{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[{"file_id":"1VDzeZyw5dQEni3I1oSoABOBF7dee8oGv","timestamp":1735482701187},{"file_id":"1ZYogLNhD2G2-R5S9dh-e0xpAtnl2-x3H","timestamp":1735482594838},{"file_id":"1FG7ZKNWvY9NzttqgpQZ3lrCo4bBNQfa0","timestamp":1735482435351}],"mount_file_id":"1e7RrFWyvPr-7xIhv-HwCgtg_buMpn5Ew","authorship_tag":"ABX9TyPVgMo9K0VjXoR5S9+gzWjf"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["## Reranking Applying\n","\n"],"metadata":{"id":"Ok2K9KTnSsUb"}},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","file_path = \"/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Datasets\"\n","files = [\n","    \"australian_user_reviews.json.gz\",\n","    \"australian_users_items.json.gz\",\n","    \"bundle_data.json.gz\",\n","    \"steam_games.json.gz\"\n","]"],"metadata":{"id":"ndVraj2XhD0Y","executionInfo":{"status":"ok","timestamp":1735799988374,"user_tz":-420,"elapsed":306,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":1,"outputs":[]},{"cell_type":"code","source":["# Open the gzipped file\n","user_item_interactions = {}\n","data_dict = None\n","count = {\n","    \"users\": 0,\n","    \"items\": 0\n","}\n","data_items = None\n","with gzip.open(f\"{file_path}/{files[1]}\", 'rt', encoding='utf-8') as f:  # 'rt' is for text mode\n","    for i, line in enumerate(f):\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","            data_items = {}\n","            if data_dict[\"items_count\"] > 0:\n","              count[\"items\"] += data_dict[\"items_count\"]\n","              count[\"users\"] += 1\n","\n","              for item in data_dict[\"items\"]:\n","                data_items[item[\"item_id\"]] = item[\"playtime_forever\"]\n","\n","              user_item_interactions[data_dict['user_id']] = data_items\n","        except (ValueError, SyntaxError) as e:\n","            print(f\"Failed to convert string to dictionary: {e}\")\n","\n","        if count[\"users\"] == 10000:\n","          break\n","\n","print(f\"Number of user {count['users']}\")\n","print(f\"Number of items {count['items']}\")\n","print(data_dict)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yPu3n3l6hRLA","executionInfo":{"status":"ok","timestamp":1735800052536,"user_tz":-420,"elapsed":63844,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"8bd7e60e-26d9-47e0-e9d5-bca0c24b484b"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of user 10000\n","Number of items 1132592\n","{'user_id': '76561198030000787', 'items_count': 314, 'steam_id': '76561198030000787', 'user_url': 'http://steamcommunity.com/profiles/76561198030000787', 'items': [{'item_id': '4000', 'item_name': \"Garry's Mod\", 'playtime_forever': 32, 'playtime_2weeks': 0}, {'item_id': '2600', 'item_name': 'Vampire: The Masquerade - Bloodlines', 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '2200', 'item_name': 'Quake III Arena', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '2310', 'item_name': 'Quake', 'playtime_forever': 26, 'playtime_2weeks': 0}, {'item_id': '2320', 'item_name': 'Quake II', 'playtime_forever': 5, 'playtime_2weeks': 0}, {'item_id': '2330', 'item_name': 'Quake II: The Reckoning', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '2340', 'item_name': 'Quake II: Ground Zero', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '2350', 'item_name': 'Quake III: Team Arena', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '9030', 'item_name': 'Quake Mission Pack 2: Dissolution of Eternity', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '9040', 'item_name': 'Quake Mission Pack 1: Scourge of Armagon', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '4760', 'item_name': 'Rome: Total War', 'playtime_forever': 124, 'playtime_2weeks': 0}, {'item_id': '4770', 'item_name': 'Rome: Total War - Alexander', 'playtime_forever': 5, 'playtime_2weeks': 0}, {'item_id': '18500', 'item_name': 'Defense Grid: The Awakening', 'playtime_forever': 486, 'playtime_2weeks': 0}, {'item_id': '17460', 'item_name': 'Mass Effect', 'playtime_forever': 1896, 'playtime_2weeks': 0}, {'item_id': '1250', 'item_name': 'Killing Floor', 'playtime_forever': 949, 'playtime_2weeks': 0}, {'item_id': '35420', 'item_name': 'Killing Floor Mod: Defence Alliance 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21680', 'item_name': 'Bionic Commando Rearmed', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21670', 'item_name': 'Bionic Commando', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '38400', 'item_name': 'Fallout', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '38410', 'item_name': 'Fallout 2', 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '38420', 'item_name': 'Fallout Tactics', 'playtime_forever': 48, 'playtime_2weeks': 0}, {'item_id': '20900', 'item_name': 'The Witcher: Enhanced Edition', 'playtime_forever': 38, 'playtime_2weeks': 0}, {'item_id': '17450', 'item_name': 'Dragon Age: Origins', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '10180', 'item_name': 'Call of Duty: Modern Warfare 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '10190', 'item_name': 'Call of Duty: Modern Warfare 2 - Multiplayer', 'playtime_forever': 835, 'playtime_2weeks': 0}, {'item_id': '550', 'item_name': 'Left 4 Dead 2', 'playtime_forever': 683, 'playtime_2weeks': 0}, {'item_id': '223530', 'item_name': 'Left 4 Dead 2 Beta', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '22370', 'item_name': 'Fallout 3 - Game of the Year Edition', 'playtime_forever': 3, 'playtime_2weeks': 0}, {'item_id': '24980', 'item_name': 'Mass Effect 2', 'playtime_forever': 1837, 'playtime_2weeks': 0}, {'item_id': '33910', 'item_name': 'Arma 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '33930', 'item_name': 'Arma 2: Operation Arrowhead', 'playtime_forever': 57, 'playtime_2weeks': 0}, {'item_id': '219540', 'item_name': 'Arma 2: Operation Arrowhead Beta (Obsolete)', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '22380', 'item_name': 'Fallout: New Vegas', 'playtime_forever': 5078, 'playtime_2weeks': 0}, {'item_id': '42700', 'item_name': 'Call of Duty: Black Ops', 'playtime_forever': 537, 'playtime_2weeks': 0}, {'item_id': '42710', 'item_name': 'Call of Duty: Black Ops - Multiplayer', 'playtime_forever': 2037, 'playtime_2weeks': 0}, {'item_id': '47810', 'item_name': 'Dragon Age: Origins - Ultimate Edition', 'playtime_forever': 1522, 'playtime_2weeks': 0}, {'item_id': '78000', 'item_name': 'Bejeweled 3', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '56400', 'item_name': 'Warhammer® 40,000™: Dawn of War® II – Retribution™', 'playtime_forever': 917, 'playtime_2weeks': 0}, {'item_id': '48720', 'item_name': 'Mount & Blade: With Fire and Sword', 'playtime_forever': 424, 'playtime_2weeks': 0}, {'item_id': '20920', 'item_name': 'The Witcher 2: Assassins of Kings Enhanced Edition', 'playtime_forever': 2141, 'playtime_2weeks': 0}, {'item_id': '105600', 'item_name': 'Terraria', 'playtime_forever': 1807, 'playtime_2weeks': 0}, {'item_id': '17430', 'item_name': 'Need for Speed: Undercover', 'playtime_forever': 2, 'playtime_2weeks': 0}, {'item_id': '24740', 'item_name': 'Burnout Paradise: The Ultimate Box', 'playtime_forever': 48, 'playtime_2weeks': 0}, {'item_id': '24870', 'item_name': 'Need for Speed: SHIFT', 'playtime_forever': 102, 'playtime_2weeks': 0}, {'item_id': '47870', 'item_name': 'Need for Speed: Hot Pursuit', 'playtime_forever': 211, 'playtime_2weeks': 0}, {'item_id': '47920', 'item_name': 'Shift 2 Unleashed', 'playtime_forever': 7, 'playtime_2weeks': 0}, {'item_id': '33440', 'item_name': 'Driver San Francisco', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '72850', 'item_name': 'The Elder Scrolls V: Skyrim', 'playtime_forever': 10060, 'playtime_2weeks': 0}, {'item_id': '91310', 'item_name': 'Dead Island', 'playtime_forever': 1853, 'playtime_2weeks': 0}, {'item_id': '111400', 'item_name': 'Bunch Of Heroes', 'playtime_forever': 167, 'playtime_2weeks': 0}, {'item_id': '45770', 'item_name': 'Dead Rising 2: Off the Record', 'playtime_forever': 206, 'playtime_2weeks': 0}, {'item_id': '102600', 'item_name': 'Orcs Must Die!', 'playtime_forever': 209, 'playtime_2weeks': 0}, {'item_id': '48220', 'item_name': 'Might & Magic: Heroes VI', 'playtime_forever': 1314, 'playtime_2weeks': 0}, {'item_id': '110800', 'item_name': 'L.A. Noire', 'playtime_forever': 243, 'playtime_2weeks': 0}, {'item_id': '16450', 'item_name': 'F.E.A.R. 2: Project Origin', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21000', 'item_name': 'LEGO Batman: The Videogame', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21010', 'item_name': 'Watchmen: The End Is Nigh', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21030', 'item_name': 'Watchmen: The End Is Nigh Part 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21070', 'item_name': 'Wanted: Weapons of Fate', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21080', 'item_name': 'Terminator Salvation', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21090', 'item_name': 'F.E.A.R.', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21100', 'item_name': 'F.E.A.R. 3', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21110', 'item_name': 'F.E.A.R.: Extraction Point', 'playtime_forever': 4, 'playtime_2weeks': 0}, {'item_id': '21120', 'item_name': 'F.E.A.R.: Perseus Mandate', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21130', 'item_name': 'Lego Harry Potter', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32800', 'item_name': 'The Lord of the Rings: War in the North', 'playtime_forever': 64, 'playtime_2weeks': 0}, {'item_id': '35140', 'item_name': 'Batman: Arkham Asylum GOTY Edition', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '57400', 'item_name': 'Batman: Arkham City™', 'playtime_forever': 1924, 'playtime_2weeks': 0}, {'item_id': '107100', 'item_name': 'Bastion', 'playtime_forever': 36, 'playtime_2weeks': 0}, {'item_id': '200260', 'item_name': 'Batman: Arkham City GOTY', 'playtime_forever': 18, 'playtime_2weeks': 0}, {'item_id': '205790', 'item_name': 'Dota 2 Test', 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '3900', 'item_name': \"Sid Meier's Civilization IV\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '3910', 'item_name': \"Sid Meier's Civilization III: Complete\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '3920', 'item_name': \"Sid Meier's Pirates!\", 'playtime_forever': 91, 'playtime_2weeks': 0}, {'item_id': '3990', 'item_name': \"Sid Meier's Civilization IV: Warlords\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7650', 'item_name': 'X-COM: Terror from the Deep', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7660', 'item_name': 'X-COM: Apocalypse', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7670', 'item_name': 'BioShock', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7730', 'item_name': 'X-COM: Interceptor', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7760', 'item_name': 'X-COM: UFO Defense', 'playtime_forever': 27, 'playtime_2weeks': 0}, {'item_id': '7770', 'item_name': 'X-COM: Enforcer', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8800', 'item_name': \"Sid Meier's Civilization IV: Beyond the Sword\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8850', 'item_name': 'BioShock 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8880', 'item_name': 'Freedom Force', 'playtime_forever': 98, 'playtime_2weeks': 0}, {'item_id': '8890', 'item_name': 'Freedom Force vs. the 3rd Reich', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8930', 'item_name': \"Sid Meier's Civilization V\", 'playtime_forever': 1591, 'playtime_2weeks': 0}, {'item_id': '8970', 'item_name': 'Axel & Pixel', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8980', 'item_name': 'Borderlands', 'playtime_forever': 12, 'playtime_2weeks': 0}, {'item_id': '16810', 'item_name': \"Sid Meier's Civilization IV: Colonization\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '34440', 'item_name': \"Sid Meier's Civilization IV\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '34450', 'item_name': \"Sid Meier's Civilization IV: Warlords\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '34460', 'item_name': \"Sid Meier's Civilization IV: Beyond the Sword\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '40920', 'item_name': 'NBA 2K10', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '40930', 'item_name': 'The Misadventures of P.B. Winterbottom', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '40990', 'item_name': 'Mafia', 'playtime_forever': 21, 'playtime_2weeks': 0}, {'item_id': '50130', 'item_name': 'Mafia II', 'playtime_forever': 300, 'playtime_2weeks': 0}, {'item_id': '50310', 'item_name': 'MLB 2K11', 'playtime_forever': 9, 'playtime_2weeks': 0}, {'item_id': '57900', 'item_name': 'Duke Nukem Forever', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '65950', 'item_name': 'NBA 2K11', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '201020', 'item_name': 'NBA 2K12', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '409710', 'item_name': 'BioShock Remastered', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '409720', 'item_name': 'BioShock 2 Remastered', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '67370', 'item_name': 'The Darkness II', 'playtime_forever': 146, 'playtime_2weeks': 0}, {'item_id': '207610', 'item_name': 'The Walking Dead', 'playtime_forever': 457, 'playtime_2weeks': 0}, {'item_id': '97330', 'item_name': 'Magic: The Gathering - Duels of the Planeswalkers 2013', 'playtime_forever': 300, 'playtime_2weeks': 0}, {'item_id': '65800', 'item_name': 'Dungeon Defenders', 'playtime_forever': 4376, 'playtime_2weeks': 0}, {'item_id': '211420', 'item_name': 'Dark Souls: Prepare to Die Edition', 'playtime_forever': 71, 'playtime_2weeks': 0}, {'item_id': '730', 'item_name': 'Counter-Strike: Global Offensive', 'playtime_forever': 1900, 'playtime_2weeks': 0}, {'item_id': '204300', 'item_name': 'Awesomenauts', 'playtime_forever': 584, 'playtime_2weeks': 0}, {'item_id': '200170', 'item_name': 'Worms Revolution', 'playtime_forever': 423, 'playtime_2weeks': 0}, {'item_id': '217200', 'item_name': 'Worms Armageddon', 'playtime_forever': 4, 'playtime_2weeks': 0}, {'item_id': '204360', 'item_name': 'Castle Crashers', 'playtime_forever': 614, 'playtime_2weeks': 0}, {'item_id': '49520', 'item_name': 'Borderlands 2', 'playtime_forever': 3393, 'playtime_2weeks': 0}, {'item_id': '216890', 'item_name': 'Blood Bowl: Chaos Edition', 'playtime_forever': 846, 'playtime_2weeks': 0}, {'item_id': '200510', 'item_name': 'XCOM: Enemy Unknown', 'playtime_forever': 715, 'playtime_2weeks': 0}, {'item_id': '4920', 'item_name': 'Natural Selection 2', 'playtime_forever': 10, 'playtime_2weeks': 0}, {'item_id': '220240', 'item_name': 'Far Cry® 3', 'playtime_forever': 1336, 'playtime_2weeks': 0}, {'item_id': '219740', 'item_name': \"Don't Starve\", 'playtime_forever': 4806, 'playtime_2weeks': 0}, {'item_id': '322330', 'item_name': \"Don't Starve Together\", 'playtime_forever': 2, 'playtime_2weeks': 0}, {'item_id': '220440', 'item_name': 'DmC Devil May Cry', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '226700', 'item_name': 'Infestation: Survivor Stories Classic', 'playtime_forever': 22, 'playtime_2weeks': 0}, {'item_id': '4540', 'item_name': 'Titan Quest', 'playtime_forever': 40, 'playtime_2weeks': 0}, {'item_id': '4550', 'item_name': 'Titan Quest: Immortal Throne', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '4560', 'item_name': 'Company of Heroes', 'playtime_forever': 136, 'playtime_2weeks': 0}, {'item_id': '9340', 'item_name': 'Company of Heroes: Opposing Fronts', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '9350', 'item_name': 'Supreme Commander', 'playtime_forever': 15, 'playtime_2weeks': 0}, {'item_id': '9420', 'item_name': 'Supreme Commander: Forged Alliance', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '9480', 'item_name': 'Saints Row 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '15620', 'item_name': 'Warhammer® 40,000™: Dawn of War® II', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '20530', 'item_name': 'Red Faction', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '20550', 'item_name': 'Red Faction II', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '20570', 'item_name': 'Warhammer® 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{'item_id': '216370', 'item_name': 'Nexuiz Beta', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '225760', 'item_name': 'Nexuiz STUPID Mode', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '228200', 'item_name': 'Company of Heroes (New Steam Version)', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '475150', 'item_name': 'Titan Quest Anniversary Edition', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '228280', 'item_name': \"Baldur's Gate: Enhanced Edition\", 'playtime_forever': 481, 'playtime_2weeks': 0}, {'item_id': '11020', 'item_name': 'TrackMania Nations Forever', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '200210', 'item_name': 'Realm of the Mad God', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '205710', 'item_name': 'EverQuest Free-to-Play', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '207230', 'item_name': 'Archeblade', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '208090', 'item_name': 'Loadout', 'playtime_forever': 140, 'playtime_2weeks': 0}, {'item_id': '212500', 'item_name': 'The Lord of the Rings Online™', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '218230', 'item_name': 'PlanetSide 2', 'playtime_forever': 2808, 'playtime_2weeks': 0}, {'item_id': '230410', 'item_name': 'Warframe', 'playtime_forever': 252, 'playtime_2weeks': 0}, {'item_id': '236390', 'item_name': 'War Thunder', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '238960', 'item_name': 'Path of Exile', 'playtime_forever': 3579, 'playtime_2weeks': 0}, {'item_id': '243870', 'item_name': \"Tom Clancy's Ghost Recon Phantoms - NA\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '263500', 'item_name': 'Dragons and Titans', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '39120', 'item_name': 'RIFT', 'playtime_forever': 2866, 'playtime_2weeks': 0}, {'item_id': '242720', 'item_name': 'GunZ 2: The Second Duel', 'playtime_forever': 0, 'playtime_2weeks': 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'playtime_2weeks': 0}, {'item_id': '242760', 'item_name': 'The Forest', 'playtime_forever': 1677, 'playtime_2weeks': 0}, {'item_id': '206420', 'item_name': 'Saints Row IV', 'playtime_forever': 2402, 