diff --git a/.github/workflows/automated-deployment-dev.yml b/.github/workflows/automated-deployment-dev.yml index ad5458b..5cd3a93 100644 --- a/.github/workflows/automated-deployment-dev.yml +++ b/.github/workflows/automated-deployment-dev.yml @@ -29,5 +29,5 @@ jobs: docker push ${{ secrets.CADDY_ECR_ENDPOINT }}/${{ secrets.CADDY_ECR_REPO_ID_DEV }}:${{ github.sha }} - name: Deploy infrastructure run: | - aws cloudformation deploy --template-file infra/template.yaml --stack-name "caddy-dev" --capabilities CAPABILITY_NAMED_IAM --parameter-overrides StageName=dev MessageTableName=${{ vars.MESSAGES_TABLE_NAME_DEV }} ResponsesTableName=${{ vars.RESPONSES_TABLE_NAME_DEV }} UserTableName=${{ vars.USERS_TABLE_NAME_DEV }} OfficesTableName=${{ vars.OFFICES_TABLE_NAME_DEV }} EvaluationTableName=${{ vars.EVALUATION_TABLE_NAME_DEV }} OpensearchUrl=${{ secrets.OPENSEARCH_DEV_URL }} OpensearchIndex=${{ secrets.OPENSEARCH_INDEX }} CaddyServiceAccountSecretArn=${{ secrets.CADDY_SA_ARN_DEV }} CaddySupervisorServiceAccountSecretArn=${{ secrets.CADDY_SUPERVISOR_SA_ARN_DEV }} CaddyImage=${{ secrets.CADDY_ECR_ENDPOINT }}/${{ secrets.CADDY_ECR_REPO_ID_DEV }}:${{ github.sha }} CaddySupervisorGoogleCloudProject=${{ secrets.CADDY_SUPERVISOR_GOOGLE_CLOUD_PROJECT_DEV }} CaddyGoogleCloudProject=${{ secrets.CADDY_GOOGLE_CLOUD_PROJECT_DEV }} LLM=${{ vars.LLM }} DomainName=${{ secrets.CERT_DOMAIN }} + aws cloudformation deploy --template-file infra/template.yaml --stack-name "caddy-dev" --capabilities CAPABILITY_NAMED_IAM --parameter-overrides StageName=dev MessageTableName=${{ vars.MESSAGES_TABLE_NAME_DEV }} RoutesTableName=${{ vars.ROUTES_TABLE_NAME_DEV }} PromptsTableName=${{ vars.PROMPTS_TABLE_NAME_DEV }} ResponsesTableName=${{ vars.RESPONSES_TABLE_NAME_DEV }} UserTableName=${{ vars.USERS_TABLE_NAME_DEV }} OfficesTableName=${{ vars.OFFICES_TABLE_NAME_DEV }} EvaluationTableName=${{ vars.EVALUATION_TABLE_NAME_DEV }} OpensearchUrl=${{ secrets.OPENSEARCH_DEV_URL }} OpensearchIndex=${{ secrets.OPENSEARCH_INDEX }} CaddyServiceAccountSecretArn=${{ secrets.CADDY_SA_ARN_DEV }} CaddySupervisorServiceAccountSecretArn=${{ secrets.CADDY_SUPERVISOR_SA_ARN_DEV }} CaddyImage=${{ secrets.CADDY_ECR_ENDPOINT }}/${{ secrets.CADDY_ECR_REPO_ID_DEV }}:${{ github.sha }} CaddySupervisorGoogleCloudProject=${{ secrets.CADDY_SUPERVISOR_GOOGLE_CLOUD_PROJECT_DEV }} CaddyGoogleCloudProject=${{ secrets.CADDY_GOOGLE_CLOUD_PROJECT_DEV }} LLM=${{ vars.LLM }} DomainName=${{ secrets.CERT_DOMAIN }} MicrosoftAppIdSecretArn=${{ secrets.MICROSOFT_APP_ID_SECRET_ARN }} MicrosoftAppPasswordSecretArn=${{ secrets.MICROSOFT_APP_PASSWORD_SECRET_ARN }} aws cloudformation deploy --template-file infra/opensearch.yaml --stack-name "caddy-opensearch-dev" --region eu-west-3 --capabilities CAPABILITY_NAMED_IAM --parameter-overrides StageName=dev CaddyRoleArn=${{ secrets.CADDY_ROLE_ARN_DEV }} diff --git a/.github/workflows/automated-deployment-prod.yml b/.github/workflows/automated-deployment-prod.yml index 664c576..924851e 100644 --- a/.github/workflows/automated-deployment-prod.yml +++ b/.github/workflows/automated-deployment-prod.yml @@ -29,5 +29,5 @@ jobs: docker push ${{ secrets.CADDY_ECR_ENDPOINT }}/${{ secrets.CADDY_ECR_REPO_ID_PROD }}:${{ github.sha }} - name: Deploy infrastructure run: | - aws cloudformation deploy --template-file infra/template.yaml --stack-name "caddy-prod" --capabilities CAPABILITY_NAMED_IAM --parameter-overrides StageName=prod MessageTableName=${{ vars.MESSAGES_TABLE_NAME_PROD }} ResponsesTableName=${{ vars.RESPONSES_TABLE_NAME_PROD }} UserTableName=${{ vars.USERS_TABLE_NAME_PROD }} OfficesTableName=${{ vars.OFFICES_TABLE_NAME_PROD }} EvaluationTableName=${{ vars.EVALUATION_TABLE_NAME_PROD }} OpensearchUrl=${{ secrets.OPENSEARCH_PROD_URL }} OpensearchIndex=${{ secrets.OPENSEARCH_INDEX }} CaddyServiceAccountSecretArn=${{ secrets.CADDY_SA_ARN_PROD }} CaddySupervisorServiceAccountSecretArn=${{ secrets.CADDY_SUPERVISOR_SA_ARN_PROD }} CaddyImage=${{ secrets.CADDY_ECR_ENDPOINT }}/${{ secrets.CADDY_ECR_REPO_ID_PROD }}:${{ github.sha }} CaddySupervisorGoogleCloudProject=${{ secrets.CADDY_SUPERVISOR_GOOGLE_CLOUD_PROJECT_PROD }} CaddyGoogleCloudProject=${{ secrets.CADDY_GOOGLE_CLOUD_PROJECT_PROD }} LLM=${{ vars.LLM }} DomainName=${{ secrets.CERT_DOMAIN }} + aws cloudformation deploy --template-file infra/template.yaml --stack-name "caddy-prod" --capabilities CAPABILITY_NAMED_IAM --parameter-overrides StageName=prod MessageTableName=${{ vars.MESSAGES_TABLE_NAME_PROD }} RoutesTableName=${{ vars.ROUTES_TABLE_NAME_PROD }} PromptsTableName=${{ vars.PROMPTS_TABLE_NAME_PROD }} ResponsesTableName=${{ vars.RESPONSES_TABLE_NAME_PROD }} UserTableName=${{ vars.USERS_TABLE_NAME_PROD }} OfficesTableName=${{ vars.OFFICES_TABLE_NAME_PROD }} EvaluationTableName=${{ vars.EVALUATION_TABLE_NAME_PROD }} OpensearchUrl=${{ secrets.OPENSEARCH_PROD_URL }} OpensearchIndex=${{ secrets.OPENSEARCH_INDEX }} CaddyServiceAccountSecretArn=${{ secrets.CADDY_SA_ARN_PROD }} CaddySupervisorServiceAccountSecretArn=${{ secrets.CADDY_SUPERVISOR_SA_ARN_PROD }} CaddyImage=${{ secrets.CADDY_ECR_ENDPOINT }}/${{ secrets.CADDY_ECR_REPO_ID_PROD }}:${{ github.sha }} CaddySupervisorGoogleCloudProject=${{ secrets.CADDY_SUPERVISOR_GOOGLE_CLOUD_PROJECT_PROD }} CaddyGoogleCloudProject=${{ secrets.CADDY_GOOGLE_CLOUD_PROJECT_PROD }} LLM=${{ vars.LLM }} DomainName=${{ secrets.CERT_DOMAIN }} aws cloudformation deploy --template-file infra/opensearch.yaml --stack-name "caddy-opensearch-prod" --region eu-west-3 --capabilities CAPABILITY_NAMED_IAM --parameter-overrides StageName=prod CaddyRoleArn=${{ secrets.CADDY_ROLE_ARN_PROD }} diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..871f80a --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.12.3 diff --git a/README.md b/README.md index 6751088..003cc04 100644 --- a/README.md +++ b/README.md @@ -49,6 +49,12 @@ To explore the connection to DynamoDB, I have attached the docker-compose file t $ docker compose up ``` +If you get an error with docker, note you may need to change credsStore your .docker/config.json file with: + +```json +"credStore": "desktop", +``` + ## Testing Running tests on platform agnostic Caddy components with pytest. Tests are stored in tests/caddy_components, and can be invoked by running the below: @@ -95,3 +101,24 @@ For ease of deletion, you can remove all the created resources with ```bash $ aws cloudformation delete-stack --stack-name "INSERT_CUSTOM_STACK_NAME" ``` + +## Local Teams Deployment + +In azure (https://portal.azure.com/#home), creat an azure bot, and add app_id, app_password to the .env from configuration space. + +Then you need to build the container and provide a tunnel. + +```bash +$ docker compose up +``` + +Go to ngrok dashboard (https://dashboard.ngrok.com/) and create a domain then expose the domain endpoint for local forwarding on the desired port i.e. 80 + +```bash +$ ngrok http --domain=insert-static-url 80 +``` + +If you recieve a ngrok 381 errror, this is because ngrok has created an automatic edge. Delete the edge in ngrok dashboard and retry command + +In azure bot got to setting > configuration and add static-url with /microsoft-teams/chat into the messaging endpoint +Then in channels use the open in teams button to test locally \ No newline at end of file diff --git a/caddy_chatbot/src/app.py b/caddy_chatbot/src/app.py index 980a001..1bf584b 100644 --- a/caddy_chatbot/src/app.py +++ b/caddy_chatbot/src/app.py @@ -3,6 +3,7 @@ from caddy_core import components as caddy from caddy_core.services import enrolment +from caddy_core.utils.monitoring import logger from integrations.google_chat.structures import GoogleChat from integrations.google_chat.verification import ( @@ -10,6 +11,7 @@ verify_google_chat_supervision_request, ) +from integrations.microsoft_teams.structures import MicrosoftTeams from threading import Thread @@ -26,17 +28,22 @@ def google_chat_endpoint(event=Depends(verify_google_chat_request)) -> dict: """ Handles inbound requests from Google Chat for Caddy """ + logger.info("New Google Chat Request") google_chat = GoogleChat() user = event["user"]["email"] domain = user.split("@")[1] domain_enrolled, office = enrolment.check_domain_status(domain) if domain_enrolled is not True: + logger.info("Domain not enrolled") return google_chat.responses.DOMAIN_NOT_ENROLLED + logger.info("Domain is enrolled") user_enrolled, user_record = enrolment.check_user_status(user) if user_enrolled is not True: + logger.info("User is not enrolled") return google_chat.responses.USER_NOT_ENROLLED + logger.info("User is enrolled") included_in_rct = enrolment.check_rct_status(office) if included_in_rct is True: @@ -247,14 +254,39 @@ def google_chat_supervision_endpoint( @app.post("/microsoft-teams/chat") -def microsoft_teams_endpoint(request: Request): - return JSONResponse( - status_code=status.HTTP_200_OK, content={"text": "Request received"} - ) +async def microsoft_teams_endpoint(request: Request): + event = await request.json() + print("POST request received", event) + + microsoft_teams = MicrosoftTeams() + + match event["type"]: + case "message": + query = microsoft_teams.format_message(event) + caddy.temporary_teams_invoke(microsoft_teams, query, event) + case "invoke": + match event["value"]["action"]["verb"]: + case "proceed": + # TODO Handle Proceed Route + print("Adviser choice was to proceed") + microsoft_teams.update_card(event) + return microsoft_teams.responses.OK + case "redacted_query": + # TODO Handle edit original query + print("Adviser choice was to edit original query") + redacted_card = microsoft_teams.messages.create_redacted_card(event) + microsoft_teams.update_card(event, card=redacted_card) + return microsoft_teams.responses.OK + case "approved": + microsoft_teams.handle_thumbs_up(event) + return microsoft_teams.responses.OK + case "rejected": + microsoft_teams.handle_thumbs_down(event) + return microsoft_teams.responses.OK @app.post("/microsoft-teams/supervision") -def microsoft_teams_supervision_endpoint(request: Request): +async def microsoft_teams_supervision_endpoint(request: Request): return JSONResponse( status_code=status.HTTP_200_OK, content={"text": "Request received"} ) diff --git a/caddy_chatbot/src/caddy_core/components.py b/caddy_chatbot/src/caddy_core/components.py index a1c2151..9792c68 100644 --- a/caddy_chatbot/src/caddy_core/components.py +++ b/caddy_chatbot/src/caddy_core/components.py @@ -3,8 +3,7 @@ from fastapi import status from langchain.prompts import PromptTemplate -from caddy_core.utils.prompts.default_template import CADDY_PROMPT_TEMPLATE -from caddy_core.utils.prompts.prompt import retrieve_route_specific_augmentation +from caddy_core.utils.prompt import retrieve_route_specific_augmentation, get_prompt from time import sleep @@ -18,10 +17,10 @@ from caddy_core.utils.tables import ( evaluation_table, - message_table, responses_table, users_table, ) +from caddy_core.utils.monitoring import logger from caddy_core.services.retrieval_chain import build_chain from caddy_core.services import enrolment from caddy_core.services.evaluation import execute_optional_modules @@ -49,6 +48,7 @@ def rct_survey_reminder(event, user_record, chat_client): def handle_message(caddy_message, chat_client): + logger.info("Running message handler") module_values, survey_complete = check_existing_call(caddy_message) if survey_complete is True: @@ -107,10 +107,12 @@ def remove_role_played_responses(response: str) -> str: """ adviser_index = response.find("Adviser: ") if adviser_index != -1: + logger.info("Removing role played response") return True, response[:adviser_index].strip() adviser_index = response.find("Advisor: ") if adviser_index != -1: + logger.info("Removing role played response") return True, response[:adviser_index].strip() return False, response.strip() @@ -128,9 +130,14 @@ def format_chat_history(user_messages: List) -> List: """ history_langchain_format = [] for message in user_messages: - human = message["llmPrompt"] - ai = message["llmAnswer"] - history_langchain_format.append((human, ai)) + human = message.get("llmPrompt") + ai = message.get("llmAnswer") + + if human and ai: + history_langchain_format.append((human, ai)) + elif human: + history_langchain_format.append((human, "")) + return history_langchain_format @@ -147,7 +154,15 @@ def get_chat_history(message: UserMessage) -> List: response = responses_table.query( KeyConditionExpression=Key("threadId").eq(message.thread_id), ) - history = format_chat_history(response["Items"]) + + sorted_items = sorted( + response["Items"], + key=lambda x: x.get( + "messageReceivedTimestamp", x.get("llmPromptTimestamp", "") + ), + ) + + history = format_chat_history(sorted_items) return history @@ -198,14 +213,14 @@ def format_chat_message(event: ProcessChatMessageEvent) -> UserMessage: def store_message(message: UserMessage): - message_table.put_item( + responses_table.put_item( Item={ + "threadId": str(message.thread_id), "messageId": str(message.message_id), "conversationId": str(message.conversation_id), - "threadId": str(message.thread_id), "client": message.client, "userEmail": str(message.user_email), - "message": message.message, + "llmPrompt": message.message, "messageSentTimestamp": message.message_sent_timestamp, "messageReceivedTimestamp": str(message.message_received_timestamp), } @@ -213,22 +228,22 @@ def store_message(message: UserMessage): def store_response(response: LlmResponse): - responses_table.put_item( - Item={ - "responseId": str(response.response_id), - "messageId": str(response.message_id), - "threadId": str(response.thread_id), - "llmPrompt": response.llm_prompt, - "llmAnswer": response.llm_answer, - "llmResponseJSon": response.llm_response_json, - "llmPromptTimestamp": str(response.llm_prompt_timestamp), - "llmResponseTimestamp": str(response.llm_response_timestamp), - } + responses_table.update_item( + Key={"threadId": str(response.thread_id)}, + UpdateExpression="set responseId = :rId, llmAnswer = :la, llmResponseJSon = :lrj, llmPromptTimestamp = :lpt, llmResponseTimestamp = :lrt, route = :route, context = :context", + ExpressionAttributeValues={ + ":rId": response.response_id, + ":la": response.llm_answer, + ":lrj": response.llm_response_json, + ":lpt": str(response.llm_prompt_timestamp), + ":lrt": str(response.llm_response_timestamp), + ":route": response.route, + ":context": response.context, + }, ) def store_user_thanked_timestamp(ai_answer: LlmResponse): - # Updating response in DynamoDB responses_table.update_item( Key={"threadId": ai_answer.thread_id}, UpdateExpression="set userThankedTimestamp=:t", @@ -333,12 +348,12 @@ def check_existing_call(caddy_message) -> Tuple[Dict[str, Any], bool]: def send_to_llm(caddy_query: UserMessage, chat_client): query = caddy_query.message - + domain = caddy_query.user_email.split("@")[1] chat_history = get_chat_history(caddy_query) - route_specific_augmentation = retrieve_route_specific_augmentation(query) + route_specific_augmentation, route = retrieve_route_specific_augmentation(query) day_date_time = datetime.now(timezone("Europe/London")).strftime( "%A %d %B %Y %H:%M" @@ -348,7 +363,7 @@ def send_to_llm(caddy_query: UserMessage, chat_client): office_regions = enrolment.get_office_coverage(office) CADDY_PROMPT = PromptTemplate( - template=CADDY_PROMPT_TEMPLATE, + template=get_prompt("CORE_PROMPT"), input_variables=["context", "question"], partial_variables={ "route_specific_augmentation": route_specific_augmentation, @@ -486,6 +501,8 @@ def send_to_llm(caddy_query: UserMessage, chat_client): llm_prompt_timestamp=ai_prompt_timestamp, llm_response_json=json.dumps(response_card), llm_response_timestamp=ai_response_timestamp, + route=route or "no_route", + context=[doc_without_embeddings(doc) for doc in caddy_response["context"]], ) store_response(llm_response) @@ -535,8 +552,13 @@ def send_to_llm(caddy_query: UserMessage, chat_client): store_approver_received_timestamp(supervision_event) +def doc_without_embeddings(doc): + doc_dict = doc.dict() + doc_dict.pop("state", None) + return doc_dict + + def store_approver_received_timestamp(event: SupervisionEvent): - # Updating response in DynamoDB responses_table.update_item( Key={"threadId": event.thread_id}, UpdateExpression="set approverReceivedTimestamp=:t", @@ -545,12 +567,12 @@ def store_approver_received_timestamp(event: SupervisionEvent): ) -def store_approver_event(approval_event: ApprovalEvent): - # Updating response in DynamoDB +def store_approver_event(thread_id: str, approval_event: ApprovalEvent): responses_table.update_item( - Key={"threadId": str(approval_event.thread_id)}, - UpdateExpression="set approverEmail=:email, approved=:approved, approvalTimestamp=:atime, userResponseTimestamp=:utime, supervisorMessage=:sMessage", + Key={"threadId": thread_id}, + UpdateExpression="set responseId=:rId, approverEmail=:email, approved=:approved, approvalTimestamp=:atime, userResponseTimestamp=:utime, supervisorMessage=:sMessage", ExpressionAttributeValues={ + ":rId": approval_event.response_id, ":email": approval_event.approver_email, ":approved": approval_event.approved, ":atime": str(approval_event.approval_timestamp), @@ -559,3 +581,42 @@ def store_approver_event(approval_event: ApprovalEvent): }, ReturnValues="UPDATED_NEW", ) + + +def temporary_teams_invoke(chat_client, query, event): + """ + Temporary solution for Teams integration + """ + route_specific_augmentation, _ = retrieve_route_specific_augmentation(query) + + day_date_time = datetime.now(timezone("Europe/London")).strftime( + "%A %d %B %Y %H:%M" + ) + + office_regions = ["England"] + + CADDY_PROMPT = PromptTemplate( + template=get_prompt("CORE_PROMPT"), + input_variables=["context", "question"], + partial_variables={ + "route_specific_augmentation": route_specific_augmentation, + "day_date_time": day_date_time, + "office_regions": office_regions, + }, + ) + + chain, ai_prompt_timestamp = build_chain(CADDY_PROMPT) + + caddy_response = chain.invoke( + { + "input": query, + "chat_history": [], + } + ) + + _, caddy_response["answer"] = remove_role_played_responses(caddy_response["answer"]) + + chat_client.send_adviser_card( + event, + card=chat_client.messages.generate_response_card(caddy_response["answer"]), + ) diff --git a/caddy_chatbot/src/caddy_core/models.py b/caddy_chatbot/src/caddy_core/models.py index 75e0fdf..7c79f8b 100644 --- a/caddy_chatbot/src/caddy_core/models.py +++ b/caddy_chatbot/src/caddy_core/models.py @@ -1,4 +1,4 @@ -from typing import Union +from typing import Union, List, Any from datetime import datetime import uuid import pydantic @@ -35,6 +35,8 @@ class LlmResponse(pydantic.BaseModel): llm_response_json: Union[pydantic.Json, None] = None llm_prompt_timestamp: datetime llm_response_timestamp: datetime + route: str + context: Union[List[Any], None] class SupervisionEvent(pydantic.BaseModel): diff --git a/caddy_chatbot/src/caddy_core/services/retrieval_chain.py b/caddy_chatbot/src/caddy_core/services/retrieval_chain.py index 30a565b..e4b2d05 100644 --- a/caddy_chatbot/src/caddy_core/services/retrieval_chain.py +++ b/caddy_chatbot/src/caddy_core/services/retrieval_chain.py @@ -1,5 +1,4 @@ from langchain_community.chat_models import BedrockChat -from langchain_community.embeddings import HuggingFaceEmbeddings from langchain_community.embeddings import BedrockEmbeddings from langchain_community.vectorstores import OpenSearchVectorSearch from langchain_community.document_transformers import EmbeddingsClusteringFilter @@ -19,6 +18,8 @@ from opensearchpy import RequestsHttpConnection from requests_aws4auth import AWS4Auth +from caddy_core.utils.monitoring import logger + import re import os from datetime import datetime @@ -26,18 +27,16 @@ alternate_region = "eu-west-3" opensearch_https = os.environ.get("OPENSEARCH_HTTPS") -bedrock_embeddings = BedrockEmbeddings( +embeddings = BedrockEmbeddings( model_id="amazon.titan-embed-image-v1", region_name=alternate_region ) -embeddings = HuggingFaceEmbeddings(model_name="model") - try: session = boto3.Session() credentials = session.get_credentials() auth = AWS4Auth( - region=os.environ.get("AWS_REGION"), - service="es", + region=alternate_region, + service="aoss", refreshable_credentials=credentials, ) except NoCredentialsError: @@ -65,6 +64,7 @@ def find_most_recent_caddy_vector_index(): # Initialize most_recent_index with the original index name as a fallback most_recent_index = opensearch_index + logger.info(f"Index initalised with: {opensearch_index}") # Pattern to match indexes of interest pattern = re.compile(opensearch_index + r"_(\d{8})$") @@ -73,6 +73,7 @@ def find_most_recent_caddy_vector_index(): index_list = client.indices.get("*") most_recent_date = None + logger.info(f"Checking through {len(index_list)} indexes") for index_name in index_list: match = pattern.match(index_name) if match: @@ -80,14 +81,17 @@ def find_most_recent_caddy_vector_index(): extracted_date_str = match.group(1) try: extracted_date = datetime.strptime(extracted_date_str, "%Y%m%d") + logger.info(f"Date extracted from index: {extracted_date}") # Update most recent date and index name if this index is more recent if most_recent_date is None or extracted_date > most_recent_date: + logger.info(f"Setting as most recent date: {extracted_date}") most_recent_date = extracted_date most_recent_index = index_name except ValueError: # If the date is not valid, ignore this index continue + logger.info(f"Most recent index is: {most_recent_index}") return most_recent_index @@ -145,7 +149,7 @@ def build_chain(CADDY_PROMPT): ) llm = BedrockChat( - model_id=os.environ.get("LLM"), + model_id=os.getenv("LLM"), region_name=alternate_region, model_kwargs={"temperature": 0.3, "top_k": 5, "max_tokens": 2000}, ) diff --git a/caddy_chatbot/src/caddy_core/services/router.py b/caddy_chatbot/src/caddy_core/services/router.py index 15dd40b..35246a0 100644 --- a/caddy_chatbot/src/caddy_core/services/router.py +++ b/caddy_chatbot/src/caddy_core/services/router.py @@ -1,296 +1,80 @@ +import os import boto3 +from botocore.exceptions import ClientError +from datetime import datetime, timezone, timedelta + from semantic_router import Route, RouteLayer from semantic_router.encoders import BedrockEncoder - -session = boto3.Session() -credentials = session.get_credentials() -embeddings = BedrockEncoder( - access_key_id=credentials.access_key, - secret_access_key=credentials.secret_key, - session_token=credentials.token, - region="eu-west-3", -) - -benefits_and_tax_credits_route = Route( - name="benefits_and_tax_credits", - utterances=[ - "What are benefits available?", - "How do I apply for tax credits?", - "Can you explain the eligibility criteria for tax credits?", - "Are there any changes to tax credits this year?", - "How can I calculate my entitlement to benefits and tax credits?", - "What documents do I need to provide for benefits and tax credits?", - "Can you help me with a benefits and tax credits claim issue?", - "Where can I find more information about benefits and tax credits?", - ], -) - -benefits_and_universal_credit_route = Route( - name="benefits_and_universal_credit", - utterances=[ - "What is Universal Credit?", - "How do I apply for Universal Credit?", - "What are the eligibility criteria for Universal Credit?", - "Can you explain the Universal Credit claim process?", - "What documents do I need to provide for a Universal Credit claim?", - "How can I calculate my entitlement to Universal Credit?", - "Can you help me with a Universal Credit claim issue?", - "Where can I find more information about Universal Credit?", - ], -) - -charitable_support_and_food_banks_route = Route( - name="charitable_support_and_food_banks", - utterances=[ - "What are the eligibility criteria for receiving charitable support?", - "How can someone apply for charitable support?", - "What types of assistance do food banks provide?", - "Are there any income limits or requirements to access food banks?", - "What documentation is needed to receive charitable support?", - "How can someone find local food banks?", - "What other resources or services are available for individuals in need?", - "Are there any restrictions or limitations on the frequency of accessing food banks?", - ], -) - -consumer_goods_and_services_route = Route( - name="consumer_goods_and_services", - utterances=[ - "What are my rights as a consumer?", - "How can I make a complaint about a product or service?", - "What are the refund and return policies for consumer goods?", - "Can you help me with a dispute with a retailer?", - "Where can I find information about consumer protection laws?", - "What are the regulations for online shopping?", - "How can I avoid scams and fraudulent sellers?", - "Can you provide guidance on product warranties and guarantees?", - ], -) - -debt_route = Route( - name="debt", - utterances=[ - "What are the different types of debt?", - "How can someone negotiate with creditors to reduce debt?", - "What are the consequences of not paying off debt?", - "Can you explain the debt collection process?", - "What are the options for debt consolidation?", - "How can someone deal with overwhelming debt?", - "What are the rights and protections for individuals in debt?", - "Can you provide guidance on bankruptcy and insolvency?", - ], -) - -education_route = Route( - name="education", - utterances=[ - "What are the available education options for my client?", - "How can my client access financial support for education?", - "What are the eligibility criteria for educational grants and scholarships?", - "Can you explain the process of applying for student loans?", - "What documentation is required for enrolling in educational programs?", - "How can my client navigate the admissions process for schools and universities?", - "Can you provide guidance on special education services and accommodations?", - "What resources are available for adult education and vocational training?", - "How can my client address issues related to bullying or discrimination in educational settings?", - "Where can I find more information about educational rights and regulations?", - ], -) - -employment_route = Route( - name="employment", - utterances=[ - "What are the rights and responsibilities of employees?", - "How can someone address workplace discrimination or harassment?", - "What is the process for filing a complaint against an employer?", - "Can you provide guidance on employment contracts and terms?", - "What are the regulations for minimum wage and working hours?", - "How can someone negotiate a fair salary or benefits package?", - "Can you explain the process of redundancy and severance pay?", - "What are the rights and protections for individuals facing unfair dismissal?", - "How can someone access support for workplace health and safety issues?", - "Where can I find more information about employment rights and regulations?", - ], -) - -financial_services_and_capability_route = Route( - name="financial_services_and_capability", - utterances=[ - "What financial services are available for individuals?", - "How can someone access financial advice and guidance?", - "Can you explain the process of opening a bank account?", - "What are the options for managing debt and improving credit?", - "How can someone access affordable loans or credit?", - "Can you provide guidance on budgeting and saving?", - "What resources are available for financial planning and retirement?", - "How can someone protect themselves from financial scams and fraud?", - "Where can I find more information about financial services and capability?", - ], -) - -gva_and_hate_crime_route = Route( - name="gva_and_hate_crime", - utterances=[ - "What support services are available for victims of gender-based violence and hate crimes?", - "How can someone report a gender-based violence or hate crime incident?", - "What legal protections are in place for victims of gender-based violence and hate crimes?", - "Can you explain the process of obtaining a restraining order or protection order?", - "What resources are available for counseling and emotional support for victims of gender-based violence and hate crimes?", - "How can someone access emergency accommodation or safe houses?", - "Can you provide guidance on safety planning for victims of gender-based violence and hate crimes?", - "Where can I find more information about gender-based violence and hate crimes?", - ], -) - -health_and_community_care_route = Route( - name="health_and_community_care", - utterances=[ - "What are the available healthcare services in the area?", - "How can someone access primary healthcare?", - "Can you explain the process of registering with a general practitioner (GP)?", - "What are the eligibility criteria for receiving community care services?", - "How can someone apply for community care services?", - "What types of support are available for individuals with specific health conditions?", - "Are there any income limits or requirements to access community care services?", - "What documentation is needed to receive community care services?", - "How can someone find local healthcare providers and specialists?", - "What other resources or services are available for individuals in need of healthcare and community care support?", - "Are there any restrictions or limitations on the frequency of accessing community care services?", - "Can you provide guidance on mental health support services?", - "What are the options for accessing long-term care facilities?", - "How can someone navigate the process of obtaining medical equipment or assistive devices?", - "What are the rights and protections for individuals receiving healthcare and community care services?", - "Where can I find more information about healthcare rights and regulations?", - ], -) - -housing_route = Route( - name="housing", - utterances=[ - "What are the rights and responsibilities of a tenant?", - "How can someone find affordable housing options?", - "Can you explain the process of renting a property?", - "What are the regulations for tenancy agreements?", - "How can someone address issues with their landlord?", - "What are the options for dealing with eviction?", - "Can you provide guidance on housing benefits and assistance programs?", - "Where can I find more information about housing rights and regulations?", - ], -) - -immigration_and_asylum_route = Route( - name="immigration_and_asylum", - utterances=[ - "What are the eligibility criteria for different types of visas?", - "How can someone apply for asylum in this country?", - "What are the rights and protections for asylum seekers?", - "Can you explain the process of appealing a visa or asylum decision?", - "What are the options for family reunification for refugees?", - "How can someone access legal representation for immigration cases?", - "Can you provide guidance on immigration detention and removal?", - "What are the requirements for obtaining citizenship or permanent residency?", - "How can someone address issues with their immigration status?", - "Where can I find more information about immigration and asylum rights and regulations?", - ], -) - -legal_route = Route( - name="legal", - utterances=[ - "What are the different types of legal cases?", - "How can someone find a lawyer or legal representation?", - "Can you explain the process of filing a lawsuit?", - "What are the options for alternative dispute resolution?", - "How can someone access legal aid or pro bono services?", - "Can you provide guidance on court procedures and protocols?", - "What are the rights and protections for individuals in the justice system?", - "How can someone navigate the process of obtaining legal documents or records?", - "Where can I find more information about the legal system, courts, and justice system?", - ], -) - -relationships_and_family_route = Route( - name="relationships_and_family", - utterances=[ - "What are the legal rights and responsibilities in a marriage or civil partnership?", - "How can someone navigate the process of divorce or dissolution?", - "What are the options for child custody and visitation rights?", - "Can you provide guidance on child support and maintenance?", - "What are the rights and protections for victims of domestic violence?", - "How can someone address issues related to child protection and safeguarding?", - "Can you explain the process of adoption or fostering?", - "What resources are available for couples or families going through relationship breakdown?", - "How can someone access counseling or mediation services for family disputes?", - "Where can I find more information about relationship and family rights and regulations?", - ], -) - -tax_route = Route( - name="tax", - utterances=[ - "What are the different types of taxes?", - "How can someone calculate their income tax?", - "Can you explain the process of filing a tax return?", - "What are the deductions and credits available for taxpayers?", - "How can someone address issues with their tax payments?", - "What are the options for resolving tax disputes?", - "Can you provide guidance on self-employment taxes?", - "What are the tax implications of owning a business?", - "How can someone navigate the process of paying taxes as an employee (PAYE)?", - "Where can I find more information about tax laws and regulations?", - ], -) - -travel_and_transport_route = Route( - name="travel_and_transport", - utterances=[ - "What are the available modes of public transportation in the area?", - "How can someone plan their travel using public transportation?", - "Can you explain the process of purchasing tickets for trains or buses?", - "What are the options for traveling between different cities or regions?", - "How can someone access information about train schedules and routes?", - "Are there any discounts or concessions available for public transportation?", - "Can you provide guidance on navigating public transportation systems?", - "What are the rights and protections for passengers using public transportation?", - "How can someone address issues with delays or cancellations of trains or buses?", - "Where can I find more information about travel and transportation services?", - ], -) - -utilities_and_communications_route = Route( - name="utilities_and_communications", - utterances=[ - "How can someone reduce their energy bills?", - "What assistance programs are available for individuals struggling to pay their energy bills?", - "Can you explain the process of switching energy providers?", - "What are the options for accessing affordable broadband services?", - "How can someone address issues with their broadband connection?", - "What support is available for individuals experiencing fuel poverty?", - "Can you provide guidance on energy-saving measures for heating and cooling?", - "What are the rights and protections for consumers in the energy and communications sectors?", - "How can someone navigate the process of installing and using prepayment meters?", - "Where can I find more information about energy crisis management and resources?", - ], -) - -routes = [ - benefits_and_tax_credits_route, - benefits_and_universal_credit_route, - charitable_support_and_food_banks_route, - consumer_goods_and_services_route, - debt_route, - education_route, - employment_route, - financial_services_and_capability_route, - gva_and_hate_crime_route, - health_and_community_care_route, - housing_route, - immigration_and_asylum_route, - legal_route, - relationships_and_family_route, - tax_route, - travel_and_transport_route, - utilities_and_communications_route, -] - +from caddy_core.utils.monitoring import logger + + +class AutoRefreshBedrockEncoder: + def __init__(self, region="eu-west-3", score_threshold=0.5): + self.region = region + self.score_threshold = score_threshold + self.encoder = None + self.refresh_credentials() + + def refresh_credentials(self): + try: + sts_client = boto3.client("sts") + role_arn = os.environ.get("TASK_ROLE_ARN") + response = sts_client.assume_role( + RoleArn=role_arn, + RoleSessionName="CaddyTaskSession", + DurationSeconds=3600, + ) + + credentials = response["Credentials"] + self.encoder = BedrockEncoder( + access_key_id=credentials["AccessKeyId"], + secret_access_key=credentials["SecretAccessKey"], + session_token=credentials["SessionToken"], + region=self.region, + score_threshold=self.score_threshold, + ) + + self.expiration = credentials["Expiration"] + logger.info( + f"Refreshed credentials, new expiry time: { + self.expiration}" + ) + except ClientError as e: + logger.error(f"Failed to refresh credentials: {e}") + raise + + def __call__(self, *args, **kwargs): + if datetime.now(timezone.utc) >= self.expiration - timedelta(minutes=5): + logger.info("Credentials expiring soon, refreshing...") + self.refresh_credentials() + + return self.encoder(*args, **kwargs) + + def __getattr__(self, name): + if name == "score_threshold": + return self.score_threshold + return getattr(self.encoder, name) + + +embeddings = AutoRefreshBedrockEncoder(region="eu-west-3", score_threshold=0.5) + +dynamodb = boto3.resource("dynamodb") +table = dynamodb.Table(os.getenv("ROUTES_TABLE_NAME")) + + +def get_routes_dynamically(): + logger.info("Fetching routes") + response = table.scan() + routes = [] + for item in response["Items"]: + utterances = item["utterances"] + if isinstance(utterances[0], list): + utterances = utterances[0] + route = Route(name=item["name"], utterances=utterances) + routes.append(route) + logger.info(f"Fetched {len(routes)} routes") + return routes + + +routes = get_routes_dynamically() get_route = RouteLayer(encoder=embeddings, routes=routes) diff --git a/caddy_chatbot/src/caddy_core/utils/monitoring.py b/caddy_chatbot/src/caddy_core/utils/monitoring.py new file mode 100644 index 0000000..df9f03b --- /dev/null +++ b/caddy_chatbot/src/caddy_core/utils/monitoring.py @@ -0,0 +1,48 @@ +import logging +import sys + + +class Colours: + RESET = "\033[0m" + BOLD = "\033[1m" + BLACK = "\033[30m" + RED = "\033[31m" + GREEN = "\033[32m" + YELLOW = "\033[33m" + BLUE = "\033[34m" + MAGENTA = "\033[35m" + CYAN = "\033[36m" + WHITE = "\033[37m" + + +class ColourFormatter(logging.Formatter): + COLOURS = { + "DEBUG": Colours.BLUE, + "INFO": Colours.MAGENTA, + "WARNING": Colours.YELLOW, + "ERROR": Colours.RED, + "CRITICAL": Colours.BOLD + Colours.RED, + } + + def format(self, record): + log_message = super().format(record) + return f"{self.COLOURS.get(record.levelname, '')}{log_message}{Colours.RESET}" + + +def setup_logger(name, level=logging.INFO): + """ + Function to setup a colour-coded logger + """ + logger = logging.getLogger(name) + logger.setLevel(level) + + formatter = ColourFormatter("%(name)s | %(asctime)s | %(levelname)s | %(message)s") + + handler = logging.StreamHandler(sys.stdout) + handler.setFormatter(formatter) + logger.addHandler(handler) + + return logger + + +logger = setup_logger("CADDY") diff --git a/caddy_chatbot/src/caddy_core/utils/prompt.py b/caddy_chatbot/src/caddy_core/utils/prompt.py new file mode 100644 index 0000000..40d1a8f --- /dev/null +++ b/caddy_chatbot/src/caddy_core/utils/prompt.py @@ -0,0 +1,30 @@ +import os +import boto3 +from botocore.exceptions import ClientError +from datetime import datetime, timezone, timedelta + +from caddy_core.utils.monitoring import logger +from caddy_core.services.router import get_route + + +def get_prompt(prompt_name): + dynamodb = boto3.resource("dynamodb") + table = dynamodb.Table(os.getenv("PROMPTS_TABLE_NAME")) + + response = table.get_item(Key={"PromptName": prompt_name}) + logger.info(f"Fetched prompt: {prompt_name}") + return response["Item"]["Prompt"] if "Item" in response else None + + +def retrieve_route_specific_augmentation(query): + route = get_route(query).name + logger.info(f"Route returned: {route}") + + prompt_name = f"{route.upper()}_PROMPT" + route_specific_augmentation = get_prompt(prompt_name) + + if route_specific_augmentation is None: + logger.info("Route not found, using fallback prompt") + route_specific_augmentation = get_prompt("FALLBACK_PROMPT") + + return route_specific_augmentation, route diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/benefits_and_tax_credits.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/benefits_and_tax_credits.py deleted file mode 100644 index e711e18..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/benefits_and_tax_credits.py +++ /dev/null @@ -1,28 +0,0 @@ -PROMPT = """ -For example, if the question is "I get PIP as Im disabled, -but I also care for my elderly mum (aged 76). Can I claim Carers Allowance?" -you could respond with: ------ -If your mum receives a disability benefit (middle/higher rate care component of DLA, -daily living component of PIP, or AA), are not in gainful employment and you provide -35 hours a week care you might be able to claim CA. - -If your mum gets a severe disability addition/premium in Pension Credit or Housing Benefit -this will stop if you are paid Carers Allowance. - -If you get the daily living component of PIP, the DWP might look again at your PIP award -if the activities you are able to carry out as a carer for your mum suggest that you dont -need help with your own daily living activities. Being a carer and qualifying for PIP arent -necessarily incompatible. It will depend on the reasons you get PIP and the tasks you carry -out for your mum. For example, if you have a mental health condition and need prompting to carry -out daily living tasks, but are physically able to carry them out there wouldnt be a contradiction -in receiving PIP and being a carer. ----- -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to benefits and tax credits is likely to also -be advised on universal credit, charitable support (such as grants) and food banks, debt and -utilities, communications and energy issues. You must think step-by-step -about the question identifying any evidence of these present in the query and formulate your response -to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/benefits_and_universal_credit.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/benefits_and_universal_credit.py deleted file mode 100644 index ef90c6d..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/benefits_and_universal_credit.py +++ /dev/null @@ -1,21 +0,0 @@ -PROMPT = """ -For example, if the question is "Ive moved into a leasehold flat and have to pay -service charges of £40 per week. I get UC, can I get help to pay the charges?" -you could respond with: ------ -Yes, a housing costs element in UC can be paid for service charges that you -have to pay to occupy your home. They must be related to the provision of adequate -accommodation. Examples of service charges that may be included are: - -Charges for using shared facilities, such as rubbish collection or communal lifts -Charges for using essential items in your home, such as domestic appliances -Charges window cleaning of upper floors ----- -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to benefits universal credit is likely to also -be advised on benefits and tax credits, charitable support (such as grants) and food banks, debt -and utilities, communications and energy issues. You must think step-by-step -about the question identifying any evidence of these present in the query and formulate your response -to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/charitable_support_and_food_banks.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/charitable_support_and_food_banks.py deleted file mode 100644 index fe4353b..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/charitable_support_and_food_banks.py +++ /dev/null @@ -1,9 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to charitable support (such as grants) and food -banks is likely to also be advised on utilities, communications and energy issues, debt, benefits such -as universal credit, financial services and capability as well as housing. You must think step-by-step -about the question identifying any evidence of these present in the query and formulate your response -to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/consumer_goods_and_services.