JNtt8nrKtnPXYXGi51HJjc02VF4DAOd8JJX5i16nHwUitfGyo0JGUq0Pu2bE4JL6Lvl3+Z2vxBucJ0qZF3SzAANWkCIiACIiACIiACIhAE4FWccKlzIDOCk31n7/Ycte0b1tOZo22nJ/pbct5e/u0J6dtublmc7m58rTnswothVkqz3KppRG9nXcCU2K10tYRH1Hi1ZLA8ctersP1SolNL5lQJnYI1JIsmfenoQZFQAREQAREQARE4PkJKPH3+RmpRtsQQHaEidsw4qTo+oXECxLXQ4lMahGuc0y+a5tpayIiIAIiIAIiIAIisEIITOM5WSEj1zBF4FIIxIkbxQiSXOz6ceuqXM2ypLl8KR3pHhEQAREQAREQAREQgYslIHFyscRUfwUTIJUkTpwo9h2PT/7Egg3eRBiX1MgKfrIaugiIgAiIgAiIQHsQUFhXezxHzWJ6AjZOq/kaC3aF5MW7XsRCBiaCS5qkGY/KIiACIiACIiACIrCUBOQ5WUr66nsRCCRmDS7+c3GbRLETRS4/qdsEzwlLrTVtcLIIo1EXIiACIiACIiACIiACMxOQOJmZja60CwHUCcqEV3wl7OoZxUgSfIbn3CYT3pPMzyJvSrs8es1DBERABERABERgZRFQWNfKel4a7aUTMLtxekaiRCTFG3Fij8lCpkw43VyerKffIiACIiACIiACIiACC01AnpOFJqz2l5zAOT+IZ4pJHMfBOXGy5MPTAERABERABERABERABCYITH5tLCAi0F4Eznd+4DnhZJIkMf8hU85plvaauWYjAiIgAiIgAiIgAiuWgMTJin10GvjzEWjSJ6ZoM9/DKKrVGrwxmy/qEAEREAEREAEREAERWE4EJE6W09PQWOabQKpPJkSKFSfEdNXDULpkvkmrPREQAREQAREQARGYBwISJ/MAUU2IgAiIgAiIgAiIgAiIgAjMnYAS4ufOUC0sUwLTukfSNYWnvbJMZ6FhiYAIiIAIiIAIiMDqISDPyep51qtrpk36g3gu847orvSH3Ri92DV7MrYeE/Ff2jW+FYzei4AIiIAIiIAIiMDiEJA4WRzO6mXJCFiVwgcd6YEgiSM2ifdyQYHdGF3f9wM/ZhWv2OzPaI7JV7u0V9OptKgXERABERABERABERCBhSSgsK6FpKu2l44A6gIpMuE/cU05SsVJlLhx5PleLkycXJDz83kESZL6ViYcJ+lbM3Des5X80k1BPYuACIiACIiACIjAaiMgcbLanviqmG8YxbV6FLk+0sJzE9wmkes2XKfhenHiu24ujOpeEPhB3vdznpfuGc+u8SkbJAmKBFcKN1OVc2yL4k5ctIplVTDUJEVABERABERABERg8QlInCw+c/W4sARQFwePnP3BPQfd/LrAT3J+Evip1Cj4QUfHkeMJ25x4bs5LPN8volVOjSTjo1FAiFeqQGLXuExq9Vq55Pb1FPgLOadMFnbgal0EREAEREAEREAEVjsBiZPV/glow/knTiN0jjwX3vPoE0kSFXNJDiXiO/W47pfXHB/qqjVyhXzOiA6v+OjTJ97/kW+dPTuCnwRPCbIkNqFcNd+p3nLTjlfctu88PlRRqNd5VHRCBERABERABERABOaDgMTJfFBUG8uJAOqh0lFav7nvp1943PODzkq+kPdiL642kjioV93Y9Xy8JgRuRX7lyNmR4Z+cGhkb9x2XzPiIEC4nDquH9141QNAX02rVIm7rieU0dY1FBERABERABERABFY2AYmTlf38NPpmAkZZEJrlOj29xV1XrY2CY16+wyt1OvnAccN8vlGnlBQiJ0dyvEkk8Tvqjjvm9ASdrseNcRLFURQ3atXq3htv3H3VjubGVRYBERABERABERABEVhoAhInC01Y7S8eAZJD8GuYw3PyeX/T+t6h8XwjyTcaudjNuR6yxAtdHwljDpP1XqglfuJ2+NzAylxeErphLRpO3OLAQJmEk7SeXkRABERABERABERABBaJgPY5WSTQ6mYxCeAF6agEr3/15u7O0UY0EpBzYpYSZu9FCq7j4SbxfOMs8T0XfY4jJYeGqSdBNYzHGrXtW9d1d1TMUl/KL1nMx6a+REAEREAEREAEVj0BiZNV/xFoRwA+aSdF99a9xY7S0Eh1qBazqjAeknO7whtHycTEUSx+7AaxQ+iX24jqY9WzL/uZ7ZvWd5m/jQlHTDsy0pxEQAREQAREQAREYPkRkDhZfs9EI5obAVQHP0XP2bzW6e0kD6U+Vq8n3oQYYaFgP2G54IjdTdK9Ge1Gi+ZqEoduMlrMje25qr+vt8Sp6f48JtqZ2xh1twiIgAiIgAiIgAiIwDQEprO+pqmmUyKwMgggHfjBc5JznVLiXL6+t7urNFKtRzFrcXGwISMeFKNM+PHd2DPelMRNeNuIo9FCML5rc6mr4gUeOzCyHUo2a+62bpRzp7JrKoiACIiACIiACIiACMwLAYmTecGoRpYXAatPCp5z8w07d29dH6I7QnYvIWGeA+nCq4dGSZf2MhvIx6wv7MZRY3hNR/SGl+0e6MznqLS85qTRiIAIiIAIiIAIiED7E9BqXe3/jFfhDNEVyG48Hdsv8zYMJI3xyOkmFR6HysSBuyRisS58LCTFs8ZXEtU4qmcHO+u37e3tyPkmcV7qZBKXfouACIiACIiACIjA4hCQOFkczuplsQmgLPjpLDtre/PrenCihDEukiyLJFUe5KOQd8KB7yRK6h3lZONAfmNvgIiRS3GxH5j6EwEREAEREAEREAHZYPoMtDEBNAbi+7L1pWuvKIa1M3HccAjgssFcSeyx3QnqJCY7PomdMApHL9vQsXvn+rznBGSbtDEXTU0EREAEREAEREAElisB2WDL9cloXHMmgFMEpbFza2HfNe7pM/sb0bjjRSSToD2cJApIgo9CXCYeufJRdbx6Zse27pv2budPwoR/pR6VOQ9BDYiACIiACIiACIiACFwEAYV1XQQsVV1BBKy4YMWtdX3O5RvYv+RkFNXCMMfKXIHr59mWEWcJefGOizYJ6yOdpfpgr9PXaZwtJnd+BU1VQxUBERABERABERCBdiEgz0m7PEnNo4VA4sSx8YGUfKe/K79r65paWKs1GlESR0Z9eDELBZMK7xrHSaM2cvna4rq+fBCYNHm7ZnBLe3orAiIgAiIgAiIgAiKw0AQkThaasNpfIgKp74MXkkz6e8q3vXB7ISCzhP1MzApdUWS3PfHwnLD5olMfvvmq3u2bu4n4MuKEbJQlGrW6FQEREAEREAEREIHVTEDiZDU//TafO8qDreA5BnpKL3nBxrIJ5UJ2uJ7rhTH+EhcFYjLikzDv1a/f3bd1QydhYByRSZU3BR0iIAIiIAIiIAIiIAKLSUDiZDFpq6/FI4C4MPuYpJntxYKzfjBxGmSdRCgPz/F812cjExwptbCeJPU1PYXunEsAGPvKI1nMLvKLN1L1JAIiIAIiIAIiIAIiMEFA4kQfhTYnYCK7HKfo+y+6bsv67lzcqMUEdeE3YaHhnOcmdT8efeMrblw/2IMySf8ecLcYn0qbc9H0REAEREAEREAERGD5EZA4WX7PRCOaJwLIDxLi7U85cG9/QWVj/2hj/EwSRUaaEN5FmFc4XPTPXn91R3dX4HGSIyFP3uyGMk+jUDMiIAIiIAIiIAIiIAIXSkBLCV8oKdVbWQSMtsD5kUoMJHgxcK7d6Q92jkb1kGiuwPdDckvCasEb3dAXrl+TEPqV7hrPLelvaZOV9bw1WhEQAREQAREQgbYgIM9JWzxGTeJ8AjYyKw3O4lNOyFZfh9nGpJhL4pANTtjeJAprQwOd9X1X9xXzHtnz9kCVTKiU89vUGREQAREQAREQAREQgYUkMGmRLWQfalsElpIAme+JCe7Kec7Vu7buuHzDaJUk+IggrvHR05vXxD/3ut2VovlDsFkmUiZL+bDUtwiIgAiIgAiIwOomIHGyup9/28/eCg7H8ViDK3GuvrL7yp0dYRiTER81qh3FaF2vv7bTK6RZJpN1lQvf9h8LTVAEREAEREAERGCZElDOyTJ9MBrWXAm0JI2kGe4DA7neXr/aCOthrV4f37q2a+umjoKv5Pe5wtb9IiACIiACIiACIjAvBCRO5gWjGlmWBKw+SR0iJpOEtPic09cdrOvLV2vD/Oy8vP/KHYMEfbHlolmqy9Y/93tZTkqDEgEREAEREAEREIH2JaCwrvZ9tqt7ZkiSLEzLig6EOGkn2zZ33n5zb1I7kkSnrtjq79jeYQR6uu2JrTapUFY3Ps1eBERABERABERABJaCgMTJUlBXnwtPAI0xITPSki3nXefKTc7Lbxw7c+xH63vHezpc5AqX8r7Lcl52RxSGZoXN1Ff8K/xMe0knL5TA+Y8dr9X5J+0jmPa8ToqACIiACIiACLQ3AYmT9n6+mt05AogQ5EdX3ukv1/zqUy/cM7hlXVcuve6nGSn8MVgNY1/P3anSAhKYRpxMc2oBB6CmRUAEREAEREAElhEBiZNl9DCahiLzrAnG/BVZsAsPSXcp94Kr1rz0xnWXr6kEOExSZdIiSFrezt8QVm9LMyCd5jSnpjm7eslp5iIgAiIgAiKwiggoIX4ZPmwpkwV5KEmSIEOwevu7Km993Uv27ezv7wr4A5hJoMs+XpDHMLXRVBhOPaV3IiACIiACIiACq5iAi8W2iqevqa8uAkma+B4nSXW8XizlXdcIk/TFcuBvIftz0Nf3C/PZALBk38KgVasiIAIiIAIi0AYEJE6W8iGa7/KbNyTPbGNrGE/YyZm5vJRDXbF9NxvC6ZrBJq/dTeLY9czqweYwvyzkFtTN96Y19TI/BNwJ3gAW4/lBqlZEQAREQAREoE0ISJwsgweJSWx/Ivtr0mKbcGq1WMzLYMArYAgZtMz+nWRrBt9iEWeVV8DEVuoQDfIMO+LExHMlXqrNM32eXV+pk9S4RUAEREAEREAE5kpAOSdzJXjp92cmcRTXh0eGDh2Nh0aTKDJKhegjjDe+3r/01nWnhYfBm9m8zfpkej5p/gk3eiI/PaBLPeuadZg5bIKPh+5287lcV0f32kG3kxWdA5MNZKtkj+tS+9J9IiACIiACIiACK5eAxMkSPbvUTsZEGzl5sj42Nnrg8KHv/ijZf9ip15I4wpAzIUdJmA6u2bxeotGuvG5n1yHm6qQl3IyXczE2MvhTSSMzeb4efJxuEkNrVoH4RNU5lXJp68Yt+653128orx0sdnWaD/1kqN18dax2REAEREAEREAEVhYBhXUtxfOytjFBXJHzmT/9s/0PPFSJ4o2xt6YRBXFi7GKzqlSC58TRF/gL8HxAjHPKNmxIYyjbg5WGzbf3xnNiRMo5l8sCDGJVNYkjKg3jmpR84A3GvOSUE54KnCEnueUtP3/d7S93OkpOwMefR2Bq6xABERABERABEViFBCROluKh89V8FI8fOfHQhz9x9OHHklqtEuS6HbcjdnzCXSZHxJfMWXnynH7PA4FUghA+Z470u/oMs1Um9gobNuqYLwITtNPmjPrmL6DuOuNeMpIkI2Gt0Nu34aa9u157u7NuwPH9zM2SypT5GoPaEQEREAEREAERWAEEFNa1FA8pcU4/e+jZO74z+qN7Bjy/kM8X3SDvODnMtqZjIkr/3JmJSKRzJ1ZCaY7fgbPA1gXOMlUYmcywN81CLGM95ZbJvAd6nXL+AsewaqtNB78ZBnqj6S1OwYRkePOBLyVJt++OHj914gd31X33yre+MddRMVWb6zfdqqIIiIAIiIAIiEB7E5A4WfTnmxrbpw8cfPxr39gaJ5V8UOS74tQWPk+NTBkbVTLTecqF5f1mMY3Mlr5m/d69pW4GceL8TJezeiq0EJiVWOsnl1W6OEW0V+B6BY/c+Pzxk6ce+tadm190S9eWDV4hbz7sOkRABERABERABFYfAYmTRX7mxmCOG1F1dHz87HCpqz/veR7bAJodOMwG5u13XLjrY+5zX8y+5j7aNmvhEuCbhJ+UQiGXK7lRrtY48eDDhc6OIkt4pWsNt+MfRJs9dk1HBERABERABOaZQBbcMs/tqrlpCBBkFJtsk9NPPD38xFMVP/D5/nhyHSNj211oBNM0beuUCKxEAsgPHIa+51Vy+UriPPytO4eOHHPDNEdFfw4r8YlqzCIgAiIgAiIwNwISJ3Pjd3F3G0sMfVI/esw9cqzb8/KpWZZuRMeFOWZnXNxQlqp2+mU535ef+1mqkajfZUDACHLzVxE7ecfvdnNnH9tfPzPsIE5mSRdaBuPWEERABERABERABBaIgMK6FgjsTM0aceKNjBZGx2LX992JPbKNz2RVhrAs4Zfj8F7C3mf6fKy286gTo1OThJR5kq/cU6PJWN1pxE4B4b4q/yRW2ydA8xUBERABERCBqQQkTqbyWIR3SRKEcT6MIpMUbOwvz+SaJM2LrS7CKJaqi0WOXZvFvDV5PnBvTdVeKjCrt1/CusxfgcM62kk+TvwoJvQxfTarVLGv3o+CZi4CIiACIiACjiNxsrifAqwwJEnimiR4E8c1EVbHPoAeey7OYkov7jDbozezp2LT0ULXrI1mvrM3ZrDIN3FasqLH/vCIdAV0LdkTUMciIAIiIAIisPQEJE4W9xmY7+qNo8QYyqtg93dj95tlyJgzioxJmyUBUjkwwcBDlHFMfkWeujG46dxhQM18TKk6Wc1mMfAuTKYgNv1MGr6skcYmi02NZxvGG7lyyVrFeGNmcMU0KaV0EQSjjfjhl3nLnvUeW3+YM5fe+ySAFfk7/QywAcqKHLwGLQIiIAIiIAIiMF8EJE7mi+QFtpNa5liwWMmYogmrd2Gb8o2xMWrb50hNTKbaiKIwThpO3EgSCgiCOIqiOE4t81SVuMZ5hOEe1ht5NqPM5XKB77FHeCphUipWvJxTEtzLLUCDmMGXcjPVzYGdz1JPUUjRc+sh3Ro5YoaDPqJobjOYyXAIooTV0gqFfKlcimNaihkLPzwWM0LPlM0w0sP+oivr6pqQMmlj2XPjkpE/M6hOHrF50txiSh4IqrVqFCdxkB+t1kq+U4yTgDEEgZcLjGya/EDQbCp4JkZix6NXERABERABERABEWhLAhIni/xYUxMzNXmtUZ0a3ZMG9CKPZSG7S1VBUo+ifE93YbA/7OpouF5A1E4UJXFqpOOeSIWFUSCJG9ZqxSiqnTw9dOZ0LokKXpBuKj5h+afOlemGm4oBc8FY82B0kSNBZ0elr88Z6K1HDc6kxMlhQMoQMsRbCk6AHycMg7GxZHhkdGQ4rFdzRhSwJWCqSahpWmSEE51O/p5ozkoUrmU+FlM77czUpAfXKC57pNLCKJP0Ljema9+P47AWRm5vb9fOHW6tUeKmw4fiI4c9MsPPHRPdGlmVzfTcVZVEQAREQAREQAREoN0ISJws1hPFVJ20Vlu6NFcy47fl2sp9izGdOLUk6V23vvfmG/NXbncKOYPACJMJ99G5yVkyJ08evu++Z39879hzJ3typSL6BFcGtY12Mxa/fTEOitSDQUs2UsveTaQWl0Yb9a41gwP7bsjtuZLtM9K7muAa1mkDFFiv9rljZx559Jl77h0/dLbHwWXDRd8soGZa4rANp8X0JWtocizEYp3TJ1SxFXjlfFaZZlKVYx6yadHMyWlEcT1Jui7bvOkNr3XygVNrnPn6N4ePP4fXqLVX2yzMzrWYjkYvIiACIiACIiACItB2BCRO2u6RLvWEjCFuzejEqSbu6UaYzwf53h6nHDi5nLHlCaFycE1gbuPQSK147HV+NvSu27Yhd8XmB/7qb+vj9ZyXBEGO7flSL4aRAbRr/SBmiqlrgqiozKmCnsDZMt5onI3DUt7v6el0yvl0yQFOp1KJvowHxRj/JsIq5zkberp3btm596oH/+ZD9aPPBWHDD3KkwXCYLJl0IkijKUpjAq/JoWEKzMEKoLTZ5tFN+FjSkdp8G9M1fafdu5HnjzZCfEROZ9H8jIeNwB0fHyv6HR4iydw2UZeR2gHwmjlqJkahXyIgAiIgAiIgAiLQXgTsN8TtNSfNZnkQwLhuOEnNcyKER+A6OTJO0lViw4joLlM2djpWODrDCAvUgtdV6tm969pf/SWvUkYV2HSTIHWJZHNCFGCjc2vqgzFOGFRC+mOqhygiN6mzRDPuiLyfOk/S2kZLeLx1/YC8DqfoOwXPqeTd3o7i9i273vWOwvq1YUiuilE7Rp2kIWdGfDTFbmVjyAooE9rNDjox/aSHLTAHI3PQJCaazLRGm1Ec8ZYknDoQ3MiMsxgkgW/mZdLizXTMLZM/dr6cRJ/oEAEREAEREAEREIE2JiDPSRs/3KWfmsn4Z4lkY24bI5/1s45+7+6RZ55l+0k/CEgBIfW8ETj+QMe2fTcE3d2O7+d6Ont27ThWqbi1EJ1g5mAseUx5ktaNbU6ae5TqlsCnDZI3IqSET0yWxw4Z7B6DMyLNuMeQ5ydKjt5938mfPFTpqCTGCWMyPpJcUC/ntu7dUxnsd8g1qRS6dm4/1tVBnJVxxSQR6gnVYPrjP1RErW7uS9PvGSC94l3xTd6+l1CTWqkLJSS9PRUP6aCN3yVsIEDMKc4EZLTgEwl8GooaYeJ76Y0IDlbQNbrJaDV2+WDKtMkgzGDMwe1mgkgmsy2OIZJ2wmkdIiACIiACIiACItBuBCRO2u2JLrP54BlIf7CoUQ1hcuZH95745nfyhUKukG8kMUpjNOc0NvYjXTbtvaFMIjv2d4F1u9gufBipgGsCWcIKX/UYg97NVcpBuQdj3QlDp1qt1mpRrV7I5RAK3GhcEyScpy4HRJHxVUTJmXt/+uz7Pz64ZYOby9WRL65Tz/mnOnJeWN98897ODWuNdCgExUolzgcxC335fq1eD8nRRwL5XrmzM+gsoguoFrP6WD2M6DpqIDIKfsFIrxiFhRDygnKxgUuE97VGvVbzczm/XAzKZVRFPDZaqzXGoxr+EcRNjIvGy6WyIxUnKDe7jjD7fPg+PbC+WZzDw5Nj5gEKDEcO0qfeMMsE6BABERABERABERCB9iUgcdK+z3a5zAwjnNCr9DWKO4hcwmwP8iyOhVEf5vyCFx86MfTlD3/yTf1rLuvuMW4GLPO8ERJmoxI/qMbxSL2Goij0d3du27zuyt1+pdIYHh56ev+zjz3WONWIcKU4NYSFj0SZOCbzO+K4I3HX+rnBXNEr5lgxqxbGQ1FjaDMOnSkAAEAASURBVKR6zx13+oMDu9atMeIkcbp6e+NyR2N0BJfFSKNWyxecYr7U29Wzc0dHT4/f0cFIwpHx0wcOnj1ybPzkKXesGjUaBZRMHDXQU10dfdu3jDdqrIl89vjJkwcPl3t6Lt+9q2fzFjcfjB4+ePjp/eS7J6O1UqPR4bM2wORhXSHoLQSW7+MGOtsYjyvl8pr+Yl8PQqhUKhVq9caJk2PHTyRukLpN0pfJBvRbBERABERABERABNqGgMRJ2zzKZT8Rtg1BogQey2K55J+Q6554gZPgHUBXdOUqAU4NfB++cUbgmjBJ8iaaK3yuVkt6u7fc/uJ1+/Z4XWWvVEZO5MKo98arO8dvTw4dP/iFr599+PFiLuju6qQHrP2Jw+yhYux4zqCJGuM1UuyJkyJkiuCwfOj7LDXciExmvOsODw1Xx6qUxqs1kvg33bxvzY3XFzZvCCplM1rTlOPHSX/jht5ao/boU6d/ePeh+x5Y09kx7sR+f1/Xddd0vOiWSt5LzgwXnt7vHz685YW3Fvq6vGKBXP+OaPf2eiM+efrwd3905Js/sOLEjMqqDBr3TfxWrRYOB2PH6rVrfv7162641q0UjR/J80595/sjJ46ZhBSrZCbnp98iIAIiIAIiIAIi0GYEJE7a7IEux+lMqAXSJXznZG3s6MipfFgK8nmyKjC9x1230VV+8Rte3z+4xqR1GBXgEu9lcsMdEk+ioSTc/crb1uy9Or+uzySyG51g5ISXVHJR6HZ0rosSr6Ny5t77UxFipYhpxNT0k3EvOUFQWG28Wq/HRhDlaq5X9b0bXnDL+o0b0xAwU3l8eJRUED+fHx8bL65b13nNVZXdO73ODpPKTyUzMCMUzP8ix8sXxthD8eGHieJquHHoO+O4ggZ6GZHb293d31Mc3VEc7CcqjJwW8t0JyzK57H09xWPHC/c/4g43Uia8MBezCBkFkuOHatXxcuGqn33dwPXX5Ig3K+bInX/0a18/88BP82fO9p3zCy3Hp6wxiYAIiIAIiIAIiMDcCUiczJ2hWpiVQGqGmxoUcm7fDbvdjkKQL5i8Eax91wvZXaRUueym64NuQqe8ZGw8OnAgGR1DEjTiJMwFl11/3dobri5irPtJfWRo//0PJsM1jP7y+rWbrt7l9HZVrt5ZOXXq7JNP1MbGWZ7YLNjL/0zjrNaVdO2+YsPbXkeQVZ18Evaod1kUyxvM+ZtvuqG8ZtDkozdC58gpd2ScdbPQM26lvOHmmzq3b3N7upOwUT945OizB+qjYyaZnpWHX3ALAsYb7A0u31Aa6I3Ojpisd/MfHhjfZS+XvNnlHv/Pkz/8kYevplQoXbZxw57dxinUme+8bPPgru2jd/zYzXWZlHkjTghFo5iMNhq1Un7Dvms3vOAmo0zKhdr42LH7Hzj2g7uSQ0dKEWFlhVlB66IIiIAIiIAIiIAIrHgCEicr/hGugAlghJsfYrrczS+5efOtN7Eql1lb17oCcCngOiDV2/dD/BsHDoz+4EdetYpXpRrWo3Lpmpff5q7tZ9OS6pnTRx548Cd/9zn/yKkon++58ZrutYOVwTVeb6W4ZV3n5Rurd/3UyZNUbvLLXbMnCF24a/fuWXvVziSfM1srIk7SPHmjSQp5pEFUq9aOHq3f/VN/aNTx2eTEz5eK5XXrxjkOHnbGhs/c/eNH775n7PjJkTCMtm7edsP1fiXPOsW5zkplTb9zmgSWBvs5pm4eOkRsJNXRkeceeuChT322eHq0USn2vnjf+l1XsDwZw+lYu8bdteu5z3y10tWBeEo3ZCRcyzzDuJwv79y64xW3+ZvWOZVSdXT0uUcfe/RzXygefq7bcTtyeVM/PdLqtqhXERABERABERABEWgrAhInbfU4l/FkMKzRBpHTUUxtcXwFNkArNc1ZlovVdZNk6JkDR+648+i3f7ij2OmyblUcmR1LNm1wSjn0xqGnnvr6hz9eOV1dkwRDI7Vjjzzx0J3fve41ryp2dHRetiF34/VPfe/uJMjTfmrFE4vFQmH4K0pOV9lY9pSNeCCzheV6nYQVuWrh6LMHD377u8e+c9fG0OmslEPPHR8ZffjTnztZyfuVYikKjz76cCmXT1hrqzo2dvoUvpSEgQM6cP1SscHKXSy0NSkbzIXEOfbkk3d/7JOdo43BfOnEWG388PHw+Inc2jTzvlRyBvo93DtGJKEyrNAwwWzrd+3oH+wPrtzukGqSuEcefuTBz/x99PSBdYVyV5BnEWH4ZPpkGT9oDU0EREAEREAEREAELp2AxMmls9OdF0nAmPTmML9NTJcppfZ5dXjk/o9+8swz+70zZ8vjtX4XN0GuigPED7xSycWpkoqKIHS6Gm53V08xYkuTMPbzp/cficbqTiV2OzqStWvrY6MxWytOxHUlODRMzBQBVWnGSCpL6A99wq4i7gOf+Nzphx5LzpwtjI71hm7eD9hYhBwPlv6NGvHIUVwlLFQcFSJvzY6tG3fv6Ny6JdmwvkDOPaNOYjY5KZRLyCczISN80j0ljVsm8UZq+WNn+nsHig6buYR11vg6dKy/f5AtUhyW6WKvSaeBz8aIJOYIAu7CqbJrexJdZna1Z4CNKDxyPHrg0cFiueyxhoCZBBOb3LeS9zpEQAREQAREQAREoA0JSJy04UNdVlMyC1IZJ0GqQ5AEd37n0BNPuEE+V+q48eUv7+pjhxPUR27Tlbu9o8+NnD7gjtW6evrwReAoyHd0lAfNzidp+JPTv37DLW96c54N3r2ADRox8N1yni1TbFQY2xo26nWz0leqFgwErPokfuzHP37i7rsLpXKxXNq17+aBLZebbePjZO22HYSHjRw45pw8W+npwq1jdj00u6M440ND6zatL23dklszwPaHlYHeznWDhbX9ZKHYUDTEBAe7MU7jykicXOR0NzwW+cqxHJnnsxFjODzGfpNGHRlhlvhJqkxw36A5AMTCZOxK2dNhrlJOj76e7m2XXTZ28KjHkl2pOOM0BZNPo0MEREAEREAEREAE2pSAxEmbPthlMy1jbzOY1EOANX7q/kcPfftOv1hxSuWOXOWKm27s3bAuKBY23LCnyKrBjjf20CONBhuX5EKyRnL5Iju7G5Pe6JOO3p6O6/fgTmG7dZM9gt5Bn5B9HhGkhVzwkDzGxTJxpFFQYXL2kScPfOYfe9YMuvlCaTzyXuj2bduGtb/mml1lzzvpuqe+/+Mwiow/w3XYRbEahl2Xbxncd1337l259Wvs0GvDZ48/e3B4/7Nb91zlsa+i8ZWYw+iFliN2gsQtJ26epBmzPhnqxnPZud6IE3N4hIGZsK5URE2cYg0x016jVh0+e7a7v9/33J7LtsS37nvgk5/HicKO9Aw4vV/KxCLTqwiIgAiIgAiIQHsSkDhpz+e6TGY1YbxbZYJxXY8HI9bVZZ+PzrGx8OHPfAGL/OqX/UyJdbq6y337bmC3j6PV8ZP3P1zoytVZT7jh59gt3dr/5MdXx0eOHHbLBHoF5HmwXyHBVfGpiAo5MljOnC52dY6iBYxiMEa80QNh3FuNr6z5g17H8PD4ka/dyZJdpe6eUn+/01XouO5KNE/txKmTDz+CAMAhM8aGj1F4w+0/U7xml9PfS5770Injbq0+/PDDj9577zOjw5u2vK9YMOFa9BEbL41dGmySd6odvCjx+UllDS6gAHFiRjTp86CAv8T8cHJC2+AnIjX/xKGDjz/w0M233+4XS/6m9fl9N7jf+f746WGfqLNcjkZM2glNTdw02al+i4AIiIAIiIAIiEC7EJA4aZcnuRzngSWNAZ7Z0sZbUAmduOEEDacUevXAOXDnD7Dnb3rTaxMipApB155ryBM58tDjoRMGuXyjNnbq6NF0Zsayf/rxxz/3h39UIJArH4xH0ZmoMZ6w5Xo99twNQX5Pkt85CcEEZxmdQKK9U244/dW4P0wGOnqi0bMn777voWLpxl98u0n/8PzKVVes99/01O88WGk0Snk/DrykWE42rXf6ep1S4eQzz/z97/9BKYpLsTM8Olbt6XSKRFlNuILY4J4NTIz7hM4mZUbab+osMr4RdjdhHKlkmRhbysPsX596UMw4wWIqsBjAw1/76je+9e09+24p5sssX9a1Ye2L/8kv/PT9H66OjAc5FiqWLpmAqF8iIAIiIAIiIALtSkDipF2f7LKYl8mnwPJGIhhngTHBcRewzwi7pvt+MOhGZ46d9R9/1jl41F3fT7CW293RtWvbnrf/3OHPftEh0x3XBBuesIk7jbhJX0fX9Tt3H3z0iXIU5Z14YMOGG1/zqlxPD2sE54dGgsefOf3FO4wvg84mfQtunOqAdDMRdiPpzRXik8Pjdz9Q3X1V/srtXrFE1kp564ab/59fPv6Fr4ycONEoF2KWGC7kE1YVjmN3ZCz/5P7O7p58Id9g35Vi0awIzISMB4PliL2YhHiT1I5sMK/ZwRszDK4hT4yooJhC4E5zCmGEZwWRk95HI1Ey/NhTtXsf3trw7/vAx655/asHdmxzSwX/im2FtYP10QO1er2zUGLPR9PF5Oyy7lQQAREQAREQAREQgfYgcC5Cvz3ms+JmMcWkXXGjv9ABp7PEpDYSw5jk5IsUPL/H9dfEXvzMwQe/dkc0XjdGN9FLawd69l6X37gmJPEijAthVD90KGGfRN/rWbf22pe/7JaXvGjzxk3btm67bt+NO6+/bue11+687jrel0ulmAR4tjnh1Qwsc1rg2zAyIA6jCmnnsZ87eurxO75VO3HaJKt4id9T7rvpem/tYM1zqmajRjMQXBvIiUqlsu+lt+WCgAiudVdccctrX80OjCY7JO0AfRVHMXKLZPqURLNooEwt8zO5xJbRNBYYDIxkOXeYHeiT08MdJ89uK3ScvfuntSPHnXqDKbM22brbXuJtXj/Kxi8h81tNRzOh1TRvzVUEREAEREAEVjMBeU6W4Omf/y17u5phRiqYuU3Oz/w2GRd4HDzfiId84J88deapO3/Qs3vn4M4r8n3ETRW8jWt7b71p+Nvfrx88mquH++++e8uWDcWOcmGgd8O+G9atX3vo0cfZi71n+2X53m6H1brCcPjU6aPPPktmBk4WfDToB7PN4uRhNRErCpOa0pX3knrjwN339Vxz1ZpcUBjoY7N5p7+764arzwyfHt3/TLmac6pVJw6dfKE80L/7zW8c76pEYWPdNVdtftELjbxAY5Dpns+XBgdZacxxWDkMN0jAvCblB10bxwgqxnhNkCjmd1o08yf1xskRcWaupECQMDErAMSdoZOrFJLh02eeeKqyZUPPFZej1vpuvvHkU88MHThSr9cLRRw6VhlNzq1Nfk+wOBcd1ybz0jREQAREQAREQAQujoDEycXxmlNtDLCJr87NN+fNB++MmdoWR+qwmJgJxrnnkQE/qROssR5HrKvr4rJIcZT9oKtWf+DDn9z77n8yWNrpFAO3UlrzmlcePnai8dzp8bGxh7/17fItewdL+Vyx6A30et2VzTu2mR3gUT6BG9XHG0eOH3n4waceeeSKzs5kdMR4NljLi/WCOYyzwksIJcO5wRnS09ka3nPL1drBr349lw/W7dubbk6frHvlS0+Njxx65snS2TO1I4dza/vZY9FFLBV27N2+hZESvzUeNcLjx8t9vX65mOvs6t65+1ipy2sMeV6O1ZAJzSL/nnpGiKQbs7DfPLrF7EtPMNjkE2ZAYRSGialnwCSh4+Tx4QSxQ7RbIYrXVSpPfeOOakfhxm1bzNJk3Z1d2y6PHn+68dSBoNBFiy0fnrb41BgBl04EImmhbf4e2uPxaBYiIAIiIAIisFgEJE4WizTG1lRB0pZfgFuaEz4Cx1jbA5WOSlBgjd6k2nBrcT6Xj0plBAsOAIK7sN4rXq4vjI8eOeEeOJqsW+viDMGezxWuuvXWM5F35O6fdCf1737wIxt379yxd+/aa642IVQsrYUtG8XxePWJb3zjmfseqB15rrdYZNHeci7fX6r0+nlntOo0fKcas1hWrlyEPUtvsRoYti/7LfY6hdNP7W88/pSzcZOzYT0DYeQ79t4wWG888/l/+PEnP73t1MmNt9xc2LTRLFdcKuOPOfrII3d98Qvj1frLfvmd67Zd7oSJWyx39/TUq7XOYmmwq8dsW1KLnEbiNqIARUaeTJAUXBJYCv2d3R6Z/mMNBkEifGdvJ7qo4jqlwPiP3GrojNdzCTkmBZ+oNN/vaDiFM0POsZPO4ADXB669vjRcGzr69+xKn36Ipn6SFusjvGD9pDLStI67afJosylOTku/RUAEREAEREAEZidgFiedvYauzhsBSJPQXI3OfOErJ7/+7dGjz/WwY0aartBmXxNbcULg0nij4VUqSW93o7MUuk459r2n9vtDY/lyyexmSMa5y4rAhDnFZ8fGSpvWJV2VemDuRreU66F7+mzt1JnhIBly46CjXOnpLfZ0s7FJ4mPDs1JwFNfro0eO1kbG2DG+y/E7E38kbHh4PLq6GuVi6CYdft47cNQ9+lyptzvEzMeXwXf0iVNNoqGxkfxgXzA4UC8U4ohRuMUoDs6OjB86RHe5tWtyg31+pVLI5etRSL7K2Jkzpw4caoSNNTu25/HhRHEl8qIHHiN0zevsdHs6w26zFFnZzwcnz4ZPPFXqqsRBMBI1qjm/sG5NXC6ESZxz3NJIPXngsXx311ijEXaXc1s2jkS1UuJ5h58LTp4pdJaJDjsV1sPeruL6tQ1UU5gUYzd/6qx36HC+0jEZKTdvn8olbwg5xucfR9JwnDzy+BM3//Z7N/7MLU5Xyeyh2WZ/GEvOWgMQAREQAREQgWVPQJ6TJXtEE2EsS9b/gnVsfAFMzuRYsLhVODTaOHU2xr5nZSsT45T4OeKq2FIQrWayb4i4KhKGVSjVD5+o7z/ssLEJ2RvY5Pl8LsjhDWHDxXKcRGdGkxNDDQQJaejEihEvxpJZYVTO5TpzucDL43ngi/cONwhHqvWTQ0mj4SZxFBBw5eVKJVQQh/2KnpExMC9fCE+NhM+dTcIoDkP8FVEQsOl7R1AoeE7tuTPh8dOR69YCn2AuBp93nA0+w/aTh56KGo04ThpBPp+4AW6Zeq12cDh8qp6YHvOsikyv2NW+E5XwvFSr4ZP7o6ge1eo+8Wa5fKGYzxHVlvNqQ8O1e3/q1Kqh76OCgkLeRJ55Xqefr54eqZ84HdfqrAoQ+ezrwq0TjoU2+zqhWYBQztwoC/YBVcMiIAIiIAIiIALLl4DEyRI8Gyx3s//eEvS8WF2m+oTOCKkq5H03nzf7FaIlMN5RJBjohGWZhbVMNJVxZJBXnssVOc9aWAmKgBNml0JAkVtCzRzJJelNLO7VIHscA55W+GEbdpI9WBHL5KgTKZYQTlXMF4gKS3CGmBP0mgol3tjAutRVSLmUK7hsbEjnrJQVRx4CwFSgulv0vDLbKJpRuFEYmU3oOWjGKAeXhJkkb+rSEoLBaAbyWNxCEuR8yqYxUmrMgKiDqyTn5/yiHzdyTr5kpoyqYt0tItpyiKqgHOR7imU+Dy56BvETmcmj3gqk2gcBuirlY4aVjqB9gwHT52OeRlv/ZZgPkg4REAEREAEREIGZCUiczMxmIa4YQ9kYX8Ztki67ZCxYYxOnpuxC9Lj4bdop0S9z9dksJJ2f0QbGsOYi0oKIL8rM2zcgjJl/zp7HqZIhMtf4Jj1Ch1CkCTwbqdeFd/Yr9tSZgEowa4ClTZorppeJneInuSJA0q4MeTsM+2oih0hL9/DfcBhFwXn0BSLCzgNvirmSHrYDJIS9xDiREqwPhj/F1A48kuZpwSTBB3kzHt4ZD4rJjjGyhjgl0weSJU8WvClROz1pFBInSItBDpmpwcsInHSSZgDp4E1TdhYU2uownw7zY0AaLOY/HSIgAiIgAiIgAquQgMTJYj50s2Is/fEfu+lFbL23Cg5rTGNxWnszfWuLqamNrsAcnVAjxrVi+Jg9C88dLLN17k1TKaszEQiUNpJd56rpID1oFCHBQcH2TZkzLHvFa1aNk81lc8N0h52RbdO2Zhu3dWnB/tBTOgZTBQlkRNaEfuJ6NvYWsUElOwRe0xvMgNlI0uyL0tzLdONawedQjuhVc5jJMhELYQXPSEMXAREQAREQARG4NAISJ5fGbU53mTChICB9glYwXdveEEu/CzfTNJPFCk19EnbWbCtoQq8mrHXjdrCHqWOsenNYQx5T3aoCzlizHb3DGbuurjkzFaVp03RsvomflBO29cl2U3Pf3G7Hl/ZFp5NDsO/PvVIxG4A9a7UNZdsiN9rBpC0wIpLsTXv0b1WJh8elpQkzyHNdUKIF24gZlkmiMcf5Xdvz7fTKp4DMHnaPIeytnealuYiACIiACIiACFwUAdkBF4VrzpWxRFlAdqA/GOirhWRPWLN2RoN4zv0tfQPNln82Gj52ZMZjsvMToVeQGebHmO7pDzelpNLX1L4n2MnE/Bh8Ez/p7/SWrNnUiueUbWziXWr9W1XAvRz2deImBEz6FCYeBKLIdmcG0/KT3mdP2lY40aRGJhqc6MOIEGbJq/mxbTJ+BtPy09rL5D22uYmr55TaRC/t9cuITJYyq8VR32WbcpUyQW1Tn1J7TVezEQEREAEREAERmJmAxMnMbBboCuJk88b85o2jLE+bWuSmn8zmnTRnUxt1gUaweM0yrexoLuMMMf6QCSmSuhOsGW9IWGUyFcDkVXuj9aVkLZ8rTGgBcy/FNF/F6AdanGzOnJ4sp8VzvgsupaKJO8zAcFxM+eEuWiJ3JL194pV+TO2mp0YdU5MXU7B/X2xOgg/EjCL9sd6RidesU1sZ6TJZzRSskqHQvkcq2NjgMg6H3HDTC/dV1g44ebMFTvtOWTMTAREQAREQARGYkYDCumZEswAXMGXNFh7OYH9j3Zox163WG+WAYB8MUpMJTRp0alNP9Gy+TzYG6go+sK0J0pn6NXgaqjRpeaamOBOcfD9h10++NXKgiUAzD9PoVAN2aje0hGxI7yaVxfRA3BdEJ2udazb1s0xqjFRboBPSe1rJ07/dBDG7QMupDklPpEkmlFJFgs2Np8T0kvbErZzOVNXkBCfuS39NvgAtO86NMjvVHgX76Ihh88DkhFE0XB8/Ebi3vvplpU1rnEKQ+qSYvVV37TFnzUIEREAEREAEROD5CUicPD+jeauB0WnMLdfJBeu2Xn7tK19++Cvf7Ovo7MwVciYdgTWfWsRIO5imZmnc2Y7zLp93Ysrd012drgvqGavXqj30A+VzKsK0iOMCvIYweiQy+64YQ9joRHMVVTFdT+bS1CNt2Ty47GCp4YlmOUUjWd4IbU+Us7oUzn/G559prt8mZRPEZw4WbK4lyUitWi3kBnZeFvR2ugU2tpmUkAbPhT0I25xeRUAEREAEREAEVjgBiZNFfYCpqWUMr/LaNRtuvSU6evzMU89EI8MdhWKQL5jVZqcMZ+q7KZdWyZtLJmBuxG8ymabSYvBnJq9xbbCOlnFyGJmR6peJlwvq2npObOvN4scon5aHyYDS0TQ/OXPjqvUNmEyjJAobJ6vjtWLQsePy9be9JKgUU2Vi4ZuHk+K6oGfRDFZlERABERABERCBFUrALpW0Qge/8obN98XGzsLiYlfyM0Pjd/9k/133VJ8+4JwZrochu/U1f02cfXu88ua5DEac2rNTTNtJC/fcSUr2jR2vrYALK31EFyQauKW5hfRrfh4y67BNPb0MgCyrIRjxlv7P87yorye/Zf3A9ddsuPUmt7vDMZta8tnP0E4+t2U1AQ1GBERABERABERgYQhInCwM1xlaNeIkNbrMgrqNhjM6jiw59sN7nrrz+4f27w+CIL08cXO2D+AMjen0bASMSTshECjy05zKkbpIjMeEBzJFRRhB2OwBma2Haa+l3ZqAsinNTlt1NZ80e2LGiR/4Pf191732Vd1X7nAGep1KISkVzR8I/5lfOkRABERABERABFYdAYmTJXrkZGebn9hphNFINRyrxmgVHfNLAOlhjjSPxARwYe+mr5nhm9rAmMnpqmnWGp6jqMDfQgtzbMSY5/NLYvm1ZhG5nu/nO8puuejkA8fHa8U6XSnAVKMsv2FrRCIgAiIgAiIgAgtLQOJkYfnO2LoxwPjWPv3inqRgs4MgP21vks7IY/4vZHgnNIlNApm0+xERFC31KVpi4tQljaf58TWXL7axudx7sX0tYX1Qc7BMAJrEuKzSnzSazuiT9BK/VwmMdMJ6EQEREAEREAERkDhZus+AMYOt8ZXFFskQm9fHYbWfbRJ71+xb4oxXk6FhFoeq5gv5OGoU895Af6cxgY09TB3z64KP5srWuM5uncOjbG41a2+lF1p4mI+8macRJeZSRj51ZpnJcrXlHnNWhwiIgAiIgAiIQHsT0GpdS/d8jemVml8mgiU1xdrSKl06wJOSIx0BkM025M7x4fGHHzvx7LMHOzu6otqZyzZ0vvhF1/EAzJYoE/Zw+lCed9hTZMxEpkr6AC/s9hnan9PNM7S59KenmdVkZo+51Ixt4hlImSz9U9MIREAEREAERGApCEicLAX1rM8Joy01zjg5jQ2XVVXhkgiA1LinrPhgSw3n2ZPDX7vrsW98667OYmd16MhrX3rFzS+4Nm+W/Y2z9HhrOE8+lRn6nXKZN7Rgn19zeYZ7ZzxtfD1mU872OqagSqeWLZqd7j5qdaE+/u311DUbERABERABEbgkAhInl4Rtnm9qN2N0nvFcanNWJVjNQNms7+s6Nac4kqzxKtudYndccyKvnG6AiWWcPgVjR6figLXSLrrfi7+jtQtamHsjrY0u+ftZpmQxp/BnqbXkM9AAREAEREAEREAEFomAxMkigVY3S0gAxcEP6/uyl3yY5GpOV93rL/jdDfdo7Jq9Zc7ZxZSoaoTJuXNLOHJ1LQIiIAIiIAIiIAKrisAF7TS3qohosu1GIBUaKBOOVKL4oZNvOEV+YqfgOP7kfK2Ese+kTCap6LcIiIAIiIAIiIAILCIBiZNFhK2ulgEBVEpstl8kz8EuJ5zpEMSJDhEQAREQAREQAREQgaUkIHGylPTV9yITmHCOJGQ64DBhI3ePJWwXeQzqTgREQAREQAREQAREYCYCEiczkdH59iQQR04jikiCR6FImLTnM9asREAEREAEREAEViwBiZMV++g08EsiECdRHMaua2O6WppQZFcLEL0VAREQAREQAREQgUUlIHGyqLjV2ZITSGInjBPf9b2JnJM0TX7KsBToNQWH3oiACIiACIiACIjAohGQOFk01OposQmcLzKMuyRxYnJNvCBNO2nxn3CH/Vnsoao/ERABERABERABERABCEic6GPQ/gQQHNkHnT3Y43Qv+Ol0iJRJ+38YNEMREAEREAEREIHlTECbMC7np6OxzQ8Bk0rCslwuiwg7tUZSq/KeT77vppFdZgkvcxVl0nxMm3+S1Zn2avPtKl84gYzqhd+imiIgAiIgAiIgAu1JQOKkPZ+rZtVCIBMTxHTVQ4K7gnS1LsxiD2WSuOm+8NyT1TP3T3mTelqaW2252nxJ5YsiIHFyUbhUWQREQAREQATamYDESTs/Xc0tI4D84CDhhJ8kIsiLhPimtYTPCQ1KmVKZ3Wie/WrWswoiIAIiIAIiIAIiIAIXSkDi5EJJqd4KJYAYSaUHqsRhAWEkRRybXRhZTdgc5MZzwaSkpBWsiLF+lNnUx2zXVigoDVsEREAEREAEREAElpyAxMmSPwINYAEJpLLEtG8K6W7wSZKk4sQz6qTZeTJlFNIeU3DojQiIgAiIgAiIgAgsDoFsEaPF6U69iMAiEbDuEjpDlsTpL85EsRNF7MIYmzyTNAmereJxm0yrRZAxHIs0XHUjAiIgAiIgAiIgAiKQrlkkDCLQngQmhcU56UHQVmg8J7HZgxHZ4rmejwsl9asYLwqxXVnCCYrl3I3tCUizEgEREAEREAEREIFlRkBhXcvsgWg480EAj4fZadE3aSQTx4QC4V2C3yQIECduwK98YF0rJsQrEyNZYfJu/RYBERABERABERABEVgEAgrrWgTI6mKRCGRRWPVGNDJaJ3LLSJA03d3KjcisGkwcl9tohPyudFSKxY4wMvufcPBifk8qE/s2a3OR5qBuREAEREAEREAERGAVE3Ble63ip9+GUzdJIq7z+FOH/vErPzxwZKQRR2xkwjzRKSiWsLjh0PCap0729HVWGmGcqx9aVzqybXCsEVaTqM4fQ6pdEC/jvlt76Ytvev1rXyb53oafEk1JBERABERABERguRJQWNdyfTIa16URSMO38sVKoXfzHV99wM/ligWfgC2ivHCbxLl8zSvkc8XYDWLOBd0nqrWh/VEY+kmcR6gjZAgIGx8+euXlldDNcwsOliZXymTx0samu0RABERABERABERABGYlIHEyKx5dXJkEuvt7dl579fDfnSkWuwodZbYzceMk53qRU4idsuPk6yzg5eUSrzsOcg1nAPcIWSq+mWzihLXRkbFd1+7YesX26NySEcb9okMEREAEREAEREAERGBBCUicLCheNb4EBNAd+YLT1+8VO7oaTmU87sx5eZdFuRKXGC/y5CfTSnibi9xO1+nwzcrCiY+TxE0aySh3XbHjss2XrVuC0atLERABERABERABEVjFBBRRv4offptOnc80Px3F/Ot/ZvfaLj+sjUdhEkVO5PhGmZjILBLlieCKcZPEjo9ECR3cKnnXz1OhHkaXbRzo7SoUAsfIlQlK/J4stik3TUsEREAEREAEREAElpyAxMmSPwINYJ4JoCEI0Ooqea+4tTJQGYsbVc9oEo+MEpwq6QoQJkYrlSl8/o3qILUkcv1GHI9Vx8bqQ699xZ7LNgzkJEfm+cmoOREQAREQAREQARF4HgIK63oeQLp8UQQw/Zu2C7moW+enMlID5YHmKPnOzs1+d7EWx7nYcXNBDucJB/sw2l8oFsrWk5I6RUiQD8N4NJ+rXnt130BPMd07Pq085YXmbRNTzuqNCIiACIiACIiACIjA3AnIczJ3hqu6BdQIh0WQFZaWCNKBj3XBdXqKzobBSmc5V4tizwvMDif8pOtvoaAiU0aA2LPkpDD8ej6obRz0BvrcQsEsQTydCpmY7NLOUb2LgAiIgAiIgAiIQFsSkDhpy8e6eJNq9pNQbn67eIM4rycrO4q+c9P1O7dftm6s2iCTBKdO6vQweSTEd8WtyiOJwrHOYnXvlb3lPFLGKJNJ2XVeBzohAiIgAiIgAiIgAiKwAAQkThYA6mpqEnfDMhEkLdT5ZCMtrrmmsPXyXD2KGzGChD1QUn0yGdrF1vD8cNp3E59rjdGtfeE7Xrt1sJILiPoyW8m3tKq3IiACIiACIiACIiACC0hAOScLCLftm0aZhGG4f//+Wq1GmWM5TNl4PMhxdwM/V6zm16I+OgpJ4IaOQ/LJuYPVg1PniNUfSKyYHPqeUuKMnn7yubNbN63t6+miduoNkkY5x00lERABERABERABEVg4AhInC8e2DVtGigwNDT300EMnT560giSKoqeeeoqy9Z8sB32SihMvdvNBrhRXdjx0pMOtFb1C4vjdSA2zYFf2ZFIXihFVblytVwv1seOHDnzp84+dPXVs86Y1vT2dVLTiZMeOHdu3b+/qQq5IqGT4VBABERABERABERCBeSZgsoDnuUk1144E+JycOHHiyJEjzzzzzCc+8YmDBw8iSwqFApuvc4nXIAiw45fNx4lVg9nVJB/mN8eVrbyOxmtyHZcnHluaWI8Jv5AZaBWPADDfqQ0Pne4LDqx1H3ZO3lWrjUThOG4hpsNx6NCh17/+9a9+9avRJ2vWrCmXy76f7ibfjg9acxIBERABERABERCBJSSwfKzJJYSgrp+fQLVa/fP0GBkZ2bZt29vf/vYXvehFGzduxHbnZsSJ9Zw8f0OLUiMV3J7n50M3P1TzfnDfsd/9/77ftW6fny/HLk6V1PuRmO1NYuK52I0xGhode+6XX7PmF1+xoTupOU7oeUbF2ON//I//8ZWvfAWJgjj5r//1v9544409PT2LMg91IgIiIAIiIAIiIAKri4DEyep63pcwW0K5zpw580d/9Eff+973du7c+a53vQvXwdq1a4lxwoHAVdrMYrqsVrmEXub9FiM6EB9B2QlyP330ud/6f+8661+VK3T6gW9GjPLA+UE6PKknEZvIH+ytjP3K6ze/6SWby43QdflpJAkLEHulUunZZ5/Fa3Tvvfd+7nOfI4ANL8prX/vaq666iskuK0k27wzVoAiIgAiIgAiIgAgsMgHlnCwy8BXWHQ6Tp59++mMf+xgOk9e97nW33HLLTTfd1Gg0kCWY5nEcWwOdV3swveVir5vRxW5jvBA4a3orN167485HgpiluRAUJqTLOFdMYBfiJAmj+tkXvnj9zm09ed9xGw67MSJtqMekUF8osXXr1g0ODvb19d1///0/+tGPCGnjEvpkhT1ODVcEREAEREAEREAEljcBiZPl/XyWdHQY9yiTL33pS3fffTcOk5tvvhkb3SaZoE+wzu3osgJvbblFn2QVMgfL4kyLhYDjJHTisLureOtNm7/z6HP1RlQIzGceUeWn6wRHScw6w348vO/K3Vs3dHoJMV8h54xqSaeDPKOQy+XWr19P2smePXs++clPPvLII0yqWCxu2bKFS4szHfUiAiIgAiIgAiIgAm1PQPuctP0jvsQJYnwTy3THHXd8+tOffve7333bbbdt2LABuTI+Tqa4Oc5vF+0xU/LJtPXPb2F+zwQ+MVzGW1IsOldfnU+S8UaU5sObSK4oiJ0AMRWHRHX1lqL13U534Lhh6Do1b+qaXowKMcaRz+evuOKK3/iN37j66qu/+MUvsjAADqX5HbNaE4FVTmD2fytmvzrv6Ba5u3kf/+wN1ut11jg5mh5nz56dvbKuisByI2D/PPkCEVvl8OHDfJjHxsba+292uT2ChRuPPCcLx3Yltczfc4u7g7d/+Zd/+a1vfes1r3nN7bffjl2OdU6M06X95dOaPc7vaIEw0ZHJh3H9iEguz2Vhse1bOp84FMVRzffz+cD3OG88KPW8X3vRtTsGOiuB04jjGicZUpoyP2VohHKhzWiTlJuXvexlp06d+uhHP/pLv/RLJMcztSlV9UYEROBSCfDXNMu/Etnfmq0zS81L7X/KfbMPhqoLPYApo5nvN6wC/453vAPfL/88vulNb3rf+9433z0su/aan1dzedkNdIYBrcQxzzCVCzrNfKmX/dW33GPPkw37kY985K677uLq7/7u7xLgQKboTLe0tKC3y5aAxMmyfTSLOrCWv2QM8XvuuYcUcNbjestb3lKpVEgEn4sysZNZzH9Y7YxcD2+Iz1LHZd97xa391W88+8yx8UJ+wOxsggBhseBoqJwbuv0lVw/0ltwk4i7XMcLFJqU0PwM7ePQJBdYr27dv38c//vH/+T//56/92q/hSGmuqbIIiMAlExgeHv6zP/sz/tD4QqSlEVLd+C5gYGCAdK/LLruMty3/cLXUn/tbvpFhMDhIieFsbs38Q+G6nZ2djIdlQjiwh5orrIgy/84fOHAAnogTvnJeEWOeyyD5v7AnnngCMWb1GMmEc2ltSe7l/4iJtWbh/u7ubtakaflYLsmQFq5TPpP4Q/h3gFnzt0ZU+bR98THGecIObBxUoD5/m9PW1MkVREDiZAU9rMUbKv+I//3f/z1/4S94wQswxHnL37/9DmNSYNg//mmCu7JRco1KBHplh720KP9w2IHxrQtrHHuJ78euc+NVhXvurx84RtGEc6E/PK/RXYw2Dua2benoKPv52IndAsKEcdrtGbO5NBcwifiH8vrrr3/Pe94DpTe84Q0SJ818VBaBuRDAEPn85z/PPzgdHR32Xx6ECg3y7wZ/ethkvb29LOq9adMm/gxf+tKXskwFtuZcepzlXgbw5S9/+bnnnqNf6zi1g+EW/lljhBiIW9OD8t69ezdv3kxhlgaX2yVmgYGLPUdhuY1t3seDCfupT32KV75u4yP0tre9bd67WOgGWTnzQx/6EL2gz1mcZteuXQvd4xK2T5jWBz/4QT6cPDIW43njG9847WD46FKHbwf4XgPZxjFtNZ1cWQT0FFfW81qk0RKL/LWvfY3/47/11luxCXg7aR9gIvD/YeSSG3GC68HklpsC/5kXyhMBYtQwJ3BDkPrh8wUkm8qfPn2af2WszqFZq3ZMpfk/zED4YXBGC7n+uONX3Xx95IQbdxnfB7IljonjKgbVQjT8yE8feC7fyFGd0ZuppL9SlTI5NNNM6mGmWVMAyLXX7vnoxz76wAM/xRxh0S/+x0z5f/r+/n67csDkvfotAiJwoQT4GyRmkn8l+JPD5uBLfeSK+YNl+6EwZLuhJ598kkAO/gDZEZUzWC2kw83FcWH+6u2/VtONkX+4sAixeKiDFMn+BePftOPHjzOe++67j9EyAEKk+DfzyiuvRC9N19KUc7N3aqteSJ0pjU59Y6FxbpbZYdgxNV5nqTO11Tm9s0Oapa/nrXCx3Tcz5IP0mc98hi/jeUDEKr/1rW+dZSQX29FC17cTwTnw/ve/n/9HJgyPzz8uu3mfQkaMAscSqla+FPjABz7A53N0dJR/ClrECWOzc+eVQfJ/vhmK7BIFnkt2fqGfkdqfRwISJ/MIs02a4v9oyXrnnwNWptr1/7N3HwCWXNWd8PuFDjOjGY0So6xpQLIECJAINkKAGCEw4EBeEEnAGvAabDBgDHz28jmtTfCyC+sFVhiDZSG8xM9gMEICRM4ySiiN0kgaaUaTU4f3+vvdOt13SvW6e3qSPKFKo9e3bp177jnnhvqfm+rUU2008aVCQ5eOt0rvsL70RfVwPdLH4fvsQuk2Wqlz4KMg7bPDo9loed+1myB8Z6zjleAV7tQvDo8pacMbgIX+ArCIbmVPG05/lERuF9tHTJR0+/rHmosXHHpC/1FntR/0pKGhzoJ2PxmanZFNa1Zc8f3vff2fbhwYub05sWnCp0/SnhPyUS31a9NeNtFb+7Vw4aEr77n7/e9/T7s9MD7Of+szlLt06fCzn/0bYEqMR+Yes+4fp7VkHVlboGyBQBWAvk4D9jr55JONcOsx9BXIRN52223GOKAWDsw999zzJ3/yJ7/7u78LqEFpZT47DGf4gjJ1BbOicw6SmRODDjabEYZbopO01osAbm3GJY/bj370o9dff/2LXvQi30HK7b2cUUglxiXsV74zieopwXQgMxF4Go/kFdkF2+AcjyIm5xJkMzGsxEs7E/0sj2ZhIlXIPJM8CBh22rLIOeZAJaOZbqNwPZUwaGK+C9iNvEQm85W8U5SuckzQiAwOHvUSxKM9/lvOKATgmXi5qJMMFdpVRN2hDMEnUkU4Jyk/Yh/8GSo/nXsAn52VCvNIldNS0A5PIwIkEZnj5yJGWCanylVuLmmDJrLLmQarXeAz9xxryrIFauekbI06nCxgmPA73/mOgB7Q7+hY8jharUEjbJ1uY/OW0ZGRsTRLMPl65WaYnuh0+xwu3KcL4Zi02s7e5cl071t1z6cv/qef/+xnAS8sf3rkIx8Jc7hyz5UDKe89cSV50mXbiA7S+5tctsUPNVoL79l2ws9uX3TlLePtwUFOV19n25kPO+4pL33t1nV3DjY2tpujiK33mtpwMvkq6hUKR2Lrp8bHx3hlgI1unEd3xx23X3vttU7x+sxnPgNVvPKVr3TKmeOGyxxyZ1eOrMO1BWoLsEDuDfghNrydd955Z5xxBs9Eq/HUr1am3VmM/oMf/OC9732vR/bCxsaPigEjSWZYeZrjkc3iAEQq2MjwrSVbT3/60wVEgj6uQG98FZ8/eve7302YH/7wh9bBPulJTzJOgbNcckZlAQLi4CBJZogg4kUKk8otmuCAm9vgGayCOLMtP5IkEkYSNEQVuUNNMzeBsuRl5mWaHYYzExxcswuAgMA5SYW5p5WY2W+DPueY2YoBuF0CrIRJ5Os305Rtm+PzU6mmJeiVJ0ohJ4y8/JZjelMFWdDIXQWzcDEnCeE58IB71q6cZFqG5cjMSqRwVjB8gKiQHmGe6085SZlVDmPiymbZIX1OWA5EqpxWgOLkwVbYhVgu5SQzhYM4yyNVxKCvFN/sHDzNOc7dGjPxrOPnboHaOZm7rQ4WSgOBX/rSl3zWw2BhWqxk53jatjFwz9qtd96z4b51WzvddvJH7NlIJjFvkhZPCRVrvSYG+ttWgG/ecO8NN1x17S9+Or517aMe9Sjjmt7WFjsZtbLeV6+a2/neM2tah9Xwmvf6Ie9gt29g9bahTd/d+t2r183rb0EWRx7S/pUHzz/7V0/atuXIweZYq1m8qKiU5kyKRWk7Ei6pXBDqv/TsRnOf8GtnrV231rmcDg9x3PBPfvKTJz/5ydYP7IhT/by2QG2B7RaIpaQQmO3aERsQIUAGuAbBmzC57LLLNDojAtdcc01l61fGIhlbaKHmNwy+WBvjm6r6N+MvGb5sz7snJDvOEoZGVUBDzzPPCOvc/viP//gjH/mIJUNWedmm8tznPrcMHDNLCWGjgMXE0NlaJ6ZjxAEOC7YyQkNaZJ7KMePFUMoj6gsHfAwZ3JpTwjAWoenA+WzSindR028WY+4BeSGWXI6EIaQx+7mzCn2TBAUIZn9r4RSuF4GZKPbPKsslyCqyMb4rJgqCpkJQviWtOX+vGJE4s49fbHGIgGF4AdwC7kfpe8rp9VZCGQlDa/EI2FAS8aEC4amgh6eCWiSvSFUWoxKWnPWCm3zxDGEqZG7FR9ELV0C5eJHSWpPmN2oLOekoHnPhGE90u1MX2TQiA4hSMYJ24Vd2IeQOtZMKJQOaP1SlWZiE6vNOyRBM/EZ2jExHF0nYQT9A38yQssLlmPwoB4gkrEUoLKqRKuAHnhWNQs2cUCDSCqB0afv0CvtQTbnn9lhOVYf3rAVq52TP2vNA4KYR+gg6j0K3W4xRWLTVP95orrxvyw23r9+41botC7b4K8k5mbB0q5hosJbL5hKYv781sWrlbTdc/4tbb772xGMWnvW4Rz7uMY/2eZDolBkoGvwDYilvGqcJ80/COWkNTLSOe9DoYYPdLZvXjnc7x58y77RTFh95+MDo/Earz8jidp+kcLd28C73ItMBJqLivatHW7ToUIcI6f30rQZQDaOypI82er1ZEKJTewB1f0AMXGdSW2DvWCAgGryVwUQgBi0owMTSpUuf/exnf//73wcdHDllFKDinIRciMN7gSbhJ7+Bw8BKeCUgsqYKuACsM6mCCTwkI0AwsGCmDKmc+2RS5ZJLLsGcf/Ld736X41ShjCTQuU+4IoOhw5cgldwhQv0tvP6YxzxGwhtvvPG6665jBHNET3ziE61to3hwEGNxrA/jytqWaHbgM1x55ZXh6oBi4ZzYh+PkAGoODw+jmR3JZXXKAbmDm1dddRWeRGIBc0d2YJO2TDZLmIRKkN3o4mMqVKastXC6R+CV26ljFLC32/EGuaArDG+44QYdKXjK3bKfZ/bc+WZOU2BJbCmOc1QYWpAhSkRBg+PqjDG4wPTkEak6+UWvXPi6dmOTVqVyMCORrEy+9dZbGYT95YJGFsyrCgHQBCNebxUKbhb7LV++XBgrmqKv6JhvSXL