From 4a7bffea0c95e97116c5ea665cc40e23338a3a64 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 10:23:51 +0000 Subject: [PATCH 01/19] Peft feature implemented --- .readthedocs.yaml | 42 + README.md | 2 +- docs/Makefile | 25 + docs/make.bat | 38 + docs/requirements.txt | 4 + docs/source/conf.py | 43 + docs/source/csdata.rst | 28 + docs/source/csmodel.rst | 27 + docs/source/index.rst | 38 + docs/source/prompt_formatter.rst | 19 + docs/source/quickstart.rst | 38 + docs/source/tasks.rst | 36 + docs/source/utils.rst | 34 + setup.cfg | 51 + src/cell2sentence/csmodel.py | 729 +++--- ...l_type_conditional_generation_prompts.json | 19 + ...gle_cell_cell_type_prediction_prompts.json | 24 + .../tests/small_data_diffgenes.csv | 1 - src/cell2sentence/tests/test_csmodel.py | 120 +- ..._10_perturbation_response_prediction.ipynb | 1478 +++++++++++ .../c2s_tutorial_5_cell_generation.ipynb | 2226 +++++++++++++++++ ...al_9_natural_language_interpretation.ipynb | 1051 ++++++++ 22 files changed, 5684 insertions(+), 389 deletions(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 7052740..07be3bb 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -34,6 +34,48 @@ sphinx: # install: # - requirements: docs/requirements.txt +# Declare the Python requirements required to build your documentation +python: + install: + - requirements: docs/requirements.txt + - method: pip + path: . +# Read the Docs configuration file for Sphinx projects +# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details + +# Required +version: 2 + +# Set the OS, Python version and other tools you might need +build: + os: ubuntu-22.04 + tools: + python: "3.12" + # You can also specify other tool versions: + # nodejs: "20" + # rust: "1.70" + # golang: "1.20" + +# Build documentation in the "docs/" directory with Sphinx +sphinx: + configuration: docs/source/conf.py + # You can configure Sphinx to use a different builder, for instance use the dirhtml builder for simpler URLs + # builder: "dirhtml" + # Fail on all warnings to avoid broken references + # fail_on_warning: true + +# Optionally build your docs in additional formats such as PDF and ePub +# formats: +# - pdf +# - epub + +# Optional but recommended, declare the Python requirements required +# to build your documentation +# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html +# python: +# install: +# - requirements: docs/requirements.txt + # Declare the Python requirements required to build your documentation python: install: diff --git a/README.md b/README.md index 9383258..6951089 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,7 @@ [![Code License: Apache 2.0](https://img.shields.io/badge/license-Apache%20License%202.0-blue)](https://www.apache.org/licenses/LICENSE-2.0) [![PyPI version](https://badge.fury.io/py/cell2sentence.svg)](https://badge.fury.io/py/cell2sentence) [![DOI:10.1101/2025.04.14.648850](http://img.shields.io/badge/DOI-10.1101/2025.04.14.648850-B31B1B.svg)](https://doi.org/10.1101/2025.04.14.648850) -[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/release/python-380/) +[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/release/python-310020/) ![cell2sentence workflow image](c2s_overview_figure.png) diff --git a/docs/Makefile b/docs/Makefile index 8b95755..2a0cd09 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -1,3 +1,4 @@ +<<<<<<< HEAD # Minimal makefile for Sphinx documentation # @@ -20,3 +21,27 @@ help: @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) # Example: sphinx-build -M html docs/source/ docs/build/ +======= +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line, and also +# from the environment for the first two. +SPHINXOPTS ?= +SPHINXBUILD ?= sphinx-build +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +# Example: sphinx-build -M html docs/source/ docs/build/ +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/make.bat b/docs/make.bat index dc1312a..7ca1d33 100644 --- a/docs/make.bat +++ b/docs/make.bat @@ -1,3 +1,4 @@ +<<<<<<< HEAD @ECHO OFF pushd %~dp0 @@ -33,3 +34,40 @@ goto end :end popd +======= +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=source +set BUILDDIR=build + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.https://www.sphinx-doc.org/ + exit /b 1 +) + +if "%1" == "" goto help + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% + +:end +popd +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/requirements.txt b/docs/requirements.txt index 856b3f4..80c152f 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,2 +1,6 @@ +<<<<<<< HEAD sphinx +======= +sphinx +>>>>>>> 593fb74 (Peft feature implemented) sphinx_rtd_theme \ No newline at end of file diff --git a/docs/source/conf.py b/docs/source/conf.py index 3ee9a8b..29ec1d5 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -1,3 +1,4 @@ +<<<<<<< HEAD # Configuration file for the Sphinx documentation builder. # # For the full list of built-in configuration values, see the documentation: @@ -38,3 +39,45 @@ # html_theme = 'alabaster' html_theme = 'sphinx_rtd_theme' html_static_path = ['_static'] +======= +# Configuration file for the Sphinx documentation builder. +# +# For the full list of built-in configuration values, see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +# -- Project information ----------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information + +import pathlib +import sys +import os +sys.path.insert(0, os.path.join(pathlib.Path(__file__).parents[2].resolve().as_posix(), "src", "cell2sentence")) + + +project = 'Cell2Sentence' +copyright = '2024, Cell2Sentence Authors' +author = 'Cell2Sentence Authors' +release = '1.0.0' + +# -- General configuration --------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration + +extensions = [ + 'sphinx.ext.autodoc', + 'sphinx.ext.napoleon', + 'sphinx_rtd_theme', + 'sphinx.ext.autosummary', +] + +templates_path = ['_templates'] +exclude_patterns = [] + + + +# -- Options for HTML output ------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output + +# html_theme = 'alabaster' +html_theme = 'sphinx_rtd_theme' +html_static_path = ['_static'] +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/csdata.rst b/docs/source/csdata.rst index 34d4c2a..8f03525 100644 --- a/docs/source/csdata.rst +++ b/docs/source/csdata.rst @@ -1,3 +1,4 @@ +<<<<<<< HEAD CSData ====== @@ -23,3 +24,30 @@ representing the dataset after C2S rank transformation. .. autofunction:: csdata.CSData.get_sentence_strings .. autofunction:: csdata.CSData.__str__ +======= +CSData +====== + +A CSData object is a wrapper around a single-cell dataset, which tracks its path on disk. +It's main functionality is to keep the dataset stored on disk so that data need not be +loaded in memory until it is used, either for inference or finetuning. + +.. autofunction:: csdata.CSData + +.. autofunction:: csdata.CSData.__init__ + + +The ``CSData.adata_to_arrow()`` function takes as input a single-cell dataset in the form +of a H5AD Scanpy object, and returns a pyarrow dataset which stores cell sentences +representing the dataset after C2S rank transformation. + +.. autofunction:: csdata.CSData.adata_to_arrow + +.. autofunction:: csdata.CSData.csdata_from_arrow + +.. autofunction:: csdata.CSData.csdata_from_multiple_arrow_datasets + +.. autofunction:: csdata.CSData.get_sentence_strings + +.. autofunction:: csdata.CSData.__str__ +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/csmodel.rst b/docs/source/csmodel.rst index 6eff74d..5071353 100644 --- a/docs/source/csmodel.rst +++ b/docs/source/csmodel.rst @@ -1,3 +1,4 @@ +<<<<<<< HEAD CSModel ======= @@ -22,3 +23,29 @@ The class contains utilities for model generation and cell embedding with a Hugg .. autofunction:: csmodel.CSModel.embed_cells_batched .. autofunction:: csmodel.CSModel.push_model_to_hub +======= +CSModel +======= + +A CSModel object is a wrapper around a Cell2Sentence model, which tracks the path of the model +saved on disk. When needed, the model is loaded from the path on disk for inference or finetuning. +The class contains utilities for model generation and cell embedding with a Huggingface backend. + +.. autofunction:: csmodel.CSModel + +.. autofunction:: csmodel.CSModel.__init__ + +.. autofunction:: csmodel.CSModel.__str__ + +.. autofunction:: csmodel.CSModel.fine_tune + +.. autofunction:: csmodel.CSModel.generate_from_prompt + +.. autofunction:: csmodel.CSModel.generate_from_prompt_batched + +.. autofunction:: csmodel.CSModel.embed_cell + +.. autofunction:: csmodel.CSModel.embed_cells_batched + +.. autofunction:: csmodel.CSModel.push_model_to_hub +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/index.rst b/docs/source/index.rst index cac513b..97d8f09 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -1,3 +1,4 @@ +<<<<<<< HEAD .. Cell2Sentence documentation master file, created by sphinx-quickstart on Mon Sep 2 12:15:19 2024. You can adapt this file completely to your liking, but it should at least @@ -33,3 +34,40 @@ Indices and tables * :ref:`genindex` * :ref:`modindex` * :ref:`search` +======= +.. Cell2Sentence documentation master file, created by + sphinx-quickstart on Mon Sep 2 12:15:19 2024. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +Cell2Sentence: Single-cell Analysis With LLMs +============================================= + +**Cell2Sentence (C2S)** is a framework for directly adapting Large Language Models (LLMs) to single-cell biology. C2S proposes a rank-ordering transformation of cell expression into cell sentences, which are sentences of space-separated gene names ordered by descending expression. By representing single-cell data as cell sentences, C2S provides a framework for LLMs to *directly* model single-cell biology in natural language, enabling diverse capabilities on multiple single-cell tasks. + +C2S is developed by members of the `vanDijk Lab `_ at Yale University. Check out the :doc:`quickstart` section for quickstart instructions. + +.. note:: + + We are actively adding more features and documentation to the C2S API. For any feature requests or issues, please leave a GitHub issue or reach out to us! + + +.. toctree:: + :maxdepth: 1 + :caption: Contents: + + quickstart + tasks + csdata + csmodel + prompt_formatter + utils + + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/prompt_formatter.rst b/docs/source/prompt_formatter.rst index 3020c16..e6a05f0 100644 --- a/docs/source/prompt_formatter.rst +++ b/docs/source/prompt_formatter.rst @@ -1,3 +1,4 @@ +<<<<<<< HEAD Prompt Formatter ================ @@ -14,3 +15,21 @@ cell generation and cell type prediction. .. autofunction:: prompt_formatter.PromptFormatter.get_keys_for_task .. autofunction:: prompt_formatter.PromptFormatter.format_hf_ds +======= +Prompt Formatter +================ + +A Prompt Formatter object deals with formatting prompts for specific tasks, such as +cell generation and cell type prediction. + + +.. autofunction:: prompt_formatter.get_cell_sentence_str + +.. autofunction:: prompt_formatter.PromptFormatter + +.. autofunction:: prompt_formatter.PromptFormatter.__init__ + +.. autofunction:: prompt_formatter.PromptFormatter.get_keys_for_task + +.. autofunction:: prompt_formatter.PromptFormatter.format_hf_ds +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/quickstart.rst b/docs/source/quickstart.rst index d4ab3b7..114cbea 100644 --- a/docs/source/quickstart.rst +++ b/docs/source/quickstart.rst @@ -1,3 +1,4 @@ +<<<<<<< HEAD Quickstart ========== @@ -33,3 +34,40 @@ This will install the latest development environment of cell2sentence, along wit .. code-block:: console pip install cell2sentence +======= +Quickstart +========== + +Installation +------------ + +To set up a cell2sentence environment, first pull the repository locally: + +.. code-block:: console + + git clone https://github.com/vandijklab/cell2sentence.git + +Navigate a terminal into the root of the repository. Next, create an Anaconda environment using python3 using anaconda with: + +.. code-block:: console + + conda create -n cell2sentence python=3.8 + +Next, activate the environment: + +.. code-block:: console + + conda activate cell2sentence + +Finally, install cell2sentence and other package dependencies: + +.. code-block:: console + + make install + +This will install the latest development environment of cell2sentence, along with other pacakge dependendies. You can also install cell2sentence itself using pip: + +.. code-block:: console + + pip install cell2sentence +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/tasks.rst b/docs/source/tasks.rst index 1c2df09..6141993 100644 --- a/docs/source/tasks.rst +++ b/docs/source/tasks.rst @@ -1,3 +1,4 @@ +<<<<<<< HEAD Tasks ===== @@ -31,3 +32,38 @@ embedding vectors. .. autofunction:: tasks.embed_cells +======= +Tasks +===== + +Cell Generation +--------------- + +To generate cells conditioned on cell type using a C2S model, +you can use the ``tasks.generate_cells_conditioned_on_cell_type()`` function. +This function will call the batched generation function of the CSModel class +with cell type generation prompts. + +.. autofunction:: tasks.generate_cells_conditioned_on_cell_type + + +Cell Type Annotation +-------------------- + +To predict cell types of data, you can use the +``tasks.predict_cell_types_of_data()`` function: + +.. autofunction:: tasks.predict_cell_types_of_data + + +Cell Embedding +-------------- + +To embed cells using C2S models, you can use the +``tasks.embed_cells()`` function. This function loads a CSModel object, and +uses the C2S model to embed cell sentences from the CSData object into +embedding vectors. + +.. autofunction:: tasks.embed_cells + +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/utils.rst b/docs/source/utils.rst index b54c091..1cbb8ff 100644 --- a/docs/source/utils.rst +++ b/docs/source/utils.rst @@ -1,3 +1,4 @@ +<<<<<<< HEAD Utils ===== @@ -29,3 +30,36 @@ rank transformation, train/test splitting, and tokenization during finetuning. .. autofunction:: utils.reconstruct_expression_from_cell_sentence +======= +Utils +===== + +This module contains utility functions for various C2S-related workflows, such as +rank transformation, train/test splitting, and tokenization during finetuning. + + +.. autofunction:: utils.generate_vocabulary + +.. autofunction:: utils.concat_vocabularies + +.. autofunction:: utils.generate_sentences + +.. autofunction:: utils.get_benchmark_df + +.. autofunction:: utils.sort_transcript_counts + +.. autofunction:: utils.benchmark_expression_conversion + +.. autofunction:: utils.build_arrow_dataset + +.. autofunction:: utils.train_test_split_arrow_ds + +.. autofunction:: utils.tokenize_loss_on_response + +.. autofunction:: utils.tokenize_all + +.. autofunction:: utils.post_process_generated_cell_sentences + +.. autofunction:: utils.reconstruct_expression_from_cell_sentence + +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/setup.cfg b/setup.cfg index 9775de0..9fa7060 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,3 +1,4 @@ +<<<<<<< HEAD [metadata] name = cell2sentence version = 1.2.0 @@ -41,4 +42,54 @@ install_requires = where = src [options.package_data] +======= +[metadata] +name = cell2sentence +version = 1.2.0 +author = Syed Asad Rizvi +author_email = syed.rizvi@yale.edu +description = Cell2Sentence: Single-cell Analysis With LLMs +long_description = file: README.md +long_description_content_type = text/markdown +url = https://github.com/vandijklab/cell2sentence +license = 'BY-NC-ND' +project_urls = + Bug Tracker = https://github.com/vandijklab/cell2sentence/issues +classifiers = + Programming Language :: Python :: 3 + Development Status :: 2 - Pre-Alpha + Operating System :: OS Independent + +[options] +package_dir = + = src +packages = find: +python_requires = >=3.10 +install_requires = + torch + transformers + peft + bitsandbytes + datasets + anndata + scanpy + numpy + pandas + scipy + tqdm + scikit-learn + jupyterlab + accelerate + plotnine + sphinx + sphinx-rtd-theme + tiktoken + sentencepiece + protobuf + +[options.packages.find] +where = src + +[options.package_data] +>>>>>>> 593fb74 (Peft feature implemented) * = *.json \ No newline at end of file diff --git a/src/cell2sentence/csmodel.py b/src/cell2sentence/csmodel.py index 7490619..d71f9bd 100644 --- a/src/cell2sentence/csmodel.py +++ b/src/cell2sentence/csmodel.py @@ -1,337 +1,392 @@ -""" -Main model wrapper class definition -""" - -# -# @authors: Rahul Dhodapkar, Syed Rizvi -# - -# Python built-in libraries -import os -import pickle -from random import sample -from typing import Optional - -# Third-party libraries -import numpy as np -from datasets import load_from_disk, DatasetDict, Dataset - -# Pytorch, Huggingface imports -import torch -from transformers import AutoTokenizer, AutoModelForCausalLM, Trainer, TrainingArguments - -# Local imports -from cell2sentence.prompt_formatter import PromptFormatter, C2SPromptFormatter -from cell2sentence.utils import train_test_split_arrow_ds, tokenize_all, tokenize_loss_on_response - - -class CSModel(): - """ - Wrapper class to abstract different types of input data that can be passed - in cell2sentence based workflows. - """ - - def __init__(self, model_name_or_path, save_dir, save_name): - """ - Core constructor, CSModel class contains a path to a model. - - Arguments: - model_name_or_path: either a string representing a Huggingface model if - want to start with a default LLM, or a path to an already-trained C2S - model on disk if want to do inference with/finetune starting from - an already-trained C2S model - save_dir: directory where model should be saved to - save_name: name to save model under (no file extension needed) - """ - self.model_name_or_path = model_name_or_path # path to model to load - self.save_dir = save_dir - self.device = "cuda" if torch.cuda.is_available() else "cpu" - print("Using device:", self.device) - - # Create save path - if not os.path.exists(save_dir): - os.mkdir(save_dir) - self.save_path = os.path.join(save_dir, save_name) - - # Load tokenizer - self.tokenizer = AutoTokenizer.from_pretrained( - model_name_or_path, padding_side='left' - ) - if self.tokenizer.pad_token is None: - self.tokenizer.pad_token = self.tokenizer.eos_token - - # Load model - either a pretrained C2S model path, or a Huggingface LLM name (if want to train from scratch on your own dataset) - model = AutoModelForCausalLM.from_pretrained( - model_name_or_path, - cache_dir=os.path.join(save_dir, ".cache"), # model file takes up several GB if loading default Huggignface LLM models - trust_remote_code=True - ) - model.save_pretrained(self.save_path) - - def __str__(self): - """ - Summarize CSData object as string for debugging and logging. - """ - return f"CSModel Object; Path={self.save_path}" - - def fine_tune(self, - csdata, - task: str, - train_args: TrainingArguments, - loss_on_response_only: bool = True, - top_k_genes: int = 100, - max_eval_samples: int = 500, - data_split_indices_dict: Optional[dict] = None, - prompt_formatter: Optional[PromptFormatter] = None, - formatted_hf_ds: Optional[Dataset] = None, - num_proc: int = 3, - ): - """ - Fine tune a model using the provided CSData object data - - Arguments: - csdata: a CSData object to be used as input for finetuning. - alternatively, data can be any generator of sequential - text that satisfies the same functional contract as - a CSData object - task: name of finetuning task (see supported tasks in prompt_formatter.py). Ignored - if prompt_formatter is not None. - train_args: Huggingface Trainer arguments object - loss_on_response_only: whether to take loss only on model's answer - top_k_genes: number of genes to use for each cell sentence. Ignored if - prompt_formatter is not None. - max_eval_samples: number of samples to use for validation - data_split_indices_dict: dictionary of indices for train, val, and (optionally) - test set. Required keys are "train" and "val", value - should be a list of indices of samples in that data split. - prompt_formatter: optional custom PromptFormatter object. If None, a default one - will be created using task and top_k_genes parameters. - formatted_hf_ds: optional Huggingface Dataset object containing formatted data, - used in cases where custom formatting is desired (e.g. multicell - tasks where more complex formatting is needed). - num_proc: number of processes to use for tokenization. Defaults to 3. - Return: - None: an updated CSModel is generated in-place - """ - # Load data from csdata object - if csdata.dataset_backend == "arrow": - hf_ds = load_from_disk(csdata.data_path) - else: - raise NotImplementedError("Please use arrow backend implementation for training") - - # Define prompt formatter, format prompts - if prompt_formatter is None: - prompt_formatter = C2SPromptFormatter(task=task, top_k_genes=top_k_genes) - if formatted_hf_ds is None: - # If formatted dataset not supplied, format hf_ds using prompt_formatter - formatted_hf_ds = prompt_formatter.format_hf_ds(hf_ds) - - # Load model - print("Reloading model from path on disk:", self.save_path) - model = AutoModelForCausalLM.from_pretrained( - self.save_path, - cache_dir=os.path.join(self.save_dir, ".cache"), - trust_remote_code=True - ) - model = model.to(self.device) - - # Tokenize data using LLM tokenizer - # - this function applies a lambda function to tokenize each dataset split in the DatasetDict - if loss_on_response_only: - tokenization_function = tokenize_loss_on_response - else: - tokenization_function = tokenize_all - formatted_hf_ds = formatted_hf_ds.map( - lambda batch: tokenization_function(batch, self.tokenizer), - batched=True, - load_from_cache_file=False, - num_proc=num_proc, - batch_size=1000, - ) - - # Define parameters needed in data collator: - block_size = model.config.max_position_embeddings # maximum input sequence length possible - tokenizer = self.tokenizer # define tokenizer as variable here so it is accessible in dataloader - def data_collator(examples): - # Note: this data collator assumes we are not using flash attention, and pads samples - # to the max size in the batch. All sample lengths are capped at the size of the - # LLM's context). - max_length = max(list(map(lambda x: len(x["input_ids"]), examples))) - batch_input_ids, batch_attention_mask, batch_labels = [], [], [] - for i in range(len(examples)): - sample_input_ids = examples[i]["input_ids"] - label_input_ids = examples[i]["labels"] - attention_mask = examples[i]["attention_mask"] - assert len(sample_input_ids) == len(label_input_ids) == len(attention_mask) - - size_diff = max_length - len(sample_input_ids) - final_input_ids = [tokenizer.pad_token_id] * (size_diff) + sample_input_ids - final_attention_mask = [0] * (size_diff) + attention_mask - final_label_input_ids = [-100] * (size_diff) + label_input_ids - - batch_input_ids.append(final_input_ids[: block_size]) - batch_attention_mask.append(final_attention_mask[: block_size]) - batch_labels.append(final_label_input_ids[: block_size]) - - return { - "input_ids": torch.tensor(batch_input_ids), - "attention_mask": torch.tensor(batch_attention_mask), - "labels": torch.tensor(batch_labels), - } - - output_dir = train_args.output_dir - print(f"Starting training. Output directory: {output_dir}") - - # Perform dataset split - if data_split_indices_dict is None: - split_ds_dict, data_split_indices_dict = train_test_split_arrow_ds(formatted_hf_ds) - else: - # Dataset split indices supplied by user, split formatted arrow dataset accordingly - train_ds = formatted_hf_ds.select(data_split_indices_dict["train"]) - val_ds = formatted_hf_ds.select(data_split_indices_dict["val"]) - ds_dict_object = { - "train": train_ds, - "validation": val_ds, - } - split_ds_dict = DatasetDict(ds_dict_object) - with open(os.path.join(output_dir, 'data_split_indices_dict.pkl'), 'wb') as f: - pickle.dump(data_split_indices_dict, f) - - train_dataset = split_ds_dict["train"] - eval_dataset = split_ds_dict["validation"] - if (max_eval_samples is not None) and (max_eval_samples < eval_dataset.num_rows): - sampled_eval_indices = sample(list(range(eval_dataset.num_rows)), k=max_eval_samples) - sampled_eval_indices.sort() - np.save(os.path.join(output_dir, 'sampled_eval_indices.npy'), np.array(sampled_eval_indices, dtype=np.int64)) - print(f"Selecting {max_eval_samples} samples of eval dataset to shorten validation loop.") - eval_dataset = eval_dataset.select(sampled_eval_indices) - - # Define Trainer - trainer = Trainer( - model=model, - args=train_args, - data_collator=data_collator, - train_dataset=train_dataset, - eval_dataset=eval_dataset, - tokenizer=self.tokenizer - ) - trainer.train() - print(f"Finetuning completed. Updated model saved to disk at: {output_dir}") - - def generate_from_prompt(self, model, prompt, max_num_tokens=1024, **kwargs): - """ - Generate new data using the model, starting with a given prompt. - - Arguments: - model: a C2S model - prompt: a textual prompt - max_num_tokens: the maximum number of tokens to generate given the model supplied - kwargs: arguments for model.generate() (for generation options, see Huggingface docs: - https://huggingface.co/docs/transformers/en/main_classes/text_generation). - Any kwargs are passed without input validation to the model.generate() function - Return: - Text corresponding to the number `n` of tokens requested - """ - return self.generate_from_prompt_batched( - model=model, - prompt_list=[prompt], - max_num_tokens=max_num_tokens, - **kwargs - )[0] - - def generate_from_prompt_batched(self, model, prompt_list, max_num_tokens=1024, **kwargs): - """ - Batched generation with C2S model. Takes as input a model and a list of prompts to - generate from. - - Arguments: - model: a C2S model - prompt: a textual prompt - max_num_tokens: the maximum number of tokens to generate given the model supplied - kwargs: arguments for model.generate() (for generation options, see Huggingface docs: - https://huggingface.co/docs/transformers/en/main_classes/text_generation) - Return: - Text corresponding to the number `n` of tokens requested - """ - tokens = self.tokenizer(prompt_list, padding=True, return_tensors='pt') - input_ids = tokens['input_ids'].to(self.device) - attention_mask = tokens['attention_mask'].to(self.device) - - outputs = model.generate( - input_ids=input_ids, - attention_mask=attention_mask, - max_new_tokens=max_num_tokens, - pad_token_id=self.tokenizer.pad_token_id, - **kwargs - ) - pred_list = self.tokenizer.batch_decode(outputs, skip_special_tokens=True) - predictions_without_input_prompt = [] - for pred, prompt in zip(pred_list, prompt_list): - pred_cleaned = pred.replace(prompt, "") - pred_cleaned = pred_cleaned.replace("<|endoftext|>", "") # remove end of text string - pred_cleaned = pred_cleaned.lstrip() # remove any leading whitespace - predictions_without_input_prompt.append(pred_cleaned) - - return predictions_without_input_prompt - - def embed_cell(self, model, prompt, max_num_tokens=1024): - """ - Embed cell using the model, starting with a given prompt. - - Arguments: - model: a C2S model - prompt: a textual prompt - max_num_tokens: the maximum number of tokens to generate given the model supplied - Return: - Text corresponding to the number `n` of tokens requested - """ - embedding_list = self.embed_cells_batched( - model=model, - prompt_list=[prompt], - max_num_tokens=max_num_tokens) - return embedding_list[0] # return 1 cell embedding - - def embed_cells_batched(self, model, prompt_list, max_num_tokens=1024): - """ - Embed multiple cell in batched fashion using the model, starting with a given prompt. - - Arguments: - model: a C2S model for cell embedding - prompt_list: a list of textual prompts - max_num_tokens: the maximum number of tokens to generate given the model supplied - Return: - Text corresponding to the number `n` of tokens requested - """ - tokens = self.tokenizer(prompt_list, padding=True, return_tensors='pt') - input_ids = tokens['input_ids'].to(self.device) - attention_mask = tokens['attention_mask'].to(self.device) - - outputs = model( - input_ids=input_ids, - attention_mask=attention_mask, - output_hidden_states=True - ) - # Take last layer output, average over sequence dimension - all_embeddings = [] - for idx in range(len(prompt_list)): - embedding = outputs.hidden_states[-1][idx].mean(0).detach().cpu().numpy() - all_embeddings.append(embedding) - return all_embeddings - - def push_model_to_hub(self, model_id_or_name): - """ - Helper function to push the model to Huggingface. Note: need to be logged - into Huggingface, see: https://huggingface.co/docs/transformers/en/model_sharing - - Arguments: - model_id_or_name: name to push Huggingface model to - """ - # Reload model - model = AutoModelForCausalLM.from_pretrained( - self.save_path, - cache_dir=os.path.join(self.save_dir, ".cache"), - trust_remote_code=True - ) - - # Push to hub - model.push_to_hub(model_id_or_name, use_auth_token=True) +""" +Main model wrapper class definition +""" + +# +# @authors: Rahul Dhodapkar, Syed Rizvi +# + +# Python built-in libraries +import os +import pickle +from random import sample +from typing import Optional + +# Third-party libraries +import numpy as np +from datasets import load_from_disk, DatasetDict, Dataset + +# Pytorch, Huggingface imports +import torch +from transformers import AutoTokenizer, AutoModelForCausalLM, Trainer, TrainingArguments +from peft import LoraConfig, get_peft_model +from huggingface_hub import login + +# Local imports +from cell2sentence.prompt_formatter import PromptFormatter, C2SPromptFormatter +from cell2sentence.utils import train_test_split_arrow_ds, tokenize_all, tokenize_loss_on_response + + +class CSModel(): + """ + Wrapper class to abstract different types of input data that can be passed + in cell2sentence based workflows. + """ + + def __init__( + self, + model_name_or_path, + save_dir, save_name, + peft = False, + r = 16, + alpha = 32, + modules = None, + bias = "none", + task_type = "CAUSAL_LM", + huggingface_token: Optional[str] = None + ): + """ + Core constructor, CSModel class contains a path to a model. + + Arguments: + model_name_or_path (str): Huggingface model ID or local path to a pretrained model. + save_dir (str): Directory where model should be saved. + save_name (str): Name to save model under (no file extension needed). + peft (bool): Whether to enable parameter-efficient fine-tuning (PEFT/LoRA). + When True, LoRA adapters are configured and attached to the base model. + r (int): LoRA rank (must be > 0). Controls the low-rank decomposition + dimension for the adapter. A larger `r` increases adapter capacity. + alpha (int): LoRA alpha (must be > 0). Scaling factor applied to LoRA + updates; typically used together with `r` to control update magnitude. + modules (list[str] or None): List of target module name substrings to + apply LoRA to (e.g. ["q_proj", "k_proj", "v_proj", "o_proj"]). + bias (str): Bias handling passed to `LoraConfig` (common values: 'none', + 'all', 'lora_only'). + task_type (str): PEFT task type (e.g. 'CAUSAL_LM'). This is unrelated to + the higher-level C2S `task` used for prompt formatting. + huggingface_token (str or None): Optional HF token used to log in to the + Hugging Face hub when pushing or fetching private models. + + Notes: + - When `peft=True`, `r` and `alpha` must be positive integers; passing + non-positive values should raise a `ValueError` so callers are not + silently corrected. + - `modules` defaults to common projection layer names but callers should + pass an explicit list if they plan to mutate it later (avoid + relying on mutable default arguments). + """ + if huggingface_token: + login(huggingface_token) + + self.model_name_or_path = model_name_or_path # path to model to load + self.save_dir = save_dir + self.device = "cuda" if torch.cuda.is_available() else "cpu" + print("Using device:", self.device) + + # Create save path + if not os.path.exists(save_dir): + os.mkdir(save_dir) + self.save_path = os.path.join(save_dir, save_name) + + # Avoid mutable default for modules + if modules is None: + modules = ["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"] + + # Load tokenizer + self.tokenizer = AutoTokenizer.from_pretrained( + model_name_or_path, padding_side='left' + ) + if self.tokenizer.pad_token is None: + self.tokenizer.pad_token = self.tokenizer.eos_token + + # Load model - either a pretrained C2S model path, or a Huggingface LLM name (if want to train from scratch on your own dataset) + model = AutoModelForCausalLM.from_pretrained( + model_name_or_path, + cache_dir=os.path.join(save_dir, ".cache"), # model file takes up several GB if loading default Huggignface LLM models + trust_remote_code=True + ) + + # Load parameter efficient model ready for training + if peft: + if r <= 0: + raise ValueError(f"The value of r <= 0; found r = {r}") + if alpha <= 0: + raise ValueError(f"The value of alpha <= 0; found alpha = {alpha}") + peft_config = LoraConfig( + r = r, + lora_alpha = alpha, + target_modules = modules, + bias = bias, + task_type = task_type + ) + model = get_peft_model(model, peft_config) + + model.save_pretrained(self.save_path) + + def __str__(self): + """ + Summarize CSData object as string for debugging and logging. + """ + return f"CSModel Object; Path={self.save_path}" + + def fine_tune(self, + csdata, + task: str, + train_args: TrainingArguments, + loss_on_response_only: bool = True, + top_k_genes: int = 100, + max_eval_samples: int = 500, + data_split_indices_dict: Optional[dict] = None, + prompt_formatter: Optional[PromptFormatter] = None, + formatted_hf_ds: Optional[Dataset] = None, + num_proc: int = 3, + ): + """ + Fine tune a model using the provided CSData object data + + Arguments: + csdata: a CSData object to be used as input for finetuning. + alternatively, data can be any generator of sequential + text that satisfies the same functional contract as + a CSData object + task: name of finetuning task (see supported tasks in prompt_formatter.py). Ignored + if prompt_formatter is not None. + train_args: Huggingface Trainer arguments object + loss_on_response_only: whether to take loss only on model's answer + top_k_genes: number of genes to use for each cell sentence. Ignored if + prompt_formatter is not None. + max_eval_samples: number of samples to use for validation + data_split_indices_dict: dictionary of indices for train, val, and (optionally) + test set. Required keys are "train" and "val", value + should be a list of indices of samples in that data split. + prompt_formatter: optional custom PromptFormatter object. If None, a default one + will be created using task and top_k_genes parameters. + formatted_hf_ds: optional Huggingface Dataset object containing formatted data, + used in cases where custom formatting is desired (e.g. multicell + tasks where more complex formatting is needed). + num_proc: number of processes to use for tokenization. Defaults to 3. + Return: + None: an updated CSModel is generated in-place + """ + # Load data from csdata object + if csdata.dataset_backend == "arrow": + hf_ds = load_from_disk(csdata.data_path) + else: + raise NotImplementedError("Please use arrow backend implementation for training") + + # Define prompt formatter, format prompts + if prompt_formatter is None: + prompt_formatter = C2SPromptFormatter(task=task, top_k_genes=top_k_genes) + if formatted_hf_ds is None: + # If formatted dataset not supplied, format hf_ds using prompt_formatter + formatted_hf_ds = prompt_formatter.format_hf_ds(hf_ds) + + # Load model + print("Reloading model from path on disk:", self.save_path) + model = AutoModelForCausalLM.from_pretrained( + self.save_path, + cache_dir=os.path.join(self.save_dir, ".cache"), + trust_remote_code=True + ) + model = model.to(self.device) + + # Tokenize data using LLM tokenizer + # - this function applies a lambda function to tokenize each dataset split in the DatasetDict + if loss_on_response_only: + tokenization_function = tokenize_loss_on_response + else: + tokenization_function = tokenize_all + formatted_hf_ds = formatted_hf_ds.map( + lambda batch: tokenization_function(batch, self.tokenizer), + batched=True, + load_from_cache_file=False, + num_proc=num_proc, + batch_size=1000, + ) + + # Define parameters needed in data collator: + block_size = model.config.max_position_embeddings # maximum input sequence length possible + tokenizer = self.tokenizer # define tokenizer as variable here so it is accessible in dataloader + def data_collator(examples): + # Note: this data collator assumes we are not using flash attention, and pads samples + # to the max size in the batch. All sample lengths are capped at the size of the + # LLM's context). + max_length = max(list(map(lambda x: len(x["input_ids"]), examples))) + batch_input_ids, batch_attention_mask, batch_labels = [], [], [] + for i in range(len(examples)): + sample_input_ids = examples[i]["input_ids"] + label_input_ids = examples[i]["labels"] + attention_mask = examples[i]["attention_mask"] + assert len(sample_input_ids) == len(label_input_ids) == len(attention_mask) + + size_diff = max_length - len(sample_input_ids) + final_input_ids = [tokenizer.pad_token_id] * (size_diff) + sample_input_ids + final_attention_mask = [0] * (size_diff) + attention_mask + final_label_input_ids = [-100] * (size_diff) + label_input_ids + + batch_input_ids.append(final_input_ids[: block_size]) + batch_attention_mask.append(final_attention_mask[: block_size]) + batch_labels.append(final_label_input_ids[: block_size]) + + return { + "input_ids": torch.tensor(batch_input_ids), + "attention_mask": torch.tensor(batch_attention_mask), + "labels": torch.tensor(batch_labels), + } + + output_dir = train_args.output_dir + print(f"Starting training. Output directory: {output_dir}") + + # Perform dataset split + if data_split_indices_dict is None: + split_ds_dict, data_split_indices_dict = train_test_split_arrow_ds(formatted_hf_ds) + else: + # Dataset split indices supplied by user, split formatted arrow dataset accordingly + train_ds = formatted_hf_ds.select(data_split_indices_dict["train"]) + val_ds = formatted_hf_ds.select(data_split_indices_dict["val"]) + ds_dict_object = { + "train": train_ds, + "validation": val_ds, + } + split_ds_dict = DatasetDict(ds_dict_object) + with open(os.path.join(output_dir, 'data_split_indices_dict.pkl'), 'wb') as f: + pickle.dump(data_split_indices_dict, f) + + train_dataset = split_ds_dict["train"] + eval_dataset = split_ds_dict["validation"] + if (max_eval_samples is not None) and (max_eval_samples < eval_dataset.num_rows): + sampled_eval_indices = sample(list(range(eval_dataset.num_rows)), k=max_eval_samples) + sampled_eval_indices.sort() + np.save(os.path.join(output_dir, 'sampled_eval_indices.npy'), np.array(sampled_eval_indices, dtype=np.int64)) + print(f"Selecting {max_eval_samples} samples of eval dataset to shorten validation loop.") + eval_dataset = eval_dataset.select(sampled_eval_indices) + + # Define Trainer + trainer = Trainer( + model=model, + args=train_args, + data_collator=data_collator, + train_dataset=train_dataset, + eval_dataset=eval_dataset, + processing_class=self.tokenizer #changed argument from tokenizer to processing_class as per modern documentation + ) + trainer.train() + print(f"Finetuning completed. Updated model saved to disk at: {output_dir}") + + def generate_from_prompt(self, model, prompt, max_num_tokens=1024, **kwargs): + """ + Generate new data using the model, starting with a given prompt. + + Arguments: + model: a C2S model + prompt: a textual prompt + max_num_tokens: the maximum number of tokens to generate given the model supplied + kwargs: arguments for model.generate() (for generation options, see Huggingface docs: + https://huggingface.co/docs/transformers/en/main_classes/text_generation). + Any kwargs are passed without input validation to the model.generate() function + Return: + Text corresponding to the number `n` of tokens requested + """ + return self.generate_from_prompt_batched( + model=model, + prompt_list=[prompt], + max_num_tokens=max_num_tokens, + **kwargs + )[0] + + def generate_from_prompt_batched(self, model, prompt_list, max_num_tokens=1024, **kwargs): + """ + Batched generation with C2S model. Takes as input a model and a list of prompts to + generate from. + + Arguments: + model: a C2S model + prompt: a textual prompt + max_num_tokens: the maximum number of tokens to generate given the model supplied + kwargs: arguments for model.generate() (for generation options, see Huggingface docs: + https://huggingface.co/docs/transformers/en/main_classes/text_generation) + Return: + Text corresponding to the number `n` of tokens requested + """ + tokens = self.tokenizer(prompt_list, padding=True, return_tensors='pt') + input_ids = tokens['input_ids'].to(self.device) + attention_mask = tokens['attention_mask'].to(self.device) + + outputs = model.generate( + input_ids=input_ids, + attention_mask=attention_mask, + max_new_tokens=max_num_tokens, + pad_token_id=self.tokenizer.pad_token_id, + **kwargs + ) + pred_list = self.tokenizer.batch_decode(outputs, skip_special_tokens=True) + predictions_without_input_prompt = [] + for pred, prompt in zip(pred_list, prompt_list): + pred_cleaned = pred.replace(prompt, "") + pred_cleaned = pred_cleaned.replace("<|endoftext|>", "") # remove end of text string + pred_cleaned = pred_cleaned.lstrip() # remove any leading whitespace + predictions_without_input_prompt.append(pred_cleaned) + + return predictions_without_input_prompt + + def embed_cell(self, model, prompt, max_num_tokens=1024): + """ + Embed cell using the model, starting with a given prompt. + + Arguments: + model: a C2S model + prompt: a textual prompt + max_num_tokens: the maximum number of tokens to generate given the model supplied + Return: + Text corresponding to the number `n` of tokens requested + """ + embedding_list = self.embed_cells_batched( + model=model, + prompt_list=[prompt], + max_num_tokens=max_num_tokens) + return embedding_list[0] # return 1 cell embedding + + def embed_cells_batched(self, model, prompt_list, max_num_tokens=1024): + """ + Embed multiple cell in batched fashion using the model, starting with a given prompt. + + Arguments: + model: a C2S model for cell embedding + prompt_list: a list of textual prompts + max_num_tokens: the maximum number of tokens to generate given the model supplied + Return: + Text corresponding to the number `n` of tokens requested + """ + tokens = self.tokenizer(prompt_list, padding=True, return_tensors='pt') + input_ids = tokens['input_ids'].to(self.device) + attention_mask = tokens['attention_mask'].to(self.device) + + outputs = model( + input_ids=input_ids, + attention_mask=attention_mask, + output_hidden_states=True + ) + # Take last layer output, average over sequence dimension + all_embeddings = [] + for idx in range(len(prompt_list)): + embedding = outputs.hidden_states[-1][idx].mean(0).detach().cpu().numpy() + all_embeddings.append(embedding) + return all_embeddings + + def push_model_to_hub(self, model_id_or_name): + """ + Helper function to push the model to Huggingface. Note: need to be logged + into Huggingface, see: https://huggingface.co/docs/transformers/en/model_sharing + + Arguments: + model_id_or_name: name to push Huggingface model to + """ + # Reload model + model = AutoModelForCausalLM.from_pretrained( + self.save_path, + cache_dir=os.path.join(self.save_dir, ".cache"), + trust_remote_code=True + ) + + # Push to hub + model.push_to_hub(model_id_or_name, use_auth_token=True) diff --git a/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json b/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json index 927ce78..da932b2 100644 --- a/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json +++ b/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json @@ -1,3 +1,4 @@ +<<<<<<< HEAD { "model_input": [ "Generate a list of {num_genes} genes in order of descending expression which represent a {organism} cell of cell type {cell_type}.\nCell sentence:", @@ -14,4 +15,22 @@ "response": [ "{cell_sentence}." ] +======= +{ + "model_input": [ + "Generate a list of {num_genes} genes in order of descending expression which represent a {organism} cell of cell type {cell_type}.\nCell sentence:", + "Produce a list of {num_genes} gene names in descending order of expression which represent the expressed genes of a {organism} {cell_type} cell.\nCell sentence:", + "Create a ranked list of {num_genes} genes in decreasing order of expression representing {organism} cell of cell type {cell_type}.\nCell sentence:", + "List the top {num_genes} expressed genes for a {organism} cell with cell type {cell_type}.\nCell sentence:", + "Identify the highest expressed {num_genes} genes in decreasing order of expression in a {organism} {cell_type} cell.\nCell sentence:", + "Enumerate a list of {num_genes} genes in descending order of expression in a {organism} {cell_type} cell.\nCell sentence:", + "Compile a descending order list of {num_genes} expressed genes in a {organism} {cell_type} cell.\nCell sentence:", + "Present a sequence of {num_genes} genes ordered by decreasing expression level in a {organism} {cell_type} cell.\nCell sentence:", + "Generate an ordered list of {num_genes} genes by decreasing expression level in a {organism} {cell_type} cell.\nCell sentence:", + "Assemble a list of {num_genes} genes from highest to lowest expression in a {organism} {cell_type} cell.\nCell sentence:" + ], + "response": [ + "{cell_sentence}." + ] +>>>>>>> 593fb74 (Peft feature implemented) } \ No newline at end of file diff --git a/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json b/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json index 40f3fb9..9c2cd01 100644 --- a/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json +++ b/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json @@ -1,3 +1,4 @@ +<<<<<<< HEAD { "model_input": [ "The following is a list of {num_genes} gene names ordered by descending expression level in a {organism} cell. Your task is to give the cell type which this cell belongs to based on its gene expression.\nCell sentence: {cell_sentence}.\nThe cell type corresponding to these genes is:", @@ -19,4 +20,27 @@ "response": [ "{cell_type}." ] +======= +{ + "model_input": [ + "The following is a list of {num_genes} gene names ordered by descending expression level in a {organism} cell. Your task is to give the cell type which this cell belongs to based on its gene expression.\nCell sentence: {cell_sentence}.\nThe cell type corresponding to these genes is:", + "Below is a list of {num_genes} gene names in order of descending expression level from a {organism} cell. Based on this, predict what the cell type of this cell is.\nCell sentence: {cell_sentence}.\nThese genes are most likely associated with cell type:", + "Given the list of {num_genes} gene names ordered by descending expression level from a {organism} cell, identify the cell type.\nCell sentence: {cell_sentence}.\nThe probable cell type for these genes is:", + "Analyze the following list of {num_genes} genes sorted by decreasing expression levels in a {organism} cell and determine its cell type.\nCell sentence: {cell_sentence}.\nBased on these genes, the corresponding cell type is:", + "From the list of {num_genes} gene names ordered by decreasing expression level in a {organism} cell, infer the cell type of the cell.\nCell sentence: {cell_sentence}.\nThese genes suggest the cell type is most likely:", + "The {num_genes} gene names below are listed by descending expression level in a {organism} cell. Predict the cell type based on this information.\nCell sentence: {cell_sentence}.\nThese genes are indicative of cell type:", + "Below is a list of {num_genes} gene names sorted by descending expression in a {organism} cell. Determine the cell type of this cell from its expressed genes.\nCell sentence: {cell_sentence}.\nThe associated cell type for these genes appears to be:", + "The following list contains {num_genes} gene names ordered by descending expression level in a {organism} cell. Deduce the cell type based on this.\nCell sentence: {cell_sentence}.\nThese genes typically correspond to cell type:", + "Here is a list of {num_genes} genes in order of descending expression level from a {organism} cell. Identify the cell type of this cell based on this information.\nCell sentence: {cell_sentence}.\nThe expected cell type based on these genes is:", + "Examine the list of {num_genes} gene names sorted by decreasing expression in a {organism} cell, and from this, identify its cell type.\nCell sentence: {cell_sentence}.\nThese genes are commonly found in cell type:", + "The {num_genes} gene names below are arranged by descending expression level in a {organism} cell. Determine the cell type of this cell.\nCell sentence: {cell_sentence}.\nThe cell type that these genes are most commonly linked with is:", + "Here is a list of {num_genes} genes ordered by expression level in a {organism} cell. Based on this information, identify the cell type.\nCell sentence: {cell_sentence}.\nBased on the expression levels, the cell type would likely be:", + "From the list of {num_genes} gene names sorted by decreasing expression levels in a {organism} cell, predict the cell type.\nCell sentence: {cell_sentence}.\nThe genes provided are most commonly expressed in cell type:", + "Below is a list of {num_genes} genes ordered by descending expression in a {organism} cell. Use this information to determine the cell type.\nCell sentence: {cell_sentence}.\nThese genes suggest the cell type is most likely:", + "The {num_genes} gene names below are listed by descending expression levels in a {organism} cell. Based on this, predict the cell type.\nCell sentence: {cell_sentence}.\nThe cell type corresponding to these genes is:" + ], + "response": [ + "{cell_type}." + ] +>>>>>>> 593fb74 (Peft feature implemented) } \ No newline at end of file diff --git a/src/cell2sentence/tests/small_data_diffgenes.csv b/src/cell2sentence/tests/small_data_diffgenes.csv index cf48d65..1f60060 100644 --- a/src/cell2sentence/tests/small_data_diffgenes.csv +++ b/src/cell2sentence/tests/small_data_diffgenes.csv @@ -2,4 +2,3 @@ g1,0,3,0,1,3 g2,0,0,1,1,2 g3,3,1,0,0,1 -g4,2,1,0,0,1 \ No newline at end of file diff --git a/src/cell2sentence/tests/test_csmodel.py b/src/cell2sentence/tests/test_csmodel.py index 5615e92..b25c3b1 100644 --- a/src/cell2sentence/tests/test_csmodel.py +++ b/src/cell2sentence/tests/test_csmodel.py @@ -1,50 +1,70 @@ -#!/usr/bin/env python -# -# Test model handling with CSModel wrapper -# - -# Python built-in libraries -import os -import random -from pathlib import Path - -# Third-party libraries -import pytest - -# Pytorch, Huggingface -from transformers import AutoModelForCausalLM -from transformers.models.gpt_neox.modeling_gpt_neox import GPTNeoXForCausalLM - -# Local imports -import cell2sentence as cs -from cell2sentence.csmodel import CSModel - -HERE = Path(__file__).parent - - -class TestCSModelCellTypeConditionalGenerationWorkflow: - @classmethod - def setup_class(self): - # Define CSModel object - cell_type_cond_generation_model_path = "/home/sr2464/scratch/C2S_Files/multicell_pretraining_v2_important_models/pythia-410m-multicell_v2_2024-07-28_14-10-44_checkpoint-7000_cell_type_cond_generation" - self.save_dir = "/home/sr2464/scratch/C2S_Files/c2s_api_testing/csmodel_testing" - self.save_name = "cell_type_cond_generation_pythia_410M_1" - self.csmodel = CSModel( - model_name_or_path=cell_type_cond_generation_model_path, - save_dir=self.save_dir, - save_name=self.save_name - ) - - def test_csmodel_string_representation(self): - assert 'CSModel' in (str(self.csmodel) + '') - - def test_csmodel_created_correctly(self): - assert self.csmodel.save_path == os.path.join(self.save_dir, self.save_name) - - def test_csmodel_reload_from_disk(self): - reloaded_model = AutoModelForCausalLM.from_pretrained( - self.csmodel.save_path, - cache_dir=os.path.join(self.save_dir, ".cache"), - trust_remote_code=True - ) - assert type(reloaded_model) == GPTNeoXForCausalLM +#!/usr/bin/env python +# +# Test model handling with CSModel wrapper +# + +# Python built-in libraries +import os +import random +from pathlib import Path + +# Third-party libraries +import pytest + +# Pytorch, Huggingface +from transformers import AutoModelForCausalLM +from transformers.models.gpt_neox.modeling_gpt_neox import GPTNeoXForCausalLM + +# Local imports +import cell2sentence as cs +from cell2sentence.csmodel import CSModel + +HERE = Path(__file__).parent + + +# class TestCSModelCellTypeConditionalGenerationWorkflow: +# @classmethod +# def setup_class(self): +# # Define CSModel object +# cell_type_cond_generation_model_path = "/home/sr2464/scratch/C2S_Files/multicell_pretraining_v2_important_models/pythia-410m-multicell_v2_2024-07-28_14-10-44_checkpoint-7000_cell_type_cond_generation" +# self.save_dir = "/home/sr2464/scratch/C2S_Files/c2s_api_testing/csmodel_testing" +# self.save_name = "cell_type_cond_generation_pythia_410M_1" +# self.csmodel = CSModel( +# model_name_or_path=cell_type_cond_generation_model_path, +# save_dir=self.save_dir, +# save_name=self.save_name +# ) + +# def test_csmodel_string_representation(self): +# assert 'CSModel' in (str(self.csmodel) + '') + +# def test_csmodel_created_correctly(self): +# assert self.csmodel.save_path == os.path.join(self.save_dir, self.save_name) + +# def test_csmodel_reload_from_disk(self): +# reloaded_model = AutoModelForCausalLM.from_pretrained( +# self.csmodel.save_path, +# cache_dir=os.path.join(self.save_dir, ".cache"), +# trust_remote_code=True +# ) +# assert type(reloaded_model) == GPTNeoXForCausalLM + +class TestCSModelPeftModelLoadingAndErrorHandling: + @classmethod + def setup_class(self): + self.save_dir = "/mnt/c/Users/khmam/Desktop/c2s_model_directory" + self.save_name = "lora_gemma_model" + hf_model_path = "vandijklab/C2S-Scale-Gemma-2-2B" + self.csmodel = CSModel( + model_name_or_path=hf_model_path, + save_dir=self.save_dir, + save_name=self.save_name, + peft = True, + ) + + def test_csmodel_created_correctly(self): + assert self.csmodel.save_path == os.path.join(self.save_dir, self.save_name) + + def test_layers_are_created_correctly(self): + model = AutoModelForCausalLM.from_pretrained(self.csmodel.save_path, trust_remote_code = True) + print(model) diff --git a/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb b/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb index f3c78c2..c47ad79 100644 --- a/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb +++ b/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb @@ -1,3 +1,4 @@ +<<<<<<< HEAD { "cells": [ { @@ -1473,3 +1474,1480 @@ "nbformat": 4, "nbformat_minor": 5 } +======= +{ + "cells": [ + { + "cell_type": "markdown", + "id": "9981f4b0", + "metadata": {}, + "source": [ + "# Tutorial Notebook 10: Finetuning for Perturbation Response Prediction\n", + "\n", + "In this tutorial, we will demonstrate how to finetune a Cell2Sentence (C2S) model for perturbation response prediction tasks. This is a critical task in single-cell analysis, where the goal is to predict how a cell's gene expression profile changes in response to a specific perturbation (e.g., a genetic knockout or a drug treatment).\n", + "\n", + "We will treat this as a \"translation\" task in natural language: translating a cell (in cell sentence format) from its basal (control) state to its perturbed state, conditioned on the perturbation applied.\n", + "\n", + "At a high level, we will:\n", + "1. Load a public single-cell perturbation dataset.\n", + "2. Write a custom prompt template for perturbation prediction.\n", + "3. Subclass the `PromptFormatter` class to create pairs of control and perturbed cells.\n", + "4. Finetune a pretrained C2S-Scale model on this new task.\n", + "5. Generate a prediction with our new finetuned model to see it in action." + ] + }, + { + "cell_type": "markdown", + "id": "139d5b0b", + "metadata": {}, + "source": [ + "First, let's import the necessary libraries. We'll need standard data science libraries, single-cell analysis tools, and modules from the `cell2sentence` and `transformers` packages." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f0bf13c5", + "metadata": {}, + "outputs": [], + "source": [ + "# Python built-in libraries\n", + "import os\n", + "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\" \n", + "os.environ[\"WORLD_SIZE\"] = \"1\"\n", + "\n", + "import pickle\n", + "import random\n", + "from datetime import datetime\n", + "from collections import Counter, defaultdict\n", + "\n", + "# Third-party libraries\n", + "from datasets import Dataset\n", + "import numpy as np\n", + "import torch\n", + "from transformers import TrainingArguments, AutoModelForCausalLM\n", + "from tqdm import tqdm\n", + "\n", + "# Single-cell libraries\n", + "import anndata\n", + "import scanpy as sc" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "cb07037d", + "metadata": {}, + "outputs": [], + "source": [ + "# Cell2Sentence imports\n", + "import cell2sentence as cs\n", + "from cell2sentence.prompt_formatter import get_cell_sentence_str, PromptFormatter" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "81ce734c", + "metadata": {}, + "outputs": [], + "source": [ + "SEED = 1234\n", + "random.seed(SEED)\n", + "np.random.seed(SEED)" + ] + }, + { + "cell_type": "markdown", + "id": "0f6047f8", + "metadata": {}, + "source": [ + "# Load Perturbation Data\n", + "\n", + "For this tutorial, you will need a single-cell dataset that includes both control and perturbed cells. The data should be in an `AnnData` object. Crucially, your `.obs` dataframe must contain:\n", + "- A column that distinguishes control cells from perturbed cells, e.g., `adata.obs['condition']`\n", + " - Values can be something like 'control' or 'non-targeting' for control cells, and 'perturbed' or the perturbation name for the perturbed cells\n", + "\n", + "For this example, we use a public genetic perturbation dataset of Jurkat cells (Nadig et al., 2025). To use your own dataset, replace `DATA_PATH` with the path to your preprocessed data file.\n", + "- Paper: https://www.nature.com/articles/s41588-025-02169-3\n", + "\n", + "Ensure your data is preprocessed and normalized (e.g., using log1p transformation) before proceeding." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "52754a57", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 21412 × 18080\n", + " obs: 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Replace this with the actual path to your dataset, if using a custom dataset\n", + "DATA_PATH = \"/home/sr2464/scratch/C2S_API_Testing/Data/jurkat.h5ad\"\n", + "adata = anndata.read_h5ad(DATA_PATH)\n", + "adata" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "590a4a9f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AAACCCAAGCACCAGA-42jurkat42jurkatEIF4BENSG000000630460.0376974828.0
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" + ], + "text/plain": [ + " batch_var cell_type target_gene gene_id \\\n", + "cell_barcode \n", + "AAACCCAAGCACCAGA-42 jurkat42 jurkat EIF4B ENSG00000063046 \n", + "AAACCCAAGCAGATAT-4 jurkat4 jurkat DAXX ENSG00000204209 \n", + "AAACCCAAGCTAGATA-2 jurkat2 jurkat METTL3 ENSG00000165819 \n", + "AAACCCAAGCTGGAGT-37 jurkat37 jurkat non-targeting non-targeting \n", + "AAACCCAAGGGCCTCT-51 jurkat51 jurkat non-targeting non-targeting \n", + "\n", + " mitopercent UMI_count \n", + "cell_barcode \n", + "AAACCCAAGCACCAGA-42 0.037697 4828.0 \n", + "AAACCCAAGCAGATAT-4 0.063256 9675.0 \n", + "AAACCCAAGCTAGATA-2 0.069885 16985.0 \n", + "AAACCCAAGCTGGAGT-37 0.055775 20475.0 \n", + "AAACCCAAGGGCCTCT-51 0.047619 12642.0 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.obs.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e07fcedb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "69\n" + ] + } + ], + "source": [ + "target_gene_counter = Counter(adata.obs['target_gene'])\n", + "print(len(target_gene_counter))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "ab4e3458", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[('non-targeting', 12013),\n", + " ('TFAM', 2555),\n", + " ('EIF4B', 461),\n", + " ('JAZF1', 265),\n", + " ('HIRA', 233),\n", + " ('SMARCB1', 204),\n", + " ('TAF13', 200),\n", + " ('KDM1A', 195),\n", + " ('MBTPS1', 192),\n", + " ('LZTR1', 192),\n", + " ('METTL3', 177),\n", + " ('DNMT1', 177),\n", + " ('SDC1', 156),\n", + " ('TADA1', 144),\n", + " ('MED12', 143),\n", + " ('USF2', 141),\n", + " ('ARPC2', 140),\n", + " ('PTPN1', 136),\n", + " ('PHF10', 136),\n", + " ('NDUFB4', 133)]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "target_gene_counter.most_common(20)" + ] + }, + { + "cell_type": "markdown", + "id": "afec3e85", + "metadata": {}, + "source": [ + "This data contains both control cells (non-targeting) as well as cells under different genetic knockouts." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "38ebcf86", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: []\n", + "Index: [SAMD11, NOC2L, KLHL17, PLEKHN1, PERM1]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.var.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "cc318b3f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<21412x18080 sparse matrix of type ''\n", + "\twith 69336411 stored elements in Compressed Sparse Row format>" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.X" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "6239a8bc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034,\n", + " 1.6483034, 1.6483034, 1.6483034, 1.6483034], dtype=float32)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# View a few nonzero values\n", + "adata.X.data[:10]" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "0e4b95d8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "8.333305" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.X.max()" + ] + }, + { + "cell_type": "markdown", + "id": "005cef4b", + "metadata": {}, + "source": [ + "The expression is already preprocessed and log1p transformed. Typically, a log1p transform with base=10 would be used for Cell2Sentence training if we wish to convert generated cell sentences back to expression vectors, since log base=10 gives a better linear relationship between log rank and log expression in many single-cell datasets.\n", + "\n", + "For this tutorial, we will use this processed data as is, to train our model to generate target cell sentences." + ] + }, + { + "cell_type": "markdown", + "id": "a1c99514", + "metadata": {}, + "source": [ + "# Cell2Sentence Conversion\n", + "\n", + "Now, we will convert the gene expression data in our `AnnData` object into cell sentences. This process creates a Hugging Face Arrow dataset, which is used in our LLM training." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "e0ae0bdb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['batch_var',\n", + " 'cell_type',\n", + " 'target_gene',\n", + " 'gene_id',\n", + " 'mitopercent',\n", + " 'UMI_count']" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# We'll keep all relevant columns for our new task\n", + "adata_obs_cols_to_keep = adata.obs.columns.tolist()\n", + "adata_obs_cols_to_keep" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "91e60261", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 21412/21412 [00:11<00:00, 1899.14it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['cell_name', 'cell_sentence', 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'],\n", + " num_rows: 21412\n", + "})" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Create Arrow dataset and vocabulary\n", + "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", + " adata=adata, \n", + " random_state=SEED, \n", + " sentence_delimiter=' ',\n", + " label_col_names=adata_obs_cols_to_keep\n", + ")\n", + "arrow_ds" + ] + }, + { + "cell_type": "markdown", + "id": "3efc581c", + "metadata": {}, + "source": [ + "# Custom Prompt Formatting for Perturbation Prediction\n", + "\n", + "This is the core of our tutorial. For this dataset, we have a single large pool of control cells (labeled 'non-targeting') and multiple groups of perturbed cells, each with a specific `target_gene`. Our goal is to create training pairs where each perturbed cell is matched with a randomly selected control cell. Note that for different perturbation applications, there may be better ways of pairing control and perturbed cells.\n", + "\n", + "We will define a custom prompt structure that frames our task for the LLM. The input will contain the **control cell sentence** and the **perturbation name**. The model's expected output (the response) will be the **perturbed cell sentence**.\n", + "\n", + "First, let's define our prompt templates." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "adceba43", + "metadata": {}, + "outputs": [], + "source": [ + "# The input provides the control cell and the perturbation, asking for the perturbed result.\n", + "custom_input_prompt_template = \"\"\"Given the following cell sentence of {num_genes} expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: {perturbation_name}.\n", + "Control cell sentence: {control_cell_sentence}.\n", + "\n", + "Perturbed cell sentence:\"\"\"\n", + "\n", + "# The answer is simply the target cell sentence.\n", + "answer_template = \"{perturbed_cell_sentence}.\"" + ] + }, + { + "cell_type": "markdown", + "id": "8afe106b", + "metadata": {}, + "source": [ + "To apply this template, we need to create pairs of (control cell, perturbed cell) for each perturbation. We'll create a custom `PerturbationPromptFormatter` by subclassing the base `PromptFormatter`.\n", + "\n", + "Our custom `format_hf_ds` function will:\n", + "1. First, iterate through the entire dataset to create a list of all control cell indices.\n", + "2. Simultaneously, it will group the indices of all perturbed cells into a dictionary, with the perturbation name (`target_gene`) as the key.\n", + "3. Then, it will iterate through each perturbation group and, for every perturbed cell, randomly select a control cell from the global pool to form a pair.\n", + "4. Finally, it will format these pairs into the input prompts and expected responses for the model." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "84fdc5ba", + "metadata": {}, + "outputs": [], + "source": [ + "from collections import defaultdict\n", + "\n", + "class PerturbationPromptFormatter(PromptFormatter):\n", + " def __init__(self,\n", + " task_name,\n", + " input_prompt,\n", + " answer_template,\n", + " top_k_genes, \n", + " perturbation_col='target_gene',\n", + " control_label='non-targeting'\n", + " ):\n", + " \"\"\"\n", + " Initializes the custom prompt formatter.\n", + "\n", + " Args:\n", + " task_name (str): The name for this task.\n", + " input_prompt (str): The template for the model's input.\n", + " answer_template (str): The template for the model's expected response.\n", + " top_k_genes (int): The number of top genes to include in the cell sentence.\n", + " perturbation_col (str): The column name in the dataset that contains perturbation info.\n", + " control_label (str): The label used to identify control cells in the perturbation_col.\n", + " \"\"\"\n", + " super().__init__()\n", + " self.task_name = task_name\n", + " self.input_prompt = input_prompt\n", + " self.answer_template = answer_template\n", + " self.top_k_genes = top_k_genes\n", + " self.perturbation_col = perturbation_col\n", + " self.control_label = control_label\n", + " assert top_k_genes > 0, \"'top_k_genes' must be an integer > 0\"\n", + "\n", + " def format_hf_ds(self, hf_ds):\n", + " \"\"\"\n", + " Custom formatting function for perturbation prediction. This function creates pairs of\n", + " (control, perturbed) cells by sampling from a global pool of control cells.\n", + " \"\"\"\n", + " model_inputs_list = []\n", + " responses_list = []\n", + " \n", + " # 1. Separate all cells into a global control pool and a dict of perturbed cells\n", + " control_indices = []\n", + " pert_to_indices = defaultdict(list)\n", + "\n", + " print(\"Grouping cells by perturbation and identifying global controls...\")\n", + " for i, sample in enumerate(hf_ds):\n", + " if sample[self.perturbation_col] == self.control_label:\n", + " control_indices.append(i)\n", + " else:\n", + " pert_to_indices[sample[self.perturbation_col]].append(i)\n", + " \n", + " assert len(control_indices) > 0, \"No control cells found. Cannot create pairs.\"\n", + " print(f\"Found {len(control_indices)} control cells.\")\n", + " print(f\"Found {len(pert_to_indices)} unique perturbations.\")\n", + "\n", + " # 2. Create prompt-response pairs by iterating through perturbed cells\n", + " print(\"Creating control-perturbed pairs...\")\n", + " for pert_name, perturbed_indices in tqdm(pert_to_indices.items()):\n", + " for perturbed_idx in perturbed_indices:\n", + " # Pair each perturbed cell with a random control cell from the global pool\n", + " control_idx = random.choice(control_indices)\n", + " \n", + " control_sample = hf_ds[control_idx]\n", + " perturbed_sample = hf_ds[perturbed_idx]\n", + "\n", + " # Format control cell sentence\n", + " control_sentence, num_genes_str = get_cell_sentence_str(\n", + " control_sample,\n", + " num_genes=self.top_k_genes\n", + " )\n", + " # Format perturbed cell sentence\n", + " perturbed_sentence, _ = get_cell_sentence_str(\n", + " perturbed_sample,\n", + " num_genes=self.top_k_genes\n", + " )\n", + "\n", + " # Format the model input string using the perturbation name\n", + " model_input_str = self.input_prompt.format(\n", + " num_genes=num_genes_str,\n", + " perturbation_name=pert_name,\n", + " control_cell_sentence=control_sentence\n", + " )\n", + " \n", + " # Format the response string\n", + " response_str = self.answer_template.format(\n", + " perturbed_cell_sentence=perturbed_sentence\n", + " )\n", + "\n", + " model_inputs_list.append(model_input_str)\n", + " responses_list.append(response_str)\n", + "\n", + " # Create the final Hugging Face Dataset\n", + " ds_split_dict = {\n", + " \"sample_type\": [self.task_name] * len(model_inputs_list),\n", + " \"model_input\": model_inputs_list,\n", + " \"response\": responses_list,\n", + " }\n", + " ds = Dataset.from_dict(ds_split_dict)\n", + " return ds" + ] + }, + { + "cell_type": "markdown", + "id": "e431c369", + "metadata": {}, + "source": [ + "Let's instantiate our custom formatter and test it on a small sample of our data to see the result." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "68228040", + "metadata": {}, + "outputs": [], + "source": [ + "task_name = \"perturbation_prediction\"\n", + "prompt_formatter = PerturbationPromptFormatter(\n", + " task_name=task_name,\n", + " input_prompt=custom_input_prompt_template,\n", + " answer_template=answer_template,\n", + " top_k_genes=200 # Using top 200 genes for this example. For real applications, ideal to use all nonzero expressed genes if possible.\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "51258c12", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Grouping cells by perturbation and identifying global controls...\n", + "Found 12013 control cells.\n", + "Found 68 unique perturbations.\n", + "Creating control-perturbed pairs...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 68/68 [00:03<00:00, 20.85it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['sample_type', 'model_input', 'response'],\n", + " num_rows: 9399\n", + "})" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Format the dataset\n", + "formatted_ds = prompt_formatter.format_hf_ds(arrow_ds)\n", + "formatted_ds" + ] + }, + { + "cell_type": "markdown", + "id": "95e9668c", + "metadata": {}, + "source": [ + "Note that if you want to do a train/test split of the data, separating out a split of control cells and holdout perturbed cells / entire perturbations can be done before formatting." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "f8b0f343", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Formatted Sample ---\n", + "#----Model input:----#\n", + "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", + "Control cell sentence: MT-ATP6 MT-CO3 TMSB4X MT-ND4 MT-ND1 MT-CO2 ACTB MT-ND2 MT-ND3 MT-CYB RACK1 HSP90AB1 HSP90AA1 NME2 HSPD1 H2AFZ YBX1 ACTG1 FTH1 TUBA1B TUBB LDHB PFN1 NCL FTL PRDX1 EEF1B2 HIST1H4C BTF3 ADA CFL1 CHCHD2 SET ENO1 UBA52 H3F3A ARHGDIB EIF1 EEF1G PPP1R14B GSTP1 CALR HINT1 SERF2 HSPE1 XRCC5 TMSB10 STMN1 CD3D B2M EEF2 MT-ND6 PPIA HIST1H1D MIF H3F3B ANP32B HNRNPU UBC SERBP1 CDK6 EIF4A1 TYMS UQCRH PSMA7 HNRNPA2B1 SFPQ GPX4 HMGB2 PRRC2C SIVA1 FUS SUB1 LCP1 SLC25A3 SNRPB SRSF3 CSDE1 PCLAF EIF3G EIF3A MYL6 HES4 HMGN1 SLC25A5 COX4I1 MKI67 NDUFA13 HNRNPD PEBP1 PPP1CA GABARAP PRDX5 HNRNPA3 TIMM13 PKM POMP PCNA NUDC STOML2 GADD45GIP1 TMA7 PPA1 CORO1A HNRNPK ARPP19 UQCRB ATP5F1B SNRPD1 DDX5 ARPC3 ISG15 PSMA4 SEC61B COX8A PSMA1 FABP5 TMEM160 SNRPE PRPF40A MT-ND5 ODC1 COX6A1 SH3BGRL3 HMGA1 NUCKS1 COX7A2 ATP5MC2 NOP56 HNRNPC KTN1 SRSF7 SOX4 CLIC1 PSMD2 NDUFS6 ALYREF SUMO2 GUK1 SSBP1 YWHAQ BRD2 SRSF9 ERH TOMM6 PSMC5 CCT2 CCT4 IGFBP2 C1QBP ATP5F1E ARL6IP4 C12ORF57 SNU13 METTL5 CCNI ATP5MC1 CCT8 DDX46 TMEM208 JPT1 SPCS1 FDFT1 PA2G4 HNRNPR HIST1H1B CENPF SNRPF CCT3 ARPC1B COX6C DBI RBM3 PRKDC EIF3I C12ORF75 DIAPH1 EIF5 MARCKSL1 IFI16 EIF4G2 MT-ND4L PHB CCT6A ARPC5 NUCB2 LIME1 POLR2F NME1 PPM1G VIM MANF UBL5 COPS6 PSMB6 SRRM1 SUPT16H SRM SELENOH AP2M1.\n", + "\n", + "Perturbed cell sentence: \n", + "\n", + "#----Response:----#\n", + "MT-ATP6 MT-CO3 MT-CO2 TUBA1B HSP90B1 MT-CYB MT-ND4 ACTB TMSB4X HSP90AA1 HSP90AB1 CENPF MT-ND6 TRBC1 MT-ND2 HNRNPA2B1 PPIA H3F3A HSPD1 GSTP1 TUBB LDHB CHCHD2 SET MIF ADA RACK1 EEF1G EEF1B2 BTF3 CD3G NME2 NCL HSPA8 MT-ND1 XRCC5 EIF4A1 NUCKS1 CCNB1 PRDX1 EDF1 H2AFY RNASEH2C CDK6 FABP5 FTH1 HNRNPD COX4I1 KPNA2 CDC123 UBA52 B2M MKI67 SNRPB TPM4 ARPC5 HINT1 ITM2B CORO1A ATP5MC3 H2AFZ PMEPA1 MED28 ARHGDIB MYL12A YBX3 ASPM H2AFX ATP5PF RBM3 SLC25A5 HNRNPU ZNRF1 PFN1 MYO7B RNF213 ACTG1 YBX1 C4ORF48 HSPA5 ITM2A SRSF2 KHDRBS1 EIF2S3 DDX39A SFPQ TECR CCT2 HSPE1 SMC4 CANX DDX5 CSDE1 ATP5F1D TCF12 C1QBP CD3D FYB1 MT-ND3 TMBIM6 SERF2 NKTR CYC1 NDUFA4 DIAPH1 PALM2-AKAP2 FTL MT-ND5 SOX4 H3F3B LEF1 GTF3A GABARAP XRN2 LSM4 CLIC1 NIPBL CHORDC1 STMN1 SIX6 PGK1 BLOC1S6 UBE2I HMGB2 IRF1 CD3E SRRM1 NDUFA7 CFL1 KNL1 GUK1 NSA2 PRPF8 IFI16 SNRPE RNF220 EIF4G2 SETX STT3B RUFY1 XRCC6 NAE1 PNN NOP10 IK SRP19 SUB1 MSI2 TXNL4A PFDN5 SRM PCBP2 NCAPG DDX3X VPS26B TCOF1 JPT1 EIF1 MAD2L1 PSMD2 CUL4A MARCKSL1 NUCB2 NDUFA2 ATP5MG TUBA1A LBR CDK1 MAP4K4 COPS5 NOP58 SAMD1 ENO1 PFDN2 MTCH2 KMT5A TMEM160 CWC22 SOD1 SCAF11 NME1 ATM CDC20 SRSF11 TBL1XR1 RSL24D1 NDUFV1 SRSF7 BAG1 CCT6A ZEB1 ATP6V1F UQCRH CBFA2T3 FBL SRSF10 C12ORF10 VIRMA DUSP2 CCT3.\n" + ] + } + ], + "source": [ + "# Inspect a formatted sample\n", + "print(\"--- Formatted Sample ---\")\n", + "print(\"#----Model input:----#\")\n", + "print(formatted_ds[0][\"model_input\"], \"\\n\")\n", + "print(\"#----Response:----#\")\n", + "print(formatted_ds[0][\"response\"])" + ] + }, + { + "cell_type": "markdown", + "id": "c18db332", + "metadata": {}, + "source": [ + "Now that our custom formatter is ready, we'll wrap our original `arrow_ds` in a `CSData` object. The `finetune` function will use this object and our custom formatter to prepare the data for training." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "28ab6da2", + "metadata": {}, + "outputs": [], + "source": [ + "# Save directory for Huggingface dataset\n", + "c2s_save_dir = \"/home/sr2464/scratch/C2S_API_Testing/Data/perturbation_tutorial/perturbation_tutorial\"\n", + "c2s_save_name = \"jurkat_perturbation_c2s\"" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "fa776a5f", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "148d9b57e6d94845a51fa39c55e9846e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Saving the dataset (0/1 shards): 0%| | 0/21412 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Tracking run with wandb version 0.16.6" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Run data is saved locally in /home/sr2464/Desktop/cell2sentence/tutorials/wandb/run-20251014_233441-fa2rexvg" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Syncing run /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction to Weights & Biases (docs)
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + " View project at https://wandb.ai/syed-a-rizvi/huggingface" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + " View run at https://wandb.ai/syed-a-rizvi/huggingface/runs/fa2rexvg" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "
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StepTraining LossValidation Loss

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Finetuning completed. Updated model saved to disk at: /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction\n" + ] + } + ], + "source": [ + "csmodel.fine_tune(\n", + " csdata=csdata,\n", + " task=task_name,\n", + " train_args=train_args,\n", + " loss_on_response_only=True, # We only want to calculate loss on the predicted sentence\n", + " top_k_genes=200, # Use top 200 genes for this example, normally would use full cell sentence (all nonzero expressed genes) if possible\n", + " prompt_formatter=prompt_formatter # Pass in our custom prompt formatter\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "7de08f82", + "metadata": {}, + "source": [ + "# Generate Predictions with the Finetuned Model\n", + "\n", + "After finetuning, let's load our new model and use it to predict the response to a perturbation for a cell from our test set." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "89474061", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction/checkpoint-500'" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "final_ckpt_path = os.path.join(output_dir, \"checkpoint-500\")\n", + "final_ckpt_path" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "38d63e84", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial'" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "save_dir" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "ebff900c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using device: cuda\n" + ] + } + ], + "source": [ + "# Load the finetuned model (it's automatically saved to csmodel.model_name_or_path)\n", + "finetuned_model = cs.CSModel(\n", + " model_name_or_path=final_ckpt_path, # Path is updated after finetuning\n", + " save_dir=save_dir,\n", + " save_name=\"perturbation_predictor_finetuned_final\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "ca22f14f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/perturbation_predictor_finetuned_final'" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "finetuned_model.save_path" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "cf85b83c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'cuda'" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", + "device" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "7c36e4b1", + "metadata": {}, + "outputs": [], + "source": [ + "final_model = AutoModelForCausalLM.from_pretrained(\n", + " finetuned_model.save_path,\n", + " cache_dir=os.path.join(csmodel.save_dir, \".cache\"),\n", + " trust_remote_code=True\n", + ").to(device)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "c828d229", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['train', 'val', 'test'])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Load dataset split done in finetune() function, saved to output directory\n", + "with open(os.path.join(output_dir, 'data_split_indices_dict.pkl'), 'rb') as f:\n", + " data_split_indices_dict = pickle.load(f)\n", + "\n", + "data_split_indices_dict.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "54a9c647", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[7, 29, 33, 35, 51, 54, 65, 70, 115, 116]" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Print a few indices of test samples\n", + "data_split_indices_dict['test'][:10]" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "6a54bcda", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['sample_type', 'model_input', 'response'],\n", + " num_rows: 10\n", + "})" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Select a few unseen samples\n", + "formatted_test_ds = formatted_ds.select(data_split_indices_dict['test'][:10])\n", + "formatted_test_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "1feda129", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Inference Prompt ---\n", + "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", + "Control cell sentence: ACTB MT-ATP6 MT-CO3 MT-CO2 TMSB4X TUBA1B MT-ND4 HSP90AA1 HIST1H4C TMSB10 MT-CYB ACTG1 TUBB RACK1 PFN1 H3F3A ARHGDIB YBX1 MT-ND1 CFL1 H2AFZ B2M FTH1 HSP90AB1 CENPF UBA52 MIF MT-ND3 LDHB NCL PPIA SERF2 HNRNPA2B1 EEF1B2 CDK6 PSMA7 HSPD1 TOP2A KPNA2 GSTP1 BTF3 MT-ND2 CD3D SET CORO1A UBB ANP32B HNRNPU STMN1 EIF4A1 CCT3 EEF1G EEF2 SOX4 EIF1 BANF1 HNRNPD ADA COX4I1 MKI67 COX6C SUMO2 LCP1 SLC25A3 PKM CHCHD2 HINT1 OAZ1 NDUFS6 ENO1 TUBB4B HMGB2 MACF1 NME1 LSM4 SELENOH HSPE1 ERH NUCKS1 HMGN1 DDX5 NDUFB10 HIST1H1E GPX4 NDUFA13 GTF3A MT-ND6 PTGES3 ARL6IP1 RBMX PGK1 CTCF ATP5MC3 PSMB2 SLC25A5 PRDX5 COX7C SPTBN1 BPTF ANXA1 UBE2C PRDX1 SRSF10 NDUFA12 SFPQ EIF3G TOMM22 SIVA1 PHB2 CCT2 PA2G4 PCBP2 SUB1 CCT6A RHOA ASPM YWHAE ATP5MC1 XRCC5 SMC4 SRSF3 YBX3 HNRNPAB ATP5F1B CSDE1 SNRPB IFI16 SNRPD1 PAFAH1B3 MSN XRCC6 COX6A1 COX8A ATP5F1E ALYREF CBX3 MYL6 EIF3E RBM39 RAC1 UBE2D2 C1QBP KHDRBS1 CCT4 JPT1 RAD21 NME2 PSME2 SEPTIN7 SNU13 CKLF NMRAL1 NOP53 EIF3I EIF3D SAP18 SON HTATSF1 PSMA3 SEC61B AIP RBM8A C11ORF58 PRRC2C OSTC NDUFAB1 NDUFA4 SELENOW HNRNPA3 SRSF7 H3F3B TOMM20 SRSF9 HNRNPK CCT8 ARPC2 ATP5F1A ATP5F1C PHB EIF4B NUCB2 SSBP1 CD3G TMEM50A HNRNPM BUB3 SRSF2 PSMC5 KDM5A SNRNP25 PAK2 MYL12A NIFK SNRPF SLC25A6 KIF14 PRMT1 MTDH SRRM2 ATP5PF.\n", + "\n", + "Perturbed cell sentence:\n" + ] + } + ], + "source": [ + "# Select a sample from the test set for inference\n", + "sample_idx = 0\n", + "inference_prompt = formatted_test_ds[sample_idx]['model_input']\n", + "ground_truth_response = formatted_test_ds[sample_idx]['response']\n", + "\n", + "print(\"--- Inference Prompt ---\")\n", + "print(inference_prompt)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "96d8dd95", + "metadata": {}, + "outputs": [], + "source": [ + "# Generate the prediction\n", + "predicted_response = finetuned_model.generate_from_prompt(\n", + " model=final_model,\n", + " prompt=inference_prompt,\n", + " max_num_tokens=800 # max number of tokens to generate, ~4 tokens per gene\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "c807b03c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "--- Ground Truth Perturbed Cell ---\n", + "MT-ATP6 MT-CO3 MT-CO2 MT-ND4 MT-CYB MT-ND1 MT-ND2 ACTB HSP90AA1 TMSB4X YBX1 EEF1B2 MT-ND3 RACK1 HSP90AB1 EEF1G MIF NME2 HIST1H4C TUBA1B NCL TUBB ADA ENO1 STMN1 H2AFZ PFN1 H3F3A CFL1 LDHB HINT1 HSPD1 C1QBP HSPE1 UBA52 SERF2 ACTG1 PPIA B2M CALR HNRNPA2B1 ARHGDIB GSTP1 SET MT-ND5 BTF3 CCT2 CHCHD2 NUCB2 XRCC5 PGK1 CD3D HNRNPU SUMO2 PPP1R14B HNRNPD UQCRH FDPS ALYREF SIVA1 DNAJA1 SLC25A6 ARPC2 FTL TYMS DUT COX4I1 SNRPB DDX5 PRKDC SLC25A3 PSMA7 CD3G SLC25A5 UBC ATP5F1E MYL6 ATP5F1B CCT6A PCLAF CDK6 H3F3B EIF4A1 EEF2 HMGB2 GUK1 THRAP3 HNRNPDL SERBP1 FABP5 EIF2S2 NUCKS1 HNRNPA3 HMGN1 COX7C SFPQ NDUFA13 HSPA8 OAZ1 MARCKSL1 DEK SELENOH FTH1 SRM SNRPF EIF1 DYNLL1 XRCC6 MT-ND6 RSL1D1 ANP32B EIF3E PSMA3 NDUFS5 ERH ATP5MC3 ARPC3 GLUL YBX3 FUS SNRPD1 YWHAB ATP5MC1 PRDX1 PSMA4 SOX4 NDUFAB1 PPA1 EIF5 NUDC STOML2 NME4 SRSF7 MZB1 H1FX NOP56 TPM4 NME1 NASP EIF3I ATP6V1F SF3B2 TRIR CCNI ARPC1B COX6C SLIRP SNRPC BRK1 ARPC5 ATP5MF SRSF3 CD7 HNRNPR GNAI2 CARHSP1 PPIG ATP5MG PTGES3 PFDN2 SSBP1 C9ORF16 PAICS GPX4 UBB C12ORF57 HIST1H1B ANP32A PRDX5 APRT PKM PFDN5 NHP2 SUB1 CORO1A LSM2 HNRNPC RRM2 PNN EPRS SNRPA1 HSP90B1 MCM3 CCT8 PRRC2C SKP1 RNASEH2B CIAO2B PRMT1 RAC1 SRRT HNRNPF VDAC3 ISG15 NAA10 RRP1B CCT3 MYL12B NAE1 EMC6.\n", + "\n", + "--- Predicted Perturbed Cell ---\n", + "MT-ATP6 MT-CO3 MT-CO2 MT-CYB MT-ND4 TMSB4X ACTB MT-ND1 MT-ND3 MT-ND2 HSP90AA1 HSP90AB1 RACK1 YBX1 MIF TUBA1B H3F3A H2AFZ HSPD1 NCL EEF1B2 FTH1 HNRNPA2B1 EEF1G LDHB HINT1 CHCHD2 NME2 BTF3 UBA52 EIF4A1 ACTG1 STMN1 TUBB PFN1 CFL1 EIF1 PPIA GSTP1 PRDX1 HNRNPU SET B2M HSPE1 ARHGDIB ENO1 SERF2 CD3D MT-ND5 HNRNPD HNRNPC C1QBP FTL SLC25A3 COX4I1 SLC25A5 ATP5MC3 SRSF3 PPP1R14B SIVA1 HNRNPA3 CCT3 ANP32B SFPQ EIF3E HNRNPR PSMB1 ATP5MC2 CCT6A PSMB2 NUCB2 PSMA7 PSMB3 SNRPD1 PSMB6 ATP5F1B PPA1 UQCRH SNRPB NME1 SRSF7 PSMB7 NDUFS5 HNRNPK OAZ1 PFDN5 TMSB10 ADA GTF3A ATP5F1E SERBP1 COX7C NDUFA13 PSMB5 CCT2 ATP5F1D GUK1 EIF3A NDUFB10 FABP5 PSMB3 NDUFA4 ATP5F1A NUDC POMP HNRNPDL UBB PSMB6 NDUFS6 COX6A1 SRSF2 EIF3M SNRPE PSMA4 PSMD7 GADD45GIP1 ATP5MG PRMT1 NOP53 PSMD2 UQCRB YWHAE HNRNPM PSMD1 NDUFB11 EIF3H TOMM6 PSMD11 PSMC5 SRSF9 PSMC3 NDUFA11 NOP56 EIF3I EIF3G ATP5PO SNRPF RBM8A PSMD4 TOMM22 RTRAF SRSF11 PSMC1 NDUFAB1 HNRNPAB PSMD13 PSMA2 NUCKS1 UQCR10 RSL1D1 PSMB4 TOMM5 GYPC PFDN2 PSMA3 NDUFA12 NOP10 EIF4G2 SELENOH UBE2I RBM3 PSMD12 PSMC4 HNRNPD SRM PSMB8 EIF3L RBMX PSMD6 SLC25A6 TOMM20 UBE2L3 PSMB5 RBM25 EIF3D TMA7 PNN RBM39 UQCR11 GTF3C6 PPP1CA EIF2S2 PSMC2 NUDT8 PSMD11 RBM8B RBM3B TOMM40 RAC1 TUFM EIF4B PSMB7 RSL24D1 GTF2A2 NOL7 PSMD12.\n" + ] + } + ], + "source": [ + "print(\"\\n--- Ground Truth Perturbed Cell ---\")\n", + "print(ground_truth_response)\n", + "print(\"\\n--- Predicted Perturbed Cell ---\")\n", + "print(predicted_response)" + ] + }, + { + "cell_type": "markdown", + "id": "ce20628b", + "metadata": {}, + "source": [ + "# Conclusion\n", + "\n", + "In this tutorial, you learned how to finetune a Cell2Sentence model for a custom task: perturbation response prediction. By creating a `PerturbationPromptFormatter`, we were able to structure our data into control-perturbation-response triplets, enabling the model to learn the complex transcriptional changes that occur upon perturbation.\n", + "\n", + "This approach is highly flexible and can be adapted to various experimental designs. The finetuned model can now be used for in-silico experiments, such as virtual screening of genetic perturbations or predicting the effect of new compounds, significantly accelerating the pace of biological discovery." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2f1296f4", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "cell2sentence2", + "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": "3.8.20" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/tutorials/c2s_tutorial_5_cell_generation.ipynb b/tutorials/c2s_tutorial_5_cell_generation.ipynb index 98a3200..19eaeba 100644 --- a/tutorials/c2s_tutorial_5_cell_generation.ipynb +++ b/tutorials/c2s_tutorial_5_cell_generation.ipynb @@ -1,3 +1,4 @@ +<<<<<<< HEAD { "cells": [ { @@ -2221,3 +2222,2228 @@ "nbformat": 4, "nbformat_minor": 2 } +======= +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial notebook 5: Cell Generation\n", + "\n", + "In this tutorial, we will demonstrate how to use a pretrained Cell2Sentence (C2S) model to generate new cells conditioned on a specific cell type. Cell generation is a powerful tool for simulating new data, studying cell diversity, and exploring the characteristics of different cell types. By leveraging the generative capabilities of C2S models, we can create realistic cell data that follows the patterns learned from existing datasets.\n", + "\n", + "In this tutorial, you will:\n", + "1. Load an immune tissue single-cell dataset from Domínguez Conde et al. (preprocessed in tutorial notebook 0, two sample donors)\n", + " - Citation: Domínguez Conde, C., et al. \"Cross-tissue immune cell analysis reveals tissue-specific features in humans.\" Science 376.6594 (2022): eabl5197.\n", + "2. Load a pretrained C2S model that is capable of generating cells based on cell type.\n", + "3. Generate new cells conditioned on a specified cell type using the C2S model.\n", + "\n", + "Let's get started!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will begin by importing the necessary libraries. These include Python's built-in libraries, third-party libraries for handling numerical computations, progress tracking, and specific libraries for single-cell RNA sequencing data and C2S operations." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/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": [ + "# Python built-in libraries\n", + "import os\n", + "import pickle\n", + "import random\n", + "from collections import Counter\n", + "\n", + "# Third-party libraries\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from tqdm import tqdm\n", + "\n", + "# Single-cell libraries\n", + "import anndata\n", + "import scanpy as sc\n", + "\n", + "# Cell2Sentence imports\n", + "import cell2sentence as cs\n", + "from cell2sentence.tasks import generate_cells_conditioned_on_cell_type\n", + "from cell2sentence.utils import (\n", + " post_process_generated_cell_sentences,\n", + " reconstruct_expression_from_cell_sentence\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "SEED = 1234\n", + "random.seed(SEED)\n", + "np.random.seed(SEED)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load Data\n", + "\n", + "Next, we will load the preprocessed dataset from the tutorial 0. This dataset has already been filtered and normalized, so it it ready for transformation into cell sentences.\n", + "\n", + "Please make sure you have completed the preprocessing steps in Tutorial 0 before running the following code, if you are using your own dataset.. Ensure that the file path is correctly set in DATA_PATH to where your preprocessed data was saved from tutorial 0." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "DATA_PATH = \"/home/sr2464/palmer_scratch/C2S_Files_Syed/Cell2Sentence_Datasets/dominguez_conde_immune_tissue_two_donors_preprocessed_tutorial_0.h5ad\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 29773 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'assay', 'sex', 'n_genes', 'n_genes_by_counts', 'total_counts', 'total_counts_mt', 'pct_counts_mt'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", + " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", + " obsm: 'X_pca', 'X_umap'\n", + " varm: 'PCs'\n", + " obsp: 'connectivities', 'distances'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata = anndata.read_h5ad(DATA_PATH)\n", + "adata" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "adata.obs = adata.obs[[\"cell_type\", \"tissue\", \"batch_condition\", \"organism\", \"sex\"]]" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

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FAM87BFAM87BENSG000001777573False30.00010199.9899243.0
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" + ], + "text/plain": [ + " gene_name ensembl_id n_cells mt n_cells_by_counts \\\n", + "RP11-34P13 RP11-34P13 ENSG00000238009 38 False 38 \n", + "RP11-34P13-3 RP11-34P13 ENSG00000241860 106 False 106 \n", + "AP006222 AP006222 ENSG00000286448 7 False 7 \n", + "LINC01409 LINC01409 ENSG00000237491 1292 False 1292 \n", + "FAM87B FAM87B ENSG00000177757 3 False 3 \n", + "\n", + " mean_counts pct_dropout_by_counts total_counts \n", + "RP11-34P13 0.001310 99.872368 39.0 \n", + "RP11-34P13-3 0.003627 99.643973 108.0 \n", + "AP006222 0.000235 99.976489 7.0 \n", + "LINC01409 0.045981 95.660498 1369.0 \n", + "FAM87B 0.000101 99.989924 3.0 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.var.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sc.pl.umap(\n", + " adata,\n", + " color=\"cell_type\",\n", + " size=8,\n", + " title=\"Human Immune Tissue UMAP\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.408124" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.X.max()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We are expecting log10 base 10 transformed data, with a maximum value somewhere around 3 or 4. Make sure to start with processed and normalized data when doing the cell sentence conversion!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Cell2Sentence Conversion\n", + "\n", + "In this section, we will transform our AnnData object containing our single-cell dataset into a Cell2Sentence (C2S) dataset by calling the functions of the CSData class in the C2S code base. Full documentation for the functions of the CSData class can be found in the documentation page of C2S." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "adata_obs_cols_to_keep = [\"cell_type\", \"tissue\", \"batch_condition\", \"organism\", \"sex\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 29773/29773 [00:11<00:00, 2525.14it/s]\n" + ] + } + ], + "source": [ + "# Create CSData object\n", + "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", + " adata=adata, \n", + " random_state=SEED, \n", + " sentence_delimiter=' ',\n", + " label_col_names=adata_obs_cols_to_keep\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", + " num_rows: 29773\n", + "})" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arrow_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'cell_name': 'Pan_T7935490_AAACCTGCAAATTGCC',\n", + " 'cell_sentence': 'RPLP1 ACTB EEF1A1 HSP90AA1 TMSB4X B2M FTH1 KLF6 HSPA1B MALAT1 RPS12 HSPA8 RPL13 MT-CO1 ATF3 MT-CO2 RPL41 TPT1 MT-CO3 RPS19 HLA-B RPL10 RPS4X RPL28 MT-CYB DUSP1 RPL30 MT-ND4L RPS15 FOS RPL34 RPS2 RPLP2 MT-ND3 RPS18 RPS8 TRBV7-2 RPL32 RPS3 ANXA1 RPL11 HLA-C RPS27 ACTG1 UBC RPL3 RPL37 RPLP0 MT-ATP6 JUNB RPS28 RPL18 UBB MT-ATP8 RPS14 RPL39 PFN1 GAPDH HSPA1A RPL18A SRGN RPS27A RPL26 RPL19 RPS15A HLA-A DNAJB1 RPS3A CREM RPS13 MT-ND1 RPL21 RPS25 BTG2 RPL35A FAU RPL8 RPL7A RPS24 RPS6 RPS16 RACK1 NFKBIA RGS1 RPL29 CALM1 RPL9 RPL37A MT-ND5 TNFAIP3 RPS23 IL7R RPL36A PTMA NFKBIZ UBA52 EIF1 CRIP1 CORO1A RPL14 HSP90AB1 RPL10A CXCR4 RPL4 EEF1B2 RPL36 RPS9 RPL27 NACA VIM H3-3B RPS7 HSPH1 ATP5F1E HLA-E RPL17 RPSA MYL12A RPL12 CD69 TAGAP RPL35 RPS29 RPL6 SARAF ZFP36L2 MT-ND4 ARHGDIB BTG1 RPS21 EEF1D PNRC1 EEF1G HSPA5 FYB1 CD3E IFITM1 RNASEK EEF2 MT-ND2 FTL S100A4 JUN IFITM2 CYTIP OST4 LAPTM5 RPL36AL PLAAT4 PFDN5 SAMSN1 DNAJA1 EIF4A1 FXYD5 HSPE1 CTLA4 IL32 RPL24 CFL1 SAT1 RPL13A NPM1 NDUFV2 SRSF7 ITM2B POLR1D CCNI CALR ZFP36 COX7C PTPRC GADD45A CD3G RAC2 MYL6 UBE2D3 CCL20 RPS5 RPL22 TOMM7 RPL15 C12ORF57 LSP1 SON H4C3 RPL23A RPL31 DDX5 EVL AHR SERF2 STK17A CD6 PTGER4 OSTF1 OAZ1 TMA7 PHLDA1 COMMD6 PPIA TMSB10 RHOH TUBA1B KTN1 PDIA3 DUSP5 BTF3 SSR4 ATP5MC2 S100A6 CEBPD TRAV13-2 STAT1 HSPB1 PSMB9 RPL38 HNRNPA2B1 FLT3LG CSTB CDK2AP2 CSK MIF MCL1 PSME1 TXNIP RHOA HNRNPA1 UBL5 PTGES3 PDCD4 SLC2A3 ERCC1 SNHG29 NFKBID SRP14 ARPC1B NR4A2 CMTM6 CD44 ITGA4 GNB2 TRAV19 BHLHE40 HMGB1 ARPC3 TRIR PRKCH NME2 KLRB1 CLIC1 ANAPC16 NCOR1 COX5B MYL12B SAP18 RHOB TCF25 SOD1 SRSF9 FOSB PCBP1 CD96 TBC1D10C CD164 CD3D ACTR2 COX4I1 SH3BGRL3 KMT2E HSPD1 PABPC1 SPCS2 SERP1 TNFRSF1B TAGLN2 PCBP2 RPL5 LDLR YWHAB CSRNP1 COX8A MYADM TRMT112 ATP5MG GABARAP ELF1 PRR13 RPL22L1 WAKMAR2 SIT1 GADD45B RPS17 S100A10 RBBP4 HNRNPDL CD2 UQCRQ COX6B1 RGS2 CHCHD2 TAF1B RPL27A TAP1 MTDH CD99 ARF1 TBCA TMEM14B HNRNPA0 RPS11 SEC61A1 RSRP1 TUBB ACIN1 HNRNPUL1 OXNAD1 LMO4 CTSH RBM8A RGL4 NFU1 AP1G2 TSC22D3 CASS4 CCNH RPS26 PIK3R1 SH3KBP1 SSBP4 TPR GADD45G ZFAS1 COTL1 BCL7C MZT2A LAT FUS SDF2L1 KRTCAP2 MRPL41 CENPX SETD5 TMC8 COX17 DNAJB4 CDKN1B ODC1 ACAP1 ANXA6 CYBA SUMO3 TMBIM6 TMEM259 CD37 PRDX2 UBE2D2 BTG3 PARK7 CD247 TMEM258 HNRNPAB SPOCK2 SEPTIN1 LAMTOR5 RNF11 SNX5 SASH3 PPM1G ARF6 EIF5A IL4I1 RBM3 RSF1 SLA CALM3 SNRPB SHISA5 ARID5B KXD1 PTPRCAP GBP1 STN1 NSA2 ATP1A1 LCK PSMB8 PSMB3 HNRNPC RNF167 RESF1 ACTR3 CKLF CD52 RPS27L GSTK1 GIMAP7 DCXR RGS14 VASP PBXIP1 GOLGA4 RPL23 YWHAQ SNHG16 TAOK3 IGBP1 DOCK10 SRRM1 PSMC3 IKZF3 AHI1 RPL7 TMEM87A EIF5 MED1 ANKRD12 IWS1 SLC25A6 TUBA1C LRRC41 SEC11C DLST VMA21 MKNK2 RALB THUMPD1 DBF4 RHEB WASHC3 VRK2 SUPT4H1 FADD CHD1 CAPN1 TMEM179B CKS2 RGS10 EIF4E BPTF RNMT DDX39A GADD45GIP1 DYNLL1 SF3B2 CDKN2AIP RAP1B ACTN4 ABRACL MOB4 METTL23 ITSN2 MTF2 VSIR PER1 COX7A2 COX14 IPCEF1 YWHAH CYRIB MOB3A SP2 BCL11B STUB1 RNF213 PRKRA EDF1 PRPF38B RHOG BAG1 ATOX1 CACYBP MAP4K1 PPP1R2 PAXX ADA NDUFA12 WAC ELK3 PRRC2C MUS81 CCT4 ARL5B RALBP1 FBXW11 LCP1 LEPROTL1 PDCD10 HNRNPR NR3C1 PPP4C BATF ABLIM1 PSMA2 TRAT1 RUNX3 CIB1 ARPC2 ABI3 UGP2 NDUFAB1 HCLS1 DERL1 RAB5A INSIG1 CNBP CHROMR DSTYK DPP4 TOMM6 PDE4D LUC7L2 JUND ARHGDIA CEMIP2 POLE4 ANXA11 PLEKHB2 SDCBP MANF FAM83D IMP3 TMCO1 SUCLG1 MBD2 NDUFA10 PDIA6 S100A11 DNPH1 TARDBP PTDSS1 RP11-25K19 LPXN FYTTD1 RORA NASP ATP6V1F RIPK2 IDI1 RASSF7 MT-ND6 RWDD1 CYB5R3 MAZ PIM1 PSMA3 GPX4 PACS1 TNIP1 PLEKHF1 STXBP2 MSMO1 UQCR11 EPB41L4A-AS1 TMIGD2 PATL1 COX6A1 CCND3 TUBB4B OCIAD2 UBE2V2 ASMTL MAP3K8 FERMT3 SH2B1 ACP5 RPS6KB2 GABPB1-AS1 MTRNR2L12 ZFAND2A EIF3D ATP5PB NEDD8 NDUFA1 C19ORF25 CYB561D2_ENSG00000114395 PPP1R18 SYF2 PIGT SLC25A3 KHDRBS1 GIMAP4 NAXE HMGN1 RGS19 SUMO1 YWHAZ ERN1 LRRFIP1 NCF1 GALNT11 PSMG2 SNRPA1 IFNGR1 ENSA LAMTOR4 TBRG1 LINC-PINT PSMA7 SH2D2A HCST GUSB SEC61B TAX1BP1 RNF149 GNG5 PIP5K1A SIGIRR ATP6V1H RXYLT1 TRAPPC2B STK4 GPR174 CLEC2B CDC5L MLEC SQSTM1 GNAS DAXX ADAR NRIP1 TPI1 ITM2C NOSIP HADHA GTF2B ATP5IF1 ATP6V0B VEZF1 MYBL1 TOMM5 UQCRFS1 PDE4B ELL MRPL18 TRAC PIGBOS1 PPIB MDH2 PMVK PGAM1 PEX2 RPA2 FBXW5 MICOS13 CYBC1 ELOB PSMB4 COX6C GTF2I CHMP4A ALOX5AP SSR3 SELENOF AIP UXT TBCB SKAP1 RBM4 NDUFA9 DNAJB11 ATP5MK REX1BD GATA3 MVP GIMAP5 DNAJC2 SHKBP1 CAP1 SSBP1 SUZ12 SNHG6 LTB HECA WDR83OS DUT ANXA2 RRAGA PPP1R12A TAPBP DOK2 DYNLT3 RBPJ ATP6V1G1 CD40LG OCIAD1 TCEA1 ATM SLC44A2 OGA HNRNPK PPP2R5E NDUFA4 PLAUR NT5C3A RBL2 PHTF2 ZFAND5 CCR6 BCL3 GYPC SPTY2D1 MBP AKAP9 CD83 HNRNPF RAC1 SSR2 SMARCC2 MRPS21 SRSF3 DDX21 NDUFC1 BST2 FSD1 TRIB2 SF3B6 GDI2 HLTF APBB1IP LY6E NDUFB4 NAA38 FKBP1A PSMB10 FDPS MBNL1 UQCRB TMED2 H1-10 RO60 CEP57 CDKL3 CAPNS1 GIMAP1 EZR HOXB4 JAGN1 EIF2S2 DNAJB9 KCTD20 ARGLU1 EWSR1 SH3GL1 EIF3F RABGGTA MEA1 MLLT3 SARNP UBAC2 TRA2A ARL6IP1 GPI GUK1 DPH3 TGFBR2 ASB2 SRP9 GNAI2 RAB5IF PPIH EIF4A2 UBQLN1 GPR65 RASAL3 NDUFB6 RPN1 HNRNPA3 GBF1 OGG1 LCP2 DESI2 DUSP2 MGST3 CCDC18-AS1 CD53 POLM RTRAF ME2 PHAX ATP6AP1 RDH11 TCERG1 ACTR8 SLC1A5 DSE SLC25A39 FDFT1 CIAO2A LATS1 WDR33 CCDC107 MARCHF7 FAM174C LRPAP1 COG6 IL10RA MNAT1 CLIC3 TUSC2 NAT9 FAM13B EPG5 FKBP11 CREB3 ARHGAP45 MRPL9 MGA MIDEAS PHF20 CHD9 RCE1 VDAC2 EEF1E1 SSB GBP5 NMRK1 CCT8 SCAP ACER3 VAMP8 TALDO1 PHGR1 TC2N GRID2IP EIF2AK1 TOLLIP TBC1D10A C17ORF100 NFRKB CCDC137 E4F1 XRCC5 FCMR PGPEP1 DGCR6L CHURC1 OFD1 MAP4 PLEKHA2 AMD1 MORF4L1 IER5 DCTN2 CTDSP1 DDX6 AHCYL1 PNKD ELOVL1 FXR1 SAPCD1 SELENOT UBE2L6 PMM2 RNF113A PGRMC2 CPSF6 ZNF267 MRPL50 IL16 CREBL2 ASXL2 NUDCD3 ZNF445 C3AR1 CCR5 DGKE RUNX1 AKAP11 RP11-562I5 ARIH1 PPP1CB NDUFAF3 MRPS5 ACTR1B TPD52 SF3A2 CLTC TMEM33 NDUFA5 HMGXB4 PPP1R21 RC3H2 ZNF580 PRKCSH GZMM SEC13 CTNNA1 VPS18 SYNGAP1-AS1 MAPRE1 ZC3H8 DSTN MAN2B2 MGAT4A PAK2 CRY1 LSM7 ZC3H6 TMEM230 CPQ PSMD3 TIMM17A TYMP ST6GALNAC6 PHB2 KDELR2 LAMP2 NUMB RALY ADAM8 R3HDM4 DNAAF2 ADPRM CCSER2 THRAP3 KIDINS220 RBM15B DEF6 ADNP POLR1E IQGAP1 POFUT2 EIF3K NOL7 NMUR1 NOM1 GNPDA1 PKM CWC25 IGF2R ATP2B4 GPS1 LRP10 CA10 ERI3 SMAD3 ANP32B COX7A2L EHBP1 CHUK H2AZ1 LPIN2 ASAH1 MRPL33 BCL2 DNAJC1 USO1 SUMF2 CHCHD3 NAA20 TMEM60 IER3IP1 FLII YBX1 LAIR1 MESD TSC22D1 SF1 TMEM273 PLCG1 NMD3 TMEM18 ABHD14A SLFN5 ENTR1 CHMP6 IRF2BP2 CHCHD5 HTATSF1 RPS10 LSM14A SUPT7L PEX26 YJU2 HDDC3 CFDP1 SELPLG ENO1 KDM5A MTLN ZNF706 ERVK3-1 DCP1A DBNDD2 TAX1BP3 SPINK4 RNF31 NEPRO SHFL PSMD8 IL17RA CHST14 MPC1 GLOD4 BICRAL SMIM26 KIF5C PRKAR1A TENT5C NPRL2 TTC9C RPUSD3 SSH1 ARHGAP35 RSBN1 ECHDC2 G3BP2 PRR5 SMG9 SUPT3H ATP2A3 SIN3B LSM12 PTEN ZNF93 NONO SRRM2 ITFG1 C21ORF91 HINT1 GOT1 C1QTNF1 AZIN1 MZT1 LAP3 NDUFB8 NDUFA13 FRMD4B LYRM2 IL21R PARP12 SCMH1 PBRM1 HAUS4 RAB4B FLJ40194 HIKESHI NR1D1 MFSD8 SRSF1 SMIM30 XRN2 SAMD4B SEM1 CAPZB PIAS4 IKZF1 EIF3I AGTPBP1 MZT2B C1ORF122 MUTYH WDR61 DDX39B CCNDBP1 ZNF816 PFDN2 POLR2F ANO6 NDUFS6 CTNS ATP11B SIVA1 EIF4E3 CTSC SMC4 CDC42SE2 FAM131C PLPP6 TRPC4AP MTMR14 GABARAPL1 FAM133B RFNG EIF2B1 LSM1 ISY1 EIF3G ORAI2 FAM53B SEPTIN2 HTRA2 SEPTIN6 KAT7 MBD4 CAPZA2 WDR20 NDUFB7 TWF2 COMMD5 GPR68 SPPL3 TMEM59 NCL PJA2 SDHA SLMAP CBX3 TMEM161B-AS1 PPOX ACBD3 GOLGA7 GTF2H1 MAP3K2 COA6 PHF5A COPS7A NAA10 SNX14 CUL1 ALG13 TNIK STARD3 LINC00892 SNAI3 RABAC1 USP42 NDUFA3 DDX58 PSMC6 RBCK1 HNRNPH3 ZFAND6 SDHD CHCHD10 PUM1 LDLRAD4 TCHP CNOT11 KIF1C SEC61G TACC1 PSMD6 NIPBL DAPP1 RAB2A TRIM5 LMNB2 SUPT6H AP3S1 CLK1 NSUN2 NUP88 PPA1 UMAD1 SETD9 DCAF15 ANXA2R TMEM9B EGLN2 MRPS18B PSD4 GTDC1 SUCO BUD31 IER2 UPF3A PINX1_ENSG00000254093 NUDC TAF7 UTP15 PTPMT1 PSME2 MALT1 PSTPIP1 TSPYL1 CTSD HIGD2A SBF1 LINC00667 FEM1A RAB5C TAF2 SHOC2 RASL11A AMZ2 TRIM65 ATP6V0E1 HEBP1 PSMD1 NDUFAF8 CORO1B MRPL34 UBN1 RAE1 SPINT2 SOCS1 TRIM52-AS1 TFDP1 TES YIPF2 STX5 BZW1 PDCL3 NOLC1 TPM3 INTS11 RAB35 COQ10B ZNF480 C1D THAP4 EBAG9 FOXP1 SLC30A6 NUS1 MRPS24 PPP2CA USP4 C9ORF16 MSH2 UQCRC1 SLC38A1 ACO2 WASHC5 TXLNG PHF20L1 RAB6A SERINC1 YTHDC1 MIF4GD C1GALT1 KRR1 NDFIP1 GMFG DCAF8 SNX6 PAIP2 PLAA SRP19 RAD21 TECR OTUB1 CLK3 BNIP2 NEK9 COPE RAB9A RMC1 JOSD2 MAP3K1 RNF144B ADGRE5 UBA5 NLRC3 LYPLAL1 SURF6 PDE9A ZNF720 C17ORF107 SPPL2A OPTN LACTB DNAJA2 CAMK4 PLP2 ARMC6 IDH2 FUNDC2 SNHG3 CAPG TMEM106C DR1 PGGHG TUT7 CYB561D1 EIF3E FURIN VPS26B APBB1 NTAN1 ATP5MF MAX MRPL14 ATP5ME ORAI1 SEC62 TNFRSF1A HTT EIF2AK4 SCAPER POLB FAM204A RRP12 ABHD5 IMPDH1 TAF1D TDG IMP4 SMC6 TRIM28 FAS ILK PPP1R16B TSR3 NOP56 EIF5B CUTA GLO1 PPP3CB CENPK MTRR ITGAE GOLGA3 GFER EPSTI1 THEMIS TRIAP1 HSD17B7 TSTD3 ANKRD39 PIP4K2A MTFP1 FAM222B SRFBP1 HOXB2 TRAPPC5 SRSF8 HECTD1 CCAR1 XKR8 RBM26 ISCA1 TRBC2 UBE2B TIMM8B RPUSD1 SAT2 FAM102A ST6GAL1 METTL9 C2ORF68 PERP SNU13 ANKZF1 CBX5 GPN1 COMMD8 EGLN1 HERPUD1 SENP6 SLC38A2 AARS1 GNL2 G3BP1 GPR108 PSMA4 SP100 MFSD10 TMEM70 QRSL1 DAD1 RPS19BP1 SNHG1 CSDE1 TAF4B ASF1A N4BP2L2 RNF138 FBXL5 JAK1 NCLN RAB11B PPP1CA ITGB2 KDELR1 PSMB1 MTX2 SLC35E2A NDUFS8 HAGH PIGW IVNS1ABP SDHC POLDIP2 EIF4G1 ANKRD36 SEPTIN7 CSNK1D PSMF1 TM9SF4 GAB3 MYL6B HNRNPL WIPF1 GATAD1 RFFL PRKCQ-AS1 GTPBP10 INO80D IFITM3 GAS5 WASHC1 CTNNAL1 PTGER2 USP33 ARRB2 ARMCX6 GMIP UMPS TRIM22 DDX41 SFPQ RBM25 MRPL38 CNP FAM193B MAP3K11 WDR74 PIGC CDC37 PPIP5K2 TRMO AGTRAP JMJD8 ARID5A ALKBH7 CYTH1 SET PAF1 SNHG5 FAM174B ADI1 SUDS3 CDCA7 GTSF1 MTCH1 TGIF2 MLX PYGO2 EIF2S1 DNPEP IL23R RPA1 CDC37L1 GYG1 ANP32A SRSF2 RNASEH2B WDR44 ZPR1 GIPC1 RRM2B ILVBL ARL2BP BRK1 YIF1A CEP164 DPY30 NUDT7 PPP2R1A R3HDM1 MSN PSIP1 HMGN4 CCDC152 STOML2 EEF1AKMT2 H2AZ2 CHST12 CHFR FKBP15 SPNS1 APH1A NR4A3 CNOT9 GPSM3 TESK1 CDK5RAP1 TNFAIP1 FAM118B ZBTB7A PCED1B-AS1 MRPS18A BUB3 ICMT DDIT3 DNM1L DCTN4 PPIG CCDC91 LZIC CHD2 BIRC2 AHSA1 ARAP2 COMMD10 NUCKS1 ASAP1 DCTPP1 ETFDH NAA80 STAU2 CCNL1 CASP3 CCDC174 PRNP APOA1-AS PPP1R11 SRP68 C1ORF43 RASSF1 MYD88 AKAP13 SLC25A5 ERH UBE2I ATP5PD ORC3 NUP37 TTC31 WBP2 PDE7A KPNB1 ETFA STK25 PJVK COX19 ATP5MC3 PPP2R2A MDH1 PSMB6 GTF2E2 B3GNT2 TSC22D4 GPD2 MBIP ZFR JTB GPRIN3 LPIN1 SLC35A1 NXT1 KLHL22 DYNC1I2 AP1S1 PPP1R15B SMIM15 TMEM65 HAUS3 KLHL28 MRPL20 MVK ATR MIB2 YPEL3 SCOC WASHC2C SPRY1 LCLAT1 CCDC25 SLC43A3 CIAO3 WBP11 TRIM4 C17ORF49 DTX1 VAMP5 ZSCAN16-AS1 TNFSF13B ARHGAP15 CISH DCP2 GRPEL2 PHB AASDHPPT PUM2 ISG20 PFKM SLC2A1 NBL1 TMED4 COPS3 SRSF11 ZNF710 POMP TTC14 ZNF414 PISD TMEM219 MIR23AHG COQ4 OXA1L DNAJA3 KMT2A MAGOH LYPLA2 WSB1 POLR2B AKIRIN2 PSMB2 UIMC1 DDX18 TCOF1 TNFRSF14 STARD3NL CELF2 NABP1 PTP4A2 LRRC59 TMEM167B CAMK2G SLC4A1AP EIPR1 NUCB2 MED6 VEZT SP4 ARL3 USP12 ARHGAP9 VMAC FIP1L1 RP11-316M20 ADH5 TMC6 IRF1-AS1 LIG4 SNX1 MACF1 GNL1 TPM4 RMND5A LPAR6 DNAJB2 NOP53 CDK2AP1 FIS1 PITPNM1 SF3B4 SNAP47 S100PBP C4ORF33 CHST11 RGS18 C7ORF31 PSMD4 EFCAB7 TTC39C ANXA5 KRI1 FAM214B DUSP12 NR2C1 CBLB UNG LSM8 MYO9B GLMN RALA GTF3C6 ISCA2 DNTTIP2 SELENOK MRPS36 KPNA3 THRA PTS DUSP6 VTA1 PPARG SEPTIN9 UBE2N FRY BCAS2 CAMKMT SAMHD1 GBP2 TMEM50A STAT5A IL17A PCYT2 ISG15 MAPK3 PDCD4-AS1 TIAL1 RTF1 CSNK2B RBM17 LPCAT4 ST13 CNBD2 TMEM184B RNPC3 ARCN1 SMAP2 BLOC1S1 NAMPT ZNF597 EMG1 SLC66A3 HDLBP C11ORF58 SH3BP1 SMARCB1 RP11-726G1 ZNF564 IFI27L2 ATG3 C6ORF226 REL GIMAP6 OLFM2 OGFR BAZ1A RAB7A EIF3L TBC1D20 SDHAF2 PARP10 GAK FYN TBXAS1 PRDM1 FAM241A TMEM263 SRPK1 CD2BP2 SERGEF SURF4 MTERF4 PPP1R10 IRF9 USP14 ZFAND2B AK3 CYTH3 PEBP1 PLIN2 NARF ICAM2 ZRSR2 HELZ C14ORF119 DCAF5 RBM42 ITFG2-AS1_ENSG00000258325 ZNF524 CRNKL1 FASTK UBXN1 MYO1G QTRT1 FLOT1 DNASE2 STK40 USP47 RFLNB ZFYVE28 FHL1 TATDN2 SLC25A25 ATP6V1B2 GSAP MRPL10 PSMD11 ZNF821 RANBP9 TIPRL TMED10 EIF3M HMGN2 UHMK1 TRBV30 EMP3 HPS6 TTC17 OSBPL8 COMT ERP29 GRPEL1 ZNF595 ROGDI RAD23A LYSMD2 ANKRD44 FRMD8 SRSF10 BCL2A1 TBC1D31 ALDH9A1 CHMP1A GABARAPL2 RPS20 MRPS2 CAST TMEM200A H4C2 ATRAID CRYBG1 CRY2 OSBPL7 TRAPPC1 POLR2K TESMIN UBE2D1 GNAI3 SLC39A6 HMGCS1 TMEM138 TMEM223 CHP1 ATP5MJ MSRA SQLE ATRX ZNF207 PPP1R15A DNAJC3 SNX3 FBXO9 FAM162A BTF3L4 NKIRAS1 PRDX6 EHMT1 SYS1 USP36 STX4 TMED7 NR4A1 GNA13 LINC00299 ST3GAL5 IDH3A NAA16 SLC38A10 CRYBB2 B4GALT1 METTL26 MRPL54 TRAF3IP2 DTX3L NDUFA6 NDUFAF4 SUCLA2 CALHM2 GTF2IRD2B RP11-706O15 IK MAGI3 TCTA PBDC1 BRD7 IRF1 P2RY10 CTBS CUX1 PRKD2 PGK1 BCLAF1 IRAG2 CIAPIN1 TNFRSF25 SNRNP200 IL2RG PSMA6 UQCRC2 RTF2 SLC35C2 GNG2 ZBTB22 MEF2A NOP10 LY9 MAP2K2 COMMD1 TMEM203 VPS29 SOD2 CITED2 FLI1 FMNL1 MRTO4 RETREG2 FGFR1OP2 RNF41 UTP4 TKT DHX36 ID2 TMEM245 ERP44 ESF1 BAG3 NDEL1 DAP3 HM13 PTGR2 ZFAND3 UCP2 BIN2 MCF2L2 PHKB SUB1 PDE3B CEP250-AS1 RNH1 WDR1 FAM117A CAMTA2 UGCG LINC00294 PHF14 PTPN22 KATNBL1 NT5DC1 TRIM38 ZNF780A C19ORF53 SNRPG TDP2 EIF4H TMEM140 ZCCHC17 ANKLE2 CDS2 EPHB6 CCDC90B ATAD3C COL18A1 FBP1 AHCY AFTPH ZNF432 HSPA9 CMSS1 FGD3 ANXA7 SLC25A13 RNF5 KRT10 KDM2B-DT ATP5F1D SCAMP3 KIF2A SHMT1 MRPL57 CD5 MLH1 ACOX3 ZNF593 TTI2 TRAPPC10 SRP72 CXCR6 COPS5 TET2 HEBP2 OGT ANKRD13D CEBPZ MRPL23 UBE2V1 AP2M1 SLC39A4 LLGL1 DLD ACAA2 SCAMP4 PARP8 CXXC1 MAD2L2 GIT2 OSGIN2 FAM219A ERLEC1 PTPN7 TMEM41B SERTAD3 TCF7 ARPC5 NCBP2AS2 ZNF211 SNRPB2 B9D2 ANKRD27 TIPARP RAB1B SRM PARP16 EIF4EBP2 GDI1 ARPC5L CEACAM21 IVD EXOSC4 KDM6A STARD7 JAK3 CBR1 ARL6IP5 STK26 UFM1 ARHGAP18 ESD ISOC2 HCFC1 RING1 PRELID1 MGME1 NDUFC2 CELF1 PNP IFT27 KBTBD2 TUFM TSTD1 CISD3 C17ORF67 BUD23 SCRN2 CHCHD7 FARSA RP11-29H23-1 LINC02481 TPP1 THYN1 ARHGEF1 GCLM PRPF39 TRAPPC6B SLF1 SMIM3 EVI2A AZIN2 ASH1L API5 COG2 SLC25A22 CHD4 WRAP73 CDC26 UBE2L3 EPC1 ATP2B1 CCAR2 RRN3 UBA1 CSNK1A1 CASP8 PELI1 CNOT2 SRP54 VAPA MRPS33 NDUFB11 NAF1 UBE2G2 DVL3 TLE5 CALCOCO2 UQCR10 SIRPG COX7B NDRG1 EIF2S3 H3C4 SMCHD1 RAN MAPKAPK5-AS1 TSG101 HAX1 ANKDD1A DCTN3 CD55 PSKH1 PET100 IMMT SRGAP2C H3-3A PIGH RBM48 FAM177A1 TEFM FBXL4 MID1IP1 PRR5L SLC25A11 NGDN NCAPD3 SLC9A3R1 CDIP1 GRK6 SDF4 DENND2D CASP7 EFR3A NFAT5 PRELID3B TEX30 CIRBP CSNK1G1 MCRS1 CHMP2B TMOD3 PRKX POLR2C NSFL1C POLR1H TAP2 PIANP ARL6IP6 RIPK1 TDP1 SCAF11 SNRPN ZNF335 USP3 UBQLN2 ARMCX3 HSDL1 RSU1 TXNL1 TMEM101 BAD KIF5B AP1AR FAM104A GBP4 AC058791 NDUFB1 DPP7 NDUFB2 RANGAP1 SETX MAF1 NME4 TRGV10 TACC3 AP5Z1 PITPNB EDEM1 CTD-2095E4 ANKRD28 MINDY2 YPEL4 IGHV4-34 TRIM44 ARL6IP4 GART RAD18 SF3B5 BZW2 ECD ZYX HECW2-AS1 CNTRL RECQL PARP9 UPP1 PYCR2 ARHGAP30 TBC1D22B RASGRP1 STIM1 ZNF263 ZNF230 LDLRAP1 PDCD2 FOXO1 UNC119B RNF114 YPEL5 IFNGR2 PRRC1 EIF4B PDXK RAB8B RICTOR ARL8A ESCO1 RBM38 PPIF GMPS HDDC2 FBXO42 PTP4A3 SERPINH1 TRIM69 WTAP PEMT VPS72 WAS PPP4R3A CDV3 CETN2 VAC14 TRIM21 DAZAP2 ARF5',\n", + " 'cell_type': 'CD4-positive helper T cell',\n", + " 'tissue': 'ileum',\n", + " 'batch_condition': 'A29',\n", + " 'organism': 'Homo sapiens',\n", + " 'sex': 'female'}" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sample_idx = 0\n", + "arrow_ds[sample_idx]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This time, we will leave off creating our CSData object until after we load our C2S model. This is because along with the model checkpoint, we saved the indices of train, val, and test set cells, which will allow us to select out test set cells for inference." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load C2S Model\n", + "\n", + "Now, we will load a C2S model which we will perform cell type-conditioned single cell generation with. We highly recommend loading either a model which you have finetuned to do cell generation with (see tutorial notebook 3 for how to perform finetuning) or the C2S-Pythia-410M conditional cell generation foundation model which was pretrained to do cell type-conditioned generation on a diverse array of datasets (details in the repo ReadME, Model Zoo section).\n", + "\n", + "For this tutorial, we will load the best checkpoint of a model which we finetuned to do cell type-conditioned cell generation with using tutorial notebook 3. This model was intitialized from the C2S-Pythia-410M conditional cell generation foundation model, and finetuned for cell generation on the training set of our immune tissue dataset. We load it here as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using device: cuda\n" + ] + } + ], + "source": [ + "# Define CSModel object\n", + "cell_type_prediction_model_path = \"/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_3/2024-08-30-10_59_21_finetune_cell_type_generation/checkpoint-3700\"\n", + "save_dir = \"/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_5\"\n", + "save_name = \"cell_type_generation_pythia_410M_inference\"\n", + "csmodel = cs.CSModel(\n", + " model_name_or_path=cell_type_prediction_model_path,\n", + " save_dir=save_dir,\n", + " save_name=save_name\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will also load the data split indices saved alongside the C2S model checkpoint, so that we know which cells were part of the training and validation set. We will do inference on unseen test set cells, which are 10% of the original data." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_3/2024-08-30-10_59_21_finetune_cell_type_generation/checkpoint-3700\n", + "/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_3/2024-08-30-10_59_21_finetune_cell_type_generation\n" + ] + } + ], + "source": [ + "base_path = \"/\".join(cell_type_prediction_model_path.split(\"/\")[:-1])\n", + "print(cell_type_prediction_model_path)\n", + "print(base_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['train', 'val', 'test'])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "with open(os.path.join(base_path, 'data_split_indices_dict.pkl'), 'rb') as f:\n", + " data_split_indices_dict = pickle.load(f)\n", + "data_split_indices_dict.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "23847\n", + "2948\n", + "2978\n" + ] + } + ], + "source": [ + "print(len(data_split_indices_dict[\"train\"]))\n", + "print(len(data_split_indices_dict[\"val\"]))\n", + "print(len(data_split_indices_dict[\"test\"]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Select out test set cells from full arrow dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", + " num_rows: 29773\n", + "})" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arrow_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", + " num_rows: 2978\n", + "})" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_ds = arrow_ds.select(data_split_indices_dict[\"test\"])\n", + "test_ds" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here, we do not need to create a CSData object. We can simply supply cell types from our test dataset to the cell generation function from tasks.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Generate cells conditioned on cell type\n", + "\n", + "Now that we have loaded our finetuned cell generation model and have our test set cells, we will generate cells using the generate_cells_conditioned_on_cell_type() function from tasks.py, which takes as input a C2S model object as well as a list of cell type to prompt C2S to generate. The function will return 1 generated cell sentences for each cell type supplied, and will handle prompt formatting for us." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "cell_types_to_generate = test_ds[\"cell_type\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2978\n" + ] + }, + { + "data": { + "text/plain": [ + "['CD8-positive, alpha-beta memory T cell',\n", + " 'CD8-positive, alpha-beta memory T cell',\n", + " 'CD8-positive, alpha-beta memory T cell']" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(len(cell_types_to_generate))\n", + "cell_types_to_generate[:3]" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "inference_batch_size = 16" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Reloading model from path on disk: /home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_5/cell_type_generation_pythia_410M_inference\n", + "Generating 2978 cells using CSModel...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2978/2978 [1:54:29<00:00, 2.31s/it]\n" + ] + } + ], + "source": [ + "generated_cells = generate_cells_conditioned_on_cell_type(\n", + " csmodel=csmodel, \n", + " cell_types_list=cell_types_to_generate, \n", + " n_genes=200, \n", + " organism=\"Homo sapiens\",\n", + " inference_batch_size=inference_batch_size,\n", + " max_num_tokens=1024,\n", + " use_flash_attn=False, # at smaller sequence lengths (< 1024), flash attention doesn't significantly benefit text generation.\n", + " do_sample=True,\n", + " top_k=50,\n", + " top_p=0.95,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that the function has generated 2978 cells given the cell types which we provided it, mimicing the cell type frequency in the real test set. We can save our generated cells below:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2978" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(generated_cells)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "with open('/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/generated_cells.pkl', 'wb') as f:\n", + " pickle.dump(generated_cells, f)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here, we view a few of our generated cell sentences:" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['MALAT1 TMSB4X B2M MT-CO1 RPLP1 ACTB MT-CO2 RPS27 HSPA1A MT-ND3 RPL41 HSPA1B MT-CYB RPS12 MT-ATP8 RPL28 RPS19 EEF1A1 RPL13 MT-CO3 DNAJB1 RPL30 RPL10 RPS15A MT-ND4L TPT1 RPL39 JUN RPL37 RPL32 RPS28 HLA-B RPS3 RPS3A RPL19 RPS27A BTG1 HLA-C RPL36 RPL34 MT-ND4 RPL26 RPS4X RPS23 RPL11 RPS18 RPL35A RPS6 RPL18 RPS21 RPS29 FOS HSPA8 RPS14 RPL37A RPL7A RPL29 RPLP2 RPL12 RPS8 RPS15 MT-ATP6 RPS25 TMSB10 RPS2 RPL8 RPL18A RPL3 CCL5 RPL15 RPS24 TRBV19 PFN1 RPLP0 MTRNR2L12 RPL21 RPS13 RPL6 RPL23A MT-ND1 PTMA HSP90AB1 FTL RPL9 VIM ATP5F1E UBB CD3E RPL36A RPS9 CFL1 RPL35 HSP90AA1 RPL24 ACTG1 PPP1R15A SH3BGRL3 IFITM1 MT-ND2 RPL5 RPL13A EIF1 EEF1B2 HLA-A FAU H3-3B UBA52 HLA-E ARHGDIB IL32 RPL27 RPL17 MYL12A RPL14 LSP1 PPIA EEF1D RPS5 RPSA CALM1 JUNB PTPRC DUSP1 HNRNPA1 PABPC1 SLC2A3 NACA SARAF RAC2 TNFAIP3 RACK1 TRAV9-2 MYADM CORO1A TMA7 FTH1 EEF2 CD2 RPL10A LTB S100A4 RPS16 CD52 KLF6 SRSF7 BTF3 FYB1 GZMA CD3D SERF2 TSC22D3 RPL38 IL7R DNAJA1 MT-ND5 CYTIP NPM1 H3-3A TOMM7 GAPDH TRBC1 COTL1 ARPC2 STK17B HSPH1 HNRNPA2B1 HCST ZFP36L2 RPL27A RPL22 RPL7 HINT1 DUSP2 CD74 EVL TENT5C SRGN PCBP2 RPS7 CLIC1 RPL36AL FYN RPS11 LAPTM5 DDX24 CD8A UBC ARPC1B STK17A CYCS HNRNPDL COX4I1 IFITM2 RPL4 MYL12B RPL31 TUBA1A UBL5 CD7 PPDPF.',\n", + " 'MALAT1 MT-ND3 MT-CO2 JUN MT-ATP8 MT-CO3 MT-CO1 HSPA1B MT-ND4L EEF1A1 MT-CYB RPLP1 RPL41 HSPA6 FOS B2M RPL34 RPS12 MT-ATP6 DUSP1 RPL10 MT-ND4 TMSB4X TPT1 MT-ND2 RPL13 RPS27 BTG1 RPL39 RPS28 HSPA1A HSP90AA1 RPS21 RPS15A CCL5 RPL30 HLA-B RPL28 RPS3 RPL32 RPL14 RPL19 MT-ND5 RPS14 RPS19 DNAJB1 ZFP36 RPS8 RPS27A HLA-A HSP90AB1 RPL26 FTL RPS15 HSPA8 KLF6 RPL18A RPS23 RPL23A RPL37 RPS29 RPS7 RPS18 RPL8 RPL7A TRBV2 MT-ND1 RPL17 RPLP2 RPL12 RPS24 FOSB RPS25 CD8A RPSA HLA-E IL7R RPL18 RPS2 RPL35A JUNB RPL29 MTRNR2L12 NR4A1 RPL9 RPL3 RPL5 ZFP36L2 RPS4X RPL11 ACTB HSPH1 RPL21 KLRB1 UBC RPL37A DDIT4 RPS9 EIF1 RPS6 CD69 RPS13 RPL36 RPLP0 RPS3A RPL15 PTGES3 NACA RPS5 RPL36A RACK1 RPL27 RPL22 PPP1R15A HLA-C RPL4 RPL6 RPL24 ZFP36L1 RGS2 H3-3B PFDN5 HNRNPA2B1 CD3E CD7 HNRNPK ATP5F1E PTMA SARAF NR4A2 RPL31 CD3G BTG2 LRRFIP1 PTPRC RPS16 PPDPF CD52 PFN1 SERF2 EIF4A2 TRAV12-1 NPM1 SON NCL YWHAZ EIF4A1 UBB LCP1 PTPRCAP DNAJA1 ZNF331 PPIB NUCKS1 RPL10A TRGV10 RPL13A UBA52 TOMM7 FTH1 SRSF7 UQCR10 EEF1B2 TRAV12-2 EMP3 GAPDH VIM CDKN1B FAU BTF3 EEF1G RPL27A GIMAP4 NOP53 RPL35 TMSB10 TUBA1A EEF2 RPL38 CALM1 ARPC5 EPC1 YWHAB PABPC1 PRMT9 RPL7 UBE2D3 CFL1 EIF4H ST13 NDUFA4 HNRNPDL G3BP2 CD44 MYADM RBM25 RPS20 YWHAQ NME2 ARL6IP5.',\n", + " 'IGLV2-23 MALAT1 IGKV3-20 JCHAIN MT-ND3 MT-CO2 RPS27 MT-ND4L MT-CO1 EEF1A1 MT-ATP8 MT-CYB B2M TMSB4X RPL41 IGHV3-15 RPS12 MT-CO3 RPS19 RPL39 MT-ND1 TPT1 RPL37 HSPA1A RPS15A MT-ND4 HSPA1B HSP90AA1 RPL34 IGHM RPS21 RPS27A RPS14 RPS28 FOS MTRNR2L12 CCL5 RPS15 MT-ND2 MT-ND5 MT-ATP6 RPL3 RPL11 RPL13 RPS3 HSPA6 RPL32 RPS29 RPL7A RPL23A RPS18 RPS8 RPS24 RPL19 HLA-B RPL26 ACTB RPS25 RPL17 RPL28 RPS6 RPLP1 RPS3A RPL15 CD69 UBB RPL18A RPL30 IGHV3-23 RPLP2 RPS16 UBA52 RPL29 TRBV9 RPS5 RPL36A PTPRC ATP5F1E FAU RPL35 RPS4X RPS23 RPS13 PTMA RPL13A RPL37A VIM IGHA1 S100A4 RPS9 RPS2 KLRB1 HLA-A TSC22D3 RPSA RPL22 DUSP1 RPL36 BTG1 HSPH1 TXNIP HSP90AB1 RPL35A FTH1 RPL10 RPL6 RPS7 RPL21 GADD45B UBC SRSF5 DNAJA1 RPL10A CXCR4 RACK1 RPL27A DNAJB1 EIF1 EEF2 RPL38 CD8A HLA-C JUNB ZFP36 PFDN5 CYBA RPL31 HLA-E RPS11 RPL4 JUN RPL24 YWHAZ IFITM1 EEF1D DDX5 ZFP36L1 BTG2 YWHAB NACA CD8B UQCRB HINT1 EIF3E CD74 TRBC1 MYL12A TTC39C CD3E FTL RPL9 RPS20 TMSB10 PFN1 PABPC1 ATP5MG ACTG1 COX6C GZMK ARHGEF1 RPL8 GIMAP7 RPLP0 SH3BGRL3 RPL18 EIF4A2 MYL6 TMA7 RSRP1 CD52 PPP1R15A RPL12 H3-3B NOP53 RPL14 EIF5A CFL1 EIF4G2 CD3D DUSP2 LINC02446 HSPB1 RAC2 TUBB HSPA8 FOSB CALM1 SARAF SRGN TRMT112 COX6A1 KLRD1 RPL36AL HNRNPA3 BTF3 CD99 CTSW HMGN1 EIF3L.',\n", + " 'CCL4 MT-CO1 MALAT1 MT-CO2 TMSB4X MT-CO3 MT-CYB FOS HSPA1B MT-ND4L MT-ND3 ACTB MT-ATP8 B2M MT-ND4 MTRNR2L12 MT-ATP6 RPLP1 TPT1 MT-ND1 DNAJB1 HSP90AA1 TNFAIP3 EEF1A1 MT-ND2 RPS27 PTMA CCL5 RPL41 HSPA1A HSP90AB1 HSPH1 RPL37 KLF6 DUSP1 MT-ND5 RPS3 RPS19 RPS12 BTG1 RPS6 TRBV4-1 JUN RPS21 ZFP36L1 FTL RPS27A UBB RPS29 RPL39 RPS14 RPL36 RPL19 RPS28 RPL28 RPL21 HLA-B RPS18 RPL13 SRGN PFN1 RPL35 UBC H3-3B RPL34 EIF1 RPL29 RPS15A RPL30 CD3E RPL10 RPL11 JUNB GAPDH HLA-C RPS23 RPS25 ACTG1 RPL26 FAU RPS7 NR4A1 ZNF331 DUSP2 FOSB RPL9 RPL18A RPL10A RPL3 RPS2 UBA52 TMSB10 RPS8 RPL22 RPS4X RPL17 ATP5F1E HLA-A SERF2 HLA-E IER2 NACA RPLP2 RPS24 RPL23A RPL14 RPS3A CORO1A RPLP0 ZFP36 BTF3 PPIA RPL36A SLC2A3 SARAF ZFAND2A CALR CD69 LY6E SRSF7 ARPC3 HNRNPA2B1 RPL6 CFL1 UQCR11 YWHAZ RPL8 SH3BGRL3 RPS13 EEF2 LTB MYL12A GADD45B RPL37A RPL12 RPS15 CD8A CD3D RPL18 RPL38 RPL32 CLK1 MYL6 RPS16 CD52 DNAJA1 NFKBIZ NME2 PNRC1 CALM1 RPS9 VIM RPL5 PPDPF IL2RG RPS20 SERTAD1 RBM39 EEF1B2 ITM2B DNAJA4 IFITM1 CALM2 RPS11 RPL15 CKS2 PCBP1 CYBA HSP90B1 H3-3A MYL12B RPL27 DUSP5 TUBA1B CD96 CD7 AREG HMGB1 HSPA8 SLC25A5 IL32 LINC01871 TUBB4B ATP5MG CYTIP PCBP2 RPS5 NCL RPSA DDX21 SLC3A2 DDX5 PFDN5 CDKN1A IL7R RPS26 EEF1D CALM3 SRSF3 COTL1.',\n", + " 'MALAT1 HSPA1A MT-CO1 TMSB4X EEF1A1 MT-CO2 HSPA6 MT-ND4L JUN RPLP1 DNAJB1 MT-CYB RPL41 MT-ND3 RPS27 B2M DUSP1 MT-CO3 RPS15A JUNB RPS12 RPL10 RPL39 RPL32 HSPA1B TPT1 RPL28 MT-ND4 RPL13 RPL30 RPL34 CCL5 RPS18 RPL19 RPS27A RPS3 RPS24 RPS14 RPL26 RPS23 HSPA8 ACTB MT-ATP8 PTMA RPL18A FOS RPL21 RPS29 RPS21 MT-ND1 RPS28 UBB FOSB HSP90AB1 FAU RPL11 RPS8 MT-ATP6 RPS19 RPL9 RPS3A HLA-A RPL29 MT-ND5 RPL37 HSP90AA1 RPS6 FTL RPL23A RPLP2 EIF1 RPL7A IL32 PPP1R15A CD52 RPL37A RPL12 BTG2 MTRNR2L12 RPL3 RPS16 RPS25 RPS4X RPL24 RPL35A S100A4 MT-ND2 PFN1 RPL5 KLRB1 RPL36 RPSA RPS9 RPL36A RPL18 RPL14 RPL15 EEF1B2 RPL35 RPS5 SERF2 DNAJA1 HLA-B RPS13 HSPB1 RPL8 FTH1 RPS7 RPL17 SH3BGRL3 HSPD1 HLA-C RPL13A MYL12A TMSB10 IER2 HNRNPA2B1 CCL4L2 UBA52 H3-3B RPLP0 RACK1 EEF1G S100A6 LTB ZFP36L2 TRBV4-1 RPS2 SRSF7 KLF6 CFL1 HNRNPK SRSF3 ZFAND2A CALM1 TRAV23DV6 H3-3A RPL22 PCBP1 GADD45B RPL27 PNRC1 GYPC CD3E CD7 RPL36AL HSPH1 GAPDH CD3D EEF1D YWHAZ RPS15 RPL38 SRGN CD37 OAZ1 TRMT112 PTPRC ATP5F1E HSPE1 RPL7 RPL6 CORO1A ARPC3 ACTG1 CD2 YWHAB IL2RG KLF2 NPM1 RGS10 HNRNPA1 COTL1 PPIB RPL10A GADD45G RPL27A RPS11 CALM2 CD44 IL7R EIF4A1 RPS4Y1 RPL31 BTG1 RAC2 TRGV10 MIF TMEM123 CYBA MYADM EGR1 ATP5MG NACA ITM2B RPS17 PABPC1 RPL4 UBC EIF4A2.']" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generated_cells[:5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Post processing and reconstruction\n", + "\n", + "Now that we have generated cell sentences conditioned on cell type, we need to perform some postprocessing steps, namely:\n", + "1. Removing words that are not gene names in the dataset\n", + "2. Deal with genes which were generated more than once in a cell sentence (duplicate genes)\n", + "\n", + "We will use C2S functions to do this post processing, as well as convert our generated cell sentences back into expression vectors for visualization." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we get a vocabulary list of gene names from our AnnData object. This will helps us determine what is a real gene word for our data, and what was some nonsense word or unknown gene mistakenly generated by the model." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "23944\n" + ] + }, + { + "data": { + "text/plain": [ + "['RP11-34P13', 'RP11-34P13-3', 'AP006222', 'LINC01409']" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vocab_list = list(vocabulary.keys())\n", + "print(len(vocab_list))\n", + "vocab_list[:4]" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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gene_nameensembl_idn_cellsmtn_cells_by_countsmean_countspct_dropout_by_countstotal_counts