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/consumer_goods_and_services.py deleted file mode 100644 index 2964f6b..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/consumer_goods_and_services.py +++ /dev/null @@ -1,49 +0,0 @@ -PROMPT = """ -For example, if the question is "I bought a used car 3 weeks ago on finance. -Its a Vauxhall Corsa 63 registration. The brakes were making a noise so Ive had -the car looked at and theyve said there are other faults and it shouldnt have -passed its MOT. The garage I bought it from has given me £200 towards the repair -cost but Ive spent £600 on urgent repairs and the other repairs will cost at least £750. -I want to keep the car. Can I get the money back for the repair costs? The garage has given -me £200 towards repair costs and say they wont pay anymore. Ive spoken to the finance company -and they say they cant make the garage pay." you could respond with: ------ -Because you bought your car on finance, your contract is with the finance company -and theyre the legal owner of the car. This means its their responsibility to sort -out problems. The law says the car you bought should be of satisfactory quality and -fit for purpose in relation to its age and usage. The car should also match the advert -or description the garage used. Youre entitled to claim the cost of repairs if the car -doesnt meet these requirements. If the repairs mean the car ends up being worth more than -the age and condition of the car as it was when you bought it, it would be reasonable for the -garage to reflect this in the amount they offer you towards the repair costs. - -It sounds like youve got evidence of the faults with the car from the garage you took it to. -Check the finance companys complaints process to see how you can complain to them. Send a copy -of your evidence to the finance company, explain that you think it means the vehicle you bought -wasnt fit for purpose, isnt of satisfactory quality or doesnt match its description and ask them -to refund the £400 giving them a deadline to sort the problem out - wed suggest 14 days. Theres -a template letter on the Citizens Advice website you can use. If you send a letter, send it using -Royal Mail Signed For and keep your proof of posting. If you send it by email, send it with a read -receipt. When you reject a car, you need to stop using it. - -If the finance company doesnt sort the problem out within 8 weeks of you first complaining to them, -or sends you their final response (sometimes called a deadlock letter) before 8 weeks, you can take -your complaint to the Financial Ombudsman Service. - -If the MOT was done within the last 28 days you can let the Driver and Vehicle Standards Agency (DVSA) -know that your car passed its MOT but you think it should have failed. - -Follow up questions -When was the MOT? -What mileage was the vehicle sold with? -Did you speak to the garage you bought the car from before you had the vehicle inspected and got the -urgent repairs done? ----- -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to consumer goods and services is likely to also -be advised on utilities and communications, benefits and tax credits, debt, charitable support and -food banks as well as financial services and capability. You must think step-by-step about the question -identifying any evidence of these present in the query and formulate your response to the advisor -accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/debt.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/debt.py deleted file mode 100644 index 9f7abc7..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/debt.py +++ /dev/null @@ -1,144 +0,0 @@ -PROMPT = """ -For example, if the question is "Im 55 and I have a small pension pot. I owe £35,000 in various -debts and want to get a DRO. I need my pension for later life. Can I get a DRO or do I need to go -bankrupt? I have about £10,000 equity in my house but half of that is my husbands who no longer -lives with me." you could respond with: ------ -You can't get a DRO as you have an interest in a property. You also owe more than £30,000 -which is the limit for a DRO, although not all debts count towards that. You could consider bankruptcy -but should get debt advice. There are no eligibility criteria as such for bankruptcy, although it will -cost you £680. You might be able to get help with this fee form a charity or trust fund and you can pay -this in instalments. You should be aware that: Any unapproved pension will be classed as an asset and taken -to pay your debts by the person that controls your bankruptcy, known as the Trustee, although you can ask -your Trustee to make an agreement not to take your pension but it will be up to the Trustee. You have to -ask them within 9 weeks of going bankrupt. You can apply to court to have the pension made exempt within -13 weeks of your bankruptcy, and it will be up to the court what order to make. You should try to get -legal advice on what arguments to raise, for instance, if you need to fund any care needs, whether the -pension is approved by a foreign tax authority if the pension is from overseas etc -You will not be forced to take any personal pension that is approved as these are protected by law from -bankruptcy. However, as you are over 55, you will probably be able to take your pension if you want to. -Therefore, the person that agrees you can go bankrupt, known as the Adjudicator, might decide you are still -able to pay your debts if the value of your pension after taxes and costs, is more than your debts. -You will not be forced to take your pension, but you might not get your bankruptcy order and you would not -get your £680 refunded If you did go bankrupt and drew on your pension, any lump sum might then be claimed -by the Trustee and any income you are paid will be used to assess whether you can make payments into an -income payment arrangement or order, to repay bankruptcy debts. If you do get a bankruptcy order, the -Trustee has 3 years to decide what to do with the equity in your home. They usually won't sell it for at -least 1 year after you go bankrupt. You can try to delay this sale but might need to go to court to do so, -and the court will only usually delay the sale further if you have exceptional circumstances. You and your -husband probably have a 50/50 share of the equity, known as 'beneficial interest.' Therefore, your share -of the equity is probably £5000. The Trustee is likely to value your home after 2 years and 3 months to -see if there is more equity If you have more than £5000 equity as your share at that point, the Trustee -may apply for a charging order or an order to sell your home. This might happen much sooner if your home -goes up in value quickly. If you have less than £5000 the Trustee is unlikely to apply for a charging -order or order for sale as there will not be anything left to pay creditors after costs, but this is -just a guide of course. A third party could make an offer to buy your share of the property, to the -Trustee. You should always take legal advice about this, and be certain that the third party will let you -stay in the property You or your husband may claim to have more than 50 percent share in the equity, for instance -if you paid the entire deposit for the house and used only your funds. This is a complicated area of law -and you should get legal advice if you want to claim more or less than 50 percent share. You should decide this -before going bankrupt but any agreement must be for the right consideration -If you later go bankrupt and the Trustee believes you have given away all or part of your equity, in order -not to pay creditors, you might have a longer bankruptcy period. This is known as a bankruptcy restriction -order, and can last between 2-15 years. The Trustee might also try to seek payment from the other person to -recover the lost value, or ask a court to reverse the transaction -The Trustee can review any sale or transfer of assets if they occurred in the 5 years before your bankruptcy -if the person you gave away or sold to, was an 'associate' like a business partner or family member. There -is no time limit where the Trustee thinks you did this on purpose to avoid paying creditors -The Trustee in bankruptcy may argue you have more than 50 perfect in order to claim more funds for creditors, -but ultimately only a court can decide the shares -The Trustee may still allow you to sell your home if this will raise more funds, but you should get their -consent. However, if you own the home jointly with someone else, you do not need the Trustee's consent to -sell You should also be aware that bankruptcy will not stop certain creditors chasing you for payment. These are -court fines, family or child maintenance arrangements, social fund loans, student loans, debt incurred -through fraud, and damages for negligence and injury ----- -Another example is: "Can I get a breathing space to stop my creditors chasing me, and how long will it last?" you could respond with: ------ -You have to meet certain eligibility criteria such as not being subject to another insolvency procedure, you must live in E&W and owe a ‘qualifying debt.’ You must not be subject to a mental health crisis moratorium, standard breathing space moratorium, and not have had a standard breathing space moratorium that ended in the last 12 months. -You must be unable or unlikely to pay some or all of your debts as they fall due, and the moratorium must be ‘appropriate.’ You must see a debt adviser to get a moratorium and they will decide whether it is appropriate, considering things like whether you can pay your debts, whether you will be able to enter a debt solution during or soon after your moratorium, and whether you need the moratorium time for the adviser to consider your options and put in place a recommendation for you. -A breathing space moratorium typically will last 60 days. -If you have a serious mental health condition and are in crisis treatment, you might be eligible for a mental health crisis moratorium. These last as long as your crisis treatment, plus 30 days. Most of the criteria above will apply, but you can have as many of these moratoria within 12 months as needed, so long as you are in crisis treatment. You will still need a debt adviser to enter you into the scheme, and an approved mental health professional will have to provide evidence that you are in crisis treatment. -When the debt adviser is considering whether a mental health crisis moratorium is suitable, they might ask for more medical evidence from a mental health professional. They have to get a credit report on your behalf as well. -The adviser might not have to consider whether you can move into a debt solution quickly, like in a standard breathing space, but they will need to work with you as much as you are able, to help with your debts. Your nominated point of contact (usually a health professional like a MH nurse) will have to provide evidence that you are still in crisis treatment, every 30 days. Otherwise your moratorium will end 30 days after the point they should have provided it. -Some creditors can still chase you for money even in a standard or mental health crisis moratorium, such as for child maintenance, a court fine, a universal credit advance, social fund loan, student loan or any debt incurred through fraud. Any council tax arrears where the council has not sent a reminder can be chased, as well as any payments you have to make for damages for personal injury. If you have deductions to pay bills from your universal credit, these will continue, and if you agreed to have a pre-payment meter installed before your moratorium, that meter can be installed. -You will also be expected to pay your ongoing bills during a standard moratorium. ------ -Another example is: "I’m about to get evicted by the bank but I don’t have anywhere to go. I’m worried as my employment contract says I might lose my job if I get a court judgment against me. Can you help me?" you could respond with: ------ -Debt answer: Most lenders will apply for a money judgment as well as possession, so you might need employment advice about your work contract. - -It’s important to know where you are in the eviction process. Before you are evicted your lender has to take you to court for a possession hearing. If the Judge gives the lender a possession order, you will be given a date to leave your home. On that date, if you do not move out, the lender will have to apply for a warrant of possession. That warrant allows bailiffs to return on a given date to evict you. If you do not leave they do have powers to use reasonable force to make you leave. If you have not yet been to court at all, you will have more opportunity to negotiate with the lender. If you feel able to, you should always contact your mortgage lender whatever the stage. - -If they have not yet taken you to court, they have a lot of rules to follow, and these continue up to actual possession. They might be able to help by agreeing a repayment plan, reducing your monthly payments temporarily if your income might increase in future, or by allowing you to miss payments for a few months (known as mortgage deferral). You would still have to make up these payments later. They might add your arrears on to the end of your mortgage, known as ‘capitalising’ arrears if you can afford to pay the slightly increased monthly amounts this would require. Always consider getting debt advice to help (link) - -As with any debt case, you should maximise your income as best you can (link to our pages) and also reduce non-essential expenditure where possible (link to our page). If you receive Universal Credit or another means tested benefit, you can apply to have some of the interest on your mortgage paid by an interest free loan, called support for mortgage interest. You have to apply for this support and will usually have to wait 13 weeks before it is paid, or 9 months on legacy benefits, like JSA, ESA or income support. If you get pension credit, payments start straight away. - -Assuming you agree you owe the mortgage and it was not incurred due to fraud or undue pressure, you should complete the defence form you are sent (called the N11M) if you are being taken to court for a possession hearing. You should also seek advice from a debt adviser or legal aid provider, if you qualify for legal aid, as your home is at risk. On the day of the hearing, you should also try to meet with the duty scheme solicitor at court. When completing the N11M you should check carefully whether the lender has included the right amount of arrears as they sometimes get this wrong if they add in other charges. You should return the N11M to the court, and send a copy to the lender’s solicitors, within 14 days of any hearing. If you miss this deadline, still send it in late. Even if you do not send it at all the court will let you take part in the hearing but they might make you pay more costs if they have to rearrange a hearing. - -You should complete the budget sheet on the N11M and prioritise paying your mortgage arrears. If you’re not sure how to prioritise your debts, you can read about this on our advice pages (link) and get advice from a debt adviser (link). If you are able to make an offer to pay the arrears, you should do so before the court hearing. The lender might agree to stop the court hearing, or at least agree to ask for suspended possession, based on you paying what you have offered alongside regular payments. This means you will not lose your home so long as the payments are made. In any case, you should start to pay what you can afford. Usually the court will give you up to the end of your agreement term to pay arrears back, but you should try to pay more quickly if possible. - -There are also lots of rules a lender has to follow before going to court. If they have not given you the chance to negotiate payments at all, or have refused offers that you think are reasonable, or if you have a complaint with them that has not been dealt with, you should raise this in section 27 of the N11M. The court might agree to rearrange (known as adjourning) the hearing for the lender to engage with you. Likewise, if you have made an application for support for mortgage interest and can prove this, alongside showing you can make the payments to cover anything SMI does not cover, you should raise this. The lender may have been wrong to have started the claim and the court might adjourn it. - -If you do not think you can pay your arrears back within the term of your agreement, or you cannot afford to pay the monthly contractual payments, it is more likely the court will agree to repossession. You might be able to apply for something called a time order in these circumstances, to ask the court to extend the period you pay back for, or to lower the interest rate to make payments affordable. You should get advice on this first though. With a time order the court can also consider more circumstances than just whether you can afford a particular amount, for example, whether an illness has caused the arrears or if a lender has behaved unfairly towards you by adding lots of charges or refusing offers that would have controlled the arrears earlier. They will decide what is ‘just’ in all of the circumstances although that might still mean giving possession to the lender. - -If you have already been to court and you are referring to the date that you are to be evicted, the situation is more urgent. If this is the date the court gave at the possession hearing, you do not have to leave on that day. If you do not leave, the lender will apply to court for a warrant to use bailiffs to forcibly evict you at a later date. You should get legal advice if possible, certainly if you qualify for legal aid (link). As you have nowhere to go, you could consider: - -● Applying on form N244 to suspend the possession date, or thee actual eviction, but you will have to show that you can make payments towards the arrears and maintain the contractual monthly payments (£14 unless you get fee remission - link) -● Apply on form N244 (£14 unless fee remission - link) and seek a time order if you are unable to make an offer that will cover the arrears and monthly payment, or need interest to be reduced, or the term of the agreement extending to make things affordable -● If the home is simply unaffordable, negotiate with the lender for more time maybe to sell, or see if they will help you sell it in a controlled way -● You should only hand the keys back to the lender as a last resort as you will still be liable for the mortgage, insurances and bills - -On the day of any eviction, the bailiffs that the court will use, are allowed to use reasonable force and are likely to change the locks on your door. They should give you time to remove your goods and you should act quickly as soon as you get any notice of an eviction date. - -If your home is repossessed and sold at auction you are likely to get much less for it. It might not even cover the mortgage debt(s) and your lender will be able to chase you for the remainder of the debt. - -Finally, you might be able to get something called a ‘breathing space.’ This is free but you need to apply with the help of a debt adviser who will assess whether you are eligible and whether it is appropriate. You can find out more about Breathing Space here (link). Importantly: - -● breathing space will stop and enforcement of your mortgage for 60 days -● if you have a hearing listed, that can still go ahead and a court might still grant possession, but it cannot be enforced for 60 days -● if you are due to be evicted by bailiffs, this will also be paused for 60 days - -If you are receiving mental health crisis treatment you might be able to get a breathing space that lasts as long as your treatment, plus 30 days. Again a debt adviser will discuss this with you. - -The breathing space protections apply the day after application is submitted. Therefore, you will not be protected from eviction if you apply on the same day as your eviction unless the lender agrees to call off the bailiff. - -Employment: If you have been employed less than 2 years your employer can dismiss you for any reason - whether it’s fair or not. If you have more than 2 years service your employer can only dismiss you if it’s fair to do so - an employment tribunal would have to decide whether it was fair if you made a complaint to them. It might be fair if it was important for your work that you have no county court judgments against you, for example if you are responsible for finance or money at work. Get advice about whether it would be fair in your own case. - -Housing: If you are homeless or threatened with homelessness within 56 days then you can make a homelessness application to your Local Authority. It depends where you are in the process - a notice has been served or a possession order/warrant of eviction has been obtained to determine whether you will be accepted as homeless or threatened with homelessness. - -You can in theory make a homelessness application to any Local Authority however the Local Authority will consider whether you have a local connection to the area (you have lived in the area 6/12 months or 3 ⁄ 5 years, employment, family associations etc) when considering what further duties they owe you. - -The distinction between the both is that with “threatened with homelessness” the Local Authority would try and keep you in the property by preventing homelessness. This will depend on the amount of arrears and will usually include a referral for debt advice and following the advice the debt team have given above. With “homelessness” they will look to assist you to secure accommodation. - -If it is clear that homelessness cannot be prevented, then a homelessness application should be accepted. In order to carry out enquiries, the Local Authority must have reason to believe you may be homeless and may be eligible (this is purposely a lower threshold). Eligibility is ascertaining if someone has a recourse to public funds. - -You should be placed on a “relief duty” which is time limited for 56 days. The Local Authority should complete a housing needs assessment and personalised housing plan. If the client falls into a priority need category (has dependent children, vulnerable as a result of some special reason etc) they will be provided interim accommodation. If they do not fall into a priority need category, they will not be offered accommodation during the 56 relief duty period. - -As the end of the relief duty 56 day period approached, the Local Authority must satisfy themselves that the applicant is:- - -● Eligible -● Homeless -● In priority need -● Has a local connection -● Is unintentionally homeless - -For them to proceed to “main duty.” - -Main duty is not time limited and the burden is on the Local Authority to find you a permanent offer of accommodation. You will remain in interim accommodation and the Local Authority will need to find you a suitable offer of social or private rented accommodation. - -When considering “intentionality” the Local Authority Homelessness Officer must consider whether the mortgage arrears were a “deliberate act or omission.” Factors that can be used to argue an act was not deliberate would be unaffordability, increase in interest rates etc. - -If you are deemed to be intentionally homeless then you would not proceed to a main duty and the Local Authority would have little to no obligation to find you accommodation. If you are in priority need and are in interim accommodation, they will give you “reasonable time” to vacate which could be days or weeks. There are different rules for when someone is still owed a housing duty where they have been found intentionally homeless. - -You can also at the same time make a housing allocations application, either in tandem with the homelessness application or standalone. Some allocation policies exclude homeowners or give them very little priority however if the house is repossessed you may not have these barriers. - -You may look at finding suitable private rented accommodation. Most letting agents carry out credit checks and therefore it may be difficult to obtain private rented accommodation. ------ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to debt is also likely to be advised on benefits and tax -credits, utilities, communications and energy supplier issues, charitable support (such as grants) and -food banks. You must think step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/education.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/education.py deleted file mode 100644 index 51ec3e9..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/education.py +++ /dev/null @@ -1,9 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to education is also likely to be advised on -benefits and tax credits, universal credit, charitable support (such as grants) and food banks, -debt and utilities, communications and energy supplier issues as we all debt. You must think -step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/employment.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/employment.py deleted file mode 100644 index 9e1e7d4..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/employment.py +++ /dev/null @@ -1,56 +0,0 @@ -PROMPT = """ -For example, if the question is "I am about to return to work after maternity leave, but I -can’t continue working evenings and weekends because of childcare issues. My employer has -rejected my flexible working request on the basis that all staff have to work evenings and -weekends. Is this fair and what are my rights in this situation?" you could respond with: ------ -You are entitled to make a flexible working request to your employer to vary your terms and -conditions of employment to suit your needs. Your employer must follow a fair process and -can only refuse your request on certain grounds. You have the right to appeal against this decision. - -If your employer turned down your flexible working request on the basis that the same workplace -rules apply to everyone regardless of their circumstances, you might be able to show this is -discriminatory because the rule about working evenings and weekends has a bigger impact on you -because you have childcare or caring responsibilities. ------ -Another example is: "I’ve been dismissed for redundancy after 22 years of employment. How much redundancy pay am I entitled to receive from my employer? Am I entitled to any other payments? I am 64 years old on the date of dismissal and my average weekly earning were £650" you could respond with: ------ -You are entitled to £19,290 statutory redundancy pay as a minimum amount, your contract of employment may say that you are entitled to more. - -You can check this using the Gov.uk Redundancy Pay calculator and by asking your employer if you are entitled to contractual redundancy pay. - -You are also entitled to be paid wages up to the date of dismissal and any accrued but untaken holiday pay. You are entitled to receive 12 weeks notice, which the employer can either make you work or make a payment in lieu of notice - there may be other contractual payments due on dismissal, depending on the terms and conditions of employment. ----- -Another example is: "My client is abMy client is about to return to work after maternity leave, but she can’t continue working evenings and weekends because of childcare issues. Her employer has rejected her flexible working request on the basis that all staff have to work evenings and weekends. Is this fair and what are my client’s rights in this situation?" you could respond with: ------ -You are entitled to make a flexible working request to your employer to vary your terms and conditions of employment to suit your needs. Your employer must follow a fair process and can only refuse your request on certain grounds. You have the right to appeal against this decision. - -If your employer turned down your flexible working request on the basis that the same workplace rules apply to everyone regardless of their circumstances, you might be able to show this is discriminatory because the rule about working evenings and weekends has a bigger impact on you because you have childcare or caring responsibilities. - -If your employer refuses your flexible working request ------ -Another example is: "My client’s employer has refused to allow her to take paid time off on holiday and isn’t paying her correctly for all of the hours that she works. I want to know more about her employment rights and options in this situation. Does the fact that she is employed on a Health and Social Care Visa make any difference to your advice?" you could respond with: ------ -You are entitled to be paid correctly for all hours worked in accordance with your contract of employment. Failure to do so can be treated as a breach of contract or an unauthorised deductions from wages. It can also be a breach of the National Minimum Wage rules if your pay is below the minimum rate the law says you should be paid for your age group. - -You are also entitled to be paid at your normal rate of pay when you take holiday. The amount of paid holiday you are entitled to is a minimum of 28 days each year. In your first year of employment, your employer only has to pay you for as many days you have built up when you take your holiday. - -If your employer hasn’t paid you correctly for wages or holiday pay, you should speak to them about it. If this doesn’t work, you should make a formal complaint, known as a grievance. If you are still not satisfied, you can make a claim to an employment tribunal, but you must take action within 3 months of the last date that you were not paid correctly. - -If your complaint is about the National Minimum Wage, you can make a complaint to the Government’s National Minimum Wage Enforcement team. - -You can read more about what to do If your employer hasn’t paid you what they owe you - -Because you are on a Health and Social Care Visa, your right to work and live in the UK is linked to your sponsor employer. Sometimes complaints about employment rights can lead to problems with your employer, possibly causing the withdrawal of your Visa. - -You should speak to a Citizens Advice adviser about your situation before you decide to take action about your problems with wages. ------ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. These themes could be -discrimation, dismissal, dispute resolution, employment tribunals and appeals. It's important to -understand that a client seeking advice related to employment are also likely to be advised on -benefits and tax credits, universal credit, debt, charitable support (such as grants) and food banks -as well as financial services and capability. You must think step-by-step about the question -identifying any evidence of these present in the query and formulate your response to the advisor -accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/financial_services_and_capability.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/financial_services_and_capability.py deleted file mode 100644 index 4199add..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/financial_services_and_capability.py +++ /dev/null @@ -1,8 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to financial services and capability is also -likely to be advised on benefits and tax credits, debt, utilities, communications and energy -supplier issues. You must think step-by-step about the question identifying any evidence -of these present in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/gva_and_hate_crime.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/gva_and_hate_crime.py deleted file mode 100644 index 8e15d3c..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/gva_and_hate_crime.py +++ /dev/null @@ -1,8 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to gender based violence and hate crimes is -also likely to be advised on relationships and family, benefits and tax credits, housing, legal -and universal credit. You must think step-by-step about the question identifying any evidence -of these present in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/health_and_community_care.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/health_and_community_care.py deleted file mode 100644 index fa96225..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/health_and_community_care.py +++ /dev/null @@ -1,8 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to health and community care are also likely -to recieve advice on benefits and tax credits, universal credit, charitable support (such as -grants), housing and debt. You must think step-by-step about the question identifying any -evidence of these present in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/housing.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/housing.py deleted file mode 100644 index 9ac9be5..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/housing.py +++ /dev/null @@ -1,37 +0,0 @@ -PROMPT = """ -For example, if the question is "I am a part time cleaner. I rent my house in Birmingham from my -employer. He and his wife own the house but they are going through a divorce. My contract is for a -fixed term of five years and ends on 06/06/2024. There isn’t a break clause but I really want to -leave now if I find suitable accommodation. My employer has said that I can stay until the end of the -fixed term but that I might need to leave earlier if he needs to sell the house as part of the divorce. -Can I leave without a financial penalty?" you could respond with: ------ -Is the client a service occupier? Probably not as it is not necessary to live in accommodation for -better performance of her duties. - -What is the client's security of tenure? She is an assured shorthold tenant. - -How can the tenancy be lawfully ended? -Surrender: requires agreement of all the parties including the employer's wife. -Client’s NTQ: not possible at the moment as there is no break clause. It can be used once the fixed -term expires. -Client can leave on the last day of the fixed term. -Section 21 notice can only be used by LL on expiry of the fixed term. - -Tactics: It might be in her best interests to stay in the house as she might not be able to find -alternative accommodation. ----- -Another example is: "I am a single mother with two children ages 11 and 14. I made a homelessness application to Dacorum Borough Council as I was evicted from my private rental property due to rent arrears. I have been talking to friends that say I could be found intentionally homeless because of the rent arrears. Is this right?" you could respond with: ------ -The client could be intentionally homeless if the rent arrears were due to a deliberate act or omission. Look at whether the rent was affordable. Even if it was affordable, look at whether the client was on benefits and these hadn’t yet been paid which lead to the arrears. - -Also check to see if accommodation was reasonable for her to continue to occupy. For example, if she was at risk of domestic abuse in the accommodation, she wouldn’t be intentionally homeless even if the rent arrears were her fault. ------ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to housing are also likely to be advised on -benefits and tax credits, universal credit, debt, charitable support (such as grants) and -food banks as well as utilities, communications and energy supplier issues. You must think -step-by-step about the question identifying any evidence of these present in the query and -formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/immigration_and_asylum.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/immigration_and_asylum.py deleted file mode 100644 index 2a39c31..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/immigration_and_asylum.py +++ /dev/null @@ -1,36 +0,0 @@ -PROMPT = """ -For example, if the question is "Ive had pre-settled status for 5 years in January next year. -I want to know what I do next. Ive lived in the UK since 2018." you could respond with: ------ -You may apply for EU Settled status after you have had 5 years continuous residence in the UK. -Residence is broken if you have spent 6 months or more outside the UK in any 12 month period. -You are allowed a longer absence for important reasons such as COVID, pregnancy or military service. -You should take advice if you have had longer absences to see if an exception applies. - -As you have already spent 5 years in the UK you can apply immediately. You should ensure that you -apply before your pre-settled status expires. The Home Office will automatically extend your pre-settled -status for 2 years in the month before it expires if you have not yet got settled status, whether you -have applied or not. - -You can apply online. You will need to scan your passport using the 'EU Exit: ID Document Check' -app using an Android phone, or an iPhone 7 or above. Automatic checks of HMRC and DWP records may -confirm your residence. If not you will need to upload other documents. There is no fee for the -application. - -EU Settled status entitles you to stay in the UK indefinitely, and you can be absent for up to 5 -years without losing it. You will be entitled to claim most benefits on the same basis as a British -citizen and without having to prove you have an EU right to reside. Youll usually be able to apply for -citizenship 12 months after youve got settled status. ----- -Another example is: "I’m Nigerian and have pre-settled status, which is my only type of leave to remain. Can I claim Universal Credit, and will it affect my immigration status? " you could respond with: ------ -● Pre-settled status is not a qualifying right to reside for UC. To get UC, you will need to have a qualifying right to reside. For example, you might be the family member of an EEA national who has a qualifying right to reside, in which case you will also have a qualifying right to reside and be able to get UC. -● Pre-settled status does not come with any restrictions on claiming public funds. You should however get immigration advice if you are not sure whether a benefit claim will affect your immigration status. ------ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to immigration and asylum are also likely to -be advised on benefits and tax credits, universal credit, charitable support and food banks as well -as housing. You must think step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/legal.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/legal.py deleted file mode 100644 index 160b7e2..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/legal.py +++ /dev/null @@ -1,8 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to legal issues are also likely to be advised -on benefits and tax credits, relationships and family, housing, debt and universal credit. You must think -step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/relationships_and_family.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/relationships_and_family.py deleted file mode 100644 index 252987b..