77bd7ayD20lQzVQlh+fLA5auUGU1pKhSTh4RkNyXFyCid+59ZzR5QNFIRjFIaBc7e+1iRTbugmnlL77LyGodehqSNklWrmYWQ6p7kStYvOXFQZzjJvWlnj/n2t79NJDrSnVRK33rOL37xi+GWUBZb85MzMaGRbWnIMFHfGI0M0crIZqhUwc3uYMiIOrSjF+0wxER2jKzEXQIOxVHixJtJjDp+dyxQOye7Y70DM62OW7P0ssxdrZVLnYnGui2ddZub7aFD+5pDac/J1HRJck+KKeD+/tb8gc66VSt++vOfL7/+mtNPO/Etb7jguKMXzRtKU9I6Mg1eh8hqbsuwY4/bsfCpUj6WMzSsNSs+aeJjjM3B5rFHDD1sePAHV9002mguPelknb+TyPTtnY61aoVzUmyJN9o2m1QFoV7JxxxtsHGZa2E3Uy5pErrdNoIFUji9R+/sxOH3ve99Omt9Gasm4vqqLVBbYFYLRDMJ6J8JRQaoEjCEaY2oAOACxFx99dWZLAc0SeiE3+KTRDAueAGveCqJ7gjsADLg12c961lnnXUWBO828s0cIqCli8dN90WATCMct1CvtNAYzno58lQogw/oBiU7MMovsE4A8dIGsS6CRn/wB38AkvI9/uf//J+EB+hNyIhBGfkCkYDXu971LvL87d/+reTgrPOOKQhMo3HpXdETGw4DWH35QUdEtpAWQchT+fU050Ik3Ph+H//4x/kGVIPnXv3qV8PWlVSz3PKaHCcAHVp6Z6mwgCzCQwhJ5MLsF1xwwbJly6ivewxTl3kqvje/+c2Ep8hrX/va2Z0TYN0UFmk5UTb+8Rn0xnL55je/+f73v5//QHdPWdVB+UqBl6hKKLLTTjvN+JFHCMhpaa7pL+X11re+1d5LbMHlL3/5y1Kh5xuQPy7q8APldfbZZ1vBS4uy8MHNKl8WAPS9CPzO5JxgiDk/k77Efs1rXuMc/5g5BM3tg+f0KgXqyJT7qs7DzcpaZZaQDZkIk5nKNwuGRhI8DZx95Stf4XdJIkfxmLtI6MAA3Jw2Me2By2hkzePSslQPHAiAAz6YuEioNG2+YlUGpHXOfaZAFlvyiy+++PLLL+ddi1T0OHPYVHslIrmGc/755/c6J8hYQ6vxIYQ///M/50BqI+gxjF+seJsWMtBLRcoIpyKSJqbErX246KKLjDW4xTbqLYaqqM7H2/x1r3udEhfetQmrSqb1bcUCtXNSMUh9m0C2cQJjdQYbvMQA7jFLDPqaY+Otkc5Aa6LdahQb4tMLDpD3z6xJX7NtE3x3wUDnc//2mRuuvnLZkx//R299w4OOWNDtWoCRZpxd2bg6Cy08pS96jRy/pwKpK0pX0SUVZ4vxT7rjo62B9oOPH3rKY4e+88Mbjzz6+KOO6M6b1x0dHedeNS1PC3crJbNSbYpHcOr9TQveOs4HSC5NQZw+j5LSpn4/ujADeFZ3GACzU/b3f//3vZme9rSn5S64l2UdU1ugtkBYYNqeASTyNHcdaPQq2hoEzB/oNR3o6bQfR69CTsg0PXBEq9SzQTBixBscNZUB97zsZS+zAnMmvCJTkBT6qeQSzdlvEEC3RNIDZDJCeirSr0VoXA7zHiBsxEhllJobAOqtWLECEoKrdBdgGdwDDxkvpzWybBBICMYSCbbyiMBuEMrnO+Qo3oWYG+ZXcn4LWAw+vvOd7+SGYdKrQoiKIYwujICoVIDP/vf//t9mGGKK4Hd+53d0X+EbhFJZx5kC1PnCF74AmoN3GBJJFnTntAjIRV5o2OSKK65wFhMniv2JjTLzjCJmEAW3w/kfgsmItwBe4+MSE9woGHq5FQ77s7wweQBZMYjli0DykFOYDX3aj7uIJh5FJZFR9PPG8j7wgQ8wcpyFkCWPgBIhduSO50z2l7VL/cGcPGzuIgYmxJZcdqT1ixtRQ07cIiFJIhJxRYDeW8ZXuG95y1s4tBJiIlN5SStrVVGM7y+rVNyPN73pTZmDvII/SXibf/VXf6Ud4YaJeDWTbNqUSyQUwfnhUHGx3vCGN2QmOwxgRV95BWVkyvKueMQ5IUCFj0fcITVffeO0a/s0YvwwkSRRahrUX//1XxPJQdJc95xL5iaGzJ/73OcoSAwJ1SJp8UFDL0Wgw+Gs8pdsK1Vv+cByzxzqwB6xQLWr3SNMayYHgAW0Rn1BoYhd5d3+gb5Dhlrz+yfGR7eaadASQXmfBIHoE9VEd7A5MDoy+o3vf+uuW697wW+d84Ln/obPGmrHXnleBBr5A2yTKUdjss/Qc3jn2n6yaF7fSUuqnaU4AABAAElEQVRGultuOvOhv3LskfOtY7WpxhI1PWGa/ihWacU2lanwzILP7L94T0T3qkfTc73+9a/Xy3/wgx/UX++Ph+vPbIL6SW2BvWWBwA2Vt/5UpzSZqVYGCUGuMb4bOMYzAW3QqL+BYQRgk0kJMyRLly4FNUBAkYbPIU5rRQAsO9oFpLI6a+76hGzR0oUDM2FextBBQ2xOghVH8tK1wkyEMbNqcYgwxOMyFg7KG6/9u7/7O14H+bGqqB+y4eYR7AVCQcygv1FkzhVuOhxJgEVO16WXXkovYVME9r9R3PzATNrhGWJHcg7b3/zN34CwoJhZCG4Dy3CHAqJNK1WFs5VRJh98CUqnh94KNJPJHCSSh88APvIJuSVsQkIlQqPHP/7xtKiwklwS11zyjbQVSoNEllQx8l/+5V8C3yqMEXTTHWLQMzW9Ap3nrHHgDrEAGAqnqkL/6T/9JypY7xRGVu4mH0ynAKk4MLgw4XGWMPMpB/B0lWNyOOKL51UaRaMI3v72txuqZytzAmxo+V98hSyaiV/QHDeBmbLIeRFb4XKGiY2P9WzDw8PxxpdcFhdeeKEXlvkQtZH62g5PiRg4B3/VSX1mSaUG4qsehPFUGTGLliW5T5RgZRoKMV/iv/yX/zKTWbJgWX4TVr5ujIlpQwy5TGZg+H7R1lTpmFAqJySeVqO+aQ7alOTxEaSQmaaGBngddJdczfReNg1lnCI0whk39cFSN+v9jBEgw0cl0U5lhz8CfLjr+ETHotNQbficakVZmDq8+xaonZPdt+GBySHeBOYBEnhvjLX7Bk462sfFGvfcN7p1vDjdEppvFNMNfd3+/rRn0+DlZV//t19/wunPOPfshwwfN2FMc2y0OM43ofjcY+oL9r7JvAAaDhFuTmXlPvUtjc6C/uaSxc3TT+p/8hlLTnrQIcadHN5RSNcqJkAk8G/7srWdF5V+6ZJQR+ZXp++V/Hu/93sGcb2J9YmmuXeebZ2itsBBZ4FoSrnryAGGAHkNgkJpaCzXqcBuT6EHuMrAvJVI1qjYROfgLyAjM4GrzANAk9ZZWXlv5FsYGRq9X9nWkuRUOZAJCADH8EwE8NTegRUcQnhkIjGHjSB+EGd4eBhW9gkpcyOQTeA5xBwnS0TAUAuZuASwJmwUkKiclzAZ4GNPjW2T2fKbc845B6wH/rJ40BLsRcGvfe1rgJdj3OWLeUW14CxVXG4RW1nkeyB+iQF6mjDhmWBFGGRZmFkCuj7JqWxWQRIjMvR1MHQsrAoZQFirfR7xiEc4Zd76MX6UgXZC0qiXs6xdvfFzjLFFQdYWBSkpSkkFbcs6JKEygRVcRTsOCY/RAjwBS9p4gBYUKJcgU2QWy/Fz9Of8QBMsFn3hbF1Zxc8JISvMZ5e8TCysRnmJEB5eZzfSKmuL/eBmfBDEFeHZOXuqdagPhFTlOBXLli2jBVOENYL/hz/8YR4jpdQfBUcACaksa8hekbGM1mfhlpLleRLGU2IgY+EwFLdEI8XkG9/4horEtet1KqaVVkWVkRKPBsW34UVYSRV1QEa9lUHWbGJakiS//du/HZ6bNiIevctTLUKfoGaqlhxOVZpIoVf8sox5SOVoBkaXwh1VSXQg3J5QDR+qqU5MZ+yD78o+nlqaOK0ideQuW6B2TnbZdAdHQt0NB6TR53CrJYcNzBtqHnrI2OZxUykJfGuuXfB/ojNvcOCelffdfvN1G9asPO+prz7t1Ida4rR16zYtOU1FoCsuScQIzm675BEVV4kugpPxsyZP+U3+y+RJjCLf7hjRFy9oPu0Jv/LYU49asnDAYq8JCqbXns+idJIn5v80hxJMZs1q5odUpCZl9bACXns+JG9IxniM11jtnMxsufpJbYFkAa0GVALBc4+R+w1QUiRYAGCJdAvlQ2kis+2ADGMBxoYhEuO+z3ve84B1YTyRuYI5wASvaKSGgfknDtqyyRgQh2kyqxCmfFsJk0F2JgGM74JlEA9gBDxFRp7yW4ywav6QFlGtA7Fd3lRPaBfckFmMBPgODw/D0CSRCnys5IUnSpd4Ex2Grg12cHX4VJBiGbFBVBAnen4RwfhFMKJAODyMFkwQYBXhyIuc/DqwEg1Ab8QaeAVPA7lW5JnpFnLV1/lcJo1MWQCLoB4Jk+hT/b9HxBbP/mZRQEY2hAuJPe0+h5ny2mE8RaK4WQzyVkYGyP2yvxjyICADmixb8PRUNYNTDZ8btleFJMk0TMe5shQQkkajLEwUQO2U5fnQboeC7ZAgSgeZkvUSYUCXQhQfcz4ihT3NUu2QJ2XpTtSlxUV4eomMyoMPyTnzGpdJBnkpR/U2s0VpdsKUI3NpO895znP4DJxqlsk0hFTNNAQB9KZfmNEsH1i/Q+ckFMEtLgIoBQJjXvEes3FyvlQglder9k62YBW/iLkZysUtpwtzQwD8Pc6JmGClxfH9OBuKUjvl8Ct0T6NiBI1blZP/zD8xNIAJbpQy+8QIKLMwdWA3LbC9Pu0mozr5gWcB7dBVoGyAfaTV6Cwaas87Yb7lpemN5sSu4tfXF7XIW6+/+Uff/vqvP+Xxp5w8vGD+kKNt+rodZ3oluuQrwPsx7lW4Ht6t24FEejx5eZh4l56l+RkPpRVZihd3/7spFqhTApITsIhEJ3l6GRs16+uMzB9onfvExx571Px2o2M7jCzRFl+Hjxe134JJ2hm/81dhsJAWXz2a4S6/gJEdk97WxpDsea17sZ23bJ3iILJA4AwtCDAKWEB5ASDSMKpII7JGcKEWMMi2LjgjCPzCbRY7WWYjuVUrphTyjAGolLl5CqMAMa961avAYgPknBmzKNppr3MSbRlU0nKDQwijdbtsTY5l7oCU+RnYCBlRIxXQA+FxYDgbsLhBVqAtHmEi4CK2X/nC61AR/wT0yXl5GldQSkURFytRDfoXEOkKAsTSgmIwFobQoRiQC9ty1iLRuyT3S2BLYuwFD3ymy+KZGBonM4IQYI6/1qcBbawBxlnPQwzhEDJzkKNIRcDgyov7JGzGxhi5TDNZBEK7SuQcbxkqdESvwlBTDIayEy8y1O/lFgKrXW9729tMnlSMIC0jiwwgy78yUySG9TgtzF5mGBmVY2YPEw9BJZXbkMFTtY4ibv2WWXlUSVV+Kkx3aSV0UQrij3A8ktytSsKlV2/VB7cipaKavFQhK7X80tqEiYszI0c0kVHkjthl7SK3hLur7pkcM18ha2aviNR7G9z8lq9eshwTlgmnQnnxFrIRcMgimeniSvF+NWSNnSLx1C9Wbq3XQuyilwlD9TMnL+clXhHbhRW73ehlCEBj0WQyWR3YTQvsuJbsZgZ18v3cAvpuOzL6HNLusPg+J+468aphp0ajmY7BSE6HyfB2q29kzb1j6+96+5v/5NijD9f/SdZutsbTuqrklqT9KfEeLBIlm6SXwuQVvVrRGesKJjrpyyRFnPkZr5BWu9EsAEGa1th+lRhsj4xQeqRHsl29yL7Iy6uXHir8RLvZPu6YEyfGacAz8ZCPIkESOe02mexk3e7c+3hSiGLuBbe0nq3YYp806qRtu3CScUGvbW9iL+ByH93bA05yq//UFjhoLKAVZF3BdGjeUh8xQFIgMD6JZVpGN00CxNG0YoxqG/6EhOAnQAqwMASglQnDXh5Zei4yOIvMWeQwqLF06VI8gQxD/vhkmpwKsUF3PgZYw/khqhZtUT5hrEEnFXnEO/VLM+eE5BZNC24S5EoLEzVmeCA/bT9yTzioJJtICY1GA3+8L5KUbRLCRIxf8hi+zSPEWZ0sPM5Gr0F/AyIMSAZymp+RFnHkKz7fQlqW+Nthb1gdW07dy1/+chiUbbOQmfksAQzN/AB/CtFyIDIwCCbTJsHZyP3w8LDCQsPNA2enpdzlyHLWoUsYtmyxsoLCcXGDCW/WKBD8tAKgFM/It9xyi2kTwNfCoWXLllWcEzTBc1omc49k26ifFHFJGL+ZQ8iTb3sD6MNBVYHVZ3WSM4yswsekgfk9edGdlxtP1ZCPfexjfuViOIDb6VE2I9kquWtZnBzrvuzG4RbyP625UqMqZL1CZoIyzxzZS4+MOhogD0F2Ub1FVihpwZXibNsQpesgklTYhgpK0JouTKQiJMsI5ExzIHgyCz5RMSxodyZnrKus5Fjf7rIFaudkl013sCTUwn3+XQ+ckH7fuBGS5sR4Qu6p4XvDtYZa/XeuuOvuO25bONQ9Zsnh7WaaoHCSFY+i5dDhVtNH47XxXnvpOiAFHgNOuRcpIuUR/ONheo96ayMiiSvxskzLb/GTonqvmN7ZHp9zSCz4WD0iZYLtaXYrlHpG54B1rBhgDf2gjsxwC110ZLp+r//Mv9Lx5fg6UFvg4LFAuRWANeC+tSUGXGFERgAsYAhgGnSG3TUoQBCOB0cgHmnjQmmNjRUpADFoBRwjCzyHYCZjLl26lFsCZBh87cU08gVZ+DxWmXM2ABreBYRHMIhfdrH4xIQJYaDSMs4jaiwjIQM8x1PKnglhekUSA9O7kIXYZZmzjiKJBD/FLo6QuZeboVzru7BysRgHKTItUwZPcnIMzCDxuCxQgbZf+tKXSqvXKhOXhamEyZApw4WD7IeHhxkqwF9kXUnllmwGaxQBf4aEgQ57yfZITJZwLtzg18DuWf6ZUrFSlBpKVWhaFSpZz1RkM2WR4yWMtDlmpwLEUL7qqqVZaq/pRw2KA6ZmKi/tDjcVWM3RghCXdVc65hZUJGXqqVdYuar3iiG5ZYfcdUdBSKKJ8TxNX/RS7pEY7ZFq6lLmVrG5eMVEAM5J6EWXUNMjyfUbBLaHxIwf1fQ20yoY9mcrF4bS6qwQ53zrwO5boHZOdt+GBziH1D0lz0Rb9u4p3JF0Zu7ke96TVrNxw/XXr7j9tuOPO2posH98dFt3PLVSCce6rZX3bd0yYl3TJCyIMcliWiHZzXlfflH7U1Ck23S1ite2tVadNJvcP+Cc3uSipO0gxXQE4vvRb/duIiO0aX3Y1BWR7rZHTTKYoij/DanKMTsTpqtcJloTo84rG0qjpGZjrCtgwNbw8DDsYhjJHtayc7Iz/Gva2gIHhQVAQ5dhWqABsqGzW0jCjAG4Y2U5DOF7BUCtgKdFk0/jytAhrIAS8gC4HS0a46OzWA1YAbw0UcljMgG3Mr1IYtiXgnnkBYCCJrIgibUiBv4tr7KkpIyNUFoYA5PB3zhDTuC+XELUMv9y2FOc4d1e5ySTgUeyxi1WsCS4WvR3FbFJZUBEFypTRmBAZMJlPsJScQy4grAjWGbntzX0XCliVxjmhJVA5C6SzARjLgGj1PzGaeFdObm0oLC+0RwUITOrMs2eDVNqLnoxF+tZODcXYqamL93Vk16cWmR4vxo1F57Tah0Jd8dKlDLfqFzM5Kv5gcgZ326KwOW2Z6irKmFFAAYxmcmHCYezUj2m1cjQgCqqMmiP6pjmXOG5p25loUmGizgLT5Lz51mP+n6VV16L5VbBifdrM4kOIW4r3MLylKW+4QzlLkanFPEV4vp2ly1QOye7bLqDKGHLthJOQaPPB0+2bR21d2NKeS20OTQ2ePW1169ade/pj3hYs9X0bu9OWF/R4nKsXL3pmts2rd3o64SWK6TJDi/Q7B8UXXV6o6Z/Kdbz5LzIqNmKqRLLrsYH2gNjHd2ObSzp1/bFlCL5S5FUgnB5CqGSF1TI6jexTOzwK57FfcqpuArKqZvSX9M2maYUPdcgYbhQnXbfppOOWXz4wqEB69sKfjDJxo3pFEuT6TAT1JK7Mx2cXtUor1fCXPOp6WoLHLgWAAu0haVLl8LKIBGkbs2VxUIgiMviKAdAQRVwdgztR1OSSsCwvXkAIAN6MBXgWB6TGx5Na61AVBqgC41b+FgWkmd68W5BOiML8YiLYiW99ZluOSSOu7AOBJiLVLld40B4CCZ1lMVu3TLgC7IQIOclIIbkUBTmZVZlGvFwFTQc0ApzxGWCCMvOwptgQgv9Z8T3suXOmTPBxCIrG/qtUSmL2su5NyYUwYH98Xfp0wzBlH2h3lRiJKFsQFhhCaclm3tk5iBQNm+OnyMr5iKYbjkSlln1clAPUaql0zon6GdP3stw2hhMdp+PasP/JKfGxTmx2M8vOE5Zje4hD3mIvSLDw8OcEIVCqSyJpqEyawi5qudHMwVIGxVA09BegPiZKHcnXgGpOWo4wVxhol5DISMGB0zAJQmNcr7otTuRppKs0HMsBGnRi8k0ApFWvKYnLAk3RqbCZbI6vJsWqJ2T3TTgwZGcL9A/b3R8YvWadbfcvmLz5i1Fc9UU9Tvto5ccfcPyO20sP+HE45nDai6rr6QYGR3/+dU3rh07fLTPmTPcgzQbEs2Xu5AchuRepC0aUxMpXR+bR2KBs3/WRPU3x/gJvJIbb755ueGdO+66555VsiimJqTz4km/aaPIdncizeokRyjl5DcJWfzbiZIqVqxJmFjs7EXgbjrDbKTZ3dga33DIQHP+QL8zwfAZbPcbwNywcT3k5LtjukJv8UAVxhddINe5556LUseny3PtbO41fW2BA8MCML2lJnGUJ400FltOgYY480rAipR8ppPuyKUpQSdBLKxxuQUZtaYYy5/WMoFg0IdPAnAIVHCGGLjNTIJPqWKI2Bgw7GL3PPxqc4gvXVgNgn8lYeQoC/GcHwimIoP4EKASLwtiZ1+i8tSthKSSFmU8zYEKMcuUNYrsWKacb4T9uiJruVf4zH4rYSYIpcTIWtiVH00bQEYevy4EZVaZXuRcWAV9zlGgwi0/ypxnD0ge1+xknrKYSiKg1EKRSCJ5TrtDFYKgnCSn3YMB/PmNZu+9brgl1lw5Q1IlUQpmNrQs9dkgmqdOHjMfSLUQya+3ErJQdqYqVxZVkrioVpTwpPMpsky2m2HcCBP1fHbOZAhNaRGVQUwo4tYjyWkXL1+3mi2CoCSkQFwRRqy4kXF4Zs93NxU8CJPX6OcgLPSdVdlyriZ34fpbV19746pt2/ra/YcVUxzJJfBmNHOyfrS/0xwcmje/mK7gazTtUvGG37Bxy1j/Yc0B1cxKhrYfDbvIvnAY9FaptXMC0jilt49lW96J84b6Bwda7YnN1/3iZ5d99UubNm1cvXbNokWHnHDsMQ874wTJU7eW3BxHAPv1z4s2RYdixTxJ2qJSXCLTIoq4mfr1rBIz9STSpOf+n2Rxv2dzuEmdsO32faMtLko6pCy9V1OXVyznMK30mMec6d3AFNHr+XVOiH2oRmt8aRj6cVSI82qMX4bkYbQeLeYgSk1SW2D/tAB3wuyEIUngIGo+191H6H73d3+XQlqKHuMd73hHYIjUuIpFGm6FJbG2yuYQI7XW1luhFJijbAn0UIWWJaABShWNUVpbxkWWiYXJY6TZLERkYdm6w3wsGBPPOTGWbIcGDhICOlO9XOKBISdq+fLlZkp5XGgypJOpq5IRURHwrMz2SFt5WrmNPqQSOdMtYpcc/ZYVFKPPsdbFMDmQatcytCrSfuiZWM0Sj7Ox9tBR8VknRuVZ6D2SF9savwfuy4LlVLjx6xiEAXPkTAHa5Uc453AEmDeMUImf9lZZKwhjSZD6tAQiIzsZEc/KKKKal8jj6OLZNt/C/SrMTKzEqyTqbSxTnIWMleQLXs9Cs8NHrE1Bn4w0V3b++ecrAi63+ROr+7goxHDsmPk0zdAW85gloJ3KLBViltlhFkFAVGZ3ySgsySxzL4Ww8Bzz6i3xSBjxfl0zZR1yqq7mQp0nbvJQmLI4SJUFqMjj1oVM88k0dWD3LVA7J7tvw4OBQ3PbeN+ajRP3bW4PDS6caDgH0/sm/Ws3O+OtBZ32vG6r39gFW3j7cQe0Zh9eT4d2FY06vS4m27f7eHk4lUsozaF4Zq+7xWN2lwz2Wxo29oPvfmflHb/ctu7Ohxy36KnnPNuRhocsPCSmmAt+qYeRqFjZVXTQiU3xZKo0Jm/S+cWJdCp6MutCrBw59bD4K3ZqWdcO3qn3S1a6AQC6aR+Nf+kzMJNKZvWn3J7o1CKdF4B3mx7fq8tL2g5au29tBeaiLF26FEYpd46lrOpgbYED0wJaB2Tggoei8nMMLDiBkzgDFs/Yzgs82YBebh2pXyg2MIDakKIGBSkODw9jUjGTGMxFRhKBGEkFMkDJ3uZWyDLpe3gqUydlveY1r/HdQBtRXP/wD/8AzVsnU8mIm+TAIm3ZeIR1U5bs26CChpxBWcmLYB6FL2SZfoVb5TaY+K0wqZDFLTJXfhRJ4lc8dXyyg1W5EywsawI762yHMmSGEcCQCswI++rWbrnlFsxnF0+/r6SclgbHBxYs8/SUtRWKs5X5CeVHlbAS5HDm4pNpb764hVNKqh0KxgLkV3YmGXqrUNY3WHGc9OHAd5Rg1C5h9RayZw30fFRHPKkSM3GzaEolkWT25U+APtXoUrHATt0GB7JRk8vBelxuE/iGxuTu1BaTKi41PL55j15B2I7CY1E/yRDWnj1TDg8bEpUzY+kjNz7oe4tmFj4sPMvTyqPZOc/yVN1jDeVorJCm9hpNW0NwKDOJ0legvVW3Ilh9u1MWqJ2TnTLXwUmsJXpf2nDS6vY5fWteOlB40sHodG16bwx2Gv0T6WMn6YIO0q/vNrYaRx15+MqNTV8mS3MvjbSQwN7wgiZR+gxKIk+v6e5Ew5ccBwfaQ5s3bbj5+n+/7OtfOuno+Y99xNLHPfrUpz7prC1bfV6g0Taf4ljhlDRBDQzTKz4x5KXcz9Mgw1RMii91bKXg/ZMkrnhO/hZci/Au/aSPphS8gk8yYOJTWCYFkn8yiU6im0smKC4BXb+F2kawrGMx9At+ATf1qEyyW30dxBbQUqA6MyEQqnYBy/oYnNFNiJZVPHWFeayVN+t4xRVXRGuC9ng1M1kOjUcAKIcHB7jQJntwLXPrTRhJ0Bhe9QkRowmWmcFwvA7gpoLmoVU7VWBTcAc2Ra85B3N8XBWI6dENN9xAO3BnFhl6pdq1GFmQAdYkNsGcIuhLI3K3VRpapQ5gysHbWeaS0NfoO2y6w7TgoDJlRn4F8FqZN2AfrFgDgamYXm7kD0MpBQ4MmRH3kkWMggCp9bXhi85uYflycXXFz3jGM2ZiKB4TskG02ILgKhv1gzPZYuYkRHKotGPQRPZyE+liLscnyHdaTcupZpe8TFkJm5xR1RkcBz48d5rZGdkv45DcvAHj0Igu1P/GN77hm/dkw8ecmE+IXnLJJaaAzK6wjKMpwu+q5JJvTcQhYwTcLNSU405JvlPEOdOdDdBORvbbaPsaKROxD+9LG+9lhdKlFnHj+V0qOTJ+3fDwMBv20tcxu2aB2jnZNbsdVKlSp8k38Bn4dmtkdGRb29KFZABQwDoGC1XH0yb4yQWc5lO6Vmc5Emag1Xzw0uPHVmxbu3m8mL2YfIUkwF50zsXch1ejpD4mNTF/qH/r5nU3Xn/9pV/9/xa2Nrz4t5617MlPOPKwBfMG262BNNzlhWKnamH6QCGJi+T38z6Kx/Fq0oMUd+UfSYq8U9w0L7CUoOBqTqY3cZnRLOFkL4+35y40xXgy9yxDerFlVt4QOnrvNiNMUNdll10G8XhJgA4GjHcBImTOdaC2wP5uAa0KgLaYykfcOfCQKKAPx8eHn6faXMINzrACAT/4wQ9ChGYqli5dKkbLKre1sIZUGpfh6o997GPgOOfH4jGnb0GHvcRlA4KhbiEtuZs2geZhFCv1QT0wpUwJahuNhntAcFDPd9C1aBA8cEyInendItPwbf0HsnP83gtQMzLVwVL/ggsuMPzv8/CAl4MECM+GDLJTwuBpB45NgswCwrKPPm1anBd6MYtyNM3CqtyAigHhWg4epAgxg4zEK2/RJrwrCgus9I0RMmd/L7TL1nOrGkDJ2TnJj6YNKCPFylugiCVJM6FwAsDfppvQE88ElGmo8EZkJFPhEIlzQgWKiAmZc76YKHoZmTOfKaNMzCY4K7IcM/cAz4QrrhGR1siXF03eu0UGgikpsvG0CePS1ggcioRz4vRhTpTy9Xpy1HJMFk0rgEbq9BeXvDRe1WCnzqgkRtit11y92VXs2UtQjqFpvs0J9RKWgL7vfe/TJ6iTqpPW7WmZWKqg5z1a/2bjmeqhgb/61a9WQ6iZ2daB3bRA7ZzspgEP/ORaZmd8ZGB++/CFrcVDnXtXr+7oV6fQdqPVnRgd7BvbPNEZ4ZIkc9hU0U0he8pOPH7x4Uc3x0yXFGBfslKfkGjTLV7NvoFBHkvjkksuvezSfz3jlCXv+sN3LD1pCR+oMzq2xadCsE5rhbsWdKdkxUdQwk3Bo1i2NdnX+BPOCshf9CmT8UWqyk+xHqwSt/2WaLOk3U43Q0j+2euoKl3u76Lj8+vyDvAO1hF7OXm7B/R55zvf6QWpu7RoBE3uSWfIt46uLXBgWiAAil9HYxm4BaC1iz/6oz96z3ve49OH+hwXKKOB+AWwAETjmlwODoNvOFR2kuR2BD07nQIZvCUJdBKIfBYjSmsJh0uDfdnLXiZfn4eX6hOf+ASYYmQhMw8mKGE44BswtaH/4x//+Otf/3pzocioU84IQ1gQ0gXouQoIXGWCvRGOnocW0fO88Y1vZL3//t//u7x8yxLechkg36msn//855tJAG2pbGvQX/7lX5qWmYkDhPepT31Kp8cjeu5zn2tZUZmSoSyF4tRBtyzDdSnPY2QT0QKg9BUOfKIalJnksLKQJNWVHe2EkYRBdMg8ine/+91/8Rd/oXpkPjmADyfBNB3ZGMqCqHPPPRdl9NU4CJBcaSIjoWqmygH0HODMJPJS9BxXK9xM33GYy08rYQxVFZSV+LncepXwKz75yU/yNLhSxDjvvPNC2vAEgonqqn3xl1TsiEFDQdOSktDL7CUXmsCEmcnzVH+4uFhJoli56LKIvOYiqpJSmiwsu7Jsc0m7CzRUs47xve99r+xsvpLjn/3Zn82UL9P9r//1v6imxNVthV4p0F0QoE5StkDtnJStUYensYCBA18z7o50Tzx8aPGZR2/ddkSaqygu4J1fccQRA1cc3rpllS8zJjzfKT6NzuOYSKGxec1+PVmC+eHQJKLtl+TWzbYH+hrtxoUXfurSL1/xyBMPf8ebXvXgE5a0nCLsgDCzJdaOpW0saaVWkTr5HVikt7p+btLx2c4zv+3Tw7hS1jv3ji9ck51LkiVIyap+2JQkBdF2wXKaqYBH3jpeCfpEPb7hq1e+8pVe3t/61reM6XJXZuorpxjUf2sLHAgWyKA8B2glDDdYaOTgLLsjDIEbmo2RS8DCU1cob2oCmvzTP/1T+Inj8ed//ufGs5ctW8ZFQZMboBO9rVFx3LCFHHwYLkQswSpbECALtvk350IY0A1cJo8Bb3ANpoH5zHOWOcCavqVtRBZ0JrB1MpwrW5C1bsyzMKC8ln755ZfzqcxUwHxGZ/PTzFCMK4FrY0BFFxfyCGfBMrEYQvrNl0fCmSACYpBF32JU3jgIUAiZEcNBHcKAF7MjjhynZVLmqadiSbDelAg0zNXBUxEwcpaTzY2ps5gZp8CvTjvg3cmuzAoftoJxAXrlpW8E3C0/I2eQ6TB5NfZIYMUmAZ0zh7KyFDQ6zqoAJQ8BsDZpENllqcoJVTCFa8pa7vyTl7/85eYZlEum4U5wSxRZCIab7ppnkmULSouFrC38x3/8R2nJKWzKouyDQbqy+NKXvmT6hQq8jiivnFE5oKT4OWq1ymxTYkXyym05YYSJd8YZZ8T7xbwiq7oiJgj4YyxsdsWKLIqozzw6mWZWb3vb2y688MIvfvGLYv7qr/4KoKdOrh4kpwLbfuQjH1G+nDF5mVV47Wtfy2+XpFwimee0AQnlrrEIMBGfquz5l/nQWqazGG1a/lK58iONkUnf+ta36hOIrUT41UYfTPhoCDk79ZkjygIqkoKguMERhsoEmWEd2B0L1M7J7ljvYEir6Xrngcxj8/qbQ4ua4wu9Eop+KrZ1NPo02wUDfe308ZPUznMHobNoTYw1vUC5IOFWVA2WJj0cr9sY7/ziyuu+87WvHX/YoS958TNPfegJE51tY6OjOEiRPJ60xir9j71A0Z9M9incldKbthBgMpfsj8y100h8JrkmNeQzyWkn/0hWEmmuictS0jBZr9UCa6xj0Ql6zesx3/CGN4icK8earrbA/myBMm7IeojUKM455xzDutAezOTkLoPrZjzKLQhC5TCAsNqLQffYvsV/sKoEGIVCoAogY/ny5bFITCSc5+BUI9xlHFbOV7icRdzib9WT70LwPQAUqIWHU3FOZAffvOAFL5DcKAMkrUVr4HwVj1zgNXnE87gchvHqV78aHBRAlo2Qs46A+BwTQlZus+QR7zeuHF8J5KfUByXBTet/Pve5z8GpUBp5mD1DecSV5JVb9rftB6DkgcCpFuBxKiBvWJOVCE9lj7hhvEcZMTsE/5znPIeTWbG/RyysKC3ZglMhZj6DJPigxApnt9bY8IhsSfKJW7bNdisLJolZl5i/gj7/z//5PxwP9md8gvEryn4RHTkJNmDwjnggciczP4o7ikwYiOfhkIdedOEPK3fTerB+WQV8hoeHWUNxM4UqJ6Gydkse4mHFUIrb5dxefJz0EOXba2dZk8cMjKxVXZN+KF2Y8DpYqTdJ2QLCHCTT8l4lzmRjNzWW+lgRRiljRetYM6noOQOO82acMlvJnRCgAarMio/wyhEl2ZAxPoY48NmUF4ac8Be/+MVS7dTiQKIq0Fe84hUf+tCH8GRk/kDMveCvlTF1SJX036WXdSUhbiq5jWR8TtWJkTVAhuWxKHT1BIGsRRoQ0aUI2EWjRvG6yyVeMXh9u2sWqJ2TXbPbQZVKE+YkjAHu8H6/3fDOFU4onouSHIA2/6KPZzLpnGilVmEFsm82rO+SlhMy7csscTRDYiDr//v8F7esv+9ZT3vyOU96XLNvzB56nT8rewkWKaf8hKm/2Y3wNG0vTwLpn3I2EZeSpv6rYLH9pyi95PPc/4o0OS46vny7w0C5f9zZtNMyT3bvdoeHh3WXXgCAgtUpVjjkefZpU9WRtQX2awuo9hCAsW3vfjA0dInGFc3Kr1YA/VjybsT9sssu43IYcReZFUcDTFhrIQZQNkIMhBlsFo4LZ1nAYRCVhEAGz8S4eC/IgE7kAn0CwSGG33IDB8sMncJecKdVW0An+GhcvMwK7DPAjJWLswRZwtAcG/EmSHGmLGcJegP7rImCfgxdx/6EyDSrxjiEd8G4EvrNj3oDOhAEOJOfvujLNDizgFwAUzT5Eako5SPiUJppJdMCUCbZDJTojuYCMdlHiZiqwp++7M8s8JxC0X3JlyShAiM4Fom5IHtOSO8CIWZUviCyfLlJICNh8CSktBSkF+2UoH5SUVqwJAlihsoaRUBZw5F8VPaPpU3iiUoS3qP5GQTlJOJlreDkDoVD8Ga9yI95GJ/RFCgOVFB5fNkQaC6Xe3AD7rnKVqzFdITZJBcj8BOkZQpWwpDLrRIKXHzxxbJ2CZflEcZK9VB5DFcRyWla+DACJvxJzkmFvvdWjjzAOPk67GnKTgWglNIJezKpgBJkUh4jyB585CWAmBOFgLm0Ke4ZMRQHdZQImxCG8WWkFikX1UatlkpMrzyzxBh0kJBny/KcE/WQtQmpuGlqRICp8WQlzYezxIxRIsSYiS2xGZaCLoFytZcE86VLl1rnppeQqRydDyFStRQjLxm5aKcaKC92UKMU+kzZ1fG7bIHaOdll0x1ECbsTnQLgp55l0lHRpyfIz+lwAJdapM+aHLsIXyD5C2lrSuHJRFTFYIVroLU3G81NG7d8/jOfffazn3nGGac7OESXwb2xziD5G3kN2WTyIlmR9f34pfxyxPb88I/LM4FMIRD9bDmmxOF+0XO/CZ45x51NiL4slW7UrReAF5tO0HCa1epvfvObdfdz51xT1hbYvywAcFj8AwFAGLAI4XOzEvbULbgANUK01o2IgY3Mn5SdE5SaoZF+8xVLly79H//jfwCjuGlTkBPmgcYAMgPVhnXBSsO0FWwaTCAkaFiOZXRVbqfkNLYKv9pVLwuQ0bHCNmkQDId8yYuzhNJOfdg0oCeUA1GhhHXw17StQIMdAWiwSbwwVJSZCEgid+oH/+glKp1bpvcUdDPeLAn4WBYbDclpRzWK+82pBGRqJB6EheGMjHDPKAWkuihSppwpjDnQxqoQnjkKZYSSfdiftHKUBXlw4wUZfjZDQoZpFUFjUatJDBjRGA3Fg4/kwcev5TeG0jlantIUKwJUZBNjmRZQy+ZW0EkVBiHStMeNiEeg/rzrXe8yz2CbEyCOpyJgVVmEK4Wt0ucbKKxypsGcRi4w3SQAD/aiiy4yQyIGB0VMVNpxObB605vexK3lwAirDBRRfBUVyMmJikLnwVIhaIjKN0AsU8wrqSq3+Ktp9muZ5LGWTPmyJ6XUScmJpCzQmIZSNHkiKKuDm1ajyDiT1v4RQ4MiBiZRaVWSsAObmNK0JaNShyvyzHRLErlbTSdrnm1oyiy0pqxbYWmjxAkcBUoG4Zl4YkVONtco8Gc3lNliAiQ3zaXqeu3aS6b+y8glgFKhh3Y8NwvAVCesQlmcM5+Zcq/j526B7atv556mpjywLWA0xVCHVcL6en2QfqeYm4if5IFMOQKTzsn8Qxb+2bv/32uuvvqFL3jB+S958dYtW8bHDVlpp77eOK812OZ/wP3hVYTpUt9Z3NsdZ6XozTffsezJT/roRz947tOeqr+w3kJXmVybKVzSa/A051I4E5N/9Mnpn6gU4f/ITrel43Alae6PFXp5VmKiL65EPgC3vR2cntG8udEye/Ws9NV1PgBi1FnUFvgPsQCQFEAWDgMgelFjgABAis8ANGsdksAlRq97BUYMiaKEBSFXkxuwlIFzi+zRB0CRBfCk54mmh2HuK4Rha/H4wyXDw8O9zVOmmMMu1upEGA1kkykzahGAnGxNAYkgQh4I5hJCb8AiP0Euulz9lXkhQrpFDAB5lFWTF3XsW0AGDcORyPLTSkCODGWUnXZAFWJoL9PImqnFI/NrPwaZy9KS0+QJDvIS9svfY7TMYYcBBpScFhQ34G1myRC4XCjF/lw1Yfbnmwm4ZmGIVZQ4SWjkUiLsZtG/8qIXJqGsAH2xJW0vQ/WB8ekeOfqVilV5DhREz3X8+7//e5ttVJU//MM/5JmwSXho6pvFTvxP9ud3Oc1JlYjcwWWZlrPLloxI8kfWXqkMwvJmgZQsOyxduhQTRa8emgHQ27uNwuWlVPi4RUOS8ATIH5zlvlND+PgQAx+mUC6UZV6wnhPItSYJl4kNSRLyhxhZGAEo38IwYjAOXZSsSqsWqfzKV0LAXb0Krz4nLJtoh2GqRZNRRiEJPgzI2owWyVmD5AjEy9fQRm9FyrkraNI6rQFbdYaR1aJeeqoxC7YSKnFVQtfBwgZELHqkl7ABAmmzfXaoS02wUxa4X1vaqZQ18cFkAQu5gHtDFAYWTHWkBV2TMyfp++scAFPs8QUSq7iSk4AK9Z33bFqxatuGrfa0O2C49OLxDXlUje6CBYP3rb778q/+S3Ng6FBv2X6H0Ntq0uFNyMKrot3S+K23isTbOUyt3zKzUmyD4zoJOfK4maq0DiVKR8ehM4JdenufHRZfZrJDyj1OUJFWP6hDdDqq78frWPXCMRAVEsYvTQUqCfe4YDXD2gJ72wKBsdTk1Pzvj/Yi66jkEA8wB4iIhGBmkgoxvAWCIAAmAEqD09AtXJJhk7aDzBVMymhDGFYLAk8zTSU7cuKWWyV5ypQ5LMCRIIam6pf8gLUOCgSM5AhC5RCPBUhe8T1Ecg8CzcNGbivClG8xZCiwWwBlhZhlCCBH8vTqGGn5D9GxUMolxzL/HYaxlQsVMAEHqcz+UgGXsK9fYTSuubBiFrYiBi+LYyAVOwSAphqBMYSMw4YVZTN/xUSecLEkEQ+J4tlLT2YXAmQKCCTlSygR+JubQS9iREEUGlRVCOY5XzTEk7u8eE2qIjBNEnYIJqGCjLgr0ubCrfBxG0nIFo8EqJAzmmNAWvJjpQZqR6ZBFBAZCMDOAq5yuURe8Rs2YWcFSp1oWaqZlkVBJcJWYRO/lYRzFC/IJFeBo8nkrAlcFoz1lEUYgT0zWTmjHEkp4ikI9MKMnB+V6T0KtiIVuhKPNZ+qjbQUlwrNtGnLfOrwLlugdk522XQHT0L9N/+jf3y8s3HDxjVr1xS9oEh9sZ3urUMWLlqzYSv3I/UXuvrCL/DjrK3ld9y7Ym3/ppH+Tjr8VydVOC6F5Qoo3T18vHnzLWuu+NG/v/SlLzn+uOM8djpX2j/ftqLDYNXWTZsMXYjWCaS3CDclbWGJkL9OBPP1x2bDrvp2q+FDLID7zTcvN4ojEH33TM6Jp/t+EYbWukL9oDEqLzOHMxpt9QIQ44UkYLW097Hu20sCfbnX3vcVrCWsLVCxgDrs9V+J7L1Fpl24eh9VYoJSpCYDxMQshEiXyPitJCnfzkUY9IGiygmnDcuOGB751XhnEiar1usM4JCfTptFJZJgM6ngERBZoS/fygvaK8fsQjgElpDY7K+nCibid7azYjSX5Jhk05WZeApTzi6kfAs22526udQiubhQMogs4uUiBrfZsys/zVkrVoUS76AKE7LNVF6ZVRLl/u5cbz3JxLMEgo8c2TP8fMTBeY56hSWZRWUG3EMjaeOaJeu5P8KqUkCV20ppzs4ZtznSh3Fwk51msjdUm13Ug/zpjnv2g9xAB736et7km/Q1B+/buHH5bRtWrFjZSfvdU3xaW9VytMuxq52H3kkTK8ylr07/TTRGRjt3rbxva/OY5uCCRrOdPyFfmHSCs9JojA7OH+prtrpjHevBjj0uDdFxGdLMTKOxdsOW21esvWvlep6Jf1EQyaGYCsbXHpNnkj7S2JkY37pl46rVq+514s2dd644/PAjdqqT7S3o6Ix64x+YmMnefWqVBWHM/9h7Z4qZl0I1byMOmJUqhtmsmB8eHja74gXj9f/ASFjnUltg/7LAHgRMu694rzCp85saC999/vsgh16Vd1nI6Nt3OfnuJKQFdLs7HCLtf6AKFeFpJGbXlFJjpd2DJVuRbR+5zYV1YLfQfcTaIUbtnOxTxbEvCmPGo2+ivbXbuOGOzb+8dWRw8HijRYWg6bfRsjHwsM7g4on2Wt1Uci14Gzo7P83G5m2jnaFOs5XcFnvci++7x7nCBvknWn0+5zjR6o4PjI8ce6zVC4M25RmcGk9ffRy/9oYVN9+1ra95GBhu6KRgPpE4b7+63Bbng3QbnY2b1q24+dpLPvkh606PXnKE3TIXXPCqPP4Une/2dEVo2shMk2BC0e3mmAc+ED1+iOHXrfcHF0VYQHdpUew///M/26bpMp739re//ZxzzjEBHYOdkeSBF7vOsbbAPm6BfaFp9Mowe4+0j5v0gRSv13S9MQ+kPLuf1/4r/8FQaQ8GHXe/Du9xDrVzssdNeqAxNDBiM8fI2MTWbv9o38KB1vy8HIpXMNEcG20MjE20OyZSipkTsyfF6qK2A4bnDw5s8IWUMVvZ+rkrxbcYk31MhBQ75B3CKNixOqs/fTe2O24tVxrCGVx+2y1rN4w32ouaQ0dxQSwZK5Kl44rjavR1201HyrQOGWr+9Mc/+PH3vrnm7uvPePSjXvnKl59wwnGHHrrIPDUcjxhfl/7F71TqOf3dWfoy091JW+YjnCUXML+cO0pZWBnslBiHLdo+6xiZz372s05nd2DlC1/4wkhYYVXf1hY4aC0QTTKaT25EB6019h3FlcvOFgf63MGWC7RcxHtVwT2SESYu8se1VwWenXmIMTvNLjzdS2x3QZI9mERh7UFuNatZLFA7J7MYp36ULJDaoi0P6a9NDs2x8YnBdprU7ib3AtwvPmGSWqztIJyN5HjYntcwHzLQf/ojTr7uztF7149sHXXkFx4FWUqEgZmT0cWHNG0y6XNwcCwGS1zMuPgq1mCnM9idGPAF+bSorEiZhEkcUloSDQ30DfT3/fTH3/v2N742vzny4uc/6+zHP/yUU0+ZPz+ta7K3zybHgjjRF+vQSs5JKThFU/2rb61Gze1+Ssi5Uc+ZijwxbZJT2E5jdsjFE4s1Xc6FvOiii1asWPF7v/d7u79YPGdUB2oL7O8W2EutcpfNsq/Js8uK7GbCXbODVL3Yd9dY7YL8eySjYLJHWO2CCuUke0mGvcS2LHkdPoAtUDsnB3Dh7iHV0rZFO84bDzp8aM2a0Y0btoyMmSZJfknXlEZrvDPS9kH3xkTHDEuK5Wqkc7PGnbVzwnFHjQ9uXrxu87aRcd+J95BvUfgXia7VN3DYoQP3LOc5pF3uUxcezSOcibFyZO2WzujWzclxKWZO7EQhCTKHZPT3tztjozfdcvM3L/vqUYf0Pf0pZz39vCcvPeHozkQ6dyVdE77/6Jp0ZlKwdKXvLe7oktGOSKZ/rlPes/1ySOKXNxJZBn8b4kVa38UPcfaLDSfiP/OZz3z6059eunSpDSp5j+P0gtaxtQVqC9QW2D8tsGf72F4bVPp/t3s8xz3OsFeLOqa2wH5qgdo52U8L7oEU27KqcSdWLj16gbVXN928cWxshBdi0wj3xAG2C/pH+/tGR7pwc9p0AtKnH05C38i8gdZDT1hw0gkL3Jj/6Dq0K3kYk8K30kFbfXdfbx5mRNLkTqR/TkXsHr3k0CWrN20e3bhtPH232HSKzHgmNrL4IuTQYHugv3P3Xbdf+q9f2Lz+zte95OXPPO8pRxyxqDM+1rEyLB1a5WgwlOFeEGinzTWZdKfTpQS7k3baDHsZiokXW/LCCv/Eii9HLvqgrw3xH/rQh/7bf/tvjpTxRRTnQk7Ls46sLVBboLZAbYGyBaKn1ak6EtdxI5WZ6jJlHa4tUFtgr1qgdk72qnkPBObJWRjv9I03FrUHHrH0kFNPOjk5JcXMScxKDAz1XfHleTeutjvd2iwfhAKci1OD+7qtiU5rrMGPUc84DJWpCJMgg/P6htrjjYktHjp3yzbvTndsfGyTIy4ffspxJ53Yt3VbyiTlmGw5wcHhFi1a1Fqx4q5rfnzdz394+Yc/8BfnPOnXHDfvdRLH1adsknfiRbPzTskeKrEHLOs4RSTepsLOc7Qn3iGbPqPpq8z2zS9btmwP6VSzqS1QW6C2wIFsAf22QR9Lgn2k76abbvIxk/z9kHqW40Au+Fq3fc8CtXOy75XJviURf8AyK5MWY3aH6Lp9HTH5IAn2p/912UONef19jhce9b8ogDgN5rsQdEZa3JpCo9hUUuxQSXML4Wz0+6BJ4jOKJq0GM7fS1/XRkr6Jba3GwMKh1oLBtL8l5RQrtHxwJa1ialx+zU9/8J1Ln/6UMx7z6IcvXrSA/+Tq2PRiYoZMnJNEH+mKxAfcTzJwYX+/yZ5sV6zyssTrxBNP/Ju/+ZuLL774tttuO+D0rhWqLVBboLbAXrFAjPUMDw+/853vfN3rXufr6cKRU7m/3St510xrC9QWKFmgdk5KxqiDM1iAk8HpMIWSIDCaNC/iKqA/b4G3It7TIiZtg/AQRRqFmmg3uvyJ9OkST6emMhBE0JcT0XBIim30ZkVMvxScO+ZmxlrmXrg9QZqynMBoaF7/XXfd+ctrf9Ed2/LaV//OcccuwX9q/t3+mGKLDO8Jq5Tl9quQefI24id9mKmvMsXt9gT7YYgKnENfwLW+65vf/OY111zzk5/85DGPeczsqtXv3f2wqGuRawvUFtgrFrAg1sejjPV4rZQ/bjh7L7pXRKmZ1hY4WC1QOycHa8nvpN42hKS1UsX+cvA/Uhd+hY+eJNhv0oQTkfyMyV0QxXRLs73NYivnENs6n3yF8DxS6vT5lL6++Q3ruDxI4ZjySI/wSkx5O04ZLv4Tm3i7Wv3N/l9ec/WKO259yNJjz3nKk2DxkW2j4TRxgtKOlkK8JBMvKhybFJZB+FTBKE3fSxtDZd5A69evdyDvhg0bvJNcoUWk2x9/6WUXylVXXWUiJRa82ZHiM7eLFy92rldYIvlvxaE3+6OCtcy1BWoL1BbYGxbQK3ojuKySzfyjz8y3daC2QG2BvWqB2jnZq+Y9QJhDuj6gaPd6q+1D7wB/+gpj4ZkUDktC/cmzAHb5AkUnnlBvs9ny2fiV921eu2GTfSSYFM5Boin8jOQ+LFly+OYRS728AySQQatRuAb+yietKLufe1Hsp+/r+9lPf+IUr8ee9cShwYGtW7dxJBKvRl+7bY+9BPIppEheSrg0RUFE0G6UwvVpIZ7o2vW4ZcsWj6+88sof/ehHN9xwg+Vh0LzfJOh+eBGbqfkha9euXbNmzWWXXXbzzTdv3Lhx0aJFTvR6+MMf/sxnPpNaDiBGw3UpLLUf6lmLXFugtkBtgdoCtQVqCxyIFqidkwOxVPeoThB6t9PlWLTb/eYitm4d3zbi44YJuKftJz7x3g/gNgedFtW2eAulDfDJ1TD78OMrl9+2enzbaNMWeSmavps4OcWSRGz0ja8ZGVyxypb5Id6FCZNi0iWtHWu3m/3tZrs/eStTLkKaFbGsC+vrrrtu4cJFjqLCxGb9ia4vzTfa/e32QLs77k6StFwsfd4xXZMM/AnfyTdS+geSp8QV+cpXvnLJJZf41Lq9j74Wcuyxx8acvnmG/RG180xcdDZtksN8FT7Y7bff/v3vf////t//+4EPfIBPcv755//mb/6m1QvI9kdNi5Ktf2oL1BaoLVBboLZAbYEDzQK1c3Kgleje0McxWu3BodVrNt951+pVq9d3fT5x0jnpNprjxxz3oJWrN4yl04LTdAkBkqcxMWH6YeV960e6R3b7F3hkTsP2EU+KaY60kKvRt23bxNDIRH9fy2cT0xRJAtaNxsDgEN9g9X1rV65avXHjpjQZklh6kpYqHTJ/YOU9q574hCec/NBTxsfT+cOeWaK1YcvYdT+/dmxsouP0L3IVX0RxQHFhkCLjdHJxgwtjw32zOf7D719x1VVXrlu37owzznC2lRn8mEyQhdN4i3meNBe0N+z5gPHMXofpKBNEFq3Z4mlSaPny5bEd5ZGPfORrX/taa71o/YBJVWdUW6C2QG2B2gK1BWoL1BaYyQI1IpnJMnX8lAWs2Gq2xif671w9+svbTTB0m8U2dm5Gchp8eWRDd+N4u9MYTO5GutK8iScOz9qydWRi0O6HfqPzxeRJwvrJLUlrq9D5IIm1VVO+R4pOmaHftHXstrvW3HH3+i0jnhcTLxI2fRK+u2hw86at3QWHLFi0aOHY2LhDqnyDZctYd8W9W66/c2uzOZgOAuvk3Ir8CoFMEAy0bVlpbNpw309/9K1rrvzuw0598LOe9axTTjn5zDMf45ORhfDJQUpy+H8/vGYRujhCjUpOhu6cdtpp5oi+V1w0PXfZslNOOeXQxYv3U633w4KqRa4tML0FNM8YGZn+cR174FqgePXM0oXPqHkMokXvXQ7PmKB+sCcsEKYOTvWrc09Y9H48aufkfuaob3osoK/kV7S2jfWt2tRYtcUEw6HWXCXPJJF2Gq2x0fbisf5FE+2h2ImenI60raNpFddAf3t0YrzbGRFj3kKCya538k+n4ezg+LR8zrhhgqV57+o1K+7ZtGZzuzV0eDelTQnsX+cLrd+2aiwt45KFFVzJOWkM9m/eOLpi1dYNnSPmDcyTsXmdwrnQYxQ5FftMTJm02421a1b98qa7f/yLG37lpKUvfOELzz77CWj6+wccROyfq9hbb3Fa+i8Ltd8EwlLTicsv5PexoUmSE5eedMIJJzz0oQ/9wuc//29f/eqmjRs5aWeceaa5o+mS1nG1BWoL7C0LVCCp20rM3sp4T/O99dZb7XPjWbn0Leaf93QOBz6/KPqdrQCZ3vvL51ks4vVSY3+lMPkGPPAtt1saZgOWuYiM22zDHAMkWIlgMyeDOxvTh8WskdmKlAAAQABJREFUPiinrcO7b4HaOdl9Gx4MHJpOzhpvDE20D+3rHxxPa6XS2b8WajUaY2ONobGJfgdy5SVQvBnOw9DA4DFLjrx11fjm0U220jcbA8V3SDg2rkQ70dhq/ZWdJ5ycIkbbL77XMdFdtWbtlhFuh/VgCy0XS3MZsHXLFErffeu22PQiva7D+cXpXONmc7TT3bi10+Um9fXbbmLlmG8wEsKVMkpb+BuDQwtGRzb++MqrvnX511/5vKe/7EXPWHrCgyz+Mhk0NralOCM5SSWB3TGFfOnngLmSxWJPj6mlZmNocOhRj3rUCcefcNqpp33swgutjjvssMNOe9jD6BtGO2AUrxWpLbAvW6DS3PbTBZb62E996lP/9m//BhM7aeM973nPgx/84H3Z7PuabAyYa0IOzFFI3mBQ+nzkhz/84RtvvNGtyXBfu4rqtLMM55jvgUTG/tRhqByIcNl0EeaQcP9uueWWt73tbVyUZcuW/fZv//YOz+s/kGz1wOhSOycPjJ3351z0md2+/v6+Qfvh0/FWI/A7zK8VW5fVbDkNvjNm0sEnGotjhLkCqX13us7pfdTpSxfdM7Z+k+kIUW3fMdH8Uz862RFsfdCS+evvsh5sq7i0pqvYXuKI38MPPeyOlaPdEbtbCu8iJZRdmssYH+W1pJ3uHBnbJwR8gdEUjdOorl+56ZD5pkHSsrMgkI8OxUb9/gH7Tca/8rUv/+Ln3znrUce9+hXPO/qIBcD6trFRfU3RKZE6pUoJ5FXomG4PlKvQLSlDP67IyLZt3luLDl30zGc9c2jevK9+5Ssf//jH/58/+ZOFCxdGF3yg6F3rUVtg37WAbrHc3DIwEjA6q2tyoG2ZYJ/VhMD2761YscLsK/8keuZ9Vtp9ULA9UspK4e6773b2Cfs79cSvTj5z9jSH95QFyjzL4T3F/4HhwyzaGvm5efwN60PYLdTxS4Zst6CxAEHA1k3eoNlCvsoDI+dBlUvtnBxUxb2LynpRmko48Rhrflr33jeybcxpXV1rpwrnpG/xgrZPxI/ay5DmQRIGFig+q9hYMDRwwpL+JUdyTURD/+GVJBckXU1f3mhdP986LDlo/3aVWNNlndf4EYcvPvrIbZvHNm3cdC9a3gOXZsJ7eqA5tm1zoi54pN3uhOh2D1nQfsiJi9dsG9qwbv34+FbxTvlqNtNUQZoHGXCg2OC1v/jlTTf8+5mnHff6Vz7vuCWHjo85L3hMl4RGvgWn5ANFwG/0SkXEgfQTKibtCq+sb+GiRWc94awVd6z43ve/e+GFF9ofzz85kBSudaktsF9YQJOEdRwh+I1vfAPKHx4efsELXnD44YdDQvuL/Pp/qG7qk7j7hdT7hJC8CF/ZcpQiv8J3qJ70pCedfvrpvIs5Chevqnj5Mr4Xopj4nSOHXSYro3aZ5ttdZvgflZDkLmfGXHzxxXfeeafPCTzsYQ97xSteEfGkEsiy8WG0Sr9h5EzjlSqcJ7IyfR3YBQvUzskuGO3gSpKWb02MN7v9Ry1qD/W3jjq07aMlqRuK2Yxm59DDBhfP726aKCIn26/OkdPQ6euMLRhoLhCZWvakc1I4KmxoUqPlwN7BlgmVtKwrHe6LaXJkxhYMDZ147GEDgwPrt4wnToXJB/vtGpmY3z10Pmdo0o8oUnQ73ohHLR44/cED69aZThnjODV9mb5pUiVh8YH0eZbupz552QlH9D/r3F973JmPsFtlbNSnG9MMDNGKXlXIfy5J/J0E8SliDhcOmSrpus9e5EziJQV1rMT0MjvyqCPPftLZq+5b9ZnPfMan5U8++eTy18f2WVVqwWoL9OKh3BJnaYa9qf7DLRliAzf33Xff5Zdf7tTvpz71qS960Yv2rGBzMc4sOe7QbvphUz0PzLRJ6DJtKevZxMejHcoc+s6RbBbjTPtodrb5qYB+2Depvvvd7z7hCU+I79NPy3DayMwnnoY3my0gsoKhp2Wy70RW1HlgBAuPgk/y85//3BfP7rrrLvswy85JWQy2Ra+qh4sSNQ1BDpSJhdm/9lgqNtnhbe2c7NBENUGCsM2J8aFm37yFzSWL+vsa/YVnktwLQyXt/sbiwe7KibFio4ZI0f4D1jsT46Y73bisqmqaxkgLpiZhPP/FN1L4Dd1GZzTwvBEfExlmPBoTI0cfOe+oow6xp0TuKV36doc96uM3DWw7dAHnJEkVTkAC2ePj/c3O0qNajQcdilX6hGM8c2pXq9npjN654s4VN/7ogle85OwnnNlq9m0bGelMpGlcZIQTiHCRTzCO9MI7vqStEM3USVXIHtjbpKMck2JTIabTHes3T3/k6WvXrf3Xf/3Xb3/72/b22S6PZJ/U4oG1WZ3bvm2ByYo82donZd1h1Z0LAV5R/3dI3GuhShK3mabcpnJ8BCKVZVFAT6AZe233IKbB3zWtJBEZT8sSZmKPytbIt5mgzKESWb6dJYsy2bThuacN6xFYEldF8mAeT/OjSo45VSW+cotMTDCpPHKb8p4y+Cw0Hill39fi2rkMDNm0I1LamVJV8qqQFdluF8wtg/B71atKwjneTiuJyEiec4+Y+C1H5vAcs6uQlRkK7ya3CvN8i7PLLeN7AxojcKs4MoFAEEQMMeLWL/P6FTNtaw0CT11lbnMJRxaRMLKYS6oDg+Z+pj8wVKq12KMW0FyLbs7+j66Tt5z+y/uImYzUlB3kNdg6pL9vvOXkriLj5JwkBJzuTF84UKs4+MoSq4l20/qE7DckqrYjuBL9uGjHZWnkwaPYJW/lGM8k8Sk4S9zm87T6Rrk9YorIgjyFLTzbNsHHsRlep+Efx8nHHJ3D1Rq8977V37z00oUD4w87+YQlS44YGxs1c5LYps5Ck08ClwIpnGTfya6koC9Wp92vEyt47wM/TJeskmxla0/SMc1RFWegGbTzRrSB9XnPe579lKeeeurxxx+/D4hci1BbYAcW6H15a4ZFS5wt4bQYopygzKEcLtPMEq4kqdxKGDhD/FTnsx3g5mFvwKg34SyZVh7pSyXPHMo5igw4VbFDJi6zyhKKDIJgNRNNOX7aMCa9HKalrESWxQupyjGZ2KOMKXsJckIBRsjWzskFPOpNWCbI4WnJIovMZxZu5eTx7hMTkTmQ89qpQCSP36gJPh22UxzmQow/7SoKRmSog4nbubAq0/Qm6c2lkqnkvTFlnnMJ4xBVQrvgyOVaFOufRXrqN8QLNSPf/CvQK7xIrDAX2Nkr5yLhtJx3luF+RF87J/tRYf0HippAPHTL8Ui+yVR3kzyQ1GJ8iIRsqWn7kyKLhpTefI2+gQGfeU8JPG6lb8wXcyqTqqSPmiTGrphuSWlTPgk4+y69d2jx0J6UNHnTTKcJ+wj9FIuCuNiNkmSSsUmYQoAUTN+H9xWVxHvl3Xf900WfeNjDTzvqqMMaE7bvjxVjHC0OiM+0IMbV3yKrRF/in25nvnIKacIpC+cKhzThs49dbFGIN9Ho+HYlt7H4ZeyiT+4cddRRy5Yt+9jHPmYuheQHW1e4jxXWQS2OGtlb/aKaZrsgcGWsUE4i7MqUOYBeOH5z5EwBHDJlRic5ZqZU4iPrHVLiiYb8WdQIOJbUpi/Dt8YLytrhvEOeZalS91tcoYi0OSP7d6ElV5l+2nBO4qkeA5O4KsQiy5SVp3EbBCjdxm+FrExQedR7Oy2HIKs8yrcCsnCFZSLsNxPkXIKyNz4TzB6IhNa2uewbcRsxs6QikgNdTJ6YNxM4+uijc/FJNa2Qs3DL2UUgs8LH0ZTeoTvrqGSGkWmuum7Lj7JhxedMs5xz1yIo/QZ/WZRzyfGZcwTKNJVHc7kNtspLA4xDHcJK4ZAEB0qVW4EkLu2ISQUKMSchgVtJIjLS7rJ4u5xwLlrvyzQ77p72Zelr2R4QCxTtzXvU3wTmWz6/LpSyTjFpZZf5gmK+pOhNJqOtrWp2G62V967dtMVBvWmmwi4yTbgs8+JFh/pkuV0hBTduQvHuwiYad3Id0ivWgb+y4D6kL5gUOZWYJIZFSh9vlJwnhE7fQN5u+iRLq7V5y5ablt/y+3/wxhOOOw7j6G4c4GXr4IbN2zZu3NJq82LCu5iSLwmQ1MnX/eTOsUXAYIqvzk80uoY6kyiFqPcn2RfuwnT08pLuM6c0D/wZmpc60L7Uw1oubsKEcWzNtC/QkpJ9QehahoPNAps3b3Zw3Pr1603lnXnmmXZA2SX8i1/8wmc0QKtsDUgOwa/92q8Bc8BBfoXfcccd11133fXXX49PJla51W2r+e02LhNngkrAjlgb030yYtWqVeg1Cs0ENBH2AdNHP/rRs0wtkiR1Hn19V199NTGwKovtJCtp7Xh2cncAOPTQnuyuvPLKW265xe3KlSs5JxKaxuRIeEoAWWuSv/Vbv/WgBz2oIm3lNrXoRuPTn/70bbfdJqEt9S9/+cvl+8tf/vLHP/6xrfZmSs8777xHPvKRbFhOi5jZr732WsJQPLQIAslZm+KGMDK0jYzKHGYKBytSIaCOLBiHJOB7GEHWyuiYY45xvvlJJ52kTMusnANmEw5jOknpxBNP/NVf/VXCZOuVKSOM2zXXXPPv//7vdg7I4uyzz374wx9+xBFHEEAqv+RhBEt3fvKTn6hdqkrIJiHtfKCWcR7ykIcYPieqfSCxyOfZz3428XJ2ioZJv/SlL+HJMpIoUzaX7z333KPQ5RKVh7eJ22Mf+9je4w2CXo1Fc++99yp3ae39I4bkcbGMzQ9Ac8569kCoiSaSX3XVVT/72c+oQDsnLogHweFvupgkD7PMzpAu7OliT8zxQU810to1Tnd6eWUgUMEYU4wdU+oMsm9+85s/+MEPJGEle6gU3Ox5Ket//Md/xITwjCaJQCSJMhLWQFhedps2bXKby448tusQybLk2XPpfXrFFVf89Kc/NTCnLFjJq1HRaIB0J7xapIBUPN1RbjUhmEqCGM3y5cuZWq1WMTJ/xGqsfkzx7fCEA/nqvvR1mOQ6KRemttLM2dAOLM655ywO1EDtnByoJbun9EqvE31D6tKbzfHOxOZNvsreLiY0ikmU5sQhh7S2meNoFEu2UE+i+Imxzvjd9226+Y616zYk50R68wl8Bl3m5BB+o3vMkuZ9G/gt6evyae4k/iV8r+9re8eOJ2L75dMjwWJ3iRH/qe4qRRY9V/IKAJTW1hFnlSQh0PIRfJvelpP1mx133HrEox61ePFhnXHZmYSxrb+5cvXGu1eu27BxxGdYxhMbX4QsuE2mF5OviTQ7lF6uyXvRG7qsMwOKGCZ1XmOjY6NbuuMWv8neHM8+eCWvJBVm4boN9vcvXnTIYYcdalOfySiPjP9s3LjRG0Unq4M2egdGUEPPq//VP3oD0XofVKwW6UCyADTAOfGSfs5znuON7oX9rW99C8QBZ0Fn9TAuoOoRj3jEmjVrgEKvf8BddYVXfvjDH0KTQCcfW3VFDNup1VAFfAZeQDxA5EwWkx1w6YJUeAu+syZ5dDLQFch41llngQ5nnHEGmEUGkb2sAAvJiWFnLUjtsNFAGIjBbogQkgMNia1NRXKN7gtf+IKt8NynwI6gKjvAagATqSjim3pw9g6dk2DokyPf+c532ITiEJ4W/bWvfe3rX/+6j2DgqXXDOmWgw7acMdKSGZblJpFZz5Z6ukaDeakMrkH5GILvkQsaT3stMG2MknXQLU2/973vAaxwvxg2wQS9fgay9BS05QHKJTOhBfF8R4UjobiZl+lmgXoYKrt/+qd/AmH1aaAqzsEtpFU3aOqyB51lArgjkBGAK2veI0BJZTl+8YtfBDrxUXPKzolcOMy+6MKMr3/969UNzBW6bXuqDT9KtxmqqcYSqqtU43pls3vKBVUul1xyiXhFrKJyCz/3uc+pIcodJiYSR4JTOnfnhElV2kDMmoOdhOqVSqs0wwgEA3bVpcc//vFcpmycbPAcUEASMiPnECuVhzz4uEgbTHgsxggoReuLLrqIxf7zf/7PT37yk4OJW/6bR4zDbViyZAkLZ/6VAH0Vjdl7lZ8b/Ju/+Zs+lIyGoST3y6VUsopDA1eLFJwkCKJYtWsaaePKjqnVkIiv5DLtLbeKKyILVZ0u0qqrf//3f6+xaH3sYExB41VMkTzkYWpFhiDk4eGoVFwm9mFkly6CebHiV+gxWGza3EVSmVtCNVVInVRbRJLHFQ6zkkLjGDeS5Co0E7cDIL52Tg6AQty7KqT3RrqaY+MTa9Ztuf3u9VtHBzqWd6U5E1tOxo4/fsnGbdZa9TfTlhJuRPrPtAM/4UdX3rBubOF4n09naMW2l3iRx5sMxOfgjA5sba/d6tDfeSmX9IrC1ZRHE1A2P7NlZHTDlm2TAkw0Bgc6/e0+rs5o0R8VeZlmHbPlHXuLwDZu3bZ69fptI3qGNJnTaKVP1HOr7rp3SzO9+xaEbyMHcOXOe9dee+Pdd9yzud2/2H3h/7STDJOvWn8Slp+8wnOimU38zgDQMfsCS6MzPjFmUmfj+o2r77l3/drVGzfcNza6zVHIU9typpLvC38Lz0TJcKqsmut2RucPtI847JBFi4YmOtZxdRfMnzc0OGB8SPeqtMAmPTLBvRS9TpjP+1WPrNd2ezB0jvtCoR2EMngZgyBe+aqi17xh1C9/+csgCIjmUg9VQgSgG7QEfztv116pAH8f/ehHQUPgVVoAGjhQkzGUHPL2yj/33HPPP/980LOCWtCIUeGB47/9278FEfAnA1ybmYBl8o3DfEAEg9lPfOIToQ1AsFxMmPCR/viP/5hPEu0FmBDABwejqrwsTAzDkxxA9IiQnsoOugKAxKD0S1nxMoV0dWoeoSznNW1YQvGkYgS/WivA93d/93dOKNZ4oSX2yUoFBzH8MWgeimUKdjaJgSbMwnrE5rTwbcBQ1iZ8dvAiu2klKUeyJ98GUHZUK08D3tKx6EYld9FOLnDwP/zDPzDXr//6r7/mNa8JAjLIy3fuOCcQW4Ddl73sZTiU+ZfDuAH9smNAKnM2IN1MAPdzjXCDR9mT2WMZFVsxtUtCcJyh/ut//a8IeIMAKxysUDITAczZlng6Q0z4WmqjS0K1gvBRdlLRXY6gpwOgXvziF0Or8qK1tCwQ5Y4VsbGVI5lFgrwhD5q5lLu0eIaEkrsY4a//+q+VLAlZgDzxlEha1le/+lXSqoSve93rspMcBPFLbN7X5z//eTM5jEZfpggmJMeEeCqVOqOwnv/858tCFSUt7eQeTDTMZcuWKVnlq11wiTnn5VzKYVIxPkr68kJVNk9T/Sj0Ugn5zO973/toJJ48fFQBwsSl6UH2Lmnf/e53cybV5DL/WcIEVmT4BA0BpGU3WdMUZ3UATdTYoEGspIS5Xv/yL//CP1EnNTqlryhxkJYuGjvXTgVmosc97nGM0yuGFkHsD3zgA4oMAdX0PDiEXphoocpL89F94aP/mZZPL+f9N2YaM+2/ytSS7z0LdJuDy2+94/qb796wxWv2UPMkxTh8t6811je4af227kT61GFxHn/RPWri5jc2bRntDPgs4mKOgpkNHe9k31nsGwEGOs3BbnOgrzGAmzG6RNBs2cSu4V17/S033Xr3us1bi94ivZIHB/oHBwZWrbx944bNU3xMA/AsWuPdxsrV67/742vGOlr0EB5YgRvz5g1CMb+88c6+hsPGvAINBkqRPu1418q1ZnSa7cWNgcN1JBSQRbE6Tf+EluMV67pSvGkTYvBDzDL0Oxx5XtskyS233XzZt75x/S9v2nDfOvCn0T9x7FGLPKJnbLjfe8WxK5zT1E+yJd1SF9wZa02Mt5uGnRypzDnptFvNobQJsO31bzAMjbejX0OGsJGEeky/RoCgE5dH8c7YFWHqNLUFZrCASqUSggVe+Za4wMTqoVf7smXLli5dCv14fxuhNJfCkQDpwAJ+CGDEjfGCh6JMbqifYBB4YawRBjV2K17XgEC2xiBVZrdZhKjJpjve8pa3qPCgAAHMzBixNl8BHANG3BvTEXCG5gBmvf/977e8BEwHpjMfAS4T98YjOMY8A3eI5IFiQT2zQD5nAe6AdMCQLGBZuYNTbl/ykpfIxSOqgdSvetWrQCINDTYCBIX5DOW8Zg8TAFoCMd/73vcabwaYGMTQL3TIkgEfZY2/CQSD9zCfW2QgFBgNQ6N3Cy8yOPNKwsHjwyiCN77xjWFDydGEAWeSx1NDHqaG6E4el7kRWcgIkiOngmY3INgYs84HILa0jNiKVVoXFMiFgHHBOBBWpjPlJZ7xuTGqjeS/8Ru/ISEOQS/hP//zP5sMoZRINMqIs0oSSFclYXlD8gQwd/fJT34SwFXl2KFcW4KV5CQHRpWLmqPamFhQbS644AIVLDJV4koTQ5LLy5SI2iKJUmA0PJUyL1cNUcQsDHyrb894xjOgT5VEEuXOXBSZRd9pH1HwTW96k3I3h/C0pz0NQ5kynSzC1JTCXNHL6B3veAdhspWCIQ+NwC4E7EZs3oJSYyiK89b4Y1YPKlmenlJ77nOfy3WpGEozNAHFkrLTfMwezOKcaPJmC+WOvxahXMqqKRFeUMwlapLxJhoeHsaZ9by2vvKVrzC10ucHvvSlL+UGm6upyFNmmMO0CxMpFNVDOWKC/5/+6Z+qmUoBf50SR0v55lRRARS93sAlLbfBlJGiV121EQMlLi1aS+FaaODmRcOhykyiGjDgJz7xCZNmTM1RVAHIo5HKQr0yVsJ0l156KbaKgzxownvJfA68QO2cHHhluoc1ijkDb591m/vXbT2kr3+eOYzCkfB+AOn7R7qDncaQLx0Cqylvr4HiTSChMRQjYyk6zaYE4E8IudgFP7l9Pvawx6sm/Xo7Ntq3r1y3/K6Nqzb1NzlCUiTHxj4J66ig6dXdYhmYGMcBAxiGldZt2Hbrnes2dBb39w+2WwMFfcqw2+zfNrZm45Zu39BCfa+3aPpApIkZcyRtWgymA8PSfE5anpUyTwokKYqZoaTJZFz6M2Fr/4J5g/2NrTdc86Mf/uDbt916y9D8xgvPe+zDTzv1SAs8Wtyn9kA67ziN5SRO+9KVhCpUKxbXJeM5QI2xHcLGTknj4lMzesMQ3m8EdIXxcjJ+423kMroZY6iAl96WligrL7Z9SfValv3PAqCAmQcACCSCsQAsC0IgA+gHmheGbvknsAhHwpglYu9vMBHUg2lAQGEQB6qDFQBQT/kVoAbU+5GPfMQ2DFihbBdjwJAWPhAb9+YpT3kKiBlQUqaaAFbgAnfls5/9rKU4piMEiGE4GWjIrIAnqA5gkhYy1kYyASCOiSQEgLQMqZoUIom2A2xJwsuCY8gJJeMJMQdnuQMxxECTM9phIJokPMrBA/Ugy/+fvTuBsyyp6sT/9pdL7dXV+1JJsyPIqIwii03jiIgoLoDrZ2YaGRdwFPGjo6ODf5VB5oPD6EfQGVHRcQNHmHEcFZEBlb+AfxAQEWi7q+mFrqVrzays3N7y/56IzMvr915mZWVVQ1X1vV39Mm7cEydOnIgb93fixCJrZhK4BiEVMgNPFOi9lgXFkke+rKCsQLlAQgSjVS8+EAZ1QbessjwyLRcMc1+xnkjqSGHhYDibveSkV9xkoSqJgYMALZmNQyGKLwuQV5VB7bLGVhZqVhek5/GLFadTHu/PxSyyVgpP4cusMVODCmSvZsFWhQXcPWV1MLFgZS0BKy1NgBjKxSfGPoGV1TIySqP8oYyKHBUBNKcBi5oIKbnaVI8IMCS/cvFRaDM4GPwmD/1nbphLThVkY7lRlITsE5ah1pvrnajZkixy3DiAM2GY09rYD//wD2vGeuncwKiOPAwG+n/DG95Az1C4qiF/0Uoxx4EkdEWTkhCAg0US5o3ktIFAU9HCof88UqBJKEIG8YPiKQ7dEsCbxfKkT2SUWdDklpNlZnlqhx55U1w5o0zJ9WSSFSbas8O4LJrSmAmT+wRC0qrbW265RQsxGGEEwRiBCWbe5SKv9QJyVyNqgQAYuqU9xBhiq/gqQqQWol8S8IjYAkpHJI1TfRlKMNagxlWWR/Sp1AwzfRSzXKkpSqHMABwSgzmkK6MZ5dXgmTeKptdyi5IAFIj/i1/8YiViPBvgIM+rX/3q3MaGuF02t6VxctlU5UNYEEtB7fW71G0tdbe12lPdMBVcydthHUqlHdaCw0+iT8znPSXfdKOxd8+OQ7OdhYVTBkO5REydiuH7hINtptWvLve625ygEos98jIU5kOlutKvHDkxP7toypRPwh4p0oIWH+dGn1FR35Y9LdGFMiuij6gsLndOzNmEa3utPlmp6z7YLMA240Smp7sOlm+0I9uIxM4UgsqunTsnJxZn5yxbPNO3yn9gGDW8PorCNMlJUmdt17FGrXr65Mk7PvGhA5/8u+ri8ec883GPfMSNX/ikJ910403bprfFAGLA/UgX6rnIrthLYNVkCicVNBG6UMxeJ6yz9DQUlHreLHv+bOReOMcb5/Mt99GCUXxKdeUGePSkg6kusnKX4lx6GtDkfO8BHYjKOLQ25gstxqUwGaNDdUCAKVJwiWFpGMvvK17xCjOCZmZmYAjYDh8B33jJwXo0BtSBiT/6oz8yygtGFKoBZbACsNADytndAXtlSIqPAFRNHkO/WjsyA5kGa/1CM9BnwQoKMdgpR7gNWMkDpYSRCjQhBibGdKEfLxEEY4hXufBHI4AbVkA8eqBk6M0aui0yXS9AOYTPJQIugS1ZZLVkZUoIgIKn5CEzywTyQ0YYV2ZLbLBMwY1TkDwPTnM+IGatoSEVnpl47C/rCLiETdUFzT/3uc+Fj/GXMItBnzQDzNEDBfJ30aFBYh0OYTJP49ZqBKWGYaTZI/oZzQ6UtGZGY9A8VDEJC2SvjGAr5w8O6sV6Bk0LDRlcqcR1gE8FyYg8XBkGrZVaeD3Ng4kSQszaAIZMptxmsmAMDxVKTmRal2pldDEJPM0MFYdOSEgkOkTglwxy1N6EXYiJN1rS9WJwpgRiWH3xrGc9i6qJkWtTAHMVSqsk0XqZpgbseRSzKgqepFXRjHliMNS1CgVUllxrssCK5EwUbUMqXgtqLzIq1CVAmUx6LcdbxpUkX6+GeJeEfnMZvZs0kz2csvOhyTKjoV4GP1BOD2A6eW655Zai4hBQIzn1CQwMbd6LqZZ5LbR5zYacaDa+KByBtocV7al0v3i6spyeFgFhMrtFrMoUkFFKJAIUMkuYq57C2R6KwCRW9iEx5MJoMWKiDTBrLbQzkqKCsp7lIgtKVlgKwYGjWJvkDVZANbuZog3leKnclsbJpVJTnzc544XkXuDCNjrYaC1bTxFnHCYIHv4Fi6lrLAqGR1gJcH24gHumZ7Vb9Zkbrq4cXJhb1L966IgS5gKSwMSQsU53z/bqdutN+ks4xUp56yLCvLEugnFh5liz2+eWiQeS1fp1B773a06BNE4Z1gdniAXu5mpZ+d6anF45Xq11HTgfK++5qNG0enXHq/Q5RvKCdv2L7I1CLvf27dp2et98ZaW76Bb3sEYil3SlD0JePq7kfCatWqtRWV44/cEP/c2H3veem66aft5zn/GVtz5j7x6+mhCmZ/2/0c04CEaxBjuxNZaf77+pSKF7KgglhDwRUllph2GaXSXJ0q/drcrtq+BrB6AYPNPd6xyNcRqj0jXrPQGFz3f5yvwvNw0AClC1OdY+80PgTJODpI1KZsTsw6/wvugwjQ98/q5ndWjM0kIJvAHADdQC+AJkcFKGlZlMzIEDBxjb4AWUZuBcOy9wRn4jMiuRAKhmD9h5I8zWmJmZKYwTb03x4mTQiV5M5kASZVEog9kygpVhDgKkROmNTGuyFZxshfw5ULDNt5v8xYoAZomQGRwvSlTwREAtXAS0B+uwHCDpIW27zTG33nqrgW1WnOKbgoXt/v37NyOJLMwvglwxlwXPgLCERaHoh2wumszIkkjAJdMU1hSPQCVCacw51UT5L3/5yyXPghUyKA6My2PAfwUyaiEFuMRHJP8YG1XV6LKYhSApDvjkCvLrEqN24FrQnM0AOMKXQGSRSxGQUHxOzhBlCRTlKnhqJGSGLHWb2Qgkv4vCMx85CpCchOrdJVA8yk+LHDcTkCQbVNwdJv8UtllOq3REEsn5oGhavqz15JaS59aYyVRZXkShRByAPG8EHhRG2IUba8HbRLeahJKKHBSSHhgMhgx4opDJkdljPAvNECVJwG6RhNdcswGTWfGDSUhO2Rk48C5rCUPJ3eoWNDB61lCNoKkac9hc4P4Q8aCEo+GiWmWnOqQdmzzHa5z6CrPdqHSIzCOGrqo3Q0zVM86ZXjqr3OrkqwdgRet5aI9O1IiiDfHJuZBE6eTivWCWeAGNDvDVlMbJaPWVMQ8XDei3ewB+u7Jz58SOHUsPnLC4fHUlogMznJZowRijAjBfYVQksyDOXu/FeNLNM1dddU0t7JmYARYrN8IEoLn4n5eht2177cR97WpvwRhdLJGPlAyL/nVX7bnv4OzxuaV+Z1nfsLYOscGoidmv2IQ5ZBcvXKXBZ9u1109//L77dSVWeyf4zVUTp88nCtZIJ3eZDJcYqeku7ZxoP+mxV+2/Yd8Dx1fSDl+OfESSqULE6GPTmA50sWO6fubM3Afe/49vf+ubnvy4m779Rc973nO/0uDs0tLC8pIFN6iNbDk1chVhJC/NxddCyLlqloRsIWuSNxslRclDwQ++xOQPpy5StfrYGAkDTay25LA2JYCLeRBBoh/qph/Mr7wrNXAWDQAWWhpgBBeObUuaIrRqqhJjA5w1fDszMyMG8MK6aMNFWp92qMWnHUTAGYSFDIpPuwF1Ky6kld1LX/pSQ/hoxoooX6lgIDYGtAS/csXodsTLyyWhd8GvgWSgBHTLgLWQShZWtkjiIifK/L5IS8hMliHvWAHOKZKEhLGUxSyR0RJ5qU2cA5TBQS81ZSraKFmRI/FgeqsXzLNXcArc5JtO57REY2AcWEkDmaciF8xzQBXgbxDaGDOVmlwE0eaxeXmxatgAVnEoFJBHADhvUAaRvDRKxKjYn+bgFe3BI8P2GMqIGBoDttK6zWLkcCGPhOwo9GAlXO7pEEFOKJL2sDILLueV4weLRqUsJRPhtDGFYh0pHbdGkVcRSJmMyagg2GSAZlDC8dkhMJSKbNok0Aw6y0xj45fISVDmGL26tmEIQFOnc3U3WKJBhkpHmdRr1YS0g48yN9Wt+eEgC68q+za/LEOUlMOHoI15Sl1kKwjUuEfK4rVl53inRoWRdY7UD5gZZcGSStEYsCJ/wWozAQLkC/FoRoMcvF/kZJJliyIXPycpwhTISvQKsJn5AxlLRZ9Aw9Z6sUzw1OyZ4nQ1mONQWFkYkF5SL8Uv/uIvUoWWPCjP5RQuPSeXU20+VGWJIxE7lRuuae/YdYW139bEBxwPYGtBfPf6Gyb27qx85pDBHtFgOZgeHhAOiWp/aaJhFYihqejzfIj4O+JzlIbsrTaxQqOBSX/F49VeMTwhC9u3TT32kde2J04fPrHEOMljVs1GLNpeqCxXK0Ef2fh1wEi4sLvXXzPxrKddf/TI8vJih8CxUr7W2jbVmG3OMy36PZ21LPyvCyPJSsUi+mprul1vXWmNihG4ZNGsqZCQqLERHR6jevXd7/rIG17/c09+9FU/9LKXfOlTvsgBKosL8+AFutSDkDGKsFq4FFhjdtH8pfsQ0LX6J4WG8UEiGPOjt82YSal9kADBl73sZT7bhsRe+9rXft/3fZ8+ekyyMqrUwLlrQBuDYn16c2Mb/EgXzOAYnhOfagjSUDeEBCLkp+gLsFLQQ1qaKyipa2DS+MBLmzEEYAQ6QDMIYKANAHrmBiVbCWN3HclNFpcWFM6PJPcigB0kf9Ob3gSL2KBJDGmLUpAzv0o5JktbyFkEsmzF7bkGsCUDRCi7sSXyyIA0hXjK42S2FdAvl7H54uYyvs7MMKaOBtJiA4yFv4WoyAA4GZHEKD6ATufF07GBbDmoI0CNMWlo2SA6SrkD9JA9n63Ox7AIVvwb4gs+ZLMQSHtQIqBQoXJZ0JCWz8etUWfNBn7Nj4q0owEIXkLtZPRREYOAAnmltJwsCbY5UNAIMF1AZPEuDMk5+PTChqlOLsQYbHJDWSCID2SrpcZVjRH9wl2jZWq9CiXgtaIoekY/xCHf5sLKyLsDOiOTapBSLmjkwpuh4tiH2XRUuR5lSkmEyWCCGT78ipTpUaFJdcf4kSS/m2OFKSJVPTKtSHKtRfsZlOfChqlOM9NTCSgCGQoxcoAMlKPqvYNosnmm+eUBC4UyoY7mWThUTUtF8vXkpBnZaT9YDal6vSSXaHxpnFyiFfe5ExuebZo91eu0q/U9E/Xt+6pLrIkwDFzc6pXtpmY1V+oVOzsl44STJDwOQRA2TbJETOgKSyb5JiImsHFPp1Xvt9OjVeNEEtsCh/HQX7pqz8T0VPvmJWtaIispvPtONb9/4oqd25rpnPi0iRZrI2aLdSeq3Rv2NK+c1BfGGnuiEK7Vqh2dbt55hZRzwSM4pcyj3zNsuVSrNCbi/MRkLXmYixX5hYi+h3qcyWbV5I23vuVte3dOvOLl3/PFX2QO6+TKSvTdQZGkS9R+stMmkl6UV3w2c8FGxEvRI7FDEbTmEunXNx7k4vF3a/gH7PBdKdDhUMLyttTAOWkAojVGyAbICEZ7G/1s++ojgJwQgyMmb2RsnTMapTd2CwGAAlopgCgVyuhu0uph8dAPlJBz3FhaZCa6QBvI8jyi/fv35yRGQBntxjVBZFDMqm7wyJj6zMwMkG3QFLZACULlVymnGpU2x5/Pb1aarDEf5Z9LfeDAAf0YhZjObomF7Kgll2soSVaLSAsDCE/5TDIodmPjhFaRsWGIAZUa/zYpRdYb4CqU7D11IS9p4ctsnJBND6PPcRHSunlrnRkngypSrbw65DdFjaoHUbVHqkMpMhbMa4EG046GCUAz0KckGwisdOoUGQ5Z56OsqIuiskr1nNrGKM2FismiynEDhiRxKZ2LuhShKKCAalVkZfFUe851MZYbJsg8Yi56AU3NKvhkereZjylJpvax1bUfi77cehkzjUpRa5qiTFUZRx/XJc5FjjSmxtW+X98afk62U863oCkCCq44WBGbVaPVFY8uYIB4ikYMXQGvY+Y8KHMRQx4l9cooJlWTp1CRW01dvItyeHuYHOuVC0NNiN9JpniO5nUBS3cxsNqo+V4M8pUyXAQaALh7cYI6sB8rSapTCd+uglkbVtTqE72OfWnzNIhYEh7GSawfMamqVlnRxyQAz2aJiVNpTTwUHwzYGDGuEnZL3HrfEmW3t9JpN9qTOxq9SjNlFDPCwknS7/RO2x8YbVgg/DAxiyvuuvXq0rZ6b8f2imXrZiiDDZi22tX+cn/bxEq/72MQhOG+SfL4PkoWa/ED9qTYYCoQ/3tqVMfs3HajZZP//+997z94393f+e1OSPhyOxp3VlY6jn0JUoLloiQxo6CrrCKbi+8i7TgJs/DnIG7ul+nNIJDJA/aiYb9lgIhLoc9z4FiSPuw1MPhV9gEGjPg6fLbXU4xmZkDaGKTWCNEi3hiQYch6QYwnWFBkh49LLlgBQDm8XqY5HiVQgoMcjfia41TQQyrmjpuqAYWbKw9e+wWq8oQov4wu8BqS81vIUCS/sAGQiKhycY2Wi1Rmm1CFUpjGw4iC6lwZPElSCBMKSiM1AB+ekB+8CMJmkD1IWSTJAZQ4I5YKUjTNBn+34ocoi1vVRGYEgBroRr2F8CrOSm5LO/Q2dG6gHU9VltOSh6oNKiMzd99VNB4cFBYBMRQEf2C6YFtkPRRASRgVTUVDj9xKni+ccctGmiT5kd8cLhLmWyJJNZZhQXmegaxbZcyNfEiMgrl4temNoMNBeYTpUKFQesqK83IVqdYLUJSRAgZGbjyZTElzAAdPNXhknJYsdovaC+OEJBbfM2zILJI5lB+Jx8EvYUil7vCxf4MmxNQsmBciZXpMXJK4FE1jKwguSCDnm/OiavXOm6FaxYzlnxthFl6YVAUZXRGPPSaG2UZ7TJfRchX0mnquKTSDVVYQXE6B0ji5nGrzISkLI8KLUK2FMRBdjWBYHQUGr9fsbM428MnPtkelZg1KWAGmUJviFXOoWBHoRQjGrK/8NIyVQB4R6V8QpEcxqhaOj6VeNT5giVlYNDXnnJiPWlmOxSbJ0gjylNBdrYK4YyMqZgW7AQP5GzNsVldq5nTFUR54xD8WCTvKxsK+tilHgiQR8mNCRa5R1ka9N9GuffjDn7rv3nse99hHfcuLXzg5OaFnZJuEXbOqhGRmRTgxSzJdnD9KlNQ2Rs5ivtfmJachCNLXiwPdmWivec1rDHcJ+05vnklJWWpgrAZ89aMD2XD0V0I9hV9N0ZVBgICY1NWMYZyf5t+hx5LgcNYcc6pMnH+hhAyAsBUDhZhhb7dcg8HmbJhKxFCB9vzmTU4Rm55krpdVvyhHxcDENRS/tVt8NigRgUGl6G57PXgO9KF2l1vZjWoJtwzuFRnbvMoC2SDlkOQeZYYCkgCdPAwy3QBaqQW5kIFZghiczTxxEICVDbrbkFfPw7JijRS7EYB3lnGLp2EAl2srJ8mqE3Zh7hoScj3dIiMJsQmzXhI8PUWDUjiTCeC5XhLx6z0aq/b1xBsbj3POPYtdiDRKjDKLnat7kCC3CjF0pWFsIC2a/FTxc8+fuWUZ8lNMcmBmZsY3wrITS26YDcVogiReEx4V1c16ZzIN1lHBKjNh4Wg8DFe3Q1cuu998eSpgLGCIbONb2eUc8+8GxAhIQlQmUy7jIHFOTgCRfhFQkV/x+VEmVnZPVYR2S4HeqcGngwyFcy7o5evjq2qGCC6n29I4uZxq88KXxYuVYCsY2onXixnSs21f01nv8fmKt07fnDYAhvnztKnkNomlGk3jHLEZYkLEem2Ol8E1plwTde9r2C8B67E3poWA4VH1Eqd5Wdkyie8k37C8mRGdTnxNZY2z/U3ACbYGUyZGQmM5fiT0sMtDE6E+Vr4blX4n2RAikqWEMsbPGvba4pAJZvE4l0nySBvWTeL8n/7T626//Z9ezDKZmFxa1CfIKbob9A5aQRyEYUIlk83f87pC+vO4Nsres9RVjrKPJ+l7un7uqXJDoSkHBXbpIiEPgMPKPFuw2y3UVAo7HY1mUMaUGjirBtI7tUqV+o38lkVTG3xU8BHpew9IuURqjX7HUuYk0WTTVXAoArlLwWfjkcuCvgjoDuAJkEuMrLH3qxcCqVkgcLMXxMxyZom9p+wgBJOBMqZwCP/Lf/kvf+RHfmQQYUjrwgqfIoscyPFDkRvfKpQLK1oaTS4GHrIOhDwK7s11kEJG9lLhPCpDLp1HVM3cstw/T2gpmBeBQjCoayZtVCCJuU/sChOuZEdvBc3YgLy4ZRhvkmeCzJy2rSSBX0UyReC5wjjhpDIAT/lo6F+pC865sNCw7ZuzTvBHWRCsFyCDkX4MRwnwdI3V0ihnlCKjPtI1mirzXy9+NPehGPzFhEApo8xHbY5KMpgwk0kyGCmJmqJh8WwA8/0sJsFqkGY0bMzO+iWtXarM1u8gZ2GfCcpExuxkojAz+BzoQ2Pw3nlN7K6mERbmqFwyB01UQ3Krun/oh37Ir+Y3yDzLk3PM8dgqiBEBZRmV9qwxuQjIcMsMiyT5Fn8BZBq2cPG0CAymEtbm2cz0M6gWEnK8SK4T0F04w1H/4BaNq2A1FMANH57D3O0MPb1sbkvj5LKpyoeoIAFHvaGOLaw3WwaR4shD06sykE99mp6tbrKXMw3X3ie4P8YI6vUHjp2648B9p2bnknGRXrbkB4GE49vnjKq9+w7cc8zRBaSPbRTjJffC+mbI0YCNfYHjHY/OkzlRtxC/48QS3Tz68OgQw64+kaJuXI4x5Il/ER/6qPYkcXR9HH4ypaeMOBeWiKrVg0dO3H/o6NHjJ5LguTtY6xKiYzUjoj09ue2f7vzM17/gm1784m8hdv6m5iEQnOTLksJRjiRayyButnoFwDqPK1S3peShM4VeL+2q+ZV0HrXpdJT4dWIM+zCWrtq8y7Y2digqjZP1dFjGX7QagH7IBoma+bPWjW0krKlKztRDof8BeWceDKAzhzwsLQzY2ePYXljgl4Qgtd2HoLH3vOc9HgFbgzB6o1wv9DOQiKvT+ws2KQicxHKIDjddG+sB2IIRyY9+A0qKhQ5lpKOAdGlYjuaxyO6spfFBkBBUHaSUHTkhOb2NaV2u4il8DPsqjgNY8ma1HpEtl0gfxZTSgasXqUy6M7OuSLteAH0e48e20Mx6xFkVZyVbL3kWNTNZj+ZzEK818mAor7zMnrLzL/NPXW+cNXuDn1Bl5SaBeFQPwDRrU5NQs5aOsEysfTdzz+Gn3gtJrAqzvmj0dRBDOSoCIuff00o1p7HyFJlmZSLLr/ZY4rGRWqa0+UJQMBxLfJ6RlOxdUC6vBr0ZIKCZtcwfZNoNZpRbiJapmgbjL7NwaZxcZhV6gYsTmNunCk6vNbs9+28u3v/A3PxKXcfA1WC5Rr3a3bt7x/0nO4sWj6TuLFBsfN36C4uLn7jj3vuPrSwtpx1g4pXK7OJp/KutVBcap5edWzKRxuWzDRIZ1u3MVanPL3ZnzywlzC/O+B8zpXdybnFpxXknwYqNYXJWfDRqRKodOT5/anZh2WqTfMZg1Vr2ug2JDx1dDOMkmRDcPDHZrNE+OXvm0wdn7zk4v7DcrFebMdkrL0EJzoE5GDvtpUbwXGxcfd0NV19ztckInLKecsXI0fSuONjEYnwL8lN8lPu8rqSW8+JAhK1JEVknrY7PHtP4WNGM82pq1cmWpT09h8wwVFw6Vlv9mDRsosX49GVsqYGLWAOGbJkloA/7wS/EkMfm1xPZFBS7QkESkK5hdfZJpsw+AfFuMckwCwQxSGx6iTcFNAcp5GVhq6XedgmDRQZzcYtMjFSuwUcXPKyM8BAhYTjL+g1p2/HMu7xBRga8CQ/wMTPsRctOQJzR0thUHmEoI7kYxjafR9q8omAsvUho1UWH6sJChVFi8NQRJbQH0RpBtw2ulW9cIpSpIBJabVIc3UiAnJGlI+Jtd0uSAwcOWE9/VuOEGGQu0O1QTY2Vv8hu7NOzRkrueqjrfWMx5E7nGjZJVAEjcOwcqiEmWj51mXQn1XqK0gw4YTQ5LQ1bdYeJLCxBEWY6Su5twmGIOfvWK+bFlAt7dWNLCQ1LyZdIQFM512ld3j4XAUbFGJLq/G/p2XfT9gCKxg4kMIMts806HJXBwjAvYKbRw9DG+YtxcXIojZOLs14uIql8OaOvqDePnTh94J4Tnz60MLc8bRZFVxdU7dZrnZuunzg6X1uxjiN3KQHzfW/7C0vLd91/fKV+tQ17A9mGEWG+1CpROo5xuduc6jAbas6Yj3lduuWwYOKEksYDR+c+c2Tu5Gnef9PGYuKWM5Qd0374gZOLS3bqCPsmOnE2js3E+pXZ00u333X4xOzK4oqzGpuOYuTT2DnVODN7+uCJpUqTDHlL4pheVmu0Dp944P5jS6eW2rX27mq9GXOyYowthKd9hau3LJ5ZOXTonn5rW2tikhZsUhz+G2XuVObm5w8fPdmhBWtsaCOZPucNJWQduZ/HRb1Zw+fKI7KOdUXrX6mC1V+vUe9vn2pee/VeM+Z6TLM0kc5uiTrWzXzG1s+hfFJq4POjgVtuucWkILs5gQg8GzCN+U7riWJ43hR5TkINPlsdBoyBCUgCJGKiA81ujTcDW1iJd2XECSJbCwFzowR8DZoO5oIM2vCbI4EVyLi4HaS8IGHMIULD1ewH8litbuINAbJNNZoF5VhI4wBW9GQD+xRnlGwohvyGzBEDoPwV9AxcZqtmiDLfMmBUARuDveTkh8LwK4iltU+XE8epHapzNvltt91GeLJ5xPaDgAv8mutFWjHWM+Q+igzonbbJhtkA3qliAoOAkmewWMhwYQNUpC60EAFXNm4vbBbnxE39arraNsuBOcrqo1jtZD0mVvtQfm45FLWerhRNFdhgjSUZBujRo/jz2rFVNCfxXhlKGE3+5Cc/WauQixpXKSTZYEaTt88EY/Q8aU996lN5LNcTe2x8bg9EXe8tGJtqa5FaoxkH7373u8lMzyYlui2M4SGe1EJvipb1YBxBHQ3RXE63pXFyOdXmhSyL/tH4QSDW9KH0bb334IlP3XW019rbnOLzdf4iA8G0zpVKc3u1NdVvtIyig+m99BM+jl5/eaXSrbdr1WnQHa/kOVlbgy51tbJUaXUtGqnFllzxbY/LUpTGYqf3yTvvufOeE926kbm8FsXOIc3JduPY0dOLS7G9cNArsQT12un5lXsPnvzkXUebE7sq1Xa3YjghZoPZ4vjMcmOpI4spU0QTcI88FOrk7ML8shX0U43atmXOgFiEgl22URyfUq00KitLs3cfOthotxrtpgFNw3IN882a7QeOnr79zsN333eElRNeGqWLAm/RLHhwtZ2/cfJgfudwp0rWv5LhpVJZio6wnGj2bnnaF+/ZvS3m+IViYtMSvWr+rvjNlbM+u/JJqYELqYGi4W2NqWlCMLfZVqxrg+u++nADu2KUm0FZg+5mZBkGNrNCwv3792vteku/EAaPyu/93u8J/9t/+29NIh86AE681yQPS5M5j9EWuUBm4H7GqeAa/wwQtgF6LhJuOSBHXiMQn2EGg0I/+SzwDJQLtkT1RQAiHc3uIHBlt+AE+CsIciDXgrDAYBgxZ4VVN0wgqtNX3HzzzWPLZVT4ve997y/90i9RlEH05z//+UNZuM06ZD0aUGdmkMdpiZZGGFRmybCvDEijKUQqwjC3woJ3pnVZSW9HWjuhj9onJNehgc4O4YYX81g+JgWfUZHOM4a26QQadql3SjhP+6RQ/hYEy8UE6+nW1s842GNam2QQMvBGlcCGpMlf/dVfZTMoSJEjGUaJGSf2gXjjG9/okSahFrxxeVahV0kWY1MxMNSvXDS8X/7lXyaMU4DHvp6sHfX7+te/3rvj9fRuUmwh0gaBrDH6V4r8eiImmzYzWooN+JzTI7YW96N3nLQf+9jHfv3Xf503b+wrrz0omq5JH6WT0UE9+9nPHvsGnZMAFzNxaZxczLXzeZPNi2pKtHc7DxjxJix1+qeXmou96cnWtjjjMMbYA5OHMZKOkO+ZyRBmSZgcERmeiy5UP2/uTyySC5cJJ0O4JzwPMyVZN2nvLH1YMhvStKowhpqfvOOeIyeWe81dtYndyTxiPPQtHgloXJtgIITXJD5SVdxr7faZpYX7j56uNPf2atOVKstEF2mWmcGPpo2Oq/WpWnOK+RAGkeloPD7dyo5tu0yE7i3CB7H7cP6WoeG3Ua5Ob4XBtLJy+sDdn+hXFhDkygBATOT6zLHF2w92q82r6/YGiMWmF7CmqPR8rlVNniuLUEpCFGMTqq34znAbMTE1jg67bvbjdx550uNbe7bb8yAg1qoGU/rB8FiGZWSpgY01kLHCxjTFU8T5GozZoBEiHnoKjtjfyditMXtdn90d/DpvARlibDO9sLP/gCQg3osPin3jN35jHprNlObQG9d0LCnkZLtbPEeNE2+L5OwByYGtQmYBYsDKIsEvOB5YYeGMug4Gk2wcHlLLIDExXErxkpe8hMXF8ADZf+InfsIaffAxD5MXitKHQ8zOYTBuzZPA3/LzP//zHBQFQaGfwRxzWBYcU8AlZwUY+ju/8zvirYy3LCQrLafNsjkfhicEaKOK//Af/sOQ9gblv/XWW6nItl1kA3NBZMYSsW+77bY8k0cu6Au4LBeS//AP//BP/dRPMbHYHvC0bxz7B2LOnCVBxjyA/xyyiS3LxEU/0GFmOCiDmHwNRm4tTE6XeueXM5SudAWqlsWgijbJfwPBPMIEzw3YOnvRCZgk0Uj4CcFi6n3BC14wmjtLQ4MXz1zUhDBXELdjxdYYVK5GzkDP5OMAAEAASURBVI3G2cJzmBuh90V5FX+sSOIxzyMIEnoH8bHf3VAWbs0QY1Jqq4D7TNocjEE1RDZaBDE5X6lYC+xnObJMtHbOnPySYlKQ5dJltmMFHswiJ8y/OWHxVFoZOT+eT5IZTOE/9mM/ptnng30y/0zMy2pTDXPhNEUKZH6bHZd9egW3yyxQGieXWYVegOJ4FQ1r+cT6PN9Q4TdMn2cf6UYDHl/pOnrEm9y3DNzLCtXriMIM0CGB9fExSIswqtVt09NPevwjP3nf4om52Zj7E8RmZ+WPPdcHNLxU7fJPLLMFIGMYP3b6iGldPg+2xOKcadWrU245T3q2xqpUV6zDrrWScRJ8WEmRIOYV1aqNiWAWhobJsuTCn1eDj9gJkmiKpp4mhPUq11y148Tsmdm543OnDjbrDXZWepAVyAbp16frK4snessnat35KhfLmmoVZKlXW1xpNScmnfvCeeRJ0fUEVZBGR7bVS9qtJd+iZRJyxoy7qJyxMq/6hGLpUZDF4qL6ytxCJzYwSPUwNlUZWWrgfDSgoXm7M4fB8Fie0f2kKz8tEo4lHn0qxjQJmMb4JfRjlgUMbSmwOUJW38I3MAF4DbManjfMCUxAwKC8E9NhBbngQMg8H8aos/24AK/f/u3fhsCsMwHEIQmA2GwTayRMFoI2QBBHl2YkV8gJlGMIJOl+rTCGufkHsBUvR5h+k7YKYVxZsIL5YIDAEJ5f4Nt6ffK87W1vA8F/4zd+w1p/w7dQmrUcxmthJgIT3joZBSf2i170IiubRwdulSUXB9t8ZRngTlmwBP7Lf/kvNMn8gHfz8gMz3EhF4TRjGQn4pcjKeMsttwCjG0wbo1Ljx7KDbq2oJiR5ZCStco0tuHhP8yk0LCVfOgakmsJHSRWZbKpYRQPZJCEzGE0qTWJQdUU4lzEXuYhcL4B4Y0qFJZKK0Ag1LaK6JTP8aol/NhfHMsd5KD4LNhRZ3Bb0qY2M7/Nlbdobg4S5qEGy09gnTHe1tn//flJ5WShKZXlNlItBy57ReNRyZju2sLLWchTnzW9+M/tce0PPvOTv0hLGJslicylIpXZUDUPam8WBSRjxNIOJR2wJrhhvqFxEfv/3f//gWTdF8TcIeNF4Dv0SjOPoDW94AztcJ0AwnYCzWUCjbDRmHebmjaFAodUh/jl+vac48ytqvZoZ76XO4ed+7ueUy6XnyevTvH0291NwNHT1rGc966UvfSlzbgN1DclwKd4WiO1SFL6U+SHRgF5J72PmtF6SH8EVAL9WuWL39iv29o7PLnYsg46c/Zj+tLK46MCj5QqjJTau8oVO3pBahU/hhmt2V5tL80uWqAQx82RNYsRIuzu2T534dL3SW8wAPxKH86J77b49B48uHV/od5eDbfpnibqF7LVkaQSbtf44bKHJifa+vTvvODi71F0ywyJeWjOteD+qE0v6vuVOZWU5yZysCH6Tamf7ROMR1+/aMd08sxQrSWQtp0zDUlJqp8ufOtG9akfzaL3rsMgkebKCqgFB2pOTiwwoU7oCAYRFlQj8uM1s1iLO7e95Jj+3zAaow2MVul/nohFPojKYiR1bLPev2LPDV9NwYtLA+RR5nSzL6IelBnzmQQ2oKKOWDXSA0qfaODfKTFxghbGpoFjEOEOxEg4RQzMsjdtuu83sI54NABEGYg9ABsCZ9d8ANNyDMzMDnrCSNR8kV0CEjD/AF0OhwtA2gKsjNehrxhQm7A2DPoAISaBhYA6ky6kGBcYWEDHNDFbmHMirk8FBnPl2YNZB4vXCsqATnopcUoUdyqi4xZm98cIXvhA4NiYNrCu+XJgi8Dp1gX1kJrwiUBHMCh4J41AwIYYcZWe8mZIL3WYCvwwAAJRIfB0Y0oOJc3QrHjF3AfibvUlsOdbd2AlXg4VlUwGO5KQlleVXQvaMTmlQqsEkwmw8gFWOCvuud71LpiQhhjpS1ywxsqllZeEEIzDtuVX7ow0GNxBWeV2eSjKU19CtTGmGivxKOPTULUtVRpqfXzBUATVUqXxtuCy0z9EkozEkkQX+5NlADzkhGsKQXxIZDXKTlj6JhJUV2yqIdeqNYFow2DxlljBORLrVJLRMmtda6FAtS0XVgwyLMMCt5f/BH/wBDsgQE8OELtkVNKMBqVTc93zP96g1li2wrn2qNXVHUZjQmHgCeF8MNDDj5WLZzCirDWK8C5JY4uJlx9DFFMGQljQPuEiOYuiKnulNvh5tRtVZz1kzhapzQM0SVTei6ll6ptLJkVYpREDD9vYxuhB7ZdQIXx9V0PYGBbkMHo1vPZdBwcoibFkD3gcdjWmmehl9EH+ISVqmNV11xTRL4d5DxxftIruGvw2ib5vqtRx7at8q3z+5RhcH6jM9utPt+s3XbYsF6IbazcjiwWAHrEqmK681G7U7dzarvYWYU5Q693B3dJevvXLnkROLZ3rLc3G+vMxBY6dB1Sda/WXnMBJKHgGXI8NsnFx3VevaIz6MOf+QQ2e7Y7pf7zWmJhv95QURq5sME663VK01r907de2+6GgIhlPRNwdTudZq99/f2butNVnvsZ/iebK8PN29Y+L6a3r3H5nrcv2YwxaJc6LI97yMk5gpdx5XNjG2wiCsj6IM6zOg9b6No3dNTO+/bt+Eb2eX5UnmQnnrJy2flBrYhAa0MGgMAgAU8sdbovSyj0nsk+8jjdhvQTyGLkXBEF5qqNr4yyhDjwBlxyzAu5ABo8LYMEcB9ANCoZcFZGZE01NTuaxzGMvHU9PB5WVsHvaF3gzBQsCYKJGiQfwgDngBkczMzIxKAvorF3kM2EONLmhVCfxiu17phuJl5BKZhRzNxSMay/GQnxIpvvIyh2AyYkP8hqLJ7KJhMpP81ltvZTkIiyxyzHyAUWDar2s0O9oze4rtJxWwxfskIwFDxWJwkxYao14TaUBV5t9YPkWm9MNaYyyZhY/SrTlgxCsI1gsQ3qgzfxQl0zA70Jcu4z9JiIGtegG4iUG8XBeajVwGeea6oGQaJj8BBp+ODWOOD1WMJdZsVLF2ArUD2bCvX3BWFmdt20V2iOWCid8icr2AEhEepfotqqzIS7wqM0hPEuCYopgoXgoBDNErC+va3EWSM7ZNTBKPodLB7rn5jWaNIKN8RfMUmddKRht4yZDh6cX0ejJFtMPsZ+Oc9Jbl95pWOTe4+9SdlUWM7SzJqAAbxCiUUvPayY6VrrCEdMmInN7ErBw50rDiIxt8EdbjLBXxcMhVX6g602PCDcjw0CYNfHj7NABvh34jJ5SFd9PbgUC3o+tYT7frCXApxj/oZbsUC1DKfME14M3/ru/6Lo5yHyq43VmKi0u9znJvx1TtcTdve8wjtxUznPJ3EjZ/1xUTnz7CHImIeF2d/pGGFrzAtQYnrwlbMcAeHZpF9CExEC3GsvNJpkmc7O5ZdHcBj43mMGIe+6hrd1xRuedo2A0WrHjgvMRWY/m+xemJtjEDhkJcAt2e9ezdK/dMfNVXXDd/prJi8UuCyj4W2yYrDxycOnLXLpuHxaqVNRuCcyYWeMo5zpJPEj0ImIcV0mw1W9XuysJcrc9CwjH9iyPoK1ftbbXajV07J47bTawT2wjnHKNkcT2IV47a3G8UZ3OU61FJvmUOSWuDjBX1s0aXMpp6F+fc7Nm+6xHX7bxiJxvPPLuVqNTyKjVwgTTgS2xmhXH6mZkZIHJjrnoMn21fa4By43kO0XrT2e0G16EWSKjAmh7lngeBeGttDZmD5ibcG6A1cgmUIPYIrrV/lByBDEzIVqQtAjpAKIrzBB9zusxfh3LAX3AN7mG6GNaFMAzQupXjaAGNpFpJD/bxtxirhuPDiV2tAu4509EkozGgDGgrU4bH2FwGk2BOGOV61ateJS+z283d1/8TGwIzXOWR2VCm0FBCBlhF8qLgxFM09FiNyikLYhDmZS97ma7XqmVj50wgFY1hthaMWMOFPkA4FLVTZDQYyJnCoGAirJwHmCUnYa7KQeLBsIQqiBgMD/RcW0bi6VlJPQINTS6ieRO6yEAwyld2kvPSKPsQK2gYH0Ums9/Bp0PhLDAPFT6yGOsGkaNBce0T8mYS80uoi9xsNglGFY2RQGxqITYZcr5jhREJ7BKJhcb8KOQfVKCCA82vfOUrwXQbFXCsaRXalSzokCUAKmQPD/iu0oFsWqKNQSZDuXskOSWjlEpFywITwg9RDt0ikAWXiKboveCCoyj2EutRPHm8d2wSNir+oy1wiNvg7ZCWGOosZM4T5pbxBWXXCZBQrRXNUhZo2C36BKYdbkNMCv7iNXj2GHtbpZBzsKRZUdhSmj6BSWxEgKq1SbWvaNq2fHWJ1oZJmC2cgvllHAiEdxkXryzaFjSgSeipjer5Qn/Hd3yHiY/RHy31K05FrLccP7I6hSkNtHNGTE9WfvqnfuaTH/v7b/3mr/u2b/u2xaWFzkoH5Ne2oH6u5ZBhrZlFa1v7X3B6euodf/aOH/3RH/2b971v27bt3MvLKw42iSNNevXJlWp7xcQxBk9qpEwZjvG777znR1/5A8/96mf94A/+ADlxCzxea1dq7eVeLNgu/OVynpqsHDl09I//6E9f/f/85Ic+9Fd79+zRm4Q3KK6i5YfpI2GWLBUrWBqBMs3gta999Uc/9tFXvvJHvvZ5z59n+sSOyY7dbfRMaIuNycKwydZAZlD4lMSPvTLx2EerkWenWCd1UaB1ng9Fr5U4VUh6FsVO5VcqNZarrkgVpoqbvpU91WZdpSz1rQOqdLixmi19Zhwnp/e0U0qRpAyUGjhXDUBjeV4NtASz+vAPfssHuUFgLtgUtALsYB2IJH/skRWBnES35ksPCus0MAQ1cIYwhsgQo8RWp2cYGw5LmcRrDqjJBbbQ1HEYTZgzKrLLTMAvrPB0SQKFyBcaK7IeywcxPUioaMTGCltpzS0hw2BG64WBNsLjQ2wW0VkFznxyYWnJJcYt8aQlLZCUgZHb0UxlpCIInJ8aC19PzlwWtZCRd5EFOWH9XCmblFam6oiFgx4fycG4sfocFTiXTnIVRMngYy4psZko2dAVo0RU4auBAPalhIJVzp2ekaF30U/xdDSgQuFdfJBl+lEaPJGpOJdMFUoM/kya9fQ5yASxEXcJRaKXKj/FYZCsCDNLVIQcJUQ8+PoUNALEIHauskIkOpcFPK3i8EeQdYVbURHr5Ss7zgH0uKHBim431l4hj7QuVVbUCyaeejtcuRNwS6oiybkGchbeO0WmzPwCYqjT0DZIi0A8F4dA7qb8il8vI2Tqhczeo1z1iIeUkzP1q+rli5gmFU2+Lvy9+5Lka72MLqf40nNyOdXmhSmL1u8VMqPasISRA2Mh5kH0egsB+2udeo+jIvV0YRWEy2Ci0mr3l+t9HWLCtLpTSB+2RcCJQiidT3RfYQmvzerKONrh7nF4xoNBdXr3pe8t1+3OhUWsleco8YamDX5rKzUr59dMgjWLwqQyGxJngyN+o0c3HFitt6tWnizynCTKyCpL77WXky4io/Ci946ZZ0ESyZNC/SpEDqeIdDh6PQ5/jHlqCQQhTZnG83V7qJw4/a73E4Kv92xz8SH55igfRBVpUrVFSYIDwzILEww/y1FxIzpVrol8iSbRP4hbeVNqYMsa8J4bg5fcC+j93IAPAnAEPIqOJRGvvbNa6PB75JFujWkBvggX1yh/j+QLhQDKmU/+FY+YeDkwmnAwBg3KzCSDp/xUvCv6nYG3ajBhQZbtAThv8OnGChmkBGWInSXffCqULiqCwwa5JalXfwbji7BnDAPqFZCpshePhgL4iwHRKCcJGHWXaTzK4SJmKO3QLTJMijHyTaYqmMgum0NZSzkek3y5FdAG8B+rRk/lnh0UWLkKzmMD2iorMbNdjxhP9Z5bDspCsA30OZiX5JwhOZWwa/DpaFgtM7cyfc5CeDSVGFIhVmuDTMQrSKZXulynCHJ8IfxgkswfgTbGRM+3fjdZwMxccmCdMTOURc53MLuthfFxMb0IKYsil6KwnsqdzyTzX682i9zR53oJvklpxaMikB+5zZ1GzteveJF+N6+iguclHSiNk0u6+h4q4fVE/Ms8pzbEsP7kMY95lFlMXWZ8fxk2Nckqffnjx1ypeqVpvbiJUm69RqwKb1O8Sv7UmytpoeDaTOnVzjIzYJXgWJQhEkVfl+0F8TjhGYvvExjuNhyL2ODjsKykuzbPSmoWkWwJwGLJn4ecS6yWiX27nFxv+994GnkhjV6A3HwyIWMMuUXvEz1AuqIM0RXAIQnhcAzEopf8ECqPzYT9MXks2TWJpYggoJskT6Yd+0uGGOZZ/4rirv904ydkWJVzY7r8NFmKA+UKHSbZopBIVivN3gKDbD+L+oIm7gZ0t5lsS5pSAxtpwLsH6GxEsfYMpeDmv9nxVq8Pmte4xl+UrsGYrYUzatlkpqNZkGHLaXPWozw3ExOd8Nmg9iifcxL1fIo2mDU+m2wtg6mK8FnF2JjgXHPfpKhbUH5RonOqhU1mpJj4R5vYsFUM6SqnKgTLgSJyY1ZDqUZvh/IaJTj/GFm4NuBzTqrePPFZ891ApMvp0aa+AZdTgcuybEYDXiTTuE0gZpzY1P/qq1/SnmjbmcqhIqB8hvarfLxJMcjeix29Eqj2NovDoV5vLCz2nHVoe5JsAMSrHmPursC0oPDu3dsXrGHPRkV6KdNetXFqRp0BwVmfcHGM6cf2W5afI4pJXplNmo0l48STAbFqRMQqloDUssv/wj8TqVJXE90NJrwwBEub2ZBOBp/thhKneqvdnJtbWF6xH1XmW5hkaONK2xYzb2J0I2tDwhxY/5cUZxlgY4+tn3zjJ3I/K/MHcSD82n0oldcoDdiIC23Ff9n6SApeo/RXRvFvNXFS68DTMlhq4HOkgWJk8Zzy21qqc8piY+LNCzBIORjemP+l8vRSL9E5yX9OxA9pDW5ZksGEwoWQ6WsYd4MExdPRwCbJRhNuEPNQ8BzN7nOTy2i+Yj6PWY+V56GOLI2Th1rDlwx/TT/LmjsaYzwWZZr+6LTjJ/+zL3zKl3xJmuTQW1pdAB3gFShlQDAN/AtnQwKpRkS63TinkR3z8U/ceeDeo/PztveNC03GzowHi6mZFtdcveeue4/ZsQO7dCJ9wsLAP19xY7LRbFQaVrWsrjkRvbTcqTYcs6jdZjMgyRygmjsnznFXhFwMwLljA2EeE4fQVySxZI19Ej7okKJaX+lU//H2A3feeY99htlSa6WP1HFgZMU04snlpdnDx2aXV0SG4CnLRNDgdWn3qm3+FWNJg+A8i5U1uZXf80yfC7+5jAtaZY8C9zrdldiDMvYISGVlcK6p87Mck6IiKT1+NrYMlRq4cBrY/Gd4vUa4XnyWceOnaMYKMDZybKHPSlkIsHlKGRWpxmZaRI7lOTaySHL+gS3wH0rilhibLON6Ag/xXI+siM+ZbpzvufIsmA8Fzqlo559p5jCWD0nGxhN4bLzIrKKzFmFjgiHmmW3W0sYJhzQ59vb8OYyyLQo++KiIHCrOIM1oeJB4MDxKOTZmC0nG8rmEIkvj5BKqrAssatHcLdVy2pc9IqxRM2/Y5oz2mfGq79+//9nPfrb9A3/mp3/aeUZPe9rTrFprNltp+WCsN4j5TiZhJb9EANVAuLH1Oz+E3o/P4f4H5hb7O6rT7TRdq2FZnU4uZg6tjrkvd5o7lqs7+7UpaDj6vwSKLTeXy9G5lTsPHbvr4ClHydfSEYrNJuujdvT+u44en0cMG9dN2OpWUVca7VNneh/56MG5uXkxcSxL6n+3TzbmZk9+8q65yuRVac5V2CcMqV514p7Dxw+frJypXVGf2mZRS3oa4qMISQD0iWbk0N5Rb29TxlS46LsbNvFqNE8v9u87fPTwscWVTrLLkr97tViRfEtXKDFlvqXUKVH2Ip01feQU9cV466zYh3Oq2b1qT2vm+t1ms6VKilpKFKyyVZFW/6RUqQrT4qNQ13nKnLIqf0oNrGngocAZa7w39XesAGMjx7J7KCjHZjQ2cmzuYyPHJt9a5Bb4DyUZuv3ciLGZTDeg2eDR1uQvUp0/58xhPT7nFD+WeGxkIf/YQJEkB4rbscQXQ+SohIMxg+GzSjtIPBg+a8JMsIUkm+R80ZKVxslFWzUPuWCaO6htu0y7Rjp5yp6Jti6xzuzAgQOWwlsQPzMzY1e+F7zgG37/93/XMUxsGKeDiWEVJAskLdUIXBr/J/MDkMWVYRDzsBw0dWp+ZaW+u97abm+rnmlhNvpK/zkfUZJaZblT39bhCalNpjPIpY2FIrVme2Gpc/dnjt9x//zROfO7Wo1KS7p6szHpYMSFvs2CAxxbk2KOWRhI9fmF7r2HFu86uOB4ANuKmRQWh6vwtHQb86cbc0v2l5oyKyx7CJIbpHZidmF2sbpSYZns5DnphW+kF0tRojicB91Ovd6tn+lZZh/WF0ju/6BxQMqxkwv3HDx135GFU4tN5UrxZFqF7YQ7jytbBVtmEHJuIvEajb9KXO20qmeOnzh+eu7k4x+zny1IscGEJqLgG1xR9bkBbEBUPio1UGqg1ECpgVIDpQZKDWxSA6VxsklFXZ5k9tJ+29vexvAwZctWG7ansIedk4nt/m5ClwOP7CP81Kd+mX26//ydf/7BD37w2PHjhw4ffuTNN1951VXOngpPSCxBqdjyw8lPc7NzwGy4UkQFkhdqdnr1Xq9pIhZThukB+ifzJEBtHOFeYRWA/nlrFzhYwrrdio8cn733yKkTc05e3FOvtdgnEHDD+nWzvBpte4fk+mCfSMFpMX9m6eDhufmluj1t0zL4tLMXW8da/fpC30bD1WayTNbqMVLZRbRBqG6/iTfhAqfH7sdhnDA52Fcdv1bTsIAyCFeqEK/BYfKpu0+cXm72G86u4mBxKn3aB2CN/Zb/JtNoy6kl3NiWGOKsODHRTT0ud1fmz5w+OTt308wjJmPSnHVEabZepAjNDKVMt0VeRWAcVRlXaqDUQKmBUgOlBkoNlBrYtAZK42TTqrq8CMFwyPTNb37zX/3VX7FJbM/lZCh72HGP8KJYcPIbv/EbjrhyypLd9Jx59KhHPfptb/tDxx79+TvewWj58qc97cp9+8BW6Fbiqek4ztmhUQnFiuTMcBZyfe/eXYsna8uWqWQzYnWjKlkDuyA9RO9BGCxcEmEaMBVMNOr2D544PbdgvpTDdCcCPwc+rlYatWqd48JddtHEsnsmhN2AzU2aX1ysVByJ0BQrf3PDkhgWvltab2nIg6ZcYXflFbuOnlo+vXDGnmABwyMDPyFMGCympvXsFWyKmDiZ+OOSrm5CG+/NsblGe3pHtTntSXhkLL6Jp+d1yaUwg7bKKClqc4llpkTZU0NFy73K0vLciTPVxja6M/nN7gNJK8ENaSIf4ByVkrSSamfgQRksNVBqoNRAqYFSA6UGSg1sVQOlcbJVzV0W6czgMpvLTuc24XY2sF3q3/72t//ar/0aW8VxUflsJgV1+4hHzPybf/NvTOt65zvf+cZffqN/3CJG3D36gsc/wfFbTtSaTMcCMAvsqgXat5vNL33Koz9+5+mDRxcWHQtl5pY1IumE+DBF4pjG7p5t9Z1T3CDhg3EmSq3e6YDE9er2Hdvrjbn+Qhy2gVUvWzVMhhjlz4P6uQJYEiKI4UiBiZXDi/VmrVmPk7A6naVqvWGiFgq3yTGSk7Cowha6ck97eWUvx8r9po6ZcpZMC2v0A3GHsdSpW+jSW3TUYLVv8+JsRUHpsSlZrd5qNCecRshwSp6g8D/gmwD8hiZKwP2E6FdledCfyHj9pw8iXffmHIwTPLJy5LnSq3V6zV6lWY0ymZb3WbtkLauwT1K4KGDOK5lUa0Tl31IDpQZKDZQaKDVQaqDUwPlooDROzkd7l2raVbze7//4j//47Ows/4NpXTfddBMXikBeT6Js4RaJX8DbVd+1a/cTnvDEffuufPrTn8luOXTooINQPv3pTztKaeeuPXfcccfBg4eBa8vTmSaMjG5nZbI5+Zibpm+6ZjL8EMFqVWOQr3F4CzymphrHD3Sq3TmHNcZClWR9eHbtFdNHHth+auHM7KnjzAYWgyQhXqu25LBenoxkSzAp2DKsk23bWjM37T08O7uw2FlZdo67JxV7da1UW52lMzYMrtqci4URRg57RWiZq+PK3a1tU1c8trOL34P1Eu4YxgnJkgnRqFcfOFx775728cOcJTw6WIax5N8Vu6auv6pz96FZu1uFCyrj81XjZLWM4/8kzuMfrWaw3sMLH6+8Ueo4XNkMtqVmfemqvab28XLFgcGhj2TXFRln+y1pPmpSoqjPUJe/+V9BWwZKDZQaKDVQaqDUQKmBUgNb0UBpnGxFa5d6GqZGQp/VL/qiL8qGiqXwtgxWLqtNlpaWAFYL4q+77jqUqbDx17klfCyO1L3xxpukOnHixBOf+KQjR44gdvvXf/3XZoi58HSkLuOk5yT1ysL2iZp/a7h2UHNY9tvt2lQb4l9IAF8gGw+d6VbbzlET2yfnlmKiV55RZP9eU7VOtPdNT4VvJEkW8sHWlqNcsav9xMdUF5ZWzAorQPVks3Hi2I77D+yorHCAxHp2dkTgaqtdKrWJRrXdgq3D+oonwTOvfulz/zQa9f5ie8Kx872VYi0KOeluz472o/bv4N2ZX7EFmYispHC7bOLK1OMJN3o2PsX5xCZxw7qoNCrtiVZv787WRN0aG8ZJd63q1+EftVcIi8+mSr4OrzK61ECpgVIDpQZKDZQaKDWwqoHSOHmYNoUMPfkicvmPHTv2ute9TiS7woZdV1999Qtf+MKZmZkh7SDgZnGJNxPMzsJxfGECqe122+Su3/qt37rhhhtuvPFGC9J5Vyrd5QRbA/uvXoGE8+Wv9eYT9fBmMBXYL8Cuf+EmqfaWr9ozuWfPtk6tmk+DlyZOFOl27q3t3TbNOJEtDsweJk0A5clm5ebrJvsV55kEl4ycm/XK0W21u66cqnTPhHdkFU977oB3tlP8TTOYIo2na7LZ8cu0tbb5TWB6WFnxKASOQL873aq29rav3D2x0AmW8c+zlFhgjUmwv5ivrCVz5ii2Va84VKZZ6zUsQumxB/3Ldtq6JYhiYhFXcMqh8rfUQKmBUgOlBkoNlBooNXA+GiiNk/PR3mWV1uklzBI2BpPjWc961uMf/3h+kvVKCLNzmLgKgqc+9akMm6/5mq/5ju/4jmuvvZbZY3oY2J58DgVVgvCr4N0feJ4pEt6SDHAZMTFFii+kA+zWbABsMbv1H5Cyy7kjjUbvcGW+XrH2PdBw7PTFFpAk/BfLQWrVPLPCI5lbIN+snqkvNPsnK92TNXklQJ3+eBgczF7K3hI2x6pckZV4POx8zPgRSP9QpjyrvSUSNeNslNqkjcRytEcD6QeCid1F+ZPKH5ZJNq4okUOp1l+xZCiiolIGL2VaLRaNJ6UXxhz9oA9+5VVqoNRAqYFSA6UGSg2UGjgfDZTGyflo79JOy24IZJ4uNgmD5NSpU6ZpffKTnzx8+LBjGX/wB3/QwYtjC1kkLJhYGb9z587rr7/+Na95zSte8YrnPe95TJczZ844kvHBHHKOGcsOIto1aBseCgvq4eMljguWA5wcUNg5J8yVfqVZWea7CKsnsHLydsRUK4cnMheqHfDaqm4rKdJ+W62qAxpX6n2rUBYCPQfmjoQmcvnHP1KvNdNkMXmGnKvqiBCm1ohzFbUajfagGcarYHmMJSuyqfbCvRBcI0n+Pxsrn+WUnl28PzFtLpqB/Qo6oYSwDpMVFiIPlkJ48DY8TYlW9FrdXbylLCUrNVBqoNRAqYFSA6UGLg0NlMbJpVFPD4WUoDXnhl/I20qSl770pcvLy//0T//03ve+11EnH/jAB8z1Omu+hZUiwGHy2te+9hd/8Rf/z//5PxbWs3YmJyYXFpe6nWSfwP+rttBGWBbQj2XxsRexQ9k5LgIqi4tV8atXbI2Vdxc2Yg8vh4GEd9rKt8Vx4uJvsXYiuXfCyoCeM4CO3zTqr2Cxp1j9zOnu3OkF/NdMqOR18bRmOUr96MnF0wsrzkhhoyTHAF7ZBsGHfcJcSimTbElXIU6UcqMinlWpn2sCAicNh9A0xV+1JoGS+Jf+j99Qc1iFtBV0asddRJRXqYFSA5eZBrzYuccuApdZATdTnNy7rX25NpOipCk1UGrgAmigNE4ugBIvXRZ//ud/zgIxBYvTI8/LMrPLBlx/93d/x4viHEbrRpx5snEBi+7bMY633norr4tl8X/4h39oYf2znnVrzO+q2U/Liet5D6gAuAPgfRX+DmQRLo9Gg0PDehgHOCY/RSBjGLjWdTZ97Lb12VQMFXsSJ1umEWcmWucShkayZ2Bn3psVB9GHBySyCBztX+BvK2IOHz116OiZ0/MyqTI1It4xKmk+EyI7iS2cnjt1enmlm42gSOn/OHvetscOoa80gtxh9Iknu2X1iqlgxc1a5MX9NyawRdGzocH0i7KGKbZWkFABVVNOHPrStzSFrjtpdzWkuQ1c3EUspbs0NKDPMUTi17RSm5vrVbYs99/+7d/aKt2YCyYxVjI5uWVWGyd0du1dd93Fe2xgxO6FV1555cb0l9bThzM0t5DS2V9mLKsyyyxV7qVVd6W0pQYuUQ2cBXdeoqUqxd6MBgBKJy2avuXL/ahHPYrfQ8/LtDh69KivkQs+4Fo5q3FS5OXDzBRxRKPAW97ylv/8n//zju079+/fv2PnLsc8Lhtvj+PkXVLAuq6wKtbgb44RaWy+h8PCUnd+qbtoLbpZXpGkP8Fgqa0cnV1eWLYKP9K7sGMnOEl+udc4dmrpzJllpkgA6GQw7Ng+efTY0onTvUpjGz75X5rV1Tp5+swdn37gM4fmqq3tPZZGZBFelmRX9Fd63e2Ttc7SwtJyr5u2/wpzx1BinOLimPrmSrd6+syy40HCTjHNK3wJ4eTBBcwPyS6tSxGSwMnwsxDIyS/ZRIlye6JI/tGrfZy5tLa1K9tt7JVKnVR9aZW2lPbi1YAxkf/5P/8nuP+Yxzzmn//zf+7XO16MgGxSbvS6r7e+9a3vfve7sTLd9Au+4AtsP5g389gkk82TmQ1rt0Mdqfmxzq69PIyTrPbcX29eFZcZ5ac+9SkTARjJPknPec5zSuPkMqvfsjgXrQZK4+SirZqHXDBfHZ/SPJroyMVf+ZVfMbnLKe/WnPi064vz+vizylF8vQK7V6tSvehFL9Kb/7t/92Pf/MIXfc/3fPcLXvCCJzzh8e32FJshFl2HkYISeeSS+GfoG5yAfwOQ9Ub7zjsOfuLu2RPzvCW1tEVvf6LVmGjVTx06eOLUQgLLMbsImLZoZKlXP3hs6d3vvwt6DjeIyGS37Nw+cebUyXuPdhpTV7JAbExl0N+iedbF3fedPHKqu1zf3m7tZHMkaJ5W3zMtqp1Wpd+cNJVrodW0/ZdUWQ3wuj2GJ5Y6/fsOnfy7f7h3YWXCpC8PGTCB6JPXZc3eymj/rPq7KAiy5ERJGwCEdjmG6n02W5x5GY6lZLWoIEqfbPVv3Ff9siff1Gyk8xopKGw2icqr1MD5asDOHIA+/+2/+Bf/gvPksY99LI7n2rqMqjgW9hOf+MTx48cNe997771QJm4PEbhknJjOqtPbvXs3UXlpzlcLn+/0OucsQg6cq/4/3+JfmPyV3dfwjW98I2tTK2InP/GJT7wwrEsupQZKDWyogdI42VA9l/vDV77ylb/2a7/2v/7X/9ILm8rFVrGE3ZknKysrX/mVX3nNNddsRgHSFp+uHOY/MUnsl3/5je997//r31/+5V/ecP31nDNPf8bTH/WoR+/evcs6dAbK6nB8oN5VXBtxZlw1Jg4dPnboqBlVjf7EHjHZm1FtNxoT9Wpzqloz4yuMm253JZaz1yqzp87cde/cYneyNTERU7ySc4RUDkDp1pd6lal+rb2KrsPTEhlWa3xCbXvnrlTbkpigFUsowjngcRxaH46WijX2UHpyiEhjApfUteq9h479wx0PLHQnevWdlaqXKO0TlgqRja30YV/9um9GhxcDDcmT+lMxkuxUEdZKlN6TMNpCzn5/oXvmM0dO3nnP4Ruuu2KqVe91nQMT18VQilKGS10DXlu2rkVrxkr8pha32rSKfuasZeQhMVVVm8zTU73qLAf9Uk4ofvOszpoXAtyAVzkS+CFyzmxGjAtFc+edd5qa+853vpP36bu/+7tti5LnNV0o/pcKH9WauzVmrcZzGdTspaL5Us5SA6Vx8rBuA4aCvu3bvs1sByvgDx06xCzR/5r/YDbFk5/85JmZmc1op/jMFwHYwgii0xivuOKKRz7ykffdZ+Dyvr/8q7+888Cde/funZycQBCdfr86NTl1++2fCgQci+ChX0DYDr314yfPnF5gqtQb9WY37xdsAXotdu5KvpGwIlxpwD6OJLGg5cyZxTidpNZ0Rn3gZG4ZNhCmjIdqvZsnJ6VUkXW3v2/3jqPHzfgyNWuF46TwGADg6Zz4rqM/up2uMx2TyZRShj+mYY7Z7GLv+Olao7mdo8i2XdlRgyJtX5woM47PwUvjNzRqXc4qDEwypzUncJybUCjFcJBEFVT6Zzpn7j58Zs++3tREqxKHNg6muzQKXEp50WrAS+vV1hf5JaRbDczv5gVGzAFriqnZqqZ16dPy/uY4PBRtVXbsn3xlmTcv6kVIyXnFl25nFF+Eb/mWb/m8g/Jzrf0Lq9LclijhnFrghZWh5FZq4OGmgdI4ebjV+IPKawrWl3zJl1jn5+REXyOzvX1fhb/8y79cZJ7x9aAEm77xhZ6enn70ox+9f/9+8yuscN2+fdvs7OzSkg+fXX3jMkVqeWHpzNxpeMHCDl0/QBLTvpLzpFI5A/GyE5Ivwo8FHewEQ/j5iMAYyA8cALH0e41GbXKi2est9nqwMhwtHXOk23PKe5/J0ONkSfAaho65ZVZOXLlnenZ+eam6cHq5zTCKJCFS7L9FMCJNT9W7VaNl4WhJ16rt1O1XV/qN5V6zgrs9wdLjTJL2FU655xSX0i9LJAyM1bImyQdjPIz/wjyjoFq32ljqN3p2IAAdU0WUX+5LqbYvNVm31rosEtCb6Xac2mRYZPMgewtoeGsSfo7rIRtmZxVVv0pXOlt7CQj4KMRbnwYgzpp28yU6V4ZDlbLJ5EOpNi/eIKVSX8CCD3Iuw6UGSg2M1UBpnIxVy8Mo0vgi+4HzxCxt/bjL1+hCubB95MwHyGfJs4LMGRPjw5f1Cwc36o0/+5M/+ehHP3xqdta6eQPzFSvge5V9+/bufGDxxOJyp7sMEcfyB+C555yTLqdLzaKSNFJPWt+MbrfDMrl63/YD988a0+91m6ZasVp6Fq23m06C73eWnVWfsHca9w/zpjM12bh5/94de/tHZ7EhUYLlQcQ4YRH1tk/X508u7ZqeONKAv5MUVcevxASndrsx1a7PL5xptXJx4PNViTBi6lySDSi0kNQ6TvpwWIVlGCuG+t3ldr1yzZW7Y56MB+HCujSLPK6kZdzFo4GNEWF+/TeQVs/Deavdgtde1Ey5Mc9RmrPmMiiAvHJvMhh5AcPnJMxovrnsZ2VCXab4erv9+hxIddYko3kVMeul3UxFZCbrUa4XP5i1MAGKmMEk6wlWEG8yMMRn6HaTTEqyUgOlBgY1UBong9p42IVzN+qzHShz4BrswQeizzm4xqfKwzA5WW+3Y0PGgdH5mMrVnGyfXlp879+87znP2bZz+47O8qJJVjunph+x/6qV5tzdR5yfaHco/+IQRr+24fH9z/jfN9PWwu4slJ+5YXu/PnP/0dnTSwBz7O5rk689u2wrtTQ90agsmvS1mizmJVWWF1dW6rXWVbsa+3aF+yUbTGFkxH8Opmc4Ve7vV3dMVVo8KEwj8NuuxX1GTnPm2h1mnHz4YwfPLM9X02GMPn9p+hPOuDNxLjGwTrFpQ+RUP2N/kuek16naFHqq1b1x39Rjb9gx2WYaLkbUil3dPosAxjIoI0sNnJMG1nqPdRNtTJCfwtbnCa83zmVIOH1pptdPeXROaYdYjb29IAw3YJLF5jO3cwDLhPeb9kYlyR+O0fixMbIbpM9ZZMoNJBllNUQ8dFvQD+Y1lqYg8LQIS86wLCzYgttmAoO5DDLcTNqSptRAqYGxGiiNk7FqucwjdaBKqEstetUi8FCUPPwOKcOh8fWwCKqVfVfu+5KnPMW5KE960hcwThpQvbNDar19e2yUtfum/TtMowqpULNNet1D227atWNblpPYhkPDILAJV61//VXtvVfsWe7FaL4vKg/MRLtx/MiOT9++u9JbtvcW4m6YDb5JPeOBveqSc+i5YVgaaUJxyjtEdQY8ho1WrdvrLHRXFmMmWHgV2B0Wv3enms0brpya/tLrlzoIUyqPk9cFwSVnmawqM7YPzsExv7FhWlqXo/E0a5Xd7dp0u9vvrpg7F9Ua/5VXqYELqQGwuBg0+ehHP2pdnIXaHLzyACK5RGzaa+MNSHps96Whvu1tb7vrrrvMTQKyb7vttuLIlFEEaf/097///R/+8IedzuTiOpDEHh5f/dVfbV0+SXh9sfof/+N/gLBf/MVf/JSnPMV+IYN8chhlBrhE+vu//3u7jBw4cMB0WTLjuW/fvic96Un2GtmkmuRl+8T3ve99d9xxh+mwlqfjz2aYmZkx8/YRj3iE241Zzc3NEeCv//qvnddBDFJlk+PLvuzLrMMx1W0wucU5dl6+7777bHHm1+J+ZXnXu96VdUgYmlGEL/zCL1T8wYTrhf/hH/5Bx845b8GPdYwm16kLh8986EMfuueee+zv/IpXvGJsWtWB7CMf+YhFL2qc2DzwSm1p/s033ywJbf/v//2/qUW9CL/85S+3yjGzcktgSjOXmIn1Dd/wDVdffTVFWfj4f//v/5UvPSiLGDy/9Eu/VCvKW79szTKhtN/8zd/0axcZAijU85///CHFji1jGVlqoNTABhoojZMNlHPZPtLX68EvYPEyN2zX47lmn8QChaHrxhtu1Jv/7M/+9NzsnO93r9XqdKxAWWrVW7u3Nab7yaVDWMZJ2DKdzvFWu5k/yWlPYku0cex3zeKaaNTb7Im0Qj1cLX27D9d6C5XpCSbJgoicedDn6VuxLoWxkTbb6mV3R+bctalw7BqcDJJeLPgOCyjgOa69ZRvsthu1q3a2O2Ec4Yo8nsW1Onkk31wyv7nw42VPRYvyUwfDz37MJrbVTL9bZq2FRlT8aL1eMkUvBb0YNZDNA79QspXZH/zgBz/+8Y8Le6k1NvF234I+7fTKPrHrhv2UBouReyS2wQc+8AFgFEj99m//9sI4KSiBVKfQOovWQXsf+9jHMAQx8+xTNo/1KnKEXFkCNpMFQB3AggC+f9zjHofJaLOHdz0F7v/4j/8YNLeXMQ4QOUrxZLajMegMptsieQMISwZmiUOoPvOZzxAMpMaEbcBac8H6cDkcnE0UdlRRosEAWwvEVyhmEpHogVqUi9Vhp2YCEIOlVJRCFswGqs47oygLvC53pZCWaUQqtoHsNmmc0Orb3/529AwAphRV/Mmf/ElWiyWO9lwZlDaHlVR2MlXdJJcv40Q10Z6KuP3226UittWMCDQM1efpS17yksI4URyFVfD3vOc9Mv26r/s65pmEisa+dZAXNSoXkwlPFgs+isN2Ws/KHRWyiFEip6DY7pLGRO7fv5+1o4IKgjJQaqDUwNY0UBonW9PbJZ+q+CB9zkoyFr6CtldeddXTnvblrWbjnrvvfuxjHrtr1+5ud9EykjisvVZpZZ9LkrLpiBHGS3+5nkwFTyx1N2SfJhwJhjnR63KBcLHEaL4vcct+wRXHP56uVJaSaYFR2BLJSpG5ncFqtiJGn2wL0av4XFRs8xVLvW32lS2QYBBmXc/iHJPJxDaaVetRVh9n46TaCfZjC/s5U/VWMgp3T3iWxl5UHae48A0JULc//Q6/SVJj8lMp8KVX5rFlLSMvCg1khOf8kH/8x3/89V//dUPpTAsWAqRrgTssCGVCluApmPv1X//19gZksWiZxbsnbB9hCQFcFoVbl7LF25naKiwOPRti/6Vf+qUTJ04AweApM4YJAbwyRRgSzBuYmP8BiAfWMzcMM7fMJ+tLWCoygMs8Fa973evwZwZgSHLcsszAt6fPfvazv/mbv5nMo/YSzjgA08j++3//7xwm8mV6kUrZFSQ/ZW9QESU4DYaZUUDzovKYbUAzG0nRiEF1TBpPCS/VX/zFX7B82AwcUPZsRJATUgIjRC5uFcclhkh+XR4plN8il40DiG0CSTZlV1mu17/+9WwJqTDBcDA5YgRKzVakdk8pk/1GRbwc7CJGHaOF2M973vNoFU9aVSMSZp4FN/JrJB5RGgEYabZFlhYr5aU3uUurWv/mb/6GMcYjp6SsXBZLweSsAZxtuPzf/tt/08wQs5dw+Iqv+IpzYnLWXEqCUgMPTw2UxsnDs97Pq9S+VYNfZbyGbjfDPeGEsAjseLV7185/9kVP9k1imTznq7/a0hQ7evX6K0yNOFUEu2R4NJPvpFZZqcW0q8jUnjKRl2XqPqXgMXDNqmFgmKXF3HDSfGWqWjH1aLHSWwzKdAUhO6ZW7zhasF/vVBvJExPIe+1yALzvcbUTC+8ZOM5OCdwetkvQxNbBzbCJcGb5iPG/OVGeM16yMjJuX+N3CfwlfRRgvSspOvbmatWbSmiZiWZAwwpO1VtoAOtlVMY/zDWgVdEAYMpy0CeAlbCpIfAnPOEJUDhTwcg6i8VwuKlKMOVb3vIWcPOmm26y/L1QXW6QnkKKGeYWj4qA5Ia93/CGN4C2snNKCeZG5XlFMMwuC8P8Av/1v/7XbJ/A2ZknkWRB1KLlC2BiVN7cIWzRmxVGYGLzwDA2yAwEy5Q873jHOwBlxoYZYgWHLJhbE8zMH4PCxbCXctkJhiG7wvA/JwDlyOLNb34z8ez2e8sttxR8SCULFhegz7Zh2HB3OBdScmKTwdwtvyA1G+Anf/In2VGAtXIpNb8EQE9IJh+BFYdLgW6heRfDxrSumZmZQocbB4iEp5LSsHpke+Cgmogh4aDjiMzcHYrjUCy506SCk8Q2KqpDERQzz+vD5Hd/93d5jdgkqkwqgSEx8M/50oPmISEL7cYbb1QX7DGp2C0cJipXvHJRNTOY/03pzmpa5PZJsSqa9agWSKtQ3/iN38g7J98hYcrbUgOlBraggdI42YLSHu5JfHIGv8rnpw5IpG8Y7NU/87M/+ROvev/7//YJT3jiTTfdWOk1zywZD+tk80OGaQdh4JmRABCvrTknSCwDYWzkcwaaNcvYYxTfSL8vtCnaFYeY2w847Js05B8swtfBvdI4cnT2roOnj89i0ehX0WCesjJ9qdfZPlVfPHPi0IlFGxLH8hjmEPQeWYVnJmWbltEHqA+Mbr1+sl9iVLYACuennM9l6rCvRvNTltVoSqvWVpwXn+5zAWNSlz0C/B/nyI9JPsqwjCk1cFYNaF2m3ADips14b//jf/yPoLm1HyJhR4AVNAT3rWcwewe4BBMBxH//7/99bpYZPgoXF3CcIwezNkfr93//98XgAJRzvwDi3BQuCUFeSNr4OsuEd4ULgi+Ch8GAfWYroUDBUBi+h+alAqaB/uyXALIBVpyN/TOozDX67d/+bVnwXVgLoSwFBwFCEoZRwWxwq7A/+7M/y7MB38ta8Vk7kpABWP/xH/9xkBqw9shsIjwJIBXlmBCVF1fMzMywW17wgheA3Qg8JdVXfdVXWY3D8Mu+COt5GF3gNT5cOgqOOZ8ATE9mM8duvfVWCV3ZzEOWbzfzm20eFgVW9GAFyLd+67fq8KXN8mQmLCWmgvUtPB5iFPO2227bv38/TSJTudRigpaiUeDP//zPMynFU1e2c4YkyXWRzQxuE2K/9KUvNXlYEtWBmxi31Pirv/qrJv6xVbS017zmNT/wAz/ARBniNnSLuXxVX1agArq+93u/lwtrsERDqcrbUgOlBs5JA6Vxck7qKolXNcAVrkP3sYQYDEf5nvkWGmzzLbHi06f0rJpa+6zH173ZbN1w48zTnvHMD33w79761rd+7/d+t3nR7WplecXGXNCwC/BlGGT4uwqC2RoBjMOFwgsSZzWeOrl89MTxpWW7D6dZSv2uz+HJEycPH5uttafRJVZ+WBkN5zzec//Jew/x0UxzwfQrDYspwryQOHblqi87zWOxsriSFlnIPV1hnzBCai2L9gm35Gkv9guLh+mXqYJHXgiTk1wuv8oV51HySbWa9YlWIwoqJpl02WK5XEpaluPzrwEIEsqHYi0ngLzNxgFDszGgz4EO/aIB9wF0ZowpWPBrpslkuQw5jH7w1kurBzMzyiB9dk286EUvYj+Y+wRoFkmkgmL/9b/+12hAWIgf+kSwnnYkZJzoAwkM0OOmhxTpwooBkH0I1nmDwsbs2Qbkn5mZQZB5GoY3GM9aAOV5M77ru77LynVKUNLgktaFKzj5GRuvetWrzClCzAlgTTb/iSzwoTdTmLAiPKcHFC4LSD1LzrQg4dd+7dcyA1hBaMB9zhnGCQKPiEo2v9nQkh3lYyt3kQIbaCCXYugXPduDJWbWkxlZHDjUkhkWlDw5v/d7v8cUZH4wkFhT1oFQV1GhsqYHv7p0kb/wC7+gIFxP6wmDksAUpXl83/d933Of+1ymjpiCHoGyO4OYuhhFPmH08K/+1b8qRFovgJ7C/+zP/swv/nT+/d///U9/+tOJh/96qcr4UgOlBs5JA6Vxck7qKolDA7p1w3U+7b5bXOSG2XzMfLnNNPA5MRnA2J7xp02ZKMGP1eE459Yzn/lMxzV+5KMfMZxpVxaOe8NcvB8rKx2OjIC/qwjDnzWokZZA+FZ1eo2T873b7zp5/NRcnjAdvo1Kf3JiZX72zLFT3Vp7p4xWGXhWax46Nn/4+NLcUq3fmIi1LeEFCQ9IrK1g9lR75ocxeGL59+o/H54Q1cTyxZXK8dmFB47NLXfjbPkkWUyLCoJUomTDpODl9UM1Zq+1mpU92/s3XLMj9jiL9pCWxV9eJS1L83nUQEaW8KI+BKw0/yePgg+KBBTaNkpHYSIQlA9qM1HYA3A8slGYOBgDlZplBBCDqnowlgkbIKPzwSyEcXviE58I6BMGhM3WC/FcQ5T5FplJXOZQ6b6yJDk+5w6/mqT0Td/0TW9605vgdaM5xvUzaM5kgC8XDdMF7NaFcnGwi/RvRV6Zjxhic4mYoKXsTCxbVzFCsnGidLThFzEEb3IU7RVMRCo1a4T5pN8WzmvccxZuc+lYejj4RV+kLcQ4pwA+TA4FdyamLcKyoTXIgdIUma+G0aKuLcVhxihgLuwgpbDZWXwUZr4xRyUcoiG87HLtCLhYcWzFmZmZ0XwVljyyYyISwHAbTXKnUL6MMME8a0NAcvQKYqOCP/iDP+CyQ8/QYuYpF817OiRqeVtqoNTAljVQGidbVt3DN6H+2gwHmMAwm3EsE6AtDfSdy135n/7pn1rr+cIXvtB06s3rCE9fLx8GOOA3f+u3Hnjg6DOf+YzHPf7x8bntWx8fY2DBLX8rYg12TLHynYWO6/XG/HzPBK2///TpZr1dq036TOSlKt1afX55+czKZKW+PR8DHy4VaWr1k/P9+RUnmDQrNYc2+vyHcSKD+B4xM1DFEGowCmdJNjpSSktUTpxc/NRdx+6892ivNmn5CVIUyVuS7JPALasJNq+Bi5iSWykKlIYizTvp1ioLV0wvTk3N7No5VXekZqzMuZzKexFXxeUumvfbW6eU2Q0CJrIHcsxQ0WFBT+FUS1DuuOMOQxJ+IdoCSQ+lwrnggLmZWnot0N86E+P0WK0HLiF7ThUjL+yZ3AtlzoWoBVsxCJglRv0HLZOCQELFYW79zu/8DjlZU4wTuWfZFMHojIwgYBaRmWZGfwYqGzGlAABAAElEQVTFLvgIYAXKszHYQqwsJopUclcKfTKHCSePLCzJ4FoxlYuJIr7gQDxC6nKznMVMrZzdkOqKVFsIYJgtHDieMUmkUeZMAvO+9Pye+mqYwreeZUIANAwY08NMt6OrUZEoodCnMNtD2derDpXL82+KoO3L6JO56ENWGCeYY5W1mvXJD8OIMp+QGUn5mh/HGu2NFmpUsDKm1ECpgc1roDRONq+rknJVA7nr96lz+SL6LvpgsCJ09GYCIPIV99X3RVzvez+qSp07Yh8SA13gginFf/Guv7jtttu43X0zPPKFk2/OOicXlgpmthZidv70Zw6f6NR2NFttS0JA5QA4CGzsVV3sVVrd3qrtkcybsHNMCqg3lqyTR9sJyycwkWFD+9SY1mVZSYbbvnTxrVudXSYOUq8eOX76nsPz1dbuZmtn5BHmi1Sr5xhytlxenhOqiAKFrqGfVr/amT+1cPDjt9/7pMfv37190sc7GWNZYblyyt9SA+elAWPeZhNB3vk1z7+DHMXoFsx9AmSFDaJz4ZpTKtKtNqlTGqLPtx4hBi51Kddddx0OG0/WkkoXRJj9+/fD+rkjGuRchMksdxYFD0kRORRAoNvUVeq6+DfA6/T6hLFhGy5LTZgoaJ7xjGcURoviDDEpbhkwULUe2IQostmPS8fL3QQ0WzXuEYay0ItywphYJWGhFpSugtWFDZA5+ua1Sx1Ri4Lnwq5Fr/5lofGEENtkNsvKWU2DaYeI3WajlPvCXOJRStrLkWRQcUwdnEWup0ZKc+UlMYxDA2SEzPQC6lRCtg3hsTVfwIZjdKjNWDzznd/5nXS4AfNR4cuYUgOlBjajgdI42YyWSpphDeidfV/9GjR69atfrXPXcRt2svGLz6Qu3nd3OM3Z7nHwDWCZGBXD0LfHhjMmOVgc+TVf8zVWhWYUYhKCjw1mPgmG7budOG3DjOxGGCI8KgGU7akVgDrslopHlknYL9inMtkQVm87CqV73ZU7jp9aOHl6bv7MPF62BsZTkiSmm16rVu8tLXass1gFBwjiTBRbgy1066dXWu2JSR6YZLb4EodFVICIdCDj2Qp8MT2Pwo+71qys0I61NbHjMs+SMzL7k3PL1eV+jT8qHEfhOyqvUgPnq4EMK3Ex6mGcguWQY4r4IoPcXTADdETgI2MDCofsMwbVORSUOZA5eIoGjoc7BSBmJsco86G0uDFjzDXi8WDY5CwKGrcuDD0iDBRbPBob0MuBtsjYOcSWezYYwGJmhrDsuKatvpN8NLtBnuwZs4ywgsL1uohhZcLIgn1i5pjFJ5wSluDbc9m8Ne4LU86UJecoI2JjSAbXIOcLGCaP8tIMnqP1IpKchEfDeaIsmVK8hH5HBRODxqdHMVUimuLySBZ+pWVXIPD5KPxCBdlgQBMysmZYDU8frzy+hoCKcBikNN+YhGJkapMGuwbTNjLZuQYpy3CpgVID56mB0jg5TwU+HJPriHOPrPC+KMwGswiEzfLy8fNZ5fuGLXx6fRvGfo3W0xrOGLJPDBzihpWxMZvGGBPlyveNwc0nhBfeNGJfiEazYUmKrYS3Tbevv3rn3Q8c6S4tMhR8UnwreD861frK8unOykKvY3EJhO1rx9bo1ror2yebj75p9849U3NLdUZMtiviCyPkT78/PVGdO7G4c/vU3AMZ6GSS+G02Gw6CdCpaI6aPgeZpelmUqhfngUT64HQJXSFxkjuVvxB8VS3uQysxl84pL51eZ5F+du7aazwRfgifSpgoRaoyUGrgfDWg9/C+e+ujaa1zeaQjAkMFdDWSIFyPvojXb8D0eUSccaK3KR6tk0+gZBBW5wbKZ8Q8Sqlr8og8JBl9WsTIy8WWyAILe5TZAr4sDf0bVpweljQoEXtjg0ylRaBEfrNxIkZybK3GUTqTb21bbMKbNRVuDfybBccLpDjmdJlnRckh0PpKLiQ/p8AgQ2oxnKRjX48Dk8BgFoUou1/yr0dZxONPh+gVvIjMgShMurLdJeuNayRnmqtV1i6pM6viVmuhZJ8hBiQbjxsqL1IqKIdkKG9LDZQaOE8NbNSNnifrMvllrAGdst5c7+9jXIx1+c4ZkzMBOn9N88DVuSoBZ98SM7NvueUWkxZwA1BMSjbEyODx1GCVHHnhIQwTFbhFHCg/OdGyPvvRp+a7Jn/lLE2ualSnJxpTjdbO6Vqv8/+z9yZAlpX13f+5++29Z9+ZlRkGhgFEQHgRZFgE8Y/iSyRGMK+JSSqaUEkqxlTqTUXzWrFSKUsrKTUxBo1bRIwighpRRARhYNiGgRlmX5l9pvfuu/8/z/Pce+b07b2np/ve298zPbfPec6zfs7tc37f83sWVvDljB27bgZJZHg/OXtmXVNrfS96wm78OmOM05cj5h2LdbTUhw6blVLcK7QcpjhTec1tTqxY3HjsRF9vLkO3LqtPnHFeXMewaOePtfFTGp8nslUY5k1qaRtoJWCd5WIJBsQ3LpnXyhyfdmEZC7aURr9F4OwJcPfANOQvnayGMQHdXYg4zqYfJmYwH4x+EhKZIriDjVhbF5n7EpFJxTYwCYFEIwJ5DjxbFuKsXvfJKRKycdvEArbZmyF2mN28xXdVLUvukvBJcdjovPh3dSPErxsDxxlrwY0UhzOyh/EtuFB43cOMvbAinGlLGHWzbNkyfAtulIWf1i+OWvn749tx7UKZ+AqBkLKCuNZsLn+Y+Gf9nbKiXa04O1QEF040F5Pk/k5ZVv6hzezMhwvn2F0jquc8KlwOHkAIHvd9czm7zF2hfobaEQEROBsCEidnQ09pDQFu33y6+zg3bn+fW/a479ckxC6hXwfPXSQKjwRTUukZg1DhNeG2bVsXLpzPs4yzOEtmNCfe/pYlqRQz+/IoMiuhUKeGhtDxY9G9uxoL+R4GTJgfj5UX8W5gC+By8aJepIHC7ConpgAMDGN4mIono6HeaD5RSHmZLkZ1msKNqsFvEF0wK9HUEN3bnDrSRr8vI1g4Z7SN0T+4F2zpJrvq2mzXNzM1mb/1M8IACrVIIdLc0LB8fuOcFt4VZws5Ax+otul+Qu2IwFkR8A0+89c59J2Em497FWL+Yke3YSXjN3BGJ3cS3LwjpiNz3u7jfMAkHShmOMtGJq6ebn/4PDF2iexvVIlW8HKH7qyMEiEczcBEUryCYX9gVn4gqTiLjKEhDMRHqHDKVYAGIktYpYQh5kSgfxcTB+OFdg4WelIxwRd+FVzQf/Znf8bYbppGVqT1M+eQfXfI52jaVVZVm9qILpdJ2Vn/kKcGGwqK10+uRf6pgTsuTypDo+ydf4TrPmLpwSIGRnatplAuGTyhhP/kP/7jP5hLDU8UISR3dQb4OBAFS9e+CIiAT0DixEehnYojwL2eh4H/ys2vH73ImDLlySd/vWHDBrNKI66TbCaU74iHIvEkX+koSsEohFChPhnqiuViIc728hCxJgQPM/MQwc5mJZUInb+MtnA/PIGdE4AnNO6QqPmVT8fc3F8mS3Mc8dIMv2iIRc5f2rB8RT2hRpXYDQvd+h1GeF76DamcHWMBWb/JMFUyAgwqjDwphJJMkpZLG4GHLiGhgThMUp0SgSkm4Bu13E9cbzHuAkgORsoNbzpTbyLgvMW+55U5gmEoG3So8OFb7lLxifuCCQAw0PGfoEw+9KEPuYTDVC9YIvY9d0sXmXD/tonXgnDmGmFaqt/7vd/DoKfPGMPl0So0n8U96NxFnOXLlw9fz3GfHab+Lk9MfJw8GP00gRDiB9tVVi6n2IjDhcCbwX5ZhKEOfTJDRRg0HOHBBkAE7Yc//GFE3V//9V8jIz/1qU/9xV/8BbNCc9Zpy+GrPWjmChQBERiKgMTJUGQUXkEEyp5ArOWMrcDKKm2nTzc2NvEyP4OVjNooMLU/b/BzdgYvHhaY0XXhECKEF/xuHApuAaNErB3uDHIi0y/L2tbmOWfcAya5iWIee2FeatrnJflbDWJUD0Miw6zwiKWeM5OA2RP2BScnR/usrCC8rio0wHK2DSnWrl9jTAQLKGx7oISY2IzebkbABZ0tFdcuVahKCZg/YLuV/fmPrzl+Jrg+MC55z00+3Ebo6UQhw+dJBHpA4XZgIBxv0LFHB8Ynf7+IgWeHCSE38iQtkgkvMR5jDhklwvgQht4Nk9A/RXzcCCSkUVSVDINv8ckZ65kQ/CokIQLNZ0VzvDSsj86p3/zmN2ih5cuX+xm6aMT0W+TvBOMMv09yIowmoZtzjAm70EiPPvoon0ipYTJHv7HICZ4WKu9KGSYyFRhNHYbJwZ0iE1wlqMe7774bpxNzKjBlC9hZ+xL+4GUbMRNFEAERGCUBiZNRglK00RLgaeG20SYYNh5ZDTxPd2rm7GL+/m9/69sfvOdeJgUmTiZr3uKbyKRAX5hlTYyQQD1EWFzR9Muym33Jj+5g4Cov/Fnx3IXaR5hZhBED3GSA24VkdDmO2Sm5XFpzBvvcnLciqC/sMSWoeya5cHuyGLnKftEquxV/lw5NmGmbOTZPeSPZoJOnNxu0LAfTr2GEnhs2Z32IwGgJDPqHP9rEw8bjS8yLcNwFvHenjxOdtZjJCmvYddEZNCnvQVgOnMHQvOA3fwNDb8OfHSodqdgwyhlsjQWMyUtxdNNiUDv2N6eGSogpj4yBFcoEo5nqERO7mUHwdPQiH3ofsUSgS471TFZERmLhAkKV4Q0gZPfu3SzuQXhZQfxRO+vfqZ2h6jBM+CgvIjIJZzgXBfm0adMm+qENL05w+Pzwhz+kzhBzQ0GGqUNZo4aJOegpkrMhP3DUwGHZsmUsdsnoHbAzeodT1BnC8CT5QIaD5qlAERCBEQlInIyISBEGIUDHA15c8ckDj1s2Mbgvs8M7LZ4czuHOY4Mb98Au2oNkN5YgCuKRyez1r27e/B/333/hunWXXXoZ/QFymMt2SRKTmXmaG7uZ3zzZTb8j93w3Dxp7mnl+wpH2rnRHb2/Oi2FZmxgugUmPue3Fo96pNp7wuQwDKmyONk8imchEp9cXrhOzpkkx96I974qy2Qz+EbT7B48xFaEIOiO7aKT7ZaWeEV4cmw0mBjAkTHMNLbeZU9pEYAoJ2O+n/Y72rwR3JDZOlP5Ci6e5KTHhEmPE2bBxeQWOmUuvJ6z2/hmYbz7djX7+859v3LgRA5R8SFuWG3FI5Ux/V1xZJkMdkg8bCdmIwz7K5LrrrqPDFZKJxW2x1N2EWgNz4E7LvFv/+Z//+fjjjzMwj1R33HGHqwldjx566CEEFU279dZbuVUGZyQjjmsCN2dazT2cG7U/qM8VxClqQlvY4T7PNoxyG1g3QiiFjRa5s+z70dy+f4pwSmFqE9adZPoTetnRfY46M0zfTxLcYRIzfCws9YtgwAUEh2BWwZjsB+tQdsodEiH4DeGQLRiTzLk6fCL2oARq1u9iCZof/OAHeG+oKrTReKgpTg1Tk2Ce2hcBERiRgMTJiIgUYRAC3IV5LcfNmmeYu6ETwg6BbLwDIw13bXpRuzv7IFkEgkjo39aD+0Txw/3oLoSFunioPPX001/96lejfxDlZRtPOJ6yTp+4OO6Rz4OFVRqtRnI2tTWrQ6FUJvv6jkNb97SnQ60pump4uE1MHy1XEE/V1saw13f80LHTfWYGMOceoT5UkFgssRLlv6kgwy2KlXO/Od3v8ebX3N8Z4bQfb7J3Su3wG2T58/SmyeYnH0rjnirW3jA2geYS2V5wk11blScChgD3AexUPtmCRDgknHtU2S2FONwNGK6G3kAA4A9h3AX2JfHp3YQLgo04pMVwxyTlJf0DDzxABzBGjXNPIy1bsCC37250pGIbeLasDhyylUXjDwkNwPB0RAVVwvb9u7/7u89+9rN4FagSN1XKJZWTExjxn/zkJ7HmuQNj1v/Jn/yJM46JgOSgoxT90DDcETkIld/6rd/iLDlQBJkQTiZ4jSiIFz3k72br8uvjlr/kdoorBpFDTVBurtUuB1L5kQfdASYx2dxN2LTWboTwm89gKkKWLVvG+A2WzCIhWpGZGP/+7/+etNSZjaKh6kTU008//elPf5rr4pwVrqBgbuy7IiiFs8FTZeVyigh8Q/h09QxGdvsuK/j7l5Wvyl133YV7ivrs3r2bATxUm4Eo9MFzGAc2cGC2ChEBERiewAi3mOET6+x0I8Bt1zX54x//OL2Wudfz2OC1HHd2TvFI4xl5zz33cK/nHSSzVfJcGfg8GAgtGIf90dzceTryTvHLX/4y1fjXf/1XCuUdIYE4bfynCFmxUTf3bKNcY0YbmRHOhxMHDh050Z5OhxoLsRnRJP273NAR89jE5KYW0Xpa2xXiXMT23WKwPMEmj7gXjnelskePHT91moXPjCIydnrRpmcHi73c8hjY6koPMcLDmhEsadLSvGTRwjmzWpifOWu7z1nrwra00puh+lUlAffH6z6HbwB/9Zjj+E7dqxAXmXsIRid/+5xyd4CyTDA36Z/D7YJ1FTE38Y28/PLLvK1npUUmsCJPjE7UCz2+EAC4DvBL3H777Z/4xCcwi/07jF8WdzwCqS3ZkrasLA455d/W2HGbkxnByFQVFcGrFqxeenZR1p/+6Z+iNKjVlVdeiQWPQcwQEWrLpF7oE+pPnVlvkcWmuNm6OjDJ4Uc+8pHnnnuORaL27NnD0oF4YFgknmwZ1gIW5hLB30Ig1UCowIHk1NCvCR4JYNJqHBq//OUvWX0F/YOGIX/k0/Lly1kc04886I6vZNxZdx1dEe5UMBWtpj8bfdhoKa2mjc8888zv/u7v8gRhoUMazg5toa8aXXnpjYasYiF5lBWOL/ZJHsyNa8FGCLWFMGf9ptFef9+vGNfLPSD4dPV0p8jERWaHKhHosiVDrjKd6CDJup+s0IIO/NrXvsbhu9/97oFFuNz0KQIiMCYCg9xGx5RekachAW7ZrGfCXdi1nYciOwSyw1OE5x+H3MHZxgfHPRJGTMvjk2fkRz/60YcffpjuDbzU5IGBLcIzyT2WXA5YLTxQXZ4sQpBjTXcjMCInOvJd6agXrQvHmXqKjQ/z2/oDzIAVlkHH3DAGuO0dZqKwQ/JI/MTpzP43O46e7O4xz6xE8bFejOZM9iIck6r/dsYE6B9eEUf02jLSqvjhHrRIr2Md6ePth5efl58/p4nZ0wrGf+L6dZk2axOBc0GArx/biDljMmKDOp9tMD5GJ3/13AqIEAx3GXKKRRV5Bc5rlH/5l3/BysdM5xNzk15VnMXqZWgBxj3hTNOENYxvFrVAcncz8SvGIfc6SsE8paCys8Fo/r6rDzV0N08/nLQE3nTTTeglbHEWiSdPLGNMc+feIQLdzFz3J2qLZsAgJr6b58rlQ554PO67775vfOMbiBDqz70RDj/72c+wqqknqga9gUlNWSwmyIYICdaBUriT33nnnU4CkQOOIzwVlMhIGLTQiOIkmBuNdRuBlE7mbH4Et0NNqANKjLHmaCccPhTKLM9cBSQid3WawDAPONC6a6+9Fl/Q97//fS6QYx7MjcwpzhVEOF8M9l2EgeWaqpQq47QiGbrIfg5EgB7onHrhLJcbDcnrMOJ84Qtf4BDJRM2JiYJ1yfUpAiJwNgQkTs6G3rRL69/Hy56pPghu02zu0D0hOPRT+dHKdngeYBPgyicm2obnX1mEQQ+JzBs+N9zzF7/4BS8IeYozmwpvAXl36KpBHB5s9HwgB55BpjLGycNHKBpvLETozRWOWGvcPi2dJYTBzRPULZRCBqyqFiExRocdbxFB2Jzs6NrzZnd3OpLzEgysp4VWuBDD9Pew8xH3605QVv/wyBZXWYpJOzQ1K9bOeU5s1618qq/7eE86d6KltZ43w8yHZpwqRTknfTJpV2daFMR9A4OSF9JsWMPDt5nI2JSMc8N4xZBlnxCSYDXyx05y7ircFriruPBgbljb9ONy4xawgxnCgdGPywJL1EXGFYzdj9GM24T11OngRFa+pRvMiiTUgZsFO07ABM8G98mZjb5kVIysBjaQai9btgyxQfXQGEgRnAnoJTIhf268pOIUDhNcx4gE1lJcvnw5p1zO7LBhRrPCCRipPAY9vdfIgdssG2cpAiC4KRgpQbtIzk2S5Jxyn5RFQuYyphQmDSMH2o4jhWoTny5ewRYNtU9WXA4uIky4OuwPFdOFUwecJNSB5jOWA13EQ4HmE0K1aQveFXTU+vXrkWRcOG74nGUICsKGslwm7LBxCbgcbCSEMBXgLPkMrAAwiUy7iOZSuUtsnhQ2PhGoOV8tpKmj57LiQjDZwG233YYDx8kkMgERcd7xjneMdYjOwIopRASmOQGJk2n+BZiw5runQtkDgMDhC+C+T+ddXuMx8wmWAcnp2E33Ax5U9BYbOD6V3MjTL4VHCE+s97///TzF77//fvwnpEKu8Njm8cxZvCs8VCjF2QF8EmgmmvK82bNajrdnuvp6WMGMd2EEMeVwaWOG3Hw2HsbGYdWUEAuehKzqsOY4g0y6+3KnuwqhRH04mmBGL2upkxRz3QmzEVpdseZ8+ePbTMiFTuO5zoM5dPhkZyqTK9QhTugdx/OeZhpkI7S2xFS/RWA0BLA1+fvl75qXFNwHhk/C3QDbmo5YxOcmwJ3B3XP4S2eHHDCm+fPnFNkGs3K3ETQA9jedtTDBf/zjH3Ov4L7B5m4UuFY++MEPMjEgNyKnlzA9sXSJEMyNyOTjOoNRYec6DpY1cJ88qRW58TLFv5u5aO4QXUSPJmxx1kn86U9/ijagUCI4OxvHNSMcGJZNucGOZK7t3OLYEF0oK+x4uqtxG0R90QQXgUyY8JAX/9wqMbLJwdFwZ101ILZhwwaUD13I8F3gynBqis5dnHLxB7YrGAIW3goxfJyaL1u2zL0homLBOMF9Gk5l0CdIpu3bt3/zm99ElTnafKIZeOvEuBQi0DRigojK4OHBy0QTXFZUjMicBRHjEvkCgIhThA9aNJHBQt1AzQ6PD74D7upTbc6SP44aAHLF0YR+hcmNmHx5cN0DBx8Op5BDvCYDmsSJD0o7IjA+AsVb+fgSK5UInCUB3o3hDWdAIY8T94x0z2xezv3N3/wNvZBHmT+peIOF3/8v//IvX3/9dYwJnqC8/MPKwcKglM997nM87d72tqvpTc1w0HC8PpcP7T/SvXVv++6DnfRmynqsc17yoZgVPPIzmuLh9OlHvv+dk4d3/+0n/vj2W2/s6u6NRmJeMrnptfbnX22PJuLxuqTp9cW66c7VUho3P8pqV1g0VEZAaPCG1YwoNYH5fLqQ6fa8vlvevmJOcyxMT+5QDn2C9uQ0z+l4LMqjmlXJ2Ad1hbVL1akmAtiRGHnYhZiDzvIe1Kx0TcKOpP+PM7uJzG2EVMQnHNOfrNjhE8PX6ZwyJeBzITLmL7cRIrjknMI85VtNhgTSr4mh2H/+539OWX/1V3917733cochjiuC2lIQh6QlFZ8DCyKmi+8UjktCTGe1u1PEIcTFJISN1/kuZ3dIJcmZZlIxvyDiExhM5SK7OpCcVBTqULhTfJIDhjup2IK1De6TBCZsfgPdRQF1MJqfZ3CHbB1Vdyn9S0OcshKDqdw+SeDMxiEFEZ+a0F7KZQMR4XgqyJ9TjqEL5NBV1a8wqdzmIpSVRbZsDg47xGFz8YnpMiFP9v1TwYa74rhGICIOCYmGduIzGK2sUB2KgAiMSKDfy6QRYyuCCEwUAW7r3L55W/n1r3+duzk3d27xZM4zjBdUzA9D/womlKRr72hK5JFJTF4TfvGLXyQfXhPSk4EhoQweZWwlnQrw2uN8Z0L9Cy5Yy0OzkOsNFcLzZsUaW+asXzczk7NrdljniXkQGSO9EI+E2g4nX3hqVtuxPSzvSCDDUYji5QuzW5uXLgy9eexYX3cXT048LHT5sh25eGo6/8sZL4zNr/I/aFo/G8WvMc9sL5+pT4YuXreiMZlgBUZrLRCZKKSqupb6LdNOhRLghuDuDyMaeUTAyMZgpSXcT/z47HAnIdBZlu7sMK3FrES9kFXQpmTfbSREnOBdQUhwb+FuE3TpuEJdQX78ocoiAskpbmAEThHoV5h9QlxBfqAvsSjURfA/2fE3l5U7JKY16Yu+hYFxgpGD+8R0aSHpV8AFlkXz8yzbcVRJ6xCRys/H7QyVDwn9yxrM0+XjQoLKinACXZ6k5ZBPd+gXHczH3/fP+vWhSm4jDjsu3MXn0E/oh5CD/81hn3CXZ1lMHYqACIyJgMTJmHAp8tkS4F7vbvF8uu7UDCVEM+AkoTMxgTj0mR+GV1Z0O8Zpjmt+NEWS0L2ZQ89QBH1/8fiT1r2C5cUYnYYZXcrsLhdeeBFTU6YzKUafxCOJSCye92IMPXEd0OjZZUecmNm24jEv2h1JhHojhRTOg1I1zICL2S3RdSsb5s2ak8rmjDgxiV0Mnl7Owih/jJWSV+xvIzbcpTlTRdwmdOBiiuVwvrEufN6C+lgk6+XRadAwTSamFWxmR5sITAgBvoRYlqPPqiwyf/5sJHdf5uCnnycR8LIy9RM3BBwgdJFilBrWsB9h4A7ihFEQ6Aq0Op9ODgVLCRY6MLkf0+0QufxvLZAmeMrZu4GT/XZHLNTFLkMUzMKVNUw+RHBxgqlGs+8SurTu05UymrTEGb7hg0bw68mOX5YfOFS5RPCVTFlkDstCBmYSlCIjRh6YXCEiIAKDEpA4GRSLAs8VgeDtm3GWqAj8JPQeZjpLtARnGbhJH2sMBQai0Jd3lOLEr64zGvikIzJCBZHjTiFOGECJ8qHDGIYIK48Z2zqfQoREQjGzMrw1sN2H6d/FMItoOMHkXrnuUB43ixEn5sWZWRw90xAvJGeFZ7e0pHJm/Igz0I29YfwnTpZUpThhyZYzA28MC5xCpiGRcCEezdclsnCjg4VpL0BorT1bdU11Xwl91gYB3wylOQP3gzcczrpDdtzwAGYKXrFiBW5bBmAwumAoIHSLQpwwcxdWLF4d7k7ok6EijyY8WKvRxB8YJ9hSd5Y8BwaWJXQRBpY+mrTBrMhnYCbBCGX7I1asLP7ZHBpPr5Wmo6mhX7HRRD6bWimtCIjAmAic1R12TCUpsgj4BNyzjS7Fy5Yt27Bhgxt0iJwghN5ZfAZ7TfipBt0JPibdI5ZPNswINv8FJ84TtMpLL73EEMnbb39XPJ5gEvx8LhvKs14yDgIM7KKNzQgS2+k7xDTDTOQVCWVQI84vYmOgPzIhLxv1wtFYtC5upv8yia2sMW4Xl08xs0GrfK4CzTN5/JupMZ0Sgpk4ZQJhOnKHCplcOof1Z1vGq2m3M/7ylFIEJoSA/X66Pz+TX9kbd24Ffin+PjvcB4jJaDRs2W9/+9vLly9HdfjDP1wSciYm0oXXKCx7wuAW7ifME+XLGCL4mQf3CfTL8iNM7M6g+RNYVg1XqB/o7wys4aAZBuvs0g5VRDCmv08Sl8p9kpbNP8sO4WUhwbMj7vvJgzu8kCJPbv4jJifCiErG1dxlNWhVieA2d3bQOKOpieKIgAgECUicBGlof5IIcAfnhs78NgxYRzZgJaBM+MQCQD/wYhJ9gpZgrsYRK1T2MPAP/R2XA2rn93//9z//+c8zCoUVzZjbp7u7K5zPYmQX8m76UaMxUBYY6DxAsToizDhserF7ZoRtMTuUC3tYJFQ/V8iZ4Zgc9HvemiMy6B82YjMmIsLZywWUGhW3BpcRKXnTXGd/kbfxJ/nVtDxo45kQ/5R2RGAyCZSpkdEUzbeXlyDLli1j0iqGqHHbYamTP/iDP2B6K5IX/9btDsYrq4KwxN5PfvITTuE/Yb4HZul1pfgxg6ncqfF9BjOcwBz8bP2dcWTup/V3RsyEmGWR7f3yDOERcxg+gp95cMeNNRo+oX92RA3j5+wnKdshwohxypLoUAREYEQCEicjIlKEc0KAGzqvIf0Hibu/s9QAM1dibTD11vLly7EeJqpsumHQoQvjg44cGCKf/vSnk8k6Fju383lmjZIwk3WZ384YZ69opdsamBNnDHHbqcl0dmJSIMSKjRH8KOTNuMhJ34JOj9EUXi4srO4isNggM9AffWJzMkHl0UdThOKIQGUSwCplXUW0B3cDfCYMQfnyl7/MaDfm9mW4Gj0/mQyKnqW4VujNxX2JfqFEY9FGbkqj9+tWZtunsFay46cQvooWgSoiIHFSRRer1qpa9sqTGeJZw5i3mDzAWPaY0fBlvSzOpv3kydzz1113HdYGL0HpmEERDMRHIHEKjWIzL7O/A66IkgKxQQUWZsSbQreugusR1r9mxS5e/QMn4ais9iOWiMYKKA7jIsnn+MfkAC64lJ+UyYgoFaHaCPBXjwhhqAnjSXghwuQcmzZtQqKwPoZbMgWPCvcKFvdgJXWECl5cXm1wA+HWUXbjqramq74iIAIiUOkEJE4q/QrVfP1w9GMf8G6Snt/0ueKN5vLlyz/wgQ8wUBUDYgKbT26secLSZkxS/JWvfIVDt7iyWzSNd6imj5bdhi7U2un09gpHWDWgo62T5Q1IMdCrMJH1Hro2ZWdKYqIseMhDPC0BHRWKRWP1dczQz9omZmwJfS+sK8bIsbHmPGSROiECFUPAeVPp38UbCt6JMP0GvbbwlrBQkrvz8Ml8tdyOeK9BH1ReZ6BnfGdvxbRDFREBERCBWiMgcVJrV7SK2mPNes+NN/1//+//MZUW40/QD/SdYFgIRsPEtoXiMEeYs5jFGb/0pS+xvgqrqt1xxx233Xab38GMwZTUwZXrDBTekrod290JQx17PtKXjRw72bZ167a+tFmezDUkWNuA0R8MPrf7AUfP2AsqhGbPmLX2gvPnzmz0zNTJdHUrqhKUiSMwsJljL0YpRKCCCHBDYGT8fffdx18xd4PHHnuMtyT042LsO3/4rAtOLy8WiWfOQLysCJXSraCCmqCqiIAIiEDtEZA4qb1rWh0twtLlSY9NsHHjxn/8x3+kWwXWAFLhve9979q1a1nifcLtAJchLz7xyXziE59g1YIHHnjgU5/61P333487BRPEH+LiF02VqAldzI1EMcY6ooPlUeJ79ra99saJ3t7GaDwRivrqxZAvulHcyJXJvRRj9W9Yz4lNFA4Vcvm9p7MnXjpw+4YL4pGY6dnFiH8Wl3RNCPb/KjUKX5MDxaVkKwXrtwhUEwH+tN1yftdeey3zcyBLeF3CfYk24MXldoHbBJXi+n9WU8NUVxEQARGoWgISJ1V76aq84ti1CBJGoDLOhPlwsA+wAFjzhIGnzz77LMYBS6DQz/ttb3vbBDYUG5pysTNwntBPA+cMExnTy+vxxx/nk9Ipiwhs7GC1sK78li1b6HVmjG87QB6Jkg+Fu1OFU90YLjO8sBmyUhpCjjThLAKGYiaw1uc6K+rK4Pd8utDX15U60eHNbggzUbLH9MG2LSM2hWhGvNntXNdV+YvAhBNwX13uP06llCltJIq+2xPOXBmKgAiIwDAEJE6GgaNT55YA/bgYivrMM88gErAAeBO/a9cu5ulCltC3iv7fdPKeWHGCkUGT+KQ4Vn5k/mKG3dPdHPcI41+pAC9NESQuDi9NsVeQMXTzQCxZ14DxnJABa6bnvWimEPO8GJMPnzHfjTVvjqrIjwAShtt4rHsf4idbklXFltKYwbwm5ovhYJo9K+SgxwZYF6JPEaguAu62UF11Vm1FQAREoCYJSJzU5GWt3EY534WrH2NPUSDsIwNQI8iDU6dOYeC6PhVHjx4d6/Lwo2y2qwMv+3GhMBoeiUJHMgIpGidJe3s7O5ylPzp9PF555ZV//ud/DkznhR1fqK+P09uro6M37RGzuAxjoHTcDoGjCt6lmsgPM6g/z7KS2camusZ6lBtSxWkPJ7tGaAxWHbiY0YjVaXj3XMHNVdVEYAQC/CkQIyi8R0ig0yIgAiIgAhNNQOJkookqv9ERwAhAk9CTCm3Aqosc+n0qsAyMtZzPT6ylS56D2hyIENdzw1UcjwoxXWQkE9MZI04QLdYdgl/B2C4L5zb1pgqvvnqqo+NUxEwrzIKNZ5rNyoVjXXLkTOJJ3MM5wrTBLAOfNWsqF2bPbF6zclEyFgnlMzTTtGgEVVKsK1TZmHG1o6NjYi/ZJMJQUSJgCPBN5m/fsXA3AXERAREQARGYZAISJ5MMfLoXx7PfIWDnlltuYTJfvBNoA98g8AHhP3GT/PohZ7kTLNrPygX6pwhnn83VB91CHageSgkF01Bf19PTW0hnG8Kh1Qsbl8xczaogNjq2vJ+l2WGxkKrYzFAae0HomhaLRerropF8xsulzYCTsTQAXIwUQsstWLBgLOkUVwQqjgB/0a5O/k7FVVEVEgEREIGaJiBxUtOXt7Ibh93PaJOBssSvNZ2F/P1J3nF2CZ90/WLZtc2bNz///PNIKWO35DORcK4hFmmIhQuseWJr1k+bmIMx2faT3Lh+xVFZW1fcSgiVdD6XRZlYp8momuD6vyHennjiCdwmzATdL3cdiIAIiIAIiIAIiMBYCEicjIWW4k4EAdSIM/2xa9kmIsuJz8NJJupJDVkahVH7LIPAGJh4PJbJZplm1/Pscij9REmwGqOy7IMJpmLfVdKMeLej3q2oKjB9sJlk2NaHTwJdIwdpEXxwK+HjYuK1V1999V3veteFF144FQ1RmSIgAiIgAiIgAjVCQOKkRi5kFTXDKRNfolRmzX1xQm1vv/32bXY7efIkI1I8uxKC1SeD1716JhJ2l8K2omBGxXNslYkTJCPrRpQJA4eYxoBZ11Bx69evZ/bnwaEoVAREQAREQAREQARGQWBk+2MUmSiKCNQaAWOml7qes2jjypUrmeaYdeUZGY9FbpZkLLoUMOnZsOz9H2PZ2y5SZjhHJf/YabqC1S5eRDdfUaljmu85Kb/EdOWizxsbbpPPfOYzN9xww5o1a4BTHk/HIiACIiACIiACIjBqAvKcjBqVIk4oAd/0n9Bcz0lmGNzve9/78AywojzTi911110LFszPZNKpNCM0zEqFbiuVzWB6xse7rlClsIr/TRNsHflkOUVb+WIT2CfQnS22i8jQqK+vx23C+pXf+MY3Vq9ezaI0S5cudQ2l+aUMK77lqqAIiIAIiIAIiEAlEYh88pOfrKT6qC4iUCkEfPOaHVZpZOYuVrL/9a9/jT6ZPXvWzJkzcKC4uvox7SFHRVO+Uloy2nqcESElNeIkVjDcQ5agSZLJJD4TaCDYWMXyj/7oj6688sqWlhbX9qolMFpSiicCIiACIiACInCOCEicnCOwyra6CZSZ11jkTEXF3GJbt27dv38/nbgYfMJGOF4EIhsrvuhq6GfKVxWFUs3Nb7fSvQvh02w0E4WGMmGHJRdffvnlBx98kD5d11133Yc+9CEWhIGGi6lPERABERABERABERgfgTMLTo0vvVKJwDQhwBCLrq4uBsZ/9rOfPXr0yK23vvMjH/kIy0fiQIAAM1Zls8UZeKuxW1f/i2iUiVUkTmyYXbxBbrXKTCZz4sSJLVu24HRlMuh77733zjvvpIuXL+fUp6s/TB2JgAiIgAiIgAiMgYDEyRhgKeo0J4A+YUD8wYMHv/e9B3/wg+/Ttemmm266+uqr1669cP78eeFwJJfPMU7e+VKqmZXfm8s1wnlOCjhG6Nj2ox/96OGHH8ZhwvIv9913H/Mst7a2ckqapJqvuOouAiIgAiIgApVCQOKkUq6E6lEVBDDBcR3s3r1786ubd+5g29nb25tMJpqbW9AqDE1x01X5boSqaNQwlaS9eE16e3va29vZ7+joYOLgOXPmbNiwYf78+RdddBH7mqFrGIA6JQIiIAIiIAIiMCYCEidjwqXIImAI0Imrs7MTN8KLL76ID+HIkSMsgWLt+Frj4zeKPl2MsWHgDX6SCy644JprrqErF4F21E1xUEqtNV7tEQEREAEREAERmHQCEieTjlwF1goB18sLoXL06NF9+/YxIgWJgl+lVtpn2oE4wQvEYPeFCxcyUzDKhDE2aBI+fe+QEzD+YS01X20RAREQAREQARGYZAISJ5MMXMXVIAFUir/VXvNQHWx4SNwWbKCTLsEQ7YuACIiACIiACIjA2RCQODkbeko73Qk469y5DmDh79QGFzSJ3yirUMztwgXWRgPVChEQAREQAREQgUojIHFSaVdE9REBERABERABERABERCBaUpAi6ZN0wuvZo9IoMbcICO2VxFEQAREQAREQAREYMoJRKe8BqqACFQIgdN2o9uSkyUMsWBCKlbzqJDqqRoiIAIiIAIiIAIiUPMEJE5q/hKrgaMl8N3vfvef/umfWPQdcZJOp2fOnHnLLbd8+tOfHm16xRMBERABERABERABETg7AurWdXb8lLqGCDAX8PHjx2OxGDPn4jNBpbC8oDp31dAVVlNEQAREQAREQAQqnYA8J5V+hVS/ySGACGERj7Vr17Kgh1tRkRXfESqTU7pKEQEREAEREAEREAERgIA8J/oaiIAhwFATlMn73//+G264gX2WVuTTbQIkAiIgAiIgAiIgAiIwOQTkOZkcziqlCghcccUVl1xyCaPiH3rooRpb6L0K6KuKIiACIiACIiACIiDPib4DIuATiEajDDLp7u7u6enJZrN+uHZEQAREQAREQAREQAQmh4C6dU0OZ5VSBQToxEUtkSX5fL4KqqsqioAIiIAIiIAIiEDNEZA4qblLqgaJgAiIgAiIgAiIgAiIQHUSkDipzuumWouACIiACIiACIiACIhAzRGQOKm5S6oGiYAIiIAIiIAIiIAIiEB1EpA4qc7rplqLgAiIgAiIgAiIgAiIQM0R0FTCNXdJR9GgfMEr2Jna7AjwUSSo2ig00zTVbjXf2GI79UsEREAEREAEREAEqpaAPCdVe+nGVfFCwevozG7ZdvjJ37yRzhZQKbW8FbxUn7dly5u/eWZ7LufRdm0iIAIiIAIiIAIiIAKVTECek0q+OhNYN2eYh/h14nT6Z4/veua5LZddtioSjoTCLI4+gQVVTFa2xR2d3qM/eX3n7n2XX746HPJorDdsY5lEmKmE2VJ2Y6di2qOKiIAIiIAIiIAIiEDtE5DnpPavsW2hMckx1/nV2FyXqGtq767PZL0a95yEvJ5eL51vCidmZXMea5c4iTbMJUeSHD169OTJkwcOHNi1axc7hpt8LsMg0ykREAEREAEREAERmDgC8pxMHMtKz8nqk5BXXx9KJqLpdLzS63t29SuETD+uo6faTqX6Cg2xTMSLh7yRHCdeY2PjZZdd9vWvf72vry+RSMyePRtl4hZnPLvqKLUIiIAIiIAIiIAIiMDIBCRORmZUMzGc3yAa9aKxUHd3fsvrpy69aEZLo/kODNvXqYoBbN2+rSvVvui8eUaX2HY699FQTYrFYrNmzbrqqqucJgmH5VocCpXCRUAEREAEREAERGDiCcj2mnimlZujVSeMu2ie0TBrTsuTT23t6OzJWw9D5dZ5XDUzDbUzkr2xbUs82n3pxUtQGaMcWoMgwWeSTCb5RKuMq3wlEgEREAEREAEREAERGA8BiZPxUKvSNM46Z+jFshVzr71+1VPP/qa9s8OMp6gxvwktKjCcptDXmz12+ODC2eEr1i+MRbwIA+LHfuXUp2vszJRCBERABERABERABMZJQOJknOCqMRmmOT8Rz1s8P3n5pcnte3afaE/1Zr3cKEaKV1N7bTt7+zJP/2ZPPpdYMLtxRoMXtV6jamqF6ioCIiACIiACIiAC04+AxMn0uubY7VzypmRo4ezEkiWLv//T1zZtOZjOm2msasN6Nw0peH0pb9/Bvm98d+PFl1x7+aVvjfX3mdRGS6fXF1etFQEREAEREAERmB4EJE6mx3V2rbRWOZecPk4LZjfd84Gbtu05/vwrbx45mWI5jxrwnxhl4nm05c2jbb/69Rv7DnWuXr30vCXzcBbRagbXTKeLrbaKgAiIgAiIgAiIQPURkDipvms2/hrjNyn17JrZ0nDXe665cPXCA4dOvbT5wIn2dDZfQJ+4xUCq14rPFrzDJ7o3vrT3iac3X3XFyqXnNTTWmc5stulOvIyfn1KKgAiIgAiIgAiIgAicUwISJ+cUb4Vmbjp3hb36hPexD9/WXJd74KHHnn3lSGcqn2McuXOhMNVVaeVBdkapVUYZbRgoA9WDC7Ezb53J3o8WrJoL7M3mH31i19d/8Go4lv3oH163cvmsaMRjbXizPLxn1j6xP8NUQadEQAREQAREQAREQASmjIDWOZky9FNVsPUhmGHxjMRYNMu7/uq1nd09X7z/vz3vfW9dP392a4LvBKY8zoaiGhjlFLxT0R6m0jKaxGoXJ6u++Z1nH/3ljkWLWj/2u7fPnZWIR53PxFXONX0qKqoyRUAEREAEREAEREAERkEgFHz3PIr4ilIjBLDp89ZPcuRUz/Ovv/nzp7Z3dnQvXTR7w/9adeUlSxL4Gex66rQWi34SjHrqEyyl7HAo6EaWhIy3J53xDhzu/O4PXty26+DyZfPefs3qt73lvMaYv/Siy51cXYOGyk/hIiACIiACIiACIiACU0lAnpOppD+FZaMEzBjxkDdrZv1bLl4aq2t6+plXXnj1cGdXqq+754Jl8+fOa4zFIsTBxxKUDZNW5+H1CWf5Yew72849h3fvPblzT+fTm05ccdnCW25Ys27twjqUiT9Jl1MlU9OOSQOmgkRABERABERABESg6gnIc1L1l/BsGuDs+1Te6+En5X31m89u3PhGS11owzUXXXLZotbW+vpErCkZba2P9evb5Wz9cyZZilKif8P6lVbwuvsyp7tSXX3ZTD7z45899/wLe8Lh5ssvu/r2m5csWZisjxWXXOyXqn+GOhIBERABERABERABEag0AhInlXZFJrs+KAE3SVem4LV15V59/eTPHt/+yC+ej0TDF6xeedm6xVevm33DVYsirK9e6hvlxngYP0TJNeGGzCNg2LHjVcbQCjoWDlyFnVqVSRRfZriyNr1y8EePb3/q5cOHjh1snRG//ca33Pmu/zWnMdyYDDNoJmYnevCTjKE2iioCIiACIiACIiACIjB1BCROpo795Jfs7P0BNrtTAnSRyuS9to7Mmyd6Dx3r6OrzXtlydNf2HYXOXUtn9bJOYywcjUSjXjgajdW1zpw9Z96C2bPntDY3rrtoST2dqErDVMbZDYwBMCErk2wlGee+fefhbTv2HTh0oK3tdDqVyqb6crl0IZ9L9aWQHu29db2RRfOWrr/skpmzZ8cWzWs+b25zU8yLhj26KtomonlAPKC1k49dJYqACIiACIiACIiACIyOgMTJ6DjVeiynT3ChZPNeKuf1Zc0i67v2nTy0/83etsOJUDfujZ6ezOm27hMdPV6kLpXxwon6aLQ+05c7b+Hcujpv/tyWNasXrlnRGg+Hzgz2GImbk0vEwh+S8bxXth9/YfPBvs5u6nH0ZMfp7q5Urrenu31Gc+PMpmRdIhoP52c0J6OhcCFan2icO3fx0pXLW+rrw4mIl4x68VBxhExJkZB9abdfTYYK7xdJByIgAiIgAiIgAiIgApNMQOJkkoFXSnEDzXNC+HGLMDKRF6sZsihjnuM8Fn8h74XaO3oPH28/fKI9G44ePdHR1pnq6s4eP9pRyES7ulL1dZHzV7S8Zd2MxfNnLZjb2tKYwHExqDLwEdi8TaGpdGb7jgMnu1K/eenYc6+enNcSi2Ry0bpw86zGllkNIS+zaN6shXMZAlOHLpk/t5kRMMYrwk/E9OAKhU1fMjd2n8yHL7TUX2ykWH4ttSMCIiACIiACIiACIjBZBCROJov0VJdTpkbKDstqx1k29+mseDMuJW8UC6PncXGk817O/uTpDZb1du7s3fjc1o3P/6azs+36ay696foL169d0NpYN+j4E5ct+ZOUdem7+7KHjxz7/Bcf3H+4J9608PLL1//O+y5PMnwl7BVYpYT+YiEvHvEStr8Wa7NEcY9YD4mtYz8pQlUHHcHiYpY+g80qhem3CIiACIiACIiACIhABRCQOKmAi1CRVfAlBLUzRr+x+82n6foVOLQnvFSq0N2TOXai+5mXjj721KuZnqO3X7fij3/vXf74E6cZTCamscYPg6MDkfP6ns6fP7nlx489Xt/YdO/dN685/7ymutisJtZONENQKJh45rdzjNhPDknLp9v8nVKAfouACIiACIiACIiACFQrAYmTar1yU1Jvpy7ojuU2ozSYngvFYruB9abyb55M7Tx06ldPPH90/57L1869+cZrVy6b11CfJCIqwk/uOo899fyux57ccuBI1/nnL1538aKLzl84u7keDwkDSCJ2dUVTihUfToFQkNvcofsshem3CIiACIiACIiACIhA1ROQOKn6SzjJDbCuj35lIhLc6BE6evWxXkrOe+XVPZue23pw78FF8xrves87Vi1fGIkUfR0kx/fS0Zt+fdeJhx55MpUurFmz4q2Xr1m6uKUuFmJEOx238LcM2h8sWKqUSZCG9kVABERABERABESgNghohfjauI6T14pBVQGBTlGEGBwS8d52yfJFc+Y8+/zO//nJT5cu3ZlIJhcvnMlYETOK3fO6evre2H3swUdeOX287bab33bdNZc2N5hUnMQ3YtwjhaKSmbxWqSQREAEREAEREAEREIEKICBxUgEXofqr4BSLGbluvSihqLd0UWNj4wX5bOahHz/e3tl5z/tvbW2gr5bZ9uw5+oNHnvmfJzb/yz/88VsuXFKfKHpLyMREGPsyjjZXfYiACIiACIiACIiACFQ9Ab8bf9W3RA2oEAJoDGbTwhMypzl+y83rLrniio2vHP7Pbz2C8HC9v/bt27Pj9Vf/6f/+8drl8+pZNtGOK+GLWPScOKFTIY1RNURABERABERABERABCaRgDwnkwh7mhRlh8gbpRENz55Rd+OGizs6Tr30+pt7DqbmzIs9+5vNz23atWr5eZdfvABfCquUoGSkR6bJV0PNFAEREAEREAEREIHhCchzMjwfnR0zAZSGUSZ2FEo87K1dOefii1YUojMefXL3ia7MU5v2H28LveP6t81sisSiIadMBhMnrgvYmEtXAhEQAREQAREQAREQgeolIM9J9V67Squ5kxPGD+LEBp+Mkq+PeutWr9h7KPS1H766bPWsAyci8xcsu+qqS4wssQPf3Sj5wRpDhoPJlsGiKkwEREAEREAEREAERKAGCMhzUgMXsVKbUDDiBPm7YkXrpW9ZdPB0/Ev/uWvvYa91ZkuUUNv7S+qjUi+e6iUCIiACIiACIiACU0BA4mQKoNdokXg5+js67BEfsYjHOozz5y3Yf3D/9dcs3vD21bGoZ2YWHg4EJ4c9P1xanRMBERABERABERABEahKAhInVXnZqqvSrKjYWJdYtWRub8+JpYuiy5Y0MQ6e3lzmp7paotqKgAiIgAiIgAiIgAicSwISJ+eSrvIuravYUBddvbQllm9vjKUa64oLwEuZ6AsiAiIgAiIgAiIgAiIQJCBxEqSh/YkngAJh5ElTMrz6vHh9qC1aSDHehBApk4lnrRxFQAREQAREQAREoMoJSJxU+QWs7Oo7BcInc3YtmuVFc6fD+ZSvTAoFzRdc2ddPtRMBERABERABERCBySUQkoE4ucCnY2ksDN+XLZxoz778/PPrL1y+7LwF05GC2iwCIiACIiACIiACIjASAYmTkQjp/FkTwD+SL3jZQqGvu68uEYvHtbrOWTNVBiIgAiIgAiIgAiJQiwQkTmrxqlZWm5xzzs7MxaqLGmtSWVdHtREBERABERABERCBCiKgd9gVdDFqtSpOkDDARMqkVi+x2iUCIiACIiACIiACE0JAA+InBKMyGYZAcdQ7ygR9woFGwQ8DS6dEQAREQAREQAREYDoTkOdkOl/9yWk7HbmKfbnkOZkc4ipFBERABERABERABKqUgDwnVXrhqqjaGmVSRRdLVRUBERABERABERCBqSQgcTKV9FW2CIiAazGB+AAAQABJREFUCIiACIiACIiACIiAT0DixEehHREQAREQAREQAREQAREQgakkIHEylfRVtgiIgAiIgAiIgAiIgAiIgE9A4sRHoR0REAEREAEREAEREAEREIGpJCBxMpX0VbYIiIAIiIAIiIAIiIAIiIBPQOLER6EdERABERABERABERABERCBqSQgcTKV9FW2CIiACIiACIiACIiACIiAT0DixEehHREQAREQAREQAREQAREQgakkIHEylfRVtgiIgAiIgAiIgAiIgAiIgE9A4sRHoR0REAEREAEREAEREAEREIGpJCBxMpX0VbYIiIAIiIAIiIAIiIAIiIBPQOLER6EdERABERABERABERABERCBqSQgcTKV9FW2CIiACIiACIiACIiACIiATyDq72ln2hLIZDLt7e0HDx7s7Ozs6elJpVKFQqGWaITD4UgkEo/H6+vrZ86cOW/evBkzZtRSA9UWERABERABERABEagNAhIntXEdR9sKVEcoFPJjI0Xa2tqOHDmyd+/ejRs3Hj169PTp093d3fl83o9TAzvRaDSRSCSTSTTJihUrLrroovPPP7+pqYnDuro6GhhkUgPtVRNEQAREQAREQAREoEoJhGrsHXmVXobJr7ZTKZs2bfrWt7718MMP4y3Bal9pNxwLk1+fc1oijUVu7du378CBA9u3b9+9ezda5Xfsdumll6JMyjTbOa2MMhcBERABERABERABERiKgMTJUGRqPBwz/VOf+hSfq1atwkA/77zz6O9Eryc2uj/VWOPRHmwIsL6+PvxCOIheeOGFJ554IhaLvec97/nDP/xDmiznSY1ddDVHBERABERABESgGglInFTjVTurOjO2ZPPmzc8++ywG+lve8parr776wgsvbG1tpe+Ty9d5Es6qjMpI7OsNJ078SqFSDh069NJLL7344otolXXr1l1//fWrV69ubGz042hHBERABERABERABERg8glInEw+86ksMZ1JP/roow8//CPGmbz73e++6cYbFy5ciAOBXk9suVwOO576uU9T0TPjU/xq2yAbyw8yEe1QljMJg+embt+vFRVjWDwVcYPj+aSxr7/++i9+8YtnnnmGUSgf/OAH0SfOa0RkX9hMXd1VsgiIgAiIgAiIgAhMOwIaED9dLjlqAvlx4OCBn//i54ePHHnve+/87bt/u6G+LpfPZdJpLPVBQZRm7fLHxzuxwmch5LkZvSpa3/piCbHhJIdVYaY5jI+nP9usWbMYFv+FL3yB7m0tLS2LFy/mlEslfTLoV0KBIiACIiACIiACInDuCEicnDu2lZVzwSv09vV8/BN/mU3n7vrfd73nve/FOu/u6cVfgs9jEAfJMNU3lj6n+e8b/8PErpRT1DVYXcaf4CdZsGDB7bffjiPle9/7HlMqf/jDH2asPDWWMqmUy6Z6iIAIiIAIiIAITCcCWoRxulztQwcPfelLXzx08M0NN7JtaG5uSmdYzyTnFXUGv/r92B5d/qzDiJfij/tlj9gNY8S7rfI5Us+ySmazWeQKMwG8853vXLRo0WOPPfZf//VfhAyMWZZQhyIgAiIgAiIgAiIgAueCgDwn54JqxeWJwX3s2JHvfu97t97yzhuufwfuArwEOUxz6/rAA4LI8Cvtemu5T3wqtvvWmbNEK+Qx341vIWS1CesbVqk1b1pg12ekN9d73/ve73znO7/+9a/vuusupiwj3AeiHREQAREQAREQAREQgckhIAtscjhPcSnHTxzftm3b4cOH77jjjlXnn8+4C6bVtb2yUCf2x7lNCgzMsD/GM8J3I2zcKYSUPgmxxrxZcJ3ZvdxWLcqEegY3d0mQbfhP2DZs2HDllVeyJOUrr7yStoNwhhqHM8XXUsWLgAiIgAiIgAiIQO0SkOekdq+tHRGCOU4LNz678YHvPrh+3fpZs+ZwyJxdZphJAc9HGA8I2sMNeGfHx4EKQZ2wemHBy1vvCSPgPURJIh4Nh0MY7igcLHs8MKdOncK49xOyQ7h/6CrgH1bOTlnFGBnPYi/MJszg+H/4h39wzhM+XYWdDHPuFFpXlrZyGqWaiIAIiIAIiIAIiEBVE5A4qerLN1zlgwrh8JHDJ0+d+pOPfmzmjFbGsVvzOszkurFYXTgSRnyUxIQRKU6iFLs1FU+YX5FwKBryUpn09te2Pvnkr1584QWWTCEr9EmwrOC+yS0gVIar7qSfKxMYzKeMysK5hNDau3cvh0RwW3Nz880338xInQsuuIDmEDjplVWBIiACIiACIiACIjAtCEic1OxlDtrQqVS6LlF3zTXXxBNxfB6Mbre9s5IdHX2nOnq7+rKFUAwQSBDTy8tMumuOrGnuRcMhBpXEYpGuztN7d+/csvmFA3t3pHq70Tk333zTkiXnBQsyyezmYy0764dX2o6rNu4gKoafxFWbQyb1YsHKxx9/fNOmTWvWrLnttttWrlyp5Ror7fKpPiIgAiIgAiIgArVBQOKkNq7jcK3o7e3t6+1j4mDWW8xkUvTIwvJGnPT2ZfcdPHXkZHdnKpQLJ8kilC+UvCjGVrfjS7xYNJ+IhY4cPrhjx7Z9yJLOE6uXz1uycP6a1avWrD5/3rz5xAwWX3YYPFXJ+67avpRix+3jSGEiry1btuzYsWPjxo3t7e0MTbn88svpA1bJzVHdREAEREAEREAERKAaCUicVONVG1udsac7OzsxtaMRI0hYBz4ai+EgOfDm6T37T3X2hXOxukwxSzosMRqFwSbs5CJh+n0Vcrn06RPH/+en/3PgwJ6li2bfece73n3bhvpkIhalR1gom0XsFNeVd3lQUD99cjZ9oPqpnrG1ehyxjRwpVZ4dq80iDDu54YYb3v72t+/fvx//yQ9/+MPXXnuNDmCsjjJ//vxxlKIkIiACIiACIiACIiACQxGQOBmKTNWHoxCwsGkGHZOYm4sF4hEkuUI+HzKLu/ekUq9t39uTbs3F6r1I0gtFSg22ZjkdubxCNOw1JvJ9nae/9+37t2x5+cP3vP+eD75/1crzwnaCK4aapG0nqH5SpJSL/7u/W8UPHtXO2eiaURXQPxIN8dtiJFcuRxuhRyyWa2QJ+SVLliBU/vZv//Zzn/vcgQMHPvnJT/bPQEciIAIiIAIiIAIiIAJnRUBTCZ8VvkpO7JQJNezp6cG9UVdfj0/EzrBlVIoZdhKJZULRnBfPh2OhSLz0E2NOLmLgOaAn2JEjRx77n59te/2lv/+/f/F/PnT3ssVzvVw6m0nnshk8MG7CruEhIDCG+hk+YUWdpXMXQoUJlJcvX44mYVGUF1988Stf+UpHR0dF1VOVEQEREAEREAEREIGqJiDPSVVfvlFVHqsaFYFhbca6m+mBmTg4FI1Fl684r2tXX0dPlmXivZA/FzC6BZeLF2tItrWd3PrG1j17dt77gfe94/qrly5ewPqLLN2Yy7GwOkXb/yX/zNBVMdEG3RBLQ56zkoZUw0QYNM8JCRzosXEyjI5ezOLFnF133nknvhSWk2dk/PXXX8+ilhNSrjIRAREQAREQAREQgWlOQOKk9r8Afm+lHKa+WdSdlUsKkUh46Xlz21Knj5/OZnJm1RNnkZvVT0KFaNRraY48/dS2vbu2rlg6j95cixbMo2MY/gPMdNwvJbeM6QZV2h+cpM12cIlBaKnYwdMOnmzwuOc81OkTGoxDad26dXT3YgjKgw8+uGzZMomTc05fBYiACIiACIiACEwPAhIntX+djYCwAoWmMt4EaZHzsswPXJfwLlk7s7OHQSlmyInfwy8S8ZIJVEz6e994Pt977H/fc9fa1Stxv9CxiWEYJrfAZjP2tUrghN01npGBbohSrOE9J8QaOmkpiyF+96viEHHGFOxazScSBVmSSCTQJPfeey/LNe7bt2/9+vX+co1jylaRRUAEREAEREAEREAEggQkToI0anafblqRsJEfLAgfDTHY3fOyOS+XiYeiM+JhL47348wP4iQayT33/NaTB7dftHLxjde9NZ/LZLOMfjdrgAT9JOzjgRmBmllZfoDKMB4TE+hk0zA5DNfxa+hkNOds9IlJa2oXqHbY7tvBOnBgCMrMmTNvueWWb37zmz/72c9YXf6mm24aujo6IwIiIAIiIAIiIAIiMCoCEiejwlT9kbCtsa+dxY3lbnwAXqEPzRKxcgMNYFQH/5lx2Cwan/3hg/+V6zu1dtWVjXWxVF8fQ02AwCh5E6n/6vH9jPj+pJx1H1QKQb8LsoU5wpxTon86c1RKO/DMyCFOmZyNPjE0gpudYjifx3FkIKFPGMMzY8aMW2+99cknn3zjjTckToK0tC8CIiACIiACIiAC4yMgcTI+blWXCuPaDCexNn/J7DZB1hliVMcZ3wnelUIu//JLz7HY4NuuuoJBKsZnYmKEIuEoyoSOYUiKknwARSnDAVSMPCgQ+8xmxYnpBsbGudLOmQj+nsm0cKazmR8+mh3TKragKnIho/4saxLVhkMsFqctdO1yLaJzF86T55577sSJE6POWBFFQAREQAREQAREQASGJCBxMiSamjlhfB3GUDf2NnrE/jKioBBi1mCjRELG8C7w33hX8KFEwrl0prOz+5L1l1x00UUMMzHaJBxlrqpUNtfV3pVKudm6RkUohIvGSiAbm1LIhv+sCMkOlr7ZhsrIVGjIk0MlMuEkypt2TtiGwqK6ybpkS0uLmUHZek6Yueviiy+eM2eOm2iYwwkrTxmJgAiIgAiIgAiIwLQkIHEyHS57KMwcwvRHMmNOzFqMxmsRjhTC8bwRJcahYoajWPliRUuhN5PPFBKxRD3j5nv7UnZ6rmg6Hzl0rO3Flzan0xj/piPY8OzcaeOvMYUgUVA+eSz4WDQUD7MTYo35XCbNWo5D5WMqPC5xgjIZV7qhKmLlTshj4uArrrgiwlxmnueWaGSHofDssyAMo1DK0gMzGo3SYgNcmwiIgAiIgAiIgAiIwEgEJE5GIlQT5zGNjXWMU6QQYmESbHdkSSYU3vTawaOne9M5M7cwq58gRRLRcAzHSU/n6Q78APRiIj7elTAnDr7ZseNAe3dhRrShCWvbKA6z4VUxWsUzhwET3Agec5jLpfGToEgSSdZWiXS0tx/Yt/ONrS9s3fwMI/Iz6T6WdLT5DPwgW9MRbXzb2YoT08JA4bYbG4Nx0Cf2jHEAMeyEScx27NiBAvnVr37FZ1lV586de8cdd9D1ixHzwbM4i1zm1m9kfDJlCXUoAiIgAiIgAiIgAtOTQLk5NT0p1HarfRPb9NgqeKx2wpB2OmsdOtZ5+ES6rSecD8ezXtTLerFwNI5bI5Tp7ujM5BLW0UIi471AzJzuTB07jdekIRRuIYeSFDESwu775VicjLg3xn2BUSoMus8WMm3HTz/z7DPHjh5J9Zyuj/TggqhPxubNndPa0jw0f8TJOFXGOJOVqtJPmZQCg79RFGzOf0LkYJ8uOn319PTs37+fgfI//OEPN27cyND5a6655vLLL0eukImfub8TzFn7IiACIiACIiACIjBtCUicTItL31832P5VOW//geM9vZypi0QSyBbjpkBHRE2XrzyHLH1ilQFWPl2yGJkSwf0RTeRSTFnFZMTmm2NcJsY94nQI+74iQFRgePNRiCeTXe3H9+95Y++OLZs3v3rh6uWXrV27cF7T5etX1Sfis2fPam4eXJzYOpOhn+ekXqmhZIM/QoYIiBMOkSKGQsDNQiBroRw8eHDbtm18Hjt2bM+ePXzu3LkTicKiKEElE0w4qS1UYSIgAiIgAiIgAiJQeQQkTirvmpyDGvkGvtthQmDm2+o43ZFLtzAqgtEnHOYLhQgOEtOR6owkYI/l481xwZvZ2rxgXr5v/ym6Y7HIPNW0uZkuSXbHxGKfKYrp8kWXp3A4FokUenra33jjtc2bnvR6jr5t/eL/86H3XXrJuki4EI/hfHGzftnUg7W6pE8GO3fuwwaVDb44oXw/QjDQhTc1NbW2tjKdANKlra1t8+bNDzzwwFe/+tW9e/cyx9eKFStYZh5tc+4boRJEQAREQAREQAREoJoISJxU09UaX1192x/dYUabkAsv+wvenNkzT+5PF7IZRAQyAC+AERVm1i70iJUjaAfjHDEzB2dT+RlN8RVLWrLp7JvHOlnxw0oRIpqk6Bcjb1z9Cjl8CvFIIh5NkvHD3//BSy89e92lyz7/b1+MJWKN9YwOL/Sm0qmeLM4GUze/fi556dPUwZwb4nQp2jn67QuPgfm7U74gcTv+YTA+8oOhJvPmzWPYCT6Tr33ta//93//92muvfeYzn1mzZo0WlQ+y0r4IiIAIiIAIiIAIQEDiZFp8DXwb30gIJEE+z9julSvmd/a2vXmyq6OjO4cKyedj4XAmGsaTYgapZzNGGOTy7MSMUDDTB89ujNavmXPx6hlk4jY39MQJCNOXy+oZzHcGwTMZ8Ve/+sDR3c/99jvfes8H3jOjtS6VSvf19dqeUHkEEoNSbDalvAa5FH7FBzl3ToMGFRtjLZEmMmKeT/xIDQ0N73vf+9Akzz777Mc//vHPf/7zF1xwAdKFgoYRQmMtUfFFQAREQAREQAREoKoJSJxU9eUbY+VD9NGyLg4zN3ChuSl+warm+QsTPdlc1k4MHA15TO+LVmg7lahL4l3J40aJGNsZkZC1h+FovVEeHnN7lXwaZlYuE6OoMViokZ5ix48df/nZJzc++cit77jh/7v9xgtWLc7ifMllsdTRL9SbFCaZ2Zy0sbuBD0KHUS2BiBW9i/ZgFRRazTZ79mzGxIPz0Ucfvf/++z/4wQ+6w4pugConAiIgAiIgAiIgApNIQOJkEmFXQFF2JmEMZuO9YMquubOTc0J19OKikxYbg+JjUVwahcN10UQia8abmFXhI4UCU3yxEWK7cNmeYVZUGF3BUHmT2GxGTUTirGLiHdiz++Hvf2/BzIZ3v/Mdl1y8ht5kPakUWRgRYzUHOVtHCwGDixObYY18MKkXG6KN0f/r1q27++67v/Od79DdiymGly1bViONVDNEQAREQAREQARE4KwJaEjuWSOslgyMc8OKA8/4Q1jvPZtOFTL5SN5jrq5E3otmvFiuEM15Eboh5VNeoZeRJnTTsiLCzNxlfR24U4zHgxm9+AmzmLwXtZ/s8ENIOBaNd3Z0vbF129ZXXvmjP/jI6tWr+JKlU2nnBmEsvt0Ykm++e1aXcGaon2qBO0I9abI/tRea5GMf+xhzdj3xxBOPPfbYCCl1WgREQAREQAREQASmEwF5TqbT1TZtNXLA2MqhMOstmmMWWcRBUijgMmHsO+qCwe7ZbFeo0G2HwpsUIY++XeYX//GThGNJJ2qd3qBbF3rF3yKR0BO/fOKRH/101arzL730svr6Oka/03GMEhmIUopGBm5isGHcJkgpyvSTlJJW22+jCFksJhyy7hPjdaqrq/ud3/mdf/u3f2MhlGprjeorAiIgAiIgAiIgAueQgMTJOYRbUVkbo9hsxtanU5cxl1luEReIVQAE580sWznWPSdCOBo283TxY8SLWU3RTDTMqVC4L1VoO9VOqElnRYnVD+YDycN6i8R6ecvuaLzhT/7ko60zZuRzOeYG4wzRMdBNprZvl5kVzAwFN/OGDbGZ0oc4VbnBvpoqVd0qQdOULOj5AUcmm33L5ZcvXbbs9TfeeOTRR5nLy1/5pOqlWOVeGdVMBERABERABESgCghInFTBRTrrKiIvnKGPmCg6OTCZQxH6doVSGTMvl1nEPc9swgSEmZYry/CTSB3rMJIMWWLmHw7FMrlQe2fP/jdPdvRmzah2Y32HSELeJlNrhCfi4Z7ezl37j7XMmHXFlVciddLpDDERJ0a48GM2E5vU5hdJXY1MQNlmSrCllIVX9KFtlBFeZ9oDVRqSjxSYdyCf4186nW5pbVl38cU7d+380SM/2rBhgy9OKrptqpwIiIAIiIAIiIAInGMCEifnGHAFZG8cFcbIN3MIW0cJQ+HZIplCpLMj1daVTae9SBRxYnp3RWORXNg72ZHNFBryoZjp6YUvALdJNNrWldp1sG37nqOFaF1RWTDOxCoXz/TSymODNyTDe/fsOHG6fd6qhQ2NzB1sJqqyugVZEjnd1pfK4yvhh2UfjThx3cOAZFwoZzbOmE5myKKAjX/mdIXv0SjXf81qQrOADGKlIR5piEdZeJLOXflMmqUY11988ebNrzz11NOEVHiLVD0REAEREAEREAERmBwCEieTw3lqSzHKxPoq7GRdyI1whK5abV25p184eqKtx6gWhICxocOxWDgaC2fSPT090XwhgtWMkGCNxkI0fOBU547D3alIazzRRA8uIy5YU74oMcg/h8JJNhaOnDyJZwBlQmcw+i/hY4lGY3QU6+jqe/bFnce7wukCI/CZAQwm1s3gtJNZwtE5G1ygUS9Wn7jAqQU4ttKtODH6yspCQzceCa1a1Lh+1cwZjZFc3ozq4dTyFctXr179yyeeGFvuii0CIiACIiACIiACtUtA4qR2r22/lmHimzXdeXGPycyY9XSusH3nvs4eRpk0eCzkTlAecRKhqxcdu9I9mUKyGXeJHXeCmwVxYRaKz5gB8/F8KEmPLyMtGFfvnCZ5BlTkcaOEw/n2U6eTieismTOwv43bxKiiyOn2nude3H6qO5IJNeXpMMZK9DahycPU0/hfsOJLG13FkDZ0FKs+ZVKqshMn+E7oFsfcZ9l9h0/PaozElsxorEum+5hzIMeyjC0tLUVFVmq5fouACIiACIiACIjAdCYgcTI9rr7xjbAhFdiwlr10JnOqrT2Tb43EEuFEzLhUmEc4hJMjbMbCExEdgnDAwWF+GM7tzWlpWTgnv+/NDmYgZul4m5FREEZmmEHzeVLl6wunTh5tqIvOnTPL6g6m8grRXawnGzrWEYskWsLhes/jW4djhPxNAcbBYDYjR+xmfiFOyNGNUHGh1fXpNBdcLEoamOvr6Th8ore1ta6+oRFRR98ulj2J4myyLqTqap1qKwIiIAIiIAIiIALniIDEyTkCW5HZmoEdmP4IEaM3mhrqT/eiM7L087KeC7NsvJdj4RMzaJtoCIsoK6KYwd2ZfCY3ozG5clErEqK9K5orMJLCqAqzOiP6wwx1D9cnQnNmMnilJ1kXaqzDPWIgcJassoVwXz6ZCCVwuRjDnVNGg/DLlGk301HM38xAF2u24z3xA6tox8oq0zAkFg2kxxwEsoVIJke3LuMWYqXLYrsdpipqm6oqAiIgAiIgAiIgAueMgMTJOUNbURkbIWGcFQWjOHKIk1g0uuy8+d3pDubeyqRTZkQ8giQcZTwKPax45c+YbjN2wvT08vLZHDNNJWKhBXPrWlrqjhxPM4TbDa7P0R3LCg3yrU+EF82NNybxidDLy/Qic74aCsdH0NxU15tOZ01C0yXMShoilEx0Y8cHkZkxJ2xVKk6ci6rYfDOcJxePhWe0NtbXJ3NZy6tfY4MN174IiIAIiIAIiIAITF8CEifT5NpjC6MHsPj5ZE5bFi3xli9ujYWTO/afPNbW40Vi2TxOkkIshhyIZpOJcFd3KJsxY0rQGSyB4mXoFJaIFOqbYrObE1Bz1jUnjI/DGuOxsBePeYkYKy5mzYxcJobxxoRD0RlNySvXL37xtX0nO7pSeeNXMOrHDGMpdjUzIS5H9sxW9KO4zl5VJFFMvY0UdC0zCgvfTyzqzZ/TsHRh/azmSD5rFjzRJgIiIAIiIAIiIAIiMJCAxMlAJrUXYgWEbZbrZGV2EQf5/JyZ8cbGuX2oCS/MIhwMfI9GCfYOH07WNzP2HbcIQiONeZ0vZIyOyGeZBtd05HJSwk0AbLqJGWVRYDh9vB4tY8Za2OJM/61crhCKJiLRBTNDV126oJdOY1ju9Nqyn65vmI1rzHljywc2ouGQKeYVCB/lLkWMextToQMLssmZfqDYUgDOrgu3MMAkZzGaap1F5cbdKiUUAREQAREQAREQgcomIHFS2ddnwmqHecxP0d2B/KCjEQskMvo9kgjVMSA+wht9OnEhThAkhUxPOB5JGZeJmWuKOYJDBTPLFzMSG38IfhKrLGzlGO9unR8Y4jncJYyoYNYvc8YIE0rEP8JoeiYFS4TDc5oT9Gkimt+soIWOQR88tFnYiGei++lGt1OW3egSFWONrtDSwBHUme2B5kp0rIPFFQrJUD6SzxSgbHAZfmg6U4hNMrrSgjlqXwREQAREQAREQARqkIDESQ1e1EGbZEaYm81IDLflc6zdzhah25Xtu8Ug91DUDFDPJ0N9oUKnZ7wlyBOGoLCuiZnel4UUzWTDZuF4lx0rL5o8XdZEKuV9ph+WOWWW9UDqhKMhOo0xKbHbMM+NHCklMdmc2TdR+h8VU03SL9eioQrza43OsErMVtWIMtKZk0YIljbiGB3CxAN0jXMd4Gys0vmAVvODtCMCIiACIiACIiAC05JAyVCclo2fdo02JjR2MUKDKbOYbgs3iJEmxvnB63yjFRgEH8mb+bt6vGwX3hWHKMskU5FI2MiKWJYIJaFTPFtSEWiLaDZve4e5gsx51A8SBDeBmVQXd03IfuWYKNga8dZuJ5Yz6038wEZ17ViWQNCk7RpMQxSG+EC/8QkGvECuDxvwnKPIJqKxRWXFL5dP2MgSx3OYvIcoUsEiIAIiIAIiIAIiMD0ISJxMj+tsWulsYmMqmxXK89lIPGZ+wlGWYGQuYKMiGAsfKbCqexglYgQMU3VFYrF4LpcxrpNItKM7u3P/if0n0nTvClvhgIWeymXpD0bsZDy8ZG59R1ehpTHuPAqY5sY6Z+KvMIPgETvkTKZEN84EV6WSGW9n3+13NYzLoV/AJB4MIyCQJUbVoe2MSDEfpVrSokHUlHWtGOpT2JxJJKeiREAEREAEREAERGD8BCROxs+uqlKa9/rGf2EMaXposYJJxIvWtXX1dXSc7uvpw9zO4tYIhxAriIiTJ072piNm3mEjL0ynpHAk2d6V3vdm265D7T2FZtaaNxkVwnhAsqztbrp3MQeY191TYJZhsxJ9yWI3/cEYsxKJMV6eHmKZXBh/DKNZrOfEzB5m/S7GvKeo/huZDAjrH2Oko5JqGCle2XlXp7LAwKGliO8JNxCrwMA1n6GPXKm2xU5uLj418NswztoECtauCIiACIiACIiACNQ2AYmT2r6+rnVYxdjbRRmAZY0ngx5Y3V2FnfvaT7b1ZDJm6Q3ECaPX41HWNSl0tqVSuXovFMNFkMepQn+kaPh4e9/eNzvbezyvLobgQOAY5UIElAkGullDxXRdMgWZzTkMbJxQpC8bPnW67yiLqmQjrCZvI5HaaJiS58QqGpuy9GGsepN+nNtZaYFh9YmtWKgQj+TnzGqaMyPJojH4m2w1LQAQBAadmNaaC6BNBERABERABERABERgBAISJyMAqonTGMbux4wsYR9vBpMHHzrcvuNAT09fPhpNhCMRXv4zACUWZWRJvrMnnvWazPB4M6zCKBmUR3tP5mQXs02xaIdxqqBHyMx2cDLZW/9Knt5g5G4NcVMURjleF7qAdfZl39h7av+R9lQ2lg/R6ctpjmKtHGQXFAROnsbZM57NyJ5xJrXKiRE5pUoOUjx9usKFbCycWtKWiq+dM6slDijbaj5IaHcD6cqPA6e0KwIiIAJVR8B1A666aqvCNUxA38laurgSJ7V0NYdpC+ax78owI0kymcKufYd7s81eLOlFY3RRMmMoGPcRZSebCXXlQwmzFIrNEpWRyRWi8USyLtnbbfptWbufBMwbbKLwmc/lYoxbscLESJWi/LDiJO919WZ3H+oIxVrCyXo6Q2G/G/eJyYdfRdPdhdgC3Qedw0o2fyB0LLtnMh9LKlP5Yp36J6PVDOo3U5JZcRIqdO06dHrx4ubWpkTILHsPCj8hkbSJgAjUAgGMHteMoEe0Fhp2Fm0QirOAp6SDEzhLdaHv5OBYqzNU4qQ6r9uYa23kAIkw9l1ShrtHE7FILpTO06GrEMrlc/xnXmEECuPWbSSiIg/4Md268t7iOS2pVOGFrYe6u7usEc5IE7qCGYucn3Aol0uEeroTOSNeit8rswx8JFIIR3KFcDqbSMRZ7MQ4YYwR7/s1Sma8c7j0b9lZ3m0GlRj9SxjkiFSlOg04y6zK9HJDllkCiVQh0psNp3NeogjWlUjyYYoeMvMBpSlABERgign4yoR6nKXxNMUtUfEiUNkEeN7rT6yyL9Hk1U7iZPJYT11JWMPux5nMuDmyzMt13uI5J3a2ZfvSdo7gcJbuVzmWCTQOlrCZ9NYMbMfEpuuWcY/k0g3J+NIFTeHYkh6PRRmda8TZ2VZueIVYJLS4NdzQcGbeLZLnmNgrkmchFUazZDNpRqaw4KNZ0dEONjE9w4a01Y2SCozdGCs/1M8wCmG43GydhqyWqbvxGWWzhb5EPBqL0UvOST+LeeQyR44xXOV0TgREYFII9PT0HDhwIJvN9vb2zpgxY+XKlZNSbHUUghG5devW7u7uurq6xsbGRYsWxWKx6qi6almRBPhGnT59eu/eve6LNG/evLlz546ypm1tbZs3b3722Wf5m73qqqtuvvnmKOtJa6tmArp+1Xz1Rlt3q0zM+A0Gi+QRBqgT5suaN6d5ZSrX1plmBi2WRsR/gijB1GZerc5IJm7WYczxJoNUxljPZyKhcEsDfbta067vlnUeWCdIUUJEQ97Mei+ZwPfiXC9F5UFHscZkdPXSpqNtfd3pNPrHGfMY6e5nqHZQgrX3hzo/fLhbNXL4OEOc9b065nyxLYGoMMlHI/m6RHhW64wZjYkYiGhyUQ0NUDUuQJIkQFC7IjAmAn19fSn8toVCS0uLuSWd+42yTp069eMf/7ijo6O9vR2LR+KkjPqvfvWrHTt2INuWL1/+nve8R+KkjI8Ox0pg//793/72t5PJZCKRuOGGG0YvTo4dO/bd735348aN/LXyZ7tw4cJLLrlkrKUrfkURkDipqMtx7iqDp4PhEuYzbKxt83xvqvPWnz+7syfXm8G5EaNTFxMGM9o9nM+faIjVRTMeDhY7h5Yd284qJRns/bpIJI6IMYrFbL6hQIbM4RU3Yy9sR6+ifV+IsVPwmpPRSy+YxTTExztTPWRs5viyOQyw5PshMN6VgdqgX5QhDpA/E2LBDFI/Oy2Zl4xGZrUkly5oaUjiimYeYdvq4uKMVCqgSGBkZdYQVVWwCIjAIAS6urp4k4rXgp6ivBlFIRBpyZIlzLrBa9Hm5uY5c+awP0jKCQqi9EcffRTnCeYO/oG77757gjKe+Gzy+Tz2Ga+NM5kMht2yZcvGXQbYQY1LhPvW4sWLsRTNDYxnxwBN+Mwzz/zkJz/hilx99dXvfOc7m5qaxl3oJCTEAwYfKPF1amhoQFPxOQnlqohREuALdvjw4a9//evu6ixduvTaa68dZVr+QvlTjcfjvMV44403nnvuOYmTUaKr2GgSJxV7aSa2YtjKpR87CB2jP1RIxcOJWY2s+M6AeNY5Md25YhHESTiWTsYTdrJgemUxsRebWXLQjE0xwsJWjVsJG2msx8U4T1jOMVpIon8CHg9jo5M3c3hFYqE1K1pWRUJ5PCusjmL8NCMICBKPT5rYCk7QR5nGKXj0WgNNxC5DyWcuk2b5FjN2v9hwymXfNNxu5sFuRBxQilmZw9JZ/RYBERicwKuvvvqtb30LCxhlgs3N7Yd43HMwQXgz+u53v/u+++7DEHeBg2cx3lBnizNxSH19Pb4aLPXx5jRJ6dLp9Ne+9jVssoMHD55//vnf+MY3xi3b6B7z0EMP/fKXv4Ttl7/85VWrVgF80GZwLeCDSuTTPgsGjVUpgZ2dnc8///xnP/vZkydP8lYeqfnWt761UiqnelgC/MUhcfmLo6Mg+2Oiwheev1OkNW8uWltbx5RWkSuQgMRJBV6Uc1ElBpSYfl1muUTr7cA6NhqBASHGxcEQeONXwXqOFqJmPqpcVzjfw9onTAvMcJEswgRHBwa2VSMRk4l5Y8n4EerKoRkgbu0G82lsCPdjI5h14TP0EDPn8zEvR3TzshPnC73DzMxXg29nab4Pme/gpQVDjY9pmI3VXIBh5gkw/cbyuYiXNfMtW8+JHaxC2mLppUMjw4bNc5jidEoEph0BbkX//u//zlt5TG2sDd55O2XiQOAlOHHixCOPPMIr0uuvv/7GG29kwMPEMnKmNp9sGD18Tmz+E54bfFyHliNHjqAWxpe/gwxtmPMO2/WucTbioAQMHbuNr7jJSUWjqKMri32+OUePHqWBduKWyamCShkbgeK3qnTVRpN47dq1999//ze/+U06f3JPYBtNKsWpZAISJ5V8dSa2bigKM8id/lTujQRGdsQEYDfzjxm6UC44VOKFfDib6S3kUxjZxm+SdWuf84yOsNZ7IWxWZiQHDHBu+eaub0ZcmCMe4uwb/4Axzt3zgBP849ioG1Mi/4xMMomw712kwdrJncm37Qc7P3yYVVzDRxnmrKn+kJttsWkDzzw0Xda02rTYtLH0U5Z46FaWRdShCEx7AvS9efDBBxnswXhrXoIy0uOmm25yr0KxWrAv8aW8/vrrmJh4VLA1GTjLe1betp4jclUhTmi7kxZ8up1x0HBGPO0lLbY7IhBl4g4H5uauhbMjB56tnBDXKOrDDs2hUU6WDNWuyqn59KzJ+L5R+FucH4zrSz/D2bNnT096tdRqiZNauprDt8Wa3NaQzpllOkKsBW87I1lBgTWPFuCGTbcrcx9HTxhfCvZ2zvS/YsR8BDXR25c71dmTykVzVmBQHunMo8zIDDNbV0tDuC+dSzByhexMsP0xB+b1FZN8RVk6xbomTHlFcWIrZmL7G6ese6WYix8+pp2B2Y4hOYkHrLtik9uZySwtc8jMAoZiEUOptabZxa0osWBq1pExKk2bCIjAUAR4bX/8+HEGxe7bt49hHiiTW2+99V3vehcjBJzVgvGxYMECRpu8+OKLTOyDSvn5z3+OdGHA+lB5jjWcP1PK8lMF9/3Asjh++FTtUEl6YbE5d8fZ3GnIBPIuHx4IgzY/2EwiVIWhj9BFxNI0R4kGBluh/aomwDeQvoWMfeKbz4Wuii9kVQOfhMpLnEwC5EoowhjbRa2A4mBVE1Z9T9RlU5lsLotWQWHk6W9lBUM+ixnNyiQsA48kiURjcaKwk0pnDx5ue2XbsY5MEwrD2u7mGU5+tqdTPhn3ls5Jtnfl58yIom9Ms60EMRKDQyNv2Ix9bk86Qz342Q8UJ+j6NYxvpV/sQQ5s1QI6YZAoQwdR+hnz5Ew0S8hqERvGU9ksKEnM4gkTaiWdbaY9MtnglQIgneikTwwTbSIwBAH622zfvh19wiCKCy644LbbbrvnnnsY8+BbGxgfGzZsYMwJo2a3bduGufn973+fwyuvvHKgGe1LCF6WM8jbH7hC4WSIeYqpOnCOKT/VEHU846PwSyQJkRnVQK8Sv78QZ6m5s4bNja/0asJPNWj+JAcC+XC3YHO+C/JxamFgEiYMYCM+p2gL0UjCUH5XCjkQDiUscp/hwEwIAQ4+K8QhO5h3VJtCgcYIDc5SeTbyxwQkPJgDBfk5k9bVx8XnFJWhaFKRZzDVwH2SuDpTB4Y1UxlXeWKSPxvOMXexiEmgizwwn4Eh5OYyJBN30akMpfhNIyty9gf0u5z9+lAN8Do4rmiKoF18A6E0TDXcpYQJOQDBd+65DF3XMlcKFaNK9Mfjc6yt89vLnwzXnayoG82EOadczWk+9UTSc8qP73Yojnq6aMGvLhV2X10Xje82mbBPfN4UuAvhTpGKwR5cd4qgjXw92CGQJFTJ5UkIFaNKVGz4bwL5s7mcB/3EX8q1c9HIiu82JRLCBXLFUQSXkuL85NQBMiQhkHa5iRDcd5VGuayoofuukmEwrZ/JoDtwc399rs5kQpWogCuCJEQADlecCAS6izJoVgosIzDC/aIstg6rmgB/rAgOmoDTJMq8XPHk9m0H3jxyrDvVx7AJxqkzfMS6TsI9Hb1dnRkcG1nuy5ksw054whw9cnrHvuNtqWgh1sy6ikTlx9xGzN8lj8BcKFYIM49wOGa9MM6256+V25I5kS2ETp5kUo1TPb29vuSwNyGTxWBgkTAm9WCnRhlmHszj2AatjZ8PFbKeE/fbBFvtVTxv0zod6J8KJ2Px5csX1yWjjObJuQkGitH1SwREwBDgLsIf+5tvvslobA55nNNP46677sKYCN4EiIYtsmbNGmYdZZQFFgk2EHcVTIShHvxkhUHzhS98Yc+ePSTBjiEHDAVGRTMdEM6Z4AUg/xFNE+rjausnJATD6Dvf+c4rr7yCssIiIROKuPjii+n+jlfHxefTTzLoDncHqko+mzZtcq3DVJo5cyb5vP3tb1+/fj2pHA2/AgzyfuyxxzhkIDs0KPT/Z+8+4DWrynvxv6dPZWZo0pmDXTFiIRaMUbBgVIr1gtcCsceo6F9NopiPMXqjMZhrbkzMNTc3XoPBgl2woAgIKkFQxJJQpEqHqWdO/3/Xfs5Zs+d933PmTD1l1mbYZ71rP+tZz3rW3mv/fqttCS1kB4mYxBJoiRuPPPLI6deiGKqyyMdSE4TEUh/AlM5//dd/5X9WQXJg3EMe8hBfkHjEIx7BjFwW9sgifCKh/YXtmxSYD4QFiHnAxDyz76LIqoOwo60HqGWDmXuUqFNFCE8CxGecccZhhx0GQU6Vtq1CkSrFJrNqP6AkF1mtZP8ASFqMA5p0R73sZS9zY2QlcmGMM0/S4La89dZbCbPfncYeuyc/7WlPiyQhmdNGQEV8+ctf/vnPf65O3cyvf/3rI141ibRGgoACigSm+/v7TzvtNFtUbWvpcqYGEj/wgQ9QZQfeY445xlosl8yNdHtcdNFFwmrTvZTlIyA7NImALRAUUEWL5xCjEB4Qt03Y85WvfOXSSy9VFzzwrne9q/7UmFr5rergine84x0K4p5B/Oy7ZWDTVfePS+7kE0444clPfvIOrhCj9vrrr2eGe8wMrle+8pWMMcnTRFDVKl+V8t/+239jQy6p9uEv/uIvuFrxH/e4x73whS90yf2gyBdeeKHiKzULGaaP45RTTnHz57Rta1ZkCOhJueCCCzyDjImGRfE5//nPf340IwRMUnUDMPjkk0+2qd121282aQ8JFHKyh1R0AtCmciEn2ltD9aMj49ffcPdvbh1cs2HJSMeytNuUdpiAKVyjY+s3jYz2rBpq9Pp+vD5/gyr227pn4/hdG7tGe5Z19/VZEJ+GP7ATQL0iKIZeOrvt84XR0ISexNPrDdRpn+J1AyO/+K9777t/7cDQ8IjdjGOwYcL3WXjLuqDA3K4p3mFbirb+itw39520SkwfM9H2tBNKS+EnLqc5alVh0hYB6X0dZG1iSlpKnCxQvrHhW+75zyMfevD+ey9NC3bS9gDlKB4oHtjsgXjfw22QBwAK0IC2rXg6XvmQx9FHH20vL296mCDw0GZdVSgUfvOb3wScgAMoIfA6eUpoAGhAE2lhJjtcwazSzRA61MV8+g0wskcty3XQgtSwDgFZAOumn61evfqJT3wiWAY11hM2GWx3MvAR17r22mthLFjKEb3XNMvlgAMOeNaznnXUUUfV9aBzkKUceQymhLEU8JJLLqFHJH9yo6wVsCm7pp+AMlOBZmbzP1VQ+FVXXUWJgyUwHAfCdvWEiiPH6KhWHXAwe7ALNlDiErdYo8/Pxx57LNRoSl7UYF1JhGVx3XXXIUgQrVTBBBSKvCJQxUKUQFle/OIXR+VO48y6fiYhe9dcc43pf7QpGgKGyymgTMFKVa+M8mpSiwD/4Ac/4EzVYUdpziQjFWMcyvXVr34V6XrTm97UdnsoOlXclVdeySF52OScc86B8pVOLRNQBCbRhhzKAvuCjw0Y1u2fYZh/THF0k9hgDddye/+v//W/FIGdlMuI8XVVCgKgu68uvvhiMki1W1fFOZgUFBE5Ma8SHWWw24N/5PLHf/zHdT186D7HJz2tKt2nb+hURgUkHGVUg+4r0zXxAVz9Fa94xQzrrp6Revz4xz9uSzpkgyVK+trXvja+haISZYck8KEnmv31hIgBk5SLe+2OTZhn3A+EeSkqnYVRy1dccYU+Cw8sPZQ03RKh1oOgmIrDbzRIqJgO+XK4G9iD8NSnPpUSHvBMkfE8+rkdpa4XZI8KF3Kyp1R39FNV3+jwgHRoiq+/8c41G3oGx5eMd/d4A8DRaYJxeqiHEZRG91LrKUY7bCycGA3s3dm3uKtv+egAgWpKVxr+SGMGgHqAdUjdkzwJ61OGFe1IYhs2jV536/rRMdsW945VeN6H4iddj8xMNcSBnGzRykwm2epfVkylc6tptyKQ1uYkCqbgbEulSyWp9mZOn7hM5fYzsbbkNGEvgdHhdQPrVt25FnhYuWxR2n1gQq4SLqfigT3VAxqMeGHnlgNK4Ayd8d70IptwRvhJEl3ywG78JAwVRTjOgAjEEB3w8CVYSUbPKHQCR8KmOlmhGWcYBYCAJMDu7ejTBbshVMMFsmMVqAQXsg1SgQghPP3ZsoDeAG652FaobmeE9S7DygDN+eefDyDSw079wTqbqQVwKXFGVJAfWBBAz13gygVbcxTAJKHGxllCMSSFwzkCrfnWYzjQgABV5CnhQGc4HqakR6VQKJyrIxRGHTHy85//vLEOQBwKP+KII/bZZx9eVXw40tXAqXQaw6Gz1RjOAQrVF6LFVwxTTQZqkBmQGoiE8HgJiKfTVT3QTJV7q6p6oSLMeK4jz344NW4qYUX20zkYYKiKsyIDwQ4mGTZRm5Top0dFgpbAoMC6WlNSmnWWo3+4Uz13GdGvQh3K7iZ0q/hWIMonF9iaQgH+UWQ1C8Ia6EADyOMnrKpr22qYoyhBFOnkMdvZffGLX6RKQsRS5bLHEQUkrLLwLof7UwGJMYnDSdKDt+CKHhBuN6Tj7pIErMfzBerGUKh0slCzZlpK4k5WEFzFneB+YAN73A+eOzoVkzOf+9znZsJW1zZVmD06GjwgMdDxyEc+EkfFndzqkrhXuZqRcmFMvktDm1LLWqRq9Sjhh+aC4hXuMRaqhWDUSq0uCChy+K2/v7/VHmVRg25URFqmBNwAHlh3giqmyr1KQJ2yxNMkd9r4Te6t2krMVB4o5GQqzyykeEh94t/kWvTUw792w9BwY+VYx6Kxju5GWtWNaKSHuqsx1N3pcyVmjpq8lcD32LgBlPG9Vy4/cP+xjbd4xgYAcotIMIe0GzAKksD4WLfPyA/GQIpz5cDIb7yxaWz8vo2ji5cs7+zqNRusWgmfcqwOLCekJyPy38R8tvJOzbJNgYo0NcXtpJ+pbKnQlW3JQVHYxFYm/JwKlIqUim+gyjiT8aJF960bXL9xZNVe9lMujdROqouiZp57IKBSxkwAja+nwWfgCxADNsVcJqUk4xzyAjAlfOlnjql7AoLRR+tzH2Ax+GL5CuCoRxk3gC+BD1AYjAAxCQDWIC8YAS0F1qmrahtmDKhhNMZwgU5iaXEJS19gHSAVyXFVByp+AuvIwrQi2VGFtwAx2eYoOGNM5dKBrUQGRmAm2EvBMRAWQsDOkJOAOSTAMTAUm6Vqrw3LALIUQtJKAZ/xoQEWOAk2it5cyInmtgXJkfLSYcxF6IReYUVzCZviEGCUHjhMrzP2lSsrAuLJf/e735UvjE6Gk8Fc1QeJQnKs4nDGU8g/j33sY5tgN19BtDwJ7survzo4Sq0pnaxdla8ScSZP0qw48soMLZeibUDxFYRW2JoDIUUVBNeqCFk7uNR8KndU1IscIVezcbgUWnVXmFZHRhUTk7VqVeToNVdA3fkq12QhYwL1muWfuEv5UKa0fexjHxNAuuhRNAoZLK07RMXRyfluJ/rdpTLl0rYlahspa7bJy92IG1CrII95zGPEKCPS4pmSkFWcrFxmakHYSqE6jI0QUzsOT4pRFHevS+rO+AD4rgYJyILyptyV0YGZEOBe0FwZTeRTO9TShhi4neSomM7CBi5UAdtaCygLRz0LBrMHiVIj7gE8xA1mtBM5Ud4QdmaYOmKGQBM5oY2FhMWzgYeFVZZbwg3vcKPGvRpDdu5VuZAhQLMj2yMe8UBv1CbDCLiLVJYuCV4yPKITwcEDblQ+F8ntrHKu68kKS2AqDzTfZ1PJlfh57gEvdr0dxjZGDVNYQtLV27P3vvusvbUxPDrWOe5L8J3Gqzt95AQ3GR0fGR4h2y22I01h8hCODI7tt6Kn47BlGzcO3Hq3WV/UpWGYRDNMBqtw+YjZS8PddiKWKFC6Zzo91+YxpW+CdA2PjPQk/qOPE3dIUKM6qmlgkz+2+Fsp3yJmhj/qQzgzTLItYtl0BROufipP+ssTwbom4w2SpO81Dpky0LPYLgSp00m5UnO3ucnblsyLbPHAQvNABQDS4xBfV9QHD2GYowKR/+3f/i1gAXY4a4jyC17Y0YpCKAHK0ZsPfvCDwBk9gP6rX/1qEAQSAjjoAc4CvpvxddZZZ4FxJoSAZZAERDgT58Io4NqZZ54J68hOwphQDqbIUQwlVok465+WRUA93fBQu89HMltB2B+4H9YBZSQEwWPWPlMVWXIA3QARcAnSmT6kY5hzAB3ADqYUwOVAQAzBJb2zyiILuwiwUPJwrCI7/JzmABbBa5bDtVAgvsRX5u6Lr6cK/7M87HeWtV5tMibrx9oSlsud85WOVVZrGDHQkcxXH/7wh0F53fOhJ5QgG+Ag5/AAYibTwJ1slhFV5sMoEfj4L//yL/rOlfGP/uiPPvOZz1gXsdVy0cA/+AC8iNugrIirujaG019BT/qZQY/co6TuOtDTAVUD3CYQMjsMrrsClzCdz0w8l1QKtyM8hh1ULp1huXN64XV1KaDcgWw3nsUq5m5F/YZCYnz1nve8B0GFv929Phb57ne/u2kSXT33tmF5qTWMgpJgJn/6p3/qzg8bmBGFVSlueAMRCgg345NmarnT3HVkCLPHLUeJ2VCmTimjS/zjatt8RXKCuxGFEFaDb3zjG0NPXR43M6jiwWEAnTh2FLDVt/VUbjDjk+odWSIplTvtBS94AcvrYtOHlUhaDFCRnT1K6L37MAqFqPA/txsC/bu/+zsFUV9olftQuK5Zco8qeuPGUEBmeMw9I9xOknu53UNEG78h224SBpN0TF/Mei4lzAOFnOwpt0EFhAHo9CF42HjRkr6HPfzANevvvO3ONR5+n4tHTro6e4Z1MHiIRjd1jA/74nlnNQfLczU2PtwxMr7P8p4nP+4gwyCUYDnO6QDHq0GEns7xJV0dq/byTq3GFaqLZL2El/Z1HrzfYpMzq1F0rAeInxg5ab9jb5V2np7Sl1wsK6mmdXGs4ZMOsySG1u+3z0Gr0pqTCbfN09IVs4sHdp0HYDtA32cKdEh70wPKp556KnRlsTIcExguXvPe9BkqiScMEwB84uF4gyFQgp5yyP6kk04yCgEikA98QANQ4rC8GwSBdAELmAM3QE4Cx0xfRtAN0ISSZYqQGA0wTYXZYQDNObmsAcT3ve99+lP1uRoQ0OkrCwLO8JbPTULt7IehgSG96brqMyQCehwkYcf3vve9MCthE42kesMb3uASPQoVxQ8+EFkro/JmS6Lg2arWAHmZOhQNjleuyDdLhoasR470K29kpFAAN7RHA2vDw8IQ5Ete8hKzfbgr6IGztASIRY3objcBCdeS9Vve8harUyA/+ea8SPqpc9rNoDcal2Ob2Xo6rXWiZwvbBiiRFzu95tASZ4cbQ15RWTkXAaV2VlMf+chHQHNiVja/7nWvY1sWy7moKbeW2sef4V1EhZ1ve9vbCMjRWenESBiehGt5CSnClt2NdYVRwLe//e1uD/O+pMVmcST25BrM+W41wGwczxDcS1/60v5qeXrk5RwZIYp/9Vd/pYBcgfj94R/+IWE1xeCsXJjZkLcBFoYxhs4oV5ZpDeZ/c2wAAEAASURBVPDwW9/6VvSb2Wq/SQBpgdoNxXjMFRCXDsPcDyTrYckjL7e04R3MRFNAALH5xCc+YYhvm5gJ5RSqbpUuoafePYZRsDAydZVnDGfZA8DD5UCYcRWck7C7MfxGz//4H/8DvxWgh9/oQe04ih4HMapcFeBhD6nuj5yL+HLM3AOb29CZpymS88sDiQn4l3rrRyFmXGF4bLRzZGTJksUPe+iqww5baklE9X14QyUdvdqEsbF7bl+7uGugc3zY9rfdVm97l6S1H8Ppe/E2+ZpcEJ5UVrSkYj5a5MbyRY1F1pWkRSnpdSI+jZKMja9c1POkI/e558ClG9NmJ2FOJEpiC+xIgycGquzMVRVRk9Xd1ejrPuCgB6xI23WN8GqUegGWfYFVZSnObvYARIItGD2wl5HOXVjHPBDACPjTM+3F76r+crgQVIIGsnnCrkaMnmOABrADIHRmYw4QbR1XBYwQQ0lMEdHHKRVGJFVI1pXnXCKgCdMhysLAskA5xBljJq2pwFDWAuimLeEV2AhYJibQFaTOVLNBGA8b6c2N3mvgJsxwDp0YC0wGLQFY0Cfn6JoNVAdHOsA+9jhSC1sdOW2T/VP9jIwkd2Q0FsJxqTVhZAR+mTdl9hT8R6YuzDAUAlpls6lfNBtKUh14IEk2izdpzdiLmjVTS33heFH2nF0o5DEMzfiD1RRiaDODbqvkhJKsTXapbNV3GIVb/SPG/YacuBmEAXcmYcuhoV4uatWsS9Czu4hOcNb0MzJclyVzIOSRE0UI6pVLJxBihg1RXIbZkEqORg5VunGbuuT0YVk7sA5kA9HlH04L4yOhjNxsyIlb3Z3mPsT5EfIY8JE2G0NSQgbwMIbG26acQeHTGCCJh7S/vz9XrtqPokUqVzFMAiqRGcZPeM+dX8+XpHxlJF5B1IVxPOMYmAwa8Gd/9mcqxa1SVzuNSfmSp8ZdKiNV5mHEooOaZgEKxagCi/UNlKlNbY6nLGY2ZjHDd+4QN7BSuEQ+MxMylDgEVKLHwSiZB9xoUtR4FDOrKoHpPVDIyfT+WQhXPSv68k2tUhj/J36SehntEzK+/952/k1dOBolT46GpKcLJRnrGhns6diAxSQuYxsuKdKssErOWIBJWnRNAAM0RFucHNU93tHX2W1nr+ohrFgLKdJjI4u7Og7Zu2vvpSsGh00kS8JxuUq30DB6DAml6Vx8l7zWsBdzb894b3dyhblvVT1MuC/5ohzFA8UDkx7wsvfW180Mx+huN9tHFyb8CuhAWvAN4GhaDjIAYcCyGRAHLIDO4Riz9sXrogatJJGW+gwOqhYvNTtgkJnx+r/BNWr1y2Id/VVn86Q57f/CLqYqSQt2GNhhBujTXrTR0O+uREgIq9hmqoxeW2WBaMEvkYoMeNED64ikJ8pSD9AP8wGvcKcOb6Wr5xhFk9YhLLmiZSVTGdYan12UA60yERM+DLjPmNWrV0NscameVpglJqGZJ0YYoLcmwWiS6qNBjB5x9avWeBJ255lcWXX76fFTFmqTl7jRaIxaUF76pzKyKZ6SfLhU1x+SYqBP9EmNIMZosFlzdT/XFcpXcVQc7K43XUK3K/4pRuWGcjJyVF/wNJJscEwRxDTZLIZmcNw9T8xaKWwBqMVk7EHcamfdjKZwZBesO5tRlwkSxcl8rl6QEywlBGQUluSfYty9th9QLg8It9RVNYXpxHY8FDwW92GTgHh1hzJhcUhpDN0oNbF6GYVlxEWYvDmBdlpT3VzhY6zukLaFasqo6WcUys2mIhQHGaO/nmPIR2FjEIn9/IMzO4d5DNZKsNlPpXBvxFOc9dRdR0a5NAtoGJIZlR65lPMMPVDIyQwdNb/FAOE0cjKeBjU08olM6D0a2WgOqaEQS0uMnKRV7wlI9xDt7LJP/xBKkp63lDK92NNZeHyop6OHmgp4i+qSMF3Rc5keU3dUpWeCcVAwNp52aBwdGzeo0tFXfSI+6YpOGvhA4nRIkHKY74eipaIjexGowslFFvZY1YMbGjapyj7fS1rsLx7YFR7QioAOUDhI5NXuJ9gHK+hk1XcLr5gCJF/962CciSJQC3RFTCvjrEcWsQFEoBCXQF49nZJPZapLgSYhJ/qDOUwPwuTCGGtn4bDIWsLU0lVDFk0ZRTykAshCnDHdH8wCH/WqGhRyJoOZxCBAE2xt0mbtO7REnpgCRqn9dAjnn65miB8aXGpS1fqTknpk08/6JWEKo1KEOSHQZMhEwsiRDEvCUayCLM2FC4QXSjhcjGriHLAVBASCaZCw7orQIwkBJA1z0BeuFprEwoD6marWsrcWLcfAzfiwylIvqIL+77q2pjAL1aM5h1CsyYTuPYsWLCmJ+0e+DhZSpWj60RWThpxX1kYswvzDmeFPhBzbyTIzDFDuTg7umtXW0/I2figjtYAsueuUgpEh7ExDPaHqA7KRKw6v62kKS+XOtLaHQySXqkkPeRnhlggMSWFV6eAT8n6GQuH46ZlCaD/96U+zrb/a79tSE8Jx/5NpMmCan4Q9gGGPgLJPJUwymJVMHZ5W5xB2y1lqgt6QQUt0N8Q9ny2hPyTFRHG0UebpuUvFOKbKtMS39UAhJ23dstAiK9bh4dfw+KK575ULNXo7u7rtJGXVYmPEtlsmBWgfRu3q60le3NFpfF6K1GKMj1h8YpmcmV3aHKEuMzUzOZE0jZZ6Lkm08gsvmbT6Ii08sW7eu8SS/LRevoLuepXkJ6l/aWQm8tvs/ZTLRJu1OXJuh1JBq0YqlTJt1BWl44Y0DKWI+jMn2+G5XZJiXfHAbHgg3uKQt8wNfZhi4e3umTIbypZWmAkBQFZnqhW9Jvqb2P20pz2twhIJYGEveuIF4AMw13SU2Ep4+qJIBU4BlxAhybBhmiSUgyaBwHS0MwZqYYOETEWNshIy4A55E2lARggP13ImJhVQ66oCmm1iOGiaHONSuKUuJkeHmExa4mpE1iW3Gm5KEu1YTtV0VbyiyRTaw6yUIguIj1Q0BEojQ0Dx/QT4+CqUK7jKCoQKwRuMcimcQyBk4ky55PSgc8gnbQ6XuFpkNrI1kK2qX2qNzDGUg+/YFJAti3qqCGd74qcSxbpq8W4AFIVPQluYFx32cOqxxx4bpop35ByzWjG0KSZywgl+xtFqwzQxcmdPmNRWLAoIoMcyEqyDmIyycD0ckaxijwrKMk0BSQig6x5YrourIhWzLimGYboM1DKd7n83A8+EpHMIR6qYSBYs9P3vf7/eCk8cD7u7smRd+fThyMIMQwZQIvep5ElqXviHGfEgR2W5SzVBisl4HElJ1VTdkrpOSRxi1LizHP2cKscS39YD0z3VbROUyHnogQD9nsYU8CdhZI2jxVvgc4/ZWGkNRKIWXb4dn77v7jWioa0E8QObe5EzyNLj/8Gxxm/vXGvqbsUokjMoTeSjo9HX13vAfisslE9ZTLQzEqZWwDNcPcZpFX1XmusU11NrVAnKs3p0c7LwcpUmgvPlrARK4l+yPfmO4VXpksurC9XF+VKcYmfxwCx6wEMEkTjYoPvWWlu7NkEJsQEU7Ai7/OM//qM+YEMKgVrAHYckcLwZUygBPEEMRJimOTG/HOaI/nKIeXr4whjaZCFHwuYXOSSHC8U76hkJi4FRWBWw1U8axMsUfXJJWhgRcoJg6mm31fM7krZtXtuNqKZPyM4wVdnVneL7KYBt8gkvhTFqIRwVP2FBDocXVSj96jRqLW6PtvZvRyTlbrBgPmFkq5K28SKlRWzY31p8VxkfqtomlyTi+cRKjxgzaSvZak+OCRDcmnsWEOBtfgtPZslpMopLniZHlq8rjHDY7x5WHREW36o2YrJAqx4x8bB4TNAho2T2gTCHSu6hsFVnWyVNkduUigFyd6fVSYXK1XOhch3i2xLXeqY5x3Ba/lmXKeFpPFDIyTTOWUiXggWkTX41kBWHH08jID3dNr0bscgEJ0n8wn+dI2ONDQMjo9VOXVrZkdExs7+wj4HBsfvXrbnp9jX3rLOPV8UlwkNSaoUa44t7u9ZvHF0/ML5ssfGZinRUAh5Lj7rsrBO3NDx97nGCk9SE0shJjq6C8Tvxl3l2aIwq7yhmKmliJKkPZiwau6ro869Q86wOirkLwgOajgzpzNvWo2kKFpQAPehdNmwCJRi4sCT92GOPrc/WEO9xIwZD0DDxRE7tE9AHzQCtkATyW0USFNJPH2FoTEYOqEVD52jNh7ye+IjX7RomkQS4qxRpZUIgoa1m3ap8V8SwJw7KmbStVpGXfCrD8lUBxSfJmXyCHDpDz1whbWgg4/DTpQi4DQTcBjw5TS5T5b7VeMrlpTZblUeMc1hSVyWS2RHferU1pp5WOAQocci66epMfkpILM5TybuqaB4K/ESOkelUwvV4RXNMr5w85VGh02umilhdfw5XRqVt0+Slip3tnWXuWSyyn15tVtIaqFu+VSVhWz0JhVLxm0txH7q6VT1hRojNULjV8j02ppCTPaLqtfRmayUG4f/UnT9x3HXvmjVr1w0NjtrycWRsFF+x4R4ecsed9w8NajuSPHGNkj0p71u7/vqb77nu1nWbGivjYx5JZwLghi9To7i4Z6S7d8OmocbSxe6rdKk6vH8QEzM+O++9/97h9P1Ba+onYPukDPPavMmqV1LWk2XndIAnlKUaB0re84/zRfrU8qK+Hg0bZ87pAhTjigfmqgcgg6ABVvEK3HDDDYYsrFI1QUU/epATgNWBacA3JvrbAku8n9JOgw+gJTJQrxlK5KeR5Bu4BJjW0y8VYUM6ptoDUiLl4iBDQx2+uOSnQxIQR0ZkMCJT0sUoi8k2JtljXDvue7nsuBIaQk+8KkKhmOk9U893q5K0OXBODjGhTtmPP/74qAjxWVU2ICvkYf5U4zyP3WXJnRJgjDplhvqVy8x1EgZbYegAr00JMS5VrIy5OE0CuXTuW95gQJPAVn9mDVNlEV5VOmZYiNXWzqlyUTqG5SzaiqXqrCqOmMD0wm01iJRK2VWrLRP8tOwkdp7wjFisMlWqmcRn27bVsJB3Y+gZ0eawRIzhtXiKZ5I1GUkcMxQuYjxQyMkecBt4JBIliQdDq5EWh3V3dt23fvDKa2684877RkdsJNU7VJGTtDF+V8/gpuHBTR1d410m+Y71Lh4aHOjq6b5nzcBtd24c61ze2b3CAIuxkfQShryNx1jwbWlJzyjVVqzUfJoy1T840ui+f92mq39525p192nlUmxtbCW9iOho4SfJ7vn4OCtPVSSlSgWzEUFX52EH73/E4QfutazPF2VMg6su1fxUgsUDxQPVnBMYLmEcH0dauhRyzV6pXu7RnqQpVeaOP/nJTzZxC8bCK0DJkDSF3YEqkDe73ea8IAW4I8k0rQmBQKJQEcmc6VQBwjJ11l5iSr7AGL28FTeZWIwubeToLJ68XBxAHnSogEiUbX8okSOKZfV/f3//VDlGPEhU+SadYgAh4nNGfro0vZKtXs0acmCnqK3nGwbzhtpRy6a3KY4dhxE2FeoIAQYIxBE28CSf8yF/zrCyIl+qsra6JU1hVYMx8jPyE4RTdpGQJEuEBXKM6sONSYqE+2MnqLpOSRTHXX3NNdfYegvGDT11mRwmTKEZgMSkUth8aQcDYTYlCmhVul3plEsxTZ2KGVNT6ZeQq53ZM5XMzONzVeZAa1qVyyRbBlu+YpmHQR7bcGN3p512mhgJW5PMJEYRHNuU3P2Z5ZlknYk18XH7WaW2evXqqXwilbxYFWc/HTMxsshkD9RxZI4sgQXlAa9KOwRbT6JUQ/pjxsd7uzoFrrzmpt+uWzzcu6RnsbWM7oQRy0Ea5l35UuPAmrHulY3OHvO3cBbr4LXKQyOdA0OJf6SJYbFGZPKB8/K1XbGJYNaAyyaeQo9m9a/D5z7uXjtw4Y9v3DTIjP3T+7tycCwzqfk6UtQiJvXXouZDMC0v2dwSaZ7Ghkd+9p93d/YseeBhi5cu6h0bGZwPxSg2Fg/sJg94RmAyDYP1xL7QDIggGxC/j+7VLSCmSUgAvxqyMCoCHEBO0EyAAGfzsiAY2ijxmQITQmxJFEpECmQ8QdgRlwTkHu1NbnWq6xMCTWZQAlI7G+4A76Bkyf2cbNs2i2dtrjKbTgGRbMa+kBMBuBxyNWjz9Kc/fXPKlhD77bMEq4HCYKXPw0HDIUWhI4qQC1VXIJJAPWaqcIiFrypPpyXIhMWH5hnqmUp/PZ4q7NHwl7l5ID7AZ4Os6JCOXJpyzKVQUvA9ezvH15W3hhUn1EroaEoVP3XP2wXO6hfJbS2NVLijgghJS8bhkrOfDkTCRxgRS/eAW8IXb6DYuJrFrCGh6jOf+YxbkbYmw5LG6vaLePeDTKlyG6OvTcJtf0rOkrgUYT9bI8WQMSKBtNv72M3jAbEdGRqQSjJZOp4hFr6KSAtp3G8KGBqabKiSTkzPayuQ5V2Nw90F4uf4yCV+EnDV2BEPIANsu/jii43zfOELX+DDv/zLv4zHJ6edYYDaGUpmMUkYln+yxycpfYLGjWf8xLcyzzjjjHg0sgynCcetJbnbxqMakeGlLFkCW/XA5vtjq6JFYJ56wEOlIVi3fh37E1FJzUjX0PDI2g1jg2NLO7oXNXqMbDRGxobGcIdETvTt65/TfThBH4Dt4ZHxvffex9701910d3cDmTFykqaKacYMBFSPsM81jo0MW7sCAVhzEofMukwM2zg6fuf9Y4uW7uUj9GN27fLtFNc3P/ghLNFkusnktcZhImpe/NGssTPWwCeDbYo2PHj3vZv2XTWwbOnKRrVzemv550XRipHFAzvdA97cWiVnQP/666+HRYAhndBQEfjelF0Igy96VTEQIABsgrRgGpe0dUZOoEBKfFoRnoBvAi9mkJ0VkpfFBz7wAdm5at3t6aefXr9KIP/MAaYeccQRr3nNa0BYONLms6gFIBUCOUmGwnYl+vu//3uDPKxFll7/+tdrk2XHckAHOtRJH5uMCTA1XBHaKCHmoFa8L98rtUumD9nMVKnzVZHC5MMPkTyfs1U5ZqoAwxyuglZUhX4/aZi5kqmU53h2OpTIyIn6wtNUwT/90z/5wro5cjmjHJCQJTxpn99zzz1XQojfB0Zwm6xz+oAk7hPQn06qIlBPEvEqyG1gUzgjDL5QYRTFXguqKSyJs+S0RVphiyKM/HCaJE3VFzJSoZR2abM9g1EyMvV8hUOtACAua9WKnNsm29hgk+RMfmZtbYVtg+te9aBhPiZNmfroAQlJCXPaHACvfW/UXRcrgtrqnGFkpX5zFm1T8ad4Z/70aNgAg+t42IPG2rPOOsvGzdqEbF5bJbsiMhoWhrlzfCsGnVZH7qh8J8g0W0VMWPvggVXdOX5XGLZQdU48YAu1eKVcPGAhpmbFmyY9OxUh8L6zTmTlyn06uyw16bGMc3C4Y3ikc2S0w7/RaklItSokvZi1Fam9GB/fZ0XfAw9Z0X/IylXLu1Ys7VyxtGvlsq7ly4S7q3D3ymV9q1YsNmNMoslXuqeyEzmxS9dIo2d0rGes0dfoMEsY8/FPQEz6V80JS+ex2r/xWrgeP7fDvWOpXJv/jStvh1IvUnYl9V4rt2XxQPFAkwe84zUWunVhwehxvOqqq771rW/VxTREEG3E4B72CAZcxABz4H7EUwJvveAFLwAddMabhkHMJfEOgdCQ2rRGw2Sqb3/72zYtdfYVajpFuhRXhdse9IBHvlXiKlMxk4suugh4qkN5lyI7eBqOAXPPP/98YrrYA+kmazo69KO/8pWvxDQgHjNtTK+H0euZkgl76AF0dHXThsP4VBw9IUlGILa+5cb6dK+6qhmGmeR9QSevwtzyktDPfMxQzzRi4d5QyFr1pS9fRogHR2GnTf73k29VnLJ/5StfcVd8+ctfVnxkIHKhaprs4hJWgGkIQ72czJ9tkxivwDyNn9APkftuCUycAShLmBHZCahN21vjt2ofH/Ylk7iNiTnq+tlvp13d7T466c5sukpSjNK5D31zMDxjRc3q1avrSnZKmMMRQntIKCCQzefuzKZbV0ZhA5vddZxghJB8PDutZoRD6oWqh1vlQ3/b+BxJJ/rECT5176udas3daA8Mz4iBiyw2wwB7HGHnDJM0iUnrFjruuOP6+/s1Oypd1dsIm9osScYRP/HM8847T8+FB5PfwsNZsgS26oEycrJVF817Aa9tLxtNe+odNCmikRp6PYyHHrLf/UMb16y1jnPI7K2x8WENUiPxCMRE99JomgGm0UxzuHwkfmhZX6P7AR7PA+5eM5j604yreHEm93gaU3BRT+eB+y62waZvmaSYdClpQIVSr8M+y9ev2zTiU4+daYZZBTHSJ9QT7/EzSVfKKnV+BITPj3pSNj8OYMIeAZuHhVKj2Bi17eiKFcuXphH/+VGMYmXxwO73gJUkvtf+9a9/HWwC4zw6MF9sohUdt4AdIIh1GBVBJ2B6He0wnO7JQI1aDN8MMeXJdsO4h2/8aXzgA5gb7oTM/KSWBsDrRz/6EZgrBsy1HsAHs6u2MSGM9NRWEK2tE8jrftaxDUoC0+iNTE0zMwigR18ukjMV2zFnyRQaM1J0skJaT3jCE1ylM/Qz7IUvfOHVV18NK4NcPg3OAzqMFVm7HZjYJclRl3/4h3+gEJOBLM150xZnI0mGE5LpHR14nfLKCKSTF5DX1MXbtlC0SasI5DmWw3kPJKUZUeEZSvjZmVhbDTOMDKDGtsiRJ5WIo/ATVU+JQSFEIuiWn95cgCl8rCuaSQzjagtU3BszzJEYsxWNo+TLnyglBkJV0AlXOVy5XA3mCZS709whbg+HamUPl5IxaufmUS/ohNEeUJW3jbe461xVKEeTYdKq03POOUetUSsLBQxGLbm7UenwLlRBFcuOB7g9bpUmVTP8yYa21SSeJdg7y43XGZTg3iideAEWGldhkgKaRuiu4xPx8o2lNU0G5FxSsVsK3iocLmqKb/tT1aggcx05nJFYIoMRPJXlhuTDtqnaRmbDsrVtxaaJlNDhrrPLMzNU4ic/+Unm6SaIylVZuiqYym9q0wQwzMSjpJY50z0/FbWbJtM9+VIhJwu/9rUsNtTcNDh8y623HX7YIQbqq72DGwfu3zsw0vvbO9esWzfoK+5DPsJocYqV8voWu4a6GtZFYBA4xqiPdYwMD3Q2RhZ19e2/qne/fY11JDqhAfaO8p7CMAQsbFna2+g1/pGuROuM9NgGrHP54r7HPPwBV171nwMD6wykTLZgFSXxmt5y9UmolYVxnjwEM3/qSenT+ym/vasGe2zvfZcevP/SFct7fehyG7aAmT/FLpYWD+yIBwI9gMIQEtAZ8Ag/MQnKJk5PecpTdK6jBLoqL7zwQuMhXvxe9jC070ab2yOc8YcWD4K3fBY+sIhFZzywTubYY4+lBI6UCrfBXkBPGTEb0NEnKhfwgg1iAJH6OX7WC8iY97znPX/xF3+hIx9IRR6sjDeLzIoFRAUWQTaQFqMlbIY4TafxIbmXvOQlLkFdgVSYCqSaVwPxoCiUvPOd79QBD+aa1eaqQuE/slBkEAcAAobIW9NMCVUJMVWQ2moNMEgM5PSnf/qnymIEIGYQMcyQFDxXt781TI9IMFQu9LAQQEfw5MhIGJqXLIyRNfSck1f559YuRzcHQrlYJaLcIcaZKiQBZ8M6VBYP+KqmXmcDaBgLPskJSoRDXnDBBbyk7mDBV7ziFUoHRjdnM+1vqjiB36699tqguJxGCRsUUHZRLuTwVa96FYcDxDrIddUbsMI9jjnmGPcPDYgNIgHWIzluGKnQ1KOPPpqSfB/m8kaRZYQPqBeI1kgF4Wc/+9mmkPEGcmtwz10aEJaRKuvMM880vlFXMm3JJrhuW5n8XOSrvOpWvOSSSxQQITRA9KY3vQkzRwNQdBTOHeu+5YGgzeZWuYHNS4yHJetpCszQ2lZ7mvTUf9LJ4VbyqCaOchP62Ih5fWTM78JSZpgpsW3Kt25DPaweDeNwi1tI1Vtu1N/f7+7lOjdk0DmO9eC7aTUFKpHraIjnva6qhKf3wOYmZnq5cnVee2DpkqV23Pril849/VWn4fqoiGldFkIcckDHQQ9Y3jFuEN/3TLAG5MQH4Udvu2Xp0sWbjJb4trvfdpfyqRMf6hge3WjcpTHck17dFr8np6RPyiMb6bPzBjvs9SWQoHkiJ85dnWl4ZHn32KJ9Ow94ygNH8RjxFXNJp2r2WBpFqXRV0X5Uv/zY+isvCc+pIwqVbI/CVBPpvPSXLupYZHrq2KBtfuaUwcWY4oG54IEMMiBsAN3+PF/72tfAES91c130KEMnYCUgqFfSAQeIefvb3w7kAc2B4+tKTLsCwqxChuwhWogQBATWA4CCZeApJS4Bo2gGBE8hV1ACNGef+AkDRaocKSBH/OQtb3kLMPfP//zPfurZBa9ZLiwjK0zYCXHKAuPyBUn8RzyFDmUJtKSA2BdKEF+WlAoahgtDAzHd1RAkU8EdGpQLBWKAhPQIhB60ATz68Y9/bNAJbELhQHxgjuVW7uIqQF7d/qnCcjQYRR4iZ5VCoYgyQgzAd6gdy4q0DJC1S+hcWDKVTvF8QowrhAVYJSOpHNwLrP/5n//52WefrbIgfnBZKXjSJbnAxOqLM1WZOWCgKuqCZEbu02TadIkHIFq5QJbUYjtcxL3igXJQMmqZqcjtJz7xCd/3REIMkrgfTCgyu8kdwmDGWAcfVrHwj/7oj/AWFKsqzRYjJyx0qD6FxfH+5E/+xHgFbqNenKNG1LhBNj3uAipO5br/8RNmNNk/1U9Z5EtMjZ8p41p8PUwzGPCud73LxCRPGbjvJ8CNTnOOUqgm960qYLaivfSlL0UO3QYSRq3l7AR4UqbO2WAa6gL1cJhBSTJu0jzJ60k4IV+SNi5xy/ve9z5LkuRiNp3HWV0YP0SkZU3eTZVT1Y2J3FWTXML+uj3bGqZBg+Pe+9znPoeEyJHT3CFGRyMLN4Yb2NPqfuA3TYQuElk7snnbmumeKV/IyR5R7/39qx/20Id+4+tffemLX7x8+V6dHWMjIPL4mLEOG3F1VfsMj46M+R4JcmFZ/LJFI70dm5AKbQyCoeUb9xH4NCIgYriKNFqSGkRDJha8V02jvb46uzu6q3GU7FXpvEFNJxvu7uzuS9MZInUIpLDEeZQhN7EuzNOjKsKE+bkUOB6fd4wP8vmW/pmnpSxmFw/sKg8ALsjGiSeeaOhAPzoEEFOnwAIH4AKUmB9lNhS0pxfTPCjxXvx1fCMGsIY4nfVqQ9hQr15wRhNzQJY6NY2lAD2AID0mYDQVCZ4AiHUYA2rwaNNVP+EhpuoRxwosdzbpCOoF7MAUdhJgBs3KYiwF9kVRZJ31CAeuMhQAnbtqSAQtMZ5jKMYlSmQhYLAi+trp0XdLnpeyngA9Mo2M9OijKJgMs6F5QErfbdiTk0wTYBXHvuENb2AM7G4Nt4MeIJ6joGrZRY7hHwh79erVwtPodFVCU7Ogf3ZyZvghewPEVC499DJVfDSSB5SRvLwYz6vGvlTlox/9aDSMr3hmmhzbXnLnGJVSCk4OFgdHuhO4SD1GXTBJjnETGuZyp2EROsLRTh6oux2bBdwJxMiSItQzzUUTSbOzG8zwC7SK9SHbDMjy1LLNaIbSUaiAvFTXkCWnCoSXONZIV3iYZJQlKitri4AcPTgmKSF7qKDVEe7zKCBXc7irz3jGMxQQU2UP4uQOp0o95rr2kzA47vZwlqNbjj/dEvS7mjPNZrsKuCNj9BCO2ym8Spg2HNgRAjmVAL95gt7//vd/6EMfUhcEUD6ZKgK2zGB3l8MDi+ZRSz4nZ0k8C3IPO/OltgEy7nluVHFRd3UxTYoa9wxqPXQBGINlTxZA87jU46NN0IKhLlxHiTK2eiOnKoFWDxRy0uqTBRijcdHof/e73/nZ1T9dvHjJ8mV76emwQVfDQIZxjkQxjLULa1B6EJHOxlBH+kcmEYfqoQKvdfelV2sM6Wt4gkuIEdAQpV6VJF39nvAibpJeWmmpS6fpYa7FEYGQnlQ0eW2+/63muKUC5kKm15NdYpC95IJEx+Z7GYv9xQO7wgNgBLUgKUhkXYHVCJAHfA+LAPoOb3owTq+kSHBWmHxbGCQShIVRQGcNICpSJxj0GPEAMowGQI1NSDfQEsxqAYz+Y2hM+9laXmJwGDMYCc2Y1QMeEQZroCUGKAikYrjDJZEZhNVVBXDRVS875UI/zGpDJ+ihhH4C8JApQMCQ8tLDD61FFkMG8pYjPSAgiEYDtMSZTdC5bkBrGBfiEx4TUCJYDapjPE8qKfnI3dwzP4OcOLfqyTFeHQp1+umnCyiLwuZLEaCchaobpOMBZ6hOLuIdAmAr4I4PGOZSWTwgvnoxNWma7qdUbirjaaiIWwIzUTSaDVL56Wo9MeUmcXECryqm3nqSKjRkXOVVU6GYGjXCnnry1rAkUct0MgMJyTIuUYIny8utIhcx+epWAyFM+Rvf+EZhBaRHqlZgLZIz46y8bhWuUBD3HjargJITcO95djwdDiicw3Hj0OaqS6EkDDPUqRcAHOdGxmc/tC2CTBWfndIiG0EhIlM6VT09zHAzsC30x5la+RpjNOUMj+Iit6jDVQkZaaxPcs+1SVZNVekRMA/QPUwtwlBX2zZsjpbniBJqWx8c8Yqp9eA3JqlHjCjMcOYElYtIqwVhY7/IEn8yOHumbaYlsskD6UZsiio/F54HNCs/+9lP/+RP3nnEEf2veMVpRz36cSPD2Ak2MpLYSSIPqT3q9CF387rGxu+6884XnPSCd7/3zBNPPGnA1iIoiqXyVeM7bD+vhg24EqGR0KiJ0Rf3EPLh6Ovpfv3rXt3Z0WnkXT+Qpp/a5E/NT3qXTE52SlFxUFLD8JOx8/ovb8RjVTkolU/px6pPT3IRP/A5dyxevOhLX/qibUx1E0YjO69LXYwvHthBD+SXUYY1Gi7w2iEgEiyIgOdIOA4tTNW6bAENqRJPgEmSODCTun4xlEBdmTO0Gk8G1pE7YEHMOcuEKuf0aFeHvKAfuIqMSIcAAalglPyzNRCQVzxhmpitA1vYIWtsxCXxzhFObUgVE4EwiXAO0CBhAE2SjjBeIGRmcg4zomjOkvAVDUEMIjsujfLWyziVcsKcSYO0HMKkVskopqypFeYH8orpIOwsd+coSJxpi0CrtqaYLCkQLpKFsIMGRajzq4gMe+hhj8olFpZEjpKodOG4Q7Jh0kbWZvvY+tZaGnjaXCBhpXaVWgoddQvpydUUudevziRMocEEklS5VRzZ/ogMJdk8Yo6wh6vDG3XJeDoilepTzJCH1+t+oEHNOsIb05dCLvQQppb+8CFtYap6kVGE6XHIkaSYMMxP/RRk/FRf8YA700AnMQE6aSaQD/HZM1HRoTYLNAVkwZlkaHOvOtcFsgNZ6wjbREZ8pJIkApYSmaTnJ5vf8Y53nF7bqbyus4RbPbC5tW29VmIWjAc8G0ZpTznl1A9/+EOPfezRD3nww5YtXW7liW/DW2niHQpAa1E9457ytH6kOiaaWG1d4g8dpmVtGhy6+ba7b/vtXV4dYhJlMVHJY5wahy6t4YH7rRwYGFq6ZHMvWrQCHnPQIi1TCV0VIYlLVVYe/tQGbXlM5r9l7Nz/FY0UO6v2Kr2LuFQ7Fz0BfldFULr5WsC5XwXFwvnogVqDMGG+ZiUwSvyOB0pkXTIASlN5CWQZAUkgqioutTP5knDorMdkVSLlDp3kmJAPYaAkp6IEmoks6sI5TIBwlq8HMpASqSwOmeaSZg0RCEQbkoBRdkUolEqMg87IsSn5zH9SwgzGTKUHxIQOXeWHXISp9BOjjRiFdb/V5SMj58jaJfpzuSIQZ5eIOVMlQGddz0zCEKojcmwrL6O4Gjmy3FGXrKelKsREZplsasQoVBZjsJ9el1lYoC5fD9dlpgq7EyShX09/uDc0OMuIVXXDIkaS8BsZAcbUJSMcSiJTdeGYygCX1K+bkyqpHHJkCT3C9VRiSMoOl2Bw2EBAvLMY/XRRrTlhNj5iPGUOMg7yrkZ8fk5z1jlfyg3RRHycc75Zph6g38+suX5JOLJzlZIwO0u65PAzeDWH4CQxYpOFm7SVn1N5oJCTqTyz0OJtpHnccc+8/vobzjvv/DVr1r3qVaetXLnX6NjI+LDVJN6yymsZqH4+LKMTfBbt6ay84Bpmsui+tZtuuvXu/7rhruHG4rTjVuIZGhQyqXXwQPYOdixZ2jU40u3LjtWllNpIQfWnqzt1AeqCGhpLM8rSMdlo+ZuoTjNWn5g1FrLz6RxNVU+vvQVSD1kaoQpPpgJXo1ApMFn6+VSyYmvxwO72gLYlZxntTD0mX2oNwA1ZPpK0Tdg2MrS5FOCjrjyrCv0uCTgEpldVV7LVMFVttYE4Ob4VYOVL0xuz1dwj+TSFkhGw7qxlC7HpdZIMYWJTyROIfFtVxaV6fMRMpaoumcNZSWsgy9QDWawemcP1q60VkcWivqJ/vS62TZZnbVMFptIcuTC1bi0lfoZhWWGrZFOSLNkaCEkagr/FT2cxbZVEJIrSqipiwph8lXwkyTECWXnrpUp8c6ORU4kPza1Jskw90CrmbrdJg3EwARO6Xv7ylzcRtnjRS5hLF48JtUhXjqznUsJTeaCQk6k8s9DiPRimUZ500sm2L7/wwu9pN04//XQdGBopTaduMD0d8TR6hP1T/qAmzh50X46/5/71N/123frhvrGu5RaYpKX01eskLfUWSIvlx4fGfIKwe8wa+wnwnS5IPDTWec/dG+644/ZNQ5tgdRPDKv9SnBuRHMieT7Qn/5hHgdRCdTSWLO477NCDlizuTV890bO1meqFR+dl0eZRLRRTF6QHWhHDVMWcbM1aG5apUrSJnya7fCkH2qTf2VFzJ6+wZJvs2Sbhne25uaJvjjhhV5jRpLPpZ1MFTH+1Sbjtz+3QsB1JmrI2U93+HPiJtTqWr1glZclNlsn6I2ADNFtxuGr1l1Uo/f39WbIEtuqBQk626qKFI2AM1ONkSZldEa1zsKLriCOOsOzMyi2FBKkdHirnTPcTd0iw2o6/4xs2ja7ZODbasaTRuXjc11AmOwotO8FmxjtGO00BsD8xXX5OrC5JoysdnT0bBkZ+cf399tIYHU/zVhtW1yd+ErhhKvQwX8lJTGTu61473r38kIP2Xraox2YD1W1UCMnCeZpKSYoHigeKB4oH9igP2NfB/oF2EbQuxZbfMJVdE1qXjIJMNhi4qPpWjOEac9hsvAFu7VG+2sHCFnKygw6cT8k9MJ4l+wPae8Tu5tbnea7syGl/Q+Mq5lnGsKypnDEDVdkQCY+WoRUMpHfR4u6+pWvXDfV2+wVtO1djJ8YFhBujicaMdVtf4d/E5xUrcuPCmoHRa27YsHjxvt09pmkmxoPRpPGF9JmUaY5JjjONyDSXdpALTEWapskxLnH06Oi6wXXX3rx20eLFyw9Z0TE8VF0Jr2y33q1mXASKB4oHigeKB+aiB7wWokN9LhpXbJqBB1Sfzax17NoG2mKSL3zhC4ZNoKP+/n4rXjJ8suDEVcyEpE3egCsrfmMfthlkUkQmPFDIyR50K8SES4+K58SwiRFJW4b7NJitMPETw4629jOKog01kzKEnfEZj9/QYMc+e+996EFjd119/aCvCVUDH1hGmrbl/7SsYqSze3xo05LGqE1INg96pLGU8cbIeNfg+NLujr5qriifGzZJYy9CW2EQ273yJC3u2Iruaeo+WZbKtT1HStdhu4HxNRs2DgxVI0WppHxWjuKB4oHigeKBPdEDhZksgFoHn3wqxz7dn/70p22K/dnPftYHlACqpz/96TYyBpxsAu67MbZoQ0vi60BWp3z4wx+273BgqgXghN1ThEJOdo+fd34uxjcozbe7qZA2LvRgGAAxemhjbxzDkQXqFqD4NurWBxDfMzJG6fDRKztaGDORyhIUXxP79a9//Zvf3HjYoYduGhjrGBnea1HPQw9fuc/yh64fMHdrEvlX5MSQic0tF/V2PGDv7uVLF6VPDcLm1SqLBNStOunqsFfL0PAIWmPopFoBT4fBk4nvzNfNmwwHtdhugrHjXGDaQZ1JK5v+Vrlyxsjgpk37HbDXssVLq6/FmPhG246b1JRb+Vk8UDxQPFA8MBc9EG9SneiO2GZtLlpZbNpGD6AZvrsKYn3+85+HuGxSbD8unwOKwRMzuHzwUbyzXl3dvj6xov83dgDbxqz2aPFCTuZ39XsSfCMMTb/tttvi26iYvaVaVpJ4HlavXt22eLpw8BODJz5X9MAHPtA0Sl+8wm08SyFvXNKMSV/GvfLKn6xefXhaND825NvvqxZ3L37AssHhLkAbw4gD9/APWfG9+RXLbBRoyla1P1XaosqoiTlfPcsW9zziwctvv3P94GDaT70C6RQgJ13ViMJUDCRpmMxnW//aT2wqtVtXlZb3b1fWqWhK1dFYsWpp/8F7r1i+eCzt1pxK4dL2G7R1k4tE8UDxQPFA8cAc8oB5B161uvxizs8csqyYsr0eMJULZEJFfKLU5yB9Hh58ApYMp6CjwJJLwNVTn/rU/v5+nw3VC2xRShk321Z/F3KyrR6bK/IxJIKQnH/++f/+7/9+yy23AP0inT0hPux6wgkn+GQsfu+paH0wIjJmQxLzpdtIGMVDTqxLodZ2E/T09fVuGtjUMTpoLUW3vbfSdufpmyXVRKWEt2Fx6Nsml71diW1shuAVPzGKsnxR75EP2mv5osb6DRt9XQVM7zS4gtNs5jhtHUtTJkFtBXZp5PZm7YOU3Z37rVh68IGLl/R2jqfyJpdUa2w2+2aXml6UFw8UDxQPFA/MogdM8vH5cGhVJ7rP28+iJSXrnegBKMscEzVrCAU5sR/Xz372M8wEGNO9i45iL3iLefI4jC1SoaydmPueo6qQk3lc154E8xo/+MEP6pjRDuqbCXJiH4nLL7/cMOLjH/94AyOejVZygsBEySVxRL+OyCz50pe+1KqvO26//Z677j7gwANGR4bHRnwMFc72cRQDLGZ2pfESkFssloKs6DTw8d/4hiPakUZT0kZfY+Y49XR2reztWta/V3f3XvG5VQL52F4SkBXs5MD2D9ZMjrbwCwf52vPY6FBjfLi27F+5Cz/ZyfVV1BUPFA8UD8w1D1iT8KIXvSh96qr6XOBcM6/Ys90eAJOQEIf5KWbRn3zyycBYhk+uBqYiIBC55KvbnemelrCQk3lc45iJXe3Mv0ItjjvuuOc973kGTIx1GPG4/vrr77777ssuu+zwww9HXdoWMvOQfLUeI5XF8V//2tc+8jcf+fCH/3rRosXDg4ON4RGPYKeZWpPzlKT1zcbENKpxgfQkJvgd601CsW88DvkaYYePO1qM4le10tx3a12WI3GrT0K05TxVfIvgTo2IaWczUMm8sDA5IIcNnChWNYJldGliTlclEGJVsJyKB4oHigeKBxauB7wFvJodili96BZuUffUkuEeOn+jitGPXNHoqBGzXOmFmWzHDVLIyXY4ba4kMXpobOT973+/x8B+EfYFti/EqlWrvvvd7yInOmzMzvJ45CekbnfbyCYBq742DQxccMEFn/rUvz7n+OfQDHH75rlnMI2U5A8wp9XwIqqRFOtJJhA7IJ6xeAXQ0/hKYiZy8X9S4rcf1SNdz3oynHTOoSNZW7U+zJowDNcaUfhY1F+VJpUeMbHQHy1h/JYlSDHlKB4oHigeKB7YEzyQO873hMLumWVMACt1sW5xNEW2CmwhXX6080AhJ+28Mk/ijBr/zu/8Tn9/v1vfQAcqYm2Wb5ea/miQ0biHaZEGFre7NJL/wXOfe+ddd8WuefadQH5stjWcNt3CLfxfDZekIQPEAy4XLVBB+JRremKjzyCe1c6OrvEGe9KjnP7FN04SnG8C8dnk2Xmog0O0YRLpA5XMTuVyjBrysW1yKn31uypIKkz6mf6fkKsullPxQPFA8UDxQPFA8cCC90AGCQu+pLuugNuPXHedTUXzDD1gPBEDcZC3F/BVV131k5/85Kc//ald7Q477DBfJHXsyGIsg5W+fAKP/9mf/dnXv/GNzq6uY445xjYUNkY0goL/OIepZBxTPpC2EtaD1NU1PNo5YvtggmmJCpTvUyfVMcFxJn5t/pMYzywg/OAazStPEvmaIF6VwLjBo66emKk2arCkKn4kmqQvm0tSQsUDxQPFA8UDxQPFA8UDxQNb90AhJ1v30ZyVqJMBK+AtNfFlEpOvbCXx6le/+qSTTrJKfiu0YeqySegiVfjJe9/7Xsvu8R/bDb/mNa+hFjPxLZRY6hcUhTFml7WOYkP0nQnFO7rvuOv+tRtHhnwx3roV/6qFK2FCNeLSag2tE+vJWq/tupggJy36J6mJ0aCOcSNSy5Z0PWB/6/urnZPTOhzkZRaoVIudJaJ4oHhg3nhgum6deVOIYmjxQPFA8cDO9EAhJzvTm7Oly+sN9gfk7dPFBuTBh0uNb6AomZy00obprc3MxxbdJnSdddZZZ5999ic/+cnvf//7NvA+/vjjDznkEMMymAlJR5AZgSa13V093T29A5tGf33tDbffuXbTaPdYmtnV6SskSbLNyIj4zUpaFTbp3xU/sZDmYZPN2bAtfbzFNlwdHZsOesCKB60+eMUyWw5IId1myzenKKHigeKB4oEpPJCbuFgl6CMJOWaKFCW6eKB4oHhggXugkJOFUMEYgm3UfdLkrrvuwkk+97nPGeXAIg499FBEwnKUHXnbWbViccujHvWol7zkJT5+4mND5557rrMNvFeuXGn+mD2LCUQumAwDvF8rLiRbX0Ax9NGzbtPIf968aXisb7Sjr9Hhc44dvr/oqBhKFdqiHib4ySwMmlRmTLVbVzKUxYmIISdd9uMauH1g3weML1/eY4fl6lsvRFqLs0XZkg47nlXbCTRfKL+LB4oH9lQPGPfWAaTH58ADD/R5XOsJd6Td3lO9WMpdPFA8sBA8UMjJPK5Fk6xuuukmH3jS5eZ7QM94xjOg3vXr19uty7eBbrjhhm9961tecgZSdvAlJzm+cfTRRxstufLKKy+88EJfpv/lL385MDCw3377oSX2DfNORWOsmPfFeutSNmzYwLOJmYz7unxj43DnPRt6excv6ehmjD2FAXTX61C+ipiojQlyUn2vfhbGIqahF9WCeFaOjXYOj4313bdx7cCoGV0dvk1ZTepKW5LNhJ8UcjJR1eVP8UDxQOWBm2+++eMf/7iW1leldf0gJ3XH6PTRqmtjtbTaWx1D9aslXDxQPFA8sJA8UMjJPK5NwyN62i6++GIrQN71rnc9//nPt0TEUhDA1ywvm3fhCQZVpppwNfOSIyeUWB+PnPic/NOe9jRqf/WrX1166aX2B7vnnnt8cUV2MmWAgJjbbrstjQ+kXXU7RtN3GTsbXUuGxnq6xns6O8zsavheo12Hqy82VlxgC0KQCckES5m5qTsuGYZsYc6WSg2dVDO77DU2Nt7Za1385HWBiQXx0/MTnuErPlRxk2nL3+KB4oE93QOabqPQ0dfT5AudUFp7Q9P6g3x52mYnTQLlZ/FA8UDxwILxQCEn87UqAVwvKsvf7733XmMXJnF5aT3xiU/84Q9/aOUJIqGPzUtuZ/XQx9gLbfJyyP0xj3mML6vozwvqIkbA8YMf/ODLX/6yUR0AHQTHP3q6GksXd++zauldazYODQ52dI7aUTgNnqTFG1hAEIFWHhIxzrN5tGMp4kZHxobGRjfss3Lx4j50y3gJWhLDJlu3lhtV0Lp16wCOrUsXieKB4oE9wwPaT21mNNrC9ULbIP4Tn/iEcRWt7gtf+ELj2E0CdeESLh4oHigemNceKORkvlYfMhD7Bf/bv/2bMvz85z9fu3btV7/6VctODJiYcPXABz7QsnUURQ+9t93OKmd+I5pdAGHjP1lz8BO9eqaTgd1JstP71fjA+JJFXY991Irb71l+39qhwaERgw+TL14bXKVlHGkKWI6b0Bgik4I5m9kOVITK91/7Fi9afthBi/Zd0We7rjRmkj7AGEcOTEa0/OUcmz7/6Ec/2olV05JJiSgeKB6YZx7QimaLo0WNn5pxU3bN0c3sJYuVQPFA8UDxwALzQCEn87VCoVtzqKyDf8tb3oIMmFgF6XqBOYyoPPKRj3zmM59p7jIKkenEzi0qtU3AOl6lBx10EAN8C9Lgyd6r9h3tHB0fG+np6DhgZe/SvsbA3pagpLlMk9t0VW/ixGFyTJOZO41WNend7p/j6QPwNkLu6O3p3Guvzt6OsY5R32JUkEAVm7HFVFmE38yL0xv6vOc9D4GcSrLEFw8UD9Q9kLF7U7MWjY/WT7ywCZNAvLCjnjzCIdwaHzFmxgYB8HN6yayBmMPPyK41U1dFMk+A8pywKRBK2kZKrjPIqLUmnQaq6s2vhGIkFNmae5PC8rN4oHigeGCOe6CgojleQVOa5w3kFWURyGmnneaNZXm6wQqvVQmMZpjf5YOJdn2JF9hOf121VRiRKJNl8daiWDp/7LHHdXV3jA6NdI6NL+pq9C4Z71xGym5d8/gwJS0REQQF0hjj8JHOcXQrxU1fKiUPjIKNWJljMwMszgwNmGP6hOVq8cCe4wHPiCEC5fVcAOLRgok0GozMa+WMGNuZkEA0OAHKIyySmAmTNIgxCYpkjDbUKUE8hk0uFSmGtjVr1pitKuA5jeQCddAfkjl3ra7H2VnDK5dsSV1/Vk6SZgfbpnrwQzgnjw3iqaVfUy8LAtHUk4l1a8ookkycI61c7FzCFXziUvZGWwtzdiVQPFA8UDww6x4o5GTWq2CHDPCisoDyla98ZbyivJkc3qPept589ffxDmWzLYm9+Q4//HDfqj/vvPNwJG/37u6OkZGhjvFhFMXOVltH8duS3azJggLg0QyyVyOkMm5QNZDE9ddfn0aW9t7bGNesVNMMDC8ixQOz4AGw2yRVT429N3SvaEDAa2zhlltu+Y//+A/jw29/+9sf/OAHsyxAtqYvAnYIlMqeV9dee62zJJL39/cby6UEso8xB8JBeOplkxCOxxykklzfCoqi78AuiDbOktZhz/RICPST9yDTIFMPssm00hqpllFdbQ5LKIltFfErvRICD3rQgxSQQKsxOZWAVCHPPM2FVl3u6Mrdd9/tLMwA5TryyCOzHkkcrrpkiq+y2OZLQs2yub4HHHAAhuMIxlXPq4SLB4oHigfmiAcKOZkjFbFDZugS8zaiwjne084RyDE7lME2Jn7Oc57jVf03f/M3L3rRi4466ihY3Es06NM2alpo4gABWMAbH/nIR2COE044ISDOQitnKU/xwPZ6wLjH+9//ftv9/f7v//6LX/xi21J96EMfMgwL1mMpt99++2tf+9o6n/cEaVtMkvzgBz+IJEDk6E0wFmIB2dGMU089VV+JoWYco/WhwxYuueSSr3zlK1aCaTlDCTEJqZLk2c9+9ste9jKbjlBIbW5vkaUvfelLdgFBS/75n/8Z+m9VzhMeebTHI28fdp+ypeEd73gHnfRP7ye5+26VibvYkQEQ8mjJF77wBV0/FIrR0v7e7/2exjaaemfF56i//uu/5jQFwWqUTqFwGBSFefygLLpFps+6XC0eKB4oHpgtDxRyMlue35n5JiLSMrU6Xp+t8Tsz4yl02YPfsvjHPvax//AP/3DGGWfYsN970TvSG3qKFAs5WhWoCwcnOGCsCy64wKZqtn62LmhWKmghu7uUbZ57QCuBmYDgELzhi7/927+1FeFvf/tbWBzUjuECT5NSxrNjROWyyy779re/ffXVV5MXiUuYXKpPxB4hMUdLjwAK8Ytf/OIP/uAP7IQO8VNe95Ndej2VBhnkSwMOED0+fgL6Htvzzz9f1m94wxuQED/JRGvGKrkYoKBQZJPanIVLUjGbNi0AUoFC4Anis0zbAAE2GGhtfaBDAABAAElEQVRFq1ALlmMaktODxXEIbea5oSi00e/Sdddd93//7/+9/PLLuZGRURYBM+LIs5CwtHpGtD9tMy2RxQPFA8UDs+uBQk5m1/+7MPetvvZy3t6vXq6+T+wF5j23evVqlyxi8bkSL3gvRVMjZq5NWp2LlFjqrcsTJvDT+Al84KXo5Uqgji38XPAH74EO0ImeXbTk05/+9FOf+lR7qeln5Ypt8u2C91Up4J7sgWgZeAAHAKDNDrUvOUhtHpeGyOgBbB2zochor0B8H3r64he/SNLzZYMQE7HMXJJc2xXwHXsxvoGZmOsl0oo4k6Cyk3WaiP/Od75DA0KiJ8WheyVGOHEAz+wVV1zho1LMMHKC3pgn5pnNTy6T0AacQWCqZ1m8ZtDZESzC2ZHNmCpAHptSIvptzKi8JneZEqYIwXCcNdpcEfaYwfW1r33t61//uoSmmdl3WFmUWsOLXOF4hlOwHQM43KU4Wuapsi7xxQPFA8UDs+WBrTeOs2VZyXe3ecALWKfjP/7jP3rz6UuDm72G7UrsfezFZg6AaQNeh/ojZ2JSvCO99szK8CL01pdKRyaG4xXuDe0tmyHITBTOa5kERipcAh/oxMVMTNKAlkxcAS+gkz3HFfO6Hovxu8cD8bw44wax9kOPhk8qPeUpTzESe+ihhxoHcBDw4Givrrnmmm984xseKy0VATg+5m7F/CUCWhvjIYC4mVeGOC666CJPotYMD9EWKZS2zpiJ3hkK8Z/nPve5elVk4RLE7wDosQ49NWaUmTkG8R988MHxUEtCwDnsEXBI6GeruyplSZhVrso9DGiVrMeQOfHEE41ymLfmOyfcgpw8+clPPuWUU3JDWmlKZZGvwn72s5/VsCiC7g9UKhhd5I6Gff7zn8deFOfHP/6x9YqYmFSOeqYlXDxQPFA8MLseKORkdv0/J3L3sjQ3ABTwAvvud7+rl9F7K3XrVR17fn70ox81yzleY16uM3mTeV/q4DzzzDMpB8cpNz1j3333hRLEGKuJt7jyz0TbnHDT1EbksjSJKBofwkkOl/C0T33qUzZZftOb3gRmReQCKH5TqcvP4oEd94CGQivh6dBXYrd0tMHzEi1SVo5s/Pmf/7m2RWvz0Ic+1DouiFxCXCJkyGvTNFzvete7Pvaxj2EmZjpdddVVELwhBfyEGHLyve99z5mSI444AugXL18JPddUGYSxOETPwrnnnutsCCI/swI5nK3a6QGG0SkjWTsYFj+VLlpjAmGGSwaLMJAYWnG2mj8uRRtlWOl1r3vdpZdeimjZff5nP/uZ1pierGGnG18UFg8UDxQPbIcHCjnZDqcttCTeTF78XupeY0b8fXLeO8w4id5ErzpXDa1YKkrGSpKZF542nZRmadszR1/dH/7hHz7qUY96+ctfHiMGoUfnn9ftzHXOC0ke874PTOBs3oVeT9zMTDlIy5iJaSGGkuZFWYqRxQOz5QETrkxYeutb32qkwoiBRykQdjxZqIsxDb0q2hCjGYY7Vq1a5dFzMDhLEkYwTOWy5bp+AaBcE3fOOedYC4eEENP+mO9EG5juZzSDNER2YiRHbww1IDameFn+oWfBIxwyxBzZRTnfHLODAQpDvzMLjSPFgIliRl5hRs43hLEUDXguS5aRCn/DtbiU94xvJ39NcpsdNLUkLx4oHige2FkeKORkZ3lyHuvxPsuvKK80fZDxZUCcxBCK6cv6Dk3QMl/i4Q9/eLz8piltXYBa+1eaKeHsvf7Nb37T5DHvRTMTYnaEN2Xu5pxG59y/VC81DAHugBF2RDU1DiTC92Cgk08+2VQ3DC1Tl7lfrmJh8cCseAAE95hoKKxe00R4vmIoQ8DBJBv4GorUeyLeMIippyHmUkbqYTl5HSv0ODyPklg9b8uvuArBS04bPc5mfz3hCU8gL1VG7WiPTcPMj8KXrBPTHmZiEEp23blelhg2YadDjuEHATJinBmsODo+/NQhYvqohigGgrIeNM90L80vP2jtF0bzu+v8XzQXDxQPzIoHCjmZFbfPuUy95xxQtVEOE5pjFxfvMzEmdOlgi1GUmdstLYXkIQyzC8CCWL5pM00rU+0bc8MNN+iANFPc23TmaueFJFylI1Z5TYjXTQvoWM963HHHPf7xj0fM/JwXpShGFg/Mogdwe42DAQoNCDMCW9ftMZRhepIY7Yz5ohqTJpn8M9oizx1tnkQtj4lPWrbQpn/kWc96ln4Ej6rWyZIMrZPOFBPJqI2sIXg/pfUTAQhAH+1bnEPVNGc2BH+YRmarl+Ql9+nFtNWW6OBgZm0hWuTFYF+Wl0TLw3gD4ygWqkOhY3qF5WrxQPFA8cDu90AhJ7vf53Mxx3iR6xf0AvYmi/kA3lveZCLhA+9yL9eZv8nqkpQ49Ni95jWvAdx9ScDuOqY72wCUzrnojh22SfG51ITvJz3pSaZycani8yqsEFBph3MoCooHFrIHkBNzsSwCiUJGe+LxyS0GAQMdqIWAxSdGCeptTqtrgh4YK9Ca1SeJ0aDjwFo7w5u6YExAFdY784xnPMOXQOg0NxWyN/6gEaM2msqsn4Aj/2wbkAQTcDA+299WsimS5np2is+G1uzEhG2S85hxb1sJK45Bbx9I0TGk4bXdmZLiJ8ZVlIUTHOTpp7Yp3/KzeKB4oHhgdj1QyMns+n8O5e4tFVMpvL/r77/623H7zM3avOZpM4BgepixhW16T29f1rOSKpfX61+RQYEge7NiTMm0eGAeeSC3Ntoik6mMVzQZnx8uAuadaqw8YjbsMsULHG8Szj+lQkhAc0BcwhhDyFcF3va2txmo+T//5//Q6apPHNrCS0BCG4W94hWvMBzRFsQTcNRVtQ3r3NEIoBAoSluBqSJnqD8nNzZrhy5sygRau8NrZq3+t21AOFYvyate9SpT4MxM21bNOYsSKB4oHige2NUeKORkV3t4Pumv+vXSKb9uvdLirbbjxaAn1HpJe+tXitO2mwv1iMI6wzTZnwpbDy/UspdyFQ/soAdQCBqid38qVblpMngChRs/mUpSvOcuhh0IB0OoP4mIUHyN3tK4f//3fwfoY50YSmOAN9aOG5SwbxiTcr7TZNd0SYunXdUUUOhStH7bqofB0ZhE8rr9OTtltFDnmGOOMYfNPmY+3uKTJmas8adLFqL87//9vxXQB2Gsf7PyJIxpqyrrLIHigeKB4oHd7IFCTnazw+d0dkFOsonb9wbNyZsC8f5zjkDT1QX2k+v2hGIusForxZl1D+SnJgP3pkcpC4DpxkwYbFDi6KOPBset8prG/tyaRecLBB/CFLoEuNsZDKCPkRNo3lJyi0+wFOs3zETFZwxKGKg56aSTYvFJziublGNyIEpBgLXyZaHNiF2N+Cw2TaCuPIejLPlnTh6kCxGyjTu6ZUIXQmV3RGXhJWWxjbLVNWbqWl1j92QJfRymVU9WWALFA8UDxQOz4oFCTmbF7XMrU686L04vNodA/cUp7K3mcKkev+MFoG0BvxQXcNF2vOqLhuKB7fBA0zMFgsPf+APkbYtze5QbHCBTF4smS0y97YqwEYzcBEUAf6ATabHTLvNEWnNv5MHqOJuAX3fddQD9WWedZXsPizfs3BUyAhgLYQPCiI2mUqC1dGygHzOxd5+s2dwqs00xcmyVj8jkgmoamzVv1u2YkOYnw5QFv7IZgIBtkS2tQcmmmq7WqrzEFA8UDxQP7DYPFHKy21w9dzPySvNe9/ZyjkNM9YJL23fqZjNlQoxjJ5aB/p2oragqHigeWJAemKqhQAn6+/tNuEIJtFF6T0y4wi7q8pqvaMe0XQQMXGjfeAkoJ4ktCIs3H0wMSRqsEHNEX4ytC22DbgnHJZdcYg8PO6HL6PLLLwfx0SE66Tc6QUzYQnNjLMIoQa6IbEwEfJWFwRa3YCmSOLLkzgqYtBbMx7BSOMRZSf20eMYuyXYQfve7320sCEuxU3yYwTyBbO3OMqboKR4oHige2D4PFHKyfX5bUKm8k7zAvDIFvJidHVFCP011sLzS661tj+CCckQpTPFA8cA88YDNcF//+tejCliBld+Yw4knnsj2jPgjEOBbz8uNN95ojTg4rk2zddV73vMeLRt5O3R94AMfgN3pMYzw/Oc/X+sXvCU8QYNpY4ZNbKourWEHW3r4GBRmotk0NGHwRJgG6/Kt4I8vGzZ5ESnCf/AoX4GMZSdNAjP/GSVqK2+XdjzK3C1t9Ute8hKfVDK4FJIKxQCHgJlpWJaNhjEZo0MGi1C1tgpLZPFA8UDxwKx4oJCTWXH73MrUW1mP2vve9z6vcNOp7fHv/cdErzGvYTMZvOqEvY/nlt3FmuKB4oE91QMgvjEKh6EA67wvvvhiFMJaCzg7N1/ZN7D4l770JcMFPnJiGcZznvMcU7PiquEUgJ42xAN2d6lp+IUY4mGgRjMYIF5j6EBgnCV0SKjxNAHM7sYCYsIGackIG4r50Y9+5FO2WEpczQLZyK0GJGGGsiA5dfqUE7pqTMYKeE26HiWsKbqcIi+WkJSQhhhTCoVitsOYnGkJFA8UDxQP7HQPFHKy0106/xR69fqEWUxO8KKK3jWvK4eOQK//eKvpJpx/ZSsWFw8UDyxED2iUEIwXvehFn/nMZ5ATAxrnnnuusQLblBu7cNWhBUMVDFb88Ic//N73vmcnLpd+53d+x3dm4fjwCqogFdqAVxhzMALjw0Q0Z/RPj6v0YyYmuOqvMeQC3IeAs0byqKOOsi5FZPAcO/bq4pFQFmzAfwxT0GwxusY28k3N6wymdZEJPc7Bu8wNY6rFNhhItNW5en010mE8BHtRZE23LYN9clHaKrdxtMRqk//4j//gE2nxMcXPJc16SqB4oHigeGB2PVDg5uz6f07k7tXlReVotSbi8wuyVaDEFA8UDxQP7CIPBKQOdN6aBWxt8hKkDoubdmWTXMzh+OOPN8YbrRm2gBhcffXV//Zv/+YrjYhBbKEL1mdEboTBYnpY35yoa6655uMf/7gREhwmBklkKvdzzjnHl08kQWnswGutC825wZSdNfT27TU8Qsyn2X3A0ddXyYf9lP/TP/0TAROokBYTzEJta7laY0hG84tFmHVmyQptxn8uvfRSo9xMdRWVMsmNpHESxqBexog4BB1iEnpGJvQYZVLG2FwYdcHKohRt85WkHMUDxQPFA7PigUJOZsXtuztTryavp85qIYlA2pGrYffMtB60imtjT/11VQ+3EZ0iyhvRq7F+kR4v7O3TVtdTwjviAXWvSzfdBv5vpO9DT3UP7EguJW3xwHZ4IGB0biIEcrhVm0v4yWmnneb8d3/3d5ZPfP/73/dZErc04cwNtEIGExxWsft6+gknnJCJBzHIHpcwNmJEAoGB+9/85jdHMxVZCxswcZgl5cvxRpjzqEuYhG/4rOFFF12EBckFyTGK8tGPflRyHEbupnKhT2gDYoMS/P3f/714ah2thYoYfsiuiAC+9M53vvMv//Iv4+sl8orZWZa/H3fccZ/61Kci4ROf+ESjJaeccopMLcVRHF+LF2ZM2IOrOMSQ9OX4TLGmsqTEFw8UDxQP7H4PFHKy+30+CzlCn7HEHRy94841l/3wqv+89oa3vvnlvd1d4xUy3RXw1Mvea9gONl6f3ovexDDBy172Mh17ei5nwQsly4qjBjO5+bf3/ujyq6+97sY3v+mUJb096QZAVXbFfVDcXjwwYw8EgNZiYBqWqmtDQHORUylw1dDHySef7CslhkfMm4qPJ8YWVTFuYMzBOpPTTz/dFz9Wr16tFQpuEDqjaTr11FNRF7vrWtRu8y6RULsmi358gwYLWiy413Y1feSEEpL0v/e977XuxWAFnuMTInKRlgFU4T+mivnMvNXzRjzsSowbKBqxeksoUtYi8RBnmqPgccaITB577Wtfa98wU7ZIIicOTCO254riyNc8rrPPPttsN3PJbMnFhkSDKiKk4LQpAj2IliU607s3dJZz8UDxQPHAbvZAISe72eGzn11HZ98d945d+bM7h0YNnjT03e2KnnPdeza3ueCCCyAMb3dvRG/HeGH7qfNy9h2xR1qQmAka0tG4/c4111x37813DG4aHV8Uo2odhZvskffEHCs0KH/mmWcaaoChLd4IaD6NjVoVkqZRGTGwqsQ8LsDdVxQFDFMY7jCbCwcw48t6DOFWhWLsDuwSPUgIxC+52VNaKjqtMDEy42zow7BJ26V3mIMdwGhAfkwzwxYkRzAkt1+WEuU5VHiOyVdIgoxMyqqXCzv6n//zf4pBTky4ql8SRoGUwrcmlcLuxigHJXG26CULK4vsrKtxFZVCgXiSWxijFNiRg1W+DY/O0dnqjayqBIoHigeKB2bLA2md3GzlXfLdrR4wkavqf1y7sXHOF3/82S9c+ul/+eOVS7t68ZMp+yW300Dv5m9/+9t209er513os2Veqzo1vSltJvPiF7/4jDPOgAPKe3E7/btjycYaDf8++6UfXHTFjQceevgbX/7EFX1dPdUEk519I+yYoSX1HukBryRzqJx1Z2ACbclAq2PIa20gcgErKzAE5EQjo+XBXjQ1mACFTW0OYaoiUhjWp0QAOTECg6XA8aA/RgHHsyTGH1pzjxjJjX6wgZL4xjyegIogLVEWGRFwyIJVFNbtkVyOLsnLVeemjFxySE4yXxJDkoU5JgJsiOJojXkDOWEGYmPdC2Pob/VGk4bys3igeKB4YLY8UEZOZsvzuzff9Ar2f4f/exc1lu+1pGvRqutvuOcRD967d2l3urDzzPGytBWM2Vy2hdFraCqFHXW84E26sGEOcmKmgZkP1q3WX8w7L/+iaToPqGt4bGBo/JpfXLt+/dDvPekx3YGBdu5NMJ0J5VrxwHQe0Czo469LaFK22lYQCBIiIRSuT0Qq+NshRnirCmlITKjak1B7ZSwlUoH+W809lMsrSAL70ZIwOxsQShjpqBuTwzIyAhOpcmRTgLbQML1JlIQYV7AEJ4mySEXD9Gmbciw/iweKB4oHdr8Hqv7S3Z9tyXE3ewD5mJy37e/qIw476tGP+qsP/+stt97BkMxMtnyDb6eJ3nwmVduUUy+g3keLNU1gMHjyxje+USeiF7BI1GU7tZdk2+sBlRv1q9v219duvOPOgQNXNh794CWLuhvdJnSVOV3b69iSbld7YIZgOosJaGfQjCAGzBMTR5gqnAM5XC+FhKGBkrYCdeEcrkuGhroBWWz6QF1Jk2Rcco5A09X6z7qAcC6LQP1SPUkJFw8UDxQPzB0PFHIyd+piN1mSyMmhS495wt433nzHZz73/SuvvmG46lUcN9fHkbrWd9QS+3W+7W1v89Wzz372s/axMe3bHAPDKeZwm/OgU9P60fKO3FEvb0v6VKVWm3Q0hoYbd949fvbnz9v/gAc887jfW9bX6K2YyU6p922xqMgWDxQPFA8UDxQPFA8UD7TxQJnW1cYpCzsKH125rOvIh+1z6qnHX/GTm8674D8bje7HHHko8Ko7EYqd7FXcfjeYRWBCV8z/NrtAd92tt97qCwCWZpowbW2ouV6FnGy/f7cxZfBN3HNwqHHTLfd96bxLr7/1jucf/7sPf9jhXR1pR4TUjZyHz7ZReREvHigeKB4oHigeKB4oHtiJHijkZCc6cx6oAkGtsuzobBy47/JTXvqMDSOX/eLXN4yOXNHVOfzQhxzWaw5DVYgdRKomMzjy5Gl7xVxxxRWxRyfSYpcYH6SfB86a/ybGGJiz9bP33LfxxpvvvfKn1178o58c9fjHPvxhh6xcubiMnM7/Si4lKB4oHigeKB4oHlhQHijkZEFV5/SFQTliy67O8Q67M+2zsvHKU5909mc3fudbl9xy62/+vzNOPWDflYv6LJDuTARmel0zu4qfWHlia3+r4VEUiZ7whN+1PaixlExdZqapSG2bByZoyXiiJRaZrNkw/OMrf/PdC3980y23HnvsU571rN89cN+l3agJuZ1S09tmXZEuHigeKB4oHigeKB4oHmjvgbKVcHu/LOzYtDZab3pHY3C4ccf9A1f9/JYvn/eTW278rxc+7xnHPfWRRxy2PK2QrrmgojT1iC2uZsEJoBu4eFL8G1//xrnnfvGSH/zAgpP+/tVvfvObnv70p++114pIVZOdSJ21LaRAU9mafraUdGvXWxOo0Q5bsVlUMuF3Kszjch4cbfz2vk0f++Ql11x9zcMeuP/xxx195CMPXrXXor6eDqtNSudEiy9LRPFA8UDxQPFA8UDxwGx6oJCT2fT+LOad+ElHY3S8sWmsceeaTb+67u4bf3Pvr37+68bohoc9+MBjnvC4/tUr+/rSLC//rEyY5BqbTW6NmcDU/jg6GlaYfO2rX/fBk59f/XMfLnjggx70ilf+dyMn1pzYCycUTcr6BUsv2ElGE56JMm99uCK8UjlxMsk0f7N0yPg5UlXuwGDjiit/cdnlv7z13uH7N656zJF7P+7IAx502H77rFzU25k+brOzxsemsa1cKh4oHigeKB4oHigeKB7YJg8UcrJN7lpQwlBsArI618d8+KKxdm3jsh9c/tOfX792/cj++x5w2Oq99t9v5RGr93vQ4SsXVUQk2EiGwn628pPkoEri1ttuu/DCC7/yla/e+Jvf9PX1PuLhjzj2uGP9W7VqpaXwPpVmZteW3pQs59Be8Zbyc/xXLk6yc4sfLT+3LAlZ/xzhhK27IicIPfetHbz25vuuveXedesHfvVf19973/0PXH34oYf2P+7RBx+y/5JFPQ3MJNOSrWsPpeVcPFA8UDxQPFA8UDxQPLBbPFDIyW5x81zNJHCtZQljFieMpVle/3XdPZdcfsNlP7lW73tP3+LHHLn/044+cFnn6IqVK1etXLZkUV/acLiCtE5BL1oB7n333XfBBd8766yPDmzc2NvXe9ihhxz9+MejJl096aMBvlvsU2WPfOQj2m3YNYHL/WlVO1e92Mau+gyrNpeni1J0Plb6cMB0biDnn0Gw4ZHRtWsG1q9fO7Rp429uXXfpT+/58a/u7+vbtO9+ix736P4Tjnvcku4GWtLTlQanMjMJK6bLYDo7y7XigeKB4oHigeKB4oHigZ3vgUJOdr5P54XGvB4dtE2Hj2DgJx2NTSONDUZRBhv3rm3869nf+f73f9Q3fNfyzrXH/8Gzn/WsJz3kIYfY6UsKn/Lq8UHlarpXK7o977xv/r//d/YPfnDpIQcf1NnVPTIyPLhpyP/3r1s7PDI2Mjr8u7/7+K99+YudXZ2ReZV/ZUZ1mrRoc8weFuIA//h1wrXZS/wgKi4nTjI+PjI6Pjrecc896y688Bc//OFFv7n2V2s3ji3d/5GP/73nPfuZqw84cDFOsrKnscRoiXlck9PzcpVFNnuYe0txiweKB4oHigeKB4oH5q4HyoLYuVs3u8ayCTiaRy02f9UEeB1vLOpqdC9qLO5trFzceOPLnvDfT3zUwPqB31x7x0WXXfPjv/lOz6LlXX19K1atfPyjDjjmqAMe0r9XfZlIQF4ZDA6NbNg4tHbD0D33bhgDoEdGRoHosbGRke7RsbFNm4Y2DAylEZiq49857RqVVnRXUZWBE8EJ5pQ+8OwaQuWcLa+kZ/lU43jJNkc2L5do4kJcniQc9UhhxUsxlRPGx+lIBU7FrRyxhfB4Y6yjMTAwfuttAxde9strrr/39rvXbli/bnDTpsc87MFvfPYzDj1k30bPoqUr9lq5qre3N3393cL3nmRYUhYZTSoO9ZOWlb/FA8UDxQPFA8UDxQPFA7PtgTJyMts1sLvzD6BbYd6WrOOaWV4CJnoNj6W5XsPDY3ffs/Hnv7rlvrVD963ruvXOzvvWbewcvPkBy9bsv3Kko7NzUd+ifffdf7/9DnRetXLFqlXdN9108y9/dd1dd91jTpflJemgskLVfo6Mju6z94oXnPjMDouyJw9bTU2Qk2reUeY8Gf1PCk7+zfh6MmJu/U3FTVQgebL6l4ua4mvG87OdCVJ504XkhPGxtFo9PGDHgjVrx///9t4DSLKrvNu/qePkmZ2N2tUGrXallVZZQkIBEFgYW2AbbOOvjI1xAEdcNrbLVXaVbcouyjl8lP8FOKc/DjiUCcKAhUhCQgLlLK3i5t3ZCT0dbviec8/03Z7ZqN2dnu7p32XUc8MJ73luL3V+877vOUcmKwcOHti7d3dl5sjE4f2VSrVaCyqzhRf2x6XRTatWD42NRPnA2bp+ePv5K8ZGy/TreWY3m0yQLAjAa+nfdKpDBERABERABERABDqEgMRJh7yItplxinlpOkOeMyZTKeSfVOskNjhHpp0Xdke79x165fnHZg8/74TTtcjdf3AKb0rf4IrBQUQHE+XA97wwZnbtJZ7neoHrB67nu76PGkmVSpLPJeNjxXQ+nhSCoFwueC4VmKfzyBsdKPYXXT8TKC1s5sxLB5FN91uet+nUmmENaD0/2n0qTmr1pBomlXo0NVM1NBJ3tt6YrdY5QYbwWQ+jymwtAhOSBOcSugS/CC1GYRI3WDcAcTJxxJ2YnNl/eP+BQ/uCeLq/nBTMTjSFfK4/3z++8cJLN24eXz0OWaecc/rId09zSujAGoZJ1k77aS3kUevlUbN1JgIiIAIiIAIiIAJLSkDiZEnxd1jnC+bZXPJjUq7tD66P2CEei884Yq5tPo/MRl++97Gnd+1/6ZUje/fPhMy064gazwtyrp+bjfNeruQHBdfPu17R5KvgOnHqpXyyZuVAHDdofrC/sHpFOedVXbw1cTxYDC48f2jVaEL29lx4E5rG83O5PGn0xWIxF3jGx9IyuZ5/tehMMxrGjHQhgTqSY3a2Xq/FoEnMKNL/0HLx5Kx74EjjpT2TseNHsXd4cvbARMVxCgmukdibmmnsP1QJk5xBGYduwn6JEQ/cuOKGVTeuxy6aznfzXqEvGB0pb1pbfsMNl2xez6pbxGoZl4sfOF6QekhMiyaIq8UdNQ9FC7B593UhAiIgAiIgAiIgAp1DQOKkc97F0lvCtJvDzmLTeCpzZW9ylsZmGa2SHdypxsl0I67UklrdqTcSNn73kC6p36ARuc++7E7Pmm03KjVnz95otlYl8cSJ67OVyV3PP8uSwm4S12anJ4/siRuTbsIEPfbiai46mIsPBF7MvDwI8oXyYHlofNPGLTsv2XnFZZdu2NDHLilYhZ2oHWbk2fJTizH/th0dHXK6+LKN1EKe4eqYqTiPPfnC1+7+xhOPPzIzOcFwqrPTlekpo9GCkuP3h+5AzS2niwjkC30DA4Nj+dKgm5CdnhscHFm5ak3sFt24sWZl3/iKshmY46wac8aHknLJDBIJhF5Bc6BDWHRrpByUWHfLZeipbkwDwBi4TVCxBNLLuYA4o6CMhmpVc+aODhEQAREQAREQARHoQAISJx34UjrXJOa46eT5qIUIjwYulNSpgtuAg8kwgsZM3xNnumo8LcQmGZdL3XgUrE+BeKV6dYbCxs3QiOKw7iRsuJJOsZPYT0I/mWVWTsWZamPXS4dfOFDZu3dqerLhx/lyud8PyqW+YNXq0qU71t9w9ZqhcmB2i8R1kK45ZixMrSRYikR83C8eZxzpNN2cnPhgRh9GccAeLM3CtNQ8NdUY1Iv74wee2PfAIy/ueWV3fbrSQJ7V6rO12aFScum29RvXj68YLufzJkSLjhM3iF30mhFQRmgEQYDrJ2AhClp1OcsVjQQhqo0tLws5FIuRWwWis3KOsSLtGw+JMYMN3clu9+bcIzzhZmZeWnD+wLJn82/rSgREQAREQAREQAQ6loDESce+mg41jBnvggMPAYf5y33zQJzY+TRTeZu40nySFptf0goJ5tZ2ts0ls3OECR8hSRq1xisHp/ZMzO7bN3Xk4PTsdBg7uanp/MGJ2emZiVxu+sLzg6FSPD46dP7551+0dUuuYBqiKdQAWiWOCIxCI6RT9/TjqCXp2fx7aI8EsZGjQqoHMAKVxXAqM/Hzz+9+9NEHp2eOvHyo8OKhQjUsrxkdWDHUcAMnCZxCMVgxWNy4bsXaFUPDgwWzB3tTG/Dbjtg4oeiPlhf0yr3UQ2IG3vwx1qUD4betnt6YWw7YNtB635TXIQIiIAIiIAIiIAJdTkDipMtfYAeYn02Rj7WFR6k35dgnR++kTg0zKV9w2Lo4T+omeMwJw9S5QuRX4hyYcF58afLp51549tnHG9XDtenJfC6/dvX6y3de0jfo9Q+Wx1f0r1vV7+O7SHMwjpuGYVRH2qX9pFl72N9UrDacA5P1Z1/cX69WJw+HTz3x3MMP3r1yRbHmDBSGN2zcdOEVl164YTXZNCbsivIFz7g1CqzFzKYi6aj4aB3+gssF47WXlDkWRWvJkz9tLalzERABERABERABEeg6AhInXffKusng5oT/1DYfO+emrqlOSJhrslY4KMMPKoKfRuSE6Q8em6ef2f/Vrz/5la88/vLLs/m+3HkbV99y46a33Lql7PvlUo5YKdRCKhaOmkF7eEWsErBdsxYZh43/Yk2tsF7fOxHf++jE//cPX5qZPOxH0cqR3HU71/z4u9+CWyShQd8pBKkIwT+DmcmcT4M2s70Oj/b3as6ORfFqaqusCIiACIiACIiACHQxAYmTLn553Ws6U3lcDad5zKmUrHQqV2jBOCXSz+lqPDVdPzLVqFWSp16Iv3zPg48/9VB/fva6K7bf9sbXbNm8oq9kdiFcsOFoq+eELozmSTVGtRbdc8+Td9511/2PPH+wOji67pIfeecVa8cHSr4z2uevWVn2XdfGZaFkkCLWEjscI4EYGiLqtEeXDUsnIiACIiACIiACIiACEif6DnQfgdSPkpqdOCGLWZHZgheFVXxD59BU8sq+gwcOHzp4eOrzdz0RBN7mjauvvWLzTddsKLHwbpraYQdMI3MKIlU7OGcmJpNHHz/w2c994/kXnrvwwjXnbVg1MDw0MDx20daxgUKOZHRWNy7aVPYmM9tCZo+9bBEm9knLjWZF/RYBERABERABERABETiWgMTJsUx0p2MJzJ/rp1c4MQjQsgdODCNUWBkscQ5N1z5z56N7903s3V9FUFyzffjW668YX1HM541bo1UuUIuQrocf2/XQo/ufemZm99762rWNG264aNvWdYMDBULCCN8ia4WFg/lc4BKx7VhDjucvmW9w0079FgEREAEREAEREAEROC4BiZPjYtHNDiRgJ/oY1lQW3EhPswc845zoLORKlWWIQ6dRd+6+55nP/c+DB14+8H23v2H79pF168ojw0Wz9HBam/K1WuOpXbv//dNffXbXwfGR9Tdc/9rLrxgZGvRYzDeXOltMsFZauNlxej3vw5pw7PMT3Z9XWRciIAIiIAIiIAIiIAKWgMSJvgnLhIDVAXYwiBN+iNQyCSGRc+hQ8s1vVv/vh/9748bS7W/d/rrXbe5ntWAqsKpvnLz8yt6f+eU/O1hz/s873vz277ipv2A2GLE7nSBLWlf6OlZ8nCk7ky+THjR57lptNqrfIiACIiACIiACItClBCROuvTFyezjEEjlhrnPCT8m3AtxQpRXwzkyGX/jm0f+/T//t+5Mffu37fzu77yiyE4ojnP31x/6849+YnBszRvffP1ll25aO9KfJ4IrXRqYp5l0oDV7mf4++w+Jk7NnqBZEQAREQAREQASWIYEFKxgtwxFqSL1DIPNB2BOjPjhj+5G8MzbiXXXZSBhe8cWvPfW/X3xlx7ZLt270773vgTu+cF9hcPStb7354u0bxobLpLybfxJp/ay15o1zCDJrOzs5h42rKREQAREQAREQARHoVgISJ9365mT3yQnYWb/xpeAJQaEEzsox56YbNkVO/o7PP/eZzz4Wvn79l+5++sW9U7d/5y1XX7G1XPTZQpFclLbIhbZ0cnJAeioCIiACIiACIiACnUdA4qTz3oksOkcErAJAmbCNI59Bzhkddq65al2lmvvj//v/N6Ib9xx0L96+9fU3X2E2QnGNz0Si4RyxVzMiIAIiIAIiIAIicCYEmLPpEIHlSYB8eDswz7G7JhovyppxZ+dFTqHofurOR0aGN9xyww2DeaeIMmkuE0yduWrLk4pGJQIiIAIiIAIiIAKdS0DipHPfjSw7OwJWZdiFhfk0ioOvu5s45WLp+usui9z+tecNXrB5gMx4HCYsDSG3ydkBV20REAEREAEREAEROFsCEidnS1D1O5gAcgPJYX6skVZ+FIulSy7ePjg8Uh4o9vUFZm0uG9AlfdLB71KmiYAIiIAIiIAI9AIBiZNeeMu9OUarOKweQX6YEzTK1HRt997JydmGky/seunws8/t4W5WiDK2Wm8i06hFQAREQAREQAREYGkJKCF+afmr98UmcFRrcNZInBdfnrrjC0995msvVPw1//6pJ/3pFy77hbe66Z4nc6ZYL8ucXlls89S+CIiACIiACIiACIjAUQLynBxlobPlSIAcE/aCN9vB84M4mXWLs96KqjNQ7B/xcyWS5j2UiZEwTRnT/L0caWhMIiACIiACIiACItDRBOQ56ejXI+POmID1f6SfxgmSXYZOvuYNRrlBJ1d0czmXDVAWHpQ1VXSIgAiIgAiIgAiIgAi0mYA8J20Gru7aR8AKEhbqamoTI1FqkVepB0lQdFw/dtyIZYbbZ5F6EgEREAEREAEREAEROBkBiZOT0dGzbifQqkzMWFynEcdTtchxg9j1oiSJ4hhxMl+fyG3S7a9d9ouACIiACIiACHQrAYmTbn1zsvv0CMyTHmgVvCWJ6/HpJBxOlLjR6TWkUiIgAiIgAiIgAiIgAotNQOJksQmr/SUkME+ZYIdJejf6xBwu+5uYbRmT1pW60if6EAEREAEREAEREAERWBoCEidLw129toXA/HCt+V2iU+zmJ/Nv60oEREAEREAEREAERGDJCEicLBl6ddw2AnFLUglJJo1GuKBrZZksAKJLERABERABERABEVgSAhInS4JdnS4ZgSgMZ2t1uk+9KidzrSyZiepYBERABERABERABHqVgMRJr755jdsQmEtKkUbR10EEREAEREAEREAEOoGAxEknvAXZsFgEsu93uk6X7cX1SDbxyI03iwhzX8pkseirXREQAREQAREQARF4lQSyydurrKfiItDxBNJ8d6TI3GFFiFEmjucnNs3E3IuVcdJEpN8iIAIiIAIiIAIisLQEspnb0pqh3kXgHBNIFYddOhgFMucd4VcYJ2GDvvjm8yNdco6xqzkREAEREAEREAEROBsCEidnQ091O5pAU3kkbGaCPvFSkVKvxzMzkevmUnFyBvbbXVLOoKKqiIAIiIAIiIAIiIAInIJAcIrneiwC3UygqU8clMmc98RxYyfdId6Mi+dZkW4ep2wXAREQAREQAREQgWVBQJ6TZfEaNYjjEkjliBEfCRLEhHiRaYLjI+TUXLFHvM//zPOj0uW4DbXe1D+ZVho6FwEREAEREAEREIFzSUAzrXNJU211IgGiuhw3Deky1tnluVAp3HE5yDzJlAkn6U8njkI2iYAIiIAIiIAIiEAPEFBYVw+85J4eIkFcKBPjQ4kSJzJOFJJNjNskQYi4nusFRrcY94p5xD3jZDFXLUd6s+VapyIgAiIgAiIgAiIgAotCQOJkUbCq0aUlECdJGEVGaThOPXbCJMl5bj1yZ4jpityC79aN08QtFEu5fK4RRqiVsGX1rtS7kiBc/DToy8gW5MtCybK0Q1TvIiACIiACIiACIrAMCaR/P16G49KQepQA/hBUx2OPP/vxT3z2uZcmnCAfuh4+kyAIfCef9G3YO7v6hcND5VIh5/rRzK4Ng/uv3JqvViv8SwjIQUGOeG4SzTSqR6696qLb3nij8bLoEAEREAEREAEREAERaAsBeU7aglmdtJdAX//IqvWXf/rr9yX5glMoJJ6f8wJ+wqly1SsEuSJLCRPu5eRHDtSSe5+abYQlE9vlEublu24UVqZWj8aXxD4bohTaa7l6EwEREAEREAEREIFeJiBx0stvfxmOHYHBqIbHRi657NL4vw8khb5834CTy/skmsRuFOcTty8flGKTEZ+4wVA9yR2oV9kk3rhc0jCwJA6nJ/ZdedXGdRvX2xwV+U6W4RdFQxIBERABERABEehIAhInHflaZNQZEbAxXVQtFp2xlT7+k6moFPlDXq4PP0lYj1lE2PVyvhcYcRLHiVOMXBLi+0OjTexB0nxjNipefNGWCzafd0ZWqJIIiIAIiIAIiIAIiMAZEtBSwmcITtU6kIB1m2AY7pNyMbj2yi2Bx37wVSf2oyQIvZzj51AncRSjTNiW0TNJ7n7MfidEc3l5dEtswrrc1SP9w+WgFDg5pcF34GuWSSIgAiIgAiIgAsuXgMTJ8n23PTwyNEdfyX/jzWPjo7E5nKAR4RIhsIsnrpElaQTXHKGEDeP9JPEI7Ko3qlOVQ7fdesWGNeMoE7+HGWroIiACIiACIiACItB+AhIn7WeuHttBoJhzL9yUGxuMwrA2M1sPWV0YQWJSTbIUEnPd/AeAPmFRrygKpz3nyGU7hlaMFLJy7TBXfYiACIiACIiACIiACKRbOwiDCCw3AkiOwHNG+521q/v7yjm0CRFchGhxv/mDLDE/c/rEKBYvCuu5ZHrNcGPdKqLCtK/JcvtWaDwiIAIiIAIiIAKdT6D5h+POt1QWisCrIUBEFqsA79y2fvP6cdJIfB+1Yr7tsZvEjv1xyJLHYULaCff5FTcqffnKVRcNDpW8HKXZQf7V9KiyIiACIiACIiACIiACZ0lA4uQsAap6JxIwfpBUc+y8eHDdSmffgYnKzCyKhIQTlEnoJnXP/DRYsouEeMfsA5/EjaQ2sXll/J537BztK7D3YroocSeOTjaJgAiIgAiIgAiIwHIloKWEl+ub7fVxWdk9NOCN9CVFt+E7keewdrBZoMus1YWfhCgv/sd1gjghX75eCMKVQ+66kXy/79h/GPKc9PrXSOMXAREQAREQARFoLwF5TtrLW721hQCiwuqKvpyzcW3/pZsHnaiCHskCuoxj5eiKXWSeRJXq1PhIYcuG1ezXaKtLmbTlXakTERABERABERABEThKQOLkKAudLT8CBc+5ePPQay8biaqHk4S0eBPaZZRJ+sGlyxLCTuS6jUp1Yv26/h3b1yeR8bCYpb10iIAIiIAIiIAIiIAItJeAxEl7eau39hJAY5y/1rlsW6NhxEk013l81CmSkITihL5TK/rVC873t23tc8LUc3K0SHstVm8iIAIiIAIiIAIi0MMElHPSwy9/eQ89dX2wDpcX8RPl3CreELZZtFsxsqcJqwenqwnHpKM48dR5K53xEb+Yd/KONoZf3t8MjU4EREAEREAERKBzCchz0rnvRpadJYE4ThDf/Xln/Xj/jddsi8NGGEWeWZrL9fzA9zjcnOe6SThxaPe1l6y8cOMKdoVnEWGFdJ0leVUXAREQAREQAREQgTMjIHFyZtxUqxsIsDiX6xR8Z+2q8htvXk/sFvrEJaGEw+Obb1RKksRR2HDqkzsvGNy0pj/Ho/S59Ek3vGDZKAIiIAIiIAIisNwISJwstzeq8VgC5Iz4Zp1gJ0yc8oB3xc5CX9AI69UoqscmvotdT9woimu1RtyorR7Kr1vhjpYdI05IQmH7RakTfZNEQAREQAREQAREoO0EJE7ajlwdtoUAC26hMIwOSXdjDFxnuBwH0UxYnU3wlcQRGqQWhjP1mTCpXLBpbLRcQJmwvDA+FeNWUUJ8W16TOhEBERABERABERCBVgISJ600dL58CLhs8J4KDD74Kef8t73pgs3rAj+uFAO/YFJPvMBPomQ6CSZuv33b2Hgf5VyzSaMWEl4+XwONRAREQAREQAREoLsISJx01/uStadPIA3MQm+wKpfr5H33qp19Y/0zjdp0Hl3CYl3ky8c136sM9zc2rOsvF3GumINVvBTSdfqUVVIEREAEREAEREAEziEBLSV8DmGqqc4hgL4wP2gTVhPmjDW41q1yRgYavktQV8P1SYV3wtrUULF+6QXD5aJrFvHSIQIiIAIiIAIiIAIisKQENCNbUvzqfDEJJGS1m8R2JIpxnpR85/zzRleOlianZ5w4CpIomp1cP+x+22u2DJc8mz2fuk3SOotpmNoWAREQAREQAREQARE4LgGJk+Ni0c3lQcAoE+M9cR38JxxXXbbliovX16uNRr1e8N2c01g9HF964UDJ8wInMXsymvx5HSIgAiIgAiIgAiIgAktDQGFdS8NdvbaBAKqEXtDfLMzFJz/nrQlWjbmVSmPlmD8zMz02EGxYXR4peXnX4V9CmnNiE0/Mp2RKG94RXVji7elLvYiACIiACIiACHQ4AXlOOvwFybyzIcDXG69JutuiY+THQNlZMRysGshFtanp6YNbNw5dum1Ngfz4dIpMyeznbHpVXREQAREQAREQAREQgTMjIHFyZtxUq8MJZCqDEyM5+KIT2cVOJhtWFq++uDQ9+XyjfvDCLQPbt67kkRUnHT4kmScCIiACIiACIiACy56AxMmyf8U9O8CF+oQ4LcTJ9i2lt9xSmJl8Yqg8tWI0Gho0ufLppvDzQLVW1vmiEpjHXRciIAIiIAIiIAK9TUDipLfffy+N3m54MlxyVo9UG5NPXba5vG6sZDc3keekl74IGqsIiIAIiIAIiEDnElBCfOe+G1l2rgjwh397IEIKvjNccC9a7XzHjeu2rR8qskVjGtaVBn81y+m3CIiACIiACIiACIjAUhCQOFkK6uqzjQQyZcL6W77jIkVWDJS+6w2XX3/xmjXDZlv4lgJtNEtdiYAIiIAIiIAIiIAIHEOAfbK1YuoxVNp8Q29gMYBnmuMoXlJLuOvWavU9e/avWj1eKLCGcHrYX7ZkVnExrFKbIiACIiACIiACIiACJyYgcXJiNu15YifEfGpOvNjAIQznhH0ZEydOHN8zywwbcZ44Hhswpk/5ZTaI19FGAsabpUMEREAEREAEREAEDAGJk6X7Htg5MLNk5sd2Zhzzp30di0/AChKkiVEn6ZHpkeaNVLQsviW90kPG1w64SZnfdpkCxKF9F80nvQJG4xQBERABERABEZhPQDkn83m07cqqkfRP+FPPPj/x1LMzExNBFCMW50zgL/j2T/marp3zl4IYNNNipHkGt4n9qAMru3POu+/BBlvXaoa5B9zYdZLAL5TLqy+7pLh6pVMsHGXfg4Q0ZBEQAREQAREQgZSAxMkSfRGYHzfC+qHDh17ZM3HfA0e+9VB1/4FinLixmaHZMBdO7ATZ+lM0WT5XryoDe64aVDsnJ4AMmV/AjZMkcp0wH+T6+6Mj030XbS2vXzuwatxl0xmO9IPfVGuezm9AVyIgAiIgAiIgAsuUgMK6luLFMucKo8bBiT1fu+fhO/7H2XNw1A/6/aCPtaSI8kqP1jD8OXHSemsprFafInBmBJDcCw6yfELXqTpxNQx3J1Gwcd36115/4Ztel+svkwuUKRKJkwXcdCkCIiACIiACy56APCdL8YqJ3Zo4Unv4kcf+5T/KtfpQvtgX5PKOlyOUyyfexZjU+gfjJM3WXgpD1acInAsCfKubB99uq7K5FzhJyc95UePIy/sPfvlrzzjxlrfcmiuXs69/67+CZgP6LQIiIAIiIAIisJwJSJy09e0mBG4x4YqTvbteeOoznxucrg4UisUgyKWqhCdmpahjZmTHvdlWu9WZCJwtAb7Fcx6UhFyfZE5x+6474Ae5OJrYd+CZu7++8XU35golB+Fi/hUc8y/hbG1QfREQAREQAREQgU4nIHHS1jdkgu9JBJ6tTr+yZ++TT18U9PGX48AsVOSaHGGC7E88H5uL92qrvepMBM4hgbmvML/SM7uEcJJ3Pd93Z+vV6u59Bx55fOXF2/Ojg83grhP/eziHdqkpERABERABERCBjiEgcdLeV8FcK06q+w/W9uz1a2GxlPfTFGBuM107yUSMp4gaHSLQtQRSPZJZn36ZbQAjp2SZFINcXxTt+uLXyqOjo4N9jp9m0dv1hbNaOhEBERABERABEVjuBJRk3cY3bKdnsXNg14tHdr3UXyj5HhsBGgOs9pg/fTtqmH169FpnIrC8CLAdZsHP9bn+i/c/WDl42Ini1LciOb68XrNGIwIiIAIiIAKnQUCek9OAdA6L4P5gM5PpSjBTLbtBc1kiu5iRe3LfyImkyzm0bjk1pYltR71Nvr3NN2JObRCj/cKb+0mSc51S4kcHp5JKPYnMmto4T1pqddRoZIwIiIAIiIAIiMBiEZA4WSyyx23XTLYSNwijQhjz1+J0wsY9HWdIoDnftTkMZ9jIcaqR+tOyN4eZI3PM/ZpX3GMWnU6u7V1NpufRmX9xIjhWqCDU854X1CI3jN1Q/yjms9OVCIiACIiACPQMAYV1tfVVp5PpOIiTfJL4Jvl9btqbqpRTWJJNxE9Rbjk+ZuzZ8LN5q73J1Jaf7Kkd/dylWRrNlspO5uik9+eTarZjHrHfTIwWYcIcpLf5Z4JYWdgJysR1PD99lLB7Jv4AlqEyPaYvNjO02c+C+s3bPfHbvoZsqLBsxZk+Ncto+xCMielij9Jj8GWVdSICIiACIiACIrB8Cchz0t53a7wlZhFVj/x2prLzZmintqRnZ7egYtLKdNX+4gQUzGWNaEjXfEKftATF2Xkt0sI4O9KJLkFCVDX8uMevY8WJlek20K6ROA2T9cAyUqZh21FTx9vOzctCmZhePdbFjcI48X2vHtVZG5dcbh9jA+paS+bemxUuLXae+o0vxxKGhuXSOjrzUswbitKHxz5vLatzERABERABERCBZUtA4mRJXi0TVKZfNtVkSQzopk79dKZqPhABUcy24rUw8uKk6Holz/VzBZcDoTJPn5gBokAacdQIo1oYRknkBV7B83OsQuAidGJTaU418Af7OSCIoDhJ2LZ8NvHqtXoUh6VSMUiikuvliMNLy9uynPIW3SSmUCNJGm4SshhuZbbg+/25wKczx43wpzR1EObZ3o61c67vnv9lvClymPT810AAREAEREAEepyAxEmPfwG6afjE+/B39fLK8aFV43l29Nt3YPqZXb6fN8vOzj+snEHL1KPQKRVHxtcNrVpRqVQOPf/87NTMQKHgmZTspiLJ6iJa4rjRCBvF4vD5G/xyX9So9xXzLz/yWKNaC/yckUcY4aGMjLAJPBeRNFOvx6ViaWxkdHQEd0seHXTgUOWl3Xmvj7XY6EMaNAN8ypOFL/KUFVRABERABERABERgeRGQOFle73OZjiYNiPKSOCTwZ3jb1sLWLV4hX33imcOPP1085m/tmeZAQVSTaGDFyMiO7eXNG/ON2v6ZyfqRI/1OISvTCiyN/cLZkfhD/QOXbC+vW4vnhFWk9uzdHb2yD1mCz8UkldjUeMQN4iSJZ6NGac36FddeVRwdJmjMr4czDz/WeHpXvlw2vhKKmxqmH9tpa65Fa+86FwEREAEREAEREAERkDjRd6CTCdi/pJMugpHGrRF7Xv/KVf6WDU6prz4zG9brJhslGwGnJqXECAgOPqtx3N9Xyq1d5WzZkHfi+t1fnY2jmPSRmLSfuQMfii1MDZQJeiMpFfwNa4rbLuBO0qiP7ry4MlON9h/Kl4smfMx4TUxMF11zzDpxed3K4WsudYo8dZ3ZerLvQFirNyOUTE4MsofyxlmTxvM1e9ZvERABERABERABERCBeQQkTubh0EVnETCyAaVh5YDRDVFUT+KGk88lhYAZf6NmxEnTZiRDOvdPU96NG8Rz2DJjOm7MelGulHeixqxrtIRZWKtZB8Fgz61soLUwCmfCelTwnH5ixxw39NbefMPuF/dMvfCSVyigMljKwK4DTWHkUpTPxcNlZ3zQiCEP907E7UajYVLvM9PS7tAnOkRABERABERABERABE5CIPvz8UnK6JEILCUB46M42r9ZHYskExbScvzWb2+qTEwxSh8VaiC2OgAAM51JREFUAZHrNPihCmtn+aSIoDXM/n5mxbQ0h/5o0bQL2xGZJBHejrDuNOpOuZQMDUaFArn4+FVMN+gZk3TChTtdrRVXjPSNDqF8nNlp5JJZIWzOc3PUaJ2JgAiIgAiIgAiIgAicDoHW6d3plFcZEWgjASsFjAwwYVH2mHOVpJdoiRbdMlcgXQ64WTq9Z+vakK+5Qsf7ZZtCuiBpWCWYhJPG9LRz4BBaozg8nB8eqtRqrsfywh5d4MapNBoTjfrKHRev2rq1Uq899OADlXrdSCa7XPHxutA9ERABERABERABERCBkxCQODkJHD1acgJz6qNFgbSczll37J00L6Rpe9OPYjJFOD9O6WZJ+3uuAKksiVOdnnn4S1+tTk71b9xQ2Lp5ql5lCxRTgGWLY6fuebNBrrhmdXlktDFT3fPiS2HYsA/nNzl3RcVT9n7ciropAiIgAiIgAiIgAj1CQOKkR1708hlmOr9vdYyYKK3mz9wwzfbuxF/xZO5o+lma16fz2wtys5XaVz7xyanDk8XNG7xtmw/XavVG1CDRhKR5NjbBjTI65PaTml+pvPCih18FyUI82Fyuie2+1dS5/JbT6V1lREAEREAEREAERKAHCUic9OBL764hH8fZkO71bib9bCjeMvc3uSBmTa80qYT7/KTfb3t6uqM2+8HTUpB38sV6Ldn91QfC2aozPFAbHTwUsS8juSeR63t0fKQxO7Bxfb5Ymnj8md2f/9KYlwvYh4WgLlJc5nwknBw95l0cva0zERABERABERABERCBOQISJ/oqdBeBV6c0FozNiJcFt1ou5zedkHSSazRWVMOgWiUFvzQ2NLrxfALDIvaQd5wwiStOfOFtb2C7xsrBicknnxkrlH0jl3CrHHXZtDSvUxEQAREQAREQAREQgVMQkDg5BSA97jwCJ9EX58BYE5hFaorZ8iTOxfFKst4ffKiyb9/QmjVbb7mpVsd3EjbqdU6ccqG0eoVfKjqN0J+slr2c5+B3ma9xzoFFakIEREAEREAEREAEeoWAxEmvvGmN81URSCPHksB1xovB4Ucfm9m3vzQ0tGL7NnZBYUnhWqMR+e7o6lVeITe7f19jz958mC4xnKa6zEWTvar+VFgEREAEREAEREAERECzKH0HROC4BMh1J3nET5zhcnly377ZqSk2WHT6yn6xwL6PlSjy+gfO23FxEAQHH3108sknWV84MfFeaYaM9jk5LlPdFAEREAEREAEREIFTEZDn5FSE9LzHCPBPwiTER7ETmWWDEy+oTE41ZipOGPm53OjatXXHOTxbj0fHNtx0Y9BXevnFl/bv21voL/q5wMn5Jge/uXpxj5HTcEVABERABERABETgbAlInJwtQdXvUgJZasjx/BzZQxRKkveDVx5+9PkHHgqK5dW33TozMjTJppDFousGbBHPCsIekV5mZ3h7LG5KTJfSltkiIAIiIAIiIAIicDoEJE5Oh5LKdAyB+WFTZmNFMtDtzdTjgdODn1MeLNtli1HXCBE+05O0YqpMXNo2zRPMNVAsVXbtPvjMC26hULhk65GhvnB8uLxmVRwlk/c/nNs/UfAD0wD16Po0ej+leSogAiIgAiIgAiIgAr1JIOjNYWvU3UggFQ3oBasAjAhoFQLZeZrL3nx4VHKYwraFTJFbVWNRWGWRnlOQ/eFNaZflt9xkKF+sTEw39h9G0CTjI5X+Qt/ghpUXbU2i6NA993v7D5W9wO6oYpvSpwiIgAiIgAiIgAiIwJkRkDg5M26q1TYCJoeDzoyjw6SbN3/Yoz2JwtiphWHsBQgSk4xuhItVFUYseGyHSE1Tm9yR2I3Ym4QdFONGHDnslmicHab0XBF2TjQrCFPa6BSaM/dpgR1OPK+/Vs1NTTWmJnODK3JjQ+PnbVi1Y1t46Mj0cy94UzN5qs41ZZpo2pk2rQ8REAEREAEREAEREIHTJiBxctqoVHAJCJg5f+oqMX2jHKIw5MNBWzTq4Uzl8NRUzXVyhSIygs1HzNbsQc4oCs/ry/v9+RwlAzfxjdyInekjqIvpI0cO1xIvRKvEHjfT7HWEiJ83Ry4I/MDIoVSboHBo0g8ajZHAr+3bs+vLd21++9uuu/nGYl9/wkpetYpTm8nFjRzSyPMCs8IXdVN1FBl1M2e6kTk6REAEREAEREAEREAETk1A4uTUjFRiCQlYzwYGmI0RXVLQUwdHFDql8sAFmy5/37u9XM7z86ZAFPHc5IikgiKp1Q9+6o44xluSbtkeeMnQ0KU3v7axZVs518c+7o7Zx52dFtNUEerlCgcff/zwQ48VvIKD0KBFIyrQHPnAdfsCv1KZefmZZzcl8cpNGz3fm9l36OX//V8Hj4rvI2USn1+YSIOe8dNgBf+LyYDJRkBrOkRABERABERABERABE5GQOLkZHT0bMkJkOWBLLGHF/g5dmHHH0I4l+vk14yPv+EmM/t3033ZUQIcHuccfv3gxJ5PfhbvRS6HR4ScEM/tK4/v3OleUJsrb50jqQRBpDiBv68ydeTBR8Zc30ec0Fg9TMIwwv8R5FAocVibOjxBVFihvx/VMTE19cKDD6/FR5PLRY0Q/0qe9bswC89LnvW9TKQZV6kLpjmA1DJ9iIAIiIAIiIAIiIAInIiAxMmJyOj+0hPIArowBbGAaghyuep0Jdm7L6lWTaoJsVXmQFsYr4lxWeBfSZwcWSX1KpsimkirKA6nZ2f27K2n4VrGARNGSWA1zJxAMS4Zx6l4SdX3YzdgO8XawcPV4u5w3wEnn8crkgTIlZCd4Q/ueoGt4pEdk6/snZqY9Ap9rp/DX4IFtdmae+CQ5wZRZTYo5hMPT4qRJThT0liv1FJ9iIAIiIAIiIAIiIAInJiAxMmJ2ejJUhNgUm+CrpoHEiJqNPY+8nh13+6qT9oIiSMEUpmpvw3OwmGSJqm4Q35+ZT0ivqrg+dO79+36+r3F557dNzuJTGCXRDQD25LQKkomre3kHHeg3Df13EtknLDXe/3wxN5vPlB/8pniKwcGVow0TDJ9lA+CQq1xz798YnTFeCGfqx84WHZ9j4R5P4i8qDoz+8KDD3kThwrVurvrZT+fQ7D4Zov5VFc1h6DfJydgcOkQAREQAREQARHoYQISJ21++fyF3RxMi9N5sb3S53EIzJunph4OxIYXx/WX99b2Hww9QqvSmKnUL9EiYbh2K467vxEXC3nXS+qVSvT8S1O7d7txxJJflGSTE9/xY5NzkqBUzK8En0m+HMZD5VIZdRI79WdenHKdsF7Pl/IOKfKuU3DdcdepHJjwJ2YQRflGuLpUQoJEYR33TMkLqvsOVicnG1FSnKVWgdQX07IZ2Zx1dkStph5n2L17i38RqZOpdwlo5CIgAiIgAiIgAo7EyRJ8CeZNu5eg/+7s0ix+5eLXIEzLqzXmRF7rUNLALm6AFxGCbGDxLYoXXNb4QkJE/UZiOJ5NTTErEZuz9MdEgnlu3XfJaiGEy2HH93ylimTxCdjyfbwsJnfFcfojt1ANXTfkmhixPPklaX+4Ymi52Ii9aNaPnYAdHnM4Y1BUxharTTjTcTICAnQyOnomAiIgAiIgAr1CQOKkV950142T6X42XzXJG8bjYPQHIoGfuSONzmpezBUy9chLRz14To4TsweJOdjC3SScpDu501JMUogVJ8SE2ebTMsa7YlwrpkYqLShFJQfRUmh2TQGezdlkShp1giYhYYUmkSN4bNLbcx/zLlof6LxJQIiaJPRbBERABERABHqagMTJ0rx+pmKt2RRLY0TH92r0iD2OnhlVcPSYS2jPbpgpLpoBYWKOdMJryyMtAM59LlEasZEo1vtintsyVDRPSbynwFwDlE1rmlomBgxZMlfezqapYE+MIKK+bcncmztL29HHqQkY95QOERABERABERCBXicgcdKubwAzLzv5MsnbZnlce8WnZrGn/w4sLuPcOFkdi9aUSLNSWF3YiIY0oAtNMvc0FYe8BytYjLCgPCtsGT+L8beYcigRJEnWlc27zy7T9rOnacumbRSMedJaTOcnIWDeQUqLDwMbegYgB/gzvPaOPkVABERABERABJY5AYmTNr5gplzMYAlM6i975eJsaBInTEaCnWqbSbGOkxIwhIyvxHgv0u0N5yaxx1RKyxjcnOAFATAXJnckrWiLmzeRulhsI6SgcJ9wLS+VJyY+Kz343Tzleu7UTpmpYKWOsWvuYfNt2rgwez+r1rzUb0MgzcgxLwE+MI+TRtgojw4H7GPDm7Ivi0JzR8tLaN7SbxEQAREQAREQgeVHQH+YbNc7nZtcmclW6fwNwcYNlXqdjThMEgQZCmaWq+nXqd9FOmk1s9nm5BWBcNwf25Qpmc5+zSWs+TE+Kysp7OzYyJf0iSli3kfsxgR9meLpzNhIlRPoxuwfT7OMeblmUq03aWCe7DAvxb6YVISwSlc9Cquuc/4VO8ujI+yY2fzXMPcWTtaWnomACIiACIiACCwjAvKctPdlMhVjS/E1a9x16ypOUq3X2U3c8/ibvsmgNn+6TyfE7bWpe3qbP+k3Xo6WmKvWYZgM91QjZDWY5KZ4U+Fgck5ai2fnRm4YhXH0MJPk5p2FdbhO9YkRN9RoFjtaWWcnIjDHqikcUemVsDEVuNtuuKa8ZqWTN/8i0le1kPmJGtR9ERABERABERCB5UFA4qSN79HMc8lm8J1y0R8b8Vevntw7wfK1fp6kCHtofvvqXofdS/FEdVodHs2/xBsJ0Tw/rYkvjZjypq2jb8fqnGxFLh5S5ASC50TW9fZ9E3CXysfEiRKnHoYVdrAZGixffrG/aizJsfSAedwUL+ZChwiIgAiIgAiIQC8QIMX36JSrFwa8tGOEtlkmKkmi6ZmJB5/82m//4ViQW1Es9+WCyOQ7nNZ0eWmH0C29H4vyDL7oWSPHrZs9zZgct1j2tJdPFrKyzia+8J47Va8dnp4pbly39XveMvCaq9xS0Ug985PFzfUyOY1dBERABERABHqLgMRJ2983E1h+wig8PHXwgUee+Od/959/ecj3g0IhCIJWfbJwPtd2S9WhCJwrAumX+ah2Q6VHuEriuFav76nOrrn8kk2vu3Hoqp3eqlEnwI+YFpdWP1f01Y4IiIAIiIAIdA8BiZO2vys7QyP1OoydSm3X/94VP/2cv+/g7P4D9XrNpGTrEIHlSaDlu82p7/mlUv/Y2NTY0PilO1bu2OauGnOKVp8bv8nyZKBRiYAIiIAIiIAInJSAxMlJ8SzSQ2Zm/OmYRAWkyMysc+BgddeLh555dnpiMo5tOsNcx6aQDhFYZgSM7nCDXK5/ZGj1xs3uxnXO8JBTLpAHz3rPTVkicbLM3rqGIwIiIAIiIAKnRUDi5LQwnftCRp8YheLGkXGhRJHTIOvERuKf+97Uogh0EAGrO0y6OzknvlMITCgXOfB21YFUuiBRrC6XRumgFydTREAEREAERGDxCUicLD7jE/VgJ1/p3n+pF4XNHk5UVPcXjUA2+RX8RWN8TMOpLLF3jURBidhPbs1JkuxtZO/nmEZ0QwREQAREQAREYBkSkDhZ0peaTcGwQhFc7X8VZubLO0gnwK3vov2W9FaP8xWHvZq713wdvQVEoxUBERABERABEZgjIHHSSV8FzY/b+TbMPvGGePpH+zTETknY7eTf2td8tdL6ROciIAIiIAIiIAI9RUDipKdetwY7jwDSxC5MYKOKeKZJ8jxAuhABERABERABERCB9hLQNmft5a3eOoaAXX0git1Gg/0vnSgN8JLvqmPejwwRAREQAREQARHoRQJBLw5aY+55AogQvCUIkt0HJr5+7+Nf+vLdiRPEYWXb5lU/8kPv6CuXPE+6vee/JQIgAiIgAiIgAiLQdgISJ21Hrg47hgAOk0rdffmQd9/T9SBfrM3UgtwRP8ghXORCadtbUihd21CrIxEQAREQARHofAISJ53/jmThohBAfuA5aXiFmjfeyG/w+1YlUSnOOblCXqkni0JcjYqACIiACIiACIjAqQhInJyKkJ4vXwLok0bsz0blhjPsuCMNdyJ2a1Imy/eFa2QiIAIiIAIiIAKdTkDipNPfkOxbJALsK4M44SdOfMfNO04udvykRZoo3GiRyKtZERABERABERABETgRAWX9noiM7i9zAiTEo0SSxItiL/FyiePFCStrm91POKRMlvnr1/BEQAREQAREQAQ6koDESUe+Fhm1+ATIhk/DupJqA0niJ3NixeGfhJTJ4uNXDyIgAiIgAiIgAiJwHAISJ8eBols9QsBsbxI7tZAtT1zX9awmkTLpkbevYYqACIiACIiACHQgAYmTDnwpMqlNBOy3P3H8uKlIPPSKPCdtwq9uREAEREAEREAERGAhAYmThUR03VMEkiRpNNAm/ENAoDQ1Sk8h0GBFQAREQAREQAREoGMISJx0zKuQIUtBII6TMGS/EytOnDj9B5GmxC+FNepTBERABERABERABHqbgMRJb7//nh99Kk4QI8Znkq4tbBfr6nkuAiACIiACIiACIiACS0FA4mQpqKvPDiBgvvoJm5w4jYgFhecCuqzPRJ6TDng/MkEEREAEREAERKAXCUic9OJb15ghMLcJY+JEkWNW6mrmm2TJ8aIkAiIgAiIgAiIgAiLQZgISJ20Gru46i0CcJGGUeF7AWsKdZZmsEQEREAEREAEREIHeIxD03pA1YhEwBOxe8BFhXYR2eah0X1xEQAREQAREQAREQASWloA8J0vLX70vJQEiu6I4aUT85h8CsV2eZ3ditKnxS2ma+hYBERABERABERCBXiQgz0kvvvUeGTN7mJiRpuFaZg/4dNju3HJc5grnCQkns3XUCZfsEc9h/Cdm9S6jT0z11nAvGjTVFAAGBB0iIAIiIAIiIAIisAgEJE4WAaqa7AwC6IrIZLsbYRI7vtUUXqotkB3sBW8+k6hRj9AkqRfFjRNKpxFfVMpy5JvDaRUqzXv6LQIiIAIiIAIiIAIicM4ISJycM5RqqNMI4OjAFYJV+DvweBg/ims0CbesMuGGFwQDA6V6GPMoX8jnSw47MpqjuWk8ZVoP4znRIQIiIAIiIAIiIAIisDgEJE4Wh6ta7QAC1tGBujh0aOKe+x/bd2jWxGWlR+J6juc3gsGnD/TPVHPGt+J6flA6MFH73Bcfjxo13Cw+/hSW8cLzktSjqLZm9ejOHVsZlvRJB7xbmSACIiACIiACIrA8CUicLM/3qlG1Epicqd//8EufvPPZeuwWcgHKBN3h+oUkv7KWX1vzxwMv57uB4/e/fHDm459+dna24rhxDmXi+4HrhY3DrnPkpuu2XrRjay5tV/qkFa/ORUAEREAEREAEROBcEZA4OVck1U4nEmCVYDwdK1aufNPt3/XpB+/0wkKxv88Ee3kui3TFTiHwuCzjRiH2y82PVuNg18RMFLP9SWL/811v6sjUhlUDYXGwmpC54nhpm9Innfi+ZZMIiIAIiIAIiECXE5A46fIXKPNPTsAmmeScoRG3kfRNR2XXGfbdPJUij8QTP3YDMlNYStiIDq/YcP26P0CKCnnz/CBR2AVlNtl9400bb77pQrJWSF9JtcnJe9VTERABERABERABERCBMyEgcXIm1FSniwigJVAexaJ35aXnf+upqVojdoI8bpLYrMuF/MBpYrwgoREd7HSSTxLSTMxFmLCWl9NoNIqBt2akvHq4lEsT67WScBe9fZkqAiIgAiIgAiLQXQS0CWN3vS9Z+6oJoDyQE6Wc9/rrx9eOxdXGLCtzkRiPKrHbm9gUd+MVMYsL8y/CJ3orSnCsuHEUTc9OX3De2KqRvpLnIE44TIOv2gpVEAEREAEREAEREAERODUBiZNTM1KJ7iVgJAhqw3GKgXPdZflVQ9W4ViFYK2Jh4Zj/XDfdfrEpN+wOjXxSDwESx3G1Ujlw9eXrN6wayaeLC5uEEx0iIAIiIAIiIAIiIAKLQ0DiZHG4qtXOIIDPhK84wYtF1xktOyVvJqxPh42QNbi4z0+63LDxhZjD2OySemJ+Ge8KifGTYbT32qsGzltb4qapkkZ2mYI6REAEREAEREAEREAEzjUBMw/TIQLLmwCqwzhPHOfqndsu335+ZbZmPCOux4+RIS2H/feQfiZxVHXjI5tXxgMlJ/DNIl3zirbU0qkIiIAIiIAIiIAIiMA5ISBxck4wqpHOJHA0BsuokMTZuWNk+wV9MzM1ArdiJ80qSXeLt9bPaRLKOXhPkqgxM1ys/8CbL1tpU+ElTTrzJcsqERABERABERCBZURA4mQZvUwN5QQEkBVGWbjOmpW5NeNeEjfiODQLdbUc9l8CqwubrHiyUZIoCWfH+hpvfO3m0f6CorlaUOlUBERABERABERABBaLgMTJYpFVux1AYJ6zg8guorMG+/21I169No34SHXIcc2M62HNd+qjA8554yaZ3jY0r7nj1tNNERABERABERABERCBsyAgcXIW8FS1ewigK/gJXGfLeUOvu2b1zNTuJKyyE6PZyyTdC77Vj4LbpFabGRkILtiwKu+ZpYWVcNI9r1qWioAIiIAIiIAIdDEBiZMufnky/dUS4Ou+YY137WVOvbIvjutEduFOMYnxzbW60gZZYTis1o5s3Vh84y2bfdfhRxsvvlrUKi8CIiACIiACIiACZ0BA4uQMoKlKdxCYl1OSmowUGS6568edgXwYR/U4jrhtpIdZt2suaAsdkkRV36uuGA3WrR2gihEn3TFiWSkCIiACIiACIiAC3U1A4qS735+sfxUEErODCWFaw8Vg57a1gZs0wogMeJYI5tOkwjfVTLU2tW5FsHpFMc8Kwmk8mMTJq+CsoiIgAiIgAiIgAiJwpgQkTs6UnOp1GwGzISP6JHFGhwbe9ubrB0qFRj1i3WCiulicy2SepNssOlFUmdp/9bbRS7euJEdF/0K67T3LXhEQAREQAREQgS4moKlXF788mX5yAse4O2wAl9Pf51xzFcnxjbAWkV9iU+ETF/9JEkVR2KgH9SNXXJDbsaFcpommO+XkfempCIiACIiACIiACIjA2ROQODl7hmqhawigNfjG5zyHTd9Xj+TK+TgJ607Mgl0muAshEsWNWmN67Uh+9VBusOjaVPhjRE7XjFeGioAIiIAIiIAIiEB3EZA46a73JWvPAQG+9HnHuWbH8Hkr4rA+xYLC7AefelWSOJ4NwyOvfc3GNeODAdkmqWQ5B12qCREQAREQAREQAREQgdMgIHFyGpBUZBkRwA3CT951brpmZPOaMK4dxl9C1kl6OwrjadedeN1NW9auHpLDZBm9dg1FBERABERABESgOwhInHTHe5KVZ0+A2C2jQdLILjLdt25wxgenG/UpcuG5SUJ8FLLzyUypMLViOCnkzd4mngTK2XNXCyIgAiIgAiIgAiJw2gQkTk4blQp2OQGzkWK6Ywm/+d4XPGd8uDw2VKrM1o1ucZ1GY6a/UL/pyo3lUoAs0b+NLn/hMl8EREAEREAERKD7CGgC1n3vTBafPQH0CcnuF21bc+Ula2rVBg0mSVSvTa8YiN5y08bBUo69F3WIgAiIgAiIgAiIgAi0mYDESZuBq7ulJ2BjtQjx2rJxePuW4ZnZeswSwlGYc8K1w/7lF4705zzEiS229ObKAhEQAREQAREQARHoGQKsSKRDBHqOAKKc9bkG+53hocQzW5vUGkk0PpDbuLowlDNreUmc9Nx3QgMWAREQAREQARHoAALynHTAS5AJbSeAV4Qf0uLHh4tXbR/xokNHjryyZcPQa668KJdmpMht0vZ3og5FQAREQAREQAREQEm/+g60hQArYtlFsdrS22l1gi4n7WTTuvzbbi1FtWeiePe6NY2NG/LaEv608KmQCIiACIiACIiACCwCAXlOFgGqmjT55fPUiJseHQXGeE4cZ+Wgt2OL41SfWdk/vWosGRwwHhW74nBHWStjREAEREAEREAERKAXCEic9MJb1hiPQwARwre/nHNW9EWDweGrLxzatGagkO5topiu4/DSLREQAREQAREQARFYfAJKiF98xj3WAx4T6ydhAaypqSk7+iAISqWS53k86gQe1giy3tEn/YF36aaRt7zh0p0Xrst55g42doSVnUBKNoiACIiACIiACIhAGwm4TCXb2J266hUC9Xr9+eef/8Vf/MWDBw8y5iuvvJLzdevW5XIknHfGkX7xWbNrerZ2z7ee2LR10/joADszYl9ilvLqDBXVGahkhQiIgAiIgAiIgAi0h4A8J+3h3HO9PPvss3/zN39z1113VSoVBr937148Jx/4wAdWrlx59iysc+Ys20Gb4B7hp1TI7bxoc7mvOOc2Me22VZmcZDgneXSWw1d1ERABERABERABEehAAso56cCXshxMeuWVVz7xiU9MT0830uOFF174r//6LytUzmB4rf49e9565wwapIrRH2nwlu95Y8P9hVyAUifQyzxKP9v2cZJQt5M8Oq55YDl7MsdtWTdFQAREQAREQAREoA0EJE7aALnnugjDcGJi4plnniHthDguEk64s2fPHlJQOHlVOOxUO5ujL9LMGzVi80/OoSw5Y1PPuGIG9uxbyJrSiQiIgAiIgAiIgAi0k4DESTtp90pfk5OTpJqgTBjw6tWrh4aGmC6ThfLkk08iWk5JIY5jytujVZa03qcRCpyyqawAdRccWXUEif2xhW2/FM4KZI0sOLFlji1pK2K5bep0GszKtLZp21nQ6YJLytsq9r7FRcUF9xfU0qUIiIAIiIAIiIAIdCYB5Zx05nvpbqs+9alPfexjH7Nj+JVf+ZWnnnrqT/7kT2q12u/8zu+MjIy84Q1vONHwmFU/9NBDv/Ebv0GCCtrmLW95y7ve9S4m3I888sh//ud/3n333dl8fWxs7MYbb/yxH/uxEzXVep+gMmLMvv71r8/MzGT3r7/++ttvv/2SSy7J7nDy2GOP/fEf/zHKCg/Pd3/3d//wD/9w69PsHDO+9a1vffCDHyyXy4VCATvf/va38zQzz5bE8gcffPB//ud/vva1rxHdxpIAN9xwA36krJ3s5DOf+cznPvc5xBtV0BV8ouiuvfban/mZn2GJs6xY6wkNYsO//du/Pf7441u2bPnxH//xjRs3FovFBx544B//8R+feOIJjPnRH/3Rt73tba21dC4CIiACIiACIiACnUzgOPOkTjZXtnUFAcQAk3JMZZLNvJmJPmKDyTTC4/Dhw6gO7p9ozo1rhZk6wWDMrbdv304w2Ec/+tGXXnoJZcKEOxt+X1/fc889t2/fvq1btyIzzjvvvOxR6wkzdSz55je/+dWvfhWFgw10zUGZXbt2kbV/442vvfba6y688ELf91mlC6UxPj7+yU9+8sCBA+vXr7/11ltp2aoFW8s2fuTIESTBpz/9acZFxQsuuABrKWA/s5JWP/zTP/3To48+aqUC1Rk+VbjknMi3L3zhC7t370ZmAOfll1/mPmT4zOfzjBeZBIrv/M7vvOyyyzCjdS1m2mH43/jGN77yla+geahCO/fcc88dd9zxxS9+kaYwA9VkDdanCIiACIiACIiACHQFAYmTrnhN3WQkC3Nx4Cdhen311Vfj4uAv+tddd92Xv/xlptdMmvfv33+SNbsoQ11iwBjzww8/jGfgQx/6EDeZfA8MDBAkxgrFs7OzaBjcEczpaRnxc8stt6xdu7YVE3N3OkLnkIiPPrGyhDI0Qpo+jaBV8FQgCQ4dOnz++ecjM6i+YsWK22677R/+4R8wgN5Zbeyd73wnXfMokxycU5HhVKtVmuUpCgoxw0htSWuG1SqMF4GE/YODg8gMKzxsMdpHBf3zP/8z7hqqUAZiKCKcS5iH8WgqyqBk7HYxl156qW05+8RIy4oRoZfQJP/yL/+CVgEIrdEXELLCOhEBERABERABERCBzicgcdL576jLLEQz4FVg/j08PPwTP/ETeB6YtfO3/zvvvJOIJhwgF1100Zve9KbTGdV///d/f/azn2WSvWbNmtHRURwpTNBpH88MYuDQoUPM2mkWdwfhVQvil1gZjEcEg917772ogm3btjHpJ1AKxwgeBpweKBw8D/fffz8zeDwkeD9oBAlBoBdCBWmBFwIR9b3f+702EIsRZfrkvvvu+/jHP84Q0AB84sNBSBCuZgUJJTmoZbwxjoNUwMKbb74ZDhTgoBZa4u///u8/8pGPWHWBOurv70c7vfa1r2U3GCghSzCPRc+w80//9E9J4/n1X//1VatW2TYzesDhHBpf+tKX/uIv/gIXE9gZqe2I2LCspE5EQAREQAREQAREoPMJSJx0/jvqMguJYsLhgNH4KF7/+tczv2cuvnPnTu4gA/BjoDGsOGEGz02m0ScaIX4Jpuxkhrz3ve9F5KAxyKkgD4T7iIF//dd//du//VvOiYzCf7JAnDD7J8WFyCi0wete97oPf/jDaA8OJvdU+bmf+zm8H3/+53/+H//xH3g23vGOd/zd3/0djWSWYBuOEfQPnVo7s0ec4KkgPg1hYMUJLgtcLt/2bd/WWoZHaCc0EgNEJPzqr/7qjh07KMB9PB5sAkMuCkbyFBmDdwgvE31hIf6Tt771rfT+9NNP/+7v/i6Ncw5VtApGUqC1F+skQa1Rku5QX9///d8PMUtV4qSVlc5FQAREQAREQAQ6n4DESee/oy6zkIArvAFMuJkZM5NmBs/BCVkiTLKZl/OJSkEknESW2DEzWceP8f73v5/EFevNoArtoBZe85rX0AuxVczLaZDUi89//vM4QDJYdMFsHh1CeeLKcE3QI5ZQgOp4SDi4zx1KEkZFI1aEYPm73/1uxAPRVggJntpatmKrzagIFBG+F9JXCN/CxYGHJCvMCfKDLHzbLOqFpzRCCzSL/wd1xKMNGzb80R/9EbrI+lW4QwE0GPSwHG8JQyBSC+FBhgzxcvhV6Dcbpm2QWuT6I+He+MY3ogNxNFk7M2Nay+tcBERABERABERABDqWwPEXAupYc2VYJxPAn4BaIFmCuTJ56vwJP1MUBCz9/M//PBNu5vp4M5htU+aUYyHGiQk3Dgf8JzZKitk2J4gWpvLXXHMNbRLCxFyf5BMCwBY0SF/2DrWowidTdj5RKczvCX8iveTXfu3XfvmXf/k973kP4sGahIQgCI0UeeriHkFFIAzogqd2xo8QQrfQDjawSBcBY3SEhDhWbhGdhVsGg2mcHq0BBGgRbwYE5NAVV1zxgQ98AE1FvBYFMNIOk6Y4wUIKvO997yPfHWPQP3iKiElbMEwMswft2LUBbDu0QI8LCutSBERABERABERABDqZgOYunfx2usw2gqBwOLz44ovYTWIJE3c8AJwzdUacEI5FiBfnTO5JBWG6f8rhXXnllazny1TbqoLW8twh0IuEEHJRuE+uBfpkQQFkBsXw1eAYoVN8C1ZjUAwz+GQxYtbq5UAC4ZGw1emOwDPkBJekfBBPhUSxVawGIMkecYVb46qrrsLjga7gKeFbLL2F88S2zB36wqNCNghZLsSVWWO4zx00BpQoyQB/8Ad/kPg3K2ywlhMOK2O4tErJBsVhxp/92Z+RfE8jCw50CF4g0magQfUFT3UpAiIgAiIgAiIgAt1CQOKkW95UF9iJT4B1rlj9lrk1s+RNmzYxUbYTetwCLLRFcBfTaP72T8YI48nm8ScaGzrBypvWArZB7tALT61zAN8FwqC1GF0TMUW/ZGWQLP4Lv/ALiAdsI83DxpXRDo4d7CQIijx7FIKtbtuna1qgPKtp4TnhnI7QGwgGFvgiA55IM4QTfhv0A09pnOgsxIwVXXxiD4FnnFx88cVsQpKlf0CJxBvM4BEVsRDVhNOp9aBHe3ATcWUTS/jEHlw0rcO054zi27/92/G0WBrHFtAdERABERABERABEegKAso56YrX1OlGWpnBJ1NnPpkr4ySxE2Vm8xwMgEvcKaSI4GCxxez90xkbbWaFsxMqtp4vaAcDSB//6Z/+aRI/EAl4Tn7kR34EhYAXgmguIqCQH5iUtWCHQCO2r8svvxzHCLXQEigfhAQlKc+5rYIviLR+5A3BXRzIBlY9Js8evUELKBM0DOk3NEinBLkhQmxFnmbDZ1mzv/zLv8wkjR2ClR+ZPXhmWLkLUWdtyAxuHS+yBGuPFXKtZXQuAiIgAiIgAiIgAp1PQOKk899RF1jIjJm5OG4TO7Nn8Su8CgvsxsPwkz/5k8zX2T8ePwPbwONPYFsPq2EWFG69tG223mk9P+5knQLM5on7Yo0sPgnNIuyKjU24SYgX+R4oFs7JZiFxBc9GplKyvgjEIgGd1YRtX7YXXC5YTngVOgElgP5BirDRIXnqf/VXf4WvA12Bf4PCnKNV6ItzVBAaxg6Tilbq0BF1yYlnN3fUGpfZoCjAub1DdZQP7VCxtUxWGKoMBGMIHuMku68TERABERABERABEehGAprNdONb60Sbmcp/4hOfYALNfJoltjgWWMnUGSWAVKAAeRdsyoGGIfJqQbFjLyl/7E1757jzdfuIWvRoU8nJJ8EBwhSftbNI9sBTQeI+BUg3J7WdMm9+85ut2yHri5g0Di7pgqgwvB+YiuRg/WL0CTFgBIOhOuiLkSJvrCVErFGLdcDwnKB/WC6MxHp6scqEMvbIeqFB7MHrkg2QAtm5PYEVmsf2RYjXsQVoDZ2D/aeUeQta1qUIiIAIiIAIiIAIdBoBiZNOeyNdaQ+zZ+bQzNr5Az8TZTwJdj0rBrNgMo3bgck0zgEW9bIpGZQ/mzEvaL+1KSbrNI72QBTRFxnzxGLh4aEKaR6EVLGaFoFbn/vc5/BOXHbZZYgKqlvlgBggQwaPBy6Xj370o3h4OMgA+eu//muS78mkp03aoTCZ8ZRkRPSFpwVxgpIBCDTQEjfddFPr/ieUxyoO6sIK1URTaBjOWy1vPaeKrcVN/E5ZbowtQ0fW00KZ1lo6FwEREAEREAEREIFuJCBx0o1vreNsRnIQm2Rn2MyVf+/3fo9NzZmCYyizcI7MYlwKXDKTphh6hqn/gtl2VvLsT+x8HZlhA5+QASRmEHaFZkBg/NIv/RLLBCNaHnzwQYLQSFK3bpasXxI5WLYLSUPKB6OjNQaIPMBythPJ4ta4jyyhC3QCi5WR00KGCV3QDo9YaHiBE4nh04K1DenC5on2POt3wQnl6ReYdMEJqyovKMAlZTiOva87IiACIiACIiACItBdBLRaV3e9rw61lvwKEk4y45ia45ogZokDbwPn2WHn2UzHmW3/5m/+JtufZ7XO7QmTdbvIFT1ybgUALg60EEtskZrPsrzscIKQoACSA2mxwAC0CikrSALu26m/NZtPYqhwqtjyVMfr8lM/9VNIFNb5RW4R3EXYGL1TwIqK1papS6wXzdIOWfKIDUwyW0Ke+EAmUYYeKUwvra3pXAREQAREQAREQASWEwF5TpbT21yysRDCRJQU3TPhZldBVg22roNjDWKGTSQVWeBM99mgkOCuY8uc/R0cHbg72I0Exwhp63gz2J0wkxa0jyrAp/Fd3/VdqKY//MM/xJXBFocYQ0QWjyiAeUgC9pWnlr1knbFPfvKT5MQjIpAKiIRMsWzevPmWW2758Ic/zKhtUyScIE6uvvrqrIVsUCSrsPPjb/3WbwHtvvvuY88TtjqxnWZlshO6uOOOO5566ilkHi4g1i8mU5/c96yATkRABERABERABERgORGQOFlOb3MJxoLfgDk9AVrMy1k5ijgoNoZnss6lnbsvsAm/AYkf999//6OPPoqzgooICZYeXlDsLC9RCGSZf+QjHyGdA3nwfd/3fVacoDQysYHvAklgE83pDhnTajPGU5IyGIydbGzy+c9//uMf/zhl2FEEkUAV2xSfSBoS/anCQcAYoWvoImz4ju/4DnLlW8dCYfw2t99++8c+9jGWECBmjKWE2WUFT46N16IFyvBJLdiiSVhm4Atf+AKgGMj73/9+ms0atMX45KBwdl8nIiACIiACIiACItClBCROuvTFdYrZ+AeYiLMVOgbho3j3u99Nkjfz75PYx1wctYDrgPk0zhMOvAFMr7NJ+UnqnuYjm+BOg+gKXDos0oVmIHMdjwcKir6Y4iOK2Oudveppk5IYTy2e2i6sPYSBXXvttcRoffazn0Wl0A42k23CAlytllAdGUP7yBIKc44oogApJURwZQ3aEwK9aJbd3PHtoKAQaezHgqLDk0MLGIBPBrNx6fCUFcZwNOG0weNEle/5nu/Bn9PaNXZyySeG2fPWpzoXAREQAREQAREQge4ioJyT7npfHWct02gcFMzasYyApR/6oR86edARc2j8KuwNwhScA21AJjruCEQOn61ugTMYajY7Ry3gFcG/gaKgnTvvvJNpPQFUzPIxgAMV8Qd/8Ae4L55++mkKUBHBkCkT7mAbKoLlg0lNwR2EgrLKhJYZICKn1Txu4vx517vexeddd92Fo4M7VMctw2dmFSf2HPXy27/926ykTDFECEFu73nPez70oQ+Rms8jWuYm0Vxs6fje974XcUUtsvl/9md/logyDOOSIVAMxUIXNEIt7KevVqt0LgIiIAIiIAIiIAJdR0Cek657ZZ1lMBNlG9OFWUyUT5mxzayaOTSagUk2UoT0cSKX7PT67AdGO1kj6IQPfvCDaABWCkZB4aBAnLBjCZ4HiiGEWEcYdwo2sEbw7//+77OmVmt12uER1jIipv60wFN7oGGyYLCsOxwv73vf+2gTGcNNyuByQUvQAoeVHFS34oQTzGP3ej5ZrYs1AxBLiDR8KaTrUJhLfCZsFgkcqhAG9gM/8ANsWs8jLjlsv4SiIeq4xFSSYbL7mVU6EQEREAEREAEREIHuIiBx0l3vq7OsZT8T/sDPElXMv0m6YDqO5Di5idaTwIyf4CiiqliDmF3SObnttttOlBR+8gYXPGWCztSfm8gDgq/wSKA6vvnNbyJR0Cd4ITCAAhjMtB4fyHXXXUcOya233rogXMo2S2GcJFZa0DIWEpNG8FXWS9Y7cosILtQIjziIEHvnO9+JYqEv22NW0p7QJnFcb3/72zlBI+FswavDhoxcUsXqIhwj7KZy8803Ex5GTj/BcvYRnxzYf+TIETQJDaKd7BrHC3rRpQiIgAiIgAiIgAh0FwGJk+56Xx1hLZNvJseYwh/4yTZh9syf8JmaM8W3909ipRUnzLMJAMNvwKq7qALm5UzHqUXL3LRbiNAU0/eTNMUjPBhvetObCLvinE+q20aoS0doCbZ+Z53fe++9l5x162RAllDMRm1t2rQJ42kBSUD5BX3ZFhA5pMTg0KAWsgS1gKSxHbWWp0caQUUgS6xUY+9Fhrmg2YyPLb9jxw4ix1iMizbJj6dZGkFpcEJFULDeF0Og92OVGwWoRbgXnh/yfNBFC/pqNU/nIiACIiACIiACItAVBObiTIytc6EiTbOPBsg07+i3CMwnwCwcWcJkmtvMqpEKfGbz7/ll510x+aYWsVW0YKfpaABbApWC5qEA95mRZ/ft0wWNU4zCVOEEvYF4aO3GNOK4cWKcJNhJXzyNQqK1IlrmqbUZs08+rZ+tVBpET8WJ6xmTKO97vnO8fyBEqVkaGIPlNOu53oKSxw7Bmsco7CNasNqJRH2I2naycZlBNVc3pkqtWmU8nm+UGIYtaDyrpZOMAAA554ux4L3YAvb/BY/3brMGdCICIiACIiACIrCIBP4fbuHUOdUMeBAAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cross-encorder re-ranking\n",
