cognee/Demo_graph.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d35ac8ce-0f92-46f5-9ba4-a46970f0ce19",
   "metadata": {},
   "source": [
    "# cognee - demo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd981778-0c84-4542-8e6f-1a7712184873",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## Let's tackle the problem first\n",
    "\n",
    "## Since LLMs appeared, people have tried to personalize them.\n",
    "## You usually saw that by people doing \"prompt engineering\" and adding specific instructions to the LLM\n",
    "## \"Become a sales agent\" or \"Become a programmer\""
   ]
  },
  {
   "attachments": {
    "82bccd2a-f1ec-4ddf-afc0-15586ce81d9b.png": {
     "image/png": 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    }
   },
   "cell_type": "markdown",
   "id": "4a9159db-1422-4756-b2e7-f0dc28e918e1",
   "metadata": {},
   "source": [
    "![1_GG8LmLk1vgxYW4QkivDE1w.png](attachment:82bccd2a-f1ec-4ddf-afc0-15586ce81d9b.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8e606b1-94d3-43ce-bb4b-dbadff7f4ca6",
   "metadata": {},
   "source": [
    "## The next popular thing was RAGs (Retrieval Augmented Generation) systems that connect to a vector store and search for similar data so they could enrich LLM response"
   ]
  },
  {
   "attachments": {
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     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "23e74f22-f43c-4f03-afe0-b423cbaa412a",
   "metadata": {},
   "source": [
    "![1_Jq9bEbitg1Pv4oASwEQwJg.png](attachment:df72c97a-cb3b-4e3c-bd68-d7bc986353c6.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6a98710-a14b-4a14-bb56-d3ae055e94d9",
   "metadata": {},
   "source": [
    "## The problem lies in the nature of the search. If you just find some keywords, and return one or many documents from vectorstore this way, you will have an issue with the the way you would use to organise and prioritise documents. \n",
    "## If you search  for an apple, you might get both the information of your last laptop purchase, and the information about apple as a fruit.\n",
    "## This fact makes it difficult to use vector databases and implies we might need another layer on top of them to have a semantic model LLMs could use\n",
    "## How about graphs? "
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "e2fdaa34-ee4d-476a-bc53-155dd39f916a",
   "metadata": {},
   "source": [
    "![1_bbDJqUbmOnNTm511KSti1Q.png](attachment:6ebdb7b5-f432-4e61-893b-80672bf0dcac.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e042cbb4-4bac-469b-bd4d-d98f861800cf",
   "metadata": {},
   "source": [
    "# HOW DOES IT WORK\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5b18c25-c981-40f2-84b1-1b7636600430",
   "metadata": {},
   "source": [
    "## We first take some text from the internet, in this case two articles from the Guardian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8a8942b5-91d6-4746-b35d-00f58bc16d7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "\n",
    "from langchain.prompts import ChatPromptTemplate\n",
    "import json\n",
    "from langchain.document_loaders import TextLoader\n",
    "from langchain.document_loaders import DirectoryLoader\n",
    "from langchain.chains import create_extraction_chain\n",
    "from langchain.chat_models import ChatOpenAI\n",
    "import re\n",
    "\n",
    "from dotenv import load_dotenv\n",
    "import os\n",
    "\n",
    "# Load environment variables from .env file\n",
    "load_dotenv()\n",
    "import instructor\n",
    "from openai import OpenAI\n",
    "\n",
    "\n",
    "aclient = instructor.patch(OpenAI())\n",
    "\n",
    "from typing import Optional, List\n",
    "from pydantic import BaseModel, Field\n",
    "\n",
    "from cognitive_architecture.modules.cognify.llm.classify_content import classify_into_categories\n",
    "from cognitive_architecture.modules.cognify.llm.content_to_cog_layers import content_to_cog_layers\n",
    "from cognitive_architecture.modules.cognify.llm.content_to_propositions import generate_graph\n",
    "from cognitive_architecture.shared.data_models import DefaultContentPrediction,  KnowledgeGraph, DefaultCognitiveLayer\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "14484e25-fae8-4306-b03f-dae91fe5d0aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_article_one = \"\"\" In the nicest possible way, Britons have always been a bit silly about animals. “Keeping pets, for the English, is not so much a leisure activity as it is an entire way of life,” wrote the anthropologist Kate Fox in Watching the English, nearly 20 years ago. Our dogs, in particular, have been an acceptable outlet for emotions and impulses we otherwise keep strictly controlled – our latent desire to be demonstratively affectionate, to be silly and chat to strangers. If this seems like an exaggeration, consider the different reactions you’d get if you struck up a conversation with someone in a park with a dog, versus someone on the train.\n",
    "\n",
    "Indeed, British society has been set up to accommodate these four-legged ambassadors. In the UK – unlike Australia, say, or New Zealand – dogs are not just permitted on public transport but often openly encouraged. Many pubs and shops display waggish signs, reading, “Dogs welcome, people tolerated”, and have treat jars on their counters. The other day, as I was waiting outside a cafe with a friend’s dog, the barista urged me to bring her inside.\n",
    "\n",
    "For years, Britons’ non-partisan passion for animals has been consistent amid dwindling common ground. But lately, rather than bringing out the best in us, our relationship with dogs is increasingly revealing us at our worst – and our supposed “best friends” are paying the price.\n",
    "\n",
    "As with so many latent traits in the national psyche, it all came unleashed with the pandemic, when many people thought they might as well make the most of all that time at home and in local parks with a dog. Between 2019 and 2022, the number of pet dogs in the UK rose from about nine million to 13 million. But there’s long been a seasonal surge around this time of year, substantial enough for the Dogs Trust charity to coin its famous slogan back in 1978: “A dog is for life, not just for Christmas.”\n",
    "\n",
    "Green spaces, meanwhile, have been steadily declining, and now many of us have returned to the office, just as those “pandemic dogs” are entering their troublesome teens. It’s a combustible combination and we are already seeing the results: the number of dog attacks recorded by police in England and Wales rose by more than a third between 2018 and 2022.\n",
    "\n",
    "At the same time, sites such as Pets4Homes.co.uk are replete with listings for dogs that, their owners accept “with deep regret”, are no longer suited to their lifestyles now that lockdown is over. It may have felt as if it would go on for ever, but was there ever any suggestion it was going to last the average dog’s lifespan of a decade?\n",
    "\n",
    "Living beings are being downgraded to mere commodities. You can see it reflected the “designer” breeds currently in fashion, the French bulldogs and pugs that look cute but spend their entire lives in discomfort. American XL bully dogs, now so controversial, are often sought after as a signifier of masculinity: roping an entire other life in service of our egos. Historically, many of Britain’s most popular breeds evolved to hunt vermin, retrieve game, herd, or otherwise do a specific job alongside humans; these days we are breeding and buying them for their aesthetic appeal.\n",
    "\n",
    "Underpinning this is a shift to what was long disdained as the “American” approach: treating pets as substitutes for children. In the past in Britain, dogs were treasured on their own terms, for the qualities that made them dogs, and as such, sometimes better than people: their friendliness and trustingness and how they opened up the world for us. They were indulged, certainly – by allowing them on to the sofa or in our beds, for instance, when we’d sworn we never would – but in ways that did not negate or deny their essential otherness.\n",
    "\n",
    "Now we have more dogs of such ludicrous proportions, they struggle to function as dogs at all – and we treat them accordingly, indulging them as we would ourselves: by buying unnecessary things. The total spend on pets in the UK has more than doubled in the past decade, reaching nearly £10bn last year. That huge rise has not just come from essentials: figures from the marketing agency Mintel suggest that one in five UK owners like their pet to “keep up with the latest trends” in grooming or, heaven forbid, outfits.\n",
    "\n",
    "These days pet “boutiques” – like the one that recently opened on my street in Norwich, selling “cold-pressed” dog treats, “paw and nose balms” and spa services – are a widespread sign of gentrification. But it’s not just wealthier areas: this summer in Great Yarmouth, one of the most deprived towns in the country, I noticed seaside stalls selling not one but two brands of ice-cream for dogs.\n",
    "\n",
    "It suggests dog-lovers have become untethered from their companions’ desires, let alone their needs. Let’s be honest: most dogs would be thrilled to bits to be eating a paper bag, or even their own faeces. And although they are certainly delighted by ice-cream, they don’t need it. But the ways we ourselves find solace – in consumption, by indulging our simian “treat brain” with things that we don’t need and/or aren’t good for us – we have simply extended to our pets.\n",
    "\n",
    "It’s hard not to see the rise in dog-friendly restaurants, cinema screenings and even churches as similar to the ludicrous expenditure: a way to placate the two-legged being on the end of the lead (regardless of the experience of others in the vicinity).\n",
    "\n",
    "Meanwhile, many dogs suffer daily deprivation, their worlds made small and monotonous by our busy modern schedules. These are social animals: it’s not natural for them to live without other dogs, let alone in an empty house for eight hours a day, Monday to Friday. If we are besieged by badly behaved dogs, the cause isn’t hard to pinpoint. Many behavioural problems can be alleviated and even addressed by sufficient exercise, supervision and consistent routines, but instead of organising our lives so that our pets may thrive, we show our love with a Halloween-themed cookie, or a new outfit for Instagram likes.\n",
    "\n",
    "It’s easy to forget that we are sharing our homes with a descendant of the wolf when it is dressed in sheep’s clothing; but the more we learn about animals, the clearer it becomes that our treatment of them, simultaneously adoring and alienated, means they are leading strange, unsatisfying simulacra of the lives they ought to lead.\n",
    "\n",
    "But for as long as we choose to share our lives with pets, the bar should be the same as for any relationship we value: being prepared to make sacrifices for their wellbeing, prioritising quality time and care, and loving them as they are – not for how they reflect on us, or how we’d like them to be.\n",
    "\n",
    "\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "50d5afda-418f-436b-b467-004863193d4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_article_two = \"\"\"Lee Parkin had been the proud owner of his terrier-spaniel cross Izzy for nearly 10 years when he stepped out for what would be his last walk with his beloved pet.\n",
    "\n",
    "He was walking Izzy near his home in Doncaster when an XL bully pounced on her, mounting a 20-minute attack and ultimately killing the dog in front of Parkin, who desperately intervened in vain.\n",
    "\n",
    "“It was such a nice day,” he said. “We were walking a normal field where I go, and I saw this dog loose. It appeared wild by its demeanour.”\n",
    "\n",
    "Parkin, 50, took his dog through a gate but found himself cornered. The dog approached and started circling them. And then, he says, “it just grabbed her”.\n",
    "\n",
    "“I’ve never encountered a bigger, stronger dog before in my life,” he says. “I’ve dealt with dogs attacking another dog before.”\n",
    "\n",
    "Lee Parkin and his dog Izzy\n",
    "Lee Parkin and his dog Izzy. Photograph: Lee Parkin\n",
    "Parkin did his best to fight the dog off. “I smashed both hands against it, I twisted its balls, I kicked it in its back end. It did nothing whatsoever. I just shouted for help.”\n",
    "\n",
    "At first there were no other people around, but “all of a sudden” there were about three other men, possibly including the owner, attempting to remove the animal.\n",
    "\n",
    "A passerby gave him a lift to the vet but Izzy was “bleeding so profusely” he could hear her choking on her own blood. Her bones had been crushed.\n",
    "\n",
    "The owners were handed a caution and the dog remains alive and living nearby.\n",
    "\n",
    "“It was dangerously out of control,” Parkin says of the XL bully. “I’ve been brought up with dogs all my life. There’s no place for this type of dog in society.”\n",
    "\n",
    "He welcomes the incoming ban on XL bullies but says he does not think it is enough and it will not work.\n",
    "\n",
    "He believes the majority of XL bully owners will not be fazed by the ban and will keep their dogs and ignore the new law and regulations.\n",
    "\n",
    "“The only effective thing that I’ve seen the police doing is turning up and shooting these dogs, which is what I think they should be doing,” Parkin adds.\n",
    "\n",
    "He was left with significant mental impacts from the attack and was subsequently diagnosed with post-traumatic stress disorder. He received counselling but still struggles with walking dogs, and often rises very early in the morning to avoid other owners. He also carries a dog spray.\n",
    "\n",
    "Marie Hay’s siberian husky, Naevia, survived a savage attack on the beach in Redcar on the North Yorkshire coast by two XL bullies – but has been left with life-changing injuries. Hay, like Parkin, has also been left with mental scars.\n",
    "\n",
    "The owner of the dog that attacked seven-year-old Naevia is facing a criminal trial next year.\n",
    "\n",
    "“We must have only been three minutes and the guy pulls up and basically he’s just got his dogs out of the car. They run down to the bottom of the beach and one starts to run towards Naevia.\n",
    "\n",
    "“The owner turned to me and said: ‘They’re friendly, don’t worry,’ because I must have pulled a face at the size of the dog.\n",
    "\n",
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    "after newsletter promotion\n",
    "“But then the first one jumped on Naevia’s chest and just started tearing into her.\n",
    "\n",
    "“So she was screaming, screaming like a baby. And then the other one just came out of nowhere. The attack lasted about 12 minutes.”\n",
    "\n",
    "An American bully XL with cropped ears. The practice is illegal in England and Wales, but it is still carried out by unscrupulous owners.\n",
    "Perfect pets or dangerous dogs? The sudden, surprising rise of American bully XLs\n",
    "Read more\n",
    "Hay said several people attempted to remove the dogs but were initially unsuccessful. They attempted to lift the dogs by the legs and her 20-year-old daughter was bitten, as were other people who intervened.\n",
    "\n",
    "The owner eventually placed a harness on one of them and put it in the car, while Hay had to walk the other dog back to the car on a lead.\n",
    "\n",
    "Naevia lost 83% of her blood. “She was bleeding to death on the beach … she had hundreds of bite marks all over, she had an incision that ripped her chest open.\n",
    "\n",
    "“She had to have between eight and 10 operations. She’s now in kidney failure because of the stress that it caused on her kidneys. She had to have two blood transfusions.”\n",
    "\n",
    "Hay said the vet bills were more than £30,000, which she has been able to cover through donations on a fundraising website.\n",
    "\n",
    "Like Parkin, Hay struggles to go out for walks now, due to the stress caused by the incident.\n",
    "\n",
    "“I carry a full kit that I’ve made myself, it’s got a rape alarm, a couple of extra dog leads … I’m constantly in fear.”\n",
    "\n",
    "Hay says she is “100%” supportive of the new ban. She says she accepts that a dog’s behaviour is partly down to the owners but is confident the breed plays a part too.\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3ae099a-1bbb-4f13-9bcb-c0f778d50e91",
   "metadata": {},
   "source": [
    "## Our goal is to create a semantic representation of the data and split the data into a multilayer graph network containing propositions"
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "id": "e9928ff6-4d82-4d87-9c5a-bf80a50bfa71",
   "metadata": {},
   "source": [
    "![Screenshot 2024-03-08 at 12.06.13.png](attachment:5962bf80-e424-438a-b7e3-50c13810ecf4.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "785383b0-87b5-4a0a-be3f-e809aa284e30",
   "metadata": {},
   "source": [
    "## What is a semantic layer and what are propositions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3540ce30-2b22-4ece-8516-8d5ff2a405fe",
   "metadata": {},
   "source": [
    "## Multilayer network is cognitive multilayer networks as a  quantitative and interpretative framework for investigating the mental lexicon. The mental lexicon is a complex cognitive system representing information about the words/concepts that one knows\n",
    "Article 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a21f1cf-ff91-43e6-bd05-39e5ee885790",
   "metadata": {},
   "source": [
    "## A proposition is: Propositions are defined as atomic expressions within text, each encapsulating a distinct factoid and presented in a concise, self-contained natural language format.\n",
    "Article 1"
   ]
  },
  {
   "attachments": {
    "313b90cc-03f2-4c01-acb9-382f6b1d41c8.png": {
     "image/png": 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"
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+8MMgnT516owG0O3uW548edK1G9Q51EQIjzriiXk8XhdA+HPDIBCGWDfMpw4ZvdII0Kn6zpbGFoLCMzp7XrcPiQjSEOyZlveLcGioUS/A4IbOmYadX/e5s84/U5V01L7x99OX+OHe6wkSF24x8TQ5i2voj8cSHMkbz2DX19fr7sEGXWLwSEq856e6kTQv1BQ5nSqdHR2oJ4n+eg3BMKOk+vzR+TNlDgZ+IOGlebjBHtzQtwVTzPDwyPi9L2MzivwadxyvK+Sfeogd5YxFeNQryuKZ06dc3QVHX7a4R+rvJaO1tXWSNEeDtEC4rn7BiH8DX0cg16iP+PqwePHCcbLtSbdrf6UuxZWyQBvt68uQ2txIVSdap8D7YK5/BAKJvv6/ccjhHCLgO1VPMiDIdKz8IL6e7EGOeYf7fD7nOmCSBbnl5xtc/HnjG3pIj5d8YJdOTUzn0pj7uH2njv9cbmScqJMOSDXuSAe6tFE6ooU33BOvJ9o+/qt9JV0eF9Lm8+AHGOQHbFDFABekf80LWpwd95BG3gfzTgQgCvzADeLgSQJSbK+vCiGgXPANkFyDP4ZvQbm7Hg159QSJvFNfeC4WR1195j2YMUjjSvlq71w4rqfspdBg4zG+HnG63vMUtSeRtJlvjEpX1NakXX2hfcFQbxiAUi76KwsffTuLUARDfZlvbatLWPgzKwgEdY5ZgTEEciMhQOeKVArJBY0n0jsIG50mZCMu9aQx5uf19nDT3LzA2WHvJVXcQ174ce+nHMEVAk2jjT2/xorOHu/QscRgTxq4YiL7yL3X8eOdJ0u4gWiPjhYVV9ZJtCHh6NlCUtEHrKurd3nC7dUwSNkhMEj0SBvpQuWCPHi8/TcgfeSPDi2YmSHgy4wvH9735LJJOXRkQd+Fewgj3wTS4Im393stXaMBZEH1oMaVM4izrzOFQjTAZaBGnaL+YpDie9zAIpgbAwG+efx7+3ad3LdViDZuINz8MAOqLyxGXtDS6gZl2FN3grk+EAg9zvXxHUMu5ggBL3mCxLE4aMmSJU46hzQXwga5hWxwT+O4bNmy8c41rpsab3h9R0ySfUc8+X7ys3fnr7zHxJ/j90jKvInHHSc7jY1Nzgn+yANkAgMp8tI4J7nW1HXn4iUuLtxAYmfTgDGGdDA9ym/58uXnEWI6Kwi0z6PvoLw/F0D4M6sIeKwJ1BNqvhV61L4MM7tCWWEww8CLcueldLOamFkODMkg0/DkiwExg1/KHPmirFG++LW3t42XuXg9imMzy0kLwV1DCMTLQbzce1UpsrJAgy/fxlHuuOeH8IXyxuCMZ8KKh3cNwXBDJzWQ6Bv684fMT0aARg7CDNnk/syZ025BCY2bl3LSWLKyngYQe08wCOtaagTjaSVPvhMg755sQyii3SvSTlqNaggDBcg0BIq8QzbACv/xMCdjG38ualsvpDNgCplh6pPOhPgg6YTJfdxMN+y4n3A/uwjwDXw9IGQGip4gcJgG3wySjYSa+gHx9O+vxvcjbq/2Q72G6KObXC6XbFjqKQzMGAAwe4SJ1wOer0aaifdaNZO/Nc8ew8n35NG/u1bzO510k0efT/oNbzzR5h3CCmbeGMgxqKN9pS6BGT/qUjDzE4HwZebndwmpuoIIIEmDHGK4hxzS8dKhtmgKzkvX0IvD0OhB8nzD6Cyv0z8QpkwmWslOo++ldeBDQ08DDzlhhweINPhBirGfbPADueIdbtjP2OMMaQdPSFdc4jw5jPn87PEgjegTewzAhB8GjDjxDYMd2GHw67HxmLoXlXf+fr5d6dx9XWDXCQg0BiJAfjDoUvN8pQxlCpzBkXiR+GEiXCP7bFbEWemljpP+uJT5SqXzWogHzPhhKK/g6u8Z+HqsfZvJe8igrwu9mlWijBMGM0zsmoMfyoQvH4Tj9Yex82tJCIPf9WoQFvhZPYQRDOTAiTILHtwPDw8ZCxa5BwvfXlyvmFyL+QqS6Gvxq82TNFOxX9vxmnX3dNv27dsd+Tmwf7898MD3bP2GW+y+++5zUp7XX3vNzkgV4p577hmXcF4oCzQUnnBcyM2l2kPS+PmGn8YeYkg+aOA9kUNfjTTgFhLpO45Ljfd69UfDD5b8kJpwpfGnQwU7cM2NDFuNdiYARzpIcEbHOZWKdjLge0Ng5juJIZ2QLfJEeYB8kV/yiiSTZ7bBQppOOUIqS56feOIJJ62FNOzff0AY5CyhvLcJg21bt1l7W6s998JLtmL5MjdAYZEf4XIiGyfFUQ5RI4Kgcg9+dLzosQ9IepWRHm/UESPxi7ZAZI9o0qn/V80we0H8fHN2+aiqihbDInGjrIDXbBryC26QeogGdRu9+bGxyM4TNuLmW/Kb7yZqr5COz43ONZgRBwbsMODnF5CCVa8GumNyQ7keVlmn7KOeAMa44ztSLn098N+BK4ZwuefHN2CAnExGA2/eP/vMM+o/elxfwf7tD/7wQTt86LCLb+vWLbZly1bbu3ef4hi1jRs3ujUbhEk7E9cr9vkgLcwy+PiJ41oyzJRQtxOJaodXUWtWPHbkmXK9cGGn8hhhSjt6IxsEXLSz/vtfDSwCib4aqF8ncdJw/j9/8idGYwdBprJ/+9vftj/4g9+3++5/n61bt85WrlypBnbY/uqv/sqRp61bt16wwEPGv/HtJ23HnlNzglBDTdKK6itG8jTsSKs4qUoVUP9KanhT2vUCQ7dyFfmHS8O19CfqhqMUl4UrDTyNO/1oddWYtTZmrKu/ZK0NSTt2Rod8VDDHx/qVzfav/8efnRfZpfzyg0jQGdPpQ4ghXIcPH7ZV2lMa++PHj9uKFStcmiEVDABoxOnUfYPOAOPJJ560P/7jP7bf+e3ftmdEFv7x7/7O1t68zooK78iRY/ahD33I/v1v/qa9+sor9tQTj9vXf+d3XNwEzEADQ1o8WRjODdu3nvyW7Tu+R/YpRyx4z31tda3lCjkD/yotgkuKUOfVIV8VowIxXodUBkgTdQyMRkWG0m4WZ3Y7/4zIHOWN8KnbYOy+xXhK4qX0qqAy40gFl9UtrbF/+9HfErGaOOFvxgHFPFBeozKTlAoBC0Sr3CCMgRqDMQYeEGTcYLIq/9QJTA2LekVg+Y5+4MjA0kvyueIPYu39Q7hxz4+ZPOy5J55Dhw7Z7/3vv2df+cpXbHBg0P7oD/8Pe1L1ZLkGj2c0CP3e9x6wr3/96yLrA/YXf/Ff7Pf/4+87aS3pYzAJIaeOMjBj8Mn3fvjb/2zHH/6hqTm/ho0vqxMDYUHmBiS0ReCbbtBJlZohLJzrcteEsC9JYHEjmaIwqdl6u/30f/fzbmB+tfIeSPTVQv46iPeBBx5QQ3jQfvVXf8URCRbbfeNv/9bqJcHYs3uXiMIRRzaWr1ju3j/++OPu9DSIyWSDdOGNNw/ZPz10wI70r7Wx5Pn6sJPdT/e5oTFtQ70nrZxs1yEcSauuSUmCN6oGabohBHfTR4DOVh1muc8a1Xn29Z7fkzU1p2VXdN+hLfOWjfSdsluXFMalWHTCV8pADOjMvVSLDplpZKZS2aHEd9QQZNKF7i8EAKIBmcYvxpNd7r0qA/eE+5d//Zd2y8ZNtkUDx8dFkls6Ftr//Z/+xHX4f/iHf+jsRiSZ/uQnPmFf/1+/bq+/8Ya9//3vd/EhBcQQp9edPHLyiP1w1wM2tESr/RsjYuMcTfpTW5akd6zK+lKRitLi0WV2ouqotRXbrW+4z0YbpEKCdgk/DlNUVhIKbizK0qTQ5u7xvHT2KR4dQtdQ1h9xgYEa5XGq3knpVAnTINfd2Ir8ajucPTB3ibxaIbM72t6U3ZRbb8P3IcmPyuF0k+PLt5cSU74hmai2cE+ZQurJqZWUb3/6JeEjdfYGt97EZw8o/54o897XXex93cB+KjfYk75//MdvigQX7MMf/oibsXni6aftX/7Lf2W//Mu/bK9p9vK3f+vf2+s7XrGf+dkv2n/+z39mTz39lG3SyYLUDfoQwiYu4iZtDG53Pva4LX3oMauVtKR7eZu1HKmo8ijOhpL26E9pDYsOX8pX6m9W6RjUgL9OdqOyK0PM5A67GgkDeB7Vr65il5UdJq/ZHsIhPMkJTMJ1G6nYjciO5yqFPaRw5jq+/kbN+lRJvbAv2lKP9GUq6bwe8jcVngPCdY/KcF9ri5sR8eWBvF9pM1UzdaXTEOK7BhFgRPzkk09aR2eHrV692jVmTz/ztJ3WNPTPfvGL9sILL7j3SKghGhvW32w7Xn3FTUdNRaKHpCP76DO77eTwJitl7hYilzPdC0FCBzNtvUOSmjQct2J+hY2INIwMiD2r8bXZFYRdg19wtpNcEqy9Io/oxCZtePSoldMrYpGUrYdthtXijEhaeC6RtdV1u23z5vfb0aNHHTGlU6RzjXe8sQBmfEtYGDpaL12DSKCPXZAEq0nEmG3+Bvv7HLGgXHopGuQhTiCQdHkTJwnebvL1xIkTtmfnTvuN//nfuQ6f96dOnbD/8Lu/q+dq2/HaTk1P32LNTc22eNFikZome/nll+3ee+91aZgcHhLEH/zw+5bvGLbqOyV1rb7wKFDa1eLHOrmxwkLP2Ul3P5TvtSqJb5J1OuGwP23JUlKEelQEWoOD3mobaZcajoJNyL5cdeHwJ6ftUp9JJz/SWd2lhbx1msru1oEXhxba2bYT1r8iGgQkSiJmLk2SLg9p+nYka0UNBIrVUnUZOmZZ5ee6Miq2idOS6B6ts8/c9nmnuuAHUpPz6ckyV8o45ZsBHKpF7CzC1nyRikMkQW5pYe/0aPrbr/EgzOmU6clxX87z0OCQK+8ct90q0v7WW29Zo6SrH/jABxwp5hTBP/q//tgNWpdpsd3tt2+z55591r785a84ku/bCAg0P/L+4He+ba2PPm6fHFKZEoaDJ7utPqc9mquSdrYma82yrxktW38agqwZGxFjhvmp0fMH+y5fbuHzpBxOaTfJDY/R8ofoxVRhT2U3ZdhTpWuK+LqHxi0HRfhLdRlrGhy1nIgmXV1GGGBoDfU6MpcT35XO3xTxHdEg4a3WZttw211uNsK39T57V/IaqMSVRPs6iosptIMHD9oS6WoinUOC951vf0cNYb2I0WZbuniRPfH4Y066RyPXoQMJenr73NTbVDDseette2bXkLrUtXp9KQS6qMaUE/5oKqQHmRhRx4BeM7q4K2JRUuRxE8zlI4DaRr8a5qiDTiaZtqfhlyrBeZgTE7hHP9ynhnbbB7evdxIwCAJlhDLEtDIDNBpFyMBMDX68P2ZGKKeENaDpYsgzBlUTprExLDBrbY8WjDJFjRrG5Rrio26UE6lxtQ/sEH4VRNrd0eSqM6QTgoO0G0ng6dOnpXc69ZTszr1v2GtnXrXkBqkivQuB9mlHWjvZlMUsSnURpqV6LRITgR5L6xvmpRpSE3W0qVzast2aKVIVSUgMlx4R4RKJnWtTaNBuHqWUtR7vsIXdS23pvrUizNE3ShZSlu2pdukp1mlxVdOII9CkyednrtN3JcNPFFSL3ja7tWWbLVq4aHwHHNJAOfL1g4EV5ZtnyhL3kEnqEtJkpNcMCrmP9Oaj8g7RvtrmtHY96lV/cJNU/srKE2sF0kqrF7CQRtYB+ENOVq1a5Q4zYSvCyQZM9u/fb/u//127X2FCoDH1A5E6U1rEubNfg09JjjE5xVNWG4CzkwtqLKfizT01YAraKttrx9QrI9mhaLEyJDonCTVmRAOJ/loNvnU/81bVBTFv/vCd3qyXwOO2rbZ89Wqn7uYHVVcjkYFEXw3Ur4M46fxHS6OWEjNAivH22/vt6aefsR7p2f31X/6Fm47bu2ePvfjiC+490o+yajAN/mSDbvU3v/+cHe9fJjUOtgCKV3Xu+WF89Y/bId5E6sxiKj9klX5YuUUdyzvVRibCIjwfDtepwr4UO8LFxP1GNhNx+3fYv1vevDufTtzPlh1hYeLhRTbvTBP28XTih6lDkSxUBhKQXvSI2+Vq8h7Sk9Muol08YBsWddm2LRtdA0hHSadJ5w+RpTxBqNF7nKq8kJq48W7oTCHO/CLSOkH+IOpeRQLiXKuDZIiHOIl7tiVx6Gr6xXSktaQOvK2tw/7Nv/tN+z3pdn7+85+zV1560R0ZTdzZbMZKkg75AUA8f5CjHzz4PetedtqSHbPTZOtzOQJNPKP1OhZeP0w5UxZJFfkQdJBoSDW6HslcJK12jmbpT1mYjByUNFqzQ2UNDFIjqrdqH44uPWDdi89Y80Edwax4y1ntYtKsI7eZI1e6yhlfFmcpIfMpGGWt2FO2lu4O27b2NquXUMKXW8o0xPmMZvsgyzz78gKJQM8Yssw9g0FPlme7bM8GXOSDtKdU96o0oF20aJFT62JWCsNuP3/6p39q3/3ud12eOaXVpPvv63o8DSMjOXvq4Yds/d63baEwmVw6eI4PKjtGVDcLarNk36ArNLMkwnmuvtqGJaXGDEma63sTZ6E/Gr762/PusZ14M9Gi4jiKJfJGq+ndvdOPfzPhHxvfOsfjjkKb+Ds5rOpKUA06KKh+OBoc0/mmJHmnRTynLJK/a9WckwrSLi3EXnXHXdas3bNYM3I1y/jVH5Jeq1/yBk83+p8dIgW9/QMiTyV7/vnn3JZlX/va16S6sd5Yaf3n/++f24MPf19TdB+UlKTXqkUUfIcQh+8VLax6ee+wDZVutUSayk3TQWPmmwfuJ9vJSnbJhCSNxuIXSDOLsWgm4v5wF0lHuYveExbuvOGen4+DKyYer/cz2d1UfvGHPemIu9ejs+M9afI6wLiL28XTf7E0yesVTmcycUIEUQvvCsutMLrEEWhScXEjHUaR79b0Dtu+sdGtMqcc+c4eiSw/DI2iJ7cjWjAzqOlf1IK8xIEOGDf8kOBChpHmer1N7L1UmXsI7ZUyxMehPKNaTT8oQo9B+t3ddUpT1H9kWU2x73v7oNWIyGe1YAwydPZslxbi3iSdfZSUJwzvdu5/w148+bxV35tWZ4+0nzI1N6acVnnjJ1NWXBBqR7izIrr5iFakh7Wn+FDGcq3ayhBie4lmdLhoRx86YS13NFvb1gWWb83b8eaDClOUAeIuybRTK1F2S9l3Dr4vMdp57Q05QGJ32tZk1tmyjkW2QCpHlPXTUs9oqSyeY7FfVKajo+25x/iyP68zWEkcdRmpMzraGUnM77zzLvvGN/7Wfvd3/zf7zGc+a7u0puapJ5+y3/iN33B57eo6YxnVoclqLdSPffv22dFHH7NfHik4/eSo9EYtL9HRsmIgtNIcHr9CTBsltQW9MWHcOpy3lMLDHJe0eklCCyz1iLto+TlzaNF74oCu06JhE7XeUfiEN/m9d+vTQDikhSth8C8Ke6J2x91M2CrwScbHh7UPj/h8XkGiWgR6jG035YaWsJjXLJSuZ6ozViOBWK36cNzjD0P6yTPpjVIXhe3TTJhRvB6DyB+2E2kgpOg94Xis4mnDDuPzerH4cL1Laa7evMmWr7lJ6nAT/YcL6Cr8uXI9y1XIXIhy7hBA4vGeu+6y73/3O8biwnNnz9htt21To/evJRFpdlOLx7TQY7g/7wj1gQMH7OabbnYLtOKp6u7usYcfe9oO922yRAa9U6pvnFDimgrq7ZIiV9p2SQunSqVGDbCX4KBifHNJGBBUrlQ7f897b0eYPlwfZ9QsTMSFv7iddyfrcb+XSoYnp4kwp7KbHD/P07HzWPg8Xl4602lWfqF+oMHK2GIRaNIrFMZI82TjcfJx8ozRoKd8ypa3nrZbN97pBlRxvePITfQXiTQ/jN/GCOkbkiiINNJZyAUSrLY2P3iy8/SYPbmIQryyf1etWmXNbe327PMv2P3ve59I9VK3s8DB/QetpKnrDj3/0i/9kq1cudItwD158pT91E99djzPPrX9IuEPvvCA5dcPWdWCqLv172Z6pfN6t86Y8Hwn6typmEFmndH9aFNEoou1kiIy+6B3qHpkBrKWl6SYKpHQ6sTpEuuUSHJqSAODt8fsmAYYDatqrX5FnZOADxwesoFDOsxHz/XaoSJdk7ZCf8GwL/SMWtPNDVbToVkLLea6nkwin7Da3gZbfctqETvaOg5BSkvlqE3XaHFhfOHftZp3SPTatTfZSy8+79Ss7rjjDvtN7VSD9PnP//zPnUT9Cz/zBfvUpz7ldF5f1/qCm9ZvOG/RI3lnxmrHM1pwuHevdTgd54g8elwovRA0SoknbFwhaxBCbyjmLAT0ZnXvoCORqHqcqKu1RVKzqlbZZvFhXlLcvSvabOXbp601r/ZInuIk0RPCqJ0+n7zH0xC1kglJvCdIuo+fq0+f9xN/N/net/bez2QyO5EmnaBIxJJMc6nXIgj84m9ENyVd6/Vi/4IGy6mP33j6nOp0NHD3YcfT4+3i7cqEHamMMH43O1z59/4at4vHd1ZpfHZZp22+805r1QxmbWUBNu6vlgkk+mohfx3E+4lPftIe044br776qv2LX/tX9uu/8W/GJYlIDNiBAEnB7t27HZH+2td+8TxJNITo1dd324Ov6QSx7B3qhKnOVG3Il7/3QGEf2RWLDbqncno73/hx9Q0j7zDYeXeE6w32hIcdfvxVt869v8bdXThNuI6Mj8vHj+1ku3iavLu4nU8LdlPFP127KEXvjH+qNMXtfPyabk0Nirg2qUP3TQXpBS+PM/58OrHjHuPzdf61Of2S3X6zOiWRX7/jReR+6r9+2pqpanbPQPUHaTUqIHSgRU0LcxjMfDNI2H/u537OvvnNb9qxo0fcjgO/+Iu/6OoDgwAvSWQg8J3vfMdJrrdvf4+z93nh3Wtv77ADXfut+gMZIcp3ubCZiiTH7XxH54nyVCHhxr+X7Fk1BN3Rd5Lvck3lu+qT+0WIybx2v+mttaGFA27RIskdY+uCeFFRpD68UrJkuT4R4wND1rSt3g4+dtza7tbCt6yk9k9oseeqGtv/wGnr/Ik66/hAqx366+M2elLrHBrU4e/K25IvdFq2/eLT0j6+eH4vxy4ezlT3MwpbxExLN2wsJYxFmpN7quzWqm22ZdVWVyb8QHK2tribKr1Xw46Zo89+9qe09eOT9sgjj9gnP/kJSaA/Y/ffd6+d1rqIhroGW7hooZuN4v3Jkyfs137t1xy59umlb0FlsEs7cnxWaoSeyEbyVu8qukatkm+bIrvJ7nzr5YsrxJPiu3wwWqdQ0oCtL5uyvPSMd956h3UtPm3bn37FGoYlsVaQxO8N9/4JEujjIkzsfRzRsJS1iN61D+HSrvE8cE86vF38nnpOWqpHInUPWpZ8XbWVC8w4jdqJdcvs8C1bLPHYE7b+6AnVZ9+OX1q6LtcXeShrAPOMZrPrN2+x1Wtuduuv/Czm5YZ/Of59z3g5YQS/NygCq1at0mrpLzvpIA2an4oHDkiCX8yCfuiHP/xhrbC+w027e7jQef3x03utb+wmVecFsqYhUXOkOc1ysU9haFyaZqGXqtCYqrl23BjT1BN2CVOjqdOvklUQapEojZblIXKrv849V4Xh/DtS55sTT55pGLyfqRox7843e969fyaCqfxhfzmGNMWNjy8e14Xs8OfdeTdxu3i4U93H/UpCkDznSHSp7Bfc+cY07i6e3skY+zi0K4SdtGV1e+zWTe9309R+EZF34a8MrtCZhECwGBD9e+7RfePnVTog0PxYkATh9OTUh3M1rzTun/70p637XLf1SeUJ0jDVdDu7g2D/pS99yZGmeJqpH0+/8qS2tOu1sTa62Qky6+/9FX9R9zxxjRNi/w4773byvXfjr1P5d55jf5A6F7SrBga95kJDdDJhclSEUKKtYqPqstRCklos53WZffj4SWgHteY19bbiy0vs8N+LJB8tWfaujFQ8miy7SiojJ3V629va//q2sg3sGbK2jTrMZrP0fpWPZDYi/IQ3VV7idsTl450qXxez8/69u3jYU9l591z9e2/HM/+cUbNWNagdNLRgMtkv/e+3Urb+TiSuC1xZjxxdf3/pH26//Xb7+a9+1UYqdZzBcJsW+fLzhrpPG/ClL33Ztm3bdt4gMyf7vc89a8slhW6rkDyI4eUYvkr0mxhMUtYINyHpbVVxzA4sW2JDDS22t7HZGnv6bfPLb2oxI+oKkeiAFMSJVTxNhM17frSkXKeay5P1JRkfvi9zpMkb7EiLt8MthjRApRsGdBCUrl0t9XZ6+Qo7W99kr9+2xVoG+2zRWZ2a6FzKwVUyJ1VmXljSYdvvuc/aJUThEC/K0dU28W99tdMS4r/GEIC0fFLSaBq6CxEisrRlyxZjK6O4PjRE6bXdB+ylvVqgmLhVrqjKaliKkjYe/wcbHdijhihvmSU/Y1W1K23gyDe0rkTbclVp26Ya6eJ2/bONFUQuarQ6d9nXrJg7aaXcMatd+BmFcdKGTj5k1S3vtar6mythU9l8hfNE0D9HcUfveUczg138Xo/O4Id33i+W3Mfd+veT7XDLOx8+95iL2UWuor8+/gvZ+XR5d/4Z99xPTpO34z0S0rIGQ0f0TZtFnhtFZlGXwc/kcEizT7cP01/1ajyeyG6sLH3F0cel+9hsa1Yu0YKpCTKMa8oDRBhCyaCLxYEMwiDNDNAwENG4qavspIE/FiQh2eY3Xww62r+iPdTJ04UaeySMSKxRayF/5BW35AkVqH3n9lr5nqIGCBHx8h1ZmkV4kgajTsFWdWNabMe/1LD0iGvBPDJRxzkhUfb+eTvVPXa+A64EMe0Lfgt1kZ5PKaNTAdNiiCrq6UGpbRT1XTMVgi1LpNwpzTxlqqusdl20mDRZJ/sh7eF7XAdo7By0ml4NjvW/xJRzbdKWfWWR9Tzfb30/GLDqRfK3psZSjVGZuFBefOKn+3623RG/DxNcMUjsM8Papi+jbfpqdUJrvbCSkKCwq2y3N9xlN6++SeW+0UlhnYfr9A99xld//quu7qOqMpWhTrDtHX3NZNWvo5rhOa6Z0A/19FpG9SZqJaYKZfp2EOZIYnv+wAw1g4hIl7UdY5+976kntE3koLbQK9he9X87tW3nFzLV9pT23qauvg/VG0Xrw/MpmKiZUkuQelqvhD8fkz9tLT0rxocfJ+7jgwDFQDRRmxDhRU+0W+l/QIP5X5P0v0YOJIy25TvesFvzr1tSgqraQQbJ56OLP8IBq7k2pB8Rwgt1WWvccqvUejY6LjGVUGKu0zJV+IFET4VKsJs2An668d08TG78cItO6zMv7rZT/at0EIr2FkYpTQ1KrusRK/S9Zk1rf13X123kzCM21nKPJbr+yUptP2k1bVts6PQPLdN8n2UXvNfO7fotG+76sWUaNthI16OWbb3TiiNnpD/5hty+XzFRyfkxccYvvnBrcgMw0QTJoYz3Gz1Ffye78e64+ndxf3G7KITz3c3UzqfZX/Hv7/01bufjn8oO994PU5YscpPOX3657qNWHW29d+IQD9PfT77K23jYEGBJoceesnvv/qo7lIRy44klxJEjhJE4LVy40A3I/PvJxJlQvYm/44hsOtqSFs9w5DbqH/GZEe/nSl7JX3whFPn0JJkjfHkf1Z+E8h5JpNnCi3ywwPC5/c/Z0LJeS7VEKhU1XTqhrT46UCE7UGMjNcOORNf01Dmd5HK2YNgXtHizJCKd7dFpi8mCFgeWtVVdtF0cW9ml+0Rqy5LyLhgW6ZbEuIjEWIRX4qikduQoaRHhpRhPvlEBKbPdociE66p1bgz7QWPYjxp96qL0q0elx1BMEGmlrEmaOHJU7o6atX90gbXd3mpd3xiwrlO9NtKbs+FDOVv28wutdE4DjL88amPHVXY7FWjk3YU/n/9E3y+nwY/QqAwoSHupSou6utNWu7vRtn3iNmtpjo6O9/VjPufpctM2Vd8QDxMMGEhPNsxUvaJzCtpff9WWjl6+MgRETfOc2lyVX0TaIMHR/M+EtLhJetebT3XZqH4J1Wfc7lW/9baEAFqCax0i/bSYhIf/EbmpYVCse4gtZBziyVDzuI5VPCF/H9H4AbdzYWjdPdH1xNo/R/ElrEv17mWRZexH1f4v6R2yRX1Dpt0vZSO9c5VRVClQbQEPqhv54V6tuLtGYc3NX9J9Qm3iPqn33PPpz1tjvdZJSIBCOzkfTCDR8+Er3GBpgEjsfPOAPfb6qLr71eoEoyZkrDRio8MHrKpxs6TNq3WcabtlmjZrJXGX5atvttblX5Vdp9WqMo8O7pW0+dvS2tBG80g561YrGB0YceYJK4/2SXq91FLVTAvSDCiK0hFtrr/TilV3q0FgG70bz4DvWDlnyTSDlngDpMVhVYM6KnlQElA/lRrhdvko0eQOWnXuEfvET2zSARDtIsnR6WnoOyNBXrNmjWsUkUx54uCv043f68YVdVIZ9zSwlDOk2ki0ZxredOL1hJgrknQvSaaDJw08s3MIRBqyfObUSautb3BSFPS5eY99pIoCThriSTJdVuf65r7d9sLRZ2xokw5A0W4ZENN8ndQaaqLvAoHGIPEd7oymWnEz0jmkEh+5Ga3Oy31FCu0XCMoPKhhIgjHponStUcqVSZVFriXJHktr+zSJxqrP6ijxNsUjp+lBLexr1E4G6PBK+o0Or1tYKNLtFxL6eH3Y48+c4CIDyS5WF7T+IUpfZlj6jZrtSGWi+p9pyFhyXdqKQ0U783C39ezS6YrH5VfJy+aqbfCtUzbwphZYNglbnT461qZwIthc+PPtD/llxoC1t8WMtumrEU2rfIdyBRPSPJZX+XmtZOtWL7dbV250EldfnudbnuZLetgCb8+DD9rnJCVFCn2phuLTL///bWTIXlO9ZRedz2kLzDaRxn9mm0qpcJzT99ui7fU+l62xp4sFSZ2Ldk5uB+Xvw6q/tRUyR4t6TIN4drWAOH9X/g9JQl2vhaGf065Tt2hG6kWR1b8t5i2hA1cG5Wadwp3KzFaxHlYcHMCygC3uFNFU4YLecW3t9wfDQ3ZWbc/dUqv5vKTjkOT/pp2R4rh8qCprrwuDf1b71aU2b6XauV9Se948h4SW1unV5iarv+M27R2+xBp0QNV8kULz7QKJBoVgrigCLA576tnX7AT7QqcmToJzTaEapmSM4JWLkryV0diSSYhgjEoq1fUjPWjlet0qqXc0O7JkqQanupHreUHT24NWu/xr4okTUuexRItlROaqRp+w4aqPqjPzOr4u5Bviz2j/Dst3P6sdD/4HETOOlaZJjTqgwijkmWe6Akklx5tb3k+408MMjXQ9y0dsU/tB6TR+whHaUXUkEE2179qWbqH7fhBR3zCiHgQJ5he/h2xiPEHGD/dxA/lg5T8G993d3Y64Q1h5vhxygn9+hEW6KMdIRCDQ6C+zawJkvb+/30nPcEeefBrZ05T4efZqJ7hH/9WbeklZIP4PvvygnWs4Y2lp0/AFIKaT1TTGSWqFEPMMccNwX6yJyDHPZZFXb8oN4Bi9yzdGKha45+CVUoPUairb6I3KD/ZJTjnUP8JOFlPajSMj3WcRdJ1qmO3L6l7EWES/Kl9lo9moruIWv3HDc7Ga9f/Ru1Rr2pZ+scM4+CWt/aiXbllkg7dHp68N75J+ppJZ9UHt3qGBUXKxCMevr5CahyRkOjiiZlmNZaXSMd+Mw0j64Jhoez7hNqrvktHODspn3Hgcxs5I2trTZB95z8e0DWhWZWp+6HrG0zqf7mk7vvtP/2RL39prK1T3LsfwDY6L+HapXv+kBrAviyD+fX7EPiKy+JjOQfhlXTeoHv9/uWFbKmHPAc2aPC3Vm/9JRJuS+v3RnG3SDioYpMz71S4MqF3axYyY0vY5hflYSaSzgJzb7M9yQ3a//C5JVtnflIs2EuvrXCD6w5Hk1FBX7xUWZzFgirRflfauBCn2Mzhy6OrpuDvNH1be7daeyt/raLU7h3O2XmszFknqPNXpCecUxk1qm24bS9sTap/vUZ7yinsyLnfK/jG9H1GSPqJ8vKb7IyLeC5Qu0jsX5pTycEq60Ovvvs/qpAdNmzsXQpFLTXsg0ZeKXPB3SQhAfHa/uccef01bVSXWKYyJIpiUJBkd5pGuhyx97jErDLwpSfOIpNFbXFy0EWU9lySZrqpfr4qkybfSsCPWNDOZxlstd+JvdKLbcqfecV4Ck43aSP9+qysp7MKTVsh8VP7PJ2Dnub8OH8bKQ1Ye3itp/YNiotprs2W7BiELrDh8yKm/mPDMNm2VlE/EVtL9UeE/OrTP0rWrhe1GSfq1CsxtZMs3o8lkih75Bjq/QyKXWuhXXKCuRAfgSLo5NqY9PFMD1pp41rbcvMiRWaTPqFmgdoHqwkKdyEanCPFEYss7pEyQTKZ62UeWLRNZdNSv47nZ8otGFAJbVAPe1LzAHYtMGOyIAQHl3k8T4xYy69RFhgatU/FdrAGmjHpDegkPfX7uSSeqIhgINYbwfTwQZEi8j8O75dkvtMWPJ9bcTzavv7XTXjjwrKXer860Qjonu5lMUP37C9n795OvcfdOulzpCrEv1Etipn/S/JD6AZPVkmCnNG2tEwPL7CbBu8rpidyzdzSScTcgkvoIJBIJrJPGSvrt1UR8nCXtNY46BgR9bES2GtfWpKstKRWT7JhUiwZE2s+oKG3RAAL9b7UV7fdlXDom5+NqP3MwTVIS+rLmvDkghvbI5b86GlT4PMfTid2YqtDYoYQOH9poizo6JWXj9M6JNjHuPtxHCLz55pu2/6Ef2y+pLnqVg0vFBlWBBtXNNtXhU6KuXfpw3VIPKUtyvFnf4UMiik16/4BUzXaJPNfqG9+nfuMetVN848dG83ZQZLkx1pf0q104rB08WuQfVQ/qRr+I5i5JpWlaPitijhrIoZwG35VBgG9xuB6QVPiQ0kMb68qR+0tLy/48UZ8FZSVkDEPS892prslGY007XFNnO7UIb5/I/bYzXfaJcz12s/aEjnw67+7PTUrYR6TH3au0Py+97oKeG6fAJSf7TknPDyjdbyo/SyUkaNdz1BJOhDdbdwyR9tRJLW3LVlu0YpU1ql+4HEHIbKUrHk6orXE0wv2cI4Au6N997zk73L9G219NUmjUSD+rxYDlQpflup9T66A9U9s/oi2vtB9k58edukZKRLu67X5H+lDlqG77QNQgqIFL163V1HK9ZVrvl6S10eVlTPbs8kFXXU4u0V6Y91pd4Yci3s9KteO9ehc1SmNq5BJMrdHKYRT3hJ2aCD275sqHp8bx3e3UxCnsMRpRH0flfsJOcRGfc+fTeRG7C6TTpZkUOklF1EROxBO9Zb/PotRgylWL3EAkd+4Za1j5NS3a/CulURK/3GkbOfuotWz4Tcv3PG9DJ34sNZmVVhrepYNBtDdw6k4RwdMilVJBGNMCz5QO21CYpTLqMTqoIKnjmA1prKSUmvanE6i2Y7ZhYZdtXL/NEVuIstdx5B5yCQmF9HLFQEi9VLq2VnsEVyQ9LD7y5JNrqmKPVJgfBqJbUCdAeJA5dO8hwDS87JLB8fMsWkRCjf416hQQcuL2Pw536dFiJbbRQ7WCMAmPNEHUcUf8EGRPlkmzN96O5/i9f/9uV9L2ox9+3/JLtZXfIvCY3N29m+/ZfUfnj4kTQFQ3KjXE2RdqJiTcOci1xMfuy0ua7QcjTk8bVRSpcbCndFFlie3tvCHEfI2mzs9VWeG1stVKx7tcOySpuHbiOSgMdIJfZqvq0kKFefXg8Mmd8pqShD5VkMpLlU5g1GJB8jSB1JRenOVYz5i1n11s2269U1t2NbsFhTMtMxcO/fp7w2D4mUcets1799lizVD4snipOYX8vaJB8g5JhT+Tyqp8pay7Uu7jRS1D+09klQvxUT/SUv+YnAjXEolkLlF/slj+GtRWrBIpryZASZAhXa47kbRYj874fHDtkLS4Tm0XNUmTQOPqKqhm1CLEkEFajRoLQUKJNYYb3+d6RO9q3DvpX7Ojle7X9fbbVh1Y1VkZ+MfjI7ysEoJ+szeU4Fc0mJiMCy3SVg0OEJWgz/0tqabUKb6fkaoLfmbTkJo+4XtoYYdOJ7zDWiSc8H3GbMZzuWEFEn25CAb/M0LglZdfscde1fZ0We2aMcVBHalMq9Uv/0VJmDXNLMloQtNeanmsfsmX3JXIajs+LvL8QTVE0j5LpuWWI3AlIRMBpImq7eBdRMj81ZPpoq2zgVS/LSn+jRZ2LBCxVjpEYh2Blm/+edLr7YiTJtP9JVw1SpGJ2/mxOORbnb/SFbn3JL1i54i0b6x0VQMUJ7vR/eS0Q8SlWwmBh+hHAbtLRPT7LDP0DxonSN0lvVgkeZ2I7ZIoDYqPOCKJsRramqVWu+IXJFAetO43vy7pxkGrXnCH1baulU7sAet68z9K4fznrCO70842tljV8q9YTfVpy0t/lX288wV2v4gIY7GESgj5FGo6MTJfIK+SGopgg1ddzU5rKL5iG9d22s3rpdOuRtATaDlQgyjd7IrxkmMeaSi9ibuJ7+5yIfcRmZ2Y7mM/akgv+tYrViwXFOpYRLgzItWoYbCYEWm3s688c9og0m8ILf5Q04BI4wZpsieHc0F2XnzpBXvp7ItW+8GM5aWbjJT2WjGogWAguqPVUWfP80iHBluVf+hTe1OVk1Q5p7okja2Rt0Q+39K9itfoXdIDX6St7rQnb9Uh6ULvGLL8d+Rri6awt0rSq32kY/29D+6KXx2JGkjbaIMGBZLAc2Q6xuNw0QTJeWlPwhbVLnZls6W1ZXyQeFG/N6AD6t3Bgwet99GH7CdFpqOWh9bn0g2l8YQGygu0YHCNyttzmslCCtsv+9eyVfaI1Ds4fOSgBo9fUDtyQCT0RbUFt4tI9qlt7ZHf7SmdQKp7vj7htYs0L1clGJDE95aarP1A+sOsWvi0VDu+JRWRv9Yg/VYJBH4g4rpB7Tq6x6iCYPjbInt0mH3NJ3/Yo2sdnTMY3UNaiZMegffUOPwQFmFiMuW8/eqbe+32XN5J1LGdjBd+acsIC+PvWfg4GZdzyv83tZNHq/KI7vQPB3N2TLMvhDHbhnS+JszO3vs+u2fVWrctKm35fDOBRM+3L3Idpwfp37cf3aXGZ4tI3kJV1snVeSLzCUkFIuMlVv4qW1V4VD+8gbAWhw5bse8FbXf3ZWkqLNKrKGyOc0U6GxHjyK6U2GInEz1WW35RkukGjaCXjhNfBR2RWjUL46RVlo7cxu38PVLkShxRetSgOIl21CQ5Uq6mbZyQEwGpgxAThv550k6a3T3E17kh7WoSnSTbu4Owyl7/RDekPz6iU5oPWXv6gDWNvW0j5Tbryt9lg9mflgupu0iPnIV9yaQkgUlNI7astFrpvQ71RHjSYCaK6pgO7ZN0vkdLsbUDhPTnzqY+ZkMj/2ilnb/r1DtqOz5qWbd7HAQaHInffyPdOjtNNia17aA6oTER6YIWqa1sP2Ebb97upMFxaS0+5sJMJrZIoFG7IE0s2oM0Ux46Ra5RzThw4IBt2LDBSaRJDxJtLwUvSSLkJd8cO44KSpuOXkb/mXhQOUF9JAo7Ko9x/zPN37mec/birhesuEEqSyJmkm3ONIh56T6iF1HScs2scVBpUVEr6uCUwiFhrC3wmkZbbfDDPZZcoZKl4uXyriI2uipn1UtVvw9IQv3KAhs4pSn8jdqFZZl06p1o78pnOTWq6Wv2vh7VLEpRJNpRG2py1L5MN0Vj0npq71lo7910r7U3t2nQMNGmTTeMG8kdUujXnnjcVh06ao0ivaA9M8TfiRatGCob/0XraCC3rWovbpJdQW3GEh1z/7ba7kG1A/+9FtrdJeK7WwRykRYKPqTZrrLalC9KArtK0tLFktpKzGFb5EaHTtoqtTHfktv/JBUy9IXRjV4lAvirVdVasDgidYiivVdEfIvCmry9HXkiXfQCXDHYsUIBg50n09z7ntH7QT7v/bUrH+/X8bK0V1GvQggTBhQXS33kU1ocWC03pHW7yDEqGpNxQflS22Tbx4UXefuvWoh4q2YDf1bqKbMthSaF55SW5xa32r3rVlm7tgut0WzgfDSBRM/Hr3Idpgly8eqrO2znQba12qpKLgKpke60jSo4zQcbESU1FVwqnb88Il27whrW/S9yQkcEsZ0IO36v1sRFWUzfLcL0I6uWfvRw1Yfkr01kiN4dshoRaLGtip1eT7arpMaFzTs1Vs4QvAtDfiuNHoTZyQhk7924/BOfCzeKl/gUkKy8DIKg5Ief3Dmj6bxkUluTlY6JIp+2am0dlxORK0rnu5QWEUneacOJT8u5CGFG+QAAQABJREFUGmcR2mIJ3T1UFRSEwh7NFS2fgwiLzCjYobM64KL/sNUs/JzsxnRM+3O6SI6hjqO69T6pxTTY0LG/s3yXthVs3KQkShIrl9B/Z1y6tBuFdJ/ZWzqSmNOsMM33pm1d22jLly8/T/Uh8ji3f5EyYyDBTn9a5Q/SyzM/vifPa9eureho6/Q8SYyQdvMOE5eII5l230L20Y4aUf6RUEPSseO+T6cqdqjBz6vjIrwm6bjij58n5C7wSX9I7xv737CduR2WuAsp1EQZmOR03j/6cu8TGpV15Ulb6ZWlvlA+ro7/oJ6100haR5knb5c6R1O/Vanco2ud1uEjZdXxYlrEJKeCKyjSqySFW6SlXG+pDL+uEt2lWaqbRBfaKvXORzbHV/KW6c/YaK32eNZWdaWs6lHF8I68TseMiQSWXkrYsobltmL5Mu2bHunuT8fvjeiG+nPsyGHrefIJu7+3z0FQaYEuCw7CWK3G8bfrGyWB1iyn6j7a/4+JJC+XNPhfZCPihsqCL2l3SvL88WqplslvSX6ZK10nQoy5W7rSGErBr9TWu50/6uUXgoq5Xe/ZpcPpHNMWOdt3/vF589e4i7jddO7xG3cXD4s8rVba+WFaVQc/pdk2DEvN/21Dk53TFbHUqL4BKh9Vyso6DTbYvg998bR+Fwpf3i7JMGH1bE3GsjqQZ+Hm285T8bukAOfQU4TcHEYQgg4IgEB3d489+sJBOzqwwS1mc4SVhkUVcfpGHa/0cFOSApV1gl5ETr1vFeWUyOHFwqtEN5bI2mhmu7b4ekhb371s+dQHFZCX+vowcaxuMWr/KpYVO+8EF2p4JogDJByZRBSRZOa6g9BF5Bxv/o0LW+HTQYyHUYkssoP5KnIt0tOBs1q4dFQt2Slrb+hWIzxsw5Lmj2WXSmrSbufGtF1gYp8k69Ipl5oKeSmW1LxLBQNp9OioOgPSmUCFgo5B+dJCwVS2zfJSncl1Py230pnWriWlwll3X+j6viXrNupeJFn65vgZ/2564p7FXiYdaDexqPA5IhyTTByxNXU7bMvmn3DqEJDMuTaQWXSYWZiFKkZOkpJ26UCzWNFPA5KOeFrQccZAgMHc/wjL++E9xNqT67gqCdL16FtFut1e5QRs0M3GQOKRoiHFJkzWBcS388NN/2C/vbD7ORto7dVuFSwfulD3iutry4xpd4rkWZXHAyK9x1WGmjXouFnS5U5NQGt2gxPloZ/ejErP2m+bp+GOW8s6WqsDnXKaSdmmutApu70qa0+q1K3TDiFrFZYWYGKmS2J9XNO9ss+2tre2XH3O2NGkpH2wMcSHpJ3vNRMSXT4hTI5k7L0fuNs6WnT6miSBvnxNlSbKmItP5ZABlx8IUk4xPGOPO2ZfuPJMeeOeX/z+3QZ0LsB59of6+eqTT1n7W/tsqXShJ0rL5ScUZNmSrlaBcs+iv5vUhkAO64WrWmFnNO6xrcIWQs2Wbr3C9FutzbZB9fuukejo74pTFw561O36RV8uekO6Ier85rsh3QXlc1dNldXpKPBO4e4N6QeHeN78u8u9gswRlds3tSPHbfd/wFokwIgLNy43/Nn2r+YrmIDA3CJAY75zz0F7bo8OUyitE5GLOrwZ1UA1WKg2lMst6hBo7CZXX2c5jYxU/CmQ4lirpLZ3Wnv5H7Q/pnapSN6hsCcaChfR5JiIfJLdeZJu97aSv/i9/MXT7FNP54bxV/egxom8JhPS1dW8d1VhpzVnT1lWROJE/2Lrzi9TJ75Si0YWSNqpJt7pjaPHtwGFzEqySQNETPmpRFbVeId2NdHpkJIms+NG66b/00maUzUrtJjzrPbmFilf9Clnl6zSHt0Nq7UAsddqOj6gd6vEGCrNBWkWichUnXakuaxtFUrSj45wIN6yplsfsNW3LrVVq1a5BnCuOu04ifBktaOj3Uku6jT9B3HgdzED0UaNAyKDugY7ckB6L5bu+HvIS7qywBDdacLEQNp5RzoI9/jx4w4XvvnZs11uh5IDx/bbS13P2+idWqCp6VWIGQQNQ7mBpF2KHX5QjeCKIRzJT92V58sJeyq/8fgSWhWFxHlMR1lLe0oLAxX/dhG7TuVFB4ygtxGfdfH587uEkNa8ttlLMhAEg7wOslC9KC4rWaY+bbnDRWva1WZ9u3vN3iuSuESEVuVyOljF0zkdXNy+CDpmHFPSriOkB8M3Ij6Mj9dfJ38/cMeO7zG2L2VrWtbYmiVrFYhs9aMsU/YaGznNM+XuIQ+UIxbIcuWZ3WsoUyxs7dXMB+WWwRwDNWY/KLdc2f1m8eLFbtDGoJKFtJQ/1JiYhcEfZZEFtJRN3GPPPe55z4CResU98VNm343sOyDm4M8JpfOIFhR+VMKYKqUh1krPQWymhYBpW6HvxBf3cekT2R1S18Aup4dv11fbo0uXWLcOd1p74rR0mb3L2U1SVOooa+NNuYuAEkjJqzTv56XVObjMP4TdnamynkyNVY1oYfllhjcd7+SRxZT7tK1d/fbttmZtdHqnb0unE8aVdhNI9JVG/AaMjwb5qRf22okBbXqb0qKxSbURwujVIlxTgYTT2wmvcSmt2w+KBpQJtNkwrF5eY2dSn5N048/sZLrFRsurFDBV+UobmkLIzYjUMKRzW9hnC2vfVt7NuqR+0WN3WiG3UuRD66Jj2LgWVJ1KZN6dLKKKAYF2RoSYw2wwmYYVksafk7RZg5z8Fn2LaFFYum6T7JyT8T9JScXLIjUYFhaOjWkXjFjnwbdKlt/QyV277Sc/+FWrr6t9h9R1PLBLvKEj95JiJ3EWYYAI0OFDLiAgl9LRez9Iif12dHGp30ySS1g+PEeu1Slj6AzWrVvn7iE0fDpUnZ5+8WlHLDlIZBTJv/Zr9dJYT8Y8WcPzdO0gbJi4X2+H/XTDmZY75cURXm3YMXZKpfllFd5+yZI7pT3/saSNtkiKLAVQapcn8nFyH09jPL5oxw8t1GqPpvGdO41PqjYlrbB2wFIPa+/qZ2uttFKnrm2S9F+aXvG95uNhkWeMxyAep7fjPX54V9tVbyPt2k5Re277cLj6AQRuKYu4hcBzYA2GwVVS+0VzJHtBA4EqLUCsLdTZcKsWTXZpG8TDbfazn/qyK698f8oZxs9SZDIKr1KvKEeE58sTRJoyhalT/XKplZuJ8p90pJcFsRBiyhzEHMMzZdsP/qhL/ufTgDvShOEdBN6T9i4dHpQSoWaRMPaQdQ5Qwi8kHhKOH8q2X4TLs68P/t4FPs0/hP34j35kbXvespWVdE3T6yU74ytGFPr8IOh5UOD5cUON7df2mqP6Lm9r8eAhHV/fMhzNPJ3v4/KffOvur/EQ413pVO/jbmd6T3j96m0XFHPaFWS2Q586NcRyUpjuWbHUNm+/z6nU1WmA6Mv+1L6urm0g0VcX/xsi9j37DthTr/VarrxdnU9EwOIZH5fkuooaVdZxOzl0agMiRtlMlzoWHe5QaIl71z3dcqySwzzjlf4iz+XEWjthH9PWdw/bUPojGgkvl391lZUdMeKROULvpNWT4vRpOC+umJu4ve4T2grM5UtSee2MrD09B6S1cVQHTHRZVp3xsKS7x0fuFVPo1NZgzHn7RXyash3X946FH0/k+P3F3gu5hDr40eetKXPYegsidyx4FFEeE4lzxqVbTbWCQs+6JnvERgoL9F4/pzaCq4gAyIHutaPF6Gv20Q/d6iRftXWzo+tJ50tnCglgahepGcSZgym8agTv+F2ugTBgIALEg8qHt5vNxhzpHruH7Hxzpz2//xnLbRfB0g4PEK/qPh3r3arTAgWtW7ymI73jBhLnyRxXTNyO5/h73k3HDjfxcKYK+x12+jYQxjFpAY1qwWribc2iaMFdYrHK6gelwy+9Z2kQu/h92D4ef4VMT343Vfohq7jL6fhzrintx1t9b9ZGTg5a5rgI5fPSnV6qdROqwuyW4cibkICQcgy5jy8edtxOQao+VGl9gXbbUD3M12rbPv3DsIVdUmESVjqvQU5GZVL7Zldr276EdhoaaR6WxE66svmkDbcMKaURkU5IibTIITYinGPadKj0VsI2Ld1i7W3tTprMjjWUW9LKzjAY7inf3kBOvYnr6scXI1KevIE4e+kdZNYPCiHPcf9Lly71Xlx99Q/+wCKefTpIE/v0csVQ7yDzPIMJhJp6ykAACTlScLdOoK9X+WxxbqlPSNBJB+6pV5F/2p2JgYKLoPJn7969tv/BB+ynpQstlfmrathm7qn6Gjsi9ZulA312rkYn+0lHeq8W220a1h74FKDrxJCTMyqXtSywjvenc5i/UeG7q6HWau/YZitWr57XutAehkCiPRLhOicI0FB+98cv2cm+RdrRLjpJ7lIionHO5RZdwOukhmtyhb/Yszq7YuZ9VpCUI6uFhuWqD2jfzcXqECrkMBbrhLrHpDh943leXBNuXLcjwqpuX1Kyok4mO2XV2hUjr5Xa1Ylj6kAabVSddL5qkw2WO7WHNkRVnaJTGKUTf2daoDvvbt79PZ1XRjt61NgB6ym+R+osqC+MOjWNXEFz7yIGDCQSiWHpoksPVAsHh/PqdJGSVvYrjdIQdarI55KlQ7ah85TddeeHnWQM6ZjvdN89re98yzfH4D/qjPtcBwzhgNjSEfObBd78zshlA0HwesxI5tjZg2nz2SDqPkIk6d9/+Ht2btkZS60SLawcYpJriMhbSt8gPSKd34x2YtEMALq5nCQIeYOkIdGdynii699NfsbeE0nv5lKuiYII1HGVghNSGemSBDYtqekKEfwVIkXsVKiPA9nFzEZ8EFofDuGS/3ybjlBfAHketrqDWiD2nA7bOVPvyHRxqY6F1pHh2e5qG1jWN06IXYIqfwjPh8nix+reGqf7XJL6FCc0pqTTDd7ZgWrLt4i8Sw0F7Me08IxdOtx2fslokMDR7Fp95cxolQ4f0oEypNOlNatBxTGzpp4m27B1g1PNoDx5qTKeLrWuRDHOzd94+vxgkpjiRJ37Ti2opT56iTh5wS+k3dcZ6jGGAXH3ubO2cNFi94yKCWFDzKkThAfx5/7Jhx+yNTqg63JPJ3QRXcYfjs15rTprp6XS8cGePmvWFnadxVN2Vmm9c2BQLfu7t7eXEfVV8VrQoLNXvy0FVMKujOlSe3Fw2VJbf9fd1qjjvRlgzsc6EUcjkOg4GuF+1hF45ZVX7IU9eRtKblMPEStuSHMleXAGsiqyFhEybCJSpl5q3E0yoalcJ72d2CXB+XV/aLwqfmb07Bs9+RVhzWvHjobEg27ru8HkRxSSpL+T03VeWqeKM54W3UMEXT61MKrmuCRRJ9UpH9eJbINW0BZZxdRKTZndr05lkfiySHNS0jT8EAzGSb0h0cIqhod75xyR9gvg594TEOnkxz2/CPdkstuq889renKVCPTNslc3oNfFUrTPM245uTAhScvYGAMAhSHioD+VcAjTG8jNiLUkX7a7t0anE9IAxqVj3uV0r3S47OFM50xn7CV2dNTxjn264c3UnScB3l9RnSbE3v9Ix+UYwnnj7Tfs+cPP2thnRMIqowEIFyf9YdihgmO6nUqDTlRg+zdP4mq6tR2hJKWQOEfq+F76h/HXyffu5QXeT+XnQnblnMrA2yKS+/TTLPZop1RQ7pC+b5Oe65QGQYNsOW58WJOvuJmunQ8v7t4NJGg+tJ52uF7qHUskDd2lk053SEKsg1qakq228NRyO5x4y3qXnlM5jf5VaUCCmkZKkuPMcMR8GbyMSQINxhD2kvB3VU/PI4068ZM2SP/8ITPcl7PnE3tUVuLpG8+f+GPq7Wq7qXqDrV602g0EL6d+eCzmw5W64skOV0+auaZSEzspMfPCe8p+myTxvg4hUfd+UAuhrkOkOZ3w4I8fsp8fHNEsYST1ri9EalDkW0FdEUM0+1TfdzTU2XYd2rROC+3Ymm6xpLQltQtLNMiWuOGKpOVKRdItcIe0fV+jFhTS0p1fm+cmFW9Iyp/ZusWWrlptzRKUXAv1I8Zq5gaUEOqNi0BfX79974Ef2OHeu9R7VFQwPOFzxBIypobHEVVwqjRC57mhodQxwNk+SSOr1fjiRqQRtoc/79YRO71zzxRrwpbx7lwTID/+edxf5Iy/5bFGG0jcb23lv9eiw6dFqj8mEomkz4er+OJp9WGMXxUnrbqT0uqqzrih9rBVpQdt+NwhWzj2kg1p46CesZstn9wqKZUW8o2hdEzzpGaK6WbSN54XwoMdVMiaH3Tg3rnTK3k5L016HMfEkW78Yycy4AYxeNCtThesHf4biVtbraDBA4MI/CEpL5aq1YF1W23mmPUN3Kyj1kVGtIgxIvSVtLhQlD6PJwkpnrEVHf22ZdN2J1FCd/NSTE57kHJKIUSZLeLoaPkhpbpahsa8pUUYyHR1SeQq46e53cMl/IEsfOeZf7bhm/ot086e3lAvvv/5xh/egTR0RGoMjjBrP66SjlnnKG1UC2oGtACsZfC8hXXnhzI7Tynt6WyHpa+7U9++T9dbtF/z5jHLNqjOqWhcSDI+O7FHoUyFEbQYw1HiqU4NBhfouPYDUpXaXW8L88uttqbeVr663k6oHp7bcMqpYlQPSGXGhq2kreqSAyr3Om1wTOdID7bqaAxGKzJlrRPweSqxGFLGk3D3oD/RV5v4blOlD33rkgYeNb11tnnbZlvQuMBJon0YN8o1TrSzFbUp8s7JpN6wABLDIHrnC8/b5n3akUPw9gv5gtpAkM611to5CSGWDgwZKgDMEEZL/pzXWf1DyTolMvm9zg67r7fbNuUK2rmDcqB0SOVLnRMNatQWzmrMVy8wWnlwzWXrLNk/sY3jXKZoUKOSN7Qjx62332GtHZ1We4n9x1ymcaqwA4meCpVgd9kIoCO34/U37KHdOswks029UYXMOSKoZvA8gocklUaoQhonuaGBzOWWu4bSEWiaL8gqxrmVP2ewJx7foSnMSmc4ETYO9d7Hwf04EZRUSaugziU+bA3lx0Vld0iXc71iQzIV7bQQkdFKHD4MF6emr3WqFQS4KnlY+tu9lh84brXJs1pUdMoGypvtYPkX9FaSmLQ6DOm9vsOcR3TJC25IH7iQX/3cPfmqvHN2EGSlyeWDdz592FX8ejvnRlPThUe1C0TGBqp+Qk7IW4Q9u6RiRgtaUJXQwsOkJHT6luOqLT4O54q4yLMuUlVp1SmH79lQ53QrWdTkpUzOwUX+oH+Me6RRbIeIJIpffX20IOoi3q/Iay9BixZpRdI0r6ftycF0E4Ikbse+HXaw66DVfiir1f4jghI8KyEAK/f+inXlHgmpGIONZKQ6gLWIHxJpiF+6lLbqHqkjSKKKNDtZkpqF9Hsv2ShOrXO0xKBqwZv6HVOipN5gazXc2qzwa5nEjtQqLjmO2fCoJElIHB2CCjx5zSytK1h1Rl3cAdP6Ag1iB5fYotPLbHBhnw11Dogs9zsVDRZwDrT1TaTCfwPZeALtsefqBjtuRkYOqIbTMCUG2jvStqF+o61fukEL8CJ1pGl4veGc+Hq264037PRjj9uXdNCRYLd6tRG+SljviLXLsqx2saeu2sqSDC/SgScD0pFH7aJpVPuMi/jiPo20WAIKmmd0e9m2LaU2jVaShYHc8xlLlT4lJTcqQuNV8ZTu/2tbo93a02135DTjomcMbrJIx/Gv33if5N5e239oMY4Kv9b8oHWoDwH/uTRg+aRUZeo2brJVa9iRo+GKzDbORp58eZiNsEIYAYFxBDid8LuP7tbuxpvEwSBCVEP9fG10DZaqDs/cO3JGk1ex013UKKmx02l7iaSWJpUkCaSxckZXJKt0TjSBeD3Pb+zZEb1K2FiPp4EHTCxepaWUXmfDhdPWUHhEJPqoGuNakZw75U2qFq65dYlWOKRFSg5KXyZ5XFsv9WhqT1swlQ5ocWCrVCSarKugfZsTS9Xash+xU4iYiM+F5fMja//ssFCexvPmMqdnxTuOle5dMvhDF8A7LuASPY7b8c65xbt0nrWfdIO9rcHCpwQnO3TIj8LmJL9kUguiFFyxqKOu89JjV3iZqm4tstN+yG5PaAVOOjDg6uLT9m1jh3VwxH5bv+FeN009HakxAy0XjPLEQiT8oCPKgqT5aujgOfkQg5406Ubnk6nnmZhzqh+Pv/yojSwesEKndM7p0iuw8v04HhtyjB2SZ6fO4e0mRySv7KPsyKxmTgrSyx2Tri5bzDV0N1hfp7aAI2zgpqj48kFREbnwUlc+5ZiOJEtqiz2+8RinT5xQ3NJ5Tgzoqn/pDbJbKocLVF40kHMkk3AJk6uMU2eQf/SLIajoeacKItu6ko+qfMYRexbvpUZFQhTkaHZUWzkyGyJcRf5T0kXmHjeE7Q5qSSsC/XcDFiUxqfzhP1+dlzReh15AnOt1kpymn/XG+e9ZcdZG2rTg7+Vqa+lplyS43toOLbR8s06FlGS5zHZ1pN0b8gBG/oq90pGQI3Aa/y64mYnp0r66p5psy7bbNE3dPL5QdSZBXK9uGVD6QSgngDIDldP6g30vv2irDh5w6gSDqndlEeS6QtEGNTAqqpFqlkR4MKuFnCrDTWpLJMaw04111qSjukf7S3aCRcf6Zm29g3ZGu2lUiwA363dKu2m0SMpdWyhZl/wvUJxZbQLdp2O+0wqnXnHkVAcg2Dml7aGWRmvQLij3nJFOvdKRU3xVKmOoc+Rd/VHaZM8+0vGidC1/L1qTA9m0tQsjFnP6MeNc5EnQ2XHh+FbrAtt4973Wpt1emMX0ZWIu4pzNMAOJnk00Q1gOAaRzr+7cZ6+8LWlAUvsSuy3R6JVkaGVUKWdktINFQgveTA2Xapb801rR0fOsztIZ2Tl7Ok/Zu3u5Jb7pGifdxW9Kh69stdriK1LB+FvrK99kudQaqaSIPLl4lZ7EkDrCXqsf2ys956M2KoKjYx/UAS+Wysb9NlDUIkgd/qKJbsVOmklrJSEube+SqPPy+C7uZvxKZEYrmzLajaMn8R5N/a+spKsk3TOdOFhq1nHsOvlQurcOP5H4hPagTugwFdOBLZoDV4x8PPCvuBH+SKGrizvsjpsbbM3KRSKV7HN7cZbh92Nm+paFgl4ncsbZukoeSC8Emk6/WET+FS2kulhyqB979+6xvef22Nj7kK4JK8aCvijr1hFoAtIrJ3mO22EvA0nGHQvcXNnik1RJ0qYFbc6oyI00aipWr9O5KqvK6UhinhUPCwLrzjWIdEaHh0ASS6flQYeYpFdp8eKw9oU9KEmeJNBVHSLQG6Ty0CmyI/UG4kuLFJe0UwW7cmRGdHBRTV7p0dZqIsgcRpJQGaoe1EK8urykgJr5GM64/ZXzcleV01Hsmg8v14uU6whtSJSrOkoTWIxqEaUjxTpcZbBlQPdVVj1UbYMLBiw7lNVuGLU22Knjv0WcqwfqpBNeyW+Ua42tNZ+igS0G4o4uc01nrZ0ZOyHC1KqZoYy1HuywE8s0QGb2B11l1XlXVSth+Ms4xjB9maIknFoXrAmai5dvHwbftvx60m6uvcXWrFpTWZwaHYjCQNLXFcoQakwYZmYoV7yLDu3Rd5BKESSTcsc7v0iPBXjcU65YnMfgDv8s8CN87HGP4R3+ISjY+3v3cg7/ROkouvxxTz4YeJIuduwg3RAn1kCwE8mRQ4es6+Xn7G4dmMSOF0PCgeaTH2NLyjSS5aykz1XKU5Wkzbzr7B+2Wtlx3zai3T/kkE9XJ7uSyhnNVpOwGW6qsdqz0r1WOjDY1yocwsSkVcZ7RKRfFOFOq437ZI/aetkNiGiryNuCkvCWp35JqK0v5/Y27pfbNm1zx6CMdym5Jx3eEEdRf3okcV2gBfeMCSvReSfz5loWqT1dXWebtI3hXBuavhe157bdsdXWrd94TUmhwSaQ6GmWEBqcY8fYRUF6WEuXjjd80/R+QzmDHD3z7At2un+9RugcMU01qTQntCTcOlLp79WUOHLKFaf8kam4KZW0B6z2JJ6wUyvmSbJzM7lDIxwfBvewE58GHyfP2Ou9++keyS9uFWbKTknSIGlaeUR9q/ZQNkljxxZKv/mE1aSO6hi6vWrMdUqgOtRiZqsVSq0aK7ANlYiztuNz7MeJswiecH2a9UzaXLp1743LD24g2z6NpH0qf97Oh3MBf76JroSd0GLGTGmHCMxiNfIbFbP80cNIOuiIGnE5cYquFb8QnHyhU24g1FIZKKuTr2DkMU6U37Zl1Ttt+50/5XbP8JJan7X4lc4dUpDJZF0nT33yRIIOnXvIRJVWwLu4kRKhcygzOqrt+EQk2AcafWLs6YTZNQMpNoQDkoDxJAM77qm/xMWzI21yw/PlGPx7CXRXl7YprJKEq6I3/W7hDooYPLfvOetadMqSjdGiND4FxpE2RD8kTUXBF033TjqgkGQnDa1IeLGP6oy7O/+PwiyItGJQ6SjUqoOXPwh0Q1ezLTy4TFLqbjtbf9KKQ8LnEX3bNzQgWCViLqlfeoPUIm7VEcUdmmmRlDirXS4G6qS/LXILgR2pUnlwaVXpgX24UwPFSBUv8eQVXxmmoLzkGhiIKSF6l4PIyyDZ9Qv0oM+lGgi6CJBwLdRqZwvCkx+k2ADBJHtZbgplhcuuGMIiVS2yzCdXuGwFmNCis3K1hrNDGStqNwz+QdqHF/Vb98ouzQwdj6TK2p7u1HdVrxtV5ka0dkFqSLW3sMe4AsJULi5/kY37e+KB02oTUrb0851R3mPv4rcMSlLCCIKf7dMWc+ea7LY7b7OGas1qiUAx40JZRb8e3XqK4tGjx2z58uWuDnCgCtvMUcZ7ROAoZwzY2JuZuoE6yOCAtISVXt5xIArhMiClbgz09tjyVatd3WDnC+KgDjBDiKoV5uyZ09axMFrohx9IN2Fxz5VfvN7E83ehe+ov9cvXZQgyaS2LUJ48eUJbOi5235ddN/yUPXkkLr47u+EQxuvPPmONz79ki7SgUCVLhzepHFWIcq0kxdhRNiDP3oAhkmpXzmRZLxUP3GHfoO3nMLqVG+nK9w67e8QCp+trbeHAsJNCu93AcSSzQweNjKit+0BXj3UIO0ydyhceKR7ks7l3yE4nNdiRJQsMiWtE7c3Z2mrrHNLiVtmdUvjtw9r/HxIucvr47VvttuFe63z1LS1idzlxYc+nP8PqC4b1XRZp0Ej3MVcGqM+oDB/Q4vHtH/1J138wmBqvh3MV8SyGe8OT6At1qHF77mmgvv/A96RHmravfvUXxjv2WfwW10VQNIA73zxkT+xh0c7aiTxRWyCI8QoZr53jBDZqrLxH7V/hbseQFHmDW4wPyz87OxpRub2YnXNLA+wSJvdRPP5a1m4VfeqshnIrbUHiDTV2L1lp9CmrlruqZKN1JVerE9WJfqZFMOypzCmMPj2O/Uw07kQ1np5xN9hV4nQO4m4qaSLAybg4FRaf1opHn1dEIC4RFX8+XK6Kq7r8tNXZcTtrX5IrtmrrUgNZpU5LEmhNi0dsBLfxbyDSlZSUUcOKjPbpLohQj29Tre+Z0NZeVbkdds8d7a6jhsyi4uC3ueruPqd4WCAo1RYRBvaQjbbJGnSdJjtv0MkPc0R3e4cjFgxWIRN04CdPnrRly5ZViEWXIwBOYiUC0KbFJxBkv4MHnTFx0xlDFBjMUR4hFnTmhMfuAHTgEG8OicDt4cNHFF8UB2nEPXUeMkF+6OCp/8TFj3f4w/j7Th0vjiE+yBHuLtQR7Nv7lr166EWz91FmmMGQlJcyi3+RXSeZ1j1EFOMXzUGgMWUtMIzsojTo4aIGtQX5dO6QEtcOSa2he6G1d+kUu2zezuzusuTLGe0DXmP5rPSzv6DFU5o2Tw4ofSKshXqdHMgMhQxkvIBmU8XkGiOizmNRaiXelERivfGLI3kui3hHk++RuofPHwsnPXnNDIu0D9Vav1RRStmiFv1JYq+OnW3jRptFZCjiIiDnRBZrMpK+anHgoBZWOqm8stlfGHT4Z0SEkJDnlMdSTpR6UNJvnZhY0HOd1LSGc8PWsK1OJ3kqr8yYKdziiNQ8RM6q6kTKmbNXlkoMMtTZF3qku68KUNSPsXK1tr0rSHLOt+HeYVWnHW1yIrf5rHZX0RZ8O8p2e/U227x2sxZL1buBIDgwIPRbNUI6Ec5QbjDx/ZupI97E71u1u4U37L3sDff+mbpCfSN8woaYe4Jb19A4Xo4pt5RlrtRHv5Uj9c+vT6A+4Zc0MximDnjpOPUJe+o3/qlbuEXiDIGmDi1evGS8XsTzQfjeUIdPKc69OlzlU90Dkg674b1/7Vo3/xDvPrAb56NRNfHOlK/xW1cDVOokwZZlpd50DA5rq88x663WAELWS/IFe0HpPaRBxafOdo8TaEJx+yXLDUFC5UvDGsRpQASpRiebNNTouqxvEOeq2WPWqLIxpPsmxXd25QIbkPsf3bze1khl6b1v7o2IuXM9f/7s0yC6NtcviTt1uALUHCSP1uI5DbLqbttsq9fd5PoNytS1ZKIaey2leAZp3b9//3jDsXv3buvUaLxTHeThw4ddI0PH+NZbb6mDzNvatWttzZrVrhF59dVXXYPiJQFsszOqinFa0gG/Gf4MknFDOXX7ej63005yOqF0gl1r46SpdOBu/K46SWfFsyon9dPf+ysEhXsRi2RK+qIiccVim6xUoZ1fmjAZd+/tsKjYOxIYj0tufNjOHyTbd/bEU0nPOPmO4i+WtPVbeqGdSWg1fdUuy+UXaC3/Qi1iIW9iEY5UELZ+zkhapnv2Vh7Pa5TByvv4hYxj/FVp9/mhqR/PZwUL7450j7/De+W9zwPufD5cOhSu8p5Nvi6pyBHrTn1EvA2JOfhXjAYAYEyTj/56IqHDKqSDXi5L+i+1lZT0pEtO1aNeg8eTwoGtqdKSyp9RT9JrGxa8aRs3vt9Nx0KekZZh6GRrdCgBetWnTp1UJxvt+xlNOU9sU4UfOk9IJ50tdYwOn0546dLonvAgt9hhlixb7twTBzrU2HNPR47h3h9QEd03uTrNO+KLJNqUEU37trW6sLgnHbiHTEAUeIZcIBkkPMjFoYOHbNHiRY6cINkjbt7RniARhEjgLi17TtuCvBMecUKwH971sJ3uOKnqIeKiKWP0oZGz6kPpP99PF2GWYPGpWmh3r+8L9WTxIWTS3av8sR0bfv5/9t48yq7rOvPbbx7q1TyiUIWZBAiSAAGQIMF50CxbshXJ7rbjlu22ZTvdtpOVYWUtJ/9mpbPi7laWOx13EnfHjhzLS6NlDRQocSZIgiNAEjMxA4Waxze/V/l9575TeCwVwCqgIIIQD1l499137pnuGb6zz7f3dns4wKkAeAUAKHvNoh2I7qF7St+DVZd+YdaOrzzo+nBsOmHN0Rab/NSklSfIvAmQKGlfGs9zraKbcI/nZ9JI74rkDyhQGwVpBmVRoV0sUITAZlAf7lK2WU46AlqEWpjTHc7DwyzSXLprPSiQHMtC1UDKnWvMOnffklSrnuJLK23lIe+YSn/ynWkb+M5wAIyxetHz6XZrurXR3v135wA1lH8EqkIibN2f7LCx/XjWO04fh35SQerc9WibdX4KnQWBHk5exp6btI51bZbCUs6JvYyR53CxHYFqsCZk/b/cC61gxMafm3LvojxYtsatjdaQbXAOX8IV3GEj5CzwTwWpu3sfqqU2HkjJq2eQVg602v0P38sGJe76mqdsqEb1AFJ9f7mD3pMH5krb5+H7rM/PS6f1XeNMQc/qvh9zSkeAWEH9fpJxvnbdWjauE2xYR52kXM/4MaRx48es7qv/6/NyQePjH7/9Les+eNh6eT/qtdcqCFzHeP8qkqqVgWOdIr/9OFDZ09ZiDzCoehm7HNxgvz/quNIqi4ao9rcx1RX31OqTGt/0zJ8pqszepcfYlOo5/uIT6PZ0tVvn9LhF2zKWT+FaHen2zz75M0n9XG9cgA+9oQC95RrneoZ5YKi3w7Y8/Ak3L2s8vF8fucZFWnLyNzSI3r17t5MmPfTQQ/Znf/ZntnPnTvvt3/5t+6u/+ivbtWuXPf30026CSHLEtvuJ3fYHX/mKW4T/qz/9L+3+Bx+we++911544QX3UtPpBnvjjTecbcslt/IvyAOaNA8cOmrP75vEO+G9LCg1MOlApp9GmEo0e7kp5eKHm8ncfd0TwBOwRXLkqBwAVpeG7um32pQzd0/p1YJmRKXjs3NIIgBe/EAkfkC5jlWOa8WrmyZkhsAxnGoA05UnAVZebyOVPn5ikRSwdPnyrJLzQcCmmrf80E9wlb0OydZmflc6PpLy8WVX4QS89Zsvm75yT+VRvr4tfH1cXKWh+vl09Iyu9Uz9PUnNOLp3HGaeqJ6y9sjzNjS7Da/fHRYND1qp3Mtz5B7B/rMUtPisVlV/XKwCzNz92ZTLVZ4KlW251AwIFIUCN8jlJivkm5BU7Lbtd98GiL7VbUy9tEtpe/5mLJbE2geKPIBXP0GKzuGDnqlf6ANJNVlS9/p49RKKxVxrMfehPp35+XkgI7Ag0KB8Fcdf67uAukC+rvv6+xwgUNqS9OmeghZSPeel3aNIv8OkKRCttlB6B44dtNfPvWLxXaTFAhydhuda4xBHOQ0oyWmHGDNV+pMjfyphwKMAMgBaY0zZOWm1Vn4BaG68ByxzZKz//D33El03IT5xkeva4BZoDbx3vVdHWdiofMpYLghAM2+Ex9Q/9Rf8m303b8VzKGfdDec9pRzU7/ifdMJ45VN8UR0c+AWcCMgLnYTQ8p9l7Lgy8a/4x+EsCoEpjrjLACvqFyj5YcIPikgFqbniFqI6AVGfD0pCanNtUJmA/7sapbCdnHD8YMzGXuOEY03S8sMVwKrZ+n/Rb8NPjdnwM2NWxotiBUrHqt/qspnjORt6dsw6AdLTEyjRNsD3HuakcX3exitjNv1Mznoe6ET5Fj72czkb/dGkcyTT//GVTiZw7M9PuE1BCfOCCrlmvEyiD0FBrQT/WxeutODhUh5ywKmo3Yy1gRVIkyX51anM9R7UX/Wn8aM+rc2hNonq2+rH6oMSMGncqD6imfgjeMXX72oHxZ3CCYkoTkpP6Siugr5rvPmx427yj7wTHn78cfvPAeZsZ/3ta/rpp9oqF0cBdY83Z+whuNlboX1oCMrpSN6B6BIKhxHLcrohpcYwfbs4V4fLlzUYRdSbMXb6ez+wR6CprKINxL3W0KxbBa5pXReTuKTn57HbvQVpusbhtQranBxu4KRv+3br4eRR/al+Xr9W+S53utf/iL6KGt++5Xb75je+6cBvhhd04OABJ3nWwD137pyTSH/1q191g/kv//L/sFdfe9Uee/QxjtxS9vnPf47d9hjHwMP2r/7V/+KkUn/xF/+O7rX0cHFiufSzmlSCyefSca73XzRJfnf3a3ZiYh0A2nsn9C2mTz8g/b26GtWDQHdbYIFjcSm8lRppd3XVBZ5z9+rSdulwzFYYsPzI8+4z3nS7JVruBGeWrDD6Ase1x1n02y3V+Ri/D1s5f4ZF9pxVS0igiFvOneV63BpWfA5AidLO9AHiDXH/JOD4Vkt1POTilmaOWqL1LorFZDq5jzgXrHjmPyKh2mbN6//QStPvWmH8dYAUdpdb7rJ44yYrTr3t4lVyZyzV9XE4nSt5vh4Aqy7z6+PbrS6e2shJkLHEMAtq4JEo9qgrVY6UseucSCClqyAFLcxYW3wvx5TrrRS9k0UhS3bwjZHqc9BIIkG/K5UEBpW+pCrwYCs6RQDAhFCkwW60eNOuWFLVwXuhvkQrp219x6g9cs9dDiDXA0oiOKmsxprAYwtuf+cvmIpzvYX6MtbTMQQgfPDSPH33gF/X2iQEIBf3yIAFXUuy5iXtOvL+3ve/Y9lOgFkXLwygGamZOhSQjKH8N8t+UdYlUpNpZ2VDzlYSWSgW4v5SBAG2KlYzJt6YtOnDM2zYotZ6H9ZB2mM2fTxr4y/Ck42T/5aMpftTNvLyGHtG6AwDBUv28N7hAheOo3S2Lmkt2xttijSqWOTIHsLrXyMWDwDIqZVJG9vLWOiIWcM6lPgOYksZQDH0+JhlDxQsnCHe9oyNvzFlU/s5KSK/lrtUBjQHXptwbssjigPAre2/AsVG3Gk7XjZ7RSkmFtIAeqgaCg5gI+F2Enbd0O2LTX5x5pDVETYO4TTgdwY6x3PjgGTAKkfjlQLADOcp7R/rtHQfll42Fm38zSkH0lu3wynezAYxEbKhZ0YtNgrKpUtLgt8cAyDS1bOnAfUzUZs6yzjCuVOEcZI/Bd1Di/vtYcvwftO7GhgWbBAoUQzFSeecxU9NGj7iiCvwUR3FlvjICtu59V5AZoZ0yJ/xcD0GnaCov+oEpVDIc5qSn5Mcq++r3KI2CVhrXOjPA54UklsfNAeov+t3UWlUZ117xUflId2GaczW6dRI6Yo2pecEup8GQG86fMRWsB6qOX9eYZZynAEoP49S9E6A/zaksHqTKkMKoJuAtqE+Kl6zeM6qh/ZO453MoeNw/LkWCL9c0K8HBsbtcXQ+1pNfGqD6ZqVshznxauX7J/jeSVt9kEF1HKEMOcyfrkJCrhF5+VpdWWk1fkbYnLy7eqVt2n4nApg2N86u1/FxuVrWTVOXi/bh/G3tmrWus7+O17zHHnnUdu/+kZM+i49VQDImBShxz3T82gUfcxrD7Qpt7R22du06u3DhRRb/Vsf11AK4qp+j5SXydTRB7N271x0HC0xrQtEA9EHXuqej49OnT9vK69i8ly/zpT5Fg3n5lbc5/voYk4pfLC7WtYbCeNzf858+xfrvAtG0FxJSbMzxiNLzv/tPPeev/SeTWYVj9fPfhXZxgSPdLps6+X8DGjlaLaN8M/SkJdp2WXbwCcAzR+pR+H0XvmmJvi9bBYCbH33Kwu0ft8IECnilEYDuZyz37r+2ULLfoq3328zZr7vChqONNnPu2xZvvs0VITf0hEXinRS12RKpHitPH7epU38DcN5sZQB4/sS/t9ab/jsW/OetMPAtC7U+BECvP7715Z//SXas9OIez+ICXJ+J+DCLUqAclEiMOnqFxJdVJNmeO17Id9N+BWsJvWCFUsIqDRuwmTuGNEhHteTh+iDAA8lh0IZI0Lx03rW1qql4gSSwvv3LJQCxTVsm/q7ds32DdbS2sCAGVir0lA+el6nvH8bJ0ddjKZ++nhrTAZ1EoCGwlvDiyy/a3nMvWf5elJhoV0lcZ5rh8fKfzMploTFoMZb0tZCiv2LVQq9AptuKSDl1bJyebrChfaN25tsD1n9vr517/YKVs2VrubfJTvyfZy21lg0VQtLJr01b/2/12un/dcia7gP8rIjbmb+bsOat2GLdGLeBHw5bBCnswA+yljszbp2PtNjMkRybzKL1/XqPXfj+qLXsaHRge/Rl0XOQsjcgOWxm89SMYuexnJ36m/PWCnjODxbs3Dfy1vZosx37n05b+4Mt1vHJFgdQw5KoA9xVD5m3EzQKJaGGJIK5NuBKL7BU0y1Fc6lqs8ezYiZ52kt5pmojezkOZwPR+WCrjb81aVNvZS0SQ7F0klOPIRZ/TlP0rO7pgKlwFtOOtKMsccxq84LSnw/ZBpRUoWVo8zFB5NW7mi3KcfZYHGko1mnGj49bc6HBih1swgdZN/pQuIPrrD9J3VPkGUainm1CcodUXvvNisbsEaTfjatYN1ZZM7zP600KLe6ygjYJ3tKHvmtd1MmN+rAAsYL6tf5073LBx1Mc1TeVCiCGALg2nHpedBYvuda6JwAvcH7q1Cmb2veqPQjAZqZznGPN+n4luVy+V/ObKBdDnJY81dJkq5AQ7wAPqL8qX4FoAT6t07qWakEMqhPydu5yYjWC51lOD4fZSFTRIejHnB69whVnoXI3cbMZSl6Kuf9pFKyf5W8nujd7wCPjjO/fS0OZI06Qgkvm5/qPzlEmtGkq5Rywr8cqy1kQtdExqH62+Xbr46RGa0W9oGI587rWad3QIFrSILmOfHrffvvil75kJwGpe/GA9Md//MfuOGr3j59wSkXiHJ4+c8buxFOOgK6fCPRidV8caoXDR47auvXrlvRONAnde+8uNwgv96CkuOJwf1iDJuSv//A1O1V5lNlTnNurD9VqAsrACmYUTV+Ln1aqSKHL00esYeWvA3KhMMRQugEYViZetUz3xy3R9UuYbb7VJk/+NeAFyV3jdkuv+AKDOGNFpEeZ/t9g0UZZaeoAz2ElINpljb2/acl2KCplPCeOv4IU++GgTA6MMvUg5Y6me5FIo7AH4K7kTsAZxjRX2w7AOgp5SKpL04dJD+l6+6OWWfunTso9Rw3RVB3R8TWTtTwEApZTqQHLzvSzGImbO+jaQi1RKOKWGxAmUJ3LQjNxgfrN6r5i8IGyY7T4KphhEtetn+ahdtIWggh+d5Gu9B/AejJ0zu5afca2brrTGhhnojvND++34M6Pf6N91zyipVjS6NNnTtsLe5+1/OZp3j9SVP4TWFYczT9u3zKHTwDeqYBWoaV7smM8AJD0takQXOA3sNwA6O15pMOab2+0oXPDFn0FayftKbvp91ZbZaRqZ78+aFPwhkM9cIA/027xtqjNnDhrXZ9roe/HbWLvtJVmkOBGcdWOxLj/N1bY+DtTNvAtNmijKIMVKBNgUyGSkJQXK+m3cLzP/XhbzIZ2wwWHrtV2Z7MD0UNPjlnhDAp16Wbr+XwnYB0FOjwpRsYBl914UkTxT5YPlKLAh+NJI31Xxb2b7LDM3YnjrRhgXKdwSR6C2AKnUqiUAmZFegFEK0+WbfLQtE3ux2vdKWgHF7AxjI3s899BqYt0J1+bto4NbTb67oSNv4Ylsr/N2eDAqDWuQ+rZg2QR0Fyl7WfOz+LkAQnqprglO8ds/JUpi7UgVX99wlb97grLHmeT8K1BTp1ot7fhtXbA0+aEICLxNSHbBIAvspRSHdVZCpFjYSw6XOixbZt24J1QugDByUTQJ9xjc/8IqPj79euPTif9GBLYVBxJf6WEq8wETKWDEgEAStItYZDAsECxnpWSrU6BJOHV/CwLHQKsEuyIjiHuvE5aBWC14dN9PScw409Glb8/SdW1B1W+vHOVeJ8LxffPiMbhedbKW7xpCan2PPuMrXptv63kJEa0iWHMyXViMi7KOyryPYoEeG6IvE9+i/1ZADnLe3sGm9IZ8r0nhzWgeUuNALOC/q2Xy2p0d6BPdRopeifPhbhWyCHRLtKGzXwXd1pSbs27yms1G4seLF50srn7KRLpzwIkP8uGZQtA+v8q5OwsG791tM8HGcYpm/jociJzrQIkKHtu3WrbiaWSLpRQ1Zc/rOGGBtF6Mdvg28ixwU033eQmnCEUhG655Ran/f/gg/fbV//tvzFRPeIM5h137nCKF2tWr3af27Zts1tvuc3+/M//3O2UxifGrQMptZ8MFvPSNfEkOKZ5/xDwMCssuB+2oAl3795X7NVD7NBjm4Pt+zJUIgL3VkCxWuP2LjZJSaJFw5C0WHzeZPtDgIBBzNFhczTC8ZumwxD8XPcfkoY4klUmOQXZRXYruPsW/KN0wnFpv/NEFPM70EEC8MstB6J5Vgv7XOCorzhss0jCRSkBhiDZWkGyHAUDAqKpNk40cNkMWA6HsSIQgQda7iTeLIskIH1WUmYghGgUhAo85Gx5lbtWnIWDZmsBMxZYJCPh2fPYV2UTkN4Id0+cRI7yQ0pvOSZGSVLestUohOhUR5tVv9gvXLZf7LsCChemLtjB2QMW2aTND6CJo0y9yqooOZy0zErE5V4NwA4gGUhheZ/iNyPNlVQ6zHsVFOUlOzpDsQk+OxYwGhsb7MKxQbo0ceEmu3NmCbHpm3HGTlMa/noyZykkjCnRfTAB5+gj9HVJwOPdAQCMJNmIYbNxtqCREQR17wrcXg+e3F3SlpWLMnHFL9beLImFjDCLb7wjZ+3drew9UchKAqqTwbigR1Jd/lO5QBaiZMjNvaNv6DQEdKQ2cICZ3OfAitqE+HP8cL5GkaB3P4zCIBLyEop+rVuhBWxCKbQJvj5OYdp2daDvWrH2Ozgh2dBsY6cmrXnnrA0lMUN4E1z3u6AqcQgkyblUJqpsEBIrcLQBRaTvt7ptdM+E41Gv/p1ea94ClQOJt4C1poh1f4SjlLUyx8ZzAkZcqKzVeCB/LCSKTiky9mzCVjWttp4VPQ5AVzi2F+AVmFYQKJZkVnOnAKSnQFy4cMEBWlGGZClGJzySCgsE654AbpFjdg9ClU7VnSZRHkCP/hQEpr10WYq+As/eTb3yVGjlBKmAdRL/br1EWOvbBGudJMYC5IFVDlnYaXJ10FgX7UObQ6Wl/q009OfnAV0vZZ088e67Nv2T3bYD4K8ZLkq6jSiMui0U+Y1AdJfJOJhHDlAnBaiVJ3F9X1Wdlhomefh5KCdTbE4+MQqFTy95kUF5VyibOoY2wuJP62nRPeTBUOWaYHzlUCh1ZedGqVbmST4hdVmatpb9asn7m5kXRKD4IAMj1s7TFo2MX1bCa1Ia1fCpRpwf3brR1m3e6vqYpwZ9kHW/0rxvaBCtiebhhx+27SKus9t97LHHTMBYC78G/ldQJDx48KCbCNasWeOUhzQY/uRP/mROkeJf/sv/wo4ePeriKA3t7D/ML/xKO8rlnpOJsZ/uOWSjlY1M4gKbyxMigMsqHNyqd0utldZNU/q8dIjEWKiwHlGcPsjC3oTE+T8ifbvNYsleK029A+95M5LhN5h9OciLavq6/MQ5W4QPPf0OR8PNVpzYZ9FkH89y/FuBjwlPerbMkXzhzFyBZitYtEhA6SBesv1+x5+uFM9bpq3Dxqe00GjDNEmfwoY2wFY0CuZRgA3H9tA0nC1mUivkBawVNO34yVWfqr//rqla5Q/aJjG7H5fl79BmORwUbGTRuZnFvibZcEBf8RV8Onp2/j2fdn08fw/56ewZ29B82Hbc+tDcIusVhvTER+G9LTA+NW573nreRrsHrTHUYDPY63aBly5pdBXPeQ5kCiwi/dU9gUsF1+rMSS4e3yIpHIx0s6k6xPvdAhXjeB5qBSa6AMKyKjF1CgnzaMVmcjNIQFFko48XpWSKSS+BddnYlhQ8GuFIHRvugzNTNnOAcXYXEjQkrpEknv8AjQpFaBH5swWoEGya1gTUI0mvRWFI9GCCrj1uXXd1WG6S509g4q0RKglhBosuCfiwKruDmMLRtZXG6RrrFylLUg5XV3V+F5d+GFTYdcngN9rBdVF+q1nrUFdP35TkdAhHK2xGoyiDybHLFHS8ciuWOj7eYRHM2MlGtfjl4ik33oat3gew8DPESBlDaRIrJJk7tJG+OJJUnvSGJHXVmKStSVfS8PQGHHOsRsmWfJlWXHDFJGkH42rDx289qgMA+rNJ24qUrQfThxLmSBo8MjziTmyyAFoB5A0IdgRCdQqp9UjrlbPqAlAWGBVnWGuNrv1GVcC03gKN1iMflIbiK44AtEC3nlUcSZ51LVCsPDzA7aJ8utZfZ2cHcYK5oqEhcJik+wL7/qhd7eKD8hCIVz6y/S4rHTJtJ3Ct30TZUFAdVTefp3/ef6r++194wToPHbVuwJu2UhE2WU2ASpcfebbNIBgha3kGlFQ6rs0CcSYAqGmVAeA66zacGj/vHxSnQFp7cBl+DIn3Z9lodFLOpQS35XPtwca37kGo/U5hMMRvsm+dkJSa36cYEzPkqSClyR42xQfYXG2mbV7nU67Jm7n3QQXXJpQhSx9YycmqJOeemrJcZVIeZ6nvoZ4Ou/O+B+mXWMXhtP5SfWO58r2W6dSmhGuZxQebtiYfv8Br8tCfD5pcZKVDA1UTTBAi1o+mqA+aFGQAXuHD/KJ9fZb7UxPkvnfetZfg/xVmbyF5345Xn1OxGEh/a6toLcFgErpc6uF4B4qEOyw3/LQVRp7j/bKgNH4RCVy/TcNjnnj3f3fANt2FuTfoGlIiVAjFoaHEUfSjDlEp/DM0VcwAAEAASURBVFXgxnGtaTk39DR86T1M3HAgoYSEwhhDirYB0P8KKTM2URs2Aj4wtZbsdEA9s/KLWAnIWnFmj2XHcAmeWYNCHotUopeFQItO0KeqcDGdWEzLscCuA7x+SvZt6Reu4Ls2ejJzphBcB20i3ncGAN0T2YPJsGY7UtrCAgYo9yDaTeWAF/d8fTsqfZ+eTPT5fOvjuOx4tmIQpOymtT22Zs2auQU9+HX5/9XY9ONOfU1BC7KuBUy0wEv6NjMjO7VNbgHXouy5nJKuCcToGS9pEyDQtQCHgIcWfOWja6Wra8XRp/4uzg1Lr5+eP3rsqO0797rZ/VXLtrDhQtIcxVqEghTrBBYrgD2nhOfmIUEz6s2C5oJsFfNdf1Lia9zaYNnv5e3dv8D7ZCZmTdsy1rq9yYrwfo//JX0tHbX0qpQ13ZKxkX76doOeox+vA9xg0zlO/4utlLOULBJu+v8U8u3dZkNHx6zn3g7LAH6a74EmshvLFlmBGpxTrIxBYUracH7csmdy1n1nhzWON9uFx9lgsjnLrE9ZrBfFu77g9ETlV3ldT6Y7uRrxZa5eUhDkP7dpqNVToEQxFJzLcER7znKIpNakJLqHC3yVQmaq2IDN3QneEZQKJO0SnfV9CTvmXbQvmwdJy0NjYVvZif3lQTYQuzmNUeRJ2qKRzztUOr9hCdralclZElGOKiOFF3qrqS+48ruxwrOUW99VrmgFyyo4VolNQwl5o9FWNK60m/s2un6kvqc+1IONcvUrgUv5G1C/FuAU112/qx+rDyqOfqs/4hZQ9cGPB33XGFCdNA5ySLSltCclXq1zuq+4SrM+1D9f37frOdsJwKkPGkv+Gb+W6jflqbT1m+qoeula40njUc/pWrQSraF+DPp4Pv2z0CzPPfmkPYRTmajeD8H1heDSfU/SNvoa4/dmLGP4EBfvnXvysDeEU5NGOM3pWlw/i/m49Z/Q5O2VdNzeScfsi2OTAX2hPsIir50yoboO9XYdkUv1idr/dB3eTa1OGYB+B9cdgOl34Yrfxkbl+fPD9lVOFjjnsF+iPdvpB3XVXmQpli9alnoUNMdD5whafPnSVkpq91cbEpa55x7bcPMm+umH0yJHfavc8CC6vrILXWvQ+wliod917/1+v9Rzvwj3dVT43CtH7Px0HxJPTdzB8e3V1F12lkMyIcVsUmWxdHZxAX7uxmISBo2kuj5lyda7eX4SaXQ3EiRJRZiAU6tYuMcAKJhnAmzr3iygUeAw3nSXxZp2cA/pS8fDEN4eRWL9Ose8a6yh9wukA5UjBhCG3qFz4OaN/z0AfNSSGZbaaMqK8I57bkehChN62Zk+m01hFitxzlrQ4A5HJaGBWtIFP5m6yPzcwm0V9EcBXS0lQXCzNJdB26p9/LPBtcAlZYAvG8WqQLGEK+dwK3fg6FEWl1Td1Pze9vT51ae9sERGz0XsiHXifOaTD33ZmmtSLS36AgBatLVQLjXoWfExtSDrTzZoFaSToONtpalFWIux4upaYFfSPCkG61p2qGUJQJIxxRPo0HO6Vvl0rb4qiZyudbSuxVz56ahcYEYnTYqj43XZqh6jHAIBXVJEBqzoN22qVQaVUdeaG1TvejBSX38B+qdffspGVuDMBIM1UkZz3uzwAKggEO0ksjIHR7NL+U7rsV6XgLVMx1VLwadM3InH2rgxbcl+OPsDHOvD3Y1iVUPguv8r3VYelvQVWlAn74EsbvofVrs0BA5X/9OVgNKgX/V+udNmsW4Redqs5f4Wq64s2PqP91tDS8q54u755XZrv7PVEtiQDvXzbpHmJvFY2PHP263YCFWglY3pF6BVDMC1RxMq1gFQpAw3/Y9Bfh5sus8aiBb2lMRdlj7kyEXgnA6lEejaIowNatEiFJynQz5VbjWIi0N9GgebbaoVGge2o8so/jlzelLik11sPDo2NULV2EvbDcC7nWB5I+nwCjZMq7EQ0ZlzpvnCT1Gn1cHYqsF8cgrKUKatnTKiG3vKNbivMs0F3nd8MgCm5Sak9Fk2cgy1chRvnKM4gxmYsj/85Bc48exyfUT9T8GfYKr/iT6ooP6n+4qjPqk+pn7o47pI8/5R/1N/VRyNG/VBAW7REhX0/VL9cV5Si/pav/7VX9fnIepHhg2dgsaVB8qql6TfiqtxKqtY69evd+XXGFJdn9v9hLW8c8D6nDUIvfOLM59LcP4/tL8PDXglVNDbjCLxxfIiZiJR9MPCligUEdrKz6IuYu2ffcmYvYSr6S/huXClA4y+B9THuvy1yhlHKl5iTIqipb3exZIFzwrIK3/FDVN/rTj/Ne600U3ES2LJ7kaR8BTvsSmTstWYlFN8pTE/HW5d86C8pxlH2BiyNtpYZVio7a60IEr/LHzxd6E43X3/o5z2tzo7+vX96ErT/iCf+4UH0R9k43/Y8xZ4OHDkFHahxy1f3u4WtOWpE6AklLNYHLvLuS5ASjCULwLG98slmILCcY4wmbYEkPWnEJG02QLKib/niJrcnb+gCsyII93cjIIgylgl6yWWFnTMHiVHsa7AUXlxPd+nAG+SXEY4ml3FrwQWdomvonCSHeB1wFf32CBwXBbkHQBYRQ+kRgGYn3WSN/0WfNfCFawb/p6AlqYkPefbRgCXY3XoISeqn8GD26NY3sDBSCU4Rg3SV74B2L2YNukoDf5CnFUH6WnKV1715aLWSO0z5Zfs4w9vcraQU5KoAQgU8ig1TU1OOC+CuifwqUVeC6cAqBZ51UPAV9IsgQfZhJVnQl0LuOp3XWvhVXkVtADrvv70nACErhXHO1lRflqYNRlLOiY7zbpWPIFh/7y/r3RF6dJ9BX88rmtJ8JSGfktTv2St3MpDZdN9tZHAuq6lzCVHLL4sqp/KrPqqTofwTrh/kI0YdqHFdfahmJH1Dfo5tIYIymjO1BtA1ZVI7x/pp+gEyst9spxJGU90Ai1v0QbaYP1FaaHuCUjGeuZtYmpRnJMM8qtV2Um9S4BZSVGb3oSiBsAPrUWBi/8KsyhE0ZsSvTHKRpozSJeRCkex8jLdh0UHipcsJlB+LFpkHfQByuuWXO4LSCtIgisqBd3exReVRN4YNcYUx1mSYThI+s5NLrgnAO1eO08rTdpA5vnS4ygCNuehbhRtqnECngnx4T6DlqCu0M8G4eSe03fuU84QSGV2AygFiXS4Q6bE4owLuLvsKmAi0Y05pl7PBiRobVfWCuA5CqfbmV+g79HjXP5hbeLxeFiFe54YhfdNG2cbcUVd0z5TfWZkK1r1RenSTsbs/p5HsLK00lE3BC4vF9SPfZDkVhJg9TXxkNV/1K80FtTfFLQ5FHAW4BYA1UbT92P/6dP7oD7ry6H6+TpqTK5du9aNTV2rLkeOHLF3n3vSdqUxeYiEVo5H8ihKxgGmiwk+lnpdD5LeMm0VpS814WabyYIuEsIFd8paMVEXZyzpzZ4B+L6JKbv7UVpcQX4+jcXk5+MoPz1XgH4S1bygU4nanOXj6NOnHcxmwS+9zP8aCUM882pTxrYgWZfbcY2BKVFVSEf0FIpaGw/Bc9f6X5VV5u1CUMrUvX3ZlytfDduD6YS17tjiqEzq75fbLC5Xvtc6nYsj+Frn9FH6N1wLCED88MnX7ezUWgCBVq7lqaKAg7zl5fPwEGvg14O+peQQAML3PrHQvffEYOIKA1Y02bKKWiLTa5mWR7AMIPCrQzckWvl2y+VVXxZd7ojb7CdQX94gTTVIMBUF+QYNpLlWC43uXZx3gSGurkGa9fUNng1mVF9+n1+QTpBPCArHWPVXbPL8Exx7wrHLv4oS4xqk4YEHMg/cVTZ/7dKDBpIffR5qwCY4t6v4LZBKXywnkj7+C88esw3tF7A288vuqFaLoBZ3TYSSrEXQMFcQcBaw1CIviZmka4rj4vGMyqy/devWuQVW11J60qeCwLLqp++SaPlQP+FqEdafD36h1jMCIT7Ux7nUdX26qpP+FASmfai/H6OeAuTKS2BZ0nDlqTL7hUFgf2BgwL737HdtpGvIUhlsDsNLLqMgmBAopap5LEkkJpH8ojw7jY1vEnTZOe6nqAz0naB/0Ifc6w8W6tr+ycWlCwULuFNW9KWd96n+pv9oLge2ua7i3zh2JmEr29hkbIOysQLwAaxUUL2SUyk2ibhlQeIrRyhByKOzCNikvFFOVYrQpJA/W3wGQI1CnczVRQDLzvQbG4aAjhL0ebn0FiB1SoWk75TyAKQqj+oQFmVFGJroklYn8V4oJT05hpmOIW0dVJkBqujNhkeoiOLm2UhwNCy949DtSPQ7uZkhPYS8ztELhXbp10rvgDtphJooG5sQAV/XxrRzhPw1/FT3WF5KuABXFCPjWQA4harERYWp0QhqvykFlz7PsRsyXJtay3Cbbb17i9uMaUOm9BYb6gGnNmLJJN4bmWPVl0ZGOPHiu0CzNnPqZ+rPS0l/seW4lvH8WNOn6vDtv/+6rX5zn23OlZy7bOU9CMBdOS61O8YIoDIFoBQt4nJBvxZrcRQ3U7MsI4cozbJ5rd9pr2PNDbaXjU0/yrKbkFSzr3T5XC7thX5Tfmr7KIC/4rnbC0Vc4J7OnhRUpjGeH6NcfThhkd1p906ZPzWzTbKhSgDyYxrbfA+e4uIaBKWvbpylLI2se869+TLnM8A7P7mq326/7xHHg9Y8/2Hrvws1yUcgeqFW+ejeolrgzX377dl9M9jJvIvF7yJwWdTDl4kUYmaLxSZRrONothY8ePTfl/sz7ByICGXgzppj4nKlAUka8jgW6HzoFoAhgB5nEZrIXFmYaDxAvlxZLlXu996vnx5ZjMXTrqCMAu86EOUpB8UBVFUAFBEd22qaFQAhPvdlkaQoOg2S58L5b3HEf4crpxZ5H2ar0r1mqlS6tTAL73u2jIdJuOOiqQhE1wdXTqoaCk1ZW/UN23nbCkz3BbxOAWRJy7Swa/KXwqQkZAKcMpmle1rwJfX1C35gOznIwS+o+qbf68P1PLmqbB6ou4W0Jk3UtRYGBQHqockhe3tiv5XuxVFKM+8USbNWwzLgVJ/qQXo9Jb6LJ52AFiCQKRvRMpkWQUpcbpC+PlAPioYDmnpEYE/N5RJQIheDiydwSrdw+K0Wx4M9PVceBUS+iF1xpH3RjyG8XcsGAJfYUSTiSlSAGCvIjvqh8szKXnUtKLlyBLvXcKn1viXhFkCWlF1uytOYeJxsmnBScUnYK6KrADrFcU5PY4YtBQ9bFjuot1xu2xhp8J+oLqq/AGsepdjCAIAZ7rJJCZBoiCehjZAHRaxiti/UArCQTjCA2KERoqpJFmwUd5/n2MTYEPm1y4kT6VN/Jynn9+R02pnQy6dxXlSHrAppgLMqrfKKCkNdXPsz3an8cxsaSeyPJe221q22vne9O43wG7ta9ov6UL/RJlT9S8JnbUADxcA2N64EqnWyo02n4gpgzx87i8roA46kssuk67vf+459aaZgGSgVes0KrUiRBYTFc5ZUOkEd2bvZFKCyoVCc400HsX/2X6WjPz88knrPDIZRXtazWCTpHx5H+gvlLY0SKRJqWdK4muDG2RUkkKGO3bzrQ2wUbqWudH5LUz8FlZ9Sc7hCv+KnCTZQjbz3EHGuVShSkQnm4R7aQzzz5QzaIByFs57edof1rVrtTv+uZHwsZ5mWK62PQPRyteQvWDqTk1P2+OO7bWD6diY7VsBlDCEWqhjSp3oQvYzJzyUVhsPITMVCBF0jiWklTEXl4TWXcTVeRVFIvOxMaogjuxbuZdwCL+l0MMXNJXOZi/qJyF/7T//Yxe+iq5SwTZ0989eITfCaGF+Lia5/YZUSVhgGf4SZvhEL5w8jbdthmb5fR9J8Hqcxu1kgkKhlD+CW+B6Uvz7hEpY0uTxzwjmAmY0VsIX7bSth31oCv2TvF7GffadNn/k7ON/7WW04asckn7w3ekl6LI7UnQ1FuSTN/Lw1hPdjkWPYtm3d5RwQeQVdSWL9It7c3OIkZ/ouKZMPHnD6778In9pMfPeFb9tk96iFewFuKKspSHoZKBMGrZDDxrAW+BB84HgRyX5cyyaSIMzaRTjpKOpoNQ9XPIdNYNmLpv85egGgV/1QANWJkNQtCR5ou4W9ds8Ba3GrZR/sbWTH+5j2YTWF78XWMXxq5ac104FC0pdkt5hhweZ5gR2VT+A2MOemXLjWoq8rAKdoHQoVlLzkPEaUigiS6jhKdlnsKQvdJqdT1n9gvU12jdr5daeZMwCK5zjBeBYLG+1sAG8DOL1OxljN4PwH8E3aAsg4d6kAesMtgCyctMg2cwjnLQ68qnyyOuLLUiuryqLyyowfiQUgnjqEc4yTcf5ugo0NvaNhilMO7ucasDONlQ8BZNW5CG1EpdD/FcrpzdgpXW7NAWdfBgHx6hAWQ/IZu3XLrdbc1PyeExQ9d7ngwbDGiQC0TjACC1Jw0PEaqc2mNqMKGuvapAbS6RH3fqQjoDHn39Xl8rpefhPda8+TP7XNx07YCiTNF2dBONU1IKm9TDOS2MCUHS1P/9Kr5tUirc5YBxxip3N7iUopzTIPjAlEc/0MDm+aJibtwUn0L/gu/QIpMo4BYosCqYD35BJAqiyFlLWJUafRnwq2hKC81yCB/8eOdrswiQnCOkGCUhJoVsNoM6F+IXvTWhur9AFtMt5POr+Eorj2z7FhmWGstkHYVnstZ2BbbUf6u+0WfHG04thuqac0y1mW5U7rIxC93C36C5CeJuu33nrLvvcq7oSrm1i4Wfwk+lqmIGXCbC6gICxTknPJRHAuAURHmsSRdew8814D1Ix2FAEv5lfByYsLoImZfA/KI1g40OS6JAA9l+USLljQh3+KoHgtXtF+08aP/luA7rdw2HK3VYYft2jLTkuu+29t/NhfOI+M0WSPlc7+rcVX/Y6lVv0+nhn/E5SKFurHhIvUuTD+hkUzN2Nh4RnLDnzfmtb8PgZHzmAG7WuWaH4LBai/x5zXHyOhQ+p//uvW2ITEFDfrlaq08TlClRFdk/ULnKvg4nvn5lbHYfb83/kVEwjw4PrDtKDPr8dyfN9/bL8dPnvIyp+Cs8si7UAdi6BsEkfkkswHAJiTEgMMp5D2yx6y1mMBbUk+BdDKUAkq0D2URroAjzCHEhomEgVUk0iss0iuoVm63wWJJXENFBKDT3eNaUV7jY3hEQ6Rd5L2JoApw1Z8Y5kWn1nJe0/rfQdAUZ9yL+45zgIKcrgSlJ08KHUAv2v58rtMrDs71jxbZINa7gzSi+ApsHG4xRqGG61rsBdJfMmmi1OW/w6gaAgl4CiKjcdIcwXgdhOWUvqot8RvHJgoP0qt4hD0KXihFtM35Rn85kG+L7MDNrSJgrNJzQNyE97AeI+qrQ0FXOgakqBLabKIW3XZ4Xbx3XPKQfj/Ynvqe4V5LkI89W8Vx4Ftpr7wwSimym6zm9s24OAL04KMhfcLfozIxbYUaFeu7HWAWTQoPa/Ni9+g+rRiKGbpT8/qBEhBcaRAK6AlxdkPQ9D6cebJp+yfOiDs3+97Sy6QqMMbBRFnWgB3+ipTdmUAn8ZJgesq9U8QNwwoFtAUGNSblC1pqSj/9cpONkYp65qasN8YmUBxLshPtqi1ajXy7AzvIM0cP8mzksh28Oz7rWhyRqJ+J8VCbWpcgUhvsUF1kTJlEiHJCaTi3XCja9V1SWh/7ALlaqY8kpjLictgU4O1T2exThNYlV649WrPLuEjR12K1D9NfZY7vN6IUAXvhGvW3+Qc4N0oUmi100cgerl7yy9AetKq/saP32TRv53jVRwrLCOA1vwWDcO9lChqmUI0DnBGqlcty1lBwS02MtSWy6+tld3PVhczlLtxefgrl5uIH/BdL/56ra6QOgKYS1NHrTB1iLIBdrBR7czwJXAA1PlprIdstXTXx5zEuiorIc07rLH/nyEdw9xU81aAzgCrjAAwiwxeF2U2ID/2Ggstjh1wP17lexKXxrI6Emp5wJr6HwJYn7XyxMsABJy/II2fZRNTrFyk0kRnh+HOjttNm+51x3CSPl8u6LhZ0jQp9d1Ik+Xl6lz/m8bH7r2PW6532mIrAjAlMKbwHgBd95DDb2jzCBw1TLKxS9JPnaIdPGqkuQKF+i+H2cQsIDDgEBNfgl5+i+WQ6mLxYxolN4GqMEp32F1zv8+e4fvbTPXELX8ia+E+aCdjzTbdhjfL5iknlXZAnmGgtDwlRB79FCShlrQ3XAP/AXeYH/jZ0Ua4cFMAWYrrHFH+pOMQAR/iVjspayPWGaInLXE6bQW8Dc60T3BywcatvWq5R/ES2ItpSUx/heFs1CthukLU/vFgWV917aT4XDvlRsrvyywEpHsVQHJmiFOkJE5NxguWTWABoQNpHoWbFdWENJx0X+WdF/xmZA6oI8mXJJxHyJy3watVGaKjWKY42Wqb7ttsrYDYBE5tLhU8cBbo0hgR6JUyoSx5eOC8mDGjetfH888qfVFAJLnWOPX5Xao8H8R9ndK8/eIeuwX/C63U42dn34VLNRcPUNmLWTq9MYHlaRQSIwBQrRhDXB9ftwYPmUm7Y/87NsVm5HxTqw3yfSW2091GiTaaS4tnIoBGkbB0jz2s5VB+m0XRT0C9Qvmk5Ke86p/hq/ueYIMcE2inz6tjzI+jeJcLcdK/JVe015rStrVWh4XSEGDX/RgUupWjkuvS98h3EKXJLswJXi3NQ+lNshOP4qQshZ8DhYXK4X5Y4j8DbPpOtLfazZi16+jqdnzoJSZxXUf/CERf16/n+iucpB2v7Ttorx3OIh27VaIZCqkhuDxBU2oqNWLZfDcmvgRAFp+2jroCyxbImqN44kLtqVyGjgDfuYoylEBisShwqHgXeZ4LlVwUhlRyGKDdRRoy+qPp+tqGWXjQ+eHnmB2RXjbeCkc54NcGuQowBBN1CBFiaBbupidnaiESmqqg4U1J+aIa8ilJoN4Pn6z4qVTBcjNRa2rpxawbkjiARgUFTlnxkNOXQhH30HDBmZFr6bipGl2tV23npkZbv6p7zlwVES4ZtKCL+6zPX7Sg8fH2O2/ZseHDVn2M41i9Cb0CNSmvj1d12aDfi1A6Krh9F7jjglXeQT6XjrqAktD7lYRaf3rFooGI2uFAIVzqBNYzsiHGwHHsKR9stBLm3SI3sdh3YTGFE4Z8AoU1V7CgTLp06XIh3rHSr/3s6AtKew7A8lqD37hHvZwDEj6n9uP+uhF7wWvhdqtQ/uSG38a6hm24lw0enijK9NsIIL86g4UMcZ5nQjbwD0PWsC1lHQ9zkgJgV1l8cGnVvqh9HHjmu7qp4y8rstoFCoy6usz4RdlUyHazlDdlG1tyxVkU//Av41yQu/eguvJoYLkkaIdaNu4Df0pz7aB4As2uXfy12gwWyOxLEbu54xa7bdXtjhN/qX4v4CwdAoFfD3IVV3/19Kf6Miz2WoqICk4iyqej4Cg/2UOH/uHpIC7SB/iP+qe8E44897w9iPIgb8wNjSspEs3v6Bht2ojxRc5K8kh0J/t7bHj9zc4N98TZszg5idomJPUtUEgkZZbUWs/6UL8SyB51AgBN13Km8iTpjjGm8zynPpAAwEvaXeQLe1krSGKt9PjTM0sNeuY2HMm8xunFAE5fVmGyr75sl02PssgKCVlbAaBaoh9laq7HVdZFp0NcxR+knRrLRbyaUhfdWIag+r2Willp+x22YeNmt37U68IsQxYfeBIfgegP/BV8uAowMjKCd8IjNlTYgIQ2mLiXswYCwdlcB4vB0gFYPCF7v/AF5S6byc8FFv9CXmbtgjDrZof3nyFKRUyraRZCkiVX3KVSI+le2+EipzCV3GksDmwAmGA+rjKKVBBQC+gIFS9YAaqHHMPkUAKMQ9MIRzMooJ2BL/1jjr9brQhVI9Nzj+XGZLwLugrSlwxe5KqYHyxnTzLJq10qNjaDJ7PUZpsd+Aa0kCfgVg9aNXeM+gZAPVAmDNooYqesP3PM7rzjE44LXW+xwrfp/E+BBJmNk0Ra4XpZwOeX81p8n5yetJePvoyTE04QcOjhe5oDYFrtuBOAwOAXLeeS2moR1m/6XkjAR+a/CEBQJvAK6YCf7MurqDwSgFr3DF2EfiprElo5ZUouNwiwOIBUdwrpEnvd4mqU6dhEJlDum2jFiUoDIB3QKcCJczIHnEnKPa+yCIS5UPvweSt9ldQHZ3KP+OWJil34wQiSWpxVfbnbSlg/KI+TBy66030pO/fmefohPXAFliVwzFJGubCCW+eJEYBUHGXYQTaOo/Rbhr1sLWffYZMILSV9a5ITGNkxUL5BWwXXQRuo7SpIiPVcAose4pFPZ6adFF/9WOBfVj5CkD0jU6SzifqKMqNE+Me1Jc/6d+LfQ5BHXX6gAW1gFE/SzCAe987DMT8TtW2P7XAKgEmk0HNtRyKKlwXoxDBXKKsu+q4/xdFGsz6u8rzaIImoN9no8/KfU1PTgHWswTA+P6ggxcgDe/BOyEazC3Ba35eupEw0pQvufXKdRfo+Eo1b2/iITXVmLJxN2W++e8rWo0goioZ60uXyrAfCMZQddRgjbrYUHMuyloFFjxnA7v51a+2m06edzsLSV6qLNVVZmuhPq6Zn7CAnhH2AaFeXi1EWvHJ1oPJJFVj9CeDLttRtSsQDF6tZpvL022LDEP17Jc56LsczX2xaiqd6nGc+ONTTbfd97BPOvr9OR5a7zy+lTNci7gc3mq5FbT5K85q2gKRs7xw4aG8cnrZc+d5glCxzjrLMMYsoLJAov3/i0egMC5voFnFHuxCPV8+WSjXFNs0j759MEIMFNyweKiRRpicks3AbnZKR0pTM5NqGcKQBxcBHAMnPAzim4EDvsjIUDIHrWbwjlotsEgDM0fRqS3d/ygoTb2EZoc1K2VMAjjfwyniLtfbcDG3j8xy9w5dsuBNJSbs1dHMvP2ATZ56FTtDhXJEnmrdxBInZteFnHRUk2vawhZOyqS3pNUGNxnWk9Jo9uK3X+vv7Hd/5UlI29wgTthZsLeSBaTt4uyw+ko7pOSlESaFI4FrcaZnHk6MTKUbpno55dbytZ6dZVBoaAjNecisvCwVKQ5s4gQSlNTPD0TxHkJLi6QhbHbIJ81hycKI8ZR5P6apMAvL6VJ7+2pdVZV+OoPTeOfaOvTzygpW38c60+vK/Fg2BLwXFcZ91vdL/pkVH4Fnx5bxBWyF0O6kjQBFAKPDmTMPpd5IRNzcAf+5Bl7aU6SqHkdC9CVzIVC11B1Y4uticNUBnKAPmpOiHnWSZpktM4uWuGYk01jaccqoSFVhUum5BBixKGRGUIAC7UH5BbUhyAkstJ8J4SyzaxMFpO/d3Q1AzItb9K+1IHXFH/uoMll8YQ4zN9X/aT980O/035614nj6GN8XJg4DKe/B6Oliyc//foAPl1Sx96cWQrfq9Hkt0CoAG7aOyKFQZrzE44ZmpDDSWSSuy2cCwjQuzMRyS1Arn2g19R5NiYaPqWgeGqadrc37Wpx7R7wrvyU/DXz/opg8SYb4atbUr1tmt6ze7/rYQQJ2amqTPxeEw46mNfu/DtQITPl19egcsmrvHxkYpR88HCqKHMH15/Mmf2qPQMeS6u641fbNc0adLh3ezZnjUVj71vPNsKEVEJgLsm8MnJtWl5uVmfB4STm0BgJehwkkKPdTdYqdvv8lymzZY8Ymn6RfiZ8/rG0upBc/ehKfFV1EwnJguWAtlXnSo9cc471d/CpPaJAFe41geWWzQgfJApslux5TicgU3PJirm+643dbdfIujF2nevtHCRyD6Rnuj17A+Aio/ffGYnZxcy2QiCekSBvsiy5WKDzNpYXC/3PveBavueQFdURkEnHWmi8sFKAlxLEmoTJoqKddSZ0ylzzNSyosj0YuiuJXHxF6Qppc1LH9966rlipzs/CS86IeFnJiYUYDEhnNp+iAAd4Vl+r+MIlUzQB/OpRZ66i5AvXLrF5GW5ACegFEk+OmVW5nXkTymNtAcwCEWk8Y1f4Dt1DGe0ZCXIihSvt7/zIFxOX+xMObxkF9EogAugInaMBY+YlubX7KtW35jDgQLBJ48eXLOucj58+eduS0B3LMcnQq4CgjLM5kARVtbl3OwoslT9wVw5SzC23/20mqlK4CtoOtyGZNwkq6wkgkA+KDfHP+QGwLKfHWhzCJXqWgD0OiAs4C48pDkS38yCaajdJVrw4YN7p44qXLSonzlJMXb4D1z5owD9pK6q6wCPqqfyu43A0pfQXX05SuT/4tv77Ex6Eji+eodQaDAugqSIszOKTjOMe9EgE1BgNDFob09OBSA1s85FAYVZLlD5uN0kBBCIVbWJLXXqcjih/qsTlcE2JG2hvdBYziGIuOtSF9vw9ENfcTRPJQ6ElhnhYJGEyjPNxYc9zhWhtM70WRTLRP0fvHpSY80qwBRAWgZsA2zGaqgaCg6hpRy3TENRVLZBbiTfQlrvp2FuwtO5WrYqbyy7k+2W/NOXHMfnbG+30JBtwtvZf961KaOy7EEZRmu2Oo/7HV9NHvmFJtEjuL3zlhlvGp9X0a5jpd/4j+ctelDgP8m+iz7ArWlNhUqs6sLxctK8kwZ9L9XhPQbE7Wf6zPHAeFY+6h2UDCqoY2Es5iieiqS+pmuyrSviLF8qu7KT3VWG0jar/vuObXJmYi1jrTZFz/763hKbHwPJUP9RvOl9AKkKFhPs1B2P6/gAbX6qTbCGjsq2+jwkK3s62e8B0qKPt61LJfGyZM/+pE1vX3QulGKc5uSZcywRL8ehNoxwWcTfbibMauZbJR5oqDf+Gyl76xgvhMXeSlBXUbeDwu031hvvxWaOu0k6dsj91rX0y+y/jAX16Wp+IvOgWdRU7D9+ayjVLTAjb7SoL7corZFoq1pYRglxCRgWoqJKtOlwignJTJr1wkdJEQdLxf3UmnMvy/vhCPdbbb9E7/k5lDNoz+Pfja/HNf6+0cg+lq38A2Svhaig4eP2ctvTSKFxi60A2PLXDkmoVwBJyYssHPoqJZFNB5IFCtwnGX+juIAfgRg4CuLC6kbVz30lS8WR7JSDgpM3kVjeSbDSiDZRor28whOIbBWlxCAOYw7uVjmJqTiKP7F4ZuCA2IxgAh7hkipCyrGBbiZJ62de4XYHTaVl4k+jq/FC2exr8r2dewC5p5QNKrEuZ7kCDxou2iSeChyFgrylFawhsSwTZb6uDdl3dG9tmvnFrf4isfmlBV5RwKnApNakCVF1gKta1nt8JOkd0Yi8KDJ03M+xd3U84ovYK1nFCQd9s/ovtJVUHr16b7XKQseGd17xyxTW2CpQPG9rWY9r2vlqfKqHGvXrnV5qzzylqj4yk8uvFUPBUm6PQWlxPGmFn+VV1Jz3Vd8KQ8qTUnIJUFXPc8Pn7cXjj9r8e0xjn4BynIGAgWoKjoGK5q8A5Zlwo5+JFAs6xs64BA4dQpx2iuoK/PpeMnUTXET2CeP5LHCkYRPC7d/FrGRAG4lRx6cvYryMXsWyfI+JO9w+aP3VC3ei9SfvltypF3SI2ml6xT26OZyLy6nKMpPmxUB6DIWWeIVzKkhoZ5q5xSBMrpyEk9A2Z2F058QvOnF0EMFqEmMxGVz2Y0/bRj4L9GN2cib6VMCLE0xm3glaKPKIH2SU6IqZY828Fs7bc6hUbKTkwLSqmQB/iNFu/CjYc7Q1Q7ko70EZhqkOFnG8UsIIBvBbnQJCyAOSKtM2ljQXpoFFLTZULm0gRDQL53FTfaauuVOwFhBmw/iiX+ubUxIAJprB6SpkuNFK4reC/EEqF1c7aEO4ylz9QbXP9Np7MrTB9RH1N/Uv9RPfFD/+aCDL4OO1Lt68OpJ/9XJjPqvNpB+7F6rch49esyO/Phx+xUpPtJ/ljOodX/KWP1BPmdppLBT9McvJlJ2LxSa/417kwgS2nkHZ6jvF6DcfDyBV9LLFGCSdylQnJ5XzlnSbjt9EontAP2FPsPc0MJY0oZPa5C6xZvk0UGHWUXcy+VRn32S+IhH7BTlWgOIvthz6mMt4ZqMtWFvhH6SolyMGuYGTopUL23SCRqxZeKcZoN8kFO/aIW5Tptlfr7a3qptwCH46Ymdd9kKNmuae/2cqrxvpFA3q9xI1fqoLsvdApLC/fDpt+3ExFoWEwGWYCAuZz5axhwdA6CglS2kyQmlQCkHhgF6TgFoFppF3ivcsexpsXTTwdWXJIwDiXhiytmnDvKQBjyaz0gvgrD8db50qYO8Qki/4ulWiyY/afGUHFyMWSGLabPwBUs15ABCGWsLvwLvs8cmZ++mrOz2eUbSyXA4UK6sVuEGymSdZG1Mok5E4ZAQk6uUN2XFg1CBTz6d7XbX4fJ562kes3vu/owDBQKZXiFEANcvuPUcaQ9ClYCPKymwQKiPr0+BTx/q7/t7+vT3L3dd/1t9fA8W9Hv9teJ4YDP/un6C96bD9HxHR+dcWeoBvKTqAm1KR22gev79U1+3XBMuoFfSzkh6Y7NsPHAyIiAcRpqcxA70NCDaOR6ZSVlO7qNJI8GmpxCBVsGYivFuS3gJ1IIsV9mzSJvznIyEoEnE8aTXdrLLCjw33j5moTdIH4lqiIUvdJr0V6JMeAebvyTgyK2Ctf7q0J8ag+9uuGiF5bsfOgBHSdF1Tx4CZ5twmazxDVhN0Cdy4YIzNZbIJS2bFtUp+Nk9rzT4E3DWD1SbDy5c+vCRoWdc+IcR6/0nnY7bnD1BLfUz1I7KTMWKY7QHbZO/wOZsC/cTLPRtcOq3Z9ymZnTvhKX6pUhLWaaxMINdbVktyTIuXf4qS5Cjy9/fk9k6BZVLku04niErK4TKXfRgDNAeSpd/HC1G4yKg4PCsj+dSee8/YgmEzkasY7zb7r/nQdfH5E1QwY0vPtXvfF9zP1xH/2j8zR+D6seSUKs/eiXF5SzyDAqOu7//PVtz8LD1yLEK+S1XUEoTAMNvlQu2C2+EnwMkf6NYsMeLedvB5l9LxCY2NL+FEOJ/np22Fzl5eijOZvgSZVB63ysVrI8N4P3wqzX9CxzrdEMeBDvPDBmzgqV43p8aqS55fhebaDd53xGB3wyI1jCQhJwuY8lL5MdPTsrdh33sA0nmCDJsoz5BD9avVxjINwkidumQtxQvo/R33ZlOBa7Kx/jcQ1nfaG0jbsXeQJdhp6h0PHulQe03AmA/s6bfNm67y5rh/l+LPnWl5Vvu5z4C0cvdojdoevv27bM9r2B6bfY3WSGc2Ocqasowc6Id7YUvDlYB6LjzFgiNAilzGKlTYJIuaaUCXEKNTs6xZfItFJaKiKaoi8/z5SoDEwxn5WmO44tY5CiVmhyADxJdznx8MV2F+MJijkTRSSDZOIThqFaRCIbl7KUBfihApoQSZzo5ge3nQ9ZdPY5TmGYM8PVyvHiLjfM+ZrGDWsxhIzbPFClgwCToqCiauAEJhYJcaQftVXR8ceUtsI10dE6JU5IVSZyzlrH99sCda5yEShOgB8UquRbcxQYBTAHUejC72Gevh3j1da2/rgchquNLe1+2147ttfKnUYiTtg9NJDvEoWRgNaOKc5QcYFX/SYosqoZcaDvgBlAOqCuyBIC0FUCrV9iADediBg45pzCNY83W/fZK655caedWn+S0YcpCP45bKp6y6vqi5e6asqneMQdO9e7dWPENCFh8z5oIwJzrzf5VqmsQJKl2nvlIwJXTgXuSA4nEOL0IqB2SfsN7Bxo4sKo0pI1Ev8i+i73djZwWZYjLoh2G7yxJ9PhePFk2AmgmipY9mbPOT7Xa2LNhO/v/DFI2QAbHyNFEgzVshtLx1pSNvzBl5Wl47V0pa2xt5BQFznULANp7T6yV1xXaX/NZVzP3k+6EB1UWrqTo6ePqtIsiS1I9l4YkdKqLbulP05wuFE+fQmMC5xLgn0IK3XaTdXV0M7w0j0GSAqhpnHyY+rrK672IFgGI3nGNNgPq7/V93lXyCv7R+z195KCdf+ZZ+xJWMmKk+57+eAVp1j+i6WiUnc0wZd7ESV0nG5iN/L0OKJQr8Abe62riiOKRYMOZxcW2QLE/jKhPS4D5IFSy71dK1k7caQDxGH3kHG2zi/fLds4ex4JFlni3AT6/ADBX19hdyNteytBAGS6o7fitTN6PA9hfQnM3Q96fBJBvidA/6jOsu5b3wrfIaxQaRJusdJDusgUSS2NnW2VldrEplM4nO1rtyNrVZm8fshE2gQ1Q1FBDp13o7VeRN3tRO5TBHvuWrbZq3TrXv+rXj2Wr03WS0Ecg+jp5EddzMSRF+No/7LFT+TuR1GDp4mpGGFNItYzEo4QnN6SnARjWiBUPC/vFKML5laxSxIMXQFYDP7iHZ6nJly0/+oo19P0a9AZJxDUlKcJVjHqeVpBFEJnAK7NQOu9uoFrZmBaw1N+V5cGMskDZonGZqEM6gEfARFLeATHFVem2WCJvjanTlmXTkM/3wrVDMlnAw1bpBWvOvW1j5W4bSTwAeFmDhBdwClDL4hwmEz5LGhrOWqCUpwCyn641KfprfnJhfnsBNjg6V71DlQHb0DNlt9+y2VEbPH/ZP7mUTy3CWpDHxsbckd6NOJnK0cVzLzxpxfVI/rFB7LokUlwBLge+dA2AFgCUZFT3ZJ3CBeLkJFUljliL2QxpSGJMyLbD9eV9iBISh9IRhVsQp7+0nui0gSGstSBhjTaxWLPpMvJ1HGkk0x4dCLw4EFR3zyVc/4+6ioL/DL65f1UO322ksDfRNE7dkGbhiVBS9akWtPVIG7km5rWKtuJXO2zqUNYaVqSt8XfZ9Gb0fNVu/rM1NnmIPtwBL/4xbRgwI4aSXd8fdVnuMFQX+t2a34eb1KZNc9TW/POVNnUEM2OlqrVsZSPrnMBQP9yLLxgWKLuPJ+lh9BgUmA0oFKYUsdbv5w8HPeDv+U+fiP/U+wQwh0eitnJyte3aAh+2o8t6V6xgHuM0gL6+HKDTZ/fz+vRlbsUltoJOjqQjoE3BctA8tH488/QzdtthpNA0/1UtHws0it5oC+3fgvWXCyBjfedgw0mKEQm4rs2r4f7FjqIr/dV6A1dB0D5qNQB4HbutfkCnOND/gZufR3rfirDiHwHLkjK3MQ6+iqR7CzyicRL6CZLrz0PFGEby+9YsVom49zwA+vvwnH8zlbbTtOnf82wnJzD9pKN85ocmKCjNKHsPMI2vzS/OSsf8NC77nTzVDjHqEuVk+fCaPhu66Vb8BmQsfu6sfezoMduBgqNM9y1QvMsmXf+jzrH2rV5ld27d4uxCi8pxI4ePQPSN/HaXoW5a8Pbs2WMvviPnD5uCc62rTLc0tc+y575hTev+1JlmkwhWwDqa7MQ3CIpFxVF28lAQ8L4XisiqgpyOjBKNMhRHiIuDCBYzfVaLWthZxuMcsDnp9BUUjpklFhthAZ+1PNJcAUkBUZnvkr3p4iw+rsRFXdTMooU0AEiSaou7LGmXpMIywSeKStHRUWT2igULqkq5JBfjGcs0nbeZqW4br/QCS6aZzF610Og+a0CCUZhFkaX62xQIDrG2+qJrIKmOx2eQMidRYuqrVVyFXFRBf6ahHIDmQLIl+hbeCZsd11P84KuVrAnMSYHwasD4zxT2OrkhwLHv2D7bV9hv1R1Ij+hDbtnmcy7UX8/drF0oGq9zDvjW/S5HISJHlnknE63jNrVj0kYGL1jmDHa9p3loJ9ZNukcsJCVGgF9DXgqn2JaBxiOQq4RzyZyTLoZwGFQVCCU/lW9OAluX32UvndhOBUXCjkvwAps+ga84G7g4fPpyBvNhXXjR68q4zYKgjKxiCGLPduLMolN+4nieIkTfgD50BOrKZqRe9+jkg/KAKiIoB4urnUk3WmoHFBe8CGpzoQ3IlYYQNqgN+9C2lo0x9Rc/+kpDWMqd7CpiB1O2OrzGVvauBGRiD73Gpb/SdK+X5zyY1ngXeNanxq6s40hafSUbYK0fxwBnE88+bfdAE7gWQfOyQLRoHLuhdBxkvThJvp8D1Mo/kKTAAQN61l3noFlcLoimIT50K+81DrC9C47zVxqbnJLig0zaUlw8jdRZm94TnBqNkNcdSJgfQCqNc057KxdIwN9Goi2pu3zkyuxcnrSG+VvFerVQiDEG+qan7A0oFndQbraVi1xzFkpt4Xtqq1k2G4X2DOtK0pKcEFSQsn/m0GH7WK7gHNZc+WgjT8q9B5fs6Y0321o8FMpa0tWuHwvX5Pq5+xGIvn7exXVZEk2gP33hHZu02wB8nou8lKJKeqSFi9GlgLm2wtgrmB44iSc9vORNH4CukLdYaiWe+O6x6vTzlsM9a3EGzi+e+dLdn7b8yLP8PUcSLLaFQSi83VaeOWa5oZ+y+GrHXsQ19n1Iuh4FSM9XyajlK/RwiSAnLZVqEwAeW7WAUoViAUUhsHCuTjIePK50gjRDSBa9tDcSk01kJOdQLxLJEeqU5k+8zoKVAMoC/eUyIIcNg5NAV9qIi7JTnCNqnpF3tAr870R1P2a7TgCS4Z6G8KoYvhVgsQa5MlL39yzWbDxY1CtljhOrOZpG3skowlUG/HvZho5B23rrXU4p7/28Ey4mO0kXZaFAgHNOOrqYBz8EccYmxuyZN56yif5hm23QEfgSQZrj4QZH55erbhGrKVJyu9B3zsa6MR93K9QITjNCdHdn+YP+NYMClTzqSQJO73DDTsAonMX5SigBhQRnKCg3xlDQy2XUZ4C1bBY5syAuf77/uO6tL37s/GzJHPClw6lcZRT8FBJY1xBHW1xvBzgpSlXSd+WjtCQRP0KfBUCH769JySmmgrjjmWyjTcDDn2mAquJPUa4CQCvdWfbYUogsd0FVWOq7UQIKlFGbjjgS+DB2odPHW+2WR26Zs+ASRLpx/tX78joCGq+yXqNPjV+BYo1nxVlMkK7AOy/tsY7jJ61VFiJ8H1vMw0uIo270SUDzCihHp3lhD0IvugN+tFzG/wr3GygvU6z9KgIJFUES6vcriv89BegWUBqj7s+gvNgCCO6pAWHFqXVhVjn1cvo2YFh7P1ThLQslZII4FSou8NwK2Jfi3kJBt1eWKra3rcEuoFy4Dmn0coX6t6V82kfQd9n9FGsL21zeq35PAK71m679J5fuWp/+vq4vFS6wWXizb4XtununtaM7k0IKv9i+cqk0r/f7H4Ho6/0NfYDlkxmvt9562/YehWZhGylJ/VBcTMEwmTZ7FOEN0t3ZLh5gaAJyE227bAbHIPHGTTgGeQZQvMZSgGVJmUPhboAz9pFPf5Pj6lfgU27ElvHT2DbehRe/LZYf+KbN5k45AK3iNKz4ZVxgvw3IxjZo0xbSCqw9qHQhpi/xe0PhRmgToI2fAdhBLMWpVgRwJRULHIToF5l7k8UK2ZwWd1hB1ItSke+knk6Nwk0GfGPxIuwANfWDUlGpII2ruS2XmTy/cATOWrCUAVAvyzOgpt1ZWUEYRGsaaw+5CTA2dq/DK/CQdTuSsy6e1aaAYVrf9FrQZaFECpjc93zqudlOBb2SABBrDL9qd96ctL6+Pgeil1OKIBvPDQ1IQNAEvxGCAMXBowft4PDbVr4nWPAENpYUatSNi8/RswrwNk+iUIuzEpmOE7+4mMVk1RTLtXRA++E0XphxcWR7OX0zGyjRPtjEoZHkrHYUxtgQYvlCILkCHSKvkxv+i3KUKxmaQhSLH3E2cNlUoCyYmMGjJwqMkiJH1I/lNvx96iNnLQII6ogC1FUAvLqq0hbwrKQwtVgF8PNf6AKKVvvg92+GytQLLQKOcQIFy6L44aSTbZAxZwWgSD2oD24u+V8dCEXOAZpoE/aj1EVwp34gvX+SYSTP8WnaJYMFm3jRwsdjtqlztW1edZujJ0U42r+RgwCQNsCaB2QiUn9Sql0MMFLfOX3yhA08+ZTdNzTGScMSx8YSGlZdUHzlOwHO23iuTmxjKwGvPud+517TrUSXTV09ZYz1L1ANDKKO0n/O87c9ojnZbBzlxBkS7mJMPQVP+kUA9hjd6xAAfiftdgvS6Qvcx2YRz3F4xDPJ9+l+4lT3FHL2ckMCKx3LQ+mQD8STAOUhyr6CjeQq+myFDc0g1jiyNFwfm6Ii+b6DdF3Tyzraq52/c0iRGojfyt84z84QV+YBLyUmENf6tUzKWrELveG2rejzZK7o9EJt+2EKN/YM8GF6E9dhWcX1fGrvSTs9thZgt1TggwQsdMGaZl9Bir2L2glEE5hM5I3PBQanruNt92Duah3KczM2M3SSCfokDkOGoGi0IaHFtjETX7zpdgDyCovhJGQme9pCuSPwglsB2E8iMRYIYKJkoNeHSOWEdYae4jS4auO2BmcTOB2J3Mw6imhqLqC8lEL6lU86GoeU+FRIAWjZV06lMSuGqbACYLiCbVpdF6FPcBjt7EjLnbgky2UBazdTI/Hg2ocAUugbZVPdOVKOwbNGvIMJtIOWLJ3BPBKm6azdZsqbqRPAGamyE5/5ROZ/ko7sYutouVogf01rLu/5EZf2PRI6Zb2Jg7Zj++fd8W295Y2lpbRw7BTKLNH3OUpd+Mnr8+4UR6/PvfqMDfdcCOxCu2Je/Yu48MSIjT01yaYREAxfuPG2Bhv8+rilt8St+f6MVbNVHJIwPtIoheIpML0hiSMTwPF4xXr/oMPyh0s28sKYdX8BN+7YZhYgdZJpylcMF3W+zRjAkgCWQioxqFIA2DDUI/3nADQbxtRY2vJtWFbBqovM6onzfEkKiAMG5CFuNtdqgVKKfPSF/1MjacYzpuveAkqvpN9vZCxQJg3XCsrDDjDzvYR1nCBcfRu6dCTNHgH8deKpD+BTkebuogYKEkUAvjYIrj4ogjp61yDpIYl+6GMPO7rDh8n7mkzZSRlWYFjCEX3qT3xlSZYleZZdazmFkddFgWWBYJnqkwRaZvCkYKxrnU6q7ooj3rTuKy2tFzIpqXyUruLsfeppaz50yLrIU92Et+1ezeKNv7noS/pnPlmivjfVX18qUWH9baxNxyjzWuwnszo54Cgwvpm16CVoGs38/pD0A6iVLIAM0VY/gvOcIP5OeNKraIMe2mSYTv5D+Mdx4t4H6G7hucsFpbdhOm//0NNp48OTcK9FqbncE5f/Tfq+z3LC+gPKprbXO/jDdMZOUq5/T/22s8Y9BInjB5wYTOp3wP/N9IffwDzgN9kUtNMYv4Y0+cc8f46H/zRxcW2bn/N5FCKPreixux94lPHRZg1wodUvbvTwEYi+0d/wFdZPUrYDR8/Y8/tHrRi6g1Q0/JYSipbC210F+kY50o80eN5MAH/Zg2nnVKSCfc/qW9ayop1d704chWDQfvw1MuS4uTSBtBczW/xnuL0OV9nTsyDGmjYjoX7QynjjK+fPk169AoPMDa1FovYTi029am2Ro1ZNddvM3CTGAunqhAQsjzIj95PJ80jq+F5ocxLn7HSjzUx3Oel0FU6p4s9M1TYDfKsggfZBi+zlQqYJKxtwn/PT2KzNvcru/1kUUjZCbb2ZY8Y1JI1pufmjcV6TBemr3OQNjSORmgSwN9AUVz9RyXlNuvyCPXRfn61evdotjPUWKIK8r+7fRniFN1I4ceK4vT20zyoPAv6uknYQtAu2XE8XbfgHY9b/Oz2W3Bi3ke/ich4zcIUzJVv133RZw7aUzbyRs+atGWv55UbLvUD8Z0at9d5mO/fMuPWc7rDpYzPOVFxUFjIWCgBoBSn9BTJptniA5ZlMQGWqsLAWWziBgVsaKwCo4VpXWvDYhs3pppkmx7MOpNQuFZeW+6c2BNg+Oysfuheiv+e+TS7NLNBsCNIbcDs9Aj+7qWxTmSksmMgI9DUKaHyFphjX22RzIBg3i8kpwiaicaoZCwaTboMhbnYozxjDO+F97Y/Y6t41DlwKfP68ggCtU2oEyNXTKqRrIIAsICtQ671+qmwHDx60tWvXOiBz5MgR51hIoOb8+QHHVZW+g+ydS/FLYFjUC4EYKlkmAABAAElEQVQogWhROJSPQLRAdxbzd4qvOUG/6Rmlpd+0Vuh6Bs+MjY1s8qAojY8M2znA25Gnfmo7kaxWtHlGUW+wvcWZiWuemrGBNe2WOTdpTdyfxpW2emUjVinE+plsbLC2yWn31iqUKar61xp7oZlWVIqAjKBZOgg+fu3rkj4+i5WPPHoAMksnU3gyU9fI5+8AKHNc6742AhOAUdm8/meAzhlAslaJRrULcVSS38N+uGxOa4ZOscaojH4jsVCBVI9e2i2JMvlp7Cy3Quu4XPyF0vD3lNY4ef9NbsY+m2qwj/GOv5adcTzuLGVWu/4S9YzTYL1sBP6I8gtcfwdamJ7bTl/7TrVou+gHByj5vRivZy9Qq5vPJfjU6HonzSZ/1922aXPgvVN96hch/PxmgV+E1ryB6jiNJGH302/YmfGbWBBlMWNpIWIDTCYnbDj8KYZy/WDSbheJF6C5NHUIiRQHSDWFwLFJjnkxLRTLDAOg38BO7ggWOLBf2bDKZs78vwDmByw/9BMUEFGiS66y0swRJHAnrEg6DpC/xwEMC2gkzXHaDluVOskU0ITwbQKQDHcVb4ty0hKFxxzDpF4h1+qkzqF4DAsZSJlRlspOM0UyY8RiM0ie68H5YtuB43UcX8hTxCyS8kp23KLFY9YVGkTxq8dORX6XBYhjUew6SzFysUGeFKOoT+fhjzob2QCdn0Xfi03Nx0OuHjpqa5tP2333fckpAEoKvZgjW5/CYj8loaqgXKPF9lqkv9hyXG082U3//vPftwsrzmORY/EA7f3yLWJXWU5HGu6g/QGdHb8GmNuDxYsdmLNboxMQqDxtUDAO5W3gP8G9H0C6y2FNpBVaR2/SBp8ecbaZm+9pwLZ0sJC/X54Xfw9gh5QjC/J0Qiix+Z2MI6NC4S/EyYccw8ymiAfps2kad9sNSCw5XRGHWebuUN+zlrEWfgYYNWF1ZpJEDrH4Yhmjeg+KwVBLSh0AP3nUzKELgOk/uR2/FqGK9ZIQNqVnmwHxDtRcPheZ7QvBGa/yzESGRiXITrdCaADOdqHR7nhwizulyWDCa6n9V0BYz+hT4FOAVN8FhAV69SdnLVLgkxRXFm3izEly5KJrgWg595E9Z8WTEyIBaH0XqNXzAr1e+idKltJSHvLSqd91vQJpoeIE11gW4Z7+ZAtenwreYZG+ay7olgUSrqUcrDx0rTIKaAuIazz34lTDp9uKffUn/vZr1nvgkG2aRNrNmBcY7BgRST0IbaeheHBfLRzHdjStTT9z/xI/gI4lOMVjK1tsxakxQC1OVNIpa8GBSIj2G2tptNaJafrlrI1nsFCEBFdgtcgzoo6E9c6d0IRPXS8hqBVEZVCPFoBW0L8CzjLyMgTIfB2J9Gu8k3Rbkz3A2NhYwEQc9VF8/4Sk2j4dD/JdYpf4R3EE0G+ByvFmQ9zW5xBG1fK+xCOXvE0yNqJ252IDbSIFy3/CJkCg73HZsmazvBa++BR10dnwN7l3nrchAC0+9wZoH1Ek0D/hr0zcW2l71WehcI5+ehaPmFt3optEn7vRLXLUt8FHILq+NT66nmuBffsP2HP7pznGvZ17S+wmALtE9V2bKPdbJbk2mH3mUoYqgWJgquMBWBXNHDd/nmPpVcx1aAp3PGiF0ZeQKp+1dM9n3KdFGi3R86sWGn/VSZsTXZ9BSo1HvUQnQLvHyigoRrlOQAnxkm1lJSsYCpXoJhu0T3LUjHZ1ZQTbn09jzB4u9uzNgGUtJPzJCgL/52ZkMs8H2XtlceOvKJdqbnr2v83/ZGYRmNVOnbQigGcpDSbsXSQomJ4rD7E4dDO5dttQ6G7ABpsS8a8Xj53JULMXtBGUO+XIQ9N5sShwf/VSaKz74hL8TXvs3o3OPbYWSS241yJo8RWlQ58f1iAQtO8gFjkmXrfqnbLIAVjjv6sPOHPADJw47sVjnLSswkviS1B9ziKNgg5hCUAYfXZ0z7gVTqLg9EiTlfqwDvAspzOA6OTquE2+PmOxlpSl16SWp0yiXcydIqEo1Yy0Wt+RNhagX4DFnOQxmcMyQargzEM2D3RYZqzZBtaettHzuECnaSJtPAZftSD+dZyjfZ6PlRJ4HBRtCm40NKoCFCqX9tU3pHgDFh5njLVRfjYFi3k7EUwJRjktysnZTX33R00iejRp29ruspt7N9QAaz0l7GKB1TcU1L8FMCW19XbSRZfwIFfAU5JdgVxtLAVUNeY87ULp6LcwG2ylJUlzkHbgkVMgV/cFVvSna0n+6qV/9UCm/r7S9aF+nNefPHkgrnj11/quvPynfvMSat1TXVTfkydP2qHvfss+NwoNyQHloF00W+lpfZPlC2Zfpl42htRX5ggluNC+RZ72FE9xek6NOqAdhcfbgnRa7qn1fEq2lCmLQPRskhfGAaUU5XLaeKCgF2YOngZ4q4xp7JDnuR8hjTggscQGRkFg/VJhPujVrHsBMPky4Pkt/rJ83y5zd3SXY01JO5OoWA/LwMYsJ0V16c5P51L51d/fNF2wY1jQuICEfg2S6SsJNEvgcZE2HWDN2MCNvVKM1JrHb066z+dLCK6ehLv9lSQKjZT7CWdFGwIm7dZFn3yBjdrd9Jlm2nahusjr4TE2Uakd260PL7DNUDnq+9iVlP3D9Ez9VPFhKvdHZb2GLSApxxM/fcbOTa5jkmL1c1PW4jMMh8aRBJy1XAQVD0kCNJrrQghgnO7+THCnJj0OcVTc0oEXt8xnAaBIp7k/y1FSSL+TRhQ+tCgH9dY3Up2PcU9xyMOlUwHAsvOGuxyBwxmOZKE7wDW2+7kvE0Ms8sUD8LSfARgjCYemUsg1s4gzqbBTb0gOWNZ9l3oFx26kk6uikeSCptCFlmImcewqJ5HkFkKbwABj1lg9jKLgiGVRMMyV8GwXXc+0tBKJvqS7fsi9t01qmVzyIxrTosJRp7ObPYsUaNg5XJlFaevqAhLz6mm7pXfCtm19xC3ykjb5hfJK09aCrzT06Y979d1r/euejo8FHrR461oLuiZff0StckjiKzAiQOCtBAgQ6PkCi4t41goCH7o/Pz/FU5gPBNzNK/xHkr/vvPBtG0ydt1DXcgFo9TjexQqsP2xK2ZmvDVhiJa67h0ooF8bNUTMEaFnGwg2A7MmS5U4XsLOMJ89p+hKC48xtaRv6ybil1jVgbm5JO7TFt4QH1HzKc6ILyh4A7SxxQC1Kj2WsYxi30lBBEoW0Ddw1YLnbGadrWIJTwfsQMJeFEK3mci2enIBC0CpQVCtKjXJS+7akD/WzapbN+hCSxJt4P5dpCmeDG4XKPN4/S5iMrDQsIBUfDlvTaIvdvuu2mmIsFCr6tf7UryRVVv8VQFbfnZ6csPbOLu5DkZlBp4J+rXjqi3pG/V2g2N8XIPb905uWU4XrQfClQMnVjtMlNewCkVVuP6Y1BtUWCs/95AnrPX7cVjB258909d89KBOAVnBeafn03cDdrP0jybLuK6Y+G3Kc8tV+ax4OlFLVvmnmBQFthSTvQH1N3wT29JyAdhZwGuF9yDJFgU19hXlH6al3SvotibKCT3+S9J4CgEr6rBlXtqK3Y+mjh3c5Cx1lfHya08WQHWppthOYqNvEHLEBKXK6Vg6X2CL/UWm7yL+TdE/HI9bPJk6bj6UGpSNO9QMoOP4DUuY3eD8D1PfXoZ4kANY1OROOtdjwkfhB6id71qi3Y4lEJ6lSjoyyaSi6z4U8PGoTNEpap/t7bOOOu6y1nQ10bVO31PJ+WOP7Ff3DWv6Pyr3MLaBJaP/+/fb4axUA5M0sQKJi+KlkMZnhYjd0xKrRVo6R+pzy0ILPz61sQdriFGdzkrYwRfGbTMZVnO/i2rSp3bPAsiuL7vGnI2YmSLkGr5QbAMoz1pwZsdHxNQAvLAJA2ZCTEayDYk9a+WTwNHUPdmwz1lh5nSPlaTSOdxEHIMaEmsV+8yymwOrLG+bYueIsc2glnt8OgMTKNCqBP7QVeBYcLp3EfNhpGy6uQwKyDclzH7M4C66UAHn2/2fvPcDkOK5z0TM5bc6L3QUWmciBJDIJZooUKVmyJCrLV/deSb6WLd/P1vNnWzc4Z99nfVawJVn3WbayKFEiaSYRjABBEgRA5ExkYHexeXLY9//VUzO9g5ndmcVidwB0ATvdXV3h1Onuqr9OnToHfbcp5JZlupXnNElvcSoAIFAKGKvEFeNKK8coI/tLK6YVtv1y8+JGaW5uUsu4ZulUNuXlZxwwCQwIXgkYqJPJZW6C3osXL6pd/RxYe7ERqaEJbp+hc3fm1Ek1UFbB7iwdOrS1wbQhwIfZGUsMy4cRDGgE0ZRsEUizYw4Fh9UgXYeOmoC6q+sCrIh0KAB9GHZOl69Yrs4v9XTDvJLhppx1cNmZoMVcB8EOwYwGJ3zviwUke47ukb0ndou8C9IuGKJl3skIHOJpsq7t040S2o0BPQoJ3X3YVNuEdznGCSK+Dax01N1Thf0AOIcErOJeLPZCidRVh4kmJ4+w1lFzG1ZOXKNetskgr3AZqErZoEaKyh44R4HJu9Ozj8hgYx9WgGBVBAAb4kiAmZwi8O0yUJI/VAeVEbTNBdfmXmzcVaog6fs5uca95POww8IJn2eihpPswlnoNTLhgV0B0gbgrkFdJkcMuq/73LKkeZnMqG2DChg2FwMUcyLFd7MBZrziAB+D/X0KTCqpM95t1k1VDNqRNgNklst7fOd10O8gr3Vafe9aOrIdlErv2LFDzu7YLg+CqRPtocxfVDHnmk981E6TzoET/RP7doZAWqLLNAHYROaRf1QpGUnb9h+G5aAonltjH9T80J4hAMTXh4blJeh1DwBcvwfAmVLZBqwQGMDfAPZ16P+qMX+YCyskxyD93lMLPlRi015fUDrRV3HD4GXvFurOF9JfhcwORhUoD+JYmW5DvvSF4lgO2/d+6LgvgT1rAuj7Yct6Dt5fqpysQn9Cfeh1OPI5Ua1jCc7vxJhSD/DNEY+mARdgM+VctDf388Vt1abDkELbly6XWXPmKlWnYscP5r8egh6Zr4e2WG2YBA4MQQr9w6d2yqUINtQpj4ClFWobga3a+DFsRlwKtQVoWvErLioQHFL7C4MqJM5VgXMyONwGcKwzo0ugdAodswOuiOkaOx6HNAc7510YtKPoAJKJSgBogkuWwYpNutjqmt2KA44iVqATaZJO//PwBPii9MbWoNuAXnTaLB3zMzjhbtnvvgQ6sOkvT7CNDEOq/RPYHdkqI0PQc4Q5uou2T0FTo8VIzV5H9d+sd+KBdqwNb4T4XLEBTG3cMm1qnHjJ4EaqSxa0XJLVyzcp0ErgymCW4BIca2lwfz8GF4DcpqYmtYmJIJlAgpZMBiGB80NvjkGDAQLsWpjEcqJzJnig3iTBN8+p38kjA/U7daisqhb+MbBsHWqwTKgDgXFn52x1yU57ydIlqiwO5A2QAjKOZROsaMl1CBYGvHBvy3u0JMC2Mv3AQL+aBJCevr5+1RbWyzYTkDE9j/wjeHri6cclehM277XxPbuyZ6vbYz66Ak6p3oCJH/4RWNuxqZU2qNMvE1ZlnFJzewXeWaNuWt6In0rK2W+fk4pZfqmYCb1Yc4FTeD5Y1y/9gT6lcuSEFG0E+vvYFgBrOvi+YYbPhs1adlgSST/2DGWGq3FoYWBJPAQHR7QEYodqBc32xZQN9kzScU+o7uToxSQDk027l5NoA0TpjHwvbIN28WFlKBjAngcPARXeQ7ITB9qsptpMCpZLnJdc0jbQKQtuXgCzkpwsGh0S3yMHQBXfc9rCbeuYqYtHvPENMMKsIqHf9UzC6/CEE4u3X9smM/bslVroQjNQ8sugdJTV2fT8GFQYdWtJNa/o5tqldLKhC46VgxGQjWmf7IEXwifgh2AQpuCWQwCwtrpKFmCjHyXVXXAo0tBHexYckvC+oAyWSbC7IgqHKgDTO70ueaq5UdoxwVoJ1ZNWODXBW1l0aEF5O7GGeQnfUUWEfcHEAoHwavS/GCwzBXAzJHWkGXi+Ee+2DmiN0l+nyb6fh0OwPuKGK/XLl3OYDpr6sq+tCbrQtyrvhP70+KHLuhGOFoi+EZ5ykW0kaHj9rT2yA657o/a7jY+2FIyAb9KROCw+bDQK2TuNWovMbwcQdjmHJRYHeMIA1tcPKS4GUHr/o+c/mpZzQD0jGtHACwMjwHYCUqtEFF4NkbqUToa2mE8M3iXV8iI6k+exCQuWMhIzAcRRPzovhkTMI4MxAGjUrwIrQJ36PFABD4ThRumLr0UnCicytk4kZX4jyWT82iAJ9/v7IKWvg0Sb+n1RAMEQrIbUor0ltFjRDopUljS30M4a915ZvbAWUuhmBTq1DidtOhN8UrJE4ECwTMBIE1gEBgQElA4zjudMy41MOphBca7UjcBVA9TJAhYEugwsj+XrQAm0Du2wOqIDN1FpoO/B5hoXJmMMBm2GdJmWDthu2sWl5Jo6rQeO7ZcT0WNiX0DlGqhWUITJCdoEpaaannxHQDQVraW85ufNc33NI12KB1b4pGIJVl9quYTOIa6E9yMfASXGJUIwf/bzAQkdhuoRlra9HR5pfLBGTn4LVm+onoUNk4xv+kSt+Fq54nN5SOJ91zMAB747exg8gFEX8pmThqx+9uV5dQzTxrFB09aAjZABTjr52uMXoNpBcAwLPA4/rIZgtYOWOBKo0xPGpilIE+MVsK8NaTgXyqKIdxyG5M43T5bMXCYzZ3ZgpcaY3HFSyD8rZDnAifcxWAHpe/VV2XyxT3xcqcL3GPS6xQXeegFUJ7FrzFY8CWd8R0gbLWkcgeTmRahtXIBg4CY843th1q0TfUoUetYOSKbpLMUNVQumj0MVZCiAla4Q3iW+P+iH3Gh3HcbSO2CKckn0ouxF+1+urpQWqPzcBCDdAEBN1QhdZyHyqUveGEvJWYDYdmw0vBzGFsp5ZfHsPdg2bnC8A8KKWyCJhmaHijOXTA7sqPKLZ8lSmbdgcUmrmOZyrvVzC0Rf609wEukncNryyg7pCc3HIGLo/V325YxVH7zs1di2wd7kRkiisOktDUbHymK+RwDk9fTDw58PANYLaTPckHq4nF8DKTE7HVgngJQpTpfGXPfml24i0Pj0zSUWOMcSrtsTkXi0CSaK7hNX8pA0Jt8AWOzFZpFVBu3Iys2JSp2DJuRQF62KRPvfUHW6a1YrYCu2O2GqjjdZF9NxYFWEMeLKAwb+UKgWANroclNQcYnZDQBSihTUAccZSSz7K5AJT3eJODYtSY8saTwpy5dsUkCRgyABM/WU9cYlNkBvaiLozAXEE2kgAXRfX6+S4GnJ90TKuZI8Zgkh26sD1VEYyCdzu5meUujtB7fLwMxeSCXpgAigDNJSF97HqB/OfQGk6QI7BhWGyTF5Z1BlDLfGuf7lu854fXS3Ywm63dgYyzclXx6d92odh/eEpfuZXpn5hWbBIo30/nJQgvsiEjyAjVa3QnJ3D8zw/fuADGzFRrpfpWsM9dGMIsccl8BGQyw24XPCJC3khYfGhMSwOsRgTqciTD80R+ft8UhiMYA0kIdD2XKnZBv7HoIBeG4Mw6lMFLZ78R1RzYvaXNxvgUvyM457KXzTjrMucZ3zyk23Lk7bhc6qYJiqs07THOCK1YFtW6Vx3z6pxTeuAsYAL6S3nA5ymhqCvrAvrUphJJj+X043hzCu7MGE+U1ssjuHfpC2ku+B9HkBJLAEkwkAWvbsbBXWV6SCEmueI75yCJ5A0U5awYi6sXYCEE658WB9QJouBWUjNkmeBT+OYv/Gyz631OOdmxcJyQwAY4LpQqMFN/61QJXtOEB4lCseoGsqwwLoQy9EhcbIM7pmxnVhArEHkvZNt92uVgy5Osh+80YLFoi+0Z54gfYSPO3ce1TeOAKgCFfT1CUu+HXnloHvhh+PM74Lgw82CMk8NfDlJit0bYOKAkMkEgCAC0LSiU0+I7Dtit3yNC9HKxopXGdVO5C4UM+jSir8o75xBaJRByTYKVutRB2r5SLM3FXYtosfkl4FpKUOetlx8bn7obZgSGmTkCoMn/muuBweOD9shPoGNrf1bgN2xgaq6pUwzTcffJusTiQlPnhwo7fEJIAa5yOKT+hM49HscnHBloIMB1RekmoCYJfKwEUZCjaBp1SHgbUH6Ni6Uztl1U2N0tnZqaTKBMi6E9SbhVg+43R8wfpKuEEwXlFhbKwqIduUJDW30wy0Kem+2H1BDnTtkdgmbFil3WP8o0OOONQBqH5A74CeYayMwKQanXV4Br0SqjU2POFFM0YjTrgmIWgQqY9aaq1B9SRUUVIRVD0JvwOnEtDVrlpRCdvWsIwAUB05D1UJSO9q1lSJbyEsUNTA5vswtUMN/o1VSUbqDJbFMOmlKI7qrlXhCoAVbBJ2GqoVLIPl6TDSDwCMOm0BxOF99/f7oZeNPR5e0JPA/gma5MO/pJdgx6AjDk+NDIxPoX/gZkf7DpfMrJopC+cuzGwE1HVYx8s5cOHcOTn56suyASs4VJFgT8inQjDIEMVEVK1cqavp/yF9DG9BbeEFqG6cBkhdCuD4aajntGP/DcEzg36z8kFYqnHo9vEYgESaaiuUwHuhy8yO24VzKEdKA6x20PrF23Pb5ZdDUAHCSsiyAZgqBBDPFzjxaMS9fQDz3faIzEIyTUu+9JMdp/mTr06O2DuwSllN74SLlyvhinkFcLJpKefyLBBdzk9nCmmjRY6Xtx+Sd3rnABhwG4SxpF0sCSPJIZnheEXO2d8H0FuExIagQ8kmMHOHrdjqirNwBV4n4RAk2ARtAFqUviYSk7uIhT4NPZFTgoNQj0gDXh+sBDhgg2ug7z6pGdkCTepfYnfy3VATqZfhWNa5CmmyQd8xgaXpRPisxM5/Dxso64ChId0aeFOk8/Mwv9dZLMvGSYelaHSghj60kdTrh3knqL0MD2T1hM2F2CFtdkCfNAHTYWyjxwf9ZXhiTCb8yqEMVifVhCQSrhGH7R1ZHNgqixd/REnZKI3V6g3mMq/GOYEq69N611ejjskuMwI98O1Ht8v5urMSr4Jpt/QIo3R5Ta/oYB32tuPdttNcmhOTP/xzYcNfYAA2lSvhPAI2iGmLmJvotJrGZNNqBpSTXfZY5dn9htUQDvV2gJBEOCmeVq4aAf9CN9kWxRc/CBfaMGvHQN4UFZA/lVa3oWm8cAKSYgBhtRsqXY4LVmq8A36J70Cp79ik2l8tw9hkHIYKGHWcMddRtqtTFUad5FEKz6BQcJxxStW5OrnjobulrhrqJzeolK0Qf3Lj+S2/BoscjdhU2AarFAyauxqEuQEgPfgjAAtCKkuwGYDpuakOWir+Dmj5MXR+d2LStAJCo896/TIfk2Xe1zSXSpvW+6Zk2htGP8ECVDvhsAeFcmGl5cQ5OY0lksOVfnlu/hxZfPa8LIHpPh/6xdzADYtVYOQpvH9z4aAGSnW5Sab8mlRexErcmaY62fTgr6gJJgUwUzV+THmDx6nQAtHjMOhGuE3pwP4DR2THgUHoB64E0CpFJYELV5Bq2o9Kb3IWVkdnEwPnDdTvVeoR8LbnwkDqcVPXF1Y8sMyagm6iArW0wAF6SlFVyFtZgUinm3ZpMYAq995Golg0ALrQ6duroJrxIKxC78Du5F/AZet7EF8FHThjY5nd1QQw0Ib2AgzEugCgm6R63hdBb0wGTnwFzmP2isvfAdpNqKoAHWNGK2nliMTgatwQX/KQgsUKqhqwE8UEBNdK7xVSfI8XdoOh8kJ9bSelzwDRtOARhnc5RQsmC7EIgHU60NFNYGS7rNu4WHkxYwdolrrqdFf7ePbsWWXB41qQYBw6fkheOfuCpNZgYMyy8jIWadfYdCDSW9mHQRQTQZwPVQ8p4Md3xz8Il9o1MO8GNOGFOccI3MBT+pnR+1XP/7Kiyz6i+mZs7IUKR/eP+tREeCSIjVYLAtLt61WaTpxAOBvhGhlL+hMJlLYrc2UV0Nokv8IOqRtqkKGqAam4UCP+MEz8dV2S+C64qYZ6ja0CKiP3hWWofgiAm/2Uof4yXt02OJKR/Q5YG5gpyzuXqQ2oWud+vLw36n1+ywd/+Uu5C/q+Y4EKBQExQLigOuFKS2CT3KBJgcEUMI9WKc4A8L8Kk2+vY2mzBbX+ESwodULvlwZtCPwnA6bqMvREQn/SbCO9Mi4GHF4Aqx2HAOJ3VdXIXr9T5mDFdSkk2dVQ/0CHDOsgdjkxu0UCfSE5i/6cCiSat1PBq0KPg1OkgwG4MF+/Rm2o5d4Ys0pcoXzXa7x+Jtdr+6x2FcGBEJaZnn0FG6Z6YQ3Dnt2INX5WLJvKWUgXzonX/g5cWN8EcEcAbg7cjBbChkHOVBPihrpGJOiAmoILUuYGSE6pqyuwljADgI9dg/4zlzF553ZsVLRhE9YINzqlwS7VJWCgSFWSGqmSoeQaSK3gnMWDpWAAgMFBLY0GbIUkOkUPhLFLFK/BgQSusdPEDksmI7BDTZ1tte48YZLRUSqb0JCcYbLBzYTs1h2QvNlBNyXzdOjiBnA2VF3Q+UMXNwbRKCcG4RCsYKhhAL/Mq2Y07NJ1twu9XfspmVt9QTZueK9ahjOrcUyY7AlkZOd7LUgvaGLvydefkMGKfknW4f0psq0E0AwE1sm06gEloMN1AHXpUdYOqTR37VBy64e+bpS6+m7oSsbdsFwHudOkuBMvkuArTOaa4ZC2TzXK8EGoXsA8X92DsH88D04bHoHzhWZsRsW/6pVwMV3rUmCFMcVIzakm44xhMyp5iMmuNwiVMajQJD0pCcI9siPklMbuFqnur5PQCONDkpqLyc5SbAyEuTFOYkoJNkiha4cb5N4N7xIfrHAEYPbMrOZTSlk3QlrayH7sxz+Sdngn7ExLocdqN6W1HkhYGdhbDsDFdyU8D1IF5GqFKMqmS+s9AK57sSRXhX7xw3B5vQIbBmm9gkED3qtFQ265tFO9GF4WF4S7ZD8mlu9gE/Sr8AbaDIlONSxyNMED4un5CyWM6+6jJ+UtmE+ljnQzN2mmac4tcyque/BNnccm7cU3r1N7Z8ybt6ei/nKrwwLR5fZEpoGe/fv3y5adQzDrsxS1Y/k1PfgXQ4rPflxaUo8DhMKmb2oGfJ6gc6Q0GaZ5CIqx9QqSUuj2QuKWgoQ7Cn1GA7yy47LD7TaWuGHazgUzVnEMlLlm5oqhofg0AJvYsKgCdb4ZINHyewclmqhQusdEN3YXdC7lVjQBXqnCOV0rOmPaq6bHxHjwODzJXQR4HYRN34tih060GuVVwRP/GeFGKHSSBMEOAAeqYTghrfR7h2AhohHxVHOhDWxK77E7fLgxXRkGIbQrOxShjdkLlcZuh13o1F7ZvGYeTME1TquUrQb2dCfbSsfEuV445463dsj241sldSc2qmX3IBbOMM4dSlH1JzYMCy8MBIoRWKChjjW/GnsEak7wUJjEw/cAUEeoE1zmgXQHVsFb4nJ861ilp+TY2Q1zfJtwB+8z/1VvhLpWOhBAM64QkPZHILGHLignGbSBzTl2wh4zeIHJBVViInD40nK+TWovNog3FZDGQLMMzj8qqfuweXYmJiFwRV5KsMG+tP2kUxbXLZXW5lahPXMH1NuskJ8DXDE8AoscJ194QR6B2UhO+YsJBmw1UtJmM/MlIQgYoZOPYgooIg3rIFSn2sZr6Mv34Y+6yQ/C2gXVNqqpnldEOVcria6bEvnlw2HphBT6DDYm7sfKYAgWg2Y3VcpAfbPEoGaSxIb1X4DalXD//q4zF64WSeOWy0Wa49h87V6xQto7Z9+wFjnMjJqs99VcpnV+DXGAdj2///g2uTgECxjKHTUHHUNKMH4zOOBjIIR6gIOqBHBxHcGg78KyrQeAL4JBkBYhhodpXcMYzIwuMn2OQzSETT8YHUcwuzUk0cXWPT515hR0yuKECgk3KdIyhWojJITUOaZ9Z4M+1o3BOW2sn3OBJPQps/yg3dkWifZth5vxNcqL4sCxfwDdKehCd2BT1fJ0lRNrA2kEIkcZ8KCF3orm/aoqLwAk12AzIRxQQGJO74qoENZLtMS/lLowpUmelgWtfbJi2WYFoKfLOgYZxc2sdA/c2dmpbDGnmVdWB9qTfv7FZyXaDuOxLcZ7ezUIpLQ64cWSTDrQegRBIu0Vu4fhHhurEJTE2mP4TgC06aCkHIOCyjBjZw9hgvyGF4vWcDTRBE+SmFznA8uj4jA5pMR5BP1HAu++B2pJCS9cZ2OzbwTqGWpGiEGcVjp0sIM/vXWXJLhpB27DigdcfXuXwl36LCw683sqMcDhKEB5h6xef7PUVENFxH/l3jtLJOGaSk6LNdu2PC/LDx+RBoBBcrxUrrvgBIV5QtCTppk4J8zAXcnbTXDKXvscwPNLAM5vQ3WjCoD5ATgaWQLwXINzhonQqjJehR9SVIlxZwlM57XFBuH1MC7vtNbBoVS39IDHw+BtCGZEsR4pVIaaLtoHMSgentUhy1euUEIYribe6Ks0Foi+Ch/EtVTka69tlxd2DsJr8F0AxIWlQoXaRGu5NnRM3baN4q1bLlFgjQSkOQnae1YB+sdwFpENRhdLu9BUrUjQxTeiYmENCo372fSTcwbciY8dnfyIAVJtdgzWAKwE7jHYhTWCrts4utyD4veEpX8AtqIRRmB431d/h3gqF0NaXS3uymWQRMP1M0Cv3QOVD6XKMtHun7aX41JZ26/4Mjxcp0z56brJo3jGwYqmU1GlaCvmR5VvPyxrljbLjNZW5V1qOnShNa2su70dXuDw/pRjoJRt7/F9smsQ3i3X06019HDxtKci6E2HI1DjGawfUFVyU50b5vRGACyj+OcYxDvsx/dFNYdyCXg1bUegYvSmT0Yq8b3diW8coJ9S6XyBjmQqYJUnRL1wAG0vgHMUalE22He+hI2BCpSzX6L0Pk9IwoIOnf/0HIZ79Plwjz6blnxQH2fApQZU4T7sk9b6Vmmf0Q5nQLXTslegVLKnKz03Ex4/dlx6n39WVvf2s4OdMCnMScsWDHzSfKMnOiL0gS666H4M7qoJ7H8FHvtugfSZahss19x74rIsAttMHlCAA7Poshwm9ObvPCg/aeyRva0tmBXgS0B/5A0PYVM4x+mpD/yiDmIzpGvRYpkNixz0IVCuffdUcqc8R6+p5MANXFdXV5c8/tIhuPvsgNUJqgeU1glScppyNctF+8ekP7ZYnEOYKUPyPH6A8xS46KYFCSNgo4kTy69w1a1M641fQOkp0OvEaBpOqXFAKqYkvuiblK4x7CMr6fToYuNwrT2U48WQbtAdvllICPuglZckEoWUOMYJA7u1/AP96FJNV5SEIx/bXFNzDiboGmEhhNY+OPEw+Mhn4vXBwgAk/WG4Rb+S4Eydk5vaemT54nXKpB0tDkxnoD40HZ0QrJajNONS7yV59o2npK+9W1ItlAEV825fPY5yU12kMqQqIPj0R/3wuAcTepTgwhoITbdRej0tATSMDEFXfzskt72YRC+BCbqFsA+MOTLk0ookqqzojZf+UAATd0xM/JxI0+ci+5KUDFbCgZH6R9wwPhDmuxM6FpHuH/dL0wdrxb8YGzUvAoR3QRWqHv1KBya4sAxSVOi3Se2JRrn59lukqa5J2TEvKt8Nmoh2ofdse1Uaz5yTJqpiTBKyi8H+cBRSaRv26tAOsw4svtAXyFQEz7uxWfBNSJ7xKOVhSJ7v88NhFEAn75fRVFM3adQxl30cHQKgvBN60HE6aPHArTocvujANjEP3+5CfNFpJ+PYCz6+PQPfx/p1ytvsdI8fk9GmyShDo5jJKMsq4xrigLIL/fYh2XkYJtGcd2BTXLGfIT9ZfLoY4LiHLpyci86THr4wiMd1N8CjPjcxhVVA3cMOfcYYpE/ZAKDoh6ezEHRkTVYzsvev8Az1Ouh9DBuMYnFD8q1L5GY9B5xj5APRbAL1ky8PRkcWhBMU5coYeppOuAhOKHvOZqn75TnNvZ0TeuB2AGmC+3gSkju4l6XnB+pAZwJoiMKyBsH2FQWMcDWeA7J4dqVysU0pQjls6qNXQAIh0lNOgbra+07sk2NDR8R269RJoIvlASXVaoMiJlw2TFzdMGUYwWSLb4kb70vcgyVy3OM/vcJkPprr0WkmFIdnRz1iOQXQegBqUdgYldoYlmQ7VqjUy270K5Si0xNgCmoocapVwQW4IC1DqDqoQDQnKXqiko8mpr0sHsVHTsFbaDdk8z1QHtmSkP6XhsQ9wynxQXiOuwu2bNejr8FnadDDUoygy+KRwfNihcypnyuLO5Yos13lOLEzKJ/+X36z7xw/LhdfeFE2dsH6isHCSSHMjUmVHQCakte4Gxul8S0GMd444S7eP4Q+E7XQsyBlPlWI70KHuR2qYfuwQ51rNmshdV4HT4MtmKTz7TN3p5NC4BQV4kUb7z3fLXeAv27wIoaVO3qBpMSf7WK7d8PKCV12V6RVVK4Gaawrhvp3VvvFu+pWeCdchO+jQnl3vRr1XWtl5kMI11obLHonwIHe3l554fVj0h1uBXDFIFNgudRc9EgyIrHBt2H/9QyAcJV4GzYAOGPAHj4EMAnLBZGLKMclvobNUPHgBqKcnhWXDgBHjw/6XUPZDUaU4AaDdQCPV/F1BFhFb2xujjoneFb6xewpcoIDkjEvnK0MD9fn3DEulbQYHRplHHZI0m0KCI8Nor0ebKTEQmWMrsqpnw1wwZCA7nU+KTxpoOm6K51cOOwXpc1/TG5Z/YDyTlguJonoLpwDcrkFuvje+tYr0l13QZL1hhRagy0FRkEzQVZJcXwFmSedl23W54oHeBXGK1vziemp6qHSQ10iFMBkBO84XWV74K4+jokhVSi8gz4J1gyNolWXoerP/UbTNKlR2pRQ02eKUrTbh7AJdjcIv4j3dx7e0/nQ5fZDl5vfBdrrgzm/KL75ES9AD1eu8I/3wlWGRJ38Yxv4ebJOfa3r0fzhdSEaahZXyfCOsLiqnNLzZJ8CzoG1Xul/fkiGXgtJBTY7OgKEXll+qwvTj+O4Sxw9Lllz39qMlE21wZTGOs1yIAYrF7vh3rv24CGphd7xZH/BzrQEOuSBig7qOjOvDSo+VTLrzb2QTiflX2Eajibp5kJ48wakz5Q8r8H5aoDnDji/0r3wZNOV5cDEzkCmCgSldnwHmk5GMo7SZW15g2+sF+DYDTBNz4YVaDc3nKtRDGlPY7LxPFSZVqHNXKPkjooI4iuQRodkukw6fGHsRPnRDbvQh1qaZe2m26Wuvt7aK6AZjONVRC2mWqzTsuKAkrIdPilvHoCd5uRmDF78dMcLMEsHsBw891NYdoOO8PDbANCXxN/8ILyS/RSWKk6Ip3Ez3GK/rQB1RdsHUK7WNc6WnUpBYgZNDnNQaiEJDK4YZEtVKTGXU/AcPUcSu/uTBOmmXoT12eG9j1Yw8gF4evcLwezYeGEEaikxqFqQdqc7JFWBfuntm5HJ5oQzGcAGqH0EoLLCutCdKZqy/KFkPl/bqfZCayBXBKJH4uJPbZX1Sxtlbmeb2lA4nbrQGcbgpFzAvJkmgrVjZ4/JzoEdEr8VkyNYh8gEvj/q8RngLxOPkwwATKfhvbHizACRaRUgRt0Z8IZyeG5Op4Ak06YHSnUPS+k6P2CsDEElgm6rOUi7If0NMS0ma06sqiTsGGoxOqty0s1ivdQj1mXyqK/z1cf2E6BH34EO/yuwRe7F4L8WpuXaaT4SE+VhvNcuxHmSMNOHONgBTmCIT8HaCDkyqr40r8ztVG1K00CVDvJQtS8dx/pVMKIl6UvAPjtM2fVgNWgoKTVLqyRViw3OrS4JH8TqDuehZr4is9abVvFDoO9USjY1bZAFMxdOq8WadMvK/nACUujTW56X22Atwp1+DleDaM9wSI7NaZTdazdL03C/zDh6VLZe6Jd/hToedaY38Q97KtY44U4b3wHNJpZroDrJd0JweQ+J8tvwkNgMuh9xeaWV15iI/HsEKzhIsxaTgV+F18Sd1OuGagqB8b2QNt8L1bezkD7/FOodFzFxoDFTBo7eB5H/F4g/ge9vDiI+jPycZPwbJhsncJyNsWk2zPndCcCtN1aqzEX8kO4Dyi70WlmwcKFSBaTwwwoGBzjZscINxgEuob/yKryv9XXgA6wtqvUjsFkV6n5eXJXzpXruF8TT9imJdL8A6fN5qAU4xFu/XgIdnxRf0z0yMvgWNhdiic/UodEKht2GAQ0drrIwYa4VcXV1PZDmmiMn75x6z25IgHO7V27i8ACkUs0jXyDYTam90Pnujo4zpMiQEsR90jfQCkBCgA5JIY42Wxj1Q4oAoJLA/VQq2wG5YO/WF+AiZP6JTCQIM1/BiTmnMCjEMqjjvLR7DsqmjethkqgSup7QNySwKoPAzUlcFaEt5nIJ0WhUnn3pGemvvSQj9ZCg4rmpgPdUg72Mvi7j8I9gbBTgQ1wGqPGlB7s1eMykSz+CUYA1TxzrZBodNA3qGulZN/8YFOCEeMtOHVX8623pUfHuKJZ8eyrh1IIIGmoT3BuQpl3TyWv1h4OikWWSHjNNuHAMQ/r8Cly3v1grkVnDkngIdplnQC0KE1WW5UDZXkyWCdwTlXAxD7vXil/4FnRZ6pqXaJum3XxOojM0kC6EDJ28SMepcmD5Jz4MG/QNLrH7YJnjCNRDIpB5D0INpxK844ZQgnG0R9eh8rEcBGevSyrO1MiqW1ZBragKINqyC21wJv8vpdA7tm6VwP4DUg/LGunXI3/iK4yNBnxytnWuVMA2/6DbLy9W1Mo/4x2j4ht77Wa853cCQNO2cjkDaLKBtqr/A8D5LUiP3+/x0ZS6vAIVlDDiCXZXAJjeAxffz2Pl8TBA8Y9hf7sT7+0axL8OtY1u9JU/R94hfEcbkO48vvM+eEVl/pcBquuhS/7fYPv6FCTWW9CHfRcAvBdj3IedcBsOiznPAZSHkLbU0AWVmjNtbbJ84x1S6fdZqk45DLxKsCWnFuuyrDiwZ/9R2bLHIcMjsziKFUfbSEQBZjdtIUPCbHfVqXypxDBMb9WIy9uOgS070GdGy3TpBKou2LqNwute7ndMD4J9/a1G9iLJKY5oI5XDERUXlrdjij7zAho6oAicpKD+3JGAwMkOSbXXR1N9kDIrpyfj18q2EMA4HBEJVAwp835xeESMh4PQyhiAVBMLb3D0okMSzlNGYAP0MgIQ44QFE3oeTNEpTOl9n6rCJkEMQDvkgbuXSXNzs9osVU52bzWwKQf9bDKM9Ow5tEf2BHdJbA7MqkGHl4BLAzgF+PCOKrDKZ8JzvtB54hRg44MzpRszTj0xo7xMOtKEf+PRYFSTBYmqKNCkAX7UF4HONCYqoNUFFSxPEBLqGqhU0FEQAEimfaq2LM3UZaaZvRT3DnAlpwtl7nWJcxAgfA0mp3OxCgP9a28o7cYdr3IcwDmK/kIDVh5Jn/rGWDTBdPo6w7s0D1WadJt1GnVE3CgeMBLFkm4bnCI5vVgpG0hK7aYq6XsZ+yuOwrb2+ZjU3lEJe9v4xtLpL6uPXqcPO2Rt4yZZ1HETAHQFvjt+j1bIxwHy79ixY3LgFz+TB/oHxFPs+JGvsCLifLDYsfmVbRLeHZCw1y2n8dq9F/1rENJaPH6Zj750uqxVFEF+JglpZejAvpf7IFFeCcnyXnx3pwF+eW8zQDE/i2FImqkLfhHqLAG0sxvXdZiU3gm1Fo6uFwCQ74W1kdvxjrqjNnk0EYUZddiPhgSqB2lPA2hTAn0YkvoIJsu/Bon0IgB3D0ymPpUqXVBBOwGHof9cectqmdnZKRUw+1guq5jkZzmE7GheDtRYNFx1DgRhOufZLVvlbH8bBrPiN3PZ7D548GuSBCTPKahxJMInsUzrRVwDwCmlEdhIBLChAzsGBkpiiV3paS8Rh2oEOo5RAR2GDZ0F1SpgXdoYXEcluMILlE/pbzzmzwziukRKiul+PA4dUvQ9owLbokzgATwbMr1RtwteqHzoDFMjHmyUBACG+gY3UoZ7DmKj017xtTwkDrehY+1wQpUEADpB2i4LWH6HeT3ai05FoD+uGXpZurEiYBt75IzMh5mk1aseUMvUtAutQM1Y2abwHjtkOl0pl0C7t49v/4V0ec+LpDVyCBw0GFV04vkSlDGO2GyicbpclqHLKxTHOsw0ZNLxRi4NGrSmy9XgU5eRxIQ2FKB5R6zEBL2SxKbYlJfvIt4XAGVuAAwHsEkR1yNQNnWdckm8EYN9D9RDjvqgIw7ljNthOaEG1lWwShJ3AzQDoJvbwLrMdJmvM7Sb6FbJ03w2smYnDuZ2m89ZDoOzyiG174Z3xArQMwsAvx2gOQTd0HU+8c7lpmeQki5b0QhwwcA4x3nok/bXyLINSzPfh7pp/eTlAKXQLz33rLQcOSQNcciCJxFE86noV0JXTq9+DJVDQanCHwyJwlwdxgn8MW2+PEx/BmDzIgaeFQCbBDmF0jHtVATSqtvWkB4DfQDQQdDZjz0Nr+F8IfcwgFAIjTFhFLkbwJpS5WPgwW4c6/Eisx0UA+mjA+/wENq5E6DZBgFOJwAzy+eOA460/GNada4JwHWxoRuqWBc6WmXRmg1SBQBt2YW+nHMWiL6cJ9dtDAeNXbt2yQu7IJVKtWMPIG0lF9lcfMD+lgcleP4xGTz+j7CP3CPexrvF7m6AVLrekLCyKErtnLh2UAXBGFbdcLziwJJqOAQLmOkBLFMrv3B0ABVVffDG14D8eCUn8LFnyss9gV3oKpTd39+AziQL4EewZGaDrrANljUM+87Ze5kiwJyhHmyWBLznpkoHHK04MJFIxfuVt0KgW3EF5kEw34iyoaqBCUYychZNqBF3xTw0i3rkByQAyyOVrpNyERsyfWirwDVxbPiEVPtPy1CkQ5yBuagDzyIJz47wgkh71E4PnLqMADw7uOmTTCo92GwRLPHtl42r2qQFm0LonrXc7HrynaRDExfd704zwCcte47ulbeOvSGpu7FZCjq8dryvGhxe9gT4WNLvqkqD58QyFLhOJ85IYxGry8nEmdLnjdN5TOny0cA6GTL1mmhiPBRSsvd4DamyjSM10qXgOtuwfw0t5xAmNH31UtVXK6dmH4OjE2yYPQkViS0e6NRjojkfwHsh1CbqMCHGQhSdv4TSTlR03fy81dtKGkz84bniDd/lnHuad4znOYPmh7rQP+byTGnsHpv4V7C/QT4QULUyOylV3Q2KZHksWoFwnKjrCFQAjrllVfPNMq9ltlLlKLfvQzWqjH727dsnJ59/Xt43ECpKCk31gRMAiFRl6IT0mO62qfd7AcDwPIBhK0DaDKgDMvSiv2U6AuAZmFwTMtJhShvOCQx7kIf6wTzeBLBYibK4kKA303HzHMukzu92qpzATnSTv0JakJ/l6PraUF8Q5fCvH2XNQ1mkgBLtqQxh1Ev6B0HHWbSd+sp4JcEbm5wAID4PVY+lUOVYiPf2Z5A4Y5oLvW+HvAFVDy/yPAOpdgRom+1n+1ahvFqk7ce1D212ozlPQP0Dtq/kOUipe8D/Yod78gFFyQk4U3Eup3fCTvV9sJ+2wmgOWCB6ND+u6ytK2X7w5OtyIQhA6aL7aAxZ6ESKDc7AfKnq/C8AkYMAzn78QS5AcD2DmwgJIOAsAZY5vHUb0yCa0dBXjPthwg315O2k8KXDosfQMGUM6EH45U5SYN1AjbDlDP3MnGBPXYKFre0SDi5Bx0IVk9GWO2zoiFPRs+Lr+hPpjs2RZOwSgG2zVM35jITP/BBWSnZjMKBuMzq2pX8lsdAZGT7zPZjuCokz/o7EWz+O5kIi0PWsDBCsI53d2wF+h5DuWYn0bsOSJAAKmu+b+TlsjGqXwWP/KCPBvbD32yj2RJf4Oj6tJioj6AAnEty289JUH5Qly24raykbO+ZyUOfg9/HzrT+VweY+rLtCTQCDEV9H7oinsSyqDuBlZUxGtYDPRQM0DRLNRxagAaE+muO0lJjgTwE81JmJUzEGMDfHsU4GlqfUGRRN6WvG4490k2qlloQzWsVABtzIls/rmNtY4mX9Hph/rOqqlfbTs8UFHeojC/eJvAVrH11+8dV55fS8I+Je5MBgDpr4bTFA5Um1C6e6PlU3V3LAL9KNKahyHqjbr9ui8jMf6MhMBEgjgvl6FD/T6Y1EqJ6TdtRD+vMFkqlp4DfIuphWlRmEffaL9bJww0KprW1QFgfylWHFGRzg9/Hmyy/JMngnrIG94qx/zfwcIih9GnsdXoRu7hAmba3g+29DXWY3dHN/iI11Dow/QcR/GpvrlgFAfhnvaBTpYwCEQXSMDXhl+zEkRFDOR6HX+10ASR/GqyiuU9Az+CO4w6baw6sAy5/AObeAfwMb9+7xeGQf3rrXoE+9CbrEdPf9FMAkn3k/dIg/6/LJHtS7DUC7DdL036moVIA8hftXMxB+roWTrxq8swwz0Ra6IW/DWLMa6hhPRsOYPDhlCeiIYtyaj7inYYub/cIm6CXTEokDyPinSPd/oYveCLvRG1FWB+KXgmcvgHdYZ5RWWNLg0uoq6Io/FY/I10LD+AYwuYTONGtOoPzxWkoVkR6kOwIp9NJb10lDU7NlkUM9tct/LBB9OU+uyxhu4Nrx1i55bX8Itp03QX0CAxU6sdICoASkzk5Inxmo7uBz7RVb5ASHJ/yjzItwAx8p1BDssPoBU7WwSIG0NgBZe0Xej1enM0NFUpYFA8ivaiwtTmViRuAEf3qM1eU6HWFpH3lOQvZDmLkvlEHZjMF4tCUO8mcApuga5n8IetEuCR3+EsDzIRjibZRA529AVSMk0WN/IbGhQzIC9Ra4CBA/QHYyckHioXckAYslFTPej0nFehk69W1xRveL39eD5fO4eGZ9EKB6tgyf/oEkwycgtR6QkeGdEljwp2qgDwx8AxtIqCIzfoeXZs2oA+1fVzqPyu3La2RmS52yw1wOQHUUkbggqNGux3k+XYHfx5tvvSnHLx4V+z2wLKFfPtKIwYRvNoOONgA1I7IAkPc1+NPHMeOQV5djfsoTjVPAkDSwUgRdpgKZpBw3eE+XD2JVOv3jhI326lA9rF2MSENvq8R3x+Vs9JxEO4MShS3nwCB0+7G6ocvV+XRbdTwnHegc1G2jbqNeVTlidf0aPOv8zGA+N1+b4wudM32+oGngvUxebBr2vhmQhY2LoAtNu9AVZTGRy0d/OcSRb0cPH5ZLr26VZX39Sg9XgU48a34TPCdo1kCU56cB7F4jwMUK0wyAve9g89w7kEpvxbhxB9QxHoa6wncA8n4JkN0OySknW5sQdz8A9f8MDskSgMS7AQT/DOacjlJAgzoecfuUFPrvAAxfg83kmaiH7gn4JhP4XQI4rgUo3Yh9O4lgRG4BaP8y8m+ADvJt0EX+TiyCTXcRtSLXijyfw32mJ926/xnVFpSZr30EpTQfx6P6itLnOo7PjDwzp+P39iE6l8I9AlluiCSojeP816G7PIh71DGnVJybBemq/H6vV92nHWiWR/3mOY4KJX3mfabluPkw8tJ6B2n3oQxuvPTjuArtJk3HwffnsdlQj7HklXpWOOZrH2k8VFMlTngnnDN3rho/rFUaMCVPsEB0HqZcj1GXLl2Sp1/cKf3R2VDBqOP3PLGAjHogIsBzwf11ItaMDxW6ZzCflYIZLTvsMSdh9s3lCmM3bwrWKrCbn5ppGFcBqy+r1+MOit8dleEQbQazQ+QgjOU1SLmSQDPc4DeCI0nWcfrIwvS5PrJTUObrAEI9WK6OhNBJolNlCSlIQ5jOkYqJBzswkiPDkG5cgkQEdnZTNFNnDP6qMpRDk3wxrF073GgX1DdGkM8GyXmkbzsmCrDVx80a3NxSuVTsNAF4+rtwvBIAQJ6F3KjH24bJgx8qGwsgEb8EG75Q9fBXiyP+tvSdg7wE4FsCs8HDASytzxGnfzayxaTrQiv2tPXDfBT5BoMJlAAAQABJREFUlaYJZ8UEG2ZIzpGTMrfunKxYAl22mlpsKJxe74Rj0U3LHHT+U1FBfW1DSjNW+qtxj9/H63tfk6GFfZJqomQzW4sGe2bArKTTTKPSpQdSXHBI0mDSnI8vdvaeMXDpvATsBOrZ+8TmKIcfA0I2Pp1PV1tsfaayjNJINspGPOkyQC/09r3DcnTZXvW6pTDc+gYqJT4Xli7gZlxiNul7A2pJfViBqjWcWCji0j8GjSydxI2mO8Mr3uI/DtysV6fL0JdtH4sZmy+sKVuWUb9RL/MalIymQ6dRQuszIrV9jbLq5lsgha7NTOSMvNZvLgdo0Wnf1lek4+BBqYdwgSBQfak4snfSYNF4Kgb3z2EFzQmg14JvuglHbnIbQPpBgOu5AMtU7ViHlcx/Qz9N5ylVkBjPob4zQg1A9Qy8TXQzVcVVTHSDDYibDxDZiLJaIZk9Dol2B8rRQYHC9IV+EwZQbh+kzfBEL4MA6ylIdFyQctO19mz0k3TIotoCWnR+tmWs9rEKDZaZR73ziGMe80SC37A5jvd4zfSKTziHcp8RcE71FAbSToDMOtg6H85Zj5YiU22FdqN5n2n5R1BMzwusk/FUaOL3RVfn/M7rsTlxDnhHgD1e+/g8B1DnjvYZctu6tdLU1KRMkbJsK1zOAQtEX86T6y6GAGXH7kOy40gcS2HLAQR1FzPRpgISQ5qaiLtlKNyOjxT61eiYaHKfupb4dhEHAIx/QWzwSVHPWX9/uMdPn+k1HUkA1yGY80mNmNQumF6VYzqS3BLi7KAo6YzC2xVNutGlODKrPgXDaapLziTC2A09D3pl86CPzG4nC1Y1mEZfIi4YQk3QwxpCInRcksMHxdP0MNoAVZH+F0ET8gFcO6pWArQ3wXva0xLvfkZGILVPQQ1EoM6RjJwDCA9JLNgNqwHbpGHuJqny18vAyW5Vrt0Js1rxC0h/QdzYhe4coYlAqsuo26X9QA+80rFbbllUKx0dHdAJx6YrNqSMA5+NejwTae8Vtovfx4ETB2TP8C6J3Ay73KRFDRgGMerJ49q4wnuLk0waEq0C43Ejcz3qVKUwQCHimQwxLIMDnDrimt+FUa9xn/cYjBqYbnQavhxGOSQI99J0G7kACtSJUT6pN8pXRWICiCxYEh/B3Eq1Bd9jtCIKKzKYJEJPNeWCvWk4aVH1o+LE8ZT0vzIsnlkerKwY1i7ssNAxUgkZPeg06FC/6TyKIJwb1PCObok6y7QbdCKCqTRfeB/z3Ewwt0N9oSovbqfLyNaPUlgtb6n8qlRVLiM1/3nPvs8j7YEOmTt7jtorQDOdVsjPAb5XZ0+flguvbZNV2L+g3/Fsb2mASuZWvMeRYLEe4NkGEEvgXIm/pyEBngspM70MDgAYR/GQD6HvrMR4RHBHSbQ58IrvrA70x9mLP25D7sM32wL1BAYYqVDhYlrtLZvDeK+qAb4JmJej7teRkkp4XE9h4C+zawDNOIJQhkLtUzfxo9OZ69NxTKPGm3Q6XYeuj0d9zrQM+cphnC4z3UxVrpk25iX95vy6bJ23Ee2/021XoFrHmcvQcSyLwP7N2mqpXTRP5i9bpSaYli40OZM/WCA6P1+uq9g+GMR/6Y2jcnZ4Jj607Mx9Io00ZqMpqYBt4/5+6FWnRz71AeOHl+xkCbKVneVUvo0IGHRVBqNbUCbc1Eg5uQNZCtLxEKwPAO2O7mBYt6NBeu0PwOsb3W2PATABLmyYwaciQ9iA5YV5H9p5hvvw/jdUZ2ZPDEl8aA9c0s6UWNcTkgwshDfCXmw4nA8PbT4ZPveoRC69qlQ1xDcf0m+4WbcPy8D5/ZCyo/MLn4Id3WrxtrxHIhefkeCxvxEnXGC7Ywcl5l0IXpq7uuKemNNxUeZVHpWbV75PSdnK0aGJuSWkj3/TJekIwvzgG4dfh3fCi3BbTVAIqY96P81UZs8NgIbr9GBr3MHE0JSHwE6DY51OX+ujypcuQ6cfdS9b5aizvGlQty5DJyY9574CXf5GOkbByku7W+reWy2pCynpebofk7mY+OZ6pPmRWmyOhcnL7WHp24L9Dhhs6++uFtdCpww8NSzDh+AdrgKboPq4DQqDbBc8xD2L+AMh8bahzHdhZaUawOiFYRncDaBd7xY3HJ1UbYTDhxlYARrFJwJcE6PwZZLOXNqZIl/8qLx58vFD12Ajc5auT+d1HvFI7fFmueU9a6S5oUmt0kzXu6cYWuY/dM6166UXpWrnLmmMwVQp3m2C5EKBd/jXAfDaDH3df4cOL0E0N79thsrBcqxWPo/Vp33QSd6DD+29UDkIoI/O7en4HPlcdE1dAOQ/hEOSCpR1ErEfg5408wxBeeH/g6qIAq2mrvw8zk+iTnr02wWpdRfOD6C+D2HTO3pd5Jy6oNvAGs3t1PHmuEJU6TQ6T25ZufnM6TgK87mNF5iiD1L+U031sun+h5TlJK5ilrsQZrx2Xc37Foi+mtwtg7Kp63nw0BHZtf+sBGP3gqLxP6QxyYZuGjfdDQwYdqIzPZz6YlE2jnZIo70e6FFG/dzfYIT0F22nlIvo0fSFu6DOUQVQfqmnCdGTAKRBBrCvOOCKOwE9T3NdJIY0jCThnrwCHS8kGkFaDcnDFzuAsa/zD+DpsAYguVoqFv89zNX5xVO1XFnRcFUskCS8NNoArt2VC3APHgnD5yRQuxZpFgP/JqFDvQvS5X4AmA8hnQfqGgG4cm2GHvUJ8cC2dnX7A7DWBJNhtg6pXvD/SHRgp4RgkSOCjt49AV5QnuOPvya3LJsps2bNwmYQf8auJwcZDogMNC2XCxz4rtCEFTtMSh5y7zMfy9ASFl7rwDxqZQF81/l0On2t0+YeWW8cg5wbS7PT0VkfOn5IXj65RcJroJ6TtsihacwFd4zXcfqYmzZfPNMQxOl7PObG8VrfVzdzfnLv5V5rkKizUTZ1/nvd0vRAHVxfB+TSS/3ia/PKEJyRUHxXt7laup/qlapFFdgwCGD9s36pugXv8CDMg/2oV6o3VECFY1Dqb6+R4V1YKUqvxgy8OSShMxFp+UC9dP+8Ty58t0f8HZgw7g1J40P10ov7A09GxDfPANOkx0yrPjeO6m4OsM6mN7fJnI+5eK/QfSN+NL8Zx27HftAlLXOaZfXc1cpuOnU99XvN919vdNXvrX6PFaWsE89O3+O7a75mGgZdnnFl/Oo8vGfOU6gMc97pPO/p6ZEDW56XTaGw0kvOqCCMQxTx7Edh03gv1DRoBeNXsfmvFf1EA4A01TsIim9DP7QUIJdfw+eg7xxAPEeAz8EZCfWDCf5+r6JK9qCMsyo9Vv/Avw8hD0E6Nzd+EhsTCZbb0K/PBGhnvg6kSUDnuAlxt2IzX3u6vvvwrOchzTDuW2E0B6gSQmsqe33Y/LjuVumcO1+NHx5s1OQ7SidUPNfvrn7HdZ+tr833WUPmvecKuGl80LXrfPpa52G+3G9Dp9V1mvNM17kFoqeL81NU7xB2VD+39YgcuQQrFDYuhLHzYJelOxF9ro8kTJ/zyGDkscNMnRO6y/EoujZ0TDZsVjBAr7kspAZIHh6mDerR+VmSAtA8ydQP6x1hjwyk4PRkAqBRFZX7Q3LsCUjDYZMAtCQN7b1MqhRcjJO24CAcn/BMqZao0/SP0V6mcVdU4xfmhWDhw+6Gu3MEZ8Ui/C02ztUvf6AfXrVa/alz2J/2+OMScq8DDcbEwI5dlinoprkqlorDtxjl0tQYTOMhN12MO33Qg/bBOHFqAKbxjqANnABo3mYqGuMENNhPyyz/Sdm44YPKpqfWhT5x4oQ88eQTsn/ffkh9PbJmzVp56KGHVBqqM+zdt1eeefoZOXTwALxH1sttt98umzdvVhtKzBXu2LFDnnziSbxL0G5PL4E3Y+f2ww8/LI8++qhUYqf7g+9+EGXUyTPPPCPnz5+T97znvVJfb9jGNpelz6kTTZ3LhgaYS8RgN5WBoOmF3VtkuGZQbI2oWS2lpA9gvQJeEIkqiw7p1zkL3LLPhtky8Xhm6k46nwZvjDOn0e1U9w2xa+Z5a8DINPo8k9cUZ9Rr0KuLYB6e27ocEljkldo7K8W/1ivDu+FC+ERMalZVSRzSZOUUCM8wfCwCEI1NtXDVnQynxNsJ74bLfNK7dVACS31S/W5M/Do8MvwPAN8I/jk+OC9ySXIIADIANS6UFXonLLV3VYl/E6Z+c6vgghtqSj6qlFCqD+akeUIW6nboY7YNRjp8GCqNVr9Qlabj1LnpmyBv1DeSvs9VBMUHlTBbjj1dv/OIW7zDfvnAfY+IF+bDOMmMw4LDa6+9Js89/0u5cO68NDc1yl133S0bNm7AID4iP/rRj6Sutk6ampvkqaf+Q1auWCnveuABGRwclO9///vQGW2UD33okXSN+HwBOL7/ve/JoSOH1YSd1kEY1q+DV1dssnvxxRfldnxf69evl/PnzsljP/+5rFy5UtauXTvl73+G6AIn/D4e/QHauP+gtIWMlYgCSfNGU++Zm/oYqBNMtQFerUGclq+om/ipM337zKcDdYWpI1yHfpr5Kkz3CLJp7o5/owLS0M6yDrekadDXWv9YX1tHY4NjL/b+9ED4snzNRjU20L33K6+8Ir987jk5fea0zJjRJnfccYd6d7fA1OGBAwfkU7/2a6rvPnLkiDz22GNy//33q7zPPP20bNiwQZYuWyaciP3kJz+RxdiouOm2TRnBTk93tzzx+BNy4tQ7SvDF/TweTLLuufseWbZsqXzlK19R38yDDz4IM60t8jzqpJnFj370o0pXuxyeW86bVw4kWTRMJgcOHjws23adB1Cbj2LTljM4SpkCF8xMcAB3tAalTqSGf3XBtNxQmIKnM6bDCJZOZFzbsKnQA1fWMeXARAMinYZJdd2M433WjYEYJrWyZek0iJpQQJnYfR8OcjPdGGXxFjrbsTQmuM/ZaDOW+QGAjWC0NX1hOqR5wDZhhEjGIJ1FHgWWwTOPj2DcAwcq7PrZWuxITwNsXnnh4CIexiZF2L31NdwG2uBQYCziTDXzlO7FK0Z2y13rF0gzOhwCBErZzp8/L3/8x38sb731FgDACrmA62eeeQ4gYEj+03/6NTl06JD86Z/8iZw+fUZuxv3jx47Ky6+8LFQD+vjHP57p8FjH66+/Ln//f/5e1gEAzJ83j1EAVA5V1te+9jW4PY9JZVUFQPV7ADiekr1796Aj3TgmiCad07VkuHPXTtl64iVJbIAVVi/fRDwJ0+tqADy8AeoGbqZfJ3XNtPjLjWMUA4G3AoK8SJdJUMmvS4dsVYhL12HE4R3KJOM5Y3UEzvFfA9Rsukw1Kn3KxUkuJn11kLTChEESOvwELr1b+qGihHdsLiwFcBs/Etl9sMV7T60Ej4al99VBFWmHoyHXXGOIcMCRCcMIfBWHT0clehgrBy3Q3Xc5JAJzZbA+lgnEODaYEhsVdNvSTSBd6pQnCKp9mUijHYpPqt2mNJoHSJvhyaiy+ax0BHmUYSusCEHKecoli5vhvbMRdtOhNsXvg4PyH/3RHynwu2rVStn51g7Z+uor8g9f/keZ0dYm3/nOv8r8+fNlEQDA3/3d38mSJUtVPB1PfOtb/4LvYM5lIPq7BNEH9ss6vPvcuKgs/QwOyGFMUv/6L/9Ctm9/Tb7xjW/KOXyL3/rWt+STn/yk3HLLLWUFoin1Y99wYssWeS8schhQ2HgWE/nVerd8zOnHXnQxMwGuboNk2auebdHZrIQlcCAB3h6D23vPmlulbeZMtZfmzJkz8rd/89fo1+OycPFi2blzp2zDt/G///hP5PEnnpD/ePwX8m4IYygAIYj+6le/grGnWVpbWuXr//RP8NpbIYuXLFEg+pvf/Ka8//3vl/Ub1mfGlG6A6+9+/3ty4cIF2bR+nTiwsdQD1b4QTPtx1fTrX/8aNuSjc8F3/OFHPizPwtHP47/4hdx9990WiC7h2VpJJ8iBYDAoP3vmTTkzOFOSSsym4GC6NA40Rkjvs05fGfG5cZRAJ2Nw8QtvZtl7TKvL4ZAHyRT+DNxn7iZzBlRVk46DBBa2an0e2E8eqkHZurw0OSUeCFgJjL0+fIQAq7GYabOiqSyCfaah1Y9IhKbtzPVmz2NRbdUiG2eAf1Nh6pT3ST2l9XF4QYSJpTCkcgAydP8dRjkJSPApcc4XmI8S/gTUTBLQI3cGbsqXbIw4uHsdOSsLWgbkltX3KACtTcdt27ZNnnzySfn8539D/ut//YwMwF0vgfDRo0eVNO05SBkOQeXnS1/6Q7nnnnvk1KlT8ud//ufyL//yLXnve987yqMgQQelE/ci3YPvepeip4pgBJIeG3baXwLw/t53vyfrIHUrNuilQpbL8qcqDAwMyNPP/YcM1vbJyAzCSzw/BXyNo34lCNb4ZNUbkAZv6pqveAbcqhujXqMMyNOfAtKy/EyedFmU1Gqwp+4pVJwuj1QhXzaNUZhRDAHj6HQkgF+5SpVW+1TLqWieLQLPhPCiObQ/KA0P1AIEY7MtJK3xYagTvZOQQcRXrQwoT4Q9/9EHc4t+CR4Ii3+eV4I7oRo1iG8/MiKxE3Fx1cPT31I/ADkAN7xzehvsEtyLtJB8D2zHBtouUAHgbkjwTfxL81g3UT/rfHwHBCaDdRLjyIZpnism5KRR97NxRlLUj3j7OagSBFtk4+pN2NNRoaRlBIpnARROnDiOCeMnFJg9e/asbMcmOjsmh3op2kzEOUiPKZ1+3/vep+47oFpgDsxjw0rdLGzq/cTHPiZtOHLVhpLsH/7wJ3jHPbLzzTfku9/9d1mzdp3KWo7YkOPHq5DO33TosNTTTuk0BkqOVzggYJhGGq73qvsg6T/f1iILsdJSV9+gNtzSOduJk2fkkQ99SD74wV9VjrFeevEFNb4ofuD7eeedd5TFj3P4brS6oPHdqF5IJcv3HfGG+lbwbBcuXCif+43PQyADPICxpKV1RgZoDw4MKmn1rbfcqsYYnU8VXAY/UzdilUFjbzQS3njjDXl9xwF4Zvp0uukc+gFy0xJpRiowkI4zrvhrSE8NsMwPwS7VVb0yOFSblhhzoOZeavqU4pEDHYduSl4hu4U5rGwZOo0BHo36dZyRLxV3SihBIMvBj3WTRp2mcL5sOqZnMOrliBmH5QEsICLmcjpVOkiIoxEs9ynpsm6PIalnSQZfqP+NM5juSyZobInxLDNbn3GezeeEFL6qsh/63a0sBnqkTgkO0zII9S7Bn8toMtrH+EQM6hhwn8yQoCQfUmqDfqYhRQQj5ji2JM0rGyTA9qOyfmWbNGOwrk5L2bgcSwlBGBtvHnroYbUk1tzcLH/1V38FegCIcP/t3bulsbEBS9h3KYlxVVUllus2yNf/8cuy++3dsuimRUpPlB4P2UkmMKB+/ev/JD/58Y9hucQFoP0r8olPfALgwI5l6VVy7Mgh+SlUO4oNXE7n0jgldlMFotn2vcf2yVu9b0rqQUihoWqjAR8BqwGAyXae463EC5YBrIwAOjPgKlupbqr7CiQzivcz5fDNMQLPFMQzXlgdjaNRhno3kTdDA8rIBzAJDklP3vrS9NlrYYN7tg+23VEGVCsCy50Au9DLxybA0NsRiZ6GCUhsAOQb5JyBZdQal/Q+A1AMYN1wd61U3hWQvkcHpfsHkFyjjNrb3eJqdYgv6ZHBLUEJH4fDjHpMWBuw3A7wPfhGUC7830soDW9pBUAXRhfSmGkLOIYIkwQ93WYcslJ1XCCQt6P4lG6rkuSzfSqR0f6MdJ9Z0+mM52c8R1U/2mQ/65SFvkXS0dKBiSE2QwIkM8yeMweD+E2QCH9TXn/jdVmwYIGsA7idCWkc300GPdjz/M4775Ttr2+X9vaODGig5IzOSKiOxMkrvY7uO3hIvvQ//gf2ZjjVRPT3f//3Uc6INEFSt3DBfExSv40JNvdjMGTfEeN6en85sT169Jj0PIcl+Ut9yoTadFJE7lgA+uo+gVNYQXQsW47vYZ56X/l9tLe3y5xZHfJtfBsvvrhFVmClcvWqVcrqkxMrA33otz/72c+ofps60+zHlXokvkWaK9Xgmf2tDvxOOO5w7wFVCRlehf3xz3zmM5hs2mUuVn1+7/d+T+bNnau+0ZsWL8QerEtQI3wC6Y3v0VyeLne6jhaIni7OX+V6aff2p8/tkVOJzaiJ0tQsWGPVhAA6EJgZgTDNCOY4xvT2UGGUeXLLMfIS7LmgruB2J2R4wBgYLi+L9Rrp9ZFlpwAwCS91+cXm02UQsJsDaUnGYXUj065svUyngfUIrHfooNOO5gtsXcMpi9cPU3jDBqhlenN92XxGSQmopVyKGgCacImbMB32QXFjjpCEAxq6Ao9GDOm4zqtpIP8cMG3n8vhlGCCaIZsm37PR9wGCRs7JohkDsnzxOjWIU0VC5UfnxQGRwWymiGBVg2hl65TSs7Q4jOa+PB63RKFP/pWvfA1LcV1yE4D0f//t31blECgsX75M5syZra5nzerEEfZH8bdsyWKxr7pVvvq1r0qnildJxvyhZQ7qu01l4PfxxLbHpL+jB3aQ00/dDNRIjAZrRRDGLyPz3prKyQJIcCgXQCIP7+cCSB2nvlCUxXIzcZomxGfiCtGH3r39D+kJ1Ah17ze+Sz8kxzVnKsXRMfq7qft4ldT0VIoNr44t7Z2o+fN1krwIz4M1eLrGKylVcwMSmO8TRxPym0aQwJ1eSRzBpLVmRLq/A+Cdfp9ygW+GbrTFPBEwpxsFvtnmPHzKx08dpycXiodovmPIKfUnm2XRbYuksQ7OkiCJ1mEOQPRf//VfywsvvCD79++Tl196WR772WNqoOdKDIN50L711lvFDfNqj//iZxjc+9X3xX0C3/72v4gfy9df/N3fBaiAdZKaGlmxcoUCJF5YOKjHXgPyxAFp24c/8hH58pe/LN8GkA6FDF1zTU85HMPhiOzCsn0DpO4d6edYDnRZNFwdDsBwoeya3Ym9MmukoRmqgJgIMnBz+p/82Z8pvWiqcjwNPWfufQli0hiJYLzHBtD//J8/A8FNo+yH6t4PIVhhh8VXhiDc/N1wMjk8NCz//I1/lmefeVZaZrTIex82vq8WTCw3bdqo6mxpbcXemuz3OXvWbKUS8vjjj2M1xxhbaeu6XIKpCywXkiw6rpQDyi70rr2y43AYahytaSCm5DqAOZQ7cfDUQ74h89FxfDV5riWgTthZJkBKQqJqADojHyGdkY7l8cqhJKcRzDJF0hv2ctLghkqZzWfE0MK0NxCW8LCWRo+miamY00x7Lp1GCoMmhxMSZNQdB2jNpjPoZDpVP0CIxz+kVD4S0FPO0mR8nLp9MbhCjg8YKiwafBt0GDVqmmjSzwZpcCJmqH8Y8fiFQC4Fc3rBficANR21sCXUVSVtnDoY9TE2HkZdcDEQjuAeHpHDEYOkizvXDSCVywNSwDjIraXOe0JWzfMpMEqJrt6gRxWJ2bNnw7SeS15++WVpa2+DZDwof/lXf6mAxO/+zu8ofc+db+2UN998U20YoX4aVzEosd6wfq3SlabUjXrL7BhZ9t133SXvg34bA+NoXYNYJ4CNhY888oi8sf1V2b5tq6xYvVqlGeuH0m1KJrjzW9M9Vvorvcf69r2zT070Hxfb7cb7zF9yUgM5Be7SAHYUMMuNSxMzKp+JQHO8jmZd5voYn4lLg0XWqWjAvdz6mV6DSgUW0zRpQKrzscy8AQ3NBdA6nR1S5dzgaB4NtnnfMePyOMY752NFpQ/7Iprgyh26/QzmtuTSxBRmuilJVrzJ5QNfLoRi+GmuT/Mp8EpAZjfNkcXtS5SuZwbgY4K5f/9+bJz6pdx5153y4Q9/GFKxV+VP//RPZffut5U6k6pYvR3GGfU/3//BD8qX/vAP5dKlHgWMGxrqIaVbDn1On1oGpxnMubM7sefg0+r7I5jw4Z6WvFHK/cUvflF+6zd/UwYH4Ga+jAJpPXrksHTDrN36C71lRJlFytXgABV19lcHpOKmBTJn3kIFYLWQhauYr77yKtTz1skHPvABOQhnO1/4whfU6mYUdr8rA358Mx9SqzcE2I9DbZCfCqXQXMUJAQ8MQTpNFakYfEFUY5WzA2MJN9Jys7lWOVy0aJH81m99ITO+cL+BBuA+CFkefvdDsocgHt9pa2uLsot9NXgxkTItED0RrpV5HkrZntt2TLqGsNxob8A7bUgi9dBNUJYNashCmmyckZ4gDxIoG5ZbgPwgZzaVY+TW5ap0TljBiEOyO1KXpyx+V7nl6zjG40+RSJ1qDs6MY/3ZPPnisnRm0zHOBisidCVuUya5jHaQ4mx5xoQiESXwN/Jm2zK6LLadoDwJFYYReA/MpmOJTGvQSd1qG3T2bKiXAzfv0PW2052ECgwBAOJSBOOIR3lOF5bTw5D6mZ6N25dAHCcwAKo2mBPyJyUMCwh0D2BAiGx9iFSBINxp75aOylOyYvntyiqG2S40wQKtANDSBpfkuGmwF5uEXn/9Dfn1X/91JSW76847IH17Rf7iL/5CSQPOnDkre/bskU996lNqqY6SaZbDjpUgIAbPXz/44Q/UkjaJqKysgs7cIwosJbHcNhPSi98EOKAOdjGBnS2tc7D8qQDRff198urOl6Wn8YIk67MGu8hdBoI6dVS/put0vLqXk+ayuHxpdR59TJc/Kq++p4+8qc/TR5UtXxxu5NKu0k7xj7PSIbXvqhJbWpiUS1Pm2tSeTFya1sx1nnYWupf3+SF/4gxAfU9A1tyxNu/3wWXonzz6E3nm2Wdk48aNcvLkKQCAhNx6i3kCCHBvWpKmfuY92NxEqzc0ZUlrNhuQF58JAr5qqI8cAuD427/9mzSoHsEy+GoFLFgMy+LmqPvvv09+AOsX5RSomrJn61Zpgi50LSacqmsuJwItWiaVA5ewqrIXkuR1GzZJQ2Oj+LCKyf6e7ygtJ/30p4/KU08+LmvWrRduBGRYMH+B9ELNJwEb4FzpZFqODTzSIhZVCtuwKffHj/5UzmA1YxdsjBMw34zvZvMdm6Ff/UFVx+HDh1UeWn36gz/4A/X9ODGO3nvffWoCyzLxKamNvB/9xCfl5a3bVP3GeKhOp/3H8b8Rpp0KiwD1AnID2AheyM133DFhjlDK9tqOffKTZ49Jd2gl+nOuwXJ4mcgfsC126GsTbYXLgG3iwJCSnlJiXThdLg26mXC9Cu+HHHyKz5tbVvaa9CaTen6Yjc+WbdQ7AqP/kKmNWSdN0DmddAnOZPnb5nDHlA3dlKrTaANhNMG3w4HlXtqqVpMDHFQbodeFzsaoP0uf09mtntdIirrl+OMRf0bIpsu2A3Ewr1Bl3yr33+yGCa01anavbXmmMyrJ2wroKrNzO4sOzYFOk1KFj3zkw2qDSFNjk8ybP0/ps52HFJqqIO//1ferndTV1TVKOkBps+5YKSVo72iXgN/YnNWIjpdWP+gZcfXNN8s8WO2YC322Wrgb585sWh3Q6iWaJvORwJkS80K2qc1pr/ScHf7bh3fLz97+sQwtx4bCKvLVeCq6Y6YkU/1DhD7nY1Pn+qgisveZPpMGJwRTOm9uWfmuR+XNKWvUvXS5+eJG0WBKd6U8Kzk/Xlmqg9ACCAP5kKE3TZeZ1sw9nJj5lok35WE+9c8Ul0mnTrJ856Ujio2wW/xyS+V6ufPWO9X3wRUVvsuKNhwpEZsxY4ayINAFk1v8ft7znoflYfx5IT1m17l06RJI2xZKdW2N3LX5DjVR5LIzV33WQkq3Apux+I3wj4H9cCNMP9ZDQk3VEe4nmDN7jizABqoZyLcWJiYp0e6ARJrfDy0WdHTMnJJJpCJwjJ+jADbb//07svDIUanBZMIK1y8H+HTfqvJL8u67ZOPd96t3kn01vw/+1UAliap2FMyd77qovgVaXnr3u9+N99ovnbPnysZNmxRAJoD2+X2yaeMmJZkmiObm7a6uLlXORz72USXMIZjW3wq/Qp7TtXgVLIPwW6lGndxoyHEkGo2p8WMJxhGu3vB7umnRTTDhapjgK4cnA1OdaLkVpp0DnPHRfFISM6//+b/+14Tp6Ydb1q9989/k0RfOymASNocz4K20Ih3YSVXjj8qlYUN/d7zcLnsYXqxokk2DvvFyjL4fAFANJgw1kNF3Sr/yO4exUTGrU5WvBEqMA0gXxSapeCqt7JkvIeMoDVNfiTHw5iZrrg7KxQFDhyz3npE3Xz4WmBsPpE49DlWXURLp9NgjElFuyS8rHV6ogjLDc1i+9N8/qdQyODCbdZ91Dn7mlPhS6sZOi0BBD/hMo+/zPaREOPe+LocglAAhN7As3mPHq8tlOpbLa8YXCsxHicNUgGhK2f7h2/+v/LL7KYnXQFWpMFmFyLXirzEOeE9XyGfv/7ysW7JWAdZ83wffQf195L7/fDf5/vKP7zTfZ078+G7zHs/1O69Zw37c7Eqa8UzHMliX/iZYBtPSEgjvl0N47J+/Kq9+81+kfmhQfNNslaMc+HG907Bv/kJ56HOfk5XYMEgVPgo0zIHvK9Xt+Mf3lyCb7yrjueLihFCG8fp70N8H73O84R+/Oa6Q5n4n6v1PjxPmOvU3pb89nY/fXwoSLUqrWWc5BC2uKwdaLBomgQOUsmxYuxy60G4JRq50Ia6I1wOAL4nlTLstAPyXfqnz4cNx2tZRVyune03ocZz0Y92egZnsuf7xysKHL3WqGEMLs3CJ7Az4sesPOZ0JWNfQbBab3mGfLSMSgypGNCW1FVBxKfCtw9OyVMJqwqVhPRhfPpDSNFZ1wCG9Q4UG2CpZOe9e6Im1KmkAAUC+wA6HnWNuB6nTjndfp2PnVmiwz40fxS9dQJ4jgTslFoUmAHmyTDjKjg5/Nuz6bvbdBUCklhcmXNY1nVF/Hng38WpjQEJrTHFsWyY+T0PN9/S5PuZJPvVR6bbwsGDNTbJk5mL1feQD0CSO7y4njvzLDeZvyvyO85spVB43URky6dzSjLp0LMtwAmCUU2hdulIW/crDMtKHFbjMS1FOFFq0TCYH7qquUJJjSojzjQ985wmAzWqCrJ/9O/5nQu73wHzEI/wrFNT7X2DMYh7zt8drVWfBL4sppj5Ykuip53neGidLEq0LD0OJn6ZkSg0Ei5w58mPiC8vrsQJnhgRA/AA5AOn0/DimI7B+1s0/TUs+Osz0jZWOeYPgYxJAmkuyOh+BNfV4deeSWwalWnHM3NXSMTqTsQJNxp2/cE4a6hvydjisU5WHMlmfpsFcJjsb0pfb6ZjTlOt5CpMw8oCAJF/brgbd/N74feQ+t6tRVzmWqdtNfvNcH0mrfgZ8x82g0dwOnV/H6fw6r46frqOmTx/5XXBputiJ3XTRXS71UurI/o380zw0P2PG6Wetz/WRbdDn+pgvjvcYcsud7DiLzst5rHmiHgB++J1THe9aHD90G6brmF9sNV3UWPVOGgcItvLNKsergAMn9Z8IyPJJZXLzsyPUNon1gKs7xdy0Y113QxeR5UyEZnO5pJ2Anu3XnbT5vj4nKKVHPnYcTDtWIF0MuQMwaSVIzpVG6SVfQ7SXfzKhecQjJzyJRKNaSsutg/XqNJEIdjdDR5nXuYFxmv+598r/2pj0TCWdfLc1aB/rPZlKmqa6Lr4zbLs+muvXcfpovsdzc7w+18fctNN1renhkeHa/T6mnoP8NjjpMPPQ/K5onmrK9D19zeNYceZ7+lwfzXknK07TZS6vmDhzen2uj9cynboN+pj7PDVvrOP4HLBA9Pg8uiZT8KPIB8jGawwHGi6rM28xHxYleoWko+PVZb6vpV4TodlcDoUb7BjGGzDZNgJogqnx6uR9gm7mYbkEyQx6kDHXz3OaiKuqqsZEZGy9bKYlrSxvvAkE9dB8Pi/qN62fsYDrIFBPmc5g6mBHd7xnMVnNnej3MVn1W+VYHChnDljfRzk/HYu2cuLA2OvM5USpRctV5wCX8AiKCWTYiY4XCADpApd5rjRwd3wxku/x6qFpHUqixwsEw0xXzPIVNzecP39ebSJim7nMSYl3ocBy3fDkV2yg+gxBOsH0xYsXlWQ6N68B4B1KBYG0XE+BE4Ta2rpxJz7XU5uttlgcsDhgccDiwLXPAUsSfe0/w0lrQRRgmICOYLYYEM007e1tAKLFA8ZCxAaDQQVorwRIK7UIgNFKSJjHCwTD1ImlSsZ4dRJw0wSPBtwVFXDrO2KYATLXo6XKlFAXG8hDmtjSgXl1PTrOfOQyK0Hn9RTIN/K4mHfuemq31RaLAxYHLA5YHLi2OWBJoq/t5zep1Adg/7cOgI6AZrxAqSmBrwOmZopJP155XNKnJJyAaqJBSdKhX1xMYD1a+jteeraPwJYSd0qhoREKfdrRZoBYBnlC3W4eiw2kQUvyWY8G9ORtPl7wPtVQ2FbmvdYD2zgIj1aF2nutt8+i3+KAxQGLAxYHrl8OWJLo6/fZFt0yAhlusqMah95EN15mAkVa5SC4nAw9VkpjKYm8EmkkweUINkQWEwhY6+oME3fjpSd/CPIJoCkJLrQRkWWShlLaQFURgmgNnklLMplQ9bGeQryl1J31kP+l1DdeW6fjPjdnknfXejumg3dWnRYHLA5YHLA4MH0csED09PG+bGomeCGIKwTY8hFKMEkVh1Ly5CtHx2npLcudSGB+AstiVR0IjCn9JHgbLw/5oy1+GJL3y/XFuTGSNLCsUsAggTJ5Tzp0oJSbAJ/l6A2X+h6PjKfXQH2uTq7RH7aFKjWl8OwabapFtsUBiwMWBywOXGccyI7c11nDrOYUxwGCSYI/DRKLyUVgR3WCyZSC9vcPKFUI0jORQNWGnp4etfmv2PxsAyXB4wXSRJUDprfDoUw+wEdJNTcbGg48xivRuM9ySTf5aQ4sn5MTlllIPURPXriCcC2rdZD/vb19irdmHljnFgcsDlgcsDhgcaDcOWCB6HJ/QleZPgJDWnvIBXJjVcu0vSUC1rHK473GxgbldS8fQB0vL+9TotvZ2Vm0nWnWU1tbq9QviimfEw3yiRsv8wWan6uD10WHo/hPiiCaKjGUoOcLnKRQSl2IJyNwf0oQOtGJR746pzqObXO5Jkevfqppt+qzOGBxwOKAxYEbmwOWOseN/fyVNJl60IWAWj72UApaCx1mLQ3Nl6bUOC3dHgs0FiqTIJL6yszLv2IC81AXmUflVRBgLl/gfQJoqlcwHYFtbiCQJf1UwyiFj0xLaxxmVQ5z2ZwY8I8THZafyxuqltCmNwNp4PMopX5zXdN1zrbTsU8hHkwXXVa9FgcsDlgcsDhgcWA8DhQvNhuvJOv+NccBDf7M7qzHawRBZSgUnlRVDtZJoNrf11uUekUujaSJQLNUtQZKcglOxwqUPFNNg7yivnO+iQPBOCXKdF9dSmCbWe5YAJJtIw1U7eC5ORAw8y8ajUhXV5f51jVzzslPX++ly9p2zTTAItTigMUBiwMWB25YDlgg+oZ99KKkt729vSVxgKCzv7+voFpDSYWZEquNis0tyvqFKbqoU4JQWvegXnexgeDT7w+oPGNJb7npjWoflECTV2dOnrwM8LFew8vj5VLqsejRAH0sIE/auImQNBQC25SAV1ePbxt7LFqm6x6fu8frm67qrXotDlgcsDhgccDiwIQ5UNqoP+FqrIzlyAGCs1zp5nh0UhJLqxyFAN14+ce6T8ks6ckn7R0vHyXRueoOY+XhPS0JLmQdgmWSHq0iQn7l1kHpN8uh2kWpgeohLG88XhJIE2hTakvAnssfXnNCoKXaufdLpWsq05P31xK9U8kbqy6LAxYHLA5YHChvDliS6PJ+PleNOgJEBoKYYgMBpQaWkw18WLZ2ulEsPTodwSO9DxLMlhIIgGnmrpAkmPRQjUIHAl4CX3N6AlvWPZFASTQB8liScHO55L25bvM9xo+1SdGctlzO+bzo5rzU51Yu9Ft0WBywOGBxwOLAjc0BSxJ9Az5/AlbtrKMUu8zMR1BJySnzFQv+imExyypFN9tcJmmhukOpwJ6gOJ8Umu0kPdxwmSslpkk55qNUmmlKda5ipru/v19tLCQwHy+QDr2JUNNnzsP7pKVUHpjLmOpztiMf/6eaDqs+iwMWBywOWBywODARDliS6Ilw7RrPQ/BHEFiKDjGbTKBGoMt8LGOyAwFgLmgtpg5KYfMBy/HyMg+l2LmBEwzqPxOc54JSAl4tvddS7Nw0ueUVuiYoJiAvJZC2M2fOXEY3nwfporTaLD0vpeypTks9c+qyT+SZTzWtVn0WBywOWBywOGBxIJcDFojO5cgNcE0gRgBZKvhjHv5dDdDDcqk+weX9fMC20GNhPgLeixcuFlR1KJQ3DKn62TOn826SpIpBPtUJTiAIfLX6BC1jTDRMZNLAultbWws+O6qXUMJ9LYSzZ8/m5f21QLtFo8UBiwMWBywOWByw1DluwHeAYLWiojKvzeOx2EEJJ/V/qTqhpbFjpS/lHiWplHL7/b6CADFfeczX2NiobpUqHfcDEM/qnD1qUkBwTGlzIVfgBNc0eUfViRkzZuQjqag4An/qZBtWPRxF5WEiTmDYTublMVcdh5s+GTi5KJUfKqP1Y3HA4oDFAYsDFgcsDhTFAQtEF8Wm6ysRHYeUKoUmBygF5RJ8Pocjk8Eh0kTwV0pgegJK0lQqaGR6Sr0JnJlfS5c5QSik6kIQSz5QlYP05oLYYmmvqAigvolJ9dlm1q+fRW67yQ9uMiTQn+zJTrHtGy8dec1JSC7t4+Wz7lscsDhgccDigMWBcuGApc5RLk9iCugg+OJyP6WppapkaLA6ERWEYptG8Nd7qUfp9Rabh2CsD05a6PCk1MA2EWxqHWICOgLksYAx01Cf/EomEqxXxKhrIiCSz46bHgvppvM+/4x6SuXK1KTnashErZpMDYVWLRYHLA5YHLA4YHFgbA5YIHps/lxXdwmqKMEkWC01MC9VEKhPfbUCgWltXf2YIDa3boL6+vqGCdlpJoClagpBMQOvqcYxnvSWgP1K+BCPx+QC9IG1mcHcNhVzTZDM50hrIbmBPLkaKje59VzJNem/konIldRt5bU4YHHA4oDFAYsDk8EBC0RPBhevkTIIXFpaWpTucakkMy/1bQvpCpdaXr70rINS4FKks1raWkoec93MR2k2Aenx48fHBcdMGwyGFB8IVicSHA6nNLW2TEilxlxfPJ4Yk15uMKTEV/PInHc6z0kP9d+LMe03nXRadVscsDhgccDigMWBsThggeixuHOd3aMqx0Sk0GSD1h2eKHAshpUEV6SR0vJiA6XC3Og3UYcddHjS3d2tAG17e7tS5xirbgOQGl4MJwpOmY9A+kolsYGAX1nqILDPFyhRL3VSkq+cyYxj2/UG1YnybzLpscqyOGBxwOKAxQGLAxPlgAWiJ8q5aywfAQtVECYKNgl8psJ0GoGl01m8hJdAkRvoKMWeSGB+StfJG56PVw7v0xpIJBKWYQD+UgOfA6XDk8FLLX3v7enBJGe0ig7vUWeabSoEskulfbLSkzZN+2SVaZVjccDigMUBiwMWB6aaA5Z1jqnm+DTVR9BCqxzjgcRC5BFoer3eQrcnJZ40lrrET1BaDPgtRCD5wTIIagtZ5NB5KcXv6upSDkJcTpeOLunINrIe1jkZgeW43FSBuXwSwXtaZ5pOTcoBuJqfcTnQMxnPwCrD4oDFAYsDFgduTA5YIPoGeO6URFLSSlWMiQLhK1U9KJbNVK8goCXgJzgeL9A5C9tEkDjRwPr8/sC42cm/qirDvrbzCiYUtAAyWYGTgKrqmrwAmSC1pqZGVVUugJXvIf+48dEKFgcsDlgcsDhgceBa5sDl4qtruTUW7Xk5QAAVhe5wYgJWOVggJZqHDx+eEu9yBOuURhcL2uvr6zLWNfI2fpxIWsigekZd3digTkuOKyurFG1Ui+mBGoU2jzdONZnb1C2nl8QrscyRKcx0QsspWupsila0EmiX4gXy/2fvPaD0Oq47z9s5d6PRyLEbORGJBBhAiiJFiQqUTUuWJVlyGMmzM95jzZwd7xx7Z+z1OTueOZbtGXvmzM6Mx+dYstay19ZawaKsyCBmMCIQJBLRyKkRGp0z9v+r993u1x++r+PXQDf4Cvj6vVev6lbVfRX+devWrXj8XN+Tl5FMCOY6vYRewoGEAwkHEg4kHJgqDiQgeqo4O43oAqJrJdmtSJlyG2/WiA/QnMpNhZ4nwDOWGxy0un+mK2EKpVYxFol1pvhBQt/BJsboOPOR0gQ0swHRwSg88cNnMtHO5geIrKquGfMkIRuduD95QRqfTcKNPWZA9q3WjSZ9/77kOXEJBxIOJBxIOJBwYCZzIAHRM/nrjTHvqEggMR0JJI5ECvCDLeWbAaLJB9Y5sLgxWn4BtKhzYHd5Is5VIbCUcUZ2m0cCmYA+wLqDP+LCk/FKVQOI1iSBay4dOuuA6EwbR5Hss/nS857LdMdDizrI4TYj8Xk89JKwCQcSDiQcSDiQcOBWciC3I/mtLEmSdkYOAERRHeju5kS/iW1mA9QCVkcDtRkzMAFPgCmS1dFAH0AU3Wmk0eN1gE2ks0wwAMdI2kcCtkwg0OONTySggZrLeMwGAiTZnJhrXgJMsfrR3t52A23np0vRx8urXIUH5I/lu+YqvYROwoGEAwkHEg4kHJhKDiQbC6eSu9OANkAU9YjJOIDPeMzOTSYt4pIev9EcgHa81jycJnwBNPtvJMsc2KJG/3n+/Pk3SJ45LTEOrJ1+tiuAtrKyYtQJQrb42fwpD3SzgXM28x09ctQ2bNwwrvxmS2+8/oB8ys4vcQkHEg4kHEg4kHDgduBAIom+Hb7iCGVAWookeTJSSIBmSUnpiJLaEbIw7lcALixmdAR95ezRkSJfuHBxQuoBgE0sV7ge8dWrzVltN6PHi+pGumQc/zlz6gJwzQZe03NPnLFYAkmPN9ozeSsqQt0kPyM/KOfadWtv2jeM5xfeIPVHlSNxCQcSDiQcSDiQcOB24UACom+XL5mlHAAYpJCZdGWzRBnmTXwALTRulnOwqqRHdIQrKBh/FUb94rIky3Hd3GLZWs4kJaX8pFNTk3kzoKuFjNXaBpv8kGxPlYsmHx03kHeJOxOPeLlvCDhFHoB4JhCJSziQcCDhQMKBhAO3CwfGj0Bul5K/R8qBqgES14lasABA3mwARJrkmc1ygNhsjjJhHxqAOB4H/XR+oM6BCkk6wOyVPnnTxQsjmveDP2NV6SDt69czH9M9njJkC4vEPJsqDAAaven0MmajlQt/vh8TDfI1kspMLtJKaCQcSDiQcCDhQMKBm8mB8aGPm5mzJK2ccKCzs0Mgpu8GVYTxEAf8ABRvpkP9BJNyAL9szjc8ZnufzR+JaI1Aejr4PnfunCEpjrtC6fDWzKrNKKUmHOAZnfOxSlnhZVlZeTyJnN6jIw5Qz6S+wzs2Yo4V8OciY9S98+fPj9uedi7STmgkHEg4kHAg4UDCgankQAKip5K7t5g2Esdr11qkijFx9QGkiJibG++hIrkoOmCQXzZH+UZ6nx4PqShl4ZcpHmbgMm1URLI7EvAEsJ47d35UNQ14iV7wWFU/0vM/1ueWltZgASQ9PJMGyjGSdD89zmSfsZyycOHCsKowWVpJ/IQDCQcSDiQcSDgwnTiQKClOp6+R47wAmgAwkwFNgM3xqCvkqghIdufMmTNi3lER4Dceh4pINueHvMAvyg3oZcNhRUV5RnDtdOAz+RiLNHpAgFuF8qhTcsVKR1lZZusmSNrRb0cNZqSJQS4yxiQH/XN0zTNNWnKRRkIj4UDCgYQDCQcSDtwqDiSS6FvF+ZuQLiCwtbV1UikBEAGXN1udg0x3dXWGTY2UI90BdNHv5TdWh8QYQJdJ2gwN0sGKhEuKKTtgdDSwyXuAK26kCQvhZkmdoniKVWPQ9wbQZ1LpQJ0ElQ7KNtUOfk7WMsxU5zGhn3Ag4UDCgYQDCQcmyoGpH0knmrMk3qQ5gBRwPCAzU4IAMWwkj6SbnCleLvzy8wuyAtjxSjYBt6hSAOqyAV2AJZJqB82kwXP6JsRMZQN4A8BHOnjlZm7sa2mJypqeV8rIN80EsNPDTvYZII+KTCarJ5OlncRPOJBwIOFAwoGEA7eaAwmIvtVfYArTR3qMOsd4AWd6lgCz2YBnethcPpN/QJiD2nTavOM3VkdYQHE2fsRBNKoIe/fuHREUx9MFMFZVjazSAQ+hezNcVVV1VmsYV69enXIdd05OxJQffMnG75vBhySNhAMJBxIOJBxIODBVHEh0oqeKs9OALpJPQMxklu6JP3t27S0pDaCTDY3kP10FAzDa2toiNZOxnW5I+LHwAuCH9B6Vh3Xr1o1ZigrQLy0tCyoh2fjNpIDfzQCVSM9Rp4CH6emNdsR5Lj42mxvhd/p3ywXthEbCgYQDCQcSDiQcmA4cSCTR0+ErTFEeciFxZNmfzWg3S4KazorrAr/hJzAYd4DD9nbM992oLx0Pxz1hUeWgHNyP5ADAAFDKDQhMB6AjxSXOxYsXswS5HlRimNiMlocsBMblDV+wQuL63fHIlIvJwlh4F4831nvKt2DBgrAxdKxxknAJBxIOJBxIOJBwYKZxIAHRM+2LjSO/tbWzJy0JBDwD/G4FiAbAVmpTY1kGFQzA7vz588dkOg06bKjDVN1ooBgAjaWNieiBI41mE2YmB3YH0AJebwaIhj/Z7FeTPicbTgWIxvIHuuGkMRqvM/Ep8Us4kHAg4UDCgYQDM4UDCYieKV9qnPlEKpqXdz1IU8cZdVhwNoXV1tZm1UseFngKHgDvSJEzHTve1tY+KhAEzDEJAOCOZYMgRcCiCYB3rOG92ABXwDq8TwfKYUIgcI5eNuGm2pEeqiOZHO8wHzgVG/5chSMB0Jk4n/glHEg4kHAg4cDtxIGpH81vJ27NoLIg8Tx3+vSYN8ZlKxogFgCbDgqzhZ8K/2wS06ami6NamQDMXbhwIQDxseYNIMyGTADheF1vb4+dFt/T1SjgH+W4mXzku6FeksliCBOEqQC6APORNm+Ol59J+IQDCQcSDiQcSDgwXTmQgOjp+mUmmS82dC1csnTS0kaAH0v/6aBwktkbc3SkthwMglQ1DkABgKtWrQoqGqMRQ+1jrFY8KC+b4tjQOBEVFk7oQ8qbDsDJe7MObmnVpsV4OUbL+2Tew7OampqMqwhI50+fPDGqJH+s6VMmPw3yZpVvrHlLwiUcSDiQcCDhQMKBqeBAAqKngqvTgKYDmclKG5EsAkKzqQbcjKICbNGzZSOhOwAuahdeTvePX3mHNJYyjFV1AdDOwSmoZLAxcyT68bT8HrURdKqJHwfh0K2VlZMqqXNM9pt4WqNdAfJInDOVIXzXhYtyplpCmdDB5nezyjda+ZP3CQcSDiQcSDiQcGAqOZCA6Knk7i2kjSS1uXn8IDBTlgGimVQCMoWdCj9AGaCvsLBgkDzAuqmpKSNAHAykm6tXLo+q8hEPz71LcNmIOBEHaEV6H+cZfuQ5E6CdSBpjiQOIJx98v3TnetnkabIOqTZ663yj8eqRTzbtJH7CgYQDCQcSDiQcuFUcGL/SZ5acYs3gG9/4hp05c3owBIP46lWr7ROf+ITVzJo16J/cTD0H0OtFpWOyUkFAH6bhoDPVAIm0kOCiV+wgzzlVUlKs2+vhKHD3w95xT0+3P2a8Vkudob+/T/FGB4tKPoBBTjVE+g5o7+7uykh3NM/y8jJJovsH8zvQP2AXzp+3ckmpa2rGfkDMaOmM9B5+IhnHcYR6urtw7pyZDtKZP39e+qtxPbPBk0lbUdH4bZIXFBSOeZVgXJm6TQPTPvgl7r3BAVaT0lXD3hsln1gpEQrEhRcTo5LEmikcYHwb6yrzVJUpZyCayrv3zTfsxz/4vs1bvESbi1gS71WF7rOPaJNbzVSVIKGbkQOA0HQgmjHgKJ7QwOZvJgkqfmfOnAlqFQ45zO4AAEAASURBVOgcHz502Hr1zQdUF6p1et+q1Wts7rx5dvLkKalitNnq1atHrPBXLl+yH3zrv9mZYy8LtN9ozzkvL98GlGaewDSub6DACvOzgeMoVF4IeSOt4D3KnzzLFwhdZH39QxPDUaLEXnsuTfnFTSwPMYITvJ08H7InPDnavf35trhhu/3KP//97EnM8DdI6TkUiP4QaT3P7mhbsyRcYBMwk15+IzlWFJ566il76623wqSWia23S7/3K3T83q8T8YvnZzJ0xho3SS/6poCDqM9cYz//8z8/Yr8Z59lMuwc3oKrH6h/1m8k4dQUHD1gNRBjHPhMXCGQrI7R++MMf2v79+8PYR9sYa70ba7h42mONM5lwSXqZ+zh4Sl+6bu1a+8QnPzlYZ+L8uln3OQPR8wSWPvu5z2sz2xL70m98KehGeiVOZtI363NG6cB3lvG5cvLeZB3SWDbMpYNydJK//OUvW8OKelu4YJH99m//HwEIzKurtSsCDDt37rTf/Z3ftcOHD9tfff3r9pu/+Zt2xx13ZKzwdIDHjuyxjnPP264lktgW3wg6SwAirZ1WWhAdnX3o6hxbW3spY/H6BvKso6/AKgr7rGCMSktil0lgHMKn+nHRPpmR/mie/dej9IGZFYUR0O+FtsaHseZntDTG8r6zL9/41ZZg8nB4DMrbpzwV5k/MpnOXQHCXaFcX91l+Gu3hKd341NVr9v2351hJ1eoAIlnlSK9fN8aaWT4M/gzoly5dto0bN9jzzz8fNl+ygjKg1ZFinba5fft2O378eJA20l5G2ntw4sQJ47dr166gdw+/aOPuvL/1Z64T9WOQIv9cnU6S3s3jJ6thP3n6x2HVgUkWAPJ2ax/UzbNnz9qrr7xqW7Zusb1794b6PU/to0CdZFlZuS1duszeffdd27Fzhy1fvnywPoZKmfaHtsEEk3bEuDfRuu/13es+z0l7mHjdzzU/aQe0iVdeecW6BKRpK1iEulXtI2cgmkrGgNCwoiFYBOD5rf377PSZs/a+970vdPowM3FTzwF4H83ghwbYiaZKR3St+ZoOPanUQF85jMxzzz1nhw++bZ//pc/Z2TNSDZB7/PHH7dOf/gV7+umn7c/+7M/sW9/+ln3mM5+1wr/9WyP8mjVrMlrU6JQE4sBrz9nyqku2bdmAFQ2pP8fSbDOLnUC+av4lKy3MVsbr1tMvO9kCiGMFeD39eXa1M99ml/UPpj8g8gDiItEZn5NqSgAhEXCGztWufCsvum5lWfM8vhTGErpXeegSeq8sQYI/3IG/zrUVWl1Zn5VMIE99UleBfmkBIHw47ZGeSHfPKQ2S1Utt6513D4LokeLMxHdInplAbtmyJXTy/VLDWLRoUQDBBaqU+VKl4TAhhAwvv/RSOOBn8eLFGYvKJPONN96wlStXBpBwq5cwM2Yy8cwJB+hz39Lkq6K00rZs3iKVtV4JJ3JCeloRweLTm6rTNbNqggUmJm2szDwgvFBeVhraR4kk0bQjwDErotn2qQCqGHPq6xvs3nvvHXEyOq2YkGRm3BygfTBhoi6AJ7q7eyZ9qNy4MxGLMEYZXSzGCLfszF+mmSOzZjr9FzUwfOUrfxGWa0aIlryaAg5QwSoqyidNGUA+WybmSkvLhtHi+z755JNWN2eu9N7XDEoI5syps82bN9snpQc/u3aW7d69O+hSr1u7xl5//fUgIR9GKPXw9oF91nr2RVs7v2cQwKaHA8aebyuw5q4IYRflRRLpG8IpYJfURsF1YwXQ0ABwVwtsxiXFnZJmn28vCRLb9HRGey5U6wKYI90GZFZLul4iwHkzHeC/KgOAJg/kaVbpgMX2a445a70SrvdL2s+EADrjcW3SaNh/ttzWbftwmHBTV2+VFGE8+R5PWDp67JMzuDP4syJBv3hJm2H37N1jb7y5xw4JYKPfHPTvtSnzvHTUARKZ3MF33gn0WMkBQEMf59f4fSa/EDj1J9P7XPsl6Q21c+etX0f7VkjWDuh7M+HCok9ZAJQ5Harjn+eW3bPX5rzayBKtXvuksF1++/btszf37LWjkkDDs/qGejsniTWrq5kcYY4cOWKnTp2yu+66KwBo57Vfief3fp2IXzz9ydAZa9wkvRvbETrv77xzMJxkjJoP7WM0VZ84H3N9n5OWyWCBrh5LM4Ard319/UFfNu7n75Lr1HEAfnPIBjP4XDg6uPRKivm3g4cP2uLFi4bNAl11p0Ib6Iq0RA+IwM1fsDCYjCNeuiPMS9//hq2ovWALR1GeL5Mkt6YkqmPHr5UKUN9YhZH6XuvOt+6hqpieZMZnAHdZ0cAw4F1e1G+LK7sFsDNGGdXzckdhkECDM4sEoMcD6kclPsYATe35dkUS9kyuXOVFxWQ8jm6tWfzt7BtnRMUD+x29mG9tpXfbuk3bgzQhm3RpPHmabmEBw2y2Rs85qGhIn5922SvQ3NrSFmyRt7W2hf0DtJkKLUdekw3xTPbY2RT67LPP2lrp/6EK4gNw/Bq/hxc8x/38Od3Pw/o1/n4yfkl6N36DsfKTcfSiNiGvlh38Eqn83I7tg/qBLjSTZ7fhHybSmpEzibh2rSVcaUeYDEWdMJtJU3RjUZXasGGDVD6WDav3Y+X5WMMl9Xri9ToTjyfCT+rNieON1lDfENSGb3X7yIk6x7F3j9lv/Po/txpJLDnpbf2atXbHls12Rie3Icnkl7ibxwH4TcXKlTUNJAZXJEFbtHRpWHqmJAEQdPfe8G2xhAEQYBkbEL927boAsouKiiVlG5pVOjdoRK+9stvarr1uOzZH0lF/l36lFlUIRHf3F9mVbi3z9RXZytIr6cGCJHl+RWaJ3g2BYx5nWgsE0NVpx/Sxo5p73XolUS5EbSEWfiy3S6ql/CvXK6nt1c5Icotk+GY6Jh4VsTJ52uTiUke+FQtf10giPRbHJ2QiMLd8bOHTaSKFPtFaaw3r7gxSaHTZbkdHvaYtpPd9y5Yts/e///1hUso714FmwkmcdIffwXcOWbPa0ifuvHOw/eEP6ABkeBr4+b3TmYhfNtpJehGAGC+Px8NPpGxIYudoslQnKVt1ddVtt0rjdTNduMZzVWWVPfLIB8MqKvUNAQ48ydfyIOpQ6Q7eHjp0SAIatQ+tfgYgHgsUr//j+Q7j/caeZJLe1PVLzmN058s0bixcuCAIKdK/uYe7WdecgOj6hnr7p//811WZD2pJ5UyQmnznO9+y1rYO6QMKGSXupnKASuWz+1wkjKm8eZocxaXRqO6wTN0qqQEDOZ0HJt1++vwzQYfvzTde14Ceb5/Uzlnyc+1aswBD8TCpNXm7LIscr7zwfdu2+KrVlkUgArCdL6QGzUgpIwLXPB5trrajrWvsdMcyW1uzX+oSV604TUUiSEilx4xUGUc85nGBnJbV6SCH0hgC7gDoogwC2y4B6EuSKC+s7AsqH04z6pSH5zMkqD+kF3dN7QVSFelXXod8ycNQZz2Ur3S/OB9UihAn3U8pivAQvzwcqZUozeuklSYGJwbqGJ4naJK206YMcT5B63x7sXSoe29QS3Heko9M8dzv1NUCu9C71nYt3xj0hHM10SNv08nRVjhY55RMfsbBAqc6ot+J9BleI3SgHWGVINPpkkjfXnv9Nbtz+53G5u3o20Qlpd3h4n7x+yjU8Pdj9ctEO5Nfkl7E0dH4kIl36X7Uh9MSPJ08eTLo9VZVVQ9Osvy73S5XysoYAt/iJunooxgn4tLFHm1sJwzAKd0htd63b79UCDcNW6WJh4t/m3SeEy6TXzyO05qIXybamfwmQjtTvjLRzuQ3E9OjzpzXCg2qbdslUKD+uBqQ8+JWXHMCohkEvvSlL4Wle1Q7LkiV4OzZM3ZUM8TqmlmhsLeicO/VNGkgDL6AV5bCJusABN4QnRbAetv2bfa01Hj45gzwWA1A+vzMM89YnXT5/uW/+Bf2wAMPBIBw7NgxW6VNUbW1QzsDkdQd3P+i9V99RbuvAYCZndqOOlv99Lqps9KOty23roEyO9uxyNp7jw6CaMpNQ2vryZOKAiB6iB7xIzpAR+4Bi+4HZZMEOlyG+RMOveK55Vj5kM3snvwgVa4tRVckApzDaQ2nET1Ff+MSbs9r/D330LrRZfaLyhOFju4jAEu5yBuO+xbxo0iDU3VJ9AwnPR3PU8QL50l0JX68bDyXqseI6A9dh7I8lH48nocf0MRm//lam9twr82ZtyBMqDwf0L6dHOWaN3ee7du7L2zMnaX9AYsXL5GKR1PQ3eR9gdon7aiiojIsXa9auWpQ0gwvqCNHjx4NAALrBIm7vTmAffwXXnghbLJbpNNEsTV/u7YPviSTRlZiODRr7tw5QQcc1b64sIZxh/EFtSg2Hcb5wTssdzDWPfjg+27vypGULvSDL7/0ctiMzYoefWe8rtwqFuUERFOxkawA2Pixg5wK3iW7j9j1vV2XbG/VRxtLunyTXC1zMJgjHUH/2TcYQv9nPv4z9tSPf6zNgy/bz/zMz9qf/MmfDErdmCHSSSJRaGxsDL9f/dVfGQbqr1y5am+9+YLdteSK1WjfIukA/qAdl4DiLa8ACzfWXZTpugN2qG2zdfQUWHmBg1m4EgHHWqkmuNDVwSr0/L37xdNrvFocwPjioH4RhfV0ow2CZm9cXmcnr5VbQ80VSXCPB0CJMJC8KfcBXBIHKXo8Pd7XlfcrblGwhIFqRRRuCIh6WtAZyucQbfygk55exCsPF/HQ+ceVOOg89w4gYo8kl9ByHnT0FtrlrkJbUC4zhpok+DvdKMxQOEzSUa7ZpT28CvmP8sqTEkjlm3JAO50HhDpxRZKEnnp7ZMN2TaylM686cjs7Nr0gYGg80Wj3LLjH7rnnHm3GVH0VfwKn9XGKxYN3Dh60ktISW7hoob4XvIxciyak77z9tm3atCmsLEX11d8m19uJA3z3xsbj9u6xRvvIox8K1pBc1ed2Kme8LICgdevWBROPq6T/faese4EX4lJoQPVRqYuCKdIFQrw7qLazbNnSIIWO007ubz8OIIXeJ4tvjz76aOgPaR/x/vJWlTgnIDpT5gFw5bejXZ5MhZ1mflQsljpy5aDHTvHiYokyY27FihX2aZmvOyk7tz0yM8PSdCZ34MAB27p1q5Yo7xucOTLJOvLWm9bX9LptuasnNAZAGy4OwtIbyezSXtsyp9Fae0usuUeSjCIHHREAZANdsFus+udAEUAb0SEMgDMCuVzVZ+vZrKE2Dg6HQDxx23rz7adnN9rx1nXWX4CtqXelSnJC14geNHERveF+0RttKhRArSjuF7iMfBxkRvnyUAFfhfwM+fgdwNvL6n5DV8qRnh9/iwUOd5TV+YJfkSYhdZKqRyYFh/jCO/8O0L7WUyzJaZ7NKesOE4SR8u1l4woNXG/fdfvJOxW2YOMHw4DHQJmrSV5IYBr+oYzUe4BwZ0e7zaq90WY7m6LYgLhh/YZhKljw7ZSW9jsFFAAY6fyehsVNsjQJDgAIf6oVvEUL5ttSSdk4nGc6SNkmUaRRo1K+O+7YpI22LcHyBtLFeD2nDbCJjLFs48aNN/AD1Zfz5y/Yxz72sZzt/xk100mAW8IBrBi9JGtvmAClnqAGOF3ax5SB6FvC6STRQQ5w2hUAMFdgmlmfAyJPBBD0uc9/PgW2MigTpwKiF42LgyZOJ3xn/7O2YaGkuiUuuY0ALWFT2Is7HoMEFlCGW1DRJcneYXv5/Fo7fLnEVs/mFLhI6sqBJpc7C21eRWSawwG0551OGj93+GMHGglvcVBVcMBNmpFEFZ3i+lmtdrmnS1JbbZBUeA5zYSKAI6/RL4o7RD+SOJM3HKbucKRJ+MgN3oT0yB/vfTCJ5x8AjIv7RT4RzQggu89QuF7Zy74mqT2bAT1vzo9C0dQi0iBNYkfpR3T6lGfyOr+iJ1zT48f56fFSbInR1OafiwV2sXelPSDzh0iUbldd6CHuR3dIolF18u+Z/p529dBDD93wntPb3tbkkwMm4ipQ6fGT55nPAdoNajtnzp21T/7cJ4OKA3rB7wXHgSoPPfxwqP/pbYRnQBMCnPjYAV8AVdhNX6TVG37pcd8LvHuvlJH2gfnCczIB+rDqCmMHAorp8s2zI59JfiEKziaaxsZGuyw9QJ4Td3M4AK8BO/ENTZNNGUnJFX3PdEfnxoxwpApNmHgnSP6OHnrLeptesdVze3S49lDd8Gri9YVn96NMfr+kssPuW3DQ0E2OwCPvrgvsDVh1aQRCPazTIu+Z7tt78+xCx5BqQTwMaRblD9jqqhN217y9tqT8pLX3lUkKXj3Iinj44fdRkMhP4NgKB4G0RyaPnk/8PL5fx+cXUY3HFUUpceQH0D/cP5qwYMeaTZMRWI6+g+w9yM620LUY2yJTdkxKiBuPD8/jeYuehpfF33eKv7sby23DjseDTWSAY7w+eNzb9UpZR2sf6e85TAC7uBwmkE3thUkckmzaprd1rgAM/HnPhiys62Axx78hYeL3Phm8Xfk/3cvF5jhs6K9ZtVo2+WdL17N82kjZbgbvRmoftItMfcWJE8eD+gsHGcXVP+L5pY5T/5mQ0iZw8fbBPT/4TxuiHfDs7YH4PHNN3K3jAH0Zm7Gxp89JlNNFF9o5MmWSaCrl3/zN3wT7jWvWrLXP6BS79bLjmD5YeEaSa+44AI+R9uWy8aPzjlHzXLgOLW3vf+NZqVBctLpR9j1mqi/0aejOLarsDNkB6BIOqxy6DSbqCBOPm40XhCnnwBBBzWxhSKRY6hirq05ZWd4VO9K6ynoGygVPr6ZkzNm5IvKiG73nVMC23iKZ6BuQbnHUqXua5MPvs1Mb/xvS5oCXujLE4CDfVGZSpJDuI4GPpPwCyvJv6qrSBs4KW1XdJF4OyALKjXG9TCkygdee/3hZCHfoguxCF260h7WjmgHvvSKFdt6M98rAv/vl3WEjIpLseD12Wgz0AG2WtLG8smTJIquvbwhHJ/f29lm1dM7Z3Hv4yLsBUJeUldg69cPFmsBgfnLDBpbH88MhFahh1ck8aeJuPgdoM42NjWFDNif7MsEslX584rJzgAnhD3/4I6tvqNex4EuzBuSsBDa0d3d1h0NrsLN+5vQZa5L6FHxGgo10E2EfgiBo0dYAzqhQMYnlfX19fbKvKyuXp/oFh1adD5tLOcSN7waIztQnTnVOstGfMhDN7LFGJp4wgI55pnNSCl+3fv20Knw2psx0fzrmtrZ2gTJJZfUNcuEAPtkkYuOlv192UFvOPGfrt/aGzWwOyGgYDsQAdc3tffbU3k5791yfrV9aaB/YUm4/eFOS64FeW1RXZIsWVthTb+XpyPEmu2t1qa2ur7CzMhud19thd64stavt1233kT67f1OZ9KQj9Q7yCm2AN4702HhXWdSn++A1+CceDs8StZZl1R3K8yEddY28NnKeb7/i6/eDNPUtaop7lFZB0I9WUQfzQHgvN/fu4ukTfpCWAjh9wg4PN8RDwgCakbQjUZ5X3hv0mokDLX46W9SqdKCMO+Jc7iy1N5tWSo+51zbXXdIkY3jaHjZ+jec/fk/aB3Q64erNjwQbsIDoTJKlOK33+j1L+6dlGu+DH/pg2LDNoJ7uWqRHivTyTk1MeH/y1GlbIIsOJ06c1JHJZVZfv9zO6NAO2uz6DevDBix0rJFsnzlzNuils+Ebywgsl2dKIz3N5Dm3HKCtIWw68NYBW6jDqFDbwVLLdNH1zG1pc0eNPQZMHh977LEwIc9Ud5mI0j4WL14SwDFWPJqbrwVQTNtiky9mJVvbWm3b1m0BpJ06eUq2uevUPs6EUxQ5GIzNvfRXTFrj/VruSpNQGokD8P2dtw8G6yyoxSEcnG7jR05BNB3CSZ0kc+Ysx9dKOqKZ3RZtrKHjzrbkMhIDk3cT5wDm4zgxMleOyswGKL7jZIA5UujXn/2Kra49b/Mqh9QzyGe8kwLjfvOFNnv1sDYs1hXYXz+tJWkJb//wm122dmGv/fIHZtl3v3NR6hHXgym7//rdZvudz+bL3FGffe3Ja/blfzLfDhzvsr97ptUeWDdXouQhA80OoEmzqz/fzrUWRRsLhSrj4DQejrA8FwiULq/uGgSh+Hu+/Rr34x5HeTiuHMscSIY5NjvbSYFgXwBuPH2e4y6e1vBwQwE9DGkTv6Ov0KokWXZ/6KHb3aqNk1XKV6GOUUe943T7fLs2sMJ2X2Kj6NO2fd7lYXGIF+cTz5kcaR6/JBvhxXfZznVbw4CHJCFx2TlAH/r000/b1i1bB+1Cw2sGDsCCDyDsVEcig/SMtskyJ4AZAIYlA0425Pnq1eZwkixSNb47fkukZ4qOoZsYA0xD1+sF6UFzIn7p+YQOeeKKmwztTHGnIj2W/skvgoN0PuQyPfiB1aPzkrTde++9ASgkUmi4kt2hmrT7FZlE3bEzbGSnzlIv0utGS/NVWQfrEvaITn0EfDF25anTXa6NabQb2hrxzp0/Z5eaLlm7xqYVNSvCCg8SaCaY1bIwRZshnfdqe0jvF3jmR7vOZXtIb2t8GzDHiZMnBi0UTcfxI2cgmo7ne9/7nn35y18O+nelWj5kmXGnKvu/+bf/NqvlhuzNJXkzUQ5Q+Rggc+loLDU11ep0Jq5GT8N7U6cTXj7ztj2+iwF1KId6NfgcGs81SRKO9tiH76qwj2wvsx/v6ZTMtMCW1V2zL3yoznasLrHjF/ts0ewCKygssGOXuuzdCzK7d1e5feO5DnvlSK8dP99nO9eUWEXZEIAmxXhaHDZSJxvQANEgt+VlypG/Pm3K6+i5rqtZe2e/zarUEc3SakHDoUv+laVRIQiDhYtidurJAVxT+yAjaiKGmbn8vH5rla3pJukh11d3D5aZQJ6vFN4I79wvvNefKI9DvIq/j9OI+wOQOegFP74B+SZ/ZcWAM2hGOvRir3X3FQRTf1tmvS7979M2t6wtxIEr8bT7lcn81AeMp0Ue3KELffhyrS1bdVeojwxkfNvEZeYA3+at/fvD4H7frvvCAMXAAs8A0Fx5xnGPnWnn54DeX+ebqNIVFknHXf0xahudAhKc7FUjG7uFrMAo3HJJqbFHDIhYtmz5IEgg/bjjebx+nr94PPziz6QxEdqet3jcXKdHGoAnJJ0sHzuAIk3/DoTxPPg38fdc4+/DQ+qPx3E/DqdC15MJD5Lo6Shl87xOhyvf+siRI6He3n33ztA+nN+882/BWMU6YaHAL/169GNTddR2irRpk3icZXH8+ElbtHih2keNdfd0h4kMqk0ntaJDG1q5YmWg69/O03N+uL8/c437eZrxePjFn9PjOK04nbH6TXV68Pjo0XetT5L+tevWhnLg5+XhHr6lTzi8LP6N4lfKRr7dj2fu6fP27Nmj8b0oTHp8ss/76eRyBqJR/