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/relationships_and_family.py +++ /dev/null @@ -1,98 +0,0 @@ -PROMPT = """ -For example, if the question is "My husband has hurt me. What can I do? I am very -worried about what might happen if he knows I have sought advice, or if I have to go to court." -you could respond with: ------ -Explain that domestic abuse is not just physical but can also include controlling, threatening -and coercive behaviour -Explain that at any time if she feels in immediate danger she must call the police. -Establish whether she wishes to remain in the home or move elsewhere with the children - given -the house is owned it may be tactically better to remain if divorce proceedings are to follow but -there may be financial considerations - assuming she wants to stay -It would be possible to apply for a non molestation order and occupation order - explanation of what -these orders are, how she is eligible (ie the law Pt IV FLA 1996) and how they operate, no fees etc -Advise that an ex parte order would be appropriate if she is concerned as to his reaction and how that -works ie without notice to him -Advise that as there is domestic abuse, she may be eligible for legal aid subject to means and merits. -Explain that legal aid may have to be paid back later via the statutory charge. -To apply for a non mol / occ order either refer to Resolution to find a local lawyer (legal aid if eligible) -or can apply via CourtNav on GOV or make an application herself on FL401 etc. Given there are likely -to be wider issues eg divorce, children finances etc explain legal advice would be best if possible. -Explain about going to court - the special measures that can be put in place and the ban on cross -examination in person and possible IDVA support -Signpost local support service for DA or orgs via CA page. -Regarding the risk to the children, advise on possible S.8 Children Act 1989 proceedings (child -arrangements orders) . Explain the welfare principle and checklist. Explain the no order principle. -Advise on prohibited steps application to prevent possible removal. Advise re potential eligibility -for legal aid as a result of DA evidence via GP subject to means /merits. Advise seeking further legal -advice recommended. Explain the relevance of the children’s ages in ascertaining their wishes. Advise -on the role of Cafcass . Explain court procedure and the possibility of a fact finding hearing in view -of the DA allegations. Explain mediation MIAM required before Children applications but potentially be -exempt given the DA allegations ----- -Another example is: "I’ve escaped a physically abusive partner but they’ve left me with loads of debt. I’m scared they’ll come after me if I don’t pay so how can I protect myself?" you could respond with: ------ -I’ve escaped a physically abusive partner but they’ve left me with loads of debt. I’m scared they’ll come after me if I don’t pay so how can I protect myself? - -Debt answer: Firstly, you’re only responsible for a debt legally if your name is either on the contract, or you’re liable for a bill in law, for instance because you live at a property and have to pay council tax. - -The debts you might still be responsible for in law could be (these are examples, there may be others): -● Loans or overdrafts in joint names -● Any contract in your name -● Council tax because you are one of the people liable at the time of the bill (find out who is liable for council tax - link) -● Water as you were living at the property at the time -● Gas and electricity as you either had your name on the contract, or you never changed the contract after moving in to a property - -Where there is joint liability, both you and your ex-partner are liable to pay. The creditor (the company or organisation you owe money to) can ask both of you to pay at the same time. They cannot collect twice the amount of debt, but do not have to split the debt 50/50%. - -Debts you are not legally liable to pay (these are examples, there maybe others): -● Debts that were take in your name, fraudulently using your ID -● Debt in your name but where you were forced to borrow under the threat of violence or emotional pressure -● Bills where you were not the liable person such as gas or electricity when only your ex-partner was named on the bill -● Council tax where your ex-partner lived with you and had a greater legal interest in the house, for instance they owned the house in their name, or they were your landlord, or a tenant but sublet to you - -You should get debt advice to look at all of your debts to see what you are legally liable for. In any case, where you feel able to, or with help, you can approach creditors to explain the situation. Any creditor that provided a loan that was fraudulently borrowed will investigate the fraud. They may need to get a police crime reference number although that is not essential. - -If you want to challenge a debt because you were put under pressure, you should get advice on this. You should get legal advice if you are able to but might have to pay for this. Usually, you will need evidence to say what happened, and show that you did not gain anything from the borrowing at all. This can be quite complicated, but each creditor should consider the complaint in full and sensitively. If the creditor has an ombudsman you can then refer the complaint to the ombudsman, for instance the Financial Ombudsman Service (FOS) for loans and other credit. You can see how to complain to an ombudsman here (link). They are all free services. - -Your creditors cannot give out your current address as this would break data protection law. If you feel able to, you should tell your creditors to only write to you at your new address or to write to a safe PO Box (you can find out how to open a safe mailbox or how to redirect post - link). - -Your bank will also have processes to help you open a new account or stop access to your account for your abuser. They can also de-link you from an account if you prefer, and remove an abuser as a named card holder on any credit cards. Surviving Economic Abuse has some great advice on their site (link). - -It is understandable that you might pay the debts that you are not responsible for, where you are really scared for your safety. If you did decide not to challenge any debts that you are not liable for, a debt adviser can look at your options. With some options, like bankruptcy, Debt Relief Orders and IVAs, your name is usually put on a public register along with your address. However, you can apply to court for a Person at Risk of Violence order (PARV) where there is a risk to the safety of you or your family. This is a court order that makes sure your details are not added to the register, or any court files. You do have to apply to court, and there is a fee (fee remission - link). You have to give a witness statement and only the court decides whether to give the order. - -You should also contact the credit reference agencies (CRAs) - these are Experian, Transunion and Equifax. You should add a notice of correction to your reports to say you no longer have any financial association with your ex-partner, and that you are an abuse survivor. Your ex-partner cannot access your credit reports. If you are worried about ongoing fraud, you could also pay to join CIFAS’ protective registration service (link). This is an extra service that credit lenders and banks will check before lending money. They will carry out additional checks to ensure the person applying for credit is who they say they are. It may slow down your own credit applications, but it will not affect your credit score, or day to day spending on cards. - -Finally, even if you feel you are liable for some debts, telling creditors about your situation might help, if you feel able. All types of creditors have rules and policies about how they collect debts, and most will have policies about how they treat people in vulnerable circumstances. For example, all banks and loan companies must have policies in place. Councils will have their own guidance on council tax collection that might say, for example, never to use bailiffs to collect from a person who has escaped domestic violence. - -You can get debt advice from (link). In addition Money Advice Plus is an organisation that has a specialist advice service for survivors of domestic abuse (link). - -Family Answer: -Further information would be needed to establish whether the parties have been married - if so and divorce proceedings are to follow there are separate applications that can be made for financial provision . Whilst the family court cannot change who has responsibility for the debts (see debt answer) they can make property adjustment, capital lump sum payment orders and periodical payment orders which might assist with debt repayments if appropriate. - -Assuming the partners are unmarried. - -The answer needs to include the following: -● Physical abuse can be reported to the police - if in immediate danger call 999 -● Economic abuse, as well as the physical abuse, now also comes within the definition of ‘Domestic Abuse’ following the Domestic abuse Act 2021 s1(4) “Economic abuse” means any behaviour that has a substantial adverse effect on B’s ability to— -(a) acquire, use or maintain money or other property, or -(b) obtain goods or services -So if pressure was exerted to take out the debt or in terms of ongoing payment this may fall under the definition, also if the ex partner continues to run up debt in the client's name. -● Economic abuse is not a criminal offence in itself but the behaviour of pressuring into debt, forcing repayment, or causing ongoing debt could be considered Coercive Control which is a criminal offence (explanation of requirements - personally connected/serious effect on you/abuser knew or ought to have known of effect) -● If no longer living together (or were not living together at all) the behaviour would have to have happened since the 5 April 2023 or whilst they were living together to amount to a criminal offence but other remedies are still available -● Therefore the coercive control could potentially be reported to the police alongside the physical abuse. -● Protection can also be sought from the family courts - It would be possible to apply for a non molestation order - explanation expected of what these orders are, how she is eligible (ie the law Pt IV FLA 1996) and how they operate, no fees etc -● Advise that an ex parte order (without notice to the abuser) would be appropriate if she is concerned that she is in immediate danger and needs urgent protection -● Advise that as there is domestic abuse, she may be eligible for legal aid subject to means and merits . Explain that legal aid may have to be paid back later via the statutory charge. -● To apply for a non mol order either refer to Resolution to find a local lawyer (legal aid if eligible) or can apply via CourtNav on GOV or make an application herself on FL401 etc (forms on GOV.UK). Explain legal advice would be best if possible. -● As she has escaped her partner and scared he will come after her she needs to make sure her address is not included on the application or witness statements - she can complete Form C8 to apply separately to the court for her address to be withheld -● Explain about going to court - the special measures that can be put in place and the ban on cross examination in person and possible IDVA support -● Signpost local support services for DA or orgs via CA page or other appropriate signposting ------ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to relationships and family are also likely to be -advised on benefits and tax credits, legal issues, universal credit, housing and debt. You must think -step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/tax.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/tax.py deleted file mode 100644 index 0879a7a..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/tax.py +++ /dev/null @@ -1,9 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to tax are also likely to be advised on benefits -and tax credits, debt, universal credit, financial services and capability as well as utilities, -communications and energy suppliers. You must think -step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/travel_and_transport.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/travel_and_transport.py deleted file mode 100644 index 2452a0e..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/travel_and_transport.py +++ /dev/null @@ -1,9 +0,0 @@ -PROMPT = """ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to travel and transport are also likely to -be advised on benefits and tax credits, charitable support (such as grants) and food banks, -universal credit, debt and utilities, communications and energy supplier issues. You must think -step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/utilities_and_communications.py b/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/utilities_and_communications.py deleted file mode 100644 index d7057d5..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/advice_area/utilities_and_communications.py +++ /dev/null @@ -1,71 +0,0 @@ -PROMPT = """ -For example, if the question is "My energy bill is much higher than I thought it should be. -Is my meter faulty?" you could respond with: ------ -You shouldn't assume that there is a fault with the meter, because your bill is higher than expected. -Meter faults happen, but they are very rare. It’s a good idea to check first if there are other reasons -that may explain the increase. - -The first thing you’ll need to check is if your bill is accurate. You should check whether your bill is -the bill estimated. It will have an E next to the reading in your bill if it is. If your bill closes on -an estimate, it may be that it has been overestimated. Even if you’ve got a smart meter, it’s a good idea -to check - your smart meter might not have been sending meter readings to the supplier. - -You should also check whether you are billed for the right meter. If you’ve switched suppliers, compare -the meter reference number from their old supplier’s bill to their new supplier’s bill. Otherwise you’ll -need to find the meter reference number on your network operator’s website and compare it. - -It’s also a good idea to compare the meter reading on the meter to the one you’ve got on the bill. If it’s -similar, then you are probably billed for the correct usage. Check this on the meter and not your In Home -Display. You can compare this with other bills and see whether your usage has gone up considerably. There -might be reasons for this, like someone has started working from home, cold weather or a new appliance. - -If it isn’t usage and the bill is accurate you’ll need to look at whether there are any reasons for the -ost going up. It might be that a fixed tariff has come to an end and your unit rates or daily charges -(standing charges) have increased. - -If you can’t find any other reason for the increase in cost, then your meter might be faulty. This is -very rare, but it can happen. To check whether it may be faulty you can start by switching off all -electrical appliances in the home at the consumer unit and switch off power to the boiler. You should -check if the numbers on the meter's display are still moving - if they are, the meter might be faulty. -If your gas meter is still moving there could be a gas leak you should call the National Gas Emergencies -number on 0800 111 999 from outside of the property. -If you think your meter is faulty, complain to your supplier. They should investigate it within 5 working -days and tell you what action they’ll take. If they take the meter out to be tested they might charge you. -If your meter is found to be faulty they’ll refund you. You should ask your supplier about any costs -that may be involved in getting the meter tested. - -Follow up questions -Do they have a two rate meter? If so, do they know how to read the meter -Are they able to afford to make the payments? If not, they may need a repayment plan or debt advice -Is your supplier asking for any payments that are from more than 12 months ago? ----- -Another example is: "I’m thinking about getting some energy efficiency measures installed privately. What do I need to think about before going ahead with any work?" you could respond with: ------ -Energy efficiency answer -One of the first things to think about is your budget. You also need to consider which measures are suitable for your home and if you’re thinking about more than one measure, what’s best to do first. - -Your home’s Energy Performance Certificate (EPC) should tell you where your home’s energy efficiency needs improving and the approximate cost. You can work out the ‘payback period’ by dividing the cost of the work by the yearly saving in your energy bills. If you own your home, you can get recommendations for improvements you can make to your home on GOV.UK. -Check if your mortgage provider offers any mortgage products linked to making energy efficiency improvements to your home. -If you live in an older home, there are some extra things you might need to think about before making changes to your home. Find out more about energy efficiency and older houses on the Historic England website. -If you’re a leaseholder, you might need to get permission from the owner of the freehold before you make any improvements. You can find out about making changes to your leasehold property on the Leasehold Advisory Service website. -Contact your local council to check if there are support schemes or energy advice agencies in your area that can help. Find your local council's contact details on GOV.UK. -You can also: -● get advice on the Energy Saving Trust website -● get advice on the Centre for Sustainable Energy website -Consumer answer -It’s important to use a reputable installer so you can trust them and to help protect you if anything goes wrong. The Microgeneration Certification (MCS) scheme is a quality mark for low carbon heating (for example, heat pumps) and renewable energy generation (for example, solar panels). Using an MCS certified installer ensures that equipment meets good standards of performance and that installers are technically safe and competent. You can find an MCS certified installer by using their ‘find an installer’ search. - -TrustMark is the government approved quality scheme. You can find a TrustMark installer by using their ‘find a business’ search. - -Both MCS and TrustMark have dispute resolution processes which can help if anything does go wrong. - -If you’re paying for the work yourself, think about how you pay for it. It’s worth using a credit card so you can benefit from what’s called s75 protection if something does go wrong. This means your card provider is jointly responsible - with the installer - for resolving the problem. You can read more about this on Citizens Advice website Getting your money back if you paid by card or Paypal. ------ -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be -cross-cutting - this means that the question will have multiple themes. It's important to -understand that a client seeking advice related to utilities and communications, benefits and tax -credits, debt, charitable support (such as grants) and food banks as well as consumer goods -and services. You must think step-by-step about the question identifying any evidence of these present -in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/default_template.py b/caddy_chatbot/src/caddy_core/utils/prompts/default_template.py deleted file mode 100644 index f28ad3d..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/default_template.py +++ /dev/null @@ -1,68 +0,0 @@ -CADDY_PROMPT_TEMPLATE = """ -You are a friendly and helpful AI assistant at Citizens Advice, a charity in the United Kingdom that gives advice to citizens. \ -Advisors at Citizens Advice need to help citizens of the United Kingdom who come to Citizens Advice with a broad range of issues. \ -Your role as an AI assistant is to help the advisors with answering the questions that are given to them by citizens. You are not a replacement for adviser judgement \ -but you can help advisers make more informed decisions. You are truthful and create action points for the advisor from a range of sources where you provide specific details \ -from its context. If you don't know the answer to a question, truthfully says that you don't know, rather than making up an answer. - -Use the coverage area information to provide geographically relevant advice for the adviser that you are providing guidance to, as well as utilising the current date to inform the adviser when infomation may be out of date -or would mean that a service or programme is not available at this time. - -This adviser has clients in this coverage area: {office_regions} -Current day of the week, date and time is: {day_date_time} - -You MUST provide inline citations to relevant content used from the documents by using SOURCE_URL in place of x for x \ -For example https://www.gov.uk/disability-benefits-helpline -Utilise the content inbetween the tags to provide these citations in your answer: - -{context} - -Based on the above information provided in the documents, provide a concise answer with citations for the advisers question. Make sure to include reference to any location names \ -stated in the question, and make sure your answer is relevant to the laws and rules of the location specified in the question. Using the current date \ -to ensure that any deadlines have not already passed. - -You are delivering your response to the adviser. \ -If the question discusses 'my client', your answer should refer to 'your client'. \ -You can refer to the documents as 'information available' \ - -If more information is needed to definitively answer the question, number a step by step set of questions that the adviser should ask the client to find out this missing information. \ -And use language like 'could be' instead if 'is' - in the list of questions, use simple language. Under each numbered question, identidy the possible answers and explain what the \ -the advisor needs to do depending on the answer. It's important for consistency that you ALWAYS follow this format. - -Take particular note of the advice issue specific guidance in the tags below: - -{route_specific_augmentation} - - -YOU MUST ANSWER THE QUESTION FIRST AS BEST AS YOU CAN, CITING THE REFERENCES USED, BEFORE SUGGESTING QUESTIONS TO ASK THE CLIENT. - -In your answer, use bold and HTML formatting to highlight the most question-relevant parts in your response. - -Provide a Brief Summary response at the top with a clear one line response to the question. Enclosed \ -in tags. Example Brief Summary:Client is not eligible for UC - -Adviser: {input} -Assistant:""" - - -CADDY_FALLBACK_EXAMPLE = """For example, if the question is "My client has moved into a leasehold flat and has to pay service charges of £40 per week. They receive Universal Credit, can they get help to pay \ -the charges?" you could respond with: ------ -Your client has moved into a leasehold flat and has to pay service charges of £40 per week. As they receive Universal Credit, they may be able to get help with paying the \ -service charges. - -To determine if your client can get help, you need to find out: - - - If your client bought the property under the Right to Buy scheme. If so, they may have the right to a loan to help pay the repairs element of the service charge. They would \ -need to claim this within 6 weeks of receiving the service charge demand. - - If your client's landlord is a local authority, registered social landlord or private registered provider of social housing. If so, the landlord may be able to assist your client by purchasing a share in the leasehold flat. This would reduce or cancel the service charge. Your client can contact their landlord for more information. - - If your client is having trouble paying the service charges, they could speak to their work coach about getting a Universal Credit budgeting advance. This is an interest-free loan that helps cover emergency household costs. - - If the service charges put your client into debt or rent arrears, they may be able to get help from the council. The council might give extra money if the Universal Credit housing element does not cover all housing costs. - - So in summary, there are several options your client could explore to get assistance with paying service charges, including loans, their landlord purchasing a share in the property, extra money from the council, or Universal Credit budgeting advances. Let me know if you need any clarification or have additional questions. ----- -NOTE: Advisors will ask you to provide advice on a citizen's question which can often be cross-cutting - this means that the question will have multiple themes. \ -It's important to understand that an issue related to a disabled person falling behind on their energy bills relates to \ -energy, debt, benefits as well as disability-based discrimination. You must think step-by-step about the question to indetify \ -the these present in the query and formulate your response to the advisor accordingly -""" diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/issues_map.py b/caddy_chatbot/src/caddy_core/utils/prompts/issues_map.py deleted file mode 100644 index de2b3b1..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/issues_map.py +++ /dev/null @@ -1,37 +0,0 @@ -from caddy_core.utils.prompts.advice_area import ( - benefits_and_tax_credits, - benefits_and_universal_credit, - charitable_support_and_food_banks, - consumer_goods_and_services, - debt, - education, - employment, - financial_services_and_capability, - gva_and_hate_crime, - health_and_community_care, - housing, - immigration_and_asylum, - legal, - relationships_and_family, - tax, - travel_and_transport, - utilities_and_communications, -) - -BENEFITS_AND_TAX_CREDITS = benefits_and_tax_credits.PROMPT -BENEFITS_AND_UNIVERSAL_CREDIT = benefits_and_universal_credit.PROMPT -CHARITABLE_SUPPORT_AND_FOOD_BANKS = charitable_support_and_food_banks.PROMPT -CONSUMER_GOODS_AND_SERVICES = consumer_goods_and_services.PROMPT -DEBT = debt.PROMPT -EDUCATION = education.PROMPT -EMPLOYMENT = employment.PROMPT -FINANCIAL_SERVICES_AND_CAPABILITY = financial_services_and_capability.PROMPT -GVA_AND_HATE_CRIME = gva_and_hate_crime.PROMPT -HEALTH_AND_COMMUNITY_CARE = health_and_community_care.PROMPT -HOUSING = housing.PROMPT -IMMIGRATION_AND_ASYLUM = immigration_and_asylum.PROMPT -LEGAL = legal.PROMPT -RELATIONSHIPS_AND_FAMILY = relationships_and_family.PROMPT -TAX = tax.PROMPT -TRAVEL_AND_TRANSPORT = travel_and_transport.PROMPT -UTILITIES_AND_COMMUNICATIONS = utilities_and_communications.PROMPT diff --git a/caddy_chatbot/src/caddy_core/utils/prompts/prompt.py b/caddy_chatbot/src/caddy_core/utils/prompts/prompt.py deleted file mode 100644 index b2acba6..0000000 --- a/caddy_chatbot/src/caddy_core/utils/prompts/prompt.py +++ /dev/null @@ -1,50 +0,0 @@ -from caddy_core.services.router import get_route -from caddy_core.utils.prompts import issues_map - -from caddy_core.utils.prompts.default_template import ( - CADDY_FALLBACK_EXAMPLE, -) - - -def retrieve_route_specific_augmentation(query): - route = get_route(query).name - - match route: - case "benefits_and_tax_credits": - route_specific_augmentation = issues_map.BENEFITS_AND_TAX_CREDITS - case "benefits_and_universal_credit": - route_specific_augmentation = issues_map.BENEFITS_AND_UNIVERSAL_CREDIT - case "charitable_support_and_food_banks": - route_specific_augmentation = issues_map.CHARITABLE_SUPPORT_AND_FOOD_BANKS - case "consumer_goods_and_services": - route_specific_augmentation = issues_map.CONSUMER_GOODS_AND_SERVICES - case "debt": - route_specific_augmentation = issues_map.DEBT - case "education": - route_specific_augmentation = issues_map.EDUCATION - case "employment": - route_specific_augmentation = issues_map.EMPLOYMENT - case "financial_services_and_capability": - route_specific_augmentation = issues_map.FINANCIAL_SERVICES_AND_CAPABILITY - case "gva_and_hate_crime": - route_specific_augmentation = issues_map.GVA_AND_HATE_CRIME - case "health_and_community_care": - route_specific_augmentation = issues_map.HEALTH_AND_COMMUNITY_CARE - case "housing": - route_specific_augmentation = issues_map.HOUSING - case "immigration_and_asylum": - route_specific_augmentation = issues_map.IMMIGRATION_AND_ASYLUM - case "legal": - route_specific_augmentation = issues_map.LEGAL - case "relationships_and_family": - route_specific_augmentation = issues_map.RELATIONSHIPS_AND_FAMILY - case "tax": - route_specific_augmentation = issues_map.TAX - case "travel_and_transport": - route_specific_augmentation = issues_map.TRAVEL_AND_TRANSPORT - case "utilities_and_communications": - route_specific_augmentation = issues_map.UTILITIES_AND_COMMUNICATIONS - case _: - route_specific_augmentation = CADDY_FALLBACK_EXAMPLE - - return route_specific_augmentation diff --git a/caddy_chatbot/src/integrations/google_chat/responses.py b/caddy_chatbot/src/integrations/google_chat/responses.py index cea1e99..123eaf4 100644 --- a/caddy_chatbot/src/integrations/google_chat/responses.py +++ b/caddy_chatbot/src/integrations/google_chat/responses.py @@ -393,7 +393,7 @@ def control_group_selection(control_group_message, caddy_message) -> dict: "buttonList": { "buttons": [ { - "text": "Forward query to supervisor", + "text": "I still need help, forward query to supervisor, then complete survey", "onClick": { "action": { "function": "handle_control_group_forward", @@ -407,7 +407,7 @@ def control_group_selection(control_group_message, caddy_message) -> dict: }, }, { - "text": "Complete control survey", + "text": "I no longer need help. Complete survey", "onClick": { "action": { "function": "control_group_survey", diff --git a/caddy_chatbot/src/integrations/google_chat/structures.py b/caddy_chatbot/src/integrations/google_chat/structures.py index 01c9775..2137c3c 100644 --- a/caddy_chatbot/src/integrations/google_chat/structures.py +++ b/caddy_chatbot/src/integrations/google_chat/structures.py @@ -523,6 +523,21 @@ def get_post_call_survey_card( section = {"widgets": []} button_section = {"buttonList": {"buttons": []}} + copy_button = { + "text": "Copy caddy message", + "onClick": { + "action": { + "function": "copy_caddy_response", + "parameters": [ + {"key": "threadId", "value": thread_id}, + {"key": "event", "value": event}, + ], + } + }, + } + + button_section["buttonList"]["buttons"].append(copy_button) + i = 0 for question_dict in post_call_survey_questions: i += 1 @@ -589,7 +604,9 @@ def create_card(self, llm_response) -> Dict: reference_links_section = {"header": "Reference links", "widgets": []} - urls = re.findall(r"(http[s]?://[^>]+)", llm_response) + urls = re.findall( + r"(?:SOURCE_URL:)?(http[s]?://[^>]+)", llm_response + ) processed_urls = [] ref = 0 @@ -606,9 +623,14 @@ def create_card(self, llm_response) -> Dict: resource = "Citizens Advice" ref = ref + 1 + llm_response = llm_response.replace( f"{url}", f'[{ref} - {resource}]' ) + llm_response = llm_response.replace( + f"SOURCE_URL:{url}", + f'[{ref} - {resource}]', + ) reference_link = { "textParagraph": { @@ -855,8 +877,8 @@ def create_approved_card( Returns: Supervisor approved card """ - card["cardsV2"][0]["card"]["sections"].append( - self.responses.approval_json_widget(approver, supervisor_notes) + card["cardsV2"][0]["card"]["sections"].insert( + 0, self.responses.approval_json_widget(approver, supervisor_notes) ) return card @@ -920,7 +942,7 @@ def received_approval(self, event): approved=True, approval_timestamp=event["eventTime"], user_response_timestamp=datetime.now(), - supervisor_message=None, + supervisor_message=supervisor_notes, ) return user_email, user_space, thread_id, approval_event @@ -997,7 +1019,7 @@ def handle_supervisor_rejection(self, event) -> None: supervisor_message=supervisor_message, ) - caddy.store_approver_event(rejection_event) + caddy.store_approver_event(thread_id, rejection_event) def create_updated_supervision_card( self, supervision_card, approver, approved, supervisor_message @@ -1214,7 +1236,7 @@ def handle_supervisor_approval(self, event): thread_id, approval_event, ) = self.received_approval(event) - caddy.store_approver_event(approval_event) + caddy.store_approver_event(thread_id, approval_event) def continue_existing_interaction(self, event): """ diff --git a/caddy_chatbot/src/integrations/microsoft_teams/__init__.py b/caddy_chatbot/src/integrations/microsoft_teams/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/caddy_chatbot/src/integrations/microsoft_teams/content.py b/caddy_chatbot/src/integrations/microsoft_teams/content.py new file mode 100644 index 0000000..3cd31e0 --- /dev/null +++ b/caddy_chatbot/src/integrations/microsoft_teams/content.py @@ -0,0 +1,180 @@ +from typing import List, Dict +import re + +CADDY_PROCESSING = [ + { + "type": "Container", + "items": [ + { + "type": "TextBlock", + "text": f"🦉 Processing request...", + "weight": "bolder", + "size": "medium", + }, + ], + }, +] + + +def create_pii_detected_card(query: str) -> List[Dict]: + """ + Takes a message query and returns a PII Detected field with optional redaction input + """ + PII_DETECTED = [ + { + "type": "RichTextBlock", + "inlines": [ + { + "type": "TextRun", + "text": "PII Detected", + "color": "attention", + "weight": "bolder", + }, + { + "type": "TextRun", + "text": " Please ensure all queries to Caddy are anonymised.", + "italic": True, + }, + ], + }, + { + "type": "RichTextBlock", + "id": "buttonText", + "inlines": [ + { + "type": "TextRun", + "text": "Choose whether to proceed anyway or edit your original query", + } + ], + }, + { + "type": "ActionSet", + "id": "redactionButtons", + "actions": [ + { + "type": "Action.Execute", + "title": "Proceed without redaction", + "verb": "proceed", + "data": {"action": "proceed"}, + }, + { + "type": "Action.ToggleVisibility", + "title": "Edit original query", + "targetElements": [ + {"elementId": "queryText", "isVisible": True}, + {"elementId": "redactedQuerySubmission", "isVisible": True}, + {"elementId": "redactionButtons", "isVisible": False}, + {"elementId": "buttonText", "isVisible": False}, + ], + }, + ], + }, + {"type": "Input.Text", "id": "queryText", "isVisible": False, "value": query}, + { + "type": "ActionSet", + "id": "redactedQuerySubmission", + "isVisible": False, + "actions": [ + { + "type": "Action.Execute", + "title": "Submit Redaction", + "verb": "redacted_query", + "data": {"action": "redacted_query"}, + }, + ], + }, + ] + return PII_DETECTED + + +def create_redacted_card(event) -> List[Dict]: + """ + Takes in a redaction event and created a redacted query card + """ + redacted_query = event["value"]["action"]["data"]["queryText"] + REDACTED = [ + { + "type": "RichTextBlock", + "inlines": [ + { + "type": "TextRun", + "text": "Query redacted: ", + "color": "good", + "weight": "bolder", + }, + {"type": "TextRun", "text": redacted_query, "italic": True}, + ], + } + ] + return REDACTED + + +def generate_response_card(llm_response): + """ + Creates a Teams Adaptive card given a Caddy response + """ + caddy_response = [ + {"type": "TextBlock", "text": llm_response, "wrap": True}, + {"type": "ActionSet", "id": "referenceLinks", "actions": []}, + { + "type": "ActionSet", + "id": "approvalButtons", + "actions": [ + { + "type": "Action.Execute", + "title": "👍", + "verb": "approved", + "data": {"action": "approved"}, + }, + { + "type": "Action.Execute", + "title": "👎", + "verb": "rejected", + "data": {"action": "rejected"}, + }, + ], + }, + ] + + pattern = r"(?:SOURCE_URL:)?(http[s]?://[^>]+)" + + urls = re.findall(pattern, llm_response) + + processed_urls = [] + ref = 0 + + for i, url in enumerate(urls): + if url in processed_urls: + continue + + if "gov.uk" in url: + resource = "GOV UK" + elif "citizensadvice.org.uk/advisernet" in url: + resource = "Advisernet" + elif "citizensadvice.org.uk" in url: + resource = "Citizens Advice" + + ref = ref + 1 + llm_response = llm_response.replace( + f"{url}", f"[{ref} - {resource}]({url})" + ) + llm_response = llm_response.replace( + f"SOURCE_URL:{url}", f"[{ref} - {resource}]({url})" + ) + + reference_link = { + "type": "Action.OpenUrl", + "title": f"{ref} - {url}", + "url": url, + } + caddy_response[1]["actions"].append(reference_link) + + processed_urls.append(url) + + llm_response = llm_response.replace("", "**").replace("", "**") + llm_response = llm_response.replace('', "_").replace( + "", "_" + ) + caddy_response[0]["text"] = llm_response + + return caddy_response diff --git a/caddy_chatbot/src/integrations/microsoft_teams/responses.py b/caddy_chatbot/src/integrations/microsoft_teams/responses.py new file mode 100644 index 0000000..e26892d --- /dev/null +++ b/caddy_chatbot/src/integrations/microsoft_teams/responses.py @@ -0,0 +1,7 @@ +from fastapi import status +from fastapi.responses import JSONResponse, Response + +# --- Status Responses --- # +NO_CONTENT = Response(status_code=status.HTTP_204_NO_CONTENT) +ACCEPTED = Response(status_code=status.HTTP_202_ACCEPTED) +OK = Response(status_code=status.HTTP_200_OK) diff --git a/caddy_chatbot/src/integrations/microsoft_teams/structures.py b/caddy_chatbot/src/integrations/microsoft_teams/structures.py new file mode 100644 index 0000000..66a6edb --- /dev/null +++ b/caddy_chatbot/src/integrations/microsoft_teams/structures.py @@ -0,0 +1,213 @@ +from .verification import get_access_token +from integrations.microsoft_teams import content, responses +from caddy_core.services.anonymise import analyse + +import requests + + +class MicrosoftTeams: + def __init__(self): + self.client = "Microsoft Teams" + self.access_token = get_access_token() + self.messages = content + self.responses = responses + self.reaction_actions = { + "like": self.handle_thumbs_up, + "dislike": self.handle_thumbs_down, + } # TODO check works in teams with the emojis + + def send_adviser_card(self, event, card=None): + """ + Takes an incoming request from Teams Chat and returns a given response card + """ + if card is None: + card = self.messages.CADDY_PROCESSING + + conversation_id = event["conversation"]["id"] + activity_id = event["id"] + service_url = event["serviceUrl"] + + response_url = ( + f"{service_url}/v3/conversations/{conversation_id}/activities/{activity_id}" + ) + + headers = { + "Authorization": f"Bearer {self.access_token}", + "Content-Type": "application/json", + } + + response_activity = { + "type": "message", + "from": event["recipient"], + "conversation": event["conversation"], + "recipient": event["from"], + "replyToId": activity_id, + "attachments": [ + { + "contentType": "application/vnd.microsoft.card.adaptive", + "content": { + "$schema": "http://adaptivecards.io/schemas/adaptive-card.json", + "type": "AdaptiveCard", + "version": "1.0", + "body": card, + }, + } + ], + } + + response = requests.post(response_url, json=response_activity, headers=headers) + + print(response.json()) + + def update_card(self, event, card=None): + """ + Updates an existing teams message given a card and action event + """ + if card is None: + card = self.messages.CADDY_PROCESSING + + conversation_id = event["conversation"]["id"] + activity_id = event["id"] + service_url = event["serviceUrl"] + reply_to_id = event["replyToId"] + + response_url = ( + f"{service_url}/v3/conversations/{conversation_id}/activities/{reply_to_id}" + ) + + headers = { + "Authorization": f"Bearer {self.access_token}", + "Content-Type": "application/json", + } + + response_activity = { + "type": "message", + "from": event["recipient"], + "conversation": event["conversation"], + "recipient": event["from"], + "replyToId": activity_id, + "attachments": [ + { + "contentType": "application/vnd.microsoft.card.adaptive", + "content": { + "$schema": "http://adaptivecards.io/schemas/adaptive-card.json", + "type": "AdaptiveCard", + "version": "1.0", + "body": card, + }, + } + ], + } + + response = requests.put(response_url, json=response_activity, headers=headers) + + print(response.json()) + + def format_message(self, event): + """ + Receives a message from Microsoft Teams and formats it into a Caddy message event + """ + message_string = event["text"].replace("@Caddy", "") + + if "proceed" not in event: + pii_identified = analyse(message_string) + + if pii_identified: + # Optionally redact PII from the message by importing redact from services.anonymise + # message_string = redact(message_string, pii_identified) + + self.send_adviser_card( + event=event, + card=self.messages.create_pii_detected_card(message_string), + ) + + return "PII Detected" + + self.send_adviser_card(event) + + # TODO Format Message into Caddy event + return message_string + + def handle_reaction_added(self, event): + """ + Handles reactions added to a message, specifically for the sueprvisor space but currently applied to all + """ + reaction_type = event["reactionsAdded"][0]["type"] + reply_to_id = event["replyToId"] + + # Fetch original message or log activity based on reply_to_id if needed + response_text = ( + f"Reaction '{reaction_type}' added to message with ID {reply_to_id}" + ) + self.send_advisor_message_from_supervisor(event, response_text) + + # TODO define a send_advisor_message_from_supervisor methods + # TODO return caddy message from supervisor channel to advisor + + def handle_reaction_removed(self, event): + """ + Handles reactions removed from a message, currently unsure if we need this + """ + reaction_type = event["reactionsRemoved"][0]["type"] + reply_to_id = event["replyToId"] + + # Fetch original message or log activity based on reply_to_id if needed + + response_text = ( + f"Reaction '{reaction_type}' removed from message with ID {reply_to_id}" + ) + self.send_advisor_message_from_supervisor(event, response_text) + + def handle_thumbs_up(self, event, removed=False): + """ + Handle thumbs up reaction = an approval from supervisor + """ + action = "removed" if removed else "added" + self.send_advisor_message_from_supervisor( + event, + f"Message approved {action} for message with ID {event['replyToId']}", + "share", + ) + + def handle_thumbs_down(self, event, removed=False): + """ + Handle thumbs down reaction = no approval from supervisor, caddy message not sent + """ + action = "removed" if removed else "added" + self.send_advisor_message_from_supervisor( + event, + f"Answer not approved {action} for message with ID {event['replyToId']}", + "donotshare", + ) + + def send_advisor_message_from_supervisor(self, event, text, type): + """ + Sends a simple text message in response to an event. + """ + + if type == "donotshare": + print("No approval from supervisor") + + conversation_id = event["conversation"]["id"] + service_url = event["serviceUrl"] + + response_url = f"{service_url}/v3/conversations/{conversation_id}/activities" + + headers = { + "Authorization": f"Bearer {self.access_token}", + "Content-Type": "application/json", + } + + response_activity = { + "type": "message", + "from": event["recipient"], + "conversation": event["conversation"], + "recipient": event["from"], + "text": text, + } + + response = requests.post(response_url, json=response_activity, headers=headers) + + print(response.json()) + + # TODO make this have the details from caddy and the supervisor comments diff --git a/caddy_chatbot/src/integrations/microsoft_teams/verification.py b/caddy_chatbot/src/integrations/microsoft_teams/verification.py new file mode 100644 index 0000000..03af34f --- /dev/null +++ b/caddy_chatbot/src/integrations/microsoft_teams/verification.py @@ -0,0 +1,32 @@ +import os +import requests + +APP_ID = os.environ.get("MicrosoftAppId", "") +APP_PASSWORD = os.environ.get("MicrosoftAppPassword", "") + +url = "https://login.microsoftonline.com/botframework.com/oauth2/v2.0/token" +headers = { + "Host": "login.microsoftonline.com", + "Content-Type": "application/x-www-form-urlencoded", +} + +authentication_data = { + "grant_type": "client_credentials", + "client_id": APP_ID, + "client_secret": APP_PASSWORD, + "scope": "https://api.botframework.com/.default", +} + + +def get_access_token(): + """ + Fetches an access token using the Bot credentials + """ + response = requests.post(url, headers=headers, data=authentication_data) + + if response.status_code == 200: + response_data = response.json() + access_token = response_data.get("access_token") + return access_token + else: + print("Failed to retrieve token:", response.text) diff --git a/caddy_chatbot/src/model/1_Pooling/config.json b/caddy_chatbot/src/model/1_Pooling/config.json deleted file mode 100644 index 02da4df..0000000 --- a/caddy_chatbot/src/model/1_Pooling/config.json +++ /dev/null @@ -1,10 +0,0 @@ -{ - "word_embedding_dimension": 768, - "pooling_mode_cls_token": false, - "pooling_mode_mean_tokens": true, - "pooling_mode_max_tokens": false, - "pooling_mode_mean_sqrt_len_tokens": false, - "pooling_mode_weightedmean_tokens": false, - "pooling_mode_lasttoken": false, - "include_prompt": true -} diff --git a/caddy_chatbot/src/model/README.md b/caddy_chatbot/src/model/README.md deleted file mode 100644 index 2dd37d1..0000000 --- a/caddy_chatbot/src/model/README.md +++ /dev/null @@ -1,177 +0,0 @@ ---- -language: en -license: apache-2.0 -library_name: sentence-transformers -tags: -- sentence-transformers -- feature-extraction -- sentence-similarity -- transformers -datasets: -- s2orc -- flax-sentence-embeddings/stackexchange_xml -- ms_marco -- gooaq -- yahoo_answers_topics -- code_search_net -- search_qa -- eli5 -- snli -- multi_nli -- wikihow -- natural_questions -- trivia_qa -- embedding-data/sentence-compression -- embedding-data/flickr30k-captions -- embedding-data/altlex -- embedding-data/simple-wiki -- embedding-data/QQP -- embedding-data/SPECTER -- embedding-data/PAQ_pairs -- embedding-data/WikiAnswers -pipeline_tag: sentence-similarity ---- - - -# all-mpnet-base-v2 -This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. - -## Usage (Sentence-Transformers) -Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: - -``` -pip install -U sentence-transformers -``` - -Then you can use the model like this: -```python -from sentence_transformers import SentenceTransformer -sentences = ["This is an example sentence", "Each sentence is converted"] - -model = SentenceTransformer('sentence-transformers/all-mpnet-base-v2') -embeddings = model.encode(sentences) -print(embeddings) -``` - -## Usage (HuggingFace Transformers) -Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. - -```python -from transformers import AutoTokenizer, AutoModel -import torch -import torch.nn.functional as F - -#Mean Pooling - Take attention mask into account for correct averaging -def mean_pooling(model_output, attention_mask): - token_embeddings = model_output[0] #First element of model_output contains all token embeddings - input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() - return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) - - -# Sentences we want sentence embeddings for -sentences = ['This is an example sentence', 'Each sentence is converted'] - -# Load model from HuggingFace Hub -tokenizer = AutoTokenizer.from_pretrained('sentence-transformers/all-mpnet-base-v2') -model = AutoModel.from_pretrained('sentence-transformers/all-mpnet-base-v2') - -# Tokenize sentences -encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') - -# Compute token embeddings -with torch.no_grad(): - model_output = model(**encoded_input) - -# Perform pooling -sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']) - -# Normalize embeddings -sentence_embeddings = F.normalize(sentence_embeddings, p=2, dim=1) - -print("Sentence embeddings:") -print(sentence_embeddings) -``` - -## Evaluation Results - -For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=sentence-transformers/all-mpnet-base-v2) - ------- - -## Background - -The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised -contrastive learning objective. We used the pretrained [`microsoft/mpnet-base`](https://huggingface.co/microsoft/mpnet-base) model and fine-tuned in on a -1B sentence pairs dataset. We use a contrastive learning objective: given a sentence from the pair, the model should predict which out of a set of randomly sampled other