'playtime_2weeks': 0}, {'item_id': '213850', 'item_name': 'Magic 2014 ', 'playtime_forever': 861, 'playtime_2weeks': 0}, {'item_id': '244810', 'item_name': 'Foul Play', 'playtime_forever': 19, 'playtime_2weeks': 0}, {'item_id': '244850', 'item_name': 'Space Engineers', 'playtime_forever': 60, 'playtime_2weeks': 0}, {'item_id': '6880', 'item_name': 'Just Cause', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8190', 'item_name': 'Just Cause 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '239030', 'item_name': 'Papers, Please', 'playtime_forever': 98, 'playtime_2weeks': 0}, {'item_id': '218620', 'item_name': 'PAYDAY 2', 'playtime_forever': 2741, 'playtime_2weeks': 0}, {'item_id': '209000', 'item_name': 'Batman™: Arkham Origins', 'playtime_forever': 2369, 'playtime_2weeks': 0}, {'item_id': '239820', 'item_name': 'Game Dev Tycoon', 'playtime_forever': 448, 'playtime_2weeks': 0}, {'item_id': '250320', 'item_name': 'The Wolf Among Us', 'playtime_forever': 668, 'playtime_2weeks': 0}, {'item_id': '219640', 'item_name': 'Chivalry: Medieval Warfare', 'playtime_forever': 34, 'playtime_2weeks': 0}, {'item_id': '232210', 'item_name': 'Patch testing for Chivalry', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '208610', 'item_name': 'Skullgirls ∞Endless Beta∞', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '245170', 'item_name': 'Skullgirls', 'playtime_forever': 212, 'playtime_2weeks': 0}, {'item_id': '228560', 'item_name': 'Teenage Mutant Ninja Turtles: Out of the Shadows', 'playtime_forever': 1237, 'playtime_2weeks': 0}, {'item_id': '251570', 'item_name': '7 Days to Die', 'playtime_forever': 3034, 'playtime_2weeks': 0}, {'item_id': '252350', 'item_name': 'Double Dragon Neon', 'playtime_forever': 264, 'playtime_2weeks': 0}, {'item_id': '252490', 'item_name': 'Rust', 'playtime_forever': 3483, 'playtime_2weeks': 0}, {'item_id': '252950', 'item_name': 'Rocket League', 'playtime_forever': 915, 'playtime_2weeks': 0}, {'item_id': '241540', 'item_name': 'State of Decay', 'playtime_forever': 2099, 'playtime_2weeks': 0}, {'item_id': '237890', 'item_name': 'Agarest: Generations of War', 'playtime_forever': 135, 'playtime_2weeks': 0}, {'item_id': '242050', 'item_name': \"Assassin's Creed IV Black Flag\", 'playtime_forever': 6221, 'playtime_2weeks': 0}, {'item_id': '234530', 'item_name': 'War of the Vikings', 'playtime_forever': 2509, 'playtime_2weeks': 0}, {'item_id': '257350', 'item_name': \"Baldur's Gate II: Enhanced Edition\", 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '243470', 'item_name': 'Watch_Dogs', 'playtime_forever': 2043, 'playtime_2weeks': 0}, {'item_id': '247730', 'item_name': 'Nether', 'playtime_forever': 3114, 'playtime_2weeks': 0}, {'item_id': '260730', 'item_name': 'Desperados - Wanted Dead or Alive', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '261030', 'item_name': 'The Walking Dead: Season Two', 'playtime_forever': 637, 'playtime_2weeks': 0}, {'item_id': '242700', 'item_name': 'Injustice: Gods Among Us Ultimate Edition', 'playtime_forever': 368, 'playtime_2weeks': 0}, {'item_id': '262060', 'item_name': 'Darkest Dungeon', 'playtime_forever': 332, 'playtime_2weeks': 0}, {'item_id': '263440', 'item_name': 'The Stomping Land', 'playtime_forever': 142, 'playtime_2weeks': 0}, {'item_id': '108600', 'item_name': 'Project Zomboid', 'playtime_forever': 160, 'playtime_2weeks': 0}, {'item_id': '211820', 'item_name': 'Starbound', 'playtime_forever': 137, 'playtime_2weeks': 0}, {'item_id': '367540', 'item_name': 'Starbound - Unstable', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '41900', 'item_name': \"The Bard's Tale\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '240760', 'item_name': 'Wasteland 2', 'playtime_forever': 710, 'playtime_2weeks': 0}, {'item_id': '259130', 'item_name': 'Wasteland 1 - The Original Classic', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '404730', 'item_name': \"Wasteland 2: Director's Cut\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '221100', 'item_name': 'DayZ', 'playtime_forever': 131, 'playtime_2weeks': 0}, {'item_id': '202170', 'item_name': 'Sleeping Dogs™', 'playtime_forever': 1322, 'playtime_2weeks': 0}, {'item_id': '268870', 'item_name': 'Satellite Reign', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '239840', 'item_name': 'Dead State', 'playtime_forever': 718, 'playtime_2weeks': 0}, {'item_id': '271590', 'item_name': 'Grand Theft Auto V', 'playtime_forever': 6740, 'playtime_2weeks': 0}, {'item_id': '273110', 'item_name': 'Counter-Strike Nexon: Zombies', 'playtime_forever': 6, 'playtime_2weeks': 0}, {'item_id': '274310', 'item_name': 'Always Sometimes Monsters', 'playtime_forever': 501, 'playtime_2weeks': 0}, {'item_id': '213670', 'item_name': 'South Park™: The Stick of Truth™', 'playtime_forever': 1105, 'playtime_2weeks': 0}, {'item_id': '278080', 'item_name': 'DYNASTY WARRIORS 8: Xtreme Legends Complete Edition', 'playtime_forever': 671, 'playtime_2weeks': 0}, {'item_id': '48700', 'item_name': 'Mount & Blade: Warband', 'playtime_forever': 871, 'playtime_2weeks': 0}, {'item_id': '254700', 'item_name': 'resident evil 4 / biohazard 4', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '235210', 'item_name': 'Strider', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '290140', 'item_name': 'Echo of Soul', 'playtime_forever': 44, 'playtime_2weeks': 0}, {'item_id': '290300', 'item_name': 'Rebel Galaxy', 'playtime_forever': 96, 'playtime_2weeks': 0}, {'item_id': '293780', 'item_name': 'Crawl', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '295110', 'item_name': 'H1Z1: Just Survive', 'playtime_forever': 4778, 'playtime_2weeks': 0}, {'item_id': '362300', 'item_name': 'H1Z1: Just Survive Test Server', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '433850', 'item_name': 'H1Z1: King of the Kill', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '439700', 'item_name': 'H1Z1: King of the Kill Test Server', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '222900', 'item_name': 'Dead Island: Epidemic', 'playtime_forever': 268, 'playtime_2weeks': 0}, {'item_id': '300550', 'item_name': \"Shadowrun: Dragonfall - Director's Cut\", 'playtime_forever': 1056, 'playtime_2weeks': 0}, {'item_id': '300570', 'item_name': 'Infinifactory', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '300580', 'item_name': 'GALAK-Z', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '301520', 'item_name': 'Robocraft', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '302270', 'item_name': 'Dungeon Defenders Eternity', 'playtime_forever': 551, 'playtime_2weeks': 0}, {'item_id': '304050', 'item_name': 'Trove', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '304030', 'item_name': 'ArcheAge', 'playtime_forever': 12249, 'playtime_2weeks': 0}, {'item_id': '304930', 'item_name': 'Unturned', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '244630', 'item_name': 'NEOTOKYO°', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '312990', 'item_name': 'The Expendabros', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '227940', 'item_name': 'Heroes & Generals', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '265590', 'item_name': 'The Red Solstice', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '241930', 'item_name': 'Middle-earth: Shadow of Mordor', 'playtime_forever': 1494, 'playtime_2weeks': 0}, {'item_id': '265550', 'item_name': 'Dead Rising 3', 'playtime_forever': 171, 'playtime_2weeks': 0}, {'item_id': '226720', 'item_name': 'Lost Planet 3', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '323370', 'item_name': 'TERA', 'playtime_forever': 1785, 'playtime_2weeks': 0}, {'item_id': '327510', 'item_name': 'WASTED', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '261640', 'item_name': 'Borderlands: The Pre-Sequel', 'playtime_forever': 2462, 'playtime_2weeks': 0}, {'item_id': '330840', 'item_name': 'Game of Thrones - A Telltale Games Series', 'playtime_forever': 719, 'playtime_2weeks': 0}, {'item_id': '17570', 'item_name': 'Pirates, Vikings, & Knights II', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '305620', 'item_name': 'The Long Dark', 'playtime_forever': 404, 'playtime_2weeks': 0}, {'item_id': '323470', 'item_name': 'DRAGON BALL XENOVERSE', 'playtime_forever': 920, 'playtime_2weeks': 0}, {'item_id': '333930', 'item_name': 'Dirty Bomb', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '249050', 'item_name': 'Dungeon of the Endless', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '236110', 'item_name': 'Dungeon Defenders II', 'playtime_forever': 88, 'playtime_2weeks': 0}, {'item_id': '337850', 'item_name': 'Avernum 2: Crystal Souls', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '339120', 'item_name': \"Fork Parker's Holiday Profit Hike\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '342200', 'item_name': 'MechWarrior Online', 'playtime_forever': 699, 'playtime_2weeks': 0}, {'item_id': '314660', 'item_name': \"Oddworld: New 'n' Tasty\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '345520', 'item_name': 'Infinite Crisis™', 'playtime_forever': 406, 'playtime_2weeks': 0}, {'item_id': '346110', 'item_name': 'ARK: Survival Evolved', 'playtime_forever': 23434, 'playtime_2weeks': 0}, {'item_id': '407530', 'item_name': 'ARK: Survival Of The Fittest', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '347160', 'item_name': 'Steredenn', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '287290', 'item_name': 'Resident Evil Revelations 2 / Biohazard Revelations 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '339280', 'item_name': 'Strife', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '351570', 'item_name': 'Killing Floor: Uncovered', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '232090', 'item_name': 'Killing Floor 2', 'playtime_forever': 1171, 'playtime_2weeks': 0}, {'item_id': '232150', 'item_name': 'Killing Floor 2 - SDK', 'playtime_forever': 2, 'playtime_2weeks': 0}, {'item_id': '362070', 'item_name': 'Metal Reaper Online', 'playtime_forever': 8, 'playtime_2weeks': 0}, {'item_id': '47780', 'item_name': 'Dead Space 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '362680', 'item_name': 'Fran Bow', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '329460', 'item_name': 'JumpJet Rex', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '365590', 'item_name': \"Tom Clancy's The Division\", 'playtime_forever': 10442, 'playtime_2weeks': 0}, {'item_id': '329050', 'item_name': 'Devil May Cry® 4 Special Edition', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '370360', 'item_name': 'TIS-100', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '292030', 'item_name': 'The Witcher 3: Wild Hunt', 'playtime_forever': 2140, 'playtime_2weeks': 0}, {'item_id': '373480', 'item_name': '1993 Space Machine', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '377160', 'item_name': 'Fallout 4', 'playtime_forever': 7194, 'playtime_2weeks': 0}, {'item_id': '386070', 'item_name': 'Planetary Annihilation: TITANS', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '386360', 'item_name': 'SMITE', 'playtime_forever': 498, 'playtime_2weeks': 0}, {'item_id': '234140', 'item_name': 'Mad Max', 'playtime_forever': 1123, 'playtime_2weeks': 0}, {'item_id': '393420', 'item_name': 'Hurtworld', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '445900', 'item_name': 'Hurtworld SDK', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '394310', 'item_name': 'Punch Club', 'playtime_forever': 416, 'playtime_2weeks': 0}, {'item_id': '413150', 'item_name': 'Stardew Valley', 'playtime_forever': 1321, 'playtime_2weeks': 0}, {'item_id': '268500', 'item_name': 'XCOM 2', 'playtime_forever': 620, 'playtime_2weeks': 0}, {'item_id': '444560', 'item_name': 'Agent Origins: Escape', 'playtime_forever': 9, 'playtime_2weeks': 0}, {'item_id': '275850', 'item_name': \"No Man's Sky\", 'playtime_forever': 564, 'playtime_2weeks': 0}]}\n"]}]},{"cell_type":"code","source":["# Open the gzipped file\n","bundle_data = {}\n","data_dict = None\n","count = {\n","    \"bundles\": 0,\n","    \"items\": 0\n","}\n","data_items = None\n","with gzip.open(f\"{file_path}/{files[2]}\", 'rt', encoding='utf-8') as f:  # 'rt' is for text mode\n","    for i, line in enumerate(f):\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","            data_items = set()\n","\n","            if len(data_dict[\"items\"]) > 0:\n","              count[\"items\"] += len(data_dict[\"items\"])\n","              count[\"bundles\"] += 1\n","\n","              for item in data_dict[\"items\"]:\n","                data_items.add(item[\"item_id\"])\n","\n","              bundle_data[data_dict['bundle_id']] = data_items\n","        except (ValueError, SyntaxError) as e:\n","            print(f\"Failed to convert string to dictionary: {e}\")\n","\n","print(f\"Number of bundle {count['bundles']}\")\n","print(f\"Number of items {count['items']}\")\n","print(data_dict)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZnLJTSvOm6tH","executionInfo":{"status":"ok","timestamp":1735800052537,"user_tz":-420,"elapsed":9,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"cba8565b-368a-4417-a15f-188b93e1f66b"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of bundle 615\n","Number of items 3525\n","{'bundle_final_price': '$4.77', 'bundle_url': 'http://store.steampowered.com/bundle/594/?utm_source=SteamDB&utm_medium=SteamDB&utm_campaign=SteamDB%20Bundles%20Page', 'bundle_price': '$5.97', 'bundle_name': 'The Ninjahtic Series', 'bundle_id': '594', 'items': [{'genre': 'Action, Adventure, Indie', 'item_id': '385230', 'discounted_price': '$1.99', 'item_url': 'http://store.steampowered.com/app/385230', 'item_name': 'Ninjahtic'}, {'genre': 'Action, Adventure, Indie', 'item_id': '387880', 'discounted_price': '$1.99', 'item_url': 'http://store.steampowered.com/app/387880', 'item_name': 'Ninjahtic Mind Tricks'}, {'genre': 'Action, Indie', 'item_id': '454130', 'discounted_price': '$1.99', 'item_url': 'http://store.steampowered.com/app/454130', 'item_name': 'Nil-Ninjahtic: Ronin'}], 'bundle_discount': '20%'}\n"]}]},{"cell_type":"code","source":["# Open the gzipped file\n","items_dictionary = {}\n","data_dict = None\n","count = {\n","    \"items\": 0\n","}\n","with gzip.open(f\"{file_path}/{files[3]}\", 'rt', encoding='utf-8') as f:  # 'rt' is for text mode\n","    for i, line in enumerate(f):\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","            if 'id' in data_dict:\n","              items_dictionary[data_dict['id']] = data_dict\n","              count[\"items\"] += 1\n","        except (ValueError, SyntaxError) as e:\n","            print(f\"Failed to convert string to dictionary: {e}\")\n","\n","print(f\"Number of items {count['items']}\")\n","print(data_dict)"],"metadata":{"id":"KwK2r2ospM7p","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1735800058131,"user_tz":-420,"elapsed":5596,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"307a91cd-c88a-451a-e618-26bb16e52883"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of items 32133\n","{'app_name': 'Maze Run VR', 'sentiment': 'Positive', 'tags': ['Early Access', 'Adventure', 'Indie', 'Action', 'Simulation', 'VR'], 'url': 'http://store.steampowered.com/app/681550/Maze_Run_VR/', 'price': 4.99, 'reviews_url': 'http://steamcommunity.com/app/681550/reviews/?browsefilter=mostrecent&p=1', 'id': '681550', 'early_access': True, 'specs': ['Single-player', 'Stats', 'Steam Leaderboards', 'HTC Vive', 'Oculus Rift', 'Tracked Motion Controllers', 'Standing', 'Room-Scale']}\n"]}]},{"cell_type":"code","source":["# prompt: Show me distribution of sentiment attribute on items_dictionary\n","\n","import matplotlib.pyplot as plt\n","\n","# Assuming 'items_dictionary' is defined and accessible\n","\n","sentiment_counts = {}\n","for item_id, item_data in items_dictionary.items():\n","    if 'sentiment' in item_data:\n","        sentiment = item_data['sentiment']\n","        sentiment_counts[sentiment] = sentiment_counts.get(sentiment, 0) + 1\n","\n","sentiments, counts = zip(*sentiment_counts.items())\n","\n","plt.figure(figsize=(10, 6))\n","plt.bar(sentiments, counts, color='skyblue')\n","plt.xlabel(\"Sentiment\")\n","plt.ylabel(\"Number of Items\")\n","plt.title(\"Distribution of Sentiment Attribute in items_dictionary\")\n","plt.xticks(rotation=45, ha='right')  # Rotate x-axis labels for better readability\n","plt.tight_layout() # Adjust layout to prevent labels from overlapping\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":607},"id":"9HG4u_54plVH","executionInfo":{"status":"ok","timestamp":1735479680885,"user_tz":-420,"elapsed":730,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"2a732e27-e0bc-41f3-8417-703fc4de328b"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["# prompt: From data sentiment_counts i want to sorted from very positive to very negative\n","\n","import operator\n","\n","sorted_sentiment_counts = dict(sorted(sentiment_counts.items(), key=operator.itemgetter(1), reverse=True))\n","\n","sentiments, counts = zip(*sorted_sentiment_counts.items())\n","\n","plt.figure(figsize=(10, 6))\n","plt.bar(sentiments, counts, color='skyblue')\n","plt.xlabel(\"Sentiment\")\n","plt.ylabel(\"Number of Items\")\n","plt.title(\"Distribution of Sentiment Attribute in items_dictionary (Sorted)\")\n","plt.xticks(rotation=45, ha='right')  # Rotate x-axis labels for better readability\n","plt.tight_layout() # Adjust layout to prevent labels from overlapping\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":607},"id":"sjR-gufgppmg","executionInfo":{"status":"ok","timestamp":1735479926795,"user_tz":-420,"elapsed":948,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"e8acb122-9e3e-4b2d-fd64-15bfc992059f"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["def generate_sentiment_value(sentimen_str):\n","  if sentimen_str == 'Overwhelmingly Positive':\n","    return 1.00\n","  elif sentimen_str == 'Very Positive':\n","    return 0.80\n","  elif sentimen_str == 'Positive':\n","    return 0.60\n","  elif sentimen_str == 'Mostly Positive':\n","    return 0.40\n","  elif sentimen_str == '9 user reviews':\n","    return 0.25\n","  elif sentimen_str == '8 user reviews':\n","    return 0.20\n","  elif sentimen_str == '7 user reviews':\n","    return 0.15\n","  elif sentimen_str == '6 user reviews':\n","    return 0.10\n","  elif sentimen_str == 'Mixed':\n","    return 0.5\n","  elif sentimen_str == '5 user reviews':\n","    return -0.5\n","  elif sentimen_str == '4 user reviews':\n","    return -0.10\n","  elif