n5HJ8lwTOmv/Oo/0WEKs22gV4dUqIPASHribi4HWM5ikMxlx1xSUjrYWCZSGmaVr73whO1c3izgGunfQsdhlQ/hgLpeWcDo7M6zuhrUSPJs+6piO3elzypkyWPJnAJJcmW7+hIHiejkt76O0HAH8solPcq37StL7Ievtcr8ndmn36flUYGH0IjTMs14hz+qHiFt/VHbDY533J8QUP/7F7sEogesraPP5tQIqN9To0bfb8+91WWffbBS4D7P/vHVdtu4vMQ2LC0K4Bky0AxX3eTnadOj1CmCky7qoiodZSsAC5gNLpVe6mmIKfLwIIME436DEVI3qfzzRDweuzUB6O7T8d5SQcHSyLMHOiVxzreP7ygNA0xN7BjyQpm82zZby2dS8eBwGYAyvIBYyIcIBrrun5aeQg5+z5PNRXbp+lq7b9V7yyIHPJiI46Cit7VUvW3btrDa4wNLnBaDCw4b1IQFKOPXJP3PO++6U2+i9wxAqHzMVbgKmUtD2qZDyFXfVN+l4gU45JAK9Kbjzum7X/oz/vj5oBkPl+7n7/yajZa/55otTDrtTHmI0xmJVjxcpvQAAVg3Oqtlfb4Bm/0QSnR0dBp6tvAWyT9+xGfZH0k/UjK+C7x1l04//ozawHGZB73//vt1umVViO/xkuuNHEAKTZ3HtCpL+5naB7GoK1ilKtX3wI4034qVl9WrV4c4CPdQdWxrbbMiCWBqZ9UGNQ/fjIt607PPPhtUOiq1tyDu4t/P/fG7mfXzVqfXo8kGfcsJ1d08DWLs22BVDP5dktWtdqmS0segnsRqDhs3GftxtI/Rzg2hfPyYzO7TEd/368A2vud03UuTMxBNAevr67WDckEwms49DpH/dC18yOBt+oeOHp0vKjezwlw4GgkDvS8Dj4cm6iUH9u+x62377O71AGhJdrB7rP8M7IA1AKUew5Eg1ZLwzq0psCOnu23lgjz7ix+1hE2IALh+AHRTr712uM3+9afKrLSo3A6cbNUL6TUPFNmWhiL765+224blZbZiYWSajzTUNEMCIW3dQ+tKtyxFKMXZZVJ/UQZQbygReFR21DGaXW0dsBff7rCHt5TaR++qsv/nqRZ7Zl+nrV2UZ29KUv7zuwT4JeB4+2SPLZglhLpEA2iqTF0Crn3XpSohQAqt5m6pc+go8hKBWcqKRLpQ4Br1jiiOLmQxFT90lvCJlwoylO8U75R/9xssn/yi4FE8RROIzrNrmpAsTJkOP3KmR/kqsjOXBatUN/KKSowjz0sK+qxfOjOXrym/VTqmvExL/OIFcdvbe626XLbfNYkJ+SGZkM9I4h7SD0zj+yH90eE0p6t0OuGOsAo13TaDwKbp5AAE6EL3CsBxuAqO7+8uSNdS0hr8EExs3rxFg1NTaDuozhUXFQsorArv6HNRozt/7nwYjAAKpIFjkzDStl5t0KrU4ISLpxXqHe1F6Ts48Pv41e8DgRSNdL902vGw8XvSicf1+/jV7+Px0v1ykR40Ll26bIUFhQEQo1vOoSCNjY1BWllcWGynBcpQVcRhv3ZO3ZxgBQLAwKY0L08IoD/p349v8dRTTweAt2TJkgAsctVPe5q30xV+MulgsnLfffeFosEvr5/OX/dDdWPTHZuCuswF2ZIGvAHqli5ZGup/fj4bCZdZT+8xOyf1U1ZvsP6Ac/CHygftyOuYXwnj9/Gr3/Mex3O6n/uHALE/hHPncfyKv9/Hr34fj5fu53E9jF8J587j+BV/v49f/b5ffdQ5tYlCYTsmNtjyxkoKE0Kk+zU6pZp7+h8A9muvvmb5EhyBBQHT2PxmPPBvF8+Hpw1+YSIzW/0U34HvSfzp6HIGotkxe+rUSenzPWXPPfecVUmdA3e3Dtj4d//+PwR7j9ORAbdrnqh0QQcs1lgmW1YqMTPCuKRlrDQZlA7sedK2LroUVCDURsCFArApaazatDdrrqhg7NpQbP+vwPAPX28RUCi03/pUjR27oKOnS7RJThLh5XOK7X98F3pF1nStxw4dF3y7r0wqHoXaiFggibTUWipSEwhwapD8RoM1+UbdokIbCjula322tcAOn2FJyezelQIa0g/OUwCel88ttEe2ltmGZcX2zqli6Vp32Ip55ZAIDgCJyxMgHiyEng+dzbN9Zwrt7hXXbf1C7FFb0DkGNJM24JYjXnhGOhI2CAZaEVBF3xspOg74MwReI3ATpMTRi/COXBCceNCikyJMtdQ5qthYqWfP6xuHO+3lt1sk0R+wR++ea595oMyOCVz//t9esTYxpKa8yP63x2vVUZr9l39oFX81cVhSar/+s3NtxRxyFMiF4no+U2wIaR5vzrMzHYvtsU07AkCYSJ2JUnlv/GXCy+an+vr6MElNH2D82a8MaCtXrtAAsyQwiLaJH9I2HOE4lMCtewCcfZmVgYyBD7CHP84BNveexlj9AC44wpMHHDTi/uQPP6fpVw/Ldax+nr943LhfnA5hcHE/DzuSH33neh2AU1FZYS+++GKQrgEOOJ6aAX6vJGTN0rvtV/tBKrdz587B8kPfAUeU+hBPeQdfjh45aocOH7LP/MKnQ/tIBE3OqcxX8AVL+9RnwC589O9IDL/3bwqPsToDeMaP/odvgt11jxtWGKTGwfd0gNanzdRHj7wbvkl6Ok47U3pxP8+L+zlt4pMvrxvcO038/N7j+7PT4ZrJz8PHw8X94nEIg4v7edix+JFPFUArWLPtDqk7sTJz6NChoMLLSszq1Ws0iZdqjARuHNeO1PnCxQtB559VccwNxsvtaafniU2eWFb5yEc+EmhAO6Qdcj+9/uQMRNMZo0P2GZ1ghyqBO8zKMOtI3M3lABWOisx38UY82Rw4rXjFHwtNOqlj7+yz/Muv2/otPUGfGAlqJH1mUImkwvgFFMpFQPCj0m/esarEmlr6bamAbHV5gf27z8+SjhS6xWb//pdr7egFSVAFqq2gWNLU3iDhvdoxECSmm5dLFSSFoUMnJbohTdGGAOVoVdgfHSi0fefq7NzVPPu1+yXZM1QtojyRJcBvsKOsbPXo5D06EcGFkBblV98YTuQL2Q/hI/C7ZpFO3OocsO/sm23nJMG/u6FXGwuJFw2ynBQILfStC3TFAZRFIpQPv6CrrStvCeKAlZAiE/I56Kdn/Bx4e5hIwq6JgXiBXmyPCnO1rdP+w6/Os7OSRj+9r1m71PNttzZxbmkosU/dX2df/XGLnjsFqJFc9tv/+bm59szebrtytdsa5kTSfXiJ83xGk4CIRz95u8waNnxQ+oaLw2SOjjNxmTlAPWSDGas8u3btGvNgwaDnINgpx9sm9/HJC2HpEw6llrhZtp6so22fUt47NDi2ST2kROAToAIIZYBFYs7Em42QOEDNdB0MnRfwrVr7P8rKo1U81z0HYKFOAN9RhQFAA7QAdq+++moY7NnUOZpjwvT8C8/b+nXrba7UEnK5Wjha2jP1PVJoQNlHP/rRYXU6W3kcEDL2+fjHd01vH/RL3jfxjo24pIVVsVzhFjYpYkaPiQD5YuWhQqc5owaEWgrt8rBUYRdJ4pqrNLPxZbL+tHfyy+mrTPy8f3G+Ynbz+HFOmryquj1Xbb8yTNbR/S/WRIbxYCRzmvQN8InjvTloB/7Ak/R+brLlyGX8nIFoZgof/ejH7IEH3qclxHPWpc4aXSQ6GWd0LjOe0BqZA1RqBjEq7Gg6SCNTGnoLTZZv0CerqmKTYQSihkJkvmtrvabDVZ6zlXOQGgM6UwAaMCsS0NX/AHB1EYiM1AEgP69Wpw/qhwN8FoSNe0hUpWohW82FNWW2uFIqJiVofOZJT7rP/u7ZFqufVyBVDm0gIZ4CR1nVZoVU2qTJSYUt3YV28GKdHT5XLNvNXTa3KjqaO4QT4CTNs5d77PuvttnFK6X2vPSJH9pcGVQbOjVZ/IlUO3q0Ue/8VZnrK4ik0z45KJOEeVdDt82rvmovH9UBLd2ltrO+R/rQ3YNl7gnWMQqUtpC4Oth4PrmHx9HkIgLITjsUTO8GeQkDU05kIjryIn6n9J+vdBbpFEeZuBP8LxaafmBTpW1cVhImNHn52oCjqcMGmRFECv3U3g7pgitcaaFtW3bd3j07IB3zdlsyt8jmVkdLqPCatHH8HZycKM+HL2jZbmCdPbLjvtD2k/Yf2JT1DxLifTL7yFIzfeZUOga+u3bsCIOSg4fxpEe7ibd7BCZBEqVrfX19WBrvkErDWqk/HHv3mK1eszqA6HNSK6Gm1Em/OE9mHnFRu48ks8FjmvyJly/0E2pQV65cDmZaERTBtz7Z4uYd+04Y7JGyNTY2BgkzoNqBW3qRiIPaDisBjz76aAAIuV4xTE9zpj8DqljdZtKXi4lfNn7w3dnD9dDD79f3014bPY/X8X1x8biA8iPau8A5GUhiMb23RhLbM1J9YJJJ2H0yczhLY3U6iGasFbVh9EICt/KPiuhjEqCaVVTaAStpSP9ZrWlU2+8XL7q7ewJWwJ8VsONqI/MFjIuz9HNMMuAXk+4d6qdoG2DL6exyBqIpJDOur33ta6HCM8BSIX/plz5vDz74YKIXfZNrAQ3TZ7m5TJrB4br0fMfjDh98y9rPvailHuwkA4ZTsemk1NCQYNLg0h1loIFyBcwC1Gi8PKMK0dJbFoAvktduAUVUMOqq8rWZsMrmzyq02kryORQvnX6/AGxzV750f/vs3tXdVqQtgnUVUfh4fuZWS5ohUm+f7rX3yeb0B2UtBDWHx3Zq4DzfY3OqiuxTuyqtfr5O9iN/+odTNq1EkucN8/usrrTFXj41y546WGb31PdrQiFptwJAN2XQI4qjuHTEXtbgOcKfAF6HhZfFDdiqf6lsyKb1dR2V3hOsbuCNA0xFPJUkWd+0U3olf/98i4BysdQ2iqUv3Wt5/dLzrivTRsoq69DJ6k/va9dGnEL73ILiIIXjO+B84KDA7aLzxqkK27Tj45JWzAqdYDZAESInf+xdgSoGGMycTfWEg282HtUBwvN9ATLo+zJoojMa/6ZFxZGECekd+yWYEDCoogfpLqoqUX1xP9Qg0K3EcggSavI1WJc80C24UrZSbaKm7ABmBnLADYM534mJQ6fKRxnhy+HDR9TXzg3qMkiwR3Lw8C0Bpvrl9YMCjjgvR4r7XnxHfWDSgbWUT33qU1MOqPjeE5lcUg86tBm1Uwe7UJfj7Rh6CwQi0REm3NNPP2NXpQrk6Xg9S/++AG5WqColtZ43f57KzkZwQPWtdbR3B9G02ZKS4jAp5zA2dNZZ7WpW26a90FZYqaL9oB5ZKeFbkeJkc/Dn0KHDYXIBfiTedG8fOQPRSFOefPJJ+853vmPbt2+3xYsW24svvWhf/cpfBD29+vr6bHxL/KeIAzRSBr1cVUIau8+UuR+Lo0G99vR3bVn5RZtbiWmfSAWBSVYgITLcDwODhNHLwTBKKIBKRQYDkrKMcIRrWWGvnWmTVY68Xltc3SOzbddt03JZEUmhRdIDUpJfjxvSlRRaar721uliu2NBi925rEdS6etWow2NUZwQLWw2rJZZu5+5t1pS2DwrFSjWgpZsLhfI/F6+NqZInUTWQ4o0OxC7B/NJeg780ZVeNDvfPiAgvftYgX3/QJUkvB22Y0mX6AnEy/wciQYVEhKHJzyT59QzpQCc8xzKgv61SsSExOMF6TDx1FnR1xIf1xs2S3Kc7ZBfeKE/mPDr75P1kb5Su3BNcTU5mCtjOu+clj55mSyQHOixY+c6dZhNWVBl6eoRuBbZePmgBb/J6uHzBdZRdpc9KDvHM0GK4Hy4VVeA2NPPPGMNDQ2DG5tuVV7S06WutWvl6ey5s9rvcjoAmTvuuCOA6HhYNqe6NBXwwMQ3SKioEHKhvuqea9zRL7FieWLvvmCdor6ejenzw4Ac6n088E26J102CWJdAIBAnpE+s5w8Z+48rcS1hj4QlRXKigR6584dYYJB+PQJRjzb0MZKxGUB8Qfe94B4VjbYn8bDJfdDHKB9PKP2saIB/f+lQy+myV2XgC6S09M6CZE9YctULwB/cUe/DKCkDgGCqVPgpXRzsddl8SnuaB+A0HekfkW9WSw1EFY54gA9Hv5m3IMp+A7UZcpBfd8mvFepvQObNt0RVlhoB6is0AdgrW37ndvtmg66ydcYyb4CVFmyOSapp06f0gE4W8MKOqvo6f1Gtri3yj9nIJpZU2Njo23dusX+4A/+IDDqJz/5if23//7fg1oBnc50Z8at+ghTlW5LS6s697ZQ6XPJeyo6gya6jqO5V159xa5e3G0f3SHbkRpDA/RLA81Yc6BRBuCsKy48BzAY4NlgMkiduySFPtdWbAsrWqWEoBWPsnabE461xgIGy3Cy3yw9XlwEKCP6TgRVDXR9f3SwSmlet3tW9EgafT1sViT5AGBTaS+pK7YHN2uZTwAa6xS4Dh0v3t6TZ1UVQ36ed+Liok4mApc8MyGo1taAD6zrswU11+yb++bZeUkjPnpHbzim/HhLmc0q7ZUlDzpXdbvKF7QoL/nFwYlwTaURgWRUXyJ/mTtRvEhvmnAev0P2mk91lNuq2o5A48E7ho5NXSJdcyTNy6Wq8b9/stb+6qlWu9Dcbx+RlL2zo8s+sLXcvre7z/af6LF71pfJLF5FSC/+vTyP2IU+cqnSlm28Oyzh0QG6tCVkPPlzAweOSIpJe3r88cfD4DgdJE3xTLZI9/ell182LBzQ5lE3YRCP57NHS7ZnJVFmyfasTkMslUSKsJx4ybiADvAFLc8ijYs7ACi7+lsaWsJy9ys6RGOWrIhs3LghSGlvVd3BUgM/d64OhyoKv3SH5JHfaA5AiE71/AXzAx/RF81lvzxa+jPtPX0MJhzRhf7Zn/3ZaPVsGkhi43xkL8BrUs9AYky72LZt+w357Bc4pgzseWAlokcTR1ZsTmtiipCJ9s9BL3lIMGIOMIqlnnpNLpHG7355d1i1Wb9+XQDTt0pPOK5eQR4cB9Ce+aW7GpmppbyjOdrC2wfelknO8jCZhtZMaB9DPcVoJRzlPRUI/R5O2/rHJ74rO9Hz7Sc/+TGyszAbmQnMGKWIM+51jZYW6ahz7ZBGj2U2zMaJl5/5niS9lyWFjmaudIw4B5tchfsCPAz3PPCsYJEqx9AzoBFAWSSwmJ8fzeprJS3l9D/iEgfbxq0C0lUyJcezA0ziRiA0zzq6ZF7qSLl19RbYQ2vbZEkmSsPBKk/EIysL67QUVyuJlMCs5xNLF9UyCQf94y1a6pVpuLnl0qUmDXlS1z0/0Ar5lv/lLu0wVpxNi7tlJ/uM/cPeOnvixX7bKYtmdVXSHRNd7De3SSpcUdgnaTubMKEHlUgSDV3oceWH8+fU4+BzSFfxa6UvXqJDZTzcJtmzxkG7okwn2C3SBiqVYUtDqTV8tiSY+aspH5AUpFibQfLtXz4uc2jajFgovRMmJc6nwW8pOqR94nKBtRRvt+1rtwUpAoNA4rJzgM1prNZt18ALCIsD0+yxbu4bpGGztYkIm7rsr+CXnk/ALqoZu3fvFkDo0a79O4Ikd77GAPQkkdTNksRqdrBJnarMqWLQVhhg0dNuWLEiHHLx+muvh8G4YUVDGFPob24VoM4Vtykne4VQX7nnnnsD8PBVvVylcbvRYfL1xhtv2JbNW4JqYnq9mw7lZRxk8ghA5n7psugE0fS8IZXdr4OUmFSysrFw0cKgZ//Gm29IGFMZThnNNqYCUplsYnkHsA7QZL9BvH3cKkCdXs6JPtM+sAt99N2jQZPBV4ImSu9mxssZiGZ28oCMYr/22mv25T/64wAkMHb+6U//girZ5HeB30ym3C5pMQCiY0QFzdZAx1tWaDFDpENzwJiJBp3GW3tesJ5Lz9ud90ZA0EEX4UUmQs7+IBSGH2AsvAv+w58j4CjwJ/lzeWGXDhDRQQeyvdzaXaTNhZ2yPIEEekAAtFtAT+oaOogFyS7+xCXJTsV58mCJndJBII/d0WpLZnFUSgRGPStco3wAnBUPRW5cKoMRiIzyWyTpQVlRr9KTVQqliZoJ0nEPztXTnlPKhsLwyhbWFthn7262Z7Xh8MeHSmzrwlZbs7jYTrQttpNt82zjrGNWX3VJgaMIxHNJtINn51f82dPjGr6PrhxtXiQe8I+SMEFIZcNKxa+F0pfGwbM22dnuH5CN6Ovip0Cz0wZMQ88nJYRPcSXwpUcHKx28VGsLGu4KS3wABOpK4jJzgPaDlK1bOpR333N34G3mkLfOl81vhw4ekjmryFYr35+l2Hg75h4dyYaGBoHkOvUzhUEKzbdn0GdZF1dRwbLskHmv9FIRHik3ghgm3wBvAHi+4iC5ZX8HYILlbaR3M0VKRTkpG8v3r8iCx+w5dZLILxhxSTudN+/FZ28frTq445FHHhlW56YDP/imAGJOUGScveeee8JYS72Mtw/ySlhUILBUhqMN4bd9+52hLoOdXOCQHpfw7seKCDTYXHlWtq0bGxt5HdSPqFNMRqHLhJa2MlMmnuSZ9vHqK5GFG/oMxg/4OhNcTkA0M8ami02hE/zsL37W9ryxx5qvNYdOFPuZyYz71lQFGh8NioadKxBNSejgmDWyZJttmYYB+K03nrK7669ZrVQllJVhbthz6sH9sl1D2oJuzV1RtZ0tKTR7l3qVnz7pOBcoosNDtUttqONo6qFkOeXweYHWE1cL7NH1rUE9g8NVCrTxzp2nHdKKP8jDO7N42IUV7XrMs0udxTqUpNCWCMwXp+ilRQ8SXvwA9TjUOx5e22V7T0nv7VyBnezcYlcLlofTBWcVXballZe1EfNG3oXI+pNO/4ZnhYEPV8WvsmJZ29BvqKQRFYAzJvwCyBYBpNbSlA561BwUU6YTDHEOpsND6s8gLcU721JgTf2r7H2SQlPffFCIh0/uhziAFJql/c1bNgeprb+hjjGo+BV/v/frRP2IN1ba9Bt79+zVioLso+twBAZwBrq4Iz8M1HODDnFVWHHkPf44pGMOdj3v6VfCeXiu0HMwzbjCZvVL6ms4PbBO0nqa80U9b5XOPUc1j7U8I4UjDyO95x0uW95Hi8v7E8dPSIp4yh56/4MB4CTtI7A06x/UHjhtcEVDtAGTgM7/+L3XndG+QXqcyX5T6uZ+baClTWB1A9CK4Ciejt+jN8yYSVtwP64OnseTd+IhpYXW4sWLgirIJVnh2nPhfGg3vHv7wIFg2QLzieOhnY2/Y+UVeZtIeqRLO8es3cMPPzzj2kdOQPSeN9+0P/3P/znMtn7602eDDU0kchgdu5fDVv7d/5UctkINu8mOAYnl11zPSGkoNOJsdOkwDu193fou7dWpXjIFlcNyB1AZDLWxuVA6l5KyzinpVuMdngoS5LKUXnRrb2EA3heuyqbtlQH7wNoOW6XDqZql16yueVK5i/CCJHSSeJdJBQO1iVapiSCNLhOIT42/IQ1OMGzXhsQ66T5TDly5NkLubOjTUeaF9q232yxfmwz7dUzzlf56qamckEm/ye3GJn9zyrAEwiAUkhz2p7O/QNL8EltQ3hFOTyzKjyYk56VD3SVz76vRo84UMUalX7azX2yssrpVD4Rd5GyY8o43Fiy5TXEAfh4/fjxIrpAspfPXn/1KNL/360T8xhKH78YO+5defCkMZhyo4EIQgF88fegxOV+xcuVgX8B7H0h5j/M46e/c38P7lTj0LfQxSLO7JMXDzm6jDl/AnB6WMTiuecfOuweFA04rPT2ecf7er3G/+H2m95Pxgza60E89/ZSOYK8zTpZEEjlTpGzk/2Y7+M1GOmwNY+YMXvk38Ct5ynQ/1X7UUb4nB79wveuuuwbBMfmk3jL+xfORySxf/L3f+zVetkx+vCcdB9PQp32cUJ+Cygg61gWawKIZ4Jv4MtHJtd9o+c6W3oB0xl+RKhibijkgCuHcTGof0U4pSj8Jh4kijkVl8+DWrZttx13b7M6779Hx39vC8gMzrsTdGg4gDYoPTrnIBfRonHzXeMNw2pcuNdlb+39qmxZetvKUXWh/N9nrdUmc55V3SV96IKhrXNQGw45e2W2NhAAZyZcLbF9pG7AXjpbbynkmAA2alCUOAd9igcZcuJL8PqmYyAKGBoCWrgJrll1mTHzGcSvvAfyu7uHpIk1vmD1gv3zHO9beetiuyeD/2WvFdrVn8u2G9Nk8GdkbHT7wkD6610skTef4cXdIpeeVdVpDTUcoD/a0h956qKHr8eYCnU64RFLV7aFeFGt5P3HZOYCUDSk0/SXqCzjalP98curPvB+Pn8fjios/Z/KL00aVgmXVSu2lQM0ECbTHiYeL+9HH8M77Aq7xNON5CBnSH8J7mEzxCOfpMahiixnLB91STwOkvP3OwXCimefDacXjpfv5c3oc9yeu33P19N1vJNrxuB6OeDiW3RuPNwr0R6uyiRQ6sCXrH6S7gEHsDQOscvEd4t/Q7/1KRvye60jpocJB3tgciAoHEmiPz5W66bR4hhaA0CcC1PVs9D0eV1z8Oe4HDX6khWMcBkjXNzQY1kIIe1yAGkk+6k+TTc/zkY0OefAw3GcL52G44vz5jDYjHz3WGE79pK1THg8TAk7zPzmRRK9fv95+/dd/PQwMzCR4pmNtkbL9iZMngsTlVvAB3TmWCZCkMHDV19cPfmDPDxWRnbPkN26aho0CLGneapMyns+JXtGJvqqDAmZryTXXnXdT0yV1IpVhoPX8saT17sH9lnfldVu1Hl1bl0x5COAYjciv+Pu9X9P9eGaJ2+xcR7GVF/XrqOz+oIJQX9NprdJ9buktsdn5MmY8jFYU75xUDfaeLrXVc7pt1TzlSXR6BwS89Sst6BXdaPncTcWFWGro6P9GjZl8RY1+yE9klCG3/hHFjfSP+6UGsaxaZuPUx3GYS1WxLJMoPlS4Q+0ENeshWtc1CdApgrJZXXD1onUWdNjl/iV2sq7KFpS1kXTKQWF8vOu5XmDXBOorpMpRmS/D+KJAvgM/9UReYSynGUaODlo69Bx7rqQudJZaW09BpKYyOOHwfEjHXOx89nC5rd72uKTQ84MUwTtRp5hch3Pg5ImTYbXuXg3C8Io6Fn2T1BcI38e/U+TnA2Y83Eh+nmI6bfzT/ZwmEiw2LWGWauu2baG/8HfEy5Ze1EYIEeU5nX6mZ6flcT1Menr+Hn/6r4ceeihIn+EbkjgP71fPQ/zKvafHvbt4nEx+/t6vhPF7v2bz8/SQVu5+5WXbsE6nEwa7t+UzSsrmfLmZ1zNnTtsJtZGPP/ZYAFTOy9F47u/9Sp49bjz/8ffuH/fze78Shnu+Jad9Aky3qX2AK/D3uuvXeDzS9zrsaXme0sP5e65OK5Of04unTThWhe7TiaeuugnAj9MZKT3ix9/zjIv7+b1f4+9H8/MyB6KxP+wJ2bt3r+ymLwubq2eaFJqi5AREMzv78z//n/bd7z6h4187bNnSZaGj6OzolP1Pdp6umpKThvhwXqFi32XwFnD81a9+RcdOrrYD0hP6vd/7vTDI+wcnLg3iH7/3j+FgiE984hOD9JhtvvTSS/bFL34x6BoNEp1hNzSoWm34YZKQa1daWnLDgNDW1moH9j1n9bUXrabcwRbXyMHzOHh0/9Tb2CNgEedXZrhmtaV90j0usBoBU31+beZjk6FUKbTdsFfgT9oUsqQxFO9cc5794J1qWyRd5ftW9ViFJOOoNrRJlaNF1icW6xS/uINm1PFE1+hdlAd/5+Hj4XhHvSoVuJ+njXoA6G6pSgiH6wX/dXqT8opqySzlXQuUTiZcW3T8eLFA7hceuWiX2y/bla4mmy8LICHYIAuimyjdKH4mfsb9UBupFIBGtzmy9DFILJSTCUie8j1LutDkf2giEU1aevoLw2mQgOqgdy56bLfEEf5okyYw+evsIa060QF6Bx4CJH9u4ABHR7MUvFiSIzbLpTv/tn7lvd/7dTx+Tp+4OO/70v3Zw4B0nDbNoSl8y7jztP3Ku/g9z9B2P67uF25SfzK9j/t5/uLxAczhEIee7rDi6X2Zh3Wg4nTcnyTdz6+T9UsVI9DlPp5WOm3yxebI5mtX7UMf+HAAhPA3cdk5wHj84x//JKi9LFm65IY6lYnfUMvkj18uvjs0ANDv6GhuBHPrtepepQlc3Hk6fuVd/N7zh1/6Ow/n1xAg9cfDx+On3zOeNjVdDGP8Ru1fII7T8rZBHNoRV37+Pp6Xifh5XomL87zF/bOlRxhs0DN5Z1LCJJmJidNyGtP9mhNkxcfBDBKSAXi5YMHC8EEZkDHOjwmYXDqOnn7hxReDuSA6fD7AYenKVUiHjiVSpM+NjcfDctDly1eUfnvY8U2F4gx3jt3EDui9MjXEMkhra4s2q1y0v/u7vwuV4L777guNBmk0klV+mG+iQ2Twu0cni7nt0FyWaypo8W0YdNIrdy7S4nvj4Cvp4A6+/ZZ1nH/ZVq/jdEKAXtS4/BpvUKl2lwoTD0tDBzQPB9wdfYU6VKVf+sey0yzd4nZJSGeXA/7yBaxLrLl/odXmn7alkgIDPpta+mULWvVSJxLuWtmp61AHViq03Sw1EM+XboKL8uQRimMuAABAAElEQVR5ia435tnLNJTPKEzUceo8PwF6maoT/WqpjKCu0SbwjE70LOk8x1UnUqna93Ss+IDifP79FTJ3N6A61xYONwk8SHV65A2+dHYPhENaiOt5CwUWrz0fEV2Z/BMjytkcmIrr/oSHVqWk+gGo68VQJzpUPjZOwqV26Xm3it/oc7NxknSwlf3WuQrbeNdjof3PRCnCED9uzt3RIzL5puN+79t1n/qgSO1l6BsOfc9c+3np/Bv7QEU6ANQ3Xn9Dup0VYRWRftTTj4fLFDfdj3Q8jt87LZ79nqu7uJ/HdT/CAKxOnDgRfuVl5UEF5pJWwa61aNOyNm0xGUEFgJVDQA5x6dfjeYvT83u/kobf+3U0P97j4mnw7PG5IlxivFm+pCFsgmTMmEm6npTnZjtUEI5p7P61L34hTDpIP87TTPWDMCN9h/Q4Tm802h6O74i0tE/1kE22qK/GHeFwU5EHT8dp+zNXz19HR1tQ3UANgo3+1DEmxYBT+mTHX36aIBt32W+Ac96EhwzPHsbLGA+X7ufv/JpO22n5e1bJsW6CxJw2PFP3CuQERPOh/pd/9s/s0Q9/OHRkbJZxaQEf1O+deZO9fvPb37TvfEun4C1bEk5J/Ne/+a/seUmN0ef7zX/1m/bEE/8ovaU99hu/8aUAlvmY6GliUeIPZX4Pe6Xs+H7xhRfsD//wj2QDt8+e+N4Tdo/0uDGt9NwLz9n73/f+kE3A4ZM6NOYrf/lVW7J4if3DPzyh2dM5+8Vf/MVB4DjZ8kxlfAAumw5w2KJ1sJuLNOErPGUAQ+2FAWzPi1+35RXaSS87w2qioaEPSTejRpsuiQYcKptq0HRGADh+3jHpVve9MgxwrLXGVlRf0+Y9bdyQuHlOWY9dEXjefeluO9kyTyoahXb//BZbntctNQqzp47O1omC3faZ7V2yd+x0SUvHGAuwogsMbfrA4YA96qA83/HOgPuo83B6UT7JpTvoFUuveI4AZ1Q21CY44ltL0lKJIH0k1E7/0Jle+8ZLCtNz1dYuLgiS4W+91GWnL/fYz91fax/ZVmQHz/bbm4fbrfFir92zoVp+2sAiGlH/HUkWSJ/0hpwOlRH45XTFeeXoxnneo3g8c9S5R6Jc+Pn3gTaWRDpE43jbLJtdIrN3Qf1FL/SNjjXJLnTJXbZr/WZJoGVTOrELPcT6DHdh1ev7/2hr16wNA1t8EMp0n2u/eJac9tAmwkrptG8Z3ERIWA/j8fzZr/Ew7udXj+PXuH/8Pv19/J3f04fRt/TqtMyerk7pQl8JpycCSjHBh4UTgMHLOhSmX2pRa9euCWQ9fvqVl7nw87zH6fk99LHpy5i0/r714mv5DdL9ePzkXodYyeLFc889p71U28MkyL+R8zR+Tb93/o01zljDkac3ZTihW5JodNodfGZK32n6NR5mMn5etkxX6DL+Iimn6wfoIzjcL0sX5ZLqclgSYJqxn5V1dMwROnp+/BrPazydTO9z5QcuAW9xoAx8TV/9iudjOt9H4sNJ5tBBKjOJ7//g+/YXf/EXQXrwn//0T+2ZZ57OqU40A9FBbSppWFFvv/pPftU+//lfslrp++6SfiFmkJjJ7tu3xz74wUfD0nJ/asdZjzpgAOT7HrjfvviFL9rjP/e4lmcOBn1o8s+BB7/9279tf/RHf6RjWS/bXpmvITyz0L/6+l8FA+m/9mv/1HbtuleHyDwp/45Jcu3mRKcMbF7il0sA7blHGs0Ahntt98vWdPIt27p8QLvnhwA0oCwCxhFAC4FjfwBrkaMbiKScDuY8HiB4w6zLweZxc2eBlWsjH3rEFXldVl1wToASixjaKCd94k7ZLH7pWImO9R6wn9uqo7UHV1CjhKCNFLVJm//QGT7XXhrsPKcyMXgZyjfxIqAa96MzSc8n791PyYSO7VRbmSTSvVYttYqTbRV2sYvDI4bA6lKdFtgwp0cWOspD2n/1tCYCC/LsA5tL7Gs/vmTPHOi1s5e67atP9oqv+bZ6gSYCgzwbAuPkkRTJgwN/JM3VOsSFg2ucz7w7rTztbZpney8vsPOdssQhKyf4D8WNEuC5XAfXNFQ3h82G+qp2TWowzZ0C0c2zbNWGe1O7xCumpH4NfowZfkNd2SdpFv3JPffec8tLQ36QVmHXHx1o3/R2yzOWIQNMzubpyO05sm5RoxVPVhqRNLMKOX/h/ACoe3t7grBm06aNUt9blYHKzfXycQpJORaS2DsyFf3vzS3V1KXGRAm76exdukcbWqcDrwDQqDixEr3z7ruHAeip48T4KQNAAccLFy22Mk0sT58+FVbKN6otrFixIpwmyuo94/RWHaftm5nHn1LuYtD/wNuCgsLQlsGO0+GbT6SEOQHRJAxI/Z6kuf/wne8Oqjo0aofoV77y1dDJTSRzmeIg1f6Zxz4uhucJrP+5jqR9waggi5YsVSWvsm9+85sCAgN23333BlCQz1q6HB8IaQaS0yeeeMJeffU1Af2+0EDQ46TjZVmBTq+oSKoBOuudwwFo1Fe0MQ/zSt/+9reDFJowETwKpKf9H8pHpWXGmmvHEhLf5NzFc/bK09+yrYuvSG85kraSFiAMR/r83EXP+EfvhsJEIeLx0C/ulCqEoKFVFQpIygb7xc4SWa8oEqgcsFU15wXwmiQ17ZaqQb+91phvZ5rz7f2rWq22YuiAEE8L2nNKe4J+Neoh82XtA8DLZsNuscjTjufJ48b9uPew8fK5H1d+tZJIU1/yZMpnVpEkBpjtCPA6iq9DA21xXaE1LJDKhHSjmzU/K1UhqyqKpFdeYo3noiXqjcvM/tePVlvD/Eg9x/np6WXKI3awS2RqDxfnebH49sql+2zf1e12uGWl1DV0lDMEYuHCg/7QnirE1z4dt36xs8y6dbz3iWZZDynYZIuXr09Z5EhOJ3R+ZbqiarBHIBq7+dlsq2eKN1V+QQda+0Sq1edtk+SPdjwTXLdOROxoj84lQL0OIUlkgi8vXGfJdvR0GIyRsJ3WBjnGFUDLTOHvraoD2E3fJ8EVq9iZ9grc7Hwx2T2oVY5wAqckpYC86ep87KGfBvCDWehv3tWphs1aCQHXFAj/cJ0uaqj0P+8IRK9btzYIYWbyKmYOQXSPJATnNfNpsA996ENBCnz//fcHMMqSYa4cEoeTsiG5675d9slP/oKOv2zUMt5L4UNwKhDHjq9ZsyYMVFQul0SzzP36G69r9vOOffjDj9pdOi2osFDoRRUPcIluDgD7uIB/d3eXLdDMbkBgh85vvnS8se/5sY991NbIbumaNavHvHSNROKUlvWwbzrSj/RbWlpzxaZhdGhcdFIs+eTawWNm7K+9+Kz1te2xbUvRj85tKhz60SJ9XKSpQGlO2eMgFfSNTfiwtqjF1lQf1LOMzp+dZXvOVNodi3pseZ3CI9xOc2BYdHwLrktCK9zIPItydOqkvjbpXasEaTFGfoTGSI5TEwG616QXjXoEAJ5vcqW7WJv12OxB7IhIe7eAtzpC9J67eyUBnp9nKxdiJ1U2pUtle7pkbHkj/IBUSK5potGjUxrjjrJWSjo9r/KqJPDF4t9V8U4nW8YD3XAvlRrlFb3u2uJua7xcZXMWbwsWB+iYXfJ9Q7TEIwxsSNkY4Di+91bzqr+/L6zCFUnCy0ER02VgHa2q0GYKZR+a0w/nyPxZQ0NDyHtN9fQAzp5/zEm+8sorQSCzCOmgltWnA7D3/E23K/0Rqi+tGv/YGDcd3NGjR8Nq81qBvHQd6OmQv2x5oG8B8DNRr6+vl1GB2aGNFJeUaoSJxphscW+WP3ahUdupFKgHs6HGMZPbR050omE+u47ZTfvd73zbfvd3f88qq8vt8MHDmoXXDi735+IjoWMNGGQT4CKd2APQXbdufQDtzGLZFIOOHNJRfixhMEjUahmQTYddHe329a9/XcCZ42M7dVb7u1ZZUaVNK6fsj//4P9pFnby4VQPd1u1bUuaequ2Xf+mX7Wtf+5r92f/8H9bW0maf+/znA+2xlIdKXapOVCPniMEZHDhAYCocFZRGNRUVlfKxAfP4oVdtx7JmSU5VArVVQBwlFnYMoJpnHGzQWBjAbfAiHCAWYamzKObHOw4AqZUqRL7swh1vrbK5pe3BzB1wF3pYjlhacd4aW+fb/mMF9khDi0C0zLaJndCFRsgTGRBt6FxpL7YiWdEokSTa81aap02AxbITqkBdAtSlmIRLxZfmSADbkPB7v5JtpwH9G8pDpJBPAWmB2l5JdJdURSbwiKgowbV09Os48BKrKi+yuTWFVi+J8zP7Oq1E+vw9fVgWkbUP5cPzRJrZ+Bmx8nqQQjOpCTyHz6nESqQLvbis0epK5krP/LzAvQjLZfsOzCuCFZTKfjt7WYchdGyze5euCQAhscgRWJf1D5IhJtArBfpoh4CGW+noBxB2kJeZAKDhF0eLt0sCjY4xAy/CjqamSxoLOm3R1kWhP2YwZvVwMo6JDkIVJGMTmewQ58jho3bo3bftZz/6iaDGMZOlbJPh5VjjIvVlAybjOVLoW90+yPdcqQ+BF5DeTqQejLXsuQhH/sA6TRcvKM/LQr45tXDfvv1abe8JB5iU68CGkuLJrzaxmk//MdE+n7yeOnkq9Icf1h46VFEQVE53Ho/0nXIGopHqPvaxx6SXfNb+/u//P0k+24I5ol/7tS8aZ6HnyqFD87nPfU4nId4bNsxhl5pNbTg+xBadsLVu7bpwT2f7O7/zO+GezpHO7D/+pz9R53vRli5bGqTkNJIPSnL+6c/8gmG/FUiDnWvA+iMPfzBUlgcffDDMkBsbG0NaGP4f60encsftT2fjAxMD9Jn6p0DlgrxS6ZHk5NrB1+OyC23X9tuKJdrNJ3zgII+0XBKsLAw6QB0ueKX8h419MT/wxoDOpdbnCLSXV7TI/FuRXeiustXS080XgMZVSs1jReGbNndlnkzZ5Un1IAIqg3RF09Ojk15U3ilwLh1g8qsfeYqO69ZhKZIYoz5SXiG1lBTETWkFhbT8vlBgHFo+UQgvY3kPz/qjibeAu/S1Jf1VdQhm+eDHPG2MJG2x0BbX5tvuQ53WdWeZfXhHhX3j2VZr7xqw92+psLtWFNi+4/m2fL5MClIO518qrUz8DKCZNGX+L56vgtQHwazd+orjKvdxAW2VQ2yErtOOx8GPfKIPTWGfPFJlyzbtDJPXyCJPKiNRSsnfGAeoH1iWYCXo4Ycfjr2Z+ttIcqupZqrd0w/QXhkE6cPIG36hDquS5quScs9vKibckykxOp/oktOP0WdzpDErYNQ/JL3k+c4775x0vs+fP2/82OzkKhjwb6z8wOLAk089ZSuXr7HFSxZLuJRIoUf77ui483tMdqFv1oSDeh9vF+TR2wL3ixYtDO/x44fQjfaBIx74gDo3HRx54WRPJutFRYVhEyE63PQ5TCxpL+SVCcpkJpm0AY46nyV1Vt93gB+TzvG0j30yHwxmY18D+QMjzWSXs9zDyCvabblJyzFIN/iAS9SJVFVVh02GE525ZGKuVxoqjrsXX3zJ/vpv/kYD1UNhGQ1/Kr+n6x9qmWZq/HDz5uns55TzzXf+zJV03LG7ld9MdTR8lswYjCIdwtyU5FrzVTt6+CVbWiMrHfky7jYg03YpkAcwQ+oLoEWHHYdaA+Az+AEI9Y369b5QGxG58gxapn8CHGpotws9Wr7FMoSkpUh/KUtdcVswoQcA7RVNDHtsXBSpkvTqGGqALWkoqJVoU2KvwuFXrBof0hQklFxX9zyHJHVDDi2oiVQobeJiVQPsGB03HoUlb55v8ug0Ism00lL6QQqucDgHpqFMYkqLJgEVOkWReJTvivSRP3xvnb1vc7ck+dJhFi/uXltqHTrIZKGsCMKbnXq+e514JNq4wTzE+QnflecAhlV1kXoTsDJlZg8ePLW3Xebx8mzXhrJw7dYmzK4eSayD9RIFT8UP9ENKqbREG7+jVwrtYu9Ke0CmK+kAaSNIB5EoeFtLRUsu4gCTYw4wqa+vD4DPB+6pYg71En1IJvxckT6tW78ufBvMfrK/gwGVDUd8P/oEgDVhfcNRq+4XS/BBGAbH6QAWyAcb9MgLP+ob4AAX52n8frw8hi7HTZ89ezZIIumzUMXDehP7YFauXBl4lo0uvOcwDnj8/gffH0A4K7T4Jy4zB8ANL8tqBII2xib/vplD58aXiQ7tI1it0qdZpXMsqFunT50OdouxcMEkzVc8sArTfK05fHuwDf3drJpZtumOTQEAkudb7Zjw0Z5xtIH05yh/0YR5IvmlDqPueko8uqqVZwSDpHP0yNFwNkiZ0l6Z0v8fqb6fPn06WOTgSHJwiE9Uo/zNzL85A9GI+X/4ox/ZX/7lXwadYtiB390yG/flL395ypcNl0qV5Itf+EKQIntlmpmfZGpyTcWmk8rlTJ/G+O4RLRldesk213drAx1m3NQryZ9uJeBP3eOF5BMXvU75BR8ANlEA0PIIh3mEF5AJQHdeaUfQJT5yucgOvNtiTVdk8H5JkZWvKrP9jT329qkuvTe7c1WpbVpeYmcu99srkuq2dUmPVw19xfxiO3tVtpulY7xrY7ktnFuqU/wKdRqgNhQCPHFp/SDzJ9K/JoCLWbpKSXQB1QUhkylpHfklqsKFCYPuo0lC5Bde4kc5FI8yqpTBPF+vrILoTnrZAzo4JjrwpWyWNoAK+LfKvrQEWNavQuXnC0nLkQa0XSoc5TfiI3RDORTGJwK8L5E6CnrM0QTmul1qGbAfvt4lwJwvXetiO3el39460RnibF9Zqm+oAT8klqIjGqQb0lTZO6Vbvbux3Dbu+LnBzT8u2SRa4m7kAGoHDNY7du4IEw7aYVTXo8rj936Fgt9zxcXjjObH9wAYAxQAfY3HGu2MBq5iDbKXLjUFPWIAM6bhFi5cMGhiqkqg9KBUTrB4AWBFJ5RVPu8vRssD+Yznm/Bj8SPMaLSh6+X2NIjHIO7p+NXf+5Vwfs8Vly093qF+iDmzIkkC9uzbK4n9kjD5YQICgGpoaBiMn06rva09WHVas3qN1c2pE0hI7ELDo2yO73H0KHbTz9rHP/7xwbpGeP9G8fuxfuNM4eJ0AIMcxMYkkf1aGA3IVydHu1koCTTCgANvHwjtgJX1BQvmhw2Pr776agDWgGv2OCCMc8tUcfqZ0h+rXzqd0epset2OP2eKC/14mPGkx8S1uqY6tBGEkvv276MRBqk0k0/6GiYWAGNPI54eAgUOrAGA83MhDGFmsssZiIZxjz76aGAoG1ew14ldQuwx07FPtWMmy88r61SnN9PowxcqLRMbXFzKPtGyoI+45/kf2aLSi1ar0wkBhM065hq1CE7IA8ghnQXgASRxjK1Uh0E/+Qc/JKAESIVjvAO8dWN6Td49IvSV71+xOVWytVxRZ0+80SZQ2G7ff73ddqwptXMCyV97qtX+zaeL7cDJXvvrn3bZ4/cU26FTPfa916/bJ+4usMNnemT+Lt9+5ZHiYGOadEM6upK/FP4nF8EBjMsLotMFORkxXx50DsQJjnjxssiTvMbLDEbnh0oK6SH9rhYgxyb2+Y4Km1/WHvzZZIjuN7yBf53aSFkls3gQJB+4kC7PpO9X+CTAH/Lhfqkrmy+Liaz/RIHnpdqYWCap8wnZm/7Kj6/ZvetLrb3zuv3V0632pY8X2vJ5svyR+lhh0iDaofmK5pGLsjldut0elpkkl0CTL9fzZXmdfiAXdQu6M92xQRkp2/L65aml1CEAPZYBzvsyH5D8Cl/83q/uh2Sv5RqS5MVhuZRvQ5tn4zLSNpZQmUwD7LEhy3ueGeDOaUmdDdXNkjQBMlyqSz48Hb96evF38XvC4eJ+meKMxy+dXpx2btKTCpeAMntY2rQ0zpHEWA9gGR8LUKy0NjQ0kI0bHOkfP3E8gLIPSG2nRBu5ktMJb2DTMA/qJSZwl8qyVqax27/vsEgTfIAWjit2k2sEBlFpQsUBNQgO78GSFwCZcZL6jwWJsvKysGI9d97c0FbmzpkbTjfmWHLHNVORz5GKOVJ66e/8mSvO269fx+NH3w5vysUTJulXZI96544dmjDOCXSPHTsW1FGvx/YTeDpcL168GPi6XdaAoIMk2vMVMjdD/+QMRDNwol6B9ANHBYPRX//6X9uVq1eCsvtU8uh2+BhTyR9oM8AyeDJ7zoVKBzZmWy6+bA9t6g2SYpBanlQ1egCfqlmAMIBbajwNxeMePwfLeAY/2jjx9Q7Qpv5MYDTP2vqLdJR3v12+KonzsWb7/V+Zb3WzC+2t40X2g5c7rUwbjn7poWo739xvX/7GZXvz3S4rL8mzVYvMHtlaIQmw2YmmLvv5XXPtm7o/fRVQK502JUe/Qtqez5AX/QnZU95xxQqrIHapq9jKtbmx4nqkhoGnx4NGqo+KypIqXwDlEBEtykV4wpUXSBda9x19kjwLDRdIqaOmsNv68gpVbrUbSamliBKZplM40sdBg3jhmvLkHlPo8MsnAgDs9gFtxJI97dklPQGcE6+6LN8WzpaZwNJ8e/1ol4D6dfvFB6vtavuA/advXrb9J7psxYJKshsmAiHPqUlCa7eWqpsqrOGO+yWNqAkDCkvctHvaHoCLwYjnBESHzxVs1iP1+sDDDw1b9mVAcef3fsXf7/06Hr9AV98faTLfhX4Y1boIEOfJL1/fh1qnDbS6Jxw/XIEqkd8Hj9Qfz0f6ldcj+Y323uOOJxxhcZnixv0zvR/NT1QDXT4PXygy+QjPxFC5vBSvfHKBn9NkAskZBQAzrDlgISFpB3Aos4NvSHORYH7wCx8MUuhMfCW289ivk/Xje0Z9dvRtw8nE2rgdVkz15cP31ifnGtqRXpB2eFYbCe9jxfJ8pV8nm0+nNxY65MnDx/Pnfn4dCy0vmsfxq9Pl6v0EbSI84wdvUn2Jx/H06If43rQLpNBItZ2GpzdTr1HvmYPc04n83//1v2rD3z06EWerNnlst9/6rd9SJ96nk3OiQyRykExCYhIcYAmGCsyMcrKOo9J3P/sDW1l70eZqA57aUABfNdrgV1OslQgHe1yjMSgkyT2gD6CHd9SZRaAN9Q+AJgNYq8CzugWBy16BPp262KZTEWsrbM7sUltc3W07G4AB2pWshltRVmA1FQVWLeTeK4kv7bhSqiXlAovoJs+WveWSYnkqcdJs6iy0sx3MgqO0CA/IDACVPOmnRyuQLnK4ikZNaZ+VWFQuvYryr/jQALxSDn7c46dsBIeEuP06O/2lHyuLHyfayu1af7Fd7im2pZUtlq/OhTJzDHlFHpMRheN4cPEwmPSLsh1UYyAIXWi5415BguOaEiJbmfKKzWwc5cIR1qP2SLe6uqzYqsW3KoHr6go2oCkQZQA4EzBVBi6nruh0wuK7bO36bUGKwDI/y55MlLFoA2BgzwB1K96BKup70nXICtDzz78QNl/Ok4lMdz5wMPD4oJTNz8N4uPhzJj/oFOo71OhgD8AJ0rQ9Om3tsiRvHP2LOge/I9Jj7OrtCkdROx3yx54EgCN+nif8PYz78Rz382f3iz9n8stGx9PyONnCxenH47h/ul82OvFw3NM6oMEmMtQ6qOMc7AUf+aEz7nU7nhb02Yx4TmoJ9fX1AgqVQVoX0Uz+ZuJAT093WKnefMfmMPEAQMNTXLbv5Tz3cPHnTH7Z6DAGIo1G9/2g1AtQXaKN9vb2SbXkfGg7ly5eCsImaDht8ob5UfKKGUN3no9s6RHOw3CfLZyH8fTiz5n84nSolx6Ge6+nuUwPWqTBqhX9PP09B6Y0SYp/4tTJMC74xDGed/KJ2gx23VGhYS9DLjAI+ZkOLmeS6EKhlWWyeIEONJ0PjEMPb9euXUG3bjoU9r2eByo234ZlNCq7b7YcL1/oRF7b/ZJ1XPipbb/HdZpT0lD1Lag+dF8v1KmCkYQacBZAmRKi79EG4iBtps9UNQngDbBLOBwKFK1dMjFXJjSnMOhTr1xQLBvJXdJ17pLKQYl9+8UuW1hnUt3osTclVW1q6ZM1i35bNqfQTjZxmqEOl0khWU42RJ/Y81AnQJwvaZznS+SDdDc8R1kI4LtXm+7EpgAqtWVSmY3Kxul+ZZIYA/JDXMWJun/xQDcA2a5+5V+WQ1DbuKwDSspkiQOTecsrO6xdx3DrhWj0mQwGBdvUNdZrA/JD3aSjT1JvqWKUlETqHfCIjZOkNcg70lRa6tMjHlKGlF+YDChCrdRBvGz40bGygRA+rV1UZC+9c81eP9JlrZ39dulary2pqwjhIUQ8HGm0SQr9bnOtLV11Z5BAs+RNXYIeUhyWuufKbi9+gGqesZow0foVpTxz/8IXTkNFMr9zx52hID6opV95mckvLpVzTng4f47H9ft8Vdily+utRwMWYBmLP2tk+pMJT2dnV9BBVYq2edPmMJAxmNEXcEXthGu1QHhDfX3wj6fp934lzYnm0/PLFec0/ZrNbyrTgy+cLMhxyUjOOBgHNZi29rYwCUHlwJ3nkzrPCt+ePW/qPIEFQT2gsnL6Hszh+b+VV74hm23bpEOOLjS8hI/u/Bs7j/F3Pw/j/Y8/c0338/h+JQx0AH98S6zmoKqD7XZW1RoE8ADWfPsNG9bbAk08I/WFqL/D5B2rcPhxTz+Ic/rpV955vv3daH68x6WXJZPf/8/eewDHlZ13vh/QQDeARgYJMBNgJoccpiE5SZqgGY2iR8G2gi157Vqvy/JWPe++57Vf2Pck19qW63ldW7veqvWzpV1nu1YOI43CeKTJMxwOhzknMIMkiJy7kd7/d24f9EWzkUiQQ4I4JPp2n3vuSfeE//nO/3yfj5OrD5955bnx8sB9nH8u+BV8ZvNjMQ4gZpxHp/cRqdI7deqk29kGIDPOhJ/jO/W5d88eB56hk1FvfgEQTu9e/T5tIJrGWCxNHDRIVNAhtp91d2cNsL3LZMmWCo18qg6u2KFdL9l26YUul5Q4AG101gAsEyP8YSSj3AO8qp+POBeeXyE/nkVSC2fYWREskOWl4XxxrFBfN2DlRbn2zOaYvXu8y+qv6aR+acQ+sTkusJtj//BOj3DfoH1ofVyHCCUdFfh9QAcMAYxLqqO2ZonyonIuEA0EE+DkRzG79H0WfD69JBe1yZn5djWleHIJpP9UnX9uQGJ0Fg8cQszR/V4tIvK1HMhTOvMLOx24dnWg54rzJM0gCqUhBrKsMKKjQ2aYpU2DNOYX9bg6wIKigliMgHI8n/o6QunweeDq61PBnDXHIpn8LlR+/DOA8TklOXby0qCt3xK3pzYWu7rLF7jfokOaqxdqqZBaeHggze5AY1fEmm2tPbZik2szLMRwtB0mJP5wDOYMjn4gdZ734QcH9w7IOuFWGXQqr9RKL4vz/c5PhD4I/uFJEf+p+iHp2SAJHxJV3oWfsDAShfEnKB1R0aBwcKJx0Ltqa2vd9/z8MiuRARPc7cynL5dLKPXxQaZHvbP4e2D9eldnLC6QPgMCwvUYrhfyy4G0S5ca7EOPPzbjpGzhdzNd31lkH5EE0xtF8/GG2324bfjv/urDc8UPN5V+xLskbfoC75g/HMCa8wE4P8bBkfYO4IwjTU9b9en6vPmrDxcu01T8CIubbPl8PjKvPj/+6uPMzJdLbBLpUR8AaQQk1Bv8ZuoRFccIUnE+D+6HPq5dvWYnROVALTH9C+wxk9y0gWheUkdnm/3TC//gKANULo7BGQ7u/SqVuhsbCxMnE6vvoFPJI6vaY/t221Dnftu4LG2oxAE8QJ4iAwg78Jb6jWdqrFMHEzhVGMJ5oObwnzwAloPSJgEvGAALJUH0YMU37KS161aU2wNLepwKuaoSTGLrkODTJXa9PQhfUSFwJ+kvYLBunrRqiI6xcVnMVi0C9A3btpUxB0pbkzErFHAtQYeyy4guupIv7/hNfoIhWr6pcF4i3SeA66TNwiLRIWnuUAE7xXEuz0tanqTAXJEe87w0dAeHDfWDOInreqLA6XBmgZAroI2lxD5JqOdLYwjPg2XhYRcon9F8tg+DPKYedwuWcF5dnXIzlQaqBR2zGr/AW0ZpcuzpB+O2qa7A5pbn2c8/WSIJdFB3c8sj4nwHpSUtHO8gIdrHPlmBnLPsYUnaAvWI4XbDQMqgiVSHwZFJyOslZdsPqc395OgfbA8DvB5Yv87VTbj8foLxV+5l+34rfsQJvzkSGT1Z0eenOoFly0c4z9nuT7ffnUqPdGjbgCzvmLfCc5cvm78ikXtL1teqqiqdWkCER37R4uOYvaZrgP5x7tw5p1Jxh3QZ+7ry9Zl55cmp+k30DPd5zx4o8xuXzS+4M/rT5yfs6/38lXv+u79Ol99Y8eCf6Xza/sp9/91fJ/IL3+d9+Xrj+fAihHCZjl2a997b5RbrLEKYD/w7zwx7r/6eNhDNhHno4BF7f/ce2/3eL48MPNA5/lAGTlCXNOvujhpgkoDSwUTvO8Rkc8ZBqUMHX7dN867JeMjopzQuOQf40hrfrgsElos6Uahf3vkw/HZgTYAtkLOKFyzrgYBAng8EopJsph7MlzXBuZKiRmSmGoltXAfmMLQCkOZPqvDtUk+pVNL1W21xtwPQPBoRmIwWSrqnRNC/jMuT2jhoFvxyQDmVprupD/KIP/kYcaHvYEw4cRENKOc6ZV61pN0KBPir8kXOSMWrEO5RH084TvyKYwF4JVCXqB+9AuVdg3EbhBcNoUXpVcm8NmbCiYrkfd35Ognn3adDfDxbpsOLoSybTMtY3mDSisV/TuQWWJfi7JO0fPH8hLjeqveUo955HgevvbEnT/W6yD71wGa3uxQGGEEo6mJYW3RxSanTAIL2xWS5Zs0aH+y+uCJl44AZW5vFxYEe4/ui4PdpITHQderMafvCz37B9Y+pjqf3W7UxLsCjrRb9q1oaL2bdzK4B6DFHjp2w53/qU06gyiI+LISZCaWfNhDN4IFlP/gurE6oKEAaHBivFH8mVNhMKAOgh8me9zSVQX9A3Iozxw5YTsseq1sr6aoAlweaAGJAnr/mSqMGVgSRJoPJdNs5vnugxncA9NU+7VYU9LuDez6+pDRVtPTK/LW4xEh/OXAXE8CEQ5wQkO4TwovkyLALkchhAnxJYVvwY4xP8jAgsAp8BnQOKrPQL3yePRCVsGQEsHqgitEVONB8XtehwEJxlkvFOV5W1CTht2TJKjwGWTId5fHx6tGReijUoiAp899J6afrkxS6QNLm5REd0JMkHkjLcy4+RdktDjZGYlAh6OOjrt2fwhK/XqX6G/WZY63SbV2M9BouuH7HJc3ulbrpXBnDKZV2EaTwOYooZt062Kg8qRIVnXPUpyuFPpK695NjBdLI8akRfmA2KQJ+TIj092BrT+WRxOF+A9D0KxYO6AsGRNO/Zt3MrQEER2+/85atlLEOLLD5uW/mlvjWS8YBzMuXLxsmn6PTYIb61nM0G8PtqgF2afbu3StjNnWOAsKcMBPHxGkB0Yjs2cJkAoG+8aBMb7MFhmUf7KRz+Aji/qy7O2qABQ6UjqmuCNt1oODY4bdtWdV1aXRISYlBXAJeo8CdvPiNPmQAXvegDhkC3ATPCA5Qw39I3Ez8AMo5Auiox+M+H2jCKI8OO+4yYXslrQVUxgR6FxZ1Ogk18XjHV34D0JuSlTpU1+J++/tcieN4xxJrS8oMoBKpjDXb6tKr7pAg6ZJnroBTgDXlGtYPctWSiFmJjKJwONBRNeSPdDuqRBtlgbBEVgELdVgx7PyvcN1wv1vaOa70zZGGELjEg7as+LKAboeTnl9PyIiMtGrE0azh8qHDhqq/PB1ClI0Ulz/i0C333dej0+Sh+oGqMiDVgHlDCbcbQDhcKWr1IlpqaDFA2QqUbpE0mLhyBkHcOyGvOPJ+VtYJmwdX2JObNjpQPN6CCwDJgZPAUuki1//Zuu3u7tHAqYOYGhem2t5cRu6hDyYNDkyh5gydzLNu5tYA7R1tA02t1+3Tn3je0WTG6x8ztyYmXzJwwhtvvuEoX/SRWTezawDrhGhBgQvNDuZMnQOmBURjdONb3/qWffe733UnlWvmVDneS1KdZtHiJfbhJz40s1vLPVg6Fjm9vb16X+IG60T6ZNypE0ctcX23LauTdo/UAwBOgBzXbC4pyWo3mioECj3oJfyA/DvEIS6JSAItGgfSUO8AcD06ZFiEmDTlAH+k0SP9x73iDpeLOuGQpA/gr5rcugRSK9K0Rn9HHOUhAdIKO9G+TnEN25Y5+8U/bhi57wAl2VAGAJMdkhDD0S7PTwrkijCiZ7gdc2CZXAZlr4oGOkbhScNn5g+Xisp99x+k0SY6ys5rD1nPYKmAeZdVF7ZbqfVIap90ABrpeNoJ7Ct+YvT1TN6SAsr4RUX36FQ+iRdwHxPFpQSqiFIv1HfvsFqIjJt9AbSfDCLVJoKQGwHQ8sc64f7LcVv/0Ke19Vo9IZcNgIwkjsEyLG0IVEF5AkoosRn49Zys2l29dtVpdchGe5mBRb5vi4TmFSy2rahb5Q4f0vbD3On7tmLGKfgpHS6rrz9nX/rCF6bMzR8n2tlbd2ENQNvhfSNM4OA5ZwXC88JdmOWbztK0gGhOZsJ9RhKF5gas2GCxCTSyQgZYFgtIz7q7rwbYek8mpYd5EiC6t7fH9r3+PVtUeNEqZZ3QAU4VycM0AJ7DZP6qe/wG5AEygXwOBMoPMAypAgAdEdDDH5e6uO9IfvOKEpYvWgguziFAuYQSTDggLcMQ0j4BUB3lFPmigmvOy8fr72MJcEHhBTuau9KlNSd6TcAasyaBI300YnDUT0qunNlsQCBlZRGAy4yTZygPcbQlC60sH1PiafDv7useVz64zo312tqKw7ar5XFJr6UeLtpmxVIHiFVDJN2kB20FigqOMnZpwdGvhQR1iSYQjKngoLQUqx4xTEPeuhUuX7QXVjk+rzzv8qj7vAfCc/XvkHjIl3d8r2+SlbboFntqy3ZH+ZmMlA1JA+G8HlFoHpzGxiG5m8kOKfSPf/xjLTCXWXVNNSWeycW9r8uGusxz585be2uboee4oKBwFhRO0CKwI/Hqa6/ZGqlbXLBQlrBm+8cENXYv3xblUWenrkq3OtraWGAyN8xUNy0gGq7L5z73OXvmmWccdQMeNJIpJJ0QyWdX6Hdn8/EAZzK5279vv7Vee9c+vkVSaIEjIALCY4AaAA0HTkKaCaVixOGp/z3i9WpXX8Bw0DoGY5IUB1osCEdwH5f/XRPtlqXCVMTybBc4xPBKTCCzuqBvBDyHk+JZ71r6o077RlQg3YchtnikU5Lly+JUz7WqWJvLu79P3hMydNIrDBotQKKsByRV9veJO/yd8BSP8nOdG+smyKgw/PZ14sNh3ntZ8SU73gbYH1I6wHalk6pItHyg7m+ODhbmaxFCfcKZ7uqN2rmuuC2Jdwt0i+SsRCGbAIhzU2LlIkno4Y/jSBdH3nhPTaJ6EKwyFph+19cbHI/0aKVypCFma3Y84VTaMQhm40Lf8LA82kXhOlNfb+s3bBgZOJFKQPdCr+hMdehLbbjSYJ/7/OccfcXpJdcLGBQvnV0AHAsJ6hGai6e2ZPPjWSgwXHE0iyA+tRJepvMLrEQSd8rLpTOb3o11PN31SXs+ceKYYQoawx0IIWaqlM01tlv8oM2e0GFb+NCf+tSn3G5V0Adm2zVVSx+eSf0WwdPJEyfd7iXq8G5Wle4tNrs79vi0gGhyS0fBqtNf//VfOx2Mb7/9th2UrtTPfvaz9ou/9Etuy+uOlWo2oSnVQEPDFR2MqXETfLYH4bS/9YO/sQeqm511Ow++PFj2kzjPer9wPAF4DCSlaMvo6JWO6ggcXy8DHv0cFIp8HdwjHeBHQoLdpMBtUhSUIYESTIsWCHjifF7cj9QHUtmkKB+DSHU97yQVtlyS4rryDrsurm5cPGPi1/FEa1SeFhb2OJ3UJeoV2eINp8H3FMYZueIHXmrSwUMoHaUC/ThfJ4QnPTSXJMRz3lh5WJovpK/UoNP0EdS5Eh1YLJFvUPYca+uPuYXD/IJegX8NuFpcuEOHKdDNQ4Qlz56Hjp9/L/iTryqVPSCkcHdsd7k9asnSh23BktUOCE9GCu1jK5c6y03i24dBBc+vXLnCB5lx166uTtu9e7c9+sijI5J3D24Bw94BnHkn4QVJNj/6SBCOtxq8x+x+gGriC1Lg+0xOL6iLYR1e1Q6UqgZ915R9ovpkUmfHLV+Winx932x90tPQOICVzkcefthtU09VbWDwtu6fT85J7Nu/31kyxigTI5VfWHIN3mXQ1qkV3mfgl64j7xf4BGF5/4Qbyy+chg8189PTfKlFHjqbWTzS5hkTxhsnuJdIJN3ixi/ufT8J963sfWb0WEU9t7S02slTJ22bGAkolZjK/OHf0710TY/wt5hrtjNffvll27N3jx0+fNh++MMfakIps9ffeNMpo7/F6Gcfv001wOJnCDvPYzg0Lry/8y1Ldu2zTYslMR0ZtMZ4YAxvzFoPiipxLVFtZ7tW2uU+bXmr82Y6om+XdolkCnkSJCYgPLcgYdHhAVEacq09IaqBQOhYLk/gfF5h7wgFIxwOoys1eadtQ+Up6+yPiL6B8ZQBq5DU17ss2fK3JrwyIBWK+sEByGwOIB1RenMkTV9S0GDry94T97t1VFUkxCFvF28aCgfaNQq14NDawYWBEw6QznwNxNvenydwnu7SlIO/PtVVj+Kk7BO9P6Twp9sqrXrJZidlQwrtB9Zs5cn0Y9Bl5wlqFxpgcDzPSXzGCLZ1vTQ189l78Tf94+jRY27iemjbQw4cUD7agS9n8Js3MTW/dBzBs7zNwM/F5OIL/Lx/Oo1w2j7difyyx02eb2d6RD5R+Xwegm1idjVY+LNlnC4TYdLl92Wm7SHcOSl+JmadgzATpTd2fQ7qADQaB7B9MH/+Ageiw0CDdGddugaQONdrZ4qxYNODG90N3kG2dzWRX9A+J9Nexn5/4TTC38kYv8N+k08vaJ+jn72xLYbv31p62crnqtZZJT106JAO9DW7xR5nngLnn8nsJznWpUUOmI2xmUXireST971r1y4nfcYwCzSOmd4/0jNuqqpv9gK/tqWl2eZUzbErDZfdIPP8Zz5j+anJ07+Ym41/9rnbUwNMMtBvcACCTMdEdXT/K7ajVoffpGP4ZhxPcRDuZOcCe6Nxu53sWGcXu+cbhw4zwSBDT5kksZEU2uN+QuAb0IzUCQMpUEGcarpxMgPYbkoWiZqRTsF/mxvrcdSL4Le2zpUWGjGmw5F/DkRCO+mRNJzDk94xKJ+5KJDaMGSnGiN26lrE5cMD7mbxwHFImbH4yPFAaB6Xr/Xam0d7rVc0C8qP5g69ttFOHsSD7uxM5/SigLIncPTR69ILfW1guS1ftemmpQgMpLQbLOaFHafzkZLMpLEAKduJEyds9erVrr54x4ELpG0BJSPV0nQTSVjgF4TiO37pOgnuB1I0H1ngFyxm8NN+gt53OG780nFPLT22kgE5jN/w2XGMBbyrXk2saOVBUjWRS5f9xpBj3QuXIQgTlI/Jv68PE/LdjiJI26HM5LO9rd2duYFGiB91BwDAUmRfX7AYpg2iapCwvKMw4AYokO5U65NSnZde6PMXzgfvu7Rklgt946se5cN7QS/00iVLbY4OKIfdWG2CMOPd83GE28vkw/unR18nep522NzcIm1D3U7oxM4Gba2zs8u1u2xz53hxjnfP54ww7KJk6+8Ivlz/7E1IYNE+Mq7STxqvN7q2XVgIDS8YC+i/7Ch7IQZ9hvx3dKh/aCft2rVGp56UtP3YMtVxiecuX25w73v9+vUOSCOFDvqZL9XMu44tzptiWdnSmjdvvv35n/+5U20HjWP//n2W6OtxVI6ZXpFTrK67KjjvBnWEOFQR+ndFhzxxYI9EnPtt7ZLRgGiyBcCMtKxwqzNropMxka5EkegIuXalp8Y6SgvE+9XqNwQIwXoYu1aWnGNKBRBjUpu4OgalKkc0jFgGVzkzP2jikJzZhiUVzdVBuwFZ3iOu9gEpexcYnyNNFoVxaaqAFUKaSs/TLjLjGu83z2XiU9KB4x0DP0v65ZYe+j2ggHvOSjezet3qxTJQooclH3aq7XqTekplwkFz0dpTdTCkx4fs/PUBO34pYVuWx6xIftRfd3+uA/6+ngQldCiROFwUwUcQndLRu5N/6mcowOivwh2261yxVa94RId/FjpOm28Lo0OO/wvJQ21traTP6QUETyCVAPjMFMkEE9HZs2cdsHvyySdH2mz4JfhJLLuffFPvK1zP/ru/Unf+u7/iN37c6YaQDndjeoDN06dO2WmpayNudh62bNnsQPO7777rJkLOtrAtu3XrQ7rvLVCyDR+k4a9TzSeCFyxdRtVHFy5eNEIBIk+nlKf6c/VWGCvSDkbC6ZllYnZtR8leb2y0osKYm1suXbosAzcnND5ogSktAFu2bBXgaRIP94QDIUig48Vxl1+f18zrZOoT4PSTn/zEFi1c5ExEc6DQx8Pzs+7GGnBqzvQusGAcSZmFDteZ/+6vxJBur9nacDa/G9s18fg4/XUsv4nSu3Llqu3bt2+k7a1ds1btq1ltUHr9VaZ+tYvaulrRWFcqicBGhlInuax5mCg996A+AMro1GacWbBgvtvNC0bxHCdpfv/999XeiwWGe1373piS9JM0C0cAf3l5mRuf9u7dZ329fRJqRm3DhvVuHKZM9G36VOZutM/jRHXn73Nlp3GP8oTVWkyoM9bP5PNwHb1mP/dHsmHhX9itXlHpxKEBVjuoNvnKV79qr7/+mj3++OMjks5bTWP2+dtTA3SAbKdn21pbNBG9bQ/Mb7ZiWSccYmk8RdeJYRSpYKuW9HdL5QlbUHTF9jY9aL3Dc8X1rbaKvLPuwCHRMid3DYiPK5AIfzcYhnQYUCAwLiTKwbse6VEe0sm5LgE+VLohqc3m8gRQK6TXOSmQ/N6ZhL28r08H84btwxui9vSGQtt1KmnvHe+WyXAdgO0fss89GreHVgrgjRFftjQaeyLW0CiDK/MiskAoSWAqw4DR98/1264T/crvgHV0D9izm0tsx+qotfdJn3Qs1642S52dJPs5raX2zuEuO3K62xbNjdjPfihuNaW5Vn+t377zdpfT+VxUIGuDKj/xMqBipAU1f/DCodxSA1f6ihwlpVAScO96h0TvkKq6MtVDCp/7WzdcoXocv6pBu3ex/czWx1x7uFk1bbQnFtUM5AAiDrDixx+/4RCjvedm478h8x+QB1IdgFpdXd3ImQ/KxwSqoqqsSIfhIwZtdHw/JKpBQXw9MZEFfkE8SIyDegziDg4fTiY9H0/Qx4J8BX7E2aIFNLr90R2/d99ea5aGpWJNzry/1atWydDOPNv17nsCvIEFSsrNBO3LdTPVTzlYpB87dswdOFumOly3do3NrZnn6q6/P2ltLW320DMPuXQI197eMZIUALxPjR9pHBYieQfV1dUGsDh29IjL35KlSxzlArPDhA96CnXHYU8W5elDn9TJePVJeID9pcuX7Mtf/HJqQTjzrK+NVPA0fOH97t2zx+bpnXLmhvZPe/btJt0fxm6fZGO8/uDB3kTvL4jH98mppYeACZPVy5Ytc+0VehB9AAmuU6agnZp6LabRfc0ijraL5DqbdHoq1eqEWNrlOif7G0tl8fkB9Y95WsDRFmnPYK0VKwJDP4cOHrIrV664PLB/ybOAZq6HDh12i+Ht27e7vnJMOwMxAVzG6K1bt1q9FtDHlQ71TB+hLrO/m2D8zhyXfH+6LL3QF/X33HPPucX4TD8rAIA+cUUKCKbyUscLS8fgJSwRDwYp4K6dO50xCiZnXuSsu7trABBNZ+BdsXrk+9nTByy37V1bvKTXcXJdH5tkMQILf6JfyMgH1vMQkhYJ9NUWaoKuec/2t64V7zfH+gt18EFK5XAMsIXSOlGQKxI0gCIFSjE2ki9d0pjAXiCuc0LUEJ0tctLeAGS4x0d90B7RRV3fFrN/3NVjG5fm25XWAfvuu522qTZq+84N29/vHLCvPCUT2H0R+8/fbbNvfGWuLa/OtZYeqZBLCp2O4zQM27mWqL3w1mIrq0nYU8ubbN0CGYiRERrc3tMJe/G9hH35w1GrKsm3l3ZXWWlxqwzMyMR3pNJe2NlotfMk+S9J2vEL/fbhjcX29uFO+9OXBu1nHo/bn/24zZbWxGxuWZ69dmjA5lWlu2qBDl0WaAFBHSNfp5rQZY2+be+ol3xJrWX4US4YHP29zCvvtVO74HuulNuKTc9b1ZyqaZEYs5WeK6AT1gLDe0EyGJUhnXvdIUVtbWu1bdsfcmMfoCxwAf+Q7/Qj73xbZYs2mKjSkzm/vfMgI+xH3PRN+IvFkgrTRyebXjgen4ewH9b2AAqN2tLtEFBFojRYgP74EqeOjG3hisoKaxJFZ0igGjWmSILTOfY5n9qVuoGeAYXk/IULkqYVW0lZuQBqgasfOJVov+A+wKG7O+DY89wQ29zKAGCmo7PDSQZ7BOxp660CF2gQQkdtqSgXSMUAGJSZP+rA1124HrwfEafrKVi4kE8kd0gh5+hwHHUSPjw7tZLfH6Hr6886jTUf/9jH1V7zR+rclz5dx+mWhF/QZxiz+GNeCO5ne1dhPyhAAEskoPzhsvW/8DPZ85BOj7TZncVoCAtmruzW4A+w9mMb6dBOi7Xj0SrVh2giCaftMjPFD9oj/Z3+yGFW2lxpRaUD6sRdUlxiSwSuGQuKpSGGNkp5sFOLY27gWege8XiRndFZAhadSdHs+rsG3MLT9XHROS+lJN6UK/gLMju6rtL1EtxN96NeAfYjOhuyQOcE0AsNgJ7J/eN/+6shO9ek8URVkp6Zfa3c5JWX9eKLL9p/+c//SXzoMosXSfokMNQrOseTTz810thuMvrZx+5ADbC6pSMikUIv9IFdr9r8giYrL9JwFoxnk8oFiymALw3MaajQgUDvkNbWSMvEo3MPipIg8XbIYVClo2fQCvNljjsWJEgcPaJwFInigIGUXkm1i6TnOF/65+jsYzn0PWMpsbQoR9QJeFmaiDW4tHQOWJPE2Ehwt6yM2mceiTuT2LtP9tpBSY9XzCsQOBZfuVEgJY1/bkhGa3LrlBaOBgH6a9dkzjSnwgqiTfbgIkm0FFqHom3bynz79I4Sl+/f+NZZO3OlWAOraB2yp11Vlmt9SW2lNwxbvEDSSm1FL6qK2pmrfXbsorRECwR8/tFim1MiidlQr10QpSPsGNzapbIOIzBDqu8iHT70TgwQpy8as+Re3Z2/l+1KLZ6+HrHOvAftI1u2ugloOqTESDBpC4GEI0iZAZ/2heP9he8FIe6NT8a79/e87wBaZeXkrRNSXgAr/F0kV9QHDqmVP0XPBJk5AeEHYEQaukYSqWDypg8EIG+crjBuhSJRPnb8mEzzrnDnWACkufCdUnmCN8mhUCZftoJpl2zXMlHeiqMeGG8oNyC+rq7OAWYmX18WxiDCsHgYUP+gTviNU6tyGIt4IppnSgX4qZOE3ks0FrVmHaziHdHG2LKm/oh3vDFjrPLw7LmzZ917AxBC4ygoCM4vjPXM/e4PoHxT1gnnz1sw5Z1oDiICXMNtjHfAu9Z/B8Z9//BjSHDfXP+A+rBw4SIX3r9vnvXfp/JuaHv19WcEYOOSqFdbUlJm/HC0K9ovv30+aJQs3srLy6eSTNawgOg8TVSMl4Dl+QK7YekufYF6jgvUDyoPueofvoyuD6WmRxaUAP8q9dmIrNaywAjOD/S5fpFQHEjPb9aRJotUzh1s375N40VU9TVzqU6vHRu2Hx+W4bZUlU0biKYxsc2xfMUq+83//d9ZeWlg5pvtDU4yz7q7vwYATqxMGaAO7t9rvVd32YpV6IWefN4Bnicu6/CYeMsr5o8GyT4WOh0GPwB+Gtq8t/XoEOCPDw7Y0jnD9sjqAjcgALqdAROF2rIleAAAQABJREFU6xeZeEDaJwDosh/o9EaHnyeiLgHuyLD0SUsbSLEk3ycv9NrbB67bhzaW2ZxygfECIK6GOsUbj4pbLVvagyB1/R7SCj0np8BWVw/ZonImYBd0JDy/eY4rhxFPXmm1860lUpnXZo8u67NFFdraUV0hJGPQjhdGpKoveKggKml6vMySre1WFWm1dknn++GLa/ArlvntQU0ScwSsiwQA8h13MKIyBFztEglV4hlzNvEXyJR6Qjr8uqTNJCa6DHVFQZBA9EvirRQcoE+X4sZvFLFHOwKnm+O2dvNHrUwcOgZAP0nd+MTkfQBcAEYckyK/vUN7BxMC48O96E5q+xNO5CMPP+ImDT95TVQWxkmAMJxK+pufgJkw52gHAAkWE1yJpLJLJOniPVy8eHFEwgZIJC2kbhckCW9XWMAjgDw8wU6Uj/B9JmMAOqCAtAHWjANc0WpBvPhv2rRJaQcAfzraBwsIdIejjgug7p2vy+uS+nEojfxFJckMFve9rm8hiSYcOpoB4VBS+tV/yee6dessqYNUJ05KcqiJ/QJS7ltoZ0i4j4pOguSR/lFUND39w5d3pl15L2hQOXPmrH3157+sRQ0LI0aa8R1jGrscR6QpoloLtbjquaOj042RtEUOwLfpPV+/3qQFXZ4z4oYOYg7SXb16TfS4wtSCiR2HIakhbHTgjvbLbgRtmjSm6oJDrr2urzFuEQd/xO+1WgBSkfZSTvrGdPQP4lq1epVLC/pbOO9870tI4KJ2CShm12+lwmr2ccVzxVRRKXttXa0bV1o05tBPoNdQb2e1MGQ8QrqOoa+bdYxhUHgrKsrdwoe+Nh3lv9n83O7n/uOL2iFIa6SdPkk0q49V2uo7ePCg9SqFpYsDaRP+XrJxuws3G/+t1QAgh/cFF/L9d35iS0quWqUwzlSGna7EsP3Dzh5JVSMClTmWEKrs7NbEKylyWbE4xM0Ddq1twB6sK7BCAV1wVUKH/s41isOlE4hXmxNWURQcSLvcqsbaOyhKQ8QqRIqOSjVcvoC3KMza5QgkxZmS1jZJh0uimLyGBzxkrV2S2OY/KC50k+0+1m3d4kXjhEHsvVM5tvuUTih391tnT78trpYeWd2LR4f054KN+xFfIs0mFZdsgZo6knEP6ElB44rtOZW0g5cKrKlHkmpRUWrivXY2OtfKSjqsv6FFkutcq9CBdShPD68tsn/e3WEtXRHbvibPfrB30L63d8AeXR2xl/YlrEZ2zB0GZXRkQtIfVhQ1VygeSSFA0PIb1B988KpIYkIetCucojrfLCCev9Eef2CjA9DTIYUmbgZ6soVu77DDH0keW7z3ogNwvvrqq056C4CbDEDw5eQ90cf447nd773naAxwG6GHsB2NpPeMeIosrNCFe/XqFed3TQC7TxJhdiFOCMSj5m3RooV2SSC7XxPqylWrnTTKpzWZK5Pptoe2CWw2WaFAC4f38lOrZibDKknZkXZhmQ9ea3h7dzLxjxeGdgD4GMuxNUweANHLly93IIX6ZkHGJM14Rf1sUJ7hY/aqbpiDAgMoJQ5AkffNmze7dg1Yvxl3RfWOlO3JJ55Quy10cd1MPPfLM+wAvP766/bAurW2WLz0yfYPwjH25OmvEDqG3u0x8d1ZiK/Q+0c7xrlzZ92iCYFdW1uH1dXVukUpbQKAy3uqq6uTQO+q7FQcsqW1S93CisUY1vOynf0Z772Qnw0yHHXp4iUXjPbFYhPJK3EDUgsEcNl1Cy8Ex4tzsvfoH1A4sjnqinMLnAPo7ekVgF4t/n+Nq+ttW7c5YE0/IP/Lly9TfbIg6bDFWogsgHKrcZkxCD+43gBx+uJU+ze7Z9eutTguNPxqxhNPpcmW73vd78D5YbvYEmAIX5Zpk0QzWDGw7xQX+rXXXtULgpM07A4W/v7v/75WjYt9mrPXu7gG6JxHDh6wjobXbNNW0QHUSYaR1E7C0ek7Rbc4ddns3DUpaBNv9+9eb7Elc6P2xPoCa2wzO3ROvEUB6qjQ7//yfIWMt0TsD/6+Q2BXW66ic/Tr0NyK+SX2T7u67H++KX6bJMVLFlXYV8UtXjpHBwolNS2RFFeyODcQKLs6iIjxEkl+BbAXFqSsBqZw27blETtUf9L+6B+1Khc4XiBw39CMCj3RQgry7IV3ux2A/sLjJbZ9RYHA7+TKSnUUCgQvm8v2op5RRvyTqJRzg5R611sHO+1SU6s9tq5Iera1Bdh9TfmI2JKaAkm7h61uXr795Wsd9rt/22zR/Bz75eeKbNX8fPvphwftH99pFfCPWJkWFesWYVhCMN2/Cw2CYNPOwagk76j8G3ZGadAjTT3kq459fsZ7ddTn2fZyW7r2cUk0kbJN3jrhePFyj/ZQIRDmt2J9+AA8xd2AjxTDUxr8/bv5Sv/AGheH71DhCZijfJN1hGfCRwLEhI6UjkkaKRtqptgGZhJiMgIoUFcAyKUCIzwHGIBaceHSBatbWud2+dAa0SQDB3WKM6r4p+KIH9Beo61qACmOMjrupyRrdctqVUbUSwZq4aYS9y2FVR6QHAJafP0ywVNngcTP5ZRuZwXyQwrHfZ9PwgEOcPjhpgoQeAYAf/DwAZu3QBSWlHVC6mzWZa8B2s7RI0ck8Wyxz6h/UFf4TdbR7tmFKUmpD2ShBIBev2G9FpgdVltb68Yo+g/SbjQAzRV9Yu0D69z7RSLLmIKUuKxCu48pfi4LVHYUpgqiyTcS1rKyUn0TdUjzIW2iRYC+XPx9VFv69jnZMk5LONfuC9zBQrTSBH0XPrNsKoizz5V2H/D8NYdq/CCf5N/3A8YU7lPH6bBTyx1xHTp00PVVrBOy6CW+mepePiQtY2mTEq6Y0waiWZF97GMf08porttaSUgtESsltgAZ/GfdvVEDDA47f/wd27igXRondChUABF1bRM5DvENq5PWFA3YtjUxq5F0tiSeZ00defbrzxfbmkX5OiDXZ199ttJpsvivL3bY0fPaRhYAGBwetP/w1Wo7d33I/vb1HoHtAR3667OvPFFsy0QJ+Z9vd9jrB2P2c0+VWfdwkRUNSzenKAxFcKexXKgRwzGR3eQ2esAuFyf6Xz4njrd0LKPnmrudMkrS0NZjD68asl98ptz5VUrSPYWx3lUHk4PG8htcuzSMmA71Pbwm1z6xo1x5FO+zIuLU9D22ttCRLNYsMWk8GZIu61L72mfLbaiv02ntKC0MKvupDQXSFhIT72rI5paIC6oFRu9wvhXIviIhyCvUFRYd0XyAk6TRuoH+7KkMYZfa8qw1d72tW77BTU5IJ6bTUUdQF+DlVWqyCzsmwgYdaIG2cK+4Tklu3tv9nrh/290EfbMTqAcW1DcTDyqm0FrSpkNJSIShI9CqY7qPpIvwjLEx0R6YxAekdgYJXVKAmj+Ax61NXqPBjgOhtXUjwNpPvHfiPQG85mlCpn34egqnmy0v3s9fJwofvj/WdwBHff0la7x63QmDinWQi3cw68auAXYxD8rYBzsXqFfL9j7Gfpo7qfFbF949KuTKBKgZ7xDUAY55B/3CF24xI/98905ytBjPdare6JP0n16pfrsqiTH9BeEAnP6bcUEZgnE5AKVSoLBksdNwka193kwaU32mVKCeRWKQ/ui+6+vcCXdSEROO+vL38Oa7X+SEw042Lzx7/XqTtHvU63D1dkcrm+75Y7J5uVPhXhcfWtU2yk0biGbboLa21pm/PXXiuCZ3AQdxb8rKK2e0eH9Ubd7jPxh8juzbbYNd+23j8n7rllQzIkpEXNzbiRzcXA7zoYEj7OrEL962SiBAcavb2u6TfVYa5TDGsHVKz2Jz55AtrxG/Tdon8gWKkRQ3tuvwX2fMLjSJ99mkQEgAhAzFmJDqu54AROqzUTqn5+ZLWi1tFVFp9cjmAJYsBpIRHXQVxQEpbcdwgdLrtbnS21ciYE0Y/b8lR8eibxFPgfjgtdVRR60oL82XKj5Jy1WFvUNwpCWBlBo6qbiVlhEdvBUQnhOTme8UV9tnQuOTlQlQl0lSjxsWiNbxkZF8kg6m02Vu0eWfQ5Ro48DQy2QdBxCPNlVazaodThoJcHIT02QjmEQ4Hx/UhEwH6EPKc684+scJcf8GNCmjSzlTt+pkyuEnMaRlDiSmQAPGEK6J14lmFCTDbE0ndKhPL8SuNV4zJk2vWiuaH3WSaoDBQnE9GyWx5lBRUNcZI/xkMpUlDHEvra11EqoRYJMl3O3y8tI0ONgfjBMVTe9kz573Je2vEIUAKdv07dJ8MGW6vanSPwBU3Tqc/sgjj6QSm1p7BCzzxIDwA/G5P3lyhaoBGITf3CiKDYtMqB+YmWYByiFYFpZe1dygFqbou4dXjVERTGBPR1tGajtfhxddXj+g9onE3i++b+9bHTt2tCxBR0NbEAcfmT9ubSE/dlp3y51MKgf5mjYQzYTwyiuv2rf+9Fu2YuUyW7hgkb2/+31twbTp+2+7Sr5bKmI2H9lrgFX+IVkn3LrgupOSSgjquLzZQ4/2jQk8xySy1ljnHBxhdnXyJR1gh/n0lX471dBvz+8Qz1IaJ94/0yXJQY6VinN99JwkBwLVPeI/X2/rs7nSk1xZlBCPudLKJSF+60yxLa3udQNov8A6VvnKpNKtQImJ7TGu88CiKCfhrAgCTnEP1uULeOc509pIiuOiiNyK6x6MWZ/yVpnX64ygPLY6qiWDKCTSniE5gTNdnq/DlGSXPCWFYBOS8hdHOqXvWZbhhIcxbw6gz+byVGY6q1sF6/keHbAscGr/ZEBGlI72fi0ool0OSGd7PtOPPJyTxo/WoaW2ZfVGNyCzEL4djtPq2RwDbnGJNCpIkgql424/jAJ/EJ3Ea9asVX0Vu/aYXn6lpTpj+dH2AAFIa/rFG3WacHQokHJTfg6tAZQ5XAVoyNdWNRzgBknT3n9/jyRqSUf3QFK9Zs0ad6gIa4I8v1ycak9b8NIp0gO04x/4BW0v7cdbGTvftBGAQuDGDjdd6fl4SI+0yT8uyMPE6adCu2fDcWWWcTL1Qpjz587ZWXFwP/WJT7nt6unmvAb5nTmfnBU4LgFajdpssAgKGs9U3h/vDZoEYBjucZnGh6h2YmjDUJ3YKYU2ytjBDk2pDpa2ijqyb99+5wcFiIOfKDM4IloJB/9wUA3ytfhMt/0gb7SztB8hJ9fOfPu81XY22fSyhZvu/j5eWaiZcB4oPyoxD2jX4fmf+rRb1DOu4T+TXXcGlYOyThuIpsGfOHHMNm7aaH/4h3/oKvWHP/yR/bc//m+O6wcneqZX8L3ceFgEnT6834Zb9tjSNQMOrGFGGtCWFNhDi8UIHzdUUExyQzVAAporHi7y4D6JXfedGbB1tWnNCxxWgqbxwz0yXy103tDSI3VzObZjTaH9ZF+H/fbfEWmOnb+WtKceLNMhQ7M/+VGHLZoTtastXbblk8XS+yw+c2+p1OZ1BuB8MCkpubr2yEQfyljqKwMDbIc8dwgv4IwtEG/atUVxQIeG0MiBdgxJigVkpbbaAdnJDgXQoaG7lORpSz2UfFJ6MbBlpI15ac8IbmCwxuVVH90iZiCZRi/21YSsTg0VWE1+k5VJah4MZqHIUl/R5nEtWSKwrAOSsliYL2m2jlda3BJSCygtKioHVTGZvCcE4t+7XG7z1z/npDW3U4pA/aLnFIeUKOyQyCJhgvKFZOVudYDacwJVAAUOFAVzRbimg++jx7hsfsPuMFCJwAGSsdraWhU5aMAAY+KHgxyLyeiQgDYTE1IerzEjWGgEWinge+IPhzqYwILaC+fBT7TZ/QifLY+BnwcXqVjdJRxPtmdvJb1w3OG0w3UdDpMt/cn6TZRP2uVrOhy3UIcbFy4KrHf6Z4L6mP3MrAE0y9DPMbbBgty/w6m8P8bHB9Y/4PoBYHiDjAD5/rFw4QIHjumL7JSwU8Bh0dq6OhcekIyOcR9+x44d7uAcfSPYZUvnONyO/HudSj7TZQv6ShDzjX0pHXc6XNqPp258ZrJ+2fKQjnv60wvnC7zwzs53rE5jIWM6Y9C9dLYl3RKm9s3N3xmPTBuIZnAvKoo7dUw7d74rXYmVtnfvHgESTmBP/zZxRjlmf95iDcBbPXL4DVs9p9FKBM68RBQw2DGQb5W5fY5OkZkM0/+ggLSlaAQSPNunH4rJ4l6erVkcsVXzykS3GLYVC/LsFz9SamevD0rKPWyffKhIhwvN1i2M2m/97Bw7fF6GSkry7Kc/VGp6RHziInvjYJdUySjstritVjjA5ZLiDhvWBNcnSeywwMaw1NlN5ADIfQKs3Tr0WCqwCTUiJgoIiwIGTqfiTpH0CsjmD8k0qsrgwKjupYei0alwnw51PVEoUN/rwPdIWEUKsGa7kXAWyZdVRFk1HA6sMLIwKRW1pFSBWhJRsZmj0qiBNDzIC3kaicsni59ulEYltdUhwnmFMmmueNr0bjjFXqb4OJjpJxD/2FjX09fMriQetcd1YIcJ5nZJoX36HFCl3JmOgZdT5Hf7AAwfkwOFTBiMbbipSG54o7xXP/HF44Wpqggqhbjg4KKyzTveC+8T/0DvLGFZCAbSMgBEoHM7HQdtxOcrnF7gF7QhnwfaD/GFn8HH+zEhB2HSfj5uFyzj2VtNLxy3BwNhP58v7zed6WXGjWq/5pZm+/znftpxcNEmEwZeQflnP30NAKp27dplNToTNU90JFz6HfJr7Hbm36d/JjdXer+1Q8MzwZ8+U20eLEFfwr8QTlzKhcP7Nkv6aX3NQR9Jt/3gN+807Udkk8+nC+0SIz/u16i+dDvbJ6ml65eyjB5fgjqdWn8Pv4fx68GE8y65sy7PPvusW8DPZI0c1PV4btpANJX4yCOP2ltvvW2/9Vu/qYoNLBR99rOfm7Ky9fEyPHtv+muAzlN/6qgNNO+zhUt1cI3JXv0SIC1mr1XkB1xcVMsBknESBtiAdBFDhcjPQ1tG8AzPrpB2iWXzdKJfP+rmyvqY4hcOcGa1N68I4gDYcjAuR9LuB5bk6uAhIFnpCVgSnng+80iJM3HdLdPhXcpQVAcQY/qTUgzlQ+q/RJgg3YkccSElR7czPOS+wYhV5cqgifxxXIinMiqQqx/dMqmNi0t67W66X+mPARlYSQqwFgjMwtFmMKO+iIfnUdnHwkE14h5C3V6hTG/jQ7lb+2NWFZPMXuWsEKgvcVqvRe+QpL1bBybLokmTHGd02nqYOsyRqcYOUUfK9BxpRcT7y5WqQBYVLBTQvw2A595YjoXJgatltl4qiTi3wEGd28llY6KqVjpIkDId9wDwSF1xgaQ1M9QH//vC+Qt2VWqzkLIB+Gmr5J0rzn/nigvfD/vRVoJ7Lljoe/qF+fvpiZD4gj4xOt60fxCbjyNNhfBpK4dBEH16P7LKgtI/m8r6iJ/PB/fHC0fc/lkf982kF47Hp+3jG13uIM/4peszmx859/Xtrzf6OR8VwKeByeYDBw7YqhWr3IJp1johNTS+O3v2rHZqzrut/ZgWHP798dRE7Szbew+3/SBl307TbT6cxuj+ETwR3A92H30+fHsiTe+8383kc3TefZy3oz/cGHdQZvzvVHpBHqDfQWuDIsMOIov9u3Xc9u94uq5BGxkd27SBaBri5s2b7Bvf+LpTcwd/kO3Jhx56KCUtGZ3w7K+7pwZ6errt8Lsv2aKiS1YV2lEHGOI82GyThUG4yEhqpezCgTkHIlP9m+AMXDjaA18HfCTON4gLfweMBQYF/ST91UFDaZnoHBSXLafHhRTmdc/Dqy4QkJfY2AHXDuWhKpZwuqJ7UmAyFfW4F8yGl0liTP7gb1Mmn7VU9t3z3A/zrH2YcOQDAh7QWIgz34H+9N2EKCHtAwLJkhhTTgyhRHXQsEhAl7jwkwx9pKJQz9c5gDS7h5qwzqEiSayl9k0caF+XPnbyDKWjbSiuOAHLw9JQAjAdUg0B6qHUBGlkPuvjoKznW8QFj260Z7Y9PEIF8Pdv15Xt8cvSxAFnEb6in7hIj3udnV2SPgWGfm5XHm42Xk73v/3O205NJ3pZw45B9dYcLeKWI5kwCzeXz5vP282lFy7GzacdjmWi75n5RCoJIETLBHMXPOhZ64Tj1yJUzpdeeslq62od9YWxh3pNg7zxnx99dyrvHYCc2Xcm93zmex+dh8n8mlw6PqZbT8/HNLnr7UqPd8tB5qam69K8FuhfD3bMJpevez0URs/ChlYoz7SBaDpSgxTec3L2F37hF5zhAKTTbNXeTinXvf5S7ob8H5aBnJbLO0Wh6JO000G8rNmKSaLqpJy6K1XHViGKhwfYWR/I4unDdyOIFQhEQozDGEmB6A7e4TsktXntUkdXKn3THE5E+1u/aBg4NHX0DekwlvjAk3XNSdGKlIEKgWmk3d6lvwU+gGMcUuOGRJmkzZ0CwTLzKYCcr3yiRi6mK//CIJuBC3sO5QK4bhBTxCwCAOU+HPVXIUmzTxMqSYKE1BMLVf5IBAJNdgk7cZTHZCZ8uN1pQulWfkrzgwUBgJq/iVx7X64dbiy1B7Z/1G2Z0kfvVP/E6lY2iQWSaDQg3Kl8TFRHmfePSTczXM+PfORpx2PmvgcIXHFu0ajvwRUf/JFuBld8vB9XP/mnFxNpPx834fx975eeHH282Z8jfsL654J8TC2f6bJkz7uP25fnVtPz8ZBauNzUIy697R6UnfRG+wXPpf14KqhD/NLl8d99HabDoeEBi5Ic6IQKUFw8s62vUfJbcbSBE5JKciD2uWefGUULS79DUgjqOmiHwfv0ftneu39vPm/ZnvPxu9hT/Sz9jhVDqj+G4/J+QXxT6w9j5dP3ZR+3Dzed/YE4g36Q7u+jy+9qIdXGfdjsfun+EYSbSj/CemN9/Vl3sBqBAudY7tZxm9JPt1tcmWPHGqi3tNP0fuuOU+Z/8Ad/YF/5F7/gLBZC5P/TP/kT+/kvfcFefvllp6fx1lOZjeF21ACLnzdf/BtbWdUoLvL4zaFEXOZ+URnakgLaakdIS6fiwIqdMu7BYTxAeI+krqjFw0ETKRZQxTHEQgWBrhEVcO+Q9gkkrTwHeMbR8WtigWGVwGf8T/KLTulOUSkae2T9z4/j4zwGAJ4fk95e5YucdQwWWa8FPDwNZTc8iRVEvH29QL8olXaOXEnRSa49mWctSRE1Qo8S94LCHgFtlZWFgn43SXXf5R4ptAuFY+Br0iIAVXkRgfyYpNtlKQBNRoi/RfdbkuJu4pHFUQeNHQIeJVttybI1Tgp9p7hsAGUs3gUc3tGZYzJgIIZ3DLfybnKuf7z1ltN7W+kMx6BuK3gxXKlT/kb7Bf7ej8k1+AvCBc8EfoRJxxP4UX7v5+97P//bpxmOy4fxfoQd7Te1fAZ5GDvvo+O+s/VCfd5q+Xw9+XfD9eLFi87QzMqVKwWg0fSQ3WKcq9jZD6dhZpfUnK1bu86qpQbQt8/w1devf1/Bb9pVup17P/+cv+d/U9U+TOY9woT9fDieybwX9vPPpP3S8eDn4/HhuHo/n6+wXzqeIBxhRvtNrf+F4x4/D2P30WzPjc7T1PoR6gRP15+xurq6ESGMK+R98vHE2sAKb7i4AYIJ+9zE9/3799vf/u3f2I7tO6y2ttbF8JwMr1TMqbZvf/vbIyfzbyLq2UduYw3AUX3njVetp2OvbVw04GBh0O2zJ8qYMCCDH+2Dpe4wIQZWEtIlnRorsj8U8oVDnRiOuYEtLrCY57jAQYotAreo1MO1CWw2iwYBUI4JNcdEhQAY9uoM4fVEYHiCcPCb+RsLNBLGO+IqEaBdFG2xOQUcwvN3xr8C5hMDgSXGKlEuisfQR00sPeJad4rnjRuUJLBNUnRoH0i/Sa5I+raL4ZeHMkw+ugfj1iceNv4sHbgGnG8XVfAhz2LlH00jrTJt3tpf6OL0IYifA46l0hIyVtF6+3PsaPMcm7/sIXE9q+44QEDzBGoU0YGc6QDPHG7NxpvODHunfpMXVGT19cp0tPRCh9/bncrDbDp3rgaQsrHrgNYT/sKHPO9cLu6dlOgfZ86cdkB62/Zt6h+hge3eKcZsTidZAywg9u/b66TQMA5YYN5v7/zZDVKUkT7P6mpuWkA0E01hYdy++MUvOnVMVOwTTzzhfneIW9akyXHW3X01AKA5vPtl27642eJSrTYm+kplnVVtLCdp86NtTmJ4PlFnB9tWu4N645UOoNgvwJ2vQ4EV+X0yMKIDdAKb8VwZThEFgaEXaS3hSMNZIhQvGAe1ARt/ObqB+rk4epdTg3VSh+l6BybfhAG01wdqlJdJsJiUDxwyZPQ/53AoLjVHZAXgCl8oYzEYWsERFNPbuco34bukRQMqCAZRwm5Qkv0Wafjokco6Vw96piraa+U6ONijOuK5pPKNej/ipn4osec/h+NCmj/WPMZi4EqbdHHnr7LaFQ+O6PUMP3+7vzMIw3/Otv0HzeNu09LRITPD6JpF5RZb+9T9rJuZNcCYcrnhsp2/dN6ZUg5UEN6chbuZWUM3lqq7u0smnw87qWRYL/SNIWd97vUaoH+gwhBjU+vWrknpTb//+sfGpTkGpSPsJo9Awk9lfOegEKfr0ffKIRwcJzivyEgAE2dUW7mz7u6qAcDMsX3v23DXAVs3P7B650HiWDntlUQW8ItE+UL/Snun4UE7273K2gars+qQ9vEAFLsklQU+QqOAdZ0jkAzdAWDCthe0B8AiPOc8KX3D+AltB0lzJ3QOPYykmjg6paoOWgmS2ZL8/slJlZUO8fUqjaQOMeJIeyzHwck+4WFAcKkkyCUy0U1+MbPdKsMm4WdRlYe2DnB2VEAZB9e7UNo94HpTvh5Jgd32XkaaTl1drMnKC9LlQG7dpUOWXQLWXTIhTj7Q+JFIMR2QNmOghToJO/LUkiyyniwLCw54HrleZXNqH3OnqjkM4hcj4Thu53csvsE1DdRRjU6JvEADQ++xH0NGh7izv5yUrf60o5isW7fuziY+m9odrwGsr73xxhtOW01g8a5I/P1pmR7veFnuRIKMpeelsQajKGvXrlWSo4HFncjDbBp3pgY0NLsx+T3RdtihQQp9P2nkyKzl//VTMhKGOvKUm4RIzgcd+8pWZ7wkbl//xjfs1VdfdZMkUs5XXnnFPvrRj7pJe+ynZ+98EDWAVbTjx962FWVXpH5tcgMgXN8cSYXbk8V2pGGx9eaWWEKTz9mmCquad1Vs4QyEmCoYz5XpcCCdkRBImqWOw5r641LJJpaxdD0DTCvyugU+lQYB5bjC/80VOm0RqNzZtA1f6bEetHUlR61G1AyAJYf8MDQyrtPtmNTOLcm5qnjJRUCbyPYME8RATtR6kpIsFyJZTpcrovwV5fa6svhnh5V2jxYJeYqXsgJu2wcLVB4dvNQ8nKfThHMKkirbjXkMcgJADlTmQf3AFeaoXhyNJek0ezBHXdEhx7l57aJ65Eh3d7Cn5FXd8QzRI8UOyodP2p1r7Ler/Uvt0xsecttwH4xeZlFc2lodMIUbzaEU/67JKZQOqB7cu916q9M1k/0bYP7E8ZO2rLZW+UFn7aybqTUAWMYK3rmz5+yLX/jifStlm8r7RWh2SAfSFy5Y6HaQpvLsbNh7rwbYpblw4YJ9TDRdTI4Hxp2CuereK82t5fhJ8aKfWZ9rLx2UsgEpSJgWEL2sbpn99te/YX/0R//VXnjhBW3Z9uvQUqGhiPvXvvZrjn95a9mefXo6awCwUn/soA037bY1KwNxZjZrhD5NgB6aMuDj5gtgRnK67ENLd9rupoTUuc23xsgKax1otOqc62C9EZeQtDgpMFoiqaljBSsipMAJxYWFwwoBQigPPVJih3NSav0Ws2PE0UBl2M06EjHRG+ZLOquwuc3uOTRbdIlPnCOecoEsD07kWAK06HnUw5VFB7NKzwkjtSHKn6Tc0uvvDbH4uClfgQ4BUo4+8cPhSOPHIsE5lZFyRIaTqjPpb5Y0GWAdFbc7Wx0jeW/uL1aYQZsrLSARpNqSlisW5WPI+nOjdq13SFzqIatSfQXsauUvgiYT8hochgkSx2dYeWbxwVsDWMPpNtt1qcIWr/+4s5Z3JzVy+Hz5K1Jm6BzZKB0Ae6QcH7RjEcWEgZrO7Tu2qw5nJZIf9Du5Xemz8EQvNIZCkKjOlbGQ2603/XaV5U7Ge/78ebui7X1vbONOpj2b1p2tASxDHjl8xNn7QDc088cHI4S5s+UeL7U/+DktvKWl48QVCc7GCzjZe/AZn376aekN3GQXL1y0bukdht/IthirlrC0abJxzoa7fTXQ0d5mRw+8botKrooLPRqEZaaKlBVpb7coFV6ymi+gViVu87M1b8tkdYXVdy+VdDpfIC/HSWNdHABJ/em4YDpK/U4KQPcLfA4K5GHqOiGeNLumJdI/7aBKgP1GnkmIv4zChqq8NltTcdL2Nz0ojnSTuNGSWitUVb5MeI+EHv8LwLdVQLxCYH94qPOGwCQNXxutGCXS5BHWjhEOzMSr9YTlKGPDQsx9iteZFhfZhDhEVBFIZyWAOXEZnZHPcHhlEIoMnnNNtN35uHIo8s7BMjvfNU9gv8sqCzpUp/2qKwFnHWxMYWMtIgTwFVZ4zwFnH4GsebuDh3OkS5t84k5el1YQW2vPbH3IDYAflJSXcaAmZc2MfI01LiAFZrswG9DmudvtkLJxWHrR4kXOmACgetbNzBrg1Z49e9ba29vt8ccfd+0OED1W25yZtTC1UkHVZNGBirOgP48/h0wt9tnQd1sNQMu91njdHn/sUbdDeKc0Ot1t9ZCZn7/61xH7uT8anB4QTeT+YBDgmUlndhDKrPK75/exIwet79q7trJOep8nELJxoA/A5mgDFGEETyCRlgq4gjbpPe7SwbfgYBxBkOai0aJAOp2Fq9PP6Nm4+MWFMq7SKlVsCdlDjEpKHRXQHoQ1kW1Jp2cAgxzKWxw9aSdyFzkADacaa2Vwl5G8khZJjefQ7zw/etkKx9CwwfOxlPlyB0BHyjo6ViZeeN1o2uB7y0CJlUuenqc8YNWxc1hUjlyoKajtQ0I+RkTuTiBbHpD0OULairDfiu1sz2odmsyzrdVHrCbvnPwHHTe6EPSuMAB8LD7GJTGHRuKcLvQ7zKpTaZSnvS/HjjcW2bqHPmkV0sXMAJhNV3MQwe3/ZALu65OebkncMbySDdAjAcafLcMPwqFxAE0hW2XR0ddVeEzz3/2VPPrv4eugeD20UT8WcuW+/yPucHgfLuxH3P45f52MH2HC8WSLO5vfZOIm3sxw/L4X00M969GjR4zdVPieaBy436Vs7uWO8cE7PnPmjJ2pP2uf++xnnNSe5hB+9zzq26q/Zvrxm/7Bc5iv5xoOw24p/cM/76/hMFPx47lwHnl2Mn6E8en462T8JhN3tjxMJu7MusoWz2T9JkoPgQJUp+q5gcYa+ocfE3n2fnal2qn+3m9EssKWW64X/wJvOaLZCKa9BpDy7X/vVVsQv2JlhYx+YycBUEMCzQE5yY5HB9Q9zGgDsuORAUddgKurIcdRPzTy6LsQZSj+pJpbjwTT5dJvXKhnEjrciH7kAEamB6twQuhD9g7O9KrykzroR0wBgOWgHwAe/crhtPwz4StZGh4asGuD5TYvv9WBXO4Lz4mOosFBtIty8ZidC+U78MjymQoDrxs6BqiVKogO9UnajiXCmFM5h2n0sVxSBye7pN6uZ6jQqvPbHW+7S3q4+/sGbUGFwGbPVSuq0CJDxWseKLUK0TjiWn6QDubEPW3Dx6/pyGlQYU7SI3apLc96Yw/axo1bHID+oICpzx+TI6rEACpjjROAmQ8KyKAX+pVXXnVahhAI4Pyk5a8T+THxXJLhqatXxL/Xi1q+fLmT2l26fMnQ+AFwox6WLVs2ik+aLf6J0sr2zK343Y3puQO5atd+Z2I6y3fp0mUdjmuzTU9tdtYJ7yfra7zrqTraNuee6mqXOupVtndBnN7fX8N+HNrFOMsFHUzsS/S5eGpra52VSKyaDqlvtGlnYMGCBbZ06VIH2rLFcyf8wvm+W9OjPskb/cPn0V8nyv949xmfm5qanVYOrHcCoGel0NTYaDeBHHJ04Nlf934N7N6925rPv2Irqvqcdb2JSjQkqXE2KkJrz7C9fqzXvre3305dCzRLnNb16KV+e+1wj+0702d9Opg3ymHeG2QnVyRgDhjmQF2RDvyhNzrc8YNQOhUsakRCgJSYODA3L/eMQHjjCAAulrCyJE9AOyMp/3z4ijq8Fum4lgxkVHAHSHVYsMTxjMNPjP8dikWv8l8c6XeHG4kUyXuJpO2A6hKBa2/9cKyYoHPMiSVtiST6BaoHtI4URlrsiYWv2I7Sl62yZFCHFEsk0R60eI6oK4MBPUbJOMuJfgESjr8lkadDm8XuYOTJxgJbseFJJ/W9G6xLkQdAMirjxgLKDN4YXmFyuJOO9nf69Gmn1/7BBx900nAP9Jmg+O7/yFfYzwM87nOoGopA3dIl7pDkoUOHpHWky5quNzm90/C+OTx57tw5p9WIuHy8XMNx8Rs3Fb9wXP5Z75cZz92entOSop2B86pP38l9WXzZuE7Gz4fhiksmE3bk2CGbt6DG0XbQC+3vuQCzHzfUAHq0WSA++eSTIwthX2e0LV/H47Wzbi0iT586bWXlZW6BefLUSWtuarJe6ZE/rL6CZdO6ujq7rAUOB40z4yJTU/HzeZpqPv1zd3N65BGtaEf1Xljg+Lz6vGfWE/6Zfv4Zrv654LvZ8ePHnKIIaDtQc2el0NTMaJdtA310iNlfM6YG2qSOaPeP/97WVTfb3BKtn8YBnsGtHCvXAbxM1yVw/O2X2+3s1YSVSnnza/uH7atPl9l/eqHNqsuiVlqUYxeb+61pa6F96qGiEcALJWNObMAa+zCkIh6xgGYkNyK+r7ZE9N2rhwunlxSnGGAZFYhk6psfhx6RPkSIlEr6OxB9KJ1xCqSnoqJblIl2EZdpbRwS6D7RKKBDAOSn7HIl5ZVRmJj0XQP226WODloGRlmYp9EaMpFr6xmyA+eke3tOga2sUTn1zMKCTpc3yjsw1ON2AoipPDqgQ4cYmAm0ljhVdtryLM2gp5Q4mkm3XWgVZaZkh9Wt2Oi4ntmoExPlb7rvB5JolUMDPmoWAZN+UPdpcQ+OKpzLO+nYpXnzzTdlNGq7A/phEB/+7vMU9vMLQMp0vem600hUI0lapaTZlKW9rd0tEhcvXuzU/NE+vEpQOLj+eeL23/0VP58Wfr4OSYs/T0HgO2VQEGk+KXJ0GMJj5IZFCbsQSJKo73Dc/ru/ZqbHb1w4D4FP2s//Dofju4+TK3/E4Sdify/8jPejjNB6CA8FaEj0Hr73dPdavw6uA7QKCwucH2HZQcBBDYhE8twCyMcVjt8F0gd1cPlyg7W1tNtjjz7mFpm8h1k3dg10yubDnr17bfu2ba7f+vbgnwj/9nXvr4ThO+N+szRD5UfznZQZs+otok41aoFZVlpqNVKBuVRSboQ3Z06fEbCG+hUspsNxjefHPcYQwtPuea+0e/zpC6gzLCoqdP7kh8PO9BvaZZiuMNn0soXzdcLV55XvPqy/jvJT/gibo7bpnwmHC/vh78vSozri8J/vB/QF+rpXQ8dz1APjQ75O6dM/uD9W3OSJ/sH4dEkWPDdv2TLbP6iUMdwsiB6jYmaaNx3pwPu7LNm1z9YtxWDJ+JsQAFc4t2idgPvsHWDu6IWknbyUtN/6mSqrKs61//6TDjt4PmndUvO2eWXMnt9eYP/jlR6F67dPbFWH1PMYW+kRNQQAWySpc0SRDokvMqh89Qooox4vmuIjo03CAVwphh4a7rWyooBvjV93Qho5pK0iXpBrJQWYAs+xSx25ojBI44Y4SvFx1PUhJS5UGt1SPxcVJQJQD0iPiFqi4c0XcVJXQscEnQtSeqpzxVl2LG8Nyl2SeJOWs044RmxYX+zoGTSoG7tPDdmGnDxbOmdQA+GwtXeJSyu6w5z4sAPO6Ihu7wsO76AzOyJAUSFVdqjsY0HBZ+gVOSCOdcITzZU2f822EeuETBgftGNyg84AoGcQz5YnJjzue7B1J/JM/0Ca06/8bdPWZThv/ru/kh//nSuOcvjvxMUk5MuGasMglNqntkQDEJueUP2zPnw47kw/XmFDw1Wrrz9rpSWl1tPb4yRFixYtlvS7XpOlAKdAJVKj1WvEq9eEeuz4cfXBoL8vXx5QSMijTzf93RVF/uHy3bwfT6bLIkukUm/YoO36yqpKLVLmuok8s3yEZ7I/deqU00HMhN/Z2eG29qFeMKnnqW0AGNasWeN2NOrP1DtT3XkCCLQtaADcG53+6LbG8xwexcYBUra7YZfGZfgu/aCNID0GuD3x4Q+NtO2x6jj93tP1jl/YuX4hv1zHfdYdtTv6PTtUfSjHz3DZ2kqmH490dXVqx+eIxQpiNiDATDrLRKninAO7RMHYM2SrV68W0CyyAwcOqD3RH8wtcJcsWZLqo0F+yXe6PEGmbqaP8OTY8chwmOqWPoyhHxYTAF3GitHPBXm5dPGSMw7EGEkfZ6GAzm60plA+Fgb0A8oCdeacdr2Ceu3TQiFumzdvGjVGpfMVlJk+uHfPHivSziFxsLjwde0yNPsxUgOzIHqkKmb2F1aVB/f82B6svm6VAr6TcXChNa7c4K62DrrDg3XVMosiIcHiuTFr7JCkV4cES+Ml0m8siZCQMxYFPXoYECjHUEuhDsJBTWA8TWhiBwSXy3hImNv74u5uu9Ssg3QC0YT72Na4Pbg03443JO2fdnZZT0IS5aI8+8rTpXatbcB+oPAJnehbWh21zz5SbOWShGdzlKZtoFB51sCuCTcf4B0VCCWRqThF3zcok96iclRKsg7ihz9+pS1izd25Vl5stqhswA3Kvvwj0evZFoHkf9zZZ+eu9WiFoWc6hm3HGuml7ovYC7u67NzVpJXEC2xzba49urbAXjuUYycvK83+dksOtNond1TYgqWYOw+sIY7ErS+UhMXGieYi68jdYptWbLC4pD0MyHeDY7BnkPeTQ7aBGT8mbS9FyhZmusuCtPjYsWP2wAPrrEgAFBduF/67v451n3JVVlTI0NRVB+y6JL1LCJgzCeEGBN4oG/H4q4/TX8NxZ/pRF9QLkrMHHlgvCVSfnTxx0kmK8gQ4ly6tcfcAnADKNvF92zvabP269W6BEI6b9AEWjA0B75i7t8ehi5lJvr6+3r17KC2rVq0SJ7xav4P+Sln5a9LWPtbRoNTgWNz49lCd2lY+Kctp6LqnPi5cPG9rV6+xAoGDPe+/n5LGp/u0r0N/5RnABhz1Zz7yjJVIAjorhR7/vdOWjh476jRuVVRWjeobPOnr1l/H88PYUoN2AVCRh7SU97182XI3XrK48Rx44hqSViOuvLPJxE24gf5gF2P1/NVOgABIDtr4kONfMxaySGtubpFEfdAuIm3dvFmqVINzGqTj/9gNuXb1mnY/bgT149fY1O4q227H5bgWvLi5oryt1kIQDWd+rPTlp+/TfhcvWexoSPQpFjdJ7diws1etPnXx0kVXZhaJHAxkoUhclLujg12xIH8+Tn6FvwO8D4pa88lPfvK+1wsd1NTYn7Mgeuy6mTF32Bo7eXCvVDXss/VrNCBNUDJAGKA224E4nl0xX2rbdAjvQpN4zUURO3213xbXFEpymI54UDzmIUlnvcvTAcICGRDhOfpvS1JbSpIED+bErEMAuCIaUCwIf+hsr51tHLLf/JlKJ81+79Sg1dXkCSz32KKqqG2TtPvPX2m3oxcT9t4JaffQ4Peh9fm2+2TCGtulfzoeSDkpx9W2QR3wk2RT5sqTUq3XrUEaDRwNAsExaBziU6Npo39YmkIknfYKayJSS5eUbFlGt7VgIITU9zm/qAPf6Lom/jZxmpPDMTfY77tSagcuViGWtGdXXZAlyKRVx0VZCVU4g9dP9vfaO0d77Fc+UWrnGwftu+9K3Z4OPDZK011D07B9/vFSV5Yf7dEBQtnyfnHvsP30o1G72hyx//LikD1Y22fLF5RYn5T9DWsRUhbpcnxq6o6k+uV3pqnQatY+ZPMljWCiYnK5Gxz5YKLkCggCvGSzYIh0hXBMeLc77wA0JqKktkSXLV/hqik8oUyl3sjr/PkLNKn1GkCPeOrq6lwZq6rUNuQIA6hmUmNBcTOOyREjMJ2dqFFkURoADgABUii/fUuaDVcaHNebNEs1yfqyce1P9gt0iIwkAB68F/Knxa3U5UTUr4ZVNzi2mAcFJAjHGQnaMVKwAcJpIUhc+AfxpE27U7f4kQYdn/SS/dq1km5m6ptnFJNLw3+Q90LZGSDvSMS4AiTYoWBybxdPFiDBrgbgIRqNWaVAB/er5lRN2F54DuuENdU1DlRBC7ndbcyX7V688m458AfYffrpp917v5Vy0N9p+xjwoM1Vi/JUMy9Y/AWgUWNtXr4tWLhAAK5kykkx7xRLgkq7gdaUqwUc75xxkPbDu2Z8gRbEDgRgFFDKWIPU1TvXP9RuCafTEK5PeEDr2zX9hP5CnPRDFrI31Y/Uzgd14Jpnoc1EY1Hr0jkKfvs0fb4oSyQvovLNceWD9oYauqjGUsbUixcvOApZTP0hoZ0ppOwckuYcCuAcehRlG8vR5959911Hq2GxS78a6/zKWHHcT/6zIPo+eNuN0vF46ODrVltyRdYCxy9wUhLjtkFpqhhKWBVS1ixuydx8e2hlkf0ff9ZoZXGBINEOPvNw3N45lGs1pZIkSLdzXHqK4zFNkMJuSKuZKlFv5yXODDrgh5gm1ATECBlLiaR4yYDTpzfEbO3CPKu/Nmz7D/XY89vynUT64vV+gdBugeuILZmTtGLpfDt9QbqWZTHzkbURWzqXST49QJxsKrCGM5JuFS+0PElx0TNSpq3C5niFFQ32qZwD1hPVYbeuRoXRgNEfcCv78gtTfgutKNltg+I/J/JiVtV93ZqKBH4GmmwoEreh3DlW0dNsrUXVGkQlfZd6u9b2TvvBgRJZVmyTnmeVOdTLsIJ44fqwbVlRaI+s0qRfEbGDF6nzYluuM49bVw3Y4fMDduBMt7V259je0xFbXjNkj64plAS+2F5494rAiIC8FiUDyvugQAi0lBGner10fdCu9i2wRx54wE0SDIAMjF7lGr+pfyYC6opBOvO3r8PMAXwkHX0hDHFkOp4BfJErH7cPS/jWluYR4OzTCcdBXhjw75QDiJ2UtGb+gvlOknOr6bIwwFQ4YBAwAE8XxwTty1shaTV//vdU06SOvKO5X2sEXLY76S0T+7lz591ttINAbQAAn6mvt/qz9SN8b94NZV64aKGP6rZeG5VHAD5SMYCLl85nJkrZEjr0B4CgHSUSvaqnHLfQWb1qtaOD6OcIuPBhCQ84AhiN5zg8ihT6y1/8sgNWvK9wfY737P14j7ED6stcLVDm1dz6OQUWX0t06Ja2R/v3u2T0ed8n8GOnAnczfYT3GaYsAkwbrjbYujVr1e4CS6kBMB602qW17v03NDQ49X2AUtKnf3AIGgB6J9oHeezs6nTc8BUrV46MkZltjrywGHX9Q/UHqKbdo3qQhcIKUVegrSBFZ/6FokZ4xl63eFAfHKtOiZt6AJR/+tOfdgB6dpcm8w2M/h2a3kffmP01M2qAjlZ/+pik0AdtxZJADRvghokXpz7jJKrsqOKHBcGyiHQey+S0DxcOwzPxWI598cPF9siamOgUQ7ZyUcwWlefY//mFKqsoEUDTk596SABTMx16qJt0kHBYIDQm4BcR5QPJbIWjUYgXLNCZK8BeIN3GgGfSwhUVF7n8xKT5ojKuiVRZ/7OftFtFcZ6tWpBny+f1KO6oPb6uwBbNlSSxod1e/VHS/uVHywQ4dYgkVb5Hlg9Y3yKAnlQnSWJwqadQgw/S5GZbWCJrg5IeSJ5MknLiTNzgbvTrGbjq6CzFeS0uNEr6BoY0ADdJln0iadvXDdnGeY1WXKItfKR0gu7khzpmkMICI7xVV7/9CUnk+mTIJtf2Hh+yNw73qUyFkjQX2oGz0qksgni+CNadsnwIjSUiIK+x3S2GoloE4Aa0aFEOXN1Bgdl7pdwWrnpWAL3CSTqhKby78x1t8V22OZJgbtu+zTY8uNHQGoEE5sMf/rA7xLdz506Br3NOP/JlgYyI3tmHn/jwmJInttzffvvt4AR96r2VlpbZI48+ant2v2fdvX322GOPOakTedgtv49//OM2x23hy2plvHjMwZwBn8kBSe3t5kZfuHDeHXbapC3d6UwLCU7YhSeu8PdwmIm+00eR7PqFEO0pqjrKF1hn0kfKhDEltt+pPyS2SKcXS6qXp/tMsplpZ1sITZSPm7lfXl5hOx7e4QAK+c7m8EeCSDvEShq81qamFic1LpDEGCk2tBBUBSL1q62ttVh+zFFx4IE3SyXXeCAaELFf2/vQP7BOCCd2Ot95tjLd636XL11y4wR9N19S/+ly9G3ed7g9jvV9KmnSD1i84ugvtBPSoZ30q3+0SDqL1g/AIe3hwP4DTupK+GwLKvIUzhfhbodjvNixY4fLw3htknZeUlri9JuzIOX9MB44brkyBhhHIs3ikjjnzZ/naBzd3Z2aAzSuh7eMMwrCwp+xmgU/u12MF8Q968augdnaGbtuZsSdLh3KOfr+j6Xx4aIkowFQDReMQQYHyBsQ6EW7RExcaO/HNRzG3dAHB/jWLoraUlE7GKCkZMJqyoIBkShLCwPeNc8WSgIdExc6RX108fVINzIUj6j1WpfBF9XWLpG7D74E0ms3IAp1cxCvoXnANi8rsqrSXOuSGrc2qdl79UC3xQuVl8UFdq5RlAhxpN2zqXjQvMEBROenyOdpAInLAEq+5N+BfDD7ZO4eGOMDWyaULl/lxqHho0/mxOdVDNmXtl5zmk8KovDFZYVR6XtAzxW++OpFEfu7N3rtB+/3ahHSb5eb+lQnhXa9A9mI8qvq6Jae6LbeiK3UgmHn8YT9ZG+Xdeog4oUmTQ6KB+uL3QLWwznSMz0UtxrpvaY89U3SEhJZb8/JUEhUAygSid/93d+1c/VnbK04tIDp733vu/a7v/dNB1S++c3fd0DrySeesG9+85uOR/c7v/M79v/98R9bvjQgAHrGkhhCV/g9xcP7f2DNKmVrWFKbGlulAzv/73/8Qyc5/Lf/9t/YL//yv7LXXnvN/v2//7+k0mqFBudgex7wBieX7d1MaQeLPyYDANFY6bvKv8UPpGx79ux1h3CQOt3tjsl8jrZxMVRDvRfqHa9evcpNdo2qR6TqLE5WrFjh6o1w1HOfAPUcSdjm6cDSnQAE2eqRyXgyEzLvfMOGDa4tUkbMcdNGFkhyeV2UAvKPjm3u0W7Wb1jv2jmSxyodWhzL8Vy9+gE89cc++pwD8wUC6bNu7BpgUfbPL7/saC8cVJtuN91tkfiQNC9bvmxksUZbATgCmDn7AHhHdztXpN9rdAC3U4vOAlGI0J4zmTY63fVAfORxMmMd+UZKjxCD97NUC0n6DHMldBWAMO+KsY2yEBZNNNBNKlTePj2TzVF3xIm2lK06XE3fyhQEZHvufvebBdEzvAUcP3bEOht22vZlCacXOoUts5YajRxQL2KjKYrZwwpwE1exOMXoX+4c4NBgOij3AMrQDoqkWq5XhwyhckA94N6wvuOAoUx+Hmji+/j6IltczcE5Ez1DZrjXxmxBea793JNl0kMttV4KvHmFTgtLgv3gsgLbeazHekV9+ND6Knt0HRYM9WDIESc8YZjNlXnX3R0WDBOpxAtFMeprVLxuXFAC9DUPW6m0dOTkD2mxIGoE9zQgoaGjR+XuF8gulYEZHAuJR1aLu9Y5YMcvSpe2qBmf2FElVWgVtljgvqt30I5I5d2CyojtUH2u1uKA+rnQKDPeer66lHgkvVfqEl5LIj4kPdXaOdDNjkSuHbteZuu3f8INokwQe3TC+tChg/ZTPwbPQC8AAEAASURBVPW8/cqv/IqTKP3gB993A+xHPvIR+853vmPf//73rblVB08PHrBf//V/Y3V1dapDWaQU+BrPUUb+PvL0U/a1X/s1F5Rt0HLxbgFuaFX4wQ9+aI8++pjbeiQA6qU6OjoFAovdAO/jyEyHwb9cemRzJcm/ne6EDvJcEWf4M89/xk2qtzOt6Yqbg6L8w+WrvuemVAFykp76ZDLF+e+ACN4HoNPfcwHu0g/yiRSM9ksZwpKzCvnjKAf3cFAAAl69aCCyhun7pbsZ+mCBcUKHMDHggY5igEc47lDQ2a+qAeqX/sFu1Ze+9KV7pn8wBrGb4Z3/TnuCqkH74s/3j0UCzizacfdKe6DtMk7Tr8Ogn4OFvlzco59Q1uXLl7nyIbWGrpHNQbWqFyWkLFVPs/0jWy3d6DcLom+skxnjwyp110vfsdriizanJAC9YxUOgAbYlRpiB9bGCoc/QLCnPyLZcYHVyOQ31gKjkRtXtwBVIBBQDD3KpME3XLGe4bcYClIzJ7qH8w0+nt4Q6JbGr64m3xbOhX4xbM9tLrQnNgTmxlFbNDgU0xZdjm1ZFtVgorSUGPTTcFzESH47JbnOB8wPy6CCy9GQLP71OU0hQaoTfxJPYzI+8pxPRxropLovMDiDn/cnRrSPsJDwjsVCiVYbP/NosaOoJJH8qxcO69DlkjKzbUvL7UqiTPXaoYOYUlemQXC1pNFdYm60Dpfb4YtnXFQsAArFIZecW4sTHW6UZLq+Nd/6irbaqjXSxKABMSkeHHw+Drr92f/4M7elt0WUhY8993FJ7zY4qcfnP/95J6k+ckSmj1csty9+8YsBjUKFHX0gMlA9Bt+WFuIH7oGBpP3opR/ZkaPHNXgPOqrI1772NUlDeiXVkaoo5fC7L/yTth9VODk0MQCOmawY3MfiG3KPdJCm3K6JDWMbL/3zP9uqlatFMQmsE7pM3qMfmQA5qEPVourydtXh7ayqzPKQVrgcvnxh/8Xahs7mABYcjmOb+0G1fWgcbFXPurFroLu7x94SXWvd2nWOkjV2yHvnzkTt594pSbCQzOwj4d/hsnr/Si0ukHajLSfTQZO6pD6yZVYvdGbVjPt7FkSPWz337k0mjXfeelPGBN63px4IVASNVxoAL1APsDqRAwgGklVRDCRtRtKKRNofGuR5YvHSV36XCGSGXY9AX0STexRJ9WCnKBGB5ULiBj/5XAAyOwdj0lctSbokwPC+UCcHIEbXNOHgDAO50KCBeiThzpAT2FZdVMZ0EEOB+4R48wa6rAKT51N05A2+uJem8zgHMa/1V1plpO0GQE4KqPPD8Z3DUZ7ewYEvqbpGv4bLt05QWa6YGr39ktYP9znedExhzifmyER5k5Xr8GZHe49t0oKhbgHGOQL6TdtA3Ipl7KVPeqFPNS22uk1P6HBcuZNAoJWlrq7Ovv71r9sLL7zgNDT85V/9pX37v3/b/p//++v2pS9/yZ566ilJi39gP/nnl+w3f+PfOQn2OfFRpTBFJt0DAEb+4df+8Ic/VNjvO4n7L331X+HtABrbi6WlxS7NIoETdBIDcObpxP1HP/Zxe/F73xcvr8aFZzAPgx/UMiEFQoqa6eD2SpjiuKuZ9271N/0Dbiyc4Y2bNro8IbmZdfd2DQQSaS3cM94l7ffEyROOzlIl2g6aTcLt8N4u9fTnnv5x+vQpR3949tlnXd/20trpT202xjtVAywc/eIx3EfoC3ChocKgIQWg7YH3ncrbvZrOLIi+V9/cBPlGL+b+N1+09XObJIUehSqzPokxFMFPgejRYDczMJLVAYUF/AJhOTzYL4MlklOOBPVW9eIyYiIc6KSxWBXEQiFgFzesOJL6gzag4w8Wk4RzKGVsJQgRfJJOuVONFwDRxkShA1YL472SbadBDwC5fSBmER22K5eACcCLa0sGlBLMiiNZrcrrcGA1IXBOiUdptggeGfMzKTwczbBsCJWjLCJrV0KcqSSzPt+txQbAF2uC3pHnbkn0OXQ5KJpDNMpipN/qSrpcyVhYAKiHFVC4VLqxc+znnyq1Qh3s7BSFxr0xlalbALq5K2K5xfNtca0OWonLxnY4E+HZs2fdqe2vfOXnnUqkd3e9a9/8vd+zN7XAAkSzFQ5n7uDBg7Z56xafNV31bgVu4REy2CLZ5sqhthy9cwZd6jiWH7XndODoV3/1V92zAGp4uFiUE8Q2KCNnBF5+8KMfufvE0yYtEtA52HZFhzLqzwo1aGeCmlItBm6Xgxt58MBB27hx4whtgLTIA/Xm8+K/+yth/Hd/vVk/nptN7/bXJ2AArie0nccffVxtr/SeoSbQRj4IB28cjRwrxa1ntwgAHW6rt9r2s/UvyhlOg98+HX+dTj/imk2PWtDhf501QJ/044/TP0rc2Bzcmf2cqAZmQfRENXQP3mcL/NCeXTbQtd/WrwXcTgyi0Z2MFomJHMAJ6XC+pMLCG5KmDoh2oAMM+u4dgDKmJLmPA3j3Dsocr1NxF/hhnTBHoHpA6LB/WFoyQs8HIYJPYDKSbsAqUtzKqLjBekYs6nAwB9axhhhRRoZAqylXKIm1/0XeOwalz1rxIJmKilScnwW4+2fDVwBvp8x6Fw3KcEYUiEm5MLois9t5gZaMcPjM7xxwHC0hVwg9j3S6UIsNOOKqBfcY8ZLPuCgylXnSGapeCqcbXdJDedLZKRqKVJq4MhfldNmlZIk0clTYwvXSfCAAzYQH/xPA2i7F+n/xF39h/z97bxak2XHd+WXt+15d1dVrVTca3QCx7wCJjaQIkaAokqIgaTSmHhQKazThB8/YUoTDYT2MPLbDoReHPaEJ+cGOsOUJ0iOFZFmiCYKbAAIg1kajF/S+VFdv1bXvq/+/vHWqsm7f76uvGtVV1Y083V/de/Nmnjx57r15/3nuyZPf+9733Vd/9Vdcd88lRQOZdoQK4wViLzOABqDWCB5Hjx5xf/Inf+I/oTPp7jvf+Y53/SAP/nKvv/6Gn7D24x+/5jvhJL3a+1/jKgGYxwfxN155RXlf95N3+MRYK59e+9TITPPwBWn1syUP1wnXEZMzPH+z+wwGWHSACTiAaHuRpvkh11pRrjaG/GN9oTby769Gn/SH7777jlx2WhV7eLvu3Whly6dddMvgmxBpTz7xhH8+yW86D7ek2/Nj20LSyBPysec7nWY8bVsIb3ik83Gc5p2VZvXYNs0ni3dWWhbvrDSrx7brXR/10te//fbb3qDCxEos1dEKzZUojCKILkxPt1UuIh4c+/if3D3NV/yS2YDHfNQ/Uy13i3GBsxUyikmpwGyNIm0AjIe1zPe0Ims0ybprRFqdJtGF/rT4BJfIwo1V2ghgDFgE5BbPTmr1wkpX67SCX4roD0fmql1DsRZqIcqzgPe0XB8mNGGvUmUDlt46zuRI6qbNyFge5KF1WMRnBfAaFMOaDqRQQvaGcgF/MYEPNDpX6QZntRpgSZ/kstTkXPovsiIT8qFDapZGtISxwKsWgsF5nIVdIMQimgnXQ6uB+3K0t1RW8HK5xVAWC7rnoTa+3d3mxos/5/buf8SHoMLf014YgOU/+IM/cH/1V/+X+4HcMVgy/Bu//mvuW9/+lm8/neU9imn8FS1+wSduCIDMZEBA9dCYYmsrtnWlRg5YmbFcG7UpRNiXv/wl13O1W1ETrmphGH2VmG7wnTKfgFkEg8+CTz/9jPtD+Um/9e4vfIxgwLWRAX7qND/r8Fxf7zXXtrXjhnOW52a2gIOjWgWPGfp8/g8/a9oL0bbwt33b3kzazZSJ9SXPVJYeCtUn9zdxoc+dP+++8fVv+OsdDhbhE2m5BhiAf6w5EtsV4QHXF/Sf7iuzrsl6pCGp1WPbW5l2K3lnyb8R9TFXgMWmXnrpJd/383ykrzdyRcrWQJEuZP63f3a5mLrGGsAq9ud//ud+UYT/5k//9Ka5A0re/Mmr7sPX/kf35bsverC4ErPrk2WuXNZgCwWXK/+1SUWFKNHMZ4FmfIGHtOrgkHDvriYs0bKkKm1Y7gmKxulq5XKQj4haMS7MOFGkT/+yrLKSIeA7C4z6CYrijwvGxfEmuT5Mu0ZZpFurtKJfUA0AtWd6i2uYuyJwyrLcWoK7fLmvdj6ZVnuO+obH5xTHOhAiD5NJub0QxaRBlmtA8IiWQR+b08ps0ieAf1ALrmwp0+qFeWhSdUIMFEznf3X4brfj7l9zX/nar3uQAEjFDYNZ2IQ6AqCaGwWrs3FcSCeZ7hqyyqTzIFtWPtLJi1yE3SPUGuGTuO+Z7IX7SVY4JQDuWlpFkOHjjz92P/v5zzQAUCxthduLdOdqgC8i3//+9/1zwcCO8IrV1ZtnBc/NqPmjR4+5f1DEHlyxtmvFukh3rgZ4L/xEXxLH1C+zxDcRTAoJs3fnamT1LYuW6NXrbFOXAKQcvnbCXRmcdj8+3uR9aXMJPC9ANqdYxiULgelz5bN0vyS2vCj8ND4t8GHRxz66lOSYE2hldZXiwD+aM6wSSCnieRhhR1WcDdUvbsWV2tdiETqPtTkk3B3mWUWwWIuMyNIJr3kt311SpNGybNdp8rbpOYUxWvBgUQsXs+DzTfmltOUyLWbM2BkvapLn9pAs0Yl8Xi7JXiwLc2Gksaom+s2prW6uTvMIFYqruNbNlFS5SrVHtnqdVuxsDVIgLXjt9+dnRxbZ+zxFVdJSpaueV7xc1T+vizA9V+8eeuxpbykGQANi8YnHcswxLhEsLkCoJ3OjWGSaZycXGA6LFJLH8pMXK0eyIliyGIJfDECAOhcfJooS9WM1clt9WVteGicU35pYqD9+7bU145tVV0zbeA0wSBtUSMXnnn3Wf6YmLnSue23jpd0cEpw5e1qLD11XZI7Xo+/45rgkt0wK5qMMaIXdl1/+qu+b41ea1as6gujV62xTlwA0vfDg0+6SLC6s7pWPpie0YMfoVVffJHAlMJZrapxZECsrqj3Qm5y8LmuwfItl5S2v4DN/uYCaXDLGSlxdI0HtlgjADVieVTzkEk0Q9M4QwpOAmVmsjFqxsEyLwAwqznNNZbJC3VJpgUlNmhse6ncV5fWuUhbfSb+CnyyYU0NKq/AW5zA/lsveK6OuqVV8GRwERmJkmdTkw6L5US/zrOouKcKFZKWPMX7YsFiN14cWPpmaUHxoLdtNpI1CaV6gcGhAS51PytWmQZMAq5dA+PREuRZI0ZKsYjYjC3VNZY0C419dfOkjxWxJmyZPXvVW3aHBSXV8zu2p2+XBIFKY1ZZ4oUboBJnZ2m+jPtkBhgHOJidyTWgFsTJ9OQD0pwnwT97m5iU3knSe1RxT/8MK4URIOwac+NdHurM1wCTWrR0d3sK2VoOxO1lj9993v6urrfNfifR4RrrDNcDzgWEjCX23/P19hzd9TZoXQfSaqHHzMAGI7L/3Mbf37of8akaAJrO8AFjYty3nsFJSJny52HlrFcfMbmeJUQANE3UoS3gwHjxzH8CVJHQVMD5WR1g3fndYieDFRAbKwod9K2dbm1xGncwixneW8u168JlIF7aPPOfl/2juAmGdtId6INpr/NNbzlsa/CjDMrL4Kts504GN3EMZ0nUaLyuLT64q8CtH4caA/lmmmXzMjNbG18UxZLxtH5kg+JSqHeMCofVaBrZWZY3w9UVvuErgx8y1g9/Y2Lh0rhUbA8Aa8rfyt2qLzAygbHVAZBofH9P9pAmTGRMImYS4lvJx3bu6uvwKbNx/a8n7Vuks8v10GuAeo9/Kchf6dJzvzNJMLuvQoIN1BqwPujNbGltlGqAf5P0b+0PTSOHbCKIL19VtlRNAEgLjTys8q3zB0wAcvLF28tDxMz+qrIewW6sk7dIiCABkI/LDKwTILFkKzxDgkR9gDtGhw4Ny1JO2pnKe34EDBxLLrPKEhOURUInfFyHO6DRsNaswX7hvQLS+XpE5JDP8ebnYS5ntaggAScgodMkEUNpGe5PByfRiW+GJSwYyWuxb0gDbWGd3yFfR9IIld3KSpcMTazO8qIdjQLndB8l1YpCSWIJtQII+1ou4frTJCFmpH9my7h2Aj91zVmYttuicaxDps6OBrPvrs9P61bV0rd8fq6s95t4IDcTn4+a0Ht8iN6e326JUvocCQDk8POI/k+cDE4BILLEGXgFw5AcIYY0FyAFISWM/q07iEGeBTdLgSxlAH/uAm5AHAAqwB4ANASfpAErk4AdgNFCI5RWZAY8hL/IBKgGnANlc8oYXlzJYtSF4JfVcl0V31C8fvBrrFmVZFYoy8OJn7bVBiNVNXs5ntSEcvNBOVgfkemJZBZCiR3SB7LQT3XKtbNABX8jAO/voM+sacW4tydob8kQe6mdrstl5BixMRMQ6ttaUrmut+Ud+UQO3swbi83E7X70o+3ppIILo9dL0JqsHcEakhpWAEyCGnwE/ABxLN4+PT3gQa0AUPrk6XQBcGjwB+gCUADsDhQCpNPiFJ3VTHjkAh7gCAO5x6eA8YBECICPHpMDkgHg3piI+kBeQicy0f6W2A2SpkwGCDTTgsX37Ng/64FEowQtCdurFCs1qfbQZPgwICAlXXp74BVMPAJjzIaEHZDGQTTlANEAfnXBtOMeqU0bDWjgBvcIvJPQOmbWd86tpU8irkH3kot1cA9Mn5WgD9wO6SdePrriukaIGogaiBqIGogY2mwZW9y16s0kf5bkpDZjVz0BnPiYATiy7gLrphYmKrFqH5RTQBTjD3SBtSQ15YkkEjIYEMAY0lWtC2bziPgOqWHgDQBUCR+pFBs4DIHG/AIzxozznAOlYYQHT/PCTbpFs5q9MveTHHxc/bvaxRg/jm5yHyAcAhTdkPAB8ELIVSsg4ONDv20Y5wCKRAmgrfJErrSOTE0uyEXyQ3fKis9bWLR6Ycy1GFO+ZLYMc0yPxnwGuuQhZ4INc8AdU3yqiDtoVEtcQ3/CsQU1yX9y4JHhYPu5HDUQNRA1EDUQNbIQGIojeCK1vcJ0AMKzABrKyxAHo4KYBYARkcTw8jNUzAWeAS8r3Xe/1oC2Lh6UBwgHAIQGmAE21WoIXCyxk4C0EU9QLsB4cHPJy4KoAAAe4A7BwL+EHCLX2UB7+tNPS4I8M/MgPWARs5yP4IDt1QsgCOMWv2oB0vvLhOd9e6ZEthBW4RjPgkQWQzICktvZGsJi2zFIeeRjIQLSPtkDIxz6/PoWoMqBNXms31vs0GYimvZz3Ex/TmdbgGNltImXIjnT7hens04bu7os3AO90vngcNRA1EDUQNRA1sN4aiO4c663xTVAf1lqAE8AlH2EhNiKvWaQBboAtLL119cnkQsuXtQX0hcCYPAA9In5Ma0Jcx7btrkLAGBBIPrahbNRDnVhYWVmpq6vTg2pA9OzsnLfoYs0M6wB8AfpbW1t8OvzIA5lbQ5jfn0j9wU2ioiLxX+YU+Vmlz+RMZc95iOzIWqcBA3JQnpCAxQoriAWfawGQBuiG7WYfy3uYBp9woiGDGX64b2BNpo0A/Fl9NTDwb4JZ3XacteXrBPLZbyUdZfHIlcagjOvCF4SQLwMz2kBbaV9I6Ib2hjoIz8f9qIGogaiBqIGogY3SQLREb5TmN6heAB0/gGk+YAKIamhI/IfJjzUYogzAhpBp8DAQmK85RN0wq6jlAywBZmsELIvFD1AFiGI1QvxmqR+iPizPAEL2WYEP8GlyEOMyDT4pR34ANLJCgFRAHECcssPDQ34g4E9m/KH+kydPLbpyUB6gR3n0AY9CicECgNzKwOvixR5veUd/8Dt79uyiJT7kCyBOW71HRoYX9QnAJBwV+oQ/crNtaGr2bEyPHGD9tvrCOsJ9ynItaCvLwdLetSKuRRokw5vri4XarlVYH9c2nytKmDfuRw1EDUQNRA1EDaynBiKIXk9tb4K6sCDjypEPHAHqWNHN3CsQGz9c0iF/Xi4NgGNL8ydy/AEkhZZHsgHWAFRYtwHjEDKVCDSZf65P1B9AJ24PlDEwTTnyATCZbEi7QsBIfeTnPOnICR/2sYJfON/tj62O9Jay99xzjwd4nEM2BhL80nWly6aPk/YsPWq0d8+ePYv+3LSNkHXoKU1cA2sD55CfkHamd7ahbnFrMX1MqyyDBctLeay+K11/8mHRJgA/wBYZQh6cvxlCD1y3UF7jE147S2OL3hmE5Dof5o37UQNRA1EDUQNRA+upgaU3+3rWGuvaMA3gygGYyQIyJhQAMjzPPtZOsxQCbABrCThc2SKbjsZAPYAirJ0XLlxYtKoaUKM+6ggJmSgTTlIE2CNT6N4QlgEsIyflAK7mLgD/3Z27c5ZDDoAtW6sXvaED3B0AmKSvRNQPAKUM5SFkARTjzgEP5Mc6TDq/NKE7c6PhHGVwh2AwQX6s67TRiHSsupTxlOLJwKWyMrHqW5msLXKZzNd7lyYyZuUtJI0vEYBhdJImBjcA+3DQFuax+y5Mi/tRA1EDUQNRA1EDG62BCKI3+gqsY/0AGIChWXNzVQ1Qa1ywEANwsL4CQg04AkJxxSjUV5XFVrDehgQvwCPLy8IPAuABzIliEVof7ZM+ZQCwgCragcW1pESTE1UGXiaf1YPMBkABaWZBpj7aBJjNIngD+thCgP2hocSfFx1muSRk8cHqO6C2pMExqwbyg5AFflj10XWaqA+gbLJwnol/8Ka95qJh5eCFftiWqf1M3KR+W4wFXVZXVwnMTmfWZ3zCLW496PLTELLCw651yAtZuZeQLU20hXstfW3T+eJx1EDUQNRA1EDUwHprIILo9db4BtYHaDxz5kxeCQBy+MIC2gAuHAPiQiAIgLt25XJePuFJQG4WQMLS2daupbsXAJrVB/Aj7rEBJ2TBT5p6serCCzDW1oZfdrJUKUAXoBzKaeWx1IYglHQszfDMIkAdPt9miUU+6qHM1Us9WUUy0wD8Fn7OMlB3U1NiXbY0+CN3KLudQ+4QRHNMW81qS9lQt5z/+NAhb7GnLvTEgODSJU3iDED6tWu9Odtvddu2Wu1ANgYtuQYeljfXFjlz+T0DlBnYZQFsBhGXLl3KtGDnqiumRw1EDUQNRA1EDayHBpZPhV+PGmMdG6YBrLVdXZ156wd4GXgkI+CGciEBMscnpjyQAxytRLkmhgHusFKzGp0BSUAaQBAZAIoGEAFxBiABg1hgm5ubPMAkrwFGtiHNzc16f258jo0X5zvlziGWNxD1UK9Zc6kT2QB4WT7LNzBYSKAdlAl1ySlAIa4qYTrHWFtD+YwvdbPkuhE8bSEVBhUMBAD8XBOI83fvP6DrtuRfzfVj2XV0Q/vYwgNZ7Nj459pSBp3cDFEPkyGxaKevD/y4nljXGWyFeuEc+TmfVY7zkaIGogaiBqIGogY2SgPREr1Rml/negFqgBmLyZxVfQKoklX1AGWUYUGSmcCCCagE0OBTXCiowpIKYE4TgM/q4Rx8+awPQCZ/X19iWaYeQCZgkDKAXLPOArCQGws1P9oYUllZufchxpUD2SHyjI6O+botzcpwjOuGWVyx+mLJph4m9BUC5pBndHTEMbEvTfDFok0eI9JoL3Wk5SEfspvlmTK4ogCgAd2NjU3LrgNtq65OwgWGdaA3+IT+0+gV6z31rkTkxTWGgQQ6Set5pfKTk1M5y8C7piYJ9ZfmwzkGEWwjRQ1EDUQNRA1EDWwmDUQQvZmuxi2UBZBmk+VyVQOYIiqHASRAGPtzAeAzPmEM6Vz8LB0ABIhLEyAQK3Ro4SUfQI+6sTRbOYAb1kqANBME7fO/7cObclkuHQB10g2IAlRZNIU02hMS9eF2gFUUwjKKNRjQCrguhADazc0tWkwl4RGWSVw8WpeBcdpCfdeuXlmU0cpkgWhkoS3IyqqHIbBHTww+mIDJICgk2p1O49KGYDvMn7VPXq6DrV6ZlSedhv4ZBLHNoqQdVZnnuSfxF1+NjFl1xLSogaiBqIGogaiBtdZA9lttrWuJ/DZcAwBVwGA+ix7nKqs0QW9BWkAPEwxDkAao5JiJfwAjQOFKhIU4iwB0PT09HhATccIIi2l9feL7DFhEjunpxA0CUA/4tUmNHLOCIFZSZKMNobzwNCBs/AHvHR1b/QAh7UJhA4iSkqJFtxL4kQ+wuxIZ2Men2wYAVgYgSJvT18DrXdenXWVKS5dProOHTY40PoB8iLrQFXUZoWvkpa50PQB10vmRhx8DFcjSjE+uLfLgPpLmnSs/7bXrxf2XRf6aaoVFfOHTOsYdh3sAWSNFDUQNRA1EDUQNbCYN3Gge3EzSRVnWRANmgVwJ+ACQAFolAq2AKtwMKGsAhjRAEWCIcG+5QFFaaCzE4wJ7aYIfluCysuVjOUBhdXWNB09MKsMaCdhrbW3xrgyAMspCtAmQjezIg6UamY0AYLh+sEgLYBqiTtrBMeWM4ImVFYs958+