sentences, was actually paired with it in our dataset. - -We developped this model during the -[Community week using JAX/Flax for NLP & CV](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104), -organized by Hugging Face. We developped this model as part of the project: -[Train the Best Sentence Embedding Model Ever with 1B Training Pairs](https://discuss.huggingface.co/t/train-the-best-sentence-embedding-model-ever-with-1b-training-pairs/7354). We benefited from efficient hardware infrastructure to run the project: 7 TPUs v3-8, as well as intervention from Googles Flax, JAX, and Cloud team member about efficient deep learning frameworks. - -## Intended uses - -Our model is intented to be used as a sentence and short paragraph encoder. Given an input text, it ouptuts a vector which captures -the semantic information. The sentence vector may be used for information retrieval, clustering or sentence similarity tasks. - -By default, input text longer than 384 word pieces is truncated. - - -## Training procedure - -### Pre-training - -We use the pretrained [`microsoft/mpnet-base`](https://huggingface.co/microsoft/mpnet-base) model. Please refer to the model card for more detailed information about the pre-training procedure. - -### Fine-tuning - -We fine-tune the model using a contrastive objective. Formally, we compute the cosine similarity from each possible sentence pairs from the batch. -We then apply the cross entropy loss by comparing with true pairs. - -#### Hyper parameters - -We trained ou model on a TPU v3-8. We train the model during 100k steps using a batch size of 1024 (128 per TPU core). -We use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with -a 2e-5 learning rate. The full training script is accessible in this current repository: `train_script.py`. - -#### Training data - -We use the concatenation from multiple datasets to fine-tune our model. The total number of sentence pairs is above 1 billion sentences. -We sampled each dataset given a weighted probability which configuration is detailed in the `data_config.json` file. - - -| Dataset | Paper | Number of training tuples | -|--------------------------------------------------------|:----------------------------------------:|:--------------------------:| -| [Reddit comments (2015-2018)](https://github.com/PolyAI-LDN/conversational-datasets/tree/master/reddit) | [paper](https://arxiv.org/abs/1904.06472) | 726,484,430 | -| [S2ORC](https://github.com/allenai/s2orc) Citation pairs (Abstracts) | [paper](https://aclanthology.org/2020.acl-main.447/) | 116,288,806 | -| [WikiAnswers](https://github.com/afader/oqa#wikianswers-corpus) Duplicate question pairs | [paper](https://doi.org/10.1145/2623330.2623677) | 77,427,422 | -| [PAQ](https://github.com/facebookresearch/PAQ) (Question, Answer) pairs | [paper](https://arxiv.org/abs/2102.07033) | 64,371,441 | -| [S2ORC](https://github.com/allenai/s2orc) Citation pairs (Titles) | [paper](https://aclanthology.org/2020.acl-main.447/) | 52,603,982 | -| [S2ORC](https://github.com/allenai/s2orc) (Title, Abstract) | [paper](https://aclanthology.org/2020.acl-main.447/) | 41,769,185 | -| [Stack Exchange](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml) (Title, Body) pairs | - | 25,316,456 | -| [Stack Exchange](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml) (Title+Body, Answer) pairs | - | 21,396,559 | -| [Stack Exchange](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml) (Title, Answer) pairs | - | 21,396,559 | -| [MS MARCO](https://microsoft.github.io/msmarco/) triplets | [paper](https://doi.org/10.1145/3404835.3462804) | 9,144,553 | -| [GOOAQ: Open Question Answering with Diverse Answer Types](https://github.com/allenai/gooaq) | [paper](https://arxiv.org/pdf/2104.08727.pdf) | 3,012,496 | -| [Yahoo Answers](https://www.kaggle.com/soumikrakshit/yahoo-answers-dataset) (Title, Answer) | [paper](https://proceedings.neurips.cc/paper/2015/hash/250cf8b51c773f3f8dc8b4be867a9a02-Abstract.html) | 1,198,260 | -| [Code Search](https://huggingface.co/datasets/code_search_net) | - | 1,151,414 | -| [COCO](https://cocodataset.org/#home) Image captions | [paper](https://link.springer.com/chapter/10.1007%2F978-3-319-10602-1_48) | 828,395| -| [SPECTER](https://github.com/allenai/specter) citation triplets | [paper](https://doi.org/10.18653/v1/2020.acl-main.207) | 684,100 | -| [Yahoo Answers](https://www.kaggle.com/soumikrakshit/yahoo-answers-dataset) (Question, Answer) | [paper](https://proceedings.neurips.cc/paper/2015/hash/250cf8b51c773f3f8dc8b4be867a9a02-Abstract.html) | 681,164 | -| [Yahoo Answers](https://www.kaggle.com/soumikrakshit/yahoo-answers-dataset) (Title, Question) | [paper](https://proceedings.neurips.cc/paper/2015/hash/250cf8b51c773f3f8dc8b4be867a9a02-Abstract.html) | 659,896 | -| [SearchQA](https://huggingface.co/datasets/search_qa) | [paper](https://arxiv.org/abs/1704.05179) | 582,261 | -| [Eli5](https://huggingface.co/datasets/eli5) | [paper](https://doi.org/10.18653/v1/p19-1346) | 325,475 | -| [Flickr 30k](https://shannon.cs.illinois.edu/DenotationGraph/) | [paper](https://transacl.org/ojs/index.php/tacl/article/view/229/33) | 317,695 | -| [Stack Exchange](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml) Duplicate questions (titles) | | 304,525 | -| AllNLI ([SNLI](https://nlp.stanford.edu/projects/snli/) and [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/) | [paper SNLI](https://doi.org/10.18653/v1/d15-1075), [paper MultiNLI](https://doi.org/10.18653/v1/n18-1101) | 277,230 | -| [Stack Exchange](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml) Duplicate questions (bodies) | | 250,519 | -| [Stack Exchange](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml) Duplicate questions (titles+bodies) | | 250,460 | -| [Sentence Compression](https://github.com/google-research-datasets/sentence-compression) | [paper](https://www.aclweb.org/anthology/D13-1155/) | 180,000 | -| [Wikihow](https://github.com/pvl/wikihow_pairs_dataset) | [paper](https://arxiv.org/abs/1810.09305) | 128,542 | -| [Altlex](https://github.com/chridey/altlex/) | [paper](https://aclanthology.org/P16-1135.pdf) | 112,696 | -| [Quora Question Triplets](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs) | - | 103,663 | -| [Simple Wikipedia](https://cs.pomona.edu/~dkauchak/simplification/) | [paper](https://www.aclweb.org/anthology/P11-2117/) | 102,225 | -| [Natural Questions (NQ)](https://ai.google.com/research/NaturalQuestions) | [paper](https://transacl.org/ojs/index.php/tacl/article/view/1455) | 100,231 | -| [SQuAD2.0](https://rajpurkar.github.io/SQuAD-explorer/) | [paper](https://aclanthology.org/P18-2124.pdf) | 87,599 | -| [TriviaQA](https://huggingface.co/datasets/trivia_qa) | - | 73,346 | -| **Total** | | **1,170,060,424** | diff --git a/caddy_chatbot/src/model/config.json b/caddy_chatbot/src/model/config.json deleted file mode 100644 index e85d249..0000000 --- a/caddy_chatbot/src/model/config.json +++ /dev/null @@ -1,24 +0,0 @@ -{ - "_name_or_path": "sentence-transformers/all-mpnet-base-v2", - "architectures": [ - "MPNetModel" - ], - "attention_probs_dropout_prob": 0.1, - "bos_token_id": 0, - "eos_token_id": 2, - "hidden_act": "gelu", - "hidden_dropout_prob": 0.1, - "hidden_size": 768, - "initializer_range": 0.02, - "intermediate_size": 3072, - "layer_norm_eps": 1e-05, - "max_position_embeddings": 514, - "model_type": "mpnet", - "num_attention_heads": 12, - "num_hidden_layers": 12, - "pad_token_id": 1, - "relative_attention_num_buckets": 32, - "torch_dtype": "float32", - "transformers_version": "4.38.1", - "vocab_size": 30527 -} diff --git a/caddy_chatbot/src/model/config_sentence_transformers.json 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-##華 -##葉 -##藤 -##行 -##街 -##西 -##見 -##訁 -##語 -##谷 -##貝 -##貴 -##車 -##軍 -##辶 -##道 -##郎 -##郡 -##部 -##都 -##里 -##野 -##金 -##鈴 -##镇 -##長 -##門 -##間 -##阝 -##阿 -##陳 -##陽 -##雄 -##青 -##面 -##風 -##食 -##香 -##馬 -##高 -##龍 -##龸 -##fi -##fl -##！ -##（ -##） -##， -##－ -##． -##／ -##： -##？ -##～ - diff --git a/example.env b/example.env index 1678af9..aa937e3 100644 --- a/example.env +++ b/example.env @@ -6,6 +6,8 @@ XDG_CACHE_HOME="/tmp" OPENSEARCH_HTTPS="http://opensearch:9200" OPENSEARCH_INDEX="caddy_vector_index" USERS_TABLE_NAME='caddyUsers' +ROUTES_TABLE_NAME="caddyRoutes" +PROMPTS_TABLE_NAME='caddyPrompts' OFFICES_TABLE_NAME='caddyOffices' MESSAGES_TABLE_NAME='caddyMessages' RESPONSES_TABLE_NAME='caddyResponses' @@ -14,3 +16,9 @@ CADDY_SERVICE_ACCOUNT={service_account_json} CADDY_GOOGLE_CLOUD_PROJECT="123456789" CADDY_SUPERVISOR_SERVICE_ACCOUNT={supervisor_service_account_json} CADDY_SUPERVISOR_GOOGLE_CLOUD_PROJECT="123456789" + +AWS_SESSION_TOKEN="" # Leave blank +TASK_ROLE_ARN="caddy-role-arn" + +MicrosoftAppId="" +MicrosoftAppPassword="" diff --git a/infra/template.yaml b/infra/template.yaml index 1d7a6d6..bf6e487 100644 --- a/infra/template.yaml +++ b/infra/template.yaml @@ -12,6 +12,12 @@ Parameters: UserTableName: Type: String Description: Name of the DynamoDB table for users + RoutesTableName: + Type: String + Description: Name of the DynamoDB table for routes + PromptsTableName: + Type: String + Description: Name of the DynamoDB table for prompts MessageTableName: Type: String Description: Name of the DynamoDB table for messages @@ -51,6 +57,12 @@ Parameters: OpensearchIndex: Type: String Description: Index for Opensearch + MicrosoftAppIdSecretArn: + Type: String + Description: Secret Arn for App Id for Teams integration + MicrosoftAppPasswordSecretArn: + Type: String + Description: Secret Arn for App password for Teams integration Resources: CaddyVPC: @@ -228,6 +240,10 @@ Resources: ValueFrom: !Ref CaddyServiceAccountSecretArn - Name: CADDY_SUPERVISOR_SERVICE_ACCOUNT ValueFrom: !Ref CaddySupervisorServiceAccountSecretArn + - Name: MicrosoftAppId + ValueFrom: !Ref MicrosoftAppIdSecretArn + - Name: MicrosoftAppPassword + ValueFrom: !Ref MicrosoftAppPasswordSecretArn Environment: - Name: MESSAGES_TABLE_NAME Value: !Ref MessageTableName @@ -235,6 +251,10 @@ Resources: Value: !Ref ResponsesTableName - Name: USERS_TABLE_NAME Value: !Ref UserTableName + - Name: ROUTES_TABLE_NAME + Value: !Ref RoutesTableName + - Name: PROMPTS_TABLE_NAME + Value: !Ref PromptsTableName - Name: OFFICES_TABLE_NAME Value: !Ref OfficesTableName - Name: EVALUATION_TABLE_NAME @@ -255,6 +275,8 @@ Resources: Value: !Ref CaddyGoogleCloudProject - Name: CADDY_SUPERVISOR_GOOGLE_CLOUD_PROJECT Value: !Ref CaddySupervisorGoogleCloudProject + - Name: TASK_ROLE_ARN + Value: !GetAtt CaddyRole.Arn LogConfiguration: LogDriver: awslogs Options: @@ -305,6 +327,10 @@ Resources: Principal: Service: ecs-tasks.amazonaws.com Action: sts:AssumeRole + - Effect: Allow + Principal: + AWS: !Sub arn:aws:iam::${AWS::AccountId}:role/CaddyRole-${StageName} + Action: sts:AssumeRole ManagedPolicyArns: - arn:aws:iam::aws:policy/service-role/AmazonECSTaskExecutionRolePolicy Policies: @@ -317,6 +343,7 @@ Resources: - ecr:GetAuthorizationToken - ecr:GetDownloadUrlForLayer - ecr:BatchGetImage + - sts:GetSessionToken Resource: '*' - PolicyName: !Sub CaddyLoggingPolicy-${StageName} PolicyDocument: @@ -369,6 +396,18 @@ Resources: - dynamodb:UpdateItem - dynamodb:GetItem Resource: !GetAtt EvaluationTable.Arn + - Effect: Allow + Action: + - dynamodb:Scan + Resource: !GetAtt RoutesTable.Arn + - Effect: Allow + Action: + - dynamodb:PutItem + - dynamodb:GetItem + - dynamodb:DeleteItem + - dynamodb:Scan + - dynamodb:UpdateItem + Resource: !GetAtt PromptsTable.Arn - PolicyName: !Sub BedrockInvokerPolicy-${StageName} PolicyDocument: Version: '2012-10-17' @@ -409,6 +448,34 @@ Resources: ReadCapacityUnits: 1 WriteCapacityUnits: 1 + RoutesTable: + Type: AWS::DynamoDB::Table + Properties: + TableName: !Ref RoutesTableName + AttributeDefinitions: + - AttributeName: name + AttributeType: S + KeySchema: + - AttributeName: name + KeyType: HASH + ProvisionedThroughput: + ReadCapacityUnits: 1 + WriteCapacityUnits: 1 + + PromptsTable: + Type: AWS::DynamoDB::Table + Properties: + TableName: !Ref PromptsTableName + AttributeDefinitions: + - AttributeName: PromptName + AttributeType: S + KeySchema: + - AttributeName: PromptName + KeyType: HASH + ProvisionedThroughput: + ReadCapacityUnits: 1 + WriteCapacityUnits: 1 + MessagesTable: Type: AWS::DynamoDB::Table Properties: diff --git a/poetry.lock b/poetry.lock index 5b06bed..6e5e392 100644 --- a/poetry.lock +++ b/poetry.lock @@ -140,6 +140,17 @@ doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphin test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] trio = ["trio (>=0.23)"] +[[package]] +name = "appnope" +version = "0.1.4" +description = "Disable App Nap on macOS >= 10.9" +optional = false +python-versions = ">=3.6" +files = [ + {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"}, + {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"}, +] + [[package]] name = "arrow" version = "1.3.0" @@ -159,6 +170,24 @@ types-python-dateutil = ">=2.8.10" doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"] test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"] +[[package]] +name = "asttokens" +version = "2.4.1" +description = "Annotate AST trees with source code positions" +optional = false +python-versions = "*" +files = [ + {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"}, + {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"}, +] + +[package.dependencies] +six = ">=1.12.0" + +[package.extras] +astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"] +test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"] + [[package]] name = "attrs" version = "23.2.0" @@ -198,21 +227,21 @@ dev = ["black (==24.4.2)", "coverage (==7.5.1)", "flake8 (==3.8.4)", "parameteri [[package]] name = "aws-sam-cli" -version = "1.118.0" +version = "1.120.0" description = "AWS SAM CLI is a CLI tool for local development and testing of Serverless applications" optional = false python-versions = "!=4.0,<=4.0,>=3.8" files = [ - {file = "aws_sam_cli-1.118.0-py3-none-any.whl", hash = "sha256:77c3c54424a78558af72f2eeec66621bba9ee30ff4a23be975ff0a119764435c"}, - {file = "aws_sam_cli-1.118.0.tar.gz", hash = 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b/tests/notebooks/copypaste.ipynb new file mode 100644 index 0000000..c746293 --- /dev/null +++ b/tests/notebooks/copypaste.ipynb @@ -0,0 +1,93 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Defaulting to user installation because normal site-packages is not writeable\n", + "Collecting pyperclip\n", + " Downloading pyperclip-1.8.2.tar.gz (20 kB)\n", + "Building wheels for collected packages: pyperclip\n", + " Building wheel for pyperclip (setup.py) ... \u001b[?25ldone\n", + "\u001b[?25h Created wheel for pyperclip: filename=pyperclip-1.8.2-py3-none-any.whl size=11136 sha256=8d39e47f855db2394786542c7d43c2c7d3f0536b0e6277120df73dd450432731\n", + " Stored in directory: /Users/max.hollingdale/Library/Caches/pip/wheels/0c/09/9e/49e21a6840ef7955b06d47394afef0058f0378c0914e48b8b8\n", + "Successfully built pyperclip\n", + "Installing collected packages: pyperclip\n", + "Successfully installed pyperclip-1.8.2\n", + "\u001b[33mWARNING: You are using pip version 21.2.4; however, version 24.0 is available.\n", + "You should consider upgrading via the '/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "pip install pyperclip\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import pyperclip\n", + "\n", + "text ='hello world'\n", + "\n", + "\n", + "pyperclip.copy(text)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "ename": "SyntaxError", + "evalue": "invalid syntax (2434926114.py, line 1)", + "output_type": "error", + "traceback": [ + "\u001b[0;36m Cell \u001b[0;32mIn[4], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m pyperclip version\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" + ] + } + ], + "source": [ + "pyperclip version" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tests/notebooks/topic_evaluation.ipynb b/tests/notebooks/topic_evaluation.ipynb new file mode 100644 index 0000000..77119b0 --- /dev/null +++ b/tests/notebooks/topic_evaluation.ipynb @@ -0,0 +1,644 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Topic modelling & Caddy performance evaluation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A note book to evaluate the messages recieved previously, categorise into topics and judge approval rate of those messages\n", + "\n", + "Looking for an output that shows performance across various topics as well as demand to support with corpus scraping and maintenance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Steps:\n", + "1) Locate data of historical messages / responses in download from s3\n", + "2) Use topic modelling to categorise the message / responses\n", + "3) Look at the approval rate of the messages " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Import all libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/max.hollingdale/Library/Caches/pypoetry/virtualenvs/caddy-chatbot-B-atQbAG-py3.12/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "import boto3\n", + "import os\n", + "import pandas as pd\n", + "import re\n", + "from bs4 import BeautifulSoup\n", + "from bertopic import BERTopic\n", + "from sentence_transformers import SentenceTransformer\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Step 1: Ingest data" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "session = boto3.Session()\n", + "credentials = session.get_credentials()\n", + "\n", + "# === Database Connections ===\n", + "dynamodb = boto3.resource(\"dynamodb\", region_name=\"eu-west-2\")\n", + "\n", + "# === Tables ===\n", + "responses_table = dynamodb.Table(\"caddyResponses-prod\")\n", + "\n", + "responses_data = responses_table.scan()['Items']\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Step 1a: Clean data" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "df_responses = pd.DataFrame(responses_data)\n", + "df_responses['Office'] = df_responses.apply(lambda x: str(x['approverEmail']).split('@')[-1], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "def clean_and_extract_urls(llm_response):\n", + "\n", + " # Step 1: Remove the tag and its attributes\n", + " cleaned_text = re.sub(r']*>', '', llm_response)\n", + " cleaned_text = re.sub(r'', '', cleaned_text)\n", + "\n", + " # Step 2: Extract and remove URLs\n", + " urls = re.findall(r'(.*?)', cleaned_text)\n", + " cleaned_text = re.sub(r'(.*?)', '', cleaned_text)\n", + "\n", + " # Step 3: Further cleaning (remove remaining HTML tags, line breaks, etc.)\n", + " cleaned_text = re.sub(r'<[^>]+>', '', cleaned_text) # Remove any other HTML tags\n", + " cleaned_text = cleaned_text.replace('\\\\n', ' ').strip() # Replace \\n with space and strip leading/trailing spaces\n", + "\n", + " return cleaned_text, urls\n", + "\n", + "df_responses[['cleaned_text', 'urls']] = df_responses['llmAnswer'].apply(lambda x: pd.Series(clean_and_extract_urls(x)))\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we have:\n", + "- cleaned text which is the response from each llm\n", + "- urls which is the rag documents returned\n", + "- office which is the office of the individual messaging from\n", + "- llmprompt which is the user query" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Step 2: Topic modelling" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Use bertopic as that is what consult ahve used and can ask them questions" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pros:\n", + "Works well with short texts.\n", + "No need to specify the number of topics in advance.\n", + "Can use pre-trained language models for embeddings.\n", + "\n", + "Cons:\n", + "Requires more computational resources.\n", + "More complex to set up compared to traditional methods." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Seeding approach" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Batches: 100%|██████████| 5/5 [00:00<00:00, 8.59it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Topic Count Name \\\n", + "0 -1 37 -1_the_to_if_your \n", + "1 0 34 0_the_universal_your_for \n", + "2 1 33 1_the_to_landlord_if \n", + "3 2 18 2_the_pip_to_your \n", + "4 3 14 3_to_the_uk_your \n", + "5 4 14 4_the_to_client_if \n", + "\n", + " Representation \\\n", + "0 [the, to, if, your, you, for, client, and, or,... \n", + "1 [the, universal, your, for, to, you, credit, i... \n", + "2 [the, to, landlord, if, your, notice, client, ... \n", + "3 [the, pip, to, your, if, for, they, and, clien... \n", + "4 [to, the, uk, your, if, they, for, in, child, ... \n", + "5 [the, to, client, if, your, and, complaint, se... \n", + "\n", + " Representative_Docs \n", + "0 [TL;DR Your client may be able to get help fro... \n", + "1 [Brief Summary: Your client's Universal Credit... \n", + "2 [Brief Summary: To determine if the section 21... \n", + "3 [TL;DR: Your client may be able to get their E... \n", + "4 [Based on the information provided, it seems y... \n", + "5 [Based on the information provided, here is my... \n" + ] + } + ], + "source": [ + "\n", + "seed_topic_list = [\n", + " [\"finance\", \"debt\", \"support\", \"benefits\", \"universal\", \"charity\"],\n", + " [\"tax\", \"threshold\", \"guidance\", \"council\"],\n", + " [\"immigration\", \"visa\", \"asylum\", \"UK\"],\n", + " [\"housing\", \"rent\", \"landlord\"],\n", + " [\"health\", \"nhs\", \"care\"],\n", + " [\"violence\", \"abuse\", \"controlling\", \"family\",\"children\", \"partner\"],\n", + " # ... add more seed topics\n", + "]\n", + "\n", + "# Initialize the sentence transformer model\n", + "sentence_model = SentenceTransformer('all-MiniLM-L6-v2')\n", + "\n", + "# Create embeddings\n", + "embeddings = sentence_model.encode(df_responses['cleaned_text'].tolist(), show_progress_bar=True)\n", + "\n", + "model = BERTopic(language=\"english\", seed_topic_list=seed_topic_list)\n", + "topics, probabilities = model.fit_transform(df_responses['cleaned_text'], embeddings=embeddings)\n", + "\n", + "# Display topics\n", + "print(model.get_topic_info())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Scatterplot of embeddings, want to show spread" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.decomposition import PCA\n", + "\n", + "# Reduce embeddings to 2D\n", + "pca = PCA(n_components=2)\n", + "doc_2d = pca.fit_transform(embeddings)\n", + "\n", + "plt.figure(figsize=(12, 8))\n", + "scatter = plt.scatter(doc_2d[:, 0], doc_2d[:, 1], c=topics, cmap='tab20')\n", + "plt.colorbar(scatter)\n", + "plt.title('Document Clusters')\n", + "plt.xlabel('PCA Component 1')\n", + "plt.ylabel('PCA Component 2')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Word cloud" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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6NMhoOD7la68fusRXntmDz5O/vIx0Jseh092kbpoldzg0Ht23fk5BhW1DPJnm2IV+vvvKMU5c7L9lQHG78bx/vIsTFwc4sLudzz26g/amStxOx5yOs5KMhhOYlo2mTQYVfcMTfO+V4/zTWyfJzfHna5oW45EkNqCqCw9RJbBYYWzbxsLCtLMYVg7TzmHZJjY2Nha2bWFhY9sWNjYKoCgqCgoK6vV/q4qKqujoigPt6oeqyB5HIYRYbhRFwenQ8XmcGIaFYVqY1uwTlcXi27ulmeffOs3YRGLKTHTf8ATHL/Rx3862vJ3rbNfk9hnTmjrjHfS5efCu9lkfx7YhHE3yysHzfO+VY/SNRBY0rngyw0vvn6NnKMwvPrOHuzevyWtAtZyMTcSxbAvbVukbmuD/+f77vH7o4ryPt6mlmooSX1621ElgsWzZZK0MGTNBxkqSNVMYdpaclSFjJUmZURJGhJQZI2elMe0chj0ZaJi2gWnlsDABBU1xoCv61eBBR1cdaDhwaV68ehCPFsSrBXGqHnTVga64cKoeXKoXl+ZFV5xSHk8IIZYoXVPZ2FzNzzy4jXgqQyKVJZXJkc2Z5AyTnGliGCY5wyJnTt5mXP13OmOQyU3f279UaZqK2+nA45r/bLZhWuSM28/6KkyuJORjhvcah37r/e01FQF2bGigo2+MxA3bkyzb4ifvn2X/9pa8JDjbts2HJ7pmzEHYuaGB+qqSWR9rIpbkhXdO84PXTjAcik37uqJAwOemPOjF7dRxOvTreQKpdI5QNEk8mZnyGMuyOXVpkL/6pw/JGSb37WjFswqraI2FE1iWzfhEgr/6pw+nBRWqouD1OPG6HTj0yeR3y7bJ5ozrf//WDYHjxtYayoPevIxNAotlwrQNUkaUpBklbcZJm3EiuVEmskOEcoPEsqMkzSgpM4ZhZ+98wHlwqp6rQUYJJY5KSp21lDpr8OsVeDQ/bs2PVwvi0QJo6updohRCiKXEoWvs3tjE7o1N128zTItUJkfiaqCRSGevfp7632e6hjh4+sq02eulqq48yCN3r2N8on5ejzcti86BcQ6f673t/dwuB/dsbaGmPDCv88xkW3sd+m1yBw7c1c5bH1+aEljYNhw528vQWIyG6tlf9N9KJJbixMUBUump26B0XeWpezfO+jiJVJY3P77E82+dmjGoqCz1sW5NNZvbatjUVktFiZegz41l2cSSaUbDcc50DHGua5jLPaOEY6kpj7/YPcq3f3oUr9vJni1rcOhzy/lY7kbDcVLpHD94/QSvfnTh+u0el4M1tWXUV5fQVFNKXWUQn8eJ06FjmCaReJqhsSj9oxFGxmMMjccwTIv2xkr8PldexiaBxZJlkzXTxI0wMWOMSHaEkUw349l+JrJDRLLD5OzMnQ+TR1krRdZKEckNM5j+JDp2qh6CVwONCmcjla41lDqqCTgq8OtlOFUPimyjEkKIJUPXVAJeFwHv7S8m/vmDsxw+14tpLY9Vi7aGCtoaKub9+HQ2xz+/d+aOgUXA6+LnHtnBnk1r5n2uudrYWkN7UyVD41FyNyRxJ1JZXj90kV/69J4Fn+PEpQFGQrFp1aDqKoPsuiEwvR3Tsjh9eZCfvHd22vYnBVjXXMXj+zfw5L2bqCr133LV54G72hkai/Liu2d58+NL0yp9nesc5vm3T1Fd5qe9qYrVtHFiOBTj/RNdfP+141iWjaooNNWVsW9rMwfuamdTW+1tt4nFkxm6Bycrc0XiKVrqK/JW0lcCiyUma6WYyA4Tzg4wnhlgNNPNSLqLUHagYCsRC5W1UoxlehnL9HKZj9EVJ2XOWqpcLVS51lDuqqfMWU+5sw6n6pVtU0IIIcQcOXSNh+5ey4mL/YSjn8zg5wyLt49c5nOP7lhQzoFpWRw63UMknpr2tYfuXofXPbudCKOhOG8evsS5ruFpX1vfXM2/+Mw+9m9vueN2NU1Vaagu5cufupvGmlL+5oVDdA2Epoz38Nle1jVVU10eIOifeynX5apveIJvvXCIWDKDoihsWVvHzz++kwO71+Jy3vnS3u91saW9ji3tdeRyBmoe+4RIYLEEWLZJwphgNNPNUKqD/tQFhtIdxHOhq3kQy4thZxnN9DCa6QEUfHopNe42GjwbqHG3Ue1uJuioQlPk6SeEEELM1t4tzdRVlhCJpa+vKti2TfdAiFOXB9i/rWXexx4aj3HhyvC0bVAup84je9fN6hiGaXHi4gAfneqe1sm8qszH5x7bwd6tzXPKgfF5nDywq41YIsNf/+ggEzcEPrFEhveOd7JtXR17tqxZNROXkXiaSHwyD6a1voyvfvYe9m1tntexHHnoDXIjubJbRDkrQzg7yGDqEoOpS/SnLjCe6Sv6FqfCskkYYTrjR7iSOE6Zs44693rqPGupc6+l1tOGruS/uY8QQgix0lSU+ti3dQ1d/eNTysGmswavHrzA3i3N804oP3a+j9FwfFr/781tNbTWz2572fhEguMX+xkci065XVEU7tvZzt6tzfNaVQn43Ny7o4UzHYO8/OH5KV/r6B3j+IV+NrbWEJxHA7rlzO3S+dKnds87qCgECSwWgWHlCGUH6Iofozt5iqHUZeJGCHvan/PKYtkm45k+xjN9XI59RLW7lWbfNlp8O6j3rEdTHBJgCCGEELfxyN71vPjeuSmBRc4wOXlxgIHRCI01pXM+ZjZncOx837QkaYAn792Erquzen+e3Lc/MK05W3W5n/3bmqkq8895bNfUVAS5b2crh850T9kKlskZnLw0wH07W9nSXjfv4y9HO9c38Ni+DYs9jCkksCgi0zaYyA7RET/KlfhxBlIXSZgTiz2sRZG2EvQkTzOYusSVxEmafVtp991NvXc9qrK6qjsIIYQQs9XWUMmWtlrGIwnMG7YbhaJJ3jvWyReemnt35+7BMF3942SyU5P0K0t97NmyBnUWQUU2Z9IzFKZ3KDzta5taa2iuK7tt1as7cTo0WuorWN9czUenuqd87VLPKD2DYTa11ua1BPBS95mHti25RoFSqqcIbNsiboQ4Fn6Z14e/wYdj3+dS/NCqDSpulLMz9CbP8NHYj3hz5Fu8N/odxjK3r8YhhBBCrFa6rvLkvRtx3bQ3PpXO8d7xTpLpuRd6OXa+j5FQfNrt+7e3zLpxWiSeonsgRDo7vYLYxpbJBOuFqqnws6m1Zvq5Yym6B8PEk+kZHrUyVZT42LG+YclVw5IViwIzbYPe5FlOhl+lO3maaG50sYe0JOXsDD3J0wynOxlMXWZzyQNsCOzHqXkWe2hCCCHEkrJ7cxONNSVc6h69vonatCx6BsOcvjzI3jnsuY+nMpy6PEg4mpxyu6aqPLZvA85Z9ogIR5Mzdtf2eZzUVZbgzUOX7IDXTWN1KQ5dm9LE0AZ6h8OEoimC/tVx3bC+uQqvZ+k1KJbAokBs2yZpRjkRfoXz0Q8YyXRh2sujDvhiylhJOuKHCWX7GUxdZHvpY9R62hd7WEIIIcSSEfS5ObB7LZ1941OqL0UTad4+cpk9W5pnPZN9uWeM3qHwtCpO69ZUsrapctZbi6KJDCMzNMOrKPES9LtntZ3qTjRNpSTgoSzgYSQ8dYVlaDw2Y6nclWrdmiq0JbjtSwKLAulNnuHQ+PP0Jc/Klqc5srEIZfuJT4QYzXSzueQAW0oO4FRXV7UHUTyWZRGeSHL+0hDdveOMjsWIxtLkcgaKouD1OKko99FYX876tTU01JfNqlZ4oYQnEpy7MEhn9xjDwxESySy5nIHDoeP1Oqko91NXU0JrcyVNDeV4vQufKRRCLC1P3rOR77x8jGjik+0/6WyO0x1D9I9MzDqJ+8TFfoZuquIEk70r/N7ZV21MprPTVj1gcsvOnRoxzoXf66Ki1DctsAhHk1O6kq90FaWz26JWbPN+Z+zrHOH/+eN/yudYisbldvA//8WvFuTYtm1xauINDoWeZzTdvSz7UCwVWStFd+I0kewIE9kh9lQ8i18vX+xhiRXEMC26e8d5461znD7Xz3g4QTyeJpXOkcuZWJYFKOi6itul4/O5KA16aWut4sD9G9i+pTEvy/snTvfy4ssnGQ8lgMkkxZ/7mbvZvXPqdoZQOMHrb5/j4McdjIxOBj+pVJacYU52X1UVdF3D7ZoMMAJ+DzVVAR56YCOPHti0qpIahVjp6qtKuHtLE28cunT9NtuG0VCMj053zyqwGI8kuHBlhEhiam5CwOti//aWaXkct5PO5Iglp5fL93qceZ2IcTm0GUvWRhNp0pncDI9YmQJe15LLr4AFBBbJWJojb5+/8x2XII8/f5HzjbJWig/HfsjpiTeYyE3vOCnmzsYinBvmWPhl4kaYfRU/Q7W7ZbGHJZY527ZJpnK88NJxXnvrLEPDUWLxWyX92eRyJrmcSSyeYWg4SlfPGCdP97H37lY+++xdNNSVLeiiPRxOcPJ0H4PDk/uTFUXhnn3t7NzWhHa1isrpc/185wcfc+Z8P+Fw8npzrBtZlk02a5DNGkRjaYaGo4yMRtmwrm5JvgEJIeZP01SeeWALb358iRtfDiLxNB+dusIz92/GfYdGdBeujNA7HMaypr6e7N7cRE25f9avG5ZtkzNMsrnpk6lOXVtQNaib6ZqGc4aAJ50xyBnWDI9YmSabDC69F/bVuRWqAO0iorlR3h75ey7FDpEypy8pioWwSZlRzkXfux5ctPp2LsklQDGz8WiSFz88S8fA+Jwep2sqm1tq+NyD2/M2Ftu2CU8k+fO/eotDRzuZiMx9T24mY9A3ECb0WoIr3WP82i8+wMb1teizTHKczRhjsTSZrIHX4+TQkS7+9jsfcu7CILkZ3rhvp6TEQ1Njmfy9CLEC7VzfQHNdOVcGQtdvM0yL7sEwZzqG2L256ZaPtW2bU5cG6Z8h4fqh3WvxeWa/Dcq27Gk5Gtc4HTq6lr8y8rqu4nRMP55hmpiWhW2zKiZSFEVZgmHFag0s8mw43cmbw9+iJ3mGnLV6Sp0VW85K0504QcqMkqqIsil4v/S8WCY6BsZ489hlLvTOrSqa06FhWFZeA4tEIsOf/teXOXz0yrSa7TD5huR2Oygr9eH1ODEMk3AkSTyexjSnzkokk1lOnu7jv/z5a/zebz3GxvV111cYFioSTZFO5+i8Msrff/cgZ88N3PKNW1FghgUMAKoqAqxrn16eUQix/HncDp64ZwN/+YMPp9w+Fo7zwYmu2wYWg2NROvpGSd6Ul7CmtowNLTUzXrzfzmK3+J18DVzsUYhVF1g4XQ5aN9bn7Xj9qYu8MfTX9KfOS9WnIjBtg6FUB++NfgfTNthScgBNWXVP42Xncv8Yg+NRMrm5/Y3YV5fX88Wybf78r9/i0JGuaTP/breDHVubeOyhTWxYV4vH40RVFGzbxjAsBoYm+OhwJ2+/f4Gh4U9WJQ3T4nLXCH/2l2/wh//q0zTUleZldSAaS9HdM84PXjjC6RuCCq/Xye6dzezY2sTa1mpKSjy4XQ6yWYOx8Thd3WOcPtfPqbP9xGIp6mtLqaspWfB4hBBLj6ooPL5/I9964eMpEyWJVJYznUMMjUWprQzO+NhzXcP0DIWnXYrft7OV8hLvnF7HVFW55XannGlhWvnbomSa1ozvC5qmoirqoq9WzLRNdTWZ9xWZy+OkfUvjnB6jqgoutwN/qZeSMh+BMh+v/+AQ4bHpTVlu5HTpBEp9ePwuHE4dVVUxTZN0IkMiliYVz2Dc5uKjtNLPs790Pxt3tbBmbQ2uPCRbAvQmzvLGyDcYSF6UJO0isrEYz/Ty/uh3wYYtpRJcLGWGadI1ECIUm14tpNhefeMMb7x9flpQUV0Z4F985X7uv2ctHrcTXVenvKnatk11VYDNG+p4+IGN/P13P+SjI11ks5PHsSyb85eG+Jtvf8jXfvMR/L6FVzAbHYvzjz84xOnz/RiGiaoqPP7wZj773G4a6kpxOnV0TZ2S29HUWM62LY08/cQ2YrEUnd1jeD3OvK2iCCGWnqpSP/fvbOP1Qxev32YDg2MRPj7Tw7MHtk57jGFanOscnrYNyqlr3LOjdV5VnBy6hq6rGDflOeRyxi1XW+fDMK0ZczlcjsnzL7acYa7qdZN5X401tVfzJ9/9nTk/TlEm/y+dyPKtP32RZOKGCgIK6LrG+h1r2HX/etZvX0NDWxUlZX5UTZkWPdu2DTZkMjlG+kJcuTjEqYOXOf7+JcKj0evJSJHxOL0dIzz1pXsoq1h450fbthlIXeSNkW/Sn7yAzepJFloqbGxC2QE+GPseuupgY/A+VEVlKSYyrXZ9oxGGQlFMa3FfasMTSb717Q+nLftXVvj57a8+zP33rEPT1Bln6RRFQdMUPB4nG9bV8Nu/8QjK//sWHx7quD5zZlk2r711lvv3t3PvvrULzrc4eqL7+nG9Xif/4sv388QjmwkGPCgKM45T0xQ0TcXl0vF5nVRXzTxTKYRYGRRFwenQ+PSDW6YEFgBj4QSHz/bw1L2bcNy0renKwDgdfWPTLtB3bmigvio452IUiqLgduoEPC7Csal5a6msMWMgMF85wySdnV79ye91LWoZ8GtS6eyt96auAvP+Daiaisc3v+pKiWiKv/rfn+f9l06QSU0+ORxOnQee2cnP//eP0tBWNdlIRVGuL2ndbknO43dRWuFn3fYmHvvsHpLxNG/++AgvfPNdBrrHsCybt58/RmQ8wb/6P79MaYV/XuOGyXKyQ+mOq0HFOexVHZcuNpvxbB/vjX4HXXGwNrBXci6WoM6BcYbDt1+VLDTbtvnRi8cYG5vavMnndfLs0zt48L4Ns34jVVWV2uoSfvEL+xkdi3Hu4uD1r5mmxd9+5yC7djTj980cpMzWtYkRXVP55S/ey9OPbcXvn30y5bVgSAixsqmqwua2GjY0V3Ohe+T67YZp0TUQ4nTHILs2frLDxLZtzneN0DVDMY37drVRHpzbNqhrvG4nZUHvtMAiNJEgPkMZ2vmKJzOMTySm3V7i9+B1LW7PHtu2mYinWOR5tEVV9DUjI2fynT9/nYOvnSZ9debQ7XPx1f/pM/z+n36R5quVVdSrS/yKMn2l4mbX7qOqKpquEij18twvP8D/9Be/yua7W9F0Fdu2OfbeBf7y3/+IbHp+dY5t2yaUHeTd0X+kN3FmyQUVCiqaoqMrThyKC6fqxql6cak+3Koft+bHrQXwXP8I3vDvwOTXVT9u1YdL9eJUPTgUN7riRFMcqGgsxRWB0Uw3B8f/id7kGSxbtqQtJbZt0zkYmtbIqNiSqSyvv31uyh5kRYG62lI+9+xd85qdW7+2lnv2tVMS9Ez52sXLwxw/1Tu5opoHB+7fwAP3riMQcEtlJyHENIqi4HY5eeq+TdO+NjQW5cjZ3inlZFOZHBd7Rhi6aaKlpjzA1vZ6vO75TRoH/W5qZtgVMjYRJ5pI5+U10bZtookMYxPTt9bWlPsJzqKdQCFfRU3TYjScyNvr/3JU1DUj27Y59v5FPvjpSRLRyYhW0zW+8ntP8uQv7M/7PuDm9bX8xv/8M/yn3/s7+jpHwIa3XzjGvkc289Bnds957DEjxIdj36crfmxRtz9dCyA0xXH1Q8Ohugg4KilxVBPQy3Fr/qvBQgCP5sepeibvq+pXH6ujoGHbFhYmlm1gXv0wrCwpK07aiJE2YyStOCkzSiQ7SiQ3TMqIYmFi2iamnbv6YbKY1Rh6k2c5HHoRjxakyrUGRVn8fZYC4qksvSMTxFL5m62aj6PHu4lEpr4ROZ069+9fRyDgucWj7uy+fWt594OLRKJTZ+heffMM+/e0Xd2yNO/D43E7uP+etdTIliYhxG24HBr37mjlWy8cYuKGFYNIPM25riFC0QSVpZO7Nbr6x+nsG5928bt/ewtVZb55v2aVBTwzNuWLJTKMhuNkcibuBW5VSqZzDI/HyM5QCKSuqoTSgPeOx3A6pvf2sCx7zsVFZtI3HCE7Q7XB1aSogUUuY/Dmj44w0h++ftuGHZPblxzOwmxhWbetiXuf2Mbz33qXdDKLbdl8989f554nts0piTtrpTgefoWLsY8w7OK2jFdQcaiuyRUE1YVfL6fa1UK1u5VKVxMlzslgohjbgGzbJmuliORGCGeHGMv0MJLuZDw7QNqMk7MyZK0Uhp2j2IHGxehByhy17Kn4DH5d6vYvBd3DYYZCsTvfscCOn+qdVlrW5dTZv6d1Qcdtba6kvraUru6xKQmLR0/0kMkY6N6F5f1s2lDPmsaKvPXHEEKsTIqiUBb0cGD3Wn781qkpX+sfjXLq0iAP71mHbdt09I1N6XsBk6W9797cRFnwzhfmt1Ie9NJSX45D16ZUbbKZbMQ3EoqxprZs3scHGA7FON81NO12h67SXF9O6SwmigJe5+TL8g2XKKZlkcjDdq1zV4ZXVZO+mRQ1sOg810/PpSFyN7zBH3h2F27f7PcNz8f+x7fy6vc/Jp2cDAj6u8Y4+VEHex6avmw4E8PKcTF2kLORt4vW/E5Fw6V5cWt+AnoF9d4NrPFuocbdhl8vv5qoXHyKouDSvFRrLVS7W9jAfgByVoZwdoCB1CV6k2cZTV8hYUauBhvpomwbszA5PvEKZa56tpQ8iFOZ/0y0yI/u4RBDocVtGGlZNhc7hqdVgvL53Avu76BpKmvbazh2sodo7JMeNrFYmivdY2zZtLDS1i1rKqZttRJCiJl43U4eunstL71/dkqy9Mh4jHOdQzx4VzvpbI6u/hBjE1O3p25oqaa5vnzOvStupOsaa2rLaKkv51LP1J5F568MMzASobG6dM5bT68xLYuBkQjnr4xM+9qa2nKaqktxzGISJuCfXrUvlzMZCcXJGeasjnGr8R0+052XlY/lrKiBxeXT/UTGP0m4UVWFTbtbcRQ4i79tcz0ev4vw1ee5aZoce/fCrAKLa8napybeYDzbV9BxAjhVDz6tlHJXA2u8W2n2baPK3YxTXXj5ykJyqC6q3a1Uu1vZUfY4SSPCQOoiV+InGEhdJJIbIWlGMe355bfMVsqMcSz0EuXOepq8myWZexEZpknP8ASjMyTZFVMsnmZ8PD5lj7GqKjTUl+ZlJaC+tgS3yzElsADovDK64MCirrYU/wxvgkIIcTOHrtHWUMHmtlqOX+i/fnsinaVrYDKYmIiluTIQmlK0SFHg7s1rqC6bf2Gba5rrytm2rp6OvrEpr7ndgyGOX+hnQ0v1vFdFwtEUR8/1Mjg2dbJKVRS2rq2luW52qyG1FdO3llq2TSiapHc4TFtD5bzGNzga5fjFgbz2XlqOihpYDPaMkYx/svfPG/AQKPHOO3qdLZfbSUmZj8HuMWzLxrJsOs723/mBQNwIczbyDr3JswUcoYJb81HmrKPes561/rtp9G7CrS38j3wxKCj49FLWBfayNrCHSHaEK4kTdMWPMZK5wkR2BMMu3J77wfRlzkTeptRRS9BRKVuiFslYJEnfaGTRZ29Gx6LTXuhVVaGhrjQvx6+uCuKcYXKkbyA8w73nJuB3LWgGUQixugR8bh66ex0nLw5MadQ2NB7lcu846WyOnqGp26DKgl62rq2jxL/w1dGqMj+7NjTw4YmuKQGAbcPrH19kc3st+7c143TM7fIzkzM4ebGfNz++NO1rFaVedqxvoLp8du0E2hrK8bgcJG8q5BOKJPjoZDfNteVzzvlNZXL8+K1ThCKLO5G2FBR1P01kPE7mhl+k1+9CKXBQcY3b67x+gWlbNmODE3d8jGFl6YwfLWhehUv1Ue9Zz11lT/Oput/h8dqvsjawZ9kGFTdTUCh11rCz7AmeafhdHq35NbaUPEilaw26Mj2BKl/ORt6hJ3mq6Pkw4hO9IxMMjEfufMcCi0TTU2bOYPJ5GVxA0vaN/D7XjG9CoQWu1KiqgvNqQ1AhhJgNj9vBrg0NVN9UVn80nOBy7yj9IxGGx6dug9qxvoHG6pK8TPKqqsLWtXXs394ybVKkZzDM82+d5sKVkTnN6mdzJmc7hvjxW6cYuGm1QtdU9mxpZtva+lkHA163k/XN1dNun4ilePdY59UVndlv306ls7x3rJNXPjw/LVhZjYr6jpXNGFg3dF/MZoyileRKp7JTznWtf8at2LbNWKaX87EPiOSG8z4eTXFQ5WpmZ9kTPFH7VR6s+hK1nvYV3UHaqbpZG7ibJ+r+Ox6p+WU2BR8k6KhCKUDxt4yV5Hj4VcLZQWx7dSdSLQbbticDi7HFza8ASGdy0wILFHC78xPYul0O1Bn6RSSTCwtqdV272rBvQYcRQqwiqqJQVTbZiftG0XiKs51DXBkITbmodzo0dm6Y/Wz/bNRVBnno7rWsW1M17fXrveMd/MNLRzh0upvYHUrQ2rZNNJ7m4Kkr/MNLhzl4qnvafVrqyzlw99oZq1HdiqIqPLJn3bTbTcvm/JVh/uGlI3T0jt0x+LmW8/HqwQv85Q8/YHgJFCpZCop6Favpkw2jrj2RYhNJYhNJqhvKCjorl4iliIzHsW+4uNDu0PY9YyXoiB+hJ3E6z6NR8GgBmn3b2FJygDb/XUs+fyLfnKqbdYF9NHo2cyb6Ducj79GfupD31YXe5Bk640cocVTh0nx5Pba4vVQ2R+/oBOHY9FrjxWaa0wNLBfK2xUjXtcmGnjcxVvk+WyHE4gj63ezd2sxL758jcbVfmGnZXOwenVbutam2jLVNlXjd+WsspygK29fV88z9WwhHUwyMfrJybdvwxseX6BkK89i+DWxoqaa2IoDP80nX7Ew2RzyVZWgsyvmuEV796AJd/dOb+VWW+njy3k3ctbFxTqstqqLw4F3tfPunR6flayRSWd48fIlYMs3De9bRUldOadCLx+VAUSBnWKQzOSZiKQbHonx8ppv3jnUSiiSxmVyxqa8qYWAkMmUr2mpS1MAiUOLF4dKvrxaYhsmZj7tYs64GVx6f1Dc7d+QKiRsSKxUFSipvvdXIti2G011cin1E1krd8n5zpaBS5qxlS8kBNpc8SKWrKW/HXo48eoC7yz9FnbudkxOvcy76HikzfxG/jcXJiTdo8e2k2t26aJW0VqPhUIy+0QnMJdB+VJvhDceGKeVhF8IwzRln3fLdl0cIIWbDoWu01Jezpb2OQ6c/meUfGo9O2x+wc30DTXOY7Z+taxWqIvEU//TmSUZCU7dfXe4do7NvnIbqEtY2VVJe4sPncWIDiWSGUDTJ5Z4x+kcnmOn6vCzo4cl7N/LYvvUEfXObnFUUhYpSP597dAd/9aMPSWem5gEmUlneOdLByUsDrGuqoq6qhKDPjaoqZLIGsUSagdEIXQMhIvGpqy471tXz4O61/MX33ye9SvtZFDWwqG4ow+tzT9mG9NbzR9j94AYa2qoLksQdiyR588dHScVvCCxUlTVra2/5mKQZ40riJEPpzryNQ0Wj2t3K7vJPsbnkfpzq/GtFrywKDd6NlDnr8evlHAu/TMwYy9vRRzPdXI4fpsxZh0uTn3mx9I1G6BtZ/PwKALfbOeNrSzqdnxWyTMaYvtUK8M6hT44QQuRTRYmP+3a0cuRc7/VV25tfp0r8bja31VJRUpgV/YpSH888sAUUeOHtMwyORaYECZZt0zs8Qe/wxJyOW1Xm58l7N/KZA9uoryqZ19gcusozD2ymo3+MVw9emDbRZDNZherQmZ5ZH3NDSzW//Oxe2hor+ebzH63awKKoU2qtm+oJlE19Al882cs//+37hIYjec+3SMbSvPmjIxx99wLZGyJSTVPZuqdtxsfYts14ppfLsUN5K42qKjqN3k3cX/ULbCt5WIKKGXj1IPsqf5Z7K3+OcmdDXo99OvIWMWNuyVhi/kzLon8swsD44udXAJQEPdO2Wtq2TTSWn8pkyWRmxu1WJSXSf0IIsTi8Hieb22pprL71hff65mpaGwrbgLOmIsBnDmzjF5+5m21r669vd5oPh66xoaWaLz51Fz/32E7WzLK87EwURaEk4OGXntnD0/duxu91zftYmqpy16ZGfvW5fdy1qYnqcj9VZfnLWVluirpi0b6lgfqWCvq7RjCvRoe2ZfPqDw5h5Aye+IX9rN3auOAtBLZlM9gzxns/OcFPv/sR0ZuW4EoqfOy6f/2Mj01bcXqTZxjNTE8Smg8FlTr3Wu6v+gItvu0osh3nlhyKi51lT+BUPbw7+m0mctO7a87HeKaPK4njlDiqcCjzf/EQsxNNpOkbiRBPFa6k8FxUVvin5VNYls1QnlZUxsbjZLPT8ylqb/OGLoQQhaQqCnVVAfZtbaZ7cHrpa01T2bq2riDboG5WUerj6fs301RbxvvHO/n4TA/dg+FZV4bSNZWm2lJ2b2ri3h1t7Fhfv6BA4BpNVWmpL+dXf2YfDdUlHDx5hfPdw9O2Rt2Kqio0Vpeyd2szj+9fz+a22utldNetqaSzb2xV5lkUNbAoKfez79EtXD7dP6Xcayqe4eXvHmKwN8T2/e1subuVxvYaSiv8c+pBkIynGege48Lxbk4d7ODEB5eYCMWntG1XFHjwmV1UN8wc6U5kh7kcO4Jp52MJS6HS1SRBxSwpioKGg00l92HYWd4b/UdixvSErbmzOT3xFpuC96MrTulrUWBDoRg9Iwvv4ZAvwYCb8nIfA0MT17cCWJZN/0AYwzAXPFs3MBQhk52+utmyZn5NloQQIh9KA152bmjg5Q/PE4lPbeBZVxlkfXMVfl9xJts8Lgd7tqyhtaGcPVvWcP7KCB19Y/QNTzA+kSCWzJDNGSiKgtOhE/S6qCj10VBdQmtDBRuaq1nfUk112dyuC+9EVVXqKoP8/BO72LmhgTMdg1zuG6N/OMJoOE4ilSWdyWGYFrqm4vU4KQ96qasKsrapko0tNWxfV095iXfKyvhnHtrGhpbq6zslnA6drWvr5jXGTz2wmW3r6plyMYvC2qal2aerqIGFoijse3QrZ49c4d0Xj5O+oRyjaUx2w754vJtD62upaSinprGM8poSSiv8+IIeHE4dh1NHURQMw8TIGqQSGSKhBOHRKCP9YYb6QvR1jBAeic64PaFtcwOf+vK9M/4yclaGkfQVhvOUW+HTSnmg+ku0+XdJUDFLiqKg42JzyYNkrSTvjnybrJ2+8wPvYCjdwXC6azLAQxqOFdLAeJTu4aUTWKiqyvr2Gi5cGiJzw0xUJJqipy9EW0vVvI9tmhZdV0ZJ3lS+2u120NoigYUQYvE4dI2yoJeA1z0tsNjUWkN7Y+WMFe0KqbLUT+VOP7s2NDIcijE2EScST5NK58iZJgoKDl3D43ZQ4nNTWeanqsyPr4A5a4qi4PM42bmhgU1tNYyFE1e7lKdIZwyyOQPTstFUBbfLgf9q0FNXEcTvdc2Yw7drYyO7NjbmZXwP7GrPy3GKpehNE8qqAjz3yw8QGo5w8uBlcjdtIUjE0pw7coVzR6/gdjvxBT14/S5cHiearqLpGoqiYJoWlmGSzUwGF4loimQiM6VPxs2qG8r40u8+SV3zzG/4CWOC7sRJcnm4kFVQ2V3xDOv8e1EVuZCdC0VRcKleNpccYDw7wPHwyws+pmnnOB99nybvJvl9FFA2ZzAwFmUkHL/znYto1441vPLGmSmBRTZr8PHRrgUFFoPDEXr7Q2RvStJb115NSVByLIQQiyeTNRgcixKKTi377fU42dhaQ21FcJFGNjmG1oYKWhsqFm0MN1MUBbfTQWNN6Zz6YoipFqUbW9umer70u0+i6RrH3rtIbqbMeXuyqV06lWU8D/3pmtqr+eLXnmD3gxtnbDhl2zYxY5zu5KmFnwxo9e9gV+kT6GrhukuvZIqi4NfL2Fn6OKPpbvpT5xd8zI7YYQ5UfxldcS3J5cOVIBRL0jMcJrvEejhs29xIVWWAWDx9vSpJJmvwwUcdfOqJ7QT88+sl8/GRLkZGp5dIPnDfBjRVleeZEGLRjEcSHDnbS/KmCngtdeWsX1O1oERqIW5lUfbnqJrKxp3N/Mr/7xk+9xsPU15duKjZ5XZw4Nld/Ob/+lnufXIbTpc+45t91koznOokllv4nn6X6uX+yi/g0+dfsUCAqmhUu1u4q+xpnOrCZ39jxjgDqUtM3aco8mk4FKdrKLTYw5gmGPBw4P4N1xPrYDLPoqt7jDfemV/Q2jcQ5oNDHYQjU2cDK8t93LO3vSDls4UQYjYsy2ZgJDKtXKrCZFnU9ibZqikKY9HCVVVTadlQR2llgO371/LaDz7mo9fPkIjmpyGdw6WzcWczj31uD1v2tFHbVI6q3XoGMW3G6Eudw2bhTbM2lzxArWftgo8jQFdcNHk30+7bzbnYews6lo1NR/wIbf670BYnpl7RbBuGwzG6h5ZOfsU1igJPPbqV1986R3fvJ5MHsXiaF146QUtTBTu2zb5hZTSW4oWXjnPu4uC0XK6nHt9GVUUAprWiEkKI4ogl0hy/2M/YRGLK7dXlATa31lAakK2aojAWdR1MURTKKgME7/HR0FrFp758D6cOdnD03QtcuTBIbCJ554PcwO1xUt9SybZ97ey8bz0NrVVU1Zfh8jjuuCUhZcboTy58u41HC7C7/Bl05c7nFHemKAoBRyWbS+6nK3mC9AI7c1+JH5+s0iC/mrxLZrL0jUaYiOevW30+VVUG+NLn9/F//NeXyeYmt2pNrlqM8ld/+y6/9IV72b2z+Y4rDaNjMX704jFee+sc8ZsSIttbq3jy0a04nNqMWy6FEKLQbNtmOBTjrcOXpvVvWt9cxZa1dWiqTK6JwlgSG+w0TaWqvpTKulKa19fx0HN3kUykCY/E6O0YZnRggmQ8TTqZIZ3KYVkWLrcTj9eJ2+eirCpIQ2sl1Q3l+IMefEE3/qDneqL3nRhWjonsEJHc6IK/ly0lByhz1iFXrvmjKTo1nnba/XdxJvL2go4Vzg4RyQ1T7myQwC/PxiMJOgfHl2zdblVVOHDfes5dGOBHLx6/frthWJw9P8B//YvX2bu7lYcf2Eh7WxVu1yf5UbZtMzoW48iJbt585zxnzw8QT2SmdJEN+F386lfuo66mpOiVVoQQ4pp4MsPBU9109U/dlhrwutjSXseaWtmmLQpnSQQWMDkzrSjgD3rwBz3Yts2adRab727FyBlYpo1l2dj25IeqKiiqiqoqaLqG06Wj6dq89jXnrDTDma4Fb4NSUdlc8qAkB+eZoigE9ApafTs5F30Py55/YrCFSX/qQt67ewsYnYjTOZCPviOF4/E4+aUv3sfwaJQPD31SVtowLHr6xhkZi/L2+xcpLfFQUe7D63VhGhbhiSThiQTRWIp4IoNhTH2tcLl0fvUrD7BrezO6LjOBQojFYVoWVwbD/PCNExg3bdNc31LN3q1rcBSw07YQSyawuJmiKOi6drV5VWEbuGStNMPprgUfp9G7iTJnHYqsVuSdpjiocDVR425jMHVpQccaSF1kW8kjeRqZgMktRSMT8SXVv+JWysu8/MvfegKn8w3efu/i9dttG1KpHKlUjtGxKB1dkxMXtg2WZV1vrnezgN/Fr/3iAzz60Ca8XmnAKIRYHLZtMzQW4y9/8AFDY9EpXwv63Ny9uYn1zdWLNDqxWizZwKKYcnaK0XT3go+zPngPLtUjFxYFoCgKpc4amr3bFhxYDKUu52lU4ppoMs2VoRDpmUpHL0HVVQH+5W89TltzFf/4g0Ok0lMb3Nn2ZPM78w6LY+vX1vArX7qPXTvW4HFLXpUQYnGYlsXlnjH+r2+/zbHz/dy8I3VLWy0P371OVitEwa36wMK2LdJmkkhuYc0yVDSavdvRlcKurqxmXq2EGncrmqJj2vO/gB3L9GHZBpoiPUbyZSyS4GLv2GIPY1auXfyXlnj54uf3cc/edr73o8O8/9Fl0ukcts20hMfJx13bsqnQWF/Gp57YxiMPbqSi3D+5NXMBQYWiKui6enWFdpLDoUmuhpiXyS3DkxebN96WNUwSqSzxVObq5yyJ9OS/Jz+u3p7OkEhOfr1/LELWuP3r7Ug4zl//80e8dPAcPrcTn8d19fPVD7cTv8d1/d+Tt7vwu524nFNLwKuKgqbJdsKbne0c4spAiKDPRcDnxu10oADxVIaugXE+PtPLx6e7SaRz016/muvKefr+zTTXlS/O4MWqsuoDC9M2mMgOYS+wt0G1uxWPFsjTqMRMFBT8egXlznpGMz13fsAtmHaWcG6QSteaPI5u9bJtm/FIgsv9Cy9+UEyKouB0aKxfW8O//f1PMTYe46MjXZw+20937zihUIJM1kDTVIIBN3W1Jaxtq2b3jmbWr63F63VeP85CPXjveh64Z93UWUYFCSzEvGRyBh+cusI3/vkjEunJACGVzk42rrRv7ORzwxPOnnbLrGUNk+6h8LRS08q0f3xyw7WbNE3B65oMNvweFzvXN/CvvixbVW92+vIg33rhEOORa+Vjr/0EJ39jt6qZURrw8Ni+9TyyZ5301hFFseoDC8POMZEbXPBx6j3rcKiStF1Ik924S6lwNS0osLCxGc/0S2CRJznDZGA8yuD4wkoBL4Zrf6+aplBTXcJzT+/kuad3Lso45LVD5Itl2YxNxDnfPbKo47Cn/eOTG67dZBk2ESNNJJFGAfxeWfWfiQ1YV1eiPrnl9gI+F4/tW8+Xnt6NwyFboERxrPrAwrINormFdwqudbfjUJ15GJG4Ha9eQrmzfkHHsG2bSHZx33BXknA8xcW+MelnLoQQS4CuqVSV+Xli/wa+8sweCdZEUa36wMK0TRJ5CCxKnbWyZ78InKoXv77QGtw2MWNpl0VdTiZiKS72SqAmhBCF4nbqBH1uUukchmliWja2Nbnyo6mTeSlupwOfx0lrQwXPPbSVB3a1oWuyUiGKa8kEFplUllQiQyqZIZc1sUwL07RuvXFwARRVpW3T5Ky3ZRskzIkFHc+huPHpJaiKJJwVmq468GgBHIqbnJ2+8wNmYAMxY+HBpJjccjEeTdI5KIGaEEIUyo719RimRfdAiNFwnEQqSyqTwwb8HiclAQ9rmyrZ0l7HlrZaXM4lc3knVplFfebZtk00nGBsMELn2X46zvXTfWGI8Gh0MshIZDCNhTWtm4nH5+LvPvpfJ8eARdpM3P4BdxBwVFxdrZA90sXg1Lx49SCR3PwCC7BJGZG8jmm1SmVydA+FiCYyiz0UIYRYsVrqK2ipr1jsYQhxR4sWWOSyBj2Xhvng5ZO899IJejtGsG/RgCrfbizFZtkWGSu5oOP59TI0RWYHisWpuvFoASK5+W2/sYG0tbBgUkyKJFKc65FtUEIsJaqqUFMeZP+W5sUeypwoisLaxspFHYOqqLP62ZUGPAR97iKNSojlY1GuhrOZHMffu8j3//JNzh29gpG7QxeqArKxyFmpBR3DqXpQFNnHWCyaoqMrC0mUtxccTIqrSfCJNBckv0KscqZlkcrkSGeN658zOQPDMMmZJjnDmuzebk9W9sG2URQFVb36oSho6mSnd13TcDk0XE4dl0PH7dBxOXXcTh1NVWdVPcztdHBgVzsHdrUX4btfWZwOjQd2tvHAzrbFHsqc2LZNJmeSymRJZ43rz8GsYWAYFjnTwjCvPQ/t6/16JivScf05qGsquq7iuPo8dF59DnrcTrwuhzTYE3dU9MDCMi1OHezgm3/yIlcuDhVtleJWbMBYQLM1AF113lCVWxSair7gFaKcJVt35sq2bXKmRSyRJprMEEmkOdHRT8/IxGIPTYiisSybRDpLKJYkEk9d/VtIMTaRIBRLEY4lCcdSRJNpkukcyUyWZCZHzjAnu7lbNpZtoSoqjqsXcLqu4tA1HJqKx+Ug6HUT9Lkp8X3yuTzgpezqLHnQ56bk6n10bXbBhlg5bBuSmSyReIqJq8/BWDJNKDb5PJyIp5hIpIjE08TTGVLpHKnsZMCbMyYTv03TwmYysNBUFU1VcOoaHpcDt9OBx+0g6HVdfZ55qCzxUlXqp8TnJuB1UeLzUOJ3E/S68bikcI34RNEDi8GeMX7012/fceuT7tDQHRpqATpwenw3ll6zseyFrZjoihMFSdwuFlXRFlyBy1pgMLnS2fZk/kQ0OfnmNPlGlSYUTTIUijIUijMUijIwHiVbwBVH07LpG43wo/dOF+wcS01zTRkbmqrwuqV89VKRzuYYnUgwFIoxMhGnfzRCz0iY/rEIw6E449EEhjm3fEDTtjCzFmlm91qkKgplAQ+15QHqKoLUlQeprQhc/1xTFqDE55YgY4VKZXKMRRKMhOOMTsQZDEXpH4vQOxJhKBRlLJIgnZ37+5pt21iWSQ5IZw2iydtPuvk9TqpL/dRXltBQGaS+soS6iiBVJX6qy/yUBzw4HbI1fDUr6m/fMi3ee+kkl0/3zbj9qbKulOb1tVTUlBAo9eJyO9AKsOzmcN58zIWtmmiKQ1YsikhBWXAFLsvOf1GA5cq0LBKpLOF4iolYinA8STiWZjwSZ3gizkg4PnlBFY4TTc43YX7+YzvTNcSZrqGinncxfeb+LdSW75fA4g4UZfKjUDI5g6FQjCtDIbqHwlzuH6NjYJzekQkS6WzhTnwLlj1ZgW08muTMleHrt9eVB1jbWEl7fSXNtWU0VJbQVFVCValfgoxlLp7KMDAWpWdkgt6RMF2DIboGQ3SPhEmkiv8cnBxTlngqROfgZGVFVVUo83tprimlpa6ctroK1tSU0lRVSnVZALdUp1p1ivobD41GOfnhZaLhqYmzukPjrgc2sO+xrWzc1UxNYzm+QPGSohRFxV7QqoXFQoMTMXs2NhYSGMxH1jCJXl15CMWS1z+PRRKMTiQYnYgzMhFnLJIglckt9nCFuCVNUdHU/K4UW7ZNNJHmUt8oF3pHOdc9zLnuEQbHo2SNxcsFvJ3BUIzBUIz3Tnbh97porStnQ1MVW1pq2dBUzZqaUtxO2aqyXGRzBgPjUS73jXGpf4xLfWNc7BtlJBzHtJbe+95kyfEE49EERy/143bqNFaVsq6xkvWNVaxrrKS9oZKKoDfvf69iaSpqYNF1boCxwQmsG7dAKfDAMzv53G88TNvGehS1uDMsk7Pf+oK2Q+WsLLYEFkVj2SamtbCtTOoKT7a3bZtM1mA8lmQ8kmAskrz+4j8WuXpbNMFYJMFELLVkL5qEuBWHruLM04q2ZVmMR5Oc7Bzk+OUBTnUM0DkYWpSVifmygVgyw8mOQU53DvHmsQ42N9ewpaWGrW11bGiqpizgWexhihnYNsSSaS71j3Gma4iz3cOc6x5mKBSb8xa7xZbOGlzuH+Ny/xhvH+9gTU0Zm5pr2Npay/a2OhqrSmSr1ApX1N9uz6VhYpGp1Xia19fxua8+TOvGuqIHFZMUdHQM5p/Ma9hZbJlBLxrLNjHthc2mr6TywLZtE09lGZ2IMxqJX115SDAWiROKpSZXJaJJQrEEsWQGc5ELJgiRDw5dw7XAC5Rrlc0Onevh4NluTnUO0jMysewu5m5m2TZjkQTvnOzk4wu9tNaVc9e6Bu7d2sqWlhr8HtedDyIKzrZtJuIpTnUOcfRSH6c6B+kYGCd2hzyH5SKZyXG+Z4QLvaN8eOYKG5qq2bG2nr2bmmirq1jw369Ymor6Wx0bipBOTp0BOvDpXTS0VqEu0hKZgoJDdS+or0HOykzpjSEKy7RzGPbCZhKd6vKsP25ZNuF4ipGJOCPhybyH4XCM8Ujyam5EinBsslLIcpptFWKuHLqG0zG/FQvbtskZFh+f7+GtEx0cu9TPlaHwinwdT2VynL0yTNdgiOOXB9i7aQ0PbGtlfVO17H9fJLYNsVSGY5f6+OD0FU52DtIzHJ5X8vVyYNs2Q6EYQ6EYJzoGOHSum93rm3hgexsttWVSwnaFKeqrSjKeInfDH46mq+y8bx1O1+K9uKmKilPzgjE+72OkzCimVBkqmpydIW3GF3AEBZfmy9t4imUinuIfXz9G11BoslJT4pOKTbKVSaw28w0sbNumfyzK8++f4f3TXVzuH1v2KxSzkcrkON01RPdwmBOXBziwo51Hd6+jpixQ0CR4MVU6m+N05xBvHLvM0Ut9dA+HC1pZb6mZiKc4eLaH8z0jHL7Yy/1bW3ls9zoqS/2o8kRcEYp6RZ9O5TCNT17AfUEPpRX+RdoCNUlBw60u7CIzaoxLYFFEGTNJ0ozO+/EK4NEC+RtQkcSSGV49cokrQ6HFHooQi86hazj1ub2FWZbN2yc6+PF7Zzje0b9itpzMRSyZ4ejFPvpGJ+gYGOMz929lU3NN3vJVxMxMy2JgLMpPPjrH+6e66BwMreoCGRPxNB+d7aFrIMTRS/18av8mHtjWKn1ZVoCiBhaKwuRV3dXVZq/fjaYv7pNIVTR8esmCjpE2YmSsBLZtoSywDKq4PdPOkTZjZK2FlD1V8OvleRtTsUx2S115WzWEmA/nHFcsYsk033/rJC8dOk/n4Dir+U/JBobDcV45fJHu4Qmeu3czD+1sp8Qvyd35ZtuQyeZ48/hlXvzwHOd6RpiIpxZ7WEvGyEScseMdXBkKcaJjgC88vJO6iuBiD0ssQFEDC4/Phe7QyGUmZ/ez6RyL3U5AUzR8etmCjmFhEjPGMO216BJYFFTGTBE3JlhIeV8FhaCjMm9jEkIU31ySt3tGwnzjpUO8f+oK49HknR+wSqQyOU52DDASjjEYivK5B7dTVepf7GGtGNdyC/7u1SO8d6qLgbEo1mqOaG/Bsm26BkOMTsS53DvGlx+/i3u3tiz2sMQ8FTWwKKsM4HI7rgcW8UgSI2di2/airVqoioZ/gYEFwGi6m1bfXehIvfBCSplRwrnBhR1EUSjRq/MzICHEopjcCnXnFYszXUP81Ysf8fGF3lW99eRWLNtmYDzK998+STyV5SuP76amTJrrLZRt23x0tpu/fuljzveMSDGNWYinshy60MNoJM7FvlF+4eGdeFxyTbXcFDWwaGitwh/0EI9MLgNmMwbdl4aoaSpDX6SyY5rioMSx8IvMgdQlclYG9zJMCl5O4sYE45m+BR1DQaHMVZ+nEQkhFsNk8vbt3zc+PNPNX//kI053DUmBgzsIx1K88MFZYskMv/HsfuorghJczJNpWXz/7ZN8+/Vj9I9GZJViDizLpnNgnH947Sh9oxG++un91JTJKtpyUtR9O2u3NlFSMfUJcuy9C2TTi5f4rCkOSp21Cz7OYOoyOTstjfIKyLYtEkaIUGZgQcdRUal0NuZpVEKIxeDQ1NvmWLx/+gp/8cKHnOwclKBiluKpDK8fucR/+f47DIfjktM1D7Fkmj/9zlv8fy9+RO/IhAQV82AD49EkLx86z3/4u9c41z2y2EMSc1DUwKKhtYr2LY24vc7rt739wjH6u0awFqlVvYKCR/Pj1RaWwJ00o4ymuxfUwVvcXsqMM5rpIWcvJHEbgo4qXJo3T6MSQiwGp67husVWqA9OX+EvX/iQs1eGV0Up2XxKZXO8e7KLv3rxINFVWDVrIUZCMf7937zGP394TnJ58iCZyXHwXDd/+p03OXyhd7GHI2apqIGF7tB4/Of2UttUcf222ESSb/7JT4iFE4syO6Iokw3yKlwLncG2uRT7iNyCqhWJ24nmRuhJnF7wcWo9a5ksTyaEWK4cjpm3Qp3oGOCvXzrEue5hzEWasFrusobJTw6e4ztvHJO8lFnqGBjjj775Mu+e6iQp+RR5kzMsTnUO8vXvvcPbxzsWezhiFopewmjd9iYe+7k9U7ZEHf/gEn/y+//AxPjiLL06VDdVrjULPs7F2CHSpiwfF4Jpm4SygwykLi74WA3eDXkYkRBisSiAQ9PQtalvYV2DIb7xk4852TGIacnr8EJkcibffPljXjtyEcOUlfjbOdc9wr//1mscvdi/qprdFYtp2VzsHeXPn/+AN45eXuzhiDsoemChaSrP/dIDPP2FewiWTSY6W6bF0Xcu8LvP/mde+vaHxCNJcjkD07SwrMLX7neqbqrdrQs+TsqMcjl2GNPOsZByqGIq27aJ58bpih/HsBc6E6SwxrslL+MSQiwO/Wqp2WvJxbZtMzoR5//7yUccPNctKxV5ksma/Mk/vsnF3jGZMJuBZdmcuNzP//53r3HmypA87wrIsm0u943xFy98yGtHLsnPeglblFJMulPjy7/7BOU1Qf7h/3qFibHY5BvD4AT/9Q+/xzf/5EX2PLSJrXvaWLOulpqmCpyuyTeRvBSpUBT8wU8aATkUN9WuFpyqe4GN1+Bw6J/ZWHIvPqUsP2MV2FiMZnq4EPtwwccqcVRT4WyUaidCLGMOTcV1Q+J2Kmvw3TdP8O7JTnKSqJ1XiXSO//SPb/B//+7n8Hmcd37AKmFaFscvDfB/fPctLvaOylRiEdjA5f4x/urFg2iqwgPb26atWorFV/TAIh5JEo+k6L8ySiaVpbTCTzQUx7q2bG1DLJzkjX86whv/dASY7NjtdDvweF04XI4FX7C7vS7+4tV/ff2/FUXBoweocbfRmzy7oGOPZ/s4E3mHu8s/jWprcgG7QLZtE8uNczb6LikzuuDjtfl3SXd0IZa5G5vjGabJa4cv8srhC8RTi7u3XVUVNFVBQbk+EaYoCgqTF0W2bWPbk58t28a0rGXRAfx01xD/+OYxfuXJPWhyIYdpWZztHuH//tH7XOxb2kGFokw+J1XlhuckyidphrZ9/blp2WBZV3eKLOag7+BS3xh/+8ph/B4nu9Y1SnCxxBQ9sPir//153nrhGJnk7N8AbBsyqRyZVH6SyDw+1/TbtAANno0LDiwADo3/mE2B+whId+cFM22DofRlLkQ/WPCxFBTWBfagFn8HYF5oqkqJ3015cmlUtLKxyRlmwS/mnLqG3zP9b3al8rldqKpMSNyOQ9dwOnUs2+bslWF+8tE5+kYjRTu/qiq4HDouh45DV9G1yUCnMuilstSPx+XA5dCuftZx6Bo5wySTM8kaBsl0llA0yVgkQTSZIXv19mzOJJMzllwlK9uGv3vlCPs3NbOldeHl2Zczy7K43D/OXzz/Aae7BpdMYKgqCk6HhlPXcTq06w0kg143laU+Sv0e3E4dp0PH5Zj8mmVDNmeQufqRTOeuPy+TmSw5w1qyz8uTHYP8zctH8LldbFhThaYuz/f1lajogcX4cGROQUWxuDU/DZ6NaIrjao7E/EVzo3w0/k88VPPLOJTVc0GUb5ZtEcr2czj0IlkrteDjBfQKGjwbWa4VoSqCHv67Z+9ZMhVHDMvmdOcgf//a0YKdQ9dUNrfU8uXHdhXsHEtNXUUJJT73Yg9jSdM1FYemEY4leeXwRU5cXlhvmztRFHA7HPg8TrwuB1VlftY3VrGhqYrGqhJqygJUlvpxaOqcVqlt2yadMRgYj9AxOE5H/ziX+kbpHY0QTaSIp7JkssaSmD2Op7L8Py98yJ/85qdxO1dnN2Tbtukfi/KNlw5x+ELfohcIuDbp4vc6qQj4aGsop72ukrb6ChqrSigLeOb1u7LtyX4co5EEnQPjXO4f41LfGL2jYeLJLPFUhlQ2t6hBlQ0cOt9DZYmPX39mH/WV0tBxqVicdtdLkKbolDprqXa1MJi+tODjHQ3/lDW+bawP7JOtN/Ng2zYpM8qpiTe4kjiRl2NuCN6DQ3Uv2xcfj8vJ/s3Niz2M67KGWfCETlVRqCn388hd6wp6HrG8mJZF/1iEH713mrdPdBasAZ7ToVHq81BV6mNTcw13rWtkc0sNteUBHLfooTEXiqLgcTtob6ikvaES7p783oZCMU5cHuDwhV4u9I4yFIoRTaY/2TK8CCzb5sTlAT4628OBne2LNo7FYtuTTdu+88ZxPjh9ZdFyeXRNpczvoSzopb2ugt3rG9m9oZGm6vzldSoKBH1ugj437fUVPH73+sltyckMxy71c/hCL2euDDE6kSAUTZLOLU6TY8O0ePPYZarL/HzhkV2UBTx3fpAouKIHFqqmoumLe6Gt3eINIeAop8W/PS+BhWFneWvkbyhz1lHlbp7c0yhmxbZtcnaGjvgRjoV/mpdjOhQXG4P3oSkSSwux3I1OJPjmTz8u2PG9Lgd1FUHWN1Wxd+Ma7t7QSG15sChb1DRVpaGyhIbKEp7et5HOwRDvnOjg0LkeOgbGCcdSi9bNOZ3N8b23TrB7Q+Oq2p4Ik13JX/zwHK8duUhiEVaNvS4HVaV+2uoquG9bC/dubaGq1I9apIkyRVEI+twc2NnOgzvaiKcyHLnQx1vHOzjbPcxIOE4sVfyGirFUhpc+Ok99RZAn9mzA41qdq2lLSdGvsrbsbsO9yC9ILvfMTzyPFqDRsxmP9mpeEoXHM/28OfxNHqv99Tw04FsdbNvGtHN0xo/yzsg/kLHy07200buJKlczqrLwWUYhxMrkcTloqiplx9p6Ht+9nm1ttTM24SsWRVFor6+gvb6CZ/Zv4uVDF3j7ZCcXe0cX5eLWtGzOdg/zwekrPLFn9fQDyuQMPjxzhZc+OsdoJFHUc7scOg1VJdy1roEHd7Sza109HqdjUVfeFUUh4HXz0K617N/SzIWeUd44dpmPznXTOzJBOlvcFYz+sQgvHjxH49W/XUnmXlxFf8X8+d96tNinnDVV0Sh31bPGuyUvpU1tLLoSx3l39Ns8WP1lyp31eRjlymXbNhYm3YmTvD38t0Ryw3k5rqY42Fb6CA51dc2wCSFmR9NUGitL2LOxiUfuWsfOtfXXq04tFdVlAX7xybvZt7mZFz44w9snOhgYjxZ9n3s8neX5D85w79aWVbFqYVkWl3pHeeHDs1zuHyvaeTVVpb4iyM619TyxZwM71zXgXYKz8W6ngx1r61nfVMV9W1t46aPzHLnYy1AoVtQclOOX+/npofPUVgSoryiRcv+LaGm9ci4BQUcVbf5ddCWO5yVh2LQNLkYPoitO9lQ8R7WrWXIubsG0c3TEj/De6D8ylu3N23Fr3G2s8W1FU5bei7IQYnH53E52rq3nqX0beWhHO1730u7VsL6pit/+2ftorSvn+Q/OcqZrqKhbo0xzsirSyc4h7t2ydHK+CmU4HOfFg+c4eqGvaEn0fo+Tra11PL13I/dta6XU71nyF8oel4O9m9awtqGCt4938uLBc5zrGS7a6oVp2bx1ooMNa6p5et9GfEv873glk8DiJk7VTZ1nPXWedXQnTublmDk7w5nI26TNOHsqnqPRu0n2+t8kYyY4F/2AD8a+Szg7mLfj6oqDHaWP4dWkYoQQ4hOKArXlQR69ax3P7N/E+qaqxR7SrLmdDj774HbW1JTx/714iEPne4p6/ngyw9vHL7N/UxPqCi7zmUxnef9UF2+f6ChKgrIC1FUEeWB7G8/eu5l1jVXLbltPedDHM/dsoqm6lH967zQHz3YzEV/4JO1shKJJXvroHO31FWxvr5MStItErm5nUOasY51/D4OpS3lZtYDJZO7L8cMkzSi7y5+hxbcdn16al2MvbzajmV4uRj/k49A/kzDCeT16g3cjrb6d6FL2VwhxlaJAW10Fv/DwTp7auwHfMt3Ss3t9I26HjvaCwsEz3UWbUU9nc5zqHGRwPEZDVUmRzlpcpmVxvmeElw9fYDgcL/j5VEVhbUMlz923hUfvWkd1mb/g5ywUp0Nn94ZGyku8VAS9vPzxBcaKlJtyqnOIt0900FhVQlXp8v0ZLmcSzs3Arflo8m2l3rM+r8c17Rx9yXO8M/J3fDz+PIOpy5j24pRpWwoyZpIL0YO8N/KPfDD2vbwHFW7Vx47Sx/E7ymW1Qghx3ZaWWr766f185v6tyzaogMkk2s0ttfzmc/ewa11D0c5rA6ORBB+e7S7aOYttdCLB60cvc7pzqODn0jWVLS01/NKTd/PsPZuXdVBxjaIok8H7Izt59p7NVJb4inJe07J44+glznYPF6wMtbg9CSxuocLZwPrAPrxafmdjbCxC2QEOh/6Zd0b+nlMTbxDODmLZS6ejZaHlrCy9ybMcHP8hb438Leei75G10nk/z9rAXpq929AV2WsphJi0a20D/92z+3ls97plt81kJqqqsHFNDf/iU3tprSsv2nljyTSHzvWQza28i7dMzuD45X7ePtFR8ItTXVPZ3lbHrzy1h4d2tuP3Lt9AdyYNlSV89sFtfPqeTVQEvUU5Z/9YlNcOX2R0ovArTWK65f+qWiAuzUuLbyfNvu0UolNzxkpeT1R+Z+TvOT3xBpHsCPYKDjAMK0t/8jwHx3/A2yN/y6HxHzOW6cEm/99zubORbaUP43OUyWqFEAKA9Y1VfPXZ/ezf0rKiXhd0TWX3uka+/PhdBH3FuTDNGRa9IxP0j0WKcr5i6h+N8NqRSwyOL7zs/O2oisLGpmq+/Phu7t3asmJ7MNRXlvDZB7bz4I62oiVVf3D6Cme6hsgsUvO+1UxyLG6j3FnHhuA9jKS7GM/25f34NhaR3AixyDh9yfN0xo/S4N1Ek3czFa7GFVIe1SaeCzOQvkx/8iz9yQsMpTvJWIXbb+lQPOwofYw69zpJkhdCANBYVcJXP72P3esbi9ZUrJicDo0DO9q50DPC997KT+GRO4km05ztHirqSkmhxVMZDp3v5fD5/FUmnIkCtNaV8wuP7GTfpjWL2i+lGBqqSvjcg9sZDsX5+EJvwTuXTyTSvHrkIltba6mvXJl5QEvVyn4mL5CmOmjxbWck2MWR0It5a9Z2MwuTidwQkdwIPcnTXHA2UONpo8GzkVr3WkoclWjq8pnJsLFJmwnGMj0MJC8ymL7EaKaHiexgQbY83Wx9cC8bgvtxa8t/n6oQYuHKg15+9em93Le1Fa0I3bMXg6IolHjdfPqezZzsGORC72jBzxlNpDl7ZZhn9m8u+LmKwbZt+kYivHr4QsG7SNeUB/jsA9t4cEfbil2puNn6pip+4ZEdDIdjdAyMF/x8H5/v5Wz3MBUlviXXl2Ylk5/0HXi1EjYF72c0083l2MfYBay7YWMRM0LEjBAD6Ut0xI4QdFRS5qynxt1KjbuNCmcDLs275HphGFaOmDHGaKaHoVQHY5leIrkRorlRkkYEi+Lsw63zrGN76aOUOmtW1FYHIcT8aKrC5w9s5+Fda3E6tBX9uqBpKq11FTx33xb+83ffLniDslTWoGswRCSRpsTnLui5iiGWzHDofA/nukcKeh6f28n929p4Ys+GVdFk8BpNVbl7QxOP7FrLWCRBJFHYicZYMsObxy6zvb2eaqkQVTRLJrAwsga9nSOEhqMkExnSyQyWWZh8A03XeOxze2Z1X0VRqHStYXvpo0RzYwynOwsyppvlrDTj2T7Gs330Js/i1UvwaaV4tCAlzirKnfWUuxooc9Ti18vx6H4KkQtyM9u2Me0sMSNMLDdOODvAeLafiewwCSNM0oyQMCZIm4mC5E7cTlCv4q6yp2jwbJRmeEIIAO7b2sqTezbi97hWdFBxjcfl4O4NTWxpqeVkZ/56As3Etm3Go0m6BsbZWcSqVIVg2zYD4xFe/vhCQffla6rCxjXV/NyBbZQXKZl5KXE7HXz63s2c6BjkyMU+TKuw1wkfnunmZx8IUx7wrohiDcvBogcWXecHee8nx7l0qpeJsTjpVBbTMDEMk0LlMXt8zlkHFgC66qDVt5NwdoikESFmFH4J70aGnSWaGyWam1za1pNOXJoPl+rFpXpxqC5cmo+AXo5fL8erBye/pvlwqT5cmhen6kJVdFS0yc+KhoqKjY1lm1i2gYWJaZuYdo6MmSRjJcmYCTJWkrQZJ26EiOVCJM0IOStDzkqTsRKkzSRZK1X0QOJGLtXHjrLHWRfYh0vzLNo4hBBLR11FkJ9/eAf1lUHUFboF6maqolBXHuCJPes5XYSu3LFkhs6h0LIPLOKpLB+f7+Ny/1hBz1NTFuDzD+2grb6ioOdZyuorS3juvi1cGQoxUuDKTZFEmrdPdLCusWpFrKotB4sWWKQSaX78jXf58JVTDPaME4+msAu8bHuNZx5VM1yaj60lDxMzxjkZfr2gycd3YthZDCNLgk/6Piio6IoTXXWgKQ6068GDjqZoKIqKgoqiKCgowLXP9uT/bPvqNi8bGwvTNq8HHObVz4adJWdnsZZY7w1dcbC15CG2lT6CVwtSjJUbIcTSpqoKn39oB1tb61bdTKXH7WRbWx3t9RVcKvCFcjKdpX90+VeGGoskePXIRYwC7ZQA8Dgd7N20hnu3tqzqrtCqovDA9lZ+eug8oViyoD9zgDePdfBzB3YQ9K6OVcvFtiiBRXQiwd99/WXe+8lxJsbi2AWeUckXv17G3eXPkshNcCF2ENPOLvaQrrOxyNlpcmbhk6OXEgWNDcH7uKv8aUocVUsu90QIsTh2rW3g3i3N+DzOVXcxoSoKNWUB7t7YVPjAIpNjYDyKZdnLdlUolclxoqOfiwVOeK8u8/PZB7YVreTqUub3uHhyzwbOdQ8zHi1MYZxrhkMxjl3qp7YsgMu56Bt1VryiX4XZts1P/v4D3vvJccKjsaIHFQ6nxvrtTfN6rKIolDpquK/q52n1bUdFy/PoxFwoqKwP7GNfxc9Q6WpCVeT3IYQAh67yqX2baKwqXZGlZWejLOBh59r6gl9ImZbFRDxFOJ4q6HkKaSKe4rUjlwpaAtXndvLQzrWsb6oq2DmWmwd3tNFcU1bwgNSybd48eplUNlfQ84hJRQ/dzh65wns/OcnEWPE6IvqDHu5+eBM77lnHprtaCJbNP2FKVVQqXU0cqP4lcnaW3sRprEXMLVitFBTa/bu5t+rnqHG3SlAhhLhu78ZmtrXX4V7Fs5OaqtJYWcLGpipOdBQ2iTuezDA0Hi1aZ+V8MszJRn9HL+a/V9WNKoJePvvgVhy6vFdd43M7eeSutVzsGyNe4PK+hy/2EYolCfrcq3ayoViK/qr70WunGeodn3Gloqq+lAOf3sW6HWuorC3B43OjqQoXTvTw9X/9j9dzMPY/vpXP/cbDANimTSqZIRKK031xiNOHOrlyYYBM6pPI1MiZ7LxvPQ98ase88itupioa1e5mHq/9dV4Z+n/pS5wtWjlVMblSsTawhwervkS1u0WCCiHEdS6HzpN71tNUVbLqtkDdSFEUyoJe1hchsEikswyGYmxprS3oeQohkcrw1vEOMrnCvYe7nTr3bm2hvkIatd1IURQe2NHO37xypOCBRTqb4/D5XhorS1Z8M8LFVtSf7vhwhPPHe0hEpy6Zag6Vn/uNR/jsrx3A7XOhaSqKei25GCbG4zgcGtnMZNJwsMzHhh1r0K4m5NmAbdlYloVpmFw43sMP/+otTh68TCaVI53K8pd//E84HBoPfnoXmr7wHWCqolHtauFTdb/Dy4N/Tk/yNOYSS2peiXTFwbrAPh6s+jLlrgbUJZRTYds2vfEX6Y5+n6TRj1evo7XkSzT4nlzVFzhCFNPOtfWsa6ySmWGg1OdhXUPht96ksjlCscLuky8E27aJJDK8fvRSQc/j97h49r4tyzYHpZDqK4Jsaa4hFC18Evc7Jzv51P5NOPSV3c9msRX1qqzr/ACR8djUAagKv/qvP80Xf+dxAmU+HE4dTddQ1avBhaqgair6DRGmaViYORNVU1E1FU1T0R0aTpcDt9fFjnvW8W//7Jf52V89QLDMB0AykeH/+rff5ei7F/KW16EoKuXOep5r+AM2BR/AqUqZ00LyakF2lz/Dk3W/SYWrcUkFFQDDyXc4G/o6ocxx0uYoocxJTo79B8bTRxd7aEKsCooC92xpoWGVr1Zc43Ro1FUGqSrxFfQ82ZxJNL78CodkDZOjl/oYixSuyqOuqexa18CGRsmtmImqKDx817qidMY+erGPeGrpFN1ZqYp6ZTbUPU4yNvXFZ/s9a3nsc3txXa3cMdObgaoqOJw3BhYmuVssWyrKZDDi8bn4xd9/mkc/ezde/2Tt4kw6x5/9j99jfDB/pfEURcHvKOPTDb/LPRWfw6eX5u3YYpKCSpmzjvurvsjD1b+MTy9dkhcNI6kPMG4qQ2zaaUZS7y7SiIRYXdrqKti0plqq7lylKAolPjeN1aUFPU8mZxBJLq/kbdu2SWVyvH38ckHP43LoPLV345J8z1oq9mxsKkq1pkzO5PjlfqwitTZYrYoaWIwMhEklpu6je+Rn7sbtvf2bgKIq6M5PlrUNwySXufO2I1VT+dLvPkH7lgbUq9umxoYn+N5fvJ73J5am6Nxf/QWeqPtNyp0NqMUvuLUiaYqDOvdaHqv5dfZUPIumLt2O2jkzjn1zV0fbImvGZn6AECKv7t7QRFNN6WIPY0kJeFzUlAUKeo5sziCayCyb0vHXhGMpDl8obNJ2qd/D3o3zq0S5WlSX+mmqKs6E4cfnewve7Xu1K+rVbyKWnrLSoDs01m5rxHGHJbCbVyyMnEk2M7uyYf6gl8c+twff1VUL24a3XjhOZLwwVak2B+/nZ5v+NU3erbjUwi4/r2QKCj69jI3Be3im4WusD+5b7CHdkcdRi6JMfS4rio7f0bxIIxJi9fC5nWxpraWqxL/YQ1lS/B4XNWWF/ZmYlk0ykyVbwHKt+ZYzLQ5f6CU5y2uJ+dBUlX2b1+CVFbQ72rm2Hq0IOSjHLvdjWNayC4KXk6IGFtl0DvOGF55gmQ+vz41yhyeTqqk4XZ9csGXTOVLJ2VcQ2PfoFvyln5TBSycyHHnn/BxGPje17jY+v+YP2VvxHKWOOjRFKhDMha64qHG380DVF3mm/nepdrcs9pBmpcbzAH5HE6riAhQ0xUPA2Uad7+HFHpoQK157fQUNlUFJkL2Jz+2kusCBBUAmaxCbw/vyYjMMkw/Pdhf0HLqm8vCutQU9x0qxo70eXSv8JWnv8ASRZZgPtJwU9Yo3l81hmZ9EiS6P445BBUyubFzLk4DJXImbt1TdTkmFn4bWKkb6QpimhWVZnD92hcc+t2du38AcuDQf91d9gVbfTj4c/yEDyQskzImCnW8lUFAIOCpp8e1gf8VnqXKvWewhzUmFZycby3+HgfgrpI1RfI5GmgOfxeeQZXAhCm1dUxW15cHFHsaS43RoBL2TpdvNAu4tzxkW6QLO/ueTbdvEUhmOX+4v6HkCHhc72xsKeo6VYtOaanS18IGFZduc7R6mtryw2wNXs6IGFoqqoiiT25EAchljVstRmj41sEgl0sQm5lbarqGlihMfXroaWNj0dYzM6fHzoSoajd7NPOtu4kT4dc5F32MiO0jSjBb83MuNXy+n0tnEttKH2VLyEJq6PFd5ar0PUOt9YLGHIcSq4nLqtNdXLMsGbYWmKAoup47P7SRawBUFy7bIFbhcaL5cu7gs9Mz1ppYavO6lmxe4lFSW+gl4XcTTha/adPbKMA/vWousbRZGUa/e3B4nmq5hZScTrxOxNKZhYtv2bZN2HA4NX/CTUq7RcJLx4blVdvIFP+m2aFs2odHiJNQqioJHC7K34jnWBvZwLvIOnYnjhDJ9EmAAfr2MSlcT6wL72BI8gFeXMpFCiLlpqiqhsapEelfcgtuh4/e4ChpYmJaNYS6PHAvLsjl8vreg51AU2LVWVitmS1UVmmrKGArFKHT2w6X+sckGaHKpURBFDSx8AQ8Op0buamCRTmaJhpPUNtko2q1/w063g7KqT5atYhNJRgcmMHImumN2bySapk55Es1lK1U+qIpGpauRe6t+no3B+zgf/YAriROMZ/tIGlFslsdMTz4oqAT0cipcTbT572JTyX0E9UqUJdaXQgixPKypKZOtDbfhcugFL8FrWTY5Y+m/j9m2jWnZHL88UNDzqIrCXeslsJiL1rpyPj7f+8m2lgLpGhjHsi1UZCKiEIoaWJTXBHF7XCTjkxf1tm3Tc2mIts31OG+TtOPxuahdU3H9vzOpLP1do4wPR6hpLJ/VuSOhxJQSs4tVEUBTdKrczZS76lkf3E9n/CgDqYuMZ3qZyI2Qs1ZuUpFL9VLqrKXKtYYG70bafHdR6qxBVeSPWwgxf/UVQSqDUoXvVnRdLXifAMu2ls2KxUQ8RdfgeEHP4fe4aKuvuPMdxXVrqktRoOArFqORBJFERrZOFkhRA4u6NRV4A25Co59sAbp0qo/7n96B03XrfYguj5PqhjIcTv36akf3xUEunuihqr7sjlVAclmDnktDmDfMpnh8rgV+NwujKQ5q3K1Uu5qJG2H6UxfoT15gON3JeLaPeC6MxZ17dSx1uuLAr1dQ4Wqk1tNOk2cz9d71uFW/bHkSQiyY26lTUxbA713c1/SlTFUUtAInxlqWjbFM+gOc6x4mc4smu/nSXFtWlG7SK0lliQ+lCJGFbdv0jU5IYFEgRX3WN7RW4Qu6p9x26qPLZNJZPH7XLS80NU2lvCpI7ZoKei8PAzDYPcbHb51j7bYm6tbcflbgwoke+jpHsK4mlimqQnn10qgeoigqAUcFGx330u7fTSjTz2D6EqPpHsK5ISayw0RyI2StFIWP4/NBuboyUUOpo5ZyZx2V7jXUe9ZT6qhFX8IN7lYC27bIWhMkcwNkzBA5K4Jpp7FsAxsLBQ1VcaApHpxaAIdagluvxKVVoikOZNOpWG4qS3xUl/kLfuG8nKmqWvBSnpZtY5rL4T0KzlwZKvg52usrkbmzuSnWhb5t2/SPRdjRXl+U8602RQ0sqhvLqWkop+NMP8bV2YL+zlH6u0YpKfffNs+ivDrIpruarwcWuazJ0XcvUF4d5Mmf30dNUznqTW8stm3TfXGIH3/jHSLhxPXbVVWhdcPSe0I5VBc1njZqPG1krTTR7Ajj2QFC2T5CmUEmckPEciESRoi0lWQpBBoKKi7Ni18vJ6BXUOqsodxZT4WrkQpnI0FHJbq6MpoDRbMdjKePkp1D2WBNcdHgfxqPXlW4gQGWbRDPdhLKnCSavUQ810PGGCVjhTGsFJadxcZCRUdVneiKF6dWgksrx6PX4NUb8TmaCDjb8TuaURUnigQZYhmoLQ9QVSpN8W5HVZTJPMMCsu3F22I8V+e6C18Vsr2+Ql5B56g84IUibIaybRgYm1sBIDF7Ra8KtW5HEyc/6mBibLIqk2GYfPDKKdZtb8Kl3foCtLTCz6ZdLbz9wjEyqcla2eNDEV77/seMD0XYtq+d+pZK/CWTEW88kqSvc4TDb5/nyNvnyWU+2VakaSrb71naTWucqptK9xoq3WuwbYuEESGSGyFmjJMwwsSNMPFciJgxTswIkTJiZKwkOSuFXaA/Sqfqxa168WgB/I7JQMLvKMevl+PXywg4KihxVOPRgqgrMBE7mr1MZ+TvieeuzPoxDjVAhXt3wQIL27bJWVH6Ey8zknyPcOY0GTN0y/tbZLGsLAZx0uYnb64KDjx6NQFnO+XunTQHPotLKy3ImIXIp6pSv2xpuANVAa0I0+fLIazIGSYdA2MFP097Q4Vs952j8qC3KKs8NjA0XpzKoKtR0TcAbtvbzus/PHw9sAD44OVT/OyvHqCyznHLP0Sn28HarU1s3NXCiQ8uXb99fDjCWz8+yqmPLlNVXzbZ70KZLGU73DNOaDR2fQvUNXXNlWy+u7Uw32ABKIqK31GG31F2/TbDypI0IySMCAljgrQZJ2ulyVpJMlaStJkgYybIWikMO4tpm1i2gWWbmEz+27YtFEVFVTRUNDRFR1UmP2uKjlP14FJ9uDU/bs2HU/Xi0iZv8+kl+PRSvFrJilmRWI6yZpjLkb+hL/6TKYHCXNnkSBr9JI1+LDtHo/9poDRv4xSiUMr8Hkp8njvfcTVTFNnleNVwOFbw/hWKAk1VpQU9x0rkcTrQNRWj4P1QbMaiiTvfTcxL0QOL5vV1rN3SyOCVMTLpHIqq4A96SCdv3xRFURTq26q4/+kddJ7tn9IgzzBMhvvCDPeF73h+TVd5+kv3UFqxvJfOddVJUK0i6LhxJty+OoOdIWunyVlpclYG0zawbAsbE8u2sDCxbfPqyoaCqqioaKiKhsLVQEPRcCgunKobh+rBqbpWfTlYXfHg1MrQjVFMO43N4lZAsW2Ljug/cCX2PQxr+oukgo5TK8WhBtEUJzYWpp0ma0YxrNgtx1/jvQ+HujRykIS4HU1TKfF7pAmZmLXOwRBWgbds+T0u/B4pJjBXiqLg1HXS2cIWrrFtGI/OrcmymL2iBxZur5P9j2/l7JEuSir87HloM5vuaqa8puSOj/V4new+sJErFwZ57QeHrm+Jmov7n97Jg5/eNZ+hLwPK5B+m5sGJzODlW6lrExvLfpOsOYFpZzHtFIaVwLCSGFaCWK6L8fQRLLvwnUMBxtOH6Yn9+KagQsGtVVHjvZ9S16arSdkeVEXHxsa6Ou6MGSaZ6yeW6yCauUTaHMXGxKs3Uu7aga7I80csfX63kxKfWxK3xax1D4ULngtSVepHUxXZCjUPziI1uQxJYFEwi1ILbfv+tfz6//gcpRV+mtbV4gu4Z/UHqCgK1Q1lfOpL95BN53jvpROzbnSnqAoPP3cXn//vH132qxVicbj1KtxXcyVsbGzbwLKzWHYO084yknyficzZogUW3bHnyU7Jp1DwO5rZUPablLu24darUJWZtqnZWLZB1oqSMcZJm2PEspcJpY8RcK7Fo9et+tUpsTwEfW5KfO4731GIq7oGQ4Xuv0Z1qZRTny/nLJseL1QyncUwTXRN+mjl26IEFoFSL3sf2YyqqXP+49M0lTXravn533qUxvZq3vzREXovD2PeZk9e66Z6HnruLu59chv1LZXyBy8WTEFBURyoyidbMJx6OQrFuSDPWXHG00enbGfSVR9rAj9Dne8RtBkDimsUVMWBW6vArVUQZB3l7u3UeB9AVz04JWlbLBMlEliIOeoZmSj4ikV1mR9VrjPmTgFHkQILy7ZJZXIEvBJY5NuidW/RFrDcpTs0GlqreOoL+9lx7zo6z/bTcbqP0aEJEtE0qqrgC7ipaaqgfUsDa9bV0tBSiS/gQblDMz0hloOMMY5hxafcpitearz33SGomE5BwaH6cThlJU8sL36PU/ayi1mzbJuhULTg1asOnu3ma//1R3ds3ituYtsMh4pTrcm2IZHOEfDKxES+Ldu2kIqiECzzESj10ryuhr2PbCabzmEYJoqioOkqbo8Tb8CD06XLKoVYUQw7zs3FHRVUdEWCA7F6uJ0OPC5J3BazE0mkSaYLv1V1JBxnJBy/8x3ForFtm2Rm7nm64s6WbWBxjaIouL0u3F6ZtRKrh6ZeayT0CdPOEM1exOuoW5xBCVFkbqcDt2vZv42JIhkJxzCt5dBtQxRDzljcyo4rlWRoCrEMefV6dNU35bacFaMz+o+kjNFFGpUQxeVx6nicsmIhZmc4HC94qVmxfJimBBaFIIGFEMuQqjip8uxD4ZNcJRuD8fRRjo78jwwn38ey5UVTrGxup0MCCzFroWiy4InbYnmwAcMqdCO+1UnWkIVYhhQUWoO/wEDi1Sl9LCw7w3j6KNGRy5S7d9AS/Dkq3XvQVNkqKFYet0vH6ZS3MTE74VhKVizEdbItrjDkFVmIZarEuYF1Jf+C8+E/n1J21sYka4UZSr7DaOojAs42Gv1PU+s9MNmjApVrzRSFWK4cuobLoaMgz2MxOxPxZMF7WIjlQ1avCkMCCyGWKUVRWVv6K1jkuDzxN5h2mqmVoixMO8VE5gwTmbNcCP+/VHn20uj/NOXu7ThUPwpSMU0sT5qqoKkq8vQVszURT8vFpBAFJoGFEMuYquisL/0qZa7tnA/9N2K5Lkw7xc2laMEmZ0UYSLzKQOINSpzrWRP4DDXe+3Frkx26JcAQy4mmqmiaPGfF7MWSGQkshCgwCSyEWOZURafacy9lddvojf8zvbHnSRoDGFZiyhapT5hEsuc4NX6O7uhaWoKfp9p7Px69WlYwxLKhKgqaIvVHxOylsznZCiVEgUlgIcQKoCgKTi1IW/CLNPqfZjDxGgPx14jlushZsaurGNNFc5c5Nf6fqE6+S3vJVyhz70DDLcGFWPJUVZHOxmJOkulcwbtuC7HaSWAhxAqiKAourYyW4Odp9H+K8fRxhhJvEsqcJG2MkrNi2BhTHmNjMpx6j7jRw8ay36LWewBNcUtSrFjSNFVB02TFQsxeKpNFliyEKCwJLIRYoXTVR433Pqo8+0nm+hhKvsto6iCxXAcZcwzLzk25fyLXw/nwn+PSyqlw70JRpD+AWLpUVUWTFQsxB+mcISsWQhSYBBZCrHCqouF3NrPW2UxT4GlGkh8ymHyDUPokGTMEfNIkKJHrpjv6A/yOFtxalWyJEkucPD/F7BmmNEQTotBkHVmIVcSlVdAU+DTbKv417SVfwe9ovtrX4hPDyXdJ5HqxkTdhIcTKYNtgSadlIQpOAgshViGPXkNb8BdoCXwOt1Y15WuGnSSSPY9lZxZpdEIIkV+WbUt6hRBFIIGFEKuUpnqo8z1K0Ll+2tcSub5pORhCCLFcyWqFEMUhgYUQq5hHr8GllXPzS8HkaoVM7wkhVgbJFxOiOCSwEGIVszCwMLg5iNBVH/LyIIRYKTRVkVx/IYpArhyEWIZMO4udhw3D8WwXKWOImwMLr16PKuVmhRArhKIoqLJqIUTBSblZIZah/vhLWLZBqWszQec6VGXuf8opY5i++E+IZTun3K6rfkqc69EUZ76GK4QQi04vQkNFTVXY0lqLQ9MKfi4xfy6Hjt/jWuxhrEgSWAgxJzaWbWDZWUwrg2lnsOzJz4ls9/Su1rZJLHcZVdHRVBeq4kLDdfXfzqsBwdxn0YaT7xPOnMbvaCbgbCfgaCPgbMWnN+DUym652mDbJhkzzET2HMPJdxlKvE3WCk+5T5VnL15HI4oib4xCiJXD6Sj8JY+uqfyLp/YS9LkLfi4xf5qqUF8RXOxhrEgSWAhxB6H0CUZSH2BYSUwrjWVnschdDTBykx/kyBjjGFZqymNNO0Nn5Ns4tRIUxYGKA1XRUa//23k94Kh0302lZy/qrC7obdLGCCljgLHUx7i1qslEbL0Cp1qKW6tAV32oihtV0bBsA8NKkrVCpIxhErke4rleTDs55agevY41/s/g1Mry+BMUQojF53E5UBQKWnbWMC02tdRQGfRKwrhYlSSwEOIOIpnzdEW+g2EnsWwD5tA4zsYkkj1/m3uok4EGOgoqFZ7dwNxWCmwMUuYgKXMQMpPH1FUPmuJCwYGiqNi2hWVnr34PM/en8Gg1tJd8hXL3LtkGJYRYcbxuJwoKdgEr3pmWTTZn3PmOQqxQElgIcQemncWwElgUoq+DdXUFJIs5hxKvN3fLvvmYhpXAIDHrUZQ4N9Ea/Dy1vodxqIFZP04IIZYLn8uJolDwStqpTA4bKUIlVicJLIRYhtpLv4Jbr2Yo+TaJXM+8jqGg4XOsoc57gGrvA5S4NqArPlm+F0KsSAGv6+rrW2Eji2Q6i0QWYrWSwEKIO2jwP06paxP2HLZAzYdHr0NldiVeS52b8ZTU0uB/ilRukEj2AolcD2lzlLQxTs6KYNrZq92zzclcDsWDQwvi1evxO5opdW0i4GjDq9fj0ErmVVlKCCGWi1K/pygTJ8lM7up2K4ksxOojVxJC3IFHr8Wj1y72MKZQFA23XoVLq6TEuZ5Kz90YVgqLLJaVxcKYDIRsm8mpMxVFmczn0BT3ZJCh+lEVl6xQCCFWhfKgB7UIL3eRRLqgCeJCLGUSWAixjCmKgoIDp1aKUytd7OEIIcSSVR4oTqWm0Yl4XhqYCrEcSedtIYQQQqx4FUFfUbpvj4TjWBJYiFVKAgshhBBCrHi1ZYGirFgMh2OyYiFWLdkKddVYppc3h791wy3XXnzsGW678fbJ21p829he+iguzVe4Qa5ytm1hYc67BrmKfnXrkOQUCCHEalNXGUQtQpKFrFiI1UwCi6tSZoxLsY/m/XiX6mFzyYO48jgmMdVIpps3h79Jd+LUvB7/QNUX2VvxGXRVmr8JIcRq43bqVJb4iCVnbhKaL8PhGLZlY9u2FMcQq44EFtfYLKgbZyE7eYpJuuLEpXox7Oy8Ht+fuoCFmedRCSGEWA4URaGxspQrQ6GCVm0aCceJp7J43TKJJVYfybEQy4ZDdeHVS+b9+KFUB6ZtyN5XIYRYpVrrywq+imADlwfGZLpRrEoSWIhlw6G68WrzDyyixiiJXDiPIxJCCLGctNdXFqUy1KW+UaSZhViNJLAQy4ZDcS5oxQJgIH1Jtq0JIcQqtba+oijlOy71jUlcIVYlCSzEsqEpDtyqD1XR5n2MgeSlyY7UQgghVp01NWW4nIVPL73UNyaVocSqJIGFWDYURcGhuXGr/nkfYzB9UXIshBBilfK4HLTWlhf8PL2jESbiqYKfR4ilRgILsaw4FBceLTDvx49lejHtnAQXQgixSm1tqyv4OQzD5MTlgYKfR4ilRgILsaw4VBdubf4rFlkrRSw3lscRCSGEWE62FyGwsG2bj871FPw8Qiw1EliIZWUysFhYd/PxbH+eRiOEEGK52dhcg9Mx/1y92bCBY5f7yeaMgp5HiKVGAguxrOjKwlYsQAILIYRYvRSqS/201BQ+z2JwPMqVISlxLlYXCSzEsuJQnLjVha1YhDISWAghxGqkKKCpCns3NRX8XKZp8e6pzoKfR4ilRAILsaxoqhOX5l3QMcYzfXkajRBCiOVGUxX2bFxT8PMYlsU7JzpJZnIFP5cQS4UEFmJZ0RUnTnVhgUU4O4Rlm3kakRBCiOVEURTWN1ZRXbqwbbV3YtvQPRTmdOdgQc8jxFIigYVYVnTVgWuBgUXGSpCyYnka0eqlAKpS2B62NkiTKSFEXimKgt/rYs/Gwm+HSucMXjtyseDnEWKpkMBCLCsqGg7Vhcr8K3rY2MSNUB5HtTopioKuFfYlxLZtDEM6pQsh8supqzy4o63g5zEMk6MX+xkcjxb8XEIsBRJYiGVFURR01YlDdS3oOIncRH4GtIqpCjj0ApdstG1yhmxbE0Lkl6aqbFxTQ11FsKDnsYGRiTivfHyhoOcRYqmQwEIsO5riwKG65/34yRULKQG4UIqi4NAL+xJi2TaZnIHshhJC5JOiKJT63dy7taXg50plcrx+9BID45GCn0uIxSaBhVh2NMWBQ1nAioVtkzAm8jae1UpRFDRVRVMLl2dh25DOGqSy2YKdQwixOrmdDh7ZuRZHgbd0WrZNz8gErxySXAux8klgIZYdTdHRVce8H29jk5AVi7yYXLUo7HaonGESiacLeg4hxOqjqQotdWVsbasr+LkSqSxvHb9M3+hEwc8lxGKSwEIsO5qioSvOBR0jYUpgkQ+6puJxzT/Im41sziAUSxb0HEKI1UdRFII+9/+fvf+Ok+u677vx97lt6s72ggUWi95BAiAIEuwUq3qXJdmyLFuyncROnjj+JU6eJ7/EeZJfEsd2Ylnusmyrd4kiJVJsYgVIgkTvbVG2992pt57fHzMLAtgFsbNtZhfnjde+djGz997vztw553zOt/HgLWtm/VqBlLR1D/Gjlw/jB6oghWLhooSFYt6hCQNdm46wkGT91IzZcyNjGjqV8cisXiPneKqiikKhmBXClsktaxbT2lQ969dK52xeOniW3UfOz/q1FIpSoYSFYt6hoaNjTPl4CXiBPXMG3cCEDJ3qWRYWWdvlYu/wrF5DoVDcmGhC0FBdwYPbVs/6taSEiz1D/OjlQwyMpmf9egpFKVDCQjHv0ISOLqYuLAC8wJ0ha25sTNOgapaFRTrn0Nal+o4oFIrZoSIS4s7Ny6mvis36tVw/4MCZTn708mECFRKlWIAoYaGYdwgEmpjOrSvxpKoyNBPMhcfC8Xw6+kfoG1bhawqFYuYRQtBSX8Ujt66dk+sNJ7M89fpxnn3r1JxcT6GYS5SwUMw7BAKYXolTJSxmBss0qE1EZ/06Q8ksx8/3zvp1FArFjYcQUFUR4f6tq1lUWzHr15PAuZ5BvvX8PvadakeqRj2KBYQSFor5h8jvME0HJSxmhmjYZHF95axfp38kzZ6TFwnUBKxQKGYBgaC1sZr37dzANKeXSSElHD7bzT8+9SZtXYNqbFMsGJSwUMw7pJQEcnqxqZ70ZsiaG5uQadBQXUE8Mo2GhZMgnXM4eq6Hzn7VuVahUMw8QkB1RYS7b1rB2paGOblmICWvHT3P3z7xGhe6h1QZWsWCQAkLxbwjwCeYrjCYpjBRvE08YrFkDrwWnf0j7Dp8TiU8KhSKWWN5Uw0fvHMTIWt6BUImi+cHPL/3NH/52C7OdAzg+Wp8my5SShzPJwiUF6gUKGGhmHcE0seT06vqpE+jc7fiSuKR0JwIi97hFK8caqNnUCVxKxSK2SEatrhl7RLu2Lhs2iG3k8UPAl7Yf5q/eXw3x8734LjKoz4VXM9nOJXlbOcArx09z1BKNVYtBUpYKOYdbmBj+9OrAT7dzt2Kt0lEQyxtnP3mUlLCyfY+nt17EltNvAqFYpZobaziPbetY1HN7Cdyj+EHkpcOnOUvH9vF68cukMraKql7EkgpydgOnQOj7Dl+kb97/DX+1Zd+zN8+vpv+YdUrpBTMja9PoZhBnCA37c7ZuhIWM0ZFNMyq5lrClkHOmd0Ff99wmuf3nmbDsia2rlqMps3NjqJCobhxMHSdLasW8+7b1/PNZ/eSteem71EgJW8cu0D34Cgfv/dm3rV1FXVVcQxd7QFfjpQSx/UZSWfpH8lw9Hw3Lx44y8EznaSy+cIslbFwia28cVHCQjGvCGRAzk+S9UencRaBIVQo1Exh6BpNtQmWNdVw/MLsl4Q9fqGXH798iIaqOEvqK+csXEGhUNw41CSi3L9lJScu9LL7yDn8OYzXv9AzzN8+vpvzPUM8umMtqxbXE4tYaDfwWCelxPMDhlNZ+obTnOseZO+pdt460U5H/8icvj+Kd0YJC8W8wgmyjHoD0yoXK4CwPvsdVm8k6itjrFvaMCfCwvF8Xj18jppElE8/sI2G6rgSFwqFYsZZvbiO99+xgY7+Edq6Buf02smsww9ePMjhtm7ec9t6bl3XwtLGakKmfsOMd2NJ2EPJDAMjGdr7Rzh4ppO9Jzto6x7A9VSiezmihIViXpHxRhi0O6Z5FkHcmP2cgBuJmkSUtS31mIaO6/mzfr2RdI6fv3GCkGnwobs20VSbuKF38xQKxcxjGDo71i2lvXeEbzy7l8Hk3CYDS/Ie2rOdA2xf28JD29ewYVkjS+orCZnGghQYUkqSWZv+4TS9wyk6+kc4caGXo+d7aesamPVwW8X0UcJCMY+QJL0Beu22aZ1FADElLGaUsGWybFENSxuqONM5MCfX7BtJ86OXD5O1XT5w50Zam2qwDH1Orq1QKG4MErEw79q2io7+EZ7ac5xMbm7yLS7H8Xx2HTnHobYutq5ewu3rl7K2pZ7lzbUkoqF5LTCklKSyTt4rMZqmfyTDue5BTlzs41R7H539o6p54DxDCQvFvMENHAbsdobsrmmeSXksZoPWxmpuWbOEs50DzNU0MJjM8JNXj9AznOLdO9axdfViKmPheT3RKhSK8qKloZoP3LmRvpE0rx89jzMHXtmJSGZsXjpwhl2H29jQ2sj2dS2sbalnSX0VzXUJEtHyT1h2XI/RjM1QMkP/SJq+kTSd/aO09w1zoWeIC73DJDN2qc1UTAMlLBTzhqQ7wIXMYVw5vUFHCEGFWTdDVinGqE3EuGnlIp7fd5r+kbkr85fKOTy/9zQXeoa4+6YV3LZ+KetaGohFrHkjMMZiiT0/IGTqGLryvCgU5YIQsGFZIx+/7yZG0zkOt3WVNFnY8wMOnu3i4NkuGqvjrFpSz+rFdSxvqmFxfYK6yjg1iSjRkEWphkDPD8jkHEbSOYaSWYZSGYaSWQZHM/SNpOgZzIc5dfaPkJmjqluKuUEJC8W8wAtceuw2LqQPz8DZBLXW4hk4j+JyDF1j9eJ6Ni1v4oX9Z+b02lJKTrX3c6FnmL0n2tm6ZjEblzWxZkk9jTUVJS/XKKUk53ikczaprEMq65DOOaQyNslsjmTGJpmxaayp4I6Ny1hUmyipvQqF4kp0TWP7mhZG0jnSOYcznQNl0WeiZyhFz1CKXYfbqI5HaW2qpqmmgobqChqqYtQXREZFNEQ8YhEPh4iETPQpjolj1Zls1yPneOQcl6ztkso6+XEsa5PM5Me0yz0T/SNpBkbSpLKOCm1a4ChhoZgHSJJePydGd5H0ph+/b2ohqq1FM2CX4moW11dyy5ol7DvVwUg6N+fXt12P/Wc6OXK+h5b6Kla31LGssYbWpmqaaxPUV8WpS0TRdW3a3gwpJa7nk3M9crZH1nbI2PlJNmO7pHMO6axNKueQzjpkck7hZ/sqYZH/clyfOza2sn5poxIWCkUZErIM7rlpBTnb4+vPvsX57qFSm3QJKfOhoWMJ5kJANGRRVxmjJhElEQ0Rj4SIFcRFNGwVvKPapa+xcTEIJEEg8YMAPwgKP0ucy8REzvWwnfz/88LCvkxY2GRtVwmIGxQlLBRlT87PcCb5JmdTe2fkfAmzDkuLzMi5FFcSCZlsX9vCmycu8uKBsyWzw/V8znYNcLZrgJCp01iToLE6Tk1FlJpElMp4hIqIRTxiYRlGYWLVESLfpErK/MTq+QGeH+D6Pq4X4Lgejutf2q2z3cKX45F13Evfc45HxnbyIiPnqklWoVggxCMhHrhlNY7n8c1n99LRP52eSrOHlOQ3N3IO53uuFECaEFimgWXkxYSh5b/rmnZpDLxcXIz93/F8HNdTPSMU74gSFoqyxgscLmYOs3foKbJ+ckbO2RBaNiPnUUxMa1M1d25azvELvfQMTa9D+kxgu34+KbAwuQogHDKJhEwilolp5CdUXdNA5D0RUua/53fsJL4f4PoBnufj+gGu5+N6vhILCsUNSGUszCO3riUIJN96bh+dA+UpLq5FIGXe6zD1dlAKxTVRwkJRtviBS0fmOLv7f0CffWHGzrs4sn7GzqUYT8g02LF+KftOd/DzN06U3eJbAtlCyJJCoVBMheqKKO+5fT2GrvG1p9+ad+JCoZgtSpvRqFBcAy9wOJPeywt9X6M9cxxmqICpQLA0tmlGzqW4NotqE7xr6ypWLq4ttSkKhUIxK1TFIzy6Yx2/8d4dLKmvKlkFJoWinFAeC0VZIaUk44+yb+hJjoy8RL99kZkSFQBVVhNVZsOMnU8xMYauceu6Ftq6BxkYzTA4OrcdaxUKhWIuSMTCPHTLGhLRMH/zxGuc7RgoOy+tQjGXKGGhKBucIMuJ0d0cHnmB7uwZMv7IjF9jaXQTumbOm/4G85mKaJhHd6zjfPcQz7x5smRNpRQKhWI2iUVC3LlpOYlYhL9+bBcHz3aqBGfFDYsSFoqS4gUuffY5zqUPcCa1lyGnk6Q7iCSYleutS9yBpiIA54xFNQk+fM9mugZG2Xe6A7WRp1AoFiIhy2DLqmb+4JffxVeffpOnXj+BH8zOPKZQlDNlIyy8wEHOYMhL0deX00vklAR4gYMbqFb0VxNID0+6OEGOrD9Kyhti2OlmwG6nN3eetD9Mzk+S81Ozeg/UWItZFFlNvi6QYi7QNMHG1iZ+9ZHtZGyX4xd6S22SQqFQzAqGrrGyuZbf/fBdrGyu5e+eeF0ViVDccJSNsPjexf/KsNNTsut70xQEp5J76MicQBP6DFm0kJD5fzIgICgIDQ8/cPDk3AnKtYnbsbSICoOaYyxTZ8f6peQcj7/+yW7OdQ+W2iSFQqGYFYQQ1FfF+eg9N7G8qZYv/vBl2rrUmKe4cSgbYTHs9DDodJTajCnjBBmcQCWoliuGsFifuAdDmKU25YYkZBrcc/MKbNfjbx/fXbZNpRQKhWImiIUtdm5spbWpmq/+/E1+8uoRldStuCFQweaKG4INlfdQbTWiwqBKR8g0eHj7Gn7vE/exvKlGvRMKhWLBIoTA0DWWNlTxLz96N//18+9meVNNqc1SKGadsvFYKBSzhSlCbKt+N5YWVWFQJcYyDe6+aTmNNXH++FsvcPhcN56vEhwVCsXCY2y+SURDPLhtNTevaOa7L+znhy8fIpW1VTGLGUaQz+tbVFfJg7espb4qXmqTbkiUsFAscASbq95FjbUIofbIywJd01jX0sD/+K338mfff5mXD7WRyqqiBwqFYmEihEDTBI01cf7ZB+/g4e1r+fozb/HyobNkbVeVpp0mhq4RtgzWtzbyvp0buHPTMirjETXjlwglLBQLmhprEbfUvJewXqG8FWXEWILjf/n1R/nZ68f4ypNv0Nk/iqt6XSgUigVIfvoRmIbOutYG/uNnH+LA6U6+/fx+9p/uIJ1zlPe2CAxdI2QaVFVE2L52Ce+7fQMblzURstSyttSod0CxYDGExc66j1FlNSlRUaZomuB9Ozdwy5ol/NVju9h99Dyj6ZyaYBUKxYImZBrsWL+UzSsWsf90B4+9eoQDZzoZTeewHa+ExffLF10TREImiViY1Uvquffmldy+YSkNVRWoKb58UMJCsSDRMFifuJMV8a1YWrjU5iiuw6LaBP/51x7hlUNn+f6LBzlxsY/hVFYJDIVCsaCJhEx2blzG1tWLOXquh6f2nGD/6U76h1Okss4N32TPNHRiYYt4xGJxXSU7Ny7jjo2tLFtUg66p+kPliBIWigWHQGNJdB07aj9EhVFbanMUk0TTBHfftILbNrSy6/A5Ht99hFMX+xlOZ8nkFnaTKU0IQpZBPBLCNNRkqVDcaIQtk21rlrBl9WIu9g7zysGz7D56nva+EYZTWdJZ54YoVyuASNikIhKmMh6mtbGabasXs2XVYpYvqsE0VK+wckcJC8WCQiCoD7VyV/0nqQ+3IoRapM0nhBCETIP7tqzi9g2t7DvVzquHz3G4rZu+4TRDqQyOO//zMAxdIxoyiUUs4uEQ1RURljZWs2PdUhpUJROF4oZFE4LWxmpaH7qFj9xzE8cv9PDa0QscOttF73CKkVSO0czCCRfVhCAaNolHQlREQlTG82FON69sZvOKRTTVVJTaREWRKGGhWDAINOpCLdxR/wkWR9ehC3V7z1eEyIcI3LFpObdtaKVvKMXrxy/w1sl2LvQMM5zKMpLKks45ZV9RxTJ0omGLaNgkFraoiISorYyxtLGK5U01rGiupaW+imjYKrWpM4Zp6KxormHnhtZZu0YiHqaxRomwyRALW6xf2shsBu63NFRRGVNhpzNJJGSydfUStq5eQiprc6q9j4Nnuzl6rpveoRTD6Ryj6SzJjF324yDkRUTYMoiFLaJhi3gkRE0iyrKmalYtrmP14jqWN9dgGWruns8IKcvDt/ZY+x/TnTtDyh0mF6SY1RFQseDQ0GkMr+D2uo+wquJWlVexQHE9n56hJCcu9nHyYh9tXYP0j6RIZmxSWYdU1ibneHMeMqBpgrBpEAmZRMNW/nsovwtXm4jRXJtgUV0Fi+uqWFJfSU0iiqayDRUKxRTw/YDO/lFOd/ZzuqOftq5BhpIZRjM2qWx+LMzYTsm8u6auEbZMwiGTSEFIxCIhquJhGqsrWFSbYHFdgpaGahbXV2LqmiqwsoAoG2Ex7PTQkztDT+4c/fZFkt4AKXeQtDeMK3OlNk9RxlhamEWRNeyo/SDLY1swtVCpTVLMEemcQ1f/CB39o3QNJukeHKVvOM1oOkfWdsm5LrbjkXM9bMfD8Xx8PyCQkiCQ+EH+Zynzsb1CCITICwVd0zA0DV3XMHQN09CxTAPL0AmZOiHTuDR5xsIWVfEwtYkodZVx6irz3xur4wvKE6FQKMoLKUFKSf9Imo7+YTr7R+keTNI/kmaokJuRdVxyjkvO8bBdD9f1cX0f1wvw/AA/CJBSXhoLIe9dGOu/oV323TA0LEPHMoz8mGjomIUxMb+hYlERzYd3VldEqUlEaaiK01RTQW0ihmWqHImFTtkIizGklLgyR7/dTl/uPP32BYacLpLeAEl3gLQ3QoBXajMVZULcqGFl/BZurn6I5shqdGGW2iRFibFdj8HRDMOpHMlMjmTWJpWxSWZt0jkH1/Px/ODSV15oBPlJVAg0TUPXRH7yHBMSlnFp0owVQpri0RCJaJjKWJhwyFQeCIVCMed43lk89zhSphEigq4vxTDXAwa26zOUzDCcyodLJQvjYMZ2yNleQWi4uH5A4Af4gbzk7dULmyu6rl362dDzY2E0ZBIN58fDMe9sLGJRFYtQGQsTskxV/vUGpuyExdUE0ifjjdBvX6TfaWfQ7mDY7WHU6WXU6yfnp5AqbOqGwxRhGsLLWJvYyfrEnVRajaqztkKhUChuGHyvg1Tyf2HnXiQIhtC0BKa1jWj884RCd5XaPMUNStkLi6txA4dRt48Bu51Bp4Mhp4tht4dhp4ek248r7VKbqJhFdGFQYzWzPLaVVRW30hxZS0iPlNoshUKhUCjmlHTq70mO/Bfg8nLcFuHIo1RW/wVCqLAjxdwz71LvTc2iNrSY2tBipJTkghTDTg9DTte4r7Q3TMD8L02pAFOEqA+3sjiyltbYTSyJridmVJXaLIVCoVAoSoLrvAlcXXbWwfPOIGUSIapKYJXiRmfeCYvLEUIQ0SuIRCpYFFmFLz0y3jDDTi/DbjfDTjcDTieDTjuDdid2kCm1yYoi0NCptBpoCC2jObKaRZE1NISXETMqYR6FPQUyRzr3Ehl7T9HHJqIfIGxuLGk/DildUrmXsd1jBDKLodcTtXYQttaXzCaFQqFQXGseFKjKmopSMa+FxdXowqDCrKPCrKOFDbiBTdIdYMTtZcTtZdDpZMBup9++wLDTo7wZZUjcqKHSrKfGWkxduJVaq5lqaxHVVhPmPC0hK6VDOvcyg6mvFH1syFxL2FwPlE5YpHLP0Tfy5zjeaaS00bVqYuG7qKv814SMFSWzS6FQKGYLKXN47hl8rw0A3WjBMNYgtPIJvbWsHeSyP4Mr1jJhDGM9QqgeL4rSsKCExdWYWoiaUDM1oWZAkvVTJN0BRt0+ht3efEJ47jz9djtpf6jU5i5oNHR0YaAJA0OYhPQoYT1ORK8grFdQYdRQaTYQM6qJGZXEjVoSZi2Gpkp1lpqh1NfIuQcY2wHzgl5SuReJWLcQqlDCQqFQLDx8v4ds9nvYuRcACEfeQzTWjE75CItQ5BEi7hHs3HMEwSCaVosVupto/LMIVSFRUSIWtLC4kkLYlF5BfaiVAJ+0N0zKHaTPPs+ewcfpyZ2d8tmXRNazofIeQlp0Bm1eGOR7A+hoaGhCQ0PH0CxMEcbUQphamLAeI6zH0dAXZqOceZpEJ/HJuUe52q0eyCy2e6o0RikUCsUsE/idOPZufO9k4f+3QJmVutf1RcQqfodQ5GFkkEaIGIaxAt1YXmrTFDcwN5CweBshBDoGCbPu0ld79ti0hEWV1cT6yruI6VUzZ+gCYkGKhUmiiQhV0U8QsbYQBCn8IEkgUwRBiiBI4sskjtdWWKiX18QFAsH4hoMCoXbEFArFgkRKH9/vuhQGVc4YRiuG0VpqMxSKS9yQwuJqDC1EjbV42ufJL7Zu3AW0YmKEMAlZ6wmZa5G4SDn25Vz6/2j2JwyM/jWBTJba3CsQaMTCdzGc/g6XVx/RtATR8O2lM0xRFH4wiu2ewvd7QWiEjDVYptrVVCgmQsqRQmWlVKlNUSjmHUpYkM/FqLaaS22GYgEjECB0BDqI8Unoht2Yr/xUhoU8ait+iyDIkrZfRcoUIXMNVbFPEwvdUWrTFJPEcU8zkPwLbPcEYFJb8ZtKWCgU18D3+/DcY6U2Q6GYlyhhQT6xOG5UE9bi5AK1Q6FQXI5lrKSx6j/gBUOAhybiGHoTuqaqjswHJAGOf5G0vZsgGAUM/GCk1GYpFGVL4PfhucdLbYZCMS9RwoJ8/H9Ii1BlNdKdU8JCobgcITRMYzEm0w8XVMw9QZDEcc8SBOUVZqdQlCNSOgR+B77fXmpTFIp5SemK45cZpham2lpUajMUCoViRvH8PmzvBGUZZ6dQlBlBMITrHaP8CmkoFPMD5bEoYGlhalSehUKhWGB4fi85R4V13OhI6eN753GcV3Cd/XjeOYKgHykdhAijiUp0oxHD3IRp3YJlbUOIMNfu7jx9fL8X13kNx34L3zuL73ciZRqJRNNiaPoiDGM1lrUDy9qBptfNmi0AUnr43gVcZ9+sXmdhIwn8AVz3AI5zAN87je93EgTDSJktFLkJIUQMTatHN5ag662Y1iYMczNCxGehCE6A6xzFcV7Dcw4W7v0hJDZCWAitEl1vwTQ3Ylm3YVo3Fe59xVRQwqKA8lgoFIqFhpQert+JOw/KZiqKR0rJ8MCv4bhvXnrM0FdQVft36HpT4Xd8PPcomdTfY9sv5CvPSY98t+axSm8CH4HrapB9FiEMdGMF0dhniEQ/MuMCw3UOkcl8FTv3PDIYQV5hT96zFvgC3FM4vEpWfANNqyMUeZRo9JcxzFXTtEAiZYDvncdzj+F5x3HdY3jeSQK/Bykz447IZn6Q73ItJh/oITCJxn+deMW/LNrCIEiSHPlP5HI/L+o4TcSJRD9FPPF/FX3N6SBlDsfZTzbzbRz7VWQwPMH7OuY1HbuXNLB1EBoCA0QI09xCOPIoofCD6HrjNG2yyeV+Tjb1T7jecaTMgvS58t7P2+FxCDv7NEJYGMZyIrFPE468F02rmZYNNyJKWBQwhEWlWY8uLHzplNochUKhmDZ+MIjtHkeqsI4Fi5RJZDB06f++6MFzT6FpjUg5QjbzI9LJPycIerlyMXXFWQpfAeAhJXjuIUaH/z257BNUVv0Rmr5kWjvJUgYEQR+Z1N+SzXyfIBh4B3vGbMovAqV08P00mdSXsbNPEo1/lkj0kwhRVbRNdu5l0skv4rrHkDJdsGFs4ftO9jhI6RQVUSgx84vZKSGRQeqK93YyBMKbxjWLQ0oJuHjuUVLJv8Cxn0dKm3d+HeHtF7GwyJeFR2QKx34e13kTkERjvzJFu3xc5wDp5J/gOK8XXo93euPG7gEPKXO47kHc4ePkMj8kVvG7WKF7YKE2750FlLAoIARYeowqq5EB+2KpzVHMAvlB0ENKr7DQCkBKZGHAEZC/EdAADYGOEDpgFAYUNaiUmvx7GBT6fxR2w2Tw9j5Y4f0TGAhhAGb+LZ3D907K4FJ/ksvtu/z+yu/OGQU7ZyfVTUqJ5/eRcw7PyvkV5YmUWTzvJKa5kUzm66RG/xSYymZZfrx07BcZ7P80NfXfRtenVsAh7zU5THL0f+LYrwLulM4DPr5/gdToH+O5x4lV/Ct0fVlRnyHPO4XjvI7KoZgeUkqkHCGXfZzU6J8UhOuMnBkhooTD756iXTa57E9Ijf4ffH+qnloJ2DjO63jD7cTiv00k+kkgqsTFJFDC4hL5ylDVVpMSFgsMKV0CmcEPhsnYb5F19mI7x3GDLnx/gEDmAIkmwmhaDF2rxdQXYxnLCFsbCJsbMfTGQhxymIW0cyGlhx+M5HfiikAIHU2rQhPWLFl2JVJKJA5BMILtnSGde5WccwDHa8Pz+wlkDoFA1yox9EWEzXVEQrcRDe3A0OvRRAym0cAyCNL4Mgny7V0vXa9CiHC+Rwn5xVMgU7heB+ncS6Tt17C9M/h+L1LmEMJC1yrRtXpC5nqioVuJWFsxjcVoIloQsVN6dQpmefnGiwXRJWWWrHOAnHt0gr9nFNfrKu4yQmBoDbMmhBQzhMziOgcRIkY6+UWuFBUmQkQQwiK/YWIiCUDmd+PzIUDjF/2+f5bR4f9MVc2XECJUnDnSx3X2kxr97zjObsbvHGv5UCsRRmACZl6FSye/ASRzSJnj8l1wKbNkMz9CSod4xe+hGysnfV8KoSNEuLAxMREB+dfgajvzm0zFbFIIYTL1ZZaG0KvRtEbAz79PBCDHdteDwt8w9xEWUkpkMEQm801So38C2Nf4TY38PWcBeiGMTPD23+EV5p7L7zmDUPgBNL12CnbZZDPfI538Er5/YfwviDCC8CV7hAgV7i2/cP9nufr1DPwO0sm/ACAS/RRCRIu260ZDCYvLsLQI1WZTqc1QzBD5RfMwWWcfI+kfksr94h07WwcyReCn8Pwe7MsWYwILy1xFPHwfldEPEzLXsVC8F453ke6h/5u0/WJRx5l6C801f04sfOssWTaGREoPz+8lbb/KcPpbZO29E4b2SMAL+vCCPnLuQYYz30XXaqmMfoDK2C8RMlYCkSmJi+H0d+kd+WMCOVx4RGdx7Z+TiLwPhE4QZLC9kwwm/4Fk5mcEjI/RltIj8DO4fhc59yAjme9gaE0kou+nMvoRQtaagnCdPEGQxg+GCWQaxz2H7Z3Cdk9huydxvDYCOTrBUR79yS/Sn/xiUdfSRAWrm/egi4qijlPMLVLmcOzncJ3XL8sVMNH0RizrFkLhBzCtrej6osICO8D3e/Hc/eSyj+HYbxAEfVwZziKxc89i535OOPKBImyR+N5Z0qkv4TivcfViXYgKDGMtoci7CIXuQzdaEaISkATBCL53Dsd+Edv+BZ57otAJe+wcHrnsz9BEBbGKf4WmN0/qs20Y6wq7z/6EzwdBP3buVaQcvOJx3ViJZW0tcmGpY1o3F/H7b6NpcRKV/w2Z+IN84nMwTBCMXPbzMK53BDv71DX/ltkg76lIkc0+Rmr0j5lY2JhoWgJNX4Jp3oRpbUbTm9C0KsAAmSPwe/H8Njz3WD4sLRgpvL8akehHp2CXi517lkzqK+NFhQija02EIg9hWXdhWTcjtBqE0JHSxfd7cJ29OPYvsHMvEQT9XO7RCoJuMumvoekNhMOPFgSj4looYXEZlhah0pxespCiPAiCNDn3KIOpr5DMPjOtmFOJg+0exfO7CBmrC8JCMdvkvRQ2OecAA8kvk8z+nGInUD8YYDD1D4xmn6Y+8a+oiDyKrtXMgMfJx/UuEMgUSI3RzBP0j/5vXL+TYoKwvaCbwdSXyTpvUlvxz4iH70PTYpM+Ppn9Of2jX8L2zjL18BLFwiIgCAaBsYVxGCu0nWjsC4TC94zzOAihYRjNGEYzofDD+R3f1F/ge+e4Uly4ZNLfJBR+tLDje32kHCGT+Sa2/TJXx91r+iKi0V8mEvs1NK163GdS12vQ9Rqs0FYi/qfJpL9BNvMtAr/jCpuyuSfQjGVEY7+KENdv2mmFbsMK3XbN511nH553Bs+9UlhY1i3EE7+Prs9dkRchDISoRtOqJ3zezr2AnX2WuRQW4OE6e0kn/xfjRYVAiASmtY1I9BOEwvejaYnrnjEIkrjOXuzcc/h+B1Zoe5E2STzvJJn0N/C8E1daJBKEI48Qi/8uurF8nGc4n6zdgmG0EI48imPvJpX8P4XKYG+Pqb53klzmRxjGSkxjfSGsVTERSlhchqmFqbQa0DAIVPzlvMX3hxnNPcnA6F/heGeZqfr9YWsLIWvdggoFmeP0g0mT3xXLkrJfoG/4jwt9GK6FVvgaS/Ycj+d30DX0H3C9DmoqPoeu1U1bXDjeOVy/h0zuVfpHv4g3YYyxIB9CAdeO6ZZknX30jf5vJD4VkUfQJhlu4nh5L8X1kyUVNyYWVugOKhL/BtPaet3fFsIgGvsUUuZIJ/93Yed2jADXOYDnncI0N173XFL62PZL2LlfwFVVljStgXjF7xOOfGASQlqg643E4r+JrjeRSv4pgd/59nWCYezs45jmBqzQ3dMIKVRcDyklgd9HKvklgmD4qmcFmtZIJPoJovHPFVXRSdMqCIXvJRS+h/xYVtx7GARpctmf4DpvccV8LyJEY58kFv+dQmjVO4/5QoSwQndTocVIjvzXS0nkYzj2Kzi52zBiy1RI1DughMVlaEIjoldQYVYz4vaV2hzFFPCDYYbT32Ug9bd4/rViyM1CrHtlvp42JkJoSPx8PkaQyYdFBaPIwo6FwCJibcUyls/dHzMHCC1K2NyElHYhxtS7lHgsCzH7QSHUZu7I51Ok7JfoGf6vuN75q57X0LWqQu5EJZoWRxORfMdcmcIPRvD9PrxgkCuFhkd/8s9B6NRW/Da6mLxnYCJs9zSjmccZyfzoClGhiQoMvR5dq0HTomiiAvDxgyR+MITv9+MF/VwtBmz3GMPp72EZrUSsm5iM4tO0GIbeUIhXHk9QyEu5WlxrIo5W5MSoaRWTsklRLggMcxWx+K9PSlRcTiT6Sezc04VE68sFsYvr7J2UsAiCPpzci/je6aueCRGNfZZw+NGivHOaFiccfpTA7yWd+tIVJWFd9xC2/SKGuRFdr5/0ORXF4uHYr+I6u8Y9o2m1RGOfIhr/QiHkaSpcvhEzWSSuuzdf4vaqUOdQ6O68R2wSouKSBULHNDcTjf4ySe9MwftXuJJM4TivYIXuxLQ2FWnnjYMSFlcR0qJUmo1KWMxDgiDLaOZJBlP/OKGoEFiYRithcz1hazNhcwO6XptfZGlhApnD94fx/A4c7yw59wSudwHP70HX6ohYm9G1hRVfbuqNNFb9ewKZIwiS+EGKIEgSyNHCQjjJaPYx0rmXmKvOzVIG2M5R+kb+eJyo0EScsLWRWOguouG7CJtr0LVKxiaNfK7DWTL2q6SyL5B19ubDlS4RMJD8K0LGShKxDyCYuvfJdo/jeKfxg7HJzCRkriQWvodY6E4i1jb0SyEekkDaOO5p0rlXGM0+Sc49Mi5EL2O/Rjr3EiFj1aQWXVFrB1QYXOu9sd1TjKS/i7wiZEEjGrqDWPjOov5egTVnyfqK6SNEHCt0J1borqKP1bQIofCDuM4+5GV5OlJ6uBMUAxiPxHX24zp7uVpAm9ZmQpGH0fSq4u3SawiF78dxduHYr1z2TIBjv0wodB+ads+CKa5RTuQTtlNkMt9k/HgTxgrdRST6qWmIiqnalcOxX8d1r2wCKkQVkegvoevNFLshIkQYw7oJ09qBnXvqiufGvHaGuV55x66BEhZXEdJjVFoNTJB7OWf0dAxx8UwvuUxp+mm0rGpgcWsdhjmfPjSSrLOf4fQ3cf2rd7hB12qJh+8lEf0g8fC9hVKfEww2BkB+dy+QDq53noy9B9AIT2KXbn4i0EQETY/kd7+vwvHPks69wlzE8Uop8YNBBpJ/i+0eu+I5TVSRiL6b6vivErY2TSgKNC1KxNpExNpEPPwgA8m/ZTTz2BVJ+1Jm6R/9MyKhbVjG0inbms+vyP8sMImF76Km4reIhW6fILlPoIkwYWsTIXMd0dDt9I9+kVTu+UtesbxtGTL2HmLh+4lMYkcsEtpKJHTt3ehU9heMZH4E8mphsYPais8X8ddOnp72Ic4e78T3Jh+etXRVA0uW16Ppcxdm6Lk+Jw5eZKjv2gUdZpNYIsyKdc1U1kzPc3YtdL25kGg6NTFomlsKyd2XFwDw8f3rV02UQRbPPYLnnbvaKsKR96HrLUzV+6UbqwiFHsCx3+DyGH/PPYXnHsW0tiOm6Y1UTITE99oK4UZXohtLCEc+hG4smXOrPO8cnnt4XLidFboNw1w75ftf15dgWluxcz/nciEVBP343hmkTCJE1TQsnz77dp0incxNes8vUR2ldXXTrI05YyhhcRUhLUpViRO4D75+hm/+xXN0Xxy8/i/PAp/+nQf48K/dTdyMlOT6U8HzBxnN/JjcVYtRAENroir+SWoqvoAuKie9m6UJi5C5mpC5eqbNVVwTn1TuFZLZJ694VBMxKiIPUpf4l5MWAyFzJfWV/xo/GCSVfQ55WUlExzvHcOpbNFT9W2YivCcaup36yn9L2NxQ6J9xbYQwCFubqan4dVy/g5x7ZZ+JnHsU12sjYm2cEdvmmgOvn+Fv/tvjZFK5SR/zK7/7IB//zfuw5lBY2DmX7/7NC7zxwvgxYy5YtaGZ3/wP72fzjhWzcHYdXV+CYU49XMMwlsI4gSyRwUSVxq7E9zvx3FNcXYZU0xswjA2IaVQW07QYhrkG3Vh6VZiVi+seIuR3o2krp3x+xbXwse0XGZ8rZmIYa98xIX42yQvKq8PtwLS2o2nFl6wdQ9Ni6PoShKi4SlyD550l8Pvn3DtzNV/+nz+j7Xjn5VXQ35EN21r5td97dJbGnLdZOFmoM0RIj5Aw66cVIqGYezL2G2ScPeNCS4SIUBX/NLUVv4mhTV5UKOaevLciyVDqH67YxQcNy1xNdfxXi/YwmHoTNfFfw9DrrrwWLqPZJ3D9nmnbbeiLqKn4AiFz3XVFxRhC6ITMjVREHuHqmGLP78P1uwiK7C2iUIwhRAzDXFvIi5niObRKxLh493w4zPXw/U68CTzHprkRXW+Y9jis64sxjfHV+Tz3JEEw/c+0YiKCQsngK9G0aqzQrWha5ZxblC8VewF/XOhzCMNYNakqYddG5EvmanXjnvH9TgI5Mo1zL2zU6vkqdGESM6qI6Asrln4h4wcpMs4bOOOSfCEeuoeq2MfRRIL5uPt7o5FzDpJ19l3xmCYqCjkLW6Z0zmjo1kIY2+W7r/mu1Oncq1O2dYyKyCNErM1F5x/oWhUhcwPGuF01D8/vJghKE6KjmP8IEUE3lk3zHBbjlwjyqnydiQmCXoIJ8tx0vRUxifKj17VNq0EzxncB9/2L+P4AcrJbuIpJka/S5+JNkF8jtKppecamgwxGC/fZld5RTa9F0xIzkAMRRmjji1zIYAgZlDBevsxRoVATENbiJMx6Mr5SpPMBx2vDdo8XOmi+jSbiVMV+CUNvUp6KeUHAaPanXJ3saej1VEQemPIkIYRFNHwHaXsXgbw8n8EmY++mKlZ8M6YxNFFBPHwv+jXqzL+zXQJDr8U0luA5V5aq9YMkwTR6ryjKn9lc+goRRtObZ+ns72y5lEG+klwwNO45XW+ekfwHTUugaw3khc/lHbmTBMEA+dyL4jqEK96ZIBi6okLSGJqIY5SoWmLepv7xT0iHbPYxHOfNaZ3f9y5O+DcHMn1FaK3iSpSwmICwHqfSrKc7Nz5uT1F+OO4pXG98QmHE2krIWqsq2cwTJE4hSfxyNEy9kZC5YVrnzuc+WFesiSQuOecoUnqTDmG6mpC5GlNfOuVOrJqITihKAplBqlAoxVQRZuniv6VdyMMY37BR02oRYvq5e0KYCC2BEKFx4a8yGETK7LhGgIrpkfcMXC0qBUJLoGmlKfEbyNEJ+mnkE6yz6a/O3oWlC3IumxLOL1Qo1ATkhcX46jiK8kPKAMe/iDdBrHw0tBO9xMlVisnjeu14lzW+gnzDItNonXaZX1NfjBi3jyLxgwH8CXZWJ0vIXDMt24QwESI87nEpHaRq0rmgmU0fqkCbkQX8VJDYV/SYeBuBEOEJ8jamgiiEao3/7AQyqUT5LJD3BF2NgSbiU96YmS5SZpFz2mOpcF0C5qr8+nxECYsJCOsxEqZqsjMfCGQaz+8lGDeRaYTMNWiq7OC8wXaPFwbst9FECFOffglDTauECTqmSzw8f+o9a/LeiuncY9o1QrzUxKWYDhqC0nhqpfSusbC3QBgwY2Gp5oSlRKW0QSpRPtNMLBZ1mCAHYc6QrhKRZYgKhZoAQ1jEzWpCWhS7BAk6miZUTsAk8YMR/GB8Loyu1WLo9ahbfP6QT76/cjEdBFlSuWcm7E1SDFJ6E94nyOCyBnfFY+h1aCrkYt6iGwt1nBVQsuZdkolEsRAaM7qXKbQJNwvyXeiVKJ9p5ARiTQhRMgGbx+fqnLw8WqFU8ux8vvNe5vnU52tuUauuCRBCENEriJu12PbcC4uN25fzhT94L0P9STIpm0zaJpu2yY79nMpdejxT+DmbsYtqSLVQCGSKIBjvCjX02rzbXQm0ecNEpV8lNlln37hKUTOFnGSVm2uhiZjqvjpPCYVNPvK5e9j5wEYy6dwVY20mNTbeFsbXwmOZtI1ju8hg+gvXhbr0zZdqH/+ZyC9MZzAuXXoTeibyn0cVjDHTTDTOSTm98XP6TCxWDXM9kejHZ62AgcDCtDbPyrkXAkpYXIOIniBh1jFgX7/L6EzTtKSGxuZqPM/HdTw818d1L/vZ8fCctx9zXQ/X8cllCpNfKkcmaZNOZTl/qoeDr5+d879hrpDSnrA6gyaiE8TUK8qZIBhl7pdbsrDDOTXUztX8xTB1Nm5fxvptrZeNqWNj7Nh46xXGWT//s+Pj2C7ZlE16bIMnlSM1muXVpw+TGlGVvBDmNRKn3UKYVFDwXkwT6ebDnq6+vAjnQ64UM8rEOTt+acuuCpMry4gXHhYVWNadmNbGubdJoVZe1yKiV5AwxjdGmSuEJjAtA9Oa3FskpSTwg0sixPd8HNtj1zNHFriw8JETVGfQRETtJM8zAjn5Ts3lQv4eU16x+YoQAl0X6BELJpnrHAQS3/Px3Le/slmHo2+dV8KC/AJUXKOgQT7R1oNph8/kd8qvLjEOXKoWpZhZxIRdrD2kTCGlX5L5VogImjY+xy1/n6nci1KhhMU1iOhxqq0mLG1ys42phRAlXGAIIdANHd3QCRVMDvyARPXCT16e6FVXVRvmHxN/ejR0rXLCJM2ZQNdqp39upStuKDRNoF216RN3PAyzuIXVQr1thDDQtEqEiCPllV26A78HKTPT/szJIEvgDzK+pK2YsZK2iivR9UUTPCqRQZIg6EGftb4p10YTFQgxvuN34PeOK0OsmDuUsLgGlhbh5uqHWRm/dVK/H9HjhPXptI9XTAUhjAmTFAOZndCToShfJtpl1LVa6hL/nFjo7lm6poFRgglRoVi45Bf3ml6P710pLHy/ExmkYJplwPP9C3q5evNIiCo0rQa1tJl5NK0WoVUjryrPHcgknneuNMJCq0XXx7cGCIJ+fL8XKd0p9xhSTB316bsGQmjEjWriRvEddRVzhybCaBP0AQiClOoDMM/IN4oTXL5YEAh0UUnYWl8yuxSK2WAh+1M1vQldX4LvtV3xuOedJQhG0JleCenA78fzL4x7XDeWFjwWC9UfVBryr6eJYazHdXZd8ZwMhvHcw4RCd8y9XVpVIUE7BFfkWvp43ilkkEToNXNu142OKp2gmNdoogJNjPcUeX53wRW6kKfvhYVpjHe1Szx8OTz3xigUiimj60vRjRXjHvfcQ/h+F3IaBRMAfP8innNk3OOmuRZNb5zWufMoYTIejVBo57hHg2AAx36NIEhNcMzsIoSGYSxDN1rGPefYr+IH4ysNKmYfJSwU8xpdry7sdF9JIFO4fgeBap4zb7CMVVw9oQcyh+Mu3OIDCsVCRNNqMI31aFcl/EqZwnXfQgaDUz53EAzjuccIxi0aDQxz8zVyAYrBQEzQ0VtKBymvzum4kdCxwg8wXnT5eN5pHPvVEtgkMIx1GMbacc+4zj4898SElcMUs4sSFop5jSCEoTegifFVSHLO0ZLsoiimRsTaxNWlW6XMYrunCdTkoFhgLOQ9cSE0DOsmDHPTuOdymR/geWem5LWQUuK6R8llf8rV3mjD3IhhrmPaFaeEgZigm7SUI8hgdHrnntcIDGM5pjU+79T32shmvo3vdSHl3EYJ6MYyTGsrQiSuesYlk/p7PO/cnNt0o6OEhWJeI4TAMldiGovHPZfKPYcX9KlBZZ6ga3WErasXIhIv6CVrv1kSmxYCC3kBqyhfTHMTVuhOxFWbPr7fTjbzLQK/o6ixOV9SvQM7+wSed+yqZ3VC4fsxzU3Tzq/IlzAdX2re887j+xdv2PlECIEQUWKxX2f80tHHsXeTTv0VUg5P6zWSUuaPn+Q5hNAIhe7BtLZz9WjnunvJpL9CEExf8OTt8lRRmEmghIVi3hMy1mAZy8c9brsnyNp7Va7FvEEjEXn3uEc9v4fR7E8LnXsVRSG0QhOpy/GReDfsAqlcWOivvhAG4fBDWKE7uXqpkc18l0z6Hwn8zkIvond6NSRS+gRBF5nMN8mkv371lbCs7YRC96Bp40uPFoumVWEYq8c97nuncezXkEH/DfvZEcLECt+FFbp33HNSjpLNfIvkyP8P3z+fb15blHD0kTKHlKME/oUiws4EprWRcORhNL3p6rOSTX+N5Oj/xPfPFWmTRMoAKW2CIInvnyGb/QGue2DSf9ONiqoKpZj3WOYywtZG0rlXCGTyiucGkn9F2NpA2NysGuaVPYJE9P30J79IELz9PgYyTSa3m4z9GtHQHTPTtfcGQWChiTgBw5c9KgmCUaRMIyYofKBQzBSGuZZw5IN43ll87xSXy6l06m/w/IvE4v8MQ28FLUq+i/LY5zsg34Atg++dJ5P6CtnsT+Cqan+aVkc48iFMa9uM2CxEBYa5eoI+HJJs9odoej2R6EcKZW2tgockX80uv2gNAB+kj8RHiFCRfTsuP8/Y9+Cyx4JLz8mr5ru3jy/0+RBawTYN0BBoIN7+/9hzxXh5hKgknvg3DA8cJwi6rryyTJPNfAvXPUA0+hms8F1oohKEhUAv2EPh78m/v0gPiYPvd+E6e7Czz+B5p6hreA7BZJsUC8KR9+G5J8lmvo2UV3YDz2W+h+ccJBr/Albo7nzBF2EV5pKCTTIo9L/y813dcQj8PlxnP47zal5UyiwVlf8Za4butYWKEhaKeY9AIxa6k7T1Mhn7DS6fvBzvLP2jf0lD5e9jGSsLA8nUXOVjOx2qlOHsIITA0Buoin2SweSXufx9tL2z9Cf/mia9CctYlu9fMkXyLu0cCA1tgXfo1UQYQ6vG89uveNzx2nD8dsLauhJZprhRCEcexfc7yKS+XEi4HvtcB9jZJ3DtV7FC92KF7sUwlqEVinEEwQiefx7Hfhkn9zJB0D3u3EJUEIl+gnDkvTPWRFMIHd1YjRW6Fzv3My4fh2QwQGr0f+PabxKKPIJprkeIGPk5JUDKDEEwQhAMEgR9BEE/ofC7saytk75+EKTw/Q4Cf6DQ1Tqd/x6kCWTq0s9SpvD9i1zdJFDKLHbuWXy/C6HF0EQcIWIILYYQ8fz/tVjhsTi63oKm1U16400IHdNYT0XlHzA68v8ig/6r/wI89zCjI3+AlmzEtLZgGGvR9Ho0rQIQSJkjCEbw/U4C/yKeexzf7yQvmEBMUJDlemhaDdH45wiCAXLZp4ErG+R53glGh38fTW/CsnZgmBvQtKq8gMSHIEMgUwR+N75/Ac9ry7++l+X3qY2YyaGEhWJBELG2Egvdje2exL+qgU8y+1OkdKiv/FdYxgo0kZi0OJDSJ5CZwg6vi67Xok+QKK6YGQQWNbHPkso+j+OduewZj0xuFz3D/426xD8nZK4tTJiT815IZL5br0zhBUPknEOEzFVErC2z8neUC5pWhWWuIOceuuLxrLOfrL0HS29F01SX4lJwo2xPCBEiGvsVkFkymW8R+N2MLSABgmCIXPbH5LI/LjwytsB9p1h2gRCVhKMfIRL7DJo+2Z3tyWEYrYQj78Z13ppA0GSx7aex7acL/x/bnHC5/O8ae84wNkARwsJxXic1+kd47uGpGY+P75/D989N6rfjFb9HNP6FCTtYXwuhRQiFHyUepEkn/6Lgubj6b5cEQTd27ilsnpr0uaeDYawkVvEvAbBzzxc8TleGPgV+N7nsTyD7kzmx6UZECQvFgkAIk0T0Q9juKZLZp5BcWUUolXsG2ztBVeyTxMP3omtVaKICISwERt49LMdiz20CmSMI0nhBH7ZzjLT9GgJBTcVvEgvfPmm7xtzXEu+Saxz8fDzpZY/5wcCEVVJ8vx/Xb0dggdDz7mR0xNjPQs/bj160JyVvW8Em6SELdr39WN5GPxjh6sFZ4uH53TjexcLrl7fnbZv0q+ydnG1CCExjMfWVv0f30H/Cv2w3TGKTyj2H61+gMvpRYuGd6Fotmoi9/T7mX7XC3+IQyBxSZvGDUWz3FFlnH+ncL/CCIZpr/mjBCwtDryFsbmSUn3J5CInndzGc/h6aVkk0dBu6Vo3AvOp9GktWdPOlNvEx9Npx11AoroemJYjGvwAimg9L8c4C1yoFfr3kWANdbyYc+SDR2K+iT1C4Y7oIESIUugc//lkyqa8QBP1cOyvmxqxYp2kVRKIfQ9MqyaS+nG9IJ0tfhdE01xNP/AGaVo+dewbf7+Dq8LmpIkR4xjxjCxklLBQLhpC5nOr4r+AHA2TsN5BXTVyud4G+kT9iKPVPhK2bCZtr0bWaws63QSCzBEESz+/D9TtwvLM43oVC8jdErFuKskdKn4z9OoFMEgSZvOdDZghkmiDIEsh0wXWewfbOEsjsuHOMZH5E1tmLEDE0LYomxr4iCC2KLqIIEUXTKgib6zD0+knZ5vm9OG4bXjB4yS55uY1BmoAsMkiTdY9w9W6UHwwxmPoKZnbRJbtEwa4r7Yyi63WEzFXok0ysFMIiHn6Qmvh5BlNfuUJcgI/tHqd35H9gppoJWzcRMlai63VoIkbeN2ETBBn8YADX78T12rHdU1fk34gJurUvRHQtQcTaSshYie2duOK5rPMWvcN9xCMPEg3diqHVFULMZEH4uvmkxWAYzx9ACJ26xO+U5g9ZgNxo6b+aliAW/zyGsYJs5ju47kECv5fJL/p0NK0Ww9xAJPJBQpF3o2lXlxidQXv1OiLRXwJ0cpkfFRKSM9c9bjwL1zelaXHCkfdhGKvIZL6Ja79WaICYZGp3uIGm12MYqyYoOlHEWYxW4ol/h2ndTC7zY1zveOFem0ofEgtNq0LTGzDNLRMm9iuuRAkLxYIiFt5ZWKBrZJw9l0TB5Xh+D6ns06SyT48/wQwSyCwX+399XEJ5MeTcw+Qm4RLXRAXNNf+LRPT9kzpvOreLvtE/wfGm1nxOyhxZ5w3Gv7rjCVtbaKz8j0V5enQtRk3FZwGf4fR3cK/KEQAf17+Im73I1F/dGwFByFxNIvo+BpLdBHLkimdd/wJDqa8wlPqHgjiMAMElT8/li4OQuU4JixlkppabprUdoV0ZnqnrLYX3cnpYobsIgisXUtPpbC2ESTjyCKa1BTv3DHbuRXz/AkEwgAyShXtuzGNhIEQEocXRtGp0fQlWaCeh8EMYE1QBnA10vYlo7HOY5iZy2Z/huUcJggECOZLP05KXhz8ZhUTtMEJEEVoFmlaPPq5S0TujaXVY1u0z0OhvcujGSqazFBTCxLQ2U2H8P7juQZzcc7juYQK/L/86Ben8a4VLfjwpJI+LfCNCoUULeR9V6HoTVuh2rBmo8KVpMSLRj2KF7sLO/QLHfhnfP0/gDxXevyxIh/z7J8h71g0QofxG3iWbFmOam7FCt2OYa2+YTanpoISFYoEhqIg8gK5VMJT6Ouncq3hBL+PjP+cGOafXLWaHSBb5+9NATuVaAl2roqbi8xh6PcPp72G7xwlkekZMEoTQGN8EayFi6PUkou/H9TsZzT5JEAxP8Fsy/9rO0OurmBuEEFRU/odZO39l9R/Nynl1vZFo7FcIRz6E5x7F9Y7he+3IYOBSp+R8P4kadH0xhrkWw1yHplXNij3vhKbFCIXvw7Ruw/fP4rnH8L3zhfDVTGFxqiFEGE1LILQadK0RzViCaaxE0xuKup5lbcGahyGamhYjFNqJZd1GEPThuSfyuR5eF1IOImW2UDJcy4cTiUheMGr16Hozurm6IIinXmBlIvL32ieJRD+C553Cc0/he+cLyfVJ8oJHK4jCCEKrRtcb8zYZK9D1xYhpeE9uRJSwUCxIoqEdmPoSRq2fks69RM49jndV0uBkyXf3XkTY2oyhF1+tQjF1dC1BZezjhMx1jGZ+TMZ+C8c7N0UvkIGh12MZrYTNzVjmmhm3t1yxjJXUxL+AJipI5Z7H9S6Oy0NSzC03WijURGhaHCu0Ayu0o9SmXBdNi6BpGzHNjaU2pawRQisszBuBe0ptziWEsDBN9f7NBUpYKBYsptFMbcXniYfvI23vJuccxPEu4vm9+MFwIcfBJu96FwgMhDARIoquVaBrVRh6A6beQtjaSMS6BctomfT1hTCpjn3q0g7cbCJEGNNYNunft8zlJKIfwvevLhU485jGEoxphE9oIkw0tJ2QuZass5dM7g1s7ySu34Xv9+MHo/nGSrjkd7oMNGEiRARdS6BrlehaPaaxmJCxikhoG2FzY1F9TULmOqpivzQuxto0ljCd3TVdqyQWugf9qoosYWsj+gzuzgqhEbbWUqf/cyKhrWRyu7C903h+D34wVAh9GgsL0NEKu3e6VoGmVWJodYStzTNmj0KhUCgWJkpYKBY4+RjzkLmaIEhje2dwvQt4fh9+MJJPWpY+Qoi8qCBUWIzW5EWF0YKhN0yp34EmQjRV/+Es/E3TJ2JtmWcVkQS6liAevo9Y6E48vwfbO4vrdeIHA4X67m7hN02ECBXEYQ2GXo9pLMHUFxeSk4sXArHwTmLhnTP8N+XDlKrjnwI+NePnvtb1KqMfIB66J9/LwjuP5/fk67fLHHlhYRSS8CswtGp0vR5Tb8bUZ776jkKhUCgWFkpYKG4YNC1GxLqJiHVTqU1RTAMhzLxQMJaU2pR5i65XEdG3EglNvr6+YmZZuLWCFArFjYwSFgrFdQj8gEzaZnggxchgmuRwhkwqRyZtk8u6eI6H5wUEfj6kStcFmq5jGBpW2CQctYhELaLxMInqKInqGImqKJFYSHXxfgcCP2B0OMNg7ygjg2lGhtKkRrI4tovr+riOR+BLdF2gGzqGqROJ5V/nWEWEqto4tQ0JKmti6IZ2Q73WMpBkMjZ9ncMMDaQYGUyRGs6Syzp4rofr+vngP1PHtHRCEYuKyihVtXGqauM0NFcRjlpTfs1uoJdaMQsEQcDwQJrB3lGSwxlGhzOkRrPYORfP9fEcD98PEJrANA0MUycUMYknIiSqYiRqotQ1VlJRFUXXJ9dEU/HOSCmxsw6DfSmG+pMM9ycZHc7g2C6OnR+Pfc9H0wSGZWBaOlbIzM97VdH8V3WMqro4ofDVPXPmL77nM9iXZKB3lJGBFMODaTIpG9dxcR0f3wswDA3TMjBDBtF4mKqa/OtQU5+guq4C3ZjaPVquL6ESFgrFVTi2x0DPCF0XB+hpH6K3a5ihvhTJ4byoSCdzZDMOuYxdmOgCfN/PT3QINF2gaRq6oWGFDEJhk1DEIhINEU+EiVfmB9m6pkoaFlfTvLSW5mW1VFRGF8xgOxWklPh+wMUzvVw43Ut7Wx/dFwcZHkiRHMmQGsmSTuZwHS+/uPB8Al+i6QJd1/KLi7BJJBYiEgvlJ7HaOLX1FTQvq2PpqkZaVzcSqwgvyNc5CCQjgylOH+ng4pleOs730989yujQ2/etYxcWZq4PAoyCILNC+UVZRVWURHWU+qYqFi+ro2VlAys3NlNZHZv0a6brmlrMTQKVvH0l6WSOthNddLT1090+QF/XCEP9KdLJLOnRHOlUDifn4nsBnlcYb0VeHBuGjhU2iMXDxBMR4pURqusqaFhcRfPSOlpW1rN0VeOCWtDOFaPDGc6f6ubssS4unu1lZCDFyFCG0aE0qdEsru1d2ujx/SAvLArjimkZRGKFeS8RIV4Zpaouv3GxqKWWRS01LFpaO61NjFJg51w62vpoO9lN+9n8PDU0kCQ5nCE5nCWbsfEcH8/18H2JbuTnJ9PUicRC+XG2KkpVXQVNLTW0rKhn+dpFLFpaSyg8+QpUpjUW2lteo4kSFoobHiklmZTN+VM9nDvZzYUzvfS0DzLYO8pQf5KRwTSOPbkmThKJ70l8AlwHcpmJu8sKAeFoiOq6CmobEzQtqaZ1dRNrb25h+dpFxCrKq1Z2EEjOHO3gqe/tue7v1jUmuP1dG1i+bvJ12DMpm6P7znFg9xnajnfR2zlEf/cI2Wu8fpfjexLfC3Bsj0zKZqj/yu6vuqFRU5/IT2ZLa9lwSys37VjJ4mV1k7avnAmCgPOnejj4+lmO779Ae1sffV3DjA6l85V+3wHH9y69bsMDb79uQkBlTYz6RdUsXl7Pxlta2bJzFUuWX78Bo2HqmCE1tSiuj+t4tJ3o4sSBi5w+0kH7uX76u4YZ6k/hOtcfcyUSxw9wcMmkYPiqz344YlFdX0F9cxUtK+pZd/NSNmxtZVFr7bxayF7OrqcPc+jNtuvOSfVNlTz80e3UNBTfRFBKSce5ft56+SSnDrfTdWGAzgsD417fifCD/Hhs5/I5b5ePKwBCE8QTEWrqK6htSFDfXMWyNU2s3riYFeuby1pkDA+mOHHgIoffbOPssU66Lw7S3zOCk3vn92JsMycHJEey9HYOX3ouFDGpa6xk0dJaVqxvZvOO5azd3EJF1fXLoeejHrjuOD/XqNFfcUMipcSxPc4e6+T4/vOcPtJJV2GQGJ7kpDa960M2bZNN23Se7+fIW4JEVYymlhpWrm9my85VbN6xgsqa2KzaMVmklHRdGOBn33rtur/btKSa+kVVkxIWruPx1ssn2fXMYc4e76b9bO+lCWmm8L2Avq5h+rqGObr3PAffOMPuZ46wZecq7nxkM42L528J4d7OIV54fD97Xz1F+9k+BnpHZ+S8UsLwQJrhgTSnjrRz+M2zvP78MbbdtZp73n0TtY3Xbl41FgKhUFwL23Y5vu8Cb7xwjFOHO+g8389gXxIZzOwKKZd16LowQNeFAY682cbeV07R3FrLzbev5M6HN9HcOv82F44duMDPv7eHbPqdqw22rm5kyx2rihYWF8/08sYLxzj4+llOH+1gqC+FnMGVqwxkYWc/w/lTPQhNUF0bp3FxNU0ttbz307ez8ZZlM3a9mSCTynHkzXPsevYIJw5epPvCwKQ2vSaDnXXpONdPx7l+ju49x1svn2DtzUu58+FNrN+6lEj02oVjYvFwIR6qvJSFEhaKGwopJQO9o+x9+SQHXj9L57l+ejuHGB5IEczwpFYMgS8ZHkgxPJCi7XgXB984y/qtrdz73pvZsLWVcNQqmW3FMjyYZqBnFCnlO+48nTnayXOP7WX/rtNcONOD781+M0EpJb0dw/R2DnP6aCeH3jjLPe+9mbse2VxwK88PPNfnpScP8uIT+zl5qH3cruCMIqG/a4T+7hHOHu/kyJvnuPe9N3P7AxsmfM2skEk4ooTF9SjPPdnZJfADju07z8tPHeTYvgtcPNtLNj0zC7Tr4XvBJZFx5mgn+3ef5pa71nL/B7ZQXVdx/RPMM1zHY6SIcSGdzLH72SO8/NRBTh1qZ3gwPeNCbyJkIBnsSzLYl+TkoXYe+ugts37NyRL4eW/wcz/Zy95XTtF5rn/GN74uJ5OyOXO0k462fk4cuMD2e9byrg9uY8myOrQJwkvjlZGyzLOYPzOpQjENpJScPdbF7ueOcHhP2yUX5lwsZovFzrlcPNNLb+cQpw5d5J73buGhj9xCTX1F2bqILyef4DdKJmVPGNLleT67nj7CU999nRMHL5JJlaBRm4ShviRvvHiC9nP9nD/Vw3s/vZP6pmvvxJcLAz2jPPbVV9n1zGE6LwzMyeQPgITB3iSvPX+Ui2d7OXeqm/d9eue4RZkVNuaVEFbMDf09I7z4xH5effow5050z9iO71QYHkix79VTnDvRzdF953j04zvYeufqBZUb5NgewwPpSf1u5/l+nvzOG+x65gg9HYMlmxejFWFWFBFCO5vkMg77d5/mp996jeP7L5Aazc7dtbMOZ4520ts5zLkTXXzgV+9i0y3LsK7Kv6ioKs+8TCUsFAsa3w84vu88Lz15kGP7L9BzcZDR4cz1DywD7KxL24luhgZeof1sL5/8Z++iubUOTSu/geRypITBviTDA8lxwiKTyvHkd9/g2R++xcWzvSUXdoEf0NHWx5PfeZ3B3lE+8Vv3TyqPoFScPdbJt