sentimen_str == '3 user reviews':\n","    return -0.15\n","  elif sentimen_str == '2 user reviews':\n","    return -0.20\n","  elif sentimen_str == '1 user review':\n","    return -0.25\n","  elif sentimen_str == 'Mostly Negative':\n","    return -0.40\n","  elif sentimen_str == 'Negative':\n","    return -0.60\n","  elif sentimen_str == 'Very Negative':\n","    return -0.85\n","  elif sentimen_str == 'Overwhelmingly Negative':\n","    return -1.00\n","  else:\n","    return 0.00"],"metadata":{"id":"Pd-DAKhQtwcR","executionInfo":{"status":"ok","timestamp":1735798610676,"user_tz":-420,"elapsed":2,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":5,"outputs":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"n1KqBF9ifNWl","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1735483038727,"user_tz":-420,"elapsed":200148,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"b3348ae6-1bbd-4ff3-8c76-ef6b88f42656"},"outputs":[{"output_type":"stream","name":"stdout","text":["{'user_id': '76561198030000787', 'bundle_id': '594', 'is_recommended': '1'}\n"]}],"source":["import pandas as pd\n","import json\n","import gzip\n","import operator\n","\n","filepath_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs/recommendation_data_logreg.json.gz'\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_logreg.json.gz'\n","\n","data_dict = None\n","\n","users_ids = set()\n","users_bundle_candidate_bfr = set()\n","users_bundle_candidate_bfr_sentiment = {}\n","\n","with gzip.open(filepath_rec_data, 'rt', encoding='utf-8') as file, gzip.open(filepath_rarank_rec_data, 'wt', encoding='utf-8') as outfile:\n","    for line in file:\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","\n","            if int(data_dict[\"is_recommended\"]) == 1:\n","              users_bundle_candidate_bfr.add(data_dict['bundle_id'])\n","\n","            if data_dict['user_id'] not in users_ids:\n","              # Handle for the first checkking\n","              if len(users_ids) == 0:\n","                users_ids.add(data_dict['user_id'])\n","              else:\n","                # Do Reranking here\n","                for bundle_id in users_bundle_candidate_bfr:\n","                  users_bundle_candidate_bfr_sentiment[bundle_id] = 0\n","                  for item_id in bundle_data[bundle_id]:\n","                    if item_id in items_dictionary and \"sentiment\" in items_dictionary[item_id]:\n","                      users_bundle_candidate_bfr_sentiment[bundle_id] += generate_sentiment_value(items_dictionary[item_id]['sentiment'])\n","\n","                users_bundle_candidate_bfr = sorted(users_bundle_candidate_bfr_sentiment.items(), key=operator.itemgetter(1), reverse=True)\n","\n","                json.dump({ \"user_id\": data_dict['user_id'], \"rec_bundles\": dict(users_bundle_candidate_bfr) }, outfile, ensure_ascii=False)\n","                outfile.write('\\n')\n","\n","                # Reset data\n","                users_ids.add(data_dict['user_id'])\n","                users_bundle_candidate_bfr = set()\n","                users_bundle_candidate_bfr_sentiment = {}\n","        except json.JSONDecodeError as e:\n","            print(f\"Error decoding JSON line: {e}\")\n","            # Handle the error as needed (e.g., skip the line, log the error, etc.)\n","\n","print(data_dict)"]},{"cell_type":"code","source":["import pandas as pd\n","import json\n","import gzip\n","import operator\n","\n","filepath_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns/recommendation_data_logreg.json.gz'\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_logreg.json.gz'\n","\n","data_dict = None\n","\n","users_ids = set()\n","users_bundle_candidate_bfr = set()\n","users_bundle_candidate_bfr_sentiment = {}\n","\n","with gzip.open(filepath_rec_data, 'rt', encoding='utf-8') as file, gzip.open(filepath_rarank_rec_data, 'wt', encoding='utf-8') as outfile:\n","    for line in file:\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","\n","            if int(data_dict[\"is_recommended\"]) == 1:\n","              users_bundle_candidate_bfr.add(data_dict['bundle_id'])\n","\n","            if data_dict['user_id'] not in users_ids:\n","              # Handle for the first checkking\n","              if len(users_ids) == 0:\n","                users_ids.add(data_dict['user_id'])\n","              else:\n","                # Do Reranking here\n","                for bundle_id in users_bundle_candidate_bfr:\n","                  users_bundle_candidate_bfr_sentiment[bundle_id] = 0\n","                  for item_id in bundle_data[bundle_id]:\n","                    if item_id in items_dictionary and \"sentiment\" in items_dictionary[item_id]:\n","                      users_bundle_candidate_bfr_sentiment[bundle_id] += generate_sentiment_value(items_dictionary[item_id]['sentiment'])\n","\n","                users_bundle_candidate_bfr = sorted(users_bundle_candidate_bfr_sentiment.items(), key=operator.itemgetter(1), reverse=True)\n","\n","                json.dump({ \"user_id\": data_dict['user_id'], \"rec_bundles\": dict(users_bundle_candidate_bfr) }, outfile, ensure_ascii=False)\n","                outfile.write('\\n')\n","\n","                # Reset data\n","                users_ids.add(data_dict['user_id'])\n","                users_bundle_candidate_bfr = set()\n","                users_bundle_candidate_bfr_sentiment = {}\n","        except json.JSONDecodeError as e:\n","            print(f\"Error decoding JSON line: {e}\")\n","            # Handle the error as needed (e.g., skip the line, log the error, etc.)\n","\n","print(data_dict)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Z8x2uLIoqBQw","executionInfo":{"status":"ok","timestamp":1735798802171,"user_tz":-420,"elapsed":191497,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"e2ac0637-5d33-479d-a5d5-cdc6f08258ca"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["{'user_id': '76561198030000787', 'bundle_id': '594', 'is_recommended': '0'}\n"]}]},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","# Open the gzipped file\n","data_dict = None\n","\n","try:\n","    with gzip.open(filepath_rarank_rec_data, 'rt', encoding='utf-8') as infile:\n","        for line in infile:\n","            try:\n","                data_dict = json.loads(line) # Use json.loads instead of ast.literal_eval\n","                count = len(data_dict['rec_bundles'])\n","            except json.JSONDecodeError as e:\n","                print(f\"Error decoding JSON: {e}, skipping line: {line}\")\n","    print(f\"File '{filepath_rarank_rec_data}' successfully processed and saved to '{filepath_rarank_rec_data}'\")\n","\n","except FileNotFoundError:\n","    print(f\"Error: File not found at {filepath_rarank_rec_data}\")\n","except Exception as e:\n","    print(f\"An unexpected error occurred: {e}\")\n","\n","print(f\"Count: {count}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-nz3SqNvj-F7","executionInfo":{"status":"ok","timestamp":1735798812899,"user_tz":-420,"elapsed":1844,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"3cd28fde-55d6-4584-df5e-4b64e7074da1"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["File '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_logreg.json.gz' successfully processed and saved to '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_logreg.json.gz'\n","Count: 138\n"]}]},{"cell_type":"code","source":[],"metadata":{"id":"KOOpGM97TFV8"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Evaluate\n"],"metadata":{"id":"q1DFXWFOCsP0"}},{"cell_type":"code","source":["# prompt: get top rec_bundles from data_dict with variation TOP 5 until top 20 with space 5\n","\n","def get_top_rec_bundles(data_dict, start=5, end=20, step=5):\n","  \"\"\"\n","  Gets top recommended bundles from data_dict with variations.\n","\n","  Args:\n","    data_dict: A dictionary containing recommendation data.\n","    start: The starting rank of top bundles.\n","    end: The ending rank of top bundles.\n","    step: The increment in rank.\n","\n","  Returns:\n","    A list of dictionaries, where each dictionary contains the user ID and top recommended bundles for a specified range.\n","    Returns an empty list if 'rec_bundles' key not found in data_dict.\n","  \"\"\"\n","\n","  if 'rec_bundles' not in data_dict:\n","    return []\n","\n","  results = []\n","  for top_n in range(start, end + 1, step):\n","    top_bundles = dict(sorted(data_dict['rec_bundles'].items(), key=lambda item: item[1], reverse=True)[:top_n])\n","    results.append({\"user_id\": data_dict['user_id'], \"top_rec_bundles\": top_bundles, \"top_n\": top_n})\n","  return results\n","\n","# Example usage (assuming data_dict is defined as in the provided code)\n","# Assuming data_dict contains the following:\n","# data_dict = {\"user_id\": 123, \"rec_bundles\": {\"bundle_1\": 0.9, \"bundle_2\": 0.8, \"bundle_3\": 0.7, \"bundle_4\": 0.6, \"bundle_5\": 0.5, \"bundle_6\": 0.4, \"bundle_7\": 0.3, \"bundle_8\":0.2, \"bundle_9\":0.1, \"bundle_10\": 0.0}}"],"metadata":{"id":"1M0JQWwPEAK5","executionInfo":{"status":"ok","timestamp":1735800058131,"user_tz":-420,"elapsed":3,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":5,"outputs":[]},{"cell_type":"code","source":["# prompt: Calculate hit_ratio from top_bundles_results by calculating how many items from user_item_interactions is on bundle_data by bundle_id and item_id\n","\n","def calculate_hit_ratio(top_bundles_results, user_item_interactions, bundle_data):\n","    \"\"\"\n","    Calculates the hit ratio based on the provided data.\n","\n","    Args:\n","        top_bundles_results: A list of dictionaries, where each dictionary contains user ID and top recommended bundles.\n","        user_item_interactions: A dictionary mapping user IDs to their item interactions.\n","        bundle_data: A dictionary mapping bundle IDs to their items.\n","\n","    Returns:\n","        A list of dictionaries, each containing the user ID, top N, and hit ratio.\n","    \"\"\"\n","\n","    hit_ratios = []\n","    for result in top_bundles_results:\n","        user_id = result['user_id']\n","        top_n = result['top_n']\n","        top_bundles = result['top_rec_bundles']\n","\n","        hits = 0\n","        if user_id in user_item_interactions:\n","            user_items = set(user_item_interactions[user_id].keys())\n","            for bundle_id in top_bundles:\n","                if bundle_id in bundle_data:\n","                  bundle_items = bundle_data[bundle_id]\n","                  hits += len(user_items.intersection(bundle_items))\n","\n","        hit_ratio = hits / top_n if top_n > 0 else 0  # Avoid division by zero\n","        hit_ratios.append({\"user_id\": user_id, \"top_n\": top_n, \"hit_ratio\": hit_ratio})\n","    return hit_ratios"],"metadata":{"id":"OBktUkbTEm5u","executionInfo":{"status":"ok","timestamp":1735800058131,"user_tz":-420,"elapsed":2,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":6,"outputs":[]},{"cell_type":"code","source":["# prompt: Calculate diversity from top_bundles_results by calculating how many items from user_item_interactions is on bundle_data by bundle_id and item_id\n","\n","def calculate_intra_diversity(top_bundles_results, user_item_interactions, bundle_data):\n","    \"\"\"\n","    Calculates the diversity of recommended bundles.\n","\n","    Args:\n","        top_bundles_results: A list of dictionaries, where each dictionary contains user ID and top recommended bundles.\n","        user_item_interactions: A dictionary mapping user IDs to their item interactions.\n","        bundle_data: A dictionary mapping bundle IDs to their items.\n","\n","    Returns:\n","        A list of dictionaries, each containing the user ID, top N, and diversity score.\n","    \"\"\"\n","    diversity_scores = []\n","    for result in top_bundles_results:\n","        user_id = result['user_id']\n","        top_n = result['top_n']\n","        top_bundles = result['top_rec_bundles']\n","\n","        total_items = 0\n","        unique_items = set()\n","\n","        for bundle_id in top_bundles:\n","          if bundle_id in bundle_data:\n","            bundle_items = bundle_data[bundle_id]\n","            total_items += len(bundle_items)\n","            unique_items.update(bundle_items)\n","\n","        diversity = len(unique_items) / total_items if total_items > 0 else 0\n","        diversity_scores.append({\"user_id\": user_id, \"top_n\": top_n, \"diversity\": diversity})\n","    return diversity_scores"],"metadata":{"id":"Y9x5v5iNFzlZ","executionInfo":{"status":"ok","timestamp":1735800058131,"user_tz":-420,"elapsed":2,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":7,"outputs":[]},{"cell_type":"code","source":["# prompt: Calculate inter_diversity from top_bundles_results by checkking how similar for each bundle\n","\n","import json\n","import gzip\n","import ast\n","import matplotlib.pyplot as plt\n","import operator\n","import pandas as pd\n","\n","# ... (Your existing code)\n","\n","def calculate_inter_diversity(top_bundles_results, bundle_data):\n","    \"\"\"\n","    Calculates the inter-diversity of recommended bundles.\n","\n","    Args:\n","        top_bundles_results: A list of dictionaries, where each dictionary contains user ID and top recommended bundles.\n","        bundle_data: A dictionary mapping bundle IDs to their items.\n","\n","    Returns:\n","        A list of dictionaries, each containing the user ID, top N, and inter-diversity score.\n","    \"\"\"\n","    inter_diversity_scores = []\n","    for result in top_bundles_results:\n","        user_id = result['user_id']\n","        top_n = result['top_n']\n","        top_bundles = result['top_rec_bundles']\n","\n","        jaccard_similarities = []\n","        bundle_ids = list(top_bundles.keys())\n","        for i in range(len(bundle_ids)):\n","            for j in range(i + 1, len(bundle_ids)):\n","                bundle1_id = bundle_ids[i]\n","                bundle2_id = bundle_ids[j]\n","                if bundle1_id in bundle_data and bundle2_id in bundle_data:\n","                    bundle1_items = bundle_data[bundle1_id]\n","                    bundle2_items = bundle_data[bundle2_id]\n","                    intersection = len(bundle1_items.intersection(bundle2_items))\n","                    union = len(bundle1_items.union(bundle2_items))\n","                    jaccard_similarity = intersection / union if union > 0 else 0\n","                    jaccard_similarities.append(1 - jaccard_similarity)  # 1-similarity to represent diversity\n","\n","        inter_diversity = sum(jaccard_similarities) / len(jaccard_similarities) if jaccard_similarities else 0\n","        inter_diversity_scores.append({\"user_id\": user_id, \"top_n\": top_n, \"inter_diversity\": inter_diversity})\n","    return inter_diversity_scores"],"metadata":{"id":"As-qpdgrGIDw","executionInfo":{"status":"ok","timestamp":1735800058534,"user_tz":-420,"elapsed":405,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":8,"outputs":[]},{"cell_type":"code","source":["data_dict"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"W5jfzwYKD21C","executionInfo":{"status":"ok","timestamp":1735524259175,"user_tz":-420,"elapsed":16,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"25ba9694-af66-435e-e371-d2fe8ae2fbc3"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'bundle_final_price': '$4.77',\n"," 'bundle_url': 'http://store.steampowered.com/bundle/594/?utm_source=SteamDB&utm_medium=SteamDB&utm_campaign=SteamDB%20Bundles%20Page',\n"," 'bundle_price': '$5.97',\n"," 'bundle_name': 'The Ninjahtic Series',\n"," 'bundle_id': '594',\n"," 'items': [{'genre': 'Action, Adventure, Indie',\n","   'item_id': '385230',\n","   'discounted_price': '$1.99',\n","   'item_url': 'http://store.steampowered.com/app/385230',\n","   'item_name': 'Ninjahtic'},\n","  {'genre': 'Action, Adventure, Indie',\n","   'item_id': '387880',\n","   'discounted_price': '$1.99',\n","   'item_url': 'http://store.steampowered.com/app/387880',\n","   'item_name': 'Ninjahtic Mind Tricks'},\n","  {'genre': 'Action, Indie',\n","   'item_id': '454130',\n","   'discounted_price': '$1.99',\n","   'item_url': 'http://store.steampowered.com/app/454130',\n","   'item_name': 'Nil-Ninjahtic: Ronin'}],\n"," 'bundle_discount': '20%'}"]},"metadata":{},"execution_count":8}]},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","# Open the gzipped file\n","data_dict = None\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_logreg.json.gz'\n","\n","average_hit_ratio = {}\n","average_intra_diversity = {}\n","average_inter_diversity = {}\n","count = 0\n","\n","top_bundles_results = []\n","hit_ratios = []\n","intra_diversity_scores = []\n","inter_diversity_scores = []\n","\n","try:\n","    with gzip.open(filepath_rarank_rec_data, 'rt', encoding='utf-8') as infile:\n","        for line in infile:\n","            try:\n","                data_dict = json.loads(line) # Use json.loads instead of ast.literal_eval\n","\n","                top_bundles_results = get_top_rec_bundles(data_dict)\n","                hit_ratios = calculate_hit_ratio(top_bundles_results, user_item_interactions, bundle_data)\n","                intra_diversity_scores = calculate_intra_diversity(top_bundles_results, user_item_interactions, bundle_data)\n","                inter_diversity_scores = calculate_inter_diversity(top_bundles_results, bundle_data)\n","\n","                average_hit_ratio[data_dict['user_id']] = hit_ratios\n","                average_intra_diversity[data_dict['user_id']] = intra_diversity_scores\n","                average_inter_diversity[data_dict['user_id']] = inter_diversity_scores\n","\n","            except json.JSONDecodeError as e:\n","                print(f\"Error decoding JSON: {e}, skipping line: {line}\")\n","            count += 1\n","            print(f\"{count} /  9881\")\n","    print(f\"File '{filepath_rarank_rec_data}' successfully processed and saved to '{filepath_rarank_rec_data}'\")\n","\n","except FileNotFoundError:\n","    print(f\"Error: File not found at {filepath_rarank_rec_data}\")\n","except Exception as e:\n","    print(f\"An unexpected error occurred: {e}\")\n","\n","print(f\"Count: {count}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jn67YIwICr93","executionInfo":{"status":"ok","timestamp":1735524292845,"user_tz":-420,"elapsed":33679,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"495b86f9-fa0e-4c31-cc44-2b957ee6ae84","collapsed":true},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n","4883 /  9881\n","4884 /  9881\n","4885 /  9881\n","4886 /  9881\n","4887 /  9881\n","4888 /  9881\n","4889 /  9881\n","4890 /  9881\n","4891 /  9881\n","4892 /  9881\n","4893 /  9881\n","4894 /  9881\n","4895 /  9881\n","4896 /  9881\n","4897 /  9881\n","4898 /  9881\n","4899 /  9881\n","4900 /  9881\n","4901 /  9881\n","4902 /  9881\n","4903 /  9881\n","4904 /  9881\n","4905 /  9881\n","4906 /  9881\n","4907 /  9881\n","4908 /  9881\n","4909 /  9881\n","4910 /  9881\n","4911 /  9881\n","4912 /  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Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_logreg.json.gz' successfully processed and saved to '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_logreg.json.gz'\n","Count: 9880\n"]}]},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","# Open the gzipped file\n","data_dict = None\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_logreg.json.gz'\n","\n","average_hit_ratio = {}\n","average_intra_diversity = {}\n","average_inter_diversity = {}\n","count = 0\n","\n","top_bundles_results = []\n","hit_ratios = []\n","intra_diversity_scores = []\n","inter_diversity_scores = []\n","\n","try:\n","    with gzip.open(filepath_rarank_rec_data, 'rt', encoding='utf-8') as infile:\n","        for line in infile:\n","            try:\n","                data_dict = json.loads(line) # Use json.loads instead of ast.literal_eval\n","\n","                if len(data_dict[\"rec_bundles\"]) > 0:\n","\n","                  top_bundles_results = get_top_rec_bundles(data_dict)\n","                  hit_ratios = calculate_hit_ratio(top_bundles_results, user_item_interactions, bundle_data)\n","                  intra_diversity_scores = calculate_intra_diversity(top_bundles_results, user_item_interactions, bundle_data)\n","                  inter_diversity_scores = calculate_inter_diversity(top_bundles_results, bundle_data)\n","\n","                  average_hit_ratio[data_dict['user_id']] = hit_ratios\n","                  average_intra_diversity[data_dict['user_id']] = intra_diversity_scores\n","                  average_inter_diversity[data_dict['user_id']] = inter_diversity_scores\n","\n","            except json.JSONDecodeError as e:\n","                print(f\"Error decoding JSON: {e}, skipping line: {line}\")\n","            count += 1\n","            print(f\"{count} /  9881\")\n","    print(f\"File '{filepath_rarank_rec_data}' successfully processed and saved to '{filepath_rarank_rec_data}'\")\n","\n","except FileNotFoundError:\n","    print(f\"Error: File not found at {filepath_rarank_rec_data}\")\n","except Exception as e:\n","    print(f\"An unexpected error occurred: {e}\")\n","\n","print(f\"Count: {count}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_fqAPWp1viKC","executionInfo":{"status":"ok","timestamp":1735800091648,"user_tz":-420,"elapsed":33116,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"2a0dc3e4-465c-469c-f9ac-c5f0fa91fd79"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n","4878 /  9881\n","4879 /  9881\n","4880 /  9881\n","4881 /  9881\n","4882 /  9881\n","4883 /  9881\n","4884 /  9881\n","4885 /  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dictionaries,\n","                      each containing a 'top_n' and a metric value.\n","\n","    Returns:\n","        A pandas DataFrame with the average metrics for each 'top_n'.\n","    \"\"\"\n","\n","    all_metrics = []\n","    for user_id, user_metrics in metrics_dict.items():\n","        all_metrics.extend(user_metrics)\n","\n","    df = pd.DataFrame(all_metrics)\n","\n","    numeric_cols = df.select_dtypes(include=['number']).columns\n","    return df.groupby('top_n')[numeric_cols].mean()\n","\n","# Calculate and print the average hit ratio\n","average_hit_ratio_df = calculate_average_metrics(average_hit_ratio)\n","print(\"Average Hit Ratio:\")\n","print(average_hit_ratio_df)\n","\n","# Calculate and print the average intra-list diversity\n","average_intra_diversity_df = calculate_average_metrics(average_intra_diversity)\n","print(\"\\nAverage Intra-list Diversity:\")\n","print(average_intra_diversity_df)\n","\n","# Calculate and print the average inter-list diversity\n","average_inter_diversity_df = calculate_average_metrics(average_inter_diversity)\n","print(\"\\nAverage Inter-list Diversity:\")\n","average_inter_diversity_df"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":501},"id":"r7-DgF7QKIJB","executionInfo":{"status":"ok","timestamp":1735800092164,"user_tz":-420,"elapsed":519,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"504b7ef9-9510-415b-e855-d15f88ce5c83"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stdout","text":["Average Hit Ratio:\n","       top_n  hit_ratio\n","top_n                  \n","5        5.0   0.799575\n","10      10.0   0.935883\n","15      15.0   0.703434\n","20      20.0   0.564462\n","\n","Average Intra-list Diversity:\n","       top_n  diversity\n","top_n                  \n","5        5.0   0.999972\n","10      10.0   0.999895\n","15      15.0   0.963327\n","20      20.0   0.967618\n","\n","Average Inter-list Diversity:\n"]},{"output_type":"execute_result","data":{"text/plain":["       top_n  inter_diversity\n","top_n                        \n","5        5.0         0.998265\n","10      10.0         0.998226\n","15      15.0         0.990652\n","20      20.0         0.993865"],"text/html":["\n","  <div id=\"df-89f61297-1916-4254-99e2-7f2f00638e11\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>top_n</th>\n","      <th>inter_diversity</th>\n","    </tr>\n","    <tr>\n","      <th>top_n</th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    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average_hit_ratio_df.index:\n","    row = {\n","        'top_n': top_n,\n","        'hit_ratio': average_hit_ratio_df.loc[top_n, 'hit_ratio'],\n","        'intra_diversity': average_intra_diversity_df.loc[top_n, 'diversity'],\n","        'inter_diversity': average_inter_diversity_df.loc[top_n, 'inter_diversity']\n","    }\n","    combined_data.append(row)\n","  return pd.DataFrame(combined_data)\n","\n","# Example usage (assuming the three dataframes are available):\n","combined_df = combine_metrics(average_hit_ratio_df, average_intra_diversity_df, average_inter_diversity_df)\n","combined_df"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":175},"id":"cdolqR3XOM3R","executionInfo":{"status":"ok","timestamp":1735800092164,"user_tz":-420,"elapsed":5,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"660f28e4-cd5f-43ef-c4fd-df5a65388f07"},"execution_count":11,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   top_n  hit_ratio  intra_diversity  inter_diversity\n","0      5   0.799575         0.999972         0.998265\n","1     10   0.935883         0.999895         0.998226\n","2     15   0.703434         0.963327         0.990652\n","3     20   0.564462         0.967618         0.993865"],"text/html":["\n","  <div id=\"df-40e1ea90-4e15-4c84-a951-01551fe72130\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>top_n</th>\n","      <th>hit_ratio</th>\n","      <th>intra_diversity</th>\n","      <th>inter_diversity</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>5</td>\n","      <td>0.799575</td>\n","      <td>0.999972</td>\n","      <td>0.998265</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>10</td>\n","      <td>0.935883</td>\n","      <td>0.999895</td>\n","      <td>0.998226</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>15</td>\n","      <td>0.703434</td>\n","      <td>0.963327</td>\n","      <td>0.990652</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>20</td>\n","      <td>0.564462</td>\n","      <td>0.967618</td>\n","      <td>0.993865</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-40e1ea90-4e15-4c84-a951-01551fe72130')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg 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\"num_unique_values\": 4,\n        \"samples\": [\n          0.9358828892716037,\n          0.564461554047209,\n          0.7995745111944079\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"intra_diversity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.019973134739857682,\n        \"min\": 0.9633269879545011,\n        \"max\": 0.9999718592059794,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          0.9998953573349615,\n          0.9676179795418854,\n          0.9999718592059794\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"inter_diversity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.003696828462537079,\n        \"min\": 0.9906524581486468,\n        \"max\": 0.9982647582384184,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          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average_intra_diversity_df, and average_inter_diversity_df\n","# Make it dense space between bars, and change the color of bar for the best value\n","\n","# prompt: generate bar chart for each average_hit_ratio_df, average_intra_diversity_df, and average_inter_diversity_df\n","# Make it dense space between bars, and change the color of bar for the best value\n","\n","import matplotlib.pyplot as plt\n","\n","def plot_metrics(average_hit_ratio_df, average_intra_diversity_df, average_inter_diversity_df):\n","    \"\"\"Generates bar charts for average hit ratio, intra-diversity, and inter-diversity.\"\"\"\n","\n","    fig, axes = plt.subplots(3, 1, figsize=(8, 10))  # Adjust figsize as needed\n","\n","    # Find the index of the maximum value\n","    best_value_index = average_hit_ratio_df['hit_ratio'].idxmax()\n","    top_n_values = average_hit_ratio_df.index\n","\n","    colors = ['skyblue'] * len(top_n_values)\n","    colors[top_n_values.get_loc(best_value_index)] = 'green' # Highlight the best value\n","\n","    # --- Hit Ratio ---\n","    axes[0].bar(average_hit_ratio_df.index, average_hit_ratio_df['hit_ratio'], width=4.0, color=colors)\n","    axes[0].set_xlabel(\"Top N Recommendations\")\n","    axes[0].set_ylabel(\"Average Hit Ratio\")\n","    axes[0].set_title(\"Average Hit Ratio for Different Top N Values\")\n","    axes[0].set_xticks(average_hit_ratio_df.index)\n","\n","    # Find the index of the maximum value\n","    best_value_index = average_intra_diversity_df['diversity'].idxmax()\n","    top_n_values = average_intra_diversity_df.index\n","\n","    colors = ['skyblue'] * len(top_n_values)\n","    colors[top_n_values.get_loc(best_value_index)] = 'green' # Highlight the best value\n","\n","    # --- Intra-list Diversity ---\n","    axes[1].bar(average_intra_diversity_df.index, average_intra_diversity_df['diversity'], width=4.0, color=colors)\n","    axes[1].set_xlabel(\"Top N Recommendations\")\n","    axes[1].set_ylabel(\"Average Intra-list Diversity\")\n","    axes[1].set_title(\"Average Intra-list Diversity for Different Top N Values\")\n","    axes[1].set_xticks(average_intra_diversity_df.index)\n","\n","    # Find the index of the maximum value\n","    best_value_index = average_inter_diversity_df['inter_diversity'].idxmax()\n","    top_n_values = average_inter_diversity_df.index\n","\n","    colors = ['skyblue'] * len(top_n_values)\n","    colors[top_n_values.get_loc(best_value_index)] = 'green' # Highlight the best value\n","\n","    # --- Inter-list Diversity ---\n","    axes[2].bar(average_inter_diversity_df.index, average_inter_diversity_df['inter_diversity'], width=4.0, color=colors)\n","    axes[2].set_xlabel(\"Top N Recommendations\")\n","    axes[2].set_ylabel(\"Average Inter-list Diversity\")\n","    axes[2].set_title(\"Average Inter-list Diversity for Different Top N Values\")\n","    axes[2].set_xticks(average_inter_diversity_df.index)\n","\n","    plt.tight_layout()  # Adjust layout to prevent overlapping\n","    plt.show()\n","\n","plot_metrics(average_hit_ratio_df, average_intra_diversity_df, average_inter_diversity_df)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"H53yAPjpKxgM","executionInfo":{"status":"ok","timestamp":1735524294242,"user_tz":-420,"elapsed":842,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"62bcc23a-18fc-47bd-e1b5-989ed28bc02e"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 800x1000 with 3 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAxYAAAPdCAYAAAAXkf7QAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAADuK0lEQVR4nOzdd3gU1fv38c8mpAApECEJJST0Ij1A6E00CoIISBGliIgKUiIqKFKVpkBQKYIURZCO8BVpUkQURSmK0ksIAgmdUBNIzvMHT/bHkgSy7IYQeb+uay/ZM+fM3Ds7u+6dU8ZijDECAAAAAAe4ZHYAAAAAALI+EgsAAAAADiOxAAAAAOAwEgsAAAAADiOxAAAAAOAwEgsAAAAADiOxAAAAAOAwEgsAAAAADiOxAAAAAOAwEgsASMXMmTNlsVgUFRWV2aGkS1RUlCwWi2bOnOm0fcbGxqpVq1Z65JFHZLFYFBkZ6bR9O0Nar3nlypWqWLGiPD09ZbFYdP78eUnSrFmzVKpUKbm5uSlXrlz3PV7cfxs2bJDFYtGGDRsyOxTgoUBiAfyHTJw4URaLRWFhYZkdygMnJCRETz/9dKrbkn98LFy48I77mDhxol0/3C0Wi83Dx8dH9erV0/Lly+0J3cacOXPu2w/8Pn36aNWqVerfv79mzZqlJ598MkOPd+u5ypYtm/z8/BQaGqpevXpp165d6drHmTNn1Lp1a2XPnl0TJkzQrFmzlDNnTu3Zs0edOnVS0aJFNXXqVE2ZMiVDX4sjdu3apcGDB981qU1OrNLzyOgEOfkzZLFYtHXr1hTbO3XqJC8vrzvuo3z58ipUqJCMMWnWqVWrlgICAnTjxg2HYwbgfNkyOwAAzjN79myFhIRoy5YtOnDggIoVK5bZIWVZL774otq2bSsPDw9r2cSJE5UnTx516tQp3ft5/PHH1aFDBxljdOTIEU2aNElNmzbVihUrFB4ebndcc+bM0d9//63evXvblAcHB+vq1atyc3Oze59pWbdunZ555hn17dvXafu8m1vP14ULF/Tnn3/qyy+/1MSJEzVq1ChFRERY66b2mn///XddvHhRw4YNU6NGjazlGzZsUFJSksaPH//Afy527dqlIUOGqH79+goJCUmzXt68eTVr1iybsjFjxujff//VuHHjUtS9XwYPHqz//e9/drdr3769+vXrp59++kl169ZNsT0qKkqbN29Wjx49lC0bP1+ABxGfTOA/4vDhw/rll1+0ePFidevWTbNnz9agQYPuawxJSUlKSEiQp6fnfT1uRnB1dZWrq6vD+ylRooReeOEF6/OWLVuqTJkyGj9+/D0lFmmxWCxOP+8nT5506pCha9euyd3dXS4uaXeW336+JGnkyJFq2rSp3nzzTZUqVUqNGzeWlPprPnnypCSliDutckdcvnxZOXPmdNr+7JUzZ84U52ru3Lk6d+5civL7pWLFivruu++0bds2Va5c2a62zz//vPr37685c+akmlh88803Msaoffv2zgoXgJMxFAr4j5g9e7Zy586tJk2aqFWrVpo9e7Z12/Xr1+Xn56fOnTunaBcXFydPT0+bv0rHx8dr0KBBKlasmDw8PBQUFKS3335b8fHxNm0tFot69Oih2bNn69FHH5WHh4dWrlwpSfr4449Vs2ZNPfLII8qePbtCQ0NTHWp09epV9ezZU3ny5JG3t7eaNWumY8eOyWKxaPDgwTZ1jx07ppdeekkBAQHy8PDQo48+qunTpzty2tJ0+xyLkJAQ/fPPP/rxxx+tQz7q169v935Lly6tPHny6ODBgzblS5cuVZMmTZQ/f355eHioaNGiGjZsmBITE6116tevr+XLl+vIkSPWGJL/op3WfIN169apTp06ypkzp3LlyqVnnnlGu3fvTtdrN8ZowoQJ1mMlO3TokJ577jn5+fkpR44cql69eorhXclDY+bOnasBAwaoQIECypEjh+Li4uw+Z4888ojmzp2rbNmy6cMPP7SW3/6a69evr44dO0qSqlatKovFok6dOikkJMSaZOfNmzfFtbVixQrrOfL29laTJk30zz//2MSQPJTn4MGDaty4sby9va0/cJOSkhQZGalHH31Unp6eCggIULdu3XTu3DmbfSQPx9u0aZOqVasmT09PFSlSRF999ZXNuX/uueckSQ0aNLCee0fmCJw8eVJdunRRQECAPD09VaFCBX355Zc2dZLP5ccff6xx48YpODhY2bNnV7169fT333+n+1hvvPGGcufOneKzmx5BQUGqW7euFi5cqOvXr6fYPmfOHBUtWlRhYWE6cuSIXn/9dZUsWVLZs2fXI488oueeey5dQ75CQkJS7XWsX79+is90er8L16xZo9q1aytXrlzy8vJSyZIl9e6779rz8oH/BHosgP+I2bNnq0WLFnJ3d1e7du00adIk/f7776patarc3Nz07LPPavHixfr888/l7u5ubfftt98qPj5ebdu2lXTzR1KzZs20adMmvfLKKypdurR27typcePGad++ffr2229tjrtu3TrNnz9fPXr0UJ48eaw/dMePH69mzZqpffv2SkhI0Ny5c/Xcc8/pu+++U5MmTaztO3XqpPnz5+vFF19U9erV9eOPP9psTxYbG6vq1atbk5m8efNqxYoV6tKli+Li4lIMDUrN9evXdfr06RTlFy5cuGvbyMhIvfHGG/Ly8tJ7770nSQoICLhru9SOde7cORUtWtSmfObMmfLy8lJERIS8vLy0bt06DRw4UHFxcfroo48kSe+9954uXLhgM9TlTuPWf/jhBz311FMqUqSIBg8erKtXr+rTTz9VrVq1tG3btjSH2dStW1ezZs3Siy++aB2alCw2NlY1a9bUlStX1LNnTz3yyCP68ssv1axZMy1cuFDPPvuszb6GDRsmd3d39e3bV/Hx8TbXnj0KFSqkevXqaf369YqLi5OPj0+KOu+9955KliypKVOmaOjQoSpcuLCKFi2q5s2b66uvvtKSJUs0adIkeXl5qXz58pJuTuju2LGjwsPDNWrUKF25ckWTJk1S7dq1tX37dptzdOPGDYWHh6t27dr6+OOPlSNHDklSt27dNHPmTHXu3Fk9e/bU4cOH9dlnn2n79u36+eefbYZqHThwQK1atVKXLl3UsWNHTZ8+XZ06dVJoaKgeffRR1a1bVz179tQnn3yid999V6VLl5Yk63/tdfXqVdWvX18HDhxQjx49VLhwYS1YsECdOnXS+fPn1atXL5v6X331lS5evKju3bvr2rVrGj9+vBo2bKidO3em63r38fFRnz59NHDgwHvqtWjfvr1eeeUVrVq1ymZO1M6dO/X3339r4MCBkm4Oefvll1/Utm1bFSxYUFFRUZo0aZLq16+vXbt2Wd8bR6T3u/Cff/7R008/rfLly2vo0KHy8PDQgQMH9PPPPzscA5DlGABZ3h9//GEkmTVr1hhjjElKSjIFCxY0vXr1stZZtWqVkWT+97//2bRt3LixKVKkiPX5rFmzjIuLi/npp59s6k2ePNlIMj///LO1TJJxcXEx//zzT4qYrly5YvM8ISHBlC1b1jRs2NBatnXrViPJ9O7d26Zup06djCQzaNAga1mXLl1Mvnz5zOnTp23qtm3b1vj6+qY43u2Cg4ONpDs+FixYYK0/Y8YMI8kcPnzYWvboo4+aevXq3fE4t5JkunTpYk6dOmVOnjxp/vjjD/Pkk08aSeajjz6yqZta/N26dTM5cuQw165ds5Y1adLEBAcHp6h7+PBhI8nMmDHDWlaxYkXj7+9vzpw5Yy37888/jYuLi+nQoUO64u/evbtNWe/evY0km+vj4sWLpnDhwiYkJMQkJiYaY4xZv369kWSKFCly1/fmTse7Va9evYwk8+eff6b5mpPft99//92m7aBBg4wkc+rUKZu4c+XKZbp27WpTNyYmxvj6+tqUd+zY0Ugy/fr1s6n7008/GUlm9uzZNuUrV65MUZ58DW7cuNFadvLkSePh4WHefPNNa9mCBQuMJLN+/fo0z0Vabr8+IiMjjSTz9ddfW8sSEhJMjRo1jJeXl4mLizPG/N+5zJ49u/n333+tdX/77TcjyfTp0+eOx01+vxcsWGDOnz9vcufObZo1a2bd3rFjR5MzZ867xn/27Fnj4eFh2rVrZ1Per18/I8ns3bvXGJP652Xz5s1Gkvnqq69SxHXruQwODjYdO3ZM0b5evXo2n+/0fheOGzcuxbUFPKwYCgX8B8yePVsBAQFq0KCBpJtDlNq0aaO5c+dah9I0bNhQefLk0bx586ztzp07pzVr1qhNmzbWsgULFqh06dIqVaqUTp8+bX00bNhQkrR+/XqbY9erV09lypRJEVP27NltjnPhwgXVqVNH27Zts5YnD5t6/fXXbdq+8cYbNs+NMVq0aJGaNm0qY4xNXOHh4bpw4YLNftMSFhamNWvWpHh8/PHHd217r6ZNm6a8efPK399fVapU0dq1a/X222/bTEKWbM/XxYsXdfr0adWpU0dXrlzRnj177D7uiRMntGPHDnXq1El+fn7W8vLly+vxxx/X999/f0+v5/vvv1e1atVUu3Zta5mXl5deeeUVRUVFpVi9qWPHjjavzRHJvTMXL150yv7WrFmj8+fPq127djbXlKurq8LCwlJc65L02muv2TxfsGCBfH199fjjj9vsIzQ0VF5eXin2UaZMGdWpU8f6PG/evCpZsqQOHTrklNd0u++//16BgYFq166dtczNzU09e/bUpUuX9OOPP9rUb968uQoUKGB9Xq1aNYWFhdl1vfj6+qp3795atmyZtm/fble8uXPnVuPGjbVs2TJdvnxZ0s3P/9y5c1WlShWVKFFCku3n5fr16zpz5oyKFSumXLlypeu7ID3S+12YPG9n6dKlSkpKcsqxgayKoVBAFpeYmKi5c+eqQYMGOnz4sLU8LCxMY8aM0dq1a/XEE08oW7ZsatmypebMmaP4+Hh5eHho8eLFun79uk1isX//fu3evTvNVWSSJ8EmK1y4cKr1vvvuO33wwQfasWOHzXjkW8fqHzlyRC4uLin2cfuqPadOndL58+c1ZcqUNJcJvT2u1OTJk8dmpaBkGbnCzDPPPKMePXooISFBv//+u4YPH64rV66kmMD8zz//aMCAAVq3bl2KeQjpGap1uyNHjkiSSpYsmWJb6dKltWrVqnuafHzkyJFUlzNOHqpz5MgRlS1b1lqe1vVxLy5duiRJ8vb2dsr+9u/fL0nWH4q3u324VbZs2VSwYMEU+7hw4YL8/f1T3cft12WhQoVS1MmdO3eK+RjOcuTIERUvXjzF9Xbr+3Wr4sWLp9hHiRIlNH/+fLuO26tXL40bN06DBw/W0qVL7Wrbvn17LVmyREuXLtXzzz+vX375RVFRUTbDtq5evaoRI0ZoxowZOnbsmM0StffyeUlNer8L27Rpoy+++EIvv/yy+vXrp8cee0wtWrRQq1at7rhQAfBfRGIBZHHr1q3TiRMnNHfuXM2dOzfF9tmzZ+uJJ56QJLVt21aff/65VqxYoebNm2v+/PkqVaqUKlSoYK2flJSkcuXKaezYsakeLygoyOZ5an+N/umnn9SsWTPVrVtXEydOVL58+eTm5qYZM2Zozpw5dr/G5L8CvvDCC9bJubdLHjP/oClYsKA1mWncuLHy5MmjHj16qEGDBmrRooUk6fz586pXr558fHw0dOhQFS1aVJ6entq2bZveeeedLP1XUGf1VkjS33//LVdXV6clK8nnddasWQoMDEyx/faE08PDI8UPxaSkJPn7+9sslnCr23+UprXSmLnDvRuyouRei8GDB9vda/H000/L19dXc+bM0fPPP685c+bI1dXVOg9MutmrOWPGDPXu3Vs1atSQr6+vLBaL2rZte9fPy61/3LhVYmKizfuT3u/C7Nmza+PGjVq/fr2WL1+ulStXat68eWrYsKFWr17tlNXlgKyCxALI4mbPni1/f39NmDAhxbbFixdryZIlmjx5srJnz666desqX758mjdvnmrXrq1169ZZJyInK1q0qP7880899thjaf4P+G4WLVokT09PrVq1yuY+EDNmzLCpFxwcrKSkJB0+fNjmL6UHDhywqZc3b155e3srMTEx1R6H++Vez8etunXrpnHjxmnAgAF69tlnrSv+nDlzRosXL7ZZZvPWHih7YwgODpYk7d27N8W2PXv2KE+ePPe0VGpwcHCa+7z1uM4WHR2tH3/8UTVq1HBaj0XyBHp/f/97vq6KFi2qH374QbVq1XJaEuWM6yxZcHCw/vrrLyUlJdkkRWm9X8m9OLfat2/fHe+nkZbevXsrMjJSQ4YMsWuZXw8PD7Vq1UpfffWVYmNjtWDBAjVs2NAm+Vu4cKE6duyoMWPGWMuuXbtmvcv6neTOnTvVekeOHFGRIkWsz+35LnRxcdFjjz2mxx57TGPHjtXw4cP13nvvaf369Zn6nQXcb/TRAVnY1atXtXjxYj399NNq1apVikePHj108eJFLVu2TNLN//m1atVK//vf/zRr1izduHHDZhiUJLVu3VrHjh3T1KlTUz1e8rjnO3F1dZXFYrFZKjUqKirFilLJ93GYOHGiTfmnn36aYn8tW7bUokWLUl368tSpU3eNyRly5syZrh8ud5ItWza9+eab2r17t3WISPJfNG/9q3VCQkKK85IcQ3qGeuTLl08VK1bUl19+aRPz33//rdWrV1vvBWGvxo0ba8uWLdq8ebO17PLly5oyZYpCQkJSnW/jqLNnz6pdu3ZKTExMkQg7Ijw8XD4+Pho+fHiqy5um57pq3bq1EhMTNWzYsBTbbty4cU/XS3LC5+i1Jt18v2JiYmzmVt24cUOffvqpvLy8VK9ePZv63377rY4dO2Z9vmXLFv3222966qmn7D52cq/F0qVLtWPHDrvatm/fXtevX1e3bt106tSpFPeucHV1TdHL8+mnn9p856SlaNGi+vXXX5WQkGAt++6773T06FGbeun9Ljx79myK7RUrVpSkFMvSAv919FgAWdiyZct08eJFNWvWLNXt1atXV968eTV79mxrAtGmTRt9+umnGjRokMqVK5diGcsXX3xR8+fP16uvvqr169erVq1aSkxM1J49ezR//nytWrVKVapUuWNcTZo00dixY/Xkk0/q+eef18mTJzVhwgQVK1ZMf/31l7VeaGioWrZsqcjISJ05c8a63Oy+ffsk2f7lduTIkVq/fr3CwsLUtWtXlSlTRmfPntW2bdv0ww8/pPo/d2cLDQ3VpEmT9MEHH6hYsWLy9/dPc3z+nXTq1EkDBw7UqFGj1Lx5c9WsWVO5c+dWx44d1bNnT1ksFs2aNSvV4TGhoaGaN2+eIiIiVLVqVXl5ealp06apHuejjz7SU089pRo1aqhLly7W5WZ9fX3v6T4DktSvXz998803euqpp9SzZ0/5+fnpyy+/1OHDh7Vo0SKHx5Tv27dPX3/9tYwxiouL059//qkFCxbo0qVL1mvKWXx8fDRp0iS9+OKLqly5stq2bau8efMqOjpay5cvV61atfTZZ5/dcR/16tVTt27dNGLECO3YsUNPPPGE3NzctH//fi1YsEDjx49Xq1at7IqrYsWKcnV11ahRo3ThwgV5eHioYcOGac7juJNXXnlFn3/+uTp16qStW7cqJCRECxcu1M8//6zIyMgUvT/FihVT7dq19dprryk+Pl6RkZF65JFH9Pbbb9t9bOn/5lr8+eefdvWQ1atXTwULFtTSpUuVPXt267DBZE8//bRmzZolX19flSlTRps3b9YPP/ygRx555K77fvnll7Vw4UI9+eSTat26tQ4ePKivv/46xRLQ6f0uHDp0qDZu3KgmTZooODhYJ0+e1MSJE1WwYEGbRQ6Ah0KmrUcFwGFNmzY1np6e5vLly2nW6dSpk3Fzc7Mu05qUlGSCgoKMJPPBBx+k2iYhIcGMGjXKPProo8bDw8Pkzp3bhIaGmiFDhpgLFy5Y6+kOy4NOmzbNFC9e3Hh4eJhSpUqZGTNmWJf8vNXly5dN9+7djZ+fn/Hy8jLNmzc3e/fuNZLMyJEjberGxsaa7t27m6CgIOPm5mYCAwPNY489ZqZMmXLXcxUcHGyaNGmS6rZbl8pMltpyszExMaZJkybG29vbSLrr0rN3Oj+DBw+2WQbz559/NtWrVzfZs2c3+fPnN2+//bZ1ieBbl8q8dOmSef75502uXLmMJOvSoqktvWqMMT/88IOpVauWyZ49u/Hx8TFNmzY1u3btumPcd4v/4MGDplWrViZXrlzG09PTVKtWzXz33Xc2dVI7p+k5XvLDxcXF5MqVy1SqVMn06tUr1SWNHV1u9tZYw8PDja+vr/H09DRFixY1nTp1Mn/88Ye1zt2WS50yZYoJDQ012bNnN97e3qZcuXLm7bffNsePH7fWSesavH2ZU2OMmTp1qilSpIhxdXW1a+nZ1JYjjo2NNZ07dzZ58uQx7u7uply5cimuk+Rz+dFHH5kxY8aYoKAg4+HhYerUqWNd3vdO7vR+J5/79Cw3e6u33nrLSDKtW7dOse3cuXPW1+Tl5WXCw8PNnj17Uiwlm9pys8YYM2bMGFOgQAHj4eFhatWqZf74449U34f0fBeuXbvWPPPMMyZ//vzG3d3d5M+f37Rr187s27fPrtcL/BdYjPmPzRgDkOXt2LFDlSpV0tdff51iCAQA54uKilLhwoX10UcfqW/fvpkdDoAsijkWADLV1atXU5RFRkbKxcXFZiIzAAB4sDHHAkCmGj16tLZu3aoGDRooW7ZsWrFihVasWKFXXnklxdK2AADgwUViASBT1axZU2vWrNGwYcN06dIlFSpUSIMHD3bq6j8AACDjMccCAAAAgMMydY7Fxo0b1bRpU+XPn18WiyXFGvep2bBhgypXriwPDw8VK1ZMM2fOzPA4AQAAANxZpg6Funz5sipUqKCXXnopxRrVqTl8+LCaNGmiV199VbNnz9batWv18ssvK1++fNYbbd1NUlKSjh8/Lm9vb6fe3RQAAAD4rzHG6OLFi8qfP/9d71X0wAyFslgsWrJkiZo3b55mnXfeeUfLly+3ufNu27Ztdf78ea1cuTLVNvHx8TZ3vjx27FiG3BkWAAAA+K86evSoChYseMc6WWry9ubNm9WoUSObsvDwcPXu3TvNNiNGjNCQIUNSlB89elQ+Pj7ODhEAAAD4z4iLi1NQUJC8vb3vWjdLJRYxMTEKCAiwKQsICFBcXJyuXr2q7Nmzp2jTv39/RUREWJ8nnxwfHx8SCwAAACAd0jOFIEslFvfCw8NDHh4emR0GAAAA8J+Wpe68HRgYqNjYWJuy2NhY+fj4pNpbAQAAAOD+yFKJRY0aNbR27VqbsjVr1qhGjRqZFBEAAAAAKZMTi0uXLmnHjh3asWOHpJvLye7YsUPR0dGSbs6P6NChg7X+q6++qkOHDuntt9/Wnj17NHHiRM2fP199+vTJjPABAAAA/H+Zmlj88ccfqlSpkipVqiRJioiIUKVKlTRw4EBJ0okTJ6xJhiQVLlxYy5cv15o1a1ShQgWNGTNGX3zxRbrvYQEAAAAgYzww97G4X+Li4uTr66sLFy6wKhQAAABwB/b8ds5ScywAAAAAPJhILAAAAAA4jMQCAAAAgMP+8zfIA+A4y5C7320TDzcz6KGargcASAU9FgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGGZnlhMmDBBISEh8vT0VFhYmLZs2XLH+pGRkSpZsqSyZ8+uoKAg9enTR9euXbtP0QIAAABITaYmFvPmzVNERIQGDRqkbdu2qUKFCgoPD9fJkydTrT9nzhz169dPgwYN0u7duzVt2jTNmzdP77777n2OHAAAAMCtMjWxGDt2rLp27arOnTurTJkymjx5snLkyKHp06enWv+XX35RrVq19PzzzyskJERPPPGE2rVrd8dejvj4eMXFxdk8AAAAADhXtsw6cEJCgrZu3ar+/ftby1xcXNSoUSNt3rw51TY1a9bU119/rS1btqhatWo6dOiQvv/+e7344otpHmfEiBEaMmSI0+N31MjtpzM7BGQB/SrlyewQAAAA0iXTEovTp08rMTFRAQEBNuUBAQHas2dPqm2ef/55nT59WrVr15YxRjdu3NCrr756x6FQ/fv3V0REhPV5XFycgoKCnPMiAAAAAEh6ACZv22PDhg0aPny4Jk6cqG3btmnx4sVavny5hg0blmYbDw8P+fj42DwAAAAAOFem9VjkyZNHrq6uio2NtSmPjY1VYGBgqm3ef/99vfjii3r55ZclSeXKldPly5f1yiuv6L333pOLS5bKkwAAAID/jEz7Je7u7q7Q0FCtXbvWWpaUlKS1a9eqRo0aqba5cuVKiuTB1dVVkmSMybhgAQAAANxRpvVYSFJERIQ6duyoKlWqqFq1aoqMjNTly5fVuXNnSVKHDh1UoEABjRgxQpLUtGlTjR07VpUqVVJYWJgOHDig999/X02bNrUmGAAAAADuv0xNLNq0aaNTp05p4MCBiomJUcWKFbVy5UrrhO7o6GibHooBAwbIYrFowIABOnbsmPLmzaumTZvqww8/zKyXAAAAAECSxTxkY4ji4uLk6+urCxcuZOpEbpabRXo8KMvNWoZYMjsEPODMoIfqfyUA8NCw57czs50BAAAAOIzEAgAAAIDDSCwAAAAAOIzEAgAAAIDDSCwAAAAAOIzEAgAAAIDDSCwAAAAAOIzEAgAAAIDD7unO2wcPHlRkZKR2794tSSpTpox69eqlokWLOjU4AAAAAFmD3T0Wq1atUpkyZbRlyxaVL19e5cuX12+//aZHH31Ua9asyYgYAQAAADzg7O6x6Nevn/r06aORI0emKH/nnXf0+OOPOy04AAAAAFmD3T0Wu3fvVpcuXVKUv/TSS9q1a5dTggIAAACQtdidWOTNm1c7duxIUb5jxw75+/s7IyYAAAAAWYzdQ6G6du2qV155RYcOHVLNmjUlST///LNGjRqliIgIpwcIAIA9Rm4/ndkh4AHXr1KezA4B+E+yO7F4//335e3trTFjxqh///6SpPz582vw4MHq2bOn0wMEAAAA8OCzO7GwWCzq06eP+vTpo4sXL0qSvL29nR4YAAAAgKzjnu5jkYyEAgAAAICUzsSicuXKWrt2rXLnzq1KlSrJYrGkWXfbtm1OCw4AAABA1pCuxOKZZ56Rh4eH9d93SiwAAAAAPHzSlVgMGjTI+u/BgwdnVCwAAAAAsii772NRpEgRnTlzJkX5+fPnVaRIEacEBQAAACBrsTuxiIqKUmJiYory+Ph4/fvvv04JCgAAAEDWku5VoZYtW2b996pVq+Tr62t9npiYqLVr16pw4cLOjQ4AAABAlpDuxKJ58+aSbt7HomPHjjbb3NzcFBISojFjxjg1OAAAAABZQ7oTi6SkJElS4cKF9fvvvytPnjwZFhQAAACArMXuG+QdPnw4I+IAAAAAkIXd0523L1++rB9//FHR0dFKSEiw2dazZ0+nBAYAAAAg67A7sdi+fbsaN26sK1eu6PLly/Lz89Pp06eVI0cO+fv7k1gAAAAADyG7l5vt06ePmjZtqnPnzil79uz69ddfdeTIEYWGhurjjz/OiBgBAAAAPODsTix27NihN998Uy4uLnJ1dVV8fLyCgoI0evRovfvuuxkRIwAAAIAHnN2JhZubm1xcbjbz9/dXdHS0JMnX11dHjx51bnQAAAAAsgS751hUqlRJv//+u4oXL6569epp4MCBOn36tGbNmqWyZctmRIwAAAAAHnB291gMHz5c+fLlkyR9+OGHyp07t1577TWdOnVKn3/+udMDBAAAAPDgs7vHokqVKtZ/+/v7a+XKlU4NCAAAAEDWY3ePRVq2bdump59+2lm7AwAAAJCF2JVYrFq1Sn379tW7776rQ4cOSZL27Nmj5s2bq2rVqkpKSsqQIAEAAAA82NI9FGratGnq2rWr/Pz8dO7cOX3xxRcaO3as3njjDbVp00Z///23SpcunZGxAgAAAHhApbvHYvz48Ro1apROnz6t+fPn6/Tp05o4caJ27typyZMnk1QAAAAAD7F0JxYHDx7Uc889J0lq0aKFsmXLpo8++kgFCxZ0KIAJEyYoJCREnp6eCgsL05YtW+5Y//z58+revbvy5csnDw8PlShRQt9//71DMQAAAABwTLqHQl29elU5cuSQJFksFnl4eFiXnb1X8+bNU0REhCZPnqywsDBFRkYqPDxce/fulb+/f4r6CQkJevzxx+Xv76+FCxeqQIECOnLkiHLlyuVQHAAAAAAcY9dys1988YW8vLwkSTdu3NDMmTOVJ08emzo9e/ZM9/7Gjh2rrl27qnPnzpKkyZMna/ny5Zo+fbr69euXov706dN19uxZ/fLLL3Jzc5MkhYSE2PMSAAAAAGSAdCcWhQoV0tSpU63PAwMDNWvWLJs6Fosl3YlFQkKCtm7dqv79+1vLXFxc1KhRI23evDnVNsuWLVONGjXUvXt3LV26VHnz5tXzzz+vd955R66urqm2iY+PV3x8vPV5XFxcuuIDAAAAkH7pTiyioqKceuDTp08rMTFRAQEBNuUBAQHas2dPqm0OHTqkdevWqX379vr+++914MABvf7667p+/boGDRqUapsRI0ZoyJAhTo0dAAAAgC2n3SDvfkhKSpK/v7+mTJmi0NBQtWnTRu+9954mT56cZpv+/fvrwoUL1sfRo0fvY8QAAADAw8GuORbOlCdPHrm6uio2NtamPDY2VoGBgam2yZcvn9zc3GyGPZUuXVoxMTFKSEiQu7t7ijYeHh7y8PBwbvAAAAAAbGRaj4W7u7tCQ0O1du1aa1lSUpLWrl2rGjVqpNqmVq1aOnDggM0dvvft26d8+fKlmlQAAAAAuD8ydShURESEpk6dqi+//FK7d+/Wa6+9psuXL1tXierQoYPN5O7XXntNZ8+eVa9evbRv3z4tX75cw4cPV/fu3TPrJQAAAABQJg6FkqQ2bdro1KlTGjhwoGJiYlSxYkWtXLnSOqE7OjpaLi7/l/sEBQVp1apV6tOnj8qXL68CBQqoV69eeueddzLrJQAAAADQPSQWrq6uOnHiRIob2J05c0b+/v5KTEy0a389evRQjx49Ut22YcOGFGU1atTQr7/+atcxAAAAHkQjt5/O7BDwgOtXKc/dKz0g7B4KZYxJtTw+Pp55DgAAAMBDKt09Fp988omkmzfBu/UO3JKUmJiojRs3qlSpUs6PEAAAAMADL92Jxbhx4yTd7LGYPHmyzZKv7u7uCgkJueP9JAAAAAD8d6U7sTh8+LAkqUGDBlq8eLFy586dYUEBAAAAyFrsnry9fv36jIgDAAAAQBaWrsQiIiJCw4YNU86cORUREXHHumPHjnVKYAAAAACyjnQlFtu3b9f169et/06LxWJxTlQAAAAAspR0JRa3Dn9iKBQAAACA29l9HwsAAAAAuF26J2+3aNEiXfUWL158z8EAAAAAyJrSnVj4+vraPJ8zZ46aNm0qb29vpwcFAAAAIGtJd2IxY8YMm+cLFy7U6NGjVaRIEacHBQAAACBrYY4FAAAAAIeRWAAAAABwGIkFAAAAAIele47FsmXLbJ4nJSVp7dq1+vvvv23KmzVr5pzIAAAAAGQZ6U4smjdvnqKsW7duNs8tFosSExMdDgoAAABA1pLuxCIpKSkj4wAAAACQhTHHAgAAAIDDSCwAAAAAOIzEAgAAAIDDSCwAAAAAOIzEAgAAAIDD7imxOH/+vL744gv1799fZ8+elSRt27ZNx44dc2pwAAAAALKGdC83m+yvv/5So0aN5Ovrq6ioKHXt2lV+fn5avHixoqOj9dVXX2VEnAAAAAAeYHb3WERERKhTp07av3+/PD09reWNGzfWxo0bnRocAAAAgKzB7sTi999/T3HHbUkqUKCAYmJinBIUAAAAgKzF7sTCw8NDcXFxKcr37dunvHnzOiUoAAAAAFmL3YlFs2bNNHToUF2/fl2SZLFYFB0drXfeeUctW7Z0eoAAAAAAHnx2JxZjxozRpUuX5O/vr6tXr6pevXoqVqyYvL299eGHH2ZEjAAAAAAecHavCuXr66s1a9Zo06ZN+uuvv3Tp0iVVrlxZjRo1yoj4AAAAAGQBdicWyWrXrq3atWs7MxYAAAAAWZTdicUnn3ySarnFYpGnp6eKFSumunXrytXV1eHgAAAAAGQNdicW48aN06lTp3TlyhXlzp1bknTu3DnlyJFDXl5eOnnypIoUKaL169crKCjI6QEDAAAAePDYPXl7+PDhqlq1qvbv368zZ87ozJkz2rdvn8LCwjR+/HhFR0crMDBQffr0yYh4AQAAADyA7O6xGDBggBYtWqSiRYtay4oVK6aPP/5YLVu21KFDhzR69GiWngUAAAAeInb3WJw4cUI3btxIUX7jxg3rnbfz58+vixcvOh4dAAAAgCzB7sSiQYMG6tatm7Zv324t2759u1577TU1bNhQkrRz504VLlzYeVECAAAAeKDZnVhMmzZNfn5+Cg0NlYeHhzw8PFSlShX5+flp2rRpkiQvLy+NGTPG6cECAAAAeDDZnVgEBgZqzZo12rVrlxYsWKAFCxZo165dWr16tQICAiTd7NV44okn0r3PCRMmKCQkRJ6engoLC9OWLVvS1W7u3LmyWCxq3ry5vS8DAAAAgBPd8w3ySpUqpVKlSjkcwLx58xQREaHJkycrLCxMkZGRCg8P1969e+Xv759mu6ioKPXt21d16tRxOAYAAAAAjrmnxOLff//VsmXLFB0drYSEBJttY8eOtWtfY8eOVdeuXdW5c2dJ0uTJk7V8+XJNnz5d/fr1S7VNYmKi2rdvryFDhuinn37S+fPn09x/fHy84uPjrc/j4uLsig8AAADA3dmdWKxdu1bNmjVTkSJFtGfPHpUtW1ZRUVEyxqhy5cp27SshIUFbt25V//79rWUuLi5q1KiRNm/enGa7oUOHyt/fX126dNFPP/10x2OMGDFCQ4YMsSsuAAAAAPaxe45F//791bdvX+3cuVOenp5atGiRjh49qnr16um5556za1+nT59WYmKidW5GsoCAAOvStbfbtGmTpk2bpqlTp6Y73gsXLlgfR48etStGAAAAAHdnd2Kxe/dudejQQZKULVs2Xb16VV5eXho6dKhGjRrl9ABvdfHiRb344ouaOnWq8uTJk642Hh4e8vHxsXkAAAAAcC67h0LlzJnTOq8iX758OnjwoB599FFJN3sg7JEnTx65uroqNjbWpjw2NlaBgYEp6h88eFBRUVFq2rSptSwpKUnSzSRn7969NncEBwAAAHB/2J1YVK9eXZs2bVLp0qXVuHFjvfnmm9q5c6cWL16s6tWr27Uvd3d3hYaGau3atdYlY5OSkrR27Vr16NEjRf1SpUpp586dNmUDBgzQxYsXNX78eAUFBdn7cgAAAAA4gd2JxdixY3Xp0iVJ0pAhQ3Tp0iXNmzdPxYsXt3tFKEmKiIhQx44dVaVKFVWrVk2RkZG6fPmydZWoDh06qECBAhoxYoQ8PT1VtmxZm/a5cuWSpBTlAAAAAO4fuxKLxMRE/fvvvypfvrykm8OiJk+e7FAAbdq00alTpzRw4EDFxMSoYsWKWrlypXVCd3R0tFxc7J4KAgAAAOA+siuxcHV11RNPPKHdu3dbewqcoUePHqkOfZKkDRs23LHtzJkznRYHAAAAgHtjd1dA2bJldejQoYyIBQAAAEAWZXdi8cEHH6hv37767rvvdOLECcXFxdk8AAAAADx87J683bhxY0lSs2bNZLFYrOXGGFksFiUmJjovOgAAAABZgt2Jxfr16zMiDgAAAABZmN2JRb169TIiDgAAAABZ2D2t4/rTTz/phRdeUM2aNXXs2DFJ0qxZs7Rp0yanBgcAAAAga7A7sVi0aJHCw8OVPXt2bdu2TfHx8ZKkCxcuaPjw4U4PEAAAAMCD755WhZo8ebKmTp0qNzc3a3mtWrW0bds2pwYHAAAAIGuwO7HYu3ev6tatm6Lc19dX58+fd0ZMAAAAALIYuxOLwMBAHThwIEX5pk2bVKRIEacEBQAAACBrsTux6Nq1q3r16qXffvtNFotFx48f1+zZs9W3b1+99tprGREjAAAAgAec3cvN9uvXT0lJSXrsscd05coV1a1bVx4eHurbt6/eeOONjIgRAAAAwAPO7sTCYrHovffe01tvvaUDBw7o0qVLKlOmjLy8vDIiPgAAAABZgN1Dob7++mtduXJF7u7uKlOmjKpVq0ZSAQAAADzk7E4s+vTpI39/fz3//PP6/vvvlZiYmBFxAQAAAMhC7E4sTpw4oblz58pisah169bKly+funfvrl9++SUj4gMAAACQBdidWGTLlk1PP/20Zs+erZMnT2rcuHGKiopSgwYNVLRo0YyIEQAAAMADzu7J27fKkSOHwsPDde7cOR05ckS7d+92VlwAAAAAshC7eywk6cqVK5o9e7YaN26sAgUKKDIyUs8++6z++ecfZ8cHAAAAIAuwu8eibdu2+u6775QjRw61bt1a77//vmrUqJERsQEAAADIIuxOLFxdXTV//nyFh4fL1dXVZtvff/+tsmXLOi04AAAAAFmD3YnF7NmzbZ5fvHhR33zzjb744gtt3bqV5WcBAACAh9A9zbGQpI0bN6pjx47Kly+fPv74YzVs2FC//vqrM2MDAAAAkEXY1WMRExOjmTNnatq0aYqLi1Pr1q0VHx+vb7/9VmXKlMmoGAEAAAA84NLdY9G0aVOVLFlSf/31lyIjI3X8+HF9+umnGRkbAAAAgCwi3T0WK1asUM+ePfXaa6+pePHiGRkTAAAAgCwm3T0WmzZt0sWLFxUaGqqwsDB99tlnOn36dEbGBgAAACCLSHdiUb16dU2dOlUnTpxQt27dNHfuXOXPn19JSUlas2aNLl68mJFxAgAAAHiA2b0qVM6cOfXSSy9p06ZN2rlzp958802NHDlS/v7+atasWUbECAAAAOABd8/LzUpSyZIlNXr0aP3777/65ptvnBUTAAAAgCzGocQimaurq5o3b65ly5Y5Y3cAAAAAshinJBYAAAAAHm4kFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEkFgAAAAAcRmIBAAAAwGEPRGIxYcIEhYSEyNPTU2FhYdqyZUuadadOnao6deood+7cyp07txo1anTH+gAAAAAyXqYnFvPmzVNERIQGDRqkbdu2qUKFCgoPD9fJkydTrb9hwwa1a9dO69ev1+bNmxUUFKQnnnhCx44du8+RAwAAAEiW6YnF2LFj1bVrV3Xu3FllypTR5MmTlSNHDk2fPj3V+rNnz9brr7+uihUrqlSpUvriiy+UlJSktWvX3ufIAQAAACTL1MQiISFBW7duVaNGjaxlLi4uatSokTZv3pyufVy5ckXXr1+Xn59fqtvj4+MVFxdn8wAAAADgXJmaWJw+fVqJiYkKCAiwKQ8ICFBMTEy69vHOO+8of/78NsnJrUaMGCFfX1/rIygoyOG4AQAAANjK9KFQjhg5cqTmzp2rJUuWyNPTM9U6/fv314ULF6yPo0eP3ucoAQAAgP++bJl58Dx58sjV1VWxsbE25bGxsQoMDLxj248//lgjR47UDz/8oPLly6dZz8PDQx4eHk6JFwAAAEDqMrXHwt3dXaGhoTYTr5MnYteoUSPNdqNHj9awYcO0cuVKValS5X6ECgAAAOAOMrXHQpIiIiLUsWNHValSRdWqVVNkZKQuX76szp07S5I6dOigAgUKaMSIEZKkUaNGaeDAgZozZ45CQkKsczG8vLzk5eWVaa8DAAAAeJhlemLRpk0bnTp1SgMHDlRMTIwqVqyolStXWid0R0dHy8Xl/zpWJk2apISEBLVq1cpmP4MGDdLgwYPvZ+gAAAAA/r9MTywkqUePHurRo0eq2zZs2GDzPCoqKuMDAgAAAGCXLL0qFAAAAIAHA4kFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABwGIkFAAAAAIeRWAAAAABw2AORWEyYMEEhISHy9PRUWFiYtmzZcsf6CxYsUKlSpeTp6aly5crp+++/v0+RAgAAAEhNpicW8+bNU0REhAYNGqRt27apQoUKCg8P18mTJ1Ot/8svv6hdu3bq0qWLtm/frubNm6t58+b6+++/73PkAAAAAJJZjDEmMwMICwtT1apV9dlnn0mSkpKSFBQUpDfeeEP9+vVLUb9Nmza6fPmyvvvuO2tZ9erVVbFiRU2ePDlF/fj4eMXHx1ufX7hwQYUKFdLRo0fl4+OTAa8ofcb+eSbTjo2sI6LCI5kdgiTJd4RvZoeAB9yF/hcyOwQrvl9xNw/Kd6vE9Yq7y+zrNS4uTkFBQTp//rx8fe/ye8Bkovj4eOPq6mqWLFliU96hQwfTrFmzVNsEBQWZcePG2ZQNHDjQlC9fPtX6gwYNMpJ48ODBgwcPHjx48OBxj4+jR4/e9bd9NmWi06dPKzExUQEBATblAQEB2rNnT6ptYmJiUq0fExOTav3+/fsrIiLC+jwpKUlnz57VI488IovF4uArgLMkZ8OZ3ZMEpAfXK7ISrldkJVyvDx5jjC5evKj8+fPftW6mJhb3g4eHhzw8PGzKcuXKlTnB4K58fHz4IkGWwfWKrITrFVkJ1+uD5a5DoP6/TJ28nSdPHrm6uio2NtamPDY2VoGBgam2CQwMtKs+AAAAgIyXqYmFu7u7QkNDtXbtWmtZUlKS1q5dqxo1aqTapkaNGjb1JWnNmjVp1gcAAACQ8TJ9KFRERIQ6duyoKlWqqFq1aoqMjNTly5fVuXNnSVKHDh1UoEABjRgxQpLUq1cv1atXT2PGjFGTJk00d+5c/fHHH5oyZUpmvgw4yMPDQ4MGDUoxbA14EHG9IivhekVWwvWatWX6crOS9Nlnn+mjjz5STEyMKlasqE8++URhYWGSpPr16yskJEQzZ8601l+wYIEGDBigqKgoFS9eXKNHj1bjxo0zKXoAAAAAD0RiAQAAACBry/Q7bwMAAADI+kgsAAAAADiMxAIAAACAw0gsAAAAADiMxAKZZvDgwbJYLDaPUqVKZXZYgCRp48aNatq0qfLnzy+LxaJvv/3WZrsxRgMHDlS+fPmUPXt2NWrUSPv378+cYPHQu9v12qlTpxTft08++WTmBIuH3ogRI1S1alV5e3vL399fzZs31969e23qXLt2Td27d9cjjzwiLy8vtWzZMsUNkvHgIbFApnr00Ud14sQJ62PTpk2ZHRIgSbp8+bIqVKigCRMmpLp99OjR+uSTTzR58mT99ttvypkzp8LDw3Xt2rX7HClw9+tVkp588kmb79tvvvnmPkYI/J8ff/xR3bt316+//qo1a9bo+vXreuKJJ3T58mVrnT59+uh///ufFixYoB9//FHHjx9XixYtMjFqpEem3yAPD7ds2bIpMDAws8MAUnjqqaf01FNPpbrNGKPIyEgNGDBAzzzzjCTpq6++UkBAgL799lu1bdv2foYK3PF6Tebh4cH3LR4IK1eutHk+c+ZM+fv7a+vWrapbt64uXLigadOmac6cOWrYsKEkacaMGSpdurR+/fVXVa9ePTPCRjrQY4FMtX//fuXPn19FihRR+/btFR0dndkhAXd1+PBhxcTEqFGjRtYyX19fhYWFafPmzZkYGZC2DRs2yN/fXyVLltRrr72mM2fOZHZIgCTpwoULkiQ/Pz9J0tatW3X9+nWb79hSpUqpUKFCfMc+4EgskGnCwsI0c+ZMrVy5UpMmTdLhw4dVp04dXbx4MbNDA+4oJiZGkhQQEGBTHhAQYN0GPEiefPJJffXVV1q7dq1GjRqlH3/8UU899ZQSExMzOzQ85JKSktS7d2/VqlVLZcuWlXTzO9bd3V25cuWyqct37IOPoVDINLd225cvX15hYWEKDg7W/Pnz1aVLl0yMDAD+W24dnleuXDmVL19eRYsW1YYNG/TYY49lYmR42HXv3l1///03cyz/I+ixwAMjV65cKlGihA4cOJDZoQB3lDxO/fYVSmJjYxnDjiyhSJEiypMnD9+3yFQ9evTQd999p/Xr16tgwYLW8sDAQCUkJOj8+fM29fmOffCRWOCBcenSJR08eFD58uXL7FCAOypcuLACAwO1du1aa1lcXJx+++031ahRIxMjA9Ln33//1ZkzZ/i+RaYwxqhHjx5asmSJ1q1bp8KFC9tsDw0NlZubm8137N69exUdHc137AOOoVDINH379lXTpk0VHBys48ePa9CgQXJ1dVW7du0yOzRAly5dsvlr7uHDh7Vjxw75+fmpUKFC6t27tz744AMVL15chQsX1vvvv6/8+fOrefPmmRc0Hlp3ul79/Pw0ZMgQtWzZUoGBgTp48KDefvttFStWTOHh4ZkYNR5W3bt315w5c7R06VJ5e3tb5034+voqe/bs8vX1VZcuXRQRESE/Pz/5+PjojTfeUI0aNVgR6kFngEzSpk0bky9fPuPu7m4KFChg2rRpYw4cOJDZYQHGGGPWr19vJKV4dOzY0RhjTFJSknn//fdNQECA8fDwMI899pjZu3dv5gaNh9adrtcrV66YJ554wuTNm9e4ubmZ4OBg07VrVxMTE5PZYeMhldq1KsnMmDHDWufq1avm9ddfN7lz5zY5cuQwzz77rDlx4kTmBY10sRhjzP1PZwAAAAD8lzDHAgAAAIDDSCwAAAAAOIzEAgAAAIDDSCwAAAAAOIzEAgAAAIDDSCwAAAAAOIzEAgAAAIDDSCwAAEinDRs2yGKx6Pz58w/EfgDgQUJiAQD3wGKx3PExePBgpx+zfv36slgsmjt3rk15ZGSkQkJC0h2vj4+PqlatqqVLlzo9RqRUv3599e7d26asZs2aOnHihHx9fTMnKADIACQWAHAPTpw4YX1ERkbKx8fHpqxv374ZclxPT08NGDBA169ft7vtjBkzdOLECf3xxx+qVauWWrVqpZ07d2ZAlLgbd3d3BQYGymKxZHYoAOA0JBYAcA8CAwOtD19fX1ksFutzf39/jR07VgULFpSHh4cqVqyolStXWttGRUVZex5q1qwpT09PlS1bVj/++ONdj9uuXTudP39eU6dOtTvmXLlyKTAwUCVKlNCwYcN048YNrV+/3rr96NGjat26tXLlyiU/Pz8988wzioqKstnH9OnT9eijj8rDw0P58uVTjx49rNuio6P1zDPPyMvLSz4+PmrdurViY2Ot2wcPHqyKFStq+vTpKlSokLy8vPT6668rMTFRo0ePtp67Dz/80OaYFotFn3/+uZ5++mnlyJFDpUuX1ubNm3XgwAHVr19fOXPmVM2aNXXw4EGbdkuXLlXlypXl6empIkWKaMiQIbpx44bNfr/44gs9++yzypEjh4oXL65ly5bZ7OP7779XiRIllD17djVo0CDF+Thz5ozatWunAgUKKEeOHCpXrpy++eYb6/ZOnTrpxx9/1Pjx4609RlFRUakOhVq0aJH13IaEhGjMmDE2xwoJCdHw4cP10ksvydvbW4UKFdKUKVOs2xMSEtSjRw/ly5dPnp6eCg4O1ogRIwQA940BADhkxowZxtfX1/p87NixxsfHx3zzzTdmz5495u233zZubm5m3759xhhjDh8+bCSZggULmoULF5pdu3aZl19+2Xh7e5vTp0+neZx69eqZXr16mbFjx5qAgABz6dIlY4wx48aNM8HBwXeMUZJZsmSJMcaY69evm3HjxhlJZtKkScYYYxISEkzp0qXNSy+9ZP766y+za9cu8/zzz5uSJUua+Ph4Y4wxEydONJ6eniYyMtLs3bvXbNmyxYwbN84YY0xiYqKpWLGiqV27tvnjjz/Mr7/+akJDQ029evWsMQwaNMh4eXmZVq1amX/++ccsW7bMuLu7m/DwcPPGG2+YPXv2mOnTpxtJ5tdff7WJvUCBAmbevHlm7969pnnz5iYkJMQ0bNjQrFy50uzatctUr17dPPnkk9Y2GzduND4+PmbmzJnm4MGDZvXq1SYkJMQMHjzYZr8FCxY0c+bMMfv37zc9e/Y0Xl5e5syZM8YYY6Kjo42Hh4eJiIgwe/bsMV9//bUJCAgwksy5c+eMMcb8+++/5qOPPjLbt283Bw8eNJ988olxdXU1v/32mzHGmPPnz5saNWqYrl27mhMnTpgTJ06YGzdumPXr19vs548//jAuLi5m6NChZu/evWbGjBkme/bsZsaMGdZ4g4ODjZ+fn5kwYYLZv3+/GTFihHFxcTF79uwxxhjz0UcfmaCgILNx40YTFRVlfvrpJzNnzpw7XhcA4EwkFgDgoNsTi/z585sPP/zQpk7VqlXN66+/boz5v8Ri5MiR1u3Xr183BQsWNKNGjUrzOMmJxbVr10xwcLAZOnSoMSb9iYWnp6fJmTOncXFxMZJMSEiI9Uf0rFmzTMmSJU1SUpK1TXx8vMmePbtZtWqV9XW99957qe5/9erVxtXV1URHR1vL/vnnHyPJbNmyxRhzM7HIkSOHiYuLs9YJDw83ISEhJjEx0VpWsmRJM2LECJvYBwwYYH2+efNmI8lMmzbNWvbNN98YT09P6/PHHnvMDB8+3CbGWbNmmXz58qW530uXLhlJZsWKFcYYY/r372/KlCljs4933nnHJiFITZMmTcybb75pfZ78vt3q9sTi+eefN48//rhNnbfeesvm+MHBweaFF16wPk9KSjL+/v7W5PCNN94wDRs2tHkPAeB+YigUADhRXFycjh8/rlq1atmU16pVS7t377Ypq1GjhvXf2bJlU5UqVVLUSY2Hh4eGDh2qjz/+WKdPn053bOPGjdOOHTu0YsUKlSlTRl988YX8/PwkSX/++acOHDggb29veXl5ycvLS35+frp27ZoOHjyokydP6vjx43rsscdS3ffu3bsVFBSkoKAga1mZMmWUK1cum9cUEhIib29v6/OAgACVKVNGLi4uNmUnT5602X/58uVttktSuXLlbMquXbumuLg46+sZOnSo9bV4eXmpa9euOnHihK5cuZLqfnPmzCkfHx/rsXfv3q2wsDCbOG59zyQpMTFRw4YNU7ly5eTn5ycvLy+tWrVK0dHRqZ6ntOzevTvVa2b//v1KTExMNd7k4XfJ8Xbq1Ek7duxQyZIl1bNnT61evdquGADAUdkyOwAAgP1eeOEFffzxx/rggw/uuiJUssDAQBUrVkzFihXTjBkz1LhxY+3atUv+/v66dOmSQkNDNXv27BTt8ubNa/PD3xFubm42zy0WS6plSUlJabZLnvCcWllyu0uXLmnIkCFq0aJFihg8PT3vGM/tx76Tjz76SOPHj1dkZKTKlSunnDlzqnfv3kpISEj3Puxxp3grV66sw4cPa8WKFfrhhx/UunVrNWrUSAsXLsyQWADgdvRYAIAT+fj4KH/+/Pr5559tyn/++WeVKVPGpuzXX3+1/vvGjRvaunWrSpcuna7juLi4aMSIEZo0aVKKCcXpUa1aNYWGhlonSleuXFn79++Xv7+/NflIfvj6+srb21shISFau3ZtqvsrXbq0jh49qqNHj1rLdu3apfPnz6d43fdD5cqVtXfv3hSvpVixYulOkkqXLq0tW7bYlN36nkk339dnnnlGL7zwgipUqKAiRYpo3759NnXc3d1teh3SOlZq10yJEiXk6uqarnilm9dfmzZtNHXqVM2bN0+LFi3S2bNn090eABxBYgEATvbWW29p1KhRmjdvnvbu3at+/fppx44d6tWrl029CRMmaMmSJdqzZ4+6d++uc+fO6aWXXkr3cZo0aaKwsDB9/vnn9xRn79699fnnn+vYsWNq37698uTJo2eeeUY//fSTDh8+rA0bNqhnz576999/Jd1c1WnMmDH65JNPtH//fm3btk2ffvqpJKlRo0YqV66c2rdvr23btmnLli3q0KGD6tWrpypVqtxTfI4YOHCgvvrqKw0ZMkT//POPdu/erblz52rAgAHp3serr76q/fv366233tLevXs1Z84czZw506ZO8eLFtWbNGv3yyy/avXu3unXrZrMSlnRz+Ndvv/2mqKgonT59OtUekTfffFNr167VsGHDtG/fPn355Zf67LPP7Fq2eOzYsfrmm2+0Z88e7du3TwsWLFBgYKBy5cqV7n0AgCNILADAyXr27KmIiAi9+eabKleunFauXKlly5apePHiNvVGjhypkSNHqkKFCtq0aZOWLVumPHny2HWsUaNG6dq1a/cU55NPPqnChQvrww8/VI4cObRx40YVKlRILVq0UOnSpdWlSxddu3ZNPj4+kqSOHTsqMjJSEydO1KOPPqqnn35a+/fvl3RzSM7SpUuVO3du1a1bV40aNVKRIkU0b968e4rNUeHh4fruu++0evVqVa1aVdWrV9e4ceMUHByc7n0UKlRIixYt0rfffqsKFSpo8uTJGj58uE2dAQMGqHLlygoPD1f9+vUVGBio5s2b29Tp27evXF1dVaZMGeXNmzfV+ReVK1fW/PnzNXfuXJUtW1YDBw7U0KFD1alTp3TH6+3trdGjR6tKlSqqWrWqoqKi9P333zttGBsA3I3FGGMyOwgAeJhERUWpcOHC2r59uypWrJjZ4QAA4BT8GQMAAACAw0gsAAAAADiMoVAAAAAAHEaPBQAAAACHkVgAAAAAcBiJBQAAAACHkVgAAAAAcBiJBQAAAACHkVgAAAAAcBiJBQAAAACHkVgAAAAAcBiJBQAAAACHkVgAAAAAcBiJBQAAAACHkVgAAAAAcBiJBQAAAACHkVgAAAAAcBiJBYCHVlRUlCwWi2bOnGktGzx4sCwWS+YFlYYHNa5kqZ3LjHLjxg29/fbbCgoKkouLi5o3b57hx7RXSEiIOnXqZFO2f/9+PfHEE/L19ZXFYtG3334rSfr9999Vs2ZN5cyZUxaLRTt27Ljv8eL+s1gsGjx4cGaHATgViQVgp4kTJ8pisSgsLCyzQ3nghISE6Omnn76ntt9//32W/Z/s8ePHNXjw4HT/IJw5c6YsFov14enpqfz58ys8PFyffPKJLl68mLEB3ycZ9Z5Onz5dH330kVq1aqUvv/xSffr0cfoxblW/fn3re+Xi4iIfHx+VLFlSL774otasWZPu/XTs2FE7d+7Uhx9+qFmzZqlKlSq6fv26nnvuOZ09e1bjxo3TrFmzFBwcnIGv5t5duXJFgwcP1oYNG+5aNyQkxOYaT+txPxLR5GONGTMmxbbkz+Iff/yRZvuePXvKYrHowIEDadZ57733ZLFY9NdffzklZiDLMgDsUrNmTRMSEmIkmf3792d2OA+U4OBg06RJk3tq2717d3O/v5IOHz5sJJkZM2ZYy65fv26uXr1q135+//33FPu5kxkzZhhJZujQoWbWrFlm+vTpZvjw4eaJJ54wFovFBAcHmz///NOmzb3EdT8lJSWZq1evmhs3bljLMuo9bdOmjSlQoIDT95uWevXqmYIFC5pZs2aZWbNmmcmTJ5u+ffuaIkWKGEmmdevWJiEhwabNtWvXbMquXLliJJn33nvPpt7u3buNJDN16tT78loccerUKSPJDBo06K51lyxZYj1fs2bNMu3atTOSzLhx42zKDx48mOFxSzKSTEBAgLl8+bLNtuTP4u+//55m+19//dVIMkOGDEmzTuHChU25cuXsjis95xLISrLd/1QGyLoOHz6sX375RYsXL1a3bt00e/ZsDRo06L7GkJSUpISEBHl6et7X4z5Ibty4oaSkJLm7uzt939myZVO2bPfnq/Gpp55SlSpVrM/79++vdevW6emnn1azZs20e/duZc+e/b7HlcwYo2vXrlljuJPknpf74eTJk8qVK5fT9peez5Svr69eeOEFm7KRI0eqZ8+emjhxokJCQjRq1CjrNg8PD5u6p06dkqQUcZ88eTLVckdcvnxZOXPmdNr+7sXtw9NiYmL0zTffqHnz5goJCbnv8VSsWFE7duzQ5MmTFRERYVfbsLAwFStWTN98840GDhyYYvvmzZt1+PBhjRw50lnhAlkWQ6EAO8yePVu5c+dWkyZN1KpVK82ePdu67fr16/Lz81Pnzp1TtIuLi5Onp6f69u1rLYuPj9egQYNUrFgxeXh4KCgoSG+//bbi4+Nt2losFvXo0UOzZ8/Wo48+Kg8PD61cuVKS9PHHH6tmzZp65JFHlD17doWGhmrhwoUpjn/16lX17NlTefLkkbe3t5o1a6Zjx46lOsb32LFjeumllxQQECAPDw89+uijmj59+j2dr+Rx9x9//LGmTJmiokWLysPDQ1WrVtXvv/9urdepUydNmDDB+nqTH7fvIzIy0rqPXbt2KSEhQQMHDlRoaKh8fX2VM2dO1alTR+vXr7+neKXU5zKsWbNGtWvXVq5cueTl5aWSJUvq3XfflSRt2LBBVatWlSR17tzZ4SEeDRs21Pvvv68jR47o66+/TjOusmXLqkGDBinaJyUlqUCBAmrVqpVNWWRkpB599FF5enoqICBA3bp107lz52zaJg9lW7VqlapUqaLs2bPr888/v+s5kFLOsUjrPTXGKCQkRM8880yK2K9duyZfX19169Yt1XOTfIz169frn3/+se4zeWjO5cuX9eabbyooKEgeHh4qWbKkPv74YxljbPZzp8+UPVxdXfXJJ5+oTJky+uyzz3ThwgWbc5k8x2Lw4MHW4U1vvfWWLBaLdXu9evUkSc8995wsFovq169v3ceePXvUqlUr+fn5ydPTU1WqVNGyZctsYkgeyvPjjz/q9ddfl7+/vwoWLGjdvmLFCtWpU0c5c+aUt7e3mjRpon/++cdmH506dZKXl5eOHTum5s2by8vLS3nz5lXfvn2VmJhoPfd58+aVJA0ZMsR67h0Z6nbjxg0NGzbM+pkOCQnRu+++m+I7MPm6XL16tSpWrChPT0+VKVNGixcvTvexatWqpYYNG2r06NG6evWq3bG2b99ee/bs0bZt21JsmzNnjiwWi9q1a+fQd1KnTp1STbrSml/19ddfKzQ0VNmzZ5efn5/atm2ro0eP2tTZv3+/WrZsqcDAQHl6eqpgwYJq27atzbUKOBM9FoAdZs+erRYtWsjd3V3t2rXTpEmT9Pvvv6tq1apyc3PTs88+q8WLF+vzzz+3+Wv6t99+q/j4eLVt21bSzR96zZo106ZNm/TKK6+odOnS2rlzp8aNG6d9+/ZZJ3UmW7dunebPn68ePXooT5481v/5jB8/Xs2aNVP79u2VkJCguXPn6rnnntN3332nJk2aWNt36tRJ8+fP14svvqjq1avrxx9/tNmeLDY2VtWrV7f+8MqbN69WrFihLl26KC4uTr17976n8zZnzhxdvHhR3bp1k8Vi0ejRo9WiRQsdOnRIbm5u6tatm44fP641a9Zo1qxZqe5jxowZunbtml555RV5eHjIz89PcXFx+uKLL9SuXTt17dpVFy9e1LRp0xQeHq4tW7aoYsWK9xTvrf755x89/fTTKl++vIYOHSoPDw8dOHBAP//8sySpdOnSGjp0qAYOHKhXXnlFderUkSTVrFnzno/54osv6t1339Xq1avVtWvXVOu0adNGgwcPVkxMjAIDA63lmzZt0vHjx63XmiR169ZNM2fOVOfOndWzZ08dPnxYn332mbZv366ff/5Zbm5u1rp79+5Vu3bt1K1bN3Xt2lUlS5a86zlITVrvqcVi0QsvvKDRo0fr7Nmz8vPzs2773//+p7i4uBQ9A8ny5s2rWbNm6cMPP9SlS5c0YsQISTffA2OMmjVrpvXr16tLly6qWLGiVq1apbfeekvHjh3TuHHjbPaV1mfKXq6urmrXrp3ef/99bdq0KdXPVYsWLZQrVy716dNH7dq1U+PGjeXl5aWAgAAVKFBAw4cPV8+ePVW1alUFBARIunnd1apVSwUKFFC/fv2UM2dOzZ8/X82bN9eiRYv07LPP2hzj9ddfV968eTVw4EBdvnxZkjRr1ix17NhR4eHhGjVqlK5cuaJJkyapdu3a2r59u81rTkxMVHh4uMLCwvTxxx/rhx9+0JgxY1S0aFG99tpryps3ryZNmqTXXntNzz77rFq0aCFJKl++/D2dN0l6+eWX9eWXX6pVq1Z688039dtvv2nEiBHavXu3lixZYlN3//79atOmjV599VV17NhRM2bM0HPPPaeVK1fq8ccfT9fxBg8erLp162rSpEl291q0b99eQ4YM0Zw5c1S5cmVreWJioubPn686deqoUKFCOn36dIZ/J0nShx9+qPfff1+tW7fWyy+/rFOnTunTTz9V3bp1tX37duXKlUsJCQkKDw9XfHy83njjDQUGBurYsWP67rvvdP78efn6+jolFsBG5o7EArKOP/74w0gya9asMcbcHFNesGBB06tXL2udVatWGUnmf//7n03bxo0bmyJFilifz5o1y7i4uJiffvrJpt7kyZONJPPzzz9byyQZFxcX888//6SI6cqVKzbPExISTNmyZU3Dhg2tZVu3bjWSTO/evW3qdurUKcUY3y5duph8+fKZ06dP29Rt27at8fX1TXG8290+xyJ5DsMjjzxizp49ay1funRpivOU1nj85H34+PiYkydP2my7ceOGiY+Ptyk7d+6cCQgIMC+99NIdY71137fOjRg0aJBNHOPGjTOSzKlTp9Lcz73OsbjTuG5fX19TqVKlNOPau3evkWQ+/fRTm3avv/668fLysr5XP/30k5FkZs+ebVNv5cqVKcqDg4ONJLNy5Uqbuuk5B6mdy7Te0+TYJ02aZFPerFkzExISYpKSktI8jjE35zw8+uijNmXffvutkWQ++OADm/JWrVoZi8ViDhw4YC2702cqvce71ZIlS4wkM378eGtZcHCw6dixo/V58vn56KOPbNquX7/eSDILFiywKX/sscdMuXLlzLVr16xlSUlJpmbNmqZ48eLWsuRrqXbt2jbzWy5evGhy5cplunbtarPfmJgY4+vra1PesWNH65yfW1WqVMmEhoZan9szx+J2H330kZFkDh8+bIwxZseOHUaSefnll23q9e3b10gy69ats5YlX5eLFi2yll24cMHky5fP5jOSFkmme/fuxhhjGjRoYAIDA62fj/R8FpNVrVrVFCxY0CQmJlrLkj9Hn3/+uTHGvu+k289lx44dTXBwcIrj3v7Zj4qKMq6urubDDz+0qbdz506TLVs2a/n27dtTvbaAjMRQKCCdZs+erYCAAOvwE4vFojZt2mju3LnW4QINGzZUnjx5NG/ePGu7c+fOac2aNWrTpo21bMGCBSpdurRKlSql06dPWx8NGzaUpBTd5vXq1VOZMmVSxHTr2Pdz587pwoULqlOnjk13ffIQj9dff92m7RtvvGHz3BijRYsWqWnTpjLG2MQVHh6uCxcupDoMID3atGmj3LlzW58n/1X/0KFD6d5Hy5YtrUMxkrm6ulp7hpKSknT27FnduHFDVapUuedYb5c89n3p0qVKSkpyyj7Tw8vL646rQ5UoUUIVK1a0udYSExO1cOFCNW3a1HptLFiwQL6+vnr88cdt3tPQ0FB5eXmluNYKFy6s8PBwmzJnn4MSJUooLCzMZijh2bNntWLFCrVv3/6eltX9/vvv5erqqp49e9qUv/nmmzLGaMWKFTblaX2m7oWXl5ckOW01r7Nnz2rdunVq3bq1Ll68aH3Pzpw5o/DwcO3fv1/Hjh2zadO1a1e5urpan69Zs0bnz59Xu3btbN53V1dXhYWFpTo059VXX7V5XqdOHbs+o/b4/vvvJSlFz8Gbb74pSVq+fLlNef78+W16aXx8fNShQwdt375dMTEx6T5uci/f5MmT7Y75hRde0L///quNGzday+bMmSN3d3c999xzku7Pd9LixYuVlJSk1q1b27y3gYGBKl68uPW9Te6RWLVqla5cueKUYwN3Q2IBpENiYqLmzp2rBg0a6PDhwzpw4IAOHDigsLAwxcbGau3atZJuTrBt2bKlli5dah0nvHjxYl2/ft0msdi/f7/++ecf5c2b1+ZRokQJSf83oTNZ4cKFU43ru+++U/Xq1eXp6Sk/Pz/rcIVbx88eOXJELi4uKfZRrFgxm+enTp3S+fPnNWXKlBRxJc8buT2u9CpUqJDN8+Qk4/Yx/neS1jn48ssvVb58eXl6euqRRx5R3rx5tXz5cptzcOrUKcXExFgfly5dSvdx27Rpo1q1aunll19WQECA2rZtq/nz52d4knHp0iV5e3vfNbaff/7Z+iNzw4YNOnnyZIpr7cKFC/L390/xvl66dCld11pGnIMOHTro559/1pEjRyTdTICuX7+uF1988Z72d+TIEeXPnz/FOStdurR1+63Sup7uRfL1dLf3K70OHDggY4zef//9FO9Z8mIRd3vf9u/fL+nmHztu38fq1atTtPf09EyRuOfOnduuz6g9kr+Xbv8eCgwMVK5cuVK8X8WKFUuRcCZ/X0ZFRaX7uHXr1lWDBg3uaa5F27Zt5erqqjlz5ki6OSdoyZIleuqpp2z+cJKe7yRH7N+/X8YYFS9ePMV7u3v3but7W7hwYUVEROiLL75Qnjx5FB4ergkTJjC/AhmKORZAOqxbt04nTpzQ3LlzNXfu3BTbZ8+erSeeeELSzf/5fP7551qxYoWaN2+u+fPnq1SpUqpQoYK1flJSksqVK6exY8emerygoCCb56mtyvPTTz+pWbNmqlu3riZOnKh8+fLJzc1NM2bMsP6Pzx7JPxJfeOEFdezYMdU69zqe+ta/pN7K3Dap9k5SOwdff/21OnXqpObNm+utt96Sv7+/XF1dNWLECB08eNBar2rVqjY/VAYNGpTuSafZs2fXxo0btX79ei1fvlwrV67UvHnz1LBhQ61evTrN1+aIf//9VxcuXEjxo+t2bdq0Uf/+/bVgwQL17t1b8+fPl6+vr5588klrnaSkJPn7+9v0Dtzq9h+TqZ3njDgHbdu2VZ8+fTR79my9++67+vrrr1WlShWVLFnS7n3di/SsdJVef//9t6SUyfq9Sv4s9u3bN0XvUbLbj3X760nex6xZs2zm4CS7fYWxjLiO0yMzbvo4aNAg1a9fX59//rldq3H5+/vr8ccf16JFizRhwgT973//08WLF9W+fXtrnfR+J6UmrXOR3COeLCkpSRaLRStWrEj1fUvuQZOkMWPGqFOnTlq6dKlWr16tnj17asSIEfr1119tJvkDzkJiAaTD7Nmz5e/vb13l5laLFy/WkiVLNHnyZGXPnl1169ZVvnz5NG/ePNWuXVvr1q3Te++9Z9OmaNGi+vPPP/XYY4/d8/9YFy1aJE9PT61atcpmacsZM2bY1AsODlZSUpIOHz6s4sWLW8tvv9lT3rx55e3trcTERDVq1OieYnLEvZyHhQsXqkiRIlq8eLFN+9uXAJ49e7bNXyeLFCli13FcXFz02GOP6bHHHtPYsWM1fPhwvffee1q/fr0aNWrk9B9HyZOd0/pRmaxw4cKqVq2a5s2bpx49emjx4sVq3ry5zfVQtGhR/fDDD6pVq5ZDP6bvdg5Sc6fz4ufnpyZNmmj27Nlq3769fv75Z0VGRt5zfMHBwfrhhx908eJFm56DPXv2WLdnhMTERM2ZM0c5cuRQ7dq1nbLP5OvTzc3tnj+LRYsWlXTzx7CzPs/OvM6Tv5f2799v7VWSbi4gcf78+RTvV3Ivzq0x7Nu3T5Lsnnhfr1491a9fX6NGjUp1+dg7ad++vVauXKkVK1Zozpw58vHxUdOmTa3b0/udlJrcuXPr/PnzKcpv770pWrSojDEqXLiwtdfmTsqVK6dy5cppwIAB+uWXX1SrVi1NnjxZH3zwwV3bAvZiKBRwF1evXtXixYv19NNPq1WrVikePXr00MWLF63LQLq4uKhVq1b63//+p1mzZunGjRs2Q1MkqXXr1jp27JimTp2a6vGSV3W5E1dXV1ksFpu/ZkVFRaVYUSr5x+nEiRNtyj/99NMU+2vZsqUWLVpk/QvsrZLX4c8oyevup/Y/1rQk/7Xu1p6P3377TZs3b7apV6tWLTVq1Mj6sCexOHv2bIqy5JVdkoe73UvsaVm3bp2GDRumwoUL2/wlNC1t2rTRr7/+qunTp+v06dOpXmuJiYkaNmxYirY3btxIV8zpOQepudt5efHFF7Vr1y699dZbcnV1tVnJyl6NGzdWYmKiPvvsM5vycePGyWKx6KmnnrrnfaclMTFRPXv21O7du9WzZ0/5+Pg4Zb/+/v7Wv6ifOHEixfb0fBbDw8Pl4+Oj4cOH6/r16/e0j9vlyJFDknOu88aNG0tSimQyuRf39tW1jh8/brNSVFxcnL766itVrFgx1R6Zu0meazFlyhS72jVv3lw5cuTQxIkTtWLFCrVo0cLm/ifp/U5KTdGiRXXhwgWbu3efOHEixQpZLVq0kKurq4YMGZKi19cYozNnzki6eY5u3Lhhs71cuXJycXG54+cWcAQ9FsBdLFu2TBcvXlSzZs1S3V69enXlzZtXs2fPtv6oa9OmjT799FMNGjRI5cqVs/mLnHTzB9X8+fP16quvav369apVq5YSExO1Z88ezZ8/33ofgTtp0qSJxo4dqyeffFLPP/+8Tp48qQkTJqhYsWI2/2MKDQ1Vy5YtFRkZqTNnzliXm03+a9+tf1UbOXKk1q9fr7CwMHXt2lVlypTR2bNntW3bNv3www+p/sB0ltDQUElSz549FR4enq4fmk8//bQWL16sZ599Vk2aNNHhw4c1efJklSlTxq55FHcydOhQbdy4UU2aNFFwcLBOnjypiRMnqmDBgta/UBctWlS5cuXS5MmT5e3trZw5cyosLOyu4/hXrFihPXv26MaNG4qNjdW6deu0Zs0aBQcHa9myZem64Vzr1q3Vt29f9e3bV35+fin+Ol2vXj1169ZNI0aM0I4dO/TEE0/Izc1N+/fv14IFCzR+/Hibe17c6zlIzd3e0yZNmuiRRx7RggUL9NRTT8nf3/+urzctTZs2VYMGDfTee+8pKipKFSpU0OrVq7V06VL17t3b+hf8e3XhwgXrfUWuXLmiAwcOaPHixTp48KDatm2bauLmiAkTJqh27doqV66cunbtqiJFiig2NlabN2/Wv//+qz///POO7X18fDRp0iS9+OKLqly5stq2bau8efMqOjpay5cvV61atVIkYXeTPXt2lSlTRvPmzVOJEiXk5+ensmXLqmzZsna/vgoVKqhjx46aMmWKzp8/r3r16mnLli368ssv1bx58xT3aClRooS6dOmi33//XQEBAZo+fbpiY2NT9NCmV7169VSvXj39+OOPdrXz8vJS8+bNrcNNb0/+HflOatu2rd555x09++yz6tmzp3V54BIlSthM/C5atKg++OAD9e/fX1FRUWrevLm8vb11+PBhLVmyRK+88or69u2rdevWqUePHnruuedUokQJ3bhxQ7NmzbL+EQnIEJmzGBWQdTRt2tR4enqay5cvp1mnU6dOxs3NzbpMa1JSkgkKCkp1+ctkCQkJZtSoUebRRx81Hh4eJnfu3CY0NNQMGTLEXLhwwVpPtyyVeLtp06aZ4sWLGw8PD1OqVCkzY8aMFEsTGmPM5cuXTffu3Y2fn5/x8vIyzZs3ty75OXLkSJu6sbGxpnv37iYoKMi4ubmZwMBA89hjj5kpU6bc9Vyltdzs7UtsJr+uW5davHHjhnnjjTdM3rx5jcVisb6GO+0jKSnJDB8+3AQHBxsPDw9TqVIl891336W5bOPt0rPc7Nq1a80zzzxj8ufPb9zd3U3+/PlNu3btzL59+2z2tXTpUlOmTBmTLVu2uy49m7zEZfLD3d3dBAYGmscff9yMHz/exMXFpWiT2vuarFatWqku3XmrKVOmmNDQUJM9e3bj7e1typUrZ95++21z/Phxa53b3z97zkFq5zKt9/RWr7/+upFk5syZk2bst0tr+deLFy+aPn36mPz58xs3NzdTvHhx89FHH6VYvvZOn6m0jnfr++Xl5WWKFy9uXnjhBbN69epU2zi63Kwxxhw8eNB06NDBBAYGGjc3N1OgQAHz9NNPm4ULF1rr3G251PXr15vw8HDj6+trPD09TdGiRU2nTp3MH3/8Ya3TsWNHkzNnzhRtU7vmfvnlFxMaGmrc3d3tWnr29uVmjTHm+vXrZsiQIaZw4cLGzc3NBAUFmf79+9sssWvM/12Xq1atMuXLl7d+36V3GdW03u/kc3+n85ea5cuXG0kmX758NkvPGmPfd1Jq52/16tWmbNmyxt3d3ZQsWdJ8/fXXaX72Fy1aZGrXrm1y5sxpcubMaUqVKmW6d+9u9u7da4wx5tChQ+all14yRYsWNZ6ensbPz880aNDA/PDDD+l+rYC9LMbYMXsSwH/Gjh07VKlSJX399dfpGnIDZIQ+ffpo2rRpiomJsQ61AW4VEhKismXL6rvvvsvsUADcBXMsgIdAassqRkZGysXFRXXr1s2EiICby3V+/fXXatmyJUkFAPwHMMcCeAiMHj1aW7duVYMGDZQtWzatWLFCK1as0CuvvJJiaVsgo508eVI//PCDFi5cqDNnzqhXr16ZHRIAwAlILICHQM2aNbVmzRoNGzZMly5dUqFChTR48OAUy+AC98OuXbvUvn17+fv765NPPrGuMAUAyNqYYwEAAADAYcyxAAAAAOAwEgsAAAAADnvo5lgkJSXp+PHj8vb2trkxGAAAAABbxhhdvHhR+fPnl4vLnfskHrrE4vjx46yCAwAAANjh6NGjKliw4B3rPHSJhbe3t6SbJ8fHxyeTowEAAAAeXHFxcQoKCrL+hr6Thy6xSB7+5OPjQ2IBAAAApEN6phAweRsAAACAw0gsAAAAADiMxAIAAACAw0gsAAAAADiMxAIAAACAwzI1sdi4caOaNm2q/Pnzy2Kx6Ntvv71rmw0bNqhy5cry8PBQsWLFNHPmzAyPEwAAAMCdZWpicfnyZVWoUEETJkxIV/3Dhw+rSZMmatCggXbs2KHevXvr5Zdf1qpVqzI4UgAAAAB3kqn3sXjqqaf01FNPpbv+5MmTVbhwYY0ZM0aSVLp0aW3atEnjxo1TeHh4qm3i4+MVHx9vfR4XF+dY0AAAAABSyFI3yNu8ebMaNWpkUxYeHq7evXun2WbEiBEaMmRIBkdmP8uQu99kBDCDTGaHIEkauf10ZoeAB1y/SnkyOwQAQCbLUpO3Y2JiFBAQYFMWEBCguLg4Xb16NdU2/fv314ULF6yPo0eP3o9QAQAAgIdKluqxuBceHh7y8PDI7DAAAACA/7Qs1WMRGBio2NhYm7LY2Fj5+Pgoe/bsmRQVAAAAgCyVWNSoUUNr1661KVuzZo1q1KiRSREBAAAAkDI5sbh06ZJ27NihHTt2SLq5nOyOHTsUHR0t6eb8iA4dOljrv/rqqzp06JDefvtt7dmzRxMnTtT8+fPVp0+fzAgfAAAAwP+XqYnFH3/8oUqVKqlSpUqSpIiICFWqVEkDBw6UJJ04ccKaZEhS4cKFtXz5cq1Zs0YVKlTQmDFj9MUXX6S51CwAAACA+yNTJ2/Xr19fxqS9nGZqd9WuX7++tm/fnoFRAQAAALBXlppjAQAAAODB9J9fbhYA8HDhho64mwfpho5cr7ibB+l6vRt6LAAAAAA4jMQCAAAAgMNILAAAAAA4jMQCAAAAgMNILAAAAAA4jMQCAAAAgMNILAAAAAA4jMQCAAAAgMNILAAAAAA4jMQCAAAAgMNILAAAAAA4zO7E4tChQxkRBwAAAIAszO7EolixYmrQoIG+/vprXbt2LSNiAgAAAJDF2J1YbNu2TeXLl1dERIQCAwPVrVs3bdmyJSNiAwAAAJBF2J1YVKxYUePHj9fx48c1ffp0nThxQrVr11bZsmU1duxYnTp1KiPiBAAAAPAAu+fJ29myZVOLFi20YMECjRo1SgcOHFDfvn0VFBSkDh066MSJE86MEwAAAMAD7J4Tiz/++EOvv/668uXLp7Fjx6pv3746ePCg1qxZo+PHj+uZZ55xZpwAAAAAHmDZ7G0wduxYzZgxQ3v37lXjxo311VdfqXHjxnJxuZmjFC5cWDNnzlRISIizYwUAAADwgLI7sZg0aZJeeuklderUSfny5Uu1jr+/v6ZNm+ZwcAAAAACyBrsTizVr1qhQoULWHopkxhgdPXpUhQoVkru7uzp27Oi0IAEAAAA82OyeY1G0aFGdPn06RfnZs2dVuHBhpwQFAAAAIGuxO7EwxqRafunSJXl6ejocEAAAAICsJ91DoSIiIiRJFotFAwcOVI4cOazbEhMT9dtvv6lixYpODxAAAADAgy/dicX27dsl3eyx2Llzp9zd3a3b3N3dVaFCBfXt29f5EQIAAAB44KU7sVi/fr0kqXPnzho/frx8fHwyLCgAAAAAWYvdq0LNmDEjI+IAAAAAkIWlK7Fo0aKFZs6cKR8fH7Vo0eKOdRcvXuyUwAAAAABkHelKLHx9fWWxWKz/BgAAAIBbpSuxuHX4E0OhAAAAANzO7vtYXL16VVeuXLE+P3LkiCIjI7V69WqnBgYAAAAg67A7sXjmmWf01VdfSZLOnz+vatWqacyYMXrmmWc0adIkpwcIAAAA4MFnd2Kxbds21alTR5K0cOFCBQYG6siRI/rqq6/0ySefOD1AAAAAAA8+uxOLK1euyNvbW5K0evVqtWjRQi4uLqpevbqOHDni9AABAAAAPPjsTiyKFSumb7/9VkePHtWqVav0xBNPSJJOnjzJTfMAAACAh5TdicXAgQPVt29fhYSEKCwsTDVq1JB0s/eiUqVKdgcwYcIEhYSEyNPTU2FhYdqyZcsd60dGRqpkyZLKnj27goKC1KdPH127ds3u4wIAAABwHrvvvN2qVSvVrl1bJ06cUIUKFazljz32mJ599lm79jVv3jxFRERo8uTJCgsLU2RkpMLDw7V37175+/unqD9nzhz169dP06dPV82aNbVv3z516tRJFotFY8eOtfelAAAAAHASu3osrl+/rmzZsun06dOqVKmSXFz+r3m1atVUqlQpuw4+duxYde3aVZ07d1aZMmU0efJk5ciRQ9OnT0+1/i+//KJatWrp+eefV0hIiJ544gm1a9furr0cAAAAADKWXYmFm5ubChUqpMTERIcPnJCQoK1bt6pRo0b/F4yLixo1aqTNmzen2qZmzZraunWrNZE4dOiQvv/+ezVu3DjN48THxysuLs7mAQAAAMC57J5j8d577+ndd9/V2bNnHTrw6dOnlZiYqICAAJvygIAAxcTEpNrm+eef19ChQ1W7dm25ubmpaNGiql+/vt599900jzNixAj5+vpaH0FBQQ7FDQAAACAluxOLzz77TBs3blT+/PlVsmRJVa5c2eaRkTZs2KDhw4dr4sSJ2rZtmxYvXqzly5dr2LBhabbp37+/Lly4YH0cPXo0Q2MEAAAAHkZ2T95u3ry5Uw6cJ08eubq6KjY21qY8NjZWgYGBqbZ5//339eKLL+rll1+WJJUrV06XL1/WK6+8ovfee89mzkcyDw8PeXh4OCVmAAAAAKmzO7EYNGiQUw7s7u6u0NBQrV271pqsJCUlae3aterRo0eqba5cuZIieXB1dZUkGWOcEhcAAAAA+9mdWEjS+fPntXDhQh08eFBvvfWW/Pz8tG3bNgUEBKhAgQLp3k9ERIQ6duyoKlWqqFq1aoqMjNTly5fVuXNnSVKHDh1UoEABjRgxQpLUtGlTjR07VpUqVVJYWJgOHDig999/X02bNrUmGAAAAADuP7sTi7/++kuNGjWSr6+voqKi1LVrV/n5+Wnx4sWKjo7WV199le59tWnTRqdOndLAgQMVExOjihUrauXKldYJ3dHR0TY9FAMGDJDFYtGAAQN07Ngx5c2bV02bNtWHH35o78sAAAAA4ER2JxYRERHq1KmTRo8eLW9vb2t548aN9fzzz9sdQI8ePdIc+rRhwwab59myZdOgQYOcNhwLAAAAgHPYvSrU77//rm7duqUoL1CgQJrLxAIAAAD4b7M7sfDw8Ej1JnP79u1T3rx5nRIUAAAAgKzF7sSiWbNmGjp0qK5fvy5Jslgsio6O1jvvvKOWLVs6PUAAAAAADz67E4sxY8bo0qVL8vf319WrV1WvXj0VK1ZM3t7eTKIGAAAAHlJ2T9729fXVmjVrtGnTJv3111+6dOmSKleurEaNGmVEfAAAAACyALsTi6NHjyooKEi1a9dW7dq1MyImAAAAAFmM3UOhQkJCVK9ePU2dOlXnzp3LiJgAAAAAZDF2JxZ//PGHqlWrpqFDhypfvnxq3ry5Fi5cqPj4+IyIDwAAAEAWYHdiUalSJX300UeKjo7WihUrlDdvXr3yyisKCAjQSy+9lBExAgAAAHjA2Z1YJLNYLGrQoIGmTp2qH374QYULF9aXX37pzNgAAAAAZBH3nFj8+++/Gj16tCpWrKhq1arJy8tLEyZMcGZsAAAAALIIu1eF+vzzzzVnzhz9/PPPKlWqlNq3b6+lS5cqODg4I+IDAAAAkAXYnVh88MEHateunT755BNVqFAhI2ICAAAAkMXYnVhER0fLYrFkRCwAAAAAsqh0JRZ//fWXypYtKxcXF+3cufOOdcuXL++UwAAAAABkHelKLCpWrKiYmBj5+/urYsWKslgsMsZYtyc/t1gsSkxMzLBgAQAAADyY0pVYHD58WHnz5rX+GwAAAABula7E4tYVn1j9CQAAAMDt7J68vW7dOi1evFhRUVGyWCwqXLiwWrVqpbp162ZEfAAAAACyALtukPfqq6+qUaNG+uabb3TmzBmdOnVKs2fPVoMGDfTGG29kVIwAAAAAHnDpTiyWLFmiGTNmaPr06Tp9+rQ2b96sX3/9VadOndLUqVM1ZcoULVu2LCNjBQAAAPCASndiMWPGDEVERKhTp04297FwcXHRSy+9pN69e2vatGkZEiQAAACAB1u6E4tt27bp2WefTXN7ixYttHXrVqcEBQAAACBrSXdicfr0aRUsWDDN7QULFtSZM2ecEhQAAACArCXdiUVCQoLc3NzS3J4tWzYlJCQ4JSgAAAAAWYtdy82+//77ypEjR6rbrly54pSAAAAAAGQ96U4s6tatq7179961DgAAAICHT7oTiw0bNmRgGAAAAACyMrtukAcAAAAAqSGxAAAAAOAwEgsAAAAADiOxAAAAAOAwuxOL6OhoGWNSlBtjFB0d7ZSgAAAAAGQtdicWhQsX1qlTp1KUnz17VoULF3ZKUAAAAACyFrsTC2OMLBZLivJLly7J09PTKUEBAAAAyFrSfR+LiIgISZLFYklxB+7ExET99ttvqlixotMDBAAAAPDgS3ePxfbt27V9+3YZY7Rz507r8+3bt2vPnj2qUKGCZs6caXcAEyZMUEhIiDw9PRUWFqYtW7bcsf758+fVvXt35cuXTx4eHipRooS+//57u48LAAAAwHnS3WOxfv16SVLnzp01fvx4+fj4OHzwefPmKSIiQpMnT1ZYWJgiIyMVHh6uvXv3yt/fP0X9hIQEPf744/L399fChQtVoEABHTlyRLly5XI4FgAAAAD3Lt2JRbIZM2bYPI+Li9O6detUqlQplSpVyq59jR07Vl27dlXnzp0lSZMnT9by5cs1ffp09evXL0X96dOn6+zZs/rll1/k5uYmSQoJCbH3JQAAAABwMrsnb7du3VqfffaZJOnq1auqUqWKWrdurXLlymnRokXp3k9CQoK2bt2qRo0a/V8wLi5q1KiRNm/enGqbZcuWqUaNGurevbsCAgJUtmxZDR8+XImJiWkeJz4+XnFxcTYPAAAAAM5ld2KxceNG1alTR5K0ZMkSGWN0/vx5ffLJJ/rggw/SvZ/Tp08rMTFRAQEBNuUBAQGKiYlJtc2hQ4e0cOFCJSYm6vvvv9f777+vMWPG3PG4I0aMkK+vr/URFBSU7hgBAAAApI/dicWFCxfk5+cnSVq5cqVatmypHDlyqEmTJtq/f7/TA7xVUlKS/P39NWXKFIWGhqpNmzZ67733NHny5DTb9O/fXxcuXLA+jh49mqExAgAAAA8ju+dYBAUFafPmzfLz89PKlSs1d+5cSdK5c+fsuo9Fnjx55OrqqtjYWJvy2NhYBQYGptomX758cnNzk6urq7WsdOnSiomJUUJCgtzd3VO08fDwkIeHR7rjAgAAAGA/u3ssevfurfbt26tgwYLKnz+/6tevL+nmEKly5cqlez/u7u4KDQ3V2rVrrWVJSUlau3atatSokWqbWrVq6cCBA0pKSrKW7du3T/ny5Us1qQAAAABwf9idWLz++uvavHmzpk+frk2bNsnF5eYuihQpYtccC+nmTfemTp2qL7/8Urt379Zrr72my5cvW1eJ6tChg/r372+t/9prr+ns2bPq1auX9u3bp+XLl2v48OHq3r27vS8DAAAAgBPZPRRKkqpUqaIqVarYlDVp0sTu/bRp00anTp3SwIEDFRMTo4oVK2rlypXWCd3R0dHWxEW6OQxr1apV6tOnj8qXL68CBQqoV69eeuedd+7lZQAAAABwknQlFhERERo2bJhy5sypiIiIO9YdO3asXQH06NFDPXr0SHXbhg0bUpTVqFFDv/76q13HAAAAAJCx0pVYbN++XdevX7f+Oy0Wi8U5UQEAAADIUtKVWKxfvz7VfwMAAACAdA+TtwEAAADgdunqsWjRokW6d7h48eJ7DgYAAABA1pSuxMLX1zej4wAAAACQhaUrsZgxY0ZGxwEAAAAgC3NojsXIkSN1/vx5J4UCAAAAIKtyKLEYPny4zp4966xYAAAAAGRRDiUWxhhnxQEAAAAgC2O5WQAAAAAOS9fk7bTs2rVL+fPnd1YsAAAAALIohxKLoKAgZ8UBAAAAIAuzO7FITEzUuHHjNH/+fEVHRyshIcFmO5O5AQAAgIeP3XMshgwZorFjx6pNmza6cOGCIiIi1KJFC7m4uGjw4MEZECIAAACAB53dicXs2bM1depUvfnmm8qWLZvatWunL774QgMHDtSvv/6aETECAAAAeMDZnVjExMSoXLlykiQvLy9duHBBkvT0009r+fLlzo0OAAAAQJZgd2JRsGBBnThxQpJUtGhRrV69WpL0+++/y8PDw7nRAQAAAMgS7E4snn32Wa1du1aS9MYbb+j9999X8eLF1aFDB7300ktODxAAAADAg8/uVaFGjhxp/XebNm0UHBysX375RcWLF1fTpk2dGhwAAACArMGuxOL69evq1q2b3n//fRUuXFiSVL16dVWvXj1DggMAAACQNdg1FMrNzU2LFi3KqFgAAAAAZFF2z7Fo3ry5vv322wwIBQAAAEBWZfcci+LFi2vo0KH6+eefFRoaqpw5c9ps79mzp9OCAwAAAJA12J1YTJs2Tbly5dLWrVu1detWm20Wi4XEAgAAAHgI2Z1YHD58OCPiAAAAAJCF2T3HYujQobpy5UqK8qtXr2ro0KFOCQoAAABA1mJ3YjFkyBBdunQpRfmVK1c0ZMgQpwQFAAAAIGuxO7EwxshisaQo//PPP+Xn5+eUoAAAAABkLemeY5E7d25ZLBZZLBaVKFHCJrlITEzUpUuX9Oqrr2ZIkAAAAAAebOlOLCIjI2WM0UsvvaQhQ4bI19fXus3d3V0hISGqUaNGhgQJAAAA4MGW7sSiY8eOkqTChQurZs2acnNzy7CgAAAAAGQtdi83W69ePSUlJWnfvn06efKkkpKSbLbXrVvXacEBAAAAyBrsTix+/fVXPf/88zpy5IiMMTbbLBaLEhMTnRYcAAAAgKzB7sTi1VdfVZUqVbR8+XLly5cv1RWiAAAAADxc7E4s9u/fr4ULF6pYsWIZEQ8AAACALMju+1iEhYXpwIEDGRELAAAAgCzK7h6LN954Q2+++aZiYmJUrly5FKtDlS9f3mnBAQAAAMga7O6xaNmypXbv3q2XXnpJVatWVcWKFVWpUiXrf+/FhAkTFBISIk9PT4WFhWnLli3pajd37lxZLBY1b978no4LAAAAwDns7rE4fPiwUwOYN2+eIiIiNHnyZIWFhSkyMlLh4eHau3ev/P3902wXFRWlvn37qk6dOk6NBwAAAID97E4sgoODnRrA2LFj1bVrV3Xu3FmSNHnyZC1fvlzTp09Xv379Um2TmJio9u3ba8iQIfrpp590/vz5NPcfHx+v+Ph46/O4uDinxg8AAADAjsRi2bJl6arXrFmzdB88ISFBW7duVf/+/a1lLi4uatSokTZv3pxmu6FDh8rf319dunTRTz/9dMdjjBgxQkOGDEl3TAAAAADsl+7EIj3zGOy9Qd7p06eVmJiogIAAm/KAgADt2bMn1TabNm3StGnTtGPHjnQdo3///oqIiLA+j4uLU1BQULpjBAAAAHB36U4skpKSMjKOdLl48aJefPFFTZ06VXny5ElXGw8PD3l4eGRwZAAAAMDDze45Fs6UJ08eubq6KjY21qY8NjZWgYGBKeofPHhQUVFRatq0qbUsOeHJli2b9u7dq6JFi2Zs0AAAAABSsHu5WWdyd3dXaGio1q5day1LSkrS2rVrVaNGjRT1S5UqpZ07d2rHjh3WR7NmzdSgQQPt2LGDIU4AAABAJsnUHgtJioiIUMeOHVWlShVVq1ZNkZGRunz5snWVqA4dOqhAgQIaMWKEPD09VbZsWZv2uXLlkqQU5QAAAADun0xPLNq0aaNTp05p4MCBiomJUcWKFbVy5UrrhO7o6Gi5uGRqxwoAAACAu8j0xEKSevTooR49eqS6bcOGDXdsO3PmTOcHBAAAAMAu99QVcP78eX3xxRfq37+/zp49K0natm2bjh075tTgAAAAAGQNdvdY/PXXX2rUqJF8fX0VFRWlrl27ys/PT4sXL1Z0dLS++uqrjIgTAAAAwAPM7h6LiIgIderUSfv375enp6e1vHHjxtq4caNTgwMAAACQNdidWPz+++/q1q1bivICBQooJibGKUEBAAAAyFrsTiw8PDwUFxeXonzfvn3KmzevU4ICAAAAkLXYnVg0a9ZMQ4cO1fXr1yVJFotF0dHReuedd9SyZUunBwgAAADgwWd3YjFmzBhdunRJ/v7+unr1qurVq6dixYrJ29tbH374YUbECAAAAOABZ/eqUL6+vlqzZo02bdqkv/76S5cuXVLlypXVqFGjjIgPAAAAQBZwzzfIq127tmrXru3MWAAAAABkUXYnFp988kmq5RaLRZ6enipWrJjq1q0rV1dXh4MDAAAAkDXYnViMGzdOp06d0pUrV5Q7d25J0rlz55QjRw55eXnp5MmTKlKkiNavX6+goCCnBwwAAADgwWP35O3hw4eratWq2r9/v86cOaMzZ85o3759CgsL0/jx4xUdHa3AwED16dMnI+IFAAAA8ACyu8diwIABWrRokYoWLWotK1asmD7++GO1bNlShw4d0ujRo1l6