fOe2t2+zDZyX9wYfBCgA/5Gv8qZdJm+YqQjp10kYm7eF6Ql2h/OThGKBpbUYfpAE4Q39z0kwfWVZfriMyMOigHiP0w8/4W3quLbyRBz3ZoCNXXurkl483umIJ9CyZWTESf+5IUQNRA1EDUQNRA5tNA0sIYrNJFuVZMw0AAAFO+QAP50L3BkAPlk5cB4y8u4f4sAXw5ANGVobtxILPbzo/PFh0pFYAKiTy4fcLuMLdA7CLfMgDSKaMWSzJg0sHW8oBJA14w5NjeNmW+MyD/X3eggugBDQboATsYeXFKg4Ybddy5IBi2tsfuLmEsto+dRvQNmuwnbMtvGgPbTCizi1bWj0Ypjyxr9kawRf/atoOcWyRSmizDQw4Z/7WtJXrDchNE2WwqlMvxBYeIZ90mVzH1IM8+Yj60Gk+/uThemaBaO6/8B7MV1c8FzUQNRA1EDUQNbCeGoggej21vUF1AZqYrJfPkgqYIh+ABuKYFevMN5g0zjc2Nmhb6oEN1lOA1ErUIlDaoEVDDLiF+UcVtQH/3ZDgCWg00M+qewBesxADaoeGhhcBHPkGvVU0ieKAzLQDgAd4A7hCiZV33m1p3+pBK/oIASXgdWzBH5s6KAuww8LdIteVfPqjLqy5lMsizgMGaVtaDyUlSR3w5zohkxF5GWSQzj4/QD55+jUYmFXbjZATMEoeADvyp0EuaYB8dGHnKEN+2l/I9aQ+6gccU1euMv46apDCIMrqMlnDLbIwgMsCy/4rhspHihqIGogaiBqIGthsGoggerNdkVsgDwAG0GMAOasKzgE+zUUDCy2WzRD8AFYBfMXFJT4frgT5eFo9AEsApll8LR3eEwLHAOSQAJMARQCfbK8CpjNeftwk4AMB3ozYL1X7ioqSpb7JR11E4ADoUw9ykk77AGacRyeAR6M5pVkkDIA9oJKytJvy+dqKDPDPsqbCHz5YxOHPvhHAEf9y6qLdyAP4DPNQL2mWzpa0KlYe1Bay/OgMWfBVT/RnNS1tKY8vegha0QcW7lyDgKXSS3vUSRms3rkI+UzGXHlIp+1Z+mXwgF4jRQ1EDUQNRA1EDWw2DUQQvdmuyBrLA2AC5AAccxFgCEtg6BcLwEqDW/iYWwEANHRLyMWbdAAa4JFtSIA9olhk+bxyLgHxzk+sM3APcKfe2tqlpbcBYAwADMAaIJyamvBAEl5GgOqTJ056YIxuOLY2VQjANss1BPBpi62Y/gDABlSNl20BwOgLnSBLFgEQsdymXT1oVxgjekoDij7JFOoK3rh5AHC5JgBgzhP9w+rjHMDfgDH5OGZlwjRRBh/xcACB7vjyYHpOl8k6Rq+40oR+2WE+2sx1oZ7wGoR52EcegHIW6CcKSL6yaV7xOGogaiBqIGogamC9NBBB9HppeoPqAcgAdAAzuQiQAoABBBoBqABHIYDBOgwINDp37lym362dty0gCtCWBdDgjzXTLMxWxrtoyOrMljy4cpw+fXoRXA4OsvT1kgUbUIlFd3x8zIMyZGVxj9CKae28a99di8DOLLYAZKsLXgA78rNFF+ZOYfKFW0A0QBzAnYvgyfm0tZU6ALBsoXJdh2bJTr1GuFsw2RL9oUviJgOW+VpgwB4eie9xEgGDY9rGV4Ms4lojD20OeSBnOPExq2yYRj20CRBvfDgPb0B8vsGb8UGG5OvAkmuKnbt2rVdW+qXrbOlxGzUQNRA1EDUQNbDRGoggeqOvwC2uHzADMEqDt7BawA8r3AG6AHMeFAYT7shrfABNRoDzQqzR8McSnbZswwfAhoU75Es6oD60jAKOCfVm9c3OAv6WQCvtS6zRyaQ55MXKbJZZeNI22giARCccw4+6aTPWXuTEEgywg8jHLxdRDzwAsCHwTecHZGPtDwm9TEyMLwPgtAO54GtEPjtGlpmZJLIIoJq8nCcdneFuAyFLAqJzP+IAV3RkvCmHHtIDGtLzETpOrN5LIBi5TL58ZTlH/dwHtCtNDB6IWhIpaiBqIGogaiBqYLNpIPcbdrNJGuW5KQ0AcACpAK1chBWRPEYAsrQ1ElAJUAoBJaAVsBaCMOMRbhOwmCwQEqazj2WVJbgNHNt5A5KAWvjj8rB1a7uXC362ep7lNxDNsclDGwCFIaEPLNZYtuFDuwDPAGlcOJCjSYMDA/UsygKoJF5xmigPH+ojPzLnIiz4yBwS+bEUh2XhRX202wgZSWOL/FjubTIgeSjD9QvbShqgnWubi7h+WOxD8A9fBi+rIa4hZUI+3Cd8BYDfSgTYZkDGNiR40KZ8A8Awf9yPGogaiBqIGogaWE8NRBC9ntregLqwTqYX60iLAUgJlwMHFBFRIwRFAD0AVwhoAJEA0CwLc1gHZXCHwDKaJs5habzcc3EZcCQfABAwCXhUVapnyp08edKDXwDolUs9ApdDy1gC9AGcALIdO3bc4MZiIJE2woM2VldXLYbBo64Q1GKhR/YstwjKA1b55SPaASCEb5qQE5ngBaGPNPikHGlskbtG8vZew985sfxSBtebNAhlNUPO5SLOcQ1D+ZEDedFjPgAe8oQPsnGtKMOPeNjwtXaF+dP73D9EYAm/LJAHAG0RWdJl4nHUQNRA1EDUQNTARmsg9xt2oyWL9a+JBgBJAOl8ZCCNPOTPBYoNeBovABIAM/SltnNZW8AV/EPCpQBgXKyV+tJ8AN1YoJnUhz80dREj2oBZVU2t2rbkxw1f3CrgY24KADkssgkQT1br80BUvA3ksbALS0sTj7k3BR6RF/1YnaHs7DOwSIPXdB5A/eWL3elkD6yRM+03jPzUaQRINd0gBxMK+RlApm2ct2PKsU9ovJCP8bMtbSOmNvKF14WyKwFw42FbdAng5d5Bxra2LcvksXxZW+QfGxuXPpYPRrhOfB3I14YsfjEtaiBqIGogaiBqYD00EEH0emh5g+oA2DD5L59FkTxEezCrJsdYIdPADpBpUSzC5gB0IMrlI1wrAIxWj+XFCstEuVxgCWskYHrv3r2+CAMC2kN9gGpWtAsBIPxCwEm+8YXIGuzj9sCEPORAHkAf5WlHfX2D26oJkFYe6zF50q4tCILVFXAe1m1tSm9xVdi2c1c62YNNAHho8ScTLhsAW9MpOrh+PXHXwMJL3ZUKbwfYpR24p6T1ilzw4DrmkhGwi7U+PYGU9qMLyGTwB3n+0AYmj6J/qErLx4egPk9R70LD9Te9kxeZ0X+hPPLxj+eiBqIGogaiBqIGboUGIoi+FVrdJDwBSWmf17Ro5AktrYCW7du3e/eBMC/gKMsiCMgCrAH08hFAOAsoUx98AcaA0hC0AaQAgfAnH+cAwb291z3QNKAIqDQibRpZtIUvIHWbFluxNgK8kYV20ybAn4FkGzhwDqJO8mdZmjlHuuW1+tNbQDp800DZ+KddN0gnL4DSeFMXlmHSkXl4aCnmNmmA9KxrAy94GB+Os4hrh95C4hjLMoC+UKIMgw6uUZpfPh7UTz1hGfa57kwojRQ1EDUQNRA1EDWwGTUQQfRmvCprJBPWSSaPAcJyEQArnBQGeAHUhMCLNPiYlTHkBW9AaS4QZ3nhAVBOW0yxNiah6caX1Uk5ZMDyPDeX+O1SF/7dSSi3ZFGRUE7KALwGBTLr5EMcniMdcEcasgI+aRNyAaIBywA55DFCVsBsum20g3TavRIZiKaeNFEfkwTDOslDfbTbynBsEy+RmUmK6IJyhH/jXPoa004AupVL123HXOssv2PKI0O67VYua4u8/LhPQt1n5Q3T0DPhCq29nKM87cTiHilqIGogaiBqIGpgM2ogN7rajNJGmValgauXL/lP//kK4aLB5EADMAAamxRm5QB7WS4DnAfs4ArBNrQiW1nbwj+xbC5fwtksqYA93ArSYBDeNTXVi8Ae8Mqy49SFW0YaKAJsW1u3+DyEj7PJavCnbVhKra3wwPpNHQBGAGXYBrOqWhvYcp506i6EAL3pCZlWzizL6TZTBy41yAOxpU4AN/LWydWCMlyXnp5Lxu6GLRb6MJb0DRmUgDWdgQmypMkGR+htJUKn5GOAQ5tXQ8m1T9oUlkOmLLnCPHE/aiBqIGogaiBqYKM0EEH0Rml+Hept2dKWaT0Oq06DX0DVXXfdtQzMAlzN+hmWtX0ss0TKGA/cKuycbQFDHR0d4rN8CWfqB8ByHovw8PDylQEBZ6QboByVf/P13mv+GOuyAWHAJZZZs+JOTeEeMiDrdwIAaRfuJFv1M9BKnVjhAX2UtQgYJjPgF1AYEvLCB8C/EiEbv1xA0KzZ8AyJY2QyKzDyEiWENuCbboMAQG5XV1dYdHGfPPyoPx/BGzmyCDlwRaHOlYA0dQ0NDfv8WN9XQ9aesAwDAAYOaSt9mCfuRw1EDUQNRA1EDWykBpZCAGykFLHuNdcAwAQQlgvAWYVYAQFjBuQAXYCg0HUDoAWoM/BpZW1LHU0trYugz9LTW4AYP0Cz1Uce3CwsLcSTACjAMecAuLSpSvKWCUwCKM1tgH0ISy1W65qaZKlp8wc3kOYts/LzbVO8aVuUBEs8Vnasuvfff78HbeRPfs5btD1z/WEJbdwOQn3ZuawtAJQ6iTCSpTvzlcYSHhJ5qcPkRr9EEEF3TAREdwwqOI9usog8hViE4YHeuFdwaQmvC3yRbaX7yORsbm7y9w7Wb65JVpvTslKWaywndlnEmxfLFFJvmlc8jhqIGogaiBqIGlhPDURL9Hpqex3rAggDTvNZ8gAwgwP9i1ZexMPHFgtgSADNAeXLZdUELBmgxTqci7BYc95AF/nYByQShxngGAJU+NpEQMAoP/IC9MzCSxo8AF11dYS8SwApeQB/nKdO6iZUXp2AYhjzGaDJqni4NABSAZRs0d+1q1eW6Q+rNsA3lx7S7aYtuVw5yAufXLyQu78/WQAHebAG87NIGsjHL9Rlun7OY8XPl4cy6CDUe8gHKzVAnUFGrnuJegDOXC8GZfnaHPJmn+uE7hsbmxYBNPKiF65fGtSny8fjqIGogaiBqIGogY3SQATRG6X5W1wvYDOfC4ZVL7yyDGSx8AkgKCSsioDTlQANYC8rDJ7xgo+BQEuDJ0CZBU8oj1USwGYEMKMtWF4BsQC5gYFBDyDJQ3lAFwMG0slrxLkEpCZW+aSeag+mAZcQAJB6AdLUBZiEB+ARcEeaEWCSSBhhHXYuvYUvoD0sn87D9QF0ZpHpnHO0g3/owEA3cgJ+OZdF6ISBQ9ZS2mF+ytMuAGsuok6uq7nGpPNx3uSCn1ng0/myjpGTaxq2A16DRAZZuEZZ5WJa1EDUQNRA1EDUwEZrIPebc6Mli/V/Kg0AAnP5uhpjgEtTyucX0JcuF7p2WNmsLWCMWMG5CPBJnQDM0IUBsAlwbmpq9ADVABUWZMBbR8fWRR9kQFdDQ/2ijIBQrLYAN/yXrazJAFCFAGrIx3kAdKkWdwE4YnUnDcDMvuVHD5ULUSaoc1i+2uXlZcvktjqyttRHO3MBXQAxbTbQnuYBiOYHIecWLV7SMNXg9YNOSMt3XWgTvKG0Tnxi8Af9M+mTa5c1QKAuBla5+CCHfYmAbeKmshRRJKjqhl2A/oULF7xveqh7oqtkyXIDg5gQNRA1EDUQNRA1sEEaWDKzbZAAsdpbowGWw058TXPzxwI7MjK8aEUkJwCzp/vCskKArEKiUQCy+AF+c7kRAJrOnDmzzPpNGQATfspYiw084gedALvksz5geXJyYvE8QlIWcAxgpBxtAvQacR7LJnVaGwCEjY0JIGWyI3WQj3LUweIz3d3dHgQbH9xczNpqafm2gErqyWWJBkSnXVtCfugP1xKIvETroH70xDnauRKha8qG+sgqg+6YLJlLVsqgH0A/PI3gy8ADWThvBK+WluUTMu1cess1Y7EdBhtG8GUgB3iPFDUQNRA1EDUQNbBZNRDfUpv1ynwKuQAhxcUA2iXXhix2WEvHxydkXU0WHSEPgJSoHmmCJ78QLKXzcEwewF6uvIAmVh8M+QCgyA/hMjA2NuotwoSnKyoqXswLIIRYHhpAh+UZUMcPKyb1MkkQEBda06mLSWtm/QYszs4mriP4R1ukDSJ1wJf8yBNaQgHEhRI85qRbJkHmIoArv1APYV7TI2nwA3CjJ9qInCsR5VmohBjbNijJVwbAmksWylEvAwwGB6Fu2U+Db+rGWs4gKB9P+NqgJ8zH9Se6Cl8HwnTyR4oaiBqIGogaiBrYLBqIlujNciXWWA4AGiAmHwGuAKKhxQ9ARDoA2wjwhoW4EEBDeUApgDW0WhoveJAHYAjYMsLSmiy4Madyie8vlnSsrkbIwA+gj0zwog6AGGnwJS0tJwCwsTFxD1hqF5bVSW+tX0pbmuyH/tADwB2LsAF4kyXflrz8wvaF+ZGXMH20MxfhpkJUDwhdYq0lzN358+dz8g15oYOammRhlrQ+wnwGeAG9ueQlP7pF9zYQsTZyj4WDDfLCh2uH3lcigPlgKm95eYX3Fc8n90p84/mogaiBqIGogaiBW62BCKJvtYY3gL8Hadd7VwR+WGPTbheUvXix24NcEx0rKK4Q+UCW5WUL+MEfmOgWWWUA0LgBhOAVf+OSksQfu7k5mbxXW1vnwbHxNvBNecBcAhSTwQLnAHOAaQAe4MwIQHf16jUP7Kwd5GUyYdqHG+CM7Cw4A5EPQJ0GisY7awvArxfgRKZcNDuLZT/X2cT6zCI46Ojatd6FBXGca1IUi0LAJXrnWoY6zqoNXliXDRxn5SGNfAy28HfGvQcrNzrOur7oiqXjC9EZdddr0GVtAnhj3V5JnlxyxvSogaiBqIGogaiB9dJAdOdYL02vYz0AEtwU8oE4xJmcTPxyASyWF6DU3r51GXgF2BDlobZ2ZXcOa6a3crdkT0YDZPILCXcLI4DfpUuXPBAzueycuW8AwrGe3nfffYuyUyduF8Na9hugbZEviKgBhbwAmABC+OEe0qaJewYU8ec1KzpAEKBXCAEoAZiQTZLLKud1rFjV+QgdMBigHYODA7ICJ0CzQb7chZDJgvzoxUBqVlnOF0qJhd1Jz4lOc5ULXT5y5SE9nY/rSh34qhcCwvPxjueiBqIGogaiBqIGbqUGIoi+ldrdIN6Aj3R4tixRAJkAxBBcAraw5oYEr9USMhgIwtpt7hbGx1tJBWTLVRd1AlqxAJufMGXwb8b/N3Q3waUAgAjwQ/YscFikAcS0QD91IAOA1MAaZc2Cek0uJLiz1CsqCMQ5+DEA6e29rDBrhMwrdls7ckccsfbYljrhk4s4R9uQK63nsAzXhh+y79q10+sGQG3tCPNm7XNNaRuUpSMrwwCJcHJEIilksECeKV0nyoX3jfFjSxuPHj3qOjs7Fwcy4XnbhweDJa65+aVzffPxtrJxGzUQNRA1EDUQNbDRGsj9vXmjJYv137QGAKOELAOM5CPOA+jS+YjYgfXTiDwr+cxa3qwt4C8NLLE2jo6OLNYNiMYyDAEwu7o6FwE1aUbIiiwAOCzMWQARcIorCPyQHaBmbUQOrMUA813yM26QKwGA3NwUAK24fADq8Fmubyh8AAFvQGC+QQd5TC5rU9YW/bC4Cm0dGxtftYsD9SRW49yAnnrRX1lZaU5AnJYNvhMT4z4ut+k0nQee+/btWxGUkw9d2RcDdA/lGhyl64nHUQNRA1EDUQNRAxupgQiiN1L7t6huwAm/lYhlrAFpBl4sPxO7bOU/0gBjgFEA1M0QgJSygFcDXriQ1NUv+Q0DpLA6m9xUlQXw4UP0Bvy0sVRnyYS1lkl41IfVGWBrfAHfTNjDbYCyZk31lnGBOPIBsJETgD2hutL6ydIBeVjwBT5WV1Y+A/+5Jn0iEzyG1L6eiz3eQk8bcKcxy34W33Qa8qMjc0tJn7djZK1J+Z7buXALP+4DrlNLK8uY57/Hsq5LyI996gYwmzsJgy10GClqIGogaiBqIGrgdtBABNG3w1VapYyAEoCrAcRcxQHLW7a0LnOXIC8Al58BIfx7sfquxC9XPYAlwBwWXgOk8CLdjqkLCy1WdAhLusVJDvlSrlUgDsBNrGd4ZBFAGqAKIDYXkTDf6PCQO3L4sAfqpJPXgC1AEQAPDwXZWwT+Yfn0PnKgs1zyWH4GLoDRXLrk3JEjR9w/vf66u9B9wV1QNA7AM9cgVxnjHW7JiztHPpcR8lMfgxEAbD6yrxtcL/SCBTlXW7mW586dW9RtLr4Mck6cOLF4n6E/c+vIVSamRw1EDUQNRA1EDWwWDUSf6M1yJdZIDgAMgIjIGzU1uZeFXqou26JIZAishABLb4UUuMVvdiUgR/380vkASLa0NuchA8kAYsAZVvEq5SuRlbNZfso1WgpcEZvdzEIoOGIe0zaWCCdvrXxp7dxSe5b2KNut1fAAoESLkLfu4sm9e+9yc17OokUe8O/vuy7AP+NXCMQ3ur+v38uANTssv8jI7yRAvrKCCXpL8i7PkxwxkJiYmPKDlyz8D6cZDTgMhAKiH3r4YW8BbqhPVl/M4pudpkGKQHteUizuGg0adNEW9ZCVv6y0xF8Tp/zoHB0x6KmtrblhEEb5rs7dnk2+64O+du3a5cE49wSgnHsuUm4N8Czyi/TZ0ADPxGq+QH02tJK7lfH5yK2bO/HMZng+Ioi+w+4sbioA6eTktIBX/mga9vkc9wb7pG7qYAEWLI4Q1sp+xUru2LHDTvut+RuzuAngBx/es+fO+gl5hI7r6uryALZXMZEntNLg1vYOXw7wjHWYchAACotxbU21e+8nr7k+WWDnBP5Ky5IJjvMaELh5+SoPD+iFIstyda27os/+LQK2ZRVVbn4md7zlkVGtyCjgV9uy1RVPJjGni0qTaBRWrqikTOwTsDkskD4+MeZa6+RqIguwl69cYH5O/rq56hHYnifPRBKZwxf6FH+GJmStntbEPSHqkf7r7s0f/KM7+fpPXUN1ZeFctUjNbEW1K1kDmdCX6coEwOVkbHxE173GlWkJ9TQVlVaoTPJVIX3Ojqc0pmndf6/74ktf9YCcgREDLe7hO4F4oY8My/9ePufoi/vcvijw7DEI4Rh3HQaZ/PIRZQ4ePOguaUVNKSlf1njuDtAA/S5Rap555pk7GkjzXPAM8NzzzPBeSeakTPtnhi+DhfQJlH3vvfdct0K0yjR0B9wBsQm5NMA9w9ft7ds63FNPb+zzEUF0rqt0G6cDULNcGNJNAjgTWg4Am6aGhnoPxumYeLlvSYEb0l999VX3w1d/6P7Vf/6vvP/tX/y7/8V9eOiQB+SlArtf+9rL7l/8iz90h5T2gx/+wP2nf/CHHlgT3o640AALgAFER3n25En33ms/cuVKGxQILBOQb5sacdv7rggIz7oG1WmEXXhKILeostaVjQ5a8uJ2Su4M07IsdwhAF6tzHsfPWdsq1TlbXe8GBfIahnt9V1tSXunmBLaxntcIEM7pNynQXKUJdMWywE5UamVB9CAQHnbN/Son+OxqZKUvrZD7y1R+l4hp8R8X72pZckvVCWTRnCqoLKlwc9v3KHJJiWsZ7nMV1/vFe2nRmaxyN6SprfMlCm2XB8giwbBcekqkI/RSnEOmaemrbGzohioaVceM2lSuQVuol1nprq95m9cv57JoTPp8t7zRPdySrASJ2wkWt0Jelln8NlsanfxAf597++133IF7DrizZ8+p059yzz//vB+csmjOhx9+4J577nl3Svc9q1s+8MADmc+itY3Y5W+//bYW3tnl6uvyL6RkZeL29tQA7lMffXTIP1fcS3cyAaDff/99P4BmTgSRfV5++WUf158voo888khBX6hYsOvNN990nZ2dri4VQvVO1t9nsW0Tej6OHz/hgfSTTz29oSq4ET1tqDix8rXQAB0wIBfrcD5QAmghhFtWJ015FimpENCuk0sHVhFhJgGAxIqL1fkv//Iv3WOPP+ZFZv+dd991//q/+C9du2Ig/+M//sD9/d//P+7pp55Up9blLl7ocW+88YbbIWu2fbKng6QDBfAj8+H3P3C7BBqLtKDIcPsOV6z4zTsuj7hHS6bduOptnlpu2RwvUbi4Ii3/Xbb0kpmSkOV66QyVlbgRWYjbBGzLdDyivKOyCFbOCPTODLmx+VJXXSaPZxUtmlNUEBm9ZzRDYFL5RsqwY5S6LTpXXCxexVp9EJRYAwCe9vxo9Ce1Ve58bbPbOnjVbZ3SktjlWip8QRTAMLscT0smZJgWr0EZbetVT4UWW0FW0meUl3w6dP2yvmP1nu097WQfl6zTAv9a6ryy2FWmAOliOdUT1qfsblJ/SufGXHGZfM/9caIX7S7Wx/5IyayrEIguK0p0QRo0oXtjQgOhxulJDaaGXUmGjqfVjusCvxVzM25Sum7WoINBRbHGOqNTfa6qdE6uOYlCTAfwnpVAx2SGbtzW7p5+8Vf8YMoGa5y/E4gB4scfH9EXhSk/sZVINDxD5uZEen//gD8mtvlh+efv3LlDbj7ZS7rzjL6r5wvL5Je+9OUVfd3vBB1+lttw6tQpd1zzBR5/4ok72grNNb4olzvA8/79+12PvrKwT3+AKyHPxeWei65L7nf5iOftdc0j4avqiy++uOJXnXy84rnNrwHcHXlGHnzwgQ1/PiKI3vz3y6ok5GWLdZdOBQtyPhBNXsK/MUks8fldqopyfGoukaURYqIfnZqBaDq3o4cOuj/+4z/2Hd9bb73pfvOV33KvvPKKt6Z97t7PCUR87HbK5xWQsH/fPvfmG697C4PFL2ayIvu4n/z0pz91QxdOu+fdhDspq3OFm5X1WZZOAbnBSkXumBwTrE0AmUlZqo52WKCzQqCzQaAEKlGbAI1NOm7UTtHCcb3cNUp0PCJLcMXUrM4vB+TXVMeI3BaqlY9zVXIhwYKtEYZrEnin5l65joxqUNEq1xSIek617XbnW7a7u6+edY/297j6BTkoQBnymEylkrPSl01krFyQzQNo5aNABVZdFapbsDxjPb8kS3i15KnVL6TFcgtlrT4Oh2Ulrwz0UrVQF+fCco1yUUHGNM2rXqzM6K9C1yMk2oNVvVc66y2rdh9s63IP95xx28eTEIXcO4DvkEwHpE0Wl7qDGsTc9cSzfoIo9yuDKe6TO8X/c3x8wp05e8Zbl/nKwrNGRBgGkgDp69rnvgcs8Ix8dOhjRWO55CfNZj2zF8Tr5KnT7rde+U3/1SbUbdy/szTAZ+rjx4+73bovMDpk3Q93UovPChAxtwIXjrCtvB9q62o1mDi5IogGfPNO+u3f/m2/kBfPW6Q7UwM8Hyf09Y4FyDp3dy67ZzaixQlC2oiaY523RAMewKgzApCY1StfRfglYwlOE3z4xF6kFz43LT7OgGoIgE4EiXotz71z5075drIM9Ljbs2ePBwV/8e//Qp3Z77g/+2//zFvPcBvZppdBj6JA9OsTtxHy8evu7nbHPjnmrlfXuPc6utzWiSFXBmBUuVPNW113daOslzfeqlWyoHaMDQt7LsFA9oioMSv5DUBTH+mVknukuMx11zS4k7UKu8eJBaoTUK4VoAQ8Vysfrg3wuFBd58tOqf5KWYUB0AAXqDesAABAAElEQVRbiDwls+OubnLIdcqCXiM9hWRS2XZSbcX6bMfpLfXVCcRPCYBdENB/c3jCfTQy4apGhl1jhquIlbc6w+Mtyh8ep/dp+2WB4IEFv3Pjge6m1dZatXWrfMMTr3A7m2zhxa+3ota9s+OAG6rSy2/hKpCONT2tX6ufes9Pzrjepnb3wGOPe9cGQCaDqTsFQKuJikQz6J8TnkOI+5xJpceOHfPPzgXd8zxXPGcMdms0H2BAsdlJSxNfaX7w6o/0wtjlnzfK8INsn60975bG+dWkWTm2UHiclVYIb8rlyhfyX019WPTxn2duxaWeS34AFpYP9/PVH+Zjf63ltPbl452WgTIAQr7S3Xf//Xndeyh7uxMD6JHRMRloGm94/nEzbFAY1D5N7h4fH8vZVO4Hc+PgHQShR4hratfB0sLjrLRc9wH8rKzxzkqzPFm8s9JifUvXqhB98oX89JlTWq34cwrPunzlY8qvN0VL9HprfB3q46XLg2kTA3NVyQNNHkbt/OwBD/MDjpkABRigs+KFj/WMTp7Jh5Spqqr2gJvPK1jXdu/c5bZ1tOvz2hseIJMHoKQu7QaQACDHB2584LqrUr6rtU0Cp3OucWjYXW2ucbOyRncL8LZPDLuuDN9nXBFG5HowI1+MUu1D4zoellW5VT7MofWa/bvGBt1VgcdRgenk0fVFJFqRaxHw7NUEwTm5XGDZVsRnAeoE1MzK7WVMftQ1su72ycrbIt7FApl7es67Z4Yuu7qFfAvcbtgAvAcFLstUvky8wyEBVt0Jua5cq6l3rZo8+b+evuQOD4y5raVFrr+m3O2rqnN/sKPRNUmGQgkgvGgVzyg0w3XzA4bloA2gj6/3FrUNd5JcVKZ7YN/wddc/0ONO1be6+tmlyZ0MRuQktFy/C4ykNXekosbtfFpWaA3guKfuNFcOniWeG55Be0HSRiKRfOUrX/HP3CeffOLefe9d33ZUg4uTWaZDncOLMIAAq9/77u8tTgC255WtUVYa9fL8WT72SYOy0oxXWCZX2kr10R4GBfQZ0M3UZ+XC++SiJo4dPPiR/zJWrPt8RvfxY48+5hoV0Qe5rYzfCf5Y/eH5QtLCPMbO0ta6PvR1QpbXJhlCOjQP5U4nruu0fsSdzyIMMEwMJxqQHpFMuiB3EOYL/MZv/IYfdNi1ITP74bExsLS1vn4bXV/43Nq+bcO2p9M2sp9ALuQppF8i70cffuhqhDkYMFFuoymC6I2+AmtcPw8xn8YZxfNb6SbDOkaZXHF/eQECtLnBcekgegIWw7a2LerYBDQFgjs7O929ct/43ve+7y1lWK136TNLxS9/6fPCHyCeAPvEp9qaPapYwVcOfuj2nTvqdkneQQHzQblN1Aqk1vZddB0j/a5ZrhxYOrMIqDai6Bo18psunUnAQZWAaoncCQByRuxhIa1UO9oEEIflY82vVC96JtZdUSSLbROjblTuHqWyAkMA9AoB6zG5lMCqXedxc6jESi568+xFV1pyxdV1MM0xP2G1bpYV28DlsOq5Oj7prs8Xu6sCW71ycN6qNrSoHlrRXlPh/vXd213/1Iz7n69MuLNjcjOpW74ce64a8T9moNAxpsgQgQ7C/PhimwtMmI4LSNP0hPdtDtOz9rFWP3nlnGvSl4j6wF89F2+uwUWBnuttO92vPPuc/+yKRTEEWln13G5pPHOAYu57ng8jnhvSeZ74LX2TkIuLBr6cM9BtZXiW33n3HT1f97od8pmG4Jsm6kynZ6VZuaxzudIoUwjvsDz713uvu4vyZ7UJk4XyoD70Rt9Ev8EWP1n09/jjjytso3z49fzcd9993g3tDQ3WL12+pMWRluLGh7LAD8qVxrlCZUvnoyyUi3c6P/mgXOm4/JyV686zzz7rJ5v6zHfwH0ByuUJdhs+JNRcd8VzgUpg1+Z18ExqsfqSINQAqXF9Mr4VeD6ur0Pz5rp/VnY9nvnO5ZKDMSrx5P/NlhoErzwu8mD+RDjCQq440/1slJ3yzZCikPsoxefSwvoJ/4QtfWPwybmU3ahtB9EZp/hbVy42G2wVbfisRFmLypV/eVs7AOGDH/KZ5md17z71uQB0+VgBu6D/6oz9y//1/92/dv/k3fyardYu3PO/du8dVVFX4jhBLwfbt25YtpsGDe+r0KTdy9KD7xvR1N6ZwaW2Tw5pMN+PdHpiTVjc3Le9oJqNlW2EBpy0CxfgbGwFQswBiwmHe9VTVOqJ3bBFQB0g3CHC3Y7VWR7RjXJPoxBMgygRFCDcL407ZBgFr3B5GBbavTMoCG4Bo3DXw0y4TADdL8CTlJf9llb0yrsVNtIz3Rc1onJrRZDyB3GmBpxNq54OTI65Ijtu0+8FG+QgyEVJyVo73up7hWfdwgSAa+esXALvpJNwyUOhWVJP9GqAYobMpTQ7EGl+ljrhQYuLjfUNXXYl0Z3SmusHVKyoIvEJCmx+rzRWde71FletPJ5+rAw/L3m775t/ZpxcbLlPlus90yyxSib4qACB4lvikPawvL7z0ANdG6OX06dMejH71n391cUAank/vh7q0fduS1/ZtezNphZShTxnXRNP+hUliYX1DaitEBCAIAAUIYMAwoPzX9bmW+OzoBV9Z5mFcvXZVltkO30/BC/3SzzHwqFqIG0+61WNb+Nu+bVdKW+l8oXwKzRfWx+RRXHt2795dUP9N2duZcBlkrg3vFwAg9z+GG95H3BesuspXUK5zFl3UF5qr+irKF57wfWe6ty1lbd+2a5W2VnwKlSusjzbzwxBx9MhRP5jcu3evX60XtwcGsPYlKCxXaF2fJt9a18f98KbmXhHJaP+B/TkxC/WuJ0UQvZ7aXoe6uOnDG3+lKsMHLF9eRrdN+lwKbx7aBx580N3zuXvdq6/9XHFMn/ZA+v/4P//KHdSnlmnd7My0pnOkk2TyIpMMv/GNb/g0qwcr0/t/99du//BV11BV4moEhq/JCn1ZYHqf3BrM+pzAiiWQZuXZYtlVQDh3WbGjsTAP6YVLVIk0iAa/2GS3EQHubYpxDMEVi2CFrMv4PVMW8DukkHUA33bxDF01ypWPYyYZfljX4u4duOj58AcA/db4nPu7oVn3zytlOa4odefGptzhWbmbNG5RHO1rrlbgeZ9+32rSqpIeZBa5X8gCXzk97vaXK56wPm0OS8eHLw+5b7c3ub6paTcgcNHQ0bhYz0o7DBYaFuJeZ+UF+N4dAGjy0C4syzdDuHaE1KGBCFb8NPXI2n+6qs198yu/6oEl15+XYy4rU7r87XTMc8XL7MyZs+rwD7gXXnzBi8/zAN19937X1aVBpo5PnzjuATbzC0IggEvIRx995J8l8632hRf+ADTsE2iYvln36TvoC372s5+5fXfd5fZIP3zdIg1LMyCa+6FFcy327N2jQQVfvUq9hW10bFQ6uzsB0Xrmh7TiKK4ADEQA222KyhDqbrPoAJnC/jh9bHKSbpPjvvnNb35mJo/SbtyceD8MDgy6Rx99VBEXHvTAD6sjIJqvD+RLE1ZqJhPydZTf7UKs1Dor9706TZrMZbzK1Rbycz/5gbcGHmzpaxhQ4tbUobjJD2txLp4nYsrb+Vz8bqd0vtK888t33HfktlMvX/nNQhFEb5YrsUZy8IDxYmJEj+U4q/MJq+IlfO7Mabdzd2deMIOVjOWhJ2V55YEllNAf/tG/dH/zN3/jzp877/bqpYh16PkXXgjZ+318OndrBbvnnntu0dKGnCcOH3RzWiHwoWoBi/kZ73rQpqgUrXIneGdgxL0+OOn6RsfdffVV7ivbmt2URqCNsrBWZgA0LKF0s4DeLCIEG2HbANdtsjobDcnPeVb+eFUedGp1MMkFWQSO5CgxIgLw4TMsP+1GuS/smj3nRtSBYbcdUvo/TBa7f5iWJVrxqb8/Wep26LNzdVGp61QYuV2jPW5XY4UH4LigzMtFBbDbrZB7R0cG3DMKj6e1cdyIGlElkP2erOP/9sQVhdIodQcO7HP3r2KxQuSEsLSnCd9sLOtY3aFR8SctHCiky2QdT0pPP+vXtVIowYdkIT85NukOjk67l+THXluSXIuw3IwGJG8MjrutLzzrOjs7PXgkdJWByjDvnbDPwOB+TQwDMDJ/wFZmtLbZFx4sSBcvXXZ36fmxLz3k4fk4c+aMBxGf//znb3jZ8oxjpR4d0aqRehlTnudyo4n2YDGqqlq+cAzppxVd5Jdy8eq51ON9xvtkKSvVF5BGuWFgMUN+dIB13ohyl6Qf4tlzDr1AWC4PfXRICyJpUSHVx1eulfo647leW2TnS531l1evXtH11CRk3f/hFwfkYUDw5ptv+a8RnP8sEW4YLCB0rfeaa25p9gMj3ksAaFwDefdk0VWFWQVo8yWUwdTtQIBg3ocMABgcGHFfc79w7/Oz+5x7G6MUq9gOypA1oIHGsAaQGCCw3DMp/77P3ecefOgBz4oBqPEAqMPzTiDa8dZbyfNxz733bKomRRC9qS7HpxeGh5SXDdtCXirkqVdcZvLnI59PlmUeXn5YmYlXu2fPXi2R3Za3Ll6QWJHoLI1GFL3gyDvvuK1Xzru6YvmNCjxC+B+fmyt2/8OpE+6LisF8T121+0nfFddRW+4elu9c1iIlAN9mge/pohI3p/KEg8skvX95BePCQbxn/IVbZAHGjYHIG3PSAYuDAC9NG1inJ9WpwXNKed7UdLsd8yXuQJnqGdQCIeqoiHAxPDHpRrTK4HaVvCadtonLN4Rlt4hRkdozrkFNrQA8RFP5Tajeg5pkVzulSZOaRIh0yMC/X2lvdrtrKl2peD2hCcgN2hZK5rOdlZ9BwKDazyABX/BZ2hy4wlgZdGBQeIZBi/RKPtML1vtuAYKD49Purv073I+vyioi/Uy0N/o2NGhyYSjxGfl+H2vZ5v6ZXhw26a5Nn+fp8O9UYlD5wgsv5H3B036iMODWEuoCCxIRcAARDFhD4oXysRYw4l5mOfsL3ec9oMZHOOQRllmPfYAglkEGCPfcs/xFh8yDij5SpueG/qlSX3oYZBCVhYEU/YsBh1BWwDKRTug/aBv5+G1t3+q2CTizsM+WlgPyh24Ki93yfWS1H4CPffrQ8KtKkfqOIT0jgEGu4TkZG3JdH9zdTsu17dvf/lZO14Vb3qgNqgBLKhZo0yFicI25t/llAWR0fljWa95D5CH/7Uq0ha8xLMDU2dnp+wK+/PJlhjlD9AUMTHneqxXBin5llyL14PJEnrv23bV4X/Vc7PE8KF9aWnLDYG0z6Ij2MgCwZ4V9rl+uZwOZeT5w/fy1r/+aLO+JkWgztAUZIojeLFdiDeXghqRDKoTISzzOlfKTj0+tbOnUeBB4CA7oU/VKlP7URl2nNRofOviue8pp9b6g/2Ni26lxlkgucv9szzZXIUtTz/So+7Cn3z3fKF9m1U/EDhb1MMKdQEMGd1GWaqJfZIFoACDnPC0UHRegxP8Y9w34XlE85jIeaGXit1UTCQGNTJQbkHX5Z+NaTn1uyG2vXXAwIV0dFa4LjWL0SoUWU9H+ZUlHAL2t+rHwyIRepsSnph64s9jI6PSsGxPzU4Kqj+spbJT1GcKiXq/9/bUV7sW2Wj8wkJF6VZTPqowOsMb3a6VCLNXmt52uALeWDybnXbdUNqRBQHVpsfuKLOoMCqByteGBplr3H4auuRNDo+5Q36D72q52V6f2S1Vef0lODYyU8ObErNv/tS+6zq4ub4XhkyZg6k4mnhVeePkI4MXzl6ZLemlggX3ppa8s82kkH8DyiixwLCrBhOB53S/dF7r9iynfiyhdx1oe85In4ggWxUcfe2zxBWl10Hc88OAD3sVlWNee/M2ymlVoYAyF/Q/7WOrYYskl+g9gG32S5r+yyXrNoJx90teb6P9wv7isCY2jAjJzGkzv27dvWVxnQEzrlla/shqf1we0uM69sqJlWaE/lBtcZ2end/FZ77ZsdH1cv3SoMtJY2TYX8Wn/yLFjej5e8qDT8nHf4AvM/cWzl4+HlVmPLfcLlL5XGVzyxekdGZSQ+5qe61qtRsq9wzPjw3+qf6gScOSLE/cOzzjljh05pvttp2/n3MK7Dbcn7iW+GDMXI4mKtR4tLLwOgP8R+W/fc88BP4A+efKkf77TOME4ck0PKY5+x9Ztej66LHnTbCOI3jSXYm0E4SWDpXgeYCfrTPqhzaqFm5SZvVi98hH5sCJWVlb4GcB0VGkrWb7ydo5yH+mzbkefVvpbPt/KuxmUTSiU3qQ6EYH1IlmAKxW+bk4AGSw5oPBrfuGRmeWfqVjWGzDdmprMRp24T1xStAoL21YvKykuDPhPs4AJi7Vg4fYgW+/j0zUt7kRLu/v62UPeYquo0e61mVJ3WQD7u9Xyn5b7B7VPNMmy3KcYv5JlTkC5VkZVwPMuAWNkTYC+onnoWpibyaDA60VN6nv/ynV3WcsMNhSNuX2VWtlvAXZWqYP8zu52V6lOlKHCJYW365D/tk1ypD35iDYRom736I3LdAPmkYnQdkwkzEvqpN+fKnU/l+7BzS/Oz7pyRhwLclL2rtpqV1w37f7i5HmZrYvcw3K7IXa3zIOcXqTz+jDQs2Ov+/0vfcl36rwgRhUblns10o0a4Pl4U58uebbSftLk9nrTfWqAuYTBoMD4RhEA4dy5s97Sij9rW8aXKfohLEj8WjRRjDK5+qaE3zlvXce6jZXS3H4oAzhg4MEgPhePW60L6qXP/KV8NJlAuVNghi9uaXkA/zPqH7DQc42adJwmPskDyPGFtmuazhOPlzTA/f/jH//YPx8WF5qzpONbjftUch2K5Orx+WUge4nL+u0BeM9rQZlqTRjt6EjescjKj8EAvsu4SkJleuc98MD9Pm+pDBl2j4f3FeXIz2D68Sce93mmFiJK8QWIe45+ur6+LtOK7yvawD88y7g2MceKPo7rlQ9HsDoyYS1Dd9ANFP+GqiOIvkElt38Co28euvDBy9cqOveamtyjfivLzc9IuFgv7WrNiLeOgJcePAqt75RGnhffft39ZpGW0PYQzWpIINqTNaXuZw885P62d9B1ygJ6aGDC/c7dxLFgJb/JG8K2kY7rAZMMce0AIBO1Y4k0+ZCRuoAHge+IvEG8ZyJyGAFBtmnFPVYHPKsFXgZqmt2P2u92L3cfdh/JitorvPzSljrXOiZwKhAOjy83KaxS06yXq1/glQqa5c+9BGcU+1KpyGNuKMSv/qUWKDnXPOVXJaudGHEHtPjIM5Wy8Es+dLilUoMHX9K5toVVAE3Olba4pVTnAFT9AjBYiQH0oV94mieOGOe0LPmohMedBCv5s6WyYLPkY0ANujaPlm9x/9Vgt/vPOttde3mx65NrS638y8t1T0Dw+khX7P5nX/C+jVjksI5gQY2UrQGsr0eOHXW/959814NHPncacX9gwW/Ual0njp/QXIS93i+ST+JQmNfK3Motzz1+qcc/OaGvUvtlGdvuATJ9A2Cavog8WXKRJ4tIHxkd8eCCdhEzuVn3S8VCG+mH+JEvi28Wz7VM4xpgNeReLtWglw4AdxPuafrCsF3I2SJQw2IgX9QgEutiKDMAC4C9e9du197WvpZi3rG8WPIZsPz7v//7HiSiT+4xrgnuDI89/ph/Rl599VVv5QVYbhQh19mzZ/18gIcfeXjZO5L7xFy+kB2XBe4hXFQYTFE2vJ9IY4DNPcP8gs6uTp+X9vMo8W6mb+W5oxy/8F5bLx3gfsKP54MtAx3kQh6IgQHRZ3BfQT6OOZ8lK2VYoKpO/Qhfnnj2NhtFEL3ZrsinlIebjB83Hw9hITcdD19dXTKZIV9+HmJ7cVXIpxHigWaSE5Nn7EWerwlYs3/293/nuvovu3a5NqUfCV6rzQJnv1o+4348csW9f3raPbOlyT2myWuAZKy6TFJTWOVFYEoZFg/BNcEm1ZnlF1mow8KtjeiBZdGTGeXFIr0EeJMlwU82tnkLdbHA6+XmdvePfZfdwOh192z5rLtnbFASyL9ZegCU72qocQ2yQjnJxDLjRnhVm2V5TKCZ+rYrYgWS9JfXOKJe8zLd3dzgtvRPue3FcjVZcOfQB2udpUXqQLUHbi0H+XpiS2tsS6LtJ1vA+hZNWky8upM0ui64skDMkOSBwxItlae+qwLPH0zNu+NzJe5RAedH5zVRTPreL4Cc1LWUHzlbpzUjXOe+1l7rJ2jCvAhrtIi/p+Qn3rt1j3vu6Wd8GgsrDAvoAy7y3Ws+82fwz6ReOj/60Y/cgf0HNBm3c/E5tueZ54/n+pFHHvGfbbFiVcvdwXyGOWcgLuwHCkkLr4eVtTSr1/jYpeHlz2JJ2wWemTwZnuca0yeEaZRL87K6QtnJR39DVJJWWatK9Nxy3l7EnKeclc0nZyH1GZ9QBktja/v0X1iOAUYNAjsvfvGL7sL5Cx4ohGXDfazPjQJH9rna+CEXAxCskUyOK5W/eKT8GgCU4fpA3HS+nNpzgU4HNEm9WO8OgCn33nad5/7kHGTXMLw2+dKsXFjW0tL3FHnSaRwDFE+cOOldF0K3Lc7Bi+eDdwH3eVdXl+cRAuiwPgA09x2WWb5+PLrnEQ88yUObmBMBP/KZzGmZsuSkvOmR/FY2V5rJFOazNL66vPHGGxpUf6IPknN+wjMgGl6Wh3J8YTspvUBcR3sfkCeU4bqejTNnz7jHH3vcDxh8gU32Jz61m+yCfFpxuAFxueDHQxveuPl4j8ryw8PLxIVcBG9cRXgg6KjgTRmsTQBxXjD8GEnnok8+/tCd+/lr7lerZHn1CDZ5aC0/3R2Ar1no8Qste1xzqzrFOfkSyw9agS9kYWZxFbluCKjVyC0BIIc/dLOiWQwrHW74MhvBi7jITKLDjYEwbvyusjKhzgFVE1InLLBbL9eJezXZ8UpVvSbOlbifa/nC57a0uK6JPles2MeEvSOiBasjNskqTn24TxhIx2ViokTh65QXwtWDFfyAlDNFyDHj9iqk34W+YXfv9R73ZNm8a1dbE8tz0np19z7/sCKHTKmuBBRTEz+UhszkgazMnCZIlsnPutRH2ihZiGxN+2kXcbG3CkQvubvAC4KXBgYC6odmiwWgZe2Xu8rLFXOuU0Y2BQ8Rp3nZkk1PiQysInZ2bMa9pSgqz7bUu646LSKigUWT3GlMsgldqyOlinn77Atuiz7Bc7806L5h4FXofelF/Iz84fnCr/iKPnV+V1ZoXozoyV5AtjV18OJNBsB1/sWDXjmGcpUzHrYlr+1Tv10XS+M8FPJLUjTolG8zIfiwIhHOj74gTcYn5E0eji2NraXZFh9Q5ls89NBDiws8ZfGyNM9Af9JyWh1hPtu3LWVt37ZhGjxI57Mz/pvTGjju2bPXW91p8/btOwReEss45SArwwQv/NU7Ozu9dTRsKzyPHj3m+9LbfXJc0upb+xfdAUoZdLz88svegkma/WrkSzyvfgyfW2hAEzp5B3Ke+4ItZNtw39Js6zMu/MlKs7Kcs2cmTGMfFx18efftu2vRikp+DE42WdLuN9LD5yerTtLOnD4jK/wh17a13Ud6qa1Nnn36Cr5QkSeU51Y9D1aHyU972fduetqiaQYH9Atp4xr50EFtbY23Vt/3uc8tyhzywzJ98OCHirFfJjC+1/eH1LPZKILozXZFPqU83NyM6ngg7UYvhCXxWMOHOKsM/Hhhhg84Dy8PCwRwn1CUCjC0fZoJefLSff3HP3GPFU9rdT6gL4+agTPPwv+R94T73ybUBoG/++QQMDYj8Km0CvnnNgio1ZcqBrPK7ZSPbrkAX39tvYDziHfhANgCdIl8UT07ldRAx+L7Tw0CBKiTRUXGZC024qSs3Hq4Tza0uXGN5sdmZt3J892urbnR7Z+d9O4JHq6LV7OAIr7Fw/Lthce4dDcgdw7iPvNAMTmSdhHLgvpqVR53YgD7Ti1dzo+JH5o76Go84kQHiQzaWaDEBaVCMiXkG6Dd9DFnk3Mslw64T/Sa/OXcjK5REsvZyi6VIXePZjq+OVUkH21NFhQGe7B0zjVIYERLJn2mZdOnQp27rBB+dbLG/3qDFkdQ5isVtf5rQBIucN5d1PW6tkNLXT/8qH9pYEXhc+WdPqEQ7d4M8Xx8oElB9993v3d9yfX88vx9rJfzkaNHvLWNFxJhsJJnsdrVyvcS96wavaQ4xzPIOfvB155h25q8HIf12vkwjbxYBJnABPG5nD6APLwEqcfKsW9p4QvSF9SfrPoog6UKYIn8RiHfrHLkC+U0Gaw826y08LzlMT7UOSbDAeEEWdiDT+WdAsQYCqxtuLbRtjRR15gmelUq3B9gAp5WP2X5gnfq1En3wgsvbLjfblr2zXjMV5qjiliDRZ+wd6ZLZGUfX+AtAs0faUl4rPpYZPk6Yuftmtox26w00o3COiwtvSVPyIfz17Q4EG46nQrtiiXW7l3uE/tiQxpEeTtvx2l+PqP+EI1mRuCSLt/uOcqmny2TO+RjacbL6gqPs/az2hemUQdzF3BHYZJkvcA8saqRCRcMky+sjz6peWFeA4YVePCDLz/K9F/vde++/7576Ssv6Z2Rf4J2ltzrlRZB9Hppeh3rwRplFqlCq7WX4Er54WsAOZ2XMF0GsgnZg4UaizXEg/GJonEMHnzP/Va1Xuoeht344lG35g4zEU1h5OYmFT5NLgUvC6MTNeOKYOlZFTkncPZLnR9R2LTaIlnFJxVyT/x2F8nPWahvVsC1qKzKdck6zWS4OoFp+NLzMPFuRC4NTVNL8aQnFcu5QvJVyWpcogf5XFGVO3fxnGsRCPndqWuuU37QpZpYd12LhUCtqg/CTaNpdtw1ycKLpRukji28VJbzSVmFOY8/dI1ANASQbvRWaR0sIXgdJCCYPAklx5VaxXBlWiqLjDVyxwA+z8kK3KvJlFjdW9XWxMXCrNhWS4k7Mjnnfih9tkh/v1ulpcCVRZpfsVrA9aPyXX+4pslVypJOfXXqSCvm+JSITCXucIks9I894wERHSpfMex+WLGCz1gGng+LC03UDV4yPGe8TCC2dtwnS9yF7gsehAHmCJHHFhDOghVMOOruvqhPvloxUnwB0zyXPI8AjcTNQpNABe7Yh+wFZi9j5CHNiH2Tha9N+KQyaH722S94wG59gsltZeEHGV/24cMxW+qBKAdxzDnaw77xtXMmA8cms9W1mjT4wNvKUpfJZXw4ZvIgodQYNNx33+c0AaptUdawbZQxMj74erYrFF+bfJ3pN63N5KM+/KS5JkT1MDmMR9wu1wD66tE75bJcGb785S/7k6SFhI73yTediCklegfgJsB9BJEX/dv9yTWCLI0t14CfXSfKZKVRzq4xW5PD0ujnPjl23LUrMss9+poiJp4P5eAX3uukQdRpZHzSvBkUYMFmQPbUU0/5CbZWt8lpMhsv0gtJo66VnocsPpSj3yEcJ88K9zIDYPLSJvoXa5uV5xh8cPnyFc3p2OOfDc7ZeWQnz89ff0MuUw3uc4Gl2tq1mbYRRG+mq7FGstDh49TPLHZ7YFdizQPKQgB8Ykl/fgnLcqPzOQ3AzAsgJHuQSQsD5Pf2XneT8uH64JfvufsVE7mmhM5vqdMIeYwLAr41Vyr3guST0D9pmegGTbz7RqXcEfROf3ghqMQVWYuxol4c1HKxkqlHgPqQ8r4+r6mK01q4ZGTYyT7qWuUj1yRw2wDYlsW4SD665QK1V4sV5UOAr1Jlr2mFxGsCHvMCGmUjQ+76wKR7YPCye6W+2B2/eMX9VFh2eFQRTKZm3G/tbXMtFQIB6jy2y/UDmEEsaQB2jQByrdw46J4nFbMaZ5NtY/KFVqZjCo93SZ3NF7QYyfmxCffuyLT7VqtC6pUL8IcKWNin/IBcTuplWa+SX/JKROi8oVKBIrmL4LYCYjfXE1YjTB70BUAjZv3zpe6nWl3xlLZPaqDypPRaSTw+TybR8pfUwsnFTYV0a8SgqErXzOiyPnkfbdriflORFQBw3F8sCAKwiHSjBrB2YmXbtXOXt7TxQrOXKbkNTLK9JCCBawHPItYffJKfeeYZb7kN3QIAuwBqfrzocC24evWa58WXA/yMedYZ2DCINqDNi5pnmfohtlhNx8cn5LvZok/Kp72vKVEzWNDhA1mLBFNkdR2Xb/SOxZco5ZDRtvDimB9kL1f26bMYRFi0hePHj7uurk6BhiWQT/6wTBafQtNMnyE/S4MHlrWeC+fd0eMn5BLQ6p6SZY0+Dwrbg57gQZrxCmUgHbJzlhe/1g8++MD9zm//9uJAxmeMfzI1QP/BIiW4Z/Beg9LXAXemg3IvQrfc0716RrCKVsnVplpfZviqAdC2a2XvK7vu8AyvHcfQatKm1F8fPXJYz1aJu/uAJjQuPEd2/Y1XWna7LzhveayMycC73L762Bcaa4vlYZsuV0ia6SAsa2m5eKNv+iFc0NAri8egd+Q0PiaftZct5XDLadHCOkS1CfNQjuvCvIPDR4663/yNby9+6UaOzUjxjbYZr8qnlImbmA6fm7FQ4kYuF6BjuxJZZ5QvXwje4Xvq2BE3e+hD1ySQPjMx6K2yk/Lfxf2An7ef6t16USC3W+4FiZuDolMI/HZWlSlyxbRiLit+tNqEpbVN7hsDZZVuV32NLMNM1YPmFetZfsGCsaMCDtdkDe5VuLprskhfHOp3U+W1blJW1y3jg/J5bnQ7xvsFsOWyMKfJjlphsOfKqOusnHJdkuPbJZOuRcD3vZEp97NLve47rU3uqnzt/vczV9yfdm1xU/K/qxNoBrTKfi1Lr0BEidxO1AnUyBJdI+s3Ft0JdS6lApQfDIy6jy5fd4+11LoT4/Pub89cdF9tO+AUcTtTjUQZqVR7C7EKw4D2l8sSPSidlMxNaH/G64gJlwBcCOgyLovxSWHyt4Szmar5TU3g3FOm6CHL5EhAji9UwB/BJEXl0AQZReWo1k8ez+61afmKPv2st5rgo3j9ep/vNM3yWQDbz0wWXprdAsO9mhj1K7Ky2XNrLyJTBOno8pIsbQBdXnIAX15c4eDEXsLkIXSUhY+CH+DQz10QaMWSTMxmjgHZbCnLKoBlsuRRHv78zskV55TA8259HofHAblw4JqDNQmr9P0K70b0DFYkRB4G2Ca/ba0d6S3tAkR/cvwT//mX8wAmrLiAaGSyNqXLrvUxOsUAgfvGmMIwYkncqTYDEkyGsD1ZaSvJhP6YfNXV2eWXPl8pfzyPe8Q1f00Ic8Z9CYXXgeMR9fkMxLiXGxRHnNjTPC8MHicnu8niAR7l6Ye4rxk8csz1Jc142/PEvWnX2DPI84d757gGXaNaZffBh5Kly8meljOdZvyz8oXVIYsNIAotE5Zfq33qRqdESeG67JDb1S5F20CXUNgO27ctOkK3zHUAI9AmO2db+iEGmDt3bPcLyayV3LeKTwTRt0qzG8iXm5TPWNyghRI3NODYHs5c5eDJw8KNzr51Nrnykw4wP/Hh+4oLfdHtrynxYA/YN64JeHz+LxUYHdTkPAWFcGfF90BtpduqFxjLa2NBbhEIlRFZrhhaolsW2katMojldVAT72pUnmWsx+WiUS0rcLuialyTG0NLVYXrIN1pWeTpQcdK2D2aLHdFZWpnS9xupQ2ozVfk+zw4Nu0+EZzt1aSU6wLO3yqdck30B3I9U+Q591yT/H73bHFllyrdvz/X7d7a3u7ukVWuUctbT8v3ek5mvS1y8fC+2BJ0Sq4mRLTA95oVAWuFYYslS12l/M7Fr1Jgd5HAqxmXCVDboHB5hZJsYR7AMsiArmslxEa5mVQEdV1RSJO3Za2/JpePA3oPPaKVIoltncBrtjdH6gYF9pPwggyGzgqkH61tcX/0xS/5lxIvNe6rcGB1czXdmaV4sRBlw6/CtxBHNqul6JDV7xgNYQXGWouPLj7m9vJPl7MXk6WTj5995uY8Vj54s+W5BngY2GafCAfnFXaPSBKDskhjLQ792ok+0dXV5csf0kqK587LFaq5xUccKKR/sD6H4bFRsZ6f9Sazhl+5clkDgSY/sdH6UZNxLWTCCscXhG9961sF9Z9rUeftzIP78t133/X3XL4wZydPnvD3Ks+TX7lvV6e/hnaPM2iclKV4UvN2uL/5QoMLwryeAcoU631AbGYPprUIEG5QtZpoD8Dmqw3p3M8h8KNv45hnyi82JDcF4oWTF/48P7z/GHAW8iykrxNycu+xKBFffbhH8cFnNcyNIK4F9263+gMGzcSFx6K8Wnny6QJXDyzRX/rSF9XuJArYRrS10DojiC5UU7dRPlYv6lPnwMpHNjosRHxfTq4XvBRL1XHkIjocRqC8SO1lnCsv6d36LNr30ftyGZCvozos4WJP9Vqq2782BQqqFSJuSulXhS875Wcsnwz3icKs8Qh1y02hS8fXtEgJrgmAw1lZyybVoVXLxQK3DuIjFwsEM4EQ/+nLiveMSwQ03FDudkwMuw6B0m0CuxVyWxC+lRuIXDFKFbheVtkfTha53Up/oGTG3Sv3Bv9gCBzjI10tS3oJ378nFO5NQPiiCp6ZKnYvquwOuXZgUa+bF/iQ9a5PaL1GVlis6w3qsOdUDIAJzQqw8ylrWp8XPZGsDlLm9eTY/upwWAMGPwFSMZ1XonnJdrG63oNudDOnxpWps8Nij4EZPu/L9/kdLRjTrDZ+sVwTHNV+VmL0Aq5UQQHnqRcaFctfqJ7Hv/5Nb8EjjfuEXwTRaONG6tEL6bwmsf7a119ejIV8Yy5FStE1xZWqXs/1vn13aVLaKf9yBljzss3nhpXmZ6AQAABIgAACWOd44dt5nnWANYs7VOmluVcuObjlhHVRDh7kpRzA4bJWWwTw4L+Z74WZJRc8mEAFIZ/Jks67Vsfwpz87os/HRJ3Zp/Zh8aNda01cp2TCWedixIa1ruNO40eUC2IFf/3rX/f3Z1b7ALOnz5xdtGr6AaH6X/ocszKbOw7Xmx/gmv54Vs/VnI65b+HDdnho2A8aPbgWCAYIcx/zhYWfWbGPf3LcDQ0P+fcgrlJMqMPlhMGkuT3i5rRby3TzLBTypdfah4zMfZiemva+xsgG38cee2zZ82f5b/WWyBtHjx7xgwO+SG2TBTrsB9aiftxhjiliTbMG4V1de9aC5S3nEUH0LVfx+lfAqLBCIaJW88AiJeUq9RLVTl6h6Ux4yRT6cvzlP/y1a798wXUIERuApgJcFoxK9dK8rBh245LhgEzAg3IxeHey2O1SWI6D82pLfbN7YuiKwPakt/5eFUjuUpSLcoFnT/BCbg3QKwS0scy+vuNuN6KRbI1cDF48c9jdO3jVzaszLAJpC1wyOQ633gmV1RIR7tdlgX5WS3f71usPIHv4Op8GcXwQ1m2uc3Vnzrvn9k25EwpX9x+0ot+X5Lbx+XImLmp5a4HpDvlAl6tjHla9owIWdZIXLEvs6+vbu1yv6vknWaLw416syJcO/uhUuQB3Sais4LTtzktXRdKbbLya3Ljg0oIKlEYUE2hI7fwHGbQPK1TfF0um3RMayNQwIIBWuM5Jpvx/JwXQu2sbXNcILjqz3hXn6q597mvPv+hfVLxI+DzOJJ+0D31+zp+Ns7zsf/jaa/KDbtOgY2feRk8pogsTB4nJXKoBGy9ZJgqelasFVq+1fKEBXiGecaxf0EMCCE8//bRPo+4lIu/CPaW9Hdt3uPkO+UoregeTrLDMFdJXUM+I5jKMjoy6iUnqTIDOUj1rv4f+T50+5V1Sdsk/k0maqzE8rFainp5LHrCzXHUhOlkt/zstPyD3F7/4hf/ismdPV2bzeM/hB00/+7DcBJh8yOI8DPay3oHc2/w4F14DMwhZGUA29y8/BpKAWJ4/vsgAtLFoX5cLFvuEYXtKz8a2bR1+sMu9zH3EXAUGuyww1t62xdVpopw9W5mNCRJ5xnjmzRrNMbIse/SC/LdqFz1gHcbFgtjofAUzXa11nbj9ERf6+eefv6XP4VrKHUH0Wmpzk/CiEyjENSMtLuVCX8b0+fAYKw0dHO9awHcuOnLooLt48GP3ihYrYblsOrosAvJdEFRtk4W0UVE2BmWdHSivdqe1ktepwVE33d7mtsp3uXO4z8dO3iq3jTJ8pFVuRC4auIWUAxwFGqvlldsyOeIjYYzItWNbX684E96u3A3JbaRewBa/ZRmuFemjyP1otsx9vXTSPa2oISwz7kl86Owe6FDUA31GK1ZHslvuG092NLvWGi2UoienSUut/tN0ueuTCf3zAt9E9yil45Uf57G6Vr96oT4Synd60u2tUci+Yyfd/yTm5dLzN2Wt8HZyekSUmKIyAdIKBLyB5Dzh1ZhE36iRBZ+BRa3ajkW+X5bwSgGDIv2Oya3kTWF4zcl0/7JiSmEFYXZjXTdUsYoEliPfocmY+ISPSP0f6NvBvc88K1DY7i09dMBYFdYS4K1CvE2dlZciLhl83v/ud7/rLZ/Lwely8QeHBhTKTvc2944sbDyvvKj5dMzEP9INACwvefNHAISPPz7stigm9VNPP+XrDWUkPnKbwEGxnm0ACeG7kAm/6HLJdeijQ97/l4UgsHDnkg/LHotjfKT8WAz3dCWz9snPPbTWhIVxcHDAnTx+wg0Oj/jFHCwc11rXZfwAQydOHNfiMa2Lvq12Lm6zNYDrACD0lVdekUVZM0gy7gWsl+S7++59fmEeBkb0qX19/Zpsm/jpZnPPTg3r4F60SXzkZjER3Cp49wGs//bv/tbvE66NctxXEBMLiePO/YvcfXKJ+t73/m9Zb7dpIPqMvswlIRJ95lX/yXovrJrJigV4zhk4MEjnSxQLOnV1dXnL/oqFbzIDX2kA6J27O/379ybZrGuxCKLXVd3rVxkvPx50XmarIToBLIdYuMJRepoHHQb5+EyfCyCNjgy7n/y/f+vuHbrqtvJlNBMUJpzxf+5R3/cFWUrNC6pZ8S3a5H5wWi/nMVkALlQ1yGWiXAB5zFXJCg3xoOPOMG8uERyrA52VhbQIf2u5cOxX/SzHjVvFFkXU8FZllcV15A25ZWwXaH9Ya24Tkq4VEC0eEJGsv9Te4PdJe1KrJj52YIcsxDqvjvpJOTi3C+y+Olvu/j/5Uj9eNu265OJBTGbCyhG7Gt/oPkXZ2Kki//W9nfLQFojW58At8uuGFN1XFlyB9IU6ScOPelgT9XB3CdM5Ny2fvWFZIZulgxYNJGjTIA7fItxHKtWxD6mTf1e+z92q84CA/+Na0KWW4Yb+ryXNqW3AGwYwsL4sdD+4+y73lFaX4t4D6Jm/XC7wtJby3G688NF88603tTrhfh9ZIwSn6bZwjrB1PJcATp5Te+54WWPx7+zszAlS0/wKOQb0sbgIwAEQTCz5NNG/0Acw4KS/wIJkhFyPP/G4PsV/4hdl4cWIFT3LTYJ75fEnnvBWb3MPgWcIaIzvp92Oq288p4EL1jVCaD3x+GM+ikOhFsKbrZ9rBNh79tlnF6/dzfL6LJQjLvR78oXGoswy0bnuhf7+AW8Nxj+XLxmVGsThwtEtV4iOjq2f+pkI6y3We4Uf/AHr1aqLAR9h2GyQ6EG8OkTuJ57TefXv9fV1jkVF3vvgffcf/+Nfu+ee+4KfW5DvHWvXGHcT3j9M5svXR1j+tdjy7GPdvyBXM9rKRECe51v1jMCX54MJxXztqq1bHvlrLdp0q3jc2Cveqpoi33XVAC8lGxWvpmJuZl7OK4Ee8jFi5AHLIjoeXp5XPjzovi6XDO9dGADFZWXE67T6CT2hbhsuDOqAKvkJFN517byW8m5yR0dK3Jnd29wZnd4+2u8nE+4SkC4V6K2XPy6uDZ4W6qiVdbZ1bMRVCWhuGx/SgiPyU15wccCdo18A+ifyXS7X/gtliq+syBpzuF5I7mxKLLjolQ4NWdl26vAb8qN+W4uV/FSRP3rVYXbWVyoyhnyv1YFOlGmZcVm/WfCkVRC6UedH9ZPTpxuTxfpofZvbN9yrMH4JqKZurLr8fD0LdXk3lAXZvK+z0okLDeHbfF1AulQd3yHNzjykiZNEN3mxdEa+5HM677Ot+Z9J6WJMVpYmgX1g9OHiCrf1wUe8ryeWUSykvFAARVhzblUHvOYNWweGvAx5YVyTH+Xv/u7vegCa6wWJ3vB7ZhIUPpc8m7O677kXGazwcsOazUsWa3QuPqttFhYoXmwABIByPr7pc3aMJe+BB+73q/adPSe3E4EcLFr0MZbH5KI95rdKWvq85buZLTqkP7zWe82d0nLD6K1LVjVCcVoftpb1pWWkfvxZ6TOJoxufhbSGbjwGwOGr/qtf/ao/mXV9eM/4wZDuT/oY3B3ob5hwS9QYLKmhJfnGWm4uBXeN9997X+4b2z3AtPvWZAQcL15jXXu+ynTqfsOP+K233navvfaaf7Z4nvlyY+XS0tCWC3q2P5aFFpct8kK58qfL38zx0NCg+qaTPtoJ8vKFxgbst6pe+L799tu+ffv2Zbvh3Exb1qNMBNHroeUNqAMAw2+1xIuMTuf/Z+/Nouu6zjvPjXkeCWImiYHgPFMkNVATZUu2bEllW5JVjuJK0quHquQlL91r9UO/18pK1Uu6V/qheqW6nVSSiu04HuLEsmSLGjlInGcCIAGQIDHPM9D/3z74cA+u7gUuQEoySGzy4pyzz57PHv77299Ap+Y3NxFEJYQ/A5odK86Dy1AYJrPjP/2Re3S0y5VmCmlC4Y3nlM/74ylup1g+8qHy6n+aKMtTolyXjgy4p0V5vdU36W6NlklrRqYHzgA4gGOZeHGVucBcmjR0pLk1QwMegGJqe8NAl1g/UjyLQ5kANTC7IytX9OUZd7R32PXq7mUB6GLlmSS+aVV4fgl5Vj29417gxYNs/EJhUcP3nOp4SlV8azzN7RwYc88JWPeLL31MC/da5U2UHlGkJ5TGWpW5KyfXHS2rd+0FRW60I8MdvNUorSUBgIctI0eA3qjQ8B13Zue5NeK3zlQ5CylryGXLUmKnDNP8DKuD0pf9pAQjtyRPOVlW93UOBb0/t7PtAAU6bUwMKyp3p6jQrRUb3Dcee0L9Qmr21O70ERa5eH3o/hRmZabCSdHpM6fdtm3b/NF+eHGKHnc8Nzc1eYAZfbLEO1iwWMShcgKizfEOwB3+BmG/8EaZMDzzHgcov3z1stuzK6BAmX/0t8Tf/MJph/0AFBtkuS1blhSxtMgGC8oWgNLSDacTLr+lE8svXn7RdSYN5inYAm7cuOmpk1A3mb/C6S9WhkTzi06H8nAcDuvOiy++GFc4zuq4eg2s3wIcAXGoaAy3afg7MI66xUe7UcAL/xQJnLNxZ5yw/qGlY/OWzXNNGk7HPBfzC+dnfQmAjqaPvfsC/eGEwfGt+bFRpN/jXy75IXiJAaKcIj333BEvxHr0vaN+Y4zxmDCQtvy4wmPNJo9NH2AWUM0Px/tw/12un+XHJrOtrdVduXzVb5qRgTDiB/nc7/zC8xJU70+kb/6ll15S3ks7PfeN8SX+WQXRX2Ljf55Z0+E55srTsYgNukTzY8DY7t522LHikgfUMSYGFkQb0PhfkQL2TlESXhF7A9TihdwVMSUMCXRtkTlvD1mVP46/CB/W9uuoejTFXe7qcN92A65uqNflCjhqVHvWDdhEsjXJpIi6G8QMqLkdEuIBtO4QrzNTXJ+AXvZAn3Qkp7grMjLyqgQJqwDtcncFUrE6uEaAd55THqpYBEzzEr+Qg2qcI73MTwhjV2VOu/86muYGle/XpodcOcid4EpiUgZZNO25CVGgr+UUu2uFFV548Iqo0XW9na5S9RoSZfeKTI+XafNQoDpiQhxByaqBnrkcrY6wcbRrUzDa0+1+LbYUbX3cK2mTXssI2d4PN1v0eUldLhC/t8q2RtR2eMBhn/lwJsPl7TnoymSSF2l0+gST5DyKzLxUHt4Hxgd6iHs1Pp95+hm/OEW3BmFwjCmoXrcFwrZIZzFjOXinTawWZRY+2hhBXyjb27Zt1SLumd99fL4BztLj3hYvKFtQr6HasekBaJIeVO+TJ0667bLQZ8ZbiG/glDTCLjpt3oX9LB75wFeNgNLRo0c9kMaEc3jeCKcbnY69C6cdr37huNSRDQsaF3ZJcBBgFi/PcNrLzS+cN/eAuo8/PuZZcWBLsLwt/dXrZ1sAUAUVGtYXQCTfJfxt7LujfjFZQtvhzSXh/MZNbd3cfEO6uOv8s+USTidRP8uPb3lVm6GOjk73xBNPaN0LzNLzTflZOOY/c5Tf1mDC8Lx79y4f9xe/+IX7u7//O/fKy6944GpxLJ1MEWIAz9HO6mDX8Pul+lGmMQnynj9/wbd5vVRYbqip8XMC6fLe0rTrveRHXKsf6XF/7MQxjyF+160Thutt96sg2lriAbsGnX0+2FtKFZkcMjKCHW+8eAwuE2bi3ly/BHbOf/ie2y9tGsUGIu1l1BWGhE+kXm4jJrthTxD41IgVrBZIUJJoyMiW1zezZ9zhzquuLj3Vq7kjjEa3GxQbxpRARKFUwWUKbA6Lr5kr1NFhUWelgc5NCpiOCCT8S3Kua1GCIxIq/K4ECRvAGpRbacFO4VkoosrnH8kLZ9fg6TN/J1SONSrPv5cAJKa0fyTtHU+LKlySLf5mKMjKY1Bl6ZPmjisC0ELQAi3Jrk8A/mKRLCGKh7olt9gdK69zO6VTe2Nfh3TGycIjApnaKMw5lZl26dWfo2Ky7lU+u8Uy87h+ObObgrmwy7wZVX5NAyPuhoQmy2RhMkvttz5HlBQtWG2Z+e5EyQZXK0r/lt47rlug+WJRhfve4cM+N0AfVBcWQigZq1o55n8EqGcXLl6UEN4Gz0dpi5SNIcau+RGTdmShAYTieAfFDYf6K57RfgLljS5q6fDe0uLenPkBCPhW5jBUcU1AfFJAur6h3vOi8i6YSyLg28JbOna1sOH88aPs5sem/NChQ36Tff7CeW24hgQS1nlKXDicpWnXcNqx/Hhvzt7Dc46KsOamZg9QDktTQp6O/XGUx8LxbPd2Dftxb87eU1ZO26CqA9gARvRzvkF02vCyX7x4wb362qu+npbW6jV2C9AvscIJMGaTZW1uV2Jxz4YPdqPiouI5dgPank0bDvCJ4Ghnx11tnKrn+mF0OtHfi7j4hfsjfjyjHxkDQ4BgCFSkZS6cLn72bGG4mh/va2tr3WuvveZZO/76Bz9wzz7zjMZdw+w4jlCZKQsuHNfu7Rp+n6gfcdg4o22ETT39eO/e4ORJLTDXjwmHi24ny8euhLF7uy7mx/vbUmF4WWrtvv2t76zI8bEKovmKD6CDsoQQkg3ApVYxNzfPU1AYZLaLjpUGiwdSykxoLCBMNE1XLrvhMyfcZulONpaEWHHxuyvq8M1pLOeJksxkMTspZQgMSlbPAeZY5kcmJ9xg34i7k6+deToif4GDyi1teHOuMzvXlYqanCl2iEmB8tEU8eWqLQbE5vDJ0Lgo0Cluu0CpB/fEIj/lm6H0ud6LA9iiuL9UoPMVaQj5aCrV/VZU7wrxKB+WKrxcpQ9rBpYNe0RRzBDQzwC8y/9iUZlYOCZkcVHsJqpzu6wrrkvudqWQsaPYtHukjeT86JR+0y4vqUtA3UkVoNJaYuGZ/tvU/sQrkplwmwwwZPNxz6D76e0el6sy9ohNpmd4zP2v9eVuR1G2N2zTniftC/rmJYO9ouyLv/TwM55qCQWGCZSFbLkGBpZYjRUXHEMC8EJzrBseW+GFxyrFMW6bwqO5IkzdsvdcGXMIHzHmAXZ2BMu7xRY+e08a5HNZVDZTY2VgxMrFFWdXi2tX3tk9V5zFtXuuzBmbRVXP1QarublZ1PCATxoQmmjascKRtncqJ+AK1o3hkWG3WUfrmCMHJJizcsVKJ+xHewLqaPvIKYBUR4q6fUGUO8Eil6Z2vyOq6TZZcawVFc/qTl7Mn59KmKxGVNGN9Rst+9XrAi3A6SasN1gnxLCIetVcPwp/m0GpQoTnub6+fg44B4J/sU6VXQAAQABJREFUYmHS3MQ3K5VWp/Y7HbouLmBofYL1jPtgUxqYgKfvwJLT2NzkWZM4+YnV16lWuIyWZvhqYYhPOq+88oo7Lkuf70mV3131W1TIGUul9aXo+OG84+VHPvHCMd7pw1gd5FqhzQqWOcObwFjxLb1Y75bjx/x26vRprR3SKb+xniRWnIvMKiuu6KsFXqwFmGQQQDLp+cXCR7+HYgY4ZtGzwRwdhgEMxQfHIsMEdE5Hl1Vdd6VZI1h0o+OEny8LQAPgNgTEg+CV0hwT6E2FUqz7t9p73G+7B1xKt6w/rctwf1RQ7jZiUlDvoFbPaCAOCZiiZgseabRjqMCupW/AjSlYf0m+B4E6+HNpEvIrEZvFqBdEnEWnCt+bleMBP0KKy3VQwGG9IO88leVJqOsCxL8eGHX9quPGqgpRoMvcOglEvtB6yY2JIp0lvjrciFg8UtiIDE2IlUMCYioHKvOooyqmpVqUAQHabvGK/7OidEk1X11OujukzcZawi3DTatsP5WKvl61yy5ZL6xVeTfrNyT/D+/0uPrsDPd69Rp3RRTp/+tmp6OkGG4pksGa2p4O98SdRtcxKE0HFXXuD7TgAThM8IV7FrF4/WYZxX0gojCePj39qT/BgVUi2tmCaP6wVgyJ0s8xJ87e0y3SNN4wkMSR9tUrV72BklFZ0myQqq/oI2CLZ+ly5RthQhwqNuVCDRcnCCWzPKgWxxbO6KulZeHsmWu0H8/WF7gHlFBGgPNlGdI4pjljpwQQEZKkLGwIYqWzmB+LMvzjbaL+rpEquZ0bd/pjYjYEscrkM9Efe2flpKyUAZABVZRvxQ/+XIBGh47zAdDowE5R2n0CQJOM/SjHhonfq6++Og/ERwVbfZxtAdr/vffec3nqFzU1NfKNEDbsGxGU79MpIVG+EZt165u8o/8AEvFjUwPbEs+2KSRMOC2ecYTnh3GXabEG1kovNfH4/myGGGcIhaLGkXytrxDX7sNXy8OuhIvlOJ15XKwha3XSdPz4cbFIdmsD8eQcL3isOLHSND+7Es/u7YofdaJP0reZr5HLgOofa8xZPLsS35z52RV/u2deStIaGx539s7ic4VtlPZ+9tlnPc4Iv1sp96sgeqV8qWWVcz4f2VKTiN4Nx4rPIAGk45iAmq5ecXc+PeYemxl1GZH5L1ZUNyhA2CSrhLUCcFCe55zSKdSClCKLg20T0wLRve6lDWVu/+YM9/9dvesu5wp0C+ilweYwuzhPa1EeE8WoSIMXHl3MgPdmSzNEd6/LX5vtmgXKvyrw3JA05tZlaeIlM3hJcAqPlcMpLcCkx/NSHfqnUT9XhBChFlccJsN3SMCvVDqkfyCwenRYJstzUt21jn73JxNdooYDjQPnY6hOkwLTmDFPFY8axmCgorflFrpcaRm5NjLhfi2d1mUSZHw5U+kmy0rdpFViNqGoC0B5SpPmpHjrhlW/drV5l6KwobgjKvRpsZ20Ts64k2qvw9Lm0SD2k2F9UwQ3txTlyUiMFqLsdFejiV6rkywhTriakT63v+e2m9HC8qvJNLfjyWe8CipYA+gPLDgdMp1cLXaFMPUvqmgP5SPCf1g5e/3V1/wCxsLCj7FjjnsDAfCFwlqVrzEWDkc7Z2dleyrSkKitmRLmhGf6pihlUPIQSEpRfwzHsfTxMxDAPQ5rZKifQ00YoNo2Q5TFwoSv5h9eJEmHMOG6hP0svvkRF3awffv3eU0+H334odu8ebMbUT+iDGGVWtYm4fwsL7uy4Th16rRYVEbcTvE+G683caJBFGXAz8qCGjK/kZBuYaibw9pgcL3RctMLpyFoCfvNkSNH/GIPWGcDQDvRloUShgI0WFm4Ega9t/V19V4LiM9s9c+CLQC4OyUjPW+++eYciwZtGf7uJMDpAJRhNjVs/AgTy9G/wiey9n3CYc3P0iBNG3/DQ9KTrE1ZswAnAJqNX/hEwuKQnt2H07O+Z+MlOpyVg43ZVp1kUN5f/vKX7q/+6q+8bmx46C2OpWHjy/KxNMLh4vlBGDt75ozfMCP8SJ0gkoVdvPTxt3ax8RT2Iw3m/vMSurwjFhGIKKiQ3LJ1s9osYHMijJWb8YGpdAA85VipbhVEr9Qvl0C5EwHBCyXDAGFhYWAwUcVzTBRQoBkUH77zjquUWrqyxXgLNOndmhJ7g3b8h6SVw/P8Kh1z0F6Bh22DMooiPokGMTcXSl3c/7BJRjwEPT0LB4sgcVTGPIFMHAC6V9YMb2QXaKLtdNkCzoTdkZHqHpHFvn7xJ6dqAk4aB2zDFhJMvjkIKt6Dg30kU2mA6+cck78eMHLyjcI895OxSffJ1UsC6SnuHYH6b0sIcERAp1cU6Vu32t01Yfj0mX63N1vaDGTQhaQ6M/Pcu6X1bqaj3XVIh/ahvnZ3WCbQkwWAp2XyfEzFB3SPqI1GRCXmGYPft/QMhRndKYDmPlGuJ6WBO1+tis7oEqm+2ygw3i2+bGygH0kZd0ekqSRNbZImXvKkCVly6+l3+/PXuhaxclzqkmBjqVhNVKfK3i5v+RGz7B1l69yz4jWlD5gQKotMpfhcVwH0XE/wN4wPBIk2CIyt1+JoII6XtgCH7wFxgGhbSMPviDupDc2oxl2qzKxDJWUxrBXLAADDAF04DvfmGNfkCcWNtAoLC9wjOkYGeIdduFyx/MN1sPex4sTyIzz+Ger/gN48ae/48KNjWuC7PXUM6pSBJ6iJ8G5SN0BOkRbeZIFX8qddAV+NYgFgQT4gvc8GrPz8xdykthoX//iE+jXGOYgDZXFc7zhJG9McxxxGn83NzZHQZpaIA1rcVb6hgUEP6vftlz7pWUEyykWZmBuZJ3tU5hzFw1mbQGXj+33lK895oO1frv6J2wK0JVRoNKcAqsJ9xtrUIvfKbkB/X7/vJ7S/hU1V/2UcYMab9Gh/TmcKiwpFsVaf0VxnYS0trmE/eOgnJsbdbmmQ6VUendqUkgd9pVd9hs0Tzws5S8/Kbc/x4hCONOEB59TiX//1X93f/t3fumefedafdgCy6bP0u7Cz9MN+sfKytkBDDNYVsaSIMoCwixUv7Gf3jJcLFy74dmazy7xP+Xh/8cJFjcU2t0s84xAMsD5YV1/rQbTFJ0/K3S1rj2xOH330Ud+m4bKspPv5M+ZKKvlqWRdtATrtgPidUD4PsFmOg7rI7pVBstDEQbgLZz51bW/9zP2eNrYaUpqZ4ucodcbumlg51qsHZhryVHm9C01QKelaKLMlQCjoDJ/bmd4RUahn3P7CbAFWTWTECYUf0yQKH/aerjZ3XAZJxnIz3bDeT0igD/aINC3CsH8MyJJhhp754Uak6QKACBD2aXrfBP4obRF7PdU4Jv835dOEUdvb4Xak57sLohz3Cc4eTc10h2eGXIXUxF2+3en+76vtbkNZkbsxOOouiqf6P9SV65uluY/XVLpbOUVuXKD5wK1GVyo+72MzUnkknczDAgMjoixTg2FdU0VR9i0IoFWeuQLJaAfZJUXRMg3gynQPj7M57ooVBh3WW8XG4SGAEijQZuXg2nz3s9u9ruOc+HfVd6YQMrW2Vp0xMn42NcfVP/2c7gTQ1a4sXkzWTJALbbos/4fpyli8IrYFVEj94R/80aKgivBQVlk0AYbRjrEI+BxXXwb40e7EGRLw7pGwG6B6KZuYYHGev0BH5/l5PpN/gQTEsPRGX0LI0RuhEeUvWLQvqn4B0IB3G/26BWoXDD4RFoDNgo51TMAr7UE6fnM/e5+kPOjC/CE/wHKO5EYqRCBgfoOqDCAIhDaDo32o+oB20gY8mSsTr22HBNbOiKoHcBvSHGnH4YQhb6hsZTqir6iotGir1zgtQN+17/jNb35zXltGR2F+QUMGwBggSNw5pyWBb8561Oz57fv9OGGTxUateE3xXNB4NyNipZvSPE0+9CO+IVqHGFOcbiy0DsZLM1F/6kIffPnll93Jkyf0O+n5+3eLbQh5hf379vlTqaWkx2bvpuQD2JzSj2ukbhLK8EKOcrABBbhz5Uefpl2RYbgmPdJ37t7xcxMnYDt27NSYkpVIbTK2bNmkPGr8esDYDX8ey5P00QaCsZra2trPbA4s3Eq4roLolfCV7qGMHG2mCkAuE0P7IxkWmMUci9InH7zvtguMVbAWxxo5oUR6BfruiFL6SJLYNkLAzoIgZAg7RLm0cVSLCv3jlg5XpSPr0zIx/fWiWctJMfJI10AfEWtFv0Dx2pJilzs6IWq0JkNNrCLOUjDlignwNJcGPzJp6IdGAs3cMvISmpCtMItcYR1BHzUaQlTkzzqlSZP0i7d1IkmUcN23SsDxtCi5pRIIzBUwfqq61KWhnztrzF1va3ddEhxsl1DkuelUl3P3tssXC0WXqIZ9ipejXLRVEF05yZWqvaEsS9bSa+bgYC5DbSdFaMFGRvfzvgUFxE8OrtNd2pBAo/Y+s1VP1fun1+QKXGS4m+J5TlFbvd0VtBMbAgy/tGkD1Lu+1j33iNTaCSQA2JgYWcCYcBfbdPkCPER/oCp/dPyE2CX2unJZUVvM0ZZQ0YxlIDo84w3KZ/9Av8tXvwEksMBBKQNYRPNER8fnmcUagLcUsB0rnfvhBzChjVh0KQ/3ULvgEwWclpas0TwW6MsF2MLPPaGx/qFYQFjoaQMsEd4VpTk1RfIUAglp2gzSFhma/IyQQFqkz4aPH462juegXpolunAY0t21c5c3HZ6i9FARFgZXgHuMhRyWxhpjjQnHX72f3wKj+u6wAdBvAXoLuUGBQtgFDh448BmwzbjgOyAs19rSKl5jaWRR34D1g++UiCMNwUYfFNAMiwVphDdJiaRzL2HIa9++/QKpRb6P//Xf/I27dv2aLwNq/6yv2UaRMjPncjXHuIDfGGovYx12EVhbCEOfZ5PAlfmaeZuxRxzbhEDBZ5MOsQoeZ0YJcVMZQxpbjKMilY9NZqrf/HK6NT3XTskah0kC1rHGF6dA6NrGwqmxg1q5V9o1sV610mq1Wl7fAgy0NSVr5w2spTYNg4YfCxcTSSyKNoPkytlPXLcEpp5Oh+oZf1Eif97eEgxMU/mqxRccGfazpVN6EKdFYxCfcYp7U1SfM4Nj4uF17jsVJW5PrnRSK0wsB0CeFjie1ADfUpzvqsRmMaMJYFRA8PSaKtdaWOJ1R6fL/Pdzk82iPAtEKi0sHM4EROlYycb3U1y0bKSItSKApp8NOigWiT5tGjrEwjGq8FP6MfCuia3jaZWtTej+tHi3q7ukd1kU93S1y7gmpXpR4Yvar7ks8Ydni2INj3ma2ndKdcmckKClUDAasPnO89sj1DbK6zMu5PeZtiew3mfpm++WmfNd+t0VO8enPbLuCMldeRH9fHKmy9u0zS94mQLb5pis6Q82yZv/w3ylPdA2gOrHryZ4tA9IhBLN0XYskEv7pmmRYgFE73F2do63Bsg9xh0SWfDhWTTDOF/W96EeLOaAZoAnCzgLOXMOurFpB+rf0dXp+x5sFml6ntaYg5KMJgPeA5S5ImzJgq7Avg+Sjh8fyifaxVrco8Nw/B/LkW5+Qb7LE3sH6aMNJPyd0IXNfFlXV3dP82+svB80P74DR/8dasPnnjuyaHvdun1LFEwEYEs+0xR8F74DG0o2XWxCWbOWQ0Hmu/INvyxHPeg/CAC+/c7brquzy1v1Q8gYYE8dsYLJuKHeDQ0Nc6xfjCf0xrNub9DGpEgCu6THxpx3nC4z1gwww9bF+wzN5WwuAeRQ7Wk7nm3zyTPfC+1d9fX13uQ5m3ny92NCm8uLly5r05rtvynjl3YMO+J/IEFc5DgA9sRbyW4VRK/kr5dA2emw7MoBNwyS5ToGHYtWLNen4+OPP/jYHRztcWnFEtmT4ZCFHGwE1yZERRVgzBFvbjz0ydCC/7kSPcvilxwQEC2b1vG1sX/EyWSNAOeY+HpPSAjvtuJs0e77VxVb3B0JZyWJDxsUv3F0jGXWdYmKXCgAPS7K9aSO7vKVo0eJcdKO5Z06qTJFTRSEw0biGam3g+LcLX7McfEfQzXGEAvTyhX5D+nY8KIAdI0ozN95dLM70XHbXZERjkkdc1XInHYl6fqfIuhbDqucYwLRaWI78SoByUj+993N1gdwXpiZ5v5dZY4rywrAcqug+3WxmXz72efmFhn6GX2EjxmopbrvJVqxCSKkdu7sGVdTU+NVWiVSERZGFh9YOaIXobn4s9+dBa+istxl9mR6qo5RWOfCxbjhe3UJmGLRbYeOuUnji3aAZRb1mwIJXRLom9QzwB51fSysHEPzo6zwM8M7CXBAbzbv2Tjk5ERYLL7o8pOffRs2OwANngHUWF/73ve+5+vzZZRrJeVJP7giwAeVdO3aQBd6vPIH3/+u+GzrY65nfAN+M9rww9eMHm/SvXDhogee69cvbnLds3Joc2rfNl5Zvgh/KM3UIU+gNUOnK02NjV5bCCccfeIpZs597LHHxMIUUJzRHNLR0ek++vADD67RtNOo8SUk7jfcjCXYwHK0nubn5eu0do0fQ2wIU7Wu4Ki3/eLV0axAhtuIdt+8eYvf+ALuoWCn6xQ87AgPdfzY8ZPuze/9W7/JCb9fiffLR1UrsbYPYZmh8rDbhEf1XkC0CXqQXniA8dwoXq3JC2fcNrFmlEv1GZDOD67ZRT662QcUoE3gdo8E69JBk7Gc0oWqjCOPCQ2+H4v7Ijs1yz0mbR41Om6D7zq8h0WosF9Chbnihc5Q3hKxcj9JynE3BaDvSq+xiuddmlgg0tH+oSPYLKWBVcQpAegphCdnBRSDkAv/haLclVvgUnUtlEluHei6IdULkHlT/Mk3RFeWEg23QSbAv5mrCWV8yP1M2iwuJ6HnWcZgMlPdDb3fqAnsb/raXM+VDq9yLEnAeiKr20mVh7RkBMZlrJmyxK+XIRadOQC9cBGX/1Z1MpchwFKdrw0U7aQ2PjEjgP/YU66mpsaC+CuLIZM0E/SqC1qA9ripY30ElA49+lhCzQJ1Gf7Q0tK1cVkBGBOp2lAhQDjlhQNlqlsL5YCoTNXrqqX3tcKP+XhUHsYngnPNTTc8NQt+0c8TSNMO1AsQBHUKIAyVjHqwUdi9e5dnm4AF4rT0xt4RFRrhsE6B7A3qZ8T/5NNPpEFn0qeDNhHisnD/LjjAP44yvfvbd70atNra2t+Fov3OlwF+dqitTz55eEFZCvoAfYb+jn7lhRw6yNE7fOrTU97cPGE31tcF69JCEfWO7+bXr0XCfd6v6UuA6DUCulCZuefH+GEc5Wr8VlbqdLWl1d0Vfz7rvB9j0hCFvADCy8YOliH5mjSBcFiLMKJmApa06XJcvPaB0AbAh5cc4h2862HHxgZe7w3rq70qzvC7lXq/CqJX6pdLsNwcv4RVRSUYLWYwBgADmKMco3Z53sUPjrqNsrBXIot5cJLBk5whNgXUoUU7OAI+lVq1PK19ZVCh4zkBtxyoCQKl8HYU6fj2O5nJ7oTYJt6fSHVXFa9e8WuVjgxM+1SgPozpiBsAzdLKux15Be68jo0kPzc3MU6I6tswIH5TUaxxg9qZZ4sFJEnW04SDE3YA2WTF6RNbxlUZVmmV8B+q49JV3nIZmnkhddpVSKgvT4A9SXnOpCW7r4sHumBi1A1oQqsXqs9Q2Eel87rEVbnunBRXVrTB67kuEysHRemUqfAKAXQxUbgxdvUCIrCPAGi/UKcJHYdhnOsVte4N6YU20MVEzA8+0VU3vwVYTOD9Q+qeI+VEFi2o0JioRt0ci1WsOPgjyMNCy7hksdyio9G2W22eF/e2TN5XVyMIVeYXzljpsKCifur4iRNeqn7b9m3++DZWfvNrtfiT5ceiP6YFv08LareozX1iaWGhp6/UC9QUSZgwS0e/sGCQL5pI2OyfVJlgzUgXhZywtAXtkim/DJWb+cfyWLw0X0wIynNDZqZvSi3eql7oxNqcvgDrC3znVVXVMfu6pURfAnAXSZOMsY3Zu/CVjSNjY1PDJleypsRTa6FG56kfLda3eQ91l5MPeHXpi4vFCed9L/f0H8YzcwbrbKfYNxgv8Pp7Fia9Y8wClgkTbD6aXW1NjR8jyEMQv2rdeldeWa0xIskZtUXYURf992Mw7H8/76kHRDuIKmtm2UisDdt08tUi0P/8819dcMN0P8vzeae1CqI/7xb+HUifQccExMQTPaiWUjx2rxwFWRoMjNbr19zAqePuUQFagCtQK0kDOUkgOpYb1QA7Lit+h9MnXR5gUM/xHDBxVCCalNCZXCEBvOdF1b0jn4syl/3eeJo7oxOoPfLDbDiq7EqHBuYApuZRd2BKgle3G93HmaVuUkJCSapD6viwK5eJbXOohZsQVS8TyjRlWsTpoE/8zUmemn5d7BqDip+uyapalO/dopKvVUPkex3QSotKzFLLqCk6nis0MTeI2vx7qRKIUjhpmnVra9e5n/SMuVq935Y04daqPRHSWKtyAqCHddQ2KH7QDAl/ZIgat1C7LVL85b3Wd+pTSd6VOrV1oqhu2LB+Lh0mbn/kKOoPm7ZVF2kBKKvwez7/1a/OtQ3jhoUGZ/fha0CFLvULI/7R4XgOx7cwLLB1tXXSJlDmKb22YCGoBYiHWhrOhzQQXEJADt282TpBgM8Rf34WNjr/cN6xwhEeEADoBQigaxcBI1gv1kt1GVQym4ssLfoQ92zM4PfMl37Z/Y/s95sDqM3UjbYcEnvH+poaLxBp9bYykK/dW7pWB7sSxu7tulw/4oXzgzrIMXa9+Fg5VrcyEG7VxW4BBP6QF0CdoaklDLcpsew7YSIegAufsPUX3uHCcQC+ADj6Df0MwzsQexBaNE03seL5hPSH9e2KNKuwseMElmcrQ7x44ff23RP1I1/W5z6p7esUixUUXIT8WGuLxR4J1R01rzdv3vCqGHnP+BrCmJrWEdgwWOM5nQH850mOJUUansjfftY+5GX3Sy3nYvUJp809801tba3fiPBMGWGrQRAR9qcHxa2C6AflS8apBx2fCQfLhQGiixMwAW8mJ35QD0iTtD/9zb+60t67rkxUV2ABQDp7UrpTY6Wn8OelbWJKR9B7ktBgvIBT+jhhTDlS0w2LrPiK1+u+XFTcdgHoc+Jx/sWo+KbF27xLau+2DfbMLV7JKucaUXH3aBEfnLnjzvaUuq1C2n0SLhR5jLNXn2aR+It7ZfFwWBSxLB2FxXKwbui/+3Qm1Z3Rr1/5ZohFpGGky+2VhosKKZqTyv+ANxpyOxQAyq4yzzkSkLsrqjRUciw62ttjEpw8JQr9sDzuSgDxY73ZlpbidivtYkXDkEu2JtYs8W/PS3Mu8c/3hm92ajrN3aiqd//hK1/RJB2ZOpiMbWP1+ZZiZaXOwvj+++/7RRCz07Z4UQvGjrnwPTzAt9pvuccOPTYvfHQcngEJqEEMO/JAGArwUFVV6ak+jY2N/rgc4wqAacYweVq+LNKoqbqio1fiEcacheHZ7u1qfgYymBcAzhzNs6nCkl+RKIBYjQO8sMGyvG0BtzTC115R3xB4ZLHFERbeafRAQ4FDv3tLS6vAdrGrqanxoNsH1B8rm13xt3u73i+/6HTg9ezo7HCoaLOTOsKsutgtwPg4evSo51nmO9r4sO9kV2Kz3vRIVkTbO08hxi/8PnzPO/oi6bEpKysvEy9xk9dfXFdX6087wqdo0WlVVFR4EHv92nU/lqBiR4ex/Owafp+IH2WjToD7u3fuuhZp15lQ3+bUhX5fvLHYj0XGC44NBpvLi5cueuDMhq2mtsaD744uDDKhhSbDp0l4K4Nd8SNPnPnZ9X75RafDvGBEFfJCVqBFpzRsmBZTsUdaK8VFVsKVUuJFysnHYhKnw32ZkrWLFPMLe83AYWGUQqv7kiftyzESk9BdWaVrkYWw18XGAYA0x1AdEGV3cFJ6iqXyAso0Dv0Vn0wku02pMy4bMvFCTgOwQGEAlZPigZOWuwh4VBnS5b9eaVcrzK6sVFGlZ9w/iJK7JxnLe1Ni/wgm0THt4LMEVh8Rx3JrZ7sbEaX3lT5Jd1NegK4cf/N0JN4rSi9q8ITTfW0oNduBdrFrnB6ZdGelkYKwe6dH3ddlEKV4rF1q+IK6BWnN1ml2stKspdDzHcKGnaIePJEt4UKxpggJuW5tPS5I0JKU2pXfs6ocFhU/lt8HEj7cq/psF/UZndIIawyKXSZZ5c1OgGo+P/flPfHNR7QxaEFX9bNH5vEj8o4+xnHsqpvfAoDXa9eb3Pf+7Xf9eKGtcAY6uaftWExtgQOI5Uv7DPOX+RGOuOF4+EGBguJmgIF0cPZNMtWfsQAIBQ7q9pnTZzzfdIPANN8LEO5VV+lUBYobCzq6jWEN4Sg7XC7LP+xH+QC1xIPHGSML/f19nn0MU8KADxZ/q6OVLXy1OlI3K39vT5/XhWvxqB/tAksI5cjU3AO/K6q73n33XfF/l7uNDQ2+TrFAuqVjecWqy0J+vDNn4czP0gYQog0BwBbehFi81etnWwAqNKxOCGAaFZpQ1hfC34u+cVd9zDZjscLgR1/RqPKZEYc+zkkMLI3kd+nSZT8WGBeAZdYx+4aWH5Framo8RfjCxQtu3959/iSE9KO/ezhOdDrWV2zMWFyozGwyUUt5+85tl6W1cp2MUyHLAPXWgLONB8rDRhfgySZ7566dvq/TZtt3bPfsMFgv3bS5QfHna0eyMpGG5c99uC72Luxn8ZZSv3A6VnbLk2c2AHw/WLbC6RJvJbvfGRAddP6AuhJuUD4CExQ7e8LwM344C0cYFhN2PRwZ/Mf/+Gfuu6+/6p4Qgzsdg4FkjrCkgZ99SMvDwpIf78Lx6AT8rINbeivlys6V+tnOcLnlpl1YJNDr+e5Pf+gautq9WWuN0HlJpovSW6qwSQA93unXmiSjBGr3byUnYNBEcWeUx2iKhP3g5QDWRuWhj+RBbZU0drwiHuLr+j7vi1r69xLa26odfIWivS/K95GZcbdeQPoZWSz8lYTiTo6Ou80CpCMCsyWKlyMgPgN1TuGlkMeNCTB2KOUmsYx06n5UdSgS5fUVWfWr0zFZusKIvq+ryqQyeBddtnmtEXnoVnMMJae5iilRlNUWbCwuynBKu6hr+TOT0n0745pVnsfSxt0+WSa8LF3Rp8ZT3c9Tcl3VSL/bJOXZ2cmyUCd4D3Vc5+Qx9WxHcry3O8ZGhyjudwd0fFi3zT29/6DvR6TKO9SwMS6MWnNvuT04sVkoAXibNwXW16xmjB/ayxxtiOPKGEVwClYA5plwOMKEn8NzF/6WDv7c23vewQqBKimMRVy/3ug+OfmJF1YCXEDh9WwgohbX1tZ6Yy2XLl1yqNECYAPUWawtf9JmjoVnu1tHzxh2wUw3VDCMODA3sGm3/MPlIg0rW/hqaRNnVFpzhnQaBNsHZcePPgaIBvAwz/f0SguQKPBoJeiTAYnmGy0ejAH+4TuHDxb1Wcx3lmf4avktxY+w5sLfwerHJgI+9GePPLtKhbaGWuDK5usD2RVo0LE+/S7cpnZvbUsygEdYGAjLd40VBj/6C8ZyZjyY1vSoZ9Jh3WOjSP+EKg0LCX2KDSaUX6NMk1eQhuRmGjZq43nWXbt2zY8H3pmzstkVf7u3K36UCTwBGwrAGf3I9Gcc1OND0rNvfMNWVqsbz+bwuyvjJoBs+jhtwPu7dzscQD9NJ6ntMjKEXnXqY5sNKwtXS5+r5WHpcw37heNZmFh+FsfehdOxPPHDomdTU7N7QpYSA6Kepbryr186iIbvkx3Zhx9+JIMYo9qNrfcLMhP++fPn/cICP90WqU45duyYKB53pc6pwj0jJd3wA507f058QmMaGDd8p9+5c4dAssDHlcvuelOjVwb+xBNP+J1cl44Tjr531Au4wPvHJIwqIjo2nRHqS4UMIZy/cN5PxCg1xw8+N+zNA1gOHjzg+Xlsgl4JXYDOzALNwnyvIJr6kl7TpQuyWtTsnpWpaIQIo12GKMEatW5IfF2pWnRZzq7I9HSlYGORvo/OeqOjzH9WHjNa/B2mDWMB6FBodECPCuRuE1vGBgnuNSvKWbFGvC0AfUmU6RFRfF/NmhIbyJQ7KJL2zzsn3c+l+7hchlteXVckSkCquy3qbuPIlBsWv/ZdUZ5Txf5SpH63R2waZbJkUiIg7rG88M+IBPyGxVtdOC5KB5uEBB016ZZgXpGAeT5toIkQHdLXBKIPyjx5loQQm+WHWW+ozEhUb1fb1qZrjGjRaVEdPxIPdlrfiNuk5quQ4EiuwMIa+MDvt5udwGHSSdb4Op+a7Sr37BNVp2JeTvSn8AQ67+VD+kB7IJXOIv3m7/2eB1UsNuFFzJqGsOaPqki6OotguE3tvV0tLs/hecje25Vw3JtjYd2zZ7ef76Aanzt7TsfILX5OYHFmzkV11YkTJ735ZUxr1wq0oAcc0NPXK+FALYaAgUmdjGRly6CRFm2o2pz6GQtDuOyWt/lZ2ezK+/A9xqEQEAZg4Gg3gD6UtkfFi9+kOb0BqrN4uREeK5YefCwdAkwId0tAtqWlVWUq9HM+dWbeIw9b8C0/u5KP3ds12o/n8LciXNgPwzCwl1SrDe2dD7D6J2YL3Ghu9ms5rC/x2tzam/dYocxSH83Xemzh7UoGds8V4tew1hycpeEf9If5atNmsTVpnQd0wi/ND4uE5TpFYEOJIx4C9IQFh3CqBGaw8Wbp2tXi8J5+BqEO4Ay2oF+yOUTQD7mATeq/4AoMABHe0uCKs7pYmt5Tf9BYU6wTKuIQBnB+/fo1Nzgw6McL7cM45USETQHU6xKNj7DKUUubq7lw/ua/mB9xw2lFl93eEY53n6IlRWP4QdSb/qWDaPicfvijH3nz1FCz/tuf/ZmA6iH3b1552f3n//Sf1dnL3Ne+9jX31ltv+Y68adNm94P/979qaXeasKrdn//5n0tVyia3fdt299//+99rgu/xx4tv//ot97UXv+F5EgGQr7zyivvLv/xLb5CgtrbO/Y0sAHEs+Pc//G+uu7PPHdCO8J/+6Sf+6GfP3j3u5z//uT/WLNWC9hf/51+4ndt3eNOu5wXa//RP/9TvBukgK8HRoVnkbIDca5mhCHzw03902/vaXSUaNhbAkf1iASgQ6BzU4L6tcHvTpmWMZREATQE18NCyYYNThfd+scqeqkkrQwCZPpEn8L5dyWPt8LQAJ5Te91OyXPnEsPu68t4+3u/+eqrdXU6rdE+uFaU5LdN9Op4iC3zi89YcVimK2mYdXNSpzxSKryNdZUC0MTTneFPh6UoZQydLcaiHuyOAXjk94pI00RP7tnirJyXo+DVRuTXLul6pWi4WHzR1pw16NZEDKjaLOlcnQN8lavUNCbycV90+Hk+W37TbJyoE2ksy9cP0OC0xpcUiXeB3uQ42lmFN8gVaCIa1Celdt8mPS6PYsFBMTspsusZQ+MRmufk9SPFYPD+RxgFYGipE7TXwZn2Zq41FW2xYdOEZzJVwX1hFoIWz9rFn0kyXNU8ci2nYWT7mZ/lxZQEGpEMNgvUCijnj+YzUyuXnwcZR6Kl1v/3tb3WMvdeXnSNwgAB5olsWSlihwuUqPACVNHGWj+XL1epn13DZrC4WjytlIb20Wf2ylK9b1Pm6+lpRDdeJItnvgRBgh/D86H8AeYAJ4QEuHN2jKg+/DaJAFmptMZAfXb7wc7jM0f6xnqlDh6jQmFV+7rnnPNCLFW7VL9ICjI+zYuPgxIW+iLO+EAkV+OFPeNS4scGL/obR8egP05ov6avc855rtGOTxskFaQPQb9xolmabVlcrVoMS6aqG/QmqNZikvh6K9GkRNdK92rjotOyZPOm/nCbB5wz1PD0j3bNmgVUwzMOpTrz50uoSLreVnxOYLskbgH/w44f8AcK25Ete1IUTpAkJF7aL1bJZmmKaRf0tlw75SlkmZaNsY5UyWz6WB1dz0X4W1q7h+Iv5MXfAtvMVjQ/bHFs+D8L1SwfRraKEtNxscd///ve9cMtN3UP6Z2HgyO73f//7op7scRe0G9ywfoPDlCQUYXb+dHDUI3339dcdek6hakNF5rjxhedfcG989w33d/pHp6az/eKX/+z++I//2HeoCwLDv9FCAUGQxeL1118TxfmM13F45MgRvztlMr508aLr1DHKblGU2m+3u5/80z95MM9CspIcg6dfR7BQlQwILaf8DJiLapO7ovT/wdSgB5nTShu+58gQnE1ZYcsmA9aNRgnTTYt6Wy02hISc0ssRC4aI1/rpm0PZjuPSBID5mYNCVaK+8JQ0ZewV+GwUB/RFUZp3zYy6BvFjD98acZvXSsOHNha3JziyTnabJahYmpEiwC/QPzrk8pS3OpQlOXcdFp/pjDYEOaH85l4ucjMghusOUfD2ZIohRPmNKPnboi5vVPVYSjhByRCo7tQmo0q81hg6KVL5QduiV2ijIJAvgF0uVpTdAtLX1KYfDMsSY1qG2yDtJIek1aNBm5rzJQJu+hoNXbeWVU4Et6YFjsRbog3SlDuZnu/y9x2Svt5aP3lTTcZnV1e3BylMzqsuaAHGBwJ6zB2AqniOcGEH+OsVNTXgF4zwXobDhe+DuAFAwNoY7rPvI37hdyy6LOSAhHRt3EY1XyKc1CYq7maBZNRpoeGjo6PTs2pgJZBj7yC8dMxqDg4vuOG07d6uQTkj5VjomY1Er4gqUKwA5zio3pj3hqIGgAL4DA4OaKzAchcB74RljmNzQH+krABu2Fc+PnbcAxiIJ5w0GhBjvQhcZOYKl9vu7UpYu7erfNwxqePDWMUGsbOE22U28dVLqAVoNzY4bBg56aUfRtoyEtD8LDztipwALvwuEiO4IxzsHDgLF7wJ/ob96C/0JyjMsDbBY3/+/EXBi8sC7TfFd7/RHTp0yAvojowMu9PCByMyhZ2apnVMGzo71QVvABTbdKLerXFPnaAC76rb5UEjz5TL+ka4DFa2aD97tiuAmXWAfoYfYwXZL0A58gEQWtiU8EydCqQGsLZWhCttEKBMN15rdFXVVT4MG0tL166UI3wfq1z23q7hOPH8mGvgIGDTu00APwziLY+Vfv1SQTQNPzQkwxECEuxQAHcMFD58kjp4fmG+52OikWFKP3nypN6XuCkt7HwcOhLHO3QeJkYAdW9Pv9JL046twfsZpaRL1n3g4zt27GOpcsr0wmoIG9wRQGaCJu8MWWSjgxGHMqHUvauvQ4rMu9yv3/m1wPmods4lLlfHmEtx1DPcyWLFpT6LhYkVbyl+owJk0dL8S4lP2AEJ95z76AN3oLfdrc2UJTH59aRnuUIAoITdol2y6jWixe6qeHvLx4Y8hViIcHHHxKNQ46KCjiO8h7RfDNctrRxJohAUyEgKVFjvdC3Ub58ot7/RpNIl3mZYf7LEkuH0XcHjdT1dLnvtOpdUUOKyyipcq/rMafXBsqE+91zzBRlfGRWP8pRL1gIedoMC3flKA37RRKoRjjuqdkgW68naKVGi9UKGu90NUckfk07pdPU1KNV52uT0K99p3bM5SVU+0TVnIkIwcpeA+LbMSdeUku5OSmDzx5Pprlq6qHurN7lJbViuiFL93MAtVyye8eg0wuUK39OCOjyQWfFxnRhI761YTZrz17iXDz06t2gQnvHGQmELQziNh/keShSUW6hXhVrIEnWwIzD+mX+W0qZamhPNYl44vp/pZL5w4aLrlzAf857lXVKyxvNqMhc3aC6F0kv5Ps9FkDmQU0MAAMCDZ/KHdQNwTN5FGqM3pTJwbGzcA4Z5lZp9oA7UBR3UjzxS7IE4hmguXrwgtr9GL8BVVlYqXtfrWk+KPRuLAfJY6S3kd1uEFdj9XhchZ3UzuVBLBe+gqMJzT39io7OYIzxENtbdRHlp2RjaxnKx9HlPvyJt5AbABO+8844XYmUzzDNCiA0NGz0h7sMPP3Rbt231pzFQf7H42SFDJ5PCIrAO7dq1y2OYeyFURZeZ/ozRoSKpu7MNIGru7rTf8UQ/wDzsqxD26PdWJwB1bS0nONWuXfrjm3RaAosZddqwocYVaCyliBhjYz463/vxzPg9fea0e+P1NxL+fvcj3y8yjS8VRPPx8nXEMa5j58uXr/gOgHS43ylpAmXnhaPDwKe3b98+d+DAAeldveWpzbzr0K6WnQ7U6tZWBtsa8Vq188o7Jn7ANsImDNonDz/l+XLefvttT/k+o90lkzVuSgBpZvZeRVOHTXXVlRu0g6t2L3/zFU/R9hRwge5EHZMA2izgVSLNeI7dLAtwljr+5+Fo6xJRl5gwaJPlDJxpteP1S+JTP3PcbRf/rhpOWjLElyjAiQAhrYj2CGUwrwoDYmFoScpyX0mXHubkCMV4XqDoB+XFRiZF3yBF2j/i8YzAj50sPsroPGFHOC2q7i9n0l3H2KR7LitF4FfqwFTOXE06hTnpbnNBrvtN2Xo3XVjs+eqnh8ddhSoBP/S42DpGBMzDOk0mBIJLBUjR2blUAE2LdIkfGop9FszVKje80Kkjg64CVg5tEniXpw3D4ISOBaWhYygnz5UO9C3INgIrS8P0qKtVu1/VEfjJ6o1uRMKYXg1Y7SZ3tFnaPvpbXYGo14m4cX2rIUmLF6tck+orR4emXPnTz7uampq5PkNfpr+uar+Z36KMK068urVhh/eY/puImwOLAhZI1yfq2BCjy5ZTAfJeiiM81C1kQigz39KAapIoeSzMLMCjorwhWMUCzZwB8P68HHMlfStHbcA8BRW6t7fP7ZY2Ap5ppwx/JJ3i5/REywG4YU3ZoHUE0Et9UZeHJUkABVoPYCtY6pxIu58QFXqDiDgQbVbd4i0ABRoK6uMSMEsEaLK5HJSK0p07t/vvk0g/F8lK/WPpY4LSQzEtFWCnbOOa40z4kD6UK35mxgUA/eLFS15PMyxNUKw5FWcTBYhNpIyLt1QkBGxzsHIwBr3QpNawW9pIQpXGD9wwozUJKnmsORngvW5DjSstr3DIhaG3/tQpDNwUq/+vmT3Rz/JlZ4xRfsbbvTrG86fKZ73k3OAtf1BdYrP851h7qMh7BY7feedt7ejP+WMRdk45OpJArym7KTr0xo11Opa4LGXk3bMTamBCFi0J7733nhf869fO8Fvf+pYHcnR6JkU6GQODfL7/5pueEg1/Dh8YP4wTEIbFCAXgazQYGAiUAbvzjzzyiB/0//iP/+hbgUVkqXw9dMjFJmj0TCwW5l4/A9QdJiXyWWodyBtVVueOa9GQRg4pwAqKowGXBuVUT13ZeR58RXShBEFapHGieHrAVQG8E13rVdZsAb+ppAxpxxCIjrEBgUZLXvACRztMgqOHuVITUJ56OSrv0gCSSueNimJXkJ3pWguKXGZuthvV9xmWonrRfl2ujLNkSxdz+qjUySlRUrZrh0Bt2aBOOqIzS+B5Uu10SzkUCCRT3n4B+sbUPFc3JXVeYidhE0AV8/SnzR+XT7mygV6f94LJz052DORasXKMDXS5HB2/n0bpYEaaO1dcIS0lE25/7y1vnjxmWuoP4/ol60iQb1koAE150E5ytbrW/Y9PPDFvwWNTCsUw1oQdM/2HxBNQdUYCyAAyNuyJjmcWQQgFgDE7ik6kyaCepmqBHEEYj/6jb5ioIyzzIiCA+Q8WCuZZFtHysnLP88zcu279OndcRAqIB2tlhhy1YHaMnWheiYZjfsHUN0ZfcFCN81S+QgkJmqOMgAq0AyVKmSQu9QVIM+8hHPvO26I2ai5EKJ26QZxZSnqkCRjn99qrr2rNmK+vm/erbn4L0Ec5Tc4V1RdNGYv1V077ALGcThfoNCIRcEqayTqFox8lEn5+CbWWqM/v2LHD3dJmq1nCj8xzzHc4D0Y1HuA9ztCJ4d59ez3rRHh9X06e0WWIfjYjKgH/uFScapx0CAzDhkLejEfW9iFtNmZmSuK2K2OnsqrKC1GygYYFhf6LYCVUbuYs0oMVjVNG2uJe3C1RvwHsX3vha3MU9HtJ73c17pcOoqE8cPwCfxS7uWvXLnsAC1j9oz/8I39Ewod9443vaUC1iVE/U8IteZ6RnqOCyqpq8U3/vigYE35XBW8T0tvwBREPzRwsDHSI77z2qjsgHicWLToJCwJx6YToVOU+R7tJTM2+/PLLs/6Z7k/++E+8BhEmyurqqiVNtgw88lnMMViZxKe0EH+ejs2DHQktNR+sE45+cszVi885XarewsgWCJikss+xVMwmjmDfyTGMi0y4SbXxgPLPF+VaH2fR7DGrjbSfoPSsmrv5UdCQMabFP1NgMzo9zG9fmElzhyRQuFtUaFgjMpUW/PR78mWSVOwdGXdb3VXpYh6uWu8X1xEtqkWaINOph7Km7P2iiuWIHy5dwDddfTVZE3t0XvNLFfsJYZd+lalCgoHp6o+XVZ5u5fO8eLThfcZxXaN3GKTRdOjybKMSO8nP+GIOfGt/p1vX1+1GpWUkT2xLmZpcEbqk6pwchMtO/UQ38YB5SBRoBNVy+DZyY2rb4zJlvuOZ58TrWTM3MbNIMJY+LyDlM1+hf5iPmiWg9OKLLya8ALHo39BiDTUUS35LdZycLWfhBvADUDI1nz7zzDMeKDBn2vdlwcWxYKPGDqowxAUAxOfx7WmHIfE6s4kgb47KURu3Q7IudkRNeQD+qTqdQq0eZV0MiBEn7AjPPAvBBA0NpJ2nei81HdYt2Djq6+rFHrIunMXqfZwWoL+dkq5ylAbwHRdzgEfAHsS0pXwf5ifWfDZbS13rwAxdMk8P2AcngEPC/R02FE7PPQuUNr6UiziMnc/DkT4EHk7FjV0Ian66Th3XFAc84gBoNHOMSQNIIu1EeAA5eIvxjMwYgoiwzUyKgo/58O1SpLBj5w5ft+XUi/EBdwEbctRVPsjuSwfRdPK7Ysn48Y9/7NuZjnLkyBE/yMIDjY8e7MSCz8EECn8uPG10dKgM5jiiMxfu3PBMw98UdnQkcya4wDOUbHOkF07T/Ffidbn1YFI6Jn6wwttNboPU2gFGww5dEyVif5jRIggHLs9YDGzMgNI77XZkCsSKp9xTjTXpJOJmJsUiIuG5JH8srjyjXKYAbSbq3cLpKc8xTRLHZBxlSBPNN2TUpAieavFsa4ZBes/9PCnbdaqcr4ni/J0719xH7Tfc9W27NfFKaE9mtgHQAM4ZAck8mZqltHiVQKFV2stxCBV2Kc9tYuWYFGX+l5Iq3JUx7MpM0HK2DlCqKcCALuXKlHwTdYBwKPCiJ7o3UrUZ03Gkd6oLMgbhdupPlvq/0mq3VRuJPFHoi6DSi//cO6XTrPzbisrdHwsQMuni2IAx4bKQGMjyL1b/+EX7X/7lX7xAXm1NbcItwua5RZSgLdI8EF6sE00AEMjCuVRAyUIMlQg+UDb5tvhy5RsjPLx//35PnTqg07jTorCjgg+KufFHJ1rGRMIh5NcrFXoAXNoBlWIpqhtU8vAoYL1A0BGAw5xkfTORPCwMcQAIOKs3aS3FAQjRwPDNl765bKCxlPxWelioub/5zW+kUavS1dTUJFQdFAzwrcLrciIRAbVsEpFpWqojLoS4PGlFAmBCVLNNHIoOmPeqqqo9Tz7WSCkfWngYR8S93452Q61ktjYd4CHAaYfU8YJboIbj6MOcpA+L2LMUR9k5TeTHyTubVixItus6rJMe2EXQ/R4ef4mmz/wClfupp570qjATjbcSw33pIJrjtf/pf/n3moxe9kdrsFgkcqxGx4FKARUgDJRX4kf4ossMdYkBz6C0RWSxMly7fNHd/uU/ulcFhtEUEdMBoAWuB7RZyRX4TNf9x8JxZTJjXTIx4qT4wvPqAnJj6ZaOTjMVFXNT4r9lgQPHcZ2dqCb1/QGYqQJ885ze35BZ7kbx9T49IzV1npqrkMrTO6VxQ9TndyQ2J0zoXsoYd191I2775ZOuSfEKxIs8lw8ZUB9RCfErgPd7XmaJPwwK0CeLUrBG4PaGNIVMpOW6nSlDQqZKY7ZOUwINmEyU/g/lw2/5jrhQn68Nj7q32vrdmPjDt5ZkuccLs1x+Woq7XVzqPiqplhChgH1Hq8ufjAiForv605Qct/vFl7SZjFgipM8AcD6PxWL5Nf3yYwJgr16+5BqbGt2/kzahgCWD42QWuPnlC/txj6YCFrOAQBD05XAYix3PD3YOTuEAgWiliRcuXA4ofEjsl0qVV6lYNIJ3kbwBD+jGhQoIOxtmu9dpXkZ7QUCtjoCTxfJb7L3VD0HBAVGia2prPHgBpHJcHWwsgrIRlrbGD5DEvXzm1TnR/NgwU2/aAp3ZEGTQ21tTU6P1J6JtJlZ6yANclSDX+g3rEzplpNwPs+M7sSmCF/pVz/oC7Ah/08g4sfYeV3/o6Oh0a8XKAUAMh6ctLRz35gK/YEOJX7AxiuQzP1zwFJ0OoBX1drAUPfbYowKYEr7TugZryebNm3y+pEs4NnKMFU61AbdovopOj1zCfuH7WOWJ9oNwQR9FgQIOVgvyKllbMjveA/5lMBPjFeq7gf7otOyZa3Q5aGMo7CW+vbUxVxhANaxPwRj8bJxY6eDH2EK2DXC+XhrVliu0S1orwX3pIJpGypLBCNS0LNUBAsPU6qXGf1jDMwkwsSUKoFG/9dY//cjVi8GhUqwBC+230zW5FHrqrdS5af5qGZ9yr+nkLg1zgMqTf7dztMMd6Fm0+aEIAzDGRaXy5Z0Fm9z3CyRDVS4WNXkWBfj07ki1xK8FhrdI2G5jOkCU6WDWMXPIwYkiHC1rhmKvkL7lr0gV3gZRqjeAaNE7N5tPY06RmxLVq0AU6GQJFGL+IZSaTyvRP62i8uZIk0iWQPpRGXXZVChhptHAcpVmHV8H+KRHBIrSRUXvgQovNsuF2nqxvPtEifnhrR7XK9aVQ2sK3dtt3W5DbqXLUAOcL6pwk9n57qI2GWulkSSnH+PjfB3nbglwD6yvd4/vPzAHmJm46S/hk5vF8n9Y3rOYHn3/Q69Lnk093QyAZmOMK472C/tNTEx6/beB5gHpW0kwnqVl6YWFqIK86KWRPLmfYfzJ8R0ByIwr5lwou+EysUGa1MINSIU9BQ0FaBmB2LFly5a5dMNxglERO7+gHBFgQ9j5cYN2oVyAU4S3WLwpHxQ/q4fFoc4c1wMmADIGsKx+ieZHevwQUgewww+KADgLf0BciHyv6Pqh2vGOqIGwChrAoG1XXewWYP04deqUZ6EJWBuDvmLfNNw/7fsNakxhoAQKKd8cR3ic9Xu7zvdj+pasgAgSAYi2vheJGys/6w8tLW3eCAuKCgDH+AOiAYJXr8qwyeCQPzVCDSR9hr7KBoz+G4Bo8ok//qx+VhfCch+7LpJVYVzotCq/utKHo49i5MgIh8SlvoBoxoMJF5r6RkvXruG2ii4n/Z5NM/zkKVp8YZ1FOFqP3i1UTqsP+XCCwLzB+FiO7FWQ28r5+zsBoldOcz0YJbUBmEhtGBwXT51wt2Vx6GUnXmhRSjXiF4yaol37uFghTmevcYWjPW4dfMQCwsQDFJb2C0DzvJibHbw+2CzQ5J7cc8Qa4sth/irngEDoLyQMly/CxX5pAYlX1pzpcbdVPGaZonSzMYBHmbSGBFybBHDTpYt5XVaa68ovcudK1rvKwR63s6tVHCHwYeoImfBLcFOa5FoE7EtU8B61X2tqhvvWQLvLxFCN3vlZSmnmiIoA73WhvDtUS1Q53guIZpPBpDYoarvodu6QKA0VErYc1eRYoJOBx9uvCTz3umLpxfZlUN4Qxi9IL3T5gce1SAS8/PQBgCKTdZhtaglN8MAGpW3QXgGoO/Lstz34swUFynBA8QwWVfzNj6tpHkBlVrDILa2ZSA+wGYCF+HEVzHczjrehQMOucfDgwTkey3BM0oS6zZE2rkzsFMiL4KCKcYrFYg3YzMhI9/7Rf8gvSWMIF9xHh/jsM+AA4AOohzoPQMmQYCwuaM+gLWk3AINpPCI8fkEY8o2EC/wibc47pebD2nfAj99rjSMAAEAASURBVPoAVsiTRR8/gvLtotOmPOfPnQ+obKJEMyZWXfwW4Bu0traK9eWO+8pXv+p5e/Hj99lvFXw/+gzsAKnq23yPpbVxYLGQ9OmvsRzpR/dP/KDkYg6ckxf6gn37oD8kee1f//qrt9xTkt86fPhJsSo8pb56242KGp2yQD+IlV+sckX7EQ9KN3rZoYgPD4/4sQs///zNm1j4xGZCOaO1JkX3YdU8Zr8mHOPPhHiZKwYkI4RsQjDWM3x7xJvPGC843h87dtxvdGGdXdq3C9JYaX9XQfRK+2L3obwMNnbPTBK5GpwLuX7xQX743vvu0VGp2GFhZLJIAETC+NCoI7ltAqyZ4r/1yofJSHE5LB3RDndCEDEP+3paxGI5IDegUkuk8tUoVbmZHDHxjUBcmoQgvJMfbAm/GU9zfSrf78sITN4s94YiRJKeHenfypQhlol+d3Qy1Q2paMnSrXxDZf1P19rdqCaBwdFx92/qq5wM+Lp+GTLJV5rpmpB7JHyXIkrZml4pvrdZI5J63LsJUaHbpWVkh7RkXBbIL1ZdKjMFEJjk1R6+LbTpwBR4+sS4NHikuaYJqWkSyE9T/ZfrcpXPt8sK3PudKe7C8JS7fKdDWhcy3LNSNfjEjUtihQksHDL/oV4P15aa6W6WrnMvih/WzMXSX5hIua66+S0AqDx1GipbvawTsumgvwES6CLqwfRb7+zKEGIhm/ZULNRMBTzGBCJuJE64vS2dsB8x0nUMOyrz8+YsHOmYw49xg5ljhId2SmVccKIQlNMATZD2jGdReP755721M9gscFDNEaTr1BF7ktJDZSjgH+pb4ObnN+s5N0zC5bZ7u7LwArKKJd8yrFMswE+5qIA43lmdLDyAAYFKgK8RBOwdcaLDh/3C7UIcwBIbkR4BqGst2iiLAk9fJ41Y6bABuSTWHQTPUcW36hZuAdTEYbCsTBty2pq+Fv6msdqY74/mCCjBYdmLxL5xANDJg7xwwbS1cP+kLzU2NckoT65krNgcBeHDeSLgd/NGk/txV6dOaqZkBfllrw+ePoO+ZZzFC/eziJ+VhWukPHZvV0uH8kPFzxDRg81ii/onUwQ84hbd0gZUU2fmI+SeLC0LZ8+kbfd2tfy4WrvBjoEVToR42bSisQRNOZZfvPpxqnPi5An3+muv+3FEmg+6W91GP+hfOE79mF405hZ0LPQMpgkJFT02PhQsy7Nga8GIGrkt0s08ogXxUF6au52c7oYFfD2ysIja9Uo1gF8MzSv6ClAGJIwTFqe8gdtYDRwXa4RNkhgmOSc8ekkl/Pp4r1uj+SwyRfmYwR8mVf0worJOWjHW5aS6JgHkQf3ebQ3Ua/0fDRXuOzWV7qctd90nItBuk9Dhi9dOuYr+LlcskJsmysDcDBZKOu6t8usW6wnAP1N1aU1Oc7VS9ZeqiZf6kNaYNgDwePtnJZSr20kBBY7VluxUF3NdSv5nbX1uV06a+9+qxC6gzUITFGWlmwnvnDYvGMMxAD0jMHFiVAKihw57flQmWSgbCJMBNPitukgL0P/gE8bKHhZTcSxCtBs/E2zCzxYn8xsRValHgAyeQz598At6rYWJjkd3iPixYOtbyw9Kqo0F4nLPj7A4/KAoXRXFHKt6wRE5eQblNGqRxQMYF0ioCAtnqM8DPEAZpK779u9ze2XhFeNVCB/296NWy+oX5BVdTiuTld3KZPlNaON4V6AJU+LtMiABMM7JDQAqi7aFs3YBMCAoC/Ch3ZaaX7hdEK6kj28XSICt5o4o4uRH20SXk3zeffeoBzHwa1sYH3D1T8wW4LtCiUZwFiCI45vyDWjnoG/M79fMN1BgAYuEte9u/SdevCCcCA9aLzKjTkkWyo/vSt8ekeG3LaKeGpU3nB9jBGE7+l2JhPqqqipULmlxUvnww2gcrBSAa+uvxMexjkb8gg2vlcfqEoSzcRS0C+Oa0ypOfEgDFolqjUnYXy1taxs2G/Dy90mvOpPCcvKjDNSH8dDU1OSNLD366KN+w03+uOB7zZ9f7B11R296uexRQIV+WMbHLDrx7bP65yFpATo3x/IMNAaALaLR1Wcyu/TuO25rX5vLlPozDIQk4sY1dzQnpbt6mdHOmJJOTVGi02YXJYufJXaMLC3QsDoAgqNV4xFOS5k3+TsqzREzqILTukaHxRQ29GmWOSbAO0r/uKz2HZAFvwao3kpTFSOJuA44uFvsGVKO59LEt31BKd7QxP2jpj7XJiG7NKUxKoG7uz1JYq0Q374yx7R4vibOSU3SUL7TBUQXdYp3RkZcCsRG0ae4GI/ZJlYKLSPgHw+e81U/ODus3OLEdgOakIalPzobHdlLcaF6F6gZ1uWnu7/q63TJXZluT2GuO7JWWmcIQ2NGuVZRwNHY8aYmTlvwoArxo688LJNiVLPEfYRKhI5hwCZGC3yPVbvSVjh4KblnYcLhnaLTBfwwnpCsTYlZNWRRtE9i4WnviJ99siAt/P3ipZvZ7HweQZ4Gyr2X529ubGzyVD2k7QN+SdJhMYyAGsuXsnBP2Tg6RisB7BPUF0o2bEa4bm0CuqUOrK52g6jwVZ4qbflbWqQf8fPRfP3Njzr29w8oP2nvEa8zYB9tS6Z32cpCTIY1LmDh0PgUr2jQ1hGq8eL5BW1DPMoAu8A1sbhQP4xooE4Nf8s3Uk7prW5q9kQFVKHa+AhKtPo3VgvAV4/e9DWijAYaYOizQd+ifwTfKrhaf+F9c3OzNlQFfiNHuvZusfEQhFOHU5+a1Lckf3Px8qMMbNwQeuTb50orh5UxnB+Advfu3d6ORLPClkl1G2AbkHvp0mUv/Ifw4XrpkWbMhNdU+KkZr4Gz8Tt/bPMunB99fXR0QhvYIW/sjVMkQHtw2hW0ifVh6kD6WPq8JSFZTo1QibfU/AhPWvRtNtp8B04E2MzYxoJ2pJxhR/2IBxWadnzx619/qGTVrKXDbbJ6/5C0ALt9qDkcJ0c7FuibV6+44UvnXMOMKLAJAmjS6ZQ2jrviLz4kvmTGW/HkmAeMI2JZkBiTTFkHAHdGM8VgpvQ8ixKVEQOQIgvl2YbhDPY8ljreUhoAbtPuMaxJ930B9nzVY1+aGERYaENAMrpe9sw0UCxgW6wCTmLnekSaMwrT3N7CbFcxkuaaZTXwezK8ckq6Mt6Smr09Uj23V0BeNAFRldO8ie5EQPSUytouqnmFCnZN2KNMeeZqwlEy2kCkuF5R1XO1mcgKtW+O4sBtekdh4KNersvShPfi2jz3lPLozUxV3uK3FojzHyUq0RGxqhzVyX39E0+7uvo6/xbwzFEev+iJMyr6Q/kIhQ3hu2effdYvPCy+LGy26HOPn605PNOOLO6wReTnF2hxQqI/EoaGtDgR/wB4B+nQeVjsgsUslWNcHeECjAmv//4ahA06T4uobGyIt27d4oFqABJ8Mr5slg/+OOLih9GKQMVcAITRTctRMXlRj+qqKlmTG3LNPv1BV1tX66nIQXpB3nZvV9IP7i0PGXfQhgLqM3zlgI9iGX7QW4ULymLlIh7jmxMRVKFCdQveBe0aSdvaK1yGSL5KdbZ+gTEu7A4wD6apLU1Q3dqAMuBgazl9+rSnsKFBatUt3gLwtgPEEDAzoTvaNfw96UfWN3jHJurWrdtSr7hPGUQo1vY9uNr3C+6DD8R4sP5BCO4DCmkwBs0vnB9+gODz5895VhMD+vhTxqBcPDHW0M6x2dXW1rqxt97yfYHNHoKpbOZ4193TJa0t1xQ22VVJpiBDm8Lo/KyudiV1y8euVj/6HHMFvMo3mm+4GuVH/5zffkF8xg3sRfBNA/jt1NDysetC+QXtSd21TkjFLyxfsIc0a/NIvpya2ZiMpBO0O6dJZ2XEDpadzTp1eJgckGPVPaQtwOC0HWZ0E0zIktfZD37ryqVHuBTdxQk6BvhtUYNTRUUthd+ZeLMr0aQWv0ktzHNO/lgHnONtnnsR3AC2UwWepSxCTpOlnscEOmB/8E7xTyZnug4J6x2SMZe85fRmpZGqCeilykI3M5zi3h/od+9N9YoXe8IVCoQ+kyRwLrPjZ6ZT3M9npBVAFG9AvxdsDEoR/69mJQQJ2wXCUY83oHLXi0fcCzIqFgKKeaLI27MlJFgl3c3a2Svevboc1a2sQCbOdZJaCN+e6hTLNWnT0FRR556VdSmogIAKBG3Ck2+seA+rHwsVR5drJXjH4ksXp61wjAH78Yy/vWOhgrqEoCY8wCx2FtauFie4RtIN0uE54pei8cRmh4WP+JaPhYGSBK8nlCXUFc4W8TN5WlziWzm4BwSwKaCeUKZv3b7lebnH1G+xKltbW+O2btnqddSePnXadYvtIyh3uCxBuwTlj9zTFoAE+hkLNvzGa0TRD4xlzC+H1Yuy4eDXH1UZAqA0v40tbHR+QbkibWdpodoOFWIGoK3+XC2NlpYWT5U7fHhVI4f/AIv84bt+9NFH/sQT64QAQ2tXa9Pge0T6A89QM3P0baF+xg4X+X7Be57n+9Gv6LO8tzzC995TfzhZwXpxlsAu1OPwWIyED9Km7IwF2CZ27drl+ytzAKCfsYwhuGFp7oACjP7ot379a20KexUnyC0oa6Q88cpldaH8AFi0Y1BOWCzWC0QbKI+UL0iTccBGlDFB+KXmFy4PacF/TZ+H7QwHSJ9tzphpo6UE1ii0e0AYeJjccmDHw9Q+D3RdAz6qnHnHXlbhxuuNrl0CUztTJh2gLlGHGNKV0SlXLWqVYOlctCSNwFyjOAs4QIVlfknTZAtlGQG+aIeaHShtY8xEJKWBXCCDLnniTcadHRMVWqU7nDrhqqW2jTyW4qAS9ySlesMm+9bkuv+9rtyVp2e750vK3XeqA+p8hoDnfhlE+crMiLs1nuR+IKUgN8X+IZsprjevwPVK5/Pc7BKdudLvVr2yJUw4qIklTxPxeum9nlbd++QPKwu8yaiWCzvqkT815jphTdGx5H1xymvORbXTEOwwqTlu55HnxetX5YOxwTJNBXPxVm/mWqCpqUm6b5vdLvFCG/iae7nADYtgj/iJEdgJG3RaIMqCrwTzfL+fXavnhYVCdvLESQGSYm9mOXzEPC9gnAcWYhZk9NRyxLtv/yP+1CpXlNuNGxs86IAPEh3XHHXTDu/LIBOLr1Gr4yQ96w3/5agWfvE26x/UcihZUPIWc1k6wYLq9kU4NiloYIFtx8bHF5HvSs7jrrRWQLnftXOX7xcG+uLViXHB98QEdU1tre9v8cIu5g/wJD++G+A9lgMANzY2ed7r3VJnF4+YFCsuG1K02+DYxAL4G2QlGcuujIVDsorcKTWIP/zhP/gNJ4B4qY4xAKsUrFRsMjHLzXwMmI/nOJ1hTce66L040tixY7ufnzDosl331DGeg80E64QlsqBYs6EmXrAH1n+VneOB/bSJVYxdZ+vNG26dOr8dAU2ICvnRP//YrWu/6SpF4Z3bTieQZK9YL0YEGGuTxjz/cjiKn0o0ufUKtA1p0qyQBgpvRltl6JUe45yejnnq4+BRnBDotDV1RGwUGeIfTpJ/l+7fSst0O0YH3OYM8XWTOGA7QcdUdFFmwf92KtubOi0SlN2el+EKsydds7QdHNfkWCg2jP95ok+q8JIlDJjsvp8+4X4+MOV+lpnvnpwacRvEDpMHAI6TLxM5gDtJbCCfzKS7F9J1ZCzqMnl3qVLxZPvhwywW0fiK2ExmVLHEaxWj8iqDL1/0NRQUIdBegaKvSXUTQAvwRV9YCjgMJffA36Jx4O233xb/Y/WcKrhEK41hlFui2iBEx2J1by4wPMLmMloIFQCBVoR05bFt23b/XZeaF9Sv48ePeyDAAo26uzwt5F2iNgOUOW4+dOigX2ChHu/es9vzZV66dMkD4vr6OlGVFzbvDHBiDmoTJa9CADpXrEOLAS7qgTGMaQEhAD5aAz5PB1vCHfHNvvC1Fzxl8PPM60FIm6P93x59z5t7hsWH75uIAyymimiBVg6A50KAcaH0AOSsHQDlWI7+1dFxV8KyHV7rRK6EWE1AL1b4aD/Sh8iAg0cZgT/GQ79YQ5hrEVKF9eGtt37t/st/+X/cN178hmdxWApQp836+nQiKiIS8zH82nGWmbni0WacFvXrNPVeHO2DYDFaagLq1cIrUGdnl+eFRuUf4/Jhc4tv+R+2FnnI6suEUKgdpFGpGEAXxCN285PT7uCMgDAjFwCWwG9Ku+SLKRnibx53awR+Y8ZR+xaKhaNKP/IaEtUAyuz6u7elJWJGgnbqkrN5pSjvPAk0AhAQw7ujiQstF/0K846owkVijXhBADpdoNO7RcpIOpRRIl3u0lSquyoq9J0JhAozvEq5GQHeHpnk/lDWBE8kZ7uWafGiaSvQLX67KcoiFpdXM6bULiPuY707pTKMaMOBTuwJlcvKbddRNdtd5dErSnSJWGK2i0d8UoCHjUOd+MRTjQ86qtxozCgWqXtEi0CveMstvWVdaRjSt+9oz7N5UsbLWRIge/wpLV6lChpQH2HnWHWfbQHa5+rVK37ROHDggF/k8EvUwYM50DfgWUBszCUaNzocIAMgjoqt8PdCwKmVRV1Hzfv27U2IysY8gGPxhvpsZnspL0e1La062hXvPoZYmpqbvUBlm/wQLhzSsTOgnfqgtQLtHcQ7d+6CBwK0z2zy86qAP9TnEZkrBrBjFVEddV6YWA+kBWhPz0hX/L65uStW2Hv1oy2vSkMRwA4q+apbvAXg320Vr/DTzzyT8Leh/yDcyekMG7blAmiGIn0ZoV3r09Elhk2isbHJU42x2LkUAE1agHOALSwrUGjp88yxBWKX2r59u88XAcWvS8Du8OHDOp15X1pd3vU8/9FlifUMGIZNBG0f5EVfBxwvXk6t5dqcIyuwlDkpVhki7R9/PDIOaePz5y94+Q54xOO1eaw8HhS/VUr0g/Ill1kPOj0TF5MY9yyg7//0J27HQIcrhyWXWSlBN65F/ZQYmB8TYMzRRBDXkaZ+05roxvXzQnUKP6H8B0T9LfQAU0ZNxBKSraOiNoHUMQnFVQjEanZ1JwVgB8UO8cLkgEsnH/kt5NAWAvX7hoS1b0sDRZ+Cj4gHeJ2o7LtEYb6l/L4zM+x2S5qvXzzMsIC/L7PXOyeH3VHpTc7QZLlBgiXVArbrZLkQ9o4iac14bzrd3UjKcgcFHmpnpHlD4H5IZYXVI0tsGoD9bj13S2jvq6nSRiK/gK1D7CBxqCRWD2hrmQLwt0RxR1vHPbs437FdQqBt6ze5Fx85oO8faJPA/GsiR+r3XKYVmADCuB+LOrtt+zbPZ7yUxYqwTU1Nnp8SKs9S4i7UVCy0Ru3TEPLHwAg81upYvKhIhu81LmM5wjLmkeYHhHMMzG9A2jI4okU/7VoJEgIY4GuFFxSeT4w/fCrjS8USSIYK1Sm9uTk5uV4IEaFAhA9h/6CuZ86c9do2OALndCNcZ8o8ODDoAUNdXZ0/ro5Vzmg/ujLlBlz0qbwBz210qHt/Jo8OCYDeEiX6aVHZVk9mFm9TxscpsXHUiwIdCKLF7nvRKaEfHN7iBulbv1fHZg41cJTFxgVp8j0BvhgcgpIc6INmkUvcAXD7+4e81hFiwWLBRhYBWzaO169f833/4MEDGudrJFT5uKuUzMTHx467X/3qVw6VcfRXyhgeC/NLELA2MQZHBaRRS5koFbtE7CSt4k3mNIByxZn252e3zCfak/EPUeFJnWI+rIa4VkH0MjvQgxSNwczima6J5drFM6777Kfu26K2pmiRXYprliW+GVFdt0koT0p9Fo2aqiO3QoFS2DMGtGBrWvEGR+CRHhBIHtBufqJ/xN1cU+HOpwpEjw66Ti3w52Wa+1GB3rIFQD6ws1tU3BsCwZdlVKVfIDxdg369wO4msYSsEWDOVxG3TA3Jmp9zdRK8g/JdJAT8oniuK1NG3Z5pUQLE5tEm/3PSK3J6UqoBRZXeJf7r2uRx922xrPzzeIp7azzLPSaqOFSJ05V1rqHrttvS3uJuqQ43JjNciVLZKGQO5TlPFPiUOKBmrsFU/1zR3qdV1lEJ+QnRzL26nzcj2iyczshzZbv2amKv9rx3gJ9Y2lruZ74rNS3GCUe3XVo4Xv/u64sshJ+tJYs6VN2DomDfKxXaUiedlNmjZfwAvPDvIihnZostbPiqLu1ZIYzSDOUL9ggsoyEoibosQCqUZyjECP7xjKutrRNQSHd5Gp+5YqXg2Bl2h4sXLnoezlIt5ACorVu3unaxaaBrvq+vX3yjG30aABGoalCh2++0+7aAirWUNgnYjTJ1hN6/ABgJ13g59yIKyFw1QIk2ADSsuvgtwPhAuAwBUY72aS95LeoAuvD/AhQLtTGLDy4XTcoHIF/6ByccEXWOwSlLU2OjZBJ6vL7zrKylsR6QLmMYinmj0qH/IszX0LBJahKvuPc+eM+NaTNaV1MnvdhbPIhGww0WEGGDOnbsmPvpT3/qgfTevXs8a1CsutIe6GEfGx3z44Wxpy1AQpXPloYO6g6bFJtgUasSirecQMhDUCfmBeq7lPG7nPx+V+Osgujf1S/zBZaLyQHqEcdcxz8+6Q4OSP1WphCqdsKJujEBw3en0l21eIXzs2ZZMhaJrCk2oHRDhRYYQIguh6PoorXug7J6Nywwvn7ippsoLHfvlBQLhAro3r3ptl696HZIY8YsE8e8XEZESb6qcB9LUA7T2ZLec7tEsX4ibdpVCWwAZFGOb7N7LTsFRgGzvX6kuVZ/viL91kmQlAVmAet7BYQbxe5xPiPf/WpMx4WimO8Sr/NL00PuuPyPFcjCWlWDG8svdpOi7mZ0d7pjeWVuWCa0X+hqdNOi1I3rODxjEaq5r4y+h0yjuAqxxDTK4Mv+ALv4V/fzT0dGtjYoZe6lJ5/SRJglYINqpNUpIV4bMz7OnjsvalmDK/KaLtTREnQsMGi2ACgU6ORHnS3BmAsHA5Di4LXGXb16zcGzXSeqcbqEkqIXacArvKcIcEGtFtJxJWvXeKo1QlGUT15zjjQifI5BmTH+UF9fNxcGTRmYiAdgwD+MpbNr1657yjTqEvft2+fOiiI9KKAOBR/AzsJ7RcJIGLlAZRxAdSltwpwF4G9tRcXYmAADSiHvT5sGFROVTRuei+Ir/863v+3B0lyFV29itgCnGWyYimWFE4uT0X0vZiR5QjXtuCtjOwLQgX7w+/MdSYVTGKZ7HDzQ6HTevXuXP6EJfBfPy48Z8VC3iEXljsqZTN/TaR0b0E2bNrs9kgVA/3qbxjfClMwT//AP/yBZhG1eABHBXgz5vPDCCx50/vKXv/RjkI1G0G+DktjfsbEJb8AJ9qna4lqvYjTRvg1POaooR3WirElKSS5eP8t3qVc0/3x87GP3/Te/n/Ap0lLzWAnhV1fMlfCVvoAyMuFdv3DGTZ47IUrrlNTOLW3w3RKFtkesES/OwAu9tCMyqlcsFXCTmvBuFJa4d2p3uo70PJcnSmyfqBopukrCzg1JM0e1hJoOOVHJBXcnxH4wJlCAMGO34l6YSnEtEjaUgT5XK/aLZ6ZHXIVAcG62ZlHF9xRdQMc88ojqGa6q0sFh2tj7Kyz34IqN6SmufmbI9YsSfVFU6UtTae4vUvJdQ5Z0JOj4cCBdVADFb8wpcnlrK9UMOa6mutZdEF/3TEeze04UAplo9Okv+kfplEm382VRwMemB2SwJoRsFo28eACxfrv3hyddyStfFdgp8zypHMmvutgtwPgA8CE89Mj+fVqYg+9hQAFQFyzYRn2DD5j74IoA3O22gMUClohIF4yEi1Cb5vspmVDas/1zNm1DvOTTLF5lBJwArbAeUB6Or+E3HhDbRGdXh6ei4wcrxs6dOyT1X+zVxUG9IrwNhkhdIvlF/Dz29g1l9aOM6BOH2gzrBjqfbwl0HD95whUI7BZqQYeCB28oJr43bd7swT7sY+jbvixhxG3iJ41Qs+a3QfBVIn60PxbaaGMojgZGrDxcl9qe4fpxlP7ehx/5E5qNqtOqW7wFOGXhW8KykKoTrXB70q9sPER/F8YGgLFOgHH+uLI5b37ceOPB8qOkgMnwaSj9/4JOSmrqarzxkqB/0I/nj1so11BY4UceHhoUVb3Ta9oY0wliaUmp18ZDX+Y0qkoGhjCHzSYS4cQ3v/emxlWJgPMjPl0MMf3gBz/wJztbpAaysrLcIUextmSt+81vf+NPfx9//HHPa28Gfij7qNqCtmQMw4cfGPyZ3waEi25T2oVxzBgaEJAvn51krF2Cx8XTiZX2fD+W0kkvdLx+3fqHTi900BaRv6sgOtIWD/Ud4OCyji63DHS5Am/YJLHmYKkCb19OznAbRDktNyG/xKJHQolCOybq7pXiSoHx4JhNtGB3u6jcTUqNHFTSots33JF+WW7SEdlV8V63KXyXjpuHxPKAOrxSgduDojpXK1WID6kAHWaW2cnEI+Hw2hrJPXJHeEPVxJsFSz6AQAaAukDU60eFhx8RpfyS+JzbpKu6q/uuGxRJe1KUXYRALqoek9LyAdViolICe1LDN3hzwOVrMvZliuQY+07xSsaG3aep+U5a9VwGZfFlix18Sb5K6rp4wy+J9eQPH3vUJwuYCaiQ1H/VRbcAbBLnRIXG+EjAJmGfI9JeLMg4Lhh/CFxwBVTS/0w4zT5lONxCfpa2T2Q2Zbtn0UQQ8PbtdlHJN3rexN7eHi3Sff4HyMQFILdBx8xF/qiXxTlIA53MGGvxwXz5Y+VnfkH9FNNXLahf0D0xV4ywY7rqWeYFt6DKdQg8wzsJuwhAekgUayyb5ekoHIo0oLvK80xTnsAt1i7kFxxXBywsgC/ypoxBWcLl+qwf4aPDRfwCfcVsSt544w3PumLlWr3GbgFA6fmzZ6VdJdcbGqFvRL4FcSLtHbR74Id/uyi4WQKiJicQ9DMRLoJPOG8smZ/1ReKbi/ipb0hDVOdop+/X4+OT4lW+7kEpp0gRoB7E5JnTDE5SGKeclHBPAdAWw8awSNR1eIxtzNBvq6orPWglFcbPOmnr+e53X/OCkYyB7Tp14bTnqk5lzp4766nUjP+KinLP7oKO6l+99St34JED/mSHMYLJ8mYJZjJOdkp9pmmeibTlwv2azQO8yZSfzUAAqq3tKand2/Wzft5HdY8eH5EyOG2W2vyG/eWXXvLrBnEeVrcKoh/WLx+qNxNgsyaZrmMfuYNDvd7AiQi4CbteCc7dUvj9KdMBBXsJcecyURlmNHCzZIq7eGTA9Wgymc7Kd0NaaFkc03QUV9rW7M6K3aBbC+i0/DCuUiPgXDgz6tYK+EJHhdjrHXMNs8AsMJj1xTOGX+Stv/Ozx6yfp86F3oeeAek7lP9Wwdy7Ak0nOySVrvbrvC3raxWVLkcGZ+r677ryzjZX19slE+hQ1BPIn+yUdoXA+gjCiSIbF+hZTNKhgiz/Fir0MdHyNz/9nKuprfUTLX0gvAgtP/UHMyaLYVtbqzty5Mi8RcMW9YVqDeUXPlFYFqCe3ouLzo8zEjaYgIR8UXw5Uj9zWidK6msc6+aIQgagRViUhZ9F1b41XZHBEJ1muHwLvQuHi74nbcA9qrLIG5B8R7qDAfIdAvzIYPSJpxT9uuiYDtg5olNZ6HlG9cn4/9v7DsCqiuz9k0o6kARCCZDQe5feQUGxILp2Xevq+nPVdS2761rXsu7q+reu/tyfbe0VxYJ0XXqv0jskgUAIgZBK+H/fPCa5ebyXvJdmSM5ouPfNnXa/e+/MN2fOnCNhICtHjx3FPdG+dFnpfb9GQrUKGyc7dewkSUlJvmesxykpOV2/YaOMHTtG6LyGz9+X58HJKW0qE2fux/A3lFWHseoEcks9bZJK6u06Vyy4oZYqGfw2+T6SCFOQQDLPfQHUd+Y3w/eY9fC7sd8MiTc3X7vfJzfyMo5/LIu6/txIyD0BlNLTmcwybEym9RDWE4wN7z/+9KPZqEhVqN69exsCzT6Dlm+oK87v1/e+GSs0aPdBqJ9wPwO/d39CWXjactjHbMDKESXxSclJNrreHpVE19tHX3Lj/GBXLZovzdN2SjykU+nYINgYm+uC8RGWF9BXyHZYy8CkV5JgtcIEV09TXtbTrkfC+sZZe7diU95uOYaOOAUqEasim8ru3Hw5sW8PtJIDpAM6tAEFOUZvOQKVQ+Oh2MmKyzM4W4Rw6uD6UYF/y7sH9jYktUhHFQ4M4XIOvBvmQ/qRmZMhu4+nSlA4pBh5x+TztKNyFDqr57YAzTft8qFxmCQ0RhVhsBV9hA5diiDBLq9NPt7mdpgh3NWivVzZv5/xwuZaMvSvs/WxqjqRjN/HvHnzoDscD/3dVsXkgIMqJTuuYKWgJXF2GZXL1bR4QZu5NrjykmiUXk7mC2LjeHQ98tPLtulOYuAnASARIKGmVQJ6FyQppRSLOu4u6Zmt2VUnf50+YLrq4bUSou16V11tse0oyWvT2bLcf7vqcbWLzihaYfmXlgzYZprGa9myhbHKQDvRnTs5NydZHElcXBjbsnnvjKP+LO+TmwtJiFyEwbbR5seng+/TJWV2xbGtpeNKP4c0SPTTMWm/+OKL/SYhvN/6FvhcZsIVNvfVuFyiu55BCcZEpCTOvtd8LylxLUDfyM1zjC8J3p87k9l3gUcG9/fTSGCRkCSZ5JW6+SS4fE9oEYaT4gMgmrRKxXeIfSCPVMvw9M3YOkxl5h9XW11tccXa9jtvw4VBoKmbEmISeb77KXv3yAbsCUjFxJJWSZbASVEBVEmMEyaYqWPgSgu/59L3VvZ7TTyoLlYINccilMe2lPcc7LNxYWmfgffv6AD0wveD8I8aORIThQaum6/H/yqJrscP39767p075MD0qTIioFDCIME6QosQzp7AJvRwpJ3hVFi76GDM2iEBZucV9bJHT32U1jaA+bj43GxJOnxQWgWGyNKgcOmQf0zao+hwkMtisyHsQKvHcIWHO3WLOtV5m1g0A3RHuLUpFPG0rNECxKsgE7sCEXbt2CdZLRPkXGxqNPg485oUnv9hdxZbkG30vc3mR8/J/IrNRFsXYNLTb+x46dilq+mgbefvV0H1KDG/j02bN8lVV15lpEt2UCqNmx1U7SDET4gkmJZvXLaMnSagnHnt8rLrk3Plt3EumE8vm28cA3VP22BjXnJyMtQiWhnprCWTrryuf51kg+131Y+XAcG2xbaXZdv67TWmK4krITGMc73OrjJtGs/14dM1y80xZsmZ+qfMSzNy1DEt6gCzlsXqYKffs21LyREqKpC6kYhRisilbIuLTcN223N7ZJxtp3scpWwbN22UtsltDbFiWg1lI0BLFXSwc8011xiVB5IyhhKM+ev095rOemjPvCns01Pqy/fBPg97NDlPjUXOuJKyXeUynY1j/fwujkOvmaYY+d1RvWPz5i1G15jqGtwY2AoT4oSmzYxOM6XNtt0si8G+w2w7z1m+jWNbSvoBV3r726ZhPtsmmz8Qkmdu4OVf9569zEbcH374AWQ6TY5nZsi69aulS+du0qN7T+PIiPam2S577/bIGu25PbpagfEHWNK+OfW6aXPbtqEi/YuzbJ5TRYSbhilFt27IXfXW33+VRNffZ2/unJuOZn35sSRBV7c5SDQ/2IRcmAbCGd1SB2Fw8hrQqWRhw94h6AR3hGOWIBqLI8mtbKCEFx8sBVDHjmTLiZwsSWoaIeGor5SaifldBfVVtr02P3spdLZEcfah4zIz/ShUOkJkHTYWXphbgKaHGxfnNnmZR94bOuEEmObLDA2H58Zj2GJYucAnmYZJSVaLZBnbtx86Vw4cGspCgMvN02fOMhY5EhNbFg+iHDB9CVS1oFWAGKg1cCnZ13y+lM00HCxJGDgoR0TQjAsHd+/frB3g7ZFlOM/5m32Aixi7fnn71z2f+29T0qmC7DUeORgfAiZ02sK2UhIXemopn9d9qdtVdpE0Bq47d+w0EsXSGza9tdp7PMkGTfXRegnt3lZEvcB76XXzCvdSLFu2TDp16mQ2KNuJkS93SykxJ5jcZGqfu31PfMnvLQ3fL5ZzGGbiCiDM4KSSVjloaaYZ9JGpa0wVI5qfs6Gsb4bfA4Pz27XtdMa5p3H/jmweWx77X0rAL7l4knEVfmA/TOft2G4k4tycyeGEmwz9kfby3vnesmw+G/f2mRupxD/UGd++fZtwQyTJugaXcS/FoZ4iwI96w5oVsmfFKpkAvWKo8NrvWwqhk3wEOpVxeblwPuJ5UD4JIrET6gZhIN8t8UePg1UZcqG8Owt2omcfzpY4SLrHND310dpRtmqrq3zT2S5IU3bAcsc7+w7KhQmNJRJ6cTO2wysbwCWKPtNWg+VJSN8D5CdkpMOYEPLqSgQ8SRD6KGkxcIjEY8lfQ9kImO8DJs4OQWfz0ksvMYNuyUBYdl5e5SBIgsjNda2hF0kdyqoMLP8wCB+dR1CqR31jlxS6Kmup2rLYZk7caSmBRIYqABtAcPLFpTpmP23faj0pkdAD57I1CUNlnaHQlBmxpJ106rGSkGjwjgC/BVqsoZ7vhPETQPawj8XHMYCklbrKxJp//nxX3ltkr0ASjfGLEmiazeM7Rms03LxIPWUG01X797LZwqvsyHvmOxYDk5ddYTLTmMQbOMBY1KFaybq166QBdLKTkpJ8FniwTK7m8D4pAHBJ96uu36EJP0q3uZdBhTCuV6Hq0K2yV0sLqikEaJFj/py5clZGCiSeJIAlrJQOTyJhv9MZ594uksINtMoB9Qv4X3O/XOnfNNPcGOQzDuQvFh10KUsZlS69ugoIkK2px6RJgxAZFRch4xqGSD8M8rlYag72MhkpqyUxINEFwPaoQ2pSVvqyrh2F98Psdt2l5+ChKkUoC6hT10h+V65aCUlZB7+8r9miOUDSzBt1G6Ow/FnVgZ8rpU4cMLnJ7swgfS6TdFSboIMfbjhMhF50RQZk3j8tJnDzF5foK0vEMiG53L5jh3SFkxhOSDSUjUAeSNp6WJigxRpKeH0l0CyVG/2ox09vfFX/3qLPhK4zCTS9bHJzH50P8TvhO8O/2hRcbeIKjOuPOtO0fsG9A7T/7m97+S3xXvmN+ZvXGy58Rtw8uhYWWPr06WOk5d7S1rd4JdH17Ymful9KAqj7l7l6uQwNKjxNQhqEZehQLIWdwMeDXs4jStugunEM0rX2kCN5TuExm8+RISCQzUIDpSmIQmIElBl8lHL4XEF1JARhzovHrm6Q/yB0ZmEgz4WRDaQRDOiDKfhdYzjK46JjNqRklQk5eEJLYb+6KZYJ27ZtWyHSUpn6z7S8HNB2gFBlHs6U3r16+z3Qc9ChTiJ1HZtiQyLJXnWEMHhdo34i/ypCRKujTeWVSYk8N2uyXzEEyh7Ly+jhOvNHQjJGwlCZwHLmwy50I0gF20PKZtpVmQLrQd40kKpdkERTgurPCgi/LZpkpDk3enmt6sCVDjr82Ql1IW4gtM+yqghlVbfXlsdVq/Xr1htviNQzZ9tdkmSbwrcjvy+uylASbb4z37J5TYVPAxOkIlm8eLGx987NkRZTr5nq0QX/R/V6BE5dvlVKodf98J30PwZ9TUiSTWAv4/ijjeMMbMg4hlkt4zmBN9IenuNvTRFcRMM2dCzIrjNflZ2jvnB8vOHckEcCaiW5jjZWWV1VUSZBhMS4S/AJ2XE0D2oouTJl31FZnAdJcgNI0jEx8be9VOGIgjTiYIDrGfib36RHs46jY10W2UQ69ehd6WVv3mZdD5SU/bzhZ2PDuGnTJn5J2Sw2ZsMbNsomQO+RA5EGV/9BKS+tDmzduh1uwVNkD4gYdccrEji406UyVw1M31SBQkgIaMGBzjGGDhlabROeCjSt1mbhpGXNmjVGF79FixZ+tZNS4gyoSNHJE9UuqjrQugb3IBh1DuMdtKprqPry2D9wYkEnJv369YNTlgHG5rY/0n3bKr7PVLngZIJYVz5gRQ3fKYn96JGjdZXGDVAl0W6A1IefHHh2Uo9yF5YuYS7OjPAkkW6B1jJioRMdgY/xKDbI7Y5NkGyQaoaD2FC4JSRSuhflV3rDm1u1JT9Rf2G4SGbYScmiDb0zgYkA2w74qm5JTpBNh47I5rwcuaZRqAziWMHJhp8hCPccA33wI5jCFFRQ3n8Uk6BPg6Klw0CXFNrPJtS75CRj9PzHjT50mFARXWYOXtT5bAZ7s5QKefi8qgRXfhL8nllfRUlklTTEj0JInLrDOyGtaewBRpxktE1OBs7+fx+sllL4XPRTJA0VCSSEy5cvl46QQLdu07oiRdS7PJwgcqWGurFUp/EnHIfElRLSWLjDrugzL6s+vlcR+OZIJM8UtRx+u/yOw9FmrlpxkkmTfFxdqkjf0QB9Pr8mllnZwO9qDdQ4WmKypN47T0ez6qeBp9ehMbUMgZzj2bJhwVxJ2r9LYqEu4DXg6+WHuD+msSxr1kYyomNlyPa10ujgfkihA+DkJF/awdlIdYa4olBpWFQge6A60tbIwis20FZnG4vLZm+HTo9ceWxUgAyIagqTd0USRik6mw1psOkRSRZ87BlpgzoeyuH7YKokD3kqsrlwZwHcqTdrJb8bf65aHCh+WN5POMBzAw09E1Ja5g85ZVpucqOOLv+49MngTxneW3b6FUrdSNK5FExprj/L6qeXVjMxxKIR7AL3gJ4qB3mSakumKoITSRxtZOfDzry/hI71UgpNUjh58sUqhfbhFeD3sRQOQ2idgXbTGXx9buz6DmEzLO0hu8zaVe/4YW/H1/bZ9DV9JC78lvkdHz8OwRbGukzYP29ySmjlb/tDQKJP4NtiX1RZKxrUhebejvHjz/H7+6ppHH+J+lQS/Uug/gvXuQPLModWr5ROhbmwbYxOjF+wl5Ae3Ujmwz305qZJMLUWKSvDY+WN4MYyKwSG6WnTmXl9JIReqigzuj10oX/TIlp6kz2ynmqsq8yG+HqR7QNZDgBxjkGTw+gxihhZAs1y/LgHGGuSSBAEatzAimqZz8rZRHp/PBIWLqmwS7rmRLD0HzMOji1aOpPouRcE6JJ61+49xmyXNXPmHMTsuT2yGJ6TkFEivAEWPRYsWGCkbSS1Vhpk09ujzec8Os89peN1G3idBLQ9XH1zSd0ltSohJTa/PTKfPbfH8uJsXc50znNfy/GUju21BNp53dbpjLPn9uhsg9UFp4US3KHJ7imdpzhujtsEG8d0EkJHMBrKRyB9fxokk2vMKk1EhGsDphNbW4Izzp7TGyTVFmiRg9+Wjbd5eHTG2XN7dF73FsfuloGb8txXaJx5XKkqX597Oc46nOfu6fjbXqfahpE8Y5xYs2Y1JinLJBcE2GW20b93mmUSW/65qznZ+uzR2QZPcVyloQ3wBGweTU5OtregRwcCKol2gFEfTjmgL58xVZrCK2ALqAngK/Z+27gWm3VYOkYdlDR4D8zFTDktuqGk7D8EyTA8FYZhE07eQRlcHW8R24XesAEG2oTwUxJcSnS5PGV7Se8t/2WusF1s36m2m3ZafG2cPfrSwlN5Q04WSlZREPSaRWJ8uf9T+UKRfju2Je7v0EOuHzfOEBZfqq3PaShlmzNnDgaNJkYfmsTYDi72SHzsuT0yzkWWTxpPfJTekNxRz5a72d3JuDOfPbdHb+U7rzMNA+twl74609lze2Qee26P5cXxug2+5vElnbv02ZnHn/pIxPlHqZvr1feddHDjJ//UO6FFvOwjVztmzJotDWMaQpWjo0lsn5s9OktwxtH0GkldHog0STQD3187yfSWz5Zhj0xnz+3RGUdCGgG9e9pQpwTV6SnUmY7nNngqp6rjbF08eiqbqid9+vYxXhaJCx2tkETz3Ka3R2cZ7nFMz8DyaIubwT2Nr3G0oMKVmjFj4M7dT7UdU3E9+Ecl0fXgIdtb5If087q1snfFajkLbqSDqcpRFiHFNXrg67lvh1ywdJa0y0iTwPAYCYY768bwsX113mHpF1IGCbcVV+TIdp0ig+bI3ySQtTmwvU48nb/t/Tivl3cvSEui0RBi6CB0pkcwiSkXbcCUh82NRehI87EsuA4mCDsNHWY2AJVXXX2/zu9j8+bNsm37NkN8aSbKBkv4eHQ/d8bhBZBQ6DRywOnYsSOkdd2KCTTLsgOcM4+nOPc6mNfmsUfGsc3O377mKy+PpzZ5iqtMfWy/DZ7K9hTnqT46aomESksO3ndLFny5P06YaBe6Tes2xkybbYsevSOwe9dO2bZtK1w+jyo1Kff0rGwcj8ZcJPwR0EQaVQ3CYVWGgQTaPiv7bG0+G8909pp7nP3tvM53gCSdDksSYUbR5nem8ZTPed09j6c2eYpzluF+but0L9uZjpNtY9ca6k50DsNr9hsvK58tg22ykxLqVlOSXJF2Mg+qNha8aLGGKzW2DrZDQwkC1SFDLCldz2oVArQ4MOerKdLx4F5pZuxCo3kkej6ENsePSfT21bIyPhG6W4XS9sRRGR1cIKGY9VdrsO3jkV81jzauWiuuROG2nSzCttXZfj+LDkN5EcifQawBQXGZnspB55cBJzmNcO0g3LFnJ3eWUdhQaDtST1k0zoUAJZlUw+jcqbNxtmEHI+dA5iRp9tzix3TEOZb6vvCKRi9udmOTTet+ZF5nnPtAxWvOOJuWcTbeGWfTu8fZNvLIfO7X3eMsuXGm8xRXK+rD/YSAMLB/YxutXrhtu/PenXEHD6YbXehRo0apLrQTJC/n/D4WL1kqSW2S4TK7dal3yNO74YzjhGXzls3GNjTVyg4fpnWOEodP9rnwPXTmY1Psu2mPzjhnU+11Hhm4sZCBZfPPxts4Hj3FMd4G2y73I68745zl2GvOOJvWU5yti0deZ1rn0VmesxxnOpvXiR1NP+6A5J/Y85uw6ZnWBvc4Z/kHD2YYU4H0TsjNuxo8I6Ak2jMudTJ209qVcnDZQpkcUAAptP/kNzb7qAzJ3SJdAoIkFmVw0xw++zqJVeVvivhWDTbc+x4ByX8ONUVQpKdSi9D5wmckHLqclKbYTX0CMutV4XHSov9AadHcPxNUlb/3M68EDh6UQqeDWF16yaWGDNsBxd6N+28b7zxysLLe7igJ8iWPM78/6ZnWOSjbcvwtw+ar6PGXro8YEGsuXZfVFuc1nq+DTd7YxrHFz6ui918f8hGvnbS7nJYqZ489G6SMksqSyVh5GARhtzXt5rOcGJgk5PNisGXYY1nlOJ9feelseTxWNPhaH8v3J2157XG23Zbrfh82vqyyIumWG8PQsawss5GXeXzJxzJJxlfB0RSfk3onLAtlrC6WfVmv1hUEaClg8fyFMignU2D1tkK3Ra95xzGrbVGYB7oWILn0oleTKhboBM6IYNrpofOuQPuhei7rjhdIZma2JAWarYUlEGCAyMPAxFCI8wwskeZD5SMIk5ttyJgOixw9Bw0uHrBKMuqZOwL8PuidsFPHTmY51TnYOM9tPm9xXD7lwBMMk5CeTK55y2fLtUdnOntuj0xjz+3RGWfLqGicLdMeneV4ivul66NTCZpNa9KkSfGKS1ntJCFJT0+XnSCF3Xt0L14tcN6HnpdGgBhvMBvMEmCSMMFctBi7H3nRGcfzYKyORUZGGccsffv2LfZ450znns9U4ijL/nam8xbnXq4zj71WXpy3sm28sxxPcfa6PZZXH9PZP2dae+4sx5f6uE+Ars4zPUwunWXZc3tk2bRWs3zFchkAe9Wc9GjwjoBKor1jU2eucFa5ec1yObpyoQyAI5AAer+jtQhfAj7sz1KzZTXmW1uwyQCGeKR3TLQsST8oATn5clPHVnJegmvZzJfiNI1/CJzERp7N2TlyILdAmsBSCp6eBJ+yN50K6xuZcU2l075dZlUgHjapA/CsOUVaHxwpjQaPwrJrG4/SSv9aUbdTc/CgRY6jWUdlEFRf3KU+Zd29JWRbt2410psjWUckPi7eEGi6723frh3chncqJndllaXXKoYA9W1p8aEvNmXxefB5lvUMuTluyeIlIN3x0FtX74S+oJ6GzZd0ijN06NBSutC+5GUa7i84q39fCYM1D92g5itqlUtH1TKujPH78CeQLyxZskTiYuOkW/duZX5L/pRbV9P6yKTq6u3Xj/vKyjwsa5cul16ZB41ZOs8KAV6wwKC0Pj9H1qSly8MJTaVdZJhswvLQY91bSUKThrI0J/uU1OEMkRJ7uc3aGg0+IAXHTsjegiJ5d98xeWNHOkh1vhRQmtaoicxt3hZ66i7LKcEgB0HIsAE2vHc2T4IU4axSUmhKSSvqGa624lMV7aJt1nXr10kzOP3gph5/Q0FBvpFs0p16xw6doO95WJKTk6UDCFpKSqpxv+tvmZrePwRy4Gxl2/YdxrxgamqamdB4KyEtNcVsmBo8eAg2fZZsHvWWvr7Hk1RtWL8eniGjpXmL5hUiVSR0jUDKSKCdEs/6jm113j+fGx3aBIJI+xPoJIpChfPPP99MfvzJWx/TqiS6jj91fkg7sZs6d81S6VRw3OE0rxzSay7jH5A1hkGQ2rSLC5FkmFpLDI+SDnBj3R9Shd1FuUbyaXyuQG9XQxUhQPZMpRnAnwesNx/OkU4NgmR7cL68Djut9zdsL7sbxktOZEPZ0rydxJwokLYZ6abyFYER0mLEWJh2amt+U0pHj2zsGOkKt1evXsa2MKUU69etk+07dhjD/EwcjLhO2FhHEkjzSjbQ3irdYO/auas4La/RyxvLXL5ihbRDfV26dDGkceHi+dIoJlb69+9vi6i1x5R9cLYB74QjRoyokJSNeocNGzaSOEigg4IOS6NGjY2uLfHdH3JASUO1P/kAOXb0mJyIP4H+zWVnt1HD4cbMmXvVnEguw7vKTZ+c9GgoHwGqvvwMVQ5uMIs4ZVWj/FyuFDSRVoi+4zg2JXKjGwkdVae44TYuLs5ISn0tS9P5jgAnKvS6Smsf3BPj68SFKmjr1/8srWEzXb8P3/AuGSV9S6+pzjAEuKN6zeJF0vJAKnShoShryJkfN3GKF0cUUDvXFagucBLk3AY69kAE/myMHqsSgQaYnPSLDJXLmsbI2pxoeRudYyYqSDieJU23r5P4rEyJzzkGyl0kWzHJ2d60hdx+9jgjRUhJSZHXXntNpkz5Cjuso4zJI3rie/DBP8tZ0Hf74IMP5KupX0MFATvlUU/6gXQZPnSw3P/HP0u7diUkg5YPPvrwI/n666lGWhsaGgYVBZFLL71E4uJj5f77H5ARw0fI448/bhwcPPLgg9K77wDp169fhSRXVYlfWWVRMr8ME4w4SKDpsKQsNYCyygmEig3/PA1WFS2zrPr0mhMBbFZrGCNt2rQxpGHL1i1eV1z2YsJEUnjZry6r2ITJWW09OOf3MXfuXKMXm5yU5Nf3wfd+w88bQJwDjaUMbtxtjAlmaINQrNCkmGdl7UXXAyhr9BbZD1G1LAp66IWYOB7FXiZaK+HE3lsgNdgPYcKB9AMyFnahrW17b+k13oWAkug6/iak7N4lGTO/lWF5RyWUZu38DqfnCcwqkIDYIjlWiI0QJA4sk+bXcK6hKhHgRhNw22OF0jDcpQsdCg+O+QUB0gKOBJL2bhOqcGDPOwi0gFgHyDzoQp910SXSHNIHSo+nTp0qn3/8kVx/8y1y+eWXGSnD888/L1988aUh0VmQClGH9/HHH4V0up289OJL8t3338nuPbtKkWiuaFDHNwZLui+88P9QfnNzo1yenT59uqRiUJw9e7aMHDlSBgwYANe+WcacVVWiUR1l7cP3sXXrNrnwogtLqb74U1cR8OegRScPPJ40VmtcJdDhgydi7U/5mrZ8BEjMqHdbPGE5tYLmzEkp2+ZNm6Vj+45mwuS8pueeEaA0c8XKFfIrWKyhAxN/3mWTFh0TJ+38o151y8SWxlELvXpyVUBD9SFworDIrD7ug7OUfKxUdmjXQZIwEaJqjadQWFgAG+DbJD423kxIPaXRuNMRUBJq+xMHAAA3HUlEQVR9OiZ1JoYkat63X0gLbDhrzgno6Xy4/HsFKRiF2Wx0owhpACNqY6PC5WBUpAQGB8qwVg3laOZxCQGRw+hVflmawm8ECGtwIxjdz8WAg77v8M4jEgmhP62kRPOBnoKdjzb1ZKAcbddFLhw23JAJmvxauHCBNEtsJTfccINRu6AO6EMPP4SFA9fLQNJRWHhCDmCAC4fDiqyjWWapNRybFjnIkTxb6QXVO2jf9aspU6AfGYOl3XAZd/bZ5p5IYOjl7+spX7rsv6Jc7g6vzYGkaup338MzYStpldi6Qk0lUYiJjilWf+FO9jatW0GKE2xsq7bDxkJrzqtCFWgmnxCA4pMheHyfi4m0IyefE1dZjmQewQbEvl6JhCNLvT/l9zFv3jyztN8G5MsfAm3BY9/BiTb7ghBYrOG3YMzjqcDFQlRtRz4vSpMHDx5sJP+0uEEb3d76I+7l2LNntwwbNqzYxna1Na4OFVy7R7k6BHRN3wo/oE3r18gueIm6/sRxCabmcoV4boCMjOXmm0JzC8nhQZJszk5K30DE8RrLrVDZpiD9xxsC5LkgBU1DgqShhMAGtEBC0FB6BxZIGJ6vmRXhOrn0MRzXhjeUTkOGG2cfLJKTKA6EUZj0kNxt2rRRHnn0L5KyN1V69+5jdByZjtKml1991RCLPZDMTpo0CXmi5IP335eDGYekS+cuhnjwnSIxnzV7jkSGhUgUXP92697D6KGSRI8dO07W/7xevvnmGywh5hkC7onQsM5fOpjvY9MmY/f2yiuuNKoYnDAwsM287gxlxREr/jEPCUM4VgFYFpdPrcOHipbtrQ1ltcdbHhtfkbwVyVNT9ZEoNIJOOiVsbCc3iJK88XnY50i1hK3YGxIXH2eIBNNp8I4AcaMJwL1798n48ecYMmbfYeYq732w+NpnwGMRVmjsbyvQ4W8GeyyvXJMY/1RVuqoqx9d21WR9nKwkJiaaFRoSZ6qbAeiSZ2AbfQpPrg5EQeWPE39v0mpHFj09hYCS6Dr6KhyFPtSPP0yTHvROGAByQMljRQcO5mNnx3GHfV7xbx2IqvX1Aeb8QIdHh2IK1EBCAX47PMukuCihnrQzZASGSGZSZ+nf96ziHdXsOLnJbccODoZ7jR3dsaPGyfvQg962fXtxdqpmXH/9DcZV7muvviJboN6wG+asuFlw9+495pn37NnTpGen/PTTT6PchoaoULIxY/oMM6jRlFtLXH/zzTeh+nHYdMQcHDlw1LZAs09Lli6Rrl26mqVmtq8iA5y9N+d9OsmGM96JgTOfe7wlFDbeU7vKuuYpfV2ujxOY9u3b430LMl1Tnz59jOTTYs9jRkaG+QZGjx5dPLGxGOrxdARoF3rNmtVQe2lunNHYd9Lbu2WvO0tiHCeRnOSQlHEzoVnVQn8QFg7pNGzaM419N515fa3H5nWv39f8tk5f059J9QWANDvvC1BjBCkZN+w1HrkBdCOELGPHjFW70Pal8PGoJNpHoM6kZBzEN8M74aFVy+QSSIuDjF3oit4BPjqSIP7xKzSzWZTF3/wgTXxFy9Z8ZSJArDH54TqAwRr/BkPHNjiCn63FHhIe/FoVGi3x/QdhwEvEI+GzEaNOwKW5n376Sf7617/KhRdeKDl53CmfB3WMhiYN/6Ge84ABZxmLBTNnzoCnqtVGmv3HP/5R8qDSEQ2SwkHwBN6jY8eyZebMmRgQw6HSEyAdoF+aA3UhDmKUwg4fPtxcp9S7tgZ+H7TrfDjjsIy4yGWRww7CzoGF7beDvD26x9l7tPnsb5vO/rbPxFkOr9l87ted6ey5Pdqy/cnrbEdlyvE1b03Wx3fTKTlzVyMiTitXrsTEr5FRu7FY2zbq8XQEaOZs374UGTHS9X3wm/GEm3uc+29aQeHz4PPhRNwlEQ000k7nxjX3fGwR4/i+OYOnOOd1nnsry5nOW5q6Up/zXnluyLMZFkrUnuy3zGe7ePFiQ547d+7sET/38vR3CQJKokuwqDNnWVhyX7J4mQw6vF/isKHABPZFbh2SzzfszOc8ZwH2d+m+zueiNWEFECjG3AX6sZAGsrZZklwFaxtWfYClcpCaOHGi7EndJa//v5dlzvRpEo1l79bJbbExsJmpmIMaJUR2oEtoCisdeGeoD+20VsFNhSz78OFMefbZv6PsBlBZOCETJpwr506YAAIdbgbIpKQkue6662TV0sWGVHsarCpwx1WahVK2dT+vkdZtWhn9bQ4i7sE5mNpze2RanpMY2Dj720k2nHHO8m0eb3H2uj3a+pxH57mv6epLfXwuzuewf/9+2QgTbVddeVWp78OJh56XIEAVsHUwfUkTdDSPZr+Pirxn7F9sH8D+wz4bxtvgLNdTnL1uj0xjz+2xInG2Lmde53llyvaUtybrI+Zt0c/bfp2OUyJhktZOMJ3t4/exZu16ufqqK4xamrOdel4+AgEAU+lP+ThVewoO7M8995ycwIaxhx95pML1scNbtWiezPrXC3LZwd0Shx23GuouAjQ8+FVgpJyYdLVce8tvijtJ5x1TN5qS1wPoLOPhGpkqGexkqSednX0MhLnAnHOplSYR6XyES+SULNvA94oqEDR1ZwPLYBoOiNSVpqSP54V4h0m6SeJpQ7o2BXZ31P37ftr3ZumyeTNYGYGEhhvTGCix4X0xnYlDtDk/Fcc09jrPGZjOuUzqii35l+mR4PSykcSf+pz12nN7ZG32nMf6XF8J8ljIwXs7feZ0KcQKzDXXXmveT+d1PT8dAdqT//KLL4z1nnaw2GMni+V9D/b9Y4n23P1or9Xn97MYE/Y5ZfQvNp3FzFs/xHSe8GQ0Q5Hpy1DVqUm/sxx+H7NmzTK2u7n53Nnnu3Lrv+UhoJLo8hA6w65TirB53c+Sl54hy08GwUW0NWfDL4oEgdIzSt5OfWFuca5UNp1rflUcZ4yp2TgSByzx4T9XjO04nXG2HK3PhbvF7hR5qgI8swOCZGdislwzfoJHAs3Xl2SWTlD45x4iYXkFgujiQAsd/HMPHEhJuvnnKTg7X0o7KuL5z1O5VR1Hgk+pJB0+rIcXtq1btlZ1FVpeLUIgJ+e47E/bL5MnX6wE2sfnsmXLFjlw8AD2TWyT1NRUH3NpsjMRAQpYaDv94osuVgJdwQeoJLqCwNXWbCQwXfr0lYYR0Fk9WeIgxZJdKzUrodCk0y5JmivOkmNaH6Y0jqEkzkx5PcSRHrrKIYkmcXfJ5kqX7cpdOq6kbK3PE3ae4uxzAUHGpOi85GRp3bq1eSr6T9kIcDLQAV4WKWm3S8tW0saclOpQOuMpzkh8ThXvlBLZGt3jKPHxVI6vcVof+gZgaIO/ePI50lV1t+7dJSkp2Rajx3IQaNOmtQyH984gTND5rur34OoXnO8iIawr33vbdm2FfxoqhoCS6IrhVmtzUerYHSS6S6/ep9oIamoGIlJXkFgu7YAo2KHp9LhT17GhrSQdz0GqMSgxjsGUgw7WSrWLy8FmOK3PHTtgUo14BmHiZHa9myej/5SFAHHq2rWrcAMNg/0enHl8jXPm8XTuazm+pvNUhzPO13J8Tecs29O5r+X4ms5THc44X8ux6eyRRFC/DyeSZZ+3a9e+1KTD4ujM5SnOed3Tuac8lYnzVIczrjJle8rrLNvTuac8lYnzVIczrjJlO/Pq9+FE1f9zJdH+Y1brcxhSVetbqQ1UBH4ZBEiolFT9MthrrbUfAZIq/mlQBBSB8hHQL6V8jDSFIqAIKAKKgCKgCCgCioAiUAoBJdGl4NAfioAioAgoAoqAIqAIKAKKQPkIKIkuHyNNoQgoAoqAIqAIKAKKgCKgCJRCQEl0KTj0hyKgCCgCioAioAgoAoqAIlA+Akqiy8dIUygCioAioAgoAoqAIqAIKAKlEFASXQoO/aEIKAKKgCKgCCgCioAioAiUj4CS6PIx0hSKgCKgCCgCioAioAgoAopAKQSURJeCQ38oAoqAIqAIKAKKgCKgCCgC5SOgJLp8jDSFIqAIKAKKgCKgCCgCioAiUAoBJdGl4NAfioAioAgoAoqAIqAIKAKKQPkIKIkuHyNNoQgoAoqAIqAIKAKKgCKgCJRCQEl0KTj0hyKgCCgCioAioAgoAoqAIlA+Akqiy8dIUygCioAioAgoAoqAIqAIKAKlEFASXQoO/aEIKAKKgCKgCCgCioAioAiUj4CS6PIx0hSKgCKgCCgCioAioAgoAopAKQSURJeCQ38oAoqAIqAIKAKKgCKgCCgC5SOgJLp8jDSFIqAIKAKKgCKgCCgCioAiUAoBJdGl4NAfioAioAgoAoqAIqAIKAJnGgInTpyQ48eza7TZwTVam1ZWLgInkeLkSf6rQRFQBBQBRUARUAQUAUXAFwTS09PlnnvukTZt2sj5E8+XDh07SExMjISEhEpQUPXIjJVE+/JkaiBNQUGBZGdnS0ZGhqxevVqKiopqoNb6XUVgYKCZsOikpX6/B3r3ZSPA74RB+6SycdKr9QsB/S5q1/MOCAiQtLQ0+emnH+XIkSPy0UcfSZcuXWT4sKHSo1dv6dK5syQmtpQGDcKqtOEBIBAq9qxSSP0vLDU1VX744Qf54IP3QepEWrdu7X8hmsMvBPjB4f9TxAAnGhQBRcAjAvw6Tp7EpD6geiQ5HivVSEWgtiPAb0LwdXAg0VArEMiGKseM6dMlNze3uD3hIM2du3WVSRdNkiuvuEJaJiYWX6uKE5VEVwWKFSyD0udFixbL//3fv+XAgQMyfvwEGTBgAJYeQipYombzFQHOHVNSUiQiIkJiY2NVhcZX4DRdvUKAk81du3ZJbl6udOzQsV7du96sIuANAUqhUzF+cBxp1ry5t2QaX4MIsK86mH5Q5v33v4ZEh4WFSY8ePWTYsOHSv39/6dmzp8TFx1d5i5REVzmk5RfIZdF9+/bJG2+8IZ988okMHjRAnnrqKenatasS6PLhq5IU3ICwdetWadiwoTRr1qxKytRCFIG6iEBUZKQcPXZMBg4cWBdvT+9JEfAbARK27du3m5XMdu3a+Z1fM1Q9AnwmaZjYUIWjM1Q3Jk++RLp16yaNGzeW4OBgLBhUz4qBkuiqf5ZeSyR5ps7zjz/Ohb7Ox5Kfny9PPPGETJw4UcLDw73m0wvViADUZ6rr46rGVmvRikCNIuBS6TgpVg+0RivXyhSB2ojAicJiFScdQ2rHA2qSkADB5KcSHR1tiHNNtEpJdA2gzCWfrCNZsmz5Mpk6daqkpKYYtY3zzz/fzJj0A6yBh6BVKAKKgCKgCCgCikCdRSAoKMhInmvyBpVEVzPa1Htev369fPnll7J4yRLp1aun3H3X3UZXJyoqyqsUlMSbfyr5qeYHpMUrAoqAIqAIKAKKgCJQAQSURFcANF+zZGZmymeffQ4C/YXRvb37d3fI4KHDzFJDWeSY5lmm/TBNDmWky7gx50j79u2VTPsKuqZTBBQBRUARUAQUAUWgBhBQEl3FIFN6XFhYKCuWL5d/PPdPSU3dZxTcr7vuWmkS3+S02piem9xIqvlHyfXzzz8vU6ZMMWl379wrDz30kERic48GRUARUAQUAUVAEVAEFIHagYCS6Cp8DrRNSIsP33zzjcyZM0datWol9/z+bmNeJTQ09LSauNFw3bp1Mnv2HDn//IlG4nz06FFZvHixXHjhRdIAeZavXC5Lly6VoUOHquWO0xDUCEVAEVAEFAFFQBFQBH4ZBJREVwHulCbT5vDMmTNkxsyZEhIcIjfffLOcc845xuVkWRsHV61aJS+++IK0aNFCkpKSjKrHb279jTRt0kTWrF0LU+4B8re/PS2PP/5XsxmxCpqrRSgCioAioAgoAoqAIqAIVBIBJdGVBPAY7Kf+F8a9P/zwA8nKOgqHKeNlzJix0rZtcrmSY6pv9OnTxzj8WLp0CfKeY3SnLzj/AqPWER/XRLp27iK/hy/4FStWyFlnneV1I2Ilb0OzKwKKgCKgCCgCioCvCAQG0ZWnr6k1XR1FQEl0BR8sVTGouvH666/L/PnzjFecP//5QZDntoY8lyV9dlbJTYM9YbFjzZo1xu87nX/QTMtaSKGfhU718exjxt4hybavZTrL13PPCBDj5vA0pd4hPeOjsYqARaBFy5Zmn0dZm6FtWj0qAvUFgaYJTbGfia6/NdRnBJRE+/n0uQmQesvffDNV3n//AwmH2+iHH37USJFJzPwNdLIyfOhweenlF+VnmMKjHjVN4i1auFA6tG8nx0Ci77/vfiOF9rdsTe8dAU5IOGHRoAgoAmUjQI9fGhQBRaA0AlFR0aUj9Fe9REBJtI+PnXrPhw8fNpv+Pvv8C0k/kGZ0niddNEnaJLWplAm6/v37SnRktEyb9r2RSE+fMV06wpXonx96WDp06OBjCzWZIqAIKAKKgCKgCCgCikBNIaAk2gekaXaO6hVTpnwlq1evlu7du8lvbrnZOEyJgCTaW6DKx/79+41777i4OGOmzpNKRpukZOnQqaN8/933Rpf6oosukonnTZQ2bdp4K1rjqxEBPjc+J/5x8sTg6blVpAksr6rKqkj9mkcRUAQUAUVAEVAEqgaBAAzqqhlfBpZpaWnGZvNXX30lLaEbeOmll8rAgQONKkBZOoJU+/j222/l3Xf/I3S6MnLkCFjsuAV6uM1Oqy0vLw8OWabIaljquPCiC+DVsLdQzaOuky2+eunp6bIQqis89uzZU3r37o1JR4EsgZm/bdu3SevWrQ3ejRo1KsbtxIlC6KNvkyXwAMkyBg8eLO0guSfmxJBWTThpGTJkiFkh+Omnn8wzYPk9evQwajONsETNScquXbuE+Hfs2FFWYvNmFlR1WGZ0dLQUobxDGRmYNHU3Kjw0NchnMmrkSImEt8ktW7bKsWNHTRlMw7YHBwfLepgtXIl2sIxhw4ZJE1ha4WTqR7QjNycX9zNAOnXqVOefb/ED0xNFQBFQBM5ABPbt2yeZhzOlc5fOZq9SWbfA8WcNhGwZWLHmCjIFbxyX6DytS5cuxlJXWfn12pmJQNCjCGdm06u31ZQ+09bzX/7yF1mwYIFcccUVcscddxii5wvBXYuNgnfddad0BFlq1ixBPv74YxirExkxYoRkZ2dLKj7OsLAwCQ4JMcSLpGrU6FGG2NGmdF0n0Hx6JK+v/+8bMg/WTXi/06ZNM/dPUv3qv16VBg0ayMxZs4rxsTrnW7Zskb///VlJP3gIZHqzIeG9evUCqd0iTz79pOnslq5cLEcOZ8kMqMbQssnx48dlztw50rlTZ3n11VfNM+jXr59M/forWbZsmQwaNFge/MuDMnXqN3hezWT6jJlI94qEhjbAX6i89dZbkpOTIzt37TR2u09CWv3U00+BdGfJsaPH5McffzQdZ8ahDHn0kb9IHt6fVStXSQZIOJ/tk089KZs2bsJk4YB8//00Q6RVJ7t6v2EtvXoQ4CSThIGhPvRT1YOilnomIDB79myjZklhSHmb0A8ePCiPPva4BAUGGKHJ1xhL+vXtK88884zZ0xQfH38m3LK20U8EVJ3DDTASu00bN8qnn30qixYtMpJLfgSdO3cuc8DgoEJzdxuRlyR7JQkUCFMLELLUtFRIM3tIk6ZNjUSUZPHf//633H///TJu3DgjLS3vA3Vr5hn/kwMxsdq0cYM8+OCDZkMlJfcHDhwwZPr22/9HJk48T6bCcc1PP86Vbt26GbN/xJaTmri4xmaCQwc3TzzxVxO3YcMGGXjWQIMr7W9P+/57Wb58hbzx+msS06ix/DD9BwlAB4d/0NEFmufJdtAWN8kASTpte1911VWwzf036QG1nbvvvlu+AtGOjo6Syy+/3Gz0fPPNt0zbKR2/9Te3CjdePfLoI0bysH3HTklu116eeupp40hn+/btsnbNWniwXCF/ffxxCQkNMRZd5s2bL1deecUZ/xz1Bs5MBKiyxMl8fn6+mcxTLY3nXF1jX8T+jH0hJ5AUKJyAF9Y8XOf3dywrS956+y05a8BArLCNNPlYFr+fKKzQcDWGeVkW8+fjnMudnBRrUARqKwJcMV67dh28DKeYFVCuXAaCIVFQQjO2lChzJTMhIUH27t1rOAG/oz179pqVaY45+zHWxzYeC+HOFolr3MisQjINxxl+X5s3b5JtW7cbgwS9eoETNGlqvpPaiom2q3wElESfwogDxZ49e2QWJJ/c4NcIpOuOO34Hm89jzLJ8WVCSyNHLIMndjBkzpBlUNiZPmiyBIQ3kiy+/lMsuu0yGDR8OqefXZkbKpX9+jCSRo0aNMgNNWeXX1Wu0chIZGSGcoXOwHT16tGwEEeaA3LFjBzMoU4pfWHjCSJnZcSUkNDOmAKmuwcGeA3fTps3kMDrArCOZINtDzSBO0r1zxw7ZuGmTNEEeph0zeoy5ZvFkx2b+MMTzSILAyRKJwAl0fH369pdonGdlHoFkIR0S5O9N1njU3QCrCHSQQ6k1O0eyBJKFwxmHpG1ysrkfLuFRBWj+/PlmgrVg0ULkL5JIEPKIiHDbDD0qAjWKAN91muf89rtv5QjebX5LVFPbtGmz+T4GDRoonJCuWLkCKyaDzEpRQUG+HDp0yHx/fKcXQsBA1Sd+L7NmzTSqVydh7YsqVOzT5s2bZ74p5p+O/rQ1HEkNGDCgRu9TK1MEfEWA4//06dOx+jxX2rVvawQ5t9xyi5w8EQD1vw1wfpZgJpOL8d5znPriiy/kmb//A5PNQvngg/eN2t7+A/slG4K07Tu2Y7w4AL8RWUZNkWMUiTSFch9/9CEMESSZ8WT16lVy4403mu/P13ZqutqHQGDta1LNt4hL7lOmfIll+EfM8v952NRH6ejEiRPLJdBsLXWf/oz0GzavNzNYqg+kYDY7efJkQ7D27t0n337zrZH4kHh17drVXGuGGW19DZT8kjzn5eWbycRRzPY///xz4IaZfFysLIHzGZLsrZu3GFJLvefrr79ezjvvXOnQsb3sh3UUPrc04JyWuk9aAteE5i3Ns6AVFXZYq6FScxSqFjQZSJ3rL774XLZs3gyPkkHIv99YW9mNiROlbnZZmgTDGYKQNhbtTIBNUL4PlLzFxsZ67Pg4EWgNE4UbN/5sJOrU2f4aEydKquPimshASO5GjRwDCUW8tAPR1qAI/BIIcECfO3eu7N61G9LkAeZdTdmXgonoYZk9Z7aRuH3z/dfCVRQuUVPFKRheWIcNGy7cX8DJKSVo7aH3yQnvJnxTVI2KjIrECtv/GdUpEgcKJN599x2ZBnLi3NPwS9yz1qkIlIUAx4D0g+kguyekU4eOcsGFF5h3HMMUhCXN5aabbzKEtxDpDkFlrxCTSgaOF/k456rLIEwYqQPNcZ8TRqqAUJhTiFWc/Lxc+RHfXIOwcOnfv78REm3Y8LORepfVLr1W+xGo15JoDiYbN22U/339f4VLMWPHjsWS/WXQy00qd+mRGw656YCbxkiit4DsPfbYI9IqsY08CfUCejB88cWXzOCxHKS6M/Rib7rpRkhNmxrCxqWi7vjA6psah/OT4MY+OpF58cUXJSY6UkIahBWrR7z00kuyeNFio4dMST5JLAdyhuEYzNesXiOPQ4UiH51aclIydJoHSWJiojz77LNy7/33Yvn5hJE8N2zYyKhmxED6GxPT0HiTpOfH9957D+Qh3UiIKT1jiIuLNxZU2DHGgSjHxMSYOkdgFYEqPi+9/JKRKFCvmmYNufGRZIF/fA9iYHe6D3Tglq9YLg/86QG0ocioh7C+0dB3p141nzcnT4nYMKlBEfglEOCEkfr4e/fulqVLFmMjcy9JSkafF97ASJ0pBFg4f7Hcfdfd5v1v1bqVkS7ze/3Pf96FSlO2NGoYLW1atRY6nGBftmf3XiPdTknZZ75ZvvPsFz/++CN59NHHhE6lNCgCtRUBCkAmjJ9gxo2vvp5qNoxH3xxtViRbtGgpjbEyzZUYfjtFXHLxEDhuFBUVmitWKOP6IZKLVcoDUO+kYGjBgoUQrhVgDEnG6qd3614eqtCoWohAvSTRJM+UsEyZMsXoJnNwePTRR81SJD+msgJnrNxE9gik1hs3bjKWIYYOHYKPIhcSml0geCNkIDapzZg5Q96G3uA///m8+fAs2bJl66YyMe7Ob7rpJkM0D+F5ULJFiRVn7/zbtXOn0FsaPQsSPxtatkyEPvRDshnLz5QUc/ZPnU5OUF577TXZCqsZjWMbGz1rdmZU06F0mt4kiTufNwd5Eu3EVolmtYHlcxMpJQr8u+uuu8xz4znLf/jhh41Vj4jIyGKvlEOHDDVqG+w8eZ1pqQ/66qv/MoSCJJzWRUic7733D7IDErx8qP4kQQodBcsdGhSBXwIBfhOjRo00KyQLl8yTl1952RDfieedZ9SX2C9GRcUYazObIWUOh+oSN0HzPXeRgwAJDArBb8Fkdq188vFnMm7sGBkyeAi+yW0mHftJbsSlbjSXtZlXgyJQWxHgu7oOVpXOOmuA3HrrrfL000+blZRBgweZsYfvPd9hOz4cz83D+33crLocgOoGLpsQDBXOwFNpi+8Vr34YJNDNm7eAA7Uoue23txnd6PnzF5jvrTidnpyRCNQrEs2PgLPJxYsXyRToNB0AcbvuumvlYugvt0xsWeYD5JIMBwYOKo899hgkowmn9AFnGbN1NEv3r3/9Sw6k7ZfVkMBwQyGXb1atXAlSPajMsuvzRRJMklv+OQPx5Z+3QNLcu0/vUpfZ0ZEk9+vfr1R8Mkgr/2wg0aW+sntwrgq4T6ZYX38Qb2ewxJ71OtPTtB0l7M7AsmlGT4Mi8EsjwL6MFmJIHC6ceLFs27JbUlJSzEoKv0Oa8/zNqQ2zAZgYBgS6JrB8z81vEIYThQUQRKQbdSya7RyM1Zz//hcmHHOzzeoOVahy8o/LnXfeKe9/+L6ZiFJirUERqI0IcEzg3qa33noT5Lm17IQA59JfXSYRWJ3hvhf29ezjed6mdRusJjaT55//Jyab0ZiMNjLCH26cbYFvITSsgVH5414ZfjNJSUnmOtUB3/3PO4Y/HAcB7w3OoMKU2vg2+NememMnmibO1kBH9kts9CMR7guSM2nSJOnStUuxmoA36Ci5prk7qnBQUvrJJ58YErZt2zYsWa6Twvw8ufraa2U5TKXt3bNb2rbvCFKeKB/ig3keKh0XXHCBt6I1XhFQBBSBGkWA/dny5cvlB1gJ4gbakJBQbCy8xJhopEmvF154Qf7xj38Y04y0o061DOp3csMtN1RxcrtnL1Z3Mg5Doj0K1mumSnBQoCHh22CV4FfYpHgs+7iZ0HID9dewbpOY2Mqs9NXojWplioAfCNC6FrkBV06474VCD044uZrCfS0UotGCB78D2v0n0WY8N79TbZBEm/t0yBFIyBm4GpmWmiZx8XHmOldFyRuYjyucuiLtxwOqpUnrPInmgMENMp99/pn8F5ti2rRtLZMumGyW8/myc6boLeTAMQadaVA/9tVXXpH3339P7r7nD2Zw+cMf/iB9sZkmPr6J/AvLoeeMHy/XY+PbdFjnOIAPjOoi1JOligDVETQoAoqAIlBbEKBVgayso2awj4SKEv927dwl72AjIDdPPfzQQ2ZfCPtPkgdK6thX0ooBjyQJlGSTDFDPk/FcrcnFBqoIWLkhMefSN4kFiQgDy9CgCNR2BPjO890tLzAdv4WyOISnMiqaz1NZGvfLI1CnezV28tNhG/iNN/6N3bR5csONN8v4CeOhhxRtOvey4Oes9J133pGff/5ZnnzySRmNTYefffGlfPfdd9IXm8c4CyXJjoXu7eVwxDIeJJpLofz4UkGiz0Z6boij+SgNioAioAjUJgSCgoINAbZtIlGmRaFgkN6LL55UrJ5kdUBtOqvyRGkc/xhIpG2wcfY3j0qenWjoeW1HwBcCzXvwNZ37/VY0n3s5+rt2IFDnJNHUe6ZUhNJnOjRZBNu8Q4cONTp+XD4pK3CGSKkJbahyCYfmnl74fy/Kgw/9Wa6+8ip556235WV4u3vggQfg6nmnfI2lzeGjRssf//QnoyvFuqk2Ugh9wejomAp/ZGW1Ua8pAoqAIlAdCLDvYx9miXJ11KFlKgKKgCJQlxCoUySaivy79+ySGdNnnHLfnCC/wuaAUdDboyONsgLzcjMMdQW5sYYDyW233SY0tUZd6JdfftmoaDyEZc6WLZrJm2+9I7mQdDfCpgJuLvB3Saestug1RUARUAQUAUVAEVAEFIHajUCdIdF0pkGPQ3N/nGN2jI8bO844xmgF5xfelk+sbhIfEc3bPPHEE0bNg+acFi5cJLfccrPxOHfffffClmpvuPNsDNNOwbA1PFqugAqHSmxq98utrVMEFAFFQBFQBBQBRaC6EDjjdaLzYRlj+fKVRu95//5U2CsdJxPPnyhJMCvjNDvmBJDkmSobc+bOkeYwVTMKbjy3bdsqm35eL888+5xx2/zP55833ub+9re/GffftOrRHJ6Lbrv1NmPDWAm0E1E9VwQUAUVAEVAEFAFFoH4hcMaSaOru0XQMvcB9CH/0vXv3NvYX6X2rLILLXeU0dUfPdksXzseul1CTj5Y6jkMPmiadxo0bZ7wXToMJqPfffx8OU/5pVDtIymkLUlU36tdHonerCCgCioAioAgoAoqAOwJnnDrHSbjczMw8YrwGfvTRR5INF7S0gnHxxRcX7xZ3v0n7mxLo/7z3H6Pn3K1rV7nwwouM6brQkCC58+7fy9vYOLhq9Sr53e/uNOodC+A8IAC71d9EfD+Ys9OgCCgCioAioAgoAoqAIqAIEIEzRhJNyTPtka5Zsxob/742RtH79+8vl0yeLJ27dIbec4lbaPdHS1N3tNtMCXUjeLTLPpZtXHBOmDDB6EA/BFvOS+Eo5bpf/1pyXs+TDz/80FjbGH/eRJkJE3k7d+1QEu0Oqv5WBBQBRUARUAQUAUWgHiNwRpBo6257CvSSFy5aZFw433333YbY0sWyN/UKEu99+/bJZ599KvPnL5ToiDC5+tfXyTnnnGNc1G7cuNFY7hh39jjZsnmLXHftdfL3vz8jH3/8sbHIQbe2/eDquX+/0u6e6/H7oreuCCgCioAioAgoAoqAIgAEaj2Jpt3lKV9OkU8+/QQescLluuuuM/rKdJdprW5QTYPOURjoZtMGqnq89957MnPmTOMIhSQ8HObozj77bFmyZIm88uq/YAf6ebnzrrvk0MFDxp0tHQPQOkdKSorxanj55ZdL69atbZF6VAQUAUVAEVAEFAFFQBFQBKTW6kTTbjO9BT711FNGdeNXl14qN9xwAyxktDhN8kxLG3fedaeMGT0GljTuMCSYzzY1NdXEt01ua5yf/N9rr0hIRCTKfFrWrV8nP8790ThkcXfCQuLODYgk6nRbq0ERUAQUAUVAEVAEFAFFQBFwIlDrSDTJM70NfvPNNzJ79ixpBhN0N918swwYMMCr1Y3Dhw/LVVddJRkZGcaSxuDBg42UmmR4wYIFMn3mNFm3Zr1cffU18vTTT8Ftdz/57W9/K60TE6UZSLkSZecroeeKgCKgCCgCioAioAgoAuUhEFheguq8TjUM6i0z8JyS408//VSefPJJYx3jmmuvlb8/84xx212W2Tqap7vjd3fI0awjMmXKFDl06JApMyIiQnr06CF7d6VAeh0oJNsJCc2lDWxIJyQkSAuQaCXQBir9RxFQBBQBRUARUAQUAUXADwR+MZ1oqkt89NEn8ATYQzp27Gh0lN9++21jRWPcuLNlwoTx0q59OwkNCS33drixcMjgITIe1jZmzJhh7Dxz8yA3FdJJyvGc47J100b56MgR4zjlbGwkpKqGtw2J5VaoCRQBRUAR8IJAXl4+zHBmmj0c3PjsDAcOHBBKLhrHxVXJBL6goMCswHG/SBT2e3jq0yig4B8FBtnZxyFMyJAmTZoUq70521fRcwpDDmcckpMSIHG4t6oMLJubyxm4Z6U6AnGkkIW+AHRsqA6EtUxFoG4iEPQoQk3fGjusDz74QB555BHZvXuXrF27Vt5++y1p06aNPPjgg9j4N86YmAuGi21fA52gREVHyZzZs2XDho0SHh4uvLW5P/5oPBjeettv5ZprrpXBgwdBPzq6eFOir+VrOkVAEVAEfEFg2bKlct89d0kOnDedBes+NpAM3nLLLbAM9F8ZPGSIREZG2ksVPu7cuVPuvfdeQ4579uzpkZivXLnSbK6OjY3FPpC5cuftt0mvPn2lVatWHkl3RRrDPv2ee+4ROqiaNGlSRYrwmucIhB9U79u+fYe0h2DFbij3mqECF1YsX242refk5MqgQYOK66BZVRL4slZCK1CdZlEEFIE6goDvLLWKbpg6z5QWv/DcP6B2kS7TvvtWesPL4O/uvFMuuugiCWsQVqGa2LH26d3HOFB56aWXZPOWTdK+XTt5Bm67R44cCalQRIXK1UyKgCKgCPiDAInY3rR0OXIkq1Q2kughIM/BkAizH6TnVEptKZ3mpD8JamaUhJI07tixQxo3bizHYWEoPj5eGkJlbfPmzUZKSmtB3ExN60OxsXEoc6ixPkRp8969eyUtZZ/ENGosLVu2NNLmWbBO9B9YKaL0uSVU2MacM8HUyzbs3r3bqL81bdpUEnGN9dtQWFgo+/fvN5aKoqKijJUiCiso+MjNzTMriLTBz3Y1b95cDh7YLzm5ObJt2zbJxepfK7QzOjpGmIaeYNletol1HUC5B9PTpU1ysnGStX79ekNUmzVrJin79mL1MEdatGhp2kw1v7f+/YYEhTZAXz4c9xRuVhmJE8sjhmzrli1bTFmMp4UlxqcAi1Dka9u2rfE2a+/N/bgem9i5F6dVq0RDoLlSSn8BJO9UF7wae25GYBypLkm4e3v0tyKgCJwZCNQoiWZHx41+zz33nGzfvccgRI3oeHTufSEZaYDOrjKBHf3EiRONjecu3TvK+edeZAYGT0uclalH8yoCioAi4A0BaJdJEP/xEGbOmiXRkRHSDKTzpZdexN6MFpKevh+kM0fugu37Dh06yN8w8aeJzQSQzXQQTW6sHj5smJH0jhk7Rh64/wF54cUXZd3a1fLYY3+VOXNmQwIdKPkF+fLMM39HPxoqQcHBcsH558v5+OMGbRL1xYsXg5i2MMRwzJgxsmLFcnn3nXel8EQhpK1F8NT6O5PeEunV8N76xBNPCjdo5+UVwqb+CLn++l/LG2/8W/bs2SOvvPKKIZ533vk7uQtmQgOCQ2Tz1vVy3/33Q7Ujw5D7W2/9jbGANGvWbJgfjTaTgPvuu8+Q4JdfflV+//u7DMG9447bZfhwCDsgnadJ0jCQdYFyyO//8Hs5gAnJNkjcMQeR2bPmyMFDB+XLKV9AReWkwfmPf/qTIdxPPPFXY1UpN7dAjmQekqTkdkZ1hRj+CWno1dYTCSZh3gh1vwApku7duxvpPEn9f957VwYPGiL78Czex8pp5y5dDH4eHqtGKQKKQD1FoEY3FtJk3YsvviCrV6820oTmzVtI9569pFWbJOFyYFUEdoJUE7np+t9U6XJlVbRNy1AEFIG6jwC4HQiZ6895t5QUp0Gqmpq2H3btj0pqSipU2FqBSP5eCiAVnjdvnnzyyacgu0vk1yCr9MjKfR1HsGH6BAgypcKZhzPNZmyS1JS9+4waxz6Uw83U06dPl/Xr1hoi3r5dWxNHlZFeWKFrEh8n3bp1MyRzHyS9lGR//tnnhhTeiVVASsFXrFhhpMa2zcuXr5DlUHNIhrS4W7cukoE6qOtNner9+9OMnjWl2ST8x+AFlpJ2buC+6ILzZShI/3R4e+Wq4+effyaF+bnSu3dviYyKNOm5DyY397ip86effpK9EKpQWjwX6iaFGAsGQA2mEaTpJMBU82sOK01sR8NGDVHeF8YfwOjRo2X7tq3y1ltvG2+2tM4UH99EbrrpBuBZgHLysLo5CdeyoOY309y7vTfnkZJrSs9bJ7YxUn9eo9T+f/7nDrkZE5gk1F8dKiTONui5IqAInJkI1Jgkmrpl3377rQRjoyAHCHaYHTt0NB0kN3Jw6bIqJMbcPMNlPA2KgCKgCPxSCBSCSbvsDpVuQVGRS7+WZDMMEuNJUGHrB7L8zntvGcJICW9sbGOZfPFko9Ix7fvvJQiqagwk4ewj+UfCGgjJL2sJxO8g7B8ZPmy4rF2zThYtWgjVhTA599xzjRpbK6hpREC9gRaJDh48aMraD9WLlLRUGTFiJPagnAPvr/2N7q9TT5uWjfr27YtN30tRXqgMHDiwuC2mkFP/2H6bbWqNScFll18hJMbTv/8OEuFMmTz5Epn+wzSZhb8mIMPso6mPPeCs/rJsyWKJQv/fDKobYyFlJyGnXvUXX35hiGyDkDCj/tEQ+11CwiNN3rTUFCk6UQACvV1aQGWEknSucjL079cPm9InwOvsR9Cf7oAN54PlzTcbyRGMP2yfp2BI9NZt0qdPn2JnXVSZoQ75O++8Y/wVXH75ZRhXYj1l1zhFQBGoxwjUGInmMhq9/9E+M9UuOLO3A0I9xl9vXRFQBOoYAoEQQ4PXSlZWlpEks5+jzjP7PernctXNJbUVCQkNMXcfUBQoDSIaQC+4gdGXZt4DILoZkPoWFp6QhtB9ZhnUL6ZqBiXZDCTQJ0Aijx/PNlaIfvWrS40ayHvvvy9Tp041/W0R7IHkFYFwO0hkVGSUUZ87BOkt81L3l+Lzq668ymy8JmGnBJxEnPrOH33ykZGS09srJcR5eQXGS+z+tDTTDvtPFvTAqc99EB5gC4vEENx4CDWo4pGKtG/87xvyww8/GKI7FKT/W7Qxr6BQbrvtNmAWaOriBkVKoLlqSULduXNnU3xoSLBRx6DKx7DhI+R8qO5tgUSd+134x9sjQecfbybUYOsizpyGcBMmhTmUyFNww8D7pC40JexUpaGFDv5xfHrjjTfke0wE7rvvfmPxic9OgyKgCCgCTgRqjERzAKD0WYMioAgoAnUZAZK48PAG8u6772Bz2kfmVocOHWJ0nbkxj9aBQkAIwyIiQdZcXTDN0zWFCkHHTp2g7rZKfv1rqCRAHSEDkmPqV1MqSusbs6H/vHPXThC/nWbDG8keVRzCw8Nk08ZN8g10hXv17S9HDh+StslJZjNdo5goCTqZazYyMj1X/bjpesyokSCJ00x93JB47dVXnSKgrqezDyoWb/3739KhcxdsVkyTdu3amj0mnTt3ku+/mSq33nITiHKg0XXm/XCSkJ5+QO6++x4Q0YMgpe2MY6tnn31WcmH2r3ViSwmBMIUeYtkOkuNEqPLt3LlDzgMh5uSC+tBUTWmZ2AIMvEDa4R44doTFNJFdu7dJNgg/N2fSwslWbCTcvmO73HDjzWaTYzSk1cSXkwVK1IMgqaeEPgJkOhSS+FmzZsrXX02VZ5971kidObmh5Q1ueiThfvnll+S11143beveozvK3yohgScxefgE6h7b5cYbb9BVTterof8qAorAKQRqjEQr4oqAIqAI1AcEqO/7wAMPFFvnAFczG99IXhlPkk0i+eBfYqDO1tr8vvHGG0HksCEQ184552wpOgm7zpDMzsw+Bj3iKAPbXdBd/u/8eUIpciRIdwMQP6pc3HvvH6Q11CNiG8eBuLY3utP9B5yFTXGDDbEdPmKE5IOQJjRNMGoUVBcZBDWHgTDl1hYqD/tgwaIl1CnOgVqHtWJEknvxJZfAykcjQ9p7w57/QJTXBZvraC0kOCgEEvE06dK1m9l4SH3nxMRWxrwdpeTcjDgIm/J6gIzGxMTIgkVLJD8320igx44bZ4guVydp+WLAgIHG8gfJ8r333StLFi2G+kUWNhqOgKrJ2dDnbiK33XqDrF65AudN5fbbbweJ/kkOYYIxGW1kGhLn22//H0lKck0caEqQExNaCLn/zw+aSUgOsKQuOHEmgWYg3sOGDjWS6UJgRKl/KFRX4iD5p9Q6F9ZGGGgphBY/NCgCioAi4ESg1rn9djZOzxUBRUAROFMRsOoTlrCVdx+UilJ94fnnnzeb6Ki6kQdb0w899JCRQrM86v6yPE9WJlg+1RO42Y/kkGmY1ubjdRvHcwaWRwkwJbgkzu7BlsdymMYG5uM1ElKW77xHq65irXwwD+MMQQXxZ9t4bzRFOhUS7euuvQ6bAW8y9bMspiUWdlLB/K52FBgJPvOzfqZxtonpvAXmp0lBmsEbBxLPCY0GRUARUAQqi4CS6MoiqPkVAUVAEagiBKgLvWHDBqNXTKkwJb9JkK7WNWcftEaycMF8yYUVDW5epHS7OgPJOaXjJNNUO3GS/uqsV8tWBBSBuo2Akui6/Xz17hQBRUARUAQUAUVAEVAEqgGB09fvqqESLVIRUAQUAUVAEVAEFAFFQBGoSwgoia5LT1PvRRFQBBQBRUARUAQUAUWgRhBQEl0jMGslioAioAgoAoqAIqAIKAJ1CQEl0XXpaeq9KAKKgCKgCCgCioAioAjUCAJKomsEZq1EEVAEFAFFQBFQBBQBRaAuIaAkui49Tb0XRUARUAQUAUVAEVAEFIEaQUBJdI3ArJUoAoqAIqAIKAKKgCKgCNQlBJRE16WnqfeiCCgCioAioAgoAoqAIlAjCCiJrhGYtRJFQBFQBBQBRUARUAQUgbqEgJLouvQ09V4UAUVAEVAEFAFFQBFQBGoEASXRNQKzVqIIKAKKgCKgCCgCioAiUJcQUBJdl56m3osioAgoAoqAIqAIKAKKQI0goCS6RmDWShQBRUARUAQUAUVAEVAE6hICSqLr0tPUe1EEFAFFQBFQBBQBRUARqBEElETXCMxaiSKgCCgCioAioAgoAopAXUJASXRdepp6L4qAIqAIKAKKgCKgCCgCNYKAkugagVkrUQQUAUVAEVAEFAFFQBGoSwgoia5LT1PvRRFQBBQBRUARUAQUAUWgRhD4/xia7qVrS5NgAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "fe0bfa57-dca7-40aa-9ead-c6852b155878",
   "metadata": {},
   "source": [
    "![Screenshot 2024-03-08 at 12.17.24.png](attachment:313b90cc-03f2-4c01-acb9-382f6b1d41c8.png) ![Screenshot 2024-03-08 at 12.24.38.png](attachment:af3ff267-9245-4a36-b5cc-53b6eaf7def3.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e47bae4-d27d-4430-a134-e1b381378f5c",
   "metadata": {},
   "source": [
    "## We combine the concepts of Multilayer networks with the propositions to create a semantic knowledge graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f9c9376-8c68-4397-9081-d260cddcbd25",
   "metadata": {},
   "source": [
    "Relevant articles are: https://arxiv.org/pdf/2312.06648.pdf and   https://link.springer.com/article/10.3758/s13423-024-02473-9"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8861e1e7-b438-42e4-a16c-afffad738bd3",
   "metadata": {},
   "source": [
    "## We start using Cognee by getting the prepared data and understanding what type of data it is, using LLMs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14ef9446-ec16-4657-9f83-a4c1c9ef2eba",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f97f11f1-4490-49ea-b193-1f858e72893b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from cognitive_architecture.modules.cognify.llm.classify_content import classify_into_categories\n",
    "from cognitive_architecture.modules.cognify.llm.content_to_cog_layers import content_to_cog_layers\n",
    "from cognitive_architecture.modules.cognify.llm.content_to_propositions import generate_graph\n",
    "from cognitive_architecture.shared.data_models import DefaultContentPrediction,  KnowledgeGraph, DefaultCognitiveLayer\n",
    "# from cognitive_architecture.modules.cognify.graph import create_semantic_graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "84da594a-459e-4ec5-9a5c-3a6cc3ab98af",
   "metadata": {},
   "outputs": [],
   "source": [
    "required_layers_one = await classify_into_categories(input_article_one, \"classify_content.txt\", DefaultContentPrediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f56ae869-0dce-41f2-9db0-5f8d5eccba52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'label': {'type': 'TEXT', 'subclass': [<TextSubclass.ARTICLES: 'Articles, essays, and reports'>]}}\n"
     ]
    }
   ],
   "source": [
    "print(required_layers_one.dict())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6e64e72f-d18b-4d21-85d6-55ed3621124a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#note that you can provide your own Pydantic model that would represent your own categorisation\n",
    "required_layers_two = await classify_into_categories(input_article_two, \"classify_content.txt\", DefaultContentPrediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cdeb3631-fb55-4580-a5e5-d2a193a44e79",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'label': {'type': 'TEXT', 'subclass': [<TextSubclass.NEWS_STORIES: 'News stories and blog posts'>]}}\n"
     ]
    }
   ],
   "source": [
    "print(required_layers_two.dict())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b236853e-ae7c-4cde-b2b6-d8199973c2a5",
   "metadata": {},
   "source": [
    "## Now that we have content categories, it is time to provide them to our graph generation prompt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daa406c9-db89-43a9-a6b2-0ddc1e04bb22",
   "metadata": {},
   "source": [
    "The goal of this section is to make sure that we can turn our information into a set of relevant cognitive layers.\n",
    "Layers can be anything like \"word\", or \"sentence\" to some categories like \"movies\" or \"fruits\" \n",
    "In this case, we let the LLM decide what the appropriate layers are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c04c116-8f2e-4957-887a-aaf71874e8c0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fad0c4b0-cd61-4c3c-9964-47f019278060",
   "metadata": {},
   "outputs": [],
   "source": [
    "def transform_dict(original):\n",
    "    # Extract the first subclass from the list (assuming there could be more)\n",
    "    subclass_enum = original['label']['subclass'][0]\n",
    "\n",
    "\n",
    "    # The data type is derived from 'type' and converted to lowercase\n",
    "    data_type = original['label']['type'].lower()\n",
    "    \n",
    "    # The context name is the name of the Enum member (e.g., 'NEWS_STORIES')\n",
    "    context_name = subclass_enum.name.replace('_', ' ').title()\n",
    "    \n",
    "    # The layer name is the value of the Enum member (e.g., 'News stories and blog posts')\n",
    "    layer_name = subclass_enum.value\n",
    "\n",
    "    # Construct the new dictionary\n",
    "    new_dict = {\n",
    "        'data_type': data_type,\n",
    "        'context_name': data_type.upper(), #llm context classification\n",
    "        'layer_name': layer_name #llm layer classification\n",
    "    }\n",
    "\n",
    "    return new_dict\n",
    "\n",
    "# Transform the original dictionary\n",
    "transformed_dict_1 = transform_dict(required_layers_one.dict())\n",
    "transformed_dict_2 = transform_dict(required_layers_two.dict())\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "709ec529-bb91-45cd-82cb-c122eb69fcd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data_type': 'text',\n",
       " 'context_name': 'TEXT',\n",
       " 'layer_name': 'Articles, essays, and reports'}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transformed_dict_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "06b483bf-2fa0-414f-8253-27ffe9a2881c",
   "metadata": {},
   "outputs": [],
   "source": [
    "cognitive_layers_one = await content_to_cog_layers(\"generate_cog_layers.txt\", transformed_dict_1, response_model=DefaultCognitiveLayer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "35461aff-fd80-4eb2-94b2-66c742db8e55",
   "metadata": {},
   "outputs": [],
   "source": [
    "cognitive_layers_two = await content_to_cog_layers(\"generate_cog_layers.txt\", transformed_dict_2, response_model=DefaultCognitiveLayer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "41d06ecb-83b9-4284-8d88-6a3f710cb457",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracted Layer Names: ['Semantic Layer', 'Syntactic Layer', 'Referential Layer', 'Contextual Layer', 'Lexical Layer', 'Narrative Layer', 'Discourse Layer', 'Pragmatic Layer', 'Stylistic Layer']\n"
     ]
    }
   ],
   "source": [
    "cognitive_layers_one = [layer_subgroup.name for layer_subgroup in cognitive_layers_one.cognitive_layers]\n",
    "\n",
    "print(\"Extracted Layer Names:\", cognitive_layers_one)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1a287a2a-2fb5-4ad3-a69e-80ed2e2ffa5a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracted Layer Names: ['Thematic Layer', 'Narrative Layer', 'Sentiment Layer', 'Semantic Layer', 'Temporal Layer', 'Geographic Layer', 'Source Credibility Layer', 'Interaction Layer', 'Multimedia Layer', 'Intertextuality Layer']\n"
     ]
    }
   ],
   "source": [
    "cognitive_layers_two = [layer_subgroup.name for layer_subgroup in cognitive_layers_two.cognitive_layers]\n",
    "\n",
    "print(\"Extracted Layer Names:\", cognitive_layers_two)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "609b1287-e0bf-42a5-856a-f2e0d859ea8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we decompose each layer into a relevant graph that extracts information from the text and focuses on exactly that semantic aspect of the text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "42dbf97d-79b9-4627-b307-b64ac22db4f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data_type': 'text',\n",
       " 'context_name': 'TEXT',\n",
       " 'layer_name': 'Articles, essays, and reports'}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transformed_dict_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "25adeeb7-cce2-4eac-8fb5-4ff47029d77d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_classification_nodes(G, id, classification_data):\n",
    "\n",
    "    context = classification_data['context_name']\n",
    "    layer = classification_data['layer_name']\n",
    "\n",
    "    # Create the layer classification node ID using the context_name\n",
    "    layer_classification_node_id = f'LLM_LAYER_CLASSIFICATION:{context}:{id}'\n",
    "\n",
    "    # Add the node to the graph, unpacking the node data from the dictionary\n",
    "    G.add_node(layer_classification_node_id, **classification_data)\n",
    "    \n",
    "    # Link this node to the corresponding document node\n",
    "    G.add_edge(id, layer_classification_node_id, relationship='classified_as')\n",
    "\n",
    "    # Create the detailed classification node ID using the context_name\n",
    "    detailed_classification_node_id = f'LLM_CLASSIFICATION:LAYER:{layer}:{id}'\n",
    "\n",
    "    # Add the detailed classification node, reusing the same node data\n",
    "    G.add_node(detailed_classification_node_id, **classification_data)\n",
    "    \n",
    "    # Link the detailed classification node to the layer classification node\n",
    "    G.add_edge(layer_classification_node_id, detailed_classification_node_id, relationship='contains_analysis')\n",
    "    return G"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "b59a52d7-d82b-4546-b0b1-a3d0f62a2a65",
   "metadata": {},
   "outputs": [],
   "source": [
    "U =add_classification_nodes(R, \"Document:doc1\",transformed_dict_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3e7b9fde-fcd5-4891-b43c-177d3877559d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Structural Layer',\n",
       " 'Semantic Layer',\n",
       " 'Syntactic Layer',\n",
       " 'Discourse Layer',\n",
       " 'Pragmatic Layer',\n",
       " 'Stylistic Layer',\n",
       " 'Referential Layer',\n",
       " 'Citation Layer',\n",
       " 'Metadata Layer']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cognitive_layers_one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f06edd84-c455-4034-a38b-3a7d2f746f42",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nest_asyncio\n",
    "nest_asyncio.apply()\n",
    "import asyncio\n",
    "from typing import List, Type\n",
    "\n",
    "# Assuming generate_graph, KnowledgeGraph, and other necessary components are defined elsewhere\n",
    "\n",
    "async def generate_graphs_for_all_layers(text_input: str, layers: List[str], response_model: Type[BaseModel]):\n",
    "    tasks = [generate_graph(text_input, \"generate_graph_prompt.txt\", {'layer': layer}, response_model) for layer in layers]\n",
    "    return await asyncio.gather(*tasks)\n",
    "\n",
    "# Execute the async function and print results for each set of layers\n",
    "async def async_graph_per_layer(text_input: str, cognitive_layers: List[str]):\n",
    "    graphs = await generate_graphs_for_all_layers(text_input, cognitive_layers, KnowledgeGraph)\n",
    "    # for layer, graph in zip(cognitive_layers, graphs):\n",
    "    #     print(f\"{layer}: {graph}\")\n",
    "    return graphs\n",
    "        \n",
    "\n",
    "# Run the async function for each set of cognitive layers\n",
    "layer_1_graph = await async_graph_per_layer(input_article_one, cognitive_layers_one)\n",
    "layer_2_graph = await async_graph_per_layer(input_article_one, cognitive_layers_two)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a34971b4-d1fa-4db8-abbc-395bc70b0b49",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "de3bdbb7-0b2b-46fa-a42f-3ca288c4d875",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'{\"layer\": \"Semantic Layer\"}': KnowledgeGraph(nodes=[Node(id=1, description='Britons have a significant affection for animals and treat pet-keeping as an integral part of life', category='people', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=2, description='Keeping pets is considered a serious and passionate activity in Britain, not merely a leisure activity', category='culturalPractice', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=3, description='Dogs are particularly treasured in Britain and are seen as outlets for emotions and social interaction', category='animal', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=4, description='British society is accommodating of dogs, with public spaces and services being dog-friendly', category='socialNorm', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=5, description='The COVID-19 pandemic caused a surge in pet ownership, particularly dogs, leading to increased numbers and issues like dog attacks', category='event', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=6, description='Pets, especially dogs, are increasingly being treated as commodities and status symbols, with a focus on aesthetic breeds', category='socialIssue', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=7, description='Fashionable dog breeds, such as French bulldogs and American XL bullies, are in high demand regardless of health issues they may face', category='animal', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=8, description='Pets are increasingly treated like substitute children or used to project personal identities', category='socialTrend', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=9, description='Spending on pets in the UK has doubled in the last decade, with a trend towards non-essential luxury items for pets', category='economicTrend', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=10, description='There is a discrepancy between what pets truly need and the human projection of desires onto them', category='animalWelfare', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=11, description='Modern lifestyles can conflict with the needs of pets, leading to behavioral issues and insufficient care', category='animalWelfare', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=12, description='The relationship with pets should prioritize their wellbeing and recognize their distinct nature', category='ethicalPrinciple', color='blue', memory_type='semantic', created_at=None, summarized=None)], edges=[Edge(source=1, target=2, description='Britons are known for their serious approach to keeping pets', color='green', created_at=None, summarized=None), Edge(source=2, target=3, description='Dogs are a central part of the pet-keeping practice in Britain', color='green', created_at=None, summarized=None), Edge(source=3, target=4, description='Dogs are widely accepted in public spaces and services due to British social norms', color='green', created_at=None, summarized=None), Edge(source=5, target=6, description='The pandemic surge in pet ownership led to an increase in the commodification of pets', color='green', created_at=None, summarized=None), Edge(source=7, target=6, description='Designer dog breeds are part of the trend of pets being commodified', color='green', created_at=None, summarized=None), Edge(source=9, target=8, description='Increased spending on pet luxuries is related to treating pets as substitutes for children or personal identity projections', color='green', created_at=None, summarized=None), Edge(source=10, target=11, description='The conflict between pet needs and human desires is evident in modern pet care', color='green', created_at=None, summarized=None)])}"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "layer_1_graph[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "088e92a0-06e7-4128-b9b8-eacd9e735cb4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Semantic Layer\n"
     ]
    }
   ],
   "source": [
    "for n,y in layer_1_graph[0].items():\n",
    "    print(ast.literal_eval(n)['layer'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "142f4bd8-ec50-4715-ba58-981bda65116c",
   "metadata": {},
   "outputs": [],
   "source": [
    "    # print(\"Nodes and their data:\")\n",
    "    # for node, data in U.nodes(data=True):\n",
    "    #     print(node, data)\n",
    "\n",
    "    # # Print edges with their data\n",
    "    # print(\"\\nEdges and their data:\")\n",
    "    # for source, target, data in U.edges(data=True):\n",
    "    #     print(f\"{source} -> {target} {data}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "58644c64-7ef0-415f-8e41-e2edcf5fd15b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c94056bd-8d32-48e2-9982-e9af06da3333",
   "metadata": {},
   "outputs": [],
   "source": [
    "# from cognitive_architecture.modules.cognify.graph.create_semantic_graph import create_semantic_graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dd3f0e55-9f9d-4804-9ad6-31afd2088ab5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example usage\n",
    "user_id = 'user123'\n",
    "custom_user_properties = {\n",
    "    'username': 'exampleUser',\n",
    "    'email': 'user@example.com'\n",
    "}\n",
    "\n",
    "# additional_categories = {\n",
    "#     \"Natural Language Text\": [\"Articles, essays, and reports\", \"Books and manuscripts\"]\n",
    "# }\n",
    "\n",
    "# G = await create_semantic_graph(user_id, custom_user_properties, transformed_dict_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "2cc7c3bb-7cc0-453b-beab-2983a703ccda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data_type': 'text',\n",
       " 'context_name': 'TEXT',\n",
       " 'layer_name': 'News stories and blog posts'}"
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transformed_dict_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b3160a1d-a6ea-40ce-a521-37ad26d31ffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes in the graph:\n",
      "[('user123', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'username': 'exampleUser', 'email': 'user@example.com', 'exist': True}), ('Temporal', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Temporal:Historical events', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Historical events', 'exist': True}), ('Temporal:Schedules and timelines', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Schedules and timelines', 'exist': True}), ('Positional', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Positional:Geographical locations', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Geographical locations', 'exist': True}), ('Positional:Spatial data', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Spatial data', 'exist': True}), ('Propositions', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Propositions:Hypotheses and theories', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Hypotheses and theories', 'exist': True}), ('Propositions:Claims and arguments', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Claims and arguments', 'exist': True}), ('Personalization', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Personalization:User preferences', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'User preferences', 'exist': True}), ('Personalization:User information', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'User information', 'exist': True}), ('News Stories', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('News Stories:News stories and blog posts', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'News stories and blog posts', 'exist': True})]\n",
      "\n",
      "Edges in the graph:\n",
      "[('user123', 'Temporal', {'relationship': 'created'}), ('user123', 'Positional', {'relationship': 'created'}), ('user123', 'Propositions', {'relationship': 'created'}), ('user123', 'Personalization', {'relationship': 'created'}), ('user123', 'News Stories', {'relationship': 'created'}), ('Temporal', 'Temporal:Historical events', {'relationship': 'includes'}), ('Temporal', 'Temporal:Schedules and timelines', {'relationship': 'includes'}), ('Positional', 'Positional:Geographical locations', {'relationship': 'includes'}), ('Positional', 'Positional:Spatial data', {'relationship': 'includes'}), ('Propositions', 'Propositions:Hypotheses and theories', {'relationship': 'includes'}), ('Propositions', 'Propositions:Claims and arguments', {'relationship': 'includes'}), ('Personalization', 'Personalization:User preferences', {'relationship': 'includes'}), ('Personalization', 'Personalization:User information', {'relationship': 'includes'}), ('News Stories', 'News Stories:News stories and blog posts', {'relationship': 'includes'})]\n"
     ]
    }
   ],
   "source": [
    "print(\"Nodes in the graph:\")\n",
    "print(G.nodes(data=True))\n",
    "print(\"\\nEdges in the graph:\")\n",
    "print(G.edges(data=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b254dfc9-ce85-4175-9d1e-c0f1ede67e3b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a77b4f24-3046-4ab6-9ba1-c802096498df",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "4dab2ff0-0d12-4a00-a4e4-fb901e701bd3",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'create_user_content_graph' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[50], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m B \u001b[38;5;241m=\u001b[39m \u001b[43mcreate_user_content_graph\u001b[49m(user_id, custom_user_properties, transformed_dict_2, existing_graph\u001b[38;5;241m=\u001b[39mG)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'create_user_content_graph' is not defined"
     ]
    }
   ],
   "source": [
    "# B = create_user_content_graph(user_id, custom_user_properties, transformed_dict_2, existing_graph=G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "627d42fd-d2ce-4ccd-a2a1-2f7ac2f463cf",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'B' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[48], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mB\u001b[49m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'B' is not defined"
     ]
    }
   ],
   "source": [
    "# print(B)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "512f15be-0114-4c8c-9754-e82f2fa16344",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <iframe id=\"2fbfa75d-b567-47be-9749-f57638aef5b9\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=88b5dd9ed5ce46ddac9bec45e2efa3b8&type=arrow&viztoken=7eef4561-b27a-40fe-ad1e-e5280b3d5a29&usertag=1daaf574-pygraphistry-0.33.0&splashAfter=1710005079&info=true\"\n",
       "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
       "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
       "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
       "                    \n",
       "            >\n",
       "            </iframe>\n",
       "        \n",
       "            <script>\n",
       "                try {\n",
       "                  $(\"#2fbfa75d-b567-47be-9749-f57638aef5b9\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
       "                } catch (e) { console.error('exn catching scroll', e); }\n",
       "            </script>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import graphistry\n",
    "import pandas as pd\n",
    "import networkx as nx\n",
    "\n",
    "# Assuming Graphistry is already configured with API key\n",
    "# graphistry.register(api=3, username='your_username', password='your_password')\n",
    "\n",
    "# Convert NetworkX graph to a Pandas DataFrame\n",
    "edges = nx.to_pandas_edgelist(U)\n",
    "graphistry.register(api=3, username='Vasilije1990', password='Q@HLdgv5SMUsGxy') \n",
    "\n",
    "# Visualize the graph\n",
    "graphistry.edges(edges, 'source', 'target').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40866ff1-7c2d-4682-851c-de2442984cd5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3127724-3bef-416e-8631-ba6cea645196",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "fe634bcb-0c00-4a2a-8bcb-687a2fcf847c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def append_data_to_graph(G, category_name, subclass_content,layer_description, new_data, layer_uuid, layer_decomposition_uuid):\n",
    "    # Find the node ID for the subclass within the category\n",
    "    subclass_node_id = None\n",
    "    for node, data in G.nodes(data=True):\n",
    "        if subclass_content in node:\n",
    "            subclass_node_id = node\n",
    "\n",
    "            print(subclass_node_id)\n",
    "\n",
    "    if not subclass_node_id:\n",
    "        print(f\"Subclass '{subclass_content}' under category '{category_name}' not found in the graph.\")\n",
    "        return G\n",
    "\n",
    "    # Mapping from old node IDs to new node IDs\n",
    "    node_id_mapping = {}\n",
    "\n",
    "    # Add nodes from the Pydantic object\n",
    "    for node in new_data.nodes:\n",
    "        unique_node_id =uuid.uuid4()\n",
    "        new_node_id = f\"{node.description} - {str(layer_uuid)}  - {str(layer_decomposition_uuid)} - {str(unique_node_id)}\"\n",
    "        G.add_node(new_node_id, \n",
    "                   created_at=datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\"), \n",
    "                   updated_at=datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\"), \n",
    "                   description=node.description, \n",
    "                   category=node.category, \n",
    "                   memory_type=node.memory_type, \n",
    "                   layer_uuid = str(layer_uuid),\n",
    "                   layer_description = str(layer_description),\n",
    "                   layer_decomposition_uuid = str(layer_decomposition_uuid),\n",
    "                   id = str(unique_node_id),\n",
    "                   type='detail')\n",
    "        G.add_edge(subclass_node_id, new_node_id, relationship='detail')\n",
    "\n",
    "        # Store the mapping from old node ID to new node ID\n",
    "        node_id_mapping[node.id] = new_node_id\n",
    "\n",
    "    # Add edges from the Pydantic object using the new node IDs\n",
    "    for edge in new_data.edges:\n",
    "        # Use the mapping to get the new node IDs\n",
    "        source_node_id = node_id_mapping.get(edge.source)\n",
    "        target_node_id = node_id_mapping.get(edge.target)\n",
    "\n",
    "        if source_node_id and target_node_id:\n",
    "            G.add_edge(source_node_id, target_node_id, description=edge.description, relationship='relation')\n",
    "        else:\n",
    "            print(f\"Could not find mapping for edge from {edge.source} to {edge.target}\")\n",
    "\n",
    "    return G\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "8d6a9eb5-387e-45a3-9dc9-5f8ac36fdd38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'{\"layer\": \"Semantic Layer\"}': KnowledgeGraph(nodes=[Node(id=1, description='Britons have a significant affection for animals and treat pet-keeping as an integral part of life', category='people', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=2, description='Keeping pets is considered a serious and passionate activity in Britain, not merely a leisure activity', category='culturalPractice', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=3, description='Dogs are particularly treasured in Britain and are seen as outlets for emotions and social interaction', category='animal', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=4, description='British society is accommodating of dogs, with public spaces and services being dog-friendly', category='socialNorm', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=5, description='The COVID-19 pandemic caused a surge in pet ownership, particularly dogs, leading to increased numbers and issues like dog attacks', category='event', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=6, description='Pets, especially dogs, are increasingly being treated as commodities and status symbols, with a focus on aesthetic breeds', category='socialIssue', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=7, description='Fashionable dog breeds, such as French bulldogs and American XL bullies, are in high demand regardless of health issues they may face', category='animal', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=8, description='Pets are increasingly treated like substitute children or used to project personal identities', category='socialTrend', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=9, description='Spending on pets in the UK has doubled in the last decade, with a trend towards non-essential luxury items for pets', category='economicTrend', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=10, description='There is a discrepancy between what pets truly need and the human projection of desires onto them', category='animalWelfare', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=11, description='Modern lifestyles can conflict with the needs of pets, leading to behavioral issues and insufficient care', category='animalWelfare', color='blue', memory_type='semantic', created_at=None, summarized=None), Node(id=12, description='The relationship with pets should prioritize their wellbeing and recognize their distinct nature', category='ethicalPrinciple', color='blue', memory_type='semantic', created_at=None, summarized=None)], edges=[Edge(source=1, target=2, description='Britons are known for their serious approach to keeping pets', color='green', created_at=None, summarized=None), Edge(source=2, target=3, description='Dogs are a central part of the pet-keeping practice in Britain', color='green', created_at=None, summarized=None), Edge(source=3, target=4, description='Dogs are widely accepted in public spaces and services due to British social norms', color='green', created_at=None, summarized=None), Edge(source=5, target=6, description='The pandemic surge in pet ownership led to an increase in the commodification of pets', color='green', created_at=None, summarized=None), Edge(source=7, target=6, description='Designer dog breeds are part of the trend of pets being commodified', color='green', created_at=None, summarized=None), Edge(source=9, target=8, description='Increased spending on pet luxuries is related to treating pets as substitutes for children or personal identity projections', color='green', created_at=None, summarized=None), Edge(source=10, target=11, description='The conflict between pet needs and human desires is evident in modern pet care', color='green', created_at=None, summarized=None)])}"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "layer_1_graph[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "7f1cde10-3d83-4800-9ef4-f8eaa39cf772",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<TextSubclass.NEWS_STORIES: 'News stories and blog posts'>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "required_layers_two.dict()['label']['subclass'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "56a062e6-a530-413d-9823-95322e8a825a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import uuid \n",
    "import json\n",
    "def append_to_graph(layer_graphs, required_layers, G):\n",
    "    # Generate a UUID for the overall layer\n",
    "    layer_uuid = uuid.uuid4()\n",
    "    \n",
    "    # Extract category name from required_layers data\n",
    "    category_name = required_layers.dict()['label']['type']\n",
    "\n",
    "    # Extract subgroup name from required_layers data\n",
    "    # Assuming there's always at least one subclass and we're taking the first\n",
    "    subgroup_name = required_layers.dict()['label']['subclass'][0].value  # Access the value of the enum\n",
    "\n",
    "    for layer_ind in layer_graphs:\n",
    "\n",
    "        for layer_json, knowledge_graph in layer_ind.items():\n",
    "            # Decode the JSON key to get the layer description\n",
    "            layer_description = json.loads(layer_json)\n",
    "    \n",
    "            # Generate a UUID for this particular layer decomposition\n",
    "            layer_decomposition_uuid = uuid.uuid4()\n",
    "    \n",
    "            # Assuming append_data_to_graph is defined elsewhere and appends data to G\n",
    "            # You would pass relevant information from knowledge_graph along with other details to this function\n",
    "            F = append_data_to_graph(G, category_name, subgroup_name, layer_description, knowledge_graph, layer_uuid, layer_decomposition_uuid)\n",
    "            \n",
    "            # Print updated graph for verification (assuming F is the updated NetworkX Graph)\n",
    "            print(\"Updated Nodes:\", F.nodes(data=True))\n",
    "\n",
    "    return F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "id": "d6d602c3-f543-4843-af8d-bfa13009f3e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import uuid\n",
    "\n",
    "# def append_to_graph(layer_graphs, required_layers, G):\n",
    "#     layer_uuid = uuid.uuid4()\n",
    "    \n",
    "#     # Directly assign 'NEWS_STORIES' as category_name\n",
    "#     category_name = \"NEWS_STORIES\"\n",
    "    \n",
    "#     # Assuming 'required_layers' structure is as provided, extract 'News stories and blog posts' as the only subgroup\n",
    "#     # This assumes there's always at least one subclass and we're taking the first\n",
    "#     subgroup_name = 'News stories and blog posts'\n",
    "\n",
    "#     for layer_decomposition in layer_graphs:\n",
    "#         print(layer_decomposition)\n",
    "#         layer_decomposition_uuid = uuid.uuid4()\n",
    "\n",
    "#         # Assuming append_data_to_graph is defined elsewhere and appends data to G\n",
    "#         F = append_data_to_graph(G, category_name, subgroup_name, layer_decomposition, layer_uuid, layer_decomposition_uuid)\n",
    "        \n",
    "#         Print updated graph for verification\n",
    "#         print(\"Updated Nodes:\", F.nodes(data=True))  # Assuming F is a NetworkX Graph and you want to print node data\n",
    "\n",
    "#     return F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "66630223-3ba0-4384-95d2-df2995e15271",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def append_to_graph(layer_graphs, required_layers, G):\n",
    "#     layer_uuid = uuid.uuid4()\n",
    "#     category_name = required_layers.dict()['name']\n",
    "#     subgroup_names = [subgroup['name'] for subgroup in required_layers.dict()['cognitive_subgroups']]\n",
    "#     for subgroup in subgroup_names:\n",
    "\n",
    "#         for layer_decomposition in layer_graphs:\n",
    "#             layer_decomposition_uuid = uuid.uuid4()\n",
    "#             F = append_data_to_graph(G, category_name[0], subgroup, layer_decomposition, layer_uuid, layer_decomposition_uuid)\n",
    "            \n",
    "#             # Print updated graph for verification\n",
    "#             # print(\"Updated Nodes:\", F)\n",
    "#     return F\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "89ae9422-e26e-4180-be99-e21bae5229e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LLM_CLASSIFICATION:LAYER:Articles, essays, and reports:Document:doc1\n",