RP11-34P13RP11-34P13ENSG0000023800938False380.00131099.87236839.0
RP11-34P13-3RP11-34P13ENSG00000241860106False1060.00362799.643973108.0
AP006222AP006222ENSG000002864487False70.00023599.9764897.0
LINC01409LINC01409ENSG000002374911292False12920.04598195.6604981369.0
FAM87BFAM87BENSG000001777573False30.00010199.9899243.0
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" + ], + "text/plain": [ + " gene_name ensembl_id n_cells mt n_cells_by_counts \\\n", + "RP11-34P13 RP11-34P13 ENSG00000238009 38 False 38 \n", + "RP11-34P13-3 RP11-34P13 ENSG00000241860 106 False 106 \n", + "AP006222 AP006222 ENSG00000286448 7 False 7 \n", + "LINC01409 LINC01409 ENSG00000237491 1292 False 1292 \n", + "FAM87B FAM87B ENSG00000177757 3 False 3 \n", + "\n", + " mean_counts pct_dropout_by_counts total_counts \n", + "RP11-34P13 0.001310 99.872368 39.0 \n", + "RP11-34P13-3 0.003627 99.643973 108.0 \n", + "AP006222 0.000235 99.976489 7.0 \n", + "LINC01409 0.045981 95.660498 1369.0 \n", + "FAM87B 0.000101 99.989924 3.0 " + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata_test.var.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We post-process all generated cell sentences, which will remove non-gene words in the sentence and average the position of genes which appear multiple times in the generated cell sentence." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2978/2978 [01:31<00:00, 32.64it/s]\n" + ] + } + ], + "source": [ + "post_processed_sentences_list = []\n", + "num_genes_replaced_list = []\n", + "for idx in tqdm(range(len(generated_cells))):\n", + " post_processed_sentence, num_genes_replaced = post_process_generated_cell_sentences(\n", + " cell_sentence=generated_cells[idx],\n", + " vocab_list=vocab_list,\n", + " replace_nonsense_string=\"NOT_A_GENE\",\n", + " )\n", + " # post_processed_sentence is a list of genes, with non-genes replaced with replace_nonsense_string\n", + " post_processed_sentence = \" \".join(post_processed_sentence) # rejoin into one cell sentence string\n", + " post_processed_sentence = post_processed_sentence.replace(\" NOT_A_GENE\", \"\") # replace nonsense string\n", + " post_processed_sentences_list.append(post_processed_sentence)\n", + " num_genes_replaced_list.append(num_genes_replaced)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "avg_num_genes_replaced: 1.13969\n" + ] + } + ], + "source": [ + "avg_num_genes_replaced = sum(num_genes_replaced_list) / len(num_genes_replaced_list)\n", + "print(f\"avg_num_genes_replaced: {avg_num_genes_replaced:.5f}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that our model was very accurate, only generating 1.14 invalid genes per cell sentence on average. We can see an example of a cell sentence before and after post processing:" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Predicted sentence 1:\n", + "MALAT1 TMSB4X B2M MT-CO1 RPLP1 ACTB MT-CO2 RPS27 HSPA1A MT-ND3 RPL41 HSPA1B MT-CYB RPS12 MT-ATP8 RPL28 RPS19 EEF1A1 RPL13 MT-CO3 DNAJB1 RPL30 RPL10 RPS15A MT-ND4L TPT1 RPL39 JUN RPL37 RPL32 RPS28 HLA-B RPS3 RPS3A RPL19 RPS27A BTG1 HLA-C RPL36 RPL34 MT-ND4 RPL26 RPS4X RPS23 RPL11 RPS18 RPL35A RPS6 RPL18 RPS21 RPS29 FOS HSPA8 RPS14 RPL37A RPL7A RPL29 RPLP2 RPL12 RPS8 RPS15 MT-ATP6 RPS25 TMSB10 RPS2 RPL8 RPL18A RPL3 CCL5 RPL15 RPS24 TRBV19 PFN1 RPLP0 MTRNR2L12 RPL21 RPS13 RPL6 RPL23A MT-ND1 PTMA HSP90AB1 FTL RPL9 VIM ATP5F1E UBB CD3E RPL36A RPS9 CFL1 RPL35 HSP90AA1 RPL24 ACTG1 PPP1R15A SH3BGRL3 IFITM1 MT-ND2 RPL5 RPL13A EIF1 EEF1B2 HLA-A FAU H3-3B UBA52 HLA-E ARHGDIB IL32 RPL27 RPL17 MYL12A RPL14 LSP1 PPIA EEF1D RPS5 RPSA CALM1 JUNB PTPRC DUSP1 HNRNPA1 PABPC1 SLC2A3 NACA SARAF RAC2 TNFAIP3 RACK1 TRAV9-2 MYADM CORO1A TMA7 FTH1 EEF2 CD2 RPL10A LTB S100A4 RPS16 CD52 KLF6 SRSF7 BTF3 FYB1 GZMA CD3D SERF2 TSC22D3 RPL38 IL7R DNAJA1 MT-ND5 CYTIP NPM1 H3-3A TOMM7 GAPDH TRBC1 COTL1 ARPC2 STK17B HSPH1 HNRNPA2B1 HCST ZFP36L2 RPL27A RPL22 RPL7 HINT1 DUSP2 CD74 EVL TENT5C SRGN PCBP2 RPS7 CLIC1 RPL36AL FYN RPS11 LAPTM5 DDX24 CD8A UBC ARPC1B STK17A CYCS HNRNPDL COX4I1 IFITM2 RPL4 MYL12B RPL31 TUBA1A UBL5 CD7 PPDPF.\n", + "Post-processed sentence 1\n", + "MALAT1 TMSB4X B2M MT-CO1 RPLP1 ACTB MT-CO2 RPS27 HSPA1A MT-ND3 RPL41 HSPA1B MT-CYB RPS12 MT-ATP8 RPL28 RPS19 EEF1A1 RPL13 MT-CO3 DNAJB1 RPL30 RPL10 RPS15A MT-ND4L TPT1 RPL39 JUN RPL37 RPL32 RPS28 HLA-B RPS3 RPS3A RPL19 RPS27A BTG1 HLA-C RPL36 RPL34 MT-ND4 RPL26 RPS4X RPS23 RPL11 RPS18 RPL35A RPS6 RPL18 RPS21 RPS29 FOS HSPA8 RPS14 RPL37A RPL7A RPL29 RPLP2 RPL12 RPS8 RPS15 MT-ATP6 RPS25 TMSB10 RPS2 RPL8 RPL18A RPL3 CCL5 RPL15 RPS24 TRBV19 PFN1 RPLP0 MTRNR2L12 RPL21 RPS13 RPL6 RPL23A MT-ND1 PTMA HSP90AB1 FTL RPL9 VIM ATP5F1E UBB CD3E RPL36A RPS9 CFL1 RPL35 HSP90AA1 RPL24 ACTG1 PPP1R15A SH3BGRL3 IFITM1 MT-ND2 RPL5 RPL13A EIF1 EEF1B2 HLA-A FAU H3-3B UBA52 HLA-E ARHGDIB IL32 RPL27 RPL17 MYL12A RPL14 LSP1 PPIA EEF1D RPS5 RPSA CALM1 JUNB PTPRC DUSP1 HNRNPA1 PABPC1 SLC2A3 NACA SARAF RAC2 TNFAIP3 RACK1 TRAV9-2 MYADM CORO1A TMA7 FTH1 EEF2 CD2 RPL10A LTB S100A4 RPS16 CD52 KLF6 SRSF7 BTF3 FYB1 GZMA CD3D SERF2 TSC22D3 RPL38 IL7R DNAJA1 MT-ND5 CYTIP NPM1 H3-3A TOMM7 GAPDH TRBC1 COTL1 ARPC2 STK17B HSPH1 HNRNPA2B1 HCST ZFP36L2 RPL27A RPL22 RPL7 HINT1 DUSP2 CD74 EVL TENT5C SRGN PCBP2 RPS7 CLIC1 RPL36AL FYN RPS11 LAPTM5 DDX24 CD8A UBC ARPC1B STK17A CYCS HNRNPDL COX4I1 IFITM2 RPL4 MYL12B RPL31 TUBA1A UBL5 CD7\n" + ] + } + ], + "source": [ + "print(\"Predicted sentence 1:\")\n", + "print(generated_cells[0])\n", + "print(\"Post-processed sentence 1\")\n", + "print(post_processed_sentences_list[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we reconstruct expression vectors from the cell sentence. From tutorial notebook 1, we know the slope and intercept values for the linear reconstruction model for this dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "slope = -0.6756886579917628\n", + "intercept = 2.237853249084892" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will utilize the reconstruct_expression_from_cell_sentence() function from `utils.py` to reconstruct an expression vector from our generated cell sentence. The expression vector will have column features that match the order of vocab_list, so make sure that vocab_list reflects the exact gene ordering in the original data!" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2978/2978 [00:06<00:00, 458.33it/s]\n" + ] + } + ], + "source": [ + "all_reconstructed_expression_vectors = []\n", + "for idx in tqdm(range(len(post_processed_sentences_list))):\n", + " expression_vector = reconstruct_expression_from_cell_sentence(\n", + " cell_sentence_str=post_processed_sentences_list[idx],\n", + " delimiter=\" \",\n", + " vocab_list=vocab_list,\n", + " slope=slope,\n", + " intercept=intercept,\n", + " )\n", + " all_reconstructed_expression_vectors.append(expression_vector)\n", + "\n", + "all_reconstructed_expression_vectors = np.stack(all_reconstructed_expression_vectors)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(2978, 23944)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "all_reconstructed_expression_vectors.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('float32')" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "all_reconstructed_expression_vectors.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "np.save(\"/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/cell_generation_all_reconstructed_expression_vectors.npy\", all_reconstructed_expression_vectors)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Visualization of Generated cells\n", + "\n", + "Now that post processing and the conversion back to expression vectors using the linear model is complete, let's visualize the cells we have generated by putting them together into one AnnData object and visualizing original data and generated data side by side.\n", + "\n", + "First, we retrieve the original data from our adata object, subsetting to the same test set cells:" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", + " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", + " obsm: 'X_pca', 'X_umap'\n", + " varm: 'PCs'\n", + " obsp: 'connectivities', 'distances'" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata_test = adata[data_split_indices_dict[\"test\"], :].copy()\n", + "adata_test" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "del adata_test.uns\n", + "del adata_test.obsm\n", + "del adata_test.varm\n", + "del adata_test.obsp" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata_test" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we restrict the original adata to the top 200 genes, to match cells which we have generated with 200 genes." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "adata_test.X = adata_test.X.toarray().astype(np.float32)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "top_k_gene_count = 200" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2978/2978 [00:04<00:00, 605.98it/s]\n" + ] + } + ], + "source": [ + "for cell_idx in tqdm(range(adata_test.X.shape[0])):\n", + " ind = np.argpartition(adata_test.X[cell_idx], -top_k_gene_count)[-top_k_gene_count:]\n", + " ind.sort()\n", + " all_but_ind = np.setdiff1d(np.array(list(range(adata_test.X.shape[1])), dtype=np.int64), ind)\n", + " adata_test.X[cell_idx, all_but_ind] = 0" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(2978, 23944)\n" + ] + } + ], + "source": [ + "print(adata_test.X.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(200,)\n", + "(200,)\n", + "(200,)\n" + ] + } + ], + "source": [ + "print(np.nonzero(adata_test.X[0])[0].shape)\n", + "print(np.nonzero(adata_test.X[1])[0].shape)\n", + "print(np.nonzero(adata_test.X[2])[0].shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we create another AnnData object with our C2S-generated cells" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(2978, 1)\n" + ] + }, + { + "data": { + "text/html": [ + "
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cell_type
C2S_gen_cell_0CD8-positive, alpha-beta memory T cell
C2S_gen_cell_1CD8-positive, alpha-beta memory T cell
C2S_gen_cell_2CD8-positive, alpha-beta memory T cell
C2S_gen_cell_3CD8-positive, alpha-beta memory T cell
C2S_gen_cell_4CD8-positive, alpha-beta memory T cell
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" + ], + "text/plain": [ + " cell_type\n", + "C2S_gen_cell_0 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_1 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_2 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_3 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_4 CD8-positive, alpha-beta memory T cell" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generated_obs_df = pd.DataFrame({\n", + " \"cell_type\": cell_types_to_generate\n", + "}, index=[f\"C2S_gen_cell_{idx}\" for idx in range(len(cell_types_to_generate))])\n", + "print(generated_obs_df.shape)\n", + "generated_obs_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generated_adata = anndata.AnnData(\n", + " X=all_reconstructed_expression_vectors,\n", + " obs=generated_obs_df,\n", + " var=adata_test.var.copy(),\n", + ")\n", + "generated_adata" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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cell_type
C2S_gen_cell_0CD8-positive, alpha-beta memory T cell
C2S_gen_cell_1CD8-positive, alpha-beta memory T cell
C2S_gen_cell_2CD8-positive, alpha-beta memory T cell
C2S_gen_cell_3CD8-positive, alpha-beta memory T cell
C2S_gen_cell_4CD8-positive, alpha-beta memory T cell
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" + ], + "text/plain": [ + " cell_type\n", + "C2S_gen_cell_0 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_1 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_2 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_3 CD8-positive, alpha-beta memory T cell\n", + "C2S_gen_cell_4 CD8-positive, alpha-beta memory T cell" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generated_adata.obs.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(199,)\n", + "(199,)\n", + "(198,)\n" + ] + } + ], + "source": [ + "print(np.nonzero(generated_adata.X[0])[0].shape)\n", + "print(np.nonzero(generated_adata.X[1])[0].shape)\n", + "print(np.nonzero(generated_adata.X[2])[0].shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our generated cells will have a few less genes than 200, since 1-2 genes were removed during post processing." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can quickly visualize separate UMAPs of the generated data, to see what clusters there are in the generated cells:" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "del generated_adata.uns\n", + "del generated_adata.obsm\n", + "del generated_adata.varm\n", + "del generated_adata.obsp" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generated_adata" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "sc.tl.pca(generated_adata)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "sc.pp.neighbors(generated_adata) # , metric=\"cosine\"" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [], + "source": [ + "sc.tl.umap(generated_adata)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", + " uns: 'pca', 'neighbors', 'umap'\n", + " obsm: 'X_pca', 'X_umap'\n", + " varm: 'PCs'\n", + " obsp: 'distances', 'connectivities'" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generated_adata" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sc.pl.umap(\n", + " generated_adata,\n", + " color=\"cell_type\",\n", + " size=8,\n", + " title=\"C2S Generated Data\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our generated data looks to have good cell type clustering and structure! Let's quickly make a separate UMAP of the original data to compare:" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata_test" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "sc.tl.pca(adata_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "sc.pp.neighbors(adata_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "sc.tl.umap(adata_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", + " uns: 'pca', 'neighbors', 'umap'\n", + " obsm: 'X_pca', 'X_umap'\n", + " varm: 'PCs'\n", + " obsp: 'distances', 'connectivities'" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata_test" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n" + ] + }, + { + "data": { + "image/png": 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iIiIiIiIiIiIil5N6touIiFxBu9JWk2/y2Z2+jp2pf9Eu+C56hD/GqhM/0S10KJW8G7Do2DS+i3+dv5N+4sHKE3F38uLz/U/x3NautA+5m7q+HbGRzxObrmHI+hgWHf2MAasj+GjPwzy2oQnD1jco62aKiIiIiIiIiIiIiPzrKdguIiJyhSw9/iUjNjblx/jxlHOLIsuWxqaUxSw4OoWM/GRq+LTEzWIFDL4uwTT2v4Eu5R/Ahg2AtLxEnC0u9Ip4inLWaOKzduLu5E1Fz7rU8GlFpEdtwj2qE+5evWwbKiIiIiIiIiIiIiLyH6AxZkVERK6Q6t7NaR7Qg7mHJ+LlHEA5ayVWJHzHkoTpDK/6OVtTf6eqdxP6R71BpGdtwjyqAjC25jxmH3qNRgE38OX+MVRwr8HR7DhuDX+CbmFDCXQLw2bymb7/GZ6K+YHqPs3LuKUiIiIiIiIiIiIiIv9+6tkuIiJyhYS6V+am8Ec5kr2HvZkbOZK9m1D3qjTxv5GVJ35gzuF3WXr8C/ZmbOTvxJ8c6/m4BnJP1MvsSV/HjAPPk5gbz1Mx39M8sAeBbmEA1PfrRJRnXZ7a0o6ZB18uqyaKiIiIiIiIiIiIiPxnqGe7iIjIFRCfFctL23rQs8KTjK4+Gw9nP1LyjzLv8AdsSlmMr0s5wMKutL/5K/EHnHFhX8ZmekU8TV2/DgB0LtcfD2cfWgbdxn2rK5Jty6CcNZpgt0j6R79J53ID+HTv4zTy71q2jRURERERERERERER+Q9QsF1EROQyeX5rN45k7+bNeutYeWI2h7J2cjxnP7dVGOXIU8O7JQk5B/hs3yiSU45Qy7cNns6+7MvYzO70dTy7pTON3DsR6BPFkKof0alcPwDur/QOPx9+n/2ZWziUtYPd6WvoWK4vj1X/ooxaKyIiIiIiIiIiIiLy36Jgu4iIyGXi7uyNh5MPq07MZurekfQIe7RAoH3Jsel4ufjTJOBG4rN24u0cwM3hj5Fry+HD3UNo7H8jWYmHGeA9lgW2WXAkEXy9wMONdiF9aBfSB2MMh7J2UMEjpgxbKiIiIiIiIiIiIiLy36Ngu4iISClLz0vmqwNj6VnhCSp7NSQtL5EeYcPpXG4AhzJ3kmVLJys/lbd29SPIGkF172t4qfYyDDYAUnKPsfDYVGr6tKZlwM0kkEBj726QmEmOJZd9+fuo6t0EAIvFokC7iIiIiIiIiIiIiEgZcCrrCoiIiPzbbEv9gx/j32Lh0U8B8HYJ4N7o10nKPcLgdTE8u7kTz2zpRPfQYfg4B/F/f4dwIHMroe6VAQiyVuCt+htwdbLy0aFHyQhxYdzB23gy8WbeSRzGiI3NiEvfWJZNFBERERERERERERH5z1PPdhERkVIUn7mLw1mxjI75nlq+bQA4mLmduYcn0qlcfxr730Alz/q4OLny1YFxAHg4+TJ17+O8vvNO7oh4lh7hw4n0rEmviKep49eOXWl/E+VRh7DAqlT2aoSHiw9h7lXKspkiIiIiIiIiIiIiIv95CraLiIgUIceWRUL2AcI8qpYo/x8JM/lq/1j2ZW5mXK35eLv4AzD/6GR+Ovw2W1J+Z2ytefi6BgPg5RzA8Zz9zDn8DvszN+PlHICzxdVRXi3f1tTybc0Da6pyPHsf05sl4e7sSZOAG0q9rSIiIiIiIiIiIiIicmE0jLz8JxxNT+S6r0fy9bbFxB8/yNTv3yM7J5utCXtp8ukgbvx2FCHv3MKepHjHOgdTj7Er8WAZ1lpESo3NQHZu4cty8yAju9BFk/Y8xOB1MSUesn3ekQ/Yn7mFuyNfpLZvWwA+3fsE+zO2ArA7Yw37MjY78ncPf4T/i3qFVkG9uDX8CaY3S6BjSF+MMQXKfaDSu7g6ufPg2mrnLBMRERERERERERERkbKhnu3yn3AoLYEFe9dSMyiKtfO/Zdr371EuMAxrxWjWHNlJtYAKHM9M5sZvRzGv1ytU9C1PpxkjOJB6jORHfsTZybmsmyAiFys3Dw4lQG4+hAaAkwU83cEYyLfBkSTIyoGo8uBa8G+9kf/1pOUlEWyNLNGmHq06jYScA1T1buJIm390Mh5O3gyqNBEflyDWJs3D3dmbUPcqeLv442xx5tFq0wDYmrKcpza35/aI0dwZ+ZyjjExbKlm2NFwsrvRfHcFb9Tfg6xp06ftGREREREREREREREQumoLt8o+VnG6PkwX6nD9vg/JV2TfoS8p7BRK97mZc6jemY/MbcHdzZ9+gr4j64A7cnFzYemIfQ+e/w+xbX+DBBjdxJCNRgXaRf7qMbHug3c0FUjLs7yND7P9PTodgP/C0got9sJeDmdvJM7lEedahZdBttAy6rcSbCnALJcAttEDakMof4ebkTqOA6/khfgIzD73C7Pg3qebdlP/V+b1A3jmH38FGPgcyt5GVn467sxcAfybMokVgT0LcKrIq6UecLBqYRkRERERERERERESkrCnYLv9YM/+wx8yG3AgWS+F54pIPU94zAA9XK0fSE6n5yb00Cq9GwwbX4+7mDkCEbwhvdhzMiaxUpm6cx5CGNwPwSJOeV6glIlKqsnMhPx/c3SAxzf7y94YgH8jMAaurvQd7Vo49wO7tbu/tbgxYLDy75VrS85L4qnnKRVfh7V39Scs7wegas3lj513kmRxcLG48WnUaj1b9nHXJv1LJqwEANmNj5MbmhFij6FL+fhJyDrI84RsqeTWgW+hQXtvRm+2pKwi2RvJEzDe0TbuTz/eNpk/ki/i4BpbSThMRERERERERERERkQulYLtc9fLyYfFGiC5nj52t2A4d60FUOUhIhYQUsAHl/OxBq8zcbLzcPIhNPEjMx33pXaMD07s/hbOTM56uVvrWuY5763YtsI1TgfXnWve78g0UkdJ1+IS9J7unG2ScDKh7Wu1P5Xha7S+bzT68vNUVXJwh7jBYnCCqHLdXGE2WLf2SqrA/YzMpeccBuL/Su3y290lS8xPII4d2IXfRLuSuAvlzbdnkmRwa+l9HJc/6zDr0Kq2DepOel8SG5AU09O9Kh5C7ybFlsfT4l8w78iFNA26icUDXwjYvIiIiIiIiIiIiIiJXgMUYY670RlNSUvDz8yM5ORlfX98rvXn5h0lMg08XQNUwCA+CpZvg+sawdT/sPQrOTvYOqQ93h/vmvcaMbYvYft+n+Fm96fvz/7i5WivuqX2do6w5q6BZdaheoeR1WHFoC8czkulWtcVlaqWIlJr4BEjPtvdWtxmICLY/qXO2fJs9AO9ksc/b7mSBEL+L3mxaXhJ/JnxL2+C7cHFyw2ZsuDrZt/v4xhbsSFvJ1MbxfLD7QWLT1/Jugy1YnT0KFnKyd/2ZknOP8WfCTD7YM5h+Ua/SpfwD7Ej7i/p+nS66rhdL528RERERERERERERkdPUs12uKr+sBk93aFP7dFqAN/RpDz6ekJZhT9u8Fzo3hG374c9t4Odlj0/VCIykXkhlvN088HbzYObNzxUof3HcZo4m12BD/DGqV7DPqzx+1TdsTdjHB10edcyD/O7q79ibcoQOFRtQwSeEvnP+x87Eg2QMn4u7SyFBOxEpO8bY519PzQRfT3tvdicnCPa1DydvdS18Pecz5j0v73/J1Zh3ZCKf73sKW34eXfJ7stu6nfEH7iPSsxZtgu+kbfCd+LuVZ33KAjLzU8m2ZRQMtp9ItT8RFBlin1/+pL8T57AxeRFdyg+ikd8NrEv6jSYBN15yfUVERERERERERERE5NIo2C5XDWNg7zHwcj932anOps5eEBEE+4/D9v3QPMbewz0lwz7c/MjmdzCy+R1FbuNY/h6e3vUEM+s9A9iD7V9vX8KGY7sZ33EwXm72wNdjiyaSY8vj9VVf06BcVd679hEOp59QoF3kapSSAceS7f+3GXvg3MUJ3K2XdbPDNzTGxyWI52r9CkBd3w7cGTGW1Ozj7MpaTaJJ4VD2Dg5l72BL6u/U8+tAji2T4VWnk5x3FF/XoIIFOlnsDwAU7NjOHwnfsjbpF9oG38nyE18z48A4Hqj0Hl1DH7ys7RMRERERERERERERkeIp2C5XDYsF/q+TPd5UFFcX8LDae7tH22Pl3NoScvLswfqZy+1zuTepVvj6C/euJdOWQYRPiCPt59teJi0n0xFoB3i1/QPsTDyAMYbO0Y3pHN24NJooIpeDl/vpYLu7KxxOtM/LHn55g+2uFiuuFvs2FhydwjuxA7gzYhyfH36Wbf438nTkDzRJ/5ytKb+Tmnec5Qnf8EfCt0xufJAAt1C2pf7BiZxDNA+8mfE77yHKsy63R48+ZzvDq03ni/3PMufwO9wf/Q5dyj9As4CbLmvbRERERERERERERETk/BRsl6uKexGjPZ/p0An7qNDlTvZ29/W0/5ueZY+xeVhh/zH4exd0qn96OcC9da8nxNOPqv6nJ2wPcPchwN2nwDYeadKTH3f9wU2znsbq4sYt1duQb8vH2cn5UpsoIqXFZrP/e2qOc1eX08NgeFz+USheqfuH4//RnvWp69uBpoE3EupemareTcBi4emaP7A3YxOPrK9HmLU6/aPfIMDN/qTQ+7EPsC9zM1MaH2R10s8k5R7h9gh7sP1Y9j4+2D2YHuHDqefXkf+r+D+aBNyIh5MPH8c9gr9rOe6MfK7QeomIiIiIiIiIiIiIyJWhYLv84/xfx9OxtTN5ucN9XcDVGVbthL1H4URawWB7ak4GIR7+BYaDz82D5VuhWjhUOGNU5zYR9Xi0yW3k2/K5ZtoQdiYeZNt9Uwnx9L98jRORktt71D6kRVig/eXibD84lPO/4lWp4t2I52svAKCyV0NHenpeCj4uQQypPIk1Sb/w+s7evF1/E38lfs9N4Y/i5uRBgFsYHzTchdXJfrDKzEtj5MZrSMo9TFXvJtTz64jV2YOG/tdxNHsv1bybEeVZ94q3UUREREREREREREREClKwXcpEQgps2mufc939AjugWovp/X5qWbPqUL2Cfbj5M7268itWH9nJQ41uJtDDF4BjKbBut30o+jOD7f7u3rzZcTABb91Eni2fyv5huDnrT0bkquHmApk59jnbywdcvu0YU/gTPiXwwJpKpOUnMbXxITLzUzmRc5CjWXv4JO5Roj3r81LtJQD4uAThZHEC4Fj2XpJyD+NscWVH6soC5ZWzRhXoUS8iIiIiIiIiIiIiImVHkUMpFcu/+Ir83Fza9r2n0OUJ34D/HnAeDrjA1gOwdjeEB9l7lJ+SlWufs93tIr+ZaTmZWAAvN49zAu0AM256liMZiY5AO0B4IPRseXr06bP9dc/7OFksVAmoUHgGESkjFvsBI9D3/Fkv1olU+ysypPgnfYoQ4VGTQ1k7cHf25qbwR7kp/FFSchOI8qxLXMZ6FhybQk2f1oza1Jp7ol7mprBhVPSqzVMxP/L5vqc4mh1XZNkzZ+6nWjVv6tW7jA8aiIiIiIiIiIiIiIhIkRRsl1Ix7ZER5GZnFxpsjzsKTl9D4D6gPxAMTatBWABUDj2dzxj4bAF4WuHuDhdXj7pTBmB1dmVT/8m8/tcMOkU1omlYDcfySv5hVPIPY/KGuSw9sIFJXYbj5uxKZEjRZVYLjLi4yojI5eXmAhhwcbp823Bxts8F73RhPdu3pf7BgqNTGF5tOs4WF9ydvRzLfk/4ir0ZG2nk35X2wfeQlHuEALcwvJ1PB82bBt4IGN6J7c/65AXU9+tUoPwDBzK47bbfaXiNG2v+7HlJTRQRERERERERERERkYujYLuUipE/zyblkAt/j4FqUSdIbX6YiNq1AAj1h5VDwcMTnNwg45i9k2iVsIJlWCwQVc4ebL9YHSo2wM3JlQ1HYxm19GN6Vm/LtzePPSffl1sXsHj/el5uex9h3qfHjj+WkcSR9ETqhFS6+EqIyJVR1HAUlyI3Dwynh9fw9bS/LtDvx2fw29FP2JH2F4ezYpnS+BCeLvYe+B1C+uJicaN1UG88XXzxcQ1kUqPd55RhI59sWwYHM7c5gu15tlxS8xLwLe9CvZGTqVbbA1CwXURERERERERERESkLFiMMeZKbzQlJQU/Pz+Sk5Px9b2Mw//KZZGTB+lZ586HPn8pbEqEip/P4Ycf72JS4mHcjnqQngvulcHZCT5fBImJ8EBbcAsuZiMGOA4U0+P8fL7dvoQmoTFE+4Uy5vepGGMY1+ZeXl7xBU8vm8xX3Z/i9hqnu9B/sPYH3l0zm20n9nHgwa95ccXn/Lrnb/7+vw/wsV54sE1E/oH2HLYPs1E57Px5i5GZn8ae9HXsSlvFnowNPFTlY5wtzhdURq4tm5EbmxOXsYFna/xMQ/8u3DP9VtIrzeG9RpuJy1hPOWs0Vb2bXFJdL4TO3yIiIiIiIiIiIiIip6lnu1yw39bCrkNwTQxk5ED7uvZe6V4hEOkEftcd4YaYYbh5eGDrBzYLLBkPHT+DW3Ig2w3c3gBmAqFFbORT4D37K6kWZOZAWOAZyw2wHKgD+BdexG0x7SApCYCPN8zBGBjX5l5iAiOo6lOVwweqY6sOTk6QlZfD8EUTsTq7MqhBd4I9/cjKyyEzLwfDFX8eRUTKSoC3PdheArHrFpKVnkTtVrcWSM/IS2HukfdpH3wPtXxbO9JtxoaTpfAh7wtblpR7lL0ZmwhwDSPaqx7Z2TZWzgqj8o318G0eQsug2y6wcSIiIiIiIiIiIiIiUpoUbJcLViXMHqDecwSOJkPVMIhMhuz5cLgS3Ni3P98uh/mrbbSqk8+eYFfCg4B48LKAVw8gE/AuZiPVgfpAGPy0ChJS4cGu4OZ6cvnfwKPArcCoIsr46UeY+C6MeY5V90wE4PHFH1LBO5jn67zNoaR8MnJz8La60WnGY3i4uPFrr1dpHBoDwHudRpCZA76XMKy9iPzD+Bd3YCrou7cGkHRsH899n82RnD2EWqvw05G3Scs9wdcHXyDHlkmX8g/gbHFlX8Ymxm7twpDKH9GxXN8C5WxMXsTYrV0YXHkSncr1c6SHWCN5t8Fm/F1D8XKxD5n/25uv4uXlgreLe6k0V0RERERERERERERELp6C7VIyNiAeqAA1Iuyv+BMwYxn8tQMiP4H2G6HRTPtw8dm5sOHX3/nqg9t5a9R2vCL8YSqwDagL9Cp+c8dqg8sEeyfTpk6Qkg77jsHKHXBDEwioDdwDdC6mkMhIqFgRFiwgvEYtcrw8eG/t91T2C+PGygm8tuVrylcexZ21OnFNWC3KewbQqHx1x+q/rLE/UHDvteDjcSk7T0RKRWY2HE2Ccv7gUfZPwcQMvR+PLA9WJH3Hazt6c1uF0Xx78CXq+nbigcoTqePThvtWVwSceKbGTwS6huPl4n9OOe7O3gWW2YyNlSdmU9evAxU8YgrkjY4u+cMAIiIiIiIiIiIiIiJyeSnYLiWy7SvgV6gxEGhlTwsLhC6NIMQPeAjYDb4V4XgKXNcIJrzwAuU9q2HzAg4AI4BY4EXgOmA19gD8E0DE6W0ZA18tBU8r+HvZA/tNq8PfO+F4MmRkQ0AQMNSePy8fpi+G8v5wfWMgdheUD8VWrwE5bt64/74UOnViU+A1TG42k9Z1MzGWfII8fPHLaMfijfC/dgP5ettiErNSCfSwz0NcOQxcXMDD7dz9kZmbzfHMZCJ9y5XqfhaRIthskJwOufmQbyvr2rAnfT2fZD2Fv2soz3ssoL5fZ5oGdKOyVwNW+Pvxq3M2rfIjCHOvhs3YqOXbmo8axwFwLHs/h7NiqehZm3diB3BtuQGOZQCrEn/klR23cVPYo/SPfqPw7e9JY8KE7TzxRE3Cwz2vQItFRERERERERERERORshU8eK3KWhd6wqBsQVTC9ZiQEJwOvA/YYNT+vglnLodeolxlbZxHeuX6wEXugPQZ7z3aA74EVwF4gGZgAxNnnf29RA+pEwcEEiE+0Z29SDe7rAlZXirZvLwwdAu+9w7b9YInbQ1JQRfIaNWffMTiW6IGvayABriE81qwX+49b2H8MZu/8nbvnvMQrK79yFFW7InRtDC7O527m3rmvUnlSH+KSD1/IbhSRi5WRDWlZ4OsF3mU/1ISvSzA+LkE09u9KpGdNnqv1KzE+19Ay6DYqOJcjBC88nL14r+FWJjbajtX5dED83dj7eGZLR4avb8TqxDlsTF5UoOw6vu25OWwELQJ78kncozyyrj5/J/6MzZx+yODbb/fz9ts7+OmnQ1eszSIiIiIiIiIiIiIiUpB6tkvRTgDzgZvg5tYn0wLt/8yd+yMT5v3E2oTjrB38IRV2B8NB+7JWtSAtE+pXbgwdATfAgn0o+vaAJ8TGQ9R8cPIGp1bAr8B0wAo0gybfAY9B3WhwPyO4vnI7bIiD3m3sPevz8u3B8L6dTmbIKg9drodm11AxBP4YMpGNWaFUWWuhWzP78Pbz18H+4zA98RGOZiTyY9dpxB5uzTPX3Evfuh1LtGuui25Cri2PEA+/i9q1InKBvNztw8d7Xvnh438+/D5HsnbTL+o1LBYLAEHWCkxregyAtUm/EO1ZnwC3UACapztxu2c7nCyFP892Y+gQnLCwLnk+j1abTovAWwss93Lxw83Jnac2t6OB/3Ucyd7DC9u6MazqZ7QPuRuAhx6qRrVqPtx4Y/jlaraIiIiIiIiIiIiIiJyHgu1StBnAZMALwm8suGj79m2cOH4cq5srTjUssBA42XGzStgZGa2wZhckxUGHsZAfCU7ZcPRF2HAbtKkHwQCdAFegKfAR8AvQAzybFtxupVDIyrXP5b5yu32++DvanhzKHsDdHYY+CoA30LpjGKmroUKQPSjv4gyRIfYRqSNzw/C1erDvmIXYeBeGdbyHQJ+S7Zr+9brSv17XkmUWkUtnsYBv2QyX/tuRjzmYuY27Ip/H6lywV/2utNU8t7UrbYLu4P+i/scHux9kddJc+ke9wU3hj55T1tS9j/Pz4feYUG8dQW4R55R3Sp7Jwd3Zi94Rz+Lh5M338W9Sx7e9Y7mHhws33xxR6LoiIiIiIiIiIiIiInJlKNguRbsd+9DwhXT2HjLkEQZkDcLHp+jo9Lp1a9i1awc5Qb04kelE2xsh9jAExENTD8jqC95BJzM7Ax1O/v9BoAts9YGV8+Gm5jiC4JXK218A3u7g5wluhXyL9x+HPfGGlrUs3NAEnN9/Cw4egBf/R6MqzqzeBR2so3nwFsjJg2bVKXGgXUT+W56t+TOZ+amFBsajPOvQM/wJvFwCeGR9fTLyk7HgRE2f1oWUBOWsUYS7V8Pd2RurswepuSf488RM2gXf7Sh/XdJvzD86hYz8FPJMNhW9mvNw1U8uaxtFREREREREREREROTCac52AezTIccdOSsxGOgDFNLx0tXVrdhAO8CCBb8wd+5PtK2RQJ8OsOn/4PhQ2P4guNwN3jcAOwtZ0R2oBUlpkJQOy7cWXGwMrN4F/t7wf53AzwvYtg12xzrybNxjY81uC8defIsP50LirniIP2RfGWhcBZpUted1c7EH2vfFp7JxT16xbRKR/54At1DCPaoVuszVyco9US/jZHEmIz+ZZv438WrdFVTzaUqOLYu3dvVj0bFpjvw3ePRjQtUVBLrZhwCZc/gd3t/9AL8nfOXIcyx7Hyl5x3io8sfU9m17eRsnIiIiIiIiIiIiIiIXTT3bBYBlm2DrgdNzoZeG/v0f4PjxY0SEhbArHhZvhAaVoX1doCqQBawAngDeAlt4PiNr1iekUjRP/vIT9SvDxr32HuxnSk6HZZuhYgjc2hJ7AP3JEeDvD1M/Jz0Lov/4jjqbVhJS3hV/b9g9+CUCqxpwdgag0clAuzGQmQO5WUl8+uNufMo3wuIEtSqCk31qZlZuh41x9umib2oOf261Tx9dr1Lp7CcR+edJyj3KXye+p0PI/+HqZKVH2HDmHf6ATFsq1fJqkpmewPbctSw5Np30vGQ6hNxjn7/iWDK4utgPIsC15e7D2eLKNWfM235t+QG0CrodTxffAtvMyspn9Oj1dO9egQ4dyl/R9oqIiIiIiIiIiIiIyLkUbBcA6lYCT/cz5j4vBQEBgQQE2CP30eWgXZ2T87l/AzQGRgCfAkeADMBiwSc4GO8g+zqJafYe99m5p0q0AU74e0P3ZhB0qmO9xQL3DwJPT/YdhXlroGK2D+1yT+AyZBx9wqCoQRxWbLcH029u7oFP3kZ8ncKYvy6MfBvUrwT8H4Rnw4o+huSsDPJtXvy9yz58vYLtIleAzQY2A85O9r/1q8T3h97gu0Ov4ensS+vg3lgsFgLdwvF1DoLjyXyQ/ihLM76lY3A/OpXvZ1/JyQnCg+xtOSnIWoHbI0Y73idkH8THNeicQDvAli3JjB+/ncOHsxRsFxERERERERERERG5CijYLgCEB9pfpWoisBv4H7g4Q8MqJ9PnAoeBYUBf7EPVu4ATToz9Y7Fj9bBA6FgPIkMA7gSWANsBHzzcYN0eaFnz5JztN3QDIOOAPUBfdf9K3PPSISy82CqG+NrbHehrZdjgviSl2YPvFUNOZnCBUF9Yx3tMXTmLxrUn06d9NK76yxG5Mg4m2J+4cbZAdOhVE3C/IXQIrhYrk+OGsyPtLyp7NaSCRwzpeUk8lX4n3UMfJvVEGguOTyHLpFPLt419RU8rebZcfj40nob+1xPpWdNR5tHsvQxeW50WgT15rPoXjvRFi46QkpJLjx4RLFrUkdq1S/GpKBERERERERERERERuWgKGcrlsxZ7sD0XcD4j/QPsQ8if+vYV8S1MzwJvDwjwBigHhDkyb95nf1ULhwpB9vzGGGpEWKgaBi7WxuDW8rxVTEyzz9f+xWKoHQVtakOXxmdkmAyuQI+dDcAlnSjf8ni52Rct+PAjEvbtp9eL4867HRG5SJ5We+9258JHpygrIdaKdAsbyqJjn7HyxPcsPf4FKbnHqerVhLisjaxKncuzNeew9PiXxHhfU2Ddbal/MHnvY7RPX8ewap8yOW4421NX8FSNHzn03lNM3VmZh5fm4+ZmP3D267eCgwczycnpTfv26tEuIiIiIiIiIiIiInK1ULBdSmz69E/Zvn0bTz01FqvVev4V3sEeaD9rznX8S7a9xRshNh62t4AU57eYHnR6WZvaEBNxOtB+8yOtSE5LZNEnW3BxBq6/oWBhM7+BqGho0tSRtCEOlm+FvVmb+OHYB7wSOgqoUGhdbq7WmnohlTmRlYqXmwcAv733IYd37OTmZ0bj5m5vZGZWBtcPbkTT2q15/bGPS9ZQEQFj4MBxsLpCOX/70PFpmfanbYLOHVK9zNls+LoG81HjOIauq4unsw/P11pIuEc1HlhdhaPZcQC0Db7znFVr+bbhoSofU9e3AwDHsvdzOHs3rk5uBCe3J27fCfLyDG4nH+yZPLk5KSm5ODldHb36RURERERERERERETETsF2KbH09HTS0lKx2WwlW8F68nVKPPZe7f8HVCl0jQIaV4VyfrDYCY7l22Nxp0aQdnc7Y6h3oFxQGB7unoUXlJQEUz6BmBqk1m7Kl0vs87EH+oCPBwT47mPP3q0EBx+jqGA7QKNPH8Df6s3K3l+y4xA8+sNs8jLTHIF2sPeuz8vLJScnm1GjRtCoURNuv/2O8zdW5L/OAPk2+wsgNQOOJUOej/2P9SoRm7aGl7fdzL0eT9Mq8m7w9WRC/fUAOFnsve8/bByLhaJ74jtZnOhcrr/j/ePVv8ZGPs4WF77/vg35+QYXl9Prd+oUeplaIyIiIiIiIiIiIiIil+LqGpdXrmr33z+YN998Fw8Pj4srYA3wM/BHybKHB0LzGJgVBEtCzp2q2WaD3Dx7bO7Nkd/y5Su/FV6Qvz88/xIMH4Ex9iSDfQj6AdfBM+27Ej/kG9pXbMCeE4eYMvUjVq1ayZ49u/n886mMGTOK3btjGda4Jw81upmNe2H1LsjxjqBCzRoFNuXp4cXyz2J58aH3ycxMJysr8wJ2kMh/mJMFospBWKB9DokTqfanYXxPPkSTkAJHEsu0isYYYtNXk5h7mAxLBvZhNOzB83lHPuDWP12ZffANnC0ujsB7SVgsFpwtLo7/nxloFyktcXFxWCwW1q1bV2y+9u3bM2zYsMtal9LYxtixY2nQoEGp1Oef4OzPb/HixVgsFpKSksq0XiIiF2P58uXUrVsXV1dXbr755iLTRMqaxWJh9uzZxebp16/fVfmdvZh6RUdHM2HChKuiLv82Z1//Xq59LSL/HlOnTsXf37+sq3FZnP179t/cVhH579Ad/f+oEycSSE9Pv7Ib7Qp8CJw7qnKR9hyBD36GA0fPXfbTKvj4V1i0AT75FY6nFFHIYaB+I6gQga8n3H89XBNzerHFYqG8VyB/HtxM/ff7sXTpYp6Z/gaTZ0xl4cLf2L9/HydOHGds636MaNabljXhpubg4gTbDxS+SR8fHyZMmMg999zL0ST4dY09figixTj1RI3tZA93bw9HQJuMbEjPti8rIwuOTeH93Q/QP/pN2tcYzC+pUzmRcwiA49n7sJHP8Zz95664dglsWA7AU5va8+Sm1ley2lIChw8f5uGHH6Zy5cpYrVYiIyPp3r07CxYscOSJjo7GYrFgsVjw8PAgOjqaXr16sXDhwiLLTUhIICIi4qoIikZGRhIfH0+dOnWAooO1s2bN4vnnny+DGv4zTJ061fE9KOoVFxdX1tUUEbmqDR8+nAYNGrBnzx6mTp1aZNqlKOlDZnJxUlJSeOqpp6hRowbu7u6EhobSuXNnZs2ahTn5hHv79u0d50ar1UqFChXo3r07s2bNKrLc7OxsGjRocNV8dvHx8XTt2hUo+jv11ltvlcp3VopXWg8anu86buzYsaVSXxGRS9W7d2927NhxWbdx6th65r2O2rVrM2nSpMu6XRGRfyMF268Sq3ZuY8gHb5OYlgpAelYmR5NKrxfnxx9/wMsvj8Nms5GdncXo0SMZP/6VUiu/RJyARpTa5AXBvvZh5sMDITIEvE4OWZ+Rbe/xDsBKoDsw5fzlVfQtR7Nq9Qjp0ZS/IzJpeF1bHnjgId5++0OaNGnuyOdphcqh9jnl5662bw9g48b1jBo1gj17dhco95cFy5nz9SvEHki75DaL/Cvl5p0cMj4fktLs87WHBsDRJMg4+ZRKhSDwdIO4o6eHmr/CIj3qUNGjNtFe9VidOIeJux/ku0OvAfB/Uf/jnfqbWZM0j8lxjxVc8cAuOBALgJPFGSecHYuy8zOZHDeczSlLC66TnAC/fgHxey5rm65O+cBi4MuT/+Zf1q3FxcXRuHFjFi5cyGuvvcbGjRuZN28eHTp0YMiQIQXyjhs3jvj4eLZv385nn32Gv78/nTt35sUXXyy07AEDBlCvXr3LWv+ScnZ2JjQ0FBeX4k/CgYGB+PhcPVM3lCX71DB5BdJ69+5NfHy849WiRQsGDhxYIC0yMrKMaiwicq78/HwWb1zHl0sWsnjjOvLzL+95tSRiY2Pp2LEjERERjl5MhaVdLXJzc8u6CpfFxbYrKSmJli1b8tlnnzFq1CjWrFnD0qVL6d27N48//jjJycmOvKfOkbGxscycOZNatWpxxx13cP/99xda9uOPP054ePhF1etyCA0NxWq1FpvHz8/vqvvOStHOvGabMGECvr6+BdJGjBhR1lUUkcvA5OdzYuli4r/+khNLF2Ouguuh8/Hw8KBcuXJXZFvbt28nPj6eLVu28MADD/Dggw8W6HwgIiLnp2D7VWL64oW8//MP/LVjGwDdn3+GKg/8HykZpdP7PDk5kcTEExhjcHV145prWtK06TWlUnaxDLAH+3ztF6FSeRh8I0SXP3dZy5rQsxXUssGt34DHHsjJg6nz4fuVJzNFAE2A2uffVgWfEOb3fp1Xewzj+IgfubVRZ5o3b4G3t3eh+dvVhS6N7MF3gOTkJBZt+55Js94okC8/dRvpxzcR5JFU0maL/LekZkJyuv3JlROp9ldCqj2onphuf5978oeQsdkD8rHxkHb5pmmIS99AVn46W1P+IDZtDQA701awL3MzO9NW0dD/evpFvUq30Ecc6wS4hZKZn0q27azj9nV3QedeADxfewEv1VniWLQ3YyM/xE/gtyOf2BOOHYSsdPsrOQHSixqy499qFhANdADuOvlv9Mn0y2Pw4MFYLBb++usvevbsSfXq1alduzbDhw9nxYoVBfL6+PgQGhpKxYoVadu2LZMmTeKZZ57h2WefZfv27QXyTpw4kaSkpBLfsDs1vOZzzz1HSEgIvr6+DBo0iJycHEee7Oxshg4dSrly5XB3d6d169asWrXKsTwxMZE+ffoQEhKCh4cH1apVY8oU+9NmZ/bGiouLo0OHDgAEBARgsVjo168fUHCIy9GjR9O8+emHzU6pX78+48aNc7z/+OOPqVmzJu7u7tSoUYP333//vO212Ww8/vjjBAYGEhoaek4voqSkJO677z7HvujYsSPr16+/pP1ns9l4+eWXqVSpEh4eHtSvX59vv/3WsfzUU/1z586lcePGWK1Wfv/99wLb8fDwIDQ01PFyc3PD09OzQJqzszOF2bx5M926dcPX1xcfHx/atGlDbGzsJe1HEZHizPpjGdH39aHDUyO4642X6PDUCKLv68OsP5Zdtm0Wd6w9dS5KSEigf//+WCwWx4ghZ6cBbNq0ia5du+Lt7U358uW55557OH78eIFtvfrqq1StWhWr1UrFihUdD8BVqlQJgIYNG2KxWGjfvr1jnXHjxhEREYHVaqVBgwbMmzfPUeapOs6YMYN27drh7u7O9OnTC22rxWLhww8/pFu3bnh6elKzZk3+/PNPdu3aRfv27fHy8qJly5YFjvUA33//PY0aNcLd3Z3KlSvz3HPPFXi462LLnThxIlWqVMHNzY2YmBimTZt2Tn0nTpzITTfdhJeXFy+88AJVq1bl9ddfL5Bv3bp1WCwWdu3aVWi7R48eTVxcHCtXrqRv377UqlWL6tWrM3DgQNatW1fg9/Opc2RERATXXHMNr7zyCh9++CEfffQR8+fPL1Du3Llz+fXXX8+pT1FOTSnz4YcfEhkZiaenJ7169SoQ7D/f552Tk8NDDz1EWFgY7u7uREVF8fLLLxfYZ6eGkS/qO3XmEOmTJk0iPDwc21mjcfXo0YP+/fs73p/vO3A++fn5DBgwwPF3FhMTw1tvvVXsOu3bt+ehhx7ioYcews/Pj+DgYJ555hnHSASnZGRk0L9/f3x8fKhYseI5vRufeOIJqlevjqenJ5UrV+aZZ54p8YMbF3udVty167x582jdujX+/v4EBQXRrVu3c/42znTmNZufnx8Wi6VAWlH3f7Kzs3niiSeIjIzEarVStWpVPvnkE8fy8x2vRKTsHJk9i2U1oll9fQc29buL1dd3YFmNaI7Mvnz3Gdq3b8/QoUOL/c375ptvUrduXby8vIiMjGTw4MGkpZ3uqHXm0Oo7duzAYrGwbdu2AmWMHz+eKlWqON5f7LGoXLlyhIaGUqlSJYYOHUqlSpVYs2ZNsessX76c9u3b4+npSUBAAF26dCEx0d5x8Hy/vUVE/pVMGUhOTjaASU5OLovNX5WS09PM/HWrHe//9+2Xpverz5vcvLxS20Z+fn6plWU3xxgTbYz5s0Dq1qXLzKznXzL5eXnGzDDGNDn5mlhw7V1/rTLfjhlncrOzL70aTYwxM4zJtxkzZ5UxK7fbF23cnWU++PhTs379WnvC55+Z5BdeM7sPXNp+TU1NNZ9++rHZvXuXMcaYnJwc89prL5lb7r7O3HRfG2Oz2Rx59ybGm4//nG3ybaW9/0X+4dIyjTmebExenjGpGcbYbMZk5RiTnmXMzoPG7DpoTOwhY/Yctr8/cMz+77Eke3pqxmWp1s7Uv02PPyzm5W23mh5/WMztf3oaY4zJyEsx8w5/YNJzS/fctT5pgUnOOWZMcoIxX79tzO8/2RfkZJXqdkrD5T1/zzTGWIwxnPWynHzNLPUtJiQkGIvFYl566aXz5o2KijLjx48vsoxXXnnFkbZ582YTGhpq9u7daxYtWmQAk5iYWGz5ffv2Nd7e3qZ3795m06ZN5qeffjIhISFm9OjRjjxDhw414eHh5ueffzabN282ffv2NQEBASYhIcEYY8yQIUNMgwYNzKpVq8yePXvMb7/9Zn744QdjjDF79uwxgFm7dq3Jy8szM2fONIDZvn27iY+PN0lJScYYY9q1a2ceeeQRY4wxmzZtMoDZtWuXow6n0nbu3GmMMebzzz83YWFhZubMmWb37t1m5syZJjAw0EydOrXItrZr1874+vqasWPHmh07dphPP/3UWCwW8+uvvzrydO7c2XTv3t2sWrXK7Nixwzz22GMmKCjI0dYxY8aY+vXrX9D+e+GFF0yNGjXMvHnzTGxsrJkyZYqxWq1m8eLFxhjj+Kzq1atnfv31V7Nr1y7H9opry6n9VZwDBw6YwMBAc+utt5pVq1aZ7du3m8mTJ5tt27aVaD+e+fmdWdfzfa9E5L9r5vKlxtK9k+Gsl+Xka+bypZdlu8Uda/Py8kx8fLzx9fU1EyZMMPHx8SYtLe2ctIyMDJOYmGhCQkLMqFGjzNatW82aNWvMtddeazp06ODY1uOPP24CAgLM1KlTza5du8yyZcvMRx99ZIwx5q+//jKAmT9/vomPj3ccz998803j6+trvvzyS7Nt2zbz+OOPG1dXV7Njxw5jzOnjbXR0tOOYfOjQoULbCpgKFSqYGTNmmO3bt5ubb77ZREdHm44dO5p58+aZLVu2mGuuucZcf/31jnWWLl1qfH19zdSpU01sbKz59ddfTXR0tBk7duwllTtr1izj6upq3nvvPbN9+3bzxhtvGGdnZ7Nw4cIC5ZYrV85MnjzZxMbGmr1795oXX3zR1KpVq0C7hg4datq2bVtom/Pz801AQIC5//77z/tdKOoceaqMBx980JF2+PBhU6FCBcc1zJnnvKKMGTPGeHl5mY4dO5q1a9eaJUuWmKpVq5q77rrLked8n/drr71mIiMjzdKlS01cXJxZtmyZ+eKLLxzrA+a7774zxhT9nerbt6/p0aOHMcaYEydOGDc3NzN//nxHGQkJCQXSSvIdOJ+cnBzz7LPPmlWrVpndu3ebzz//3Hh6epoZM2Y48pxZL2Psn4e3t7d55JFHzLZt2xzrTJo0yZEnKirKBAYGmvfee8/s3LnTvPzyy8bJyclxvWKMMc8//7xZvny52bNnj/nhhx9M+fLlC1wHF+ZSr9OKu3b99ttvzcyZM83OnTvN2rVrTffu3U3dunVLdP9rypQpxs/P77z5jDGmV69eJjIy0syaNcvExsaa+fPnm6+++soYY0p0vDr776Go3xYiUroOfzfT/OppMb96UPDlaTG/elrM4e9K/z6DMSX7zTt+/HizcOFCs2fPHrNgwQITExNT4Nx49jGqSZMm5umnny6wncaNGzvSSnIsOtvZvyttNpuZO3eucXV1NUuWLClyvbVr1xqr1WoefPBBs27dOrNp0ybzzjvvmGPHjhljSv7b+9R2L+R4LCJytVKw/SrzyKT3zKMfv1/W1Sihz40xzsaYeQVSX+t2i7kLq9m/eYsxzxhja29M7L3GpLY35u/fjfl0vj3G9u5d/2fuwmp2/Lni9MpPnnxdqJ3GGFvBpEMJxoyfbcyz7y43U6bYb7qY0U+Y2e+sNONnG5OQUvLip0792Dz99BMmOzvb/PbbPDNlykfm3nvvMl9+Oc0cO3bUDBp0rxk69AHz0EMDzb333mW2bt3sWHfAz68ZXulg5setLmYLIv9Bp4LnuWc9/JKSYU/fd8S+LDHF/v+jSafzpmYYE3fYHpwvBSkmy4w288xss9mk5SaZ/+24w3x9+F3T8093M3htzVLZxnnl5xmz/ndjDu+9Mtu7CJfv/J1njIkw5wbazwy4R57MV3pWrlxpADNr1qzz5i3uhlj58uUdP4qzsrJMvXr1zLRp04wxJQ+K9u3b1wQGBpr09HRH2sSJE423t7fJz883aWlpxtXV1UyfPt2xPCcnx4SHh5tXX33VGGNM9+7dzb333lto+SUN1p59I7B+/fpm3LhxjvejRo0yzZs3d7yvUqVKgZvSxthvwrZo0aLItrZr1860bt26QFrTpk3NE088YYwxZtmyZcbX19dkZRV84KRKlSrmww8/NMYUHmwvbv9lZWUZT09P88cffxQoc8CAAebOO+8ssE9mz55dZN0La0tJgu2jRo0ylSpVMjk5hR+zzrcfFWwXkQuRl5dnIvr1PifQfmbAPfLeO0xeKT7YbYwp0bHWGGP8/PzMlClTCuQ5O+3555831113XYE8+/fvdwTbUlJSjNVqdQTXz1ZUwDY8PNy8+OKLBdKaNm1qBg8eXGC9CRMmnLe9QIGb3n/++acBzCeffOJI+/LLL427u7vjfadOnc55yG/atGkmLCzskspt2bKlGThwYIFyb7/9dnPDDTcUKHfYsGEF8hw8eNA4OzublStXGmPs1xbBwcFFPjR35MgRA5g333yz0OVnKu4c2bx5c9O1a1djjP3G/vXXX2+ef/55Y0zRn93ZxowZY5ydnc2BAwccaXPnzjVOTk4mPj7eGHP+z/vhhx82HTt2LPCw/JnODLYXVa+zg9o9evQw/fv3d7z/8MMPTXh4uCP4W5LvwMUYMmSI6dmzZ5H1ateunalZs2aBtj7xxBOmZs3Tv3WioqLM3Xff7Xhvs9lMuXLlzMSJZ/WcOMNrr71mGjduXGzdSvM67XzXPseOHTOA2bhxY7H5jCl5cGf79u0GML/99luhy893vDJGwXaRsmDLyzNLqkacG2g/I+C+pFqksZXy9ZAx5//NW5hvvvnGBAUFOd6ffYwaP368qVKliuP9qWPT1q1bjTElOxad7dSx1cvLy3h5eRkXFxfj5ORkXnjhhWLbd+edd5pWrVoVuuxijukKtovIv0EpzZ4tpWXWn8twdnLmzQEPlnVVSqAP0JuzJ2Hv++54Og0aSETFmrAb9kfDDz2gThK4eUNqon106DtffYlmt91KtWvOGKI2FrBcRFWqnptUzh9a1AD3mGhqVGpkT+x5O43f+4JQ71z8vVsVWlRuHhxIgOhykJIJ3u6wd28cBw/uZ968OSxc+Bv5+XmMHDmaSpWqkJOTQ/nyoVxzTStq1arNmjWrcXJyYsiQ+7jjjnt4tGlPKvuH0bpCnYtomMi/WDl/+9DxTmfNaOJpZf2WudisTjSMvNc+lHy+DbLzwNkJAn3s73PzwVY687fbMKSRQya5eLr4kldtIL/ZjuK9P5ByblGXVnhWBsRugCr1wN2z6HxOzlCv8OPSv98y4EAxyw2w/2S+9qW2VXPWsJmXUo7FYj95jRo1ipo1a3L33XcXmnffvn3UqlXL8X706NGMHj0asA/P7ul5+jvSokUL0tLS2L9/P8nJyeTm5tKq1enviKurK82aNWPr1q0APPjgg/Ts2ZM1a9Zw3XXXcfPNN9OyZctLalufPn2YPHmyY5jRL7/8kuHDhwOQnp5ObGwsAwYMYODAgY518vLy8PPzK7bcs+eyDwsL4+jRowCsX7+etLQ0goKCCuTJzMwsdljQ4vZfWloaGRkZXHvttQXWycnJoWHDhgXSmjRpUmzdL8a6deto06YNrq6u5yy7lP0oIlKYZVs2ciCh6CFDDbD/+DGWbdlI+7oNSm27u3btKvGx9nzWr1/PokWLCh3SOTY2lqSkJLKzs+nUqVOJy0xJSeHQoUMFzqUArVq1OmeqkpKeC848n5Uvb5/7rG7dugXSsrKySElJwdfXl/Xr17N8+XLHcPdgHxI8KyuLjIwMx3nsQsvdunXrOfOgt2rV6pyhxc9uV3h4ODfeeCOTJ0+mWbNm/Pjjj2RnZ3P77bcX2t7Lce30zjvvkJqayqhRo4rMf+b34O677+aDDz4AoGLFilSoUMGxrEWLFthsNrZv346np+d5P+9+/fpx7bXXEhMTw/XXX0+3bt247rrrLqltffr0YeDAgbz//vtYrVamT5/OHXfcgdPJ3zwl/Q6cz3vvvcfkyZPZt28fmZmZ5OTk0KBBg2LXueaaaxz7Hez764033iA/P98xDc6Z371TQ6yfukYDmDFjBm+//TaxsbGkpaWRl5eHr68vcPHXuRdynXa2nTt38uyzz7Jy5UqOHz/uGMJ/37591KlTOvdg1q1bh7OzM+3atSt0+fmOV9WrVy+VeojIhUlcvozsg8XcZzCG7AP7SVy+jMC27Ut9+8X95gWYP38+L7/8Mtu2bSMlJYW8vLxizwV33HEHI0aMYMWKFVxzzTVMnz6dRo0aUaNGDeDSjkXLli3Dx8eH7Oxs/vrrLx566CECAwN58MHC4xPr1q0r8lqhNK8HRUT+SRRsv8KWbtrAG7O/4d0HHiYypBz7D63F3epLcrY7I6dO4rNhT1CvUuVS2VZevn2OY5ci5g4tHWd9hT6HkKgoQm6MgvHAdqjwErSsCFXCIMgXWpcDJ0/g5woExtt/GK9evYopUybx8JjhxMTUhHzgQSAKeOp08fv27WXVqhV069YD63J3mA2MAQrejwfsMbnmMQDhjjRb/Qbsavk3NVsE8feGOKZ89AZ97riN1q1P/2iauxp2H4ZaFWHLPmhQGQYPHsoXX0yjdu26NG3aHJvNRoUKEQC4u7szduxLjvW9vX3Yt28vzs4uODk5UTu4ErWDK/HTa29SvmoVmt7S46L3tsi/Sm4+HEuGnDwIOSOg5OzE4h9eo1z56jTsci+EBUJ+PmTlQnaufY53Py/w9YRTN4vy8u1/9JaLeVoH/HDnLbrzMN+zkFh6UocqTkHc2mg3zpZLPFXu3wFbVoGrO1RvcHFF7E8nP98QHV34HIL/fPGlnK9kqlWrVui8ZxciISGBY8eOOebxXLhwIRs3bnTMR3bqpnRwcDBPPfUUzzzzDOvWrXOsHxgYePENOEvXrl3Zu3cvP//8M7/99hudOnViyJAhJZ77tDB33nknTzzxBGvWrCEzM5P9+/fTu3dvAMd8ch999NE5c7sXNW/5KWcHnS0Wi+PmaFpaGmFhYSxevPic9U7NWXehTtV1zpw5BW7KA1it1gLvvby8LmobxfHw8Dhv3S5mP4qIFCb+xIlSzVdSF3KsLUlZ3bt355VXXjlnWVhYGLt37774ipZASc8FZ57PTgUxC0s78xz33HPPceutt55Tlru7+0WXW1KFteu+++7jnnvuYfz48UyZMoXevXsXGfANCQnB39//kq6d8vPz2blzJ02bNgXs105//vnnOd+RJk2a0KdPHz799NMC106nAruloVGjRuzZs4e5c+cyf/58evXqRefOnS9pXtnu3btjjGHOnDk0bdqUZcuWMX78eMfykn4HivPVV18xYsQI3njjDVq0aIGPjw+vvfYaK1euvOh6n1LcNdqff/5Jnz59eO655+jSpQt+fn589dVXvPHGG4D94Y2Luc69lGNH9+7diYqK4qOPPiI8PBybzUadOnUKzAd/qYq7joPzH69EpGxkHy7Z/YOS5rtQxR1P4+Li6NatGw8++CAvvvgigYGB/P777wwYMICcnJxCz8OhoaF07NiRL774gmuuuYYvvviiQDD8Uo5FlSpVcvzWrl27NitXruTFF18sMthekt+3pXE9KCLyT6Jg+xW2cMNafvjrTwZ17U6ovy+vT2xOSFA1KjV4m9krltO2dl3a12tQKtuq89B9eFqtrJnwQamUd17JwNtADaANcAOQB87Nodmp38NzwelZ4DHgQyADCABTw2Cz2bA52ezfyjzgEHDWOXjJkoUsWjSfmJia1FlXD1YARyg02M6Ck6+ngJP3FHa98SqfbdtEo6w88iKGENlwIFZrZoHVKobA/mMQGWzvdBsRBMHBIQwdOrzY5k/f9BufbfmNqn+nQ3oO7733kWPZn2uT+erJp6lYr26BYPsve1bx9bbFTOg4BB9ryZ5gF/lHshlISAEvd8jMtnepCvACHw/78BFnue/xH/Fy8oKsHHB3sye6ucLek08Be7vDweNgdbWXeegEBPlAgM9FV/E46WSShwWYw1aiCcTNqRR+CFSqDa5WiKgK9tEoweJ03tXO1KrVfNLT80hI6Hnp9bkqlfQmVOnerAoMDKRLly689957DB069Jwb0ElJSecN7r711ls4OTlx8803AzBz5kwyM0+fV1atWkX//v1ZtmwZVapUwcXFhapVCxmOBfuT6JmZmY4fritWrMDb25vIyEiCg4Nxc3Nj+fLlREXZR1vIzc1l1apVDBs2zFFGSEgIffv2pW/fvrRp04aRI0cWGmx3c7P/XeWffDCvKBEREbRr147p06eTmZnJtddeS7ly5QB7r7rw8HB2795Nnz59ii3nQjRq1IjDhw/j4uJCdHR0idcrbv8FBgZitVrZt29fkb2SLqd69erx6aefkpube85Nl8u1H0XkvyushAGukuYrqVq1apXasbZRo0bMnDmT6OhoXFzOvW1RrVo1PDw8WLBgAffdd985yws7z/n6+hIeHs7y5csL1G/58uU0a9bskupbUo0aNWL79u1FXgtcrJo1a7J8+XL69u3rSFu+fHmBXsZFueGGG/Dy8mLixInMmzePpUuXFpnXycmJO+64g2nTpjFmzBjCw8MLLE9LS8Pd3b3Qz+yUTz/9lMTERHr2tF/Xvv3227zwwguO5YcOHaJLly7MmDHD8RBaUftr3759HDp0yFGPFStW4OTkRExMTIk/b19fX3r37k3v3r257bbbuP766zlx4sQ5geKSXju5u7tz6623Mn36dHbt2kVMTAyNGjVyLC+N78Dy5ctp2bIlgwcPdqQVN/rPKWcH41esWEG1atVK/HDfH3/8QVRUFE89dbpHxN69ex3/v9jr3JJcpxW2/xMSEti+fTsfffQRbdq0AeD3338vUVsuRN26dbHZbCxZsoTOnTufs/x8xysRKRvW0JLdPyhpvtK0evVqbDYbb7zxhmPkk6+//vq86/Xp04fHH3+cO++8k927d3PHHXc4lpXmscjZ2bnAfY2z1atXjwULFvDcc8+ds6w0rwdFRP5JdBV4hT3d+25ub92O2hWjAbih01j8fSNo3qgTtSIrUr9SFbLz8rG6XFpPpsycDNrVrUZqRtHDvOXl5+Hs5HzGMGK5wJNAB6DbhW3QBrwF3AzcdTItBhh5Vr5KQAPAFUgDnIBfocndzWjS5IwbHC7A9yeXn6FHj57UqlWH2rXr2oP6dwGh9mXblv1O8pGjNL/t5BPiy4D5wH3AycECqh4+zN35NmJu6sHOJIhsVo+ocvDrWogKgZjV0GAPNHgEsEDNyJI1PzU1lVdmvM8mnxQaV70b2wkfjibZR8nOt8Hy7blUfvpdHrir4BB2M7YtYsrGeQxu2IPGoRpaTP7FcnIhOZ2EjH0E5Z58OibIB8oHFJrdq2IUpGfZg+mnuDiDt4c97fAJe0/3PBv4edsD8m7nDs98IbLIozXRtCCSuewgEv8Sr5uSm0B81k5ifK45d6GLK0TXtP9/2Q+QnABd/w9O3tT6+fB7bEhexPBqn+PmVHhvlsGDq5GZWfyNvX+2NkAEcBD7kxhns5xc3qbUt/zee+/RqlUrmjVrxrhx46hXrx55eXn89ttvTJw40TFEO9iP9YcPHyY3N5c9e/bw+eef8/HHH/Pyyy87bixWqVKlQPnHj9uH8a1Zs+Z5A/c5OTkMGDCAp59+mri4OMaMGcNDDz2Ek5MTXl5ePPjgg4wcOZLAwEAqVqzIq6++SkZGBgMGDADg2WefpXHjxtSuXZvs7Gx++uknatasWei2oqKisFgs/PTTT9xwww14eHgUOtwc2H/QjxkzhpycnAI9swCee+45hg4dip+fH9dffz3Z2dn8/fffJCYmOoabv1CdO3emRYsW3Hzzzbz66qtUr16dQ4cOMWfOHG655ZYih/Ytbv/5+PgwYsQIHn30UWw2G61btyY5OZnly5fj6+tbIDhxOTz00EO888473HHHHYwaNQo/Pz9WrFhBs2bNiImJuSz7UUT+u9rUqktEUDAHE44XfVYNDqFNrbqFLL14pXmsHTJkCB999BF33nknjz/+OIGBgezatYuvvvqKjz/+GHd3d5544gkef/xx3NzcaNWqFceOHWPz5s0MGDCAcuXK4eHhwbx584iIiMDd3R0/Pz9GjhzJmDFjqFKlCg0aNGDKlCmsW7eO6dOnl+q+KMqzzz5Lt27dqFixIrfddhtOTk6sX7+eTZs2FQg4X6iRI0fSq1cvGjZsSOfOnfnxxx+ZNWsW8+fPP++6zs7O9OvXj1GjRlGtWjVatGhRbP4XX3yRxYsX07x5c1588UWaNGmCq6sry5Yt4+WXX2bVqlWOa56MjAwOHz5MXl4eBw4c4LvvvmP8+PE8+OCDdOjQAbAPBX+mU9cjVapUISIioti6uLu707dvX15//XVSUlIYOnQovXr1IjQ01LFfivu833zzTcLCwmjYsCFOTk588803hIaGFnrNVtR3qjB9+vShW7dubN68+ZyphUrjO1CtWjU+++wzfvnlFypVqsS0adNYtWqVY6Slouzbt4/hw4fzwAMPsGbNGt555x1Hr/SSbnffvn189dVXNG3alDlz5vDdd9+VaN1LvU4r7No1ICCAoKAgJk2aRFhYGPv27ePJJ58scXtKKjo6mr59+9K/f3/efvtt6tevz969ezl69Ci9evU67/FKIxWJlI2AVm2wVogg+9DBkx0fzmKxYK0QQUCr0r/PcD5Vq1YlNzeXd955h+7du7N8+XLHFCnFufXWW3nwwQcd59EzH3q7lGPR0aNHycrKcgwjP23aNG677bYi848aNYq6desyePBgBg0ahJubG4sWLeL2228nODi4TH97i4iUmbKYKD45OdkAJjk5uSw2X6by8/MLT7fZzI2b5ptrvpxrrI99ZdYfPHFJ21mydb75dOmH5njK0UKXZ2ZnmC+WTzYLN/5iPv98qlm/fq0xZpcxBmPMjRe+wUxjTBtjzL2FLEsxxnxvzLzlxny/4oz0zcaYWGPMhTY1yxiz1BhznzFm3+nkx2Lqmj4Wd5OVnm6M2WlMfjNjjnxfcN2cHGMyMwskrdhmzPjZxnyzzBjT1xjTwhiTWnC15OQk89FHE82uXTsKpB9JMubXNcYcT8wwY8aNNi9PeNlM/2aumfWHMelZp/O9/d5Ec++9d5lt27YULDcrzaw6tO0Cd4DIP1BGttm17RczbGUdk3XwoDEnUi5s/ZxcY/YfM2bnQWN2HbT/GxtvTGpG0eukZxmTmFbiTbxoFpoB5ltz9OwDQAm8sr2X6fGHxexN31R8xlULjFnwjTH5+WZT8lLz1b7nzAtbbjK3/eluTmTHX/B2r7TLe/6eaYyxnHxxxutU2szLsE27Q4cOmSFDhpioqCjj5uZmKlSoYG666SazaNEiR56oqKiTwxJg3NzcTMWKFU2vXr3MwoULiy170aJFBjCJiYnF5uvbt6/p0aOHefbZZ01QUJDx9vY2AwcONFlZp08mmZmZ5uGHHzbBwcHGarWaVq1amb/++sux/Pnnnzc1a9Y0Hh4eJjAw0PTo0cPs3r3bGGPMnj17DGDWrl3ryD9u3DgTGhpqLBaL6du3rzHGmHbt2plHHnmkQN0SExON1Wo1np6eJjX13L+P6dOnmwYNGhg3NzcTEBBg2rZta2bNmlVkWwvbRo8ePRx1MMaYlJQU8/DDD5vw8HDj6upqIiMjTZ8+fcy+ffYT/5gxY0z9+vUvaP/ZbDYzYcIEExMTY1xdXU1ISIjp0qWLWbJkiTGm5J/V+dpSlPXr15vrrrvOeHp6Gh8fH9OmTRsTGxvrWF7cfjz787uYuorIf8vM5UuNpXsnY+neyXDG61TazOVLL8t2z3esNcYYPz8/M2XKlALrFZa2Y8cOc8sttxh/f3/j4eFhatSoYYYNG2ZsNpsxxv7b+oUXXjBRUVHG1dXVVKxY0bz00kuO9T/66CMTGRlpnJycTLt27RzrjB071lSoUMG4urqa+vXrm7lz5zrWKex8WRTAfPfdd8WuW9jxet68eaZly5bGw8PD+Pr6mmbNmplJkyZdcrnvv/++qVy5snF1dTXVq1c3n332WbH1PVNsbKwBzKuvvnredhtjTFJSknnyySdNtWrVjJubmylfvrzp3Lmz+e677xyfT7t27QpcO4WFhZlu3boVe41QVHsLc+pa4P333zfh4eHG3d3d3HbbbebEidM3GM73eU+aNMk0aNDAeHl5GV9fX9OpUyezZs0ax/Kz91lh36lT1yBnys/PN2FhYQYocK4/5Xzfgb59+zrKL0xWVpbp16+f8fPzM/7+/ubBBx80Tz75ZKHXRqe0a9fODB482AwaNMj4+vqagIAAM3r0aMfnZYz9enf8+PEFtlW/fn0zZswYx/uRI0c6rrV69+5txo8fb/z8/Iqs65l1uZTrNGMKv3b97bffTM2aNY3VajX16tUzixcvLva7fqYpU6act+6nZGZmmkcffdSEhYUZNzc3U7VqVTN58mTH8vMdr86+ZixsX4tI6Tv83Uzzq6fF/vLg9Otk2uHvLs99hpL85n3zzTdNWFiY8fDwMF26dDGfffZZgXN7UceoXr16GaDAMeiU8x2LznbqeuLUy8XFxVSqVMmMGDHCpKUVfz9t8eLFpmXLlsZqtRp/f3/TpUsXR90v9Lf3hRyPRUSuVhZjCnu06/JKSUnBz8+P5OTkUp1v62qVm2/D1dmJtMxMqj/Yj9Y1a/P1E88WzGOzUfGvb/Hdb8V5lwtz7m9HpaDTPcyemjaZzfvimPnkmBI9FXskOZ4DJ/bRIKoJzk7n5s/Nz2X+pp9xz/Vg2vuf0qRJcwYPHop9XPZKQPkLbqftiI3tm7ey0bUmLs5O3NoS+BL4C/gdVtyexvZGqfTt7A+cMbfLAezDxf8CzMHeGz4BaJ8LD9wH0dHw7MlhaQxwE/Y53Y8B7wHN4MeVkHz8BNUOLaJ5fk+4eyl4twdeBEbBsaPw++/QpAmsWQ033Aiu9mHINu2FZZsN3ZsZInCC1JO74AwbNqxjwoTX6Nq1O7fffnqInj+3wYpthvY1k2kY48+TTw4nIeE4EydOxsXFBWMMH3zwDgcPHqB+/YbccsvtGlZM/nsysyExDTKy2eW2g6oV2xefPzndPnx8Of/Tc7AnptmHoXdzgUAfSDqZJyzQ3tO9sNFA9h+zz/EeXb7AcmPMGSN6nDadtSxiN31oQAeqnLO8OKsT57I66Wf6Rb1WZO/0s7207Wb+SvyB1+usItAaTqDb1T+f3+U/f88CHsF+YjglEpgAnDuv5b9Jv379SEpKYvbs2WVdlX8k7T8RkXPN+mMZj3z0HgcSjjvSIoNDmHDfYG5teeV7ccnVa9myZXTq1In9+/dTvvyF3wsoC2PHjmX27NkF5gj/t2jXrh0dOnRg7NixpVZm+/btadCgARMmTCi1MkVE/gmOzJ7F9pGPkH3w9H0Ga0QkMa9OoPzN/+77DCIicuUo6lcKEpMPEOAXQVp+Lsdys6jkfnrO4N93H6PDuwt4+9bG3NssigqBQYQGnDs3nquTE7ub3opLMydcnc6dy/ePbZvZELeb7LxcPEsQbC/vF0Z5v6IDN67OrnStb587vOJTlShf/uRY7BQyBHIJbZ2zmdoT63KicwYHbzg5//gk7N+y+6HZ7UNo5vsVsAOwzzfLcaA39qHgW2IfQfhdYCPwrRP4+cKZAR0LUBPwAQYBIfbktCwwHoE0t/SETwCfttDnKBBsz/D9bPhupj3QvuZvCA2D5va21omCrz8Zzcd/WRg79iU+fe5R1s6Zy0trV+Lp50deXh41a9Zm9OgxVDw5/P8pTavB7g0/8M6r39Dyxpt4+OHhbN29AXNywMbc3FzWrl1NXl4enTt3OSfQnm/L55bvnqVmUBSvtL//ove9yFXtcKJ9PgVgTcovfLv9XZ4M+NgeSA8pZOjFtEx7ID3YD5xPBsX9vMBmg6Q0yMkDd1f70PTxJ8DJYh9evpx/wXLK+UNefoFA+4mcQwxdV5cO5f6PAdGnh8NOJZvNHCEcHxpQcO7JwsSmreGVHbdxb9TrtAi6lcYBXWkc0PWCdsvASm9zXfn7qerT+ILW+3e7FeiBfR6QeOxztLcBNPSiiIjIhbq1ZRt6NG/Jsi0biT9xgrDAQNrUqqshjcUhOzubY8eOMXbsWG6//fZ/TKD93yw5OZnY2FjmzJlT1lUREflXKH/zrZTr3oPE5cvIPhyPNTSMgFZtsOh6SERESpGC7Zdo/ebv+Gj6rdze/R3e8qvNjyf2s7tpTyKtXgD4ursQHehFiLcVdzc3Vr35fpFleTgX/XHMG/sy2bm5eFrdOZ56lN+3L6JZlVbsjk8EoPUlzLdXpUq1i173TBFNKnKs/FFqtHamVRtP2I593va7gAhw8n8PssaAe9Tplb4CcoBawEPAA8BuYBsQ5Qzj3zmdNw6YCgyDs2Nhd7Q9+Z8Y4CNgIdAn+HSGW3raA+yNGsGaNdCoYHArODgYi8X+kIPNZsPYbJwa9OGVV54nMTGRV1+dgNNZD0K4OEOdmIrMW+TG8M8+wck1jWffHsDgXo8zeuAruLm58dJLr7Nv314aNGh0zj7LteXz56EtpOZkFrNnRf5BMrPByen0XOsZWRDsC1jId3fijy1zqeBWAzKy7Q/PUEiwPTTQHlh3Pvn3lphm/2Nzt49GwYlUew93mwEXJ/u/2bn2p27cnE/P3W51LTjnO+BsccXXNQRv54JzxSeQwVHSseJMAB6Qm2fvYe/vXWiv+cz8VBJyDpCWl3jRuyrEWpEQa8XzZ/zPcQbal3UlRERE/hWcnZ1pX7dBWVdDrlJffvklAwYMoEGDBnz22WdlXR0B/Pz8OHDgwPkziohIiVmcnQls276sqyEiIv9iGkb+EsUf2cxXswfR/bqXWOoRym9Jh5hcrVWxgfNLdeDEPhZunker6u1pPGwkThYnTnzxnWO5zWZj66FNVAiIxN8roJiSLq+1767m2z++YlDUw0TOrwg9sY8Q/BrQDvgC+8jANYAPgLuxP/7x9ckCZgNVgTon378LfIq9J/yIIjZqO5mvOnA9HEuG7/6EljXtPdjPFLsvnV/WOnF9cyuVQ88dTQBg9epVzJ49E4AbbuhOixatCs3357YtLN64jjre7oyZ+Ai3dO7Hk0PG4FqC70FqdgZuzi5YXdzOm1fkqmYzsDseXJ0hqrw98H4wAXw9z+11frKnO0eT7P+GnTvih71MG+w+bA+uVywHxtiD7+lZ9gB7oA/4e0Fmjr2XO0B5f/uUE76eF1T9TRwmAE8q4AuJqZCQau957+dVaP58k4+z5co8CT1//mFq1vSlQoULa1Np+zedv0VERERERERERERELlXhEUYpsbDytXn0gWVUrdSGplnO1F6/HyebrQRrHgJyS7SNnJwMps8cwIYt3wNQzjeUGxvcSpXy1flw8DA+GPxIgfxHUw6zes8KNh1YA4xl1e4vWL939QW06mfg6AXkL1xSjUQOu8eT1jQVWgC1gYrAqfh/OvaAWB3A8+TyWieXLcE+3fprZxTYDHtP2BDs86p3B/5nXzRv3hyWLl0ETpDQD36PtMfhjLGPIn32R7JoA8xZkUtWngs7VhS+b44fP8a3337FwYP7OXIknm+++bLIttYKq0BNVytNG7bk8b6v8RYb6PrtkyXaTz5WTwXa5d/ByWIf+j3oZBDW6moPVJ8Z9E5Khz2HIT/f3nM9L9/eixzsf7DnlOkEEcH23u5gH3o+0Mc+hLwF8PGw53F3s28f7D3fjyZBakbhZZ70Nwf4lo3YTk77UIdQe6Ad7PUuH1BswL5UA+2H9kByQqGLtmxJ5tprFzFkyN+ltz0REREREREREREREblkGka+BHJttkLnUT/bhB9mMXn+PFrVrEOHeg2KybkVqAsMAD48vZ28HLbHb6FyuWp4Wk/3pExIjOPP1ZPJyc2kXq0e/LlzKXuP7+bmJr3p3abDOaWX9wujZbV2ZOTsJyn9A2KPPIW76y7qRxU3L7ANe+TqT+BG4P8wZip5ebm4ul5cILiDc2dabWqLW103ePtkYvczMgwEGgNVTr5//oxl+07+e2Zv9GbAr4A/kIb92+sCxhi+++4b/Pz8adu2A5v2wtrdEB4ElUNh8I3n1i0vH6yeXvgteo7WTw0vtP4LF/7GkSOHufXWXtSsWZsjRw6zatVKmjZtfk7eFSuW88MPs/D29ua2W27nw+l/0iCkSiGlivzL+Z/RC9zJqZA52U3BAHjEyeke8m2w9yh4We1B7jO5n3UMyrfZg/rHksk+fow/lkymQds7CXD3A0+rPX9SGhxJAiz2gHwhFhLLTo7Tmar4c1YeJ6ci1yt1Wemw/CcILA+dep2zuFo1H0aMqMH114demfqIiIiIiIiIiIiIiEiJKNh+HlOP7OK+HX8wr05nOgecnij8+xXL6f3aC8waNZYbmtiDr8/36Ufn+o1oV6feeUotD1wLtCmQui8hjjVxf5GXn0eD6CaO9LDytXjy4XUEBVQCICq4Mi5OLni6FT60scViwdfDjz92LiEpYzw3NWqMkyWS5TsWczT5MN0a9cTV+cx5jA32sdzLAb8B1wAV+fLLz1m6dBHPP/8/QkLKlWBvneUacHvADboUsXwb9jnau2L/JiZj78nuBPQB5p58PYR9WuedwHb4bstL+IeF0m5mP5ycnLBg4eYmbTi4dAO24fk0H+xMhaZQqXwh29wDhMO1DYGGrtDthXPz5AEfwfUxNxLaL4yWLdvg4uLCZ599wv79+wjxG0F09YYAJCUl8sUXn7Ft21buuOMe2rRpx/atG6m06DjX3FB2Q/iLXLX8ve2vUywne6NbTs6/Xsj86AVkZMOhBAjwBg83dm75jfmfPY0bLrRqco99CHt/bwj0tZflaS2yqPtpRiKZ+OPB7vR1HMveS/PAHqXQyAvk7gUN2/HAuAT2vLKIX35pj+XUfgH27Uvn3Xd3kpWVT7u2gTg5ueDkfGWGrxcRERERERERERERkaIp2H4eQS5Woty98DtrmG+rqyt+nl5YXU8HrcODgulUvyGzVyznlhatCwRLCgrEHkUuKCq4Mvm2PCoGVz5nWURYfcf/o0MqExEYdU6eM4X4lueaqm0I9Q/H02rvWWrBgsViwcLZ9bJgH989BPvQ9quBPEJCWhEaGorVWnSwqijGwPbjEHEXeBfSOTQvH1KCIPB2oD3wDHAC+Baohj3w/gT24Ph0YObJ9E3wx7YZpPim8O3aP3j++VcIDAxi7Yxv2bJwMbfUHUlQpwiqFtKbnS1AX+xzx58c4T0vL49Fi+ZTr14DnJ2diY3dRfMKLWAy+Lbwo+3bp0cOuKZOFCkbv2LLks8dwfYpUz5i48b1BAUF07JlK6zO7kSE9adJkzD8w8IJ6nMLo267kxG3nNtbVUTO4ORkn5P9fFyc7PO3u7tBkC81y9/GrflZxDS7EbwCTwfr3Vzsvd+L4Y+Ho0f7e7EDiU1fzadNjuDnGnKprSmx7Ox8vvhiLz16xLB93+/ExqaRn29wcTl9nPb1daVePX9iqrnz+r2VKB9Vh3tf/PWK1VFERERERERERERERAqnYPt5dA+KpHtQ5Dnp1zduxpFp356T/sz0qUz6ZQ7zn3+VTvUbXdC2XJxdqB5W6/wZgeYjHiItK5PtE6cWutxisVA9rGaBtJbV2xVT4vwz/r8aCOTaaytw7bXXF1+ROOzfogggC7gXaAz7/w/mrYE6UdC5wbmrLdoAm/dBnwdOjjL9NjAJaAQ8hn1K+1uxB9zvAbxg9w2x/Jr8Mw36DcTF3cr62O04O9u/wg9+9gnH4/YTFBQBMYVX9dPHehK7L55nmi7CFfsDBDt2bOPLL6cxf/4vVKwYxerVqwh+KpgqH1Tj9xVfsHPISu6Z8Dq79+xm5i/LaXztvUR1vc1RZuvW7di6dQsREZF4e/vAk+B3XTUG35fPruNVcHV2wfnkFARZ6em8d1dfGtzQhU4PDCx+v4pI4dxcCwTlnV1caXzdvUXnz7dBcrp97vVies33i3qN+KydVyTQvndvOnfcsZzhw2uQnZ1P//4refrp2ixY0OFkoL3gtCUhIe6sXHkdtvx8ph6uRXBEEQc5ERERERERERERERG5os4/EblckAe7duepXnfRokbJguYXq1p4ODUqRJKWlcZjU15k8ealpVh6XaBCsTlWr17F1KkfYfoaGHQyMR97j/QU+3zpLVOg4eaC623dD7vi7UO8Vwu3x7/IwR4gfwOoCozEPi97PvaO9vFARfBu503KNck0aN+e3rkDecnjdfx2+MEHEFAunNCYqsz75T0yU1PPrfDhwySuXUlCxnbyr8lzJMfE1KR8+TASEo7TsmUbgoNDmDTpfWwNbSyb/TkLP/yY1OPH8fT0pFy58ryQso660x/mUEoCAA0aNCImJoaKFaPtBdYEZs0A27dUDa/A4c++4dEe9uB8+okTbJj3Kws3vM74iW347edXGf9BWzIyE0v0qYjIBUpIgX1H4UQqpGYUm7WuX3uuK39lHoI5ciSLv/46wbq1R+lyrT/PPVeXgQOr4OzshJubM+aMOe3nzDnIL7/EA2AzFnbYXscS+eQVqaeIiIiIiIiIiIiIiBRPwfbzSM84wZ+rp5Cbl33evH+nHud/2Qe5/7ZeeFrdz5t/Tdxf/BW7/ILrFH8igZ//XkWwrx+/rPmbN79bxAc/Fz2kcG5eHqM+/ZgF69cUsjQFKCQ4fR4rVixn2bIlpPVKs/c8B/ACfgbG2Ud6bvYJBH19eh1jYP462DcNqn4KNzYA65vYp68/DGzHPlx8K+xTxz8NWIHvYJr7SOa//haPP/40tWPqkP4VTKoECROBT4D9sHDSJ0x75DH++OIrti//g08ffvR04D00lGHffME76//C6unF71tg1yFwdnamffuO2Gw24uMPUa1aDMHBIaSmphDTvw/PrlhKQFgYERGRvDT8dcplB2NNdMPTyT6tgKurK489NopbbjnZ270v8C5QyMcfFBnJhLjtVGhchWOxsfz5/iT2xP1JevoJlq2YyK49pfnAhIiQl28/8AT7gJ9XydbJyIbEVPt6Fys3BxZ8DVtWFbq4WbMgjh69Be99PfhiTGuefbYOFSt6cfx4Nq+8sgV396/54os4AHr1Wk6PHkt55pkNHDiQwSuvbOXdd3dgsxnWr9eDOnJhLBYLs2fPLjZPv379uPnmm69IfS7ExdQrOjqaCRMmXBV1kX+HqVOn4u/v73g/duxYGjRoUGb1EfmnWr58OXXr1sXV1dVxPC0sTaSsleRa4mo9F1xMvdq3b8+wYcOuirr825x9/Xi59vXlFBcXh8ViYd26daVa7tl/ZyX5zXKhzv4Onv15GGO4//77CQwMdLSxsLSr0eXYXyWlv+3L6+zfHlfS5fotfbUord/0V+pv4N/+eVwI3dcqu7r825x9LVYa+/o/HWzPtdn4+cQBsm35ReZZ/MdbTJ/ZnzUbZhRIX7Pha96fegNp6ccdab8kHmLG8Tj+Sj1+djGF2ntsN3HHdp8339e/L2bIB2+Tm2fvkb02I5FAX1/CAgKI8klmeI9beLb36R6Za2J3Uu2Bvny/wh7I33HoAP+b+RXvzfmhkNLrAY1LVN8z3XvvQMaOfQmfIT7Qu5AMFuBz7EPDn0qywM3XQMu9wGwgAQjHPgS9OzAR+B/2YPWNQCdgGeAHK2fN5K9vZtoLcgEeBmcv2DMAeBR4Ajo0u5c+b7xCizt78/tn0/n13YnsXbf+dAXatMWpchWOxZ9g9U5Ye3LXt27djp49e9G6dVsGDnyQkSNHs2zZEn767WcOpiUDkJOTAw/AmqRepIybgr+3T6H7JTM7m3ve/B9fLllY6PKAsDAevHcOY/N30Wj3bQSvjWbpkveY8cNgvv/lv9Vb9fDhTF57bSspKbkAZGbmcfhwJgB/J/7MvozNxa0ucn7lA6BSKPj72OeEL4nEVEhItQfqi5OXT3peMhN3D2JrylkPTeXnQUoipCcXuXpQkJXqjbtQpUFnR9rIkWt58sn1+Pq64u1tnyJjxoyWuLk5MWvWfqKjvVm+vDOTJzfnxRc30aDBPKZPjytZu6RYhw8f5uGHH6Zy5cpYrVYiIyPp3r07CxYscOSJjo7GYrFgsVjw8PAgOjqaXr16sXDhucf7VatW0alTJ/z9/QkICKBLly6sX7/+nHxXWnx8PF27dgWKvln21ltvMXXq1Ctfuf+YxYsXY7FYSEpKKuuq/CP169fP8fdY2Cs6OrqsqygixRg+fDgNGjRgz549jnNOYWmX4nIFhcQuJSWFp556iho1auDu7k5oaCidO3dm1qxZjlGa2rdv7zguW61WKlSoQPfu3Zk1a9Y55e3YsYMePXoQHByMr68vrVu3ZtGiRVe6WedYtWoV999/v+N9YTd4R4wYUeCaUS6P0vqbPvOavrBXv379SqW+pe1qOKZFRkYSHx9PnTp1yqwOpeXs3zzz5s1j6tSp/PTTT442FpZWlooK6p35G+9SypGrT+/evdmxY8dl3UZZBvT/Da6ma4DSvjY7JTs7mwYNGpT5OegU3de6epTWfa3irsssFgtjx44tlfpeCf+pOduT05J4/J0RHMjy5+1Bw5lPKoN2reCNSk0YHlHbkc8YQ7ax4e7kTJ2YbsTG/U7l6DakZ5zAyzMQgF1xS9m68xeSUg7i7hlIxw2/EOPhx8oGN9DMp2Rz/nZtcHOJek9OXfArv6z9myd69mavG9y4ZznUrUhO0lKmfvkZfx6pwbZDu9iwJ551Ez4kOT2dPUfiOZZiD/TUrhjNgudfo2ZkxUJK74LjazAXjn12BJ8Rfrg3Ltg1O+7IYf7auY1erdsD4OnphafneXqKRpybFBkCvAQcA0Kx94o/1TP+YaAzsP/kcgtwcsT3l9f/ZY/Wn+TVEwacepMFxIFvfgg3DH+EzGzoPu4lrul9GzXatC6w/S2Ll/BSx+u5cexLdB35KByEvDfSObJnATl1G4KvHwAdOnTGy8uLFi1aMmfO98yePZOnbr2d6D434cr/AZ8CsG7dGipUiCAkxD6HdHxiAl8sXUhWTg53tutY6G6xWCy4jfekVdIQdj+9iphZnaj6VFuCA6sUvz//ZT78cBdjx24iKMiN/v2rcOedfzBvXjwbYq/hhX3dqObdjNfqrijraso/3RnHjRIJ8YfcPHAt5vSYmglHEjnhE88vRybhjAs1fVudXu7uCTcNAKei54gH6Pno5ALvBw6sQlCQlf79K/PssxuIjPSkW7cI1q69njFjNvLtt/u47Tb7cXzOHPvQ8hERHhfWvn+AfAN/5cARG5R3gmZu4HyBH+OFiIuLo1WrVvj7+/Paa69Rt25dcnNz+eWXXxgyZAjbtm1z5B03bhwDBw4kJyeHuLg4Pv/8czp37szzzz/PU089BUBaWhrXX389N910E++//z55eXmMGTOGLl26sH//flxdXS9fY84jNDT0vHn8/PyuQE1ETsvJycHNze2C1nnrrbf43//+53gfFhbGlClTuP766wH7yEUiYmczcDAB0rPAyx0qBIHTZTyvlkRsbCyDBg0iIiKi2LSrRW5ubpmevy+Xi21XUlISrVu3Jjk5mRdeeIGmTZvi4uLCkiVLePzxx+nYsaPjxv3AgQMZN24ceXl5HDhwgO+++4477riDfv36MWnS6Sfzu3XrRrVq1Vi4cCEeHh5MmDCBbt26ERsbW6Lrl8slJOT893a8vb3x9va+ArWR0rBq1Sry8+0PVv/xxx/07NmT7du34+vrC4CHx7/v99XZLvZv39nZuUz/HkvT2b95YmNjCQsLo2XLlsWmXShjDPn5+bi4XL7b7/+Wz+Rys9ny2RW3jJTUeHx9wqga3Qan89yzKWseHh7/iWPSP9Gpv+2r5RrgclybnfL4448THh5+VXQgAd3X+jeKj493/H/GjBk8++yzbN++3ZF2NfyNldR/qmf7xh2rmbHkF35eu44F69dwQ2AED4bFcHNQwSD0oF0rCFnxFQez09m68xd27F7I198PZtRL5TkQv57MrGSc3ANJu30muz3LYzOGPVlpHMjJKBBonzCpHe9MvrbI+ri7urNwwwYOJRTdE37A269Tp2IUc8e8RKenH2fZwsU025lAJ5sXd1//EL4hnfAOrE92bgbpWVnsP36MDvUakPHNHO677gZHOR3rNyQsMKiQLXwIvAdAovUEcwd/z8rc38/JNXLKJHq/+gJ/79wOm4ARwMEiq12oXbt2kpKSAn7Y52Y/WxWgG/AgEAVUAw4Bj4GPTzA+GUFw9qj7h4BawBLgOnvSN7/Dt3/7UatDh3M24R8WRnDNhriFV8fbA1gKmb+lcmLRQfb8fXqY/XXrVpOZksKb3W4lZe8BypcPxaNzXWAYcJ9904cO8vbbbzB9+qeO9SqHhrPl3U+YPHTEefdHgH8kQ6suoE6rG6lf62YqhNY97zr/Jo8MqsxPXzend++KTJy4k1q1/LjhhnAqBkUwMPpt7o58oayrKP9Fbi72AP2RRMi3sTkWeo2AP8+8pnR1Bqsrkb51ebH2Yu6u+NK55Ti7XHCgv2XLEF5/vSGLFh1m5swDDBnyNwA//niQ6dP3ct99fznyjhpViyeeqEnr1iV7uOufYm4mtDgKvU7Aw0n2f1sctadfLoMHD8ZisfDXX3/Rs2dPqlevTu3atRk+fDgrVhR84MfHx4fQ0FAqVqxI27ZtmTRpEs8880yBC8Ft27Zx4sQJxo0bR0xMDLVr12bMmDEcOXKEvXv3FlmPUz0MPvzwQyIjI/H09KRXr14kJ58eIcFmszFu3DgiIiKwWq00aNCAefPmOZbn5OTw0EMPERYWhru7O1FRUbz88suO5Wf2xqpUqRIADRs2xGKx0L59e6DgUFKTJk0iPDwcm81WoK49evSgf//+jvfff/89jRo1wt3dncqVK/Pcc8+Rd3I0npLIz89nwIABVKpUCQ8PD2JiYnjrrbeKXad9+/Y89NBDPPTQQ/j5+REcHMwzzzzjeGL7lIyMDPr374+Pjw8VK1Y858fjE088QfXq1fH09KRy5co888wz5Obmlqjezz33HCEhIfj6+jJo0CD7KDgn2Ww2Xn75ZUeb6tevz7fffgvYH/DocPIaJSAgoEAvqnnz5tG6dWv8/f0JCgpyBBrOty8efvhhhg0bRkBAAOXLl+ejjz4iPT2de++9Fx8fH6pWrcrcuXMLrLdp0ya6du2Kt7c35cuX55577uH48eOXXO6SJUto1qwZVquVsLAwnnzyyQLfh1Of3bBhwwgODqZLly7079+fbt26FSgnNzeXcuXK8cknn5zTZj8/P0JDQx0vAH9/f8f74oIjP/74I02bNsXd3Z3g4GBuueUWx7Ls7GxGjBhBhQoV8PLyonnz5ixevLjY/S9yNdt1CCb/CjOXw7zV9n8n/2pPv1zOd/yzWCwkJCTQv39/LBYLU6dOLTQNzn+cstlsvPrqq1StWhWr1UrFihV58cUXgaLPc+c7l56q44wZM2jXrh3u7u5Mnz690LZaLBY+/PBDunXrhqenJzVr1uTPP/9k165dtG/fHi8vr/9n76zjosreP/6ZIYbubmkLAwxEF7sRu1Ax11VU1tY1sNdYu3VXTKxF7A4MxBZEQUpSUrphZp7fHyNXBgZmRFz3u795v17zgnviueece+85zznPCXTo0KFGPS6u3ayv3L1798LKygry8vKws7PDsWPHaqR37969GDBgAJSVlbFmzRpYW1vjjz/+EAoXEhICFouFmJgYkfn+7bffEB8fj6dPn8LT0xNNmjSBra0tpkyZgpCQEKEBMSUlJRgYGMDExATt27fHhg0bsH//fhw8eBC3b98GAHz69AnR0dFYtGgRHBwcYGNjg/Xr16O4uBhv374VmQbgy2q88+fPw8bGBgoKCszkRknLhYiwYsUKmJmZgcPhwMjICLNmzWL8q24nWblryqBBg4R2Uam6SvTmzZtQUFCoscLH29sbXbt+mYz/6NEjdOrUCYqKijA1NcWsWbNQVFRUa15F8bU6TKWOV5f+Agi+kQULFkBLSwsGBgY1VhNt2bIFzZs3h7KyMkxNTTF9+nQUFhZKlOa69FwA+PPPP9G4cWMoKCjA3t4ee/bsYfxq+6afP3+OHj16QEdHB+rq6nB1dcWrV6KOUBSgq6vL6AtaWoLFNHp6eoxbbQP0ddU3AJCUlIThw4dDQ0MDWlpacHd3R3x8vETlIgm15R+ou9xqq9Mq34d169ZBX18fGhoajPFl/vz50NLSgomJCXx9fWvIqlxBWLmi7c6dO3BycoKSkhI6dOggNEAeGxsLd3d36OvrQ0VFBW3atGG+fUno2rUrZsyYIeSWmZkJeXn5OleTrl+/Hvr6+lBVVcWkSZNQWloq5F+1zzN+/HjMnDkTiYmJzLctyg2ou42rWibXrl2Do6MjOBwOHj16JHG82sry8OHDWLlyJUJDQ5mVfpVtZfUdN+qqG+qSk5ubi8mTJzP1Q9euXWsY18SV67+VkLfnsHyjBXb82QWHT4/Gjj+7YPlGC4S8rX0177fSuXNnzJo165vq06qrzqOiosBisYQWAwDA1q1bYWX1ZfGWON2pKoGBgZgwYQLy8vJEriCtqy8tybdpYWGBNWvWYNy4cVBRUYG5uTkuXryIzMxMuLu7Q0VFBQ4ODnjx4gUjQ9TOC9u2bRPauSwwMBBt27aFsrIyNDQ04OLiUudYC4/Hw5w5c5g+9oIFC2qMG9T32/4eOkBGRgbc3NygqKiIRo0a1aqHVqWhdbNKrl27hps3b9bQFWtDOq4lHdcCvn5cq+rYjrq6OlgslpBbbcb2srIyLFy4EKampuBwOLC2thYaP/qa+rDBoB9AXl4eAaC8vLzvep+YuIdUWlYo5Bb44jZdffaYuFxurfE2JIaR46tL9CrqFh0+5UFHzoyj63fX0R97nSkn7yM9e32Chqy3JDw4TOPePyQiIi6fR3w+X0jOpj3taev+n2q9z8uYKIJbNxq+YZVI//KKCtIY6U6tvKdSTMpHUh7Wj2Yf3E1w60acwb2ZcFwel669fExw60Zjt/wutlwqOXn/Lq06eayKnAp6Ev2IkrMSa4R9ER1J6//eShXcvUSH+URORHSHiKKIKKda4EwiKhF2Skn5SBMmjKZdu7bWnqAyIvpERCuIaBoRcYloDhG5EFH2ZzcnIjpbJU5PIupBRKVfZDxZQnRv1+frfCKaSEQnBJcVXKIdF4mO3SwnevSQqIxomWon8oAC5aalMWJnzZxKE8eNpNHg0N5Db+l2yGeP0BCivw5S+JvX9Pz5U7p06TxFRkYIyujCJUqJjKo9fw1AXFoq5RUVig/4PwA3Lp0o+iMd3hNOgB+1b3/jRydJyv8opdzihhFUwSXi8ogycoiiPxIVl1JwKFGncUTXHjXMLSr55aUNjXqqQZmlSTX8srJKydb2Eo0c+YhcXW/T6dPxxGb70fTpz4TCZWeXkbPzTdq27X3DJq4Ovmf7fbWYyDSFyKTaz/Tz72oDPeaqZGVlEYvFonXr1okNa25uTlu3bq1VxoYNG4iIKD8/n7S1tcnHx4fKysqouLiYvL29qXHjxlRRUVGrfB8fH1JWVqauXbvS69ev6f79+2RtbU2jR49mwmzZsoXU1NTo5MmT9P79e1qwYAHJyclRVJSg7dm0aROZmprSgwcPKD4+nh4+fEh+fn5MfAAUEBBARETPnj0jAHT79m1KTU2lrKwsIiLy9PQkd3d3IiLKzs4meXl5un37tlB+q7o9ePCA1NTU6PDhwxQbG0s3b94kCwsLWrFihdgyraS8vJyWL19Oz58/pw8fPtDx48dJSUmJTp8+zYSpmi4iIldXV1JRUSFvb296//49E+fAgQNMGHNzc9LS0qLdu3dTdHQ0/f7778Rms+n9+y/fzOrVqykoKIji4uLo4sWLpK+vzzzL2vD09CQVFRUaMWIEvX37li5fvky6urr022+/MWHWrFlD9vb2dP36dYqNjSVfX1/icDgUGBhIXC6X/P39CQBFRkZSamoq5ebmEhHR33//Tf7+/hQdHU2vX78mNzc3at68OfF4vFrT4+rqSqqqqrR69WqKioqi1atXk4yMDPXp04cOHDhAUVFRNG3aNNLW1qaioiIiIsrJySFdXV1avHgxRURE0KtXr6hHjx7UpUuXb5KbnJxMSkpKNH36dIqIiKCAgADS0dEhHx+fGs9u/vz59P79e3r//j0FBQWRjIwMpaSkMOHOnTtHysrKVFBQUOfzIBJ+t+vi8uXLJCMjQ8uXL6fw8HAKCQkR+v4nT55MHTp0oAcPHlBMTAxt2rSJOBwO8435+vqSuro6E97Hx4datGgh9r5SpPwIoj8SbT1f+y/64/e5r7j6LzU1ldTU1Gjbtm2UmppKhYWFNdyKi4slqqcWLFhAmpqadPjwYYqJiaGHDx/SwYMHiaj2dk5cWxoXF0cAyMLCgvz9/enDhw9CdVNVAJCxsTGdPn2aIiMjaeDAgWRhYUFdu3al69evU3h4OLVv35569/7Sd5ek3ayP3HPnzpGcnBzt3r2bIiMjafPmzSQjI0N3794Vkqunp0eHDh2i2NhYSkhIoLVr11KTJk2E8jVr1iz66SfR4xg8Ho80NTXp559/FvsuuLq6kre3d60ypk2bRkREfD6f7OzsaPLkyVRYWEgVFRW0adMm0tPTo+zs7Frl+/r6kpycHDk5OdHjx4/pxYsX1LZtW+rQoYPE5XL27FlSU1Ojq1evUkJCAj19+rSGLlGp/2VkZBAA8vX1pdTUVMrIyCAi4baAy+WSvr4+/fnnn4yM6m4xMTGkrKxMW7dupaioKAoKCqJWrVrR+PHjxZZpVcTpMNXbKEn0F1dXV1JTU6MVK1ZQVFQUHTlyhFgsFt28eZMJs3XrVrp79y7FxcXRnTt3yM7OjnmWtSGJnnv8+HEyNDRkvjt/f3/S0tKiw4cPE1Ht3/SdO3fo2LFjFBERQeHh4TRp0iTS19en/Px8sWV47949AkA5OTliw9ZV35SXl1Pjxo1p4sSJ9ObNGwoPD6fRo0eTnZ0dlZWVMeVfXZcV9X3URm35F1dutdVpnp6epKqqSl5eXvT+/Xv666+/CAD16tWL1q5dy+h+cnJylJSUJCTr9evXQuXXrl07CgwMpHfv3lGnTp2EvsGQkBDat28fhYWFUVRUFC1dupQUFBQoISGBCVO9n1VVrztx4gRpampSaWkp479lyxaysLCoMQZbyenTp4nD4dCff/5J79+/pyVLlpCqqmqN76HyeeTm5tKqVavIxMSE+bZFuRHV3cZVLRMHBwe6efMmxcTEUFZWlsTxaivL4uJimjt3LjVt2pRSU1OZtrJ6eRHVXTfUJad79+7k5uZGz58/p6ioKJo7dy5pa2sz75ok5fpv5HWYP3ktZpHXYlT7schrMYteh/l/l/s2RH1ave/h5ORES5cuFbqPo6Mj4yaJ7lSVsrIy2rZtG6mpqTHvQ2XfS1xfWpJvs1LGvn37mL6jmpoa9e7dm86cOcPoOI0bN2biiOpfbd26lczNzYmIqKKigtTV1WnevHkUExND4eHhdPjwYaE6pTobNmwgTU1N8vf3Z9oJVVVVoTq5vt/299AB+vTpQy1atKDg4GB68eIFdejQgRQVFUWORxF9H92MiCgtLY2MjY3p+fPnNer/2pCOa0nHtYjqN65VSfV6ry6GDx9OpqamdO7cOYqNjaXbt2/TqVOniEjyMa+q30Nt475fw3/W2B4edYO8FoP8r8whIqKeyxdQU69JNZSx4pJc2u3bm4KeHawh4/QFL6YR/nlPR4ovyae7OSlUUVFGT14eocupkZRSlEPrdznS35d/rRE/Mz+disuKak1jWXk5LT12iB69C2PcSssK6S+/EXTi3BS6cOM3SsvOotzCAiosKaY1p49TTMpH6rl8Ic35c4+QrPKKCtrw9ykKi/8gyFdpKZWVl9dZRq28p5KMew9h420JEWXVFsONiEDEfU0UlUmUSkRtiWhW1UwTUQcimiccs7y8nE6cOEqhoa9rT9Diz3E9iWgAEfFIYESv7F+/IOJ34RPPiUdB9x8I3A4RURciGim4LC0merCZKGPL5zipJDDWr/5ym6x8ooINW4n69iSKiqLXXtfo4ohNzLuRHhtL++fMpXEGJrR9hAcdvM4nv8DPkdetJurbk+Z5T6NJk8YQj3eJiMop/cMHGg0Orenaq/b8fSNp2dkkP6g39fZZ9N3u8d2o4BLFpRFlC5S2jx+LyK3bdeJFJVPhu2TS1/en06fjf3Aipfwvcj1tPw16LEMhubfFB64LHo8oJoUoMUPwf0kZ41Veu3203oy81pgGPGLTifuXiIioqKiCQkOFBxPt7S8T4Efz578iC4sLdPq0cOchPr6QFBVP088/P234BNbC92q/uXyiNmk1De1VDe5t0wThGpKnT58SADp37pzYsHUpXfr6+kKdkrCwMLKysiI2m01sNpvs7OwoPr7uOs7Hx4dkZGQoOTmZcbt27Rqx2WxKTU0lIiIjIyNau3atULw2bdrQ9OnTiYho5syZ1LVr11oHnqp2SmrrLFVX/t3d3WnixInM9f79+8nIyIhRkrt161ZjssKxY8fI0NCwzvyKw8vLi4YMGVJrulxdXYU65URECxcupMaNGzPX5ubmNGbMGOaaz+eTnp4e7d27t9b7btq0iRwdHetMm6enJ2lpaTEGZiKivXv3koqKCvF4PCotLSUlJSV6/PixULxJkybRqFGjiEjywd3MzEwCQGFhYbWGcXV1pY4dOzLXXC6XlJWVaezYsYxbamoqAaDg4GAiEnTGevbsKSQnKSmJ6SjVV+5vv/1GdnZ2Qs9l9+7dTNlUym3VqlWNfDRp0kSoQ+jm5iax4UFSY7uzszN5eHiI9EtISCAZGRn6+FHYAtmtWzdavHgxEUmN7VL+d+DxiQ5er9vYfvCGIFxDIkn9R0Skrq5Ovr6+QmGqu4mrp/Lz84nD4TDGrurU1s6Ja0sr423btk1sfgEIDXoHBwcTAPrrr78Yt5MnT5KCggJzLUm7WR+5HTp0oClTpgjJHTZsGPXt21dI7q+/Co9bfPz4kWRkZOjpU4E+WV5eTjo6Ooyhrjrp6ekEgLZs2SLSvyp1GRPbtWtHffr0Ya6TkpLI0dGRWCwWycjIkKGhIb169apO+b6+vgSAnjx5wrhFREQQACY/4spl8+bNZGtrS+W1jJ3UZQSspHpb4O3tTV27dmWub9y4QRwOh2nzJ02aVGNA/OHDh8Rms6mkpNqqha+gug4jythel/5CVLPtJxJ8HwsXLqz1vmfPniVtbe060yaJnmtlZSU0mE4kqAecnZ2JqPZvujo8Ho9UVVXp0qVLdYYjklwfE1ffHDt2rIb+U1ZWRoqKinTjhmBRwbca22vLv6TlVr1O8/T0JHNzc6GBbzs7O+rUqRNzXan7nTx5UmQaKsuvqgHjypUrBKDOd7lp06a0c+dO5rqu76ykpIQ0NTWFjBUODg51GkCcnZ2ZOr2Sdu3a1WpsJxI25tXm9jU6/vnz5+sVr66yrE3vFKcHi6sbiAR1kJqampDhlEjwfu3fv5+IJCvXfxs8HpeW/G4iwtD+xeC+ZL0p8Xi1L8irLw1Rn1bve2zdupWsrKyY68jISAJAERGCRWCS9PGqU5thS1xfWpJvs7qMyr7jsmXLGLdKHaeyLRBnbM/KyiIAjBFcEgwNDWnjxo3MdUVFBZmYmDB1QH2/bVHp/VYdoPKZPnv2ZbFNpW5T23jU99DN+Hw+9e7dm1avFhhUvsbYLh3X+oJ0XEuAJONalUhqbK/8Vm7duiXSX9Ixr4Y2tv9nt5G/UfAJaqbOaNlsKABAmaMIJUVFZHHLUFZehLXbmuHMxRkoKs6Cf2k5fs9KqbFFg3uv9Zj98yMUtZmJANMemBH7DF3DbmLbnTWws+6OPnpW0JSRQUZmJF6FnQWX+2WbhYLSfFwNOY/r7+8hvlT0llrycnJYPWYCXJo0Y9zyC9Lw+u1ZvA47izsPN0FDSR7qyiq4+uIZlh73xb7rl3Bj5XpsnjRNSJacrCwWDBmBZuaNEBL/AstPb4TTnGlY4XcE5bVsG+G/yAfBm3ZArerZ64sB/gBCbLhgb8EyPg8dQq7i19hnAH4H8Ccg4w/Y6AE6wcBgAP2qCFUB0AFAG+F7ycnJYfTosXBwaCkyLQCAVgDaQrCrvT8EhxxwAGh+9ncEytaUYq/FDtx7+HlbkwkAnAE0FVym5AEvrYB33T/HMQBwQ5AvACASHMVc0bUD9jg0Rwyfh5a7esPt1DywPm/5fG3bLtzfsgs//7ERXscPY3x3FoZ3+izvFy9g7XpMnOqF6dMbgc12A9FfyEYR4uz4yG/RAGeC5AEQ8cg0VVQwopMrBrZ3qen5b6eoDODygIJiAICqqhzyubK4/qoEyubaSEsbjOHDzX9wIqX8L6IlbwRDBRuoyoo6JqMOSsqB0ipbJrJY4KrI4q+ilXicEwAofDk/uK7j2+vL0JKruDl4O0pjGgMA5s17jRYtruPZsywmzJEj7fDzz1ZYsaIZ3rzpA9WCndg/1wUV5YKt2szNlZGePgh797YReY//JZ6VA6n82v0JQApfEK4hqd7uf4ucyjakpKQEkyZNgouLC548eYKgoCA0a9YM/fr1Q0mJYD/8ynO9VFRU8MsvvzByzMzMYGxszFw7OzuDz+cjMjIS+fn5SElJgYuLcBvg4uKCiIgIAIKtskJCQmBnZ4dZs2bh5s2b35w3Dw8P+Pv7o6ysDABw4sQJjBw5Emy2QIUMDQ3FqlWrhPI0ZcoUpKamori4WOL77N69G46OjtDV1YWKigoOHDiAxMTEOuO0b9+eKXdAUF7R0dHMOZwA4ODgwPxfuRVVRkYG43b69Gm4uLgwW1MtXbqUuW9iYqJQvtat+3JkRIsWLaCkpCR078LCQiQlJSEmJgbFxcXo0aOHUPyjR4+K3RI+Ojoao0aNgqWlJdTU1Jjt8sSVRdV8ysjIQFtbG82bfzmeRl9fHwCYvIeGhuLevXtC6bO3twcAoTR+rdyIiAg4OzsLPRcXFxcUFhYiOTmZcXN0dKyRh8mTJzNblaanp+PatWtC27o1BCEhIejWrZtIv7CwMPB4PNja2gqVy/3798U+NylS/m18zAIKxezsWlgiCNeQfEv9Vx1x9VRERATKyspq/aZFIUlbWomTk5NEMqvWk5V1YvV6srS0VHCcGiRvN79WbkRERL3yZWRkhH79+uHQoUMABEdtlJWVYdiwYSLz+z10JyKCl5cX9PT08PDhQzx79gwDBw6Em5sbc4Zj06ZNmfLq06cPI0dWVhZt2nzRhe3t7aGhocHkW1y5DBs2DCUlJbC0tMSUKVMQEBDwVVuGisLDwwOBgYFISRGMqZw4cQL9+vVjtgIODQ3F4cOHhd6BXr16gc/nIy4uTuL71KXD1EZd+kslVd89ADA0NBTSnW7fvo1u3brB2NgYqqqqGDt2LLKyspj3tz56blFREWJjYzFp0iSh+GvWrBFbd6Snp2PKlCmwsbGBuro61NTUUFhYKLYsvgZx9U1oaChiYmKgqqrKpF1LSwulpaXfVYf4mnITVac1bdqU0ekBQb1StZ6p1P2qPn9RVH1nDA0NAXzRDQsLCzFv3jw0btwYGhoaUFFRQUREhMTPR0FBAWPHjmXqqFevXuHt27fMVrWiiIiIQLt27YTcnJ2dJbpfXXxNG1e1vL8mXl1lKSn1qRtCQ0NRWFgIbW1toTTGxcUxafxe5fo9iYl/iNz85DpCEHLzkhAT//C73P9b69PqjBw5EvHx8cxxdydOnEDr1q0Z/UjSPl590l+9Ly3ptymJPgNI/p5raWlh/Pjx6NWrF9zc3LB9+3ZGVxDVf8/Ly0NqaqrQuysrK1vvb1ScfvitOkBERARkZWWF+suVuk1tfA/dbOfOnSgoKMDixYtrDS8d16qJdFxLQH3Htb6GkJAQyMjIwNXVVaR/Q9eHkvIdTAj/Dh7dWQmDnChoqQvOY98/dQymJ0fB5OlZhDXvjpKyPJSWFUBHyxKZTl6ILC1CMZ8LZRk5RgaHowIrCxfsMGmLuWWFyKooAzsjDDEP12PNk+2wNO+A6eOvoZGZMyJj72Lt9mZYPicSLBYLyvIqaGzcHL9kpyH85XlktBsBVVm52pLLoKttheVzosDn88DllYHDUcGZR4Hw2rcTmsoqyMjNxeIjf6KVlTWGd+wsUkZ6firsTHVx9ekHrDx1DL1at4GzfZMa4RoZGKKRgaGwYxvg3rvXGLJsJTJO/A2uHPChtAD68goQWMKbAjgPoCMgawwsrCZUAcAmsdkUzbDPvzpQ6KAId7PBUFZW/eL45ZgsWBQDQzUAHTsgIw8gPqCv+cX/9QfgwVuguZ42XqSnQvPVc1jb2Qvdo9ecWSjX14KDWz/IyAo+kcTEBGzduhFDh46Ag0MrqObloHHj8bh/PwUnTgTj5+mtYNCnHZx6961n5j/zCcBAAJ0gmNtQBXk5ORydvejb5P8DpKEAG3Af/WCP7rAWOKoqgFcqDxk1NcGlqhwCAyUfGJMipTbaaPZHG83+4gNWJyVLcKa6peCsX7BYyNYoxuUPe5HMj0UH7SH1T9TzOwCfC7TrVWuQIYMs0PmnKdDW5gAABgwwRm5uBWxsvtRtbdvqID29DI6ON/HhQwF+n56O0rRo8LkVgLwCAMG39F8gvQ5De33CSYqNjY3Ic8++hqysLGRmZjJnRfn5+SE+Ph7BwcGM4u7n5wdNTU1cuHABI0eOZM45BAC1z/ViQ9C6dWvExcXh2rVruH37NoYPH47u3bsLnTX2tbi5uYGIcOXKFbRp0wYPHz7E1q1bGf/CwkKsXLkSgwcPrhFXQUFBonucOnUK8+bNw+bNm+Hs7AxVVVVs2rQJT58+rXe6K5GTE/5GWCwWc1ZXcHAwPDw8sHLlSvTq1Qvq6uo4deoUNm/eDEBggKj6rCrP9RRH5Tl7V65cEepkAgCHw6kzrpubG8zNzXHw4EHmXLFmzZrVOE9VknxWdavsvFXmvbCwEG5ubtiwYUMNWZUDe/WRKynKyso13MaNG4dFixYhODgYjx8/RqNGjdCpUycRseuPoqJirX6FhYWQkZHBy5cvISMjI+RX2xlhUqT8WymS8AhVScNJyrfUf6Jk1VVPffjwof4JlQBR9ZQoRNWJ4upfSdrNr5UrKaLyNXnyZIwdOxZbt26Fr68vRowYITTwVhVdXV1oaGh8k+7E4/EQHR3NGMnv3r2Ly5cvIycnh9GL9uzZg1u3buHIkSNYtGgRrl69ypw9WVdd/rWYmpoiMjISt2/fxq1btzB9+nRs2rQJ9+/fr9EGSkqbNm1gZWWFU6dOYdq0aQgICGDORAYE78DUqVOFzoavxMzMTKJ7iNNhvoW6dKf4+Hj0798f06ZNw9q1a6GlpYVHjx5h0qRJKC8vh5KSUr303Mq64+DBgzWMedXb5Op4enoiKysL27dvh7m5OTgcDpydncXqTl+DuHeusLAQjo6OIs/V1dXVbbB0iLovIFm5ifr2xel5lW7i6pm66qZ58+bh1q1b+OOPP2BtbQ1FRUUMHTr0q57P5MmT0bJlSyQnJ8PX1xddu3aFufk/v1jja9q4quX9NfG+tZ6vb91QWFgIQ0NDBAYG1vCry8j3bye/ILVBw30t31qfVsfAwABdu3aFn58f2rdvDz8/P0yb9mUxnqR9vIZIPyDZt/m1+gybza5hPK5+9rSvry9mzZqF69ev4/Tp01i6dClu3boFJyen795/F6cffqsOEBUVJVGaq/K9dLPg4OAa+XdycoKHhweOHDkiHdeqhnRc6wv1Hdf6GiTRzRqyPpSU/6yxfVzfP5CX9gZbD3SEmXEbxCY8RJ5+G7i2mQkDZR2sWfhl5u615r2Qx60QMrRXRVVWDk1lNBBRnAe3lEcIJR4M9BpDT8cOCaWFOOc4G50hA3VeKVgsFrjccvD4FWhj6YzxnAi8K87FsYxYmHGU0V/btIb8m/fXQ4Yth26d5gIAkjga+D0pDBsbOSK/uAgTtm9CcVkZ2CwWjt27DbCADvZNGGP7mUeBmHdoP84vWYXWVjbo1rQPuHwu+jgMxbOo9yIN7QL4ECwfr8JoIEItEb7350O+sxzk9wPJ7YZBBqwqgQZ+/v0YTExq74Cy5gEmqQAeAkeDgQou4JUPRJ95gvV33TBknx+MzXpAR13w6seV83AkswBDFNlQURE0mOEfohEcGwGToAfo00dgxMvMzEBJSTHKy8tx8OAevHsXhk2btoPDmQhVVT/oaenj3NYGmAmpAsEK/2biAn4feHzB6n/ZuvuzdUIg8D//KgnK8cfmD6OxyO4c2iq6AQDKynjgcL7hRlL+XxNfFAYWiwVzpXp+LLrqAmN7FfQ45tjU/Bl0ODXraYaCXODpDaBJG8DIUuB292+AzwO6jxBcZ6cBvC8rYjIzS7FwYQimTrUGEXDmTCJWr3ZgDO0A0Lu3EXr3NgIAZGWVISWlBM2ba+Ds2US8f5+PZs3U4bFoP7S1ZCAr92XV/X8FfQn32ZE0nKRoaWmhV69e2L17N2bNmlWj45Sbmyt2cGH79u1gs9kYOHAgAKC4uBhsNltoZmrldaUybG1tLVJWYmIiUlJSYGQkeBeePHkCNpsNOzs7qKmpwcjICEFBQUIzN4OCgtC2bVvmWk1NDSNGjMCIESMwdOhQ9O7dG9nZ2TUUanl5wXtUdbasKBQUFDB48GCcOHECMTExsLOzQ+vWrRn/1q1bIzIystY8SUJQUBA6dOiA6dOnM26SzDSt3ml58uQJbGxsxA7KVvL48WOYm5tjyZIljFtCQgLzv6ysbK35Cg0NRUlJCaPgP3nyBCoqKjA1NYWWlhY4HA4SExNrnWUrqvyzsrIQGRmJgwcPMkbmR48eSZSXr6V169bw9/eHhYUFZGUbrjvQuHFj+Pv7C82KDwoKgqqqKkxMTOqMq62tjYEDB8LX1xfBwcGYMGFCg6WrEgcHB9y5c0ek7FatWoHH4yEjI6PBjfxSpPzTKEs2JiRxOElp0qSJ2PpPUsTVUzY2NlBUVMSdO3cwefLkGv6i6llJ29LvSUO0m6Jo3LgxgoKC4OnpybgFBQWhSZPaxgK+0LdvXygrK2Pv3r24fv06Hjx4UGtYNpuNkSNH4tixY/Dx8WF0lkoKCwuhoKBQZ9ty5MgR5OTkYMgQweTWyhVDVVfYVl5X6k61Gda4XC5evHjBPL/IyEjk5uaicWPB7lGSlIuioiLc3Nzg5uYGLy8v2NvbIywsTEjfqUROTk6s7gQIVlCdOHECJiYmYLPZ6Nfvy3aArVu3Rnh4+De9A+J0mNqoS3+RhJcvX4LP52Pz5s3M8zpz5oxQmProufr6+jAyMsKHDx/g4eEhMn5tumtQUBD27NmDvn0FCx+SkpLw6dMnifIjKeLqm9atW+P06dPQ09NrUINDVUTlX5Jy+9EEBQVh/PjxGDRoEABBHREfH/9VMpo3bw4nJyccPHgQfn5+2LVrV53hGzdujKdPn2LcuHGMW+VK4G+hvm1cQ7WN8vLyYusfSeoGUXJat26NtLQ0yMrKMisQq/O9yvV7oqYqmUFF0nANiST1qSg8PDywYMECjBo1Ch8+fMDIkSMZv/r08SR5r2rja79NSdDV1UVaWppQf7KqobCSVq1aoVWrVli8eDGcnZ2ZCQii2iBDQ0M8ffoUP/30EwCB7vDy5UumnW9I/RX4Nh3A3t6eSV+l4btSt6mN76Gb7dixA2vWrGH8U1JS0KtXL5w+fZqZ3CUd1xJGOq4l4J8a12revDn4fD7u37+P7t271/D/XmNe4vjPGtsHNHVDhV1PbA7/GwoKaijvuBTWxMee5j1qhDXmKMNYzET7A2lR+CXmCaZq2qGFbR80MuuA5JRXiC7Kwb38DLh2+x3e5i0BADv+6orMrBisWZiEmcaNUcSrgNrjk7BTVGOM7bde3MNvBxfCZ8RIPAjaBDk5BcbYfic3FX9/SoBRbAZK4pPR1sYe7WztMa3PAGQV5iP5UyaamzdCYUkJQuNj8SwqEum5uSj5vBWGrIwsZGVkYaytgEHOHWvJUTYAOwj2gD8s5DOj/0Bk8HJwJjIQQzk/QZb1P3TaQEcAJwGcAzq2FxiPcRhgxbEhKycPDVY2+nYEuFxjuLsPxt+tumMvVxUvThzAzqk/AwDatGmPwsICdOggKLu4uO7Ys0cPXbv2QmFhIfT1DaCrqwc1NXW0b98B7dt3aLj0KwDY2XDiJCHl5hvEn3wMp23jEPBGCQXFwMSeAJslPq4oDKGG7XATclOW0YA2xwTKsoJt9g8disWUKc9x/KYuWrVVgr3qv3vrKSn/PpaFdwHAwrE2mV8V736mH3bHTsayxlfQXK1LDX9rlZpbGwtRWgTkZAD5OUCl/lpeChTkAAmRgLndF6P7Z54/z4avbxx0dRWQnV2OP/+MxaBBJujUSa+G+ODgT/D2fomXL3MQH++GSZMs4eCggXnzGn9VPv/XaCsPGLKBND4gagMsFgT+bb/DPIPdu3fDxcUFbdu2xapVq+Dg4AAul4tbt25h7969QtuvFhQUIC0tDRUVFYiLi8Px48fx559/4vfff2eU1x49emD+/Pnw8vLCzJkzwefzsX79esjKyqJLl5rvXFUUFBTg6emJP/74A/n5+Zg1axaGDx8OAwPBDgzz58+Hj48PrKys0LJlS/j6+iIkJIRZRbNlyxYYGhqiVatWYLPZOHv2LAwMDEROGNDT04OioiKuX78OExMTKCgoQF1d9FEoHh4e6N+/P969e4cxY8YI+S1fvhz9+/eHmZkZhg4dCjabjdDQULx9+1aoc1YXNjY2OHr0KG7cuIFGjRrh2LFjeP78ObNbQG0kJiZizpw5mDp1Kl69eoWdO3d+1YouGxsbJCYm4tSpU2jTpg2uXLmCgIAAieKWl5dj0qRJWLp0KeLj4+Hj44MZM2aAzWZDVVUV8+bNw+zZs8Hn89GxY0fk5eUhKCgIampq8PT0hLm5OVgsFi5fvoy+fftCUVERmpqa0NbWxoEDB2BoaIjExEQsWvR9drTx8vLCwYMHMWrUKCxYsABaWlqIiYnBqVOn8Oeff0rcsavO9OnTsW3bNsycORMzZsxAZGQkfHx8MGfOnBpGFFFMnjwZ/fv3B4/HEzKMNBQ+Pj7o1q0brKysMHLkSHC5XFy9ehULFy6Era0tPDw8MG7cOGzevBmtWrVCZmYm7ty5AwcHB6FBEilS/u0YawMqCnVvJa+iKAjXkEhS/0mKuHpKQUEBCxcuxIIFCyAvLw8XFxdkZmbi3bt3mDRpUq3tnLi29HvTEO2mKObPn4/hw4ejVatW6N69Oy5duoRz587h9u3bYuPKyMhg/PjxWLx4MWxsbMRuC7x27VoEBgaiXbt2WLt2LZycnCAnJ4eHDx/i999/x/Pnzxndo7i4GGlpaeByuUhOTkZAQAC2bt2KadOmMXqRs7MzNDU14enpieXLl0NRUREHDx5EXFyc2LpXTk4OM2fOxI4dOyArK4sZM2agffv2zICtuHI5fPgweDwe2rVrByUlJRw/fhyKioq1GvctLCxw584duLi4gMPhQFNTU2Q4Dw8PrFixAmvXrsXQoUOFVgAtXLgQ7du3x4wZMzB58mQoKysjPDwct27dkthQUV8dpi79RRKsra1RUVGBnTt3ws3NDUFBQdi3b59EccXpuStXrsSsWbOgrq6O3r17o6ysDC9evEBOTg7mzJlT6zdtY2ODY8eOwcnJCfn5+Zg/f36D7n5Qmfa66hsPDw9s2rQJ7u7uWLVqFUxMTJCQkIBz585hwYIFYiccSkJt+RdXbj8aGxsbnDt3Dm5ubmCxWFi2bNlX78gBCHTEGTNmQFlZmTHc14a3tzfGjx8PJycnuLi44MSJE3j37h0sLS3rmw0A9W/jGqpttLCwQFxcHEJCQmBiYgJVVdUaqwslqRtEyenevTucnZ0xcOBAbNy4Eba2tkhJScGVK1cwaNAgODk5fbdy/Z5YW3SChpoJcvM/oraRBg11E1hb/PMTbetbnw4ePBjTpk1j2tGqhtX69PEsLCxQWFiIO3fuMFtK17a7jSi+5tuUhM6dOyMzMxMbN27E0KFDcf36dVy7do2ZyBQXF4cDBw5gwIABMDIyQmRkJKKjo4UmgVTH29sb69evh42NDezt7bFlyxYh43VD6q/At+kAdnZ26N27N6ZOnYq9e/dCVlYWv/76q9h2raF1s+o77VTu9GZlZSW2TZOOa0nHtf6JcS0LCwt4enpi4sSJ2LFjB1q0aIGEhARkZGRg+PDh323MSyzfdOJ7PcnLyyMAlJeX16Byy8qL6X7wbsovSCciooe5aZRZXkJERKZPz5LSo+NC4a+/fEbvkxKJiKi4pO60vC7IIvsrq2nkWiO6cnsF7fbtTbOXK1FhURbFlxQQj89nwp695E37j7oTv4rblfRoepKVyFy7rVlOcOtGM3fNpYxP0ZSZFcv4cfk8ep6fSX1XLia2ew9KyEhj/O6EvBLE27+Tuvw2l9gDuhNrQHdKz8n+ytLKJ6IWRLSQ8ooKqf+qJeT7hy/lRiQTEZHX3h0Et2507cXTOqWUlBV/5X2rwSOii0SUXI+4AUT0ZzW3WCLyJKJZn/9PJqJjRJ9iMikr61MNEW9LeTT5bjBdvX6llpvkU34+h3bscKUnT4Jo0qQx5OOzuB6J/T6c8J9MWw+4Eo/Hq7eM4CkH6BhGUebTaLoTQnQ+mKjKqyuaVZeIHFcRhSSKCSiay5eTycbmEo17bEZDguWJx69/+qX8/+Rq6h66mrqn9gB8PhG35nsV/OkcjX9uSBH5QfW/eVmJ8HVKPNGZnUSXDgnuGxtGlJfFeJ87l0gHDkRTUVEFffpUSufOJdLgwQ/ozJmEGqJNTM4Ti+VHHM4pmjAhmOztLxPgRzNnvqBGjS5QXFwB5eSU0alT8VRR8c9/N9+r/SYiulpMZJoi+JlU+VW6Xf3G5qYuUlJSyMvLi8zNzUleXp6MjY1pwIABdO/ePSaMubk5QdBDJ3l5eTIzM6Phw4fT3bt3a8i7efMmubi4kLq6OmlqalLXrl0pODi4zjT4+PhQixYtaM+ePWRkZEQKCgo0dOhQys7+0r7zeDxasWIFGRsbk5ycHLVo0YKuXbvG+B84cIBatmxJysrKpKamRt26daNXr14x/gAoICCAuT548CCZmpoSm80mV1dXIiLy9PQkd3d3obTxeDwyNDQkABQbG0vVuX79OnXo0IEUFRVJTU2N2rZtSwcOHGD8PT09GfmiKC0tpfHjx5O6ujppaGjQtGnTaNGiRdSiRQshGVXT5erqStOnT6dffvmF1NTUSFNTk3777Tch3cvc3Jy2bt0qdK8WLVqQj48Pcz1//nzS1tYmFRUVGjFiBG3dupXU1dVrTWvVtCxfvpyJO2XKFCotLWXC8Pl82rZtG9nZ2ZGcnBzp6upSr1696P79+0yYVatWkYGBAbFYLPL09CQiolu3blHjxo2Jw+GQg4MDBQYG1nhu1XF1dSVvb28hN1F5ry4nKiqKBg0aRBoaGqSoqEj29vb066+/MmVYX7mBgYHUpk0bkpeXJwMDA1q4cCFVVFTUmd5K+Hw+mZubU9++fWvNryjElVFV/P39qWXLliQvL086Ojo0ePBgxq+8vJyWL19OFhYWJCcnR4aGhjRo0CB68+YNERH5+voKvR+V360UKf9Goj8SbT1f+y/64/e5ryT1n7q6Ovn6+grFE+Umrp7i8Xi0Zs0aMjc3Jzk5OTIzM6N169Yx8UW1c+La0ri4OAJAr1+/FpvX6nWPqLj37t0jAJSTk8O4iWs36yt3z549ZGlpSXJycmRra0tHjx6tM71ViY2NJQC0ceNGsfkmIsrNzaVFixaRjY0NycvLk76+PnXv3p0CAgKE2pGqupOhoSH179+fzp07V0Pe8+fPqWfPnqSlpUWqqqrUvn17unr1ap1pqKyT/f39ydLSkjgcDnXv3p0SEoR17LrKJSAggNq1a0dqamqkrKxM7du3p9u3bzP+1du9ixcvkrW1NcnKypK5uTkR1d4WtG3blgCI1BWfPXtGPXr0IBUVFVJWViYHBwdau3Yt4+/j48PIrw1xOkz1dEmiv4hqo93d3Rk9hYhoy5YtZGhoSIqKitSrVy86evRojXexOpLouUREJ06cYNpoTU1N+umnn4TeF1Hf9KtXr8jJyYkUFBTIxsaGzp49K1JfEYWo76g2xNU3qampNG7cONLR0SEOh0OWlpY0ZcoUpt8kSpetWtaSPHNR+Sequ9xqq9NE6fzidL/qskSV3+vXrwkAxcXFMXG6dOlCioqKZGpqSrt27apxn+rPS1RdVVBQQEpKSjR9+vQ6y6iStWvXko6ODqmoqJCnpyctWLCgzr7F1q1ba5S/KDdxbVxt71R94lUvy9LSUhoyZAhpaGgQAKbNrF5e4uqG2uTk5+fTzJkzycjIiOTk5MjU1JQ8PDwoMfHLuJ+4cv038jrMn7wWsz7/UOUncHsd5v9d7tsQ9Wn1vkclw4cPJwB06NChGn7idCdR/PLLL6StrU0AmL6yJH1porq/TUn6jqLqqL1795KpqSkpKyvTuHHjaO3atcy3mJaWRgMHDiRDQ0OSl5cnc3NzWr58eZ3j4hUVFeTt7U1qamqkoaFBc+bMoXHjxgnVAfX9tr+HDpCamkr9+vUjDodDZmZmdPToUYnatYbWzaoiqX4sHdeSjmsR1W9cq5La6j1RlJSU0OzZs5n6wNraWqhe/NoxL0n1x7pgEVU7COMfID8/H+rq6sjLy2vQLZaeh5zAkTNj0LPzbzDvMBctX1/CCB0LnGrsiojiXJTx+WipIthuIjU7C0bjR6CVhTF2jumIUxemYmj/HXB1nsHIy85JwJ1Hm9Gt0zxoaZhh/1F3hMfdh+mw05hl8xNS0t4i4OocdHddiOb2X84M5vG4uPd4Gxpb94SxoQMAYOkGU8jLKWH5nEgAwOY7bzDvzC2cnTYMQ1uaoayiHJvOncGAth3g0EgwKzC7IB/hiQno2LQ5I9tg3DAUlpTgyK/zkFceg/CETOiqNMLCoV+2jREHEaHZjMkw1tbBzVUbEJuaglaTJ2L3NS1otTBHv9e/41FsJK4HP8bioSOhrCB69lRyVgLuht9AO6uOOFZeiuSyYiw3awFLRVXhgMcAHAfwF4Dqk59CAEwB0BvAagkzUALB6vWLADIB3IfwHg1XAKwAMBNAKoC/gVltfoGcohw2b67PsvFjAAwBdMeHD7FQUVGFnl7NFak/gp2HeiDjUzRWzI2GTC3HIIijorAU+ZEp0Hb8itmo3f4AsopQtG4g2I4WUNRXR07QQ0QtnocmO/dDtUVLicQ8/HQKhdwc9DGYJj6wlP+/cHlff7ZBZh6QVwSoKQJ6olecNCihjwB5DqBvBtw5AxhbAR36IienHFpa/mjRXA0hz7sCHEW8fZsLB4drmDDBEn/9JXy23sWLyTh5MgHXr6ciN7cCgwaZYMAAY7x6lYPdu6Ogq8uBq6sezpxJgq9vO4wf/8/OIv9e7Xcl10oAn3wgtcpiByM2sEIN6NOwC1T+daxYsQLnz58XuUXa/zqurq7o0qULVqxY0WAyO3fujJYtW2Lbtm0NJlPKj6ewsBDGxsbw9fUVeV6aFClSvo6YFCAwTHiFu4oi0LkZYG1Uezwp//94+PAhunXrhqSkJOjr6//o5EjE4cOH8euvv9a5ter/Kp6enmCxWELnvH4r48ePR25uLs6fP99gMqU0HN/jmf+XiI+Ph5WVFZ4/fy7yiAcpUuoi5O05/H3ZG7n5yYybhrophvbbhpbNpH2Ob0H6bUqpinRc6+uQjmv99/hPbSMfGXsHWhoWcGnzM5SV1OFt1Bj9tUxQXlGCM3vbQE3VCLd5ZZg46gwMtcywbsw4PHk0G3eDnsFIvzm0NYW3dXgTcQH3g3dCV9saejq2mDDyJJSengEvKw19zcsgzy3Bh8QgJKe8FjK2J3x8jvPX5iOx+QuoKOvA0rwjmtj2gZzsl0PxuupHI2CMPga2FGzLsfftMywLuoHYtFT4es8HADyNfIc5Oyfjl4Gz4T1IcC7UwPYuUFFQRP+27XH+RSK6tnDAq6gc+AXewU/NHGCio4u0nGyoKSlBiSP6ED4+nw9VRUWoft6CxMrQCBFHjyPbNxiadkaIKs5D19RnmNTOvlZDOwAoK6hCW0UXHAUVbPzwAhVEIABH7GpuXX+qcRyMS5TQCdU67s0A/Aqgfa23qUkwgL0ArCGwgYdBcM55JX0A6ANoASBLEK4rqztk5L687hER7yAnJw9raxuBQzYERv8+AKocwZWXl4vlyx/D2dkFI0cClpZWX5HQ+lNSXgJZGVnIiTGgjxhyDDfCLiEqLRKNjet3drWcisLXGdoB4KAnXiSGY8nOZZiw0g4jn25CReAbICwZxdHRtRvb+XygyhZ1nXQknyQi5f8pRaVAajagowZoqEger/J7r/j6LerqRYvP9R6PCzR3Zs5z19SUh+9fbdEo5R4QGAD0Go1mzTQQHd0fxsY1t+YaMMAEAwaYgIhw5UoKOnTQgZYWB5cuPYS8PBvp6WW4ezcdAHDqVMI/bmz/3vRRBHoqAM/KgXS+4Iz2tvKATD2PtZDy48nLy0NsbCyuXLnyo5Mi5V8Mn8/Hp0+fsHnzZmhoaGDAgAE/OklSpPwnsDYCLA2Bj1kClUpZQbB1fH2Pi5Ly36OsrAyZmZlYsWIFhg0b9j9jaP8vQ0QIDAz8LudbSvl3In3mtVNRUYGsrCwsXboU7du3lxrzpNSLls0Gw6GJO2LiHyK/IBVqqoawtugENvs7bSP8/wDptynl/xPScS0pkvKfMrbnF6SBT1yoqRogLzcBawwsoaKsg/KKErBZMigtzUNqxlsUFKZDS8MMi4ePw33TfOhqW6OJbe8a8lzaToWWpgVKSnKx53Af9Ou2Eo2zM2CZeBeb783BrgVxmDM3DmuS3kArIwrt9GwBAKaGrTF26FF8TA3F3aDNSE1/B+8p94Rkn700AwHvdXHofiQuLl2N38s+Qm5YD6xp0vdLoNIYdDMOR9mny6i0AO+b/ivjPbz9WHjt24G91y4BAEb91AU7f54Bs4mjoSAvh6h9R2CgqVUjX45zpgMA/BevYNyMtXVgPE9wznZWRSlc1PTgpKpTZ3lrKmuhXyvBeSxPWvbDX2nRGKJtjm0fw7E5+R3uO/SGpaIqCkZVYJTFAzTN18BbuAsLkQXgUedtapDrkIO7zW+ha24PaCRpApsA+FUJwAbg9Pl/AwBDgIEYKiRj69aNUFZWwdatuwUOXAC5AAqE78VisaGgoAB5+S8HBV+4GICIhAp07TUcbW2/Lu1MHt4lQ9FAHRxt1Rp+FbwKnH9xCprK2ujdou7BZnlZeagoqEFB/h9e8mmpi1MJ4bjZrhA+GnpI/OM4TC/nQbfpDLDWRQDsV8DgaopWaTmQ/AnQUhX8pEiRBDkZgCMHyH/lzg0ayoCaEsAC/P2TsGJFGM6e7Qh7+4ZfjS3Eq/tAwnvA2JpxGj/RCnidDCgIjOulpTxYWdX9DbBYLPTvb8xcGxgoolkzdQwdagZjY0WsWvUWbm7GdUj430WGBThzxIeT8r+Buro6kpOTxQeU8v+axMRENGrUCCYmJjh8+DBkZf9TXRQpUn4obBZgWne3Tsr/Y06ePIlJkyahZcuWOHr06I9OjhQI+gEJCQk/OhlS/kGkz7x2goKC0KVLF9ja2uLvv//+0cmR8j8Mmy0DW8vOPzoZ/xmk36aU/09Ix7WkSMp/aht5IgIRHxUVJVi0VhfGhi0wb9oTIf/ovGS4xbyAl741Zpk2Fynn2evj0NOxhYVpW0F6C9Jw7e4q/NR+BvjEw/rL80DZMdj86xv4pUZiYmIYuma8wjW39bgXtBW3H26CvXUP6GhZ4l7QVnhPuY9GZsJLt+OTnmLA+t0o4bIQvf8IDoZfB19GHlPtujJhuNxyBD7eDh6nMVwcukFFsaZBNS0nG9dfPkdCZjr6t2mP5uaN0GzmFMSnpyFizyFYGRohMTMdx+7dxqz+g6CqpAT3NcvAYrFwfsmqhih2AEAFnw+1YD9YcFQwTt8K65PCcMimA5YlhEBRRgY/G9iimZImXNS/ffv19PQ0+PgsRnfXXhiqMhJoBMEK+c+8uXkLMrKyaNq1S60ynjwJgrw8B61bO31xLASQD6DKlopcLhdv3oSgeXMHyMkJDO7z5s1CfmEZ+o7fj4FfsyL/M8UpOQgwmwmDbk3R7cbiGv584iMoMhAaSppobtZKhITvC+/zQmAZtmj/gpg03On5O8wX9kJKRzVY/BGElxM18dM7TVjIGoD/91OkfHwGlRG9oLF0Esoz4yCv2wgo5wJp2YCmCqBac0WvFCnfi82bI7BwYSju3+8GFxfdBpUdlncPqaUx6Kk/ReAQF47SpDBs1z2NNtruCD7oBD09DqZMERjf373Lg6PjdSxY0BirVjkIybpwQaC4ubtXP2/j38P33kZeihQpUqRIkSJFihQpUqRIkSJFihQpUqRI+V/iP7VshMVigcWSgZycEpydJkFf176mP0cdGQUZiL4yEb52fTBhpJ9QmLz8VBw9OxYWpu0YQ72aqgFGuO9hwuycfAMAwONVIPfmPIySUYZK3G2c5OXgecgxcORVoK3VCO6918PctG2N7ekBwMK0HV7tcPo8QYDw9uQAqKkYAAsTmTCysvJQ0OmNTotmY2qvKOzzmiMko7gkF9k5cejZyhFG2l+WK0TtO4ybr18gIvUFSnkW8Lv3AuvO+qGRvgFGu3bDhaW1H47OJUC2HtsKyrHZWGjSDIbyiphqaIfFps3hmxaNiJI8sAC0VtFGGzEr5SVFX98AO3cegJyc6JWu2waPhJyCAvb1SUZWThZCZ79Ct249hcK0b++C8tJSJCXEw9DYRLCCahkQGxKNP9vsx9jx49GkSTM8fBiIY8d8MWKEB3r1Euw6sGTJSpSU8aFXT5udgq4qrKd0ga6LHQAg+fIrsNgsGPcVGNbZLDY62XetS8R3xS8Q4BPg2U20P6+0AiVpeZDP5aJbohpY78uQ+bgUGjO6A8qayAt/CYMUa7Auf0RO95NIOjAaMpzDKH5vhlYXO0JWtX5ny0uRUsmZ5DUIyb2F5Y2vQkFGWWz4uXMbY+pUa6ioNNy7d/9+BqZPf47mi/ah1PoK2msNhpqcNtCoCfxYfyE49QLAV8CaNYowM1NijO2qqrKwtlaFqWnNCSfjxj0BiwXk5g6t4SdFihQpUqRIkSJFihQpUqRIkSJFihQpUqRI+ffxnzK2V8JmszF8wC4ht/LyYvx1chisLVzx3mEwdj/XwMs3J8E1aY+Y10cwvvd6NLbpAXU1Q4wbdgxPXx/BiXOT4TH4T5H3eBNxERdvLEZBYTqcDVtBwa4fTAxb4EWoH5SVdTCw9wZ8SHiMP08MQdtW4zBu2BGh+HcebUFyymuMGeILFouFkQP3Q5GjDgAIj7qO6Lj76N99NTj8JDTWSIGlxkcERz+AY6P2kJcVrLA+cmYMll7OAldGB9knzkNGRnDWzPWXz9Bn5W/o17Yx5g8ZgNnuQ2Cpb4ghHTrVWmYvoiPhncNHnpk9Huix8DrsFX79cw98Z82Hk42dROW+wryl0PUEAxt0VjeAkows9Bt4m/MahvYrADYC2AlMP+4Ltqws6BofqSkf8fjxQ8bYnpOTjYoKLjIy0nDQcwoKWlijefMWmD17AeAKFMgUICMrDXl5KwB8QsuW55CamgpHxzbMrTQ1NaEJIDc3BxoamgAEZ9Vs2bIBjRpZYvjw0XWmnS0ni3Z7JzHXj0btAltOBsOzD357wTQAOupAXftdaDQzxdDMfcjxfQj57GKgRSP85NIebGVBWWhmqICvXAj22iFQMK6Asn1n5AfrIP9VDnhFPKmxXco3k1QcjvjiUJTzSyQytgNoOEN7YR4gz0FKSjHCw/MxQ2Y+HO2mCAztn5nXWxd8rAarmzbOnHFB06bqjJ+ZmTLevu0rSjLOnevYMGmUIkWKFClSpEiRIkWKFClSpEiRIkWKFClSpPwj/CeN7aKIjgtEZMwdJCQ/x/V7qzFh5GlcvLkIp3PToV6Sj7Epsfjb1BkWCipo09IDAdfmIj8/VUjG6QvTEZvwCFMn3EZ84hOkZURg+vhrsLfujmt3VyHg2jy0d5oEi0aC7ctNjVqjh+siODR2r5Ged+8vIy7pKdx6roWWhhlsLbvgwPGBKK8owss3p/Eu8go6OE2CvUUbzO/bEoY2bRGd9h6pCffQpc0kaKqbwNFhBLrGnkexjC3UR7njxsj1cLFrBicbO0zo1gufOM2wLlAW139Rw6SefUSWSxmfh+kxT/DxVRjeFqqguYEZ5KCMpE+ZeJsQj6ScHFzNBzrKA10Vvr7cGyl+OZf4afAznCxNx28u3aHX0GeMywCQF/x1Gvj5nPP+gOl1c/zmtwKIA7imXCxZMh+ysrIoLCxEoyY2KCA+IsJCUV5aCvmBCmg5sDX2lh/CqVPDkJIiiyFDtDB69FgAQF5eLk6ePI5u3XqgrKwMW7ZswPDho9G7dz8UFRUiISEeCgpfX0g/nfUGq7Y9238AfRwFf/kVXLDlvlQRwRP34yM3C829+6H8ehxMjj4DW5EDPFoEqFQ5YPngOLD3BQJzz0Dx8ERYLbgH4hF4xVypoV3K18PjAyyW4MDRz/xqcwwV/NLaDe0VPCAjB9BQAZTrUXHVRnkpcOM4oG2IUaMGo39/Y6iKeKftjC2RnpOF83vUYMBPwbp173D6tAvMzOqeGNCtm0HDpVWKFClSpEiRIkWKFClSpEiRIkWKFClSpEiR8t35Txrby8qLkJwaAitzF/B4XJy/vgCBj7dDT9cObRw8kJrxFo1teqKZfV/0KczCGlNnvMzPQlhRDiwUVPAu8hoKCjOgo2ULPp8PNltgCC0ty4eMshGuhJxHYvwTyLBlYWfVDWy2DHQbdYaS1VNcMe+FS8VleF+SDxNFNbj3+l0obQ/fheHis8dYMuIsNu9pie0HO0NmeADyM96iIiMcn7I/YNSgA/iUFQNdbcG2wxNG+iEmIwcXAv6ATMI6qMopoIfrQrRtNRZnW43FtZfP8CTqPdrssgP4gE6gOg55z8dPO24jPjsffCLIsPgAxgFoBi5vPq6GnIe+ugEMTFricHosejWxxBmuJnqaKoHFAsZ364XBzh3xSV4ZszKBOK5oY3vV8hHHyuvnca27HXRSo7DUvIWw5ycABKCurdk/AQgFEAegAsC0Kn69P/+qoZGtAUQAmZFACsnC2bkjWCwW2Gw2Bg4cii3jJiDy3n3kLk2BnqUlAMGq+RcvDCAvz8HHj5sxduxEaGpqIjExAc+eBUNHRwcdO7rC2toWhoZGWLt2BSoqylFaWoKOHX+SqCyqYtS7hfhA/zDPZvgi7ugjuEVsgpKxFgAg+UYoAs2T8Gb9B8xbuxrJ0elQ6tcanKqGdgBQlAdamAKtPgJ6gjOdC8IuI++lP4w8dkFGQeWfzo6UfzvZBUBZBWCgKTCsV8LnAwnpgLwcYPLlGAoZlgxk6lrRzuUCJeWAQjmgrICYwpdQl9ODLsf029IpJw9YNAY0BBVVpaG9ooKPfSceo08PC1ikROMvtyx4X7TCmeeOOH8+Gc+fZyMjo1SssV2KFClSpEiRIkWKFClSpEiRIkWKFClSpEiR8r/Ff9LYfvnWMtwL2opO7abD3qYH7gVthZ62Lfp29YGjwwihsFZUgRHJd/GL/SA8OuQKmdaeMDFsCQCIS3yEy7eXYUDPtXjy6gii5TTQqd8ypLz5G6gognvvDUjLjICxQXMcLeNht+0odM9Pg5msCqISX8PEzhUA8PflX/H2/WUsnPES+65fgt/9uxje0RVG+g4oLs3F7owY5HNl8HFpNjgcgSEyNy8Z7yKvQUPNGOoaNgiKTcXBCFssbL0OZQrt8Co3E1Yq6lBly8JCSxtZXXoD5a8Bk7Z4m5SAMA4Pl6b9BEWWDGTYbACFAC4BSAJhHsq5ZSjjlkG5nIe3jgNgKK8EDVl5vE9OhI6aOnTK1KGmqQw1NhCgBJhX2kfTAewH4AEkaybi3rsb6GjXBY30rMU+l98HjUTLolRMMxKxLb0nAC6AG3UI2AXBdvGaEBjmPxvb75UCs7K4aH5kJ9aXDYLZLxaA4ec4owH0Bu6+A+KCkjHVfQw01b6sRJ3z1wFkJ39kDO0AwGKxsGbNJly5cgG3bl1H+/YuaNGiFZo3b4Hly9fA2NgE165dBpvNhqWlNT59yoSysjJ++qkL7Owaiy2HfxtpOYLFv6pVNhtQMtaCciNdyCh8KSv38D9g+fQF1HQ1oWZrCNOl7rj80yo0+fgJjX+ttnNC18aC32dyn59FbvAx6PScA0VTh++dJSn/Y+QXpEKFqww2XwOQqWJsZ7EARQ4g/5VNlSIHMNcDZGVQUJGNBWHtYa3ihI3Ng+uMFhz8CNnZWbD+SR8AYKfaXjgAiw04dq0R78/LV7D91in4p2bhXtc50NdkwaWDDhwdtdDamo+V7UMho58FQLtGXClSpEiRIkWKFClSpEiRIkWKFClSpEiRIkXK/y7/SWN7q2ZDkZ0Tj4dP9+BTdixmT30Ebc1G0FAzqhH27fvLeBC0Fb3klFBckoNXYWfQsulg9PhpIW4/2IRnr46gQ5dluPhoG3LSw/C7WXcE9lwC9FyCu4+24vcdDhg/wg8zTNojJegPWKe/xBTnuXgbdBrpEScxauA+8HgV4PLKQETYOmkaJnTrhTY29gi8lYnEjy9wZ2Q7yCtqgsP5surx8OlR+JQdB4DwuNADMen5CN5wEG9jQuC2eztYkwdisI45nMJTcejIX4jiywDtUuDXtAAeXr8D3dti/aBRWGja/LNEFQDRAJQhJyOHoe084H1wN7pd3YjQ7QegYaaBrPw8OMz6Gc5mTXA/eAswEkAF4HQRwCkAJgBeQmCzNwPkB8lDmaMCjpxk2zS3aOmAFqjF0OoOgCdGwCgAxgD6QrBt/GdKARSx2LDkNoHZVQtAH8D0L/7+986gokIeUffO4iq7Jzw8PJGenoa9e3fCzW0gHB3bIPFNGNT19aCur4+0tFQ8e/YE7u6D0aqVIzZtWgctLS2sWbMRYWEhkJWVRUpKMpKSEgAAY8dOwK5dW9GsmQNUVL5sm/+/QFEpcPoBYKQNDKtyXHSzxe5otvjL8Qf8Ci74FVy0cGmLlBtvwG/GBfEJvJJyZNyPQOqNN+h0ZhbkVEUfD2A8Zjd0e839YmiPzwVepgI9LAE1jsg4Uv73yS5Lwa7I8Wiu3hWDzBeJDlOegl9SWqK5qiuWyVwT9mSxAEOt+t388xEIKrKaGGK8EGZKzcRGuXLlItLT01CseRWQ5eNE2+zaA/N5QPA1BCu/xdmS3Yj12wjVLoVgLe4J7XbACgBOTjcwoV0mvDrnA6Ul9cuHFClSpEiRIkWKFClSpEiRIkWKFClSpEiRIuVfy7/noOgGxNK8A6aMOYfxI05iSL9tsDJ3ETK0H/t7AnxPjQYAtG01DpNH+6On62LYWnVFWkY4ImPvwL33esye+hDjx16AzYsABLaegaYj/kY8j4t1iW8Q+i4AQc8PAgASPr6GGlsOa1xno6QkG+aaRsjMDEfixxfweP8ARwxcsHpBIpQUNaCnoYnuLQWHYo8bdgwzJt5GIw0TGHOEtxce5rYTvbssQ+sPQ+CqY4v+bdqhtakOerVyxGRnVziUqyPzfTna2zeFtVNbfFz8GzBrNpqbN4KrQ0t4tmiH0XqWuJubisf5GZ+l6kNgdBfQ2tIGlt06IohfAADQUFbBzz37wdO1B+AIFDYvALcRF7AFAhWBHD4EW7XvBeAB6KkbYHDbUTBSNQHmANkbgHvP6vnQfobwtvCisAMwBQKDe5WjjfsoAB+M2FizqBewDILV7J8pLy/HjRtXERH2GE5ObeHg0BIAkJ+fh6SkBGRkpCE3LQ1LWrfHrlHjAAB3797C+fN/IyzsDczMLKCkpIy8vDy8ffsGAQF/4/LlC/j5Zy9s2bILqqqqsLdvgt69+6Fx46aYPn0SLl0KqGch1E7K9VBcdfwNueHJDSpXiQM42QAtLYXdc98l43r75Ui7+w4Fsem41HQB/I1n4M1KfzwYsg1xxx9BzdYQw3P+hIySPFJuvYG/sRfO28xGyLKz4JVVCMmTUVSFolmV7fLTi4DkAiC/rEHzI+XfxceCcLwquo0jKb/hfcGXVeXbY8bjr/jZAABNOUOMMluJ/iaCa5RVAMmfBNvAAyAiPPx0CpllifVKA4vFgofZGnTSGYl3+Q+wOqI/5r5pi8zSJJTxioXCzpw5B0uWrMQUm22Y0mhH7UJzM4HX94GMj7DM00SP1m1w6LwBLh/zEAqmrS2Pwa0LBOfNW0t3dJDy42GxWDh//nydYcaPH4+BAwf+I+n5GuqTLgsLC2zbtu1fkRYp/w0OHz4MDQ0N5nrFihVo2bLlD0uPlJpI8n0GBgaCxWIhNzf3H0mTlO9L586d8euvv34X2eLazfj4eLBYLISEhNQapnpbJElb/P8FaZ0qRYoUKVKk1E71dvKf5Hv1pf8tNFSf/p/SXf7rz+NrkKQs/q06ZX3S9b36Ov/WMvonqV4PNERZ/yeN7ZU4tRgJAz17AEAFtwx8Pg9RHwIR/eEeEpIFVmFZWXm0bDYYZeUFCH13DoZ6TfFT+xkAgPRPkbh9bw16czhofcML+WF+yOWWIzLtLfaeGYuYgnToadtCQac5br+9Cg2dpvhjeT6yLLrCodtqJKe8QsWTbbC84IE7jzYz6SoqzkZ+QRr0de1gZ1VzS2IA0NdtDFfL6ZA/LY9+D2TgN28JZGRkYKStg7k9mkHmeSGeBeeihaU9rvqsg3FHV5QpK6HfqiVQkefgsKs7TDnK6PP2NoZGBNaQn8kDDjTviQ8tLeCTHg4AkJGRwYLJM/F3xz449XsxAjin8MThAR7u5mFsObCxAII3xgmAXBVh5QBCgfRAYNkuIKOOxaDfFXkAAwBoVHGSl4ePzxrMnbsQ06d7o3lzgcHXxsYOOzfuRx8ZN6ip66LnzOnoMmUiAKBfP3eMGzcRR478iQMHdmPDhq3YsGEruFzB0nslJSWw2WxwOArM9fDho2FsbAJlZWXGvSHJj0pF9usElHzMaVC5LBbg0gSwqbbpQ2F8Jj49jUH8qcdIvvQKBdFpUG6kAwuPjrD/tTdy3iQiLVDw3jj7/oJGHh3BLShFYUw63q4JQNaLD3XfuK0RMLElYKLWoPmR8u8gryITeRWZaK7THb+a/AVHtb54nx+Msc90EfDxD7zOvYnHWf7IKEsAi8XCIOP5aKXRUxC5gguUlgPlggkbkYXB2Bw9GscTl3xzuq6n7cfL3KuIK3qN40lL4PFMC3GFoQCAJ9nnESUTCAuLRuisOwaddccI5ymvHLt3RyE/vwJIiAQ+vAMcu0C/42Qstj+HCe5dYGysxIRPTCzCo0eZcJqviiSr3sJn0Uv515GWloaZM2fC0tISHA4HpqamcHNzw507d5gwFhYWYLFYYLFYUFRUhIWFBYYPH467d+/WkPf8+XN069YNGhoa0NTURK9evRAaGvpPZkkkqamp6NNHcOxHbQaC7du34/Dhw/984v6fITX2fRvjx49nvkdRPwsLix+dxDqJiYnBhAkTYGJiAg6Hg0aNGmHUqFF48eIFE6ZqfpSVlWFjY4Px48fj5cuXdcpVVVWtMSh3+PDhGmWkoCCsr3bu3FnIz9bWFr///juIqMZ9jhw5gjZt2kBJSQmqqqpwdXXF5cuXv61QGojqdZioDnOHDh2QmpoKdXX1fzZxUr6JH1FvVm03/80ypUiRIkWKFCn/PUaMGIGoqKjveo8fadD/LzBv3jyhcaMfSX5+PpYsWQJ7e3soKCjAwMAA3bt3x7lz55g+XdU+H4fDgbGxMdzc3HDu3Lka8qKiouDu7g4dHR2oqamhY8eOuHfv3j+drRo8f/4cP//8M3MtaiLrv+m5/JeRZOKxJFQdbxX1Gz9+fIOk95/gP21sr6S8ogQ+myyw72h/HDw+CEUl2Vji/RbJKSHg8bgAADVVA8yadBc/jz0PFosNHo+L99G3EP7+MraZNkUL+35wtnBBjvMojC1NwbUWv8DPdSM+5iYgMeYqtJW1cei4G37f2RL93t3B6qxU6GhZ49emfWFp3pE5Bx4ANu9zxqotdsy9q8LjVWD/MXfs85+K5zm30PnSPLTbN+mLP58H/8u/wqlgKm5OaIZbrx4zfjJsGZjq6MFYWwelFTyUc3k4bOuCvdbta94HQAEfmGDVCxebfDH4J5cUIpwLXE4uxptMfRhpmqIsMQguuWHoxyoQXcBKAC4A3D+AeeMBvXru+vy9MDY2gZbWl7OSUyKjkB4TC6WrysASgH1NBh3HjgafJzCmq6uro2NHV9ja2sPS0hpKSkrQ1NRCq1aOGDVqLNzcBoq8j46OLjZt2oGePRt+8MR+Vm8My9wHwx7NxQeuFykAAB6fi0d+55Ae8QEcHVV8OPoIikaa0BzSFPk7rfHqz6tQtjfG+23X8X6bYMtvGXlZtD84Bd3vLkH3+0vx07nZ0HOxq/t2LBagKv+d8iLlR1DOL8WDTydRxivG3DdO8A5tgRJeIdobDcer/Gu4mLoFBbwsXEzdiumW+5BVnoxTSStrClJRxIPYGHzIyAQAWCu3wRiztXA3mlvn/Sv45VgR3hsnEpcCABLCH+PyPm+UlRQyYRw1Bd9mXwMvKMqogoty3MjYDwDY92EadsZMrFX+X399wIwZL+Hr+wFo0hboNABj9nlj+noPkeHLyvjg8wlWzQxg2KwR4x4TUyAw2EupHR4ER5bc+PxX3BEj30h8fDwcHR1x9+5dbNq0CWFhYbh+/Tq6dOkCLy8vobCrVq1CamoqIiMjcfToUWhoaKB79+5Yu3YtE6awsBC9e/eGmZkZnj59ikePHkFVVRW9evVCRcWPffYGBgbgcOo+ukNdXV3a2Zbyj1JeXv7VcbZv347U1FTmBwC+vr7M9fPnzxs6mQ3Gixcv4OjoiKioKOzfvx/h4eEICAiAvb095s4Vbusq8/Tu3Tvs3r0bhYWFaNeuHY4ePVpDbkVFBUaNGoVOnTqJvK+amppQmSUkJNQIM2XKFKaOW7x4MZYvX459+/YJhZk3bx6mTp2KESNG4M2bN3j27Bk6duwId3d37Nq16xtKpmGQpA6Tl5eHgYEBWP9PJsLx+XykxCUg5k04UuISwOfzf3SShCAicLk1+8XfE0nbY0naza/le8iUIkWKFClSpNQNj/gIzE3DyYwPCMxNA4/+XfqQKBQVFaGnp/ejkyFFBJX6q4qKCrS1tcVH+M7k5uaiQ4cOOHr0KBYvXoxXr17hwYMHGDFiBBYsWIC8vDwmbGWfLzY2Fv7+/mjSpAlGjhwpZMAGgP79+4PL5eLu3bt4+fIlWrRogf79+yMtLe2fzp4Qurq6UFJSqjPMv+W5SJGM58+fM+MU/v7+AIDIyEjGbfv27T84hV8B/QDy8vIIAOXl5f0j9+NyK2j7wS509pI3hbwLoNdh/vQm/CJ5LQZdvb2yWthy+n1HS1qy3oSKinMpNSuOhoXfo90fI4iI6Py1RTTjNzZN2NuZBl1cSF6LWfTrciX61UeN1uztRLsODyB5n7/IdOcyyvwUy8g9kR5Lt7NTqKg4h2b8xqZFa/SIiKiiooxOnZ9Or8P8iYgoJv4RzfhNhg4H7qazwUeF0paSnUxHHxygh6F/05uISzT6j7UEt24UFP62Rp7NV1wgxz+uExFRQkYa5RcViS2n2PQoOvJgP71KiSTNxX+T5uK/Gfd7725QeUWZpEUulo/ZSfQq7hnx+LwGk1krEUSUJPi3rKSExsqp0Ghw6NK2ExQ58z3RJ6KVnbrSaHAoMyFBIpHFxcUUGvqa+Hz+90v3PwCXx6XIlOlEBCIKoD8fh1LzIdvpT9kx9HrZGUq69JKutl1Kx9ij6fze/XQMo2hN84X08UYo5cekEa+8ou4bFJUTBSUS5Vd5d2KyiY6+IcoU/05K+d/hSuoucn/MIr9EHxr0WJYGPpYl75CWlFOeTvNC21FA8iZ6mnWR3ucHU2FFHnmHtKTTSatryElPzaC+LkNo/vSlX3X/Ym4+eTzVolXh/YiI6Ny2yfRbH1Bc2AMmTF55Ju2KmULRBc8przyTdsZMosj8J0REFJ73iEJz79Qq/9OnUtq4MZyyskoZt58m2FH/6W2Izh8gei24z6VLyeTt/YLKyrg16ofk5CKSlT1J/foFflXe/k189/b7DhH1JSKnKr++n92/E3369CFjY2MqLCys4ZeTk8P8b25uTlu3bq0RZvny5cRms+n9+/dERPT8+XMCQImJiUyYN2/eEACKjo6uNR0+Pj7UokUL2rdvH5mYmJCioiINGzaMcnNzmTA8Ho9WrlxJxsbGJC8vTy1atKBr164x/mVlZeTl5UUGBgbE4XDIzMyM1q1bx/gDoICAAOb/qj9XV1ciIvL09CR3d3ciItq/fz8ZGhoSjyfcVg8YMIAmTJjAXJ8/f55atWpFHA6HGjVqRCtWrKCKCjHtQxW4XC5NnDiRLCwsSEFBgWxtbWnbtm1CYaqmi4jI1dWVvLy8yMvLi9TU1EhbW5uWLl0q9N2Zm5vT2rVracKECaSiokKmpqa0f/9+IbkLFiwgGxsbUlRUpEaNGtHSpUupvLy8zvRWpmXFihWko6NDqqqqNHXqVCor+9LW8Xg8WrduHZMnBwcHOnv2LBERxcXF1Sh/T09PIiK6du0aubi4kLq6OmlpaVG/fv0oJiamzvS4urrSjBkzyNvbmzQ0NEhPT48OHDhAhYWFNH78eFJRUSErKyu6evWqULywsDDq3bs3KSsrk56eHo0ZM4YyMzO/WW5gYCC1adOG5OXlycDAgBYuXCj0PlQ+O29vb9LW1qbOnTvThAkTqF+/fkJyysvLSVdXl/788886808k/G6L4+LFi+Tk5EQcDoe0tbVp4MCBjF9paSnNnTuXjIyMSElJidq2bUv37t1j/H19fUldXZ25rvxuJYXP51PTpk3J0dGxxndFJFzn1JancePGkaqqKmVnZwu5L1iwgMaMGVMjjaLSLQpXV1fy9vYWcmvdujUNGjSIuQ4ODiYAtGPHjhrx58yZQ3JyckJ1X3Uq3/2TJ0+Ss7MzcTgcatq0KQUGCreL4t6hs2fPUrNmzUhBQYG0tLSoW7duTB1eta7w9PSs8a3FxcXRvXv3CADl5ORQXl4eKSgo1HiPz507RyoqKlT0uQ+VmJhIw4YNI3V1ddLU1KQBAwZQXFxcnWX6b+DDu/d0fNMu2r/sd+Z3fNMu+vDu/Xe7Z131HxEx5X/16lVq3bo1ycnJka+vL7FYLHr+/LmQrK1bt5KZmRnFxsbWWm+6urrSzJkzaf78+aSpqUn6+vrk4+MjJAcA7dmzh9zc3EhJSYnx37NnD1laWpKcnBzZ2trS0aNHa8Sr+h0+ffqUWrZsSRwOhxwdHencuXMEgF6/fl1reVTXH6rKrPwm/P39qXPnzqSoqEgODg70+PFjIRkPHz6kjh07koKCApmYmNDMmTOF9JajR4+So6MjqaiokL6+Po0aNYrS09OFZFy4cIGsra2Jw+FQ586d6fDhw8x3IOl9RPEj61QpUqRIkSJFEvwz48nkyRnCg8PMz+TJGfLPjP9u95REP9m8eTM1a9aMlJSUyMTEhKZNm0YFBQWMf9V2MjIykgBQRESEkIwtW7aQpaUlcy2uj1eVSp2s6q8yjeL60l26dCEvLy8heRkZGSQnJ0e3b99mZKxevZrGjh1LysrKZGZmRhcuXKCMjAwaMGAAKSsrU/PmzYX0P1G6wNatW8nc3Fwo3W3atCElJSVSV1enDh06UHx87c+Sy+XS7NmzmT72/Pnzady4cULjC/XRX+/duyeU3hs3bhCHwxHSrYiIZs2aRV26dGGuxelb6enp1L9/f1JQUCALCws6fvx4reNRlUybNo2UlZXp48ePNfwKCgqYvpSoPh8R0aFDhwgA3bp1i4iIMjMzCQA9ePBlTDU/P18ojCgq39mAgABG7+zZs2eNPmJdOjifzycfHx8yNTUleXl5MjQ0pJkzZzL+VcvC3Nxc6P2tfE++x3ORBHHjS9Xfb0nGlhqiLhGFJGOQREQHDx4ke3t74nA4ZGdnR7t372b8ahtXfPbsGXXv3p20tbVJTU2NfvrpJ3r58qVEZVi1ry4OHo9HGzZsICsrK5KXlydTU1Nas2YN4y+uDy9qnFHU9/E1/KdXthMRrt1ZhbfvL2HW5LsY2n8b8vJTkP7pPQqKBOeYc3nCZ0YHvziE5NQQyMpwoMBRAUtFHxezknAtOxnJqaG4/XAjiPiQS34Mo+ANaNv7D7RsOgQmRi0wY9wFDBl0Ch1Kz2BAymqs2GyFyX9PRf+3dzAm8iGmxz6BAkcNXVxmo3/Ptdjx8iR6hF7G9dCTePLqMADA0qwDPIcfRyebTujp4CaUNnlZeagoqMLc2AnN7ftj3sBhWDNmAtrYCK8ifhP3AWoyxWhhqI5P+Xmw/WU8bBfPRoen11DOF71E8JczzzHyWDS0VQ1gqqKJ29O64Pa0LoI06dmgc5OekJP9tpXInypKsTIhBGnlJYhIeYuwpNcoLMn/JpliKQUwAcDnhULyCgpo5dYXavp6CPr4HJtK1uJ14ku4eIzE8LWroGNmJpHYS5cCsG3bJoSECLbyvHbtEoKCHjZIkh88CIS39zQkJtZccdTQVHDLkfBJBbnFTQBYQ4atAvkKHjhcHsJLP8Gkf2u0OzAZ5sPbo2BaIML7tgJ/eHuoNNLFjY4rcKvLGiF5L+edwBntn1Gc8nm7+9gc4HkqEPnpS6DCciCnBCj9Z1ewSPl+pJbG4kbaQbTTdIerjgdaafSCiaIdirg52P/BC9FFz/Ay9xryKjLw8NMp3Mk4hMTitzj3cSNSS2KEZOkZ6GLmgqmYOG3sV6VBUUYVBx0TsNguAADQe+JGTFx3GxbNvqzwU5PTgZfVAVirOEFNTgczrP6EsqwmPJ/rI7rwGRzURR/rAQDa2hzMn98YWlpfViLdPfgOZVHr4DRPGZAT1I8HD8Zi+/YoJCQU11gxp6PDgYeHBYYONf2qvP2/4S6AhQAyqrlnfHavuVv7N5OdnY3r16/Dy8sLysrKNfwlWeHt7e0NIsKFCxcAAHZ2dtDW1sZff/2F8vJylJSU4K+//kLjxo3Fbm0dExODM2fO4NKlS7h+/Tpev36N6dOnM/7bt2/H5s2b8ccff+DNmzfo1asXBgwYgOjoaADAjh07cPHiRZw5cwaRkZE4ceJErfd89kxwnM7t27eRmpoqctuwYcOGISsrS2irsMoy8/AQ7Orw8OFDjBs3Dt7e3ggPD8f+/ftx+PBhodX+4uDz+TAxMcHZs2cRHh6O5cuX47fffsOZM2fqjHfkyBHIysri2bNn2L59O7Zs2YI///xTKMzmzZvh5OTElOW0adMQGRnJ+KuqquLw4cMIDw/H9u3bcfDgQWzdulVsmu/cuYOIiAgEBgbi5MmTOHfuHFau/LJbx++//46jR49i3759ePfuHWbPno0xY8bg/v37MDU1rTFbt3KmblFREebMmYMXL17gzp07YLPZGDRokNiVqEeOHIGOjg6ePXuGmTNnYtq0aRg2bBg6dOiAV69eoWfPnhg7diyKi4sBCGa+d+3aFa1atcKLFy9w/fp1pKenY/jw4d8k9+PHj+jbty/atGmD0NBQ7N27F3/99RfWrFlTQ668vDyCgoKwb98+TJ48GdevX2dWqQPA5cuXUVxcjBEjRoh9HpJy5coVDBo0CH379sXr169x584dtG3blvGfMWMGgoODcerUKbx58wbDhg1D7969mW/sWwkJCcG7d+8wd+5csNk1u2GS1DmzZ89GQUEBbt26xbjdvXsXZ8+exe7du2uNV1hYCHNzc5iamsLd3R3v3r2rNSwR4eHDh3j//j3k5b/o/ydPnoSKigqmTp1aI87cuXNRUVHBvNt1MX/+fMydOxevX7+Gs7Mz3NzckJWVBUD8O5SamopRo0Zh4sSJzDc4ePBgkdvdb9++Hc7OzszqjdTUVJiaCrfBampq6N+/P/z8/ITcT5w4gYEDB0JJSQkVFRXo1asXVFVV8fDhQwQFBUFFRQW9e/eu184M/xRx4ZG4dSoARfnCu5MV5Rfg1qkAxIVH1hLz26ir/qvKokWLsH79ekRERGDAgAHo3r07fH19hcL4+vpi/PjxMDc3r7XeBAR1irKyMp4+fYqNGzdi1apVQt8IIDiXcNCgQQgLC8PEiRMREBAAb29vzJ07F2/fvsXUqVMxYcKEWrfHLCwsRP/+/dGkSRO8fPkSK1aswLx58xqiyLBkyRLMmzcPISEhsLW1xahRo5jV/rGxsejduzeGDBmCN2/e4PTp03j06BFmzJjBxK+oqMDq1asRGhqK8+fPIz4+Xmi7xbi4OAwdOhQDBw5EaGgopk6diiVLhI9okuQ+1fnRdaoUKVKkSJEijnOfEjA0IhDJ5cVC7h/LizE0IhDnPn2/sVdx+gmbzcaOHTvw7t07HDlyBHfv3sWCBQtEyrK1tYWTkxNOnDgh5H7ixAmMHj0agOR9vEo6dOiAbdu2Ce2AVVW3qasvPXnyZPj5+aGs7Itd5fjx4zA2NkbXrl/G1rZu3QoXFxe8fv0a/fr1w9ixYzFu3DiMGTMGr169gpWVFcaNGydSlxcFl8vFwIED4erqijdv3iA4OBg///xznTtWbd68GYcPH8ahQ4fw6NEjZGdnIyAgQChMffRXBwcHIb/KowSr9od4PB5Onz7NjJ9Iom+NHz8eSUlJuHfvHv7++2/s2bMHGRnVB8q+wOfzcerUKXh4eMDIyKiGv4qKCmRlZWuNDwCenp7Q1NRkxoW0tbVhZ2eHo0ePoqioCFwuF/v374eenh4cHR3rlFVcXIy1a9fi6NGjCAoKQm5uLkaOHMn4i9PB/f39sXXrVuzfvx/R0dE4f/48mjcXvdNv5Y52lTvCidrhrqGeiyTUZ3xJ3NgS0LB1SVXEjUGeOHECy5cvx9q1axEREYF169Zh2bJlOHLkCIDaxxULCgrg6emJR48e4cmTJ7CxsUHfvn1RUFDLrtn1ZPHixVi/fj2WLVuG8PBw+Pn5QV9fHwB+XB/+m0z19eSfWtmeX5BBM35j0x97nRm3hWt0acZvbAqLuEqrtzahZRss6PBpD+Lx+VTK41Jmdhwd959EmVkfmDjb/KfQnLWGlJD0glZttqPLt3zo9xsrqPOezrQ29gkTjsvjUl5hFj15fYYWrzWkBat1qef5+WT9zJ8ufEqgx3lfZpc/e32cWvsOIzw4TH2e/01LX52notJC4nJFrwQrreDSo9iMWvPK5/MpMiWc8opzafiGVQS3bvTkfTiVV1SQxx/rCKt/I9a9w/SpvKRG3H17bpOW9wkyWnaOSiu4Yst16u6t1PrXX6i0/OtWuu/+GEF4cJg2JoVRYWkBpWQnf1X8enOIiK7UdM7MzKBFi+bQxIke5MFRpd9at5dYZGJiAh06sJ0inl2hiooKmjx5LC1ePLdBknvv3m2aPn0SxcfHNYg8cRSXFROX9+W9e/j2DZkOHUxnH90nIqJr7ZeRn5In3XX/g252WU3H2aPphMI4Oqkynp5OPyQkK3TF3xRg9SuVpH+eBVXBI4rIJCqr8l7diyc69Zbo2BuiwobbLUHKjyMi/zENeixDZ5K+zB7bGDmC3B+zaNBjWbqZ9hcNeixHns8MyP0xi8Y/N6LD8QtpcLA8RRe8EJK1Y8M+mjlhPpWX1b2ytD6E5QbSlqgxlFf+ZVZvcnEkjX2mSwEf/6iXzD597lHbtjeY64yMEnryJJOKiyto0KAHtHdv1Den+9/Ed2u/uVRzRXv1X7/P4RqQp0+fEgA6d+6c2LB1zSTW19enadOmMddhYWFkZWVFbDab2Gw22dnZ1TnTmkgwq1RGRoaSk7+0jdeuXSM2m02pqalERGRkZERr164VitemTRuaPn06ERHNnDmTunbtWuuuKxCxmq76arzqMzvd3d1p4sSJzPX+/fvJyMiIWZXbrVs3odXzRETHjh0jQ0PDOvMrDi8vLxoyZEit6XJ1daXGjRsL5XXhwoXUuHFj5trc3JzGjBnDXPP5fNLT06O9e/fWet9NmzaRo6NjnWnz9PQkLS0tZsUrEdHevXtJRUWFeDwelZaWkpKSUo2ViZMmTaJRo0YRkeSzdStnlIeFhdUaxtXVlTp27Mhcc7lcUlZWprFjxzJuqampBICCg4OJiGj16tXUs2dPITlJSUkEgCIjI+st97fffiM7Ozuh57J7926mbCrltmrVqkY+mjRpQhs2bGCu3dzcaPz48XWUzheqvtt14ezsTB4eHiL9EhISSEZGpsZqgG7dutHixYuJ6NtXYZ4+fZoA0KtXr8SGrS1PJSUlBIApq0+fPpGpqSndv39fZBqJiB4/fkxHjhyh169fU2BgIPXv35/U1NQoKSmJCePq6kpycnKkrKxMcnJyBIAUFBQoKCiICdO7d+8686umpiZUF1anst5Zv34941ZRUUEmJiZMfsS9Qy9fviQAtdapksxOr/79BQQECK1ir1ztXrlzyLFjx2qkqaysjBQVFenGjRv0b4TH49VY0V79d3zTLpE7LHwLX1P/nT9/XijM6dOnSVNTk0pLBbsIvXz5klgsFrP6oLZ6s3pdRSRoGxcuXMhcA6Bff/1VKEyHDh1oypQpQm7Dhg2jvn37CsWr/A73799P2traVFLypT+9d+/eBlnZXnUHj3fv3gmtXJs0aRL9/PPPQjIfPnxIbDZbKC1Vqdxlp3JFy8KFC6lZs2ZCYZYsWSJUnvW5z4+uU6VIkSJFipS64PJ5NVa0V/2xHhwm06dniPsddl2VRD+pztmzZ0lbW5u5rt5Obt26laysrJjr6qvdJenjVae2HbDE9aVLSkpIU1OTTp8+zYRxcHCgFStW1Cqjsu+4bNkyxq1y56zKMQ9xK9uzsrIIQI2dserC0NCQNm7cyFxX9j8q+wzfor9WT6+3tzd17dqVua6+qlqcvlX5TJ89e8b4R0REEIBax6PS09MJAG3ZskVsWdS1crddu3bUp08f5jopKYkcHR2JxWKRjIwMGRoaiu3H+vr6EgB68uSLvawy/U+fPiUi8Tr45s2bydbWttYdB+vSrStp6OdSX6qPL4la2V7X2BJRw9QlopBkDNLKyor8/PyE4q1evZqcnQW21trGFavD4/FIVVWVLl26VGc4IsnHyvLz84nD4dDBgwdF+kvSh5eubP9KVFV0Mfvnhxg/4stKBYfG7gBY0NQwwcIZryAnywGfz4NH5AMYPT2LC7eW4UXICbDZMkwcCyUt6KrqQ0/XFsvmvEcjM2dMchyDnePOYaqWIa6lR2J5/GvsOj4US9cb4fGzPcgvTEV5eQFOdZuLd63d4SonB2e1L+esNLHtg98MGuFGoxa4WVKIM4XZ2H/MHcs2mqG82mw7AFh3Kxwdd9xGwJskAACXJzgPuJKM/HQ8iXmI0ISXWDd2Eo78ugBtbe0R/akI5nZ90UqhI4wD1aHGrrk6/UpwDHII+LmFCVbfeCd2Ntmn/Dxk5uUK3V8Sxutb45BNB/xiYAdljgoMNY2/Kr7EXAXwG4CSz9cTAPStGUxHRxejRo2Fh4cnRq1ZicE+S2oGqgVTUzM01S9F/Et/lBfnYunSlfD2bpiVDZ07d8Pu3X/C3NyiQeSJQ1FeETLsLzPcOjZtjsSz/hjq8hOICNojW8B8WHt0PjcbNj93hfXPXWE7rTscVg5F290ThGQ5+AzBwJitUNBTFzjIsgF7HUD+y/eEDzlAdgmQVwZw//1nJEkRj72qM462ycQwkyV4XxCMWSHNARLMKp1ssR2RhY/BBxfDTZZBXVYXCmxlDDKah1Nt82GtIjwjsiC/APl5+eB/h/OznuVcwP1PJ5BQHMa4GSva4mibDAwUcyZ8dVJSirF5cwTOnHHBL79Y49y5JJSX86CmJgddXQV8/FiCK1dScOvWjz3L6H+GENRc0V6d9M/hGhBx7d3XyKmcSV1SUoJJkybBxcUFT548QVBQEJo1a4Z+/fqhpETQMKmoqDC/X375hZFjZmYGY+MvbaOzszP4fD4iIyORn5+PlJQUuLi4CN3bxcUFERERAAQzoENCQmBnZ4dZs2bh5s2b35w3Dw8P+Pv7MzPWT5w4gZEjRzKrckNDQ7Fq1SqhPFWuIq1c7SwJu3fvhqOjI3R1daGiooIDBw4gMTGxzjjt27cXmsHu7OyM6Oho8HhfdvGpOtucxWLBwMBAaFb46dOn4eLiAgMDA6ioqGDp0qXMfRMTE4XytW7dOiZeixYthM4Jc3Z2RmFhIZKSkhATE4Pi4mL06NFDKP7Ro0cRGxtbZ56io6MxatQoWFpaQk1NjdmZQFxZVM2njIwMtLW1hWZ/V87urcx7aGgo7t27J5Q+e3t7ABBK49fKjYiIgLOzs9BzcXFxQWFhIZKTkxk3UbPhJ0+ezKxqTU9Px7Vr1zBx4sQ68/21hISEoFu3biL9wsLCwOPxYGtrK1Qu9+/fF/vcJKUh6pxKGZVlPGXKFIwePRo//fRTrXGcnZ0xbtw4tGzZEq6urjh37hx0dXWxf/9+oXAeHh4ICQlBUFAQ+vTpgyVLlqBDhw71ysMvv/wiVI7V01OJrKwsnJycmHpM3DvUokULdOvWDc2bN8ewYcNw8OBB5OTkSJSm2ujbty/k5ORw8eJFAILVFGpqaujevTsAwfcSExMDVVVVJj9aWlooLS1tsHejoUlLSKqxor06RfkFSEtIatD7fk395+TkJHQ9cOBAyMjIMCuNDh8+jC5duojdFQZAjZVFhoaGNVYAVb9fREREnW1qdSpXMCkoKDBuVd/lb6Fq+g0NDQEI19eHDx8WKs9evXqBz+cjLi4OAPDy5Uu4ubnBzMwMqqqqcHV1BfCl7YiMjESbNm2E7ll1Bbqk96nOj65TpUiRIkWKlLp4mJdRY0V7VQhAUlkxHuaJG4yoH+L0k9u3b6Nbt24wNjaGqqoqxo4di6ysrFr70SNHjkR8fDyePHkCQNA3b926NdOPk7SPV5/0V+9LKygoYOzYsTh06BAA4NWrV3j79q3QzjrVZVT2HevqT4pDS0sL48ePR69eveDm5obt27czu6OJ6r/n5eUhNTUV7dq1Y2RU9j8q+Rb9tToeHh4IDAxESkoKAMEz6tevH7ODmTh9KyIiArKyskL9ZXt7+zp3QPse41pEBC8vL+jp6eHhw4d49uwZBg4cCDc3N6a8mzZtyuShT58+jBxZWVkhvbMy/VX7e3Xp4MOGDUNJSQksLS0xZcoUBAQEMDs+1ZdvfS6SUtf4Um3UNbZUybfWJfUZgywqKkJsbCwmTZokFH/NmjVi65P09HRMmTIFNjY2UFdXh5qaGgoLC8WWxdcQERGBsrKyWvsiP6oPX/ceEv8BLM2FB4hGDtwP994boKykBQBYNuc9ACA2/hXsFIugrKgJE6PWUFTQYOK4914P997rEfL2HIJf/IV3UVdha9kF08dfx6I/zHHV8VdEqFthl4YFFBW1kJYuMORUcEuREB+E2IRHuBe0FTMm3oK9tWDQRllJC0N6bwAAPFUzxvuEFJRrPANxS8Bm13wsA5oZIy6rEO3NdcDl8WG95jIsdZRx10vwQumq6aGtlQsMNYyhrqQBK0PBtiFrbr7FyVeJUJKTgY2uKqpuqlJUxgWbBSyd3wd9I9Ox+EUC8koqMLuzHbSVOTXSkJmfDh6fh78X+QhVwCLhApgNwArArwInJRlZTDCwqTUKj88Dm8UWyC0FkAzAuvZb1MojAHcATAdgIiJdGwA0BzAAcHBoKXDv2qOGmAvrNiA9rwCDl3pDR1WXcS/KyQGLzUaTTmNQmJMKJTUdmKvp1COh/37efXyDiNZZcB3dEyw2GxYjO8BiZAfxEetidDPBXzk2IPOfnu/z/woVWU0AQHZ5ChJL3mGg0XwMM/kNFsrNkV2eghbq3eGiPRyZ5QkISNmE9wXBaKvlVkPOb2saZtKKKDxM1+InndGwVqlbOb6atgdxRa/xi+U+yLBkRIbZuzcGa9a8g44OB0vmnoW6ugp8fBohL7ccyR9LMHqYIU6d6gBTUyWR8aVU45P4IF8VTkJsbGzAYrHw/v37esvIyspCZmYmGjVqBADw8/NDfHw8goODGYO0n58fNDU1ceHCBYwcORIhISFMfDU1tW/KQ1Vat26NuLg4XLt2Dbdv38bw4cPRvXt3/P333/WW6ebmBiLClStX0KZNGzx8+FBoG6zCwkKsXLkSgwcPrhG3qkGiLk6dOoV58+Zh8+bNcHZ2hqqqKjZt2oSnT5/WO92VyMnJCV2zWCxmS/bg4GB4eHhg5cqV6NWrF9TV1XHq1Cls3rwZAGBkZCT0rLS0tCS6Z2FhIQDB9rpVOy4AwOHU1K+q4ubmBnNzcxw8eBBGRkbg8/lo1qyZ2G2uROWzqlulzlaZ98LCQri5uWHDhg01ZFUaeuojV1JEHdswbtw4LFq0CMHBwXj8+DEaNWqETp06iYhdfxQVFWv1KywshIyMDF6+fAkZGeG6v7qxuL7Y2toCAN6/f49WrVrVS0blIERlnXP37l1cvHgRf/zxBwDBwAifz4esrCwOHDggcsKCnJwcWrVqhZgY4aNc1NXVYW0tUL7PnDkDa2trtG/fnjE629ra4tGjRygvLxfaXh4AUlJSkJ+fz+Rx1apVDbbFdlVkZGRw69YtPH78GDdv3sTOnTuxZMkSPH36lCmTr0VeXh5Dhw6Fn58fRo4cCT8/P4wYMYLZbrGwsBCOjo41tu0EAF1d3Rpu/waKC4oaNJykfE39V70ekJeXx7hx4+Dr64vBgwfDz89PaKv4uqirrq/tfv8mxNXXU6dOxaxZs2rEMzMzQ1FREXr16oVevXrhxIkT0NXVRWJiInr16vVVWySKu48ofnSdKkWKFClSpNRFah2G9vqE+1rq0k/i4+PRv39/TJs2DWvXroWWlhYePXqESZMmoby8XMj4VomBgQG6du0KPz8/tG/fHn5+fpg2bRrjL2kfryHSDwgmS7ds2RLJycnw9fVF165dYW5uXquMSh2nLr2HzWbXMB5XVFQIXfv6+mLWrFm4fv06Tp8+jaVLl+LWrVtwcnL67v13cfpkmzZtYGVlhVOnTmHatGkICAjA4cOHhe5Vl74VFRUlUZqroqurCw0NjW8a1+LxeIiOjmaM5Hfv3sXly5eRk5PDjFnt2bMHt27dwpEjR7Bo0SJcvXqVeTZ16YRfi6mpKSIjI3H79m3cunUL06dPx6ZNm3D//v0a76SkfOtzkQRx40vfwrfWJfUZg6z8Lg4ePCg0WQVADd2+Op6ensjKysL27dthbm4ODocDZ2fnBt2+Xdw796P68P95YzsAZOckgEDQ1rQAm81mDO2Pnh2AqVErmJu0gdqVqXBKDcEjPhfWjVyhqCD84hUWfcL56wvwKTsWqqqm6OwyG7Ky8mjTcixaqapAp1l39NL0xHMzJxw9Ow7GBi2gq20NZWVtPHt9FADw4Mke2Ft3B4/4SCwrQiMFVQCAISmj7aEIuFoPxV2vvQiPug4WSwZqqgZQUdKBupohHE21sKRDOW7d8cbgXhtgqaOMRlpfOqlsFhv2Rk3xMikbPdb4Y7N7K0xoZ4k1fVsgv5SLlsYa+MXFGo/jP+EnK8EKe/vfr8BeF8gskkVoSj7AK4aNnrZIQzsABIbfRBm3HGM6TqphaL9YAoRWAL+pAjIsCIzakRBME5SAorJCXHh5FpZ6NrDSs0HYnRC03dsBKjtVATvgaUwQAEI7647ihS2DaEM7AOQBuAQgFcCAusVceB6G0tVzoBASgJ/su8FC1woAsLC5E+QVFbAl+h1UNGuehfJfQl/NACZaZtBSqXsywat7QVDT1IB1y6YAgIzsNDwLe4h+Pw2tOSlD4f9FtfP/lg7aQ3CybR4UZVQZNy15I3TSEZzPM8JkOVpq9ISDWu3no38vODKKYg3tABD06QyiCp/C03wjM4mgOjNn2sLAQAG9extg8kQDpOXIor+bCmLeZ4EIUCjPxbBhQbC0VEFUVP+Gzsp/D0nnKzXwvCYtLS306tULu3fvxqxZs2p0nHJzc8Weobx9+3aw2WwMHDgQgOB8KjabLVT3VV5XKsOVxqzqJCYmIiUlhTln68mTJ2Cz2bCzs4OamhqMjIwQFBTErFgDgKCgIKHVaWpqahgxYgRGjBiBoUOHonfv3sjOzq7R0aw0lFVdBS4KBQUFDB48GCdOnEBMTAzs7OzQunVrxr9169aIjIysNU+SEBQUhA4dOgidDSXJTNPqxvjKs6DEKf6VPH78GObm5kLn1iYkfDmzT1ZWttZ8hYaGoqSkhFHwnzx5AhUVFZiamkJLSwscDgeJiYlCz6oqoso/KysLkZGROHjwIGNkfvTokUR5+Vpat24Nf39/WFhYiD2/7Wto3Lgx/P39hSZlBgUFQVVVFSYmohSzL2hra2PgwIHw9fVFcHAwJkyYUGf4+uDg4IA7d+6IlN2qVSvweDxkZGQ0uJG/kpYtW6JJkybYvHkzRowYUePcdknqnMpzFSsN4MHBwULv0YULF7BhwwY8fvy4xmBRJTweD2FhYejbV8TWT59RUVGBt7c35s2bh9evX4PFYmHkyJHYsWMH9u/fj5kzZwqF/+OPPyAnJ4chQ4YAAPT09KCnpydKNJ48ecKsxOdyuXj58iVzHp4k7xCLxYKLiwtcXFywfPlymJubIyAgAHPmzKlxL3l5ebH1HCBY7dCjRw+8e/cOd+/eZc6IBwTfy+nTp6Gnp9egE6S+J0qqkhmWJQ0nKU2aNBFb/9XF5MmT0axZM+zZswdcLldoIpek7ZakNG7cGEFBQfD09GTcgoKC0KRJk1rDHzt2DKWlpcxkssqVZd+T1q1bIzw8vNb2KCwsDFlZWVi/fj1MTU0BAC9evBAKY2dnh6tXrwq5VT/TUtx9RPGj61QpUqRIkSKlLgzlJVv8IGm4huTly5fg8/nYvHkz0yc4c+aM2HgeHh5YsGABRo0ahQ8fPgidhV2fPp6kurIomjdvDicnJxw8eBB+fn7YtWtXveRURVdXF2lpaUJ9gaqGwkpatWqFVq1aYfHixXB2dmYmIIjSYwwNDfH06dMa/Y/KcY1v1V+r4+HhgRMnTsDExARsNhv9+vVj/MTpW/b29kz6Kg3fkZGRyM3NrfV+bDYbI0eOxLFjx+Dj41Pj3PbCwkIoKCjU+U4cOXIEOTk5TF+uckV09f4qm81mxrWqT6yohMvl4sWLF8w4VWX6GzduDEAyHVxRURFubm5wc3ODl5cX7O3tERYWJjQWVYmcnJzE/b36PhdJEDe+VBt1jS1JgiR1SX3GIPX19WFkZIQPHz4wZ9tXp7b+WVBQEPbs2cOMNyQlJeHTp4ZdPWVjYwNFRUXcuXMHkydPruH/o/rw/y+Wlf6xzxmb9ghvk5aeGYlT56fiwPFBKC7JQcanKPD5PLi0+RndO80HEeHZ62PIzIoFESE5JQSfsmORpO+I7W3mY2d+Pop4FRjhvhsergvQ6/OW6G1aeqB/9zXIK0jBwD4bEXB1HoqKs6CspI3klFcAgJUJobB8fg6BuYLthfVUOJjXxQbTXQSrvv/0GwrfUyOwYVdr7DrUA9sOdkbGp2gMiw/FNNUmSEgPw12vbvhrlPCskupsvx+JQ08/wNvVFmtvhaPb7ntw3XkH0ZmCLQVZIDxNLERURj6G2CvBsOAW/EY2wdFncYjLKgSPx0NMykeAxwN4PLRs1AGtGrnUuM+D2AwsufkOBwsJWZUT3BQAXASwTXTawpJC4PfYF7nFgm0fZdiyUFNQgwpHBWl5KUjWSUB2/yzg8xjhx5xEJGfX3GriTeIrPP8QDADILwbyigAoQrShHQC0AZwGsK4WfwDPy4EUHjBv/3aQsgHkNBtBu8rKdscB/dCqf+2Dk6Lgcrm4des60tMl3FI6tQA4Gw5kfp/ZlZKiq6aPrk17Q1Wx9kqpvKwMh5ZtgN+GnYzbpsPL8Mua4Qh6ffefSKaUfxlVDe3VUZBRRgv1bnXvjPGDWWwfgF0tI6Aiq4lbt1LRs+c97NwZ+WV2LfGhxymEl5ct/P2TwZFnQU2pAns22mBwoDr6rVDE5n2dsW1ba6xb51D3zaQIaAlAtE3mC/qfwzUwu3fvBo/HQ9u2beHv74/o6GhERERgx44dNbaHLSgoQFpaGpKSkvDgwQP8/PPPWLNmDdauXcsorz169EBOTg68vLwQERGBd+/eYcKECZCVlUWXLl3qTIuCggI8PT0RGhqKhw8fYtasWRg+fDgMDAwAAPPnz8eGDRtw+vRpREZGYtGiRQgJCYG3tzcAYMuWLTh58iTev3+PqKgonD17FgYGBiKNd3p6elBUVMT169eRnp6OvLy8WtPl4eGBK1eu4NChQzWU7OXLl+Po0aNYuXIl3r17h4iICJw6dQpLly4VW/aV2NjY4MWLF7hx4waioqKwbNmyGkYAUSQmJmLOnDmIjIzEyZMnsXPnTqYsJL1vYmIiTp06hdjYWOzYsYPZvlgc5eXlmDRpEsLDw3H16lX4+PhgxowZYLPZUFVVxbx58zB79mwcOXIEsbGxePXqFXbu3IkjR44AEHRMWSwWLl++jMzMTBQWFkJTUxPa2to4cOAAYmJicPfuXZHGw4bAy8sL2dnZGDVqFJ4/f47Y2FjcW2XxlQABAABJREFUuHEDEyZM+CZD1vTp05GUlISZM2fi/fv3uHDhAnx8fDBnzpwaHXVRTJ48GUeOHEFERIRQ57uh8PHxwcmTJ+Hj44OIiAiEhYUxKz9sbW3h4eGBcePG4dy5c4iLi8OzZ8/w+++/48qVKw1yfxaLBV9fX0RFRaFTp064evUqPnz4gDdv3mDt2rVwd3cXCp+bm4u0tDQkJCTg1q1bzOrrvXv3Mt9148aN0axZM+ZnbGwMNpuNZs2aQVNTMGFs1apVuHnzJj58+IBXr15hzJgxSEhIENkprcrUqVMRFRUFf39/AIJt5by9vTF//nxs3rwZsbGxeP/+PZYuXYrt27dj8+bNEg0K7N69GwEBAXj//j28vLyQk5PDrMAX9w49ffoU69atw4sXL5CYmIhz584hMzOTGbypjoWFBZ4+/T/27josq+sB4Pj3pV66G0kJURG7sAsLa7YzZsyOmXOzc86OzZ41Yzpzdhd2YAIqChigSIfU+57fH/x49RUQdDoX9/M8PHrvOfecc+O9de455yLh4eG8fPmywF4YatWqha2tLV26dMHV1VXt6/0uXbpgaWlJy5YtOXPmDI8ePeLkyZMMGTJEbXiEvxNbZ0cMjAu+HwMwMDbC1rloL3GKqijnv3fx9vamatWqjBkzhk6dOqm1WMjvvPlnjBo1irVr17J06VLu37/PvHnz2LFjR4E9MnTu3BmZTEafPn1U5/7cHiU+pTFjxnDu3DkGDRpEUFAQ9+/fZ/fu3aoPVJycnNDR0WHx4sU8fPiQPXv2MHXqVLU0+vbtS0hICGPGjOHevXts3bpV1Zon9568sHzy87nPqRKJRCKRvEtNE2uK6ehT0NsnGeAo16emSWEvIz4+d3d3srKyVNfvDRs2sGzZskKXa9OmDcnJyfTv35+6deuqVax+yDOei4sLKSkpHDt2jJcvX77XUHCQ8/z2ww8/IISgdevW77VsfurUqUNMTAw//vgjYWFh/PTTTxw4cEAV/ujRI8aOHcv58+eJiIjg8OHD3L9/v8BnAYChQ4fyww8/sGvXLkJCQhgwYIBa5fWfvX99W5cuXbh27RrTp0+nbdu2aq3jC7vf8vLyonHjxvTt25eLFy9y9epVevfuXWgr3unTp+Po6EiVKlVYv349d+/e5f79+/zyyy+UK1dO7b45LS2N6Ohonjx5woULFxgzZgz9+vVTHVOQ89xnZmamej917949Ro0axaNHj9QqqfOjra3N4MGDVeXv0aMHVatWVVW+F3YPvnbtWlavXs3t27d5+PAhv/76K3p6egVW7ru4uHDs2DGio6PfObzYn9kvRfGh75fe9W6pKD70XAKFv4OcPHkyM2fOZNGiRdy7d49bt26xZs0a5s2bBxT8XtHDw4MNGzYQHBzMxYsX6dKly0ft/SC37GPGjGH06NGqIR8uXLjA6tWrgc/4DP+nRnz/QImJiQIQiYmJf0l+qzd1EMs3tFKbl5mVLkZNMRNzl/mJJ89uiEHfycSmHV+rwsMfXxIDxyJWbWwrFq6sJ8bNchKnzv8kyv/yhbDeM0FoHVsqlj4NEW6XfheD7l8QQgiRlZUhsrOzxOFTs8S306xFTGyYiHhyRVy9uVVEx4SKxOTnQgghDsQ+EXVvHBDrou6L2IxX4qedw8QvxxeIVxlpQgghzm1ZKbZ59xfbfhwsVm/uIAaORdwJPSD6hZwW1S/+JrKVClU5t509JR5FR+W73nbjdwiGbhLrLz4U/kuPixlHbosxe66LrOyc5estOSZKz/hVeE7dKpJeZQohhAh8+EIwdJPotC5QTN68XhBQXyR37yLEoP6i2vzDwm78TtXyuZosOyEYukmY/nBArLv4ME85kl4lit/Orxc3I6+r5gU/vSW2XfxVJKXlPQYUSoWIS4lVm5eRlSEystLzxN15eYvYfG6NUCqVYuVBIZbuUwgh8pbhba9eJIqUyJciTiHEyhQhkv+/Ss+yhXB8JkT7l0IoFEKMiRdieqIQX8YKcTmj0GQLdPfubfHVV53F6tXLi7bAredCLLgoROjLD8/0L3T12Blx//pt1fSdsBtizrqJIi097TOWSvJPlpqaJi6fuyqUSuVnK8OFCzGiYcNjAjYJ2CQuXIgRBw48FanXLgqxdZEQj++Lpk1PCh2dzaJetV1i8aIQ8W3CITH64dHPVuZP7ZNev48JISq+4+/Yx88y17Nnz8TAgQOFs7Oz0NHREQ4ODqJFixbixIkTqjjOzs6CnP5ahI6OjnBychLt27cXx48fz5Pe4cOHhZ+fnzAxMRFmZmaiXr164vz58+8sw8SJE4Wvr6/4+eefhb29vdDV1RVt27YVcXFxqjgKhUJMmjRJODg4CG1tbeHr6ysOHDigCl+xYoUoW7asMDAwEMbGxqJ+/fri2rVrqnBA7Ny5UzW9cuVK4ejoKDQ0NETt2rWFEEJ0795dtGzZUq1sCoVC2NnZCUCEhYXlKfvBgwdF9erVhZ6enjA2NhaVK1cWK1asUIV3795dlX5+0tPTRY8ePYSJiYkwNTUV/fv3F99++63w9fVVS+PNctWuXVsMGDBA9OvXTxgbGwszMzPx3XffqZ0znJ2dxfz589Xy8vX1FRMnTlRNjxo1SlhYWAhDQ0PRoUMHMX/+fGFiYlJgWd8sy4QJE1TL9unTR6Snv75PUSqVYsGCBcLLy0toa2sLKysr4e/vL06dOqWKM2XKFGFraytkMpno3r27EEKII0eOCG9vbyGXy0WZMmXEyZMn8+y3t9WuXVsMHTpUbV5+6/52Ovfu3ROtW7cWpqamQk9PT5QoUUIMGzZMtQ0/NN2TJ0+KSpUqCR0dHWFrayvGjBkjsrKy3lneXEqlUjg7O4umTZsWuL75KWwbvWn79u2ibNmyQkdHR1haWoo2bdqowjIzM8WECROEi4uL0NbWFnZ2dqJ169bi5s2bQggh1qxZo3Z85P5uc504cUIA4tGjR+8sQ2hoqOjWrZuwt7cXOjo6wtnZWXTq1CnP7zX3T1dXVxQvXlx0795dXL169Z1pv11GIYQYNmyYcHJyEjo6OsLGxkY0bdpULS8hCt4vffv2FaVKlRIKxev7/9WrV4sKFSoIXV1dYWBgIGrWrCn27NnzznIJIcSjR48EIDZt2iQqV64sdHR0RMmSJfOcR991DN29e1f4+/sLKysrIZfLhaenp1i8eLFq2bfPFaGhoaJq1apCT09PtW9y91N8fLxavqNHjxaAmDBhQp6yR0VFiW7duglLS0shl8uFm5ub6NOnz1/2PPshHt4JEcvHzyzw7+GdkE+Sb2Hnv4K2f67Vq1cLQFy6dClPWH7nzfyO3ZYtW6rChSj4HPHzzz8LNzc3oa2tLTw9PcX69evVwt9e7vz588LX11fo6OiIsmXLiu3btwtAXL9+vcDt8fZ58800c38Tby4fHx8vALV7kEuXLomGDRsKQ0NDYWBgIMqUKSOmT5+uCt+0aZNwcXERcrlcVKtWTezZsydPurt37xbu7u5CLpeLOnXqiKVLlwpAvHr1qsj55OdTnlMlEolEIvmztseEC9nptUJ2eq3gjb/cedtjwj9JvkW5P5k3b56ws7MTenp6wt/fX6xfv17tHim/+3ohhGjfvr0AxC+//JInrLBnvPz069dPWFhYCED1rFyUZ2khhEhOThb6+vpiwIABedItyrNjfvdCS5cuFY6OjsLAwEB069ZNTJ8+XTg7OwshhIiOjhatWrUSdnZ2queoCRMmqD2rvC0rK0sMHTpUGBsbC1NTUzF8+HDRrVs3tWeGD71/LejepXLlygLI931RYfdbUVFRolmzZkIulwsnJyexfv36fLfl2xISEsS3334rPDw8VM99DRo0EDt37lR7xn/zvZadnZ1o3ry52LFjR570Ll++LBo1aiTMzc2FkZGRqFq1qti/f/87y5B7zG7fvl24ubkJuVwuGjRoICIiItTivesefOfOnaJKlSrC2NhYGBgYiKpVq4qjR1+/Z317W+zZs0e4u7sLLS0t1XHyKfbLxIkTVekXpLD3S2+Xqyjvlj7GuSQ/RXkHKYQQGzduVN3rm5mZiVq1aqkdL/m9V7x27ZqoWLGi0NXVFR4eHmLbtm1FOoaFKPxZ8U0KhUJMmzZNODs7C21tbeHk5CRmzJihCi/sGT6/94wFvasqKpkQbw2E8RdISkrCxMSExMTEv6QZ/7gfipGS9pL5k1+ptaZUKLKQyTTR0NAgJjYMU2MHtLVzuoRTKhUcD5zP9VvbyMxMxcjQGv+641ixoQVVa3+HvMyXZGVl0Pb+OUxTnnHMpzk7NwVgbGjNqAGX1PKPS4hkylwPypRsTZcvVnPp2nr6yiwIznyFhhBMf7gHYwsvejQci76uMbO7VcJugwfV1vQlq5EliSkvqOKZtzXctbD7VPimP22q1WD72El5wtdcfMjI3dfZ2aumquv4+LRMRu8JokdlV4pbGnL4xm/o62jTtkpOS7VshZJFp2/RwNOJly/D+XHHb+xQaqBvYMAQj8aEvUymQjEz6rjbUM8r5yuXwIcv2HI9kg2Xw+lTrTjNSzlQ2/31V4HJ6UkcCNqNt0NpfBzzH58y5HkSX/56nsmNS9OsVP5dXuYnPfMVSqFEX27AlfugUC6jitdw4AVQ8Fhwf5QaRfLTWOIiVjErTYMxhqCrAZ314KdUKKsNK1PhQiYU04DHShhmAF8agI3mNaALMBToV6RyKhQKzpw5ScmSPgV2qZlHcgYYvXts13+VLAU8TwUHI/gbt3qW/DXWLP2V3zfuYtyM0VSrVbnwBT6BBg2Oc+zYcwCqV7dg4kQf/P1P8uMYW0YFpIJvTVLQ5+7dRGrVOkarVsWIjc3g9OkYnj5thaXlv+/3+8mv38eBueScwnPZAMOBv37kgb/UpEmT2LVrV75dpP3T1a5dm7p16zJp0qSPlmadOnUoW7YsCxYs+GhpSj6/lJQUHBwcVGM2/9OsWbOGGTNmcPfu3Q8eT+7fLDw8HFdXV65fv07ZsmU/d3H+Ex7dDeXc/qOkJiWr5hkYG1G9aQNcS3p9xpIVbOrUqWzbto2bN29+7qL8q02fPp1ly5bx+PHjz10UiUQikUg+qR0vIxgadoknb4zN7ijXZ4FbZdpY5t9aVlI04eHhFC9enMuXL+fbxbfkv2Xt2rUMGzbsnd3e/1N1794dmUymNtb7n9WjRw8SEhLYtWvXR0tT8nn9JwZP7tt1D5nZr/J0W3zy3GL2Hh3PwK8O4u6SM47Yw4hz7D8+mXYBi6lVdSDHTs+mmH05Bn51EIC5k153uxHx5Aq9jwygeIkAbj+yQFvPClvrnPElMjJS2HlgFK+carJO6FPJuDRhz+O4cHUNK49N5V7NGaChhZ2OPu0C5mIslGhqaDL75yqk+SahrKOFW/darD08DW0DWyp71MlT/jIubszo2pMGZXMuZpnZCnS0Xo9T+lUVN76q4qa2zPUncay6EEa2QsmmaxEElHJhTaec5ZVKQdtfThAR+4zLEU9Y3rERBye/rhxfBMw9EczI3UFMP3qXX7+sxs+B97kbnURcWiZPJrWk+LQ/uPn4Fs/KC5r4BmBqYI6RrjHtq3Z95z56mpjGtSdxhL5Iplmp/OMoFAquh1ykvHdVVVcaujo5XVAkJMQTfGEXDRokQcIgmGcALYEK+af1spklgS+jGBwbjtzajccKWJMCthrHGGXkB+iyNhU0gTGGUFoO3eNgXRrctI0GQsgZGL4R8Hobp6Wlcfr0CapXr6lWEaWpqUmdOvVV00qFEpkMZO/qEuS/VNEOcOkZXImCBi5Q6q/vwkny91KnYQ3S0zMo5VtwV1Cf2sKFFTh3Lobvv7/JrVuJaJfNoM0wG+p8UQYqWQA5n/RUrmzJ48ctMTHR5pdfHlKsmD6mplIlywepB9QGgoCX5IzRXpack7HkHykxMZGwsDCpy1jJOymVSl6+fMncuXMxNTWlRYsWn7tIH2T//v3MmDFDqmiX/G24lvTCuYQH0RGPSUtORd/IAFtnxyJ3S/hXSklJITw8nCVLljBt2rTPXZx/nZ9//plKlSphYWFBYGAgs2fPfq+uMSUSiUQi+adqY+lMSwtHziS+ICozDTudnK7jNWV/v/uhf4qsrCxiY2MZN24cVatWlSraJf9qQghOnjzJ2bNnP3dRJH9z/+rK9qzsDH7/YwiexetRoUwHsrIzKX/jAK66huwpVZ+wiLNkZaURfO8QUc/vcPPuLoq71iLk/mEiHl/m4rV1DOhxEAe712Puvox7yKpNbUn0bs9l6/Is7L4XZ7syxKYl0qxcG4z1zQGIjgnh7KVlyBOecsqtDWfOmqGvmUZADUOa1BzJPi1dEpTZ2GjA0f3DqFahJ6cv/sTTqBv4lmpDt47rOXV5NVdPTcCkyjACN27mj1lzGbF7Gw/jT3Pk1A/0676Xse06AzD54C1mHr3L1RGNKWVnAuScCGZt34KPsyvNKlUFoJ6nLWeGNMDd0pCXaRkUMzWkxuKzvEjOIDYtAyO5FtkKLYKik+hdPZb6nrZq27R7JTeuP47n8uM4emy6QKYip2OE3n7u2Bnr0c7Xkaj4+2QqFMw+EUwNN1ealLRXS0MIkefDgfqetsRMa4OFQf4VzPNPhvA0ZDtbto9j1jcr6NK0j1r4nTu3OXHiKHo2zTAzKEPtowq0TLQKrGwv0dqPB3tfYmugTx9DiFaAm9Y+Guh+ASwHuhMQFcLzqzfQaN2G4lra+GUkcCbwEqczYqnVfT1wntzB4R9lQ+94aH79HLe2bkKhyKZZs5b5Zw78UWIEcksjGp+fUmCc/xy7//dEEPxSqmyX4OruQv9veqnNy1C8YsLdBngb+9HD+cdPXoZSpUwoVcqE8PBU7t9P5pTlA8znJ1KSvGOgWlnl9IrSr58H/fp5fPKy/atpUuC5W/LPY2Ji8rcd01jy9xEZGYmrqyvFihVj7dq1aGn9Mx9Rtm3b9rmLIJHkoaGhgb3r37/V1qBBg9i8eTOtWrWiZ8+en7s4/zr3799n2rRpxMXF4eTkxIgRIxg7duznLpZEIpFIJH8JTZkGdUxtC48oKZLAwEDq1q2Lp6cnv//+++cujkTySclkMiIiIj53MST/AP/qbuRj48OZNKc4pbyaUbNKP5auC+BQ4xWUsXRje8m6pKbFceXGJiKfXuXx06s8jwlhYM8jmBjb8SImlOUbWlC1Qk80NDRpWGs0VhbuhD++xLzl1Yn36cZep4Y8qvQFplo6AJxKiKb+rcMMUsYxqWw74hIjsbYsQZKmnAuXzxIdfZk+rUairZVTobwtJpwSKU9ZvrIG5X068vxlMHHxkVSv1BtbqxKYF6vCiG29MK3Yl7bHn7Nj8nQmnz/FveRDHDg2Cd1y+/jtdhpnhzRg391nzD8Zyr6va+BmmVPZHvkyFpdeHanq5c25Hxfl2T6XDp3k211XOCF3QFtDhpWRnEn+PrT0ceDGswQaetmp4sYrwUQGGv+vIx/7RxA7bj7h4ctkKlby4HndimzUy6CCoRZnH8Zgb6yH9w/7aVHagd29a6nSeRr3mGN3DlDCvjSVi1dXK49SKImKf4qtqR2aGq9fsj5NSMBx0gG8jOKopxfIiG6TcSumXpmlVCq5ffsmLzWeE5X4hDYmndBz1wfd9zlingDrgUGAMUuXLuLy5Yt0qtOY5PBINnYdzCVdY2qt/5mvhw2g9hvfBQRlQutYGK79ipI3zlClSnUMDQvuxv54k1nomBtQY6PUmkBFKeDiU7A1BFfTz10ayd9QWnYSPa7YYi13ZUm5Ozx9FYqtbnE0ZX9NpcxTkkjkFSWx+Uvy+zv6q4eBkUgkEolEIpFIJBKJRCKRSCQSieTv7F9d2Q7wNPoWZibFuBX8Bxt+745zsSqMGnBBFa5QZDN2hjUmxg5EvwjG1qoE3w+7jVKp5MadHRx7co3wMzPxbzybgFojAXiVnoS23JB0pQJtRSbrfuuCEAKvBtPp8vAKvlcXY1iqA6bONVjhUb2gogHwJCOVH6ZbYSA3onbVgZTyasa85dWwty3DmIFXSFVkoauhiaZMg4y0NOT6+gBkZ2cy+XAIS87cI2hUE5zNDYhNeUmlb/pjY2ZOw9q9+OH4IxY3tadByeIUt3vduvxVZjapmQou/rad/eu20e7HqdSqXAoNDRnRSa+wNJCjpfm6K53gLGgQkoj+qetsbuFDRScLbj6Lx/fHg3zhWwxdOwv23nxM4rM49vapRbNSDjyOT8Vz+j7al3Vk3ZfVVGlFxkZw8u4hTPRMaVmxfc4+UCqIS3lJ0qtEAu+dpJxLJdXY7gqlgkthgRy+e49SDp60rfi64j4/CqWCrOxMVffyRbE8BX5Jhe0WUOz/dXbR0VFsXLWcp7/tQUuh5GlwCJ0iIjihZ87WbG066cGPpurpJCth5yuoJQeXf2aDrM8iKzMLLW0t9d4O4l/ldClfxQGM/2Pd6UsKpBRKul22wlTblr5uSxh/tz5fOHxLV6cZn7to/xlSZbtEIpFIJBKJRCKRSCQSiUQikUgkr/3rBydxsPVBX8+MyuW60qbpfKqW745SqVSFp72Ko3a1IfTvvg9bqxIgk3H91u9M+NEJczMXjmsY8kfF4Ri6vh5vW0/XGC2ZBoaa2iQlR3MzeA+3Qvbw4ORkDllZ4/b8GocVGqyJvs+LzDS18py9uJxFq+qR9ioegFXR9znp1Q6FexP2H5tIaNgRxgy8Rt8vdwNgoKmtGkMmt6IdICHpKcP9zImf2RZncwMAdLR00NDQ4lVmGokpYRS3MKR+mbIYG5mTlJ6lWrbl6jO4Tt1Djc5tmXtgI3Wqlib0aSQjNmyh2KTdDNt5Ta3MyQkppIVE8uBBFBciYgHwtDJmWG0v+lX34O6tSJKexaGnrYmJnjZrLz7k1yvhlLYzoaStCXOOB3MnKhEAJwtnmpZtTQOfpqr0b0Ve58CN3QihxN3GCycLV1VYfGos96NDqOnuSJsKNQrd35oamu9V0Q6QHp9KSpaSZCWk/P/QCAm5y60rV3gRHIpnjep8d+wAzZ1smGulzT5LmPhGHdOCZFibCtdTM/k+CRanvFf2/2lJcfGMDejKxh8Wqwc8SoC7LyEy6bOUS/L3pCHTYG6Zq1jJnbibdJZKZgH4GNf93MWSSCQSiUQikUgkEolEIpFIJBKJRPIf9Z9pfyuTycjMTGHH/m/Q1TUh3agBkw7e5iunE1w4Pw1TEwfkciNexj4g9OFxUlJjyMp6xXADA05FHKaSxXf5pmtlUZxu7X7l972DKO/TAa/i9alZpT+nXt7ltlNtDkfe5Ev3nPHSlUoFZy8t59nzW9wM3oOVhTtD7SviVH8cX5hYc8O5MmVKtmTqzoFYOlRmbIP88wSYtaQc+nrmTB71UDXPSNeYB8s3E/b8HnJtXRZ2cCIzW4H1uJ14WBlxeYQ/APU8bDDW1eZVloKJR4PpU82duTu2subEScpX+5qqLhYA3Ht4EiMDa2y0nTG685DedUswsEZO9+262prMb10egDruVlx/Gk9WdjY1Z21EpmeNtqYWr2a35+yjGGovPsblyFhWdqyCoY4mT+MisTcrhoE8p5v1YhZOpGQkkZ6VTtjze7hYFSf+lRa3ohIJKO1AHe9GWBpZoSHL/9uQZCVoyUDv/w2jX2Vmc+ZhDA08bdHQkOW7jGrZB9FYlRpN8851aDuzJzLggjXUqlWXYsUcsVppzmE9c/R1X+ddRjvnXyHg17ScynX3CSOx37yG7y5fo7FV4WMihv92nkcbA6m+rh9ys4K7m/+309bRwaqYHRZ2b3XL7WsDlvpQTGo5K1Gno6HLnaRTyDUN+L7E7s9dHIlEIpFIJBKJRCKRSCQSiUQikUgk/2H/mcp2AN9SbYhPfIynW11WX43j+P3n9K/anrbNralYphPOxaoya0lZHj+9yvwp6chkMtxda9KgxtA8aT15FsRvewbQuskcKpfrjKOTH/suLOdlQiRtms6j5ONLbI+8g3h8Af5f2R6f+JgnUddxd6nF5p19MDSwYvq3T+lpm1OBXavqAFLT4lhlV4sUbVNqX91A9Qpd812X2tUGI5cb5RtW3MZT9X9tTQ1alymGy/9bvwN826AkAJ3XB7L5WiRCwKTO3ahVugzlvYqhqSNIz0hm8er62NuUZuyQG0ROaqlafn/QLmQyGU18c+YNqeHCwm0/Y2ZqQ4yeD/ZGMrb3qo+GhowarlZMblKaRafuUXneIQKHVOVG5FUS0uKobdwQAEsja2p41eNJXCTGesboao+h7+Y67L1jyJ1vm1LS1qXAfZotoFYMOGjCXsuceXNOhDDhwC02dq1G5wpvL5sJLANaAC7omBlgUbk42j7OOGqCtSbIZTktaN3dPflh9wqWpAiaN+3LYlNo8RK8tGGBKdzPhu+SwEMri0T7Yti72NHZQg+d7DQylJrIdQru/jz62G2e7bvOq2cJ/+nKdj1DA8asnp83QFMDnExeT/9xDzIV8IX3X1c4yd/G9YRDLAnrTXnTptxMPEpzu6FYyh0QQqgPPyCRSCQSiUQikUgkEolEIpFIJBKJRPIX+k9VttvZlKRT6+UAfFPHlqZepqz9xYfUV3GkvYpj/7FJNKr9HX6V++RbgZORmcqDR6dIeRDBtfObeKQ4T/SLuzw0diHmeSg6xi48jb3Fht+7E3RnB47ONYj0bseV5JdUNLLEwsyFob1PYmnuxv1Hp3gZ9xClUkHIg6ME3z/EmSgrfN0t+JpXXL2zm6u6OgVWtjdvOLXQ9c2tiFrTuWq+4U6m+hjoaNLXzx0nKxO61WvI+rOrSdIyxKNqJ9o0nYeF+esu3QMzcsY2b6RlgLnIVM13NDelXy1f7mcU48ijDBp5u1DZ2YJLEbFExKUw82gwWjIZTbztsTC0pG7JRpgbWqqWf5n8guvhV6jkVo2WFZsCfRlTX5NqLmPwss7/g4JcWjKoqgN2mq/nfeHryNPEV9R1t8lnicPAUCAU+Am5hRH+ZybiX0D6G9d/h65SydD2fRFAsoDU/3c176kN80zAS+sxl0Y/odmEThhrWFG5ixOWptYc+PlqgeWutLgHpb9vhaGz1TvX7z8vPh30tCA9GzIUn7s0ks/kZeZTYjOfEvhyG2nKBHY8mwVACSM/3AzKfebSSSQSiUQikUgkEolEIpFIJBKJRCL5r/pPVbYDZGVncPXmFrQ0dYh8eg2Zhiba2nrYWJVAQ0OLwMsraOE/XW2ZhKRnXL+1jcdPr3IpaAP2LxxIiXpKi29m4l22KxYXtuBrYMbuEvVwMO/JhWtryM7O4Iu267C6souNoWe5W7EVAB5utQFITH7G/mMTMTN15FbwHm7e3cUDjfb4FK9L7xKN8I69ScPa3xZpnTKzXhF4aQXlSrfFyMgWTQ1Nph2+zQ9Hg7kywp8XKeloymR4Wupw8dEd6nlXQF9HTl8/D2q52+BlpU9ySgxGhlYkujfnmdDiacxDqlb6Gr03xj8/kwGHM+Arj4bUeKPR9sO4NMqXbUYjAzlXNl1g7aVHzGpRln7bLnP9STzTm5bB1liXnlWLA+Bo4QJAk2UnsTHS5du6RkQlPOHhkwesmfET9VotoXXrdtRwK7hl+JsmZkSxZMl8Lga0pkqVapS0NWFZ+0oFxG4ELCGnhbsROZXv1QpM+7fZx0EIvP/fdfwPJhCvfB3eTh/AjTI6EwFDQEb5ElUxN7Ek/UUMaVGtMHRuhY7pKLV0NeXa+Va0335wnYdP7tGiTocirfu/WloW/HoLbA2hXUnIkirb/6uuxe8HIE2ZAICbfnn8bfviql/28xVKIpFIJBKJRCKRSCQSiUQikUgkEsl/Xv6DYP9LhTw4yprNHfn19x78cfh7Zp6IRL/sTuZNSsHexgdNDW1epSfwKj2JsxeX8yo9CYBT5xezfd8wrt7agoamLtfcvNCtWQqvEg0w05az0K0yM1zK42TljqamFn6V+vB1111Y6Jmw2qM6C4tXzlOWMiVb4Vfpa6JfhFClXHeG9TnNr6NX4Gmgza4/+tO6yRwc7YvWYvN2yF627xvG0Qs/s/ncGm5EXMVUTwcbI12CoxOpvfgYNRYdZfqhQ8Ql3WbWwd1kKbIYsO0KzVacYtmmHoyfVYzY+HCG2tkxVC+DM6FHuRFxRS0fh/vhBNwJobq2kpBnt4lLiQVg/P6b9N5yCWtDXYJGN+H8sIZYGeqyqE0F1nepyneNStFTL5nUsyeIS3kJwO9BkZwLf0noiyS87EoiN6jB0p+PonwQS/TdZ0DRKtoB0tLSeP48mri4l0WIrQMMBGwAXUAz/2hKIB1KupWhZHFfAJ4r4NtEGJQAmeLtBYyAnN4Qlk/YxsyhS3my7wQmXhfIiPsNgHkbJjNvw+R3lm7c4kEMmN6RqJdPi7Au/3K6WuBsDM+S4chDMn68xJV2B7l5uuAeAyT/TpXNWuKs50N9yx7YyT0Y5bkVf5v8eyCRSCSfz9q1azE1Nf3cxfhbk8lk7Nq1672X+5Bt26NHD1q1avXeef2bFLa969Spw7BhwwoMf3sbvh3fxcWFBQsW/OlyfmwnT55EJpORkJAAfNjxU9i2kUgkeb3v7+bfdt1885wbHh6OTCYjKCjos5ZJIpFIJBLJa28/J3xKkyZNomzZsh8tvX/bfZNEIvn3+c9UtiuVCn5e25ibwbsoV7o9PTpsJkTWmtWXnvIw4jwzF/tSzL4c3w+7w8Vra9myux/nrqwCoE61IbRtvogvmi3ghW0TttfsxqXSnYiJvc+iVfVpo5FFE/NiABw8MZ3RU8y5cmMLAF/ZetDQzD5PeWwsPanrN4xjZ34k8MovWNv4YGlsQmJiOE+jbpCaFlvkdfMpEUCbpvOIenEPpTILmUyDQTU9ufddU4LvBdLKU06d4haUdijNpaeG6GokkpKezLcNSjK9WRnKeNTE3bU2+nrmAFgb21LGsTxmBuaERt0FICM7myO3znD60mUiYp9zKewcNyJzKuMn+JdmUZsK2JvoMmH/LfR0NFEoFRwOCWfIjqvcj0mGBfM4+ewi+4J2kpmdwaoLYSSlZ7GpW3VkMhm/34jj9wxzyjRuQMVm/py9e6vI6+/mVpwlS1bSpElAkZeBzkAMkPdDCACmAP6wIgI2pkFwFlR5AaW0YK4ihoOzZpOekqKKLgT0jYdJSa+TcO3UiqcHtqJncxCAjXuX8+veZWrZpKZD7BvLjO87h9nDV2Fn6fAe6/IvpSGDmk45YwXcfUns42ym3ptE86mViYh6+LlLJ/mLZCrTWfKwN0/TQ/EwqszS8qHY6bl97mJJ/mWio6MZPHgwbm5uyOVyHB0dCQgI4NixY6o4Li4uyGQyZDIZenp6uLi40L59e44fP54nvSFDhlChQgXkcnmBD5dCCObMmYOnpydyuRwHBwemT5+eb9y/o/wqGTt06MC9e/c+S3muX79Ou3btsLGxQVdXFw8PD/r06aMqT+5L/9w/IyMjSpUqxcCBA7l//75aWrkvIN7+i46OVov39OlTvvzySywsLNDT08PHx4crV9Q/VPxYPtW2/Ssri/+Jlf8LFy5k7dq1n7sYEonkP+JjvJQu6Br25t/Jkyc/SnklEolEIpFICjJy5Ei1dyqSP+dDP9yXSCR/nf9MN/IaGprUrzGSl3EP6dpuLTraevza5AqHjgxh2XozalTui4tjFWwsPbn++CY+5XpRpVw3AEyM7ahTfTAANt7teHpzP/p317D9RjLJqS94Gn0TB7syJCQ9Y++RcchkGmQrMtTyj098QnLKc5wcKvA06iZb9wzE0b4CAHJTN37+rQciJZKhvY9Tv+Yo9HSNi7xu2tq6VK/Um0uhRzCRaaKrrQvAzfCHfL9hFY3KleWrBp5UdnGgW+W2pKQnY2ZgTm138HO1YN/lBDq366jKMz1bUMapAnuv/05CWjyWhpbciw6nQfFXuFvooaNtgr1FVcq7OAFQ0taEkrYmbLkWwbrLj/C0NiIr4x4Pou+iq2WMpkwG34zA9EUk9sVsuRSRyOmwGMbWdMXZNKeb+tWdqvCkiQ8lbU2o22cEt54/InLbJvTluqSkJ6OpoYmejj6wBLIVkD00p2H6/8nleVvCZ2Vl8erVK4yN370tZ52FbS5ZzLOaTmmt5uhrVETXBZTF4edsME2BbwxBLgNvZRpZS+azc9Y8LJwcsUm3JerILSqt7suldC10Ty6nY9WalHAtjaauDlZNmnDz0S3Ke1vyx5JLefIetWg+dx+cZOW4BWw5+DO9Wg+lQsmCu7X/zzHTA2dTCIvHtqoxbV274qr0wtrc7nOXTPIX0dHQpZntIPZFLSE2U+rx4T9BoYA7tyEuDszNoVRp0CygF5KPIDw8HD8/P0xNTZk9ezY+Pj5kZWVx6NAhBg4cSEhIiCrulClT6NOnD5mZmYSHh/Prr7/SoEEDpk6dyvfff6+Wbs+ePbl48SI3b97MN9+hQ4dy+PBh5syZg4+PD3FxccTFxX2y9fwr6OnpoaenV3jEj2zv3r188cUX+Pv7s3HjRooXL86LFy/Ytm0b48eP57ffflPFPXr0KKVKlSItLY1bt26xcOFCfH19+eOPP6hfv75auqGhoWr3ENbW1qr/x8fH4+fnR926dTlw4ABWVlbcv38fMzOzj75+WVlZn23b/h0pFApkMhkaGp/+m2ETE5NPmn5mZiY6OjqfNA+JRKlQEHLmLAlR0Zja2VKiZg00PuF1VfJ5Va9enaioKNX00KFDSUpKYs2aNap55ubmn6NoEolEIpF8PkIJMc8gPQ109cHKHmT/mTaIn4WhoSGGhoafuxgSiUTyl/lPXVVaNv6BXp23oqOd87IyJe46Gigx0DejfYslVCr7JWcuLCUm7iEOxZtgaGCpWlYIwU9rGrN5ZTUGxJ7HPuUpzRpMYeKI+1Qu9yUApsb2dPniF4b3DaRq+e5qec9Y0YHv5tclJfUlz1+GEhZxFg1NLbQ0dUh6eRcdMnkZ+4Dn8U8KrGjPyFYw48gdLj15yfP0NLUwXbkRQ7/8jYalm+JhWwIAExM7Wtb/ku86dMfO1AFLIyt0tHQwN7RQLbfu+GFazZjIgBVTSX6VRERcKtbjdjLw9yvU8KpHg9JNufn4Ovejg3CzqUSfms2ptfgo/ivvsCbiGcFpCaq0OpRz4uSg+oysWwIHM0eaewl+apGJm6UhK1IMqLE3hVsvLNHV1sRIW4Oz48eybshwAIx1tSlpawLpcOTuj9zSWIW+XBelUPLHtd/ZfGIns7xHkp78PaRPhtZAIUN4r542lx2W/bgy8bcC4ySnwtYz8EJDkwRlMMtTTzIkAegBGr/AFidYbw6JAtKE4M7iHiRlnaHX8iVUatOKp39cI/L3Syhik1mWdJ3HvwxgzroJqvR/XDuOFkOqcvbaMeytimFvldMDQuqrFBJTEoiJOUXkkyMcDNzC8m1z2H/m93ev1H9RbSew1EMjMYOuFtVZ0HcZenKpwuG/pKfLXLZUSaaL09TPXRTJpxZ4Fnp2g7GjYfYPOf/27JYz/xMZMGAAMpmMS5cu8cUXX+Dp6UmpUqUYPnw4Fy5cUItrZGSEra0tTk5O1KpVixUrVjB+/HgmTJhAaGioKt6iRYsYOHAgbm7598IQHBzM0qVL2b17Ny1atMDV1ZUKFSrQsGHDd5Y1t2XwnDlzsLOzw8LCgoEDB5KVlaWKk5GRwciRI3FwcMDAwIAqVarkacG2cuVKHB0d0dfXp3Xr1sybN0+tO7awsDBatmyJjY0NhoaGVKpUiaNHj6rC69SpQ0REBN98842qlRyod+t27949ZDKZ2scKAPPnz6d48eKq6du3b9OkSRMMDQ2xsbGha9euvHxZlGFhcqSlpfHVV1/RtGlT9uzZQ4MGDXB1daVKlSrMmTOH5cuXq8W3sLDA1tYWNzc3WrZsydGjR6lSpQq9evVCoVC/sbC2tsbW1lb192bl7qxZs3B0dGTNmjVUrlwZV1dXGjVqpLZuBYmKiqJJkybo6enh5ubG77+/vvbntsD/7bffqF27Nrq6umzcuDHfLvOmTZuGtbU1RkZG9O7dm2+//TbfFpEFHS8F7cf8yGQyVq1aRevWrdHX18fDw4M9e/aowhUKBb169cLV1RU9PT28vLxYuHChKnzSpEmsW7eO3bt3q7WszK8bw6CgIGQyGeHh4cDr42rPnj2ULFkSuVxOZGQkly9fpmHDhlhaWmJiYkLt2rW5du1aodv/Xfbt24eJiQkbN24E3r81fkJCAr1798bKygpjY2Pq1avHjRs31LZD2bJlWbVqFa6urujq6haYVmBgIHXq1EFfXx8zMzP8/f2Jj48HQKlUMnPmTNX29vX1VTuOPhalUsno0aMxNzfH1taWSZMmqcLy6yI6ISFBrdVs7v49dOgQ5cqVQ09Pj3r16vHixQsOHDiAt7c3xsbGdO7cmbS01882Bw8epEaNGpiammJhYUHz5s0JCwvLk/eOHTuoW7cu+vr6+Pr6cv78+Y++Df7pLu/YxVAXT6bX9eenzt2ZXtefoS6eXN6x65PlmZycTJcuXTAwMMDOzo758+fn6V59w4YNVKxYUXVd7dy5My9evFCFf+ixU6dOHQYPHsywYcMwMzPDxsaGlStXkpqayldffYWRkRHu7u4cOHBAtUxh56+CpKam0q1bNwwNDbGzs2Pu3Ll54hTlmpxr7dq1TJ48mRs3bqjOk7k9a8ybNw8fHx8MDAxwdHRkwIABpLzRy9qbdHR01K5denp6yOVytXkFfeTz5MkTOnXqhLm5OQYGBlSsWJGLFy+qwnfv3k358uXR1dXFzc2NyZMnk52dXei2kkgkEonks3ryAPatg1M74eKhnH/3rcuZ/4nUqVOHIUOGFHgvDRAZGUnLli0xNDTE2NiY9u3b8/z5c1V47rPDhg0bcHFxwcTEhI4dO5KcnPzOvDMyMhgzZgyOjo7I5XLc3d1ZvXp1vnFjY2Pp1KkTDg4O6Ovr4+Pjw+bNm9Xi/P777/j4+KCnp4eFhQUNGjQgNTUVyLlnq1y5MgYGBpiamuLn50dERIRa+d/0yy+/UKpUKeRyOXZ2dgwaNEgV9j73O/nJfUbYunUrNWvWRE9Pj0qVKnHv3j0uX75MxYoVMTQ0pEmTJsTExKiWUyqVTJkyhWLFiql6Jzx48GCedAt79ti+fbtq3VxcXPLcGxa0X4QQuLu7M2fOHLX4uc/FDx48wMXFBYDWrVsjk8lU0yDdn0kkfyf/qcr2t3VqvZxR/S/Sq/PvxCc+4Wn0TZacnMWW4N3Ehe1Wi5udncG9hyd4GRdG4KUVGOhbUNo7ACsLdx48Os3qTe1JSo7Gzak6129vI+WtbuB/uapHcIIz2toGlPFuSbuAJdSvOQIba2+c7crwTY99VGq4gPOP8rZ+znXg2hn2HB5Hu+0H2HP5V8Zv/gmTji24EJLT1bue3Ag7s2LMO3mHukuOsfzcA3Y/kvMkzYiGPs2wNLJWSy8i5iGp2fdpV6MyDcqWZt/1nSSlRVHG3pQSNsaY3wzBPiqRss4VqVzcDz+PstiZmlHG3gylgG+uX2Xg/dcP3zKZjNAXSVRbcAQhM8PZyg0bk5wWyBUdzWnoZUu5YmZUdLLgwfA6NLDUwKWcr/pK6oBWU03svsj52l5DpoGHrTe6ChssH0Tze/+OcGEKlKLQo9fZrTgyA23kRvoFxjEygOUt4JjQoJHuWMKyv6H6G+8eSmiDkxa4awFKJRbZr3AuVZ56X69BR/cn/H4dQMv789AvZkFlz/LMHr6Kb3vOUC3f2K81XzToqhr3PVeLIdWo28ub+SMWsvjb9fT54huWjdtKl2Z9371S/0VGcuhYCirZw6ssuBoFm29DZOLnLpnkL6StIbX8+9cLPAszpsLbFa0vX+bM/wQV7nFxcRw8eJCBAwdiYGCQJ7wo44ENHToUIQS7d+8uNG6uP/74Azc3N/bu3YurqysuLi707t27SC3bT5w4QVhYGCdOnGDdunWsXbtWrZvrQYMGcf78ebZs2cLNmzdp164djRs3VnWVHhgYSL9+/Rg6dChBQUE0bNgwT/f1KSkpNG3alGPHjnH9+nUaN25MQEAAkZGRAOzYsYNixYoxZcoUoqKi1FrQ5fL09KRixYqqSstcGzdupHPnzkBOxVy9evUoV64cV65c4eDBgzx//pz27dsXeVseOnSIly9fMnr06HzDC9uHGhoaDB06lIiICK5evaoWVrZsWezs7GjYsCGBgYFqYXv27KFixYq0a9cOa2trypUrx8qVK4tU5vHjx/PFF19w48YNunTpQseOHQkODlaL8+233zJ06FCCg4Px9/fPk8bGjRuZPn06s2bN4urVqzg5ObF06dI88d51vBRlP75p8uTJtG/fnps3b9K0aVO6dOmiOmaVSiXFihVj27Zt3L17lwkTJvDdd9+xdetWIKcLwfbt29O4cWNVXtWrVy/S9oKcjypmzZrFqlWruHPnDtbW1iQnJ9O9e3fOnj3LhQsX8PDwoGnTpoW+fCrIpk2b6NSpExs3bqRLly4flEa7du1UlYFXr16lfPny1K9fX+23/eDBA7Zv386OHTsKHMs4KCiI+vXrU7JkSc6fP8/Zs2cJCAhQfRAyc+ZM1q9fz7Jly7hz5w7ffPMNX375JadOnfqgchdk3bp1GBgYcPHiRX788UemTJnCkSNH3judSZMmsWTJEs6dO8fjx49p3749CxYsYNOmTezbt4/Dhw+zePFiVfzU1FSGDx/OlStXOHbsGBoaGrRu3RqlUqmW7vfff8/IkSMJCgrC09OTTp06SS+W3nB5xy4WtO1E3BP1noHinj5jQdtOn6zCffjw4QQGBrJnzx6OHDnCmTNn8nwIk5WVxdSpU7lx4wa7du0iPDycHj165EnrfY8dyDluLS0tuXTpEoMHD6Z///60a9eO6tWrc+3aNRo1akTXrl1VlfSFnb8KMmrUKE6dOsXu3bs5fPgwJ0+ezLOehV2T39ShQwdGjBhBqVKlVOfJDh06ADnXqkWLFnHnzh3WrVvH8ePHC7zufaiUlBRq167N06dP2bNnDzdu3GD06NGq392ZM2fo1q0bQ4cO5e7duyxfvpy1a9f+o4bAkUgkEsl/0JMHcP4AvHqr0vZVSs78T1jh/q57aaVSScuWLYmLi+PUqVMcOXKEhw8fqq79ucLCwti1axd79+5l7969nDp1ih9++OGd+Xbr1o3NmzezaNEigoODWb58eYEtzNPT06lQoQL79u3j9u3bfP3113Tt2pVLl3LqJ6KioujUqRM9e/YkODiYkydP0qZNG4QQZGdn06pVK2rXrs3Nmzc5f/48X3/9dYEfcS9dupSBAwfy9ddfc+vWLfbs2YO7u7sq/GPd70ycOJFx48Zx7do1tLS06Ny5M6NHj2bhwoWcOXOGBw8eMGHC64ZyCxcuZO7cucyZM4ebN2/i7+9PixYt8tyvvevZ4+rVq7Rv356OHTty69YtJk2axPjx49Xe1RS0X2QyGT179lTrhQhgzZo11KpVC3d3dy5fvqyaFxUVpZqW7s8kkr8Z8RkkJiYKQCQmJn6O7PMYMclYfDPVUnxxfq1wPbFMcHqtWL5vjBBCCKVSKSJiHolXGWkiNj5CnDr/s5g0x0M8iryoWn7XwW/FwLGIKfNKiO17R4iBYxF7Ts4R2YpskZz6UgyeaC+aDvUQA8ciLl5bL85fWSMGjkUcODZVrRxhz++Je1HBqum0jFRx6OZe8ehFmBBCiC27BoiBYxEeY8YIv4UbxMztq4Vllzbi0r3Xy0QnPBM15q0T8uGbxe1n8WLz1XCRma3Id72fxEWKbRd+FVHxT8XTuMdi49nVIiLmYU5gerpQNvMX4uueeZZTKJRi/50nQrZ4g6j162G1sJG7rgn5iC0iODpn30YlpqnCMrKyRce1Z8WiU6F50pxy8JaYfexuvuXMFf7ouchMLyOEQAiRkG8chUL5zjTex91MIYbHCxGVLcSjTCG2pgoRmilERNYzIYS+ECJn28QphPCNFmJM/kXK16Sl34hvfuwhBs7oLBwaIG6EXvlo5f5XOxEuxIKLOX/Xoz53aSSS/5xPdv3OzhaiW2chmjYq+K9bl5x4H9HFixcFIHbs2FFoXGdnZzF//vx8w2xsbET//v3zzJ84caLw9fXNM79v375CLpeLKlWqiNOnT4sTJ06IsmXLirp1676zDN27dxfOzs4i+43t0K5dO9GhQwchhBARERFCU1NTPH36VG25+vXri7FjxwohhOjQoYNo1qyZWniXLl2EiYnJO/MuVaqUWLx4sWo6v+2xZs0atXTmz58vihcvrpoODQ0VgAgOzrlvmTp1qmjUqJFaGo8fPxaACA3Ne6+Qn1mzZglAxMXFvTPeo0ePBCCuX7+eJyw4OFgA4rfffhNCCBESEiKWLVsmrly5IgIDA8VXX30ltLS0xNWrV1XLyOVyIZfLxdixY8W1a9fE8uXLha6urli7du07ywGIfv36qc2rUqWK6vjJLeeCBQvU4ry9batUqSIGDhyoFsfPz0/teCvseBHi3cf12+UeN26cajolJUUA4sCBAwUuM3DgQPHFF1+oladly5ZqcU6cOCEAER8fr5p3/fp1AYhHjx4JIXLWHRBBQUHvLKNCoRBGRkbijz/+UCv3zp07C1ymdu3aYujQoWLJkiXCxMREnDx5Ui387TLnxs/15vY7c+aMMDY2Funp6WppFC9eXCxfvlwIkXNO0NbWFi9evHjnunTq1En4+fnlG5aeni709fXFuXPn1Ob36tVLdOrUSQiRd7u+ffwURe3atUWNGjXU5lWqVEmMGZPzjJTfbyo+Pl4A4sSJE2rlOHr0qCrOzJkzBSDCwsJU8/r27Sv8/f0LLEtMTIwAxK1bt9TyXrVqlSrOnTt31M4v/3WK7GwxqJib6Iw8/z+ZrhjkWFwoPvJ1NSkpSWhra4tt27ap5iUkJAh9fX21387bLl++LACRnJwshPjwY+ft4zY7O1sYGBiIrl27quZFRUUJQJw/f77A8rx9/npbcnKy0NHREVu3blXNi42NFXp6eqr1LMo1+e3fZkH3DW/btm2bsLCwKDSeEPmfe/OzfPlyYWRkJGJjY/MNr1+/vpgxY4bavA0bNgg7OzvV9Jvn3HdddyUSiUQi+UsoFUL88YsQWxcV/PfHLznxPrLC7qUPHz4sNDU1RWRkpCo893720qVLQoic+wJ9fX2RlJSkijNq1ChRpUqVAvPNfeY+cuRIvuH5PX+9rVmzZmLEiBFCCCGuXr0qABEeHp4nXmxsrADyPEPlevu+xt7eXnz//fcF5vu2t+93Cnumye8ZYfPmzQIQx44dU82bOXOm8PLyUivX9OnT1dKqVKmSGDBgQIHpvv3s0blzZ9GwYUO1NEaNGiVKliwphCh8vzx9+lRoamqKixdz6psyMzOFpaWl2vuF/J5ti3J/JpFI/jr/6ZbtuepUH0qokTPbs6CjtScDtbXoVPc7AKISnnIy+DDXIy5jbupErar9mTjiHi6OlVXLN60/iTIlW5GQ+AQ9XRNq1Z1MnMyAx7ERKLIzycx4SbYii8b1JuPj3YLSJZrTsNYYKv2/+/lcbtYeqi7gj5z+kXW/dSE67jExyc9V+XRsswltEz9qufkwtHk36jb4hqCXWgQ9iafxshNEJij4to4JV76pRCk7UzqWd0ZbM//d7GDmSNsqXbA1tcferBid/XriZOmaEyiXM9LTn6G2fnmW09CQUdfDli6mxenu5kpiYk4L49SMbO5EJzK9mS8lbIxZcDIEuwm7OBj8DICk9Gx23X7Kvrt5x12edzKERafvqaZjU16SrVBvmeLsYo22fAGwBsgZQ/Pq1cvs25fTjemdqEQMx2xj+uE7+a5v4bKBBsBQAA6lw9ZXMCYBakRlMPrJS3pHp1Anxo4XihdATgs2TcBcA0wK7n01j4n95jFv1Bq+bNaXvu1Gsvf0NjqPaURmVuYHlv0/wu7/X2L6WkNaFvweDFmFjCcgkUj+/u7cztui/W0vY3LifURCiI+Wzru64H6bUqkkIyOD9evXU7NmTerUqcPq1as5ceIEoaGhREZGqsY3MzQ0ZMaM1z2mlCpVCs03xtq1s7NTdb1769YtFAoFnp6easufOnVK1QVzaGgolStXVivP29MpKSmMHDkSb29vTE1NMTQ0JDg4WNWyvag6duxIeHi4qjv+jRs3Ur58eUqUyLnXuXHjBidOnFAra27Ym11Gv8vH2Ie5aeTuQy8vL/r27UuFChWoXr06v/zyC9WrV2f+/PmqZZRKJeXLl2fGjBmUK1eOr7/+mj59+rBs2TIAZsyYobZeb267atWqqeVfrVq1PC3bK1as+M4yF2U/wruPl/dVpkwZ1f8NDAwwNjZWS+unn36iQoUKWFlZYWhoyIoVK977mCmIjo6OWv4Az58/p0+fPnh4eGBiYoKxsTEpKSnvnefvv//ON998w5EjR6hdu/YHl/HGjRukpKRgYWGhtu8fPXqkdjw7OztjZWX1zrRyW7bn58GDB6SlpdGwYUO1fNavX1/k301Rvb3NP/T4eTMdGxsb9PX11YbZsLGxUUv3/v37dOrUCTc3N4yNjVXdJL69b99M184upzetDz2+/21CzpzN06JdjRDEPX5CyJmP22vMw4cPycrKUjsfmZiY4OXlpRbv6tWrBAQE4OTkhJGRkeq39659XJRj5+1lNDU1sbCwwMfHR20ZoMjnrzNnzqj91jZu3EhYWBiZmZlUqVJFlYa5ubnaehblmlxUR48epX79+jg4OGBkZETXrl2JjY1V60L/zwoKCqJcuXIFjud+48YNpkyZorYuffr0ISoq6qOWQyKRSCSSjybmWd4W7W97lZIT7xN41710cHAwjo6OODo6qsJLliyJqamp2rOhi4sLRkZG+aaxceNGtevymTNnCAoKQlNTs8jPNQqFgqlTp+Lj44O5uTmGhoYcOnRIdR/k6+tL/fr18fHxoV27dqxcuVI1tJW5uTk9evTA39+fgIAAFi5cWGBvaS9evODZs2cFPuPAx7vfefv+EchzL5i7DZOSknj27Bl+fur1H35+fnme0d/17BEcHJxvGvfv30ehUBS6X+zt7WnWrBm//PILkNMbYkZGBu3atXvnukr3ZxLJ34vW5y7A30HzhlNw9mzCl1lZdHKvpRamTTbPw4+iFX+Xah45YVHP73I75A/q+n2DlpYO2lpyenfezsGT09h3dAKtms7HzqU6xcydWP78Ac0G36GmsS2mb3TZ0rJxTpcvd0L3c+n6r3Ro+RP6emaq8OB7hwh/cpERzRdhYWwLgJGhFTUqduLO/9+/Pk1IY9etp2QpBDJkHAqJpkM5Z76q0lKVTlZWOpqa2mhovH7RWpC0jHR2XzhH62o10NXR4ZpbGSwM5Oy/+4xev19l3ZfVaOSWM469rrYmG76sxrJlSxi15jLjJ01FpmfB8fvPMdHVBqC0nSlVnS1wNsvpmtfSUM6D75tjoqedJ+8rI/zZe/sZh4Kj8LUTHL61F2/70lQq/nYXo3XVpvbu3UVkZAR169ZHT1sTBxM9LA3kzN7xG5ExL/iuzWBkMrDNKTZCCJ4kZyA30MVaE7IERCvAUQuSlNlsSqtJO707WGhCf0NIEbA5DWTacrI0NNCPCaGFqw8a9xPY13EaZSZ/gWPLihz//zvTJCVMS4JWelBdnt82hkv3oIwLmBtB1TK1qFqmFt3HNefG/StkZmWgoy11l10gLwsw14XNd0BfG7KUkK0E7cKPb4lE8jdWhO7T3yteEXl4eOQ7rvj7iI2NJSYmBldX1yIvY2dnh5aWFp6enqp53t7eQE5FQ926ddW6l37zxbe2tvo1VCaTqbp4TUlJQVNTk6tXr6pVsAIFdhuXn5EjR3LkyBHmzJmDu7s7enp6tG3blszM9/sgzNbWlnr16rFp0yaqVq3Kpk2b6N+/vyo8JSWFgIAAZs2alWfZ3IfXwuRuw5CQkDyV2EWV+xD9rn1YuXJlzp59XSllZ2dHyZIl1eJ4e3uzfft2APr166fWHb69vf17lSm/YQ0+xLuOl4+Z1pYtWxg5ciRz586lWrVqGBkZMXv2bLWxfvOjoZHzQeibH03kjin/Jj09vTwftHTv3p3Y2FgWLlyIs7MzcrmcatWqvfdxWq5cOa5du8Yvv/xCxYoV3+vDmTelpKRgZ2eX73jMbw5nUJR9q6en9858IGd8eQcHB7UwuTyfm88/4V37vKj77u10ZDJZocdlQEAAzs7OrFy5Ent7e5RKJaVLl86zb99OF/jg4/vfJiEq+qPG+5hSU1Px9/fH39+fjRs3YmVlRWRkJP7+/oXu46Kc0/KL865jpbDzV8WKFdWuyTY2Njx8+LDQ9fxY1+Tw8HCaN29O//79mT59Oubm5pw9e5ZevXqRmZmJvn7BQ6a9j3eddyBnfSZPnkybNm3yhOnq6n6UMkgkEolE8lGlF7Gysajx3tPHeBZ7VxotWrRQ+/DPwcGBo0ePvlf6s2fPZuHChSxYsEA1XvqwYcNU92SampocOXKEc+fOqYbv+f7777l48SKurq6sWbOGIUOGcPDgQX777TfGjRvHkSNHqFq1qlo+hd1nfMz7nfzu+96e9yHPDH/m2aOw9Qfo3bs3Xbt2Zf78+axZs4YOHToUut7S/ZlE8vciVbb/n49zNXzymW+gawLJ4Vg7V1LNO3Z2DheuriHWxI2OZduxaUcf9I3s8avYEw2ZJtXKd8NA35wXma8YFHaRSoYWXLJ3zyd1uBm8h6s3N1OvxnCci71uxdS32x7SMpIoffcMTnJDzpdtihCCB89DsTG2xVjfFAdTfcLGNcfCQI6+jhY13KwoYWOsSiMjM5WJs11xLlaZ/t335pt/Slos+rqmaGhosuzAXkb8soyf+g1mQNOWnBhUn4fRz+i46wLR8ZmsjcvATus6FkZW6BtYYqqji5dXCRKS4zkSso/KHtV4PKklcYmxZCsUNPCypbabBWFh99n56BaxyUn0tmgKN4AeqI257miqz/Dd13E208fbxoiSVvY09HFWhd94Gk96loIqLpZq5e/XbzBJSYno6xvgpg/3xwUAUHbobMKin/HwxiC0tWXsWpgTP2jsFjp2bY65iRbni2kxMzmTVana7Lb4g9tZAUxPnkg2SgYZwq0HYHgftL1hoAU0i7lLyTKlmZYKcxS6+NyKRJl9APienFbuThx7Es5mbRc0ZPlXtj+OgaCHINeCat6v56+evIvMzAz09T7Oy/V/NTO9nEp3JxNwN4OQ2Jzx2/2Lg5bUWYdE8o9UQCuqD45X5GzN8ff356effmLIkCF5KsESEhIKHfN74cKFaGho0KpVqyLn6+fnR3Z2NmFhYRQvXhyAe/dyendxdnZGS0tLbeyyoipXrhwKhYIXL15Qs2bNfON4eXmpxvfK9fZ0YGAgPXr0oHXr1kDOA1x4eLhaHB0dHdX40e/SpUsXRo8eTadOnXj48CEdO3ZUhZUvX57t27fj4uKCltaH3ZI2atQIS0tLfvzxR3bu3JknvLB9qFQqWbRoEa6urpQrV67AeEFBQWofAPj5+REaGqoW5969ezg759y7mJubF9g68MKFC3Tr1k1t+l155yd3P76Zztv7sSiKuh8LExgYSPXq1RkwYIBq3tstN/PLK7eFd1RUFGZmOR+dFjSOeX55/vzzzzRt2hSAx48f87KwHjLyUbx4cebOnUudOnXQ1NRkyZIl750G5BzP0dHRaGlpqVpif6gyZcpw7NgxJk+enCesZMmSyOVyIiMj/1RL/D/rzX2Xe/wWdd+9S2xsLKGhoaxcuVJ1HnvzQxdJ0Zja2X7UeEXl5uaGtrY2ly9fxsnJCYDExETu3btHrVo5H66HhIQQGxvLDz/8oGrNdeXKlY9ajvdR2PlLT08vzzW5ePHiaGtrc/HiRdV6xsfHc+/ePdXvsijX5Lfld568evUqSqWSuXPnqj5yKWw8+Q9RpkwZVq1aRVxcXL7Xr/LlyxMaGvpB9ycSiUQikXwWukWsoC1qvI/I29ubx48f8/jxY9X90N27d0lISMjzUXdBjIyM1Fq9Q04LbqVSyalTp2jQoEGhaQQGBtKyZUu+/DKn912lUsm9e/fUyiCTyfDz88PPz48JEybg7OzMzp07GT58OJBzz1OuXDnGjh1LtWrVVB/bv11WFxcXjh07Rt266g3p4K+733mbsbEx9vb2BAYGqj1bBQYG5ttzXEG8vb0JDAxUmxcYGIinpyeamppF2i9NmzbFwMCApUuXcvDgQU6fPq0Wrq2tnec+Ubo/k0j+XqTK9kLoyk0oXSIAB7uyqnnN6k9mU3w01y6vwUpDxsXrv1KuwRwuhV+jWd3vVfGsdfTYW6o+zvKCK1C/aDqP2lUHYW9bWm2+XMcAuY4BlYwsKaaTc9F/mfyC8/dP42zpRm3vnBOzo9nrtHMr2p8mpLHgVCiDa7hib1MaW+ucWt23u7mNfhHCzMVl8Kv0Ne1bLKFDzTq8SIynTbXXLwN2ng/kyrH1tP12Dg20Y5i1YyMNKpVk000NQl+aEjSiKRWqVuL8/dNYGFoR9uQh1UYPYWTrdsz+qi8HD+5j585t3NWQceXlC3oWa4zGRY2c3tqdXq+vjpYme/vUIj1bQYd15zDRc8TO9HVrnYCVp3mRks6r2e3V1sHGxhYbm7wviY5O/ZG0jHSOBcrQeqMhgWFxG2oeu4Zn28pAMhW1BnBXow/FNHvjo10VR81O+Op0UsXX14CGuvBTKtQqpoOmpib7X4HMyoIpcSvRMfkROAw8AJxYPbsDZGsyYMYeQP3DAAAPB9DWgmJvBWlpaqGlJ/0ci0RLAzzM4U4MOJtARCKEJ0B6NhhKvQJIJP9IpUqDpeW7u5K3tMqJ95H99NNP+Pn5UblyZaZMmUKZMmXIzs7myJEjLF26VK3rsOTkZKKjo8nKyuLRo0f8+uuvrFq1ipkzZ6o93Dx48ICUlBSio6N59eqVqgKqZMmS6Ojo0KBBA8qXL0/Pnj1ZsGABSqWSgQMH0rBhQ7XW7u/L09OTLl260K1bN+bOnUu5cuWIiYnh2LFjlClThmbNmjF48GBq1arFvHnzCAgI4Pjx4xw4cEDt2urh4cGOHTsICAhAJpMxfvz4PF9su7i4cPr0aTp27IhcLsfSMu81D6BNmzb079+f/v37U7duXbUW3gMHDmTlypV06tSJ0aNHY25uzoMHD9iyZQurVq3K0xIwPwYGBqxatYp27drRokULhgwZgru7Oy9fvmTr1q1ERkayZcsWVfzY2Fiio6NJS0vj9u3bLFiwgEuXLrFv3z5VfgsWLMDV1ZVSpUqRnp7OqlWrOH78OIcPH1al880331C9enVmzJhB+/btuXTpEitWrGDFihWFlnnbtm1UrFiRGjVqsHHjRi5dusTq1asLXe5NgwcPpk+fPlSsWJHq1avz22+/cfPmTbXulYuiqPuxMB4eHqxfv55Dhw7h6urKhg0buHz5slpvAS4uLhw6dIjQ0FAsLCwwMTHB3d0dR0dHJk2axPTp07l37x5z584tcp4bNmygYsWKJCUlMWrUqCK1GMiPp6cnJ06coE6dOmhpabFgwYL3TqNBgwZUq1aNVq1a8eOPP+Lp6cmzZ8/Yt28frVu3LnRogDeNHTsWHx8fBgwYQL9+/dDR0eHEiRO0a9cOS0tLRo4cyTfffINSqaRGjRokJiYSGBiIsbEx3bt3f++yfwg9PT2qVq3KDz/8gKurKy9evGDcuHF/Ol0zMzMsLCxYsWIFdnZ2REZG8u23336EEv+3lKhZA/NiDsQ9fQb5Dbchk2FezIESNWt81HyNjIzo3r07o0aNwtzcHGtrayZOnIiGhobqOuPk5ISOjg6LFy+mX79+3L59m6lTp37UcryPopy/3mZoaEivXr0YNWoUFhYWWFtb8/3336teDkPRrslvc3Fx4dGjRwQFBVGsWDGMjIxwd3cnKyuLxYsXExAQQGBgoGrIko+pU6dOzJgxg1atWjFz5kzs7Oy4fv069vb2VKtWjQkTJtC8eXOcnJxo27YtGhoa3Lhxg9u3bzNt2rSPXh6JRCKRSP40K3vQM3x3V/J6hjnx/mINGjTAx8eHLl26sGDBArKzsxkwYAC1a9d+r+eGt7m4uNC9e3d69uzJokWL8PX1JSIighcvXqj1vJbLw8OD33//nXPnzmFmZsa8efN4/vy5qrL94sWLHDt2jEaNGmFtbc3FixeJiYnB29ubR48esWLFClq0aIG9vT2hoaHcv39f7YPwN02aNIl+/fphbW1NkyZNSE5OJjAwkMGDB/9l9zv5GTVqFBMnTqR48eKULVuWNWvWEBQUxMaNG4ucxogRI6hUqRJTp06lQ4cOnD9/niVLlvDzzz8DRdsvmpqa9OjRg7Fjx+Lh4ZGn577cjxX8/PyQy+WYmZlJ92cSyd+M1Ay0EHEJEew7OoGjZ35UzTMzdcTNrgznS3RgblICoMRUS5viNh7EJz4h6f9jrAM0My9GaQOzvAn/n46OvqqiPTgtgcU3LzB23SrSMzOJz8pgmXs1lrjnfA1maWRN5eJ++DpXUEsjOuEZgfdOkpmdwcn7z+m95RJzToSw6/ZzhvQ+Tusms4mMDefXs6uIfBmuWs7QwBJXx2o42pcHwMHCkh+698HW7PWX7AObtWT3qO/41ceVdZvXsfF4EAlZchKztUh+lU3SqxT0dQzwLxOAnZkDLja2NC5fiZolc/oJ8C1blho1ajN74DccnfojGt9pwALUKtpzNSlpT+syjkRMaMGazlXgKfAoJ+yHAF86lTLE8qtezD5ceMsHS2MTnKxs+KoVdA14Pd+jTz1WDanNaHs9QI9KGS9pf3MHmbED0JLto47ub5j9/1dR0QO+bgxfWT5luOFEyuvkjOV+0AoWmMACDX1eifFAGFAPgBHdJjOhQTuczPJ/Wa0hAzdb0JHq1f+cx0nwMAESM8DfDbr7ShXtEsk/maYmfN3/3XG+7pcT7yNzc3Pj2rVr1K1blxEjRlC6dGkaNmzIsWPHWLp0qVrcCRMmYGdnh7u7O127diUxMZFjx44xZswYtXi9e/emXLlyLF++nHv37qm+9H72LGcsOA0NDf744w8sLS2pVasWzZo1w9vbW61S+EOtWbOGbt26MWLECLy8vGjVqpVaC0M/Pz+WLVvGvHnz8PX15eDBg3zzzTdqXYzNmzcPMzMzqlevTkBAAP7+/pQvX14tnylTphAeHk7x4sXfOf60kZERAQEB3Lhxgy5duqiF5X5BrlAoaNSoET4+PgwbNgxTU1NVhcXatWsL7da7ZcuWnDt3Dm1tbTp37kyJEiXo1KkTiYmJeR4wGzRogJ2dHT4+Pnz77bd4e3tz8+ZNta/rMzMzGTFiBD4+PtSuXZsbN26oxo/LValSJXbu3MnmzZspXbo0U6dOZcGCBXnWMT+TJ09my5YtlClThvXr17N58+Yit17I1aVLF8aOHcvIkSMpX748jx49okePHu/dVVxR92Nh+vbtS5s2bejQoQNVqlQhNjZWrZUoQJ8+ffDy8qJixYpYWVkRGBiItrY2mzdvJiQkhDJlyjBr1qwivxRYvXo18fHxlC9fnq5duzJkyBCsra0/eB28vLw4fvw4mzdvZsSIEe+9vEwmY//+/dSqVYuvvvoKT09POnbsSEREhGqswKLy9PTk8OHD3Lhxg8qVK1OtWjV2796t6gFi6tSpjB8/npkzZ+Lt7U3jxo3Zt29fkYezCA8PRyaT5dvl/fv45ZdfyM7OpkKFCgwbNuyjvNDR0NBgy5YtXL16ldKlS/PNN98we/bsP53uf42GpibdFv7/w5W3z6H/n+62YA4an+C6Om/ePKpVq0bz5s1p0KABfn5+eHt7q85PVlZWrF27lm3btlGyZEl++OEH5syZ89HLUVRFOX/lZ/bs2dSsWZOAgAAaNGhAjRo1qFBB/Tm9sGvy27744gsaN25M3bp1sbKyYvPmzfj6+jJv3jxmzZpF6dKl2bhxIzNnzvwo6/4mHR0dDh8+jLW1NU2bNsXHx4cffvhB9SGav78/e/fu5fDhw1SqVImqVasyf/58VY8uEolEIpH87cg0oGwhvcuUrZkT7y8mk8nYvXs3ZmZm1KpViwYNGuDm5sZvv/32p9NeunQpbdu2ZcCAAZQoUYI+ffqQmpqab9xx48ZRvnx5/P39qVOnDra2tmq99hkbG3P69GmaNm2Kp6cn48aNY+7cuTRp0gR9fX1CQkL44osv8PT05Ouvv2bgwIH07ds337y6d+/OggUL+PnnnylVqhTNmzfn/v37AH/Z/U5+hgwZwvDhw1XvAA4ePMiePXvw8PAochrly5dn69atbNmyhdKlSzNhwgSmTJlCjx49VHGKsl9yu83/6quv8uQxd+5cjhw5gqOjo6pnMen+TCL5e5EJkd+n7p9WUlISJiYmJCYmYmxsXPgCn1nIg6NYWbhjYeaimpeSlcn4sPN0tC9JFWMrnme+wkZHjxGTjdHTNWHamMd50jl4YjoXr60joNF0yvu0yxNe4fofXEuOhcVbOTd1Dv1T73M/LYHjDp5UcSt4HNILD85yL+ou/mVa0PO3UPbffcaC1uXoW90D3f+PZR2V8JTAeyfx86yDoZY2R8/MplbVgWrrVJBshQKPvt2xNTPj2y860rKqHwBpGansuLyZYuZO1CnZKN9yPXpxn5YV2qOrrc+lsLO8SIqmadnWaGkWoba5FRALnAI0oN/Sn1l+YCdNG3zNviF5t1/hcrtaUX+plJWd09ocggF7wCSfZTcDpYAyAIxNhF/TYKM51Pq4w2NKikKhhKRMMPt/pcKjBAiLh1pOoCON3y6RfCqf/PodeBZWLFVv4W5plVPR7vdxW99JXuvTpw8hISGcOXPmcxclj4kTJ3Lq1Kk/XSn4X9CwYUNsbW3ZsGHD5y6K5G/uxIkTtGnThocPH6q675f8O13esYv1Q0cQ9+Spap65YzG6LZhDpTat/pIypKam4uDgwNy5c+nVq9dfkqdEIpFIJBKJypMHEHRGvYW7nmFORXsxqfttyd/HmTNnqF+/Po8fP37vD7YlEsnnJ7WvLYIS7nnH0jDU1mF+iZyxPNY/D6P7vbPMdC5PZnYG2W+0bH9TSsoLYuMf8cvm9tjbBGNrXUItfIpzOa7FRlN+dAmqlShJy0dpnEtPJL+qQyEEaZmpGMgNqeBaheLWnlgZWzO/pRa1nVNo72uErrYmz1/ew9TIHjtTB3aGujIn8A5z/SI5dmYO+nrm+NcZmydthVASl5WJlU5ORaaGTIaTlTVutnaqinYAHS05xcyd0de15uez9+lV1Q25qs/2DAzkqzDU9eXwrX3cjEoFdClpo0QgUCoFgY9iqOpiydXHcey984zx/qXIUih5mZKBi4UhdIHs+CxS45IxsTTnp6/70r9pS7wdcrqNf54YzfPEZ5R2LItGkb5CrAKkklOp/pq26lfgzUsFZAO2eTZ6J7Wp3sShFXGDKhZ+gNSi+i+nqfG6oh3gXmzO2O2+1mAljXsvkfxj+dWAqtXgzm2Ii8sZo71U6U/Sov2/bM6cOTRs2BADAwMOHDjAunXrVN2b/d0cOHDgg8fQ/jdLS0tj2bJl+Pv7o6mpyebNmzl69ChHjhz53EWT/APs37+f7777Tqpo/w+o1KYVFVoGEHLmLAlR0Zja2VKiZo1P0qI91/Xr1wkJCaFy5cokJiYyZcoUIKcXEolEIpFIJJK/XDF3cHCDmGeQnpYzRruV/Wdp0S6R5CcjI4OYmBgmTZpEu3btpIp2ieQfSmrZ/hFcSIphSNhFQl4l0v5Qf3SzUpjxXTSxQoaLoaVa96ch948SFnGWJvXGo6Hx4S85bkZeIyjiCg1LN8PO7PXY5tEJzzh8ay+livniZGzBlHlelCvdlp6dfqPp8pPEPj/P7v5teRYdxLPoWzyMCGRziAfhL2I5MWMuJYo5MezBBTZGhXKyfAtKvaML/Fwjd19n7okQRtQtwZyWOd2YpGXEcfnhNLwd0rj2qBkXIxN5kurJyo6VAVgf+Iju2y7wo1VZgpzi2XQ1gqG1PFl3+REpGdk8HB+Ao5kBG2cu4sKB44z79SdsnBzU8j1+5xBP4iJoW/kV+vLpwFFyW57nrwOQBvxRYIyaLyBeCbfzDgOv5ofV37Fky0yWjN1Eq3qd3h1Z8ullKCAhHWykinaJ5FP6t12//6vat2/PyZMnSU5Oxs3NjcGDB9OvX7/PXSzJe3j16hUBAQFcv36d9PR0vLy8GDduHG3atPncRZNIJP9x169fp3fv3oSGhqKjo0OFChWYN28ePj4+n7toEolEIpFIJBLJ387atWvp1asXZcuWZc+ePTg4OBS+kEQi+duRKts/ouVRoaREnqe2ri6zzyxkq28/fnApzxhH9RcLs08E81SeyqTKZXgQeQ0QlHQow4UHZ/C291GrPM/Ps/gnXHl6k71pKYz1rourkfoYm/GpcRjrmaDIzmDTzj6ULhFARd+OvIx7yKQ5xfH28GfgVwdZtbEtIQ8Os+dpI+5HJzCmbUu87D1IkL/ElDTq+rbCxbjwsS8fx6dSZ8kxHsamEjGxBU5mBjyJjeD43UOUcSqPu00JDHUN1ZaJiExl3PibdJI7UWqmKTejEjgYEsWGwDvU8HLERE9OfU9bSsU94uqxM/ScPAp9I/U0UtJTSEiNpZjFAeBb4CRQttDyvsuCZEgSMKGQw/JxdDjbj26gV+uhGBn8e45hiUQieZd/6/VbIpFIJBKJRCKRSCQSiUQikUgkkg8hVbZ/Ij/u6Ms687LM822B//8rz6NfhJCUpYnX7CtgrmR6Dx+8om8jhMDPsw5Hbu/Dx7EcxcydOBl8hCrF/XCydM2T9pmQ4/wS85C1aDPDpTxj/1+ZL4RgUuQNyhqY0drSOc9ySqWC/ccm4eZcg5Ke/igU2WRlvyJToWTh/tW4Wxeny5zFNK9ammEtG1PTqx7aWjldpD9PjCL46S0qF/dDX5639fDZhzHceBqHvo42uy6eZ2idkvi6ORKX/JLzD05Tw6subtYeasv033GLjSmZrC5nQzufYjx/Hs13342ktG8FxkTY41/Clj/61FbFT0xL4OTdw5RxKo+rtTSmjkQikfzV/gvXb4lEIpFIJBKJRCKRSCQSiUQikUiKShqz/RMZ3WY5o9+YzsrOYNaScliaF2drr32czX5BT1sPTO08AdDV1qVlhfYY6RnzIjGajKwMYlNeEhRxhWoetbAyfj1WR+Xi1XGw8aRcWjLtzOw4eHwaZUu3RcPUmWmRN6lmbJVvZbtMpoGHax1cnasDoKmphaamEbrA+LbD2Xb2FAIo61yWeqUaAxDx4jnFLCx5Fv+EyNhwPOy8VZXtia8y+fnsfXpUdkOTDAwJ5FSoJnsewKlzk0jYshshlFgb22Kin7c7euMaXphna6JhlPO9h6mpGVWqVKNMmXLc61IGCwMdjp2Zi6N9eV5mWvM07inpIpHUzNQ/v4MkEolEIpFIJBKJRCKRSCQSiUQikUgkEonkT5Aq2z+xhMSnZGWnY2VRnHo1RmBqUgy/0o6UepaEbtYrdA3MVXFN9E0BsDW158savXj44gG3Hl8nLUO9clmurYubWTH6Gim4FXKIvUfHk5j8jA4tf+akTwMc5Ub5luX67d/5ZXN7mtSbSLMGk/KEt6tRm6hSPpiamDDi4WVcYlIZMn0a37XrTMPiaZSz8cLBzFEVf1vQY5acvg6K5zxJiMPJWEETbzdC75+mec0OAFga7aWx70ugRZ78hpppUvLKJgwNzcGnGXK5nK+/HqgKj094zM4DI7E09eHsg7Icfx5F/KYdxP9xi4unVlNxYXc0daRDWCKRSCQSiUQikUgkEolEIpFIJBKJRCKR/PWkbuQ/sanzShCf9IQ5ExLR0NAE4EVSNAdv7MHFqji1StR/5/KZ2Zno/L8r97dVmXeYJwlpbG+VQkmPBig1dNh7fQclHcpQ3rVynvhJydHsPTKe2tUG42BXpsA8rybHUjFoL620LUjdf4ZutSpz4XhbSpZuT706E/CyK4lMJiMtM5utF39Hg6ScBbXL061qxbdScweeAKmAJlv3DMbE2A7/Ot+RlZ3J/HUtyJSZs/VFRx7EpjOzuS89q7jxMjUDVwtD7oTuZ83q30hMlOHZvDOjAhpxvOksog7dpFX4IgwcLd65/SQSiUTy8fyXrt8SiUQikUgkEolEIpFIJBKJRCKRFEZqFvyJ1ajSj6SU56qKdgArIxuqe9bGxtiu0OULqmgHqOhkjr2JHlXLtwIgLSMVUwNzjPTyrwAxNrKlc5uVeeYrFFloamqrpisYWXDMpxE++mZYVW0OgJflRmKU2lwKC2T/9j8YPvhb9HW0aFS6Bs8To9DV1sPLriQAT2NfYmNqhpamJnAASAM0USiyuXR9Pbo6luzdHsHXfXvy+OERXil1ufUqACO5FnramnTecI5DIdGETwjA2bgaelHhPKrkxuhjsdjbhdN2wwBeRSVIFe0SiUQikUgkEolEIpFIJBKJRCKRSCQSieSzkVq2/8clJD5l2oKSVCr7JR1a/vTuuGnxrN24EqEhqFyjCtU8a3Hr7m427+pLny47KO5Sg2th96k0YiADmrVGx6oKrcs4UsPNCoCXyTGcDTmGPFWbvdsO0L1/L2JTg7l3cwOahl4M7LgUmUxGi5WneJGczqkhDbg29jfC5uxlf0c/nlVzZUm7apS2yzv+u0QikUg+Pen6LZFIJBKJRCKRSCQSiUQikUgkEslrGp+7AJKiScvM/tNpPI1/zOPYcADOBd/hTmQ4Wtq6mJm58iBej7SMdLX4YRGB/HF4HNnZmQDcvbMdA70LeFcswaOYMLKyM8lWZJKRmYJCkUV8wmO0FS+o51MWO2t35p0MZeX5B6/XISOVpPQkPLxL89NPq4hXvCQmM5uaDWYxqNMyZDIZGdkKDodGk5yZjVxLk1etK5E12J+vR5ejZ7kn6Gq8+NPbQSKRSCQSSV7h4eHIZDKCgoLeGa9OnToMGzbsLynTv8XatWsxNTVVTU+aNImyZct+tvL83RR2TBW2vQrbvj169KBVq1Z/upyfgkwmY9euXUDRf4Nvko4lieTd3j4/fAwf8luVFN3b1wQXFxcWLFjw2cojkUgkEsmn8F+9vr39bCa9X5BIJP8WUmX7P8C5RzEYf/s7806EFHmZ2OQYDgTtJibpuWpeYOhJTgUfIzMri9rfDaf1jIkY6lvgUX4B43YEMWv7b8SlvGTpnoks2j6fU+cWcejkdKKe3wYg5MERbofupVyx0rSq2IHk5GeULfUF8yen4Vm8LsvWN2f1hnrsGz+JOmXKYm+oRS1nA1X+TpYudKzWHXcbLwCuP7dBoVRyL/wMr9ITAZBraXJ1RGP2f10HgG6H7tBXW5cKJUpTulhZipk757u+8zdMYcyCvu+1XSX/UNEpsPc+JKYXHlcikUiKIDo6msGDB+Pm5oZcLsfR0ZGAgACOHTumiuPi4oJMJkMmk6Gnp4eLiwvt27fn+PHjedIbMmQIFSpUQC6XF1gJJoRgzpw5eHp6IpfLcXBwYPr06Z9qFYvE0dGRqKgoSpcuDcDJkyeRyWQkJCSoxduxYwdTp079y8snhGDFihVUqVIFQ0NDTE1NqVixIgsWLCAtLQ3IqXjM3U9aWlpYWlpSq1YtFixYQEZGhlp6PXr0UMXN/WvcuHGefPft20eVKlXQ09PDzMzso1Tajhw5Uu34+jv5FBVTn1qHDh24d+/e5y6GRCL5G/o3nx/e/FjnU6hTp47aNdLGxoZ27doRERHxyfKUSCQSiUQikUgkkn8iacz2fwBzfTle1kY4mukXeZmkV4nEJD8nMS0BK2MbAGp61UMhFOhoazO359dYGxsBULuUL/0aN6edXy2exT/h7sXpZCj1mPVtCFXK9+Du/UNcv7OdL9uupfidAQz9ZTNDGpZh09aWNKw1hpaNfwCgTvWhxMY/QkdHn+sRYTxLyWbato30qlFGVS4dLXlO+dKz+P5AGDaaCbTRGcu96ytQKhWM6HeeUnZWqvgrO1Qm+OZPHD15hdZNZhe4vgfO7uDJ83CmD/4JLU3psP5Xe5IMYfHgZQEmuh+WxsN4MNAGG8OPWzaJRPKnKZQKzjy5RVRKLHaGFtQs5oOmhuYnyy88PBw/Pz9MTU2ZPXs2Pj4+ZGVlcejQIQYOHEhIyOsP3aZMmUKfPn3IzMwkPDycX3/9lQYNGjB16lS+//57tXR79uzJxYsXuXnzZr75Dh06lMOHDzNnzhx8fHyIi4sjLi7uk61nUWhqamJra1toPHNz87+gNHl17dqVHTt2MG7cOJYsWYKVlRU3btxgwYIFuLi4qCrBS5UqxdGjR1EqlcTGxnLy5EmmTZvGhg0bOHnyJEZGRqo0GzduzJo1a1TTcrlcLc/t27fTp08fZsyYQb169cjOzub27dt/el0MDQ0xNPz3X4OysrLQ1tb+5Pno6emhp6f3ydIXQqBQKNDSku4xJf88SqWSyKhnJKelYaSvj5OdPRoa/6xv7hUKBTKZ7IPK/anPD/8G7zpX9+nThylTpiCEICIigmHDhvHll19y5syZv7iUEolEIpH8CUoBz5IhNSvnfaC9EWjIPnepJBKJRPIv8s96yv6PKmFjzJ1vm9GurBORseE8jn39Jfml5Bi+CbtEcnaW2jKu1u60rdwFd1sv1Tw7MweKmTsBYPJqF1dPtSc5JQYbMzOWDhhGaWdXShYrQ8XKo6lbaxJmJg6U8mrCucsrOHPhZ3S09Th77wm/nTnJjQc3AEh99bpioFrFntx7eIKf1zajlGkCFVOnUMvkFCnpyfx+cSO3HwcBkJ6VTnzKE04Oqs+WrxpS3qc9lubFSUmNZfUvPxMb+1KVZpOS9qRG7eDsxWUolYoCt9HWOSc4+UuIVNH+X1DeFjqUBI/3qOwRAtL/PxRDhgL+uA9HHn2a8kkkkg+2495pXJZ3pu6W4XTeO526W4bjsrwzO+6d/mR5DhgwAJlMxqVLl/jiiy/w9PSkVKlSDB8+nAsXLqjFNTIywtbWFicnJ2rVqsWKFSsYP348EyZMIDQ0VBVv0aJFDBw4EDc3t3zzDA4OZunSpezevZsWLVrg6upKhQoVaNiw4TvLmtvd2uTJk7GyssLY2Jh+/fqRmZmpipORkcGQIUOwtrZGV1eXGjVqcPnyZVV4fHw8Xbp0wcrKCj09PTw8PFSVzW92ixseHk7dunUBMDMzQyaT0aNHD0C9m7fvvvuOKlWq5Cmrr68vU6ZMUU2vWrUKb29vdHV1KVGiBD///PM71/VtW7duZePGjWzevJnvvvuOSpUq4eLiQsuWLTl+/LiqrABaWlrY2tpib2+Pj48PgwcP5tSpU9y+fZtZs2appSuXy7G1tVX9mZmZqcKys7MZOnQos2fPpl+/fnh6elKyZEnat29faHnXrl2Lk5MT+vr6tG7dmtjYWLXwgro5nzFjBjY2NpiamjJlyhSys7MZNWoU5ubmFCtWTO3DgPzUqVOHIUOGMHr0aMzNzbG1tWXSpElqcebNm4ePjw8GBgY4OjoyYMAAUlJSgJzeDL766isSExNVLRlzl8+vBaWpqSlr164FXh8/v/32G7Vr10ZXV5eNGzcSGxtLp06dcHBwQF9fHx8fHzZv3lzoNnyXsLAw3NzcGDRoEEKI926Nr1QqmTlzJq6urujp6eHr68vvv/+uCs/t1eHAgQOqXirOnj2bb1pPnjyhU6dOmJubY2BgQMWKFbl48aIqfPfu3ZQvXx5dXV3c3NyYPHky2dl/fniot23YsAEXFxdMTEzo2LEjycnJqrD8uqgsW7as2rEhk8lYvnw5zZs3R19fH29vb86fP8+DBw+oU6cOBgYGVK9enbCwMNUyYWFhtGzZEhsbGwwNDalUqRJHjx5Vy8fFxYUZM2bQs2dPjIyMcHJyYsWKFR99/SX5C34YxsJf17Nuzy52HD3Muj27WPjreoIfhhW+8AdKTk6mS5cuGBgYYGdnx/z58/N0D5qRkcHIkSNxcHDAwMCAKlWqcPLkSVV47m96z549lCxZErlcTmRkJC4uLkybNo1u3bphaGiIs7Mze/bsISYmhpYtW2JoaEiZMmW4cuVKnrRy5Z5/3/WbOXjwIDVq1MDU1BQLCwuaN2+uduwXRUZGBmPGjMHR0RG5XI67uzurV69Whd++fZsmTZpgaGiIjY0NXbt25eXL18/BhZ3PXVxcAGjdujUymUw1DYWfd2QyGUuXLqVFixYYGBi8s2cdfX19bG1tsbOzo2rVqgwaNIhr16590nWXSCQSieSjehAHa27A9hA4GJbz75obOfM/kTp16jBo0CAGDRqEiYkJlpaWjB8/HiFEgcu86zkNICIigoCAAMzMzDAwMKBUqVLs378feP38cujQIcqVK4eenh716tXjxYsXHDhwAG9vb4yNjencubOqVzj4sHsepVLJjz/+iLu7O3K5HCcnJ7V7icePH9O+fXtMTU0xNzenZcuWhIeHf+CWlEgkkn8OqbL9HyYw9ASB906qptdEP2DBs2CupOR9ONWXG+SZl8vawgMbK2+0tXXJzM4kJT2FhSvrMWNBab5sPoVOTUao4n7TN5CxQ3Iq10e0bMvP/YZQxbcW3hUH4eGe092qUqnk/pMgHkacIyz8DDciY4hO0aVOtf4IIbh/+1eOHRsHwM3Ia5wKPoKJ9hNqlizPoWsv2R4YSe3yv3Az6B7h4eqVoEN7n2BIn0CWbZtLTPxz8mNqZIa1eeGt8ST/AqmZsCMEToQXfZnzT2HFNXieCnJNaOAKtZw+WRElEsn723HvNG13TeJJcoza/KfJMbTdNemTVLjHxcVx8OBBBg4ciIFB3mtmUSrvhg4dihCC3bt3FznfP/74Azc3N/bu3YurqysuLi707t27SC3bjx07RnBwMCdPnmTz5s3s2LGDyZMnq8JHjx7N9u3bWbduHdeuXcPd3R1/f39V2uPHj+fu3bscOHBAVelvaWmZJx9HR0e2b98OQGhoKFFRUSxcuDBPvC5dunDp0iW1B/I7d+5w8+ZNOnfuDMDGjRuZMGEC06dPJzg4mBkzZjB+/HjWrVtX5G22ceNGvLy8aNmyZZ4wmUyGiYnJO5cvUaIETZo0YceOHWrzT548ibW1NV5eXvTv31+tUvzatWs8ffoUDQ0NypUrh52dHU2aNCm0ZfvFixfp1asXgwYNIigoiLp16zJt2rRC1/H48eM8e/aM06dPM2/ePCZOnEjz5s0xMzPj4sWL9OvXj759+/LkyZN3prNu3ToMDAy4ePEiP/74I1OmTOHIkSOqcA0NDRYtWsSdO3dYt24dx48fZ/To0QBUr16dBQsWYGxsTFRUFFFRUYwcObLQsr/p22+/ZejQoQQHB+Pv7096ejoVKlRg37593L59m6+//pquXbty6dKl90o3182bN6lRowadO3dmyZIlyGTv3yJl5syZrF+/nmXLlnHnzh2++eYbvvzyS06dOpVnXX744QeCg4MpU6ZMnnRSUlKoXbs2T58+Zc+ePdy4cYPRo0ejVCoBOHPmDN26dWPo0KHcvXuX5cuXs3bt2o8+ZERYWBi7du1i79697N27l1OnTvHDDz+8dzpTp06lW7duBAUFUaJECTp37kzfvn0ZO3YsV65cQQjBoEGDVPFTUlJo2rQpx44d4/r16zRu3JiAgAAiIyPV0p07dy4VK1bk+vXrDBgwgP79+6t9oCT5NIIfhrH10AGSUlPU5ielprD10IFPVuE+fPhwAgMD2bNnD0eOHOHMmTN5KmcHDRrE+fPn2bJlCzdv3qRdu3Y0btyY+/fvq+KkpaUxa9YsVq1axZ07d7C2tgZg/vz5+Pn5cf36dZo1a0bXrl3p1q0bX375JdeuXaN48eJ069btnS+zC/vNpKamMnz4cK5cucKxY8fQ0NCgdevWqt92UXTr1o3NmzezaNEigoODWb58uapHk4SEBOrVq0e5cuW4cuUKBw8e5Pnz53k+5nrX+Tz3Q7o1a9YQFRWlmi7qeWfSpEm0bt2aW7du0bNnzyKtU1xcHFu3bs33I7uPve4SiUQikXwUD+Jg3wNIyVSfn5KZM/8TVrivW7cOLS0tLl26xMKFC5k3bx6rVq0qMP67ntMABg4cSEZGBqdPn+bWrVvMmjUrT29pkyZNYsmSJZw7d05V6b1gwQI2bdrEvn37OHz4MIsXL1bF/5B7nrFjx/LDDz+o3i1s2rQJG5ucXnWzsrLw9/fHyMiIM2fOEBgYiKGhIY0bN1ZrJCCRSCT/SuIzSExMFIBITEz8HNn/oz2NeyyexT1RTcdmpouDb0wXVUxsmAi8tFIoFAqx/9p28d3ckmLgWMTwiYYiOzszT/yUV2lCCCGWH/hDEFBfrD21XKw7vVxcehAohBDi7pNbYt3p5WLrkWki6M5OsXpzRzFlflmhUCiEEEKMmOYqBo4zEtnZ2SIuJVbsD9ol1p1eLsJfhIleE1uLVkP9RHZ2tggPfySUSqVQKJXictAmsWhVfZGU/EJs2LtcODRALNo4/UM2m+TfIC5NiPhXQqRlCrHsihCrrguRrSjasiEvhdhyW4ik9E9aRInk3+5TXb+zFdmi2M/tBbPq5vsnm1VXOP7cXmQrsj9qvhcvXhSA2LFjR6FxnZ2dxfz58/MNs7GxEf37988zf+LEicLX1zfP/L59+wq5XC6qVKkiTp8+LU6cOCHKli0r6tat+84ydO/eXZibm4vU1FTVvKVLlwpDQ0OhUChESkqK0NbWFhs3blSFZ2ZmCnt7e/Hjjz8KIYQICAgQX331Vb7pP3r0SADi+vXrQgghTpw4IQARHx+vFq927dpi6NChqmlfX18xZcoU1fTYsWNFlSpVVNPFixcXmzZtUktj6tSpolq1au9c3zd5e3uLFi1aFBqvoG0uhBBjxowRenp6qunNmzeL3bt3i5s3b4qdO3cKb29vUalSJZGdna0KB4STk5P4/fffxZUrV0SnTp2EhYWFiI2NLbAMnTp1Ek2bNlWb16FDB2FiYlJgObt37y6cnZ1V901CCOHl5SVq1qypms7OzhYGBgZi8+bNBeZdu3ZtUaNGDbV5lSpVEmPGjClwmW3btgkLCwvV9Jo1a9TKmgsQO3fuVJtnYmIi1qxZI4R4ffwsWLCgwLxyNWvWTIwYMUKt3G8eU2/L3V6BgYHCzMxMzJkzRy387TLnt31btmwphBAiPT1d6Ovri3Pnzqml0atXL9GpUychxOtjf9euXe9cj+XLlwsjI6MCj4f69euLGTNmqM3bsGGDsLOzU02/uV3f/g0WxcSJE4W+vr5ISkpSzRs1apTabzC/85evr6+YOHGiWjnGjRunmj5//rwAxOrVq1XzNm/eLHR1dd9ZnlKlSonFixer5f3ll1+qppVKpbC2thZLly4t8jpK3p9CoRDz1q0Rk35eXODfvPVr1M45H0NSUpLQ1tYW27ZtU81LSEgQ+vr6qt94RESE0NTUFE+fPlVbtn79+mLs2LFCiJzfNCCCgoLU4rx9PEVFRQlAjB8/XjUv99iNiopSpfX2+aGw38zbYmJiBCBu3bolhCj8txoaGioAceTIkXzDp06dKho1aqQ27/HjxwIQoaGhQoiinc/zOy8X9bwzbNiwAtc3V+3atYW2trYwMDAQ+vr6AhCenp7i0aNHBS7zsdb9zWvCu+7BJBKJRCIpkEKZ8+5wwcWC/1Zdz4n3kdWuXVt4e3sLpfJ12mPGjBHe3t6q6cKub28/p/n4+IhJkyblGzf3+eXo0aOqeTNnzhSACAsLU83r27ev8Pf3LzDPt+953paUlCTkcrlYuXJlvuEbNmwQXl5eauudkZEh9PT0xKFDh4QQ6s9mQhT+LCiRSCT/FFLL9n8Ye7Ni2Jk5qKbNteX4vzGdn8fPrqNQqHczv+/oRDbt7MPsfaO4iIzEl8EY6FtRs+Y0LL9sx7xdr7vSXHbgD4w7tuTYjWs0KFuerypkkfI8lBJ2pSjlWBYAB7NiFLfxpLHfYHxLtiI9PQGhTANyWhSceFGHDaFVyMzOxszAnCrFa+Bu44W1iS2rJu1g54KzaGpq4uzsgv/tI7hd3k5Y5HnuPTxBUnIUret1Zvrgn/iyeb+PsyEl/zxb7sL2YNDLHVuJ3MOrcF4W0KEUGMkLjyuRSP5yZ57cytOi/U0CeJwcw5kntz5qvuIdrd7eN533aV2rVCrJyMhg/fr11KxZkzp16rB69WpOnDhBaGgokZGRqjG9DQ0NmTFjhmpZX19f9PX1VdPVqlUjJSWFx48fExYWRlZWFn5+fqpwbW1tKleuTHBwMAD9+/dny5YtlC1bltGjR3Pu3Lk/vf5dunRh06ZNQM622Lx5M126dAFyvpQPCwujV69eaus0bdq09+qS92Psq7f3U8eOHWnRogU+Pj60atWKvXv3cvnyZVVXxrlf83///fd88cUXVKhQgTVr1iCTydi2bRuQMz587jo1adIEyBkm4O1Wf9WqVSu0fKVKlVIbj9jGxgYfHx/VtKamJhYWFrx48eKd6bzdAtvOzk5tmaNHj1K/fn0cHBwwMjKia9euxMbGqnUn+GdUrFhRbVqhUDB16lR8fHwwNzfH0NCQQ4cO5Wn9XJjIyEgaNmzIhAkTGDFiROELFODBgwekpaXRsGFDtWNy/fr1eY7Jt9flbUFBQZQrVw5z8/yHtrlx4wZTpkxRy6dPnz5ERUV9tO0NOd1JGxkZqabf3udF9eaxk9s65c1j0MbGhvT0dJKSkoCclu0jR47E29sbU1NTDA0NCQ4OzrNv30xXJpNha2v7QeWTFF1k1LM8LdrflpSSQmTUs4+a78OHD8nKyqJy5cqqeSYmJnh5vR7a7NatWygUCjw9PdV+G6dOnVL7Dero6OTbo0RRjlPgncdYYb+Z+/fv06lTJ9zc3DA2NlZ10V7U81ZQUBCamprUrl073/AbN25w4sQJtfUvUaIEgNo2KOx8XlDaRTnvFHZ+y9WlSxeCgoK4ceMGZ8+exd3dnUaNGql1u/8p1l0ikUgkkj/tWXLeFu1vS8nMifcJVK1aVe35s1q1aty/fx+FIv9hUgt7ThsyZAjTpk3Dz8+PiRMncvPmzTxpvH2fpK+vrza8nY2NzZ+65wkODiYjI4P69evnG37jxg0ePHiAkZGR6jpvbm5Oenq6dJ2XSCT/etIA1/8Sew59h76+OQ1qqnf1eStkL8vXB+DuWodWjWfh4pjz4qOC3wiu3tzCvWur2Wlahi4yGalpMUREHEdXR462lqYqjWKWVpRwcMTS2AQ3W3t0Mq5x+dJF6lXsxryfq1CvxjCqV+yFn2cd1TIDehxQ/V8Iwe/fzSBbkY2ePKey09zQguqe+T+A2+nok65U0KbJXBrXHouJsR0A3VsM+BibSvJPVckOZOTcBAd45ozDXtTKrevRcPkZtPMGM72ceQ/jIeg5NCmeU4EvkUg+m6iU2MIjvUe8ovLw8EAmkxESEvLBacTGxhITE4Orq2uRl7Gzs0NLSwtPT0/VPG9vbyDnobZu3boEBQWpwgqqyPsQTZo0ISIigv3793PkyBHq16/PwIEDmTNnzgen2alTJ8aMGcO1a9d49eoVjx8/pkOHDgCqMeZWrlyZpwJaU1MzT1oF8fT0/FP7CXJeDLxrP7m5uWFpacmDBw+oX78+dnY59x8lS5ZUxZHL5bi5ualePuzfv5+srJwPGvX09P5U+bS11a9FMpks33mFdWP8rmXCw8Np3rw5/fv3Z/r06Zibm3P27Fl69epFZmam2occb5PJZHk+eshd9ze9PSTD7NmzWbhwIQsWLFCNQThs2LD37kbQysoKe3t7Nm/eTM+ePTE2Nn6v5XPlHpP79u3DwUH9g1W5XP2jvPyGl3hTYfs8JSWFyZMn06ZNmzxhurq6RSlukRR2nGhoaBRp372ZTu6Lwfzm5aY9cuRIjhw5wpw5c3B3d0dPT4+2bdvm2bcfchxL/pzkIn7MUdR4H1NKSgqamppcvXo1z3Xgza5Q9fT08v2Q7X2P0/wUdkwGBATg7OzMypUrsbe3R6lUUrp06SKft4pybggICGDWrFl5wnKvPUUpZ0FpF+W8U9j5LZeJiQnu7u4AqrHX7ezs+O233+jdu3ee+B9r3SUSiUQi+dNS897v/ql4n1BRntN69+6Nv7+/qjv4mTNnMnfuXAYPHqxK53/s3Xd8T9f/wPHXJ5/sPUUQCZIQRIgZhBhtUGpXQ43WHrVHfc1QRYndqtGiirRqVO2tETORxIqIETOKmBFk3d8f+fnUR7Ymgr6fj8fnwb333HPe94ac87nnnnNebRPld5snN/V81apVWbVqVYZjdnZ2uboXQgjxrpLO9veAoij8dWQBZqZFSUl5TsKTO7RrPif9WFr6g7ULl/fz/fKmfDsuvaOi6fUYrGqNZrhNCXzTUkisNYUTu1ZS16sPcV801cq/efVaNK9eS7Ndy/cnjkaf4+SlM9y4dYbdobuoXa275vjjhDus2dgLRVHwb7WIwT/9zLrDwUQvXK6V7/kb1+k8exrdvW0x1bnJJy0W8FhR+PPeNT6wLIaerp6mo10IqhWD4KuwNgr01fBZxdyPVFde+rxw8BrcfwbHbsLdRPCwA7eM6xYLIQqeg6lNvqbLLWtra/z8/Pjuu+8YOHBghgfPDx48yHHd9rlz56Kjo0OrVq1yXW6dOnVISUnh4sWLlClTBoDz588D4OTkhK6urubB9qsiIyN5+vSp5kvukSNHMDU1xdHREVtbW/T19QkJCcHJyQlI71A7fvw4gwcP1uRhZ2dH165d6dq1Kz4+PowYMSLTznZ9fX2ALN+8f6FEiRLUr1+fVatW8fTpUz744APN2rr29vYUK1aMS5cuaUa7v46OHTvy6aef8scff2RYt11RFB49epTtuu3nzp1j+/btjB49Oss0169fJz4+XvOwv2rVqhgYGBAdHU3dunWB9PsZGxurub8v/nyZu7s7R48e1dp35MiR3F1oAQsLCyMtLY3AwEDNKPrffvtNK42+vn6mP3M7Ozvi4uI02zExMbkanR0SEkLLli357LPPgPQOsPPnz2u9xJAbRkZGbN68mWbNmuHn58fOnTu1RqbmVvny5TEwMODq1atZjrzMrUqVKrF06VLu3buX6UsxXl5eREdHZ/n/+U159Wf36NEjLl++/K/zDQkJoVu3brRu3RpIf7gWGxv7r/MV/55ZNi/OvE663CpdujR6enocP36ckiVLAvDw4UPOnz9PvXr1AKhSpQqpqancvn0bHx+ffC0/P8THxxMdHc2SJUs08R08eDBPeXh4eJCWlsaBAwdo3LhxhuNeXl6sW7cOZ2dndHVf/5GMnp5eht/XBf1758ULEk+fPs30+Ju6diGEECJHJrkcWJPbdHmU2XdCV1fXTF86z833NABHR0f69OlDnz59GD16NEuWLNHqbM+L12nzuLq6YmRkxJ49ezJ96c7Ly4tff/2VIkWKvPbL0UII8a6SaeTfAyqViu4d1/HkSTz7Q+ZwJGwZz5OesnhlKw4cmQeApXkJitlX4lj4SgC62TrRqlwzovZN4OHtU5R1rkY3/8VUrdw0u6I4Gh1FURsnZvUchEvJKgQ//oxq1YZojoecPc2vfy7m6p9HOXX2D2KvHaGMQzHKFXfg/r1zPHh0k9mLfAiNXMON+Lscj4nmfMwfHAn7icdPbmOgo6aCsSVljaRCFplwsQI9HUhKhdCb6aPT10VBxK3sp33yKgq9vcD6pTcwm5RJ72C3M4Lrj2H7JXiWUvDXIITIwKeEByXM7MhqrgoV4Ghmh08JjyxSvL7vvvuO1NRUatSowbp164iJiSEqKop58+ZlmPr78ePH3Lp1i2vXrvHXX3/Rq1cvvv76a6ZMmaL1UPvChQtERERw69Ytnj59SkREBBEREZq3wxs3boyXlxdffPEF4eHhhIWF0bt3bz744AOt0e6ZSUpKonv37pw9e5atW7cyYcIEBgwYgI6ODiYmJvTt25cRI0awfft2zp49S8+ePUlMTKR79/SX4saPH88ff/zBhQsXOHPmDJs3b9aMqn+Vk5MTKpWKzZs3c+fOHc2I4Mx06tSJoKAg1q5dm6FTPSAggKlTpzJv3jzOnz/PqVOnWLZsGbNmzcr2Wl/2ySef0KFDB/z9/fnmm28IDQ3lypUrbN68mcaNG7Nv3z5N2pSUFG7dusXNmzc5deoU8+fPp379+lSuXJkRI0YA6Z2CI0aM4MiRI8TGxrJnzx5atmyJi4sLfn5+AJibm9OnTx8mTJjAzp07iY6Opm/fvgC0b98+y1gHDhzI9u3bmTlzJjExMSxYsIDt27fn+loLkouLC8nJycyfP59Lly6xcuVKfvjhB600zs7OJCQksGfPHu7evavpUG/YsCELFiwgPDyc0NBQ+vTpk2GkRGZcXV3ZtWsXhw4dIioqit69e/P333+/VvwmJiZs2bIFXV1dmjZtmu2/yayYmZkxfPhwhgwZwooVK7h48SInTpxg/vz5rFixIk95+fv7U7RoUVq1akVISAiXLl1i3bp1HD58GEj///bzzz8TEBDAmTNniIqKIigoiLFjx+Y57n+jYcOGrFy5kuDgYE6dOkXXrl3zNLNEVlxdXVm/fr1miumOHTvKiPW3REmHYpibmGabxtzUlJIOxfK1XDMzM7p27cqIESPYt28fZ86coXv37ujo6GhGnLu5udGpUye6dOnC+vXruXz5MseOHWPq1Kls2bIlX+N5HVZWVtjY2LB48WIuXLjA3r17GTp0aJ7ycHZ2pmvXrnzxxRds3LiRy5cvs3//fs1D8/79+3Pv3j38/f05fvw4Fy9eZMeOHXz++ec5vuD2ajl79uzh1q1b3L9/H8j/3zuJiYncunWLW7duERkZSd++fTE0NOTDDz8s1GsXQgghclTMDEz1s09jqp+ergBcvXqVoUOHEh0dzZo1a5g/fz6DBg3KNG1uvqcNHjyYHTt2cPnyZU6cOMG+ffuy/C6fG6/T5jE0NGTUqFGMHDlSswzXkSNH+PHHH4H05wK2tra0bNmS4OBgTTtg4MCBXL9+/bVjFUKId4F0tr8nLM2L8Tw5gYTEeHp0WkdKylPOXdyNrlqfrp+soqXfNC7E7mfb3kkA1Hx0nbK3zmJUrS8WlkUpYpBC9erVeZiSxLfXThN65QinHt3mh7ho0l6adrJT4FTafTOCMdOKcTJsMpHzfqSJ1z/rvXWZM509449T7jdf2jv+QKiVOwPbfMKw+vp892MdTp/bysUrIRw8+gMNKlXm75/XMmnQXv438BRWFiUwVusS7NmUSc5V3vg9FO8AlSq9wx3g9B24/DC9o/zAVdh/JW95FTGBhqWgfBFwsgC1jnS2C1FI1Dpq5jbqD5Chw/3F9pxG/VHr/PvOoVeVLl2aEydO0KBBA4YNG0bFihX54IMP2LNnDwsXLtRKO378eBwcHHBxcaFz5848fPiQPXv2MGrUKK10PXr0oEqVKixatIjz589TpUoVqlSpws2b6Wvj6ujo8Oeff2Jra0u9evX46KOPcHd3JygoKMd4GzVqhKurK/Xq1aNDhw58/PHHTJw4UXN82rRptG3bls6dO+Pl5cWFCxfYsWMHVlbpvzv19fUZPXo0lSpVol69eqjV6izLLV68OAEBAXz11VfY29szYMCALONq166dZj25V0f59+jRg6VLl7Js2TI8PDyoX78+y5cv15rS3dfXl27dumWZv0qlYvXq1cyaNYuNGzdSv359KlWqxMSJE2nZsqWmgxzgzJkzODg4ULJkSXx9ffntt98YPXo0wcHBmimK1Wo1J0+e5OOPP8bNzY3u3btTtWpVgoODtaYSnzFjBp9++imdO3emevXqXLlyhb1792ruZ2Zq1arFkiVLmDt3Lp6enuzcufONd65mxdPTk1mzZjF9+nQqVqzIqlWrmDp1qlaa2rVr06dPHzp06ICdnR3ffvstAIGBgTg6OuLj40PHjh0ZPnx4ttPOvzB27Fi8vLzw8/PD19dX0zn9ukxNTdm2bRuKovDRRx/x5MmTPOcxefJkxo0bx9SpU3F3d6dJkyZs2bIlT8tBQPr/p507d1KkSBGaNWuGh4cH06ZN03Rk+/n5sXnzZnbu3En16tWpVasWs2fPznRGhKw4Oztr/R9/HaNHj6Z+/fo0b96cjz76iFatWmlm1fg3Zs2ahZWVFbVr16ZFixb4+fnh5eX1r/MV/56Ojg5N6mY/arxJHR/NyKn8NGvWLLy9vWnevDmNGzemTp06uLu7a01hvmzZMrp06cKwYcMoW7YsrVq10hoNX5h0dHQICgoiLCyMihUrMmTIEGbMmJHnfBYuXEi7du3o168f5cqVo2fPnprfV8WKFSMkJITU1FQ+/PBDPDw8GDx4MJaWlnn6mQQGBrJr1y4cHR2pUiX9+3N+/N552ZIlS3BwcMDBwYEGDRpw9+5dtm7dStmyZQv12oUQQogc6aigfg5ti/ol09MVgC5duvD06VNq1KhB//79GTRoEL169co0bW6+p6WmptK/f3/N9xc3Nze+//77147vdds848aNY9iwYYwfPx53d3c6dOigWQfe2NiYv/76i5IlS9KmTRvc3d3p3r07z549k5HuQoj3nkp5dQG/N+DFVJ8PHz6UX7T56MTJ3zgW8Qtd2q/A2MiKhCd3ea5jQJJajerBVRb/0go/3/9R06sLZ65HcvB6JF8mp1Ey/hxNjk2nXfN5XCzdhB4xh6hxfj16pRoSomfJcmtbOrjUw9DAjG1hx7gVH8fjq3Mp49yAvcFzsbN14asv06dH3R0Rxp0Tl3EJT+B4H0/63zvJdOeqhP4dhfnNY0yr249v5npQvFhlBvfYh1ota2WLPDhwJX2ddTdruPwALA3gURLUcQQDNbhaZ7+O+/NUiImHsjag91Kn3fGbcOIWfOwK955Bcmp6B7zVv1t/V4j3TUHX3+vP/8WgPd9x/fEdzT5HMzvmNOpPG7d6+V7eu6Zbt248ePCAjRs3FnYo+c7JyYmAgIBsO9yF+K9JTEzExsaGbdu24evrW9jhiHdQ1KWLbD8YzKMn/8wCYW5qSpM6PriX/vcvXOTGkydPKF68OIGBgZpZVoQQQggh3pgL99IH6SS8tA65qX56R7tLxqWg8oOvry+VK1dmzpw5BZK/EEKIt48skvUe2HrvOgmpKXxS6RO8Kn3C86Qn/H33PEVsXKmydx7X9cy5W+czxg89B8Ct2+ewNDTDKPkZw+5EEX91H+VcPqRiuebUsHDk0dMH6MXtQ7+oGyHxfzP15EbOrRvFlLEnaVq1xv+X2pJTpyJJTPieJNN/Rik0rlyV3xIe0zVsK1774+lZ2xM/q2KMuXKChqU+xNa6FP26bWPuUl9++/NL/Fv9kMkVCZGFWiWglCWUtEhfv/3ErfRhr/ti09djv5MI5gZQwS7zN1NP305fqz1VAU/7f/ZXKgKlreDk33Ay/W1MytmA35t5CCmESNfGrR4tXeoQfP0UcQnxOJja4FPCo0BGtIu3x5kzZ7CwsKBLly6FHYoQb5V9+/bRsGFD6WgXr829dBnKOpfiatxNHicmYmZsTEmHYgU6gjg8PJxz585Ro0YNHj58yKRJ6TOrtWzZssDKFEIIIYTIkot1+jO/m4/hSXL6Gu3FzApsRLsQQoj/Julsfw/0ijnM7eRnNDUyYeXvXXn8+BbX4sJp0mAcxW9GYWBdjk4r2tKyRg8aWJUg8LtqVK3cCecKn1G1hAcLQ+cQfVsHUDBW6zKkVHUO36uPjiqVpoYmpN2J4NGjRJKTkzEwMOC74PN4FLPEp2Il+nbdRpkyrlrxBJ/YQvT1qyTcC8fxchSeMxtz2qslRfTSO+WTdWx5gjMpuq83lZ34DzNQQ1FTiE+Ee09BVwUV7eDSAzDRh1sJEBqXvjZ78UzWXCpnCylp6SPjX7brMly6j/KxG9eWXCJVV02prsXfyCUJIbSpddT4lqxc2GGIN6hChQqcPHmysMMQ4q3z0Ucf8dFHHxV2GOIdp6Ojg3PxEm+0zJkzZxIdHY2+vr5miQ5bW9s3GoMQQgghhIaOCkrI7LpCCCEKjnS2vwfWlKtHYloKDx/fJCpmB86ONVGr9QhPTuZO2TbUO7sS9YVtRBsYYV6mKVYOVbly/Rgnz6yndbNAAIyNrFCp09coTU55zur1PbC1Lk1/z44ceHiRrt1/Z+HB73iiZ8HY9cbULmVLyKAPqFSpMgB3711i5dqufFD/K8wTV9O74n10lKfcV6ev5VnW2EITb+zdxyw7VYoynoW/Jp94B+2Nheh46FgRLAxAXw31///Y8kjQ04GiJpmfa6IHNTPpRHezBgM1KkM1jjVN0zvx9WQkrRDi7bJ8+fLCDkEIIYTIVpUqVQgLCyvsMIQQQgghCs3+/fsLOwQhhBBvmHS2vwd8LF5Mh12cgOGXMDdzQFdXnxGXQrlw4zRVbp6gae3BOBUpz9XERxibOfIo7ihJyYmcitpE7Wo98PAeiMvZv+hg68wQnaf0+uwPzM2KEhWzA319ExRVIsk6+jxOvM0gq0C8SvcDPgAgJSWJE6d+49LVEK7HRdC/2w4Sn97jxJnN1K3+RYZ4m1atQfTC5bg4FHtzN0m8P1ys0qeOtzT4p0NcUSDoDDx8Doa6oM7j1JhuNumfJ8mo1CpIUeDvhPRppoQQQgghhBBCCCGEEEIIIYTIhHS2v2esrf6Zmv3bUlU5ezmYk6X8+KRYVYJ+74y7a1Oux2yjmmcnrt0M4/zFPXz91Q2S9c0ocfMSafcuMP+PLjT/4Gs83JvjVKIaTRqMAcDE9gL3nj/h97A52JsZacoJOb6YTTtGU6dGH/x8/4dKlb7mjUupelnG6faGpzIU7xEX6/TPq5JSwUwf6jq+ft4metCnKtx+kj4tfVJq+sh5IYQQQgghhBBCCCGEEEIIIV4hne3vsYvPHmMWvoh696IxqN2bpg3H41quJfZuTfAo6oFX0ifE34vl3IVdVPP051TVljx4dJMtN7pTyb1lhvwW/TITE2Mzpo75W7Pvr4e3+Eq/BLXNS3Do+GI+ajQBc7Oib/IyhQCVCrp6Zn7s7wQwNUjvSM8NXZ30TvtlkWBpCA2dZV0nIYQQQgghhBBCCCGEEEIIkUGeO9ufPn1KWFgY1tbWlC9fXuvYs2fP+O233+jSpUu+BShe39q7V9jt3omvzMz4wKkmoQ8u8b/7d9iUbEjv37qgPL6OkaEloFDN0x8AS/NidGqzNNP8dhzaiIWpFeN6zeDBo5tcvxnOSfPSHEl8SHOfMTg+voqpid2bu0AhcvLoOQSdhZLm0Lpc7s8z0gMDNdx/BuvOQf9q6Z3wQgghhBBCCCGEEEIIIYQQQvw/laIoSm4Tnz9/ng8//JCrV6+iUqmoW7cuQUFBODg4APD3339TrFgxUlNTs83n0aNHWFhY8PDhQ8zNZcRoQXmamsKa8NU8Cl9GjSqdWb2+O/p1x/D0zK+o719ET8+QL7/YjYJCGac6bNo5huTkp7T9aBapqSkci1iJu6sflubpa6vff3QPtVqNqZEZy4I6EH76d0b0O85TaxeqhG+mkokVZQzNqGxizUjHigCMvhzGreSnLHOrW5i3QvxXpSlw8BoUM8186vnsnL4Ne2LBzhg6ViyQ8IR410j9LYQQQgghhBBCCCGEEEL8I09DNUeNGkXFihW5ffs20dHRmJmZUadOHa5evVpQ8Yl/wUiti8PDWC5c3o+lWTFSPpzNT6aleJSUQIlilWlUdwR34i9QytGbbXsncyT0J0IjVgGwbe8kVq37gh37pvDo8S1++u0LEp9cx9zEgh9XtyMqZieNfEZQvGgl3Iws6GHvyie2Tvx57xrb7t/QxLDt/g02x18nVUkrrNsg/st0VFCvZNYd7XcTYdsFePgsffvSfTh7J/3vThbpfz58XvBxCiGEEEIIIYQQQgghhBBCiHdOnjrbDx06xNSpU7G1tcXFxYU///wTPz8/fHx8uHTpUkHFKF7DjdtXWbHpexr6jMLerhy7g7+lnOuH6KgNKFvmA774NIidf01n6baRHL0Tw5bd47EwL87ogScB2BM8A319ExrUGcyG4N/p+Uss//t5DgA2NmVITU3i/oMr6Orqo6NSMd+lJsNKVORCtTb8WaGhJo7gSk2JrtYatUqm4BZvoauP4Pw9uPE4ffuvq7D7MqSmgbEeGKpBT/7tCiG0JSYm0rZtW8zNzVGpVDx48CDHc5YvX46lpaVme+LEiVSuXFmz3a1bN1q1apVvMb5aXn7y9fVl8ODB/yqPV6//XaNSqdi4cSMAsbGxqFQqIiIiCjUmIYQQb05+1IWFqSDbCXnl7OzMnDlz/lUeuWlHFfTPLKe2nhBCCPFCftR9BS0333P379+f62ciQgjxvsvTmu1Pnz5FV/efU1QqFQsXLmTAgAHUr1+f1atX53uA4vV8/+u3rNj0HTbmZpgY22BgYEbv4uUZXLw88BkAJdv+wjc3z+MR/jMAqWnJbN/3NU+rD6B6+zVUMTShiK0rtSoZUtRuP79YFqfZncu0aTyZqOht6OkZA3DkxArMTYtS3s2PtPuXeZiWgqlDJQDMdPUK5fqFyJXK9uBgAkVN07eblIHnqaD+/w72Xl6FF5sQosCpVKpsj0+YMIGJEydm2L9ixQqCg4M5dOgQtra2WFhY/OtY5s6dSx5W9hFCCCFEPpk4cSJBQUFcu3YNfX19qlatypQpU6hZs2aW56xfvx49vTf/XdfX15fKlSu/9Q/o3zRpRwkhhBDvvm7duvHgwQPNi+1CCPEuyVNne7ly5QgNDcXd3V1r/4IFCwD4+OOP8y8y8a/0aT8cO3MdduzqSrOGE2naaHyGNF84VadyaiIb13XFwrw4hvpmbD+xgmVW1ahuasMx1w8AKFvCkd9mfU/PmEMU0zdGT8+QMYNPA5Cc/IxV6z7HzsaV8UOjmf9TY5KSEpg54dGbvFwhXo+OChzM/tl+0en+Qg4dcUKI/JealkbwxTvEPXqKg7kRPmXsUOsUzAwTcXFxmr//+uuvjB8/nujoaM0+U1PTzE7j4sWLuLu7U7FixXyLJT867PNbUlIS+vr6hR3Ga1MUhdTUVK0XRYUQ4r8mLTWVC5FneRR/D3Mba1w8y6OjVhd2WFoKu75xc3NjwYIFlC5dmqdPnzJ79mw+/PBDLly4gJ2dXabnWFtnsUyVKBRvYztKCCHE20NJVbgffIfnt55hUNQQKx87VGp55ieEECL/5OnpdevWrVmzZk2mxxYsWIC/v7+8TfyWcCzqzGcthlC6ZB1KFKuSaZrVG3qycV1XalX9gp6d1tOr80bGd9/NL2V9mF9G+y3+5bcvUMeiCD4W9iSnPCcg0JUfV3+Cnp4hfbpsoUv7lQA0aziB5h98XeDXJ4QQ4v2zPvIazpM20eC7vXRceZgG3+3FedIm1kdeK5DyihYtqvlYWFigUqm09mXW2e7r60tgYCB//fUXKpUKX19fAO7fv0+XLl2wsrLC2NiYpk2bEhMTk+tYXp3+NC0tjW+//RYXFxcMDAwoWbIkU6ZMATKfqi0iIgKVSkVsbGym+V+8eJGWLVtib2+Pqakp1atXZ/fu3VppnJ2dmTx5Ml26dMHc3JxevXplGW9aWhojR47E2tqaokWLZpgB4MGDB/To0QM7OzvMzc1p2LAhkZGROV5/QECA5pw+ffqQlJSkVebUqVMpVaoURkZGeHp68vvvv2uOv7gv27Zto2rVqhgYGHDw4MFMy7t+/Tr+/v5YW1tjYmJCtWrVOHr0qOb4H3/8gZeXF4aGhpQuXZqAgABSUlKyjF8IId5GEfsPMa5td+Z++T+WTZzJ3C//x7i23YnYf6jAynz8+DGdOnXCxMQEBwcHZs+enWH67qzqm3Xr1lGhQgUMDAxwdnYmMDBQK++Xl/B4wdLSkuXLlwP/THcaFBRE7dq1MTQ0pGLFihw4cCDbmDt27Ejjxo0pXbo0FSpUYNasWTx69IiTJ09meU5m1/TNN9/wxRdfYGZmRsmSJVm8eLHm+IvY1q9fT4MGDTA2NsbT05PDhw9r0sTHx+Pv70/x4sUxNjbGw8ND6/lLt27dOHDgAHPnzkWlUmnV+6dPn6Zp06aYmppib29P586duXv3brbX/XJsOjo6hIaGau2fM2cOTk5OpKWlaerYHTt2UKVKFYyMjGjYsCG3b99m27ZtuLu7Y25uTseOHUlMTNS6TwMGDGDAgAFYWFhga2vLuHHjMjw3SkxMzPLeAZw6dYqGDRtiZGSEjY0NvXr1IiEhQevevNyOevLkCV26dMHU1BQHB4cM/5ay8ueff1K9enUMDQ2xtbWldevWmmPPnz9n+PDhFC9eHBMTE2rWrMn+/ftzla8QQojC8/eG6/xVZguhjQ9w6rOjhDY+wF9ltvD3husFVmZu678XZs2ahYeHByYmJjg6OtKvXz+teu7KlSu0aNECKysrTExMqFChAlu3bgV47Tp6+/bt1K1bF0tLS2xsbGjevDkXL17MENu5c+dy3a7KqS0D8Pvvv+Ph4aGp0xs3bsyTJ0+YOHEiK1as4I8//tC0c6SeFUK8S/LU2T569GjNL/LMfP/996Slpf3roET+sLUuxZDewXi4t8j0eC2vbgDE37uEs2MNTE1scXaswb3k53wWHcyVZ/9U6vse3GL/g1sAqFChp2eEnp4hABXKNsXZsQYAdWv2xrf2wAK8KiGEEO+j9ZHXaLfsINcfPNXaf+PBU9otO1hgHe55tX79enr27Im3tzdxcXGsX78eSH/IGxoayqZNmzh8+DCKotCsWTOSk5Nfq5zRo0czbdo0xo0bx9mzZ1m9ejX29vavHXdCQgLNmjVjz549hIeH06RJE1q0aMHVq1e10s2cORNPT0/Cw8MZN25clvmtWLECExMTjh49yrfffsukSZPYtWuX5nj79u01X+7DwsLw8vKiUaNG3Lt3L8s89+zZQ1RUFPv372fNmjWsX7+egIAAzfGpU6fy888/88MPP3DmzBmGDBnCZ599luHL/ldffcW0adOIioqiUqVKmd6L+vXrc+PGDTZt2kRkZCQjR47UtGGDg4Pp0qULgwYN4uzZsyxatIjly5drXnYQQoh3QcT+QywZM5UHd+K19j+4E8+SMVMLrMN96NChhISEsGnTJnbt2kVwcDAnTpzIkO7V+iYsLIxPPvmETz/9lFOnTjFx4kTGjRun6UjPixEjRjBs2DDCw8Px9vamRYsWxMfH53wi6aPsFy9ejIWFBZ6ennkqNzAwkGrVqhEeHk6/fv3o27ev1ow5AGPGjGH48OFERETg5uaGv7+/5mWuZ8+eUbVqVbZs2cLp06fp1asXnTt35tixY0D6VOne3t707NmTuLg44uLicHR05MGDBzRs2JAqVaoQGhrK9u3b+fvvv/nkk09yFbezszONGzdm2bJlWvuXLVtGt27d0HlphqGJEyeyYMECDh06xLVr1/jkk0+YM2cOq1evZsuWLezcuZP58+dr5bNixQp0dXU5duwYc+fOZdasWSxdujTX9+7Jkyf4+flhZWXF8ePHWbt2Lbt372bAgAFZXtOIESM4cOAAf/zxBzt37mT//v2Z/jt82ZYtW2jdujXNmjUjPDycPXv2UKNGDc3xAQMGcPjwYYKCgjh58iTt27enSZMmeXq5UgghxJv194brRH5ymOfXtZ8zPL/xlMhPDhdoh3tu6r8XdHR0mDdvHmfOnGHFihXs3buXkSNHao7379+f58+f89dff3Hq1CmmT5+eYXBAXuvoJ0+eMHToUEJDQ9mzZw86Ojq0bt06Q99OXtpVObVl4uLi8Pf354svvtB892/Tpg2KojB8+HA++eQTmjRpomnn1K5d+7XuvRBCFAoljy5fvqwsXrxYWbBggXLq1Km8nq4oiqI8fPhQAZSHDx++1vki/0Rf3KfE34vV2ud+fIPCX8uVJTejNfsepyQpj1OS3nR4Qggh3iIFVX+npKYqJSZsUBi0OtOPatBqxXHCRiUlNTVfy33ZsmXLFAsLi1ylHTRokFK/fn3N9vnz5xVACQkJ0ey7e/euYmRkpPz222+Z5j9hwgTF09NTs921a1elZcuWiqIoyqNHjxQDAwNlyZIlmZa/b98+BVDu37+v2RceHq4AyuXLl3N9PRUqVFDmz5+v2XZyclJatWqV7TmKoij169dX6tatq7WvevXqyqhRoxRFUZTg4GDF3NxcefbsmVaaMmXKKIsWLVIUJfPrt7a2Vp48eaLZt3DhQsXU1FRJTU1Vnj17phgbGyuHDh3SyrN79+6Kv7+/oij/3JeNGzdmG/+iRYsUMzMzJT4+PtPjjRo1Ur755hutfStXrlQcHBw024CyYcMGRVHS28aAEh4enm25QgjxpqSmpCj/a9lV6Ve7eZafMa26KakpKfla7qNHjxQ9PT1l7dq1mn0PHjxQjI2NlUGDBmn2ZVbfdOzYUfnggw+09o0YMUIpX768Zvvl370vWFhYKMuWLVMU5Z/fx9OmTdMcT05OVkqUKKFMnz4929j//PNPxcTERFGpVEqxYsWUY8eOZZu+fv36Ga7ps88+02ynpaUpRYoUURYuXKgV29KlSzVpzpw5owBKVFRUluV89NFHyrBhw7IsV1EUZfLkycqHH36ote/atWsKoERHRyuZebWd8OuvvypWVlaaujssLExRqVSadsWLOnb37t2ac6ZOnaoAysWLFzX7evfurfj5+WnF6+7urqSlpWn2jRo1SnF3d9ds53TvFi9erFhZWSkJCQmaNFu2bFF0dHSUW7duKYqi3Y56/Pixoq+vr2mDKYqixMfHK0ZGRhnu3cu8vb2VTp06ZXrsypUrilqtVm7cuKG1v1GjRsro0aMVRcm5rSeEEOLNSktJU/Y7/ansUP+W+Uf3N2W/059KWkpazpnlUU71n5OTkzJ79uwsz1+7dq1iY2Oj2fbw8FAmTpyYadrXraNfdefOHQXQ9Pfkpl2V2bOJV73clgkLC1MAJTY2NtO0L9fnQgjxrsnTyPZ9+/ZRoUIFevfuzZdffomXlxe//PJLPnT5i8LiVtoXaysnrX3r3H351rkqXxR11ewzVethqtZ70+EJIYT4Dwi+eCfDiPaXKcC1B4kEX7zz5oLKg6ioKHR1dalZ858lWGxsbChbtixRUVGvld/z589p1KhRvsWYkJDA8OHDcXd3x9LSElNTU6KiojKMbK9WrVqu8nt1xLiDgwO3b98GIDIykoSEBGxsbDA1NdV8Ll++nOm0dC94enpibGys2fb29iYhIYFr165x4cIFEhMT+eCDD7Ty/PnnnzPkmdM1REREUKVKlSzX242MjGTSpEla5bwYRfjytHtCCPG2uhB5NsOI9lfdv32XC5Fn87XcS5cukZycrDUa2MLCgrJly2ZI++rv6qioKOrUqaO1r06dOsTExJCampqnOLy9vTV/19XVpVq1ajnWxw0aNCAiIoJDhw7RpEkTPvnkE029llsv140vlqZ5NY+X0zg4OABo0qSmpjJ58mQ8PDywtrbG1NSUHTt2ZKirXxUZGcm+ffu06q1y5coBZFvvvqxVq1ao1Wo2bNgAwPLly2nQoAHOzs5Zxm9vb4+xsTGlS5fW2vfqNdeqVQuV6p91cb29vTP8XLO7d1FRUXh6emJiYqJJU6dOHdLS0jLMHPDimpOSkrTaZdbW1pn+O3xZRERElm2vU6dOkZqaipubm9Z9PnDgQK7vsRBCiDfrfvCdDCPatSjw/PpT7gcXzHOG3NR/L+zevZtGjRpRvHhxzMzM6Ny5M/Hx8ZrvnwMHDuTrr7+mTp06TJgwIdOlbvJaR8fExODv70/p0qUxNzfX1Pmvtjvy0q7KqS3j6elJo0aN8PDwoH379ixZsoT79+9neQ+FEOJdopuXxOPGjeODDz5g4cKFGBoaMnbsWEaOHMlnn31WUPGJQuBuYom7iWVhhyHEW+XvK2dIepqAY7maOScWQuRJ3KNsvgC/Rrp3nZGRUbbHX0znqry03ltO09UPHz6cXbt2MXPmTFxcXDAyMqJdu3Zaa6IDWg+ys6Onp/0Cnkql0kw3l5CQgIODQ6brq1laWuYq/1e9WK9uy5YtFC9eXOuYgYGB1nZO15DT/U1ISCAgIIA2bdpkOGZoaJibcIUQolA9is96yY7XSVcQclvfvEylUmVY6/R1l2vJLB4XFxdcXFyoVasWrq6u/Pjjj4wePTrXeWRXN2aW5sUD+BdpZsyYwdy5c5kzZ45m3dbBgwdnqKtflZCQQIsWLZg+fXqGYy869HOir69Ply5dWLZsGW3atGH16tXMnTs322tUqVS5uubcyK98/o3s2gcJCQmo1WrCwsJQq9Vax16dxlcIIcTb4fmtZ/marqDExsbSvHlz+vbty5QpU7C2tubgwYN0796dpKQkjI2N6dGjB35+fprp4KdOnUpgYCBffvmlJp+81tEtWrTAycmJJUuWUKxYMdLS0qhYsWKO7Y7s5NSWUavV7Nq1i0OHDmmmtR8zZgxHjx6lVKlSr12uEEK8DfI0sv306dN88803ODg4YGVlxYwZM7h9+3au1z8TQoh31S8BH7NkpA+PzsQT4rmDW+sKbl0nIf5rHMyz7/zMa7o3zd3dnZSUFI4eParZFx8fT3R0NOXLl89zfq6urhgZGbFnz55Mj9vZ2QHp6529EBERkW2eISEhdOvWjdatW+Ph4UHRokWJjY3Nc2y54eXlxa1bt9DV1dV0XLz42NraZnleZGQkT5/+80LFkSNHMDU1xdHRkfLly2NgYMDVq1cz5Ono6Jin+CpVqkRERESW68d7eXkRHR2doRwXFxetdWuFEOJtZW6T+cwdr5sut0qXLo2enh7Hjx/X7Hv48CHnz5/P8Vx3d3dCQkK09oWEhODm5qbp3LSzs9Oq+2JiYjKdceTIkSOav6ekpBAWFoa7u3ueriUtLY3nz5/n6Zx/KyQkhJYtW/LZZ5/h6elJ6dKlM9w7fX39DCPivLy8OHPmDM7Ozhnqrby81NCjRw92797N999/T0pKSqYvnb2Ol9tHkP7zcXV1zdBpnRV3d3ciIyN58uSJZl9ISAg6OjqZjlYvU6YMenp6WuXev38/x3+HlSpVyrLtVaVKFVJTU7l9+3aGe1y0aNFcXYcQQog3y6Bo7l6Uzm26vMpt/RcWFkZaWhqBgYHUqlULNzc3bt68mSE/R0dH+vTpw/r16xk2bBhLlix57dhePK8YO3YsjRo1wt3dPcsR5nlpV+WmLaNSqahTpw4BAQGEh4ejr6+vmVkns3aOEEK8K/L0xPDRo0daD0mNjY0xMjLi4cOH+R6YEEK8TRp3+Zom3WeS+kAh8dxjnl2VqYSFyC8+ZewoYWmEKovjKsDR0hifMnZvMqxcc3V1pWXLlvTs2ZODBw8SGRnJZ599RvHixWnZsmWe8zM0NGTUqFGMHDlSM036kSNH+PHHHwE0HcwTJ04kJiaGLVu2EBgYmGOM69evJyIigsjISDp27FhgI8YaN26Mt7c3rVq1YufOncTGxnLo0CHGjBlDaGholuclJSXRvXt3zp49y9atW5kwYQIDBgxAR0cHMzMzhg8fzpAhQ1ixYgUXL17kxIkTzJ8/nxUrVuQpPn9/f4oWLUqrVq0ICQnh0qVLrFu3jsOHDwMwfvx4fv75ZwICAjhz5gxRUVEEBQUxduzYf3VfhBDiTXHxLI+lnU22aayK2OLimfcXwrJjZmZG165dGTFiBPv27ePMmTN0794dHR0drWlUMzNs2DD27NnD5MmTOX/+PCtWrGDBggUMHz5ck6Zhw4YsWLCA8PBwQkND6dOnT4ZRWwDfffcdGzZs4Ny5c/Tv35/79+/zxRdfZFrukydP+N///seRI0e4cuUKYWFhfPHFF9y4cYP27dv/uxuSR66urprRXlFRUfTu3Zu///5bK42zszNHjx4lNjaWu3fvkpaWRv/+/bl37x7+/v4cP36cixcvsmPHDj7//PM8PbB2d3enVq1ajBo1Cn9//xxngsmtq1evMnToUKKjo1mzZg3z589n0KBBuT6/U6dOGBoa0rVrV06fPs2+ffv48ssv6dy5M/b29hnSm5qa0r17d0aMGMHevXs5ffo03bp1y/GFuQkTJrBmzRomTJhAVFQUp06d0swW4ObmRqdOnejSpQvr16/n8uXLHDt2jKlTp7Jly5a83RAhhBBvhJWPHQYljMjuQYNBCSOsfArmOUNu6z8XFxeSk5OZP38+ly5dYuXKlfzwww9aaQYPHsyOHTu4fPkyJ06cYN++fXl+kfBlVlZW2NjYsHjxYi5cuMDevXsZOnRopmnz0q7KqS1z9OhRvvnmG0JDQ7l69Srr16/nzp07mmtxdnbm5MmTREdHc/fu3XybwUgIId6EPA/P2bFjB5s2bdJ80tLS2LNnj9Y+IYR433j6+lO75UCs6tjS8H4rnIe4FXZIQrw31Do6zG1dFcj4PfjF9pzWXqjf4lHFy5Yto2rVqjRv3hxvb28URWHr1q2ZdgLkxrhx4xg2bBjjx4/H3d2dDh06aNZX09PTY82aNZw7d45KlSoxffp0vv7662zzmzVrFlZWVtSuXZsWLVrg5+eHl5fXa8WWE5VKxdatW6lXrx6ff/45bm5ufPrpp1y5ciXTh+IvNGrUCFdXV+rVq0eHDh34+OOPmThxoub45MmTGTduHFOnTsXd3Z0mTZqwZcuWPE83p6+vz86dOylSpAjNmjXDw8ODadOmaUYY+Pn5sXnzZnbu3En16tWpVasWs2fPxsnJ6bXuhxBCvGk6ajXtB/fKNk27QT3RyeXI4ryYNWsW3t7eNG/enMaNG1OnTh3c3d1zXIbDy8uL3377jaCgICpWrMj48eOZNGkS3bp106QJDAzE0dERHx8fOnbsyPDhwzE2Ns6Q17Rp05g2bRqenp4cPHiQTZs2ZTmzilqt5ty5c7Rt2xY3NzdatGhBfHw8wcHBVKhQ4V/di7waO3YsXl5e+Pn54evrq3kx7GXDhw9HrVZTvnx57OzsuHr1KsWKFSMkJITU1FQ+/PBDPDw8GDx4MJaWlnmekeXFlLVZPUR/HV26dOHp06fUqFGD/v37M2jQIHr1yv7f58uMjY3ZsWMH9+7do3r16rRr145GjRqxYMGCLM+ZMWMGPj4+tGjRgsaNG1O3bl2qVq2abTm+vr6sXbuWTZs2UblyZRo2bMixY8c0x5ctW0aXLl0YNmwYZcuWpVWrVhw/fpySJUvm+lqEEEK8OSq1inKzK///xqsH0/8oN7syKnX2LwS+rtzWf56ensyaNYvp06dTsWJFVq1axdSpU7XSpKam0r9/f833YDc3N77//vvXjk1HR4egoCDCwsKoWLEiQ4YMYcaMGZmmzUu7Kqe2jLm5OX/99RfNmjXDzc2NsWPHEhgYSNOmTQHo2bMnZcuWpVq1atjZ2WWY9UgIId5mKuXVRc+ykZsvaiqVKse3px89eoSFhQUPHz7E3Nw8t8ULIYQQohAVdP29PvIagzaEcf3BP1OJO1oaM6e1F2088zZVuHi3dOvWjQcPHrBx48bCDkUIId4bEfsPsXbOYh7c+WfZN6sitrQb1JPKvrXfSAxPnjyhePHiBAYG0r179wItKzY2llKlShEeHk7lypULtKz31eTJk1m7di0nT57Ml/x8fX2pXLkyc+bMyZf8hBBCiLz6e8N1zg2J4Pn1f54zGJQwotzsyti3LlEgZUr9J4QQ/z26eUlcUNONCiGEEEK08XSkpUdxgi/eIe7RUxzMjfApY/dWj2gXQggh3laVfWtTyacmFyLP8ij+HuY21rh4li+QEe0vhIeHc+7cOWrUqMHDhw+ZNGkSwGstqyLenISEBGJjY1mwYEGOs+UIIYQQ7xL71iUo8nFx7gff4fmtZxgUNcTKx67ARrQLIYT4b8pTZ3tO0tLS2Lp1K82bN8/PbIUQQgjxH6HW0cHXNeupxoUQQgiRezpqNW5eHm+0zJkzZxIdHY2+vj5Vq1YlODg4y+lGxdthwIABrFmzhlatWuXrFPJCCCHE20ClVmHtW6SwwxBCCPEey9M08lm5cOECP/30E8uXL+fOnTskJydnm16mkRdCCCHePVJ/CyGEEEIIIYQQQgghhBD/eO15WZ8+fcrPP/9MvXr1KFu2LIcOHWL8+PFcv349P+MTQgghhBBCCCGEEEIIIYQQQggh3jp5nkb++PHjLF26lKCgIMqUKUOnTp04dOgQ33//PeXLly+IGIUQQgghhBBCCCGEEEIIIYQQQoi3Sp462ytVqsSjR4/o2LEjhw4dokKFCgB89dVXBRKcEEIIIYQQQgghhBBCCCGEEEII8TbK0zTy0dHR1KtXjwYNGsgodiGEEEIIIYQQQgghhBBCCCGEEP9Zeepsv3TpEmXLlqVv376UKFGC4cOHEx4ejkqlKqj4hBDinaKkKiTdfV7YYQghhBBCCCGEEEIIIYQQQogClqfO9uLFizNmzBguXLjAypUruXXrFnXq1CElJYXly5dz/vz5gopTCCHeCeeGRnCgxJ8kRD0q7FCEEEIIIYQQQgghhBBCCCFEAcpTZ/vLGjZsyC+//EJcXBwLFixg7969lCtXjkqVKuVnfEII8U4xr2KJpbcN+rYGhR2KECIfxMbGolKpiIiIyPU5y5cvx9LS8q2I5X2zf/9+VCoVDx48AAruXgshhHg9vr6+DB48uFBjeLWuEEIIIYR42zg7OzNnzpzCDuOtlJu23Os8C3iTz1RUKhUbN27MNk1uryE3eRWkl8uX51JCZO21O9tfsLCwoF+/foSGhnLixAl8fX3zISwhhHg3Fe9Wiur7GqBv90pn+/VHEBYHilI4gQnxjkhLTePW/rNcXnOIW/vPkpaaVtghvXfyoyNk4sSJqFSqbD9CCCEKX2pqKoci97Nx7xoORe4nNTW1sEP6T5AHkUIIIcTbQ0lLJeHcfu4fWUPCuf0oadIeehNe9wXI2rVrExcXh4WFRcEE9pbo0KGD1kzREydOpHLlyhnSxcXF0bRp0zcYmRDidejmZ2aVK1dm3rx5+ZmlEEK8MxRFQUlW0NHP5D2mozfTO9xdrMDC8M0HJ8Q74Or6Y4QO+pnE6/c0+4xLWFNtbhdKtqlRiJGJVw0fPpw+ffpotqtXr06vXr3o2bNnIUYlhBDiZVuD1zPh+0HE3b2u2edgW4KAfnNp5tOmECMTQgghhHgzHoat5+bqQSTf/6c9pGdVgmId52JRVdpDbyN9fX2KFi1a2GEUqOTkZIyMjDAyMsox7ft+L4R4X+RpZHvDhg1z/DRq1KigYhVCiLfame7H2V9sE0l3nmc82NAZWrhKR7sQWbi6/hh/tZuj1dEOkHjjHn+1m8PV9ccKpNzt27dTt25dLC0tsbGxoXnz5ly8eDHL9C/ezN6yZQuVKlXC0NCQWrVqcfr06Qxpd+zYgbu7O6ampjRp0oS4uDjNsePHj/PBBx9ga2uLhYUF9evX58SJE7mK+dy5c9SuXRtDQ0MqVqzIgQMHtI6fPn2apk2bYmpqir29PZ07d+bu3bsAdOvWjQMHDjB37lzNCPTY2FhSU1Pp3r07pUqVwsjIiLJlyzJ37twsYzA1NaVo0aKaj1qtxszMTGtfVkJCQvD19cXY2BgrKyv8/Py4f/8+AGlpaUydOlUTh6enJ7///nuu7osQQoh/bA1eT+9J7bQ62gFu3b1B70nt2Bq8vkDLnzRpEhUrVsywv3LlyowbNw5Ir5NatWrFN998g729PZaWlkyaNImUlBRGjBiBtbU1JUqUYNmyZZrzX4wYDwoKyrYuBAgLC6NatWoYGxtTu3ZtoqOjtY4vXLiQMmXKoK+vT9myZVm5cqXW8QcPHtC7d2/s7e015WzevJknT55gbm6eoX7auHEjJiYmPH78mFKlSgFQpUoVVCqV1gyAS5cuxd3dHUNDQ8qVK8f333+ft5srhBBCiFx5GLaeK9+10+poB0i+f4Mr37XjYVjBtId8fX0ZMGAAAwYMwMLCAltbW8aNG4eSzWyXs2bNwsPDAxMTExwdHenXrx8JCQma41euXKFFixZYWVlhYmJChQoV2Lp1K/DPc4odO3ZQpUoVjIyMaNiwIbdv32bbtm24u7tjbm5Ox44dSUxM1OSZm+ch169fx9/fH2tra0xMTKhWrRpHjx4lNjYWHR0dQkNDtdLPmTMHJycnLl26RIMGDQCwsrJCpVLRrVs3AJ4/f87AgQMpUqQIhoaG1K1bl+PHj2vyyGxE/PLlyylZsiTGxsa0bt2a+Pj4HH8Ox44do0qVKhgaGlKtWjXCw8MzpMnu+Qmk/ywHDhzIyJEjsba2pmjRokycOFErj5iYGOrVq4ehoSHly5dn165dWsdftF9//fVX6tevj6GhIatWrdKaRn758uUEBAQQGRmpeVazfPlyIOM08ln9TLKSU/o//vgDLy8vDA0NKV26NAEBAaSkpOR4f4UQ2vLU2b5//34uX75M+fLl8fT0zPQja7YLIf6rDJ1MMHYxRccgk1+tVoZQ2urNByXEOyAtNY3QQT9DZt87/39f6OCVBTKl/JMnTxg6dCihoaHs2bMHHR0dWrduTVpa9mWNGDGCwMBAjh8/jp2dHS1atCA5OVlzPDExkZkzZ7Jy5Ur++usvrl69yvDhwzXHHz9+TNeuXTl48CBHjhzB1dWVZs2a8fjx4xxjHjFiBMOGDSM8PBxvb29atGih+aL54MEDGjZsSJUqVQgNDWX79u38/ffffPLJJwDMnTsXb29vevbsSVxcHHFxcTg6OpKWlkaJEiVYu3YtZ8+eZfz48fzvf//jt99+e53bmqWIiAgaNWpE+fLlOXz4MAcPHqRFixaaaY2nTp3Kzz//zA8//MCZM2cYMmQIn332WaadKEIIITKXmprKhO8HoWRSsb7YN3Hh4AKdUv6LL74gKipK68FpeHg4J0+e5PPPP9fs27t3Lzdv3uSvv/5i1qxZTJgwgebNm2NlZcXRo0fp06cPvXv35vp17Yfk2dWFL4wZM4bAwEBCQ0PR1dXliy++0BzbsGEDgwYNYtiwYZw+fZrevXvz+eefs2/fPiD95a+mTZsSEhLCL7/8wtmzZ5k2bRpqtRoTExM+/fRTrZcAAJYtW0a7du0wMzPj2LH0lwR3795NXFwc69enP8xftWoV48ePZ8qUKURFRfHNN98wbtw4VqxYkQ93XQghhBAvKGmp3Fw9iOweNNxcM7jAppRfsWIFurq6HDt2jLlz5zJr1iyWLl2aZXodHR3mzZvHmTNnWLFiBXv37mXkyJGa4/379+f58+f89ddfnDp1iunTp2NqaqqVx8SJE1mwYAGHDh3i2rVrfPLJJ8yZM4fVq1ezZcsWdu7cyfz58zXpc3oekpCQQP369blx4wabNm0iMjKSkSNHkpaWhrOzM40bN860PdStWzecnJxYt24dANHR0cTFxWle6B85ciTr1q1jxYoVnDhxAhcXF/z8/Lh3T3vwxQtHjx6le/fuDBgwgIiICBo0aMDXX3+d7f1PSEigefPmlC9fnrCwMCZOnKj1TAZyfn7ywooVKzAxMeHo0aN8++23TJo0SdOhnpaWRps2bdDX1+fo0aP88MMPjBo1KtOYvvrqKwYNGkRUVBR+fn5axzp06MCwYcOoUKGC5llNhw4dMr2urH4mWd2H7NIHBwfTpUsXBg0axNmzZ1m0aBHLly9nypQp2d5fIUQmlDz49ttvFXd3d6VIkSLKkCFDlFOnTuXldI2HDx8qgPLw4cPXOl8IIYQQb15B1d9x+84oK/HP8RO370y+lpuZO3fuKICmjXP58mUFUMLDwxVFUZR9+/YpgBIUFKQ5Jz4+XjEyMlJ+/fVXRVEUZdmyZQqgXLhwQZPmu+++U+zt7bMsNzU1VTEzM1P+/PPPLNO8iGXatGmafcnJyUqJEiWU6dOnK4qiKJMnT1Y+/PBDrfOuXbumAEp0dLSiKIpSv359ZdCgQTnei/79+ytt27bNMZ2iKIqTk5Mye/bsHNP5+/srderUyfTYs2fPFGNjY+XQoUNa+7t37674+/srivLP/b9//76iKOn32sLCIlcxCiHEf0VIxD6leGNy/IRE7Mv3sl+uY5o2bar07dtXc+zLL79UfH19Ndtdu3ZVnJyclNTUVM2+smXLKj4+PprtlJQUxcTERFmzZo2iKLmrC1/UFbt379ak2bJliwIoT58+VRRFUWrXrq307NlTK/b27dsrzZo1UxRFUXbs2KHo6Oho6s5XHT16VFGr1crNmzcVRVGUv//+W9HV1VX279+vFeeL9sMLZcqUUVavXq21b/LkyYq3t3em5QghhBDi9TyO2qdEfk6On8dR+/K97Pr16yvu7u5KWlqaZt+oUaMUd3d3zXZO36HXrl2r2NjYaLY9PDyUiRMnZpo2s7bP1KlTFUC5ePGiZl/v3r0VPz+/LMt89XnIokWLFDMzMyU+Pj7T9L/++qtiZWWlPHv2TFEURQkLC1NUKpVy+fJlrbhefH9XFEVJSEhQ9PT0lFWrVmn2JSUlKcWKFVO+/fbbTM/z9/fXtNFe6NChQ7bPAhYtWqTY2Nho2n6KoigLFy7Uap/l9vlJ3bp1tdJUr15dGTVqlKIo6W1GXV1d5caNG5rj27ZtUwBlw4YNiqL80y6cM2eOVj6vPs+YMGGC4unpmeFaXs4rp59JZvchu/SNGjVSvvnmG619K1euVBwcHDItP6s2rhBCUfI0sn3EiBGcPXuWjRs38vjxY+rUqUONGjX44YcfePTo0b/s9hdCCCHEf9HTuAf5mi4vYmJi8Pf3p3Tp0pibm+Ps7AzA1atXsz3P29tb83dra2vKli1LVFSUZp+xsTFlypTRbDs4OHD79m3N9t9//03Pnj1xdXXFwsICc3NzEhISNOX26dMHU1NTzSersnV1dalWrZqm7MjISPbt26d1brly5QCynR4f4LvvvqNq1arY2dlhamrK4sWLc7wPefViZHtmLly4QGJiIh988IFW/D///HOOsQshhPjH7fi4nBPlId3r6tmzJ2vWrOHZs2ckJSWxevVqrdHlABUqVEBH55/HEvb29nh4eGi21Wo1NjY2WnUoZF8XvvDyrHsODg4AmnyioqKoU6eOVvo6depo8oiIiKBEiRK4ubllem01atSgQoUKmhHpv/zyC05OTtSrVy/L+/HkyRMuXrxI9+7dteq5r7/+Wuo5IYQQIp8lP8hdOye36fKqVq1aqFQqzba3tzcxMTFZziy0e/duGjVqRPHixTEzM6Nz587Ex8drpn0fOHAgX3/9NXXq1GHChAmcPHkyQx4vt33s7e0xNjamdOnSWvteblPl9DwkIiKCKlWqYG1tnWnMrVq1Qq1Ws2HDBiB9KvQGDRpo8snMxYsXSU5O1mqH6enpUaNGjQxtuReioqKoWbOm1r6X24JZnfNi6b+szsnt85NXZ3J++flOVFQUjo6OFCtWLMfYqlWrlm3MuZHTzySv6SMjI5k0aZLWPXgxE+LLSw4IIXKm+zoneXt74+3tzdy5c1m7di3fffcdw4cP5+bNm5ibm+d3jEIIIYR4jxk5WOZrurxo0aIFTk5OLFmyhGLFipGWlkbFihVJSkr6V/nq6elpbatUKq312bp27Up8fDxz587FyckJAwMDvL29NeVOmjQpwxRnuZGQkECLFi2YPn16hmMvOhoyExQUxPDhwwkMDMTb2xszMzNmzJiR7bpfr8PIyCjLYy/Wo9uyZQvFixfXOmZgYJCvcQghxPusiE3Wv+9fJ93ratGiBQYGBmzYsAF9fX2Sk5Np166dVprM6svM9uW0vEtmXs7nxcPu3OaTXX31Qo8ePfjuu+/46quvWLZsGZ9//rnWQ/VXvajnlixZkuGBsVqtzlVcQgghhMgdPcvctXNym64gxcbG0rx5c/r27cuUKVOwtrbm4MGDdO/enaSkJIyNjenRowd+fn6a6eCnTp1KYGAgX375pSafV9s+ObWpcnoeklN7SF9fny5durBs2TLatGnD6tWrNVPFvwty+/wkv9qmJiYmeQ/yFblpo+YlfUJCAgEBAbRp0ybDsZdfVBBC5CxPI9tfdeLECQ4cOEBUVBQVK1bM8ItHCCFE5gpyjUwh3jVFfMphXMIasno+rQJjRxuK+JTL13Lj4+OJjo5m7NixNGrUCHd3d+7fv5+rc48cOaL5+/379zl//jzu7u65LjskJISBAwfSrFkzKlSogIGBAXfv3tUcL1KkCC4uLppPVmWnpKQQFhamKdvLy4szZ87g7Oysdb6Li4vmi52+vn6G30EhISHUrl2bfv36UaVKFVxcXApklF2lSpXYs2dPpsfKly+PgYEBV69ezRC7o6NjvscihBDvq5oVfXCwLYEqi4pVhYpido7UrOhToHHo6urStWtXli1bxrJly/j000/z/IAwK9nVhbnh7u5OSEiI1r6QkBDKly8PpNdX169f5/z581nm8dlnn3HlyhXmzZvH2bNn6dq1q+aYvr4+oN3mt7e3p1ixYly6dClDPVeqVKlcxy6EEEKInJm4+aBnVYLsHjToWTti4lYw7aFXX1w/cuQIrq6umb5gFxYWRlpaGoGBgdSqVQs3Nzdu3ryZIZ2joyN9+vRh/fr1DBs2jCVLlrx2fLl5HlKpUiUiIiKyXEsd0l8+3L17N99//z0pKSlanbaZtYfKlCmDvr6+VjssOTmZ48ePa9phr3J3d8/0fmbH3d2dkydP8uzZsyzPyc3zk5y4u7tz7do14uL+mSEhp9iyktmzmlfl5meSl/ReXl5ER0dnuH4XFxet2aeEEDnL8/+Ymzdv8s033+Dm5ka7du2wtrbm6NGjHDlyJN++OAshxPvs4rWrTFnyA5HR5wo7FCHeCjpqHarN7ZK+8er34P/frjanMzrq/G3oW1lZYWNjw+LFi7lw4QJ79+5l6NChuTp30qRJ7Nmzh9OnT9OtWzdsbW1p1apVrst2dXVl5cqVREVFcfToUTp16pTrdtR3333Hhg0bOHfuHP379+f+/fuaaXn79+/PvXv38Pf35/jx41y8eJEdO3bw+eefa760OTs7c/ToUWJjY7l79y5paWm4uroSGhrKjh07OH/+POPGjeP48eO5vp7cGj16NMePH6dfv36cPHmSc+fOsXDhQu7evYuZmRnDhw9nyJAhrFixgosXL3LixAnmz5+vmaZXCCFEztRqNQH90kcVvdrh/mJ7Yt85b2Q0dY8ePdi7dy/bt2/PMIX8v5FdXZgbI0aMYPny5SxcuJCYmBhmzZrF+vXrNbPK1K9fn3r16tG2bVt27drF5cuX2bZtG9u3b9fkYWVlRZs2bRgxYgQffvghJUqU0BwrUqQIRkZGbN++nb///puHDx8CEBAQwNSpU5k3bx7nz5/n1KlTLFu2jFmzZuXTnRFCCCEEgEpHTbGOL0ZZZ/6goZj/HFQ6BdMeunr1KkOHDiU6Opo1a9Ywf/58Bg0alGlaFxcXkpOTmT9/PpcuXWLlypX88MMPWmkGDx7Mjh07uHz5MidOnGDfvn15etHwVbl5HuLv70/RokVp1aoVISEhXLp0iXXr1nH48GFNGnd3d2rVqsWoUaPw9/fXeq7h5OSESqVi8+bN3Llzh4SEBExMTOjbty8jRoxg+/btnD17lp49e5KYmEj37t0zjXXgwIFs376dmTNnEhMTw4IFC7TaZJnp2LEjKpWKnj17cvbsWbZu3crMmTO10uTm+UlOGjdujJubG127diUyMpLg4GDGjBmTq3Nf5ezszOXLl4mIiODu3bs8f/48Q5rc/Ezykn78+PH8/PPPBAQEcObMGaKioggKCmLs2LGvdQ1C/Jfl6al1s2bNKFOmDEePHmXGjBlcv36dmTNnZvnWkRBCiIwM9PWxMDXD0MCAyzeuyyh3IYCSbWpQ7/fBGBfXXkfKuIQN9X4fTMk2NfK9TB0dHYKCgggLC6NixYoMGTKEGTNm5OrcadOmMWjQIKpWrcqtW7f4888/NW9t58aPP/7I/fv38fLyonPnzgwcOJAiRYrkuuxp06bh6enJwYMH2bRpE7a2tgAUK1aMkJAQUlNT+fDDD/Hw8GDw4MFYWlpq3koePnw4arWa8uXLY2dnx9WrV+nduzdt2rShQ4cO1KxZk/j4ePr165fr68ktNzc3du7cSWRkJDVq1MDb25s//vgDXd30lY0mT57MuHHjmDp1Ku7u7jRp0oQtW7bIiD8hhMijZj5tWDT+d4raai/L4WBXgkXjf6eZT8apIguCq6srtWvXply5chmmTv83sqsLc6NVq1bMnTuXmTNnUqFCBRYtWsSyZcvw9fXVpFm3bh3Vq1fH39+f8uXLM3LkyAzt9hfTu77a0a+rq8u8efNYtGgRxYoVo2XLlkD6ywdLly5l2bJleHh4UL9+fZYvXy71nBBCCFEALKq2wan/7+hZabeH9KxL4NT/dyyqFlx7qEuXLjx9+pQaNWrQv39/Bg0aRK9evTJN6+npyaxZs5g+fToVK1Zk1apVTJ06VStNamoq/fv313xPdnNz4/vvv3/t+HLzPERfX5+dO3dSpEgRmjVrhoeHB9OmTcvwwmZW7aHixYsTEBDAV199hb29PQMGDADS23Ft27alc+fOeHl5ceHCBXbs2IGVlVWmsdaqVYslS5Ywd+5cPD092blzZ46dwaampvz555+cOnWKKlWqMGbMmAzTxefm+Ulu7uOGDRs0P+sePXowZcqUXJ37qrZt29KkSRMaNGiAnZ0da9asyZAmtz+T3Kb38/Nj8+bN7Ny5k+rVq1OrVi1mz56Nk5PTa12DEP9lKuXlBURzoKOjg4ODA0WKFMl2LbITJ05km8+jR4+wsLDg4cOHssa7EOI/KzL6HBv37qZxrdrUqeJV2OEIkaM3UX+npaZxO/gcT+MeYORgSRGfcvk+ov3f2L9/Pw0aNOD+/ftYWloWdjhCCCFEtlJTUzl6Opjb8XEUsXGgZkWfN7o+uKIouLq60q9fv1zPHpOd2NhYSpUqRXh4OJUrV/73Af5LK1euZMiQIdy8eTNPL90JIYQQ4s1R0lJ5cj6Y5Adx6Fk6YOLmU2Aj2gF8fX2pXLkyc+bMKbAy3iaTJ09m7dq1nDx5srBDEUKIQqObl8Tjx4/PtpNdCCFE7jkXL07lsuVwc3Iu7FCEeGvoqHUo6isz5gghhBD5Qa1WU9vTt1DKvnPnDkFBQdy6dYvPP/+8UGIoKImJicTFxTFt2jR69+4tHe1CCCHEW0ylo8a0nG9hh/HeSUhIIDY2lgULFvD1118XdjhCCFGo8tTZPnHixAIKQwgh/nssTM1o2bBxYYchhBBCCCFEvitSpAi2trYsXrw4y2lB31XffvstU6ZMoV69eowePbqwwxFCCCGEeOMGDBjAmjVraNWqVYYp5IUQ4r8mT9PIW1lZZTqy3cLCAjc3N4YPH84HH3yQYz4yjbwQQgjx7pH6WwghhBBCCCGEEEIIIYT4R55Gtme1zsiDBw8ICwujefPm/P7777Ro0SI/YhNCCCGEEEIIIYQQQgghhBBCCCHeSnnqbO/atWu2xytXrszUqVOls10IIfLRzetxLJy1lE+7tqOCp3thhyOEEEIIIYQQQgghhBBCCCEAnfzMrHnz5pw7dy4/sxRCiHfag7vx3L5+k9Wzvmf3bxtzfV7S3ecEu20lZuwprly+xoljkZw7c77gAhVCCCGEEEIIIYQQQgghhBB5kqeR7Tl5/vw5+vr6+ZmlEEK8U/6+egNjc1Mun4lGV1+PiL8O8/RJIhY2VugbGOQ6HyVNITUhhdTEVLx9arB49TyKOToUYORCCCGEEEIIIYQQQgghhBAiL/K1s/3HH3+kcuXK+ZmlEEK8M54mPGHTj79g42DP3Zu3ACjq5Ih79cq4elbE1MI813kZFDHE9+bHmu3iJYtlmm728bXsvnKCtS3GY2xg9O8uQAghhBBCCCGEEEIIIYQQQuRanjrbhw4dmun+hw8fcuLECc6fP89ff/2VL4EJIcS7xtDEmCr1vIkMOYaunh6o4Pb1m1jYWLFm1kLa9vsca/siWuckpSRx5nokpYu4YmFsmaty/tqwlaePn+DXpT0Hb5ym9W8PMZw7FzYOABvTArgyIYQQQgghhBBCCCGEEEII8ao8rdkeHh6e6efu3bt88MEHnD59mqpVqxZUrEII8VZTqVRUa1QPcytLdPV0SUlKpuaHvhQv40wJl1IYm5llOOfWgxucuhZOzK1zmn0pKSmkpaVlWc6u1WvZtjyItLQ0VjcfQ8e6H6NjZQLtf4ApW+DSnQK5PiH+i2JjY1GpVERERLzRclUqFRs3bnyjZb6rfH19GTx4cGGHIYQQ4j1TWG0AIYQQQgiRv5ydnZkzZ45mW565CCHyW55Gtu/bt6+g4hBCiPeGWleNvoEBdZv74ezuho5aBxeP8hnSpabBiRgn7M0a4eFYHEjvaO/+SX9KlCzOlDnjM5yzbstQEtx/pVfbnejo6GDwHAiPg9plYMspWBsKp2/Aml4FfZlCFAxFgadJkJoKajUY6YNKVdhRCSGEEO+kVCWVs4+CuZ8ch5WeA+XNfVCr1IUdlhBCCCHEG6Mo8CwFUhVQq8BQVx4zFBZnZ2euXLkCgI6ODvb29jRt2pSZM2diZWVVyNEJIcTry9c124UQQkCrXl0BBR119g8y09Ig7r4O9koZDPTS96ku3aVYqj4OtjaadInPnnLx2jUqlHHBysKRIraulCjtmn7w/N9w8jroqKCtF+iqwdOxgK5MiAKW8BTuPEx/E+UFtQ7YWYCpUeHF9Q5KSkpCX1+/sMPI0tsenxBCvA8Ox69naexg4pOua/bZ6Jegh/McvG3aFGJkBSs5ORk9Pb3CDkMIIYQQb4EnSXD3aXpH+wtqFdgagclb9JW0sL4jF1S52bXHJk2aRM+ePUlNTeX8+fP06tWLgQMHsnLlynyPQwgh3pQ8TSMvhBAiZzpqnRw72gH0dKH7B9Cy1j/7HuwKp0yV0nxYoaJm38ETJ1i/eyfnLl+iYd0hjB4YibmZffrBvx+ld0yqdWD5IdBXg49rfl+SEAUv4Sncuq/d0Q7p27fupx8vANu3b6du3bpYWlpiY2ND8+bNuXjxYqZp09LSKFGiBAsXLtTaHx4ejo6Ojubt7AcPHtCjRw/s7OwwNzenYcOGREZGap2zcOFCypQpg76+PmXLls3xS+WoUaNwc3PD2NiY0qVLM27cOJKTkzXHJ06cSOXKlVm6dCmlSpXC0NAw03yWL1+OpaUlmzdvpmzZshgbG9OuXTsSExNZsWIFzs7OWFlZMXDgQFJTUzXnrVy5kmrVqmFmZkbRokXp2LEjt2/f1sr7zJkzNG/eHHNzc8zMzPDx8dHcy27dutGqVSumTJlCsWLFKFu2LACnTp2iYcOGGBkZYWNjQ69evUhISNDk+eK8gIAAzf3s06cPSUlJGX42I0eOxNramqJFizJx4kSt47NmzcLDwwMTExMcHR3p16+fVjkAS5YswdHREWNjY1q3bs2sWbOwtLTUSvPHH3/g5eWFoaEhpUuXJiAggJSUlGx+ckIIUTgOx69n+vn2Wh3tAPFJN5h+vj2H49cXSLm+vr58+eWXDB48GCsrK+zt7VmyZAlPnjzh888/x8zMDBcXF7Zt2wZAamoq3bt3p1SpUhgZGVG2bFnmzp2bId+ffvqJChUqYGBggIODAwMGDNAcU6lULFy4kI8//hgTExOmTJkC5FzXvjivadOmGBkZUbp0aX7//fcMZV+6dIkGDRpgbGyMp6cnhw8f1hyLj4/H39+f4sWLY2xsjIeHB2vWrNE6//Hjx3Tq1AkTExMcHByYPXt2hiVQnj9/zvDhwylevDgmJibUrFmT/fv35/n+CyGEEOIfT5Lg70TtjnZI3/47Mf14QfD19WXAgAEMGDAACwsLbG1tGTduHIryTyDOzs5MnjyZLl26YG5uTq9e6TNUHjx4EB8fH4yMjHB0dGTgwIE8efJEc97z588ZNWoUjo6OGBgY4OLiwo8//gj8833/ZRs3bkT10jD+rJ4d/P7773h4eGi+mzdu3FhTblpaGpMmTaJEiRIYGBhQuXJltm/frsnzxdI7v/76K/Xr18fQ0JBVq1ZleX9ePFcoXrw4DRo0oGvXrpw4cSLbe/rgwQN69+6Nvb09hoaGVKxYkc2bN2uO53TfhBCioElnuxBCFCJ9Pbhy8xqR0elrtj9u6s4Nez1uO5lq0lQtXwGfqtUo41hS++Sjl0BXB6xNIPwKTG8HnWohxDtHUdJHtGfn7sP0dPnsyZMnDB06lNDQUPbs2YOOjg6tW7cmLS0tQ1odHR38/f1ZvXq11v5Vq1ZRp04dnJycAGjfvj23b99m27ZthIWF4eXlRaNGjbh37x4AGzZsYNCgQQwbNozTp0/Tu3dvPv/882yX6zEzM2P58uWcPXuWuXPnsmTJEmbPnq2V5sKFC6xbt47169dnu75sYmIi8+bNIygoiO3bt7N//35at27N1q1b2bp1KytXrmTRokVaHQ7JyclMnjyZyMhINm7cSGxsLN26ddMcv3HjBvXq1cPAwIC9e/cSFhbGF198odURvWfPHqKjo9m1axebN2/myZMn+Pn5YWVlxfHjx1m7di27d+/W6kB5cV5UVBT79+9nzZo1rF+/noCAAK00K1aswMTEhKNHj/Ltt98yadIkdu3apfWzmzdvHmfOnGHFihXs3buXkSNHao6HhITQp08fBg0aREREBB988IGms+aF4OBgunTpwqBBgzh79iyLFi1i+fLlGdIJIURhS1VSWRo7GMis3kzf92PsEFKV1EyO/3srVqzA1taWY8eO8eWXX9K3b1/at29P7dq1OXHiBB9++CGdO3cmMTFR8yLb2rVrOXv2LOPHj+d///sfv/32mya/hQsX0r9/f3r16sWpU6fYtGkTLi4uWmVOnDiR1q1bc+rUKb744otc17Xjxo2jbdu2REZG0qlTJz799FOioqK00owZM4bhw4cTERGBm5sb/v7+mvrt2bNnVK1alS1btnD69Gl69epF586dOXbsmOb8oUOHEhISwqZNm9i1axfBwcEZHigPGDCAw4cPExQUxMmTJ2nfvj1NmjQhJiYmX34mQgghxH+NoqSPaM/O3acF8pgBSG8P6erqcuzYMebOncusWbNYunSpVpqZM2fi6elJeHg448aN4+LFizRp0oS2bdty8uRJfv31Vw4ePKj1HblLly6sWbOGefPmERUVxaJFizA1NX21+Gy9+uwgLi4Of39/vvjiC8137zZt2mheDpg7dy6BgYHMnDmTkydP4ufnx8cff5yhnfLVV18xaNAgoqKi8PPzy1UsN27c4M8//6RmzZpZpklLS6Np06aEhITwyy+/cPbsWaZNm4b6/wc65ea+CSFEgVMKwcOHDxVAefjwYWEUL4QQr+XSdUU5FJFzunu37yiXo84rd+P+Vk4dPq6kpaZlm37Bml+Uid/PV54nJSmKoihPEhNzF1CT2YriFaCkbD+lXF68VXnyNJfnCfGaCqz+fvJMUWJu5Px58ix/y83EnTt3FEA5deqUoiiKcvnyZQVQwsPDFUVRlPDwcEWlUilXrlxRFEVRUlNTleLFiysLFy5UFEVRgoODFXNzc+XZM+1Yy5QpoyxatEhRFEWpXbu20rNnT63j7du3V5o1a6bZBpQNGzZkGeeMGTOUqlWrarYnTJig6OnpKbdv3872+pYtW6YAyoULFzT7evfurRgbGyuPHz/W7PPz81N69+6dZT7Hjx9XAM05o0ePVkqVKqUk/f/vsVd17dpVsbe3V54/f67Zt3jxYsXKykpJSEjQ7NuyZYuio6Oj3Lp1S3OetbW18uTJE02ahQsXKqampkpqaqqiKIpSv359pW7dulrlVa9eXRk1alSW8a9du1axsbHRbHfo0EH56KOPtNJ06tRJsbCw0Gw3atRI+eabb7TSrFy5UnFwcMiyHCGEKAwnH+xTWh5S5fg5+WBfvpf96u/klJQUxcTEROncubNmX1xcnAIohw8fzjSP/v37K23bttVsFytWTBkzZkyWZQLK4MGDtfbltq7t06ePVpqaNWsqffv2VRTlnzbA0qVLNcfPnDmjAEpUVFSW8Xz00UfKsGHDFEVRlEePHil6enrK2rVrNccfPHigGBsbK4MGDVIURVGuXLmiqNVq5caNG1r5NGrUSBk9enSW5QghhBAia4lJinLxfs6fxMy/wv4r9evXV9zd3ZW0tH+eB44aNUpxd3fXbDs5OSmtWrXSOq979+5Kr169tPYFBwcrOjo6ytOnT5Xo6GgFUHbt2pVpucuWLdP6DqsoirJhwwbl5S6gzJ4dhIWFKYASGxubab7FihVTpkyZorWvevXqSr9+/RRF+afNNGfOnEzPf5mTk5Oir6+vmJiYKIaGhgqg1KxZU7l//36W5+zYsUPR0dFRoqOjMz2e0317Ue7s2bM1x3N65iKEEHklI9uFECKXpi6FEYFwL4cBuAc37WDn6nVsXraaQ1t3czfuVrbpWzVozKdNP0L//9cyMjZ6ZW3qp8lw+S6A9mjbSS1h5iecLaXHipSLHI6MAOAqDxjNdsK4kafrE6LQpOZyZF1u0+VBTEwM/v7+lC5dGnNzc5ydnQG4evVqpukrV66Mu7u7ZnT7gQMHuH37Nu3btwcgMjKShIQEbGxsMDU11XwuX76smVI9KiqKOnXqaOVbp06dDCPpXvbrr79Sp04dihYtiqmpKWPHjs0Qo5OTE3Z2djles7GxMWXKlNFs29vb4+zsrPU2vL29vdY08WFhYbRo0YKSJUtiZmZG/fr1te5TREQEPj4+2a6R6+HhobUWXFRUFJ6enpiYmGj21alTh7S0NKKjozX7PD09MTY21mx7e3uTkJDAtWvXNPsqVaqkVZaDg4NW/Lt376ZRo0YUL14cMzMzOnfuTHx8PImJiQBER0dTo0YNrTxe3Y6MjGTSpElaP9eePXsSFxenyUcIId4G95Pj8jVdXr38O1mtVmNjY4OHh4dmn719+nJIL35Pf/fdd1StWhU7OztMTU1ZvHixpn65ffs2N2/epFGjRtmWWa1aNa3t3Na13t7eGbZfTfPy9Tg4OGjFnpqayuTJk/Hw8MDa2hpTU1N27Nihif/SpUskJydr1SkWFhaa5VQgfUmV1NRU3NzctOqYAwcOZLm0jRBCCCGy9+rU8f82XV7VqlVLa/p2b29vYmJitJZre7X9EhkZyfLly7XaA35+fqSlpXH58mUiIiJQq9Wa7+Ov69VnB56enjRq1AgPDw/at2/PkiVLuH//PgCPHj3i5s2buWpXvXo9WRkxYgQRERGcPHmSPXv2APDRRx9p3ZuXRUREUKJECdzc3DI9ntN9E0KIN0G3sAMQQoh3Ra92cPkGWFtkn65aIx8Obd3Dw/h4vJs2wrZY0WzTO9jZaTXAM5i2FTZFEDGnCZuiQuncvCWlSpSA6qUAcEtKon6NGlRyS39ot/fEXu5USePe04dgXDxP1yhEofj/qb/yLV0etGjRAicnJ5YsWUKxYsVIS0ujYsWKGdYEf1mnTp1YvXo1X331FatXr6ZJkybY2NgAkJCQgIODQ6brrL66dlpuHT58mE6dOhEQEICfnx8WFhYEBQURGBiole7lTuvsvNohrlKpMt334uWeF9O9+/n5sWrVKuzs7Lh69Sp+fn6a+2T06ktCmchtfK8ju/hjY2Np3rw5ffv2ZcqUKVhbW3Pw4EG6d+9OUlKSVkd+dhISEggICKBNmzYZjr1Y504IId4GVnoO+Zour3KqZ160e9PS0ggKCmL48OEEBgbi7e2NmZkZM2bM4OjRo0Du6hd4c3XMy7EDzJgxg7lz5zJnzhw8PDwwMTFh8ODB2bYjXpWQkIBarSYsLEwzHeoLeZ0WVgghhBDp1Nk8ZnuddAXh1fZLQkICvXv3ZuDAgRnSlixZkgsXLmSbn46Ojta68JC+JFxO5arVanbt2sWhQ4fYuXMn8+fPZ8yYMRw9elTzrCM3ctses7W11SwJ5Orqypw5c/D29mbfvn00btw4Q/qc2oM53TchhHgTZGS7EELkUrUK0P7D9L8nPXtGSiYNVgAH55LU+egDUOmgb2iQbUd6Wloa81avZOWff2RdcH03+LACRkWssDA1xUBf+wGmjr6aLVXvssLsZHqe+mqMEhVqKiXydoFCFBYjfVDn0CTR1UlPl4/i4+OJjo5m7NixNGrUCHd3d83b29np2LEjp0+fJiwsjN9//51OnTppjnl5eXHr1i10dXVxcXHR+tja2gLg7u5OSEiIVp4hISGUL18+0/IOHTqEk5MTY8aMoVq1ari6unLlypV/ceV5c+7cOeLj45k2bRo+Pj6UK1dOa9Q4pI/6Cw4OzvSLfFbc3d2JjIzkyZMnmn0hISHo6OhojfiLjIzk6dN/Fts7cuQIpqamODo65qqcsLAw0tLSCAwMpFatWri5uXHz5k2tNGXLluX48eNa+17d9vLyIjo6OsPP1cXFBR0daVILId4e5c19sNEvAWTVBlVhq+9IeXOfNxlWpkJCQqhduzb9+vWjSpUquLi4aI3mNjMzw9nZWTPqKbdyW9ceOXIkw7a7u3ue4m/ZsiWfffYZnp6elC5dmvPnz2uOly5dGj09Pa065eHDh1ppqlSpQmpqKrdv385QvxQtmv1Lu0IIIYTInKFuzh3palV6uoLw4sXBF44cOYKrq2uGF+te5uXlxdmzZzP9zqmvr4+HhwdpaWkcOHAg0/Pt7Ox4/Pix1nfsiIiIXMWrUqmoU6cOAQEBhIeHo6+vz4YNGzA3N6dYsWJ5eoaRVy/uycvf+19WqVIlrl+/rtV+ellO900IId4EeTIohBB5lJKcTGDvHiybMFZ7Wnfg9rVrpCQncyv2IjpqVY4dMCqVCiszcyzMzLJO1NAdprejrLsbgz7rSrEi6VNvJj57ytFTkaQkp1AEU+xIH/ny+UY1c0clYW6cTZ5CvE1UKrDLYcoIW4v0dPnIysoKGxsbFi9ezIULF9i7dy9Dhw7N8TxnZ2dq165N9+7dSU1N5eOPP9Yca9y4Md7e3rRq1YqdO3cSGxvLoUOHGDNmDKGhoUD6lGnLly9n4cKFxMTEMGvWLNavX8/w4cMzLc/V1ZWrV68SFBTExYsXmTdvHhs2bMifm5ALJUuWRF9fn/nz53Pp0iU2bdrE5MmTtdIMGDCAR48e8emnnxIaGkpMTAwrV67Umg7+VZ06dcLQ0JCuXbty+vRp9u3bx5dffknnzp01UwwDJCUl0b17d86ePcvWrVuZMGECAwYMyHUHt4uLC8nJyZr4V65cyQ8//KCV5ssvv2Tr1q3MmjWLmJgYFi1axLZt27Relho/fjw///wzAQEBnDlzhqioKIKCghg7dmyu4hBCiDdFrVLTw3nO/2+9Wnemb3d3no1alf8zxuSVq6sroaGh7Nixg/PnzzNu3LgMLztNnDiRwMBA5s2bR0xMDCdOnGD+/PnZ5pvbunbt2rX89NNPnD9/ngkTJnDs2DEGDBiQp/hfjASLioqid+/e/P3335rjZmZmdO3alREjRrBv3z7OnDlD9+7d0dHR0dQxbm5udOrUiS5durB+/XouX77MsWPHmDp1Klu2bMl1LEIIIYT4h0oFtjlMkGNrlO+PGTSuXr3K0KFDiY6OZs2aNcyfP59BgwZle86oUaM4dOgQAwYMICIigpiYGP744w9N28TZ2ZmuXbvyxRdfsHHjRi5fvsz+/fv57bffAKhZsybGxsb873//4+LFi6xevZrly5fnGOvRo0f55ptvCA0N5erVq6xfv547d+5oXkAcMWIE06dP59dffyU6OpqvvvqKiIiIHK8nK48fP+bWrVvExcVx7NgxRowYgZ2dHbVr1840ff369alXrx5t27Zl165dXL58mW3btrF9+/Zc3TchhHgTpLNdCCHySEetxrFsWQyMDJnYvjXfDRnE0W1bOR8Wyrwv+/LrzG/5ffYMXNydcPWsmG1eKpWKri1b07JB9utQZibszBm2HwzmbEwMI6jHZ1RJz/PCbXRibkNaAS08JURBMDWColYZR7jr6qTvN83dNLJ5oaOjQ1BQEGFhYVSsWJEhQ4YwY8aMXJ3bqVMnIiMjad26tdaUZiqViq1bt1KvXj0+//xz3Nzc+PTTT7ly5YqmA7lVq1bMnTuXmTNnUqFCBRYtWsSyZcvw9fXNtKyPP/6YIUOGMGDAACpXrsyhQ4cYN27cv77+3LKzs2P58uWsXbuW8uXLM23aNGbOnKmVxsbGhr1795KQkED9+vWpWrUqS5YsyXYNd2NjY3bs2MG9e/eoXr067dq1o1GjRixYsEArXaNGjXB1daVevXp06NCBjz/+mIkTJ+Y6fk9PT2bNmsX06dOpWLEiq1atYurUqVpp6tSpww8//MCsWbPw9PRk+/btDBkyRGt6eD8/PzZv3szOnTupXr06tWrVYvbs2Tg5OeU6FiGEeFO8bdowym0tNvraSwrZ6pdglNtavG0yLolRGHr37k2bNm3o0KEDNWvWJD4+nn79+mml6dq1K3PmzOH777+nQoUKNG/enJiYmGzzzW1dGxAQQFBQEJUqVeLnn39mzZo1eRqlNXbsWLy8vPDz88PX15eiRYvSqlUrrTSzZs3C29ub5s2b07hxY+rUqYO7u7tWHbNs2TK6dOnCsGHDKFu2LK1ateL48eMy9akQQgjxL5jog71xxhHualX6fpMCHPTcpUsXnj59So0aNejfvz+DBg2iV69e2Z5TqVIlDhw4wPnz5/Hx8aFKlSqMHz+eYsWKadIsXLiQdu3a0a9fP8qVK0fPnj01I9mtra355Zdf2Lp1Kx4eHqxZsyZX353Nzc3566+/aNasGW5ubowdO5bAwECaNm0KwMCBAxk6dCjDhg3Dw8OD7du3s2nTJlxdXV/r3owfPx4HBweKFStG8+bNMTExYefOndlOWb9u3TqqV6+Ov78/5cuXZ+TIkZo13nNz34QQoqCplFcX8ngDHj16hIWFBQ8fPsTc3PxNFy+EEPnifFgoGxbM48nDB7h4VeXj3n35c9FCPOs3IDr0OPXatsO+ZO47YS5eu4qNpSWWZrn7vfgkMZHI8+eoWr4iBi9NixSVcovFaUfool+DKkjDUuSfN1J/Kwo8TYLU1PQ12o30C+5Vc/HW69atGw8ePGDjxo1vvOyePXty7tw5goOD33jZQgiRX1KVVM4+CuZ+chxWeg6UN/d5K0a0vw1UKhUbNmzI0Dle0J48eULx4sUJDAyke/fub7RsIYQQ4r9IUeBZCqQq/0wdX5CPGXx9falcuTJz5swpuEKEEEK8VQpoVRIhhHj/uVWtxqhlP7Phu3mE7drJgzbt6Dx2AgCVfOrlKa97Dx/wy+ZNuDiWpFPzj3M+ATAxNqZ2Za+MB3R1SJGJS8S7SqUCY4PCjkL8B82cOZMPPvgAExMTtm3bxooVK/j+++8LOywhhPhX1Co1Hha+hR3Gf1p4eDjnzp2jRo0aPHz4kEmTJgHQsmXLQo5MCCGE+G9QqcAo60nXhBBCiH9NOtuFEOJf8qhbj+RnzylSwvG187A0M8e3eg0cizpkejwtLY2twQcoamtHtQrZT03vThHmk7sOeyGEEOmOHTvGt99+y+PHjyldujTz5s2jR48ehR2WEEKI98DMmTOJjo5GX1+fqlWrEhwcjK2tbWGHJYQQQgghhBAiH8g08kII8QY9vn+f54mJ2BYvnnPilzx99ozAFT9Rwr4o3Vq9HWtsiv8eqb+FEEIIIYQQQgghhBBCiH/IyHYhhHiDVk6eyO1rV/nfL2vQNzDM9XlGhob0+7QjRnk4RwghhBBCCCGEEEIIIYQQQhQc6WwXQog3qOoHftyLu4meft7XpLa2sMz/gIQQQgghhBBCCCGEEEIIIcRrkc52IYR4g2o2bab5e0pyMs8TEzGxsMjxvJTUVJ4nJWFiZKTZdyQyArVaTfWKHgAk8JwgTuKDM2Wxy//ghRBCCCGEEEIIIYQQQgghhIZOYQcghBD/VevmzmJGz895FH83x7S/btvC7JXLeZKYqNm3P/QYf4Ud12xf5yFHuEo4NwskXiGEEEIIIYQQQgghhBBCCPEPGdkuhBCFpGS58jxPTMTQxDTbdE+fPePSjesY6uujr6+v2f9Fq7bo6PzzzlQ5ijCGBhTDvMBiFkIIIYQQQgghhBBCCCGEEOlkZLsQQhQS7+Yt6DI+AH1Dw2zT6evp4V6qNHW9qqKn+887UkVsbLC1stJKWwprDOQ9KiHeqOXLl2NpaflelKNSqdi4cSMAsbGxqFQqIiIiCrRMIYQQ4l0wceJEKleurNnu1q0brVq1KrR4hBBCCCEKy6vPC/bv349KpeLBgweFGpcQQhQW6WwXQoi3nFqtpt2HTfD2rFLYoQghMtGhQwfOnz9f2GEIIYQQ/0mvdoILIYQQQvxXvOj0fvHR19fHxcWFr7/+GkVRCjs8IYT4z5Dhj0II8Y7Ye+wIf8ff5dMmH6FSqQo7HCEKRFpqKrFngnl8Lw4zawecK/igo1YXdljZMjIywsjIqLDDEEIIITJITYPIaIh/ADaW4FkW1PLKvRBCCCH+Q1JTUwkOjiAu7i4ODrb4+FRG/ZY9Z0hKStJaOjKvdu/eTYUKFXj+/DkHDx6kR48eODg40L1793yMUgghRFbka7YQQrwjoi5d5HxsLEdORWZ6PPHxvdfO+wYPucbD1z5fiPxwJmQ9Mz535sevGvDbtx358asGzPjcmTMh6wuszO3bt1O3bl0sLS2xsbGhefPmXLx4UXP8xVvi69evp0GDBhgbG+Pp6cnhw4c1aV6d3v3FCLuffvqJkiVLYmpqSr9+/UhNTeXbb7+laNGiFClShClTpmjFMmvWLDw8PDAxMcHR0ZF+/fqRkJCQp+u5fv06/v7+WFtbY2JiQrVq1Th69Kjm+B9//IGXlxeGhoaULl2agIAAUlJS8njXhBBCvAsOHId2Q2HgVAhYmP5nu6Hp+wuKr68vX375JYMHD8bKygp7e3uWLFnCkydP+PzzzzEzM8PFxYVt27ZpzklNTaV79+6UKlUKIyMjypYty9y5c7Xy3b9/PzVq1MDExARLS0vq1KnDlStXWL58OQEBAURGRmpGdC1fvjzL+H766ScqVKiAgYEBDg4ODBgwQHPswYMH9OjRAzs7O8zNzWnYsCGRkZm3u4UQQgjxbli/fh/Ozi1p0KAvHTuOo0GDvjg7t2T9+n0FVqavry8DBgxgwIABWFhYYGtry7hx47RGmjs7OzN58mS6dOmCubk5vXr1AmDdunWatoqzszOBgYG5KtPGxoaiRYvi5OREp06dqFOnDidOnMj2nDNnztC8eXPMzc0xMzPDx8dH63nI0qVLcXd3x9DQkHLlyvH999+/xt0QQoj/BulsF0KId0SrBo1xsLWjqI1thmPB62byzae2XDq5/7XynkkwMzjwLyMU4vWdCVnP6inteHT3utb+R3dvsHpKuwLrcH/y5AlDhw4lNDSUPXv2oKOjQ+vWrUlLS9NKN2bMGIYPH05ERARubm74+/tn20l98eJFtm3bxvbt21mzZg0//vgjH330EdevX+fAgQNMnz6dsWPHanWE6+joMG/ePM6cOcOKFSvYu3cvI0eOzPW1JCQkUL9+fW7cuMGmTZuIjIxk5MiRmmsJDg6mS5cuDBo0iLNnz7Jo0SKWL1+eodNfCCHEu+/AcRgzH+688i7mnXvp+wuyw33FihXY2tpy7NgxvvzyS/r27Uv79u2pXbs2J06c4MMPP6Rz584kJiYCkJaWRokSJVi7di1nz55l/Pjx/O9//+O3334DICUlhVatWlG/fn1OnjzJ4cOH6dWrFyqVig4dOjBs2DAqVKhAXFwccXFxdOjQIdO4Fi5cSP/+/enVqxenTp1i06ZNuLi4aI63b9+e27dvs23bNsLCwvDy8qJRo0bcu/f6L7QKIYQQovCsX7+Pdu1Gcf36ba39N27cpl27UQXa4b5ixQp0dXU5duwYc+fOZdasWSxdulQrzcyZM/H09CQ8PJxx48YRFhbGJ598wqeffsqpU6eYOHEi48aNy/ZFwsyEhoYSFhZGzZo1s0xz48YN6tWrh4GBAXv37iUsLIwvvvhC85xj1apVjB8/nilTphAVFcU333zDuHHjWLFiRZ7vhRBC/BfINPJCCPGOKG5vT6/2HUh8+pQHjx5haW6uOWZboiwOZbwws3Z4rbxbUZ40ZC0nUTjSUlPZvGgQZPpvUAFUbFk0GPdaLfN9Svm2bdtqbf/000/Y2dlx9uxZKlasqNk/fPhwPvroIwACAgKoUKECFy5coFy5cpnmm5aWxk8//YSZmRnly5enQYMGREdHs3XrVnR0dChbtizTp09n3759mi/AgwcP1pzv7OzM119/TZ8+fXL99vjq1au5c+cOx48fx9raGkCrEyEgIICvvvqKrl27AlC6dGkmT57MyJEjmTBhQq7KEEII8fZLTYM5q7JPM3cV1K1aMFPKe3p6MnbsWABGjx7NtGnTsLW1pWfPngCMHz+ehQsXcvLkSWrVqoWenh4BAQGa80uVKsXhw4f57bff+OSTT3j06BEPHz6kefPmlClTBgB3d3dNelNTU3R1dSlatGi2cX399dcMGzaMQYMGafZVr14dgIMHD3Ls2DFu376NgYEBkP4AfOPGjfz++++a0WZCCCGEeDekpqYyaFAgmS1briigUsHgwbNo2bJegUwp7+joyOzZs1GpVJQtW5ZTp04xe/ZsTXsIoGHDhgwbNkyz3alTJxo1asS4ceMAcHNz4+zZs8yYMYNu3bplW17t2rXR0dEhKSmJ5ORkevXqRZcuXbJM/91332FhYUFQUBB6enqa8l6YMGECgYGBtGnTBkhvn714af/FMwUhhBD/kJHtQgjxFjvx8UFC/f4Zca4oCqu2/Ml3v64mKTlZs9+9Zgv6zwvFrkTZ1yqnPqVpQJl/Ha8QryP2THCGEe3aFB7evUbsmeB8LzsmJgZ/f39Kly6Nubk5zs7OAFy9elUrXaVKlTR/d3BIf6nl9m3tt+Nf5uzsjJmZmWbb3t6e8uXLo6Ojo7Xv5Tx2795No0aNKF68OGZmZnTu3Jn4+HjNyL+cREREUKVKFU1H+6siIyOZNGkSpqammk/Pnj2Ji4vLdRlCCCHefpHRGUe0v+r2vfR0BeHlOlOtVmNjY4OHh4dmn729fXoML9WB3333HVWrVsXOzg5TU1MWL16sqYutra3p1q0bfn5+tGjRgrlz5xIXF5enmG7fvs3Nmzdp1KhRpscjIyNJSEjAxsZGq568fPmy1nSqQgghhHg3BAdHZBjR/jJFgWvX/iY4OKJAyq9VqxYqlUqz7e3tTUxMDKmpqZp91apV0zonKiqKOnXqaO2rU6eO5rzg4GCtdsqqVf+8Xfnrr78SERFBZGQkv/32G3/88QdfffVVlvFFRETg4+Oj6Wh/2ZMnT7h48SLdu3fXKu/rr7+WdpEQQmRBRrYLIcRbLPleEmnP/2mIL/x1Dc+TnlO5rDt6uvIrXLwfHt/L3QPz3KbLixYtWuDk5MSSJUsoVqwYaWlpVKxYkaSkJK10L38BffGF+dWp5rNK/+KczPa9yCM2NpbmzZvTt29fpkyZgrW1NQcPHqR79+4kJSVhbGyc47UYGRllezwhIYGAgADNm+kvMzQ0zDF/IYQQ74b4B/mbLq9yqgNfrUeDgoIYPnw4gYGBeHt7Y2ZmxowZM7SWWlm2bBkDBw5k+/bt/Prrr4wdO5Zdu3ZRq1atXMWUmzrSwcGB/fv3ZzhmaWmZqzKEEEII8faIi7ubr+kKgomJSZ7SV6tWjYiICM22vb098fHxQPpI+hcz27m7u3Px4kXGjRvHxIkTM/2+n13bKCEhAYAlS5ZkmIq+IGYBEEKI94H01AghxFus5sGGWttW5uao1Wo+qle/wMpMJQ21THwi3qDcLn/wusskZCU+Pp7o6GiWLFmCj48PkD6NbGEICwsjLS2NwMBAzej3F2vV5lalSpVYunQp9+7dy3R0u5eXF9HR0VpTywshhHj/2Fjmb7qCFhISQu3atenXr59mX2ajpqpUqUKVKlUYPXo03t7erF69mlq1aqGvr681SiwzZmZmODs7s2fPHho0aJDhuJeXF7du3UJXV1czy40QQggh3l0ODrb5mi6vXn5pEODIkSO4urpm21nt7u5OSEiI1r6QkBDc3NxQq9UYGRll+D7/orP9VWq1mpSUFJKSkjLtbK9UqRIrVqwgOTk5w4uS9vb2FCtWjEuXLtGpU6dsr1MIIUQ66U0RQoh3iH+z5nzi1/Rf53OfpwxlMxs5o7V/FeEMZjNbiOIIV7M4W4j85VzBB3PbEoAqixQqLGwdca7gk6/lWllZYWNjw+LFi7lw4QJ79+5l6NCh+VpGbrm4uJCcnMz8+fO5dOkSK1eu5IcffshTHv7+/hQtWpRWrVoREhLCpUuXWLduHYcPHwbS18j9+eefCQgI4MyZM0RFRREUFKRZV1cIIcT7wbMs2GW+oohGEev0dG8DV1dXQkND2bFjB+fPn2fcuHEcP35cc/zy5cuMHj2aw4cPc+XKFXbu3ElMTIxm3XZnZ2cuX75MREQEd+/e5fnz55mWM3HiRAIDA5k3bx4xMTGcOHGC+fPnA9C4cWO8vb1p1aoVO3fuJDY2lkOHDjFmzBhCQ0ML/iYIIYQQIl/5+FSmRIkiqLJ4zKBSgaOjPT4+lQuk/KtXrzJ06FCio6NZs2YN8+fPZ9CgQdmeM2zYMPbs2cPkyZM5f/48K1asYMGCBQwfPjzH8uLj47l16xbXr19n27ZtzJ07lwYNGmBubp5p+gEDBvDo0SM+/fRTQkNDiYmJYeXKlURHp68zFBAQwNSpU5k3bx7nz5/n1KlTLFu2jFmzZuX9ZgghxH+AdLYLIcR/kApQo4Pq/zs343jEOHbymOcYoWYDZ/mJ49lnIkQ+0VGrad577v9vvfpNOH37o95z0Mnn6cp0dHQICgoiLCyMihUrMmTIEGbMmJGvZeSWp6cns2bNYvr06VSsWJFVq1YxderUPOWhr6/Pzp07KVKkCM2aNcPDw4Np06Zp3pz38/Nj8+bN7Ny5k+rVq1OrVi1mz56Nk5NTQVySEEKIQqLWgcE5DEIa1Ck93dugd+/etGnThg4dOlCzZk3i4+O1RrkbGxtz7tw52rZti5ubG7169aJ///707t0bgLZt29KkSRMaNGiAnZ0da9asybScrl27MmfOHL7//nsqVKhA8+bNiYmJAdKntt+6dSv16tXj888/x83NjU8//ZQrV65o1pgXQgghxLtDrVYzd+4wgAwd7i+258wZWmDTonfp0oWnT59So0YN+vfvz6BBg+jVq1e253h5efHbb78RFBRExYoVGT9+PJMmTaJbt245lte4cWMcHBxwdnamV69eNGvWjF9//TXL9DY2Nuzdu5eEhATq169P1apVWbJkiWaUe48ePVi6dCnLli3Dw8OD+vXrs3z5ckqVKpWn+yCEEP8VKkVRlDdd6KNHj7CwsODhw4dZvl0lhBAibxRFQUl6yv2jq7Gs1g61sWWuz71IPN9ygDLYEMNdSmJBVUrQjHIFF7B45xR0/X0mZD2bFw3i0d3rmn0Wto581HsOFepkXGdcCCGEEFk7cBzmrII79/7ZV8Q6vaO9fvXCi0sIIYQQ4k1Zv34fgwYFcv36bdinG+EAAHd6SURBVM0+R0d75swZSps2GZeWyQ++vr5UrlyZOXPmFEj+Qggh3j6yZrsQQrwHnt2M4sLk6piWb8yj8D9IfXyHIh+NzvX5ZbDhK3y5zkN00aE71bEg45pOQhSkCnXa4F6rJbFngnl8Lw4zawecK/jk+4h2IYQQ4r+gfnWoWxUioyH+Qfoa7Z5l354R7UIIIYQQBa1Nmwa0bFmP4OAI4uLu4uBgi49P5QIb0S6EEOK/STrbhRDiPaDS1UdtaotxmToYOVfDqu7neTr/Ec/4hn1YY0R9SqMnq4yIQqKjVlO6km9hhyGEEEK8F9Q64OVe2FEIIYQQQhQetVqNr2/Vwg5DCCHEe0w624UQ4j1gUKQM7jNic5U2Lfk515Z0xqRsfWwb9QfAFAMM0eMeT1nPGUzQpz6lCzBiIYQQQgghhBBCCCHeL/v37y/sEIQQQrxh0tkuhBD/MamJD3gUsYm05KeaznYdVIyhAQ94yi0SqEXJQo5SCCGEEEIIIYQQQgghhBDi7Sad7UII8R+jZ2FPuekXURtbAfCY53zHYbwpSX1KU44ihRyhEEIIIYQQQgghhBBCCCHE208W5RVCiPfE0yvhpCU/y1VaPavi6BgYA5BIErHc5zoPCzI8IYQQQgghhBBCCCGEEEKI94p0tgshxHsgIWofMQFe3Fo3Js/n2mPGLD7Cn8r5H5gQQgghhBBCCCGEEEIIIcR7SqaRF0KId1RSavqf+mowLF4RixqfYu7Z/LXyMkY/HyMTQgghhBBCCCGEEEIIIYR4/0lnuxBCvKPiEkABnC1A19wOpz5rsk2feDkUPcti6FkVezMBCiGEEEIIIYQQQgghhBBCvMdkGnkhhHhHWRqClSF8/PEw3NzakpKSkmXa5AdxXPi6JleXdHqDEQrxbouNjUWlUhEREVHgZS1fvhxLS8t8y2///v2oVCoePHiQb3kKIYQQ7yqpF4UQQgghcs/X15fBgwcXdhi51q1bN1q1aqXZftfiF0K8+6SzXQgh3lEWBukfU1MjzM1NUKlUWabVNS+CXZMR2DTsn+nxOyQwn0NcJL6gwhVCZKNDhw6cP3++sMN4bzg7OzNnzpzCDkMIIYQocPn9wp4QQgghxPr165k8ebJmW75jCyFE9mQaeSGEeEedPn2Rrl0D+Oabvvj5eWebVqWjxqH9tCyPX+UhkcT9X3t3HV919cdx/LXuDhg5amM0o7sFAwmlpUNFRJRQVJAwEAFFxUIcqIQiqEjzoxk1ukaNGOCIERsLWH1/f1y5cN2ADTdC38/H4z7knnO+J77zcb/fez/fcw4l8aEEPrndVZFsS0/PYP36C8TEJBMQ4ES9en7Y2Pz7nw10cnLCycnpQXdDRET+ZdLT09m/O5JLF6/g7eNJ2Yoh2NjYPOhu/SukpKRgb2//oLshIiIid5GRns6JA/u5evkybl5eBJYpi/VDdj/0sN1XeHt750m9D9s4RURyy7//12sRkX+pM2fOs3PnIY4cOfWP66pCQUbTFE+c+IQNJHA9F3ookjPz558iMHABjRqtonPnTTRqtIrAwAXMn//P/x+/nYyMDMaPH0/JkiVxcHCgSJEivPfee1mWTU9Pp3fv3hQrVgwnJyeCg4OZPHmyRZk1a9ZQvXp1XFxc8PT0pE6dOpw8eRKA3bt306hRI9zc3HB3d6dKlSps27YNyHpW2h9//EG1atVwdHTE19eXNm3amPN++OEHqlatipubG/nz56dz586cP38+R2O3srLi66+/5qmnnsLZ2ZmQkBA2bdrE0aNHadiwIS4uLtSuXZuoqCiL47788ktKlCiBvb09wcHB/PDDD5nq/fbbb2nTpg3Ozs6UKlWKBQsWWJRZu3Yt1atXx8HBgYCAAN544w2LrTDu9Hdp3LgxAwYMsKjvwoUL2Nvbs3LlSho2bMjJkyd59dVXsbKyslj1Y8OGDdSrVw8nJycKFy7MwIEDSUxMzNF5ExF5VISv3UyvZ/szfOAoPhr9CcMHjqLXs/0JX7s5z9ps2LAhL7/8MoMGDcLLy4t8+fIxdepUEhMT6dmzJ25ubpQsWZIlS5aYj9m3bx+PP/44rq6u5MuXj65duxIbG2vOv3r1Kl26dMHFxYWAgAA+/vjjTEuD5vS6mJSUxOOPP06dOnW4cuUKFy9epFOnThQsWBBnZ2fKly/P7NmzM41twIABDBo0CF9fX5o3b06vXr146qmnLMqlpqbi7+/PtGnTALh+/ToDBw7E398fR0dH6tatS0REhMUx+/fv56mnnsLd3R03Nzfq1atHVFQU69atw87OjrNnz1qUHzRoEPXq1WPNmjX07NmTuLg48zVv1KhR5naHDBlCwYIFcXFxoUaNGqxZs+auf0MREZF/k/2bNjKhX2++G/Emcyd9xHcj3mRCv97s37Qxz9q8cc8wYMAAPDw88PX1ZcSIERiGYS4TGBjI2LFj6datG+7u7vTr1w+AefPmUbZsWRwcHAgMDGTixIkWdcfExPDkk0/i5OREsWLFmDVrVqZZ51euXKFPnz74+fnh7u5O48aN2b17tzl/1KhRVKpUiR9++IHAwEA8PDzo2LEjV69etRjDjXutO33Hvlt/bzfOv7vbbzOnTp2iffv2eHp64u3tTatWrThx4kT2/iAiIveBgu0iIo+o5s1rceHCMgYMaJ8r9RXEg6PEsp9zxCnYLvfZ/PmnePbZDZw+nWyRfuZMMs8+uyHPAu7Dhw9n3LhxjBgxggMHDjBr1izy5cuXZdmMjAwKFSrE3LlzOXDgACNHjuTNN9/k559/BiAtLY3WrVvToEED9uzZw6ZNm+jXr5/5i2iXLl0oVKgQERERbN++nTfeeAM7O7ss21q0aBFt2rThiSeeYOfOnaxcuZLq1aub81NTUxk7diy7d+/mt99+48SJE/To0SPH47/xpXfXrl2ULl2azp078/zzzzN8+HC2bduGYRgWge1ff/2VV155hcGDB7Nv3z6ef/55evbsyerVqy3qHT16NO3bt2fPnj088cQTdOnShUuXLgFw5swZnnjiCapVq8bu3bv58ssvmTZtGu+++262/i59+vRh1qxZXL9+83Pqxx9/pGDBgjRu3Jj58+dTqFAhxowZQ0xMDDExMQBERUXRokULnnnmGfbs2cNPP/3Ehg0bMgXuRUT+DcLXbub9tyYQe8Fyi6DYCxd5/60JeRpwnzFjBr6+vmzdupWXX36ZF198kXbt2lG7dm127NjBY489RteuXUlKSuLKlSs0btyYypUrs23bNpYuXcq5c+do3/7m/e1rr71GeHg4CxYsYMWKFaxfv54dO3ZYtJmT6+KVK1do1qwZGRkZrFixAk9PT65du0aVKlVYtGgR+/bto1+/fnTt2pWtW7dmGpu9vT3h4eF89dVX9OnTh6VLl5qvNQALFy4kKSmJDh06ADBs2DDmzZvHjBkz2LFjByVLlqR58+YW18X69evj4ODAqlWr2L59O7169SItLY369etTvHhxiwfbUlNTmTlzJr169aJ27dp88sknuLu7m695Q4YMAWDAgAFs2rSJOXPmsGfPHtq1a0eLFi04cuTIvf9xRUREHiH7N21k9ofvE38x1iI9/mIssz98P08D7jNmzMDW1patW7cyefJkJk2axLfffmtRZsKECVSsWJGdO3cyYsQItm/fTvv27enYsSN79+5l1KhRjBgxgunTp5uP6datG3/++Sdr1qxh3rx5fPPNN5keMGzXrh3nz59nyZIlbN++ndDQUJo0aWK+9wDT9+PffvuNhQsXsnDhQtauXcu4cVmviHm779jZ6W9W48zKnX4DSE1NpXnz5ri5ubF+/XrCw8NxdXWlRYsWpKSkZOvvISKS54wHIC4uzgCMuLi4B9G8iIjcRqqRblwykh50N+QhlVfX77S0dKNQoV8NmJXly8pqllG48G9GWlp6rrYbHx9vODg4GFOnTs0y//jx4wZg7Ny587Z1vPTSS8YzzzxjGIZhXLx40QCMNWvWZFnWzc3NmD59epZ5YWFhhoeHh/l9rVq1jC5dumRvIIZhREREGIBx9epVwzAMY/Xq1QZgXL58+bbHAMbbb79tfr9p0yYDMKZNm2ZOmz17tuHo6Gh+X7t2baNv374W9bRr18544oknbltvQkKCARhLliwxDMMw3nzzTSM4ONjIyMgwl5kyZYrh6upqpKen3/XvkpycbHh5eRk//fSTOa1ChQrGqFGjzO+LFi1qfPzxxxbH9e7d2+jXr59F2vr16w1ra2sjOTk5y7ZERB5FaWlpRrfW/Ywn6jxz21e3Nv2MtLS0XG+7QYMGRt26dS364uLiYnTt2tWcFhMTYwDGpk2bjLFjxxqPPfaYRR2nTp0yAOPQoUNGfHy8YWdnZ8ydO9ecf+XKFcPZ2dl45ZVXbtuP210XIyMjjQoVKhjPPPOMcf369TuO5cknnzQGDx5sMbbKlStnKlemTBnjww8/NL9v2bKl0aNHD8MwTNdAOzs7Y+bMmeb8lJQUo0CBAsb48eMNwzCM4cOHG8WKFTNSUlKy7MeHH35ohISEmN/PmzfPcHV1NRISEgzDyHwPYRiGcfLkScPGxsY4c+aMRXqTJk2M4cOH33HcIiIi/wbpaWnGh726G2+1evK2r/G9uxvpeXQ/FBISYvGd9/XXX7e4nhctWtRo3bq1xXGdO3c2mjVrZpE2dOhQo0yZMoZhGEZkZKQBGBEREeb8I0eOGID5++/69esNd3d349q1axb1lChRwvj6668NwzCMd955x3B2djbi4+Mt2qlRo4bFGG6918rqO/bd+nu7cf7d3X4D+OGHHzL9hnD9+nXDycnJWLZsmWEYhtG9e3ejVatWt+2/iEhe08x2ERExs8UaL7RvtNxf69dfyDSj/VaGAadOJbF+/YVcbTcyMpLr16/TpEmTbB8zZcoUqlSpgp+fH66urnzzzTdER0cDpj3NevToQfPmzWnZsiWTJ0+2mOn22muv0adPH5o2bcq4ceMyLc9+q127dt2xX9u3b6dly5YUKVIENzc3GjRoAGDuS3ZVqFDB/O8bT42XL1/eIu3atWvEx8cDpnNWp04dizrq1KlDZGTkbet1cXHB3d3d/LR9ZGQktWrVslh6rk6dOiQkJHD69Om7/l0cHR3p2rUr3333HQA7duxg3759d53Zv3v3bqZPn46rq6v51bx5czIyMjh+/PgdjxUReZTs3x2ZaUb738Wev8j+3ZF3LHOvbr0G2NjY4OPjk+naAnD+/Hl2797N6tWrLT6bS5cuDZhmXB07dozU1FSL1V08PDwIDg62aDO718VmzZpRsmRJfvrpJ4v9QtPT0xk7dizly5fH29sbV1dXli1blun4KlWqZBpvnz59CAsLA+DcuXMsWbKEXr16mceQmppqce20s7OjevXq5mvnrl27qFev3m1Xu+nRowdHjx5l82bTagTTp0+nffv2uLi4ZFkeYO/evaSnpxMUFGRxbteuXXvH+w8REZF/ixMH9mea0f53cbGxnDiwP0/ar1mzpsV33lq1anHkyBHS09PNaVWrVrU45nbft28cd+jQIWxtbQkNDTXnlyxZEi8vL/P73bt3k5CQgI+Pj8U9wPHjxy3uAQIDA3FzczO/DwgIyPHWdHfr7+3GmVU9d/oNYPfu3Rw9ehQ3NzfzeLy9vbl27Zrua0TkoWH7oDsgIiIPqV93wIyN8HkXKOR19/Ii9ygm5vaB9nspl11OTjl7sGTOnDkMGTKEiRMnUqtWLdzc3Pjoo4/YsmWLuUxYWBgDBw5k6dKl/PTTT7z99tusWLGCmjVrMmrUKDp37syiRYtYsmQJ77zzDnPmzLHYiz07fUtMTKR58+Y0b96cmTNn4ufnR3R0NM2bN8/xEmq3/rB/44eArNIyMjLuud4b9WS3juz8Xfr06UOlSpU4ffo0YWFhNG7cmKJFi97xmISEBJ5//nkGDhyYKa9IkSLZ6puIyKPg0sUruVoup7K6Btzu2pKQkEDLli358MMPM9UTEBDA0aNH79peTq6LTz75JPPmzePAgQMWDwB89NFHTJ48mU8++YTy5cvj4uLCoEGDMh2fVYC7W7duvPHGG2zatImNGzdSrFgx6tWrd9d+33C3656/vz8tW7YkLCyMYsWKsWTJkrvuvZ6QkICNjQ3bt2/HxsbGIs/V1TXbfRMREXlUXb18OVfL5YU7PTh3rxISEggICMjyXsHT09P873/ynT2n7jbOu90LJSQkUKVKFWbOnJkpz8/P7x/1TUQktyjYLiIiWYtNgD+vQJL2P5K8FRCQvaB3dstlV6lSpXBycmLlypX06dPnruXDw8OpXbs2/fv3N6dl9RR15cqVqVy5MsOHD6dWrVrMmjWLmjVrAhAUFERQUBCvvvoqnTp1IiwsLMtge4UKFVi5ciU9e/bMlHfw4EEuXrzIuHHjKFy4MADbtm3L9rj/iZCQEMLDw+nevbs5LTw8nDJlyuSojnnz5mEYhjngEh4ejpubG4UKFcLf3/+uf5fy5ctTtWpVpk6dyqxZs/j8888t8u3t7S2epAcIDQ3lwIEDlCxZMtt9FRF5FHn7eOZqubwUGhrKvHnzCAwMxNY2888TxYsXx87OjoiICPODUXFxcRw+fJj69esDObsujhs3DldXV5o0acKaNWvM16/w8HBatWrFc889B5geBDh8+HC2rm8+Pj60bt2asLAwNm3aZHHtLlGihHmP9xsPhaWmphIREcGgQYMA0zV/xowZpKam3nZ2e58+fejUqROFChWiRIkSFrPIsrrmVa5cmfT0dM6fP5+jwL+IiMi/hZtX9iaNZLdcTt36UD7A5s2bKVWqVKaH4G514/v2rcLDwwkKCsLGxobg4GDS0tLYuXOnebWdo0ePcvmWBwZCQ0M5e/Ystra2BAYG5tp4srrfuFt/s+tuv82Ehoby008/4e/vj7u7+70NQEQkj2kZeRERyVrf+hA+HILyPeieyL9cvXp+FCrkxC0rrFmwsoLChZ2pVy93n1h2dHTk9ddfZ9iwYXz//fdERUWxefNmpk2blmX5UqVKsW3bNpYtW8bhw4cZMWIEERER5vzjx48zfPhwNm3axMmTJ1m+fDlHjhwhJCSE5ORkBgwYwJo1azh58iTh4eFEREQQEhKSZVvvvPMOs2fP5p133iEyMpK9e/eaZ/0VKVIEe3t7PvvsM44dO8aCBQsYO3Zsrp6b2xk6dCjTp0/nyy+/5MiRI0yaNIn58+czZMiQbNfRv39/Tp06xcsvv8zBgwf5/fffeeedd3jttdewtrbO9t+lT58+jBs3DsMwMj2wEBgYyLp16zhz5gyxsaalA19//XU2btzIgAED2LVrF0eOHOH3339nwIAB//zEiIg8RMpWDMHXz+eOZXz9fShbMetr0P300ksvcenSJTp16kRERARRUVEsW7aMnj17kp6ejpubG927d2fo0KGsXr2a/fv307t3b6ytrc0PbOX0ujhhwgS6dOlC48aNOXjwIGC6xq9YsYKNGzcSGRnJ888/z7lz57I9jj59+jBjxgwiIyMtHkhzcXHhxRdfZOjQoSxdupQDBw7Qt29fkpKS6N27NwADBgwgPj6ejh07sm3bNo4cOcIPP/zAoUOHzPU0b94cd3d33n333UwP4gUGBpKQkMDKlSuJjY0lKSmJoKAgunTpQrdu3Zg/fz7Hjx9n69atfPDBByxatCjb4xIREXlUBZYpi7uP7x3LePj6ElimbJ60Hx0dzWuvvcahQ4eYPXs2n332Ga+88sodjxk8eDArV65k7NixHD58mBkzZvD555+bv2+XLl2apk2b0q9fP7Zu3crOnTvp168fTk5O5vuipk2bUqtWLVq3bs3y5cs5ceIEGzdu5K233vpHD+ln9R37bv3Nrrv9BtClSxd8fX1p1aoV69ev5/jx46xZs4aBAwdy+vTpex6TiEhuUrBdRERuzy77T6KK3CsbG2smTzY9lf33gPuN9598EoqNTe7ftowYMYLBgwczcuRIQkJC6NChw233KXv++edp27YtHTp0oEaNGly8eNFilruzszMHDx7kmWeeISgoiH79+vHSSy/x/PPPY2Njw8WLF+nWrRtBQUG0b9+exx9/nNGjR2fZVsOGDZk7dy4LFiygUqVKNG7cmK1btwKmZdKmT5/O3LlzKVOmDOPGjWPChAm5fm6y0rp1ayZPnsyECRMoW7YsX3/9NWFhYTRs2DDbdRQsWJDFixezdetWKlasyAsvvEDv3r15++23zWWy83fp1KkTtra2dOrUCUdHR4u8MWPGcOLECUqUKGFeVq5ChQqsXbuWw4cPU69ePSpXrszIkSMpUKDAvZ8QEZGHkI2NDf0GZV4Z5Vb9XumZoxlHeaVAgQKEh4eTnp7OY489Rvny5Rk0aBCenp5YW5uu+5MmTaJWrVo89dRTNG3alDp16hASEmL+7L+X6+LHH39M+/btady4MYcPH+btt98mNDSU5s2b07BhQ/Lnz0/r1q2zPY6mTZsSEBBA8+bNM11Xxo0bxzPPPEPXrl0JDQ3l6NGjLFu2zLy/qo+PD6tWrSIhIYEGDRpQpUoVpk6dajHL3dramh49epCenk63bt0s6q9duzYvvPACHTp0wM/Pj/HjxwOmrW26devG4MGDCQ4OpnXr1hYrBIiIiPybWdvY8GSffncs80Tvfljn0f1Qt27dSE5Opnr16rz00ku88sor9Ot35/6Ehoby888/M2fOHMqVK8fIkSMZM2YMPXr0MJf5/vvvyZcvH/Xr16dNmzb07dsXNzc3832RlZUVixcvpn79+vTs2ZOgoCA6duzIyZMnyZfv3ifTZPUdOzv9za47/Qbg7OzMunXrKFKkCG3btiUkJITevXtz7do1zXQXkYeGlWEYxv1uND4+Hg8PD+Li4vSBKCIi8ojI6+v3/PmneOWV7Zw+fXNv9sKFnfnkk1Dati2c6+3Jo+3GF/2IiAhCQ0MfdHdERB464Ws3880nYcReuGhO8/X3od8rPanToOYD7Nk/k5iYSMGCBZk4caJ5dviDlpCQQMGCBQkLC6Nt27Z50kbv3r25cOECCxYsyJP6RURE/o32b9rIom+/If5irDnNw9eXJ3r3o2yt2nnSZsOGDalUqRKffPJJntR/q9OnT1O4cGH+97//0aRJkzxvT0REsqY920VEROSh0LZtYVq1Ksj69ReIiUkmIMCJevX88mRGuzy6UlNTuXjxIm+//TY1a9ZUoF1E5DbqNKhJzbrV2L87kksXr+Dt40nZiiEPxYz2nNi5cycHDx6kevXqxMXFMWbMGABatWr1gHtm2ts9NjaWiRMn4unpydNPP53rbcTFxbF3715mzZqlQLuIiEgOla1Vm5DqNThxYD9XL1/GzcuLwDJl82xGe167sRpO+fLliYmJYdiwYQQGBlK/fv0H3TURkf80BdtFRETkoWFjY03Dhve+tJn8+4WHh9OoUSOCgoL45ZdfHnR3REQeajY2NlQILfegu/GPTZgwgUOHDmFvb0+VKlVYv349vr533of1foiOjqZYsWIUKlSI6dOnY2ub+z+xtGrViq1bt/LCCy/QrFmzXK9fRETk387axobi5Ss86G7kitTUVN58802OHTuGm5sbtWvXZubMmRbbz4iIyP2nZeRFREQkW3T9FhERERERERERERG5SeuyioiIiIiIiIiIiIiIiIiI5JCC7SIikqXr6cmMO/Qsy859/aC7IiIiIiIiIiIiIiIi8tBRsF1ERLKUkHaJbZcXsvPKigfdFRERERERERERERERkYeO7YPugIiIPCROxIKPK7g5AuDjUJCvK0fhauv9gDsmIiIiIiIiIiIiIiLy8NHMdhGRR1zUqWiuXb/+zyo5GwfPfAFv/2qR7ONQEAcbJ8uyMXHwwya4nvbP2hQREREREREREREREXmEKdguIvIIizoVzY8LF7A6Yss/q8jbBZ6qCI+VhfNX4aWZsO4wbDwKTSaY/jvmD1i4G2ZuhonLYcOR3BmEiIiIiIiIiIiIiIjII0jBdhGRR1hB/3xUK1eeCqWC/1lF9rYwuhU8WQEOxUD4UWI//Jq4nxbDxUT4KQJ+3wlL9sFzNaFrTahdIncGISJ5JjAwkE8++eS+tnnixAmsrKzYtWtXjo67X31t2LAhgwYNumOZ7I4hO3Xlpb+3/yD+3iIi8uCsWbMGKysrrly5AsD06dPx9PR8oH0SERGRB+dev4//1+geSkRym4LtIiKPMEcHB56o14CC+fJl/6Cj502vrGyKgoGzud4yiMj1YZw6Gw4NguC5WvBLf/igLYQfhR82w287c2cQIvKP3e6LYUREBP369bv/HXrEFS5cmJiYGMqVKwdk/iJ+w/z58xk7duwD6KGIiDxMblwnbrycnJwoW7Ys33zzzYPumoiIiMgd9ejRg9atWz+QtkeNGmVxD5XVS0TkUWD7oDsgIiL3wY6TsHgvDGoGvaeDtRWsHpq5nLUVGOBwJJ66JQdhFA6CCR0ty1QrBo+XhxrFLdOTUyAtA9wc82wY8u+XgcFhYonjGh44EoQv1ujL1b3y8/N70F145KSkpGBvb0/+/PnvWtbb2/s+9EhE5B9Iz4Ad0RB7FXzdILQI2OiZ+9u5cQ24V4cOHcLd3Z3k5GT++OMPXnzxRUqUKEGTJk1ysZciIiKSExlGBufjzpKckoSTvTP+Hvmxtrp/90P/9P7iUXEv4xwyZAgvvPCC+X21atXo168fffv2ze3uiYjkKX3LFhH5L1i8F37Zzo9da3GhS3F4seHNvB9vmaVeqYgpkP5MFawah2DdqIxlPdtOwLT10KwMFP9bEK/3dHj6M9OPuiL3YDtneJ0lTGAdU9nKBNbxOkvYzpk8azMjI4Px48dTsmRJHBwcKFKkCO+99545f+/evTRu3BgnJyd8fHzo168fCQkJ5vwbT4BPmDCBgIAAfHx8eOmll0hNTQXgzTffpEaNGpnarVixImPGjDG///bbbwkJCcHR0ZHSpUvzxRdfmPNuLAM3f/58GjVqhLOzMxUrVmTTpk2AaTZdz549iYuLMz/5PWrUKCDzsuLR0dG0atUKV1dX3N3dad++PefOnTPnjxo1ikqVKvHDDz8QGBiIh4cHHTt25OrVq+YyS5cupW7dunh6euLj48NTTz1FVFRUjs77+fPnadmyJU5OThQrVoyZM2dmKnPlyhX69OmDn58f7u7uNG7cmN27d+eor4mJiXTr1g1XV1cCAgKYOHFipnYCAwMZO3Ys3bp1w93dnX79+lksvXfixAkaNWoEgJeXF1ZWVvTo0QPIvIz79evXef311ylcuDAODg6ULFmSadOm3fY83K38vn37ePzxx3F1dSVfvnx07dqV2NjYbJ9nEfmPWxkJT0yGvjNg+HzTf5+YbErPIw0bNuTll19m0KBBeHl5kS9fPqZOnUpiYiI9e/bEzc2NkiVLsmTJEovj7vZ5d6/1rl27lurVq+Pg4EBAQABvvPEGaWlpFvUOGDCAQYMG4evrS/PmzenVqxdPPfWURT2pqan4+/vf8TMdwN/fn/z581OsWDEGDhxIsWLF2LFjxx2PCQ8Pp2HDhjg7O+Pl5UXz5s25fPkyYLpP+eCDDyhWrBhOTk5UrFiRX3755Y71iYiIyE0nY48zf+tslu9dyPpDq1i+dyHzt87mZOzxPGszq/sLuPv9ztWrV+nSpQsuLi4EBATw8ccfZ/rOaWVlxW+//WbRnqenJ9OnT8+yL+np6fTu3dt8LxEcHMzkyZPN+aNGjWLGjBn8/vvv5t8T1qxZA2T/95D33nuPAgUKEBwczJgxY8wrxN2qUqVKjBgxIlO6q6sr+fPnN79sbGxwc3OzSLsd3UOJyMNEwXYRkf+C5xsQE2pHbMZ5MpqHQPtqpnTDwPh0JakfLeDAwBc5NHKYaan4dlVhQjvTHu43bD4GfWbA77tg8Z7MbRTwhPhkWHf4foxI/mW2c4Yv2cxlki3SL5PMl2zOs4D78OHDGTduHCNGjODAgQPMmjWLfH9ty5CYmEjz5s3x8vIiIiKCuXPn8r///Y8BAwZY1LF69WqioqJYvXo1M2bMYPr06eYvul26dGHr1q0Wwej9+/ezZ88eOnfuDMDMmTMZOXIk7733HpGRkbz//vuMGDGCGTNmWLTz1ltvMWTIEHbt2kVQUBCdOnUiLS2N2rVr88knn+Du7k5MTAwxMTEMGTIk01gzMjJo1aoVly5dYu3ataxYsYJjx47RoUMHi3JRUVH89ttvLFy4kIULF7J27VrGjRtnzk9MTOS1115j27ZtrFy5Emtra9q0aUNGRvYftOnRowenTp1i9erV/PLLL3zxxRecP2+5vUW7du04f/48S5YsYfv27YSGhtKkSRMuXbqU7b4OHTqUtWvX8vvvv7N8+XLWrFmTZdBjwoQJVKxYkZ07d2b6AaBw4cLMmzcPMM1YjImJsfhx4lbdunVj9uzZfPrpp0RGRvL111/j6up62/Nwp/JXrlyhcePGVK5cmW3btrF06VLOnTtH+/bt73J2RUQwBdSH/Azn4i3Tz8eb0vMw4D5jxgx8fX3ZunUrL7/8Mi+++CLt2rWjdu3a7Nixg8cee4yuXbuSlJQEZP/zLqf1njlzhieeeIJq1aqxe/duvvzyS6ZNm8a7776bqV57e3vCw8P56quv6NOnD0uXLiUmJsZcZuHChSQlJWW6Zt6OYRgsXbqU6OjoLB+6u2HXrl00adKEMmXKsGnTJjZs2EDLli1JT08H4IMPPuD777/nq6++Yv/+/bz66qs899xzrF27Nlv9EBER+S87GXuctZErSEpJtEhPSklkbeSKPA24//3+Ijv3O6+99hrh4eEsWLCAFStWsH79+rs+tHc3GRkZFCpUiLlz53LgwAFGjhzJm2++yc8//wyYZpa3b9+eFi1amH9PqF27drZ/D1m5ciWHDh1ixYoVLFy4kF69ehEZGUlERIS5zM6dO9mzZw89e/b8R2O5le6hROShYzwAcXFxBmDExcU9iOZFRP57Fu8xjIqjjOsj52TKuhQ2zwj38DVW+rsZq4v43b6OS4mG8favhvHrDsOIS8qcvznKMOp/aBhrD+Vev+WhklfX73QjwxhiLDJ6G7/c9jXEWGSkGxm52m58fLzh4OBgTJ06Ncv8b775xvDy8jISEhLMaYsWLTKsra2Ns2fPGoZhGN27dzeKFi1qpKWlmcu0a9fO6NChg/l9xYoVjTFjxpjfDx8+3KhRo4b5fYkSJYxZs2ZZtD127FijVq1ahmEYxvHjxw3A+Pbbb835+/fvNwAjMjLSMAzDCAsLMzw8PDKNoWjRosbHH39sGIZhLF++3LCxsTGio6Mz1bN161bDMAzjnXfeMZydnY34+HhzmaFDh1r09+8uXLhgAMbevXst+rtz584syx86dMiiTcMwjMjISAMw93X9+vWGu7u7ce3aNYtjS5QoYXz99dfZ6uvVq1cNe3t74+effzbnX7x40XBycjJeeeUVi3PUunVri3b+PobVq1cbgHH58mWLcg0aNDDXdWNcK1asuO25yuo83K782LFjjccee8wi7dSpUwZgHDp0KFP7N8Zy4xyKyH9YWrphPDbJMCqOyvpVaZQpPy0915tu0KCBUbdu3ZtdSUszXFxcjK5du5rTYmJiDMDYtGmTYRjZ/7zLab1vvvmmERwcbGRk3Lx/mDJliuHq6mqkp6eb661cuXKmcZQpU8b48MMPze9btmxp9OjR47bjvnGdcHFxMVxcXAxbW1vD2traePfdd+9wtgyjU6dORp06dbLMu3btmuHs7Gxs3LjRIr13795Gp06dLNq9cX263f2AiIjIf016Rroxd/OPxox1X9/2NXfLj0Z6Rt7cD/39/uJu9zvx8fGGnZ2dMXfuXHP+lStXDGdnZ4vvfIDx66+/WtTj4eFhhIWFGYZx9+/jhmEYL730kvHMM8+Y33fv3t1o1aqVRZns/h6SL18+4/r16xbHPv7448aLL75ofv/yyy8bDRs2vG1/bpXd77S6hxKRh432bBcR+Q9IqeDH0XN/kPy/FVQZbTkjx7NrK4o5JOFavhL2fn7EntqPq1cBHF29LCvxcoaxrU3/Ts+AXmFQ1AfeedqUVqM4rB2W94ORf53DxGaa0f53l0nmMLGUJvf2II+MjOT69eu33Uc1MjKSihUr4uLiYk6rU6cOGRkZHDp0yDwDvmzZstjY2JjLBAQEsHfvXvP7Ll268N133zFixAgMw2D27Nm89tprgGmWeFRUFL1797bYkywtLQ0PDw+L/lSocHOliYCAAMC0HHvp0qWzPd7ChQtTuHBhc1qZMmXw9PQkMjKSatVMK14EBgbi5uZm0dats86PHDnCyJEj2bJlC7GxseYZ7dHR0VkuF5dVP2xtbalSpYo5rXTp0nh6eprf7969m4SEBHx8fCyOTU5Otlgl4E59jYqKIiUlxWJGobe3N8HBwZn6VLVq1bv2+2527dqFjY0NDRo0yJXyu3fvZvXq1VnOjI+KiiIoKOgf9VdE/sV2RGee0X4rA1P+jmioFpjrzd96vbKxscHHx4fy5cub025cP298Xmf38y6n9UZGRlKrVi2srKzMZerUqUNCQgKnT5+mSJEiABbXoxv69OnDN998w7Bhwzh37hxLlixh1apVdx37+vXrcXNz4/r162zdupUBAwbg7e3Niy++mGX5Xbt20a5duyzzjh49SlJSEs2aNbNIT0lJoXLlynfti4iIyH/Z+bizmWa0/13S9UTOx50lv2eBXG//7/cXd7vfSU5OJjU1lerVq5vTPTw8svz+mlNTpkzhu+++Izo6muTkZFJSUqhUqdIdj8nu7yHly5fPtE9737596dWrF5MmTcLa2ppZs2bx8ccf/+Nx3Er3UCLysFGwXUTkP8C+YH5chnfGPzjkZuIfu+H3XViNf5aATs8BkHDpT7b/MgmPVacp+FgrCj/fP+sKMwyIiQN7W/hhE1QoBBULZ11W5C7iuJar5bLLyckpV+qxs7OzeG9lZWWxpHqnTp14/fXX2bFjB8nJyZw6dcq8DO2N/c6mTp2aaZnZWwP4f2/nRuAgJ0u3Z9fdxtOyZUuKFi3K1KlTKVCgABkZGZQrV46UlJRc60NCQgIBAQHmveJudWtQ/m59za5bf0C4Vzn9/+lu5RMSEmjZsiUffvhhprwbD1uIiGQp9mrulsuhrD6b73QNy+7nXU7rza6srgHdunXjjTfeYNOmTWzcuJFixYpRr169u9ZVrFgx83WqbNmybNmyhffee++2wfY7XQtu3CMsWrSIggULWuQ5ODjctS8iIiL/ZckpSblaLqf+fn9xt/udo0ePZqteKysrDMOwSEtNTb1t+Tlz5jBkyBAmTpxIrVq1cHNz46OPPmLLli3Zau9usrqPatmyJQ4ODvz666/Y29uTmprKs88+myvt3aB7KBF52CjYLiLyH1F04GuWCfvPwK5ouJxkmrW+ZB/OFQpQ5Uwou5d+T/TeI7cPttvZwMKBEH0R2nwBtUvAF8/l/SDkX8kDx1wtl12lSpXCycmJlStX0qdPn0z5ISEhTJ8+ncTERPMXyPDwcKytrXP0dHmhQoVo0KABM2fOJDk5mWbNmuHv7w+YZuEVKFCAY8eO0aVLl3sei729vXlvstsJCQnh1KlTnDp1yjy7/cCBA1y5coUyZcpkq52LFy9y6NAhpk6dag46bNiwIUd9LV26NGlpaWzfvt08m/7QoUNcuXLFXCY0NJSzZ89ia2tLYGBgjuq/oUSJEtjZ2bFlyxbz7MXLly9z+PDhbM8+v+HGk/p3Osfly5cnIyODtWvX0rRp07vWebfyoaGhzJs3j8DAQGxtdcsuIjng63b3Mjkpl8fy6vMuJCSEefPmYRiGORAfHh6Om5sbhQoVuuOxPj4+tG7dmrCwMDZt2nTPe4za2NiQnHz71XsqVKjAypUrGT16dKa8MmXK4ODgQHR0dI6vWyIiIv91TvbOuVrun7rb/U7x4sWxs7MjIiLC/P01Li6Ow4cPU79+fXM5Pz8/YmJizO+PHDlCUtLtHxgIDw+ndu3a9O9/8/e9W1eLg6x/T/gnv4fY2trSvXt3wsLCsLe3p2PHjrk22eEG3UOJyMPG+kF3QERE8tbh4UM4OHhg5oyhLWD5a1DCD/aegTfnY/35GnzbtaRmhw8JfWYkLNx9+4ptrKGYH0xoB68/nncDkH+9IHzx4s5fvLxwIgjfXG3X0dGR119/nWHDhvH9998TFRXF5s2bmTZtGmBa/t3R0ZHu3buzb98+Vq9ezcsvv0zXrl3NS6ZlV5cuXZgzZw5z587NFFQfPXo0H3zwAZ9++imHDx9m7969hIWFMWnSpGzXHxgYSEJCAitXriQ2NjbLL9tNmzalfPnydOnShR07drB161a6detGgwYNsr2MupeXFz4+PnzzzTccPXqUVatWmZfEz67g4GBatGjB888/z5YtW9i+fTt9+vSx+PLdtGlTatWqRevWrVm+fDknTpxg48aNvPXWW2zbti1b7bi6utK7d2+GDh3KqlWr2LdvHz169MDaOue3v0WLFsXKyoqFCxdy4cIF85PytwoMDKR79+706tWL3377jePHj7NmzRp+/vnnLOu8W/mXXnqJS5cu0alTJyIiIoiKimLZsmX07Nnzrg9WiMh/XGgRyOcOVrfJt8KUH1rkfvbqtvLq865///6cOnWKl19+mYMHD/L777/zzjvv8Nprr2XrWtCnTx9mzJhBZGQk3bt3z1ab58+f5+zZs5w8eZK5c+fyww8/0KpVq9uWHz58OBEREfTv3589e/Zw8OBBvvzyS2JjY3Fzc2PIkCG8+uqrzJgxg6ioKHbs2MFnn33GjBkzsn0eRERE/ov8PfLjbH/nFcycHVzw98h/X/pzt/sdNzc3unfvztChQ1m9ejX79++nd+/eWFtbW2yJ07hxYz7//HN27tzJtm3beOGFFzKt/nOrUqVKsW3bNpYtW8bhw4cZMWIEERERFmUCAwPZs2cPhw4dIjY2ltTU1H/8e0ifPn1YtWoVS5cupVevXvd+4m5D91Ai8rBRsF1E5F/u/IJfOf/bvMwZNtbg/dcXjzIFYFBT6FkHKhfBZXJ/nFacgllb795A0zKmvdtF7pE1VnSk4h3LdKQi1reNGty7ESNGMHjwYEaOHElISAgdOnQw7/Xq7OzMsmXLuHTpEtWqVePZZ5+lSZMmfP755zlu59lnn+XixYskJSXRunVri7w+ffrw7bffEhYWRvny5WnQoAHTp0+nWLFi2a6/du3avPDCC3To0AE/Pz/Gjx+fqYyVlRW///47Xl5e1K9fn6ZNm1K8eHF++umnbLdjbW3NnDlz2L59O+XKlePVV1/lo48+yvbxN4SFhVGgQAEaNGhA27Zt6devn3m2/42+Ll68mPr169OzZ0+CgoLo2LEjJ0+ezNGDDh999BH16tWjZcuWNG3alLp162a5N+/dFCxYkNGjR/PGG2+QL18+BgwYkGW5L7/8kmeffZb+/ftTunRp+vbtS2Li7fcJvFP5AgUKEB4eTnp6Oo899hjly5dn0KBBeHp63tMDAyLyH2JjDcNamP7990vnjffDWpjKPQTy6vOuYMGCLF68mK1bt1KxYkVeeOEFevfuzdtvv52t45s2bUpAQADNmzenQIHs7eUaHBxMQEAAJUuW5PXXX+f555/ns88+u235oKAgli9fzu7du6levTq1atXi999/N894Gzt2LCNGjOCDDz4gJCSEFi1asGjRohzdI4iIiPwXWVtZU61E7TuWqVa8NtZW9+d+KDv3O5MmTaJWrVo89dRTNG3alDp16hASEoKj481V/iZOnEjhwoWpV68enTt3ZsiQITg73352/vPPP0/btm3p0KEDNWrU4OLFixaz3MG0x3pwcDBVq1bFz8+P8PDwf/x7SKlSpahduzalS5fOtGVebtA9lIg8bKyMv2/ycR/Ex8fj4eFBXFwc7u7u97t5EZH/jrQMUt+fj1G2APbP/O1LxooDUDo/FPY2vd8ZDe8uhLefgqnrIP6aadZ6fg9T/vojYGMFS/aZAvM+rqb0lDTYchxqFjctLy//Wnl9/d7OGeawm8vcXG7VCyc6UpEqFLzDkSIiIpLJykgYvxTOxd9My+duCrQ3CXlw/XpEJCQkULBgQcLCwmjbtu2D7o6IiIjcg5Oxx4mI2khSys2HoJ0dXKhWvDZFfR/uwGtiYiIFCxZk4sSJ9O7d+0F3J0cMw6BUqVL0798/x6vhiYg8irQBpIjIv0zK+fOkXLqIa+kQuJiA3a/7IToRbg22HzkHQ+dCjWKQlgHda0NyCkRdgPNXIeE6GMbNQPu2E/DyLCjuB8cuwKGz8G13cHeCnyJg4nJ4+0l4NntLUYtkpQoFqUwBDhNLHNfwwJEgfPNkRruIiMi/XpMQaBgMO6Ih9qppj/bQIg/NjPaHVUZGBrGxsUycOBFPT0+efvrpB90lERERuUdFfYtR2Kco5+POkpyShJO9M/4e+e/bjPac2LlzJwcPHqR69erExcUxZswYgDtuSfMwunDhAnPmzOHs2bP07NnzQXdHROS+ULBdRORRFxkDidehaiAAuzs/Q1zEFuofi8He3Q0c7eBaquUxJfzh1WbgbA/vLzId+2JDqFMKXB2geVnL8mULQuPSsOogBPqaAu5Xkk3B9kalIfoS1C11P0Yr/3LWWFEavwfdDRERkX8HG2uoFvige/FIiY6OplixYhQqVIjp06eblyMVERGRR5O1lTX5PbO3JcyDNmHCBA4dOoS9vT1VqlRh/fr1+Pr6Puhu5Yi/vz++vr588803eHl5PejuiIjcF1pGXkTkUffEZDgfD5vfAltrTod9y6mvPse7URPit28jtGxfbMoVhT71sj7+XDz4uYH1XWYPd58Gu0/DqKehftDN/d5vWLoPvlgNH3cEHxf4Yze0qgzujlnXJ48cXb9FRERERERERERERG7SI9oiIo+6IY9BXDLYmpbA8m3WnMgB/Ui/epXk6BMkvDcej+o1bn98vmwGTZ+tCsH54amK5rYA+POKaeb8xQTTvxOvw4Yj8PEK0x7uHavf89BEREREREREREREREQeVgq2i4g8Sq6lws8R0KwsBPy1n3rjEIsijoUKU2PDNhwCTEtkOeTPf/d6z8bBqAXQvipgBY2Cweqvme6TlsOFqxATBxUKWQbaAfr/aMrb8Aa0r2ZaUr5KURjaHJ6s8A8HLCIiIiIiIiIiIiIi8nBSsF1E5FGy4QhMWmEKfg9uftti7pVDzf++HL6e6M8+JnjCpzgWKgRA4qGDnF/wK0VefhUbR0f4ZTtsPgbRF+HPOPiiC9Quaapg8zFTe1ZW4OWSubHONeD0ZTAMsLc1LTfvZAcrBufq0EVERERERERERERERB4mCraLiDxK6gfBW09Cw+BsH3Jx5QrOL/iVgj37moPtJz//hPgfFxD4cxq89pipvlUHoWtN08z0SkVMB3+3AdpUhicrmgLoNrfMan9jHqSlQ60SMGsLHIiBb7vD8w1My8eLiIiIiIiIiIiIiIj8i1kZhmHc70bj4+Px8PAgLi4Od/ds7hUsIiImG4+SMT0cq1FPY1XAi8RDB7n4v2UUev4lrG0zP0OVkZpK4sFI3MrfXNL92p9/Ev/TIvzmXsCqdSgMa3HzgB0nIcAT/N2g9gem//4x8Gb+thPw1VqIvQrpGXDqsindwRa2vHXnvsdfAxd7y6C9PDJ0/RYRERERERERERERuUnRDhGRR0zqmr1Ybz1B9BujADj+0fscGjqIuM0bATAMg5TYWHN5azs7U6B9ZzT0CoOj53EsUAD/tm2xSkqFM38FyxOuw0szodd006x1G2v4sQ9MeY7L504QHbnJVC4yxhRw71Yb3ngC3nwSetaGkS1N+fHXIC0jc8ejL0GTCTBuSd6cGBERERERERERERERkftIwXYRkUeM0acuu93WcK2ALenXrlH8rVGETJmKZ+26GIbBkZHDWRuYjytbN9886Oh5CD8KO6JN+7IDsYciON/OF0b8FSQ/Hw8bo0z/dvprhnypfFDEm5/HdyFscCMSLp+D52rC/P6wdJ8pOP/hEvh+E5QvBOfi4bGJMPI30/EDZkGP70z/dneEcgUhOF/enySRf6Bhw4YMGjQoz9vp0aMHrVu3vms5Kysrfvvtt1ypK6/8vf2cnsMTJ05gZWXFrl27cr1vIiIi/9TdrrPTp0/H09PzvvXnTv6L19Rb75X+i+MXEREREZEHS8F2EZGH1IIpL7F02jAyUlJIT042p9v7+1Fw5BtEfzqJrfVrYGVrS/5n2nNh4QLWlSjIyUnjcQkujUO+/Dcr6/Edxq87YOkgaBwCwOHhg9n9/sukOf5VprgfzHsRnq8Pg5vfPHbdYR6/+Bgj/3wDlwELwMoKxi6ErcehQZBpL/f8HuDqYHpVKAwhAaZjr6fCtVTTv8/FQ9R5wCrPzpnIv1FMTAyPP/44cPsfkCdPnsz06dPvf+dERESEDh06cPjw4QfdDQAKFy5MTEwM5cqVy9V6AwMD+eSTT26bv2bNGqysrO74WrNmTa72SURERERE5GGQeXNfERF5KOzfOB8HJze8f9zAteiT1DscjZWNDQDuFSvjVimUq7t2sPitF3HbdRDr4ycx0tMpVrAJruVrcOyDsZR690PsfX1JfK4Ca+aM4fC0rSw8cYDxr35LuW9/IHHrTs4NGIvfuNewz5/PtO96zRKmGe03TFhGkWgAKzgYA40+gnx/7df9ZAWY3Mmy4990u/nvqd0t86ysFGuXOzIyMrgUc5jrSXE4OHvgHRCElfV/89nAlJQU7O3tyZ8//13Lenh43IceiYjIoyYjI4PDhw9y5coVPD09CQoqjfV/9Lqal5ycnHBycnrQ3cjRvUNuq127NjExMeb3r7zyCvHx8YSFhZnTvL2973u/RERERERE8pq+ZYuIPKRe+XIfL368BfdKobhVrEzq5cvmPHt/f6qv2YT915/ySsxiwqyO41m3AQZWFHOuhfvWRP78/jvit0cAcCJqCXYRW7A6dZFDJ/Zz7uKfuFcOxXnlnxTc5Uz8V7+Ylpjv/h30DIOLCTc70rc+lPQ37c/erCxcTgI3R1g0EB4re7PcvjPQbRp0+No06/3vgvPD2mHwTJW8OmXyiDt7bDtrZg4j4o+P2LPyGyL++Ig1M4dx9tj2PGszMTGRbt264erqSkBAABMnTsxU5vr16wwZMoSCBQvi4uJCjRo1LGZm3Vg6dtmyZYSEhODq6kqLFi0sfnBOT0/ntddew9PTEx8fH4YNG4ZhGBbtNGzYkAEDBjBo0CB8fX1p3ty0wsStS6MWK1YMgMqVK2NlZUXDhg2BzMvbZmRkMH78eEqWLImDgwNFihThvffeu+15uFv5U6dO0b59ezw9PfH29qZVq1acOHEiO6c4R44dO0ajRo1wdnamYsWKbNq0yZw3atQoKlWqZFH+k08+ITAw0Pz+xnl4//33yZcvH56enowZM4a0tDSGDh2Kt7c3hQoVsvjhH+D1118nKCgIZ2dnihcvzogRI0hNTc3U9g8//EBgYCAeHh507NiRq1ev5vo5EBHJLdu3RzB06CuMH/8e33wzhfHj32Po0FfY/tf9YV5o2LAhL7/8MoMGDcLLy4t8+fIxdepUEhMT6dmzJ25ubpQsWZIlS5aYj8lqCfbffvsNKyvLJzT/+OMPqlWrhqOjI76+vrRp08acd/nyZbp164aXlxfOzs48/vjjHDlyxJx/8uRJWrZsiZeXFy4uLpQtW5bFixcDpmt07969KVasGE5OTgQHBzN58uQcjfvvY7jbdeObb76hQIECZGRkWNTTqlUrevXqBUBUVBStWrUiX758uLq6Uq1aNf73v/9ZlA8MDGTs2LF069YNd3d3+vXrl2kVnOyM78b1c8KECQQEBODj48NLL71kvhY2bNiQkydP8uqrr5pnqf/djSD/jZeTkxMODg4Wafb29lmev9OnT9OpUye8vb1xcXGhatWqbNmyxZz/+++/ExoaiqOjI8WLF2f06NGkpaVl4y8jIiIiIiKS9xRsFxF5SDm7++Dk5kXpjz/H2t6e9aWLknTkCFf37AbA2t6eKs/0oF29DvR45ysighPY0yqAS71Lsj/V9EOcZ606pF29ii02WBnQNKMIB3+P54l6bQFw7dCc5JLOeL/aA174HmIToFEwTFwOrT8nLfkaiU1LwC8vQsdq0KuuaXZ6Pnco6GXR32u7jsOe03DoLBw5d1/PlTz6zh7bzq7lX3A98bJF+vXEy+xa/kWeBdyHDh3K2rVr+f3331m+fDlr1qxhx44dFmUGDBjApk2bmDNnDnv27KFdu3a0aNHC4kf8pKQkJkyYwA8//MC6deuIjo5myJAh5vyJEycyffp0vvvuOzZs2MClS5f49ddfM/VnxowZ2NvbEx4ezldffZUpf+vWrQD873//IyYmhvnz52c5ruHDhzNu3DhGjBjBgQMHmDVrFvny5cuy7N3Kp6am0rx5c9zc3Fi/fj3h4eHmBwpSUlLucHZz7q233mLIkCHs2rWLoKAgOnXqlOMf01etWsWff/7JunXrmDRpEu+88w5PPfUUXl5ebNmyhRdeeIHnn3+e06dPm49xc3Nj+vTpHDhwgMmTJzN16lQ+/vhji3qjoqL47bffWLhwIQsXLmTt2rWMGzcuV8YtIpLbtm+PYMqUT7h8+ZJF+uXLl5gy5ZM8DbjPmDEDX19ftm7dyssvv8yLL75Iu3btqF27Njt27OCxxx6ja9euJCUlZbvORYsW0aZNG5544gl27tzJypUrqV69ujm/R48ebNu2jQULFrBp0yYMw+CJJ54wB4tfeuklrl+/zrp169i7dy8ffvghrq6ugOmBs0KFCjF37lwOHDjAyJEjefPNN/n555//0Xm403WjXbt2XLx4kdWrV5vLX7p0iaVLl9KlSxcAEhISeOKJJ1i5ciU7d+6kRYsWtGzZkujoaIt2JkyYQMWKFdm5cycjRozI1I/sjm/16tVERUWxevVqZsyYwfTp081b1MyfP59ChQoxZswYYmJiLB4o/KcSEhJo0KABZ86cYcGCBezevZthw4aZH0RYv3493bp145VXXuHAgQN8/fXXTJ8+/Y4PEYqIiIiIiNxPWkZeROQR4Fm7LqlxcRx6cwixi/+g9q6DuJQKwtXZjWb7TnF25UhiPK7g4VcIv4HdsS5XkKSoo5ydN5eDr7xA4JDhlBw7jnytn8HZ2c1cr81H/8PpWiqsiISuteHURXinFdT5AIDBLWqxzO0oG2cex9vDF3ZFg2GAiwMAF/88yrZl31L/2dcJL3mFD7ym8EaJnjRrEnKz8+fi4bsN8FxNKKylIyUzIyODyPDZdyxzMHwO+QIr5+qS8gkJCUybNo0ff/yRJk2aAKYAQaFChcxloqOjCQsLIzo6mgIFCgAwZMgQli5dSlhYGO+//z5gCkh/9dVXlChRAjAF6MeMGWOu55NPPmH48OG0bWt60OWrr75i2bJlmfpUqlQpxo8ff9s++/n5AeDj43PbJWKvXr3K5MmT+fzzz+ne3bSVQ4kSJahbt+49lf/pp5/IyMjg22+/Nc9kCwsLw9PTkzVr1vDYY4/dtr85NWTIEJ588kkARo8eTdmyZTl69CilS5fOdh3e3t58+umnWFtbExwczPjx40lKSuLNN98Ebj5YsGHDBjp27AjA22+/bT4+MDCQIUOGMGfOHIYNG2ZOz8jIYPr06bi5mT5Du3btysqVK/Vjv4g8dDIyMpg16/s7lpk9+3sqV66SJ0vKV6xY0fy5euMz19fXl759+wIwcuRIvvzyS/bs2UPNmjWzVed7771Hx44dGT16tEU7AEeOHGHBggWEh4dTu3ZtAGbOnEnhwoX57bffaNeuHdHR0TzzzDOUL18egOLFi5vrsbOzs6i3WLFibNq0iZ9//pn27dvf83m403XDy8uLxx9/nFmzZpnvQX755Rd8fX1p1KiReXw3xggwduxYfv31VxYsWMCAAQPM6Y0bN2bw4MHm939feSa74/Py8uLzzz/HxsaG0qVL8+STT7Jy5Ur69u2Lt7c3NjY2uLm55foS9bNmzeLChQtERESYl5kvWbKkOX/06NG88cYb5nuU4sWLM3bsWIYNG8Y777yTq30RERERERG5Fwq2i4g8AnxbPMnhN4fiVbcB+Z7tgNUtSzDuSdpDIeuCPHe5BefblOLg4IFcCV+PV8PGRH86CafAYrgElyagQ+fMFdcsDmsPg68bNC8Hrg6mmeuNgmFjFCXwo0JhZ5wcnE3lA31JL+XHpBUTqRy5EqOJE+vmfkhA8Uo0rtcez2c/pOrUaGg9BZYMAi9nCD8KP0VAAU/oXvu+nC95tFyKOZxpRvvfXUu8xKWYw/gUzH7Q9W6ioqJISUmhRo0a5jRvb2+Cg4PN7/fu3Ut6ejpBQUEWx16/fh0fHx/ze2dnZ3OgHSAgIIDz588DEBcXR0xMjEU7tra2VK1aNdNS8lWq/PNtFiIjI7l+/br5x/t/Wn737t0cPXrUHCy44dq1a0RFRf3j/t6qQoUK5n8HBAQAcP78+RwF28uWLWsRPMqXLx/lypUzv7exscHHx8f89wHTAwWffvopUVFRJCQkkJaWhru7u0W9gYGBFufg1r+xiMjD5PDhg5lmtP/dpUuXOHz4IKVLl8n19m/9LL/xmXsjyA2YV07JyWforl27zMH6v4uMjMTW1tbiOuvj40NwcDCRkZEADBw4kBdffJHly5fTtGlTnnnmGYt+Tpkyhe+++47o6GiSk5NJSUnJtHVJTt3tutGlSxf69u3LF198gYODAzNnzqRjx47ma1hCQgKjRo1i0aJFxMTEkJaWRnJycqaZ7VWrVr1rX7IzvrJly2JjY2PR3717997L0HNk165dVK5c+bb7ue/evZvw8HCLh9vS09O5du0aSUlJODs753kfRURERERE7kTBdhGRh1TikcPs7dqB4sNH4t2oCX5PtMS/zbMcHNSfhL27qb3jAADdPlmH06fheK27SFD1nmz5rjXXTp/Cr8WTpF26RKl3P8Te39+i7p+XTSdifzjvT/gCWxtb0iIOYddwPPSpD36u4GwP19MY2GEIA1+7Zdbq+4vIuJxAaHJ+VqTsZdSzc8lfrAJlarfBOvoSVft2hd8mm/Z1v/7XfsctK4KPC9QsgUhWrifF5Wq53JSQkICNjQ3bt2+3+AEaMC8/C6ZZY7eysrLKFEjPDhcXl3vr6C2cnJxytXxCQgJVqlRh5syZmfJuzLTPLbeexxuz6G8sI2ttbZ3pnN66r3pWddyoJ6u0G/Vu2rSJLl26MHr0aJo3b46Hhwdz5sxh4sSJd63373vtiog8DK5cuZKr5XLqbp/D9/L5ntNr29/16dOH5s2bs2jRIpYvX84HH3zAxIkTefnll5kzZw5Dhgxh4sSJ1KpVCzc3Nz766COLPcPvxd2uGy1btsQwDBYtWkS1atVYv369xRYmQ4YMYcWKFUyYMIGSJUvi5OTEs88+m2kLl7vdO2R3fA/qOped+5DRo0ebVwe6laOjY151S0REREREJNu0Z7uIyEMq5fw5ru7bQ9Kxo9i6u1Pp598o0Ok5CvbsS0CnrkQOfJEz06eR9MMvbP/uVS6+WoaU/A7Eb4/AxtWNi2tWETjszUyBdoDf18xh7vLpXIqL5eiIN1jbrAJX86eDtwu8uwiWmwL5hBa1PLCEP3apBo2MYEZ+9AOOLh6Ur98emznbTbPZp66HCwlgb2teah47G2gQDA56vkuy5uDskavlsqtEiRLY2dlZ/Nh8+fJlDh8+bH5fuXJl0tPTOX/+PCVLlrR4ZXcZVQ8PDwICAizaSUtLY/v2nO9Db//Xqhbp6em3LVOqVCmcnJxYuXJltuq8W/nQ0FCOHDmCv79/pnPg4ZG7f5M78fPz4+zZsxYBmV27dv3jejdu3EjRokV56623qFq1KqVKleLkyZP/uF4RkQfF09MzV8vlNT8/P65evUpiYqI57e+f7xUqVLjtdSokJIS0tDSL6+zFixc5dOgQZcrcnLlfuHBhXnjhBebPn8/gwYOZOnUqgHn5+f79+1O5cmVKliyZ6yu3ZMXR0ZG2bdsyc+ZMZs+eTXBwMKGhoeb88PBwevToQZs2bShfvjz58+fPtER8duTW+Ozt7e94/3GvKlSowK5du7h0KevVGEJDQzl06FCme5CSJUvmyTYIIiIiIiIiOaVvJiIiDymvOvVoeOYSga8OJWbubLY2qs31s2cJHjeRgj37cmbGNGLm/IhrhYrY+fqw46WOXFj4O/b58nMt+gQnxr/HoSGvZFn3lDdns+rb/eTzCcCldBncK4ViN/V56FANJnWAPnWhcQjU/tts9HqlICkF6+51cS6c72Z6xUKmslWLQlA+CM4PKWl5eHbk38Q7IAgHF687lnF08cY7IOiOZXLK1dWV3r17M3ToUFatWsW+ffvo0aOHxQ+3QUFBdOnShW7dujF//nyOHz/O1q1b+eCDD1i0aFG223rllVcYN24cv/32GwcPHqR///73NKPQ398fJycnli5dyrlz54iLyzzb39HRkddff51hw4bx/fffExUVxebNm5k2bVqWdd6tfJcuXfD19aVVq1asX7+e48ePs2bNGgYOHMjp06dzPIZ71bBhQy5cuMD48eOJiopiypQpLFmy5B/XW6pUKaKjo5kzZw5RUVF8+umn/Prrr7nQYxGRByMoqDReXlkvyX2Dt7c3QUG5tzXLP1GjRg2cnZ158803iYqKYtasWUyfPt2izDvvvMPs2bN55513iIyMZO/evXz44YeA6XO8VatW9O3blw0bNrB7926ee+45ChYsSKtWrQAYNGgQy5Yt4/jx4+zYsYPVq1cTEhJiPn7btm0sW7aMw4cPM2LECCIiIu7L2Lt06cKiRYv47rvv6NKli0VeqVKlmD9/Prt27WL37t107tz5nmaa59b4AgMDWbduHWfOnCE2NjbHx99Op06dyJ8/P61btyY8PJxjx44xb948Nm3aBMDIkSP5/vvvGT16NPv37ycyMpI5c+bw9ttv51ofRERERERE/gkF20VEHmJ2f80aPfnxBOK2bCJ2+VIA7H19qbV9P0HjJnFp5QoChwzH7/GnAEi5cJ7A19+mcP+BFH9zZJb1erp5UbxQEIZhUOC57lRfuxnHAgVMmY1Lw/MNYVJ70wz1Wz1ZwZT+dCVYe8iUdj0NgvLDlC5Qo7hpH/id0bAk7/d4lH8HK2trQup0umOZ0nU6YpUHs5c++ugj6tWrR8uWLWnatCl169bNtG96WFgY3bp1Y/DgwQQHB9O6dWsiIiIoUqRIttsZPHgwXbt2pXv37uYlXNu0aZPj/tra2vLpp5/y9ddfU6BAAXMQ4e9GjBjB4MGDGTlyJCEhIXTo0OGOe+PeqbyzszPr1q2jSJEitG3blpCQEHr37s21a9cy7Wt+O6NGjSIwMDDH471VSEgIX3zxBVOmTKFixYps3bqVIUOG/KM6AZ5++mleffVVBgwYQKVKldi4cSMjRoz4x/WKiDwo1tbWdO7c7Y5lOnXq9tDMCvb29ubHH39k8eLFlC9fntmzZzNq1CiLMg0bNmTu3LksWLCASpUq0bhxY7Zu3WrODwsLo0qVKjz11FPUqlULwzBYvHixeWn09PR0XnrpJUJCQmjRogVBQUF88cUXADz//PO0bduWDh06UKNGDS5evEj//v3vy9gbN26Mt7c3hw4donPnzhZ5kyZNwsvLi9q1a9OyZUuaN29uMfM9u3JrfGPGjOHEiROUKFEiV7eRsbe3Z/ny5fj7+/PEE09Qvnx5xo0bZ96+p3nz5ixcuJDly5dTrVo1atasyccff0zRokXvUrOIiIiIiMj9YWXcy4ai/1B8fDweHh7ExcVl+0daEZH/svN//M6pb76g/LQfsPf3JyMlBWt7e059/QUHX32J4ImfUeTFAQCkJSRgZWuLzV32MFww5SX2rv+JV746gKunv7kd5xIlcS1T9mbBzcfA0Q4qFYbYBPhuAxyPhU1R4OEEV5PBxgaeqgANgyE1HYbMhSLesODlPDsncv/l9fX77LHtRIbP5nriZXOao4s3pet0JH/xKnc4Uh523bt3x8rKKtNMRRERyTvbt0cwa9b3XL58c3lub29vOnXqRpUq1R5gz0RERERERET+PbSBrojII8C/ZSv8W7bi6t49bKlblWt/niH4o8kU6vsCziVL4VW/obnsjqebc+1UNPUOnsDKxoaUixex9fDA2vavj/xTl8DDCSdXL1w8/LCxMc34uXbmDLs7tMazVh2qrdxgKmsYMGCmaS/35a/BhiMwa4tp2XiAuGRwsgMvZ7C1gVfmQK0SYG0FdUqayuyMhhOx0CbnM3HkvyV/8SrkC6zMpZjDXE+Kw8HZA++AoDyZ0S73j2EYrFmzhg0bNjzoroiI/KdUqVKNypWrcPjwQa5cuYKnpydBQaUfmhntIiIiIiIiIv8GCraLiDxC0uKucC3mT2xcXLh25hSbq1cgcMhwrP9aIhPArVwF7Ly8sbKxIelYFBtDy1CgS3fKTPkGLidB2y+gUmGaTX2XZp1GwZpDUM8Vx4IFKT3pc1xj7UxB9SpF4VoajGkNLvamyp+sAO5OUKEQLN8HX6wx7c8+rYdpj3ZPJ6ZbbyQ65CIjXm6BFcCEZbD/T6gfBD6u9/2cyaPFytoan4IPxx6ykjusrKw4efLkg+6GiMh/krW1NaVLl3nQ3RARERERERH519Iy8iIij5jEwwfZWCkEt8pVSNi3hxIjxpCvbTt2tW9FscFvENDpOXPZ1EuX2N3lWfI/25FCvftBWga8vwhK+UOnGvBzBLy/GF5tBt1rQ1IK1P4ACnlBPnc4dBaWvwpvzAdr4KP2YGdzszNXksDBzjS7/S/NX6jM0VMH2Tf/Ek4OTnAwBk5fhvwe8MIPMKyFac93eeTo+i0iIiIiIiIiIiIicpNmtouIPCKu7t1DwoF9BHToTMiUqbiVr4hb+QpYOzgQv2M7SUcOc+30KcAUZLfz9sbO25uqS1bdrMTW2rQk/MTlUCUQGoeYAuEuDtBtGnzwDBTzhehL0Lws+Lqa9mPfcRISrkPdcfB8A+haC4bOhbIFoG99i37+8P4SEpMTTIF2gMQUKFsQLiWCjTWkZ8DW41AtEKys7s/JExERERERERERERERyWXarE1E5BEQM2cm+3p3ZV/PLiQdP0ahnn3wqFoNawcHANxDq9DobBzFhg7ndNi3rCnkw/k/fr9ZQdQFmL/DtAd7YW8o6Q/ujqZg+qBmcDIW9p2B2KvQsw50qQEvNYYPnwUHW/i+DzQrYwrKp2fA0J9hU5RpP/YbDAO2HMPfyYdiBUuaZtH3mQ69p8M7v5sC82uHQUwc9PseVkbe13MoIiIiIiIiIiIiIiKSmzSzXUTkIZeRlsb+vt2x8/Uj5PNvcC5WPMtyNk6mmeTOxUvgVrEyjoWL3Mz8fBWsPghlAqBVJdPrhimr4MfN8FlnqFjY9Pq74r7wUTvTvyNjYMpqaFURBjaDRXtMgfh1h2HIXOhXH/o3gmupsP2kKVjftdbNupqEwIWrULlI5nZEREREREREREREREQeEQq2i4g85Kxtbak0fxG27u541qh11/LeDRpRc9MOy8SXGkGdEhCcP/MBZQtAaFEolS97HXK0g+dqQL+G8NNWU+A9JQ3qB0HbUGhcGvrMMO35XrYAFPCCeqVuHh+cH955OnttiYiIiIiIiIiIiIiIPKQUbBcReQT4Nmt+27xDr79G8rEoKv70K1bWt9kdpKS/6QXwzVr4dSfM6A3+bnDwLFhbgadz5uMuJWbOm7UZ5m6H2iWhZUW4ngaNSsN3G8DHxRS0PxsHVsCPfeH8VVgVadofXkRERERERERERERE5F9CwXYRkUdc/I5tJB05jJGWhpW9faZ8IyODU19+hle9hrhVqAgp6aYl3g3DVODIeTh01jQ73eGvy8Jbv5oC5icvmmayLxx4s8K+DaBCYahRHGysYUBjU/ofu8HBDmITYFiLm7PZP1kBi/fChPbQVAF3ERERERERERERERH5d7AyjBvRlvsnPj4eDw8P4uLicHd3v9/Ni4g8si4sXcyJieMoN3UGToHFAMhIScFITcXGxSXLY+J37mBLnSr4P92GipO+gwwDCnndLJCeYQrAO9ndTOs7wxRsr1vKFIAf1OzunYtNgOMXoO/38GQFeK+NKX3/n/DqHIhLgjXDwCnzAwHyaND1W0RERERERERERETkJs1sFxF5BKReukTKydNc3b6dK+HrSY4+aQ62W9vbc/3SJcIrlaZA156UHDnG4lj3yqGUnToDj7JV4JkvTMu+j38WmpYxFbCxBidr00z3lHRTcP2bbmBgWkJ+9UGoMhbyu8OvL4G9LaSmw/ilEFoEHi9vqsfX1fSa2ReKeN/sgK21KfiecN00811ERERERERERERERORf4Dab+4qIyIOQevkyp6Z+RXpiokX6no7PsKluKAWP+VLvyGm86ze0PNAwMFJTMdJSuRy+noyUFIvsAl264XI6DZJTTTPb31mQufExf0CdD6D156ZgurWVKf3qNdMxiddNAXiAnyPgl22wcE/mesoWADfHm+97T4ffd8FbT96sU0RERERERERERERE5BGnYLuIyEPk5Gcfc/CVF4mZM9Mi3a9VG/yL1cCuemkcCxY0p187fYrT336Nna8vDU6cxbVsebY1q0/kxPc5dvrIzQoO/AlVA01Lu7coC41Lm9J/3QEfLDYtJV/YG5wdIC3dslM2f81671rr5p7uk/8Hnk43l4q/kwGNoX+jezgbIiIiIiIiIiIiIiIiDy8tIy8i8pCImTOT4+PG4lCwEPxtAnjsssVcio7gUrHreCUlcej11/B7oiUxc37k3Nw5pFy+RPGhw01BcWtrfto8jxlr3mXt1/tI/fRr/BbH4xlaw7Sc+7hnb1a8cA/sPmUKhveqa3r93cEY03/LF7qZNqULJKaDk8PNtPhkiImD4PyWx3es/s9OjIiIiIiIiIiIiIiIyENIM9tFRB4SjoUK41yyFNdj/uTKpnDSk5LMef6tn8HGzY2dbZ/k6t7dnJn2NTFzfsS7cVMA0hOuknrpEg4FC2Hv60eVms1p1agTZ3v05MRXn3DK87hpCfmPlsHZOFOlW49D21CuTX4aw80hqy6Z1CwBDYOhuN/NNF8v2H0Jtpy5mTZqAXT8GqIv3X2wpy6ZlpffGJWDMyQiIiIiIiIiIiIiIvLw0Mx2EZGHhFfd+tTZc5jkkyc4HfYtqwM8qbE+gsvr1xD1/miKDX2TjORkPGvUovr6CJyLl8DOywvX0mWIaFSbM9O+oeHpWBqcOAtAK2Df0W6kXb5EqV++h54/QUl/yO9hanDwzxhXk1l/eDQl3h5D8TdHWHYoLQO6fgsBHvBJR8u8AFeo4A/BPjfTnqwAXs6Qz/3ugz19GbafhDoloXaJez5nIiIiIiIiIiIiIiIiD4qC7SIiD5nT337Fud9/xcrGluOTxuNSshRp8fEYqWkUH24KiHtUqcrVPbs5OnYkdj6+WHt6kFTMm7TU61xPusqiWsXx8i1Ms3X7TZUahmlmegHPmw2V9CdlWyTezsXwuJpFgDwtHQ6eNb3+7sg54Brkc7mZ1iTE9MrK2TjwdIaTF037vb/SFJa9Cv5u93SOREREREREREREREREHjQF20VEHjLxO7eTfPQwWFuTejEWgoJNGUaGRbmDg1/mSvh6rGxtuTKwJTt3/Erxnf+jUKmqOFxMwkj882ZhKyv4uptlQ190weHgWaosrAfd68CmKFi+H4Y0BxcHcLSDj541zXD/u1G/Q9QFeK4G1C5159npf16Bpz+DxiFQq7hp6fjHykLLiqY946sXy95seBERERERERERERERkYeIlWEYxv1uND4+Hg8PD+Li4nB3V4BFRORWGampHP/oA2zd3clITuboO2+ClRWuZcsRPOFTvOs3BCBu6xZiV63AztOL3cMHYDzbhCe/XIKNrR0ZKSlgGFg73GEv9lsdOgudp0J6BszsC2ULZC5jGLDmEFQqAkfPwbztsHQ/1C0Jn3e5fd3JKfDWr1CvFLQJheOxUMzXFHTv/yO0DYWRLXN+ouS+0/VbREREREREREREROQmzWwXEXlIJByMJKJxbYq/MYISb44EYEu96tj5+IKdLQn79pJ8LAr+CrZ7VK+BR/UapFy4wKW1q7C1cif98hWSL5zn6Oi3KTnqPVxDyty13Yur/oeHbwlsPZ2gdWVzoP3KpnCu/XmG/M+0NxXcchxe/QlqFIMLCabZ6FZW0LfBnRtwsodJHW6+L+Zr+m/VojCwCTQqnaPzJCIiIiIiIiIiIiIi8jBQsF1E5CFhZWODtYMjVnZ25rT05CRcQspg5+FJ4rGjFOjaI9Nx9n5+eNaszZHhQ3AuWYrT337F9dOn8G3+BK7Fg0wz0h3/qnPqOjhzGd55GoCLrd9gx4rxFOnQm+BfPwd3R9KTkrBxdubAy8+TeGA/nrXqcGHRHwQ83Q7bXnUgNR0j4jixdezw6NMB+4qFLDs05GeIS4ap3W+mdZ0GF67C/P7gbA+xCXDsAmQYUNTHVObXHRBSAErnz83TKiIiIiIiIiIiIiIikicUbBcReUi4lAqiwfEYYubOYV+/npT9+jtqb9vHtT//ZGPFIPK1bY+VjQ3XY2JIvXLZYtZ6od7PY+fljVulUI5/MIb8nbpSsGcf6PA1JFyHxa+YCq4+ROqx05wvfJ78j7fF/awjhYrUJ/8maxi/lNOB54gc1J/QP5YT8ulX2M3ahV2baZyInIQRn0iRwYMBuFzBhl2tmlGgWy/KVplmOZBLiXA+HhqMhz71oGst07LzyanwvwOmme3dpkEBTzhzxbR/u2HA6D+gZnH4quv9OeEiIiIiIiIiIiIiIiL/gILtIiIPmUOvvkTqpUvY+/sTOHAwNi4uOAQU5Ozc2biWK8/ZuXOI37kdv6daUXriZ5z46H0ub1xP9TWbsXFyouHpi1g7OxO3dTPO/nbY31i2HeDrrpye+AFHX+6H0fskha7bETLgHbicCE3K4HAeXAoWw97TG7fKlSE8EePQPsq1HIznzERoHA2Vi+BRugLFhr6Jf6u2pnqvp5n2Yi+dH77sCk9/ZtqrPSkF+syAaoGw9wzULGEKrIcWheZlTQH3It6mOkY9DSEB9/t0i4iIiIiIiIiIiIiI3BMF20VEHjKlxn7ImR+nc3LSeNITEvCoVoOko4cBOLfgN5JPnsDOy4sLv88nX+tnSL1ymdSLFzHS0wGwcXEBYMfTzbG2t6fhqdiblbs5cuXAbmxcXPF5pRc0vgJNyoC7IwB+U8/g59QVvj0A5eNg5masXmqEVzFf+GYdeDnDbzuxGbWAkuM6QWg5U72frYQfN8O33aFCIfBwghrFTUvWbzsBFQvB6qGmsukZ8OGz4OtqOfDWlfPqlIqIiIiIiIiIiIiIiOQ6BdtFRB6w1Lg4rKyssHV3B+DkF5+SeGAfDkWKUvj5l7CyscE+fwApF85j6+ZG6oXzYG2Nna8fUaPfpu6BYxb1xe/YjmEYlP54ClY2Npz4ZAJXNoVT4fs5pF+7ho2jI04lSmJfMABKFocdJ6GkP7g7QfNyZERfxPqPPXAtFcoEmGar1wuCpn8tWx+XbAqoF/E2zWh3sIX6QaZ92Ev4g70t/PyCqezXayHAA95re7ODk/9nCszP7KuZ7CIiIiIiIiIiIiIi8shSsF1E5AHbXL0CVvb21N17BIC0+DgwDNITEsAwcAkKpsGxP8lITQUbG1Z62GNlY4tPs+Y4+Ofj2pkzOAQEYHXmCvQM4/zJJZxK3E6jPy8DsLPtU1xavZK0GWs5tPl7zv3yE9aOjiQeisTdJh/0mg6tKsHoVhiFvah3cgj1QkMY1/JpGLUA5u+Egl5Q3M/U4YqF4fve8FMEPDcVRrWCuqVg3DOWA5u/wzQbPj0DthyDQlVg9ynYehzKFsg8s11EREREREREREREROQRYv2gOyAi8l/n2/wJHAsVIWbOTAACBw3Fv2070i5dZGuj2qRfuwaAtZ0d1tbWFHiuB0bKdey8vHGrFMr6oMJsrhVKwoEDkJaOf4uWBI2bZK6/wsy51Ks2AvtvtpD/mQ44FStOxrVrnPpqCpTwg/ZV4akKAFhZWVE0oATXSvtAw2BoWRFWH4T3FmXRcVdwc4KRv0PnbzLnJ143XWXKFTAtKQ+mWfQHz8KxWIiMMaXN224KzIuIiIiIiIiIiIiIiDxCrAzDMO53o/Hx8Xh4eBAXF4f7X8smi4j8l630dcHWzZ0Gx00BaMMwWFPQh7Qrl6m+biuu5cqTdvkyDgEBnJwymdPffkXSoYPY58uPrbsHSUcOUaBbL8p+Nc18fFLUUS4uW0yhfv2xjr4CSSlQviBGejp//jgDnybNMAyDqNFvE/jqMFzLlsu6c7O2mJaSDy2aOe9/B+CDxfB4eRjSPHO+YYCV1c33GQb8ugM+Wgbvt4HGIVDvQ7CxgjXD/uFZlLym67eIiIiIiIiIiIiIyE2a2S4i8hAoP30OVra2HPvwfcA0w7zs12EEdOmOa0gZ9vXuxvrSgSSfiibp0EGunTyBd7PmpJw7i0fN2mBlxcWVywFIOBjJan839nbvxKGhgzg5eSLn922A8gVNddvYULB7LxwLFebKhnXEzPqB2GWLLfoT8/Ns1hT1J25bBHSukXWgHUz7uK8cYgq0R1+CPjNMS8YDRByHkxchNd2Ut2AXvDrHFPTf/KYp0A4wtRt83S3Xz6mIiIiIiIiIiIiIiEhe0p7tIiIPgdRLF7l+5jQxs7+n+OtvAuDfshX+LVsBcO3MKYy0VNKuXKH0J1Mo9d54AP78IYwLSxaBYVBsmOk4awcH7Hz98HvyaQr16sfR90aRGnuBpnEpWN06yxzI37ELjkWK4lG95s3EtAxc1p3HJdUNIz0tc2cNw7Ss/J7T8E038HQ2pZ+6BNtOQJ2SEJwf+n0PIQWgUmHT7HgAaytITIGutW7WVzrA9N/0DFP+3/ooIiIiIiIiIiIiIiLyMFKwXUTkIVCwWw+wsca3SbNMeZc3biAx8gBulUKxsrEBw8DWzQ2AIv0H4lwyiIR9e3AIMM1cdy5WnIqz5uFcKojY5UtIj4/Du16DTIF2MM2g96pTzzLxYAzuG65Q7bkPocZfQfE5W6GkP1QNNO3h/st2U/re01AvyPTvOiVhySDI724KmL/aDOxtIS0d6pcCXzfTPvB7TpvqaxwCdjbg5QzX0+DpzyAoH3zWORfOqIiIiIiIiIiIiIiISN5SsF1E5CFRsItpKXXDMDBSUkiNi2Nj1bI4lymLkZaK3+NPsalqOXyatSC5x2P4FAyidPUnOTt3NinnznJp7SriIrZg75+Pw0Nfwa9lGy788Ss27u64VQzNfkfSMsDXFTwd4ecIaFgaxi0xBds9HOF8AtjbmALqNUvcPO5ELEwPh34NoIAndKsNzSbB5USoXATm7zClf7sebK3h81WQzx3m9Yf3F0FKmum9iIiIiIiIiIiIiIjII0DBdhGRh8yBF3pz/vd5lP32B/b5xHKedQyOPIF9QirHxo3l0qE9rPl2GQElKlPEL4TYpab91q2dXTjx0ftY2dqSv9Nz5H+2A06BxTj19efEbdmY/Q4s2wexCbBoH6TthnZV4eMOsP0k/LjZVMbGChqVNgXNd52Cc3Fw/ir8tgvOxsPkTuBgCy81gk9WwNHz0LKiaWb7zmgo4WcKrnu7mOrbe8YUvK8amKvnUkREREREREREREREJK8o2C4i8pBxKlYc55JBeNVrQEj3gdif2ELqsZM4lyhN7Z2R2Dg5Uyz2MG7eARx/dyypF2NNAfbWz3D9xDEyUlIpN3UGVtbW+DZ/gvSEq7iWLUdGSgoX/jzM75+/wGM9xxFYtm7WHShTANydYPjjUNjbFARvVBrqB5lmvO8+BUH54cJVSEk3zUo/fA5WD4H1h2HzMYg6D5Ex8OUaeK4W/HkZhj0OjnYwpYupnXPxcPUahB81zZS/ngpj/4AW5e7buRYREREREREREREREblXVoZhGPe70fj4eDw8PIiLi8PdXUsGi4jcybXTp1lfuig+jZsSPOlzwAqXkiUBSDx6hIsrllKo74tY25qen4pdvpSMa9dwLBrItqb1KP5MP6yj4zi0fjoJoUXY5nKclv2nUPOp/lk3GHUBAjzA2d4yPf4aNJ0A5QqaZqSvjISutUyB+HPxpiD5lmNwPBb83eGDxaaAvKsDJFyHOc9D6fw36+v0jSlI72ALSSkwpDmULWBacl4eSrp+i4iIiIiIiIiIiIjcpJntIiIPKSM9nchBL+FavgKFXxiAS5mybKxUGjIycK9ek6rL1nBh0QJIT8fa1ta013tqKvv79SAt7gr5Oz5HemICyTv24xHrjI2TM67bTtD6uU5Uu1Og/dkv4PHy8H5byzwXe9NS8EH5Tfu3Hz4LMzdDzzpgY20qM3w+JKdAvSBToL1aIEScgOB8plnxoxfAqoMwrQc8EwoRx2H1IRj1NLSunIdnU0REREREREREREREJHcp2C4i8pBKi4/nzx/C8KhWg2or1nF6xnfYenqSkZJC8vFjrPZ3w0hLA8CtchXOzv6Rc3/8ilv5irhVCiV/23YY6WmUGPE+lxYuJn3wr2BnR0rErts3GuABzcpC49KZ82ysYURL2Hocek+H1pVgbBuYvRW+WQfDWkCgDzQIhrah0KEaWAMvz4ZD50yB9v1/QlyyaVZ7o9Iwvl0enDkREREREREREREREZG8p2C7iMhDys7Li9o7DmDn6QXAhd/mkR4XR92DJ7myZRN7u7bH1sOTtCuXOTRsECkxf+JYsBBxmzeSeukS+Z/tQLlvpgPg36c75bycuLwpHKciRQFIPnmC+O0R5Gt7S8D79GVYeQA2R8H5q9C5hin9UiLsijYFyN0doUwAPFEeKhY27el+4E/TTPYd0aZAu5sj/BQBy/fD1G7wx26oU9K0BP3pS6Yl6asF3sezKSIiIiIiIiIiIiIikrsUbBcReYg5Fy9h/ne5734k5fw5HAsWJH/bZ8nXKpWDgwcSu2wxbmUrcCU+nmorw4nfsY0dTzbl2LvvELpgGQDW5xII8K1MwOQu5voODx/C+d/mUWPDNtxDq5gSPZyguD+ciIXLiaa0kxfhx00wdzt8+Ry8vwhOXYZzV2HNavhqMRx0hbqlTIH1KoGm42oUMwXd09JhxQHYcwZ8XEwz4INv2btdRERERERERERERETkEaRgu4jII8LOyws7Ly/zeysbG66diiY9KZEyU77BxsUFAJ9GTajw48+4li1/8+AJy2DNIZj7ApTKB0Dg4DfISLnOkXfepOL3P2O79xzUKG4qk55hWjZ+8V54cz70rmvam/2jZWBrA0W8oXYJ+HUHnEiBkj6mWe7uTmBtBWsPwdiF0K0WvDjTFGQv4QsrD8KxCwq2i4iIiIiIiIiIiIjII8/6QXdARETuXaWff6PM51PZ0fpxkk8cN6fna9sOl+DS7Ovbnb09u5iC5a80hRL+5jIeVapi4+LKlfB1pP2yEQbOhp+2mjJtrGFnNMQnmwLwjUPgpcamQHoJf/jiObC3hZqPwTVvqFAUft8JT02GgzFQzM90XM0SpmXmU9NNQfpPOsDj5f8+DBERERERERERERERkUeOZraLiDzCrGxsSNi/lysbN5AcfRKnwGIW+fE7tmGkpkL5QqbXXxKPHOb4R+9T/M13KD3xM+zT7SEmDWytTYHxU5egZ5ip8GedoGwB079/6APJKfDYJKgaCF91hTnPQ1FvCD8KZ65APg/wcoavu5qOmdgODp2Dr9dCCT9oWDrvT4yIiIiIiIiIiIiIiEge08x2EZFHXLHX36LekdN412+YKa/mxh3U3LonU/rFFUuJ+XEGV8LXY+/rC/ncwdcVxi+D5fuhgCcU9TEVnvXXbPc5W6HOB3D4HDxZAZqVMaUnp8DCPdC0DHzWGVwd4Ks1sP9P2HgUZm6BlhVNgfqedfPkHIiIiIiIiIiIiIiIiNxvmtkuIvKIs7KywrFAgSzzrB0cskwv1K8/ruUq4FWn3s3ElhUhLR3qlgJHO2hdGb5YDalp0GyiaRn5QB9TUH50K9MxnafCgT9N//Zzg4bBEBkDX62Fk5egpB9sPwmnL0PN4rk5bBERERERERERERERkQfKyjAM4343Gh8fj4eHB3Fxcbi7u9/v5kVEJCc+XwW/74LZ/UyB9hsMA1p8AufiTe8LeMLCgbA5CuKSIbQo+LvB+aummfPyyNP1W0RERERERERERETkJi0jLyIidzagMax4zRRo/2gpVB0LYRug2rswqCn0qA1eTlAt0LQEff+ZcPKiKcBuZaVAu4iIiIiIiIiIiIiI/CtpGXkREcm+LcchLQOupYG7k2nJ+EHNTC+AiwnQroop8B5xHKoVe6DdFRERERERERERERERySua2S4iItn3cQeY1AFebGjag/37TbAr+ma+jyu89RTMjoC+38Phcw+sqyIiIiIiIiIiIiIiInlJM9tFRCT7CnubXgB960P5glCxcOZy7atCQU8I9Lmv3RMREREREREREREREblfFGwXEZF7U8zX9MpK9WKml4iIiIiIiIiIiIiIyL+UlpEXERERERERERERERERERHJIQXbRUREREREREREREREREREckjBdhERERERERERERERERERkRxSsF1ERERERERERERERERERCSHFGwXERERERERERERERERERHJIQXbRUREREREREREREREREREckjBdhERERERERERERERERERkRxSsF1ERERERERERERERERERCSHFGwXERERERERERERERERERHJIQXbRUREREREREREREREREREckjBdhERERERERERERERERERkRxSsF1ERERERERERERERERERCSHFGwXERERERERERERERERERHJIdsH0ahhGADEx8c/iOZFRETkHty4bt+4jouIiIiIiIiIiIiI/Jc9kGD71atXAShcuPCDaF5ERET+gatXr+Lh4fGguyEiIiIiIiIiIiIi8kBZGQ9gelpGRgZ//vknbm5uWFlZ3e/mRURE5B4YhsHVq1cpUKAA1tbaiUZERERERERERERE/tseSLBdRERERERERERERERERETkUaZpaSIiIiIiIiIiIiIiIiIiIjmkYLuIiIiIiIiIiIiIiIiIiEgOKdguIiIiIiIiIiIiIiIiIiKSQwq2i4iIiIiIiIiIiIiIiIiI5JCC7SL/QQ0bNmTQoEGZ0qdPn46npycAo0aNwsrKihYtWmQq99FHH2FlZUXDhg0z5Z0+fRp7e3vKlSuXZdtWVlbml4eHB3Xq1GHVqlXm/HXr1tGyZUsKFCiAlZUVv/32270MUURERERERERERERERCRPKdguIrcVEBDA6tWrOX36tEX6d999R5EiRbI8Zvr06bRv3574+Hi2bNmSZZmwsDBiYmIIDw/H19eXp556imPHjgGQmJhIxYoVmTJlSu4ORkRERERERERERERERCQXKdguIrfl7+/PY489xowZM8xpGzduJDY2lieffDJTecMwCAsLo2vXrnTu3Jlp06ZlWa+npyf58+enXLlyfPnllyQnJ7NixQoAHn/8cd59913atGmTN4MSERERERERERERERERyQUKtovIHfXq1Yvp06eb33/33Xd06dIFe3v7TGVXr15NUlISTZs25bnnnmPOnDkkJibesX4nJycAUlJScrXfIiIiIiIiIiIiIiIiInlJwXYRuaOnnnqK+Ph41q1bR2JiIj///DO9evXKsuy0adPo2LEjNjY2lCtXjuLFizN37tzb1p2UlMTbb7+NjY0NDRo0yKshiIiIiIiIiIiIiIiIiOQ62wfdARF5uNnZ2fHcc88RFhbGsWPHCAoKokKFCpnKXblyhfnz57NhwwZz2nPPPce0adPo0aOHRdlOnTphY2NDcnIyfn5+TJs2Lcs6RURERERERERERERERB5WCraL/Ae5u7sTFxeXKf3KlSt4eHhkSu/Vqxc1atRg3759t53VPmvWLK5du0aNGjXMaYZhkJGRweHDhwkKCjKnf/zxxzRt2hQPDw/8/PxyYUQiIiIiIiIiIiIiIiIi95eWkRf5DwoODmbHjh2Z0nfs2GERFL+hbNmylC1bln379tG5c+cs65w2bRqDBw9m165d5tfu3bupV68e3333nUXZ/PnzU7JkSQXaRURERERERERERERE5JGlme0i/0Evvvgin3/+OQMHDqRPnz44ODiwaNEiZs+ezR9//JHlMatWrSI1NRVPT89Mebt27WLHjh3MnDmT0qVLW+R16tSJMWPG8O6772Jre/ePnISEBI4ePWp+f/z4cXbt2oW3tzdFihTJ2UBFRERERERERERERERE8ohmtov8BxUvXpx169Zx8OBBmjZtSo0aNfj555+ZO3cuLVq0yPIYFxeXLAPtYJrVXqZMmUyBdoA2bdpw/vx5Fi9enK2+bdu2jcqVK1O5cmUAXnvtNSpXrszIkSOzNzgRERERERERERERERGR+8DKMAzjQXdCRERERERERERERERERETkUaKZ7SIiIiIiIiIiIiIiIiIiIjmkYLuIiIiIiIiIiIiIiIiIiEgOKdguIiIiIiIiIiIiIiIiIiKSQwq2i4iIiIiIiIiIiIiIiIiI5JCC7SIiIiIiIiIiIiIiIiIiIjmkYLuIiIiIiIiIiIiIiIiIiEgOKdguIiIiIiIiIiIiIiIiIiKSQwq2i4iIiIiIiIiIiIiIiIiI5JCC7SIiIiIiIiIiIiIiIiIiIjmkYLuIiIiIiIiIiIiIiIiIiEgOKdguIiIiIiIiIiIiIiIiIiKSQwq2i4iIiIiIiIiIiIiIiIiI5ND/AY1a6rFTIrcNAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sc.pl.umap(\n", + " adata_test,\n", + " color=\"cell_type\",\n", + " size=8,\n", + " title=\"Original Data\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The original data has a similar structure. As a last check before we make a joint UMAP, we can look at a heatmap of gene expression between generated and original data:" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "markers = ['MALAT1', 'MT-CO2', 'MT-CO1', 'MT-ND3', 'MT-ND4L', 'MT-CO3', 'MT-CYB', 'MT-ATP8', 'MT-ND4', 'MT-ATP6', 'MT-ND5', 'MT-ND2', 'MT-ND1', 'MTRNR2L12', 'HSP90AA1', 'HSPA1A', 'HSPA1B', 'DNAJB1', 'FOSB', 'HSP90AB1', 'HSPA8', 'JUNB', 'FOS', 'DUSP1', 'BTG1', 'JUN', 'FTL', 'B2M', 'RPL41', 'RPLP1', 'RPS27', 'RPL10', 'RPL13', 'RPS12', 'RPL28', 'RPS19', 'RPL39', 'RPS15A', 'RPS3A', 'RPS27A', 'RPL32', 'RPS28', 'RPL34', 'RPS14', 'RPL30', 'RPS18', 'RPL37', 'RPL11', 'RPS21', 'RPS23', 'RPL19', 'RPS3', 'RPL18A', 'RPS15', 'RPL26', 'RPL3', 'RPS6', 'RPS8', 'RPL35A', 'RPLP2', 'RPL12', 'RPS2', 'RPL21', 'RPL36', 'RPL14', 'RPS13', 'RPL18', 'RPL7A', 'RPS25', 'RPL8', 'RPS4X', 'RPL29', 'RPL23A', 'RPL9', 'RPS24', 'RPLP0', 'RPS29', 'RPL17', 'RPL37A', 'RPL15', 'RPS7', 'RPL6', 'RPL10A', 'RPS16', 'RPL5', 'EEF1A1', 'RPL13A', 'RPL22', 'RPS5', 'TPT1', 'RPL35', 'RPL36A', 'RPS9', 'RPL24', 'PTMA', 'RPL38', 'FAU', 'HLA-B', 'RPSA', 'EEF1B2', 'HLA-A', 'UBA52', 'TMSB4X', 'RPL4', 'EEF1G', 'EIF1', 'ACTB', 'NACA', 'HLA-C', 'RACK1', 'PABPC1', 'RPL27', 'PPP1R15A', 'TMSB10', 'HSPH1', 'PNRC1', 'RPL31', 'H3-3B', 'RPS11', 'EEF2', 'BTG2', 'PFDN5', 'RPL7', 'HNRNPA2B1', 'SARAF', 'BTF3', 'NPM1', 'FTH1', 'HNRNPA1', 'RPS20', 'CD3E', 'RPL36AL', 'MT-ND6', 'HSPE1', 'NCL', 'SRSF7', 'CD8A', 'HNRNPDL', 'ZFP36L2', 'TUBA1A', 'SLC2A3', 'CD3D', 'EIF4A2', 'HNRNPU', 'SRSF5', 'RPL27A', 'RPS17', 'RPL23', 'EIF4A1', 'CD7', 'PTPRC', 'HSPD1', 'DDX5', 'H3-3A', 'EIF4B', 'SERF2', 'SLC25A5', 'EIF3E', 'RPS4Y1', 'CD52', 'TOMM7', 'PCBP2', 'IL7R', 'SLC25A6', 'RBM39', 'EIF3F', 'RPS26', 'MYL12A', 'EIF3K', 'CD69', 'RPL22L1', 'TUBA1B', 'EIF3G', 'ATP5F1E', 'EIF3H', 'CFL1', 'EIF4A3', 'UBC', 'RAC2', 'CD8B', 'CD3G', 'RGS2', 'SRSF3', 'EIF5A', 'SFPQ', 'TUBA4A', 'EIF3D', 'EIF4G2', 'EIF3L', 'HNRNPC', 'TSC22D3', 'EIF1AX', 'HINT1', 'RPS10', 'SLC25A3', 'RPS27L']" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING: Gene labels are not shown when more than 50 genes are visualized. To show gene labels set `show_gene_labels=True`\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sc.pl.heatmap(adata_test, markers, groupby='cell_type', swap_axes=True, vmax=3.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING: Gene labels are not shown when more than 50 genes are visualized. To show gene labels set `show_gene_labels=True`\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sc.pl.heatmap(generated_adata, markers, groupby='cell_type', swap_axes=True, vmax=3.0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see from the heatmaps that the generated cells have very realistic gene expression profiles compared to the original data, which is promising. It indicates that the cell generation of our C2S model is accurate, and the linear model is able to reconstruct gene expression effectively.\n", + "\n", + "Now, we will move on to visualizing a joint UMAP of generated and original ground truth cells, so that all cells are in the same joint space." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Combined UMAP in shared space\n", + "Now, we create a combined AnnData object and run PCA, neighbors, and UMAP:" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [], + "source": [ + "del adata_test.uns\n", + "del adata_test.obsm\n", + "del adata_test.varm\n", + "del adata_test.obsp\n", + "\n", + "del generated_adata.uns\n", + "del generated_adata.obsm\n", + "del generated_adata.varm\n", + "del generated_adata.obsp" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex', 'data_label'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata_test" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 2978 × 23944\n", + " obs: 'cell_type', 'data_label'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generated_adata" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "adata_test.obs[\"data_label\"] = \"Original Data\"\n", + "generated_adata.obs[\"data_label\"] = \"C2S Generated Data\"" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(2978, 23944)\n", + "3.3575494\n", + "209.48633\n", + "1.9250746\n", + "0.008749011\n" + ] + } + ], + "source": [ + "print(adata_test.X.shape)\n", + "print(adata_test.X.max())\n", + "print(adata_test.X[0].sum())\n", + "print(adata_test.X[0].max())\n", + "print(adata_test.X[0].mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(2978, 23944)\n", + "2.2378533\n", + "193.574\n", + "2.2378533\n", + "0.008084447\n" + ] + } + ], + "source": [ + "print(generated_adata.X.shape)\n", + "print(generated_adata.X.max())\n", + "print(generated_adata.X[0].sum())\n", + "print(generated_adata.X[0].max())\n", + "print(generated_adata.X[0].mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 5956 × 23944\n", + " obs: 'cell_type', 'data_label'" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "concat_adata = anndata.concat([adata_test, generated_adata], axis=0)\n", + "concat_adata" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 5956 × 23944\n", + " obs: 'cell_type', 'data_label'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "concat_adata.var = adata_test.var.copy()\n", + "concat_adata" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Counter({'Original Data': 2978, 'C2S Generated Data': 2978})" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Counter(concat_adata.obs[\"data_label\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [], + "source": [ + "sc.tl.pca(concat_adata)" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [], + "source": [ + "sc.pp.neighbors(concat_adata)" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [], + "source": [ + "sc.tl.umap(concat_adata)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 5956 × 23944\n", + " obs: 'cell_type', 'data_label'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", + " uns: 'pca', 'neighbors', 'umap'\n", + " obsm: 'X_pca', 'X_umap'\n", + " varm: 'PCs'\n", + " obsp: 'distances', 'connectivities'" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "concat_adata" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/anndata/_core/anndata.py:1230: ImplicitModificationWarning: Trying to modify attribute `.obs` of view, initializing view as actual.\n", + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n", + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/anndata/_core/anndata.py:1230: ImplicitModificationWarning: Trying to modify attribute `.obs` of view, initializing view as actual.\n", + "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n", + "/tmp/tmp.cdyXGrsOEn/ipykernel_784881/2650716503.py:19: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all axes decorations.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 5))\n", + "ax = sc.pl.umap(\n", + " concat_adata[concat_adata.obs[\"data_label\"] == \"Original Data\", :],\n", + " color=\"cell_type\",\n", + " size=8,\n", + " title=\"Original Human Immune Tissue Data\",\n", + " show=False,\n", + " legend_loc=None,\n", + " ax=ax1,\n", + ")\n", + "sc.pl.umap(\n", + " concat_adata[concat_adata.obs[\"data_label\"] == \"C2S Generated Data\", :],\n", + " color=\"cell_type\",\n", + " size=8,\n", + " title=\"C2S Generated Data\",\n", + " show=False,\n", + " ax=ax2,\n", + ")\n", + "plt.tight_layout()\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that the generated data by our C2S model (right) comes very close to the original data (left), which is promising for the potential of C2S to generate realistic data. These cells are being visualized after conversion back to expression vectors from generated cell sentences, so we can also observe that we did not lose too much information in our data by going to cell sentences and back to expression vectors. This allows us to leverage the strengths and generation ability of LLMs without losing too much information." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.8.19 ('cell2sentence': conda)", + "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": "3.8.19" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "30854c2c12e6a68630235fdae2d040378c6582e0cbda77c6d9a96d02c39a5866" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} +>>>>>>> 593fb74 (Peft feature implemented) diff --git a/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb b/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb index 76ceb5b..b2f947d 100644 --- a/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb +++ b/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb @@ -1,3 +1,4 @@ +<<<<<<< HEAD { "cells": [ { @@ -1046,3 +1047,1053 @@ "nbformat": 4, "nbformat_minor": 5 } +======= +{ + "cells": [ + { + "cell_type": "markdown", + "id": "200e725e", + "metadata": {}, + "source": [ + "# Tutorial Notebook 9: Natural Language Interpretation of Single-Cell Datasets with a C2S Foundation Model\n", + "\n", + "In this tutorial notebook, we demonstrate how to generate natural language interpretations of single-cell datasets using a Cell2Sentence (C2S) model. We will utilize a pretrained C2S foundation model to generate descriptive summaries for sets of cells, treating the task as a form of natural language interpretation of complex biological data.\n", + "\n", + "This notebook will guide you through the following steps:\n", + "1. Load an immune tissue single-cell dataset from Domínguez Conde et al. (preprocessed in tutorial notebook 0).\n", + "2. Load a pretrained C2S model.\n", + "3. Format multi-cell inputs into prompts for natural language interpretation.\n", + "4. Use the C2S model to generate insightful summaries for different sets of cells." + ] + }, + { + "cell_type": "markdown", + "id": "0c85ef67", + "metadata": {}, + "source": [ + "We will begin by importing the necessary libraries. These include standard Python libraries for data manipulation, as well as specific modules from the `cell2sentence` package for handling single-cell data and C2S models." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "9b66f739", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import json\n", + "import random\n", + "\n", + "from datasets import Dataset\n", + "import numpy as np\n", + "import anndata\n", + "import scanpy as sc\n", + "import torch\n", + "from tqdm import tqdm" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e9149a9c", + "metadata": {}, + "outputs": [], + "source": [ + "import cell2sentence as cs" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "44342a01", + "metadata": {}, + "outputs": [], + "source": [ + "SEED = 1234\n", + "random.seed(SEED)\n", + "np.random.seed(SEED)" + ] + }, + { + "cell_type": "markdown", + "id": "894938d9", + "metadata": {}, + "source": [ + "# Load Data\n", + "\n", + "Next, we will load the preprocessed single-cell dataset from tutorial 0. This dataset has been filtered and normalized, making it ready for conversion into cell sentences.\n", + "\n", + "Please ensure you have run the preprocessing steps in Tutorial 0 before executing the following code if you are using your own dataset. Make sure the file path in DATA_PATH is correctly set to your preprocessed data file." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b727f9d5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 29773 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'assay', 'sex', 'n_genes', 'n_genes_by_counts', 'total_counts', 'total_counts_mt', 'pct_counts_mt'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", + " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", + " obsm: 'X_pca', 'X_umap'\n", + " varm: 'PCs'\n", + " obsp: 'connectivities', 'distances'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "DATA_PATH = \"/home/sr2464/scratch/C2S_API_Testing/Data/dominguez_conde_immune_tissue_two_donors_preprocessed_tutorial_0.h5ad\"\n", + "adata = anndata.read_h5ad(DATA_PATH)\n", + "adata" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "0cb6535d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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cell_typetissuebatch_conditionorganismassaysexn_genesn_genes_by_countstotal_countstotal_counts_mtpct_counts_mt
Pan_T7935490_AAACCTGCAAATTGCCCD4-positive helper T cellileumA29Homo sapiens10x 5' v1female219121916542.0327.04.998472
Pan_T7935490_AAACGGGCATCTGGTACD8-positive, alpha-beta memory T cellileumA29Homo sapiens10x 5' v1female204620465871.0429.07.307103
Pan_T7935490_AAACGGGTCTTGCATTCD8-positive, alpha-beta memory T cellileumA29Homo sapiens10x 5' v1female212921297248.0337.04.649559
Pan_T7935490_AAAGCAATCATCGCTCCD8-positive, alpha-beta memory T cellileumA29Homo sapiens10x 5' v1female126212623927.0305.07.766743
Pan_T7935490_AAAGTAGCAGTCACTAgamma-delta T cellileumA29Homo sapiens10x 5' v1female224822486574.01083.016.473988
\n", + "