    "\n",
    "Cross-encoder re-ranking to scores the relevancy of the retrieved results for the query that has been sent. In re-ranking, after you retrieve results for a particular query, you pass these results along with your query to a re-ranking model. This allows you to re-rank the output \n",
    "so the most relevant results have the highest rank.\n",
    "\n",
    "Sentence transformers are made up of two kinds of models:\n",
    "- a Bi-encoder, where a Bi-encoder encodes queries separately, \n",
    "- and then we can use the output of the Bi-encoders to perform cosine similarity and find the nearest neighbors.\n",
    "\n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Collection(name=microsoft_annual_report_2022)]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chroma_client = chromadb.Client()\n",
    "chroma_client.list_collections()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# only run if collection already exists\n",
    "\n",
    "chroma_client.delete_collection(\"microsoft_annual_report_2022\")\n",
    "chroma_client.list_collections()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "349"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "embedding_function = SentenceTransformerEmbeddingFunction()\n",
    "\n",
    "chroma_collection = load_chroma(filename='docs/microsoft_annual_report_2022.pdf', collection_name='microsoft_annual_report_2022', embedding_function=embedding_function)\n",
    "chroma_collection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "• operating expenses increased $ 1. 5 billion or 14 % driven by\n",
      "investments in gaming, search and news advertising, and windows\n",
      "marketing. operating expenses research and development ( in millions,\n",
      "except percentages ) 2022 2021 percentage change research and\n",
      "development $ 24, 512 $ 20, 716 18 % as a percent of revenue 12 % 12 %\n",
      "0ppt research and development expenses include payroll, employee\n",
      "benefits, stock - based compensation expense, and other headcount -\n",
      "related expenses associated with product development. research and\n",
      "development expenses also include third - party development and\n",
      "programming costs, localization costs incurred to translate software\n",
      "for international markets, and the amortization of purchased software\n",
      "code and services content. research and development expenses increased\n",
      "$ 3. 8 billion or 18 % driven by investments in cloud engineering,\n",
      "gaming, and linkedin. sales and marketing\n",
      "\n",
      "competitive in local markets and enables us to continue to attract top\n",
      "talent from across the world. we plan to continue to make significant\n",
      "investments in a broad range of product research and development\n",
      "activities, and as appropriate we will coordinate our research and\n",
      "development across operating segments and leverage the results across\n",
      "the company. in addition to our main research and development\n",
      "operations, we also operate microsoft research. microsoft research is\n",
      "one of the world ’ s largest corporate research organizations and works\n",
      "in close collaboration with top universities around the world to\n",
      "advance the state - of - the - art in computer science and a broad\n",
      "range of other disciplines, providing us a unique perspective on future\n",
      "trends and contributing to our innovation.\n",
      "\n",
      "our success is based on our ability to create new and compelling\n",
      "products, services, and experiences for our users, to initiate and\n",
      "embrace disruptive technology trends, to enter new geographic and\n",
      "product markets, and to drive broad adoption of our products and\n",
      "services. we invest in a range of emerging technology trends and\n",
      "breakthroughs that we believe offer significant opportunities to\n",
      "deliver value to our customers and growth for the company. based on our\n",
      "assessment of key technology trends, we maintain our long - term\n",
      "commitment to research and development across a wide spectrum of\n",
      "technologies, tools, and platforms spanning digital work and life\n",
      "experiences, cloud computing, ai, devices, and operating systems. while\n",
      "our main product research and development facilities are located in\n",
      "redmond, washington, we also operate research and development\n",
      "facilities in other parts of the u. s. and around the world. this\n",
      "global approach helps us remain\n",
      "\n",
      "when the world around us does well. that ’ s what i believe will lead\n",
      "to widespread human progress and ultimately improve the lives of\n",
      "everyone. there is no more powerful input than digital technology to\n",
      "drive the world ’ s economic output. this is the core thesis for our\n",
      "being as a company, but it ’ s not enough. as we drive global economic\n",
      "growth, we must also commit to creating a more inclusive, equitable,\n",
      "sustainable, and trusted future. support inclusive economic growth we\n",
      "must ensure the growth we drive reaches every person, organization,\n",
      "community, and country. this starts with increasing access to digital\n",
      "skills. this year alone, more than 23 million people accessed digital\n",
      "skills training as part of our global skills initiative.\n",
      "\n",
      "also increased the number of identified partners in the black partner\n",
      "growth initiative and continue to invest in the partner community\n",
      "through the black channel partner alliance by supporting events focused\n",
      "on business growth, accelerators, and mentorship. progress does not\n",
      "undo the egregious injustices of the past or diminish those who\n",
      "continue to live with inequity. we are committed to leveraging our\n",
      "resources to help accelerate diversity and inclusion across our\n",
      "ecosystem and to hold ourselves accountable to accelerate change – for\n",
      "microsoft, and beyond. investing in digital skills the covid - 19\n",
      "pandemic led to record unemployment, disrupting livelihoods of people\n",
      "around the world. after helping over 30 million people in 249 countries\n",
      "and territories with our global skills initiative, we introduced a new\n",
      "initiative to support a more skills - based labor market, with greater\n",
      "flexibility and accessible learning paths to develop the right skills\n",
      "\n",
      "at times, we make select intellectual property broadly available at no\n",
      "or low cost to achieve a strategic objective, such as promoting\n",
      "industry standards, advancing interoperability, supporting societal and\n",
      "/ or environmental efforts, or attracting and enabling our external\n",
      "development community. our increasing engagement with open source\n",
      "software will also cause us to license our intellectual property rights\n",
      "broadly in certain situations. while it may be necessary in the future\n",
      "to seek or renew licenses relating to various aspects of our products,\n",
      "services, and business methods, we believe, based upon past experience\n",
      "and industry practice, such licenses generally can be obtained on\n",
      "commercially reasonable terms. we believe our continuing research and\n",
      "product development are not materially dependent on any single license\n",
      "or other agreement with a third party relating to the development of\n",
      "our products. investing in the future\n",
      "\n",
      "but generally include parts and labor over a period generally ranging\n",
      "from 90 days to three years. for software warranties, we estimate the\n",
      "costs to provide bug fixes, such as security patches, over the\n",
      "estimated life of the software. we regularly reevaluate our estimates\n",
      "to assess the adequacy of the recorded warranty liabilities and adjust\n",
      "the amounts as necessary. research and development research and\n",
      "development expenses include payroll, employee benefits, stock - based\n",
      "compensation expense, and other headcount - related expenses associated\n",
      "with product development. research and development expenses also\n",
      "include third - party development and programming costs, localization\n",
      "costs incurred to translate software for international markets, and the\n",
      "amortization of purchased software code and services content. such\n",
      "costs related to software development are included in research and\n",
      "development expense until the point that technological feasibility is\n",
      "reached, which for our\n",
      "\n",
      "fiscal year 2021 was a year of both successes and challenges. while we\n",
      "continued to make progress on several of our goals, with an overall\n",
      "reduction in our combined scope 1 and scope 2 emissions, our scope 3\n",
      "emissions increased, due in substantial part to significant global\n",
      "datacenter expansions and growth in xbox sales and usage as a result of\n",
      "the covid - 19 pandemic. despite these scope 3 increases, we will\n",
      "continue to build the foundations and do the work to deliver on our\n",
      "commitments, and help our customers and partners achieve theirs. we\n",
      "have learned the impact of our work will not all be felt immediately,\n",
      "and our experience highlights how progress won ’ t always be linear.\n",
      "while fiscal year 2021 presented us with some new learnings, we also\n",
      "made some great progress. a few examples that illuminate the diversity\n",
      "of our work include : • we purchased the removal of 1. 4 million\n",
      "metrics tons of carbon.\n",
      "\n",
      "we protect our intellectual property investments in a variety of ways.\n",
      "we work actively in the u. s. and internationally to ensure the\n",
      "enforcement of copyright, trademark, trade secret, and other\n",
      "protections that apply to our software and hardware products, services,\n",
      "business plans, and branding. we are a leader among technology\n",
      "companies in pursuing patents and currently have a portfolio of over\n",
      "69, 000 u. s. and international patents issued and over 19, 000 pending\n",
      "worldwide. while we employ much of our internally - developed\n",
      "intellectual property exclusively in our products and services, we also\n",
      "engage in outbound licensing of specific patented technologies that are\n",
      "incorporated into licensees ’ products. from time to time, we enter\n",
      "into broader cross - license agreements with other technology companies\n",
      "covering entire groups of patents. we may also purchase or license\n",
      "technology that we incorporate into our products and services.\n",
      "\n",
      "15 corporate social responsibility commitment to sustainability we work\n",
      "to ensure that technology is inclusive, trusted, and increases\n",
      "sustainability. we are accelerating progress toward a more sustainable\n",
      "future by reducing our environmental footprint, advancing research,\n",
      "helping our customers build sustainable solutions, and advocating for\n",
      "policies that benefit the environment. in january 2020, we announced a\n",
      "bold commitment and detailed plan to be carbon negative by 2030, and to\n",
      "remove from the environment by 2050 all the carbon we have emitted\n",
      "since our founding in 1975. this included a commitment to invest $ 1\n",
      "billion over four years in new technologies and innovative climate\n",
      "solutions. we built on this pledge by adding commitments to be water\n",
      "positive by 2030, zero waste by 2030, and to protect ecosystems by\n",
      "developing a planetary computer. we also help our suppliers and\n",
      "customers around the world use microsoft technology to reduce their own\n",
      "carbon footprint.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "query = \"What has been the investment in research and development?\"\n",
    "# now get 10 results\n",
    "results = chroma_collection.query(query_texts=query, n_results=10, include=['documents', 'embeddings'])\n",
    "\n",
    "retrieved_documents = results['documents'][0]\n",
    "\n",
    "for document in results['documents'][0]:\n",
    "    print(word_wrap(document))\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c3cf20b7f3324f78aab93a064e2bf476",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "config.json:   0%|          | 0.00/794 [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "966bfa0fc7e34588a6087c35853b4ff5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pytorch_model.bin:   0%|          | 0.00/90.9M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5577fb91dce448bbaecf3517f4e8aac9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "tokenizer_config.json:   0%|          | 0.00/316 [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "90be9021f65348df9e42d36e3a77a4bf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ffcfd4b7b0d849779209a0603906a70d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sentence_transformers import CrossEncoder\n",
    "cross_encoder = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores:\n",
      "0.98693466\n",
      "2.644579\n",
      "-0.26802942\n",
      "-10.73159\n",
      "-7.7066045\n",
      "-5.6469955\n",
      "-4.297035\n",
      "-10.933233\n",
      "-7.0384283\n",
      "-7.3246956\n"
     ]
    }
   ],
   "source": [
    "pairs = [[query, doc] for doc in retrieved_documents]\n",
    "scores = cross_encoder.predict(pairs)\n",
    "print(\"Scores:\")\n",
    "for score in scores:\n",
    "    print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New Ordering:\n",
      "1\n",
      "0\n",
      "2\n",
      "6\n",
      "5\n",
      "8\n",
      "9\n",
      "4\n",
      "3\n",
      "7\n"
     ]
    }
   ],
   "source": [
    "print(\"New Ordering:\")\n",
    "for o in np.argsort(scores)[::-1]:\n",
    "    print(o)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Re-ranking\n",
    "\n",
    "\n",
    "The cross-encoder re-ranker can emphasize different parts of the query than the embedding model does. And so the ranking that it provides is much more conditional on the specific query than just what is naively returned by the retrieval system itself.\n",
    "\n",
    "Cross encoder\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "original_query = \"What were the most important factors that contributed to increases in revenue?\"\n",
    "generated_queries = [\n",
    "    \"What were the major drivers of revenue growth?\",\n",
    "    \"Were there any new product launches that contributed to the increase in revenue?\",\n",
    "    \"Did any changes in pricing or promotions impact the revenue growth?\",\n",
    "    \"What were the key market trends that facilitated the increase in revenue?\",\n",
    "    \"Did any acquisitions or partnerships contribute to the revenue growth?\"\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "queries = [original_query] + generated_queries\n",
    "\n",
    "results = chroma_collection.query(query_texts=queries, n_results=10, include=['documents', 'embeddings'])\n",
    "retrieved_documents = results['documents']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Deduplicate the retrieved documents\n",
    "unique_documents = set()\n",
    "for documents in retrieved_documents:\n",
    "    for document in documents:\n",
    "        unique_documents.add(document)\n",
    "\n",
    "unique_documents = list(unique_documents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "pairs = []\n",
    "for doc in unique_documents:\n",
    "    pairs.append([original_query, doc])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores = cross_encoder.predict(pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores:\n",
      "-10.711212\n",
      "-10.042844\n",
      "-6.90209\n",
      "-9.918428\n",
      "-3.794862\n",
      "-10.148884\n",
      "-7.754099\n",
      "-9.80788\n",
      "-10.0839405\n",
      "-4.651892\n",
      "-9.357721\n",
      "-1.136996\n",
      "-4.8184834\n",
      "-5.141832\n",
      "-7.9171767\n",
      "-10.00014\n",
      "-9.768024\n",
      "-3.7681527\n",
      "-5.2747498\n",
      "-8.505108\n",
      "-4.3417683\n",
      "-7.4906564\n"
     ]
    }
   ],
   "source": [
    "print(\"Scores:\")\n",
    "for score in scores:\n",
    "    print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New Ordering:\n",
      "11\n",
      "17\n",
      "4\n",
      "20\n",
      "9\n",
      "12\n",
      "13\n",
      "18\n",
      "2\n",
      "21\n",
      "6\n",
      "14\n",
      "19\n",
      "10\n",
      "16\n",
      "7\n",
      "3\n",
      "15\n",
      "1\n",
      "8\n",
      "5\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "print(\"New Ordering:\")\n",
    "for o in np.argsort(scores)[::-1]:\n",
    "    print(o)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Embedding Adopters\n",
    "\n",
    "<img src=\"./img/embedding%20adoptors.png\" width=\"500\" height=\"300\">\n",
    "\n",
    "Embedding adapters are a way to alter the embedding of a query directly in order to produce better retrieval results. \n",
    "We train the embedding adapter using user feedback on the relevancy of our retrieved results for \n",
    "a set of queries. \n",
    "\n",
    "Torch is used in order to train a model, but a very lightweight one. And we create our embedding function and load everything into Chroma.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import umap as mp\n",
    "from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
      "To disable this warning, you can either:\n",
      "\t- Avoid using `tokenizers` before the fork if possible\n",
      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "349"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "embedding_function = SentenceTransformerEmbeddingFunction()\n",
    "\n",
    "chroma_collection = load_chroma(filename='docs/microsoft_annual_report_2022.pdf', collection_name='microsoft_annual_report_2022', embedding_function=embedding_function)\n",
    "chroma_collection.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/dev/miniconda3/envs/llm/lib/python3.10/site-packages/umap/umap_.py:1943: UserWarning: n_jobs value -1 overridden to 1 by setting random_state. Use no seed for parallelism.\n",
      "  warn(f\"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.\")\n",
      "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n",
      "100%|██████████| 349/349 [01:45<00:00,  3.31it/s]\n"
     ]
    }
   ],
   "source": [
    "embeddings = chroma_collection.get(include=['embeddings'])['embeddings']\n",
    "umap_transform = mp.UMAP(random_state=0, transform_seed=0).fit(embeddings)\n",
    "projected_dataset_embeddings = project_embeddings(embeddings, umap_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import openai\n",
    "from openai import OpenAI\n",
    "\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "_ = load_dotenv(find_dotenv()) # read local .env file\n",
    "openai.api_key = os.environ['OPENAI_API_KEY']\n",
    "\n",
    "openai_client = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a datasez\n",
    "\n",
    "def generate_queries(model=\"gpt-3.5-turbo\"):\n",
    "    messages = [\n",
    "        {\n",
    "            \"role\": \"system\",\n",
    "            \"content\": \"You are a helpful expert financial research assistant. You help users analyze financial statements to better understand companies. \"\n",
    "            \"Suggest 10 to 15 short questions that are important to ask when analyzing an annual report. \"\n",
    "            \"Do not output any compound questions (questions with multiple sentences or conjunctions).\"\n",
    "            \"Output each question on a separate line divided by a newline.\"\n",
    "        },\n",
    "    ]\n",
    "\n",
    "    response = openai_client.chat.completions.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "    )\n",
    "    content = response.choices[0].message.content\n",
    "    content = content.split(\"\\n\")\n",
    "    return content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
      "To disable this warning, you can either:\n",
      "\t- Avoid using `tokenizers` before the fork if possible\n",
      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1. What is the company's overall financial performance and profitability?\n",
      "2. How has the company's revenue trended over the past few years?\n",
      "3. What are the company's major sources of revenue?\n",
      "4. What are the company's total assets and liabilities?\n",
      "5. How much debt does the company have, and what are the terms of that debt?\n",
      "6. What is the company's operating cash flow and free cash flow?\n",
      "7. How is the company managing its working capital?\n",
      "8. What is the company's dividend policy, and how does it compare to its earnings?\n",
      "9. What are the company's major expenses, and how have they changed over time?\n",
      "10. What are the company's major risks and uncertainties?\n",
      "11. How does the company's financial position compare to its competitors?\n",
      "12. What is the company's operating margin and net profit margin?\n",
      "13. What is the company's return on assets and return on equity?\n",
      "14. Has the company been involved in any legal disputes or regulatory actions?\n",
      "15. What are the company's future growth prospects and strategic initiatives?\n"
     ]
    }
   ],
   "source": [
    "generated_queries = generate_queries()\n",
    "for query in generated_queries:\n",
    "    print(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = chroma_collection.query(query_texts=generated_queries, n_results=10, include=['documents', 'embeddings'])\n",
    "retrieved_documents = results['documents']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate_results(query, statement, model=\"gpt-3.5-turbo\"):\n",
    "    messages = [\n",
    "    {\n",
    "        \"role\": \"system\",\n",
    "        \"content\": \"You are a helpful expert financial research assistant. You help users analyze financial statements to better understand companies. \"\n",
    "        \"For the given query, evaluate whether the following satement is relevant.\"\n",
    "        \"Output only 'yes' or 'no'.\"\n",
    "    },\n",
    "    {\n",
    "        \"role\": \"user\",\n",
    "        \"content\": f\"Query: {query}, Statement: {statement}\"\n",
    "    }\n",
    "    ]\n",
    "\n",
    "    response = openai_client.chat.completions.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "        max_tokens=1\n",
    "    )\n",
    "    content = response.choices[0].message.content\n",
    "    if content == \"yes\":\n",
    "        return 1\n",
    "    return -1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "retrieved_embeddings = results['embeddings']\n",
    "query_embeddings = embedding_function(generated_queries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "adapter_query_embeddings = []\n",
    "adapter_doc_embeddings = []\n",
    "adapter_labels = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 15/15 [01:22<00:00,  5.49s/it]\n"
     ]
    }
   ],
   "source": [
    "for q, query in enumerate(tqdm(generated_queries)):\n",
    "    for d, document in enumerate(retrieved_documents[q]):\n",
    "        adapter_query_embeddings.append(query_embeddings[q])\n",
    "        adapter_doc_embeddings.append(retrieved_embeddings[q][d])\n",
    "        adapter_labels.append(evaluate_results(query, document))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "150"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(adapter_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "adapter_query_embeddings = torch.Tensor(np.array(adapter_query_embeddings))\n",
    "adapter_doc_embeddings = torch.Tensor(np.array(adapter_doc_embeddings))\n",
    "adapter_labels = torch.Tensor(np.expand_dims(np.array(adapter_labels),1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = torch.utils.data.TensorDataset(adapter_query_embeddings, adapter_doc_embeddings, adapter_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# setting up the model\n",
    "def model(query_embedding, document_embedding, adaptor_matrix):\n",
    "    updated_query_embedding = torch.matmul(adaptor_matrix, query_embedding)\n",
    "    return torch.cosine_similarity(updated_query_embedding, document_embedding, dim=0)\n",
    "def mse_loss(query_embedding, document_embedding, adaptor_matrix, label):\n",
    "    return torch.nn.MSELoss()(model(query_embedding, document_embedding, adaptor_matrix), label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize the adaptor matrix\n",
    "mat_size = len(adapter_query_embeddings[0])\n",
    "adapter_matrix = torch.randn(mat_size, mat_size, requires_grad=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/100 [00:00<?, ?it/s]/opt/dev/miniconda3/envs/llm/lib/python3.10/site-packages/torch/nn/modules/loss.py:535: UserWarning: Using a target size (torch.Size([1, 1])) that is different to the input size (torch.Size([])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.\n",
      "  return F.mse_loss(input, target, reduction=self.reduction)\n",
      "100%|██████████| 100/100 [00:02<00:00, 35.06it/s]\n"
     ]
    }
   ],
   "source": [
    "min_loss = float('inf')\n",
    "best_matrix = None\n",
    "\n",
    "for epoch in tqdm(range(100)):\n",
    "    for query_embedding, document_embedding, label in dataset:\n",
    "        loss = mse_loss(query_embedding, document_embedding, adapter_matrix, label)\n",
    "\n",
    "        if loss < min_loss:\n",
    "            min_loss = loss\n",
    "            best_matrix = adapter_matrix.clone().detach().numpy()\n",
    "\n",
    "        loss.backward()\n",
    "        with torch.no_grad():\n",
    "            adapter_matrix -= 0.01 * adapter_matrix.grad\n",
    "            adapter_matrix.grad.zero_()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best loss: 0.5144663453102112\n"
     ]
    }
   ],
   "source": [
    "print(f\"Best loss: {min_loss.detach().numpy()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_vector = torch.ones((mat_size,1))\n",
    "scaled_vector = np.matmul(best_matrix, test_vector).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.bar(range(len(scaled_vector)), scaled_vector.flatten())\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 15/15 [00:04<00:00,  3.20it/s]\n",
      "100%|██████████| 15/15 [00:04<00:00,  3.50it/s]\n"
     ]
    }
   ],
   "source": [
    "uery_embeddings = embedding_function(generated_queries)\n",
    "adapted_query_embeddings = np.matmul(best_matrix, np.array(query_embeddings).T).T\n",
    "\n",
    "projected_query_embeddings = project_embeddings(query_embeddings, umap_transform)\n",
    "projected_adapted_query_embeddings = project_embeddings(adapted_query_embeddings, umap_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x3264a9090>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the projected query and retrieved documents in the embedding space\n",
    "plt.figure()\n",
    "plt.scatter(projected_dataset_embeddings[:, 0], projected_dataset_embeddings[:, 1], s=10, color='gray')\n",
    "plt.scatter(projected_query_embeddings[:, 0], projected_query_embeddings[:, 1], s=150, marker='X', color='r', label=\"original\")\n",
    "plt.scatter(projected_adapted_query_embeddings[:, 0], projected_adapted_query_embeddings[:, 1], s=150, marker='X', color='green', label=\"adapted\")\n",
    "\n",
    "plt.gca().set_aspect('equal', 'datalim')\n",
    "plt.title(\"Adapted Queries\")\n",
    "plt.axis('off')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "llm",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}