      "Updated Nodes: [('GraphModel:user123', {'id': 'user123', 'user_properties': {'custom_properties': {'age': '30'}, 'location': {'location_id': 'ny', 'description': 'New York', 'default_relationship': {'type': 'located_in', 'properties': None}}}, 'documents': [{'doc_id': 'doc1', 'title': 'Document 1', 'summary': 'Summary of Document 1', 'content_id': 'content_id_for_doc1', 'doc_type': {'type_id': 'PDF', 'description': 'Portable Document Format', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'finance', 'name': 'Finance', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'tech', 'name': 'Technology', 'default_relationship': {'type': 'belongs_to', 'properties': None}}], 'default_relationship': {'type': 'has_document', 'properties': None}}, {'doc_id': 'doc2', 'title': 'Document 2', 'summary': 'Summary of Document 2', 'content_id': 'content_id_for_doc2', 'doc_type': {'type_id': 'TXT', 'description': 'Text File', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'health', 'name': 'Health', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'wellness', 'name': 'Wellness', 'default_relationship': {'type': 'belongs_to', 'properties': None}}], 'default_relationship': {'type': 'has_document', 'properties': None}}], 'default_fields': {'created_at': '2024-03-09 16:57:03', 'updated_at': '2024-03-09 16:57:03'}}), ('UserProperties:default', {'custom_properties': {'age': '30'}, 'location': {'location_id': 'ny', 'description': 'New York', 'default_relationship': {'type': 'located_in', 'properties': None}}}), ('UserLocation:ny', {'location_id': 'ny', 'description': 'New York'}), ('Relationship:default', {'type': 'has_document', 'properties': None}), ('Document:doc1', {'doc_id': 'doc1', 'title': 'Document 1', 'summary': 'Summary of Document 1', 'content_id': 'content_id_for_doc1', 'doc_type': {'type_id': 'PDF', 'description': 'Portable Document Format', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'finance', 'name': 'Finance', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'tech', 'name': 'Technology', 'default_relationship': {'type': 'belongs_to', 'properties': None}}]}), ('DocumentType:PDF', {'type_id': 'PDF', 'description': 'Portable Document Format'}), ('Category:default', {'category_id': 'wellness', 'name': 'Wellness'}), ('Document:doc2', {'doc_id': 'doc2', 'title': 'Document 2', 'summary': 'Summary of Document 2', 'content_id': 'content_id_for_doc2', 'doc_type': {'type_id': 'TXT', 'description': 'Text File', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'health', 'name': 'Health', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'wellness', 'name': 'Wellness', 'default_relationship': {'type': 'belongs_to', 'properties': None}}]}), ('DocumentType:TXT', {'type_id': 'TXT', 'description': 'Text File'}), ('LLM_LAYER_CLASSIFICATION:TEXT:Document:doc1', {'data_type': 'text', 'context_name': 'TEXT', 'layer_name': 'Articles, essays, and reports'}), ('LLM_CLASSIFICATION:LAYER:Articles, essays, and reports:Document:doc1', {'data_type': 'text', 'context_name': 'TEXT', 'layer_name': 'Articles, essays, and reports'}), ('Britons have a significant affection for animals and treat pet-keeping as an integral part of life - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - 357e8b46-d100-43de-914b-997b77bad1ff', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'Britons have a significant affection for animals and treat pet-keeping as an integral part of life', 'category': 'people', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': '357e8b46-d100-43de-914b-997b77bad1ff', 'type': 'detail'}), ('Keeping pets is considered a serious and passionate activity in Britain, not merely a leisure activity - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - 0dbb43df-6c9a-4c77-a1c2-bc90d88cb219', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'Keeping pets is considered a serious and passionate activity in Britain, not merely a leisure activity', 'category': 'culturalPractice', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': '0dbb43df-6c9a-4c77-a1c2-bc90d88cb219', 'type': 'detail'}), ('Dogs are particularly treasured in Britain and are seen as outlets for emotions and social interaction - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - f1832ca3-e4fe-4bb5-8968-40ff827e21c6', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'Dogs are particularly treasured in Britain and are seen as outlets for emotions and social interaction', 'category': 'animal', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': 'f1832ca3-e4fe-4bb5-8968-40ff827e21c6', 'type': 'detail'}), ('British society is accommodating of dogs, with public spaces and services being dog-friendly - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - 41e0def6-6416-4b4e-bc00-94c56b487476', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'British society is accommodating of dogs, with public spaces and services being dog-friendly', 'category': 'socialNorm', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': '41e0def6-6416-4b4e-bc00-94c56b487476', 'type': 'detail'}), ('The COVID-19 pandemic caused a surge in pet ownership, particularly dogs, leading to increased numbers and issues like dog attacks - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - 7858704b-bee4-474f-8a9c-d40bed669e34', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'The COVID-19 pandemic caused a surge in pet ownership, particularly dogs, leading to increased numbers and issues like dog attacks', 'category': 'event', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': '7858704b-bee4-474f-8a9c-d40bed669e34', 'type': 'detail'}), ('Pets, especially dogs, are increasingly being treated as commodities and status symbols, with a focus on aesthetic breeds - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - 7b858921-60a3-4e9d-9a5f-265fa7fd6f2c', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'Pets, especially dogs, are increasingly being treated as commodities and status symbols, with a focus on aesthetic breeds', 'category': 'socialIssue', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': '7b858921-60a3-4e9d-9a5f-265fa7fd6f2c', 'type': 'detail'}), ('Fashionable dog breeds, such as French bulldogs and American XL bullies, are in high demand regardless of health issues they may face - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - f8ad99cd-c53f-45a0-b2f8-b229cf08ca24', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'Fashionable dog breeds, such as French bulldogs and American XL bullies, are in high demand regardless of health issues they may face', 'category': 'animal', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': 'f8ad99cd-c53f-45a0-b2f8-b229cf08ca24', 'type': 'detail'}), ('Pets are increasingly treated like substitute children or used to project personal identities - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - 9633980e-c85e-4047-8648-ce3b38ea2724', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'Pets are increasingly treated like substitute children or used to project personal identities', 'category': 'socialTrend', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': '9633980e-c85e-4047-8648-ce3b38ea2724', 'type': 'detail'}), ('Spending on pets in the UK has doubled in the last decade, with a trend towards non-essential luxury items for pets - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - e47bd33c-3b82-4264-b817-f989d509ac04', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'Spending on pets in the UK has doubled in the last decade, with a trend towards non-essential luxury items for pets', 'category': 'economicTrend', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': 'e47bd33c-3b82-4264-b817-f989d509ac04', 'type': 'detail'}), ('There is a discrepancy between what pets truly need and the human projection of desires onto them - b7eec528-c804-4bfd-acf4-1642b20d1f5b  - ea735e18-aa21-46c9-9dad-56212f575fd7 - e336492a-09c2-4275-a6b5-66b5cae4677d', {'created_at': '2024-03-09 18:31:23', 'updated_at': '2024-03-09 18:31:23', 'description': 'There is a discrepancy between what pets truly need and the human projection of desires onto them', 'category': 'animalWelfare', 'memory_type': 'semantic', 'layer_uuid': 'b7eec528-c804-4bfd-acf4-1642b20d1f5b', 'layer_description': \"{'layer': 'Semantic Layer'}\", 'layer_decomposition_uuid': 'ea735e18-aa21-46c9-9dad-56212f575fd7', 'id': 'e336492a-09c2-4275-a6b5-66b5cae4677d', 'type': 'detail'}), ('Modern lifestyles can conflict with the needs of pets, leading to behavioral issues and insufficient care - 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      "LLM_CLASSIFICATION:LAYER:Articles, essays, and reports:Document:doc1\n",
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     ]
    }
   ],
   "source": [
    "\n",
    "T = append_to_graph(layer_1_graph, required_layers_one, U)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "c7dd7e00-d0ff-4f5c-a82e-3f1ea05840be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'label': {'type': 'TEXT',\n",
       "  'subclass': [<TextSubclass.NEWS_STORIES: 'News stories and blog posts'>]}}"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "required_layers_one.dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b15feb48-6c19-4b18-81d8-d28651ea63f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "News Stories:News stories and blog posts\n",
      "Updated Nodes: [('user123', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'username': 'exampleUser', 'email': 'user@example.com', 'exist': True}), ('Temporal', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Temporal:Historical events', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Historical events', 'exist': True}), ('Temporal:Schedules and timelines', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Schedules and timelines', 'exist': True}), ('Positional', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Positional:Geographical locations', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Geographical locations', 'exist': True}), ('Positional:Spatial data', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Spatial data', 'exist': True}), ('Propositions', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Propositions:Hypotheses and theories', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Hypotheses and theories', 'exist': True}), ('Propositions:Claims and arguments', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'Claims and arguments', 'exist': True}), ('Personalization', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('Personalization:User preferences', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'User preferences', 'exist': True}), ('Personalization:User information', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'User information', 'exist': True}), ('News Stories', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'category', 'exist': True}), ('News Stories:News stories and blog posts', {'created_at': '2024-03-08 14:41:03', 'updated_at': '2024-03-08 14:41:03', 'type': 'subclass', 'content': 'News stories and blog posts', 'exist': True}), ('Britons have always been a bit silly about animals, particularly dogs. - 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5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 39f53999-53f1-43b2-8d4a-28f5f4872e3c', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The number of dog attacks recorded by police in England and Wales has increased by over a third between 2018 and 2022.', 'category': 'event', 'memory_type': 'episodic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '39f53999-53f1-43b2-8d4a-28f5f4872e3c', 'type': 'detail'}), ('Pets4Homes.co.uk is a site with listings for dogs that owners can no longer keep post-lockdown. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - a4c2bab4-905e-4b94-9a8f-959e102f1e2c', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Pets4Homes.co.uk is a site with listings for dogs that owners can no longer keep post-lockdown.', 'category': 'website', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': 'a4c2bab4-905e-4b94-9a8f-959e102f1e2c', 'type': 'detail'}), ('Designer dog breeds like French bulldogs and pugs are fashionable but may live with discomfort due to breeding for aesthetic appeal. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 65a501eb-ba51-41d0-b8f5-bea04be36811', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Designer dog breeds like French bulldogs and pugs are fashionable but may live with discomfort due to breeding for aesthetic appeal.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '65a501eb-ba51-41d0-b8f5-bea04be36811', 'type': 'detail'}), ('American XL bully dogs are controversial and often sought after as a signifier of masculinity. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 4d3a81ab-dbb7-4f52-b6e6-76c778208bf0', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'American XL bully dogs are controversial and often sought after as a signifier of masculinity.', 'category': 'animal', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '4d3a81ab-dbb7-4f52-b6e6-76c778208bf0', 'type': 'detail'}), ('The total spend on pets in the UK has more than doubled in the past decade, reaching nearly £10bn in the last year. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 8f61e1e5-48fa-4fa7-9bb6-2bc2945c9c41', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The total spend on pets in the UK has more than doubled in the past decade, reaching nearly £10bn in the last year.', 'category': 'economicActivity', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '8f61e1e5-48fa-4fa7-9bb6-2bc2945c9c41', 'type': 'detail'}), ('The presence of pet boutiques and dog-friendly businesses like restaurants and cinemas is increasingly common in the UK. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - fd225af9-2e75-4f0e-8a9c-905584c71e1f', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The presence of pet boutiques and dog-friendly businesses like restaurants and cinemas is increasingly common in the UK.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': 'fd225af9-2e75-4f0e-8a9c-905584c71e1f', 'type': 'detail'}), ('Many dogs in modern society suffer from behavioral problems due to insufficient exercise, supervision, and consistent routines. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - d88342cd-5f27-421e-923d-a005ca15736b', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Many dogs in modern society suffer from behavioral problems due to insufficient exercise, supervision, and consistent routines.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': 'd88342cd-5f27-421e-923d-a005ca15736b', 'type': 'detail'}), ('A significant number of pet owners in the UK buy trendy non-essential items for their pets, such as grooming services, outfits, and treats. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 168af846-5e23-4ac2-8d57-f0a048b6898d', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'A significant number of pet owners in the UK buy trendy non-essential items for their pets, such as grooming services, outfits, and treats.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '168af846-5e23-4ac2-8d57-f0a048b6898d', 'type': 'detail'}), ('Dogs are social animals and keeping them isolated or in small spaces for long periods is against their nature and can lead to behavior issues. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - eb692cd1-42c8-4f27-bcf8-98f484592d65', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Dogs are social animals and keeping them isolated or in small spaces for long periods is against their nature and can lead to behavior issues.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': 'eb692cd1-42c8-4f27-bcf8-98f484592d65', 'type': 'detail'}), ('Britons have a significant attachment to pets - 5d03159e-6486-41da-a908-2db49a7d61d1  - ed602834-9712-4ee6-b8e6-8cc2be19a0c0 - a58be3ed-49cc-4dfd-b01f-1a97d40cf1d8', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Britons have a significant attachment to pets', 'category': 'sentiment', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'ed602834-9712-4ee6-b8e6-8cc2be19a0c0', 'id': 'a58be3ed-49cc-4dfd-b01f-1a97d40cf1d8', 'type': 'detail'}), ('Pets serve as an emotional outlet for Britons - 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5d03159e-6486-41da-a908-2db49a7d61d1  - ed602834-9712-4ee6-b8e6-8cc2be19a0c0 - deabcde1-da02-4896-ad05-9ac40d372d33', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The human-dog relationship is deteriorating', 'category': 'sentiment', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'ed602834-9712-4ee6-b8e6-8cc2be19a0c0', 'id': 'deabcde1-da02-4896-ad05-9ac40d372d33', 'type': 'detail'}), ('Increasing consumerism in the treatment of pets - 5d03159e-6486-41da-a908-2db49a7d61d1  - ed602834-9712-4ee6-b8e6-8cc2be19a0c0 - b0a337b6-a1b6-4055-a25c-e67da2d958f0', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Increasing consumerism in the treatment of pets', 'category': 'sentiment', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'ed602834-9712-4ee6-b8e6-8cc2be19a0c0', 'id': 'b0a337b6-a1b6-4055-a25c-e67da2d958f0', 'type': 'detail'}), ('Pets are being commodified - 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5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 8f61e1e5-48fa-4fa7-9bb6-2bc2945c9c41', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The total spend on pets in the UK has more than doubled in the past decade, reaching nearly £10bn in the last year.', 'category': 'economicActivity', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '8f61e1e5-48fa-4fa7-9bb6-2bc2945c9c41', 'type': 'detail'}), ('The presence of pet boutiques and dog-friendly businesses like restaurants and cinemas is increasingly common in the UK. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - fd225af9-2e75-4f0e-8a9c-905584c71e1f', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The presence of pet boutiques and dog-friendly businesses like restaurants and cinemas is increasingly common in the UK.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': 'fd225af9-2e75-4f0e-8a9c-905584c71e1f', 'type': 'detail'}), ('Many dogs in modern society suffer from behavioral problems due to insufficient exercise, supervision, and consistent routines. - 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5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 39f53999-53f1-43b2-8d4a-28f5f4872e3c', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The number of dog attacks recorded by police in England and Wales has increased by over a third between 2018 and 2022.', 'category': 'event', 'memory_type': 'episodic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '39f53999-53f1-43b2-8d4a-28f5f4872e3c', 'type': 'detail'}), ('Pets4Homes.co.uk is a site with listings for dogs that owners can no longer keep post-lockdown. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - a4c2bab4-905e-4b94-9a8f-959e102f1e2c', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Pets4Homes.co.uk is a site with listings for dogs that owners can no longer keep post-lockdown.', 'category': 'website', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': 'a4c2bab4-905e-4b94-9a8f-959e102f1e2c', 'type': 'detail'}), ('Designer dog breeds like French bulldogs and pugs are fashionable but may live with discomfort due to breeding for aesthetic appeal. - 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5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - 8f61e1e5-48fa-4fa7-9bb6-2bc2945c9c41', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The total spend on pets in the UK has more than doubled in the past decade, reaching nearly £10bn in the last year.', 'category': 'economicActivity', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': '8f61e1e5-48fa-4fa7-9bb6-2bc2945c9c41', 'type': 'detail'}), ('The presence of pet boutiques and dog-friendly businesses like restaurants and cinemas is increasingly common in the UK. - 5d03159e-6486-41da-a908-2db49a7d61d1  - d2792828-97ee-4874-a75b-6cfa351bb94f - fd225af9-2e75-4f0e-8a9c-905584c71e1f', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The presence of pet boutiques and dog-friendly businesses like restaurants and cinemas is increasingly common in the UK.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': 'd2792828-97ee-4874-a75b-6cfa351bb94f', 'id': 'fd225af9-2e75-4f0e-8a9c-905584c71e1f', 'type': 'detail'}), ('Many dogs in modern society suffer from behavioral problems due to insufficient exercise, supervision, and consistent routines. - 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5d03159e-6486-41da-a908-2db49a7d61d1  - 9558903a-a3a7-42d8-896a-8561ac245e64 - 55d64518-4af3-4cd8-9a98-4720d2f150b9', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'American XL bully dogs are controversial breeds sometimes used as masculinity signifiers.', 'category': 'animal', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': '9558903a-a3a7-42d8-896a-8561ac245e64', 'id': '55d64518-4af3-4cd8-9a98-4720d2f150b9', 'type': 'detail'}), ('There is a cultural shift towards treating pets as child substitutes rather than appreciating their natural traits. - 5d03159e-6486-41da-a908-2db49a7d61d1  - 9558903a-a3a7-42d8-896a-8561ac245e64 - 24ab91c6-1afb-4324-bad0-0c726ba15346', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'There is a cultural shift towards treating pets as child substitutes rather than appreciating their natural traits.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': '9558903a-a3a7-42d8-896a-8561ac245e64', 'id': '24ab91c6-1afb-4324-bad0-0c726ba15346', 'type': 'detail'}), ('Expenditure on pets in the UK has greatly increased, with a trend towards non-essential pet indulgences. - 5d03159e-6486-41da-a908-2db49a7d61d1  - 9558903a-a3a7-42d8-896a-8561ac245e64 - b037d6f3-9e6b-48e2-8a00-ff85b1ead9af', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Expenditure on pets in the UK has greatly increased, with a trend towards non-essential pet indulgences.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': '9558903a-a3a7-42d8-896a-8561ac245e64', 'id': 'b037d6f3-9e6b-48e2-8a00-ff85b1ead9af', 'type': 'detail'}), ('Pet boutiques selling luxury pet products have become a sign of gentrification and consumerism in pet care. - 5d03159e-6486-41da-a908-2db49a7d61d1  - 9558903a-a3a7-42d8-896a-8561ac245e64 - 3898e563-2af2-4a84-bfa2-d883434d78c0', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'Pet boutiques selling luxury pet products have become a sign of gentrification and consumerism in pet care.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': '9558903a-a3a7-42d8-896a-8561ac245e64', 'id': '3898e563-2af2-4a84-bfa2-d883434d78c0', 'type': 'detail'}), (\"The rise of dog-friendly services and products often cater more to owners' preferences than dogs' wellbeing. - 5d03159e-6486-41da-a908-2db49a7d61d1  - 9558903a-a3a7-42d8-896a-8561ac245e64 - 781ba06c-589c-4b3c-9c22-06e3507384e3\", {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': \"The rise of dog-friendly services and products often cater more to owners' preferences than dogs' wellbeing.\", 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': '9558903a-a3a7-42d8-896a-8561ac245e64', 'id': '781ba06c-589c-4b3c-9c22-06e3507384e3', 'type': 'detail'}), ('The humanization of pets leads to strange, unsatisfactory lives for dogs, deviating from their natural needs. - 5d03159e-6486-41da-a908-2db49a7d61d1  - 9558903a-a3a7-42d8-896a-8561ac245e64 - 70d9e255-ea5c-4f68-841c-47875f0d0cff', {'created_at': '2024-03-08 14:58:52', 'updated_at': '2024-03-08 14:58:52', 'description': 'The humanization of pets leads to strange, unsatisfactory lives for dogs, deviating from their natural needs.', 'category': 'concept', 'memory_type': 'semantic', 'layer_uuid': '5d03159e-6486-41da-a908-2db49a7d61d1', 'layer_decomposition_uuid': '9558903a-a3a7-42d8-896a-8561ac245e64', 'id': '70d9e255-ea5c-4f68-841c-47875f0d0cff', 'type': 'detail'})]\n"
     ]
    }
   ],
   "source": [
    "R = append_to_graph(layer_2_graph, required_layers_two, U)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "17199837-35b8-4530-bf03-efbc3486b71d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <iframe id=\"39e0be4a-a521-4888-bd97-7214bfdff1ed\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=4d08a6541c01413c9b0315b3e5624d86&type=arrow&viztoken=2c4759ed-98fc-4c09-846e-7b6958d63320&usertag=1daaf574-pygraphistry-0.33.0&splashAfter=1709906350&info=true\"\n",
       "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
       "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
       "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
       "                    \n",
       "            >\n",
       "            </iframe>\n",
       "        \n",
       "            <script>\n",
       "                try {\n",
       "                  $(\"#39e0be4a-a521-4888-bd97-7214bfdff1ed\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
       "                } catch (e) { console.error('exn catching scroll', e); }\n",
       "            </script>\n",
       "        "
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       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import graphistry\n",
    "import pandas as pd\n",
    "\n",
    "# Assuming Graphistry is already configured with API key\n",
    "# graphistry.register(api=3, username='your_username', password='your_password')\n",
    "\n",
    "# Convert NetworkX graph to a Pandas DataFrame\n",
    "edges = nx.to_pandas_edgelist(R)\n",
    "graphistry.register(api=3, username='Vasilije1990', password='Q@HLdgv5SMUsGxy') \n",
    "\n",
    "# Visualize the graph\n",
    "graphistry.edges(edges, 'source', 'target').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "id": "187f4220-45b1-43cc-9ab3-1e51264544c5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f17dc174-f325-44b9-8fc7-761146aca2d0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e4eee8a7-5d3b-4848-9cdb-2b397e158519",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Utility to check if relationships are as they should be"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3adc8483-3207-44f1-abf5-275e925e04d4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Graph Relationships with Node Attributes:\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, username: exampleUser, email: user@example.com] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category]: Relationship [created]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, username: exampleUser, email: user@example.com] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category]: Relationship [created]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, username: exampleUser, email: user@example.com] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category]: Relationship [created]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, username: exampleUser, email: user@example.com] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category]: Relationship [created]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, username: exampleUser, email: user@example.com] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category]: Relationship [created]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Historical events]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Schedules and timelines]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Geographical locations]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Spatial data]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Hypotheses and theories]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Claims and arguments]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: User preferences]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: User information]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: category] -> Target [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories]: Relationship [includes]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: For Britons, keeping pets is an entire way of life., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: d443269f-44ff-4c10-ab4a-fab9ead0f904, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Pets, especially dogs, serve as outlets for emotions and social interaction within controlled social norms., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 2d588b35-062e-44e7-bbb2-1642ba0411e3, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Dogs are encouraged and welcomed in public spaces such as pubs, shops, and public transport., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 6a34c9bd-0dee-4db0-8258-86d2dd87303d, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The rise in pet ownership and the desire for designer breeds can lead to negative outcomes for animal welfare., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 630b58dd-65f6-4d55-b3fc-67b59d696b4c, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The COVID-19 pandemic saw a surge in pet ownership, leading to growing concerns about pet abandonment and the treatment of pets as commodities., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 54db7b9e-5f2f-4287-9185-7214eb8f0ccd, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Ownership of certain dog breeds is seen as a status symbol and a reflection of owner's identity., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 53b9fc97-7c9e-46f1-ab2c-741405fa12ac, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: An increase in spending on non-essential pet products and services reflects a shift in how pets are viewed and treated., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: e221c461-f9c1-4d99-9ae5-25299b6e0516, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Britons use pets, especially dogs, as an emotional outlet for affection and social interaction., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 9dce0831-6e87-4fd9-93ba-e6944b22929b, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Pets in Britain are often treated as substitutes for children and valued for aesthetics, leading to questionable breeding practices., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: f800260d-6de1-4a5f-a501-f5d58f3258c3, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: During the pandemic, the number of pet dogs in the UK rose from about nine million to 13 million, leading to issues such as increased dog attacks., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: d4beb707-c19e-45fc-8fa9-387e4410282f, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The COVID-19 pandemic led to a surge in pet ownership as people stayed home, but many pets are being rehomed as life returns to normal., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 2f3e9b5f-17bf-4346-9cfc-104fdd467ff9, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The rise in spending on non-essential pet items, like grooming and outfits, reflects a change in how Britons care for their pets., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: a75bae98-0748-4c4d-b807-5d3e19a9d638, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The shift from working at home to returning to the workplace has resulted in lifestyle changes not suitable for pet ownership., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 446383f7-ebbd-4ca1-891f-f0294bb11782, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Many dogs develop behavioral problems due to lack of exercise, supervision, and consistent routines, exacerbated by their owners' busy schedules., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 28368449-6e7a-4dd5-89fb-7dac13995c63, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Concerns over the welfare of animals, especially dogs, in British society, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 0caf3fc9-0ad7-4012-b278-89335518e5fe, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The culture of pet ownership in Britain, with a focus on dogs being part of lifestyle and an outlet for emotions, category: culturalAspect, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 1f26c212-a164-49f5-8029-c7a36519ef41, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Increase in the number of pet dogs in the UK from about 9 million to 13 million between 2019 and 2022, category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: b55e1f62-4294-456f-b42f-3283e3cb5a46, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Challenges faced by 'pandemic dogs' as they enter adolescence and owners return to offices, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 2ff11ce2-c8d9-45cd-aadb-e6875fb98708, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Rise in dog attacks recorded by police in England and Wales by more than a third between 2018 and 2022, category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 67cba62f-e3ae-4db8-8c6e-b7be5e6149cb, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Re-homing of dogs post lockdown as owners' lifestyles change and the pandemic ends, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: ec1f580b-fadd-48bc-bf70-558cb6a2df05, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The trend of treating living beings, particularly dogs, as commodities rather than sentient beings, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 4dd3cb46-ca57-46ca-9781-e8b917491720, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Health problems associated with 'designer' dog breeds like French bulldogs and pugs, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 8d2c705d-f257-4611-8baa-d73f37c77bbb, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The use of certain dog breeds as status symbols, particularly regarding masculinity, category: socialAspect, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 7ee6f0a7-cf4a-4659-a886-1f0b40d75b97, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: A shift in pet ownership where pets are increasingly being treated as substitutes for children, category: trend, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: bce65459-262a-4a6b-a319-5deb8e6d0d96, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The growth of the pet industry in the UK, with spending reaching nearly £10bn, category: industry, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 4343ab14-2ab3-4e94-b25c-cf1efe8b81c6, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Rising consumerism in pet ownership, with pets being indulged with non-essential items and services, category: trend, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 48d756f6-2b24-4f43-950e-c4670d14c8c4, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Articles, essays, and reports] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The negative impact of busy modern lifestyles on dog welfare, leading to behavioral problems, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 737bce65-bb12-4d3e-ad1e-ecd756e1e842, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0025c486-d9eb-4820-9b95-f48a97c51d9b, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 1531d1cb-3f68-46d7-a366-48d19f26bc93, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 2b18da1f-bd6f-49a6-b058-0387898dc5dc, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 5fddebc9-5092-46b6-9fa3-8c6170eb2e16, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0d22c2e8-a39b-4c71-abe6-88a90cdfd65d, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 58b37c6f-1574-4b93-8ee5-16a22f01aa41, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: c7bea689-6862-482a-b156-4fc1be3fa07f, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 69dea290-4f26-495f-b6df-c994d6de5f69, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0f371d44-7362-434d-843f-813add8f25c6, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 49ab2d1b-9163-485f-81c8-8667fc707554, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 3a6f81c3-ecdc-483e-88dd-59068ae332b1, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 5560940a-8504-40bc-94d4-71aa399af5ab, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: ff3446b4-59ea-4ef9-969a-4afac7706aa6, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 9872ba50-8783-49b4-8fc4-9c53aae7cf57, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, a 50-year-old man, owner of Izzy., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 18b461fc-af3d-4e67-8cdb-3a02eb42192c, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross owned by Lee Parkin., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 3a63bd68-0238-4865-9ea1-d7f88f58d6e8, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: XL bully, a type of dog that attacked Izzy and Naevia., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: b168a539-5398-4588-b4a4-6963c73b5526, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay, owner of a Siberian Husky named Naevia., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 99675528-5a7f-4941-b378-87b03e151cf4, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a seven-year-old Siberian Husky owned by Marie Hay., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 6ebecd15-37bd-4553-9c33-89df1fea543c, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 90cde4a1-7b75-4e61-844f-5a5f5e602690, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: News stories and blog posts] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: f866a9f5-3b89-418e-a94b-37923e0c4982, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 15d3a8af-4e1a-4c3f-9d29-9c46723fd03a, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b507af42-4ef7-4cb6-8df1-236d9abc4832, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 3a47799d-afa6-4ff0-b34b-627c81e46059, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b0a798cb-39c3-4cab-a67c-778bc4e2df21, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: c61a5496-bb75-445c-9ae4-a4cca37cd794, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: e0a882a8-f8b1-4a9f-b154-fa061eaa684b, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b086b7b2-daf2-47f2-9a1e-35812afd9313, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 1b10518f-3973-4f79-9dab-3ef238c2cbaa, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 59cca039-7f8b-4da5-b67d-51ac14e7c74c, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: 7c87ffb5-0359-4421-8e03-61457119ca4b, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: f38b0084-b074-4e47-ae66-cccb9827a87f, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: a942b1b8-7ff2-4177-83ef-022bb69affac, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: 88635a41-2a86-4bcc-bd34-affe7e302208, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: 13374d73-bb3b-4e2f-8a94-ff90f0056970, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, a 50-year-old man, owner of Izzy., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 504729be-4ffc-493a-9cc8-1ae4ffc799e1, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross owned by Lee Parkin., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 517b7476-e446-4986-8445-0a2cb14e543f, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: XL bully, a type of dog that attacked Izzy and Naevia., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 13a45934-879a-4fe4-90e9-0a5277e56297, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay, owner of a Siberian Husky named Naevia., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 3fce46e3-8006-4940-bc47-e011408f663c, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a seven-year-old Siberian Husky owned by Marie Hay., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 939465bc-c763-4122-9328-984c5c59f712, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 3cc5365b-b9e7-46d7-81c8-e125af634e32, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:16:14, updated_at: 2024-03-04 20:16:14, type: subclass, content: Personal narratives and stories] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 4aa02775-42e7-41d5-b91f-1f8a764657ed, type: detail]: Relationship [detail]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: For Britons, keeping pets is an entire way of life., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: d443269f-44ff-4c10-ab4a-fab9ead0f904, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Pets, especially dogs, serve as outlets for emotions and social interaction within controlled social norms., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 2d588b35-062e-44e7-bbb2-1642ba0411e3, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: For Britons, keeping pets is an entire way of life., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: d443269f-44ff-4c10-ab4a-fab9ead0f904, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The COVID-19 pandemic saw a surge in pet ownership, leading to growing concerns about pet abandonment and the treatment of pets as commodities., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 54db7b9e-5f2f-4287-9185-7214eb8f0ccd, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Pets, especially dogs, serve as outlets for emotions and social interaction within controlled social norms., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 2d588b35-062e-44e7-bbb2-1642ba0411e3, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Dogs are encouraged and welcomed in public spaces such as pubs, shops, and public transport., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 6a34c9bd-0dee-4db0-8258-86d2dd87303d, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The COVID-19 pandemic saw a surge in pet ownership, leading to growing concerns about pet abandonment and the treatment of pets as commodities., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 54db7b9e-5f2f-4287-9185-7214eb8f0ccd, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The rise in pet ownership and the desire for designer breeds can lead to negative outcomes for animal welfare., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 630b58dd-65f6-4d55-b3fc-67b59d696b4c, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Ownership of certain dog breeds is seen as a status symbol and a reflection of owner's identity., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 53b9fc97-7c9e-46f1-ab2c-741405fa12ac, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The rise in pet ownership and the desire for designer breeds can lead to negative outcomes for animal welfare., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 630b58dd-65f6-4d55-b3fc-67b59d696b4c, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: An increase in spending on non-essential pet products and services reflects a shift in how pets are viewed and treated., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: e221c461-f9c1-4d99-9ae5-25299b6e0516, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The COVID-19 pandemic saw a surge in pet ownership, leading to growing concerns about pet abandonment and the treatment of pets as commodities., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 54db7b9e-5f2f-4287-9185-7214eb8f0ccd, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: An increase in spending on non-essential pet products and services reflects a shift in how pets are viewed and treated., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: e221c461-f9c1-4d99-9ae5-25299b6e0516, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The rise in pet ownership and the desire for designer breeds can lead to negative outcomes for animal welfare., category: cultural norms, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: 67200cb4-16fc-40f9-b231-c9e720aeb14a, id: 630b58dd-65f6-4d55-b3fc-67b59d696b4c, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Britons use pets, especially dogs, as an emotional outlet for affection and social interaction., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 9dce0831-6e87-4fd9-93ba-e6944b22929b, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Pets in Britain are often treated as substitutes for children and valued for aesthetics, leading to questionable breeding practices., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: f800260d-6de1-4a5f-a501-f5d58f3258c3, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Britons use pets, especially dogs, as an emotional outlet for affection and social interaction., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 9dce0831-6e87-4fd9-93ba-e6944b22929b, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The rise in spending on non-essential pet items, like grooming and outfits, reflects a change in how Britons care for their pets., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: a75bae98-0748-4c4d-b807-5d3e19a9d638, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: During the pandemic, the number of pet dogs in the UK rose from about nine million to 13 million, leading to issues such as increased dog attacks., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: d4beb707-c19e-45fc-8fa9-387e4410282f, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The COVID-19 pandemic led to a surge in pet ownership as people stayed home, but many pets are being rehomed as life returns to normal., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 2f3e9b5f-17bf-4346-9cfc-104fdd467ff9, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The COVID-19 pandemic led to a surge in pet ownership as people stayed home, but many pets are being rehomed as life returns to normal., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 2f3e9b5f-17bf-4346-9cfc-104fdd467ff9, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The shift from working at home to returning to the workplace has resulted in lifestyle changes not suitable for pet ownership., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 446383f7-ebbd-4ca1-891f-f0294bb11782, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The shift from working at home to returning to the workplace has resulted in lifestyle changes not suitable for pet ownership., category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 446383f7-ebbd-4ca1-891f-f0294bb11782, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Many dogs develop behavioral problems due to lack of exercise, supervision, and consistent routines, exacerbated by their owners' busy schedules., category: concept, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: ccf6645e-9fad-441b-821d-b1d47b93ebca, id: 28368449-6e7a-4dd5-89fb-7dac13995c63, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The culture of pet ownership in Britain, with a focus on dogs being part of lifestyle and an outlet for emotions, category: culturalAspect, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 1f26c212-a164-49f5-8029-c7a36519ef41, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Concerns over the welfare of animals, especially dogs, in British society, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 0caf3fc9-0ad7-4012-b278-89335518e5fe, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Increase in the number of pet dogs in the UK from about 9 million to 13 million between 2019 and 2022, category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: b55e1f62-4294-456f-b42f-3283e3cb5a46, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Challenges faced by 'pandemic dogs' as they enter adolescence and owners return to offices, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 2ff11ce2-c8d9-45cd-aadb-e6875fb98708, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Challenges faced by 'pandemic dogs' as they enter adolescence and owners return to offices, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 2ff11ce2-c8d9-45cd-aadb-e6875fb98708, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Rise in dog attacks recorded by police in England and Wales by more than a third between 2018 and 2022, category: event, memory_type: episodic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 67cba62f-e3ae-4db8-8c6e-b7be5e6149cb, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Re-homing of dogs post lockdown as owners' lifestyles change and the pandemic ends, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: ec1f580b-fadd-48bc-bf70-558cb6a2df05, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The trend of treating living beings, particularly dogs, as commodities rather than sentient beings, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 4dd3cb46-ca57-46ca-9781-e8b917491720, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Health problems associated with 'designer' dog breeds like French bulldogs and pugs, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 8d2c705d-f257-4611-8baa-d73f37c77bbb, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The trend of treating living beings, particularly dogs, as commodities rather than sentient beings, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 4dd3cb46-ca57-46ca-9781-e8b917491720, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The use of certain dog breeds as status symbols, particularly regarding masculinity, category: socialAspect, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 7ee6f0a7-cf4a-4659-a886-1f0b40d75b97, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The trend of treating living beings, particularly dogs, as commodities rather than sentient beings, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 4dd3cb46-ca57-46ca-9781-e8b917491720, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: A shift in pet ownership where pets are increasingly being treated as substitutes for children, category: trend, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: bce65459-262a-4a6b-a319-5deb8e6d0d96, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Rising consumerism in pet ownership, with pets being indulged with non-essential items and services, category: trend, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 48d756f6-2b24-4f43-950e-c4670d14c8c4, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The growth of the pet industry in the UK, with spending reaching nearly £10bn, category: industry, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 4343ab14-2ab3-4e94-b25c-cf1efe8b81c6, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Rising consumerism in pet ownership, with pets being indulged with non-essential items and services, category: trend, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 48d756f6-2b24-4f43-950e-c4670d14c8c4, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: Rising consumerism in pet ownership, with pets being indulged with non-essential items and services, category: trend, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 48d756f6-2b24-4f43-950e-c4670d14c8c4, type: detail] -> Target [created_at: 2024-03-04 20:28:36, updated_at: 2024-03-04 20:28:36, description: The negative impact of busy modern lifestyles on dog welfare, leading to behavioral problems, category: issue, memory_type: semantic, layer_uuid: 66009783-f985-47e5-9553-d60573e7cc33, layer_decomposition_uuid: d0c2bd1c-7cec-4e5a-af13-dbb655623dda, id: 737bce65-bb12-4d3e-ad1e-ecd756e1e842, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0025c486-d9eb-4820-9b95-f48a97c51d9b, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 1531d1cb-3f68-46d7-a366-48d19f26bc93, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0025c486-d9eb-4820-9b95-f48a97c51d9b, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 2b18da1f-bd6f-49a6-b058-0387898dc5dc, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 1531d1cb-3f68-46d7-a366-48d19f26bc93, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 2b18da1f-bd6f-49a6-b058-0387898dc5dc, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 2b18da1f-bd6f-49a6-b058-0387898dc5dc, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 5fddebc9-5092-46b6-9fa3-8c6170eb2e16, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 2b18da1f-bd6f-49a6-b058-0387898dc5dc, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0d22c2e8-a39b-4c71-abe6-88a90cdfd65d, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0d22c2e8-a39b-4c71-abe6-88a90cdfd65d, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 5fddebc9-5092-46b6-9fa3-8c6170eb2e16, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0d22c2e8-a39b-4c71-abe6-88a90cdfd65d, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0f371d44-7362-434d-843f-813add8f25c6, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 58b37c6f-1574-4b93-8ee5-16a22f01aa41, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: c7bea689-6862-482a-b156-4fc1be3fa07f, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 58b37c6f-1574-4b93-8ee5-16a22f01aa41, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 69dea290-4f26-495f-b6df-c994d6de5f69, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: c7bea689-6862-482a-b156-4fc1be3fa07f, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 69dea290-4f26-495f-b6df-c994d6de5f69, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 69dea290-4f26-495f-b6df-c994d6de5f69, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 83b60dcf-0a04-474f-962b-121cc518e610, id: 0f371d44-7362-434d-843f-813add8f25c6, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 49ab2d1b-9163-485f-81c8-8667fc707554, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 3a6f81c3-ecdc-483e-88dd-59068ae332b1, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 5560940a-8504-40bc-94d4-71aa399af5ab, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 3a6f81c3-ecdc-483e-88dd-59068ae332b1, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 5560940a-8504-40bc-94d4-71aa399af5ab, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 9872ba50-8783-49b4-8fc4-9c53aae7cf57, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: ff3446b4-59ea-4ef9-969a-4afac7706aa6, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 6fb85c94-f488-4f31-8e7c-a5905580a78c, id: 9872ba50-8783-49b4-8fc4-9c53aae7cf57, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, a 50-year-old man, owner of Izzy., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 18b461fc-af3d-4e67-8cdb-3a02eb42192c, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross owned by Lee Parkin., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 3a63bd68-0238-4865-9ea1-d7f88f58d6e8, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross owned by Lee Parkin., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 3a63bd68-0238-4865-9ea1-d7f88f58d6e8, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 90cde4a1-7b75-4e61-844f-5a5f5e602690, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a seven-year-old Siberian Husky owned by Marie Hay., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: 6ebecd15-37bd-4553-9c33-89df1fea543c, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f, id: f866a9f5-3b89-418e-a94b-37923e0c4982, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 15d3a8af-4e1a-4c3f-9d29-9c46723fd03a, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b507af42-4ef7-4cb6-8df1-236d9abc4832, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 15d3a8af-4e1a-4c3f-9d29-9c46723fd03a, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 3a47799d-afa6-4ff0-b34b-627c81e46059, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b507af42-4ef7-4cb6-8df1-236d9abc4832, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 3a47799d-afa6-4ff0-b34b-627c81e46059, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 3a47799d-afa6-4ff0-b34b-627c81e46059, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b0a798cb-39c3-4cab-a67c-778bc4e2df21, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 3a47799d-afa6-4ff0-b34b-627c81e46059, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: c61a5496-bb75-445c-9ae4-a4cca37cd794, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: c61a5496-bb75-445c-9ae4-a4cca37cd794, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b0a798cb-39c3-4cab-a67c-778bc4e2df21, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin., category: animal, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: c61a5496-bb75-445c-9ae4-a4cca37cd794, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 59cca039-7f8b-4da5-b67d-51ac14e7c74c, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: e0a882a8-f8b1-4a9f-b154-fa061eaa684b, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b086b7b2-daf2-47f2-9a1e-35812afd9313, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: e0a882a8-f8b1-4a9f-b154-fa061eaa684b, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 1b10518f-3973-4f79-9dab-3ef238c2cbaa, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: b086b7b2-daf2-47f2-9a1e-35812afd9313, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 1b10518f-3973-4f79-9dab-3ef238c2cbaa, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies., category: event, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 1b10518f-3973-4f79-9dab-3ef238c2cbaa, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 92562711-f2a9-4ce6-9c7d-d5226080f982, id: 59cca039-7f8b-4da5-b67d-51ac14e7c74c, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: 7c87ffb5-0359-4421-8e03-61457119ca4b, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: f38b0084-b074-4e47-ae66-cccb9827a87f, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: a942b1b8-7ff2-4177-83ef-022bb69affac, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: f38b0084-b074-4e47-ae66-cccb9827a87f, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: a942b1b8-7ff2-4177-83ef-022bb69affac, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: 13374d73-bb3b-4e2f-8a94-ff90f0056970, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: 88635a41-2a86-4bcc-bd34-affe7e302208, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 84fa9b73-12c0-4486-a0eb-3a03a81ca135, id: 13374d73-bb3b-4e2f-8a94-ff90f0056970, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Lee Parkin, a 50-year-old man, owner of Izzy., category: person, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 504729be-4ffc-493a-9cc8-1ae4ffc799e1, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross owned by Lee Parkin., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 517b7476-e446-4986-8445-0a2cb14e543f, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Izzy, a terrier-spaniel cross owned by Lee Parkin., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 517b7476-e446-4986-8445-0a2cb14e543f, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 3cc5365b-b9e7-46d7-81c8-e125af634e32, type: detail]: Relationship [relation]\n",
      "Source [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Naevia, a seven-year-old Siberian Husky owned by Marie Hay., category: animal, memory_type: episodic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 939465bc-c763-4122-9328-984c5c59f712, type: detail] -> Target [created_at: 2024-03-04 20:28:37, updated_at: 2024-03-04 20:28:37, description: Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies., category: location, memory_type: semantic, layer_uuid: d0fde4d0-c358-44b2-b698-a19314a336e0, layer_decomposition_uuid: 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d, id: 4aa02775-42e7-41d5-b91f-1f8a764657ed, type: detail]: Relationship [relation]\n"
     ]
    }
   ],
   "source": [
    "# def list_graph_relationships_with_node_attributes(graph):\n",
    "#     print(\"Graph Relationships with Node Attributes:\")\n",
    "#     for source, target, data in graph.edges(data=True):\n",
    "#         # Get source and target node attributes\n",
    "#         source_attrs = graph.nodes[source]\n",
    "#         target_attrs = graph.nodes[target]\n",
    "#         relationship = data.get('relationship', 'No relationship specified')\n",
    "\n",
    "#         # Format and print source and target node attributes along with the relationship\n",
    "#         source_attrs_formatted = ', '.join([f\"{k}: {v}\" for k, v in source_attrs.items()])\n",
    "#         target_attrs_formatted = ', '.join([f\"{k}: {v}\" for k, v in target_attrs.items()])\n",
    "        \n",
    "#         print(f\"Source [{source_attrs_formatted}] -> Target [{target_attrs_formatted}]: Relationship [{relationship}]\")\n",
    "\n",
    "# # Assuming 'F' is your graph instance\n",
    "# list_graph_relationships_with_node_attributes(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "734a1d1d-a583-4d3f-a1e2-a33f339bfaf0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ace3c0f-93f3-47aa-81d6-0e3297971b5a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de96473f-620c-4d14-8e43-380507d06988",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "id": "c5e2c97c-9b80-4e4b-a80c-940e5428419e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def extract_node_descriptions(data):\n",
    "#     descriptions = []\n",
    "#     for node_id, attributes in data:\n",
    "#         # Check if both 'description' and 'layer_id' are in the attributes\n",
    "#         if 'description' in attributes and 'layer_id' in attributes and 'layer_uuid' in attributes:\n",
    "#             descriptions.append({\n",
    "#                 'node_id': node_id, \n",
    "#                 'description': attributes['description'],\n",
    "#                 'layer_uuid': attributes['layer_uuid']  # Include layer_id\n",
    "#             })\n",
    "#     return descriptions\n",
    "\n",
    "# # Extract the node descriptions\n",
    "# node_descriptions = extract_node_descriptions(R.nodes(data=True))\n",
    "\n",
    "# # Display the results (displaying a subset for brevity)\n",
    "# for item in node_descriptions[:5]:  # Adjust the slice as needed for display\n",
    "#     print(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "id": "a0a7fac1-0e8b-41de-b33f-435496ec1865",
   "metadata": {},
   "outputs": [],
   "source": [
    "# descriptions = []\n",
    "# for node_id, attributes in R.nodes(data=True):\n",
    "#     if 'description' in attributes:\n",
    "#         descriptions.append({'node_id': node_id, 'description': attributes['description'], 'layer_uuid': attributes['layer_uuid'], 'layer_decomposition_uuid': attributes['layer_decomposition_uuid']})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fee432d0-75de-43b2-9a3b-3b8844a2cf19",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c214724e-4bb3-4b75-b104-77ac98348394",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'node_id': 'd443269f-44ff-4c10-ab4a-fab9ead0f904', 'description': 'For Britons, keeping pets is an entire way of life.', 'layer_uuid': '66009783-f985-47e5-9553-d60573e7cc33', 'layer_decomposition_uuid': '67200cb4-16fc-40f9-b231-c9e720aeb14a'}\n",
      "{'node_id': '2d588b35-062e-44e7-bbb2-1642ba0411e3', 'description': 'Pets, especially dogs, serve as outlets for emotions and social interaction within controlled social norms.', 'layer_uuid': '66009783-f985-47e5-9553-d60573e7cc33', 'layer_decomposition_uuid': '67200cb4-16fc-40f9-b231-c9e720aeb14a'}\n",
      "{'node_id': '6a34c9bd-0dee-4db0-8258-86d2dd87303d', 'description': 'Dogs are encouraged and welcomed in public spaces such as pubs, shops, and public transport.', 'layer_uuid': '66009783-f985-47e5-9553-d60573e7cc33', 'layer_decomposition_uuid': '67200cb4-16fc-40f9-b231-c9e720aeb14a'}\n",
      "{'node_id': '630b58dd-65f6-4d55-b3fc-67b59d696b4c', 'description': 'The rise in pet ownership and the desire for designer breeds can lead to negative outcomes for animal welfare.', 'layer_uuid': '66009783-f985-47e5-9553-d60573e7cc33', 'layer_decomposition_uuid': '67200cb4-16fc-40f9-b231-c9e720aeb14a'}\n",
      "{'node_id': '54db7b9e-5f2f-4287-9185-7214eb8f0ccd', 'description': 'The COVID-19 pandemic saw a surge in pet ownership, leading to growing concerns about pet abandonment and the treatment of pets as commodities.', 'layer_uuid': '66009783-f985-47e5-9553-d60573e7cc33', 'layer_decomposition_uuid': '67200cb4-16fc-40f9-b231-c9e720aeb14a'}\n"
     ]
    }
   ],
   "source": [
    "def extract_node_descriptions(data):\n",
    "    descriptions = []\n",
    "    for node_id, attributes in data:\n",
    "        if 'description' in attributes:\n",
    "            descriptions.append({'node_id': attributes['id'], 'description': attributes['description'], 'layer_uuid': attributes['layer_uuid'], 'layer_decomposition_uuid': attributes['layer_decomposition_uuid'] })\n",
    "    return descriptions\n",
    "\n",
    "# Extract the node descriptions\n",
    "node_descriptions = extract_node_descriptions(R.nodes(data=True))\n",
    "\n",
    "# Display the results (displaying a subset for brevity)\n",
    "for item in node_descriptions[:5]:  # Adjust the slice as needed for display\n",
    "    print(item)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74b65ea2-b325-4bed-8286-0f2030462794",
   "metadata": {},
   "source": [
    "## HOW TO CONNECT INTERLAYERS WITH SEMANTIC SEARCH"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff33bc54-72ce-4e92-8368-b6285077fccb",
   "metadata": {},
   "source": [
    "## Idea here is to pass descriptions to the vectorstore and embed them, then do a semantic search for each description to other one and retrieve only those between layers that have a connection\n",
    "## We load each layer as a qdrant collection and then search the terms in other collection to establish links between layers, after that is done, we save the relevant IDs and create connections in the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "65178488-6424-4f40-8420-edf921ff1678",
   "metadata": {},
   "outputs": [],
   "source": [
    "from openai import OpenAI\n",
    "client = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "d8e722e9-bffe-430f-bedd-b38dfbe1774e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from openai import AsyncOpenAI\n",
    "client = AsyncOpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "19ba87f3-a9d9-43d6-8a8d-b2491ace5330",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_embedding_b(text):\n",
    "    client = OpenAI()\n",
    "    response = client.embeddings.create(\n",
    "        input=[text],\n",
    "        model=\"text-embedding-3-large\"  # Choose an appropriate engine for your use case\n",
    "    ).data[0].embedding\n",
    "\n",
    "    return response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8812936f-2b3c-4084-a75a-a79ac8726a62",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "599cd4f9-4f8d-4321-83a5-fa153d029115",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'cognitive_architecture.openai_tools'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01masyncio\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mcognitive_architecture\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mopenai_tools\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m async_get_embedding_with_backoff\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m# Ensure your async function is defined in a cell above or within this cell\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \n\u001b[1;32m      5\u001b[0m \u001b[38;5;66;03m# async def run_async_function(text):\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     10\u001b[0m \n\u001b[1;32m     11\u001b[0m \u001b[38;5;66;03m# Use asyncio.run() to run the async function\u001b[39;00m\n\u001b[1;32m     12\u001b[0m loop \u001b[38;5;241m=\u001b[39m asyncio\u001b[38;5;241m.\u001b[39mget_event_loop()\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'cognitive_architecture.openai_tools'"
     ]
    }
   ],
   "source": [
    "import asyncio\n",
    "from cognitive_architecture.openai_tools import async_get_embedding_with_backoff\n",
    "# Ensure your async function is defined in a cell above or within this cell\n",
    "\n",
    "# async def run_async_function(text):\n",
    "#     text = \"Your input text here\"\n",
    "#     model = \"text-embedding-ada-002\"  # Or any other model you wish to use\n",
    "#     embedding = await async_get_embedding_with_backoff(text, model)\n",
    "#     print(embedding)\n",
    "\n",
    "# Use asyncio.run() to run the async function\n",
    "loop = asyncio.get_event_loop()\n",
    "\n",
    "# Create and add the task to the event loop\n",
    "# Replace 'your_text_here' with the actual text you want to process\n",
    "task = loop.create_task(async_get_embedding_with_backoff('your_text_here'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39932ec2-3197-46db-bf68-ee2868ab15d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "id": "b14cc96a-ecd4-4532-a8d0-02071f8d93fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import asyncio\n",
    "import nest_asyncio\n",
    "\n",
    "# Apply nest_asyncio to the current event loop\n",
    "nest_asyncio.apply()\n",
    "\n",
    "# Your async function and the list of texts remain the same\n",
    "texts = [\"Text 1\", \"Text 2\", \"Text 3\"]  # Example list of texts\n",
    "\n",
    "async def get_embeddings(texts):\n",
    "    tasks = [async_get_embedding_with_backoff(text,\"text-embedding-3-large\") for text in texts]\n",
    "    results = await asyncio.gather(*tasks)\n",
    "    return results\n",
    "\n",
    "# # Now you can run your async function directly using await in the notebook cell\n",