" + ], + "text/plain": [ + " cell_type tissue \\\n", + "Pan_T7935490_AAACCTGCAAATTGCC CD4-positive helper T cell ileum \n", + "Pan_T7935490_AAACGGGCATCTGGTA CD8-positive, alpha-beta memory T cell ileum \n", + "Pan_T7935490_AAACGGGTCTTGCATT CD8-positive, alpha-beta memory T cell ileum \n", + "Pan_T7935490_AAAGCAATCATCGCTC CD8-positive, alpha-beta memory T cell ileum \n", + "Pan_T7935490_AAAGTAGCAGTCACTA gamma-delta T cell ileum \n", + "\n", + " batch_condition organism assay \\\n", + "Pan_T7935490_AAACCTGCAAATTGCC A29 Homo sapiens 10x 5' v1 \n", + "Pan_T7935490_AAACGGGCATCTGGTA A29 Homo sapiens 10x 5' v1 \n", + "Pan_T7935490_AAACGGGTCTTGCATT A29 Homo sapiens 10x 5' v1 \n", + "Pan_T7935490_AAAGCAATCATCGCTC A29 Homo sapiens 10x 5' v1 \n", + "Pan_T7935490_AAAGTAGCAGTCACTA A29 Homo sapiens 10x 5' v1 \n", + "\n", + " sex n_genes n_genes_by_counts \\\n", + "Pan_T7935490_AAACCTGCAAATTGCC female 2191 2191 \n", + "Pan_T7935490_AAACGGGCATCTGGTA female 2046 2046 \n", + "Pan_T7935490_AAACGGGTCTTGCATT female 2129 2129 \n", + "Pan_T7935490_AAAGCAATCATCGCTC female 1262 1262 \n", + "Pan_T7935490_AAAGTAGCAGTCACTA female 2248 2248 \n", + "\n", + " total_counts total_counts_mt pct_counts_mt \n", + "Pan_T7935490_AAACCTGCAAATTGCC 6542.0 327.0 4.998472 \n", + "Pan_T7935490_AAACGGGCATCTGGTA 5871.0 429.0 7.307103 \n", + "Pan_T7935490_AAACGGGTCTTGCATT 7248.0 337.0 4.649559 \n", + "Pan_T7935490_AAAGCAATCATCGCTC 3927.0 305.0 7.766743 \n", + "Pan_T7935490_AAAGTAGCAGTCACTA 6574.0 1083.0 16.473988 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.obs.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "78b71e4d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 29773 × 23944\n", + " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", + " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", + " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", + " obsm: 'X_pca', 'X_umap'\n", + " varm: 'PCs'\n", + " obsp: 'connectivities', 'distances'" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.obs = adata.obs[[\"cell_type\", \"tissue\", \"batch_condition\", \"organism\", \"sex\"]]\n", + "adata" + ] + }, + { + "cell_type": "markdown", + "id": "c2be1277", + "metadata": {}, + "source": [ + "# Cell2Sentence Conversion\n", + "\n", + "In this section, we will convert our AnnData object into a format that the C2S model can understand. This involves transforming the gene expression data of each cell into a \"cell sentence,\" which is a string of gene names ordered by their expression level. We will also prepare the vocabulary from our dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "842861e5", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 29773/29773 [00:09<00:00, 2995.86it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", + " num_rows: 29773\n", + "})" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata_obs_cols_to_keep = adata.obs.columns.tolist()\n", + "\n", + "# Create Arrow dataset and vocabulary from AnnData\n", + "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", + " adata=adata,\n", + " random_state=SEED,\n", + " sentence_delimiter=' ',\n", + " label_col_names=adata_obs_cols_to_keep\n", + ")\n", + "arrow_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "ac96a758", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'cell_name': 'Pan_T7935490_AAACCTGCAAATTGCC',\n", + " 'cell_sentence': 'RPLP1 ACTB EEF1A1 HSP90AA1 TMSB4X B2M FTH1 KLF6 HSPA1B MALAT1 RPS12 HSPA8 RPL13 MT-CO1 ATF3 MT-CO2 RPL41 TPT1 MT-CO3 RPS19 HLA-B RPL10 RPS4X RPL28 MT-CYB DUSP1 RPL30 MT-ND4L RPS15 FOS RPL34 RPS2 RPLP2 MT-ND3 RPS18 RPS8 TRBV7-2 RPL32 RPS3 ANXA1 RPL11 HLA-C RPS27 ACTG1 UBC RPL3 RPL37 RPLP0 MT-ATP6 JUNB RPS28 RPL18 UBB MT-ATP8 RPS14 RPL39 PFN1 GAPDH HSPA1A RPL18A SRGN RPS27A RPL26 RPL19 RPS15A HLA-A DNAJB1 RPS3A CREM RPS13 MT-ND1 RPL21 RPS25 BTG2 RPL35A FAU RPL8 RPL7A RPS24 RPS6 RPS16 RACK1 NFKBIA RGS1 RPL29 CALM1 RPL9 RPL37A MT-ND5 TNFAIP3 RPS23 IL7R RPL36A PTMA NFKBIZ UBA52 EIF1 CRIP1 CORO1A RPL14 HSP90AB1 RPL10A CXCR4 RPL4 EEF1B2 RPL36 RPS9 RPL27 NACA VIM H3-3B RPS7 HSPH1 ATP5F1E HLA-E RPL17 RPSA MYL12A RPL12 CD69 TAGAP RPL35 RPS29 RPL6 SARAF ZFP36L2 MT-ND4 ARHGDIB BTG1 RPS21 EEF1D PNRC1 EEF1G HSPA5 FYB1 CD3E IFITM1 RNASEK EEF2 MT-ND2 FTL S100A4 JUN IFITM2 CYTIP OST4 LAPTM5 RPL36AL PLAAT4 PFDN5 SAMSN1 DNAJA1 EIF4A1 FXYD5 HSPE1 CTLA4 IL32 RPL24 CFL1 SAT1 RPL13A NPM1 NDUFV2 SRSF7 ITM2B POLR1D CCNI CALR ZFP36 COX7C PTPRC GADD45A CD3G RAC2 MYL6 UBE2D3 CCL20 RPS5 RPL22 TOMM7 RPL15 C12ORF57 LSP1 SON H4C3 RPL23A RPL31 DDX5 EVL AHR SERF2 STK17A CD6 PTGER4 OSTF1 OAZ1 TMA7 PHLDA1 COMMD6 PPIA TMSB10 RHOH TUBA1B KTN1 PDIA3 DUSP5 BTF3 SSR4 ATP5MC2 S100A6 CEBPD TRAV13-2 STAT1 HSPB1 PSMB9 RPL38 HNRNPA2B1 FLT3LG CSTB CDK2AP2 CSK MIF MCL1 PSME1 TXNIP RHOA HNRNPA1 UBL5 PTGES3 PDCD4 SLC2A3 ERCC1 SNHG29 NFKBID SRP14 ARPC1B NR4A2 CMTM6 CD44 ITGA4 GNB2 TRAV19 BHLHE40 HMGB1 ARPC3 TRIR PRKCH NME2 KLRB1 CLIC1 ANAPC16 NCOR1 COX5B MYL12B SAP18 RHOB TCF25 SOD1 SRSF9 FOSB PCBP1 CD96 TBC1D10C CD164 CD3D ACTR2 COX4I1 SH3BGRL3 KMT2E HSPD1 PABPC1 SPCS2 SERP1 TNFRSF1B TAGLN2 PCBP2 RPL5 LDLR YWHAB CSRNP1 COX8A MYADM TRMT112 ATP5MG GABARAP ELF1 PRR13 RPL22L1 WAKMAR2 SIT1 GADD45B RPS17 S100A10 RBBP4 HNRNPDL CD2 UQCRQ COX6B1 RGS2 CHCHD2 TAF1B 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RNF213 PRKRA EDF1 PRPF38B RHOG BAG1 ATOX1 CACYBP MAP4K1 PPP1R2 PAXX ADA NDUFA12 WAC ELK3 PRRC2C MUS81 CCT4 ARL5B RALBP1 FBXW11 LCP1 LEPROTL1 PDCD10 HNRNPR NR3C1 PPP4C BATF ABLIM1 PSMA2 TRAT1 RUNX3 CIB1 ARPC2 ABI3 UGP2 NDUFAB1 HCLS1 DERL1 RAB5A INSIG1 CNBP CHROMR DSTYK DPP4 TOMM6 PDE4D LUC7L2 JUND ARHGDIA CEMIP2 POLE4 ANXA11 PLEKHB2 SDCBP MANF FAM83D IMP3 TMCO1 SUCLG1 MBD2 NDUFA10 PDIA6 S100A11 DNPH1 TARDBP PTDSS1 RP11-25K19 LPXN FYTTD1 RORA NASP ATP6V1F RIPK2 IDI1 RASSF7 MT-ND6 RWDD1 CYB5R3 MAZ PIM1 PSMA3 GPX4 PACS1 TNIP1 PLEKHF1 STXBP2 MSMO1 UQCR11 EPB41L4A-AS1 TMIGD2 PATL1 COX6A1 CCND3 TUBB4B OCIAD2 UBE2V2 ASMTL MAP3K8 FERMT3 SH2B1 ACP5 RPS6KB2 GABPB1-AS1 MTRNR2L12 ZFAND2A EIF3D ATP5PB NEDD8 NDUFA1 C19ORF25 CYB561D2_ENSG00000114395 PPP1R18 SYF2 PIGT SLC25A3 KHDRBS1 GIMAP4 NAXE HMGN1 RGS19 SUMO1 YWHAZ ERN1 LRRFIP1 NCF1 GALNT11 PSMG2 SNRPA1 IFNGR1 ENSA LAMTOR4 TBRG1 LINC-PINT PSMA7 SH2D2A HCST GUSB SEC61B TAX1BP1 RNF149 GNG5 PIP5K1A SIGIRR ATP6V1H RXYLT1 TRAPPC2B STK4 GPR174 CLEC2B 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PHAX ATP6AP1 RDH11 TCERG1 ACTR8 SLC1A5 DSE SLC25A39 FDFT1 CIAO2A LATS1 WDR33 CCDC107 MARCHF7 FAM174C LRPAP1 COG6 IL10RA MNAT1 CLIC3 TUSC2 NAT9 FAM13B EPG5 FKBP11 CREB3 ARHGAP45 MRPL9 MGA MIDEAS PHF20 CHD9 RCE1 VDAC2 EEF1E1 SSB GBP5 NMRK1 CCT8 SCAP ACER3 VAMP8 TALDO1 PHGR1 TC2N GRID2IP EIF2AK1 TOLLIP TBC1D10A C17ORF100 NFRKB CCDC137 E4F1 XRCC5 FCMR PGPEP1 DGCR6L CHURC1 OFD1 MAP4 PLEKHA2 AMD1 MORF4L1 IER5 DCTN2 CTDSP1 DDX6 AHCYL1 PNKD ELOVL1 FXR1 SAPCD1 SELENOT UBE2L6 PMM2 RNF113A PGRMC2 CPSF6 ZNF267 MRPL50 IL16 CREBL2 ASXL2 NUDCD3 ZNF445 C3AR1 CCR5 DGKE RUNX1 AKAP11 RP11-562I5 ARIH1 PPP1CB NDUFAF3 MRPS5 ACTR1B TPD52 SF3A2 CLTC TMEM33 NDUFA5 HMGXB4 PPP1R21 RC3H2 ZNF580 PRKCSH GZMM SEC13 CTNNA1 VPS18 SYNGAP1-AS1 MAPRE1 ZC3H8 DSTN MAN2B2 MGAT4A PAK2 CRY1 LSM7 ZC3H6 TMEM230 CPQ PSMD3 TIMM17A TYMP ST6GALNAC6 PHB2 KDELR2 LAMP2 NUMB RALY ADAM8 R3HDM4 DNAAF2 ADPRM CCSER2 THRAP3 KIDINS220 RBM15B DEF6 ADNP POLR1E IQGAP1 POFUT2 EIF3K NOL7 NMUR1 NOM1 GNPDA1 PKM CWC25 IGF2R ATP2B4 GPS1 LRP10 CA10 ERI3 SMAD3 ANP32B COX7A2L EHBP1 CHUK H2AZ1 LPIN2 ASAH1 MRPL33 BCL2 DNAJC1 USO1 SUMF2 CHCHD3 NAA20 TMEM60 IER3IP1 FLII YBX1 LAIR1 MESD TSC22D1 SF1 TMEM273 PLCG1 NMD3 TMEM18 ABHD14A SLFN5 ENTR1 CHMP6 IRF2BP2 CHCHD5 HTATSF1 RPS10 LSM14A SUPT7L PEX26 YJU2 HDDC3 CFDP1 SELPLG ENO1 KDM5A MTLN ZNF706 ERVK3-1 DCP1A DBNDD2 TAX1BP3 SPINK4 RNF31 NEPRO SHFL PSMD8 IL17RA CHST14 MPC1 GLOD4 BICRAL SMIM26 KIF5C PRKAR1A TENT5C NPRL2 TTC9C RPUSD3 SSH1 ARHGAP35 RSBN1 ECHDC2 G3BP2 PRR5 SMG9 SUPT3H ATP2A3 SIN3B LSM12 PTEN ZNF93 NONO SRRM2 ITFG1 C21ORF91 HINT1 GOT1 C1QTNF1 AZIN1 MZT1 LAP3 NDUFB8 NDUFA13 FRMD4B LYRM2 IL21R PARP12 SCMH1 PBRM1 HAUS4 RAB4B FLJ40194 HIKESHI NR1D1 MFSD8 SRSF1 SMIM30 XRN2 SAMD4B SEM1 CAPZB PIAS4 IKZF1 EIF3I AGTPBP1 MZT2B C1ORF122 MUTYH WDR61 DDX39B CCNDBP1 ZNF816 PFDN2 POLR2F ANO6 NDUFS6 CTNS ATP11B SIVA1 EIF4E3 CTSC SMC4 CDC42SE2 FAM131C PLPP6 TRPC4AP MTMR14 GABARAPL1 FAM133B RFNG EIF2B1 LSM1 ISY1 EIF3G ORAI2 FAM53B SEPTIN2 HTRA2 SEPTIN6 KAT7 MBD4 CAPZA2 WDR20 NDUFB7 TWF2 COMMD5 GPR68 SPPL3 TMEM59 NCL PJA2 SDHA SLMAP CBX3 TMEM161B-AS1 PPOX ACBD3 GOLGA7 GTF2H1 MAP3K2 COA6 PHF5A COPS7A NAA10 SNX14 CUL1 ALG13 TNIK STARD3 LINC00892 SNAI3 RABAC1 USP42 NDUFA3 DDX58 PSMC6 RBCK1 HNRNPH3 ZFAND6 SDHD CHCHD10 PUM1 LDLRAD4 TCHP CNOT11 KIF1C SEC61G TACC1 PSMD6 NIPBL DAPP1 RAB2A TRIM5 LMNB2 SUPT6H AP3S1 CLK1 NSUN2 NUP88 PPA1 UMAD1 SETD9 DCAF15 ANXA2R TMEM9B EGLN2 MRPS18B PSD4 GTDC1 SUCO BUD31 IER2 UPF3A PINX1_ENSG00000254093 NUDC TAF7 UTP15 PTPMT1 PSME2 MALT1 PSTPIP1 TSPYL1 CTSD HIGD2A SBF1 LINC00667 FEM1A RAB5C TAF2 SHOC2 RASL11A AMZ2 TRIM65 ATP6V0E1 HEBP1 PSMD1 NDUFAF8 CORO1B MRPL34 UBN1 RAE1 SPINT2 SOCS1 TRIM52-AS1 TFDP1 TES YIPF2 STX5 BZW1 PDCL3 NOLC1 TPM3 INTS11 RAB35 COQ10B ZNF480 C1D THAP4 EBAG9 FOXP1 SLC30A6 NUS1 MRPS24 PPP2CA USP4 C9ORF16 MSH2 UQCRC1 SLC38A1 ACO2 WASHC5 TXLNG PHF20L1 RAB6A SERINC1 YTHDC1 MIF4GD C1GALT1 KRR1 NDFIP1 GMFG DCAF8 SNX6 PAIP2 PLAA SRP19 RAD21 TECR OTUB1 CLK3 BNIP2 NEK9 COPE RAB9A RMC1 JOSD2 MAP3K1 RNF144B ADGRE5 UBA5 NLRC3 LYPLAL1 SURF6 PDE9A ZNF720 C17ORF107 SPPL2A OPTN LACTB DNAJA2 CAMK4 PLP2 ARMC6 IDH2 FUNDC2 SNHG3 CAPG TMEM106C DR1 PGGHG TUT7 CYB561D1 EIF3E FURIN VPS26B APBB1 NTAN1 ATP5MF MAX MRPL14 ATP5ME ORAI1 SEC62 TNFRSF1A HTT EIF2AK4 SCAPER POLB FAM204A RRP12 ABHD5 IMPDH1 TAF1D TDG IMP4 SMC6 TRIM28 FAS ILK PPP1R16B TSR3 NOP56 EIF5B CUTA GLO1 PPP3CB CENPK MTRR ITGAE GOLGA3 GFER EPSTI1 THEMIS TRIAP1 HSD17B7 TSTD3 ANKRD39 PIP4K2A MTFP1 FAM222B SRFBP1 HOXB2 TRAPPC5 SRSF8 HECTD1 CCAR1 XKR8 RBM26 ISCA1 TRBC2 UBE2B TIMM8B RPUSD1 SAT2 FAM102A ST6GAL1 METTL9 C2ORF68 PERP SNU13 ANKZF1 CBX5 GPN1 COMMD8 EGLN1 HERPUD1 SENP6 SLC38A2 AARS1 GNL2 G3BP1 GPR108 PSMA4 SP100 MFSD10 TMEM70 QRSL1 DAD1 RPS19BP1 SNHG1 CSDE1 TAF4B ASF1A N4BP2L2 RNF138 FBXL5 JAK1 NCLN RAB11B PPP1CA ITGB2 KDELR1 PSMB1 MTX2 SLC35E2A NDUFS8 HAGH PIGW IVNS1ABP SDHC POLDIP2 EIF4G1 ANKRD36 SEPTIN7 CSNK1D PSMF1 TM9SF4 GAB3 MYL6B HNRNPL WIPF1 GATAD1 RFFL PRKCQ-AS1 GTPBP10 INO80D IFITM3 GAS5 WASHC1 CTNNAL1 PTGER2 USP33 ARRB2 ARMCX6 GMIP UMPS TRIM22 DDX41 SFPQ RBM25 MRPL38 CNP FAM193B MAP3K11 WDR74 PIGC CDC37 PPIP5K2 TRMO AGTRAP JMJD8 ARID5A ALKBH7 CYTH1 SET PAF1 SNHG5 FAM174B ADI1 SUDS3 CDCA7 GTSF1 MTCH1 TGIF2 MLX PYGO2 EIF2S1 DNPEP IL23R RPA1 CDC37L1 GYG1 ANP32A SRSF2 RNASEH2B WDR44 ZPR1 GIPC1 RRM2B ILVBL ARL2BP BRK1 YIF1A CEP164 DPY30 NUDT7 PPP2R1A R3HDM1 MSN PSIP1 HMGN4 CCDC152 STOML2 EEF1AKMT2 H2AZ2 CHST12 CHFR FKBP15 SPNS1 APH1A NR4A3 CNOT9 GPSM3 TESK1 CDK5RAP1 TNFAIP1 FAM118B ZBTB7A PCED1B-AS1 MRPS18A BUB3 ICMT DDIT3 DNM1L DCTN4 PPIG CCDC91 LZIC CHD2 BIRC2 AHSA1 ARAP2 COMMD10 NUCKS1 ASAP1 DCTPP1 ETFDH NAA80 STAU2 CCNL1 CASP3 CCDC174 PRNP APOA1-AS PPP1R11 SRP68 C1ORF43 RASSF1 MYD88 AKAP13 SLC25A5 ERH UBE2I ATP5PD ORC3 NUP37 TTC31 WBP2 PDE7A KPNB1 ETFA STK25 PJVK COX19 ATP5MC3 PPP2R2A MDH1 PSMB6 GTF2E2 B3GNT2 TSC22D4 GPD2 MBIP ZFR JTB GPRIN3 LPIN1 SLC35A1 NXT1 KLHL22 DYNC1I2 AP1S1 PPP1R15B SMIM15 TMEM65 HAUS3 KLHL28 MRPL20 MVK ATR MIB2 YPEL3 SCOC WASHC2C SPRY1 LCLAT1 CCDC25 SLC43A3 CIAO3 WBP11 TRIM4 C17ORF49 DTX1 VAMP5 ZSCAN16-AS1 TNFSF13B ARHGAP15 CISH DCP2 GRPEL2 PHB AASDHPPT PUM2 ISG20 PFKM SLC2A1 NBL1 TMED4 COPS3 SRSF11 ZNF710 POMP TTC14 ZNF414 PISD TMEM219 MIR23AHG COQ4 OXA1L DNAJA3 KMT2A MAGOH LYPLA2 WSB1 POLR2B AKIRIN2 PSMB2 UIMC1 DDX18 TCOF1 TNFRSF14 STARD3NL CELF2 NABP1 PTP4A2 LRRC59 TMEM167B CAMK2G SLC4A1AP EIPR1 NUCB2 MED6 VEZT SP4 ARL3 USP12 ARHGAP9 VMAC FIP1L1 RP11-316M20 ADH5 TMC6 IRF1-AS1 LIG4 SNX1 MACF1 GNL1 TPM4 RMND5A LPAR6 DNAJB2 NOP53 CDK2AP1 FIS1 PITPNM1 SF3B4 SNAP47 S100PBP C4ORF33 CHST11 RGS18 C7ORF31 PSMD4 EFCAB7 TTC39C ANXA5 KRI1 FAM214B DUSP12 NR2C1 CBLB UNG LSM8 MYO9B GLMN RALA GTF3C6 ISCA2 DNTTIP2 SELENOK MRPS36 KPNA3 THRA PTS DUSP6 VTA1 PPARG SEPTIN9 UBE2N FRY BCAS2 CAMKMT SAMHD1 GBP2 TMEM50A STAT5A IL17A PCYT2 ISG15 MAPK3 PDCD4-AS1 TIAL1 RTF1 CSNK2B RBM17 LPCAT4 ST13 CNBD2 TMEM184B RNPC3 ARCN1 SMAP2 BLOC1S1 NAMPT ZNF597 EMG1 SLC66A3 HDLBP C11ORF58 SH3BP1 SMARCB1 RP11-726G1 ZNF564 IFI27L2 ATG3 C6ORF226 REL GIMAP6 OLFM2 OGFR BAZ1A RAB7A EIF3L TBC1D20 SDHAF2 PARP10 GAK FYN TBXAS1 PRDM1 FAM241A TMEM263 SRPK1 CD2BP2 SERGEF SURF4 MTERF4 PPP1R10 IRF9 USP14 ZFAND2B AK3 CYTH3 PEBP1 PLIN2 NARF ICAM2 ZRSR2 HELZ C14ORF119 DCAF5 RBM42 ITFG2-AS1_ENSG00000258325 ZNF524 CRNKL1 FASTK UBXN1 MYO1G QTRT1 FLOT1 DNASE2 STK40 USP47 RFLNB ZFYVE28 FHL1 TATDN2 SLC25A25 ATP6V1B2 GSAP MRPL10 PSMD11 ZNF821 RANBP9 TIPRL TMED10 EIF3M HMGN2 UHMK1 TRBV30 EMP3 HPS6 TTC17 OSBPL8 COMT ERP29 GRPEL1 ZNF595 ROGDI RAD23A LYSMD2 ANKRD44 FRMD8 SRSF10 BCL2A1 TBC1D31 ALDH9A1 CHMP1A GABARAPL2 RPS20 MRPS2 CAST TMEM200A H4C2 ATRAID CRYBG1 CRY2 OSBPL7 TRAPPC1 POLR2K TESMIN UBE2D1 GNAI3 SLC39A6 HMGCS1 TMEM138 TMEM223 CHP1 ATP5MJ MSRA SQLE ATRX ZNF207 PPP1R15A DNAJC3 SNX3 FBXO9 FAM162A BTF3L4 NKIRAS1 PRDX6 EHMT1 SYS1 USP36 STX4 TMED7 NR4A1 GNA13 LINC00299 ST3GAL5 IDH3A NAA16 SLC38A10 CRYBB2 B4GALT1 METTL26 MRPL54 TRAF3IP2 DTX3L NDUFA6 NDUFAF4 SUCLA2 CALHM2 GTF2IRD2B RP11-706O15 IK MAGI3 TCTA PBDC1 BRD7 IRF1 P2RY10 CTBS CUX1 PRKD2 PGK1 BCLAF1 IRAG2 CIAPIN1 TNFRSF25 SNRNP200 IL2RG PSMA6 UQCRC2 RTF2 SLC35C2 GNG2 ZBTB22 MEF2A NOP10 LY9 MAP2K2 COMMD1 TMEM203 VPS29 SOD2 CITED2 FLI1 FMNL1 MRTO4 RETREG2 FGFR1OP2 RNF41 UTP4 TKT DHX36 ID2 TMEM245 ERP44 ESF1 BAG3 NDEL1 DAP3 HM13 PTGR2 ZFAND3 UCP2 BIN2 MCF2L2 PHKB SUB1 PDE3B CEP250-AS1 RNH1 WDR1 FAM117A CAMTA2 UGCG LINC00294 PHF14 PTPN22 KATNBL1 NT5DC1 TRIM38 ZNF780A C19ORF53 SNRPG TDP2 EIF4H TMEM140 ZCCHC17 ANKLE2 CDS2 EPHB6 CCDC90B ATAD3C COL18A1 FBP1 AHCY AFTPH ZNF432 HSPA9 CMSS1 FGD3 ANXA7 SLC25A13 RNF5 KRT10 KDM2B-DT ATP5F1D SCAMP3 KIF2A SHMT1 MRPL57 CD5 MLH1 ACOX3 ZNF593 TTI2 TRAPPC10 SRP72 CXCR6 COPS5 TET2 HEBP2 OGT ANKRD13D CEBPZ MRPL23 UBE2V1 AP2M1 SLC39A4 LLGL1 DLD ACAA2 SCAMP4 PARP8 CXXC1 MAD2L2 GIT2 OSGIN2 FAM219A ERLEC1 PTPN7 TMEM41B SERTAD3 TCF7 ARPC5 NCBP2AS2 ZNF211 SNRPB2 B9D2 ANKRD27 TIPARP RAB1B SRM PARP16 EIF4EBP2 GDI1 ARPC5L CEACAM21 IVD EXOSC4 KDM6A STARD7 JAK3 CBR1 ARL6IP5 STK26 UFM1 ARHGAP18 ESD ISOC2 HCFC1 RING1 PRELID1 MGME1 NDUFC2 CELF1 PNP IFT27 KBTBD2 TUFM TSTD1 CISD3 C17ORF67 BUD23 SCRN2 CHCHD7 FARSA RP11-29H23-1 LINC02481 TPP1 THYN1 ARHGEF1 GCLM PRPF39 TRAPPC6B SLF1 SMIM3 EVI2A AZIN2 ASH1L API5 COG2 SLC25A22 CHD4 WRAP73 CDC26 UBE2L3 EPC1 ATP2B1 CCAR2 RRN3 UBA1 CSNK1A1 CASP8 PELI1 CNOT2 SRP54 VAPA MRPS33 NDUFB11 NAF1 UBE2G2 DVL3 TLE5 CALCOCO2 UQCR10 SIRPG COX7B NDRG1 EIF2S3 H3C4 SMCHD1 RAN MAPKAPK5-AS1 TSG101 HAX1 ANKDD1A DCTN3 CD55 PSKH1 PET100 IMMT SRGAP2C H3-3A PIGH RBM48 FAM177A1 TEFM FBXL4 MID1IP1 PRR5L SLC25A11 NGDN NCAPD3 SLC9A3R1 CDIP1 GRK6 SDF4 DENND2D CASP7 EFR3A NFAT5 PRELID3B TEX30 CIRBP CSNK1G1 MCRS1 CHMP2B TMOD3 PRKX POLR2C NSFL1C POLR1H TAP2 PIANP ARL6IP6 RIPK1 TDP1 SCAF11 SNRPN ZNF335 USP3 UBQLN2 ARMCX3 HSDL1 RSU1 TXNL1 TMEM101 BAD KIF5B AP1AR FAM104A GBP4 AC058791 NDUFB1 DPP7 NDUFB2 RANGAP1 SETX MAF1 NME4 TRGV10 TACC3 AP5Z1 PITPNB EDEM1 CTD-2095E4 ANKRD28 MINDY2 YPEL4 IGHV4-34 TRIM44 ARL6IP4 GART RAD18 SF3B5 BZW2 ECD ZYX HECW2-AS1 CNTRL RECQL PARP9 UPP1 PYCR2 ARHGAP30 TBC1D22B RASGRP1 STIM1 ZNF263 ZNF230 LDLRAP1 PDCD2 FOXO1 UNC119B RNF114 YPEL5 IFNGR2 PRRC1 EIF4B PDXK RAB8B RICTOR ARL8A ESCO1 RBM38 PPIF GMPS HDDC2 FBXO42 PTP4A3 SERPINH1 TRIM69 WTAP PEMT VPS72 WAS PPP4R3A CDV3 CETN2 VAC14 TRIM21 DAZAP2 ARF5',\n", + " 'cell_type': 'CD4-positive helper T cell',\n", + " 'tissue': 'ileum',\n", + " 'batch_condition': 'A29',\n", + " 'organism': 'Homo sapiens',\n", + " 'sex': 'female'}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arrow_ds[0]" + ] + }, + { + "cell_type": "markdown", + "id": "61148588", + "metadata": {}, + "source": [ + "# Group cells into multi-cell samples\n", + "\n", + "Here, we group together cells with the same tissue label" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "d2d9b29a", + "metadata": {}, + "outputs": [], + "source": [ + "def get_multi_cell_groupings(hf_ds):\n", + " batch_tissue_to_cell_indices_dict = {}\n", + " for sample_idx in range(hf_ds.num_rows):\n", + " # Load sample, get batch sample and tissue type\n", + " sample = hf_ds[sample_idx]\n", + " batch_sample = sample[\"batch_condition\"]\n", + " tissue_type = sample[\"tissue\"]\n", + "\n", + " # If new batch sample and tissue type combination is found, add to dictionary\n", + " if (batch_sample, tissue_type) not in batch_tissue_to_cell_indices_dict:\n", + " batch_tissue_to_cell_indices_dict[(batch_sample, tissue_type)] = []\n", + "\n", + " # Add sample index to dictionary\n", + " batch_tissue_to_cell_indices_dict[(batch_sample, tissue_type)].append(sample_idx)\n", + " return batch_tissue_to_cell_indices_dict" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "89acb513", + "metadata": {}, + "outputs": [], + "source": [ + "batch_tissue_to_cell_indices_dict = get_multi_cell_groupings(arrow_ds)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "a5edfe42", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(batch sample, tissue type): [list of cell indices with this combination]\n", + "('A29', 'ileum'): [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n", + "('A29', 'lung'): [346, 347, 348, 349, 350, 351, 352, 353, 354, 355]\n", + "('A29', 'thoracic lymph node'): [3547, 3548, 3549, 3550, 3551, 3552, 3553, 3554, 3555, 3556]\n", + "('A29', 'mesenteric lymph node'): [8117, 8118, 8119, 8120, 8121, 8122, 8123, 8124, 8125, 8126]\n", + "('A29', 'bone marrow'): [10955, 10956, 10957, 10958, 10959, 10960, 10961, 10962, 10963, 10964]\n", + "('A29', 'skeletal muscle tissue'): [12365, 12366, 12367, 12368, 12369, 12370, 12371, 12372, 12373, 12374]\n", + "('A29', 'liver'): [12381, 12382, 12383, 12384, 12385, 12386, 12387, 12388, 12389, 12390]\n", + "('A29', 'spleen'): [13041, 13042, 13043, 13044, 13045, 13046, 13047, 13048, 13049, 13050]\n", + "('A31', 'spleen'): [16664, 16665, 16666, 16667, 16668, 16669, 16670, 16671, 16672, 16673]\n", + "('A31', 'ileum'): [18835, 18836, 18837, 18838, 18839, 18840, 18841, 18842, 18843, 18844]\n", + "('A31', 'omentum'): [18868, 18869, 18870, 18871, 18872, 18873, 18874, 18875, 18876, 18877]\n", + "('A31', 'lung'): [18898, 18899, 18900, 18901, 18902, 18903, 18904, 18905, 18906, 18907]\n", + "('A31', 'liver'): [20155, 20156, 20157, 20158, 20159, 20160, 20161, 20162, 20163, 20164]\n", + "('A31', 'thoracic lymph node'): [22211, 22212, 22213, 22214, 22215, 22216, 22217, 22218, 22219, 22220]\n", + "('A31', 'caecum'): [25214, 25215, 25216, 25217, 25218, 25219, 25220, 25221, 25222, 25223]\n", + "('A31', 'bone marrow'): [25285, 25286, 25287, 25288, 25289, 25290, 25291, 25292, 25293, 25294]\n", + "('A31', 'thymus'): [25648, 25649, 25650, 25651, 25652, 25653, 25654, 25655, 25656, 25657]\n", + "('A31', 'mesenteric lymph node'): [26002, 26003, 26004, 26005, 26006, 26007, 26008, 26009, 26010, 26011]\n", + "('A31', 'skeletal muscle tissue'): [28373, 28374]\n", + "('A31', 'duodenum'): [28375, 28376, 28377, 28378, 28379, 28380, 28381, 28382, 28383, 28384]\n", + "('A29', 'caecum'): [29110, 29111, 29112, 29113, 29114, 29115, 29116, 29117, 29118, 29119]\n", + "('A29', 'transverse colon'): [29378, 29379, 29380, 29381, 29382, 29383, 29384, 29385, 29386, 29387]\n", + "('A29', 'sigmoid colon'): [29640, 29641, 29642, 29643, 29644, 29645, 29646, 29647, 29648, 29649]\n" + ] + } + ], + "source": [ + "print(\"(batch sample, tissue type): [list of cell indices with this combination]\")\n", + "for key in batch_tissue_to_cell_indices_dict.keys():\n", + " print(f\"{key}:\", batch_tissue_to_cell_indices_dict[key][:10])" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "208c2009", + "metadata": {}, + "outputs": [], + "source": [ + "def get_multi_cell_arrow_ds(hf_ds, batch_tissue_to_cell_indices_dict):\n", + " \"\"\"\n", + " Function to take in a Huggingface cell sentence arrow dataset and a dictionary \n", + " mapping a tuple of (batch sample, tissue type) to a list of cell indices, and \n", + " return a new arrow dataset containing the multi-cell groupings.\n", + "\n", + " Arguments:\n", + " hf_ds: Huggingface arrow dataset containing cell sentences to group into multi-cells.\n", + " batch_tissue_to_cell_indices_dict: Dictionary mapping a tuple of (batch sample, tissue type) to a list of cell indices.\n", + " \n", + " Returns:\n", + " multi_cell_groupings_ds: Huggingface arrow dataset containing multi-cell groupings.\n", + " \"\"\"\n", + " # Initialize list to store multi-cell groupings, each element is a list of 5 cell indices\n", + " multi_cell_groupings_list = []\n", + " batch_sample_labels = []\n", + " tissue_type_labels = []\n", + " organism_labels = []\n", + "\n", + " # Loop through each sample in original dataset - keeps number of overall samples (roughly) the same\n", + " for sample_idx in tqdm(range(hf_ds.num_rows)):\n", + " sample = hf_ds[sample_idx]\n", + " batch_sample = sample[\"batch_condition\"]\n", + " tissue_type = sample[\"tissue\"]\n", + "\n", + " # Retrieve list of cell indices for this batch sample and tissue type\n", + " sample_key = (batch_sample, tissue_type)\n", + " all_cell_indices = batch_tissue_to_cell_indices_dict[sample_key]\n", + " if len(all_cell_indices) <= 5:\n", + " # If there are less than 5 cells for this batch sample and tissue type, we will sample with replacement.\n", + " # Note that another option here would be to just skip this sample.\n", + " sampled_cell_indices = random.choices(all_cell_indices, k=5)\n", + " else:\n", + " # If there are 5 or more cells for this batch sample and tissue type, we will sample without replacement\n", + " sampled_cell_indices = random.sample(all_cell_indices, k=5)\n", + "\n", + " # Add list of sampled cell indices to multi-cell groupings list\n", + " multi_cell_groupings_list.append(sampled_cell_indices)\n", + " batch_sample_labels.append(sample[\"batch_condition\"])\n", + " tissue_type_labels.append(sample[\"tissue\"])\n", + " organism_labels.append(sample[\"organism\"]) # all cells should be of the same organism\n", + "\n", + " multi_cell_groupings_ds = Dataset.from_dict({\n", + " \"multi_cell_groupings\": multi_cell_groupings_list,\n", + " \"batch_label\": batch_sample_labels,\n", + " \"tissue\": tissue_type_labels,\n", + " \"organism\": organism_labels,\n", + " })\n", + " return multi_cell_groupings_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "61064af0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 29773/29773 [00:02<00:00, 12727.38it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['multi_cell_groupings', 'batch_label', 'tissue', 'organism'],\n", + " num_rows: 29773\n", + "})" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multi_cell_arrow_ds = get_multi_cell_arrow_ds(arrow_ds, batch_tissue_to_cell_indices_dict)\n", + "multi_cell_arrow_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "34cf2803", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'multi_cell_groupings': [225, 59, 3, 46, 298],\n", + " 'batch_label': 'A29',\n", + " 'tissue': 'ileum',\n", + " 'organism': 'Homo sapiens'}" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multi_cell_arrow_ds[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "1c844580", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cell 225: A29 ileum\n", + "Cell 59: A29 ileum\n", + "Cell 3: A29 ileum\n", + "Cell 46: A29 ileum\n", + "Cell 298: A29 ileum\n" + ] + } + ], + "source": [ + "for cell_idx in multi_cell_arrow_ds[0][\"multi_cell_groupings\"]:\n", + " print(f\"Cell {cell_idx}:\", arrow_ds[cell_idx][\"batch_condition\"], arrow_ds[cell_idx][\"tissue\"])" + ] + }, + { + "cell_type": "markdown", + "id": "8428d5c9", + "metadata": {}, + "source": [ + "# Prompt Formatting for Natural Language Interpretation\n", + "\n", + "We will format prompts that provide the model with multiple cell sentences and ask it to generate a summary of the biological information contained within them. This is a powerful feature of C2S, allowing researchers to gain high-level insights from their data in a human-readable format." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "b3c8d896", + "metadata": {}, + "outputs": [], + "source": [ + "from cell2sentence.prompt_formatter import C2SMultiCellPromptFormatter" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "16092cfc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "task_name = \"natural_language_interpretation\"\n", + "prompt_formatter = C2SMultiCellPromptFormatter(\n", + " task=task_name,\n", + " top_k_genes=200\n", + ")\n", + "prompt_formatter" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "cda801f0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'multi_cell_groupings': [225, 59, 3, 46, 298],\n", + " 'batch_label': 'A29',\n", + " 'tissue': 'ileum',\n", + " 'organism': 'Homo sapiens',\n", + " 'abstract': ''}" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# We would like to generate natural language summaries at inference for groups of cells.\n", + "# For the input sample, we will put an empty string as a placeholder for the abstract, so that\n", + "# prompt formatting code is not affected.\n", + "multi_cell_arrow_ds = multi_cell_arrow_ds.add_column(\"abstract\", [\"\"] * multi_cell_arrow_ds.num_rows)\n", + "multi_cell_arrow_ds[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "f5e51eef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['sample_type', 'model_input', 'response'],\n", + " num_rows: 29773\n", + "})" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "formatted_ds = prompt_formatter.format_hf_ds(\n", + " hf_ds=arrow_ds,\n", + " multi_cell_indices_ds=multi_cell_arrow_ds\n", + ")\n", + "formatted_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "8ff9f0b2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'sample_type': 'natural_language_interpretation',\n", + " 'model_input': 'Consider these 200 highly expressed genes, ordered by descending expression, from 5 Homo sapiens cells. Using this, your task is to generate an abstract summary which summarizes the biological insights contained in these cells.\\nCell 1:\\nTMSB4X MT-CO1 CCL4 B2M MT-CO2 MALAT1 ACTB RPLP1 MT-CYB MT-CO3 HSP90AA1 MTRNR2L12 MT-ND3 EEF1A1 CCL5 MT-ATP8 HSPA1B RPS12 MT-ATP6 RPL41 RPL10 RPL28 HLA-B MT-ND4L RPS19 RPS27 RPL13 HLA-C TPT1 SH3BGRL3 JUN MT-ND2 MT-ND1 RPL37 RPS18 RPL19 RPS4X RPL30 RPS2 RPS15A IL32 HSPA8 ACTG1 CD69 XCL1 RPL26 DNAJB1 RPS15 KLF6 RPS28 RPL39 TMSB10 S100A4 RPL34 RPS14 RPL29 FTH1 GAPDH RPLP2 BTG1 MT-ND4 ATF3 RPL18A RPS3 FAU RPS27A RPS3A RPL32 RPL12 RPL21 NKG7 RPL37A RPS21 RPS24 PFN1 RPS13 RPL3 RPL11 IFITM1 CD8A RPL9 RPSA RPS23 CD3D MT-ND5 TNFAIP3 RPL35A RPS6 RPL18 RPLP0 RPL27 ZFP36 IFNG PTMA RPL8 RPS25 TRBV4-1 HLA-A CD52 PHLDA1 RPL17 VIM RPL14 RPS8 UBB H3-3B TSC22D3 SRGN RPL23A RPL35 RPS7 HSPA1A RPS16 RGS2 RPL36 CORO1A RPL13A GZMA RACK1 RPL15 RPL4 NR4A3 RAC2 RPS9 RPL7A ARHGDIB CD3E UBC ANXA1 EIF1 HLA-E RPS29 CLIC1 FTL SERF2 CALM1 SPRY1 RPL6 ZFP36L2 INSIG1 ZFP36L1 CD8B UBA52 PPIA STAT1 PLAAT4 CD160 LAPTM5 DUSP1 RPL24 ATP5MC2 NR4A1 COTL1 ARL4C CD7 EEF2 HNRNPA2B1 ATP5F1E ARL6IP5 SLC25A5 MYL12B HNRNPA1 HCST MYH9 MSN EEF1G BTG2 TRAPPC1 NACA HMGN2 GNG2 MYL12A RGL4 LMO4 CRIP1 PNRC1 PPIB EEF1D SUMO2 NEAT1 FOS SARAF ETS1 TNF SNRPD2 RPS5 STK17B RPL36A ARPC2 RHOB SEPTIN1 SAT1 CYTIP EVL GUK1 MIF JUND CFL1 COX6B1 C12ORF57.\\nCell 2:\\nRPLP1 CCL4 TMSB4X B2M RPL41 ACTB MT-CO1 MALAT1 RPL13 RPS19 RPL28 EEF1A1 RPS12 CCL5 HLA-B MT-CO2 TPT1 RPS27 MT-CO3 RPL32 MT-ND3 HSPA1A XCL1 RPS4X KLF6 DNAJB1 RPS27A RPS3 RPL10 RPS15A RPLP0 RPS18 RPS28 RPS23 MT-ATP8 RPL11 RPL30 FOS RPS2 RPS7 NR4A2 RPS14 RPS6 HLA-C RPL39 RPL18A RPL37 RPL19 JUN SH3BGRL3 TMSB10 MT-CYB RPL34 PFN1 RPL26 RPL15 HSP90AA1 TRBV9 RPS15 RPS25 RPL29 RPL17 RPS24 VIM RPS29 MT-ND4L ACTG1 RPL7A RPL36 RPL18 RPS21 RPS3A RPS8 IFITM1 H3-3B HLA-A PPP1R15A PTMA MT-ATP6 FTH1 BTG1 GAPDH RPL23A RPL3 ATF3 CD74 DUSP1 UBA52 RPL35 PNRC1 RPS16 RPL37A ATP5F1E RACK1 RPL21 RPLP2 RPL9 RPL12 RPL10A HSPA8 RPS13 EIF1 RPL8 MT-ND1 SERF2 RPL38 TNFAIP3 ARHGDIB SRGN RPL36A RPSA RPS5 IFITM2 SPRY1 RPL6 PPIA CFL1 FAU CD7 EEF2 RPL35A HCST MT-ND5 SLA IL32 CORO1A NACA RPL24 HSPA1B CRIP1 HNRNPA2B1 H3-3A CYTIP RPL27 ZFP36L2 RPL22 CD52 MT-ND4 TRAV19 ZFP36L1 CKLF RPS9 PPIB RPL14 EVL COX6B1 MYL6 RPL4 ZFP36 UBC RHOB FTL IL7R EEF1B2 UBB RPL27A TOMM7 GYPC EEF1G RAC2 CAPZB OAZ1 MAP3K8 PSMB10 HSPE1 RPL5 CD3E SARAF CD99 PABPC1 SRP14 RBM3 CHCHD2 CD3D CDKN1A NDUFS5 MYL12B EIF3F TAGAP RHOH PFDN5 SRSF7 RPL31 NR4A1 MCL1 MYL12A OST4 HMGB1 RAB9A S100A10 SAMSN1 NKG7 FYB1 S100A4 NFKBIA CNBP MT-ND2 PLAAT4 DYNLL1 SLC2A3.\\nCell 3:\\nCCL4 MALAT1 CCL4L2 B2M RPLP1 MT-CO2 EEF1A1 MT-CO1 CCL5 JUN TMSB4X IFNG FOS MT-CO3 RPL41 MT-ND4L DNAJB1 HSP90AA1 RPS12 MT-CYB ACTB RPL28 KLF6 HSPA1A PTMA TPT1 RPS19 RPS4X MT-ND3 CD69 RPL30 RPS27 RPS27A RPS28 RPL13 HLA-B RPL10 RPL32 RPS15A MT-ATP8 RPLP2 RPS3 RPL19 RPS18 RPL37 RPL18A RPS21 RPS3A RPL18 RPS14 PPP1R15A ANXA1 MT-ND1 H3-3B RPS15 RPL34 RPL39 SH3BGRL3 MT-ATP6 NR4A1 RPS8 RPL35A MT-ND2 RPS25 RPS23 ATF3 DUSP1 GAPDH RPL7A RPL26 RPL8 RPS13 RPL29 MT-ND4 RPS7 TMSB10 HLA-E IL32 ACTG1 RPL12 TRBV7-9 HSPA1B RPL14 CD8A UBB RPL3 RPS29 RPS24 RPS16 RPL36A HLA-C RPL5 HSPA8 S100A4 RPL22 RPS2 TMA7 NKG7 TNFAIP3 RPL36 RPL21 RPS5 MT-ND5 RPLP0 ATP5F1E RPL11 HSP90AB1 FAU TNF CKLF RPS6 JUND RPL9 FOSB FYB1 MYL6 FTH1 CD3E BTG1 RPL6 MYO1E ZFP36 PTPRCAP KLRB1 MCL1 VIM HCST RPL37A CD7 RPL4 FTL COX4I1 SRGN EIF1 RPS9 IFITM2 PCBP2 ITM2B NFKBIZ EEF1D SARAF RPL13A CDKN1A NFKBIA PNRC1 CFL1 MYL12A OAZ1 UBA52 IFITM3 TAGAP LY6E RPL24 ARHGDIB LDLRAD4 RPL35 TSC22D3 GZMA CRIP1 JUNB CD3D PFN1 UQCR11 NEU1 NACA RPL27 RPL15 BTF3 PCBP1 ATP1A1 RPL23 HLA-A COX7A2 HNRNPA3 MRPL18 ARGLU1 PABPN1 IFITM1 ZFP36L1 MYADM CORO1A MIF IL2RG SNRPB2 RACK1 HNRNPK CHCHD2 TPM3 ANXA11 HSPA5 SLC25A6 EEF2 CSK CALR RPSA ELF1 RBM39 STK17A COMMD6 CD2.\\nCell 4:\\nB2M MT-CO1 TMSB4X MT-CO2 RPLP1 HSP90AA1 MALAT1 HSPA8 MT-CO3 EEF1A1 H3-3B HSPA1A RPL41 MT-CYB ACTB RPS27 HSPA1B RPS18 KLF6 RPL28 RPS19 HLA-B MT-ATP6 RPL10 RPL13 MT-ATP8 RPS12 RPS28 RPL11 TPT1 MT-ND3 RPS27A CCL5 JUNB RPL39 DNAJB1 RPS2 UBC ANXA1 RPS21 MT-ND4 RPL32 MT-ND4L RPS15 RPS3 ATF3 RPL34 DUSP1 RPL21 TNFAIP3 RPLP2 RPS3A RPL37 RPL30 RPS15A BTG1 PTMA MT-ND1 RPS23 PFN1 NR4A2 RPS4X RPS14 TRBV4-1 HLA-C RPS6 HLA-A RPL12 RPL3 RPL29 PNRC1 SARAF RPL19 RPL18A RPL36 VIM RPS8 RPS7 NR4A1 TMSB10 RPSA RPL26 MT-ND5 RPS29 RPS13 RPL15 EIF1 RPL17 RPL35A CSF1 FAU GAPDH HSP90AB1 MYL12A S100A4 RPL14 FTL CD69 ACTG1 RPL18 SH3BGRL3 RPL7A CD8A ADGRE5 GZMA JUN PLAAT4 PTPRCAP NEAT1 RPLP0 RPS25 RPL22 DNAJA1 CD7 RPS24 SELENOK RPL24 RPS9 RPL5 RPS5 FOS LGALS1 MT-ND2 RPL37A STK17B NACA EEF1B2 SAT1 CYTIP RPL23A JUND CORO1A RPL38 RPL13A RPL8 PPIA FYB1 CFL1 SRGN ZFP36L2 RHOH EEF1G RPS16 HSPE1 EEF2 IL32 KLRB1 RPL9 HSPH1 TSC22D3 UBA52 SEPTIN6 PFDN5 RPL10A CD3G YBX1 CD3E HLA-E RPL4 ARHGDIB PTGER4 LIMD2 CACYBP HSPB1 SERF2 FOSB HNRNPA0 ITM2B CKLF FERMT3 RACK1 MCL1 CRIP1 RPL35 PTGES3 CAPZB RPS26 SDCBP TPI1 RAC1 CAP1 COX7C RPL36A FRMD4B TOMM7 PPP1R15A IFITM1 HSPD1 GNB2 IL7R PMAIP1 ARPC3 ATP5F1E CD3D MTRNR2L12 LSP1 MYL6 CYCS TIPARP SPATS2L.\\nCell 5:\\nMT-CO2 GNLY MT-CO3 MT-ND3 MT-CYB MT-CO1 RPLP1 MALAT1 TMSB4X MT-ATP6 EEF1A1 RPL41 MT-ATP8 HSP90AA1 RPS19 MT-ND1 RPS27 MT-ND4L GZMA CCL5 RPL13 MT-ND2 RPL30 RPL28 RPS23 RPS18 RPS27A RPL10 RPS15A ACTB B2M MT-ND4 RPS4X RPS12 RPS3 HSPA1A PTMA TPT1 RPL32 RPS8 RPS14 RPS6 RPL26 RPL34 RPL39 RPS28 GAPDH CD7 RPS24 RPL18A RPS3A RPL11 RPL8 RPS15 RPL7A RPL3 RPS7 KLF6 RPL35A RPL12 RPL23A RPL19 NKG7 RPL6 RPLP2 RPS9 RPLP0 CD52 RPL29 RPL37 TMSB10 RPL37A RPS13 RPL35 DNAJB1 MT-ND5 RPS25 RPS2 RPL15 FTL TYROBP RPS21 EEF1B2 HSPA1B RPL36A HSPA6 UBC ACTG1 MTRNR2L12 ZFP36L1 RPL18 FAU RPL22 RPL9 RPS29 NACA FTH1 NR4A1 RPL21 RPL17 ATP5F1E RPS5 RACK1 PABPC1 RPL10A IER5 CORO1A RPL14 RPL36 PFN1 H3-3B SRGN TAGAP MYL12A IFITM2 RPS16 RPL27 HCST VIM HLA-B HOPX CFL1 ATF3 SERF2 SH3BGRL3 NPM1 HLA-A EEF1D NR4A3 IFNG RPL27A CKLF EEF1G UBB RPL4 H2AJ HSP90AB1 EIF1 YBX1 PLAAT4 TRDC RPS26 BTG1 GEM CD3E COTL1 HSPA8 RPL24 FCER1G PNRC1 ARHGDIB RPL5 TOMM7 IFITM1 RPL38 RAC2 CYBA TRA2B MIF SEC11A CD247 RPL7 RPL31 OAZ1 PFDN5 CD69 KRT86 RPL13A RPSA EEF2 BTF3 COX7C MYL6 RHOC UBXN4 UBA52 DBI HMGN2 GSTK1 HSPB1 KLRB1 KIR2DL4 HLA-E FOSB CIRBP PTPN22 PHLDA1 TMA7 SYTL3 ATP5MG RHOA GNAS GYPC HLA-C H3-3A COX6C KLRC2 PARK7 NFKBIA ATP5MC2.\\n.\\nAbstract summary:',\n", + " 'response': '.'}" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "formatted_ds[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "285ca7f6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Consider these 200 highly expressed genes, ordered by descending expression, from 5 Homo sapiens cells. Using this, your task is to generate an abstract summary which summarizes the biological insights contained in these cells.\n", + "Cell 1:\n", + "TMSB4X MT-CO1 CCL4 B2M MT-CO2 MALAT1 ACTB RPLP1 MT-CYB MT-CO3 HSP90AA1 MTRNR2L12 MT-ND3 EEF1A1 CCL5 MT-ATP8 HSPA1B RPS12 MT-ATP6 RPL41 RPL10 RPL28 HLA-B MT-ND4L RPS19 RPS27 RPL13 HLA-C TPT1 SH3BGRL3 JUN MT-ND2 MT-ND1 RPL37 RPS18 RPL19 RPS4X RPL30 RPS2 RPS15A IL32 HSPA8 ACTG1 CD69 XCL1 RPL26 DNAJB1 RPS15 KLF6 RPS28 RPL39 TMSB10 S100A4 RPL34 RPS14 RPL29 FTH1 GAPDH RPLP2 BTG1 MT-ND4 ATF3 RPL18A RPS3 FAU RPS27A RPS3A RPL32 RPL12 RPL21 NKG7 RPL37A RPS21 RPS24 PFN1 RPS13 RPL3 RPL11 IFITM1 CD8A RPL9 RPSA RPS23 CD3D MT-ND5 TNFAIP3 RPL35A RPS6 RPL18 RPLP0 RPL27 ZFP36 IFNG PTMA RPL8 RPS25 TRBV4-1 HLA-A CD52 PHLDA1 RPL17 VIM RPL14 RPS8 UBB H3-3B TSC22D3 SRGN RPL23A RPL35 RPS7 HSPA1A RPS16 RGS2 RPL36 CORO1A RPL13A GZMA RACK1 RPL15 RPL4 NR4A3 RAC2 RPS9 RPL7A ARHGDIB CD3E UBC ANXA1 EIF1 HLA-E RPS29 CLIC1 FTL SERF2 CALM1 SPRY1 RPL6 ZFP36L2 INSIG1 ZFP36L1 CD8B UBA52 PPIA STAT1 PLAAT4 CD160 LAPTM5 DUSP1 RPL24 ATP5MC2 NR4A1 COTL1 ARL4C CD7 EEF2 HNRNPA2B1 ATP5F1E ARL6IP5 SLC25A5 MYL12B HNRNPA1 HCST MYH9 MSN EEF1G BTG2 TRAPPC1 NACA HMGN2 GNG2 MYL12A RGL4 LMO4 CRIP1 PNRC1 PPIB EEF1D SUMO2 NEAT1 FOS SARAF ETS1 TNF SNRPD2 RPS5 STK17B RPL36A ARPC2 RHOB SEPTIN1 SAT1 CYTIP EVL GUK1 MIF JUND CFL1 COX6B1 C12ORF57.\n", + "Cell 2:\n", + "RPLP1 CCL4 TMSB4X B2M RPL41 ACTB MT-CO1 MALAT1 RPL13 RPS19 RPL28 EEF1A1 RPS12 CCL5 HLA-B MT-CO2 TPT1 RPS27 MT-CO3 RPL32 MT-ND3 HSPA1A XCL1 RPS4X KLF6 DNAJB1 RPS27A RPS3 RPL10 RPS15A RPLP0 RPS18 RPS28 RPS23 MT-ATP8 RPL11 RPL30 FOS RPS2 RPS7 NR4A2 RPS14 RPS6 HLA-C RPL39 RPL18A RPL37 RPL19 JUN SH3BGRL3 TMSB10 MT-CYB RPL34 PFN1 RPL26 RPL15 HSP90AA1 TRBV9 RPS15 RPS25 RPL29 RPL17 RPS24 VIM RPS29 MT-ND4L ACTG1 RPL7A RPL36 RPL18 RPS21 RPS3A RPS8 IFITM1 H3-3B HLA-A PPP1R15A PTMA MT-ATP6 FTH1 BTG1 GAPDH RPL23A RPL3 ATF3 CD74 DUSP1 UBA52 RPL35 PNRC1 RPS16 RPL37A ATP5F1E RACK1 RPL21 RPLP2 RPL9 RPL12 RPL10A HSPA8 RPS13 EIF1 RPL8 MT-ND1 SERF2 RPL38 TNFAIP3 ARHGDIB SRGN RPL36A RPSA RPS5 IFITM2 SPRY1 RPL6 PPIA CFL1 FAU CD7 EEF2 RPL35A HCST MT-ND5 SLA IL32 CORO1A NACA RPL24 HSPA1B CRIP1 HNRNPA2B1 H3-3A CYTIP RPL27 ZFP36L2 RPL22 CD52 MT-ND4 TRAV19 ZFP36L1 CKLF RPS9 PPIB RPL14 EVL COX6B1 MYL6 RPL4 ZFP36 UBC RHOB FTL IL7R EEF1B2 UBB RPL27A TOMM7 GYPC EEF1G RAC2 CAPZB OAZ1 MAP3K8 PSMB10 HSPE1 RPL5 CD3E SARAF CD99 PABPC1 SRP14 RBM3 CHCHD2 CD3D CDKN1A NDUFS5 MYL12B EIF3F TAGAP RHOH PFDN5 SRSF7 RPL31 NR4A1 MCL1 MYL12A OST4 HMGB1 RAB9A S100A10 SAMSN1 NKG7 FYB1 S100A4 NFKBIA CNBP MT-ND2 PLAAT4 DYNLL1 SLC2A3.\n", + "Cell 3:\n", + "CCL4 MALAT1 CCL4L2 B2M RPLP1 MT-CO2 EEF1A1 MT-CO1 CCL5 JUN TMSB4X IFNG FOS MT-CO3 RPL41 MT-ND4L DNAJB1 HSP90AA1 RPS12 MT-CYB ACTB RPL28 KLF6 HSPA1A PTMA TPT1 RPS19 RPS4X MT-ND3 CD69 RPL30 RPS27 RPS27A RPS28 RPL13 HLA-B RPL10 RPL32 RPS15A MT-ATP8 RPLP2 RPS3 RPL19 RPS18 RPL37 RPL18A RPS21 RPS3A RPL18 RPS14 PPP1R15A ANXA1 MT-ND1 H3-3B RPS15 RPL34 RPL39 SH3BGRL3 MT-ATP6 NR4A1 RPS8 RPL35A MT-ND2 RPS25 RPS23 ATF3 DUSP1 GAPDH RPL7A RPL26 RPL8 RPS13 RPL29 MT-ND4 RPS7 TMSB10 HLA-E IL32 ACTG1 RPL12 TRBV7-9 HSPA1B RPL14 CD8A UBB RPL3 RPS29 RPS24 RPS16 RPL36A HLA-C RPL5 HSPA8 S100A4 RPL22 RPS2 TMA7 NKG7 TNFAIP3 RPL36 RPL21 RPS5 MT-ND5 RPLP0 ATP5F1E RPL11 HSP90AB1 FAU TNF CKLF RPS6 JUND RPL9 FOSB FYB1 MYL6 FTH1 CD3E BTG1 RPL6 MYO1E ZFP36 PTPRCAP KLRB1 MCL1 VIM HCST RPL37A CD7 RPL4 FTL COX4I1 SRGN EIF1 RPS9 IFITM2 PCBP2 ITM2B NFKBIZ EEF1D SARAF RPL13A CDKN1A NFKBIA PNRC1 CFL1 MYL12A OAZ1 UBA52 IFITM3 TAGAP LY6E RPL24 ARHGDIB LDLRAD4 RPL35 TSC22D3 GZMA CRIP1 JUNB CD3D PFN1 UQCR11 NEU1 NACA RPL27 RPL15 BTF3 PCBP1 ATP1A1 RPL23 HLA-A COX7A2 HNRNPA3 MRPL18 ARGLU1 PABPN1 IFITM1 ZFP36L1 MYADM CORO1A MIF IL2RG SNRPB2 RACK1 HNRNPK CHCHD2 TPM3 ANXA11 HSPA5 SLC25A6 EEF2 CSK CALR RPSA ELF1 RBM39 STK17A COMMD6 CD2.\n", + "Cell 4:\n", + "B2M MT-CO1 TMSB4X MT-CO2 RPLP1 HSP90AA1 MALAT1 HSPA8 MT-CO3 EEF1A1 H3-3B HSPA1A RPL41 MT-CYB ACTB RPS27 HSPA1B RPS18 KLF6 RPL28 RPS19 HLA-B MT-ATP6 RPL10 RPL13 MT-ATP8 RPS12 RPS28 RPL11 TPT1 MT-ND3 RPS27A CCL5 JUNB RPL39 DNAJB1 RPS2 UBC ANXA1 RPS21 MT-ND4 RPL32 MT-ND4L RPS15 RPS3 ATF3 RPL34 DUSP1 RPL21 TNFAIP3 RPLP2 RPS3A RPL37 RPL30 RPS15A BTG1 PTMA MT-ND1 RPS23 PFN1 NR4A2 RPS4X RPS14 TRBV4-1 HLA-C RPS6 HLA-A RPL12 RPL3 RPL29 PNRC1 SARAF RPL19 RPL18A RPL36 VIM RPS8 RPS7 NR4A1 TMSB10 RPSA RPL26 MT-ND5 RPS29 RPS13 RPL15 EIF1 RPL17 RPL35A CSF1 FAU GAPDH HSP90AB1 MYL12A S100A4 RPL14 FTL CD69 ACTG1 RPL18 SH3BGRL3 RPL7A CD8A ADGRE5 GZMA JUN PLAAT4 PTPRCAP NEAT1 RPLP0 RPS25 RPL22 DNAJA1 CD7 RPS24 SELENOK RPL24 RPS9 RPL5 RPS5 FOS LGALS1 MT-ND2 RPL37A STK17B NACA EEF1B2 SAT1 CYTIP RPL23A JUND CORO1A RPL38 RPL13A RPL8 PPIA FYB1 CFL1 SRGN ZFP36L2 RHOH EEF1G RPS16 HSPE1 EEF2 IL32 KLRB1 RPL9 HSPH1 TSC22D3 UBA52 SEPTIN6 PFDN5 RPL10A CD3G YBX1 CD3E HLA-E RPL4 ARHGDIB PTGER4 LIMD2 CACYBP HSPB1 SERF2 FOSB HNRNPA0 ITM2B CKLF FERMT3 RACK1 MCL1 CRIP1 RPL35 PTGES3 CAPZB RPS26 SDCBP TPI1 RAC1 CAP1 COX7C RPL36A FRMD4B TOMM7 PPP1R15A IFITM1 HSPD1 GNB2 IL7R PMAIP1 ARPC3 ATP5F1E CD3D MTRNR2L12 LSP1 MYL6 CYCS TIPARP SPATS2L.\n", + "Cell 5:\n", + "MT-CO2 GNLY MT-CO3 MT-ND3 MT-CYB MT-CO1 RPLP1 MALAT1 TMSB4X MT-ATP6 EEF1A1 RPL41 MT-ATP8 HSP90AA1 RPS19 MT-ND1 RPS27 MT-ND4L GZMA CCL5 RPL13 MT-ND2 RPL30 RPL28 RPS23 RPS18 RPS27A RPL10 RPS15A ACTB B2M MT-ND4 RPS4X RPS12 RPS3 HSPA1A PTMA TPT1 RPL32 RPS8 RPS14 RPS6 RPL26 RPL34 RPL39 RPS28 GAPDH CD7 RPS24 RPL18A RPS3A RPL11 RPL8 RPS15 RPL7A RPL3 RPS7 KLF6 RPL35A RPL12 RPL23A RPL19 NKG7 RPL6 RPLP2 RPS9 RPLP0 CD52 RPL29 RPL37 TMSB10 RPL37A RPS13 RPL35 DNAJB1 MT-ND5 RPS25 RPS2 RPL15 FTL TYROBP RPS21 EEF1B2 HSPA1B RPL36A HSPA6 UBC ACTG1 MTRNR2L12 ZFP36L1 RPL18 FAU RPL22 RPL9 RPS29 NACA FTH1 NR4A1 RPL21 RPL17 ATP5F1E RPS5 RACK1 PABPC1 RPL10A IER5 CORO1A RPL14 RPL36 PFN1 H3-3B SRGN TAGAP MYL12A IFITM2 RPS16 RPL27 HCST VIM HLA-B HOPX CFL1 ATF3 SERF2 SH3BGRL3 NPM1 HLA-A EEF1D NR4A3 IFNG RPL27A CKLF EEF1G UBB RPL4 H2AJ HSP90AB1 EIF1 YBX1 PLAAT4 TRDC RPS26 BTG1 GEM CD3E COTL1 HSPA8 RPL24 FCER1G PNRC1 ARHGDIB RPL5 TOMM7 IFITM1 RPL38 RAC2 CYBA TRA2B MIF SEC11A CD247 RPL7 RPL31 OAZ1 PFDN5 CD69 KRT86 RPL13A RPSA EEF2 BTF3 COX7C MYL6 RHOC UBXN4 UBA52 DBI HMGN2 GSTK1 HSPB1 KLRB1 KIR2DL4 HLA-E FOSB CIRBP PTPN22 PHLDA1 TMA7 SYTL3 ATP5MG RHOA GNAS GYPC HLA-C H3-3A COX6C KLRC2 PARK7 NFKBIA ATP5MC2.\n", + ".\n", + "Abstract summary:\n" + ] + } + ], + "source": [ + "print(formatted_ds[0]['model_input'])" + ] + }, + { + "cell_type": "markdown", + "id": "07376fd5", + "metadata": {}, + "source": [ + "# Load C2S Model\n", + "\n", + "Now, we will load a pretrained C2S model that has been trained on a large corpus of single-cell data and biological text. This model has learned to understand the \"language\" of cells and can be used for various interpretation tasks. We will use the `CSModel` class from the `cell2sentence` library to load the model." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "0317ac96", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using device: cuda\n" + ] + } + ], + "source": [ + "# Define the path to your pretrained model and a directory to save model-related files\n", + "model_path = \"vandijklab/C2S-Scale-Pythia-1b-pt\"\n", + "save_dir = \"/home/sr2464/scratch/C2S_API_Testing/Cache_Dir\"\n", + "save_name = \"natural_language_interpretation_1B_model\"\n", + "\n", + "# Initialize the CSModel object\n", + "csmodel = cs.CSModel(\n", + " model_name_or_path=model_path,\n", + " save_dir=save_dir,\n", + " save_name=save_name\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "7fd868a0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'cuda'" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", + "device" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "98fb6e3e", + "metadata": {}, + "outputs": [], + "source": [ + "from transformers import AutoModelForCausalLM" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "7620bdf2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GPTNeoXForCausalLM(\n", + " (gpt_neox): GPTNeoXModel(\n", + " (embed_in): Embedding(50304, 2048)\n", + " (emb_dropout): Dropout(p=0.0, inplace=False)\n", + " (layers): ModuleList(\n", + " (0-15): 16 x GPTNeoXLayer(\n", + " (input_layernorm): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n", + " (post_attention_layernorm): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n", + " (post_attention_dropout): Dropout(p=0.0, inplace=False)\n", + " (post_mlp_dropout): Dropout(p=0.0, inplace=False)\n", + " (attention): GPTNeoXSdpaAttention(\n", + " (rotary_emb): GPTNeoXRotaryEmbedding()\n", + " (query_key_value): Linear(in_features=2048, out_features=6144, bias=True)\n", + " (dense): Linear(in_features=2048, out_features=2048, bias=True)\n", + " (attention_dropout): Dropout(p=0.0, inplace=False)\n", + " )\n", + " (mlp): GPTNeoXMLP(\n", + " (dense_h_to_4h): Linear(in_features=2048, out_features=8192, bias=True)\n", + " (dense_4h_to_h): Linear(in_features=8192, out_features=2048, bias=True)\n", + " (act): GELUActivation()\n", + " )\n", + " )\n", + " )\n", + " (final_layer_norm): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n", + " (rotary_emb): GPTNeoXRotaryEmbedding()\n", + " )\n", + " (embed_out): Linear(in_features=2048, out_features=50304, bias=False)\n", + ")" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = AutoModelForCausalLM.from_pretrained(\n", + " os.path.join(save_dir, save_name),\n", + " cache_dir=os.path.join(save_dir, \".cache\"),\n", + " trust_remote_code=True\n", + ").to(device)\n", + "model" + ] + }, + { + "cell_type": "markdown", + "id": "23d5cbde", + "metadata": {}, + "source": [ + "# Generate Natural Language Interpretations of Cell Subsets\n", + "\n", + "With our model loaded, we can now ask it to interpret different subsets of cells from our dataset.\n", + "\n", + "Here, we select a sample of cells from our dataset to interpret" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "475cb926", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'multi_cell_groupings': [9744, 10316, 10819, 9040, 8557],\n", + " 'batch_label': 'A29',\n", + " 'tissue': 'mesenteric lymph node',\n", + " 'organism': 'Homo sapiens',\n", + " 'abstract': ''}" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multi_cell_arrow_ds[10000]" + ] + }, + { + "cell_type": "markdown", + "id": "5d76d4d2", + "metadata": {}, + "source": [ + "Note that the Dominguez-Conde dataset contains immune cells taken from many different tissues around the body. These are a group of 5 immune cells from a mesenteric lymph node tissue of one of the patients." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "1805db5c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Input Prompt ---\n", + "Examine the top 200 genes ordered by descending expression level in 5 Homo sapiens cells. Based on this information, generate an abstract summary which summarizes the biological insights contained in these cells.\n", + "Cell 1:\n", + "CD74 EEF1A1 MT-ND3 HLA-DRA RPS27 IGHV5-51 RPLP1 MT-CO2 RPL41 FOS RPL13 RPS19 MT-CO1 RPL32 RPL10 RPS12 RPS8 RPL30 ACTB MT-CYB HLA-DRB1 CXCR4 B2M MALAT1 RPS15A RPL8 RPL28 MT-ATP8 RPL35A RPS3A RPL18A MT-ND4L DUSP1 RPS4X TMSB4X RPL39 MT-CO3 TPT1 RPS27A RPS15 RPS28 RPS3 RPS21 RPS13 RACK1 RPL37 RPS18 RPL35 MT-ATP6 RPL26 RPS25 RPL29 CD69 RPL21 RPL19 RPS2 FAU RPL23A RPL34 RPL15 RPS5 BTG1 MT-ND4 CD52 CD37 RPL36 RPS14 RPS9 MTRNR2L12 CD79A RPLP0 JUN HLA-B RPS6 HLA-DPA1 EIF1 RPS23 RPSA RPS7 RPL27 RPL11 TCL1A HLA-DRB5 H3-3B SLC2A3 TXNIP RPS24 RPS29 RPL37A IGKC RPLP2 RPL7A CD83 CYBA PABPC1 RPL18 HLA-DQB1 MT-ND5 RPL9 RPL38 RPL10A RPL5 MT-ND1 HLA-A FTL RPL6 HLA-E EEF2 PTMA TSC22D3 FTH1 TAGAP UBC MS4A1 TMSB10 RPL36A PCBP1 LY9 ASH1L SARAF UBA52 ZFP36L1 NACA RABAC1 EIF4A3 HLA-DPB1 JUND POU2F2 RPS10 MZT2B PCBP2 RPL7 SESTD1 HLA-DQA2 RPL14 RPL13A POLD4 ECHDC1 PFDN5 RBM38 UQCRB ARHGDIB HLA-C PFDN1 HECTD1 IDI1 GNB5 TUBA1A SOCS3 SMAP2 DCAF7 LINC02397 SNHG8 IER2 HMGB1 TNFRSF13C ENO1 ACTG1 MT-ND2 COX7C HNRNPA1 BAX FCER2 RPL24 PKM SRGN PNPLA2 ARPC2 CHCHD10 DDX50 COX19 HVCN1 NCF1 CCNI FCMR HTT PTPRCAP GOLM2 JUNB CD79B SLC44A2 PFN1 TMEM258 MAX RPL22 REL SSR1 LAMTOR4 CD19 ORAI2 OAZ1 CHI3L2 KLF6 LIG1 LTB H2BC4 KLF2 HNRNPA2B1 ZNF106 KLF4.\n", + "Cell 2:\n", + "MALAT1 EEF1A1 RPS27 RPS12 RPL41 RPL13 RPLP1 RPL39 RPS14 TPT1 RPS19 RPL37 RPL30 RPL11 RPL32 RPS15A RPL10 RPS27A RPS18 RPS29 RPS8 RPS23 RPL34 RPL18A RPL28 RPS28 RPS3A TMSB4X RPS4X RPL19 RPS6 RPL26 RPS2 RPS21 RPL29 RPS25 RPS3 RPL21 RPS13 MT-ND3 RPLP2 RPL3 RPL12 B2M ACTB RPL35A MT-CO2 MT-CO1 RPL22 RPL18 MT-CO3 RPL7A RPL5 RPS9 RPL23A MT-ND4L RPSA RPL8 RPLP0 RPL17 RPL15 RPS24 RPS15 RPL37A TMSB10 MT-ATP8 MT-ATP6 RPL36 JUNB HLA-B FAU MT-CYB RPL14 RPL13A RPS16 EEF1B2 RPS7 FTH1 RPL6 RPL9 RPS5 MTRNR2L12 RPL10A RPL4 PTMA ACTG1 RPL24 NACA EEF1G S100A4 RPL38 RPL27 RPS10 TRBC1 SARAF EEF1D HLA-A TMA7 RPS11 ATP5MC2 PPIA PABPC1 MT-ND1 ZFP36 DDX5 SLC2A3 UBA52 PFN1 SLC25A3 UQCRB FYB1 HLA-E IFITM1 FLT3LG GAPDH SNHG29 ZFP36L2 VIM RPS20 NOSIP SH3BGRL3 IL32 RPL35 RPL23 EIF1 COX4I1 ATP5ME FTL SERF2 BTG1 ATP6V1G1 RACK1 CD3G CCR7 YBX1 EEF2 RAC2 PSME1 ARHGDIB CORO1A MT-ND5 MYL6 EIF3K GPR183 CD3D ITM2B SUMO2 TUBB GAS5 UXT HLA-C PCBP2 EIF3H ATP5F1A SOD1 PTPRCAP CD7 RP11-290D2 RPL31 FUS HINT1 PRKCQ-AS1 OST4 C12ORF57 H3-3A ACTR1A HSPA8 CCNH LITAF DNAJC8 GHITM RYK RPL36A STK4 CFL1 ATP5F1E TRBV6-1 RPL27A PSME2 TRAV12-1 LDHB NEDD8 KLF2 ARPC5 ARPC3 PCBP1 COMMD6 EVL TCF7 MSL3 ARL4D ZNF330 ANP32B LIMD2 CD55 TBCA ESYT1 NSMCE1 SNRPC DAD1.\n", + "Cell 3:\n", + "EEF1A1 MALAT1 B2M RPL41 RPS27 TMSB4X MT-ND3 RPS28 RPL30 HLA-B RPS15A MT-CYB DUSP1 RPL32 RPL39 RPL37 RPL28 RPL13 CD69 MT-CO1 RPL10 RPLP1 RPS3 TRBV5-1 RPS12 SLC2A3 HLA-C TPT1 RPS23 RPL26 RPS27A RPL34 FOS RPS18 RPL9 RPL35A RPS29 RPL11 MT-ND4L RPL19 RPS21 RPS15 MT-ATP8 RPL29 RPS6 MT-CO2 TMSB10 ACTG1 MT-CO3 RPS7 RPL12 TRAV14DV4 JUNB RPS2 ACTB RPS8 RPL8 RPS3A RPL18A HLA-E RPL3 RPS14 MT-ATP6 EIF1 RPL21 RPL14 RPL18 H3-3B MTRNR2L12 KLF6 EEF1D JUN MT-ND2 RPS19 MT-ND1 MT-ND4 RPL37A RPSA RPL15 RPL7A KLRB1 COX7C RPL36AL RPS4X RPL35 TSC22D3 RPS25 FAU RPS13 IL32 RPLP2 RPL5 ZFP36L2 HLA-A RPL36 HSP90AA1 DDIT4 EEF1G TCF7 HSP90AB1 SEPTIN1 RPS24 TUBA4A DNAJB1 PABPC1 RPLP0 BTG1 RPL24 RPS10 EIF5B CD5 DDX5 NEAT1 CYTIP ZFP36L1 UBB LAPTM5 RPS20 FTH1 CD3D RACK1 SRGN FTL IFITM1 BTF3 FXYD5 HNRNPH2 YWHAZ NACA SAP18 DNAJA1 PFN1 CD44 SRSF7 BTG2 RPL38 CFL1 EEF1B2 ICOS CTLA4 HNRNPA2B1 BAZ2A ARHGDIB WIPF1 PSMB8 HSPA1A SON SS18L2 RPL17 GAS5 ZNHIT1 RPL10A EVI2B RPS9 ERLEC1 PRR13 RBMX PFDN5 MT-ND5 PARP1 HLA-F RPL7 RPL23A RPS5 FCMR CMTM7 RPS16 PCBP2 SARAF FYB1 RAN CCNI CHCHD2 MYL6 RPL4 IFITM2 GAPDH RPL22 COX20 CD3E CD2 CCR4 COX14 MAGOH ARAP2 MRPL23 UFD1 LAT RPL6 VIM UBA52 CREM NPM1 SPN DAD1 OAZ1 TRBC2 DDX24 RBM39 EIF3F.\n", + "Cell 4:\n", + "EEF1A1 RPS27 RPL10 RPL13 RPS12 RPL30 MALAT1 RPLP1 RPL41 RPL32 MT-ND3 MT-CO2 RPS15A RPS28 RPS23 RPS3 RPL28 RPS27A RPS3A RPS8 RPL18 MTRNR2L12 RPL29 RPL19 RPS21 TPT1 B2M MT-CO3 RPL34 RPS4X RPL26 RPS19 RPS13 RPL11 RPS14 RPS18 RPL37 RPLP0 RPS2 RPL39 RPL12 RPL3 RPL14 RPL5 MT-ATP8 RPS25 RPL35A RPL21 RPS6 RPS15 RPS24 MT-CO1 RPS29 MT-ND4L TMSB4X RACK1 TMSB10 RPL6 RPL7A RPS9 RPL9 ACTB RPL22 RPL15 MT-CYB RPL8 PABPC1 RPL10A JUNB RPL36 FOS RPSA DNAJB1 TSC22D3 RPL37A RPL38 RPS5 MT-ATP6 VIM RPL18A PTMA RPLP2 EEF2 FAU NACA HLA-C RPL36A RPS16 EIF1 RPL23A NPM1 RPL27 RPL24 RPS7 RPL4 DUSP1 RPL35 RPL13A HLA-B UBA52 ACTG1 HNRNPA1 COX4I1 MT-ND2 EEF1G RPL17 BTG1 HNRNPDL EEF1D MT-ND1 PFN1 FTH1 CD69 KLF2 ATP5MC2 SELL PNRC1 BTF3 GAS5 ARHGDIB MT-ND4 SLC2A3 EEF1B2 SNHG29 HLA-A LTB H3-3A RPL23 FTL SRSF7 RPL31 FOSB LINC02446 TRBV6-1 IFITM2 PTGER4 PPP1R15A RPL36AL ZFP36 HCST EIF3E PTPRC SARAF CXCR4 RHOA SLC25A3 ZNF331 R3HDM2 EIF3G PFDN5 LDHB S100A6 CD48 ATP5F1E CD8A CD3E PRR13 HSPA8 RPL27A EIF3H TMA7 TCF7 LCP2 SNHG3 NR4A1 HNRNPA2B1 CD3D ATP5ME TAX1BP1 COX7C SNHG8 PPIA HLA-E PCED1B-AS1 TRAF3IP3 CD55 SLC9A3R1 MYL12A RPL7 SLC27A5 DUSP2 RPS26 H3-3B ST13 HLA-F TXNIP WDR1 PICALM LIMD2 MT-ND5 CD52 GYPC NFKBIA GZMM HSP90AA1 TSTD1 YBX1 PCBP2 CAPZB TOMM20.\n", + "Cell 5:\n", + "MTRNR2L12 RPS27 EEF1A1 RPL41 RPL13 RPS12 RPL10 RPL30 TMSB4X RPL32 MALAT1 RPLP1 JUNB RPS28 RPL39 RPL19 RPL34 RPL18A RPL28 RPS14 RPL11 RPS3A RPS15A MT-CO2 ACTB RPS23 RPL35A RPL37 TPT1 RPS18 MT-ND3 MT-CYB RPS4X RPS8 RPS3 RPL29 RPS21 RACK1 RPL12 RPS29 RPL3 RPS15 RPS2 RPS27A PTMA RPLP0 RPL7A RPL5 RPSA MT-ND4L B2M MT-ATP8 RPL26 RPS24 NACA ACTG1 MT-CO1 RPL15 RPL14 RPL23A RPS19 RPL9 FAU RPL36 RPS6 MT-CO3 RPLP2 RPS25 RPS13 RPS9 HLA-B RPS16 RPL18 RPL8 RPL6 RPS7 MT-ATP6 RPL17 IFITM1 RPS5 HLA-A RPL38 RPL7 RPL21 ZNF331 FTL RPL37A MT-ND4 MT-ND1 EIF1 FOS EEF2 RPL10A BTG1 FTH1 RPL31 SARAF NPM1 RPL4 DNAJB1 TRBV14 RPL36A RPL22 PTPRCAP TRBV6-6 CD37 HLA-C PABPC1 CYTIP LDHB ARHGDIB EEF1G PCBP2 MYL12A SNHG6 RPL27A RPL35 PPIA TMSB10 RPL27 ZFP36 NOP53 CD69 RBM39 BTF3 SUMO2 MT-ND2 GPSM3 SNHG29 HINT1 COMMD6 CCNI RPS17 ATP5F1E EEF1D CORO1A PFN1 HSPA8 DUSP2 HNRNPH1 PPP1R2 RAC2 PFDN5 CFL1 CAP1 HLA-E H3-3B STK17B MIF SSH2 SON GABARAP PNRC1 MYH9 RPL24 FAM177A1 COX4I1 HSPE1 EIF3K RHOA TOMM7 BTG2 RGS10 LEPROTL1 PTPRC SELL DDX39B FXYD5 ARPC1B TXNIP SRSF3 SNRPD2 TAF15 RIPOR2 ZFAS1 HNRNPUL1 MPG CD3E VAMP2 EEF1B2 SATB1 SLC25A6 GAPDH CYCS TRAM1 SLC25A3 MTRNR2L8 TMC8 PCBP1 RPS26 H3-3A ITM2B TMA7 SKP1 LSM4 EDF1 EIF5A GIMAP7 ARPC3 YWHAZ.\n", + ".\n", + "Abstract summary:\n" + ] + } + ], + "source": [ + "# Format prompts for both cell subsets\n", + "input_prompt = formatted_ds[10000]['model_input']\n", + "\n", + "print(\"--- Input Prompt ---\")\n", + "print(input_prompt)" + ] + }, + { + "cell_type": "markdown", + "id": "016d6924", + "metadata": {}, + "source": [ + "Finally, we will use our loaded C2S model to generate natural language summaries for each of our cell subsets." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "0c478051", + "metadata": {}, + "outputs": [], + "source": [ + "# Generate interpretation for the ileum cells\n", + "natural_language_interpretation = csmodel.generate_from_prompt(\n", + " model=model,\n", + " prompt=input_prompt,\n", + " do_sample=True,\n", + " max_num_tokens=1024,\n", + " temperature=0.7,\n", + " top_k=30,\n", + " top_p=0.9\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "c1cfe9cd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Interpretation for cells ---\n", + "The study used single-cell sequencing to analyze immune cells in 16 human tissues from 12 donors, generating a dataset of ~360,000 cells. They developed CellTypist, a machine learning tool for precise cell type annotation, and identified tissue-specific features and clonal architecture of T and B cells. This approach provides a foundation for identifying highly resolved immune cell types using a common reference dataset and antigen receptor sequencing..\n" + ] + } + ], + "source": [ + "print(\"--- Interpretation for cells ---\")\n", + "print(natural_language_interpretation)" + ] + }, + { + "cell_type": "markdown", + "id": "f1ae0d82", + "metadata": {}, + "source": [ + "The summary produced by the model correctly identified some details about the dataset it was sampled from, since this dataset (immune cells from Dominguez-Conde et al.) was a part of the C2S pretraining dataset. Sampling with different temperature and on different datasets can give different interpretations." + ] + }, + { + "cell_type": "markdown", + "id": "5e55401f", + "metadata": {}, + "source": [ + "# Conclusion\n", + "\n", + "In this tutorial, we have seen how a pretrained Cell2Sentence model can be used to generate natural language interpretations of single-cell datasets. By providing the model with a collection of cell sentences, it can produce a high-level summary of the biological information contained within those cells. This capability is a powerful tool for researchers to quickly gain insights into their data and understand the biological context of cell clusters in an accessible way.\n", + "\n", + "The ability to interpret complex single-cell data in natural language opens up new avenues for data exploration and hypothesis generation. As C2S models become more sophisticated, we can expect them to provide even more detailed and nuanced interpretations, further bridging the gap between computational analysis and biological understanding." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "75094e42", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "cell2sentence2", + "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": "3.8.20" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} +>>>>>>> 593fb74 (Peft feature implemented) From fccd40d47352664526873e2e95b63fcb5cfeffb0 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 11:29:50 +0000 Subject: [PATCH 02/19] Minor updates --- ..._10_perturbation_response_prediction.ipynb | 2954 ++++++++--------- 1 file changed, 1476 insertions(+), 1478 deletions(-) diff --git a/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb b/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb index c47ad79..008aef2 100644 --- a/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb +++ b/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb @@ -1,4 +1,3 @@ -<<<<<<< HEAD { "cells": [ { @@ -1474,1480 +1473,1479 @@ "nbformat": 4, "nbformat_minor": 5 } -======= -{ - "cells": [ - { - "cell_type": "markdown", - "id": "9981f4b0", - "metadata": {}, - "source": [ - "# Tutorial Notebook 10: Finetuning for Perturbation Response Prediction\n", - "\n", - "In this tutorial, we will demonstrate how to finetune a Cell2Sentence (C2S) model for perturbation response prediction tasks. This is a critical task in single-cell analysis, where the goal is to predict how a cell's gene expression profile changes in response to a specific perturbation (e.g., a genetic knockout or a drug treatment).\n", - "\n", - "We will treat this as a \"translation\" task in natural language: translating a cell (in cell sentence format) from its basal (control) state to its perturbed state, conditioned on the perturbation applied.\n", - "\n", - "At a high level, we will:\n", - "1. Load a public single-cell perturbation dataset.\n", - "2. Write a custom prompt template for perturbation prediction.\n", - "3. Subclass the `PromptFormatter` class to create pairs of control and perturbed cells.\n", - "4. Finetune a pretrained C2S-Scale model on this new task.\n", - "5. Generate a prediction with our new finetuned model to see it in action." - ] - }, - { - "cell_type": "markdown", - "id": "139d5b0b", - "metadata": {}, - "source": [ - "First, let's import the necessary libraries. We'll need standard data science libraries, single-cell analysis tools, and modules from the `cell2sentence` and `transformers` packages." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "f0bf13c5", - "metadata": {}, - "outputs": [], - "source": [ - "# Python built-in libraries\n", - "import os\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\" \n", - "os.environ[\"WORLD_SIZE\"] = \"1\"\n", - "\n", - "import pickle\n", - "import random\n", - "from datetime import datetime\n", - "from collections import Counter, defaultdict\n", - "\n", - "# Third-party libraries\n", - "from datasets import Dataset\n", - "import numpy as np\n", - "import torch\n", - "from transformers import TrainingArguments, AutoModelForCausalLM\n", - "from tqdm import tqdm\n", - "\n", - "# Single-cell libraries\n", - "import anndata\n", - "import scanpy as sc" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "cb07037d", - "metadata": {}, - "outputs": [], - "source": [ - "# Cell2Sentence imports\n", - "import cell2sentence as cs\n", - "from cell2sentence.prompt_formatter import get_cell_sentence_str, PromptFormatter" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "81ce734c", - "metadata": {}, - "outputs": [], - "source": [ - "SEED = 1234\n", - "random.seed(SEED)\n", - "np.random.seed(SEED)" - ] - }, - { - "cell_type": "markdown", - "id": "0f6047f8", - "metadata": {}, - "source": [ - "# Load Perturbation Data\n", - "\n", - "For this tutorial, you will need a single-cell dataset that includes both control and perturbed cells. The data should be in an `AnnData` object. Crucially, your `.obs` dataframe must contain:\n", - "- A column that distinguishes control cells from perturbed cells, e.g., `adata.obs['condition']`\n", - " - Values can be something like 'control' or 'non-targeting' for control cells, and 'perturbed' or the perturbation name for the perturbed cells\n", - "\n", - "For this example, we use a public genetic perturbation dataset of Jurkat cells (Nadig et al., 2025). To use your own dataset, replace `DATA_PATH` with the path to your preprocessed data file.\n", - "- Paper: https://www.nature.com/articles/s41588-025-02169-3\n", - "\n", - "Ensure your data is preprocessed and normalized (e.g., using log1p transformation) before proceeding." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "52754a57", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 21412 × 18080\n", - " obs: 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Replace this with the actual path to your dataset, if using a custom dataset\n", - "DATA_PATH = \"/home/sr2464/scratch/C2S_API_Testing/Data/jurkat.h5ad\"\n", - "adata = anndata.read_h5ad(DATA_PATH)\n", - "adata" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "590a4a9f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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batch_varcell_typetarget_genegene_idmitopercentUMI_count
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AAACCCAAGCACCAGA-42jurkat42jurkatEIF4BENSG000000630460.0376974828.0
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AAACCCAAGGGCCTCT-51jurkat51jurkatnon-targetingnon-targeting0.04761912642.0
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" - ], - "text/plain": [ - " batch_var cell_type target_gene gene_id \\\n", - "cell_barcode \n", - "AAACCCAAGCACCAGA-42 jurkat42 jurkat EIF4B ENSG00000063046 \n", - "AAACCCAAGCAGATAT-4 jurkat4 jurkat DAXX ENSG00000204209 \n", - "AAACCCAAGCTAGATA-2 jurkat2 jurkat METTL3 ENSG00000165819 \n", - "AAACCCAAGCTGGAGT-37 jurkat37 jurkat non-targeting non-targeting \n", - "AAACCCAAGGGCCTCT-51 jurkat51 jurkat non-targeting non-targeting \n", - "\n", - " mitopercent UMI_count \n", - "cell_barcode \n", - "AAACCCAAGCACCAGA-42 0.037697 4828.0 \n", - "AAACCCAAGCAGATAT-4 0.063256 9675.0 \n", - "AAACCCAAGCTAGATA-2 0.069885 16985.0 \n", - "AAACCCAAGCTGGAGT-37 0.055775 20475.0 \n", - "AAACCCAAGGGCCTCT-51 0.047619 12642.0 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.obs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "e07fcedb", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "69\n" - ] - } - ], - "source": [ - "target_gene_counter = Counter(adata.obs['target_gene'])\n", - "print(len(target_gene_counter))" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ab4e3458", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[('non-targeting', 12013),\n", - " ('TFAM', 2555),\n", - " ('EIF4B', 461),\n", - " ('JAZF1', 265),\n", - " ('HIRA', 233),\n", - " ('SMARCB1', 204),\n", - " ('TAF13', 200),\n", - " ('KDM1A', 195),\n", - " ('MBTPS1', 192),\n", - " ('LZTR1', 192),\n", - " ('METTL3', 177),\n", - " ('DNMT1', 177),\n", - " ('SDC1', 156),\n", - " ('TADA1', 144),\n", - " ('MED12', 143),\n", - " ('USF2', 141),\n", - " ('ARPC2', 140),\n", - " ('PTPN1', 136),\n", - " ('PHF10', 136),\n", - " ('NDUFB4', 133)]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "target_gene_counter.most_common(20)" - ] - }, - { - "cell_type": "markdown", - "id": "afec3e85", - "metadata": {}, - "source": [ - "This data contains both control cells (non-targeting) as well as cells under different genetic knockouts." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "38ebcf86", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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SAMD11
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" - ], - "text/plain": [ - "Empty DataFrame\n", - "Columns: []\n", - "Index: [SAMD11, NOC2L, KLHL17, PLEKHN1, PERM1]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.var.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "cc318b3f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "<21412x18080 sparse matrix of type ''\n", - "\twith 69336411 stored elements in Compressed Sparse Row format>" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.X" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "6239a8bc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034,\n", - " 1.6483034, 1.6483034, 1.6483034, 1.6483034], dtype=float32)" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# View a few nonzero values\n", - "adata.X.data[:10]" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "0e4b95d8", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "8.333305" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.X.max()" - ] - }, - { - "cell_type": "markdown", - "id": "005cef4b", - "metadata": {}, - "source": [ - "The expression is already preprocessed and log1p transformed. Typically, a log1p transform with base=10 would be used for Cell2Sentence training if we wish to convert generated cell sentences back to expression vectors, since log base=10 gives a better linear relationship between log rank and log expression in many single-cell datasets.\n", - "\n", - "For this tutorial, we will use this processed data as is, to train our model to generate target cell sentences." - ] - }, - { - "cell_type": "markdown", - "id": "a1c99514", - "metadata": {}, - "source": [ - "# Cell2Sentence Conversion\n", - "\n", - "Now, we will convert the gene expression data in our `AnnData` object into cell sentences. This process creates a Hugging Face Arrow dataset, which is used in our LLM training." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "e0ae0bdb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['batch_var',\n", - " 'cell_type',\n", - " 'target_gene',\n", - " 'gene_id',\n", - " 'mitopercent',\n", - " 'UMI_count']" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# We'll keep all relevant columns for our new task\n", - "adata_obs_cols_to_keep = adata.obs.columns.tolist()\n", - "adata_obs_cols_to_keep" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "91e60261", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 21412/21412 [00:11<00:00, 1899.14it/s]\n" - ] - }, - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['cell_name', 'cell_sentence', 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'],\n", - " num_rows: 21412\n", - "})" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Create Arrow dataset and vocabulary\n", - "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", - " adata=adata, \n", - " random_state=SEED, \n", - " sentence_delimiter=' ',\n", - " label_col_names=adata_obs_cols_to_keep\n", - ")\n", - "arrow_ds" - ] - }, - { - "cell_type": "markdown", - "id": "3efc581c", - "metadata": {}, - "source": [ - "# Custom Prompt Formatting for Perturbation Prediction\n", - "\n", - "This is the core of our tutorial. For this dataset, we have a single large pool of control cells (labeled 'non-targeting') and multiple groups of perturbed cells, each with a specific `target_gene`. Our goal is to create training pairs where each perturbed cell is matched with a randomly selected control cell. Note that for different perturbation applications, there may be better ways of pairing control and perturbed cells.\n", - "\n", - "We will define a custom prompt structure that frames our task for the LLM. The input will contain the **control cell sentence** and the **perturbation name**. The model's expected output (the response) will be the **perturbed cell sentence**.\n", - "\n", - "First, let's define our prompt templates." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "adceba43", - "metadata": {}, - "outputs": [], - "source": [ - "# The input provides the control cell and the perturbation, asking for the perturbed result.\n", - "custom_input_prompt_template = \"\"\"Given the following cell sentence of {num_genes} expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: {perturbation_name}.\n", - "Control cell sentence: {control_cell_sentence}.\n", - "\n", - "Perturbed cell sentence:\"\"\"\n", - "\n", - "# The answer is simply the target cell sentence.\n", - "answer_template = \"{perturbed_cell_sentence}.\"" - ] - }, - { - "cell_type": "markdown", - "id": "8afe106b", - "metadata": {}, - "source": [ - "To apply this template, we need to create pairs of (control cell, perturbed cell) for each perturbation. We'll create a custom `PerturbationPromptFormatter` by subclassing the base `PromptFormatter`.\n", - "\n", - "Our custom `format_hf_ds` function will:\n", - "1. First, iterate through the entire dataset to create a list of all control cell indices.\n", - "2. Simultaneously, it will group the indices of all perturbed cells into a dictionary, with the perturbation name (`target_gene`) as the key.\n", - "3. Then, it will iterate through each perturbation group and, for every perturbed cell, randomly select a control cell from the global pool to form a pair.\n", - "4. Finally, it will format these pairs into the input prompts and expected responses for the model." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "84fdc5ba", - "metadata": {}, - "outputs": [], - "source": [ - "from collections import defaultdict\n", - "\n", - "class PerturbationPromptFormatter(PromptFormatter):\n", - " def __init__(self,\n", - " task_name,\n", - " input_prompt,\n", - " answer_template,\n", - " top_k_genes, \n", - " perturbation_col='target_gene',\n", - " control_label='non-targeting'\n", - " ):\n", - " \"\"\"\n", - " Initializes the custom prompt formatter.\n", - "\n", - " Args:\n", - " task_name (str): The name for this task.\n", - " input_prompt (str): The template for the model's input.\n", - " answer_template (str): The template for the model's expected response.\n", - " top_k_genes (int): The number of top genes to include in the cell sentence.\n", - " perturbation_col (str): The column name in the dataset that contains perturbation info.\n", - " control_label (str): The label used to identify control cells in the perturbation_col.\n", - " \"\"\"\n", - " super().__init__()\n", - " self.task_name = task_name\n", - " self.input_prompt = input_prompt\n", - " self.answer_template = answer_template\n", - " self.top_k_genes = top_k_genes\n", - " self.perturbation_col = perturbation_col\n", - " self.control_label = control_label\n", - " assert top_k_genes > 0, \"'top_k_genes' must be an integer > 0\"\n", - "\n", - " def format_hf_ds(self, hf_ds):\n", - " \"\"\"\n", - " Custom formatting function for perturbation prediction. This function creates pairs of\n", - " (control, perturbed) cells by sampling from a global pool of control cells.\n", - " \"\"\"\n", - " model_inputs_list = []\n", - " responses_list = []\n", - " \n", - " # 1. Separate all cells into a global control pool and a dict of perturbed cells\n", - " control_indices = []\n", - " pert_to_indices = defaultdict(list)\n", - "\n", - " print(\"Grouping cells by perturbation and identifying global controls...\")\n", - " for i, sample in enumerate(hf_ds):\n", - " if sample[self.perturbation_col] == self.control_label:\n", - " control_indices.append(i)\n", - " else:\n", - " pert_to_indices[sample[self.perturbation_col]].append(i)\n", - " \n", - " assert len(control_indices) > 0, \"No control cells found. Cannot create pairs.\"\n", - " print(f\"Found {len(control_indices)} control cells.\")\n", - " print(f\"Found {len(pert_to_indices)} unique perturbations.\")\n", - "\n", - " # 2. Create prompt-response pairs by iterating through perturbed cells\n", - " print(\"Creating control-perturbed pairs...\")\n", - " for pert_name, perturbed_indices in tqdm(pert_to_indices.items()):\n", - " for perturbed_idx in perturbed_indices:\n", - " # Pair each perturbed cell with a random control cell from the global pool\n", - " control_idx = random.choice(control_indices)\n", - " \n", - " control_sample = hf_ds[control_idx]\n", - " perturbed_sample = hf_ds[perturbed_idx]\n", - "\n", - " # Format control cell sentence\n", - " control_sentence, num_genes_str = get_cell_sentence_str(\n", - " control_sample,\n", - " num_genes=self.top_k_genes\n", - " )\n", - " # Format perturbed cell sentence\n", - " perturbed_sentence, _ = get_cell_sentence_str(\n", - " perturbed_sample,\n", - " num_genes=self.top_k_genes\n", - " )\n", - "\n", - " # Format the model input string using the perturbation name\n", - " model_input_str = self.input_prompt.format(\n", - " num_genes=num_genes_str,\n", - " perturbation_name=pert_name,\n", - " control_cell_sentence=control_sentence\n", - " )\n", - " \n", - " # Format the response string\n", - " response_str = self.answer_template.format(\n", - " perturbed_cell_sentence=perturbed_sentence\n", - " )\n", - "\n", - " model_inputs_list.append(model_input_str)\n", - " responses_list.append(response_str)\n", - "\n", - " # Create the final Hugging Face Dataset\n", - " ds_split_dict = {\n", - " \"sample_type\": [self.task_name] * len(model_inputs_list),\n", - " \"model_input\": model_inputs_list,\n", - " \"response\": responses_list,\n", - " }\n", - " ds = Dataset.from_dict(ds_split_dict)\n", - " return ds" - ] - }, - { - "cell_type": "markdown", - "id": "e431c369", - "metadata": {}, - "source": [ - "Let's instantiate our custom formatter and test it on a small sample of our data to see the result." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "68228040", - "metadata": {}, - "outputs": [], - "source": [ - "task_name = \"perturbation_prediction\"\n", - "prompt_formatter = PerturbationPromptFormatter(\n", - " task_name=task_name,\n", - " input_prompt=custom_input_prompt_template,\n", - " answer_template=answer_template,\n", - " top_k_genes=200 # Using top 200 genes for this example. For real applications, ideal to use all nonzero expressed genes if possible.\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "51258c12", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Grouping cells by perturbation and identifying global controls...\n", - "Found 12013 control cells.\n", - "Found 68 unique perturbations.\n", - "Creating control-perturbed pairs...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 68/68 [00:03<00:00, 20.85it/s]\n" - ] - }, - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['sample_type', 'model_input', 'response'],\n", - " num_rows: 9399\n", - "})" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Format the dataset\n", - "formatted_ds = prompt_formatter.format_hf_ds(arrow_ds)\n", - "formatted_ds" - ] - }, - { - "cell_type": "markdown", - "id": "95e9668c", - "metadata": {}, - "source": [ - "Note that if you want to do a train/test split of the data, separating out a split of control cells and holdout perturbed cells / entire perturbations can be done before formatting." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "f8b0f343", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Formatted Sample ---\n", - "#----Model input:----#\n", - "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", - "Control cell sentence: MT-ATP6 MT-CO3 TMSB4X MT-ND4 MT-ND1 MT-CO2 ACTB MT-ND2 MT-ND3 MT-CYB RACK1 HSP90AB1 HSP90AA1 NME2 HSPD1 H2AFZ YBX1 ACTG1 FTH1 TUBA1B TUBB LDHB PFN1 NCL FTL PRDX1 EEF1B2 HIST1H4C BTF3 ADA CFL1 CHCHD2 SET ENO1 UBA52 H3F3A ARHGDIB EIF1 EEF1G PPP1R14B GSTP1 CALR HINT1 SERF2 HSPE1 XRCC5 TMSB10 STMN1 CD3D B2M EEF2 MT-ND6 PPIA HIST1H1D MIF H3F3B ANP32B HNRNPU UBC SERBP1 CDK6 EIF4A1 TYMS UQCRH PSMA7 HNRNPA2B1 SFPQ GPX4 HMGB2 PRRC2C SIVA1 FUS SUB1 LCP1 SLC25A3 SNRPB SRSF3 CSDE1 PCLAF EIF3G EIF3A MYL6 HES4 HMGN1 SLC25A5 COX4I1 MKI67 NDUFA13 HNRNPD PEBP1 PPP1CA GABARAP PRDX5 HNRNPA3 TIMM13 PKM POMP PCNA NUDC STOML2 GADD45GIP1 TMA7 PPA1 CORO1A HNRNPK ARPP19 UQCRB ATP5F1B SNRPD1 DDX5 ARPC3 ISG15 PSMA4 SEC61B COX8A PSMA1 FABP5 TMEM160 SNRPE PRPF40A MT-ND5 ODC1 COX6A1 SH3BGRL3 HMGA1 NUCKS1 COX7A2 ATP5MC2 NOP56 HNRNPC KTN1 SRSF7 SOX4 CLIC1 PSMD2 NDUFS6 ALYREF SUMO2 GUK1 SSBP1 YWHAQ BRD2 SRSF9 ERH TOMM6 PSMC5 CCT2 CCT4 IGFBP2 C1QBP ATP5F1E ARL6IP4 C12ORF57 SNU13 METTL5 CCNI ATP5MC1 CCT8 DDX46 TMEM208 JPT1 SPCS1 FDFT1 PA2G4 HNRNPR HIST1H1B CENPF SNRPF CCT3 ARPC1B COX6C DBI RBM3 PRKDC EIF3I C12ORF75 DIAPH1 EIF5 MARCKSL1 IFI16 EIF4G2 MT-ND4L PHB CCT6A ARPC5 NUCB2 LIME1 POLR2F NME1 PPM1G VIM MANF UBL5 COPS6 PSMB6 SRRM1 SUPT16H SRM SELENOH AP2M1.\n", - "\n", - "Perturbed cell sentence: \n", - "\n", - "#----Response:----#\n", - "MT-ATP6 MT-CO3 MT-CO2 TUBA1B HSP90B1 MT-CYB MT-ND4 ACTB TMSB4X HSP90AA1 HSP90AB1 CENPF MT-ND6 TRBC1 MT-ND2 HNRNPA2B1 PPIA H3F3A HSPD1 GSTP1 TUBB LDHB CHCHD2 SET MIF ADA RACK1 EEF1G EEF1B2 BTF3 CD3G NME2 NCL HSPA8 MT-ND1 XRCC5 EIF4A1 NUCKS1 CCNB1 PRDX1 EDF1 H2AFY RNASEH2C CDK6 FABP5 FTH1 HNRNPD COX4I1 KPNA2 CDC123 UBA52 B2M MKI67 SNRPB TPM4 ARPC5 HINT1 ITM2B CORO1A ATP5MC3 H2AFZ PMEPA1 MED28 ARHGDIB MYL12A YBX3 ASPM H2AFX ATP5PF RBM3 SLC25A5 HNRNPU ZNRF1 PFN1 MYO7B RNF213 ACTG1 YBX1 C4ORF48 HSPA5 ITM2A SRSF2 KHDRBS1 EIF2S3 DDX39A SFPQ TECR CCT2 HSPE1 SMC4 CANX DDX5 CSDE1 ATP5F1D TCF12 C1QBP CD3D FYB1 MT-ND3 TMBIM6 SERF2 NKTR CYC1 NDUFA4 DIAPH1 PALM2-AKAP2 FTL MT-ND5 SOX4 H3F3B LEF1 GTF3A GABARAP XRN2 LSM4 CLIC1 NIPBL CHORDC1 STMN1 SIX6 PGK1 BLOC1S6 UBE2I HMGB2 IRF1 CD3E SRRM1 NDUFA7 CFL1 KNL1 GUK1 NSA2 PRPF8 IFI16 SNRPE RNF220 EIF4G2 SETX STT3B RUFY1 XRCC6 NAE1 PNN NOP10 IK SRP19 SUB1 MSI2 TXNL4A PFDN5 SRM PCBP2 NCAPG DDX3X VPS26B TCOF1 JPT1 EIF1 MAD2L1 PSMD2 CUL4A MARCKSL1 NUCB2 NDUFA2 ATP5MG TUBA1A LBR CDK1 MAP4K4 COPS5 NOP58 SAMD1 ENO1 PFDN2 MTCH2 KMT5A TMEM160 CWC22 SOD1 SCAF11 NME1 ATM CDC20 SRSF11 TBL1XR1 RSL24D1 NDUFV1 SRSF7 BAG1 CCT6A ZEB1 ATP6V1F UQCRH CBFA2T3 FBL SRSF10 C12ORF10 VIRMA DUSP2 CCT3.\n" - ] - } - ], - "source": [ - "# Inspect a formatted sample\n", - "print(\"--- Formatted Sample ---\")\n", - "print(\"#----Model input:----#\")\n", - "print(formatted_ds[0][\"model_input\"], \"\\n\")\n", - "print(\"#----Response:----#\")\n", - "print(formatted_ds[0][\"response\"])" - ] - }, - { - "cell_type": "markdown", - "id": "c18db332", - "metadata": {}, - "source": [ - "Now that our custom formatter is ready, we'll wrap our original `arrow_ds` in a `CSData` object. The `finetune` function will use this object and our custom formatter to prepare the data for training." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "28ab6da2", - "metadata": {}, - "outputs": [], - "source": [ - "# Save directory for Huggingface dataset\n", - "c2s_save_dir = \"/home/sr2464/scratch/C2S_API_Testing/Data/perturbation_tutorial/perturbation_tutorial\"\n", - "c2s_save_name = \"jurkat_perturbation_c2s\"" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "fa776a5f", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "148d9b57e6d94845a51fa39c55e9846e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Saving the dataset (0/1 shards): 0%| | 0/21412 [00:00" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Tracking run with wandb version 0.16.6" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Run data is saved locally in /home/sr2464/Desktop/cell2sentence/tutorials/wandb/run-20251014_233441-fa2rexvg" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Syncing run /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction to Weights & Biases (docs)
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - " View project at https://wandb.ai/syed-a-rizvi/huggingface" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - " View run at https://wandb.ai/syed-a-rizvi/huggingface/runs/fa2rexvg" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
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StepTraining LossValidation Loss

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Finetuning completed. Updated model saved to disk at: /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction\n" - ] - } - ], - "source": [ - "csmodel.fine_tune(\n", - " csdata=csdata,\n", - " task=task_name,\n", - " train_args=train_args,\n", - " loss_on_response_only=True, # We only want to calculate loss on the predicted sentence\n", - " top_k_genes=200, # Use top 200 genes for this example, normally would use full cell sentence (all nonzero expressed genes) if possible\n", - " prompt_formatter=prompt_formatter # Pass in our custom prompt formatter\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "7de08f82", - "metadata": {}, - "source": [ - "# Generate Predictions with the Finetuned Model\n", - "\n", - "After finetuning, let's load our new model and use it to predict the response to a perturbation for a cell from our test set." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "89474061", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction/checkpoint-500'" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "final_ckpt_path = os.path.join(output_dir, \"checkpoint-500\")\n", - "final_ckpt_path" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "38d63e84", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial'" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "save_dir" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "ebff900c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using device: cuda\n" - ] - } - ], - "source": [ - "# Load the finetuned model (it's automatically saved to csmodel.model_name_or_path)\n", - "finetuned_model = cs.CSModel(\n", - " model_name_or_path=final_ckpt_path, # Path is updated after finetuning\n", - " save_dir=save_dir,\n", - " save_name=\"perturbation_predictor_finetuned_final\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "ca22f14f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/perturbation_predictor_finetuned_final'" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "finetuned_model.save_path" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "cf85b83c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'cuda'" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", - "device" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "7c36e4b1", - "metadata": {}, - "outputs": [], - "source": [ - "final_model = AutoModelForCausalLM.from_pretrained(\n", - " finetuned_model.save_path,\n", - " cache_dir=os.path.join(csmodel.save_dir, \".cache\"),\n", - " trust_remote_code=True\n", - ").to(device)" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "c828d229", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys(['train', 'val', 'test'])" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Load dataset split done in finetune() function, saved to output directory\n", - "with open(os.path.join(output_dir, 'data_split_indices_dict.pkl'), 'rb') as f:\n", - " data_split_indices_dict = pickle.load(f)\n", - "\n", - "data_split_indices_dict.keys()" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "54a9c647", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[7, 29, 33, 35, 51, 54, 65, 70, 115, 116]" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Print a few indices of test samples\n", - "data_split_indices_dict['test'][:10]" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "6a54bcda", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['sample_type', 'model_input', 'response'],\n", - " num_rows: 10\n", - "})" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Select a few unseen samples\n", - "formatted_test_ds = formatted_ds.select(data_split_indices_dict['test'][:10])\n", - "formatted_test_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "1feda129", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Inference Prompt ---\n", - "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", - "Control cell sentence: ACTB MT-ATP6 MT-CO3 MT-CO2 TMSB4X TUBA1B MT-ND4 HSP90AA1 HIST1H4C TMSB10 MT-CYB ACTG1 TUBB RACK1 PFN1 H3F3A ARHGDIB YBX1 MT-ND1 CFL1 H2AFZ B2M FTH1 HSP90AB1 CENPF UBA52 MIF MT-ND3 LDHB NCL PPIA SERF2 HNRNPA2B1 EEF1B2 CDK6 PSMA7 HSPD1 TOP2A KPNA2 GSTP1 BTF3 MT-ND2 CD3D SET CORO1A UBB ANP32B HNRNPU STMN1 EIF4A1 CCT3 EEF1G EEF2 SOX4 EIF1 BANF1 HNRNPD ADA COX4I1 MKI67 COX6C SUMO2 LCP1 SLC25A3 PKM CHCHD2 HINT1 OAZ1 NDUFS6 ENO1 TUBB4B HMGB2 MACF1 NME1 LSM4 SELENOH HSPE1 ERH NUCKS1 HMGN1 DDX5 NDUFB10 HIST1H1E GPX4 NDUFA13 GTF3A MT-ND6 PTGES3 ARL6IP1 RBMX PGK1 CTCF ATP5MC3 PSMB2 SLC25A5 PRDX5 COX7C SPTBN1 BPTF ANXA1 UBE2C PRDX1 SRSF10 NDUFA12 SFPQ EIF3G TOMM22 SIVA1 PHB2 CCT2 PA2G4 PCBP2 SUB1 CCT6A RHOA ASPM YWHAE ATP5MC1 XRCC5 SMC4 SRSF3 YBX3 HNRNPAB ATP5F1B CSDE1 SNRPB IFI16 SNRPD1 PAFAH1B3 MSN XRCC6 COX6A1 COX8A ATP5F1E ALYREF CBX3 MYL6 EIF3E RBM39 RAC1 UBE2D2 C1QBP KHDRBS1 CCT4 JPT1 RAD21 NME2 PSME2 SEPTIN7 SNU13 CKLF NMRAL1 NOP53 EIF3I EIF3D SAP18 SON HTATSF1 PSMA3 SEC61B AIP RBM8A C11ORF58 PRRC2C OSTC NDUFAB1 NDUFA4 SELENOW HNRNPA3 SRSF7 H3F3B TOMM20 SRSF9 HNRNPK CCT8 ARPC2 ATP5F1A ATP5F1C PHB EIF4B NUCB2 SSBP1 CD3G TMEM50A HNRNPM BUB3 SRSF2 PSMC5 KDM5A SNRNP25 PAK2 MYL12A NIFK SNRPF SLC25A6 KIF14 PRMT1 MTDH SRRM2 ATP5PF.\n", - "\n", - "Perturbed cell sentence:\n" - ] - } - ], - "source": [ - "# Select a sample from the test set for inference\n", - "sample_idx = 0\n", - "inference_prompt = formatted_test_ds[sample_idx]['model_input']\n", - "ground_truth_response = formatted_test_ds[sample_idx]['response']\n", - "\n", - "print(\"--- Inference Prompt ---\")\n", - "print(inference_prompt)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "96d8dd95", - "metadata": {}, - "outputs": [], - "source": [ - "# Generate the prediction\n", - "predicted_response = finetuned_model.generate_from_prompt(\n", - " model=final_model,\n", - " prompt=inference_prompt,\n", - " max_num_tokens=800 # max number of tokens to generate, ~4 tokens per gene\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "c807b03c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--- Ground Truth Perturbed Cell ---\n", - "MT-ATP6 MT-CO3 MT-CO2 MT-ND4 MT-CYB MT-ND1 MT-ND2 ACTB HSP90AA1 TMSB4X YBX1 EEF1B2 MT-ND3 RACK1 HSP90AB1 EEF1G MIF NME2 HIST1H4C TUBA1B NCL TUBB ADA ENO1 STMN1 H2AFZ PFN1 H3F3A CFL1 LDHB HINT1 HSPD1 C1QBP HSPE1 UBA52 SERF2 ACTG1 PPIA B2M CALR HNRNPA2B1 ARHGDIB GSTP1 SET MT-ND5 BTF3 CCT2 CHCHD2 NUCB2 XRCC5 PGK1 CD3D HNRNPU SUMO2 PPP1R14B HNRNPD UQCRH FDPS ALYREF SIVA1 DNAJA1 SLC25A6 ARPC2 FTL TYMS DUT COX4I1 SNRPB DDX5 PRKDC SLC25A3 PSMA7 CD3G SLC25A5 UBC ATP5F1E MYL6 ATP5F1B CCT6A PCLAF CDK6 H3F3B EIF4A1 EEF2 HMGB2 GUK1 THRAP3 HNRNPDL SERBP1 FABP5 EIF2S2 NUCKS1 HNRNPA3 HMGN1 COX7C SFPQ NDUFA13 HSPA8 OAZ1 MARCKSL1 DEK SELENOH FTH1 SRM SNRPF EIF1 DYNLL1 XRCC6 MT-ND6 RSL1D1 ANP32B EIF3E PSMA3 NDUFS5 ERH ATP5MC3 ARPC3 GLUL YBX3 FUS SNRPD1 YWHAB ATP5MC1 PRDX1 PSMA4 SOX4 NDUFAB1 PPA1 EIF5 NUDC STOML2 NME4 SRSF7 MZB1 H1FX NOP56 TPM4 NME1 NASP EIF3I ATP6V1F SF3B2 TRIR CCNI ARPC1B COX6C SLIRP SNRPC BRK1 ARPC5 ATP5MF SRSF3 CD7 HNRNPR GNAI2 CARHSP1 PPIG ATP5MG PTGES3 PFDN2 SSBP1 C9ORF16 PAICS GPX4 UBB C12ORF57 HIST1H1B ANP32A PRDX5 APRT PKM PFDN5 NHP2 SUB1 CORO1A LSM2 HNRNPC RRM2 PNN EPRS SNRPA1 HSP90B1 MCM3 CCT8 PRRC2C SKP1 RNASEH2B CIAO2B PRMT1 RAC1 SRRT HNRNPF VDAC3 ISG15 NAA10 RRP1B CCT3 MYL12B NAE1 EMC6.\n", - "\n", - "--- Predicted Perturbed Cell ---\n", - "MT-ATP6 MT-CO3 MT-CO2 MT-CYB MT-ND4 TMSB4X ACTB MT-ND1 MT-ND3 MT-ND2 HSP90AA1 HSP90AB1 RACK1 YBX1 MIF TUBA1B H3F3A H2AFZ HSPD1 NCL EEF1B2 FTH1 HNRNPA2B1 EEF1G LDHB HINT1 CHCHD2 NME2 BTF3 UBA52 EIF4A1 ACTG1 STMN1 TUBB PFN1 CFL1 EIF1 PPIA GSTP1 PRDX1 HNRNPU SET B2M HSPE1 ARHGDIB ENO1 SERF2 CD3D MT-ND5 HNRNPD HNRNPC C1QBP FTL SLC25A3 COX4I1 SLC25A5 ATP5MC3 SRSF3 PPP1R14B SIVA1 HNRNPA3 CCT3 ANP32B SFPQ EIF3E HNRNPR PSMB1 ATP5MC2 CCT6A PSMB2 NUCB2 PSMA7 PSMB3 SNRPD1 PSMB6 ATP5F1B PPA1 UQCRH SNRPB NME1 SRSF7 PSMB7 NDUFS5 HNRNPK OAZ1 PFDN5 TMSB10 ADA GTF3A ATP5F1E SERBP1 COX7C NDUFA13 PSMB5 CCT2 ATP5F1D GUK1 EIF3A NDUFB10 FABP5 PSMB3 NDUFA4 ATP5F1A NUDC POMP HNRNPDL UBB PSMB6 NDUFS6 COX6A1 SRSF2 EIF3M SNRPE PSMA4 PSMD7 GADD45GIP1 ATP5MG PRMT1 NOP53 PSMD2 UQCRB YWHAE HNRNPM PSMD1 NDUFB11 EIF3H TOMM6 PSMD11 PSMC5 SRSF9 PSMC3 NDUFA11 NOP56 EIF3I EIF3G ATP5PO SNRPF RBM8A PSMD4 TOMM22 RTRAF SRSF11 PSMC1 NDUFAB1 HNRNPAB PSMD13 PSMA2 NUCKS1 UQCR10 RSL1D1 PSMB4 TOMM5 GYPC PFDN2 PSMA3 NDUFA12 NOP10 EIF4G2 SELENOH UBE2I RBM3 PSMD12 PSMC4 HNRNPD SRM PSMB8 EIF3L RBMX PSMD6 SLC25A6 TOMM20 UBE2L3 PSMB5 RBM25 EIF3D TMA7 PNN RBM39 UQCR11 GTF3C6 PPP1CA EIF2S2 PSMC2 NUDT8 PSMD11 RBM8B RBM3B TOMM40 RAC1 TUFM EIF4B PSMB7 RSL24D1 GTF2A2 NOL7 PSMD12.\n" - ] - } - ], - "source": [ - "print(\"\\n--- Ground Truth Perturbed Cell ---\")\n", - "print(ground_truth_response)\n", - "print(\"\\n--- Predicted Perturbed Cell ---\")\n", - "print(predicted_response)" - ] - }, - { - "cell_type": "markdown", - "id": "ce20628b", - "metadata": {}, - "source": [ - "# Conclusion\n", - "\n", - "In this tutorial, you learned how to finetune a Cell2Sentence model for a custom task: perturbation response prediction. By creating a `PerturbationPromptFormatter`, we were able to structure our data into control-perturbation-response triplets, enabling the model to learn the complex transcriptional changes that occur upon perturbation.\n", - "\n", - "This approach is highly flexible and can be adapted to various experimental designs. The finetuned model can now be used for in-silico experiments, such as virtual screening of genetic perturbations or predicting the effect of new compounds, significantly accelerating the pace of biological discovery." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2f1296f4", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "cell2sentence2", - "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": "3.8.20" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} ->>>>>>> 593fb74 (Peft feature implemented) + +{ + "cells": [ + { + "cell_type": "markdown", + "id": "9981f4b0", + "metadata": {}, + "source": [ + "# Tutorial Notebook 10: Finetuning for Perturbation Response Prediction\n", + "\n", + "In this tutorial, we will demonstrate how to finetune a Cell2Sentence (C2S) model for perturbation response prediction tasks. This is a critical task in single-cell analysis, where the goal is to predict how a cell's gene expression profile changes in response to a specific perturbation (e.g., a genetic knockout or a drug treatment).\n", + "\n", + "We will treat this as a \"translation\" task in natural language: translating a cell (in cell sentence format) from its basal (control) state to its perturbed state, conditioned on the perturbation applied.\n", + "\n", + "At a high level, we will:\n", + "1. Load a public single-cell perturbation dataset.\n", + "2. Write a custom prompt template for perturbation prediction.\n", + "3. Subclass the `PromptFormatter` class to create pairs of control and perturbed cells.\n", + "4. Finetune a pretrained C2S-Scale model on this new task.\n", + "5. Generate a prediction with our new finetuned model to see it in action." + ] + }, + { + "cell_type": "markdown", + "id": "139d5b0b", + "metadata": {}, + "source": [ + "First, let's import the necessary libraries. We'll need standard data science libraries, single-cell analysis tools, and modules from the `cell2sentence` and `transformers` packages." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f0bf13c5", + "metadata": {}, + "outputs": [], + "source": [ + "# Python built-in libraries\n", + "import os\n", + "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\" \n", + "os.environ[\"WORLD_SIZE\"] = \"1\"\n", + "\n", + "import pickle\n", + "import random\n", + "from datetime import datetime\n", + "from collections import Counter, defaultdict\n", + "\n", + "# Third-party libraries\n", + "from datasets import Dataset\n", + "import numpy as np\n", + "import torch\n", + "from transformers import TrainingArguments, AutoModelForCausalLM\n", + "from tqdm import tqdm\n", + "\n", + "# Single-cell libraries\n", + "import anndata\n", + "import scanpy as sc" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "cb07037d", + "metadata": {}, + "outputs": [], + "source": [ + "# Cell2Sentence imports\n", + "import cell2sentence as cs\n", + "from cell2sentence.prompt_formatter import get_cell_sentence_str, PromptFormatter" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "81ce734c", + "metadata": {}, + "outputs": [], + "source": [ + "SEED = 1234\n", + "random.seed(SEED)\n", + "np.random.seed(SEED)" + ] + }, + { + "cell_type": "markdown", + "id": "0f6047f8", + "metadata": {}, + "source": [ + "# Load Perturbation Data\n", + "\n", + "For this tutorial, you will need a single-cell dataset that includes both control and perturbed cells. The data should be in an `AnnData` object. Crucially, your `.obs` dataframe must contain:\n", + "- A column that distinguishes control cells from perturbed cells, e.g., `adata.obs['condition']`\n", + " - Values can be something like 'control' or 'non-targeting' for control cells, and 'perturbed' or the perturbation name for the perturbed cells\n", + "\n", + "For this example, we use a public genetic perturbation dataset of Jurkat cells (Nadig et al., 2025). To use your own dataset, replace `DATA_PATH` with the path to your preprocessed data file.\n", + "- Paper: https://www.nature.com/articles/s41588-025-02169-3\n", + "\n", + "Ensure your data is preprocessed and normalized (e.g., using log1p transformation) before proceeding." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "52754a57", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AnnData object with n_obs × n_vars = 21412 × 18080\n", + " obs: 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Replace this with the actual path to your dataset, if using a custom dataset\n", + "DATA_PATH = \"/home/sr2464/scratch/C2S_API_Testing/Data/jurkat.h5ad\"\n", + "adata = anndata.read_h5ad(DATA_PATH)\n", + "adata" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "590a4a9f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

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batch_varcell_typetarget_genegene_idmitopercentUMI_count
cell_barcode
AAACCCAAGCACCAGA-42jurkat42jurkatEIF4BENSG000000630460.0376974828.0
AAACCCAAGCAGATAT-4jurkat4jurkatDAXXENSG000002042090.0632569675.0
AAACCCAAGCTAGATA-2jurkat2jurkatMETTL3ENSG000001658190.06988516985.0
AAACCCAAGCTGGAGT-37jurkat37jurkatnon-targetingnon-targeting0.05577520475.0
AAACCCAAGGGCCTCT-51jurkat51jurkatnon-targetingnon-targeting0.04761912642.0
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" + ], + "text/plain": [ + " batch_var cell_type target_gene gene_id \\\n", + "cell_barcode \n", + "AAACCCAAGCACCAGA-42 jurkat42 jurkat EIF4B ENSG00000063046 \n", + "AAACCCAAGCAGATAT-4 jurkat4 jurkat DAXX ENSG00000204209 \n", + "AAACCCAAGCTAGATA-2 jurkat2 jurkat METTL3 ENSG00000165819 \n", + "AAACCCAAGCTGGAGT-37 jurkat37 jurkat non-targeting non-targeting \n", + "AAACCCAAGGGCCTCT-51 jurkat51 jurkat non-targeting non-targeting \n", + "\n", + " mitopercent UMI_count \n", + "cell_barcode \n", + "AAACCCAAGCACCAGA-42 0.037697 4828.0 \n", + "AAACCCAAGCAGATAT-4 0.063256 9675.0 \n", + "AAACCCAAGCTAGATA-2 0.069885 16985.0 \n", + "AAACCCAAGCTGGAGT-37 0.055775 20475.0 \n", + "AAACCCAAGGGCCTCT-51 0.047619 12642.0 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.obs.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e07fcedb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "69\n" + ] + } + ], + "source": [ + "target_gene_counter = Counter(adata.obs['target_gene'])\n", + "print(len(target_gene_counter))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "ab4e3458", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[('non-targeting', 12013),\n", + " ('TFAM', 2555),\n", + " ('EIF4B', 461),\n", + " ('JAZF1', 265),\n", + " ('HIRA', 233),\n", + " ('SMARCB1', 204),\n", + " ('TAF13', 200),\n", + " ('KDM1A', 195),\n", + " ('MBTPS1', 192),\n", + " ('LZTR1', 192),\n", + " ('METTL3', 177),\n", + " ('DNMT1', 177),\n", + " ('SDC1', 156),\n", + " ('TADA1', 144),\n", + " ('MED12', 143),\n", + " ('USF2', 141),\n", + " ('ARPC2', 140),\n", + " ('PTPN1', 136),\n", + " ('PHF10', 136),\n", + " ('NDUFB4', 133)]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "target_gene_counter.most_common(20)" + ] + }, + { + "cell_type": "markdown", + "id": "afec3e85", + "metadata": {}, + "source": [ + "This data contains both control cells (non-targeting) as well as cells under different genetic knockouts." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "38ebcf86", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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SAMD11
NOC2L
KLHL17
PLEKHN1
PERM1
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" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: []\n", + "Index: [SAMD11, NOC2L, KLHL17, PLEKHN1, PERM1]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.var.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "cc318b3f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<21412x18080 sparse matrix of type ''\n", + "\twith 69336411 stored elements in Compressed Sparse Row format>" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.X" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "6239a8bc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034,\n", + " 1.6483034, 1.6483034, 1.6483034, 1.6483034], dtype=float32)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# View a few nonzero values\n", + "adata.X.data[:10]" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "0e4b95d8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "8.333305" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adata.X.max()" + ] + }, + { + "cell_type": "markdown", + "id": "005cef4b", + "metadata": {}, + "source": [ + "The expression is already preprocessed and log1p transformed. Typically, a log1p transform with base=10 would be used for Cell2Sentence training if we wish to convert generated cell sentences back to expression vectors, since log base=10 gives a better linear relationship between log rank and log expression in many single-cell datasets.\n", + "\n", + "For this tutorial, we will use this processed data as is, to train our model to generate target cell sentences." + ] + }, + { + "cell_type": "markdown", + "id": "a1c99514", + "metadata": {}, + "source": [ + "# Cell2Sentence Conversion\n", + "\n", + "Now, we will convert the gene expression data in our `AnnData` object into cell sentences. This process creates a Hugging Face Arrow dataset, which is used in our LLM training." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "e0ae0bdb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['batch_var',\n", + " 'cell_type',\n", + " 'target_gene',\n", + " 'gene_id',\n", + " 'mitopercent',\n", + " 'UMI_count']" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# We'll keep all relevant columns for our new task\n", + "adata_obs_cols_to_keep = adata.obs.columns.tolist()\n", + "adata_obs_cols_to_keep" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "91e60261", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 21412/21412 [00:11<00:00, 1899.14it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['cell_name', 'cell_sentence', 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'],\n", + " num_rows: 21412\n", + "})" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Create Arrow dataset and vocabulary\n", + "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", + " adata=adata, \n", + " random_state=SEED, \n", + " sentence_delimiter=' ',\n", + " label_col_names=adata_obs_cols_to_keep\n", + ")\n", + "arrow_ds" + ] + }, + { + "cell_type": "markdown", + "id": "3efc581c", + "metadata": {}, + "source": [ + "# Custom Prompt Formatting for Perturbation Prediction\n", + "\n", + "This is the core of our tutorial. For this dataset, we have a single large pool of control cells (labeled 'non-targeting') and multiple groups of perturbed cells, each with a specific `target_gene`. Our goal is to create training pairs where each perturbed cell is matched with a randomly selected control cell. Note that for different perturbation applications, there may be better ways of pairing control and perturbed cells.\n", + "\n", + "We will define a custom prompt structure that frames our task for the LLM. The input will contain the **control cell sentence** and the **perturbation name**. The model's expected output (the response) will be the **perturbed cell sentence**.\n", + "\n", + "First, let's define our prompt templates." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "adceba43", + "metadata": {}, + "outputs": [], + "source": [ + "# The input provides the control cell and the perturbation, asking for the perturbed result.\n", + "custom_input_prompt_template = \"\"\"Given the following cell sentence of {num_genes} expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: {perturbation_name}.\n", + "Control cell sentence: {control_cell_sentence}.\n", + "\n", + "Perturbed cell sentence:\"\"\"\n", + "\n", + "# The answer is simply the target cell sentence.\n", + "answer_template = \"{perturbed_cell_sentence}.\"" + ] + }, + { + "cell_type": "markdown", + "id": "8afe106b", + "metadata": {}, + "source": [ + "To apply this template, we need to create pairs of (control cell, perturbed cell) for each perturbation. We'll create a custom `PerturbationPromptFormatter` by subclassing the base `PromptFormatter`.\n", + "\n", + "Our custom `format_hf_ds` function will:\n", + "1. First, iterate through the entire dataset to create a list of all control cell indices.\n", + "2. Simultaneously, it will group the indices of all perturbed cells into a dictionary, with the perturbation name (`target_gene`) as the key.\n", + "3. Then, it will iterate through each perturbation group and, for every perturbed cell, randomly select a control cell from the global pool to form a pair.\n", + "4. Finally, it will format these pairs into the input prompts and expected responses for the model." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "84fdc5ba", + "metadata": {}, + "outputs": [], + "source": [ + "from collections import defaultdict\n", + "\n", + "class PerturbationPromptFormatter(PromptFormatter):\n", + " def __init__(self,\n", + " task_name,\n", + " input_prompt,\n", + " answer_template,\n", + " top_k_genes, \n", + " perturbation_col='target_gene',\n", + " control_label='non-targeting'\n", + " ):\n", + " \"\"\"\n", + " Initializes the custom prompt formatter.\n", + "\n", + " Args:\n", + " task_name (str): The name for this task.\n", + " input_prompt (str): The template for the model's input.\n", + " answer_template (str): The template for the model's expected response.\n", + " top_k_genes (int): The number of top genes to include in the cell sentence.\n", + " perturbation_col (str): The column name in the dataset that contains perturbation info.\n", + " control_label (str): The label used to identify control cells in the perturbation_col.\n", + " \"\"\"\n", + " super().__init__()\n", + " self.task_name = task_name\n", + " self.input_prompt = input_prompt\n", + " self.answer_template = answer_template\n", + " self.top_k_genes = top_k_genes\n", + " self.perturbation_col = perturbation_col\n", + " self.control_label = control_label\n", + " assert top_k_genes > 0, \"'top_k_genes' must be an integer > 0\"\n", + "\n", + " def format_hf_ds(self, hf_ds):\n", + " \"\"\"\n", + " Custom formatting function for perturbation prediction. This function creates pairs of\n", + " (control, perturbed) cells by sampling from a global pool of control cells.\n", + " \"\"\"\n", + " model_inputs_list = []\n", + " responses_list = []\n", + " \n", + " # 1. Separate all cells into a global control pool and a dict of perturbed cells\n", + " control_indices = []\n", + " pert_to_indices = defaultdict(list)\n", + "\n", + " print(\"Grouping cells by perturbation and identifying global controls...\")\n", + " for i, sample in enumerate(hf_ds):\n", + " if sample[self.perturbation_col] == self.control_label:\n", + " control_indices.append(i)\n", + " else:\n", + " pert_to_indices[sample[self.perturbation_col]].append(i)\n", + " \n", + " assert len(control_indices) > 0, \"No control cells found. Cannot create pairs.\"\n", + " print(f\"Found {len(control_indices)} control cells.\")\n", + " print(f\"Found {len(pert_to_indices)} unique perturbations.\")\n", + "\n", + " # 2. Create prompt-response pairs by iterating through perturbed cells\n", + " print(\"Creating control-perturbed pairs...\")\n", + " for pert_name, perturbed_indices in tqdm(pert_to_indices.items()):\n", + " for perturbed_idx in perturbed_indices:\n", + " # Pair each perturbed cell with a random control cell from the global pool\n", + " control_idx = random.choice(control_indices)\n", + " \n", + " control_sample = hf_ds[control_idx]\n", + " perturbed_sample = hf_ds[perturbed_idx]\n", + "\n", + " # Format control cell sentence\n", + " control_sentence, num_genes_str = get_cell_sentence_str(\n", + " control_sample,\n", + " num_genes=self.top_k_genes\n", + " )\n", + " # Format perturbed cell sentence\n", + " perturbed_sentence, _ = get_cell_sentence_str(\n", + " perturbed_sample,\n", + " num_genes=self.top_k_genes\n", + " )\n", + "\n", + " # Format the model input string using the perturbation name\n", + " model_input_str = self.input_prompt.format(\n", + " num_genes=num_genes_str,\n", + " perturbation_name=pert_name,\n", + " control_cell_sentence=control_sentence\n", + " )\n", + " \n", + " # Format the response string\n", + " response_str = self.answer_template.format(\n", + " perturbed_cell_sentence=perturbed_sentence\n", + " )\n", + "\n", + " model_inputs_list.append(model_input_str)\n", + " responses_list.append(response_str)\n", + "\n", + " # Create the final Hugging Face Dataset\n", + " ds_split_dict = {\n", + " \"sample_type\": [self.task_name] * len(model_inputs_list),\n", + " \"model_input\": model_inputs_list,\n", + " \"response\": responses_list,\n", + " }\n", + " ds = Dataset.from_dict(ds_split_dict)\n", + " return ds" + ] + }, + { + "cell_type": "markdown", + "id": "e431c369", + "metadata": {}, + "source": [ + "Let's instantiate our custom formatter and test it on a small sample of our data to see the result." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "68228040", + "metadata": {}, + "outputs": [], + "source": [ + "task_name = \"perturbation_prediction\"\n", + "prompt_formatter = PerturbationPromptFormatter(\n", + " task_name=task_name,\n", + " input_prompt=custom_input_prompt_template,\n", + " answer_template=answer_template,\n", + " top_k_genes=200 # Using top 200 genes for this example. For real applications, ideal to use all nonzero expressed genes if possible.\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "51258c12", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Grouping cells by perturbation and identifying global controls...\n", + "Found 12013 control cells.\n", + "Found 68 unique perturbations.\n", + "Creating control-perturbed pairs...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 68/68 [00:03<00:00, 20.85it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['sample_type', 'model_input', 'response'],\n", + " num_rows: 9399\n", + "})" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Format the dataset\n", + "formatted_ds = prompt_formatter.format_hf_ds(arrow_ds)\n", + "formatted_ds" + ] + }, + { + "cell_type": "markdown", + "id": "95e9668c", + "metadata": {}, + "source": [ + "Note that if you want to do a train/test split of the data, separating out a split of control cells and holdout perturbed cells / entire perturbations can be done before formatting." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "f8b0f343", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Formatted Sample ---\n", + "#----Model input:----#\n", + "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", + "Control cell sentence: MT-ATP6 MT-CO3 TMSB4X MT-ND4 MT-ND1 MT-CO2 ACTB MT-ND2 MT-ND3 MT-CYB RACK1 HSP90AB1 HSP90AA1 NME2 HSPD1 H2AFZ YBX1 ACTG1 FTH1 TUBA1B TUBB LDHB PFN1 NCL FTL PRDX1 EEF1B2 HIST1H4C BTF3 ADA CFL1 CHCHD2 SET ENO1 UBA52 H3F3A ARHGDIB EIF1 EEF1G PPP1R14B GSTP1 CALR HINT1 SERF2 HSPE1 XRCC5 TMSB10 STMN1 CD3D B2M EEF2 MT-ND6 PPIA HIST1H1D MIF H3F3B ANP32B HNRNPU UBC SERBP1 CDK6 EIF4A1 TYMS UQCRH PSMA7 HNRNPA2B1 SFPQ GPX4 HMGB2 PRRC2C SIVA1 FUS SUB1 LCP1 SLC25A3 SNRPB SRSF3 CSDE1 PCLAF EIF3G EIF3A MYL6 HES4 HMGN1 SLC25A5 COX4I1 MKI67 NDUFA13 HNRNPD PEBP1 PPP1CA GABARAP PRDX5 HNRNPA3 TIMM13 PKM POMP PCNA NUDC STOML2 GADD45GIP1 TMA7 PPA1 CORO1A HNRNPK ARPP19 UQCRB ATP5F1B SNRPD1 DDX5 ARPC3 ISG15 PSMA4 SEC61B COX8A PSMA1 FABP5 TMEM160 SNRPE PRPF40A MT-ND5 ODC1 COX6A1 SH3BGRL3 HMGA1 NUCKS1 COX7A2 ATP5MC2 NOP56 HNRNPC KTN1 SRSF7 SOX4 CLIC1 PSMD2 NDUFS6 ALYREF SUMO2 GUK1 SSBP1 YWHAQ BRD2 SRSF9 ERH TOMM6 PSMC5 CCT2 CCT4 IGFBP2 C1QBP ATP5F1E ARL6IP4 C12ORF57 SNU13 METTL5 CCNI ATP5MC1 CCT8 DDX46 TMEM208 JPT1 SPCS1 FDFT1 PA2G4 HNRNPR HIST1H1B CENPF SNRPF CCT3 ARPC1B COX6C DBI RBM3 PRKDC EIF3I C12ORF75 DIAPH1 EIF5 MARCKSL1 IFI16 EIF4G2 MT-ND4L PHB CCT6A ARPC5 NUCB2 LIME1 POLR2F NME1 PPM1G VIM MANF UBL5 COPS6 PSMB6 SRRM1 SUPT16H SRM SELENOH AP2M1.\n", + "\n", + "Perturbed cell sentence: \n", + "\n", + "#----Response:----#\n", + "MT-ATP6 MT-CO3 MT-CO2 TUBA1B HSP90B1 MT-CYB MT-ND4 ACTB TMSB4X HSP90AA1 HSP90AB1 CENPF MT-ND6 TRBC1 MT-ND2 HNRNPA2B1 PPIA H3F3A HSPD1 GSTP1 TUBB LDHB CHCHD2 SET MIF ADA RACK1 EEF1G EEF1B2 BTF3 CD3G NME2 NCL HSPA8 MT-ND1 XRCC5 EIF4A1 NUCKS1 CCNB1 PRDX1 EDF1 H2AFY RNASEH2C CDK6 FABP5 FTH1 HNRNPD COX4I1 KPNA2 CDC123 UBA52 B2M MKI67 SNRPB TPM4 ARPC5 HINT1 ITM2B CORO1A ATP5MC3 H2AFZ PMEPA1 MED28 ARHGDIB MYL12A YBX3 ASPM H2AFX ATP5PF RBM3 SLC25A5 HNRNPU ZNRF1 PFN1 MYO7B RNF213 ACTG1 YBX1 C4ORF48 HSPA5 ITM2A SRSF2 KHDRBS1 EIF2S3 DDX39A SFPQ TECR CCT2 HSPE1 SMC4 CANX DDX5 CSDE1 ATP5F1D TCF12 C1QBP CD3D FYB1 MT-ND3 TMBIM6 SERF2 NKTR CYC1 NDUFA4 DIAPH1 PALM2-AKAP2 FTL MT-ND5 SOX4 H3F3B LEF1 GTF3A GABARAP XRN2 LSM4 CLIC1 NIPBL CHORDC1 STMN1 SIX6 PGK1 BLOC1S6 UBE2I HMGB2 IRF1 CD3E SRRM1 NDUFA7 CFL1 KNL1 GUK1 NSA2 PRPF8 IFI16 SNRPE RNF220 EIF4G2 SETX STT3B RUFY1 XRCC6 NAE1 PNN NOP10 IK SRP19 SUB1 MSI2 TXNL4A PFDN5 SRM PCBP2 NCAPG DDX3X VPS26B TCOF1 JPT1 EIF1 MAD2L1 PSMD2 CUL4A MARCKSL1 NUCB2 NDUFA2 ATP5MG TUBA1A LBR CDK1 MAP4K4 COPS5 NOP58 SAMD1 ENO1 PFDN2 MTCH2 KMT5A TMEM160 CWC22 SOD1 SCAF11 NME1 ATM CDC20 SRSF11 TBL1XR1 RSL24D1 NDUFV1 SRSF7 BAG1 CCT6A ZEB1 ATP6V1F UQCRH CBFA2T3 FBL SRSF10 C12ORF10 VIRMA DUSP2 CCT3.\n" + ] + } + ], + "source": [ + "# Inspect a formatted sample\n", + "print(\"--- Formatted Sample ---\")\n", + "print(\"#----Model input:----#\")\n", + "print(formatted_ds[0][\"model_input\"], \"\\n\")\n", + "print(\"#----Response:----#\")\n", + "print(formatted_ds[0][\"response\"])" + ] + }, + { + "cell_type": "markdown", + "id": "c18db332", + "metadata": {}, + "source": [ + "Now that our custom formatter is ready, we'll wrap our original `arrow_ds` in a `CSData` object. The `finetune` function will use this object and our custom formatter to prepare the data for training." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "28ab6da2", + "metadata": {}, + "outputs": [], + "source": [ + "# Save directory for Huggingface dataset\n", + "c2s_save_dir = \"/home/sr2464/scratch/C2S_API_Testing/Data/perturbation_tutorial/perturbation_tutorial\"\n", + "c2s_save_name = \"jurkat_perturbation_c2s\"" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "fa776a5f", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "148d9b57e6d94845a51fa39c55e9846e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Saving the dataset (0/1 shards): 0%| | 0/21412 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Tracking run with wandb version 0.16.6" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Run data is saved locally in /home/sr2464/Desktop/cell2sentence/tutorials/wandb/run-20251014_233441-fa2rexvg" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Syncing run /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction to Weights & Biases (docs)
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + " View project at https://wandb.ai/syed-a-rizvi/huggingface" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + " View run at https://wandb.ai/syed-a-rizvi/huggingface/runs/fa2rexvg" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "
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StepTraining LossValidation Loss

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Finetuning completed. Updated model saved to disk at: /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction\n" + ] + } + ], + "source": [ + "csmodel.fine_tune(\n", + " csdata=csdata,\n", + " task=task_name,\n", + " train_args=train_args,\n", + " loss_on_response_only=True, # We only want to calculate loss on the predicted sentence\n", + " top_k_genes=200, # Use top 200 genes for this example, normally would use full cell sentence (all nonzero expressed genes) if possible\n", + " prompt_formatter=prompt_formatter # Pass in our custom prompt formatter\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "7de08f82", + "metadata": {}, + "source": [ + "# Generate Predictions with the Finetuned Model\n", + "\n", + "After finetuning, let's load our new model and use it to predict the response to a perturbation for a cell from our test set." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "89474061", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction/checkpoint-500'" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "final_ckpt_path = os.path.join(output_dir, \"checkpoint-500\")\n", + "final_ckpt_path" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "38d63e84", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial'" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "save_dir" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "ebff900c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using device: cuda\n" + ] + } + ], + "source": [ + "# Load the finetuned model (it's automatically saved to csmodel.model_name_or_path)\n", + "finetuned_model = cs.CSModel(\n", + " model_name_or_path=final_ckpt_path, # Path is updated after finetuning\n", + " save_dir=save_dir,\n", + " save_name=\"perturbation_predictor_finetuned_final\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "ca22f14f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/perturbation_predictor_finetuned_final'" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "finetuned_model.save_path" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "cf85b83c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'cuda'" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", + "device" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "7c36e4b1", + "metadata": {}, + "outputs": [], + "source": [ + "final_model = AutoModelForCausalLM.from_pretrained(\n", + " finetuned_model.save_path,\n", + " cache_dir=os.path.join(csmodel.save_dir, \".cache\"),\n", + " trust_remote_code=True\n", + ").to(device)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "c828d229", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['train', 'val', 'test'])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Load dataset split done in finetune() function, saved to output directory\n", + "with open(os.path.join(output_dir, 'data_split_indices_dict.pkl'), 'rb') as f:\n", + " data_split_indices_dict = pickle.load(f)\n", + "\n", + "data_split_indices_dict.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "54a9c647", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[7, 29, 33, 35, 51, 54, 65, 70, 115, 116]" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Print a few indices of test samples\n", + "data_split_indices_dict['test'][:10]" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "6a54bcda", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Dataset({\n", + " features: ['sample_type', 'model_input', 'response'],\n", + " num_rows: 10\n", + "})" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Select a few unseen samples\n", + "formatted_test_ds = formatted_ds.select(data_split_indices_dict['test'][:10])\n", + "formatted_test_ds" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "1feda129", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Inference Prompt ---\n", + "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", + "Control cell sentence: ACTB MT-ATP6 MT-CO3 MT-CO2 TMSB4X TUBA1B MT-ND4 HSP90AA1 HIST1H4C TMSB10 MT-CYB ACTG1 TUBB RACK1 PFN1 H3F3A ARHGDIB YBX1 MT-ND1 CFL1 H2AFZ B2M FTH1 HSP90AB1 CENPF UBA52 MIF MT-ND3 LDHB NCL PPIA SERF2 HNRNPA2B1 EEF1B2 CDK6 PSMA7 HSPD1 TOP2A KPNA2 GSTP1 BTF3 MT-ND2 CD3D SET CORO1A UBB ANP32B HNRNPU STMN1 EIF4A1 CCT3 EEF1G EEF2 SOX4 EIF1 BANF1 HNRNPD ADA COX4I1 MKI67 COX6C SUMO2 LCP1 SLC25A3 PKM CHCHD2 HINT1 OAZ1 NDUFS6 ENO1 TUBB4B HMGB2 MACF1 NME1 LSM4 SELENOH HSPE1 ERH NUCKS1 HMGN1 DDX5 NDUFB10 HIST1H1E GPX4 NDUFA13 GTF3A MT-ND6 PTGES3 ARL6IP1 RBMX PGK1 CTCF ATP5MC3 PSMB2 SLC25A5 PRDX5 COX7C SPTBN1 BPTF ANXA1 UBE2C PRDX1 SRSF10 NDUFA12 SFPQ EIF3G TOMM22 SIVA1 PHB2 CCT2 PA2G4 PCBP2 SUB1 CCT6A RHOA ASPM YWHAE ATP5MC1 XRCC5 SMC4 SRSF3 YBX3 HNRNPAB ATP5F1B CSDE1 SNRPB IFI16 SNRPD1 PAFAH1B3 MSN XRCC6 COX6A1 COX8A ATP5F1E ALYREF CBX3 MYL6 EIF3E RBM39 RAC1 UBE2D2 C1QBP KHDRBS1 CCT4 JPT1 RAD21 NME2 PSME2 SEPTIN7 SNU13 CKLF NMRAL1 NOP53 EIF3I EIF3D SAP18 SON HTATSF1 PSMA3 SEC61B AIP RBM8A C11ORF58 PRRC2C OSTC NDUFAB1 NDUFA4 SELENOW HNRNPA3 SRSF7 H3F3B TOMM20 SRSF9 HNRNPK CCT8 ARPC2 ATP5F1A ATP5F1C PHB EIF4B NUCB2 SSBP1 CD3G TMEM50A HNRNPM BUB3 SRSF2 PSMC5 KDM5A SNRNP25 PAK2 MYL12A NIFK SNRPF SLC25A6 KIF14 PRMT1 MTDH SRRM2 ATP5PF.\n", + "\n", + "Perturbed cell sentence:\n" + ] + } + ], + "source": [ + "# Select a sample from the test set for inference\n", + "sample_idx = 0\n", + "inference_prompt = formatted_test_ds[sample_idx]['model_input']\n", + "ground_truth_response = formatted_test_ds[sample_idx]['response']\n", + "\n", + "print(\"--- Inference Prompt ---\")\n", + "print(inference_prompt)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "96d8dd95", + "metadata": {}, + "outputs": [], + "source": [ + "# Generate the prediction\n", + "predicted_response = finetuned_model.generate_from_prompt(\n", + " model=final_model,\n", + " prompt=inference_prompt,\n", + " max_num_tokens=800 # max number of tokens to generate, ~4 tokens per gene\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "c807b03c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "--- Ground Truth Perturbed Cell ---\n", + "MT-ATP6 MT-CO3 MT-CO2 MT-ND4 MT-CYB MT-ND1 MT-ND2 ACTB HSP90AA1 TMSB4X YBX1 EEF1B2 MT-ND3 RACK1 HSP90AB1 EEF1G MIF NME2 HIST1H4C TUBA1B NCL TUBB ADA ENO1 STMN1 H2AFZ PFN1 H3F3A CFL1 LDHB HINT1 HSPD1 C1QBP HSPE1 UBA52 SERF2 ACTG1 PPIA B2M CALR HNRNPA2B1 ARHGDIB GSTP1 SET MT-ND5 BTF3 CCT2 CHCHD2 NUCB2 XRCC5 PGK1 CD3D HNRNPU SUMO2 PPP1R14B HNRNPD UQCRH FDPS ALYREF SIVA1 DNAJA1 SLC25A6 ARPC2 FTL TYMS DUT COX4I1 SNRPB DDX5 PRKDC SLC25A3 PSMA7 CD3G SLC25A5 UBC ATP5F1E MYL6 ATP5F1B CCT6A PCLAF CDK6 H3F3B EIF4A1 EEF2 HMGB2 GUK1 THRAP3 HNRNPDL SERBP1 FABP5 EIF2S2 NUCKS1 HNRNPA3 HMGN1 COX7C SFPQ NDUFA13 HSPA8 OAZ1 MARCKSL1 DEK SELENOH FTH1 SRM SNRPF EIF1 DYNLL1 XRCC6 MT-ND6 RSL1D1 ANP32B EIF3E PSMA3 NDUFS5 ERH ATP5MC3 ARPC3 GLUL YBX3 FUS SNRPD1 YWHAB ATP5MC1 PRDX1 PSMA4 SOX4 NDUFAB1 PPA1 EIF5 NUDC STOML2 NME4 SRSF7 MZB1 H1FX NOP56 TPM4 NME1 NASP EIF3I ATP6V1F SF3B2 TRIR CCNI ARPC1B COX6C SLIRP SNRPC BRK1 ARPC5 ATP5MF SRSF3 CD7 HNRNPR GNAI2 CARHSP1 PPIG ATP5MG PTGES3 PFDN2 SSBP1 C9ORF16 PAICS GPX4 UBB C12ORF57 HIST1H1B ANP32A PRDX5 APRT PKM PFDN5 NHP2 SUB1 CORO1A LSM2 HNRNPC RRM2 PNN EPRS SNRPA1 HSP90B1 MCM3 CCT8 PRRC2C SKP1 RNASEH2B CIAO2B PRMT1 RAC1 SRRT HNRNPF VDAC3 ISG15 NAA10 RRP1B CCT3 MYL12B NAE1 EMC6.\n", + "\n", + "--- Predicted Perturbed Cell ---\n", + "MT-ATP6 MT-CO3 MT-CO2 MT-CYB MT-ND4 TMSB4X ACTB MT-ND1 MT-ND3 MT-ND2 HSP90AA1 HSP90AB1 RACK1 YBX1 MIF TUBA1B H3F3A H2AFZ HSPD1 NCL EEF1B2 FTH1 HNRNPA2B1 EEF1G LDHB HINT1 CHCHD2 NME2 BTF3 UBA52 EIF4A1 ACTG1 STMN1 TUBB PFN1 CFL1 EIF1 PPIA GSTP1 PRDX1 HNRNPU SET B2M HSPE1 ARHGDIB ENO1 SERF2 CD3D MT-ND5 HNRNPD HNRNPC C1QBP FTL SLC25A3 COX4I1 SLC25A5 ATP5MC3 SRSF3 PPP1R14B SIVA1 HNRNPA3 CCT3 ANP32B SFPQ EIF3E HNRNPR PSMB1 ATP5MC2 CCT6A PSMB2 NUCB2 PSMA7 PSMB3 SNRPD1 PSMB6 ATP5F1B PPA1 UQCRH SNRPB NME1 SRSF7 PSMB7 NDUFS5 HNRNPK OAZ1 PFDN5 TMSB10 ADA GTF3A ATP5F1E SERBP1 COX7C NDUFA13 PSMB5 CCT2 ATP5F1D GUK1 EIF3A NDUFB10 FABP5 PSMB3 NDUFA4 ATP5F1A NUDC POMP HNRNPDL UBB PSMB6 NDUFS6 COX6A1 SRSF2 EIF3M SNRPE PSMA4 PSMD7 GADD45GIP1 ATP5MG PRMT1 NOP53 PSMD2 UQCRB YWHAE HNRNPM PSMD1 NDUFB11 EIF3H TOMM6 PSMD11 PSMC5 SRSF9 PSMC3 NDUFA11 NOP56 EIF3I EIF3G ATP5PO SNRPF RBM8A PSMD4 TOMM22 RTRAF SRSF11 PSMC1 NDUFAB1 HNRNPAB PSMD13 PSMA2 NUCKS1 UQCR10 RSL1D1 PSMB4 TOMM5 GYPC PFDN2 PSMA3 NDUFA12 NOP10 EIF4G2 SELENOH UBE2I RBM3 PSMD12 PSMC4 HNRNPD SRM PSMB8 EIF3L RBMX PSMD6 SLC25A6 TOMM20 UBE2L3 PSMB5 RBM25 EIF3D TMA7 PNN RBM39 UQCR11 GTF3C6 PPP1CA EIF2S2 PSMC2 NUDT8 PSMD11 RBM8B RBM3B TOMM40 RAC1 TUFM EIF4B PSMB7 RSL24D1 GTF2A2 NOL7 PSMD12.\n" + ] + } + ], + "source": [ + "print(\"\\n--- Ground Truth Perturbed Cell ---\")\n", + "print(ground_truth_response)\n", + "print(\"\\n--- Predicted Perturbed Cell ---\")\n", + "print(predicted_response)" + ] + }, + { + "cell_type": "markdown", + "id": "ce20628b", + "metadata": {}, + "source": [ + "# Conclusion\n", + "\n", + "In this tutorial, you learned how to finetune a Cell2Sentence model for a custom task: perturbation response prediction. By creating a `PerturbationPromptFormatter`, we were able to structure our data into control-perturbation-response triplets, enabling the model to learn the complex transcriptional changes that occur upon perturbation.\n", + "\n", + "This approach is highly flexible and can be adapted to various experimental designs. The finetuned model can now be used for in-silico experiments, such as virtual screening of genetic perturbations or predicting the effect of new compounds, significantly accelerating the pace of biological discovery." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2f1296f4", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "cell2sentence2", + "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": "3.8.20" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 7e4a8e13a0da7a4d3cbf245663ffa1a0f4590ed1 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 11:45:17 +0000 Subject: [PATCH 03/19] Removing errors from merge conflicts --- README.md | 5 +- ..._10_perturbation_response_prediction.ipynb | 1476 ----------------- ...al_9_natural_language_interpretation.ipynb | 1051 ------------ 3 files changed, 3 insertions(+), 2529 deletions(-) diff --git a/README.md b/README.md index 6951089..ac068ae 100644 --- a/README.md +++ b/README.md @@ -47,7 +47,7 @@ git clone https://github.com/vandijklab/cell2sentence.git Navigate a terminal into the root of the repository. Next, create an Anaconda environment using `python3` using [anaconda](https://docs.anaconda.com/anaconda/install/) with: ```bash -conda create -n cell2sentence python=3.8 +conda create -n cell2sentence python=3.10 ``` Next, activate the environment: @@ -62,7 +62,7 @@ make install This will install the latest development environment of cell2sentence, along with other pacakge dependendies. You can also install cell2sentence itself using `pip`: ```bash -pip install cell2sentence==1.1.0 +pip install cell2sentence==1.2.0 ``` The C2S package will allow usage of the core functionalities of C2S, including inference using existing C2S models and finetuning your own C2S models on your own datasets. @@ -86,6 +86,7 @@ The following notebooks provide guides on common workflows with C2S models. For | [c2s_tutorial_4_cell_type_prediction.ipynb](tutorials/c2s_tutorial_4_cell_type_prediction.ipynb) | Cell type prediction using C2S models | [c2s_tutorial_5_cell_generation.ipynb](tutorials/c2s_tutorial_5_cell_generation.ipynb) | Cell generation conditioned on cell type | [c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb](tutorials/c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb) | Cell type annotation with foundation model +| [c2s_tutorial_7_custom_prompt_templates.ipynb](tutorials/c2s_tutorials_7_custom_prompt_templates.ipynb) | Custom Prompt Templates with C2S PromptFormatter class ## Model Zoo diff --git a/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb b/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb index 008aef2..f3c78c2 100644 --- a/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb +++ b/tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb @@ -1473,1479 +1473,3 @@ "nbformat": 4, "nbformat_minor": 5 } - -{ - "cells": [ - { - "cell_type": "markdown", - "id": "9981f4b0", - "metadata": {}, - "source": [ - "# Tutorial Notebook 10: Finetuning for Perturbation Response Prediction\n", - "\n", - "In this tutorial, we will demonstrate how to finetune a Cell2Sentence (C2S) model for perturbation response prediction tasks. This is a critical task in single-cell analysis, where the goal is to predict how a cell's gene expression profile changes in response to a specific perturbation (e.g., a genetic knockout or a drug treatment).\n", - "\n", - "We will treat this as a \"translation\" task in natural language: translating a cell (in cell sentence format) from its basal (control) state to its perturbed state, conditioned on the perturbation applied.\n", - "\n", - "At a high level, we will:\n", - "1. Load a public single-cell perturbation dataset.\n", - "2. Write a custom prompt template for perturbation prediction.\n", - "3. Subclass the `PromptFormatter` class to create pairs of control and perturbed cells.\n", - "4. Finetune a pretrained C2S-Scale model on this new task.\n", - "5. Generate a prediction with our new finetuned model to see it in action." - ] - }, - { - "cell_type": "markdown", - "id": "139d5b0b", - "metadata": {}, - "source": [ - "First, let's import the necessary libraries. We'll need standard data science libraries, single-cell analysis tools, and modules from the `cell2sentence` and `transformers` packages." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "f0bf13c5", - "metadata": {}, - "outputs": [], - "source": [ - "# Python built-in libraries\n", - "import os\n", - "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\" \n", - "os.environ[\"WORLD_SIZE\"] = \"1\"\n", - "\n", - "import pickle\n", - "import random\n", - "from datetime import datetime\n", - "from collections import Counter, defaultdict\n", - "\n", - "# Third-party libraries\n", - "from datasets import Dataset\n", - "import numpy as np\n", - "import torch\n", - "from transformers import TrainingArguments, AutoModelForCausalLM\n", - "from tqdm import tqdm\n", - "\n", - "# Single-cell libraries\n", - "import anndata\n", - "import scanpy as sc" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "cb07037d", - "metadata": {}, - "outputs": [], - "source": [ - "# Cell2Sentence imports\n", - "import cell2sentence as cs\n", - "from cell2sentence.prompt_formatter import get_cell_sentence_str, PromptFormatter" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "81ce734c", - "metadata": {}, - "outputs": [], - "source": [ - "SEED = 1234\n", - "random.seed(SEED)\n", - "np.random.seed(SEED)" - ] - }, - { - "cell_type": "markdown", - "id": "0f6047f8", - "metadata": {}, - "source": [ - "# Load Perturbation Data\n", - "\n", - "For this tutorial, you will need a single-cell dataset that includes both control and perturbed cells. The data should be in an `AnnData` object. Crucially, your `.obs` dataframe must contain:\n", - "- A column that distinguishes control cells from perturbed cells, e.g., `adata.obs['condition']`\n", - " - Values can be something like 'control' or 'non-targeting' for control cells, and 'perturbed' or the perturbation name for the perturbed cells\n", - "\n", - "For this example, we use a public genetic perturbation dataset of Jurkat cells (Nadig et al., 2025). To use your own dataset, replace `DATA_PATH` with the path to your preprocessed data file.\n", - "- Paper: https://www.nature.com/articles/s41588-025-02169-3\n", - "\n", - "Ensure your data is preprocessed and normalized (e.g., using log1p transformation) before proceeding." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "52754a57", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 21412 × 18080\n", - " obs: 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Replace this with the actual path to your dataset, if using a custom dataset\n", - "DATA_PATH = \"/home/sr2464/scratch/C2S_API_Testing/Data/jurkat.h5ad\"\n", - "adata = anndata.read_h5ad(DATA_PATH)\n", - "adata" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "590a4a9f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "

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" - ], - "text/plain": [ - " batch_var cell_type target_gene gene_id \\\n", - "cell_barcode \n", - "AAACCCAAGCACCAGA-42 jurkat42 jurkat EIF4B ENSG00000063046 \n", - "AAACCCAAGCAGATAT-4 jurkat4 jurkat DAXX ENSG00000204209 \n", - "AAACCCAAGCTAGATA-2 jurkat2 jurkat METTL3 ENSG00000165819 \n", - "AAACCCAAGCTGGAGT-37 jurkat37 jurkat non-targeting non-targeting \n", - "AAACCCAAGGGCCTCT-51 jurkat51 jurkat non-targeting non-targeting \n", - "\n", - " mitopercent UMI_count \n", - "cell_barcode \n", - "AAACCCAAGCACCAGA-42 0.037697 4828.0 \n", - "AAACCCAAGCAGATAT-4 0.063256 9675.0 \n", - "AAACCCAAGCTAGATA-2 0.069885 16985.0 \n", - "AAACCCAAGCTGGAGT-37 0.055775 20475.0 \n", - "AAACCCAAGGGCCTCT-51 0.047619 12642.0 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.obs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "e07fcedb", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "69\n" - ] - } - ], - "source": [ - "target_gene_counter = Counter(adata.obs['target_gene'])\n", - "print(len(target_gene_counter))" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ab4e3458", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[('non-targeting', 12013),\n", - " ('TFAM', 2555),\n", - " ('EIF4B', 461),\n", - " ('JAZF1', 265),\n", - " ('HIRA', 233),\n", - " ('SMARCB1', 204),\n", - " ('TAF13', 200),\n", - " ('KDM1A', 195),\n", - " ('MBTPS1', 192),\n", - " ('LZTR1', 192),\n", - " ('METTL3', 177),\n", - " ('DNMT1', 177),\n", - " ('SDC1', 156),\n", - " ('TADA1', 144),\n", - " ('MED12', 143),\n", - " ('USF2', 141),\n", - " ('ARPC2', 140),\n", - " ('PTPN1', 136),\n", - " ('PHF10', 136),\n", - " ('NDUFB4', 133)]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "target_gene_counter.most_common(20)" - ] - }, - { - "cell_type": "markdown", - "id": "afec3e85", - "metadata": {}, - "source": [ - "This data contains both control cells (non-targeting) as well as cells under different genetic knockouts." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "38ebcf86", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - "Empty DataFrame\n", - "Columns: []\n", - "Index: [SAMD11, NOC2L, KLHL17, PLEKHN1, PERM1]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.var.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "cc318b3f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "<21412x18080 sparse matrix of type ''\n", - "\twith 69336411 stored elements in Compressed Sparse Row format>" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.X" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "6239a8bc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034, 1.6483034,\n", - " 1.6483034, 1.6483034, 1.6483034, 1.6483034], dtype=float32)" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# View a few nonzero values\n", - "adata.X.data[:10]" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "0e4b95d8", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "8.333305" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.X.max()" - ] - }, - { - "cell_type": "markdown", - "id": "005cef4b", - "metadata": {}, - "source": [ - "The expression is already preprocessed and log1p transformed. Typically, a log1p transform with base=10 would be used for Cell2Sentence training if we wish to convert generated cell sentences back to expression vectors, since log base=10 gives a better linear relationship between log rank and log expression in many single-cell datasets.\n", - "\n", - "For this tutorial, we will use this processed data as is, to train our model to generate target cell sentences." - ] - }, - { - "cell_type": "markdown", - "id": "a1c99514", - "metadata": {}, - "source": [ - "# Cell2Sentence Conversion\n", - "\n", - "Now, we will convert the gene expression data in our `AnnData` object into cell sentences. This process creates a Hugging Face Arrow dataset, which is used in our LLM training." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "e0ae0bdb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['batch_var',\n", - " 'cell_type',\n", - " 'target_gene',\n", - " 'gene_id',\n", - " 'mitopercent',\n", - " 'UMI_count']" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# We'll keep all relevant columns for our new task\n", - "adata_obs_cols_to_keep = adata.obs.columns.tolist()\n", - "adata_obs_cols_to_keep" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "91e60261", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 21412/21412 [00:11<00:00, 1899.14it/s]\n" - ] - }, - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['cell_name', 'cell_sentence', 'batch_var', 'cell_type', 'target_gene', 'gene_id', 'mitopercent', 'UMI_count'],\n", - " num_rows: 21412\n", - "})" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Create Arrow dataset and vocabulary\n", - "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", - " adata=adata, \n", - " random_state=SEED, \n", - " sentence_delimiter=' ',\n", - " label_col_names=adata_obs_cols_to_keep\n", - ")\n", - "arrow_ds" - ] - }, - { - "cell_type": "markdown", - "id": "3efc581c", - "metadata": {}, - "source": [ - "# Custom Prompt Formatting for Perturbation Prediction\n", - "\n", - "This is the core of our tutorial. For this dataset, we have a single large pool of control cells (labeled 'non-targeting') and multiple groups of perturbed cells, each with a specific `target_gene`. Our goal is to create training pairs where each perturbed cell is matched with a randomly selected control cell. Note that for different perturbation applications, there may be better ways of pairing control and perturbed cells.\n", - "\n", - "We will define a custom prompt structure that frames our task for the LLM. The input will contain the **control cell sentence** and the **perturbation name**. The model's expected output (the response) will be the **perturbed cell sentence**.\n", - "\n", - "First, let's define our prompt templates." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "adceba43", - "metadata": {}, - "outputs": [], - "source": [ - "# The input provides the control cell and the perturbation, asking for the perturbed result.\n", - "custom_input_prompt_template = \"\"\"Given the following cell sentence of {num_genes} expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: {perturbation_name}.\n", - "Control cell sentence: {control_cell_sentence}.\n", - "\n", - "Perturbed cell sentence:\"\"\"\n", - "\n", - "# The answer is simply the target cell sentence.\n", - "answer_template = \"{perturbed_cell_sentence}.\"" - ] - }, - { - "cell_type": "markdown", - "id": "8afe106b", - "metadata": {}, - "source": [ - "To apply this template, we need to create pairs of (control cell, perturbed cell) for each perturbation. We'll create a custom `PerturbationPromptFormatter` by subclassing the base `PromptFormatter`.\n", - "\n", - "Our custom `format_hf_ds` function will:\n", - "1. First, iterate through the entire dataset to create a list of all control cell indices.\n", - "2. Simultaneously, it will group the indices of all perturbed cells into a dictionary, with the perturbation name (`target_gene`) as the key.\n", - "3. Then, it will iterate through each perturbation group and, for every perturbed cell, randomly select a control cell from the global pool to form a pair.\n", - "4. Finally, it will format these pairs into the input prompts and expected responses for the model." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "84fdc5ba", - "metadata": {}, - "outputs": [], - "source": [ - "from collections import defaultdict\n", - "\n", - "class PerturbationPromptFormatter(PromptFormatter):\n", - " def __init__(self,\n", - " task_name,\n", - " input_prompt,\n", - " answer_template,\n", - " top_k_genes, \n", - " perturbation_col='target_gene',\n", - " control_label='non-targeting'\n", - " ):\n", - " \"\"\"\n", - " Initializes the custom prompt formatter.\n", - "\n", - " Args:\n", - " task_name (str): The name for this task.\n", - " input_prompt (str): The template for the model's input.\n", - " answer_template (str): The template for the model's expected response.\n", - " top_k_genes (int): The number of top genes to include in the cell sentence.\n", - " perturbation_col (str): The column name in the dataset that contains perturbation info.\n", - " control_label (str): The label used to identify control cells in the perturbation_col.\n", - " \"\"\"\n", - " super().__init__()\n", - " self.task_name = task_name\n", - " self.input_prompt = input_prompt\n", - " self.answer_template = answer_template\n", - " self.top_k_genes = top_k_genes\n", - " self.perturbation_col = perturbation_col\n", - " self.control_label = control_label\n", - " assert top_k_genes > 0, \"'top_k_genes' must be an integer > 0\"\n", - "\n", - " def format_hf_ds(self, hf_ds):\n", - " \"\"\"\n", - " Custom formatting function for perturbation prediction. This function creates pairs of\n", - " (control, perturbed) cells by sampling from a global pool of control cells.\n", - " \"\"\"\n", - " model_inputs_list = []\n", - " responses_list = []\n", - " \n", - " # 1. Separate all cells into a global control pool and a dict of perturbed cells\n", - " control_indices = []\n", - " pert_to_indices = defaultdict(list)\n", - "\n", - " print(\"Grouping cells by perturbation and identifying global controls...\")\n", - " for i, sample in enumerate(hf_ds):\n", - " if sample[self.perturbation_col] == self.control_label:\n", - " control_indices.append(i)\n", - " else:\n", - " pert_to_indices[sample[self.perturbation_col]].append(i)\n", - " \n", - " assert len(control_indices) > 0, \"No control cells found. Cannot create pairs.\"\n", - " print(f\"Found {len(control_indices)} control cells.\")\n", - " print(f\"Found {len(pert_to_indices)} unique perturbations.\")\n", - "\n", - " # 2. Create prompt-response pairs by iterating through perturbed cells\n", - " print(\"Creating control-perturbed pairs...\")\n", - " for pert_name, perturbed_indices in tqdm(pert_to_indices.items()):\n", - " for perturbed_idx in perturbed_indices:\n", - " # Pair each perturbed cell with a random control cell from the global pool\n", - " control_idx = random.choice(control_indices)\n", - " \n", - " control_sample = hf_ds[control_idx]\n", - " perturbed_sample = hf_ds[perturbed_idx]\n", - "\n", - " # Format control cell sentence\n", - " control_sentence, num_genes_str = get_cell_sentence_str(\n", - " control_sample,\n", - " num_genes=self.top_k_genes\n", - " )\n", - " # Format perturbed cell sentence\n", - " perturbed_sentence, _ = get_cell_sentence_str(\n", - " perturbed_sample,\n", - " num_genes=self.top_k_genes\n", - " )\n", - "\n", - " # Format the model input string using the perturbation name\n", - " model_input_str = self.input_prompt.format(\n", - " num_genes=num_genes_str,\n", - " perturbation_name=pert_name,\n", - " control_cell_sentence=control_sentence\n", - " )\n", - " \n", - " # Format the response string\n", - " response_str = self.answer_template.format(\n", - " perturbed_cell_sentence=perturbed_sentence\n", - " )\n", - "\n", - " model_inputs_list.append(model_input_str)\n", - " responses_list.append(response_str)\n", - "\n", - " # Create the final Hugging Face Dataset\n", - " ds_split_dict = {\n", - " \"sample_type\": [self.task_name] * len(model_inputs_list),\n", - " \"model_input\": model_inputs_list,\n", - " \"response\": responses_list,\n", - " }\n", - " ds = Dataset.from_dict(ds_split_dict)\n", - " return ds" - ] - }, - { - "cell_type": "markdown", - "id": "e431c369", - "metadata": {}, - "source": [ - "Let's instantiate our custom formatter and test it on a small sample of our data to see the result." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "68228040", - "metadata": {}, - "outputs": [], - "source": [ - "task_name = \"perturbation_prediction\"\n", - "prompt_formatter = PerturbationPromptFormatter(\n", - " task_name=task_name,\n", - " input_prompt=custom_input_prompt_template,\n", - " answer_template=answer_template,\n", - " top_k_genes=200 # Using top 200 genes for this example. For real applications, ideal to use all nonzero expressed genes if possible.\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "51258c12", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Grouping cells by perturbation and identifying global controls...\n", - "Found 12013 control cells.\n", - "Found 68 unique perturbations.\n", - "Creating control-perturbed pairs...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 68/68 [00:03<00:00, 20.85it/s]\n" - ] - }, - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['sample_type', 'model_input', 'response'],\n", - " num_rows: 9399\n", - "})" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Format the dataset\n", - "formatted_ds = prompt_formatter.format_hf_ds(arrow_ds)\n", - "formatted_ds" - ] - }, - { - "cell_type": "markdown", - "id": "95e9668c", - "metadata": {}, - "source": [ - "Note that if you want to do a train/test split of the data, separating out a split of control cells and holdout perturbed cells / entire perturbations can be done before formatting." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "f8b0f343", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Formatted Sample ---\n", - "#----Model input:----#\n", - "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", - "Control cell sentence: MT-ATP6 MT-CO3 TMSB4X MT-ND4 MT-ND1 MT-CO2 ACTB MT-ND2 MT-ND3 MT-CYB RACK1 HSP90AB1 HSP90AA1 NME2 HSPD1 H2AFZ YBX1 ACTG1 FTH1 TUBA1B TUBB LDHB PFN1 NCL FTL PRDX1 EEF1B2 HIST1H4C BTF3 ADA CFL1 CHCHD2 SET ENO1 UBA52 H3F3A ARHGDIB EIF1 EEF1G PPP1R14B GSTP1 CALR HINT1 SERF2 HSPE1 XRCC5 TMSB10 STMN1 CD3D B2M EEF2 MT-ND6 PPIA HIST1H1D MIF H3F3B ANP32B HNRNPU UBC SERBP1 CDK6 EIF4A1 TYMS UQCRH PSMA7 HNRNPA2B1 SFPQ GPX4 HMGB2 PRRC2C SIVA1 FUS SUB1 LCP1 SLC25A3 SNRPB SRSF3 CSDE1 PCLAF EIF3G EIF3A MYL6 HES4 HMGN1 SLC25A5 COX4I1 MKI67 NDUFA13 HNRNPD PEBP1 PPP1CA GABARAP PRDX5 HNRNPA3 TIMM13 PKM POMP PCNA NUDC STOML2 GADD45GIP1 TMA7 PPA1 CORO1A HNRNPK ARPP19 UQCRB ATP5F1B SNRPD1 DDX5 ARPC3 ISG15 PSMA4 SEC61B COX8A PSMA1 FABP5 TMEM160 SNRPE PRPF40A MT-ND5 ODC1 COX6A1 SH3BGRL3 HMGA1 NUCKS1 COX7A2 ATP5MC2 NOP56 HNRNPC KTN1 SRSF7 SOX4 CLIC1 PSMD2 NDUFS6 ALYREF SUMO2 GUK1 SSBP1 YWHAQ BRD2 SRSF9 ERH TOMM6 PSMC5 CCT2 CCT4 IGFBP2 C1QBP ATP5F1E ARL6IP4 C12ORF57 SNU13 METTL5 CCNI ATP5MC1 CCT8 DDX46 TMEM208 JPT1 SPCS1 FDFT1 PA2G4 HNRNPR HIST1H1B CENPF SNRPF CCT3 ARPC1B COX6C DBI RBM3 PRKDC EIF3I C12ORF75 DIAPH1 EIF5 MARCKSL1 IFI16 EIF4G2 MT-ND4L PHB CCT6A ARPC5 NUCB2 LIME1 POLR2F NME1 PPM1G VIM MANF UBL5 COPS6 PSMB6 SRRM1 SUPT16H SRM SELENOH AP2M1.\n", - "\n", - "Perturbed cell sentence: \n", - "\n", - "#----Response:----#\n", - "MT-ATP6 MT-CO3 MT-CO2 TUBA1B HSP90B1 MT-CYB MT-ND4 ACTB TMSB4X HSP90AA1 HSP90AB1 CENPF MT-ND6 TRBC1 MT-ND2 HNRNPA2B1 PPIA H3F3A HSPD1 GSTP1 TUBB LDHB CHCHD2 SET MIF ADA RACK1 EEF1G EEF1B2 BTF3 CD3G NME2 NCL HSPA8 MT-ND1 XRCC5 EIF4A1 NUCKS1 CCNB1 PRDX1 EDF1 H2AFY RNASEH2C CDK6 FABP5 FTH1 HNRNPD COX4I1 KPNA2 CDC123 UBA52 B2M MKI67 SNRPB TPM4 ARPC5 HINT1 ITM2B CORO1A ATP5MC3 H2AFZ PMEPA1 MED28 ARHGDIB MYL12A YBX3 ASPM H2AFX ATP5PF RBM3 SLC25A5 HNRNPU ZNRF1 PFN1 MYO7B RNF213 ACTG1 YBX1 C4ORF48 HSPA5 ITM2A SRSF2 KHDRBS1 EIF2S3 DDX39A SFPQ TECR CCT2 HSPE1 SMC4 CANX DDX5 CSDE1 ATP5F1D TCF12 C1QBP CD3D FYB1 MT-ND3 TMBIM6 SERF2 NKTR CYC1 NDUFA4 DIAPH1 PALM2-AKAP2 FTL MT-ND5 SOX4 H3F3B LEF1 GTF3A GABARAP XRN2 LSM4 CLIC1 NIPBL CHORDC1 STMN1 SIX6 PGK1 BLOC1S6 UBE2I HMGB2 IRF1 CD3E SRRM1 NDUFA7 CFL1 KNL1 GUK1 NSA2 PRPF8 IFI16 SNRPE RNF220 EIF4G2 SETX STT3B RUFY1 XRCC6 NAE1 PNN NOP10 IK SRP19 SUB1 MSI2 TXNL4A PFDN5 SRM PCBP2 NCAPG DDX3X VPS26B TCOF1 JPT1 EIF1 MAD2L1 PSMD2 CUL4A MARCKSL1 NUCB2 NDUFA2 ATP5MG TUBA1A LBR CDK1 MAP4K4 COPS5 NOP58 SAMD1 ENO1 PFDN2 MTCH2 KMT5A TMEM160 CWC22 SOD1 SCAF11 NME1 ATM CDC20 SRSF11 TBL1XR1 RSL24D1 NDUFV1 SRSF7 BAG1 CCT6A ZEB1 ATP6V1F UQCRH CBFA2T3 FBL SRSF10 C12ORF10 VIRMA DUSP2 CCT3.\n" - ] - } - ], - "source": [ - "# Inspect a formatted sample\n", - "print(\"--- Formatted Sample ---\")\n", - "print(\"#----Model input:----#\")\n", - "print(formatted_ds[0][\"model_input\"], \"\\n\")\n", - "print(\"#----Response:----#\")\n", - "print(formatted_ds[0][\"response\"])" - ] - }, - { - "cell_type": "markdown", - "id": "c18db332", - "metadata": {}, - "source": [ - "Now that our custom formatter is ready, we'll wrap our original `arrow_ds` in a `CSData` object. The `finetune` function will use this object and our custom formatter to prepare the data for training." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "28ab6da2", - "metadata": {}, - "outputs": [], - "source": [ - "# Save directory for Huggingface dataset\n", - "c2s_save_dir = \"/home/sr2464/scratch/C2S_API_Testing/Data/perturbation_tutorial/perturbation_tutorial\"\n", - "c2s_save_name = \"jurkat_perturbation_c2s\"" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "fa776a5f", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "148d9b57e6d94845a51fa39c55e9846e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Saving the dataset (0/1 shards): 0%| | 0/21412 [00:00" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Tracking run with wandb version 0.16.6" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Run data is saved locally in /home/sr2464/Desktop/cell2sentence/tutorials/wandb/run-20251014_233441-fa2rexvg" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Syncing run /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction to Weights & Biases (docs)
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - " View project at https://wandb.ai/syed-a-rizvi/huggingface" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - " View run at https://wandb.ai/syed-a-rizvi/huggingface/runs/fa2rexvg" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
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" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Finetuning completed. Updated model saved to disk at: /home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction\n" - ] - } - ], - "source": [ - "csmodel.fine_tune(\n", - " csdata=csdata,\n", - " task=task_name,\n", - " train_args=train_args,\n", - " loss_on_response_only=True, # We only want to calculate loss on the predicted sentence\n", - " top_k_genes=200, # Use top 200 genes for this example, normally would use full cell sentence (all nonzero expressed genes) if possible\n", - " prompt_formatter=prompt_formatter # Pass in our custom prompt formatter\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "7de08f82", - "metadata": {}, - "source": [ - "# Generate Predictions with the Finetuned Model\n", - "\n", - "After finetuning, let's load our new model and use it to predict the response to a perturbation for a cell from our test set." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "89474061", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/2025-10-14-23_33_53_finetune_perturbation_prediction/checkpoint-500'" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "final_ckpt_path = os.path.join(output_dir, \"checkpoint-500\")\n", - "final_ckpt_path" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "38d63e84", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial'" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "save_dir" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "ebff900c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using device: cuda\n" - ] - } - ], - "source": [ - "# Load the finetuned model (it's automatically saved to csmodel.model_name_or_path)\n", - "finetuned_model = cs.CSModel(\n", - " model_name_or_path=final_ckpt_path, # Path is updated after finetuning\n", - " save_dir=save_dir,\n", - " save_name=\"perturbation_predictor_finetuned_final\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "ca22f14f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/home/sr2464/scratch/C2S_API_Testing/Cache_Dir/perturbation_tutorial/perturbation_predictor_finetuned_final'" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "finetuned_model.save_path" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "cf85b83c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'cuda'" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", - "device" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "7c36e4b1", - "metadata": {}, - "outputs": [], - "source": [ - "final_model = AutoModelForCausalLM.from_pretrained(\n", - " finetuned_model.save_path,\n", - " cache_dir=os.path.join(csmodel.save_dir, \".cache\"),\n", - " trust_remote_code=True\n", - ").to(device)" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "c828d229", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys(['train', 'val', 'test'])" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Load dataset split done in finetune() function, saved to output directory\n", - "with open(os.path.join(output_dir, 'data_split_indices_dict.pkl'), 'rb') as f:\n", - " data_split_indices_dict = pickle.load(f)\n", - "\n", - "data_split_indices_dict.keys()" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "54a9c647", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[7, 29, 33, 35, 51, 54, 65, 70, 115, 116]" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Print a few indices of test samples\n", - "data_split_indices_dict['test'][:10]" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "6a54bcda", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['sample_type', 'model_input', 'response'],\n", - " num_rows: 10\n", - "})" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Select a few unseen samples\n", - "formatted_test_ds = formatted_ds.select(data_split_indices_dict['test'][:10])\n", - "formatted_test_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "1feda129", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Inference Prompt ---\n", - "Given the following cell sentence of 200 expressed genes representing a cell's basal state, predict the cell sentence after applying the perturbation: EIF4B.\n", - "Control cell sentence: ACTB MT-ATP6 MT-CO3 MT-CO2 TMSB4X TUBA1B MT-ND4 HSP90AA1 HIST1H4C TMSB10 MT-CYB ACTG1 TUBB RACK1 PFN1 H3F3A ARHGDIB YBX1 MT-ND1 CFL1 H2AFZ B2M FTH1 HSP90AB1 CENPF UBA52 MIF MT-ND3 LDHB NCL PPIA SERF2 HNRNPA2B1 EEF1B2 CDK6 PSMA7 HSPD1 TOP2A KPNA2 GSTP1 BTF3 MT-ND2 CD3D SET CORO1A UBB ANP32B HNRNPU STMN1 EIF4A1 CCT3 EEF1G EEF2 SOX4 EIF1 BANF1 HNRNPD ADA COX4I1 MKI67 COX6C SUMO2 LCP1 SLC25A3 PKM CHCHD2 HINT1 OAZ1 NDUFS6 ENO1 TUBB4B HMGB2 MACF1 NME1 LSM4 SELENOH HSPE1 ERH NUCKS1 HMGN1 DDX5 NDUFB10 HIST1H1E GPX4 NDUFA13 GTF3A MT-ND6 PTGES3 ARL6IP1 RBMX PGK1 CTCF ATP5MC3 PSMB2 SLC25A5 PRDX5 COX7C SPTBN1 BPTF ANXA1 UBE2C PRDX1 SRSF10 NDUFA12 SFPQ EIF3G TOMM22 SIVA1 PHB2 CCT2 PA2G4 PCBP2 SUB1 CCT6A RHOA ASPM YWHAE ATP5MC1 XRCC5 SMC4 SRSF3 YBX3 HNRNPAB ATP5F1B CSDE1 SNRPB IFI16 SNRPD1 PAFAH1B3 MSN XRCC6 COX6A1 COX8A ATP5F1E ALYREF CBX3 MYL6 EIF3E RBM39 RAC1 UBE2D2 C1QBP KHDRBS1 CCT4 JPT1 RAD21 NME2 PSME2 SEPTIN7 SNU13 CKLF NMRAL1 NOP53 EIF3I EIF3D SAP18 SON HTATSF1 PSMA3 SEC61B AIP RBM8A C11ORF58 PRRC2C OSTC NDUFAB1 NDUFA4 SELENOW HNRNPA3 SRSF7 H3F3B TOMM20 SRSF9 HNRNPK CCT8 ARPC2 ATP5F1A ATP5F1C PHB EIF4B NUCB2 SSBP1 CD3G TMEM50A HNRNPM BUB3 SRSF2 PSMC5 KDM5A SNRNP25 PAK2 MYL12A NIFK SNRPF SLC25A6 KIF14 PRMT1 MTDH SRRM2 ATP5PF.\n", - "\n", - "Perturbed cell sentence:\n" - ] - } - ], - "source": [ - "# Select a sample from the test set for inference\n", - "sample_idx = 0\n", - "inference_prompt = formatted_test_ds[sample_idx]['model_input']\n", - "ground_truth_response = formatted_test_ds[sample_idx]['response']\n", - "\n", - "print(\"--- Inference Prompt ---\")\n", - "print(inference_prompt)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "96d8dd95", - "metadata": {}, - "outputs": [], - "source": [ - "# Generate the prediction\n", - "predicted_response = finetuned_model.generate_from_prompt(\n", - " model=final_model,\n", - " prompt=inference_prompt,\n", - " max_num_tokens=800 # max number of tokens to generate, ~4 tokens per gene\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "c807b03c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--- Ground Truth Perturbed Cell ---\n", - "MT-ATP6 MT-CO3 MT-CO2 MT-ND4 MT-CYB MT-ND1 MT-ND2 ACTB HSP90AA1 TMSB4X YBX1 EEF1B2 MT-ND3 RACK1 HSP90AB1 EEF1G MIF NME2 HIST1H4C TUBA1B NCL TUBB ADA ENO1 STMN1 H2AFZ PFN1 H3F3A CFL1 LDHB HINT1 HSPD1 C1QBP HSPE1 UBA52 SERF2 ACTG1 PPIA B2M CALR HNRNPA2B1 ARHGDIB GSTP1 SET MT-ND5 BTF3 CCT2 CHCHD2 NUCB2 XRCC5 PGK1 CD3D HNRNPU SUMO2 PPP1R14B HNRNPD UQCRH FDPS ALYREF SIVA1 DNAJA1 SLC25A6 ARPC2 FTL TYMS DUT COX4I1 SNRPB DDX5 PRKDC SLC25A3 PSMA7 CD3G SLC25A5 UBC ATP5F1E MYL6 ATP5F1B CCT6A PCLAF CDK6 H3F3B EIF4A1 EEF2 HMGB2 GUK1 THRAP3 HNRNPDL SERBP1 FABP5 EIF2S2 NUCKS1 HNRNPA3 HMGN1 COX7C SFPQ NDUFA13 HSPA8 OAZ1 MARCKSL1 DEK SELENOH FTH1 SRM SNRPF EIF1 DYNLL1 XRCC6 MT-ND6 RSL1D1 ANP32B EIF3E PSMA3 NDUFS5 ERH ATP5MC3 ARPC3 GLUL YBX3 FUS SNRPD1 YWHAB ATP5MC1 PRDX1 PSMA4 SOX4 NDUFAB1 PPA1 EIF5 NUDC STOML2 NME4 SRSF7 MZB1 H1FX NOP56 TPM4 NME1 NASP EIF3I ATP6V1F SF3B2 TRIR CCNI ARPC1B COX6C SLIRP SNRPC BRK1 ARPC5 ATP5MF SRSF3 CD7 HNRNPR GNAI2 CARHSP1 PPIG ATP5MG PTGES3 PFDN2 SSBP1 C9ORF16 PAICS GPX4 UBB C12ORF57 HIST1H1B ANP32A PRDX5 APRT PKM PFDN5 NHP2 SUB1 CORO1A LSM2 HNRNPC RRM2 PNN EPRS SNRPA1 HSP90B1 MCM3 CCT8 PRRC2C SKP1 RNASEH2B CIAO2B PRMT1 RAC1 SRRT HNRNPF VDAC3 ISG15 NAA10 RRP1B CCT3 MYL12B NAE1 EMC6.\n", - "\n", - "--- Predicted Perturbed Cell ---\n", - "MT-ATP6 MT-CO3 MT-CO2 MT-CYB MT-ND4 TMSB4X ACTB MT-ND1 MT-ND3 MT-ND2 HSP90AA1 HSP90AB1 RACK1 YBX1 MIF TUBA1B H3F3A H2AFZ HSPD1 NCL EEF1B2 FTH1 HNRNPA2B1 EEF1G LDHB HINT1 CHCHD2 NME2 BTF3 UBA52 EIF4A1 ACTG1 STMN1 TUBB PFN1 CFL1 EIF1 PPIA GSTP1 PRDX1 HNRNPU SET B2M HSPE1 ARHGDIB ENO1 SERF2 CD3D MT-ND5 HNRNPD HNRNPC C1QBP FTL SLC25A3 COX4I1 SLC25A5 ATP5MC3 SRSF3 PPP1R14B SIVA1 HNRNPA3 CCT3 ANP32B SFPQ EIF3E HNRNPR PSMB1 ATP5MC2 CCT6A PSMB2 NUCB2 PSMA7 PSMB3 SNRPD1 PSMB6 ATP5F1B PPA1 UQCRH SNRPB NME1 SRSF7 PSMB7 NDUFS5 HNRNPK OAZ1 PFDN5 TMSB10 ADA GTF3A ATP5F1E SERBP1 COX7C NDUFA13 PSMB5 CCT2 ATP5F1D GUK1 EIF3A NDUFB10 FABP5 PSMB3 NDUFA4 ATP5F1A NUDC POMP HNRNPDL UBB PSMB6 NDUFS6 COX6A1 SRSF2 EIF3M SNRPE PSMA4 PSMD7 GADD45GIP1 ATP5MG PRMT1 NOP53 PSMD2 UQCRB YWHAE HNRNPM PSMD1 NDUFB11 EIF3H TOMM6 PSMD11 PSMC5 SRSF9 PSMC3 NDUFA11 NOP56 EIF3I EIF3G ATP5PO SNRPF RBM8A PSMD4 TOMM22 RTRAF SRSF11 PSMC1 NDUFAB1 HNRNPAB PSMD13 PSMA2 NUCKS1 UQCR10 RSL1D1 PSMB4 TOMM5 GYPC PFDN2 PSMA3 NDUFA12 NOP10 EIF4G2 SELENOH UBE2I RBM3 PSMD12 PSMC4 HNRNPD SRM PSMB8 EIF3L RBMX PSMD6 SLC25A6 TOMM20 UBE2L3 PSMB5 RBM25 EIF3D TMA7 PNN RBM39 UQCR11 GTF3C6 PPP1CA EIF2S2 PSMC2 NUDT8 PSMD11 RBM8B RBM3B TOMM40 RAC1 TUFM EIF4B PSMB7 RSL24D1 GTF2A2 NOL7 PSMD12.\n" - ] - } - ], - "source": [ - "print(\"\\n--- Ground Truth Perturbed Cell ---\")\n", - "print(ground_truth_response)\n", - "print(\"\\n--- Predicted Perturbed Cell ---\")\n", - "print(predicted_response)" - ] - }, - { - "cell_type": "markdown", - "id": "ce20628b", - "metadata": {}, - "source": [ - "# Conclusion\n", - "\n", - "In this tutorial, you learned how to finetune a Cell2Sentence model for a custom task: perturbation response prediction. By creating a `PerturbationPromptFormatter`, we were able to structure our data into control-perturbation-response triplets, enabling the model to learn the complex transcriptional changes that occur upon perturbation.\n", - "\n", - "This approach is highly flexible and can be adapted to various experimental designs. The finetuned model can now be used for in-silico experiments, such as virtual screening of genetic perturbations or predicting the effect of new compounds, significantly accelerating the pace of biological discovery." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2f1296f4", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "cell2sentence2", - "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": "3.8.20" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb b/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb index b2f947d..76ceb5b 100644 --- a/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb +++ b/tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb @@ -1,4 +1,3 @@ -<<<<<<< HEAD { "cells": [ { @@ -1047,1053 +1046,3 @@ "nbformat": 4, "nbformat_minor": 5 } -======= -{ - "cells": [ - { - "cell_type": "markdown", - "id": "200e725e", - "metadata": {}, - "source": [ - "# Tutorial Notebook 9: Natural Language Interpretation of Single-Cell Datasets with a C2S Foundation Model\n", - "\n", - "In this tutorial notebook, we demonstrate how to generate natural language interpretations of single-cell datasets using a Cell2Sentence (C2S) model. We will utilize a pretrained C2S foundation model to generate descriptive summaries for sets of cells, treating the task as a form of natural language interpretation of complex biological data.\n", - "\n", - "This notebook will guide you through the following steps:\n", - "1. Load an immune tissue single-cell dataset from Domínguez Conde et al. (preprocessed in tutorial notebook 0).\n", - "2. Load a pretrained C2S model.\n", - "3. Format multi-cell inputs into prompts for natural language interpretation.\n", - "4. Use the C2S model to generate insightful summaries for different sets of cells." - ] - }, - { - "cell_type": "markdown", - "id": "0c85ef67", - "metadata": {}, - "source": [ - "We will begin by importing the necessary libraries. These include standard Python libraries for data manipulation, as well as specific modules from the `cell2sentence` package for handling single-cell data and C2S models." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "9b66f739", - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import json\n", - "import random\n", - "\n", - "from datasets import Dataset\n", - "import numpy as np\n", - "import anndata\n", - "import scanpy as sc\n", - "import torch\n", - "from tqdm import tqdm" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e9149a9c", - "metadata": {}, - "outputs": [], - "source": [ - "import cell2sentence as cs" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "44342a01", - "metadata": {}, - "outputs": [], - "source": [ - "SEED = 1234\n", - "random.seed(SEED)\n", - "np.random.seed(SEED)" - ] - }, - { - "cell_type": "markdown", - "id": "894938d9", - "metadata": {}, - "source": [ - "# Load Data\n", - "\n", - "Next, we will load the preprocessed single-cell dataset from tutorial 0. This dataset has been filtered and normalized, making it ready for conversion into cell sentences.\n", - "\n", - "Please ensure you have run the preprocessing steps in Tutorial 0 before executing the following code if you are using your own dataset. Make sure the file path in DATA_PATH is correctly set to your preprocessed data file." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "b727f9d5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 29773 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'assay', 'sex', 'n_genes', 'n_genes_by_counts', 'total_counts', 'total_counts_mt', 'pct_counts_mt'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", - " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", - " obsm: 'X_pca', 'X_umap'\n", - " varm: 'PCs'\n", - " obsp: 'connectivities', 'distances'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "DATA_PATH = \"/home/sr2464/scratch/C2S_API_Testing/Data/dominguez_conde_immune_tissue_two_donors_preprocessed_tutorial_0.h5ad\"\n", - "adata = anndata.read_h5ad(DATA_PATH)\n", - "adata" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "0cb6535d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "

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cell_typetissuebatch_conditionorganismassaysexn_genesn_genes_by_countstotal_countstotal_counts_mtpct_counts_mt
Pan_T7935490_AAACCTGCAAATTGCCCD4-positive helper T cellileumA29Homo sapiens10x 5' v1female219121916542.0327.04.998472
Pan_T7935490_AAACGGGCATCTGGTACD8-positive, alpha-beta memory T cellileumA29Homo sapiens10x 5' v1female204620465871.0429.07.307103
Pan_T7935490_AAACGGGTCTTGCATTCD8-positive, alpha-beta memory T cellileumA29Homo sapiens10x 5' v1female212921297248.0337.04.649559
Pan_T7935490_AAAGCAATCATCGCTCCD8-positive, alpha-beta memory T cellileumA29Homo sapiens10x 5' v1female126212623927.0305.07.766743
Pan_T7935490_AAAGTAGCAGTCACTAgamma-delta T cellileumA29Homo sapiens10x 5' v1female224822486574.01083.016.473988
\n", - "
" - ], - "text/plain": [ - " cell_type tissue \\\n", - "Pan_T7935490_AAACCTGCAAATTGCC CD4-positive helper T cell ileum \n", - "Pan_T7935490_AAACGGGCATCTGGTA CD8-positive, alpha-beta memory T cell ileum \n", - "Pan_T7935490_AAACGGGTCTTGCATT CD8-positive, alpha-beta memory T cell ileum \n", - "Pan_T7935490_AAAGCAATCATCGCTC CD8-positive, alpha-beta memory T cell ileum \n", - "Pan_T7935490_AAAGTAGCAGTCACTA gamma-delta T cell ileum \n", - "\n", - " batch_condition organism assay \\\n", - "Pan_T7935490_AAACCTGCAAATTGCC A29 Homo sapiens 10x 5' v1 \n", - "Pan_T7935490_AAACGGGCATCTGGTA A29 Homo sapiens 10x 5' v1 \n", - "Pan_T7935490_AAACGGGTCTTGCATT A29 Homo sapiens 10x 5' v1 \n", - "Pan_T7935490_AAAGCAATCATCGCTC A29 Homo sapiens 10x 5' v1 \n", - "Pan_T7935490_AAAGTAGCAGTCACTA A29 Homo sapiens 10x 5' v1 \n", - "\n", - " sex n_genes n_genes_by_counts \\\n", - "Pan_T7935490_AAACCTGCAAATTGCC female 2191 2191 \n", - "Pan_T7935490_AAACGGGCATCTGGTA female 2046 2046 \n", - "Pan_T7935490_AAACGGGTCTTGCATT female 2129 2129 \n", - "Pan_T7935490_AAAGCAATCATCGCTC female 1262 1262 \n", - "Pan_T7935490_AAAGTAGCAGTCACTA female 2248 2248 \n", - "\n", - " total_counts total_counts_mt pct_counts_mt \n", - "Pan_T7935490_AAACCTGCAAATTGCC 6542.0 327.0 4.998472 \n", - "Pan_T7935490_AAACGGGCATCTGGTA 5871.0 429.0 7.307103 \n", - "Pan_T7935490_AAACGGGTCTTGCATT 7248.0 337.0 4.649559 \n", - "Pan_T7935490_AAAGCAATCATCGCTC 3927.0 305.0 7.766743 \n", - "Pan_T7935490_AAAGTAGCAGTCACTA 6574.0 1083.0 16.473988 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.obs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "78b71e4d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 29773 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", - " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", - " obsm: 'X_pca', 'X_umap'\n", - " varm: 'PCs'\n", - " obsp: 'connectivities', 'distances'" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.obs = adata.obs[[\"cell_type\", \"tissue\", \"batch_condition\", \"organism\", \"sex\"]]\n", - "adata" - ] - }, - { - "cell_type": "markdown", - "id": "c2be1277", - "metadata": {}, - "source": [ - "# Cell2Sentence Conversion\n", - "\n", - "In this section, we will convert our AnnData object into a format that the C2S model can understand. This involves transforming the gene expression data of each cell into a \"cell sentence,\" which is a string of gene names ordered by their expression level. We will also prepare the vocabulary from our dataset." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "842861e5", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 29773/29773 [00:09<00:00, 2995.86it/s]\n" - ] - }, - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", - " num_rows: 29773\n", - "})" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata_obs_cols_to_keep = adata.obs.columns.tolist()\n", - "\n", - "# Create Arrow dataset and vocabulary from AnnData\n", - "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", - " adata=adata,\n", - " random_state=SEED,\n", - " sentence_delimiter=' ',\n", - " label_col_names=adata_obs_cols_to_keep\n", - ")\n", - "arrow_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "ac96a758", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'cell_name': 'Pan_T7935490_AAACCTGCAAATTGCC',\n", - " 'cell_sentence': 'RPLP1 ACTB EEF1A1 HSP90AA1 TMSB4X B2M FTH1 KLF6 HSPA1B MALAT1 RPS12 HSPA8 RPL13 MT-CO1 ATF3 MT-CO2 RPL41 TPT1 MT-CO3 RPS19 HLA-B RPL10 RPS4X RPL28 MT-CYB DUSP1 RPL30 MT-ND4L RPS15 FOS RPL34 RPS2 RPLP2 MT-ND3 RPS18 RPS8 TRBV7-2 RPL32 RPS3 ANXA1 RPL11 HLA-C RPS27 ACTG1 UBC RPL3 RPL37 RPLP0 MT-ATP6 JUNB RPS28 RPL18 UBB MT-ATP8 RPS14 RPL39 PFN1 GAPDH HSPA1A RPL18A SRGN RPS27A RPL26 RPL19 RPS15A HLA-A DNAJB1 RPS3A CREM RPS13 MT-ND1 RPL21 RPS25 BTG2 RPL35A FAU RPL8 RPL7A RPS24 RPS6 RPS16 RACK1 NFKBIA RGS1 RPL29 CALM1 RPL9 RPL37A MT-ND5 TNFAIP3 RPS23 IL7R RPL36A PTMA NFKBIZ UBA52 EIF1 CRIP1 CORO1A RPL14 HSP90AB1 RPL10A CXCR4 RPL4 EEF1B2 RPL36 RPS9 RPL27 NACA VIM H3-3B RPS7 HSPH1 ATP5F1E HLA-E RPL17 RPSA MYL12A RPL12 CD69 TAGAP RPL35 RPS29 RPL6 SARAF ZFP36L2 MT-ND4 ARHGDIB BTG1 RPS21 EEF1D PNRC1 EEF1G HSPA5 FYB1 CD3E IFITM1 RNASEK EEF2 MT-ND2 FTL S100A4 JUN IFITM2 CYTIP OST4 LAPTM5 RPL36AL PLAAT4 PFDN5 SAMSN1 DNAJA1 EIF4A1 FXYD5 HSPE1 CTLA4 IL32 RPL24 CFL1 SAT1 RPL13A NPM1 NDUFV2 SRSF7 ITM2B POLR1D CCNI CALR ZFP36 COX7C PTPRC GADD45A CD3G RAC2 MYL6 UBE2D3 CCL20 RPS5 RPL22 TOMM7 RPL15 C12ORF57 LSP1 SON H4C3 RPL23A RPL31 DDX5 EVL AHR SERF2 STK17A CD6 PTGER4 OSTF1 OAZ1 TMA7 PHLDA1 COMMD6 PPIA TMSB10 RHOH TUBA1B KTN1 PDIA3 DUSP5 BTF3 SSR4 ATP5MC2 S100A6 CEBPD TRAV13-2 STAT1 HSPB1 PSMB9 RPL38 HNRNPA2B1 FLT3LG CSTB CDK2AP2 CSK MIF MCL1 PSME1 TXNIP RHOA HNRNPA1 UBL5 PTGES3 PDCD4 SLC2A3 ERCC1 SNHG29 NFKBID SRP14 ARPC1B NR4A2 CMTM6 CD44 ITGA4 GNB2 TRAV19 BHLHE40 HMGB1 ARPC3 TRIR PRKCH NME2 KLRB1 CLIC1 ANAPC16 NCOR1 COX5B MYL12B SAP18 RHOB TCF25 SOD1 SRSF9 FOSB PCBP1 CD96 TBC1D10C CD164 CD3D ACTR2 COX4I1 SH3BGRL3 KMT2E HSPD1 PABPC1 SPCS2 SERP1 TNFRSF1B TAGLN2 PCBP2 RPL5 LDLR YWHAB CSRNP1 COX8A MYADM TRMT112 ATP5MG GABARAP ELF1 PRR13 RPL22L1 WAKMAR2 SIT1 GADD45B RPS17 S100A10 RBBP4 HNRNPDL CD2 UQCRQ COX6B1 RGS2 CHCHD2 TAF1B RPL27A TAP1 MTDH CD99 ARF1 TBCA TMEM14B HNRNPA0 RPS11 SEC61A1 RSRP1 TUBB ACIN1 HNRNPUL1 OXNAD1 LMO4 CTSH RBM8A RGL4 NFU1 AP1G2 TSC22D3 CASS4 CCNH RPS26 PIK3R1 SH3KBP1 SSBP4 TPR GADD45G ZFAS1 COTL1 BCL7C MZT2A LAT FUS SDF2L1 KRTCAP2 MRPL41 CENPX SETD5 TMC8 COX17 DNAJB4 CDKN1B ODC1 ACAP1 ANXA6 CYBA SUMO3 TMBIM6 TMEM259 CD37 PRDX2 UBE2D2 BTG3 PARK7 CD247 TMEM258 HNRNPAB SPOCK2 SEPTIN1 LAMTOR5 RNF11 SNX5 SASH3 PPM1G ARF6 EIF5A IL4I1 RBM3 RSF1 SLA CALM3 SNRPB SHISA5 ARID5B KXD1 PTPRCAP GBP1 STN1 NSA2 ATP1A1 LCK PSMB8 PSMB3 HNRNPC RNF167 RESF1 ACTR3 CKLF CD52 RPS27L GSTK1 GIMAP7 DCXR RGS14 VASP PBXIP1 GOLGA4 RPL23 YWHAQ SNHG16 TAOK3 IGBP1 DOCK10 SRRM1 PSMC3 IKZF3 AHI1 RPL7 TMEM87A EIF5 MED1 ANKRD12 IWS1 SLC25A6 TUBA1C LRRC41 SEC11C DLST VMA21 MKNK2 RALB THUMPD1 DBF4 RHEB WASHC3 VRK2 SUPT4H1 FADD CHD1 CAPN1 TMEM179B CKS2 RGS10 EIF4E BPTF RNMT DDX39A GADD45GIP1 DYNLL1 SF3B2 CDKN2AIP RAP1B ACTN4 ABRACL MOB4 METTL23 ITSN2 MTF2 VSIR PER1 COX7A2 COX14 IPCEF1 YWHAH CYRIB MOB3A SP2 BCL11B STUB1 RNF213 PRKRA EDF1 PRPF38B RHOG BAG1 ATOX1 CACYBP MAP4K1 PPP1R2 PAXX ADA NDUFA12 WAC ELK3 PRRC2C MUS81 CCT4 ARL5B RALBP1 FBXW11 LCP1 LEPROTL1 PDCD10 HNRNPR NR3C1 PPP4C BATF ABLIM1 PSMA2 TRAT1 RUNX3 CIB1 ARPC2 ABI3 UGP2 NDUFAB1 HCLS1 DERL1 RAB5A INSIG1 CNBP CHROMR DSTYK DPP4 TOMM6 PDE4D LUC7L2 JUND ARHGDIA CEMIP2 POLE4 ANXA11 PLEKHB2 SDCBP MANF FAM83D IMP3 TMCO1 SUCLG1 MBD2 NDUFA10 PDIA6 S100A11 DNPH1 TARDBP PTDSS1 RP11-25K19 LPXN FYTTD1 RORA NASP ATP6V1F RIPK2 IDI1 RASSF7 MT-ND6 RWDD1 CYB5R3 MAZ PIM1 PSMA3 GPX4 PACS1 TNIP1 PLEKHF1 STXBP2 MSMO1 UQCR11 EPB41L4A-AS1 TMIGD2 PATL1 COX6A1 CCND3 TUBB4B OCIAD2 UBE2V2 ASMTL MAP3K8 FERMT3 SH2B1 ACP5 RPS6KB2 GABPB1-AS1 MTRNR2L12 ZFAND2A EIF3D ATP5PB NEDD8 NDUFA1 C19ORF25 CYB561D2_ENSG00000114395 PPP1R18 SYF2 PIGT SLC25A3 KHDRBS1 GIMAP4 NAXE HMGN1 RGS19 SUMO1 YWHAZ ERN1 LRRFIP1 NCF1 GALNT11 PSMG2 SNRPA1 IFNGR1 ENSA LAMTOR4 TBRG1 LINC-PINT PSMA7 SH2D2A HCST GUSB SEC61B TAX1BP1 RNF149 GNG5 PIP5K1A SIGIRR ATP6V1H RXYLT1 TRAPPC2B STK4 GPR174 CLEC2B CDC5L MLEC SQSTM1 GNAS DAXX ADAR NRIP1 TPI1 ITM2C NOSIP HADHA GTF2B ATP5IF1 ATP6V0B VEZF1 MYBL1 TOMM5 UQCRFS1 PDE4B ELL MRPL18 TRAC PIGBOS1 PPIB MDH2 PMVK PGAM1 PEX2 RPA2 FBXW5 MICOS13 CYBC1 ELOB PSMB4 COX6C GTF2I CHMP4A ALOX5AP SSR3 SELENOF AIP UXT TBCB SKAP1 RBM4 NDUFA9 DNAJB11 ATP5MK REX1BD GATA3 MVP GIMAP5 DNAJC2 SHKBP1 CAP1 SSBP1 SUZ12 SNHG6 LTB HECA WDR83OS DUT ANXA2 RRAGA PPP1R12A TAPBP DOK2 DYNLT3 RBPJ ATP6V1G1 CD40LG OCIAD1 TCEA1 ATM SLC44A2 OGA HNRNPK PPP2R5E NDUFA4 PLAUR NT5C3A RBL2 PHTF2 ZFAND5 CCR6 BCL3 GYPC SPTY2D1 MBP AKAP9 CD83 HNRNPF RAC1 SSR2 SMARCC2 MRPS21 SRSF3 DDX21 NDUFC1 BST2 FSD1 TRIB2 SF3B6 GDI2 HLTF APBB1IP LY6E NDUFB4 NAA38 FKBP1A PSMB10 FDPS MBNL1 UQCRB TMED2 H1-10 RO60 CEP57 CDKL3 CAPNS1 GIMAP1 EZR HOXB4 JAGN1 EIF2S2 DNAJB9 KCTD20 ARGLU1 EWSR1 SH3GL1 EIF3F RABGGTA MEA1 MLLT3 SARNP UBAC2 TRA2A ARL6IP1 GPI GUK1 DPH3 TGFBR2 ASB2 SRP9 GNAI2 RAB5IF PPIH EIF4A2 UBQLN1 GPR65 RASAL3 NDUFB6 RPN1 HNRNPA3 GBF1 OGG1 LCP2 DESI2 DUSP2 MGST3 CCDC18-AS1 CD53 POLM RTRAF ME2 PHAX ATP6AP1 RDH11 TCERG1 ACTR8 SLC1A5 DSE SLC25A39 FDFT1 CIAO2A LATS1 WDR33 CCDC107 MARCHF7 FAM174C LRPAP1 COG6 IL10RA MNAT1 CLIC3 TUSC2 NAT9 FAM13B EPG5 FKBP11 CREB3 ARHGAP45 MRPL9 MGA MIDEAS PHF20 CHD9 RCE1 VDAC2 EEF1E1 SSB GBP5 NMRK1 CCT8 SCAP ACER3 VAMP8 TALDO1 PHGR1 TC2N GRID2IP EIF2AK1 TOLLIP TBC1D10A C17ORF100 NFRKB CCDC137 E4F1 XRCC5 FCMR PGPEP1 DGCR6L CHURC1 OFD1 MAP4 PLEKHA2 AMD1 MORF4L1 IER5 DCTN2 CTDSP1 DDX6 AHCYL1 PNKD ELOVL1 FXR1 SAPCD1 SELENOT UBE2L6 PMM2 RNF113A PGRMC2 CPSF6 ZNF267 MRPL50 IL16 CREBL2 ASXL2 NUDCD3 ZNF445 C3AR1 CCR5 DGKE RUNX1 AKAP11 RP11-562I5 ARIH1 PPP1CB NDUFAF3 MRPS5 ACTR1B TPD52 SF3A2 CLTC TMEM33 NDUFA5 HMGXB4 PPP1R21 RC3H2 ZNF580 PRKCSH GZMM SEC13 CTNNA1 VPS18 SYNGAP1-AS1 MAPRE1 ZC3H8 DSTN MAN2B2 MGAT4A PAK2 CRY1 LSM7 ZC3H6 TMEM230 CPQ PSMD3 TIMM17A TYMP ST6GALNAC6 PHB2 KDELR2 LAMP2 NUMB RALY ADAM8 R3HDM4 DNAAF2 ADPRM CCSER2 THRAP3 KIDINS220 RBM15B DEF6 ADNP POLR1E IQGAP1 POFUT2 EIF3K NOL7 NMUR1 NOM1 GNPDA1 PKM CWC25 IGF2R ATP2B4 GPS1 LRP10 CA10 ERI3 SMAD3 ANP32B COX7A2L EHBP1 CHUK H2AZ1 LPIN2 ASAH1 MRPL33 BCL2 DNAJC1 USO1 SUMF2 CHCHD3 NAA20 TMEM60 IER3IP1 FLII YBX1 LAIR1 MESD TSC22D1 SF1 TMEM273 PLCG1 NMD3 TMEM18 ABHD14A SLFN5 ENTR1 CHMP6 IRF2BP2 CHCHD5 HTATSF1 RPS10 LSM14A SUPT7L PEX26 YJU2 HDDC3 CFDP1 SELPLG ENO1 KDM5A MTLN ZNF706 ERVK3-1 DCP1A DBNDD2 TAX1BP3 SPINK4 RNF31 NEPRO SHFL PSMD8 IL17RA CHST14 MPC1 GLOD4 BICRAL SMIM26 KIF5C PRKAR1A TENT5C NPRL2 TTC9C RPUSD3 SSH1 ARHGAP35 RSBN1 ECHDC2 G3BP2 PRR5 SMG9 SUPT3H ATP2A3 SIN3B LSM12 PTEN ZNF93 NONO SRRM2 ITFG1 C21ORF91 HINT1 GOT1 C1QTNF1 AZIN1 MZT1 LAP3 NDUFB8 NDUFA13 FRMD4B LYRM2 IL21R PARP12 SCMH1 PBRM1 HAUS4 RAB4B FLJ40194 HIKESHI NR1D1 MFSD8 SRSF1 SMIM30 XRN2 SAMD4B SEM1 CAPZB PIAS4 IKZF1 EIF3I AGTPBP1 MZT2B C1ORF122 MUTYH WDR61 DDX39B CCNDBP1 ZNF816 PFDN2 POLR2F ANO6 NDUFS6 CTNS ATP11B SIVA1 EIF4E3 CTSC SMC4 CDC42SE2 FAM131C PLPP6 TRPC4AP MTMR14 GABARAPL1 FAM133B RFNG EIF2B1 LSM1 ISY1 EIF3G ORAI2 FAM53B SEPTIN2 HTRA2 SEPTIN6 KAT7 MBD4 CAPZA2 WDR20 NDUFB7 TWF2 COMMD5 GPR68 SPPL3 TMEM59 NCL PJA2 SDHA SLMAP CBX3 TMEM161B-AS1 PPOX ACBD3 GOLGA7 GTF2H1 MAP3K2 COA6 PHF5A COPS7A NAA10 SNX14 CUL1 ALG13 TNIK STARD3 LINC00892 SNAI3 RABAC1 USP42 NDUFA3 DDX58 PSMC6 RBCK1 HNRNPH3 ZFAND6 SDHD CHCHD10 PUM1 LDLRAD4 TCHP CNOT11 KIF1C SEC61G TACC1 PSMD6 NIPBL DAPP1 RAB2A TRIM5 LMNB2 SUPT6H AP3S1 CLK1 NSUN2 NUP88 PPA1 UMAD1 SETD9 DCAF15 ANXA2R TMEM9B EGLN2 MRPS18B PSD4 GTDC1 SUCO BUD31 IER2 UPF3A PINX1_ENSG00000254093 NUDC TAF7 UTP15 PTPMT1 PSME2 MALT1 PSTPIP1 TSPYL1 CTSD HIGD2A SBF1 LINC00667 FEM1A RAB5C TAF2 SHOC2 RASL11A AMZ2 TRIM65 ATP6V0E1 HEBP1 PSMD1 NDUFAF8 CORO1B MRPL34 UBN1 RAE1 SPINT2 SOCS1 TRIM52-AS1 TFDP1 TES YIPF2 STX5 BZW1 PDCL3 NOLC1 TPM3 INTS11 RAB35 COQ10B ZNF480 C1D THAP4 EBAG9 FOXP1 SLC30A6 NUS1 MRPS24 PPP2CA USP4 C9ORF16 MSH2 UQCRC1 SLC38A1 ACO2 WASHC5 TXLNG PHF20L1 RAB6A SERINC1 YTHDC1 MIF4GD C1GALT1 KRR1 NDFIP1 GMFG DCAF8 SNX6 PAIP2 PLAA SRP19 RAD21 TECR OTUB1 CLK3 BNIP2 NEK9 COPE RAB9A RMC1 JOSD2 MAP3K1 RNF144B ADGRE5 UBA5 NLRC3 LYPLAL1 SURF6 PDE9A ZNF720 C17ORF107 SPPL2A OPTN LACTB DNAJA2 CAMK4 PLP2 ARMC6 IDH2 FUNDC2 SNHG3 CAPG TMEM106C DR1 PGGHG TUT7 CYB561D1 EIF3E FURIN VPS26B APBB1 NTAN1 ATP5MF MAX MRPL14 ATP5ME ORAI1 SEC62 TNFRSF1A HTT EIF2AK4 SCAPER POLB FAM204A RRP12 ABHD5 IMPDH1 TAF1D TDG IMP4 SMC6 TRIM28 FAS ILK PPP1R16B TSR3 NOP56 EIF5B CUTA GLO1 PPP3CB CENPK MTRR ITGAE GOLGA3 GFER EPSTI1 THEMIS TRIAP1 HSD17B7 TSTD3 ANKRD39 PIP4K2A MTFP1 FAM222B SRFBP1 HOXB2 TRAPPC5 SRSF8 HECTD1 CCAR1 XKR8 RBM26 ISCA1 TRBC2 UBE2B TIMM8B RPUSD1 SAT2 FAM102A ST6GAL1 METTL9 C2ORF68 PERP SNU13 ANKZF1 CBX5 GPN1 COMMD8 EGLN1 HERPUD1 SENP6 SLC38A2 AARS1 GNL2 G3BP1 GPR108 PSMA4 SP100 MFSD10 TMEM70 QRSL1 DAD1 RPS19BP1 SNHG1 CSDE1 TAF4B ASF1A N4BP2L2 RNF138 FBXL5 JAK1 NCLN RAB11B PPP1CA ITGB2 KDELR1 PSMB1 MTX2 SLC35E2A NDUFS8 HAGH PIGW IVNS1ABP SDHC POLDIP2 EIF4G1 ANKRD36 SEPTIN7 CSNK1D PSMF1 TM9SF4 GAB3 MYL6B HNRNPL WIPF1 GATAD1 RFFL PRKCQ-AS1 GTPBP10 INO80D IFITM3 GAS5 WASHC1 CTNNAL1 PTGER2 USP33 ARRB2 ARMCX6 GMIP UMPS TRIM22 DDX41 SFPQ RBM25 MRPL38 CNP FAM193B MAP3K11 WDR74 PIGC CDC37 PPIP5K2 TRMO AGTRAP JMJD8 ARID5A ALKBH7 CYTH1 SET PAF1 SNHG5 FAM174B ADI1 SUDS3 CDCA7 GTSF1 MTCH1 TGIF2 MLX PYGO2 EIF2S1 DNPEP IL23R RPA1 CDC37L1 GYG1 ANP32A SRSF2 RNASEH2B WDR44 ZPR1 GIPC1 RRM2B ILVBL ARL2BP BRK1 YIF1A CEP164 DPY30 NUDT7 PPP2R1A R3HDM1 MSN PSIP1 HMGN4 CCDC152 STOML2 EEF1AKMT2 H2AZ2 CHST12 CHFR FKBP15 SPNS1 APH1A NR4A3 CNOT9 GPSM3 TESK1 CDK5RAP1 TNFAIP1 FAM118B ZBTB7A PCED1B-AS1 MRPS18A BUB3 ICMT DDIT3 DNM1L DCTN4 PPIG CCDC91 LZIC CHD2 BIRC2 AHSA1 ARAP2 COMMD10 NUCKS1 ASAP1 DCTPP1 ETFDH NAA80 STAU2 CCNL1 CASP3 CCDC174 PRNP APOA1-AS PPP1R11 SRP68 C1ORF43 RASSF1 MYD88 AKAP13 SLC25A5 ERH UBE2I ATP5PD ORC3 NUP37 TTC31 WBP2 PDE7A KPNB1 ETFA STK25 PJVK COX19 ATP5MC3 PPP2R2A MDH1 PSMB6 GTF2E2 B3GNT2 TSC22D4 GPD2 MBIP ZFR JTB GPRIN3 LPIN1 SLC35A1 NXT1 KLHL22 DYNC1I2 AP1S1 PPP1R15B SMIM15 TMEM65 HAUS3 KLHL28 MRPL20 MVK ATR MIB2 YPEL3 SCOC WASHC2C SPRY1 LCLAT1 CCDC25 SLC43A3 CIAO3 WBP11 TRIM4 C17ORF49 DTX1 VAMP5 ZSCAN16-AS1 TNFSF13B ARHGAP15 CISH DCP2 GRPEL2 PHB AASDHPPT PUM2 ISG20 PFKM SLC2A1 NBL1 TMED4 COPS3 SRSF11 ZNF710 POMP TTC14 ZNF414 PISD TMEM219 MIR23AHG COQ4 OXA1L DNAJA3 KMT2A MAGOH LYPLA2 WSB1 POLR2B AKIRIN2 PSMB2 UIMC1 DDX18 TCOF1 TNFRSF14 STARD3NL CELF2 NABP1 PTP4A2 LRRC59 TMEM167B CAMK2G SLC4A1AP EIPR1 NUCB2 MED6 VEZT SP4 ARL3 USP12 ARHGAP9 VMAC FIP1L1 RP11-316M20 ADH5 TMC6 IRF1-AS1 LIG4 SNX1 MACF1 GNL1 TPM4 RMND5A LPAR6 DNAJB2 NOP53 CDK2AP1 FIS1 PITPNM1 SF3B4 SNAP47 S100PBP C4ORF33 CHST11 RGS18 C7ORF31 PSMD4 EFCAB7 TTC39C ANXA5 KRI1 FAM214B DUSP12 NR2C1 CBLB UNG LSM8 MYO9B GLMN RALA GTF3C6 ISCA2 DNTTIP2 SELENOK MRPS36 KPNA3 THRA PTS DUSP6 VTA1 PPARG SEPTIN9 UBE2N FRY BCAS2 CAMKMT SAMHD1 GBP2 TMEM50A STAT5A IL17A PCYT2 ISG15 MAPK3 PDCD4-AS1 TIAL1 RTF1 CSNK2B RBM17 LPCAT4 ST13 CNBD2 TMEM184B RNPC3 ARCN1 SMAP2 BLOC1S1 NAMPT ZNF597 EMG1 SLC66A3 HDLBP C11ORF58 SH3BP1 SMARCB1 RP11-726G1 ZNF564 IFI27L2 ATG3 C6ORF226 REL GIMAP6 OLFM2 OGFR BAZ1A RAB7A EIF3L TBC1D20 SDHAF2 PARP10 GAK FYN TBXAS1 PRDM1 FAM241A TMEM263 SRPK1 CD2BP2 SERGEF SURF4 MTERF4 PPP1R10 IRF9 USP14 ZFAND2B AK3 CYTH3 PEBP1 PLIN2 NARF ICAM2 ZRSR2 HELZ C14ORF119 DCAF5 RBM42 ITFG2-AS1_ENSG00000258325 ZNF524 CRNKL1 FASTK UBXN1 MYO1G QTRT1 FLOT1 DNASE2 STK40 USP47 RFLNB ZFYVE28 FHL1 TATDN2 SLC25A25 ATP6V1B2 GSAP MRPL10 PSMD11 ZNF821 RANBP9 TIPRL TMED10 EIF3M HMGN2 UHMK1 TRBV30 EMP3 HPS6 TTC17 OSBPL8 COMT ERP29 GRPEL1 ZNF595 ROGDI RAD23A LYSMD2 ANKRD44 FRMD8 SRSF10 BCL2A1 TBC1D31 ALDH9A1 CHMP1A GABARAPL2 RPS20 MRPS2 CAST TMEM200A H4C2 ATRAID CRYBG1 CRY2 OSBPL7 TRAPPC1 POLR2K TESMIN UBE2D1 GNAI3 SLC39A6 HMGCS1 TMEM138 TMEM223 CHP1 ATP5MJ MSRA SQLE ATRX ZNF207 PPP1R15A DNAJC3 SNX3 FBXO9 FAM162A BTF3L4 NKIRAS1 PRDX6 EHMT1 SYS1 USP36 STX4 TMED7 NR4A1 GNA13 LINC00299 ST3GAL5 IDH3A NAA16 SLC38A10 CRYBB2 B4GALT1 METTL26 MRPL54 TRAF3IP2 DTX3L NDUFA6 NDUFAF4 SUCLA2 CALHM2 GTF2IRD2B RP11-706O15 IK MAGI3 TCTA PBDC1 BRD7 IRF1 P2RY10 CTBS CUX1 PRKD2 PGK1 BCLAF1 IRAG2 CIAPIN1 TNFRSF25 SNRNP200 IL2RG PSMA6 UQCRC2 RTF2 SLC35C2 GNG2 ZBTB22 MEF2A NOP10 LY9 MAP2K2 COMMD1 TMEM203 VPS29 SOD2 CITED2 FLI1 FMNL1 MRTO4 RETREG2 FGFR1OP2 RNF41 UTP4 TKT DHX36 ID2 TMEM245 ERP44 ESF1 BAG3 NDEL1 DAP3 HM13 PTGR2 ZFAND3 UCP2 BIN2 MCF2L2 PHKB SUB1 PDE3B CEP250-AS1 RNH1 WDR1 FAM117A CAMTA2 UGCG LINC00294 PHF14 PTPN22 KATNBL1 NT5DC1 TRIM38 ZNF780A C19ORF53 SNRPG TDP2 EIF4H TMEM140 ZCCHC17 ANKLE2 CDS2 EPHB6 CCDC90B ATAD3C COL18A1 FBP1 AHCY AFTPH ZNF432 HSPA9 CMSS1 FGD3 ANXA7 SLC25A13 RNF5 KRT10 KDM2B-DT ATP5F1D SCAMP3 KIF2A SHMT1 MRPL57 CD5 MLH1 ACOX3 ZNF593 TTI2 TRAPPC10 SRP72 CXCR6 COPS5 TET2 HEBP2 OGT ANKRD13D CEBPZ MRPL23 UBE2V1 AP2M1 SLC39A4 LLGL1 DLD ACAA2 SCAMP4 PARP8 CXXC1 MAD2L2 GIT2 OSGIN2 FAM219A ERLEC1 PTPN7 TMEM41B SERTAD3 TCF7 ARPC5 NCBP2AS2 ZNF211 SNRPB2 B9D2 ANKRD27 TIPARP RAB1B SRM PARP16 EIF4EBP2 GDI1 ARPC5L CEACAM21 IVD EXOSC4 KDM6A STARD7 JAK3 CBR1 ARL6IP5 STK26 UFM1 ARHGAP18 ESD ISOC2 HCFC1 RING1 PRELID1 MGME1 NDUFC2 CELF1 PNP IFT27 KBTBD2 TUFM TSTD1 CISD3 C17ORF67 BUD23 SCRN2 CHCHD7 FARSA RP11-29H23-1 LINC02481 TPP1 THYN1 ARHGEF1 GCLM PRPF39 TRAPPC6B SLF1 SMIM3 EVI2A AZIN2 ASH1L API5 COG2 SLC25A22 CHD4 WRAP73 CDC26 UBE2L3 EPC1 ATP2B1 CCAR2 RRN3 UBA1 CSNK1A1 CASP8 PELI1 CNOT2 SRP54 VAPA MRPS33 NDUFB11 NAF1 UBE2G2 DVL3 TLE5 CALCOCO2 UQCR10 SIRPG COX7B NDRG1 EIF2S3 H3C4 SMCHD1 RAN MAPKAPK5-AS1 TSG101 HAX1 ANKDD1A DCTN3 CD55 PSKH1 PET100 IMMT SRGAP2C H3-3A PIGH RBM48 FAM177A1 TEFM FBXL4 MID1IP1 PRR5L SLC25A11 NGDN NCAPD3 SLC9A3R1 CDIP1 GRK6 SDF4 DENND2D CASP7 EFR3A NFAT5 PRELID3B TEX30 CIRBP CSNK1G1 MCRS1 CHMP2B TMOD3 PRKX POLR2C NSFL1C POLR1H TAP2 PIANP ARL6IP6 RIPK1 TDP1 SCAF11 SNRPN ZNF335 USP3 UBQLN2 ARMCX3 HSDL1 RSU1 TXNL1 TMEM101 BAD KIF5B AP1AR FAM104A GBP4 AC058791 NDUFB1 DPP7 NDUFB2 RANGAP1 SETX MAF1 NME4 TRGV10 TACC3 AP5Z1 PITPNB EDEM1 CTD-2095E4 ANKRD28 MINDY2 YPEL4 IGHV4-34 TRIM44 ARL6IP4 GART RAD18 SF3B5 BZW2 ECD ZYX HECW2-AS1 CNTRL RECQL PARP9 UPP1 PYCR2 ARHGAP30 TBC1D22B RASGRP1 STIM1 ZNF263 ZNF230 LDLRAP1 PDCD2 FOXO1 UNC119B RNF114 YPEL5 IFNGR2 PRRC1 EIF4B PDXK RAB8B RICTOR ARL8A ESCO1 RBM38 PPIF GMPS HDDC2 FBXO42 PTP4A3 SERPINH1 TRIM69 WTAP PEMT VPS72 WAS PPP4R3A CDV3 CETN2 VAC14 TRIM21 DAZAP2 ARF5',\n", - " 'cell_type': 'CD4-positive helper T cell',\n", - " 'tissue': 'ileum',\n", - " 'batch_condition': 'A29',\n", - " 'organism': 'Homo sapiens',\n", - " 'sex': 'female'}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "arrow_ds[0]" - ] - }, - { - "cell_type": "markdown", - "id": "61148588", - "metadata": {}, - "source": [ - "# Group cells into multi-cell samples\n", - "\n", - "Here, we group together cells with the same tissue label" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "d2d9b29a", - "metadata": {}, - "outputs": [], - "source": [ - "def get_multi_cell_groupings(hf_ds):\n", - " batch_tissue_to_cell_indices_dict = {}\n", - " for sample_idx in range(hf_ds.num_rows):\n", - " # Load sample, get batch sample and tissue type\n", - " sample = hf_ds[sample_idx]\n", - " batch_sample = sample[\"batch_condition\"]\n", - " tissue_type = sample[\"tissue\"]\n", - "\n", - " # If new batch sample and tissue type combination is found, add to dictionary\n", - " if (batch_sample, tissue_type) not in batch_tissue_to_cell_indices_dict:\n", - " batch_tissue_to_cell_indices_dict[(batch_sample, tissue_type)] = []\n", - "\n", - " # Add sample index to dictionary\n", - " batch_tissue_to_cell_indices_dict[(batch_sample, tissue_type)].append(sample_idx)\n", - " return batch_tissue_to_cell_indices_dict" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "89acb513", - "metadata": {}, - "outputs": [], - "source": [ - "batch_tissue_to_cell_indices_dict = get_multi_cell_groupings(arrow_ds)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "a5edfe42", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(batch sample, tissue type): [list of cell indices with this combination]\n", - "('A29', 'ileum'): [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n", - "('A29', 'lung'): [346, 347, 348, 349, 350, 351, 352, 353, 354, 355]\n", - "('A29', 'thoracic lymph node'): [3547, 3548, 3549, 3550, 3551, 3552, 3553, 3554, 3555, 3556]\n", - "('A29', 'mesenteric lymph node'): [8117, 8118, 8119, 8120, 8121, 8122, 8123, 8124, 8125, 8126]\n", - "('A29', 'bone marrow'): [10955, 10956, 10957, 10958, 10959, 10960, 10961, 10962, 10963, 10964]\n", - "('A29', 'skeletal muscle tissue'): [12365, 12366, 12367, 12368, 12369, 12370, 12371, 12372, 12373, 12374]\n", - "('A29', 'liver'): [12381, 12382, 12383, 12384, 12385, 12386, 12387, 12388, 12389, 12390]\n", - "('A29', 'spleen'): [13041, 13042, 13043, 13044, 13045, 13046, 13047, 13048, 13049, 13050]\n", - "('A31', 'spleen'): [16664, 16665, 16666, 16667, 16668, 16669, 16670, 16671, 16672, 16673]\n", - "('A31', 'ileum'): [18835, 18836, 18837, 18838, 18839, 18840, 18841, 18842, 18843, 18844]\n", - "('A31', 'omentum'): [18868, 18869, 18870, 18871, 18872, 18873, 18874, 18875, 18876, 18877]\n", - "('A31', 'lung'): [18898, 18899, 18900, 18901, 18902, 18903, 18904, 18905, 18906, 18907]\n", - "('A31', 'liver'): [20155, 20156, 20157, 20158, 20159, 20160, 20161, 20162, 20163, 20164]\n", - "('A31', 'thoracic lymph node'): [22211, 22212, 22213, 22214, 22215, 22216, 22217, 22218, 22219, 22220]\n", - "('A31', 'caecum'): [25214, 25215, 25216, 25217, 25218, 25219, 25220, 25221, 25222, 25223]\n", - "('A31', 'bone marrow'): [25285, 25286, 25287, 25288, 25289, 25290, 25291, 25292, 25293, 25294]\n", - "('A31', 'thymus'): [25648, 25649, 25650, 25651, 25652, 25653, 25654, 25655, 25656, 25657]\n", - "('A31', 'mesenteric lymph node'): [26002, 26003, 26004, 26005, 26006, 26007, 26008, 26009, 26010, 26011]\n", - "('A31', 'skeletal muscle tissue'): [28373, 28374]\n", - "('A31', 'duodenum'): [28375, 28376, 28377, 28378, 28379, 28380, 28381, 28382, 28383, 28384]\n", - "('A29', 'caecum'): [29110, 29111, 29112, 29113, 29114, 29115, 29116, 29117, 29118, 29119]\n", - "('A29', 'transverse colon'): [29378, 29379, 29380, 29381, 29382, 29383, 29384, 29385, 29386, 29387]\n", - "('A29', 'sigmoid colon'): [29640, 29641, 29642, 29643, 29644, 29645, 29646, 29647, 29648, 29649]\n" - ] - } - ], - "source": [ - "print(\"(batch sample, tissue type): [list of cell indices with this combination]\")\n", - "for key in batch_tissue_to_cell_indices_dict.keys():\n", - " print(f\"{key}:\", batch_tissue_to_cell_indices_dict[key][:10])" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "208c2009", - "metadata": {}, - "outputs": [], - "source": [ - "def get_multi_cell_arrow_ds(hf_ds, batch_tissue_to_cell_indices_dict):\n", - " \"\"\"\n", - " Function to take in a Huggingface cell sentence arrow dataset and a dictionary \n", - " mapping a tuple of (batch sample, tissue type) to a list of cell indices, and \n", - " return a new arrow dataset containing the multi-cell groupings.\n", - "\n", - " Arguments:\n", - " hf_ds: Huggingface arrow dataset containing cell sentences to group into multi-cells.\n", - " batch_tissue_to_cell_indices_dict: Dictionary mapping a tuple of (batch sample, tissue type) to a list of cell indices.\n", - " \n", - " Returns:\n", - " multi_cell_groupings_ds: Huggingface arrow dataset containing multi-cell groupings.\n", - " \"\"\"\n", - " # Initialize list to store multi-cell groupings, each element is a list of 5 cell indices\n", - " multi_cell_groupings_list = []\n", - " batch_sample_labels = []\n", - " tissue_type_labels = []\n", - " organism_labels = []\n", - "\n", - " # Loop through each sample in original dataset - keeps number of overall samples (roughly) the same\n", - " for sample_idx in tqdm(range(hf_ds.num_rows)):\n", - " sample = hf_ds[sample_idx]\n", - " batch_sample = sample[\"batch_condition\"]\n", - " tissue_type = sample[\"tissue\"]\n", - "\n", - " # Retrieve list of cell indices for this batch sample and tissue type\n", - " sample_key = (batch_sample, tissue_type)\n", - " all_cell_indices = batch_tissue_to_cell_indices_dict[sample_key]\n", - " if len(all_cell_indices) <= 5:\n", - " # If there are less than 5 cells for this batch sample and tissue type, we will sample with replacement.\n", - " # Note that another option here would be to just skip this sample.\n", - " sampled_cell_indices = random.choices(all_cell_indices, k=5)\n", - " else:\n", - " # If there are 5 or more cells for this batch sample and tissue type, we will sample without replacement\n", - " sampled_cell_indices = random.sample(all_cell_indices, k=5)\n", - "\n", - " # Add list of sampled cell indices to multi-cell groupings list\n", - " multi_cell_groupings_list.append(sampled_cell_indices)\n", - " batch_sample_labels.append(sample[\"batch_condition\"])\n", - " tissue_type_labels.append(sample[\"tissue\"])\n", - " organism_labels.append(sample[\"organism\"]) # all cells should be of the same organism\n", - "\n", - " multi_cell_groupings_ds = Dataset.from_dict({\n", - " \"multi_cell_groupings\": multi_cell_groupings_list,\n", - " \"batch_label\": batch_sample_labels,\n", - " \"tissue\": tissue_type_labels,\n", - " \"organism\": organism_labels,\n", - " })\n", - " return multi_cell_groupings_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "61064af0", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 29773/29773 [00:02<00:00, 12727.38it/s]\n" - ] - }, - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['multi_cell_groupings', 'batch_label', 'tissue', 'organism'],\n", - " num_rows: 29773\n", - "})" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "multi_cell_arrow_ds = get_multi_cell_arrow_ds(arrow_ds, batch_tissue_to_cell_indices_dict)\n", - "multi_cell_arrow_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "34cf2803", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'multi_cell_groupings': [225, 59, 3, 46, 298],\n", - " 'batch_label': 'A29',\n", - " 'tissue': 'ileum',\n", - " 'organism': 'Homo sapiens'}" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "multi_cell_arrow_ds[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "1c844580", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Cell 225: A29 ileum\n", - "Cell 59: A29 ileum\n", - "Cell 3: A29 ileum\n", - "Cell 46: A29 ileum\n", - "Cell 298: A29 ileum\n" - ] - } - ], - "source": [ - "for cell_idx in multi_cell_arrow_ds[0][\"multi_cell_groupings\"]:\n", - " print(f\"Cell {cell_idx}:\", arrow_ds[cell_idx][\"batch_condition\"], arrow_ds[cell_idx][\"tissue\"])" - ] - }, - { - "cell_type": "markdown", - "id": "8428d5c9", - "metadata": {}, - "source": [ - "# Prompt Formatting for Natural Language Interpretation\n", - "\n", - "We will format prompts that provide the model with multiple cell sentences and ask it to generate a summary of the biological information contained within them. This is a powerful feature of C2S, allowing researchers to gain high-level insights from their data in a human-readable format." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "b3c8d896", - "metadata": {}, - "outputs": [], - "source": [ - "from cell2sentence.prompt_formatter import C2SMultiCellPromptFormatter" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "16092cfc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "task_name = \"natural_language_interpretation\"\n", - "prompt_formatter = C2SMultiCellPromptFormatter(\n", - " task=task_name,\n", - " top_k_genes=200\n", - ")\n", - "prompt_formatter" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "cda801f0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'multi_cell_groupings': [225, 59, 3, 46, 298],\n", - " 'batch_label': 'A29',\n", - " 'tissue': 'ileum',\n", - " 'organism': 'Homo sapiens',\n", - " 'abstract': ''}" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# We would like to generate natural language summaries at inference for groups of cells.\n", - "# For the input sample, we will put an empty string as a placeholder for the abstract, so that\n", - "# prompt formatting code is not affected.\n", - "multi_cell_arrow_ds = multi_cell_arrow_ds.add_column(\"abstract\", [\"\"] * multi_cell_arrow_ds.num_rows)\n", - "multi_cell_arrow_ds[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "f5e51eef", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['sample_type', 'model_input', 'response'],\n", - " num_rows: 29773\n", - "})" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "formatted_ds = prompt_formatter.format_hf_ds(\n", - " hf_ds=arrow_ds,\n", - " multi_cell_indices_ds=multi_cell_arrow_ds\n", - ")\n", - "formatted_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "8ff9f0b2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'sample_type': 'natural_language_interpretation',\n", - " 'model_input': 'Consider these 200 highly expressed genes, ordered by descending expression, from 5 Homo sapiens cells. Using this, your task is to generate an abstract summary which summarizes the biological insights contained in these cells.\\nCell 1:\\nTMSB4X MT-CO1 CCL4 B2M MT-CO2 MALAT1 ACTB RPLP1 MT-CYB MT-CO3 HSP90AA1 MTRNR2L12 MT-ND3 EEF1A1 CCL5 MT-ATP8 HSPA1B RPS12 MT-ATP6 RPL41 RPL10 RPL28 HLA-B MT-ND4L RPS19 RPS27 RPL13 HLA-C TPT1 SH3BGRL3 JUN MT-ND2 MT-ND1 RPL37 RPS18 RPL19 RPS4X RPL30 RPS2 RPS15A IL32 HSPA8 ACTG1 CD69 XCL1 RPL26 DNAJB1 RPS15 KLF6 RPS28 RPL39 TMSB10 S100A4 RPL34 RPS14 RPL29 FTH1 GAPDH RPLP2 BTG1 MT-ND4 ATF3 RPL18A RPS3 FAU RPS27A RPS3A RPL32 RPL12 RPL21 NKG7 RPL37A RPS21 RPS24 PFN1 RPS13 RPL3 RPL11 IFITM1 CD8A RPL9 RPSA RPS23 CD3D MT-ND5 TNFAIP3 RPL35A RPS6 RPL18 RPLP0 RPL27 ZFP36 IFNG PTMA RPL8 RPS25 TRBV4-1 HLA-A CD52 PHLDA1 RPL17 VIM RPL14 RPS8 UBB H3-3B TSC22D3 SRGN RPL23A RPL35 RPS7 HSPA1A RPS16 RGS2 RPL36 CORO1A RPL13A GZMA RACK1 RPL15 RPL4 NR4A3 RAC2 RPS9 RPL7A ARHGDIB CD3E UBC ANXA1 EIF1 HLA-E RPS29 CLIC1 FTL SERF2 CALM1 SPRY1 RPL6 ZFP36L2 INSIG1 ZFP36L1 CD8B UBA52 PPIA STAT1 PLAAT4 CD160 LAPTM5 DUSP1 RPL24 ATP5MC2 NR4A1 COTL1 ARL4C CD7 EEF2 HNRNPA2B1 ATP5F1E ARL6IP5 SLC25A5 MYL12B HNRNPA1 HCST MYH9 MSN EEF1G BTG2 TRAPPC1 NACA HMGN2 GNG2 MYL12A RGL4 LMO4 CRIP1 PNRC1 PPIB EEF1D SUMO2 NEAT1 FOS SARAF ETS1 TNF SNRPD2 RPS5 STK17B RPL36A ARPC2 RHOB SEPTIN1 SAT1 CYTIP EVL GUK1 MIF JUND CFL1 COX6B1 C12ORF57.\\nCell 2:\\nRPLP1 CCL4 TMSB4X B2M RPL41 ACTB MT-CO1 MALAT1 RPL13 RPS19 RPL28 EEF1A1 RPS12 CCL5 HLA-B MT-CO2 TPT1 RPS27 MT-CO3 RPL32 MT-ND3 HSPA1A XCL1 RPS4X KLF6 DNAJB1 RPS27A RPS3 RPL10 RPS15A RPLP0 RPS18 RPS28 RPS23 MT-ATP8 RPL11 RPL30 FOS RPS2 RPS7 NR4A2 RPS14 RPS6 HLA-C RPL39 RPL18A RPL37 RPL19 JUN SH3BGRL3 TMSB10 MT-CYB RPL34 PFN1 RPL26 RPL15 HSP90AA1 TRBV9 RPS15 RPS25 RPL29 RPL17 RPS24 VIM RPS29 MT-ND4L ACTG1 RPL7A RPL36 RPL18 RPS21 RPS3A RPS8 IFITM1 H3-3B HLA-A PPP1R15A PTMA MT-ATP6 FTH1 BTG1 GAPDH RPL23A RPL3 ATF3 CD74 DUSP1 UBA52 RPL35 PNRC1 RPS16 RPL37A ATP5F1E RACK1 RPL21 RPLP2 RPL9 RPL12 RPL10A HSPA8 RPS13 EIF1 RPL8 MT-ND1 SERF2 RPL38 TNFAIP3 ARHGDIB SRGN RPL36A RPSA RPS5 IFITM2 SPRY1 RPL6 PPIA CFL1 FAU CD7 EEF2 RPL35A HCST MT-ND5 SLA IL32 CORO1A NACA RPL24 HSPA1B CRIP1 HNRNPA2B1 H3-3A CYTIP RPL27 ZFP36L2 RPL22 CD52 MT-ND4 TRAV19 ZFP36L1 CKLF RPS9 PPIB RPL14 EVL COX6B1 MYL6 RPL4 ZFP36 UBC RHOB FTL IL7R EEF1B2 UBB RPL27A TOMM7 GYPC EEF1G RAC2 CAPZB OAZ1 MAP3K8 PSMB10 HSPE1 RPL5 CD3E SARAF CD99 PABPC1 SRP14 RBM3 CHCHD2 CD3D CDKN1A NDUFS5 MYL12B EIF3F TAGAP RHOH PFDN5 SRSF7 RPL31 NR4A1 MCL1 MYL12A OST4 HMGB1 RAB9A S100A10 SAMSN1 NKG7 FYB1 S100A4 NFKBIA CNBP MT-ND2 PLAAT4 DYNLL1 SLC2A3.\\nCell 3:\\nCCL4 MALAT1 CCL4L2 B2M RPLP1 MT-CO2 EEF1A1 MT-CO1 CCL5 JUN TMSB4X IFNG FOS MT-CO3 RPL41 MT-ND4L DNAJB1 HSP90AA1 RPS12 MT-CYB ACTB RPL28 KLF6 HSPA1A PTMA TPT1 RPS19 RPS4X MT-ND3 CD69 RPL30 RPS27 RPS27A RPS28 RPL13 HLA-B RPL10 RPL32 RPS15A MT-ATP8 RPLP2 RPS3 RPL19 RPS18 RPL37 RPL18A RPS21 RPS3A RPL18 RPS14 PPP1R15A ANXA1 MT-ND1 H3-3B RPS15 RPL34 RPL39 SH3BGRL3 MT-ATP6 NR4A1 RPS8 RPL35A MT-ND2 RPS25 RPS23 ATF3 DUSP1 GAPDH RPL7A RPL26 RPL8 RPS13 RPL29 MT-ND4 RPS7 TMSB10 HLA-E IL32 ACTG1 RPL12 TRBV7-9 HSPA1B RPL14 CD8A UBB RPL3 RPS29 RPS24 RPS16 RPL36A HLA-C RPL5 HSPA8 S100A4 RPL22 RPS2 TMA7 NKG7 TNFAIP3 RPL36 RPL21 RPS5 MT-ND5 RPLP0 ATP5F1E RPL11 HSP90AB1 FAU TNF CKLF RPS6 JUND RPL9 FOSB FYB1 MYL6 FTH1 CD3E BTG1 RPL6 MYO1E ZFP36 PTPRCAP KLRB1 MCL1 VIM HCST RPL37A CD7 RPL4 FTL COX4I1 SRGN EIF1 RPS9 IFITM2 PCBP2 ITM2B NFKBIZ EEF1D SARAF RPL13A CDKN1A NFKBIA PNRC1 CFL1 MYL12A OAZ1 UBA52 IFITM3 TAGAP LY6E RPL24 ARHGDIB LDLRAD4 RPL35 TSC22D3 GZMA CRIP1 JUNB CD3D PFN1 UQCR11 NEU1 NACA RPL27 RPL15 BTF3 PCBP1 ATP1A1 RPL23 HLA-A COX7A2 HNRNPA3 MRPL18 ARGLU1 PABPN1 IFITM1 ZFP36L1 MYADM CORO1A MIF IL2RG SNRPB2 RACK1 HNRNPK CHCHD2 TPM3 ANXA11 HSPA5 SLC25A6 EEF2 CSK CALR RPSA ELF1 RBM39 STK17A COMMD6 CD2.\\nCell 4:\\nB2M MT-CO1 TMSB4X MT-CO2 RPLP1 HSP90AA1 MALAT1 HSPA8 MT-CO3 EEF1A1 H3-3B HSPA1A RPL41 MT-CYB ACTB RPS27 HSPA1B RPS18 KLF6 RPL28 RPS19 HLA-B MT-ATP6 RPL10 RPL13 MT-ATP8 RPS12 RPS28 RPL11 TPT1 MT-ND3 RPS27A CCL5 JUNB RPL39 DNAJB1 RPS2 UBC ANXA1 RPS21 MT-ND4 RPL32 MT-ND4L RPS15 RPS3 ATF3 RPL34 DUSP1 RPL21 TNFAIP3 RPLP2 RPS3A RPL37 RPL30 RPS15A BTG1 PTMA MT-ND1 RPS23 PFN1 NR4A2 RPS4X RPS14 TRBV4-1 HLA-C RPS6 HLA-A RPL12 RPL3 RPL29 PNRC1 SARAF RPL19 RPL18A RPL36 VIM RPS8 RPS7 NR4A1 TMSB10 RPSA RPL26 MT-ND5 RPS29 RPS13 RPL15 EIF1 RPL17 RPL35A CSF1 FAU GAPDH HSP90AB1 MYL12A S100A4 RPL14 FTL CD69 ACTG1 RPL18 SH3BGRL3 RPL7A CD8A ADGRE5 GZMA JUN PLAAT4 PTPRCAP NEAT1 RPLP0 RPS25 RPL22 DNAJA1 CD7 RPS24 SELENOK RPL24 RPS9 RPL5 RPS5 FOS LGALS1 MT-ND2 RPL37A STK17B NACA EEF1B2 SAT1 CYTIP RPL23A JUND CORO1A RPL38 RPL13A RPL8 PPIA FYB1 CFL1 SRGN ZFP36L2 RHOH EEF1G RPS16 HSPE1 EEF2 IL32 KLRB1 RPL9 HSPH1 TSC22D3 UBA52 SEPTIN6 PFDN5 RPL10A CD3G YBX1 CD3E HLA-E RPL4 ARHGDIB PTGER4 LIMD2 CACYBP HSPB1 SERF2 FOSB HNRNPA0 ITM2B CKLF FERMT3 RACK1 MCL1 CRIP1 RPL35 PTGES3 CAPZB RPS26 SDCBP TPI1 RAC1 CAP1 COX7C RPL36A FRMD4B TOMM7 PPP1R15A IFITM1 HSPD1 GNB2 IL7R PMAIP1 ARPC3 ATP5F1E CD3D MTRNR2L12 LSP1 MYL6 CYCS TIPARP SPATS2L.\\nCell 5:\\nMT-CO2 GNLY MT-CO3 MT-ND3 MT-CYB MT-CO1 RPLP1 MALAT1 TMSB4X MT-ATP6 EEF1A1 RPL41 MT-ATP8 HSP90AA1 RPS19 MT-ND1 RPS27 MT-ND4L GZMA CCL5 RPL13 MT-ND2 RPL30 RPL28 RPS23 RPS18 RPS27A RPL10 RPS15A ACTB B2M MT-ND4 RPS4X RPS12 RPS3 HSPA1A PTMA TPT1 RPL32 RPS8 RPS14 RPS6 RPL26 RPL34 RPL39 RPS28 GAPDH CD7 RPS24 RPL18A RPS3A RPL11 RPL8 RPS15 RPL7A RPL3 RPS7 KLF6 RPL35A RPL12 RPL23A RPL19 NKG7 RPL6 RPLP2 RPS9 RPLP0 CD52 RPL29 RPL37 TMSB10 RPL37A RPS13 RPL35 DNAJB1 MT-ND5 RPS25 RPS2 RPL15 FTL TYROBP RPS21 EEF1B2 HSPA1B RPL36A HSPA6 UBC ACTG1 MTRNR2L12 ZFP36L1 RPL18 FAU RPL22 RPL9 RPS29 NACA FTH1 NR4A1 RPL21 RPL17 ATP5F1E RPS5 RACK1 PABPC1 RPL10A IER5 CORO1A RPL14 RPL36 PFN1 H3-3B SRGN TAGAP MYL12A IFITM2 RPS16 RPL27 HCST VIM HLA-B HOPX CFL1 ATF3 SERF2 SH3BGRL3 NPM1 HLA-A EEF1D NR4A3 IFNG RPL27A CKLF EEF1G UBB RPL4 H2AJ HSP90AB1 EIF1 YBX1 PLAAT4 TRDC RPS26 BTG1 GEM CD3E COTL1 HSPA8 RPL24 FCER1G PNRC1 ARHGDIB RPL5 TOMM7 IFITM1 RPL38 RAC2 CYBA TRA2B MIF SEC11A CD247 RPL7 RPL31 OAZ1 PFDN5 CD69 KRT86 RPL13A RPSA EEF2 BTF3 COX7C MYL6 RHOC UBXN4 UBA52 DBI HMGN2 GSTK1 HSPB1 KLRB1 KIR2DL4 HLA-E FOSB CIRBP PTPN22 PHLDA1 TMA7 SYTL3 ATP5MG RHOA GNAS GYPC HLA-C H3-3A COX6C KLRC2 PARK7 NFKBIA ATP5MC2.\\n.\\nAbstract summary:',\n", - " 'response': '.'}" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "formatted_ds[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "285ca7f6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Consider these 200 highly expressed genes, ordered by descending expression, from 5 Homo sapiens cells. Using this, your task is to generate an abstract summary which summarizes the biological insights contained in these cells.\n", - "Cell 1:\n", - "TMSB4X MT-CO1 CCL4 B2M MT-CO2 MALAT1 ACTB RPLP1 MT-CYB MT-CO3 HSP90AA1 MTRNR2L12 MT-ND3 EEF1A1 CCL5 MT-ATP8 HSPA1B RPS12 MT-ATP6 RPL41 RPL10 RPL28 HLA-B MT-ND4L RPS19 RPS27 RPL13 HLA-C TPT1 SH3BGRL3 JUN MT-ND2 MT-ND1 RPL37 RPS18 RPL19 RPS4X RPL30 RPS2 RPS15A IL32 HSPA8 ACTG1 CD69 XCL1 RPL26 DNAJB1 RPS15 KLF6 RPS28 RPL39 TMSB10 S100A4 RPL34 RPS14 RPL29 FTH1 GAPDH RPLP2 BTG1 MT-ND4 ATF3 RPL18A RPS3 FAU RPS27A RPS3A RPL32 RPL12 RPL21 NKG7 RPL37A RPS21 RPS24 PFN1 RPS13 RPL3 RPL11 IFITM1 CD8A RPL9 RPSA RPS23 CD3D MT-ND5 TNFAIP3 RPL35A RPS6 RPL18 RPLP0 RPL27 ZFP36 IFNG PTMA RPL8 RPS25 TRBV4-1 HLA-A CD52 PHLDA1 RPL17 VIM RPL14 RPS8 UBB H3-3B TSC22D3 SRGN RPL23A RPL35 RPS7 HSPA1A RPS16 RGS2 RPL36 CORO1A RPL13A GZMA RACK1 RPL15 RPL4 NR4A3 RAC2 RPS9 RPL7A ARHGDIB CD3E UBC ANXA1 EIF1 HLA-E RPS29 CLIC1 FTL SERF2 CALM1 SPRY1 RPL6 ZFP36L2 INSIG1 ZFP36L1 CD8B UBA52 PPIA STAT1 PLAAT4 CD160 LAPTM5 DUSP1 RPL24 ATP5MC2 NR4A1 COTL1 ARL4C CD7 EEF2 HNRNPA2B1 ATP5F1E ARL6IP5 SLC25A5 MYL12B HNRNPA1 HCST MYH9 MSN EEF1G BTG2 TRAPPC1 NACA HMGN2 GNG2 MYL12A RGL4 LMO4 CRIP1 PNRC1 PPIB EEF1D SUMO2 NEAT1 FOS SARAF ETS1 TNF SNRPD2 RPS5 STK17B RPL36A ARPC2 RHOB SEPTIN1 SAT1 CYTIP EVL GUK1 MIF JUND CFL1 COX6B1 C12ORF57.\n", - "Cell 2:\n", - "RPLP1 CCL4 TMSB4X B2M RPL41 ACTB MT-CO1 MALAT1 RPL13 RPS19 RPL28 EEF1A1 RPS12 CCL5 HLA-B MT-CO2 TPT1 RPS27 MT-CO3 RPL32 MT-ND3 HSPA1A XCL1 RPS4X KLF6 DNAJB1 RPS27A RPS3 RPL10 RPS15A RPLP0 RPS18 RPS28 RPS23 MT-ATP8 RPL11 RPL30 FOS RPS2 RPS7 NR4A2 RPS14 RPS6 HLA-C RPL39 RPL18A RPL37 RPL19 JUN SH3BGRL3 TMSB10 MT-CYB RPL34 PFN1 RPL26 RPL15 HSP90AA1 TRBV9 RPS15 RPS25 RPL29 RPL17 RPS24 VIM RPS29 MT-ND4L ACTG1 RPL7A RPL36 RPL18 RPS21 RPS3A RPS8 IFITM1 H3-3B HLA-A PPP1R15A PTMA MT-ATP6 FTH1 BTG1 GAPDH RPL23A RPL3 ATF3 CD74 DUSP1 UBA52 RPL35 PNRC1 RPS16 RPL37A ATP5F1E RACK1 RPL21 RPLP2 RPL9 RPL12 RPL10A HSPA8 RPS13 EIF1 RPL8 MT-ND1 SERF2 RPL38 TNFAIP3 ARHGDIB SRGN RPL36A RPSA RPS5 IFITM2 SPRY1 RPL6 PPIA CFL1 FAU CD7 EEF2 RPL35A HCST MT-ND5 SLA IL32 CORO1A NACA RPL24 HSPA1B CRIP1 HNRNPA2B1 H3-3A CYTIP RPL27 ZFP36L2 RPL22 CD52 MT-ND4 TRAV19 ZFP36L1 CKLF RPS9 PPIB RPL14 EVL COX6B1 MYL6 RPL4 ZFP36 UBC RHOB FTL IL7R EEF1B2 UBB RPL27A TOMM7 GYPC EEF1G RAC2 CAPZB OAZ1 MAP3K8 PSMB10 HSPE1 RPL5 CD3E SARAF CD99 PABPC1 SRP14 RBM3 CHCHD2 CD3D CDKN1A NDUFS5 MYL12B EIF3F TAGAP RHOH PFDN5 SRSF7 RPL31 NR4A1 MCL1 MYL12A OST4 HMGB1 RAB9A S100A10 SAMSN1 NKG7 FYB1 S100A4 NFKBIA CNBP MT-ND2 PLAAT4 DYNLL1 SLC2A3.\n", - "Cell 3:\n", - "CCL4 MALAT1 CCL4L2 B2M RPLP1 MT-CO2 EEF1A1 MT-CO1 CCL5 JUN TMSB4X IFNG FOS MT-CO3 RPL41 MT-ND4L DNAJB1 HSP90AA1 RPS12 MT-CYB ACTB RPL28 KLF6 HSPA1A PTMA TPT1 RPS19 RPS4X MT-ND3 CD69 RPL30 RPS27 RPS27A RPS28 RPL13 HLA-B RPL10 RPL32 RPS15A MT-ATP8 RPLP2 RPS3 RPL19 RPS18 RPL37 RPL18A RPS21 RPS3A RPL18 RPS14 PPP1R15A ANXA1 MT-ND1 H3-3B RPS15 RPL34 RPL39 SH3BGRL3 MT-ATP6 NR4A1 RPS8 RPL35A MT-ND2 RPS25 RPS23 ATF3 DUSP1 GAPDH RPL7A RPL26 RPL8 RPS13 RPL29 MT-ND4 RPS7 TMSB10 HLA-E IL32 ACTG1 RPL12 TRBV7-9 HSPA1B RPL14 CD8A UBB RPL3 RPS29 RPS24 RPS16 RPL36A HLA-C RPL5 HSPA8 S100A4 RPL22 RPS2 TMA7 NKG7 TNFAIP3 RPL36 RPL21 RPS5 MT-ND5 RPLP0 ATP5F1E RPL11 HSP90AB1 FAU TNF CKLF RPS6 JUND RPL9 FOSB FYB1 MYL6 FTH1 CD3E BTG1 RPL6 MYO1E ZFP36 PTPRCAP KLRB1 MCL1 VIM HCST RPL37A CD7 RPL4 FTL COX4I1 SRGN EIF1 RPS9 IFITM2 PCBP2 ITM2B NFKBIZ EEF1D SARAF RPL13A CDKN1A NFKBIA PNRC1 CFL1 MYL12A OAZ1 UBA52 IFITM3 TAGAP LY6E RPL24 ARHGDIB LDLRAD4 RPL35 TSC22D3 GZMA CRIP1 JUNB CD3D PFN1 UQCR11 NEU1 NACA RPL27 RPL15 BTF3 PCBP1 ATP1A1 RPL23 HLA-A COX7A2 HNRNPA3 MRPL18 ARGLU1 PABPN1 IFITM1 ZFP36L1 MYADM CORO1A MIF IL2RG SNRPB2 RACK1 HNRNPK CHCHD2 TPM3 ANXA11 HSPA5 SLC25A6 EEF2 CSK CALR RPSA ELF1 RBM39 STK17A COMMD6 CD2.\n", - "Cell 4:\n", - "B2M MT-CO1 TMSB4X MT-CO2 RPLP1 HSP90AA1 MALAT1 HSPA8 MT-CO3 EEF1A1 H3-3B HSPA1A RPL41 MT-CYB ACTB RPS27 HSPA1B RPS18 KLF6 RPL28 RPS19 HLA-B MT-ATP6 RPL10 RPL13 MT-ATP8 RPS12 RPS28 RPL11 TPT1 MT-ND3 RPS27A CCL5 JUNB RPL39 DNAJB1 RPS2 UBC ANXA1 RPS21 MT-ND4 RPL32 MT-ND4L RPS15 RPS3 ATF3 RPL34 DUSP1 RPL21 TNFAIP3 RPLP2 RPS3A RPL37 RPL30 RPS15A BTG1 PTMA MT-ND1 RPS23 PFN1 NR4A2 RPS4X RPS14 TRBV4-1 HLA-C RPS6 HLA-A RPL12 RPL3 RPL29 PNRC1 SARAF RPL19 RPL18A RPL36 VIM RPS8 RPS7 NR4A1 TMSB10 RPSA RPL26 MT-ND5 RPS29 RPS13 RPL15 EIF1 RPL17 RPL35A CSF1 FAU GAPDH HSP90AB1 MYL12A S100A4 RPL14 FTL CD69 ACTG1 RPL18 SH3BGRL3 RPL7A CD8A ADGRE5 GZMA JUN PLAAT4 PTPRCAP NEAT1 RPLP0 RPS25 RPL22 DNAJA1 CD7 RPS24 SELENOK RPL24 RPS9 RPL5 RPS5 FOS LGALS1 MT-ND2 RPL37A STK17B NACA EEF1B2 SAT1 CYTIP RPL23A JUND CORO1A RPL38 RPL13A RPL8 PPIA FYB1 CFL1 SRGN ZFP36L2 RHOH EEF1G RPS16 HSPE1 EEF2 IL32 KLRB1 RPL9 HSPH1 TSC22D3 UBA52 SEPTIN6 PFDN5 RPL10A CD3G YBX1 CD3E HLA-E RPL4 ARHGDIB PTGER4 LIMD2 CACYBP HSPB1 SERF2 FOSB HNRNPA0 ITM2B CKLF FERMT3 RACK1 MCL1 CRIP1 RPL35 PTGES3 CAPZB RPS26 SDCBP TPI1 RAC1 CAP1 COX7C RPL36A FRMD4B TOMM7 PPP1R15A IFITM1 HSPD1 GNB2 IL7R PMAIP1 ARPC3 ATP5F1E CD3D MTRNR2L12 LSP1 MYL6 CYCS TIPARP SPATS2L.\n", - "Cell 5:\n", - "MT-CO2 GNLY MT-CO3 MT-ND3 MT-CYB MT-CO1 RPLP1 MALAT1 TMSB4X MT-ATP6 EEF1A1 RPL41 MT-ATP8 HSP90AA1 RPS19 MT-ND1 RPS27 MT-ND4L GZMA CCL5 RPL13 MT-ND2 RPL30 RPL28 RPS23 RPS18 RPS27A RPL10 RPS15A ACTB B2M MT-ND4 RPS4X RPS12 RPS3 HSPA1A PTMA TPT1 RPL32 RPS8 RPS14 RPS6 RPL26 RPL34 RPL39 RPS28 GAPDH CD7 RPS24 RPL18A RPS3A RPL11 RPL8 RPS15 RPL7A RPL3 RPS7 KLF6 RPL35A RPL12 RPL23A RPL19 NKG7 RPL6 RPLP2 RPS9 RPLP0 CD52 RPL29 RPL37 TMSB10 RPL37A RPS13 RPL35 DNAJB1 MT-ND5 RPS25 RPS2 RPL15 FTL TYROBP RPS21 EEF1B2 HSPA1B RPL36A HSPA6 UBC ACTG1 MTRNR2L12 ZFP36L1 RPL18 FAU RPL22 RPL9 RPS29 NACA FTH1 NR4A1 RPL21 RPL17 ATP5F1E RPS5 RACK1 PABPC1 RPL10A IER5 CORO1A RPL14 RPL36 PFN1 H3-3B SRGN TAGAP MYL12A IFITM2 RPS16 RPL27 HCST VIM HLA-B HOPX CFL1 ATF3 SERF2 SH3BGRL3 NPM1 HLA-A EEF1D NR4A3 IFNG RPL27A CKLF EEF1G UBB RPL4 H2AJ HSP90AB1 EIF1 YBX1 PLAAT4 TRDC RPS26 BTG1 GEM CD3E COTL1 HSPA8 RPL24 FCER1G PNRC1 ARHGDIB RPL5 TOMM7 IFITM1 RPL38 RAC2 CYBA TRA2B MIF SEC11A CD247 RPL7 RPL31 OAZ1 PFDN5 CD69 KRT86 RPL13A RPSA EEF2 BTF3 COX7C MYL6 RHOC UBXN4 UBA52 DBI HMGN2 GSTK1 HSPB1 KLRB1 KIR2DL4 HLA-E FOSB CIRBP PTPN22 PHLDA1 TMA7 SYTL3 ATP5MG RHOA GNAS GYPC HLA-C H3-3A COX6C KLRC2 PARK7 NFKBIA ATP5MC2.\n", - ".\n", - "Abstract summary:\n" - ] - } - ], - "source": [ - "print(formatted_ds[0]['model_input'])" - ] - }, - { - "cell_type": "markdown", - "id": "07376fd5", - "metadata": {}, - "source": [ - "# Load C2S Model\n", - "\n", - "Now, we will load a pretrained C2S model that has been trained on a large corpus of single-cell data and biological text. This model has learned to understand the \"language\" of cells and can be used for various interpretation tasks. We will use the `CSModel` class from the `cell2sentence` library to load the model." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "0317ac96", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using device: cuda\n" - ] - } - ], - "source": [ - "# Define the path to your pretrained model and a directory to save model-related files\n", - "model_path = \"vandijklab/C2S-Scale-Pythia-1b-pt\"\n", - "save_dir = \"/home/sr2464/scratch/C2S_API_Testing/Cache_Dir\"\n", - "save_name = \"natural_language_interpretation_1B_model\"\n", - "\n", - "# Initialize the CSModel object\n", - "csmodel = cs.CSModel(\n", - " model_name_or_path=model_path,\n", - " save_dir=save_dir,\n", - " save_name=save_name\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "7fd868a0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'cuda'" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", - "device" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "98fb6e3e", - "metadata": {}, - "outputs": [], - "source": [ - "from transformers import AutoModelForCausalLM" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "7620bdf2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "GPTNeoXForCausalLM(\n", - " (gpt_neox): GPTNeoXModel(\n", - " (embed_in): Embedding(50304, 2048)\n", - " (emb_dropout): Dropout(p=0.0, inplace=False)\n", - " (layers): ModuleList(\n", - " (0-15): 16 x GPTNeoXLayer(\n", - " (input_layernorm): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n", - " (post_attention_layernorm): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n", - " (post_attention_dropout): Dropout(p=0.0, inplace=False)\n", - " (post_mlp_dropout): Dropout(p=0.0, inplace=False)\n", - " (attention): GPTNeoXSdpaAttention(\n", - " (rotary_emb): GPTNeoXRotaryEmbedding()\n", - " (query_key_value): Linear(in_features=2048, out_features=6144, bias=True)\n", - " (dense): Linear(in_features=2048, out_features=2048, bias=True)\n", - " (attention_dropout): Dropout(p=0.0, inplace=False)\n", - " )\n", - " (mlp): GPTNeoXMLP(\n", - " (dense_h_to_4h): Linear(in_features=2048, out_features=8192, bias=True)\n", - " (dense_4h_to_h): Linear(in_features=8192, out_features=2048, bias=True)\n", - " (act): GELUActivation()\n", - " )\n", - " )\n", - " )\n", - " (final_layer_norm): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n", - " (rotary_emb): GPTNeoXRotaryEmbedding()\n", - " )\n", - " (embed_out): Linear(in_features=2048, out_features=50304, bias=False)\n", - ")" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model = AutoModelForCausalLM.from_pretrained(\n", - " os.path.join(save_dir, save_name),\n", - " cache_dir=os.path.join(save_dir, \".cache\"),\n", - " trust_remote_code=True\n", - ").to(device)\n", - "model" - ] - }, - { - "cell_type": "markdown", - "id": "23d5cbde", - "metadata": {}, - "source": [ - "# Generate Natural Language Interpretations of Cell Subsets\n", - "\n", - "With our model loaded, we can now ask it to interpret different subsets of cells from our dataset.\n", - "\n", - "Here, we select a sample of cells from our dataset to interpret" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "475cb926", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'multi_cell_groupings': [9744, 10316, 10819, 9040, 8557],\n", - " 'batch_label': 'A29',\n", - " 'tissue': 'mesenteric lymph node',\n", - " 'organism': 'Homo sapiens',\n", - " 'abstract': ''}" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "multi_cell_arrow_ds[10000]" - ] - }, - { - "cell_type": "markdown", - "id": "5d76d4d2", - "metadata": {}, - "source": [ - "Note that the Dominguez-Conde dataset contains immune cells taken from many different tissues around the body. These are a group of 5 immune cells from a mesenteric lymph node tissue of one of the patients." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "1805db5c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Input Prompt ---\n", - "Examine the top 200 genes ordered by descending expression level in 5 Homo sapiens cells. Based on this information, generate an abstract summary which summarizes the biological insights contained in these cells.\n", - "Cell 1:\n", - "CD74 EEF1A1 MT-ND3 HLA-DRA RPS27 IGHV5-51 RPLP1 MT-CO2 RPL41 FOS RPL13 RPS19 MT-CO1 RPL32 RPL10 RPS12 RPS8 RPL30 ACTB MT-CYB HLA-DRB1 CXCR4 B2M MALAT1 RPS15A RPL8 RPL28 MT-ATP8 RPL35A RPS3A RPL18A MT-ND4L DUSP1 RPS4X TMSB4X RPL39 MT-CO3 TPT1 RPS27A RPS15 RPS28 RPS3 RPS21 RPS13 RACK1 RPL37 RPS18 RPL35 MT-ATP6 RPL26 RPS25 RPL29 CD69 RPL21 RPL19 RPS2 FAU RPL23A RPL34 RPL15 RPS5 BTG1 MT-ND4 CD52 CD37 RPL36 RPS14 RPS9 MTRNR2L12 CD79A RPLP0 JUN HLA-B RPS6 HLA-DPA1 EIF1 RPS23 RPSA RPS7 RPL27 RPL11 TCL1A HLA-DRB5 H3-3B SLC2A3 TXNIP RPS24 RPS29 RPL37A IGKC RPLP2 RPL7A CD83 CYBA PABPC1 RPL18 HLA-DQB1 MT-ND5 RPL9 RPL38 RPL10A RPL5 MT-ND1 HLA-A FTL RPL6 HLA-E EEF2 PTMA TSC22D3 FTH1 TAGAP UBC MS4A1 TMSB10 RPL36A PCBP1 LY9 ASH1L SARAF UBA52 ZFP36L1 NACA RABAC1 EIF4A3 HLA-DPB1 JUND POU2F2 RPS10 MZT2B PCBP2 RPL7 SESTD1 HLA-DQA2 RPL14 RPL13A POLD4 ECHDC1 PFDN5 RBM38 UQCRB ARHGDIB HLA-C PFDN1 HECTD1 IDI1 GNB5 TUBA1A SOCS3 SMAP2 DCAF7 LINC02397 SNHG8 IER2 HMGB1 TNFRSF13C ENO1 ACTG1 MT-ND2 COX7C HNRNPA1 BAX FCER2 RPL24 PKM SRGN PNPLA2 ARPC2 CHCHD10 DDX50 COX19 HVCN1 NCF1 CCNI FCMR HTT PTPRCAP GOLM2 JUNB CD79B SLC44A2 PFN1 TMEM258 MAX RPL22 REL SSR1 LAMTOR4 CD19 ORAI2 OAZ1 CHI3L2 KLF6 LIG1 LTB H2BC4 KLF2 HNRNPA2B1 ZNF106 KLF4.\n", - "Cell 2:\n", - "MALAT1 EEF1A1 RPS27 RPS12 RPL41 RPL13 RPLP1 RPL39 RPS14 TPT1 RPS19 RPL37 RPL30 RPL11 RPL32 RPS15A RPL10 RPS27A RPS18 RPS29 RPS8 RPS23 RPL34 RPL18A RPL28 RPS28 RPS3A TMSB4X RPS4X RPL19 RPS6 RPL26 RPS2 RPS21 RPL29 RPS25 RPS3 RPL21 RPS13 MT-ND3 RPLP2 RPL3 RPL12 B2M ACTB RPL35A MT-CO2 MT-CO1 RPL22 RPL18 MT-CO3 RPL7A RPL5 RPS9 RPL23A MT-ND4L RPSA RPL8 RPLP0 RPL17 RPL15 RPS24 RPS15 RPL37A TMSB10 MT-ATP8 MT-ATP6 RPL36 JUNB HLA-B FAU MT-CYB RPL14 RPL13A RPS16 EEF1B2 RPS7 FTH1 RPL6 RPL9 RPS5 MTRNR2L12 RPL10A RPL4 PTMA ACTG1 RPL24 NACA EEF1G S100A4 RPL38 RPL27 RPS10 TRBC1 SARAF EEF1D HLA-A TMA7 RPS11 ATP5MC2 PPIA PABPC1 MT-ND1 ZFP36 DDX5 SLC2A3 UBA52 PFN1 SLC25A3 UQCRB FYB1 HLA-E IFITM1 FLT3LG GAPDH SNHG29 ZFP36L2 VIM RPS20 NOSIP SH3BGRL3 IL32 RPL35 RPL23 EIF1 COX4I1 ATP5ME FTL SERF2 BTG1 ATP6V1G1 RACK1 CD3G CCR7 YBX1 EEF2 RAC2 PSME1 ARHGDIB CORO1A MT-ND5 MYL6 EIF3K GPR183 CD3D ITM2B SUMO2 TUBB GAS5 UXT HLA-C PCBP2 EIF3H ATP5F1A SOD1 PTPRCAP CD7 RP11-290D2 RPL31 FUS HINT1 PRKCQ-AS1 OST4 C12ORF57 H3-3A ACTR1A HSPA8 CCNH LITAF DNAJC8 GHITM RYK RPL36A STK4 CFL1 ATP5F1E TRBV6-1 RPL27A PSME2 TRAV12-1 LDHB NEDD8 KLF2 ARPC5 ARPC3 PCBP1 COMMD6 EVL TCF7 MSL3 ARL4D ZNF330 ANP32B LIMD2 CD55 TBCA ESYT1 NSMCE1 SNRPC DAD1.\n", - "Cell 3:\n", - "EEF1A1 MALAT1 B2M RPL41 RPS27 TMSB4X MT-ND3 RPS28 RPL30 HLA-B RPS15A MT-CYB DUSP1 RPL32 RPL39 RPL37 RPL28 RPL13 CD69 MT-CO1 RPL10 RPLP1 RPS3 TRBV5-1 RPS12 SLC2A3 HLA-C TPT1 RPS23 RPL26 RPS27A RPL34 FOS RPS18 RPL9 RPL35A RPS29 RPL11 MT-ND4L RPL19 RPS21 RPS15 MT-ATP8 RPL29 RPS6 MT-CO2 TMSB10 ACTG1 MT-CO3 RPS7 RPL12 TRAV14DV4 JUNB RPS2 ACTB RPS8 RPL8 RPS3A RPL18A HLA-E RPL3 RPS14 MT-ATP6 EIF1 RPL21 RPL14 RPL18 H3-3B MTRNR2L12 KLF6 EEF1D JUN MT-ND2 RPS19 MT-ND1 MT-ND4 RPL37A RPSA RPL15 RPL7A KLRB1 COX7C RPL36AL RPS4X RPL35 TSC22D3 RPS25 FAU RPS13 IL32 RPLP2 RPL5 ZFP36L2 HLA-A RPL36 HSP90AA1 DDIT4 EEF1G TCF7 HSP90AB1 SEPTIN1 RPS24 TUBA4A DNAJB1 PABPC1 RPLP0 BTG1 RPL24 RPS10 EIF5B CD5 DDX5 NEAT1 CYTIP ZFP36L1 UBB LAPTM5 RPS20 FTH1 CD3D RACK1 SRGN FTL IFITM1 BTF3 FXYD5 HNRNPH2 YWHAZ NACA SAP18 DNAJA1 PFN1 CD44 SRSF7 BTG2 RPL38 CFL1 EEF1B2 ICOS CTLA4 HNRNPA2B1 BAZ2A ARHGDIB WIPF1 PSMB8 HSPA1A SON SS18L2 RPL17 GAS5 ZNHIT1 RPL10A EVI2B RPS9 ERLEC1 PRR13 RBMX PFDN5 MT-ND5 PARP1 HLA-F RPL7 RPL23A RPS5 FCMR CMTM7 RPS16 PCBP2 SARAF FYB1 RAN CCNI CHCHD2 MYL6 RPL4 IFITM2 GAPDH RPL22 COX20 CD3E CD2 CCR4 COX14 MAGOH ARAP2 MRPL23 UFD1 LAT RPL6 VIM UBA52 CREM NPM1 SPN DAD1 OAZ1 TRBC2 DDX24 RBM39 EIF3F.\n", - "Cell 4:\n", - "EEF1A1 RPS27 RPL10 RPL13 RPS12 RPL30 MALAT1 RPLP1 RPL41 RPL32 MT-ND3 MT-CO2 RPS15A RPS28 RPS23 RPS3 RPL28 RPS27A RPS3A RPS8 RPL18 MTRNR2L12 RPL29 RPL19 RPS21 TPT1 B2M MT-CO3 RPL34 RPS4X RPL26 RPS19 RPS13 RPL11 RPS14 RPS18 RPL37 RPLP0 RPS2 RPL39 RPL12 RPL3 RPL14 RPL5 MT-ATP8 RPS25 RPL35A RPL21 RPS6 RPS15 RPS24 MT-CO1 RPS29 MT-ND4L TMSB4X RACK1 TMSB10 RPL6 RPL7A RPS9 RPL9 ACTB RPL22 RPL15 MT-CYB RPL8 PABPC1 RPL10A JUNB RPL36 FOS RPSA DNAJB1 TSC22D3 RPL37A RPL38 RPS5 MT-ATP6 VIM RPL18A PTMA RPLP2 EEF2 FAU NACA HLA-C RPL36A RPS16 EIF1 RPL23A NPM1 RPL27 RPL24 RPS7 RPL4 DUSP1 RPL35 RPL13A HLA-B UBA52 ACTG1 HNRNPA1 COX4I1 MT-ND2 EEF1G RPL17 BTG1 HNRNPDL EEF1D MT-ND1 PFN1 FTH1 CD69 KLF2 ATP5MC2 SELL PNRC1 BTF3 GAS5 ARHGDIB MT-ND4 SLC2A3 EEF1B2 SNHG29 HLA-A LTB H3-3A RPL23 FTL SRSF7 RPL31 FOSB LINC02446 TRBV6-1 IFITM2 PTGER4 PPP1R15A RPL36AL ZFP36 HCST EIF3E PTPRC SARAF CXCR4 RHOA SLC25A3 ZNF331 R3HDM2 EIF3G PFDN5 LDHB S100A6 CD48 ATP5F1E CD8A CD3E PRR13 HSPA8 RPL27A EIF3H TMA7 TCF7 LCP2 SNHG3 NR4A1 HNRNPA2B1 CD3D ATP5ME TAX1BP1 COX7C SNHG8 PPIA HLA-E PCED1B-AS1 TRAF3IP3 CD55 SLC9A3R1 MYL12A RPL7 SLC27A5 DUSP2 RPS26 H3-3B ST13 HLA-F TXNIP WDR1 PICALM LIMD2 MT-ND5 CD52 GYPC NFKBIA GZMM HSP90AA1 TSTD1 YBX1 PCBP2 CAPZB TOMM20.\n", - "Cell 5:\n", - "MTRNR2L12 RPS27 EEF1A1 RPL41 RPL13 RPS12 RPL10 RPL30 TMSB4X RPL32 MALAT1 RPLP1 JUNB RPS28 RPL39 RPL19 RPL34 RPL18A RPL28 RPS14 RPL11 RPS3A RPS15A MT-CO2 ACTB RPS23 RPL35A RPL37 TPT1 RPS18 MT-ND3 MT-CYB RPS4X RPS8 RPS3 RPL29 RPS21 RACK1 RPL12 RPS29 RPL3 RPS15 RPS2 RPS27A PTMA RPLP0 RPL7A RPL5 RPSA MT-ND4L B2M MT-ATP8 RPL26 RPS24 NACA ACTG1 MT-CO1 RPL15 RPL14 RPL23A RPS19 RPL9 FAU RPL36 RPS6 MT-CO3 RPLP2 RPS25 RPS13 RPS9 HLA-B RPS16 RPL18 RPL8 RPL6 RPS7 MT-ATP6 RPL17 IFITM1 RPS5 HLA-A RPL38 RPL7 RPL21 ZNF331 FTL RPL37A MT-ND4 MT-ND1 EIF1 FOS EEF2 RPL10A BTG1 FTH1 RPL31 SARAF NPM1 RPL4 DNAJB1 TRBV14 RPL36A RPL22 PTPRCAP TRBV6-6 CD37 HLA-C PABPC1 CYTIP LDHB ARHGDIB EEF1G PCBP2 MYL12A SNHG6 RPL27A RPL35 PPIA TMSB10 RPL27 ZFP36 NOP53 CD69 RBM39 BTF3 SUMO2 MT-ND2 GPSM3 SNHG29 HINT1 COMMD6 CCNI RPS17 ATP5F1E EEF1D CORO1A PFN1 HSPA8 DUSP2 HNRNPH1 PPP1R2 RAC2 PFDN5 CFL1 CAP1 HLA-E H3-3B STK17B MIF SSH2 SON GABARAP PNRC1 MYH9 RPL24 FAM177A1 COX4I1 HSPE1 EIF3K RHOA TOMM7 BTG2 RGS10 LEPROTL1 PTPRC SELL DDX39B FXYD5 ARPC1B TXNIP SRSF3 SNRPD2 TAF15 RIPOR2 ZFAS1 HNRNPUL1 MPG CD3E VAMP2 EEF1B2 SATB1 SLC25A6 GAPDH CYCS TRAM1 SLC25A3 MTRNR2L8 TMC8 PCBP1 RPS26 H3-3A ITM2B TMA7 SKP1 LSM4 EDF1 EIF5A GIMAP7 ARPC3 YWHAZ.\n", - ".\n", - "Abstract summary:\n" - ] - } - ], - "source": [ - "# Format prompts for both cell subsets\n", - "input_prompt = formatted_ds[10000]['model_input']\n", - "\n", - "print(\"--- Input Prompt ---\")\n", - "print(input_prompt)" - ] - }, - { - "cell_type": "markdown", - "id": "016d6924", - "metadata": {}, - "source": [ - "Finally, we will use our loaded C2S model to generate natural language summaries for each of our cell subsets." - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "0c478051", - "metadata": {}, - "outputs": [], - "source": [ - "# Generate interpretation for the ileum cells\n", - "natural_language_interpretation = csmodel.generate_from_prompt(\n", - " model=model,\n", - " prompt=input_prompt,\n", - " do_sample=True,\n", - " max_num_tokens=1024,\n", - " temperature=0.7,\n", - " top_k=30,\n", - " top_p=0.9\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "c1cfe9cd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Interpretation for cells ---\n", - "The study used single-cell sequencing to analyze immune cells in 16 human tissues from 12 donors, generating a dataset of ~360,000 cells. They developed CellTypist, a machine learning tool for precise cell type annotation, and identified tissue-specific features and clonal architecture of T and B cells. This approach provides a foundation for identifying highly resolved immune cell types using a common reference dataset and antigen receptor sequencing..\n" - ] - } - ], - "source": [ - "print(\"--- Interpretation for cells ---\")\n", - "print(natural_language_interpretation)" - ] - }, - { - "cell_type": "markdown", - "id": "f1ae0d82", - "metadata": {}, - "source": [ - "The summary produced by the model correctly identified some details about the dataset it was sampled from, since this dataset (immune cells from Dominguez-Conde et al.) was a part of the C2S pretraining dataset. Sampling with different temperature and on different datasets can give different interpretations." - ] - }, - { - "cell_type": "markdown", - "id": "5e55401f", - "metadata": {}, - "source": [ - "# Conclusion\n", - "\n", - "In this tutorial, we have seen how a pretrained Cell2Sentence model can be used to generate natural language interpretations of single-cell datasets. By providing the model with a collection of cell sentences, it can produce a high-level summary of the biological information contained within those cells. This capability is a powerful tool for researchers to quickly gain insights into their data and understand the biological context of cell clusters in an accessible way.\n", - "\n", - "The ability to interpret complex single-cell data in natural language opens up new avenues for data exploration and hypothesis generation. As C2S models become more sophisticated, we can expect them to provide even more detailed and nuanced interpretations, further bridging the gap between computational analysis and biological understanding." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "75094e42", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "cell2sentence2", - "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": "3.8.20" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} ->>>>>>> 593fb74 (Peft feature implemented) From 2d2d598ee75d39d8425764979cdea1ba384e5238 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 11:57:03 +0000 Subject: [PATCH 04/19] Cleared merge conflicts in docs/source --- README.md | 5 ++- docs/Makefile | 48 ++++++++++----------- docs/make.bat | 74 ++++++++++++++++---------------- docs/requirements.txt | 4 -- docs/source/conf.py | 43 ------------------- docs/source/csdata.rst | 28 ------------ docs/source/csmodel.rst | 50 --------------------- docs/source/index.rst | 38 ---------------- docs/source/prompt_formatter.rst | 19 -------- docs/source/quickstart.rst | 38 ---------------- docs/source/tasks.rst | 36 ---------------- docs/source/utils.rst | 34 --------------- 12 files changed, 63 insertions(+), 354 deletions(-) diff --git a/README.md b/README.md index ac068ae..59a58b8 100644 --- a/README.md +++ b/README.md @@ -87,6 +87,9 @@ The following notebooks provide guides on common workflows with C2S models. For | [c2s_tutorial_5_cell_generation.ipynb](tutorials/c2s_tutorial_5_cell_generation.ipynb) | Cell generation conditioned on cell type | [c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb](tutorials/c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb) | Cell type annotation with foundation model | [c2s_tutorial_7_custom_prompt_templates.ipynb](tutorials/c2s_tutorials_7_custom_prompt_templates.ipynb) | Custom Prompt Templates with C2S PromptFormatter class +| [c2s_tutorial_8_multi_cell_tissue_prediction.ipynb](tutorials/c2s_tutorial_8_multi_cell_tissue_prediction.ipynb) | Classifying the Tissue based on Multiple cell sentences +| [c2s_tutorial_9_natural_language_interpretation.ipynb](tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb) | Use the C2S model to generate insightful summaries for different sets of cells +| [c2s_tutorial_10_perturbation_response_prediction.ipynb](tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb)| ## Model Zoo @@ -112,7 +115,7 @@ each explain which model they use. - [x] Add tutorial notebooks for main C2S workflows: cell type prediction, cell generation - [x] Add multi-cell prompt formatting - [ ] Add support for legacy C2S-GPT-2 model prompts -- [ ] Add parameter-efficient finetuning methods (LoRA) +- [x] Add parameter-efficient finetuning methods (LoRA) ## License diff --git a/docs/Makefile b/docs/Makefile index 2a0cd09..2f95a20 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -1,4 +1,3 @@ -<<<<<<< HEAD # Minimal makefile for Sphinx documentation # @@ -21,27 +20,26 @@ help: @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) # Example: sphinx-build -M html docs/source/ docs/build/ -======= -# Minimal makefile for Sphinx documentation -# - -# You can set these variables from the command line, and also -# from the environment for the first two. -SPHINXOPTS ?= -SPHINXBUILD ?= sphinx-build -SOURCEDIR = source -BUILDDIR = build - -# Put it first so that "make" without argument is like "make help". -help: - @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) - -.PHONY: help Makefile - -# Catch-all target: route all unknown targets to Sphinx using the new -# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). -%: Makefile - @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) - -# Example: sphinx-build -M html docs/source/ docs/build/ ->>>>>>> 593fb74 (Peft feature implemented) + +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line, and also +# from the environment for the first two. +SPHINXOPTS ?= +SPHINXBUILD ?= sphinx-build +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +# Example: sphinx-build -M html docs/source/ docs/build/ diff --git a/docs/make.bat b/docs/make.bat index 7ca1d33..2d9471d 100644 --- a/docs/make.bat +++ b/docs/make.bat @@ -1,4 +1,3 @@ -<<<<<<< HEAD @ECHO OFF pushd %~dp0 @@ -34,40 +33,39 @@ goto end :end popd -======= -@ECHO OFF - -pushd %~dp0 - -REM Command file for Sphinx documentation - -if "%SPHINXBUILD%" == "" ( - set SPHINXBUILD=sphinx-build -) -set SOURCEDIR=source -set BUILDDIR=build - -%SPHINXBUILD% >NUL 2>NUL -if errorlevel 9009 ( - echo. - echo.The 'sphinx-build' command was not found. Make sure you have Sphinx - echo.installed, then set the SPHINXBUILD environment variable to point - echo.to the full path of the 'sphinx-build' executable. Alternatively you - echo.may add the Sphinx directory to PATH. - echo. - echo.If you don't have Sphinx installed, grab it from - echo.https://www.sphinx-doc.org/ - exit /b 1 -) - -if "%1" == "" goto help - -%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% -goto end - -:help -%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% - -:end -popd ->>>>>>> 593fb74 (Peft feature implemented) + +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=source +set BUILDDIR=build + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.https://www.sphinx-doc.org/ + exit /b 1 +) + +if "%1" == "" goto help + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% + +:end +popd diff --git a/docs/requirements.txt b/docs/requirements.txt index 80c152f..856b3f4 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,6 +1,2 @@ -<<<<<<< HEAD sphinx -======= -sphinx ->>>>>>> 593fb74 (Peft feature implemented) sphinx_rtd_theme \ No newline at end of file diff --git a/docs/source/conf.py b/docs/source/conf.py index 29ec1d5..3ee9a8b 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -1,4 +1,3 @@ -<<<<<<< HEAD # Configuration file for the Sphinx documentation builder. # # For the full list of built-in configuration values, see the documentation: @@ -39,45 +38,3 @@ # html_theme = 'alabaster' html_theme = 'sphinx_rtd_theme' html_static_path = ['_static'] -======= -# Configuration file for the Sphinx documentation builder. -# -# For the full list of built-in configuration values, see the documentation: -# https://www.sphinx-doc.org/en/master/usage/configuration.html - -# -- Project information ----------------------------------------------------- -# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information - -import pathlib -import sys -import os -sys.path.insert(0, os.path.join(pathlib.Path(__file__).parents[2].resolve().as_posix(), "src", "cell2sentence")) - - -project = 'Cell2Sentence' -copyright = '2024, Cell2Sentence Authors' -author = 'Cell2Sentence Authors' -release = '1.0.0' - -# -- General configuration --------------------------------------------------- -# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration - -extensions = [ - 'sphinx.ext.autodoc', - 'sphinx.ext.napoleon', - 'sphinx_rtd_theme', - 'sphinx.ext.autosummary', -] - -templates_path = ['_templates'] -exclude_patterns = [] - - - -# -- Options for HTML output ------------------------------------------------- -# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output - -# html_theme = 'alabaster' -html_theme = 'sphinx_rtd_theme' -html_static_path = ['_static'] ->>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/csdata.rst b/docs/source/csdata.rst index 8f03525..34d4c2a 100644 --- a/docs/source/csdata.rst +++ b/docs/source/csdata.rst @@ -1,4 +1,3 @@ -<<<<<<< HEAD CSData ====== @@ -24,30 +23,3 @@ representing the dataset after C2S rank transformation. .. autofunction:: csdata.CSData.get_sentence_strings .. autofunction:: csdata.CSData.__str__ -======= -CSData -====== - -A CSData object is a wrapper around a single-cell dataset, which tracks its path on disk. -It's main functionality is to keep the dataset stored on disk so that data need not be -loaded in memory until it is used, either for inference or finetuning. - -.. autofunction:: csdata.CSData - -.. autofunction:: csdata.CSData.__init__ - - -The ``CSData.adata_to_arrow()`` function takes as input a single-cell dataset in the form -of a H5AD Scanpy object, and returns a pyarrow dataset which stores cell sentences -representing the dataset after C2S rank transformation. - -.. autofunction:: csdata.CSData.adata_to_arrow - -.. autofunction:: csdata.CSData.csdata_from_arrow - -.. autofunction:: csdata.CSData.csdata_from_multiple_arrow_datasets - -.. autofunction:: csdata.CSData.get_sentence_strings - -.. autofunction:: csdata.CSData.__str__ ->>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/csmodel.rst b/docs/source/csmodel.rst index 5071353..5f48259 100644 --- a/docs/source/csmodel.rst +++ b/docs/source/csmodel.rst @@ -1,51 +1 @@ -<<<<<<< HEAD CSModel -======= - -A CSModel object is a wrapper around a Cell2Sentence model, which tracks the path of the model -saved on disk. When needed, the model is loaded from the path on disk for inference or finetuning. -The class contains utilities for model generation and cell embedding with a Huggingface backend. - -.. autofunction:: csmodel.CSModel - -.. autofunction:: csmodel.CSModel.__init__ - -.. autofunction:: csmodel.CSModel.__str__ - -.. autofunction:: csmodel.CSModel.fine_tune - -.. autofunction:: csmodel.CSModel.generate_from_prompt - -.. autofunction:: csmodel.CSModel.generate_from_prompt_batched - -.. autofunction:: csmodel.CSModel.embed_cell - -.. autofunction:: csmodel.CSModel.embed_cells_batched - -.. autofunction:: csmodel.CSModel.push_model_to_hub -======= -CSModel -======= - -A CSModel object is a wrapper around a Cell2Sentence model, which tracks the path of the model -saved on disk. When needed, the model is loaded from the path on disk for inference or finetuning. -The class contains utilities for model generation and cell embedding with a Huggingface backend. - -.. autofunction:: csmodel.CSModel - -.. autofunction:: csmodel.CSModel.__init__ - -.. autofunction:: csmodel.CSModel.__str__ - -.. autofunction:: csmodel.CSModel.fine_tune - -.. autofunction:: csmodel.CSModel.generate_from_prompt - -.. autofunction:: csmodel.CSModel.generate_from_prompt_batched - -.. autofunction:: csmodel.CSModel.embed_cell - -.. autofunction:: csmodel.CSModel.embed_cells_batched - -.. autofunction:: csmodel.CSModel.push_model_to_hub ->>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/index.rst b/docs/source/index.rst index 97d8f09..cac513b 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -1,4 +1,3 @@ -<<<<<<< HEAD .. Cell2Sentence documentation master file, created by sphinx-quickstart on Mon Sep 2 12:15:19 2024. You can adapt this file completely to your liking, but it should at least @@ -34,40 +33,3 @@ Indices and tables * :ref:`genindex` * :ref:`modindex` * :ref:`search` -======= -.. Cell2Sentence documentation master file, created by - sphinx-quickstart on Mon Sep 2 12:15:19 2024. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. - -Cell2Sentence: Single-cell Analysis With LLMs -============================================= - -**Cell2Sentence (C2S)** is a framework for directly adapting Large Language Models (LLMs) to single-cell biology. C2S proposes a rank-ordering transformation of cell expression into cell sentences, which are sentences of space-separated gene names ordered by descending expression. By representing single-cell data as cell sentences, C2S provides a framework for LLMs to *directly* model single-cell biology in natural language, enabling diverse capabilities on multiple single-cell tasks. - -C2S is developed by members of the `vanDijk Lab `_ at Yale University. Check out the :doc:`quickstart` section for quickstart instructions. - -.. note:: - - We are actively adding more features and documentation to the C2S API. For any feature requests or issues, please leave a GitHub issue or reach out to us! - - -.. toctree:: - :maxdepth: 1 - :caption: Contents: - - quickstart - tasks - csdata - csmodel - prompt_formatter - utils - - -Indices and tables -================== - -* :ref:`genindex` -* :ref:`modindex` -* :ref:`search` ->>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/prompt_formatter.rst b/docs/source/prompt_formatter.rst index e6a05f0..3020c16 100644 --- a/docs/source/prompt_formatter.rst +++ b/docs/source/prompt_formatter.rst @@ -1,4 +1,3 @@ -<<<<<<< HEAD Prompt Formatter ================ @@ -15,21 +14,3 @@ cell generation and cell type prediction. .. autofunction:: prompt_formatter.PromptFormatter.get_keys_for_task .. autofunction:: prompt_formatter.PromptFormatter.format_hf_ds -======= -Prompt Formatter -================ - -A Prompt Formatter object deals with formatting prompts for specific tasks, such as -cell generation and cell type prediction. - - -.. autofunction:: prompt_formatter.get_cell_sentence_str - -.. autofunction:: prompt_formatter.PromptFormatter - -.. autofunction:: prompt_formatter.PromptFormatter.__init__ - -.. autofunction:: prompt_formatter.PromptFormatter.get_keys_for_task - -.. autofunction:: prompt_formatter.PromptFormatter.format_hf_ds ->>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/quickstart.rst b/docs/source/quickstart.rst index 114cbea..d4ab3b7 100644 --- a/docs/source/quickstart.rst +++ b/docs/source/quickstart.rst @@ -1,4 +1,3 @@ -<<<<<<< HEAD Quickstart ========== @@ -34,40 +33,3 @@ This will install the latest development environment of cell2sentence, along wit .. code-block:: console pip install cell2sentence -======= -Quickstart -========== - -Installation ------------- - -To set up a cell2sentence environment, first pull the repository locally: - -.. code-block:: console - - git clone https://github.com/vandijklab/cell2sentence.git - -Navigate a terminal into the root of the repository. Next, create an Anaconda environment using python3 using anaconda with: - -.. code-block:: console - - conda create -n cell2sentence python=3.8 - -Next, activate the environment: - -.. code-block:: console - - conda activate cell2sentence - -Finally, install cell2sentence and other package dependencies: - -.. code-block:: console - - make install - -This will install the latest development environment of cell2sentence, along with other pacakge dependendies. You can also install cell2sentence itself using pip: - -.. code-block:: console - - pip install cell2sentence ->>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/tasks.rst b/docs/source/tasks.rst index 6141993..1c2df09 100644 --- a/docs/source/tasks.rst +++ b/docs/source/tasks.rst @@ -1,4 +1,3 @@ -<<<<<<< HEAD Tasks ===== @@ -32,38 +31,3 @@ embedding vectors. .. autofunction:: tasks.embed_cells -======= -Tasks -===== - -Cell Generation ---------------- - -To generate cells conditioned on cell type using a C2S model, -you can use the ``tasks.generate_cells_conditioned_on_cell_type()`` function. -This function will call the batched generation function of the CSModel class -with cell type generation prompts. - -.. autofunction:: tasks.generate_cells_conditioned_on_cell_type - - -Cell Type Annotation --------------------- - -To predict cell types of data, you can use the -``tasks.predict_cell_types_of_data()`` function: - -.. autofunction:: tasks.predict_cell_types_of_data - - -Cell Embedding --------------- - -To embed cells using C2S models, you can use the -``tasks.embed_cells()`` function. This function loads a CSModel object, and -uses the C2S model to embed cell sentences from the CSData object into -embedding vectors. - -.. autofunction:: tasks.embed_cells - ->>>>>>> 593fb74 (Peft feature implemented) diff --git a/docs/source/utils.rst b/docs/source/utils.rst index 1cbb8ff..b54c091 100644 --- a/docs/source/utils.rst +++ b/docs/source/utils.rst @@ -1,4 +1,3 @@ -<<<<<<< HEAD Utils ===== @@ -30,36 +29,3 @@ rank transformation, train/test splitting, and tokenization during finetuning. .. autofunction:: utils.reconstruct_expression_from_cell_sentence -======= -Utils -===== - -This module contains utility functions for various C2S-related workflows, such as -rank transformation, train/test splitting, and tokenization during finetuning. - - -.. autofunction:: utils.generate_vocabulary - -.. autofunction:: utils.concat_vocabularies - -.. autofunction:: utils.generate_sentences - -.. autofunction:: utils.get_benchmark_df - -.. autofunction:: utils.sort_transcript_counts - -.. autofunction:: utils.benchmark_expression_conversion - -.. autofunction:: utils.build_arrow_dataset - -.. autofunction:: utils.train_test_split_arrow_ds - -.. autofunction:: utils.tokenize_loss_on_response - -.. autofunction:: utils.tokenize_all - -.. autofunction:: utils.post_process_generated_cell_sentences - -.. autofunction:: utils.reconstruct_expression_from_cell_sentence - ->>>>>>> 593fb74 (Peft feature implemented) From d8131c3128cada78910a1855a3364101f441f2a2 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 11:58:34 +0000 Subject: [PATCH 05/19] merge resolved --- setup.cfg | 46 ---------------------------------------------- 1 file changed, 46 deletions(-) diff --git a/setup.cfg b/setup.cfg index 9fa7060..1ce4c69 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,48 +1,3 @@ -<<<<<<< HEAD -[metadata] -name = cell2sentence -version = 1.2.0 -author = Syed Asad Rizvi -author_email = syed.rizvi@yale.edu -description = Cell2Sentence: Single-cell Analysis With LLMs -long_description = file: README.md -long_description_content_type = text/markdown -url = https://github.com/vandijklab/cell2sentence -license = 'BY-NC-ND' -project_urls = - Bug Tracker = https://github.com/vandijklab/cell2sentence/issues -classifiers = - Programming Language :: Python :: 3 - Development Status :: 2 - Pre-Alpha - Operating System :: OS Independent - -[options] -package_dir = - = src -packages = find: -python_requires = >=3.7 -install_requires = - torch - transformers - datasets - anndata - scanpy - numpy - pandas - scipy - tqdm - scikit-learn - jupyterlab - accelerate - plotnine - sphinx - sphinx-rtd-theme - -[options.packages.find] -where = src - -[options.package_data] -======= [metadata] name = cell2sentence version = 1.2.0 @@ -91,5 +46,4 @@ install_requires = where = src [options.package_data] ->>>>>>> 593fb74 (Peft feature implemented) * = *.json \ No newline at end of file From ab78081f5f4a17f18610ae02a0fa4586ef00faa4 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:00:11 +0000 Subject: [PATCH 06/19] merge resolved --- docs/source/csmodel.rst | 46 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 46 insertions(+) diff --git a/docs/source/csmodel.rst b/docs/source/csmodel.rst index 5f48259..58f5aa7 100644 --- a/docs/source/csmodel.rst +++ b/docs/source/csmodel.rst @@ -1 +1,47 @@ + +A CSModel object is a wrapper around a Cell2Sentence model, which tracks the path of the model +saved on disk. When needed, the model is loaded from the path on disk for inference or finetuning. +The class contains utilities for model generation and cell embedding with a Huggingface backend. + +.. autofunction:: csmodel.CSModel + +.. autofunction:: csmodel.CSModel.__init__ + +.. autofunction:: csmodel.CSModel.__str__ + +.. autofunction:: csmodel.CSModel.fine_tune + +.. autofunction:: csmodel.CSModel.generate_from_prompt + +.. autofunction:: csmodel.CSModel.generate_from_prompt_batched + +.. autofunction:: csmodel.CSModel.embed_cell + +.. autofunction:: csmodel.CSModel.embed_cells_batched + +.. autofunction:: csmodel.CSModel.push_model_to_hub +======= CSModel +======= + +A CSModel object is a wrapper around a Cell2Sentence model, which tracks the path of the model +saved on disk. When needed, the model is loaded from the path on disk for inference or finetuning. +The class contains utilities for model generation and cell embedding with a Huggingface backend. + +.. autofunction:: csmodel.CSModel + +.. autofunction:: csmodel.CSModel.__init__ + +.. autofunction:: csmodel.CSModel.__str__ + +.. autofunction:: csmodel.CSModel.fine_tune + +.. autofunction:: csmodel.CSModel.generate_from_prompt + +.. autofunction:: csmodel.CSModel.generate_from_prompt_batched + +.. autofunction:: csmodel.CSModel.embed_cell + +.. autofunction:: csmodel.CSModel.embed_cells_batched + +.. autofunction:: csmodel.CSModel.push_model_to_hub From afdfef7a0fe2e3a556253855989b14b2ca96448c Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:03:00 +0000 Subject: [PATCH 07/19] merge resolved --- ...l_type_conditional_generation_prompts.json | 19 --------------- ...gle_cell_cell_type_prediction_prompts.json | 24 ------------------- 2 files changed, 43 deletions(-) diff --git a/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json b/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json index da932b2..927ce78 100644 --- a/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json +++ b/src/cell2sentence/prompts/single_cell_cell_type_conditional_generation_prompts.json @@ -1,4 +1,3 @@ -<<<<<<< HEAD { "model_input": [ "Generate a list of {num_genes} genes in order of descending expression which represent a {organism} cell of cell type {cell_type}.\nCell sentence:", @@ -15,22 +14,4 @@ "response": [ "{cell_sentence}." ] -======= -{ - "model_input": [ - "Generate a list of {num_genes} genes in order of descending expression which represent a {organism} cell of cell type {cell_type}.\nCell sentence:", - "Produce a list of {num_genes} gene names in descending order of expression which represent the expressed genes of a {organism} {cell_type} cell.\nCell sentence:", - "Create a ranked list of {num_genes} genes in decreasing order of expression representing {organism} cell of cell type {cell_type}.\nCell sentence:", - "List the top {num_genes} expressed genes for a {organism} cell with cell type {cell_type}.\nCell sentence:", - "Identify the highest expressed {num_genes} genes in decreasing order of expression in a {organism} {cell_type} cell.\nCell sentence:", - "Enumerate a list of {num_genes} genes in descending order of expression in a {organism} {cell_type} cell.\nCell sentence:", - "Compile a descending order list of {num_genes} expressed genes in a {organism} {cell_type} cell.\nCell sentence:", - "Present a sequence of {num_genes} genes ordered by decreasing expression level in a {organism} {cell_type} cell.\nCell sentence:", - "Generate an ordered list of {num_genes} genes by decreasing expression level in a {organism} {cell_type} cell.\nCell sentence:", - "Assemble a list of {num_genes} genes from highest to lowest expression in a {organism} {cell_type} cell.\nCell sentence:" - ], - "response": [ - "{cell_sentence}." - ] ->>>>>>> 593fb74 (Peft feature implemented) } \ No newline at end of file diff --git a/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json b/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json index 9c2cd01..40f3fb9 100644 --- a/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json +++ b/src/cell2sentence/prompts/single_cell_cell_type_prediction_prompts.json @@ -1,4 +1,3 @@ -<<<<<<< HEAD { "model_input": [ "The following is a list of {num_genes} gene names ordered by descending expression level in a {organism} cell. Your task is to give the cell type which this cell belongs to based on its gene expression.\nCell sentence: {cell_sentence}.\nThe cell type corresponding to these genes is:", @@ -20,27 +19,4 @@ "response": [ "{cell_type}." ] -======= -{ - "model_input": [ - "The following is a list of {num_genes} gene names ordered by descending expression level in a {organism} cell. Your task is to give the cell type which this cell belongs to based on its gene expression.\nCell sentence: {cell_sentence}.\nThe cell type corresponding to these genes is:", - "Below is a list of {num_genes} gene names in order of descending expression level from a {organism} cell. Based on this, predict what the cell type of this cell is.\nCell sentence: {cell_sentence}.\nThese genes are most likely associated with cell type:", - "Given the list of {num_genes} gene names ordered by descending expression level from a {organism} cell, identify the cell type.\nCell sentence: {cell_sentence}.\nThe probable cell type for these genes is:", - "Analyze the following list of {num_genes} genes sorted by decreasing expression levels in a {organism} cell and determine its cell type.\nCell sentence: {cell_sentence}.\nBased on these genes, the corresponding cell type is:", - "From the list of {num_genes} gene names ordered by decreasing expression level in a {organism} cell, infer the cell type of the cell.\nCell sentence: {cell_sentence}.\nThese genes suggest the cell type is most likely:", - "The {num_genes} gene names below are listed by descending expression level in a {organism} cell. Predict the cell type based on this information.\nCell sentence: {cell_sentence}.\nThese genes are indicative of cell type:", - "Below is a list of {num_genes} gene names sorted by descending expression in a {organism} cell. Determine the cell type of this cell from its expressed genes.\nCell sentence: {cell_sentence}.\nThe associated cell type for these genes appears to be:", - "The following list contains {num_genes} gene names ordered by descending expression level in a {organism} cell. Deduce the cell type based on this.\nCell sentence: {cell_sentence}.\nThese genes typically correspond to cell type:", - "Here is a list of {num_genes} genes in order of descending expression level from a {organism} cell. Identify the cell type of this cell based on this information.\nCell sentence: {cell_sentence}.\nThe expected cell type based on these genes is:", - "Examine the list of {num_genes} gene names sorted by decreasing expression in a {organism} cell, and from this, identify its cell type.\nCell sentence: {cell_sentence}.\nThese genes are commonly found in cell type:", - "The {num_genes} gene names below are arranged by descending expression level in a {organism} cell. Determine the cell type of this cell.\nCell sentence: {cell_sentence}.\nThe cell type that these genes are most commonly linked with is:", - "Here is a list of {num_genes} genes ordered by expression level in a {organism} cell. Based on this information, identify the cell type.\nCell sentence: {cell_sentence}.\nBased on the expression levels, the cell type would likely be:", - "From the list of {num_genes} gene names sorted by decreasing expression levels in a {organism} cell, predict the cell type.\nCell sentence: {cell_sentence}.\nThe genes provided are most commonly expressed in cell type:", - "Below is a list of {num_genes} genes ordered by descending expression in a {organism} cell. Use this information to determine the cell type.\nCell sentence: {cell_sentence}.\nThese genes suggest the cell type is most likely:", - "The {num_genes} gene names below are listed by descending expression levels in a {organism} cell. Based on this, predict the cell type.\nCell sentence: {cell_sentence}.\nThe cell type corresponding to these genes is:" - ], - "response": [ - "{cell_type}." - ] ->>>>>>> 593fb74 (Peft feature implemented) } \ No newline at end of file From 2b02223e61c3d0d3f8c619bd63c43e45df41450c Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:04:57 +0000 Subject: [PATCH 08/19] merge resolved --- docs/Makefile | 22 ---------------------- docs/make.bat | 35 ----------------------------------- 2 files changed, 57 deletions(-) diff --git a/docs/Makefile b/docs/Makefile index 2f95a20..19417c7 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -21,25 +21,3 @@ help: # Example: sphinx-build -M html docs/source/ docs/build/ -# Minimal makefile for Sphinx documentation -# - -# You can set these variables from the command line, and also -# from the environment for the first two. -SPHINXOPTS ?= -SPHINXBUILD ?= sphinx-build -SOURCEDIR = source -BUILDDIR = build - -# Put it first so that "make" without argument is like "make help". -help: - @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) - -.PHONY: help Makefile - -# Catch-all target: route all unknown targets to Sphinx using the new -# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). -%: Makefile - @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) - -# Example: sphinx-build -M html docs/source/ docs/build/ diff --git a/docs/make.bat b/docs/make.bat index 2d9471d..9d3a30f 100644 --- a/docs/make.bat +++ b/docs/make.bat @@ -34,38 +34,3 @@ goto end :end popd -@ECHO OFF - -pushd %~dp0 - -REM Command file for Sphinx documentation - -if "%SPHINXBUILD%" == "" ( - set SPHINXBUILD=sphinx-build -) -set SOURCEDIR=source -set BUILDDIR=build - -%SPHINXBUILD% >NUL 2>NUL -if errorlevel 9009 ( - echo. - echo.The 'sphinx-build' command was not found. Make sure you have Sphinx - echo.installed, then set the SPHINXBUILD environment variable to point - echo.to the full path of the 'sphinx-build' executable. Alternatively you - echo.may add the Sphinx directory to PATH. - echo. - echo.If you don't have Sphinx installed, grab it from - echo.https://www.sphinx-doc.org/ - exit /b 1 -) - -if "%1" == "" goto help - -%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% -goto end - -:help -%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% - -:end -popd From a37661e62cf4be568644a03757ebcd9c3df506dd Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:07:10 +0000 Subject: [PATCH 09/19] merge resolved --- .../c2s_tutorial_5_cell_generation.ipynb | 2226 ----------------- 1 file changed, 2226 deletions(-) diff --git a/tutorials/c2s_tutorial_5_cell_generation.ipynb b/tutorials/c2s_tutorial_5_cell_generation.ipynb index 19eaeba..98a3200 100644 --- a/tutorials/c2s_tutorial_5_cell_generation.ipynb +++ b/tutorials/c2s_tutorial_5_cell_generation.ipynb @@ -1,4 +1,3 @@ -<<<<<<< HEAD { "cells": [ { @@ -2222,2228 +2221,3 @@ "nbformat": 4, "nbformat_minor": 2 } -======= -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial notebook 5: Cell Generation\n", - "\n", - "In this tutorial, we will demonstrate how to use a pretrained Cell2Sentence (C2S) model to generate new cells conditioned on a specific cell type. Cell generation is a powerful tool for simulating new data, studying cell diversity, and exploring the characteristics of different cell types. By leveraging the generative capabilities of C2S models, we can create realistic cell data that follows the patterns learned from existing datasets.