/7qefbvPk1qZO4musvxvXyC/U+/+Rq9HUN85HP3XBH2lvdYKGFxPcoreGH2CALJ4T1n+dm3X+fgG2cZKbF3eIyxcer154/ReW6AOw9e5H2/vJPK6vIIP50uruMxPHh9j8Xx/Rf48Vdf4a2XT+YXzyV8a9ZvbSWWiJTOgAKjw2le/OkBnvjGbjrPD+SLXZSA5HCGva+cordrhA9+5g7uemTzFa9PQgkLhWLuGege4RtfepbjBy5eNya1XBnuT/HKzw+RTdt87vffPS/ExVBfksHeJIuXvb1Iz6RtfvgPL/P0999koGekLBYXkF9gjA5leOXnh7FzHr/8Ow+wdNXUO4XPFsf2nefrf/4Mh/dcP3FztpESRgbTvPLzw6RGc3z6XzzA6k35viJjlbkUCsd22fXMER7/+i5OH+3EmcUwkqniuT7nTnYz2J+kt2uYj3/+3rLeXJgs1wuFklKyf/dpfviVlzi0pw07W/r3Zvs9a0o+tw0Ppnj6+2/y+Nd30d89UlJbAFzX59yJLr7xpWfJ5Vwe/NA2YhV5cVFZE1OhUArFXFNVV0GiOlayHYeZws66vPnSCYQm+Of/8YNUl3lY1FB/PmZ2DCfn8sQ3dvP09/fQ3z1SdlUsIJ9Mv+eFY4TCJp/91w+/Y4LyXHN4Txtf++IzHN17rqzu5VzGYe8rJwn8gE//zoOsvamFUNgi/A4Jh4obg9RIhmd++CY//dbrdLeXLrxmMkgpGRlI8dJPDzDcn+QTv3l/2SUQF8s7eSyklOzbdZrv/s0vOLr3/KwXK5kMmq6x9Y7VJZ3XRgZTPPnt13nsq68yMji5MLK5QEro6xrhO3/1C2Qgefij2wt9sSZfBnwuWTgBhQrFBFghgwc/tI14orzKt04Fx/bY88JxHv/67jlLeJwqeY9FvkJREEie/uGbPPWd1+nvHi1LUTFGNuPw2nNH+cnXds9qkl4xnD/Vzbf/+vmyExVjOLbHvl2n+d7fvsCF072EIiaRmAqFuh7ltxyYOdKjWX7+/T388Csv03l+oKxFxeXkMg77Xj3F17/4DIfeOFtqc6aF6/gkh7P4/vjX/uje8/zwKy9x5K1zZSEqAFZtaKamvnRJ9Jm0zatPH+ZH//hKWYmKyxnqT/Ktv3yeXc8cwc65VNXElbBQKErBzTtXsXzdogWRmOfYHo997VWO7TuH75XfInOMbMZhoHeUbNrmwO7TPP/jvXR3DM1o2cLZIjmSYfdzR9j97JFSm8JAzwjf/qtfcGhPW1mKijHGygY/9tVXyGUcoioU6oYlnczx9A/f5If/8DL9vaPz4jN/Oa7jc2jPWb7xpWc5vKet1OZMi1zWITVyZU5h2/EuHvunVzjw2pmyGlO23bUGwzRKslB2HY+Dr53m63/+LMkyz8EcHUrzj3/6FCcPXiReFUGU4bJGhUIpFjymZfDIR2/lxIGLpJO5KZ9H0zVqGxIsWVHPkuV1NCyuprYhQXVtBZF4CCtkYphavhFO1mW4P0l/9wgXTvdy5mgHp492zsjuUDZt882/eI41N7UQT0TKcscC8hWETh5u55kfvcXJw+1FVS8SQlBZG2PdTS2sWN9M4+Jq6hZVEq+IYIVNNF3g5DxSo1kGekfpPNfP6SMdM1Z6taOtjxd/eoDVm5aUrJGe63g89tVX2fPS8WnHpmuaoK6pkvXbWlm5vpnmZXVU18aJxEJomsCxPXKZfDWv3o5hzp/u4fj+i3Rd6J90Lkwu6/DKzw+BEDh2eXh7ypn5tdyeHI7t8vKTB/n+3714RSjkVAlFTFaub2bN5hYWtdbS0FxFZXWMUMTEMHRcJ3/fDg+m6ekYoqOtj5OH2rl4Znr9cHwv4PCeNr7918/zmdDDrL2pZdp/SylwbI+RwTSVNXEgX5nr59/fw2vPH5uyqNB07VJzu3DMwrJMNE2QzdikkzlSI1lGBtPkssV51bfdtRrDmPtVsgwknef7+cr/epKhGbhnDVNn9aYlbNi2lJaVjTS11BCNhQhFTHw3yIu90XyTvM7z/Zw+0knb8U6SRRTjGOgZ5S/+8Mf80m/fT+CX30iihIXihuD2hzbyw394mZOH2q+7gyYECE3DChksXl7H5ltXsH5LK6s2Lqa6Lo6ma2iaQIjClwYg8qENhV41knwcq5QSGUh8PyA5lOHNl0/wi8f3c3Tf+bzHYYpjwrF9F9j1zBEe/NA2dEOf2klmmQOvnebUkXYGekYnFQqhaYLK2jh3PbKZe99zEyvWN6MbGkLT0ERebCDEpWS1/NsokQEEMkD6kkza5shb53j6B29y+M02MqnclF7jIJAc23ee1547wkd+/Z45F29SSl5+8hC7nz1CenRqYlgIiFdG2Xbnah76yHbW3tyCFTLQNA2h5V9HgQBx2Wsp8xNtEEiCIKC3c5hdTx/m+Z/spfPcwIRhFZczOpTh5999Y0r2KuY3vh+w79VT/ODvX5qyqBBCYIUMbr59Jfd/YCtbdq66JH7F5WMuXDbWvn3fSikJ/IDhwTR7Xz2Z7/NysJ1c1ik6BNP3A/bvOk2iKspn/tXDNLXUlO0mzrVwci4jg2mklOQyDi88vp+nf/DmpDa4hCbQNEFtY4ItO1ex7ualrNm8hMaWGgxdRxSSrMfeC5mf9JCF6/Z0DHHuRDdtJ7o4uu88F0/3ksu5l96ny1nUUkPLioZL55wrpJSMDKX59l//gottfVM+j6YJlqyo58EP3cLd77mJqto4+tg6QROAuNTHLj/USoLC2iAIJOlklmP7zvPC4wc4+MZZksOZ665TLpzu4X//+++XTSjb5ShhobghME2d9376ds7/4WMT7qRomsAwdWKJCGs3t3D7Axu46bYVNDRXX1qEjXHdyUWMxU+//XuGlIQWVfLoJ3Zw3/u3cGD3GX7w9y9x/MCFKe0cSSl54huvcc+7byKsa2U54Y01Pboemq5RVRvjPZ+8nQ985g5iFW83/Xmnv0uMzWga6GhgghkyuOOhjdz+wAYOvn6Gb//l85w4eHFKu5cjg2n27z7DtjvXTKqL+EwhpeTciW6e/dGbtLf1T+kckViITbcu55O/fT/rtrRe9/W89FoCXKZTW1bU80u/dT8f+fW7ef4n+/jB379E14V3jpm/nvhQLDyCQHLy4EW+//cv0T6VBZrIVxO77b71fOpfPMDSVQ2X7tV3HNvEpS2dK+7bhmaTRz++g0c+ditH957nB3//EofeOEu6yI0G3w949ZkjVNbE+eQ/u79sk2WvhWO7DA+mCPyAt14+yRPf3H3d6oiGqRNPRLj9gQ286wNbWXtzSyFE6e3fud5rEAqbVFRFWbVxcV70SUlf1zCH97Tx1isnObynjdGhNJ7rEwSSrXeuxgqbc/raSilxHY9dzxzmhcf3T+kceeFVyQc+cycPffQWEpXRS8PohH/LZWuDy30zVsjgjoc2cfsDG2k73sXjX9/F6784xuhw5pqefikpS1EBSlgobhCEENz97pv5/pdf5MLp3sKD+Zr7sXiIZWsWce97bmLb3WuoX1Q1K9cfIxINcfsDG1i5vpnHvvoKT31vz5RCtE4faefkoXZuum3FTJo6p4QiJtvuXMNv/Nv3sGhp7bRLDY69zrou2HrHalZvXMxX/+wZXnh8X1Gu5jHOHuvk8JtttK5pmrMyiK7j88JPD3D8wIWijxUCahoSvPuXdvCxz99LKDy9JOq8lyj/OXnkY7ey4751fPX/PMOLP91ProQNzhYC82d5+s5IKenvHuH5x/ZNKSdBNzQWtdTw6/+f97Dj/vUzkgt3uSjZtH05G7ct4xc/2cc3//I5ui8OFiV+nZzLC0/so6mlmvd88vYJu82XK/kmeSnOHu/iqe+9QU/70DV/Vzc0Kqtj3Pf+Lbzvl3fSuLgaTZvae3H5fDe2adG0pIamJTU8+OFbGOxLsueF47zwxH7OnermlrvWYJXgdR3oHeXbf/n8lI41TJ1N25fx2d97lNWblkzrvr183lq1cTG/84cfZttda/jBV17i7LHOeVP8YIz58wlRKKZJOGLy7k/cxj/8yZNYYZOaugpue2ADdz+ymVUbF8+5G7a+uYpP/Nb9xCuj/PArL5McKT5pbNfTh9m8Y0VZ1rK+HhWVUT70a3fxoc/eSTQ+O1W74pVRvvDv30ckavGzb79edPfUwb4kp450MDKUpro2Pis2Xo6UkqNvnePga2eKrvwlBDQsruaTv/0uHvn4rTO++yeEoKY+wW/9h/fRurqBb/3l82Wf6KiYfRzb49AbZ3j+8X1FH2uGDG7esZJ/9v/9AE0t099YuBZCE7zrQ9tYu6WFL/7HHxVdYW14IM3LTx5i2ZpFbN6xfMoL7rnGzrqcO9FNf/cI+149dc3fi8RC3Hz7Sj72hXtZs3kJpjm7S8Oa+goe+fitPPzR7Zw+2kHLigb0OcyvkFLi2B5PfecN+qbQq8IKGex8aCOf/hcP5EO4ZnisNS2De997M01LqvnGl55l/+4zZeudmAglLBQ3FO/60Db2vnqKHfet4+53b76U1FYqEtUxHvrodlKjWZ74RvElTve+egrf89Hm0S4aQKI6yq/87kM88OFbZr2CkGnq/MrvPsRgX5IXf7of1yku9OzCqR7ajndSfeeaWbLwbTIpmzdePM6ZY51FH1tVV8FHf+MeHv3Ejlmw7G0isRCPfnwHpmnwT//n5yXrAD7fKb+Uy+IJAsmF0z08+Z03yBTpdTUtg53v2sDn/917qFtUNSdhMIuX1fPv/vRT/O9//z32vnqKoAjPxbF953nl54dYvLyOujLqcfNOpJJZnv9JXvBNWIRBQHVtBQ99dDvv+/Tts+KtfyeEJi411pxrutsH+dm3Xyv6OMPU2X7PWn7pN+9n6crZbaS69ualfPb3HkX+yVPs3326rKp4vRPzQ3YrFDNERWWEP/ybX+O9n7695KJijNqGBPe+92Zuum1F0ZNr18WBd3RvlyOxijAf+fV7uO/9W+asLKkZMvi133uEJSsaivbudLcP0nFu8tWRpoqU+Tj1Y3uLry0fjljc//4tvPdTt8+SdVcSiYW4+9038b5P3U4obM7JNRXlRzqZ5a1XTnLkrXNFHafrGlt2ruTX/s2jcyYqxqiui/O7/+UjrL1pSVHxaEEgee25o+zfNX8WeDLIJ21fK2yxvqmKT/zWfXz0N+6Zc1FRSgI/4Onv7yFVZGEMIfL9Nj7wmTtZtrZplqy7kpXrm/nIr9/NinWLSt6VfLIoYaG4ochXcRJll4C3fN0ibrt/PVW1saKOkxJOHWmfJatmHsPUufe9N/OuD26lojI6p9eubazkI5+7GytU3EJ4ZChN5/kBspl3TnqcLo7tcWz/Bc6f7inqOKEJ1ty0hF/67XfNaYhGZU2MBz+ynZt3rpqXoXiK6REEAZ3nBqaU+LpsbROf/p0HaVhcPedjsRD50su//f98kKbFNUUd2989wpsvn6D74uAsWTd31DYm+Mjn7ubBD99Compux+JSMzqc4aWfHSz6uOr6Ch7+2K2s37J0Tu/brXes5l0f3EZ1XekaCBaDEhYKRRlgGDobb1nO2puWFneglJw93jU7Rs0CKzc08/DHbqW2oTShBHc9spnmYvtSSOjtHKZ/CrG4xdDe1seJAxeKzq2IJyJ87Av3lWRx0NBcxSMfv3XeTHjlxHzXYpmUzb7dpzh/qjghXFEV5QO/cgetqxtL1rRU0wTL1zbx0c/fQzhaXIGDA7vPcGz/eRx7/sS8X01FZYSHPrKde957E/FEpNTmzDmvP3+UgZ7ixnPD0Nl+7zq27FyFVQIv7f3v38q6rUsxrfIsL385SlgoFGXC4uV1rNzQXFRoiZRyauUdS0A0Hubhj97K0pUNJXPphqP5kKFiN5sGe0cZ7p9+471rEQSSs0c7p5RbsWXnKm65a/UsWHV9TMtg1YbF3Pau9SW5vqI0jFWCevGJA0UdJwTc/sAGbt65iki0tN3ZDVPn7kc3s2XnqqKOGx5I8dbLJ+ntmF8hqGMYps4td6/l/vdvoaY+UWpz5hzf8/nF4/uL7mvS2FLN9rvX0tRSnJdrpkhUR7n//VvnxSaOEhYKRZlgWgYtKxuoXzT53Xwpob9rdnfSZ4rNty5n4y3LiMxRXsW12HHfeowiq54MD6RmpKP3tUgns5w/1cNgb3GNxUIRk/d9+vaSVqmpqa/glrvWUFlTXBifYv7i2B6nj3YU7a2obazkzoc3UdtQ+gWtEIJYRYT3fPI24pXF7doffrON86d75l0ZUMj3prnnPTexZEVDqU0pCT0dQ5w+0lHUMZqusWn7ctbe1FLSMOqtd6xi2ZomjDJtijuGEhYKRRnR1FJNXVNVUccM9ScJgvKe4CJRix33raNxSXWpTaG5tbZoO0aHMlMqBzxZui4McO5k93W7rV7Nqo2LWbelyPC5GcYwdZasaGD91taS2jHfmM9VodKjWXY/e7To+3X7PWtZvqYJwyyPhZFh6qzeuIRtRVZ8G+gZ5cSBi4wOp2fJstkhErO45Z61bLp1xbxJBJ5p9rx4ougwtpr6CtZtWUpdU2mrgUXjYbbfu45oxeyUZ58plLBQKMqImvpE0Tu/uYxT9lVKlq9bxIr1zYQj02vYNhNommDtTS1FHZPL2mTT9qwIOCklnecHOH+muN1fgPvee3NZLNLqmhJs2NZasph5xdwR+AF93SMc3nO2qOPilRFuvn0l1Q3lFcoRS4S5+92bsULFeTEP7D5NT8dQ0eKqlLSuamLbnWuoKNJDs1CQUrLnxeNFNUgEaF3dyKoNi8tCjG29Y1XZe4fVLKBQlBEVVdGik+mkBCdX3omEm7YvL1ls6jiEoHV1caUCA1+SSdmzkrDp2B497YMMFRkGFY2H2HLH6rKocBaNh1m6qpHq+vJaNJYzpX/XpobreJw8eJHRoeI8eKs3LaFlRf2sN18rFsPUWbFuEcvWFDcmnDvVTee5/rLf1BnDChmsuWkJazaXpm9EOTA6lOHciW5kEaXDTUtn6apGmltrZ9GyydPcWkvLivqy2FC6FkpYKBRlhBUyCUetIndGJLZdXGO9uSRRFWXZmiYqyqSkoRCwaAoiJ5d1cIpsYDgZhgdSdF0cLHoXbeWGZuoaK8tCWAghqG1IsHTljRm3fSNh51wOvlGctwJg/ZalZdkrQQhBvDLK1juLK4Dg2B5njnWRnCcNIusXVbH25qXEyjyMZjY5e7yz6LLhVbVxlq5sIBovj9dN0zTWbW0tumz6XKKEhUJRRmiawLQMdKOIj6akrHfNWlY20LikumzCZIQQ1EwhHMNzfDxv5l/nob7klOrib96xorj7ZJaprovTooTFgkZKSSZtc3z/haKOq6iK0rKygViZljaNxkKsu7n4Up6nDl1kZHD2ijrMJIuW1t7Q3gqAkwcv4hWZcF+/qIrFxZYon2XW3dxCKFxenr/LKZ9ZSaFQAPmutMVU+ZFQ1nG+S5bXU1MGVWAuJz6F5nye7xftVZgMwwMpeqZQunLjtmVoZSLWIL94XLS0BlEGccjzgfL9xF6bwJd0nR9goGe0qOMWt9ZRv6iqbDYXrkY3NBqXVNO0pLhwl7aT3Qz3pwiKCK0pBVbIyBetWFz64hml5PSRDvwiN4fqmipZtLQ8wqDGWLa6qSzyFa9FeX7KFYobGSFYKK2MhYCmlhqqyizZrJheIWP4XkDgz+wCQkrJ6FCaob7i8ivCUYvFy+vLIplwDNMyqKqtIJ4oj5ABxczj+z5nT3QVvZHR3FpLVW18lqyaPkIIovEwy9Y0FnVcaiRLd/sQThmHogJU1sRoWdGAaZXvLvds4/sB7W39BEVsDumGRk1Douzu3XhlhNqmRFmN/5ejhIVCoZg1YhURahsShMLltbsylcQ3GcgZ9wzZOZfhwTR2kbkbi1pqiEStssivGEMIQUVVlJoSdVWfb5TPOzd5fC8ouncFQGNLTdlXsolErSmF8nWe7yObLi5uf65JVMfKbtd9rhkdTJMcyRTVGC9WEaa2IVF2idJCCJYsbyirUNjLKU+rFArFgqCyNkZFdbTswmOmvCCf4YiHTDLHUF9xYSWQDy/Ty7BJUiweLjvvlGLm8LyA8ye7izrGtAzqGhMlb4x5Pca8gMXScW6AbMaZBYtmjorKKA2Lq0ptRknpujhQdC5iRWW0LJo5TkTjkpqyCoW9nPK0SqFQLAgqq+PEK8ozYbMcyKTtKXX0blhSjaaXl1iDfAOucqn+pZhZpJT4nk97W39Rx1VURohXRss2v2IM0zKorqvALLKfRef5AXJlLizyO+83tiexp2Oo6E7p0XiobD1tdY2VReViziU3bsCdQjED+J5POpljdChDJp0jl3Wxsw521iGX8/BsD8f18BwPx/HxHA937Mv13/7Z8S997zjXV/Yxu5MlUR29ocsbXg8765AayRV9XH1TJXoZTirhaEgJiwVMajRLJl3c/Zqoic2LMUAIQSRqUVUTo69rZNLHDfSOzEoZ6plC0zWi8TDhaHmFo841+ST74oRFJFa+41ldU6JsxboSFgrFdQj8gOHBNN0XBuhuH6SnY4jezmEGe5MkRzI4tovn5isGBb4kCAICPyAIJEEgkUH+ZynH/p//CmTh+9XPlXGFp2KJxsOEyrh6Ramxcy7pVPF18GsbK8vSDR6KmMTi5R3yopgaUsp8kYEih6dEZZRomYdBjWGFTarrE0UJi3QyRy7jEASyLJNprZBBvDJSlrbNJSODqaKLb0TKeKOkqjZediHGYyhhoVBche/59HUNc2z/BU4f6eD8yR76e0bIZR1c28MpeBk81y/atXqjEY5aU6rAdKPg2B6ZVPGJn4mq8stbAbAsQwnJSTLftg9kAINFdoeH/K7vfBkDTFMnXqR3RQaS0eE0vuejlWHVJdPUiSqxz8hwpmiPhRUyiETL87WLJcJoZVS843LK71OgUJQAz/Vpb+vj9V8c49AbZ2lv6yOXcbBzLq7tzUr/ghuBSNTCKuNGPqXGsb0pVZSJJyJlVRFqDMMyyrq+umLqSCkZnEKhgXDUwizjLsGXY5j6lJr4DQ+k8Vy/LMu5arpWlnbNNcnhTNH9RsyQUbYhZLGKSFluLoESFoobGCkl2ZTN7ueO8NKThzh56CK5jKOExAximHpZVi8qF3zPLzqfRtMEkVioLFudGIaGFTIRgqLKOirKHynllLxr4aiFVWRCdKnQjant7mfTdtnOGZqmYagxmFzaRhYpLCzLKNt7NxK1VI6FQlEuSCnJpm2e/fFefvbt1+i5OITjeEU1zlFMDl3X0Mt0V6UcCPwAr8hwOitsommiLD0WQgh0Q6DpmgoTvA7l9+5dn6kUlTAMvWzr7V+NpospLSQdxy160TpXCE2U7QJ0LnFdv6j8Rd3Ie3rKcZyF/FhrWOUpGJWwUNwwSCnxXJ83XjjOP/zxk3S3D6rFzyyj61pZJhmXC0Egi74HdUMv687sQtOUsJgE5bkMfWcc2yv6GN3QyrYs5tVoQkzJw+raXtFhNoq5xXX8oj5zQhNlP3eVW+O+MZSwUNwQ+F5Af88If/9HP+PVnx9Sk8AcIcp0Z71cCIIA3yuuaZOhi3LWFWiaQNc0yrcAp2IqSDk1j4Wma/OmItFUd/eL3Q1XzD2e6xUVn6mJ8vf0GIaed32W2a2nhIViwePYHkf3tvHX/+9PuHCmb04mAKGJS+EqY4trISh8v/bPCC4ljSsWPkEg8YssgZjfUS3fhZomxLxZSCqKYyobMpqYP5sLAqa0S+17gRIWZY7nBUXlfeU9FuV93+q6Vo66QgkLxcIml3XY/ewRvvw/fspgX/GlEt8Jw9AxLR3DMjAMHcPU0HUd0zKoqIoST4SJxEJEYyFC0RDhiEkobBKKmITCFuGwiVX4eexx09L5wd+/xPOP7ZtRWxXliRD5ycsvIsIkv7grt6nkMvJKudRWKGaBqVQX8oOAYJ4sugNJ0R5EANPS5414ulHRda2oohJSTk1Izylles8pYaFYsDg5l1d/foh//JOnZkRUmJZOJBrKi4WKEA3N1bSsaKCppYbGxVXUL6qiqraCisrIlEOAPM8nnijPhjyKmUfT82LUZfLKwvN8VXFpAVCeS4JrIwRTSmwOfImcJ4UxZCCnKCwM5aUrcwzToBhlIQNZdEM9RR4lLBQLEt/z2b/7NN/40nP09xRfe30M3dCIJyJU11XQsrKBdVtaWHvTUlpXNxKrCKtdKsW00DSBUWTFnKksfOYSKRdW93jF20xFWPieX/47vwXyBT6KF0GmaZRtTwFFHtPSiwobCoKgbEsIj1GulciUsFAsSM6f7uG7f/cCPR1DUzpeNzSqaytYtraRrXes5pa719LcWqsaDSlmFE3Tii7F6To+QZCP6S5HYet7AZ5b3uJHUTxCiCk1P3RsD9ctvppUKfD9gNwU8tuskFG2XZAVed4OV5vcYjwIZME7XJ7jLICdc8rSe61WSYoFRzqZ5afffJ2zx7qm1JsiVhFm9eYl3PXIZnY+sIGahsQsWKlQgGHmG8oVg+f6OLnyXKhJmQ8l8crcq1IOlOF64J0RkKguPkwzl3HK9n69Gs/1ySRzRR8XS0RUI9AyJxwN5b1KkxyaZCBxcm7ZdlSXUk6p/PNcUH6vlkIxDaSU7Hv1NAdeO002XVyXWCGguq6COx/ZzLs/sYNla5vKdqdCsTCwQibRWPGdflOjWWQgEWVWtSQIZL70Zpm66BVTRwhBbWNl0cdlM/aUytSWAs/zyaSKFxaVNbGy7SmgyJOojBadB+M6PrmsW5bCwnW8svUMl9+rpVBMg9Roll3PHKa3s/gQqJr6BI/+0g7e9+mdVNXGZ8G6yaIWZTcKVsggEi9eWCRHMgSBRCuztYzreOSyTqnNmBeUlyS8PpoQ1E7Be5tJ5ebNPeE6HqPDmaKO0XWNikSk7Hse3OhUVEeLzoNxbJdcxqaiMjJLVk2d1GiubHPZ1CdBsaA4vv8CbSe6cZ3ilHw8EeH+D2zlA79yR0lFhQyk2u29gbBCJrF4uOjjBntHCYLySyy0sy7ZKez4KuYBIr8zX+zu7ehQhkyqOO9xqXByLoO9xRX7iFdGCEVMlbxd5lRWx4ruAJ/LOqRGsrNk0fQYHUyVbVEEJSwUCwbfDzi0p61ob4Vh6mzY1sp7P3U7ierYLFk3OTzPL/tKFIqZIxQxiU1hN6yva6QsSyHaOZd0cn4sIhXFIYTADJk0NFcVddzIYHpKeQtzTeAHZJJ20QvJ2sYEVri4PCnF3FNdFy/aq5RN20V7sOaK4cF02W5CKmGhWDAMD6S4eKa36N2xqto4D310O00tNbNk2eRxHQ+3TOMmFTNPNBamqqZ4D1lv51BZeixyGZvkSHlOxOVGeS4J3hnd0Ghd3VjUMZlUjpHBNK5TnommYziOR1/3cNEbO4uW1hKOFl8tSzG3NCyuLroCXyZlMzKUniWLpkd/90jZbkIqYaFYMFw808tAkT0rDENn+dpFbLtz9SxZVRzZtIM9T+KRFdMnVhGmpqGi6OPaz/bheeU3qaSTOUYGUqU2QzFLGLrGsrVNRR0TBJLermFSo+UZUjJGLuPQ3tZX9HHNrbVEosXnSSnmlkVLazGKrNyVGskwOI0+WLNJT/vQlKpezgVKWCgWDD3tg4wOF7e7EI5ZbL1zFdEpxLnPBqmRLOl5EDagmBmssEFlTazokrMd5/pxcm7ZJe+lkzmGlLCYFPMxIl83dFasXVT0cT3tg4wMlufO7xjZtM3FM71FH9e8tE55LOYBlTUx4pWRoj54qdEs/T3l6RnoujhQlnaBEhaKBcRA72jRi/JwxGLTrctnyaLiGRpIlW1Mp2Lm0TSNRHWM6rriwqHSyRydF/rLKsY2CCSjQ+my3eFTTB9d12hZ2UA8UVxeUHtbH0P9yVmyavpIKUkls7Sd6C7quIrKCA2Lq6fUkVwxtxiGTnNrXVF5Fq7jM9A7ymiZhUP5fkD72T78MvRagxIWigXEyGC66N4V0ViIJcvrZ8mi4unvHmaor3wnYMXMU10bp2FxddHHHdt7vqx2rHIZm76uETJFfgYV8wehCRLVMVZtXFzUcT3tQ/S0D5VtnoXreLS39TPYV5wobl3TRHVdvOhqQ4rSsGrj4qIbGQ50j9B1YWCWLJoa/d0jDPYly85jPYb6NCgWBL4fYGfdohS8pguq6ioIR8rDje3YLj3tQ2UfMqCYWWrqEyxaWlv0cQffOFtWwmJkME3H+f5SmzFvKM8lwfUJhU1uum1FUcfYOZe2E11lO7ZlUjbH3jpXdKW11RsXU1niSoKKybP25haMIhO4e7uG6Wgrr3HtzNFO7Fz5Np1UwkKxIJhKF0pN06ioipRNd+3ezmHa2/rKdldPMTtU1cVZ1FJTdFfYEwcuMtSfKptdq8HeJOdOFhdKoph/WCGTjbcsw7CK2/k98tY5ejqKb1w620iZD+F769VTRR1nGDor1jdTURWdJcsUM82qjYsJFVkaeLA3yfnTveQy5VNU5chbbThKWCgUs0vgS4IpLLCKbfY0m5w/2cP5Uz2lNkMxx1ghg8Yl1dQU2dU4ncyx79VTZSEsfM+np2NoSsmvivmFpgsal9Sw7qalRR138UwvbSe6ymqBBvmmeMf3X6T74mBRx7WuaaR5WR2GWZzAUpSORGWU5esWFdXM0HU8LpzuKRtvrJ11OLbvArathIVCMavohih6xxcJTrY8PpzJkQwnDl6gu8xiORWzjxCC5tY6lq5qKPrYXzy+rywa5Q31pzhx8ELZLRrLmfLwkxaPEIKKqig7H9pY1HGO7fHWSyfo7Sovr0VqNMcvnthXdOnOzTtW0Li4umw83orrIzTBrfesLbpRXtuJLs4c6SiLTZwje8/T3z1cVoU7rkYJC8WCwDCNopvfBEFAqkxKu5452smhN86q5ng3KM2ttSxbU1x/AIBTh9o5tu/8LFhUHD0dQxx47UypzVDMEeGIxabty6lrrCzquAOvn+XkofayiQ93HY/Db7Vx9K1zRR2XqIqyfsvSKTW3VJSWHfevL9rLNNg3ytF95+nvHpklqybPrmeOkBwu754wSlgoFgSaJohEQ0UNGIGUJIcz+H5pF/PDAyn2vnKSM8c6S2qHonTEKiIsXdVYdLM8O+fyk6/tmiWrJkdyJMORt9qm1FzsRqZ89xuvj6YJ6hdVcvuDG4o6Lpu2ef6xvfS0Fxd2NBtIKUmOZPnJV1/FsYvLa1u/rZWWlQ1Fb2YpSk/jkhpWbmgu6pjAlxze08aJAxdnyarJ0Xa8iyNvtZHLlbdnWH0qFAuCMfd8OFJEYpaEdDJLewkrPvh+wMHXz/DSkwdxHeWtuFHRNMHKDc2sXF9cGU+AfbtO8eZLJ2bBqusjpaTrwgAv/vRg2dZUV8wOieoYdz+6uegeLIfeaGPX04dJlrhfj+t4PPXdNzhxsLjFYiRqsePedSxeVjdLlilmE13XeNcHtlFsBFvXxQH2vHi8ZKVnpZQ8++O36O0YKvtdCSUsFAuGqto4kVhxHbRzWbekuxCnDrXz02+9Tm/HcMlsUJQHrasaWbelpeiqJZmUzdf//JmShPUND6R4+clDnDvRNefXVpQWTRMsWdHAve/dUtRxnuvz2Nd2cXz/BVy3NBXwgiDg+IGL/PArLxUtiG+6fSXrtiwtq8IfiuK469HNVBYZxhb4kteeP8reV0/hlKBy4/7dp3nzpZNkUuXfJ0gJC8WCoXFJNYnq4kr/ZdM59rx4vOjEvekipeT8qR5++A8vc3jP2bJIClOUFsPUWb+llWVri8u1kFLSdryLf/hfP5uzvhZSShzb5dCeNn727dcJyjiRsFyZ7ym/QgiqauPc+fAmGots8Dg8kOJv//sTtB3vxveDOR3/xrxsf/IH3yVdpBiPxsPceu86lq5qVEnb85hYPMS7Pri16ONGhzL87FuvceiNuZuzpZQM9I7yo398hY5z8yPcVAkLxYJhcWsdVbXF7UK4js/JgxfZO0dlO6WUBEHAhdM9fOsvnuOVpw6qRZkCyC/U1m1tZdP25UXvhjq2x4s/PcD3v/xi0f1cikVKief6HHnzHH/3358gkyqPAgiKuUcIWL5+ER/67F1FJ8S2t/XxZ//39zlzpGPOxEUQBHSe7+e//s7X6W0vrjqVEII7Ht7ItjtXq9yKeY6ma7z3UzuJJSJFH3v2eBc/+PKLHD9wkSCY3Y0cWcgD/ac/fYqDr5+ZN+Gm6tOhWDA0LqlmUUtt0Yuywb4kj399F8MD6Vmd3KSUuI7H0X3n+cv/8hgv/uwAylGhuJxI1OK2+9ezevOSoo9NJ3N8/8sv8sOvvEQ2Y8/KvSylJJdx2PvqKf7s//lBWVRJma8shI++EIJYPMz2e9ay84ENRe/inz3exX//19/k4OtnyWWdWRt/pZTYOZfj+y/wn37zH6fUyHHFukXc8+6bWLS0Vnkr5jlCCOqaKvngZ+4sOtcCYN+u03z9i09z4sBFPNeflfvW9wJ6O4b5+//1JK88dQi7TErjTwYlLBQLBk3TWHtzC3WNxTUa81yfQ3vO8rU/e5rR4cyMexCklHiez0DPKM/+aC9//Pvf4eDrZ2f0GoqFw/qtrWy9YxWxiuLyhQBSI1m+8ze/4Ct/9CS9ncNFV7u5FlJKXNdjoGeUJ7/zOn/8b79Tll2UFaWhubWWhz92K82ttUUf231xkP/yz7/Kj/7hFQZ6Rmfsnh3DsT2G+lM8/vVd/Off+ic6zhVfrCOeiHDPe29m844VM2qbonSYls4jn7iVppbi71mAva+c4i/+8Me88eJxUqPZGfNeBH5AJpXjyFtt/MUf/ohf/GQv2XnWH0hlHykWFBtvWcai1lq624eK2kXIph1e+tkBhIAP/uqdNC6pwQoZ09qZGvNQjA5nOH+ymye++Rp7Xjh+3Th43dCQkjnP+1CUB4apc+fDmzl1uIO3XjpRdN5EJmXz1Pfe4PTRDj74q3eyafty4pURQmGz6PtZBpJs1iE9muXUkQ6e+Pou9u06/Y7HCE0gBGXRuE8xN2i6xsZblvGRz93N1774DMMDqaKOt7MOX/uzp3nt2SN85DfuYf3WVuKJMJFoCK3IZmaQHzuzGYd0Msuxfed5/Ou787vLXvFhglbY5O5Hb+Le99xMOGIVfbyiPBFCUFUT4xO/eR9//d9+MiWPwJmjnfyff/89HvzwLbzrg9toaK4iVhFG07WixlopJZ7jk0nn6O0cZvezR3jusb3XLepimPqsh75OBSUs5jlSykuL0CAICPx8DL/vB/heMKX451zGYXQog5QSTdPQdFH4rqFrorBwKE9X8KKltWzavpzTRzoZHUoXdWw6mePp7++h7UQX7/v0Ttbe1EKiJkYkGkI3JjdQBEGAnXPJpmySo1najnfx0s8OsveVk5NqChWOWKzevIThgSQXz8yPRC3FzLN8bRP3v38L3RcGuHi2t+iQOc/1Ob7/AudOdrNhayt3PbqZ1ZuXUFGZL8lsWiaGqaFpGkKQH0MCie/5eK6PY3vksg6pkSxH9p7jjV8c4+AbZ6/b7dUKGSxaWovvB7SfXVj3bz4/ShbGWnlpzPV9iZNzi+6H4/sBqWSW0aE0mq6haaLwPT/m6poGgrIda68mEgux88GN9HWP8JOv7ZrS3HPqSAd/9PvfZuWGxex8YAM33baCqto44aiFZRmYVr4R6pX3bX6+cx0f13bJZRyGBlIcefMcu587wtljXbhTrOJjmDpbd67ikU/cSuOS4hLUFeWPFTK546GNHH6zjV88vm9KmyHJkSw/+sdXePWZI+x8cAO33b+e+qYqIvEQoZCJaRmFNZRAkt+sCfwAz/NxHR8755JJ5ug418/eV0/y1iun8iVlr0NFVZRVGxdz8LUzc1a0Y7IoYVFipJQEvsT3AwK/IAgu+/mK797Ezzm2RzbtkMva5DIO2YxDNm2TTdtTiiU9vKcN1/HzfSGiJpFoiEjUIhwNEY5ahMMmmqGj6wJdLwiOCb9f+3ltFsXJHQ9t4sBrZzi0p63oXX/PCzi27wJnjnayfG0Tt9yzltUbF1PTkCAcsTBM/dLkD/n3z/d8XNfHtT1So1k62vo4eaidw2+20Xl+8jWvrZDB9nvX8ku/dR8v/vQgPR27cMqkQ61i7tn5wAYunO7hp996jdGhqdX8H8uH2LfrNFW1cVauX8TSVY3UN1dRWR0jHLXQdQ3PC3Bsl+RIhqG+FL2dQ1w43cuFMz2T3snTDY11W5by4V+7m2P7zvPdv31hSjbPFmMbL/lNF78wfsoJx9SJxl7PzS8CshmHXOaysTZjk0nZRe/SD/Ulef6xfRzff7Ewvha+IhaRwlhrWvp1xtj8d924xniraQht7oRJdX0FD3xoGyODKV786YEplcaUgeT04XZOH27HMHWWLK9n+domGpqrqW1MUFEZxQobGIaO7+c3clKjWQZ7R+lpH+LcqW462vqn3d3bMHVWb1rCuz95G2umkPOkmB/EKyN89Dfu4dzJbs4cnXqT2t6OIR77p1d54uu7WbqqkZUbmlm0tIb6pirCMQsrZIKU+U2bgvgd6Bmh89wA5093M9A7OmlhE45YfPAzd3D3u2/mX3/iS2VXglYJixLiuh49F4e4cKaXXPbKySqXcfKPZQs/F76yGRs7e9nvZJwZV6snD7Vz8lD7NZ8XQhAKm4SiFpHI2GRoFr7nJ8TQpf9b478XduWr6+KXFugzSevqRu58ZBMd5/qnnFzq2B4nDrZz4mA7mp4vq9jQXE1FZYRwxMKKmCDzVaWyGZvRwTRD/UkGekenVLnBtAw2bl/O+3/5DlZuWMypI51U1cYntXOhWJiEIhaPfnwH/d2jvPLUwWnF2UopGepP8ubLSd58+eQMWplHCEHz0loe+sh2br1vHd3tg5ghA3eG4+WnSiaV48SBiyRHs4Vx035bIGTdt8fY7Nvj7OX/z2UcHNub0STNkcE0rzx16B1/xzB1QpExsXHVuBp5W4zkn3v7ezgaIhwxqWtMsGL9YqzQ3E31S5bX84HP3InnBrz6zGEy0+iv4rk+5052T2mDbDoYps7KDc18+HN3sf2etfPGa6QoHk3TWLysjk//iwf58v/4KV0Xp9cAz/cD2k500TZLvX10Q2PH/et4z6duJ1EdI1YRUcJC8Tbp0RxP//BNvldmO3vXQ0p5SfRMtSbMv/vTT3HHQ5uwQrNTP+De927h7LEuXnxi/7QTnwJfMtibZLA3OUPWXYlpGazb0sKHf+0uNm1fhhCCxcvqqK5TwuJGp2FxNR/+3F2kRjO89fLJGU9snQmEgNrGBA98+BbufHgTuq5RWROjqiZOX9dwqc0DoPP8AH/8b7/DYN/sfIZnC8/18dws6dHslI7ffOsK/u2ffpK66DRERwAACdJJREFUxsoZtuydWbamiQ9/7i4QsPuZI6SmaH8pME2dlRsX8+HP3c0dD+XvZ8XCxgqZbNm5ko99/h6++ZfPMdAzWmqTJkQv5DJ98rffRWV1DE3XaFlRT1/3cFmVmVOfGMWCJFEV5YO/eiebd6wo6w6pVthkw7ZWPvb5e9l25+pLiYqLW2uprqsosXWKcmD52kV8+HN3s2Xnqrw7vZwQUFOf4JGP3cq7P7GDSCwEQGVNnOq64nrKKBYWy9cu4iO/fjfv+uBWahoS86IjYDhisfm2lXz8C/ddEsmKG4NoPMydj2ziA5+5g4bmqlKbMw5N19hwyzJ+9f96hJaVDZfWCq2rGxFl9uEq3xWXQjFNlq1p4mOfvxfH8Ti8p63sqidEYiFuum0FH/iVO7j59lVXNF2qqqugflEVVsgoy11qxdyy+dYV6LqOYeq89crJsqhpLjRBXWMlD37kFt73yztJVMcuPVdVE6NKCeMbnmWr82NwdV0Fzz22l67zA2WXaAqAgERllFvvy4eYrN+yVIU/3YBU1sR5+GO3Yhg6P/3Wa0XlSM4mpmWwYVsrn/oXD7Bm85IrmlHmu8BTVj2xlLBQLGg271jBJ4OAH4VN9r5yasrVQWaaqto4t71rPY98/FbW3bR0XIKlrmssWV5HoipKf5m6ZRVzy4ZtrYQiD5KojrH72SOMDKVL5v7WdY2WlQ08/NHtvOuDW6msudI7oTwWijHqF1Xxvl/eSf2iSl544gBH952fVt7FTKMbGq2rG9n54EYe+OA2Fi2dWl8DxcKgqibOgx++hWg8zFPfe4OzxzpxndJtSsYTEbbdvYYP/ModrNm8ZFwERuvqpoIILh9loYSFYsFz8+2riFVEqK6ryC/IBosrQzuTGKZOy4p67nnPzdzznpvfsaFUy8oGKmvjSlgoLrFyfTO//DsP0ry0ll88sZ9zJ7pntVv8RISjFpt3rODBD23j9gc2TBieVVGV/7xpmpjxhpOK+Uc8EeG+92+lZWUjLz91kDdeOE5nW/+U+krMGAKqa+NsvXM1dz26ma13rFZ9KhQAJKpj3Pu+m6lfVMkzP3yT/bvPzPm6QWiC5tZadj6wkYc+up3Fy+omDM1bvKwW0zLws+XTRE8JC8UNwaqNi/nl33mQ1lX5ie3EwYtTqt40VYQmqKmrYMsdq7jjoY1s2bmKaPydOysvWV5PZU3sHX9HceNR11TJhz57J0tW1LP7uaO89fJJBntnX3wKTdC6qpHbH9jAzgc3sHrjkmuWMrVCJtV1caLx8LxK3FXMHrqusWbzEpqWVLP2phb2vnKKg6+foevi4Jw3A62qjbPp1uXcfNtKtt+zlqaWmjm9vqL8iURDbLljNfWLqli+tpk9Lx7nzLFOcnPQBTtRHWXT9uXc8dBGtt21hqra+DVD82KJCHVNlbS3lU/fICUsFDcMdU2VvP9XdrJ83SL2vnqKA7tP03aia1ZzGLT/f3t38tS2GYYB/JEleUdehY0xBrOYlMUkNCGTNL2108m1/2j/gE4PnWl6aKZpMyQ0LCkEY2zA2Abv1taDaGZySAIohCXP72zPyB5b+h7pe9/XJWAoE8P0wgjySxOYX8piKBM71f7diGrXWchu8VIfxdLVI3tkPPhuFpNzw5j9egzPflvD6vMC9i6gi5jgEjCWS2L+XhZ3Hk4if3/io6EYAMKxAYSiAQYLeocSCeDRD/O4tZDBnYeTePF0E6vLBWytlh3PnvgQUXJheEzFxEwK8/eymLubRXpcZS0FvZcoupCZTCCeDGFmcRTPnqxj+Y9/sblW/vTb+U6eoOXyI8gvjWPxUQ7D2Thk+cPLdAF2nQWDBdElESUR+fvjmJwdxu0HE3i9sou1k4taeaf2SWowZLcENRVGOhvH1Fwa2ekhjOWSGMpEzzS3Q5JEjGRVBBUfapWzDd+iL4OaDOP7H+9idnEMGytFrL8sYn15B8XNA9QqjXMX9LlcAtRUGJmJQUzNpTG9kEFuPo1w7PR1E5F4EOFYEMWtyvkOgm60eDKEbx/nMXs3i+2NPWytlbG2vIPtjT2Utg8/SW9+f9CDxHAEw1kVE1+lMJZLIjOZQHIkCuEaTTWny+UPejG/NI7RqQQWH01h4+X/64YSSoXq+ZtpCEAg6EU6q2L81hBy+RHk5tNIjcVPvy1PsDtD/f7zi/MdwwUQrM+9QZfe6nU1bL4q4fVK8bIP5bO7/c0UkunopbbzsywLWt9AuXCI8k4Vezs1lApVHJTqqO4f47jWRvO4g26nD10zYOgmBJe94JdkCbJbhNfvxkDIDyUSgBLxQ02GkExHEU0oUJNhpEZjb1twnkfh9T7WX+yg03r/RVaSRXz7OH+qu8jnZZkWSoUq/npytuFqufwIJmZSFzII8bwsy0Kvq+GXn/480/vS4yqm5tIX+j07YZoWmkdtFDcr2C/VUC7UsLt9iOr+MWqVBo6qLXQ7fWg9HZqmAxAgu0W4PTK8PjdCsQCiqoJ4QsHQaBxDI1Ek0hGkMnH4Au4zL8Lqh02sPi+gUq5/9LVT8/bv5KLOB0fVFp7++gq9K7QP+XOIDip27YD/6tcO6LqBvZ0a9ndrqJSPUC5UsVesoX7YRP2wieNaC92OBq2vQ+vrME0LkuSC7JYgyRL8AQ+UiN+eoXIy0HRwOIxYIgQ1GUIiHYXbI137MPHP39t4s16Gccouhx6fGxMzKWSnhy74yL4c/Z6Gg906SjtVHBTrKL6pYH+3jlqlgdpBA81GF1pPQ7+nQ9cNyLIE2SPB45ERULyIqgOIDSoYTEWQGosjmY4gORJFVFXe6fh0GpZlYWu1jJVnWx99bUQdwPRCBrFB5Zyf/HQYLIhg/zkN3UTjqI1G3Q4UnXYfvU4fWt+AYZgwTROCIEB0ueASXRBPLmr25FsPfAE7ZAyEfBBcwrW/gNH1ZVkWeh0N9WoTzeMO2o0uOq0e+n0dhm7a9UWC/ahfkkXIbnthFlB8CCpehKLBG7EIo+vJMi20ml0c11poN3toN7votPrQNB2Gbt/ksSzLPg+LLoiSCLdbgjfghj/ghT9ohwxfwHOlbmrQzWMYJhr1No7rbbQaXbQbXXQ7fRi6AV03YRqm/RuV7XbhHq+M4IAXAcUHJexHQPHduHkpDBZEREREROTYzYpJRERERER0KRgsiIiIiIjIMQYLIiIiIiJyjMGCiIiIiIgcY7AgIiIiIiLHGCyIiIiIiMgxBgsiIiIiInKMwYKIiIiIiBxjsCAiIiIiIscYLIiIiIiIyDEGCyIiIiIicozBgoiIiIiIHGOwICIiIiIixxgsiIiIiIjIMQYLIiIiIiJyjMGCiIiIiIgcY7AgIiIiIiLHGCyIiIiIiMix/wCpRVg/6NAMFwAAAABJRU5ErkJggg==", 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oJk+mUCJbKE18LpbIl2xKjoPjKjyl8DwPz7v89eUPXdMmPnQNXdMx9ImvTV0n6DMJB/3EggGiIT/RYIBYKEBDPExTTYzGmgghv6/SPwpR5SSwWFAeeesEA+n/haPSKLV0qj4ZehhQDGa+zlDmGxTsM0wXAN2Ip/Lk7eNYbj8lt5e2+D8l5Ns8r+DC9XKkCi8xmP06udIRXDWzPdvXzitrvUPBPkfBPkNL/DeIB/fO6L6aZlIT3Md4/lmy1uTAIlX4GVb8NzD0OJpWnrM+meJblJxerv3ZRwK7CPk2IIGFWAqGxjKk8zMLLFrq4qxtrVvgGQlRvTzPYzRboHswyYXhcfrH0gylsoznCuSKFrmiRd6yKdkOluNiXf5sz7AwwvVoTKwY+k0Dv2niNw0CPpNwwEck6Cca9FMXDdOUiNJWG2dNUy2djbXUrqBtneLmJLBYQAqF5+WwvZFKT2XWdC3CaO5RBtJ/Tcm5xGyDivdyvDHG8k9j6jW0xv8JAbN9TuO4Xo6x/NP0pf/ycqAz81r4046nUowXfoar0sC/IB7cN6P7hXxbCPu3kreP46l3D5Zsb4RU4SWC5mo0bf7VfjxVJGMdwHaHp1xXF/4ohh4uywqQEAttLFMgX7x5GV5d09jU2YjfJ29NYuVwPY+RdI7TfSN09Y9wbmCUgbEM47kimUKJXMmiYNkzrqg2VwomAhXHheuUv/ebBiH/RKARCwVIREK01cbZ0FrPhtZ61rc20BCT96aVTF69F5CGhqFHCJjX32qjlHN5S9S1W3kMfEYduja7MwGmnsA04nOY7WR56zjZ0juUnB7eDSo0fEYzscAewv6tmHodhh5BKQvLHb58nwNYbv+U8TyVZzT3GGH/durDH5t1UrenSqSKr9KX/vPrrJ6YhHzriPp3E/Stw2fUoWl+PK+A5Q2TLx0jU3oLx0tOupfCIlPcTx9/ianXEvZvuelcDD1EPHgX6eKrU8oEj+YfozH6C+gEmO9qQt46RdE+O6W/ianXkQjei4YsSYvq53oe2UIJy7l5iVdN11jTIqsVYvlzPY+hVJYDZ3s5cK6XM/2jjGULV7c1WbNoIrmYrgQeqcsrkBoTuWWx0MS2qfpYmI2tDdy2vp2da1ppjEfRdQkyVhIJLBaUQTx4N5sa/+q6t7DcQYYy32Ss8NSky029lraaLxEP3DHrx/QZ9XOY62Rj+WdwVZYrSeWGHqMp+ivURz6GqddiaFE0zYemGSjlobBwvSxF5wIj2R+QzD9+OX/kXY43RjL/OLHAbYT09TOei1IeeesU/em/omCf5dqgIuTbTGPkM8SDd+EzGtD1MDq+iRwR5aKUhRvJYjkDDGe/y3Du+7x3tUNhkym9RX/6r1ld9x8w9ZtXookH7yJorqHoXOC9ifd56wQ56yjx4N3zTqrOlPZfDuwmqwndh89olDNCYkkolmyKJXtGidsa0FQrlaDE8qSUYjxX4NVTF3n95AVO940wlsuTzhcpLNHeKgoo2Q4l22EknaN7KMnxS4M8f/Qs9bEwm9oauXvrGm5f3yFbplYICSwWkKZpmEYC00hc9zaGE5n2el0zCRgdMzqDvhAmtgdNMPVa1tX/f4gGbsM0EmjXnonXAEKYeg1+o5mA0YGhRxnKfgelJu+rzhTfpGB1ETA70bWZnXG33WFGcj8kVzrM5OpZGvHg3bTGf4toYA+GFpma26ABhDFJ4DfaCPg6CZht9KT+B+8NUDxVIF18lWTuxzTFfvmmczL1OmLBO8hZRyZtdVPYjOQeIxbYO6/AwvHGyVmHsd1rk+U16sMPo+sRJL9CLAWW4854C4emadREV07TQLEyuJ5H72iaJ985xYvHz9GfzJAulCjZSzOYuBGlIF+yyZdsBsYynBkY5eUT3axqSPC+bWt5aNdGWutiZe1NI6qLBBbihjT8rK3/I2pC982ojKqmmQTMDhqjv0DRuUCq8Pyk6z2VJ2cdIxa8A924+ZYHT9nk7eOM5n6IYvIe7Yh/Fy2xf0w8uG+Gc9Px6Y00xX6Ngn2G0fyPJ11vuQMk80+SCD2I32y+6ViJ0AMk8z/Ftibn0IwXnsL2fge/1jrnVYWcdYyifZ5r80jCvi2EfFsulwMWovq5rod7k07k7xX0y3NbLA+e53G8Z4jvv3qEN05fIpUvkC/ZeDNZvlsGFFC0HIpWltFMjtN9w/zojaPcubmTn7tzBxta6/EZK6v09kogr+Dihhpjn6MmeM+s9vNrmk7Yt4V44A6yxbenVG4q2KdwvSy+GQQWjjvKaO7HOF5q0uWmXk99+GFqQvfOqm+EpmmYeoL2xJcZLzx/ebvXFS5F+xyp4ss0Rn/hpmOFfBsI+7dTsM/gqcK7c/ZSjOWfojn2a8x1VSFbPEDRvjDl8trwQxOrRrINSiwR7uVylzOhAaYhZzLF0teXTPG/n9nPc4e7yBatqs2ZWCyup8hcLo3bP5bmuUNneGj3Rj5/362019VIHsYyIq/g4rpMPU5L7B+ja5FZH8hqmknYv4WAb/WU6wr2uSn5F9NRysNyBxgrPDPluoj/FmpC9894O9W1/EYbidCDUy633AHSpTdQ3HzrhqaZ1IYexGc0TbluOPs9rm16OFMlp4+8fWLSdjQAXQtTE7ofQ4vOaVwhKkEphZrFGVo5vBBLWaZQ5P956g1+7X98h0feOEoyW1jxQcW1SrbLcDrHd185wm/82Xf5X0+/SSpXnNXrhKheEliI60qEPoDPmGv3W42A0Y7fmLqlyPXGUermpSddlSNdfB3Xu/YAO0I0sJOQbyNzOQzRNA1N81Mb/tCU6xQ2JfsSRev8NPecqiZ0L0FzNTB5OTdvnyRbemfWc1Moctbhy0nqUx/Lb7Qih15CCFE9lFLYrsvTh07zha9+h7968nWGU7l595VY7mzXZXA8y18++Rqf/2/f4PmjZ7EcVwKMJU4CC3FdteGH0LXgnLfdGHocQ596dt1VORQuN+uN4XlZ0qU3plzuN1svN9qb+9NXwyTs28p0fwKOl5xSRvb64wRJhD+AT6+95hqP4ex3Z/0CqZRDzjpE0em+5hqd2tCH8OmyDUoIIaqF43oMjGf44+//jN//5lN0DyUXvN/EcuN6ip7RNP/ybx7jT374PKOZvPwMlzAJLMS0NHwTB+/zSMPRtCDaNPkPniqicG4YViilcFWeXOnIlOv8RhNB35o5z2tibhqGHr3Oikqakts343FqQx+cZjuUYqzwzJS+GTdTtM+St05N6dIeNNcQ8W9H16VcnxBCVJpSULBsXj5xnt/968f44etHyZduvhIvrs/z4LuvHOa3/+L7vNl1iYIlP8+lSAILMS2/2Y6uheZ1dlzTDDSmr/igbtrJ28N2R3G8a8utgqHF8elz3aL13vlpGNP0rPBUEccdm/E4AbONePAOdC086XLXyzGa+/F17jWVUoqcdexyA8DJEqEHytKfRIjFoJTCdT1KtkPRcmZVFUqIaqeUIp0v8g8vH+L//u6znLg0JM/xMlHAmf5R/u3f/YTvv3aEdF5yL5YaqQolphUw2+ecGF0OStkUnYvTX4eN5Q5MG3TMxrWVpq7wVAnXy0573fXUhh9mLP8MJffdpHSFzWj+MZpiv4SuBW46hqty5K3jlJzeSZfrWph48G7MKdutRDkVLZu+kTTuIizB+0yDuniYeGRp9Wy48gbvuN57Ptwp/y/ZLplckWQ6z8WhMfpGpv9bm278nqEUkeDN/17mIuA36WhMSAUaMWee5zGUyvGtl97hkTeOM5Yr3PxOYtbS+RJ/8fhrDI1n+cIDe2iIR9BlG/CSIIGFmNZEbkTlFrQULo47PO1144VnGS88u3CPrbwpPTNuJhq4laBvI5Y7gOJK0yNFwTpNtnSQePDOm45RsE+Tt05wbTWpWGAPQXM1miZ/rgvpTO8o/+rPHmEklVvwx2priPPbn9zHx+7evuCPNRee55EtWJRsB9txsR0P23WxHZeS7TCeLTCWLjCWyZNM5xnLvPfrPOlccU6Jq7br8R//5skF+I4mbFvTzF/+q88SDs68RLUQV7iex4Whcf72Z/t55tBEGVmxcLJFi3945TAjmTy/9dAdrG6slZMCS4AcqYhpGVqYSlYfUrjXXVFYeB5Kza48oK75qI98lKz1Dq43/u5IqsRo7tHLnbivH6gp5ZK3TpC3u665xiAefN+0JW2FWCjZgsWPXjpCz/D45aChcDV4yOSLyM4EsdJ4nkf30Bj/6+k3efbwmWXZNbsaFSybZw6dplCy+NJH72FtS52sXFQ5CSzEtDQtgFbJsqZKTWo6txQkQg8wkP7f5L0UVypeKSxSxVew3AECZtt172t7SfLWCRxvchfvgNlKNLBz2lwQIRZKKlfgez87RN9o+uY3FmKZ85Ti4kiKv3/+AM8fPStBxSIr2S6vnbpIwGfyTz9yF6sba6U6YhWT5G0xrYoGFQAolFpa5eZ8RgM1oQfQrsmncNwkY/mnb3jfgt1F3jo25fJ4YB8Bs11eRIUQogKUUvSNpvn2Swd5+lCXVH6qkIJl89Lx8/ztc2/TM5qSVdMqJisWojpp2nVyCgyCZidh/+YFfHCTiH/bnO5ZH/4YI7kfYLvFq5d5qsB44Vkao5/B0CNT7uMpi4J1ekpTPF0LEwvejs9onNNchBBCzE8yk+ext47zxIFTZAqlSk9nRcsWLZ47coZYKMCvvv82GuNT309F5UlgIaqUfjnPYzINg3jwHlbV/psFfvS5VcQK+7cS9e9irPAcMJGnoXAo2F1krUPUBO+ech/LGSBnHcNVmclj+bYQ8m1E15ZW5SAhhFgOCiWbl09289MDJ6uq+pPPNAj7fUSCfiIBP6GAD79pvOfDxDR0dE2b+NA1NG1iH4KnFJ5SKKXwPIXrTXQNt5yJjysFGvKWTb5kkS9a5C27asrpjueKPH2oi7a6OJ+8YxvhgBRiqDYSWIiqpGFgGnVTLlfYKBwMLYymTd8jo5I0zaAh+vOkii/hvScB3PHSJPNPEg/cdU0St6LonCNnHb52JOLBOwmYqxZl3gL8pk5jIoLjuhQtB8t28WS9XYgVyfU8jvcM8thbx7k4PF6ROWhALBSgNhqmLhqiNjbxOR4OUnPlIxIkHgoS9JuEfCZBv4+gfyLQMHQNXdMxdA1D1wANTylcz7v62XlPv5mi7VCwbAolm3ShSDpfIpUvks4XGc8VSGYLjGXzlz8XKtbArj+Z5if7T7CqIcFdmzsxdNnVX00ksBBVSdNM/EbrNNcoPC+Hq3KYWnzR5zUT8eDdBMzVFOxTVy/zVIFs8W0sp5eA791gwfUK5K1TFJ0Lk8bwGU1EArdI74pF1JiI8vmHbmM8W6BQsimWbAqWQ8myKV5+4y1ZDkXLnngTvnLde76eS4lVIUT16Uum+cn+kxw837+ojxsO+GhJxGiri9NeV0N7fZymRIzGeISmmiiNNRGCPnPOeXc6GqYxuwPxKw0Bh9I5RlI5hlJZBlNZekdT9CfT9I2lGUrlFi2pXQEne4d59M3jtNTGWN8izWOriQQWoippmJeb9AXw1OR9rbY3huX0Y/qrM7Aw9Th14Y/Sm+ri3Z4UCtsdJFV8iSbf56/e1nL6yFlHUNd8j1H/boLm+qpclVmuamNhHr5r69X/e0phOy7FkkPRtic+Xw0kJgKP4nsCjYJl851nDzI8PrvmitWoJhLi8w/tKcue8mze4pUj5+keSN70toau8fG7t9NSvzBV0BoTUXym/E2JG8uXLN7susTPjpzFdmZXenwugj6TjoYaNrU1srG1gdWNCdrra2ivqyES8le8vKqmadREQtREQmxsbQAmVnTGc0V6R1P0JlNcGBrnTP8IXf0j9CXTWAv8c7Mclze6LrK5vZGWRIyI9KapGhJYiKqkaTqmXnv5zP/pSdfZ7hBFp3uBE7jnpz7yMQYzf4Pznp4WjpcmVXyZhsjPo+tBFIqic4FcafI2KE0LEA3cSsBsX+RZi/fSNY2AzyTgM6lhZnkuz73dxUgqu+QrlsQjQX7pg3vKMtbAaJqe4fEZBhY6n7hnG7s3dpTlsYWYLaUUF4fHefpQF8lsfkEfKxEJsXN1C7vWtrGxtYF1LXU0J2L4l0Dwa+g69bEw9bEwt6xupWQ79I2lOT+Q5HTfMIe6+zl+aZBUvnjzweZoLFvgpePn2bW2ldvWy2tGtZDAouI0pmtEp1Bc6YWwUhl6hFjg9imBheX0k7eOkQi9H12rzrMUQXM18cA+koXHr16msCjYZ8nbp4gGduF6WQp2FyV38lJ7yFxLxL8VQ5+avC6EEGLhZAol3jh9kUPn+xZkfA2ojYW4c2MnezesYntnM6sbawkF5lYwpBpoGgT9Juua61jbVMddmzvpHkpy7OIg+8/28PaZHkYyCxOknewZ4pUT3axrrqM2Ku+Z1UACiwrTMNGmqUCklI1i4Zdgq5mhR4mH7mE4+10U7yaJuSpDtnSYgn1mzmVhF55BQ+wzJAtP8N4A0XZHSRdfJxrYhe0OkrOOApP3pUYCuwn6NlDJzudCCLHSKKW4MDzGk++cXpB+FUGfye0bOnho9yZ2r22lra5mSaxOzIamQSToZ3tnCxtaG9i7cRUHz/fxzKEu3jnXR65klfXx8pf7W9y6tp17t62Rnk9VQAKLCtM0P4YWmnK562VxvQxKuSt2n72Gn7BvMxH/LWStA5Ouy1lHGM8/S8BchVmlXamj/lsJ+7aQt09cvcz1UmRL7+Cp4uUys0cm3cfU64j4b5HeFUIIsciyRYuD5/s43Tdc1nE1DdrravjM3bewb8tq1jbVEfAt/8OvgM9kbXMdrbUxtq1q5tWT3Tz65nG6h8bKWnHv/OAYb5/rZcfqZlm1qALL/5ld5XQtjKEnmDg7/e4fmsKiaJ/F8cbxGSuz4oGmafiNFhoinyZnHUa958y+4yUZzf+YgG81deEPo1/T7brSNE3D0KPURz5BfvzdwELhUHJ7yVvHKToXsJzJ26DC/i2E/VvQtaW7LC6EEEvRcCrLy8e7y1rdzdA19qxr59cfvJ1da1qJh1deX6Kg3zeRZF0bY0NrA9966SD7z/SUrYqU7bq8c66X+7avlcCiCkjx3wrTNT9+sxlTT0y5brzwIgX7LEqt3BKWuhYiHtxHTej+KdcV7XP0p/6K0dxjOF5mmnvPjFIeljPMaO7HjOQenc90J9EwqQ0/NKVkrOOOkSq8SsE6NWmLl4ZB1L+TkG9D2eYghBDi5mzH5fzQGIcvlK+8rKHrfGLvNv7tz7+ffZtXr8ig4r1qwkHu2tTJVz55H5+6YxvRMlZyOt07zKne4UUreSuuTwKLCtM0nYDZTtBcM+W6gn2awfTXyNunV2xwoWk6AV8nTdFfJmCunnSdwiFvn6Jn/L9zcez/JlV8FdebWYKYUi4F+xwjuR9xYew/0TXyz7g0/l9JF18r49zBb7SQCD046XLXy5ApvU3e7pp0ecBcRdi/HUOLlm0OQgghbm48V+C1UxfKlluhAT9353b+6Uf2saG1Yda9I5Yrn2mwrqWO33zoDn5h3y1lCy7yls3Bc330JdNlGU/MnWyFqgIh3yZiwdvIWod4t+/BRJfp8eLzlEZ7qQ19gFjwDvxmO7oWAuXhUbqci5HC9sawnREUNonQ/YR86yv3DZWZrvmIB++gNf5b9Ix/Fccbfc+1Lpbby2juMdLFVwkY7YT8WwiaqzGNBIYWQSkHTxVxVf5yqdqLWE4Ptjd+NZfFU3k0TDxVKOPMNXQtSEPkU4zkfsiV362n8pe3dk3eYxr2byPs33ZNZ24hhBALbSxX4PVTF8s23qfv2sFvf/gumhJyouhamqbRnIjx6w/ejq5pfOeVQ2UJ6A5399MzmmJtc10ZZinmSgKLKmDqCWKBu0n5XiNvH5t0nacK5KyjFJ1uhrLfRtP8aJcXmhQe4KGUg8JFKQef0UDYt2lZBRYTB+hR6sIfRSmLvvRfYLuTk+s8lafk5Ck5vWStw+haAA0DNANQoDwUHkrZeFgoZbE45XwNQr6NRAO3ki29DUystDje2KRb6VqEiH87AXPVdIMIIcSKYDku337pID96Y/J7YWM8wmfv2ckHd20s+2PajkvvaJq+ZKos492+oYPf/tCdNNZEyjLeclUfC/PrD95O31ia5w6fmXduy2AqQ89IiqLlEPTL4W2lyE++CmiaTjx4F43Rz9CXHsF2B6+5hYfrpXG5+RKfrgWXZZlaTdMw9QQNkV/A0GvoT/8lhWu2Ek3w8FQeTy1sY6OZmkjirqE+/PGrgcWEyUFNyLeeiP8WSdoWQqxoSilGM3nODoxOujxfssrSCX46ecvm2KUBXG/+J5va6uL8q0/fT3MiJqVPZyARCfG7n3wfPSMpjvcMzqu5qOspzgyMkMzmaauLl2+SYlZkz0WV0PUgDdGfpy3+TwkY0kFyOhMH6THqIx9nXf2fTHSw1spVAULDZzQT9e8q03jv0rUgNcF78OnN173NRDWoHWV/bCGEEDeWK1oc6R4oy1j//OF9rGuuQ2KKmdE0aEnE+N1Pvo9gGUrwdvWNMJrJlWFmYq4ksKgSGhqGFqMp9nnWNfxX6sOfwNRruF5n7mvvPfGho2nGxBag2T0yTPnQZ/C4Mxldn2ZsA22OY2uahq75ifhvYU3dH7Kp6X/REPk5TL1+FnO+8vMyMPU6asMfYX3Df2NH6w9piv3KnOZ14zmDadRTF/nwtNf7jVYi/p3TVgYTQgixcJRS5IoWRy/OP7C4f/s69m1ejd80ZLViFjRNY8/6dj5++9Z5/9zO9I8yks6jytgnQ8yObIWqIpqmoeEnFridWGAPRaebdPEtsqUDFJ2zOG4Sx8uglIOu+zH0OH6jEb/RQdC3jrB/CxH/dnz6zJurNUR+jvrIJ6fOBZ35xp2GFmVN3R+yuu4/TjP+/Jr+aZqOTph44E7igb3YXpJs6RDZ0tsU7C5KTg+OO46nimiagaGH0LUoPqOJkLmWoG8dEf8tRPzb0DQfV4KShXkz0DD1OHXhDzOU+eakfhzA5RyMPUv2jUgphe142E75tuBpGoQCviX7MxFCLA2u5zGYypItzq8jdNjv4//4wO3URkPyujUHhq7zTz+yj6cPdjGeL855nFzJYiiVpeQ4BH2ytbgSJLCoQhNVgXRCvg2EfBtojv3ygj6WtkALVxMvrrNdQZnt+BMrNX6jibrwQ9SFH1qQxyoHT02tr61rQcL+LYR85U9IXCzpbJHvPfEO//t75SvV21Qf4+/+5NeIR1Z23XchxMKyHY+e0fF5j3P/jnV0NiQwdNkIMld10TCf2LuVr7/wzrzGGUxlyZdsCSwqRP4ChFgEjpdmLP/UlNWKgLmaaOA2dE1ifCGEWGy269KXnHuDVQDT0Hlo96YV3wBvvjQNPnXXDvzm/E5GDo1ny9aPRMyeBBZCLDClPGx3mPHCs9dcoxPyrSMaKH/CuBBCiJuzXZfe0fmVmd3c1siGlvp5HxCvdJqmsaq+hj3r2+c1zlAqS740v61tYu4ksBBigXmqRLr4OpY7OTnQ1GuJ+HfiN65fLUoIIcTCcVyPwfH5rVjsWttKNBQo04xWNsPQuXvzmnmNMZrJUbSmbj0Wi0MCCyEWkFIKxxsnmf/JlOtCvrXEg/sqMCshhBAw0ftgPonbuqaxo7OFaNBfxlmtXIauc/uGjnnlqhRKNo67/Pp5LRXLNrCwvQIFJ4njFaXsmKgYhUPOOkS2dGDS5boWJuzfTti/tUIzE0IIoZSa19ntmnCQVQ0J/KbkyZWDrmm018dpjM+9a3nJcXDK0OxQzM2y/UsYLhynv3CAqNlEzN9B2KgnZNbh12OXG9dIOTixsJRS2O4wg+mvT+mGHjRXkQjej67JWS4hhKgUTymK1twTfVtrY4T8PmmIV0aGrrOmqZaBOW5RK9kOrueVeVZippZlYKGUR0/+NU6lHsP28kTMJuoDm2gIbqY2sI6I2UTYbCBo1KJrkmwlyk8phacKjOYeJV2aXIZV10JEA7cSC+6t0OyEEELAxGt1wZ5HYFEXJ+hflodSFWPoGp2NCV4/fXFO9y/ZLq6sWFTMsvxrKLrjjJa6sL08oMg5g+ScQS7mXsKvR6kPbKI+sJG64CaaQjuI++ZXgUCIa7kqw1j+SfrT/w/w3hc4jaC5hrrIxzH0aKWmJ4QQ1WsRz/4rBdY8mns2xiMEfMvyUKpidE2nJRGb8/1t18OTFYuKWZZ/DaOl0+SdESYf0E2wvCz9hQP0Fw4QMuq4t/n3JLAQs+K4KVyVRdN86FoA7fKfkacsXC9FyeklU9rPUPabON7YpPsaeg2J0AeIBW6vxNSFEDNUsh3GcgXGMnnGcgWyRYuS7WA7E2dDdV3DZxgE/SbRoJ9EJERjPEJdLLzoTdI8TzGczjIwliGZLZAtlrAcF6UUPtMgYE7MsT4eoakmSk04iGks3Bw9T5HKF+hLphnJ5MkUSpRsB6Umej5Egn7qoiFaa+M01USnzMVY5H1FOhreNMcLMxEJBhb0Z7kSaRrzqrKlgXQ/r6BlG1iU3JvVpdYIGHHqAku347GojJx9lPH8z1DY6FoITZvo7umpIrY7QsHuomCdnJJXoREgHriDxuhn0DUpTShENZk4c+3Qm0xzcWiMC8NjXBwZZ2Asw1Aqy1iuQKFkU7InEkMNTSPgMwhfDiqaaqJ01NewvqWeze2NbFvVhM8w5nyAc6p3iCMXBifV4799QwcbWhuu9ktQSnF+MMnB830cuzRI9+AYA+MZxnMFiraDpxQB0yTk95GIBGmvq2F1Uy1bO5q4ZU0LbbVxfGXsveB5HkPpHEe6+zlycYCuvhF6R9Mks3kKJRvFRKBTEw7SkoixtrmO7Z3N3Lq2nXUtdRi6jqaxqCsAmgY+08Cx5naGO+A3MTQJLMpJ0zTCgbl3zTYNXQKLClp2gYWnHFLWRSw3d8Pb6ZpJS2g3EV/jIs1MLBclp4dk4Sks59KM76NhEglspzn26wR9qxdwdkKI2VBqotzoyZ4hjlwY4HjPIGf7R+lNpinZ168W5CiFU/LIlWyGUzm6+kYAiAT9bOto5t5ta/jw7k201sXnNK93zvfx18+8xeB49uplv/HBvbTXxfGbIUq2w4vHz/HUO6d5s+sS47nitOMULJuCZZPM5jk3mOTlk+dpScS4bX0HH9q9ids2tBMNzv9ER9FyONEzyJPvnObVk91cGk3hTbPP3bUcilaWwfEsh7r7ee7IGW5b38EHd27kwZ3r8RkGsUXsCaFpGkG/SWGOCdwB00DX5SC2nDQNAvOoshXwmRjyO6mYZRdYFJxRcvYwHjd+kTA0P6uj9y/SrMRKpmESDdxKS/w3iQfvqvR0hBDvkSmU+N6rR3j+6Fm6+kfIl+aeyAuQK1q8deYSx3sGuTg8zm89dMecg4trnR9MUrQdApbND14/yj+8cpjzg8lZjaEU9I9lePzASc4PJfnF3C4e2LGemkhwzvPKlyzeOH2Jb790kHfO91KyZ56zkM6X+NmRs5zuHWFgPMPn7tlJIhKa81xmy9B1YsEAY9nCnO4vh68LQIGr5p4jEQ748BlSmKdSll1gkbH7sbyblygLGbU0BqWHgFhYPr2BmtADNER/nlhgL5osmQtRVRzPo2c0xaHu/rKOmytaPPbWcUxD54sfvZua8NwP3K84P5ikULJ58dh5/va5t+fVMdr1FMcuDvJ1+wDRkJ97t66d0xakku1w4Gwvf/PsWxy+MDDnvlG9yRRff36i38+mtsXbSaBrGvF5/G4sx8WTXlllpeCGq4U3Ew368UneS8Usu8Ai745iezc+86Bh0Bjcht+Qqjxi9gJGOzH/reS1EI6XxPUKeKqEhkLXQhh6jIC5ipBvE7HA7UQDuwj61lR62kKIacSCAd5/y3qePniadKE06bqQ36StLk5HfYKWRIxENETY78M0dWzHJZUv0jua4siFAQbHs1MOMC3H5YkDp9i2qplP37l93nPtG8vw+DunePLAaQZT2avpxoausb6lno1tjbTVxggH/PhNg4JtM5rOc6Z/hFN9I6TzU7dLnRkY4QevHaWzoZaNbQ2zmo+nFBeGxvj7Fw5cN6hoqomybVUTqxtrqY2G0HWdomUzli1wdmCUk71DZPIlFDCeK/Ctl97h3q1r5/DTmRvT0GmIh+d8f9txp93yJeZOKTWrVa9r1URCUqmrgpbdT77gjOKomwQWmk5r+LZFmpFYbiL+HZg1dTjuGK7KoZSFUhPbJyYqRQUxjXr8RjN+o0VWKYSoYqahs7G1gTs3dfL0oS6CPpP1LfXsWtPKxrYG2uri1EXD1ESCVw/YDV3H9TzyJZuxbJ5LIyl+dvQsTx08Ta5oTRo/UyjxyBvHeGDHunlv8SnZDt9/9QjJbOHqQfzqxgSfvGM7O9e00JyIkYiECJgmpqFhOS7ZosXQeJajFwd4/MApDnf3TwqAlIK3z/Zy8Hwf7fVxwoGZN+1M5Qo8faiLt8/2TgkqQn6TOzd18tCuTWxqb6AhHiES8KNpGrbjkitZDKWynB9M8sSBU7x+6iKO5zGSzvP0wa55/ZxmwzR0mudR2nQiSV5Km5aTArLF0k1vdz310TBB/9yTv8X8LLvAouiO43jTJ7FdoWPQENyySDMSy41pJDCNRKWnIYQoA03TqI2G+PRdOzBNnT3rOtjU1kBbbZzaaOi6VZNMQyfgM6mNhljbXMf6lnri4QD/8PLhSYnAnlJcGB7j2MVB7tm6Zt7zHU6/W5hkS3sj/+Jj97BzbRvxaRKeTcMgHPDTVBNlbXMdrXVx/u5nb7P/TM+k2xUsm1dPXeCOjatY3TSzwMJ2XU71DvPj/Sem9IEI+Ew+sHMjv3L/raxvqZ9y9thvGkSCE/Pa3N7IprZGaqMH+OnbJ3A9Ra40OThbSD7DoH0eOTCpfBHbkcCinDzPYzh14wI8N9JUE51XVSkxP8susLC9PK66cfKdqQeld8USVLIcBkbSjKXyM7q9aeis62wgHJz5GTghxMrjNw32rGujsyFBY02E0CzPdmqaRkdDDb9y3x6OXRjkwLneSasCRcvm0Pm+sgQWV7TX1fC7n7yPvRs70GdQWjMS9HPHxlUMp3L0JdP0JdOTrj9yoZ9kNs/qptoZPX46X+L5o+fov2YcgNvWt/PL9+1mc3vjTXt6+AyDze2N/PaH72QoleGN0zOvtlcOfp/B2ua6Od8/mcljOXPPBxBTeZ6if2zq82qm2uriROV9v2KWXWDhehZK3XhvXsxsxdSlj8BS0z+c5puPvcXxMwMzun0k7Off/ZMPsaajfoFnJoRYyibq5vvpbJzfwUhzIspHb9vCsUuDk1YtSo7L6f6R+U7zKg341Qdu5dZ1beiaNuOa/SG/j70bOnjz9MUpgcVoJs/AeBbLca/2ybgepRRj2TwvHj83pa1cS22MB3asZ1PbzYOK91rVkOA3PngHB872YruLtwJg6jrNiSjxUGBKjs1MjGTylObRuVtM5SpF/9jcChOE/D6aE1GCPlmxqJTlF1hQwuPGf+RhXyNSJG7pGUlmefPQBYaSM3vBiUUC86osIYQQs7Vvy2p8pjEpsHA9RTIzs5XWmdixuoX7d6zHb86+AV9bXZz1rfUEjhqTDog9T9E7mqJo2TcNLEq2w9GLA9Me/G1tb+LuLatvOsZ0dq5pZfe6Nt7q6rn5jctE0zSiwQAbWus5cK5v1vcfGMtQtOR9plyUUhQtm0sj43O6f3t9DXWxsPQWqaDll1WqbvZk0vDrUg1qqSmVbHoHxxl5T7OoGZFiHUKIRdSciE7ZhqHURN6A55XnTPz7d6ynNhqaU3dhn2nQnIhRG51aCSmdL2K7Nz/7nivZvH2md0o1pEjQz8a2Blpr55az4DcN3r9jw5zuOx/hgJ/tnS1zuu94rsDgeAZbVi3KwlOKM/2jc+4ns665jrppntti8Sy7wELX/ejc+EyJBBZLTypb5MzFYSnrJ4SoaoauEw8FpqyJu54qy5YZ09C5a/PqeXUmjgX9RIJTt4rkLQvXvflrbMl2ODMwdWtXU02UDa0NmHPsIaBrGns3dszpvvMRCfrZtaZ1TvsYPKU4N5icc+duMZnnKQ53z37l6IrN7Y00xiNlnJGYrWUXWJhaAF272QuuLJEtNalMga7uoUpPQwghbspvGlPfZpQqy4mRK9Wq5rBYcZXfZ+KfJjAplhzcm6yqKKUo2g7dQ2NTrquPhlnVUDP3iQHNidi8uoDPhc/Q6WysnXHi+rVO9Q6Tm2fHdjHB9TzenONWuPpYmLXNtVKwpcKWX2Chh24aWLhq7vWRxeJTSjGeLnDmwnClpyKEEDe3gOeu1jTVzim34r10TZu2kpSHuunuUddT9CfT025ViYYCNMzjbLGmaZi6Tkfd/IKTuTxubTTE7Rvmtlpy4GwPqVxhzl3HxQSlFL3JNIe6++d0/22rmmmvr5lRlTSxcJZd8nbEbMCnh7C86+3FVze4TlSjfMHiXM8I+eIczgjJ64sQYhauHBx6SuEpRaZQontojO6hMQbG0oxk8qRzRXJFi4JtY9kuJcehZLuUbIeS7ZAplFioY8yW2hi+OW41KgfX8xjNTN9jIBbyUxudXxNAXddoro1x7NLgvMaZrbpoiHu3ruGRN4/POl8imS1w5MIAnY210j9hHpSCJw+cvumq2XQ0DW5dO1EyWlTWsgssomYzPj0KXP/sdtZZ3BcsMT/pbHHGJWaFEGIu1OWtSnnLpntojBeOnuO1Uxc4OzBK0bavFoKo9DnpkN83r9WK+fKUIjvNSR5T1wn5fZizKDE7HQ2Ihxe/HLyh66xpqmPvhg5ePXlh1vd//uhZ3rdtLSG/WdHfz1JWsG1+/PbxOd13fUs9WzqaZt2DRpTf8gssfC03Tc7O2oN4ykXXZl8OTywupRTpbJFT5+YYDFb6KEAIUfU8b2Jl4lB3H99++RBvnr64qL0UZiMU8FW0lKZSivw0nbENQ8dvzv+gWtM0Iv7F3yOvaRottTE+uGsjb3Zdwpnl7//1Uxc50z9CQzyMacixxWwppXjkjWP0z7Cc/HvpmsadGzvZ3N4oQV0VWHaBRdy3iojZiIaBuk4/C8tNk7X7iPtXLfLsxGy5rsdQMsOlgfFKT0UIsQy5nselkXG++eJBfvjGUSz7+ttgdE3DZxqYuo6uaxj6RHO6iSZ1oDHx/9FMfk7bOWbCZxhoFdzj6SmmrYBk6Bo+szxbtIwKbfUK+X3c0tnCrWvbeOvM7BKIHc/jB68fY0tHE/WxsBzgztJ4vsi3Xzo4qWP9THXU17Bnffu88ntE+Sy7wMLQ/TQEtzBQeIeCO7VqBYDCY6h4TAKLJSBXsDh5bnDuSXHy2i6EuA7X8+geHOO///hlXjx2btrbBH0m0VCASMBPQzxMZ0NionJROEhNJEg44CfoNwn6TAI+k6DPx5f/1yNzbvBV7TRAv84La7kCnkom365qSPCRPZs5dmlw1r0UXjp+jkPdW7hv+1p8smoxY5bt8I0XDkzpBj8TpqGzb8tqdq5uXYCZiblYdoEFQFPoFkKZp68bWHjKoSf3ButjH0LTll1hrGUlV7Dml18hW6GEENNQaqIb9v9+5s1pg4qAz6C1Ns7utW3cs3UNu9a00hiPoM8gh6CSydULTdMgFJh66OB6CsspTwfqhVrtmYlQwMeede3cs2UNzx4+M6sz6Jbj8v976g02ttazqiEhqxYz4HmKN89c4ruvHJ7T9sN1zXXcs3UNTQnpT1YtlmVg0RDYTH1gEynr4rSlZRUeg4XD5N0RImZTBWYoZkIpRSpT4PR8+lfI67oQYhq26/HaqYv89MCpKdeFAz7u2NjJ5+/bza3r2if6UghgYjUhHJiaA+G6HiXbRSk1rwNqpRTZQmVLwnc21vLwbVs40TNEz2hqVvc90TPEd14+xG8+dCeJSFCCixtQSnFucJS/ePx10vnZ/86jQT8P7FjPnnXtCzA7MVfL8rSKoftZG3uQqK/lurcpuSnOpZ+RutNVzLJdLvWPMZbKz30Q+fUKIa5xJQH5e68envIe4DMM9m5YxRcf3sedmzrnFFTMNvF3KdE0jUhwatUmx/MoWPa8k94VkK5wYGEaOrvXtvGx27cSnUOzte+8fIjH3z5J0S7PCs5ypBR0D43xpz95hVO9w7POrTB1nT3r23nglvXEQotfRUxc37IMLABaQrtpCe3C1Kavqe2oEucyz5B1pIxptSoUbY52za1RjhBCXI8CBsYyHLkw9fW/tTbGw3s2s6m9cU5jO65HbpqqScuFoes01USm7fydLZYYyxbmNb5SipH09H0yFlN9LMwHd23g7i1r8M0yuLRdj7944jWeO3xm2gpaK53nKc4NjPJXT77O66cuYruz6xsC0NmY4KN7trBljn+nYuEs28DC1ANsrvkkdYENaEz3oqBIWZc4lXoUxysu+vzEjSkF+aLF0dN9lZ6KEGKZ8TzFiZ6hKWdJNaC9voa9G+de2COZzS/rFQtD12iqiRIPBadcl86XGE7NvQGtUgrb9bg0PD6PGZbP+pZ6fv6uHWxf1TzrEr/pQomvPvoSP9l/Yt7B1nJiOQ4Hz/fx54+/yvNHz85pVac+Fubh27Zw77a1GPPsmyLKb1n/RhqCm9lS8ymivmam22zvqALn0k/Tk3sdT80+YhYLRymP5HiO7t7RSk9FCLHMKKUYGJtaL99nGjTVRKiPzb1s5ame4WUdWGiaRtBvsrqxdsp1o5kcF+dZDWtoPMtYrjoOxA1d59Z1bfzivbtY31w/65S94XSOP/3Jq3zn5YN09Y1UNCm90pSC4VSW5w6f5U9/+govHD9PwZp9UBEN+nn/Lev52G1bZAtUlVqWydvv0lgTez95Z4Sj49+hOE2VqJwzzJGxb+HXY7SGb5UqUVXCsl1OdQ9RLM1zj6rkzYkZUkrheh6W42LbLrbjYTkOtutd/r87cZ0z9esrH8lMnplsFc4VLN46eQnL8fCZBn5Tx2ca0374TQOfYeAzdXy+K19PfFzpoyBmRwGlaSoYmYZOJOifdpvPjMZVitdOXZjT1o6lJOgz2dzewOELk7eqDqdydPUNY+3aOKfcFE8p3uy6VFWpcUG/j/dtW0uuaPGNFw7QPTQ2q/ml8kX++tn9dPWN8PBtW9izrp26WHjB5luN8iWbU73DvHD0LE8f6qIvmZ5Tv4qQ38fdW9bwmbt30l5fswAzFeWwzAOLy1uiEp/CVkVOjv+Akje5TrLCZbR0mkPJv8XDoTW8B0OTlvCVViw5HD7ZO/+BqukdSlQN1/U43j3AhcGxiSDBnggULNulZDuUbAfr8ueS7VKyrvzfnXyd5WA5797HcWZ2RjKVK/LT107wzP7T+H0mAZ9x+fPkrydfd+1nE7/vcuBhmgT9Jp3NtWxfe/2iFWKCxsRByrUmgsu5v2j0jKZ4o+vSsg8swgE/t23o4IdvHJu0OpO3bE71jnBhKMnGttnvfbccl+cOnynnVMsiFgrw0O6NuJ7Ht146yIVZBhcl2+G5o2c53T/Cg7dsYO+GDrZ3tlAbnT4HdLnIFkuc7R/lnfN9vHT8PMcuDk7bXHEmAj6TvRs6+Px9u9nSLtU8q9myDywAAkaM7bWfRddMTox/j6I7Pul6T9kMFo/gjv4NBTdJR/guQubUZV6xOJRSFEoWxyRxWywQx/V4+q3TPPXWqasBg+24czqLNleeUhQth+IctgNcoWvaRHDhM4mF/Dy0d7MEFjOgaVAXnXrW2Lq86lS0HYK+2b095koW33v1CL2j4zNatVrK/KbB5rZG1jTVcqZ/8nbVk71DvHyim46GxLTB2428deYSxy4NlnOqZZOIhPjIns0Yus53Xj7I2YHkrF4vPE9xcXicb7z4Dq+dusAdG1exa00rWzqaaK2NYS6ThnqO6zGayXG6b4SjFwY4cK6XEz1DZOZR6SvoM9m7cRW/9v7b2L22bc4rimJxrIjAAiBo1LA98Rn8epjjY98j40xOCvaUzXDxOMXRccZKZ+mM3kt9YDM+fXmfUahGnqfoHUwxODL7LpxCzIRCMZYtMJKqfPWZ+XhvcFKybMazUohiJnRNZ31L3ZTLXU/Rm0xzuneYnWtm3sm3ULL5yVsnePztk3PaN77UaJpGXSzM/dvXTQkskpk8zx4+w4bWBvZt7pzxAfP5wSR/+9zbcz6jvRiuBBfhoI/vvHSI45cGZ11e13ZcTvUOc34wyUvHz7OlvZEtHU1samtkbXMdjfHIrKtQVZrtuoym83QPJTnVN0JX3zBn+ke4MDw+6+7l1wr6Te7ZsoZffWAPu9a2ydbPJWDFBBYAfiPK5ppPEjQSnBj/IUPFI5OuV3ik7R5OpR5luHicltBumkM7qQ9sImjUyhN6kdiOy5FTffPakiCEENejabCqMUFrbYz+a5K4L42M89O3T9JaG6ex5uZJ3H3JNI8fOMmP3jjGcBWUSV0s0WCAe7eu5cXj5+nqG7l6uQJO9g7z9y8cwPU89m5YReQGvSBcz+Nwdz/feukgB89XfxXAWCjAg7dsIBEJ8d1XDvPG6YtzOni2HJfuoTEuDI3x6qkLdNQn6KiPs6ohwZqmOjoaamiri1MfDVdVoKGUwnJcRtI5+scyXBwZ4+LwOH3JNH3JNJdGxhnPlecERyTg50O3buJz9+xka0eTHIMtESsqsAAwtABrYw8SNhs5m36S89nnsL3JDdhsL89g4TDJ0ll6cq9T4++kxr+ahH81MV8bYbORoBFH10wkO7j8LNvl4IlL5RlMfj1CiGtomkY0EOCDuzby9ecPTLouUyjxzOEuAB7avZHN7Y1Er2kIly/Z9IymOHS+j7fOXOKtMz2MZfIowGforGpIcH4ouay3RJmGzsa2Bj51xzb+9CevUnpP2VDbcTlwtpdUrsihzf3sWd/OmqZaaqMhTEOnZDmM54p0D49x7OIAb3X1cORCP47roWsanY0JuoemFlupFiG/j7s2dVIfDdPZmOCnb59keI6rn4qJMr3H84McvzRIyG9SH4vQEI9QFw3REI/QkohN/D8Wpj4Wpi4WJh4KEPL7Fuxg23Zd0vkSqVyR8XyB8VyBkXSewfEMw6kc47kCY7mJVd/RbI6SXd68ovpYmM/ds5OHb9sybQUyUb1WXGChaRoaJi2hXUTMJmr8qzk89nVK7tRtN7aXY7R0mtFSF349StisI2Ak8OtR/HoEnx7B1IMYmu86vTIWX8isY2vi5yo9jTlTSpHNlTh5rkz7bJfxG7sQYu4CPoOH92zhucNn6E1Ofv0fTuV47K3jHL04QEd9DQ3xCOGAH8/zyJdsktkCI+ksl0ZTjKRyOJfLiOqaxi/cvZN1zXX8yY9ewHaWdxJ3JOjnvm3rOHZxkCcOnJr0cms5Lid6hugZTfHKyW7qY2HCAT+GrmE7LgXLZjSTp38sQ7ZQQjFxHmh7ZzO/ct+t/Lu/f2JKV/RqYug6WzqaqI2G2NDSwF88/hp9Y/PfvluwHHpGU/SMpoCJAC4a9BMNBogE/RMfAT9Bn0nQ7yMa9BMLBQgHfJcLOUxUjvObBuY1PR4U4CoPz1N43kQVPNdTWI5DwXIoWPa7H6UrXzsUShZ5yyZbtMjkSwveADIRDvK7n7yPe7asnraCllLguBPPoVzJIl96d75Fe6KghuN6LPXIfvvqFjqWYPWrZR1YeMrD9nKUvDQlZ5yim6bojlPyUhTdiY+s3Y/j3SypSGF5GSwrA1y4eqmu+dAx0TQdrUpagtQG1i3pwML1FKe7h8jk5p7oJYQQN6PrE3kW/+iDe/kfj708Jbk0W7Q4cmGAYxcHCVwu86vgaqnhaxN3DV3nF/bt4Ffuu5Vo0M+fP/4q48s8sNA1jba6OL/0vt3kShYvHT8/5VguUyhxqnd4RuOtbann//zEvaxtmsg1GJpHs72F5rgeY9k8A+MZPM9bsJUDx/UYzxWn3V6kMZFI7/eZ+IyJ8tOGrmPoGrquo0+Zk0Kpidws9Z6vXdfDcT1s1736uZJbkQN+Hx31NZzuHyZztkSmMPkjW5wIJibKgU+UBrddF9v1Jr4Xz0MptdTjCr788XsksKgWp1M/ZrBwmKKbwvGKuKqEqyxcVcLxrKtfT3y2metpbU/ZeNhVdVbc9pb2Hl/X9XjneJm2QQkhxA0EfCYP7dpI0bL5+s8OMDjNgayn1MRZW66flJ2IBPnFe3fxib3baKuLo2sam9ubeOP0xYWcflXwmQZbO5r4zQ/eQSwY4NnDZ+bUTfnWdW38s4/sY8+6dnJFi/UtdVUTWBQsm6FUlp6RFJdGUvSOjtObTDOeK5ArWuRKFsPpxZ/rRD8Wl9IyC2DHsnn+3z/4Gbb7br+gq58vBxIrodngfCppVdKyDCz68vu5kH1xXkGDqAzH9TgggYVYYH7T4B999A4+ee/2Sk+lbHRNoz4+947RC6U2HuafffoefumDt970trqmsb599v0P5krTNOLhIJ/cu422uhp++PpR3uq6NOMD44DP5I4NHXzyjm3ctmEVtZEQuj5xlnjvxlW8efriingHCvhMtq1q5rc/fBfbVjXz4/0nON03PKOz3s2JKJ/Yu42Hdm9kQ0sDuqZN5G+0NvLaqcUNzDxPkSmW6BkZ59JIiksj41waGWdwPEu6UCRfsi9/WBQsWwqMLJAr2+jE0rQsAwvHm1iNEEuLUoqR0SwX+5KVnopY5nRdZ11bPeva6is9lWUv4DPZ0NFQ6Wlcl345uLh36xo2tjZwbmCU/Wd7ONk7RM9IinShRNFy0DWNcMBHXSxMR30Nm9oa2L22jbXNdTTVRPGbxqTtMD9/13bu3Ljq6v8DvokmhjP1wZ0b2bWmbUqeRkttbFbjTGfnmlb+4PMfonBNNaNEZCJZeC58psGqxgSfunM7d2xaxYlLQ7x9tpeuvmH6xzJkihNnX4M+k8aaCOua67l1XRu717bRUZ+gJhK8unUn6DP5wgO38tDujZPGb66JzvE7vrnuoTH+6yMvMJLOXd6v71C0Jz5bjrPkt9UIsViWZWCxoi3hFz+lFIdO92LPsHvxjEhVKCHETWiaRsBnsqqhhtbaGLvWtlGwLEq2i+t5V/MpDE3HNHT8PoOQ30ck6MfU9Wn319fHItTH5r6C1BCPzPkg/2ZioQCxUODmN5wlXdOIhQJEgw2sakhwz9Y1FCwby3Gvbl3RNQ2fYRD0m0SCfsIB/5RcAF3XaU7EaE7Eyj7H60nni7x64sLVRHwhxNxIYLHcLOEDaU/B/qMXbn7D2VjCgZYQYnFpmobPNKiNhqhFmqPOlaZphPy+WXferiSFkqBCiDKojlJGonyW8IG063m8c6ynvIMu4UBLCCGEEGIpkRWL5WYJH0ifuzjCWDp/8xvOxhIOtMTi8DxFJlekuzdJ7+A4A8NphkYzJFN5Mrki2VyJQsmeKMXoeGiAz2cQ8Jn4fQZ+v0k46KeuJkxDbZSG+iiNtVFaGuKsXVVP+AZdh0V1clyP5HiOi31J+oZSDI5mGU5mGE8VyOSLZPMlCkUb27n8nNDA75/oKxAMmAT8JsGAj9p4mNamGlobYzQ3xGltrKGxLkpgnjkSQghRreTVTSwKpRQKUJ5CKYWnFJ4Hw8kM53pGOHdxhDcOdeOVscqGUhPVJYrXJCguNaY5UZ98oeqkrwQTNc0nmkI5rsf5nlEOn+rl8Kk+us4PMTyWwfPevZ3iSm+lm9dC1y7/o038c7kJ58Rn09TpaE6wYXUjm9Y2sW1DK+s7G/CZBrquoWvye62EK79jz5uo4Z/JFTneNcDxs/2cODvI+Z5R0tkCSs3+OaFd/WfiOaFdeU5oE18H/CZrO+rZvrGVHRvb2LS2mYbayNXeA1duL4QQS9GyDCxMPYhfX7jqEdXMp0/tUrnYlFK4nsJzvaudPYuWzcBQmrOXJoKIMxeHOXdphHS2tGDdVbP5Er/9H761IGMvpn/++fv41AdvIRYJVnoqi6och1aep7Adl1LJ4cjpPl49eI7X3j7HwGimDKNPuHysiZr4h/cuk9mOS9eFYbouDPP4i8fRdY3G2ii37+jkjl1r2LGxlURNGP/lQEMOKBeWUgrLdrFsh56BcV55+yxvHbnIqfNDWHPovTDtY1z9Z/rnhGW7HD7Vx+FTfcDbV4PPO3et4d7b1rO+s4FgwHc1+JTnhBBiKVmWgcWdjf+C2xr+SaWnURG6tni/0iudLZ3LW0SufM7kS/QMjHH+0ijnekY5d2mEnv4x8sWlvXJQOStvP5emTZTnnCvH9SgWbXqHxnnhzTM88+pJ+gZTU7olLzbPUwyOZvjJC8f4yQvHqE9EuPe29Xxg32bWr24gEvTj8xlyMFlmjuNSKNkkx3M8/+YZfvbGaU6fr446+Y7j0d2bpLs3yfeeeIfOtjr27V7LPbetY3V7PbFwANOcvvKUEEJUm2UZWITMukpPYdmZWIXwsGwX23avnvUbTxe42JfkfM/o5TfHUQZHM9j28uoEKhaXz5zIXZgtx/XI5kt0dQ/x1MsnePGtM2Ry1du9dHQ8xyPPHuaJl46zbUMLH71/O3u2r6K+JiIBRhmULIdMrsjp8xPPh5ffPke+WL09jlxPcb5nlPM9o3zvyYPcuq2Djz2wg+0bWqitCRPwm/KcEEJUtWUZWIj5Uery9hHLmfQxnMzQ3TvGxd4k3X1JLvUnGR3PSeMgUVaaxqwTnj2lyOZKnLs0whMvHuf5N7tIZ4sLNMPyK1kO7xzv4ejpfnZvbeeTD+7kls1t1NaE8ZlGpae35Fw56XHoZC8/feEY7xy/hLXETnZYtsMbh7rZf+QiOza18vB929i1tYOWhjh+CTqFEFVKAgsxRe9gitPdQ1zonQgeLvSNcal/jGy+es/8iuVDQyMcmnn9+5Ll0D+c4rnXTvPj548yMJxewNktLNtxeevIRY6dGeCePev4+Pt3sG19C+GQXw4kZ8B1PZKpPMfP9PPjnx3l7WOXlnzxBtfzOHSyl8Mne7llczu/8OHd3LK5jcbaqORgCCGqjgQWYorvP/kOjz53hILkRIgKmFixuHlXYKUU6VyRQyd6+OHTh5fkWenryRcsnn7lJF3dQ/z8h3Zzz23raKyLYRrSemg6SikyV1asXjrOC292kcosnRWrmVDA4VO9nDo/yAf2beaj929nw+pGYpGABBdCiKohgYWYQnY2iUrSNI1w6MZboVzPY2g0y89eP8Wjzx7hYv/YIs1ucXX3JvnLb7/M+UujfPzBHWzobMTnk61R7+U4LgMjGV5++ww//tlRunuSFU/SX0gly+GnLxzjwLGLfPqhXTx41ybamxMSXAghqoIEFkKIqjIRWFx/K5TjuFzoG+ORZw/z1MsnllQuxVzkCxY/fOYQQ8kMv/Sx27hlcxv+eVTMWk5yBYuT5wb5yfNHeeXts1WdqF9uAyMZ/urbL9PdM8rPf/hWtqxtwpR8HCFEhcm7kxCiqtwoeftKX4jvPn6AF97solgqT++BpeCVAxMVjT7/idvZu2M1Pp/JSj1JrZRiLJXntYPnefTZIxw701/W5ppLhVLw5Msn6BlM8csfu43bb+lccf1uhBDVRQILIURVud5WKNtxOXV+iG//eD8v7j+D43gVmF1lvXO8h3zBQtd09t7SuSLPUHueon84xVMvn+DxF4/TMzBe6SlVlFJw7HQff5rM8NmH9/Che7dSn4hUelpLTl00zKfv3F7paQhx1eqm2kpPYU4ksBBCVJXpViwc1+PsxZGJoOKtMzjuygsqrjh1foi//eHrxKIBtq1vQddXTkK343pc7EvyyDOHeebVU4yl85WeUlVQTGyN+rsfvkk2V+KTH9hJc0Os0tNaUjrqa/gPn/tApachxFW6tjRf2yWwEEJUlYlys+8GFp6n6B0Y53tPvMNL+8+u6KDiisOn+vi7H77Bl75wP6taa1dE4u5EcDnMdx9/hxfe7CJXqN5Gd5WSyhb4/lMHsRyXn3toF21NNZWe0pKhaRqmsfJWAIUot6UZDgkhlq2JFYuJ5G2lFKPjOX707GF+9sZpbGd5lJMth1cOnONbP357yfdpmAnHcTlzYZhvPraf5147JUHFDaSzRR577gj/8NO3l221NCFE9ZLAQghRVd6bY5EvWLzwZhdPvnRc+qpcQyl46pUTPP9mV6WnsqBc1+N8zyjfePQtXnzrDEVr5STsz1U6W+SJl07ww6cOMjiaqfR0hBAriGyFEkJUFU3TCAf92LbLsa5+vv/kQcbThUV5bF3XCAV8+P0mPtPAbxoYho6nFI7jYjsu+aJNsWhXRa+EQtHmWz9+m63rW1nTXlfp6ZSd5yl6Bsf55mP7eWn/WSy7skGFrmkEgz6CAR8+08Bn6piGjuspHNfFcTws2yWbL+FWeMteOlvkmVdOEYsE+cxHdhOPhio6HyHEyiCBhZiiNhaivTmx6FsssvlSWQ8gNQ0a62L4l3hDsVg0uKISdDUNwiE/I+NZ/uGJd7jQl1yQxwmHfKxqraOjOUF9IkJtTZhEPEQ46Me8fMBoGDq6rqEUeK6H404cOOYLFulskeFkhr7hNH2D4/QOpiqyVev8pRG+9eO3+Ne/8cFlVSXqyja4b//4bV5868yiBhW6rlETDdHaFKe1qYbmuhiJeIhYJEg45Md3OeA0DA1Dnwg8Pde7GmAUSw7pbJFUpsBwMkvfUIq+wRQj49lFLYubTOX46QvHiMeCfPyBHQQD1+8PI4QQ5SCBhZji/XdtYsemNtxFrgv/8v4zfO/Jg2UbLxjw8WufvoOOlqVZsu2KVa0JAv6V86fqeYqLfUm6e0d5++jFso7dUBth15Z2Nq9tpr0lQV1NmEQsTDjkJxzyE/SbGMbNgzjX9ShZDtl8iXS2yHimwOBImtPnhzja1cfp80OL9vfjeopX3j7HB/f1sHfn6kV5zMWQK1j85IWjPPvaKQqLcJLDZxp0tCTYsq6ZTWuaaGtOUBMLUhMNEY0ECAV9BHwze34oBZbtUCzZZHIl0tkC4+kCg6MZTp0f5MTZAS70ji14sDRRLSrNo88eoSYa4sG7Ns1o/kKsZK7rYb/nb1PTNMzLJxPEza2coxUxY51tdXS2Lf62ikt9STRt4k25HExDZ/uGVjavay7PgGJRFEs2f/ejN0hlCpTKsJ/eZ+rs3NzB3p2dbF7bTGtjnPpEhHDIP+dqSoahXw1GmuonynrajssdO1czlMxypnuIl/af443D3YuyJSaVLfKDpw+xa2vHkl+hg4mD8tcPdvPDpw6RzS9sN+1YJMBt2zu5Y9dq1nU0UF87sXoVCvjm/PzQNAj4TQJ+k5pYCEiglMK2XfbtXstwMsv5nlFeO3iegyd6SGUWbquf5ym6e0b5yfNHaW6IsXNz+4I9lhDLwcmTfXzj71+9+v/mlhoeemgH27Yt3N/O8HCaV17p4uzZIQA04MEHt3HLzlVLLqCRwEIsb8u/Cuey43qKc5dG5z2Oaejs2trBh+7dwtZ1LTQ3xIiGAwtWmtVnGjTWxWisi7F+VQO7tnRw3+n1PPLMYU6cHVyQx7zCdT2OdfXx1pEL3LNn3YI+1kLzvImeJV/7wesMJ7ML9jjhoJ8H923i/XdupKOlloa6KKEF3CqkaRp+v0lLY5zmhhgb1zRy67YOzl4c4WdvnOa1d84vWBDluB5HTvfx9CsnaWuqoaE2uiCPI8RyMDaW4403zl79/9q1jdx++9oFfUzLcjh1qp/nf3bi6mX1DVHWrW8kHg8v6GOXmwQWYnmrfH6tqIANnQ18+qFd7N7aQWtTDUG/uai9HoIBH6vb62hujLNpTTNPvnyCHz19qCwrMNczninw458d5a7dazCWaE6OUoqxVIG/+NZLnO+Zf3B5PXffupZPP7SLjasbaaiNLvoZQU3TCAZ8rGqtpbkhzqa1Tdxxy2oee+4Ix870L8g2ukLR5uX9Z1nXUc/HH7wF3zLKxxFiqQsG/QQCJtZ73iN6e8ZIp4sSWAghRKUE/SYP7tvMJx68hY2rGwkF576dZb40baLC1KY1TTTURljdVsfffO81hscW5iy843h0dQ9x+vwQW9e3LMhjLDTH9fj2T/Zz8EQPagGqbkVCfn7103fwwbs301gXq4qDa7/PoLUxTu2+zazrbOCHTx3iZ2+cXpBeHcPJLE+/eorV7fXs2b6q7OMLIeYmFPITCQcmXTYykiGbLVZoRnMngYVY3mQr1IrRWBvllz5+Gw/etYn62ihmlexL1XWN+kSEh+7eTDTk58+/+RIDI+kFeaxUtsDL+88uycBCKcWJs4M88uwRHKf8eSnrVjXwz3/lfdyyqW1Bt8TNhaZphIITQehvfu5uWhrj/OiZw4yUOQj1lOLYmX5eeLOLzrZa2RIlRJUIBExCl/s3XZEcy5HPL71moNXxzivEQpGtUCvCqtYEv/WL9/CJB2+hqT5WNUHFFVea/t1z23q++IX7FuyALl+weevIhQVPeF4IjuvxV99+aUHmvnNLO/+vf/YR9t6yuuqCivcyDJ3Guiif++gePvfRPTTWlf95Ytsur75zjkMne8tWKEMIMT+6ruEPmJjmu+9dmUyB0iKX/S8HWbGYJdezyDoDpK0+8s4weXeYgjOOowq4XglXlQANQwtg6H4MLUDIqCVs1hM2G4n6Woj72jH1YKW/lZWhOo8fRBltWN3I//Hzd3HPnnX4fUbVHjRO7Ks3uXPXGn795+7gz/7+xbLnXCilGE5mOXDsIvft3VjWsRfaj545zLGu/rKPu+/WtXzxC/exuq0OXdOq9vlxhaZpREJ+fuHDu1FK8Q8/PcDoeK6sj9E3lOb1g91sXddCW3NNWccWQsyepmn4fAY+n4njTKxSFPIWlrX4vZHmSwKLaby7t1dhe3lGS130599mqHiMcesClptF4QIKhQJ1+fPl+0zQLv+rTfyrXf6MjqmHqPG10xDcQkt4D43BbQSNxDW3FWUhZ+SWtVUttfzKJ/byvtvXYxp61f/tXDlovG/vBnoHU3z7J2+X/TGy+RKHT/Xxvts3VP3P44rewXH+/tE3sezyvonu3trBP/+V+1jTVo+msWR+HpqmEfSbfObDuxkZy/LT54+VNedCKcVr75xjz/ZVtDTG0fWl8XMRYjkz9Immm1fYtovnLXy58nKTwOI9lFIoXCwvz0jxJOcyT9OXf5uCM8rVIGKWR6pqyhfguAWKbpLB4lGOj38fnx6hMbiVtbEP0Ba+nZBRi66ZoGmXgw0hxLWa6qJ87qO38v67Ni6JoOIKTdNoqI3y4L5NHO3q4+jp8p6lzxctTp4dxLZd/EugsaLnKf7m+68zNp4v67ib1jTxL75wP2vbl1ZQccWVylG//uk7GR7N8sqBc2Xt7J5M5Xl5/xm2rG1iTUf9kvv5CLGcKKVwXW9q36MleHK0+t91FoFSCk/Z5N1RLuVepSv1Y5KlM+9ZhViwR0ahsLwMvfk36c2/SdhoYE3sftbHP0LCvxpTC6Jp1bVfXIhKi4YDfOz9O/jY/Tvw+5bey5imaWxa3cTHH9jB2YsjFIrl20erFCTTec5cHGHbhupP4u66MMSr75zDKWMjwbqaML/1i3ezcU3jkj4br2kadYkIv/ix2+gZHOfMheGyjr//6EXet3cDne11GBJYCFExruuRzRUpvue9IBAwMaugct1sregj1omAwiHnDNGV/inP9P0erw99ldFS1yIEFdPLuyMcH/8+z/T+G/YP/xWjpS4cr7ggpRdXBHmvXHYMQ+eOnav5yPu2EQwuXEOzheb3m2zb0Mpt2zvLPnY2V+TkuYGyj1tujuvyvSfeIVfGyid+n8FnH97Djo1tS/JNeTq7trRz/94NxKPlzc3L5EocOtnL8OjCNSIUQtzc0FCa3p6xSQUVQiE/Pv/Sew1bsYGFUgrbyzFQOMSrg3/Cq0P/hbHS2ZvfcZEU3DFOpL7P8/3/F13pn5JzBvHU0kviqTiJx5YVDVjXUc+H3reVVa21lZ7OvHW21XLnrjVl7/icK1icL0P38oXW1T3Mm4cvlG2LjwbctXst9+3dQE0sVJYxq8WnP7iTtR31ZV+BOXDsEt19SbwFaMonhLg5y3I4eqSHo0d7Jl1eVxclfE1vi6VgRQYWSilyzjAnU4/yfP//RU/+9UpP6brSdg+vD/1/eWv4LxkpnsT1LFm9ECtWJBJg35513LVrbaWnUhZ+n8nGNY1sXtdc1nFLJYf+4XRZtxeVm+24PPrcEdJlbABVm4jw0D1b6GhJlG3MalFfG+X+OzYSi5R31eJS/xgnzw6QKyy9EsVCLFVKKSzLIZnM8sYbZ/nJTw/S3z8+6TbtHbUkEkvvBMnS25w8T0opxq0LHBv7Dl3pn6Co3jfeKxQO57PPkHX62FX3q7SGb8MkJMl2YkXRNI2Nq5t44I6N+H1Lb3n4ejpaatmyrpnDJ3vxynTSwFOKdLbA6FiW5oZ4WcYst/M9o7x95GLZSu7qusZ9t29g24aWquiovRAevGsTT79ygnS2vNtj3zpygX23rmXzWimDLpa3sbEc/f3jN/z7uXQxOen/xZLNpUtJjh3ruc49Zs+2XUZGshw5cok33zjL0NDkpqmmqbN+XRO1S7CJ5YoKLBSKMessbw7/OX35Nys9nVkbLh7n9aH/zp6G32J19D4JLsSKUhMNcvstnWxa01TpqZRVbTzEhtWN1MRDjKXKVxkpX7ToG0pVZWChlOLFt84wni2Ubczmhjh33bqG5vrq+37Lpak+xh0713Chd4x8sXx5KafOD9E/lGZDZyNGlTWXFKKcXnvtDH/x589g36C09bVBx0D/OH/z1y+U7XjrSgWoG50bWNVZz5atbcRiSy/YXzGvIApFsnSGN4b/jL78W5WezpxlnUH2j/wlF7Iv4qiSbIsSK4KmaaxdVc/9d2xY0lV+pqNpGm1NNaxqKW/OSKFoMzCSKeuY5ZLJljhw/BL5MvVm0DS4bfsq1q9qWHbPj2vds2cd0Uh5913nCxZnLw4vyY7tQsyG63rYtnvDD8eZvJNFKXCcm99vph+Oc+OgIhIJcM89m1i3bmmeRFsxKxYpq5v9w3/BQP4A5cjo1TUfphbE0PwYmh9dM9A0HQ19YnTlofDwlIOrLFxl46ginpp/Wcm8M8L+kb/E0AKsjt4H6NLvQixrkbCfHRvbWNteX+mpLIjm+hgdLQkOn+ot25glyyFZ5o7N5XLwZA8Dw+myJQzXxsPs3tJRlasz5bZ5bTOrWhKMjGXLmnB9rKufD+zbvOyS3oV4r1gsSH19lOHhzNSeEVUgGg1w9z2buP/+LdTWRio9nTlZEYFFzh7icPIb9BfemVNOhaH5CBq1lz8SBIwYASNOwEjg18P49Mjl4MJEZ2Jvr6ccFC6OV8L28thenqI3TtFNYblZiu44RXeMojuOq2Z/1i7vjHBg9H8T8TXRGNgmZVXFstZUF+Ou3WuX7da/ukSE1qaJDsjlOli0bLesidHl4rgebxw6Typdvm1QW9a3sGF1I+YK2Mbj8xnctn0Vx88MUCiVr//J6e4hhseydLbVLftVH7FybdnSxmc+ewfnzg4zNJRiZCTL6GiGTKayr5WmqdPUVMMdd67j4Yd3sWZNY0XnMx/LPrCwvQInU49yIfPirFYLdEzCvkZqfJ3U+FdR419N3NdB1NdC2Gy43Lhudi++SikcVaTgjJKx+8nYvYxbF0jbPaSsi+ScoVnNMWV1c3D0a7yv+fcImcvzTO68yfvjkuf3Gaxb1cCWMldOqiYBv0l9IkI0HChbMGA71RlY9A+lOHV+qGwHxaaps2lNE23NNWUZbynYuaUd308PlDWwSKbydPeOsn1DK+GQv2zjClFNWlpq+PSnb8N1Pfr7x7nQPcKFi6P09CQZGkozPJRmZCRL6Zq/LcPQyxZwa5qGYej4AyaRiJ/6uijtHXXs2tXJrbeuobExVpbHqZRlH1j05t7kTPpxbDWzpEhd81HjW0VT6BaagttpCG4l5mvD1Oe/p1XTNHxaCJ+/g7i/A9iL45XI2v2MlE4yVDjGUPEoKesirprZXtfe3FucTv+UnbW/Ih26pyMpKEteTTTEbdtXEVrCzfBmojYepq4mXNbAIpMr4nmqqs5AHz7Zy+hY+bZoNdXHWN/ZQCS09Oq9z9WG1Y3EIsGyB45d3cNk9pYksBDLmqZpmKbBqlX1rFpVzz1Kkc9b9PQkudA9wutvnOWF509cvX0iEWbX7k5WdZTnBK6mgekzCAZ91NSEaW1N0NFeS00ivCxW5Zd1YJG2+jiVeoSCM5NGURphs56O8D46IvtoDu0gZNYt+BxNPUAisIZEYDUdkbsYKhyjN/cGPbnXyToDN926pXA4lXqUttAeGkPbF3y+Qiy2mniIXVvaKz2NBVcTC5V1f7vnKfJFi5LtlL0B31wppThxbqCsB8TrOurpbKtlGbwfz1g8GmJ1Wx39w6my5llc7EuWLaFeiKVC0zQikQCbN7eyYUMzgaCPV185fbVyVG1thA98YDv33LOpwjNdGpbtKW6lPM5nnmGkeBKPG9dJ1zGoD2xkV92vsbv+11kTu29RgorJNIJGgs7oPeys+1V21f86TaEdGNrNzxzl7WGOp36Ip8pTD16IauEzdTpaErQ3Jyo9lQUXCfmJlrnLqut6U5b0K2ksledi/xhFqzxz0jRY1VpLa8PK2QZ1xbrOBgy9vG/hl/rHyeWl2qBYuQxDpyYeor5+6fWPqBbLNrBIWRe5lHsNy8ve8HY6Jo2h7dxa/4/ZGP8YUV/LIs3w+iK+RtbHHmJ33T+mLXw7pnbjOsYeDv35AwwXjy/SDIVYHOFQgB0b2/Ato4Z41xMK+sq+3cvzVFV13z57aYTkeO6GpRZnIx4N0taUIBxeeVt3VrfVYpR5i9t4psDIWLaqnjNCLLZINEDzCsrZKrdlG1hczL5E2r50w61EGjp1wQ3srvtHdET2lSWPolwM3U9r+FZ21v0qzaFb0LUbH3CU3HHOpJ9AkgqusYK2RyxHkbCf7RtbKz2NRREK+gkFy3uA7HoK27l+I6jFdvr8EONlrAbV0hCnrakGfSXtg7qss60OvcxVsJRSXOgbo1hFq1xCLLZIRAKL+ViWORYFZ4yBwkFKbvqGtwuZteys/QKt4T3oWvWdEdU1g8bgNrbX/jJ5J8mYdY7rBQ6ushksHCZrD1bFqkvVkDhrSYuGA6wrU8JctfOZBv4yr8x4Sk1p9lQplu1w9uII6Vz58isa62I01S/tCipz1doYX5CAqmdgnJLlEFuaJfTFMuF5iuF0juM9g7O639b2Jlpq5/eaEI0GaWmRwGKulmVgMVw8Rsbuv+FqhaH5WR/7CB2Ru6oyqLhC1wxaQrvYEP8wR8a+RdEdu84tFQV3jL7822yq+diizlGIheAzDdqaasreZbhaGYaOUeYz0J7nVc2KxXAyy3AyU9ZApz4Rpj6xMo+Aa2IhTLP8mw5GxrJYdnU8Z8TK5XguRy8O8OePvzqr+/2Lj90z78AiHPbTVOa+QivJsgwshgpHKbjJG94m4mthS+LTmPqN8xeqgakHWBf7ED25NxgoHEQx/Yu+4xXol8BCLBMBv8n6zoZlUX5vJgxdwyxzMq5SE9uhqkH/cJp0bmZltGfCNHVqayLEVkjgeS2faRCPBMu6tQwgOZ6rmmBUrFyupxhKZTnTP5Oqnu/K5Of/GmMYOolEmJqaMGNlLI29Uiy7wML2coxbF7C96/et0DFZF30/UXPpbBkKm/V0Ru9lzDpD0U1NextX2Yxb3VhuFr8hFQ3E0hbwm6xf1VDpaSwaQy9fA6arFJQtU3qeBobTZMvwpn9FPBKkoTZS9lWepaS2JsylgbGy/oqTKQksROUppcgVZ1/6uBx/Cpqm0dZey4c/cgtDQ2mamuI0NsbLMPLKsOwCi5TVS8FN3nAblK75WBf/0JI6E6ppGquj93Iq9ch1AwtQlNwMY9Z5mkO3LOr8qtbS+RWLa/h8Bu0tiUpPY/FoLKnXpNnqH06RLWN+RSwaLGvfj6UosgDVsMYzBUqWg1JqWT8fRXXzlCJfqlxPldbWBL/wC3uxbRfTNIhGV+bK6Fwsu1M9Wbv/piVmE/41xH1Lr+FW2Gwi4V97wwpRriqRsi4t4qyqXHWcrBVz4DMNWhrkLNFy4LoeQ6MZcmVsvhYJ+YlFqn8r60Ly+0zKffbEdRWpdAFXSs6KClIK8hWsTub3m9TVRWlurqG+PkqgSpqMLgXLLrAouCM33AYF2uXyrUtvsWaiStRWTO36kbOrbHLO7KooCFFtNE2jJhokEpKzRMtBMpVjPF0oayJkOORfsfkVV5S7itgVqWyhanJzxMo01xULWWOrvGUXWOSdJI5342S22sD6RZpN+dX4O2+yYmGTc4YWcUZClJ9p6LQ0xsufcyAqYmg0W9YyswCRYPk7lS81fp+xIAdSJcvBq5LcHLEyKaUqumIh5m7pnba/CcvL4qrrPxk1NOL+pbcN6oqor+WGqy1KOZSc6+VgCLE0GIZO8wrtT7AcjafzFArlPUh49Z3zvHOip+zdp5eSXMFakADAsl2UrFiICvKUIjeHFQt51lbesgssXGWh1I0rWoSMukWaTfkF9Bp0rr/8rfBwVPkqryx5K/eYY0kzdG3FJ+YuJ+lciaJV3sDCdlzsrFQvWgiW5aJkxUJUkKxYLF3LbiuU61l41+nzcIWpLd0DFlMPcKOjZYXClcBCLHG6BBbLSiZbpCgHCUuGZctWKFFZnqfIFeVYZiladoHFTM5Qa9pS/rZv9g0qvJus2Kwo8t64JOmatuIr/iwnmXyRYsmp9DTEDFm2Uy3tT8QKNdeqULJJofKW3VYoAz86Bh7XfxNzVHk7lS4mRxW50dGyhoapl7+2uRCLSdd14lEJLJYDpRSZbJFSmbdCiYVjO7IVSlTWRI5F9b1mKAWe5+E4Lp6n8Dy1YH8rgYAP3wJVfltIyy+w0P1omgHq+oGF5WRhiZYkttzsDZv/gY6hyQHZVXL6YknSdY3oCi8lulw4rkeuYGE70hdhqZCYQlSSUmrO5WYX4qmrlMK2XbLZEvl8iZGRLIOD46RTBXJ5i1LJXpDg4oEHtrJlS1vZx11oyy6w8GlhDM28bp6BQpFx+mhgyyLPrDxyziDeDYImXTPw65FFnFGVkzfIpUmDgG/ZvTytSLm8JdughBCz4rgellP5bd227ZJMZjl1sp9XX+3i8OFLjIxkFqWB5OrVDRJYVIOQWYuphbDIXfc249aFRZxReaWsnhuW09U1H2GzcRFnVOVkxWJJ0gDTXMq5UOIKy3ZwquAAQQixNCiY02pFueXzFidO9PLTnxzkjTfOlr1k9nK1/AILow5TD3L9wlCKocJRlFJo2tI66lTKY7R48oZVnwzNR9TXvIizqnKyYrEkaZqGoUtgsRw4riddnIUQM6aUIlecW2BRrqO6YtFi//5zfOubr3H69ECZRl0Zlt07d8TXhO8mW4FGS10U3OQizah8Cu4YSevsDVcsDC1A3NexiLMSYmH4zKWXtCammggsJL9CCDEzSjGn5njl4jguJ0/084Mf7JegYg6W3YpF3NdB0Ki54W0sL8PF7MtsSXxqkWZVHr35Nyk4o9zoNLzfiFIbWL94kxJiAWjaRPdtsfS5jocnKxZCiBmaz4pFOSSTOV544SRHj1ya9npd14hGg8RiQQIBE8M0FmTXdU1NeAFGXXjLLrAIGgmivhYMLXDdLUOecjiXeZo1sQduGoRUi6Kb4kL2JUpe5rq30TUfcV8HYXPpdhYXYoKGbiytrYpieo7ryoqFEGLGFHMvNTvfUxiu63H+/DBvvnl2SnU009Rpa6tlw8ZmVnc20NxcQzQWwO83F2Rr/erVDWUfczEsu8BC03TqA5vpMV4n5wxd51aKkeIpujM/Y3PNJ6u+YZ5SLhezLzFSOI53g21QPi1EW3gPkrH8HvKjEKKiHNfDW4QKKkKI5WGiOV5lVizyuRJdpwcYGEhNujwY9LFz5yo++NAO9uxZQyIRXnJ5uouluo+o56g5tJOweeNIz1FFTqZ+xHDxxCLNau5GSqfoSj9OwR274e2CRoL28B2LNKslQnZgCFFRriRvCyFmoZLJ26l0gbPnJp+U1nWNHTs6+OXP383992+ltjYiQcUNLMvAIu7voDawHvOGjeIU49YFjox9g7HSuUWb22yNlc5zbOy7jBZPo65f6gpD89MUuoWYr30RZyeEEDcmzdaEELOhFBXLscjlSvRcmlzcp7Exzv33b2Hr1jYpgz4Dy/InZGg+OiP3EDLrb3g7T9n05t7kcPIbjBRPLtLsZkZd3q51dOzb9ORex1GFG94+YMTZGH+46rd1CSFWFl3X5OyeEGLGJnIsKhNYlEoO4+OT+6CtW9fI1m1t+HxSqXAmll2OxRUtod00BLeQd4Zx1fWfoI4qciH7AraXY1PNx2kL3z7RB6OCbK/AQP4dTqd/Ql9+P7Z3/WZ/ADombaG9NAa3LdIMhRBiZiYCi/KOaeg6iXiIWLSyr9XLVV0igq5LMCgqY6LcbIWStx2XfH7yMWNzcw0tLYl5jrxyLNvAwm9EWR/7MCPF42Ts/hve1lFFevJvkHOGGCmdYnX0Pmr969C1xY1OPeUwXjrPhexLXMy9wrh1/oZB0RVhs5GtiV/A0P2LMMslRt4bhagoQ9fRy9zsMBzycd/eDbxv74ayjismtDbGCQZ8lZ6GWKE8pSqWvO16Ctt+d9u5z2cQiwUJBuXvYaaWbWAB0BrezarIPXSlf4rt5W94W0/ZjJa6yDqDDBWO0BzaSVv4duoCG/DpC1tL2PbyJEtn6cvvZ7BwiGTpDEU3xUxibw2TrYmfoz64cUHnuGTJ/m4hKsrn0zHL3JNE1zXam2u4a9easo4rhKi8SiZv6xoYhoZ7ObbQdQ3D1GU75yws68DCp4fZkvg5hosnGCmeQHGzkoeKkpuiL/82o8UuLmVfpcbfSX1gI3XBTdT4VxMyEuja/H5snnIoumOMWxcYLXaRLJ0mZV0iY/dT8tLM5mi4I3IXG+IPL/rqihBCzITfZ5Y9sHAcD8u+fjELIcTSpahc523TZxKNBkkmJ7agO46HbbkoRdm3dC5XyzqwAKjxrWJ33a/x6tB/vUFfi2spSl6KUilFsnSGvvx+gkYCvxEnbNYRMZsJm42EjFoCRhSfHsXUAuiaiaYZaGh4ysFTLo4qYLlZLC9LwUmSc4bJO0Pk3SSWm6HojlNy03g4s/7eEv517Kn/DYJGYtb3FUKIxRDwm/jM8p74cFxv0nYFIcTyoZQiX6GqUMGgj/qG2NXAwnU9cvkSpZIt26FmaNkHFpqm0xq+nZ11X2D/8F9hqxsnQl/Lw6HgJim4E+XHdEwMPYCpBTE0P4Zmomk+dE1HQ+fdhTiFwsNT7uUgw8FVJRxVwvVKcwok3itk1LO34Z9RG1g3r3GEEGIhBf2+sldTcRxXViyEWKaUgmyFVixisSCrO+vpOj1w9bLhoTRDgyk6l2gn7MW27AMLAFMPsD72IWwvzzujf4OrSnMey8PB8xxsZheglFPYbODOxt+hNbwHDdn7J4SoXqGgr+yJwK6nKFo2tuOWfTVECFFZisolbycSYbZsbePZZ4+jLjfhuXhxlPPdwxJYzNCKaXrgN6JsrvkUt9b/IzSW7htR2GzkrsbfoSNyF4bml6DiZuTHI0RF6bpOOOQv+6pFoWiTK1Tm4EMIsTCUUtiOR2mOK5LzrdcSDPrYsKGZdesar17W3z/O2/u7GRpKz3P0lWHFBBYAASPGlpqf466m/xNTC1V6OrNWH9jE+5r/HR2RuzC1gAQVMyFVoYSoKE2DWDhA0F/eBfJcoUQmVyzrmEKIyqvUagWApmmsXdvI+x/chnG56ITjeLz6ahcvvHCCXG7uO15WihUVWMBEpaiN8Yd5sPU/ETVbKj2dGdJYE7mfe5t/j9bwrRgSVMyc/JiEqLhEPEQoWN4+O/mCRVbe5IVYVhSVy6+4IhIJcM89m3jggS1XLxsfz/Hdf3iTRx45wPj4jdsXrHQrLrDQNA1DC9IWuZ0Pd/w31sc/fDnpujqFzUbubPwX3NX8u9QFNqBppgQVsyErFkJUXG1NmHCovIFFrmBLYCHEMjPfilDlODrSNI2Ojlo++7k7ufuejZfnBaOjWf7+6y/zR3/0KC+9dEpWL65jRSRvX0vTNFAGcd8q7m76CmuiD3A4+XVGi6fxcKn00aiGjk8P0xm9l+2Jz1EbWIuGBBRCiKWptiZMpMyBRTpbIJmqXBENMTNKKTylcD2F43r0j6UZSmXJFEoUSjZBv4+aSID6WISO+hpMXcfQtbJ3axdLR7Yw9wP2chy9KaXQNI1165r4J//kQRrqYzz11BGKRZtSyeHt/ec5+M4Fmpri7LhlFZs2trB6TQP19VHCYT+hkB9dn//xmt9vYi7B4hQrMrAArh6km4TojNxLa2gPl3KvcCL1Q8ZKZ3E9a94lYWc5IwzNh1+P0ha+na2Jn6c+uBn98q9IggohxFLVWBslGg6UdcyxVJ7hsdzVgwBRXZSaCCTG80XePH2Jpw+d5nB3P2PZAp6a/vCvPhbmtvUdPHzbFu7Y2EHI78NYpADD9TyK1mK+54vpuJ5HMluo6Bxs22VoKE33+WHOnBnk4sWRSa8xSk3kXfT1jdPXN85TTx5ZkHn8q3/9UR5+eNeCjL2QVmxgccWVJ4vfiLA+/iE6o+9jqHiUc+lnGCgcpOSmcZWFp+wZdO6e5WNjTPTC0P1EzRY6I/ewNvZ+4v5O6aRdLnK8IUTFNdZFqYkF0bSJN+VyyBUsRseyWJZDoMzlbMX8KKXIlSxePHaerz//Nid7hq8bTLzXaCbPUwdP8+zhM+xZ18Y//cg+blndQsC38IcqF4fH+S8/emHBH0fcmAIGxjIVncP+t87xH//jD3Hd8h7zrRQrPrC4lk8P0R7eS1vodgpukuHiMfrz7zBSPEHeGcVV1uVAw0Hh4ikXxY3Komlo6Oiaia4Z6PgwNB+mHiLma6U5tIvW8K3UBTbg08OL9n2uGJJjIUTF+X0mDbVRggEfhaJdtnFHx/OMjudpa64p25hifpRSpHJF/uHVQ3zzxYOMzeHss+t5vHWmh55vPMGXP34vH9i5YcGDi3ShyMsnuhf0McTS4CklQcU8SGBxHZqmETbrWR29j9XR+/CUQ94ZYdy6QMq6RM4ZpOBMdOS2vAyud2VF48qR7ERAYWh+gmaCkFFH2Kwn6msl4V9DjX8VQaMGOaUuhFgJ2poSxCLBsgYWI2NZhscyElhUkaLl8NTB0/zDK4fnFFS8V/9Yhj/9ySuE/D7et20tpiF5F+LG5Iiq8iSwmCFdM4n6Woj6WuiI3Dnlek95eMrGUxNvmrruw0Aa2AkhBEBna4KaWJCh0fJtc+gfStE7mGLn5nZ5ra0CSilO9Azx+IFTDJcpsX5gLMPXnttPZ2OC9S31ZRlTiBvRNR1/mfvuzGkeS7SAQeV/csuErunoWgAob4KiEEIsB6taa0nEyrvdc2Q8R8/AOJbtEqiCA4GVrmDZHL7Qz9GLA2Ub01OKcwOj/Hj/Cf75R/bhW4JVcsTS0tAY4/4HtlZ6GrS2Ls2VWHklFsubnMQUoio01EZpro/hMw1s50Z5aTPnuh49A2MMjqTpbKsry5hi7gbHs5y4NIRVpt/vFelCif1nLtE7uo01zfJ7FtdXjrTKTZta+L3f+3gZRlqZluY6ixAzJcnbQlQFw9DZsKaRmliwrON29ybpGRgv65hibkYyOS4Mjy3M2Ok8hy+UbyVECLEwJLAQQgixKDavbSIRL+92qJ6Bcc5eGqFYKl9SuJibTL7EUCq7IGOn80XODYwuyNhi+ZBNCpUngYUQQohFsbajnqb6WFm60l5RLNmcPDdI/3C6bGOKuSk5DvkFCvBKtsNoNr8gYwshykcCC1E1tDIebAB4npKdUEJUkXg0xOa1TWXvwn3q3CDne0bxPPmLryTXVWXLn5kytqco2dIZW4hqJ4GFqBrlrvbhuB6qXG1+hRBlsXtrB7Vl3g41OJLm+Jl+xtNyRruSdF1bsF4TmrZwY4vlQ97xK0/+SkXVKHfdaNtxJ1YtJLgQompsXttMe3MNRhkPEl1P8eahbrouDMuqRQUFTINwwLcgY/sMnUhAyrkLUe0ksBBVI+Ar74qF5ykKRQtPAgshqkY8GmT3tg5iZd4O1d2b5J3jlxjPyKpFpURDAerK3KvkipDfR1NNZEHGFsuHJG9XngQWomosRIOr8UwB1/XKPq4QYu7uvnUddbXlPUh0XI9XDpzjzIVhXE/+5iuhLhamsyGxIGPHwwHWSedtUWVc1yWVKtDbO8b588OcOTPIma4BznQNcPHCyIrcMSEN8kTViIaDTJxvKN8f4nAyi227+H3yVBeiWqxqreWWjW30DabKWib2Qm+S59/sYlVrLa2NS7Nr7VLWXBNlc3sTLx4/j1PGEzq6ptGciLFtVVPZxhRiLpRSjIxkOXt2kPPnhxnoHyeTKVIs2jiOi+upq4cwLS01/Kt//dHKTrgC5GhLVI36RPmX0HsHxrFsF1lAF6J6+EyDD9y9mdcPnS9rYOG4Hi++eYbtG1p58K4woeDC7PcX04sGA9yyuoUNrQ2c7Bkq27iJSJC7Nq+mqSZatjHF8rRQ6wNKKXp7x3jj9TMcPnyJvr5xRpNZspnidXdFrF7dcNNxCwWL/v5xUqnC1ctCIT9tbQni8VDZ5r+YFjWw8JTLmfTjKBQNgc3UBFZjaH402RUngERNGJ+pY9nlK1fY3ZukaEnjLCGqzfYNrWxb30JyPF/WEqXJVJ7HnjvCulUNbF7bXNaeGeLGdF1je2czH9y5gf5kmlS+OO8x/abBzjVtfOTWTRi67N4Wiy+XK/HmG2d59tljnD49wNhYrmxFIizLYf9b53jmmeNXL4tE/Hzms3ewb9/GJfn6taiBRc4e5FzmOVLWBYJGDRGzifrgZhqD22gMbsWvx9C0pfdDFOXhMw0S8TBDo5myjdl1cZhMrkRLg5LnlhBVJBT08fH338Khk70kU+VNuD5xdpDvPfEOv/nZe2hpjCN/+ounJhzk4T2bGU5neeytE/NqmGfqOjs6W/iND+6ltS5exlkKMTMjIxmeeuooTz5xmIGBcRynvPlb4XCAcCRAf/8Y+bwFTATomza3snVrG3V1S2+VblEDi3Grm5wzePUjWTrDYOEIASNO0KihLrCRtbEHaQ3fupjTElVCA1oa4mUNLDLZIl3dQ6xuq1uQ5HAhxNzt3trBri3tvLT/bFn35NuOywtvnaG5Ic7nHt5DYoluKViKNE2jtS7Or73/dhpiUX70xlF6k7Pvih7ym3z41s3/f/b+OziyM83PRJ/j8qQ3yIT3hUKhvGFV0RQ9m02yzbSdnpnWzK40Miu/Kyl2dSNuXMVV3Lsbkq52Je3u7Kw00vRo/HRP97RjN7ubTU8WTRVZ3ht4D6S3x94/UFVksQwSwAGQCZwnAkQxccyX5pz8ft/7vr+Xbz6+n62tCcQaVodeRUZVZHfxyhFsNN2kuMxMAyffgfn5PD/9yUl+/OMTJJMFB4/8MYoi0d2doHdLI+fOjgMLjpYXL0wwMZF2hcVipLTrVMyPbzA2FhUrQ8XKkNVHSWtDRNUeV1hsUgRBYEtnnNOXxh097tETgxw5sMUVFi4uNYbPq/CrLxzgxIUx0tnS4jssgWJJ4/svnyQRDfDCEzvx+zyOHt/l3kiiSHtDmF9/bB+H+jt4+/wgb54fZHgmhbZI2ltzNMgjAz08u28rA+2NJMKBmhYVAF95eDcvHNhGQHU/YyvFtCzePD/I77707rqOo1Co8PZbl/jRj06QSq2OqLhJc3OEnp6PhQXA0NAsMzNZbLv+si3WdKaV0UbRzPw9/27YFSKerhWf52L6hyQrV+/6NwGBFv8BekNPr/g8Ls4iCNDf47zrx7HTw8zM54iEfHWZr+jispHZ1d/K0w/18+PXzjqeZpDJlfnW997FxubzT+52i7nXEEEQiAS87O1upa8lztce2UMyV2R4NsVspkCuXKGs6SiyRED1EA346GtpoDESJOhVCftVFMnZ3karRVdjlG1tjQS8rrBYKaZpMTKXXvb+TlQ+WJbNxYsT/OhHH91VVMiyRN/WJnbt6mBLbyMN8QABv8q/+TcvMjGRXvL5GhoCdHQ0IEnirULwQqHC+HiSQqFCMOhd6VNaU9ZMWFTMHGUzhcW9w1uSINOobl/xuSaLHzJSeOeufxMQkATFFRY1iCAIqyIs8sUKL75+jr/3zSgBn9u51cWllvAoMr/5pQc5+tEg0w6mQd4kmSnye995B92w+Opn97mRSyCdLZHOFWmI+AkHVzdNTJZEIn4vEb+XtliYgfZGTMvCsmysG6uxoiAgigIeWUIUhLpboQ15VUc7yW9qhAV3sfVkbi7H229fZmRk/rbHBUFg3/4uvvKVgwwMtOL3e1AUCUkSEUUBdZld5yVJpKkpTCIRYno6A4Btw9hYinS66AqLe1E0Zu8brQAIyC0o4sqNQU1bx7Qr9/irgGUbKz6Hy+rQ0RLF7/VQLGuOHvelN8/xuSd2sH1LM6LrLOLiUlO0JML89a8+xP/2B6+uSkPLXL7Cf/72O0zOZPjvfv1R/D5P3U1eV4ppWYxMpPjl0Yu8dfwaW7sb+W++/OCqC4tPIooCqrjxhF3IpyK73yuOICCsa+THtmF0NMnRo1duc36SZZEXXtjLr37jQVpbo0iSeMc9ZLm3FEEQiER8NDQEbgkLWBA4hcK95rK1y5pdCXljBs26f55a1NON25B9MyOgKjIHdrY7fuRiSeN3/vgN8iVtU3bCdHGpZURR4AtP7+bwnpWnwt6LUkXn+y+f4p/9q79iZDKFZdkb9l5g2wvPzbIsMrkSr79/hX/x71/kH/7Lb/MnPzzGtZFZSmXNMcvMzYwAhHweJDfN1hkECK5AWKz0XSgUyly+PMnc7O3R0yNH+vnq1w7T3t6ALEuOL0yEQj6in+rlNT+fd4XF/agYaQz7/sV5EU/P2gzGpSYRhIVVgUf2b1mV45+8OM5/+c5RKpqxYScULi71iiyJ/JO/8TSxiPONMm9imBZnLk/wD/7lt/nez09QKGmrEiFZa24KCdO00HSDTK7Me6eG+Ff/6Rf89X/+R/y//sOPeePYFdK5Erph4t7+nMOvKnVTC1IPCLCuEYtMusjlS5O3PdbcHOGRR/rp7o6vWp1mMOi9oyFeNlOkXK6/PlxrV2NhZTGt+6e3BBXn8+td6gtZEjm4pwtFFtEdLuQE+O7PTpCIBvjG5x/At8x8SBcXF+cRBIH25ij/9G88zf/8uz9ztFHmp0llivzvf/g6P33jHH/z649wYGcnqioj3yW9oZaxLBvdMNENk2JJ4/zVKd4/NcQHp4eYnF26xavL0gl41br73NQygiCgyjKKJKGbS78HrFQz5/MVRkeTtz22ZUsT27a1rOp7rCgSHvX2KbmmGZirMA9abda0eNu4Z93DAj4pvkajcalVBEEgFvazd6CDD8+NrMo5/vN3jlIoa3zzCwcJBb1uN1cXlxpBEkUeO9jH1z67j+/94uSqLC7cxLJtLg3O8C/+9xfZv6OTzz+5k/07OggGVFSPXJP3BdO00AwTTTfQNZNUtsiJ82McOzvMqQtj5IvO1qa5LE7I50F2IxaOIggCAa9CurB6iwv3olzR7+hZ0dwcpqU1uqrnlWURRbn9c6RpJuYyxNV6s2bCQrcKmPb9b3o+KbZGo3GpZbyqzHOPbefEhdFVyQE2LYs/+/Fxhkbn+Rtff5iOlhhB/+Yr5nRxqUVUj8xvfeUhRqfTvHdyENNc3bwdTTf54PQQH50boacjzmceHuDArg6a4yH8Pg9eVVnzFemP05rMGz8Gmm4wM5/n8tAMF69Pc/H6FGNTabdOYp0J3ohYuDiHIEBA9ZAulNf83IZhUix+vAguySKBoIp3la2qRVG8w1hmwTltVU+7KqyZsDDRsbn/6pMirl5urUv9oMgSB3d30doYZvwTDglOYpoWb390jUtDM/zKM3t48nAf8WiQYEBFkdd29cmybAzTwriR0mAYJpphoRsmqiIRi/jxKBvPScXF5W4IgkA05OMf/rUnyORKnL8yhbUGRQGGaXF1eJarw7P4VIWt3Y0c3N3Jrv5WmuNhfF4Fr6qgemQUWUKWxWVbo9q2jWktiAfDtNB181ZKk66blDWd+VSBsak0I5MpRiaSDE8kmU8XXCFRY4R8rrBwGkEQ8C+zzmKl8t++cV3eRJElPGtgUa3rJrp2u2OpLIt1aQqwZrMVyzKw7fsLC0l0m8u4LNxUwkEvzx7Zzh/94P1VKzS0bZiZz/EH33uXl944x6MH+zi0u4u2pjBBv7qi1cqbK46Gad36bRgmumlh3BANN0VEqaKTyZVIposkM0Xm03nmUgXmUnl2bGnhN790mM5WN5rnsnkQRYGOlij/8K89wb//r69xZXh2TQ0XShWdM5cnOHN54pbQ6WproLejgfbmCPFYkFjYT8B3w8deXPCxv9mTAeFmQfUnHJpsG9NcuC/ohkmhpJEvlEnnSsylCsynFq772VSeuWSeYklzpNmXy+oS9LpWs04jsDJnqJUgiiKyLKHdmOSbpoWhLxgerGbQslLWKH4qldHv96DUYd+dtRMWGItGLETcYlqXBfxeD0891M/L71xkYmZ1ohY3sSybiZkMf/nSR/zwl6fobImxrbeJ7vYG2poiREI+VM9CYacoLqxSAth8PHGwrIUf07ohJAyTYlknX6zcmkDkChVyxQq5/MJkInPjp1C6t+1jSyKMadVf8ZaLy0qRZYkdW1v4u998jN/90ze5Pjq3Lm5Gtm2TyhZJZYucujh229/8Xg/hkBefqqDI0kIBprJgRWmYFqZhYpg2pmmiGxbFskahWKFUcZ3pNgoBr8eNWDiMIAgE1OUJi5VeVbIiEgiot4SFrpsUihqGYd5RA+Ek6UyRZPL2Xm+RqB+fr/4W3NdOClVxE7Xd9RmXG4iiQHtTlC8+vZtvfe9djDVyRtB0k2ujc1wbnbv1mKJIhAJeAj4PnhspEIIg3BISxo0VSF03qWgG5Yq+qo42Li6bBY8ic2BHB3/rV4/wre+9y/WRuTVJi6qWYllzvJmnS32xkArlFm87yULx9vqkQnlVhXg8SCr1cQF3cj7H3FyO1lUq4LYsm6mpDOPjqdseb2oKEwyubxfy5bBmwkIQZASE+4oH0177Qh2X2iXg9/DE4a2889F1zl2ZXHyHVULXTZLpAsn0/Rs8uri4OI9XVXhofw+CAH/0g/e5PDiD6dYZuNQIQTdi4TjijeLt9SAQVGlvj3H16vStx0ZHkwwNzdLSElkVE4dctsTVK9PMfqopX1dXnFgs4Pj5Vps1uxokQUZY5HRlM702g3GpCwRBoLUxzFc/u494tP4uLhcXF2fwqQoP7evht7/+CHsG2vGsYkqCi8tScIu3nUdg+RGLlS45hMN++vtv71kxNpbk5MkRMpniCo9+J7pucv7CBB9+OHhb0bjf72FLbxORVWwYulqsnbAQvYjC/QMkBWNmjUbjUi/4vB4e2tvD84/vwKvWXxGTi4uLM3hVhQf3dvO3vvEID+3rxV+HuccuGw+3eNt5hPWMWARUtvY309gYuvVYpWLwwfvXePfdqxQK9+/HthRM02J4eI5XfnmW69dnb/vb1q3NdPckVrWuY7VYs6vBIwaQhPt/UFKV62s0Gpd6Ihbx87kndvHgnp66tF5zcXFxBo8is297B7/99Yd57tHtJOowTcBlY+EWbzvPSmosVoooCnR1xjn84JbbXKBGRub58Y9O8PprF5ifz6/YfKFc1jl3bozv/uUHvPvu1duiFT6fh4MHe+nsbFjROdaLNVsCVsUQkqhyP2Oo6fIZFgJZ7uTR5WNEUaCzNco3PneAQqnCifNjNVXA6eLisnbIkshAbxO/+aXDNCfCvPzORYbG593+Di5rjkeS8HnkW06BLs6wnsXbAPFEkEce2crZM6MMD8/fevzSpUny+TJDQ7McONDNlr4mEokQcpW9r2zbplTSGB6e5+zZUd5/7xpnz46hf8rsZceONh442EMw6HXg2aw9ayYsvHIDsuC77zapyjWy+hgRT9cajcqlXvAoMrv6W/nmFw9hmBanL467HmIuLpsUQRBob47ylWf30tES5edvnefEhTEKRdehyWXt8HsXbIbXsiv7ZkBg/VKh4IbV9Y52nv3sHr733Q9Ipz+urRgfT/HjH5/g5Mlherc00dEeI54IEYn477j/aJrB+fPjlMs6hXyFubkck1NphgbnuHptmmymdMe529tjPPOZnfT2Ntbt52rNhEVAbsSzSGdtzSxwOfMihxr/PoIbtXD5FF5VYf/ODkzLQhQFTl+auC186OLisrmIhHw8cWgr7c1RXn//Mq+/f4Wx6bQbvXBZE4Je12p2NVhJxMKpKz8S8fHkk9uZn8/zy5fPks9/7Fqq6ybXr89y/fosqioTCvkIhbykkrc7R6ZSBb71+29QrhiUihVSqSK5XOme3RcSiRDPPbeHhx7sq8v+FTdZM2ERklvxSOH7bmNjMph7lRb/fjoDR9ZoZC71hN/r4dDubryqwvdfPsV7J4coV/T1HpaLi8s6oSgSA73NNDYEGdjSzGvvXeaD08Nk8659+d0QRYHWxgg7trQQCdVnqkWtEPB6UNz6CscRBNatxuLjMQi0tkb58pcfQBIFXn31/G29LW5SqRhUKgt9Lj5Nuaxz8uRIVedragrzwgt7+exzu2mIB1c8/vVkDVOhogTlJiTBg2nfO1xdMGY4Mf8HVMws3cEnUcT7p0+5bD58XoX9OzoIB700xoK8+t5l5t0eEy4umxZBgHg0wOOH+uhtj3NgZyevv3+ZM5cnKFeM9R5eTeD1yGzpSnB4Tze7+lvp60oQDbnfryvBLdxeHVbSedtJRFGgo6OBr37tEIlEiF/84gzDw3OORkRFUaC3t5HPf34fjz42QCIRWnynGmfNhIUoyDSoWxkrvkfRmLvndjYW8+VLnJz/Q2ZKZ2kPPESTdxc+uT6r411WB0WW2NrdyG988SB9XQleevM8569OoRtux2sXl82KLEn0dMRpToTZubWFE+fHePPYVc5fnUTTN9+9QRQE4rEAewfa2b+jg4HeJtqbo0RCPkTXYW/FBL0eFDcVynEEwK8qCAL3TBu6375OIooCLS1Rnn9hDz29Cd555zLvvXeNudk7IxRLpaEhwMOP9PPEEwNs395KaIMI/TVtDNDk24MvG7+vsIAFcZHVRylmZ5ksnSAoNxNUWgkpbfjlBIrgRxZVREG5ay1Gxcrc9+gFc46p4smVPZkaRRZ9JLwD6z2MNUESRVobIzx7ZDt93Y288cEVXn33MlOzWdc1ysVlE+PzKgz0NtPeHOWBnZ2cuzrJ28ev8dH5USraxo9gBAMqu/vbeGBnJwNbmmhJhEnEAvjWOb1koxH0qm4q1CogCAKyJKIqMuUauF4FASIRPw880EN3d4IjR7Zx7uwYp06PcP3aDMUlmEZ4PBLd3Y3s29/F/v1d9PbedJbaOJ+jNRUWUU8PDeoW0toQpr14kxHDLpPRhsloI0iCB0X0IwsLjfZEQQTEuwqLvDF13+NOFU+Q1UaX+zRqmrCnk8+0/S/rPYw1xe/zsGNLCy2JMA/t6+XoR9d59b1LzMznlrza4eLisnEI+lW29TbR2RrlwM5ORidTvHviOkdPDDIzv/IVx1oiFvazq7+V3dtaGehtpjkRJh71E/SrdesuU+sEvJ6qrUZdlsbNdKilCovV/MqXZYnm5giJRIiBgRaeenoHyWSBiYkUExNp5ufz5LIlSiUNwzARBBGPRyIU8tIQD9DWGqO9o4HGxhANDUEiEf+GEhQ3WVNhIYsqXYHHmSqdJqePL2FPG9OuYJrOdDysWFkqWtaRY9Uawtr1PKwpRFEgHg0QDfvo7WjgyQe3cuL8KEc/GuTi4PQdPtG1jOqRaWuKsKUzwZEHthAL399NzcXF5f74vB562hvoaImyfUszX/rMHi5cm+aD00OcuTRBMlNc/CA1hiyLdLU2sHNrC3sH2unrShAOegkHvQR8HkS3G/SqE3SLt1cN8YawmM/V3rUpSSLRaIBoNEBPj82uXe2UyzqaZmAYJqZp32qgJ4oCsizh8Uh4vR68XgVpg39m1lRYALQGDtKU303RmKsqauGyRDb5wpQkijREAkRDPno74jx7ZDsjkyk+ODXEyQtjXB2ZqymLWlEUiIZ89HTE6e9uZGt3I52tMaIhH15VIeBX8alrfpm6uGxIZEmksSFIIhagu62BIw9sIZMtcW10jlMXxjh/dYqRyWRN1mME/SpdrTH6e5rYvqWJvu5GwoEFERHwq6geBTcwsbYEVI9rN7tKiIKAX1XWexiLIooCPp+nru1hnWbNZyyK6Gdn7FeZr1wmrQ2u9eldNgmiKBIKeAkFvDTHQ+zsa6FU1knnSpy7MsGZyxMMjs4zPp2mWF59u1pRFIiF/bQ3R2lvidDRHKW9OUZrU5hoyIfqkW/9eBS5rgorgwGVrz+/n88cca62R5ZEApvsRi1LIr/xhYN87smdjh1T9cjEowHHjrdREAQBn9eDz+uhqSFId3sDj+zvoVTRSWdLXBuZ4+rwLNdH5xieSJJMFzDXqDeGV114z9qaonS3xehua6C7PU4iFsDrVfB6ZFRVQVVkBAE3zckhfIpCf1tiSfu0xyOobirUqiAIAv5lOEO5V8P6I9j22mehW7bB9ewrHJv7XUrm/OI7uFRNg7qVr3T/1/UeRs1iWTaabqDpBrphUdEMZuZzjEwkmZrLkcoUSGaKJDNFMrkS5YqBrhtohomum5iWhSxJeBQJj0fGI0soioRHkfF7FaIhH9GIn3jUTywSoCHiJxbx0xAJEPAvrG7Jkogsiwu/JRFBEN2VRheXGsC2bWwbdMP8+Ec3yRcrTM9lmZzJMJPMM58qMJ8pks2XKBQ1CqUK5YqOblgYpoVlLURFFVlClheueUWWFppp+dWFRY+gl3BAJRz0EY8FaG4I0ZQIEQn58MgSkiyiSBKyvLCvKAquiFhFdMMkU1xa75OA14NXkd33ZRVI5Yv8iz/9OW9dGFrSfv/zX3ueX3nQucUZl6WzLjkWoiDTG3oazcrx0fzvo1kbq4jOpXYRRQGvquC9EWK1bXshorG1BcuysWwby1rIj7Qse6EQzL75+xMHEkBAuCUIBEG4tXooCsKtSYAo3v7/Li4utcvN6/hm9BAW7C4TDUG62hqwLGvhPnHjXmFbNhYLYuST9wmbT6ycCjf+LSxYjSycQ0C8eb+4cW+QRAFRFN0oxDqhyBKJsBvdqxWW233b9WtZf9YteVsSPWyPfgWf3MCx2d+lYMxgUzu573VLjV5Vlm1j2Rb2pwYoC9K6fokKgoAkCTVbTGXbNjY3JjHYCAiIgnhrguLiLDdfb9Ou7l4kCZL7XmxwhBuLCKIkQI3eJ1xcNhoLNRbqeg/DZRmsa1WoKMj0BJ+m0buT43O/x2jhbQyrgk3tFc65rIxz2Wt86/oPuZr7uL19Qo3yr/b+Y1p8S8tr3UwYtsmr08d4afIdJstztPkSfLP7BQ5EtyOzvqJsI1IyNX4xeZr/fO2Vqrb/l3t+lUMNfas8KhcXF5fNxULEovaLt13uZN3tZgRBIKi08GTLv2C2fJbz6e8zVfoI3Spi2jqWbVCzy/C1SK3OM22wbAvrE+/lnfELl09zMn2JH4y/xkhxoTfL5dwIv3v5O/ybff8DTV63G73TpPUip9LDzJars6OumOvfvMnFxcVlo7FgN7t0YVGrU6DNxLoLi5sIgkCTbw+N3l2UzHnGC8eYLp1mvnKFspnGsg1sTCzbBOwbU9I7p6W2bWHa2n3TqkRkJHFjOs7Igne9h+DiIFdzo6S122uQZrU0Y6UZEt4oEq4jiVPYtk1GK3AlO7neQ3FxcXHZ1IjLdIWqZ8plnVLp4y7efr8HtQ4sdz9NzQiLmwiCiF9upD/yefojn8eyTcpmipw+SclMUjYyGPZCNMO2DT5talU0ZhktvkvRmLvnOeLqNjoCD6/2U1kXfPLSV7Et26ZkljFtExAIyF4kwZ2w1gJlU8Ow70wNLJnlhYJRd3nGMSxsZis5hgoz6z0UFxcXl02NIAqEfOqSGxAKdWTV/kls2+b996/xi1+cuTWv/drXDnPoUO86j2zp1Jyw+DSiIOGXE/jl6vLwU5VBUtrQfYSFQKN3BwcSf9O5QdY5eaPA6zMfMlmaQxFlvtT+JAk1ut7DcgFinjBeSaVofmyDqIoKjWoM0a2vcJS8UeZqbgrNcmu8XFxcXNYTSRToaorx5O4tS9qvJRpcpRGtLqZpMTw0y3vvXr312OOPO9cbai2peWGxVFQpjCy4TgJL4Xp+nF9MvcdgYRyv5OHJpoOusKgRdka2cCJ1kZJZRjN1vLLKwdh2Wn0Jt3DbYXJ6iQuZ8fUehouLi8umR5EkDvV1cKivY72Hsibouommb4xFrQ0nLDxiEEl0hcVSGCpMkNHdXiK1SH+wk692PE3bfCPzWpo2XxPPtzxMUPYjuHlQjrFQX1Hkcs6tr3BxcXFxWVt03USrbAwzkA0nLGRRRRH9CEiubW0VaJbOcHGSrF5Y76G43AVBENgfG2B/rD5DovWCbplMlFJMldLrPRQXFxcXl03GQsRiYwiLDdntxytFkITN5SawXGbLKWbKybsWCLu4bBYKZoXzmXHXANnFxcXFZc3RdRNN2xjzsA0pLFRXWFTNcHGSpFadZ7+Ly0Ylb5Q5nxld72G4uLi4uGxCDN1E19yIRc2iimEksf68f9ca27YZLkyScoWFyybGsi1SlQJX89PrPRQXFxcXl02IrhtoG0RYbLgaC3BToarBxiar5xktTlMwSus2jk+WH9u2TcmsMFacZraSImsUqJgaFjaKKOMVPYSVIE1qjCZvAwHZ5+hYbNumYmlMleeZLadI6zlKZgXTNhEQUCUPITlAQo3Q6m0kpPgRhQ2pze/JzfdovDTDTDl54z3SsbCQBQmfpBJSAjR4wjSpDYSUAFKNv0aaZTCYnyGnr9914OLi4uKyedEN0xUWtYwqhV1h8Qks26JkVkhp2Rs/OVJ6lsnSHJdyQ1ifyCs3LJOXJt+hwROu6th+ycfuSB9bQ51LHpcsSHDDMlUzNU5lrnAmfYXr+XGmy0myRp6SqWHbFoqo4JM8RJQQLd44vcE29kT62RrqIrhCgXFzsnwxN8T5zHUGCxNMl+dIaTmKZhnDMhAEAa+oElYCNHkb6PK3MBDuYW9kKzFPeNkCQ7N0LmaHOJu5uvjGNwjJAZ5tfgif7Jz72VRpjg9TF2+5g3lEhRdajhBU/MDCa6RbBqczVzidvsJgYYKp0hwZPU/F0rBsC1mU8UkqESVIQo3S4k2wP7qNvdF+QkrAsbE6TdHQOJMZWe9huLi4uLhsUjZSjcUGFRZuxOImY8Vp3pw9QUrLktZypPUbP9rCavyni1UNe0FYVEujGsMneZYlLFTJg4hASsvy8tR7vD13ksH8+G1C5yYVS6NiaaT1PMPFSU6lL3MidZknGg/wWON+EmpsyecHMG2L6fI8r00f53jqPEOFcTTrLqsGtk3BLFEwS0yW5zidvsLx5HnOxrbxTNNh+kNdeJaRfqdbBqfTV/jzkZ9VvU+bt5FHE/scFRaT5Xl+MvEWw8UFu1VFkHk4vudWVChvFHlp8ijvzJ1ksDCOaVt3HEOzdDRLJ6PnGSlOAQsRqe3h2u4cWjI1zqZdYeHi4uKy0ZiYSHH16jTpdBFVldm2rZXu7gTifTp0F4sV5mbX1oJ/fDxFPl9efMM6YEMKCzcV6mNGi9N8d/RlKpa+3kO5A5+kkjeKvDpznFem3idrVG95W7Y0LuWGSGkZNEvn2ZaHq46y3MS0TQbzE/zV2Kt8mDpPfgkpYTY2k+U55qbSTBRn+UrH0+yPDqBKG6O2R7cNskaBNmzKZoXvjv6Sn0+9R24J75FHVGjyNhC6EfWoRRaEZZqxYnK9h+Li4uLi4iCDg7N8/6+Oc+7cGLlcGUWR6OlJ8Nt/80n6+pru2WR2aGiOP/vTo2s61kymxNRUek3PuVpsSGGhShFEV1gAC5PnWhQVABIiP588yhuzJ26bsEaVEN2BFsJKEFVUqFg6yUqWsdI0GT1/2zFmKil+MfUecTXKY4n9qFJ177tlW4yVZviT4Z9yInXxNrtdAYGwEqDD10yDGsYjKBi2QUrLMV6aIaXlsFhYsdfthfSgklXBL3nZEe5FFqXqXwNBpMUbZ0e4l5JZoWxWKN340S1jXe1Pk5UMWkDnRxNv8NLkUQrmx8JLFT0k1Ch+yYsiyrciFWkth24vRHya1BhtvsZlRXLWioqpcz5zjyiVi4uLi0vd8vZbl3jrrUtksx9/d01NZYjHQ/yTf/oC99AVJJN53n23+vRkl9vZkMJCFm42yROxuTNlYzPRG2jnb2/56l3/ltKyvDd/hvHSzK3HZEHiV9qeJK5Gqjq+X/IyEO5e1tjGSjMMF6duFY9HPSGebXqQHZEtNHjC+CQVWZAxbIOCUWayNMv7ybMcmz9H2dJuHWeqPM/782fZGuykO9C66Hlv1lR8b/QVPkpduC2tp8ET5pH4PvZGt5JQYwRkH5IgYtkWRaPMnJbmdPoKR+dOM6+lb+13JTfCd0d/yT/o/wZNasM9V0I+jSIqHIgN0O5vQrcMdEtHswx020Azda7kR3ln7uS6OHfNaxnenjt5S1QICHQFWnioYTfdgVYiShCPqCAJIoZtUjIqJLUsw8VJLmWHaPUlaPM1rvm4l0LF1DmVGl7vYbi4uLi4OMy1azMUCpU7Hj927Dpgc7t9jItTbEhhIQgiXimMKMiYtrb4DhuYFl+Cz7U+ete/jRQnuZIfuU1YSILEo4376A20V3V8AZa0Qv9JPhl9aPHG+Ru9X2J3pI/YPVKa+oId9ATaCcsBfjH13q2VcRubc5lrDBbG6fA3L+pCZGHx5uxHHJ07dUtUCECrt5GvdjzN4YZdxNXIXQuyt9qdbAt10eFv4gdjrzNZnrv1t1Ppy/xy6n2+3vks3iojJ5IgElejxNXoneO0LUJKgFPpy+siLE6mLjFZnmO+kkEWJD7X+iiPNx6gw9dESAnc9fXRLYOsXmCuksYjyrR442s+7mqxbZuCqXHW7V/h4uLisuEQJfGuUQm3DerqsiGFBdyss1A2vbCQBBHpHpNcj6ggfqqViSAsPF7txNgJApKXv9n7ZR6M715wiroHiijTHWjh6ebDjJdmOZm+dOtvGT3HSGGKQqxIWAne8xi2bZPUsnxv9BVK5scrGVElzBfbHufJpoP3tbEVBZGEGuOppkOktCw/nXyHrL6QxqXbBr+Yeo+nmw/R6m2sOmpxv3NJgrhuaypnMlcpmxpg82udn+X51iMk7iKAPokiysTVCHE1UvNdrE3bYig/Q7KSX3xjFxcXF5e6or+/mZMnhslkirc9vm9fF260YvXYsMJClaKIQu3mdrt8zLMtD7M/NoAsSItOxkVBpCfQxr5oP2czV2/VRtjARGmWjJ6/r7AAeHfuNFOfiDQogsyOcC9PNx+uujdGUPbzmeaHOJW+QlYfvPX4nJbmnblTfKX9aRShvi+vm8LrkfhePtf2GDEltKT9hRq/ceuWyanUcM0LIBcXFxeXpfP00ztJpYq8+cYF5uby+P0e9u3v4hvfePCe9RV3IxBQ6e5JEG+4/9xiJaTSBYaG5sjn6t8Zqr5nPvfBdYaqDwKSj882P4RPUqte4feKHtp8jTSoEWbKH7v5zGuZRZ2dTCxennr/tqlkSAnweOMBwkvstdDsjTMQ6mG4MEnR/Phm8O7cab7Y9gTKBri8PKLMr3Y+S0wJrTgCU2tolsGJ1ODiG7q4uLi41B1NTWF+/dcf4vnndlOu6MiyRDjso6lpaQ6Szc0RvvQrD7Bn79Jt9avlwoUJvvPt97icm1q1c6wV9T/zuQcRTw8dgYcoGZ+2kRSIqlvWZUwud7I72kdcjS5p0ioIAhElSIMnfJuwKJpl9EXcfa7mRhkvTd/2WFgJsD82sLSBs5Bm1hfsICD7bhMW1/PjFIwSXtFT95PxB2I76PQ3r/cwHMe2bbJ6kcu5yfUeiouLi4vLKiCKAvF4kHg8iG0vLCcu5zs5EFBpbgnT0lKdqc1ySM7nCQSc6021nmxYYZFQtxGJd2Dz6U6GApK4Md68jcDucB8eUV5y2oxHUvBKt7+PFVNbVFhczA7dZi2rCDI9/lZC8vJ6LbT7GvF9ahy6bXAtP0ZDQ6TGk4EW54HYdjyiUvcC6dOYtsWZ9ChlszatmF1cXFxcnGMl32GqKuP1rm5qvaxIeDwbY0q+MZ7FXZBED5LopkLVOp3+FuRl1CJIgoTyqUJv0zZv9Ze4F5dzw1j2x4lQiijT7r93o5zFCClBFPHO8S9EUurfzm5bqHtRl616xLAtNw3KxcXFxWVRVFVBVVdXWCiKhLJBhMXGmzG41A0CAk2+hmVNXIVP/Pcm9q3/3Jvr+bHbinVlUaJRjS35/DfxSR6ku1xGOaN4l63rC0WQiXnCNV+EvRxM2+TD5PX1HoaLi4uLS42zFhELRZHweJZn3V9rbAx55FKXqJJnwV52jeatlm3d0bk7qxf4nSvf5nev/uUyj2qjW59Ot4OcXqh7ryG/7EUUxA2XBmXbNmOFJGPFT9dfubi4uLi43M5aCAuPR0LdIBGLjfEsXOoSr+hBRFyzFfGSWblrqpRhm2DfKQ5Wgm7Vf+6+V/RswFgFWNh8kLy23sNwcXFxcakDVK+yBhEL2a2xcHFZKcvt2L1cCkYZu97DCC4rxrZtPnSFhctdsO2FREnLtjBsC/PGj2VbWLaNfSOR0rbt21IqhRvLI4IgIAoCIgvNLSVRRBYk5A0Y+XNx2agoskQksmDoIggQifjxeNYiFWpjTMk3xrNwcakCwzbuaIYmIBCUfch3KcBeCf4qG+25rA22baPbJrplkNPLnEmNrPeQXGoA27axbJuypVMxdcqWTl4vMV3OMFVOM1lKM13KMFfJkjPKC9uYOmVLo2zomLaFKIoogoRXUgjKPkKyl7gapMkbocUXpcufoMPfQFDxoYoyXklBlZQNaYrg4rIR2LWrg3/9r38dWBAWsYbAkhrqLQdXWLi41CEeUbkj7Soo+/hax2foC3Y4eq5GNYpY54lE9Tp607bQLIOKqVO58btoVpgophgqzHIxO0HOcKa76UQpxZXc1Kp/6ThFSPYRV0MoaxwtrCVs20azTHJGiZxeYq6c42JunAuZcS5lJxgvJW9zjlsMyzIxMCmZGimtcNdtJEGk3d/AQKiNHZE2dkY6aPJGCMpeArJ3U78fLi61RjDkZdtAy5qeU5YlAkH1tl4Wslyf9wVXWLhsGgKyD/FTq4SSINHhb+Jgw451GpXLcrFtG8O2FlaQTY2yqVEydTJ6gfFiipHiHCOFhZ+JUgptkR4ny+F/vfBjx4+5mjzXupd/vO1zNPtWr9FTrWJYJhm9SForcDU3zdG5S5xIDTFdSq+60YJpW7c+iy9PncYjyvQGGznU0McDDb10BRI0eIIEZPWOe5SLi8vGR5JEduxo56tfO3SrmV93d2KdR7U8XGHhsmnwSSpB2U/O+HhV0byLU5RL7WHZNrplUDQrFA2NolmhYFRIVvKMF5OMFucZK84zWpxnvpLDsO/fz8Rl81A2dWbKGQbzMxxPXuf9uSsMFWbXdUyaZXApO8ml7CTfG3mfbeFWHm/awb5YNx3+OFHFv+Y1aC4uLuvL3r2d7N3bud7DWDGusHDZVHT5m5kqz92qtdAtg/HizDqPqjZZjzr3m0WxJVOnYJQpGBUKRpmcXma2kmW8uGATO15KMlFKktFKd9TNuLgAlAyNyVKKC9lxXp06ywfzV6msQtRqpZQtndPpEc6kR2j3x3miaTsPxfvZGmoh5gkii24Ew8XFpX5whYXLpmIg3MOx1PlboUbd1hksTKCZOh5pdV0fXO5N0agwWpwnq5fI6EWmS2kmSqlbP9OlNEVTW+9hutQBmmUwWpjndHqYN6bPcyI1RKkOPjs2MFac58+G3uH16fM82byTI4ltbA+3E1J8iPVSyOPi4rKpcYXFJkZEvOPLyvqUjeJGY390G98e+QUVe2GiYdoWU+V5BgsTDIS713l0tcVaTmOG8rP8xysvM1KcY6accVOZXJaMbdvMVXKcSg/zs4mTHJ+/TtGsrPewlsVEKcVfDB3l2NxVnm3dy5HGbfQGmlDdxQ8XF5caxxUWmxiPKCMJt+fx6paBZupYtr0hV8h6g+10+Zu5kh+99VhWz/Pm7Ef0BFpRJc86jm7zMlPJciI1RGUDNBZ0WXtKhsbV3CSvz5znlamzTJZSdb88YmNzNT/N6LXXOZMe4fnWfTyU6Cei+DfkvdnFxWVj4AqLTYxP8uIRb18Bs7GZLs+zNdi5IVODFEHmuZZHuHZ1DOvG1KNkljmePMfeaD+HG3a6riwuLnXEXCXHu7OXeGniJGczo5TNjSVOK5bOO7OXGMrPMpif4fnWfXQFEm5xt4uLS03izqA2MQHZS0QJIn8qavFh6gJ5o3irDmGj8UhiL9tCH6c92cB0OckPxl7jROoS+jIKPG1s5isZLmQGl7V/LbIx332XjYJl24wU5vir0ff5g+tvcDx5fcOJik8yXkry50Pv8PvXXuWj5CC6Za73kFxcXFzuwI1YbGJkUabT30xECTKvZW49/mHqAv2hbj7TdJiA7EPYQGF3QRCIKEF+tfNZ/q8r3yal5wDQbYML2UH+bOQlxksz7Ilspc3XeN/UqIqpMa9lmCrPMV6cZbAwTk4v8j9s+ybKCjt529iY1kKn6E/XvFhYVCwd0zIRBXFDvT8uLtWg37Br/eHYMd6cuXDPxnQbjbKl88upM8yUs3y96yGebt6FR5Tde4DLrS7yFd1ANyxMa+HHsCxMy8a0LOwbKc6SKH78IwnIoohHlvDIMqLofpZcVoYrLDY5uyJ9HJ07dZuwyOoFfjT+OtPlebaHekioUVRJudVLoGxplIwyBbOMJIjsivTR4o2v47NYGgICB2Lb+XL7U/zl2C8pGCVgQVxcyg4zXZrno9AFOv0tNKoxgrL/hlBYeP4lUyOnF8joeea1DLOVJFOleXJGkWa1AZPFC481S2eiNMtocRrN0tGthS7RN/+tWTqaZTBZmiOl5W7bN6sX+IuRnxOUfSiigkeU8YgKHlFBufFvVVRIqDG2h3tW8Dq5uNQeFVPnRGqI7wwf5aPk4KZzC7OBU+lhMnqBtFbgK50PorriYsNj21CsaKTyJZL5AqlCmUJZo1jRbvzWKVZ0yoaOYViYto1lWRimhWXZmLZ9S1iI4ifFhYAkCiiShNej4FcV/KqHwM3fXg+xgI94yE8s6MPr2Xgp0i7O4gqLTU6nv5lDDTsZK82Q0rK3Hp8qz/PTibf50HueiBLCI8pY2BiWiW5/3Ok4rkZIqNH6EhaCgCoqPNfyCKZt8uOJt0jfiFzY2KT0HMeS5zmRukRA9uGXvMiihG2DaZtULJ2CUUKztGWnC5XMCseTF/jl9HvolnHjdTUW/m3fPVJxk6JZ5pfT7wMgIiCLMoogI4vSjd8yHlFmb3TbioSFi0utUTF1PkoO8keDb3IqNbSp3cOGCnP88eBbVCyD3+g+4jpGbSAs2yZdKDE+n2U8mWE2k2c+WyRVKJEtlskWK+TKFUqaTlkzKGs6Zd1AM1aWHicIoMoyXo+MV1EWfnsUQj6ViN9LxK8SC/qJh/w0RYK0xyO0N4QJ+70OPXOXjYArLDY5HlHhicYHmKukeW3mOHmjeOtvum0wVpphrHTvBnKqpGDW4Ze7IAiElQCfa32MsBLi5el3uZwbuW0bwzbJ6PkldeaWqmxmZVgmSS3DaHF6SeP+NBb2QnQDHT7xnSIAzXUk9lxcFkMzDU6mhvjD629wKj1cl/cdp5mtZPmL4aOYtsVv9jzmios6xbQsUvkSg9NJhmdTjMymmUzlmMsWSOWLZIoV8uXKioXDYtg2lHWDsm4A5btu41VkQj6VsN9LQ9BPIuynNRamuylGT2OMrsYoseDGSqFeK2ZmskxNZW4VOHZ0xmhoCK7voJaBKyxcaPI28KX2J4kqIV6bOcZEaQ6rinSeeuemuHi6+RDt/kaOJ89zbP4cY6WZJfXyEBBo9sbZFd7CoYYd+CR1FUe9drjF2y61wk1R8a1rr3E6PbLuomIhUihh2zaGba7rtTJfyfHdkfeQBZFv9jyG4rpF1QWmZTGfK3J2ZIqzw1Ncm0oym8mTzBdJF0qUtNo0AbkpPGazBa4xjwD4VIWG4EKqVHM0xNbWOLu7WtjR0URDyLVHrgbLsvnooyF+/KMT3Pz2/c3fepQjR/rXd2DLwBUWLgC0+Rr5XOuj7Ir0cT5znSv5EUZL02S0HCWzgm3beCUPXkklIPtoVGO0+OJsCXTQ5W9Z9PjdgRb+9pavkL9RzwAL0ZKYJ7Ss8bZ4E/xG13M83/LIrcdUUaE32L6k4wiCgE9S2R3ZSqe/hcMNuxguTHIlP8JYcYa5Soq8UUK3dARBwCMq+CQvUU+IRk+UNl8j3YE2mr0NNKoxEmr0DpetuxFS/DzX8jB7IluX/NyrJeYJV73tlkAbf3fr1ykaH69SeSUPAdm3GkNzcaka07a4nJtcU1EhIhBTA3QHGmnxRkmoIeJqiLDiwyspyIKEJIgLJgu3as900pUC85Ucc1qOyWKa6/lpCmvQpG9BXLyPKil8o+th1zK7RrFtm2ypwofXxvjo2jhXJ+eYSueZyxbIlyvUoxGjDTfqOzKMzWc4NzLNsSujNEYCtERD9LclONjXwd6eViJuytQ9MU2LqakMFy9O3HoskyneZ4/aRbA3qqeoy7KwbZu8USSrF8ibJTRTx7RNbGwkQUIWJGRRwiuq+GUvfsmLV/JsmC8yy7apWBpZPU/BKFE2NXTLuBHBEZAEAUmQUEUPXsmDX/YtFFELbvHkSpgtZzmbHl2TSeNkOcXvXPqZI6vMf33LkwyE2hw40trQ4ouyNdSCt05SZmzbZryU5Hcu/Yw3Zy6sak2FIkr0Bpp4oKGXbeE22n0xQooPv+S5saiyYI4gCQICwq3r3bZtLGxM20IzDcqmTtnSKBoaGb3ISGGWC9kJTiSHGC3Ordr4BQS6AnH+Qf9zPN2ye9XO47J0LMtiKp3j9bPXeffiMMOzaeZyBQrljW08IAgQ8HpoDAfpbW7gkYEuHt/RS3M05LpPfYpiscKf/slR/uIv3rv12P/4P32ez31u3zqOanm4EQuX2xAEgZASIKQE1nso64J4I4KxUdKZ6oW4GuLxpu1rcq4ruSkWqlBWLi12Rzo50rgNoU48tARBQKyTsQKk9SLfG3mfo3OXV01UhGQfjzVt55FEP1tDLUQ9AUKyt2obV0EQkBCQBBGPKBNUPl6VtW2bXZEOHmvawVw5x+XcBG/PXOR48jolh92sbGzGikn+ZOhtmn1RdkY6HD2+y9KxLJsrk3P89MOLHLs6ynQ6TypfxLQ2x3qubUO+pJEvJRmbS3NmeJIXj1/gcH8nLxwYoLcphiy5qXsAum6i1Wj621JxhcUGw7RN5itJRovjzGlzJLUUaT1D0SjesDLVsLGRRQWP6MEneol5osQ9cRrVBJ3+DuJqDKmKdB4Xl2qwbJuUlmKyPMV0eYbpygwZLUvZKlMxy1QsDRBQJQ+q4MEr+Yh5oiTUBuKeBpq8TTSpjSiiM6vs1RbYV3UsQUQWJDdatQqUDI1Xp87yo7EPV6XxnSoqPNO8iy92HKQ7kCCi+B0vfhYEAb+s4pdVmtQwW4JNPBjfyqXsBC+Of8QH81fRHGyoadoWF7PjfOvaa/yPO36FFl/UsWO7LI2pdI6/eOsUr525eiPVaWNHJxZDNy1mMwXmsgWuTyV5/cw1ntmzla8+vJsWN4JxQ1hsjKaXKxIWSS3Fz6d+yan0maq27w/28YW2F2jxNq/ktKvORGmSlyZf5kr+alXb7wxv50ttXyDqiazyyO7Etm10W+di9jJnMucYKgyT1FJolo5hGxiWgWmbWFg3QvYLq343Q/ki4o30JhlZUFBFD3E1Tl+wh/3RvfQFtiDVUDHg9fwQL078lInyVFXb/50tv01voHtdU7Uyepbfu/Yt5rXkotuqoofPtz7PQ/HDqz6uFyde4p259+5bqL4/upevdXwJj3jvRoF3w7ItpssznM9e5Fz2PBOlSUpmGd3S0W/7TFpYN84vIt76TEo3rXMFGUVUCClBOn2d9AV76Q/20eJrdsXvBsa0LC5lJ/iD66+T+0RdllMMhNv4B9ueY1uolYjiR16De5wgCPhkD21SjEZvmB2Rdo7NX+Pbw0dvRNGcQbdMPkxe54+uv8k/3v4Cvvs0+XRxnny5wg/fP8/33z/LRDK74dOdloptQ65UIVeqMJVaSA/78oM7+fJDOwl61U27SGO4EYsFApKfFm8zL5V+UZWLTkpLcTD2AE1qY83m5Nu2zVR5mo9SJ8gaucV3AJ5uevy+HZpXi/lKktdm3+RE6iRpLUPFqnyiHuD+2Ni3hIZhG2B9XGA4W5njWv46b86+Q7PaxIMNh3i86VH80voX8mpWhenKLOOlicU3ZqE79npj2SZT5WlmKrOLbquKKgVjbQq20nqGsdL4fbeJeaJLqnswbZPR4hivz7zN2ex5cnoOzapg2IuvxFhYYIOJiW7qt5kdzlbmGCmMcSx5HK/kpc3Xwp7IbvZGd9PidUXGRsLGJmuU+Nb115gpZxbfYQkICHy58zC/veVJGtXwmgiKO8YgCHgEmRZvlOda99EXbOY7I+/y6tRZKg5FLwpGhXfmLrJtooWvdD7oyDFdFufdS0P8p59/wLXJOXKliuustwj5ssaViVn+48/e42cfXeS//+JjHOrv3JQuUm4q1A08oocufyed/g5GiqOLbl80S1zIXqQn0LUuq/vVkDPyXM8PVS0qYp4oW4Nb8Ypr53YwW5nllanXeTf5AXmjcCO9yTksLCpWhYpVIavnGC6O8urMG3y25RkeSzyCV3KdHTYLaS1DNf4ONjYz5Vlenn6VD5Ifktdz6LZzN0mbhcicbuoUzCIpLc3l3DXyRoEvt30Byc3T3TDolskvJk5xbP6ao8f1iBL/dMcX+WzLXkKyd91XRgVBwCspbI+0848HXqDDH+fbw0fJ6s5EaKZKGV6aOMmeaBd9ocWd+1yWT65U4Q9fO86PPjjPbKaA5XriVI0N5MoVzo3O8D/+4U/4jcf28beefRBV2VyZ+rphoumusEAQBBrVOPsiu6sSFgAn0qd5OPEgESW87jf2T2PbNkktycXcpar32RPZRcwTXfXnYts2mqXx5uzb/HTqF6S1dFWrwCs+LzYVq8JEeZI/H/lL3p57l1/r/BrbQ9tuc0Zx2ZiktDT2jTS6u73XN1PxzmbO8/3xHzNaHMNcg8+lhYVXUmnwxByrvXBZf2zbZqKY5FvXX3XUISwoe/l/7PwSTzTvxCsqNXXfkgSRuCfEN7sfxS95+NOht5mrVLewdT9sbC5mJ/juyPv8k+2fd5vnOYxtL7zGp4cm+d2XjnJqcPJGYzmX5WDZNplCmT945TjHrozxz7/2FAPtjZsmerGRIhYrzkcKySG2hweIKNV55k+WJ7meH7xRsFlb3MwLv5YfrGp7SRDZF91DWF5eL4ZqMW2TocII/+Hy/8Wfj3yXucr8moiKT6NZGtfy1/nfL/8ufz7yl+SNfFWr2S71S8EsoN0jnWzBmrjAq9Nv8HvX/oChwvCaiIqbNKtNtPvaamqS6LJ8bNumYhn8n5d/TkpzLh0wrPj4f+/5VZ5u3l1zouImgiAQkFV+teth/vqWJ2nyOhPRL5ka781d4ReTp91VdAexbRvdNPn+e2f5f/7JS3xwedQVFQ6hGSYnro/zD//T9/nxsQvohrnseYZt23Xzo2kG+gYRFiuONQmCQLO3id3hXbwz/25V+3yYOsnuyE5UsbGmbvIZPcOF7KWFmoMq6Av00uptQRZXJ2RnY6NbOidSp/je2A+ZrLJgebUpmkV+Of0aE6VJfqPrG7T5Wtwc9w1MSs8Q9URve8y2bTJ6hlemX+fHky+tqaC4SbO3iVafm+KxkTiZGuKtmQuOHc8nefiH257nwfhWPFJtp1YIgoAqKXyp4xA5vcS3h98lo69cYI2Xkvxy6gz7Yz10BuIOjHRzY9s2uVKFP3vzBN955zTzufpsYlbL2MB8rsi//f7rTCQz/DdPPUBA9Sx5vphMFuomCjAznaVQqL0F9+XgyJ027mlgZ3g7x5IfotmLvzAXs5eYqcySUONI1MaE1LZtknqa89mLVW0vALsju4kq0dUZDzZls8yrM2/w88lfktLTq3Ke5WLYBmcz5/gv1/P8WufXGAhtWzWB5bK+pPQUPXTd6tWwICqyvDz9Oi9O/LQqswCn8Uk+WnwtVUdKXWof3Tb5k8E3HTueIkh8s/tRnm7ehU+uH2ckn+Th610Pk6zk+cnECUf6XVzOTfDmzHl+o/tRR+2WNxuWZTOTyfMHrx7nJ8cvkCutflf1zUyuVOGPXvuQ2UyBv/fCwzSGA0sSF//qX/2IEx8Nr+IIXe6GI3cYWZTp8LexJdhb1fa6rXMydXrN3G+qQbM0xorjVUcFQnKY/lAfQXl1GskVjRKvTL/umKiQhAX7To+o4BEVFEFGWuHbb2FzvTDEX4x+l/PZi+iW817zLutPSkvf+rdt2xTMAm/PHeUnky+ti6gAaFTjdPjqp+O1y+KcTA7xUXLIkWMJwOFEH59vP0DUU3/NPmOeAF/pfJB90W4kBxwU5yt5Ppi/xvAqdv7e6Fi2zVQqy3/8+Xv84P2zrqhYI4oVnZ8cv8D/9oM3mUrl3PTrOsCxJeYmbxM7wwNcyV+pqujuZPo0TzU9TkgO1kQ6VNbIcTZzrurtd4QHSKjxVRl7ySzx5uzbvDz92rJEhYCAT/Lik3yooopX8hJSgvglP8qNqIJm6RSNInkjT9msULYqlM0SJbNclXXwJxkqjPC98R/yDeErbA8NuJGLDcZCAbd9y0Dgo9QpfjD+46rTn0RElBuCVhZkJEFCFEQEBGxsLNtasD22DDRLR7O0RQVLo5qg3RUWG4aKqfNnQ287VrDd5I3wjc5HaPXFHDneerAt3MpnW/cyVppnrLh4D5zFuJQd5+jsRTr9Dbe+B1yqw7ZtZtJ5/viNE/zi5GXKdZJes1Eo6wZvnr+OzyPz9z/3CE2R2pg3utwdx+4uQTnAlmAvjWojU+XpRbefqcxyJXeVJrURVVKdGsaysGyLZCXJxdzlqraXBZkd4W3EViENSrM0Pkye5PWZt0hW0VDtk0iCRMwTpdHTSH+oj75gL53+dqJK9J7OObqlk9JSjBbHuZYf5Fr+OjOVWdJ6pupaE4DB/BA/nvgZvk7/ujekc3GWlJ5e6HkiWFzNX+e7o99f1HxBERQCcoCQHCDqidLsbaZRjRNTogSVIKroQRZkDNukbJapmBXSRoap8jTT5RkyepaiUaRgFCiZpVtN9G4eu9nbTEJ188U3CqfTI5xMDS15UeNuKILEF9sfYGe0HaWGmnsuh2dadnMuM8p85eSKU6KSWoHj89d5KNFPf6jVoRFufGzbZjZb4Ntvn+Inxy+4De/WiWJF55XTV/GpCr/9mcM0hoO42qI2cXTZos3bykCon+nyTFVfEB8kP2R/bB8ecelFOU5SNitczV8no2er2r7d10qnv8NxQWTaCxO312ffZKI8WfV+AgIxT5QtgV4ejh9mV2Rn1SlaiqjQ5G2iydvEwYYD5I085zIXeH/+GNcKQ6S0VFXvpY3NldxVfjH9Cl9t/xWavU23cvJd6pv0jYjFXGWevxr/0X2jaF5RJa7G6fJ3MBDaxkCon2Zv05IsYS3bJqtnuV4Y5Fp+kOHiCPOVJCktTdEsEvNE6fC1u4YBGwTLtnhp4gSaQ83h+kLNHEkMEFXqLwXq0wRklc+27OFcepTLuckVy65LuUlOJIfYEmx2JMVqM5AtVnjx+AV++ME5MsXy4ju4rBrZUoWffXSZoFflt558gEhgaT21RFFAlmvze8O2bQzDZCNkejkqLBrUGFuDfXyUOknOyC+6/eXcVabK00SU8LoVcS9YZuY5nTlb9T7bwwMk1ITjY5mrzPHm7NtczV+veh8Rkd5AN483HuFI4mF8K+yOHZSDPBQ/zN7obt6de5+3597lemGoqrQX3dY5nT5DoyfOC63PrVr9icvaktLSlM0Kv5x6lcu5K3fdRhZkGtUEO8IDPNhwiL5g77IbKYqCQNQT4QHPfg7E9lExNQYLQ5zLnOdafpCoJ0Knv2MlT8mlhpgpZ/kweR3DgTQojyjzdPMuugKJDZMqsTfWzb5YD6PFJEVzZXn985UcF7LjzFdyjlnabmQqusG7l4Z58diFmnJ/kiURryIv/HgUVEVGlkQUSUSWJBRJRBJFBEFAFBYcxwRhYanPsheWCm3bxrJtLMvGsCwMw8KwTHTTQjdMKrpBWTcoawYV3agZu+JkvsjPT1yiPR7mcw9sX1Ijvda2GLt3dSDLtSeq5+byXLo0QTpdO5+z5eKosJAEie5AJ72Bnqom6rqtcyz5Ib2B7hVPiJeLhcVMZbbq3hVBOUhfYIvjbjQls8xHqZOcy1xYUu76rsgOvtr+K/SHtjo6Hp/k45nmp+gOdPPD8Rc5kzlbVe+MvFHgw9RJOv0dHIwdcOstNgApLc2x1Ie8PvvWXf/uk3xsD23j0cQj7I3swic7dy0LCHgllR3hAQZC/aS1DDkjR4u32bFzuKwvb85cIKM50216a7CFAw29hD3r832yGiiizGdb93IiNciV3Motxy9nJ7iYnaDRG3ajyvfBtCwuT8zx4+PnuTY1vy5jEACfqhD2ewn7VEI+L2G/StjvpSHgIxb00RDyEw348HsUfKpCQPXgUxVUWUYSBaQbIkMSBQQETNvCtGxM08K0LHTToqzpFDWdUkWnWNEpVDTShRKpfIlUvkgqXyJbqpAtlsmVKmRLFXKlCpV16t0xMpvmRx9coDMR5UBvO6JY3ef4wIFu/t7fewafr/Zc4k6fGuH3f/8NV1jcjRZvM/3BPi7mLqNV0QTvROoUz7c8i1f0rssKU8ksczZznopV3UrQlkCv430bbNtmuDDM8dQJ0nqm6v12RXbwza5fW1V3nL5gL9/s+gbCiMCJ9Kmq0qLGSxN8kDxOh6+ddr9bYFvvFMwCfzn6V3etqwjJQQ43HOSZpqfoDnSu6jhEQaRBjdGg1m9BrsvtlE2Nt2YuUHHAUU4UBB5MbKXbn9hwE+adkQ62hdoYKcxRWWHK2EhhnouZcQ41bMEvr299Yy0zmynw0ocXOXZ5dE3P61Vk4iE/jZEATeEQ7fEwbfEIrbEQrQ1hWmMh/J7lN3oUkVAkYAmN2G3bJpUvMZHKMZXKMpnMMn7j92y2wFymQDJfQjfXpp+RDZwdmeKH75+nKRKkMxGtar9w2FezkUxFkfB4NsZCrOPPwif56A320OJtZqS4+AU5ryU5n71IIhFHFtb2Rb2VBpU+U9X2siDTH+qj0eE0qLxR4EzmHIOFoar36Q308PWOr9CxBp2HW7zNfL3zK+SMPFfyVxfd3sbmQvYyp4NnSajxdS/Od1k5eaNwx2NBOcDjiSN8tuUzbiG1y7K4lpvmen7GETeoJjXCzkg7EY/fgZHVFooocaRxG8eT15guV7/4dDcqls6F7DijxXkGwu7Cz90oazofXB3l5VNXqBirP1n2yBLN0SDdjTG2NDewpSXOluYGuptihH3eqlfkVwtBEGgI+WkI+dndtRAtNi2L+VyRwekkQzMprk8lGZxJMjqbZjabRzdX14q8ohscvTjEtrYEXz+yB59ncaUUDq3/a3kvFI+MR3WFxT3p8nfQF9zCWHG8Kp/7o3Pv81DDISRBWlM1adomo8UxxkvVFUo3qgl6/F2OpnrYts1wcYQzmfNV94EIyyF+pe1z9AS61uT1EgSBDl8bX27/Ar9//Q+rssDNGTnOZs6zPbSN3mDPqo/RZW3xiioPNhzi+ZZnaVAb1ns4LnXKseR1RxrAAeyJdtITaNqwjnQPNGyh3dfAbDl7m0vacriam2IwP8O2UGvNruCuF7ZtMzaf4ZVTV5nJLF4ruhJCPpVtbQl2dDazo72JHZ1NdMQjS6obWC8kUaQpEqQpEuTB/i7Kms7QbIqLYzNcHJvlwtg016fnyZVWz0VrNlvgzfPX2dvTyt6exZ3O3IjF2rAqzyKiROgL9HDKc5qkllp0++v5QUaLY2wLbVvTAHbZqnAidarqJl99wS20+VodDbMXzCKXc1cZK45Xvc8jiYfYHdm5pl+goiCyPTTAE42P8aOJF6v6WruWv87F3GVafa143ajFhkESJLaG+niu5TOuqHBZNqZlcSY9QtlceRqUIkpsj7TT4tu4BclxNcjuaCeXchMUjJUVcc9VcowU5imZmpsO9SkKFY1jV8c4fnX1UqAifi97e1o50NvGA33tbGtrJOCtvbz/ahGEhVqQHR1NbG9vIre3zKXxWU5cH+fk0ATnRqZJF1bHUevcyDRHLw7R3RQj4r+/YUgo5KtZi1pFlvAotelYtVRWZWYqCiJbgr10+7uq2l63dY7Ov4/lUHOkarBvWFqezZyvavuA5GdLoIeYJ+roOKbLM1zKXUa3q/tybfE28VjiCKqornkesUdUOJJ4iA5fe1XbF8wil3JXmK3MrvLIXNaSqBLls83PuA3qXFbEdDnDaGGuKlOIxWjxRunyJ/BK9Ts5q4YHGrYQlJfntvZJTNtiuDDDTLk6i/XNgm3bjMym+cWJy+RXoV+FKks80NfO3/rsYf7h54/wW089wIEt7XUtKj6NIEDY7+Vwfyf/zdMH+Ueff5Tf/sxhDva1V5WutFTyZY23zg9yYXR60a7cofD61PJWw0aKWKzaknezt4neQA/+Kt2eTqROkdGza9au3bANLuWuVN3ZusPfTqe/Y0l+/IuOwTIYL40zXKh+ZeThhgdpUhvXJdwvCAJxTwOPNR6pep+FaNS4Yx11XdYXRVDYF93N7sjO9R6KS51zLjNK3nBmFbMn0FjXXbarZUe4nagn4MiS0mBhlsnS4hkFm4liRef00CRnR1buvvVJBAFaoiF+88kD/KPPH+HXHt3Hjo6mukh5Wgk+j8LOzma+8ehe/tHnH+Wbj++nMxFBdHhyf2Vijg+vjZMt3j+SFw77arjGQnJrLBbDI3roD/VxKt3CtcLiVq5pPcPpzBmeanx8tYZ0G7q1YHVbDQu9Inpo9znbrTSjZ7meH6Jg3lkYezciSpi90T3rmlakiAq7IztJqAnmKnOLbp/WMwwWhtgZHiDqcLTHZe0JKyGebnoCj7hxVthc1ocz6RGKK0zpgQVLzp5gE62+6IqPVetEPX76Q60M5WdW7A41XkwyXkpiWCZynXcod4rZbJ53LgyhOViwLYkCuzqb+fXH93NkoJuG0MYzF1iMgOrhgb52uhujbG1L8L2jZzgzPOnY61wxTE5cH+fxnb3sDXw8T9u5sx2vurAYLIoi4XDt2lArirxhIhar+ix6Al10B7oYKo5U1Zvh7bl3eSLx6Kp31LVsm5nKHFdy16ravsHTQE+gi4DDDd/mtSRDxeGqt98e2kZCja9rcaIoiESVKHsiu3ht5o1Ft7exuV4YYq4y7wqLOkcSJAZC/W5zOpcVY1gm1/LTjtRXBGUfbb4YAQdShGodQRDYGWnnzZnzKxYWJVNjrDhPVi/RoAYdGmH9opsmwzNpTg5NOHZMSRT4zN5+vvn4fvZ0t6DUaNfntSIeDvDs3q10NIT5zjunefXMVYqVld8DAC6Oz3JpfJbtHY145IWp7Qsv7KVUWji+KEIo5KZCrQWrOkMNSAG2BvuIe6or8BwpjHJ9CZary8WyTU6lT1O2qgvDd/k76PZ3OTqht2yLpJZiolR9yHVXZGfVqWWriU/ysju8o+oaj/HSBPNack1raFycRxFkHoofXnXh77LxmavkSGuFFbsbATR6wzSqYcfTK2qV/lArHocaj06W0qS06iLmG51socz7V0YWTaepFgF4fv8Af++FhzmwpX3Ti4qbqIrM3p5W/vZnH+QLB7fjV51JL8+VKpwammAq9bGTV1tbjL6+Jvr6mujtbUKu4fdAliV8Pg+qqqCqMqoqI4n16XC3qvJIEAQGQv20+9qYqaKAV7M0js6/R3+ob9XGZNs2um3w/vzxqrZXRZWeQDdN3kZHx1E0ikyWJimZ1XWcDclBOn3tjtZ4LBdZkGnxtRBX41WlQxWNIhOlSYpmiaDDUR+XtSOgBNke2rbew3DZAIwW5x2zmW3yhkl4Q44cqx7oDTbhc6hIfaqUJqO7wgIgWSjx7qXqMwgW47kD2/i7LzxMT9PGr/1ZKoIg0NvcwG9/5jCiIPKjY+coaSvv4n1qcJKxuTRdjdGVD3KNEUWBJ57YzpYtTXBjwaW319l551qx6nGXuNpAX7CXq/lr5Iz7e0JbWJxKnyGtZYh6Vs82cLgwzES5ut4VLd5megPdjueU580Ck+XqoxVtvjaCSrAmPNoFQSAg+ejyd1QlLGxsJsqT5PScKyzqFAGBvkCvoz1cXDYvo8U5Sg6kQQE0eyMk1LAjx6oHgrKXdn8DE6XUik0xpssZ0lrRoZHVL7ppMpnMMjKbduR4e3ta+bvPP0x3HU5w15L2eIS/8ZlDTGfyvH1hEGOFTfUmUllG5zNUdKMuC+Pb2qK0tUXXexgrZtVnqZIgsSM8QLO3qartM3qWj1InV208NjYfJD+squYDoNPfTk+g2/FxFI0is+XFJ+U36fC14RVrJ4dYFdWqbWcBZsqzd+3e7FIfiILI1uCWNbc4dtmYjBbmKTsUsWhQg0Q3YLfteyEKAt2BBLIDi0xprcC8lkdfYb1GvVOq6Jwfm17xxBagORrkv//io/Q0xWo2n7+WaI2F+UdfOEJfc3zFPSYM0+La1DypfHWZIC6rw5osf/cEuunyd6IIi6fx6JbOu/PvVz3xXyoVS+PD1Imqto0qEXoDPYQV58PsRbPIrFa9sGj1taDWkEe7R1JpW4JL1mxlnoIrLOoWAYEuf+d6D8NlgzBWTDpSuO2TPEQUP8omq/tp8zUgOSAsLGymS2ly+uo0L6sXChWNM0POWMz+zWcPs7urZdPU/KwUQYC+5jh//3OPOBJluDI5x3zOnWusJ2siLBRRYUd4gHgVXXptbCbLU1U7Ni2Vc5nzZPTqmgK1elvoC/Y6nn5k2iY5o0BWz1W9T9zTUFMWn4og0+CJIVb5EcobeTJGFmOTr4zVKwICbb6W9R6GywagaFTI6EVHetuEFR9hxbfpVoZbfTFHhAUsFNKvtJN3