    "# embeddings = await get_embeddings(texts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "9238422f-5a1b-48b9-9ea8-e0973bca2f8a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7befc950-f0d5-4807-909e-1946c17e3a9b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "0c4670d9-c7e3-476e-be90-7cb52efd6f3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# embedding = get_embedding(\"Example text to encode\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "d9ce8103-375d-4e77-8d64-46edc753b375",
   "metadata": {},
   "outputs": [],
   "source": [
    "# some_embeddings = []\n",
    "# some_text = [\"bla\", \"blwea\"]\n",
    "# for st in some_text:\n",
    "#     some_embeddings.append(get_embedding(st))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "91763457-bf41-4e60-ad8f-0bd5542b250a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qdrant_client import models, QdrantClient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "c35342d7-a3ce-491b-971d-142b52110bca",
   "metadata": {},
   "outputs": [],
   "source": [
    "qdrant = QdrantClient(\":memory:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "e8ccd86e-01d0-44ac-9376-c848bed1adad",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qdrant_client.http import models as rest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 441,
   "id": "6470ed2b-1842-43f2-9ac4-88db32909ec6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# unique_layer_uuids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "id": "92c76fe6-bdbb-40d6-b136-3b83b1d85b32",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "unique_layer_uuids = set(node['layer_decomposition_uuid'] for node in node_descriptions)\n",
    "# Create a new collection in Qdrant\n",
    "def create_collection(collection_name):\n",
    "    qdrant.recreate_collection(\n",
    "        collection_name=collection_name,\n",
    "        vectors_config={\n",
    "            'content': rest.VectorParams(\n",
    "                distance=rest.Distance.COSINE,\n",
    "                size=3072,\n",
    "            )\n",
    "        }\n",
    "    )\n",
    "for layer in unique_layer_uuids:\n",
    "    create_collection(layer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "id": "3c53de05-65d2-4232-bb23-f1b50fbd36c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for item in node_descriptions[:5]:  # Adjust the slice as needed for display\n",
    "#     print(item)\n",
    "#     print(item['description'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "b810075a-3c1a-4e2e-98d6-150427951491",
   "metadata": {},
   "outputs": [],
   "source": [
    "# collection_schema = qdrant.get_collection(collection_name=\"97597864-a11a-4058-b854-8f21864c7e06\")\n",
    "\n",
    "# # Print the schema to inspect it\n",
    "# print(collection_schema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "id": "313a893d-31b5-4599-8f6f-2a2cd0759fa0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# collection_name = 'Articles'\n",
    "\n",
    "# # Create a new collection in Qdrant\n",
    "# def create_collection(collection_name):\n",
    "#     qdrant.recreate_collection(\n",
    "#         collection_name=collection_name,\n",
    "#         vectors_config={\n",
    "#             'content': rest.VectorParams(\n",
    "#                 distance=rest.Distance.COSINE,\n",
    "#                 size=3072,\n",
    "#             )\n",
    "#         }\n",
    "#     )\n",
    "\n",
    "# Function to upload embeddings to Qdrant\n",
    "# def upload_embedding(id, metadata, some_embeddings, collection_name):\n",
    "#     qdrant.upload_points(\n",
    "#         collection_name=collection_name,\n",
    "#         points=[\n",
    "#             models.PointStruct(\n",
    "#                 id=idx, vector={\"content\":doc}, payload=metadata\n",
    "#             )\n",
    "#             for idx, doc in enumerate(some_embeddings)\n",
    "#         ],\n",
    "#     )\n",
    "\n",
    "# # Example usage\n",
    "# upload_embedding(1, (\"meta\":1}, some_embeddings, collection_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "1aed2283-f889-42d2-bbc2-05341a145583",
   "metadata": {},
   "outputs": [],
   "source": [
    "async def upload_embedding(id, metadata, some_embeddings, collection_name):\n",
    "    print(id)\n",
    "    # if some_embeddings and isinstance(some_embeddings[0], list):\n",
    "    #     some_embeddings = [item for sublist in some_embeddings for item in sublist]\n",
    "    \n",
    "    qdrant.upload_points(\n",
    "        collection_name=collection_name,\n",
    "        points=[\n",
    "            models.PointStruct(\n",
    "                id=id, vector={\"content\":some_embeddings}, payload=metadata\n",
    "            )\n",
    "        ]\n",
    "        ,\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "317036c5-0d03-46f2-b5c9-26f112b07f0d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "49b94ef4-6f40-474c-8610-367f98860d59",
   "metadata": {},
   "outputs": [],
   "source": [
    "async def upload_embeddings(node_descriptions):\n",
    "    tasks = []\n",
    "\n",
    "    for item in node_descriptions:  \n",
    "        try:\n",
    "            embedding = await get_embeddings(item['description'])\n",
    "            # Ensure embedding is not empty and is properly structured\n",
    "            # if embedding and all(isinstance(e, float) for sublist in embedding for e in (sublist if isinstance(sublist, list) else [sublist])):\n",
    "            #     # Flatten embedding if it's a list of lists\n",
    "            #     if isinstance(embedding[0], list):\n",
    "            #         embedding = [e for sublist in embedding for e in sublist]\n",
    "            #     print(f\"Uploading embedding for node_id {item['node_id']} with length {len(embedding)}\")\n",
    "\n",
    "                # Create and append the upload task\n",
    "                task = asyncio.create_task(upload_embedding(\n",
    "                    id=item['node_id'],\n",
    "                    metadata={\"meta\": item['description']},\n",
    "                    some_embeddings=embedding,\n",
    "                    collection_name=item['layer_decomposition_uuid']\n",
    "                ))\n",
    "                tasks.append(task)\n",
    "            else:\n",
    "                print(f\"Skipping upload for node_id {item['node_id']} due to incorrect embedding format or empty embedding.\")\n",
    "        except Exception as e:\n",
    "            print(f\"Error processing embedding for node_id {item['node_id']}: {e}\")\n",
    "\n",
    "    # Wait for all upload tasks to complete, if any\n",
    "    if tasks:\n",
    "        await asyncio.gather(*tasks)\n",
    "    else:\n",
    "        print(\"No valid embeddings to upload.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "id": "fb0235a8-7e91-4d34-9058-0cdd1dc7cfe7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# unique_layer_uuids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "id": "4cd43233-533a-4929-b3f2-7b8a310669a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# node_descriptions[:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "id": "68f5a029-b1d3-4476-896d-711462099d52",
   "metadata": {},
   "outputs": [
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      "f866a9f5-3b89-418e-a94b-37923e0c4982\n",
      "f866a9f5-3b89-418e-a94b-37923e0c4982\n",
      "15d3a8af-4e1a-4c3f-9d29-9c46723fd03a\n",
      "15d3a8af-4e1a-4c3f-9d29-9c46723fd03a\n",
      "b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "3a47799d-afa6-4ff0-b34b-627c81e46059\n",
      "3a47799d-afa6-4ff0-b34b-627c81e46059\n",
      "b0a798cb-39c3-4cab-a67c-778bc4e2df21\n",
      "b0a798cb-39c3-4cab-a67c-778bc4e2df21\n",
      "c61a5496-bb75-445c-9ae4-a4cca37cd794\n",
      "c61a5496-bb75-445c-9ae4-a4cca37cd794\n",
      "e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "1b10518f-3973-4f79-9dab-3ef238c2cbaa\n",
      "1b10518f-3973-4f79-9dab-3ef238c2cbaa\n",
      "59cca039-7f8b-4da5-b67d-51ac14e7c74c\n",
      "59cca039-7f8b-4da5-b67d-51ac14e7c74c\n",
      "7c87ffb5-0359-4421-8e03-61457119ca4b\n",
      "7c87ffb5-0359-4421-8e03-61457119ca4b\n",
      "f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "a942b1b8-7ff2-4177-83ef-022bb69affac\n",
      "a942b1b8-7ff2-4177-83ef-022bb69affac\n",
      "88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "504729be-4ffc-493a-9cc8-1ae4ffc799e1\n",
      "504729be-4ffc-493a-9cc8-1ae4ffc799e1\n",
      "517b7476-e446-4986-8445-0a2cb14e543f\n",
      "517b7476-e446-4986-8445-0a2cb14e543f\n",
      "13a45934-879a-4fe4-90e9-0a5277e56297\n",
      "13a45934-879a-4fe4-90e9-0a5277e56297\n",
      "3fce46e3-8006-4940-bc47-e011408f663c\n",
      "3fce46e3-8006-4940-bc47-e011408f663c\n",
      "939465bc-c763-4122-9328-984c5c59f712\n",
      "939465bc-c763-4122-9328-984c5c59f712\n",
      "3cc5365b-b9e7-46d7-81c8-e125af634e32\n",
      "3cc5365b-b9e7-46d7-81c8-e125af634e32\n",
      "4aa02775-42e7-41d5-b91f-1f8a764657ed\n",
      "4aa02775-42e7-41d5-b91f-1f8a764657ed\n"
     ]
    }
   ],
   "source": [
    "for item in node_descriptions: \n",
    "    print(item['node_id'])\n",
    "    await upload_embedding(id = item['node_id'], metadata = {\"meta\":item['description']}, some_embeddings = get_embedding_b(item['description']), collection_name= item['layer_decomposition_uuid'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "9c33fe6a-30fc-4ae9-85c3-c3c0563ab7c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import nest_asyncio\n",
    "\n",
    "# # Apply nest_asyncio to the current event loop\n",
    "# nest_asyncio.apply()\n",
    "\n",
    "# await upload_embeddings(node_descriptions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "302dc698-2c14-4408-81d7-76282524dba3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for item in node_descriptions[:5]: \n",
    "#     print(item['node_id'])\n",
    "#     upload_embedding(id = item['node_id'], metadata = {\"meta\":item['description']}, some_embeddings = get_embedding(item['description']), collection_name= item['layer_decomposition_uuid'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "e48f1104-829d-4150-82f6-e42cc53c8e8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_data = {}\n",
    "\n",
    "# Iterate through each dictionary in the list\n",
    "for item in node_descriptions:\n",
    "    # Get the layer_decomposition_uuid of the current dictionary\n",
    "    uuid = item['layer_decomposition_uuid']\n",
    "    \n",
    "    # Check if this uuid is already a key in the grouped_data dictionary\n",
    "    if uuid not in grouped_data:\n",
    "        # If not, initialize a new list for this uuid\n",
    "        grouped_data[uuid] = []\n",
    "    \n",
    "    # Append the current dictionary to the list corresponding to its uuid\n",
    "    grouped_data[uuid].append(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "id": "a507c77e-9190-4a71-8321-ccc081121534",
   "metadata": {},
   "outputs": [],
   "source": [
    "# grouped_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "id": "95cfd736-f2c1-40d3-920c-ebc14c230f21",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def qdrant_search (collection_name, embedding):\n",
    "#     hits = qdrant.search(\n",
    "#     collection_name=collection_name,\n",
    "#     query_vector=(\n",
    "#             \"content\", embedding\n",
    "#         ),\n",
    "#     limit=3,\n",
    "# )\n",
    "#     return hits\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "id": "32e3f64e-bdcf-4f28-a17b-774930c1f970",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for cl, e in relationship_dict:\n",
    "#     print(cl)\n",
    "#     print(e)\n",
    "#     g = qdrant_search(cl, e)\n",
    "#     print(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "id": "bf0e8bb8-9412-4f98-bb83-83abeec0b619",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[ScoredPoint(id='d443269f-44ff-4c10-ab4a-fab9ead0f904', version=0, score=0.4133083905881839, payload={'meta': 'For Britons, keeping pets is an entire way of life.'}, vector=None, shard_key=None),\n",
       " ScoredPoint(id='6a34c9bd-0dee-4db0-8258-86d2dd87303d', version=0, score=0.17809770074247908, payload={'meta': 'Dogs are encouraged and welcomed in public spaces such as pubs, shops, and public transport.'}, vector=None, shard_key=None),\n",
       " ScoredPoint(id='53b9fc97-7c9e-46f1-ab2c-741405fa12ac', version=0, score=0.1524232010928769, payload={'meta': \"Ownership of certain dog breeds is seen as a status symbol and a reflection of owner's identity.\"}, vector=None, shard_key=None)]"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# qdrant_search ('67200cb4-16fc-40f9-b231-c9e720aeb14a',get_embedding_b(\"Britons\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "id": "983c44ef-6486-4abe-ba2b-d953cfea33ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "async def qdrant_batch_search(collection_name: str, embeddings: List[List[float]], limits: List[int], with_vectors: List[bool] = None):\n",
    "    \"\"\"\n",
    "    Perform batch search in a Qdrant collection with dynamic search requests.\n",
    "\n",
    "    Args:\n",
    "    - collection_name (str): Name of the collection to search in.\n",
    "    - embeddings (List[List[float]]): List of embeddings to search for.\n",
    "    - limits (List[int]): List of result limits for each search request.\n",
    "    - with_vectors (List[bool], optional): List indicating whether to return vectors for each search request.\n",
    "        Defaults to None, in which case vectors are not returned.\n",
    "\n",
    "    Returns:\n",
    "    - results: The search results from Qdrant.\n",
    "    \"\"\"\n",
    "\n",
    "    # Default with_vectors to False for each request if not provided\n",
    "    if with_vectors is None:\n",
    "        with_vectors = [False] * len(embeddings)\n",
    "\n",
    "\n",
    "    # Ensure with_vectors list matches the length of embeddings and limits\n",
    "    if len(with_vectors) != len(embeddings):\n",
    "        raise ValueError(\"The length of with_vectors must match the length of embeddings and limits\")\n",
    "\n",
    "    # Generate dynamic search requests based on the provided embeddings\n",
    "    requests = [\n",
    "        rest.SearchRequest( vector=models.NamedVector(\n",
    "                name=\"content\",\n",
    "                vector=embedding,\n",
    "            ),\n",
    "            # vector= embedding,\n",
    "            limit=3,\n",
    "            with_vector=False\n",
    "        ) for embedding in embeddings\n",
    "    ]\n",
    "\n",
    "    # Perform batch search with the dynamically generated requests\n",
    "    results = qdrant.search_batch(\n",
    "        collection_name=collection_name,\n",
    "        requests=requests\n",
    "    )\n",
    " \n",
    "\n",
    "    return results\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "5210715c-66ae-430a-a5d5-469fa2ca860c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# hits = qdrant.search(\n",
    "#     collection_name=\"Articles\",\n",
    "#     query_vector=(\n",
    "#             \"content\", get_embedding(\"bla\")\n",
    "#         ),\n",
    "#     limit=3,\n",
    "# )\n",
    "# for hit in hits:\n",
    "#     print(hit.payload, \"score:\", hit.score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "d6253483-4bd3-426d-88fc-7ac29ed1d5dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# b = get_embedding(\"dog\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "4a7173ab-3e1b-496d-a56e-c7d05b84f0fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# c = []\n",
    "# for collection in unique_layer_uuids:\n",
    "#     try:\n",
    "#         # c.apend(qdrant_search(collection, b))\n",
    "#         c.apend(qdrant_batch_search(collection, [b], [3]))\n",
    "#     except:\n",
    "#         pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "5d2ebcac-8dae-4495-bd6c-415edca60b24",
   "metadata": {},
   "outputs": [],
   "source": [
    "# qdrant_search(collection, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "91fcac9b-04ec-4238-800d-f291c8e7c13b",
   "metadata": {},
   "outputs": [],
   "source": [
    "unique_layer_uuids = set(node['layer_decomposition_uuid'] for node in node_descriptions)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "id": "339881a7-664b-4ad4-8579-5996fd1b0676",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       " '67200cb4-16fc-40f9-b231-c9e720aeb14a',\n",
       " '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       " '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       " '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       " '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       " '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       " 'ccf6645e-9fad-441b-821d-b1d47b93ebca',\n",
       " 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda'}"
      ]
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unique_layer_uuids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "id": "8e517772-d4eb-4e7a-9393-1ea695020e65",
   "metadata": {},
   "outputs": [],
   "source": [
    "# count = 0  # Counter to keep track of how many values we've printed\n",
    "# for uuid, items in grouped_data.items():\n",
    "#     print(f\"Group ID: {uuid}, Items: {items}\")\n",
    "#     count += 1\n",
    "#     if count == 3:\n",
    "#         break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "id": "c585ca09-139d-4d00-aed0-68ecaa991564",
   "metadata": {},
   "outputs": [],
   "source": [
    "nest_asyncio.apply()\n",
    "async def process_items(grouped_data, unique_layer_uuids):\n",
    "    results_to_check = []  # This will hold results excluding self comparisons\n",
    "    tasks = []  # List to hold all tasks\n",
    "    task_to_info = {}  # Dictionary to map tasks to their corresponding group id and item info\n",
    "\n",
    "    # Iterate through each group in grouped_data\n",
    "    for group_id, items in grouped_data.items():\n",
    "        # Filter unique_layer_uuids to exclude the current group_id\n",
    "        target_uuids = [uuid for uuid in unique_layer_uuids if uuid != group_id]\n",
    "\n",
    "        # Process each item in the group\n",
    "        for item in items:\n",
    "            # For each target UUID, create an async task for the item's embedding retrieval\n",
    "            for target_id in target_uuids:\n",
    "                task = asyncio.create_task(async_get_embedding_with_backoff(item['description'], \"text-embedding-3-large\"))\n",
    "                tasks.append(task)\n",
    "                # Map the task to the target id, item's node_id, and description for later retrieval\n",
    "                task_to_info[task] = (target_id, item['node_id'], group_id, item['description'])\n",
    "        \n",
    "    # Await all tasks to complete and gather results\n",
    "    results = await asyncio.gather(*tasks)\n",
    "\n",
    "    # Process the results, associating them with their target id, node id, and description\n",
    "    for task, embedding in zip(tasks, results):\n",
    "        \n",
    "        target_id, node_id,group_id, description = task_to_info[task]\n",
    "        results_to_check.append([target_id, embedding, description, node_id, group_id])\n",
    "\n",
    "    return results_to_check\n",
    "\n",
    "    \n",
    "# async def process_items(grouped_data, unique_layer_uuids):\n",
    "#     relationship_dict = {}\n",
    "#     task_to_id = {}  # Dictionary to map tasks to ids\n",
    "#     tasks = []  # List to hold all tasks\n",
    "\n",
    "#     for id in unique_layer_uuids:\n",
    "#         if id not in relationship_dict:\n",
    "#             relationship_dict[id] = []\n",
    "        \n",
    "#         for uuid, items in grouped_data.items():\n",
    "#             if uuid != id:\n",
    "#                 for item in items:\n",
    "#                     # Create a task for each embedding retrieval\n",
    "#                     task = asyncio.create_task(async_get_embedding_with_backoff(item['description'],\"text-embedding-3-large\" ))\n",
    "#                     tasks.append(task)\n",
    "#                     # Map the task to the corresponding id\n",
    "#                     task_to_id[task] = id\n",
    "\n",
    "#     # Await all tasks to complete and gather results\n",
    "#     results = await asyncio.gather(*tasks)\n",
    "\n",
    "#     # Process the results and update relationship_dict\n",
    "#     for task, result in zip(tasks, results):\n",
    "#         id = task_to_id[task]  # Get the id associated with this task\n",
    "#         if id in relationship_dict:\n",
    "#             relationship_dict[id].append(result)\n",
    "#         else:\n",
    "#             relationship_dict[id] = [result]\n",
    "\n",
    "#     return relationship_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "id": "933beda7-27e6-45e2-9ce7-3084b6243f54",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "67200cb4-16fc-40f9-b231-c9e720aeb14a\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n",
      "ccf6645e-9fad-441b-821d-b1d47b93ebca\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', '67200cb4-16fc-40f9-b231-c9e720aeb14a', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n",
      "d0c2bd1c-7cec-4e5a-af13-dbb655623dda\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '67200cb4-16fc-40f9-b231-c9e720aeb14a', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n",
      "83b60dcf-0a04-474f-962b-121cc518e610\n",
      "['796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '67200cb4-16fc-40f9-b231-c9e720aeb14a', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n",
      "6fb85c94-f488-4f31-8e7c-a5905580a78c\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '67200cb4-16fc-40f9-b231-c9e720aeb14a']\n",
      "796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '67200cb4-16fc-40f9-b231-c9e720aeb14a', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n",
      "92562711-f2a9-4ce6-9c7d-d5226080f982\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '67200cb4-16fc-40f9-b231-c9e720aeb14a', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n",
      "84fa9b73-12c0-4486-a0eb-3a03a81ca135\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '67200cb4-16fc-40f9-b231-c9e720aeb14a', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n",
      "3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d\n",
      "['83b60dcf-0a04-474f-962b-121cc518e610', '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', '84fa9b73-12c0-4486-a0eb-3a03a81ca135', '92562711-f2a9-4ce6-9c7d-d5226080f982', 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda', 'ccf6645e-9fad-441b-821d-b1d47b93ebca', '67200cb4-16fc-40f9-b231-c9e720aeb14a', '6fb85c94-f488-4f31-8e7c-a5905580a78c']\n"
     ]
    }
   ],
   "source": [
    "relationship_dict = await process_items(grouped_data, unique_layer_uuids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35e868ad-d8cd-4341-8909-fdf791e4ce12",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "a23a7517-64f2-4d9f-8cc0-f6dfdd0fe3c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This code compares and runs a semantic search across the nodes and calculates if there are relevant nodes in different layers that interconnect. this is not efficient and needs to be completely redone, batching and ideally done on vectordb side\n",
    "\n",
    "# relationship_dict={}\n",
    "# results_to_check = []\n",
    "# for id in unique_layer_uuids:\n",
    "#     if id not in relationship_dict:\n",
    "#         relationship_dict[id] = []\n",
    "    \n",
    "#     for uuid, items in grouped_data.items():\n",
    "#         if uuid != id:\n",
    "#             # print(\"this id is orig %s\", id)\n",
    "#             # print(\"this uuid is relevant for search %s\", uuid)\n",
    "#             for item in items:\n",
    "\n",
    "#                 results_to_check.append([id, [get_embedding(item['description'])]])\n",
    "\n",
    "\n",
    "\n",
    "                \n",
    "                \n",
    "    # results = qdrant_search(id, item['description'])\n",
    "\n",
    "    # for result in results:\n",
    "    #     if result.score > 0.9:  # Only consider hits with a score greater than 0.9\n",
    "    #         # Append result information to the relationship_dict under the current id\n",
    "    #         relationship_dict[id].append({\n",
    "    #             'collection_name_uuid': uuid,  # The uuid used for the search\n",
    "    #             'searched_node_id': item['node_id'],  # The node_id of the hit\n",
    "    #             'score': result.score,\n",
    "    #             'score_metadata': result.payload,\n",
    "    #             'score_id': result.id,\n",
    "    #         })\n",
    "                \n",
    "                \n",
    "                # print(item['description'])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 435,
   "id": "69967cdd-3957-4c39-b5d7-8e58d0f8c13c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# unique_layer_uuids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 630,
   "id": "594825c9-a6c4-4760-bd0e-4d7d3a25d090",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ff= get_embedding('dog')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 631,
   "id": "7ee6a445-e783-4d43-9d02-e97bc83502f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# sample_embeddings = [\n",
    "#     [0.1, 0.2, 0.3, 0.4],  # First sample embedding\n",
    "#     [-0.5, 0.8, -0.3, 0.2]  # Second sample embedding\n",
    "# ]\n",
    "\n",
    "# # Corresponding limits for each embedding search\n",
    "# search_limits = [3, 2]  # Find top 3 for the first embedding and top 2 for the second\n",
    "\n",
    "# # Call the qdrant_batch_search function with the test collection name, sample embeddings, and their limits\n",
    "# search_results = qdrant_batch_search('97597864-a11a-4058-b854-8f21864c7e06', [ff], search_limits)\n",
    "# search_r = qdrant_search('97597864-a11a-4058-b854-8f21864c7e06',ff)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 629,
   "id": "a9cb5f13-d284-4cc5-ac74-78d7f4316148",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for i in results_to_check[:4]:\n",
    "#     print(i[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "836a7b57-9b65-43e2-b57a-8f2914061b40",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 424,
   "id": "baff4d94-5e9a-4ba6-a42a-a1b5939fb1fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "# def qdrant_batch_search(results_to_check):\n",
    "#     results = []\n",
    "\n",
    "#     for result in results_to_check:\n",
    "#         # Assuming result[1] is the list of embeddings and you want a limit of 3 for each\n",
    "#         embedding_list = result[1]  # This should be a list of embeddings\n",
    "#         limits = [3] * len(embedding_list)  # Create a list with a limit of 3 for each embedding\n",
    "#         try:\n",
    "#             search_results = qdrant_batch_search(result[0], embedding_list, limits)\n",
    "#             results.append(search_results)\n",
    "#         except:\n",
    "#             pass\n",
    "#     return results\n",
    "\n",
    "# async def adapted_qdrant_batch_search(relationship_dict):\n",
    "#     search_results_list = []\n",
    "\n",
    "#     for id, embeddings_list in relationship_dict.items():\n",
    "#         print(id)\n",
    "#         # Flatten the list of lists of embeddings for this id\n",
    "#         flattened_embeddings = [embedding for sublist in embeddings_list for embedding in sublist]\n",
    "#         print(len(flattened_embeddings))\n",
    "\n",
    "#         # Set a limit of 3 results for each embedding in the flattened list\n",
    "#         limits = [3] * len(embeddings_list)\n",
    "\n",
    "#         try:\n",
    "#             # Perform the batch search for this id with its flattened embeddings and corresponding limits\n",
    "#             id_search_results = await qdrant_batch_search(id, [embeddings_list[0], limits)\n",
    "#             search_results_list.append((id, id_search_results))\n",
    "#         except Exception as e:\n",
    "#             print(f\"Error during batch search for ID {id}: {e}\")\n",
    "#             continue\n",
    "\n",
    "#     return search_results_list\n",
    "async def adapted_qdrant_batch_search(results_to_check):\n",
    "    search_results_list = []\n",
    "\n",
    "    for result in results_to_check:\n",
    "        id = result[0]\n",
    "        embedding = result[1]\n",
    "        node_id = result[2]\n",
    "        target = result[3]\n",
    "        b= result[4]\n",
    "\n",
    "        # Assuming each result in results_to_check contains a single embedding\n",
    "        limits = [3] * len(embedding)  # Set a limit of 3 results for this embedding\n",
    "\n",
    "        try:\n",
    "            # Perform the batch search for this id with its embedding\n",
    "            # Assuming qdrant_batch_search function accepts a single embedding and a list of limits\n",
    "            id_search_results = await qdrant_batch_search(id, [embedding], limits)\n",
    "            search_results_list.append((id, id_search_results, node_id, target))\n",
    "        except Exception as e:\n",
    "            print(f\"Error during batch search for ID {id}: {e}\")\n",
    "            continue\n",
    "\n",
    "    return search_results_list\n",
    "\n",
    "def graph_ready_output(results):\n",
    "    relationship_dict={}\n",
    "\n",
    "    for result_tuple in results:\n",
    " \n",
    "        uuid, scored_points_list, desc, node_id = result_tuple\n",
    "        # Unpack the tuple\n",
    "        \n",
    "        # Ensure there's a list to collect related items for this uuid\n",
    "        if uuid not in relationship_dict:\n",
    "            relationship_dict[uuid] = []\n",
    "        \n",
    "        for scored_points in scored_points_list:  # Iterate over the list of ScoredPoint lists\n",
    "            for scored_point in scored_points:  # Iterate over each ScoredPoint object\n",
    "                if scored_point.score > 0.9:  # Check the score condition\n",
    "                    # Append a new dictionary to the list associated with the uuid\n",
    "                    relationship_dict[uuid].append({\n",
    "                        'collection_name_uuid': uuid,  \n",
    "                        'searched_node_id': scored_point.id,  \n",
    "                        'score': scored_point.score,\n",
    "                        'score_metadata': scored_point.payload,\n",
    "                        'original_id_for_search': node_id,\n",
    "                    })\n",
    "    return relationship_dict\n",
    "\n",
    "# results = qdrant_search(id, item['description'])\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "id": "838bdc96-7712-4b9d-816b-588500d034be",
   "metadata": {},
   "outputs": [],
   "source": [
    "# results = []\n",
    "\n",
    "# for result in relationship_dict:\n",
    "#     # Assuming result[1] is the list of embeddings and you want a limit of 3 for each\n",
    "#     embedding_list = result[1]  # This should be a list of embeddings\n",
    "#     limits = [3] * len(embedding_list)  # Create a list with a limit of 3 for each embedding\n",
    "#     try:\n",
    "#         search_results = qdrant_batch_search(result[0], embedding_list, limits)\n",
    "#         results.append(search_results)\n",
    "#     except:\n",
    "#         pass\n",
    "#     return results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "id": "44a0065b-e3a8-431c-af07-c710aa6d1fa4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# relationship_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "id": "849cc731-cf2d-44dc-b363-9e195dab66c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# await adapted_qdrant_batch_search(relationship_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "id": "9d17db26-2168-4f55-bd14-cf41c18bbda7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes containing ID '3a63bd68-0238-4865-9ea1-d7f88f58d6e8' in any attribute: ['Izzy, a terrier-spaniel cross owned by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 3a63bd68-0238-4865-9ea1-d7f88f58d6e8']\n",
      "Attributes of node Izzy, a terrier-spaniel cross owned by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 3a63bd68-0238-4865-9ea1-d7f88f58d6e8: {'created_at': '2024-03-04 20:28:37', 'updated_at': '2024-03-04 20:28:37', 'description': 'Izzy, a terrier-spaniel cross owned by Lee Parkin.', 'category': 'animal', 'memory_type': 'episodic', 'layer_uuid': 'd0fde4d0-c358-44b2-b698-a19314a336e0', 'layer_decomposition_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f', 'id': '3a63bd68-0238-4865-9ea1-d7f88f58d6e8', 'type': 'detail'}\n"
     ]
    }
   ],
   "source": [
    "# desired_id = '3a63bd68-0238-4865-9ea1-d7f88f58d6e8'  # Replace this with the actual 'id' you're looking for\n",
    "# nodes_with_desired_id = []  # Initialize variable to store the node if found\n",
    "\n",
    "# # Iterate through all nodes and their attributes in the graph\n",
    "# for node, attrs in CONNECTED_GRAPH.nodes(data=True):\n",
    "#     if any(desired_id in str(value) for value in attrs.values()):  # Check if any attribute value contains the desired ID\n",
    "#         nodes_with_desired_id.append(node)  # Add the node to the list if the ID is found in any attribute\n",
    "\n",
    "# # Check if any nodes were found and print the results\n",
    "# if nodes_with_desired_id:\n",
    "#     print(f\"Nodes containing ID '{desired_id}' in any attribute: {nodes_with_desired_id}\")\n",
    "#     for node in nodes_with_desired_id:\n",
    "#         print(f\"Attributes of node {node}: {G.nodes[node]}\")\n",
    "# else:\n",
    "#     print(f\"No nodes found containing ID '{desired_id}' in any attribute.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e45b7ed-1bb2-494d-8c5d-2af1cfa26f0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# CONNECTED_GRAPH.get"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55c4aa77-00db-4e1e-985f-fb04de74f371",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "id": "19eb60cc-554a-423d-a52e-8197e62b9906",
   "metadata": {},
   "outputs": [],
   "source": [
    "# await qdrant_batch_search('83b60dcf-0a04-474f-962b-121cc518e610',[get_embedding_b(\"bla\")],[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 422,
   "id": "3c28c2f1-ecd4-4b2b-8797-c07c89e01d6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = await adapted_qdrant_batch_search(relationship_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5992847c-daee-4851-b200-6ef9b5d8d9a7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "id": "cd2094ee-75d2-40a7-bd65-38392a53df4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# relationship_dict = {}\n",
    "\n",
    "# for result_tuple in results:\n",
    "#     uuid, scored_points_list = result_tuple  # Unpack the tuple\n",
    "    \n",
    "#     # Ensure there's a list to collect related items for this uuid\n",
    "#     if uuid not in relationship_dict:\n",
    "#         relationship_dict[uuid] = []\n",
    "    \n",
    "#     for scored_points in scored_points_list:  # Iterate over the list of ScoredPoint lists\n",
    "#         for scored_point in scored_points:  # Iterate over each ScoredPoint object\n",
    "#             if scored_point.score > 0.9:  # Check the score condition\n",
    "#                 # Append a new dictionary to the list associated with the uuid\n",
    "#                 relationship_dict[uuid].append({\n",
    "#                     'collection_name_uuid': uuid,  # Assuming this is the same as the uuid from the result tuple\n",
    "#                     'searched_node_id': scored_point.id,  # Assuming you want the id of the ScoredPoint object\n",
    "#                     'score': scored_point.score,\n",
    "#                     'score_metadata': scored_point.payload,\n",
    "#                     'score_id': scored_point.id,\n",
    "#                 })\n",
    "\n",
    "\n",
    "# relationship_dict={}\n",
    "# for result in results:\n",
    "#     print(result)\n",
    "#     # print(result)\n",
    "#     for i in result:\n",
    "#         if i !=[]:\n",
    "#             # print(i[1])\n",
    "#             if i[1].score > 0.1:\n",
    "#                 print(i)\n",
    "#                 relationship_dict[id].append({\n",
    "#             'collection_name_uuid': uuid,  # The uuid used for the search\n",
    "#             'searched_node_id': item['node_id'],  # The node_id of the hit\n",
    "#             'score': result.score,\n",
    "#             'score_metadata': result.payload,\n",
    "#             'score_id': result.id,\n",
    "#                 })\n",
    "#         else:\n",
    "#             pass\n",
    "                # Only consider hits with a score greater than 0.9\n",
    "#         # Append result information to the relationship_dict under the current id\n",
    "#         relationship_dict[id].append({\n",
    "#             'collection_name_uuid': uuid,  # The uuid used for the search\n",
    "#             'searched_node_id': item['node_id'],  # The node_id of the hit\n",
    "#             'score': result.score,\n",
    "#             'score_metadata': result.payload,\n",
    "#             'score_id': result.id,\n",
    "#         })\n",
    "            \n",
    "            \n",
    "#         print(item['description'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bab83148-8143-4d4c-8aa1-506f64de8f95",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 415,
   "id": "cc98c03c-d1bb-4a58-8227-5e4db7d03676",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       " [[ScoredPoint(id='3a63bd68-0238-4865-9ea1-d7f88f58d6e8', version=0, score=0.3264356832472073, payload=None, vector=None, shard_key=None),\n",
       "   ScoredPoint(id='90cde4a1-7b75-4e61-844f-5a5f5e602690', version=0, score=0.25116409155343133, payload=None, vector=None, shard_key=None),\n",
       "   ScoredPoint(id='18b461fc-af3d-4e67-8cdb-3a02eb42192c', version=0, score=0.21469044119941377, payload=None, vector=None, shard_key=None)]],\n",
       " 'For Britons, keeping pets is an entire way of life.',\n",
       " 'd443269f-44ff-4c10-ab4a-fab9ead0f904')"
      ]
     },
     "execution_count": 415,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "id": "2b4a8d09-2f80-461d-a95b-e943c1d305e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "relationship_d = graph_ready_output(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "id": "12032d28-3f2a-4a29-93f4-3a5b453605dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'83b60dcf-0a04-474f-962b-121cc518e610': [{'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '1531d1cb-3f68-46d7-a366-48d19f26bc93',\n",
       "   'score': 0.9515395831652365,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '3a6f81c3-ecdc-483e-88dd-59068ae332b1'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '58b37c6f-1574-4b93-8ee5-16a22f01aa41',\n",
       "   'score': 0.9383203721228301,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'ff3446b4-59ea-4ef9-969a-4afac7706aa6'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': 'c7bea689-6862-482a-b156-4fc1be3fa07f',\n",
       "   'score': 0.9031738514995704,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '9872ba50-8783-49b4-8fc4-9c53aae7cf57'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '0025c486-d9eb-4820-9b95-f48a97c51d9b',\n",
       "   'score': 0.9999951119054207,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '15d3a8af-4e1a-4c3f-9d29-9c46723fd03a'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '1531d1cb-3f68-46d7-a366-48d19f26bc93',\n",
       "   'score': 1.000000059988928,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b507af42-4ef7-4cb6-8df1-236d9abc4832'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '2b18da1f-bd6f-49a6-b058-0387898dc5dc',\n",
       "   'score': 0.999999997458257,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '3a47799d-afa6-4ff0-b34b-627c81e46059'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '5fddebc9-5092-46b6-9fa3-8c6170eb2e16',\n",
       "   'score': 1.000000011544502,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b0a798cb-39c3-4cab-a67c-778bc4e2df21'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '0d22c2e8-a39b-4c71-abe6-88a90cdfd65d',\n",
       "   'score': 0.9999863092459667,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'c61a5496-bb75-445c-9ae4-a4cca37cd794'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '58b37c6f-1574-4b93-8ee5-16a22f01aa41',\n",
       "   'score': 0.9999319831842581,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'e0a882a8-f8b1-4a9f-b154-fa061eaa684b'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': 'c7bea689-6862-482a-b156-4fc1be3fa07f',\n",
       "   'score': 0.9999999766141177,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b086b7b2-daf2-47f2-9a1e-35812afd9313'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '69dea290-4f26-495f-b6df-c994d6de5f69',\n",
       "   'score': 0.9999667262300376,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '1b10518f-3973-4f79-9dab-3ef238c2cbaa'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '0f371d44-7362-434d-843f-813add8f25c6',\n",
       "   'score': 0.999999377442629,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '59cca039-7f8b-4da5-b67d-51ac14e7c74c'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '1531d1cb-3f68-46d7-a366-48d19f26bc93',\n",
       "   'score': 0.9515395831652365,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'f38b0084-b074-4e47-ae66-cccb9827a87f'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': '58b37c6f-1574-4b93-8ee5-16a22f01aa41',\n",
       "   'score': 0.9383203721228301,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '88635a41-2a86-4bcc-bd34-affe7e302208'},\n",
       "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
       "   'searched_node_id': 'c7bea689-6862-482a-b156-4fc1be3fa07f',\n",
       "   'score': 0.9031738514995704,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '13374d73-bb3b-4e2f-8a94-ff90f0056970'}],\n",
       " '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f': [{'collection_name_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       "   'searched_node_id': '18b461fc-af3d-4e67-8cdb-3a02eb42192c',\n",
       "   'score': 1.0000000492660635,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '504729be-4ffc-493a-9cc8-1ae4ffc799e1'},\n",
       "  {'collection_name_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       "   'searched_node_id': '3a63bd68-0238-4865-9ea1-d7f88f58d6e8',\n",
       "   'score': 0.9999909638430637,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '517b7476-e446-4986-8445-0a2cb14e543f'},\n",
       "  {'collection_name_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       "   'searched_node_id': 'b168a539-5398-4588-b4a4-6963c73b5526',\n",
       "   'score': 0.9999999987186259,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '13a45934-879a-4fe4-90e9-0a5277e56297'},\n",
       "  {'collection_name_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       "   'searched_node_id': '99675528-5a7f-4941-b378-87b03e151cf4',\n",
       "   'score': 0.9999993260326947,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '3fce46e3-8006-4940-bc47-e011408f663c'},\n",
       "  {'collection_name_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       "   'searched_node_id': '6ebecd15-37bd-4553-9c33-89df1fea543c',\n",
       "   'score': 1.0000000153915702,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '939465bc-c763-4122-9328-984c5c59f712'},\n",
       "  {'collection_name_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       "   'searched_node_id': '90cde4a1-7b75-4e61-844f-5a5f5e602690',\n",
       "   'score': 0.9999999726705717,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '3cc5365b-b9e7-46d7-81c8-e125af634e32'},\n",
       "  {'collection_name_uuid': '796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f',\n",
       "   'searched_node_id': 'f866a9f5-3b89-418e-a94b-37923e0c4982',\n",
       "   'score': 0.9999981225768191,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '4aa02775-42e7-41d5-b91f-1f8a764657ed'}],\n",
       " '84fa9b73-12c0-4486-a0eb-3a03a81ca135': [{'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': 'f38b0084-b074-4e47-ae66-cccb9827a87f',\n",
       "   'score': 0.9515395892645451,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '1531d1cb-3f68-46d7-a366-48d19f26bc93'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': '88635a41-2a86-4bcc-bd34-affe7e302208',\n",
       "   'score': 0.93886233238224,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '58b37c6f-1574-4b93-8ee5-16a22f01aa41'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': '13374d73-bb3b-4e2f-8a94-ff90f0056970',\n",
       "   'score': 0.9034716970959398,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'c7bea689-6862-482a-b156-4fc1be3fa07f'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': '7c87ffb5-0359-4421-8e03-61457119ca4b',\n",
       "   'score': 1.0000000150401713,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '49ab2d1b-9163-485f-81c8-8667fc707554'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': 'f38b0084-b074-4e47-ae66-cccb9827a87f',\n",
       "   'score': 1.0000000663828739,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '3a6f81c3-ecdc-483e-88dd-59068ae332b1'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': 'a942b1b8-7ff2-4177-83ef-022bb69affac',\n",
       "   'score': 1.000000017737942,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '5560940a-8504-40bc-94d4-71aa399af5ab'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': '88635a41-2a86-4bcc-bd34-affe7e302208',\n",
       "   'score': 0.9999993598583296,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'ff3446b4-59ea-4ef9-969a-4afac7706aa6'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': '13374d73-bb3b-4e2f-8a94-ff90f0056970',\n",
       "   'score': 0.9999975500994932,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '9872ba50-8783-49b4-8fc4-9c53aae7cf57'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': 'f38b0084-b074-4e47-ae66-cccb9827a87f',\n",
       "   'score': 0.9515395892645451,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b507af42-4ef7-4cb6-8df1-236d9abc4832'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': '88635a41-2a86-4bcc-bd34-affe7e302208',\n",
       "   'score': 0.93886233238224,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'e0a882a8-f8b1-4a9f-b154-fa061eaa684b'},\n",
       "  {'collection_name_uuid': '84fa9b73-12c0-4486-a0eb-3a03a81ca135',\n",
       "   'searched_node_id': '13374d73-bb3b-4e2f-8a94-ff90f0056970',\n",
       "   'score': 0.9034716970959398,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b086b7b2-daf2-47f2-9a1e-35812afd9313'}],\n",
       " '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d': [{'collection_name_uuid': '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       "   'searched_node_id': '504729be-4ffc-493a-9cc8-1ae4ffc799e1',\n",
       "   'score': 1.0000000492660635,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '18b461fc-af3d-4e67-8cdb-3a02eb42192c'},\n",
       "  {'collection_name_uuid': '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       "   'searched_node_id': '517b7476-e446-4986-8445-0a2cb14e543f',\n",
       "   'score': 1.0000000474370807,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '3a63bd68-0238-4865-9ea1-d7f88f58d6e8'},\n",
       "  {'collection_name_uuid': '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       "   'searched_node_id': '13a45934-879a-4fe4-90e9-0a5277e56297',\n",
       "   'score': 0.9999991449822498,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b168a539-5398-4588-b4a4-6963c73b5526'},\n",
       "  {'collection_name_uuid': '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       "   'searched_node_id': '3fce46e3-8006-4940-bc47-e011408f663c',\n",
       "   'score': 0.9999999773199107,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '99675528-5a7f-4941-b378-87b03e151cf4'},\n",
       "  {'collection_name_uuid': '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       "   'searched_node_id': '939465bc-c763-4122-9328-984c5c59f712',\n",
       "   'score': 1.0000000153915702,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '6ebecd15-37bd-4553-9c33-89df1fea543c'},\n",
       "  {'collection_name_uuid': '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       "   'searched_node_id': '3cc5365b-b9e7-46d7-81c8-e125af634e32',\n",
       "   'score': 0.9999999726705717,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '90cde4a1-7b75-4e61-844f-5a5f5e602690'},\n",
       "  {'collection_name_uuid': '3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d',\n",
       "   'searched_node_id': '4aa02775-42e7-41d5-b91f-1f8a764657ed',\n",
       "   'score': 1.0000000557427815,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'f866a9f5-3b89-418e-a94b-37923e0c4982'}],\n",
       " '92562711-f2a9-4ce6-9c7d-d5226080f982': [{'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': '15d3a8af-4e1a-4c3f-9d29-9c46723fd03a',\n",
       "   'score': 1.0000000076286752,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '0025c486-d9eb-4820-9b95-f48a97c51d9b'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'b507af42-4ef7-4cb6-8df1-236d9abc4832',\n",
       "   'score': 1.000000059988928,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '1531d1cb-3f68-46d7-a366-48d19f26bc93'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': '3a47799d-afa6-4ff0-b34b-627c81e46059',\n",
       "   'score': 0.999999997458257,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '2b18da1f-bd6f-49a6-b058-0387898dc5dc'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'b0a798cb-39c3-4cab-a67c-778bc4e2df21',\n",
       "   'score': 1.000000011544502,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '5fddebc9-5092-46b6-9fa3-8c6170eb2e16'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'c61a5496-bb75-445c-9ae4-a4cca37cd794',\n",
       "   'score': 0.9999999990559993,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '0d22c2e8-a39b-4c71-abe6-88a90cdfd65d'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'e0a882a8-f8b1-4a9f-b154-fa061eaa684b',\n",
       "   'score': 0.9999325716139726,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '58b37c6f-1574-4b93-8ee5-16a22f01aa41'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'b086b7b2-daf2-47f2-9a1e-35812afd9313',\n",
       "   'score': 0.9999999766141177,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'c7bea689-6862-482a-b156-4fc1be3fa07f'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': '1b10518f-3973-4f79-9dab-3ef238c2cbaa',\n",
       "   'score': 1.000000063164407,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '69dea290-4f26-495f-b6df-c994d6de5f69'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': '59cca039-7f8b-4da5-b67d-51ac14e7c74c',\n",
       "   'score': 0.9999999750870483,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '0f371d44-7362-434d-843f-813add8f25c6'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'b507af42-4ef7-4cb6-8df1-236d9abc4832',\n",
       "   'score': 0.9515395831652365,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '3a6f81c3-ecdc-483e-88dd-59068ae332b1'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'e0a882a8-f8b1-4a9f-b154-fa061eaa684b',\n",
       "   'score': 0.9382967722184876,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'ff3446b4-59ea-4ef9-969a-4afac7706aa6'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'b086b7b2-daf2-47f2-9a1e-35812afd9313',\n",
       "   'score': 0.9031738514995704,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '9872ba50-8783-49b4-8fc4-9c53aae7cf57'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'b507af42-4ef7-4cb6-8df1-236d9abc4832',\n",
       "   'score': 0.9515395831652365,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'f38b0084-b074-4e47-ae66-cccb9827a87f'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'e0a882a8-f8b1-4a9f-b154-fa061eaa684b',\n",
       "   'score': 0.9382967722184876,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '88635a41-2a86-4bcc-bd34-affe7e302208'},\n",
       "  {'collection_name_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982',\n",
       "   'searched_node_id': 'b086b7b2-daf2-47f2-9a1e-35812afd9313',\n",
       "   'score': 0.9031738514995704,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '13374d73-bb3b-4e2f-8a94-ff90f0056970'}],\n",
       " 'd0c2bd1c-7cec-4e5a-af13-dbb655623dda': [],\n",
       " 'ccf6645e-9fad-441b-821d-b1d47b93ebca': [],\n",
       " '6fb85c94-f488-4f31-8e7c-a5905580a78c': [{'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '3a6f81c3-ecdc-483e-88dd-59068ae332b1',\n",
       "   'score': 0.9515395892645451,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '1531d1cb-3f68-46d7-a366-48d19f26bc93'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': 'ff3446b4-59ea-4ef9-969a-4afac7706aa6',\n",
       "   'score': 0.9388291030193505,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '58b37c6f-1574-4b93-8ee5-16a22f01aa41'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '9872ba50-8783-49b4-8fc4-9c53aae7cf57',\n",
       "   'score': 0.9031739051820826,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'c7bea689-6862-482a-b156-4fc1be3fa07f'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '3a6f81c3-ecdc-483e-88dd-59068ae332b1',\n",
       "   'score': 0.9512102439110068,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b507af42-4ef7-4cb6-8df1-236d9abc4832'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': 'ff3446b4-59ea-4ef9-969a-4afac7706aa6',\n",
       "   'score': 0.9388291030193505,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'e0a882a8-f8b1-4a9f-b154-fa061eaa684b'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '9872ba50-8783-49b4-8fc4-9c53aae7cf57',\n",
       "   'score': 0.9031739051820826,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'b086b7b2-daf2-47f2-9a1e-35812afd9313'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '49ab2d1b-9163-485f-81c8-8667fc707554',\n",
       "   'score': 1.0000000150401713,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '7c87ffb5-0359-4421-8e03-61457119ca4b'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '3a6f81c3-ecdc-483e-88dd-59068ae332b1',\n",
       "   'score': 1.0000000663828739,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'f38b0084-b074-4e47-ae66-cccb9827a87f'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '5560940a-8504-40bc-94d4-71aa399af5ab',\n",
       "   'score': 1.000000017737942,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': 'a942b1b8-7ff2-4177-83ef-022bb69affac'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': 'ff3446b4-59ea-4ef9-969a-4afac7706aa6',\n",
       "   'score': 1.000000001710429,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '88635a41-2a86-4bcc-bd34-affe7e302208'},\n",
       "  {'collection_name_uuid': '6fb85c94-f488-4f31-8e7c-a5905580a78c',\n",
       "   'searched_node_id': '9872ba50-8783-49b4-8fc4-9c53aae7cf57',\n",
       "   'score': 1.0000000355409906,\n",
       "   'score_metadata': None,\n",
       "   'original_id_for_search': '13374d73-bb3b-4e2f-8a94-ff90f0056970'}],\n",
       " '67200cb4-16fc-40f9-b231-c9e720aeb14a': []}"
      ]
     },
     "execution_count": 426,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "relationship_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "id": "42e6095b-7b75-4e9d-96c2-f45ca5bdf4bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import pytest\n",
    "\n",
    "def test_connect_nodes_in_graph():\n",
    "    # Create a mock graph\n",
    "    G = nx.Graph()\n",
    "    \n",
    "    # Add nodes that will be referenced in the relationship_dict\n",
    "    # Use the 'id' attribute to match nodes, as used in the connect_nodes_in_graph function\n",
    "    G.add_node(\"node1\", id=\"1531d1cb-3f68-46d7-a366-48d19f26bc93\")\n",
    "    G.add_node(\"node2\", id=\"58b37c6f-1574-4b93-8ee5-16a22f01aa41\")\n",
    "\n",
    "    # Define the relationship_dict based on your test set\n",
    "    relationship_dict = {\n",
    "        '83b60dcf-0a04-474f-962b-121cc518e610': [\n",
    "            {\n",
    "                'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
    "                'searched_node_id': '1531d1cb-3f68-46d7-a366-48d19f26bc93',  # Matches 'node1'\n",
    "                'score': 0.9515395831652365,\n",
    "                'score_metadata': None,\n",
    "                'score_id': '58b37c6f-1574-4b93-8ee5-16a22f01aa41',  # Matches 'node2'\n",
    "            }\n",
    "        ]\n",
    "    }\n",
    "\n",
    "    # Call the function under test\n",
    "    connect_nodes_in_graph(G, relationship_dict)\n",
    "\n",
    "    # Assert that the edge has been created as expected between 'node1' and 'node2'\n",
    "    assert G.has_edge(\"node1\", \"node2\")\n",
    "    assert G[\"node1\"][\"node2\"][\"weight\"] == 0.9515395831652365\n",
    "    assert G[\"node1\"][\"node2\"][\"score_metadata\"] is None\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29b1bbe8-de2f-4b0c-9ae1-16e5547e1544",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "id": "f66f9940-9792-4600-a804-ab649384f6d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_connect_nodes_in_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "id": "97302500-241e-41b3-9355-4523bcb4d01b",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def connect_nodes_in_graph(graph, relationship_dict):\n",
    "    \"\"\"\n",
    "    For each relationship in relationship_dict, check if both nodes exist in the graph based on node attributes.\n",
    "    If they do, create a connection (edge) between them.\n",
    "\n",
    "    :param graph: A NetworkX graph object\n",
    "    :param relationship_dict: A dictionary containing relationships between nodes\n",
    "    \"\"\"\n",
    "    for id, relationships in relationship_dict.items():\n",
    "        for relationship in relationships:\n",
    "            searched_node_attr_id = relationship['searched_node_id']\n",
    "            print(searched_node_attr_id)\n",
    "            score_attr_id = relationship['original_id_for_search']\n",
    "            score = relationship['score']\n",
    "            \n",
    "\n",
    "            # Initialize node keys for both searched_node and score_node\n",
    "            searched_node_key, score_node_key = None, None\n",
    "\n",
    "            # Find nodes in the graph that match the searched_node_id and score_id from their attributes\n",
    "            for node, attrs in graph.nodes(data=True):\n",
    "                if 'id' in attrs:  # Ensure there is an 'id' attribute\n",
    "                    if attrs['id'] == searched_node_attr_id:\n",
    "                        searched_node_key = node\n",
    "                    elif attrs['id'] == score_attr_id:\n",
    "                        score_node_key = node\n",
    "\n",
    "                # If both nodes are found, no need to continue checking other nodes\n",
    "                if searched_node_key and score_node_key:\n",
    "                    break\n",
    "\n",
    "            # Check if both nodes were found in the graph\n",
    "            if searched_node_key is not None and score_node_key is not None:\n",
    "                print(searched_node_key)\n",
    "                print(score_node_key)\n",
    "                # If both nodes exist, create an edge between them\n",
    "                # You can customize the edge attributes as needed, here we use 'score' as an attribute\n",
    "                graph.add_edge(searched_node_key, score_node_key, weight=score, score_metadata=relationship.get('score_metadata'))\n",
    "\n",
    "    return graph\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9266a9f7-06ce-4586-acd9-7c70056675f3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "id": "450ba952-192e-40aa-a51e-0bf0d28b6e12",
   "metadata": {},
   "outputs": [],
   "source": [
    "rel_s = {'83b60dcf-0a04-474f-962b-121cc518e610': [{'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
    "   'searched_node_id': '1531d1cb-3f68-46d7-a366-48d19f26bc93',\n",
    "   'score': 0.9515395831652365,\n",
    "   'score_metadata': None,\n",
    "   'score_id': '1531d1cb-3f68-46d7-a366-48d19f26bc93'},\n",
    "  {'collection_name_uuid': '83b60dcf-0a04-474f-962b-121cc518e610',\n",
    "   'searched_node_id': '58b37c6f-1574-4b93-8ee5-16a22f01aa41',\n",
    "   'score': 0.9383203721228301,\n",
    "   'score_metadata': None,\n",
    "   'score_id': '58b37c6f-1574-4b93-8ee5-16a22f01aa41'}]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "id": "750c651c-2b95-44ae-83e3-4ae4257781e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                                                                                                                                                                                                                                 Node 1 ID  \\\n",
      "108  Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 0025c486-d9eb-4820-9b95-f48a97c51d9b   \n",
      "\n",
      "                                                                                                                                                                                                                                                                                 Node 2 ID  \\\n",
      "108  Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 15d3a8af-4e1a-4c3f-9d29-9c46723fd03a   \n",
      "\n",
      "       Weight  \\\n",
      "108  0.999995   \n",
      "\n",
      "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Node 1 Metadata  \\\n",
      "108  {'created_at': '2024-03-04 20:28:37', 'updated_at': '2024-03-04 20:28:37', 'description': 'Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.', 'category': 'person', 'memory_type': 'episodic', 'layer_uuid': 'd0fde4d0-c358-44b2-b698-a19314a336e0', 'layer_decomposition_uuid': '83b60dcf-0a04-474f-962b-121cc518e610', 'id': '0025c486-d9eb-4820-9b95-f48a97c51d9b', 'type': 'detail'}   \n",
      "\n",
      "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Node 2 Metadata  \\\n",
      "108  {'created_at': '2024-03-04 20:28:37', 'updated_at': '2024-03-04 20:28:37', 'description': 'Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.', 'category': 'person', 'memory_type': 'episodic', 'layer_uuid': 'd0fde4d0-c358-44b2-b698-a19314a336e0', 'layer_decomposition_uuid': '92562711-f2a9-4ce6-9c7d-d5226080f982', 'id': '15d3a8af-4e1a-4c3f-9d29-9c46723fd03a', 'type': 'detail'}   \n",
      "\n",
      "    Edge Score Metadata  \n",
      "108                None  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import networkx as nx\n",
    "\n",
    "pd.set_option('display.max_rows', None)  # Show all rows\n",
    "pd.set_option('display.max_columns', None)  # Show all columns\n",
    "pd.set_option('display.width', None)  # Use maximum possible width to display\n",
    "pd.set_option('display.max_colwidth', None)  # Display full content of each column\n",
    "\n",
    "\n",
    "# Assuming G is your graph object already populated with nodes and edges by connect_nodes_in_graph\n",
    "\n",
    "# Step 1: Traverse the graph and collect data\n",
    "data = []\n",
    "for (node1, node2, attr) in CONNECTED_GRAPH.edges(data=True):\n",
    "    node1_data = CONNECTED_GRAPH.nodes[node1]  # Get metadata for node1\n",
    "    node2_data = CONNECTED_GRAPH.nodes[node2]  # Get metadata for node2\n",
    "    \n",
    "    # Collect information: node IDs, edge weight, and any other relevant metadata\n",
    "    edge_info = {\n",
    "        'Node 1 ID': node1,\n",
    "        'Node 2 ID': node2,\n",
    "        'Weight': attr.get('weight', None),  # Get the weight of the edge\n",
    "        'Node 1 Metadata': node1_data,  # Assuming there's meaningful metadata in the graph's nodes\n",
    "        'Node 2 Metadata': node2_data,\n",
    "        'Edge Score Metadata': attr.get('score_metadata', None)  # Edge-specific metadata if available\n",
    "    }\n",
    "    data.append(edge_info)\n",
    "\n",
    "# Step 2: Create a pandas DataFrame from the collected data\n",
    "df = pd.DataFrame(data)\n",
    "df_filtered = df.dropna(subset=['Weight'])\n",
    "\n",
    "# Display the DataFrame\n",
    "print(df_filtered.head(1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 429,
   "id": "2c344176-8f70-4a0c-b528-0e85ed810984",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "0025c486-d9eb-4820-9b95-f48a97c51d9b\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 0025c486-d9eb-4820-9b95-f48a97c51d9b\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 15d3a8af-4e1a-4c3f-9d29-9c46723fd03a\n",
      "1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "2b18da1f-bd6f-49a6-b058-0387898dc5dc\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 2b18da1f-bd6f-49a6-b058-0387898dc5dc\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 3a47799d-afa6-4ff0-b34b-627c81e46059\n",
      "5fddebc9-5092-46b6-9fa3-8c6170eb2e16\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 5fddebc9-5092-46b6-9fa3-8c6170eb2e16\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b0a798cb-39c3-4cab-a67c-778bc4e2df21\n",
      "0d22c2e8-a39b-4c71-abe6-88a90cdfd65d\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 0d22c2e8-a39b-4c71-abe6-88a90cdfd65d\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - c61a5496-bb75-445c-9ae4-a4cca37cd794\n",
      "58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "69dea290-4f26-495f-b6df-c994d6de5f69\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 69dea290-4f26-495f-b6df-c994d6de5f69\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 1b10518f-3973-4f79-9dab-3ef238c2cbaa\n",
      "0f371d44-7362-434d-843f-813add8f25c6\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 0f371d44-7362-434d-843f-813add8f25c6\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 59cca039-7f8b-4da5-b67d-51ac14e7c74c\n",