FgAAAHiI2N1jceLECd24cSNF+Y0bN6x33s6fP78uXrzoeHQAAAAAsgS7E4sGDRqoW7du2r59u7Vs+/bteu2119SwYUNJ0s6dO1W4cGHnRQkAAADggWZ3YjFt2jT5+fkpNDRUHh4e8vDwUJUqVeTn56dp06ZJkry8vDRmzBinBwsAAADgwWT3HIvAwECtWbNGe/bs0b59+yRJJUuWVMmSJa11GjRo4LwIAQAAADzw7vkGeaVKlVKpUqWcGQvw/9q777Aorv5t4PeCsEtXojRFih1FUFREI1iI2CXqY481PiZBjSImEgtiASuisTdMjAW7JlHUEGyxxRZNFEQDYgEUFRERUDjvH77s4wrqLru47M/7c11zxT1zZube3dnNfpmZM0RERESko0pVWNy+fRt79+5FSkoK8vPzFeZFRERoJBgREREREekOlQuL2NhYdOvWDc7OzoiPj0eDBg2QnJwMIQQaN25cFhmJiIiIiKicU/ni7eDgYAQFBeHy5cuQyWTYsWMHbt26BR8fH/znP/8pi4xERERERFTOqVxYXL16FYMGDQIAVKhQAc+ePYOpqSmmT5+OOXPmaDwgERERERGVfyoXFiYmJvLrKmxtbXHjxg35vIyMDM0lIyIiIiIinaHyNRbNmzfH8ePHUa9ePXTq1Anjx4/H5cuXsXPnTjRv3rwsMhIRERERUTmncmERERGB7OxsAEBoaCiys7MRHR2NWrVqcUQoIiIiIqIPlEqFRUFBAW7fvo2GDRsCeHla1IoVK8okGBERERER6Q6VrrHQ19dH+/bt8ejRo7LKQ0REREREOkjli7cbNGiAf//9tyyyEBERERGRjlK5sJg5cyaCgoLwyy+/IDU1FVlZWQoTERERERF9eFS+eLtTp04AgG7dukEikcjbhRCQSCQoKCjQXDoiIiIiItIJKhcWcXFxZZGDiIiIiIh0mMqFhY+PT1nkICIiIiIiHabyNRYAcOzYMQwcOBAtWrTAnTt3AAAbNmzA8ePHNRqOiIiIiIh0g8qFxY4dO+Dn5wcjIyOcP38eeXl5AIDHjx8jLCxM4wGJiIiIiKj8K9WoUCtWrMDq1athYGAgb2/ZsiXOnz+v0XBERERERKQbVC4sEhIS4O3tXazdwsICmZmZmshEREREREQ6RuXCwsbGBtevXy/Wfvz4cTg7O5cqxNKlS+Ho6AiZTAZPT0+cOXPmjX1Xr16NVq1aoVKlSqhUqRJ8fX3f2p+IiIiIiMqeyoXFiBEj8PXXX+P06dOQSCS4e/cuNm7ciKCgIHz55ZcqB4iOjkZgYCBCQkJw/vx5uLm5wc/PD/fu3Sux/+HDh9GvXz/ExcXh5MmTsLe3R/v27eUXkRMRERER0fun8nCzEydORGFhIdq1a4ecnBx4e3tDKpUiKCgIo0ePVjlAREQERowYgaFDhwIAVqxYgV9//RXr1q3DxIkTi/XfuHGjwuM1a9Zgx44diI2NxaBBg4r1z8vLk19gDoB3ByciIiIiKgMqH7GQSCSYNGkSHj58iL///hunTp3C/fv3MWPGDJU3np+fj3PnzsHX1/d/gfT04Ovri5MnTyq1jpycHDx//hyWlpYlzg8PD4eFhYV8sre3VzknERERERG9ncqFxU8//YScnBwYGhrCxcUFzZo1g6mpaak2npGRgYKCAlhbWyu0W1tbIy0tTal1fPvtt7Czs1MoTl4VHByMx48fy6dbt26VKisREREREb2ZyoXFuHHjYGVlhf79+2Pfvn0oKCgoi1xKmT17NrZs2YJdu3ZBJpOV2EcqlcLc3FxhIiIiIiIizVK5sEhNTcWWLVsgkUjQu3dv2NraIiAgACdOnFB545UrV4a+vj7S09MV2tPT02FjY/PWZefPn4/Zs2fj4MGDaNiwocrbJiIiIiIizVG5sKhQoQK6dOmCjRs34t69e1i4cCGSk5PRpk0b1KhRQ6V1GRoawsPDA7GxsfK2wsJCxMbGwsvL643LzZ07FzNmzEBMTAyaNGmi6lMgIiIiIiINU3lUqFcZGxvDz88Pjx49ws2bN3H16lWV1xEYGIjBgwejSZMmaNasGSIjI/H06VP5KFGDBg1C1apVER4eDgCYM2cOpk6dik2bNsHR0VF+LYapqWmpr/UgIiIiIiL1lKqwyMnJwa5du7Bx40bExsbC3t4e/fr1w/bt21VeV58+fXD//n1MnToVaWlpcHd3R0xMjPyC7pSUFOjp/e/AyvLly5Gfn49evXoprCckJATTpk0rzdMhIiIiIiI1qVxY9O3bF7/88guMjY3Ru3dvTJky5a2nLSlj1KhRGDVqVInzDh8+rPA4OTlZrW0REREREZHmqVxY6OvrY+vWrfDz84O+vr7CvL///hsNGjTQWDgiIiIiItINKhcWr9/5+smTJ9i8eTPWrFmDc+fOaXX4WSIiIiIi0g6VR4UqcvToUQwePBi2traYP38+2rZti1OnTmkyGxERERER6QiVjlikpaVh/fr1WLt2LbKystC7d2/k5eVh9+7dcHFxKauMRERERERUzil9xKJr166oU6cOLl26hMjISNy9exfff/99WWYjIiIiIiIdofQRi/3792PMmDH48ssvUatWrbLMREREREREOkbpIxbHjx/HkydP4OHhAU9PTyxZsgQZGRllmY2IiIiIiHSE0oVF8+bNsXr1aqSmpmLkyJHYsmUL7OzsUFhYiEOHDuHJkydlmZOIiIiIiMoxlUeFMjExwbBhw3D8+HFcvnwZ48ePx+zZs2FlZYVu3bqVRUYiIiIiIirnSj3cLADUqVMHc+fOxe3bt7F582ZNZSIiIiIiIh2jVmFRRF9fH/7+/ti7d68mVkdERERERDpGI4UFERERERF92FhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2lhYEBERERGR2spFYbF06VI4OjpCJpPB09MTZ86ceWv/bdu2oW7dupDJZHB1dcW+ffveU1IiIiIiIiqJ1guL6OhoBAYGIiQkBOfPn4ebmxv8/Pxw7969EvufOHEC/fr1w/Dhw3HhwgX4+/vD398ff//993tOTkRERERERSRCCKHNAJ6enmjatCmWLFkCACgsLIS9vT1Gjx6NiRMnFuvfp08fPH36FL/88ou8rXnz5nB3d8eKFSuK9c/Ly0NeXp788ePHj1G9enXcunUL5ubmZfCMlGMRbqG1bZPueBz8WNsRAAARfz3QdgQq5wLdPtJ2BDnur/Qu3F9Jl2h7f83KyoK9vT0yMzNhYfGO369Ci/Ly8oS+vr7YtWuXQvugQYNEt27dSlzG3t5eLFy4UKFt6tSpomHDhiX2DwkJEQA4ceLEiRMnTpw4ceJUyunWrVvv/G1fAVqUkZGBgoICWFtbK7RbW1sjPj6+xGXS0tJK7J+WllZi/+DgYAQGBsofFxYW4uHDh/joo48gkUjUfAakKUXVsLaPJBEpg/sr6RLur6RLuL+WP0IIPHnyBHZ2du/sq9XC4n2QSqWQSqUKbRUrVtROGHonc3NzfpGQzuD+SrqE+yvpEu6v5cs7T4H6/7R68XblypWhr6+P9PR0hfb09HTY2NiUuIyNjY1K/YmIiIiIqOxptbAwNDSEh4cHYmNj5W2FhYWIjY2Fl5dXict4eXkp9AeAQ4cOvbE/ERERERGVPa2fChUYGIjBgwejSZMmaNasGSIjI/H06VMMHToUADBo0CBUrVoV4eHhAICvv/4aPj4+WLBgATp37owtW7bg7NmzWLVqlTafBqlJKpUiJCSk2GlrROUR91fSJdxfSZdwf9VtWh9uFgCWLFmCefPmIS0tDe7u7li8eDE8PT0BAK1bt4ajoyPWr18v779t2zZMnjwZycnJqFWrFubOnYtOnTppKT0REREREZWLwoKIiIiIiHSb1u+8TUREREREuo+FBRERERERqY2FBRERERERqY2FBRERERERqY2FBWnNtGnTIJFIFKa6detqOxYRAODo0aPo2rUr7OzsIJFIsHv3boX5QghMnToVtra2MDIygq+vLxITE7UTlj5479pfhwwZUuz7tkOHDtoJSx+88PBwNG3aFGZmZrCysoK/vz8SEhIU+uTm5iIgIAAfffQRTE1N0bNnz2I3SKbyh4UFaVX9+vWRmpoqn44fP67tSEQAgKdPn8LNzQ1Lly4tcf7cuXOxePFirFixAqdPn4aJiQn8/PyQm5v7npMSvXt/BYAOHToofN9u3rz5PSYk+p8jR44gICAAp06dwqFDh/D8+XO0b98eT58+lfcZN24cfv75Z2zbtg1HjhzB3bt30aNHDy2mJmVo/QZ59GGrUKECbGxstB2DqJiOHTuiY8eOJc4TQiAyMhKTJ09G9+7dAQA//vgjrK2tsXv3bvTt2/d9RiV66/5aRCqV8vuWyoWYmBiFx+vXr4eVlRXOnTsHb29vPH78GGvXrsWmTZvQtm1bAEBUVBTq1auHU6dOoXnz5tqITUrgEQvSqsTERNjZ2cHZ2RkDBgxASkqKtiMRvVNSUhLS0tLg6+srb7OwsICnpydOnjypxWREb3b48GFYWVmhTp06+PLLL/HgwQNtRyICADx+/BgAYGlpCQA4d+4cnj9/rvAdW7duXVSvXp3fseUcCwvSGk9PT6xfvx4xMTFYvnw5kpKS0KpVKzx58kTb0YjeKi0tDQBgbW2t0G5tbS2fR1SedOjQAT/++CNiY2MxZ84cHDlyBB07dkRBQYG2o9EHrrCwEGPHjkXLli3RoEEDAC+/Yw0NDVGxYkWFvvyOLf94KhRpzauH7Rs2bAhPT084ODhg69atGD58uBaTERH93/Lq6Xmurq5o2LAhatSogcOHD6Ndu3ZaTEYfuoCAAPz999+8xvL/CB6xoHKjYsWKqF27Nq5fv67tKERvVXSe+usjlKSnp/McdtIJzs7OqFy5Mr9vSatGjRqFX375BXFxcahWrZq83cbGBvn5+cjMzFToz+/Y8o+FBZUb2dnZuHHjBmxtbbUdheitnJycYGNjg9jYWHlbVlYWTp8+DS8vLy0mI1LO7du38eDBA37fklYIITBq1Cjs2rULv//+O5ycnBTme3h4wMDAQOE7NiEhASkpKfyOLed4KhRpTVBQELp27QoHBwfcvXsXISEh0NfXR79+/bQdjQjZ2dkKf81NSkrCxYsXYWlpierVq2Ps2LGYOXMmatWqBScnJ0yZMgV2dnbw9/fXXmj6YL1tf7W0tERoaCh69uwJGxsb3LhxA9988w1q1qwJPz8/LaamD1VAQAA2bdqEPXv2wMzMTH7dhIWFBYyMjGBhYYHhw4cjMDAQlpaWMDc3x+jRo+Hl5cURoco7QaQlffr0Eba2tsLQ0FBUrVpV9OnTR1y/fl3bsYiEEELExcUJAMWmwYMHCyGEKCwsFFOmTBHW1tZCKpWKdu3aiYSEBO2Gpg/W2/bXnJwc0b59e1GlShVhYGAgHBwcxIgRI0RaWpq2Y9MHqqR9FYCIioqS93n27Jn46quvRKVKlYSxsbH49NNPRWpqqvZCk1IkQgjx/ssZIiIiIiL6v4TXWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARESnp8OHDkEgkyMzMLBfrISIqT1hYEBGVgkQiees0bdo0jW+zdevWkEgk2LJli0J7ZGQkHB0dlc5rbm6Opk2bYs+ePRrPSMW1bt0aY8eOVWhr0aIFUlNTYWFhoZ1QRERlgIUFEVEppKamyqfIyEiYm5srtAUFBZXJdmUyGSZPnoznz5+rvGxUVBRSU1Nx9uxZtGzZEr169cLly5fLICW9i6GhIWxsbCCRSLQdhYhIY1hYEBGVgo2NjXyysLCARCKRP7ayskJERASqVasGqVQKd3d3xMTEyJdNTk6WH3lo0aIFZDIZGjRogCNHjrxzu/369UNmZiZWr16tcuaKFSvCxsYGtWvXxowZM/DixQvExcXJ59+6dQu9e/dGxYoVYWlpie7duyM5OVlhHevWrUP9+vUhlUpha2uLUaNGyeelpKSge/fuMDU1hbm5OXr37o309HT5/GnTpsHd3R3r1q1D9erVYWpqiq+++goFBQWYO3eu/LWbNWuWwjYlEglWrlyJLl26wNjYGPXq1cPJkydx/fp1tG7dGiYmJmjRogVu3LihsNyePXvQuHFjyGQyODs7IzQ0FC9evFBY75o1a/Dpp5/C2NgYtWrVwt69exXWsW/fPtSuXRtGRkZo06ZNsdfjwYMH6NevH6pWrQpjY2O4urpi8+bN8vlDhgzBkSNHsGjRIvkRo+Tk5BJPhdqxY4f8tXV0dMSCBQsUtuXo6IiwsDAMGzYMZmZmqF69OlatWiWfn5+fj1GjRsHW1hYymQwODg4IDw8HEdF7I4iISC1RUVHCwsJC/jgiIkKYm5uLzZs3i/j4ePHNN98IAwMDce3aNSGEEElJSQKAqFatmti+fbu4cuWK+Pzzz4WZmZnIyMh443Z8fHzE119/LSIiIoS1tbXIzs4WQgixcOFC4eDg8NaMAMSuXbuEEEI8f/5cLFy4UAAQy5cvF0IIkZ+fL+rVqyeGDRsmLl26JK5cuSL69+8v6tSpI/Ly8oQQQixbtkzIZDIRGRkpEhISxJkzZ8TChQuFEEIUFBQId3d38fHHH4uzZ8+KU6dOCQ8PD+Hj4yPPEBISIkxNTUWvXr3EP//8I/bu3SsMDQ2Fn5+fGD16tIiPjxfr1q0TAMSpU6cUsletWlVER0eLhIQE4e/vLxwdHUXbtm1FTEyMuHLlimjevLno0KGDfJmjR48Kc3NzsX79enHjxg1x8OBB4ejoKKZNm6aw3mrVqolNmzaJxMREMWbMGGFqaioePHgghBAiJSVFSKVSERgYKOLj48VPP/0krK2tBQDx6NEjIYQQt2/fFvPmzRMXLlwQN27cEIsXLxb6+vri9OnTQgghMjMzhZeXlxgxYoRITU0Vqamp4sWLFyIuLk5hPWfPnhV6enpi+vTpIiEhQURFRQkjIyMRFRUlz+vg4CAsLS3F0qVLRWJioggPDxd6enoiPj5eCCHEvHnzhL29vTh69KhITk4Wx44dE5s2bXrrfkFEpEksLIiI1PR6YWFnZydmzZql0Kdp06biq6++EkL8r7CYPXu2fP7z589FtWrVxJw5c964naLCIjc3Vzg4OIjp06cLIZQvLGQymTAxMRF6enoCgHB0dJT/iN6wYYOoU6eOKCwslC+Tl5cnjIyMxIEDB+TPa9KkSSWu/+DBg0JfX1+kpKTI2/755x8BQJw5c0YI8bKwMDY2FllZWfI+fn5+wtHRURQUFMjb6tSpI8LDwxWyT548Wf745MmTAoBYu3atvG3z5s1CJpPJH7dr106EhYUpZNywYYOwtbV943qzs7MFALF//34hhBDBwcHCxcVFYR3ffvutQkFQks6dO4vx48fLHxe9b696vbDo37+/+OSTTxT6TJgwQWH7Dg4OYuDAgfLHhYWFwsrKSl4cjh49WrRt21bhPSQiep94KhQRkQZlZWXh7t27aNmypUJ7y5YtcfXqVYU2Ly8v+b8rVKiAJk2aFOtTEqlUiunTp2P+/PnIyMhQOtvChQtx8eJF7N+/Hy4uLlizZg0sLS0BAH/99ReuX78OMzMzmJqawtTUFJaWlsjNzcWNGzdw79493L17F+3atStx3VevXoW9vT3s7e3lbS4uLqhYsaLCc3J0dISZmZn8sbW1NVxcXKCnp6fQdu/ePYX1N2zYUGE+ALi6uiq05ebmIisrS/58pk+fLn8upqamGDFiBFJTU5GTk1Piek1MTGBubi7f9tWrV+Hp6amQ49X3DAAKCgowY8YMuLq6wtLSEqampjhw4ABSUlJKfJ3e5OrVqyXuM4mJiSgoKCgxb9Hpd0V5hwwZgosXL6JOnToYM2YMDh48qFIGIiJ1VdB2ACIiUt3AgQMxf/58zJw5850jQhWxsbFBzZo1UbNmTURFRaFTp064cuUKrKyskJ2dDQ8PD2zcuLHYclWqVFH44a8OAwMDhccSiaTEtsLCwjcuV3TBc0ltRctlZ2cjNDQUPXr0KJZBJpO9Nc/r236befPmYdGiRYiMjISrqytMTEwwduxY5OfnK70OVbwtb+PGjZGUlIT9+/fjt99+Q+/eveHr64vt27eXSRYiotfxiAURkQaZm5vDzs4Of/zxh0L7H3/8ARcXF4W2U6dOyf/94sULnDt3DvXq1VNqO3p6eggPD8fy5cuLXVCsjGbNmsHDw0N+oXTjxo2RmJgIKysrefFRNFlYWMDMzAyOjo6IjY0tcX316tXDrVu3cOvWLXnblStXkJmZWex5vw+NGzdGQkJCsedSs2ZNpYukevXq4cyZMwptr75nwMv3tXv37hg4cCDc3Nzg7OyMa9euKfQxNDRUOOrwpm2VtM/Url0b+vr6SuUFXu5/ffr0werVqxEdHY0dO3bg4cOHSi9PRKQOFhZERBo2YcIEzJkzB9HR0UhISMDEiRNx8eJFfP311wr9li5dil27diE+Ph4BAQF49OgRhg0bpvR2OnfuDE9PT6xcubJUOceOHYuVK1fizp07GDBgACpXrozu3bvj2LFjSEpKwuHDhzFmzBjcvn0bwMtRnRYsWIDFixcjMTER58+fx/fffw8A8PX1haurKwYMGIDz58/jzJkzGDRoEHx8fNCkSZNS5VPH1KlT8eOPPyI0NBT//PMPrl69ii1btmDy5MlKr+OLL75AYmIiJkyYgISEBGzatAnr169X6FOrVi0cOnQIJ06cwNWrVzFy5EiFkbCAl6d/nT59GsnJycjIyCjxiMj48eMRGxuLGTNm4Nq1a/jhhx+wZMkSlYYtjoiIwObNmxEfH49r165h27ZtsLGxQcWKFZVeBxGROlhYEBFp2JgxYxAYGIjx48fD1dUVMTEx2Lt3L2rVqqXQb/bs2Zg9ezbc3Nxw/Phx7N27F5UrV1ZpW3PmzEFubm6pcnbo0AFOTk6YNWsWjI2NcfToUVSvXh09evRAvXr1MHz4cOTm5sLc3BwAMHjwYERGRmLZsmWoX78+unTpgsTERAAvT8nZs2cPKlWqBG9vb/j6+sLZ2RnR0dGlyqYuPz8//PLLLzh48CCaNm2K5s2bY+HChXBwcFB6HdWrV8eOHTuwe/duuLm5YcWKFQgLC1PoM3nyZDRu3Bh+fn5o3bo1bGxs4O/vr9AnKCgI+vr6cHFxQZUqVUq8/qJx48bYunUrtmzZggYNGmDq1KmYPn06hgwZonReMzMzzJ07F02aNEHTpk2RnJyMffv2aew0NiKid5EIIYS2QxARfUiSk5Ph5OSECxcuwN3dXdtxiIiINIJ/xiAiIiIiIrWxsCAiIiIiIrXxVCgiIiIiIlIbj1gQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQEREREZHaWFgQ0QdLIpFg2rRp8sfr16+HRCJBcnKy1jKVpLzmetXrr2VZmjdvHpydnaGvrw93d/f3sk1VtG7dGq1bt1ZoS09PR69evfDRRx9BIpEgMjISAJCYmIj27dvDwsICEokEu3fvfu956f1zdHTEkCFDtB2DSONYWBCpaNmyZZBIJPD09NR2lHLH0dERXbp0KdWy+/bte28/TDUpJycH06ZNw+HDh5Xqf/jwYUgkEvkklUphbW2N1q1bIywsDPfv3y/bwO/JiRMnMG3aNGRmZmp0vQcPHsQ333yDli1bIioqCmFhYRpd/+uGDBmi8H6ZmprC2dkZvXr1wo4dO1BYWKjUesaNG4cDBw4gODgYGzZsQIcOHQAAgwcPxuXLlzFr1ixs2LABTZo0Kcuno5awsDClCp/WrVsrvGZvmt7H593R0RESiQSjR48uNq/os7h9+/Y3Lh8REQGJRILffvvtjX1Wr14NiUSCvXv3aiQzkS6roO0ARLpm48aNcHR0xJkzZ3D9+nXUrFlT25H+T9i3bx+WLl2q1eLis88+Q9++fSGVSpVeJicnB6GhoQBQ7K/UbzNmzBg0bdoUBQUFuH//Pk6cOIGQkBBERERg69ataNu2rVq53rdnz56hQoX//S/lxIkTCA0NxZAhQ1CxYkWNbef333+Hnp4e1q5dC0NDQ42t922kUinWrFkD4OXzvHnzJn7++Wf06tULrVu3xp49e2Bubi7vf/DgwRJzd+/eHUFBQfK2Z8+e4eTJk5g0aRJGjRpV9k9ETWFhYejVqxf8/f3f2m/SpEn4/PPP5Y///PNPLF68GN999x3q1asnb2/YsGFZRS1m9erVCA4Ohp2dnUrL9e3bFxMmTMCmTZvg6+tbYp9Nmzbho48+QseOHTURlUinsbAgUkFSUhJOnDiBnTt3YuTIkdi4cSNCQkLea4bCwkLk5+dDJpO91+3qIiEEcnNzYWRkpFR/fX196Ovrl3Gql1q1aoVevXoptP31119o3749evbsiStXrsDW1va953pVTk4OjI2Nler7vvbHe/fuwcjISGNFhTL7SIUKFTBw4ECFtpkzZ2L27NkIDg7GiBEjEB0dLZ9XUrZ79+4VK7CKjk5psvDKzc2FoaEh9PS0d0LCJ598ovBYJpNh8eLF+OSTT1QqvjWlfv36SEhIwOzZs7F48WKVlrWzs0ObNm2wc+dOLF++vFhxf+fOHRw9ehT//e9/YWBgoMnYRDqJp0IRqWDjxo2oVKkSOnfujF69emHjxo3yec+fP4elpSWGDh1abLmsrCzIZDKFv1bm5eUhJCQENWvWhFQqhb29Pb755hvk5eUpLCuRSDBq1Chs3LgR9evXh1QqRUxMDABg/vz5aNGiBT766CMYGRnBw8OjxMP6z549w5gxY1C5cmWYmZmhW7duuHPnTomnI9y5cwfDhg2DtbU1pFIp6tevj3Xr1pXq9UpOToZEIsH8+fOxatUq1KhRA1KpFE2bNsWff/4p7zdkyBAsXbpU/nyLpiKFhYWIjIxE/fr1IZPJYG1tjZEjR+LRo0cK2ys6FevAgQNo0qQJjIyMsHLlSqXzlnQtw9mzZ+Hn54fKlSvDyMgITk5OGDZsmPz5ValSBQAQGhqq9ikebm5uiIyMRGZmJpYsWfLGXF26dIGzs3OJ6/Dy8ip2Os1PP/0EDw8PGBkZwdLSEn379sWtW7cU+rRu3RoNGjTAuXPn4O3tDWNjY3z33XfvfA2KvPq8p02bhgkTJgAAnJyc5K9LcnIyfHx84ObmVmL2OnXqwM/P742vj0QiQVRUFJ4+fSpf5/r16wEAL168wIwZM+T7mKOjI7777rtinyd195FXTZw4Ee3bt8e2bdtw7do1efur11gUvXdCCCxdulRhH3FwcAAATJgwARKJBI6OjvJ1KPM5LDqVZ8uWLZg8eTKqVq0KY2NjZGVlAQBOnz6NDh06wMLCAsbGxvDx8cEff/yhsI5p06ZBIpHg+vXr8qNLFhYWGDp0KHJychRe+6dPn+KHH36QPwd1rxFYtmyZ/DvNzs4OAQEBxU6de3W/bNGihXz/W7FihdLbcXR0xKBBg7B69WrcvXtX5ZwDBw7E48eP8euvvxabt2XLFhQWFmLAgAEAlP9Ofl3R+/C6N11ftX//frRq1QomJiYwMzND586d8c8//yj0SUtLw9ChQ1GtWjVIpVLY2tqie/fu5fpaLdJ9LCyIVLBx40b06NEDhoaG6NevHxITE+U/kA0MDPDpp59i9+7dyM/PV1hu9+7dyMvLQ9++fQG8/KHcrVs3zJ8/H127dsX3338Pf39/LFy4EH369Cm23d9//x3jxo1Dnz59sGjRIvkPkEWLFqFRo0aYPn06wsLCUKFCBfznP/8p9j/AIUOG4Pvvv0enTp0wZ84cGBkZoXPnzsW2k56ejubNm+O3337DqFGjsGjRItSsWRPDhw+XX2xaGps2bcK8efMwcuRIzJw5E8nJyejRoweeP38OABg5cqT8r5wbNmyQT0VGjhyJCRMmoGXLlli0aBGGDh2KjRs3ws/PT76OIgkJCejXrx8++eQTLFq0SK2Le+/du4f27dsjOTkZEydOxPfff48BAwbg1KlTAIAqVapg+fLlAIBPP/1UnrtHjx6l3mavXr1gZGRU4uk0Rfr06YOkpCSF4gwAbt68iVOnTsn3MwCYNWsWBg0ahFq1aiEiIgJjx45FbGwsvL29i/2Ie/DgATp27Ah3d3dERkaiTZs273wNStKjRw/069cPALBw4UL561KlShV89tlnuHTpEv7++2+FZf78809cu3at2JGBV23YsAGtWrWCVCqVr9Pb2xsA8Pnnn2Pq1Klo3LgxFi5cCB8fH4SHhyu8FkU0uY989tlnEELg0KFDJc739vaW78uffPKJwj6ycOFCAEC/fv2wYcMG+WdM1c/hjBkz8OuvvyIoKAhhYWEwNDTE77//Dm9vb2RlZSEkJARhYWHIzMxE27ZtcebMmWLr6N27N548eYLw8HD07t0b69evl5/iB7x87aVSKVq1aiV/DiNHjiz16zZt2jQEBATAzs4OCxYsQM+ePbFy5Uq0b9++2Gf60aNH6NSpEzw8PDB37lxUq1YNX375pUp/8Jg0aRJevHiB2bNnq5y1R48ekMlk2LRpU7F5mzZtgoODA1q2bAlA+e9kdWzYsAGdO3eGqakp5syZgylTpuDKlSv4+OOPFYqGnj17YteuXRg6dCiWLVuGMWPG4MmTJ0hJSdFYFqJiBBEp5ezZswKAOHTokBBCiMLCQlGtWjXx9ddfy/scOHBAABA///yzwrKdOnUSzs7O8scbNmwQenp64tixYwr9VqxYIQCIP/74Q94GQOjp6Yl//vmnWKacnByFx/n5+aJBgwaibdu28rZz584JAGLs2LEKfYcMGSIAiJCQEHnb8OHDha2trcjIyFDo27dvX2FhYVFse69zcHAQnTt3lj9OSkoSAMRHH30kHj58KG/fs2dPsdcpICBAlPSVdOzYMQFAbNy4UaE9JiamWLuDg4MAIGJiYt6as8jrzz8qKkoAEElJSUIIIXbt2iUAiD///PON67h//36x9bxNXFycACC2bdv2xj5ubm6iUqVKb8z1+PFjIZVKxfjx4xWWmzt3rpBIJOLmzZtCCCGSk5OFvr6+mDVrlkK/y5cviwoVKii0+/j4CABixYoVCn2VeQ2EKP5azps3TyFzkczMTCGTycS3336r0D5mzBhhYmIisrOz37qdwYMHCxMTE4W2ixcvCgDi888/V2gPCgoSAMTvv/8ub1N1Hylpe6+6cOGCACDGjRsnb/Px8RE+Pj4K/QCIgIAAhbaiz8e8efMU2pX9HBbtS87OzgqfzcLCQlGrVi3h5+cnCgsL5e05OTnCyclJfPLJJ/K2kJAQAUAMGzZMYVuffvqp+OijjxTaTExMxODBg9/4WrzJtm3bBAARFxcnhBDi3r17wtDQULRv314UFBTI+y1ZskQAEOvWrZO3Fe2XCxYskLfl5eUJd3d3YWVlJfLz89+67Ve/k4YOHSpkMpm4e/euEEK5z2KR//znP0Imk4nHjx/L2+Lj4wUAERwcLG9T5ju5KNerr2XR+/C61z/7T548ERUrVhQjRoxQ6JeWliYsLCzk7Y8ePSpx3yIqazxiQaSkjRs3wtraGm3atAHw8tSAPn36YMuWLSgoKAAAtG3bFpUrV1Y43/rRo0c4dOiQwpGIbdu2oV69eqhbty4yMjLkU9EFu3FxcQrb9vHxgYuLS7FMr54X/ujRIzx+/BitWrXC+fPn5e1Fp0199dVXCsu+PkqKEAI7duxA165dIYRQyOXn54fHjx8rrFcVffr0QaVKleSPW7VqBQD4999/37nstm3bYGFhgU8++UQhk4eHB0xNTYu9Vk5OTm89nUYVRee+//LLL8X+ilqWTE1N8eTJkzfONzc3R8eOHbF161YIIeTt0dHRaN68OapXrw4A2LlzJwoLC9G7d2+F187Gxga1atUq9tpJpdJip/Jp+jWwsLBA9+7dsXnzZnn2goICREdHw9/fHyYmJiqvc9++fQCAwMBAhfbx48cDQLG/FmtyHzE1NQWAt75fqijN53Dw4MEK3wUXL15EYmIi+vfvjwcPHsiXf/r0Kdq1a4ejR48WG83qiy++UHjcqlUrPHjwQH5alSb99ttvyM/Px9ixYxWuBRkxYgTMzc2LvV8VKlRQODpiaGiIkSNH4t69ezh37pzS2508eXKpj1oMHDgQubm52Llzp7yt6AhG0WlQgHLfyeo4dOgQMjMz0a9fP4V9Q19fH56envLPdNF1SIcPHy52yihRWWJhQaSEgoICbNmyBW3atEFSUhKuX7+O69evw9PTE+np6YiNjQXw8n+APXv2xJ49e+Tndu/cuRPPnz9XKCwSExPxzz//oEqVKgpT7dq1Abw8BedVTk5OJeb65Zdf0Lx5c8hkMlhaWspPzXn8+LG8z82bN6Gnp1dsHa+PZnX//n1kZmZi1apVxXIV/dh8PZeyin7oFikqMpT5H15iYiIeP34MKyurYrmys7Pf+Vo9fPgQaWlp8unV1+ZdfHx80LNnT4SGhqJy5cro3r07oqKiip23r2nZ2dkwMzN7a58+ffrg1q1bOHnyJADgxo0bOHfuXLH9TAiBWrVqFXvtrl69Wuy1q1q1arELj8viNRg0aBBSUlJw7NgxAC9/aKanp+Ozzz4r1fqK9vHX92kbGxtUrFgRN2/eVGh/0+epNLKzswHgne+XskrzOXz9+SQmJgJ4WXC8vo41a9YgLy+v2OdAnc+oqorejzp16ii0GxoawtnZudj7ZWdnV6zgLPquVOV6AWdnZ3z22WdYtWoVUlNTVcrcsWNHWFpaKpwOtXnzZri5uaF+/fryNmW+k9VR9N62bdu22Ht78OBB+b4hlUoxZ84c7N+/H9bW1vD29sbcuXORlpamkRxEb8JRoYiU8PvvvyM1NRVbtmzBli1bis3fuHEj2rdvD+Dl8IQrV67E/v374e/vj61bt6Ju3boKF6wWFhbC1dUVERERJW7P3t5e4XFJI9YcO3YM3bp1g7e3N5YtWwZbW1sYGBggKiqqxHOB36XoL5gDBw7E4MGDS+xT2uEh3zSi0at/bX9bLisrK4UL5V9VdPF0kddfqx49euDIkSPyx4MHD5Zf8PsuRWPcnzp1Cj///DMOHDiAYcOGYcGCBTh16pT8r9Wa9Pz5c1y7dg0NGjR4a7+uXbvC2NgYW7duRYsWLbB161bo6enhP//5j7xPYWEhJBIJ9u/fX+J78Hr+kvazsngN/Pz8YG1tjZ9++gne3t746aefYGNj88bhPJVV0sWvJVF2lDBlFF0roqlhp0vzOXz9+RStY968eW+8fuT1902dz6gumTRpEjZs2IA5c+a8c9jcVxkYGKB3795YvXo10tPTkZKSgsTERMydO1feR53v5Dftu0VHw4sUvbcbNmyAjY1Nsf6vDvk8duxYdO3aFbt378aBAwcwZcoUhIeH4/fff0ejRo2Ufu5EqmBhQaSEjRs3wsrKSj5y0at27tyJXbt2YcWKFTAyMoK3tzdsbW0RHR2Njz/+GL///jsmTZqksEyNGjXw119/oV27dkr/GHrdjh07IJPJcODAAYUhEKOiohT6OTg4oLCwEElJSahVq5a8/fr16wr9qlSpAjMzMxQUFKj9A6803vQ61KhRA7/99htatmxZqh+ECxYsUPirq6rj2ANA8+bN0bx5c8yaNQubNm3CgAEDsGXLFnz++eelfv/eZPv27Xj27Nk7T9UxMTFBly5dsG3bNkRERCA6OhqtWrVSeH41atSAEAJOTk7yv/CW1tteg5K87XXR19dH//79sX79esyZMwe7d+/GiBEjSj2kbtE+npiYqHCfhPT0dGRmZspHXyoLGzZsgEQiKTbEamlp4nNYo0YNAC9PmdPkZ1lT+3rR+5GQkKAwull+fj6SkpKKZb579y6ePn2qcNSiaBSuV0fSUkaNGjUwcOBArFy5UuWbnA4YMAArVqxAdHQ0kpKSIJFI5IMUAMp/J5ek6AhRZmamwvDDrx+9KXpvrayslHpva9SogfHjx2P8+PFITEyEu7s7FixYgJ9++umdyxKVBk+FInqHZ8+eYefOnejSpQt69epVbBo1ahSePHkiv+uqnp4eevXqhZ9//hkbNmzAixcvio301Lt3b9y5cwerV68ucXtPnz59Zy59fX1IJBKFv2glJycXuzNu0Q/UZcuWKbR///33xdbXs2dP7Nixo9iIPQDK/I7QRT8aXh+pqHfv3igoKMCMGTOKLfPixYt33tnZw8MDvr6+8qmka1Xe5NGjR8X+Ylv0F+CiU4GK7vOgiTtM//XXXxg7diwqVaqEgICAd/bv06cP7t69izVr1uCvv/4qtp/16NED+vr6CA0NLfY8hBB48ODBO7ehzGtQkje9n0U+++wzPHr0CCNHjkR2dvZbR4N6l06dOgFAsRGTio4IljQCmibMnj0bBw8eRJ8+fRSKdnVo4nPo4eGBGjVqYP78+fJTtVRdR0lMTEw0sp/7+vrC0NAQixcvVti31q5di8ePHxd7v168eKEwJHB+fj5WrlyJKlWqwMPDQ+XtT548Gc+fP1c42qCMli1bwtHRET/99BOio6Ph4+ODatWqyecr+51ckqKC4ejRo/K2ouF9X+Xn5wdzc3OEhYWVeM1T0Xubk5OD3NzcYtswMzMr81M56cPGIxZE77B37148efIE3bp1K3F+8+bNUaVKFWzcuFH+w65Pnz74/vvvERISAldXV4W/ogIvf1Rt3boVX3zxBeLi4tCyZUsUFBQgPj4eW7dulY+x/zadO3dGREQEOnTogP79++PevXtYunQpatasiUuXLsn7eXh4oGfPnoiMjMSDBw/QvHlzHDlyRP4Xv1f/Cjl79mzExcXB09MTI0aMgIuLCx4+fIjz58/jt99+w8OHD0v1Giqj6AfCmDFj4OfnB319ffTt2xc+Pj4YOXIkwsPDcfHiRbRv3x4GBgZITEzEtm3bsGjRomI3mtOUH374AcuWLcOnn36KGjVq4MmTJ1i9ejXMzc3lP2aNjIzg4uKC6Oho1K5dG5aWlmjQoME7T2U6duwYcnNzUVBQgAcPHuCPP/7A3r17YWFhgV27dpV4msPrOnXqBDMzMwQFBcl/kL6qRo0amDlzJoKDg5GcnAx/f3+YmZkhKSkJu3btwn//+1+Fe6uU9jUoSdH7OWnSJPTt2xcGBgbo2rWrvOBo1KgRGjRoIB/IoHHjxu98vm/i5uaGwYMHY9WqVcjMzISPjw/OnDmDH374Af7+/vIBF0rrxYsX8r/w5ubm4ubNm9i7dy8uXbqENm3aYNWqVWqt/3Xqfg719PSwZs0adOzYEfXr18fQoUNRtWpV3LlzB3FxcTA3N8fPP/+sci4PDw/89ttviIiIgJ2dHZycnFT+qz/w8qhMcHAwQkND0aFDB3Tr1g0JCQlYtmwZmjZtWqzItLOzw5w5c5CcnIzatWsjOjoaFy9exKpVq0p1U7qioxav/2h/F4lEgv79+yMsLAwAMH36dIX5yn4nl6R9+/aoXr06hg8fjgkTJkBfXx/r1q1DlSpVFIaHNTc3x/Lly/HZZ5+hcePG6Nu3r7zPr7/+ipYtW2LJkiW4du0a2rVrh969e8PFxQUVKlTArl27kJ6eXuIQzEQao4WRqIh0SteuXYVMJhNPnz59Y58hQ4YIAwMD+fCQhYWFwt7eXgAQM2fOLHGZ/Px8MWfOHFG/fn0hlUpFpUqVhIeHhwgNDVUY0hAlDFNZZO3ataJWrVpCKpWKunXriqioqBKHLXz69KkICAgQlpaWwtTUVPj7+4uEhAQBQMyePVuhb3p6uggICBD29vbCwMBA2NjYiHbt2olVq1a987V603CzJQ15iNeGJ33x4oUYPXq0qFKlipBIJMWew6pVq4SHh4cwMjISZmZmwtXVVXzzzTfyoSNL2v67vJ7h9aEdz58/L/r16yeqV68upFKpsLKyEl26dBFnz55VWM+JEyeEh4eHMDQ0fOfQs0VDXBZNBgYGokqVKsLb21vMmjVL3Lt3r9gyr+d61YABAwQA4evr+8Zt7tixQ3z88cfCxMREmJiYiLp164qAgACRkJAg7+Pj4yPq169fbFllX4OSnveMGTNE1apVhZ6eXon5586dKwCIsLCwN2Z/3ZuGf33+/LkIDQ0VTk5OwsDAQNjb24vg4GCRm5ur0E/VfWTw4MEK75exsbFwdHQUPXv2FNu3b1cYLrWIusPNCqHc5/Bdw6VeuHBB9OjRQ3z00UdCKpUKBwcH0bt3bxEbGyvvU/R9cf/+fYVlS9rn4uPjhbe3tzAyMhIAlB569vXhZossWbJE1K1bVxgYGAhra2vx5ZdfikePHin0Kdovz549K7y8vIRMJhMODg5iyZIlSm37Te93YmKi0NfXV3q42SL//POPACCkUmmxrEIo/538+nCzQrwcGtzT01MYGhqK6tWri4iIiDd+9uPi4oSfn5+wsLAQMplM1KhRQwwZMkT+uczIyBABAQGibt26wsTERFhYWAhPT0+xdetWpZ8rUWlIhPg/dmUWESnl4sWLaNSoEX766SeF4RKJ3pdFixZh3LhxSE5OLjYqERHw8s7bGRkZJZ4WRkTlD6+xIPoAPHv2rFhbZGQk9PT05HcuJnqfhBBYu3YtfHx8WFQQEf0fwWssiD4Ac+fOxblz59CmTRtUqFAB+/fvx/79+/Hf//632NC2RGXp6dOn2Lt3L+Li4nD58mXs2bNH25GIiEhDWFgQfQBatGiBQ4cOYcaMGcjOzkb16tUxbdq0YsPgEpW1+/fvo3///qhYsSK+++67Nw6KQEREuofXWBARERERkdp4jQUREREREantgzsVqrCwEHfv3oWZmZnG75hLRERERPR/iRACT548gZ2dHfT03n5M4oMrLO7evcuLVYmIiIiIVHDr1i2Fu82X5IMrLMzMzAC8fHHMzc21nIaIiIiIqPzKysqCvb29/Df023xwhUXR6U/m5uYsLIiIiIiIlKDMJQS8eJuIiIiIiNTGwoKIiIiIiNTGwoKIiIiIiNTGwoKIiIiIiNTGwoKIiIiIiNSm1cLi6NGj6Nq1K+zs7CCRSLB79+53LnP48GE0btwYUqkUNWvWxPr168s8JxERERERvZ1WC4unT5/Czc0NS5cuVap/UlISOnfujDZt2uDixYsYO3YsPv/8cxw4cKCMkxIRERER0dto9T4WHTt2RMeOHZXuv2LFCjg5OWHBggUAgHr16uH48eNYuHAh/Pz8yiomERERERG9g05dY3Hy5En4+voqtPn5+eHkyZNvXCYvLw9ZWVkKExERERERaZZO3Xk7LS0N1tbWCm3W1tbIysrCs2fPYGRkVGyZ8PBwhIaGvq+ISpOEvvvuhUQiRGg7AgBg9oUMbUegcm5io8rajkBERFqmU4VFaQQHByMwMFD+OCsrC/b29lpMRERERPQS/3BD76JLf7jRqcLCxsYG6enpCm3p6ekwNzcv8WgFAEilUkil0vcRj4iIygH+UKN30aUfakS6RKeusfDy8kJsbKxC26FDh+Dl5aWlREREREREBGi5sMjOzsbFixdx8eJFAC+Hk7148SJSUlIAvDyNadCgQfL+X3zxBf7991988803iI+Px7Jly7B161aMGzdOG/GJiIiIiOj/02phcfbsWTRq1AiNGjUCAAQGBqJRo0aYOnUqACA1NVVeZACAk5MTfv31Vxw6dAhubm5YsGAB1qxZw6FmiYiIiIi0TKvXWLRu3RpCvHnUm5Luqt26dWtcuHChDFMREREREZGqdOoaCyIiIiIiKp9YWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpYWBARERERkdpULiz+/fffsshBREREREQ6TOXCombNmmjTpg1++ukn5ObmlkUmIiIiIiLSMSoXFufPn0fDhg0RGBgIGxsbjBw5EmfOnCmLbEREREREpCNULizc3d2xaNEi3L17F+vWrUNqaio+/vhjNGjQABEREbh//35Z5CQiIiIionKs1BdvV6hQAT169MC2bdswZ84cXL9+HUFBQbC3t8egQYOQmpqqyZxERERERFSOlbqwOHv2LL766ivY2toiIiICQUFBuHHjBg4dOoS7d++ie/fumsxJRERERETlWAVVF4iIiEBUVBQSEhLQqVMn/Pjjj+jUqRP09F7WKE5OTli/fj0cHR01nZWIiIiIiMoplQuL5cuXY9iwYRgyZAhsbW1L7GNlZYW1a9eqHY6IiIiIiHSDyoXFoUOHUL16dfkRiiJCCNy6dQvVq1eHoaEhBg8erLGQRERERERUvql8jUWNGjWQkZFRrP3hw4dwcnLSSCgiIiIiItItKhcWQogS27OzsyGTydQOREREREREukfpU6ECAwMBABKJBFOnToWxsbF8XkFBAU6fPg13d3eNByQiIiIiovJP6cLiwoULAF4esbh8+TIMDQ3l8wwNDeHm5oagoCDNJyQiIiIionJP6cIiLi4OADB06FAsWrQI5ubmZRaKiIiIiIh0i8qjQkVFRZVFDiIiIiIi0mFKFRY9evTA+vXrYW5ujh49ery1786dOzUSjIiIiIiIdIdShYWFhQUkEon830RERERERK9SqrB49fQnngpFRERERESvU/k+Fs+ePUNOTo788c2bNxEZGYmDBw9qNBgREREREekOlQuL7t2748cffwQAZGZmolmzZliwYAG6d++O5cuXazwgERERERGVfyoXFufPn0erVq0AANu3b4eNjQ1u3ryJH3/8EYsXL9Z4QCIiIiIiKv9ULixycnJgZmYGADh48CB69OgBPT09NG/eHDdv3tR4QCIiIiIiKv9ULixq1qyJ3bt349atWzhw4ADat28PALh3716pbpq3dOlSODo6QiaTwdPTE2fOnHlr/8jISNSpUwdGRkawt7fHuHHjkJubq/J2iYiIiIhIc1QuLKZOnYqgoCA4OjrC09MTXl5eAF4evWjUqJFK64qOjkZgYCBCQkJw/vx5uLm5wc/PD/fu3Sux/6ZNmzBx4kSEhITg6tWrWLt2LaKjo/Hdd9+p+jSIiIiIiEiDVC4sevXqhZSUFJw9exYxMTHy9nbt2mHhwoUqrSsiIgIjRozA0KFD4eLighUrVsDY2Bjr1q0rsf+JEyfQsmVL9O/fH46Ojmjfvj369ev3zqMcRERERERUtlQqLJ4/f44KFSogIyMDjRo1gp7e/xZv1qwZ6tatq/S68vPzce7cOfj6+v4vjJ4efH19cfLkyRKXadGiBc6dOycvJP7991/s27cPnTp1euN28vLykJWVpTAREREREZFmKXWDvCIGBgaoXr06CgoK1N5wRkYGCgoKYG1trdBubW2N+Pj4Epfp378/MjIy8PHHH0MIgRcvXuCLL75466lQ4eHhCA0NVTsvERERERG9mcqnQk2aNAnfffcdHj58WBZ53urw4cMICwvDsmXLcP78eezcuRO//vorZsyY8cZlgoOD8fjxY/l069at95iYiIiIiOjDoNIRCwBYsmQJrl+/Djs7Ozg4OMDExERh/vnz55VaT+XKlaGvr4/09HSF9vT0dNjY2JS4zJQpU/DZZ5/h888/BwC4urri6dOn+O9//4tJkyYpnJpVRCqVQiqVKpWJiIiIiIhKR+XCwt/fXyMbNjQ0hIeHB2JjY+XrLCwsRGxsLEaNGlXiMjk5OcWKB319fQCAEEIjuYiIiIiISHUqFxYhISEa23hgYCAGDx6MJk2aoFmzZoiMjMTTp08xdOhQAMCgQYNQtWpVhIeHAwC6du2KiIgINGrUCJ6enrh+/TqmTJmCrl27ygsMIiIiIiJ6/1QuLAAgMzMT27dvx40bNzBhwgRYWlri/PnzsLa2RtWqVZVeT58+fXD//n1MnToVaWlpcHd3R0xMjPyC7pSUFIUjFJMnT4ZEIsHkyZNx584dVKlSBV27dsWsWbNK8zSIiIiIiEhDVC4sLl26BF9fX1hYWCA5ORkjRoyApaUldu7ciZSUFPz4448qrW/UqFFvPPXp8OHDimErVEBISIhGj5oQEREREZH6VB4VKjAwEEOGDEFiYiJkMpm8vVOnTjh69KhGwxERERERkW5QubD4888/MXLkyGLtVatWRVpamkZCERERERGRblG5sJBKpSXevfratWuoUqWKRkIREREREZFuUbmw6NatG6ZPn47nz58DACQSCVJSUvDtt9+iZ8+eGg9IRERERETln8qFxYIFC5CdnQ0rKys8e/YMPj4+qFmzJszMzDg6ExERERHRB0rlUaEsLCxw6NAhHD9+HJcuXUJ2djYaN24MX1/fsshHREREREQ6QOXC4tatW7C3t8fHH3+Mjz/+uCwyERERERGRjlH5VChHR0f4+Phg9erVePToUVlkIiIiIiIiHaNyYXH27Fk0a9YM06dPh62tLfz9/bF9+3bk5eWVRT4iIiIiItIBKhcWjRo1wrx585CSkoL9+/ejSpUq+O9//wtra2sMGzasLDISEREREVE5p3JhUUQikaBNmzZYvXo1fvvtNzg5OeGHH37QZDYiIiIiItIRpS4sbt++jblz58Ld3R3NmjWDqakpli5dqslsRERERESkI1QeFWrlypXYtGkT/vjjD9StWxcDBgzAnj174ODgUBb5iIiIiIhIB6hcWMycORP9+vXD4sWL4ebmVhaZiIiIiIhIx6hcWKSkpEAikZRFFiIiIiIi0lFKFRaXLl1CgwYNoKenh8uXL7+1b8OGDTUSjIiIiIiIdIdShYW7uzvS0tJgZWUFd3d3SCQSCCHk84seSyQSFBQUlFlYIiIiIiIqn5QqLJKSklClShX5v4mIiIiIiF6lVGHx6ohPHP2JiIiIiIhep/LF27///jt27tyJ5ORkSCQSODk5oVevXvD29i6LfEREREREpANUukHeF198AV9fX2zevBkPHjzA/fv3sXHjRrRp0wajR48uq4xERERERFTOKV1Y7Nq1C1FRUVi3bh0yMjJw8uRJnDp1Cvfv38fq1auxatUq7N27tyyzEhERERFROaV0YREVFYXAwEAMGTJE4T4Wenp6GDZsGMaOHYu1a9eWSUgiIiIiIirflC4szp8/j08//fSN83v06IFz585pJBQREREREekWpQuLjIwMVKtW7Y3zq1WrhgcPHmgkFBERERER6RalC4v8/HwYGBi8cX6FChWQn5+vkVBERERERKRbVBpudsqUKTA2Ni5xXk5OjkYCERERERGR7lG6sPD29kZCQsI7+xARERER0YdH6cLi8OHDZRiDiIiIiIh0mUo3yCMiIiIiIioJCwsiIiIiIlIbCwsiIiIiIlIbCwsiIiIiIlKbyoVFSkoKhBDF2oUQSElJ0UgoIiIiIiLSLSoXFk5OTrh//36x9ocPH8LJyUkjoYiIiIiISLeoXFgIISCRSIq1Z2dnQyaTaSQUERERERHpFqXvYxEYGAgAkEgkxe7AXVBQgNOnT8Pd3V3jAYmIiIiIqPxT+ojFhQsXcOHCBQghcPnyZfnjCxcuID4+Hm5ubli/fr3KAZYuXQpHR0fIZDJ4enrizJkzb+2fmZmJgIAA2NraQiqVonbt2ti3b5/K2yUiIiIiIs1R+ohFXFwcAGDo0KFYtGgRzM3N1d54dHQ0AgMDsWLFCnh6eiIyMhJ+fn5ISEiAlZVVsf75+fn45JNPYGVlhe3bt6Nq1aq4efMmKlasqHYWIiIiIiIqPaULiyJRUVEKj7OysvD777+jbt26qFu3rkrrioiIwIgRIzB06FAAwIoVK/Drr79i3bp1mDhxYrH+69atw8OHD3HixAkYGBgAABwdHd+6jby8POTl5SnkJSIiIiIizVL54u3evXtjyZIlAIBnz56hSZMm6N27N1xdXbFjxw6l15Ofn49z587B19f3f2H09ODr64uTJ0+WuMzevXvh5eWFgIAAWFtbo0GDBggLC0NBQcEbtxMeHg4LCwv5ZG9vr3RGIiIiIiJSjsqFxdGjR9GqVSsAwK5duyCEQGZmJhYvXoyZM2cqvZ6MjAwUFBTA2tpaod3a2hppaWklLvPvv/9i+/btKCgowL59+zBlyhQsWLDgrdsNDg7G48eP5dOtW7eUzkhERERERMpR+VSox48fw9LSEgAQExODnj17wtjYGJ07d8aECRM0HvBVhYWFsLKywqpVq6Cvrw8PDw/cuXMH8+bNQ0hISInLSKVSSKXSMs1FRERERPShU7mwsLe3x8mTJ2FpaYmYmBhs2bIFAPDo0SOV7mNRuXJl6OvrIz09XaE9PT0dNjY2JS5ja2sLAwMD6Ovry9vq1auHtLQ05Ofnw9DQUNWnQ0REREREGqDyqVBjx47FgAEDUK1aNdjZ2aF169YAXp4i5erqqvR6DA0N4eHhgdjYWHlbYWEhYmNj4eXlVeIyLVu2xPXr11FYWChvu3btGmxtbVlUEBERERFpkcqFxVdffYWTJ09i3bp1OH78OPT0Xq7C2dlZpWssgJc33Vu9ejV++OEHXL16FV9++SWePn0qHyVq0KBBCA4Olvf/8ssv8fDhQ3z99de4du0afv31V4SFhSEgIEDVp0FERERERBqk8qlQANCkSRM0adJEoa1z584qr6dPnz64f/8+pk6dirS0NLi7uyMmJkZ+QXdKSoq8cAFenoZ14MABjBs3Dg0bNkTVqlXx9ddf49tvvy3N0yAiIiIiIg1RqrAIDAzEjBkzYGJigsDAwLf2jYiIUCnAqFGjMGrUqBLnHT58uFibl5cXTp06pdI2iIiIiIiobClVWFy4cAHPnz+X//tNJBKJZlIREREREZFOUaqwiIuLK/HfREREREREQCku3iYiIiIiInqdUkcsevToofQKd+7cWeowRERERESkm5QqLCwsLMo6BxERERER6TClCouoqKiyzkFERERERDpMrWssZs+ejczMTA1FISIiIiIiXaVWYREWFoaHDx9qKgsREREREekotQoLIYSmchARERERkQ5TqbAQQiAlJQW5ublllYeIiIiIiHSQyoVFzZo1cevWLQDAlStX4ODgUCbBiIiIiIhId6hUWOjp6aFWrVp48OABAMDe3h76+vplEoyIiIiIiHSHytdYzJ49GxMmTMDff/9dFnmIiIiIiEgHKXUfi1cNGjQIOTk5cHNzg6GhIYyMjBTmc5QoIiIiIqIPj8qFRWRkZBnEICIiIiIiXaZyYTF48OCyyEFERERERDqsVPexuHHjBiZPnox+/frh3r17AID9+/fjn3/+0Wg4IiIiIiLSDSoXFkeOHIGrqytOnz6NnTt3Ijs7GwDw119/ISQkROMBiYiIiIio/FO5sJg4cSJmzpyJQ4cOwdDQUN7etm1bnDp1SqPhiIiIiIhIN6hcWFy+fBmffvppsXYrKytkZGRoJBQREREREekWlQuLihUrIjU1tVj7hQsXULVqVY2EIiIiIiIi3aJyYdG3b198++23SEtLg0QiQWFhIf744w8EBQVh0KBBZZGRiIiIiIjKOZULi7CwMNStWxf29vbIzs6Gi4sLvL290aJFC0yePLksMhIRERERUTmn8n0sDA0NsXr1akydOhWXL19GdnY2GjVqhFq1apVFPiIiIiIi0gEqH7GYPn06cnJyYG9vj06dOqF3796oVasWnj17hunTp5dFRiIiIiIiKudULixCQ0Pl9654VU5ODkJDQzUSioiIiIiIdIvKhYUQAhKJpFj7X3/9BUtLS42EIiIiIiIi3aL0NRaVKlWCRCKBRCJB7dq1FYqLgoICZGdn44svviiTkEREREREVL4pXVhERkZCCIFhw4YhNDQUFhYW8nmGhoZwdHSEl5dXmYQkIiIiIqLyTenCYvDgwQAAJycntGjRAgYGBmUWioiIiIiIdIvKw836+PigsLAQ165dw71791BYWKgw39vbW2PhiIiIiIhIN6hcWJw6dQr9+/fHzZs3IYRQmCeRSFBQUKCxcEREREREpBtULiy++OILNGnSBL/++itsbW1LHCGKiIiIiIg+LCoXFomJidi+fTtq1qxZFnmIiIiIiEgHqXwfC09PT1y/fr0sshARERERkY5S+YjF6NGjMX78eKSlpcHV1bXY6FANGzbUWDgiIiIiItINKh+x6NmzJ65evYphw4ahadOmcHd3R6NGjeT/LY2lS5fC0dERMpkMnp6eOHPmjFLLbdmyBRKJBP7+/qXaLhERERERaYbKRyySkpI0GiA6OhqBgYFYsWIFPD09ERkZCT8/PyQkJMDKyuqNyyUnJyMoKAitWrXSaB4iIiIiIlKdyoWFg4ODRgNERERgxIgRGDp0KABgxYoV+PXXX7Fu3TpMnDixxGUKCgowYMAAhIaG4tixY8jMzHzj+vPy8pCXlyd/nJWVpdH8RERERESkQmGxd+9epfp169ZN6Y3n5+fj3LlzCA4Olrfp6enB19cXJ0+efONy06dPh5WVFYYPH45jx469dRvh4eEIDQ1VOhMREREREalO6cJCmesYVL1BXkZGBgoKCmBtba3Qbm1tjfj4+BKXOX78ONauXYuLFy8qtY3g4GAEBgbKH2dlZcHe3l7pjERERERE9G5KFxaFhYVlmUMpT548wWeffYbVq1ejcuXKSi0jlUohlUrLOBkRERER0YdN5WssNKly5crQ19dHenq6Qnt6ejpsbGyK9b9x4waSk5PRtWtXeVtRwVOhQgUkJCSgRo0aZRuaiIiIiIiKUXm4WU0yNDSEh4cHYmNj5W2FhYWIjY2Fl5dXsf5169bF5cuXcfHiRfnUrVs3tGnTBhcvXuQpTkREREREWqLVIxYAEBgYiMGDB6NJkyZo1qwZIiMj8fTpU/koUYMGDULVqlURHh4OmUyGBg0aKCxfsWJFACjWTkRERERE74/WC4s+ffrg/v37mDp1KtLS0uDu7o6YmBj5Bd0pKSnQ09PqgRUiIiIiInoHrRcWADBq1CiMGjWqxHmHDx9+67Lr16/XfCAiIiIiIlJJqQ4FZGZmYs2aNQgODsbDhw8BAOfPn8edO3c0Go6IiIiIiHSDykcsLl26BF9fX1hYWCA5ORkjRoyApaUldu7ciZSUFPz4449lkZOIiIiIiMoxlY9YBAYGYsiQIUhMTIRMJpO3d+rUCUePHtVoOCIiIiIi0g0qFxZ//vknRo4cWay9atWqSEtL00goIiIiIiLSLSoXFlKpFFlZWcXar127hipVqmgkFBERERER6RaVC4tu3bph+vTpeP78OQBAIpEgJSUF3377LXr27KnxgEREREREVP6pXFgsWLAA2dnZsLKywrNnz+Dj44OaNWvCzMwMs2bNKouMRERERERUzqk8KpSFhQUOHTqE48eP49KlS8jOzkbjxo3h6+tbFvmIiIiIiEgHlPoGeR9//DE+/vhjTWYhIiIiIiIdpXJhsXjx4hLbJRIJZDIZatasCW9vb+jr66sdjoiIiIiIdIPKhcXChQtx//595OTkoFKlSgCAR48ewdjYGKamprh37x6cnZ0RFxcHe3t7jQcmIiIiIqLyR+WLt8PCwtC0aVMkJibiwYMHePDgAa5duwZPT08sWrQIKSkpsLGxwbhx48oiLxERERERlUMqH7GYPHkyduzYgRo1asjbatasifnz56Nnz574999/MXfuXA49S0RERET0AVH5iEVqaipevHhRrP3FixfyO2/b2dnhyZMn6qcjIiIiIiKdoHJh0aZNG4wcORIXLlyQt124cAFffvkl2rZtCwC4fPkynJycNJeSiIiIiIjKNZULi7Vr18LS0hIeHh6QSqWQSqVo0qQJLC0tsXbtWgCAqakpFixYoPGwRERERERUPql8jYWNjQ0OHTqE+Ph4XLt2DQBQp04d1KlTR96nTZs2mktIRERERETlXqlvkFe3bl3UrVtXk1mIiIiIiEhHlaqwuH37Nvbu3YuUlBTk5+crzIuIiNBIMCIiIiIi0h0qFxaxsbHo1q0bnJ2dER8fjwYNGiA5ORlCCDRu3LgsMhIRERERUTmn8sXbwcHBCAoKwuXLlyGTybBjxw7cunULPj4++M9//lMWGYmIiIiIqJxTubC4evUqBg0aBACoUKECnj17BlNTU0yfPh1z5szReEAiIiIiIir/VC4sTExM5NdV2Nra4saNG/J5GRkZmktGREREREQ6Q+VrLJo3b47jx4+jXr166NSpE8aPH4/Lly9j586daN68eVlkJCIiIiKick7lwiIiIgLZ2dkAgNDQUGRnZyM6Ohq1atXiiFBERERERB8olQqLgoIC3L59Gw0bNgTw8rSoFStWlEkwIiIiIiLSHSpdY6Gvr4/27dvj0aNHZZWHiIiIiIh0kMoXbzdo0AD//vtvWWQhIiIiIiIdpXJhMXPmTAQFBeGXX35BamoqsrKyFCYiIiIiIvrwqHzxdqdOnQAA3bp1g0QikbcLISCRSFBQUKC5dEREREREpBNULizi4uLKIgcREREREekwlQsLHx+fsshBREREREQ6TOVrLADg2LFjGDhwIFq0aIE7d+4AADZs2IDjx49rNBwREREREekGlQuLHTt2wM/PD0ZGRjh//jzy8vIAAI8fP0ZYWJjGAxIRERERUflXqlGhVqxYgdWrV8PAwEDe3rJlS5w/f16j4YiIiIiISDeoXFgkJCTA29u7WLuFhQUyMzM1kYmIiIiIiHSMyoWFjY0Nrl+/Xqz9+PHjcHZ2LlWIpUuXwtHRETKZDJ6enjhz5swb+65evRqtWrVCpUqVUKlSJfj6+r61PxERERERlT2VC4sRI0bg66+/xunTpyGRSHD37l1s3LgRQUFB+PLLL1UOEB0djcDAQISEhOD8+fNwc3ODn58f7t27V2L/w4cPo1+/foiLi8PJkydhb2+P9u3byy8iJyIiIiKi90/l4WYnTpyIwsJCtGvXDjk5OfD29oZUKkVQUBBGjx6tcoCIiAiMGDECQ4cOBQCsWLECv/76K9atW4eJEycW679x40aFx2vWrMGOHTsQGxuLQYMGqbx9IiIiIiJSn8qFhUQiwaRJkzBhwgRcv34d2dnZcHFxgampqcobz8/Px7lz5xAcHCxv09PTg6+vL06ePKnUOnJycvD8+XNYWlqWOD8vL08+chUAZGVlqZyTiIiIiIjeTuVToX766Sfk5OTA0NAQLi4uaNasWamKCgDIyMhAQUEBrK2tFdqtra2Rlpam1Dq+/fZb2NnZwdfXt8T54eHhsLCwkE/29valykpERERERG+mcmExbtw4WFlZoX///ti3bx8KCgrKIpdSZs+ejS1btmDXrl2QyWQl9gkODsbjx4/l061bt95zSiIiIiKi//tULixSU1OxZcsWSCQS9O7dG7a2tggICMCJEydU3njlypWhr6+P9PR0hfb09HTY2Ni8ddn58+dj9uzZOHjwIBo2bPjGflKpFObm5goTERERERFplsqFRYUKFdClSxds3LgR9+7dw8KFC5GcnIw2bdqgRo0aKq3L0NAQHh4eiI2NlbcVFhYiNjYWXl5eb1xu7ty5mDFjBmJiYtCkSRNVnwIREREREWmYyhdvv8rY2Bh+fn549OgRbt68iatXr6q8jsDAQAwePBhNmjRBs2bNEBkZiadPn8pHiRo0aBCqVq2K8PBwAMCcOXMwdepUbNq0CY6OjvJrMUxNTUt9rQcREREREamnVIVFTk4Odu3ahY0bNyI2Nhb29vbo168ftm/frvK6+vTpg/v372Pq1KlIS0uDu7s7YmJi5Bd0p6SkQE/vfwdWli9fjvz8fPTq1UthPSEhIZg2bVppng4REREREalJ5cKib9+++OWXX2BsbIzevXtjypQpbz1tSRmjRo3CqFGjSpx3+PBhhcfJyclqbYuIiIiIiDRP5cJCX18fW7duhZ+fH/T19RXm/f3332jQoIHGwhERERERkW5QubB4/c7XT548webNm7FmzRqcO3dOq8PPEhERERGRdqg8KlSRo0ePYvDgwbC1tcX8+fPRtm1bnDp1SpPZiIiIiIhIR6h0xCItLQ3r16/H2rVrkZWVhd69eyMvLw+7d++Gi4tLWWUkIiIiIqJyTukjFl27dkWdOnVw6dIlREZG4u7du/j+++/LMhsREREREekIpY9Y7N+/H2PGjMGXX36JWrVqlWUmIiIiIiLSMUofsTh+/DiePHkCDw8PeHp6YsmSJcjIyCjLbEREREREpCOULiyaN2+O1atXIzU1FSNHjsSWLVtgZ2eHwsJCHDp0CE+ePCnLnEREREREVI6pPCqUiYkJhg0bhuPHj+Py5csYP348Zs+eDSsrK3Tr1q0sMhIRERERUTlX6uFmAaBOnTqYO3cubt++jc2bN2sqExERERER6Ri1Cosi+vr68Pf3x969ezWxOiIiIiIi0jEaKSyIiIiIiOjDxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUxsKCiIiIiIjUVi4Ki6VLl8LR0REymQyenp44c+bMW/tv27YNdevWhUwmg6urK/bt2/eekhIRERERUUm0XlhER0cjMDAQISEhOH/+PNzc3ODn54d79+6V2P/EiRPo168fhg8fjgsXLsDf3x/+/v74+++/33NyIiIiIiIqovXCIiIiAiNGjMDQoUPh4uKCFStWwNjYGOvWrSux/6JFi9ChQwdMmDAB9erVw4wZM9C4cWMsWbLkPScnIiIiIqIiFbS58fz8fJw7dw7BwcHyNj09Pfj6+uLkyZMlLnPy5EkEBgYqtPn5+WH37t0l9s/Ly0NeXp788ePHjwEAWVlZaqZXU652N0+6Qev76f+Xm/1E2xGonMvKMtR2BDnur/Qu3F9Jl2h7fy36LSKEeGdfrRYWGRkZKCgogLW1tUK7tbU14uPjS1wmLS2txP5paWkl9g8PD0doaGixdnt7+1KmJnp/LGZbaDsCkVKKf8sSlV/cX0mXlJf99cmTJ7CwePvvEq0WFu9DcHCwwhGOwsJCPHz4EB999BEkEokWk9GrsrKyYG9vj1u3bsHc3FzbcYjeivsr6RLur6RLuL+WP0IIPHnyBHZ2du/sq9XConLlytDX10d6erpCe3p6OmxsbEpcxsbGRqX+UqkUUqlUoa1ixYqlD01lytzcnF8kpDO4v5Iu4f5KuoT7a/nyriMVRbR68bahoSE8PDwQGxsrbyssLERsbCy8vLxKXMbLy0uhPwAcOnTojf2JiIiIiKjsaf1UqMDAQAwePBhNmjRBs2bNEBkZiadPn2Lo0KEAgEGDBqFq1aoIDw8HAHz99dfw8fHBggUL0LlzZ2zZsgVnz57FqlWrtPk0iIiIiIg+aFovLPr06YP79+9j6tSpSEtLg7u7O2JiYuQXaKekpEBP738HVlq0aIFNmzZh8uTJ+O6771CrVi3s3r0bDRo00NZTIA2QSqUICQkpdtoaUXnE/ZV0CfdX0iXcX3WbRCgzdhQREREREdFbaP0GeUREREREpPtYWBARERERkdpYWBARERERkdpYWBARERERkdpYWJDWTJs2DRKJRGGqW7eutmMRAQCOHj2Krl27ws7ODhKJBLt371aYL4TA1KlTYWtrCyMjI/j6+iIxMVE7YemD9679dciQIcW+bzt06KCdsPTBCw8PR9OmTWFmZgYrKyv4+/sjISFBoU9ubi4CAgLw0UcfwdTUFD179ix2g2Qqf1hYkFbVr18fqamp8un48ePajkQEAHj69Cnc3NywdOnSEufPnTsXixcvxooVK3D69GmYmJjAz88Pubm57zkp0bv3VwDo0KGDwvft5s2b32NCov85cuQIAgICcOrUKRw6dAjPnz9H+/bt8fTpU3mfcePG4eeff8a2bdtw5MgR3L17Fz169NBialKG1u9jQR+2ChUqwMbGRtsxiIrp2LEjOnbsWOI8IQQiIyMxefJkdO/eHQDw448/wtraGrt370bfvn3fZ1Sit+6vRaRSKb9vqVyIiYlReLx+/XpYWVnh3Llz8Pb2xuPHj7F27Vps2rQJbdu2BQBERUWhXr16OHXqFJo3b66N2KQEHrEgrUpMTISdnR2cnZ0xYMAApKSkaDsS0TslJSUhLS0Nvr6+8jYLCwt4enri5MmTWkxG9GaHDx+GlZUV6tSpgy+//BIPHjzQdiQiAMDjx48BAJaWlgCAc+fO4fnz5wrfsXXr1kX16tX5HVvOsbAgrfH09MT69esRExOD5cuXIykpCa1atcKTJ0+0HY3ordLS0gAA1tbWCu3W1tbyeUTlSYcOHfDjjz8iNjYWc+bMwZEjR9CxY0cUFBRoOxp94AoLCzF27Fi0bNkSDRo0APDyO9bQ0BAVK1ZU6Mvv2PKPp0KR1rx62L5hw4bw9PSEg4MDtm7diuHDh2sxGRHR/y2vnp7n6uqKhg0bokaNGjh8+DDatWunxWT0oQsICMDff//Nayz/j+ARCyo3KlasiNq1a+P69evajkL0VkXnqb8+Qkl6ejrPYSed4OzsjMqVK/P7lrRq1KhR+OWXXxAXF4dq1arJ221sbJCfn4/MzEyF/vyOLf9YWFC5kZ2djRs3bsDW1lbbUYjeysnJCTY2NoiNjZW3ZWVl4fTp0/Dy8tJiMiLl3L59Gw8ePOD3LWmFEAKjRo3Crl278Pvvv8PJyUlhvoeHBwwMDBS+YxMSEpCSksLv2HKOp0KR1gQFBaFr165wcHDA3bt3ERISAn19ffTr10/b0YiQnZ2t8NfcpKQkXLx4EZaWlqhevTrGjh2LmTNnolatWnBycsKUKVNgZ2cHf39/7YWmD9bb9ldLS0uEhoaiZ8+esLGxwY0bN/DNN9+gZs2a8PPz02Jq+lAFBARg06ZN2LNnD8zMzOTXTVhYWMDIyAgWFhYYPnw4AgMDYWlpCXNzc4wePRpeXl4cEaq8E0Ra0qdPH2FraysMDQ1F1apVRZ8+fcT169e1HYtICCFEXFycAFBsGjx4sBBCiMLCQjFlyhRhbW0tpFKpaNeunUhISNBuaPpgvW1/zcnJEe3btxdVqlQRBgYGwsHBQYwYMUKkpaVpOzZ9oEraVwGIqKgoeZ9nz56Jr776SlSqVEkYGxuLTz/9VKSmpmovNClFIoQQ77+cISIiIiKi/0t4jQUREREREamNhQUREREREamNhQUREREREamNhQUREREREamNhQUREREREamNhQUREREREamNhQUREREREamNhQUREREREamNhQUREZGSDh8+DIlEgszMzHKxHiKi8oSFBRFRKUgkkrdO06ZN0/g2W7duDYlEgi1btii0R0ZGwtHRUem85ubmaNq0Kfbs2aPxjFRc69atMXbsWIW2Fi1aIDU1FRYWFtoJRURUBlhYEBGVQmpqqnyKjIyEubm5QltQUFCZbFcmk2Hy5Ml4/vy5ystGRUUhNTUVZ8+eRcuWLdGrVy9cvny5DFLSuxgaGsLGxgYSiUTbUYiINIaFBRFRKdjY2MgnCwsLSCQS+WMrKytERESgWrVqkEqlcHd3R0xMjHzZ5ORk+ZGHFi1aQCaToUGDBjhy5Mg7t9uvXz9kZmZi9erVKmeuWLEibGxsULt2bcyYMQMvXrxAXFycfP6tW7fQu3dvVKxYEZaWlujevTuSk5MV1rFu3TrUr18fUqkUtra2GDVqlHxeSkoKunfvDlNTU5ibm6N3795IT0+Xz582bRrc3d2xbt06VK9eHaampvjqq69QUFCAuXPnyl+7WbNmKWxTIpFg5cqV6NKlC4yNjVGvXj2cPHkS169fR+vWrWFiYoIWLVrgxo0bCsvt2bMHjRs3hkwmg7OzM0JDQ/HixQuF9a5ZswaffvopjI2NUatWLezdu1dhHfv27UPt2rVhZGSENm3aFHs9Hjx4gH79+qFq1aowNjaGq6srNm/eLJ8/ZMgQHDlyBIsWLZIfMUpOTi7xVKgdO3bIX1tHR0csWLBAYVuOjo4ICwvDsGHDYGZmhurVq2PVqlXy+fn5+Rg1ahRsbW0hk8ng4OCA8PBwEBG9N4KIiNQSFRUlLCws5I8jIiKEubm52Lx5s4iPjxfffPONMDAwENeuXRNCCJGUlCQAiGrVqont27eLK1euiM8//1yYmZmJjIyMN27Hx8dHfP311yIiIkJYW1uL7OxsIYQQCxcuFA4ODm/NCEDs2rVLCCHE8+fPxcKFCwUAsXz5ciGEEPn5+aJevXpi2LBh4tKlS+LKlSuif//+ok6dOiIvL08IIcSyZcuETCYTkZGRIiEhQZw5c0YsXLhQCCFEQUGBcHd3Fx9//LE4e/asOHXqlPDw8BA+Pj7yDCEhIcLU1FT06tVL/PPPP2Lv3r3C0NBQ+Pn5idGjR4v4+Hixbt06AUCcOnVKIXvVqlVFdHS0SEhIEP7+/sLR0VG0bdtWxMTEiCtXrojmzZuLDh06yJc5evSoMDc3F+vXrxc3btwQBw8eFI6OjmLatGkK661WrZrYtGmTSExMFGPGjBGmpqbiwYMHQgghUlJShFQqFYGBgSI+Pl789NNPwtraWgAQjx49EkIIcfv2bTFv3jxx4cIFcePGDbF48WKhr68vTp8+LYQQIjMzU3h5eYkRI0aI1NRUkZqaKl68eCHi4uIU1nP27Fmhp6cnpk+fLhISEkRUVJQwMjISUVFR8rwODg7C0tJSLF26VCQmJorw8HChp6cn4uPjhRBCzJs3T9jb24ujR4+K5ORkcezYMbFp06a37hdERJrEwoKISE2vFxZ2dnZi1qxZCn2aNm0qvvrqKyHE/wqL2bNny+c/f/5cVKtWTcyZM+eN2ykqLHJzc4WDg4OYPn26EEL5wkImkwkTExOhp6cnAAhHR0f5j+gNGzaIOnXqiMLCQvkyeXl5wsjISBw4cED+vCZNmlTi+g8ePCj09fVFSkqKvO2ff/4RAMSZM2eEEC8LC2NjY5GVlSXv4+fnJxwdHUVBQYG8rU6dOiI8PFwh++TJk+WPT548KQCItWvXyts2b94sZDKZ/HG7du1EWFiYQsYNGzYIW1vbN643OztbABD79+8XQggRHBwsXFxcFNbx7bffKhQEJencubMYP368/HHR+/aq1wuL/v37i08++UShz4QJExS27+DgIAYOHCh/XFhYKKysrOTF4ejRo0Xbtm0V3kMioveJp0IREWlQVlYW7t69i5YtWyq0t2zZElevXlVo8/Lykv+7QoUKaNKkSbE+JZFKpZg+fTrmz5+PjIwMpbMtXLgQFy9exP79++Hi4oI1a9bA0tISAPDXX3/h+vXrMDMzg6mpKUxNTWFpaYnc3FzcuHED9+7dw927d9GuXbsS13316lXY29vD3t5e3ubi4oKKFSsqPCdHR0eYmZnJH1tbW8PFxQV6enoKbffu3VNYf8OGDRXmA4Crq6tCW25uLrKysuTPZ/r06fLnYmpqihEjRiA1NRU5OTklrtfExATm5ubybV+9ehWenp4KOV59zwCgoKAAM2bMgKurKywtLWFqaooDBw4gJSWlxNfpTa5evVriPpOYmIiCgoIS8xadfleUd8iQIbh48SLq1KmDMWPG4ODBgyplICJSVwVtByAiItUNHDgQ8+fPx8yZM985IlQRGxsb1KxZEzVr1kRUVBQ6deqEK1euwMrKCtnZ2fDw8MDGjRuLLVelShWFH/7qMDAwUHgskUhKbCssLHzjckUXPJfUVrRcdnY2QkND0aNHj2IZZDLZW/O8vu23mTdvHhYtWoTIyEi4urrCxMQEY8eORX5+vtLrUMXb8jZu3BhJSUnYv38/fvvtN/Tu3Ru+vr7Yvn17mWQhInodj1gQEWmQubk57Ozs8Mcffyi0//HHH3BxcVFoO3XqlPzfL168wLlz51CvXj2ltqOnp4fw8HAsX7682AXFymjWrBk8PDzkF0o3btwYiYmJsLKykhcfRZOFhQXMzMzg6OiI2NjYEtdXr1493Lp1C7du3ZK3XblyBZmZmcWe9/vQuHFjJCQkFHsuNWvWVLpIqlevHs6cOaPQ9up7Brx8X7t3746BAwfCzc0Nzs7OuHbtmkIfQ0NDhaMOb9pWSftM7dq1oa+vr1Re4OX+16dPH6xevRrR0dHYsWMHHj58qPTyRETqYGFBRKRhEyZMwJw5cxAdHY2EhARMnDgRFy9exNdff63Qb+nSpdi1axfi4+MREBCAR48eYdiwYUpvp3PnzvD09MTKlStLlXPs2LFYuXIl7ty5gwEDBqBy5cro3r07jh07hqSkJBw+fBhjxozB7du3Abwc1WnBggVYvHgxEhMTcf78eXz//fcAAF9fX7i6umLAgAE4f/48zpw5g0GDBsHHxwdNmjQpVT51TJ06FT/++CNCQ0Pxzz//4OrVq9iyZQsmT56s9Dq++OILJCYmYsKECUhISMCmTZuwfv16hT61atXCoUOHcOLECVy9ehUjR45UGAkLeHn61+nTp5GcnIyMjIwSj4iMHz8esbGxmDFjBq5du4YffvgBS5YsUWnY4oiICGzevBnx8fG4du0atm3bBhsbG1SsWFHpdRARqYOFBRGRho0ZMwaBgYEYP348XF1dERMTg71796JWrVoK/WbPno3Zs2fDzc0Nx48fx969e1G5cmWVtjVnzhzk5uaWKmeHDh3g5OSEWbNmwdjYGEePHkX16tXRo0cP1KtXD8OHD0dubi7Mzc0BAIMHD0ZkZCSWLVuG+vXro0uXLkhMTATw8pScPXv2oFKlSvD29oavry+cnZ0RHR1dqmzq8vPzwy+//IKDBw+iadOmaN68ORYuXAgHBwel11G9enXs2LEDu3fvhpubG1asWIGwsDCFPpMnT0bjxo3h5+eH1q1bw8bGBv7+/gp9goKCoK+vDxcXF1SpUqXE6y8aN26MrVu3YsuWLWjQoAGmTp2K6dOnY8iQIUrnNTMzw9y5c9GkSRM0bdoUycnJ2Ldvn8ZOYyMieheJEEJoOwQR0YckOTkZTk5OuHDhAtzd3bUdh4iISCP4ZwwiIiIiIlIbCwsiIiIiIlIbT4UiIiIiIiK18YgFERERERGpjYUFERERERGpjYUFERERERGpjYUFERERERGpjYUFERERERGpjYUFERERERGpjYUFERERERGpjYUFERERERGp7f8BZ4TZOvQptygAAAAASUVORK5CYII=\n"},"metadata":{}}]}]}