\n", - "\n", - "In this tutorial, you will:\n", - "1. Load an immune tissue single-cell dataset from Domínguez Conde et al. (preprocessed in tutorial notebook 0, two sample donors)\n", - " - Citation: Domínguez Conde, C., et al. \"Cross-tissue immune cell analysis reveals tissue-specific features in humans.\" Science 376.6594 (2022): eabl5197.\n", - "2. Load a pretrained C2S model that is capable of generating cells based on cell type.\n", - "3. Generate new cells conditioned on a specified cell type using the C2S model.\n", - "\n", - "Let's get started!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will begin by importing the necessary libraries. These include Python's built-in libraries, third-party libraries for handling numerical computations, progress tracking, and specific libraries for single-cell RNA sequencing data and C2S operations." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/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": [ - "# Python built-in libraries\n", - "import os\n", - "import pickle\n", - "import random\n", - "from collections import Counter\n", - "\n", - "# Third-party libraries\n", - "import numpy as np\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "from tqdm import tqdm\n", - "\n", - "# Single-cell libraries\n", - "import anndata\n", - "import scanpy as sc\n", - "\n", - "# Cell2Sentence imports\n", - "import cell2sentence as cs\n", - "from cell2sentence.tasks import generate_cells_conditioned_on_cell_type\n", - "from cell2sentence.utils import (\n", - " post_process_generated_cell_sentences,\n", - " reconstruct_expression_from_cell_sentence\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "SEED = 1234\n", - "random.seed(SEED)\n", - "np.random.seed(SEED)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Load Data\n", - "\n", - "Next, we will load the preprocessed dataset from the tutorial 0. This dataset has already been filtered and normalized, so it it ready for transformation into cell sentences.\n", - "\n", - "Please make sure you have completed the preprocessing steps in Tutorial 0 before running the following code, if you are using your own dataset.. Ensure that the file path is correctly set in DATA_PATH to where your preprocessed data was saved from tutorial 0." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "DATA_PATH = \"/home/sr2464/palmer_scratch/C2S_Files_Syed/Cell2Sentence_Datasets/dominguez_conde_immune_tissue_two_donors_preprocessed_tutorial_0.h5ad\"" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 29773 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'assay', 'sex', 'n_genes', 'n_genes_by_counts', 'total_counts', 'total_counts_mt', 'pct_counts_mt'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", - " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", - " obsm: 'X_pca', 'X_umap'\n", - " varm: 'PCs'\n", - " obsp: 'connectivities', 'distances'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata = anndata.read_h5ad(DATA_PATH)\n", - "adata" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "adata.obs = adata.obs[[\"cell_type\", \"tissue\", \"batch_condition\", \"organism\", \"sex\"]]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Parameters 'cmap' will be ignored\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sc.pl.umap(\n", - " adata,\n", - " color=\"cell_type\",\n", - " size=8,\n", - " title=\"Human Immune Tissue UMAP\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "3.408124" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata.X.max()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We are expecting log10 base 10 transformed data, with a maximum value somewhere around 3 or 4. Make sure to start with processed and normalized data when doing the cell sentence conversion!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Cell2Sentence Conversion\n", - "\n", - "In this section, we will transform our AnnData object containing our single-cell dataset into a Cell2Sentence (C2S) dataset by calling the functions of the CSData class in the C2S code base. Full documentation for the functions of the CSData class can be found in the documentation page of C2S." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "adata_obs_cols_to_keep = [\"cell_type\", \"tissue\", \"batch_condition\", \"organism\", \"sex\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 29773/29773 [00:11<00:00, 2525.14it/s]\n" - ] - } - ], - "source": [ - "# Create CSData object\n", - "arrow_ds, vocabulary = cs.CSData.adata_to_arrow(\n", - " adata=adata, \n", - " random_state=SEED, \n", - " sentence_delimiter=' ',\n", - " label_col_names=adata_obs_cols_to_keep\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", - " num_rows: 29773\n", - "})" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "arrow_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'cell_name': 'Pan_T7935490_AAACCTGCAAATTGCC',\n", - " 'cell_sentence': 'RPLP1 ACTB EEF1A1 HSP90AA1 TMSB4X B2M FTH1 KLF6 HSPA1B MALAT1 RPS12 HSPA8 RPL13 MT-CO1 ATF3 MT-CO2 RPL41 TPT1 MT-CO3 RPS19 HLA-B RPL10 RPS4X RPL28 MT-CYB DUSP1 RPL30 MT-ND4L RPS15 FOS RPL34 RPS2 RPLP2 MT-ND3 RPS18 RPS8 TRBV7-2 RPL32 RPS3 ANXA1 RPL11 HLA-C RPS27 ACTG1 UBC RPL3 RPL37 RPLP0 MT-ATP6 JUNB RPS28 RPL18 UBB MT-ATP8 RPS14 RPL39 PFN1 GAPDH HSPA1A RPL18A SRGN RPS27A RPL26 RPL19 RPS15A HLA-A DNAJB1 RPS3A CREM RPS13 MT-ND1 RPL21 RPS25 BTG2 RPL35A FAU RPL8 RPL7A RPS24 RPS6 RPS16 RACK1 NFKBIA RGS1 RPL29 CALM1 RPL9 RPL37A MT-ND5 TNFAIP3 RPS23 IL7R RPL36A PTMA NFKBIZ UBA52 EIF1 CRIP1 CORO1A RPL14 HSP90AB1 RPL10A CXCR4 RPL4 EEF1B2 RPL36 RPS9 RPL27 NACA VIM H3-3B RPS7 HSPH1 ATP5F1E HLA-E RPL17 RPSA MYL12A RPL12 CD69 TAGAP RPL35 RPS29 RPL6 SARAF ZFP36L2 MT-ND4 ARHGDIB BTG1 RPS21 EEF1D PNRC1 EEF1G HSPA5 FYB1 CD3E IFITM1 RNASEK EEF2 MT-ND2 FTL S100A4 JUN IFITM2 CYTIP OST4 LAPTM5 RPL36AL PLAAT4 PFDN5 SAMSN1 DNAJA1 EIF4A1 FXYD5 HSPE1 CTLA4 IL32 RPL24 CFL1 SAT1 RPL13A NPM1 NDUFV2 SRSF7 ITM2B POLR1D CCNI CALR ZFP36 COX7C PTPRC GADD45A CD3G RAC2 MYL6 UBE2D3 CCL20 RPS5 RPL22 TOMM7 RPL15 C12ORF57 LSP1 SON H4C3 RPL23A RPL31 DDX5 EVL AHR SERF2 STK17A CD6 PTGER4 OSTF1 OAZ1 TMA7 PHLDA1 COMMD6 PPIA TMSB10 RHOH TUBA1B KTN1 PDIA3 DUSP5 BTF3 SSR4 ATP5MC2 S100A6 CEBPD TRAV13-2 STAT1 HSPB1 PSMB9 RPL38 HNRNPA2B1 FLT3LG CSTB CDK2AP2 CSK MIF MCL1 PSME1 TXNIP RHOA HNRNPA1 UBL5 PTGES3 PDCD4 SLC2A3 ERCC1 SNHG29 NFKBID SRP14 ARPC1B NR4A2 CMTM6 CD44 ITGA4 GNB2 TRAV19 BHLHE40 HMGB1 ARPC3 TRIR PRKCH NME2 KLRB1 CLIC1 ANAPC16 NCOR1 COX5B MYL12B SAP18 RHOB TCF25 SOD1 SRSF9 FOSB PCBP1 CD96 TBC1D10C CD164 CD3D ACTR2 COX4I1 SH3BGRL3 KMT2E HSPD1 PABPC1 SPCS2 SERP1 TNFRSF1B TAGLN2 PCBP2 RPL5 LDLR YWHAB CSRNP1 COX8A MYADM TRMT112 ATP5MG GABARAP ELF1 PRR13 RPL22L1 WAKMAR2 SIT1 GADD45B RPS17 S100A10 RBBP4 HNRNPDL CD2 UQCRQ COX6B1 RGS2 CHCHD2 TAF1B RPL27A TAP1 MTDH CD99 ARF1 TBCA TMEM14B HNRNPA0 RPS11 SEC61A1 RSRP1 TUBB ACIN1 HNRNPUL1 OXNAD1 LMO4 CTSH RBM8A RGL4 NFU1 AP1G2 TSC22D3 CASS4 CCNH RPS26 PIK3R1 SH3KBP1 SSBP4 TPR GADD45G ZFAS1 COTL1 BCL7C MZT2A LAT FUS SDF2L1 KRTCAP2 MRPL41 CENPX SETD5 TMC8 COX17 DNAJB4 CDKN1B ODC1 ACAP1 ANXA6 CYBA SUMO3 TMBIM6 TMEM259 CD37 PRDX2 UBE2D2 BTG3 PARK7 CD247 TMEM258 HNRNPAB SPOCK2 SEPTIN1 LAMTOR5 RNF11 SNX5 SASH3 PPM1G ARF6 EIF5A IL4I1 RBM3 RSF1 SLA CALM3 SNRPB SHISA5 ARID5B KXD1 PTPRCAP GBP1 STN1 NSA2 ATP1A1 LCK PSMB8 PSMB3 HNRNPC RNF167 RESF1 ACTR3 CKLF CD52 RPS27L GSTK1 GIMAP7 DCXR RGS14 VASP PBXIP1 GOLGA4 RPL23 YWHAQ SNHG16 TAOK3 IGBP1 DOCK10 SRRM1 PSMC3 IKZF3 AHI1 RPL7 TMEM87A EIF5 MED1 ANKRD12 IWS1 SLC25A6 TUBA1C LRRC41 SEC11C DLST VMA21 MKNK2 RALB THUMPD1 DBF4 RHEB WASHC3 VRK2 SUPT4H1 FADD CHD1 CAPN1 TMEM179B CKS2 RGS10 EIF4E BPTF RNMT DDX39A GADD45GIP1 DYNLL1 SF3B2 CDKN2AIP RAP1B ACTN4 ABRACL MOB4 METTL23 ITSN2 MTF2 VSIR PER1 COX7A2 COX14 IPCEF1 YWHAH CYRIB MOB3A SP2 BCL11B STUB1 RNF213 PRKRA EDF1 PRPF38B RHOG BAG1 ATOX1 CACYBP MAP4K1 PPP1R2 PAXX ADA NDUFA12 WAC ELK3 PRRC2C MUS81 CCT4 ARL5B RALBP1 FBXW11 LCP1 LEPROTL1 PDCD10 HNRNPR NR3C1 PPP4C BATF ABLIM1 PSMA2 TRAT1 RUNX3 CIB1 ARPC2 ABI3 UGP2 NDUFAB1 HCLS1 DERL1 RAB5A INSIG1 CNBP CHROMR DSTYK DPP4 TOMM6 PDE4D LUC7L2 JUND ARHGDIA CEMIP2 POLE4 ANXA11 PLEKHB2 SDCBP MANF FAM83D IMP3 TMCO1 SUCLG1 MBD2 NDUFA10 PDIA6 S100A11 DNPH1 TARDBP PTDSS1 RP11-25K19 LPXN FYTTD1 RORA NASP ATP6V1F RIPK2 IDI1 RASSF7 MT-ND6 RWDD1 CYB5R3 MAZ PIM1 PSMA3 GPX4 PACS1 TNIP1 PLEKHF1 STXBP2 MSMO1 UQCR11 EPB41L4A-AS1 TMIGD2 PATL1 COX6A1 CCND3 TUBB4B OCIAD2 UBE2V2 ASMTL MAP3K8 FERMT3 SH2B1 ACP5 RPS6KB2 GABPB1-AS1 MTRNR2L12 ZFAND2A EIF3D ATP5PB NEDD8 NDUFA1 C19ORF25 CYB561D2_ENSG00000114395 PPP1R18 SYF2 PIGT SLC25A3 KHDRBS1 GIMAP4 NAXE HMGN1 RGS19 SUMO1 YWHAZ ERN1 LRRFIP1 NCF1 GALNT11 PSMG2 SNRPA1 IFNGR1 ENSA LAMTOR4 TBRG1 LINC-PINT PSMA7 SH2D2A HCST GUSB SEC61B TAX1BP1 RNF149 GNG5 PIP5K1A SIGIRR ATP6V1H RXYLT1 TRAPPC2B STK4 GPR174 CLEC2B CDC5L MLEC SQSTM1 GNAS DAXX ADAR NRIP1 TPI1 ITM2C NOSIP HADHA GTF2B ATP5IF1 ATP6V0B VEZF1 MYBL1 TOMM5 UQCRFS1 PDE4B ELL MRPL18 TRAC PIGBOS1 PPIB MDH2 PMVK PGAM1 PEX2 RPA2 FBXW5 MICOS13 CYBC1 ELOB PSMB4 COX6C GTF2I CHMP4A ALOX5AP SSR3 SELENOF AIP UXT TBCB SKAP1 RBM4 NDUFA9 DNAJB11 ATP5MK REX1BD GATA3 MVP GIMAP5 DNAJC2 SHKBP1 CAP1 SSBP1 SUZ12 SNHG6 LTB HECA WDR83OS DUT ANXA2 RRAGA PPP1R12A TAPBP DOK2 DYNLT3 RBPJ ATP6V1G1 CD40LG OCIAD1 TCEA1 ATM SLC44A2 OGA HNRNPK PPP2R5E NDUFA4 PLAUR NT5C3A RBL2 PHTF2 ZFAND5 CCR6 BCL3 GYPC SPTY2D1 MBP AKAP9 CD83 HNRNPF RAC1 SSR2 SMARCC2 MRPS21 SRSF3 DDX21 NDUFC1 BST2 FSD1 TRIB2 SF3B6 GDI2 HLTF APBB1IP LY6E NDUFB4 NAA38 FKBP1A PSMB10 FDPS MBNL1 UQCRB TMED2 H1-10 RO60 CEP57 CDKL3 CAPNS1 GIMAP1 EZR HOXB4 JAGN1 EIF2S2 DNAJB9 KCTD20 ARGLU1 EWSR1 SH3GL1 EIF3F RABGGTA MEA1 MLLT3 SARNP UBAC2 TRA2A ARL6IP1 GPI GUK1 DPH3 TGFBR2 ASB2 SRP9 GNAI2 RAB5IF PPIH EIF4A2 UBQLN1 GPR65 RASAL3 NDUFB6 RPN1 HNRNPA3 GBF1 OGG1 LCP2 DESI2 DUSP2 MGST3 CCDC18-AS1 CD53 POLM RTRAF ME2 PHAX ATP6AP1 RDH11 TCERG1 ACTR8 SLC1A5 DSE SLC25A39 FDFT1 CIAO2A LATS1 WDR33 CCDC107 MARCHF7 FAM174C LRPAP1 COG6 IL10RA MNAT1 CLIC3 TUSC2 NAT9 FAM13B EPG5 FKBP11 CREB3 ARHGAP45 MRPL9 MGA MIDEAS PHF20 CHD9 RCE1 VDAC2 EEF1E1 SSB GBP5 NMRK1 CCT8 SCAP ACER3 VAMP8 TALDO1 PHGR1 TC2N GRID2IP EIF2AK1 TOLLIP TBC1D10A C17ORF100 NFRKB CCDC137 E4F1 XRCC5 FCMR PGPEP1 DGCR6L CHURC1 OFD1 MAP4 PLEKHA2 AMD1 MORF4L1 IER5 DCTN2 CTDSP1 DDX6 AHCYL1 PNKD ELOVL1 FXR1 SAPCD1 SELENOT UBE2L6 PMM2 RNF113A PGRMC2 CPSF6 ZNF267 MRPL50 IL16 CREBL2 ASXL2 NUDCD3 ZNF445 C3AR1 CCR5 DGKE RUNX1 AKAP11 RP11-562I5 ARIH1 PPP1CB NDUFAF3 MRPS5 ACTR1B TPD52 SF3A2 CLTC TMEM33 NDUFA5 HMGXB4 PPP1R21 RC3H2 ZNF580 PRKCSH GZMM SEC13 CTNNA1 VPS18 SYNGAP1-AS1 MAPRE1 ZC3H8 DSTN MAN2B2 MGAT4A PAK2 CRY1 LSM7 ZC3H6 TMEM230 CPQ PSMD3 TIMM17A TYMP ST6GALNAC6 PHB2 KDELR2 LAMP2 NUMB RALY ADAM8 R3HDM4 DNAAF2 ADPRM CCSER2 THRAP3 KIDINS220 RBM15B DEF6 ADNP POLR1E IQGAP1 POFUT2 EIF3K NOL7 NMUR1 NOM1 GNPDA1 PKM CWC25 IGF2R ATP2B4 GPS1 LRP10 CA10 ERI3 SMAD3 ANP32B COX7A2L EHBP1 CHUK H2AZ1 LPIN2 ASAH1 MRPL33 BCL2 DNAJC1 USO1 SUMF2 CHCHD3 NAA20 TMEM60 IER3IP1 FLII YBX1 LAIR1 MESD TSC22D1 SF1 TMEM273 PLCG1 NMD3 TMEM18 ABHD14A SLFN5 ENTR1 CHMP6 IRF2BP2 CHCHD5 HTATSF1 RPS10 LSM14A SUPT7L PEX26 YJU2 HDDC3 CFDP1 SELPLG ENO1 KDM5A MTLN ZNF706 ERVK3-1 DCP1A DBNDD2 TAX1BP3 SPINK4 RNF31 NEPRO SHFL PSMD8 IL17RA CHST14 MPC1 GLOD4 BICRAL SMIM26 KIF5C PRKAR1A TENT5C NPRL2 TTC9C RPUSD3 SSH1 ARHGAP35 RSBN1 ECHDC2 G3BP2 PRR5 SMG9 SUPT3H ATP2A3 SIN3B LSM12 PTEN ZNF93 NONO SRRM2 ITFG1 C21ORF91 HINT1 GOT1 C1QTNF1 AZIN1 MZT1 LAP3 NDUFB8 NDUFA13 FRMD4B LYRM2 IL21R PARP12 SCMH1 PBRM1 HAUS4 RAB4B FLJ40194 HIKESHI NR1D1 MFSD8 SRSF1 SMIM30 XRN2 SAMD4B SEM1 CAPZB PIAS4 IKZF1 EIF3I AGTPBP1 MZT2B C1ORF122 MUTYH WDR61 DDX39B CCNDBP1 ZNF816 PFDN2 POLR2F ANO6 NDUFS6 CTNS ATP11B SIVA1 EIF4E3 CTSC SMC4 CDC42SE2 FAM131C PLPP6 TRPC4AP MTMR14 GABARAPL1 FAM133B RFNG EIF2B1 LSM1 ISY1 EIF3G ORAI2 FAM53B SEPTIN2 HTRA2 SEPTIN6 KAT7 MBD4 CAPZA2 WDR20 NDUFB7 TWF2 COMMD5 GPR68 SPPL3 TMEM59 NCL PJA2 SDHA SLMAP CBX3 TMEM161B-AS1 PPOX ACBD3 GOLGA7 GTF2H1 MAP3K2 COA6 PHF5A COPS7A NAA10 SNX14 CUL1 ALG13 TNIK STARD3 LINC00892 SNAI3 RABAC1 USP42 NDUFA3 DDX58 PSMC6 RBCK1 HNRNPH3 ZFAND6 SDHD CHCHD10 PUM1 LDLRAD4 TCHP CNOT11 KIF1C SEC61G TACC1 PSMD6 NIPBL DAPP1 RAB2A TRIM5 LMNB2 SUPT6H AP3S1 CLK1 NSUN2 NUP88 PPA1 UMAD1 SETD9 DCAF15 ANXA2R TMEM9B EGLN2 MRPS18B PSD4 GTDC1 SUCO BUD31 IER2 UPF3A PINX1_ENSG00000254093 NUDC TAF7 UTP15 PTPMT1 PSME2 MALT1 PSTPIP1 TSPYL1 CTSD HIGD2A SBF1 LINC00667 FEM1A RAB5C TAF2 SHOC2 RASL11A AMZ2 TRIM65 ATP6V0E1 HEBP1 PSMD1 NDUFAF8 CORO1B MRPL34 UBN1 RAE1 SPINT2 SOCS1 TRIM52-AS1 TFDP1 TES YIPF2 STX5 BZW1 PDCL3 NOLC1 TPM3 INTS11 RAB35 COQ10B ZNF480 C1D THAP4 EBAG9 FOXP1 SLC30A6 NUS1 MRPS24 PPP2CA USP4 C9ORF16 MSH2 UQCRC1 SLC38A1 ACO2 WASHC5 TXLNG PHF20L1 RAB6A SERINC1 YTHDC1 MIF4GD C1GALT1 KRR1 NDFIP1 GMFG DCAF8 SNX6 PAIP2 PLAA SRP19 RAD21 TECR OTUB1 CLK3 BNIP2 NEK9 COPE RAB9A RMC1 JOSD2 MAP3K1 RNF144B ADGRE5 UBA5 NLRC3 LYPLAL1 SURF6 PDE9A ZNF720 C17ORF107 SPPL2A OPTN LACTB DNAJA2 CAMK4 PLP2 ARMC6 IDH2 FUNDC2 SNHG3 CAPG TMEM106C DR1 PGGHG TUT7 CYB561D1 EIF3E FURIN VPS26B APBB1 NTAN1 ATP5MF MAX MRPL14 ATP5ME ORAI1 SEC62 TNFRSF1A HTT EIF2AK4 SCAPER POLB FAM204A RRP12 ABHD5 IMPDH1 TAF1D TDG IMP4 SMC6 TRIM28 FAS ILK PPP1R16B TSR3 NOP56 EIF5B CUTA GLO1 PPP3CB CENPK MTRR ITGAE GOLGA3 GFER EPSTI1 THEMIS TRIAP1 HSD17B7 TSTD3 ANKRD39 PIP4K2A MTFP1 FAM222B SRFBP1 HOXB2 TRAPPC5 SRSF8 HECTD1 CCAR1 XKR8 RBM26 ISCA1 TRBC2 UBE2B TIMM8B RPUSD1 SAT2 FAM102A ST6GAL1 METTL9 C2ORF68 PERP SNU13 ANKZF1 CBX5 GPN1 COMMD8 EGLN1 HERPUD1 SENP6 SLC38A2 AARS1 GNL2 G3BP1 GPR108 PSMA4 SP100 MFSD10 TMEM70 QRSL1 DAD1 RPS19BP1 SNHG1 CSDE1 TAF4B ASF1A N4BP2L2 RNF138 FBXL5 JAK1 NCLN RAB11B PPP1CA ITGB2 KDELR1 PSMB1 MTX2 SLC35E2A NDUFS8 HAGH PIGW IVNS1ABP SDHC POLDIP2 EIF4G1 ANKRD36 SEPTIN7 CSNK1D PSMF1 TM9SF4 GAB3 MYL6B HNRNPL WIPF1 GATAD1 RFFL PRKCQ-AS1 GTPBP10 INO80D IFITM3 GAS5 WASHC1 CTNNAL1 PTGER2 USP33 ARRB2 ARMCX6 GMIP UMPS TRIM22 DDX41 SFPQ RBM25 MRPL38 CNP FAM193B MAP3K11 WDR74 PIGC CDC37 PPIP5K2 TRMO AGTRAP JMJD8 ARID5A ALKBH7 CYTH1 SET PAF1 SNHG5 FAM174B ADI1 SUDS3 CDCA7 GTSF1 MTCH1 TGIF2 MLX PYGO2 EIF2S1 DNPEP IL23R RPA1 CDC37L1 GYG1 ANP32A SRSF2 RNASEH2B WDR44 ZPR1 GIPC1 RRM2B ILVBL ARL2BP BRK1 YIF1A CEP164 DPY30 NUDT7 PPP2R1A R3HDM1 MSN PSIP1 HMGN4 CCDC152 STOML2 EEF1AKMT2 H2AZ2 CHST12 CHFR FKBP15 SPNS1 APH1A NR4A3 CNOT9 GPSM3 TESK1 CDK5RAP1 TNFAIP1 FAM118B ZBTB7A PCED1B-AS1 MRPS18A BUB3 ICMT DDIT3 DNM1L DCTN4 PPIG CCDC91 LZIC CHD2 BIRC2 AHSA1 ARAP2 COMMD10 NUCKS1 ASAP1 DCTPP1 ETFDH NAA80 STAU2 CCNL1 CASP3 CCDC174 PRNP APOA1-AS PPP1R11 SRP68 C1ORF43 RASSF1 MYD88 AKAP13 SLC25A5 ERH UBE2I ATP5PD ORC3 NUP37 TTC31 WBP2 PDE7A KPNB1 ETFA STK25 PJVK COX19 ATP5MC3 PPP2R2A MDH1 PSMB6 GTF2E2 B3GNT2 TSC22D4 GPD2 MBIP ZFR JTB GPRIN3 LPIN1 SLC35A1 NXT1 KLHL22 DYNC1I2 AP1S1 PPP1R15B SMIM15 TMEM65 HAUS3 KLHL28 MRPL20 MVK ATR MIB2 YPEL3 SCOC WASHC2C SPRY1 LCLAT1 CCDC25 SLC43A3 CIAO3 WBP11 TRIM4 C17ORF49 DTX1 VAMP5 ZSCAN16-AS1 TNFSF13B ARHGAP15 CISH DCP2 GRPEL2 PHB AASDHPPT PUM2 ISG20 PFKM SLC2A1 NBL1 TMED4 COPS3 SRSF11 ZNF710 POMP TTC14 ZNF414 PISD TMEM219 MIR23AHG COQ4 OXA1L DNAJA3 KMT2A MAGOH LYPLA2 WSB1 POLR2B AKIRIN2 PSMB2 UIMC1 DDX18 TCOF1 TNFRSF14 STARD3NL CELF2 NABP1 PTP4A2 LRRC59 TMEM167B CAMK2G SLC4A1AP EIPR1 NUCB2 MED6 VEZT SP4 ARL3 USP12 ARHGAP9 VMAC FIP1L1 RP11-316M20 ADH5 TMC6 IRF1-AS1 LIG4 SNX1 MACF1 GNL1 TPM4 RMND5A LPAR6 DNAJB2 NOP53 CDK2AP1 FIS1 PITPNM1 SF3B4 SNAP47 S100PBP C4ORF33 CHST11 RGS18 C7ORF31 PSMD4 EFCAB7 TTC39C ANXA5 KRI1 FAM214B DUSP12 NR2C1 CBLB UNG LSM8 MYO9B GLMN RALA GTF3C6 ISCA2 DNTTIP2 SELENOK MRPS36 KPNA3 THRA PTS DUSP6 VTA1 PPARG SEPTIN9 UBE2N FRY BCAS2 CAMKMT SAMHD1 GBP2 TMEM50A STAT5A IL17A PCYT2 ISG15 MAPK3 PDCD4-AS1 TIAL1 RTF1 CSNK2B RBM17 LPCAT4 ST13 CNBD2 TMEM184B RNPC3 ARCN1 SMAP2 BLOC1S1 NAMPT ZNF597 EMG1 SLC66A3 HDLBP C11ORF58 SH3BP1 SMARCB1 RP11-726G1 ZNF564 IFI27L2 ATG3 C6ORF226 REL GIMAP6 OLFM2 OGFR BAZ1A RAB7A EIF3L TBC1D20 SDHAF2 PARP10 GAK FYN TBXAS1 PRDM1 FAM241A TMEM263 SRPK1 CD2BP2 SERGEF SURF4 MTERF4 PPP1R10 IRF9 USP14 ZFAND2B AK3 CYTH3 PEBP1 PLIN2 NARF ICAM2 ZRSR2 HELZ C14ORF119 DCAF5 RBM42 ITFG2-AS1_ENSG00000258325 ZNF524 CRNKL1 FASTK UBXN1 MYO1G QTRT1 FLOT1 DNASE2 STK40 USP47 RFLNB ZFYVE28 FHL1 TATDN2 SLC25A25 ATP6V1B2 GSAP MRPL10 PSMD11 ZNF821 RANBP9 TIPRL TMED10 EIF3M HMGN2 UHMK1 TRBV30 EMP3 HPS6 TTC17 OSBPL8 COMT ERP29 GRPEL1 ZNF595 ROGDI RAD23A LYSMD2 ANKRD44 FRMD8 SRSF10 BCL2A1 TBC1D31 ALDH9A1 CHMP1A GABARAPL2 RPS20 MRPS2 CAST TMEM200A H4C2 ATRAID CRYBG1 CRY2 OSBPL7 TRAPPC1 POLR2K TESMIN UBE2D1 GNAI3 SLC39A6 HMGCS1 TMEM138 TMEM223 CHP1 ATP5MJ MSRA SQLE ATRX ZNF207 PPP1R15A DNAJC3 SNX3 FBXO9 FAM162A BTF3L4 NKIRAS1 PRDX6 EHMT1 SYS1 USP36 STX4 TMED7 NR4A1 GNA13 LINC00299 ST3GAL5 IDH3A NAA16 SLC38A10 CRYBB2 B4GALT1 METTL26 MRPL54 TRAF3IP2 DTX3L NDUFA6 NDUFAF4 SUCLA2 CALHM2 GTF2IRD2B RP11-706O15 IK MAGI3 TCTA PBDC1 BRD7 IRF1 P2RY10 CTBS CUX1 PRKD2 PGK1 BCLAF1 IRAG2 CIAPIN1 TNFRSF25 SNRNP200 IL2RG PSMA6 UQCRC2 RTF2 SLC35C2 GNG2 ZBTB22 MEF2A NOP10 LY9 MAP2K2 COMMD1 TMEM203 VPS29 SOD2 CITED2 FLI1 FMNL1 MRTO4 RETREG2 FGFR1OP2 RNF41 UTP4 TKT DHX36 ID2 TMEM245 ERP44 ESF1 BAG3 NDEL1 DAP3 HM13 PTGR2 ZFAND3 UCP2 BIN2 MCF2L2 PHKB SUB1 PDE3B CEP250-AS1 RNH1 WDR1 FAM117A CAMTA2 UGCG LINC00294 PHF14 PTPN22 KATNBL1 NT5DC1 TRIM38 ZNF780A C19ORF53 SNRPG TDP2 EIF4H TMEM140 ZCCHC17 ANKLE2 CDS2 EPHB6 CCDC90B ATAD3C COL18A1 FBP1 AHCY AFTPH ZNF432 HSPA9 CMSS1 FGD3 ANXA7 SLC25A13 RNF5 KRT10 KDM2B-DT ATP5F1D SCAMP3 KIF2A SHMT1 MRPL57 CD5 MLH1 ACOX3 ZNF593 TTI2 TRAPPC10 SRP72 CXCR6 COPS5 TET2 HEBP2 OGT ANKRD13D CEBPZ MRPL23 UBE2V1 AP2M1 SLC39A4 LLGL1 DLD ACAA2 SCAMP4 PARP8 CXXC1 MAD2L2 GIT2 OSGIN2 FAM219A ERLEC1 PTPN7 TMEM41B SERTAD3 TCF7 ARPC5 NCBP2AS2 ZNF211 SNRPB2 B9D2 ANKRD27 TIPARP RAB1B SRM PARP16 EIF4EBP2 GDI1 ARPC5L CEACAM21 IVD EXOSC4 KDM6A STARD7 JAK3 CBR1 ARL6IP5 STK26 UFM1 ARHGAP18 ESD ISOC2 HCFC1 RING1 PRELID1 MGME1 NDUFC2 CELF1 PNP IFT27 KBTBD2 TUFM TSTD1 CISD3 C17ORF67 BUD23 SCRN2 CHCHD7 FARSA RP11-29H23-1 LINC02481 TPP1 THYN1 ARHGEF1 GCLM PRPF39 TRAPPC6B SLF1 SMIM3 EVI2A AZIN2 ASH1L API5 COG2 SLC25A22 CHD4 WRAP73 CDC26 UBE2L3 EPC1 ATP2B1 CCAR2 RRN3 UBA1 CSNK1A1 CASP8 PELI1 CNOT2 SRP54 VAPA MRPS33 NDUFB11 NAF1 UBE2G2 DVL3 TLE5 CALCOCO2 UQCR10 SIRPG COX7B NDRG1 EIF2S3 H3C4 SMCHD1 RAN MAPKAPK5-AS1 TSG101 HAX1 ANKDD1A DCTN3 CD55 PSKH1 PET100 IMMT SRGAP2C H3-3A PIGH RBM48 FAM177A1 TEFM FBXL4 MID1IP1 PRR5L SLC25A11 NGDN NCAPD3 SLC9A3R1 CDIP1 GRK6 SDF4 DENND2D CASP7 EFR3A NFAT5 PRELID3B TEX30 CIRBP CSNK1G1 MCRS1 CHMP2B TMOD3 PRKX POLR2C NSFL1C POLR1H TAP2 PIANP ARL6IP6 RIPK1 TDP1 SCAF11 SNRPN ZNF335 USP3 UBQLN2 ARMCX3 HSDL1 RSU1 TXNL1 TMEM101 BAD KIF5B AP1AR FAM104A GBP4 AC058791 NDUFB1 DPP7 NDUFB2 RANGAP1 SETX MAF1 NME4 TRGV10 TACC3 AP5Z1 PITPNB EDEM1 CTD-2095E4 ANKRD28 MINDY2 YPEL4 IGHV4-34 TRIM44 ARL6IP4 GART RAD18 SF3B5 BZW2 ECD ZYX HECW2-AS1 CNTRL RECQL PARP9 UPP1 PYCR2 ARHGAP30 TBC1D22B RASGRP1 STIM1 ZNF263 ZNF230 LDLRAP1 PDCD2 FOXO1 UNC119B RNF114 YPEL5 IFNGR2 PRRC1 EIF4B PDXK RAB8B RICTOR ARL8A ESCO1 RBM38 PPIF GMPS HDDC2 FBXO42 PTP4A3 SERPINH1 TRIM69 WTAP PEMT VPS72 WAS PPP4R3A CDV3 CETN2 VAC14 TRIM21 DAZAP2 ARF5',\n", - " 'cell_type': 'CD4-positive helper T cell',\n", - " 'tissue': 'ileum',\n", - " 'batch_condition': 'A29',\n", - " 'organism': 'Homo sapiens',\n", - " 'sex': 'female'}" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sample_idx = 0\n", - "arrow_ds[sample_idx]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This time, we will leave off creating our CSData object until after we load our C2S model. This is because along with the model checkpoint, we saved the indices of train, val, and test set cells, which will allow us to select out test set cells for inference." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Load C2S Model\n", - "\n", - "Now, we will load a C2S model which we will perform cell type-conditioned single cell generation with. We highly recommend loading either a model which you have finetuned to do cell generation with (see tutorial notebook 3 for how to perform finetuning) or the C2S-Pythia-410M conditional cell generation foundation model which was pretrained to do cell type-conditioned generation on a diverse array of datasets (details in the repo ReadME, Model Zoo section).\n", - "\n", - "For this tutorial, we will load the best checkpoint of a model which we finetuned to do cell type-conditioned cell generation with using tutorial notebook 3. This model was intitialized from the C2S-Pythia-410M conditional cell generation foundation model, and finetuned for cell generation on the training set of our immune tissue dataset. We load it here as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using device: cuda\n" - ] - } - ], - "source": [ - "# Define CSModel object\n", - "cell_type_prediction_model_path = \"/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_3/2024-08-30-10_59_21_finetune_cell_type_generation/checkpoint-3700\"\n", - "save_dir = \"/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_5\"\n", - "save_name = \"cell_type_generation_pythia_410M_inference\"\n", - "csmodel = cs.CSModel(\n", - " model_name_or_path=cell_type_prediction_model_path,\n", - " save_dir=save_dir,\n", - " save_name=save_name\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will also load the data split indices saved alongside the C2S model checkpoint, so that we know which cells were part of the training and validation set. We will do inference on unseen test set cells, which are 10% of the original data." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_3/2024-08-30-10_59_21_finetune_cell_type_generation/checkpoint-3700\n", - "/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_3/2024-08-30-10_59_21_finetune_cell_type_generation\n" - ] - } - ], - "source": [ - "base_path = \"/\".join(cell_type_prediction_model_path.split(\"/\")[:-1])\n", - "print(cell_type_prediction_model_path)\n", - "print(base_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys(['train', 'val', 'test'])" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "with open(os.path.join(base_path, 'data_split_indices_dict.pkl'), 'rb') as f:\n", - " data_split_indices_dict = pickle.load(f)\n", - "data_split_indices_dict.keys()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "23847\n", - "2948\n", - "2978\n" - ] - } - ], - "source": [ - "print(len(data_split_indices_dict[\"train\"]))\n", - "print(len(data_split_indices_dict[\"val\"]))\n", - "print(len(data_split_indices_dict[\"test\"]))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Select out test set cells from full arrow dataset" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", - " num_rows: 29773\n", - "})" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "arrow_ds" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dataset({\n", - " features: ['cell_name', 'cell_sentence', 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'],\n", - " num_rows: 2978\n", - "})" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test_ds = arrow_ds.select(data_split_indices_dict[\"test\"])\n", - "test_ds" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here, we do not need to create a CSData object. We can simply supply cell types from our test dataset to the cell generation function from tasks.py" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Generate cells conditioned on cell type\n", - "\n", - "Now that we have loaded our finetuned cell generation model and have our test set cells, we will generate cells using the generate_cells_conditioned_on_cell_type() function from tasks.py, which takes as input a C2S model object as well as a list of cell type to prompt C2S to generate. The function will return 1 generated cell sentences for each cell type supplied, and will handle prompt formatting for us." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "cell_types_to_generate = test_ds[\"cell_type\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2978\n" - ] - }, - { - "data": { - "text/plain": [ - "['CD8-positive, alpha-beta memory T cell',\n", - " 'CD8-positive, alpha-beta memory T cell',\n", - " 'CD8-positive, alpha-beta memory T cell']" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "print(len(cell_types_to_generate))\n", - "cell_types_to_generate[:3]" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "inference_batch_size = 16" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Reloading model from path on disk: /home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/csmodel_tutorial_5/cell_type_generation_pythia_410M_inference\n", - "Generating 2978 cells using CSModel...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 2978/2978 [1:54:29<00:00, 2.31s/it]\n" - ] - } - ], - "source": [ - "generated_cells = generate_cells_conditioned_on_cell_type(\n", - " csmodel=csmodel, \n", - " cell_types_list=cell_types_to_generate, \n", - " n_genes=200, \n", - " organism=\"Homo sapiens\",\n", - " inference_batch_size=inference_batch_size,\n", - " max_num_tokens=1024,\n", - " use_flash_attn=False, # at smaller sequence lengths (< 1024), flash attention doesn't significantly benefit text generation.\n", - " do_sample=True,\n", - " top_k=50,\n", - " top_p=0.95,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that the function has generated 2978 cells given the cell types which we provided it, mimicing the cell type frequency in the real test set. We can save our generated cells below:" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2978" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(generated_cells)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "with open('/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/generated_cells.pkl', 'wb') as f:\n", - " pickle.dump(generated_cells, f)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here, we view a few of our generated cell sentences:" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['MALAT1 TMSB4X B2M MT-CO1 RPLP1 ACTB MT-CO2 RPS27 HSPA1A MT-ND3 RPL41 HSPA1B MT-CYB RPS12 MT-ATP8 RPL28 RPS19 EEF1A1 RPL13 MT-CO3 DNAJB1 RPL30 RPL10 RPS15A MT-ND4L TPT1 RPL39 JUN RPL37 RPL32 RPS28 HLA-B RPS3 RPS3A RPL19 RPS27A BTG1 HLA-C RPL36 RPL34 MT-ND4 RPL26 RPS4X RPS23 RPL11 RPS18 RPL35A RPS6 RPL18 RPS21 RPS29 FOS HSPA8 RPS14 RPL37A RPL7A RPL29 RPLP2 RPL12 RPS8 RPS15 MT-ATP6 RPS25 TMSB10 RPS2 RPL8 RPL18A RPL3 CCL5 RPL15 RPS24 TRBV19 PFN1 RPLP0 MTRNR2L12 RPL21 RPS13 RPL6 RPL23A MT-ND1 PTMA HSP90AB1 FTL RPL9 VIM ATP5F1E UBB CD3E RPL36A RPS9 CFL1 RPL35 HSP90AA1 RPL24 ACTG1 PPP1R15A SH3BGRL3 IFITM1 MT-ND2 RPL5 RPL13A EIF1 EEF1B2 HLA-A FAU H3-3B UBA52 HLA-E ARHGDIB IL32 RPL27 RPL17 MYL12A RPL14 LSP1 PPIA EEF1D RPS5 RPSA CALM1 JUNB PTPRC DUSP1 HNRNPA1 PABPC1 SLC2A3 NACA SARAF RAC2 TNFAIP3 RACK1 TRAV9-2 MYADM CORO1A TMA7 FTH1 EEF2 CD2 RPL10A LTB S100A4 RPS16 CD52 KLF6 SRSF7 BTF3 FYB1 GZMA CD3D SERF2 TSC22D3 RPL38 IL7R DNAJA1 MT-ND5 CYTIP NPM1 H3-3A TOMM7 GAPDH TRBC1 COTL1 ARPC2 STK17B HSPH1 HNRNPA2B1 HCST ZFP36L2 RPL27A RPL22 RPL7 HINT1 DUSP2 CD74 EVL TENT5C SRGN PCBP2 RPS7 CLIC1 RPL36AL FYN RPS11 LAPTM5 DDX24 CD8A UBC ARPC1B STK17A CYCS HNRNPDL COX4I1 IFITM2 RPL4 MYL12B RPL31 TUBA1A UBL5 CD7 PPDPF.',\n", - " 'MALAT1 MT-ND3 MT-CO2 JUN MT-ATP8 MT-CO3 MT-CO1 HSPA1B MT-ND4L EEF1A1 MT-CYB RPLP1 RPL41 HSPA6 FOS B2M RPL34 RPS12 MT-ATP6 DUSP1 RPL10 MT-ND4 TMSB4X TPT1 MT-ND2 RPL13 RPS27 BTG1 RPL39 RPS28 HSPA1A HSP90AA1 RPS21 RPS15A CCL5 RPL30 HLA-B RPL28 RPS3 RPL32 RPL14 RPL19 MT-ND5 RPS14 RPS19 DNAJB1 ZFP36 RPS8 RPS27A HLA-A HSP90AB1 RPL26 FTL RPS15 HSPA8 KLF6 RPL18A RPS23 RPL23A RPL37 RPS29 RPS7 RPS18 RPL8 RPL7A TRBV2 MT-ND1 RPL17 RPLP2 RPL12 RPS24 FOSB RPS25 CD8A RPSA HLA-E IL7R RPL18 RPS2 RPL35A JUNB RPL29 MTRNR2L12 NR4A1 RPL9 RPL3 RPL5 ZFP36L2 RPS4X RPL11 ACTB HSPH1 RPL21 KLRB1 UBC RPL37A DDIT4 RPS9 EIF1 RPS6 CD69 RPS13 RPL36 RPLP0 RPS3A RPL15 PTGES3 NACA RPS5 RPL36A RACK1 RPL27 RPL22 PPP1R15A HLA-C RPL4 RPL6 RPL24 ZFP36L1 RGS2 H3-3B PFDN5 HNRNPA2B1 CD3E CD7 HNRNPK ATP5F1E PTMA SARAF NR4A2 RPL31 CD3G BTG2 LRRFIP1 PTPRC RPS16 PPDPF CD52 PFN1 SERF2 EIF4A2 TRAV12-1 NPM1 SON NCL YWHAZ EIF4A1 UBB LCP1 PTPRCAP DNAJA1 ZNF331 PPIB NUCKS1 RPL10A TRGV10 RPL13A UBA52 TOMM7 FTH1 SRSF7 UQCR10 EEF1B2 TRAV12-2 EMP3 GAPDH VIM CDKN1B FAU BTF3 EEF1G RPL27A GIMAP4 NOP53 RPL35 TMSB10 TUBA1A EEF2 RPL38 CALM1 ARPC5 EPC1 YWHAB PABPC1 PRMT9 RPL7 UBE2D3 CFL1 EIF4H ST13 NDUFA4 HNRNPDL G3BP2 CD44 MYADM RBM25 RPS20 YWHAQ NME2 ARL6IP5.',\n", - " 'IGLV2-23 MALAT1 IGKV3-20 JCHAIN MT-ND3 MT-CO2 RPS27 MT-ND4L MT-CO1 EEF1A1 MT-ATP8 MT-CYB B2M TMSB4X RPL41 IGHV3-15 RPS12 MT-CO3 RPS19 RPL39 MT-ND1 TPT1 RPL37 HSPA1A RPS15A MT-ND4 HSPA1B HSP90AA1 RPL34 IGHM RPS21 RPS27A RPS14 RPS28 FOS MTRNR2L12 CCL5 RPS15 MT-ND2 MT-ND5 MT-ATP6 RPL3 RPL11 RPL13 RPS3 HSPA6 RPL32 RPS29 RPL7A RPL23A RPS18 RPS8 RPS24 RPL19 HLA-B RPL26 ACTB RPS25 RPL17 RPL28 RPS6 RPLP1 RPS3A RPL15 CD69 UBB RPL18A RPL30 IGHV3-23 RPLP2 RPS16 UBA52 RPL29 TRBV9 RPS5 RPL36A PTPRC ATP5F1E FAU RPL35 RPS4X RPS23 RPS13 PTMA RPL13A RPL37A VIM IGHA1 S100A4 RPS9 RPS2 KLRB1 HLA-A TSC22D3 RPSA RPL22 DUSP1 RPL36 BTG1 HSPH1 TXNIP HSP90AB1 RPL35A FTH1 RPL10 RPL6 RPS7 RPL21 GADD45B UBC SRSF5 DNAJA1 RPL10A CXCR4 RACK1 RPL27A DNAJB1 EIF1 EEF2 RPL38 CD8A HLA-C JUNB ZFP36 PFDN5 CYBA RPL31 HLA-E RPS11 RPL4 JUN RPL24 YWHAZ IFITM1 EEF1D DDX5 ZFP36L1 BTG2 YWHAB NACA CD8B UQCRB HINT1 EIF3E CD74 TRBC1 MYL12A TTC39C CD3E FTL RPL9 RPS20 TMSB10 PFN1 PABPC1 ATP5MG ACTG1 COX6C GZMK ARHGEF1 RPL8 GIMAP7 RPLP0 SH3BGRL3 RPL18 EIF4A2 MYL6 TMA7 RSRP1 CD52 PPP1R15A RPL12 H3-3B NOP53 RPL14 EIF5A CFL1 EIF4G2 CD3D DUSP2 LINC02446 HSPB1 RAC2 TUBB HSPA8 FOSB CALM1 SARAF SRGN TRMT112 COX6A1 KLRD1 RPL36AL HNRNPA3 BTF3 CD99 CTSW HMGN1 EIF3L.',\n", - " 'CCL4 MT-CO1 MALAT1 MT-CO2 TMSB4X MT-CO3 MT-CYB FOS HSPA1B MT-ND4L MT-ND3 ACTB MT-ATP8 B2M MT-ND4 MTRNR2L12 MT-ATP6 RPLP1 TPT1 MT-ND1 DNAJB1 HSP90AA1 TNFAIP3 EEF1A1 MT-ND2 RPS27 PTMA CCL5 RPL41 HSPA1A HSP90AB1 HSPH1 RPL37 KLF6 DUSP1 MT-ND5 RPS3 RPS19 RPS12 BTG1 RPS6 TRBV4-1 JUN RPS21 ZFP36L1 FTL RPS27A UBB RPS29 RPL39 RPS14 RPL36 RPL19 RPS28 RPL28 RPL21 HLA-B RPS18 RPL13 SRGN PFN1 RPL35 UBC H3-3B RPL34 EIF1 RPL29 RPS15A RPL30 CD3E RPL10 RPL11 JUNB GAPDH HLA-C RPS23 RPS25 ACTG1 RPL26 FAU RPS7 NR4A1 ZNF331 DUSP2 FOSB RPL9 RPL18A RPL10A RPL3 RPS2 UBA52 TMSB10 RPS8 RPL22 RPS4X RPL17 ATP5F1E HLA-A SERF2 HLA-E IER2 NACA RPLP2 RPS24 RPL23A RPL14 RPS3A CORO1A RPLP0 ZFP36 BTF3 PPIA RPL36A SLC2A3 SARAF ZFAND2A CALR CD69 LY6E SRSF7 ARPC3 HNRNPA2B1 RPL6 CFL1 UQCR11 YWHAZ RPL8 SH3BGRL3 RPS13 EEF2 LTB MYL12A GADD45B RPL37A RPL12 RPS15 CD8A CD3D RPL18 RPL38 RPL32 CLK1 MYL6 RPS16 CD52 DNAJA1 NFKBIZ NME2 PNRC1 CALM1 RPS9 VIM RPL5 PPDPF IL2RG RPS20 SERTAD1 RBM39 EEF1B2 ITM2B DNAJA4 IFITM1 CALM2 RPS11 RPL15 CKS2 PCBP1 CYBA HSP90B1 H3-3A MYL12B RPL27 DUSP5 TUBA1B CD96 CD7 AREG HMGB1 HSPA8 SLC25A5 IL32 LINC01871 TUBB4B ATP5MG CYTIP PCBP2 RPS5 NCL RPSA DDX21 SLC3A2 DDX5 PFDN5 CDKN1A IL7R RPS26 EEF1D CALM3 SRSF3 COTL1.',\n", - " 'MALAT1 HSPA1A MT-CO1 TMSB4X EEF1A1 MT-CO2 HSPA6 MT-ND4L JUN RPLP1 DNAJB1 MT-CYB RPL41 MT-ND3 RPS27 B2M DUSP1 MT-CO3 RPS15A JUNB RPS12 RPL10 RPL39 RPL32 HSPA1B TPT1 RPL28 MT-ND4 RPL13 RPL30 RPL34 CCL5 RPS18 RPL19 RPS27A RPS3 RPS24 RPS14 RPL26 RPS23 HSPA8 ACTB MT-ATP8 PTMA RPL18A FOS RPL21 RPS29 RPS21 MT-ND1 RPS28 UBB FOSB HSP90AB1 FAU RPL11 RPS8 MT-ATP6 RPS19 RPL9 RPS3A HLA-A RPL29 MT-ND5 RPL37 HSP90AA1 RPS6 FTL RPL23A RPLP2 EIF1 RPL7A IL32 PPP1R15A CD52 RPL37A RPL12 BTG2 MTRNR2L12 RPL3 RPS16 RPS25 RPS4X RPL24 RPL35A S100A4 MT-ND2 PFN1 RPL5 KLRB1 RPL36 RPSA RPS9 RPL36A RPL18 RPL14 RPL15 EEF1B2 RPL35 RPS5 SERF2 DNAJA1 HLA-B RPS13 HSPB1 RPL8 FTH1 RPS7 RPL17 SH3BGRL3 HSPD1 HLA-C RPL13A MYL12A TMSB10 IER2 HNRNPA2B1 CCL4L2 UBA52 H3-3B RPLP0 RACK1 EEF1G S100A6 LTB ZFP36L2 TRBV4-1 RPS2 SRSF7 KLF6 CFL1 HNRNPK SRSF3 ZFAND2A CALM1 TRAV23DV6 H3-3A RPL22 PCBP1 GADD45B RPL27 PNRC1 GYPC CD3E CD7 RPL36AL HSPH1 GAPDH CD3D EEF1D YWHAZ RPS15 RPL38 SRGN CD37 OAZ1 TRMT112 PTPRC ATP5F1E HSPE1 RPL7 RPL6 CORO1A ARPC3 ACTG1 CD2 YWHAB IL2RG KLF2 NPM1 RGS10 HNRNPA1 COTL1 PPIB RPL10A GADD45G RPL27A RPS11 CALM2 CD44 IL7R EIF4A1 RPS4Y1 RPL31 BTG1 RAC2 TRGV10 MIF TMEM123 CYBA MYADM EGR1 ATP5MG NACA ITM2B RPS17 PABPC1 RPL4 UBC EIF4A2.']" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "generated_cells[:5]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Post processing and reconstruction\n", - "\n", - "Now that we have generated cell sentences conditioned on cell type, we need to perform some postprocessing steps, namely:\n", - "1. Removing words that are not gene names in the dataset\n", - "2. Deal with genes which were generated more than once in a cell sentence (duplicate genes)\n", - "\n", - "We will use C2S functions to do this post processing, as well as convert our generated cell sentences back into expression vectors for visualization." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First, we get a vocabulary list of gene names from our AnnData object. This will helps us determine what is a real gene word for our data, and what was some nonsense word or unknown gene mistakenly generated by the model." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "23944\n" - ] - }, - { - "data": { - "text/plain": [ - "['RP11-34P13', 'RP11-34P13-3', 'AP006222', 'LINC01409']" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "vocab_list = list(vocabulary.keys())\n", - "print(len(vocab_list))\n", - "vocab_list[:4]" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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gene_nameensembl_idn_cellsmtn_cells_by_countsmean_countspct_dropout_by_countstotal_counts
RP11-34P13RP11-34P13ENSG0000023800938False380.00131099.87236839.0
RP11-34P13-3RP11-34P13ENSG00000241860106False1060.00362799.643973108.0
AP006222AP006222ENSG000002864487False70.00023599.9764897.0
LINC01409LINC01409ENSG000002374911292False12920.04598195.6604981369.0
FAM87BFAM87BENSG000001777573False30.00010199.9899243.0
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" - ], - "text/plain": [ - " gene_name ensembl_id n_cells mt n_cells_by_counts \\\n", - "RP11-34P13 RP11-34P13 ENSG00000238009 38 False 38 \n", - "RP11-34P13-3 RP11-34P13 ENSG00000241860 106 False 106 \n", - "AP006222 AP006222 ENSG00000286448 7 False 7 \n", - "LINC01409 LINC01409 ENSG00000237491 1292 False 1292 \n", - "FAM87B FAM87B ENSG00000177757 3 False 3 \n", - "\n", - " mean_counts pct_dropout_by_counts total_counts \n", - "RP11-34P13 0.001310 99.872368 39.0 \n", - "RP11-34P13-3 0.003627 99.643973 108.0 \n", - "AP006222 0.000235 99.976489 7.0 \n", - "LINC01409 0.045981 95.660498 1369.0 \n", - "FAM87B 0.000101 99.989924 3.0 " - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata_test.var.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We post-process all generated cell sentences, which will remove non-gene words in the sentence and average the position of genes which appear multiple times in the generated cell sentence." - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 2978/2978 [01:31<00:00, 32.64it/s]\n" - ] - } - ], - "source": [ - "post_processed_sentences_list = []\n", - "num_genes_replaced_list = []\n", - "for idx in tqdm(range(len(generated_cells))):\n", - " post_processed_sentence, num_genes_replaced = post_process_generated_cell_sentences(\n", - " cell_sentence=generated_cells[idx],\n", - " vocab_list=vocab_list,\n", - " replace_nonsense_string=\"NOT_A_GENE\",\n", - " )\n", - " # post_processed_sentence is a list of genes, with non-genes replaced with replace_nonsense_string\n", - " post_processed_sentence = \" \".join(post_processed_sentence) # rejoin into one cell sentence string\n", - " post_processed_sentence = post_processed_sentence.replace(\" NOT_A_GENE\", \"\") # replace nonsense string\n", - " post_processed_sentences_list.append(post_processed_sentence)\n", - " num_genes_replaced_list.append(num_genes_replaced)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "avg_num_genes_replaced: 1.13969\n" - ] - } - ], - "source": [ - "avg_num_genes_replaced = sum(num_genes_replaced_list) / len(num_genes_replaced_list)\n", - "print(f\"avg_num_genes_replaced: {avg_num_genes_replaced:.5f}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that our model was very accurate, only generating 1.14 invalid genes per cell sentence on average. We can see an example of a cell sentence before and after post processing:" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Predicted sentence 1:\n", - "MALAT1 TMSB4X B2M MT-CO1 RPLP1 ACTB MT-CO2 RPS27 HSPA1A MT-ND3 RPL41 HSPA1B MT-CYB RPS12 MT-ATP8 RPL28 RPS19 EEF1A1 RPL13 MT-CO3 DNAJB1 RPL30 RPL10 RPS15A MT-ND4L TPT1 RPL39 JUN RPL37 RPL32 RPS28 HLA-B RPS3 RPS3A RPL19 RPS27A BTG1 HLA-C RPL36 RPL34 MT-ND4 RPL26 RPS4X RPS23 RPL11 RPS18 RPL35A RPS6 RPL18 RPS21 RPS29 FOS HSPA8 RPS14 RPL37A RPL7A RPL29 RPLP2 RPL12 RPS8 RPS15 MT-ATP6 RPS25 TMSB10 RPS2 RPL8 RPL18A RPL3 CCL5 RPL15 RPS24 TRBV19 PFN1 RPLP0 MTRNR2L12 RPL21 RPS13 RPL6 RPL23A MT-ND1 PTMA HSP90AB1 FTL RPL9 VIM ATP5F1E UBB CD3E RPL36A RPS9 CFL1 RPL35 HSP90AA1 RPL24 ACTG1 PPP1R15A SH3BGRL3 IFITM1 MT-ND2 RPL5 RPL13A EIF1 EEF1B2 HLA-A FAU H3-3B UBA52 HLA-E ARHGDIB IL32 RPL27 RPL17 MYL12A RPL14 LSP1 PPIA EEF1D RPS5 RPSA CALM1 JUNB PTPRC DUSP1 HNRNPA1 PABPC1 SLC2A3 NACA SARAF RAC2 TNFAIP3 RACK1 TRAV9-2 MYADM CORO1A TMA7 FTH1 EEF2 CD2 RPL10A LTB S100A4 RPS16 CD52 KLF6 SRSF7 BTF3 FYB1 GZMA CD3D SERF2 TSC22D3 RPL38 IL7R DNAJA1 MT-ND5 CYTIP NPM1 H3-3A TOMM7 GAPDH TRBC1 COTL1 ARPC2 STK17B HSPH1 HNRNPA2B1 HCST ZFP36L2 RPL27A RPL22 RPL7 HINT1 DUSP2 CD74 EVL TENT5C SRGN PCBP2 RPS7 CLIC1 RPL36AL FYN RPS11 LAPTM5 DDX24 CD8A UBC ARPC1B STK17A CYCS HNRNPDL COX4I1 IFITM2 RPL4 MYL12B RPL31 TUBA1A UBL5 CD7 PPDPF.\n", - "Post-processed sentence 1\n", - "MALAT1 TMSB4X B2M MT-CO1 RPLP1 ACTB MT-CO2 RPS27 HSPA1A MT-ND3 RPL41 HSPA1B MT-CYB RPS12 MT-ATP8 RPL28 RPS19 EEF1A1 RPL13 MT-CO3 DNAJB1 RPL30 RPL10 RPS15A MT-ND4L TPT1 RPL39 JUN RPL37 RPL32 RPS28 HLA-B RPS3 RPS3A RPL19 RPS27A BTG1 HLA-C RPL36 RPL34 MT-ND4 RPL26 RPS4X RPS23 RPL11 RPS18 RPL35A RPS6 RPL18 RPS21 RPS29 FOS HSPA8 RPS14 RPL37A RPL7A RPL29 RPLP2 RPL12 RPS8 RPS15 MT-ATP6 RPS25 TMSB10 RPS2 RPL8 RPL18A RPL3 CCL5 RPL15 RPS24 TRBV19 PFN1 RPLP0 MTRNR2L12 RPL21 RPS13 RPL6 RPL23A MT-ND1 PTMA HSP90AB1 FTL RPL9 VIM ATP5F1E UBB CD3E RPL36A RPS9 CFL1 RPL35 HSP90AA1 RPL24 ACTG1 PPP1R15A SH3BGRL3 IFITM1 MT-ND2 RPL5 RPL13A EIF1 EEF1B2 HLA-A FAU H3-3B UBA52 HLA-E ARHGDIB IL32 RPL27 RPL17 MYL12A RPL14 LSP1 PPIA EEF1D RPS5 RPSA CALM1 JUNB PTPRC DUSP1 HNRNPA1 PABPC1 SLC2A3 NACA SARAF RAC2 TNFAIP3 RACK1 TRAV9-2 MYADM CORO1A TMA7 FTH1 EEF2 CD2 RPL10A LTB S100A4 RPS16 CD52 KLF6 SRSF7 BTF3 FYB1 GZMA CD3D SERF2 TSC22D3 RPL38 IL7R DNAJA1 MT-ND5 CYTIP NPM1 H3-3A TOMM7 GAPDH TRBC1 COTL1 ARPC2 STK17B HSPH1 HNRNPA2B1 HCST ZFP36L2 RPL27A RPL22 RPL7 HINT1 DUSP2 CD74 EVL TENT5C SRGN PCBP2 RPS7 CLIC1 RPL36AL FYN RPS11 LAPTM5 DDX24 CD8A UBC ARPC1B STK17A CYCS HNRNPDL COX4I1 IFITM2 RPL4 MYL12B RPL31 TUBA1A UBL5 CD7\n" - ] - } - ], - "source": [ - "print(\"Predicted sentence 1:\")\n", - "print(generated_cells[0])\n", - "print(\"Post-processed sentence 1\")\n", - "print(post_processed_sentences_list[0])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now, we reconstruct expression vectors from the cell sentence. From tutorial notebook 1, we know the slope and intercept values for the linear reconstruction model for this dataset." - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "slope = -0.6756886579917628\n", - "intercept = 2.237853249084892" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will utilize the reconstruct_expression_from_cell_sentence() function from `utils.py` to reconstruct an expression vector from our generated cell sentence. The expression vector will have column features that match the order of vocab_list, so make sure that vocab_list reflects the exact gene ordering in the original data!" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 2978/2978 [00:06<00:00, 458.33it/s]\n" - ] - } - ], - "source": [ - "all_reconstructed_expression_vectors = []\n", - "for idx in tqdm(range(len(post_processed_sentences_list))):\n", - " expression_vector = reconstruct_expression_from_cell_sentence(\n", - " cell_sentence_str=post_processed_sentences_list[idx],\n", - " delimiter=\" \",\n", - " vocab_list=vocab_list,\n", - " slope=slope,\n", - " intercept=intercept,\n", - " )\n", - " all_reconstructed_expression_vectors.append(expression_vector)\n", - "\n", - "all_reconstructed_expression_vectors = np.stack(all_reconstructed_expression_vectors)" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(2978, 23944)" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_reconstructed_expression_vectors.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dtype('float32')" - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_reconstructed_expression_vectors.dtype" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "np.save(\"/home/sr2464/palmer_scratch/C2S_Files_Syed/c2s_api_testing/cell_generation_all_reconstructed_expression_vectors.npy\", all_reconstructed_expression_vectors)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Visualization of Generated cells\n", - "\n", - "Now that post processing and the conversion back to expression vectors using the linear model is complete, let's visualize the cells we have generated by putting them together into one AnnData object and visualizing original data and generated data side by side.\n", - "\n", - "First, we retrieve the original data from our adata object, subsetting to the same test set cells:" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", - " uns: 'batch_condition_colors', 'cell_type_colors', 'log1p', 'neighbors', 'pca', 'tissue_colors', 'umap'\n", - " obsm: 'X_pca', 'X_umap'\n", - " varm: 'PCs'\n", - " obsp: 'connectivities', 'distances'" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata_test = adata[data_split_indices_dict[\"test\"], :].copy()\n", - "adata_test" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], - "source": [ - "del adata_test.uns\n", - "del adata_test.obsm\n", - "del adata_test.varm\n", - "del adata_test.obsp" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata_test" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now, we restrict the original adata to the top 200 genes, to match cells which we have generated with 200 genes." - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "adata_test.X = adata_test.X.toarray().astype(np.float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [], - "source": [ - "top_k_gene_count = 200" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 2978/2978 [00:04<00:00, 605.98it/s]\n" - ] - } - ], - "source": [ - "for cell_idx in tqdm(range(adata_test.X.shape[0])):\n", - " ind = np.argpartition(adata_test.X[cell_idx], -top_k_gene_count)[-top_k_gene_count:]\n", - " ind.sort()\n", - " all_but_ind = np.setdiff1d(np.array(list(range(adata_test.X.shape[1])), dtype=np.int64), ind)\n", - " adata_test.X[cell_idx, all_but_ind] = 0" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(2978, 23944)\n" - ] - } - ], - "source": [ - "print(adata_test.X.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(200,)\n", - "(200,)\n", - "(200,)\n" - ] - } - ], - "source": [ - "print(np.nonzero(adata_test.X[0])[0].shape)\n", - "print(np.nonzero(adata_test.X[1])[0].shape)\n", - "print(np.nonzero(adata_test.X[2])[0].shape)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now, we create another AnnData object with our C2S-generated cells" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(2978, 1)\n" - ] - }, - { - "data": { - "text/html": [ - "
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cell_type
C2S_gen_cell_0CD8-positive, alpha-beta memory T cell
C2S_gen_cell_1CD8-positive, alpha-beta memory T cell
C2S_gen_cell_2CD8-positive, alpha-beta memory T cell
C2S_gen_cell_3CD8-positive, alpha-beta memory T cell
C2S_gen_cell_4CD8-positive, alpha-beta memory T cell
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" - ], - "text/plain": [ - " cell_type\n", - "C2S_gen_cell_0 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_1 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_2 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_3 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_4 CD8-positive, alpha-beta memory T cell" - ] - }, - "execution_count": 46, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "generated_obs_df = pd.DataFrame({\n", - " \"cell_type\": cell_types_to_generate\n", - "}, index=[f\"C2S_gen_cell_{idx}\" for idx in range(len(cell_types_to_generate))])\n", - "print(generated_obs_df.shape)\n", - "generated_obs_df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "generated_adata = anndata.AnnData(\n", - " X=all_reconstructed_expression_vectors,\n", - " obs=generated_obs_df,\n", - " var=adata_test.var.copy(),\n", - ")\n", - "generated_adata" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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cell_type
C2S_gen_cell_0CD8-positive, alpha-beta memory T cell
C2S_gen_cell_1CD8-positive, alpha-beta memory T cell
C2S_gen_cell_2CD8-positive, alpha-beta memory T cell
C2S_gen_cell_3CD8-positive, alpha-beta memory T cell
C2S_gen_cell_4CD8-positive, alpha-beta memory T cell
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" - ], - "text/plain": [ - " cell_type\n", - "C2S_gen_cell_0 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_1 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_2 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_3 CD8-positive, alpha-beta memory T cell\n", - "C2S_gen_cell_4 CD8-positive, alpha-beta memory T cell" - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "generated_adata.obs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(199,)\n", - "(199,)\n", - "(198,)\n" - ] - } - ], - "source": [ - "print(np.nonzero(generated_adata.X[0])[0].shape)\n", - "print(np.nonzero(generated_adata.X[1])[0].shape)\n", - "print(np.nonzero(generated_adata.X[2])[0].shape)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Our generated cells will have a few less genes than 200, since 1-2 genes were removed during post processing." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can quickly visualize separate UMAPs of the generated data, to see what clusters there are in the generated cells:" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [], - "source": [ - "del generated_adata.uns\n", - "del generated_adata.obsm\n", - "del generated_adata.varm\n", - "del generated_adata.obsp" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "generated_adata" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [], - "source": [ - "sc.tl.pca(generated_adata)" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [], - "source": [ - "sc.pp.neighbors(generated_adata) # , metric=\"cosine\"" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [], - "source": [ - "sc.tl.umap(generated_adata)" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", - " uns: 'pca', 'neighbors', 'umap'\n", - " obsm: 'X_pca', 'X_umap'\n", - " varm: 'PCs'\n", - " obsp: 'distances', 'connectivities'" - ] - }, - "execution_count": 55, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "generated_adata" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sc.pl.umap(\n", - " generated_adata,\n", - " color=\"cell_type\",\n", - " size=8,\n", - " title=\"C2S Generated Data\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Our generated data looks to have good cell type clustering and structure! Let's quickly make a separate UMAP of the original data to compare:" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" - ] - }, - "execution_count": 57, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata_test" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [], - "source": [ - "sc.tl.pca(adata_test)" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "metadata": {}, - "outputs": [], - "source": [ - "sc.pp.neighbors(adata_test)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [], - "source": [ - "sc.tl.umap(adata_test)" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", - " uns: 'pca', 'neighbors', 'umap'\n", - " obsm: 'X_pca', 'X_umap'\n", - " varm: 'PCs'\n", - " obsp: 'distances', 'connectivities'" - ] - }, - "execution_count": 61, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata_test" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sc.pl.umap(\n", - " adata_test,\n", - " color=\"cell_type\",\n", - " size=8,\n", - " title=\"Original Data\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The original data has a similar structure. As a last check before we make a joint UMAP, we can look at a heatmap of gene expression between generated and original data:" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "metadata": {}, - "outputs": [], - "source": [ - "markers = ['MALAT1', 'MT-CO2', 'MT-CO1', 'MT-ND3', 'MT-ND4L', 'MT-CO3', 'MT-CYB', 'MT-ATP8', 'MT-ND4', 'MT-ATP6', 'MT-ND5', 'MT-ND2', 'MT-ND1', 'MTRNR2L12', 'HSP90AA1', 'HSPA1A', 'HSPA1B', 'DNAJB1', 'FOSB', 'HSP90AB1', 'HSPA8', 'JUNB', 'FOS', 'DUSP1', 'BTG1', 'JUN', 'FTL', 'B2M', 'RPL41', 'RPLP1', 'RPS27', 'RPL10', 'RPL13', 'RPS12', 'RPL28', 'RPS19', 'RPL39', 'RPS15A', 'RPS3A', 'RPS27A', 'RPL32', 'RPS28', 'RPL34', 'RPS14', 'RPL30', 'RPS18', 'RPL37', 'RPL11', 'RPS21', 'RPS23', 'RPL19', 'RPS3', 'RPL18A', 'RPS15', 'RPL26', 'RPL3', 'RPS6', 'RPS8', 'RPL35A', 'RPLP2', 'RPL12', 'RPS2', 'RPL21', 'RPL36', 'RPL14', 'RPS13', 'RPL18', 'RPL7A', 'RPS25', 'RPL8', 'RPS4X', 'RPL29', 'RPL23A', 'RPL9', 'RPS24', 'RPLP0', 'RPS29', 'RPL17', 'RPL37A', 'RPL15', 'RPS7', 'RPL6', 'RPL10A', 'RPS16', 'RPL5', 'EEF1A1', 'RPL13A', 'RPL22', 'RPS5', 'TPT1', 'RPL35', 'RPL36A', 'RPS9', 'RPL24', 'PTMA', 'RPL38', 'FAU', 'HLA-B', 'RPSA', 'EEF1B2', 'HLA-A', 'UBA52', 'TMSB4X', 'RPL4', 'EEF1G', 'EIF1', 'ACTB', 'NACA', 'HLA-C', 'RACK1', 'PABPC1', 'RPL27', 'PPP1R15A', 'TMSB10', 'HSPH1', 'PNRC1', 'RPL31', 'H3-3B', 'RPS11', 'EEF2', 'BTG2', 'PFDN5', 'RPL7', 'HNRNPA2B1', 'SARAF', 'BTF3', 'NPM1', 'FTH1', 'HNRNPA1', 'RPS20', 'CD3E', 'RPL36AL', 'MT-ND6', 'HSPE1', 'NCL', 'SRSF7', 'CD8A', 'HNRNPDL', 'ZFP36L2', 'TUBA1A', 'SLC2A3', 'CD3D', 'EIF4A2', 'HNRNPU', 'SRSF5', 'RPL27A', 'RPS17', 'RPL23', 'EIF4A1', 'CD7', 'PTPRC', 'HSPD1', 'DDX5', 'H3-3A', 'EIF4B', 'SERF2', 'SLC25A5', 'EIF3E', 'RPS4Y1', 'CD52', 'TOMM7', 'PCBP2', 'IL7R', 'SLC25A6', 'RBM39', 'EIF3F', 'RPS26', 'MYL12A', 'EIF3K', 'CD69', 'RPL22L1', 'TUBA1B', 'EIF3G', 'ATP5F1E', 'EIF3H', 'CFL1', 'EIF4A3', 'UBC', 'RAC2', 'CD8B', 'CD3G', 'RGS2', 'SRSF3', 'EIF5A', 'SFPQ', 'TUBA4A', 'EIF3D', 'EIF4G2', 'EIF3L', 'HNRNPC', 'TSC22D3', 'EIF1AX', 'HINT1', 'RPS10', 'SLC25A3', 'RPS27L']" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING: Gene labels are not shown when more than 50 genes are visualized. To show gene labels set `show_gene_labels=True`\n" - ] - }, - { - "data": { - "image/png": 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8XZ1c6MwgQ6UOqqSxmYKeJ/Pu5tAunJ3ClhGbK5Nr9gJs5BU61/Z1uu7JXGMVyhFnR8dG7J6SxqYeOtXyDMHemjElnzwIsCXI/eIei7VUqoqNoYzMfx7I+WV8F+NZ0X1+gMksJlD9/bx7nmgKO8vdM5e1d6OdaoKALMhFH+46O0qcHW01yuw5O8YqCCwmV+jCBlBOjrXi7OhAnB2VQV7cGxbyQJwdoxR5KUVHe86O9jM58zzQuayHQbnJjfIFA/rW2xWsm8tkllIA3IZ44UlFsg6U5fV4KMfsmP7fumVwgpSVrRrWs7KgY0UWG5JhOYDs7vxYxHM1lp1WiG9S4rUSeZCjg4xo0qJrCWklx1uTRThe6jAzs0U6maCsKCBv09C5tUd3ykKQyw/oIhqSK9ymHNi5YzFBRhZaogtVWrfHkCtMpPC2NeSIxQfkXo51LFW/h1YW3FzeiLRERI2VqFTXoGIxBLJcE3oJXjMnzWVMbOTQ2WdxmloiHB2JUDlthelorIbMh7QqSl8nCn/DYDoKd8vgdBW5ZzE9xU43wGpIhzOskY2CgjzIGXkYTJHV0bE8RFrLyHxL5iORgc7eUtiMK1yKx/F1ysHSNjvdgJLuUfVjDDkZmlbso4DQSMR1u1vC81K6O7IBp50dSrpH1PJpPf8EAN3EwdWyNtSWx+oT42RoiDV5kNPdDsk7Dlmu8ZqWvCVOwtZ2meXVYWxWREgKw6/q9wBIMkP1Sk7ZxP1nKJd7uCYTQ11ZkpqllzmU/Jh27JGnGp0qvFJCPJ7R7XkETkIvcrnYHsOmGqVzksyQZRqlRIFUKpH8gLFYAzbM8CY6ougKUalEX5yWJkkMWufEbQ+nrbDaonJwOpCNJpgwxavLGsmXQrJI1nIaWpKDPdKGRzyeYkty+JqOrDGvriBVklUaSck3fLJqRu6JoRqth3IzsabTCEBZehsh3cRFpZBuhDhthbPugWOZrLXIShaVKtY2ahLVbylq1Q5YxfhIE6oJwVgXfyjCcTOSoQynK3NhFbK/gPAfP4PecVEtWee31tbI2y4m0gReQtp1+g5TFmvyUo5X7d2gZ5wudCQ5htdU/WdJM42jc2ojHUIdE4YxeSlnstqi6u5dw21qTA8uNkZJtwKykZQkdiDVnG+N00sd6GmeaEywfXEE0zI4dUO+HtA+kEOsUU6OCjJ2XngSf0vBut/XAQBOW9Hdl5J0XfJKhm46mEgxOdKUe2hoNtslTFvjbynWGhXi1EFHCltKJQhRXK/i9VCZZPtQQCKOb3elAmKzoVMwkcJWJSuTl3LQEE3kqByMn0HTFZ3r761HgDxXNDbLRJlDrRwxVW0RtXx0DE7dkMaGRidARwp3S/eNt6ge4IcJpmnQmaw3s+1KZNxYidKnCtUzaKcwojuGrGv6p8vaVg2badKGB6lCtSWzZ4Zioo6HjQx6rIfuamzXYNpa1pWxst5zIBJnxWrI1wPyUoapJvg7oKzC2XRBi97LqlkRUZXzhVz17zPal+J0NG5dbs56FpsD1RSz7FPa30KlitbhnLRc7PFUDKRGR3Rbmun+vHk6I84NKoOSH5PniqztUgl6oKCZ+piGwWiZj9HhFpPVFmUvoeZFVNweXq1H2Yvp9WTvZ7mi5kYYZemkHmmuaUQ+aTkn6Tn0coONNZ7O8EwGQDdxYbyHG6SUhrrEsQOOnEFuQ5N7ltyzEGn0hot2c7LhFOuA6UF7s4R1LNbPWb86ApliZ6dEd6NEWsuKRQQo6EYuzo6hvRVSrkaoFHauDJEM52RlQQ2oHHFsUkVezrB+DjmoUip/a7Adh9zLyWKDGil0tyPjlDuSsVQW3CYMPebgbStULuegt+jhPF7srXWDThWjjxSLfd0nGcrFWAwsVtO3WUwP/C1N7svcug0j5y+SlSlfccQRcyVQqqysn2BDzmUdA12DicDdclAWVC6Z0HBF46+ZPuLCaisIjK6SzzcU/raiO5MRrYeYjjhZ1rGEi4adxSGMl5GVLMGqoXpRk7ZdnA7YXDH8uIw/CryGBKFy16JTsVMATHG+uw1FUs3JfOgNg+2JcRWuKlSi8esKr65xWgp3R9PbH2PDDLelMF2F25Q1v7o6jNVypllH/gPIQouKNfSMOHupRm158t1Vjzw2BOsap6PwtjTRuCBOTFuzujxM3nQxHY3uKZKuS5rLHHh1hYo13qYEU8JlBx2L02N3PJyGxmkqVK72rNdU0eu55A54ftrXeTpTmI6ik/uYtugrf9sW86XJPHDbFqVkDnNH5mKpPSRrzu3eoEPxbtSpACjLULVLsCm2liknmN1sd67QkdhxikI3+fJbIFlCpwvOugsttwg0pDJHGSRHI2yu8OqQ1KwgQQJL7lji7UDGKFWopoPWBSJo4N/8L+ULdnZKboy75VC65ELdhRXx3sM1LU6BheCKeL1uS6NyRe5AHoryMU+U0MribhnyXFLJZsWjdtahetbgb+/dkooVZtslTQznVyYE/tPS5E2XYE2hlgP8TUNStWzulFlpVlmvVyif9URBLcnOrD3oU3sCvGsuyuTEVUkls+OS+eAtemSVHOd8gNvUOG1N+QkPVXcxsWwC5eUFLgJMT+6xk7g0tkuolvyOShSlRUOeaKoXDKZlJIX7hMfVS+Ns7FQI/+oM2eNFetFYaucgLVmcHUNasnIfHUU6khJNZeL4tOXAzwJLb0QMm7RcpM3DXJyYwhgHSCq5OGk7UFp06E7J9fxNiQDj5fgbhqyWoRMIL3rkriWvyqG2HNVIrMO55jgX22MEXsLp5s0sro9w7+YhTq8fIck1aeTQSWWu6+sV4keGqDzqUb7o8DdbT+Xx3j5U3aXy4dOM3WPo3D3O5e44AF5dEy4b/nbzqZQvy/h5aw7uhkN7rUzjKBItfqwiSm7ZR9VdvIZm+Kzs6KX6EO2eR5Q6dKY0y90aUeFstRsBl1bHWHtwis6lGsGGYrE1zPL5CeqNEqWHAyqXFMF8hfCaQ7RU5oGl/eSR4fGNSdCWfLHETiukt1Tm2taQzPnFITauDFM65xFsKNxVF/dMleHH99ZtNGnJfVFMSlmylRLazSQN7QqcIg2hdN7DnA9Jqpbgikc+EUOksaUMHSuq9wW4dUO46DL5KTmEvYYc+JkH4/cY3JYSKJsW6IQ1Fp3QN8r9NQd6hqQeoDLFysOT/bUabMq6CK+6bLTKZL7FbSqCUozpKXSi2N6skm97bN89iW07ZOcq9Bo+yXqIjjXlq0XGt6tw1mUeu1/9FPwNjUnkvfnlo+iOJq1kdB4awdQd3C0H1ny0k+Nua+yF8g16RvcUunBqsyIAjWNJMsPV5jCds8Pcu3mI1loZFSsuro5xsT7a/77bBLelaPc8nKbGv+aSbfiYpuFaa4he6uC0DI3YJ1gzOF3RCSovfrurCc4G0HIY+qNTxEMSKAiX904TlYG3aXDWPMIrLjpWpIHtj3FuoLUT4jY0B944jzE5neUKwYai/JiPTpBgC3BhfQx/VYwkOeg14bpCdzSlFXGWVAojj+U46y7xagl/1RCsiRFfewKyrkOwLEZNcNXlBmm4qI6h5CTUGyXOPzxDeahLd0oi0XnbJc9Fh9tjHfxNg8oUum2ItgKycoZXl3WVVcXRDVYM1s8x4z2stmRNF9024ijFGhK5f6Ustqdxh6M+PI0gw64E2I6DCjLyLb8/36anyDyLu+6QB7ImVaYwdXEm9USE7hjcJ8Sh15HAdIMlB39L9kNp0RSGssJsO9hKJjrnmiNQ3mJ4/A2DtQr3qkcW5nQWK5JhGu2J4bajsKk4TZWwh7fqkGVixAG0Uo+Vdg2dStAlSw1kinorRHU1m1EZq2FlY4iL9THWV4e4ujnMylaN+xcPcLkxgs0VqztV0o2QZten1Q640BxjcXWENNfyWr1E6Zohb7lcbY2gIs3VxhDrzQoAZS/GPxuSbgV0lytoZVFtpx/YM5EiL2V4W4Z8MsZaqJz1xIh0AGVxGgbV06At7rrLoekt8DNxcjJxWsgVSdOXc7uU0rpSEyO2oyldNZhW4ZwqcLZEZ+mmrElnx8G55su5Hsm55m0b3EVPIE2I7eC0FMlwTlK1OG1FZyanvd+ShZbaecjCnGBTHI/ct6Qli0qheVD0cV7O5KwryzlnHcvwgy4qg3hYnJzcsVQvIQ7kZIINJYDZnRQ7RaUKb8v092Tmix2AFudaZ3Ie7566Oobyck60LyWtZcTDkvF3WhodQxZAb9SSGwiXDIQZSU32ntMuHG8nlyBApMhCS+uQZEDRoIxl/bjcWzAcSVDLIs5lR5FW8j701FtzSCoCUUNbgfNlYkB3psXYjybyAhIPyXCO2XZRbYHNp6EECgDcMMFqMbbzciYOM+Iw6oQbHIC8nOE1ZM8Qa3JXnKK0bElrOb2RnCzMKZ335PzZULL2eoZLm6MCyQskoJeGFrcleiALLCpMBb7oWXoT8qy6gHOTKfJtH6+uiLYCSqt7ai93LWe705SWFaUlmctgQ1G6avAa4HZz1GJAsJ3jtgALS5tDJFW4/+LhG1Sou76X2fGXC7hupNlulIjGQEeafMsn6xlw8n5gedepBAlY9cZzkppF90DlSgI7hY7J6h5ZKPadWgmwLYd4GPxNRWlJk/viwAIktRy3rvF2FJ6f4m+L8zT0xMDj+XwyoGoYyEAGMpCBDGQgAxnIQAbyRSlfsLPT7PkktUyimnWN09J4O6ATqF6xeA0lHj/gtsHblmKsYMXBbWnSikQCvIYi6xnJMJQlxR0PQxoUeMNMYSKNziDvOiglBfduQ2PamvJKLjC1hkQC09iheXmIpONJxLSt6E0IVMttWLpTimQkR6/5eDsSubFBJhHdWOHsGClgFARKP5WdGwg2JSW5G4FRObjbhk7PQxlLsC6v+3UpfjPLPklZoDTBskAcRmd2+mOY1GQMzLZDUM8ldRwpSfmuG8I1i7PpUDtncCLQGYw8Ip8ZfUigHOVFjduA4YccnLZAVKpXLN6GwdvWhGsW07P0RnOcDvjLLn5d7t3Zkii0ty6RUKuhckWj2hKtaMQBW2mZy5ujxJnDyuIooUnIM0UncekkLs1ugAlSVtpSPOtWe1gNrVsTeqOWmtPj9PZRvC0Zm/YBRXxrl4fr02y+dJZDb5inN2pxdUY0mVO9YEgqlmQ0Y/8nFaWV3eiQZfQBzdBZgVWZCJyOjF8UubRbAeubVUnXZw4U0ZTgiofSOVZB7ufM/No8O90C43qxRGnVUlnO8HcswbpgptPEoLqGoTBi39+5hKuauOUx8ojC9bK9TeBKlNGrS9RZp9dlH5BUfO2sIVzRxF0X01F4T4S4O4rwsidRwGuWA786Dxq8HUXuWNSmh8oU3qrMi4ksmW/x6jD8hwv4W7I+nQ6UVi3RqGTvps7kWD/Ha8ie9HYUTreAZjhWMpwF1CIbSSmtSZYiqYC7Ie+1NsqMfkbGLo4ddE8JFNSC09AkRXGk6cm8WGMZelyytiCFsaYn3w//8TOyzopoVq/n4jY1OpL94W1r0pIFDXnHwXQVXvNGPVNas1QWb4QN6IZAZ0puQjqakOYa0zKYSJOnmjjZi7yNPZKw/03ztJsB4YqickWiaBP3W0puQqvrU70AgZMSD+ccft0CI4/lWM+ybyGjckUz/pmUW151GoDDr1vAbSpGzib93xh/MGffQsrow+DtwE0/vcD+f03RxTjc9JoFbGSYvE+gFVHXwwYZM78+j78t83/k5xZkjJo+Q+dzyosKb0cxfrdm5tfmqZ0Ht2HxtyxHfn6B6p+dYuwhqUMI1+X1cFUx9v4F9I7DwV+eZ99CjvNZCAwA09ZcbIyiL4SYjqZ7vtZ/T/U0ca/IBCyH6J5Eq/NKirvtUHvCIS2Bt2HQHcmQmAScbQfvoRLBqiNrty7RejR4G46QqkQO5IpsqSSZw0UXIiM6J1Woukv1CUP5quqTd5hY/istCQRL92TvqxyylisZmwgmf2te3mtpgi2IhyQirGOJ4JpIoMHhRYHYTNyf9hEIOy86KVHjTa+ItGrKiwanrameCSWr7wOppnZBs35tmNyHXsPvZ+S6sUer51G7lLFVr5A1XHRH9n24bMhywe3nPUOzU9TeaEvSdZkYalHzeiRtlyR2MKM9skyTRA47vQDHS2nGvsAvlcVpyx7uJi7WtXQivw+v3WxURFdsCHQ62fFFx686qFSgSaWLLk5b4V71Zd9FUg8z9DiQSPbQOnsIgcvXxiEyBKsOpauC5lA5KC+TyLqyuDsaty1Q2rQEwbpAkyRqL3NhHVucrzJ//pYhXBbdoRO5t10YVjSZYbqKykXDxP0y7+FqkflQkHuK6kVDe7+leiXHXzcMPUGfyCd3razJOtSeMOTG4m9o4qrYHJXLsq5NpMgdRfWcQXWMoAp2BA7ndCzVcwIXT0sWb9XB9KC0Ipkl3dE4LfC2dD+ToRNFXFUMPerg7BictpzlTluy+CqF6mWFiWH0USnq97cF+mY6Ag/VXYMZinFayJpdUdiG2DNmySdYFtugt1bCRHJueFsGtwmVSwadQLBpKS9CeVHhbwqUevx+i2lp3KbA9p2OwNSCNY2/Df66IVxV+OuG0rJk6TPfEl4TCHf1clGq0NP9uVCpoHlUW6BUesPFNA1OG5wIyRJmxRhta4YeMYSrGqdhJKPlWZyOkE+424bASzAt2ZduQ+FvabmXjiAQnGUflQnBQLiiBaKayZpRscDDJx5MIVMM/8WDALgt+f592wfJTYGg6YLTkTpop2PxdlJy15IGCq+V4zUUjpvhb1tGx288lOze8UI8IvskXFHYlQDTg2BNUz1v8Bdd3A2XYEMJeUwtl/VzTda5v6EpX5UaOrcpmddwRfehebVLOW4BrTRdTfVKjtewqAzCaw7hmsJfdZj+d0VpWeE2FO21Mm7LknsQjQwyO59PvmBnJ4odRh4y5C6kIfSmUjr7LdGEpX6bGGK2uGpShmhKUo7REYE66J4izzXdqbxvzFrXEo1bkortLyjr50U6O0N1NWnLpXswJZpJyco5m0+TtHpShrSAX1UO76CaDq1DOcEGjN2vC/YRhdMF3dVklQzTs4SrYJpG0ssj4jglNUvrsFwrC8A0NbZ4Thtr0rIYX2mYk9ZycqtwvJSkgJRlvqU3lZIfiMh8S1LNsS60jqWkmemzZ+zi4XWsiIblkJF6GognMrqTwh6T+QJXSsuW7rji0Ovn2bwrFdzvlLwfCSoMt5QQjauCUcbSPgBJVVG9oOlMW0wkqXh/U5OOJsTDwnSTlgWz3bglxWvIxM2UGhzwtqiEPXQBMK0nJWymCJyU8VKbTiMgixyyXDZW0nNIyzlmx8GrKy60xjgxcpF4OGfxtXOEqxa76ePpjLH3L/DEO07ithSbvTI6VvRGpPbIX3W49pycNIThzwgMYvu/RGzclQmcMIf6LQXcp8Dn+mFCUrZEqYMpjPy4Zkl7DllFal22vncW302ZumkD/44d1k9kLH+pYvPplqSmME2D5ydgoR27rHyJKBcsxF+7g1tg4/vwsE1Fd0rw1+0DOdH4noLRMTRuzegNW7xLASZWMt5GanEAdo7BE799gswTxWm6CjsWE6wY4skUFDSOWbwdzc6TU86/ZZbeiKU7JXVWOpGUeFyFaFjjrTo0bxKoXG90D4ZgeorepNy7dS1KW3rDSogsegIzcFug3JyNu3Li4Rz/MyX8Ovhb4F/1SCs5+UiCv+qI87Tm4G4bmkcLYxDZ872xPYewcyAl2i/zc2h8SwrpY4WeirBGjKLyFY2z4xCP5PRG9owsgK2nWBrHimfY9S+sglTLvtty2WyWKV/VeHWF66cE3h5e+9p/cVh75Rxjoy16I7B5MsG6ltWTlqsbw7huys5tlo1WmeHHFeffMsvql9jiu4beCCx+leLs++5k54Unufpzc6Rly8bT9rza7dsNq3e6rH1FQnfScv7XT1I/5mJleXLhTbMArD/NYemn5khbAiW79tNzNG+CpZ+a4/yvnwSgNNylfqumNwKdfTlbT7NcfOMs289KaR2C3ojiyuvnuPjGWdafJTDExk2QloTR5+KvzhIcbnL+LbOsPVvTnvksfHkpQwHbrRLOHQ2cm1tk1UyMu7YYD3bLIw2lViKtCPxFdQzJUEbz6N7cmlgRTWe09+ekIymdgylJNce0tDDJIcZOWhLIkLfkCXyqkvXhSd6WofGkBHIJRjSPZbQO2T7rkNWil6NRS1ZwLSS1op7JzVG5orMv59IvzcpZNBUTVxGIkgu9MfntaFx0dTQl9WzLX2rIQmG2HPrQKdnjQPmaOPCdGYH2tI7IuZX5Qsixc3tGONqVgnWriCZkfJNMY7QldxX5bk1TrLCZJprI2eqEDD1mUG6O6xb1NRvC+rG8McRGpwSJxuaQrwTEkQtW0Yp80tghShyStotNNfEwOG1Z/8GK4PR7xZlSK0ckNdm/yorzqhNIhnJ0JmdINJkTTeWig7SleSTHbSpaB8XJbB9JKV90cLYdkvGU8lCXYMUh2BQnMpqQsXGWZdNnyyH5zV3iKqhE4GvRZE5vJiENBO6YhRaVK9KhjHgiIznYIx7OaR2WWpakbOneHJNN9Qq9KvPTG7FsPF0CSdGYxasrvIYirkLzWIbbVmw+VRFswdbTJIBSXhR9mRUB1fZMcc6mEK7L361DMt9eY9e5sphIgi/VixKo6k4oeqOAEigsFtISdKcUrUOqsFcEQhcPybgmtZzmYWgezaW2J1EkowI5d9uKpCYQMmtg6w6DyhWZD61jidRhuODuaPSlsLCt5Mwmg+6EJR3OBMY+qlA9RRaI8a57cp3mrSnWQDykqN9uiYcL6JlvaR3QuE1NUrPEw1JP7O3Q17lZyWJi6I3lZJ7YD2jwtyxZwyOpiv0ktTcytlkA7YOZOLZrAlnbxfR1p6wQUmhZd0nFsnNrLs5tQYrk1kXH9sYzOdO3y2TTMaYnUEO3BZknMLfOvhxvW5yxpGbpTsu1diF1bltjOpqVEwbd0yx//9MBsQEq1yzPGrmK17CUliHYFvtq6p6E3IPuuIu/pfEblriimby3R3StgunB1saNbGbX18MEm0UgbxQm71jHq8u9NJ8R9Z3baCInd8F0JLAI4LTlzM1dcUytkTM6HraEyxq8nMYRgT7qg210InoqqcqcZ6F8JwssK18i67AzI7q3N6wgL1jbBvI5MoCxDWQgAxnIQAYykIEMZCAD+aKUL9jZCbyUtCRQNacrESSvXhQcdhW5Sz+yWVoRuIxOQDVciZSFljwRYgKQNLaOhH3Hq6t+Vkh1dd9DVaMxOkxx6gZvQ9hOgjVh7cCCijVKWzodH4YSKlc0OrZ0phTBumL6bfO4DYu3UxQ8h4rcp18Qa41EaawjUAZ/W6IP6Ugq8J8M/OGoDw3ytwyqp8hzYRLJSrsRJIW34ZAnWoqdE0mDh4uO3NvuoBdQq6SW0Tgm2Ru3paQgs27IPWH50gn425LqtQbWXjmHv1qQIaQSbck9icokHSnAzELJjplIkQYS5bQakqrFbcl7/pJbQE6EnSbzwd0xfb7+HDgfTbKv2mArKkOiCE0s1K06Z6VZZXi0BbHGd4pougIbSrGkzmA8aLEW19CJYvhcRjyksOWUcsGYJUXH4BSh1d2CX2sspu7g122/EM9u+XgbBret8Lct4VoR0XEygjAmTQzWBaMs2ViRBlBW2NtKKc6OoXVQkeXCNNZaraAjLSn2usbftmTVDMfkmEhT9hLh+x+CYKhHe7FKnBbjnoPyJVuERYpYNzVeY2+PRFMC71A5xEciMs/i1YUNL61IpNXfVoTXjKTNmwonKtiJfItKhEnMdAXe5m0Y3KbC31LkHjLfVUXzWIbpQVouSALamol7c8LVIjqHFNX6awbTNtggk0LxpsW6kj1zG4q0BMrklK4Kw1/39ojeMERjEI8JcxI92dTJSC50pj2Bb6QFMtDpQrBm+mPgbZp+AWk3FdiR05Tod28yw2sUa1OJDvhsqV7UzLzzwWK/7GZCZV7jzJC7lpmRHZq3ZFI8nGmi62Bs+xYyaldTNh8fw+lAeNkT5ry6ZmK4Racd4G9qZmoNdm6W75iWxt3SlJcKON6KwBoBKlctyXjajxCDwCSsAdUq9qyBuAb2gDD2Td2dC+tcikB4/Axnoou3Y3GaimBd4AsA3ZaPiQQKHKxrnLaidgG8dUfgJy0oL1rKVxUT9wmTX7gumQSnrShfU3SvVXCbitKS6vdi2hVTL6CJytLZKJGdrxAsubhN0X1OVyAUu1BEf1Oi037B+DP6kCbYEFiS21C425rKZQ1W+uDkrsVtKLxtI2s3Ktgw6wqnJXpQd4T5yt+SaLluGYJ1gUnpnsBVdCLwHacjsEgFOAUUTfR6AW81UmhtIon4q4aLziTjqXLRL9G4pbQi+9xparLQUr4i51FcQImdtpBSROMWf1s+aw2UrmlKq1IgTyrPC7InyVSf9cpzMpSy1P74FNoIm6G/pVAdg04UZT+meUTWTNmPIdaUJtooJ6dW7WK0ZD5KlR56OsL1U0gVtTDCFMxkys1xSwn+FiSTCUYLU1ytFEFxjtYLIgxUkSUOpU9LuGSgGKfyVY3bkMwEsaa8WBDWIGs3XHLojQpJDqmic7lGbzwjGoPaxYINtEAhZCUp6E8jB+sClUTmo6twNx05uzOxCchlb+muxiz7+JtCupGWBcKt6w52l4kulOzdyGOW0oqwS5WXlOytYUuwaYWFEsgqOdGozLV1oTMtBfrBiiEeFphXWhZoT3u/wOZKyxIhd5uW3hhULxWMZj3JlCYVK9DxVBjP/G3JYqhUoKpOW8bS30agxj1hXXQ6isqi2EEqE3iS7iqqV3LCVds/W5MKHPjVeXSsKF+zBNdc/G1VMHXZAtYsmYN4SGDJ5SXZLyYq7CMtNoMp+rVYA+GiQ+WyYuhCDlrg67ULYrsEm0IS4DZET3jFWta7R3cCJhJbLffluXSimHjPAgePrhe6zhKP5ng7e1D+cMkIQ5uWfWQdiIco5lVTWZT940SKobN7+igZEpIe0yvIYBKFcXPcqx5+3aIzaDwlJpoU4omRhxW9UduHUgdrYj96BaOiTmT97u7lXR2tY8l6ZWi6EwprFHFFaM+37nD7mai0ZIlGFOFWSuOQhy1ldCcUqrl3nn227MLWvQbUWyXRJR2wXYGc7p6/u/vL6UoWaFc3AaShInOFqdga20c7qVTuKUsMFoHbjj2ckBVz3Ru25K5AmZ1IEBtZRZA+uW/xtwcwts8nX7CzE6dOf+FlgeA7d1OYKpf/dp2UaLRQdD3BplpTUDrmivIlgzscCWtSQwz3cMP204PBhqTyyMHWPfKu4MmDTVEoaUk2Su1yLtfe8sg6Duy4pAG0DgqELqnB5ktnGXv/ApkvB4vpWtozcijoHpSvaoIVweh6dcX02+cBcHYcdEG52Gv65AX8LPME6tFZLxNc8vsGi9uUA0F19oyuYEPh16FUEmpVgPEH9njxJ+/JSYYs0WRWGDWCN/eWXYEBTsiYxiM5jWMC3wBxcuIh2dC5A86GK5C3ak64LOn/yjWBPZWXhK0ldwXnHq7K+92pnLQkNUThWkFnDDTikCPBBpvdEleWxiDI+eTV2wiHIybCFkNhRG9hDF1JaO7WwUSG2mdcKlct5NBJPZ5oThKsyzVrl3KCKx6fWdoHwOR9Of42HCpvU7kCYw+nuDvyLOVrCr8hMCvTUxz4Hzm1i+Bvyk/5zQKmsFmi2/LJUk24qlhcGcFfFMzLxP05JIravXJ/4w9l1Otl8pZLeM1h6HHFxAMpI48XeNrLDs2G1NVcWx/G6SpqFy3p+QrhkiFqFHj7nkKve6gUhi4KrMMabqAktqpwkOsK2zN92le/LoaGieSACFeF+UblAikwTWHAChcNvRFLaVkRj2d4O4rSqhzaMn8WE1luedVpVC4HaDKaM/wY9IY1SRUyZ9fZsSRD8ozuhosup4SbObWzTrGOYOLBhDw27H/TvFChRoL/1ok0AySTmjZ/W4yW3CnYYopAAAjTkL2+bqmhhKoYWNuu4bbkt2qnQoYeEfhoZVEcP7e5Rye+K2m493c0Jv/PAwuOZXVzCK8ucJ6JU5rhJ3KyDR+t96BbOtk78EqrFm8Hqg97jDxm2f6f0+TbHqVVy8UzByktK8Y/bRk6B/FUyvTb5hl7OKdy1TJ5WjH0R6cY+eACY2ccRn9vof8b02+bp3bRcssPn2boHAw9rjj4K/MM/4usufJfnEb7GeGapbyay0F4qczEexbwt2UNjD4mFkdY6TH+Gfm7cs1y+HULmAhq5+Xwnvxt0UmT75rHa+aojtCt+1uWuGYZPhdjHcvYIxmV5Yxg40YoQxbk5IXB5ewUjnsxd6YINOjRHuWlgj2pJK/3bookaBMqymuZwDACOXRHnkgxbc3Q41ID0BvPicfTAvYjhn/uQPf2COtKAMBEcl7knpwdbkuMLbelpXFuVyBEuzVDwbrC6dDfIyoDMqlr0rEq1k9hnNbFoHM6Ynj4W6oPgVO5OHDpLpykgHlmvkACM9/S3Ve0UthRBJuWuIA/7zaaslaCCLqciBMEdHoum1sVOt96gnzTQw3FtI4V9QfA2kZNIEAXA9bWhvDXDPG5GjYy1FerrC8PUbpi6D06hPdQiXgrQHcMS0ujZFs+21sVaLnos2WyAMILHu2eh+7B6vlxnECCO46XYXoKp6OlIWVLAgLdA9JDTWWQVMUBCNYMqmgPkVQswRbk1bTfssAZjShddTBTXYHNOQKjthqysDjPlwzORCSseznc8pL7hPq3gIdhwbQMOhXmLrclMEG3KQ6M7omx7G8XdT5F64NgRRyUaETTG5bAjukV9RGrCq+1GwyAyQVFPCoOk1ViPwCUlmSdWEeubboQbIo+i8ZkbTSPwuS91wXqHEvtguxJtynOQmfG0pkRPRduWEwsujsNLUlFdJ7KlbB6tRQ6FiM0HhWIeFbNaB3QTLx7gWBdxk/HUH/xLCqHzj4xVpMKxdgK81gWXKcHS1I3PP0pTXnJ9mmLR57I8Lds/5q5J/faG1Jiy3QVOpFgw8gHFooWFXJWJdXCdkgUXlMCHeU1UQbBhjxjsAaLPzPH4vIo/rbUuJDvBbJ3xboCjZMgq2X8oYypBUVvLKM3susM0oegA4zeL9TfTgdKS0Ljrk2OzhS9YaHH1g2HeCSjvCTQPZ3KM1Yuy9kz+qDojt215m9KjWW4qvs1O7vW7ZmNw7gdaB2QOXTbSCDYU4QbCW5LEW7mZJ6WAKsqIISfJXqvXLNfbtGdzknPV0iqsu6HH3LIi8a65auacE1RviaBvYO/PE/mF/A1LQGWeERY27JahtfQhIuOlBtsK/zHQtKJhKEPnaJxyCHYFPi5t6MoLWuCdU0awNBjUkeZe+J4+9sDGNvnkwGMbSADGchABjKQgQxkIAMZyBelOP/xR26U7kqZ6UclchKNakzPUllO6Ew4jHxgge43H0e3cxYBf8eSxxJBaRx2sG0YfVTROOIRbliyz1SEZSJXDF1KiSsab0e80mDbUnnM0p5xiKuWeMwycZ9FJzmjj2QkFUN72pA7ltKqJa1oYk9gFuOfSdk56jD98wss/dQcY++XaOzwE9CZMky8Z54J4OrPzTH1QEZ7UqAXnX2K/W+a54l3nGTmUxk7Nxtmfk0iqis/Okd6XrEEVBbBdaGrZRyq13YjsilhlrF1h8HfgpGzljQAp5uzfLXWjyZ2JiU8MvagghCCNYW3o3F6Od1xzfC5lM2nOJSWLeFmRv0Wh2Bd0soAjRecJFxXmF5OUpHoSSdTVK/mVK8qdJaRlDTBdsbkvYryX5ym/LwTWJPT6ykyTzF5b05nXBPUpdgvKVm8hoz9EysTvO0zTybaChiebhLdO8rBm+s88c838emzVdKyJQRY9+ktSwrXNA2NpyR46w5Yy2JzmG848BkeHr+JmV8/zeoPzWGescNd+66yCqw9Uwpo/+ruZ+HNQHfCkchiDo2nxSRlj2gyx1ZSFo9ZnCVDWsuoPW5ozeyFl9Smh/Us02+bp/unTyMqIIWbTzGYMGPn6RZ31WXrNkO5GtFsuXSPxvibHtu3OtKvIIdkyGIjQ/dAyuhQm+1pj2hCYaa7RMshbixN79y2EFeYWKIz5WVhcilf2Av7DJ+1jD2R0p5yAGkK57YspdUElbqUV3P87ZTmAZejP7NA+9tO0DxgilS8JfMVlWvSlG7oEYepd85T/+5ZDrx3nuRr7kQnOZ0pj+gbjjN1bxf9r/ez/v2zOJGlPaI59IZ5Lj/voOyjDUWtgCZ5zZytKKTy4XnqPzOHXxcoVjRi0AXxzPTpjLVnulSuWXRiyUIjzEBrEu0vX1N09kkh+YE3zrPzIimwH3kYuqt7mZWhixmqZVkEWPGxWmCt0bgwymUedKY0wRpUF3OIboxGhddlJiqLsIYUyJYe9+jsExjP5WvjTADtaY2JLJ2dUv87q3dKmsm7ZYedtCb9RDR0ZqB2yybdlRrtGcPYM1ZZf3iC7pREvytnXa799JwwBTYU3YMZQx8SXRHty+j8/BwHf0l0wsVfleL49Xcfp3RFIIZLPzFH+3DGGAI7Vas5rUOShVCpJS3nbL9kFrdtac8oogmH/Z+A3oUaG09RHHjjPFdeP8fG205SuSLNLcMVzeLPzKEy0UOtgzn+hqY1IxkSnVgaR1xwUlbvlCZ/8eUb9fb4pxXeftgYKVHaFl3ROCJMUeGaRVloOSFuy7JvIcf0crZv8Qg2AoGqGAg/dobei2dRVuHX5TO1c6I7K1cgd7QUY1fAxKLLdWpBBSRlS+2C7RMIpEUGwN+Wgn9/2+I3crpjopPak4ZgE6qLCSqzbDzVI1y3eK2MRtfBaVsqS5baHy+w/v2zDD+qGHkiojXjk5QVY+9boPkdJ3GinNY+0Rfl1QyvkdI86NEbkt8fezinPa2L7Ici2JJ7AGE8TEMYetTBa1g2y2Um74WVL3epLsla70Uufq4o/eVp7HOOM/ovAWPvX+DcW08yeQ+szUh2MR7OsZGRqL+xmJYhG0oxdUeyujF0DqaoRJpXxkNWGiGOWDJjhTHwF05x8U2zGCuQv/hASlawXdqlkHLbklQU2aZD7kqBudPVJGXJjoy9f4GNV8ziNsHbCdCJZeislqzhD86hckuwbWmvlqks52x5ZcIVi3UUlWsZ0YjGa8m5YRKLvq/M6FKO30j7YxlXFLWLOZmvpNA6kcxbUoGhs4bhcwmdSQevlbN1u8FtWtKSonqhICOJLbUHpYlk6XGBLXnNjHBD43Ry/L+9m+wls5jY0t6nqZ2DyrUMZS3hx86w8uo5nJ4Uo+sUgvpek22dCJFE8PEztJ5/guDjZwiA/Adm+4QvB/9HgvsP91Dw/tD+thNEIxqnYwm2MzoTDuP3KSrLMa19Lk6U47Zz2lOGsfcvUP7m4zQPOFQXU8J1pw9fCzdyxh5OcD95LwDZy2cZ+9152t92gqSkcSJLa0YyC2MPx3QnHPx6ztqzHMqrOdu3aYbO5cz82gKLr52j/JF5Ot8/i7+tKC/lDH3oFK1vP4lfT4mrXgFlErZGgHBFM/q42FjhmmL4D+dZe+Ucw3+4gPfcE8W5BbXLMXHNoT2lOfCrC1x+wxyltRRrFL0RQ/hIymVElwfKUlnUxEOCRumNaKAgi7poKK3leK2caNjgdiztKc3o4zn1Y4bSEpTXMtpThsqiZXPa59C9KTrOyULN9NvOyP76+rsAYex0qoqhiwnDT+S4n7wXx24DQkLi+Jbg42fofsVJohc9HT70T1Qv54xvNDj7jGluvq9LUnYoXaxj9Rgmtvj1hKTsMHQ+x2tk+Gsdgi2f7mTI5D1tmrffmAvw63tnUu1ixgpw4K0P0XztIWbeMk/v6+/C/+u7yX90Dm/HojIhAwrqFq9laT/vBOMPpbT2Gw7+ynz/WuvfP0un5zL2UEbjsGHfW+Vcrd+qGLlbzrHx31mg9fwTVBehPQ21S2Lj1q4ImVFSdRg+l5GEGtsZZHY+n3zBzo7T0sRVRWUpIykpogmF2xGawdUfmmPqN+dZfb5QnrgdS2SgccghC6C0ktMdFcrk3rDgcL2WGEDtSUP1asrqgcIhmFKkhzROt2DhCXI2nmYoLWviYcPBX5on+e5Z3G5O84AhLeW4Qz3yeontWx3Cdcvyj88BsPjaOZwIqlcz/OJw2HnRSayBnaOOQHeKZoybL53F6ULzkKY7mbP1vbNygBTMaFDcexX8FQe3VVzjn6E7ZjBlSbHnPiShoj2jsMYw9Bi0D+zhdgF6VU1nVON0Badav0VjtSV4+xnUHXOMfHCBzZfOSgPKFcv2f5+leUThbwo7THlZYE1ZIKwuM792N51vPUHjkNQQuG1F84Bh+7VzDF3MCdcTOpM+7QOW3DEEWxYT58RlQ2efIitqmrQuaqVSTePCMNVtOLc+TrAB3QnF0JFtJn/kMZrfcZK1u9qyLroKZ8vBbSn8Lcvq+CgXR8cJNhWt559g6jfnOXf0JA/o/UzTIK1Yxj4N5hltwjM14qpQj4frimSfLWiyNVng0TvUkxykko7Hu6n0YNmBcSjNSD47LSiToaDKXPGllqApa63T8cWoaTgkVTmE05Kkp/0tRRZI+r9eLQuOfkmTr5fJRyzJlmALgq2cPAKvaYmGNToTp6A7vreV4opie7/ACjMX8qpAOuOqi9ewdCY1OjV0pxQrPzIHSu4DK5jw3pjFa0JSUfSG4erPz1G9ZNn4vlmiUTFUvZYYW9vHAvInzZKUlThJixmbL5+l6ywCAvnr3iQQip1bpB5t7VVz8lsdgTbsHNOUlmD1h+dIKuAVzogTSc1OsGxoHYTSsmCyy4ti0C7/2JwYgwgcqD2zdzhsPtnQ2VLwt1JfEmkAgVEGW5bcEye9ddgCmmTlRhhb5il2UXHhwhOyxnoynt6O1OqlHUNnuqj/iIHran9UwUDlIE3zbJBRe8ijcUdG87FRVChMSavnxqle1bQPiQORBQIZtUr2TzoseAYTg6rFmIt7+Lq0KthzmT9LPJXibjj9juzNm3OykRSvaJioI0VWyWnPCJY/9/ZqFFFWGKAArw65o3BbBSyrLeO+CztTmcCuDr1hgYtvnMVpK7afmvXrg6yzV494vTSPAsYSj1gajnT2Li+Js94bg3g6IV50qP3JGTZfNktSEaiFda3U5wBOZOlOKOq3aNLAFScxFWgMCF7c9ARy1i0guMpK9/TNZ+Z425pgE3ojxRiGqmBtU6hck5YU2xMGv27pTiqsdjCx7PvmYUWwZXA68pw7N2lqCEuWysHt+HTHJQC3/gOzlFdyOXtCeY4sNEy/7TTxD8/htkTHdSbFKYvGpCt7a7+ivJxT+5NTAk0zmtZBuT872qO9L6B0WZOUivGNDNRlfmuPil5Ze9UcwQY0jkCeCIxVFVBQnRad2rXUTvYmMyrnHdyWRScOvdFc6lySgjp+w6e0Ksxuze84KbAlZUmqoLTFRru1LjmRL8x8Yw9ZUl/R2SdQJqdrSaqKnReeJAukFsRtQerIXG183yy9YaFmj8ZUAaXSRDMJJnJRKTSOGHKnOPsciB1h0GzdnDM5b9h4regxLESjpqCBBtWGzkyhs5Vi42kuQVFTYTVEY4rc0IcBhZsZ6QGFiS3diYIyekcX1zOYm+eIRmH4ib2ztDuqSWqKxg/N0RuRc6M3AqVly9rNjtS6rWZEo4ZoRJN92wmsUSz95BxpWWCUu8bnzotO4jzvBKiiLmU1JndkXcU1gVPpGBqHXLJA4PTdMZn36BuOs/5Mh9KSpTtqcCLL8B+e2tt/hzzCbzlOr2ZIA8Xmy2bpTkggKRrVpKHso/VnegTrlviAwIlNLLZJb0Sz8uo5uvtEEZRXczamDb2aZvnHxNZpzXjSuHIUUJpoDMYQNr3uqLDoNo9A5yfn+jUrW7cZxh5NpZE3HnFN4TUs2y8RNsn6MYfykkCOm/tlvfWGFbqmKK3mBJuWzrQmKByr+jGpd+uOadrTug9D7eyz6FRg0H7HkjsCaTUR6LZh56imdjll+5hDiAR1u2Oaqd+cZ+P7ZnFWIa5q2tMu2TPn6K4uwgf/SWi0M0X7205QvqppFjBAk+S0bq5gvZyt2wJqV1LaN4+Q+YrekCJ3PYLNhOZBg7IOuVOmtc8h2pfSPBKSVLZu0J9JZU+ndqbFCGl/7VPp7MvZ+L5Zqospl35lFn8TRn9vgdUfmuvbgb1Rxb7fkDXW+V4Z17VXzeG0CyZHz7L5VNNnfGsd0ALjW9SsvXIOE4vDtPpsxc0/Oc/mS2fpjUH4m2e4+vNzxEM5zUjm11sc1Ox8PhnA2AYykIEMZCADGchABjKQgXxRyhfs7KhEotomksjybhNOJ8qpLGXUXzyLUxQUqsxy5GcXGH2sR+Va8fm2pbPP4jaFacNtC1tJeS2jtd/pNxJ0G3LtcFWieKrpcPRnFpj6zXnCVbl+d0KRBopgy1K9oDn6XQ8AMPOWebrjiuqVDJUK3Gb6bfOY66Ay/k7OxKdT/C3LyNmEiXdLQXCwk3P0NQsC55i3VBcTpt45T1yzjHxECt8q1zLJikQKt20pLcs9D33sQUY+uCCc7qs5Ix9cIFy3jDwukZhdFrZyMRYmlcLi6mKGE1kO/8I84w8VRcSSMGHs/QsEG5ZgK2XkAwscev08U785T+VazvAfLOB2c5yOZexuibiYXs70O+apXpXfCDdzDrxxnuqfnqJxyGPyt+Y5+poFvKZl+A8XhIUlow/NAVBrUoyvego7IvAsY3IaNwsTV+P8MGfffZz6MU3+mHDRZ67FaUmUTllwRyK24xBvx1L58Gm2vmdWGPccGYtjPyoRL89JUVlRQLwtkbqxeY/J357HaolmVx71GX5UWHYAJn9P5jkNhRWsc01SZTbV/WaKpbVcePitROXHHsnIU42/Zihdk0Zdk++aZ+KBlMq1nGjMkg8lhGsKm2r8dS3sdQZu/skFqBSNIUc0uZGI8OS75hl/7wKl9RyvtdeHpHItZeqd81SWcrymFJz725IV6k4qJu7volNLuGqZfsc84w/1qF3KKS9b/IYUp5dX5Rpjj2SMPpIx/IcLjL93oZ9Kz40Ujatc9uPYIwnT75in8uHT0jSvyHDlpmg+WbdMn5J7nPyteUwM1UV5Jm9bMktT75xn5PEMtyGRUNPLcbdkTMvXINgumrlOSNYk3LD9iKjbsUy9/4H+GIw/mKGLRoFmy2X6VEJlUZoAR6Oq3/dp5t8yxh6O+WzZLcgH6M7eAkDtQiyQlFTWCkaKY0EyGbq3p84OvHGe4ceBe4fY/09w68vuQWdw6/efIR1L0LFi5LEMf1MgFtULmsn7Ew7+8jwT98KxHztFdTGj+s9lAGZ+bZ6Jv/MFclfIvk/B6GcUk/OG8QdzJv7dYebf0j673PS8RTUdhi7k7DsVCZvVqkPtcs7QH53i0BvmOfwL8pw6Vow9JNedfvs8ow9bxn53geHHLcMXBLqx/82ix8YfkELm6BuOUzsvBa+3vOo0Y/Muk/fllK9K5uh6SX1hpnTXXYEILVuGzuWM/a6sqZHHcrwVh/JqAUNZTqks5kyfyplaEDIGgMqfn8J0YeSxnLH3iT46+Mvz1C5AaUXIAcL1nMn7ckorivEHLOWrMPFAysynpIB58rfmqV4Wfed0pDmrSqVxbrCZU7ucU17NOfjL87htWXfBtmXofM7YZyL8usXtCHwZYPiJnKHzObU/PsXwuQS3balezcg8xejjMcPnMoYfhdFHRZcNXUxxirOgci0jGpfMfe7eMGSU/vI0w+ciKldg4oEI/3yAKZZqZbkobk8V1pOxbt4sY+c1pKA72BSylsOvWyB3hcEsWFfCpGQFgoiS5piZX0RjlTA8SeZVyHi603Ld6p+dwmkpop5L7WIOTRenXkD0rhpGzqWMPWhvaCroRJbyakppTdbc1DvnqVy1OG3LvrfOU72WMv7eBWqX5ZwYPif3OHQxZ/yUg9OB2uWM6bfNM/OWecYeSahczZk608P0ILzqMPwHC9Qu5Qyfk7mbeDCmejnn8C/Ieq1egsm7c0YfS5n5tXlKGxlOO2PigZTRx1NGH8twmzIf3r89TPVaytjvLjD2cMTwOTkbK9cy9v3GPKXVjLFHMmp/cop9b51n4tMJY+9fYOhiytRvzuO2RI9NPJAy/juyPoN6ThqIrVC7kuK0c5xI7ufQ6+cZPp+z9T2zbLxiltJaSvkvpJGwiXLa+32SUDH5W/NMvHuB4XM93K5l7H0L1C6lTLx7gcl3zbP/zfOYOGf4bE5pIxfCjFZO8l+fLWvuj04xfF6yxMN/sEC4mVNZSqleyTGJ7HmdQeWqkPWUVzMm3rPQJy2pXcyZ/K15/LolXDZsvnSWuKqpXRBdXVrN2ffWecYeifHrlolPp7jtotEmAj+uLsaMvW+BiftlnkbOyXujhX0y8z9Thi7E7PuNefwdi9+URtX7fmOe2p+cIjdQXit629UtlWs5cVVIQspLOf6OpfSXpzn0i/OoFKbfMc/Mr88z+a55SqsJ5WuSGRt/MCXcyqn+6SmGLqaUNoUlc+qd84R/dYbxzyT9tTtcwMN3IfaltZhgK2fmLfNMfLA4b5TFdC3lj5wmDenbPpmr+0Q18bCifrNs8NKq6Ig0ULiNGJ1AuBZTOr9NaSMjXBSY5W6j212pLOxhg3dtSbdd9J7qgv/Xd1NakrNt/QdmqV1JGX8wKfRMcXZ+w/E+0cHkb80z+vti0w49AUPncsYfLPTvomTBy6sZfiOXM+pPTzF9Wtaq27Ecer3o5IO/NE+4opl++zxjDyfobABj+3zyBTs7acUy9KFTZIGmN6YwPYu/k+G28r6S2Lm5WAjNjJ0XnqR+i0fjsKY3LI2Phs4LTaQTQTQscB6AsfctENfklrJAWFN6I8LUVDSKpvGCk6RlSQH7dUnX94YEhnHtNXP4BaNYuCFG9r637hlNWaBwCzyj6eX0hgxpCTqTDus/MFscUorLb5hj7HcXaBw09IZEsYw8BvXnPk2u4ykm3r0gDa7GFXH1OvjOy2aJa6rPIDP2vgUqHz59wxh2J+Xzaahw/kkwvHFVsfzjc3QmNdE3HMcklt7X30X0DcfxdyzbtwlUYv0HJAWalBW9r7+L8kfk2pKChtaMOD3VPz1FsJmQBjIeW987y+jvS83P5ksLzPPzTuD93d1UrsVE33icZKi4wakeva7b71AMkOfSDdivC+1q7TFH4E4FtaKJFdFURjwqdUTZSomSk1C/vXB8c4hnYvJiHi//4iydfYrtlRrdCUU0YelOSF1F4ya5X1s0DotGLVtPtaRFPc76i58u9+QLPGa367fekRocEFYyE+12UIf1Z2hsQSPcmZHGXZsvn6U7ZogrQqfrrHn0RqR2Jx4uGrOWLRfeNIuq7yrKjLRqqV0WpdT8Dkm1O60947Jx1KX1/BO0Dmh2npSSBohC+6NTBFuWpOpgunm/liypGvx6htO1xBXFzotOkpQN0TccJy7r/r4CGD6fULkmFpfTtYz+/gJDHzrF9i0uydfcSf3Fs1SWk37tm9vO8Zo5E+9eIPyrM/1AgemJco5GFdPvmEcVCtjElt7YLpV1VlAAQ+Yran9yitKqZeTRnNFHZO3vyu462xWdWqZ/Rw4joUiV9+MaVBczpt45z763ztMdM6Rl02/K9vkkLuor2vtkDqJp+b7uCoPizK/L/bvtvXtY/vE5Wgek+ePqCc3qD8+hUsvZ9xyHWJrs7dxsiKZS4pqiO7XXMHT9mYpzbz1J/WbD1rPkcN986SybT1V0Jvb2+vbthuYhxebTLOvP1DSPKDaf7OIWgYrWfoGhNA9pOlMeyUhGWpa6vOgbj7P0E3Ms/ZTAT4S2WnH15+a48vo5tu9QbHzfLPXbFJt3uLSnNVd/bo61V86xfXtRX/KJM8RDiqSsqL94ls0vSVh7trDxtfbfqNp7w1KTpDKoXNKMvU/W3s6LTkpz6CFFVpK6B4DcFRa6nZsNTpTTft6J/rVK6xlJQXe++No51n9AapBMV+r+Smsp3VFhBYpGd5s6C1Y/CRVb3zMr9K/fO0t1MaNx1FBezaV+oVJAmEY03W85jjWyljK3oGstGzrTmvJSTLhRNPYMpTkzCKRIJxJoC7ZTesNOn7q8PeXQ/rYT9IY0uohNxBXdh+KAOChe87q9fEQwMZkvNUSma/tnESBNRDuaxgtOUr5q+hDbiQdSojGBo9W/e1a6zadCoetvaXRPKI+dHYf2vqKbeksor9szFndL6j2UhdKSIVgvGD8LBqpeTWPae9TRvWFLr2Zoz2jctkD7xh5OyR1Fb9jgtnI2XzbLzotO0pmWxpmbL5slGpYbzjxFp6jdiCYslT8/xfYd0rS4cdjQeMFJGt91ku6YoXVQ99fsLn1x66Cm8uen8HcykrLpt0qov3iWsd9dIK5omgekue7OEYftWz16NU2vpmkeNH3nM/6yJ/drrKJRF2sU1cWkf8ZWPnyaaEiz9T2zLL5W9k79xbP4mwntbzvR36u70vyOk6S+womk/jUNi3Uyagg+Lmu9M6nxGznltYydoy71F8+SBor2lEOwkWA1xF97l1z7jj2qtMxXNF4gNYvpVz0b9x/u2dsjawlbdzjEw07/fjqTHr3q3niD7LPhP5C9qGP6tpCJc5KvuZPuqKH00dO09st+GPmAfHbs/Qv9dZqGitxRtL79JM39bt/20IklLhdwyGJdxl97F7mrqPz5KTKvaMBd1vSqhu6Yg/NP9wp80xGYfebD1vfI/ZueQBQBqp94kMwXuywpKUwizkP9xbMFpCuh+Z0nabzgJO3nnSAecpj87XkqS7Jgcqdov1HSpL6+wRL1/u5uWs8/gdPO0L2cznNPyLk0ouhMepjYsvW9s0T/r6f0v9OZgegbjwv0uoCbuc0MfzPGrcRMn+4ycV+b8mPrmDinci1m5JEmpDlBPUdZSzYU4tcTqlctmaf6OuHzSeWfn+ivAZXtzeFuQDCpKNJQ05ksWE8LlHvwiTOYwgFrfufJoiZJ4JxxVdE4bNh+ySxeMyceycl8zdCHTlH741NE33hc6ubaltqfnGLpJ+dkjL/rZB+W25pxqP3Z3f/L+/7/ZxnA2AYykIEMZCADGchABjKQgXxRyhfu7FhoP+8EW7c7ReM46A0ZolHDxitmGf6DBcqLRcRg2CGuCtxmtwEfQOuAIq1aeiNFoaIST3/re2cJN3c9Y2F/SkvCgU8uBdGdKU13yuJElsZNFL8DSSUnHrb0hi1Xf24O0xPvfzcTsvnSWVr7JPLVee4JGodcOlPCTBaNKrpTCq+d0zwoRdy9r7uL3ig0D0mUaucY/eh0b0Sz+No54YdP6fdu6H71U+V+igzJxiv2ok+9YWkWBsK4tStrr5qTKF1Poq7RmHj/aahozTi0p4xkDrpCUJBUFJ1vPUHmKYnkFdHQ3R4auSMFp83vPEnzkI8TSaFhuJmRftWz2Xz5LNtPkchFb0iiRZ0pl+YBg7uzN81joy2CTYVNhYu/2/bx6xJBTIYzpt8xT2k1Jw2LxneZNFstX5WCXzXR4+H1acqLmtbzT2ASS+VRn52mMGbpRFFaFrYdJ5LiWGukONu7rUF3QhFsFsXY4S5hAkXj1GLxRopoIgNtabxAincpgrKZh8DqfNvP9uAJXMY6UpjvtizNQ9JszN8R+J3pSpNbt6UY/3QOCrKZHrZUXFiDV5dIcuMFJ2kc1fRGFe2ZPQxMsJXTOmD6PTzyIoq38uo5kopE/3eOuqz+0BzRNx4nrmj8v7mbtbugdjlh45kSaW8ccvrfq3/3LFtFYePOUR+dWaIRw/KPzbH50llh7DnmSSTudq8PubSOIhrVXP35OZZ/bI7ulCL6xuOo1LLzopP9KKBJ4OrPzrHxVImMt6cMjcMeKFmT0bhl86VSUJt5ip2jsiZ3SUB6I4qdb31afwzqxxw2XygZuHhfgu5ZmkeEaMNt7kH+dm6B1rQhHr4xM7Ty6jnaXyf7aTdL1RuVxpcqUVz4tVnyIGf08Yyln5jr93DYle5ksR98IRvojUJSU5i2pnzJkR4kkzlOwwgc43CvH8XMqgXsNAGKrGFaVjjdvYytXFyi88FNTUwkhd1JzfYZHJPKHjRq/ZmKYNnB9KQfx85Rh7QCnekCchFKb46DvzwvMKdcEWzvQvQKxsCa6L14PCMPctZ+cA7TFb3aOKIwflYwf1ky78aoZO7Jf1kgPTauvWaOuKoY+tApvJYVCMqSZJU3XzZLe9LIZ2qWlVlDe0r0e/SNx+lMGLoTknmKhyy1KynRiCbYtkIYgWTjdqPUAL1hYdXcjejmLjQPyz7KDcRl+duvW9qThixQbN7h0BtRRMNSHJ87iq3bpI/a2rMDmgdMf110Ziwbr5hFpwLjiocM7WmX9pRm56hD84hkM1r7DJ0pTVxWfSbB+q17ezQpS6Z++yUSoc4daByD9We4tA5ZkpowpW3dIROrewJLc7qWtAxJWWBK68+ULLNbF/SA1aKPdglUrCtNEMmlp1RvRDLYVhf9uYz0bsmLviiZL5Hr3INkIyTc2uubBJBOpORFU8fOlMJpweaTHbqTitRXbN3ukAWiC0DWgdeUxttb3zNLGirWnqlpT2mql6XHSjaaMHwul+L2MU3jiKY3ItH+9Wf5+FuKzv6M6BuPk/nQ/ZbjtGYc6sekaL59sCCzePEs7RlFb6R41rGC0GSfRqcyZrvZItjrx9KZ1HQmNNu3enjNnN7X3UX3W46TlhXhdsaBN86ThprMhaTm0Dgs68TpWbojhku/IoQuOoPg42cI/+oMlT8/Re4rRn9vgegbj7P58lmsgfVnyu+HGzmZKxAqlUPuSXPopKypv3gWk1i8RsbaK+fYfKohKStWf2iOjacJ9Lu9T5OEiuYhF6cFXj0l90Sv1I8Z4pqc37tZmd6QovmdJ9l54Umm3z7PodfP0xk3tGZcekOyvre+Z5Zww7J1m0P3W2QNdL/5OO0pYdpLfUXzqKI1oxn9/QWahzVZIGx4vSFN8ztOMv2OgoDhiDCt1V88S68ghWgdUPjNjNZBRf27Z2nNGPydjJEPLvRhwo3vOikkCYWe7jznqXSmJavsdizRkO4zHALENbn3tFhzrX2axnedpD3pEHziDF4jk8z1rRqVW7xtQa1svnxW0DuhJi0bkppDe1LTPGSY+fV5OlOG7VvlbN25SX4j2BDWUfis/myjDu39AflSSG/EpXk0JJ2sEY25tPZ71G+vEI8FdCY00ahHWvFw19s0johN0Dp4gwolvmPvhZ2vu1X0mKPIxpJ+9qt+TNbR0IWM1Fe0DuyNydor59j63lmaxVqPRhTbx1w633qCYFMyVyBZnvoxOfu7Bcqi/bwTJGVNe0bhbyUs/eRcvxdQXBVd2/62E7RnBuQE/yv5gp2dcEWzclJTXrYMn0sItgQrXV3s4TUt7W87weifC3ylM6lpHhEF3J2yjD7SY+hSSmXRcvQ1Cww9ITjtA2+UjRjUc8J/FOD60EVL5+ldukdjbv7xU0zeLQu5tJpTviITWlpWQvd4zRKuatTRNuHtdWqX8r6T1Z1QnH3fnex8lRRzmC60JzVeS+qGyqs5wZZl/MGMxkFD5klTsc0nu1ht+w6dv62oXRD4UFKVmoCbfnpBGhYWEJy4rAjqOUktx+lKI0erofv3R+nuT/uQul1DdOyPHmDf8y6x9WRhwWnelBEdEDzR2DctUllK2ZxLCDcFWw9C1Vr6y9M4XfnN8kdOE2wJK9TG983itSx3vORR4rKitJqw/iwY+eACaai5+E0u0Zg0pNq5ReqWWvsM7X1a0uBHxchzzwVsrNZoH0kJL3o0v75F+GhA/WkJM3cuc/DoOlvfM0tcVVAcuP6OYEin3z7P9pMseaLpfGZEsL0fPk3tj0/Rmc7JmmIkHPyleSrXYt785X+OSi3TpxKO/swCI08k7H/uw4w/mBBXxeC85UdOcfNPnMLfVpQ2UqbfK+tr6IJlakExcr9D7Y9P4e2oft3IxB88wNjDGTf/+CnGH4o5/LoFpj7p0j2ccMsPnSZct6Sh4tAvzlN/csrkb80Trgr177FXnwIrULihczDy7z7jpwsFNaTZ/yZpDpaEQlU+eU+vPx8A3k6G6VppZrdi2Lk14+x7jjN8XgySzIPWIWjcGbFyUqBOW987S1bKWX+mx7FnXmXrS3vUn5ISDwkzTloSiNmVr3ZJA0X4sTNFjYOwGa4/S7FzeyaGTtey+nJxNMJ/fIg0FOOptJrjNoWic+I9C2zfLnDMqz8/R+YKI1F5yZK7Ar9EixFWWpFu5u39Sti7SrL+c3dPsbpN24dmAIRrOcGWHOjlJ1zWn+GiY8Xo7y/g/f09LP/YHFc+/FS8uhyWcfVGPVNdzPrMNLsHmNOFYF06aE8+bRWcnKVvSmjdEVO7lPedYoB9C2IMVS447P+XlMl7BT9984+fYv+b59k3n3Lsx06xbz6j+qenuOUl93HwlwRDfev3n5H33jpP5XHxlKfeOc+hN8wz/jt7TUUP/so8R35+gf3PfZjaJcvR1y5w+HULLP3lkwDplD72acX+N4uuGH8oo3RNKORHH4s59Pp5SksFPOeyYeRsQv3Fsxz52QXGH8yo/PkpDr9ugem3S53eTT+1wOjvLeBuG4YeN0z+tuDhy0tSv3LzC+/n0BukJm/mXQ/y2dK8JcM93O43fW4egXNvO0nrgKZxWNN8Sk9ePyz1kF7dom5tYTqKaFyoYlfvEqYtv24LOl+48nVi2K78F0v89Darz/aIxiztwxmdaWHtWj0udVXrJ6RGpjei6E2mbN6VEU1JjYPpycGdlsCv5wxdyCkv5Ww/CcqrKUlV9RvmVRZzdGrZeeFJ0jLEoxnBtsBTrSNww82niuF84HkXsY6lspQzdDElXLfs3AJDHzpF/XahzW7cnNO6NRFnYVpLUGBUUdrIyB2pDcs9S3dSmv3uSmlFY/2c1eOayhWL2xJK8on7pR6kfE1Jrd2WpXoJqZV4PGP6VEbtvNQTHnjjPJP35Yw/KLUUlau5UCpfteybl7+rlyybT3LY/6Z5DvyjNI889HcZw4/LvQRXXJxI6rB26b2tgvaTe0Jp3xEI7s7tKdXL0oizfkzTG7FsfnlMNAHZTRHNZ0XUbxWGLNU1bBf0u3FNqLjbB4rGl8cb6BjC/S02nuJw8JfmWfnOiKSkKK2I41e9JA1xt54sDnv5moyPvwlpWaDqcVUa8VaKOgvv3x6mupiy+kNz/doq07M43Zz0RzZZen5Cd0qcmcXXzrF1h1A+Nw45jDyeEsxt4HYsjWMCn20fgGAj4YkPPJu1V81x+Q0SnFn+8TmiYYO/Y5m8u0N6ZJd1USi6t243fabE9gFp35D5AlO68qKUeFiM7N1z2elY1l41J+fzakJpTdZje8Zj+ImY5lFhuewNSy1Y/ZjB/5u7Ka8KrNUkcP43TnLpl2fJPRj5gMDf67eD27Vknpz9rX2GcNVy7fkJ4ZalfiJm+8mWff+zR+vOLjsvOkn3GR02n2IYOZvRPij75dKvzLJ6p49OoXGHjGt3UqCMu/ogLVt0ZoVpt2xYefUcP/j1f4vXlvUWD4Fb1M7Ub1a0D0mt0PpzO8TDUg81/AdSW2qNoj2l6X1TndrFmIkHIjafJkx+0Tccp3HIoTuhmD4VY7W0M+hOCXttXFFEz62z8RSB8EmD9JwnPvgsSqsZlWuWndukgSuI7ZF54tCmZdtvKlr96wf79WtLX2Lgu9dpHA1pTxoaN2lG79uiO+EW857jbXVZ+q/jpGVLebGLu799g/5sHb3OmasWAbiaRjUdUNKewGtK8H3pK+g3Q63fAY2jUuNbv00Ctk+84yQ6lZrqlVnN5pdLDVw8JIEAp2OZOCPslEs/MUf5L05T/dNTRAcStm/3pV1IFbZv1TSPip3ZnjQMn8tpfMddn6P7BzKAsQ1kIAMZyEAGMpCBDGQgA/kilS/Y2Ymmcm7+yQXiqmLlv0f94nv9r/fTOqDJXEXyZU8GYPwPH2D4LBx6g7D1XP56l9W7DPXb4Ox776I9I2QA595+ko1v77D4NZalVwoURieWib/32f+3hiu/MEfmK6pXdqEpUpw9fK7ItJQVM2+Z58h3PMi+b3lUoBkFu8vk/Sm1hz3Mub38Zns/BFspQxcTqn8qrGBuI2X6HfOMPp4x9v4Fxh5O8HYkSj7x7gWm3zaPc/pRQCJUV392jpUfmWPnGAx/VCIJ4WZG+SOnOfajp+gNG0Y+uMDBX5kne98kww87fUhbq4DnLP3w02i+86CkYC2MPKw59FeSSm5+aD/rT3OpPO5R/bNTLL52jqQkzfIaLzhJuCm9IDZfPovO4OjPLJCWFMFWxn1//STG3r9A/ZjHsR87xdn33UnzgGb0IUVlMaeymJP5FifKi6auUkCvit4cuQOT/+oy/a8C6av+dYUDb5zn1lfcTfx704TPuSgR+qbl0C89LOPXsqy9Up5v+HHF/v/LoXx1D5Kw8iNz5JWMIx/di767n7yXX/qdF1J/ck5nwqH7zcfZOSKRlsYR6ZUUTWb94ujeqGXpSx22v03WSO4qWvs1Q5ek6PHw6xZYf4lkNLa+/elsPlnS3CsnPIkAh4pbXyHFe8N/KFFygOn/qftFfld/do72t53Ar0PzEGw9I2f8vQuYRB7EkeA3fsP2CQbcT97bZ30BcBceobKcMfPr8xz8lXn2/ZuwgG0+SaCf4w+n7P/XhFtech/BmkJnAk86/AnLyNmM9T87hLvoc+srzzD1TskGjr93AZUJM1w0WezFbzhOd1IyB8OPQrhiqF6xuC2LV0TAo698CtNvnycpW4b+6BTNo5D812ez/ZJZxh/Iyb7yWRz8pXmCLUvzO05SWUpw2gJp604oxh6U3y6vZhz6xXnSkqTut18yKwxAvzFP4wUn8XfsHkMVkjUs/61kadsHM2qXcw69YV4IS148S3fKMvSxMiqTAtd979ljcgPJWO72Mome1Ou/HtekSDv+synMjsPov/mUznt0JzROSz6//pKn9wvtlZWizeDjZ/D+7sbCzfg5d7LxFIcLb5rls6X17SeL3ytgHC84yfKPCQxh9YdlnW+8YpbGd8nnVGa58OZZOs89gf83Q/3r7JKCgBT81q4UrH6jAlPYZRmyWgpzdwtdSx+9kdTkehl92PbZgHpfdxduJ6e0Juuz+83HAeh8zVNv+E71as4tP3iaQ89/iKOvWWD/m+a56TULHPvRU8z82jzjn0nY9/cuwSfOcOTnRW+5HTj87Q9RvWw59IsFG9sVIckIN4WRqrwE4TXDTT+1QO1xQ7YccuCN87hNxdCjhpHHc46+doFD/5By6A3zHPikYvhcRrhmGb/bMP0pzbFXn2LkgwvozBJs5zgdYa+q/tkpvGbG/n9JiGumz17ktoWZbOLdCwz90Sn2/2vEyIOGyodPM/FAwuRvzVO7kjJ5j6W8ktH89YNUL0Ltj0+RBQqvmXPTa2Scj/zsAjoRdkhv1ZF7bwgUMXelAPnYj52itKSYOgVHX7vA1Dvn+8xurSf18FdcksmE0d9bYPSxBL+u6Ewazr3tJNGYjH/uKraeZmnt16zMCqxs/UtTkoql860n2LzDsPRVlrgs0CAT02c1jcYU9dsgmihYPLs5bttSv9nt75Ghiyk6sWzfUWSbP90l3LCMzHvCHHYlpfLh0+z/J4XbzaldykU3ncq45b/fSxpYxv/G55aX3EdpRfUZ/kYey/F2JPsy+nsLWGD0M5bq/1UVJskPlPvIjKPf+SC1KxnRmGTgMk+RuXDTTy/g7VhGf2+Bfb8hWcrxhzKm7pExvPDmWcp/99De3tsnEMCkrBn7XWFG7Q0byl97gZtfeL8wvP7+AtUrOToRgoKJdy8QfOIM4994ltJHTzPyqOXgL81z5Gdlnkf/pzCRjj2c4zaE2S2oZ2QuNI8EHHvR/bgNYfBrfNdJRh/LSEsCJR55LCP7imdRWivgtxs+5SVL7VLK8o/PUVnOaM8oysvCHBeNufRqQuQQbqY0Dnscft0Ck781T3lZ5nv/m+fpPPcEbivHdC2ZC/v+3VK9LNH+9vNOEH3DcfbNZySholz8ttuCifcsMPUJH7edcfAvDMd+7BRZYDj2ovsBuPkFn2byHpnvifv3zqWxR4QFbf8/CkHBgTfOk5QVBz/ZI/zYGY787AKl1YTumCYNFCay/O2Th/HrKUOXUg7+8jx+YVdNfDpj4ozA5Px7KpRWpadV/cWiS0urMSPnEvZ9y6M0DnuYf7mPffPyDMEnzhDUBTGQVA3VPzvF/n+TTKiJpIFm9PAwaOg89wThVk6vqnCv+lQ+fJrKYsyxV59i37vF7ir9w0P0Rgs2v50b4dSmB25Tc/NPLlD7uvOM3rdJ86hl9NGMR181zM5NmsxXrBx3ufRNw0w80MWrK9T8A5Q+Vb5R7/7Nlf7fTkGG4zdyhh6X3kEmguFzKQd+dZ6JuzXl5ZzhJzJu+qmFPtvtyCMCbz7wzwKpB+kJOPavPk5HEEbD53PSYl/v+415yiu5lDt83V14qw6mZxl/KEUncOgX5zn62gVy39I+KI12/XrGQD5XvmBnJzjSpP28E9SfnLJvpHHDezNvEYrC62WXtWfkAwvsu2ONeColGZWur8Pnc3r7ElSisFZRvujgHJXUYfjJzzD0oVOUP3KaQ2+YZ+QDCwz/4QK1Pz7F9NvmKf/Faby/F/aT3Vqg62X9WUV6/+Nn6E7JRpj6TYF9OB2F+w/39L8/8oGFfmfj8kdOs/LqOTpTDq1bkj572/VS/cSDclB882Xi4b1iAe/fHmb9+2Wz1/54bxwqHz7N5G/P70EwCiNw5p0PUvpLYYwrrYlRHXxC4EkjHxB43+gjsiO6t0fUnyXOXVzdS6eO/e4Cm3cULGPFc+7SAU/+9jyX3zDHrS+7h+qiUF3uMnuEaxr/r+9m6I9O9WllnXbB3OILbGDtv/XYORHRmVJc/Xkx8HadQxCWqV2pH1PUrqbEz7lTGJk+epqJ9yz0GbuyEFRP98d8V6Jxi7cljE/hX52hOy3PsH1nQm9UYTqanaNGWEsspLWcYKcw7Caka/31Rmwm0GmSqtB19v7bXVgjxtPY+xa48gtz/c9e/bmCzeeYZvt2LYwow5bmAYPpFbU+hd7w/1mcuurHH/yc+ZWxv3ERhn915rqxMZx760n2v3mexrN7tKZNfxySmjDS1P74FP7f3E3po6fJHUVy3braxVLvyi4teeOI0/9788tjDvzqPGtfklL7k1N0Z+T14J8/A+yxJt30U7LWRz4oMAnzz/fJeD8to/pnp3D/4R7SMgyfy4me1GX4D8VYKH/kNFdeN8fOl3fxGlbw3MU6rP3xKWp/cgrvUw/37zH4xN7zjz2g8Bp7z7M2l5F7AiPc91ahhv18sgv3nPgtOWSqV1K6BzKmfnOe7pTCHOgA0kF76p3zfdrxPiUpAv3YdUp3ZeVHZN69v7+H0ppl6HwxnoXjAkKxDPQhS+19wto1+nsLfQc0rqm+vhv6o1OMPCJOys6xz/s4jHxwoT8uu/tod15m3jL/+b/0eWToQ6f6bGr+395N+S9OU/pLcY6sEZbG0j88dMN3Ul99znWAft3KxlPdPoPb1Z+du+EzIx8sAiwfOyNUqH+9t99Mjz4F9NQ751HTEVdePyf0801Lbm783dJH5V7jIXE6qpe6/fdqf3yK1n7D5Lv2xsL/m7vx/v4eqn96ip0Xnuz/zvVi/vm+vnHg/43cW/hXZ6j+2SnKf3Ga4BNn+uNV/oj8fvQNx294PoCklrP42rk+DbS3Q5/tcuqd81T/bG/POwuPABCECU4XdMPp/353UmDHdjQmqcnatg7Yasr+N8+DRjrbpwp/S1P6y9N0j8Z464YsVOzcUsCY/vwUnUlN+0jGTa9ZwNvRnH3PcRqHXeq3KiZ/e57omTJ+SUljEks8JQ6E/tf7GfvdBYYK6PXuuiv/xWnCj53p1w3sBgV0Jmv44q/O0rwl7Y9J46gmvc7mu+k1C9T+5NQe+9TH9/Y5CERr+u3zjL1vAavp773dDvC7sn2rwfu7uxl73wJOZ2+NXPmFJ+3NVcFC2TrwuQbc2XcfJ64qWrfF/XvZlc5zTzD0ob25yj3N5pfELP7MHJU/P0VSMzS/8yTBx88w9EenWH+2rPnVV0VsPF1jYmEx605JHUXmKcy/3Ef4V2cof+Q0OlKMfED28sSne5Q/cprct5T/QuDa0YgSiPG6ZftW9wb9k7vQnpKxL31U1mYWCvNh6aOn2fqyHm4z669bkIBJ+LEzjP/OQl8fV//0VD+Iszu/G98323/u3e9W/vwUrQOa9FDU/+z17J7T75jvnwEAzj/d2x//ifcUwbx/uAfv7+5m63tnKf296BV3/mGG/2CBynJG7UrOyldm5B79uVh9doBOLPmXP7O/n4KPn6E7UdT8TAoj5O7+2tUpu9DB6iWoXRA7YuOp5oYxdD95b78We1d29Wg8ZG+wj1oHFWMPZX0nLHv0CaxjaRwyOE1Dbzxn+lQLlCUezmkcCpg+04PjT2X7af9rp0EXR1avVrSg+J0Fus/q0J4y7LzwJMN/sED1T0/19TJI3U3jJtUPHG3Mij1mnl0nGlP9mp3t2zTRuO3P9eqX5ow+2sP/27s58nMLNI/A6l0OM2+Z759lyURC7bw4R/7f783nQPZkAGMbyEAGMpCBDGQgAxnIQAbyRSlfsLPTXpMwT/W8w+Vr4ze8txt9dv9tL8K7y5y18YpZVrdqVJ5wUT2Nbkl/E+Vn1C5AdqVMZyYn2g74bHniA8/+397T9Ns/Nyp6808ukAXC8GEPdemNZ30e/okHkv/weiMfWACrbmjQ9tly9qGD3PLDN8JNdqMhn0+uZye6XtZ/YJbWAd3nXAfYfLmM5W6EJjgXEF6SYunx9y7cEDE4+CvzbL58lspVhf83d/efE6S547m3ncTp5vh/czfnf12io7mhz+6VfpWM727viZHHcrpjGv9sSPW+gNKqZXpBoES7kQTghojfyBO5QIX+/p4bIqCjjxdN0S7l1J743BRc5YrCbe7B3cK1osfLpouOIdiSprH+X9/NxAM5pauG8B8/U9xnSu1i3s+mgbCggBQ0uh1LFmi87b3fCzav+3tjN/UN06cSwlUpxJ9++zyVpYybfnqBcMX0o0L/O7m+Ye2utL79JJsvnyXYtP1eQKP/7hFc11Mmd/icyGRcg1t+cG9+p+5J+lEe2ItiTf7WfD8KblY8kq+5E6deNJdt37jWdiNmnx0R25Xa487e9ROBCZUr0Q2fCTYg2/H697IbAfyPJPMU3XGZe6dn2f9JhTPTYex9woi08YzPvy+SL3nyDf82vQxvU7Pxiln2v2meuO3RmVTUzsnDlVfSz7nG58vMXv/a2O8u9IuMPzsrDXvNTff9hvRJul7CdUvvv+3t2d1o+PXQkf9IdqGU/9+SzFU3ZF76r3uf+9nrI+AT90szQdjLDKvMknzNnQB0x2WMg4+fKdZ0Qv6lz8Dt2BueId/wCTbAq1vScK9H0vU9SNKvejZxDbpjGuveeATtwkGzr3zW59zvZ4//fyS7974LSeT4HrTv+szjrvhbBrdNH2rYPriXcdzts5J/2TNv+E7Uddn/pvl+k2TY22sj836/MWHlWk5wxevvv10GysqiPG940aO0Ks0rd1mWWt9+kvH3LnDLq05z4U2zpGXLrd9/Bn/H9rMh+bqksoPtAua0vscK2Xr+iT5i4bNl5teL6PIrbtQHR39GCDp2RaVSuL4ruxn+nReepPmdJ/nfyS4DGMhcXN9vbuhCTvy1dxF/7V0cesPe5w69QTJm+ro+w2OPJP2M3a6YjhRv3/qyG5ECADtHTR9SDZJtqzziM3mfnPvhx85QvibnWfJfn031oiatWNprZQ6/boGkrIlrCrep8BpCWnC97EIggX6fvGB9T4dlwS5rqyL9LHNm/L0LTLxn4QY9PHxO7mvl1XOEjwY3oB82nuLwn5Xx9y701/zus3W/5Tj7fmMetSrrpPTR0zf0zNqV7rdIprNvC6SWS79049owPUvvK0Qnd54je2njaYbGEY0ppf1mniAsuu4/3ENn0iPcysm+Qvbzru21S0izu5+eeMdJmt9xUhrqInp591wsXxMm0HB1b4wn3n2j3nQbBWnVNUV5de8+wnXJuPmNvSyNVxcmUacjZE3d6QCnrRh+XPWRIZx5iJEHPw9kqJC82OOdA9ehEpYDxt63sNcg+PNI+Zolfs6dhB87Q/Ux2avJg8PS2LTIkHt1GDq79x2V7fVjhIL4YxVWf2iO9oGin966y9j7FvrzN5DPlf+3qKfLf3Ga1tEM+1lnentGsfaDc/2aneTLnkw8JB8a/50F0qZLNGYZv0+jrLBSmGWfnduE2SdY1xBeR0tbQCxstLfo1n9AKHiv37C7DCu7svaDcyz9xBxJWaBOQ/8U4m8YVu8UatXL3ypsLLv49rVXzbH2qjlWfnSO9e+fZeXV0igvXHQwPT6vUq+/eBa3qTj7nuP9GhwQetDr5fp/R/vkEN39/JXXPpmVV8/ROgjdyRz/r+/u0wxHBeXgrsJJqhZ/S9iTdhuqrbx6jiu/II0Gx353gfqz5YTYvsXIc/yosHjoqYjmQYfWt5/Eq2uuvG6O3ljOzi1y2O0c9ai/eJasYFZr7TPSBLRmaT6z14f57bzw5OcYj+2vlWfZdUCAPtwEhMIYoFdTlFY/13gYPh/j71jctry320nbaQnuOxrbM6Z6VS101YW48w9T+5NTNyi33aZxuVHkjij3XTpzEAdhV3a/F41bOpMOo7+/QHk5J37OnQQfP8PKjwil8fXOSDJ3owG+K0Mf22O/anzTHmZ47HcXSMuK0jVJb289xfYhJAC1i8Lis2vcrf3gHN3p/Aa43bX/4rDyI3PotGDRKljz6t892z/US8uKleMewYbi/K+f7FMe79Kh3/TThSH+7s9vXCfXOa5uw1J/8Sytq7Ub4HOmZ/HX9/bibkPM/4yUVlNazz9B+SOnufZfLXHd5+x7jpMGCnug+x9fAND3PEZvWli5rr1mDu/a/83ef4dJdlX33vhn75Mqd5zunqiRNCOhLCTNTHcTDSYJuASTkw0iZ4SxTbgG25jgIAE2JpqLMWAMNuHFYLARtq9x94wCQQmFkSZ0zpWrTtr7/WNVVc9IAiPe5/29P1/3ep5+pqe6qs45O6y991rf9f16BGWoPETaY/3c+28Mil86TPik09lp/JrtHQiWX/+LPcPGr9//kBgX1f02Yf9fm/nF90an1QXFBacXNFh7ufx7KhzkVOiY27K4192E/sGP8WvpaUGa0lGpreky9Z0633qfv+4mhm5PcSKBW51qcV7RevrB06A1XUse87MX8r7j94eceP90I62nHcRtdub/9bfc7z2nWuFkV3xUxnh2aXOedqGy+t/lfs0VDwFAVTxWXzVx2jjKrGhaTzuIcRXRQMry6wQ+FZ3don4G2P6YoJpicwn1XUJFrAzU9hqhz35IndVXTvTu+66PHZQAh5FgU1BOKJ7sUP4nXZilS2vQIe7bbIfmqPMzgxvdzW2XXbDUgXLO/fbmc6y/bOK0gBbQqz2wjjoN0gwieXDqWFh6w2RPdDMqCnV58xmyblfO0ixd7uF/5wYRnezsGaJHXMD6yyaI+mTzX3nhOBv7PTZ+Q56j+oJxGs86hI4FAnvXXxxk4erT57Bftj12zPJLJpj77UnaQ+Ljl183ydxvT6L//Ue0n3qQ5SsCamcZjGfZdtjhrr+8gvULOkxxJaHnXpwQRiyQPcns2yd7+4+T7xHq//oe0xsDrRHL/NsmqZ+VkhSEMbAbgCy/eILFN02SWzbM/Y6IQlb2ytrstK2IYj7hClZfJfuQ/qMpK6+eIHnM5cS/ennvGiuvnsA4m/uL9lMOcuL3JmmOuL2aQu97N5H6mtVXTTDSOT9153bXuv596UAnGHXdTZz4/QlWHro599deMcHKq4V9tSuH4NUMJ98j9MfGgbTuUtute8FQt9UVLNbUd2hWLsmwcPUk9R0ux/9wAhMIFfPqxRIN77tLU/zbw7RGwDzqoay9Qtop/tXLRXIAYShrPf0glReOM/+2yV59LmzKf8RFCdJ0beDOiMW3TBJsnBLgtjD2r6u4TZE1CDZisitSuzz06WmcluzTupD1B7KuBIHpiOcCDNyqevOnOz5ODZRGRc3wJ6dpjnidNrLc/dnLSQPL2IemcEMrAr77DKuH0l7fZOecXr/d/eFxNi7YfL5uYMQqaDzrEOV9PvVnbB54t2zTtmBsW7ZlW7ZlW7ZlW7ZlW7ZlW/Z/pClr75ufeWCrVqv09fWx/63vo1AJaOwSUchTdSfWXzZBYS6m/Z1/5nqu4+wXXM2ulW20tnmkgaK+U9F/j6H4JSmE7DsKzTFF8aTpwSlOPmM3d331Wg7yWEpqgPZTD96vCPLBWO2546fBqhq/dui0Ar348Vf0IBbtpxx8QHhD9z1Lj93JLd/7cO/eurb0q7u45Z8/dL/Xf5ZV7QbXcx0HeSzRq69k+BPTp127/pxxVGpPu8/1l04QVM1pr/Xu71cvx/veTSK4FmiMx2kFmsuvn3zACGv5xRO4ocWrpwTfvqF3Xxc97k1kt+1+QFjPsfdNcOY7OoVzb5wkPj7DHd+49gGfPXrigfsxYD3QPXRhUa2nHewV9p98zyR73jNF+iuX4fzLD4kffwW1nR6D/2v6tPa77zV/3t/ua/ft7/DKAwTfvkFIFjpQgvDKA7SGXfRfffvnfu/aw3bwox98BOAB3xM+6QDBP95A8tjLT0tJ/ywLn3zgAeFIv6j9rHZoPvPQAzJ9/azX/59c8+f1ReWF4z1YUvspB4m++d37vbf7+Qs4wG3cwEEeS/PNTya7Jv6i/uxD+NW011f39R3dedtt+59nlReOk11L8b9zA8uvm8R4Ame9548nOPttMj7v/cAEY9ebXjvVn30I4wpJwdIbJgkHBabQhfctvXGS0Y9MsfSGSUb/7PT5Fz/+CtJA0xoU1saZd00yemOM/50bqD1vXCC+nYTE4GeEICDsU/TdG/eed+M3JgRu27G1qyYoLCYE39qcy107yGPxnv4E4HTyjMqLxk/zFfe1U/1v8pjLcb+/OXbNwy9F/+DHvf+nj74M519Pz8isvmqC4U9MU3/OeI/04T+zbr+d6psf6HrNZxyS4v6nHyQsOfR/bproCVeQ5EWfo/KicVQK+YWIcNB7wPHdnfM/y7rztfFrh4iKmtKJEOdffkj58lFuvPGjDzi2yy8Rce2ufznVx/0/te4zd+2+c6w75rrWfspBkpzutX33nu7btl2rPW/8fhmb+rMPUfjKEcInHxDh6wGHoHo6UcXaVRMM/eV0r72qzx8/bf2IH38FTpjSHvTJfe3I/cbKzNN2c+fXZe4GT3n8L+z77tsev4idOo7jX70ctHrAtnhQ3/kL+vXW0w/2SCF+lp0650793Tziob3M4i9i3X3BL2rdtfbn2eLjd3Hrdzf3Ol3f+kBz/8FcozvGHsiazzyESu1pfgtg+Vd2cvP3ZT9mXnJlb47dd06svGaih2hIH30ZTjuBwzf3hMhLx9pgLNbVeAtlwjMGZQzfZ/05i/O5F4FZnrom/bx9xs8an915+p/53/ta41mH8MvJz+3XxMb8K9+gUqlQKpV+4e/+P90eBOhBbOCuFCcweE3FxnmKU6t28ksJ/ndvpIv0H/riT/DUAF0U8dq14zTqmugVE+TnFMa1FGYsqSfqr1Fek8ZzALR+9UKc/l3k//4Iq6+cYPiT06y/bOJ+GPdTN8j3tVPfP/uOSUrHhK55/aUTPUrYsM+h/JoJ+u+OehvfxTdLmrn0xcMsv26SkY9OkT76MrLfk81D/UkXUb94DyoRJjjnR8IW1XrcRTj9O3sMI13rTuSFqyfZfs0U7cdcCN+/jvXnX8LeT8h9RCWNevIBWoMu/X89TXjlAUkDB4rSTEwaCHyw/dSDNIcdMmURBB35iymc2FB7nmyGhj8x3VPzXX3lBNk1Q//RmMoLx1GW3jP13Stp3cKXD9N8xiGBLW3Mwv91HZUzHUZub3P8by+m+M952kNCb9x62kFKx+SZFt80SX7RsDiyme7uLqT1Zx9CpwKT6U72xTdN4jXs/eo8vJah/JIJrOa0jVv/nYbmMw9R3e3QVzqITixBzYji9R0n4H9fx/pzL6G9bRfZNVGfDzZSWtE8fO86Gk+8CDe38+cuhN3+7jrs4Ns3MPOuSQbvSPE7zzhwd0z/56apPsDnT13gvB9s1qnFE+cT9e8iKjlYBUElpTnqkj7zEE5oSK88AEoYaCovHMc6isxGStincSKICkpU7TvXSDOa1JckrNdIWbvAp3gypbHdud8htjvWokdeAP/7OhpPuojSd2aZf9sk234U/qcHmvjxV5D6+gEP/V2LnnAFaUb35t3iWyYpzBn4238EoPq0iwniMcrZRfj761h6xSWYaCdBJSX7jeuZf9skO/54qnfgWb3YxQ0vgn/a3JzPvn2S0vu+BUDtMfvh+zdQf9JFDB2NaQ84hFceYOUyTX7WIdgmC0aXAr5r3j/dKAeHvCLg/tbd6K69YqJXtwObdTpA76Cz+qqJHla/e8gwnuqx8t33MAOb0K/CgkCLTj1Qev90Ix4QP7fDMNY56AD322zCJvtf+cUTdMtvTp0vIMxXzWceEijRP/zT/b6jNeiQXU97PrNbs7P82knB1ftKWAhdyJRToqJDa1CTQeZIbbdLIX+Q+g6H/qMRrW0eRTYP5s6//pClN06SW5L5mPqK/JI8e9inKEDv0FN9/riIXbaEAj/41g0svHVSaNNrlurLJ+g/GvYw6O51N1E+J0u+7wBx3iHOKoqzAtvNfv16skhwpbLXJb9sxMcdizGeMGkFv3IZG78+QXYtlUPL3xym8qJxiifC09aX7FraG9err5qQ53z6QaKCZuCz0zSedYg8YDq1RmsvvATYcVof9X9OfLAbWlbfPsmu90/1nnv+NydJM1A8aWltUxTmJPi39vIJhj49zdpVE1hH4GVrV03gtWzve+8LkQaoPeVi+IfrCB99AcsX7SWzbgQWZ4VRrO8Lh6m+YJzoiQdoDTkEFUP1+eMoA+3ndtaMT06z8NZJ/LIwF5564AmvPEDhK0dIHns5YUmENvu+cJj6c8bZeNNkry6ny5ZVOcuHvRM9quTGsw711sPy2Rl0Ajlg7YIMpWIHgjXg0PdX3+49U/CtG6i8aJzCXNTbGIdXHqA54pJfTIgL+n5rrHnEQzGexv3+Tadt8ttPPYjTSlm7IGDwzhisJc1qWp1n9L53Exu/MYHqHFChQ+k/5KBT25sfbsvSf2+byt4McV4xcDQi9TVRSRNnRdy8u/51/Vr0hCtoDbv0feFwb45U97iEnWt1N7prV02QXTc0RjVB1eLXjBxSs0oOmVceIOxzyK7EVDsH58qLxoWevHXKvPUUysihIHnsZgA0+/XrWbtKgqXdQ2v3MLn28gn675EDfHPUh05wuPqCcVJP9eoQQQ5PYXEZkJodP9iB00rZ+I0JUh/6/CtojHm9oEM44KJSi9c0qERopsOiJtc5gFu96eu8DmSzu2dbfPMkOhZfnPvqEarPHyeLHBZ1aEFD5hQf1z3olF8yge6MpXjifFQ4yLaPTWMe9VD0v/0If3aD1r5hvMlLyC7HpBlHRIhHAvLzIenRYzQPjvKfHRE2nnwOfOsGak+5mNK3Zlh+vfibbrt2g+pu63Sm0e7YCDYs6y+dIL+cCMvdckpjVPZ1UUHjtexpwaFTA8fhoEe1E1zoWvspB0kzCrdpqAwn8Fff+E+e4L+fbcHYtmzLtmzLtmzLtmzLtmzLtuz/SHvQh53abqcHpQrWRdNh/aUTvSL+1tMOUr9SiqLDX5Giw9VXTdB62kFy83I5HUNjl8UJobFTYV3h3W8PKVSnjqxb4Lr6qgmMK78Pfmaaxq8d6hVXll88QXvAuR+7SO154yy+eRK/JlmDtask01HfrWn82iFqe1XvXmt7HAoLKe0hj7WrpBBv7ENThH2K8MoDFOeSHmNNV8zSbxhyi5bSyZTckiX7z1L46rQ3T/FdNjWgl57tFns2R6QYMPUEYlZ77jhxXhHndI+9KMlqkqxCJ1DZ61E7UyLK3ULC1FeM/MUUjWcdojmySbV0KjtUe1iRZBX+d25ApxCUU5ZfP0npREJcdGiOiThkklWk/mZ0pe+YROWcWwsMfXqa3JIl/tXLiQq6FwEf+/AUaxerns5L+OgLyPzD9Sy/dpLCV470IthdnSW3bXtF8/XnjPeilPm/O0IabEapu1oMqa/IffWIZM5CKSiPs5qwT/X0XHIrKSMfnaL4JdEOCgec3ljJf+eWXlbngdhnTrXgH2+g+Ux5z+73TvWihmMfnrofxKXydBkD7acc7GV1ms84JNm6jq2f79EedDAuNEc11T0uzVElxYyXeUQlh+aw2+lnicqFfRqvaXGbhsZ2Rfls3bvG8mXScF2R1OyKoT0gcyn+VYl83/tHE1ReNE55n8Pc70wS9nXHmJJMW8xpqe+VV08QP/6KXuHvqRmfzD9cz9IbJznx+x1yjMdfwfLrpPBy+XWT+N+9kSSre8XPtbNSovxmhi8JFGlW0//3N3fuQbIF3Yh5a8z0Ilwrr55AR/REW7tWmLXUnixt3dXPAdjYJ21R3ueRn1X4VXs/GMDaCzYLV4NySnZdvrvbx9252c3qdAWIH8i6jIXDn7g/DOm+WktAjwyhS64Cm1otD5RVczrsY1FR+nP5dZOnzeFTrf3Ug70I5gNF+bv2syBAxbmY7Deu710r99UjwqxWNqSeOo2IQ8eScRn5i6nTmNEy37ye3LIhyTnoxApZzOgmQKCrR6NTyfSD6Bd1BRlTT+aL+CODdTbZ45SR+RBUUkrHI4yvaQ17RCVXxForkgEqfPnwaRFn8/BLe78XFlOUseSXUpKcRse21+9997ZxW3IfdvISmqMa/e8/onQyof6ccQY/M027f5OAY/gT07jX3USS0bgdtsUuW1xXZ8dpSzF8EogYZfz4KyRLvluxeokiP2+pPU8y9HO/LRnQ3e+VbEhm1VI9Q/qiMJdQfolkg3prQE4yh6uvmmDtFRNU97jUd8j9Lb9uUuCWHdcf/Ott9B+NCcqG3NdES8eJ5Nm747TvC4cJ+yWrVfxb+Rn+pGShvLpkdU5dt4BeQbp73U2U/uZwz58XvnyYgaPxaeOw/pxxsquGob+cJliXrFt37EdFh8J80htjIx+doj3gkPnm9T1ymq6tvVz0YlYuyVB73jjV50uh+6mZzNVXTVB54ThpoJh51yStUZ/mqPiG5pjX2yPEOU1tt09cgvaggxMaVi9wcduG9lMPyrpWksz6/G8KUVF5n0vpZEh7UBNeeYChn7ZxIkvqaawD/ffGpIH0W+pLVmfxLZPUdkvf6ETGfFx0SH0lGbqq7CNSH+IcPb8bPeEKwkFFbZdDftnghJbqbve0zHrlLA+vZdg4J+hpCvZ9/jDVjs5d/u+PUN8hWdju3Havu4n6sw/R7nNEjLIhwtXzvzVJa9Dt9VucV73smRPJnK+8aJzmNn0ae+zayyeIS26PoMirGRqj4gPinMJtS7Y6yUrfrD/ER6WWwleO0Bp0Mb4IzutEUCxuSzKa0ROuYPn1kywdkL7rPl84KDp3teeOn6Z/lnqKqM8h+NYNpxFD1ToZ8nSTjBC3maBime9JVsZxevQYtV0uauonGF+TnWtQ3xGQXY0p7xeyhO6c7Jq54Ezua12CgtSXvtSxZeViuXjymMup73BoPOsQYb/D+ktl/9v4tUNEJUX0hCsIaileS/Y1q1ekAi0tqB45Csj+dukNm+Qb4ZMO0B7QvbW29tzxHsnWyqUujRGHpYPeA+pObtkvcdhp7rCcfM8ki49NBDr0rRtojSjinGLmcQ4LD3MIauK81i4UBqrGDsXcozWNC0KsCysHU5KdIZX9wpySW07Z9b4p+o6nPbrPxnZNY9RBpVA7W5g/QCZ25UyXk787uYnR3Ht67y5OyuZq7SJN2N/ZbLc2KUHDnRF3feoAlbNcWqOW1YtcVi5XFGfjnrBTULFUzvKo7XQpzKecfGLQEzn0//dtPSrX9qBi7o2dQ9C/30b+745QeeE49V0dNfdT2HAG7pCJpzqsWq3dCc3tlsVHWNYuS5l/jGX4lhbHvnQxK5dpyo9uU9nXYbIbioUVraaong0rlyvu+sQBNvY7VM9wWHikob4HTjxFsfZQw8y7JvFq0BjTHP/bi1l4QszJJ2oaOy2zj9UsPAyiK+qsPDxh8eGGtcmY7PeEUS37z7cy//AcOpY6haio8L53E0sPMz0Grnv/aAIdK7xGVwG+c8joqkx3LCrI68OfmO7hZrvp2a6D8uq259C6B0PjCQPW9ms24UH9fz3do0wFyHxf7rfL8FP64uFenQPQO+Tm//4IK6+eOE3UDuTA0nX6ua8eofnMQxx73+mL/fpLJzh6zfhpivRdtrkua05tlyw0vftat6xfIJud0Y9MEfUr3CasXqoJz2mxfp7uMcxEJUX5HM3KZbB6kcPSQYfsqmXwDnGAJ35/AqcN6w9x0DGsXOpTOVtTO1OYZLp21m9N09qmya5aCrOGZgdeWPq/bqbwFRH6O5Wiu7ldYTzV20B02cZWLpaBHZQtKt2kDR756BRrV030GOFOZera/4YjNMc2/z/45Z+ctrHf8Rc3E+dVr/2DVUnTg1C1h8OW+o7TEbX9fz1N8Vsy37rCtM1RTWOX7R30uu1XedE45RdPMPOb0kdDX/wJy6+bZO3lE/jfuaEXhOje06mQtaFPifjb8usme5vi6gvGmfvtSWbeOUl7+P40oqcezLsHk7WrJtj49YlebVDf5w/3NjSnti9sMiKtv3SCZofSOeyTw+PIR6eonOX17uNU624848cLW+Ds2zvMTK+RYNPiWyZ74/iBLOx3e/d26vP7VUP/Xwt8qdZZ6BcP+FT2yvvnHpEh+McbcE6hA169yKW8T/zu4Geme8869ztyT0mHfrc16PRqNzZ+fYL2oKa8zxFI18Pl33v/SJgjvZolu2Ion+3hfe8mars8/FqK1dJ3YZ+m+oJxll83SeNZh1i5VMCJ84/M9Z559QKXtfNc8n93hNpuh6UDHtXOJnTtQuEBNp7CBA6NnYZ7PzDB+nneZk1LhwVz9h2TrL5qgpXXTJBZjXvjvrnNYfEtkz3Gxf6/F2HocFAR9ivmHuHJhqbfkJ9TNHYoFidFIFAnQm8+/7ZJ6jsVK4+O2PnBKe7+80OceLal/3PTLB+Qjd78b0qd14nfm6R2JlTPQpiqXPGbIx+dor7HUr1MKJSTifNZuVTGzdxvT3LvByZw27YnOJ1kNe2nHmTp4ZtwoZXXTFB9/jjVsyHTCQj4NRGUnn2H9GNXSuHE701Sff44ze1yqFt7xQTBt25g7XyXuz8sDGUb52haw5qVV08w/4gc9/zpOEevlfe2+zXr53kc/dA4x987wdFrx8ktJ6SPvoy5X7WUnyntufyyS8itphx/rxzAlg6JsOn6eQ4z75xk8aBHu0+ooVcvg6VxWdeTQPwtyPsbnYDi6qUi1hhsQHWvZuOcgGjAMP9wzdIBh4WHB0R9sPxQl+YOQ+lEQpqBe5/l0dpmCb59AysXZ2gPaVYeGhDnFQsTHk5oKO93qewXxtRwQMbHyd+dpD2gaGzXrJ/rsHGBHDL0v/+I5phQG9fOhLVLBL5f3euJ+K4nY3z5gNAir75qgvI+h5O/K/2wfq5L7WzT87Nzvy1MoQuTDnf/2SGSnCKoWdYuVMy8c5Kj14yzfIVm/WLL4oRLda9m/VyX9rBl9aGWhUmHk++epDVmuedPx7nr01eweFAz/0gtotbFzbk+865J1g4kLF+uqeyT67cHHZqjivL+gMp5KY0dct2uOPrYh6fYOMfh+HsnCPsVSVazfr6ieqaivksz80QpXaic6WEV6FBozcvndPzSLQavZqmdoanu1Sw+OuXkuyWQGucUR68Zp9q5l/XnXUJjh2bxzSJmPP9aGUvqJ3dhszIn/O/cgHnUQ2k9/aDQQz/6MrKzNdrbcyLCPewJNPlRD2XX+2WP0ZU+0Lcd475W+t7dMtbOtjTHFLllg9sU337vc+VQvHKpZuEJMc0x2f+W9zm4TVi6wmfmaSkb52iOfWCCc17bCQKOWup7LJX9sNSJIYz+mdT1VPa6VM9wCfsUq4dSvKZl8ZGW2cdKW/gVqJyfEqzD0Gd++Rr3/5NtC8a2ZVu2ZVu2ZVu2ZVu2ZVu2Zf+v2sc+9jEuvvhiSqUSpVKJiYkJ/vEf//HnfuYrX/kKD3nIQ8hkMlx00UV8+9vf/rnvfyB70IeddCCmvTMme8KnuUOiQa0xw+BnpgnWNFbbnqhoUkhZu0SR7GsxdM4aVERnx99wwIJfUVQf0WbmyRIVWTvfwWl19Bk+8xNG/mKK9UvlGnvec4pAWQ6ML58Z+Ow0wcbpMBSbkc84LUXQEXBMsuBVJQuUu8dn23+4NMcs6VhIa0eCV1GsXuTjtqU4euMhAi9KM7DwMIfCCTj5Tjnp155yMeuXGuYfoYgL9ITjQAoy+76wmWHoZjOWXzfZy1rUzu5oJGQT4j6DdS3+moPT1Bx9vkeynKV4HMyaT/G4fM/OXeucfI8UdqdntXDrCqfuoBOJxhWOu+TmFZlld1N7YZelvj8mXs7irPpY15JZVTih/HA0D9qCb6Ctexmq1uMuJByyjF4fMnqj6RVfn/Pa69GhQO+SYkp7V9SLhJ4qpHWq1kI3Grz82sleVmjtqgmSjGLjXBl+9d2a8n7NsfdJhPquTxygsl9EGmvPG2e1kx5uP/WgaC88Q+5z9cWX0Hr6QZYObQ7j3D8JpHDlJZdQnEtYf+kE8781SZJT1HY7vczNvR+YYO0Cl+XLhPcfYPlyTX528znqzz5Efikh2FOnurdzDSVwEOMpwn6X4U9MM/pnU6dlAOK8Yu87p3FCiYiGg5bGLsved07jZxLycxY6Q7axx6BSGL0e0qxkJFvDqgfByy4pVAqtc0PigmXHH03R3hHjbyhWDpleofTdHx6n/2hC+VxLY7voWAEsXSWQrtm3T7Lt49PMvFP64Ix3TxF86wbaT5EQUjcTeWrmrCv2V3veOKuvlILILpxr6FPTp2n2dKNhD2SzV19EbsVswjkLnfneyXDE/SlDX/jJz/z84DdFYa04m2I6c3v0I1M0dlmSnLyn/6+nceub42Dko1OUzxXI2vyjNrNG3Yh1/dmHmH+bwFZO/P4EQdn0IEJrFyrSjNxn4wzJVK5dNcFdHz94mv5Ra1izdqEnUNmDCQN/Nc38b072IL3d7O/x907Q2HF6hmjxzZMENUNrm7yeXTcUZ+Va7WG450/HWXy44Z4/lbaPnnAFUZ9E9U8+TuZDdnXT7xW/dJj6GYZjH5j4mSQUQVlgZadCI1pPO4iODfXnCJFDVLL0feEw1hG45NEPjTNwp2HjNyZYGe8IVzZSiicNyoi22uKbJhn47DQnf3eS5o6U2nPH0bHF/84NrE7INStnuvQfbTH6Z1Ps+OMpZt8x2fNtIzdInw59WrIfwYZl+bWTVM+G+naXjXMcgRyfoVi7SNEcs5TPdnrtq1JYOqCZfbRLXJQ2mf+tSVojlrhkqF4csXJphtY2RXmfT//nplk8mGHf1YcxvmXs2s2x213TnLZkoyv7LUnBIeyTsdXapsgvGKr7OhnOR8qasP1Pp6ica9n7P6cpX5CgE4XbsLRHTU94WsdCGrPjj6foP5pS+rFkpgrHHM552Y0sv34Sr6rIz6ieGLdKRcvjzLdPE5cM9SsE07n+0gnS0Qi1Kt+xMOHQOCdicdyhdMJw1u9Mk/nm9bR2Jhz90Djr5zk4rRTdludo7FR4DVh9qMJtqM0C8fM0a+e7RBc2WX/ZBOGVB1h+/SQqhbBf0R5L2HiIprJPfMrOD06x/02HSfKWuGQFEXGOpfmQEIzCZA21vcK6Wjs7xa0p9r5rGr+s8b9zAycfH1C606W+1/aet3KGS3ZJ4bYsA7crSscMffcadv/hFP1HDeGQIhyyWAf8dU3puIzZLoFI6ZjpQbAKJwUlUDkvZeSHMYWFFK+m0ZHijN+dpnjc0tod47bA391g5lc1Yb8ls+jgNkVHL7sqWYbckkXHljPePcXGPp+h2yL8DcXe/zmN05LMno6huQOcEAbvTMnP6B7r5J7fnyLNWNKsoXBS48QWtwnWFYTE/G9N4tYEem48EZx1m5tIkNLdisE7ZD7t/OAU+UVD6R4YOaJoD1u8Wkp2ReG2IFjXWNdSvEeyDDoW3168F/ruVpz5dnl2HSlKRxWD13sY31I6KkKo1pE9E0BuybJtyiXJW7z6ph/LrFvK51qcVoc8pwm5rx3h+HsnOPF7k+QXLPm5TnbiTFmTSscsjZ0GDMRZLQKsCvwq9N8l2VAQhMfQp6fpPyp6XNkZj/aeSFgp+xW7r0spCC+U6O9sE62a5qg6jXarPZyh8WuHmP/NSeo7A9bPdWk86xDOv/6Q5fEBrFaYRz2U6pkOS2+YZGNfhsW3TNJ8xiGS3M/eHjcesV/8RKjY+YEplLHU98ocOudVNzD2oSn2vmua4GRA3zHDnu+m7Pzgpmizrnj4FVn7uhn60j3g1RUqVYx2kjNdWGluxbDt49O0t1mcmmTL97/uCNa3DN2s0LEls+DQ3PGLC1r/f2W7du3iAx/4ADfddBM33ngjj3nMY3ja057Gbbfd9oDvn5qa4vnPfz5XXXUVP/rRj3j605/O05/+dG699dYHfP/Psgef2TEKf9kFC8FaBzM6K/8mOcvYYUv512Qz6pUdjG8xiWLjlmGcliLNWVSi0Ks+UZ/FOZaheKfH/NsmSTMWkzm9s/a//ggqUSy+eXOB7j9q8MuK2nPHBcc4dPpGwl9y8auWXe+fwgktrRFFdsnSGpUNSJKzDHx2GmXAOxmQnXNxIhi+JaK1zeK2oHSvQAfcpsVtKLZ9bJr+W2QzFFRTvIomu6RRKUTbNwWruhjlzIr8vwuTGvnoVE9wyt+Q73HmA/InHFSsiEYTzn7rYXZ8X/fgQ7l5h7DzbHMnhnBa8n35G3J4DcjNaVojcr/Fk4baXkt7R0xuURNsyOTJzHk4QyF+WeG0NE4I+RlxytFAyuARD2/FI7vgkg7Jc9S3O+RnFceeLl7jVDhOOChCgZlFl8ys3xO18utdUdC0xxwGm9DBTFnqnECYe4yrGL1JrmccKB235GcV9Z2anf+s0YlsWOo7NNklUXLv4um7gnGpTw9q07XaU2XsbfvcT6hvF6HQ1Kd36D3zHdPM/M9J+u7uqCvPWYr3Csba31CYU2i7Cl85wtIBj/ZcgaFb5F67yt65rx0huxrTfOYh1l4+gVff/Fx+UTaFuQXIrMG2mwy6O0RuK2Jc2TABDP1YFvPilw6jEnF2SdH2DozhAAzeGaNXfPZ8Txo7M++RXbVsO6J7sCmnpVg/z6X/ToXVp9xnR5VZyxrJ0E/T03D2XWy4c4rmGgij1NFrZNNe/NLhHsV8V7Du51n1aRef9v/iMYV7Sj1bbl6xcqnuMfN1x/t9rStO3JqQhSXOabyqJrNhWH/pBNt+aNjxx1M0xjo49ebpn/caiqFPTeNVVe++o5K0R+ErR8guW0b+fIrB2y1hv8bp1GVkVxRJ3pJbUIxMy70N/eU0Kj79Pp1QYLgAbsXt+agek1UHqujVFH3HTq9LSDN0aJHl87mvHunVg3TbZOhHDtv/Q1i7kryDV4PWkCazJt/bFRAN+xW1543jb2iCVfGL3XnQa8uHX8DChE/lRePEhc3Xo6LG/+6NrFyqyK6LXz357kkyqxD2a/a9+TALj0sY+Ow0Z305pfySCZYf6pNkFG4dWrsS8kuG8EkHGL4lFZ/Vp2iOambeOYmud3xdaJl9jMDN1l86gfGgfL7UVLYHNfkFQ/LYy2ltE5amNCuq6DqF3KJl6QqnB0UOyookB9nlbn9Zisfk9dK9MHxr0qsltBpy9/iygXPl/fHjr6B0QvrDbWz26cn3TPbWtMyaCENmVgTW0603LB03NLbrXrAi9Tc/f+r4UCm0RhT5GRF1rD9nHLdhqTxK5vDyFZq4KIcfq+HuPzvUY1YsX5wwfItM2MKMpXhCUX7xBHYgRi1mWLtQUTsTbKjRHdTwyA8NpZ/4OKHUBoZPOsDRa8YpHnXJz+hee+TmOmv2nMUJLZllqaNoD3TWtvXOc/5btsdkmmQgLhnSQJE76TJ6Q0JmTZFbsj1Bz+IxyC7KpssJFf2HfdmkzrpyKKnB0A81mVVF/Tnjsv488QCDt1laIxavIve17a9+ghNZRv9sir4vHCa/kFL6m8O9uqPSFw+jYzjzd6bJLOnT/G7XNs5V+GX5fdvHphm8M5E1tqil5mzB4tWkrzIbKQM/chm8I8E9UmT/m+TQ5DZlfhfudUkyisJCQulEuwfrGzga4f3TjT2/rlMYvSkiuyoHgsy6YWO/g70P321hFmGQ3JBaQycWH9QdR34VSjMJI38+Rf9fT+NEAiUsnjT0H41Oo63OLsf4NfmegZ/KgCzOGApzhu3TIaOHLV7D4jQFPgeyDqh0c18SrHcO9p+cZscPRFjT+Irhm1OGb+nC7iXwqNuKzJpcx4ktYb8is6IJ1hRJzvaEqQdvl/f4NQnkNZ9xiIG7UwozUu+8/02HcZpaoMqzKX33JuSWU4HLN+6/Wd/+p1PoBM656kZKXzzM4E/jHqQX5GDmNhQn3zNJXLJkFjfnofEV+b8/gl8VVkOvAbWdItIZFxSVM130v/2IzKrFq1sK84kcbL92pFeL/UDW3e8oIzXBxlMM3twpXejAxSsvGifJG9r9itpuud+oT7H6qgn8DU1tXwrK0tqRMv+2STYushRmLaV7LVFe0f/X0wx9apr181VvH+U2FZk11YPol37qMvDZaaJ+8ZWjRwy/rLXbbarV6i/1U6lU7vdaGIYPeJ2nPvWpXHnllezfv59zzjmHP/zDP6RQKHD48ANTcH/4wx/miU98Im9729s477zz+IM/+AMuu+wy/vzP//xBPd+Dpp7esi3bsi3bsi3bsi3bsi3bsv/61m63OfOMAov3qbn+Ra1QKFCvnx55ePe738173vOen/u5NE35yle+QqPRYGJi4gHfMz09zdVXX33aa094whP4+te//qDu8UEfdvJ3e9CvGLwjRSfCNNMesiy/fhK3KaxqupNdUqnC39Ck7QCvohi8MyX1FUnGUtmv8CudDMaSwSpFOAT9d8A8Uqi49NDt5Gcdtk9LlOvujx4id9IRiEne0n+PpT3kUJg1PfHQxq8dwmkrjC9FmFaD28k+ZJcgHIKRHxlOvnuSnf8asf4Qn8y6FeaaEY/sisKrWcIBRX5OoqfGt8y+Y5JwZhYQgoLohbtwGy6FOUujUwRXe/LF1M/fTX7BUN9jGQHWz3PJ940T9mmGbk9oPe0gY5/8LicBHCFOGLhVk/pSgOmEUDgBrW0SgUkywi3fd5vL6EemOPb+Cdy6wMOifosTCYvK6sUSoRv+3w7NUVCppT0kbEBRPSeFp22NE1oa2xX5WSiccGjuUHhViEuW/imPRWD4tjbBzoT6bof8303TCdiIBs1PJXJQOGmJiwp3RvrG+/fbQA3gf/dGfDY1RbrR+9IXD/dgS/XnbArONZ51iKGfJqdFrBrPOsTed96f/aq/82/VbgDCGjfyL1Mc/4PNSVL85qbWSldLqct+BFLYue3HCZlvXt8TduyKtrmn6KB0xdyGb0nJffUIc1fulr5vpqxdNUFxLsH/zg2sv26S3HLK8Jd/wr3d+x9zJI0/Zxn92BT1Zx9i77umKb94gtyCpTiTsHa+R+1tkwzekbBysUv28VdQPA5Dn5Z7XXjrJAPqIIN3pKxe6HH226ZYfv0kxf6DBOuQXU2ZfYwms3GQxqjDth9bwJL6Ak8JTkq/NHYo1l82IXDMjs5T/dmSjdKxROwqLxpnxx9NcfLdk1gtEDeAM74tYctTBQhHPzJF7bnjuG3DykPdHrx06Y2TNNZm4fPXUfrGzXCK0Fp2LcXNGmY7miPGk0zU2ssnCCqG7f+mWHjFJfCp62g97kJK35vbHFPQK8pNfdj7zunTmM7WXjFBflHGZDfq2LWRm6QNdr1vqpfZGb7Z9nREBv5qmtbTDuK2DCMf3YwqjV0ruih+JSYqbZKfjBxW9H1hcyydqvnVjxTgn8oS5nXEmXZ+cOo0goKhT09z7P0T5L52hMrVp7Dt9Dk0XzJBbv50sebaGyZpDWrSQLLPXVHRU9mSil86jOpouTSfeYgkc1pT4P3gNrYN7yL7jevpO+X1vs8fpv2Ug+z8t5jmqEdxxlD828M9IcyN35ggmFM93YjMUw/S/7nrWbh6ktLJFPUTh/I+RRoodl8XsvMDR2g/5SDWkWL+3X94mOiJByjMp+SXFI0R0RLZ83vSj6V7m8w8Po/XsLjX3cTIdeK3nRYU1gzZ1Y4e2LyivtPDqyoyG4ZgQ6LVlReOY1yJTK++Upj10kCRXTPoWJFds9T2yLNm1sE4ivoOD68hrFP5+U1tqj3vmWL5tZv9kVuS6HV1j4PXsKSPvgyrJRM99oOU+c77ms84xNr5Dme/bYrVV02w4/uGjXMlS5yft7ihpTWo2PbxabymFOz33wnZtYTsN4TBsniPjLP8PAzcocl+/XBPjHb59UKUMfpPHs1tivyiwXgQLnnUqjIG1s53yJc6EK5hTZxXlO5VYAXOHKwp5h7lYzzLXZ+5gpF/EZKRwpyhcpam7/OHWXqj6OYsvHUSpy1w5MaIy44/kefSsaU1Itlgc9EkaSBQp2PvnyDYUDgtYdMrnAC/blEnFe2hzbHW2Kloj6bU9kNmCeYe6aIMZJcVte57nngRxVXpm8o+jdOG3NAEze2KzKqsd8G6pfX0gxRPGrympTmiCZ98gJWLPbbdHMsaXt+EypaOR2QXXMJ+S/uVE7SHhAE2ffRlNEcc0oyieoZLYc4w9zuToo22YSmdTEhymiRQxHlN5cwM0cQkuQVLY4fCjE9SOiZkAk4b2oMuSVYYSo2rGL41obLXZeFqgQH235sQlAWJ0R1/je2a6KoJ/KrFtDqsfPs8nMdfQdjn4Fc6jHodYovoVybY+07RewpLmrVLLPVdk+QWDXFR2ObKZ7t4DYfaboc0ENjUyqsnmP/NSXQifjLJatpDwmapE5j/zUmCiiXJyNxZvcRh+GbZ+BbnYqInHmDsesNKJ8OpI0vfvaKnFfYp8gugjOHoNeP036kY+WFCY0yysfXtDk5oUQm0+zStq0RnsfGsQzRGRfup7/OH2XjnJMO3iu6MXzOgFMG6zH+nLVBiZSWbEheUrDNA39dupvT1md44W3z8rs05fLKBhZ4/7enSjV8Mh0/ZK5ziyx9Ik+2+5v3oHrn2UUvtfIexa6cIXzoh43FUM/fbk0QDlrN/c5qT755k7Egs83w2Zfkyzd53CdLHqztkNgylL06x8poJmmMKHUFzu2WQjk7VrMI6kt3d83uidxjnumgqyQ47IXgdVtH1Xz/4oHV2oihicTnl2E1nUCo+OMBXtWY48/ITzMzMnCZiGgQ/uyVvueUWJiYmaLfbFAoFvva1r3H++ec/4HsXFxcZHR097bXR0VEWFxcf1H0+eDa280PUpRWWnhky+/QUt20YutXiVyxpYMkt2N7mJNoR9eA06UNrhFets3qxYuVREYWL12huNzQvbrH02JjlR8WMXm9Yv0ImWHbF0neHw44/mmLu0Zrs169n/+uOsPODUwQbwj6V+9oR+j5/uEelCcK8VZi1NHaKOJdfs5hHlqk8VrDO7dGUpQOavnsM6+f7FObl0Bb2SdrQbQgF59i1U7S2weCdEV5Nset9Uz3IFsA5r76euCAMOoW5Tgr5Wzez40+mTsMP7/ijKfo+f5jWqCXzzevJfuP6HmuUW1OM/PmULKj7U3b/4RRJHmr7UtwWNM6JyKyJaF7lIQkz75rkzLdPk2Ytoze02fvOaTIrSqiXj0E8Ggubz4CVhbUu9SPWRUSrdptebY1fE0hFOGCIi5Z4KCEqyd/UTXcy/zCHHRcvcuL3Jll6w6SIPB4T4bO1qyao71FU96WsXCSLdPjoCzbHyDPk0GAfdmmPcW3xzZP3q1uovHCc/N8dYe08OXM3fu1Qb7Nx958Ju9LsOyZPo0NduHqyB9HJfP9WWk8/iDLyveGTDvTozuMJmTiVF433YHiSura9w433TzeS+eb11J8j95j76pHegaxrqa+49wMTPWaw4F9uY+gvp3sCXyMfnaLwlSOnwYZ0IgeGTAfi1B7QhE86gPEE2tIalg3Ejj+eojXksPsPp/D+6UbctqX8Yqkx2v6nUz2I2c4PTrH4pklG/nyK7Deup7CQ4rZS+u5SOO10U9DvTE31TEXfsZjyPmnTsU/+pOfI/Zpl5TUTtIZk2nc35n2fP8zimyfZ83tTZJc2n33twqDXTtAR23v6QYp/e5jsN64/rY6uOJsy/PkHrrtJfcXaBT673j/F+ksnKM6mtMYMQ5+epvCVI6xerBj9lHw2+8/3x+EOfe2u3u/3fnCCyj65//I+h/puWOkwI9d3nz6+uv289IZNVfnSFw9T/NJhTr5nkvKLJ8h+4/oeJfapFKdJoGgPurRPYdnrXrdri2+aJHmMUH+XXzLRY6Hs1uyM/IVcc/HNk2TKmxGzlVdPcObbZcNSmJPPtJ8q7dr/uWmKswnH3zvRu/fSTEJ23bDjT6bwv3tjj250bFqca7deqjGqWX6dMLINfOV0gdWVl1zCxrlujy0NJCDRepoIIZb3SwHMymWKY++bIL8UC+PZoyKifsPiuOboNeNkvnk9C28VkUW/KsGrkR/F7L4uZP5hGaE979dUznKJC4q7/vIK/O/cwMa5LrmvHunBgOrPGae8X6OmfsKe90xR3ylte+wDIn5Y32uJikqUzM/wOXGlS+0MRXOniBSGA4r2oKLvCwKxvOsTAvtcv0DRGHEofukw65emVM50aOySmouoJHT9ykhAorxfYL1dn3j0Q+N4DUv7KQep71GsXSzr2vZrpnqMgCgJMnVhX1FRk/vaEXb/4RT3fnCC4U9Ms/JrLdwWxAVDUDOEfYrsuviC5UNQPRuao4rVi2SOFhZSgbQAmQ1L9RkSIe3WSo78+RRj107R3Kapn2FYGpcNXzgAcV+nnuO4ZfiWhKVHJziRHJZTX6iypRZA6ol2/CDlnJfdSG2vov+ekMo+zdDtKZUXCczu2Psm2P6nUzR2Kjb2eZTPk01me1Ax+Jlp3IZi/rcmGbyzA9Vdspz59mkGb0/wq5agktIaU6SeHDicUCBn9d2W3X8wRWbRof82affB2yzbfmRojdjePKju1R0RZs3ATw2ZFUtuNSG3KILUueVO3dkBh6VHpsw9Vmqrgm/dwK73Sx1ia7TDdvr0g/g1i/e9mxi6XT43/EmBqMUFi/OvP0THElD0q5a1ixX9d6eEw4b6GbB2odfxA5r83x9h28em2fmBKQb+alrqMH5/SgRgPzFN2gkueHVLkpcawo39LlGfwK7HPjxF5pvXU92riXOb83L0xjZpVqETS3NUMf8ol9E/k/Ugzms2zodgIyZ5zOXk5w19QgJGsJ4QFRX733RYGG2XYnRsKe9zcVuWNKMYvjmk/x7TOahKzU7pZIrXNBS+fJiRHwrba/9fTzNwNEElIrfQ9/nDDN5uWDqw6e9qu4R9sSuQnPmXW1m9VFE7QxOXpH60tU2z7+rD+DXLxn6pZw2qKUM/bTP0l9M0dqheANK4Askd+egUueWkI+BrWL7MZfAzsi4UvnyY9pDH4pul/i4ckDEYFRU7/njqNOrpLtV441mHyH13E362+Ig+Nn59oicfsvSGSY59YILmjiwnf3eSe/9oguXXT/ZqI8svnmD27ZPUnzPO4is3JQzua92anbWL6NWMrz+mLdC9RNbsM39nulfj6X/nBkwAcVZq1tZfJuLB4SCEJQlI9t8T0393SnOnYc8/yyEv/3dHiPolmNX/19Pc9fGDrJ3vsvEQLWyj4+s9mZbGDqn1HfyrX56NLV/45X6AHuFA9+fnHXbOPfdcfvzjH3PkyBFe85rX8Ou//uvcfvvtv/R9/yK2BWPbsi3bsi3bsi3bsi3bsi37b2wGi+H+dVP/2WcerPm+z759+wC4/PLLueGGG/jwhz/MJz7xifu9d2xsjKWlpdNeW1paYmxs7EFdU1lrf6E7rVar9PX1ccUz/gDPyYi2jZXUbBeClDzmctzv38Ts/9jNHd+4lnOe+RYKA7tEc0FB7UxD/51K0qcVS37J0O7X+HVJRRfmU5a9BY5+6RrOfuHVjITbqe9wGP2zKarPH6e1TTP6kSkW3zJJdkWgb6kP+aX0NBGulVdP9CKId/3FQYZuciifb8msaHZ+QKLLxhfRNr9i0TFU9inOeLdwmtd2i16JSqTI2C9b4pIivWuGn/7DtRzksYSvvRKnLYWJ5XCOo1+6hnOf/ha8s3ZTmE1ZvVRTOAFRvwIDaQAmsMJA15hh5mPXcsmj38i2f5tn7eUTRCWFE9GDn/QdSwn7RFh05KMS4dv4jQmMi4hPtizlfQ5x0bLjf0esXRD04HjGQ2AXvqL4t4eZ+Z+T9N9tqO3WUqhvwA0tmY2U2k6X4U9Os/SGSaqtWU586houetybyIztpnqmxrjCoFLfrdj9B3If9Q5cZumNk7g/PM6P/v0jXPLRl/Dqxx7n28sXcX5pgb//h4fBOQ3OG1viT/f+Pb83fyU/uHsftuVw7Kmf4rPVEdrG43+9/3/wynd8jS/NHyBwEupRwIUDC+wIypyfneMP77ySt+7/Z25t7eL26hirrQJnrf2Qv37+dYy97c0UDgxS/Kc8u15yL7dPn0UzvoeFd/0Fj/r0s8jt387OXJm7KiO8+6xv8tbbn0X4g2Ee8+wbuKs6Qn/Q4nhlkMdsv4vZdj8/WdqJ66RU7hjieY/7AdctnEPBj1iuFWgcXeTYWz/Frte+hfzwbjIH1uDbg3hNWH1cG/+rq9z11WsBuOCJbyY/tIs4q2iOKYozFqsFluiGlrCoiIuKsQ9NiWaPkv5qjGqKsyn1nQ5+TeAFbsvQHnDo/9w01eePExUVxZmEuKCpnOX0GF5qzxunNShzKcmC//Fvcz3XcdaLrybYuav3vo1fnwAFWCmSDyqW+k6N27QYT+E2LbUzAQN990iBd3E2pr7Do/wQGDucsnjIwS8rdn5wipO/O0l2WaAZ62aOY5+T8aPOOYNGeZZ7vnANlz7yjfRld5BkNRvnuuz4I3nusF9glUOfnmbuyt389FvXMvbON3Lh++ZFxPS2E9z8Lx/mAg5wGzew7zlX45+5C6clEVS/bvCrKcuX+6QBqB/PcNdXr+VL/7CNT+ZeRNFrk3NjAp2QdWL6vSYZHfO52w9yztgKvk6Yr/cRJRKlf+u53+P7G+fRSH12ZsqclV3hTw4/gU888q8omxx3tbfTTH0uzZ/gIn+B7zXO49/W9xMZl+3ZCgCXF0+w01vnLHedf6hfxGPyP+Xjy7/CefkFnlOSbMu755/I8fogMysD/MrZd/GnO/6FJ7/mjVz1x1/lvV97Npc98k7aicdA0OR4bZDjM9s4dO69DPpNzsisMdMe5HXb/oXX3v183n/2V3nBt17LUyZ+yDdveCiXX3gvi40S8zeXOfG2T/Z84v5nvYX80C7SQFE6mYj4oIXmmJaiZA+8qqU4m1Ld65JkIL9gCAeEMMBtCTzMeDKO00Aimn7dil/ZsOJPq+IrsstWoFADMs670IugmhJ864YeRGvt5RMoI0XGVsn7++9Jqe12yKzaHpFDGtDJVIvPjUoyVv2qpbJfM3RrSm2nI9mESAqovYahOezghjL/4rzcnxOLVlP1TOg7Kt8VbEjk2GuIf0xyCieyZNcMSaBErFhBUDXEOUW9PMdPv3ktY+94IwN2L24TWiNClBAOCaNV/1HDyuXgbwgjVjicChmHATUasuPLHksHHJKCRbcVSSklu+CS5KTIP85bzGiIXgo4+23TzL5d5ppftx2GLctGMs+dX72W8698M/7u3Z1VXTLIXhXyi3K/4aBi4K6E6hku9V2WYEPawm1J2w5/ovP9q5ahT033IK/hlQeI85qooGnsUpTuNYR9mjQjY0LHMnZ0JCQe6y+T/nRCyaT5NYtxFaknfeu2wW10/la1tIeVZKlOznL0y9dw6SPeiHrIGUR9QqKTWzZYBeX9moE7DfnFkI19GbympfQ3ApH0v3MDq6+coDAv+4DmMw+hjCX79espv2QCJ5Kx0BhzyK4ZmsOa4lxC+SyPNCNF/blFYexzW7Ju9h+Nifoc3LbBaVvq212y6yk6sqxd5OG05N6igiK/lLJ+vsvg7QntQYfGDinkV0mH1SynsEraq3RC4KJWCzy3dFzQEigYvCNmY7+H8aB0IiXOaZqjiqBiya10EC9fl+ernuH0SDP67kmFfdMKcc7KayYIKharhBCgMeow/Anp0yQrsLbFt0ziVTuQz3UhyFl7xQRDn5qm+YxDVPc6PZbC1tMkm+CEoH9yglu+92EeOvlGuOAMWUsQMofaboVXF+Ywr2HQiaUx6pJdS0WANIa+4yFx3mXjHBenLbp8VkmGNOxXbL9G7m3s2inKL5nAqg4rnBKyieoLxjGO+KFqQ/ZdF/35S0h37QWgUc1wvjnMP/7G/8W+51xNX24nffe0OPHkLPkZedaFxyUU7vCxWoR9u+PWbUuGzGklpFmX5ve+x/Vcx9Arn8PaJ7/M9oc+kYUffQeA3b/6Ama+90XOevHVnPX5k6y+Shhm04ygkgY/IzDdxg5NkoWBOw1JRvX6vHKm7DHjnGga7X7vVA8xk5/bhDE3n3GIOK8IyjJ+00CRWzHUdwg5ltu2nbEle9jsChRvr/If172HSqVyGqzsF9nfz9+565eCse04d/ZBXe++9pjHPIY9e/bw2c9+9n5/e+5zn0uz2eSb3/xm77XJyUkuvvhiPv7xj//C13jQh50z3vdevH2GZD6H6Y9R2mITjXIsetUjLRh07SjHf/OTjL3zjfh7doGyqMCgyh50MJdsb2PWA1SscLY3icsZ8AzR8TkWf//P2P7e1+KfsQubKrRn6O9rYIym2faJKgFeMaJYaBHGHo1KBtV08YZbJHM59FibJHQg0ahQ4wyGJGWfwvY6zYak1qxR5IttGrUMSllM7IABJ5fguinhehZdiDENF6eQkIYO0dF5Fv/wI+x67Vtw9+8UpVptiY7PsfAnH2Lvn7wSM3SWPKNjyZXatBo+uUJI62gf1rNCUcndzP7Oxxn7/dfhj5yBW3FIBhMwCjyDu+aRDMWQKFSs0aE4S7+qSTIW56w64UZGHI1jccoujIWYsg+psA6pWAaszaW4Gy5Jf4KKNTZIoct+ZZVQT2uL8g3p7Ayzb/8YB3ks7Tc8mcp5KW5VNkOpD6MXLRH+/ShDn5qm8u19LM33E9+2yMI1H2Lsd95EdngPXk0RDqc9utV7/mSc0SOWhYcrbCHBXfXIzyqq56R4Zc3e/znN0WvHcesCt8PSo5/06pbqWYpoMIW+GHc2wK8qaqW7mH37x9n1urfg792F21A4ocD3ms1jLL7nzxn7rTcR7N1F/phDY29KZlGcrXEBDVGfwatp/E5dRfXchGDZIeo3ZJYd2tsMXl3a3aspkmOzHP2ba9j5prdw3kdmOPnuSfmOuiLqs5jb55n5+DUAjP32m/DP3gHAzjPWmFsY6OzkNHgGp+KiYoUJOoKsjgUHbC5BVT30tjbMZzCBMBeqkRCzGmAzKVihprTKkhtt0FzKy/8zRhiirIyJ5NZF5q/9ELs/+CqK546S8RJWZ/s579xZ7pwdxfVT0lSTNl2y/W1aKzl0McZEDtpLyeQi2i0frS3aMb05k81GGKvkb47B81J2PvM27v7s5ajlYxx/2yc5yGMpqQGqdoPruY4zrroafcEO0oEEf94jPauFiRwcP8UPYpqrOczacWbf/jH2PedqhpwdFL90mOPP3cPRL13D9qe+kIVvfoGx35ZDuBMpkh0hwdEM7bGkB8ZVNy5y4lPXsP0330yxuIfo7BZqOSCzrHFb0H54DfemotQ7nNvCmcuQ5A3+hibJW2GaPLNGez6Pv+FgXYEAVfYLxejITQlLB4SSVscyJ7psYZWzFcaXzZ8OVY/6Oy7JpifaHqNaDl5FEw2luGUHZaU+z23LJnr5ck2Ss1jfYj2DajlkFzXWhfaYbHastmQWZOPR3JmiIyX3EymsI+NaJ4rk6BwnP3FNz3+PvfsNBENnkFnRhEMGkzGobIo1CndF/LJ1LU5bEawraucI7CdYcgm3JcKgGStUorCObMaNJ/ICAE5T47QU0VCKsgrd1BjfEmxoopLUzyT9CaQKpyFtazIGp+6QlhKyMx4oiIsWryqinMrIwcA6kA7FqJqL21QkRYPT0KQFQ+Eeh3DICpNnYMVfWeQ+tSUpCPNWNGB6lPwqkcCSc26N+J4iacZiMykDP3apnCu08F5V6kXSrAWriIsGNdbGuytHOJwSHROfP/buN5A5ZwxT91DZBNsQsIQuxdKm6wH0RxT7WlRX82AUKpPizgXEozFBISRq+thQowIDNRc9FJLJxLQaPqbhkR9pkCSaNHFIIwdqIi+Q2VODmRnueNNn2PPKq9Hn7yCzrGntTMnOO7SHDW5L+skqGasqhsKMHPCMhxyMdqQM3KJpjUi9gNVSazTwV9PUnjvO6qWKvrtkcx4XLUFZ0Ro15E8KrM70J7grQl3stMSP52cVSVZkKZxQkVlRhP2W3JLqwHnlwJafVThty3JuhvlrP8TY772eYNsZWN/gL7nEJYNf1oQjKd66iIynWRl/0fYY1XCwniVYcokGU/x1mVdx0WA6/aqrrjBUJqAjRVIwMg8HUzKLLu3dMcQKHIvufF93nGBFWsJqqd112op4ICWzIP1sXYvpUKA7baHm9soOxrWkfSlOtcNG2FJEOzr3m01xyq70i2fwqo7cU1ljfAjWFc2dKW5N/JJX7fShazt9ZnsBK5s1qJZQaWMVKGmbJCd9kfQZVKywnhyoTcZCouRvpRQUMgcHYpwN6UMdCWU4Bva/8QhHrxnHBhbrG9KbF5n7yLVsf+ubyY7tJs2anu9ASZ221RYdalm7LKSBRaVszkvXkublvuS+QXeYDOP+FKepMUMx1Fy8ivhEU0jJHfdoj0jfhbuj3n5s7J1vJBjb3VsDzS2LzP7ZtZz5kqsp9O/Cr1rWL5KAx44fWGq7HGGOU5BdsmQ3DNUzHOKc+PI0K/fi/PA4P/qPj7DjKS9k/h++wMDjnsjGP8thZ8eTX8j8t77Ajje/hdzkAGniwHyGzKqisT/CK0TiN9ouxBpSRWa41fPH8ck8A+eus3bPILYUQ6xlf5ZNUS0H8gnbrvNZvVyYCsOxuLdv89cdotEEf8mVILpvURbsQISzGBAFdWbf9O5f6rAzc8fOX+qws/shc7/w9d7+9rfzpCc9iT179lCr1fjiF7/IBz/4Qb773e/yuMc9jpe85CXs3LmT97///YBQTz/qUY/iAx/4AE9+8pP50pe+xPve9z5++MMfcuGFF/7C97kFY9uyLduyLduyLduyLduyLftvbP+/gLEtLy/zkpe8hIWFBfr6+rj44ot7Bx2AkydPovXmgWtycpIvfvGLvOtd7+Id73gH+/fv5+tf//qDOujAL3HYSXMGlrOobSFq3QercIZD0paDHQuh7pHeI/xdTj7pRSFs0wFHTqlJweIdzRKXLKaUYNYlS+Gse7irnciYBrXuY32DO+9T9TISidAWnUtIQpeNtQER5Bxo494d4N1ZICpBqyBRQlKFzaT0XZclLinqUQlnrEm8nsEbbNOoZlAbPiafgmNBg9kIYNWB7TE20eh8gr0PdXlSNDiBRUUSnbfZTpHxeoZ84hH3peiGQ7PmYj1LdDLD7v8dM/8Ij3h3iJrOntIDlnQsgkhDkEKiSUciyZilEgUyBYuNNKFnoRSTVIPeZ7WXorYnkslyLOQkc2Mdi9cXYmZz0m6OxRp5RgzyXiWfN4nGthzsgmDoWo+7EOtBbsahcUZCZsElP2spvO1eCh3OsdZ3R1DnpIzdYFgA3LrGKUI4ZCgddWg+UwgGnJZi+QqFX4HcHR6FhZTZX9F4ZS3RuSdcQWZZk2Ytcc4SrGtqey2Fk4raXkVu0eKEDswLs0s4aAlulQrPJGdx8oY0AzrU6BjcVcnt60jjrzo0dht0SxMOS9Rn31sOc+L3J8isaNrbDCqVyBFW4BwqkUwNSgQrrWPxag7NsU52Q8FdnziAUzeYrCHyFU5DEw4lvS7NjTYwuQQUzC/1ozc8dKxIRyPQFjMckclHtFZyqGyK9gxp6KAcixoKMbHGDiaSpfEMpuVAJsUpdkQdrMLEmtZcgfyuOu2WD4sB3p4GYcPHRhrTiU6mCzkaOzJ40wFcEZP+yjz2c2PEK1mJxnmG1kYWt+ZgijGEGm/Wo7nTkeijBjMcoucy6BTq2SwmK1G5tC8mWchx7G8uwdY0YU3G5cnfuRB//3aik3Pwe9dhHYFwkijiAUPm9hyt3TFJ2yHNabw1l8aGhEcbF7WJRlOW/8elRIfX5Bm62ltBJ5PWbwjuyUiEtz/CbAQU73aodzgA/A1NeEkb73gGt6lojRn8iiZayZEOCIQne2uWaMDiNCV6agKLV1EkdxUZvBfWDsR4ay7VsyCzIuyOjVGHJGdxm4rmDoPxLDpW5BYV4YhEdMORlKGbHDbOt1jPMvbvisVHWEo3+zihwGFBItThrpiNbZA9JvooSdZiByNs6OCWXbyaIi5Zkk4U1LqW/ltcwkERCbS5lGDBx3jSRm5T4bQV+TnFau4+TssxoCQDwnCIsgqqHu5giHd2mzhyJXs4FuKeF+GEHibWhLsMxBrrWVLX4g2EJDUfm00wicbx5XtNzgE/FZFLBWpnCzYC2rsivHxM3HZR2uL6KQxAXO+Ew3e2oOaRObhGtZbDGoh22W7gGs9LidouuVxEWpDshg0dkqxC+yn1SxQ21ThBigb0SEIcubheSjqTwxlrEeZ98YnZFDcnvjLT16ZZD9C72rhOSrKSpXyBwXoGvz8k0jmJug+EpIlGaUhrHun2WESY+4Qcwim72HUfPRBhGh66FGOqHnZdRJx1CiZ0qB/vI1PWpIElDRyJdtcd4nIePRqi532SvJUo70KGZhBIhj7UNJZF/NmpOTAUY12LLSS05gqE80VAMof5sRahkXkdXtjE1DyinGQssBAMNWmWs9T2R8TVoJfpd7Ip5XMDTC6VyLtvaJ6hGPgrWHxyhI00ayUH6xowiiSvsbmUuKgx+ZTMSZ8ka9GjbeKWrN+VIVAtB9UfkaSK8MyEqO4TDWnIGFTNxQaGykUW1daYDkyLuktwQZOw6RHvMmjPEPUpSDR2bwTakDZ9TMuheKtP7ZwEf6BNMBZjQw/WC4RntVHaQqrw/JSkizoZiskNNKmXc0R5Je+5qIUbOyRtF2KFs6Mp/tUqfD+h3fSxrqGQb1Mp50i1lblzUYt2LSDf35Jx5BrSVOFoSHIJ2jXQFsRFWvVwdrVxEgcnH1HItankcniOIQhiGqUMtukS746xkYOzt40KXdiWQtsj3ZbieSlposkECc1qBi8bE7c8XD9FFQ3GaNKWS1AMSWIXDORLLWr1LNpJicsZ0pLBycdYo+RePYOJHEwuwfUMSaLJbWvQWiygShGOJ31iCinKl/VT7ZDshBqMSIZivFwsa2Uk81spYD6D3t0Aq0gTjeNYLJ1klFXomQy2EOP5CYGfkKSa5loOjCK3rUEUevhHswJhPaeOk2q0VTTPtjjZhGSbQhtwCx3tu6ZGGUUw72FcS0eXniRvGbmxwdJ4nuyyIhwQ/RrjwcDdKakn5BO1nQ5JRljqMhWDrSkWJ2Dgh/I98Rky101206dGA7Immf6YbV/OsvAIhQ0M0aVtfG1762t2uEl7KQ/FmPZKFm+wTdL2sH0JG3cMolyg5oKVvWphoEmUd4nqPpX9kjELt8c4hZg0dCB0iMZiBkZqbDhFnEyCMgrTcmVuFlO0u7kXebBmsKT/Lx92/vIv//Ln/v1f//Vf7/fas5/9bJ797Gc/qOvc1x40G5vOx7gNTanYwmmL0zNlH51JcdyUYLAlqUlAKYOKtYiQKtCDEdFwCgaiIYMaaePlYrzBNk4pJh2OetfJ3JYR4c55cZ4Dt4NudVJ9qcJZ9vHXBaYWr2bpu6cjEtcEb9UlM+cRLDvoqkt9j9zPwC2KuBbgNDVx08ebDQQ/3dKopoNqOuiWHGAy8x7ejI81Crvh0/cjXxYbEOz2ikOwLrj3oHOP3obUMnhlB5MzZOcdcickhd4c8SgeB9t2eilbGq4swongwbVrUJGW60aC40WBXvF76XW9Igu3W3FRLQe7HpC0XFTdxV91ZPOhwS27WCNOoHiXtL/KpBArvFKIajm4qx6mLZ8lVQzeLm2Y/edbSTIdHH95k3r3VEtyoFuqRw8cbCiBfDgiLpb76hFyXz0i2PCybMK2fWyazHKIO9IiKXRw9EUHJwTjg18W8TvrSk1SNGBw2h3omRL2oczKpkAavoEUlFGkfQlp1vba1morh5i+GK/Rgd50vGA4mnQ2qyKK6ERK2q6t8GqaYF3hVTRus/svuA2ZKn5V4feHOE2BHKKEOvXU+d5qyrjx/IT8bRmBVRZTrJW+tImmVc2g2xrtp6RNF+UabNPF1D3cuQAijZtNoOpBrMkd9zCJJq17MJ/Bth2sbzFGoWYzeFVNFLrYWAsc0ulA5FyLsxiw7WPTqFbnEFrx8CqaYFkONCgr4r8NF6fu4NUV3rJHdlGTWdHYso9XU+TmFPlZTf64i1fV2MjBZFPijUDgOR0BSTyL8gx0/IAJZLPlL7k9eFPuuEd2xiVzZwarwQk7sMu6HFbThofq7H8Ks52GTRXhSIotJrTHEqmDmsliHUt7m+0JhuaWBVrrNqUeoFsvZXMJuSVF4yEhViOHCNMRg+ysY25TCV26UWRWFcM/MeSWDK1RQ+0M8OoyHoJVmZ99dyr8usGtOMT9Kf6qQ32XIregyZ9wqO2W94WDne+vC8wtPwdEGtVwSYpSf+Q2FLbpkpn1KB6DkRtjgSikMn+cpqa+1+LVhT0qmBPcuTKgE0VhRiAs9T0WHd5HqDV00EMRxRNgGh7ZvAi+JW2XsOXJOEoV+UKb5nJeTvV1D2fdQxfiHjY/rgSQKoJsjBukmA2ftOZhY41dypCbd3C3dTZEpUgW4JUMyrFySIkd4qaHk49RoSYNHdxiTDvySFsOmVyE1oak7eI4Bq2lY5prOcJqgNJGAkNGYTssjH5ePqOdlLiz6YpDFxNY4kqAk09Q2ZTicAOTKggd2i0fdzaQOakt1rG4NY1Tc4g2MiI4PRDieinZfIS1CIQ0MOiKh+4O9ZoiN++g5zOyPqwGFI67PViPEyroSDA4LXrCwdaBYM3Br2jSmtfrJi+ToFLxO9lZl+JxjVd20HWnB3v1yg5KW4K1U9aSUBNXfUEyxUrg3w0RrA762lKftZTHWfeIK4GsD50AX9p2sI58rw4VKtIES7Km5W7P4K14WGV7PiW72IHlrAnsK1iHdDQi6YwXIg1hB3697stGvuVJoDKSNdPmE4Fs5+Xw1oXo5Oc04WIOZzHA8VPStoOflU110nZJ2h5uJukJuKpQE5UDAi8hbnmMXR9DzcOEDtQ9/CAh3yd7EidIqa0UZNzECm/WJ4kdGRORwAjNXI401djlDK21LDZVJDWPWiMDdU/2Aw2Xdt1H+ylR5MhBp93Z42iDbcngUDUXkygIDNF6BhNroo0M6zP9pKFDmmpqywVMU0TanaUA5RlMqjFtlzR2oOFiEk27GhBXAuLOa2nioD1DUvWJqwFp20X7KWE1wCQKW/UprxYwGz5xyyNYcnFyCfpEFptobOiQNl1sqLFGkdQ9VKpoVrLYzrqWrElQ1inEKMegGrKnAOSeFSShS9zwUas+pu6R1l3MSEhcF5izrfokTRlLScOTsX5GE9NwiSOX6nqeZiWLU3HBMzTXciRNqVvTIRijSGKHdCMgc9Inbbn4QYxJNEnSuRcX/PUO7DRjMe7mYuyui5qucQTuZR2BHzuhsD12WfTiotTIOm1L4cuH8aoa7z9kb6M6Pgiz6VNtZy7QdoiKUj/jNDVx3cccz5OdcwiWXJSyuEMtqHjgWuKNjCQANFgXjC/f7ZfF98Sx+B86kFubTfFWXYIghtDBX3Ug0mysFnGCFBYymMjBXXdRDRdvsI1p//KArW5m58H+/FewLRjblm3Zlm3Zlm3Zlm3Zlm3Zf2NLrSX9xcr4T/vMfwV70Icd0/AwnqWykYfAkpn1aO8NJYIXuTgLAcYv995vfUO0I8XNJKSrAV5dS4QqVqQVH5Mo3LrGZiyOgaSDbmicG5I/p0HY8iBWbHguppjg5SVtmj+3SXmpCI4lP9Bi8WEFSkehti8RaAuglcWuSRFyuDPpQbic3U0GCy1WogF0IUatBujhNmmsYdBw5gt+zF2fOoBqdRJffTHVyxPSezrpQcfS3hmTPemhjCIck9fTAFqjRor5lCXqsyRDCaqliUoOrRHw+kKCjqYAgcEpxkKQkCqsVXjDLeI0S1AKMamWKEA27qWDc2Mh9UqWwliN8koBVTQUim24sx/3Yes02z5ppFFnNDCpgxkNae9OcaxCa4PqIOiy2+uEoUcpF1KvZdAaVi9R8D35e1KwDN5qWXyUIQ10L/LetV3vn+LotePEj7gA/v06vLpFrWjyc90q+c548UQA1a9ayi+ZoP9z03iPnqSwbtn28SnUQy8gypeIi4rMCiR5gZqtv2yCwnGN1zLs+f1pNn59osfgk1/qtJ9nUIMRJnTInPAJhzbTzH5Nk59V6OMBSV6ikV09jXNedQNLb5zsRPyFbSrsiN8F63SE6oQ1pXyOJrNhSVc7sDAf3LvzEp1d9fAqUtTrNTYzYEEmwQkS0sTBPLSBnctCX4qXjTHbUzwlRf9hqKHikxlukcQOthgTZCJa2QDHMyQd0g3PS0kGHXxlcfIhUcGDhodqOjiOIdrVJloOJGKpLE4pRhdlTFrPkAzGzL59Ej3QIrtkcYctkdtJj/kG5VhMYCRyu7NFw8/ghIrmdoPJGSEOGVBYRxMXLWkpEQhlkKK0JX9DjtolIWqok5l1jGSkukMm7fiBYQuZlLFvucw/NUYvB6R9CU7NwXQiZU5LoxuSGe1miLvm5CWi6636eHUhCWgfqEM5Q34GvJMiSFz85s3oc5+M32ExKsxqGjvAn/cZu3YK7xUTxHnIn3TIzxvquzSZo5ribML6uRJlH7rRwYksha8cYfn1k+x7y6ZmzuhHRJh11/uP0Hr6QbJfv56h7Dh9X7ie6vPHKf3NNOsvnWDwf00TXnmA3JKLEwvjEYgWRHObRjc1wZrGbYsm0I74AMefYxm9MSbNaOKiQ+luyU4FFUt7ULKj9eeM47YMrW0uxRlDda8mPyPsismiQ1C2bMSnNR1+X0gaiZCgW4poruQlI+SlaEcyhKaYUFsuUBirE8cO3o6Q9p19KG1x+tvksxFx6tCsB0ShR1+pwXpLIsoocAoRjSDA7yQ6HddIknE4lExNIcb3EwIvobyeR5ViHMdSyLdpNAOcXEIUejhuivZSKe7NgEk0bkF8YBK5eKWIuOlhQ5lzMUII0yXLwTXyr2/wSgIJdr2EdtvDCxKMJ0QfacbiBwnWShYn9j1IFfltTdotH2M0SQwoi+ulxDmFWvOxQxGqJb4m6jeobYZ0IEFXXZzRFq0kS27GJSlY4j6D1x/SdgWu5ZU10ZAR6E0K4aDpZUyCDU3Y50LekDgWt+LQ2hvjL3m9LL9tOyRFg5dJiIsG68qcC4ZaWE9IH8gY/CAh6mgDxaErc9E1pBmDE6Sk2RTXNbheKtBXz5AOxThuik0cwrxM3ub5bWyiCQqSCQwbPtFFESrRVB4mUO9G5DP47z4bv9KWSHWiJGPkG4E/NV20Z7CdQnblWGyicDKpZFUCg1fsfP9FTQo76rRPFnEdgw5S8XFNn/6hOkpZGq0Auy2k7vq4Q20c11CpZ3EzMSeeHpAbrAssM5uQJBqtLWnOks3EePk27cjD8xLaJZ9ivk0r9LFBQriRwd3dwHEMpXOrlOs5VIdpJGx5eMMtyfD5KX6QEHgxYezh6JiGlUw+QDDSIE014WCIn0loVwJK22vU6xmy29o0qxkGhupEiYuXb1NvZNCOIckleH7KQLFJxTU4jkEVQpLEIVIu+B1GtrE6rXqAjTXBYAtrFY5jCFsehaEm1irarsXzE3S/IY4d1PkROlU4++pkvQTfTanUM5jUwfXkvn0/odkMcF1pc6cgwoKZTEy77aEGQ8yG+BOdT8j3S3vEsYPX36JZlTSJNxOQ7G2TJg7BSBPTyYik2uIVIvTdOdSeCKUQOF7bJS2mjO3YYHmtRL7QJjk+QGtnQtY1+H5I27G0c5p8X1uul0mIOhk0r6ZxEQKK/Iym74cdaH1DoeIEp20Z+WGb5Uuz9N3TwmsG5I5VyZ2A1s4ilbM8tv1IGPmMr0keezlOuOk7zXpnrdSb+5ouSiQz1KKaU3hVReHAKqvLJdQZDVq5rLCsJg5J5OKPNgnXs5S216iu5lEdMhhnrE28LntUOxYS1gN2n7nCRjNLqxDgzmUwe1s0K1nJYm6P6R+uUynn6Cs1qLsp2oLFw2ZS0thB13/5w4ehB3J4UJ/5r2APGsbmVRwKJ6TGI1gTDLK34OP6icAURiJ0JwWXtD1UpFF1h6Tsk11weow+flmTWXSxvhGmjlRSed2MoXYtyXqGYMYnM++RWVaotgMnciTLWaIjg2RPeJAoGis5souObIRPujCXhYUMcdUnsyATIpj3cJdlMUvmcqycHECFGj2fwS9rkpYLZR/vLqkHyZ7wcJoa23ag7AvkrC3N1YW9uQ1wa5pgsVNnlCCwH8/gtDR+RSAMTlPEs5w2xE2fRkdAj5YjB5CTWWzFx5sJiCoB/oZDWA+Imx5p7ODdnMdWfMxKhtp6nsxdGSobeUkrR5rGyRKpD5WZPuLQxVvyiWsBadUje2cG5848adXHzOZIE4eo4RMeL8J8hupSAT2XwZoO5KJjmWURDMOxZJeEzaorZlh/zjjrL50gWNW0Bjsp+w49bPlc+fzGr08QPfFA7/sa2ze/O8nJZFy4ehL7o9ukrCuV0Wg82QzWzhDK2voOTfTEA9R3K1Qqyslhly0k1tiKD0bYlVQqtQwAxrU96FCch7gkFJ4gInl+1RIXoe94QpoRekuvAa0xEcLzGlA+R567/3PTtIfk/nXcgaHoTsrch+yaIe7bnPLtuk/S9khqHu6teYzfOdzHDnYpI3CESMaM2xfRXsuStF3SpkuznEWt+ZiNQMaYa2jNF0jmchijaJ8okjQEEqIGQxrVDN7dWUxJmKB03SVteJiKbNrdqqS93ZbAVdR//Bgzm8NpaNyKQzDnodc8gSsqYC5LdknjVRR+VaA0TiYlu6TJrMrBtf9mj8xJH1P1SFsuUVFq8kwHrkDbQUcK1Zkvblvhrbm4NQfVcJn/FcjekcGrK9x1l9ycJj/bmVsGrG/RLY3uxBaSzgHdrvrCqpcoskuW1oiFY3l0U5NmVKceBjaeJQKvQ5+eprbTxWtKn0ZDslkoP0Rgkk5baGF1Au0hRW2XS9IR/AtqltyyDKawD2beNUnlheNk1ixzvzNJVNRUXzDeo913IsvKqzvitR0R3OXXTlLe55EppxS/dLhXx5b6ckD2K5rScYPbkHFZ2+WSvdenPeCQ+6qwGW77+DTZNYPXNGTX5H2FL8uhKRoQCuXiCUt23ZD5h+tRBipnaTLrpy9B0UoWd8mnMCv+xlt3yM86mLZLUvUxTZfMjC81XEf7iCOXxmxR+mAmS1z3qZzso7HegcEYWF8pCftRomElIF3KotuaeEnGc7IsC7S+J4uuyrhsN3zK8yWB1S37pKFDeaEkG56yT9LwBILWEAqxqOGjXUPSkkCabTk9KJ2ud+oUyz4mcsjnQlAW26n/wijiurB3xpFLErqEa1k4nieuBJhCSns1S1gL2Pa1rMCYGw6NpTzu0Sxp20E7hrjlCbQpFOioOx+QxOL3TGBw61qCaK1OsKGl0KmwyAUrAt0r3OmRm3VAw+CPJYgVbIjP1dlEmMJCsInCrWqycwIz85Y93IYw4XVjSNk5h7jtohOFXpaNWDyfEyhUw0G1HMKGj7Mg8FLTFJhylxUqDR3cuYCk7dJeyULdxV9zcGYzJKtZTM3DXfZZf9kEzmKAqrmE1YCwkoGWQ7oW4M4FDH4/Q+6nAWnWkv6PDWzZxyYKFTroiisQ2aonMNlUYdcENm7bjtzXui99FWniTr0fs1nCtg/bZLdpE00cO9i2Qyv02FgrEK1lBB5WSEiXssSxQMIcxzI87dJu+rheil3MYFJNaz2LihWNSoZ25BFHLrWVAp6fsLFWoL2WJVqU+smwnKG5kmfp3mHiyKW1kaVVC/CCTkAzlvFnjKLRElhZvS6bfGvlMFhfKhC2PWzZp10J6N9WJ+3Av5pLeQgdmm2fdtuj3siQJpqoLsx78VKWjVqONFW02x6NSpZ2NcCmnbqxxKG5mkN7huJwg3AtS1QJaNflPfWNHK2mjx/EaG1obmSJ1zOkRwukiUO4nKNey7C6XCJu+qRVaY9wLUttI0cmE6O1JQo9mvf0ydiKHQmkWSVBBAALjeU8rVqGpO3RWhBlSaUgc2FZDpiRQ9R2SVNNHLo42QRjFSOHFskUNk8TXkbYHlc2ipjIobaax6uDW3OIIpdmLZB6lUQTtj2iuk/c8KATX7S+wJiND83tltWO0Ll1IdrRj9uE6hkZWmOWJO/SHNa09hSxvkt5v0dm3VDe59Ae9jGuIioJrDB+mAiU224c09s8RHT3uO3VLMM3p6SBZXVJmMjijYzQzQeGJHIolFrEs3l0PqY2U+rt25ymwszmcOsCZzWhQ/Zen5kTw7Tv7EOfzODWFWY1gFhqgjCK8kIJpS2VO4ZIT+alHitjyR4TP276fvmanbRTs/Ngf/4r2BaMbcu2bMu2bMu2bMu2bMu27L+xpVZ+Huxn/ivYg87sJDkjUUPP9AqI0Qi7S1vjz/vkuzCtVOHUNW6HLSMc6hScB1aE2/Idhhklp3Crwa13ipobokWSFIww2GQlogWAA82zItKcJbMgcBkdiyCnkXprvJoGLXCs/p8qgg1hTdINiQyrWBGsaaxjCQeMcPFnU+K8Ze2qCYEndBBZKpWiz26RuhPJZ4MNi1sXJqZu2+hYCrH775DnKN7l9jImw7cmZE76ePXOY4QKezInzFlGIs+qreXaNSEg0PMZKZ5raWHqAcJtnfZ1rPCzD4bklkSTxbYdrEJyi74h6rfERSMsYBlLWvOEmMCFtCAEEmnWYhreaZkdJ7QE6xZdd2iNSp9nvyFR7MKXDzP4v6ZpnRlR+oYIJRoPMivQfyfoRDQa/O/cgEpFUyG7Yun/3DR28hL8skTT+47LANKxCAFGRfBqcv3SvZa1l09QmDcipLUokRurYfDLP5F7rIs2EtqS+h1hws6INp4IbcVFgU5kVjdnZNzRmHBaUN0t532/qmgPiaZBc1SgQ4VZS5wX+J0jGf3emLeOjFUdQZxTuLXTp5LqaNM4MXgVjconmMgRjSktkBvd1qQd2A2xEvhHJOPWOhbrWpKjxZ7uA1Zh+hOUZyQKPZcBKyxeTtkVwoahUL4r6BB2NBRu1SG3ZKR4GEhLCcG67ukxgBBMBHNCCtDNqKQZyYg4x7skApZgTW2y1FUkghuXDG7Vwd2Q+dmFn+UWN9vEOtJ2wapD3+0OcckSF4StKg3oFYo6oaJ4t4MJTK/Ni9+/u/Mlnbbt3F/hpNy/TkQM0qvKGwb+7mbCfkvteeOiqdOnhdSi8/nu3OxCFwF2fnCK7LohtyhvSgJFbY+0V+m4Ibsir/sNec/gZ6ap7dGsvGaiJ/IHIho79Klp/IYlvyQihO1++Vs3WxPnFIX5hLhgaW3TtEYVy6+fJL+U0h6VAVZ9/jjG7WSUznRojDqU92nKL55g5TUTNEYdMquS7UwzUN3jsPLqCXLLKcWThubI6cQiykhGEthk6vOFzEUKZjvCtw0XdrQxDWHL0pHCbQiBis2mKNeKr9zwIVH4Cx664nU0Njp6GQ7QvV4qkCYTGFRbS/axEKPbGpO1qGZHh8QXXR3VlggnICQtbS0aNm2HNG8gFWRAZs7Dep3POxZdcamu5XHnAomARhpvw0HXJIvgzGawLVf8oGchkMLfrg9deBjQF2MD0TFKCgZd6WSCEk1a9VGh7rA2WlRnMGU6IqC67hKsK+LWph9VicwhG4l+SntE5mRQNh0YnWizmLYQA8TFjj/vaAtlO/Mn6rP4ZYWKFJl5l6jfCmtXS/Uy2SoV/2F8C6n4CgAbSnaeIEXlEvENQDyUiL/xha0yyYs4IcVYEBeujPFkOBaSl0LUYfAUgo14NKaxQ9E4JyK7qKkc7xdEw4aHdSwml0r/xgp/1cU2XdSgRPN1Wwu5jmdRg5G0a8eSwVTYKNcCooaPco0U6jtWWMYApz+Cmkf2zgAdSaYqDSVrEZWEmapVzqBSRdz0RIuuLWNbKdvR/UuJYynyx4AtpAKLNEqIYwZCIa/IJhBpoqYvWioAQUoUeoSrWYEIWkibLnHoYo0SvaVUoUOFV4io3zEgEC8Lysr4VUqYBrVjsJ2+QwuDY1QJSNrChkjD7bHZpnVX7qnhkFZ8avNFIW0KhNHTthyZL02XVjVDqx70tPiSvDCvWcdiWq7AEg2oXEImG6GLMdo1tBo+7XpA0nSlXOFF4ySREGKYsr/pUNZ8dD4WaGLbgZJoLlJ3SY4MkFR83EAYSdO2i+snpBUfz0uZv3WUVi3ApIokckgiB7cmZCVKCzy66++1Ethjt2AfwMkm+IteD1bmtEQbzK1DUFaCqEE0dLyVeu9zmVURB/ZrFpVajO/g1SzNUU12xaIT+QFZA7sEBd2FQ9U2fWqS7ywm+YT83x+RfUeocTZcGd9G0Aym5VJbLqATJZpbxQQdKXTTIc1Z0pwhKaWyFlZcWns6DHMpJIXOHtQBPCvoCy17RdN2cfY0ZJ0sxrgtRXt7is6L5tUva+aX/PmvYA8exrbh0BzV6LrggHXS2XwoUAMR0WhMa1vna11DMpQQ96XiCDuLgFfRQoFqIc2b3sBJ8pawv9N0mVTqLPKmp9rd2i7pQlIgEcrg9kiCzibU98VkNkR0y7iWcJvQPwcbiup+UQfvQqVUCk5bPp/mO5TCfodKMGMonyd4SpWCzgk7jsmmwjZGR2xMCwQGwK10Njpt3RMYa23bFLq0rqX84gnCkiYuGGLJ+AojVCkl7ZNrALLg5lJw5XPpaITe15mwoSMOoK2wsRZGGm3J5DrUiIUEHFnMVSIsUJll1WP6IJXFzXhWrtFhAnFCYWIyp+yP4kJH/TpjKB574GHSd/Om80s9RdQH1TMVcUGexTl3HyjwywrjKWrPHUdN/YRwWFSqy/s2L6iSTXhb/u+OCFxtUFTMW0MO4aBAx7yGpfo0gSmlvjASecseuSURD1Tdc2BbNgJWgV9RxHlF2NfB2a5ZUk+RW7IEVSMQL9+Sn5MNSBrIwcu44LYU/Z+bpjgjTii7ZmmNmR6MLe6zGFccU9eC/CarYHvIEg8YvJkAJyNq0ULjqQTyGGlIdI8eFtVherGAZ4lH5bt0pEhCFydIhfmqkJD0p7hBgvEsaSkVWF+qJd3eGU9RvxwoSn9zGONbURcPNc09CdFwitUCH01ykJzdRicQFyxx0eI2ZAMWDaW0t8mh03jyTG5D9QQw04IhGUxI+jqH120h6UBC64J2py+Est46EJUMUQm8qurAyKwcfDpMauGOmNpDQ5yGIyx8p5gOpX/9ivy/OWaxgcEvS/8WvyUH77UXXEJcstR2aYpzKbU9Cq9u8dcdll83SXNUEfYrjCe1We0hy8LVk53+6uDL/c1DVZKTMR0OaKq7HQY+O0392YdIcrYXuDA+tEYVqxc7rL1igupeLUJ1BcXGeTD/W5NyKHrBOElOkWZE/NK4CJypbWmMithmbY+mOaopffEwblMOM60RoW+v71K0h4QxLvUg6pPDU9qBYa5e6FLbo4mLp7ed1dA6K6Lv8wKBMx2hvyRv0PkEJ5cI/fa2FmnVQ+eTDoU9RIPCzkSi5bCQTcVfOlILYbIpTkthhmLyc0ooihNNNBqLb0kUbsXBZowI19Y92Vhboc8GSEOh2VcDEU42RWUTlG9w+mLxhUHaESmUg1eSFZHDzKKD1ULZ7WYTkp1hjzUpHk569OpJ1gp1u5Y1x8vGcjDzDCqXEGzIQSwz79A+I8Iva6lXcyxuPkZlE7yKhkJCsKqx3cOEK+NbR4okLwxcSc52/L6Mc9URg+wyp62fvylcKV8iTJayPsmhM8lZWqPCLhlsKKnt0RCOpjhtJWtrzvbWJECYPGvCKEkqgRjV9S9GYVsOXtVBl12CBQ86dL1eTUQns8sKZ1FgaZll8fmZEz7BsYB0Pkfubr/HMOesyYbKW/I6SvTCjNpjqdKyTmWXtAQ6sgnOjEQ0TCGReoWag2m5eNVTavMiRZCPUEMhmaLQ8HuBrPGen6A9I7DJQkJzfyQimJ5heFsNCrHsFXwjbJA7W+ggxc0K4ybFGGuVSC2kirjpywbdtaiGg5NLBI442iJtuphYy4HDKvxchEmV1McmGq2FltymMh6dfEyuEOJmEhHqDRLSooxt7+wahf4mJnbwtzXRgyFxJIxuAG4ga7GuOyI6nRcGORBGQzeToIsxwUAbxzEEe+pktzXxBtsdFlcrbITFmOxIU55HW4Jc5yTsWJy2xs9HqEyKyqSE9QCvEGEjh1ZNDmJBNhZqeCUHDltIqe3RuL7U8Nhs2gviMRTJHEjlcEfVg6pHYVeV5jkh+FIPBkg/po7sPYwid3YFPxfjZ2L8bIzjGeJ+qaOzscZxjcDK60rq/iJH1kwttYWum5Ke1RI2MjoQ+qwwxCZZaA/LGIxLCtVo4dcNQTUl2LDk79nAaxkyc/Xe/B2+OSSzYcjONwgWamSX2r0gQrf9AAmidOda9+8d6LYTKpy+uLNXNGSXOoyYriU/3AQj6ywd0WFnrImOkHYqC4uvyafouiMH8T4jIrKu1N2CMMrpqhx+nZywD3ZZMjHg1KU+Ldl2n4LNB2EGRfogfwzqP//i/z+wLRjblm3Zlm3Zlm3Zlm3Zlm3Zf2MzVn4e7Gf+K9iDzuygbA8SkmYsUb8hKYj4ma34kvLvQFJINO6GS/GoK+QCSFRWpXKizs8pvA0R2MOCjsBtdgqVyx6FWSMpQSs86H5ZGGysb9FNiWLhG0zdI7PgUd4nwpLd4jGvqlAJZJcUQ385TTgATlMi0mkgKUS37GC9DjtOrHEbwpCkI8kk2KovUa9ZD6/a0QLRFq8qcITiSdvTPyDpwJyURFKdCHSqyKwo+v96mrB/swi715xG4ZRdiVpGCmoeuXuFeMFfcbCpItyQYm4VaikypdNesRQNthYLVM8EYo274mFyBqtFtC7qF255pymMIbQFvqTrjkDqKhrjWtyq7kWpAbZPNyn9zWH8tQfW2Vl/6QRuc3OUJzl5XutIpLP5zEMkwwWcENKsJclCGoiIaG5OEQ7I5xrPOkR9t8CMuv02885J3JbAkip7HdrDitaowa9a2sOqVzAoGTr5feMCI5CRTpDBuBZlJLNhHIn8pBkhRWiOihbJxgUQljTtIbAeNHYJ3MGrC7In6pPo6OqrJqieJZHM1jbVyxqpRKAKbnszagsQrmewGz66wxaj25IRSZsuOlYCSWi6NM+M8Za9jtZTh1mm7OA2JA2uWhpaDiqSyK9NFXYlkJvrvD9ueNjA4m6IkJxtSQavCynzapKxqz5/HKetyH31CNa3EgVqSeGzdSRS5d+eRcfyfG5bMglWQe6kS7CmcULpb7cpAm3WMz1ojb/s4nQY6dK1AHfVo3CTFB0neYl8KwNsC9EJZJdF3DNYlfHoNjtZ0jVXoqg508v2dM1tK9wmNHda6nsUQVmhWzJ20gBqT5aMn0AUO1C1omb4lpSoTzIMIx+dov+oIShLJF13YHtxUaBgm7oL8vn6sw/hNmX8xnkwnTrq9fMcisclE5T76hGctsAm/DL4NYtftuSWDDv+ZAq/ogg2LLmvHqG+S5P6UD3DERHcFh2yDMk2AaI75UL5xROkQSfzE0Jm3WB8evM0Gtx0JN2sqPUky9SdF722a4h2EohvMsMRwYboPZiaR1rxBZ4Uii8ybUeyAnS0YZY8dFtj6y5uRcYakWSXvXWBcHkzPo2dnbFo6eizyDqhE8jMepi6fI+OFLkZB2fNE78XdwroVwPRfWm56DUPuxKg6w7umicZHEd8FUpgrK0zI9y6vD+p+FDxcGoOuqVxyy5OSzRfCie1ZKzqjpAo1ALC0QRVc9ErPqkvsFLjg78oMF+3LJn0pCX6VcYB6i7WlX+hAw9syDojRDsKpwP9S/LSX1Q83IZkm91GJ+PS8V25BYEKKwO5JYG3KCPz1uvAZI0H2WWNdS3BiiN9Gzoyt/3NOYlGsmUOvb7zqrqDNVE41c49p4q4JGue21DCGFfWNHcYWVPZjI47YQeK50BzbyzrpQNpISU/b4kHUtwWtMdS3IZ8n0pkTZNMrhA22KYr+lrzQqBgHSswR2VJirZHZoJnCRdzUty/koWWQ7SYwzRd2rUAZyaDXvZRZa+n5WPqHuVqDhs51M9KUBseetUXgoKaR9J2JUtcFl0dZz5AVzxUQ/ywU3FRHd+qrEARdU1IHVTVw6lrktjFJprqSgFdc4hrPulCFkIp3k8rPvVyFrMspEpJW/Yk8Ybo9TRqGYhEeDmt+pg12StFTY+k6qMaLm5L4a16sBhQ38hhY42eywiBSN0jrGSIWx6t1RytWkAaO5iswbk3I3C91YDWWhblil+IYwddc3HXPIxviZezUHWhJlpIcTVAtbSM7bpHq5whKgfYlhCEOBsuxZOGeDVLEjuozjwDMFVP5lrZhYqHimUtrK2JoDxGiX5X06W9niGteaiWkHWEoUe0liFs+IS1gKTiCyS9C7Gs+vQfTfHqEIUuzpqQ6DjrHaHjeoBdzpBWO3AtK5B0ZURnsbu/Sj1IZueICprUk+x/MpAjCRQqTbGeJqhYVi8KiHOa9miOZCCHmvoJxt0kKOhuKrpzqutPQdAGjV87JBnWxYCklOLUHJrbRc+PVNGsB5iMlf8bSPsS3NsKWAXumteDjfvLrhANNV0oCGlDGljcsotqOpiM6TDIKoJbs+gVn/yMg5rJkF1RKCtaRo6f8svag83qdH/+K9iDPuxYt+PUDeRnIbvo9IB7Xlnjlp3eQqvr8nvtwpBgXRMXDWlWPpuUUprbbU/Uz/QlZFaFxQZkYVg+aMku6g4bTacex8ghwGnLocVf8tBNTX7WsvsPp9AJ9N8BNkjJLinSh1Xov1tGU2YVMmuKbTcqCic1wZqD21bkZl2UBbei8Tc2O27gp+CvCp66tTPpiVUpo3oDNCqqXo2CEyvaI4ZgvbNR2tPB+VdPgRqkipHP/KTzusIra3Ss8BqyWNlMSmtXKpjRhkJXXIJFj9Ixi82kOJ26IVJF6ShkZ9weaLLvpwItVKGw+ThNTVwyRH0GJ1JYVxhOvKosuq7obZFdEpx4D153+bksjudYfeUE/XdC7UxDVLz/gK7s2/w9tywwpeFbUryWIffVI6j/+DFB2ZJdEgG6/s9N43/3Rtym1PBkVi2Fe+oM3yxp1+IJWVRzyx3YRwLbr5ki2LBs/4Fl6NPTZJcsuSUZJH5FhMSUgeIxh8yKxukgyDKrirFrp+g7KmcDlYBfsWy/RsbI4G1QugdKMwmFWUtmRQmcQ0NxNsW4UJgx5JYsbguyKx24owP9P5UascKs0NcaB3ILpzjCuiObDAvbfmiFbt2zuOsuac6g8gnuhovfEe7rblK6svFOW4ngZ0vjrzs9Zr//m73/jrIsu+u74e8OJ91cudP09CSNRogRetDMdBWP/dr4MVlLmCDAEiAEsgFhwBgbsB8nsA2YaB6TQQEkQCJZSwTZYIMf21U9M5JhRmEUJnTuquqquvnek/be7x/ffc7tFtim5eXXL1B7rVozXeHec8/Z8ff7/j5fOdYQ6ykXsIlC61mNoFmgcVlx8pUAdKXt9f3N8ZAw2yDdbPYFj/lAgYRKabYqDJA+kKHoOsiCB8Qydpie4YZkdm8OnQIrP7tDXHFBGVS8rxHfpEmouyVHHIwYlKgkYdmyoTnrlHr6xp6jKzr8wuQoS+IzFYj+S5tO9sPb+1zeowQ0GAq0LjseIK6z5qxsOrSucuJZe+tTCIcCa0/nyJYEGr/+ODovWIQjYPTXz9d9OTrkZrLzHHD2n26jsWc9Oh0Ixg7Lb97hNU0odTz9vduQGbD3jVtYfoZ9pHvR42b7Ds19i6WPFGj/0gXEA4fu2y/g+rdu4fT3bmPlp/lap/7lNroXDTqXKP3Sc09Yu2o4Rj6g0blscOr7t5EclDjz3dtIV4DWVQsTCpz9p9tIDtgXex8WaF53ULnD2h/4733EIjpC/bpVK9sWeiIwf9Wj6D0jIA8ooYkOFJJrJOWFI0DdiLhhH2hEfelruGgMHA4kmpc1x9KhgsxkPS+XCfXy937bDsKh4AG5LxAfctPOgAc368FIsl+dNqzjOmJNhsgFbGyh+hqdZzRMYlkrOeP8r1LiutVc1HOYyFjL07jM+S65oRCOBFQmEPYFkn0B4QNE4QFrwQBAzBR6T/Ngpyoj6Zu0RXCKslQbulr+q/rcMKoZJdhV/WY198aHAs1rDuGQ1EI9B+I9xcOI5PhI9irJK/utyh3m6wwudJ4Dho/Q/NP6+jYngfndBZJ9hzLmOhnfRB1oaV/mAQ2g9FSPJYoO5TMu9lIYBSC2UAMNG1nWInnZuW1YTM+VkJmANIL0urZD2bBoXfYbz7aDKLm5a1wMUPY49zYuawxexLUwW3JIrires4CEUhu6+t6kd+cQCf8uXbVwgYPplUjvymmimRgE65RtyamECy2Wn5JAzGCnXp9DNkogoyTORvyMS0/xwBcckRAnpwqt52nibZYLxDcldDeHOgwQTHjfTO5rhAXQOD2BmCnWe4wrubcEcsrx5IQHEJUJ4EaE6GoAGZcIJoIb04YFtKUB6kxCDgLYyDIYPNZ1rW/jYkDa6pFCeJ0bdGEE1FABjhJPPWYAQKUCOJH5+o8Aesa6ZzWlTBCGAWK9H0Jdi+vDrRpo6LGAapW8nt0Qbi+GTDlWkl1J6WS3AEoGiUROiZ7IJVrPcQKP9jT0gAE2mQtkHU/UDHiYDY78RK9dXX8SjCTife5jVF/jRV/1PsixghuQlCpSBTWVlN8PQsQXWpw7hoGX5Uu0LwrIZgk5VoiWUpQJLSFcKWETC6sBm1hK+T0OPBjy2mwIFB3nzZVvp8pW87cNuLaL0sIpHnqcFEh7Ar3nS8iSf6/7sxo9XdfsVHK5W4LUJnb1c2z+6uOQOY2mo30F0yvRuAF0PqL5jIc06I72NFxsEe5rBBOgeZ1SvfhQIO95Cf+zIYQV6D0ewjUNpGEZQLSvEAxI+o32Fcom7SLmGwuJW7FkIMcK6vkEn2j7s3zYOZaxHbfjdtyO23E7bsftuB234/bnuFknYN2dHV7u9Pf/d7U7l7GBkiAbORRNgWTfIT6QUHPJYioFBN7UyIaWEae9ENmaQeO6Qu/ZEiZyaFxmYaINGc1tfShEuraIRprYIexTVlI2HIQVdfF20WWEKux7WVnkMD0jkH3OI5A5MD7HQq7hiw3KD3Ww94jGcz9wHrOTjJDNNgQm9xikGyWscjUpymlgdppp+aJjcfRJ/Jx67qMvXmqjUkqiiqZA3iGdDQDCvkNyQ9ZZifhAQBSUIQCU2gDA5LM/GQCQ9SzyUznKtkW2ZqAmkgZyJYEB8xMWNrbIexaHDzuI2MAkto6uTe4G5vflcA0DGzlMTzuULcINslUL07YI+6T2zE+XKNsWZa9EtmLhNDC9y8AqYHbGID9ZsJgXgHjfRxAOHMqGwPB+Fpnmnds79PKbdxCMBaafxc+Sd/j8914hkS7J2menkuZkSwKDr6D/yHyDRdbD+wH3Bx9E7n1z5uukas1XKVcqWgLjLz0PYYDDlyhc/9Yt2BAYe4JatmwxPWNrAhuw8GRJNxwu/rNNHD3MqFC27OpMQ5kAo3sFJmcEbr5Mw0QCZYyaEDjdUJAlcPNT2VfCscXk1ELSk64wZTw5S0qSNAQa1NfQNSz+Dx3yjqijQADgYkuZQOCQnyxgkkV0Fo7RGRM7ZCuGr7NsIBxT4k7Q4ExYEqEm95b07Gk5ylJSRv9s4G57z7xrceKHt2FiSqmcZgaHpC2JouXQ/sOI8A/fv2VBaUzRoddHGVMKZ0JKW6JDXnO2So8hJxckPFLcRJ0J7T3DaLiTQHw9wOHL6IsQjjztLSMIAgBmp9i3dV+jucuo1fjTH+C9N4zABxNg8BAwugeYfnJa03j6L+HDP/zrL0PZcNj/P0L0nitx9e9vwUQC2TKv5+ilDrOTAkWHfeHgUYvha87DhAImYvYnWxIYfPkmWr/8OJJ3PYGiDex/wxbiI75G3mamLGsr7H7TFrIl+j8dPBxg/KXnMTklceNbthBMHF74nk3sf/3W4nk0JbIOqYvjuwVmJwRMxP/ONxyG9yhc/Y4tZEsKF//5JlQOZF1KIcdfch4m4L0a3sdxVTT9vTsh0H8x55/qe1VTc4lsmZS2wUMOaiYwPgekd+WY35uj7BhkPYeybeAUI+9lw0GnnBvznkN6NsfsoRRllxJD2zAolviMypbD+KEc1759C7O7S8xPGkzPGKSrFvPTJU03C2bnsrMZihbhFmXHIFs2LPouWHhvlkqM7yeQwHRonpmvlTXkItswyJcIttEjCZEJwmv83JauGZSJQ95zGD/AYvh01SFf49zIAn+HyTl/DU2CaqroagXtcMp7bDhGlcWJlCQ3gVq6bCPem6JJj7GiZZGuMpvfuOGY5beMKmdLlIzKXMCEwHyV66dTlAHHz8a1RNaGJFMGBxoy531TqUC6wnVETSUGD6I2PwxHBG7IgmukHGkEY0bH5cB7es0k5dKWIB6RUS4LyfnEaYdyleCGyTlvmrpecp46m2J2X16boZZNh3AooIcS0gjMzpbQUwnTIgBH5oQeVHOC2g9hY4dgLJkVHGuITEH0Q7SeC5AfeXhBSLjK0aflpE41LIpBDLFHsljZMlAziXI9R/8VBebncpRdCxdZOOFNvdslvWweyFGOQjjtMN+wML0SmGqUHQPXMJj2E4jlHLO7S5Qth/REiXK5RHCkIFcz2HaJYqlEvkyyXLZq4I4iZGuGhNSZhMiUHzMAVrN6/nexRbrO95mfNnCakr98jf3aLRGmAK9yKboG+f1zpKcLmDmpW045ZOsGdi3n7wpAjRTKjkXZNSiWS6ipJLG2yTXd+M9nEgfbK1D2DOZ3F0hXSZ1TNyJCjDolZEoZoQstpncbfpYEMG0/pk9SJuFCi/woRrFSwiSe8tlXlL+FBNgUbYKR9Ezgoz/7Cq4xGQFKEAToOK9gGD2ckdbXKum3lFiMHrCQ12O4wCEbxsjbgvvBYQB48JL0Ju+yzw1VseHJZR5EZMMFLRVArRKarUsEM4tg6pAvx0gOSojtpyAzQwLnpRGCuUUwLuBCDf3v3weVuYWMzZdg3FZ+4JfXCsghC46BvEfQRDCl7Nm0CBrIlknF1X0NNRcYvbio54P5GrNK0YCwHDRLjO8G1n8vgFU+G6odXEAfrfSuAvl6SRPh0KHsGqgMaD1LmXyxdCxj++PaHR92ZO6dp48kTAKM714YOQqH+kAAeNlBScmXU5QmHXyyhp4JUqk8xtMkDtmKp2lVMracNLO8S/xeOPDv7xHQohQIx4vrytYM8raCDbmBCUeShDMJ3P2PtxEdchOQrluUTQACCEYKwlIXKXNKehJvQhqMJHQqYEJX46crapyJqQe1gYCeo07Xz09wwFkNBCPKFoquw3yNG6fGnl3QanyLX4goI5hzcSgbXLAaNwTUTEDNZW0q56aaiN8BNemyEICv40n2JMqOgcwlYPicKslb2bYIBoqHqZuadTqeBlR2vDTOI13rZ1cAeubqDXDrmsXHt2zVovme9wMAmrslVMoDXty3WHrrDoJxgfaVSnLm6pqP3rMWvWcNkn1PNJIC8ZHD0kdKhGOHM9+9DRtQGmQCHoCWPmqw+n5OvsH0Flmg9ZK8GRfWcMTvR4cC7ReA7oc58TSvEiFcvX/zukOyByw/Y6Ayykw6lyziQ17T6vtLnP6PFu2rFo1ffxyt6x4b22fNmsyZXgaAcHz7gUtOSa2Ss6rGi/3WNC3iK0F9uKlQ0KLg89UTVT8zp4kSR2hRNi1EquoJFpZyB+FYx1U2HZqXJWxoa1lOdOQXhgI1scVWByBHuYppuPpgM72L2PRsyW8Gwc8Y73P8qhyY3EW5Y7bCWr1sySI8om6e9QO2fs+ysahlKxs8pOgZEPYpv+o8yxoup4DGLtHhABDfVBg/YHjQ8rTDCj0tStR9tHmV8qbgCiMIjT0L6fuXDdgPOxeJSz/zL7b5jBXQ+YULUBllcOEAiIbA6hMS3bdfQJlw89j5hQs49f3b6P08pWfzVz2Ks/9kG+v/ehsAsPEj2wjHFsmRQe/nd3DiX1ECF40X6OrWdYuTP7iNzuUS3Y8A6z/Gv00/71EsvXUHrRsFokOJxg3W9yQHBut/wA3Qqe/bRnLTofMLF3DuH+xg+cMlVn9qB9GIAaZKXhcfUB7a2HMwkcCp79tG76MWyx8p0H3hdmM5G3Azq+ckbdkQOPGEJd5+pCkPywSCEeUSyPms9WRR7xdeCyA8cjqYsL5ETbz5qwNQsB6J+n3Ov81rNK8VY41wzH6ujgII5yUzE0UJ0Jz9SGTcCKsZA2jJ1QDBWEKkCnoiPcWL1xoOJPTEj4WSMk+Ah2I9E9BzUR/+beAQHCmoEYM/MEDrIg2fZSEo5ZsLBMOKYmjrA73IfR//aIMSsUp2Cs43okB94GcdH/uqLAE9Zc1K2XDIu34MDCm7WflQiXSF68/sJImQ1ZhxkhRFPRWYnRRoXWGdkp6zhss0LNoXUVM8ZQHoiUR0JOvaR6s5hgOPxQ+GfI4mcmhcoiWCGkske/x+vC+RvEDpUesi/6b7/gDxlRBuGGLpfZRVxTe9tLBkoHLpGUuZleEhrPpZMJSAJNFNzQXiGwrx4QLbryYS4UAi6zkaswKUR8UWLmWdlpxTumhahuusdpQljzX0AWtG5EwCpYBr0PwYOfte60OcVFxIPD0KSqmEpXRLTBVJX4aSLZGUEHPFgNNkUbejx4o0QCfgQkuyYGBhEwuniUx3gYMtFETha28rumop4RoGQTej5UAhWHs2V4B2kGOiioOhArzpKjxJVXjSG8YBiVyO41h4wqHw870LXI3vFhn3Ri72AYRUEuceOqipQrlUwkkHWAHTslD+56IQcIlZkEBBpPT6j20z+Go53m2Dc7xJWGfltC9DCPhcs3UDoS1k5g/aMxIm5bQy+uR7q4mCyBTrUbx81TT5eaBcXdPrQssDT7X9EA4ucvwM3uA0GLP+U81vr1esiGl5R2C6rnwZhA9W/IWXQ2w/heioRP/hHqwWEIWBaYY4+qpNBu0rGVuVubglg1Gt98KwZiccUCbbuMaau3SZgUJRCohGWePkq4Bq0KfMsUwWEvB0hZJyl0mUyyX6L+EeOT6QKBNA+zo+fag5DhIe/NVUYnI3gzVlh9/7RJuB/IS+/jS0YxnbcTtux+24HbfjdtyO23E7bn+Om/sEZGzuz6qMrXnDIewzmr76/hKh9zaRpS+s7gO9X6XfhZ4LJLuUZCXXtC8ud2jeoHxFz1CTz6Ijge7ztjZ/1FO+buOaRPt54MQPb6Nxg5E3PaGXQNEkcU2PJE78vwJlIhCM4DMM/Fn7BeC57z8PPQeWPwS0XyCdafkPJBrX6fUhS8HoQ86I1Ikf3kbU52sIR/qRDRZyNeGLAgEvUfN3MdkFmtcos1EFMwDNq4ww935+B2Xio5E+Ah0fSJgGIQzBRNZGp7IUmJ5hgbbMSZ0KBwLJdQ1pWAwbH5CiFgwU5ExCZkBylbCCYCRhEkbqhQGS64QsxIck7xRdSiLCgYSasfhdH2o0r98iIwyA1Z/aqek8t7bJq88j+5xHbvPfkYYmodHAofkrNE8U/+UP658nR4vMUOudF6BTh85lZn3a77gAJ4GiKRH1Sxy+YRPLb9qByh3CqUX7HRdQNCRsKBGOHIIJXyvZl3VWsTICDUc+u5B7eUiTUf+1n9i57f1hgbhv0fxVXmv7osP0hEQ4dMg7wPSEwuA+jSLxZL/xokgx2XcIJiy4DkdAMDF1ypz3grQ761P+yx8Ayrapo5eiYFFnss++7JRDMOJniQ4koiOB8FAh3lWIr4bQE2b31IzEG5UyAxEMWOi99EGBcOQQ72qE/YUpIcCMWnhE88vWc/xm6xJ/JxhRjicsIRUA+yvA4kk9Y6G7MIxmR4ekanWeA9bf683cBoxm6xmgfHSxOJkzMp1VUWdeQ96hd8h8ldHq9R9lBsMqoPu8l040HBpXlM9w3p4FDUcC8eHCDLSxx0hYMAZ0uUvlywABAABJREFU6pD0+RDW3vqUpzI6FP/XpyL77EfQfseFmtDW/RizTfGRRftKWXtjrf3ETp01qdrwteeRvOsJTL/oMQCosz3jswpF4/bps/Frj2PprTto/9IFqMxnAn/rSUTjRd+Pf4PGvEVTQRq+Z9x3KBsS4XuehNXA/PMfxcrP7CD77EcwfM155E1Z99vlN+1g8urzALz8z88l7V+6gMmrzyOcWJhIIvxPH7z10hCMJVb+QKL7tgvIlxi9bfza44h3FcI++1fjRiVjFAgGqvYlM17OtvwhZoVal5gNkZ7aF4yYRWlc1mhfdogOWDguc4Giwfsd9T1xMRdoXiVJUxakjrWuLvyxoj3lzUn5+YoWi/rDAaliwjCbEIwFiUkdRvr1lONIFsxQOAlY5RD1ZS3XrEAaesY+u/5j23CSxtBRH5AZ0LzOzPrG4ws/pyqjpKec+6MjZtwBILlpcO4f7mDpAwJLzwCNXYHeswbLb95B0RJo7lsk+wInLhh0P8rPdeKHt7H2Xy3KRCIcAZ1nJdb+0CI+4rp67h/uINnzffUFi/iQMjk14zgrG0B0qGBCgeRgIb2zEWmUnecJW2hdEeh6P974kB5i1VhuXfVF3lPeR5VTxl02HHofRe3TNDvloKdA+1mF6WlPnxvT4Dlb5rOZnCbB1Cqv4Ai9AiRi9tsknDdM4jDbYJYtHDM7VLQ9Ac4vM/ENDeQS8S4j3ypj5kL6TAisIOlvLLHyfq7ZpunVA7uaGS7vezff4NwlZxKti4y8wzFbEB4oFusLQjNkDqi9CNEhs0JiTuhLdKCYTZkpOOGgJt4MtWDWBEb4bIygV0/Kon85Z8RdziTUYYBiQjqnnnDN1SNFv0BQIqlSfs74RoDwQJEQZ4HwkKCbKlovLMeVnNOjTafMPAHezLlDObooJCl/BmhdUkh2PZxDEFJ0qyEnM/MS6kh7kp+ACx30UGH42vP0uYoNgpGoMzRqLmoVgZ5J6DnHVHxdQxyF9BCLLWQqIHNCRYRhJhWO65wo/No3lIROeVWDmCs09igRV1OJ+EBCTySkAaLdgFk2K6BG3t9wTu+8aEDoUbUnqObGcOQQThySQ4vg372X88t/+gPIh18MPSsQTizNRJ94P0TBsRuOF2tP9XpO3iJHr+SZKQEFKneIDwjr6D0j0L5iEPY5R1JjxzmMZE6/p5hyjgv7As0rzNqUyyXURCHaJUEw2fUwnT7XWhM7NHap6HFzVatjOs9yj6hmsl53P5F2LGO7pY3uoRRsftJidFaz5uME5VdWL9KPAFN0s1PWI0OJ8g3HlHUVHcrahPPyMAfM1mRtJFgmlCXRxFDg4G9sYnaSkrey7ZAvGaYL122N3yw9NlaWAjLnRJx3eIAoE2rasyXWfwxfBOQdoOiyvqHC/GUrfK35hkO67FHVCZDsL0w3hQF0SkM/ACi8vG2+zjqT+YbD5IzA6k/tIFte6OfzjkC6ZjE5xRcqm67Ww1tN92QTOZRtW+u4AU/aaDlkyxZF2yJdox5dFgLFcgkXOb5Px8E2rNcCC6+r5vuYyNU1USaxsIrO3NWgDUeirmkBKGMDmBZu7LnbaGytd15A/4EAk7OLTVzaU5itSZhQIP+sR+rvy9Khsb841ADA9W/dwnxZ1bUHABAfORSJgFPczKevfLSerABOXPG7n0AZs76hfn2PTm7sUSJS4b3zJT+hjByyjsDe39pC5A9Cg6/YRDR2KFoCw9eyBqJoCURD9tNwBJSJwMkf3EZzr8TB39xEsPOh+tmbmHU6wYQbh7yjENwiqSwTLioiFxjdw34nSi7SNqSGuWxZlA2g6FnWovg6m2yF36dpLTcGKqVUx4b+4KGAfIl9gbUJAoOHuNnJl1hPUdHN5ms84KoMmJyriEgcG3B+Mxmyrwkr6j49PcXagMld/LcJiWN2kgfLo5fwoDR6wOLeb9/xGwt/A6aUyKAey7xfJqHG2IZcnC7/4y0M7+MYr4yIwyGffzASf6TupGjxM639QYlg7CgfVNyYWQ2ERwszNeGqmgqJ6LefRPrKR+u+XjQEGnsGZUNgts5N4+HXsMZs/KU8SAy+nPVl3bddwLVv34IJeS1Hr+f3T/7ANjq/cAHzz3+U/ewWDDsAjM76urLPeQTB2GD+qkfR/0r+7fSLHkM4KiFz0vHSJeKrh69hUAYA+l+5iei3n8RsQ0IVHA9Va73zAoavOY/GTQsTAsHMYvAVm2i98wLKWEJlFulffult1xNMgNF9lOQFowX1spobACBdo7w473kaYi6Qt3lwLprA6B6JvOswPUsJoywAPUWNCC8bDuOzlGyVTerQTewwuo/yGxNSQtLYYx2dSiljHt/jZaByIQeTBefdilJoEo5NE3vjaIV63peZx9H72pi8WwXTKIs2LRpwVmMw7/LvbvydLWKRFTDb4EFofLc3zu0JlA2+drFk6lo1NecmvqqJKxOJg7+5icGLOS5mJx36Dypc/fus0Tp6UGH8QInrf0Fh9ACDL4dv2ET/RQqD+yWKFjC+12J0VkFPOTYuftcmJnczWJYue1mr4j3MloD2FY77dBWYbfg+3ST1UjgaO2crFtNTDqN7KTufr1vW5Sg+l+H9i7GVrThkPYd01aLzAiU41XxW3c/ZSa7xTgFHn2KRdyz0lIG8+Trl2k47b7JKjbrK2TfUnGPaaUrAlUfX25Bzm9NYyKp9DWPetSiWWefhQtbjiLnykinKXvsv4QZROAHRYJ1kY4/1LLDAytMMCDntkK552qkGUFQofwkx1Sia7FOVwbko2W/0lM9aWM6NwgiYXon4JqWbNrHEnje4F3GxJW3TArZBoqoLHMxyAd0s4CRrGaMjT6sTnjAmHdKTJaJ9km3ztZKyroZFvkzpu41poCwKBmRtZIGSm2jjX4MWHoJm4+Bhowp6lYnzP6OVhxx53LbidRRdC9OhYW0w8Ycp7WhCbEhUyzbKOihRLrEm1UR+japQ/+usT3ICEAVN4WUuUKyUtYRfhBbzkwa2YWgaH3HsO8X+KVOWMMABps16lLLJoFh2qqDsNhP169kAtQwaDvVBpfT7hLUf30F8ZGADAfnwi2+bF2enEkT9guS8Rz4ZasK6K6sX46OquXZ/zG65MhPPu4LWFTnX3KwrKRVvGzjLe+q0qwNrogBUtvh36YndzedJfTQR95wq516vaDuka5x3Jucs9EhBTRTSFdYbZssCk3tL1sVN/+h1/kmbcfIT+vrT0I5lbMftuB2343bcjttxO27H7bj9OW4WAvYOcyAW7n/8S/9/0O74SKZnlAkIX/8qDVPgVQG/jRwmn0NCl2kapqEVkJ4oka04DO+RUFkVRXYEEBhGj/LO4kR9m0wMhAE0ry4i5HpCE0xSOBx2P82hbFZ/6zDf8OaP3sBQz4GsV0WTvKmbj9TpCdPplZHopX+6xeJzyYhivmSRLbmFWVXoUDYY1SwblAIAjPQHE6YzowFw5R9uIToCpqf48/jQ1dcE8NorLwSrwRQ9gOBIMiqjeb2zu0sUPe/zEjFTVvUvNdJwsUF0xMgUtIXx0Qab0MuoaDuUPRYfulaJwKd/XWIACczuKjG7u6hpcQBqI0phgPFZ+pHc2k78q+3bePYqY6YEAML3PFl/f3xGYXC/wnxZMrq+9TLfb1wduZ9//qOYr/qMTEch7wjM1ny6PLU4ev0mhHFIX/kopqdEXaif9xzyDqO243soZco71Qdg9s0pARMLmAS1ZwAAzJcpe5yvScQDi6xHOlLeET7LwX4wOa2x+pM7mH0G+3SZsMixTJghyZYACIF0+ZYBH1nYBiNcjV2Sl4KRRNE1KDoWpk1yVHqipOSwxw5hQxrdwgJF26JYJRHLJMz6mI5B2S0ZVXYs9rSdEumaQ7wvUPQsbGShZouol4lI3lp+0w5CbzRati0JT0ss3HWC0h4nnZe0UWaiMqDzAl+jsUuTzGjA6wFYhB2MBC7+s03OB9XtFczCSA86EJaRt7AvEQ4Z1SzaNGKM+gLpqkDrOu+BiRlpTk8YWJ9NmW+SxuY0kK4B0w1+jsH9CkWLWV5ZAgcvW/gLmLgq0hYYvuY84nc/UY/fog1MTiuUMcEWJl54Ao3PLPpI/pmvwOSLH0PRdEiXfOZpbNF/3SaOXr+Jm1+3ieTfPOH7E3/e/8pNjL/0PDqXSwxfcx7Rbz2Jw08KkbzrCSy9dQfp5z2KtCeRrgTIloDpuqw/Z9W/so7C0lspl2vsWZSxQPzuJ+rM0PxVj6L79gsY3E+zvOlJhdTT46YnPJQkuT0rNj1X1sXsJnaABS7/4y0UqyUzhWsGJmJ20LTZd7MV46OmDum6QbbkYDZyRo4l6WbzEwRoVM+uWgOsJwUpX9BvNTPuJnbY/YskTJYNePgLiUzFasG5MGHW0voMqYktyhavybYM0pMl+6ADypUC2arhNXQLzoFAneEsWj7jECzmQBsAtlMi7/B6sxPMCBYth2yD0ebJWXrMVNkjGzpMzlpkq6QlVpNQuiQwX6Ukr7HHyHQllbMh10c9VPQeuu4zTSHhOq0rlDxXUJ/5hmAiywpEhxwfsnCQOaPKTlMufvQSSoHKhkPkgSpOA6MHSh8FZpTexCRlMTPBz1DRKouORblaIFshPQ2SmbzJGa7LlUdclZFRc0qbrKJcSXlQ0c1PBdqXOBfAcc0tWvSaKZuUsuZdi+k5Axu4WsJTeYrly+a2uaJsOGCFtC4wGQFRSrjIAkt5PcfYhCbS8wdTZn5KAdUpcPAphLqIpRz7n2ZQ3JXBrXDxyk8UsDH7VNkraWLpZV/88mvnSgbbKzG7p0C5VsDGjutx4ADpML0/J+wlJN0Ukj+H9lmYlgGcQL5igG5BjyMPMUjvzjB7IKPUbCkHPNQFmp8nPZtTNtY0lOBlAogs0CmYkVopkJ8qeD88VdMlBi7gPgUjDdeoKE8OtlVSbhiiBhCUJ3KSbQPLtaVXwjYMVKtA2TXITvv7dCKrr801Ssi5qrPAKAVQCtiGhemWmN2fw7QN5FIOvTbnHNLgV7nGz2S7JaWkqYKLLTNGSQnT5JplAwco7mPyNrN/CBwmL8pp/H5mxnvdLTnHeJk4PamYhbuVTikNr/Xm121yDxAK2Kc/jKyroB56wPfvCqpz+4b9NvqsN2m9lcb28cmMvOdgmqTSZSvMXMtCQDZKCLnIWuY9/sw0HNJlqoXyJUpFs2WL9OEZxFIOPReYrzs4xXnAJPS+AwDbLmFPpTA97gXknPCt8Ij+SNnqJ374OJax3foHObW6shQomqh11BUB5tZNsZoq7ypNok3lOqvnlBzpmdfqCm56KowmwI1cJeOxIQlcRYs1QxA+JR55BK6juaksKCeJ+gLpOk3ViubiNfWMUrWijZoqZRK+XlUjJPMFWroa2NEhayNqV3LvON++ZhAOUW/+qkb5wUIO5+rO/nH4QiugJ7L2k1Q5n4iNgPCmgswFbOwQ7WmaVAJILgck9gjUi5iYaMw3qJVXAw059wStsarfT00knADkIKhNYXWf6WCZ0fDq4z9D3hZIT5RoX3ZY+Vlfq+BlPgCw8rRD8ReIZyxaXCTTVdY5VM0GlaGgwPiMgth+CmUTOPokgelJgfwzX4G0q2ADYHZKwAQCWY99ZnJKIfqtJ1HGAoefLDG4j4aU0w1PGssEor6sF9DpSVHT2Mqmw2xdoGxyc1u0HDK/Yc26AtmSl8lYyidNTJNKPQdWn84xX2M/mJ0QlLGNzW2fyUk+L5VTFiXsLQM+k5BTUmimp7lxP/d/71BPmws+l4nGynu91nqq6gO8cDxkq5lEfD3g+8wFimUDNdSIrwWIjiRUKhH26UZuYm7YRS4QHi1M86o+1thbjM3ZFzxGmqEVNbJTGB5wTMNC5TwolPGiD8gSKDoC6ZL00iXhpXeLYEQwFrUGvcLbVod6UXoZU8MhXTMkH3laFclpDpNT2vc7Bz0VtTEpACQ7vvDAsT4nXSGRrGxQs9+8rCALh84VvmH66S/FfN1huq4wuF/j8GUC1759C2XD4fBrNj2eF8iWgGyJUqL40OHg4aDG5k9PCUxOBZitK2y812ByN2V36ZLE0ls4FvIu5bUA++7Nr93E4CHWz/Qf1Mi6EuMvOY+iDex+0wI9bSKBvMnN0Hyd9zH/rEfqBXZ0TuDat21h/qpHcfRS1lRc+3bira992xaG92ikr3yU0tQVgXSZfTzrCWTLwNGDQS1/qpqaKOQrBsm7nqB0reEQHfmxslxCZNTdO+1YN+EAmfFgatvcvJmVAi6TJCJVyFU/f5iIB4OlZ3hotjGDR9mqretJsvtS1hUImtXawKHwMh1hBOREs4ZmpGATLy1ukewEL+ERuYSaqFrWJqbsNy5w3OgpXofMPHksdov6I6DG66uh5nojAQQ8ADmJ2sAxX606MyjJmvt6ykoi5GVXquCBxkT+wCxYK5QcWGgvbXQBgwh51x+CKnJVj7LqSoKT7LG2RXuqFGtoBMomZWV6yrqbaIA6kDI75a8jY51f8yprOvSRRuOGRHjE+qVgJH1NrfCyMgG9H9DoUfq59Mjjq0vUtZrGS8NNwk2VNPDzj4AseU+CKQ/Qka85kqVAsseNetGmrEt5gqoNuL45yXurh5z76oDhWMKOAwRHGiKnlEpkJJy5ia5lV6Ig4VEehFAjBaEdzDjgdQ01XD9EeKiAcQC1G8GEDmqggcCSrjehDMhlXCOFEay/KQVcPwRSCTlWEBNK52A9CbIUCPYD9tkZr10dBgiGCsLXw1TfF56gaiMHmyuS0SaaNT2ZgB0HQC5JCBxq1uJMNMmbEwWbEFMNy88ujICYKKgjDQiuGzYA9FHA+6M4ZvQhnysszXCLrq//nXlaXD+gpG6kSBCcK4hMwkxIPRNzT3u9HOPSP92CHGmog5D7t+pw5tc7OZccS0cB1FTC7UUwJeV4wpNixVQDBWmJLrKIdrXfmwjI/cgT7UjNg1kQBoMpa1NgBWQqEb2vWdNnbdMAlfQxZoCyQsVX8n8TC+h7zwEAon6BrCt4yBGAiwKUnRgmltD9OSanNLKVGKbFiO9tNff+euwtweBqbbMKmH7hYwxOWNahwXF/YUMHNwqBsaY0OCZRL1vl3CgL7sOaV7hPkaWAmQSwGQ+Vyb5giUjLeoog5wBkEmIvgpjTHLyS3lfz1a21RXfajmVsx+24HbfjdtyO23E7bsftuB23P5ONMrY7y9Tc6e//72p3fCRzDOzVBmZVQb+JPc2sEJierMgh8OZiLDKsih5nG5XEBIhv0iuhbALRwN12egZQM8jnq6L29dFTkidkCaQblGLNT3ujzTN87YpKIQ0wOSsQeJO3YOypV0cCZcP6FCjqIrm6AK/l0LzGU3rRcj5rUZG+6K9TRvSAqbwZqgJqp/laUZ/FmKtP8+/CMWUdVcG+C3lqh2SmyEkfmWgbFB1fTJoxG+UkI2rze3JGhXxxoJPw6WyBbIWvawPU5l+VZ4pKBY0eewUzAQ1XRyfifYls3SCYLO57cmgRjh30RGHpLTt1tqb9Sxfq38nbAoGnPlXyPZUD0cBi9gWkV8nC4e5/tIPkwMJ6IIEsgNYlT/b7t+9F61oOGwLtSw69n9/B8kcMgrlDfGgx+PJNtK+VaNxgZmL5TTu3GOkB6ZrB9O6SJJIMKFrw1yOgUwIKwgHQuA6o1GfqhsziBFPv2SOY9XNKYL4GXPvLAeJDRjWDEdDYtxifYwrDBYyeO+nlIwIIprYmtgB8HrZBk8/mNUYlP/YjjzHV3Kc3AYRDtix84SjljGWTEZy8R3lB0bJwiaFRmfeaSE+VSDcoCSlaXu5QepiBf+ZV1BRg5ml8Nz930aWpaNmwdTrdhpTIlQ2g/Zz2hd+Lv81WWGzqpPeQChh5bl9kBD3ZJeXvtqhXzr5Wpd0rXytRCkRHCk6x6LKSrAELT4RKDhvfFEgOP87bSS48FKpmY4uiTdlW3vAUpmWJ3oeBpWdzdJ83OLFj0XmBr9XcozSrfdmgfckh65LApecOvWdN3be6L1gsv3kH0ZBePRtPWJz9p9uIRg7915EW2L5ssfpTzPJ0nifx755v579P/cttyNKh/Y4LWPmgwYl/RZ+d+DeewPqPbkOnDsFAovscaVt5W2Ltx3cQDgXOfuc24kMHq72nydzh9PdsI5g4nP7ebQRTwjpkKdC6bhEOOdfomUPrKqlE3edv99kBWKw9f9WjcMohHEjOXQeakeWMmVlR+D4pGVltXBeIrwQcTzcDRsULFjpDuBoCAMd5uf8Q6swkKWj00JAZo9xOOUbsFfs8aU0+4z8WcDGBM6JgoXV4QIqUSJm5l3PJjKoHdrjQMqM9YxZAzmU955nYez61LCUlM5KwgrHPzGZgBHqsoVOBcCToVVYAyTXti+MdYS9dUxf+qoqwBM4peYdAhGDiASdjGhGbiDIV471J4gN6jeVd1MbTUZ+v6ZSX3WrK54RZmFBPzxCcU3QoPwyHzERlSw7haJG1LZuuzoo7zTEmLCP+FTSiTChtCwcsmKY3GyEmFYBAGFF7ytmA33OS84vMqZooG5TVZGsWsw1mWWic6OeaNudUPSWAoDI7taEvQi+Y0TIJJWT133VNvSsRjlkxFziS00ILRDTWrrIYTvFRuHIhYZe5gIssyrNp/RlUTvm7mHq1g2Txu0glbMw5UHULSsjCRbYMznvwVMX81hvDpt4baq5qCp4rJH9Hutp7BwBcbCAqgIAA9M2AheRDxeyl95fJ1krKkMcSUKhfW/eZyYEVlHmtFN7zxvh53Hn4Ap+RSSxM1wDCwbQMRC7q/UTlJ1gZkQN8tjKVzBblpKSFI6odwhFglwrYtRz5soGa+PoC5UjztJRrwXv3uNUcUjoEI0WPnICGryJVtZFtfnfG/UkpYJYLiEJSvhgQ1gMLqNyDU3Tl5+MwuY/moqIUlCD67FLRQb3ehSOqhgAgHCwyHPI//gF06mAbIYIpx2OwP0YwKjG/q41w4hDvTqEmGWZ/7bF6bwRwDwegLt0AOMYB1GolSk19P8rpx2c14CIDuZzDCSC5rukZeSTZ733Ge3aSMrZipSRBL1WUzd5fID4QcE1Tq36KJQs1p3mvaxmSWedUw1TP8jaVyR02+wl47Nxpjc//rvYJXWUlY2nsMdWmUoFgyMGhZ6gPNdVEqacCeqhQtIHkgAtDTRoLqtSjQ9YTyP2kV6EK6TgNmIRoUJnTEFFYysKCoYQeSyz/AbHE0REnUVkSt5ktObS8DMtE3tBLclMcjDzO1PJarWZHSfY50OZr3PAlN336vzo4zPnecd8g64l6o9u8Xt0fygBM6GlEd3OCyNvcSFT6/mBAGZso4bXpvIbkGiUIwpDiAQlvLArEV0OEfUnD0YyHLqf4uV1oKSHYlQgGCsFEIj4Akl2+lkoF5CBAdChr3KwNKeXTI4XmLg9L87+6IDmZyOHaty0kOIdv2Kz/f3zP7f3CKR4ObEi6FLA4FNhAYONHuOELxqjJZwAwPRWSONegTC5dkphukOyWHHKGCccOcZ+TVNvXd2QrDnoq0XqBkpRw5GoUKwCIkppXEwHNfXsbba5qRVNApeyT2TIQHQFLH6LUMhyyFqnx648j9htvE3BjbgNQfjFBvXjWraRhHuBlIJIO9tC819Wk2blkEfUp74gOVa1jJ+aW1xpfD4gIT5nK1wOFYCQRHdCQT/XZV1qXQbPZnNKfykhQTxcSkarOS09kXbMmC4/P3CPlz4Y8IOoUHjdNfb7MedgpmqxLS1cX16jmDvYWs1xuVoHIBwGEJ9clNzmGV5+2CAeC6PTxx9H1/KYl75KIdWsLhgwU2Ij1JqtPc6PLvwPav/k0AGDpV55G1hOYbgQoE4HGrz+O9jsuIPTXQ7rg7VNfNLIMXsxvlwCozGH4mvN1nZDKXS1ji48W0sasK+sD/vhLz2Py6vP1QSjz7zX7gscw+usMGoQT62lPPMxU98CGDoOv2MTKz+yg+auP4+QPbtfktGjkcPT6TURDV5PbhKWMav1HtxeSyj/GQDsYU06atyU6H1O31ES6+hlFRwtjYRuR3iUNneVhaSWgph6FW9GXVi3KDk1go77/OlC1pj0+8NJKUOJjQ26sHFAfcioZsA2A4JASOtZWLEiZMhULw2rLwJKaC+iRQtHmZlOPfP9v8PV4f/i3VqHexJYt4qYbe6wLCkY0AnUKaFzW0BOazjZuLA5IMqMuXs0E4gPUz0SnfqOpOJ6EoVTNRBJ66tC5SEPnasxbLdC8zo1vcmiRHFpimUPWCVQGqQDnorxN/KxJOFacpta/qoWNBosATu/D/OzxgUCyJ9G8woNAdMgDXjASiI8E4n0NG/L7yQ1Ni4bnJaKB8JYECwR9dCDR/QjniHiPgYqNbT6LcCgQ9iWiPp9R4wbvIxy/oiNuhKMDyhyDEW0kgiEDnMGUZLLAm8QCfm4q+fmEoaxQGB6UUUqog5BG2zOJtScZqLM9moEGRwrLH6SjvJzQpLPa4FM2K2oZoxOUMjrtoId8f3UxRuDnYzWTKNt2IdmUqM1yVbbonzb2m8+mreVrRFNzzyMzCdUPgInmAdfvIVzCOjOn/eFfUvafXNUwDVuTyYQByuWFa7uLDfTNkAGEqUJ8U8I2LETOa4PzksG5RIXABihTrA4Ewsvb9ER6iaVgvc2U8jOnHLJlktlO/sA2xGhhfm3iRQBKzwQPVr6GVOWAm2mIywnKpoUaK+iDoMZVI2BgV+1FRG+DVDg95vom5gq2XfIgGnIuEZmEC3mNwVABFdHNCiiPGI+O/MFBeWm2n3ucBsrnL6KxT1olADglaSCaFTAffY6XNSl9kE/BhRqNX3+cKOqq+derrEdubSZ2aP7q4ywbmCpitAcMtIYjATFTsAcR9IwSzmoPWe3nVCqw8aTFfAPofCBA51niyq0G1v+zhsocWs+Ei0uZsX8m1zT0fsAgZ8w9bu8jqA+Ln2g7lrEdt+N23I7bcTtux+24Hbfjdtz+TDb7CWRq/rTQ2O74sJOvWHT2mNkYPsDIdt5xt6REFxSMKp2Wd0iq0KnG+G7UciknGWUThpExYQFdRT40o2SwlN+UCc03yxa54tM2oyfBUKJYMigTDVk4FB2m923kkK+WaFwMMHjIYvQ9m0h2gWKZhmLZellLLYzwpDUBWM0sUP8Hz8NEDgJAusLIgTysoq880adLigSQlaqoGRBLwnsOAfFRlVrn5137iR30f+xRuMp3p+eg2xYusCwW1A42cUhDH0nKmQqPDhQlCA3P2s8kXKtEUTDqBUXoAqxAsVagTHTtX+SERHn/HGYcMMqzmsGMY2RrBiKnFCVbY9Hmzf8DwO8Cye98AKO/ezcpPBnlCZVcYuWnF6aLlfEdAAjnYCUzdmq+CC20rhvsv3EL4Yg0tfjdT6C5ZzE6KxEf+ajkyCDracR95z09BHrPlchbkjSrN2xivkYT2+FrziMdXuOLG6BsWggrYUJeT95aXJMNBYKxg5MC03WJ09/LzFLv53aw//Vb0DOH5Tft4Oj1m8iWgOZVh8ldAu1rFk6wcF04gcFXbCIfX61f1ySeVpYy+lgm4vaCRu19ERIDdTGkBCQAnGBmx8aM2u09IgE42LUchQg8abCSEbF/ZyssUm1cl5h2LcrIQjiBogP2hblCuuYgeryuYMJodOqJfEUHiECyXkXpq7KtgAdxNC0G9ysAJD9N7gbCAceRygSyJQs4ibU/LHHj05SX8VEaki/R30qnogZ6BCMJlQhUWX+Vej8fRUnrzZdLqDnf20aUQ9TRsxRoXmWUf9S6PZJWdB0mSwp51+L+v30Bky9+DHnP0veicMj+8icBv/fvkX76S1G0KAta/ckLuPr3t9C6ymcQv/sJDL5pC+GYfa1z0WK+KnHzYY27/vl2/V7DeyTCz3wFWr/8eE0/G77mPOIjg/7rNlE0CQ448R7/B5ImnaMvO4/OL17A7jdvYfqNW5C5Q+NgMR46v3ABo79+HslBCQjKKMtEUCr6mvO1h0z/KzfR2C8xulvDhgLuS86jaArkXZL10lc+itE5WQM9Dr+a3lHCd8T5qrrt3qUbBu2pQPdtO+j/s00EE1LwzFIBkTIinfW8tKeg5KeKluqx8rKmBRjFRq5+ZsFQwWlg3rMIRpJzS+GzECs+c9/x843zdL4Gs49lgxmaolVCDiTpYcYDMBIHGEp0TccgLyiTpeTYS579dVKWxAg3o9MkfJZt4wueXe1zoTKBfM3gZlNy7uxZmMZiDNtOibIZIF/2shkvoStjAIKyMuszKrM1iXggkC2722Rn1fianpIwkYUNBbKQ71G0BKKBQ/9BEkXLhvXvTaCCMEAeMRsXjjlOGlcl5hsLw0STcExOXsS+NXzQIF+h9Ctdd8hPeD+SAr54m89u6iPBakpVQ9kxCEYKJl54fjm1GHcqA8bnUEvcIID+iyXyZUPpE+grIoxDuk5lgsq4BlbGpPQYASVXETO6TleSMC+9OrpFDh9YZEtc1xBTqihCA6kdTGCBXMIoh72/4iDGNCF1rRKFUui/WAOwsJ0S+iCAbVmUXcC0BJwmAcx2SohUwTQMRCZRrJHMJlol3EwDoYXxyhNkEhZUTcACzgoUHUq9TJMyLZP48dIqYacKiAxcIdjXNuYIwhJ5FqAchfwbxet2CQluciI57oxAmvj3cuzDZskAuYTu5jAHEZAvNH7yRIrMxohX5khtwsyOBMyJHK4UEKGFKwO4wMJmHI+mYYBUAh0LO1WU2AUWyBSleE1DeZgAisBg/+u34KKSRfESgM+OwgHpGuV3NrJACNjAZ5HuncBNQ9iphmuZGkIlx5r+QZFjlqrhCbEzDZVx/yOmGi4xSFcVVAZ6GE38z0oBFLKW3Rmf8RKO0s50RaDMBOw+L7FsCKgH70fe8kX8YwcbcZ9ougnUi+5DGiukKwGikYHMFynxaOjqLXy1rt2aMa88HZ2XjhdtqiTyJYuyKWC1QNHkZ0RJ4qbVJBTrQKFcKrHyfoXxp+YYPBAjmACz0w5mPYczhBAcPqwQHQnMT5raVNY2LPRyivmAk42ck9w7vscTdn1ZwyfajBMwTvyPf/Hj/uZPQ7vj/FP7OTqPR32B5lUSZHTqB3tkka4sakFMwyBboa5QppxcVcoJX6VegpFVbrw8QGl/EKrS/sIRb9v9KFO9eiYQDCRaz2kkNxQ3nN65Pe47BJ5KoacC7Y8GSG463PetF6gvNUB8XaF9kcSh5lXKeWzIegKZidrUNNmTaF/y1+spH7ZKgUtK1rpvv4BggtqxNtmn63ZjV6D7HDWjyc0FZW7/jVvoPqOx9tanAHARaFxRaLwQsJZDUU7W/ahCcl1BlgLNKwrpmQLNq9zwBn1FKtBYo/mCJj2oWeCuf7YNPVRIng+BSpvbKtG64rD872LogULnOQk3CFm/M+VnFyXd0l1k0bq42CA1dy3alyzifSK/1378dmf5qk0/i0jm5Hc+gHDgcOr7tyGLxeauaArkHSCcWsTvfgJu62UYnZU49f2sPQCA5N88gWBMKY9OHdpXDcqEz3T8peex8tM72HhvDhMJpMsS7XdTruQ00LiuUPQsus9SWhL3vYRlAsSHFqqgw3o4dph8MWVGk1efp3u6J6no1GH5I5zJlj9s0fyVx+EUcPY7F4ej3q/xPRs36YhO9DNRyN23XahNBgEQywmm6E0MJDcWk7WaC7iEOupKCqP2QsiSSPdgImoaWSWREBaYneShWGYSImNfbX00gOsUMKFD53kAimhLYYBowPunUo6xzi9eoGs4fOr9GmVE0ZFAclUhGLNOJhwCSx92aF2zRKmPWVcHR+Rz92NA44ZA5wXKVExMpG+ZOKhKAhU6zM+UmJ5diJxrDO8MaF/kwrH6h6z5yXuLxWPma++Gj6a1webivlJ+evr3Lfa+cQt5WyLeX0xhVc1O0SRZbPUn2WfP/Itt9H5uB/Gh79t7lpSrRKBsCJz4V9v1QSf7HBrinv7ebYT/9r0YvvY88pbE9IseQ/ftFxD99pNYessO1n90G63rpv79xB9oogGvv0yAjR/ZhsqA5q9Q0jld988kdwj+3XspffDI091v3kL37ayHi8YWS2/dQfTbT1K+eWgRzCxU7nDih7Yxf9WjyDoSvecssp5A71kLEwu03nkBGz+yjaW37twuwwCAgH2jqr2bnaQhqT4MoMfcbFUBlmBAqYRpWEQjW8tChOO8SCPOxYG86Bqk6yUpRKsGesjNYNG2NLRNvaSnpJRM5iS9lQ0v0zmZA5Z0OpFJuMDW7upw3ql9pGBalgeTxCK5zs2ZaVrYpoGNLIKB9DUiHgHN8ztcaGtZKUDssigFOs960pN3kK9Ia2qgUXQt4l2/GGgH07J+I+Nx1BWNLWXwrnmVBxhRCCx9qDKXFtBTh+hI0iRwzyG5yTqIdJlyuJM/sI34JtcanQJ6wjli6cOswSrjhWm1LLkemQSIbio0dkUt4xSFRDgSlLoJILwRIBhJBEN+Tzj/2jMBPeIzNInjJsoCratco5MbEt2PLWhs8SHrsiC56avqgfRYIjriM2pd4xorc0rFKkKjNIsNYFXzYzUPytW9dgqId3W9tgoLyEZJGXchSGJLJTAOIC/FQCERDBU6Hwrwote/l3PlkYLsB9BjhWSPhDc50ogPBFDydVrPKcg5pcIiVUApEN0gpjnc1QhGCs2nY0R7GuowgN4PoG8GUF42hJL7DFGQQAfrzTsrPLQDVF8DvQLhtRAutmhclyj3E0S/24Hdjeu+FV4NeR25BHIJWQqu6/uKz9P49ypJzFMTCXMz5nVEFuZEBj3UkC8kxGJ/uFUHORBaxB+LIGYKbkaZXnI5QHxASZs6DChpPwwAKxDuBnBzDX3EQ0ZwqBEMFfRAId7VWP+xbcg5yaDxrqI8DpRl6zmDc2qi0Lii/T5OQHygDTkI/JonSV7LZF3D1L4ooaeS1LgByXDLH+SaqFIBOVXovEBpang9QHxT1Uh3xAZIeDCML1PeFXqz8O7zFlHf1fsrAHABx/Dym3aQ9iTULMd8RUEN5yjW29AzA2kc5isaZTuCyEuUf+VTMTl1y9Y4rlCOi29V8t/gkK+frpBGGPYlZZQl17lwL0B8gybbzesC8a5GsiuQXAwwX5VInomRdxjECMYC4aUIKCTHxHrGNXMiUa6UdSDTXksQ7WuIhFJDWF9Lb1irFgw/cVnZndbrVF9/GtqxjO24HbfjdtyO23E7bsftuB23P8fNOgl7hzU41v3pkLHd8ZGsaDG6XlGvKnPN+KaEHilGg2c+sm8E4n1Vk8Aauw6tK8z8CEs6jfNRID31HilVcVkAT7WgrKd9rTId5I3Nlh3iI8qCVCowerEvrt/gazVu+ALaZf73zL/YJhVKAnmPaVoTevmcWbyuLIAXvmcTesashA0YzWrsilpiJywQTIGDv7GJ+MjdRogKJg5FEzCBwOpP7SDroTZya+wbDF9aYPLZzIaojKngvOsgK768BYomJUQyB+ZrDigFpqcd8iVGFYVhVD5bdihXCtiDCNf/3hZlIxsGzcskzsiRxvgc5YYqp0zFhYxOOs0InSx5L8JDheV3LiIiwcyh84sX4DT9SG71zqmanjk03/N+AMDRq1+Goi1w5R9sIVsO6mLtim4nCxZep+sRVMbXyzv02Rl92Xmka5Sg5U2JdEkiXRLIurzfB39zE0cPhpiuK+jUof/FD/P+pQLpKqO2sw1mB/O2l/GccJivS8zXJMqE3ibjuxgFnW5IXP/WLagUmK8yYzhflkhXBEZ3S17nqsDlf7QFGwCDr9isTUXTZYnpKVKVRAHAATe/dgFt4GcVi7Q7SApc/a8sGHWazwWK5p7hiIWKNqAZGcAIbtmgJMkp571w6M8jM0ZZZeG9lA4DOEU/ID3x2c+5QN5x9TMqOg43v+6Wa/Qc/qrvq5zZjqJFycxsQ2J4L4Ef7asGNgSSm8y83Uqdm6+RRBgesL8FAx+tlZ5W5GUu0jjIzFMCA9SgiYNPIYWxcWMxWbaeVwRfjII/YtymCpr1VnCBcGyR9zhOpicVwhnngPa7n0bZBE1ov+gx7H/9Fg6/ZnMhM9pgAagNOCZ3v2kLN76FEI7RWcZ/bn7tJo6+ivdsdE5icop9Z/LFj2HvG7ew/8YttH75cUxO6vo1Z1/wGGbr2n9mYP/rt7D85p26f+g5kH7eozChQPrKR1EmwOQkaYd5l9crCwINrvyDLUy/8DGky5JF8OCYnH/+ozCRRPftFzC+S/K5NQjhuPm1m9j9pi0cvmET5hajUgCAAcKBZBYyYSQxHAJly8CEDnrIyKzM6eUic2Z/h/eRfpbsMZo9P0GJjZxLoJAwTQOZM9ouLPDANz4OE1OmJAz7pMxB6ZSPQhYd+lmplHOP9FFm7V9DDTVkKpBcZfF8NT6CPrOaYZ9ZIVnS20JNVJ0psmFVAM9C4Xhf018EHEMy55oES+iNHikvm6syjpTPBUNSO4WXzVTSunBI6bMcV1lSzu+VmXEwoTGxDZnxqTxyogH/P1312aOCWcrdb9qCSUjQK723m4kcCWcBsz2d59mfKrlnMPE01Fs87WQuMD9TECpRUEZWUc6yFeuLy1lkXawXzEiNBJpXOZYmZzgvpOsWo/sW0uvpKUrpAJ+VKwgmcJrPMRxKTE4Lrj+K2SPhMzp6ImpTVjgW/ceHAnosasBFMPGytltUlzbVSFcXprLCA1/KpoMeKJiQBKvL/3irNpiGoLRvfK+lb5QDZqcs9IiqBfooUf4kfFapaDtKpAICC6ZnacSqMqDsGQ8tAvck0nmAjEC2bGviWnCgYRMHPfNAocsR8mUDFDR31DOB/qeUlM4V7ENli68VDEhz0xNvHBmTwCkzWXvwyRL1PZSlgBxpiIMQJrEoOhyLZZN7BFFS/kRgAN9LziXSDUNvxHxBMAymzPhJL/usIDZFz4MTFJ/h8LXnKXFdtjUNEKDypuiQzicsyxFs5JjpKlC/LhzqEgeUzEzInM+rggmEhwqTUyQq2oA0PBMt1sGywbXUKkD2A0rdAofsHm680mWJbIk+cEVLYPy5Dy/60gc+jNkJgaPXb/I9Zzm6F1M4pRAczSAcSxjCiQcQfeijCG9OoW8F1aSc08tb/BQrBVDR45rTvM79WHpXAZlK5F2H6Wneo2yZxDyZcc81O23ZB0BpdkU5rUoVICkRDi9FlOK2LMJ9TTmdn4uqUpBkj9nd1uVKqupqkuJxu73d8WGnTEitcrdMUCakjlp6StVszdN3plwo8yWieQuvwY8GDtEhEX1qLtC6wgnGBgvcJgC/eXUIhwLj05o1PbXZGdGsJnYwiUV0U3niEg8R09MOk3sNrAKufgc3MvFNkrCsqtxsuQAne6LGKOqZQDAUkCUPIDJjatVEqAd6tchUG79Ktlc2eG3h0CFdo+4+mADtK/xDnTqsvFfXjulFk5sA4e+rzLmYZSsO8SEXFBs6tJ7TvjaEn7VsepmGBOIrIakrGRab6zV29sZ1LviO+2w2T3gh3YiTC8l3wN4bXlbf+6JBw8S862o518e36ZlbtN2Fq6lmwdTUNLa8xUNsuqQoJdrPULS5oS4TgfDfvtejn1kf5CQ3w7IAnBZo/9IFWK8h71wpUcYC4Xih7ybNhwuyLF2tq9VzPznm3KgDQHzEuqHuxRKNPUdj0YZA1pWYniZlzHqz2vjA1TKq3s/twASLg25jl5s01jRR2hZMbq0V8oeJgAfh5JpC3vYEJYH6/kf7ihtBvTDJq5osBOTcS9rG3FRazf5SjYHJK+ZcNEceG1zy70y0kJLmXYH2RWDtx3dqs7HwSGF6FzwBELdtNCpKojQ0ZZuepMGZyoH1H9v26GmH+aqozQGt9pREf8BymnU41X0omoKoTguUbYfDTyIN7L6/uwM9JaGqwoXqjJu96EBB5vz78afT7ZqfyyEcWwRjh/FZVdOVmjdMLWMbv/JhiBIY3aURTCwaBxbNPYPpaY7D+YbDiR/eRvci68LYH/izbMlvwqbA8pt30H3bBax+oET3+RL737CFMuYhUM9JRqta77kSWVuisV9i7xu30Llo0b1YYPwl5+saiKW3UlZXYYnDAdC64RfLa54UlgDB3GHlGYPmrz6O+MhCGqKmASBrK7TeSblbtlyRuCy6Lxi0r5oa1R/Mbl/w4hu63mBGB8Sf24BysoqA17jBeg5gUZPjJADLjaNTNOu0gSdsDhTlLGNu1uCAvW/cItnKm+AJww0LHElm4RGRtCbi3O8EarRvtdERjvK0yvzUxNxY2pCHERPTgVyl8NJOUdcIsf/xfYu2Q9G2UHPO6aIQNfFQGM7pVvP9RAlMT1OWllylaWm2Yomq7vNwpKeU5gGexgX+fu9ZU9fuQXAMRUcOJuR1zDcc1NwhPrJI9oh51zMvMS35usN7JXrPGsiSCOyaluefZ2Xgq6dA9wXWe6ncLUyjMwE90IgPBSB4CFEzBkSiIy8hEg7ZsoXq65oSOd/gPWtdRY3yTfZ4WKrmATV3NepZFFw/YUnvy5csgikweTAnCl+jlvuYmGuLTQxlcW4R+MuX/H1UqPtT1e+Ed4QP+qqmV5UdAxdxE24TEgDTu7kQl20vtVTA2vuAxvNBbUxpIgc5VchWHGTGYJBtmJoE6LS3f3DEpQuDWk4JgLYOnmRWydUrE1bhDyKkZzmUqwUDAbmsyWhl0yLo5JSI+j5uI/arStI/P12ibDkaseai7s824h4r3q8ObDxsOO1rQSpjTy+Prkzanfb1nF4WFu8pT2P0wbSZQnq6QL5i6gDb/LTHHpdestjkz7IOaXcQi7UVAMqu8VQ8/57CB/lig/mLeQgRjrYLMDzoQjvoucDsL05QtizyUwUPYJr7RxvxgK5HJN7VRpsRZZPJnpeoRr5+ahr4vs8vG1KuPl/3a7EB5EtfjNPfu43lN+0gmDiYZz6GvB3AdLjRzDus4QkmBro/h/yUl8A+/eHbiZbeSFXcMqVqP5fWfT3y6/pEMXA/FJBGQI8lIB3KlsP4Hh5mgqFEsVpCZQ5l29ZktpqiZkkNLtqs/WteVigbvHfRAftwtuwgb4bIljl+ihbX+eBI18/5E2nHMrbjdtyO23E7bsftuB2343bcjtufyWZx58CB/wnS9f9P2x0fyYIJCy2jIxb4Fm1Goaxi9C7qe28R8FReJqg9Y7IVh3hgYAKBsilQtBj9m9zFYm2VOQQ+ah/fFJidsguPEHgfhhkQ9gXCgYQsnS/ClDj7T7bRf90mOpdI/3AS0EOJ1Q8siqTzHn1pQAgZGjeYDrQakEbUHPpkn1H9Ml5IfW69WyZmVqa5VyJvL6AGzkepsqUFlMBpRrYBkqBmG6KOWOs5gQkqFYj6jLg2rjNiVLQZxYkOJSO4klJBUTL9nOwya5Ots0htdsr5KB4pJmomkK4QGKDnjPCUTQcxV/450jslOmBaWRYCwXDxnJMDg9Wf2kHnOdzms7P7Tfz/o6/ahCgWgIJgynumZ4zUV03l3gMkY1ZFbD8FmQONPVv77sRHBnrqULQFdFZF6ss6y5ccWjR3DUwk0Hu+gM58MXifMrai7aBn9GlS/u9FASx/uERyaCEsCxQDD0lIlxTyrkBy00JmzFQEY3rxMMPEvmg10L7sI7i+kFzNGU2NhowsV6CNW+cHmTFrE/YXw2t6xtVcfZnRfFfPKAWRJZ+Hmi48EfSUz8wGjOQtP6UoOaukP7mAfiGGMALN6/QzqaKZgc+iALy+yRn+f+VTIizHl5MEepgAGJ0lcYtGwEC67GoT1mCykBQCQOtaUffP6nUraSVAuVQF/aj6Rn1vco6nSromDKN68YAv1nnX04iOJJrXHVxw+6RbeXEM7tco2vSxig54zyofHIAyNlkAzX2DdJmZkPjdT6D7Uf796tMO+9+wheE5jXBiMTyn0X37BRLQdv3YzBbXnLzrCUw3FNb/9TZUQZ+d5TcxS9O6wfmlymbP1rUHE1iUiUT7HRfgJEEbAE1F43c/QWiBBMZnFPqv26ylavRc4XVOv/AxzDYkss7is1UyzfSVj2Ltv7Lgu2hI5G2JsiERHVHeVGXRq1aZNt74O15uNBa10aOaC6iUmVo9kt7fg9nu6AgkzV2XiA8ki8sNyX82cogOJPKNkl45/i2r+VB5U0lmkASyFV5veMCMZt6z0L5QPtqnsWkwYLZZj+k/pubMbNJXzI83Q3NeYQVWntT1vKwnhHlUdDaOA09A6zDzKQpRG1uyP3oPqchDbS5TWhIdMmpdSaxkJjw5sDJL5ZsmRwajc4vnUyYOjV3HTLc3F+Q4Fpic9uPbKyC6F0sEU2azxS07Bj3lZ8yWBcKRw/QMM/fhkNHu6bpiBjcUtc8OwHFajcOi5XxmTSzMJDWY8cmoiFh5mlkNlQqky/S9EaWoJXkAMy8mYUZOzUXt6xSOmBlTM/oVnfhdjfhAElTi54EKQtC4GPDZjggOkQXX72AioOcLWRzALIaaS8Q3pTc79jKjQwU1Yd8MDxXCI4UXvf697LsetiNnEpMz7ANlxyDqyzqb2bgmAMnouD6iL5uaC6i5RNCXhMVIT6oc0r9GpZTPyYLSSoB9ShifcWh6mZ3z2cm5Qtni83YEbSIYSYjnGwh2Awg/z8uMn6Myjw369E6z3h9QFlQFwApEhzSZruA2EEB0qKCOeE9FwWdSGb/CMZOqRwqVd1/R4T3UEz77cCgR7mlo71Oj5hLhofe9yaSHlDDLs/5j24gvhnDeRL6ag8NDDRtUWdeqQB6QUwVxFNYZr6qEwcSUm5vIIXxfC+GRhJiqmhKYtxfXSD8wgfimJ/T6PWBlkivHij5P3r/LRCwfCIdcs2/12rMf+DCufdsWDv6Gl7E9/GI+s+2nYD70UTQuTxGOCgT/7r2wH/gw7B9+iPfkVomoh5tUGfBqjFbzx+7f3kIw4TpY9flwSO850+Bz7H5YoP0C57JoAMRX2R+U97yzAWofuMpfkhlI0hWjQ5Ib03X6O+kZx2s4wi2G6tw76vknnmmp0NN3+vWnod15zU6bkpi8g3pDD8nFwinqkBu7VYraIdlzJEkpmqKlPU9MavlDRsFNf9ECnBTEOILp7tYlCSdIhLGBpzxtuJpiNff6Z5M4jL/kPMp4oeeXOaUO6ZLC/IzB4VdvQs0r6QYnrdlJh9xrJosWZRNli+jp8TnKdITjRsHEC0KcLClZmG5olA3U9BlKNgSivkP7MqUaJiB5BwAOv2YTTgOt32adi4loyme18/JAh/kJduRqATQN6qT1dEHPkSV/t2w7ND1BLRhzAbOBqyckAeDyP9oi6a65cE+uiF1OsjZKWCDvWtY0+TY6q3HwNzZrjXnpTQ8rJ/jmHm9GVbPjFJCuCjT3zW31Ak4uNliVFKdz2SKYubqWwcQ8/HJxdigSiei3n8TJH+B7td9xAa1ffhzTdYXphq43f+mKoymn5X1v3rhF+y0X9RfpsqhriADK0oiqlOhcKVG0OLlMTi4mz2hkkRw4jM9IzP7a4m+rzzY5zUNo3mO9T2VkCLCfVjIegIvP0jPcCMkStTwoOiJSvZKoyJJ9WfkahWqhqBycnabEy/p6q/iQsohsSSA+dPXmNV9auCib2Jvrfu4jtTTFJOxv9TVK1IfEskmH93AoUDQF0tXFxD76Mm7YB/eH1HsboHnDofesrQMMAJCued1329fZRdxwBhMu9u3LDknfcjwompjO1/jHN77uYQRjYHg/UPrDbvs/fIz92dcCVFKYcOTHT3i7bCv9dJriNn/l8VrOl77yUUzu5v/nbYHGnoFKHWbrqu7TS2/dqY1nq/4OADe+Zas2Gy1jfv/G39lCcoupaJkILL11p5aqDe/RaP7q4zj6qk20bhi0f4nSs/TzHl1c56pDMGGtRtaRiN/9BKxm/2z82uNo/urjiAauvq9qbrH+Yz5A8O4nMLpbIV2WSJcFej+3Az2jzCca29s152B/yrsOvWdL5EsWJnGkeh0pZGv8Xjigi7cLHGy7pF7ezwl5z2F2Xw4140YaAnArOWbnCkByzjFNi7JBCUw1DuncDm4wDOcwG/Lfeu5rS5RDtm7gBNcEm1jaCbQ5H6cbJcoupUplmxs6HpwcBg+yps20DUziUPQMfy9xKFoOpk2neBOTqFb2DK8p4uAsu4aENUWU9eBB/5wbvF8ucijXCpilEirlZ3fKoWzy75Pf/QCsZm3N8AFuzHo/t4O8LRAOXS2LpCQZmJwVCKYc84P7tX82HBuje1Rd/9m+bBGMKcupDkf5ElhrFFMSZkMg88a7ua8NmJ52tba/aPOwkK2ahaS0ZZGvUwbXf0hCZgLpPRkl5DFtHfLeQvdvI4fBwwWyjRJl2yJbphXBfMPWmOz+gxKzDYm8w3uTdy1rmRrsF/OTlESlJ0vkXV5PVYuR9yxmd5cwTY4lp4CyV3It83IzG3HT6BQWUkUvT897lkQyT+TTU2D6YA6Zsi6v7Blikld5gC/bFs5v0gv/s7LN5wHLubvsGsxPlXUdb9n0/ShxyNdYD1Q2WA9kY4eyZRiUCi3rpbwZqQ0dio4ldv/uFDYAhBXofoQHl2qdKNsWKvUWHiHqeivh5aM2dlATWmzwsA3WZrQM9FygWCphY5IPAdRGpLbFyU+W3PNU5r3ZskG+zDFaEdSKjr8vbcOamWQhkXSa/cmE/n4CyJcNbMJAYhWAq8Z82Pcb+AbHrJMOrjYf9bXGTS+LtFyzwjGfc9mxsCHJk3mHMsCi5413I/6uixzyUwWKyl7Bo56jsa2tK4BF0D0cOTT3ed326Q/XczgAZBsNpCsh5p//KNzWy6Be8iK4rYWcH1isaxUxEABSL/8MhxInfojybgYzeZjXKevjhK9Pn97F8g8bVmsvMF8nJbEKppuE81jQl7AKiPY4P7A+ymG+zn7hNJCeMMi7FnmH9d1lk308P1FCj+4sM3NrOzYVPW7H7bgdt+N23I7bcTtux+24/ZlsFgIWd3ZYutPf/9/V7vhIJgsa2DGKDMDLXqx2noiyOP06zciUSllUKgwjUapwdUFy0eSp1AaMrkSe1FQmDrPTjADMTi5uZuc5MCOzbL3BHCMo+4/412tQ3gIJhEcSo3sFlv8rP2be9VKziJGy+kTt/61mC/mPKOnV4gRfS6WLyEXZYAYGYCSyigAVPZ6+5xsCh58sYENGLipAgYkE0hNlTWMzoSOxJkCdRXKSp/aKFiW8ZMREjBgIB0zPMTKmxwLzdecjqoyamJBZmqJrSfEYMvrNgmQHUUg0ryoUXWbaTMgIZpV+re/z5RJD1oXj9Pduo3Mpv+3n0W89icbe4lmHE4uiCQzPqT9Cgor6DmnPP4PPfAUG90voma1TxUWDP9Nzh7zF/7/5dZvY/eYtzL7gMcxf9Shuft0mC3LN4rlJAxpegrKrqngeAMrYoWwB4zN8vcH9CvMV/v/hV28iWxIomsDRgwRfmJAZA6cJSBjdTUO+YOLQ+PXH6+uHYD8CmLZWmS9cvLWgESSwZcuMsMdHAocPU4poA0aFy5bB+J5FoWPZtMg3SgjDjFW+bOjr0aDp6+geRsaDsfd9ksD4HmZUipY3VGu5GoJQwQhUys8V/eaTNfmw6LGQ3UTAfN0hW7Io2gR1qDmlnk76e3HACFkwIRiAGShGIGUhMHgQ2P0/GWWvAAvxTcoykC2eK/1JeK2T0wLDcwqDB31Gy9CTCqB/1fhei3Ag/ghVpqJUrb6/rCWQya5E3iOspP2b9EKanqCU8/BrNuEk0H/dJuJ3PwFhmeEJxw7psoSJBBr7NL09/JpNzL7gMQST22Vsw9eex8kf3EaRVNKcCroAzJdVDRtJjm5XLgsDDF9zHkVboEgk5q96FP2v3MR0QzHL9OrzlCVmDnHfMZL5WY/ALBWYf/4i+2NCRippIqqRf+YrMH8Vf56t8lqqzBRAIIUJxG1SUgCeXEZJXkUWa15j/wr7lKyYBICXQoq5gg0pTa0Ks9VRAD0nwctqQByGSK4ECG8ELOCv5B4pi7NVzgy1LPlVRTFbV/j9KvIfHSqOHy8JUhNPdyvZj9VUQU29NLJgdqgCJdiEgAGZ0pdKppQkVXO1nMu6oBwWCI5YQFwVHcMxMq1yStZkyf+GI2bTZeoJWBNde2vwwfhs/WtehviAigM9EzANh8v/ZAsmEjX0pGwxSi1zIBjzeeoZ15h0hdlZk3A8Gg8AGt4vUbSZQWZmnnOa8yoASL5elQlq7MpbwBCCIJMpJVdqStmbE5SWitTLvjLeP3UUePIc5WLhQNQSVGEIPtADVc8pFbSn+tJzYPTikuSwmBH7cCgIx9GUXYmSz8JEDnrCgv5q7hOZRHSgfX939J8BSXhcFAGcyGATCxf6rIAB0g278HwCaXE2pMdQ5eki5xK2aeoieho8uxrAYXqkpNnAR81DZoCgHVzgaigHpP//qSIMo+WzZYYyMJvYWjKJ0vudVN5O3QImlxCOa/PgpZaZFQGUHQs9lSjaPuNpAdsp4QJS5cIRaYDlMk3Qiy4zYXadi2fRoSG4C5wno3k5fikR7Ae1YXvR5v0p24bwBOFBOpKSv+S6qp+3TAkCqOAQRcvRKDt0tc8OHHhPJLOFsvT7wJh+VDZyzOgor3QYKma7GhZFx9SeiTby8JFqvGaLvldlhJ2isibZ87JU5SBmCsrvWaSXQg/vVTCRqCE70ZB9YO3HCRgqY0A99ABLJu6/B9lnP8JMYiyQtyTUrEC51IDYfqq+HuB2iWnV9KQaH/x3GTOzkq3Sc27wIq8ualkvDV/cy7zrkK5ZNK9Tcty5xIykmnMs5CcK6Jmox3ml2AH8+DWA6ORwyqHzvKv33O2LgBwrZGv/E4CC/8WZne/+7u/GI488gna7jfX1dXz+538+PvKRj/x3/+Ytb3kLhBC3fcVxfMef7RM67IzvpYzA0NMJ2TIfaNnkJqX1W5W0yWH/MeeJTQ5Fi4NuetIvdskthAtHDXm12QXAlH0EYii1TweevqUeJENNUVl/khv0ijJTDVQbOBQdv1jnlZM7D1Nli9fmFOVFNgAguBk2MR2gy6b1WMgFejA6It1ndpK0m7pWYiCQ7PvUZQnInK8/voufqbFvIOeyTrNCUEZWdgwnBkEKUdCnVM1JTmZ6yo1K3mGaFqWgK3UAwOt0V5/2N1JS31kZneVdpqq5yaYkYnaSrzk/aetJv5IUAMD8r74Ug/sDNK9RtrH3t7YQ/O776vs+eTXlTMP7b3lUChy8JWpzRIAHh2xJIBrytcN/+170nrXI27LekHR+4QL01CGYOgRzh97P76C5Z3Hih7fR+LXHkbzrCfSeKxBMHRoHJcIpZxiVCqw/SclVfCRqN3r2DYHVpwuc+v5tmskeOPSe5QIRjZmi7z5vcOr7t9F9rkA04OQoSsqfmhUla5/X3b5C9F4wcwiHPMCFA0q8WtcKRINFvxSFqPGm2ZJA3iW6V3qqX7XZXH3aQc24sMhcQA1VvcGXKfXO0uOtK2ljRXgSBvWCvPwhh+k9htS0OQ9gNR1OcNxkn/tIPTGrseKBuG1JjPEyufkGJ+K87X8vpVlm3nUY3c+6mLwjkPVoiCgK9leZU2dd1S2lJ0uOFT+U87ZHGocczx9vFjpfFZjc5etxPqUkyaZcGBvWzQmoHDj4ZE1T0Q7qw362JJD95U8CAKz8wlOwAdDcM4gPCiy9hdKy3kcWUsr21RJLHyu4yOUOKz+zUxMEAdTEs+7bLuDGt2wh9v236ttnv5OEn6xdbRK8ROSzGXUJJg7dt19A79kCvZ/fQfKuJ7D01h2s/OwO4nc/gWhQItkX6L79AsqEfXe+opBcDJH8mydqyeDaT+zQWPTdT2Dtx3dILwQPUvG+QHPXIPtcvmf8G0+g92wJqxeyxLpPGt7P4WvPY+VpboTHZ/mAii5pVPFNbjzUlBssPeMGIe9Zj3r2wamE9YMy42Y2X6OcRhQVZYwb3bLBDZPMeXBN9nhQn57ha8f7cmHG6zjHmYgyjbLNOoXoQPmN12JjoaeUdwoLRPuqpk3KlNddyU0qOW98IFmnWS4O0MEeFy89IemoTHhPOs+RIhoOeL3wBzSVesNE54NOdb2aQ7oq4OCvXXLu775QonnNIe+KWjIcjhiQKRMg63IuqQiKMveoar/GFG1uhLIlHoTyruVhyo//MnFIVxdSnWzJS2cNza2DAQ99UZ9rUjCsAhk8XAYjBkeim4r1nyN4BC433csf4JxhQyJzAaD1gkZyUyCYsi8FHklttTfyzAWS63R9r+pIYBkwgRNI9iWSfZq3hiMe4qJDiWRX1i71leysbDrvDs+aB1yPabSZe2Syf7Y2BGtj+hpqKtHYs8hPFoD1hEPHQ5PKeJKuqH01Gr066JWcX4OB7/sDzXncm+vKiT9wJxamaT2yenE4EqWXFjZYh1bVy1RySRmQIJbsskZIzXj4gfDy5kLUhDuRKoT7GnKsUMYMIge+RsaGFt0PargZjVDVXNYm1aZlgaqvHSqUXcrqirWCNgUTWR+M2He9tUYp6n4kMh4oIIBsxUu/umVtlF2t2XosoQeaweaEEjcTOwQDBds0ntzHQyLpbjS7dKGtJdb5ikGFDLdBFcjw9bgDC5VxbyYKWfdLKEeD0oZB2eb1hUOH5nWLU/9y25cQ8Pt67qDvPYfpFz6GcOylcM98DKqq+f3tJ9l3ZhaRrxnV/Rnc1svqGlKAstpb5xNgUdKQ+oOFnrHOSo84H6k576keKRo2gybcskBdS6cKSjkPHiZpcnbGsFasHyBftpQmthZzqJoLNK75fcH1GM0rCtNToh6Dk7sEr+Hj1807aP+raWz/8T/+R7zxjW/EhQsX8Du/8zsoigKf8Rmfgel0+t/9u06ngxs3btRfly5duuPPdixjO27H7bgdt+N23I7bcTtux+3PcbNOwN4pjc3//mg0uu37URQhiqLbvvee97zntn+/5S1vwfr6Ot73vvfhL/7Fv/jffA8hBE6cOHFH1/Xx7Y4zOzYAzv2DHbQuybporHmNUfroUCHvOUw+xxO6JhK9D0l0ngM6z0nEh6CnTs5Td3LToX0RlMIVQHxka3MnWQpEA5qDxjdlLd0Rvni7cVVCZYzGkeYhEP3Wkzj5g9tQc6YEgynQvMoC6KJDSUHUF0gOGNlvXSIRpnWZRnQVWWvlZ3fob+IPm8KSQNe8wX+XDSAckyhFqZO/mYaRPj0Hus8x05Qv2VruNV+RCIeylrxo72/TflYjHAg0rwnAeLqVZVSueUVBT/n+nWdJhqlgBHpKqZ5TDkcPkc6mp4KyntBBTyVWPmgQjhhFjX1UrfMs72c4kLjrdwzUTCDqk4ADAMnvfADhiF4kas608PC152v5TBX1bl5fDIro9z9YF/JVkebqM5/8gW2kK4uu1nrnBYRji9Z1hkfGX3KexbYdAT33z79wGH3ZeYy/9Dzyz3oENhAIJxaDewPIihI2Ag5eTo8ZPXPov1gg99Qw4YDhOb2AIITA5IyP5s4tROkwX5Hov24TkzO6jmzZkFK7yWkFG6CWvhU+gl8kzM6UsWCB+dQhXdEo2osxIhyLNKMDiaJJuUhFwwqHpKC5wCFrCxRdZnfKJqPdasZIbOMGn5GJKDd0lR+IRZ2tab6gIDKB0T0SJ/4TMzTzM6X3c+C1mIDFjVlH1RLNqm8EY0ka3ZSR5fbzzH7GhzQ9BPwzmQmsPkVwh54tvHXKliNVpyRxsc7ElIwgxzcYS2ns21oSFQ6Yntdzh/ZFRr/CkauNC9e2eb+zZVcTmuab1FPqGSOLnYv02alkkMk1heSmrX12qucIAMHvvq/OtvRfsnhG4zMak9OksZlQYPiaRSYFuN0otrFnazJd+spHsfeNJBJOvvgx9H6ev5/1JG5+7SYyD2CpMox5W2H0Zeex+01bt0EyipZCugJc/3tbWHrLDtIVGoVW0JfOLy6yo1azTx78zU2Mv+Q8ZusK0YheVOmSxOisrmlvybueQPftF1A0Pm7BsqR5hWOLo5f6bKKfa/SI93xylt8vuwbxrvbF+MziBN4gMpgy6+aUz+plwNJTzEjagHNjJRU2EaU/Sx+2iA4kZSReZlkVQIeDRVS/BhkUAvENVdPd9FT4ecjVWcj2Jc5xKmOUtXFd1tQxlfnMj2EBcd5jJlvPJCmeufDmncyS6KnA6f+3RDSg/KToWAwfWMhVhWHUv/KFs8FC9qtTZrziI4H4JrP6Sx8xOPwkjaW37kBPmV1QGbO84Yi0KBtS5qLn/AwdH422Ie9j47o3Jh0LJPsOS88sfOBssJAEVjI24eBhJw7DF9FwUhhGi6fnDNKXzAlwaDmkJ0rM7im8r53D/ITF5CznFxuxqL7/EkpfZS6YKZFUBEzvonddetJgfoJeRJU6omhbpKs0TJyfoIzXxA6DTy5huiWm9xSYrxNWlG6UmN9dYH6mRLpm67VDj2kuCXgq5owAGpswYyIsP3/RtfQq6zOrUraZxUiXpJdVUkaovMKBBpcCKqUHTnJdI7qpatqXcEA4ovxSjxTKloHKPRRozswQDcYFus8oRAcKjSsK0l+fzJnJ0CMJWGaTRAmIXELeDBE8T3Lm/AQ/RzDhe8Ewu1W0LRUWLX+tkmCAcCR4PW1mRGQuMXqAmRzrjT9Rcl2XM3622vi5FCiWS0TXAk9SY8ZfT0Qt3Qv70sNuUFNqoyPe02RX1aaiaqTR2JW1YkCnBJKolJ85OloQCuOrQU0ms5qfR48VbEQPpIoKJzJJ76TAYfkZg+hIQk8UVCoxOsdnI/JK4SBqc1HhgPB6gNbz3uyzITA9ITH48k3M1wXKiNcRjA2QF2j+KjP2JhbIP+uRRanCyz8JTgkEI0OaZTuCCzXE9lO1iTSAmpJ6qx9dlZGu4EHV+q9yUn7bV1iqISzQ+mgAPeecGB1KNG4INHYFJfbO7/vArGLedbVPnSiFN/5lH67IeibmHD25v8DKh0okexJrf1jSqHkmUXZuz+rfSbOfQFanorHddddd6Ha79dd3f/d3/w/fbzgcAgCWl5f/u783mUxw991346677sKrXvUqfPCDH7zjz3bHh53kwGH6hY/BKaB1zaD3nEWZeAJHwYGS+fqGSvdYtEl1chKYbwgEI0/QCAWyJe+4W9JostpkNa8zNRpMifIMJlxoKMXihl4WqM1MV35mB1f+wRb6r9uEylFTmOzH4WtNSNlMhekUlkjqSqqQ7AkcfvWml41xUxgOBZJDV8vPKlnb8pt3ahdgANBTusyHI1J4phsarcuUyQBA+5qB1Q7z5cVtdwo+BQxkS0DjGgc5LCcnE/oNeFdgdtp5o0ym8csGN7LBUKF11cEF/P1wIKjRLyg9El6ip3Kv/wzhzRwdrn66rh3Km7uLwhM9t8Q1+tbYLZC864n/Zr9IP/2lkCVw4oe3a1qaepA6t6vfsYXGvsX4S87Xvx++50nMVjUnHK8/d1og6yhc/7tbiN/9BHTm0P6lC5ivKOJ1WxLxka2RxHl3IXUKx5wgghHvNSUlJIY1blr+fMpZbrqu4CTR50tv2eFkPHMwoUBjz6FoK6isQkXzesd385mZmGnzYMZ6gzIRNS60fqZeZysNcPc/3kbR5oFF5fy9sK8QHiqM76nS2oLGf4qLUUU11JOFsVx0SC11ss/xouZ+0xlRv374SewTlQFtJRVzwWJCVqlA/ys3eegt6eoeH1F6ozLWmlXa4rxNuVK6QrlK7vt++1oJYSnBaV32aOARr72WCHk8b+g102Xi3efHPMC0rhEzHg28RDQStUSpaEjoKcdh1OffJzuksdkAWPlggaIhsPzmHZiQfbp92f6Rzb1KgdmqwuyvPYbxWY3xl5yvEaYA6nqsW2Wzsy94rD40OC3qw304sdh/hcbwNeeRdWRdLwQA2ec8gtkXPFYHOTq/eAHjLz0PWfrD0ZLA8H5Z19UcfvUm+l+5CZVRppHsOVz79i20rhukr3wURdth/vmP1gej4WvOw0lgthEg7jtEgxIrP00pnIkBEwh0Lpc17W3vG7dw9PrNP2Iq6jQw3/A1O+VCzitK1GS0xg061IuSh55knwGgslHhqQXyzoLSJLOqrwq0X2DwQ8/8ZskwCBYfCExPsb+pguMyPmBQpmg56tTtLXV4majHXLLHGhg152EjOuT1wAHjcwxQ5V32/6JDLDRASVIl/7SK60XU9zUFwaLur/cxi6jPjdT+yxkd0DOBsE/stJ5zXSOe3h+2pa+F8etL1pOUfTrOQcIBR5+karS69p/PRKiNEld+egfJTc7rzX2Dou0wPq1QxqgDTrJg36iCAPNVUdMIwyHHtPX1lhxz3kDyyNsSHNG4N7muEO0rxM8kSHa5MU+uaW7AJh4lXQj0PkIpYLwvEYxo4Fi11odDqDkDYs0ritYMI4l7vmMHKuWc2bwq0bokKdfNGaSLb0okNwUalzTUSCHoE08d9QWSqxrNZwOoqcT933KhlrPHu4u5ivVUXrbrDTIriU7zCtflMmFgVM45/+mU+waaTXN9jfdUvZG3vrZFz1Bj8AHOtU4uMODhkeL7zxc4b1EKyLnE7JRDvkSJkZ4KlA3S1PSUB5joSEAPZT03mpahjYKkJKlae2VOBLcNHJI9ifbz/L5KeXipyGvaI8HVjJ9x5Q8lVEo52srTDuFNYsEbN1i3JsoFerz1bOD7Ke8L/IFZzWR9gNAjhfE5i/BA+X7FsaVnlPE2nid6umi5OoiWLVsEg+pQWgUieFhPT5T14U9lPAQ5UZny0rbExFxfw32N8EBhdM/iJCEMcOr7thEdudoMNRwsUOeVUXHqzdMrCbGJGDirdrXzdQ3ba6P/lZsYnaV5qCwsyoZEem4ZUAIyt5htBAjmFjZcrAW32iUsaJiL+bQKutQ7aOdleCFryq3mGk6EPO/99JRfDxtA1uN61rxKCXM4cmheR00lNBHQeVZ6qiHn52jA56/mAkFfQfc19l6hULQdjl6sYUIfvJrcvhbeSbNOfkJfAHDlyhUMh8P66zu+4zv+++9lLb75m78Zn/Zpn4aXvvSl/83fe/DBB/GmN70J73rXu/C2t70N1lpsbW3h6tWrd/TZjmVsx+24HbfjdtyO23E7bsftuP05bgYC5g7patXvdzoddDqd/8FvL9ob3/hGfOADH8B//s//+b/7e5ubm9jcXATet7a28NBDD+Enf/In8V3f9V1/4ve748xO1hWYnFZk7a9KDO5bFLmqnKfY6vQvS6YYi3ZFoqHvTtHxWYaQ5CmV8+fJgcX0BF9vtsHI1XxN1DQ25aMcwZARaBuQbiOMwOV/soVwDEzO3G6KVtGTAHqkCEdPBBsw6pN3GOHMly2E44l75Wd3kHcd4puU95QJcPCwqE0uWTztcPRVm2juGVj//dxL5eZrjDiZCJivuTrFOj5NucdCxoY6UiUs09ZOUn4XHzGyFfUZtaxaOPTGqGIBVjCRY1SxYHpZ5ZT7QdIvxnkfCBPy/qWrjtGCmfBRFn5/euKWPC2A1Z/aQWOPco+8+0fPxY2926kf01MCgy/fRDDz9LmPPAsT+evxv5p/5iswefV5zL7gMcjSwf3BB+EUDfRgad7ZfcFg8urz0P51kkMaihZNgfmahPGZHVky2qKnAjdffvsAjQ4FZOnQulYibwqYSNTGjSs/S+mRTuGj6czQ5B0gbwk0f+VxmiyeFLWZaCVVjPsO0XCR5cu7+CNZhXBEaU4lfQ3G7DsyZ0ayAms4vYhCV4ajlFX4KLAvIHaKGRgbkQJoYlfL7tRYYn7SoHkNSE+UyHtMg1fGjtERM36dX7wAlaP2gYn6JIqly1VhuJcn3FIn6DwUJFumBGD0ZecxuFfDamB0DzO2FQmmaLnbpsiy4WrPGhMwGjdbp0mliYDeswaTMxKta4y0V75Nk7sWGaLqeVWtisJWWYsz372N+CYlDCpHTWMbv/JhRH2H5TfvQOUWqz+5g2Bma58hgO8nS4eyIbD+o9vovv3CbYCC9X+9jeRdT2D42vNI3vUE2i8s/jb7nEcw+eLH0Prlx0kl/LXHIc3i3rZ/6QKaex6ikQF3fRezOo1fexwrP+u9eHzmeOmtO+i8YNH4tccRv/sJJHsCyb95os7+dt9+AXHfovdzfO1bAQXCkAI3X/Z+Up/3KNpXDZbftFPLQaumZ6KmwaiU82D7skW2YmlmZ4Giw0xo6wVKOCsSZeMGsy0VkCbvubqQvnmd84OJBPI2I6tFmz93ipnQ2Ulb90WVkSBZNh0aewJFhzLOqmA9vslrK1oO6SrHUNl0KLrMmuQ9FmxbzfVAeN+qqg/eSgQVFrVcbL7hZWt+3MlSYPAAvbJM7BAfOkzOou4jsvSkTS+dKxsO2TLXDFmgltip1HGODGlcXDZISFp+8w52/zbljjJndrRz0cAEwOEbNus1crpO+hmJWZwbwiHXHJUD8zWCNuoCcsdIr2k4tK4siqaTm5ZGrd3FWhIO6B1EJYJDumG9+XBFfuN6k+wJjO5j9DjvEgZRvV/VnKJ/T9FyGD3AsXjl/96qJTgAzQ/LBt+/aDOLO1/js5MFMxNF06Focm6rvFYuftcmJV0gjY7ZK/YDq5nR03OBMvafxwLzE7xXFUhDlnxG09OCVL5i4alXeQzJzGc1Unq9FC1eV9FZ+ApVfj5Fx9Ymqk7x81MKyUygygQL7xNCPcrEQzW8WqR6nlYD3Wc0oQHeZLpz2dQGlUWb12ADP/5KGshaRTJguualpPskqDntcPQw4RUyE+g/JJGvmhqSFN1UJBrOmT2db1jIzBvGWt6Tssl9g7De261FaZ3TXFds6BAN2Jf2v34L6apF84qs3wOAzzJSklomrpZXRkcSy08pZq5uNS3O/T28RWVQNRug7nfwz3zwFZuYnRT1GpktERhCQi2zWBWkwglRZwadXPjsWA3YD3wY4cQi7lPdof/9+5Ac5Ih2p3Dv/QCEcYj7hsqeWQkbKv+at3R+///5LfuwSpZeZX2CGfdeQDVuRW1cW0l22y8wa1YmvPfdFyxsBBy91EHPHSZ3UUKpp5RnhiOHpY/SR66Sjjf2fXaoZdG8Jupn4DR958qGg0xv34/cSfufyezcSfuGb/gG/MZv/AZ+7/d+D2fOnLmjvw2CAC9/+cvx7LPP3tHf3XnNjubDal6hPKVzyTKtPWUKr3kFWHvrUwCIkZyvc5LsvmAxOyG8AVS1KPrNu9+8WCVq8ovMUeukZc56nmoDJ7z+vLFvEQ4ocWtedWjsWeiZp9o0gPZlg/iItQYnfmgbyYGt5SvxTb6WSrnA0+SLHQZYyKOcPxQ1ry2kSk7y/5ffvIOjFy8OCBVtR/gapNWf2kH7EuUNvZ/f4eHmFimNnjkEU3hzL08LajhkPR66eBhjLUXTyyKyFYv4gDrwcOD1t0YgbwsEMx58ynhBwpmcoUFVtuRqGVvjOjfYUZ+biXDE3w9HtxwM/ea3faVA1P/j+0JFcwKA+D98AHf9s+2aPAUA7tM+Bes/uo32ZYPWOy+g/Y4LCMa8iY1fexyNPf5/920XsPzhAvGA2u10SaL1zgsoPZI6fM+T6L7tAoKpQ/OGRfLvP8DXF5ys4wOH7rOUOFXyxWDqeMCLSb1ZftMO1Nxg/xu4Aek9l2P9X3uD1F2L9lWL5Y8YhBOH/DNfgXBi0bzhkHrTvuVfZJ+uDjbh2KF53WH5wwatq3m9EQc44YQDWZvdOgW0L1NvGw5ELQfofAw1BbCqSZMFkK5wk9bwNVFM2/vaBU+FUillpCZxOPX73FS3LmqmsJ2oJ2FhF+n3avwUXW78kptc9EhtYiCiMj+M+gLxgavr1gB/YPKSnuY1wboZX0uh5qLWQgOU1cSHi0OLyjwiVFPGU11PZbgb/R41uOFQ4O5/tIP5hkO6dPv0JEtgeC6o/z354sfQvmrQ3LXQqcXRl72s/lk0tig+4xWIfvNJ9s93P1FvzNq/dAHRbz6JYGrra6na8J7b31NlDsPXnEdyaNB9+wU4KTC4P8Bs/fbAQDD543Gf1SHu41v020+idYXSudmGxOSLKVubnvEH8p9ZXFelOa9q5SavPo/u2y/g5A9uIxybeuMc/wbHXfa5jyD8T7drmk3oar19su/QvMIaodO/bylnswvaUqU/L5uultjOTlGq07osfCCBG+3Bi+A3naiNdStypgko/WrckMh6DpO7OL9XB3urOYcFU6BokzRZtrxsrpIYOT/G9xdjQRbcdFaLPA8glFkFI2KVYbkRlbmfX2ce2y4Wa0uyxz02535KJxs3KB1N9haBJBPzcKRSANKbXPs6IxMzIBaOicvXM4G8s7hWG3Bj39hzmK1LqAxoXy6w/EyB7nM5Zie5kWvsWSQ3uWkOJh7T3gTaFx3GZzSiASXbp79nG+GInysacO0FgNkJSkllBrSuWtYBNgSSvepecnxW65OJOWar9UJm/F3WFC4CC8neYlPnFA8LwZCb8mDsa3b3DHrPltATUhppRcHASTgSWPoQeMhyXEfhiXVVcCc+FLV7vFOoDRqr+pyKeEXsPg8H7ReAkz+4jcZeFaQRCEd8RsFIIlviAbZYprl3MGJ/NTE31VaxXxUti9YV0gODESWAwvA1TIOHZ+HnLae5yazuX+DNG/XYy3CNQNl29YE8Goh6k2oblL2FA4GDhxVrPqoSx6bz99bXd3YZoDQxZVxF23Jz7fic4j0JpznumlcdZMZ6tdkp1ksBPLA4TyBMDvxhr2CtSPUsbeBlyEeSRLiKcKdo5aDnwPqPbcPGFmXM67yVkJlXJqaWc4RJaDZbNoS/fl5v2eShTxiBdM2Tdf38Ua1TrcsMfPNCuT45yWsRhs9VZfAHMov5+oK6uPzOp7DxI9tY+ZkdzlG+FtiGAvrec7zHiUTREHBbL0MZK5hOVJuHZl2FvCVhIwU1yervi5fcx//6y6pQ6be2qC8w/cLH2N8n7O9OcW3V3sQ+HEgfAKCMUs8ZbEyXBLKeQ3QkMTlD6ShrDRf3ZXpCIl1lID6YAKN7/dq8r5CtMDAe9X3gtVPVef2Ry/wTN4NFdudP/vUnb845fMM3fAN+/dd/Hf/hP/wH3HPPPXd+jcbg/e9/P06ePHlHf3csYztux+24HbfjdtyO23E7bsftz3H7RDI1d/L7b3zjG/ELv/ALeNe73oV2u43d3V0AQLfbRZIkAICv+IqvwOnTp2vAwXd+53fi/PnzuP/++zEYDPB93/d9uHTpEr7ma77mjq7zjjM7KvMwgZOUbJlQoGh7wk7DoWwKzP8qi43KJmlr4Ujg8KUC4ZgyJScrSIAnV3myUtlYSFecZvEWU8/MNNiIaTynvfHaPaqWSkzPCLTfcaEuuBaWRpJVYTnAjEEw9pGPgBE6p+GLC1mgWLRQ/7y6O3pGQEA4XmQ+Sh/hb+y526L68cCi+7xB6xoL/OdrzLoMvpyaw1vTt7MNgbzHyJGJmTqnbISR8LzH9xu8hFK7YMST//SUqKOGec/BdEsUDXpiyIIQCUj6XwCMqMvCZ8gOWGBJszE+ExPSy6iKSFbP7+BvbGJ8V4CN/2e7ji7f2qoCcoCAgqPXb+LwaxbayqId8DXO3lJ8uP1UHaG+1btntqZRJAKdX7gA5eVl82V5G8GqjMXCowgEBVjN9H84dhjcH9QwiKIpUDQAlS4+F0B5UvpKFp6nn8f/6tQi6wgUDYF0RWC2ESBvSchi4dE0/tyH2S9CYHqSpopFU2Dusw+3jnfhZS5WA+138LOOzwqULVNHvZ2ihCrvUHZWeXSYiH3KBg7zNW8Y5vjZbcBnWGWv8jYjRpPTCrMTzKzOTzIlXxmIZl1R/37VZMZsWLZEyIVVBIeUTWZzKkqUkyT+hKMFHW/9R7cp45xQpiANYGP216ow0gZAvmQxPuezkUv8nCbiGD98wybGZxQae4Qg2ACYfcYn13/77A+eR9E1t9FvqntvNTOBVTt4WOLoJQLR0NTZt7wtMFuTCP7de1H8X5+Kg7+5ifSVj0KUt8viphuM9ey/kdm+/LMeQfcFW/eN0ZedR7rMDMh0gxfT+/kdhCOHxj7HVpWRybqeIufJb+PTun6P3W/eqt8z/bxH6/6Xd0UtnSsaEvlnPQJZANMveqz22bm1Vd+rYBGHX72J6bquZX2DL99E49cer7NZtz90ZgqGrz1PyVmPUri9RxRMgwSuOvPXov9LVSBetOgTVTZZFMzCW8pswyFlaXmXz398lnOULAkXqLyVAB+VTRySm1WRtpc7KZ91FMzwWG8OWRMFQ2Z8ikpqlDgE40WmXZSMMpOwRpUBTVQFpL9OG7GoXDh+LtOwiEb8tw0dhg9YqKyS5PF95huWHkENV5teW0WgDXwmTOaUrBVN0jfVnHK+yavPQ08d5bm3NJUBeUdhcH+A4X0hC/B9t2xd9b4jsR+HhX8v0LRQzfnMgUUmTqfeAyRdeHjMNmjAqnKOaxMuCuIrSYxJqIhI9mi6qtOFMqHoutqYMV0R0J5SWjatnxt4z8MxlRtHL9a1b5pJOMaFo6RdFhyPeYfZRRMJlAkzSHnXMZMWLiSS1X8BIFszME3D+2OBbI2+cJXUcPia85iecihjesSlqxbxISEANrIY3UuwgYkdkgP2DzggXafkvmjz82ZLC/mi8feHdEFXZ2Bs7FB0je8HnLOzFcrw8vWyJmhVGcuyYxZywqEDDPvc/IRF5xZJrE3Y303skC0xeq+8Ka8eM+spnM+Ehg5lm75nFaxpekbUvjkEefD6VMr1wmmH8T3sOzZ0mJyluqVsWpiYEqnKJyvvWUDQt0xlhP0MX3ueZqbthbIE8JKqG9KTCVF7xbnIetAGr6vsWECAZqY5AOFI05xwbbGB9+9qUWEDxwzUyk/v0CfJ36OyxbEJAbimwX1/dwfw68PBa19WKzbKpkCZcC7WM4fy+YsAgGhkfGasRN5RULMCMjewkUQ44VqjpwXMhz4KAAjmDu5Dz/H9P24d4vjzfXTJofmrj9dzVLbCMWIiL6GM6MenMpqzV8ooZnB9H/B7URN7+qpXU8xOUP4ejCWKpoPK+FxNyPFutUPv2dKbU3uFjkS9h/1E2v9qU9Ef//Efx3A4xF/6S38JJ0+erL/e8Y531L9z+fJl3Lhxo/53v9/HG97wBjz00EP4nM/5HIxGI2xvb+MlL3nJH/cW/832CR12rOZDae4bTE/y5rvAyxcMF26AtQtlY0E9q2o84gMeZiqd7uSM5CTbEjXFSBgg7wG950tEI4t4YCCzxSEpGFOqlC2RjKOnRBgXjYVBW95jiv7wqzex+7e3iDdeFphtMM3afwk7ZLqy2EDKkr/fe7Ya1LyevOdgYl+DEHPjAHhKjv9bEwtMN9Rt2MJgSplU7+d3ak1/GS1qTvIuB3LZoC43vskaJRPx/uQ956lDnkJz1dcuzVh7Iz3eMlv2spOYB9EajeglTLIQKFrA9FzpN6N09abRq6sdkAGip6u6mMldAhf/+SamX8hNXUWrAnhYq1oZ86AwuUvUpqPhe55E2eR1Dl+7+Lvq57ceZJxgDcj4S8+j9/M7GJ9RkAXlbpX7fLX5nf8VHsZmpzjBpCsO47MS2RLqZzQ7bZH3BEZnNYomcONbtjA6x5U0fvcTGNwXov8ijawr+czOAqO7JUxIs9RsiRQpAJj9tccQH/EhRwNO7kVLYHqam5nx2bBeDACOhbzLhfnwDZs0XuxZqLlE3mNNg2kb6BkdpcumQ75qkPcssiUuTibixEYzPG70q7EHUON89Mk8IGXLPHiWLQftF6ZKc1y5SGef+0i9oMcHAuNz3nx0zANLMOZGdr7OP5yeAYQlUS7vss6saAgcvZ6brfE5wdq0GFh/gpSpCgVtlkpAcJIGeDBSGRG62YrFbENAT52vcbsd6RkfOtjEIuyrerNbtaqf7v2tLVz79i3M1n1tiQamG4tfDscO09PA0VdtwkYScd9huqEweAnH9O43bRGlvk7iWroKXPs2LpaVjC3+jSegCofY19fNN4invvEtREXP1hV2v2lxiKmCH1lPYfyl59G+VqL/uk0uVhN327iJ3/0EZl/wGPKOw9HrN2vz4clJTULPrzyO2YbE9Asfw82v3cTe3/KHsY7A3jduYfnNO0hf+SjGXgFQNBbj5vrf3cLNr93EwWsXkj4AXsLk0H3bBcxOO2TLBoMHudHMlw1sZNk31wuYXsnNXsh6wbxnKT9pkLxZbThtyGdimoYm0wmDVtnJghIXS/mbifg3pLyxfiZddZieM8jWDcb3l0Av52GlYYm/blqYloWNvWnsilno8gUwO+1rejz5UBigPJnXm8FshUbNecfWWHfTMih6lvUoFhg8IFEslyg6Fs1rEtPTnG9lKTC6l5vTYq3kZrTFjS6kw3yDm12A0uv9b9iCDYAbmxpFx6F1zWG+wuBBdMT3rtYLkzAIR/uC6gMBOqNss2gxgFP9TM8c4kNK/PKeq9eBMnboP6hqOWXeZT0LDUi5eZ+vcf3Kl7wsqm2RdyzmJw1kIZCt0Mk9PWHqObRsOATDBR3Raa6PZYNyKc5fvOfVPSoTYG+LdS+zU6yNs5prTrrG+1XVtqTrvvbwJBHU43ss8ltqZpxi7d/4oRzBkYRwou43TvoDSeQw2xDY+z+Jm7YxA3486AnMT5cI+8rL+gSgHKanJGmlKwWNQX39qp4LmNChWLKYnbHINgyCKQ9LNnawEe+9bZc0jAw4f6sZN/plxyDaDUjGW6Wxsw0AhBazEzSGPHy0hAu9tO1IYvDA4rCBwPI9JGtCxvdZlB2DYqNAvsz1IBhJpOcyT+Z0MC2LbN14EqKFnIuFdLTF1ypWS8pWnfDWBpTg2cQiWzOAl64KA0iP+rYN6+ucaGEw3xBo7HO/UHYNbHhLYFcuSIAV2TFf4ueZvSjD5G7rZaYc08IKzE8ZyEwi/ZIBEeU9wyDEikHpN/rCP9+L/3wT6aqgIacDXMh+ZGMLGIGP/evHUHZ4MZVB/fVv3ULeXthFiJJ46eavPo7+izTNf5VEGXuyapNrxnxZo0wEpmcasP+fl8MkGumtxFxvDFtJBIFFIKaqB4OgjM1JrtXBlFS2YiPH6KES43sMnvu+zbrWK++52hCUUlKB099LWf30NA+h07P8fJV57/ABfqZbr2O2ruo5troX2eofL6n+kzQHAXuHX7dX6/4PXt+5P/brda97Xf07v//7v4+3vOUt9b9/6Id+CJcuXUKWZdjd3cVv/uZv4uUvf/kdf7ZjGdtxO27H7bgdt+N23I7bcTtuf47bnWZqqr/509Du+Crna0DrGtOQaU+h95z1hXCMGLO4cEE/KRu+SGsoMDpHklbZBFafLtC8YesUoVW+MFP7U6JjpOLoIY3xXRLj05opXcuUfrpOrnvZZDTx1Pdt15IhgBHwZF8guclrOfFD2wjGDnmHv28Dyi5M4hD1ma2paCMrP7uDySlmm2Qp0LxhEYwoTwAYRVcZ5S9/XDFYNKS8T2V8XZXxGtJXPsqitdBLEOY0vav8DoqOQ7pCeYHTNEBlAT6L24IxI+7hyKF5g34VJgT0WDL1KeCN54DWCxJBX9W8eCcYQRfedEylXgrnCxX1VNxGv4qHjA60rjA9Hw6Z2aj8PADUZqkA5YfREe9l650X6qzNiR/axtp/tbdJj6qfT9cX3W/5zTuIBvTVmX7RY0gOHaKxp7G96wlI49DcM4gHtiak6TkLF/WM96F92dXmj0vPAOHAIZwQjnHyB7cRDRcRj2BG2EHRpASueRXoXLIIxsDJ/8K+2bloar+M1BOvZEkZj0r5fNqXLVrXCkRHi+iGmrOAOjySmK1XRdkCekIPmWAsEO7z9ZKrCjKlAWfnOe9BcUPUwIwKXNHY9TKakJFnPaMPg54Jmuj6IvFgSMKenvFawgmzm1lH1RLK+Un2MdiFB4iJ6GGhUn62ZM97cOTMEo3uVlj52Z26PzWv+3S7pPGoLJjSBwB9qBEeSeRLPjI15fvJkv1dGPaXkz+4XfsZ5S1eW7oikFzTvtjZy4m8qWh0RHLaxv+zjdPfwyiYLIB7/94OwomtpYbtdz+N3kcpL5KZRTA2WPmZHXQ/ukghzVcl1v4wR96SaF90OP292wjf8yTWnqI2Kv28R9H8lcfR+mXKzJY+aphhPnLov24T6z+6jcZNW3s3Vdndzi9eQPuXLtQytrWf4D27ddxULRoIxAMLnbL/Nw4MZAHMP/9RnPhhSkeb+xbJAd+jfblcZMff/QTCAWmBy2/aQeYj/u3LFms/sYPOpfKPvFfjBjNZeiLQ/Qi9OZI9gfBQofMxjdZlgfBGgN5TAYIxTYpbl1lgGx1KNC5rb1wn6qJYGzm0XtA0PM4ETn/PNpJLAQ0CZwLNa5ybuh8VNbij6BjEBwKNKwrJFY34hkb0fIx4XyK5qhHvaiQ3FJqXeI3RTYXoUNUkLeG4toQjb7p3jWACeRAgOlQcX33lPXsEWpcJadF9jdbz9DGLDhX9Ta4GiG8qJHucT2XOftZ5Hlh+SiG+RoPExqUArcs0L21cpz8KQBBGmVCJ0HketU9Vckj5UkXeLHz/DgfM/KjUgzL6lHRNNyTiPqlY8ZFD/yGB5h6lP2XsC+99IXw05N9UBrSA9+fy8AWVenjNnHNRdEjPl+ZFhXAoEQz4bGTGrEl4pNC4LhANHFafZoHzrdJXPWUfCEeEU1RjUU8FHvjGxwn9GUpEhwLRgUTrCvsawHVGzTnnVR43rUt8Xs2rkoQyh9sK31UqENwMII1ActU/9zmvVY/YF2VJA8Wia6EnAtE1Zu3DIdB8QdfeTcIB0YFipikTCK+HUGNF2daK4fWlAkFfQqb0x0nXDMIjGoaGfUXp3mEAnQroIWlZNOkUUFMFJ6m+EDmNuWUB6IMA4UgiPFQQKb2r9ETChA69j5HMplIJfTNA2Ofc3L7ENSO+rhHsBczIJJS3y36AeF8hGHC9kP6+hn3p5ZoetuRNTvVA/3/Z++8wy667zhv9rp33yXUqdlS31LIky5aMbXVXFZfLCwPYOIyNnHEOgME2Oc/ACzMDhiGY4ADOAWdso9fGGDyYyzMvVdUtG9uyHNVWq3NXPPmcndf947vW2lU2MCPNM/e9hlrPU091V9U5Z4e1V/j9vr/PF0mLpMW8wrkZBe+12+O5cZ7iNc+qkt4tE2aD3C7Hys4Jj/5N1xwEykMJAIJNZtXdIa+f1+O9b59xYXVd+sJ0LISXHfhbNpy+xT7SERjfOwUr47hjTyx4WzbCLWk8jURG3yc7oqGn27cQXLNJKNu04XQdSEfCHvAYmw9kCLYlapcLVK9IkxXNA0B+9ou49lPLmLknpcRxEKG6nqL43Jdg/f1n4XVTVNdT1C+kqN3Xg/X3n4Xzt5+B3921VlDXwuuWfTRcV/8o9PiqnhUF8BgdEGieBZwND5XzDr31epxT3T4Jl+GGJOhnKBB0Clz7iWVYSgWVViWCaxyrqtcK+DuC62ufksfJPO9t/wZmvZwRVRFeTxivrofSCike0te3QnvQVyXcpGbeHVJWkdQEvF45yPtdidrHvwCgJOUAKqVYEJXavD9H/zoHg+toXJUHlNIkDQF/wAVSWqfhXKFctd0RkZV2Qn1x7QGhJGxc7J19DWUig+MSecjjSJrEQOsWzerOpqQC/ZJkQToINbuXfmnZSIYqVyWSulD1Agr7FwrULpcadz0x5B5121G7JPL4OxLDQ7wIWVDqvPkCPtBSmft5XS5is5D/lhY3ZJM5ieqlkoqTNAQ6N/Pf1csKhxkDXocL3bSmrsGOQONCinBdGX65pKlYsYDXgam5qJ8Teyabyfc+As64QOtsgvrFFId+e2VPfc0/1dKKRYO8Kjd1uhZh9PRT6J6gE7M2FV1/1TIyX2l0AXReuITNH6WR6/ZLl7Bzk23qerrPX0LvuYvIPYHxDK9jYeuJlK93Jtx4TWbKc4hbFpoPZJjMUpN+8T8uI1ebzO4LljCZIW7ajrlY1xvQuA1sPNrDZJpmsHpjpWt3rETRVHpcsCQNAe+vP200vLo/uAMB6bLGLNiWrD9TfcxKBYJtgT7X8PC7lEIOj5L0U/jlRg4Aml/nMXg9oTZLenPDjaiVqePQC1CXchYAmLQtVK9K+P3cHKOtqDJZhRtxPeEVvlQUHRISC5fXqLJO2dnGjy3DiVVtg0dpjtcBJnMCXleaCUAP6npMMNclJaZ06r4c27epxfnlnDV7auE299bPY3IkRe2SNAtEbSoqLeyRjgF8djZ+bHmPUW/03Y/AeN7Cxo8to3e9h+4JF1d/ehm5D/R/cBGD6wvULufYvtVD891riFsCF/8D39f/OOtdNh/lYOfFS4ifeAe2f2gJo3kbo3kb4XaOqbevYuMVyxgqmWP3BUtwJxKbL18ym/z65cyMPaMDFrZ/iPK/4GNn0P9BJWkrgJ2bbDjqtdGUjXBdYDRnG+na1iNtFK5A9wVLGBx1MJ63sPmjfC9tWKklptsvXUI0RePYuLVXaB63KDsL7zpjJK5+Rxk3D1VNhZLO2rvqJqXNidwdcTPrDpSZreDxex0LuU85bLBNg1R9X7KKNDYASVMvZABvmxLV8aGccmZF/8qq0nxm4WlTZyJxRa6w6ILjnDvkQs2ZwNS2WSklSdKRgCCN0UoptcwrXAiMF6ShvAXbwtRljA4K9SywlqB3E2WWzpj1B1koEW6zHiFpsv4E4Jju9flZzkTC6/F8NcWuf5QGo+5QYvYNq6xrUfjkwbMXFZKXz0bnZhpAW6nE3D/mGBxmLV7hAa37c1MjmVaFkdHoAJU74njk9fneNNAkJY7Bxl2Y3JGSgit6VPWKhBNJxC2B7gmOe1quJDJVzzOAoUj62/yMw69ewdnfXzTPrpVyfk7qrNdxB/zc1tkcdkTTWTtmsBKg9MiZcOEn1Vw6c09OC4UR57RMmWNKmxIwK1MESw/wtyzMrwGtr2nUNutR81BhyKHMl2PSsWzVH6qXKA12+jYKm2h+r0c8sr9TGm7aERfexE2zz3h9Es2ckTLOvSTgDSg39juU+fk73BTWzkuInD+3JtxcWLnA8LAizwlaTEx/gUFCShuhZPrc1Ps7Am7PQrBF2Zwd83icEb/sFGbjKh0a+XodBiqcEa+31xWYzAsEGxbssVCod20oy+e/9SUec+WyMEGE+gO8lpT7KYx7Wq6XwmvK6HUsVK0UZYTBhgVnoExaBZ+VrKrpfwyK6/WNnrMsdR4i4zFHbR3s42dICzj8mytw1UbT7ZTBu7Rqwe8XyAKBoJcjqat5Y4edeO7uMfpHWduYTVXgDFPYt9wI8W23ovAsiEzCTgqkMyxUk8u3Q1q75i41b+6u3dF9vnrJMs+7rumTDum54wUGhfwOAwj+Dp+HXOHg229bRdLg2Np47xrC7QKz/1gg2LBUIJVrYB0o9jsk5lUvlnPdzOckKhdtk2CwJ8LUAj2UlsN6SF/fCm1fxrbf9tt+22/7bb/tt/223/bbv+H2UDI1/2ozO9Kmn0BaA5yRVNEcaaLGuzMpzpgRu9ZZ7rD9HYlJ20JStxBuFSarE2zxvcJNiVSRNIJN7uCn7svhdYH6BVY/25FEWgHGB5WvzgSIZoGpL/Jzb/i5VbPrtieMWhkTyZGK9OQsCtMZFVEwwmTHQOWaiqIPSKXKKgLSJj1o7jOUuPhdiagtEG4Vhv4FMLKZ1K2SIuSXhcsATGah9lfMfDmxjjbRlIqFqUDtkjKX6/MYtQdB3FZENuV3IS0VxQ9YNKq9WuwJI+1pDUjqNqJpnrOnaTE+iyXthDKpPGTUoH6RFy785L0YHnBw6bs87Nzs4fIvLBsKEKCyLy9ewnheoP8URSlzgeFBm54ZVd7D5PF3YNKm4SNkSSZL67wW2tdn6h30IEoaAn6/QGVDYnznKWzfYsNOS2lj4QFRy0IWqsxEWPazeErAHUlIlfVJ68B4zoHXlUhqjNrFUxazRC5w8HdXmC6u0J8oC2l+WbnGzA0sIJqy+bOPnDZeUJMZm2ax0xacSCJ3Wbi+24RP9ymvQ5NbJ1JGgIE0pqGjIwX8bUax0rpUHhRKAjGCIhbxuvaPMxqY1iQzlg0WJDtjEo28roTX5/NDw1xpwBRZVV3Xv7zbZHCE8iZqnc1NBKtxIUflCmVQQYdeCfWLGeqXcuQ+ULuaY+71K5i0GZWfe90Ko7QVqGJ1URbpTzGSp30b0irvTdBhdmk0b6P+AGWg/escxFOleevW82+Hv+5gvLCXfgiUAAQAWP/xZVQ28lI2tFPAG3OcCT51L6JpCSuXmHnjKtI6MHVfhmhGonvCwsIua52rP72MpMXM4NWfWUb8hDvQ/8FFGiv67AMAx6mkQQBJ50VLyAOee1q10HrnKiYzFuI2PTQA0tiqVwoMnrWIeEru8fMZz1vMfFocc8bzzEKmVRbvA5RLxt9/B5wJ+1AWALUrucm6mL5WAJ2b+JnTb1mFdOjzsJtqpZsuYi08YLxA0qCdMAqeTBUQGSUz248pC38nswLORGJ8gLLNaEYaipo7UFJdn9nBSI39eUgilKdoUm5fIm4pjw5RHsORv5HGEydpMjtTKDhB4dAXKGmxuLlwgGiGz4+tiGBpTZM8GYkmQICRbE34kpYyah6oSHJfKN8qPiNWyv8H28wkmozJkF4taU0aaMHVZUbuRQZS3lBm9e0Y6N5EiWYW8Bi9AYEaJCkKXP6FZTPPAKB0rZsbUE+4LlWBO7N7aU2g/ZUckzmBpGphMl+SFaVN6bZuaVUgmZJGUpdVFfV0jnM0zYhLT5S4BeOpBTDzJh0gWsjN+wMloCCpM9usCXh5wCyrv21h6r5M+eEofxSHkio9Jo7nbNgxMDwijbGlNlLWfVJHzzs3O8hqyu/LLaV77hCKWgYjwQWAwRELnZtVcXvBuTIP2Heqyk9OAxPcEQlvWhLuDpl9L2yJrArEczmyKqELpp+6EtEMVRzS4nsNrmOGy44IYLAnACRhAf4OC9AnCwVGB9kn0ypBB4WiBaZ1wjooVwJ611twJmU2LVXZ0NzTfjhKHjwSSBsKAOGWxpacwyVQcPzIatJk8aTFub2q1hR2yj5Lbz+ByQLXGKNDSuK8IBWtTRJio+fCGWUkvOv5TWulke9kXiiIRoHxdZnpIyJnf3D7vC7SIREunuLnJlO7iv59KCNS9d1S0uwB56z1Vy0jbvM4wvUSwpSGAmloobKVI61YRlKcVHZ5IA7ZP8TK5zGZD5B/+T7Iz34RzjBF/zoP0hLwNoawHvVwiJXP7zEVTWcU1XaXeiNSKpJopsyCW8rIPatwfaiVGYNjClzg8xkpXCCeJpXUTkiVvfaTyxgctXDluxTFUKk1Cg84/+vLVCnNaRkb4IwsjA8WWD+p6a0Eb6UNidGhvXPEg2kFrIf09a3QHvRR1i7nmH3DKmszrmbIKhwo0xp1hNIGuk/jAjhuSwRbEjs32dRP2irdnkhMZqgthaCUJpoWShanFsotfl73hI2kCezc4sPrswNku8hXhTLXiqcEBs9axMaPLcOeMCXv9YHBcRgn6/k/XqEJ5OXMOEknLQ4qSYsL3mhGUaOmuEGIpyREzs63cwtnhqjNySvo5EirJY1tMk98sdeTmP+jFcy8cRVWKo3mvvnuNfNwAKXpXO1SAb/DQXAyy99R7kDTtzzEHtpG0iCNyJlwMssqEq2z1KsGW3yf4VFODlnI1LF+eKVTku5EvovqcUBgcMQ3/69dzXDsV7hAq6xLOKruaPDsRUy/ZRXV9QyVdYnGXfcA4D0kBU/C6+eQ3/4oeJ+4G5XNAvULOXYDO8J1iXAnhzfkIBI/4Q5YKSU1Vg4EHXW97udmsrqeof3WVcz86Srab101MkkheT1GhyQO/dYKCkeYVLOl5BJ2Ks2mbuorMaVrGlmb0xBPG/nlPhcpwY5ENA3ULiVGquj3c/UaDjawgNFBgbQBBJ3ckM4A4iezkDSWYBtG0qiN9rJqKQeI5rigomyHbvOjIxLORCBu8/30oCkdoHN7DmkrCU1FQrrlvendyMHXVTVg+rV6U5iHlAzCYl/tH7ONgeRo3kL/BDdv2sxztEAJVdKUGB6w0X/OolmoXP2ZZYRbJEAVAa+d2eSHBZKZHNkcL3TuU3LaO+ZQJpJIVNcLNC5kaJzPYE+kqdkZH8sQz+YYHs+QfwONDZILSLl0O+b/aAW1D55GHkgjYdBt84W3G5lT/MQ70P5yjuCjNNw8+p9W0D3B87MToPX1DEd/fQXORKJ6pUDnRheN96whq3KDRxwxgwcHfp9/lzQE6hdy1M9LU7NTuED7KzlaX9X0NuKovUGOxv08ris/v4zoSSfhDiTGP3CKdSRjCSuhcWRlg+aBfp+SJ/+v7sbB/8pNpRMBg8M2Zt64inBbYvtlS/C7BXKX45weg7weF02tD92z59L53bLGo3GW8iC3T8KRHQmzeJSeRHjJQTKVm8VEPEXZSVblgqnwSUiLDuaIp/g8xNNcIOlgkTPis0haGmVnWY3o32CHyPOtRzpIa9KYiFoxJZO0E+A4Jh0gms9UX2bdT+5TSiYdkhOzQCKaK4ybeDzFzRYEAEFKVFqXSJtc9OYB++zc61cQzbAeM+juooBOSTTuLx3b4wMZgw9dUrq8fomnTkOByYxAZT3H0V9bQeHxXg0PWuhfR4lMWgeq6wU3PmFppNt8IMPgEBf3hcvXBTucB2feyKDdeM5C9ZIyNt1FY8xDie4LlhC3ShlQ4alFeAxVB0PJ0ORgblDFaVWisLk5FRk3g70THJdExhqJ3ZRN1p1KY1jKusGyv+WBRO+4YwxCIUuTTD0mTOa5Wfa6lJTFs6WklkadMDQ2KyE1zB0ASZsUwGi2wOhIjqRJGtnokESww0W8M1GLd4vyOmcEI3tKq4oilwrM/gklhCJl/7ISbiLSuRT1B/j/xlccVC9LSI9zWbBNWlu4biGvFWoTTtlddCBD0iyQtgpSOWcK2JFA3Gb9RFHLuUa6qLDMsUXCZiwQXiNGWkj+Tqq5pHmOc0xWkZgcyFWfh+kfkwO8aJUrlrrXErkyXZUCapPDRX3SJOUsVkad4U5BMt6sNM91VuN9kjb7Sh5QekzyrAr6AYinClgx5YJJk8eVewxOeD0Bv0OJlkZktz/LWpM85HOXB4V6bxqmFj6fOVHoGmOB9ltX4Yz4rBauROtsgmBLKgId1wXjQ7z/RcD5VcvY8qAMUuSuQO0aO6cmqG4/MkTtcozMF7BvudFsBK3bbkb3piraXx4hmnYhvVLoVLi7TEU9nvMeBLV6RIKdctMz/eWUNMFMBaoVIU8oKqXfkZi+R8Lv0iwYKCWdlfUCzgiY+bSqp1NWLIXH+iASeFlXHq5LTH2lwPG7ElSuWYbq5owVftx96JudXIqH9PWt0PZlbPttv+23/bbf9tt+22/7bb/9G277MrZdbXTQxvZLlyByifGcA1sV/3l9Fk55PaCqDPecsZKYbCmjz1z5CbQsGopmjATSoAw0fdI+OwXg9xV5aFti7nUrRqZVv58yt+EhC16/NJurv38Nc69foUxN7Zj9bWF2z1s/soThQRtJg1v06tWctCslLdIkm+m3rJpiUHdIeY7IShlNuCWVjMWCO5LIlImTtEn5iqeEySZZKYvlAUbV7Vgg+m76xKQVEqf611vMLgwEwk0SqbJQF5AL5UNAmcHsPRnSZumjMn0PIQZJXSCa4Vf7S4zuB1sCWSDQ+jojIVbGiKTfUYW8Ns0FKecoMxAAJWDXfnLZ0Lcyn3ItTZXyP373HpmRE0m4Y4npN68ymvEPn9vTb9yxNGaK029hxkubH2ahBWkJVK8VBmygpWuVD5+G9wn+3ejpp5B+z2PMe3odFYHbErj8i8uoXclNj65sFHBHzMh5Q/qljOddTL+ZBoDRk06iup6i+qHT8AaUhzUuZJSm+YDfoempO1ERR120bQssrMaYe+0K3BFQP1/wWvTKa2dlQpHHBOb/aIUSkDFUdFwV/Q4EDv7OCtyeQHjNghVr6ZuF9r3S9B2Rw8jP3J5AeMkhcWWrJL4ldXocOWNG4MNNCUcdtx0zQtd/ziKzW+9YNdmeYJvXT9r0OKpcLYcDLXmpv29tD2hA35fcU5TBAgjWKd/R1771FVKIvCueeoakiUjbMVC/kGI0b6Fzo4Pu9Q6kVWYd3C0b7c/aCNYdc+1NE4SDRHPMQA6fcQpTXyoLOLVsYfYdn0f1ikTrXauImzYqH2Gfmr+b44n20Kqs5wjvYsan+e41BJ3cSCvbXy7M7+Zeu1L6cOXA/B+tYDxnY+odqwZosPCaFVQ+fNpk2aa/WGDu9SvwP3432m9jhvTgf11B8LEzmH7zKiofOU25T0Jim5UC1Q+dRuWKtYfcNr7zFFpfz9B652pJGfKA6Tevwk4k3EkBr0ep7vCZiwh3MhIDl2/dc+niViltTOssIi5c9pk8lKhdtJBVAX/DRjxdIFi34faFydS4A4657kDRq3oW/HUbx395FdKWJA4mNM+1J+z/fkearClQEiAn86Xxs98lyUmTAZM6jS6dkQWR87PCy47JbtrKU8QdctzyOyyoDjZZAO7vsGDc37JMobfXseD1+GxYGZ8nty9w/teXKa8B0L3BQu0S/S2cIbPh9LYSCM+7EBKoXZYIr7KPaTlX7VoGdwxEbQs7LyFkJWlQtkloAT8v8wVmvpDAmQALf7CCYKdAFlqoX84QbAo0HsjgTArzvhuvWDZF+wCza35XIugoSVZfoPXOVThD/XuJxlk+h8FOweL0hPNl7QEbhccCcXckYCfMrBGUQLnX6LA08jN9v3VrnCWkQj8DaX2vBG7+j1Zw3f9JSR1Jd7xH0paYzBVwBxyvrJQRcG/HVlIplYEPS1AQQMqa1yd8pfYAI931czYhAFvKi26e1K2oDVQvU2KX1Zjxs2KOM+4IqF5hxmH4jFOIpiW8HYtAikOUAQcXPCQtoYrvFWxlS3sXMYNRuEDlgg0rZV/NquA43CHZLtjh8wSpYQAS/lUHWQUYHWIftHKO7dKiOWT1sjYy5znnoUTvuG0MYL2uBSfSWTuB+nn+zOtaVMxs8LpIu5xvgk0BKyFoQOQEMHgdyptG8xZqF4TK+lOWD7Cvi7y8p1YKhOsC1QsW3D6z5s6ImZNoRiC8piBBvkSwSaliFtCYNXeB+nlmLoVkltDKgGDdhtdXsI9rNiqXSMtzhgL+FrO1Oy9ZImlwywIEMJ53lf+bhcks+7y/JXgPdngMJRiDPjXBR8+UskgAzpgddvYNSkIsAKQZvEGO5HGPRdYIUL2SovBteL0MYhSVff5CakxFrR1XfV45H9WU4Wk0y++z/yixeZtLCIS6b86ozBa3v6DGmRu51ounaJyahxJBp0DjvVQTpBWqeUTOcd5VY76/w3sdbFGtNJ63cP7xPqxdRMa511MFEF590Mt606S0UDzIL/mvFT2du0DQLZAHAlNv54QbN4Wqe1F1DW12Rp3qzkKh3LcFMp+4VX+QG+dcAEABNC7m5aIiBUYLlqLT8Gd+R6V8D3HAOfD7lA0UHvXLnRctUU/vEYFa2eD7ORGlbLlHslnUon50PGeb97ZjRRtRpqLdh3HihaTURKckAaY4/Z2SjKMnnMYDGhFbktoAmHqP2uWEi4ZP3QuAUrJohinLaJr6di1js1JKz7IqNy5ZyMl952aH1LWO0sg2qIP3BpSBRdPKQM3i4iPoFNi6jYNtWuEAq+981OaEVPicFGf+7PO8f9/7CEop7okRdAsMjgpMv2UVzXdzEVZ857fxPHehvgEey/bLllA4AvLbHwWAUp7xnI0sEMZsdv1Vy/A+cbchV2kp0GTGwuQpJzE4bJtrGz/hDvSeu2hMSdOGg/Q7uJArPA7y0SxlbNu32sYYNWpb1LHXOaHk/q7NiPqbuGkjevJJZIFA3BJI6jaSqkDuCdQu5+aYAGBwhANe0C2w83Af2y9bUnUdigy3a2FujznZJy1lKmpTQlm46rMtTixXfo4LmsLXGw6JvCIxOGIpKYHaLLdVCltSeuB3qTFPmpQbDI9w4wLJBcxkVhgUce7zGjXeu2aclQuHaXQdgAD4XDsjJeWLpJEgdZ+/BHfEZ6jx3jUTjPD6HHC9nqLEZDAD73heGJkewJo+Z8LvuQ8MjrpI6wIHfp8BjKBboP6XlF0VLuD3uQnThBndco+1QnoTktQtjBcEes9bRLidmffgeXNzHOzk6LxoCYNnLSKpWWbDnfuUzPaeu4hLv8TAhPeJu82GX9MAax88TdNIh47tu1v/BxfRff4SSWnKNFQbBkctgc6LlhA/4Q5sv2wJk6ecNK/bfPkS63HGpSxp6h2rGDxrEZV1ia0fXkL/OeVn5R6PO25axtQVAOIGgwR2StNSZ1zQmNQRSJp7h3Y7EYhmgd7zFjG8LmfNzUgqs0gGhLw+ZRIiZx0bUC5wkybHK92H3QHH9Iv/cRle34IzKcltQnIB1L+Br5/MCVTWlQGoqi0ItkqTXGnBGIZaGVQ9BD/HUqa6SaukcomCBDZnzE2PyMsakKyyV24iZPneeSDNZ4br3GDbEc01s4pE/5iFYBvGNLh1lmQwCEqXxgvCkOL0OBo3bThjacYBaXETPf2mVfg7EtEMzZxb71pFUrfhDQts/9CSkV1GLZuLn5YNb1AgrQKtsynrVfoSM3+6CifiueaeCoJVeezJ4+8w5+kOFf2zI9G7gbV/IuNCXao6Jm227Q5K6VcWcCFpTzR2m4EeLQvKKhJ5KJBWYMYjd8C5yR1KVK6RFBg96STx+hPKgN0hr/H0PXqDyXoqvytQvbwrmKPqZfVzIG3ek8F13NAlLX5PqwAKmFoeZ8Kx3U4owXaGitj16hVjuph7QNziPYvV82ApiwzW9nDMmsxKFJ5ENAvTxzRGX+P+C7URTOu0r5A2zaO9rjByWytTm5OYdLSkyTG5dp7BrTxgkHIyL9A/ofqiS1mT1xVG+mcn3LQ4I0XS6wgaSioinL9DqZnXJ3nL63Ajr8fyeIo2j+6Qv9dB2vEBNXZ3oM6N/d7f5j3JlFwxrXDzM7yOgSQ74SY594BUGYkGm5aq92FNmzMh8XA8L9A4T3NSry/M+iz3WENcP89aVE1eLFyOOcPDlIRDEHPuTEg+FDlQu8QNkaaRWQn7VNzmusHv8b36z1lE0JWI62qz2uaN6bxwCeM5j/PP2XMQuYT315+G9X9/Dt72GPGUC7efIpupo/jclwAAw4O7NNRaEr5rY6GlqIUjMXraKUQtHmPaoCQ9mhZImoIUTB9I6lwvcz1HieXg2YvIfWDrNhvXfpIE4LnXryBQG5vJ8YRr1nkGBKTFQFHuAaPDBZxI0EC4KhHNANd+cpkG5XU85JZDPKSvb4W2L2Pbb/ttv+23/bbf9tt+22/77d9wK+SDl6UVD71E6P+n7UFnduwY6B8jkerqTzNbotOf0TSjC7poUssu0mppdjn1DqYUhwds7nyntGRGIq0IEzkuXJopBdssst/6YUY0rYwp1PqFgkW+DqMi669aRmWDYUiRk26x8VgLVirRuo8/D7cKhBvMckiLqdekxaLetAoameaUhISKBqepNGmt9Cnw+oUqGKNUSl/FwWELkxkL43mmb7d+eAlJg8V3AGVRaR2GYOYNVGGpw0hmNC2NyaPflSYi4/VBryFVRNg4X2JBohlGlEbzFvyuRLipJQqMdmQhjQE1ISyaVdmnczAFiFnA6MvkeyivCz95L2Y/O8Z43sXOTTaO/qeVPfIx6+8/CwDYflkZZbYjiVRlRYKPnTEyNmdCSZU7LkwmSGe6cldFR1xGjVpnU2ShhYU/WEHtA2twRxL+x+82EiNXeTC5//2L5p4ATN9v/cgS5u9OjWTRHTI9PP0mSuaCbmEyU1pmaY49UUXogxyZMhl1RwU6L1pC7UqO8Q+cMnK+NBSorBfwBjyvtCKQfs9j9nD59fMQbDJVbSfAhV9dVp4eylvJ4vfcY7SPUWam9r0+I+fBNoulRcFoqTYNHR0S8LqUyXkDylK0J4j2pdDABHcoETf1NYHpd/GUQFpVWcEeDUJHRyj5Gx1iljELhen3+rn0u/QkYZSXUpLJnECwU6BQEoKknUOK0peqsIXJfGUhz7V6uVDXns+0NgT1OwI7Dy+pU7ubM5IYPuMUrv7Msnov9nUAcP/m0+bvBk++DeF2geqfUwJZWc9Qf/8axguUOtTft0YpyXoGb1hg+kvlh2kZm2695y2ifjFD0GP/0RKzPAAa71lD612raL1z1fy88V5+D7oSU29nNN+OYbJR2y9dwuyfED5QvVI+x/3nLPIY51mcrt+n8uHTELlE8NEzmHvdCtpvXUXzz9YQPfkk8kCg9oE1eIMc9fetIfjYGQTdAlPvWEVVER/NtRvT46H5Z2sINmw07qcsQ1osdBYFVDF9gcpVgXiK0VpvQONnPQ7G0wUJZU3KWOy4jBQDlDRpKUn7Xva5tE5pb+UqpVR+R/WfjM+KE7GQ21bF0VpW645VAbdQ8ppNabI4/o4wcA3dr9OGSuOojLiGnjgjevZoeY87JMGzfoHQAHtCA8DKOqOihcvj6h+1KQUTjP77HZKqChum3xUOMPOnq7BjmrumNSCaspi9HhUItvia9VctI2pZmLQt5B6jvpmvouV1mohu3ebC7xBWAfA4Nl65jGjagjOSzFo5AguvWUHuAd0byuhzsF0gmlF9uIc9M7uVUX7pTJgtyioAVEbF69MzDhbJp3mgxsMA2HnJkiEqZlWJ5tkC7lDCHUhU1ksfrLglcG3RRrhB2WJaZXQ/94HxglIuKHpV7TJNdIWSObojRu93y480DSxpEd5C02M1HyqoUdqQGB2BkX1FcwWShkT/OYvIKqRBpnX+ncg53jljRt+TpoJfWCSX2Qn9dAA1T2rPvWDvWFA4hApYuSKkFcw42inH3TxgJqfw+H9nTF+dnUcVyOok+h37lVWVdWO2yh1aGB8gYSwLYWiCJAYy608oB9cZJJ5JOEOOfdLhHJG0Sqlo4fM9opkC40PM0qcNYcithfKAckYCtQt85obX8bpKwWdcq1h6z1tEWiOpMWkVECpjnzRowlt4irznl31q4w7+Pg9k6aOTc14bHRTo3poptQWvv+4DWcD7Fs3lqH3wtBrfJXo3FhCS99DKuB6yUqBxfznnhls0G4/r4ptWtVPvWIU3KEzmy0p4cnL5dkjPQXgtQlZ3IVY/X77fdrlG0GPfbgiOpmLaEwvVD50GBM+x/UVNBdSZZ4Fgg2PVtZ9ahpUIxC2V7XIFwk3e68p6Aa9Lw2qA9z48x2xU677CqADCdeUHtW3BSnQJhkDtgi7/2Gs2/GDbg5Ww6a9vhfagj9IdSzQe4KBYvVpw0VShFldaHChn38FOE7VZQ2KnMESiwbMXEbWIns491ckrArnPm6hJWQDxvtF02cFGBykPEjklHIMj3HQ5E9Zo+B+/G1NvX0XuC7MJAmjkt/CaFeohA05WmipVucbUrZ1w4NByhKQJzH4+Vc7wxAjqVHvcIm7W//jdCDqF2QRpjKBeMAVdiXBr74DpDriAAADkwPAYB5asyhR/435ORqODXGi6fRr+WQlTy4VLfG5a4ySpzdPiNifCeIqDuHRJahseJrI0mmGKVZuHJg1K+qSl5FO+xOAIn+r+U25D/3iA8byFrCZx+ReWv8lUdOfFS4inynuTNC1lYvcNE4QLOrw3Sm1JVqH0aHSAF27StpE2BPpHeYFHTz+F8Z2nEHRyDJ5NM9KtR7rw/vrTsOMCO8+5HQAn8bQOVd8k0D3hGvzx8ChR2BuvWMbogI3th9tmIAk+egajAzb6x2x0TzgGh7rxGC4ehocE+tc5yEJg83Yb4znLoJHzUGA8byGpkcKUNoCsaht6IKBoVSGlZgCQ1CWSFhcU2oAxD7VuB4CQiGaYoi98YmFzX6J/fWGwtL0blamfMn4cH1D40SqfB6+vJCtCmS/qPpmydgAoNfbxFL9LhwveLBBoXMhJxgoEjv6nFThjidqVApUNPqdx08L2S5fgxIUx6MtCmo6mjQJR2zLp/mCDckJ/Vx1T7guDXs99oH/cUlJATlD2LsmalZBqpKlwusVtgaRuoXWWm5PKRo7Ck6ZmJ/4uyhsHx7hQ3foRyseGBx3K2BTF8fIvLMMdFzQ2PuKge4L9bnznKVMn1H3+EkZPPwU7lhgcccyx9567iM6LlkwNiW7DZ1CS2XkhJW1JVdW4vX+NgRT1/tNvWUX05JOInnwS/WMWZt5I+VrjvWtIHn8HDv7OCrHud55C/P13GNna+M5T2HjFMrrPL/tw0uDn6do3gMQ2bd67u+mxa/KUk4ZiFrWpL/cGpGlW14l5jmYkIDnujA4ofbw6X+3ObaUC8QwXouMDHEMrVyjdsxIAAhgepbQo2OK4FE8RjZo0JAMsu+q4ejdwjOPin+PhZF4aOaSVsf6w8Pl6bcw5OsTxMlf1NVoWB6kkvpI43XCD5zVe4DOUBRI7DyeuWUuZo2nKsPT/h9cVmMxR4iRdyjO1Wa/0yoDNxiuXkTQF+s9ZJEWpSkf0pFraEFipxPigMAsnr1dSFCGA2gWgcS5HNCOQB1zIuiO+bu61K2ZTmDSAKz+7jDwk1dRVgaPxvIXck0iaXIDGavGbNHmtoxmJpAmMDrNOtPAUCa0qDZ1w5yYbdsS5J/c5btsx0dP188DOrQJ5KDA8KjA4pq7ZDI8xbRK1LG3OO/o9c0/VcwSca7ZvFRgcpTxtMqtkeQE3tQDHuLSuahYC0r7SBjcLaU0iWiAlUOOYC58SMysVyGoFoikLIqMJbFovkNU5hjoTRelzlOFrqAxkHS7is4raFLV3keSUwa0VU4KWV5SJc6LG8TrH+bjFc8uqBbKqRDzL8SmeKZBWiZlOWzlyX+L+31qiYXqsEO025+TCU3hih3VOk8OKAOZIZHWpKKzcyOceSXXxTI6kLg0ZLZqViOdyhNcERscywJLIagW8QWmpIQXPMZrLleyKC2RAS9olvL5lgqJxw0IRSIyvy+Bv79abcl7T2HjiovmcV471GbRV55TVCsTTOXo3c46xW4maCymjm8yqIG8oYSWkiXVfsFSaF9vcRI6OFIinCgyPFpjMS3RvKUzfjxsCUctC2igl3P0jpXDJ+8TdSCsCOPlIiELCPnEczhajJCLNkXsWxGPKOsfJdLleMUjwZjlH5WrjkzbKTZHIeCx+R1FDLfbn4Q0Z8d4HpZFtpjXWlI6O5saIOK0JbN8mMb5twhqlbrnWzSp83fCoRLyQYbJQYLKQI1PPCzeyHPe0jPOhtALiIX19K7R9Gdt+22/7bb/tt/223/bbfttv/4bbQ0FJf6ugpx90ZicLGNH1O5RsSEE6mTsQCHYkxgul0aQ7AKpXKEvYze5PmkD/uE1q1HiXD4gHTFQ0VxRA/VIOO2Z0pbqRm4JGgGk+zdlP6ywAi59wB0ZPO2X+Jg+ZItXNVkWsVk5vm2BHIqtQAmTHQLDJHfH2S5fQ+lqB3vUuDciUTEJThayUnhk7L14yxfQAMP3uzyMLGRFKq5S1pVVS4Mz1C1lYzXOUaH9eIJ4p4HWhAAOCBaSpIoKNgGBTmZ4mjMK0zhaGNFR/gFGs9pcLjA4zEuYOWbDodQXcvnqfAYs4K9cYfbFSoH5eINhksaYzFph7GzNyjbvuManV8JowNDAAphD7G1v1r77AIvlvaFr+5UxKyU5ap5xm6j6GUKfesWqoIwBoEPbh04imbNTftwYnKjD1VRJU/L+8G+338jizQEW1lOeFlUl46h5Vr9CEce51K3CHEtUrErVL1AUOn7mIcLuAO5AINwvT3w7+3wxfe32+FqDB68yfloaQ4UZOWVdOOZgoKFHS0RmA0ShpM2J95eeXUbsITN/D6++OmJESGZSkTUBkvFfSYXTbiRRFqmeh/gDf056UIA9nXNKLpC2NDETazGaOD0mT1cxdYciC4aYuLmVkV6fBAWVwuGGZrGPSoGdUWrEQ7EjKwtbLKNbc60gocyYS1csWksZuOg4DgFqaYuWUYFg5VCRUoHGuQO7TsNKdkNBo+swAqF765nR85Rqj2UndUqaivJ+95y1i+IxT8P+O8sb6Awq48aerkJZAuEMJZes+dS0jIK2Q1kX5ZClj03K01rtWUf3z06h98DR9wKYICQh2cky9fRVzr1vB1g8vYfJUggdqHzyNzguXMPUOStrCndzIJuuXc/PcbPzYsupvjPx1XrhkTHILV+Dif1xG2FEmzH91N4JuQUrbh09j7nUr8Ac5hs/kezljwJ1IbP4ox5foSSex8AcrlCd+Q0trhD4kdQvugKTM+T9egd+hnMbvCnRusg0BUEhFR2toM0UlNwoofbJSGImTlSpppk0aW1rnuC4t/i732H915NFKldFuSJ+X8QFCWFIlKcqV6bGlZUu6a6jvzoQqgEIbLktmAbSnCu8xswxZldHUeIrn5IyFIVke/+VVSFDqlNaFGb+ciOS8mc+xMFsUSnaa8LlNFbgGANof+DxBGhLoHyOoYeE1K8hdgbQmjAdI4QpUrhAuUtmgUW/9fWsoXFVwrbJJWcisVeNcASfm/KRhFUkdCDckgh0JkROqUv9YCeUQOeceK+O5pnVSsfKQsidtJj0+qKRlbWYqpE0pot+VGB/kWLm75YFE/zhMFs/v8Pq6Q8qvgh0JFJwncl8a89G0QXBJHlJOOD7AzGFao3lsHjAboaEVAGU/7E+EnOQ+JTvOgPOav23Djkjfc4YClasCTsTXVK7YJLzlLHo/8dNrsMdUJyR1Sh/53HAstmOgdpGEMXdEyZT2RXFHVHM4YyWptQC3RxKaqwhmdkJamNcXcEYCVkxCWnjZQdrMYcXsP1Yi4PRIc3MHlHFasYDbE8grzFS6g7KfWamAv2lDWpQoeTvs+O5IGCmdM+K8UbjMetoR39uaWEgbgLdto3LJhr9hw+tLDA8Lc16iYPbdjlhAn4X02nL7Fgq7lFPP311g6mxC4txVxxiTAygJnSpzq41AAWD8QMOAeJKpAvZYwO1a8Lfpt5j3PUNftGMej5VTxSItILjioPVOmkELAOEVm59nS9Mv7FjA6fO6NM4rH66YUmettPF7EvZNJ3Dtp5ZRfOe3UcHhO5jM+8jPngMcG4VrIZkOFV2wjP2nu8zg9Rxp4E4AoKZCt8/1n7TZX5K6MnYNKYcXErAiC3YMtL/IcUP3u8GzFzH1BQvhNjOSeQD4OxaCL4bGdyoLCSiwUo6XtQsC/jUH82uAv2Nj5nOU+RYu13p5KMu1wkNo+zK2Xc0bSiR1DkL95yzCjpUULeQNZiqWf6vxz3GbGwavJ5H5AlNfy1G5Ks0k6kwUZjkBvGG5KO7cZMNOuJhLQ8tIz7xOqddOa0qPPpDonnAxmrfhRBxkw3XiObdfysWAOyaCOdwu0D9G7bSVcNMUN4mJBIhG7j7MQlLnJCAKTiBaIpVV2bGr63SO1pKB3lNvg9+nlKB2iSaEaZ31DAClLrtxolmFMj9/yyKVaodpdifiJtGZyD1O6PULOaqXJPrXEV/ojNSiM+Fi1esKVSsiDXGMxnnc6Emb14sLC8BKSgmfKNexkI+5CYCib6UkiQGUwOjFYPttq3sWo/H/catZ7OiWPP4OWJnCSu6aP1tnC0RPPonxTHkx7JjXtf4+1kFs/uiSkXmEd51BNGUhrVOiM3gSN9PVq0DlGmU4lXVeY70hjRsC0tYSGPWzqfLzKh8+jXCbZpSFo2rNplzYERfUowUbs29YNWSnyt+wBiKasuB32CeTukpd/8ApI08BSM1x+8SV189Toz44KpRrNYCiRLxa6tq7Q0oUq1ekkT2JjFIPO+Kmy45KPbKWyGHXxkofg8iEqWciuUogfuIdGFy3l0gnLWCitPTV9QJpU2Ko0PK1y4VBoEdtgaRKmWHmE7d+6ZeWEbeA0QGSvPyd8rnPQkobTN9okKqojVu1eZ7fLTA8bCENy1o9gLKjrLJXIw2UhKi0QqR394YAra8AOw/nPdQytvpH74GVU4pW+chpg57uH+f7LfyhxuTyGc1Cy/SJ+Al37PnM+Il3wBlL06+Spo31H+eGpXEhQ/gXZwxVUNcjDp69aDb3my9fMnVC3RM2GhfUxqpgIGPqHatwJsSypxVKIPSx6O96Q9V/ziLCv2Dtz8Yrl42xnQ7GBB87g50XLyHolmOobn6XEqzmn60pzKzE+quW0TqbcXMh+T6ahqWDCMG2hDcA6hcYtNJUJW4suDE9sJaRClSh9MKJNLWMi0ddl2VlQPWyokZJoH6xUAtXYbDH0gKg672kMFRKfc3sCbX/WQWmvjGrcfMvMhgz0cKXxrDQGVKeZk/43Zlwk3TuN5dg5UC4ITD32hVjVlq43IT2TnDxnntcAOoNXeVquTjv/cBtqi+Rxpk2OM4nhobIv7NSytaSusDwkG1kMPXLmZFwZaGFynq5ya99YM1YAuQ+n/20JlC7nCpsd/nMVNYLWLne6LFOg5I8RR4LJZwBDQmthPVQ9fOsU7KSUn4sHbq/6w2PdIiStjJeJynKIEnucYGd1LnYzqpSBW80ua2UMbojgWDLUga5AsGOQO2irlEUsM0mlZJ3bmwEIJSsraDUS+QwNSdJU5pAqd7kBtsSbo8I8is/u8y6srFA9aqqYRwJmnxmREQPj9CI2+2zr7hDotMh2Q81HTD3SBsTsqx/tVJuPpKGVJsOrk+cCeBv2awPjhmAciZ6LmLdVB5SnuZvW4DF8TvYhglW2hNV0xnq2kthaHTOSN2HiPfWioHqJR3wUia9E0GzUYeG7f6OkmsWfPYKlxvmYGvvot7KeV3tRKB/1Ib7N5+G32H9aGErKZ06j/p5znN2TENXCD7zGlXN61RKN7NQyehd1s+EG5apx5v+YorqFUVCbKh6zhhqIc/Pa3+WRvR2xJpVVxMRG7ap8XSiMlDpTCTyr56FHUlkoaOM7QVyV8B6xM1IZ6sYHQ6R+xYmUzby0IF94jiyf/cYOFH5bOmNx+6Wquvg9YHR006RMKmCJdKCWbu5A4H2PQwAjeeFCSDlHgP0wyOUvhUe0Dqbo/3lHFbOc49bDFq4A95bJ1IkwrHA8DBrdurvW4M7EmieU9LuK2IPCfjBtgLCeO38T3/ty9j2237bb/ttv+23/bbf9tt+22///97kQ6jBkd8im50HndkZHrQUUIAFrtVrOSkZuU4Rl7SrrEIKS7BZZnmcWGI0b6tCVC3f4K54PGsZ08LC4dfoIIs1dTaJ0gTF5ncZUbYn/P38H61g7vUrSBqM9A+PSqz/+DLSxt6b0T1hwx0xy5FV6QOhDe4SRa7yejyXeJrRoywsCRzuQMIZS0RTNprncti75BxpReDQb69gMivQeSEzSrkvkDzusQBUtEZFqHWWRxdERm1GRLyexOA67vqTpsRknsfaPWFjPE+jv6wqEU8BX/+dJeQh5QcsiAOiWRVVDIEH/ssSKlcY6RM5cOi3VtSHkqM/mWcB62QhR//fqyjlZ76KWBXcZhXggd/geWii1D/V0gqjdkd+Y8V4mXifuBsil4qisivSXycVS0fCoyefBATQ/nKKwbPpXTL7hlUT3c6/69Fov5WyIgBGujE6QAO9wiEZq7JRwiL8XVStzCcRz+8w+lH7wBqiJ51E4QhjzmgyQ2MWj+rMWKLIgt07eW2CXkHfi5iSFK8nUfnI6T2RIIDRoMk8fzY8pDw9Ykq60jplXZnyrshDcvLtWJjsix0BsMqoIv+W8iAdNatd0tmGAu6E2aasxuPX0eLcB5r35/D/8m40lZmmdITJVDgTEn82Hm0ZGUI8LdA9QWM/S0UxnVhi7vXsO+N5mvnqTIATwRRuA4wWOyOB6lVF/ruYklAUAlNfYnasf9xC3FJGji6M/NDr87Vp/ZujaYUrEDct5L7A+o8vIwvpfeIOBRrvXTMyNoDPaOtdq3teL3YlPGofPG3Gmt0mnp0b3T2v8f/ybmQVgal3rJoMjQaQ6Oh85cOn0X1BKVWtv2/N0OGCjsTo6cz8tM7mSBoWgo+egZXL8vq8fw1JzdrjWzW+8xSGz1zEzkuWkHtKrqEIbXFToHE+g9+VcEc5wp1ShseMa4HkO/aaio4OFSbb5w6Y5ahfznH12204EcedpEE/EEBJxWL22/FBif5xZoa8voDXU146VWZBr/y/HAWakZj/oxUVOeZnpVWOSfrax1NAVmeGbzJjcdybliZT5AyFipALFK40UeHCkcb4cLzA7I20yuhvPE0SpTNhMbkVC3hdjpNWro6jIZFWSRrLAyDYZoQ8npK4/78uEZITsYB7Mi9w3a+uwkqYhRC5ku4pXxd9XE5EqRnniFIiV7tSIOgUaJ7LKTkeAYOjFsKdAu0vJ8ZwcDRnwxkJ+Fo+qhQLg6OWgVFU13NkAVA7z4zn8JCr/FkKbL7gdtMXnSHQvL+ghKZP0hsKesKFG5T+JQ1mYJIGP6d3I9A8VxjTyGDDQuWaNETVmXtScy/zgGoJACYbVFmXqK7nuP4XVikvisoMB+lsmlrFY6ldogGttHi9tGxSt3hKovcw7SGmsnFj/l2u4BTSIiBl+gucm0Wm/IJcysDthMXkhQtM5gkfKBSMIatIJTNmFiqr5xgdJlSB/koE+eQKMiPy0ttJZw6lw+cgC0qvssLVXj2EzQAkveYBx9e0KpUnXIHRIeUlNaGkL1T0w8msui5VaYAFWchsiVYCiAyYXJ8gr0hIVxE6hwLDo7x+dsxMD72qhPJSKqmvomDmxO8Q6OB3ldQwIADCSoWhGRYeZbfRjEQ0zetQPo9A72HMsunzTWsS4bqlyIq8RhqIpP2upA1Mr7jK2FwpINTacXRQ+UANLWz/0BKvtycRtwvTB+2JQFYtSJJUx2Ll0hBDnUgaRYdus29YJZVzs4D9//lH1C5FKO79Cqy//yyqlyZwRjnqFxN4G6x58DZHJUQKQHjlm5fJ4Tq/Z1WaQQvJDJqnxlY7kYb6278eqF4EDv02x8Zgh2OZN1B9qcfsatSy0L3RRtwi1MLv6kyOIgDaLAtImmVW/dIvLVMOOmUjbVBmunuee7DtQWd11Ne3QnvQm53KBheGIte4aL5FFqjJalzKT6wUCLakcZ5NmgKTtmVkFtUrhRkYC0/AjqWhIUlbkgo1UeZzLm9+62xOSUyfNz6tAfF0eXyjp51S5ojEKur03vZLSX7yenwPK1bI3QE7ZaEoWV6PHaiwKWlwxuKbOo9OncctC2nFMhKtLKRBYvo9j4EzKt3qm3+2Bu+vP22uiW7ajFTkvG7BjiLBeKpu5CJlWhrbnUxJtM7S5btxPxeq9QcoIbj+F2hYZSWlvt6esH5hcEzpWSPg/t9eIp5ZAMGGQLhOrXV4zYY7Lk+0ulFgPG+p3wlTF6Dbzov3/t8fUPZ07SeXEXy03BSN57ij201ji6eIEtebQV4Xie1bXZp6BjAT/c6LlzA86GHw7EXsvJgo78n3EpFtZSSjFS7Rzkm93CzHDUqves9bRNwW2HnJEoaHS03g4LCN0QEL135iGcNDxIVHyniOemGBaz+xjOplqRDn5QO9c6vAeNZCPEUZYvSkk3uogXZMPXW4znowK+dAl9YlxgdKx/j2lwu4A05WXl/1gS3ep7SmzP08qQhUwuildX+czFL7fcPPrpl+FGyxhkvr0wFgPG+r7zy/uAmEOwWyKvuF16Ojt7SBymaB2qUCrbMFXcjHEu6g1DA7cQG/wxoer8+auGhay6CUnPNGTvyDI/y8wRGXWmpbYHAcpmbH9J2+NHUrABelWUjTPgCYLN0IgM+FMyFS3B2o2gePCOH0+x5b0tiefBsms4Jo/O96NNZftWyuj96Ix0+8A+MFge0fIj2t99xFdF64ZMaqaz/JmryrP7OM6TetInoSX3f1p5cx9XZuojonHEyeepLktCaDG5s/yvfTdTVpRWA8Y5m+3njPGjZesQyRS4wOWIbu5sQSWz+yRJT3FO9X7QNrigZnYfCsRUNjKxxKA6O2wKTtYNJ2sPUjNHbcefESkpptpHm6hesWgk31rCWcRAeHbFQvChTKGLB2SSJtcvGTVaWRyYmU/VBTq2gECEDwXtYulLUG6z++rORl5Wa1cNQEXPB9nQEXVPGUMg9NKX1Km/x8jRd2B0ryJspFJalZ/HsnUguAIeuHRocK5D4XbKRTcaGc1iSCbbUQzESJMlbofVEIhNe4YXFHZW3Hud9UtVDTEslUYQxFbYVO5rkRBQ0w4Fa5JpGFFpKqQOM9a3DGnCudWCJcl+jeYMP7608jqwpMnnIShcsNZeYLs1AXmXqWOzmckUTvGCU4o8PcCGqDy/GcbYIEWUApYBYIhenlM0SCk8B4QWJ8sFALaDVPhKw12X4E64ukqtfo3lTK70bzDryBklcNdiHIp6QZ8waHbZz7LV6reEYaIt5klpvPtApTu6ONWaMZqah7DLal1VKuZSUcx/wu52Ud1PR6tHSoneffJ3WBYEfdQ/Bn018iQdUZsQbL61iwYwG/V5jaKDviuJlWJVpfcuD1lEm3xfne76i61x2LRrQRpWjuUNXJ2JSuB9sMCPhdwX9PBJr3cc62UqLWhQTimRz+jlBSXgvBVhn8siOue/TfWyk/S2+qWl9lfUw0Q/xw5ZrA8fdIhNcs1i1N2CdFoUsFiDMGuOj2dwSyukS4U3BuqEkEGzbiKQm3b9EAOhbwOpS0OWPaG2jq3NzrVxCuc04ReWm/EW5IhNf4N5CUuoeb/H/nEYVCS6tnU1HVnAHPe3s5NXhu6XKt1zvGDZAmik6/aRVWJmHHAtXLFgqXQdPCo+moHscABk0Kh3PteI6kVACwU84xo6edws5LlhDXLdi33IjRoQDisY+A/fCHIW77SBs2hoc8JPNVyFqIyeG6qasGgGRaBQbH3xyAkwI0j55i30rqql6uailjUbUJnxW4/AscGwuHfdtOpCFQOhEDLAD7fvsrhaJRwgQZrYxYd3vCMo7JvMThV6/AGbF+r7AZLPpfSbT8a67Z2Zex7bf9tt/2237bb/ttv+23/fZvuD2UTM2/2sxOWmFBonRYIJlVyJsXUFKrR2SIGyqCPJ2jdyONxXKvzIgAwGSePPTcp2Fb3GLEX0eDnRGj8oXDCIEu8u+esJHVKe3KPcpdkiZT95svX0L3RhvSZqRqdEhi5xYHC69ZwfRbVhn594CkasEdS2RVGivWLhaM4MTMihx+9QoJNT1GDmuXGdHUsjtNO5p73Qpa71w1Ub6pP78HdizRPeEhbdBUtHDo6wFQOjM6XCBU55JVgPGhAu5ImdgdZ7QjmmGUMXcFhkd1YaVEuC6w9SiBqM20de4zOqANJJ2Rou8ElFCNDxaYzAlUryhZm0d5SuGrVKiK1CRNRRX7b/cCIKDASiUW/oARhfk/XkFlY296q/22VSPTAmj0qdOxu9vU21fhdyT8PrUKyeMei8aFAo0LmZGxBR89g7QqcPB3eJ+m37QKb1RgfOcptN+2inA7p2nf21bROFd+gDMBmg9kcCaEHniDAk7E43TGSmIS8n3bb13dYxQW7pD8VF0vcOD3VhjxSwmFGD39FOZeu0J6WABUPnLaUOWsTKJ6qSzodQdAWrOw+3nXpp67jfLWX7XMyPEAiObpfRDX6f2R+3w2xgcKGo7ZzOqM52VZtA0gmimMD0XSlPQumcnx9d9lFiGaK+h3ZTPCClBCOT7Af0ezSlKSAFeXLCNnGR8QqK4XqFxhlNfrF4jafDbjhsDoKDNSmgplJ/TRGB3m8VsJ5Z+6KFvaWjbCe0GpXlmw7XeZwdXXJ2pZBgQxOghkU5khvQFAuEqMms6gssieke1c9f3JtFPS2D56D8INicaFHPbf/SPm/3gFg2ctUi770TMYPHsR/l/ejeoViek3kZ7WfPcapt6xitk/YZ9c+IMVtN+2igO/p6L2akw78Psr5p4e/N0VhH9xBpUPn8b8H6/w9W/g+2mfnfbb+J5Gsvmkk5h73QqkzSi93yvgTCQqHz6NxvkMm3cUaL+tlHA2372GA7+3gvr71zjevGsV3kCi+e41iJzUuNa7VjHzp6sIPnbG+K7sph/qZiQoHqUseky1UmZAAMpxgm36mDgjUFZpsUjd61oINoV5jYTyEqkpYlVBU1GvRwlL5aqA12fWUBd4F46mWJHEVvgqs+/qiDvHwMKh4aCW03h9YYqzvT7Hy7TGv9V0SZFxPsg9RlOzqqY1MouU1goS/SaUhbBTMZvqDilfEhklb7lPyVZaLwzxcHSQx9P+am4KxwuH2WeRw4yR0bSAN6KEeudmF+MDEiOVVa1dLjB8xilFV7LQ/nJsMj9ZoCSrSqY9mrcNpIUSNHq4xVOaXEeYAO8H56/JnMpodPndHfKcKtdI27IyoHLFgtdThpQtFo3XL+TwVZYkXBeon1fSpLpAor3MwrL/WDmlsElDYPYNq8yGSWbFCk8V4g8oT69foLzLjjmvpXWJyhVGoO2JQLgpy/sBesh4fVL6ClVwPz4glVloge4tJL6RpKoywZWCpMeGjcks+9nwOmYLRU7PvsKjVGtyKKMJaC3HZI7qjjzgtYAExodJ3JQ2+1RWlZgczBG3JbI6qbBFwPk1aRawEsrgch8YHKUcNGlIDA8T6OEMLYyPp4jbEmmtQNDRMjcS6YbHON7HUwLhlsToaIa0po57TiBt0otvslBgcLzA1W/3MTyeIW6VxyAUWGB8MEfcondQMlVgeH2O+jlg0rYwmVPmpTWJeDZH2mC2Uq8f4rbE8FhGuWejlLGNDyjJnA3kofLfmRKIp6V5bi//wjIKl1444RVKM5NmgWia7yVdkM6mwDW5tyv7K+jlNFlgP0mbStLZVH5JVf5NPKP8hBboR6Wlzs5Ion4lQ2EL1C+Vkt7c5TNX/dBp1K7Q60a6NqxUovBsxAeYwQmvRYqYaKHwbPgfv3sPHKdQ8+9ktuyj4wP87g65xrFSeiZqE+TCUetiyfNOq1xvZFXVlwP6WvnbVIe037pKEFedflidh1k0EFXy+GiG975wmH12B5RxbvzYMpIGyyqsnPQ74+H3ENq/Zp+dB73ZkTY7erApaSQI5fa+QblV/axTLlLWbbTvlZj9fKYkOhL1yxmiFolW3lAqY0+B2kVq2OsXVe3EiAaH/g51/Lm/C6G7zpS6NyzQ+hpMWq9xIVNmhgWyAGieLc3wANYKiJyL2rSiUtoxMJm1EF4TRhIBKAJITjnZeI4dT0vQ3BEH+a0fXsKlX1qmszNIY0vqrClo3Zej8Lhg1Mjf7ZctweuVl9xOAX+TeGqNaQVIYqte4WCjcYdZyAkp2FSadlUnNJlhen3w7EUuAlS62EpJv3FGnOilA9QuS8RTBer3E+2r9eHuiOe780zqv8Vnvgp/J8HFX1lGdSNH50VLe2RGutXPfXPf0PVamy+nrKH/g1wga12299efNhO/NkzUbfIUSoVGTz+FyodPlzU7vjBmr9G0a9LJflciajElPzhqIalbGC1wRZfW2Q8AYOMVyxjfeWrPABY3hSEqDZ+5yNqtWQv9Y3z94FmLELk0/af+lyXiNZ5StB7Jib/+vrU9ZLqsykFO9yVt6OZ3+Ix4HaKa47Yw6NysInm/IiVZbIEGcopgYyUKMTohXap+nnILZ2xR5tASRLQO+Z72qNR4O0MlQRsKXocK0Pg6ZYzOhMTB7gkbVkL5W/CxM8hCygLSmjCLn7QiENdt1N+/BmkDjfu1i7ZEuE6JK0AELIMFaoF3JVfPGhdhdgz0jtmorDNIEXQLc/38bYHqWdcc++5mJbz2vectYv6PVlDZyGGPBY3vdtHYAJIOdY3X8Jk099Tyv6ROOt03Zt87L1zCtZ9gYELLKAEaidqJWhB8/15am27J4/f+3E4lgk6OnRcvof+cRUyechKVD59G8DFKPNOqDZFLY17Xf84ivE/cjeoFe8/79J67iO2XLSF53GMNwl6bqOpz23nJkvmdlUvU37+Gyeze92ndv/di2jEloNrgVuSs5/C6FkaHKOFJaxz/pE3JRO2ixPAocf+6j1cvWHCHfE4KX+LCry4jnqLhYFZRi6Ipbtj9HWFqB/KQx+AOOM5qmY8zFgjXLRotOpQ1OQOh6F7cSFPTzg2B7u8aDR1sEgXsdQXx5Ql/T6dxC8PDACwuYnNV7xG1FVlvXai6FF6jhT9cgb9N41VnJLBwuoAzFqz5HLLzND/CccFWsrC0xnOMm4L1fOsFKlcFrFQi6BbIfL6eFNICg6Mesgo/z4lKMmbhkgo6nrfg9SSCTYnqFRqr+h0JXz1HjQc4sEpbYDLLezM6IEwQYHyg3BgmUzmcCTA+WMDKuEl0xgJJS2LnVvaXPGD9U/96Nd7OkMYHUFIWtxnQsmKS4dI60H3BEkaHygAeUGLKtUGp2yfhj7UGauM61PVbwqC8AcAeUV7ldVgL7O8IiELN12ML/raFeEoa409NRguvWeYc3BHlbiT9sa7Kyti/3Z7NvtexUXgMvOahRB4WlHmt81pwE876L3/LhhUDQqp+k3McdyYCoyNEeEPwekJycx5ss98VNmD3bUMETCuqFmnEwGN4VZj6zf71xBl7PUsFWCXssVByekrW80DC2yYu254Qwy0y9vPWl7nGoTRewO1xPZKHJQbb7Qtexy3K1AtV72SlAt4Or40dkdyXh7y+3g7/tnqJ1yaZKtQGQQcjJBJlblm4UPh5geplnqsVl5I3u+sgq0oEG5SnsU65RNijoIzYnlDCV3i8BpqS5wwtZc/BPur3CvSPOig8YHjANusxAHCuP4ZrP7Vs7icAhOsRxMrnYU8y+L0c44Mhqtdy+Jtj4MwXYN12swluckzld29Qrh/0v03t3gSoXCY+Wq/9va5Q/USg9TUGUYItgcb9PJbaJZq62glMINHfpoTRrEOVfN7rWGh+zSJOO+Zz2bvBQlYj3TBtsF6u/oAFe/zQNx//mmt29mVs+22/7bf9tt/2237bb/ttv/0bbvsytl0t6BSoXyhQeALuSEEJlAwr97kzr32cniR5QGJb7zj3VFlVIAst2KmKkjbICtdyKTsB3GGZz06rAvEUTOEWwCh5FjD6PZ6zEDcZ9Tj8mytI6jaCHYnco2kdi8ak8dmxcolwq0Du0qjJmUhDCkpa9IjQhLTm/QWckaJm9CWyalmc5w4pJ6hfynD41SsIt5V8YZZFqe5Ione9jcpGgeb9BarrGbrPX0J1PUf1Mr2G9PtoOIKmwflbAkmT0VCAcgCvD+XrogzDFA2qsl5KPervW0PcYnQw3JLGy2LhD1fgd3hv+se02RsLASvrZUoZAMKd8tp3HhbiyH/mfendCFSu7SIr/BMtXb4VjXOJiaZrOVDjPWtov3V1D7Rg/o9X4H3ibrTfWtKyrAzIAgvxE+4w76FbeNcZQ8yqv38N7j9QrhS3FI1rIHDot1boobTFe9E4z3OZftMq6pczVD68l5g2/aZV9uX3rUHkErWLBRZeswKvK1H989Oov38Ns29Y/WaiV0Y/DYB9sHaZn7ObKATBSLXOBuw8ghFPejKV2caswsikM2YGLwtL+IC/Q0mFMxJKpsHC0Txkn8kqyotppAhUvjAmfnYM82RbuTTZUisnOcwZ83r7Xcr2Cp8mitE0I+T9H1wkhU0Z5xUO+4g75nFc+bllFK7E4Agju+0v8fkYz5V0xcq1ksbmjAoT8a1cY2GxM6HEkL5S0owJWU2fvzC+VrrZsUT9Qm5IObUPnoadAH6fcoykUmYzTCbmiXfQ9BGEmuiWVizTH7Th59Q7Vo0Hz+773nz3GnJPRfKcf35g1347ALMv0ZSN9ttWEexkCO86s+f3lY+cRlplsXb9/WuGtFZZl3u8fprvXsP0m1fh/fWn95jbAuzr7ihH+62r5nf62Wl++J49f7v9cAdxm/+2lCGnM+bY4Q4YMbUnlK+5yiy3co0UR3vMyORkhpnAuAVjWpvWKSeWNrPK9QvM8tiJQO6yLyZNCSeiXNnfIbEod5np155MhQ9AKFpUlcAEt0+pSlalnAlQBew5jzdpSPg9dU65Mi7dBUagdFoas8Y8IAVRivJ5tVXkePvhLhb+YAV2xD7ojIBrP7EMJ1JUqb7AZFrBeHbJsUff/0hCC2LK1wqH/mUiA7xRgbgpkExRNhu16KcWbkk0zuUI7zqDoJsb02ZNaKusF8h9ZhetlHKepKUzXdJQAFvvXDXySmkB1SuC2eik9PHyuoQmuH1mRQqXUubRISUz7BJ20zxbmOfE6wljklw/B8y9lnOIUKaSWY1zFlCOZc2vWqhdlKhdIAxC+7o0v06ymxSq+H9Hrxk4VvnbAuFWYWSU9oTRbyuDytwo+bAi9WkD0eplgcOvXjFR/GCDoKBoysKB1YLmywpAkfvKhyhWmfK+zpTzWch9QjMql20W9W+XNEG/o7I+PjMVzsCCv02D0cKlWavX4XrD6+nrq8hlFrPx/g4Nou2ohAfo93eGljHkbNzP8ZyZLN4nmo1yvnaVYkNnKLyuohZ6pG9S8s+sXuWahcIpn1ORsU9aKY/LHRBuEE9LVC9YhpZrJcI8G/6AEu/KFQE75XihiY7VCwLte/k8Fh4zZ3YsUL1kobJOeIPXE5jMCqNGETmvZ+tLnLO0L5Mm+1UvqexS38LCH6zA60u0vsYMHQQMeMLrKJiVyn5ImyTehT9YQdCRZuxP6gJIUiy8ZgXOJIPfz1Hc8xVAqLXVJIOVFPC6Gay0ACwL1qMejuKer8CJJMTDb8Cetjv7qOYOyxhpS7gjiebXmO2KW4JG6QXMM1y7VBqe2gmz/xrUE02Rfto4n9MTLeA6Tzo0zdbqGz0P2bFA8+sFCrscz92hxHheItz6X5Cx/SvO7DzozU7cstiJwMlEFEDzfApIyrV2myt6PdaD1K7msDIg2C6Q1AWm37SK2tUcoqDWsPe8RQS9HFYm0T/CUSCt8gGvXmGHCLo5jUdTDpZ+v0Blg3p3K+MCLAsFa0T6JWYVgEFPe31JepcD1C6yc7pDHpc7IImqerVA9KSTlDmBA1daUzIMZeIWT1nwBhL+x+/G6OmnjCxLL4IbDySY/mKK8RxxsoPDDlrv4oI/aQjU/oqbwbjJgaVyldfNHUr4HWIeNfJSm2UVLrWh0pKmw4/nKdfwt4hqdJVredTmZGVlwJWfZQrXjpnab31VKJylMuSrcgLwusCkzZs3+d5HoHGes0j1z0/j2H9YRdL8p5OAqULcFh4wmXXRff4S4u+/A/LbHwX57Y8y7vbRk04aEpbefKbf8xjzPlz0FvA/fjcAynN0ajf/rkcjfuIdNCLdtWB0h5KTZwZc/sVlTjKqRycNC1HbRvyEO2DFNDbtX8dziJ580qDAoyefRPVDp+HE7IeFxxR677n8bE2dG3/fI3nPFFUu3M6Ug7h2t95Vv6RkM7nHvl65KsyCxu8qmcUQqF4iujVtsB9qo12AgQG/w/uoZWhCmSqKHAYvaqV8zrIK0+VWtncxZsdljZmup3IH3KhbOTX91SsFrvz8MmqXJeqXCjTew4V3uFmgeS5F/WIBdyzReO8aqus56hcKTN8rUb8o0TzLvw/0BhvK7VkFOgDAXf0SqleoNy5conRn37BqpIlJ1TIyydzfJR28uFd6VTjAeM7GaL4cZHKPQRNNSNOtsslnMa3aqHzkNKInnzQbruk3raL2wdMQhdxjlAuUGx/dR3vPW8TlX1w21ySt7h0y9cbE+8TdRnap30NvpjSJsfLh00bWCdDhO+gWGDyLfX3wrEUkdWGeAfMZT+Rn6L6//UNLiJ58EnYikdRt8/t/qRWOxNFfV/VHTWKXvYEadwZ68uVixOvz51lIkuDUVwve0xoXXHbMe+F3aD7pDaShXE29fZXvNWG9hh1z0SZyINzkwmx0kKS3cJu1CP6OMGaHWn6jF+vOkP+2E25wco/9PdyUhk5YuJzsGTTiwjoPGZCy0pKmyUWuUNQq4MDvrSD3pKJvSVz7yWVIBxhdl+PA769gfIDGgM6Im7pwu1ASJV4z3VpnE+Q+cPB3VhhAiDhP6XHa7bM+b/otvDbTb1otN/eBpTDERFXbMSlsh357hbKXnQKV9QKBWsDYKRfuzpjyXP1M642KyGlaWThcQCZNRUe1FEJ+xAVmsE1p4uCGHFmFtbKFK9A4XyhCHt83rQtsvHKZqO4tCX9bwhkCtQv8DCvlPZl7/Qqlhhk3w0lTIKtSxlY4gN+DqqMicU6Pc86ENC1Pza1+v0A8zf6Uh1w0R3OUTCVNYqf1JubC/7lMGZsi1EnBZ240bxnT5bjNzXwWsh6GRD4YWhigZPg7apOfk+6qsfqFq7DTuww90wY3zlaqzHATXWsljTS+cHUgUaJ+oeCG3aX8qLquajssUg71wnYyz2sDtTmHLOXtPAduWvVGKWkCsEqD6MJnvVC4LhC3WNeU1mCw4qIA6+cC1uONDhcqQAA0z3Lc9TswkuL1Oyz0nrdo7DiAcnOr11RptTQRBcq5J63y3yLX6wxVR1ehPNOOdPkBXz+eZy1yHvC6DZ9xCnGbm/I8EGZjqus241ZpnJ1WhcH7W5lErgJSzbMRskuXDQnTmRSwbyHZ0z5xHFacwtuO4IxT+FsTyLu/gOJzXwKgNqtf+rp6tvQGo5zjNZ1UB8cLhzKytF7KZnNfoPCB6S+lyH2YIF0WUnKahgL94xbmPsMLHk8J1pXbHHMGRwWq1wqMFmgi7w5Zix3NsL+vL6q5vyrRuMD31qjqh9r+NW929mVs+22/7bf9tt/2237bb/ttv/0bbhJ4CKai3xrtwQOyVZRMm0xN5gR617nwepLFmYlE92k0YNREs7TCNKmOMF/+xWXEdRvSEsiqpLvFdRvd6200LjKkZKdK5qMitwB3z9r7ZTJtYXjQRtJkWrd+oUBlI8PlX1zGaN6mKZkyLtU+CGlFwBlLJC1S2EYHLNhJme0ZzVvIAoHuCQdJgwXaXo+FkCzK1bAAZk82XrG8J8ocaa+Nb/PRucmFlUhFgeLrOi9cwujwXkpSsCUxmWHUMm4JpHWBwmFktXAAf1tidJgR0I0fW0awpYryOophn6L0w1DypvpFEl90VCj3GGm3Y1WE3OP1yj0BZ8SokTORRsYWfvJeRNMO+s9hcTTP+ZsfAG8g4f53SsqSmo24qSMxFsQ/fI4/rwtS6BZspBX6hUy/ZRU7L17C9iMYWhs+4xRJfIcc4+fjTHh8g2cvonfcR/+og/GMjcm0hdHjmWXJPYG4TZlG7rEwN26xr4wOUFbVP+pg63YX3YeVcr3tWx10bvLQu8HCZNrGxiuXsXOTjdFBC5MZgWhWIm5auPBryxgd4nlrSmBWAfrHLOzc7KJ3EzA8zGMcL5TXRUu//C7vf9IkJMKZKGCAirxkFYHxAXp8RHOKfqQ8KdIaP2t0pEzXa1mZlleODrKINGlScmSljOx5PcBTMI+oXcoedNZ19k9WMTjsIAsEBkct5B5T7oPrBJKawLWfWkZSB31gjruImwKZTxpb50YHaZX/797E5/Drv7uILBRGUjKZ30uEGTzxNgwPkQRVuAJpxcLmjy6hcSGDdBSpUWV5/G2hpFGlP5Bu0mV6XxPHAGYrAT4b3pj9t/P02zCZtrD9siXYcYH4++9AWrEM4OTif1zGxf+wjMm0hcvfaeH+/7pkIBYAZXy7i1yDbYkrP7+M7ZctYdK20HlRCd/wP343ui9YwvAZZcZxPGch/b7HGtnT6Omn2EfuPIU0LKOQaU0gajH768QS7riAN5DoPZeZHu0P0bvOxfbLljA8YJuMZPDRM+iesJHUBHrHXYx/4BQ2X76EnZcsYfCsRZOJLPskPbAA9o94mkS3YIsF17nPvpwFNKi0I2Z90yrHDAA4+msrmCwUJtvs78g9/lJ+l2N7WmHWyu9JiJyReJEDzXM5rIRyK3fIyKe0eK/9DjMmWVVltBOVvRlQmut3SoqbHZGMqX3Kwg1JCExRPiNWoqVAzDJVLxP6Emwy+ps0gUu/vAxvQAleWhNY+IMVFA5QP2uj88IlXP+Lq8oYEwg3gd71NpwR5X7aUwoANh7NcezSLy0jnuI1TOqCBtxVYUAN6z9O/7YrP7eMrVsdXPol9sEsBPrHHHRP2Eir9CbrvGiJ/aNtwZ0UiGYY3U7qAv1jFqJpoLKRo1BjWuESOGPHzI7YMTMmtvLsAigP09cwqVOiVrlkU85Ykwi2C6NS0JH6eAoYHSL9kQazpDNqCtyB36eJ95WfX0Zhs/heZ3jdPr/CLc5F4aaE1y2JndJi/5J2adDbfRjVCtGMMheuQEl1mfFzxgKTeWZDspAmyzpb50woJRwd5PtnIVC5yvnBmUgMjnH8TeuUNtYfYHZBWqRAJk3lWZMBEByntdGmzjTmHrMr4bow5tNWQhklIQU04bUjgeGxHOGmoAzWl/A7BAt1b7Th9gWCLQ0q4NoompFINeBB9eW0puRSCeWFWZWfY0dCZZ5Uxm9Cn57aRanmHp6XLvzX2c20IVC5xufb37Y4zgk++5VrlKnlLp8Zd8D5QTr82eAYzMrW7UsMD1FWJ3JmeLIan/Wdb8uN0aomvjpDYdYj9732FKWrHj8jmWL/8gal52DcsgieUITctErVCwq1LvRLitx4XmBwxMb6q5bRO2abEoDeiWDXmOyhc6MH6drIfRv5TB3IcmQtH9K2kLYCiMfcCvntj1Kdsxw700ZJh9NNP3fm/w4wOkTVzPSXUthxCZjavN1FHgCDo3YJIxkLIzlPGg7GB3l+U29fRdKkLLx+QWK0YKF6rUC4SZDHzD2UaGqqYtwG2vdKDA9ZSGsCtUsCg6P7gIJ/qj3ozY6Wj4mC8jRnBFS2CgyuZ4o2DwRaH6JePG5LWKnE6KBQ7sMCuVtKemDptDoXbnYMjGeZbKLBFx/y+pUM4V+cUTVB0kgKnIk0qD4A8D9+N1r35Qi3C0zfQ8Mlf0eR0F7KmhlvIEmFu5TD60sUDidFO+aEn1Y56VXWJRoXcwyPChz4vRViPDVueMxzmXvdCuxEYubPPs9jdgTCnZwyoQs5Zt64ivr719A8x9VmWhM48VNr2HoeqWez7/w8kqZA44HCyLGSJlBZJ3nNmXASaH5VoHYlR3U9hzPmROsNiA2ezFPT7g2UidwYiJuUGkazfEgP/P4KqleJ96aUgBrR+iVV1/LFFHZSoqf7T7kNVk7H9rglsP6qZTT/bA2Tp5w0Eh0A6J4ou483zNG4mCHYkqh8pKy5qV7jMYTbBervXzMu8ZWtHNWrBZLHPRa1D55G62yO+uUMs28ocdQASWfttxLpSwx1geonKAP0e5RcpBXWOoRbdBUHgOpVwO9IzP4J0dfX/+IqKuvazFYi3Czg7yiDvomE35WYvjfF3GdTzH62gBNJNO8rUL3Mez7/ls+r85RGO18/B6VFpjxCt8m8RNwuF4LBFhdrSZMLwLTGv9FUOU3CmcxT+w0oE71+SbwLdiTGh4vSwV1d+u3HFmh/KYc74QBZvSKRtGDqXawMZf2XWmRc/JVlTGa5sfb63CQ6Y07yemFbWWdqvHqVfcTK2WecMev2Co/HJh2SreJpXkuAcqa0UWAyp2p2Yspwdpuyzb5hlfKzr8SoX0phZUq+cGNmaka0XNa0Aup+C1z+xWVsvIK406TFY9I1O1N/fg/GcwK5JxDedQYbj3H3GOYe+S8rOPIb1HfPfgaY+iLvh5ahNd6zZu6dli5IC5h+8yogKCcdPuMUejewxswbciwa33kKnRcuwZlIxC3HSBtzVxipnDsp5U3S4oK186IlStyuczCeFwg6OSWDH+LxSIfBBncoMZ5z4ff4vu2v5HAiqQIyArN/Qnxp4WAPeRBgAMQZS2z/EDdq9pho7Mp6YSRE4bpEVpewIyJgrYTX2+tLjA4IXPyVZTTOUpZUeDyPwuHY7Y64salckwh2JOImA1O5L0y/cMZchDujsi9Ih32t8Oj+7YyVlDEBhkeA4WGiZ+2Yz000K42bfdLiRimaEZjM0TAxqzDwUXiSPws1FlhgeIQY9skM++fh31zhwi6CkbG1vs6dXO4DWz+yhP4NQDRHd/uswn7iDWkPAADVv/pCWXPxQKEIjYLGgR1KRJ0x55f5P1pR1wHwBkDzXME5JCYCv3a5lHDaMZ+/udeWqHPtVF+9Ukq5dG2W3y0M7j5uWUiarE/1+sRzjw5LTOZIEU3VpmhwnNfeSkhnjKZ1ULHc7Ex9pcDsPxZof0liqBZRoarHO/zqFfSeuwivL82mJZ7iIi5uSyMlY1CKi8U8FIhmgcH1yph0lmOJlj/VLlCSyE04+4WWNuUB7y3JbhyTwi2JvCLRvzlDpORvVs46EmfCOrHBcdbwzXyuQOHRnd6ZKKldjTWNU1+hXN4ZcbOsg0jhBulYecB6NitjvcjwGDH/cZuEwqQpMZkvkIUSc58hDvrIJyVGhwo88BtLcAeUi9kxNwrSBgbHKOeczFPiVbsg4I7Zx6VNE/HqFUq90gY/I61zUZy0eb9bX+W8kofcgA6PiBIR7rI/TeYl2l/mOF7YvNbxtK5fYv/PA2BwTK0ZLGKuk6bkM+Lz/OsPwOCedd0vBOfZ6Xslml+lAW/7sza8Pt8/aUpDBix8Hj9y1vckU1w/WjHQOMe1T66If363QON8TumizY2prt2Wqo5Lb0BrlyQWXrNCSfa1MhgDkMbmDQskddZGiTTH4IgHkRVIDzSQNBzkvo3xvItovmJepwPzAACr7H+6FeYYVH3QFK/jzBcybD/chTvimKvLEbT0PNzg+TgRn7PqlQL9YyTgJQ2B0dNOqZo5ida7VkltbVjo38BNdBqyNk7XU898IcN43lKGtexHGt39UNq/5s3Ovoxtv+23/bbf9tt+22/7bb/tt3/DbZ/GtqvFLQvjOUZ4OycctO5P0b+ObG+piiAn3/sI/nHO3bgzYuRAy2ikzQiytCgzywPlLbNewB8wAhFNM4MzvE6gc4KSqsmcxGRWIG5LIxGxEoF4JsfgaCkv6dxkoXuThfP/aQmjwwKXfmkZaUNg49EOdh4u0LkFuPJdTH/GrdLQKmmx+AtgtHt40IbXAS782jIG1zF6CKhiWIfFybkncOHnKBkRmcSkbSOrUH4wfOYiui9YwvYtDJP53QIXfm3ZZIKuvvx25AHQvUmgfwMLBqP5DCKT2LnFRv+mHKMjEr0bgWtLAht3WOjezEzZ9u3SyKWS6Rw7t1iIZhiRHRyTmMwpc8sqcN8fLqJzi0R0IMf4UM7i8VmJrdstRLMSG492sfOI0mencdc9pgBPS6C2X7q0h4oGlDQ3QMkoajbsuCzaFv/wOWShwM5LlpDULSNR4/tKBNspfXeedgrjOQvRlG0yR9GTT5ro4uQpJxE/8Q4j/0n+34QixE3L0OUAoHYpg7TLB0/aLBZ3DeWIJ9N65yqsnMWs029ehTuRCLcl8sDCaN6BO2DRbvPda2i/bW/hexqSquJEPOfqlQLuqIyO83MlpMNiwq3bBSrrOeb/eAWFC2w/khE3aUt0b+b96z88JXgilEgaBFQkLUa6+tfzXg2uo1RheFSaqKXIAadv4ep3MHOQhxKDo5R3pC0VeYqlke+Njqqi/boujgbiNgscAUW0ioCF16wgbgtMpkmgmsySDjj3ekaTdm624Q34LAKK7NahuR9AuYUzsowXlDOiue3gqAUrJY1t/ceX0blZ4PJ3euje4Bkvg9a9NqPcl5gh2N2iacpRJnOU7829jseT+zCZIQAYPPk2gk0uZoifeAemv5gj+OgZkxEZPHsRG69cRloVxkz0ul/lfdb9W0fsah88jek3raJ1Vkk8t0sS3NRXcvgfJ5hgPGsjrluYegdNcf1uhua717D+48vmuCofPo3Ge9Z2wQ6A3vWUzPafs2iyaP7H7zZFte23rqJ6rcDU1xKEOzla71rFRGWd4qaFwhZwx0V53Anlad+Y2dm5lZLj6Tetmmj5eN7C5mOYQYFkxtDtCezcXrDIuc0xcf0UxxJ3APRPSGMC2n9Ywb9pSmw/Sppnj3JcYLwgjbne8FiB80+0zHjWPwF0bqIEpnszMLw+V9QiymFyjySrImDmoXsTARheT6B3Ym+xsJWqousxvU3yAIbyZMccB3oPY5QVljKazATO//oy0qbE6CAl2IULrD/WxvgApc4zf7qqTJppOp1VCUXoPkyYZ6r7tNvgd5g1752waNJcJ3HSnUiCdjyUWVxP+Z7ZQO845yxpw2QVrZz+cQBl1ed/fdk8q16XWbLBMX7vnrAxeBIl46ODFoItPqfDIwRQDI9YGB+QOP5Lq7Bi0teSOuU/mhY2OEZTw3iqLDJnZlg9S0csbD7awuajlTHihMc/OGph8OxF7Nyqsj3rHEs0ndUd0tRUF80DpOeJTMLrAPX7KUXyupbxIQOA4VGOI/GUMhGtFZRReUDazpHWJSYHCtgJMPUlzoV5IOH2bPq19CXi6RxpjeNrMst/D47Y2HyMZYADvMekrG3dLrB9G78m8xKjIwW2HyWR1guMDtNnp3CUeWlVonuLAl9IJUdKKU8TBZAcSHF1yQIEcPn/4Of52/Qqi6eYoYnbgqbeGRDPUPIVzRWImxzj8pCZodyXGB2SyJo5RF7en+4jCqAg5Wz7NhIGC680KU2mmHXKahLDY7y2G4+mN9HkYI7xQb53FvI+D25J+f9aATsiJc2KBbJmjt7zFiEFn8V4Shij6LTO+xPP5RgcA7YfIdC5VWLhNKW4kwVpYCHSUgAFj3Nf82sWskDCHfCYhGSJQtzm56PgOnPj2yw4kerrt/Dz0ibvizNipgig5L3/gzRwzl2B9vuUCmMgkd3/AKofOo1wJ4fflcimKmh/aQj56XvhXu0jvOsMsqqNxnvWULlv29A2K1slXtXb4sJVex4CZVZpdJj/d4bMoF38XqHma3rfZbUS2jWZpxQwmuF4kVUFeifYR5pnSRQdzdsYX5ehfz1w8T8sAxLonyhQuBLVi5Qbdh4OfP13F1G/UGD9sTYGxwv4XYnxvMDooIS38+CrU3Tbz+zsau5QIowLjCwblY0caYWowahNnCDAmg8AaJyTsNUnHPrtFYzvPIXuCRvOkLKTaNpCsC3Rfusqtl+2BCGBuG6rzxHwLS5Im+dSuH/zaRTOEqIZoHINEIWisnWA2c9JBB/jwqfzoiVUr1C2UFkv0D9uw0q5gOu+YAm5y8Wxrx44K4Mxh8wqwjimi4JmiJO2BViU4dkKpet3JbyQNLY5AKPnHAVA+Yz37w8grfOkx3MWcq+UclXWU4wXfETf/QjgU38Lvwf4oJaXjs00Bwt3JPy+RPUKKVVT9yXoX+ci2CnQu95GsCURbhGrTbMxG7NvWMGFX12G3+UiSkjA6/NBOvAPPJbCppnfod9awfqrlpFVSADzewUGRy3UP/B5c5+1caGrEKHfSLsCeL3U+Ivwk/fCevphI1Pb3XYjpnXzPlESp6ofOo0quEnSJKrgo2dgKaPG8C5K2uSTTyL46BlksgOACzt3RP3+zJ+uIv7+OxBsKxR0xj4mbWGkbe5/+4z5zNoH1kydReM9a8Q7DgsEkvSshkdyXPf5S2i9a5WGlX/3twg7OWqDBO5/+wwGz2Ktiv/xu+E+/nB5PhcEfHAjFm4WGM/bGL1qGY2zlC2QFmVh4TUr2Hz5EvyOC2lDUZAoQ3OGlIf2jltGb23quHa44KhelYgTStAGz15E5TLpQIUD5Ao56vclAoWenvlHde07xLZqGVjjnDREJCvjxrZ+voATFYgbNipXJYJewQ3vVoHaFYm4YcEdkRZ14PfWcO0nl+Ful4NesCUw/fp7cAlAVrUQbnCTMvPGVVKkUlKw7ISGjl21eG3cdQ/wnENIGgJCEagG330j8Km7UT8PtD++iuKHl8wmNFfY39oHT6NQ/aL+0XtgP+Mggo+eMUa1AEztXP19a1B+upg85aTpXwCvY/19a0biCdDYs3AEqgDcUSkR0HQdAAi6hamdGzx7kZsDAK2z6TfR1XSrXJOYeeM3bKZfsITJU09i6h38+fjOU6h9YO8zpaVO7qhA7YN7Me0aYd3e9SwDgNu3ULR4vu5Aov3lDKMFB95AkDwpAGvMxaIdc+EYrgvUL+VIahYgJMYLNAcMtiX8LhDNcExpnitodtnLUfnIaYx+eRnNsxLeqEBStVC7TAO82kUuTp2IUrZCyeBImrIhJGsYY4VoDjZhjD5FYSHc5Oah/UVwzB5SGnbtJ5bRPMs6PStTdT0xnyU7FqhdJEEz92jAF2xzo169WiBqW0jqrMuaescqLvzqMoIdHt/WjyzB6wj427Yxh57MApVNwFHy1spmjuQGgZaiEj7wX5YQbFP6W7uaI3dpnDr9llX0nrcIKwHm706w83CPcjRltLv+qmXkIeB1JSZt0j6b5zKE2xbCvziDytQSiWgdCVwDBtfRMNrepmbHSlmbc+Q3VmgwK6Uxv95+2RK8Pue4YEcijfncCSkoqxFAdSND/6jDWk/HKmszhhKN8wU27rAw81nWlPgd1tQCwPFfXsXgWYuov38V669aNmbgVsJjHduCi4yI9SO1Kxl2bnJRuEQ8SwsGUQ4As5/NkQRC1W0pTLmipk1/2sb4gEDtAs1Sm+9eQ/LyJdgTtWB8IMfWI22EV2zULxZo/tkqrv70Mmtux8QCR9NCBWcoratdZKBkcMTi5qsHVK8ASY0krUyZ2bojEt2cMVCo+sL6+QKDIzT1tlIg2LEQtT3ULklE05YijHLtMXr6KdixBTum5Lt/zOac37FZc+oKQEglLeaahe9ZIK3aiNrcUOYB8dW9G0mQsxNKmIQkfXC8YLEmry0ghTbtJXY6DwQK18ZkgQj4LFT2A593kQUkGWYVPoPRjMDCGYHKh9cw/MVlI2eNU67PKpeBAAKADWfE4IBzBah8ZA1bP7KE+gMKxe6yv0ACSSpQ61J+Hrd53OEW145+r0DlCoPoWSgw/aYVZK9aRtzm/JQ0LDhjiXhKwIlYZ+acK3AJQPi396IhLn/T+GqnKmjwtFOQFimHIitMUCb/2tchl29H7gtk/+4xwCCBuzlC/O8es8dKQs+/zqTclGsyr6vMRd2RhHs/IC1b4d8l/H6BoCvQPSHgd4lwv/Lzy/B6RPo3z6dwRg5pdaomurqew/pHBsyDbQlvWKDykdO49hPL8PsF8kCg8iVgvGABKHDsV1ax9cNLyD3W+ERjAbEr8Ppgm5QC8kFuXh7s3/8/1fZlbPttv+23/bbf9tt+22/7bb/9G24FxIOmsT3Yv/9/qj3ofFcWMBKfB/QIiNo05ytcFkDrIn6A0bRgp4CdSFz+hWXEdQv1CwXsVCJqM+WfBQLDZy4ibrGguPF/seBSZED9Umm41n/OIuyUO2ItR7ETUlnGczau/BzT/WlFoLAZ5ap98DTq5wu4fYlrP8XfS7s0nAy3C+P1IW0SqbS/hqYxJU1Bv5EHMiR1Xq64RQpY77mL2HjFstn5D554GyZtG4VKW869dkUVb/Izhoc8ZCEQfIqZLy3FcIcS0mIGwkpJpso9RkWsTOLKt3ssyK2TaufE0kSoSCohEaxxThoakcgpH2jdl6N/zDKfVbvEg80DBSsIScPzehKT76H8sP+U2/bc8/H8P92ZdcE/AETf/QhzfbSccHfb/bPtly4ZDx3zs5ctoXfMxfAZp9B9Pv92d/Yn/T5SqDZfvoR06eEAlClsVcDrSvR/cBFZxTI0Nt3shFm+3nMXjXeO9vuZTFOKET3pJHKP5LZM0bLihoXhM04ZP4zcVfe+bqN/nYetH17C8DAj26OnnUI0VX5uVmFkM/cIcdAmsOODlDoMj/I5Wn/VMk3gfD472S7ylZ1K9I9axpOicABIEvjcESVe3qCgxCChvI6AjdJMDwDCT34BY0VY0gX/0uLzVL+cIdhhVNOOJbKqQHWdsIPcJzXNTukFMzxgo7qew+9miKZIftndtGQIoBRpdKjA9nNvL+9BKNA6m2P09FNGfgZQ+snzZV/aev7tiBsCSaP0Mqh/6j5e+7ZA/MQ7TDZk+IxTqF+gj0X6fY9l9g3si3Fdmy2Wx6m9SLRUcuclS8xa7GpeP1f30DJ/E++6t5NpPtwbr1je0z8nbctIkervW0P3BkqU/rmsTvzEOzCZo8Rz/ceXjZ/T4KhA+BdnEH//HZg85STpbU87hfGdp9B7Ho/bG0n6BoX0wRg97RSSxz0W0ZNOovPCJfSeu2ieZd2kRSJZeNcZEjSPu2i/dRVZQDCMtCihGi8wIy5yjk+DwzaiaQFvQIjK7Oek8tSi3KSyLuENchI1mzxnr68oncdJy+wfZ7Q5C2E8erIKxzu/o+Q0NclsjQKo2AkoOVN91plAyWiUv5gyqu09l1m0LGDRvx0RcmAnUhG1mFFM6sozJefrC4eFvzryPDpIKaGW7dox5yYhS7rY4DpeI2kLjA5onxELB39nBWmFfbN+DqhdylksvcscefPlSzTTjSXG8y5ql3I4MbMgWZUZQC3nygMBd6LgHhOJ/nMWOV47nBfq718zcIto2lF9m5mnqz9DIlw0IzA6aCGaoU+JrTzI4hb9ZqJpzrGTGcrsesdcWAnHCJ05BAhbiBsW3J5A471rxjsqatOb5/IvlDLNwqUSQ0vWR/MkeVkJi/IncwJbt7nIQwUgmihPrkoJXBkecJA0mHn0+syCpzWCL8YLvOaTWR7j1Z9eRnW9MIXZvett1M8TYDE4aqH7/CUTja9fzpmZVD42eQDUH5AYHCPBk3QrEucms/TSgVRwkAqfhcKn35LXZZ8dHuZB5x7nWpGTKDaZo8yxdomQg+2XLiGuk3o5nieNTcsgc5/3IFbUzMIGkjrpdZNZoH+dZfz4pMN7NThKY9MsEGZMi6YJBMnCsp+LHIhm9PNCeIUmUuqmQRsAz9UdAWNFs9t6pG36loZAaXljHgh66VR4vu6AWZfuC5bMeKPXQbnP4npnwrXKeN5CsEnKaNxkFi9uMhOWNEs4hh3TD6h/PeeDeIrKhaTB99TrjdH3PxKDZ3FsdHdlX7ydFNYjbsZ4zkLtg6eR1C3YgwiFa8N6xM3A4m3IAwfusIAzSGAlOfKaD3uS7ZkXNPVNKwMAGsjr89StNAvnXDyas9G73oI74Dlt/BifFb2mHR504A8KpA3BsTiU6N5om+ucNEiZu/TLyySUusy05wEzkIOjFiZPOQlvIDH9llW4k4KgkIeuYvtXLWN70Jcl2CnQe94iqlcKGjh5AtEUO7udSLTftloulgWNBZ0JJ8Wpd6waxKw20fQGErUPrCHc5ELdLJAiYHDYVhOjpSZTAb8n0X0YN1hplam+tCpQV6ZKGkvrDrkYSpSZ28JrVhDskNQ2PGijfz03Q3mgUaXU0moEpjuUsCOamaUVgWjKNnUBdsy0cPPda5h73Qos5djr93NMvWNVLUZ5PN6uzV/tcoKsKjH8ftb4OBNlfJdxITaZ4e1wYg4cdkQ8a+s+0sG8QWGcrQFOOJVr0rgfx1PCbObcAeVxo3lbEdoEgo5E74SF/g8uQuSsk6pfKqj7H5Wmoo277jEIxtwTOPTbKxg9rUTr/lNN2hz0R08/Bb9XboJyjwu63Sng6besorKeYuclHBiTx98BK6MxnZ1I416/20C0cAWCj55BdaMwE3zc3Nt9k7qF2se/YP7vDQpVT2HtGQQBIHrSScz+ySrq71vD4DBlKo0LGayMRqrhdo60apW1EGox3vi/7mHfVRRB6ZRpbnOsPsw9OfIbK4imBeb/eAVWrDbxD/B1k3lp6mTykHIOd0h39YkygcvU++j6lcJTXw6R3u6Qm5T221b3OCdrIk3vB24zmFzdF/WkM2kTdUsClkD7yyl6x3ht7Vii2EURq6l6ku4Jj7KOIUmLQSfHpV+iGaOWmwQbAl7XwvS7KaWKWpRFTWYs7NzCPka5FI8p+NgZQ1ID2I/TBmVOu5szlhjNO5g85SQu/+Iyah88bTCb7t98Gv7fEYMefOpeY/ZW+chpYyraP8b+Un8fJYx+r4A3LLjhVRvg0TxfWPsA6YNaghlu5+g9dxFWKtF50RLmXreCyVNPmvq06bfslaO1vk5H+s2XL5n3Boir7rxwCblnwR3yOlfWC7Tftmo24wAQt2yEd51BUhewcpLi7ASYPLV8r7gp4EQS1Q+dNsal/qBA891reyZmgH0s6NJEdeYLGcYLRFxrKiCNLTmW9E5YcCIgaXG89QbSGMQOD1nIXWFkNrsx4KMDJArpCdeOufkgaVLViVUZiCISnxI1K4dB6qc1Sm/SGhdLuVc+S86E/Vra3FyKrFxYFB4lOIXLBdFkViCaFlxIC6BxvoATcQGoTVMBLpzshFjquCWQtCSyQNWaRhJZpVyoOWOeG1DWMprrG9NwOG6X113XGNqRhDvioj/Yzo3BoH62pEXcNMBzC7YLRC0b0ZRtyJZEKyvy0+MeC2lx/nIiDj6i4DVI67xuVqauV8K5Ja1z3PAGUBYRvA7OhPNI4XDROjys6lJ3o6cPc5H9wH9ZwmTGgjvmYrx+scD0lzLkPutirZQBJE3VSprl4hhQdTdVRSQbSnMtNc0OIO1Vy+HNdd41dOtNXWWdZqvDQzbHnpDrB2ciUbtc0Coi5LmKAhgcUvWk7TJYSlkmTK1c0uD/rUS9VvXjYEv1K6HqYEMBf0cdm5qCvD4/izJj1dcrRDhnVYHRQSUxdktqJTdRpXlpoeR83oDHbGVA62zOOi5NvLOU4alV1kildWVsqsw7tSQqq/Jv/S6Q7LLNsCOSHb0+Je3OSGLqbIasojHwXEfMfCHH1Z9ZRhYyUGLH0gSBC698xmuXOFcE2zzvmT9dRVIXkC5I0Iwp94qmJYJt1uBJhxs4v8f1Tx5wo+WMYd4nULLqcFMFMlQwTQrOV7tlxFYuMXo60f6DJ3L9OZn3YXVL99/cFci/fB+yig2R5yh8G3aUwfvE3UgbxFLbO0OIlc+bTT0fLux5JgCFJwePdfS0UygcYdYYua9sQKrl6wyRcsR+llU4Jk+mLdQuFbj4K8uoP0Bpsz7v3WvL6mVKXgeHbYTbEkGHgaLwrjMYHLVw5WeXkYaUlufuQ998aBnbg/36n22vfvWrcccdd6Ber2Nubg5PfepT8dWvfvV/+LoPfvCDuPnmmxEEAR75yEfi4x//+IM+t/+FPeB+22/7bb/tt/223/bbfttv++1bvf3vzuz8/d//PV7xildgbW0Nn/zkJ5GmKb7v+74Po9Hon33NysoKnvOc5+ClL30pPvvZz+KpT30qnvrUp+Lee+99UOf2oDc70qGhYBbQS8DrM6IyOsRo2tWfWTayLZGSSjOZZVp3fOcpODGzHn6HmaCkSbM7aTMFqaPBOppXeED/iIOZN64yaqjkM4OjFgsw6yoNr2QjUVsg9wXqlzIMjjJ8t/3SJWy/dAnDQzbW77AQbhXwt2kKmlVIIYqmhTFl1FK24SGHcgYVmdGFiVmovASecAehByobNJq3WXDeK9C5icZ0g+ssE7XqH/PgjMQ3RayTukDQUcV0h2lGB2hqHTNLdiqx/UgbzXMMKWjpyfBwaTZH0g7T+dGMMstrAJUNElIilS1KQ55r7gPDAxaciTJgbZbHNDroUzqYMJIdtaw9kWcARh4FEFDgKenGbp+dqbevMjq+65Qv/fIynE99xkjrvE/cbbJB4V1nTER0d0uVrCh3BYJebvoGwAhQUhewE4neUxnVyT2ge72L7R9aQmWzMBIjgOnlpG7hys8to/e8RVQ2KWfsHXdROFCF+8wkal8SnXnoPOM2+D0JJ6LPUVpVEozdWH4lYXMmNBWdzErE338H6TVt9rXCoU9NFsJIJvwuI3X94zacSEVFhZJ6BMI8E+N5Ftc+8BtL5nmIn3AHBkeZoSucMouTezQuBYD+9RbGd54iLWeOkopUmR42LuTYucVFWmP/GB6ykFaBaz+xjJ1bbIxnLONVoKO1k3mBjUe5yKqMOu6mOUEAGy9hljatEfCRNOlZsf1DSxgdonQuqQts/fAS6n9J+WqhfE/sqJRo6JY0me4P7zqDQ7+1guEzTqGyIUlSeukSuneW8svcFUYOqZvO9mz/0JLJVAyOOJhMW8bXSTdNHwQoR+1f56D57rU9sjiA5LTxnaf2+E/p1nz3Gg1cD7HvjO88hcZ7SH+zo4Kykl5hoB5OJFG/oLJvMSOGs3+yiqjF19c+sIbwL86g9oE1jOZtZFVFMXois0tZxULmC2y+fAnVv/rCnmMpPMqKwrvOoHvCIb2pLmBlgmaBqokCSJoFIuWblNY4xo/nmSXRHh7RLGU9veMW+kf5fu6o9JJxlR9V4bKf9K9XGTtlkhhPMaOiPaAms8yiTBZIJbJjZnf8jspaOEqGWEBJ4lgsntQZMU+rzIxmIQDJSHv1CjMaVgpMZgkiEDlfK21mEdwRz1H7vHldAhQaDxSI2uy3zohR6XBTwh2oz1DdIAsEdl68hGhGEALjAllI+WdS5f/thHKhpCXQP+bA7xbYfBQflvqFRJntMoubVYTJWKdVev0kDYHuw/g3o4MC/etcWClw7reWTDa+cHm9gi0eG+8dzL0rlJws92kSWr0qTRbKyvgVbkhjUqnnrPm7U1gJxyY7pvm0luxGUwLbD3eQe7wnk3kJ6fCe+Tskl+UeVHaM98sdcWyMpzhW2SqLYjJJDRbxd084nNda/NzhYWGMikeHBIaHqfYobCVL9IC4JdF475pan6h+73Ce9AYS1asFIGiGqTOGQjK67g4pz4TF6+ZM6Kfn9fl3o8OMtmtjzMkCx7xMKUP0+1nKq4ykNr5/7+aMlNp55QOUMSsmLXoNWUkZ/c99YLzA37kDINjJkDQU7bTJDGwe8j0KT5pztxJm//2OMM9xFjJT6/Ul6pe5btB03GhGYLwgcfkXl9E/AVxdtIGCkkFpcQzuH7VVBk1ieIRyVJPdkFTruEPeY2nxORoeFvjaWx5LtUPBY0rqiuSXCIwXBEZHlB9Um/05d5mdKhygdjmn0fzjHgtnQqkqpfpcS9oTmExX5yb2w+pffQGFTQ9HK99r+JlduozZN6yi/4OLcMcFiu/4NvaLqg/3ah/JlAfrtpvLF3gu5PLtezLjuaK+7c4wajlg3Baofug0pAN4gxx2zIyZ9tHh+lFJzesqi5lJ+gLuZPR6CpjNjmYEorZA9wYL9oRwpMJlFjZpCvSu51qy9oE1RFPWnnHbHUqjrIjm/9cBBQ8ls9Pv9/d8xXH8Te//iU98Ai960Ytw66234vbbb8fb3/52XLhwAZ/5zGe+6W91+8M//EM8/vGPx8/93M/hlltuwX/+z/8Zj370o/Ha1772QZ3bg97siIwafu0mqxdbflcg3KRkYfo93LDYSsbROJ8bqVj9fZyorUyi+WdryD0g3CrgjiQm0wL9f88Fi9dXNJkmTby0fGPhNSsI16nLTaul1Ofwb66gspHhwO+vGFJG7sHoGSfzAuF2geZ9XMxpbbE7ZEpSU2msjDpxPdgXDlC9WqB6RZqJ3o5J4/A/fjfG88KkNAtfwO9T2ucOoRY1nMC6z1/C9JtXlQGoMrf8qy8gmiZ5ZzLNTYfXAxb+YAW5T4pZ+ys5JvN8kL0eN1T63HQqWn9+uEW9ujayazyQm9+Jgoup9pdL07zKRoHm+Qztt63CG0iEu1DSgaL8BN0CU29fxfRbVtF8914q1PwfrSD9jlvN/9OqwJWfXcbwGaf2SNCGzzi1B1ntqsyyrpcCKDfSEp/RvG1qesZ3ntpTa5MFwmB17YkyrZ3X2unSwDBuC4Q7xR4Jjt8vVL+E6rMk0Y1nqdnOQsouvQFpY3YizfXTeGtvKGGn1NqzbkbC62V7DDOlzcEw3Jaov38NU18B/L+6G5V1geb9udHU9m9kjVu4Ucoj7QRonMuh3eBd5RKfVUqtb7DFAAPR7SRHJQ0bwRaxll6fpo4AB1ZLjTm5RzlU7gszIIuC7zuaJxlRy+WciTQTqDtinUI0ZaFxoXRsm/oyF6bOSBgpBs9fKsdvRVg7l6LwgPaXM1ixMChnZyIRbhfwhhLj76O0s34xx/iQOoYx9jRnBLOw1y1uCUzfQ/JNSxksdp5+G6obual72PqRJQQfPWNqL6I2TTDjBgld9UsZtl/GOjJdM6VlaVd/ZhnbP7SEoFNg45XLRjY0fMYphH9RbpDsmGOdblqTHz/hDsz+SSlx6/+g2hRZvD6FJxA/4Q6ipz90Gp1b+OvKh0/vwagnj3sshs8sN1TTb+bYUn/fGoYHHSSPeyziOolRQUci+q69NTv1iwVShaCzEi7qAWD2sxncESUlSYvynHCdOnN3yA2Gft6yCtA6W1BCscNNfuGTuqVrAQHl7r1ZGIdwd0jDRL8jSdns8mfNP1uD2+d18Duc8IMNVZc4BPwe5xC/I9Vr+SUKZaJc5WLRHXDhpc2h/S4lN3rR5kxo7klMvZJ4jRkwq1yljE/r8sMtLiijljBSUD4j5b1wJqU+n4tOPsfegHVHzqTAZIbnUb+UIfc4b1XWC2Ps6+9IDJ69iO4JD+5QonY54/OYURqYe0C+i9BUv8CNbbAp0TifAhKoXiwDIF6P4wjrMjhGNL9OrLE34JinpYf1c6oeKQPqlzNznlmViOSkUW52+kcdboIcGIPlrMbrpO+7nQDD6yTcgTBjjbQEWl/h5gbg9U7rrN0JtrnoZ7CDG0td69v+wOfNdUqrfOZ1/Un9nOqTCY/PG0glA5WwIwG/S8l0pOqQkoZQYxc31uN5C1aiJGI530MKYOaNqxCFssYoeDxWWpqr5gEJlm4fqF1kHY4z5CbbiShVE5JGpFbKzQ+lwcRtex0b0VwBty9QWWf9kQ5oBlvCSJktRSerXirJmOuP9eH1KQl0Rqy9EqrP2RNNrSul1GmN5rtZqOre1LTUO+ZA5ECwXUrhrBx8/jqKcGixn2cVSgUbF3LWtalanrQmjYyekkCuS6rrOUTBMSZpSLTPuAyghqQeWjnNWSvXNLaeCHM74SZZSK4Jwi3JumQfGM+T2FcaypZBaP2s1h/g9+6dt2Eya6FwOP8bGZ/6riX40haw/vtn99gUOOMc4+saKPxyKSxWPm9kfwDx6PpZ100HzvRzklaAjW9zucYLOW5qs1xd/3jotxkIKhyhgtM212oR15bBVlmCAahNcw4c/N0VFB77XuECw2cuKpy9IF1zqIMILCepXsJDbvIhZHX0ZufIkSNoNpvm69WvfvX/8PN6PXaodrv9z/7N6uoqvud7vmfPzx73uMdhdfWbKb//Utunse23/bbf9tt+22/7bb/tt/32b7hJAPJBJob0n1+8eBGNRsP83Pf9f/F1RVHgJ3/yJ/Ht3/7teMQjHvHP/t21a9cwPz+/52fz8/O4du3agzrOB09jq1iofug0gh1GnyobuTEo+8bGqBKlTVNvX8XwoM2d6FjC7+UY33kKIgcq11JEUwLhtjRFXklTYPrNq2jen8PvSYR/cYapyxcuYeaNq2jdlxuzSG1IaDxaurkptNYtXOdx2CqNnNYE6hdyhJsFPFUkV1mXaJ7LTZSpdjlT0cQCrXeuGgmZlUm03sldZWVdIlQStMpGgVSZUbbOpur3BeZeu2KK7ttflIbGBlAik1YEvCELZFtnMwyfuYjKNcp9oqaF6iVmE7RUqHeclK765Qxzr1tBHgDTb1pF7gtYiSKU9UjU0mlPAKhfJFGuup6jdrkw0rBrP0EqmCbhAYDbi4xnxz9FVzN/99+/aP49/aZVHPzdFdQ+eHqPbOwb2/wfM8Kx239n/AOnkHsCU+9YxdzrVtB475ohXDXfvQZ3XCD46BlIu/RxshR5zspZFAnQGwlQ1LIhi4B19ImWXJAAAQAASURBVEVLlVrvXEXjvWtonE8RfPQMZv9kFX63wPSXUjTvT9F65yrC7Ryzb1g1fi7t935evW8BK2FBppXSKNb9b58xUSSAkTc7AeI6ZXDOpDDUovGcRUPTMVC5TGkQ5UTMdJEcZaGySWNNryfphTBWmZ6BJvcBB/4hhx0xC+H1c8IdvspMom7BTmGyNVNfUZADmxna6tUCzkRi6mwKZ8wIuDNmJDnYkfAHEu6Ykorm/akxFfW7hI3U37/GotKIUacDf8Jr5G+Lb4I26BEx3GQhqe4fw4M20lCg8jeUXY0WbFQuU/Kii8h1210gqlvlmsRoYe/gM/Xn96D656cNDUv3jfZX2DcO/fYKmn9Gw9jW1zOEd53B9JvZJ3abVQLAgd9bQWUjh9fnc1z7IMey3f42lQ9Turk7g6N9qpK6vefvUtVP/L+8G1bKn/kfvxtBh8d2/JfK99DP7dTbV+H99afN/ydPOYnoySdRu5xj8pSTmH4Tfz/9FkpG6+9fQ/B3e/XMo3nLRA6DDqPxdsLIvauyfEAp05G2Jh7xmaxdYlH/8JClIuTs50d/rSTraRlF4QBRy0KwXcDvF6heKVB4zI66A76/yGEAJca/xC0zQUGnQGHzd7lLaXJaEyxsVrK2wgEq65TWkRgHQFBOnQXM3lspz2l0kOaVdqRkTQqQMZ7nczzzBV6biaJTaWqclTNT4kwod7YTwjp0BtnKJCobhcka2gkwnrex8AcrSjpsYzLHjLczkahdyZCFFoJOAUdlHgtbwP+ru+FMSBarbHCead1XhpLTCs/bToHxnAt3SFNd/WxbGbM6wRajxLkvjF+Ro4ACACPOcVsYoMjgkKOyCMySu2NpslvsKyQpZiEwPKqKyrfLZ2Q8z+xo7bxA+6sZiakuffAAksv8Lu+DloblvjCQAHcERFOWKXzfeMntGBzhwWqJvLQZ9R8dLMl8OsoedKWRAemmwQxTZzMjXXQiZgWDbWkycc6IY1nveYtGNmYnhPiIoszOFg4zC2mN0fY85DhZu0A6bNrQ8k9mxaRVjlVWKuD2BYINC35HKuARDUq13JkKBSDcKZTUk1nWpA7jydI4VzCbMkOpoD3hfQo3CWSwUoIJRMa5wVH0vfoFymV10buBI4TMFKUNwnZ6JwRq55UEa8zMX1y3MPf6FcRTQqkMhKFnhtt8PqNZrgnzABgtWGic43ibewLOSJhnLmlxvKisS9Tvt1S/h1nDHfi9FcQtyiTdIefoLOC1K2xmpLIKvY/siVAADL5P68P3oHkuRetdq/D7hVEW6Vb9EM2c9ZxkTzLIT9+L/GtfhzNMEV4ZIbg2hry7lP5Of6HsULs9d8zPsvJ3nRctoXaJ5xk9+aSSyObw+uynmpALsB85E4m5168YtYszkWg8wIM78PsrsGOJ6nqBudetGFCCNmYFgMl0KScez3F+iVsCVbUW362YebBNo6cf7BcANBqNPV//o83OK17xCtx777143/ve95CP98G0B73ZccaksY3nBfx+gdGCbdzcJ7PCpPcAPljjeQujp5/CtZ9YNjSNwiWyM66z7qZ/3FP0EYnwk+xwVsb04+CQDScukH33Y1A41IRe/oVloxuurtN5W6OnR087haROAyqvT/O13S3aRcupffA0JrOky3CgEhjN20bCMpl2IJSb724JibTYqUdPJ+2t8zCVNvW4QYuefBKx0tnX379mJvXecxfNIgggeW7jlcuwcpLFapcLI1MrXHbaPBDo3sQaBH1tRUEKyGTawcYrlgEBU1tSXS8QblNmODpAjefGK5eVIamL8byFpEGz0ixk/crMvTHG82IPrnZ0XY3HfGzvivOfqk0AgPQ7bjX4x91t/AP/MsUNANLveQxGC5ZBVY6eThnc9Ju/OU0ZdPeS3qiR3YU7V+hpkZVp7H9qIz585iLN2p58EqOnnUIWCERt29C40iqxjhuvZL/SWOPhQQfDgzZCRVWyE4noSSf3LO6lzWdBy1D6x0nESxqcRNIqJz1nzAWkkJzUNNEuCwWilmUm97TKhZudaOw5pZvjORtWRqlV0uCiqn9cwBnLEqGbSrPY15sgO5aobvCArQSIpnjhuycsVSdmmTqSwhWG5gYQvR23BDovXMKFX1vmxm4iYeUSk+9l/yl8KIxo+azZMe9X0hKo/vlpbL90Cc13ryFuwwQLACXDqAOTOWmww7ub3qDrljSE2ajtbp0X8nnQpqKDZy3uwYn2nkcU+W5DUQBmw/KN9T5AiSzXm38tSRvfeQrRk06af5vPeO7iHpPd8Z2nTDBHo6f167LK/3go1uhpgBv3uGEZWk/yuMf+i6+lVEug97xFM3bmHkljhc/FT+0ypW5ZqDfVNER+4D8vscZioORafSXRqACbP7qE7VsFBketkpZkk3Q1PGIhahGdqwlFGnlfuGV/TBpA3Con9Nzj5kT/nbTpPp5VKLGJpinX202mhFC1ZApfLWQpSdUbnqwqDAU0nqKBdB5wYRm1eIzhFheXU++ghFjXAWkzX4A1HrslLV4/Q9AtjPSzsk7neY16D3YkGhcKVD90GoVCzet7MPPGVUNtGs/bSBskf868cRXBx84Y2ZudaKJigda7VpE2VCBFySrTakkSrV4t9ox5k9lyM2kllEy5Qy6U9cJa19/yfuxC7E4JjOcpFatdkIhmufEczwkG6frSjNOjedvI2kXB+5S0yv/bcUmi0jU1Xk8iD0mCAyhfLDxuTtI6F/7S5iZU5KouqVPAGenNKcmsuUcKaTQtEOyQWrp9i4O8QnnjZJrHFk1TqiktSgApfeY5JS0oKwPWkDlKMsZaHQl3zGMLN7hZGx4mNVLLAwuHwRfKi6WRmGmpXzQjMJkVmMwLStAcvt/4AElm3RM27EgibRQItrkZr1/OyxoUAfg7Aq66T5NZ1nj0j1sMPisJow6K+js8N31Pcp+1ctyM8nhbZ3NFtSVOOa1RbphVVE3mjy3zWQ+4CdI1i8ODlpKLKirkmJLEmT9dxQP/ZcmQ59i3GMAYLwhz/3SNclKnpPrif1hGWuVzHylFk5Wx3sWZwMyXhc1r5nclKhuKEHrnbRjPcN5OqmXHb9xVBm+L7/w2mn2eOA6Ib55XorkKnOuPQXoO5PLt6NxSN7/LVJ1hsWtt6w15/NJmMIpSP4n+UQd+R2JwyEG4yefQGXPs6rxoiaTElIGe7vOXzGYmCym97LxoyWxWNl6xbGiXXpdrBk2qcyZA8+uFuQbzf7yCqEVLiHDrGyON//PtfzeNTbdXvvKV+NjHPoa/+7u/w+HDh//Fv11YWMD6+vqen62vr2NhYeFBfeY+jW2/7bf9tt/2237bb/ttv+23f8PtfzeNTUqJV77ylfjIRz6CT33qUzh+/Pj/8DVLS0v427/92z0/++QnP4mlpX9ecfRPtQe92bEyVVg6oLQq6BQsuBcqTb0rCpwHNKjT0dhwO0d41xnkLj1CquuZiQbqtLaOoHt9Ul+CHYnBQQfOpz4DK2O2BlAeDR4zMVYCHPydFeN5Udgl8ax+vsC1n1re44MRbmcItmnAVtiMlutIh6aCJXVGTXKP5ndxo4QWWP9f9v47zLKzutOG72fHk0Pl1EnqVg4odHedg/3aeGyyRiaInHM0wdgGw9jYAwbbgG0wJlqAAQEim2iMsMehqoMwSAIJSS11rlwnx52e74+1z6lu8LzviPebb77x1HNdutSVzjl77yeu9Vv3L5AoVvoLh0mvhuQe3Lrm1d+IzU3jArfNF5VIr0oYMP/pQ6y+esuETfkDYoeQ6Zo7DPpFofoYvkRRgzSM/khS9aN3hQRJxdSRPv2CEGcGcozRjyyiTSGxNXaZw8LVib8SVnt72sRqS9S8ttfAy6khsWv1enfoUzS8R6t9Nl5SYuwu77zvnwsaOLedK2c7t5n96DzJz7/7t9/9PrlTwfAZ+UmRr50bJXe/IRLFcxnydkfgA6ENK68ri7wo9tlxG/K+/cfux2np80hyteeU8FMidUl87QhWJyJZibA7eihbS3/xML2iycRfbsl0AEY+JynyxNeOoA1F5RJLIrDnkMNCNy6K7WpGP7I4NAtUoRRup5YVaJGfWV1Ai6wyURmMI4l2Jjb0UD4h0oJYnhdn2NszQtczfGjOGVhtIVCd27oj5jA7df73JeI+iK4XP7E4lLY4jYjmU+cxAgGKRKbCy0v2x8spcid8OlOKie8HAnMoxlIj6xyDunMkZ/bi3bh1Kdo2+pKFDNKKzReVyJwWaMLAm2v6AxKNG71TZKQAzV/ZB8TQkjizPDDhBOnjia+fn6EZEPsGmZvs5w6dF7E2+/pngBvntoHsdPAaia8fGcogvZwUQtudWL76pcPD9x/K854yL5mrx24BFX5axjb3joWf+bv/uzbICg+zUefM3gOfnf9ek6JpgcJMvm+BzJmI8Q8uklpSEiXX4NZCwqTGrUu0WWkpps0fEzlumNjy8gIpLk5UNbnjMPojf0jpM/vERdWSTdLWlizRTw8kTVL0jsFQqqRjM+jQjbMQsXzEz4hkyPDA6Mv7ujUt1D8ki6MN+Ts/w7AoPbKhsVvRG5f53cvJ962ewGjqz5oXGlhiy8MjSKrh+9b2mthtiYJL1kdM+1SwlS2OLEVn0qYXZ5RNT9OaM0XudjYk9xnpd5lbD+E/8voh1EKAKLE6YTnuR6shZk/65cZLSrSeMs/IxxbpFk0SVaE/pr58mO6vH8BqxbLkXFw8HSI0rawaSmxHP7JIZEsmI7Ep5DkjhN6orCedSQHppFajWBIoC5zTEP81gNZuKYQOHVE+RKaMncE6n14NqT2nRHdSMjkQe4kUJBMjcjCRV5s9icwPslW9UbnXTk0PvWlMT/pHZ1LWNyPYKr4Pspp+UdPYbeDlxZxSBVtEss3LTRKbQnjsjUsUPHR1bF4+AILI12FCsi9+RvqDU9ek4rmzNyZeM6G7ZX6KIfc3SAloqTOlYgCHijP2gJLPLVlMkScn1zWrvxjR2hkRJiSbBnERehTvmZpQ3weZ0wL1SK7I3Nwb19T3WKChscfAy2n6BS2GsbMQJjSmL/TEjasFGNKdlEytl9e0d0Z0phSZMxGtWTEcNQLInoyBHEr8h3pjesvk9BwKbuFYiNuI8NMaP6vxCltjLrIls2R4xCbuivSS5vgflYYUvtCVbFNvTMa604izRfslGzQgwooZrYzbIClr3cpryxiBpj8SYfb0UEqWOSvPdG0/VC7fkrEVP7EYj4NzJJaPvBLz4r2sv3xgFK/RKZcwIROYuv4KgowsVO63jhIW00Q/vBuz1R/O7TIetrKTg9YdjYm58TygLenPA4mwSFgN8VXcHZFeCSl+fFHmxlZEe1qMkesXmPSKBiM3i/QPZA6r7TXoFxh6L0axyXxzp+zbIlsk8cmvHsHPCLwhdIQa+dOy7ofStP75/vsfba985Sv51Kc+xS233EI2m2VlZYWVlRW63S0n9Oc85zm86U1vGn79mte8hm9/+9u8+93v5ic/+Qlvfetbuf3223nVq171kK7tIQMKlh4TsvLYA2Sm66zdWcAbCdGWZnbPCmeXi7Sv0HhTV8J7bqN/ZYe1jMadbmMYEacvymDPl/B39qhdGZvjJTyUAmVGqFWX/mkT/gGa5R7dHT0i30R1THpvLdO/oIcyNEpBu21hNkyMOcG9PDhbEuOqiQjyHqYTEoWKWktytu13zxOmIhJjTZbHMnijIWbew1Catm9iuwGmGdFYS5H/FHSmNf5ISGK0y6nLk6BDvBEF/wKNa/t0Z32au0v4uYj+cgTfguq1Ie5kSONCA4yI+jtLhNmIzQNw0Tfg5B+UUZc1adWvhk/cRutSH+eaGvVI4fsmhqEJtKLjmZh2SBSaGEZE5yoDyw7xOjaqoegf9PHaCisRkMt2SCg4NjOPMdEhk+7RaCZJZ3pEkcED1z0MvaqxZtpEoUEu26Hbd+h4Fh3AMCPCwEQf8KgdBr4LladeTWNvit5YROUaA6Or6f2myBAjE6b+Qg4A9330elJ/uwpfvY3NZ16N/4iQ1fl5UssGyVU5wG1erYj+0zxaCdUksgVJmr9P0uupVU1zp6I3HZK+rExvTJM5JRp3DFh+9zyps8bQyRoN+qar4PO3Ub3OJ7G3S9SyQUH7XfP4J8/Ce2+jfqHC+8MSiQ1F4+KQxLJJ801yDX5OJtR+EbpjZbwCdGcD3FWL/iMPkFi2ZFE0ofKnJUbvgro6C8CpN12Osyuk8oEDoAKsusmZN5Vp2Mfhi9Kl3YvrqN1Zal2HysMOou0Qp9jDtkN65ZC+b2GaEcf+bJ7pS1fYaKRRCrqRwjA0Vd/EtkPafYtctkvk2dQepjDNCD9ShIFJJt2DyEAZEY3jBaymwrmijq803Z6Nd6INn4PaJRHu5X16by3D5U1GPwLeIxu0V9PgRhhOSL1vslY6SHKqTmVXkkqgIIwwWyaU5zF3tKhVEtT3lOnOhNQuNzA7EcvP6BOsJcGI8K/q0T/eg2+BcW0dPZdHpwQrc+rNl+Ps8yFS0Dcwcj664qAzIaYbUrnqIP2l0/BVWP3TC3H3NFmbSeLtAP5xa+6pXefTHTNIrBiESU1kGahdLR54+MOw703RqZyG997G6TdcSWrcJD0jfchuCTo1sX8T/hIe/JMSmVOK2u+WSa5rvJwitRKhIlj9Bc3kvyp6I7KR6o2KOd7oj0LaU6Y4W+elZsvqGRiP3U9jp0W/KBuu7AlNd1IQy71CieYFkLikTOGBgPoea6i1fvCdJbSlyR43UKEme1bIR60nNSnckqEzbpBaE1Kgn5F6iPpui9RaJHUDrqJ2rYf3Y4fwYWXyxyOaO4yhk7n5g1Pwra1oWG2/R/LCHt2JMv5lHZTRoXpJGf+iLpYdUMh0ObG3QGGsSv9ii1yyT62ZpN1ywNTQM7GLHemXkYFjB3i+RWMziZXz2Gjb2Jk293/iWlLZOj3PJAxM6jMGbtrD69nonklhsknPswlDhd92yI626dVSWAmfMDCZHquz2UyDGRECUTwmPCOi006QSveo15MoU9YBI9Wn37ew7ZCEHRBGBv3AxPMsFKCUJjI0XqRIJD3C0GCtmaAw0iJ8uEZ7Nn7fonVdSLeaxGibpHY1OP6OEsFsj7nJKl5oUm2mWJ5NYI902LjQwV+WIqfGHujPKaLZHubpBOqCNl7ToXGxIfftsQdwx5ocf2cJPxfCEw6QOqXozoXYVYPlm68nlW+yfm0cjJnoUd1/PfRC2WA/8npQPqpn4ow3ue+j1+OetSgeWOXkA2P0T8sOrH5JSPKKLqFngGfgFPrcf9lB0rM1ul2HvhMQBAZoRRgY1CYtVCIksEMaoYEOFc0LHNI767QqKVTPZN+t4OdDrL0dPMAwNESKynIasgG6Z6JCBWkPK+HjByZRxyIz3iYMDfqBgV9NgB1huCGmHRKupEjtatCsJ9Ghwr/KIwpNorNt+Ar0H95m9uplljfz5LIdgtDEVppWO8HceJV6N0Gr46KcEMcKqK5nSRe7jGdbtD2HjQuyWG6A6wbUL3YYybfpeja1RoJ8ocOo69Hsufi+RRQqlKmpXaNJuh49z8Y0IxxEzpNL9On7FlorinZAq+eStH2R7viydUo5Pn5oEobxpjQysKyQtONTqWUw0j1mE31cK6DSTrExl8FKBJgJn6BvYSc9TCNCtxOY1zdZW8/jJn2UFZIxIswrNX7fptd1SKX7RJGiU0lRmGhiWyGNdgIjUqSTHo1mkly2S8+zce2AjBkS7TFYuzpB2LNI5bukXJ/6lS7pZB+tFY1WkmTSoz2dYHqyRhgZ1FpJ3ITH2YtEyp7M9jAMjWVEBCmJtCUuqxFOF3ASPh3PQino2wG648JqAre0iaMVSslOuNNzsFwfRysKrod5qSaIDLrxZ92sZnATcthOJDw2Thfwf6HDZLpLe5eDAjarKdL5HnnHJwgNmlFra02+aAZ7zSZIRSjravjYbWxco8mnRggTitasS2OXwXQzxdq1LjPtq2jPJGlNmYz8RLHxGjHFHctcQ2fEYfNKk8IXZEj2RuJg5e4O/Kt8r7vPh++Cd3GPtVeUae7RpPZVWRvNY0518JsObqGN37UpFNtszDos/fJBjJEOrasNLKfHSjaFdWGTyuk0m+8/iDYDMDTKDdGRwl5x6M6F1P/mWiynhd+1SWQ8qlcpLCuk23PoTpSwLquzWU1CpEiPdQh3/izy+X+0/TyytIfy+x/4wAcA+OVf/uXzvv+xj32M5z3veQCcOnUKw9g6sJXLZW655Rbe8pa38Lu/+7vs27ePr3zlK/+3UIN/r23T2Lbbdttu2227bbfttt2223b7P7j9zz7s6P+BNNA//uM//sz3brrpJm666aaH8rF+pj3kw87Mt0xyXz/C5otLjJ71iRxF8itHWH11mTxCqgk/fxfLQGYxibnPZPo3RFpUfW5pmG5s3XQQI4TuiENqPSRI2GQ/d4jVX51jCSje5jB52w/YeGmJ/HGfIKVJvvXfAIYSG7sV0B1PCdnnCtjx9gUBFGQcOtOK/AMhQdIYktM2X1gidLMkKxFexsStu/gpg+InFuk88SBe2iARF4vO/HNAmDSIzBSZzx+m9ZR5WjXFCjD2jzbunD183bOP38EKkL/LZMfbDtO74QD1PRaT712g+dR5sp8TCdau31+ge+MBmg2pdB1fMJj8w7vZfFGJVDQo3FVM/OUC1eeVMAJN4Cr6RUXmbITpSTo4+7k72XxRCW3YeHm5/r3vWWD1N8rYjSQjCrqTSewmzL5/gaXfLmOcymD0wW4kyNQi+XzvW6D63BLdCYXZS1I40WAFkWrl1ClAYAG1Cw2m332+nKv/2P1c9KKjNHQVgNFP30HuluLw59XnloR49pmf7UNLbyiTP+HjfFvuS+Gcn3mPup7aXoeZdy0IpOBHEe43z5cbDd5z+jsGxskEKmL4LFZ+bY4zQPHeiMm/WqT5tHnyD2oiJ8RuBNjf/VnzqvaTDpL+r0cIH3Et3XGHzK1b17r+shKFv1nE0FVOANP/DZLTCqsTEdmKxNfkfa1fm2MAQrS/m8O8OE86kizY2qvKTPzlnVSfVxLPjph0VfTBu2OSRGyI6uXFR2HyQR/3Gz+k9uwSmSWDxi5HUuSbeugjoKMUqZoUyeZrQoJRD+Tl9ZPQqkpHnl7QWMs2+U8tUH/mPJ0nHiT1twYpDakNTXMuQaIiErPEP2WZrAbY3znK5otKGIGk453vONjf2ZKJSZ8+RO05cm9WXlcm9w8JVpKxjmkxT2osg1qNP8P3NMaSg92O8DIGIx87IrCOT99O74YDJL52mIausgKYd2ZwzmZJdzTcAytA9nv3Sz/5vk1q3GDkZnk+rZsO0j+WZvQji8N+cQbY8a67MG+aJf2Fw3iP3k+QNCh+fEsWOf5vmuxnF+W5f1HkY/I5jgz76wCgWXlBiZGbF2k/+eBQ0th/7P4h+RFgPP5/54lCmbOeNo/VjUh+9QjZc343eU6fu+CNi6y/rMT4B+U1N14ilEltlkh/YZF4GiJ45jzjH1zEe9T1ZM+GpL50mO6NB0h+9Qipmw5id/wtieezS0P53dovz57Xx1XNJn00Sf54QK2bwuzJXF3xkmTOaPxUhum6pj05wo6/WGDzRSXcgmJkJYpljIrcqQSVSyxSVZECOY5i51+cP1asHlhdh/oFBpP3hjTnTCLbpbAaxQXmRYwxRXo9Nh11ikwvh3RHHawuBIGLMyYy3uRmRHfcGJoWji1HGIGLNaJIrUe0J0zCRJJMV7ygrG5EY7eJHYDrQfF+j40rHay2xmlp7HaC6sUm+SYQOYx8YFHmzEiyvLmmeJxtvrCEYwInXGqZaZLrGmdKMXoyojuWEdnSMdH7FO7X2B5k/5uF+81FKs8vDaWwg7b8+jLT75G1KXQUuc9s3bPm0+ZBZxlvhDR3WCT/1SH9RZGq9bPmkC7ZHVf4yQzTSz6dCU344AT7PrE4HDfjRw2MWmLo9dPPZ7A7GmMxR8oUCVpxNcRPS6aQCJKbpkBsAqFK5j91iM0Xl5j5yCLLrxfp6/Q/GnTHc0IGq2kyyyGdUQOlHUZuXqT+zHm8nINWLtmlgM64iZctkI5Nw7WpaM1aFO8L6Y4ajH14kZXXlCl2BxAVW2h5Fenxhb9N0H5gimRGEYSpYaZybCmiOjZLmICkD2N39rFu+z68rITSNg2dw+pBelIki3ZTYyYU1moCc8Jg3/sWxMw4obD7mpGzAZuX2aSXIjpTBkEI6ZhK188ZuI2IwFbolMjSjLMR1qSB0RJpZrolvxtZimRL+qLScr1WR6N82LHmU7+gQM8D6hFmwaDgKlRoY4RJHBOCdJrE2Qg9YmA/6DA6ZdHPJyk8IOTUfl7md2POwGnI8537jMjhVV2TR8h33bEMU0sR/XyCtJaC+LH3LrDy2jL5riZ3MqA3kiVRCQn22iTW0rRmDKbOhPSKScykoutPCgmxqEiuRKQDTWvKpHhMUb3IER/CDTE/S9+aYXTxTlZeWybTFDldb1QxdSIUOuL9o7JfsaWcIdPQkql0Fc4J6ScAI0s+zTmbqUaE1bPxMgaRrbjobxapPadEP5WFtEJ5kAeMwCFQivxJn+aofJad7/gxObUk4+TXD+B/+Q5Zq/8pInnoyHDezZauRi3ewcw/ytep+L/2kw8y9RcLmPsuILz/QVLAdPt6BsKqzCnYAJwfJobjduSQyQaQW3CZ+MYC7jPnCe8uoAqKxA9SFP5G9h69gmL8g/82XEeqzy0Jka0DTjuiczzDzg8t0nv8AdqTJl5eMf2eo3RvPMDGFYqxOwwiS8aX6WuMwMKpBYSJBH7aIEhAeDrH2FJI4utHWHtVGXdzSxL2UFukFeohHnYeSs3O/8r20Gt2/IHmVA8X8f7j9mP29XlmTSAbuun3LNB7/AE2XiIHne6NB4YmT50xg2QlojNhEjqK1lPmhzS2gYNtZimkM3H+mSx0xOCwX7DwMuKmnD0uP0t/8bDIPn4S/EytiOlD7lSA6WmsnhhYDbT9fkpclbWpWHltmdpe0XJ2JkxBC956CKcWDN8/dGTTM6CgAeS/cie9Gw7QHTXJnA2lY5+DAWzddJDOhDlETw+wgfKaons1u2JO2B0XnbSf26LktCdNvKyi8Yx5IRKlBO0YuluUtIFuOndCcK/1Z80z8ycLOHWN1RVjtY2rLExPx8hp0ViHW+NYXicmT/lJg9k/XsD/1evO+/m5m71Bqzy/NKRYFT+xiPfo/cPXAYa0toH78KB5j95P5fklmk+dx/m724fkoX5WumflBSU2XloSyt3j9p9DRjOHWuOzbywPn82gDUhwXk5qgP69gw6Izrf1lHkqF7t0xgxWXiuvVX1eiURsUNt8nNSU2As/xvA0zreP0pzdMj/1U+cP+MRmLON7cYl+gfizxXSj6S0084BUFZkKtyImm37KoPGMeXFN3uMQJKQPeHHdmIpiTfCokGwMD0Y+tjh04M6eCVDnaJfPxSkPakOKn1ikOWeRqETYHTGhre01sL8jtR/pVdEYp794mM6ERf8xW7Ung+dj9gXbKpr/LZxs5MpiW/ii1N9oW8VO43pYI9TcabD5otKwDmbwTMc+eQd+Vp5ja/J8EqDTjIb1b4Pmp//9ibZXNGg+bR7n20dJfVmuuRsTsNqTBpUXlPAyBmuvKlN97tbnGNQCDfrxyM2LbL64NMRYyxj+92NE59bdeFmD6vNKuN88+u+S3UDqJzpPPEjzqfOMfXgxvi9yPYP7PTDEdf7udlJfOkzzqecT5AYHHZA6o+pzZRz9NHp6x7vvIrkhB7DUaiT1J0mp2fDTcphwayFGKPTG0JHDdb9g0BsVA8rKJRZOXfqhNsSYdTDvrLy2jDYVxY8v0h03yJ6KaE8YqBDyx0OcZoTVj2lKttRJJDcjzL6mcqlJZ0b6buhIHYfSYrRsduUg71b10IzPaWgiUzC1AwPKfl7RHTPInIlIrkeoSIx27VaMTk4ouiOC/3XrEaEjpCmzJ0j/Hf9VTD+rzy3h5xSJmqY3onBqmiAh1gWRLbVG43f4Q6pe+lt3xQaYcc2O/7ORS6euhzTPgdGt9+j9w3vXmjNwv3WUsQ8v0h01qD9znvaEidXXWLd9n86EjdMIsTuaftHCbYZYfX3e2tMrKLQphDQjpt71Y3f2gYl1d9SIsdwyf3Qm5VDZz2/Nm05TCwUqpp11JmVDNfeOBUJX0cub2B3BHFdeUCJIKsY/sEiQgcYOGReDGqRObPacOSu/H6QVteeU5BBkMHS7N32G1KnuqGz4Bga4ZjzfdceEzqfjGq+NK12WX1/GzwrhLEgq2jNSn+LUNEFa4eWherFBmJS53M8IgS1IK6p7bdyKHu4zjCAmCM7J7zd2G0NpqtmD9rSYa3pZocnV98r32tOKXt4YbuqlRkWosc0dNr0xRfUKzfrD4nsfY8Htthzi7JaYYhuhpnKJLYa245raPovWrEF3asuawMsL4fDU7wshrTWr6I5J7ZKflv1Ub1RqO7wcnP2dsqDCa5ogaVC92KA9aeHloLFL8PH13SadSYWflnvQnVBDxHx7Qp7fxpUOXjbGRMfTbW2vxek3l+W98kK5M3uaxk6Txi6hevpx3bNWYkA6MLpeKZm0diras4q1ax2CtKIzYdKcE2Jee0bRuukgTiuSuSBGh4O8JgasX2UP6+wqT7ma/uNkr9EZN4drtR9j/wc1O/w7S4V5+cXDuT28/8GtH0Rb4zjInG9Sem4bku4cuQcDimX7SQexuhFBbLRudzQrrysTpGTNGpAa7bam84SD59WcnnlTGS9r4NagH9eZRhZ4GUVzzmTzCpf2pElzp4GfFuT01ueRfvzztv/ZNTv/K9u2jG27bbfttt2223bbbtttu223/4ObHF4eqoztf9KH+f9ye8iZnW6cfgwScvoOEgbNOUuiFS1o7NqKxmqlWH9ZiTAhZmzV55boFUzSXzyM3Y5IbUS0Zswh3cZubp1Q7VZE+0kHaeywSK0F+EmJ1G6+uITbDBn96GKcoZHIy7meLHZL04t9bgaRf5CslGQDhD8PQqsanPyDlCK5GTH15wviVRNH64ofl9cOY6pcZKvzDA4TFfnc1SdfhZc1SG6GeFmRx50bVc98/vBQcgNCm2o8fV5MPldCIddlFcmKGIX5GYn2R5bCjA3ftrxSYpPJbiRmekj00/Alyt8rKNJLEd1Rg42XlIafY5AlMnyJtCdqmvwJ/2ees1vxCH7lOjqTcQTiv5MVObfZHX0excr59tHzMgzneo5Ethpmi5xvHyVRi4Y/H9wjtxnhfvMoIzcvMvahxWH03f0HIb8FaUVvTBHacu2rry6T/foWWz/15cNkP3voPLLKv9ciU+EnFeMfXMTqaqb+XGQmdjsa0uey35DX7T/ichJfP0LrKfPYHf7d1/bibE0yZuLveNsCZ3+nPPSyMHsSrRz9a+kfVkekCJEl0UKQiE7xPg879uJJrQkxaRAV9zNbsraf9h5yv3EUK4562f+yRckbeAMkN7fGWZA0xPhwUpE5G9OI4pQ6SNYWhKoH/IyXktnX9HNKolixh5jRZ1iID+KN47TOnxEHkeLq80p4j7p++EyXXnUVhWMRXo5hJK5bEhpbZ8IcegINMjBeHo7/UWn4bAYtsxT8DDlw4Hs09RcLjNy8KAa2f7kwlNYCQwnSuf0YROoAEo0ufnxx6J3132v5Tx0azhs//VqDZniSDXKa4VBiN6RTfksyNpPvWxhmwuH8MdTPGcPnM2gDs9efbp1HXXle9rE7ZmB3NblTAaErdKd+waQ7Dq05oQB2J2Sey5yNhNSXEPqY2RdYiAolS3b6LWVyJ0PcekT1eaXY5NMgSCsKxzzaEwa1vRapLx1Gm4rCsS0TztCV7GRyVfxHuhOSeYhsiaCHsf9EmBQpXZBUdMcNesWtObhfVBi+lkLkHUac9Ve0p2SuHxCT+iOxMamhYuO/iCCpyJ6K8B69H7chPi1GH/ykws+Kr0x3UtHaKWtGd1xR32MPM4re/3U5iZpIWhtPnx9Sms71ZRv960Wsjvjs+DGBrbHTIvvZQ7QnJWMwyORFjiJRDRn78CKZWw/RecJBcp85RJgwMH2Nl1aY3Yh+Xp23lmTPBHK/Eor2pEFvQpPciOiPKOoXmAQJ8VEZUuRsIXd1ZsQ/pjOpWP5NyWhHFrR2nN9/Vl9dJkiKnK6+1xBipHsOga0VZ+ZsyTR0plT8NdQujrM8kWS2w4QQ41qzCj8tz7s7vrUVEfNkyfr0ivI6A9KfiiR67dQ10+9ZwK2IyWbkypoWJBW5kx5BUrJ1bi32XDtHuaANwBCTW/EgkuydNsBuxCaS5+z3OtOS/TM98X1JrmrsltxLIfVJtiFIymdwaho/J/5Dhgfp0wZWW8n6HMpn7UyKuXToKMKkEGHNnlDykqvxZ8oIebAzqYbXH1ny/k5s1GoEcn1i2CpGqZGthCIYbpG9rK6Q3rqT4nszoB8avuyftMUww6PCrX3TxF8t4OU1ThOypzxUvFXQFmRP6/ieyzUPaJdWT943SEpmbrAWGAF4Wcg+GJsXB3Iv+kXxWIxsNcwwBkmDzphBe1bFFEfxlzP6DJUSA4PTkVvvkL91Zf82WKsHmZjxDywS/dI11C+Um9i74QDmpbKmNC8q4D16P/3H7UdddznmZRfJfXa3+qOXHfjsnKMamZJ1yOwNTH0lS5NeDemNKKG5FkzxlspregXF1J8tYHVkjk9uRqS+dJjQFpVS4+nzWPEezQgZZmPdhhA0B4bL2TMh+eMB/RGFlxdz0s3LLJpzpvj2dCST9/O2/1/57PyvaA85s7N5XUjjmnnCXIC1aeHUFf3RiLDgg2fgrluEN14FX72N9o4Ix1JUxk38uMNYbcX6Xx3AbpjS4eM6FKujqO+1IHc1fPY2KpdapMZNIgvqgU2/GOP/QuhMWUTXlMkfk5oFFJx4e4npfw1YfrgFEdhtReMPSxh9ResPyuz6/QUauw1yJ6Kh2WZkQ2dKkz6rqFwOfj7Az1hkgdWHa8ymQtsRQWxY2l05A0jqMpiB3piNW4HmXgv+VdyEzQ1N5RILqy0LXmfSoP6msjiQG7D5MI36wRJ84jbquy14GFhtE22B0VdoQ+PlxaCvX9R0xyHIRnh5UybWJGjToLUzwq0YVHIm3R0B0T0WzQtD7KbBibcJ/rHqRqRPGTKpRwqvGGH2FCrSNHcpvGJIq2UQ5AzsuqYfm1h2f+0KupelmHzvAt3HzfPgH5fY8ffezxx4Vn+jTPIvvgFA8/FX4V2jaOwp41bFyFI//GGc/WUL9Ysled8Axn4csDkfEN5hY3VM3CcfpLrPpLPHJ7unTGYpoj1lkFmK6I4oGq8pM3Kvz+blNv2CJrWi6D75KvjCbbEBpgbE3K3wE83mM66GW25j/RpF/+Fl0sua5k5wLipj9GWju/K6MlrJ4mzEE3vkaBp/UMYbC6lfXCL3AJJm318isa5ob56Bv76NyiUm9V+fx900UAG0Zi3C60pE95wd3pf2bARj8esmQmrvmseYbdNdTop5ri9mjpsfOICKIuyagTcmNDg/GxE6JkFaU7vcBENjdDSNvQqskJYdQaiwmibupqKzM6S9Q5EbL9G4ELQd0frjEv0z0lcrT7kad6dJ9PR5ahcZ7PwqnHmEQeKKsiCEtSzg2tL0xqD7hjLd6QizA/qlJYKEoj2nqV/gsvN7sYlfV7PyzhLpJXH5Tmxq1q61aMUo82Q1pJvQtB9zJXzrNlo7DKIxwcUm1gX93ZqVzWR6SbF+jUNnx9XwkdvInIZ+jHXtx5vzgat9d0oT7IbKFSXy90LlUpMgpUmsi8FioyfPoPrkq6Sm7oYD+GmD7GcPcfrNZfqjEbkbDrD0i7JQJVdlw2x2Y1S4B62dGndTMfvHovHvF2WjkaiKSaiXVVTfWCb/QDiUpU68X+qyMksh3RGD1g5F+7VlDI9Ylqiwu4Lx7j1eZK7NPTLWk48/QHfMRCvoPb9E6MrBqjln4sZSKrMHvReJJDZyJJhjdTT9UYXpWXSfLbLXyImd1n1N1ViCz2/R2KoXK8xLQ8aA6iUKV8reOP0YyN4vY6E1a6AtTXJN0Z6LSC0LKrw1a+Bn4rl3WqO0YGU7s+DUxCS3foFJd1xzwRsX2XzPPBjidL5+jRNvVjUn/msJvxjS7CsMX6FCRWTKhskbC0msWnh5jdVR9CY02hDZjAoFY+zUBa06OBAaQYxC9mTuFbyxol/Uw7lSRYp+McKpGfjZiCgV0R030VYEyqA3JvS8wr1C1OsXNYmKIgzAbiqClEYFCj8X0YoMvIIGpegascxr3KR/kXnO5w6JflvmwNqbyjhNqB/okbrbYvbrUL3EwLjpII0LwY8PF+1dAWHSJvilEpET0bjApDBXiql7ECTmh+jhkbtFVtS7tkNklWlXzsAtt1G51CZpiCTRbsUH0Rl5bgM8/WBz3hvTmJ70P7spYzj/YERvxKCxyyC1onFrco+9rGyyupMaq63oj2jSZ8ToOnsixt4/dZ7IAa8oaGKnLhv73riivUOhQjkshMn4/fJC3PQK8rWKFEZ1MHeCuTtEJ0MI4zW/FwdQ8z66b2C0TSLLIHxZifrF0n960yJvbbdN6hc5BKmQY5+8Bl2VNTFIKryRCGS5IExHENPlVPw+iRWT+mUhypPvdff4GDULPerh121606DTAf2iAyoiSmqUp+js1Jgtg2DUx2haYo7rRNz3gQNg+Ez+k8nqL4V0dimwIsyaJQe0ZIgKDLSpsRomnRkNKkK7EUQKo2vQH9HoZETquE17R4iKxKjV6MsGuzemsXoKrxDRnpNnrUIZTyhQvkKbmjM5izATomM6GgpUoLDrsXmvq9GmxuxKHze82ND1FWX64wH9CWjutulW5D57hYiNnZooGWJXTDavi9DJELNqkT5r0NkRYNdN/JEA1TMx+4pwsg8tG6dhEibkkKpNhFKoLfx8hAoVQT6gN2YSOVLn0y8qUHIfvKIpc9RZk15cLLn2gqtxZy1GfhKyesDA5Cr44m1yyP2V66heLCc3L6ewnyx1c8auAt3r5nFrESsHbewmZDJZkhs+nYfN0xsxGJyPB6j9cwPc3R1xf5sRyVp7VtHeGVC9LiJ5Ak79fhmnIfNl4R5o7VKceHuJ0JW5qbEPmjvKdCf1VvAogtSS7B/8jInRh96YQfSseSrXBaRO2nh5g8jVJFZl/jvzpjKdHQEqsvAz0Nob4N73/0LGFv/3UP/mf4e2LWPbbtttu2237bbdttt2227b7f/g9j+bxva/sj3kw87Uf1MUvnKIyvNLWD2N3Q3p50y8nENkQv5EgP9VSSNmjysKKsTLCBGt/sx5nFY4LLD1Hr2f7qiJ04rw0wZOM6IeF3AmNjVzH1mg9myRraXXIEgYBK5Eu8Y+vEjnCQcpHJOizJGbJaU/njwokRtbCVklbzD60UU2X1giuaZpzxjkj4fYrRCtoHifwk8ZZM9Ae0JC3ZsvLDH5rxqrF9ErGKhIU/z4IiefJLl9q6sZPxKS+JpQ6ew4oj36o5D0vxzGjMlOABlg46VblKTOdJnsJ+7gOGLIN/e6Q2y+qCSmW60ItxYRpAz8lCKxCUTQLxqk1jR2W+5TkITx74Of0ox9eJGNl5YY+9ACU8Dyb5aZfvcCnSccpDNuYnfE5Ko9ZZA/jkSKuyJTmToS0ZoyyCxHeFmF/uwdnAaSf/8j8tUCGrjwN0US89OAgv5j9zN2Z492/LXdiZh94+J5v6v+9YeM7ZqnPW2QOxkOCwHzO8pM/OUC/cftx/3G0SF5qvGMeZxGKKaztx7CefR+oT59+yjZ7EGm332Y6nNLmMuigcmdCDFs0IZm7o+ErjX6hTt4IO57+URE/tOHGP2pPlw4FhAkpS8laiFokUiN3LxA7TkiTyr8zeLw7zpPOEjmS3dwEsicgYQvf9crGlg9STOffsKW7mP0LhhVAV7OJHPrEbxH78f59h1svqhEcjOiPalwG2AEBp