PWPbUCjrnB2ZXvGxHt7WxZO7tuBV5E33mVwJoihwZHs3z+7duuKoxdXJeeayRdaoJZrLXVgTYSEgsDO8gxa1uapUiqJR4r3ksVUZy3vzH1TlTiQLEp03muI5jWEZ5PU8dpWOKKroISgHq57ErwkCeEW16miOjU1Wz6FZznczdVl9ZFEmrGyePHaX1SOrl9AcWmAIKT7CyuZJg7pJqy/qmDtbRis6Vkhfj5iWxWy2QKawsvQZjyzxW089QCIccEXFMlAVmf/u+Yfxe1a2gJorlpnN5tEMdxFzvVizmWpIDjIQ7ickLz4R1W2d85kLpLS0o2PI6BnOZS9WNaFPqAn6gn1VpW8tFc3SFy1k/yQhOYRHVGrqZiUgoIgKEaX6Ivu8nkOznCnYdFlbwkq4toStS92S1guOCYuw7CW8CQ0FWrxRJIe+DzJ60ZG0tHpFN00mkpkVGx8/tK2L/tYEcp1ahNYC7Q0Rnt23dUXHsIGZTIGStnk/0+vNml0BgiCwL7qHRjVe1fZZPcfx5EfYDsazjs1/SMWsLuTb5m1hINS/KpN53dbJL0FY+GU/klB7DgeSIC2pr0bOyKO7EYu6JFAD/VNcNgZprehYsbBXUvHJtZMiulaEFK9j3bKzRonyJr4v66bJ+Hx16dH34/MHtxMLbr60PCeRRIFfe2wf4gpfwulM3rHGey5LZ02ldYevnd5gD6qoLrptySzxQfJDDIeKuC3b4t35Yxj24l9oQTlAb7CXBs/q+E8blkHRqN7izy/5kGuwOFESJPxy9WkIRbOIXsXr71J71EL/FJeNQUoroJlOCQsFbw2ZWqwVgiAQVvyOeLRltIWIRbWpuRsN3bAYm0+v6Bjb2hLs6GjCU8MN2OqFvpY4+3urd5y8GzOpHIXK5hXL682aCgtBEDgQ3VfVhN3CYrYyy4XsRUfOPVwYZbw0UdXNs0ltYkdo26qtPNhYVQmcm3hET030r/g0oiBWJRJvoluG2327TpFrMGLmUp9ktCK6QwtGXknBJ20+0SsgEFF8jtg/543yQo3F5tQVGKbJZKp6I5W7sb+3jZBPdaMVK0QQBGRR5NEdPSs6zmy2QMmNWKwbaz5bHQhvo8XbUlXhWd7Iczx1YsXuIbZtcyz5Ibq9uIKVBIlWXwu9gZ4VnfN+WDe6f1eLJEg1ecMSEJZUQGjYBhausKhLavDz51KfFM0KhuWMsFAlBXWTRtPCHr8j3wumbVEyNIxNuuhjWjb50vJXtwVgd3cLQe/mi5ytBpIo8mB/54rseosVbUU9SWzbvvXjsnTWXFiooof9sT2E5OCi21Ysjau5a1V1d77/cSqczpytKq83pkTZHurHs4rhdRt7SX06JEGqycZkgiAgLaFQzbANLPdCdXHZ1OiWgeXQ8rgqyqjS5oymhWRnIhYAhm1u2miybduU9eWvbof8XnqbGlCVzSlwnUYUBboao8RDy3d7qxgmprX8z7NhWMzN5RkfT5HLlTAdaJx4L2zbplzWmZ/P3/ZTLGpYVn3Ol9bljrwvsps3Z94mo2cXTU3KGFlOpE7xfMuzy16duZC9RFJLVZUG1agm2B4eWNZ5qsXGXlLYufYkxQICLMkpaEH91+eF4uLi4gy6ZTq2wCAJomP9HOoNRRQd+25w8j2pNyzbXpGDUGsshNcju0FdB5FEkZ6mGLPZ5TW6q+jGioRFMpnn23/xHqdOjXDk0W08cKCbtvYY0agfVXVWQNo2XLgwzs9+dgZN+3jx++GHt/Loo/0Eg15Hz7cWrIuwiKtxBkLbmChNUrLu3/Ezb+Q5lz3PE42PLqlQ+CaWbfFR6iRlc/HOol7RS3egk2Zv05LPsxRExCWlEJm2VZOFdba91MiLjOBalrq4bGp0y3QsxUAUhJqsP1sLnDT00C1z06ap2rZNWVu+mUBrLIzP40YrnEQSBboaYxy7Oras/TXdwFzmar9tw9xcjrNnxxgammNoaI4Xf3yCgwd7+NrXD7Nz58oKyz+NKAoYhsW1q9MMDs7eeryQL9PTk2BgoNXR860F63ZHPtTwAGHP4g23LNtiqjzDpdyVZZ0npWW4kr+Gbi++IhHzRNkd2bXqaUcLKURLEBY490XsJEtN6ZJFaUV5k/WKDUt6nVxcNjK6bTqWCiUK4qa8pwAoouxYOFu3Dcwa/I5ZC2ybFTVTa44EUZXNmY63WoiCSGusuua7d0MzrWVHLCzLYnY2x+jo/K3HstkS16/PkEotL4KyGG1tUfq2Nt/22NWr04yPp7BWEHlZL9ZNWPQGuunyd1TlNpPWMpzJnFuW9/mZzFly+uKODyIizd4mtgb7lnyOpSIiLqnxnm4ZNRmxsLDRl9DwThbkTdpkzXbMNtnFpd5xKu1GREBCrMn6s7VAcbD2buE9qb8JjHMs/3UMeD1uUzyHEQQI+ap3nLxj/0/8d6kUixXGx1Jo2u3f2b29TXR3J5Y9pvsRj4fo6mxAkj4ecyZTYmI8RbFYf7a563Y1yKLM4dghfNLi+WNlq8xgYYjp8vSSzqFbOmfSZymapUW3DcoBtoe2EVhGutVSkQQJr1T9RVM2yzW54m3aJqUqUsxuoorqkiI1GwXbZkn2wi4uGxnLodROQRA2dV67k5Eay7ZrcvFqLRAE8MjLnwp5PTKiKywcRRAE/OryDXRkSURcZpe9fL7C6Nj8bY8pikRnV5ympsWzbJaD16vQ3BwhErl9/jk2liSTqb7nWa2wrlfDrsgOGtXGqlZd5ipJzmbOLyklaKI0yWhpvKpJXcwTZU9kV9XHXgmKKBOQA1VvXzRLNbnibdpmVaLtJgE5sKRIzUbAtm0srKo7vru4bHQkwZkog2Xbm7bgGFixDfsnceo9qUcEQViRo5OqyEgrbRXtchsCrCi9zCMv/z0plzRmZ27vxN7QEKCtNYrHs3opbw0NARobbxcuMzNZcrnqF29rhXUVFmElxIHYXjzi4so0Z+S4kr9Kzqi+kc3p9FlyRn7R7TyiQpe/k3Z/W9XHXgmKqFRlt3uTgpHHWEYa2GpjWCb5Kl7fmwTlwKbs4FwxK27EwsXlBopDtVY2C8KiFuvP1gLDNh2LMiiCtGmL4EVBWFEPCldSrA4rua79qoIsLe/zXKkYd9RSxBMhGlcpWnGTUNhHLHZ7xCKVKlByU6GWzuGGg1VNsk3bZKI0xbX8YFXHLRhFLuWuUDIWDyMFpCD7onuW5NS0EhRBISSHql4hKhhFSmappnJgbdtGtzQyenbxjW8QkoN4NpmwsLHJG6tT8OXiUo84JSwALCzHCsHrDcMyHXPvlkUJaZPmlUmiSMS/fEtP3dy8Vr2rhQ2U9eUvxgW9HjzS8uZzmmaQydyeiREJ+4lFVzdNPhBQCYV9tz2WzZYo12EH8XUXFq3eFraF+qua1M9X5rmYvVxVEfdgYYjpygzmIhZ6AgIJNc720Or2rvgkkiARVIL4Jd/iG7Pw5ZnWMzW16m1hkTcKlKtMhZIFmbAS2nQRC8u2SGnp9R6Gi0vNoIgyTnVgMG3b0ZSgekJ3qHs53HDsW//pwLogS+KKmrFpholdp43MahbbprICYRHxe/EsM5XKNC0qn5rMBwIeAsHlF5NXg9er4PtU5Kxc1tH12kuDX4x1v5OIgshjjY9UlXtfssoMF0cWLeK2sTmbOU+2itV0r6SyPbyNSBXWt04hCAIByU9Crd5hYKYyS8WsnZCYZunMVGarXjALKyFCSmjNokK1goXFnDa/+IYuLpuEhYiFM189pm1tWmFRcdAt0MkoUr0hSyLN0eVbm1Z0c9Na9a4WFlCoLH++0xDy41tmPYRl2Xc4QsmKhLLKlsKyLKF4bp8f6bqJZdbfZ2vdhQVAf3Arnf7qmo5Mlae5nLt6323SWoahwnBVjkUBKcDB2IGqzu0kAdlP4xKExWRpkopVOwXAmllhvDRR9fYJNY5fciKUKCypyHC9mz5ZtsV0eWZdx+DiUkt4RNmxSaxmGWhm7URy15KCUXYsCcxJsVdvKJJEe8PyFxazxTKGWX+ryrWMZdnMLbPrNkBjJLjspoU2d9Z32JaNtRZRqU+dwrKsukyzq4k7iVdSeST+UFWh2LSe4Xph6L5561fz15jT5hddzZEEiU5/R9WixkmCcoBWX/PiG95gtDheVffwtaJsVRgtVt8Vs0ltIrgEJ6x7ISyx065pr28PENM2GVvC6+TistEJyl7HukZXTI1yDUVy15KsXnKkcF0SRLyigrRJhYVHluhpji17//l8kUodpqvUMpZtMZWsvn7z07TFQssuyBdFAUW5/f5U0Qy0Va510HUT7VMd4EWxPhuA1syd5FDDAcLK4qsGpm0yXpq452TNsi0u5a6Q0TKLHksVVQ7E9lflSuU0fslPm7cVVawub2+uMsdsZa4m3KEs2yKjZxmrMmIhAO2+1qre38UQEZeUTlUy1q/o3bZtymaFidLkupzfxaUWiSp+FIf62ZRNnfISmnRuJLJ60ZFFE7+s4pM8dTmBcQJZEmmJhZc9EZ3PFlbUudvlTizLZjJVvQPoJ/EqMi2xEN5lRixkWcTvv/2zUCpqFFbZnalc1iiWbj+H16sgKzUzTa+amhlxVIlyILavqm2ny9NcLwzddbVmvpJkrDheVdpQWAmzP7p7yWN1AlmUSahxmr1NVW2v2wbX8tcp10A6lGZpDBaGKVVZuB1WIjR7m6sWUfdDEkQUsfpcx5yRX7fmghY2Q8URSlbtRJpcXNabqCeAZwnX8P0omzplc/MJC8u2yOnOpEKFZR+qtLlMNT6JIAiEfCpbWhqWtf90Or8iByOX27Ftm7JmMDqfXtb+bQ1h4iE/0jKbFno88h2N6ubn88zOLj+CUg2pVJG5udvFVDDoRVXr79qsGWEB8HjiCBKLr2TljQKjxTHSevqOv10rDDKvJRe94cqCzM7wdqJKdFljdYIGTwM9/q6qtz+VPkuxBqxLi2aJU+nTVW/f7msj7mlwZEVMERW8YvXWgPNasioXsdXAsk3OZs6ty7ldXGoVJ4VFydQpGZsvFSqvl9EccoUKKz68m1hYwELfg12dLcvaN5kvMZvJo7t1Fo5g2TaD00nypeVd173NDcSCy6/n9Pk8NDVHbntsejrDxHhqVXvmzMxkmRhP3fZYPB64I3pSD9SUsOjwt7M11LfodjY2E6VJxooTdzx+vTBIugp7T4+o8HD8MMI6hn9jnihbgr2oVaZijZXGGS6Moq9j6N+0TabLM1xZpID+k/QFe5ZUqH4/FNGDX67+pjFVnkK31/71sm2bilXhVKp6AebishlwUljkjRI5o7rI6UZippxxzA0rpPjwbjIb8E8TUD3s7WldlgmyaVlcn05R1tyohRNYls3p4cllR+O2tTXSGF5+PWcw6KWz4/boVT5f4eLFSSYm0ss+7v1IpQpcuTxFMnn7wnFLS5RwuLq2BLVEzQgLQRDwiAqPNx6pavup8jSjxbHbFOR8JclEaXLRdCEBgVZfK33B3hWNeaXIgkyHr50uf2dV2xu2wdtz71KsMgVpNSibZY7OvV91Slbc00C3v4vAEsTA/fCKniV1LR8sjFA21yd97HzmInNacl3O7eJSq0QUv2OpN1m9RFbffMJispx2TFgsRCzqb1XUSTyyRE9TjPZ4ZPGN78Ll8dkV2aO6fIxpWRy7OrqsfWNBH1uaG1bUST0c9tK3tQnpE527bdvm1KkRzpwZxTSdrdm0bbhyZZoPPrh+x7F7ehtpaKh+vlMr1IywgIXC3D2RXcQ9i+c6lswS46UJ0vrHRdojxVGSlcUncpIg8WDDwXUp2v4kgiDQ5ltoEFgtZ7PnuZa/vi5F3JZtMVGe4oPk8ar32RLopd3X5piVoV/yE/NU7+CR1tKMl8bWPMpj2iYvT7+6ro5ULi61iCyINKphR6IWOb1EZjMKi5JzwqLBE8Qvb25hIQgC8ZCfg33Lc4j86Po42UJ5VVNlNgO2bTOVznNqcHmGJwPtjXQkIojLrK+AhX4S7e0xuntuz7KYT+Z56aVTnDkz6uj7PDw8y89+dorR0dv7XTU2hujqiuPz1d+1WVPCQhAEglKABxsOLbqtDUyWp5n6RLO84cIISS11751u4JE8PNRweCVDdYyAHGBbqJ92X1tV22uWxo/Gf0LeyK/pTczGpmSW+dH4Tyiaxar28Uk+toe30eyt3lZ3MRRRIaKEq66zsLD4KHVqza16T6ZPc60wuKbndHGpBwRBoDMQdySvv2RqZPXiutVRrRdTpZRjwqLJGyEk11+6hdPEgj6ObO9BlpY+LZrLFrgwNrOibtEuC/O6185cXXYx/P6eNjoT0RWNQRAE2tpiHDp0e0aLbdlcvDDBn//Zu5w9O7biyIVt24yOzvOd77zPe+9eveN4e/Z00tOTQBTrz62tpoQFLLglPZJ4qKpO3NOVGabKU8BCQfdEeYpCFZPe3eGdxDzRlQ7VEURBZGtwC3siu6rO7xwsDPPz6VfWtHbAtEzenj3KmSUUIw+E+tkW6nfMsx4WLvqIEqbRW33NxvHUCWYqs2tmO5vVc3xv7IfrWgvj4lLLdPkT+BxIv7GBZCVPWqtusWOjMFiYw3DA7c4reUiooU1fvA0LjfK2tDSwp3vpRdyWbfP2hUFypfV3baxnDNPkxeMXlrVvVyLK9o6mFaVB3SQaDfDAAz10dcVvH59hcfLkMP/rv/0pP/zBR2Qyy7vvlMs677x9hX/zb17ktVcvUKncLqSiUT+HDvXS1hZd7lNYV2pOWAgIJDxx9kR3LbptVs8yXZ6lbJaZLE1WlQYlIHAk/lBNdRkNyUF2hXfQWWWthYXFzydf5oP5D9dksmzbNhdzl/nu2A+qtm71S352R3bS6Wt3vEC+wROjzdta9fZls8xPJn9etT3uSjAsgz8b+TaTNwSvi4vLnXQFEo7l9c+UM8xXlud5X4+UDY2x4pwjEYsmNUTU419XE5NaQRAE2hoiPLu3+tTkT/LW+UFG59KY1vr0TdoIvHzyCkMzi2ed3I1DWzvY3t7oyGdZFAW2b2/jM8/uQpZvXxg1DIvx8ST/5b+8xj/9J3/Kt37/Dc6cHqVQqNwzi8S2FxrgXb8+w/e+d4x//j/9Of/6X/+ISxcn72iKB3DkSD/7D3SvKKVrPXHGmsNBBEHAJ3l5LPEIJ1InF81Qn6nMMq8lGStNVJUG1eBpqEq0rCWCILAjvJ0HGw4yU56pqjBatw3+6/CfoIgyhxoeWFLTuKWw0HDwMv/x6n+hvIR+DPuie9gf3bsqAi7uaaDT384HyeNV1zAcT35Ef3ALzzQ9jUdUHP8itW0bzdL5i9G/5Fjyo3XrneHiUg90BRL4HRIW0+UMs5Us21lefny9cb0wQ9Ehi91mX5SoZ/kOOhuNgKpwYEsbu7taODuytMWhkmbwV++do7c5TjTgdcXaEinrOn/wyjGMZaQYNUeDHN7aSUss5Nh4gkGVp57awfhYipdfPnubaLBtqFQMhofnGBtbSGdSFJnWtiixqJ9AwIPPp6JpBoVihWymxMREimJRw7JsLMvibhpEEGD//m6ef34PTU3huv0M1ZywgIXi6i2BHrr8nQwX7+8OMFeZY64yz1R56rZC7nvxaOJhZKH2nrZHVHiw4RCjxTE+SH5Y1YS5Ylb4T9e/RUpL81TT43hEj2MT+YWJssbx1An+eOjPKZjV98/o8nfycPwwTaozqwefxiN66PJ30uptYaJcXZGXjc23R/4Kr+TnkfiDqKLHsbEZlkFGz/DnI9/lo9QJdNvNs3VxuR9+yUObP8bV/BT6CvsxzJQzzJaz2LZdt1/ES+FKdgrNoZqSFm+UqOKMY99GQBAEepsb+MKhHVwan0Ff4iT3Fycu8YVDOzi8tQNZ2vifRacwLYs/e+Mkw7PpJe8rCAKPbu/hQF+bo9e/IAi0t8f4+q8eplTSePfdKxjGnZ8H07QxTRNdN7l2dfouR6oOURQY2N7Gr/36w+za3VHX97KajLMIgoBf9vNw/KFFt03rGUaLY8xXUhiLTOgkQeKh+GGEZblVry6CINDqa+GR+EN0+TuqHqNu6fzF6Hf5j9d+n5HiGCWjtKLVcsu2FlLLylP8yfBf8PvX/+uSREVACnC44QF2R3au2oUhCAIdvja2Brcs6b00Mfmvg3/MixMvkTVyKyr4tG0b3dLJ6Xk+TJ3g313+PzmW/NAVFS4uVSAIAjsjHfgldcXHyhllJktpCutkK72W2LbNhewYFQe6jQsItPsbiHnqz85yNfGrHg5tbefhge4lzxQqhsnv/vQd5nMF1yGqSmzb5szQFH/0+odoxtLnLt2NUY7s6KE1FnZ8bIIgsHVrM3/jtx/nmWd24fd7WI1pjarKHDjQzd/6W09y+PCWuhYVUKMRCwCv6GVPZCc/mwqT0e/dSj2vF7iaHyRTRbRie2gbzau0iu4U+2N7SWopfjL5M+ar7IFg2iYfpk5wMXuZI4mHeDB+iGa1EY+o4hEVZEG+53O2bRvTNtEsHc2qMK+l+Ch1krfm3ialLf6afhKP6OFww0GeSDy26la+CTXBjvB2zmbPV5UCdxMLix9N/ISz2fO80PJZ+oN9eCUVj+hZ9HWybAvd1tEsnaJZ5Fp+kLfnjnI5dxXNundqgiIoeETPkgSai8tGZ1+sm4CsktFXXng9WJhhspimP7y87sn1QsnUuJAZo+KAMURcDdLhb8C3ya1m70ZvUwNfPLSDi2MzzGaXdt8+PTzF9949w3/79EECqnOR8Y2IbdtMp/P8+xffIlNYunOjqsg8tXsLD/ZXV5+6XHp6Gvnv/u7T9PQkePnls0xNZSiX9RWLR49HpqEhwJEj/Xz5Kwfp6Fi81UI9ULPCQhAEop4IB6L7eH32rXtup9s6F7MXFy1kExB4JP4QUg2mQX0SSZB4NPEIaT3NazNvkjPyVe9bMAu8PP0qb8y+TW+gm22hrXT7u2hUE6iSF0kQb63w2yxMlCumRlJLMlIc5Ur+Gldz1ygtoZbiJrIgsyu8g880P0WDWn2fieUiCALbQn3sCu/g6Pz7S4rS2Nhcy1/n/776n2n3tbE7upO+QC9N3ibUG+lkn36ddEsno2eZKE0yWBjmcv4KyUoKi/t/7hRB5oHYfnoCXXx79Hsres4uLhuJbaFWYp4gk6X0ivu9DOZnmCgl2Rpq3tATufPZcVJa0ZHuOD2BRlq9q3+vrkcUWeJgXztfOLSDP3/r5JJtZL/1yjE6E1Ge378Nj1Lbc471wrZhJlPg3/3oTc6PTGMtcZIuCgIHett4es9WIv7q7OdXQiwW4Nd+/SEOHd7CK6+c48RHQ8zP5ykWNSoVHctafPyCAIoi4/d7iER8DAy08tnn9rB3b+cdReL1TE1/4gNSgAOxfRydf/++K8LVWMxGPWF2RXYi1ZAb1L3wyz6ebX4GzdJ4Z+69JYkLWOh1cSl3hUu5K8CCWAnIAQKSD0VUAAHd0imZZfJGftEUssVQBJltoX5eaHmWnkDXio61FBq9jRxsOMBwcYSR4tiS97ewGC2NMVpa2FcWJIJykIDsRxZkbBZSzcpmmbxRWLK9r4BAV6CT3+j6Omk9i4i4qBBxcdkseCUPu6KdXMtPUV5has9kKcVYcR7NMhzr6l1r2NicTA5SMJzpydMdaKTFF3XkWBuRxkiQ5w9s4/rUPEcvDmMswe1JNyz+7fffIBbwcbi/E9UVF7dh3YhU/N7P3+PNc4PLSoFqawjzwgMDy7IHXi6CINDX10RfXxOzs1nOnR3n3PlxhgZnyWZLaJqBYZgLBdq2jYCAKApIkoiiSPgDHtrbG9i5o409ezrp6o7XrfPT/ajpT7ssyrT5WukP9nEuuzxv45s8ED1AUK4fW72YJ8rnW1/ABt6de5+ssXw7RdM2yepZsvdJKVsuiqAwEOrni22fY2dkh+PHvx8CAjvDO5iMT5HRs/dNmasGwzZJ65mqTACqodnbyNc7vkxCTWDaFhElTEpPO3Jsl+Xj5B3AvrHWXh93ldrjgVgPL0+eWrGwMGyLi9kJpsppugONDo2utigaFU6mhimaK3eE8koKXYEEMdWtr7gfA+2NfP3IHmYyeS5PzC1pVT1TLPP//ctX+GdfepxHt/cQ9K28nmgjoJsmg9Mp/ui147xy+iolbenXftjv5bkD23hm71akdZqYNzaGeerpME89vQPTtEilCqSSBbLZEuWKjmGYiKKIR5EIhrzEYgHi8RCqWtPTbkeo+WcYkcMciO7jYu7ysouSFUHhUMOBG6v19UPME+ULrS/gET28O/c+SS2J5UgQ3Bm8opddkR083/IsO8ID6zIGn+TlkfhDpLUMb88drSp6tRbEPQ18ue2L7InsBhZSxVq8za6wqAGcdIUzLMuVFitgb6yLBk+QtFZY8Z3tbHqUofwsnf54TfUpcopTqWHGivOO9K/o8MXp9MeRN+Dr5CSSKPJgfyfJXJE/eOU4I3PpJe0/lcrxr7/3Gn/nuYd4YtcW2mLhuuyk7AS2DZliifOj0/zR6x/x4dWxZUUqfB6FJ3b28uUHd61JClQ1SJJIIhEikXDO7raeqfm7ilfysjXUR5O6/FWo7kAXHb6OVev1sJrEPFF+pe1zfK71Obr8XTVhlSsgEFOiPJp4mG90fnXdRMVN4moDzzQ/ySPxBwnJ678C1+pt4Yttn+NI4uFbjymiQou3eR1H5XITVZIckwGaZSw5N9jlYxJqmIMNW/CIK7+vTZRSXMxOkNOdSRWqJQzL5OjsZdLayg0gBGAg3MqWYNPKB7YJ8KsePrO3n288upe2hqU7DyXzJf6PF9/h937+HsevjZItbrzP52KUdYMrk3N8790z/P++/wbvXxpZlqhQFZlDWzv4xqN76Wly64NqlfWfpS6CIAjEPTH2RfcwObW8bsaHGx7A64Ct4Xrhk3x8pvkpEmqCo3Pvcj57ccl1F06hCAq9gW4ONjzAY4mHCSvOW7wthzZfKy+0PocqeXl//hhJbfHCaqdZ6L/Sy2dbnubBhkO3rZoqokKLb2M71tQLqoORy4JRxrBNFOpv0aJW+EzLHl6eOk3lLh1ol4KNzYfz1ziS2MZupbNu0l6rYaQ4z5n0iCNpUGHFx0C4nWZvxIGRbQ4iAS9fOLQdw7T4y6OnmUguLe22pOm8ePwC50an+cLBHRzsa6e3uYFwjay4rxalis7YfIZzo1P88tRVPro2TqGyvM+wR5bY29PCbz55gH09bQ6P1MVJal5YAISUEDvCA7wz9+6SJ9QRJcKO0MCq25+uNpIg8UBsH13+do7Ovc+ZzDmGCsNVdel2AhGRNl8rA6F+Ho4/yLZQP2KNfXE3e5v4fOtzNKoJPkge53phiLK5NqtDjZ4EA+F+nml6ki3B3juiY4og0+J1VwhrAVVUFuw5HIg0pPUimmngc6iL9GZkV6SDLcFmTiQHV5zqeSE7wan0MD3BJkLKxpi0GZbJL6fOMFGq3lb7fmwJtrA90oYkumJ4KcRDAb784E5EUeB7R88wNp9ZUrTStGyuTs7zH3/2Lts7mnhi1xZ2d7fQ2xQjEQ6sW62A05iWRbpQZmQ2xcWxGd67PMrJwXHSy7CTvcmCqGjlv33qIA9t61qVXhIuzlEXwkISJFq9LQyE+jmeOrGkfXdHdhDzxDZMzm1CTfCFthfYHh7gdPosF3OXGS2OUVyl2gJFUGjztdAX7GNPZCc7w9vxy7XbqTWshHmy8XE6/R2cSJ/iYvYyY8WxVRFgAgINnhjdgS72R/byQGwfYSV815VSSZCIeWL4JC+lNRI7LnfHI8r4JI8j7jqz5awjPQU2Mx5J5tmWPZxNj674taxYOm/MnOdArIedkfruXnuTwfwMH8xdIetAvw9FkBgIt9LrpkEti3g4wFce2oVfVfju0TNcm5rHWGJ37ophcmpokovjM/Q0NbCvp5Wdnc30NjXQHg8TC/qRpfqarximRbpQYiKZZXAmyeWJOc6NTHF1Yo5ceWVRNlWWOLi1g9968gEeGeiuuQVNlzupC2EBC7UGuyI7OZU5i17ll48sSOyL7qnpifBykASJbaGtbAn0cK0wyNXcNYaLo4yVxpmrzFMySys6vldUafA00OZrocPfwZZADwOh/rp5HWVx4fXp8newO7yTK/lrDBeGmShNMVuZW7Jt7KcJSgEavQk6/Z1sDfYyENpGk9qIfJ88cUEQ8IoqCU/ilr2ty/ogCAIJNeiIsBgvJSk5kJ6y2XmscTvfGXmXwfzMio91ITPOB/PX6PDHiXjq4551L0qGxitTZxkuzDli29Hqi7Ir2klY8TlwtM1JNODjC4d2EA34+N7RM5wcnKC8xD4XABXd5NL4LJfHZ4kGffS1xNnS3EB3Y4yORITmaIjGcIBowIss1U50ybZtdNMilS8yly0wmcoxkcwyNp9haCbJtcl55nPO9FrxeRQe39nLrz+2j4N97RtioWAzUDfCQpVUuv0LRdiDhcGq9mn3tdHl70SpgYLn1UAWZQZC/fQH+5jXUowWR5mpzDJbnmNeS5LVc+SNPAWjgGbpGLaBaZsICEiihCzIqKIHv+QnKAcIKSEaPDESapxGNUG7r41mtWmhYVwdXtBeacG1aiC0jenyNBPlKabK08xW5khraTJ6hoJZpGSWqZgVTNu45bgiCRKyKOMRPQQkH0E5REQJEffEafI20uJtpsvfQVgJVx0NCyshPt/6HLOV+XtuI4sSvcFuR57/YuyN7CYoB6rKCGrybhwLTwFoVMMMF+ZWfKyh/Aw5vYRt23V5jdQKzb4IX2g7wP995eUVux5plsHPJ0+yI9zOwXgvigOF4evFidQQ78xedCRaIQsiu6Nd7I123WoA6rI8AqqHZ/ZsJRHy8+LxC7x25hrJ/PIW9GwglS9x/OoYx6+OEVAVWmJhWmMhmqJBmiNBGsNBYkEfkYCXaMBHxO8l4PXgVeRVu+8Ypkm+rJErVW79pPIl5nNF5nIF5rMFZrMFJpJZptM5Siuskfo00YCPLxzczpcf2sVA+8b5/tkM1M0dV0AgIAdoUhNVC4t90b33TE3ZSIiCSKMap1GNY9kWJbNEUkvfEhVFs4hu6Ri2+bGwECQkQcIjevBLPvzygriIKVH8sn/DpI7BwmS93d9Gu78Ny7bI6jkyepackaNoFimbFTRLu1NYCBKK6MEneQnKQUJykKgnil/yLev1CcgBHms84vTTWzZ7o7vZG9293sNYF5wqXJ0tZxktztMfat2wjdnWihfa9vPj8Y8YLsyu+FjX8zO8OP4hnYE4bb5YXX4HjBeT/GziJEMORStafFEOx/to9kYdOJqLLIk80NdBYyTIluY4f/jah8xkVm6qUqjoXJua59rUwgKUIkkLgsLvJez3EvarhP1e/B4Fn+rBryoEVAWfR0GRJGRZXPgtiXet27Bsa6GB240mbqZloxsmZcOgrBlUdIOyrlPWDPJljUJZI1+ukC9pZIplkvki+VJlVY3vQz6Vv/PZB3lu/zaaonc6Pdr2Qi1HWdMpaTolzaCsL4y9ohvopolpWU6U0a0r/W0JWqL1Z2FbN8ICoGDkmS5XFyoPyUG2h7bhlzZXyFcUxIUu23JgvYdSk4iCSNQTIepxHVE2K4IgONZEzcTmo+Qghxr6aHSFxYpoVMN8ueMQ/8ellxw53jtzl+gLtfD1rgcJK/WVEpXTS/xi8hTHk9ccqeGRBZFdkU4OxfvcHHWHMC2LTKFMoayRCAdQ5dWZTummyVy2wFz2TqthQRDwKhJej4Iqy7fEhCwtZCVIn+qZYWNj22BZNra9ICws28YwLTTDRDOMG7/NJdeOOElA9bCvt42JVJYrk3MUyhqFyoLIufnvkqbfEEEmmm7cGr9uWhimiWnb1FDbr2Xxd59/2BUWq0nZrDBSHGOiNFHV9v3BPpq8jXXZu8LFxWX1EBAYCLc6drwP5q/y5Y7DxNXghor0rQfPtuzhx+MfOlJrUTAq/GDsA5q8YZ5p3o1Prg/nLs0yeGPmAj+bOMl8JefIMVt8UR5O9NOo1oY9eL1R1g3mcwWmUjkmUzmmUjmm0zmS+RKZYplsocxsdu0t4G3bpqQZjqchrTeZYpnf+ck7t6IQn4xGlHUDTV8QEBuddGFl9bLrRd0Ii7SW5kL2EloVhbcCAnuiu4nUSI8FFxeX2kEAeoPNKIKEbi+9SdOnmS5leGf2Il2BeN2tjNcSgiDQ6A3zmz2P8a/P/QDDgQ7Tk6U0fzz4FjFPkMPxLTVfb2HYFu/NXeGvRt9npDjvyIKrR5TZG+3mwfhWN1qxCJZlU6hoTKayTCaztwqTZ7IFMoUS2WKZbLFCtlQhX66s66r+Rqak6bx3eWS9h+GyTGr7LnsDy7aYqcxyMXepqu1bvS10+ztRxfptiufi4rJ6hBQvXYEE1/LTKz6Whc1LEyd5ML6VPdEuZLc/wLIREXiscTtPN+/i5akzjhzzen6a/3TlZSw+w0PxfpQafX90y+DduSv86eBbXMpOrLiI/SY9gUZeaNtPXK2/lIq1ZGw+w3/+xfvMZQvkbgiHfEkjV65Q1owl9axwcdnM1IWwyBsFruSvktWrCwvvDG8nrsbrsmDPxcVldREEAVmQONiwxRFhATBZSvFnQ+/wz3fGSagh996zTARBIOrx882eRzmbGWWylHbkuBez4/yfl35GuU/nqeadNSf+KqbO27MX+ZPBt7icnXQkkgYQ8wR4qnkX+2Ku//9ipPJFfvrhRTTDmdfexWWzUhcJwWktzen0WewqAsNe0ctAuJ+w7K7OuLi43B1ZlHi4cZtjx7OB9+eu8MeDb1IwK1Xdq1zujoDA1lALf63nMUSHbFFtFhrN/c7ln/GH19+gaDjfMHO5zFdyfHfkfX7vyitczE44JipkQWRnuIMvtB9wO8NXgWXbrqhwcXGAmhcWmqUzVhpnpFhdU7EtwR5avS1u0baLi8s9ERHoD7bQ5GAxa9nSeXH8I/7L1VcoGhVsN3ViWQiCgCoqPNm0k2da9jh67IlSir8Yfod/eeYvuZabcvTYS8WwTC5kxvmdSz/jjwbfYKgw61j6E0CbL8ZXux507WVdXFzWlJpPhcrpOU5nzmHY1bke7AhvJ+GmQbm4uNwHQRAIKl4ea9rBX42+79hx80aZH44eZ6ac5R8PfI4Wb8S9Fy2Dm4Xcv9X7GBPFec5nxx07dkYv8c7sJQbzMzzTvJuvdh6mxRdz7PiLYdk20+U0Pxr7kFenzjBZTlM2V24p+0lingBf7DjkFmy7uLisOTUtLGzbJqWlOJM+W9X2TWojvYFu/JLrzOLi4nJ/vJLC8617+dHYMUcciG5SMCu8MXOe67lpvtnzKC+07Xeb5y0DUVhIifo7/c/yr85+n5lK1rFj65bJcGGObw8f5fWZ8zzTvJtnWnbRF2xZtYm4YZmMFef5xdRpXps+x2QxRcnUHE+a80oKZniQrAAAC9RJREFUjzft4Fc7H8Lrfu5cXFzWmJoWFgWzwIn0KbJGdUXbO8IDtHpb3BVCFxeXRRER6AwkOBTv4725K44eW7dMBgsz/IdLP+V7ox/wfOtenmreRbu/wdHzfBIbG9O2SGsFZspZZsoZZspZpkpppstpVFHhc237OZzYumpjcBIBAUWQOBDr4W9v/Qz/7uKLjq/sF02NofwMf1J8ix+MHWNbqIWnmnexP9ZDpz++4iJvy7YYLyb5KDnEmzMXOJMZoWxoVCx9VapwJEFkT6STv7f1WQKy64ro4uKy9tSssFiIVmR4e+69qrb3ST62hwaIq6v3xe3i4rJxEASBiOLja50PcWz+mqP57bBQMFwwKlzKjnM9P80fXH+dLn+C/bEetoZa6A4kaPJGCCs+5Js1YQK3usVa2OiWScnUKBoVCkaZnFEmq5fIakVSeoGUViCp5UlWcsyVc6S0IoZtYrPQUfeTv3sDTTzetMPR57jaCIKAT/LwRNMOZipZ/uDaa6vyPlUsnUpF5/1Kng+TgyiiRKMaZkeknS3BZtr9DbT7GkioIQKyikeUEW4UltufeJ/mKjnGi0nGS0mGCrOcTg0zU85g2BaGZWKtYlG/AHT54/yzHV8k7jqTubi4rBM1KSxs26ZklvggeZyklqxqn53h7XQHOhFrvx7dxcWlRpAFid2RDp5p3s3LU6dX5Rw2C92UNcvgbGaUc5kxBBYmzQIgIKKIEoooIQgLOfimbaFbJtaNSbR92/HsWw/YHz9SxTjsTx2pPhAEgZgnwFc6DlMyKnxn5F10a3XceyzsW+9VwZhluDC7ICCEhQjKzam6JIiokgy2QMUyboidm6/wwvtz699rgAB0+hP8iz2/ypZgsysqXFxc1o3aFBbYTJan+OX0q1Vtr4oedkV2uGlQLi4uS0IQBGJqkK93PcQH81fJ6MVVP6d9c7p5yzXKQjcNcJ0u74kgCDR5w/x69yPolskPx45Rsaoz9FgJnxQKnxRlhm2tyfmrYUFUxPn/7Ps1dkY61ns4Li4um5yaW963bZusnuOnk78gbxSq2md7aBtbg1v4/7d3b79xlHcYx7/vnPYwe/T5ROzEru2cTDgECkmrBgJF9KZIkUpL71B733+AP6UXvWgrtahc9Ko3pRJSBYQoIJIQaIgT5+Q4trNre2d3dmemF3ZDVVVg2DVek+cjrTw3431XI83omff9vT/H6sqcJCJdzDYWU/lBfjFxAk/3kK42lCnzy/0/4JVHniZrq4bgi1DxM4UKEekKXRUskiQhjEPeWz3L2ZUPtnVO1s5wpHSYsczoDo9ORL6rCm6WF4bnONk/i2266rYo/2MoU+K1iROc2fc0JdfvUAu9vccxFvtzA7wxd4aDBT3/RKQ7dM3ruSRJaCUtLlYv8+bCW9sqcjMYZgszHMzP4FraVk9EvrnhTJmfT5zgdrDK5bVbxGpw17UGMyVemzhJ3s3wl4X3WKxXOl7U3c0ytsdcaR+/mX2Z/aqpEJEu0jWv5sKkycXqJX537ffUomBb55S8IsdKRxnL6m2NiLTHNhYHi6P8aur0Zj+Dh/Zd+N5QTuU4s+/7vD75HDOFEVIPyTK2Hi/HSyOP8sbRMwoVItJ1dv1OHCURy40VLq99yp8X3mKlubqt81zjcLR4hMOFQ9imvb3GRUQAPMvhyd4DvB6f4rdX/s7n64sdbZ4nneU7KV4eeYzBTJE3r7/LuZWrVJu1Pbj31VdzLZuxTC8/GX2MVx55ipyTVqgQka7TdrBoxRFBFJCQkLI8XMvF+pI1ypt7fjeptQIqzQp3G0ucXTnH+ysf0Ey2v8vGWHaM4z2PM5Dub/cniIg8kLZdnu2fwTE2f7j2DhcqNzremE06x7YsnuqdYjhd5q+3zvGPxYvcqC0TdsmuTZ3QnyowV97HT8eOc6w8oU7uO6CQSXPy4MRuD0PkgaFSfreH8I2YJGlvIfH9sMK51fMshysU3AJ5J0fK8rCNjWWszQ8WMTFREhHGTSrNCkuNe3y+Mc/V9as04vBrfWfJLfLS0As8P3iKtHYGEZEd0IojPq4s8Ob1d3l/+Qor4fpuD6ktk7lBfj31PKeGjuz2UHZMEIW8e+8z/nb7I86vzrPSWN/RpnQ7LWt7TOaHeG7wMC8OP0qfGt/tmDhJiCLNTkr3sC2DZXVNxcK2tT1jEUQBH1Y+4tzqhwBYWHiWh2e5OJaDYxwsYz0IFUEUEH7NIPHf0laaY6U5jvc8oVAhIjvGsWweLY3T6+XYnxvg7cWLXF2/SyPW7EW3ytgePxo8zHR+hLfvXuCfS59xqXqDtWawp+JF1k4x7vcxVx7n9NBRZgsjmqXYYZYxWI6WVYu0q+M1FjEx9bhOPa53+l/jGIfp/BQ/7D+hJVAisuOMMTzi9/Hq+AlmC6O8vXiB86vz3AxWdqz7s7RvJFvm1fETPNkzyTtLn3B+dZ5PKjepdHn9he+kOJAbZK60j2f6pjlUHCPnpnd7WCIi27brxdvbZRub/f44pwdPMZk7sNvDEZGHSNbxeLZ/munCMOdX5nl/+QoXKgtcr93bE/UXjrEpuBkyjrfbQ/nWWMYwXRhmMj/IibUZzi5f4ULlBpert7hRW/lP//Nd5xqbgXSR/bkBZgojPNlzgNniCL6jQCEie8+eCBa2sRnP7uPHQy9wtHj4S4vDRUR2Sl8qz+nhoxzrmeBS5QaXKjf5dO02/1q7w916pSt2kDJsLgnqTxcZSBcYSBcZSBU4kBtkwh/Y7eF962xjMVMYYTo/zK1glY8rC1yq3OTK2h3mN5ZYqle/9ToM21j0pvJM+P1M5YeYzg8zUxhhNNtDWkueRGQPa7t4+3Zwhz8u/OlBjUWnucZhKj/Ji4OnmSsdwVMjPBHpEo2oyUJtmSvriyxsLHOjdo/rtWXuBPdZDdeJdrjJnmc5lD2fsufT4+Uoezl6Ujn6U4UvQkW6QNnzcR+SPg9fJUkS6nGTq+t3ubp+l4XaMgsb97gZrHInuM/9cKPjQcM2Fn2pPCOZHkayZUYym58Jv599fh95N9PR7xMR2S1d/aTxbZ8neh7jZN8zfC8/haN+FSLSRVK2y1R+iKn8EGHcYqle5XawylKjykq4wb16lXuNNSphjfVWnY1Wg41Wg3oc0oojWklMlMTESYIxBsdYOMbGsazNY8smY3tk7RQ5J43vpPCdFFknTdHNUPJ8il6Wopul5GYpbB1nHQ+jBn//lzGGjO1xqDjGwcIojbjJYr3CYlBhqVFlqVFlub7GcrjO/bDGWqvGerNOEIXUoybNJCKKYxIS7K3r5doOrrFxLZu07W5eD8+n5PqUvCzlVI4+L89gushApkivl1Mxtoh8J3VlsHCNw3RhmuPlxzlcPMhgekAPSRHpap7lMJrtYTTbQ5IkJCSsNQMqzYCNVp0galKPQoKoSTNu0Upi4q1gkWwFC3tri27bWNjGYBublOWQtl3Strf1d/PYd1KkLVfbj7bBGEPa9hj3+xn3+0mShFYSUW0GVJsBG60GtVaDIAppxE3COCJKos2ZqCTB2rpGm0HQxjYWnuXgOylyboacsxkIs04KW0t4ReQh0JFgYdGZmYQet8xUfpJDhVn2+xOMZUfwrIen2FBEvhuMMRgMRc+n6Pm7PRzZJmMMrnHoTeXpTe3N5lQiIrup7RqLIKozv3GN+Y1rLIcrrIb3qTarrLc2qEUBjahOGDeJkoiYGBsbx7JJ2xnyjk/ZKzOQ6mc4M8Rweoi+VC/9qT5c1VKIiIiIiOwZbQcLgDiJCeOQIKpTj+qEcUgYN2klLaKk9WCqPyHBYLCMhWMcXMslbafI2llyjo9neZrWFxERERHZgzoSLERERERE5OGmajIREREREWmbgoWIiIiIiLRNwUJERERERNqmYCEiIiIiIm1TsBARERERkbYpWIiIiIiISNsULEREREREpG0KFiIiIiIi0jYFCxERERERaZuChYiIiIiItE3BQkRERERE2qZgISIiIiIibVOwEBERERGRtilYiIiIiIhI2xQsRERERESkbQoWIiIiIiLStn8DFkQPOGo8/eUAAAAASUVORK5CYII=", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from wordcloud import WordCloud\n", + "\n", + "def plot_word_cloud(topic):\n", + " words = dict(model.get_topic(topic))\n", + " wordcloud = WordCloud(width=800, height=400, background_color='white').generate_from_frequencies(words)\n", + " \n", + " plt.figure(figsize=(10, 5))\n", + " plt.imshow(wordcloud, interpolation='bilinear')\n", + " plt.axis('off')\n", + " plt.title(f'Topic {topic}')\n", + " plt.show()\n", + "\n", + "# Plot word cloud for each topic\n", + "for topic in set(topics):\n", + " if topic != -1: # -1 is often used for outliers\n", + " plot_word_cloud(topic)" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [], + "source": [ + "custom_labels = {\n", + " '-1': \"Outliers\",\n", + " '0': \"Universal Credit\",\n", + " '1': \"Housing\",\n", + " '2': \"Disability & PIP\",\n", + " '3': \"Immigration\",\n", + " '4': \"Consumer goods and services\"\n", + "}\n" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [], + "source": [ + "# Add the topics to the dataframe\n", + "df_responses['Topic'] = topics\n", + "\n", + "# Get the topic labels\n", + "topic_info = model.get_topic_info()\n", + "topic_labels = {row['Topic']: row['Name'] for _, row in topic_info.iterrows()}\n", + "\n", + "# Add the topic labels to the dataframe\n", + "df_responses['Topic_Label'] = df_responses['Topic'].map(topic_labels)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [], + "source": [ + "df_responses['Custom topics'] = df_responses['Topic'].map(custom_labels)" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(12, 6))\n", + "df_responses['Custom topics'].value_counts().plot(kind='bar')\n", + "plt.title('Distribution of Topics')\n", + "plt.xlabel('Topic')\n", + "plt.ylabel('Count')\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Step 3: Look at approval rate of topics" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['approvalTimestamp', 'approverEmail', 'approverReceivedTimestamp',\n", + " 'llmResponseTimestamp', 'userThankedTimestamp', 'approved',\n", + " 'llmPromptTimestamp', 'messageId', 'llmAnswer', 'supervisorMessage',\n", + " 'llmResponseJSon', 'responseId', 'llmPrompt', 'threadId',\n", + " 'userResponseTimestamp', 'Office', 'cleaned_text', 'urls', 'Topic',\n", + " 'Topic_Label', 'Custom topics'],\n", + " dtype='object')" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_responses.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [], + "source": [ + "df_responses_approved = df_responses[['approved','Office','Custom topics']].groupby(by='approved', axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_responses_approved" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "'Custom topic'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/caddy-chatbot-B-atQbAG-py3.12/lib/python3.12/site-packages/pandas/core/indexes/base.py:3805\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3804\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3805\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3806\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", + "File \u001b[0;32mindex.pyx:167\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mindex.pyx:196\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7081\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7089\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: 'Custom topic'", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[95], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# Create a cross-tabulation of Topic_Label and another relevant column\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;66;03m# For example, if you have an 'Office' column:\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m cross_tab \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mcrosstab(\u001b[43mdf_responses\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mCustom topic\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m, df_responses[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mOffice\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# If you don't have an 'Office' column, you can use any other relevant categorical column\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m# Or, if you want to see co-occurrence of topics:\u001b[39;00m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;66;03m# cross_tab = pd.crosstab(df_responses['Topic_Label'], df_responses['Topic_Label'])\u001b[39;00m\n\u001b[1;32m 8\u001b[0m \n\u001b[1;32m 9\u001b[0m \u001b[38;5;66;03m# Normalize the cross-tabulation\u001b[39;00m\n\u001b[1;32m 10\u001b[0m cross_tab_normalized \u001b[38;5;241m=\u001b[39m cross_tab\u001b[38;5;241m.\u001b[39mdiv(cross_tab\u001b[38;5;241m.\u001b[39msum(axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m), axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/caddy-chatbot-B-atQbAG-py3.12/lib/python3.12/site-packages/pandas/core/frame.py:4102\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 4100\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39mnlevels \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m 4101\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_getitem_multilevel(key)\n\u001b[0;32m-> 4102\u001b[0m indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4103\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_integer(indexer):\n\u001b[1;32m 4104\u001b[0m indexer \u001b[38;5;241m=\u001b[39m [indexer]\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/caddy-chatbot-B-atQbAG-py3.12/lib/python3.12/site-packages/pandas/core/indexes/base.py:3812\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3807\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3808\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3809\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3810\u001b[0m ):\n\u001b[1;32m 3811\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3812\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3813\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3814\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3815\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3816\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3817\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", + "\u001b[0;31mKeyError\u001b[0m: 'Custom topic'" + ] + } + ], + "source": [ + "\n", + "\n", + "# Create a cross-tabulation of Topic_Label and another relevant column\n", + "# For example, if you have an 'Office' column:\n", + "cross_tab = pd.crosstab(df_responses['Custom topic'], df_responses['Office'])\n", + "\n", + "# If you don't have an 'Office' column, you can use any other relevant categorical column\n", + "# Or, if you want to see co-occurrence of topics:\n", + "# cross_tab = pd.crosstab(df_responses['Topic_Label'], df_responses['Topic_Label'])\n", + "\n", + "# Normalize the cross-tabulation\n", + "cross_tab_normalized = cross_tab.div(cross_tab.sum(axis=1), axis=0)\n", + "\n", + "# Create a heatmap\n", + "plt.figure(figsize=(12, 10))\n", + "sns.heatmap(cross_tab_normalized, annot=True, cmap='YlOrBr', fmt='.2f')\n", + "plt.title('Topic Distribution Heatmap')\n", + "plt.ylabel('Topic')\n", + "plt.xlabel('Office') # Change this if you're using a different column\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Create a cross-tabulation of Office and Topic_Label\n", + "cross_tab = pd.crosstab(df_responses['Office'], df_responses['Custom topics'])\n", + "\n", + "# Create a stacked bar chart\n", + "cross_tab.plot(kind='bar', stacked=True, figsize=(12, 6))\n", + "plt.title('Topic Distribution Across Offices')\n", + "plt.xlabel('Office')\n", + "plt.ylabel('Count')\n", + "plt.legend(title='Topic', bbox_to_anchor=(1.05, 1), loc='upper left')\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Create a cross-tabulation of Office and Topic_Label\n", + "cross_tab = pd.crosstab(df_responses['Custom topics'], df_responses['approved'])\n", + "\n", + "# Define colors for the bars based on exact column names\n", + "color_map = {\n", + " True: 'green', # Adjust these if your column names are not exactly `True`/`False`\n", + " False: 'orange'\n", + "}\n", + "\n", + "# Create a list of colors corresponding to each column in cross_tab\n", + "colors = [color_map.get(col, 'gray') for col in cross_tab.columns]\n", + "\n", + "# Create a stacked bar chart\n", + "cross_tab.plot(kind='bar', stacked=True, figsize=(12, 6), color=colors)\n", + "plt.title('Approval Distribution Across Topics')\n", + "plt.xlabel('Topic')\n", + "plt.ylabel('Approval count')\n", + "plt.legend(title='Approval', bbox_to_anchor=(1.05, 1), loc='upper left')\n", + "plt.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "caddy-chatbot-B-atQbAG-py3.12", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tests/ragas/ragas_pipeline.py b/tests/ragas/ragas_pipeline.py new file mode 100644 index 0000000..6bd9a10 --- /dev/null +++ b/tests/ragas/ragas_pipeline.py @@ -0,0 +1,97 @@ +from datasets import Dataset +from langchain_openai.chat_models import AzureChatOpenAI +from langchain_openai.embeddings import AzureOpenAIEmbeddings +from ragas import evaluate +import dotenv + +from ragas.metrics import ( + context_precision, + answer_relevancy, + faithfulness, + context_recall, +) + +from model_answers import questions, ground_truths, contexts, answers + +questions_mini = questions +ground_truths_mini = ground_truths +contexts_mini = contexts +answers_mini = answers + +from model_answers_bedrock import questions, ground_truths, context, answers + +questions_bedrock = questions +ground_truths_bedrock = ground_truths +contexts_bedrock = contexts +answers_bedrock = answers + + +def create_ragas_dataset(questions, ground_truths, contexts, answers): + data_samples = { + "question": questions, + "answer": answers, + "contexts": contexts, + "ground_truth": ground_truths, + } + dataset = Dataset.from_dict(data_samples) + + return dataset + + +bedrock_ragas_dataset = create_ragas_dataset( + questions_bedrock, answers_bedrock, contexts_bedrock, ground_truths_bedrock +) +mini_ragas_dataset = create_ragas_dataset( + questions_mini, answers_mini, contexts_mini, ground_truths_mini +) + +ENV = dotenv.dotenv_values() + +azure_model = AzureChatOpenAI( + api_key=ENV["AZURE_OPENAI_API_KEY"], + openai_api_version=ENV["OPENAI_API_VERSION"], + azure_endpoint=ENV["AZURE_OPENAI_ENDPOINT"], + model=ENV["AZURE_OPENAI_DEPLOYMENT_NAME"], + validate_base_url=False, +) + +# init the embeddings for answer_relevancy, answer_correctness and answer_similarity +azure_embeddings = AzureOpenAIEmbeddings( + api_key=ENV["AZURE_EMBEDDING_API_KEY"], + azure_endpoint=ENV["AZURE_EMBEDDING_ENDPOINT"], + azure_deployment=ENV["EMBEDDING_DEPLOYMENT_NAME"], +) + +# list of metrics we're going to use +metrics = [ + faithfulness, + answer_relevancy, + context_recall, + context_precision, +] + +import time +import requests +from ratelimit import limits, sleep_and_retry +from requests.exceptions import HTTPError + +# Define your rate limit (e.g., 5 requests per minute) +RATE_LIMIT = 5 +TIME_PERIOD = 60 # seconds + + +def ragas_evaluate(dataset, model, embeddings): + result = evaluate( + dataset, + metrics=[answer_relevancy], + llm=model, + embeddings=embeddings, + is_async=True, + # max_concurrent=1 # Add this line + ) + + return result + + +print(ragas_evaluate(bedrock_ragas_dataset, azure_model, azure_embeddings)) +print(ragas_evaluate(mini_ragas_dataset, azure_model, azure_embeddings)) diff --git a/tests/test_embedding_local.py b/tests/test_embedding_local.py new file mode 100644 index 0000000..5653404 --- /dev/null +++ b/tests/test_embedding_local.py @@ -0,0 +1,7 @@ +from sentence_transformers import SentenceTransformer + +sentences = ["This is an example sentence", "Each sentence is converted"] + +model = SentenceTransformer("sentence-transformers/all-mpnet-base-v2") +embeddings = model.encode(sentences) +print(embeddings) diff --git a/utils/route_loader.py b/utils/route_loader.py new file mode 100644 index 0000000..87fdabc --- /dev/null +++ b/utils/route_loader.py @@ -0,0 +1,264 @@ +import boto3 + +TABLE_NAME = "caddyRoutes" + +dynamodb = boto3.resource("dynamodb") +table = dynamodb.Table(TABLE_NAME) + +routes_data = [ + { + "name": "benefits_and_tax_credits", + "utterances": [ + "What are benefits available?", + "How do I apply for tax credits?", + "Can you explain the eligibility criteria for tax credits?", + "Are there any changes to tax credits this year?", + "How can I calculate my entitlement to benefits and tax credits?", + "What documents do I need to provide for benefits and tax credits?", + "Can you help me with a benefits and tax credits claim issue?", + "Where can I find more information about benefits and tax credits?", + ], + }, + { + "name": "benefits_and_universal_credit", + "utterances": [ + "What is Universal Credit?", + "How do I apply for Universal Credit?", + "What are the eligibility criteria for Universal Credit?", + "Can you explain the Universal Credit claim process?", + "What documents do I need to provide for a Universal Credit claim?", + "How can I calculate my entitlement to Universal Credit?", + "Can you help me with a Universal Credit claim issue?", + "Where can I find more information about Universal Credit?", + ], + }, + { + "name": "charitable_support_and_food_banks", + "utterances": [ + "What are the eligibility criteria for receiving charitable support?", + "How can someone apply for charitable support?", + "What types of assistance do food banks provide?", + "Are there any income limits or requirements to access food banks?", + "What documentation is needed to receive charitable support?", + "How can someone find local food banks?", + "What other resources or services are available for individuals in need?", + "Are there any restrictions or limitations on the frequency of accessing food banks?", + ], + }, + { + "name": "consumer_goods_and_services", + "utterances": [ + "What are my rights as a consumer?", + "How can I make a complaint about a product or service?", + "What are the refund and return policies for consumer goods?", + "Can you help me with a dispute with a retailer?", + "Where can I find information about consumer protection laws?", + "What are the regulations for online shopping?", + "How can I avoid scams and fraudulent sellers?", + "Can you provide guidance on product warranties and guarantees?", + ], + }, + { + "name": "debt", + "utterances": [ + "What are the different types of debt?", + "How can someone negotiate with creditors to reduce debt?", + "What are the consequences of not paying off debt?", + "Can you explain the debt collection process?", + "What are the options for debt consolidation?", + "How can someone deal with overwhelming debt?", + "What are the rights and protections for individuals in debt?", + "Can you provide guidance on bankruptcy and insolvency?", + ], + }, + { + "name": "education", + "utterances": [ + "What are the available education options for my client?", + "How can my client access financial support for education?", + "What are the eligibility criteria for educational grants and scholarships?", + "Can you explain the process of applying for student loans?", + "What documentation is required for enrolling in educational programs?", + "How can my client navigate the admissions process for schools and universities?", + "Can you provide guidance on special education services and accommodations?", + "What resources are available for adult education and vocational training?", + "How can my client address issues related to bullying or discrimination in educational settings?", + "Where can I find more information about educational rights and regulations?", + ], + }, + { + "name": "employment", + "utterances": [ + "What are the rights and responsibilities of employees?", + "How can someone address workplace discrimination or harassment?", + "What is the process for filing a complaint against an employer?", + "Can you provide guidance on employment contracts and terms?", + "What are the regulations for minimum wage and working hours?", + "How can someone negotiate a fair salary or benefits package?", + "Can you explain the process of redundancy and severance pay?", + "What are the rights and protections for individuals facing unfair dismissal?", + "How can someone access support for workplace health and safety issues?", + "Where can I find more information about employment rights and regulations?", + ], + }, + { + "name": "financial_services_and_capability", + "utterances": [ + "What financial services are available for individuals?", + "How can someone access financial advice and guidance?", + "Can you explain the process of opening a bank account?", + "What are the options for managing debt and improving credit?", + "How can someone access affordable loans or credit?", + "Can you provide guidance on budgeting and saving?", + "What resources are available for financial planning and retirement?", + "How can someone protect themselves from financial scams and fraud?", + "Where can I find more information about financial services and capability?", + ], + }, + { + "name": "gva_and_hate_crime", + "utterances": [ + "What support services are available for victims of gender-based violence and hate crimes?", + "How can someone report a gender-based violence or hate crime incident?", + "What legal protections are in place for victims of gender-based violence and hate crimes?", + "Can you explain the process of obtaining a restraining order or protection order?", + "What resources are available for counseling and emotional support for victims of gender-based violence and hate crimes?", + "How can someone access emergency accommodation or safe houses?", + "Can you provide guidance on safety planning for victims of gender-based violence and hate crimes?", + "Where can I find more information about gender-based violence and hate crimes?", + ], + }, + { + "name": "health_and_community_care", + "utterances": [ + "What are the available healthcare services in the area?", + "How can someone access primary healthcare?", + "Can you explain the process of registering with a general practitioner (GP)?", + "What are the eligibility criteria for receiving community care services?", + "How can someone apply for community care services?", + "What types of support are available for individuals with specific health conditions?", + "Are there any income limits or requirements to access community care services?", + "What documentation is needed to receive community care services?", + "How can someone find local healthcare providers and specialists?", + "What other resources or services are available for individuals in need of healthcare and community care support?", + "Are there any restrictions or limitations on the frequency of accessing community care services?", + "Can you provide guidance on mental health support services?", + "What are the options for accessing long-term care facilities?", + "How can someone navigate the process of obtaining medical equipment or assistive devices?", + "What are the rights and protections for individuals receiving healthcare and community care services?", + "Where can I find more information about healthcare rights and regulations?", + ], + }, + { + "name": "housing", + "utterances": [ + "What are the rights and responsibilities of a tenant?", + "How can someone find affordable housing options?", + "Can you explain the process of renting a property?", + "What are the regulations for tenancy agreements?", + "How can someone address issues with their landlord?", + "What are the options for dealing with eviction?", + "Can you provide guidance on housing benefits and assistance programs?", + "Where can I find more information about housing rights and regulations?", + ], + }, + { + "name": "immigration_and_asylum", + "utterances": [ + "What are the eligibility criteria for different types of visas?", + "How can someone apply for asylum in this country?", + "What are the rights and protections for asylum seekers?", + "Can you explain the process of appealing a visa or asylum decision?", + "What are the options for family reunification for refugees?", + "How can someone access legal representation for immigration cases?", + "Can you provide guidance on immigration detention and removal?", + "What are the requirements for obtaining citizenship or permanent residency?", + "How can someone address issues with their immigration status?", + "Where can I find more information about immigration and asylum rights and regulations?", + ], + }, + { + "name": "legal", + "utterances": [ + "What are the different types of legal cases?", + "How can someone find a lawyer or legal representation?", + "Can you explain the process of filing a lawsuit?", + "What are the options for alternative dispute resolution?", + "How can someone access legal aid or pro bono services?", + "Can you provide guidance on court procedures and protocols?", + "What are the rights and protections for individuals in the justice system?", + "How can someone navigate the process of obtaining legal documents or records?", + "Where can I find more information about the legal system, courts, and justice system?", + ], + }, + { + "name": "relationships_and_family", + "utterances": [ + "What are the legal rights and responsibilities in a marriage or civil partnership?", + "How can someone navigate the process of divorce or dissolution?", + "What are the options for child custody and visitation rights?", + "Can you provide guidance on child support and maintenance?", + "What are the rights and protections for victims of domestic violence?", + "How can someone address issues related to child protection and safeguarding?", + "Can you explain the process of adoption or fostering?", + "What resources are available for couples or families going through relationship breakdown?", + "How can someone access counseling or mediation services for family disputes?", + "Where can I find more information about relationship and family rights and regulations?", + ], + }, + { + "name": "tax", + "utterances": [ + "What are the different types of taxes?", + "How can someone calculate their income tax?", + "Can you explain the process of filing a tax return?", + "What are the deductions and credits available for taxpayers?", + "How can someone address issues with their tax payments?", + "What are the options for resolving tax disputes?", + "Can you provide guidance on self-employment taxes?", + "What are the tax implications of owning a business?", + "How can someone navigate the process of paying taxes as an employee (PAYE)?", + "Where can I find more information about tax laws and regulations?", + ], + }, + { + "name": "travel_and_transport", + "utterances": [ + "What are the available modes of public transportation in the area?", + "How can someone plan their travel using public transportation?", + "Can you explain the process of purchasing tickets for trains or buses?", + "What are the options for traveling between different cities or regions?", + "How can someone access information about train schedules and routes?", + "Are there any discounts or concessions available for public transportation?", + "Can you provide guidance on navigating public transportation systems?", + "What are the rights and protections for passengers using public transportation?", + "How can someone address issues with delays or cancellations of trains or buses?", + "Where can I find more information about travel and transportation services?", + ], + }, + { + "name": "utilities_and_communications", + "utterances": [ + "How can someone reduce their energy bills?", + "What assistance programs are available for individuals struggling to pay their energy bills?", + "Can you explain the process of switching energy providers?", + "What are the options for accessing affordable broadband services?", + "How can someone address issues with their broadband connection?", + "What support is available for individuals experiencing fuel poverty?", + "Can you provide guidance on energy-saving measures for heating and cooling?", + "What are the rights and protections for consumers in the energy and communications sectors?", + "How can someone navigate the process of installing and using prepayment meters?", + "Where can I find more information about energy crisis management and resources?", + ], + }, +] + + +def load_routes_to_dynamodb(): + for route in routes_data: + table.put_item(Item=route) + print("All routes have been loaded into the DynamoDB table.") + + +if __name__ == "__main__": + load_routes_to_dynamodb()