      "1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "18b461fc-af3d-4e67-8cdb-3a02eb42192c\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 18b461fc-af3d-4e67-8cdb-3a02eb42192c\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 504729be-4ffc-493a-9cc8-1ae4ffc799e1\n",
      "3a63bd68-0238-4865-9ea1-d7f88f58d6e8\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 3a63bd68-0238-4865-9ea1-d7f88f58d6e8\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 517b7476-e446-4986-8445-0a2cb14e543f\n",
      "b168a539-5398-4588-b4a4-6963c73b5526\n",
      "XL bully, a type of dog that attacked Izzy and Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - b168a539-5398-4588-b4a4-6963c73b5526\n",
      "XL bully, a type of dog that attacked Izzy and Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 13a45934-879a-4fe4-90e9-0a5277e56297\n",
      "99675528-5a7f-4941-b378-87b03e151cf4\n",
      "Marie Hay, owner of a Siberian Husky named Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 99675528-5a7f-4941-b378-87b03e151cf4\n",
      "Marie Hay, owner of a Siberian Husky named Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 3fce46e3-8006-4940-bc47-e011408f663c\n",
      "6ebecd15-37bd-4553-9c33-89df1fea543c\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 6ebecd15-37bd-4553-9c33-89df1fea543c\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 939465bc-c763-4122-9328-984c5c59f712\n",
      "90cde4a1-7b75-4e61-844f-5a5f5e602690\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 90cde4a1-7b75-4e61-844f-5a5f5e602690\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 3cc5365b-b9e7-46d7-81c8-e125af634e32\n",
      "f866a9f5-3b89-418e-a94b-37923e0c4982\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - f866a9f5-3b89-418e-a94b-37923e0c4982\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 4aa02775-42e7-41d5-b91f-1f8a764657ed\n",
      "f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "7c87ffb5-0359-4421-8e03-61457119ca4b\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 7c87ffb5-0359-4421-8e03-61457119ca4b\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 49ab2d1b-9163-485f-81c8-8667fc707554\n",
      "f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "a942b1b8-7ff2-4177-83ef-022bb69affac\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - a942b1b8-7ff2-4177-83ef-022bb69affac\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 5560940a-8504-40bc-94d4-71aa399af5ab\n",
      "88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "504729be-4ffc-493a-9cc8-1ae4ffc799e1\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 504729be-4ffc-493a-9cc8-1ae4ffc799e1\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 18b461fc-af3d-4e67-8cdb-3a02eb42192c\n",
      "517b7476-e446-4986-8445-0a2cb14e543f\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 517b7476-e446-4986-8445-0a2cb14e543f\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 3a63bd68-0238-4865-9ea1-d7f88f58d6e8\n",
      "13a45934-879a-4fe4-90e9-0a5277e56297\n",
      "XL bully, a type of dog that attacked Izzy and Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 13a45934-879a-4fe4-90e9-0a5277e56297\n",
      "XL bully, a type of dog that attacked Izzy and Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - b168a539-5398-4588-b4a4-6963c73b5526\n",
      "3fce46e3-8006-4940-bc47-e011408f663c\n",
      "Marie Hay, owner of a Siberian Husky named Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 3fce46e3-8006-4940-bc47-e011408f663c\n",
      "Marie Hay, owner of a Siberian Husky named Naevia. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 99675528-5a7f-4941-b378-87b03e151cf4\n",
      "939465bc-c763-4122-9328-984c5c59f712\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 939465bc-c763-4122-9328-984c5c59f712\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 6ebecd15-37bd-4553-9c33-89df1fea543c\n",
      "3cc5365b-b9e7-46d7-81c8-e125af634e32\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 3cc5365b-b9e7-46d7-81c8-e125af634e32\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - 90cde4a1-7b75-4e61-844f-5a5f5e602690\n",
      "4aa02775-42e7-41d5-b91f-1f8a764657ed\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 3f7bb086-5ffc-4f61-8b5d-dcd2e708d01d - 4aa02775-42e7-41d5-b91f-1f8a764657ed\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 796b74e7-f6a6-4d0e-a4d3-4e72212f8b1f - f866a9f5-3b89-418e-a94b-37923e0c4982\n",
      "15d3a8af-4e1a-4c3f-9d29-9c46723fd03a\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 15d3a8af-4e1a-4c3f-9d29-9c46723fd03a\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 0025c486-d9eb-4820-9b95-f48a97c51d9b\n",
      "b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "3a47799d-afa6-4ff0-b34b-627c81e46059\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 3a47799d-afa6-4ff0-b34b-627c81e46059\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 2b18da1f-bd6f-49a6-b058-0387898dc5dc\n",
      "b0a798cb-39c3-4cab-a67c-778bc4e2df21\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b0a798cb-39c3-4cab-a67c-778bc4e2df21\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 5fddebc9-5092-46b6-9fa3-8c6170eb2e16\n",
      "c61a5496-bb75-445c-9ae4-a4cca37cd794\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - c61a5496-bb75-445c-9ae4-a4cca37cd794\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 0d22c2e8-a39b-4c71-abe6-88a90cdfd65d\n",
      "e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "1b10518f-3973-4f79-9dab-3ef238c2cbaa\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 1b10518f-3973-4f79-9dab-3ef238c2cbaa\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 69dea290-4f26-495f-b6df-c994d6de5f69\n",
      "59cca039-7f8b-4da5-b67d-51ac14e7c74c\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - 59cca039-7f8b-4da5-b67d-51ac14e7c74c\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 0f371d44-7362-434d-843f-813add8f25c6\n",
      "b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 13374d73-bb3b-4e2f-8a94-ff90f0056970\n",
      "3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 1531d1cb-3f68-46d7-a366-48d19f26bc93\n",
      "ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - 58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 83b60dcf-0a04-474f-962b-121cc518e610 - c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b507af42-4ef7-4cb6-8df1-236d9abc4832\n",
      "ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - e0a882a8-f8b1-4a9f-b154-fa061eaa684b\n",
      "9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 92562711-f2a9-4ce6-9c7d-d5226080f982 - b086b7b2-daf2-47f2-9a1e-35812afd9313\n",
      "49ab2d1b-9163-485f-81c8-8667fc707554\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 49ab2d1b-9163-485f-81c8-8667fc707554\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 7c87ffb5-0359-4421-8e03-61457119ca4b\n",
      "3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 3a6f81c3-ecdc-483e-88dd-59068ae332b1\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - f38b0084-b074-4e47-ae66-cccb9827a87f\n",
      "5560940a-8504-40bc-94d4-71aa399af5ab\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 5560940a-8504-40bc-94d4-71aa399af5ab\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - a942b1b8-7ff2-4177-83ef-022bb69affac\n",
      "ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - ff3446b4-59ea-4ef9-969a-4afac7706aa6\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 88635a41-2a86-4bcc-bd34-affe7e302208\n",
      "9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 6fb85c94-f488-4f31-8e7c-a5905580a78c - 9872ba50-8783-49b4-8fc4-9c53aae7cf57\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills. - d0fde4d0-c358-44b2-b698-a19314a336e0  - 84fa9b73-12c0-4486-a0eb-3a03a81ca135 - 13374d73-bb3b-4e2f-8a94-ff90f0056970\n"
     ]
    }
   ],
   "source": [
    "CONNECTED_GRAPH = connect_nodes_in_graph(R, relationship_d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e86c07ad-0597-48ad-a9bb-f99d45297beb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "id": "fce71784-66c3-4e96-8dbe-01b52478312d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The graph has 142 edges.\n"
     ]
    }
   ],
   "source": [
    "num_edges = CONNECTED_GRAPH.number_of_edges()\n",
    "print(f\"The graph has {num_edges} edges.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "id": "1497b257-70f3-4eb1-94f5-fa234eafd574",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    source                 target relationship description\n",
      "0  user123               Temporal      created         NaN\n",
      "1  user123             Positional      created         NaN\n",
      "2  user123           Propositions      created         NaN\n",
      "3  user123        Personalization      created         NaN\n",
      "4  user123  Natural Language Text      created         NaN\n"
     ]
    }
   ],
   "source": [
    "edges = nx.to_pandas_edgelist(CONNECTED_GRAPH)\n",
    "print(edges.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "id": "6e2c0c8b-bbcf-43f1-a980-8122e195b48c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matching Node Keys: []\n"
     ]
    }
   ],
   "source": [
    "target_id = '31bf1fcd-1b58-4402-aa51-66f9a5ae09e9'\n",
    "\n",
    "# Find the node key(s) with this ID\n",
    "matching_nodes = [node for node, attrs in CONNECTED_GRAPH.nodes(data=True) if attrs.get('id') == target_id]\n",
    "\n",
    "print(\"Matching Node Keys:\", matching_nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "id": "d1197355-706a-4b53-8238-3b599e2723c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No node found with ID 31bf1fcd-1b58-4402-aa51-66f9a5ae09e9\n"
     ]
    }
   ],
   "source": [
    "target_id = '31bf1fcd-1b58-4402-aa51-66f9a5ae09e9'\n",
    "\n",
    "# Find the node key(s) with this ID (assuming IDs are unique, there should be only one match)\n",
    "matching_node_key = None\n",
    "for node, attrs in CONNECTED_GRAPH.nodes(data=True):\n",
    "    if attrs.get('id') == target_id:\n",
    "        matching_node_key = node\n",
    "        break\n",
    "\n",
    "# If a matching node is found, list all nodes it's connected to\n",
    "if matching_node_key is not None:\n",
    "    connected_nodes = set([connected_node for _, connected_node in CONNECTED_GRAPH.edges(matching_node_key)])\n",
    "    print(f\"Node with ID {target_id} (key: {matching_node_key}) connects to nodes: {connected_nodes}\")\n",
    "else:\n",
    "    print(f\"No node found with ID {target_id}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "id": "488dfddc-3774-4f8c-9478-117b94fc70f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <iframe id=\"2d690ffe-ece8-42b7-bc46-6d83be2ea182\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=f14855a5888d4611b05a160d4ca444b4&type=arrow&viztoken=dc57ebed-4930-4a3e-ab45-9cdb5db57f4a&usertag=1daaf574-pygraphistry-0.33.0&splashAfter=1709657655&info=true\"\n",
       "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
       "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
       "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
       "                    \n",
       "            >\n",
       "            </iframe>\n",
       "        \n",
       "            <script>\n",
       "                try {\n",
       "                  $(\"#2d690ffe-ece8-42b7-bc46-6d83be2ea182\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
       "                } catch (e) { console.error('exn catching scroll', e); }\n",
       "            </script>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 433,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import graphistry\n",
    "import pandas as pd\n",
    "\n",
    "# Assuming Graphistry is already configured with API key\n",
    "# graphistry.register(api=3, username='your_username', password='your_password')\n",
    "\n",
    "# Convert NetworkX graph to a Pandas DataFrame\n",
    "edges = nx.to_pandas_edgelist(CONNECTED_GRAPH)\n",
    "graphistry.register(api=3, username='Vasilije1990', password='Q@HLdgv5SMUsGxy') \n",
    "\n",
    "# Visualize the graph\n",
    "graphistry.edges(edges, 'source', 'target').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11afb7e6-165d-46d3-8a09-7673bf7d6e8e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50b67330-db2f-45ab-86a9-7170564c56de",
   "metadata": {},
   "outputs": [],
   "source": [
    "## SEARCH \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36354c1f-17c3-419a-9c71-4618d2bde8ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# pre filtering\n",
    "# each semantic layer -> make categories, dimensions, on semantic layer given on the LLM\n",
    "# weights need to be used topk and cutoff\n",
    "# entry through entities\n",
    "# combine unstructured and structured\n",
    "# address / entrypoint node/ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cfe6574-e079-495b-b820-1b361d62c25d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17d27c7b-5a6d-4ef4-b785-76f5c239afc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# add meaning to relationships\n",
    "# check interlayer relationships\n",
    "# move shit to prod"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de42394d-7a4c-46ac-9a08-6fb2911c11b9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c33237a-fee9-4480-81cc-d17b5ec497bf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "id": "1992d379-9dab-4839-a33a-21861c8c8864",
   "metadata": {},
   "outputs": [],
   "source": [
    "async def find_relevant_chunks(query,unique_layer_uuids):\n",
    "    out = []\n",
    "    query = await get_embeddings(query)\n",
    "    # print(query)\n",
    "    for id in unique_layer_uuids:\n",
    "        result = qdrant_search(id, query[0])\n",
    "\n",
    "        if result:\n",
    "            result_ = [ result_.id for result_ in result]\n",
    "            score_ = [ result_.score for result_ in result]\n",
    "            \n",
    "            out.append([result_, score_])\n",
    "\n",
    "    return out\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "id": "139bb41c-ef21-4558-9142-eae912a56c58",
   "metadata": {},
   "outputs": [],
   "source": [
    "val = await find_relevant_chunks('uk', unique_layer_uuids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "id": "2e81754a-2a2c-4a51-a678-5fff298d9fe7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[['c7bea689-6862-482a-b156-4fc1be3fa07f', '58b37c6f-1574-4b93-8ee5-16a22f01aa41', '69dea290-4f26-495f-b6df-c994d6de5f69'], [0.10496980604641798, 0.08607680886252467, 0.08296533762140104]], [['6ebecd15-37bd-4553-9c33-89df1fea543c', 'b168a539-5398-4588-b4a4-6963c73b5526', '99675528-5a7f-4941-b378-87b03e151cf4'], [0.10060454880247681, 0.09422832938531824, 0.09048113259735407]], [['13374d73-bb3b-4e2f-8a94-ff90f0056970', '88635a41-2a86-4bcc-bd34-affe7e302208', '7c87ffb5-0359-4421-8e03-61457119ca4b'], [0.1105763743356234, 0.08263447659128495, 0.07497919232031232]], [['939465bc-c763-4122-9328-984c5c59f712', '13a45934-879a-4fe4-90e9-0a5277e56297', '3fce46e3-8006-4940-bc47-e011408f663c'], [0.10060454880247681, 0.09420080324132485, 0.09046091116775384]], [['b086b7b2-daf2-47f2-9a1e-35812afd9313', 'e0a882a8-f8b1-4a9f-b154-fa061eaa684b', '1b10518f-3973-4f79-9dab-3ef238c2cbaa'], [0.10496980604641798, 0.08606484768040133, 0.0831070520843658]], [['4dd3cb46-ca57-46ca-9781-e8b917491720', '7ee6f0a7-cf4a-4659-a886-1f0b40d75b97', 'bce65459-262a-4a6b-a319-5deb8e6d0d96'], [0.11607958908310784, 0.0879278593824074, 0.08666557927817456]], [['f800260d-6de1-4a5f-a501-f5d58f3258c3', '9dce0831-6e87-4fd9-93ba-e6944b22929b', 'a75bae98-0748-4c4d-b807-5d3e19a9d638'], [0.07682790557037841, 0.0752726545054383, 0.06904576598032586]], [['2d588b35-062e-44e7-bbb2-1642ba0411e3', '6a34c9bd-0dee-4db0-8258-86d2dd87303d', '630b58dd-65f6-4d55-b3fc-67b59d696b4c'], [0.08260691278813655, 0.0642977938657605, 0.06420510357558001]], [['9872ba50-8783-49b4-8fc4-9c53aae7cf57', 'ff3446b4-59ea-4ef9-969a-4afac7706aa6', '49ab2d1b-9163-485f-81c8-8667fc707554'], [0.11060872514096692, 0.08261564014738146, 0.07497919232031232]]]\n"
     ]
    }
   ],
   "source": [
    "print(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "id": "aedb2c4b-1af6-4663-8a7d-cf8bbfb3dc77",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def fetch_context(CONNECTED_GRAPH, id):\n",
    "    relevant_context = []\n",
    "    for n,attr in CONNECTED_GRAPH.nodes(data=True):\n",
    "        if id in n:\n",
    "            for n_, attr_ in CONNECTED_GRAPH.nodes(data=True):\n",
    "                relevant_layer = attr['layer_uuid']\n",
    "\n",
    "                if attr_.get('layer_uuid') == relevant_layer:\n",
    "                    print(attr_['description'])\n",
    "                    relevant_context.append(attr_['description'])\n",
    "\n",
    "    return relevant_context\n",
    "\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "id": "4f17da0f-749e-4543-9213-24bdaa31a85b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c7bea689-6862-482a-b156-4fc1be3fa07f\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy.\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin.\n",
      "XL bully, a type of dog that attacked Izzy and Naevia.\n",
      "Marie Hay, owner of a Siberian Husky named Naevia.\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay.\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy.\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin.\n",
      "XL bully, a type of dog that attacked Izzy and Naevia.\n",
      "Marie Hay, owner of a Siberian Husky named Naevia.\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay.\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.\n",
      "58b37c6f-1574-4b93-8ee5-16a22f01aa41\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy.\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin.\n",
      "XL bully, a type of dog that attacked Izzy and Naevia.\n",
      "Marie Hay, owner of a Siberian Husky named Naevia.\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay.\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy.\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin.\n",
      "XL bully, a type of dog that attacked Izzy and Naevia.\n",
      "Marie Hay, owner of a Siberian Husky named Naevia.\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay.\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.\n",
      "69dea290-4f26-495f-b6df-c994d6de5f69\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy.\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin.\n",
      "XL bully, a type of dog that attacked Izzy and Naevia.\n",
      "Marie Hay, owner of a Siberian Husky named Naevia.\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay.\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.\n",
      "Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.\n",
      "Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.\n",
      "A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\n",
      "The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.\n",
      "An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.\n",
      "Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.\n",
      "Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.\n",
      "A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.\n",
      "The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.\n",
      "Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.\n",
      "Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.\n",
      "An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.\n",
      "Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\n",
      "Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.\n",
      "Lee Parkin, a 50-year-old man, owner of Izzy.\n",
      "Izzy, a terrier-spaniel cross owned by Lee Parkin.\n",
      "XL bully, a type of dog that attacked Izzy and Naevia.\n",
      "Marie Hay, owner of a Siberian Husky named Naevia.\n",
      "Naevia, a seven-year-old Siberian Husky owned by Marie Hay.\n",
      "Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\n",
      "Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.\n"
     ]
    }
   ],
   "source": [
    "context = []\n",
    "\n",
    "for v in val[0][0]:\n",
    "    print(v)\n",
    "    context.append(fetch_context(CONNECTED_GRAPH, id=v))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "id": "1007d1a9-19c4-4d02-a187-ad7c1c514e9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.',\n",
       "  'Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.',\n",
       "  \"A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\",\n",
       "  'The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.',\n",
       "  'An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.',\n",
       "  'Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.',\n",
       "  'Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.',\n",
       "  'A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.',\n",
       "  'The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.',\n",
       "  'Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.',\n",
       "  'Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.',\n",
       "  'An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.',\n",
       "  \"Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\",\n",
       "  'Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.',\n",
       "  'Lee Parkin, a 50-year-old man, owner of Izzy.',\n",
       "  'Izzy, a terrier-spaniel cross owned by Lee Parkin.',\n",
       "  'XL bully, a type of dog that attacked Izzy and Naevia.',\n",
       "  'Marie Hay, owner of a Siberian Husky named Naevia.',\n",
       "  'Naevia, a seven-year-old Siberian Husky owned by Marie Hay.',\n",
       "  \"Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\",\n",
       "  'Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.',\n",
       "  'Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.',\n",
       "  'Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.',\n",
       "  \"A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\",\n",
       "  'The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.',\n",
       "  'An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.',\n",
       "  'Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.',\n",
       "  'Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.',\n",
       "  'A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.',\n",
       "  'The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.',\n",
       "  'Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.',\n",
       "  'Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.',\n",
       "  'An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.',\n",
       "  \"Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\",\n",
       "  'Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.',\n",
       "  'Lee Parkin, a 50-year-old man, owner of Izzy.',\n",
       "  'Izzy, a terrier-spaniel cross owned by Lee Parkin.',\n",
       "  'XL bully, a type of dog that attacked Izzy and Naevia.',\n",
       "  'Marie Hay, owner of a Siberian Husky named Naevia.',\n",
       "  'Naevia, a seven-year-old Siberian Husky owned by Marie Hay.',\n",
       "  \"Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\",\n",
       "  'Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.'],\n",
       " ['Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.',\n",
       "  'Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.',\n",
       "  \"A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\",\n",
       "  'The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.',\n",
       "  'An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.',\n",
       "  'Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.',\n",
       "  'Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.',\n",
       "  'A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.',\n",
       "  'The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.',\n",
       "  'Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.',\n",
       "  'Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.',\n",
       "  'An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.',\n",
       "  \"Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\",\n",
       "  'Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.',\n",
       "  'Lee Parkin, a 50-year-old man, owner of Izzy.',\n",
       "  'Izzy, a terrier-spaniel cross owned by Lee Parkin.',\n",
       "  'XL bully, a type of dog that attacked Izzy and Naevia.',\n",
       "  'Marie Hay, owner of a Siberian Husky named Naevia.',\n",
       "  'Naevia, a seven-year-old Siberian Husky owned by Marie Hay.',\n",
       "  \"Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\",\n",
       "  'Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.',\n",
       "  'Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.',\n",
       "  'Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.',\n",
       "  \"A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\",\n",
       "  'The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.',\n",
       "  'An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.',\n",
       "  'Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.',\n",
       "  'Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.',\n",
       "  'A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.',\n",
       "  'The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.',\n",
       "  'Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.',\n",
       "  'Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.',\n",
       "  'An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.',\n",
       "  \"Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\",\n",
       "  'Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.',\n",
       "  'Lee Parkin, a 50-year-old man, owner of Izzy.',\n",
       "  'Izzy, a terrier-spaniel cross owned by Lee Parkin.',\n",
       "  'XL bully, a type of dog that attacked Izzy and Naevia.',\n",
       "  'Marie Hay, owner of a Siberian Husky named Naevia.',\n",
       "  'Naevia, a seven-year-old Siberian Husky owned by Marie Hay.',\n",
       "  \"Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\",\n",
       "  'Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.'],\n",
       " ['Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.',\n",
       "  'Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.',\n",
       "  \"A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\",\n",
       "  'The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.',\n",
       "  'An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.',\n",
       "  'Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.',\n",
       "  'Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.',\n",
       "  'A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.',\n",
       "  'The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.',\n",
       "  'Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.',\n",
       "  'Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.',\n",
       "  'An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.',\n",
       "  \"Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\",\n",
       "  'Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.',\n",
       "  'Lee Parkin, a 50-year-old man, owner of Izzy.',\n",
       "  'Izzy, a terrier-spaniel cross owned by Lee Parkin.',\n",
       "  'XL bully, a type of dog that attacked Izzy and Naevia.',\n",
       "  'Marie Hay, owner of a Siberian Husky named Naevia.',\n",
       "  'Naevia, a seven-year-old Siberian Husky owned by Marie Hay.',\n",
       "  \"Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\",\n",
       "  'Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.',\n",
       "  'Lee Parkin is a 50-year-old man who owned a terrier-spaniel cross named Izzy and has been diagnosed with post-traumatic stress disorder following a dog attack.',\n",
       "  'Izzy was a terrier-spaniel cross dog owned by Lee Parkin for nearly 10 years, killed by an XL bully dog.',\n",
       "  \"A dog attack where an XL bully killed Lee Parkin's dog, Izzy, after a 20-minute attack despite intervention attempts by Lee Parkin and others.\",\n",
       "  'The location where Lee Parkin lived and where the dog attack on his pet Izzy occurred.',\n",
       "  'An XL bully is a type of dog that attacked and killed the terrier-spaniel cross Izzy, and also injured a Siberian husky named Naevia; described as dangerously out of control by Lee Parkin.',\n",
       "  'Marie Hay is the owner of a Siberian husky named Naevia who survived an attack by two XL bullies and has been left with both physical and mental scars.',\n",
       "  'Naevia is a seven-year-old Siberian husky owned by Marie Hay, who survived an attack by two XL bullies but suffered life-changing injuries and kidney failure.',\n",
       "  'A dog attack on a beach in Redcar where Naevia, a Siberian husky, was severely injured by two XL bullies.',\n",
       "  'The location on the North Yorkshire coast where Naevia the Siberian husky was attacked by two XL bullies.',\n",
       "  'Lee Parkin, owner of a terrier-spaniel cross named Izzy, experienced a traumatic event with his pet and suffers from post-traumatic stress disorder.',\n",
       "  'Izzy, a terrier-spaniel cross, was owned by Lee Parkin and was killed by an XL bully during a walk.',\n",
       "  'An XL bully attacked and killed Izzy, a terrier-spaniel cross owned by Lee Parkin in Doncaster.',\n",
       "  \"Marie Hay's Siberian husky named Naevia survived an attack by two XL bullies but was left with life-changing injuries and subsequently developed mental scars.\",\n",
       "  'Naevia, a Siberian husky owned by Marie Hay, survived an attack by two XL bullies on a beach in Redcar, resulting in life-changing injuries and causing significant vet bills.',\n",
       "  'Lee Parkin, a 50-year-old man, owner of Izzy.',\n",
       "  'Izzy, a terrier-spaniel cross owned by Lee Parkin.',\n",
       "  'XL bully, a type of dog that attacked Izzy and Naevia.',\n",
       "  'Marie Hay, owner of a Siberian Husky named Naevia.',\n",
       "  'Naevia, a seven-year-old Siberian Husky owned by Marie Hay.',\n",
       "  \"Doncaster, the town where Lee Parkin's dog Izzy was killed by an XL bully.\",\n",
       "  'Redcar Beach on the North Yorkshire coast, where Naevia was attacked by two XL bullies.']]"
      ]
     },
     "execution_count": 337,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "context"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "217fcdd1-e1f7-48f3-a835-cfd003bd6da9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import networkx as nx\n",
    "# import uuid\n",
    "# from datetime import datetime\n",
    "\n",
    "# def create_user_content_graph(user_id, custom_user_properties=None, required_layers=None, default_fields=None, existing_graph=None):\n",
    "\n",
    "#     category_name = required_layers['context_name']\n",
    "#     subgroup_names = [required_layers['layer_name']]\n",
    "\n",
    "    \n",
    "#     # Construct the additional_categories structure\n",
    "#     additional_categories = {\n",
    "#         category_name: subgroup_names\n",
    "# }\n",
    "\n",
    "#     # Define default fields for all nodes if not provided\n",
    "#     if default_fields is None:\n",
    "#         default_fields = {\n",
    "#             'created_at': datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\"),\n",
    "#             'updated_at': datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n",
    "#         }\n",
    "\n",
    "#     # Merge custom user properties with default properties; custom properties take precedence\n",
    "#     user_properties = {**default_fields, **(custom_user_properties or {})}\n",
    "\n",
    "#     # Default content categories\n",
    "#     content_categories = {\n",
    "#         \"Temporal\": [\"Historical events\", \"Schedules and timelines\"],\n",
    "#         \"Positional\": [\"Geographical locations\", \"Spatial data\"],\n",
    "#         \"Propositions\": [\"Hypotheses and theories\", \"Claims and arguments\"],\n",
    "#         \"Personalization\": [\"User preferences\", \"User information\"]\n",
    "#     }\n",
    "\n",
    "#     # Update content categories with any additional categories provided\n",
    "#     if additional_categories:\n",
    "#         content_categories.update(additional_categories)\n",
    "\n",
    "#     G = existing_graph if existing_graph else nx.MultiDiGraph()\n",
    "\n",
    "#     # Check if the user node already exists, if not, add the user node with properties\n",
    "#     if not G.has_node(user_id):\n",
    "#         G.add_node(user_id, **user_properties)\n",
    "\n",
    "#     # Add or update content category nodes and their edges\n",
    "#     for category, subclasses in content_categories.items():\n",
    "#         category_properties = {**default_fields, 'type': 'category'}\n",
    "\n",
    "#         # Add or update the category node\n",
    "#         if not G.has_node(category):\n",
    "#             G.add_node(category, **category_properties)\n",
    "#             G.add_edge(user_id, category, relationship='created')\n",
    "\n",
    "#         # Add or update subclass nodes and their edges\n",
    "#         for subclass in subclasses:\n",
    "#             # Using both category and subclass names to ensure uniqueness within categories\n",
    "#             subclass_node_id = f\"{category}:{subclass}\"\n",
    "\n",
    "#             # Check if subclass node exists before adding, based on node content\n",
    "#             if not any(subclass == data.get('content') for _, data in G.nodes(data=True)):\n",
    "#                 subclass_properties = {**default_fields, 'type': 'subclass', 'content': subclass}\n",
    "#                 G.add_node(subclass_node_id, **subclass_properties)\n",
    "#                 G.add_edge(category, subclass_node_id, relationship='includes')\n",
    "\n",
    "#     return G\n",
    "\n",
    "# #     # # Add content category nodes and their edges\n",
    "# #     # for category, subclasses in content_categories.items():\n",
    "# #     #     category_properties = {**default_fields, 'type': 'category'}\n",
    "# #     #     G.add_node(category, **category_properties)\n",
    "# #     #     G.add_edge(user_id, category, relationship='created')\n",
    "\n",
    "# #     #     # Add subclass nodes and their edges\n",
    "# #     #     for subclass in subclasses:\n",
    "# #     #         unique_id = str(uuid.uuid4())\n",
    "# #     #         subclass_node_id = f\"{subclass} - {unique_id}\"\n",
    "# #     #         subclass_properties = {**default_fields, 'type': 'subclass', 'content': subclass}\n",
    "# #     #         G.add_node(subclass_node_id, **subclass_properties)\n",
    "# #     #         G.add_edge(category, subclass_node_id, relationship='includes')\n",
    "\n",
    "# #     # return G\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f974c87e-4117-4f93-a96c-e4fcd741aed9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c9b14de-85f1-4aec-ab80-54e4b2a8f317",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eebe4f53-c6ba-466a-8ba2-adee16fb6e21",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "id": "cca2637a-eace-4763-ada4-0ce925afd7ce",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e67c6679-f339-4ad1-b1bc-0c896a973abe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "418ef758-64e1-4c44-a844-9e3960d9db50",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pydantic import BaseModel, Field\n",
    "from typing import List, Optional, Dict\n",
    "from datetime import datetime\n",
    "\n",
    "class Relationship(BaseModel):\n",
    "    type: str\n",
    "    properties: Optional[Dict[str, str]] = None\n",
    "\n",
    "class DocumentType(BaseModel):\n",
    "    type_id: str\n",
    "    description: str\n",
    "    default_relationship: Relationship = Relationship(type='is_type')\n",
    "\n",
    "class Category(BaseModel):\n",
    "    category_id: str\n",
    "    name: str\n",
    "    default_relationship: Relationship = Relationship(type='categorized_as')\n",
    "\n",
    "class Document(BaseModel):\n",
    "    doc_id: str\n",
    "    title: str\n",
    "    summary: Optional[str] = None\n",
    "    content_id: Optional[str] = None  # Reference to external content storage\n",
    "    doc_type: Optional[DocumentType] = None\n",
    "    categories: List[Category] = []\n",
    "    default_relationship: Relationship = Relationship(type='has_document')\n",
    "\n",
    "class UserLocation(BaseModel):\n",
    "    location_id: str\n",
    "    description: str\n",
    "    default_relationship: Relationship = Relationship(type='located_in')\n",
    "\n",
    "class UserProperties(BaseModel):\n",
    "    custom_properties: Optional[Dict[str, str]] = None\n",
    "    location: Optional[UserLocation] = None\n",
    "\n",
    "class GraphModel(BaseModel):\n",
    "    id: str = Field(..., alias='user_id')\n",
    "    user_properties: UserProperties = UserProperties()\n",
    "    documents: List[Document] = []\n",
    "    default_fields: Optional[Dict[str, str]] = Field(default_factory=lambda: {\n",
    "        'created_at': datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\"),\n",
    "        'updated_at': datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n",
    "    })\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "1061c73b-271d-4044-8291-340a69b7f2cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import networkx as nx\n",
    "# from pydantic import BaseModel\n",
    "# from typing import Optional, Any, Dict, Union\n",
    "\n",
    "# def add_node_and_edge(G, parent_id: Optional[str], node_id: str, node_data: Dict[str, Any], relationship_data: Dict[str, Any]):\n",
    "#     G.add_node(node_id, **node_data)\n",
    "#     if parent_id is not None:\n",
    "#         G.add_edge(parent_id, node_id, **relationship_data)\n",
    "\n",
    "# def process_attribute(G, parent_id: Optional[str], attribute: str, value: Union[BaseModel, List[BaseModel], Any], model_instance: Optional[BaseModel] = None):\n",
    "#     if isinstance(value, BaseModel):  # Single Pydantic model instance\n",
    "#         # Generate a unique node identifier based on the model instance type and a relevant unique field\n",
    "#         instance_id = f\"{value.__class__.__name__}:{getattr(value, 'id', getattr(value, 'doc_id', value.__class__.__name__))}\"\n",
    "#         node_data = value.dict(exclude={'default_relationship', 'categories', 'doc_type'})\n",
    "#         relationship_data = value.default_relationship.dict() if hasattr(value, 'default_relationship') else {}\n",
    "\n",
    "#         # Special handling for UserProperties to flatten its structure and incorporate it into the user node\n",
    "#         if isinstance(value, UserProperties):\n",
    "#             node_data = {**node_data.get('custom_properties', {}), **node_data.get('location', {})}\n",
    "#             instance_id = parent_id  # Use the user node ID for UserProperties\n",
    "\n",
    "#         add_node_and_edge(G, parent_id, instance_id, node_data, relationship_data)\n",
    "\n",
    "#         # Recursively process nested attributes\n",
    "#         for sub_attr, sub_val in value.dict(exclude={'id', 'doc_id'}).items():\n",
    "#             process_attribute(G, instance_id, sub_attr, sub_val, model_instance=value)\n",
    "\n",
    "#     elif isinstance(value, list) and all(isinstance(item, BaseModel) for item in value):\n",
    "#         for item in value:\n",
    "#             process_attribute(G, parent_id, attribute, item, model_instance)\n",
    "\n",
    "#     # Handle the creation of category nodes from the Document model instance\n",
    "#     elif attribute == 'categories' and model_instance and isinstance(model_instance, Document):\n",
    "#         for category in value:\n",
    "#             cat_node_id = f\"Category:{category['category_id']}\"\n",
    "#             G.add_node(cat_node_id, **category)\n",
    "#             G.add_edge(parent_id, cat_node_id, **category['default_relationship'].dict())\n",
    "\n",
    "# def create_dynamic(graph_model: BaseModel, existing_graph: Optional[nx.Graph] = None) -> nx.Graph:\n",
    "#     G = existing_graph if existing_graph else nx.Graph()\n",
    "\n",
    "#     # The root node is the user node\n",
    "#     root_id = getattr(graph_model, 'id', None)\n",
    "#     if root_id is None:\n",
    "#         raise ValueError(\"GraphModel instance must have an 'id' field.\")\n",
    "\n",
    "#     # User node creation with properties from user_properties\n",
    "#     user_properties = graph_model.user_properties.custom_properties if graph_model.user_properties else {}\n",
    "#     user_node_data = {**graph_model.default_fields, **user_properties}\n",
    "#     add_node_and_edge(G, None, root_id, user_node_data, {})\n",
    "\n",
    "#     # Process top-level attributes of the graph model, excluding handled fields\n",
    "#     for attribute_name, attribute_value in graph_model.dict(exclude={'id', 'user_properties', 'default_fields'}).items():\n",
    "#         process_attribute(G, root_id, attribute_name, attribute_value)\n",
    "\n",
    "#     return G\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "31994fee-6ab1-4132-8ade-b29fd12f940b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import networkx as nx\n",
    "# from pydantic import BaseModel\n",
    "# from typing import Optional, Any, Union, List\n",
    "\n",
    "# def add_node_and_edge(G, parent_id: Optional[str], node_id: str, node_data: dict, relationship_data: dict):\n",
    "#     G.add_node(node_id, **node_data)\n",
    "#     if parent_id is not None:\n",
    "#         G.add_edge(parent_id, node_id, **relationship_data)\n",
    "\n",
    "# def generate_node_id(instance: BaseModel) -> str:\n",
    "#     \"\"\"Generates a unique node ID based on the Pydantic model instance.\"\"\"\n",
    "#     for field in ['id', 'doc_id', 'location_id', 'type_id']:\n",
    "#         if hasattr(instance, field):\n",
    "#             return f\"{instance.__class__.__name__}:{getattr(instance, field)}\"\n",
    "#     return f\"{instance.__class__.__name__}:default\"\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# def process_attribute(G, parent_id: Optional[str], attribute: str, value: Any):\n",
    "#     if isinstance(value, BaseModel):  # Single Pydantic model instance\n",
    "#         node_id = generate_node_id(value)\n",
    "#         node_data = value.dict(exclude={'default_relationship'})\n",
    "#         relationship_data = value.default_relationship.dict() if hasattr(value, 'default_relationship') else {}\n",
    "#         add_node_and_edge(G, parent_id, node_id, node_data, relationship_data)\n",
    "\n",
    "#         # Recursively process nested attributes\n",
    "#         for sub_attr, sub_val in value:\n",
    "#             process_attribute(G, node_id, sub_attr, sub_val)\n",
    "\n",
    "#     elif isinstance(value, list) and all(isinstance(item, BaseModel) for item in value):\n",
    "#         for item in value:\n",
    "#             process_attribute(G, parent_id, attribute, item)\n",
    "\n",
    "# def create_dynamic(graph_model: BaseModel, existing_graph: Optional[nx.Graph] = None) -> nx.Graph:\n",
    "#     G = existing_graph if existing_graph else nx.Graph()\n",
    "\n",
    "#     # Dynamically get the root node ID based on the presence of a unique identifier\n",
    "#     root_id = generate_node_id(graph_model)\n",
    "#     G.add_node(root_id, **graph_model.dict(exclude={'default_relationship'}))\n",
    "\n",
    "#     # Dynamically process each attribute of the root Pydantic model\n",
    "#     for attribute_name, attribute_value in graph_model:\n",
    "#         process_attribute(G, root_id, attribute_name, attribute_value)\n",
    "\n",
    "#     return G\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e6bb6a71-1e8d-4695-a3d0-0d25b1e44fa0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "from pydantic import BaseModel\n",
    "from typing import Optional, Any, List, Dict\n",
    "from datetime import datetime\n",
    "\n",
    "# Models for representing different entities\n",
    "class Relationship(BaseModel):\n",
    "    type: str\n",
    "    properties: Optional[Dict[str, Any]] = None\n",
    "\n",
    "class DocumentType(BaseModel):\n",
    "    type_id: str\n",
    "    description: str\n",
    "    default_relationship: Relationship = Relationship(type='is_type')\n",
    "\n",
    "class Category(BaseModel):\n",
    "    category_id: str\n",
    "    name: str\n",
    "    default_relationship: Relationship = Relationship(type='categorized_as')\n",
    "\n",
    "class Document(BaseModel):\n",
    "    doc_id: str\n",
    "    title: str\n",
    "    summary: Optional[str] = None\n",
    "    content_id: Optional[str] = None\n",
    "    doc_type: Optional[DocumentType] = None\n",
    "    categories: List[Category] = []\n",
    "    default_relationship: Relationship = Relationship(type='has_document')\n",
    "\n",
    "class UserLocation(BaseModel):\n",
    "    location_id: str\n",
    "    description: str\n",
    "    default_relationship: Relationship = Relationship(type='located_in')\n",
    "\n",
    "class UserProperties(BaseModel):\n",
    "    custom_properties: Optional[Dict[str, Any]] = None\n",
    "    location: Optional[UserLocation] = None\n",
    "\n",
    "class GraphModel(BaseModel):\n",
    "    id: str\n",
    "    user_properties: UserProperties = UserProperties()\n",
    "    documents: List[Document] = []\n",
    "    default_fields: Optional[Dict[str, Any]] = {}\n",
    "\n",
    "def generate_node_id(instance: BaseModel) -> str:\n",
    "    for field in ['id', 'doc_id', 'location_id', 'type_id']:\n",
    "        if hasattr(instance, field):\n",
    "            return f\"{instance.__class__.__name__}:{getattr(instance, field)}\"\n",
    "    return f\"{instance.__class__.__name__}:default\"\n",
    "\n",
    "def add_node_and_edge(G, parent_id: Optional[str], node_id: str, node_data: dict, relationship_data: dict):\n",
    "    G.add_node(node_id, **node_data)  # Add the current node with its data\n",
    "    if parent_id:\n",
    "        # Add an edge between the parent node and the current node with the correct relationship data\n",
    "        G.add_edge(parent_id, node_id, **relationship_data)\n",
    "\n",
    "def process_attribute(G, parent_id: Optional[str], attribute: str, value: Any):\n",
    "    if isinstance(value, BaseModel):\n",
    "        node_id = generate_node_id(value)\n",
    "        node_data = value.dict(exclude={'default_relationship'})\n",
    "        # Use the specified default relationship for the edge between the parent node and the current node\n",
    "        relationship_data = value.default_relationship.dict() if hasattr(value, 'default_relationship') else {}\n",
    "        add_node_and_edge(G, parent_id, node_id, node_data, relationship_data)\n",
    "\n",
    "        # Recursively process nested attributes to ensure all nodes and relationships are added to the graph\n",
    "        for sub_attr, sub_val in value.__dict__.items():  # Access attributes and their values directly\n",
    "            process_attribute(G, node_id, sub_attr, sub_val)\n",
    "\n",
    "    elif isinstance(value, list) and all(isinstance(item, BaseModel) for item in value):\n",
    "        # For lists of BaseModel instances, process each item in the list\n",
    "        for item in value:\n",
    "            process_attribute(G, parent_id, attribute, item)\n",
    "\n",
    "def create_dynamic(graph_model: BaseModel, existing_graph: Optional[nx.Graph] = None) -> nx.Graph:\n",
    "    G = existing_graph or nx.Graph()\n",
    "    root_id = generate_node_id(graph_model)\n",
    "    print(root_id)\n",
    "    G.add_node(root_id, **graph_model.dict(exclude={'default_relationship'}))\n",
    "\n",
    "    for attribute_name, attribute_value in graph_model:\n",
    "        process_attribute(G, root_id, attribute_name, attribute_value)\n",
    "\n",
    "    return G\n",
    "\n",
    "# Example usage with GraphModel instance\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "82ed3638-6252-4629-b411-b7e9029dd282",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id': 'user123',\n",
       " 'user_properties': {'custom_properties': {'age': '30'},\n",
       "  'location': {'location_id': 'ny',\n",
       "   'description': 'New York',\n",
       "   'default_relationship': {'type': 'located_in', 'properties': None}}},\n",
       " 'documents': [{'doc_id': 'doc1',\n",
       "   'title': 'Document 1',\n",
       "   'summary': 'Summary of Document 1',\n",
       "   'content_id': 'content_id_for_doc1',\n",
       "   'doc_type': {'type_id': 'PDF',\n",
       "    'description': 'Portable Document Format',\n",
       "    'default_relationship': {'type': 'is_type', 'properties': None}},\n",
       "   'categories': [{'category_id': 'finance',\n",
       "     'name': 'Finance',\n",
       "     'default_relationship': {'type': 'belongs_to', 'properties': None}},\n",
       "    {'category_id': 'tech',\n",
       "     'name': 'Technology',\n",
       "     'default_relationship': {'type': 'belongs_to', 'properties': None}}],\n",
       "   'default_relationship': {'type': 'has_document', 'properties': None}},\n",
       "  {'doc_id': 'doc2',\n",
       "   'title': 'Document 2',\n",
       "   'summary': 'Summary of Document 2',\n",
       "   'content_id': 'content_id_for_doc2',\n",
       "   'doc_type': {'type_id': 'TXT',\n",
       "    'description': 'Text File',\n",
       "    'default_relationship': {'type': 'is_type', 'properties': None}},\n",
       "   'categories': [{'category_id': 'health',\n",
       "     'name': 'Health',\n",
       "     'default_relationship': {'type': 'belongs_to', 'properties': None}},\n",
       "    {'category_id': 'wellness',\n",
       "     'name': 'Wellness',\n",
       "     'default_relationship': {'type': 'belongs_to', 'properties': None}}],\n",
       "   'default_relationship': {'type': 'has_document', 'properties': None}}],\n",
       " 'default_fields': {'created_at': '2024-03-09 16:57:03',\n",
       "  'updated_at': '2024-03-09 16:57:03'}}"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graph_model_instance.dict(exclude={'default_relationship'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b32c4472-fa5b-4358-b35d-2fb675a90563",
   "metadata": {},
   "outputs": [],
   "source": [
    "graph_model_instance = GraphModel(\n",
    "    id=\"user123\",\n",
    "    documents=[\n",
    "        Document(\n",
    "            doc_id=\"doc1\",\n",
    "            title=\"Document 1\",\n",
    "            summary=\"Summary of Document 1\",\n",
    "            content_id=\"content_id_for_doc1\",  # Assuming external content storage ID\n",
    "            doc_type=DocumentType(type_id=\"PDF\", description=\"Portable Document Format\"),\n",
    "            categories=[\n",
    "                Category(category_id=\"finance\", name=\"Finance\", default_relationship=Relationship(type=\"belongs_to\")),\n",
    "                Category(category_id=\"tech\", name=\"Technology\", default_relationship=Relationship(type=\"belongs_to\"))\n",
    "            ],\n",
    "            default_relationship=Relationship(type='has_document')\n",
    "        ),\n",
    "        Document(\n",
    "            doc_id=\"doc2\",\n",
    "            title=\"Document 2\",\n",
    "            summary=\"Summary of Document 2\",\n",
    "            content_id=\"content_id_for_doc2\",\n",
    "            doc_type=DocumentType(type_id=\"TXT\", description=\"Text File\"),\n",
    "            categories=[\n",
    "                Category(category_id=\"health\", name=\"Health\", default_relationship=Relationship(type=\"belongs_to\")),\n",
    "                Category(category_id=\"wellness\", name=\"Wellness\", default_relationship=Relationship(type=\"belongs_to\"))\n",
    "            ],\n",
    "            default_relationship=Relationship(type='has_document')\n",
    "        )\n",
    "    ],\n",
    "    user_properties=UserProperties(\n",
    "        custom_properties={\"age\": \"30\"},\n",
    "        location=UserLocation(location_id=\"ny\", description=\"New York\", default_relationship=Relationship(type='located_in'))\n",
    "    ),\n",
    "    default_fields={\n",
    "        'created_at': datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\"),\n",
    "        'updated_at': datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n",
    "    }\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a86c31fa-cb8e-4c1c-bf80-c7268caa3e59",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GraphModel:user123\n"
     ]
    }
   ],
   "source": [
    "R = create_dynamic(graph_model_instance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "823a24ce-e613-4840-b963-acd8cfec9292",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes and their data:\n",
      "GraphModel:user123 {'id': 'user123', 'user_properties': {'custom_properties': {'age': '30'}, 'location': {'location_id': 'ny', 'description': 'New York', 'default_relationship': {'type': 'located_in', 'properties': None}}}, 'documents': [{'doc_id': 'doc1', 'title': 'Document 1', 'summary': 'Summary of Document 1', 'content_id': 'content_id_for_doc1', 'doc_type': {'type_id': 'PDF', 'description': 'Portable Document Format', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'finance', 'name': 'Finance', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'tech', 'name': 'Technology', 'default_relationship': {'type': 'belongs_to', 'properties': None}}], 'default_relationship': {'type': 'has_document', 'properties': None}}, {'doc_id': 'doc2', 'title': 'Document 2', 'summary': 'Summary of Document 2', 'content_id': 'content_id_for_doc2', 'doc_type': {'type_id': 'TXT', 'description': 'Text File', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'health', 'name': 'Health', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'wellness', 'name': 'Wellness', 'default_relationship': {'type': 'belongs_to', 'properties': None}}], 'default_relationship': {'type': 'has_document', 'properties': None}}], 'default_fields': {'created_at': '2024-03-09 16:57:03', 'updated_at': '2024-03-09 16:57:03'}}\n",
      "UserProperties:default {'custom_properties': {'age': '30'}, 'location': {'location_id': 'ny', 'description': 'New York', 'default_relationship': {'type': 'located_in', 'properties': None}}}\n",
      "UserLocation:ny {'location_id': 'ny', 'description': 'New York'}\n",
      "Relationship:default {'type': 'has_document', 'properties': None}\n",
      "Document:doc1 {'doc_id': 'doc1', 'title': 'Document 1', 'summary': 'Summary of Document 1', 'content_id': 'content_id_for_doc1', 'doc_type': {'type_id': 'PDF', 'description': 'Portable Document Format', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'finance', 'name': 'Finance', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'tech', 'name': 'Technology', 'default_relationship': {'type': 'belongs_to', 'properties': None}}]}\n",
      "DocumentType:PDF {'type_id': 'PDF', 'description': 'Portable Document Format'}\n",
      "Category:default {'category_id': 'wellness', 'name': 'Wellness'}\n",
      "Document:doc2 {'doc_id': 'doc2', 'title': 'Document 2', 'summary': 'Summary of Document 2', 'content_id': 'content_id_for_doc2', 'doc_type': {'type_id': 'TXT', 'description': 'Text File', 'default_relationship': {'type': 'is_type', 'properties': None}}, 'categories': [{'category_id': 'health', 'name': 'Health', 'default_relationship': {'type': 'belongs_to', 'properties': None}}, {'category_id': 'wellness', 'name': 'Wellness', 'default_relationship': {'type': 'belongs_to', 'properties': None}}]}\n",
      "DocumentType:TXT {'type_id': 'TXT', 'description': 'Text File'}\n",
      "\n",
      "Edges and their data:\n",
      "GraphModel:user123 -> UserProperties:default {}\n",
      "GraphModel:user123 -> Document:doc1 {'type': 'has_document', 'properties': None}\n",
      "GraphModel:user123 -> Document:doc2 {'type': 'has_document', 'properties': None}\n",
      "UserProperties:default -> UserLocation:ny {'type': 'located_in', 'properties': None}\n",
      "UserLocation:ny -> Relationship:default {}\n",
      "Relationship:default -> DocumentType:PDF {}\n",
      "Relationship:default -> Category:default {}\n",
      "Relationship:default -> Document:doc1 {}\n",
      "Relationship:default -> DocumentType:TXT {}\n",
      "Relationship:default -> Document:doc2 {}\n",
      "Document:doc1 -> DocumentType:PDF {'type': 'is_type', 'properties': None}\n",
      "Document:doc1 -> Category:default {'type': 'belongs_to', 'properties': None}\n",
      "Category:default -> Document:doc2 {'type': 'belongs_to', 'properties': None}\n",
      "Document:doc2 -> DocumentType:TXT {'type': 'is_type', 'properties': None}\n"
     ]
    }
   ],
   "source": [
    "    print(\"Nodes and their data:\")\n",
    "    for node, data in R.nodes(data=True):\n",
    "        print(node, data)\n",
    "\n",
    "    # Print edges with their data\n",
    "    print(\"\\nEdges and their data:\")\n",
    "    for source, target, data in R.edges(data=True):\n",
    "        print(f\"{source} -> {target} {data}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "675e2037-65a8-4f97-974a-1bfc8789ea78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <iframe id=\"481086c4-f97a-4641-b962-0f501ae6c90e\" src=\"https://hub.graphistry.com/graph/graph.html?dataset=70be9087e1724865a6e8335ceb08b0a9&type=arrow&viztoken=bb6f7091-1e93-4f3c-baaf-fa3f6831cf09&usertag=1daaf574-pygraphistry-0.33.0&splashAfter=1710005565&info=true\"\n",
       "                    allowfullscreen=\"true\" webkitallowfullscreen=\"true\" mozallowfullscreen=\"true\"\n",
       "                    oallowfullscreen=\"true\" msallowfullscreen=\"true\"\n",
       "                    style=\"width:100%; height:500px; border: 1px solid #DDD; overflow: hidden\"\n",
       "                    \n",
       "            >\n",
       "            </iframe>\n",
       "        \n",
       "            <script>\n",
       "                try {\n",
       "                  $(\"#481086c4-f97a-4641-b962-0f501ae6c90e\").bind('mousewheel', function(e) { e.preventDefault(); });\n",
       "                } catch (e) { console.error('exn catching scroll', e); }\n",
       "            </script>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import graphistry\n",
    "import pandas as pd\n",
    "\n",
    "# Assuming Graphistry is already configured with API key\n",
    "# graphistry.register(api=3, username='your_username', password='your_password')\n",
    "\n",
    "# Convert NetworkX graph to a Pandas DataFrame\n",
    "edges = nx.to_pandas_edgelist(T)\n",
    "graphistry.register(api=3, username='Vasilije1990', password='Q@HLdgv5SMUsGxy') \n",
    "\n",
    "# Visualize the graph\n",
    "graphistry.edges(edges, 'source', 'target').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "4ed998eb-34e7-40f0-b638-80f36fb233e5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "8887b4a7-9c0e-474e-b0e2-8545e904e58a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Node 'Relationship:default' has been removed from the graph.\n"
     ]
    }
   ],
   "source": [
    "def delete_node(G, node_id: str):\n",
    "    \"\"\"\n",
    "    Deletes a node and its associated edges from the graph.\n",
    "\n",
    "    Parameters:\n",
    "    - G: The graph from which the node will be removed (NetworkX graph).\n",
    "    - node_id: The ID of the node to be removed.\n",
    "    \"\"\"\n",
    "    # Check if the node exists in the graph\n",
    "    if G.has_node(node_id):\n",
    "        # Remove the node and its associated edges\n",
    "        G.remove_node(node_id)\n",
    "        print(f\"Node '{node_id}' has been removed from the graph.\")\n",
    "    else:\n",
    "        print(f\"Node '{node_id}' not found in the graph.\")\n",
    "    return G\n",
    "\n",
    "# Example usage:\n",
    "# Assume G is your NetworkX graph\n",
    "R = delete_node(R, \"Relationship:default\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "ca9cf69d-e56a-45e3-9812-f862c0f138c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pydantic import BaseModel\n",
    "from typing import List, Optional, Dict, Any\n",
    "\n",
    "class Relationship(BaseModel):\n",
    "    type: str\n",
    "    properties: Optional[Dict[str, Any]] = None\n",
    "\n",
    "class Task(BaseModel):\n",
    "    task_id: str\n",
    "    name: str\n",
    "    description: Optional[str] = None\n",
    "    subtasks: List['Task'] = []\n",
    "    default_relationship: Relationship = Relationship(type='part_of')\n",
    "\n",
    "Task.update_forward_refs()\n",
    "\n",
    "class ProjectType(BaseModel):\n",
    "    type_id: str\n",
    "    name: str\n",
    "    default_relationship: Relationship = Relationship(type='is_project_type')\n",
    "\n",
    "class Project(BaseModel):\n",
    "    project_id: str\n",
    "    title: str\n",
    "    summary: Optional[str] = None\n",
    "    project_type: ProjectType\n",
    "    tasks: List[Task]\n",
    "    default_relationship: Relationship = Relationship(type='contains_project')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "05dd25bc-05c9-4b28-81c5-c7878c6a7a1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Instantiate subtasks\n",
    "subtask1 = Task(\n",
    "    task_id=\"subtask1\",\n",
    "    name=\"Subtask 1\",\n",
    "    description=\"This is a subtask\",\n",
    "    default_relationship=Relationship(type=\"subtask_of\")\n",
    ")\n",
    "\n",
    "subtask2 = Task(\n",
    "    task_id=\"subtask2\",\n",
    "    name=\"Subtask 2\",\n",
    "    description=\"This is another subtask\",\n",
    "    default_relationship=Relationship(type=\"subtask_of\")\n",
    ")\n",
    "\n",
    "# Instantiate tasks with subtasks\n",
    "task1 = Task(\n",
    "    task_id=\"task1\",\n",
    "    name=\"Task 1\",\n",
    "    description=\"This is the first main task\",\n",
    "    subtasks=[subtask1, subtask2],\n",
    "    default_relationship=Relationship(type=\"task_of\")\n",
    ")\n",
    "\n",
    "task2 = Task(\n",
    "    task_id=\"task2\",\n",
    "    name=\"Task 2\",\n",
    "    description=\"This is the second main task\",\n",
    "    default_relationship=Relationship(type=\"task_of\")\n",
    ")\n",
    "\n",
    "# Instantiate a project type\n",
    "project_type = ProjectType(\n",
    "    type_id=\"type1\",\n",
    "    name=\"Software Development\",\n",
    "    default_relationship=Relationship(type=\"type_of_project\")\n",
    ")\n",
    "\n",
    "# Instantiate a project with tasks and a project type\n",
    "project = Project(\n",
    "    project_id=\"project1\",\n",
    "    title=\"New Software Development Project\",\n",
    "    summary=\"This project involves developing a new software application.\",\n",
    "    project_type=project_type,\n",
    "    tasks=[task1, task2],\n",
    "    default_relationship=Relationship(type=\"contains\")\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "b4bf969f-5677-40fc-b8fe-cd3cc12ad809",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "\n",
    "# Assuming `create_dynamic` function is defined as you provided and `generate_node_id` is implemented\n",
    "\n",
    "# Create a graph from the project instance\n",
    "graph = create_dynamic(project)\n",
    "\n",
    "# You can now use the graph for various analyses, visualization, etc.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "4f678734-e615-4ac9-a1a7-3bed128d3df3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes and their data:\n",
      "Project:default {'project_id': 'project1', 'title': 'New Software Development Project', 'summary': 'This project involves developing a new software application.', 'project_type': {'type_id': 'type1', 'name': 'Software Development', 'default_relationship': {'type': 'type_of_project', 'properties': None}}, 'tasks': [{'task_id': 'task1', 'name': 'Task 1', 'description': 'This is the first main task', 'subtasks': [{'task_id': 'subtask1', 'name': 'Subtask 1', 'description': 'This is a subtask', 'subtasks': [], 'default_relationship': {'type': 'subtask_of', 'properties': None}}, {'task_id': 'subtask2', 'name': 'Subtask 2', 'description': 'This is another subtask', 'subtasks': [], 'default_relationship': {'type': 'subtask_of', 'properties': None}}], 'default_relationship': {'type': 'task_of', 'properties': None}}, {'task_id': 'task2', 'name': 'Task 2', 'description': 'This is the second main task', 'subtasks': [], 'default_relationship': {'type': 'task_of', 'properties': None}}]}\n",
      "ProjectType:type1 {'type_id': 'type1', 'name': 'Software Development'}\n",
      "Relationship:default {'type': 'contains', 'properties': None}\n",
      "Task:default {'task_id': 'task2', 'name': 'Task 2', 'description': 'This is the second main task', 'subtasks': []}\n",
      "\n",
      "Edges and their data:\n",
      "Project:default -> ProjectType:type1 {'type': 'type_of_project', 'properties': None}\n",
      "Project:default -> Task:default {'type': 'task_of', 'properties': None}\n",
      "Project:default -> Relationship:default {}\n",
      "ProjectType:type1 -> Relationship:default {}\n",
      "Relationship:default -> Task:default {}\n",
      "Task:default -> Task:default {'type': 'subtask_of', 'properties': None}\n"
     ]
    }
   ],
   "source": [
    "    print(\"Nodes and their data:\")\n",
    "    for node, data in graph.nodes(data=True):\n",
    "        print(node, data)\n",
    "\n",
    "    # Print edges with their data\n",
    "    print(\"\\nEdges and their data:\")\n",
    "    for source, target, data in graph.edges(data=True):\n",
    "        print(f\"{source} -> {target} {data}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "221728b7-4a08-427f-bb35-9db9fe5a4f3f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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