0Jg8RmRHfMRkVQ/ImmMw6ZsyL/Sm1EtCek6Nhug5cVkzkxYQtRoYnd1ox/cBHjRSVQEgVvtGQCSlYjop2IFOZ5MTziHsXoRxbo/voBegWT7oRi5k8WOP3mMiP3BiTedUSitRaMfUju6wA+kj0b0B0xueCNQstJL0csPTJi6nsm7rpmGWhPmaQ2Fa1YkjfyIx91mSaxCaMfEYmgeuY8bmNg4GtAnHrvjSryDZE0ZJbk5yNfu49lIHcM8suxfGbEYOSekH5BTGWTGxFRdQteYLc0oauG8s0dbxe6X+JrR8hPlRj9iBDOnL+7nebT5olMiaxN/KX099ZT5lGBGLuafY2XNoZyt+rzSkP4SQbJVA3koclKxOhHhd5ot0Jqe20yS1t9H4TCs/Oth6k/c35ofjyQz40gRKHivT6mF+E2LCJLZIL9vIFWajiXGE+bx08qtBVLI9bF6Dn1pcNYjz9fh2Q3FXtfEc9Jp8DPioQuP1smvRph9g0yZ0N6FYMgDbkHDcyemEZHlqK5wyC5IfNg/VnzJDZD2lMWYUKT6csYzJzRnPq9MqN3SvG1W9GECXmWak2yAMkfQGtG+nxv1CC5EaFCLRCMAkx/P6SxwyK5Fhs25qU/2y15rdxxLQaxMbXRrWm8LIzcE6GVjOPkhkhOkhsR2c8tUnt2ieSmT2vWQhsiLemNGEy/Z4G1VwwMdwV2oA3JZnkFRaKiySyFVC62yJxRpJd92lMWph8RW3yQPe1jJiIMX8cGrAovq0mthYx+RMZ+csMh+1mRI04d8lGRpnCvQXJT5iGnbpKshESmZE5T6xGhLWtc4xnz5D5ziOD5JSa+7xOkTNyGpt1MoiJ5HxDpSrYf4TREUmd1xNPM7Cuyp0OaO0QZYLfEnDR0IPeAZPSsjqyTVlsz+d7FYf8HmPiBT/0CG+oimzVPieRr5Mcig44a8jyy8d9EFrSnFE5Lk6yIaqOxyyB7Ohoad0fLMgaMQJFZCmhNi7JBxq0i+xOT7BmRnBsesRzSpzdi46ekP6Q2A5JfOULiafP082C35PqCpJAtq5caTH7PJnCliN9ua4pvP8TaK8u49QinJRnD9pRJejmkN2KSOdNHW4rGDjs2EbUJUorE9x38jEBlCsc03XFRaaBFdmV3NZGpae50RFYWQmZJE9qK5LpPbZ/Frq+KgWeYEEpr4xnzqFBoeFN/LqTMyJL71p60MUJNai2inzOIHIPeCOR/Et8nLSAJ04vH5i7InJA11k/LOOuOWtgdTaIWUrvQYvTHW/TTldeUySxHtGYMsmdCaheazP6xkARRoA2Rg/VzBpllj96YQ+H+iNxnDnHipp3S7x9UJHoKwzMJXYURGDhNkScW/maB5DPnCZKgj1si/0uCcb+L09RkP7uAelmJ1EaEnzTw8taQBlh5QQkvK3Om0wjpjlkESVkv25NC7nPrmn5BPM0AJm6+A/sJUyS/coTp/gG8v5X9Z+ZMD+vO7zP+Pelb3RsPkPnxOlExgz56F8nLLiK8+z52LV9OmHGwNrtEP/oJ2fLVGH6CgThcxcuK1d3KYUx9+EE2AacpkrXKm8sklyx2vG2B9ZeVyJ0OaE9aGL4CNJlTmpGbhfqL1oSOwvRDlDaHpNvl3xQ5cPaMInProqzH90Rkbj1Ed6yM2ddkTsvcZvWEoDr5voWY5CnkvQs+H+Jrj/v5Odt/4NTOQ67Z8fLyJ8lKiBForI7oh92qdI3IVvi/uKWdF12i0MKMAHoFk8Yz5rd+NyZxhHbs/BzI6xS+eCf1Z81jdyOSXzlC8itHMPt6WHcwwHj2CqJBHdQStCdNIkthdyOpkYlreUb/epH0aigT5ZcOU73IoTdq0RmTWTa0FVZPaGyjf71I7pZDhI6QbJxmJCjW+FAz0Gn2H7ufRDU6bxC0nywbqmq8sWw+dZ6xD8lnqD9zHqsNvV8RMyTTk81BZG/VE7QnTbojajip69hlvDeiaE+a9AuKsQ8t0thtYPWEgnQukWrkHp+Nl5ZoTwoRxepqMrceInM2xAhESwvg1iOasxZhUlG92KYzcX5X8POSxPUedT2rry7z08395lHMf/y34deJ7/2I7o0H2HxR6Ty520B7eu5mL70a61HPIUk1nyobN/ebR8+rcRhQ39wBNS+jsP91qw7F9EQzvfHSEukvHqb96CsBmbAHhJ9BzcOADJf42hEytx6i8EmpA0p8/ciwpqTwN4ukVn28R4uGvvbsEqkvHx7WgxiBYGyDhAItmmv/V687b7z3cwa9EZPqPmNITKo+TxyOOxMGQUr+39glxpUDuppbj+hMGjhN2dCD0HJknEk9T2c6dkvX4vAeuluO5H5a6im0ybBWKvn3dw0n095I7NCcUnSeeJBe3iS97OPUNZ0nHsTqyb1ZeV0ZuxPhtCKCX5GD67kEsC0CjWwaL3rxUbQJvXhuMPrgp7bqT+zFu8me8bE6msrzS7SffJD8p+VQYXZDnMaWzjqxqWnsEmmF+im646A+ymlGTL53AS9rMPqRRSb+aoHUlw8P636KX7gTt6lJf+HwkMR2bhv9iGzY/YxJ98YDWHGAJfeZ82tdkpWQkZsXyX/60Hl1PcWPL7L2yq0xMcCep750eEhkc2sB7jePMvnehfP6fuLrR4Zfu40Iw5MDxKBmZ+m3yiS/cgT3W0cFrYsY+Sa+doTIVOeNDbsVkayEcg/ev0Dhk4vD989+bat2bXBfuzdukREzZ+L52oF+Vg119a0dUjvgxTQspxnSmTSYedcCZl+z/vIS/ZxB5VKb9oz0t96ouHq35gx2/uECXk7h1OXAk9yMyCyFQ5pUd9QYykFyJwL6eUVjj0m/IIf59qRJf0T6Tn9kQMqSzaXdEiLayuvKaEuCWflPHyK5GdHcYdKZFNNXu63xM0IjW3ldGT8tNTL9fExys6TmY/k3y0PKU/ETi/QLgvjvjUldhNWF2oWWGBFnFGvX2/hZRf5ThwjtrTk3cEV26TZC/Ixi7MOLhOdo/kNbUXu2zE+Rq+hM2iQrEvSzetGwtiDz+cM4TbEbyH1GJI+5Ww7F9wAau2y8rEFjp4WKBBc9fL6VcFiT2p4ycJsSALHacthMrUUU7w/ILIXs/i+LWB2pcx25p48Vk1ST1YjNF5fo3nhgWD/rZU0m/nKBxMZWTUZ6NRyuw0FS0bvhAI2ny/ztpxXpZZFuml5E7pZDOA2pi/Qyil5xiy6VWZKNuNTdbtWSRtYWqbQzJfLn2l5byHBpudf13RbrLyvFryUmwF5OkV4N6I0YpM6KJUZtr0F3QuoUV3+jLPVReYP6LkvqFUcVzR1mTAV0qV7kDGlW3UkJlgQpQXdHFlQudukVhHLX2G0IeW1a7rkRSB+1W5p+1iBIKOoXODgNqSFWkcgCO084SGtGApr9ohw+7E6MaXYVfg4604r6HnNIMcueivAKIndqz2pas1v9z25sjfPmTgO7E5FeC2lPq2HtZXPWovGMeVZeWyZRkTrLQd2c2ZN1LkzEh9+eEOKKn1jE/s7tpJfl2ay/rISf33qv7JmQzrSiNw5OSw/JkRCvVZOKRDWKZaxyMDQ9of15BYWfNGjPqCGFMfzla4Xal5KxEKTls3cnJNhidaTmqblLSX1zvO9pP+ZKAtegd8MBguQ5tTYjMtEM1v/kV48QHjsOwda4GdTuqECDGcsmF+4YzgsARixz1OdskVqPkL+zYmph/nhE+qxm80UlgpQ6b2/T2ilBm+rzShiexssYWP1oOFcv/basJWN3eaS/eJjMrYdYf3kJtyZr9doryqAkoJdak6KpXlHk5NXnity19/gDTP35Aq0ZB/u2H/Bzt5+nXuc/amZnu2237bbdttt2227bbbttt+32H6f9PCjp/7A0ttBVrL+8RGOXRebzh7G/cztuXdOZMuLi660rDxOK1VfLKb6fEx8EkOjD6m/Iadb0JC1p9TSGr4fR2fqvX0X+U4cw+xr/kdcPX9PLGLh1TX2PnPqdlsbPqiGByO6c7/dz6vfKbL4wJjdlhS2/9qoyhi+yMC/+XHY7ojOlyJ6RnGX1eSV6RUlzt2ZjAl3smROkFL2iifvNo/SKxnkkGS8tEQanGdF6yjyhK5x171HXDyN4A58dgML90bCAtDtmYHpx9qIjxK3eqBoWUNsdTf54QOX5JXInIryMojup8Qqa8BHXsvobZRo7Lck6nNM2XlIisuUZ2C15Lt1RySCYsVfFudkpAOt7ElXeuNKhH3uF1p95Polr80Xn+Dz8yhX4KeM8Kh4wpGcNPG9ACE6wJXfzf/U6vDhb0H/s/iH5KkgZw4j3wP9l4v1bhnytWfHZCeOo9Oqry0PfBKun6RUM1l5ZJnTFE6Kfk/ddeV2ZxtPnWXtVmfqz5mk8Y57OuMGZN5WH1+SnDdZfXsKPNXbd+Dq8tPS1IKlw2lreP2EOixgBgozQdsy+RD69rEFqNcDPShQ8cuR55k5GBCmhS/XzQnsyu1qoOBkVm+6JZC2IMyWpZYn2+FnF3DvkXiRqEf3H7kdF4tMS2mrok9H4z1fRuknuYaIi3xv64djQL1rD90lsaqrPK1G4P6BXNAldA+t73xcC1o0Sve1nxbuk+twSpicUqFO/VxZT0no0vH6zvxWt7f7qFbSnbPpFg5GPLZL+gki4El87QmfSpj1p0nmkZOTaM3Jf+iPi8XJu6xfP/9ppRqy9sszSG8o/42UTWZLJqz27NCRdtWbiKOfT5gkdFXsImSS/emSYaRq0zK2Hhtms+jPnqT73fP+difcvDLN/sOU91H+M+Kf0CxJH+ml6Xe/xsX/VI6+nNW3Sj7NhUdx/Bhm9QUt96fAwojjILm2+WDyn2pPmeRmEQfvp9wTpd42dW7GtICkZycKxgM60RK27I4ZIfWdFGudnhDyWWo1Ye0WZ1qxBmBAPlAEdaOTmRYncJiXaCrHXw6QUqbdmTNoTEkHPHw/pF6Ugvj1tiOGoqTA8hjKmfkFIUt0JIUMN6FD9EaEtDTLQrWkLLytgitpeE7OrUaEUq/cL4qcjci7xXBlQ3bpjkvHujcvn9bLix3L6v5TxM4rmLoPEhsBJBm1AAMucjsf7I64d/ixMGFh9TWvWxP3GUfoFoZT282o4jw0yqpsvLBFZapgJbD5tniBhDNUGrZsO0i8Y5D99iMbT5wlSxpA66LSjWCK0SPFej96okuh3Ip5LUwbdGAKiDUVjp/g8Cd1OshDrD7NYu85i5bXi97H+8hJr17q0Zo3z1owgaQxpgM0d8f3eIVkOpx1R22vRmjbxU7I+iRnvIfGGs+OMx6iicrHF0m+LJ0x/RA0zJe1ZRXOnQWdMMipBQmSDEJPTUkJ77UwLbKE3Fj+HENpzEe0Zxdhdkjbujhniy+UKkcz9xlH8tFAaa88u4TQlcyHXBV5RspkYMZBDicKkPW0wck8fPyMZRj8jYJDQFWJb6Eqf9AqSEemOCUXNy8v6E6Qk0x0kZe7uxJCV7oQi/+lDbDxMSabyHBpea2ecGZ3QNHaJx0ztIgO7AU4MbPDTApDpjRigY4rnXVo8sHKKfkHhFaE7odm8XLJHvaJJe0IAUL3RAd1QsgH9YvzvMTVUeWhTxmu/IKQ8LyPXUH1uifqz5mnPKuoXGIx/cHEYxO8XFetXydrhVuVeBml5nY2XlmKVTOyF5wq5LnRhuWQM1/D2bLwfcWX+XLs2gQo1QUo8pBq7zKFXk9ljCItBSRbejNetXlHojImvHRlmDs9tA+PogaKoN5PCuOIStGUQJRy0bRIkTSLXGtLYgoRCXXYhIEoFYLhOAsPM7kCGPNi/gFxP4+nzjNy8OCTH2S2N04xYv9qS7NyESeeJB7FbmsyZiMbT50U+iezXBn02skUBoA25zs6EeDeZfU17TuT0xWMBTtNn7RVl2jOK9Zds7bUeavuPTGN7yIcdFWjGP7AozsaP3U/9WaJ3d+oatyYLjP3PcmBRkUgKcidDwSsvhxQ/scjYnT5OQ4yu+gWF2ZdFZ1DnArFUB5Fv1HdLJ+gVBb/pp5XIKjyNl1FDGc9gkQ8Sivpui8oLShTvjRj9a6nZiWwln2MpJDIV/bzIgJIbEe1Jk+J94XCzPMDGgmB/TY+hEaSOqTf9x8pmZ6DXd+LrDhKSVu9MiPt37mRIZ8L+mYNA6Eh63M8KVchpCLUmtRqT67oipVAhuBUZLL2iSeQwXJzshqJwr6a218WtahJVTfZsOByYQVJkFZ0JY7ghT1Qj3JqYXoZJRa9g0J1QNP7zVT/zvGfetcDOP1zA/u73f2ZDeO71JL73I9xG+NN/TuFvFpl+98JQTuQ96nom3xejnWO5m/3d7zP614s4sVGtnzToP2a/SCDjyWSA2O088SD+w0VSJrIWRe5ExNiHFpl838LwsG16InmceP8Cdidi5GaRpwFM/dkCRgiZsyH5Tx0id8shJt6/wNw7FsgsBTh/dzvpLx5m/AOL5E7J4bfwJZEFFb9wJ50nHmT0o4uoUJM7HZD4+pHh4QLEHdnsChZ98r0LZD5/mM6kRe5khFOTZ2m1Nf2sINlVoHHreojfTK3KIdTPKtyaHpqxWV2N0xQzRhVqVl5bJr0k71vdZxMmBXNt9TSZb901fP4DecHQELgdEbgKqyfa4UG9mxdLGxJfP0LhbxbxU7FxYHzIz31GpH92W8uGAdi83MZpIhvHjLxPYlOIXQNTUastk3VqNaT+zHlqzykNJTEgdUXD/nJMcN9mVw3rEQbN8EXeMJBmeFkDp6FJr0Qkqlu/27zhKuxOROJrRyh8cnG4cRu40Wc/e4iRmxfp3XDgZ97j32vnytic9tZnHWjgB68JgozOfvYQmVtjZPk5GOjOE8U8rnfDAezv3E7kqOGYGmBNs6c03V/fkpsN3v/cNkSzN6Lh+5zbnNbPXlNiUzNyr0yUo3d1hEwUjz+nDk5DMLHaUkz8W4C7Ccn1aCjBBUhuiAQse0rmj8SmpvKCEukl+X5kxVINf+tgfS7qvp810AYkKnGNyZkQ0xNEstOQw3FiU/q+EQghLHNGkPtmfwuTO5A6uXWNl5XxkqiKe73d1Jg9kZpmlkIxIa0Jqje1rGPMsBzE+jmD3KkQqwuZU7LpMHsyPxaOiXx5C9kPqdVATAAnt/wMuqOmSLXqeogjz3z+MG5dxlaQEnkTiJR6eC+/coTsZw8N+03/MfvFNHdZxkjoKqxOxMjHFof9IVGN2HhpiTBpkBysET3pj6Yv61j+wRC7rUmuSzAvvSTrhtmFxLqmeK/IoQY1gANZX/GYH2PQ5XUH0mUzXlszp6UGrjknp1KnKTUImTPRUB5sdSC1EZHc0KRW5D/Dh8yZkPRShFuVmt7sKUEkg6ytflaRXJP3DTLynl4e8sdkzU0vS51RZINTMcidjKjtdRj/4CKhIzJet6aHG86Re0NSK3HwoSCfqz1pkqiIHNhqSz9IbGiSGzo+KGk6k3aMCt4aM2KJEc/pPaS+c0oOLenT8npBQvrk6I8DDF+L6XRDNr3JNc3y68sk16UfZk9oUl8+THpZk9iQ9yncK2u8EYC7GZsvp4mfISQ25aDmVqUfh+cEXQ1fkz6tmfueR+54RP7BiMZu2Qy7NfncAOMflPUquS7GqFZbxn2vYAzlbG5N49Rl7JmxfUD+U4dIn9WkVsXawerG/XddD9HTwzlmXTPzpwt0JmU/Y/XkWrQp49XwIbUspuhuRcuhrqHJnZD52wjk8GC3BatuteX1k2si8YscsJty3xpPnx9iz7NnAsY/KGMrsxTi/V9bZRSDFv3SNSQ3AsxL92E3AqIf/YTozp+goghtGph+hNHxwZML0qZC3/2AzF3xGNDn6KAGweFBcEqbYHcFN55alXmpe+MBsqekXsfPbEkK3bpg8kH2cblbDg0l1O0nHaQ3qobvpZU8A7PHcB4ZGNMW74mE6AsY/+0HRI70WeOn5N8PqQ1kaQ/1v/8N2raMbbttt+223bbbdttu2227bbf/g9t/ZBnbQz7saEPMx5yGZvMKGyeWxPgZkUJYXZPmC66Gm2+jX4B+WqGVQWdaMf7DgO6NB6heJEWfrR2K0R+HLJdN4e+/vkz/7Bn47G14OSUp1BkxIzvzu2V6YxHFeyTFuvSGshRyJ6WAcem3ymRPSZSrO24MIw71Cwy8F5YY/etFGk+fHxaJY0DPlRN0r2jgZxXaNOiOKzb+oEzx3ojcyYDGLovaPol+9FRcuDgOalKhQov6PjAb8v2Vl1xNYlphdc2hjGf0o4usvUroY6d+v4zdgsrTxEsotONoehSbeCmJTNb3KtyaREO8nLDmrbZCafl8oRNLK/IaFUJrh8HsOxc49XtlDF8oQv2iojceMbWgOfZn8yRXJaIz9qOA6sUWhge9UZMgKeZg2lQkY4pJ48arMNwZWrMmflpIViBynu6Y0Nsytx6i+dR5No0luOU2GjdehTNn4zy7hNJCKAORunl5RXJdk6iGw+xd74YDksX40mF6NxwQGcaogXXjAXqjCj9jYT23hIok2qENCJ58kCD2GoGtSEevoNDPEE+j/lnxlwlSisYukwxQ32PRfUGJfkEx/V2hZ3WmxIw0dOdp7jBw6kK2W7vGpv+r8+x9/aGhz0rBPUjFWoZbb2PzGVfj7DTpvrhEZ0JROKboPqdE297y2QkdaOzTZI8rTr+5TPE+CZ3VLjTInta0p2MfmaImf0xTuwiSa+I3YbXl2flZ8X9JrWm644rJdyxy5k1l/DxkTsQFnXFUqXqxiVuRQtozbyqjIlCxx40RaDrTcco9zlrWLzQxfIZ0pOClJaHeNeS9Eo8/QHvKFPiDI1SozReWSCLSkCAVF7VeLBHxyjVC0ghW5fV7o4qUAUu/cRW89zYqV9gULOjnTayupjuh2PE2IRCZnmbzUpPwWGy2uNuk94cl+mMB9ZIB/wqrz9oHnzpKd0yx9NtlzC6cfWNZriGEqT9f5Pg7S5j2VfCl27DbEb1dJs1XCPxDmzD9ngUql5gYN8i16Rj6kdzQVH5HotjZUxGdCYPCgwHNWLoaukr8wmriP9LaCeHBEk5NkV7SBCnwswqimIbmaXKfOcTKa8tkT4dElqK218CtinFs6xUiIcol5wkdWH59GSMQIpZQFWW+SAKVF5Tw04rc6UCIl9kBYewQjV1C5WvFxc1OU4zrvIJkujujV8Mntnx2cn97J9VXPo5s8gArJZPMCU39mfMEqXOkXrZEKvs5g/RqSHvKZOOlMn4NH3xDpD2dSQM/DYUHIpo7DOyWJncioLbPZvK9C/ivKpOoapxGSOUSG7cq5pXalL9PVKSAvV8wJLudF0lZ9RJFakWkxNW9Fq1ZyYqErlxTb2zLEDGxIcADpyFRVNOT6G+QEg+S9oxE35UPnRlF7nhEv2BI5D2MpWUKel2hW079+eLQXBqgOSfUziClKDwQ0NhpESYELpL9wCIbTxcqVZiQSHVnWoAlbk2z9qoy/UJsnOhLlLzwSRlD/aKi9+ISZh8aexTZkxLFr15s42eF/md1GWaUGs+YZ/MqRebklhyrPWGSqIqEk5+cHH7mwTom8iuZ31UEftpEaWjPie+Q1YL88YDaBRaFBwO8vEV1r439whIYsib1xuIscFNz5k2ybg2yQIlNTfVSRfMtZXLHI5af2cO9VExHvbyBlxf/rN6YZD5ac3EmNg8V0xZVR1rm72bepDemScWQEBVKBmfH2xZEAmeJfMn05F7aLU3tIgOnJuvRYP/hFRReDs68qUxyTeZCt6ZJL8mcZrclyy1eUQqrK9Kz3ohkOwxPpGJWR3yVnIZkr52G+MH03YEEXDI9vXEIdojEPHI1Rl2xebmQx7SKM5kF+QxGAKElWYt+bN5S/Pgi6y8rYQSK2j65F4YnWSw/JfK29oy8p5eTex45iva0Jn1axoQKJYPa2G3Q2uWQe1CK9w1f7kdqRe6p1VWsvaqMCgQ8kjmjh9LTxoWQPiv+c/3H7mf9YUIFVQFkz0bUnzWP1dXU9hmM3xHSjLNerTlFuivKnciWTKmXV5z8wxLa0CQqIuGT8Q390ZDUv4nZbPUSRfEeTeWyWAamRUaYORNRuUzm2VO/X6Y/HpI9Jn0nUdGETdlnWl25Zlbks3TGTKrPLdGdlHnCOxWDDUZM1DWX8+BTc8z+Y4CKNP5YBuOff4B56T76Mznshof61x/iP+p6LFMRTOZRxyD7YJvmZRfC3bfRH/1ZU9H2rPxfm7D2ijKdGU2iCmd/p8z4Dz2WH25j9k2auxVOTX63OymSv/oegUutXm+QXIXgP13HygGX5Jpm/VqD6X/xWf4Fi8JP9NDc1svJvTI8yYx7eQjSBlYbKhdbqDeUh1m8gS/dz9X+A9PYHvJhJ3s6IPPRBbo3HmD0I1uys+bT5tGxljKpq5wA3BpMf2hhiH2OHNncRk86iNWNcL95lP5j9nPB7xym/eSDgo784h2ATDKWq+UAo0UO0nnCQdpT4kS79oqypMDTMujPJSl1bzww1NvbT50n+7lDbL6wRKIeEdqKqb9YwH/k9VT3OVgdTXotxHowpDXnkDkrdKQBTS2zHOI0pZbGO+FxAijeGzH5AZkcxj58lPVfngFg6sN3kFOnANmgD7Si+eNy8tr5B2JUqOvnynZCvKy4aAcpkdmZnkmYiElqZ6G2zyAVT4KpVS0Y72fNo8/KhtdpRiz9dlnkT32hF+VOBvTzJr2iQe4BSXcnqprmDouRuwOClEHm1kOsvapM6Ii8YOM/XwV/exu5r95J4j9NkPn8YWrPLlF9XgmnKRjnc2AsAIzeIqjn5HpIWgfnSRFBame8/JZOffj9djisC0p87Qi9Z5ewO5rkV4+QRA5Dia8dofPEg0NqSfvJB0nUQlRc12W3o5i8pMjdsoj7mP20anICSlRCxr8sh7SpPxPs8MjNW1SsmT/Zqv2JwVP0H7uf4v0Rzu0BvRsOnOdQno6f8egtW894FJHXuZ87iv9LMwy2HfkTAZYSPGRyXb5X/Pgi1tPmcZohoW2BkkNm5tZDsjmMN4AA2VPhsF7FaUbkThBfk6bwgKYzZpDcFEx5e9IkuaoZ/evF4Wa58oISUXvLgTlxLBreLxC5xeCg2XnCQSJLNP9BUsZd4utH4IYDeBmD7GZI+0kHh+7OqTUf5+9up/rcEoV7RaaoX1YiezbAN7dQoMELZlHLmjPA5EfuwH3sJL0Rk0QtZOzDR2WjnVSkVn12vP0wK782B4hkYe6ji7SffJDw83exDEx+6n424p+Nrvv0iib59x0a1jgA7HnjIg0tQnc/bZDbDCl+/Py+mDsu0rZE/NzGPrQlQ+vdcADDF/ndoD+m1ny64xZTf7E1t5yLMe/++gGSnzj/PQZNhWB1I7ysyeTtHqYX0S/aw74M4D2/xMjHFmk+dR4V6SHOelA3OJAXAiQRqZP7raOsv7zExF8u0Hv8AVQcVnO/cRT78QdIfFA+T0NXOX7O51l7/tXMng2kfuysim0DpNbS7EJ6RfDJ2bMRzTkLIxDqltnX6BW5p82dBmECssc1hQdC1q+OUasvL9GZtDA8zdk3lkmtCFHMn7SY+nNBoqZiZLjd1lhdkQeFjhzkEl87QvAr19EruqSXQwLXILmuKX5ikc0Xl4aHUKcRL/5aNodOS4upaF8081N/JnNyd9QiuSl1oL2iBL5CW+rhAHJLAd1Rk+LHBbc7kDyNf0CeRfZzh3Afs5/qRTa5kyGtaZmP/bQicyai88SDmL0leUafkfkgiJ9l6ynzZG49f64DqdUaBNwSFZHKFuKfRS8qDSXB/iOvx/7O7XR/XWqyhAwqQQbT02Q/Jn2x8nz5ujmyVSyYXguJNhV2O6I7KodjwxeJmwq1bKTTghBv7LRIbgglLLJg5k+35sPujQdot+R17Y5m7h2LLP1WGW0qpv5cfi94QYmRmyVgsedpEiSTaxeKXL9gYPblYY19aJHqc0vkj4ckv3KE1lPmGXmnyEhDR1E4ptmMKVqp1QjX0kJibWqyp0Pa03HNbEx7K9wne4LBmr/5whKplQinJiTV9ZeLOa/bDOm4JqkVzcjHpC/pnsjEu6NxUGNO7Ca8vFzbymvKWF0hz5mexvI0IXJo8bNyKG/PyIY8c1aQ3pO3e3THbCGJJQdBI4P8CQlyBV2Rq1afVxoGqNpPOihSsUDMWZMVMQENErKfCUJ5ndDZoqalV0IMz8ArKNJLsvY1d5iYPRj9cUh3TIKs0++WPVe/IIEIPyMSOhQ4TTmoZM6KiejE9yPaU+aQVJc7EQ3HJoiEqnvjATKnRe6eWo6tQTY02Uqf5pxLmBCpqTbBOit2BWuvKJPY0NidCL9mULhPavCSG5rRj8g4GL8jolc0SC+HKK3xMiaJTZFjjn/gMI1nzKNVNLyviarGz0k9avZsQL0jN6bwpTvJqdPEpcXDdSC9FKB/8GP2xHCy6Jeuwfhn+SK8536se2Sfblx1CYnllsjaBmPStdCHRcaWPQXrQGbxJGvxzyc+ez/rQOH+gLF/kXGQ/ewh7BsO0J622fV7izSfNk/uuKyR6y8rMXYqQmnOWwP6j9uPddv3mYvjUqNIAMytAOjhvil3UmS17SkTFUggFCWlBIKejq1NnnAQe+X/WZr932vbPjvbbbttt+223bbbdttu2227bbf/uO1/k0zNQ20P+bDT3GGhnnSQ9pRJeNNBvKyBlxWyhzbBf3GJ/pnT8M3bMDwpzjN7EiFqzon8x25regWLxsskrZ+aKuFnJYKhHnE5/IPI2HopYeen1qIhUUxFklYPE6AtE62E9755TnRs4woLd0cZqyNkq/qbysy9Y4HVV5cZ/XFfePE5hd0QGVh1r4U2LSKHYeGnXJNNZEtBY5CA9qyAEoKkwfLry4z8xGftlWWaDZFOrT/nakJjdiin8J5biuk4MEVMh7pYYza2uBCNXSKpUVogD+1JEz8mBLlVRb8gUqEgZvIHaUX/1ZLVas2KBK49q0iflQhOkAKnBpuX2VLAbykm/nKB5deXhWpUgNo+C62g+/KSyOdQVC6x8JbOSdPO2Kinz9OZlJT66A+bbOWjtpr/i5fDP0tYojlr0n5RicxSMPTHsXqa6XcvUH1eieLHF9Hlq6lcmsIIQL+gxMjNUoAbWdJH+o/dL5S7gon39Hnceoj36P1sXGkz8pOA0DWoP1HkSo3dJpm8yNrOvrGMU9d0V2Pi1pyF88z5YXRTaejHn6HwNxJ5wmBoBhgmxHtkYFjYzxk0X14CLcWdXkpet/KUqwlTswQpKWIkguTT5un2t2Rs9T0W7qzCCCW939ypyHxezBRDV0hR2lD0s7D5B2XxxjEMemMas6voTpg4dSmI3LjSwupAI5an9UZjiUPKoLbPwG5JZHvpDXI9S78l8q7mxRb8k0S8VZz96BcMMsDm5eLT0X+uSNJypwIae0wpkvUkCl3fY2H2NZFl0ZkS35Te4w/QmTAxni0yQG2A98oyiapkmPqxH0H3167ASDDMVHn/1+X4MxZeXihMxeRBvJw8l42rXKy9JdptuX+5r95J8+mPoXqxAaE850Hz8op20sKMMwiz71yg+uYy4SvkM/SXT8nckVW0MybV15eZfo9E3fKfPkRrh4FzwwFqF1gkNyMaLyvRG92Sp8z+8QKD0vPQAefvbh9+vfHSEnbsJTH5vgUBN6QU/tPniWwpyB0Yg4J4SXUmLFJrAbW9DsnNaFiMDgIrCF35f6+oSG5qejccoFc0RdoXz2eVF5Rw6xIR7I4YNF9SYvwDYtDcGzEYudejepFD5gkHMXz5OxT4J07Dd7bunTZhdb/J7rcswrPmBezix5K3aY2fNUgvazaukn7e1gqnLoXs3XEpkh75ScDGlRbtWUVrh4UKJaPfG1W4VYbyUj8jc5XZB/XsktDbHEVvRJOoKEJX5LORBZ1JC2dXme6Exm5C5RITqyuv1XpzGSMEL2fSmY5ILRn4OQhSGiIpdvYKMmd3pkUyikxnoKR/RXYcBTXkmUY2hAkhIvV+U36/N65xnjJPd1ShlcJ+/AFW91u4FWjOieSTKJYm5RW9UYN+LNmsPekqejM76BcgfLlIZbnpIChFa9bArWhql4C7qXAnS1h9TW2vQzZ5gF7epPiJRTpTiujlJYnopxXW7pL4bjU1jWfMxyasQif0XigUxM6USDCH8/WUQTglMiq0SXNPRP4+aA+kVrbMG3ZL054RypmfVvg5jVuBtVeW6Y9AakWyGoOi7Npeg413lLAbQgU78yZ5JpEF3mvKJDcimk+dZ/1aRWJd0X9xiSApcsMwIc/x1O+XQUO/blH7TZGWVn5f1qPEpmRMvNMxiCZn4M9JkXrogJ+x0CYxNU2eY2dSyGTt15clOzWusNpb8manqTF7MfFqRqEVhC8r0RsTY9TqxbJuro6aODWZ+yNLpPIqAj8n9yp0Fd2J2O8uliR2xw0iU+aijVHZM2jlEtlCejP68rPIhMZOEz8n39t41zzupkjMj79DIB5mV8m4nlQEKVMkmTlFfxSstsjgtCH3EaXpxNJipyYyLhUJtKA7qahcZmF2oTeqOf3mssil5+L1whP6oFPTMi570o+7U5pOXDQfuRqrrcT7Laa+hY6BH5cS9IuaxLrCa8ta4hUUG7MJUeOkGMICVAj3v+8giVW5j2AKadIQKIJb1SI57qnhmOqOWyQ25dpDV+imwXPEtL4zLpQ3Isk2RbbszbycRashn71601X4hTm0KetXq34Gvngbfjaey2KVTWNnggIiG3M2u0Q/vBv98IfhuSZ+ziSRvhqz6xP98G7aM1tYTC8r19b4hV3wL3fLv391H3z3KJuXW4z9i+wF1l9eEh88X6GeI2tL6ELnDeKTszEtslLj4jJ2W5Q73TEFV5Vx6mL0jBIAgdWF+j4IX1gSyaLWtKdlzg0T0J2IcBoG7d8TGXTrKTJPGAG0siZ8jZ+r/UfO7DxkGltkC/LX9ASXWLlS053UdOcCDF+00JWrZVvcmYP2zoj6pSGbVwnpw2lq3FpI7TKRtVldaFwoC279ooi1a+PBlNPUHtGjtTtk9REBlYM+tWs8qtf59McivF19OuUW7TnN6n6D2iWaY5+8hgffWaK72xdTuaIiyGj8fKx/vihk6RddapdF9MY0/fizdqcjupMR3dmA6pURmy8sDWkYzQtCKteGtHZCa7e8TmdS0doT0p6URbM7K7KT3ljE+i8Egmq82mPjWk1/BBpXeay9ssz6wywufMOhIfIxTMZmdFXRm3fHZXLNLEVCf+mL3rdypdQCZM5oupMR/SKsX6foTGu8vEyMtUsEi+pW48NaHlq75HmdemtZ5F5ZqZXoFwVXPTCHTFQi/KweIpwBcsd75D5ziNSqZvJ9C5z9TwXu+9B+Vl4jKO+V18hGYeVg/LzyBomq1Ch1xuXmmRfvPa/fLL++TP3CFKN/vUh7RpGITfECV5DEXkZRudRm5bVlCp9cJPeZQ4QJgzO/bMnimjFIfemwbCiQidKtyYF19p0LWN0tI0JtyCTltPRQgtWZFAO82nNKePkY65kS7X5kC2Z16bfKrMw7NHfJdQ3INwPTy5FbxXCs8IBP48KIMCmHmO7E1oDvTkQxblVTvVxczFdfXaY/Is+5uRu8AlSvkI2GViJZ8EaF+tcf0ahIiySiDt0pefZeQePl5Dm3d4VoQ36nfkkQ40SFiNjcG+LE/aB+eUjjYJcH/7jE5v6A+z6yn/Zej85UxMb1Ec1dcOqRIoVrXuZRvzTg7CMM2jOa5h5Yn49o7wqpXh1x+lGKjV/0qO+T+9XZGVC7ziN3yyEqD4vojUv6PPn3PxJiY2zq2pqRTUFrt1CSekWD5m55Hp3ZSIzp9vWG96+fU+z8g4XzjN1AxoPpCV2qMyvvlVrTeAWpzRu00VvuwOrKvVl5TZn8p8WkzeoIwc3u6CHmPXciIr0aMXp3QOPp8yy9QfDj/aJsnpfjDfHYhxZpzRnDDdXIzUKklD4WEaQV6y8ryWvEJnF+SkxyJ96/QHfEGOKrj79D/t8bVRiemD9mPn+YzphJfS9iPJuU+isAIxTUfm9U4dbFmDX/6UOCep2wxBR2wqA9aYqhZ2OL4Ddo2dMRZk/qIAc41+qlEqRymiLPMj1NYn2LPtWZjs05p30xkC2YODWGZsdKw+bl8j6tnSJNm33nguBSK4LT1qa8ngrl30FSAgyDeWrwPlZbNnZOU+pNVEC8SYvwM2B1ZDOrQnCqslntTmryxyL6A6NKVwx6VSjrx6Beyyto+kXZAEeuprVLDylx2oDcMWjsNhj/gBxWK5dZaFNkcJEt5p1+FqoXG8P5QMVd008reiPyWVs7ZZNY22uydr2iuTekPaNIrig6cxGdGTFHrF8c0s+JpFNkU1ID0BuVAFx7VlG72GD54bB5lbzfxoGQ+tUejX1QEzoulYdFtC6StWdQoxq68mz2vv4Q2hJiU+hCalnmDhVC5rT0+8xZzdThLcmL1RHSX+ZsNDR+LhyLyB2DkZ+EFO6VdcndlHqWyJGDR22vwcw/CwE0MsU4M3TlEOrUpb4quS7rS+askOEMDyZv97HbkH8gHMq73EaE0xQplhVv3tEif0qtaqyWvP4Ac+40I9q7AhKVSGwlXlGmN2LQuEBqj4KUyLWClMKJzTftltTwuNW47mVDkzk9+KwaPy39061qsieFbKcN8PIy9yY2475jykE6cmIz0ab0iwFZDiD3oBDV8vcp/KymX1AU74Fdv7eIn9P0xkQ21i+C24ywehqnKhtabUB6Sfq0W1F4I/K77TnwilE87qS/+xmZG62O7KmaOxUjd4doU8Zk8d4wrgXVWwcoHY+nOqhANuaRLa/VLwgxLP+pQ/QL8et2tsyuzZ4ETkMHCveHmF3Zexge7Hv1YexWPOYVaBv8rIyl1i5F7n7InJR7pCIhHSYqEV5BE2TiNc6VdSBICr10UJ8ra6iiuTu+BojrXxWtnVInFMXmoKnv3EXwK9fJQecZ80KM/MVr8HIWq6U81eeViBwDsx8b6BYdwrRD5wkHSW5sYebyf3ffeWMeIPfd++X/JyKOffIaKpeJzC65KsGzyuXQ3B3hp2Mc/ohm7M4Qtwq9y7qkViMqv9AntaKxW/KaiQ1Zs3IPanqjml2/t4gdS29rl+jhvjH/YERi3SB9RqSpQhs0aF3fxctuUYN/rqZ/zv/+N2jbMrbttt2223bbbtttu2237bbd/o9uiiEV4SH9zf//t4d82Ekvh/R3QmotJHNWkz1j0hlX+C15KW1C4UcmK0BiRZFrK/pFAxVAZGnoC3lm7jaf3gh0Rw12v0WKrBI1iD4nRcm5E5pUy8VPKwzPIFkN0Uqif9WLDJL3OIx+9Pucfot4jdhtcJoW7jeluLk7IpmM3W+OjfheWGLfq6Uwzs8YwyLZ5JqB3daxoZbF1J9tFWpWnl8idVZIV6GrsB5ULCERi+z9JkFKomGTPxYwSOFeRaJp4dZD1I9M0l88JIX2bxVDzIFJVzomhtltzcSnFlj6rTJOTZOoRtT2Suq1N66xuhKlmf2niH7OxG5HWB0hO6WXILMcUN9tE7pw4W+K/Kp6sYNWkFyTrMXUXywIhMAVStHaq8okV4UMpU1JQQPYTYW5unVE7484JNjiyOdOhEy/e6ugG8TXaMe75Hmlv3UXWSXXNfAkCe89RvreY7RuOnhesf/mC0tDQ0wQ+ET/cfuFU3+OF4X3aPHaueBLW+/ZeeJBJm7+NieIJSn21s+cZkSuNoj4R6RTEakvH5ZC8q9sFZIngALQuumg+LY86SDaVP+uZ8nAS2l4zTdcxeznDlF9bomZf47wUxH5Tx0ivGHH1utvGhg2JDaFQufWfc48wsKpiTQocoS2tvd1AoiwupLVS5+U4sPJIxHNneILoQ3I3wfVS+UZRY5Ebt11E6sj/569TVHfA5kTiu4Y5O4zCWIjtOIPTYxekul3L7D+shLjH1zk1O+XSa5qtCkR/oF3gnvWJnNKsmNmT7JmdluM+wZ+KwNTTbcRUPUsEhualdeVyR4DK5YQrrzkalrFORrN0/J8T/roPBTuMcR3IVRc8DsixerXhbaYuttiGVh7wdXs/bAUE3u1LWkgSBQ9/0kpmM3db7L2yjLdSYn8jv4oJIrBFc0brqLQ0+x4+wL+r15H5wkHGf+AjP1zQSYDCMa5/cKNZZQ/3TZfWGL2j7f67Nory2TPBsN+lTrnd3OIMdzEX239/uDfjWfMs+dNsalk7GUCMteMfGyR4JXl84xzO088SPIrAu0A8anKfk7mk9l3nvN7Tzg49LIC8Eoz533+1oxBuisFx53fFKPn3W9Z4MybylgtqF9okD6rae7RZE8quuPg1hR2Awo/tNGW0PfcShw51GA3hFCUXpJ+agR6SMmzupqJ9y+y9kqhdLk1zciPxJzTy6k4+yPzamJdIrhWT6hDKoy9VnLgVMUfzOyJtGjgR5I5I7SqICUR5fYsJCqK3qjGrSjspshmzH7cn/vy+s7xQaG73JfQEZqeU9Osv7wkMh8fMqcABZ3piMgysLowdodP9RKb5IYmiMlHIz/xcFshkQWZPznMWvz8Nl9cInRMyQDvsphaALfmYX/ndjZfXMIIBMYSPG2e+h5ZA1s3HaS2z6RwX4TTjuhnTQqfFJnvzLuOsPrqMsX7PJy/u53T/6XM9D9CdOuPB1AqQKTQmaWQ028us+PtC5z8A5GRN/ZKdiBMSCYtXJax3562hvQyq6M5/RYB3fRGFPbj9tPcIbLbyiUmbk3Hpo4yPwygBgOD28gWCY/pxfe9qHCa8tpeVmH1ZC7xYinVxlW2yNBPqaFxbpBQJDtaMqoazL7MeaEtJp5OQ4MhRqliJqoo/Mhk82rxt9n9FqFWFu/V+PFnDdIxjfEFJZq7VOy1I2ugeNsJlcxuifdQakVkmF5OkzklFEAMcOryt35G0R3XIoFzwc/F0r9AxoWfUUOPwdasqEtUKPO31ZV16tRbhZ6lAoU2Y2POGRMVyrqcWtJ0ZtRQ0tSei0idFflesqnoF+MxVJV1XemB7E9Id2ZXUb1IJJjLv1kmczbC8CH7IPRHYg/Epsj6BhI0py6f2ewTK00kU5ZckzEWJBl69Zk9yVgEadi8QjK+/aIa+r4NjMgH3kSpsyLha+4SiMTpN5eHEmwvB/njESCm73ZDMfqRBTZfVCJyoLlLYFdeHohlc05NEdZiYmBbMxX3xf5j99OuSFbGL102hCDZnQi3rrE3Wphdl9SXt4zdAc4RtchcfuDK4df1x1wE3zqK1TlHNvqL++CfjxIkFHuf/QNWf6NMc04NlSaTRwSs0J4RqW36tJhY195YZvIbLqGjGP+uS7ISsD5lk1rVAvg6Ln1p5l8kldWZNDD64G7Kvs+tSRbfqQucYOU1ZfGJ6sD0VxzWrtWoCj9/+w9MY3vIMjYjEKNEgO6oRfazhyg86JNckzRz8b6Q3FfvHL76yM2LaFM07E4rJjqtConN9Bimy9Nr4XlmSIYv+OKxDy0OtfCpLx8m/cXDjN4TDCUuY3cFBAlxtT93k+I0JQ09MBod/evFoXv56EcW8dMKtx6SO+VjBJr0aiQ0n8dsbW6NQFKLYx9eJH8iILkugyizFJE/HjDx/oXzNibZb9zJ6EcXz5PfnLuZKn5ikfynDg0NHxOVkLNvLIu7bkvjZQ0yZzSNnQbpM7L42A1N8itHhoaY+WOSMs+cDXC/cfT8jdGEjZ+WOpmJ9y8MsZwTf7kg6eKWpIfNnhZaUUeTXBVZYZgQPO25n7vx9HlGPypkugFZ7tx2rmEiyEQz2Ax3nrjl4jugTA3auQeaQXO/cZTcLT972Pjpdi7JxG7EJL1zDD0HeMj0t+8ammgOzC5/ug0+V/qLh7Fi9GnjGfND53Ng2Kf80mUAJDZDeo8/gNuIaE8YQ0TsuYZj6aUIIxCqVmfSwPn2US74nUUSm5r8SZ/0SoRTj69nNSS5ock/GFI4FsqE3BGph92SiTN3wmPP78rfZ05q3E0o3heROxliN7YcopOViLl3LJA9vSVNyX79TqbfLX0kuRmjSDtibJbcjMgshaRXA9xmxK7fWyS9GjLzJwvkjwc4rYj0Fw9LMOAx++k9/gCFTy5S+KQ8v5k/WWDk5kWm/myB1GrE6C1CUpz6sPzf6sXGaWmD9FrI+AcWyX/6kNAE4zqa1GrIxF8t4MYHlYFExE8r3Ob5+fj88YD6s+ZJfvUIdlP6eP5+2PX7Ytzaf4SYyWW/dufwudjf/f7wEDCoIRq0wdhsPm3+Z573oLVukr7w03124v0L5x2gf7qlV/99Is65fTxRiUh8/QjNp84P57ggdf7vn9vfQeqIzm3dG2VOO/egA2Av/Pi8rzNLEYVjsoDaTZHcgBwqwnhDlaxEpM8qOpPy88KxcHhIS25EZI8T1zCKNClIyfPqTCoyZwNSawFWJzYQDGQOSK+GOPF7uU0hCGbORkOMMgYx/j7CT4t0J7muMXyRnVld2QjaTdnIO3UthKk0sYRDNl2JDdn8JdYVdkuT2BTJlIqkvid7MiKyRR432IhOv3sBty6mkImaSEBTa5rM6YixDy/SnoX0WaG5GR60ZmWQW12NG0twe6MWTiMYymzMeO536/Ec/O2jpNYE1W9/53baT5bAT2SJ6WA/p4YylsznD5PY0OQ/fQg/aVD45KJIar5yhP5j95PcjOgXLbxHXX+eVEqeo2bsRz5mX0yBM2fk5yN3izQ2d0zmpfyDAVOHQ+yWJn88YOTegEQtwuqKWXhqVWhZVkfmZOkfclDJnRKp+tSfL1C8L6TygtLQUBTkuSVqkRwye7GBZ1dMRYv3Rozd6ZPciCjcF2E3xYQycyYi95lDW2aVmzJuDE/6UHJdKIrakvmwP6JIrmqS1ZD8sYjQUWSWQpyqIrmqWHuF1EP0czLnz/zpwlAyFboiRTKCLVPI9kwsZ32A4ZgIE1JnY3a3DgFmVyhuTkP6YGJT7onTlD6XOy5GqW5N+qcRyHzrNOSAYfiKkXtDivd6tOMN7MT3felzy3LA8WIs6IAwmoktIeyGJrliDOWjg/GaO66xY5PpxGZEkIL0WZHJ2bFpa+Z0bNTb3/pcTkPui1uT55WoyHhxmlK/6qcV/bzUARePeXJo26mGtVAweDZyzYl1ef3kqqZXVKy8rixjti0UMbci47w1J5YaJ/9Q6s7cqoxfpwntSYvscTlQDiSZ6dUQqyNBQ6uj2fkHCyRX5VCZWtWY8e+lvnPXsA+63zyKtSh1NVYnwLpgN+0nyRgiEgqbvn3roKOuuRzmr0JddznmZaIPNa66hN7kOcefgZn8OWt8L8Y7D/Z6uZMB2TMR6dUQOw6EJDZD3E2NU5P9LUDxvpDsZw+JpcUnF6nutRn5ScjIzYskahG9ETnUJ796hLVXlpn6swWCFIzcE5I/EVD45CJmXwLjmy8Sgq1blbGc/sJhivdA5uz/i9PHtoxtu2237bbdttt2227bbbttt+32H7Jp8T16yH/zv0F7yIedfsHgzO+Wmfi+R/dCi+ZbhCTRmdaS5u0q1mJTUW2IMZ7hSbHZgAW+8roy/gtLRPZWBKK+x5LInhYCU5CU94kskR/0RjTOpVuyj954RHOHGIgZgWb11WWaeyJyxww6sxLNc2uK9rRi452SbVC+fG/tPfNCA1Mm/aJ4nlgdqL1BSDHJmRJGKJEIpy6UFreqqY86cFhS7fU91pD2VN1nwT+IfKeTmZOM0i5F5bIyKoDeRMTe1x3iTEyF6/3KFfC926hfYJFriawCJKXrp2HmXUIv0wb0RxXNp86jDahdbOBWJMra3Gmx8ocl7KZEOpZ+uyzytXUprF15TZnUesTSG4Qwk1mKaE8bTL97Qe6rI5G69ats/KxN4b6IpZddDR8UgtNA8uM96npAzLLauwJGf2BCJKn6qb9YYOWlV8OHbqP12CvJffMoLkLzOtcbJ/2Fc+Q1j7oe5+9uZ+Ml4s3ifmMrkr72qjKZpXD4t8635WdnfrcsUaZYHjegsQEkv3KEzgvjgu8Rg54jEb3KU64mmzNJIBGWyguEPDf+QfGMmPlT8WoyPY3b0PhJRef5JTEs3BSfnX7OoD1tMPOuBew4WuTlDUa/HhujvkBIKf6vXofhrw2vw8soUk1N5RKLIA4Qnf0d6UOtGQunqSne67H66jLakOiQNgz6RTEVXXuYjemB74tR4dlfdkjvE4PVzpQQfLRp4Nak6PeBd82TPg3taYPaW4TulvxvEvaqPPVqmnvm6MyGmD2Dtf0lkiuQqIasHLDJntL0Rk2m3y2mt9qAzESJ9g6F3YTNt8iYa08b9MY1xnyJ5FrsJzEj5ogjNy/SGzWoveRq+LA8l5k/WaAR+21FlqI1ZbL69hK737zI6beUSWyKcVzkaDrjZTbN0/Be8XhCFZn68wWWHjP3U3OPyUC12J1UQkRLSjTXy0Puj74x/N3IVjSfJt4HrafM09glpnWDVn/WPMl18TvJfvYQ9WfOE1kKqy+SrNwt0vcHBekgJoZ2V5+XbRlIIXuPPyD+RMDmi0uMfmTxPK+t6nNLw/679IYyM+9aGHpZZD93CO/R+/HTBlZnaxxElkgrvUddT2/UojNuMPUXC0PJ2/rLS+ROBMPP0nu80NySlYBubwm+u0Vj62cVG5daGJeWyZyJ6OcVp+NnO3p3SOgoUl8+jPXo/TTnLBLVkOacSfCsecKEkJD6I4rkmo5lZYAWeVhqVVO9WMwIJ9+7MJQgBa6iPRNHpF1FfY8JWjx9rK5Er/PHQymYdsVgc+CjMwAaRJbMd6EtIIjQFWKU6cm4KfyN+JckqrIODEwpu2OKXlExck+fxm6X1pxBalV8PbwcjP8w5PgflZj5F5/aXpvmnMH0exaGPjvLry+z6/e2vt54qcwNo3f1aexxhga9/YLB6m5XyIJvLePUBAgTWZqNq0qkzwipaenP5zE7Iq+rxP2/NStURCOA1VeX8TMi5zn5BxIZX3vPPKllg7X/WsKpi2xr5J6I2oUOyUpEa86k8tqr4M9vQwVQ22vj1iJaNx2k+AnJnhqByAWdVkTm84dpPk2MobNnAvyUgdUXqW/9N8usv1xIf90bD5wDKPBxv3mUzhMO4n7jKDPfEGlTaiNi5ObFoSlucj3CCCFz6yGMmw4SugqnJb46g77tZWPZbE9TOCZyPO/R+6k9p8ToJ77JA4ifU7Yin7Xy/BJBWnxVgqRkVdKr4bBv5D8t/nn1PeZQFr3y2jJmXw+9aTZfJHP0if9aYuxO8W8Z+N0kN0Xh0NglMsXsmYDOmIkdgwxyJyVDH5katybP0e5EGIEmUYt9ZzZCkl89MrxnlUsczL4mfzykVzDIn/Bxv3GUxJMP4mUMVCRAkoFnVvjaMoanSa5H2F1NkFDkbjmE/8jrY7+okMhWBHWhABYeFOns+stKcVZBIALNp85LgXtKYfa1AAnyBolKSHOnRXtSvNkiSw0VNunVkI3LLbKnNGZPY/pCne1OKAr3h6xda2CEFqm1ELsl0BQnzigGKZErJtcF0oLSdEeE/Df1ZwtUnyvkwV5RsjJ+Tg2zjbkTMre4TRnXqXXxlWtPG8PMcC2msblVPQSQgNAhM6dDGjtN+oF8v/PIK+lfuIPUhmT6vNOn4J9k7tO2bHG7v36AftZkwFirPrfE2NFN8AI6MyncbxwlBMzLLqI/nibxtSPEQELyf3cfZ5B96KDZTbmWyFLc99HrcZZN0kuQ/ewRqq8vs34QkmdsrI4Yti79dpnm68r0RjXhw+eZ+eeA+/7qAIUfQ22fSesVZcKkZBDzx31OvK2E2RX6YfZ0RGOP+Cm1X1zCrYu/mNMUyZvT1NT3WCy9s8TOv/fY2M3P3bSW/x7q3/zv0B6yjA1g7o8WqFzqMP2eBcZ+FAhW9YQcGOxORPF+WYDdakT2lEeiIlKw3uMP0L3xANlTIaYn5ouJWkj3xgNYbc2Oty1Q+JJIqSITiveGFO+LKN4XMH0oJHNGiynVPQGZkwZz71jAiollk+9bYMd3RXaRWlLkH5A06fidAXveuMieNy4ycrekfSePQOZUbJp1PKJwf0h6OSK1qpl7x8JQsjLxbz7plZDkqqT48/HGQpsixZt+j0ywA4fc9FnN1J8tkNwMmTzqU7xXZEV7XyfSlbl3yEYg8T1JoxZ/EpDYjIT8UpeJKnsmHBrIAeQfDOnnFaav2fnWBayOJnfLISJTMXZHhFuTVPDMnywMDzogC6gfu0iDkMkyZyM2X1xi7o8WcJqa7oggHyf+ckGc449tSW8S1a1/Fz++yMT3+1z0iiOMfmSR0b9eZOovZCMw9SGRLLlNcVse3J9BS39BdOwDucNAhpOoRucddGrPKZE9Lfd388VyePEevX/4HIqfEBO66nNLJDe2PtvaK8uYvhygDV+kQSApZ6sn5nRGKLrs8Q/Kc3Ureiiz02Z8n5oRdkeTWQrwsyadcZN+0SC1ev5Ijgw5fA6kbsn1APu73z9Pulj8wp3YHcieitj1+wu0bjrI7B8vDKUa/Zyicqkz3FCoSOQ7blX09rmTEYlNkefYHU3+mBywDQ9QQlZymhqrJ3KgxLpBejUiuR7JwtWH7oQcC0Y+dwezf7zAvt84zOgdmgt+e5Hi/QG9osn4nQHpZZ/UqhglZk9qJm+XZzDx/YDpdy+QPanJnYiY+dMFLvjtRUbviqV1J0X+4MRSs8xSSOa0/Lv7a1fQeMaWNCz97buwejD2Q0HITx71MDwx2c0eh8xKyNhdW8/09FvKLP1WeSg12br50i83XlIiuaoZuXkRp6GZ+KuF8/pu9clXiUFmjHrO3HqIkZ8EQ0LZ5otL5D916DxJWP7Th6SPFWSz0Xv8AZy/u538p+Q1eo8/QP7Th4bSyEEbSCEHBx0QmWz3xgOkvygbNoBEbevzzbxrgd4NBwhSQnADCFIG6S8exmnKeEx96TCZWw9ReUEJP2OSu+XQUIboxLLN8Q8s0hs16T9uP50nHKS+R6iF7jeOkvzu+Zr0ICWylNl3LtArGiQ3Ina8bYEdb4u17nmF9+j9NHZZjH50kfakGR8gpN6hX1SkVmSzGbpKTBDjFroi3wldWP2NMrkTYpAYOkqkli1N9nSE1dakViO8rMxLVg96BYPeiDGso/HTcliJHDDiOTBwpQaiVzTwU4r0shaZZ0fHB0M/pjWKBCdwRcqWOxVQ2+cSJGDkHp/eiCx36SVNa9Zkz+8u0pqRzdDo3T6Np88TJOTwPJjbeyOK7q8fEFRwH+oXOlhdjQrls2XOBsy+c4GRe3ySq3J9O9+6wOTRkJG7Y9LeUsjcdyPm/tFn9J6AHW9bYPwDi4zeHTB5tE9qNSJ7VmSsditi6rCMybnvybjLPQjZMxHTCx7Zzx5i/IdtOhMGmTMh+WPyDHJ/eyeGJ3NGZ8Jk+fVykDV9jdMWOdT6y0oiMfQ03RGT3oiiV5DJOnsqJEipoaTTjwNw7UmLzReW6EwYNJ6+NaYHY2n6PQtMvncBpxlhelGMSg+JTEXyK0fYeGmJ5g7B2Dd2bS0MzTmb2nNKdCYsDF/TfvRWjQTI4c9tSJ/p5wz8jMgU2xMm3RFzKCFNViKxHPj1eH1pbMkIw8QWmXP3f1kkSBrUnl0itRrgZaWfhLZs2OWaDfy0Gkpg/bSiO2pIzVFO0S8ovLSBlzZozZg4LU1rxqT3+AMS0JmxcWtS/9ueNEmvhrQn5P4B+Cnoxiawm5fbbL6oRHI9wozn+cCV/lt7donWjD2kpXppsfcwu2ICe+JtcgiMLDnUn/2dMv28Gu5beiOKMKGIbEVnwsLPKBI1TW2viZ9WhLZgknt5kx1vX8CLn2V3zMBpRiTXhFaZPis1fo2dMV21r4dy70HzsrI3cWOJaWJAWewLEdJuy9xjtWVjPiCKOS1NP2sQJBStGZNENcStyrqWqIqZ5rk1tIOgkxMHJp2GHsq1tSlB8+6ofH7nn0TCG6QsqRv+4mHcqk9yU9Y2df0VFD+xSOTahD++F3ezv/U+d9+Hddv30eWrh9+rPyrGH55TZjGUhPciLnrR7Yz/cOu+OA3NzPdknhms8VZHxljuQZg4Kv3golccweqIlHPirxZwarKWLT/cIrGh2PH2hbiWKa4Nf+8CiaoYLOc+c4js5w6RWgvJfeYQk+9b4II3LuLlLMY++t+XV/8/tm0Z23bbbtttu2237bbdttt2227b7T9k25axbbXGXjBeWKI9F/HAp6/BMPoEvkki5dFbStM84OOfCuCfxR8mSLkESU3lT0pElkZpMDsKvbfDRmigN110OsDO9OCGi1hZbMHbb6O9E7rXhLinHfozIYQKuwL+WECjYuFPeLT/VGQ0QUpTe2cJe28T7xElwnSA0TMwe4qNA2A89RpS6T4sGnSmIsyZDn7DhUChtJhb2XWFtmD9/QchEJJPc7dNmNA4FzU4taNMZ/U0/AO0D3Tpjoes3fgwFNC5WyRMtUs1frmENxbirFuEKc3SrxyACCYWTZo7FVzT4NRvXwF/chvLv6hwd2qIg6QqEmlCmNSklg3ae3xUz0QnAsyGxUimRHdc0qaqHVG/FMwOBPmQ7lti47ZRTWLdoHNRH+eMIwanhQCcCLNiEeYCKlceRDsR6eMW7d0Blb86gApCVHMr8la7wGYCgR6s/06ZxIbGeuY8RogU2D12P+vXKPJnxVR0uaxIjyi6ry3T2h2x96uSKt68WpPcXef0Ugb9uANYdZNgwsNeFUnVBb+9yH03X4/p9og2HRLrJt3dHq05oQj1HjkP432im64HHVH4gUXlKhP+Sahmdluzvj9icu8GzX+cpJ5X8G2hKPl7I3L3W6wdNNFpj/7vl9n5BwtUr9B0Kia9fT0S9yWEYFPQqACshoXZV/TmfOxNi9plIYVPwuqLr4aP3Eb1qpD27ggVKhKTTTbqCYxnX4O99gD8vdy7M6+/kkxO0ZsOqf76lfSbIeoXD6KdEKNr4NQMgpSmcWWAe8ahuTfORmUCEidd8YPJabxpH2VqaFtoJ0J5BsU7DOoXSao/sW7i5zT9OR8vLzIibUGQCemnQvganPq9y0ild1O4D1o7FHlg6RdMjAC8qQhrQ/q4EYjnxHpRY1Vh84CGJ1yPakUYnmJt/iBGT+FuGnQu9GjWLMKRAPoGqb1lutMh3kngW+Kzk1NnidUgYrZ7IMTsGISZkMaFNtFMj85Ume5OH2yNd0LDP8DSO/ZhFKW/Rj0D/mFr7qk+LKS9U2G2NWEqorWjTBjPLUEhIBq/Ct5/G+1r+6x3LIzLy7R3ByTPWPTGI7Ai+r9bxmrDyVuvRN+Xialg4jNTvUxhXtzk5EwJw1P0/9M8498H61lrnH0Q7HIJq6OYePVuTCPi+L3TqL4YGoYpocI5dUM8L/a06D9uP8rt050o42c1wS/PE+UCUg84dKdCUCFm18D/8mUEd5g4O8s0LvXxMmXql4UkVky0Cb0Rk+rvlumPiHQ3TGpW95fQtsaeaeOtp0idNmnvCjC6BsEry6y7p+Dd5xiyFjUbD/MZ+Rh0ZjXRf6rT3FWmOxERZiKcDaheYaBCTfX9B3HXoH55RPqkyebbS/jZkNA1qe810ZamPWuCFuly5Epxd78o83tv1MQryrUZgUFkCVVrYDKZOamoPCxk8l9h80pFkAuxqyZhQpNclfvnFyLsuoE3GoCCxIpFb9bHqloEWelL/aLB7K+c5uQRkTuafUVvVx/VsNE5H+s2m+qlmvRZg+WyeOdoJb/n1OH+9x+UNaUY0h0XLyizp4hczf0fvw5VsWMPMwOzD86FDfQP8pIRsSVLtPLLmubjSviFEBwf1bRY+UXJMhgebF5Zwh8JUL4B2kQFCnO+RJjQMNrHOJsgSmh0QaLO5opDMBKgukA+xCqXCOb66L6JVbUJn34d2jMwWhGdGYNeDCysPO1qwn0QpiNSZ8RcsDtmUJnUpM8oOjNCqatfrCncA81div5kQPKsRevNZbyCJix6OA2b1qxIyosI8U5b4usSJUNWSwfJPgjdKej/VpnObERi1SB3IqJ2kRhdVi+ziBIR9X0l7JYQyypXKxKrsDoPRLFW0QBtaAxfwR1yPzfnAzzTwBsJ6cwahK7Gbiq0qUEbtHZGaEfT3CU0r8iRuT7xz4r733cQFWqcmkFjr0arCCNQGL7m2J/NY/SRvla3iOyIzhwkVg28gkZpTf0ijU765O+0qV/bx1p3iKxITCJDiJwItMLqGPjZiN6Y9IvawRBjwyZ7QtG4UOALflbT2GsAAhfoj5q0ZyNUBBsf3k9iSUxIvamA5HGH3hQklg0iV2M3FJ0Zed/6XlMMU12N4Sm8fBQbfoqMzgjEv6w3ZtB8R4nQjYgyIe1VMWMNE5oo59OZsXAqsdfcRERq2aBxYUTtHSUiWwAQZge6E4ZIr5UmzES0/qhEkAvpThk4dUVlBviu+MZs7hEVgdlTRJYiSEekT8cy8stk0yzPTROmdEyNg+xp8fgikr/tzgV0x228YoS7KUCQtY/sx2iauFXxSvKLIUFc1iBEQOhnDPgeVMoeTiGCvE9j2aVz5eXw9tvoTmxtbzsTzlAto2//EcYVlxD94MeYF11ICBgPuwyCCCyD6Id34xUd/IdfDv96G70LRNDWGzfgHnk9+wcPyH54l4nzvBL9vKI9p6n+1QHMfI+o4qAtmdeqF5fpj4fUropw1gxUJNe08cEDuGtyPZtXioF5/Z0l7LaitTvi9JvLeJd3ME4kCdIR9fcdxOyI5PLE2yRLO70Ycv/7DlL4scH/h73/DrOrvM7+8c9up5fpozISIAQGBKJIU86JHRew6aFjjDEYDMY2buA4sZM37X3jOH6TGPcWG2Mb02vANCPsuEyTqEZgQCCQRiNNn9PLbr8/1t77nCPJNjj5Jr/XmXVdujRz5px99n6e9bS17nXfpT4hwqgfPQB/c8/v3szvxxS3VU/otX7m/wV73Yed3hGbxEMjKJdm6PjTJyieN4hRdsivShJ1IDofwr7teXYBqW0qq+9qsIWZJ2zAeOQxofMdCYkAnGVS6zBI3CqQEvuEvoC2uv1RnfQNw/vcw+J7MrR9St5fO7kfV1MoLdPo/FQrdGP+sgxGSSV5yxOAKOeWewxSNz0d4OnnL8vQcd0I5bMHKfWoRBaVFqXz3EVD1F9NkZywqP/b00wAXQ+E6Pp5A4I1l13BHmDVP/+KlDLhPee+qcQ2PAjNt37OHqD7cTBmVBK7LVxFNgm1NkUYgW4dJnfRkGCwV+ikXjVZPDhE32eHKZ81iB2C/IEa3U/WmT8sxLIvDlM5cwBXUdDqJvkFaV+/TmrhEqkBcnWdzn8dEQX6z8lnzJhKfLJO6SdP8Yp3rz4Lkx2mhXLXt/D9m1lzP+TdBQCW/9ylc6SVsar9eyO0e/2w8jqBoal1k9BDjwX+AHDoZa0MU7/Ncu8eYsUN0g+ReYf2h0aI7+knf0APy7eWidg2k0DPYw5qTqPzO8MsQ5ihYnfKc/Q96oDroI2pGA83ni130RCK45K6sfEcPgyp91+f4lVg2S9AmdGIzdnUUkm6csIGNx1JB5+JTap0v2xRfUWj/XvCFLPrz4UiXWpCHMyYQnU2hFqHxISKq4Kjh4nNCHPT3BUZjK06lW6VxC4bxfGoYpcJ7WZ8t0P6hhEZC38t7Td7ZQYrphB+TkW7Xihplz+q0PlLoV3uflJO1St+YQdMZOWzBin3qFKDoUD79Zu9+hPx79I5gwEtcPz2/VBzn9rP7ozL8l8olObdgD660NtH8rNSQ5OYtIn/RDY4idvGWbw4Q9ufP0Hu3UOs+ox8z8xbZAxFnohx4G3jTH4yS/gJm4mm71r+U+gcbh1Xi+/JUE8q9HxtM3l3gQmg7y+eJ/QnB7YwIYJAJdu+7/X3F/f1rfS+L1E8b5D4SS+z+rQuIvc1+cVlGQ65bl9Wwd9m5bMHUesqkfvkHqSerfUaEe8ee37DNfyaN5/NDqQPwj9q1BHVTu0ncp9QwvuW3A7JeZnuO55x4Zl0MLfOvU/Ykdp+MMb0h7L0fG3Yo6hX6f6G4O9RVNqvH2bmgxnaXjIp9BnEZmwW1+jEtzuEcjbVTo30DVJDEx9xCD04RuncQaptKnpV4I92SEEzHdq2QS3t0ayv0r0aC4XIvNTlRBbBiriYUQ07IrCV9IuaHPIXIXqPfM/sXavonBdB1FpKpfNXOoU+lVA+hF51WP5LMGMuHc9ZlLulBqLSpRHOOSz//BhTH82ybNwlcm9jntTqLvZzIdq/J3VRxosCGYqMJCj3uBgll/CEHE5WPugS7pNaiMRtW6id0k+lS+QHovcIRb3i6Og1l/CihfHwFhYvzhDOO0TvlnWpdnI/tTaD1E1CRZ/+GWhVM6DN9W3u8gzREZ3YXWPefDbKrlNXsQuI77FI/NKmmtaIT5kUVurEp206t9qYSZ3YjMB6I/MadgiiU9DxrIoVdWm/fiTwz9idAsGM3iNjZ9Vnhpl7X4a2FwFXk/6rOxgloQdu8c0rM7Rtq1NcEaK8TEUvSV1oablG5zPgqjahgsP84QaxKZkDQwWBH7ovS3uu/tvnKF+zhrYXhI66uFIluVPo/fd8PEtip4qjyXykWC7x7Q6pVxQKKzVWPWRR7lFxFZdau9RaLl6cobC6IUEx9ZEsid1SD1daruIqiCCq5VJapuPoQo8fezFM75Y6i2sMqc/yYJnxPQ6hoi3wP9cVv5gLYcUUOWjlVGKTLlZMJTInQpChvENppUrPuNQ+tr3kUku7hPMO+VWiUqyXNTqfNTHjKpUulfQvXUrLVWJTNsU+DfJS+5J6WeB8dsgltdOiuFyn4ykVM6lgFFwURyQ0XEXxRHUVIvMG7dfL+lvp0EjuUKi1QTKvCpy9W8UoSi2esLW5lJapLPviKNMfymJHNUI5l+i8jVpU2APEJ0BJySE3VLAFirYI1XaX/IVDtD0vsNZ6UvFgnwpmUuqL6ymVvk11pgbChBZdYtMaesUh/LRDaZlCeNFhxT9768IHvBoVQ0OvOgFcNVRwWfCKanp/rNP1c5n/aqf0U/uRrH1+/ScI3NhnrgRQqgJds194CYbWy4uagvOkz+RmY/xS4HCppwxmEeZU34pvPQR+shmjAO23CWtiKK/S8d1xSucMYocUjLJLuQsSu02qHRqOrlNrk/bo+qbM3bNXZuj65miLLMLCJRlS22V+bL87QuJWoZg2SsKe59dAF94pzKTtvRm6vjVC7NxB8gdoGPn/QKbl94Gl/aEedpZsyZZsyZZsyZZsyZZsyZbsD8j+gGFsr5ugIPKgRJssT7MicdsY4R9tRq+2FqYDhPNOi94KiKZF+P7NhO/fjBVTKfaFWgrRVEsgPVpddHaqpw8ExYfBdQs2pXPkuuEHJAIQKrQeLytnDtBx3UgLm5K+6bHg9BwqyCk9PiURJTMmBex+Vqd2cj+FC4ZwNIXur7dGX/0COKBFk6X+JtH5MB5pjcjVTm1o9zSLa6qmS8d3R6h0atTT0nipVyws757tkBQ6dn1rhNBDWzA8UatqmxQsJnc4FFYbQbtbYenO8I82Y3haKn476TWX+JRFbNomf+EQK/9xmNqp/dghldSNo5R7Q1ROODK4N/ePjgEgsuiw8N5MkIX5TWYMb8V8x8b9/q3Di4BH7h0n9NAWiucPYb1twz7t9FrMj2aDRMwqZw6QO1Cn65sjqL94MtAXCf90K53fGQlEQZsZtKyoSuS+cYyHGxml6ukDpG8YDfQyfAv8w9PZCf1crhu9e5xQ0RHNl0ceC1LkANFZm1paQ2sqZl/5uWEcA6rtCmZUIsXhea+wM++S3Cm6TVZYoXZqv2hdeNHwwiqNekKKZxOTQqbhaFLI6vP9g/R3ZE4ihvU/9nzxF1506qbRIFprRRSJ1iMRrK5vjkgWzov++dovtVP6id8xJvoppdbCVL/NADqedQnlbaI/lsyqXoTETofSyVJ0rNWlQNqMi3+2fX8k6Etfx8bX2fFtxT8NY/y89TW3abbyM26xaZNwft972zur85usOdrXfF3f9kdAAA2ffj0Wu3Os5Trx28cC7a/Xas2kCv5nm4k+9vc7yPgPrlFwqKWlMac+kiVcEMHAufdlAlKIyLzAZaqnDxBZtGm/fgTrbRuIzrkUlxvCDrlGZ9kXJbpf7m3EzfSKy+Jag/y7hlAtyYRU21WqnSr1lNJCPFHqFahe2zaT2LT0o2pCqVel2qbKCqXgRXWlGLqW1qicOYBWl3FT7lEpdwlcrtqhEs4Js5RWEwE+OwS5gwyckHyfHYZyjzy/VnUpLtcCMpT274149+rpaJSFAdFMKNghBcUSgcvicq9oe/w5YneNtWiJ+f5dOneQcMGh7Qcj6GUnmG/avj/SotFU7dSCdckouqIV8ui+c6NiN/SUtGqjQBrAMVQqHRqhokM9qRIuuGgVm3KvQaVTpZZSidw7TmJSWBqTk1agkzZ/aYbieYMBKcH+zO8zXwsv7Gm4zV2eofDOIfLvGkKrQnFlCDsC8d0O4ZxD3dO7KfeoVNtVrKiKXnIp96pEFhwq3Sqd3xkJ2rP+pnWE52Xtt6JC8lJaplI7pR+j6KKXXDqet1BNIX8o9apeIbxLfrWOFZFC/VDeZfJPsxRXKiR3uJgnbGD6w6JpF799jGq7ItDsiouZUIO5yV9Lkzscqh26CNk6Qkik2lIEH717HMUWMVpXB0eTrItegeiUQLsic26gR1ZPCSxesiwupV6PcKAqGUmt5tLxnEmhT6fco1JPK5R7xJ+lc0XbyNEVwgVb2OYcZI3xshvRGYfovINmujiG3JeriTaVLwxe6dCwohCdt1AtF9V2MSqOkN1U5P5A9kY+0UC9zSMFSMi6ZXmkD0bFJTrjUu1UqXRpHhNaw19cVTJziUk7eL9qgl5yKfapFFaFiO8SUibTY5Ar9WqEFx0qXY2JPj7teKQK8rtqyr3U2qTPoXU/tj9B6MCHS02kKtu2A6BsWIerqbiagmI2/u4YjXtwPJ9wVGWf1/y1R3FkL5e/cIhaWg3W26hHmOR4bRtecOn65kjAchuQzhQc5t6XYfpDHrFIvUG2kbtoiFBByGHitzdIb2JTdQoXDAXkX/Hbx4SY5VXzN7bB77Q/YIICxXVfG3FcPp8nnU5z6NX/gKFFCOVdDz8pdIO1DohOy0Cr7t7JC3dcy8HvvoYOZQV6zaWeUKm1KaS3W0wfJ5MIrifUVXQxSja1lMZk2y4mvnYtq99/DfrBK0ltF4rEwkqdSq+LWhNmnlAOErttSr0qrqrQ8zWha26/XhSUQwUR6YrOuHR+e4SJvxC6TzskGGIrJqq8ig0onhCeKWq+IGrKdtSjQFVl8zV5Uh/PPvAFjjj544T7VglVcBnMV3fy3L1yzysXllPuUqm3KcR2uxT7JAUeXhA2EyuqUMxNsP17n2f1+68hFe8jMu+SP1Ch9zGT/CqdSq/QsOYOFnx5fJcrYmKGIirCQGReGMZECAwiCy65g1SckAj+2WEZLNUuuY/SCo/mdqdDaYWImrmaPJsdgeQOl+LCBL/+t2s56u0fw1i1mlKfQsdzNvWESvv1Am+Y/GOVtmcVKj0eVn9kB1sf/AJvOPtq7I19RGYUEpNOcIDd87Esrg7p7UIpXT9xI7NHhVjxz8LmlnqhwOzGFNVOUWuPLMpG3k/3hooNVq3q6QOUlmlYL+3gV5u+yCHnXk28s4/YjMPCGyTVXp6e4MXbr2XdSR8n0d5HPSmTol4VocLdGY3US3iCtibVDj3YJNkhwZ8u/xdRQK8nZRGzwwo8u4NnHv4Ch5x7NQfcsZPZKzPoFenTelLBfHUnzzz8BQAOvOwaIsv66HzOotwtE7gZFyYpf9Ngh4UGe+7yDHZEwYrQEFqrOuQP1AjPS/8ZBah2QfplEQgsLldF3LEqjIfVThUzDl3PWORX6xhFl2Jugufvupa151+D07+SNX82wrZrh+h8UiF3qNSphHIuWh0WD4X0i57om+enTqgxDtp+MELhgiGMYkMEs9inYkXACbsc8NcjzHwgg/nKTp594Ausfv819M0tx7rjQcbZxOGnXk06voK5IzWSr4hAXXgBInMOsSmTSo/BdHiSV677PAMcT8qDHsy8eQVP/fRL9J30biYe/CFrL7iGWFdfIKS7+xNZFFs2AruvyWJu38kLd17L+rd9jJ6f7BKI3w9GKJ4/hKsI/CE+LRC++csyhAoNOl7Ho7KtndJPrU0LqKcr3Tq1NpWerwiDWn61Ts9XhwPK6amPCnVsZFH8tJliutkWLskQLjhU2mVzN/WRLMkJG9V0mTtSJ/2S0D+nfzhK4YIhrLAoq0cWHWJ3+rClseCZQAJHZlQhnHcCimuf6n36LSt5+icNrN5hf3I1keV9QfAnOWFTbVcprZC5RnGE9tYxILlLYDrlXoXorCs01Ct1ap2w6v8Ms+fjwnzY/mKdqQ0CrV14bwYzLvesehuuelJqyLp+ZVNNyyYuOuNQ6VGFOXBnDcV0cA2Vwqow9aRCbNqh3C21CEZZmJfsqFwrNiVznmwwZUPpU3BH5gWGU+kSod9QQTbURl42VKopmy0z6W/CHGbXK3RsFRhPeMElNmuRO8Cg52vDzL4/Q2zGodKhEpuzKfTp9HxFXq90KyhP7+TX/3Yta991DanoSnKHQOevXPIHqoQKUGsT1kQzKQxUq/5+OKAKX3iDQSjvUlylsPrvhpm9MkO1Q0G1ZQ1ydFlvZj6Qodau0PmcRS0pEGfFERHW6IyID+9J7OaV6z7PUW//OMbqVSi21Oa5mrBB2SEF1RKGMBFpdan0ypodm3Yp98gaEpmXzbxPh26FFQoHKfSOC/X01EeyqJZQNZe7VHq+Js/jqgr1lDCN+vTZ0WmX6IL4eq1T6PMVR8Rbwzk5SDuaIgx/U0KDXp6Z4IU7Zd7W16wiMWmTP0AXyN2MHF6r7SrJXRblTk028wq4ukAcFVv8N7HHorhMD5jJZj6YwdGlzxVX5lfFlTnb0RXiUw6LB6u0v2BTWKUR3+NQSymE8y6VThXVlIBTZNGhsFpDq8jBoLxcatDan3NQbXmvURJfCuWkfq+eFnbVhUM0Yde0RDDUDisYJTm8Vzs8lk1kH6Jasueodoi4puK4xKcdaimVoicHkNphM7teIzItgaTIghMEw/SKi+GtWa4qQdzonEP+IJXIrIiydm4VOuypj2SFRTEi8hd2RKiPK72uiHd6B8q5K4S+2w6B84LsdQ4592o69JVYEWGQcwzZb9RTCrEZoZS2IxKELnvi291fl3Wk7s0TekV83YoK/bSryrX0qktujcAAXVWh56vD5N81hBlTcEIiRD+3TsN+YYJtN3+eQ867mvCqVbRts5g/TEd9agfPPPQFDnzvNRz2cxXr5VcACWwlts6QO7aHxG1jOG88hnpbCBSoJ1XaH5sFTcV+9gWh+3/wx4yziUOPvYAXnriZnqGTmR59ACB4beVHr+bwL+9k8pNykO7++ghTH81SaxdBV1eBxG6L3IEGlV6p49Mrsv7rZa/GNgrpl0Rct3TOIHrZYXGtQe+XBU6MA7EZGzOmUukWKKBjyByx46+z6GWZG6udMn9aVpXHb/lf5HI5UqnUa9neB/v7Vf/yf1Cjkdf0Gd+cSpWdn/ir1/V9/x22BGNbsiVbsiVbsiVbsiVbsiX7n2xLNTsNq3e4hGehuAqsg6uor0aIr1ug7aY2pgbBSZk4UxW4A0prTTpegumNKmodzIRDYY2CkXMpr7Yx5jXKKMwf5eKkXbRIFWezJ9YUdtFqCotvcFh8g4oTEVYexVRI/1pjcUOd8m6D+nKT1K9CTH0kS+7oOrlDMtSX1amUJc9Y7VYo3noUtVKNykqd8LRGrdMGV6HWCaGcQq3Hpu0ZnWonWAmX0IJCpdeLznTahOaF275YfBUegPLxZUoxh3BPmUpdpxJz4F7QD8szU11JvdsiNKUz80cWPb/QmX6LyarLtvDi944j3VZm2Z5Jtn8P6h02+QMtyjkNO2mTO8ggd5gwz+llFTsqjCyzbzIx9hi0veBSPBDsqEOlD1zdIbpDWEzsnSrVXofYpEqtDaorbLSiihN2qLUpOGEHraIwPShQACsqzEk4oFoK1U6FihfVi/74GZJv7KbUF2N6g0psUmHbD45l7XvGOfgeET2M7ZGsgx8pzh/k0r6gUB4oU5gP09YhmY9Kr0vnsdNMzqZw3zqIq7mkn4OX/mUIO20RXoyycLiLqzvE0Fhc76CYCnpJRS8oLB7mMnNMxmMPM4lv0ynb0rd2VIRq596XodLr4OgqxYj4T+mEMoWkg5owURRP+Go6zNprRth2w7E4RQMtZWFXABfCqRr16RhuxKb0+SFhbgrbEHJQF3WqBvAwRN4yxwsn9WMkyjiugjMfFraZNTV4WMaIowMKzK6T4TX/RhO3rqGUNdyUSWgihGopTPxFllAeSn0u4VmF3BEWGA7JZ0PUOl1qHcKsBqC01VnUIyiWgl6F2nFFqq/EWTzSAdVGK2gsrtUpHuDg6i61VyU9XlpfJX6AKPcqDuQOAaOgUDzIRu+s4jgq6s4IuUPA7KtRqWoYixp6QcHoX2BhT5KFIzIoa0p0p4vsuOQo9HGV0oE2uNB3yDQvfnkQknXqUeABiTI5kYa4cO5Ql8oBCm7IZu4gE013qJZ16ttDTP2xipasYr0iIkQz/7IG46g2ds20UX91F/xUBIUBiodYmIdWKa3KYKZtQrMukTmFF780SOeaWeKnikbXdMal/LYMrgHlu46g+oJExNWDi1SeTOIenaXW5aBWVQqrslS7XKyUQ6U7S3FjBW2HzuznMrh9VfSXDGrLTAr/MiRZZdel9OAaJidteEc/sY4cld0J1PY6c+sy2FGXuS8MYawoUVuM0NZbwBzpoN7mYvbYJDvybF8rrEnl5SpWwkFpr6DYoj47c+0Qye0quFDMlHGnI7h/sgFFr6NvyFDvtJkZGCS9Okf+ZYgekGd2IQqnbgRLQS0rxNZkyVV3tjDZ6TUZr33/MMzEp7PsOh5czUYxFaq9gKMQWlSwEg65w1RCiwqu6lLtAbWmoZehusxmx99mMRMyL9nhEOFFVzJMcYXorMPuNztEpnQc3SXsEWlMb1AJz0sGoHCQQJWtqEpuTRQr7pLYKZmbertLeZmHD1FczKREmhXHRasoQWTbTImoqZlQmL/vUKyfKJR1ydg7BpRWglb1mLzikrmywyKWaCaFQa7Uq6IcXKS0mCC06LJwOGhPadgR2P6PGRQLcocqRPcoFFcLgcL0VaL9FF6EoqdNUjysjh2XiPyeNzkYnvinvbpKpc8gsltHrcPLnxNx7fxaEa0sHihEJS9+cYj4hEJ1XQVNc3BfjeFEXBFxPqxGeEeYyfNMUOqwO0LkoAKl+Si1DgOz3cV9SsaGUbTJHSIZW8WWTNLkJ4VlTS8KAqHa7RLfJRFnM6YwM+CQ3KZhxRQmB206f2mAKlDrF788yCEfGWPmAxkqf5Ol1mVzyEfGeOmfh0i+LGKHtQ6XtuddrBi88N0NxF4Q0cdql0JppUZ4QbIUtQ65h3AO8msdKnkFxRHEweyxCqkXCSDa8+ugu6awZ0hDcVzq7TaVXg2jIMxnE29TCC2C4ggSoNLr4uqyVqsWzGVdlKpDYU2Gtl9DaQVYCQcnbaGUNFCh/SkpzJ8/Eqy4ZOJ2vd1Fz0vWy0o5KDUFxXXAUbCTNrFXdcoHmih1FSOniraeI7C+6Q0CtxQ4G9Taod7moFgKZlJDrUNyl0WlUyd/oErlqAqxJ6NUljkCi0w6uBGb0B5Dyh9UcFZVcBZC6HmVwhphKDPTNlZMJb/OQQmZxHeFqacUcoeqGHnJrtR6bJIv6pRWyfe7hsNi1EYrQLlP2qq8TEP94wx2wkYrqUT3KJSXu7LmaYDmoloaZtKl+A9CbIQqmdHiRhPuhcoKmFvm6QB1mcReNcgfbhOZ1LFishdx4jb6nLAg6mWFlz+XQXHBWlEj+lwEKy5MfIoD5ZWqsOIWFYySQr3NwVlfwtoRJ/fFIVQT7LhNYrvOxHqXyFQDWlk4wqK2wuLgs7azc/sq7PYaPATdT1SwXp4BGiKlICiO9NqDUEomEcuB0aeJrT8MJxFGzZVxs0cTnq6w55z1cMcmFteq8IQw7PlWWKXBExDdo/DiVwYJ9xZwHk+K5lGHi9VlUl2uouc0Fo7UQHFIr1lgYTKNvqjhGi61ZTWUiYiw6R7gMnv6MbBDZc2nxqj8vUDVFjfUSGwNM3VWDWVHlPRLkqWt9Drs+Nssq/92mJ1/lZVsriLPVssU4JbfsIH/XfYHXLPzug87qZfAXAbpbZD4qUr+QOj4i18zd3mG5b9wsEM63PgiE0DyWR3C0LPF8aBQ+8I8Zt+fofNZByui46o6xUWYBOI7IbUo6dCO78r7Z6/MYIck7d45YtD57RFm359BtUT1/NDLt7Dzf2Xp/pmBmVSITYk6d31rggQQyTkUl8Pqvxtj7vIMKJJmDY265NaIKKif/i6dM0gtpRJ9DOoJgfugSHNFfhYn0a7S9v1fMXdFhtSLLnuA8KYkvbU61Q4dxXFwNQ29YnPAHVJfccglXkr4WzIAux+D3s+NM3d5Bq2uoldsUq8I7MIomszbBpE5l/TLOnrVYfFgjY5nRPFerYFqqegVl/qCima6rP34KLs/kSU16bDqM2PMvj+Do6vEZgX3bBRcah0a7c9b1NpUIgs2xWU6dlSh85kq1e5GP6tVk1X/Z9iDzQzT2+QDPV8RGFHhnUO498gGc9W//Ir6B1ahjsdo22YRuW8E94+Oof17T4rf7OVHvUgtU+ihzayMDqBVXUIPjvHbTBhLhsm7C7yKbGymr8oSKrgkdgijjLpbYTeQfDBK76bxRl+m1aDOYu1FT1A8fwhHi5C6aZTKmQPUE3EA0jdsCT5T7dBI7HIJ3z/KnrcLSyB3tbM6pmDGox4zkUvyllF2nbYquM9QHsKawB3avzdC8bxBgd/FwHg+LNC3NoEUmjGF2C6BH/TeYjFzTIT2F0zMnRqlZSqJSYSp5kdPMP3hLHpJII3GT+NE5xzMmEa1SwRjrYjLsmtHmfpoFvsFYc3p3mTAVILaqf10PQ7pH4oPdj/pUOmKCgRBFxHGghmm8xkbrWYTuU9UwbsKNrV2BXU0QvSep4kjjGDhRUOoMl9cTu+MQz0RorjYwDlX2xXi3oGr5zEHfV6e0Q6FBBbmQdHMEzZgR0Is1sJMAOGfJSi9sIxETIFnQ0wCvTe+yCzQ/qRGdDJMx3VSi2XGHUJ5m2VfkD6bees6+MkmVn9mK+HTVga1K75a+fSHs/R8ZZjCBUMk/14YcKqdCsvG7KCeqdl8trRm5jOAHX+TZcWzNvWkSsd1W/f53Gu1wjuHSN7S6vM7/1c2UK3v/XLr+2sn9+OEpXYkceuvcT+SpffqrfI8HtTTZx1MuAvsavpspVNl2VapPzOKoG3XArhm57+OMH9ZBjskLFIg0CHFcYnNWFTbdWHkq2h0P1klf0AYVxOoVvfXBTbc/aTJwmEG3eMKdkhgbBGvhuDAvxxl5oMZ0tsdCis1FBd0b3PrKqDX5PCTeFU2bI4uY0i1pEZAtV3UumzEjLKLWZANfT2lYD3YRbjsqbgD0VmX1Kui3K6aMkeYccH+O4ZKZB5wXSo9Cu33xrANOQit+ZS0QdtLFuZuqamIzbjUUhJ0czXo3Fpl4dAw0TmHqlcDtfpvniOl7GHmgxnCiypmjGANWbgkQ3zKJPTgZmY+ILA4veygOBYoCqEHN1M5c4BSr8KKi4TZ1A67ROZtFg5VOfRSqdvx1d+tKKQejtINFPqg8zvj5N0FdgKl5TrRPQJZwhX4sFqH6JRC2zaTUq+OE1IIFQQ+pVddlv1cQa9ZRO8eJ3HeIKotkMmFSzK0e8SmkQXZ5K7+uzF2/lWWriccSiulf/o+K2PjwL8S1i7VdltqExQbLEUh+YpAdQBWPyiQQDMuB6H08wKl9mtBwgsqTgois9LHbc9r1BPCbFXtVEi+JLT5Ai8WlkErJnTJmgnhuZBHh+zVc+QVIrMKnVtdZo7VMIoC8TKTCtEpEfq0otD+lAhuhhddzIQm9x6Te1QndYHcv2Lg6h4kveqiVxXyB2rEPcpIO0oAsa90C3St1iZw8bl1Ml9qdVhxR4hCH0SnBfJmxjVCOYFuaqYwoSlTUYyiCHPaEUCBxKuqQBAnDNS6QaVLoMsoOlYEOrc6FBd0XBXan5E6MyuuEJlTpH6314P/qTIulHl5Tq0OiZ0yXlxVoGJaRSi8l31hmO2fzRCZUkhvt3EjHntcQWHVMzXm3xAmtttAsV0SExrFPjDTLu2/Uqj0GCR2NZ5Bq0ofa+UIkTmXKt7vdUhtlzGs1QRy3vaihROKMrdO6MyNgota13A1l9SvdWFf9Oa2tid0UttUdmxZy4pFhxlNnK3eYaCvORDr5VfQKw5GWdajrm+OYAPaoQfjqBGU9YfhPP1r1GOOwO5IoAw/RfXkftru+IVcf5vDNKDWG5v65E6b3UB03ubAD4+xeHEGre5QTyikt7sBu3DhgiEKfcIMOP2hLGldfEqvQMcnnqB07iCKrXh1ilHssMLkn2Vp/7XD9FVZVjzgUO6C+FiMUMFl8Q3Q9msXRxd/KVwwJJDUKakRq53Sz6y1P17R12Z/yNTTr5ugYMmWbMmWbMmWbMmWbMmWbMn+gOy/gKDgZz/7GaeffjorVqxAURTuvvvu3/r+n/70pyiKss+/PXv2vK7vff1sbHMOobxL2/dHyB0UIneIRJHskEL+AA0rojD5IeEtr3bJZ3JrNKqdCjMfzKDXXGqn9PPK32fIXTSEE1Io92iUVqjkD1SDCE9pBUwPuOTXwKt/l2XnX2VZONKhvFIiALU2hZ1/mSV3CAFryUv/PIRqCVTHigiTUuEAeUQzpTB3hIYTEq2bWodESGfXK0wfZ2BFobxC4dX/neHVv8tSXKFRWqkwf5jO/JEKxZVqwDZiRRWKKxVK5wqf+syx8h2FA2B2fZj8gRqz6zVmjlGYPlZn15t1STe/e4jOfx1hz/uPBqC4XGPPx7M4HtNIYbVAkfSyQ3GljlES5hHbUIjfPkZsSphbFEuiSGZCwagIC4sZU6icOUBiwkGvukz8RTaIbCZuHaX3S8OESi6xKYfFQ3TMuEKpVyc2ZxPKu8weFcFsCgjUumPs+Xg2KIae+WCGF64TBpHpD2eZ+HSW5C2jTH5E+jp31nrUuhSL15PSHsovnwyuN39phsWLG0xXE5/OBj8rthQIVs4YYM/Hsy0Md/OXZpj4tHxf6qZRzBM2MHOxtF94waXnq8OYMVh27TCReYdqu/iPoytMfyjL/KUZXE2h47oRdl+TpXr6ADMfzFBLKlhRherpA9QTqkTwTJj+kHx/tUOl819HKK7UKZ81SOxh0cuJbnoGM66SvGWU8jLxw7krMljhRtvV08KyUl4uf6u2C2wilHNxwgK/i8y6zB+ukpioo5outXaFxYPD8vphBpanLVLpVJk+xmD2ygxmXIpeq51CejF3pEY9pZB6xSZ3kEppuULxvEHqadA81qT5o1QKBznszugsHqrywjf7qScVdr1ZZ36dQuFAyB3qUGtXRKxyUCV/gM72z2aY2qgxe1SYhTdoTG3UmPyzLC9+aZDp40IUV8HiYS75I01h81vRIM9I3fM0Xd8cIf6AtFlxmU4trTB7jMeAVXeZ/LMsL3x9gIm3hSiu0FhcqzQ++60Rln1hGKMokbjC2w6R/l60saIKuYuGKPXqMr5XG+QuGmL6w9mA0a36tiOxwypzl2conzVI+IHNzF2eCZiBkjePUju1n9RNoyR3SrajevoA5bMH2fm/ssxdnmHmAxkMj7GxOatTPnuQ1X8nPh6dt5l7Xyt728IlGQoXDAWMOVMfFZ9buCTDjr/JBr5fPH+Iase+6X8n5JJbI0xm01fJ+3PvHmLP1VmKK3UW1jaS8VrdFc0to3Gd/AEa85dlAiY83+ww5FfrAfucHYLJP5PrV08bIJxziCy6hBdc2l+0MOOiCVLt0Kl4LGqODhVPnM+MK0RnXHb+LymQXVxroFUami1aXQgCaimV8tmDdH99hMW1woSmlyQTX+1QaN9WpdKlEl6UQuv4bof0KzaOIZFpreYKBKtLCq6jsxaJXRZGSRiper4yjFZ3Rf8k72IUpZDd1SA245CcsLDDCoU+LyNQ8di1dsv96VW5zu5rsnRcN8LskbrHDtVgPovNOIQXXGEOnbQp96gBa+PMxUdTPmuQaqfC3HqFelph4tNZpj6SpbRSsjeTn8xS61CYP0KjsEpn9x8ZlHt09nwsy9zhOo4ma9n8Og0rrDB/mIGjw65PZXn177LMHKOTWysF/YU+g8WDQ6iWZBj9udCMCxGCo4l+zLIvDqPasl7nDjTo+O4I8UkH1ZK+77huhOQto0JEcdYgdlih0q6y52PZgJwEIHnLKJUehflLM6z6P5KNXfF/h0nstpn5oPj45CezgS5bYrcthAeLEqFPv2xhJhR6vzRMcsIi9OBmwnmX2IyDYkPHd0eE3XJOxpqriR7Q8n8ZRqtJ9ka1BXYXyrkkJm0vqyLF80ZZ7nPlzyqEci4r/mmY3i8Ni8ZJr0J4QdgAFw4Ls+KfhgNmVaPoYuRd2l90WPFPw6gmrPjnYfSqS3KnLdnVRZf0KzZqTdjOwosuHc/Z2CEIFcWHo9MuHc/XCBVc0bmxZT8Sn5RM5Ip/HkavQGRGWNrS2y1h75u0Cc8LqULnsyZmUiFckPmuc2sdHCHhMFMubdscwvNCbpB8xWX5L2tEp11COSj0SYY2MeFiFGyiszIONBM6t9aIzDV2ouFF+Tm2xyUx4RJedIM9hVZ10aoQWXBQ65JtWfYFT5fuJyaRWZfFtVoLI6aZEKKpnq8M46oKtbRkKJLbAVWyfyCEN0ZRvjNUgNX/W5jl2l+0SUwIg6hWk2ywaiGEFb0G9aRoNbVts1EcyZjqVXkugEq3R6YRUSh3q1S7BKWgeiyooXmT6oGdMq8aCsUVOosbe5m+Staewrouat0xSmtS5C4aIndYCtfQhBFNhcLp6725TPolOt9oS19UVKu5vPKZDLU2hWq7ZCDNmMKuP88y8RdZKl1CtDD5ySxG2SUy51Be7tJx3Qgvfy5DLamSP1Ajv1oXDZ0pW0giulRCeRc75DG+efNlYocwUqZecUjucEjePEr7Npmvt382g1ZzWlhg///RSqUSRx99NF/96ldf1+eef/55du/eHfzr6flNanT7t9cNY/Mpp+euyBBedEi/qKJaLvWELH7hvE3Ko+ENLyjU2xWhoV2hopcFkgOQ2OFBEmIuqe11Kj0G4QWbRa+j2l9w6P36GLuvyZLY5ZC8ZZTF92S8dKhLOO8SnbHIHWSgWjJ5Wx/N0vslEeOsdCnMXyaTsQ8rqJ42QHGFRnTOIVQQysP4LoXYtM3CoRqdW4URqbRMKH7NRVnkExMu4ZxNNSZtEFlwMGaEwtI4cSOmoTAJRKfBaBfWlegMtF8/QuGdgmdXTZf0DwVm1vb4q+xAcOehnDBfKY5MPD7tojDDyQSv2i6lcweFnvAoDb2E/Ku6zK2T35MTDvnVOrEpgYo4OtTbRGisflI/pV6dWodsSPWywBMU26WaFpw6QGp7g3oRhG7TFxkMFdxA/LMZxrbiyw8wAaTvehrnYlEy92lUAfIXDpG6cTSAIvrW99lhcu8eQjlxI5F7heFLNR0ic24gmgWyGHY0fc545DG63QW2I4vB9FVZKj2yMWh7USZ7gFqbSteMjVFyqKekDmD55+W+rfOFfcvRxZcjczZ2VEWrOiiuUALHEfaW6JxD7K4xvHmbyvFHoqUVtLMGCS+4oAjGvfInDRibUYByj7CphfICB0rcJoKNoUWX8jKFekqh4zmH6Q1h8YO8MDfZYVnwqx6LkQ/psSKy2XNCBOKM0RmZbOeO0mj/tUPuIJXFtRpGAWzv2eI7IVpX6Ppmo/0nP5ml7dcQmxXmIsVV6LhumKmPZolNO7iqS6ggPpu6aYSF9wreuR6HFf9X+qZyxgBTAxpd/66x5+oskWlwcnL9+fOPpnBwH/YLO+GOTUTnbcJRV2qNPAhb+exBOp6DSqdQdVs1lwlEkDT13R3MXZGB514FIPnoi4D0V89XhRHLF8sVWlKFxC6bkgdjizz6DPWLVwuTmbdh7fz2iNSaIQKvvlBuuUcL6ODrJ/Wz6u9bYWW1U/sprtCD9wQLacEhevc4HjqH8lmDIsr6PWHj8WE0vV+S74kgivQg0BMrKiySvpXPFhae6JQSQPxSEEDomoEJlTMGyL17CDsk8Co/IAFy6IeG2K9vWg3sHoQOFTlwdT9ew4prFPo07LAwU5WXKVhxnXqSYKPkH2IVFyqdilDbqpA/SOZ8O+RBFMMKUx/N4moSiPBZg0o9Kot/liU6JRTX5WUKRlHYBKePiXosanK48QNXriqHEjsicCafxWhmfSi4rmrCzr/MotryfDgybkIF+XzuIA3HkHnWKHjjy5DNc7VDIbnTodjnwYfqBOsFQKVXoeYxSdohBSvukt6msPAGHdVswK66v/8UnL2cnsdNSsuk3XqeMLHD0k71k/oJ5YVuduqjArl1plQc3SU+5RCdNpk/LMyqzwjzkplSSO1oMGCWzxokdpew8FlRWcvqJ26k2qkTnwReFJrZUM7FRQ61qimU4qGCsGNZcTnYhuclqOIYAh83E1IvUVypEZ2VwFpilzd/ejVJMx/I0LbNprRMY/KTWaLTrgToQhCZFXbR2JTLK3+fITapMH+4Jj4Rlo3v9HE6ekXmHFxY/ERWmEJzgCJ+qNWhtkOwYHbIpdKhsONvsyhmw+/sMKS2Q+5gzQv2KdQ+IP1lxWB3Nhps5mc+KAyX7dssFg7R0cvCWrn7E9nAb/SK7GVKqxSq789Q7VSYvipLPSUwz2qXwC2rHZqworkS2KqnNIwSFFeo2BHxjXoyLHBJ/7OdsmkPL7js/KssdkQOEnZYqM9zH8tSTwu7pqvB7oyB4sDc4Rrp7Q6LB4dwdTBDCokdQlVtR8AOq5gpMOOhIJDphBV2/lWWUA7siNSHVbolGFZcGZbXoxCbdij1St1TpVugaq4qmpuhnCdxcKBCYkLYWa241JT2/cMwUxtDhOflcFjxpqz25y0iI+MsXp1l9zVZKQnIi3+F8lBaLvdgRaUtzKQw3aom7Lk6i6vA4lrZu1gx6HrGwQ5LMETq//yAh4xj1RRqfDuqUOkKC1xwWvo7sccibgpjIchBFCC3NkL6zseY+WCG6KxDYtIm9vwsqfYEPV+VQJxy7DrsVIjYzjqoKu7mX9HzS9krJu8ViP7iwQZshWq6MV/P/8mh8G+bKXdrHPiXI55g9Qi7/jyLHRFYXi2tUOkGtxci87IfXLgkQ89jsq/qeEbq3bqerjF9XJhqmypstIbUI9VTHhRXV2TPW4b4HpP5w0NUel0PypuRvWKbQuoll+njwhi7K/y+pvB7wNi8//P5fMvr4XCYcDi8z/tPPvlkTj755Nd9bz09PbS1tb3uz/m2BGNbsiVbsiVbsiVbsiVbsiX7n2w+QcHr/QesWrWKdDod/PvsZz/7n3prxxxzDMuXL+ftb387v/zlL1/3518/QcEtm9EVY5/Xc+8eQq+6mDGVxN1yao4sOHTfMkLp3EGW/4tEHO23HocVFaHMucszUnz2yGNU3znEwhsMYtf+Krjmrk9l6dxqBQKB9VQj6lk6Z5DQQ1tIndyPVpNoVGxK/o/M2aRvGGX+sgwdzzVUIiP3jRNBoqiBeOip/eBCdEZFrUuU0ii46GXRrtj9iSzpr8p7O5qipZ3flmhq6KEt6CdIRqP99qdJKTuD99RP6scOC4Rq8T0ShVr+L8NB1DU+baHrLqamkNhVp9JlsOwLw1RPGyC9rYL6iyepnjbQIkSo1SU7FZt20OoO4bxKaNHCeOQx7PdkqLZL8alRRLIO3n3mr8xgFFzSLzeKsWffnyGyKFz2Xd8cZur4lcH3hGfKhB7ciuPdd/qG0SDKXDx/iMStoyRvGaX5LB8qOdRP3EjooS2BLkjqxlH2trn3Zej8zgiqJe1XO6U/EKtrjlL71/hN1n7709iX9pF40sGKKiLc52UOO25+Cs5fTrVDCk+TTZ9rFrEFKfzWKg52VCVx6ygTn87S99lhL3IuA9nMHAEjm4hueoaouox6m0R4VdsLgzRFQzpvfIryNX3EZoRnP1RwmPpIlvgeG9UC1VaFf//WUfKfzIq2Q5viQSVEy2bmAxmi86Iz0v498R93UaJg3V8fwTp+A1ZUo5ZWWf23XptdMER40RbozEnik+m7niZ82jKgkSUwCi7hgkP4R5tRTtyI62WBYlMOqiVRWV8YEQigSc1WbZOIFkDl6iyRBYfILU8BwvyVesXBvUMiY2ZMJVYXP7NDBIJqkXvH4fQBnJBC7F5vzphzefn/Zugddyh6TH+VzCEwshkzoVI8b5Cub40wf2mGju+OkJywKfVoxO4aw/LGVeH09XTNW/uIa1peZlarNvXVv4p+VPSecUIPbm4p9gcR6GyOTflzUeK2MSpnDgTikH4GCSSK6mewfbPfehzaTx5vvQYNH3c0CD24mb0T8+kfCuROsdxAUDR6zzjK6QMt8Lpmq53aD/c93PKaUXSJzDScNJSXedcAzAuHsCJQXKkSnfaylRM20bvHmf5wluWjVaodBqrtUu7SRCi06LLsC63fn7toiPQNo5jv2CiwEd2DZtw+xtwVQkxTPH8IrQahkguui1FyKKzSCXnZFSsmkJPInIiauproi8VmhM0quVOyr4ojc3XqxlGcNx5DZVmYelwFRYgRfLhNqOBQ7tIwyqI/4gtp+mMhfPoAlQ6JCMdmLaJzkkkKF2QucN50LJXeEPHbxyifNYijq0TnHfRpWVdKJx9FPCoUWh3XjQTQLn+Onfh0lsSES/H8ITp+Xcd4eAvqeZKl9wkKfAiYT57hZ5Z9v/J9vdnMqELnv44Ea0k4bxPe7qDVXKptAuNrv16YKju3mlTbPdHqHSaK5eLqCsbDW0RPaFogWemX6sytC5N+xSJ5s9y/VoNaSqXz2RrlHoNquxDdJPY0xlf19AH0kk56u4lWdyiuCGHGITZrE3pWWKJ8DZWO68QHVEvWWDOuUulUid8qc8eKrz6Nev4KTydGCGAcHSLzwlaafsmmllIxyi6pm0ZZvDhDZJtDpVNgP/l3DRGfEqKFypkDJHc4FFeqxKZMQkUNO6xS7pb2US1hp8MR3Tpc6H3MpNKpo1dF/6aeEq01JwTx3S5WRLIT8d0OuTUa6e02KF6Gp6LghBTCFRejBEbFQaurFFdKNs2HjFnLFDq32jJHuBqhnEJywgmEbiMLDtqUSy0t0PnIvBSfz70vQyjvaSX1qMSmBApYTyjEp4SprbBKJf2yrCe+7lViQoRmYzMOkXmbWptG8uZRgeB6OjCFlTqJCclALf/XYeYvyxBZlDnMKIiekWK5tL3kkZwMb6X6JyeimjK3iOaRZMxCBYHn6VXRu6qlFTqeMyn3GGimSz0uGUWjItqAiV0u4R9tZsWPBDGUmBTCkrbvj2BdlvGEXxURPzYFHVRcqZHcKam/WkpDS2u0f09IRhRvnmu742lQ2ltE4ZuxK9oRh2I/sRWVfctOYq/k8eWP2l4y2e31i29hT3TVR4f46+XKz4lYe/hHm6mcMUD7iy6hBxvrUHTORjUdkpMu0bvHyV00hL7pMVZsIoBEdzxnEn5APlM/qZ9Kl0Z8t0mlW/bdoZxL2za7ZV8YPW2AartG2zYbt7SXMvrrsf8A9fTOnTtbdHb2l9X5fWz58uV84xvfYOPGjdRqNb797W/zlre8hbGxMY477rjXfJ3XndkpnrWRmQ9myL9rSH4/b5Daqf0ymcXUFgiTjyXXqm6AFV9cKw1QOXOA5IRF57dls6HXHNqfbyi/Vjo0IrNuQG0M0LatHny20Kd5WGmNuXVyzZCHsa+nNfLvGiJUcPZRUi+dM4hWdVh4b4b8hUM4hkItLQrApV5ZEDq/MxI4W2TWDZTKzTeKKr2vnls7pZ/6iRuJ/vhXLd+x52OChQ89uFkYz84bDDbxuYuGgvepdYIJodrReoA0UwbF8wapdGqY79gYvB65d9ybQFRqKY347WPMrpfnDxcaQznqLfjmOzZSPH+Irm+OoNUFtgOyQIUKLrWksN3NXZ4h+sgzLfdgvW0DsWmT2smiLu5vrvY+LPim1ZxgQxa7cyxQJW+Gh/jtCxCZk/4O379ZWPO8NLRvzQed2qlyrfLZjXoeM7uO9utHqCdVUjeOEn5gc1C3UTrpKBK3jZG+YZTELpvy2YNUT2+o1VdPG6B4nlzLCSuEH9iMbSiUzxqk77Me/rxJFd0YeTb4TuMRYUlSXDkEQmvbF05dT2LCptomcLVyj07vl4cDle56SiGSk3qP6IxsNMI514MuqtRO7Sc+5VDpkIOO/+yuJorUlTMGgonP0ZVgg+Xo4nMLlwiMAxo+C7KJBIEPxe4co3ZqP4U+g9yBDd/z2xKE/W7xPRmqpw9QuKDhtwDJnXXmLs8wfVWWcq8n6Pj2IwERJKyllKBuJDpjCUPQ9SPEp2xCD20hdqcwIlY6tRZl69Q9T7Pmz0Yo9WqBP0ZHBMYWXrRJ3DaGmzm6ZfPnbxaDe7v36RaIGIi/dz0t/hafcoI2BVqY2Kpt+9bRzF2RaakjCz53d+NzxfMGWbhE+qH5sFQ7Rb7HP+g0264/zwY+3uxre5sVUXFCaov/+vPa/u4LoPyO1pqd1L89HWC5Z9+fIZzb6zAWJoAwxadsakmN+UsF/qH95HGqHaIcr9UJIH1zl2ek/u3Ufqm/1H22JTmYqKawwIH4d/5dQ9TSwhAV3Ge3vC9UErat1KuyUPsYeNN7b2GVjpmQDWri1lFUy0Wru+z6VJbFQ6NU21TiUxZazWN/MhRPwFFFq0M9KcxupXMHmX1/JoBjF5drxKcs2r83EmzeFw/Rgzlu/oiI1P99OEulU64Vu3OMapvMVUbJQa+4cii5TOrCQg9uljqyqyRoopkyzxoPb6F2cj+J28aCDVD07nGBQCI+pJpS01o5U/o6f+EQ0QWZv/y5L/TQFmKzNosXZyQIgwQUammF+B1jxKdsIosu5gkb0KsuNe9eHUOh2qEzf0SY+cNCFN4pyuxWWCF9wyiLh4SwIzIedl+T9XzBovM7I8wdEcaKKrS9bBKfsin1tsZJ/Tmz3GsQWbCJT8t6Wk2rWFGpxfUhiqrl4ugKhT6dco/UM+bOlPqI+pvWSb1CwaHcIzVbPrQ7MWlTXKFhphRi0zKWtbpPvS01H6mbRjFjUteXX60Hvm088piwYMaFsa7j2SpRD6YZKrmodYhP21Q79KDG0o6IAGqo5BKbFniR5q3Z8TvGPFFMheJyTWppbYEVKx6cUvMY+8KLImhdT0md8LIvDlPuUal2aNTaVDqfNaklFXq+MkzqxlFPpFPBisnhqbhKYc/Hs1S7lGDcRmfk/2qHQud3RnBCColbR2nbZlHtEEmI5E4bxZa6KzMG1XaV3IE60WmT4vlD2GGpTcuv1un61gi1tEI4b5O7aEgoqGn0V/cTZbq/MULZ2yOZ2XXMH66DA4lJE6PskthlEcq7pG4cJTFpC5OiKTV3hT5DoHiGHMwiOWHaNYqyHoLUzRlFl3K3HHTmLm8cuKyoQi2pUFqhYMbloGfF5V70ikP79ySoHt9j7bOPAXDefGywB/XNfvYF1KMPh6H1MNA6X7pGowH89bF5Lxr/uaxJid0yXy1eLPPgnquz5FeJ36l1V8SYT+kP9n1OSGFxbShYO8ymubDzOyPE7xjDTGrMXZFh8pNZQg9ulsD94WGSN49S7pF7qSdVCu+Ua+bfNUTkvnHafjBCPaFS6fzvkc9MpVIt//6zDjtveMMbuPLKK9mwYQPZbJbrrruObDbLtdde+7quswRjW7IlW7IlW7IlW7IlW7Il+59s/wVsbP8ZNjAwwLZt217XZ173EdBMqEFacOdfZln1GYnohNk3gh+dkehLfrVOz9eksFirSSR/+qqsMGmdsIHZo3Q6fi2wid3nHw23bqLj1qdIKTtarudnDQCWfbERzbW97w3fL9Gy5M2iobF3tHT3J7K0P28Rvr8BTcldNESoKMXG6mkDKB4sqXTOIHrFQbXdIF1o/EKyBokHfgVKO6VePWBQabbme2vOLBXPGyR9QwP6ZcUl2lhPKWg1JYALWTGBUOQ+lCW1w8J4eEtQAAeQunGUucsztF8/Sv3EjXT8Wtq51KthxZUAMhjzn/H9GbQzBojOWlQ9yEbk3nGKXpHq7k9kBV7X9AxOxGBxbYjUqyZT/QarH5DCaCuqkrx5lD0fy7Lsi8OYb1oHP98k7b8XbMiPXvr6Nnub8chjKMeuo7A2sU9f7Q1hC/9oM/UTNxK7s0EWoJetwI98M7PrYHhTy7X89gR46cZjOPjCJ1tTwF6UJVSwAx/yrbBaxb44g/q9+6VdPMfxSRTmLxPB07D3d4Dkj54moewkga+lMkrt5H7arxcIR/plE8V26fzOOAvvzRCbNtE3SbbIfstxWHGBZfn9Z0XUlnYsNMHVIk336meZ2r83QtnT/TF+sZWwMimvXz9C+ezBwM/2hmj5EB/fmrO0EVpNf/QxOh+Vn33oleJBajpufYrEH3dS/JlkPF1DaYEzin7NWACxnH1/hiYCKLnmVxv+6MPY7Igq0FRPZyd8/+YWMotmi9w7TvX0ASL3ju+jk9OcefEt9+4hjIowPO1tfiYj9+4hIvN2kPUFTwMlpdH2/RFmPpAJNH2i94y3ECk064v5DIArPzcc+HnzeytnDlDu0ogsOBRXaIQKLuG8QHP85weZTxK3jXlaWD5EzCF6zzi1c1c1PwLlE4+i04Ne+d8DMqYjcxapG7cEOkQA7pkD6EWb8jKDwjuFRbJy5gCRBcnC+b7hZ8h831t4b4b260eIJfoJPbgZ+60CMwgvyjwGQuagWu4+WXcfaho/d5DQogWqgmJLFqDaqQc+VDlDoGepV+us/McxzHdsxHh4C86bjyX9ssD9zHdspNKlSzbw1s3UTunHDgt8KbHbxiha5C4aouO5KlZcD57FJ3Dw+6vrmyOYJ2wgebOMT+dNx1K4YIjoK0KeEfrZVmLe+Grul9waldX/e7gFMg1Q7dQIIyx9PnlF7K4xymdLX5bOGaTQpwd9lLpx1NMXa/VZ/z596HHi/l+RUiaY/nA2YEvd87GsEK7scYjMmuiPPkbpnEF6viIwpebxXju1n+6viwbX9FXZgMzFnw97v9yYY32kA8iYCOdlDQw/IPOJ8+ZjcTQVraJS6dZp+/5IAMcunyX+Xj1tgMSt0v9TH8miv+BlWX6+lXBaNLJ88o8YDWv+GQjmwWYzyi6xO8cCUo+Ql10NPbiZmDcnVM4cIHHrKAkE/ZB8uLG3SOLtCwou0WkTV1cJPbiZOA04avX0gWCsBBDpcwYxSg7FFTo9j1Wo9IZIba+i/vyJlvtbvDgT7KH864XPlyh97eR+IosOWtXdZ55qhs3WTu4HFVI3yrOrHjNj7K4xahdnaPu+h07wPqua0PmNYcn6e3DtBK224p+HKZ0ziFFyiSzY2GFZd/x7zb17iPQND0gbD2+lc2QyyCy7mviK7WUpE7eNBdevnSpjL3bnGIULhgKYdvc3RmSftlNwxb7P+UAof30AMM6QOXHlPw7jvPlY1H9/Arz1JrrpGVDaid8+JlnRE46ER2QP4MPq1X9/giigbFiHmY6gP/oYDK1n/tA48T0mOC4GwMBRuLoKw08F393+oxeEgOrx1v0oQKVT9lP+3qxNHUBxvIyeNx5qp/QH86NtSCnG9IeyROcdYW31+q10ziClXo2erw0HbedDrH1fsyON9QgIdNJAyj66njbRfrSvZtxrtf9XdHaefPJJli9f/ro+o7iu+5puNZ/Pk06nWXfFP7D824+zeHGGSpdCqc+DPkyIqGNhDdR2TTDxpWs5/LSrUd+wiuisYF3DORe9Kovx1EeztL9gYsVUiis0jILAGPTHX+Gpn3yJ1e+/hlSsj2qPS2hBQa9AVVgEhV1lUZg/SgfaGPMqB/6VsEZVO4RpZOU/DgvELi1q5GZKQa0JM0mlxyX9otD4mkkw4y7heWEYsqMueknSq5UeUfi1Iy6JnbBg72LHNz/PAe+7hkRbH7Eph9ljFLQtu9h28+fp++jVHPjKcmaP1FFcKK+0ie/UqHa4rPmUpGXnsib2E1Ps+tK1vOHsq3GPWkX780KZ3P0N2TABHnOVYFtzx9RpeyxEz1dFFbvn8RqFVaFg07rtC0Os/fgos1dmqKcV0i/bTL5JoXdMGFfSN4wGbDx6VWALtQ5hevPrHyq9Cu7Wnfz6365lgOOJHX8C+qOPsetTWWJ7XHKHENRoNNvcG1fwxM+/xLJPfYxYx2q0qoIVd4hPqKR2yH1oVVFm14sqye1CDe5016Goc8iHx3jl70Wl2Uo4GHkVs93BmFexki5qVUE5sISigDkTxVhUKeZ3sOdzX+QNZ12NceAqnBAU11ikntep7JngpRs/z4qPX41++HK0goZqQ2yXQu4Ii0M/OM62a4cw8irakTkquxJoFRV7WY3oryNUljkYRQUzIbCyyKyKVoFcdYKd3/g8y6/5OO1/nKKyLY0TcdAqKlaXSf2FSfZ89ksAHHLu1ehrV2FHQLFEZA0X9IoilKIhESqsrLBQqyrhWRUr7uKEXBRbITapYKag2msTntWwYi6RGYV6ysVKuiRfUikc7OCEHJLbdApH1mkfN4T+s0NYeuqvTvDqdz7Psj//GOFVfax+0GHHSSqHfGSMl/9vRtS/TbCSLq7hcshVY7zymQxqXaHtRYfZ9SLGV1xrkXxRp54CVxeohlpTcMJCi2knHXp/qbB4qEp5bicTX7qWo97+Mbqr3RR//hPG2cThp16Nc9wqVAu6fmUyd4SBURSmOisqFODz7GTXl67lgCuuYVlxBfWkQnXXBM/96FrWZC7k5ZEbWXvBNSwv9uLoCvOH66RfsrEiKuVeBSsBbX/zI8bZxPI//TixjZ3YU1FRVq8r2FEHta6IqJ7u4kZtlKosVFpBxWq3UGoqqqmgrqhgFkLye11BrSuYvSbJZ0IU19godQXXkGuoRR0nZqOEbSgYhHrKONsSJF+BxSPcQIhu+S9tZo7Rqbc5uB11cBX0iIlZDhF5NUSty0atKRz8p6Ps+JssZspTQNdd7JgIRao1lfC8Sj3tYCccUFy0hIWdNzByGmanBboDNY36jgn2fOZLwTg98sSPs+xhYbyafb/ME20v2RRWasSnHBYOUel9zGRxjcBNjKL4v6vJpmPuigxG0aXYp9K2zSZ2lxwyCn0Cq+i4TubfYGGxG/V35bMHqXSqJHdaKJbD7myY5Ksu7d8bwXnzsSweHMEoy7xkJhWhKM5ZTGYjrPqM1LFILYItzJS9Gu3P19B++ji7PpVl5T8OY75jo4hLhlVU20UvOVQ7NfSKS3GFJnVIW6XuJHWT1OUld0oNgx1RmV2vsfpvhZFQL4m49J6PZel6poa+SQ4Jjq4QXrQorDYozU7wwp3XcuB7ryG6vA9XkZoMV/PqXNJS64EitNlaDYy81H5UehTCC1J7Ue2QOd6nNKq1u4RyCrE9LpUuBSsGiZ0CgTJTYEVd4hMKsRmbco+G+cpOnrvvWg6+8Br0NX3eoi7w69wbXCLTKvU2l8Srst5pdSitcInMKqz83DCvfCaDq0DHs0LF7ehS06Y4jQPOxKezGEXZaPnMXdVuhZX/OMzc5RkKBwhLZCinUO1ySL+gYHvskeXlLr3jDnNHCvV3ZEZY8aw4hBalDXChPCPt2XfV1USX9RGZkTqXSq/4oVpXiMxBcZVLKC8sVUbBYwtsU6i1uUTmFWrtLkZeIZSDWqfUTjthV6DnKoQW5L60GlS7Xdqfk3YvrlSwEq63dmlC898hYzI8r6JV5f16SSE8L3Up1S7p49xaSL6qkDvEIbZbDghSp4RQKXcI7bSjQ3yXQu5wm9TzGvU2qC6T/YsdkWvU0mBHZJ43ciKJ4ITEbyIzIv5c6VGwouIn0RmhgbejQimdXwOKJfNzfKewChpFWYdKq7z7c2VcmwkIzxNIX9gRsBIew9krwoS47AvDvPRPGZaPOJR6VOaUCSa+di0HXXwNqcRKigdAZFoRpsZuF60qbIhWRJ7bKHnQ1gqYCZe2F6C4ShjabEP8rNrrEJ5RQRX/KK2E2B6F0iqR2bDiLuE5lXpa2jE+AfmDIbppJ88+8AVWfeAa9LUr0erSxs5zu3jlu5/n2MxH6J0Os/1dK+h9zKSwUg8g9CCiovYLQiFtv/U4jIUqTkiD8V9ROmcQ+/YHGWcTvR89m6kv3UnnW09m7idy2Fs7eCHbxm5k3UkfJ5VYycxxKvEJWDjKpuNJjeIBUO+xOPSKzUx8OoteFXFjoyisdUbJZU8Wki+rmEmZL/s+O8zCezMUVynEJ1wKB4ng7cGfHOGFb/bT96BK7C6pf8SBWodC+wsW84fpxCdl/+wYUI5XeOVv/pJcLtdSQ/PbzN/fH/j3n0GN7B3a/O3mVKu88r9e+/cVi8UgK3Psscfy+c9/nre+9a10dHSwevVqPv3pT7Nr1y6+//3vA/CFL3yBgw46iHXr1lGtVvn2t7/Nl7/8ZR5++GGOP/7413yf/z3gviVbsiVbsiVbsiVbsiVbsiX7/w/7DxAUvFbbsmULb33rW4Pfr7nmGgAuueQSrr/+enbv3s2OHY0sWr1e5xOf+AS7du0iFouxfv16HnnkkZZrvBZ73ZmdPzr+b4k+um8BWMt73QXG2cQAx5NS2oPXp6/K4ugC85p7nwiM+um93/XZ/0zbm3HptdpvurfXe897v9+H27xe81k/Xos1s0EBAdxmf/d12BlX0/dvO/cLn2i2wjuHyFV28et7rt3vszdDd0D0D5qZUUDSzIsHh/YpMp++Kktit0BmfDhb1WNO0q6/P2g/46wTWwrF99cXpXMGid/xmwvAf5v5cL3f1cf+34H/FN/1U9uv1XxY197349/L7+rL38V891psn+/0fj/0nKtZfefO1/XZ5tdWv+1Cdjx6437b1YfE/aZr/C7bfU0DsvMftf+MNvzPsmZ/hNfnk/ubj3y9LCCAjf2h2e8aIy3v/S2+5sML/yvu6z9jvWyea5o1qP6/NB9e5Nt/xbr//6X5cKPfx/z9SP2kflxFmAab2+a/w6zjNwTQ6mb7r+onnxH1t1nzvWjnnSSMiWcPYt3xYMs97r3+K/1H4W5uIpUaWg+jT6O9YS3289v2uf46+tnKZtZwBC8jREX+awMcj33pKftlLP3vMOv4DfDIKD/lnt8rs3PQ//79Mjvb//r1ZZL+O+z11+zENPR3bCR/gNGCHfRx44sXZ6hN7oAfb8J80zrmDz1ABJKSCondttRcXChsH0bZpXr6gJfudcGB6WVTcN0mKiccibt81T6HId9yFw0RnbHIH2C0YND9vym2XNNVFXJrVPo+O9xC41w6RyBuHdeNCAuO3RBu/E3faQ0eDmObqBx/JKVjDgg2STVPzLD+pnXMHXaAsNUsa4gV+oeSvTf/+TPWk/q3nVTbNaoXZ9ArDonbBM9cT6nC0uVREfvm14DkLhoismAz8eksHc/bhBdM6mmd6N3j7PlYlviUg2oKa8z0h7O0bTOpnD9EuUel5yvDlHt0OLVf2Oi8moN5r14qdc/TaIf1k1ur4nj9Gny/NzHPX5rBKLsB48z+rPlZgX0OOn679LDvwa25Dse3yL1CHT77x+vgZ5sws+uw2zTcpsW63lRD5NtvOujsTeu9P1v2xWFh13t2Bzws120+tE19NItadwl/vVGzUzh1Pan7d7ZgrEE2kYrjKUWbboO69bQBHEOYenwcfSjfoI9srtcqnj+E4gi1p++n/mS+v01o5e1HobavJHXTKJUzBnA1BSNvYaZ0jKLd8n6/3gIafubb/g7HhXcOBYKp+XcNUZ/YAT9rbXtoUIAWzxvEDimkfyg05sBvpE9uNl9U1Def4hiEYSi+vw/RmJMW3iv0peGcTaFPb8GC+2O4ua5nx9+ISJ+vIB587173PO/RoqZuko1KfrVG5fJMcH1fkLd6+gBmXA0CLKVzByku11rqIBYuyQS04jMfEErYcE6YjaY/lCU651DpUtErblAb4vfXno9l6fh1HceQmhRXUygXdgX+ClKzk/JgbPvbmFlv20Clx8CMCjtj/kKpC1MtF+PhLaRuHMV62wb0Rx8LfMZ8x0aqHbKE7C945NcA+RT8/nfmLxSZAv9g6B8OfJ+rnDlAKGdhxTSsiBrQeGtVBzOlUY+r2GGFxKQlbH5VF73i4IQUonePBwczn8XSeFjo7WttGqG8E9SOmHGhmU7dNNpSMwUyznwB2b2DDrVT+nGmdsCWpvY9a5DFtRrtL8i4nflgBrUua5xedQPYX/N48/vBZ7sMP7CZ0jmDMrY9HyufNYhRcYJ597cFQRYvzmCUHCLzZhDYqp4mc45WddAffaxl7MxdniE2KwGl2qn9qDWHlZ8T2KDiNFg3/f6pndovELZ2gQYbJbtlzs69ewjNlM/NXZ4BV+iFUzeOBuLaPvW0XnYonTMYMFRaL78azNv+vFk/Seq+zHdspJ7UBEaY27dGx/9MqVej65tSl6g4Qu1beOcQqi3UyFrdJXrPeODHvpnv2IgdVoM6v+JyjeROK5jv/EChP94WLsngGBDfY1NaLuu8GVdxvD1FZFGosJM7pDaz3Cs4sfQPR1vWBL8v7JASyDnkLxyinlTo8vpOr9jU07qwZ3q1R35Qq3j+EJVOJViLfJ8O5xostH67pF61CD24OWjTwGe8ObJy5gC1pIZRFtp8O6wy+/FsMAcuXJIhsauOWd4Nv9x3jq+ePoAdEkimFVWIzFmEHpI6umpHCL1st0hSgOwl6kmFxIRFtVOEQ8OLFnrVpu+zwxTPH8JVpJbUHyv5C4cILwh9Njc+EHy/H/BqrukN/rbX+t9y0AEYFYmE5oPO/sw+pA9efLbltcoJR9K710HHeeMxmGlD6oxPknmn1Kuy7IvDFN45hFZ3A6Hg5r2VbwuXCJRt1d8PB+O9cMEQ0RmTWrseSI2ArDE+rb4VVtCrDsqJx8FD9/zWZ/mN1qSb87o+8/+ALcHYlmzJlmzJlmzJlmzJlmzJ/ifbfwGM7b/LXjf1tGpKpC+5w8R62wZAIgqRRZv8u4YI52yiPxaYm6ML77wZU1qiZmZcfnd0Ba0iIpdWVCX8wGZ6rmuwYKRvGA0ECH3dAZAUePqGUUIPbaHrW8LoMXe5FMeWzhHBttRNoyRuGyN5y2iQDvWj+MmbR6knJatTOXMggBzEJ+tB1Kt2cn8QSSmdM0jx/FadkfYX9y/c5Ed1m7NevqBb+/dG2PWpbPB6OGcze6VE49q+P4JRdpj5QIZCn0bqxlERDEupVM4cCNrBDivMXpkhMmd792FTT6hoP3mc6N3C7tW+zdMTuUMYPtq2mdTatCBSN31VFqMimYV6XEWvSoat49ZG2zuJMKv+zzBtPxhh6iONe/YjuB3fHSF5yyjxBxtREl9X57Vac1Twd8HxmnVRQj8TVjxjeCtaraHFVDu5n9DPt7Z+7pR978nXK2nO6tRO7qd89iC1U/opnSuaPH7B9bIvDhN7uPGckXnRwiieN0hsyqH7GyNU3t7g6VdtN9DwASkIB8kcmnGN6N3j1NKeXsEJG3B10cCITdcpnj9E7dT+FghBs8AniLZD+oZRqqeJ/s3iWrlWPakxfVWW2qn9geZN9Me/Cvw7es84sTvHsKOaRAq9e5i/LEPszjHarx8J2iZ5y6i0xTnyHFrNCViYfH5/oyyZyB1/Lf5R96K0+TPWM/v+TKCzAw0GJz9inf7haPBzM7uTb3NXZPZ5rfpWeSZ/jBbPG2wZZ3ubHzVrv158tdqutWR1mn2jOcO0+u+Gg4hms9/597zw3gzF8wbpuG6kBV607AvDwfXNd2wMoJmRe8dbMh/x28fo/fJwICIHMjf4Edrub4yQesUKYGM9XxsmecsoPV8dljnL04vws3BaXWAvkfvGgz7eW9R0b/O1XeauyGC/5TiKK0Mkbx4NdCPCOZt6SsN4eAtzV4gmmZkSf8ldJPNtc1an8M4hchcNMfXRLM4bj6F8tjfvnNqPFfP84l1DgRaR6enclM8axCg7zF2REfKBcwaxwiqVLgMrKp8rd+sUl+uodZnzNBMSu0zRoPjhKKGCCCpqVTdgR6ycMYAZl/svni+aK4mdNepJldrJ/aimQKgdXTRZUjvkuStnDDD3vgzVNmWfDMrCezPYbz2Oekqj1r6vsPaKfxrG0RUSt43R/fUROr8zgu5lvovnD+0X+le4YAg7ogZZhPgdY6R/OBqsrbG7xojePU5sqk719IHgnpp9x7fYtEX8jjHssBasV5H7xgnfvxkrpmGesIH0DXJtf05qzjzPHxEO9LSatdRqKemHUq9O6MHNpG4aJTxv7su+WXIwSjblswZJTli0vVQjdeMoxfOEpSw6b3vCrHJffsS97fsj2KFGdNjPqJlxERE2PT0Vre5SXKEze2VD56981qB3TYW2F0WHL3bnGFZYZeLTWepJ0f9L3DaGGW9oVfl+WDljgIVDhQuycuYAlU5hP8wfoJO7aEiQKm0GuXdLtmvhkoyIkU7Z2GElEDJ1tIaujm0oaFVhjy33GkGmrny2sG0tXpzBeeMxLfsboyBaSlrNJTFpB/1b7jWox1UW3puh0KdTS2vMfCCD9bYNIuw9Ibo4C5dk0Koy5gt98h2SbVEJL7qUe3SK5w1S6tWZ/nBW1rdLhAl0/tIMJU9/L37HGOUeHSuqBMKZ85dmiE9ZFFaHAjbXuQuPDq7hmxlXya+WvUtxhSFj8d+foJZSKa4wWHxPhvCCSf7CIcpnD2JGFSILDmZCDeb0cq9BcWXY8ztBOixckiF6zzjF84eoJxRKy/XXDDf9fU074tDgZ2fdQQDYesNHa4OHAFBPNLbQhQtEW8sJNTR6yj06yZtHWxAwsbtE8NbXPYPGGrjwXkH/tL/gsP2zmWC8u/vZqc9dnqHna8O0Xz8iGkveere3XuHrMZ+N7fX++3/BXndmZ/Zondk3ZojvAqMEykVDGCUXrWJTPExHq6nk33c0fGcT5S6NeMVFr7nMvl8E10BYoCb/VJTjZ9eHsfuzuCrULsuwYO2C722i0q3x6t9l6d0iFKGLhyo4Axm0qkJkFrTLMygOlHsV2l+wA+eP3zHGno9lMd8lKs2+Ei8IfKTUI9R+etUlf+EQlU6VcrBwGOQ/lsWKCTNG+WwRTK0nVdqvH2F+QJToo5ueIfexA8hflaXaBc6zAg9ZPESn6xcwd4TOyntlgZs5VkEvKQENZsdzFq9+ZD18eRPhn26letSBzByrUm2TGqbkhM2eQQ3no1lyR1jEduj0/YPQj85fnUWrimjZ3JEGjg7RWRe97DJ3hTCaVboUVEsjOmuL+OvBLgf/6Wbmr85iXpohudOi3KWhVxxmPpghOucyd6RCeEGn6sHY5t95NLqVYOHtWYymnPD0h7OUVrgc9BcNCFf0iz8K/h56cPNvTc3uDWvzU9o+TKsZrjV9VZa2l8wg5e4vrPOXZXBfEMhD9W1HYoSFstuHrhQ96unaW9bBv09ie7TNPmWvX6Ox+J4MZlzYchK7LOyoilZ1AlryuSsygQjejr/O0vZ38pzz5x9NJ5A7SNo/MWlTPW2AcnJPy7NVOtWAxrhZebmWVqi9TzZkIPTbhUszhEou2k8eDygnpz6SpffLwwF2evKTWVb8k2yeQznpW1cT5qqVn2tM/LFpGzOmYiny3LPvOZp6fCVd3xwJoFp7hjTSHRnsSIOatBmat+Ovs0RnXFKvyuapevoAiiUU7IV3DmGHFBYuyQjrE9C2zaHSrVLR5TtT9zxN+LRl1B6QA2LurPW0RUTdO/9nWcIL4rP+AWN3VsPuPhquE3iEXyc1ccZ6uGcT86cfCvduxoooLdTLvk3+aRa9DMqzr8BPxC+sA1ejWnLgmb0yg17Z99A4f5iBs17qCFPbHRxdRFzzFwrcMzIn7JEBTX0T1C1x21iwibMjKsVlGsYlGWLTAn8xHt4SwM9cVQ6GriZU87ahoNdcovNOC6yjGWJSXKljnj9EoU8l9apsrFRLRE+tmEKURt1DaofF7JUZau0KkVlXGMjqky3PGnvoV8xeeQpmUiE25QSbC/+wGDtxIzMfyODqCnzYm2dsbzNuKHTeKHBA5fQBYtNWIFyXvHlUIFumzMWrPiOHOCuukJyA3X+ksPyXIu6ZumkU84QNKC7YIRXnzccSu0vaMTZto9ZdZo4xiE+6lJerwh5Zkbbb/RZwQlFCBZfScpX0do2cNwb0sjBzxncrwu6FBJisCJSvzJDYZeN261S7QmimS6VbR7FdahcJDLPSLZut/LtkQ+szNi1eLExl1UtlrUm9UmNxbVjYxDyWqdLJR0FHH6XlKqUPSh/s+echYruFwcsoutTahEXL9uDVkXmLekqjsFpj+b8Iw6YPf8xdNMTC4UoL8+X8pRkiOYd6QsX04GyxWRGrnuyehK/KuJnqN+jWB9gzpKHYCpw3iKsqRGdNIveNUzxvkPo5g4QXLNKvmORXy4HN31D1et+3cEmG2SszlJcrrP7bYcJ5J/i9w3uPE1YFhpRQmNtos+zfVRHjLLrE95i4qoL208fZc7UEQlQT2raZLK7Vicw7AbS00qVQ+Mss6b9vrCPgyRx4wsh2WAIcuYuG9hn7esUReGLBptaho9OAh+keZGz3NVki3iGnnlQ9CL3Djr/N0v2EReoVi8h9QkddSyu4usg3yNhsQP4Skxa5Aw1UC5Kv1lF/8WQAIa6cIXCxzu+MeDT2MufHpkzmjwgHtYX5q7NYEYgmDcKAUTAxDzKwVuukXrXIHaSTnLCFfrruECrIIaLQq5Lc6Yiw67Y6ZlLDPWFDAO1euCRDuVfHKLt0f10ENn2K7dl1OrE9MpYA0tvloGq85Ti0nz4OlwqEs3ZKv8Dif21T6lUDYepah0LHdzfTAbxy3mqZN258ioiygwiyzwnlLFRTJbVDfCWcc4nMyyLX/r0RZj6YoePrIpAdyjugCCOcbSjE98ghtRmu9uJXBkk/p3gC2xbmOzaSuHUU6+JMQH+/66Pr4UubWDx7PZVVq0hvl73NdGQCviZjQjl2Hbvfkia93UKtu9TSGlZU4JQMrafaHUE1XaaPM+h+UmCHoYe2YD/7QuBj6tbtABQPUMBj7wuPCbRar7riy1UXMyq00pUzBQoZumgI24CZD2TQ6gI5Uy0XLhhi4Q0qruYGtOV+4NUPYNXjCgd9eiSAN0bmbeyQrK+FVSE6aATW8+9qCDrbYXCq/wFY2R9wZmcJxrZkS7ZkS7ZkS7ZkS7ZkS/Y/2X6fTM0f6mGn7QWbtrtHgkiFX3BXO7mf9Ms28TvG0N+4gleB9tuehnNWoFUl7atVPXataYv26yWCmW66du3kfvT7n2I70HHTU2jnimhQqOhwwF+PB8ValTMH0MsOxsNb6KAVBlM6Z5DkLoF2pW4aDdLWIPCROARCb/UTNxKdlQLW8tmD6CWbZV9sQBf8iKvrXV8fey74W3jRDSLFUyeIvkHPdU+B0h6w2SRuHSVxa2v7Re8ZZ4W7wARQe8u6oIA39ODmoEj/wPu859ipELtLitoi8xZaXaO4UqP3S8PMXpkhOSGRpuicExQ/dn1znNK5gwILzLkc/Kce7Ow5yZJUzhjAqIign+4VaiZu9YrN56V/Om55ivjGJLE7WyFhvrCVb71fGt6nGHB/WZ3ieYO0f28kYHma+kiW9hfNoH0DQa6myPveBAV+cW/HdSPkPTGxyKPPYJy1kvpJ/QHkxxf9DCIdHjzCjwgu//wwe67Osuza4ZbrAoEAYuncQUJ5ierXTuln9f9uZBmiczbJR0dJIhAnM6YSuW+c0GkNEUcrqrD8G41sU+K2MRbemyE6Z0POJTxvSoTHs9iMHehs4F2398vDwWdq58j91E7tD+Al6ZMk41j3CmPjd4xhRQXeVjxvkHBO+jK+x6HrES96PyXwxmWjNqrpBuJnWt2l47rRoEB89b2t/dfMzOWTFjQXuaduHCUFaG9aEbyv2q4Fj5S+62mc96wMMlO++ZmS5cM29Xuf4hUEAtf3xWGmr8qS+opEezvufYHdyDwQahLx9eF5K/5ZrtvsFylllxADnLCBrm/u65O5i4Zoe9lqgfH45j+P/z7f/KyOH31rZtyKIfNKM4nD3gyDe1vhnUMYJXkev5jfz276UTvVK7aO3ygZtq5bG/drxTRcb86wzxqk65tjQbs2Q1IBzDeuIz5lE/3WOJUzBoK51M8gqqYIqvqkHZLR1jBKUrBcOkegytV2Db0iZBrVToUkEFkQrRQ/WxkqumgSrKXbQ2OGFy3KZw9SbRP4cPX8IaqdGtr5Q8SmahRWhVFN6HrGYnGNTmKnQ2zGotKlo1qw5naTSncIOwRtL9nU4yqxGYdqu8Bww686ASQXIDFpYodV6gmVSpdGertJPakRnTVRbB0zJmNl9soMy74gc3DqplHmrshIZiqm0PtlyQCHSg6OJt5slCTjpXgZpPgDIubp+4s/LvyILNAiGhhesNAffYwQjayqr1sk7eTQ/qzawsDW8d2RwMd8czWByyVPlXkn/yfrCS9ArU2l7QWwDbk/R4d6Sqd+1qBEn+Mq+qOPUXiniGbOvj9DpVth5S8qVDtDwXyZ3GHR9c2GL3d9c4TJT2aZ/nA2yITULxjy/DRD6qYR6lcKxCt/gEE452KfOUByp41RdDDjKuUeneisQ3hBHKXcaxCbkoxn4bT1cJ+Q/BiGEE1YHgFKbFqcKTIn2Sy92hCkDT24mRAyZ9uG3HtsjxkU3NcuzpCYdIIMSP3EjdTadfSqQ8ezki3Tqy6Fd0oBeNvLrdAk3/yMYXTeIXmz7Cs0jwDDOn4Dat2l/fkK9ZP6Cecc6kmBzLkaJCeEmKl6+gDp7RauolBr17DPHgw2iskdQiAQ82DD8TvGKJ81SChvYcbVYI7zzTpjgMLqEPYHM8SmHRK76kHROkA1rVL+gGS0V31G/NsxFFRb5ptmxsWO744w+/4Mrgbplz2B2LxLykMmhOdd6if1o1gO0XlBMJjZddiRZZSWhQgVHEIPbUHx1tIYsoaVe3RCZwqUTqtK29eTGkZR+kM9cSNmUqO0PETizcdSTxlUOjXMC4c45MPe2Dl7kFKPKkLAQOrVKvWUZCR7x0x2AeGcQ+9dHmQY0L39FYD7xFaWeZqubvZowvc3zYujTxNBRHD7/mEz2iFrcOMRHETcm59Idqj0pkPg55tJ7ILFvfwiMmfR/tCIZPgKdlBO0UzGJJkdl3DOkYOEC8tG6wHj3t7Md8Xzh+j4roy3rl/Jml1r00jePIpy4kZCi1YwT1fOGAjmicX3SHa48rYj+b3tDziz87prdvSKGyi9gkwM1vEbmDvSwIyplM4dxNirbgLAiqrBYPSx2CALs3mC4JNdvTX9Fr9jjMi940TvlnRs7K4xaif3o1XkoFM+a1AmuXDr5/SSg+1Jsv82SufQQ1twDEUgTTGFelpv2dzUTumncMEQWr0V/145/siWjXn0x3uxe9CoB1i8ONNSv+Hj7QHCP93K9IezOIYSYKXn3pdh8T3CzOboAtFJ3iL1SfE7xgLVbaPkMv8Gg/iUTXGZ9IVfs6NXHGGG6lQpnTNI/aR+WWzOGgw2qNXTB9AffYzKmQMes5qDGWv0i5kW+kFfIXnvewfZrJlvWvcb29c3f1Po90Xvl4f3YdRpro3Yn+0P775w7npZFD1/qp3cT/gn4nv+YUerN0ai72fLrh1uYKW961ZPH6DWbgg++Xap9YreMx4w36TueTq4XuGdQ1Kf5EBpuYcnb8LkqvXWmpPpD2elHqZNo9quUFoRYnZ9hOL5Q+z5WBa9YlPq1YIaITOmBuKys0dKPEIvw+LBBpN/lvXquuT1aqcaYN8Lq1XmrshgxtSgfqa5dqPY52HTPdVn/9kjC4IXDxVsqqcPkL/QU/M+pV8OdO/YiPW2DcIS6LVb9B5hLtpfLdX8+UdjlFwWz1kPQP2P15G+QeBOzeYrrzfXTqXueZrCBUNUuyQY0GyKA7E99RY/nPh0lv1Z7dR+IveOt2wAymc3fDl9w+h+Dzp713ilbxjdx+/3Nv+6r5d2OnnLaPDsqVf3XwPYfM3IveNB+4NsZMM/Egav5vqS/THcFZdpVDr82i6V/AGC/Y8sOCy+J0NhdYjCBUOUejURilypY0YVtJrDwhsaMTG9KjVyRsVFqxLMW47hCQl67ecf5rW6S6VDJX+AgV52UGyBZTmaBCKqbQqFVWGsqEK1XaHcJTUTjq4wt078NXeQxsKhYaptivfcCnZYNnSxaZtyj4qjKVR65RBWWqZS7dBZOET3WA6l3sQoOVhRmRerHSrTH8qSmJSah1KvPKNaFxhb75eHg7qm0KKFFVGwohrFVSp2mN9ovup8c82LXvYCD3eMUfPqnBYvboyF2F1jgQ/ZYanv2F9Ngl8rB2AU5ZrJ+2ReSv3b07RtM0nfIJAX38y4QrlHZfFgjcJK6f/Z92eIeAeO+LRN57M2ZkIYv5I3j+KEYHGtEXxnLSVrh1EUxtTIfeMsXpwJ6tDiUzbTH8oSWRDGQ0eDyKyJWnOJ3z4mG/82FdVyqXSpLK4NEXpoC1ZUDsj1RGP9Dv18a5OfKlQ6VWbXRYWlLKVhRVUqHRrzl2Yac+SV8r9jKEEtT6lHw4rK3GZG5frzl2Uo9BkCBY2oJG4dpZ5SiN8xhqNDYXWIUq9GqOAw/SGZV2Y+kGH6qizlXpXcQfLZ3LuHgsNbuUdlqj9MYbVO4cAIdlihllaxIgqRe8exIiqlXtkX+bW7sbvGxE97hFUwsuhiJjUWLskQv2MsOGxVulT0TY9he89VO6U/eD4rqmLGFSLzLtU2FTOlM/e+DDMflLoyzZQDca1dYeqjWWptGnNHiO/lDjJYXKsz9ZEsk3+aZe6KDPWUwGRdTXym0qkGPllaqZA7UG+ZS+2wwmQ2ghVRcAxFIP9tejBm6kkNK6JQ6JM2Alg4VOoCFw/Rmb/Uq0nqUqmlFcyELix/VqNmCwQOnn7FCupL8wdEpDboXUNY8d9em+IeLXU3pXMGhRWuuzFwtcMPwc0ejXb4Iaj//gRu5mgwdJwnhW3Nrw8EUL0f7abUQOlNUrNTWCXjRLVc6kmN+JQdHIxrJ/ez61NZql0K0VmbelIlducYxRUatr9nObWfekqnetpAUB/rzx0r/mk42NsqtsvCJRkKqw2MRx4LIOXRe2RvXD1tgLYfiEB8tf0/ANhyf89//w/YEoxtyZZsyZZsyZZsyZZsyZbsf7D9PoQDf7AEBYUDdEK2nEqbi9FXbJITtGq5+Gfi4slHseLOMWavzODoClWvCDq3RmPxU1lW/uOwFIf+UCIGkXvH2eMVyf8ma4aJ+NFMP9oBDU71MAQpb1whD/ChS7E7x4IiRjMmBYuKJSdqP1IJBMXqe1t00zPQJKhl/tG6Fu755hSxnwHy2yp6zzhm07USuwRSlLxZ4Eed3xlhz8ez1NoNer80jONF2UvnDrJ4sEbns1Zw7e4na9Q6dNKvyBWnPip6OvOHG6Rftqm2NVh0fHKA3EVShKuX7KAoPQpM/EUWvARV5e1HknrkMXb+VZaO52xe/lyGNX8+QmGVTrTp3pO3jLL7xL7f1FWvy16rOGqztd8u+i0BBOSBzdS8v8Uf/JX8rSky3hyZ2lu0zW/TGPtaM0FB6OdbSSqN4u9ej+q/la3NovP+kYBBsM1jx2v7gRRoCmmG3JcPZels+j6/cBmgWbbNh9xVzhjA0UUTys/0zV+aoe8fGlAH1yPTMH6xNfBVH361twBa+EebBYLlZbF8SbFmkVLYd7JozprWT+qHBx4GoOPWp4gpO2jzYGWhn8k9+IWzviaC//ny2YNwx4PBtZI3C0zQh6X5ZvxyK6oyGfhg8bxB+j473KId0vxMe9trybzs/czA7xQLjN059rpFYPe2veeLlu9vykA1+60POXotgrnttz9NShFh1/QNoy3w4d9lvWarILFvCfYv0OzPmfWT+lk41Ah8FMBLuFM7uZ/UTY22djNHo4w8tY8OCBBAxPb+bt98f/CLfQM9oKZ5uHz2YJBFa5bMc950LJF7BedSO7U/mCdrJwtM1O8PfxyueEDgrotma7a/eJ6wyiVuHd1HVLS5z3zfb4axAljh392XmukKccu2+n5FJ/12i9w3HjxjglaYTOmcQbq+JRpEzTpazabWofdfhwMykOJ54tvNc2Ozn/oQscqZA4R/tJlu73Wdhhit31/NfZmYtDEKFslbHm8Z6z7jYOe3R5h7X4bUznqQhXbefCzqv0t/7b4mK+Nu2mkZe+WzBe3R+2WBgPswwI7rRrC9ovzZKzMkEbhR6ZxBErvqzK2LEJ1zKK7QAghqjFaR2MoZA2g1gQAbD2/xoKhQWq4EcFnrnUOkfzhC/cSNkil79xDx2wWVUloua2io4NB+vVzTz4a0exH9UNEhd9EQcU9UO1RyKHeppG7ajOOtKaGcLZo2EYXO7wj8tPM7I5jv2Ij2k8eJnDZAPam3aIUp5w2ilx3skEb7i1bL2IjNiC7RxKezdD9lojS5d+qVBozTz1poNZdVn2lkPxcP1lpgyv6c0Nx29RM3Uju1n7YXrWAs+r4yfVW2Bbo+fVWW2IxDarvA87S3HBdAbn1Sl/yfCIRz7/1Y8LxPvRC8Pn1clGXXCkzYikBs1sFVwFkVJfnci+zJxOl6xsB4VuBuC4fF0H8p14kOCxlB9IkdwbV1D6bbdufTLOwlKuqPPSekEJlxg7b039M89ks9Oijimz6qyNe0a95f+21YOndQUCMekcrcFRlKKxU6npVsZMfzNXjk9e+l/ifY6z7sxCdtUve1blpAIEJ61SH8o80tm3nzhA1E5xzC81Yg5OUPivLZg8FgNN+xEUdT6LhVNky+qGh0RpiyondLzY6rCrVvvYmuEIQtpfPbwhgUWRBsefv1I0EdwjLvfYsXZ4jOWsSmJY1vlJ2AUSl/4VDLIAc5HMSmLeywijW1A8Y2Bddp+75MaJYtONbK248i9cgEkXvHKZ0zKLhqbwLznTZ30RDKDx7w3n8kvXeNBZTNRlnofZvbxBfHi98+BudIKlw/XihE/bSnUbKw33ocqR0WesVm+b9spnDBEOntNbSfPo5xUn+AJbeiCp3/KvUzWk1ghPE9Jn3/MBwsONEfP4N1/AmktzmYUZU1fy73vnfNDtBCPV0+W/rHVzL2N5fTV2VJ7bBaNsd7q7Q3M7Ht7VvQOmlW33pkwLqV+smulg2S6bGxFU5dj9u+EjskkBtHE9iU/531Ezcyf3iI8KKI/hklB8dQqKZVOr47EojdWlGVrl/Z+CCjyvFHknp0F0CwcJbPGsSc2RmI4rmGQv2kfqppTRa2BzdTO7kfV1ek/uL2sRYR1eZnr542QHKHHfyMIvUvoYLQuvoTYnTWxtGVRv2aBy+VGguLanRG2uON65g98oCAjc2ouJR6VOLTTiAqWju1/7ceBJoPE82ieNXThTEpcdsYoQc3s/D2I+HHm7zD8q7feI25KzKBD8L+heD2Z9bg4dS6VwXtlrhtrAVm6Yv7+n6xt/l1EIULhggVbBSroVS+jz82LTRzV2QwSiKOuPf7KmcO4KoKan3f8Nbeyt0tz3L8BuopXaC5p/QTvn/zPkKuzVY+W+h1m+FRzRDNufdlAhaxwjuHMHfsgOFGAMZ84zpyB60OWK1Uk1bRWE8w0tGVACKh1xyid4+j/eRxoeJv03AMhVDBwYooROcsQgWb+cukfUIFW3D6BWFbit8+RrsrsDvzHRtZXGPQtk02L3ZUaIVR5Jnmj4wR75K2Nd+xkWq7TmTBQrE9drUOXfrbC6hF7xkP5omg1m55SPqoyyDyNmGqyr9riPjuutARH78BK6pRT6pE5kX0sLA6jOMxRYZ/JDWNhZU6PV8bJoxsRLWagxVVsaIKiV31ln6p//E6+PlkIKyrvmNjUFfWLJ66t4CxX2Po99fesDX/vrWfPt5Sv5OYtPd70Km8/Sgi+nJCD26meppQKKuWK8KpDuhefZxWc4N6ljbftzw66PCCRbWrQandcd1IAEucvzRDx3dHWvwMGuuuf7/F84fAFaHhypkDwXPOfDBDervMolZMlWCNAnbIgHMGyVmTcPcmSicdhdvd12AL/I5cO3+FsLdpNRfzEmG908sCqUzePIrzpmNRfy6HICNv0VG0qZw5QGG1in7mALahUGvzGPLOFWpsn57bjClodR3VdAMGztrJUnMSyUn97+yVGTp+XQ1gQ4trDGI9IoqZ3GkTnXHJXTSEVpNrVM4YwIypKCdsoNqpUrsqS6jQEAS2wwpzl2cIFcW/FcdbPxWBKKZvGG+pRQ4VpN+MfBO8ynSJVORghAu1dw8RKjqULhZYevvzNTm0pzSBzM5b5A6SNQ9k7beiIqxrJhXcsyV4VD5rENVqBIdCBUeCtCdswDF3B98/9dEsvV+S2tLIrBvM8fkLh4JaPyCoe3NVggMapw+geuUBjqHS81U5mJaWq0Tm3eDgUz57kOIlGUJFh94vDwfC1JOfzGK/vDO4Fz+IqDhQyU3AI425L37HWCA8vb9gkrr+sEBcGkAZfooO66h91iTrDX3wvMDcfDY2aBxiChfIc9dSKukfjqLWXQlefyxLraIR8p4n9YrZMoZ9tlZ/T+dqCmEgNi07ab9dayf3Y3q12I4m80bbthrpl6QWK3HrEyJ4fPyxsOn3FRXlD7ZmZwnGtmRLtmRLtmRLtmRLtmRL9j/Y/pBhbK+boCB2r5xI9468O0bjUr6gYWTewkzpxG8fC7I6Lddqhhg9vKUFohZ95BmBmSW1IJLsp6qjd4+3ZHVCBSdgL2q/XqBi7ddL+n3vSGnb90cI37+5kRY3FML3byZ25xipG0f3gWSkbxjFeHhLSzS3ePJRQYTATGoBQUH0x78KIs3xO8YEFtdUVOpfzze/EC/ISsTUQIDPz9qARMIqZwwIYcOCzeLaELWT+yVicfsYtTYjEBVthptUOw0RWX1wM9F7xluKryP3jtNx3QjRObuFCSToj1yV1E2j+2VX+02ml+zAL5r7NjZtE7l3PIjkF88f2oc4ojnisrdvAQG7GEDkJyJaq1VF0K2Z8MIYliJ5V5NC7Y7vjngisiJgC15GIq7Rts0SwcmbR3EMBTOmEFl0qJ+4scH2kxemJDNzBOClzD3Tfvq4ZEXuGoPG7TXgRVNW0P/hBzajeOnrufdlcDzmoLnLRZvFh09W2zXRcDl/iMh949hhhcREvbUA3RNDtKIKas0NhMuq7dIO6r8/geZ9l/GLrUTmJXIUKjrE7hyj+xsjxO4cw3h4C/UTN+4D+aqeNhDct/W2DQHLFjQgVYULpA+NshMQGvhWWqYFrDTN9wzSt762S+Te8aBPfJt9z9HMvj+zX1FRM6Xvc69mtJHh9ckpIo8+s89ngSA6nrx5lPCPNrdG1/b2xya/j03bQYR67/dF7xYRT78/Qdomd9HQb4Uk6Zsew4ooAXywevrAb8zqgIyn5qwONKANtVP7W6LtyVtGg3HgW361HrRT+gYR4gTRc7LfchxWRBVSAo/YQrUE1mIB2cQuAAEAAElEQVT6jFMxFaPiSKbirjFSN41ST2nCBBeWceKL2QnMR7439NAW6if1Yzy8he5vjGCmpDhZNSX6H5kzJdNUF+KEwjuHqHTphPI2at2h0mVQ6TYwSjIuQwXJ2pfOFQ0ZgEqXQXFlSHzR01fTH32M/IVDaHUXM6FTPnsQK6phRxRSN41S84p4jbKLUfYyMe8aotomEKaFSzLs+Vg2eHbVconM2dTaZa71MwC+kCOIf9Xa9GA+T904SuzOsRZoNBAQ1vjEF8397pOUpG4aRfvp48HPIPOrT3ZQO6V/HxHnerLRdz4cr+tbI2h1iO82W97rGLQIJ4Owo4HoovhZj/D9m0WQM6Ew88HWrA6I1oc/V2g/fVwYSG8TtIJac4PsRPfXRwg9uBkrqkrf3zoqflpyiN8xJkyVEGjr+MK19ZP6ic5ZdP7rSENI+3sj6BUXK9YQ8iytDAekD7NHh6m260TvHqd3c5Xo3eMkbhsjvOgQKklW0owJQYFtSJZcNV26vjVCOOeQmJQMZWRRsueRRYfUqxbFFeEgi9j1TB294grrXESh0qWjV8SnVUvW8tRNo1gJjY5na6imS6jY8BWt5tL57ZHg/g1vPNphJZiXHEMJMhm+6Y8+xvxlGZyQglGwKPRpLXsKvSIC5eEFi3KvgZmUrE7hgiGqHTqOLppHPlmCVhM2Nq3qEl4wKZ0jmUxoCK9G7xmnflI/s+vDAfFPtUNDL8v6m5g0ieScAOKWunEU1XJxDAXNdAnnbcLzJvHbx4J9QaVDo9wj/tac8ex4rh7sBfIXDqHVHLS6S2RO/DdUcFBtSEw4AmNHsquOoQTXjz4i87+/Zgc2cBSv1dRaY9Gb/xMhOtgbegpQOqlxzeTNo0TuHSdUaoUHaTU32FfahvSvD3HXTDdY2/01I3GroHlCDwnqwhcQDz+wmbYfjATrQPKW0WC/50M77bAa9NHvbX+A5ATwexx2YF/15vJZQrm690ZEH3uuZdNrnrCBhUsywUa+mRbaX1RrbxUGpvpeLF+VM4Uu1d9ANB8G9mf5dw2RuE3oHn1hM/8gsviehnpy9O7GIaB62kAL89LcFZkWtimfejpUcoSJ6pT+fTbm+9uo+9+Ze7e3ofWoAcM/bWxIqqcNBJjvufcJK4vx8Bas4zcQvXs8qBswYypd3xwh/MDmoA2aawr8Z0nePCqHoTsagoXQwNz6be+zEDXbzMVH4z62taWtgOD+96feDfvWwfjm90Pwe9OmrZldqvn+gRZ15v2xsfkbF72y74Y79W9Pt/ze/Y2RoGYncq9sUJsn2didY6RvGEWrOcEGrZmNrdKz/ySoD31xQo3XfHiRHVFaNjL+GEm9Wg+Y7zq/7W0CvI1vgNH12kirudhRjw3p4S1BOtu/dysmm/3aKf3BtUCgiL75m2I7pLQwklXOHAiCFOWzB4O2b24X/dHHSN7cYCTz+8ufvPdXGxPfY9P57ZGAjQ1o2VSVzh0MmNmMRx6T7/bGveoVXdkhhcrbZSGpZIT5xsjvy1jmt1eznzabz8D3Wqy5bZqteXw1+zE0/LX5MJq8ebRlA9IMtWu21E2jwfwYuXd8n83r/sxfJJvttdS7RedkAfYPkeH7N5N79xC9Xx7GTOjE7xij8zsjARW2v7nwLX7HmGwavYXY3wyDbGSbA1WR+8aD55q/LNNSgxO7c4yO746gl2Rzp296jMiCTXJnndSNo4RzNvHJOuEHNuOEVEIFG6PkBGJ/xsNbiE1bGAU7CBYlbhsjsatO9O5xUjeNElq0pCboxlEicyaq6QTj3Z+fwwsWuz+RJXbXWOPQ2KYQWbTJv2uI9u+NsOyLAm2J3z5GKG9hR9TgufwAgDbekCOAxrjNXTQkDGIn9QdUy8F7fDhuW4NNyp/r2q8f2YcREMTPQg9tCebY8P2bW9rVKNoyz542ELye/qFsktq+P4LjCRJqdYEmdlw3IsEGb7Nd7tFI/7AR7EvcOsr8ZU3zb9ElvChQquYaWZBNV6jgCF2vZ46htPiEb83skNAI9IU8Btf03U+TfLVG+obRYD4zHt4itN0PbA7aLj5lE5uSWh2/bszfJC//l+GAbc4/MFZPHyBx21gwz/vXCRWdlvkucu+4x5Bmo1cc4rePEV40cQyF6IyMiejd4xgPbyE6VROfXbBITNaDtdaHjJXOHSQ8Z2I88hjJXRZaxREI3MWyvttvPY7woolWcwk/0Ai4BkyhJenT5M3Czuez0nZcJwFd45HHUL1hmv7hKOkfymHbt9iU2dgY3yzPnH7Fou0HI7R9fwTNlPnTfutxcij+yeNEp2pywL11lFp7E0veg5uJTTnBQSJ539N0fnuE1E0SDI7dORYEUEDmJNV00apuMH/682DqxlGSO+u0/WAkOLwHfuStvSDMj+EfbUavuWg/fZzi+UOypnrt4e+jQj/b2lLXaHmHHGPk2VbnG/+VsK8dfTja2oOCl52nf93yttop/ThPNcZ1x7+JwKj6UgMabR57MCAw/tI5gy37xOjdwlbo+78vLl46pxF8tzzWRp8qH2gpTSj36Cy+J0P4R5vJXTQU+OjiezItdNOFC4ZaEglazSH80L71la/ZltjYlmzJlmzJlmzJlmzJlmzJluwP0f6QYWyv+7BjHn8sIKd0vSyFqLG7xnDefCz51RHMONSmRdKpcsKRlI4+wIM5COwoVHLRK05QcF4+exDFdoOIT82DQoR+vpXSuScFkafo3ePMXpmh8JEsWs0VfnzvnvbW2Wk++VbbNdpetJh7XwbDS7v65kMQnJASMJM1Qw4cXfji897fKiccCY9sIvSzrUQ8Rq7SuYNwW4NJymefWXhvpgUi0QyL8WE2tbeso9yxikqnilaH6JwUTYYLLpOfzJKYcCiuUlmxSYr8jZJLdM4WnYoQVLoUCh/PBul0M6bQcd0IO/8yS2TOpZ5WSOxyBA4YF05/PyVqRdXgmecvFUExa/sOeGQTWg3cPzoGO6xhVBwW3puRiGO7SuGCISo9CtuuHaJ3FBbsXXDbb2bPC575N+gdhR7agnnChiDr0syG5UMxfuM1H32G2StPoetbI4R+6ztfu/nfvw8j1D2tmaJmMdLoPeOYTWxCiulST6poXuTZFzGdvyxD6tU6+QNC2FGFFJJ5yB0cIjbtYIcU8hcOYUVEG8RVFVI7LUq9esDWUk8q6GVhvNIrLordKAz1i+eL5w1SLOyCBzZhvnEdtbaVQfQ/dudYIOaplx1U09kvQcHekCo/Ohd6SKBvoYe2sPuaLMs/PxxAvPxsUvTHwo7Tdoe0mZk5gs7rR4J+9sV9fVPrbpBh7Lj1KVKKsN7szcamjz1H7bR3BM/is0WBjK/c0YfCU62+2MzA55tPUOBn5fxney1sbb4f+/PX/tjb9jY/m9BM2rE/29vn9mf70wZ6PeZndqGhx9MS2b5vPPAPkPnPaL0ExsNbUI7fgFprhSBqdZfkLaPBfAEEcDafxSr04OZ9RPSaM1Na1caPxsP+2fGCMdr0mtqkhaY/+liwsGk/fRwNida6qhI8a+ihLcS6h4Li/MRtY2heVtFfO2avzAQMWz6ZhP3W47CiGuRbCTBmPpghtcPCiqi4Kmh1An0Xv11L58iamVtjkNxloTdpczWzZe7NLNhMCrJ4cQZHb4gk+2uSPvIsKO3U2lTUk6QoPTwvYf9mgVPj4S1Yb9tAcWWIth9IZL581uA+Is7Q+A5oCJuCsN81i86WerUARu4Tr4Tn6yxckiE5UQ9Ejgt9Bq4ipAP2W47DTOoYBYvFg8OoT22HzZvInbkeJRqm+AlZ/+ywgmq6pG4Sv4osiiZZfMqmsFrFvThDqOBQuGCIWlohlHeDbMPs+zO0v1CjuDJEPalQvTiDXnXR6iImqtUlEr7n6izxSQf7zAGsiEqlQ0VxXMJ5FevMAWopjdi0RbEvJH27Ykh8acGm8t5MANtUPfKMapsW+L21Okz9gxlqbQrhBRHudc+SzHZkXgRT9YoTjLmF94rmXw+iS9PzsOi04UJ6u0m5S0hvrLdtYPq4MKiw68+zaDWIzjhophSuq7bo7/C+DKotGljJXTb5A3T0yzKiqaMIjDo67xDzfDgxaVP8QAZXVQKipPlLM9hh8enK6evh3k2BzxtF0TJyQgqOrpDzNI8i8w7FPo2exysCjau72IbC/KUZYjM2hT6NSM8Q1TYF5fAMVlRh2ReHmflABldX0K7IEJ1zmPlAhu5vjASkNosXZ4h6312e35eEBpCx4Jn2hrXYz28DhPHRHmmIimqHHoz9wkuN3484FPvZFwgttpKQ+OYcvBJekmsbT8jn6m9ah5ZsaN35+79qh0LljAHmD9fpetoU2F/FFfSA2wR1v72VybOeVJn9uyyJCZf8GlAvbMwHPnrBDqsBUYgVVpj80yypHYIKCt+/mfzpG+HeJYKCve11w9iMTU/Q+Z0RSe/eL7Cc8lmD5FdHaPvBCN3fGAk2OXrNZfnnh+n77DAdz9Xo/I7UR4Tv3xzAJVTTRS/ZOIaC9bYNhL1UaOWEIwNRUR/iFs659H55mHDOZcU/N4QhwwtWS21MM+yk7fsjRO4bp/M7MrGHCg7RuQasoHZqP9G7x0nutCmeP0SoqTYkPiVqyd1fH2kRgav/cQNitzdsLVQQiFuoIM7320RNVW9MdX57hOiMFeCIQRjr9KrLiv8rE05yQupLqu0akUWHrm+O0POkSWROJtrkzaNCrfnW4+h43iY+5dD5rBUMFNUSNqncRUPUU/I9vspvfMqSe/BS1B23PIXyyycp9xpU29Rg49LzlWGBC7zksPZqwVy339Y4BOwNSfOtWVR1f2Y88lhAYfl6retbI5TPGhR68zce87q+t9l8WGLtlP7gOZrrRprxv9XTBrBiakvqutknXI/55//H3puHyVWWaeP32Wrtrl6TzsoOioGEpLtWRRISsmeyhyRASAAVVFBwRmXmm9Fv/H2js6i4w6gMILJDyJCdhEWkq5d0wiqirNm7k95qrzrb74+33rfOOXWqekkAxbqvq6+kqs76Ls+7PPdzP+4niapV/Rtk0lF9MAdxbxeqjilwDOpIrAlB2tMFKalDyGqofrgNYoYo9rj7iPKQsf14epQ8h5y0UdfWDigensnWUkgpDVU7SByZ9PsCVTKblyKnE1lp9z7IXpHxt8uVjRGOXUT+uu7PhX4UWxdiZRBbOhXJVUEkFxAamhT9A6Fp7ukiEuobwowyJs9phmtrB+ofepmdG18bIu76PI3NHSXKN/Knp5gmxvV3Rwk99OoQMosDRGp0GKAxO8DQstJ2MFLySoHS/ox2aTiLKaOdKQdKKR0pqD0wUqVSKwgNI7U8iNg6MulKGjK5G5FYE4I8t8U2zs/ZL6P7lggccQ2pFSSZse/9LKOE0ucW93YxGlx2oR9914WhXN6M3hvCyDRIyC7yM7rewDVh1v76rw1DnTmDlW12kZ/9X/GKiK0PkcR7V4agXN4MeW4L0ktJklzn9k6IaRWZxQH03hDGwIYwau4nsQU0aSClB/VeH0ZiTQiNd0WhzG4mi40tHUQ6eJwDzu2dplgzZXYznIOEcqM6iDph1SNtbAFDqWfex9vh3NGJsT9rhfvJDrbBZ6R/WRc6QGGBG1sfQu19USbNDIDZbOP5lLOfrRPh2trB4ouoPYyfYd4aMlIw7WLlAEJVN9La+KxWiFGI6yZqc2J1ENyLL6Hu3iiydUSdT9q9D2JGR/URYjOSExxQHRxUl0AWP668bXryFWgioaJpIkmmmPNxJHFut8Jo3AAw6but8PQoSNcXpjG+BwvJixv/Owrhuf3wdMskTrFHQbqBTModCTI+56p4NLyeA6/oiE8ksY/ebhWekxpRsUuocMQ1pBsECFkdUopsOOp5k+nqV+HpkVH9cBuU/OJWzJA4ldrfRMlCw81hzCtEzjk3r4XIePdoyFVziJ3pZDTm3Hw/HHENtW/niL1M6FBmN8MxaNigeCeHvuvCUJ08qo5qqH9DQe1bKtwniJpozstBShH5bF4hC8u6e8i8LNkkoPYtGVKKXK/u3iiEbJ4yvCyAMb+IQnHxcCR01L+ZRf+1YRI7ktRR856C+rujkL2Fsab+j1miWOohcVhClsRDpZryE/ljGrJ1EnJVPAbOEaG4OHh7FPR9SoS3RwOvkE1aTiUqg5klAdS8K4NTdTT8MsrsZe8NYUgJMl7W3kdisVUnx8YMI6wUULrQ0S6bXnSscaEDAOofyPjBtb5sG9+juAxJ1/M0NscLr6PuHjIOkU00snk47o5WolyZV77jlYIt9WxuN21+K4ZNkbp7omh4ncQ/nX17lC2ac/P9EDMaan8TZTFV3TdHoDkAMQ2IKQ3JVYSKLuTMVNGRgHp2Rvr314AKja2CCiqooIIKKqigggr+llHx7BSQWE52vdNLA6bg3NrfkORcxt196YXXceLGMFNkoUGYdKcts4TkA5D2dEGTOIjPdEHOK2sZ1Y2swelifmVLd8zEZ7rg6S64HrMLCjuD3bdETOe6tnaYqBF0h1f28hBTWlFQZWJ1kORI6FfZLprjd2alI9P1n+qA66mOYSX6y9Xw8OTz7PCqXkhcVs/lc6aQ3UN5bgvbGRWyRL1DnTkDzm2dkNIaCz4GgGytVKDNNApsh1bI6sguJMoevgdIkHtyZZDtsFpV44C8IlC26OsiVSgKquZTdDwNyF1SHFxNYZeQcaiAbRqg6Nncjsa7ouB//5LtfYcD11OkXTi3F1S6qGoYYA52dG3tQDavREVhbRNSUkdsPcmbQulJ2TqR7BQ3ivD0kODREzeSHWbVWeiK2qXTwctEoz+2PgRvN9kNTTeIcPVrLNcDQHaLXAOExpGYQLYbnds6TZ4m+pzG9zG+i6u/oPAEmNXYaNlY4d7SgWQTud+ffxKEI6GxMsg0ELWj5PjCO7m2dhBFwcfa4emWSe6RJQFGM0vNJTtpyQlAsolH7yU6oJutqPRioYyPfLPQr2vubxvRbpZVHWu4v1HU3RMddtsqp7DG7mko61z18JR0nLGR7d5JSQ0nP1/YfWfCG3kPQWoM2ffiNOJ9ccTzeUrWhtB9SwTJlUEolzeTpJnjJZL75Gw3sov8zMOpeAQ0/bgVmVoezj6Z7Fh7BNb+FQ8PIR9QrQlktzXnE1B/dxTxyQ7IVRy8j7cjXS9CcRJlShrE3LeJ5MJRvAJUJ4/kqiBUBw/3FpKPJOcTTLlrBs5zIOcTkGoUIGYI1TPVJCHZRD57usmDcCqh/wLm5NTJJtJ2040SnL0y+q4jAceKm0N2oR9ydcEbKu7tgjPvbfU9SJKKUrtK3z2zOIATN4VZv02sDhZsep62l1gdJMHOlt1pZTYR2TAGMztsxDro7rXiJrmLnP0KyeuRLxdnv0KSiR7MwZt/f6vghdFG9F0XRt+mMHqvJzSj+ruJShv10hrh7SbvL2Q0k3ojHYsyiwNw9RGVs9y8FjhiRIXNsbMTAxvCTAUQIN6S3s+FoTo4uHtVNN4VJQH9Lh6uPuIBSOe90bR8eUVH411R9F1HqNk9X4ywsV+pEiDPaUaumkfNOwWRgd7rw1A8HKPjufo0yHNbkGwSSA6bPgWag0fsDNJmKL3RsbMTdfdEIeQ0aCIHcW9XPv8TsYvVD7exuhUzGmreU9F/ngRXv8bEZmh9eo/JiK8NoeHXRIxBTBGBHOqFz9SLEGSd5ABycJB9xMOkOTgTJVVK60SJtk+F7OEhZHUoLlK/2QV+xNeS3FrJJpGojvaT/i2liYfO/WQH1Fkz4D4pkzJukODMe+RUB+m7qRVBeI8XKleuEkneQ1mHFFfAyzrG/agVZ/xrK3SBg6tPgfvJDrgGVDhi5Flz1QIm/EcrFCfxsPkebEPVUYUoMz7VgUy9COcgofEDJL+QlCThALEzePLMCQ3j7mhl478RxrkdFb0BiFoZF33ZJEwAECqb6TP9vaOQPzAdOZ+1MQoq+KH6LyT3quWYuAdVXeVlHVKKHF/9UBt6vhhhCaipLc4u8rP+SXPoyW6O5epyDqg4+vcRaCIHKa/mR8f5pp+0QvZwkJI6E18x9qNRoSJQUMDguQK4q0PgVOD45SrOVlrQ3eyAkANUByAlBaTqpwEP7EXs76aiOq4jMVFA410d4K8iNAPZy4FfHWRSuYNXh5Bu4NHzfyNwvUD4+lKCZISlHZrTgVQTh5PfC8N7kEPu6hB0jkNiEgdXL5GNBIjihSZxyPo49PxrGFUHdRy+PYJJ3yXZc1WJcE91Aej/FOC9gCT7ytZy8OWPTY/TMOF3OjidxAP1f1KAlAC0BRcDOwpJReNncpDigNTxHvDiXvSvmgq5bhLiZwK5cQrG/F5EpoGDkAMcgzpqf0O4p4m+w8Bje6EJHJm06YCYAoSzyaCSadAx5s52ogb39QgcAzoc+cRyqSYe8iZynGt8CK4+BQcXiDjvibxSx1gO+qogZA8PXgUccRXHboug9m0F6XoBJ78ZwcTvtSIxUUS2jkPdnxXTRJtC//Ql4F58CZ4eGd03R1B1VIXi4hgFCsi7l3+5HQCQ+MlkhIKvYPDzDTiSqMGJA00QUxzkC1O44vw/4mCyDn96S0PN2RFkL43jR9MfwmuZyXjgjnk4b9ObGMi6MZh1YWLVILreOhMXn3MEdeLbeOWGizD37D/iEu9BfGffIkwe24+Le0+gYy2QreHx3nfCOOufo/jTnQGM+x2P496jwH/vxbGbpuJ4oAnI8Zh41klkFRHZZxoh5ICB6TlUNyQRP+lFdWMS8T4vIHMADwgDItw9HGR/HKoiQElKmDC5F0e2ycCP9+LIv30Cx8efgQkTuvHn2TNQV5/AvEl/xMM/ngbcTdrGyYsEuCZx8B4GDv1TBNWHdNTeF0XvRQKcAwLq3pShuqkaC5lkyVUcBr4egZAGema40PiKTuhSOnDkMhH19WEMXABUHQIOfjsCRz+grg5CcfHMJZ67IYzEalL3jntIvRz8xkUYN3gGGu+KoufLpB4TEwTkfIC7R4e7V8PgOQJcjWEobsCzMohMLY/kRA5cnusvzyV9HCDUkWO3RVB1VEP8bIC7LozzbyaToN71pN9nxqroHatDMMyHyGKMR+6qEHSBgwNg8UXgOGR0EgM3/hevIPeFSTj3a23o/cwEU5vsXT8NvgcPovvmfBteHUT8DA65L0bgOVGgFX3iQaBv4jgsHPMqfvY/SzF3bRsur/kDbmlbhxsv+R1+/oKGnuYwPOcPQNc5NHhT+LsJr+AcZw/+6e4Ifv5uO657dQM2nduGH21fiE/638Mbh8bhW/6n8MLgJ/D8u+fiognHMMaVwAsHz0V6wIUV0/fDySsYUDx47v3zcE7jIUz9tobOvjORVUR867z/xY8OXwGflEGjM4HVdR34z0MLIPIqzncdwPZICN+c+7/4waM6EjvPQZMnjjO8/dj6x4sx48yDOBirQ2Ds+5A4FbsPfhIN3h4s+N4A7vrDpZgy7hjOrTqJJ964BOeP78GxmA+pt48BtxbKTvbyJmN/+PYI6t9UEZ9IJGSz9Rw0gUemkUPVYQ19n3QQu5TW4RgkMWjOfrJhkavhUH1YQ9rLofdTEib8J0lEmK3h4QTgSOjovciFXJhwz7PrQpBSGhQnB7mKQ25TGHIVh8REN3wHNbz3/8JoeFUH10viA9JjOfje03HyIhGeMWFUHVGgukjsGy+TjRs+xyE1nkPiy2RS5OrTcPj2CHzvacj5iM2NTxTg6tcxcI7A6L5yNYdcDQf3CeDY1yJQ3IQG4p7vh+9BMiHRnEDVEQ3HvxIBpwGq0wVNAo5/NQLfQRUnp0qQ3yal2X3DNKR8kyCmdHR/O4Jsg4q6V3m48vSV41+NIHGGhpo/ceBzQHKsgNTniP2W88lM41eGED+Th+e4DlUCXByQ2hiGJgCpcRy8R3Xw14Qh5HQc/0oE437UCuHZ/RjYEEb2CImz7F89FTznQJbSydaEIHs4uE+q6PlyBJ5uFakmAd5jKvo/IaBpXw4nbgrDOaBDXx6EkNOQqRXAq0QxLTlOQONd5NlyVRzSDTyU60i8EFctIH5jOB/zoiN+Bo9cLYeapjBSEzjUvEUkwFUHxyguOgckJ3BwxAExQySQMxsK76gPkgVn7tIpkCSS+Pro1yOQqyRw50SQOENHw2s6OJ1D/3kiqo7k1QWvDyMzhoOY4fDOv4cx8XdkgVf3Vg7SbhJXCADjf9CB3lsjqDrCYfBsHrGvRaB4AGc/8jGzOqS0ht4pDniOkw2l+NoQZDdHKFZ1PPr/MUKSh14VgiZxSI8hdeoFkBwvwDmgoe+6MDgVOBFUMTYqwBlX4XmiHfJVIcTOEuCI6dA5YvfFtI74GRKgkfeoPqIQldVVQfRN4QAOGNNF5Ir7p+iElphvx0daeEzeo6LnEgmT/x+xycICP3LVPHSeQ9URFclxAuITSIJcbr4fbllDfJIDUkrHiUtEiEnAEdOh5dXseqe4MPanrTjxtQjGf5/Ez3hANmBq7m/D4FUhJi+fmXURfE91oPcbEaTHCnD1EtsxcTvw7vfCaOrQkBgvQVodRHKcgKaftDKKZM+XIsjWAbVvaej5UgTe4yqky6YjdqYL2VoOY15OI1PnJslJ0yQpb3ahH76DGvo+KWJ8NE1ixgSSzF3+xXgcbjoXE2pjOHiyDhemO4FrAT6jQzznLCjvvAcA5ljEeS1wDOagyfkN5TnNcL3fzzbYuJaLgM4XAJD2CQCxc3jgzbw99ZB/ExMl1O0jCw8AZKGsCOj+5wh872romwLU/lGEsioIuZq8uy4AdW/m0Pu5MFz9GrLrQ8zWAoSuHjtLhBvAwHkSvMc1HP2MgJq3SKyuI64j6+PRfXMENe8pQH5/rOeLZC6b8Y2esFURKKigggoqqKCCCiqooIIKPp74GNPYRrzYmfhf7RA5QleS0gFIuzsxaTfxKihuEhQY0/vxNgB3vwr4gKojav54HZ4nDMlA5/vBKRqkPV1wLSJqObl8gs7UWAEN3WpB5WJdCO4TZDdASqiIT5ZIUP0CP3ShQP2gx4vLAmj8bxIgTpViau+LkkBmTYdzeyfqQKgDUlIDrwhQXBzGvCSbqGzy3BbU3L+P7Gjmg74TCy7GhPuicC/0Q/HwUPP0mrrHXoGPO4SGIcqQJsMSsxrc75OgPqp2k1gTwrg72tD7uTCcAxoaftmO+JUhRoepeVdBrpo3qeOct4v8W/ubKGpBXKNSQkNivAhp9z6M300oYcZzqo4ocPUXKIO5as6kusS9+BJ5/2qB7VpY0fCrKGL0ejcfwkGuDkASVehFFd5hx5EwwGO4AMfIFz8Gvg/iYm5AFP2/Il/7AMQBXICTyALIApiMPrwB4A1MwHkgibNe1Umzrdn8CnxPHgIA1B8Q4HsgCuj9OAjiIfDdWceegah/kQDEsfnvxuf/rVscMClS2aFx5gQcATB2q4iGKKG5nTmvBbpYg65tPBpbsniPlsVhwJMlAc/Guqt/g1AG5DnNSDc4oOapLroA+N6XkUqLUJwcxkcVRj1TZjdDdRLlJHde6YgisTrI1P4AQoug9CpaL+Nf1OGcQI7xdJNdRm11EGN/2g55bgt4WcP477ej/9owXP3Eanm7VTT8mpQHVVeatLtQFuN/0IqeL0Uwrk2B66kOxNaTwExPPmjbc0TAmPeAxGDh2aofakM1zIH1mSUBOPsVZOsl1D9Cgk3TV1wE3c0RNcL/2AYAiF9+PvBMJ7zHyPWbftKK7lsi8B5TMfn/tTJlPPrOb64DfNxxbMYYTEArXvtP4DV8EufhAJ5YfwUueMBMLUsvDWDXFh8AHzybdHzj7CDG4E1sRR3ORRQygPNwDL/FJABJ1G70InnPCZxcFsDkfPB4W16dLbvgYkze0QkZQBd48DgEYV4L/mPXxUitOBODOR0ntnbgXzEDQDd5PwDnow2PYyxqNgBV//IOkgDeAHAuDmAQQA166aYiJuAPyCwJYMdTtTgDryIO4CUA5+AlqADG4ih6w2avmGfXq/Bxh9n7Vh8iuWfkq0MQckDNuzmIz3SRwP3ftkFcGYRjUIHqFghVJUcSdXIzZ8B9opAjilLYPJvboebpeNUPt8EzcwYoPYvSw2Qvh6qjCssdQfNKjG9V88IrRGmr+pAGQdYxriOHxAQJusCh/o9ZpMc4oDoAVx9RfxKzPMS0BkdMQWKiA868N8XVn2/vPSRo29WHov6dWRyAp1uDkDPTcquPKIyCpOSVvoSshtQYEY13tWLw6hDGtWeQfIa016ZfvQxxxXhGw5XntiA5jmdBxFTRKpO3McrlzRCf6SLB6HkKlpArCNHQ46haoXUsyebVruJrSbA2VSyse/QVVHGH4Mz3hf5rw6g6nENiogNjf0qureY9EpP+jfSZ6sMk0J4KIKgGtUBqm6w0TLo7bvx30ndbkVkcgC4CVccJ5UravY+pwCVWByGmddTdm1cyXBMiVMIn2kgeohiPvvz1ZS8PNU9hb3xFhuLmkW7kcc43o8gu8CN2loj6NxVGra0+oqDh151ILwug8SVDcuk89X38D1qRXBVEYnUQ9W/IyPkENHVmIfsEJMYLENOElppZQhTvlLUhSAlCC3b1KajevQ+J1UE0/IqoSWYaJShODlVHZTjiAsSUBmV2M+rfyKLvQidcfRqyPg5jowI8PTJSTRLcABOVoZ6F7AKimOfqJ1S4dD2hbWbyal61VWFISY3YlIV+THqWQ85LaKbuEzKklITYZBG1b2kYvDqExleyGDzXgca7yLu4tnZAyKtf0jEosZqoorl7ZFQ/1AU130dpotSad2QMXBPG+O8TFgzND0OFjGp+24bM7IkASGJv9fLZqPsTyXfl2loQkjr7m0TVVsyS8UhfGyK5hY6rkBIKqh/aj9x8PwbOkVD7Vg6axJOkmBvC8L2vQHGL5HsHD03icOLGMJyDhEbomO9nYliewDhS1zcdQwOXIfW9cBy6t6VYO1DeeQ/9eQ+qkZVCqer8BedCBRFJMmpL8rE0uE+dC/xhLzzH8/m83tMxkP9ddRXEKIACo4jONbm88t853yD37L82jIn/ThRZNQlQ3TyzhanlhOVEaZLOHZ2opaJcA0RN17k4AE7NJ6GPk+96bwibBHbG/rwVyuxm5CZi9KgsduxBjWR2kR/eYzloNnSomt+2YWBDGC4UqxEZpVaJgewEjbypffwVeLlD7HffgyTZVqZBhPfxfRCvLmSmB4gyRdNPWpFcGWQJ8IzStBTWQU9KaXBu7wQ/pxmqSyiK2aFG0/VUB3u2qh2vAlwdifFAYWJpRHJlELrAlYxvAYhEr48zyyfS443caZclKR2NuaHPSiV908sC4HM6mxDXG84RsqpJ4lCuFti9sgv9qHqk0/QeXPMU6F2vl0yS+mEiuTIIMaPBua2TTK62FmbeVJaVKvSMBsY2YSwjI5zPkgWt1Po6wJFFlDGJKt9ZSEzm+1+y6E0vC5gmC66ThC8u7emCtCrIyja2LkQShlruSSfxjXk1ZSmhFFSYtnQUxY3U3E/6Gk2uBxA1tqq8TDoFPc8YC+eMaxAyWpHUb6mElUapWso5zuUnXo2/eRmeWY3Qn3216DzjgEMnLBLMfYgmc6TfVT9D1NiMnOmmHxfunxorFpVdKdBnzRoWju4tHUy227jpQCdq1nKm6oRGGWh6jF0iRQo7NbaMZaFtrLtyMMZRUZtnhFxlz92mUtvu/GcqRW+9P70e3QDJLiCLGrlahO/BfMyfoQ0DYEkFjbLs6qwZbBAX5vuhC6SPeY+SvuAcUCDu7YK2lJS/y/K8dSCxKPzzB+DIS55rl00Hv/0Ak7BWZ82Ap0dBzf37kF3oh3N7p8k+DlxDxh+6wEgtD4KXdaJcdul05PJSzVWPtDHFpewCv6kuuPl+9N4QRu3bWShuAfKlU4AXSMek9iKWpxrXWt7BaFNoAkBTolWDvSkXe5ZaEWR2zhFTbY9RHTwkFKSs3fm6zSwOsCSjAOn71ghLKpVNk3RSJFYH4eoj9eTuzW9o5GN+qJKUa2sHmzzTSa8UV9n9XFs7WF9yDCrMdjp2dsIBQM3bDimpwZMiI60mcXAMKnD1aayN18z3g5c1VtaOnZ3IzWuBs1eG+4UD7HsKGifKkoiCyDa7nyR9gNpTtnjKv7exHdJzFa8AXtFRlz9GQqFfpBsljP0pmcyOuZOo5Tl27YO8Ksgk5zOGjR7njk6Is2ZAeJZsCDgM7VW7lMReiWmixiamVQjb95PnXUbipbQFflQ/ROKek2MFyD4RjXdFzTLj+biq6ofJotJqx+hmRLZOggf5eJf8+1QdsZdfNtpg4dn94A32K90gsjZV/VAb2wipfoikReBzWuF9d3ayTUeK6oNZCM/tZ/0dIG1+zJ1EqjyxJgToOsR8yhCa5N0I5/ZO0DBjKS/HXi6Fhfqnt03y1EbofyDbtO5WMv6Ihr7pOU76gXcnmQt6H29H36YwG0eo7aAS0fQZXANa0Tjg2dwOj+Xe1H5SdUbjGEEXOHRhZXofJ4/6e4eOEy2FCo2tggoqqKCCCiqooIIKKvh44mPs2eF0XR/Wo8ZiMdTU1CCw5DuQmzzwnFSRahTgOyQjPlGC93ghuE59dCc6sBcXz/kKmvYeYbst1J2YXBmE6uCgCyTAUXVy0AQOnh4FvTiGP2y/AxfP+QrqhfFQnTwS4wV4e1Sk6wWS3CoL6DwJ1BIzxA2siRzbRe+7Lgx3Hznec0JluzbJVUEkxgvwnNCgiYD7hEJcyb0KcrUixKQKx659JAFpWofiJPQyujrv/fQEHPj9jxHAbPi4Opz8fBiN/x3F0fmT8IcddyCA2RBWz4f3sXa2w5hZEoDi4ky7KjG9Hx3YiwBmA+sXwHssh9Q4BzSRiCcoTqKVz2lA1sej7l4ibODqIwo2sfVEIEJ1crY7wYNXhyAliWpb7w1hNPwqakqeyJ5jXQhSWoPOcVAdHFInD+HVPT9CALNR0/IZ6F1mhbFj+cBFCipQQN/Fx9Xhw4Cx/Kz3LPfbB3VP4+8AcPGcr8BbPwmOuMZ2cPs3ElpJeqwE3wNtGLgmzIQFKM0gu9AP1cXD8wSpYzGtQxdIG6i/O8qC+enO3Ykbw3DEddT8lqi61b4jIzlOAqfpiCWO4M3NP8T0z9wC7hNnFnk4Y+tCUNwcURDqVRA7Q4TvfQW8orNdpcSaEKSkCsXFg1d0yB6+oPvvIwn8NKmw+3Ro2WS8ufmHrIxomVw85yto1JqQ84mITxLhiJNkqDW/bcORb0Qw8d9bcWLmBLz87I9N5UvPnwI/XkcnApgNfs181pes7fGDqvu/RhjbI4BKmZxmsLa54KuocU9EuoHPJ31WIO0meahSjSSHDEVyZRC8qsP9ZEeBUrSl4BEB7JOK9m0i1DUiOKMhU8ej5t0sej/lgv7H95nN/muuX1qe566/DWcebkD8TCcrB3luC8kdlN91duwktLXEOAGuAZKPTPYQ8Rw610gvCyBbTaiRQlpFYpIDUlKDI6ayRNbZegnOPplQmGbOQHK8A7oAcKp5t1oTCF1JTGuADmhODu4niQqgmFaRGivB9yDxmukCoAscseHrQhBkHZkaHq5BDWKyoPYaW0+ofO7jGcg+B5JNIoScDnDE+5xcGSTiD5MEjLkzyt6LzivSSwOQvTwccY2omOVzvzkHFCTHSZBSGoQsGT8UJ0+S/V4bhrdbgewlggyKmyRPdfXKEJ7dzzxQ8StDcJ+UEZ/kQN29xFskuzk44xqUx8ncbuqsr6CBa8LgWU5UHyHjjpTUIHt51N5HEpVTLzllnhi9brRsvI+1s0S5UpIkJU4vC6D3QpFQTA9rcA6qEDJ5tb/nyHMqTg54YIetvT9d44B1/DkHn8I7IKqs9LtPLLsVk7cUGEix9SG4ehUkJkqQUjrxcC30Q5M4xCeKcPeS5OG0rnlFL2LPHLstgurD+TxQeW90ZnEAmTqBzRl6vhjB2J+3smSrxvur2Qy6Hvs/GBwchM/nG9675uf3F3753yA4rf718lCzGbzx038c0f0+CoxYp87z1D40/JokX2v4dRTS7n2o/58oMvVEpcP7WDtx8YMkFU2tCBLjszTAXHnex9vhe7ANNfeTJIr0X+eOTlRtJ9SXXBWfT3rIw9tTcNl7ejTU3x1Fw6+ixD1bTWQW6UInuTIITgXik0jWeSPdw/tYO5p+0opcNVlYASRjrewTSCyDlOei/zoKZ78Kb7eC9LIAfIdkJNaEkK43J19s/O8ocaHnZWD7V02F9zGSoX7gPInJj2bqSxdzzsch1eSAmCGdQEyRxFHex9vh2dwORz75Km3Q8SvJJLj64TbU3kfun11IpCXjV4agzpphGiwbfkWMFZWeTi8NoOdLRKFGyOlINQhQ3GShaExQRxc6yVWFxJzGiSW9tuld5vtLJha1gzyHSKpmF/qHTCpa7vfcfD+O30reSY5MKXncSFBOJnsoKE4enp4CDSCxOoi6e6KQ9nSBV8j7GpOKUTi3dyLr45FYTeRiPZvb4X2sHfV3k8SpUkpDzsuxOpGSgM4TmXLXAFmk1N4XRc39bYwmBABKXlqXlnf/xjB8D5IktLX3ReHc1okxv4iSZL+79zHqSdUjbWwQdm/pgO9Bkki2+uE2NPyS9D+aCRogMVQA0LdmGvRPX8K+d+95DcKz++He0oGxP2tF7X1RKHnO88R/J3z/nKfQt4wSyUbkLp2CqkfbGfXE2h4p7CRJTxcySwLDSipK+z49x3qNU8Vok4pSGPtTZnGASdTTujdKEtPyBszvFV8bQnaRv0ium9KYaKxOakWQTP7ziWRTywm1J7M4wOSSKR3ICmV2M5TZzSx7uDGRb2ZJgD0bjTvILvQzyXp5LrGN6swZUGfNIIluVxWeASCUpqGSD2cXEpl+ep3UiiCTtfXueBWKm4O7V4PvwTbEJhMij+rk2ULHWj65eS1wxDUobh7K5c2gCx2AbBwYbS4A1P9PFN5uhW0M1v0xBeHZ/XDE9aKkolbIc5qZXDRtd+llAVZHRtD6Mda3HTKLA8yWGGFXh7H1Q7dT2vYAgFMA/oUDUNwkyWZ8bciUhiJTL7D4mjF3RhntjNJjjRS22t+QRJrSni7U3RMlC8UGkSRfrCOkFmkPkY1OTHTA0y3DOahByOn5jUcdjpgKKaWThLDbO6E5OOS8fKEsGyVWZkaqUXppgEhXixzc/Rrc3TlIKYX1K2e/CiGjgWt9mUhZ3xuFmCWJv3PzWkhKga0dqPtzDvG1ZFMSKEgr8zkdzsHCRq5rawekuArFzcPVr8L7WHuBmpefG9XdS5KSO/sVSHGFbZoJz+4vSCEv8LPjnUz+WEHdvVET/cr1LLHpvEKokwCZuKeaOJz8QhjeHoVRRHWRR9+mMDSRgzprBlsUsnrKJ8ql8adCRsfY/Tk0vJYjyVo9PDQHj5MXu6BdNh1STDHVcynQdAas7SwJgGueQpTWjAhNhf7pSyCcfw4AQI9MY3LvRmQvPqPoO0deDprZzzoechWR0zcmqHdv6cDYn7dCkIkqr5hPyksTCwMFuzn+B8XjmmtrB9wnFQxcE0bPlyMQsmQ1rkokIax22XQkVxF6bvVjpanUQ6IiPV1BBRVUUEEFFVRQQQUVfCxRobEV3FwzsZSpsZU89hTciKXOpYHopUDpWsdui9iujEsha1G4KoXEmhC0h4d2m+KqBabkdnb4S6Pb0ADa7tkT8eqeH+HiK76C2JLJqHudY/mLeq8PAzwgezgWQA6UfpeUQdmnHI5/NcIUi4YLes/pkVvQED1qUjayPg91+wOwDTY3wngsABP1byQ0NusxRtEAGlT9QWO0bYwGWFpBA76N9Luh7kk/n7fmNpz16MGy9y1HYzsnvB7vRB8oeherAIndNUrBji70QcCoxleuT5Qq99FiKBqb8bly+cB/q7jFSGHtPx81VEMAeDlQhbSRwK5/ZRf5mRLZBwlj3dHnmDbzFox53ixEMpS9A4YeV8s+h0XIALC3b0b7XAp/aWNiORgD6P/SYazf02FjrPVEKZjGNlkKVkGTU0WpNmP9/s8/C+L8L7VDD08DF32ZHad95pKiROQA8eyIJxPof3PfkDS2AGZD3bSQidacKuzEZoYDozBF+vKL8OLeb4+KxvapL46OxvaHn38MaWypJcOnKQH2dIvsQj/SywKmjNUAWbAYs95St17fpvCQBplSqoaz0DHSCuwWOkZ1IvoM5VTVjCi30Dn0TxHT5+xM8q7UBdp3nZkeY6QaUN62EfQ8Sj+wQp1JqB3v/X/mcynli4KqAVFKRGK8gMl7NEbTyy7ww/d+Dg2/jJoWOuXgeaLdRGWidAY9Ms10XP0bxaovRiqc8b1j60IsMRmQV0aDWdkoOb/guk4tD8K5vZOVa7mBP7EmVDRRc2/pMN1vpKB0GuMEMjHRYTrGlg6yyI+BDeb3NoLSXIzt1HRNG4rKcGEcDCndESiojJVa6JR7Bimpm6gqvZ8LExpTngqSWBNiand2cEf/bPu9I64huSrIMk/bgdaBEfG1I1volKKM2V2bgr6/cQJQbvE/0knIqdLY6HNR1SiAJLPTPnMJgOI2VIpmZrKl+f5D67r/2uK+Q9u7nc3KLiAUNGq3AJjoJMY2VArK5YXjhWf3m2h3xvsYkZxQ2LxLLw2QjZ1hIj3nIiizm3H0HyJwbussWuj0fLnQh+S5LRi8OsRoc1Z6Wymc/IL5eewmlc7nSP859jVyv8GrQmXtXXpZgEjXGhRVR4LEmhBT2TJC3NvF7BItZ2qfjf3FSG+z2jG7Z8kuNJ+rzG7G4dsjRcfZIbkqSJKF5+l5Vprg4NUh1rYGryYyyeXq5uQUN/s/HR/iV4ZM70HvZX2XEdG8LX3QOlbYUbvluS2IX1l4dlq/VltF+xilh1rRfXPEtv9SZGZdROKR3YSPZmyTJ78QtqW3SnGV0dgA+/ZvHPeOf8X8DLQv242ZlIaXWBOCEv6U6bcJz5B/6UInsToIhKayhU5uvh/9G8OsrrjWl6H+6e2S727FcBc6pejP3TcX2jFd6Jy4qXCsdXwz2jTazuj8NLE6CGnvKSzEKzS2CiqooIIKKqigggoqqODjiI+z9PQHQmPrnjMRrz49OoWYU3Fnny4aRSafwMmaM6MvMA7723+KAGbD8Xfz2G6s8ZmN31tBaQVDvSN1ScpzW8CpOtKNEpwDhdwEVqqAdtl06DxXRNkwqvwMB0U0JEvOAivUmTNwzHcCf9zyww+VflCu/IaiMo3WlT9SGhu/Zr5JjW04GC7txgpjXpPhPq8dhkNFSC8LQEhrphxDJ24kuSUY7eya23DW+w3o9p7A6zvuwPTwzWhoO2a6Dk1KWOp5c/NakNn5NDqwF5PmX4XDO3+LAGaj6rOXg3/hAFP7MVIjRms7rIo2RtjRXPs3hk8bbeGDwnDV2KwqjaOhdFEMx/5SZSY7GNvfaPtCbl4LeFlHplEq6Y0/cVOYJUq0Yqj7MmWpIdpaemkAnFqc1409p4XaZcwLBBTqYSja6+mgf5W6x/GvRIbtyT9V0Pe45NJb0Pj7o7bHjHQ8Gw5Fz06ldDTHfxD0ZGsOLgprH7Kz/6cb1BNL1dis7Y1SYYcD43sZzxvp2DxcGpsdNUw472yob71re109Mg1c68vDUmMr116Hi1K5/UqhnA1VZjcjK+QQ3fWtUdHYpnxhdDS21+/6mNLYStFGSrnCrW5jAEUKOHaqLfQ+VMHk5BfCOHFTmH2m7lrqwhxqoI2tI65mI7Ugu4hQ6jKLAzj5+TAGrw7BtbXDNPBQF7cxiZWUMCf6tIOVQmGlFVDlsNx8v8kFXvVIG/o3hqFJHMS9XUT1ysWz58j5RMSvDLHy5p8/AOHZ/ei7LmxybRsHBqsb20j3AAiFMD2noFKSWhFkieOMtA+qekSv79vySvlC+JBRjg4FAMkmoezvo0XfugI9L/fZKURasgSoQhR7JqoQNZZQ3IZSh7LCOtAZXf+ZWYU6TawOlqQ8AoSKYKQW2KkyuZ/sKBrUaKZtisbfvAz+hQPw7iDKioq32MxQNTaA9N/Y0qmm3433qNn5J/Z//gWzi/50cMBLLXSA0klVR1pHf6mwTtyMCx15TvOwKZHqzBlETXChn1Hh7FBqkAbMVBjh2f0l751eGjD1HwrtsukQMyp0kahaGs9XZ82AMrsZmcWBkgsdel9qi42UGmo/7Z7faHOTK4MY2EAym+d8pYdX6yaI6jYfS+vBdhFyawT6py/BwIaCzU5fcXHRccNFqUn6SBc65RQIgUIZZpYETHQu49jneOF1llTTONbE1odgt9CxjmtGKjij6C00H2OkE7m3dBTRqaxjoxGOmP24H5/sgDy3pSy1FSBzFjv6mR3dkiaYNdpsPTKNtUHaPnPVp3dMM87vaB/yPNFOFGv9nyw6PrO4QIW1ezdjmWQX+W0XOtpl0+F6qqNI+dGOskahBC8c1vsYFzrCeWcDQNFCx0i551pfxnDheMF+vjEU5dbU/utI37faO0oxtM63jTaIlhdVtRT3dsG5a+SbRCZ8DClsQIXGVkEFFVRQQQUVVFBBBX/TqNDYMDo1tgtW3IpGbgJ0nuzA9l8bhuzlIKV0SEkNVY+2I7UiiGQTD14GdAFQ3z6EV5++A1MWfBXCOWdATOtw96voP0+EmAY4TUfVMRXuJztIUGAdV7SzbFSJMbpGaSIm4+9WVzelE9CkX54n2tG/MQwppeMkfxRvPfiDU05i9ZeqPDNSGpvdOR/Fc34Yz3MqamwfNrKL/Mhu3W1WpVvkJzkftnSY+kQpSlb8SpL0TchqcG7rZHQxqsYWXxsC9MJufGZJALn/3WWrxhbAbAir5kPnzd7Nni9FMPZnZPfYrnzLqbF13xJB04/NO89/qf3qo0AlqegHC2NbE1fMR7qBL8o7ZqUhUQXAxOrgsCiu9Py+TWHwCuAaUItoPh+XNl/qPYaj5FbBhwdjPXFrF8DVKyNbb6aMxtaH4D2WQ7pRMtn7vk0kWbuU0Ez9IrvAj0yDMCLRGLsxzu4ZP+ikoh9mv7NSXUtB0WU8hy2jorFd9Ll/g+AYIY0tl8Frvxw+je13v/sd/vM//xNdXV04duwYNm/ejGXLlpU957nnnsNtt92G119/HZMnT8b/+T//Bxs3bhzRc46YxlYO2UV+kxuy9olX4HminVFN6u6NYuzPyQSFdgLPE+0Y8wuSJLTxrijcTxPqi5TQUPdWjmXhnfBfrRj7s1Z4ejS2OKl+uK1ooZNcGWQLmcTqoGlwGPvzVpKZOFdQh7JyemljcvarTD2p7p4oqh5pQ/2Dw3NvGl34RmUUO9glr7JLoFcORlcvddnbuZNTy4Om+qHXt7r5KXwPFie4A+xd7h8FTlcC0VPBSNR1Tsd5pcreSMXg5cL+BaW32NGx5LktpoUObQex9SR2wvNEOzuP9mGqxlb9UJuJduR6qgPpK0on8/Q+3s4SkFKVN7rQyc1rYQngrHQ2oKDGZqQtWBc65WCkYZ6OhJ6nig/jGYz0RSNGqlxHn9WqYFbuHYx0DKsNs36m9AugmO6cXeQvso/qzBklqS2x9SEolzezv+HCSBPqvzbMaFVWG0qTilrh2dxetNABiuN16GSu6tF2OHZ2FtFEc/P9ttQ9d7+K2t8UEmSXsx1D0Q5L0WuM7aKcEhltI7Yqq/k2QtUjSyn4lUPu0imQ57awsrHGNVEYFSpz81oY9c2KzJIASaI6p7movDNL7JOjAiiqZ3XmDGYfKY0+szjAkt6WgjynmZWVdtl0U91lF5rp67n5ftM70rqk9SHPaTapmVr7krW9WvuoMru5SNnT+q7ppQFkF/ptwwpSK4JIzSvQJasfboO0pwvOAcX0vKkmHsKz++E5njNd33NSRfVDbUXJV507OuHqV9ln6/Pn5vuLxr3hpAuhGI6K40iRDZ5v+mztM0YKrBHW9ma0eUM9J52blrPhpwrq2Rnp30iQTCYxbdo0/OxnPxvW8e+++y4WLVqEWbNm4aWXXsJXv/pV3HDDDdi1a9eI7luhsVVQQQUVVFBBBRVUUMHfMj6EpKILFizAggULhn38nXfeibPPPhvf//73AQAXXnghfv/73+OHP/wh5s2bN+zrjHixk5nfjJOf9cJzlIOQ0SH7yG6ts1+H4gZ0nkP/TVOBX+xF/+qpcA+MxYkZTvBZsgL0va+g7p4o+jeGkannUP+GDOeOTsSvDIHTgR7vUeDuvRg8R4SkiagB8b6klwXQe6EIKQHI14QhpTRoIgdNApwDmq1qSdWj7Tj47QjO+HYreq8Po+HXZPeNemy6b4lAkwAhC/jeU+Da2oGD/xKB94gOxcNByis+0aRUfWumAY/sRWruxRgIn4GatzW4Tyo4OO0Y8O97cfTLUzEwZjJUlw5hRgT1b2jov5BHNS07i9pIbOlUwCvBB6K17j2uosfPo+ZN4E8/D+CCL3Ywqo8x4d/JL4TBqcBgfnPhrO0ZRs1LjRWBRX70f0JAbkMYqbEclCqg4VVy7XFRFb3Xh+Hu1zBwrgCfN4Ssj4PTUnapFUGkGnmWVBQA3v1uGGfszqLqkTYc/FYEZ/zfoXfXR5uocDgUOqn1daSXz0PWJ4BX9CGTuVphTUoJ2CujDGwIQ/3Te0C0QAuiylN2CjR9a6YhecYkjP9+Kzu/9r4oTn4+jHQTB14Gxhwo5BfKzfdD5wExrUJ18OiZ4cCYV2Twso6cTwB0YPAcAc4BHWJax+HbI9CcgCbpEJMc6t4ku2LxtSFwqo5MPY/08qnA5r1I1/M4+YUwGu8qvGfvFBHJhQF4DomQZ4Zx9j9GkVoRxODZAqp8IfgeaCNB1icVJvphTcLZf20YfRfrmPSsCue2TiTWhJDLHQEApK+4CL49R9ixcvhTyDRORrqRRw2A2rdyOPr1CCb8RyuOfCMCTgf6RA3YDSJ4YaEF9C6/ANjciXSjhJNfCMN7XGWB9cNRAaI7Yrn5frie6iirvvZh4HQmDy0FTeJsvy9HFbGjC9FnNdIn5Lkt7Pu+68LIVXNwDurMS2gUzKA7sFQxSnUWyATGNqVc3gzvY+0YvCoEMavDMaCAl3XEJzvgWeiHmFYhPLsfmoOHJpJ3s1KcrP1fntuCbK2IqkfacOSbEVQd1kxjxbv/Fkb1+4Di5uDJn1N3L3kHY5I+CuG5/cjNa4EAoOe6acDdBXtA7eH7/zeCM7/VivTSADSJg/exdhNdU7m8GYPnOuAc0CB7eGQ2hqE6Ac8JDZoAxM8QMH43uaaUUNC3KQzfwRyz70e+GcHE75FrJVYHke47DOzZS3KLtB1Dpk4EJZkbx5uTnw+j6piKvk8J8D5eVM2oub+NJb31dBdsE1U9pHDs7ERsXQjJiaQvZ5YEEJ8koPqQCl0k3jVaD7TNHP2HCCb8Z6s5+XOe6hSf7MTA+UDNlneBzr2QvTykXftgJMof/fsIJvxXKxITRThBPBSKi2MJxB279iG9LIC+b0bg7tGhc4CnVzWxNqQ9XZDy76NJQHosB8cg4OorvIeV7g4QL44qceA0QEwTwQD3k4QKrDo4uLYSxTxKMbKOKakmCTW/bUPPlyLgZR2N/x1l6pUAEJ8swAXg8O0ReI/qrP0BQHezA+PUZuSqOfRvDMM1oEJz8FDz9eTc1omD/xKBYxDwHteYp31gQxgDnwDGtamF58iPa+q1YdaW6Jwo1eRgcxTFxUOrJvM4gPRRT48CManA80Q7jl1zhqndGKmaipuHBGDcD0nZ8S8cQM+XI3D1acjeFEbNOzKyi/zQOQ6uraQMU2MFKFeG4EiQZxUyGmLrQ0iN5ZGrBbzjiK0WZs4w9cnjX43A88NtRe3Yity8lpJJOkupmg1HVTJbbf5c/VAbK9fEmhDcvQobZ4x9KDHRgeTtEUhJwNOjQTPMwL2Pt5v6tzGBd2ZxAMfDAs76p6itDc8sDoCXtWEr4pXCqcTsxGIx0/dOpxNOp3VmOXJEo1HMmTPH9N28efPw1a9+dUTXGVXMjj4vXFbqsBRnkqpE1d0bZbEy1MDSmIDh8C2tcTbdN0fQ9JPRS2SWywoPFLLalpKYPh0xO0Z5RDvJydi6EFQnVxRfYZzsxa8MwRFXAa7YzUsn1MZOfOKmMBwxHYqbQ8Ovoqbnqmn5DPSu8spmAHD47ybbSk/rn74E3IsvDXn+aHC6YnZKSXsO554nPx9G7ds5DJ7lQMOvoziycDLe2PZDAKcWH0Hr0zhoxtaFkPNxqD6swLmt08RxLpXN+y8hlmokz1AuZme4/OiPS/zC6UCpmB076dyhFox08jeULDWdJMhzWwBNh7Sni0l3D1ce1yg/Xeqc7EI/xJQKqzrXUJnttUunm9T8jIut3Hw/dGF49JjUimBJCd6R4FRkvins2jxdVCRWB5H18ah5LwfFLZAJZt7mDTXmAcXS09lFfnCq/aKYgk7wlMubIfuEIpo4fTaj7Y2tCyHdfQiv7i2drqLcBNQYgzscZBf4ISWUImVHu3sCQ6u8Wjf06JzG2t7sYOx7qRWkvoxj/GhTJZwqlNnNiE9ymBZfQPk0G8b+SsuAYqSy4XSBXA7DlZ4eLYYTs3P2tbfh3PsOms6zplU4nbDaamvbV2Y3A3vaRh2zM3XT6GJ2Xvmffyz6/lvf+ha+/e1vlz2X47ghY3YuuOACbNq0Cbfffjv7bvv27Vi0aBFSqRTcbnfJc42o0NgqqKCCCiqooIIKKqjgbxmnQGM7dOiQaXF1Orw6pxOjEiiw222jgVelgiff/9cw6u6Nsp0C95MdyM33s9V/un74j2LdLbJ6dayBiL3Xh3H81ghKofY3UVNuEivs3KCldlvsAnezi/xMdMCI5IKL0bcpzDwyNHeHa2sHsgtJsCoNYPQ92Ia6e6I4cVNBez22LmRa5Vc/3Abn9s6i3cmeL0fg2NkJ1ckjvTSA2PoQjn8lAk4FZC+HqqMKum8ulE9s6VRbr86f7gzg+FfIcQe/FUH8ylDJPDsflFfHrp6MGvkjgdWrU05Mom/NNNPnxv+OQtzbhYZfRyHPaYanRzYff10YsfUhxK8MIbE6iP6NYVMQ4+F/LJR3elkAvTeQ97LusCdXEUGNxruikD2FPsLn0z0Yd7K1z1xSMv8LbTc0GLtcvp1yGEpwoxTsArspRivWYIU+7YKSv5UKGKUoFXBvDAK2C8q269cUpQJOe28Io/d683k0VxhF/7XEZhnrqZwoQHxtqOyzlIMxR4ZRpIAGYlNKj50Xgrbp7ILCzru0ex+jh+SqBPZdbr4fqRVBJiRgDM7Ww6R/GUUv7MaZwatDJXfajX1BntsCddYMFjQ9eHWo7C67Y6fZbloDonPzC7mxjDvWuc+aRVJKCQTYCYukx5ZXNbXDkW9GWB8cKleds1+Bu1+DuLeL2Tr671BeHQBwxAuzntj6EJzbOst6dbIL/HCfJFQv8ZkuuJ/sYM9kLRdTkHojD0dMRSmklgdZnQ9sIH2nb1MYJ24Ms/ekbZWiVBC3OnMGnDs6wb9wwFQnxnafWRxg7dnY1hJrQui/NsxENbTPXAJldjPz6tD+7nmiHbF1hfZmDEq32jrHrn04cSPJj+d5oh1190TZMbF1Ibie6oA6awbxfi0LMG8TFTKgds3Yl+JXhphoAj0uvpaMQ7F1hfx8xjLrvoXYmvTSAFLLgyRfS1xjv9Mxtn9VQUDGOgcy9lc2r8vfg3p16L1TK4LsPZMrg0X1pQ2xDX/49ohJzKbc/O2DxJh7X8b7/9c8tzR6dUoJRZWCccyws+eOXftw/KuF+1U/1GYW6/Cdmv/iVAQKfD6f6e90LXbGjRuH7u5u03fd3d3w+XzD9uoAp+jZia0j3MRsrQjoOpJ513gm/3tq3sXw7T4MADjzX8yqT9kagcVkpJcG4BzUcfILYTju3F50H8p5pLzT9LIA4hNERq1QPAIGzxbh6SG8VT6nmyR1aaxOclUQsoeHkCPS17SzZhf62SKM0jwoBze9LABOIcZZ/swU4Pd7i57PCLtFkHNbZ1FMDAB4d7wKH0fKJ7kyiKpHC9K+qbEi6u6JQkKB2tG/sZD5u+b+NiRXBtHzpQhq3pVZbAedLBjdm2N/WlgMpsYKkJI6Gl/NIlsnsoVc48wZSOaPMcZNULdpcmUQk3focG/J83Fz5F5mluYHj7p7o0X3PF0LK+NEy4r6R0or8Ul7uiDo/eyzPv0TRbFA/RvDJKZqeRBCVsOkfyvUiRRX0WBZwNffHS2ShXYOkgmB4uVZ3cbXhsDLOryPt4P//UuoQn7SevIQ8DvSVgevDrF2k63m4QGgODnIc1vAy5opY7yRNpFd6EfOJ8B7OAP+9y8BAFNUSy8NQHHxpjJLX3ER8LR9/zDeg1JWATJhq3q0ndmM4cIqPZ1ZHEAucbjk8UPFjZXavDBOgO2oCeUmjaW44nbKXcbYOABF9JFyzwhg2DSectnirbFqQ2WfN963lCSqsX04dnbCYfjNOPhw0eEpXVLa2VCUGDrxoukW7Xju5eKXrPE6pSb5jt+9zmwlpezZQUyRiSOlruXm+4vqzEiHouNOzscDOtnsil8ZwsTvtbIJZNWj7SZbSGNl6LPSOJXRwmjDhhMPadcG6Hm0PuzKseknrYgZ7CdFbr4fipuHZ3M7o7HV3hc12Q8AUDwCXCdzpnMdCVLemSUB6EKhLRvbDY3BSa4MQkqS/8fXhiAlNIgZFakVQUgxBaqLUAClhAr3CRX88wdIAtFqAWJKY+3YGCfne7CNjZ104a9dNh2qmzfVc25eC7zdGjyb203UL3luCxz5xUa2ToLvwTZTjImWt8NCVmexN9kFfvCqbupzYpqMGdUPEclzYxxsskmAG6Td+g4q4HO6aXFHxwoaK5NaEUTVsUPsd3XWDJb8V64SoIkceJnQ4sWMDimhQsjojLo4cE0Y1YezAIhiaLZOhLwqCDFJYp8zSwLI1AmovS+K2rdUJNaEwCtkJk3LJbE6CF4FfO9pgGGj1c5efhgYWDEVja+oZDNgUEVivEhCAtaF4BxQWRtLLyXvJqZ1JCaSco2vDUET7e1QYk0Itb+JIrEmBNUBiGkdnJZXfnwta6KBGuvUs7kdyXkzgF1bRvdCH4JAwUgRDoexfbt5XfD0008jHB7ZAve0Sk9XUEEFFVRQQQUVVFBBBX9d4HR9VH8jQSKRwEsvvYSXXnoJAJGWfumll3DwIIl9uv3227FhwwZ2/I033oh33nkHX//61/HHP/4RP//5z/HII4/g1ltvHdF9R+XZSa4MQvbybHei1O6RZ9erRcpKAAn4c6IQrEh3G6sBW08BVbKgO4/uJztAnVfiM10QARhDqpw7OqEtK6Z8CBkd3seiRcGOxv/TZ6G7VCZFl9/bB+zLn54CvFje4wOUVv9IrgwSYQEUdorr7omynUK6U0N3+amHy/t4O7z0HYzXWxW03ekVshoaflnYETNWvnWnlAoMUIqLdZd60ndHLggxmmDL4QTSjgQfZPAgBXfgzaJ2T+tOyGlFNBxxb5dt2dTdEzV9T3dHjbuadvXs2dwOxbBTatw5ojtgYlY30Q7oriK9F/UmWj2SlK6nuPmie7uffq3oWexAn3+kdSF/egrQehSDV4dMXh0aaJ6z2R2ugCA172LwtZMgZDWTd8dOsGAkoLQUo0ejlPCHcefaTu0MKIwJpWzl6QLdlQZOXxC4c1snsgv94LRiDwYtD0oFNP6eWh6EkNHYeGrsF+LsZoh7yTl0HBjK40bfzfhedoIxtI9bFSgZu8HiqSrnuRoOKFVsuElCqSdQu2y6yWYa7d/AhjA83bKJoijPaWZlNJx69T7eziiKrj6F2UUPzGJIxmeQdu8rmvcY7aGd6Af//AG4AeJNyTNHHLv2MW8n7RtiSgX/wgF2ffq9sT+wOZPBi2PnWTOO68YEnwBQ92YWuXktJeuUjhW0n3qeMI8rQMFLPxwPonEcdz3VYZqzAWQOR7+rerQ97wEz2whPT47RVYdilejTLgBeOTGMJxs9PCdUeH9fKFcniPfWqiTr3kLmrJnFAYz/AfH6VT9UnMeQzrNomVttpLW8KYPHaHOdu4YvBFGED8Gzs2/fPsyaNYt9vu222wAA1157Le655x4cO3aMLXwA4Oyzz8a2bdtw66234kc/+hEmTZqEX/3qVyOSnQZG6dnxPt4+KjlhK0aaGbkc19EK95MdRZxm1hiGUFex8unLITevBdKLQ6uWAbAdvFPLiQqbHT/dzgipM2eYBia7pJ90MLBy/Mu9t10shjExX6nka8n5F9t+D4DFoVDYDTxHvlkcS2XkpJ7qQseaMHXwvI/GmUm506UGllKDcqnvjYnsRpM0zRh3YPe5FKWPDuAjUT+Sw5+y/d640MnOMsc+2LVr2s+sbv+RZN4eTkJPY3zfUIl9+zcObSvs3sWKUrFWfdcVrm+XEHC48Ox6FVWPtBUtbNxbOthEzw5DlZdzG4l1MdrmUgqHxjZmt9ABzBSsDxJGWuXpUrvKLsrL0ZcZ14w2lf7fs7kdzh2drA0Y+wVd6IwE9N2M72VH9ZXy1Loi+iLd8LPYqqEWOkMlEXXsLF82pVBOYa/2vmjRokIeZtyCsXzoosA6Dg+HymmH4crh24F/4QC0z1wCwD7p+EhRql6E5/ZDrhZsfxsOhGf3mxaepxt0jknjFhNrQiXbgp2d5l7+E4APJqkoheOF4rlfOYVFahvZJvIwys8Yz2Q9no7Diuf0zGs+jKSiM2fOhK7rRX/33HMPAOCee+7Bc889V3TOgQMHkM1m8fbbb2Pjxo0jfreKGlsFFVRQQQUVVFBBBRX8LeMvMGbndGHEy0HtM1OHPsgCqhRCvQfW3XY75C6dUqTgYt2BMsJud9LotjWqlQylREUFDQCy42o814qhdnDsVKAyl1/E/u/Z3I7kyqDt7otRjY0qzA2cV1rhIr0sYN5hze9c9V8bRm6+31Tu2QV+ZBf5GbXAupPPvfiSaYfCbqfVzhtk3MWufyNd8lkpaAItI8bdMXyK3FC73VZvlhQf9qVPK8rt5Fnb11DeBMC841sqEB4AEdU4DbAqHI4GVBHODqpkNkXGHax0+Pyy1+35YmmlRSuGs4tPk+IBQ+9mW/Ne2WE4u3dWigmFKUh8iCS7Q4HaU6r8VspbazyWlle53dHsIn9Z22wHo4djODgVxT56rnbpdNvfS3nVAPud9cGrQ9BaPll0jaHaSnJlkNnU2PpQ0Q6wXRsYCZuBwqgsBpjHW1qv6WXF1D3ruDgcO2SEcwfx8FG1spEoZKVnX1T0Xd+mwvn0Hei1y8HqpR4J7Nq5sQ7SSwPovzZMgvJLKO+Vg1U1DoBJpRMg7ZUKwmTqRZOSZbl+Y6f4B5jHHmvbkOJmFTxrey+lamfEUOVgZ2es71GurdH6LOUNBsrb6XLj40eBofp0Yk0I6aWBYalr0j5WrmxGgg/Ds/NRYcSLHf73RAHDOvjIc5qLGmxq3sUYvCoE19YOpJcG2IRacZPbJtaESg64jhdeh7R7H+JriXyvcVJrnGRnF/iRWRxAqqmg80ONR991YXYsTagGmI0hpVr1XxtGZnGATero4kNKaUW0DDky/Alk7X1RU7mklwbgeuY103WkpAbnjk4MXh0yS0hOkuDa2kEG17zSi7dbZc+dXBmEFFfZM7uf7IBzoCCBTCkodfdGibSqYeKvixyc2zqhujgk1oSGRe+hoEa1+uE2eHe+avrNOLErpZJmZ5SH42q2tjnjotGKUtSp8T8YffLZckjPKTyLVY6WIrUiWJAEXeRH7/VhJFYHkavmkVwZLJJn7t8YNtVLajmR6DQuPLTLprMBKbMkgMRqs4ynXZxZqbq2Ll6zC/2k/60desDLzfcTNbY8jIteKfoHxNYXFOGMoDQwz27Sjug1er4UQXYmKUd39M/kt3wZ0/enk1QqjXw6YH1X2nfLUdGG2jwZDo1tOBiKJsSOs5k4pOZdjMGzCNNbSukYvDrENjCoJH1uvh/pZQFklgSQqxaY1HZ6aYCpiVGc/EKY2c5ctUA2T/ITUnluC5HXviGMni9H0H9tGN03E2nbxJoQkyMevJrYHWsZp5cFEFtHjoutDyG70A/VRfpIciW5RnpZAP0bwzh2WwS9nwsTKdv88/dfG0ZyFZG47tsUhmPXPqRWBJFpJGNEZkmAvVtyVbBokWEcawbPckC7dDriVxZk5KuO5JAcXxhvUssL1zD2zczigInKa5x0GdXNUsvNm13GxYniJnbf2C6NEsRGGGNisgv8yCwJIH5lQaqb9ntjHEr/xjCbfFkXCcYJpFHW2jhGWeXYPZvbwT9/ALn5ROGU1qlxQpxZEkBmcQDJlQWpc6P0NO3XQk4nZWNoz6mxpNzpQoiWC530xdaF0Ht9GOllAbaop2kVcvP9bAyhiw67+UdmcQDJVUGS/mFOM1QnB3XmDPR+LoxcNY+6e6MkZmf3Pjb/SC8l79T7OXJP+t70+Y5/hbR/95Mdpg1Qa3wttYdUSt7VpyBbR/otrfPUikJ7oXUavzIEKa6yDaXMYtKPE2tCJrvu2NmJ7CLSNrIL/GyzNr0sgNQKIjltbFs197fZLngysy5CZkmAbTRllgQweHWItaXE6iASq4NILwtAF/miMSdXK5rGc2Nbo+VDf++9IcyeKTffP2w7OBLwUz8J4fxzIJx3NvkiUKDnxy8vvdlmpPHbSXrT9k3/7bsuXHJjiJYzpRtTCj9V3gXA2heFVYXulGmP+ij//gpQobFVUEEFFVRQQQUVVFDB3zBG46n5a/HsjHqxY0ffsroSPbsKeWSMgbFWxYlysCqc6DyH6ofbmAITddG6LOfE1oWKcp1YPTS5eS0s54V1hezcQZR17NyjUmsht4IdrEpCxmu4t3RAthxPgzatgdb0+WUPx36j1ANjrg7jTozw7H5ol05HptHBNOqB0qpLxgDMXNGv9jhVl6nd+VJSK1LJs8La5lzPvAZp+UTbYxWv2WlJcyZIe+yVzwCzQhNFuWdSDEpJ7j0FJTKae8O4gwqYd06d2zqRuD7MdoSzC/3s3s5tZPet6qjMAmbpjpm1jfDPH0BN/nzXU0SUo+Z+c/4jq4pSKSqXlcpIVROHA8fOTkiBcQBIUto6AL1XTQN+S1QKedneIlppYPHJApro/Z8ze6Xce14DuDrWjktRvwB7tS+q9FUO1N7Q82UPDyeIx5K2G9om6PU8T7STHWgfD0+PUkRZLEVj6782PGR+CKOCmXNHJ3LzWpCrEW37EFXkcW7rxMCci4A9BYVIoy2uub/NZDOGouJa7YZ22XQ03lV4blpmRiqx0T6RXX5zmWQX+E1tWbm8GZlaHq6ZMyCmtKLAcDs1MarISZWtjN9nF/jhfazwneeJdrbrKWQ1OAfJ93Z1Y6QLVh1VoDp5eHpyJKfInGYIz+5HtUGVyrhTaywr19ZixSmaZ8cIIaOZnt9ob6gHyDgOlgqap21bnTUDmpOD+8ni+1MVMXluCzJ1IoSsbnp+ddYM5HwiVCdvamNGT5RxHLVTU5TntrBnETI6uy8738b+5HyFQHnar43XpgH7VY+SfkgVWmm5uPI5yJwxFb4H8+WX32GnScdVJwf3FuL1EhPkeCs9m85NaM4amqtInTkDDb+Mmry02mcuYfVGxwJa3rRd0ecb9yPyDCSBeMFLam1/1B46QMpR3EvUZintS3ymC8mrQnAMaKaypLZ7DCy50hb4kWoyT/Ps5jTGNuXc3glldjNyNSI8T7TbCsC4nn0NLu4Ie191ScB0XNWj7ZDntkDavQ/qrBlw7DSPq9Sm2anWUWEC+r01L5lzBxkfsXV30XONFtorfzR/0fGq/YEWeHcSxeHe68NwJHU4YS5Lxc3DgULftM5JKTKLA0XlbCwb2i5d/VrRuacVlZidvww4du1jxmUkCkzlrmfHoaVwbu9k7veR0LxU9/AUTqTW0ipu1LgDxQkHATOlxToZ5184gFw1zwxeYk2oeMJiSID2UcBankaa3UhoP6UGfuNCDwAytTwb2EpN9q0LHWBo5b6RPJs8pxnK7GbIc5qZiz6xmlDbrPdxbutkEwTl8mZ4NreXjYug59stAOwGNyt3G7CPwcou8g9bzUZsfwMAoX46YioafltIFFluYWLE2LvJOZSuORRKxXLYLQbogGOlqtnFI9md73qqA5klAVbWxoWTZ3M76u6Nlo3NssIZ0xglqBQVzkotcuzaV3azIbvIT+gye8rLgKtO3nRPWo7K5c0mupMVmSUB8M8fKKKSpJYHGZWYttvcfBIXSJWC9E9fwqgeulhsf2rezUF4bj+k3fuK6EWag0d2kR/qzBnQLpteRNWjz0zL0xSnMK8FfZvCpjg3KakAILaRloPxmpRqKyXyGyT1EtSZM5CtIxNH+dLRxcKVU2oyQrm8uWysKGDfhwFix5z95i21zOIAhHShT2XqRHh6cvA92GaivgjP7od7S0dRG6N0MnrPcjEW6YbC5JoujOS5LSWfFwDce+3bKy0DGsNijNkxUujoZopzG5Ett4sjMY6BxkUOi4s1tHfNwbF2rEemQXiOLHTFZCERKX0mYHiqedpl0+EcUEiS1DJULNqW2UbXChLrJcVJm635bZupHVnf1Ti+OXd0wtOtsM/GOqDPYFeX4t4uU4JTq32SI1MQvzJUkOy2GVNZYt9n95s2QoyUyKE2WgCzGpvq+vDnLeUWGIPLSAx7w6+jZJPd8G7JVcFhxzIaNxCo7Rk4z1F03FDxn6NRb7Ti4xivA1RobBVUUEEFFVRQQQUVVPC3DV0nfyM9568Ap+zZobsKmsSXVMaiOyf03+zCQjCrdYfDmm/DiPjakGnlbPrNsis9lHIRfW73kx3sWewU3ejuhOupDijBCwEAiQUXQ501o6SqnJBWzcpn+Z0TFkS5tLSiXWYxCXQ07hrZ7VINtYNszINk3aXrvT5ctGM8sCGM2N+Zn8tan+mlgZLB6sadTuqZobtIx75mVstKrAmZdoKMu02pFUG2e5Gb7y/aUer9XJgkl7Tg5BdI2abmkoBB53OvF6ksZZYESnrorKIJxvwmQLHgQWZJAKqDdJ/cvBaogQttr2uEtKcL4t4uSHu64Ni1Dw2/jqLq0fayuzGZJYFh7wYbvYF2MHowaKCqEZQKYeynzm2d8D5eeidy8OoQ3vle2FSHsoeHtHsfkgtIXdCyK6V6ZbeDnakrmKZyamx0Z9DYR/pXFdpxbr6/SP2GUkvoTq5xx9fYb2l5GXeQOYvHkAYU03vQcrIG9VLxCWMOL+Oun+Is3rEsFWxKA/sBs2KVa2sHOBWQYsqQIiqeze0mG0DLUXymi/VN95MdJXeNrfbHs7m9iAbp2Ely8ND7cC++xLyM9lSmwt6btKeL2WNlNqGOyV4BwnP7wT9/AJyiszJw7uiE66kOaJdNBy+TXVhje3Xs2sdoTwDxagGkHKseaSvQBA0eUGozabJK7+PtEJ7bDyGXp2XZ5NewgnnthlBfcu4g1Cpj/xCf6TLt9topM5WjZFrzkVgp3NUPtzFP9nB2gz2b2+HcVsiTUyoHHGA/9kq797FzR8KSsD43//wB1naMNDfntk5G9ZL2dCE1Vizp9adtlwbw03sYjzfaBK71ZXZd5w5CXzWKTdB+Wk6VTLt0OvjnD7B+Vk4hzdo3qJcu22CfutMuR5/pfMO9jG2Gfj+UiqC0ex+h6q4IsrFXdZJwAsUtDKnGps6aAWNyUyMl0qqQyEQJDIH4RjU2Whanktx2pJAOvF30XTZIxqSaJ4lgF7XDxnfzPtZe1ptZCtT2jP1Za9EYcLrEbkrh46zGNirPDuViAoWO5txB+P3ppQHgyV0AgIEVU+HbfMjkeqQZXweuCcOZPy+xJgTFyUHM6nA+vIMct2QqfFsPsfPSywKofqgNJ24Ko++6MKoPy6ZObhxoB68OwZEo5n0nVwWhShx8D7bZGgi5SkRuGBnF5SoORwIucDogTIlA/dMh4Mm9GFw2Fdnxk1B9REWumsfglyNwn9CQreVIZl03KR/Fdbzkte0S8tFnTa4MFskoJlcFIaY0OLd3mmJEUsuD0Hl72UUpXWid2mXECAtZHb7/fYV9T7MAG3mjtFzoOaZrvlCIY6KLFWpYx3/frJZlXXyZ6EDGCVg+g7YRDb+MImbJ4gyAxRBQVS/ATJ0qxZUt9UzW46XoH0yfjQOSY9c+ZGyeyQoaWyDPaQav6DAOAKXgeqoDsXUh+B5sK5vBnPar3Hw/OE0Hdj1ddIy1XVuvRWNR7JLv2i2uM3medg39nP/Xt+UVgKuDdwepi/5PSmhoI/Vx8NsRnPHtVlOWeM3Boee6acDdhRiThl9GWdwRVWMDyIKJ1mvfdWFWT9LufaBC53WPvcLaol0bYuVhMxkyvrOdHbCWA+XY04VLKZotnVgaZe2BQn+3myCWmoQar22cxAOGpJzDaI/DwVATqdMF8ZmuosGI9g9aDsY+akd/4Z8/wOq63GYQmyyP4jnLjQ0nbgqbFAdp3dK2YRw3AXMcJR0/7aDMbkbtb6JsIjgc6o8dPvBErcOwZ0B5+ffBZVNR1deI+JlO8DLAaTqklAbntk6c/EIYrj4NYkaH66kOFhvbe30YrkEN3sfama10JMiit/eGMKqOKkiNFeE9riA+UWR9kF4DIAu1XG1hgUTrJrkqCCGjg1d0ZOoESCmNfJ+n9nofb0dqrATP7GbkqgXo+Ti+vk1heE6qENIqpD1dGDjPBWliiG20ZBf4kWkQUHN/GxQ3D2V5EGJag2NnJ1kYvXCA2TpqOxQnTyTO+wm1MrWcKHnW3hdFakUQzj4ZiUkOJCfwmPAfrax84leG2Pyo94YwHAkdUlKD4iZxWfG1IYgZMl9KrgxCEzkIuUIsF41f9DzRjvhsEiMrZMkcQnXxcG5uJ/HUAof+8yU0vpZl8T7aZdORrZWgrA/B1auwtptYE4LOA85+hfXZgQ1heLrJYqbhl1FklgSQrhfg7Vbg2EnmiUJOg2iJif4o4GwvjEnJlUE4kuVn/MlVQQycK2Div7fiyDciqH9TMY0/tN1aYRwDlNnNJWlsNF4TAPquDQD3bhnR+zB8jGN2KjS2CiqooIIKKqigggoq+BsGp5G/kZ7z14BRJRUdOFdCbB3RgTcG9WUX+U07X7VPEE+BKnFQLm+GkFHZzkbtb6IYvJpco+qRNtT+JmrauXMOqEiuDJpoU/G1JFdH/d1E537gmjCjmnTfHEH8yhB6vhgBn4/HO3x7BJklAUYdiZ0pINXEMxdpz5cIvUpzcGyHx72lgx1PNev7N4YxsCHMArDrHn0FZ/xrKyZ/pxUT/rOVuTJrnnwF1UdUuJ7qgOrgIMXJkpd6HRxxHe4tHXAMktaRvuIiRhWjO0WmHAYGKkxuXgvz0hipK97H2ouC2/s2hSGmNahODoNXh9Dz5QKNLL00AN8DbYweprhFKLObUf1wG05ePY09l5Alwax9n3Sw56Pl9v4CFw7fHkHvDWEc/8I0fNQwuooTCy82/TacHDE0LwilVw5sCBfR2EYLmpvj4L9EoLp5RpfLNEos/wN9BoDsMFI6C/3O92Abjn8lAue2TqSXFnJBWelf2mcuIapou/cxymX6ClIeb/0gn+/hq4V7ZhcV8k6kVgRN7aj3BtLmj/5DhD1HbF0Ix26LMFqO66mOYSWdq31bYfVwxrdbcfyrEWQaeBz6pwgGrwrB80Q7qg6XtpiUxpa7dArz6nTfEhnSWzccWPOEfJxhpWpaRQCMFDsKI+WonJgLRf9Gkq9M//Qlhe8sySWpPcosDpSk6g0nEeEp55SwAUt8baFtqrNm2NKc03MuIsH7C/3I1nKQ57aQHCP5su69geSxySwOoO+TDpy4KUzytcz3o++TIskntcCP2Dpip/s3hhk1EiDB3HI1Ebxx7NoHxSMgN69lWHbNmqOr1LsC5iD1/mvDrM7sqNq914dNx9tdp1TyS6OtpnmTjKh58hXwLxxAzf1tqH64DVWPtjO6sHNAhyOuMc/QyalODGwIo+HXUTgGyKDve5Aotbqf7MDANWGm5FV1OAfHzs4iz6riJTSs+BlO5tkACh48MZ9nz7GzE74HSf4T2g/oeCzIOsS9XfA+3g7Hzk6kVgRRdVQGn9OYB6L+f6ImRT3Fw6Pm/jaklpMgdiGjIVNH6jltyBlorENXrwxB1m29GpQR4elRMOE/CJOCHueIqazcG35FnsP1VAdLKFr9UBvcT3ZAnTUD3scJHdWzuZ3NEaoeaWPnW4VPKK2MemzG/ajVJG7AP38AzgEZvgfaoDkK082qR9pQ/VAbO6/nSxET9T6xOgjXUx2ouzcKxcNDntvCaGzSni7T+JxccDELb0itCJpy3n3QUP0Xou9CwTR3NbZ9I2tl4r+TevEe1ZlXJ7kqiNTyIBKTSNnQ9kftRynaWmydOX8SFYEBAFffKaw+PsZ5djhdH150USwWQ01NDWZiKUSOcEet0rrsWL0fHdiLAGbDZ5Fopu7h7EI/OA2ITxJN0oLlzj3dsJM9BMiEcNwdxYkKSz3bcJ+ZSs1+mO84EtDn+uTSWzH5iA961+tM7pvSQtRZM5Ae44CUUJGrFpAYOIzXd97B3qVUmQIFSUyjLPDANWG4e5WSqmeUnkXPj50hwvXTbUXlF1sfgu+BNlPZOpbMg2trR5E0bTmUkpoeqs7o7wCKjjFSr8rdY7goJSM+kue1wihxTDGwIWwagErey6bsfVwdjs2fhNd33IGL53wFTXuPFJ1H20Pv9WFIv9puOje5Kgj10Z3owF5MgR+voxMBzIZz8VxGvzPS2IbzznbS00Y63emElbL0YcPYHoHiNmmH4UhzDwejfXc68RsNSsnJ22Ek9qAUaPl+YvmtmPzkoaFPOAX0bQqb6IpGG/tBjyV9m8JwJDRbNUUrbW8koPYmfiWhM+GBHSN+j8O3RzDpu8XjtDX1A0AW2GN/2gp1pjl+ZChYbbU1PYEyuxnZOtGWXjRwTZglhvxrxIkbwxhzp/n5re2N9iVarrQPp5cGwCv6iGNrjGObNX1A7/Vh02LV+CzC6vmsDobqE9mFfjgGcuDTCvQDr4NrngK963UInzgP6ptvFV2fjj/n4FN4B4TOPnnOehza8wC596r5tuECHzaoXVB0Gc9hCwYHB+Hz+YZ1Lp3fB5b+fxAlq2B9eShyBh1b/s+I7vdRoEJjq6CCCiqooIIKKqiggr9lVNTYCkgsb2F0h+TYQj4Zo/49VeaSL53CaCKU3jBwnojY+hCc2zuRqRPgHDS73PrWFmhRPV8kdAd5bgtz7SdXBpkb2eqaN7r/gWJFLap0Rt2zqqvw+qkVQeYKHXdHa5HqmzpzRpF7lL6bUUHuxI1h5nruvzbMXI25eS2QUuZ3jS2diti6EAavCpkoIok1ISRXBhnFLX5lyNadaad+R1WfAFJWg1eHmEvUSEnouy6MEzcROkViTQjdN0fY+0kpDXrX64itC7HcRpTGlmpyEHfy9k7kqjmSVMuAoYJnc/NaTLs1tb+JmnbOrLQJFtC5iCTNHPsz804edRn7Hmgrop6wQPsdnazOe28oT0+jz5Kb77fNvzJcJFYHGRWEJpGT5zQju8gPzVEQ7MgsIVSe2PoQo8pkF/nRd124pMqN4ubL0lhSy4NIX1Foq1bVNUqTK0VLov279r4osov8hOaRvx9VvaNlk13kh++BtrKqM1TBimJgQxiDV4WQbBKQWB2Eu19jKnoA8eYZd0oH519QdM2+TWE44hoGrgkzKl05JUfAXr2KBjKfbth5Nkrl0imH0ZxjB/kzU5g9pei7jpQdtXXG8lFnzoA8p5nZ1O5b8tSzJYGSOVZo35V270NiTQi5+X7E1pM8Nn2bCop9qeUFmpceKdh7z+Z2E22H3ie70A/905dAubyZ5RGKrQ8xGlt6WQC56oItT64KQrt0uqmvG8uRenWoSmRuvh8nP0+OpfbaSvmjMI4fAFCz+RWc/EKYlaE8t4Vdi147tTzI1NSozU4vI8qWJru/Ogh5bovJBvZ8OQIxo5vserZWNH02IrkyyOjXxvcpZS+sNoAeR22plNKRajLnjYutCyG7yA8ha76WOnOGLbWQvhdAyqNvUxhiklCrPN05U5JNu3Ot6L82jJ4vR1B9kJxnzLUVWxeC7Cvew/V0k/tRr07/tWScpnaMUsPp+ydXkWfmc5rJtgnP7kduPrGJmcUBQl97rCBAAYDlUVMtihPGdmOXu8w4BwFIW7N7f+N1WP3a5EiT5zQX6JTXk/dNrQiacmlRpJcFiMJsvt57P0e8OtRmUGXU7ExiYzOzyPgi5nM3Cc/tR+/nwswzqwscnNs6oV02nVFSk6uCrE/TMk0vDSB+ZYh9b2QsKK5CeEF2oR/OeOlJNRWnsEI856wiGq3rWApifwr6AaKoqHfllRU10p74qZ8seR8Kd2+hzQ6cb+4fxrmbFZnFAdO8NbkqiL7rwqbj7ZRPjf3KapuojXbs2mcKcRgNKmpsBlRt3ofkNZcCIMkuKUVHlXi2cqKynNILr8P3+6PILA4w1aLxW8kx2YV+eLrlIlnd+ocKiQidMY3RmKgzkroLkyuDkBKqye1J70HpYvV3R030hky9ACmpmVyOVOFKiikQk2QSaqSxyXNbCGeYA8Q+UqupuRfD4ZoAV79K4lj+/D6576qpaDypmegU1Q+34eQXwmi8K4rc6iCOfS0C739tA0BUq3wcoUCklwUweHUINfe32SYNlOIqU2OjrmKreoeR3pCb74eUUOF9nHxOLw1AdfJM8cdI/3EAqAKYypn76deYmlVuXgv6L3Cg6Set8FqeqeFXUfReOgV4YS+yM6dAdk6wneQdvj2CxtcUJJsENPyqUDa9nwsT1a31IUAnfGtOzZexgValzpoB57ZOVpfJ+RcDOwlFx9h+snUCWbDt2Yu+NdPgijch3UgUbwbOE5C+gXC4BzaEofOAzpPgOiGnAzqgC0C2locjRtRqBs4X0Cj7kW4UkTx5GNi2F7G/mwrfU4eQWBMCp+nQOUBKaojjOLCNPFPus1PQaKB9OHZ2on9jmCV3o9m7gbyk+exmOAcKg4YAsHpKriJS3LTOB68OwdWrQsgVFlCxMx3MvU+pZ4pBjUv2kHqntARKSeFlHanlQWiiWbmu4deFfkNpCBLIRILGnwFkgNUkIHZjGO4+HfElU4GnSBn0bwwDx0nbdvzudSRXzYfi4lDz2zamHgQQNR7VJTAVvfQVF0HwcagGcOLaacC9e8HnF0tK8EL48s9jVSE7/tUIPD/cVni2tSEMnMuj/k0VnAoMnCdgwn+aF8pGGu77/xrGmJc0qA6OqUVm6zg0/bigHJdZEkDWxyPTwKPpx2RDRHVw4DQgV8WB03QT7aPnixHUvCdD8fCInSkwVcLDt0cgJUl2+aqjKtKNAuruiaL7lgicAzqEnI5MHYf0GA41b2tEuYgj7TU9hoerT0PN/W2MRpRcGUSmlocmkYGn8a4omYw8W6CxSb9/HQ0vHgVAYgFdfSpcAxrrY9QO5ub7oUkc9Pz4TZPzNv24UHY0hkKe24JMvQjZw6H+7ihy1QKcIAN61SNtRGEoHx9YfURmyUJpUsXM4gDEtAoRgB6ehlytwyxJXyVAyCfczS4kz+XeQiSmdY6D8Nx+HLstgrEHMnCdIJNSnQekhAa5SgSvkHcVcoBqI8nn6dagXN4Mx85OuPITCKpaVfVIG5uUCFkNYlqF8Ox+uLZ2mCab6TkXocnQJ6Td+yBuME84PJvb4cn/n9psIaPD/ST5P+3btA8mVwXhBJnUjP0pKffsQj8EFGi96aUBuJGXdY+Sek6sDkJM66g+pGLwqhBJWlvPQVgeJGUypxmZRglZHwfnoA7VycEZU1mbqLm/jW0uyfm6dMRVVD/chuO3RjDuh4U24NzWif6vkInwwIYwXH0qdJHYlPjGMKoP5tD3SSe8PSqytTyqHiUyvNlaAVVHZTh27WOSxEnLxJCO3wCxS9pl0yF7RYgpFcJz+1F9OAdxbxfbbHTs2ofsIj/SDSJ4WTfRceNXhqCJgKdbNlHbPCcVUwJSz0lSDlI+aaj3sXaos2ZAEzg4dhbGnvTSAJwDMvjnD8AoBB1bH4L7JLHv0p4uxNaF0PCrqIlSJ6Q1ZnPsaE/G56b1YZzk2tHzaHt19crILiAbaXQ+JO3pYs9ojVUyTvzoWKvOmkE2BpcH0fDLKE7cWNjYkj083CcKiWqFLFmAKy4B2twW6BxQdaSQvNTzRDvSywIsxoaOlwCxD2JKZW1ZnTUDikcging1Int+1VGIO3Ju70Ti+jCq8tc/cVMYzp9vJ2X/d1ORnTgJioeD/LkwYokjwAOkTyjvvAfH9CZWP9LufdAPvA46AvPTLoT28humstFe+aPp8+AVFwBPdyI9/QzgAKGx5aoKmysTv9fKFms0VUNyZdBEl+35YgRjf95qUtvNLvKTmOvZzSbVNSPFls6RxL1EfU9MqXD2ycgsDkD28qh+uI3NewHAa0ggOypU1NgqqKCCCiqooIIKKqiggo8jRuOp+Wvx7JySQEHJYy0BYkYN8CHvM4yAy3JB8B8kTkWgoOdLEUbBsh5vFzRpl1Onf2PYtIofDugOEUW54PbRBLt+FGIL9J4XLrkV9eJ4s179aXgeu/Z1KgIFgDkoWp7TjFwtCWodKrBaye/6GIO36bXs8h3RIPOPsl7oPUfyDHbHWgNEh7rOX6rwx0cBO4ECadk8275vtT/DDfbXPnOJKfkxYG+j7MQv7L47VWiXTUdqrMM2mP50Y6C5Cfv2/ey0tDVj36ZjpXJ5M8RnSL93xJSSOZeG0+YVy84xUPBq0vtYcTpEHEZyjf6Wcejq/Knte9gJXljfiXo97HKRlRKEKdfOh/vs9DmyC/zgVR1CVoUq8ZD2dBFxH5Fjz2PnmbHC2n+U2c3gNL2Qa+dyMnZ4nmhHYk0IYloreofMkgBUJ8fodcY8O3agogvqrBnQeY6Vq61oTUsT9nWeWrunnh3xmS6WU8h0D4swjlU4hdZNX2Ac9rcXt5nTNQ6UEygY7pgEnLog0VCCLyc/H0bjfxvazCkIFIQW/uuoBAratv/Lx0+gIDO/GVW7iNSykQZCG+DAhjD4e7ebznFt7TCpalH1JsobLTewJlcFwStEqi++NoRcNYfqgwV3av/GMNwnVcheHo64Cuf2TnaOKnEsARkF7UjxtUQFhsbR0Pfo3xhGcjyHMS/JzNjRBUN21hTg2b2IL54K37ZDGLwqBMXDIXvoELCDJBX1bTnEqH09+aSijjxtKbE6iPgZAqOxpa+4CB59HDOW4AuJHr2PFxKk0fvX3RNF7w1huHs1CBmNPR8tW2rUKPUptr6w0ImvDYHTCD0jszgAxcMzuhw12JQCBgBc8xQMXlANV5+C5HgJjrhWVnFkYOVUZMdOQnIS4O7hGO3l2G0R5Gp1iEkOYhqoezMHx659OH5rBKkmHed8M4qjfx8h/GYecAwQapkjpiN+BgdPjw6dB+JnAWKKg7MPiMcOA/fthatXheQmXOxMvQDfA20mGlvi7EkQk4SKk5gM1LxFqI5H/yECKa5DruYIPTEBwot3AFKKUB4O3x6BkCVy4cnxHNy/e4/U/ZKpyE2YBNXJwXeIJAYb2BBGqoe0AQAYXD4Vkj4eqrNQxs4dnayepD1d4PMytjRpKKeT+CR15gwoXoHQRDYSJSQRxG3uAaG2SHHVNNj3Xh+GJgG178hkobMuBDywI9/GLkbqojMw7o5WttCV5zRD9omQEip4WYPw7H7Cx/bxEDM6cl4OggzWT1x9xP2fWRyALgID54iofVuBe0sHa5u5+X6klaPA03kq37wWJLnjrExonz92WwTukzocCQ3peh7OQaL0FFs6FdiyF+krLsJg6EzU/1HFCfcx4L7ChD2+aCqUcZPg7lURO1NkbWzw6hByVRycvyB2p3f9NAyeMwnggJp3NCQm8lBdgBQDsg1kb8d7BNBEDqoTUJ2A5gAcg4D3uIbkeB45H/k87o5WHLuNyNnXvKug/3wR43/Qip4vRRgtY8wvCLddcwCaCFQf1pD1cVBdpB8c/fsIFC9Q/Z4OQdaRbuRR+7aM2GQRQo60d14h34+7oxW914cRPxtw9nNQHYD3mA5NJG00OY4HrxBKm6tPR6qJQ+NrMrr9EryHdGQayTtJHQdZ2QNAat7FaEgXeOa9eUqncfMjN98PPmeOn7BuuiTWhCAlVahOHp4n2tnkktr/unuiRRssdMJknLQI6UK8hS5yENIasvUipIQGIUPoSkZai3HCkF4agJDRAI7DwHkSPN0qxIwOXSjQMe0mUUBhMWFU1YqtC4FXC0lLe74YgeekxqhsdCGSWh4Ep+lI1wvAG++xvu578hCRnq4R4O5ViiYmA9eE4epXoTo55KoJ3bDhl2Rykl4WgGdzO3pvCMM5qEFMF+89xs5woGbWDMhVIlxPdSA3rwWcDmRrBOCRnQAAJfwpoO2Y6R1ZvEO9hCoUJtvK5c1svJN9AnLLgxBymmmRYJ3o03KwbrAYFRUbfh01LTY0J8fGIuOGJ02ACY7EwGQWByA8RRKR0zH02NciaHidyDdrEqGXqzNnYPAcJzwnVOgCmbyklgeRrufhSOqQUJwoGTDHYULXIVcL4BUd2WoBLpCxUUpqTEq/5v42aA4OsfVkzPR05yBXicj6eFQdzbF2YzcJ5Z8/AHVOs60Sm7SnC+llAWR9ApvM04012n8o1TmzOABHXGY2Pr0sAE3kILt5OJIai1Wlcxt5TjPkahGcRtJbxNaHkFkSgC4Aipsrq7SoeAT0fz6M6sMFVVSjdLw8lyiyOnZ2gu/8I6snzjUR1Q+3mdVVDQsV7dLpULwiVCdH+isAXSR1mZwgoQakbcKi6kupldTWcCoYVddIx8vUk+nryWumQRUmElU/AInBw8Dje5GdNQXCMQ9iFzVA9vLgVB11rw5AbvBAOpGCPMYDR08S6utvQrtsOqQTSah/+BMp76UB4Ml8m5x3AbCrE+kZZwD7zcnFVf+FwD6SJJ6qJiqXE4U+MaWB00n7Sy8NID5RhJjRCeU3X+/apdORaXSAl3W4tnbg2G0RjP9BYaym9DdKL+ZzGklibuhP3h7V1JZOBR9nz06FxlZBBRVUUEEFFVRQQQV/y/gYx+ycFhpbdpEffLaQQGsoN6IdRYvdp8y5HxV9jYI+2/TILWiIHi363u6Zra7ywatD4H5DcgpMm3kLxjx/9JTzW9jRmawoyg9goS+oM2cg+ezeU6KxORfOHZbr36qfP1KUK29WR+Gb0ZDf6RwNrHVCrztt1i0Y89zRouOpex8ondNkOPU03OOLXPuGne/sIj+yW3d/ZDS2i6/4Cur58Ujvetr0DInVQXA6bHNSWOu050sRiF3vYn/0Jzjj8vU4+MwDp0xjo55SALZ0l9OJxJoQy0VlpJBYc0V8UBhNnp3hohStYqQ5TMreowzlp1y/oL+VomedLtDybQ58GXWdx4t+H04urOHASteyjoH0OWaEb0a9wd7ZlRGlSJXKj3eqMNa/0T5ZbdVwaMJW7yAwdB6m4dS5NW/ch4FSbTm1Igj38QzSTS54NrcPOQ+weitHY8Ny8/3EK5Yk3tNSoJ74ou9LzIGAgl2wO3ekc7fez4VRfVAuOsdYRqXs/fG5k/DarjtOG43tvMA6vNXxIM48fy7e//NuAMU0tuSqIMS0VrY+ys17rRhNrjJaxj0bpuOVe/9pVDS2yLzR0dhad/3l09hGLD1tB+e2Tgjy0BKu1K0+2gRMH+VCBwDLSi+1vl72OGP2bytFz2jAnc+R69gZODtpylIYzgTauNABUDQonI5JynAHkFNZ6AwXUvQPQx9kgDXjd6lBx/msfd1T9345qFLp7maXqdyuXqlUKn0+Kt1r5AR/kJP44cD99Gu2hrrq0XbbhY4dxv6sFWK+Dquf+fOI7p+53D6DtlG98IMuIyrPbuXKfxgLndGglJy0EbSPlBqET9dCB0DR5NAotVxuA4D+ZrVvVJ58qO+MEr5UZr0chI43bL8faqFjlDO2k5qlsMbalBoDxegfTDLSdmVEY0GMCx2r3TsVGOvfaD9NC535/lGP48aFDlUpozL52qXToXgE2/MoEquDLJWCFbTeM0tIeopSaQeM7VCe28Kewyq5bTyftmVrPXueaAfX+nL5BdzsZjY2WGmZI7FhqeVE1tqxsxPObZ0YOM9ZfIxBZdDTLZf9nYLOddSZM5hd8D3QxuTAE6uDUGfNKKpzY7tTZ80w2Z/cfD8afhm1bSeOnZ2m+ZUdPLteLfv7SOHsIIlGhT8fLvotl0+z4n2sfcj6MM57qRR9KbtbbqEjz2lGZnFx+6TlVX/vKWxkaPro/v4KUKGxVVBBBRVUUEEFFVRQwd8yPsY0tlF7drRLp5s+D8e7IO3pMu14nM5dJSvKJXWy20UfDsR2+108K4ZSXLHCmhAsszjA8ulQGBOnjQYj8RQBH2zdnE6USowphz81out8kJQXmhhO2tNVlAiXQhdI4CbdsaHHWZPJWneMudaXTZ/tktCNBpklgSF30EYCY4LUU23LQ8H1zGu239slPj2VxLF/bbB71/TSAHLzWphgQDnQPlLOC9S/MQztM5cUHWP0ohh3wY3JqMtBcRd27Uu1y3IUICslqtR3Rk+cp8e+TEqNH3ZjTqlxyOTt8JF3G9gQHradtnuG0VDT7Oxe/7XhYXm1RoOh6Np0p9yubowYOM+BwatCzFPKv3DAJIBgBRUNojC2z+TKIKSUhti6EFxPdcC1tYOJYiRXBU0JWYVn97MxR9q9j3nejB64zOIChdF4H2v+FCtKsglOQckLKHiUjNSyhl8Ve5iNymvi3i6kVgRNiYiNv1N2i1wton9jGMJz+03JLmnC9qpH24tYJQCgeAv9OVcjIlNX+Gwth94bzP1ipPOrDxKy134KPVQ/pom2nds6S84JKI7+vTkZtLSniyVRPt3jF4dRJBU9rU/wwWHEnh159nSIz7yGbL2EzMYwNBGQvRzG/Sgvq7wuhPSJQ8DTeyFfOgX4PeF1UiUqagT6N4YhpXSI+ZiW2PoQ0g083D/eZrofVXOxA+UoKpc3Iz1GQvXDbUy9QrIZvJXZzUSS8fEOdj6VhqRKZpRTH1sfgiZwEDNELSqzJIB06ghTKxsKpTivRqSvuAi+PUeKqC52Mt2ZehEOkAGRZpymCjp2nGDKb06uDEIXOFvqGOU420kjCtlC4kuqFHPkmxFM/F6r9TLk+S6/CL5nj2DgmjB0AUXys32bSH0b35UmazzyjQjEFFE+41QUqdhY440o4kumYuKTHTj2tQjGf78VJ24KQ3nnELBzL6ToH3D0HxZhwn+1DsmVTS8LQHUQ5TSqUpVcGYRjUIHsE0cskZv77BTgBdLu3/n3MFy9HAa/EUHNOypyVTy4/GDZ+ykRvAyM3Z9FfKKA2JcikJI6UteF4e1W0PPFCFNaAUidZmp5OOMaNJGDlNAQnyQgPY7DGd9uxeDVIShuDlUgCW7xGEmC2heYhLP+mSQAjp0twPeuinQDj6rjKnSOw+A5hYSXR/8+AvCAKgGOuIiqGnJPR1JnaorHbiso1aXGcZjwH+Tc9BUXMTU2U/nOuQi+vFvejmeeWRwA8mpMsaVTwXkmovqhNsifngK8WLhe7tIpSIyfbJq0UNUjeW4LsOvpsvViHERp4uD4ZBE4TfEVo8FIZPlPBal5F2Nc/h27b47AEddRd08U7i0dGLgmjFwNB/fYQvJS2cuBl0miXUdcR3ICD7kK4GWg6rCG5HVhpJo4jHlFRv95Ety9GqQkGcDTTU44BhUWH8CpRBEqtSIITeQQO5NHbU0QsoeDc1BD/9cicJ3UUXdvFH2bwnD3q0jXCXDGNWRqiPqc4gHca0IkOagOOJYFkBgvQHFzqD6kwn1SxuDZTugCoDo5VB9SkKkT4OlRMHCuBM0BSAkdipvDuDuIQp6YAmrfzkHxCtBEDokJPLzHNEhJDYNni1BdQDo/HvR8OUISH7+vQHNwSCy8GNhuVhr0PdhmigsDCHWSjinJlUGAAzJ1PKSkzsaH6ofbkF3gZ+qHVtAYm9j6EFy9ClFjqhfAzfcDO0gMweCKqYB7IjgVSDfy8JzQkK7n4O3RMHi2APcJHTkfmZakmnR4jnFwJHTEz+TAKUDtWyoGzhNQ864GzQEIGXLvEzeGoYscFDep98REHhP+qxXdN0fQ9JNWvPedMNwnyDVoXXOaDs3BIecDeAWQ4qTss/UcXL1E9VLIAtk6DlJcR/3/RDGwYirwRKGvG8caY/wRjdngc2Cfs7UCHHFiy1xbO5i9NsYmVT3aTpKuZnRk822KErkccRU6z8H3YBuLlThxYxjeHg1iSkO60TxNSo4VSELXuS3gVL1Y1ruBqLwBgOImCZ1pXLMucEg1Sag6TFTX6NhGx+v+jWF4j8nQ8pTn2JkiGjTz+GeVhKbxTerMGUiPdaDqEaLIqjg5otzm5JGr4lhiW2qDabLz1Iog+j4hYNJ3W8nCiCMLrNgZgknF88SNYfCvvA+8uBepeRfDt/swdAGoeTdDEi7XcCzpJ1VfS6wOwn1SLhq/eZnYCu3S6UiOFeDqL8zXrLFLUlJnm4Gx9SG4e8wJYnvXT4PinkhUU0/ocNxlVgP+IKG4ODa/yC7yY/AsCVJShyOuIbvAj1yNgOqH2oj90ICxPydtWsxqbCGcbOKhGONJDclhD/1zBJO/01pUJr4HC+q7VptzStB18jfSc/4KUKGxVVBBBRVUUEEFFVRQwd8wKtLTBsgesquRrhdQ/z/FrlDfg22QPzMBACC98DqQV6qwwtNDNN2NLlYfgFj+97410+B79CCkuFp0rhHZBX6kx4hM233sz1sRXxuC4uLghlkNTdzbxV6YrsaZSzpJdhaqjuZ3XBwcU66hx+b0/mGWEob06gCAmN8Jzc33Q/by0HmyA2Xc7TV6tpIrg6ZkWxSKV4AE4qlSPALZlVUIPY5XdMhujnnW6C5N7w1hCFnAM98PuUqAOHMG8GxhZ43PyIyK6dxBvEelvDpAnjrE1RV5ZSiMbYUmQ6v5LSmjif9e+rpAsbgCRfVTrwBcHfNKjPlFFDFDHU34L/L9UIIYRvoHde/TczL5nVaaY8kIu2R9AOD43evILZgL1cVhzH4d1Q9H0X1zBFWPkt0f6AA4YNK/5T0iywIYcyfJoeQ9JjNvY9XyIMmTkPfAeTa3Q1sTgvcx4rFzbe2AvDYEzwnSdo3Uj+pDJMDU97+vwPfUIQCkbVWBeNTorqXq4CEldKRWBCFkNFZmxkR0DosyzPgfFOrLXYLSpM6cgaSrB9ixF+49ryGzZB5cWzuYV+fETWGM+UWUeffyG7XwbXkF1Rx5XulFsxiE44XXUcUdNSld0fYm7d6HdP64+JKp8G09ZPtcFOPuIO8w9qfl214pWGkxo8WH4dUBCvYNAJp+0orsQj8GrwoBHODpkVF1RIf4TBdra9QL4X2sHemlAXi6Ad8PzTZNWhtCrlrAuB8Rr6KzX4ZnM+mriTUhyG4Ogkw8GA0oKEHVvqVD9nKouZ/ksaH9N7MkAGdMI/2R7srTXVOD91me04xMg4SadxU4dnZi8OoQhGf3o/5ZQu+SqwRIcbWQB+pd4o0RU8QjCgCNr+bQ0+xAaqwE14AKTeRYmwBQ2Jmf3Yz0sgB4WUfdm1nQIHzFYGd8D7QxD6O7Vykqe0q1ojZFz7cd2o77N4bhjJH6od5TgHj9cj6ejSXGMUXI6nDs7ETeAQPvMQWuWhWOnZ2oBhkXxTQH11MdbEffjgHgNHg/eJskkmPuLNjt2LoQsw9NPyH/nvXPhd9LJeIsp8xGBQFqnyCeXccLryO+bgGqDmtQZ82A7BXhiMvE3vXK6PuEhFqpQN1JjRXhiBOGA6Ven7gpjNq3if2LXxli+fcccQ2ZeoHkzFvkZ7SrbDXJx5dZF4IjoaH/ixGIGR1CRoPm4ODpIV7K1FgR1Yey8PaokOe2QHWQ3C2Y3Qy5SkB8sghPt8rKytVH2sLgVSG4BlRk60QoeXrXwHkSGmfNgOrgIQDI+kgeNUpvSjcK4FTiEaPjH30XgMwLVAdHPPxJDZnFAUiJQtsTMjp0DlAdPBQ3x9pgakUQOgekN4Th6tcxcE0Ygqxj0ndbyRiQ1pAaK0JdHjT1h/5rw2SMipC5nWfXq4ivXYDqh4k3jM9paPhlwZapLh7apdPzZS7BNXMG5GqRsXhcfSqSq4KQ4irq/pxl75ib12JqH/3XEpYD/U5KaVDdZL5D0fDAy/BxB1Gf/0znkNlZUwAb5dSRIhs4D+iwpxLWPPkKvPnxyrmtE671IUAv9PX0BkJXtI4zxjmHN+/VG7w6BE3kkKvmUP8mGREnfydvWwcK9ju9NIBUo8Dq1MhiGrgmjKr7fjf6l63E7BQgpUhnc/cVL0Kyi/yIrQuRRU4e8pxmeB9rR/VDbUitCKL/2rCJb6yLnInrmZ2V5+y+RyrbqMhBFUVojItj1z5oDg5Vh3MwovqhNghZHYnVQSSbzAotyuVE3URxk0GPNjrNwRHuepY0HKNyzXDV4yjfuFzchJG7nphAnk2TOLj6ZDZ5SjYJSK4kid5yeU6oq09hzxFbH0JqeRDZRYRT7N5CkuSpbh6qg0wicl4Onu4cvI+3Q3UCzgEVAxvCbJLo7iPv6djZiapH2iBXm9e9etfrJfnmpWDHlbZD1SNtRSp1w+aql5hcl+OYG+NFaCJb22vb8ODp5IOqsMmRKew3cW+X7fPI4U9BdXJwP9mB6ofbMLAhzCYHqoMHn9MgJgv9R8joyC70o/btLFJjJZKkcZEfUv4Y1U3aQGp5EM4BMqB5H88vik/KUNwcmeTNLY6Fycy6qKg91vy2DZ4n2iHt3gfX1g403hWF54l2pMaSNpBZHGDJ4oDSyjCZJQHInoIJEbL5gfqKi6C4BcQnF37jVJ09x8CGMLzdGlvolEJ25hTTZ9q/aBs2vhdVtymFzJIAUiuCrP5L9VE7GpEdTnWhY1dXo0E5JS8jpN8XbPLJz4fh3N6Jmt+2wREnSeqydSKhBNWLGLwqBDGjkWSQSwJQXMSuWO9b/VAbZA+Xb6s6Uk0OAPlJWUxF3b1RCDmykE4vDTAlKM/mdjgH81TcvL3NLvCDU3Rk6kibEfOJmKnN49TCiKo5eDgHChMgT4+C1Iogq9OqR9qgOsl1KOXX80Q7eFlji0vHrn2oPqhBSmtQXHmKjMHe0XJVHTzEhIrGu6KgCx111gxC0TbAkTDTcIx2Pr42hMziAKvzqkeJzLB7SwdJKtqtmBYZyVVBtglnp4oFmBevAKHuAWR8ySwOQHNyENIqBq8KMbtGFzrpZQHErwyZbKF22fSihY7RtqWWB6G4OaSXBRBbFzL91ntDXhHNaW4jaj5xcrk4HdXBFS34qx9qI7QsJxkfM/UOeB9vh/Dcfoz7UStcT3WwzTMhp0N1cpDnFGSnvd0as1nVD7eBz2mQ5zQjV83DlV+M8lkN7p4cqh5pQ8Ovo3DGNEYFqv9jFlJKZ7FUuWoejp2dyPk4CM/uh5DRkakXyebNjk6Ie7vg3tKBxpdScMQ1VB3JwdWnQK4W4H2sndk4MaOj9jdROOIamn7SCuHZ/ZDipH6lfDJZZ78Kx659qDoqw9stm+ZZYlaDc3snPE8QVUvfA22ovS/K5jLCc/tR9QgZb4D85tYjbSxRLa0n7+PtUB2kn5DnIffwPNEOIaeh7p4oPJvb2Xierhfg7SZ9zLgBZaSkK14yZ6HjMK/oUN0CxLTC6s71VAf6NpHfFQ9PFuy79iFTL5F2m2+P2mXTcfh2EqdSd28USn6MSawJQcjoENJqyXmAcQwvpZxKIVxwbtnf2XXyamzq+ZMK9wmeX3zvRX5GZx3YELalprIyNcQaO2KkTdbc38bahpIf85XZzfnvC3bAvaUDDb8mm6PppWYZ+drfRCHPHl4cpB04XR/V318DKjS2CiqooIIKKqigggoq+FuGlv8b6Tl/BRhxUtFPz/42js2rxllbM0z3nQa8DVwThuwF+Nfex4EXfowZwS8DF50NnQMcSR2ukzJiZzvQ8EuyK0N2DTlG73Fu6xwyMSBQCEo2Um0OfjuCM749MkpK7+fCcMRJ4LU1iVlyZTDvcVEg7d6HxJoQ0j0H8fKzPy56tuE8s6ksLcfTe2VrSKCnM66j6hHias/WCPA90Gai7qSWE8oReIBT9CLvV6aWR9UxsvPZe0MY1YcVyF4enFbIVUApB/3XhqHzhGbGkmhdeRvOfrsaelfxzsjRr0dYQHr3LRFobx7E6ztPPYGXEUMlIBtOUtHTnUzTeF33FXOK6CDGJI6XfPYWNOYFCrpviaDpx4WAXiv6N4Yhpolww+DVIVQdzqH/E06IaRRRFmkQa/fNEdT9WcaJaRIaX5Hh3NFJAol5Dp4TKlQnh+TJw/jDjtL1Yg1yNX4+fmsE435YeNbhJMLMzfcjs8OcyHQkdWF3LP3OmsDNdF9DW3lv7Rl468EffGiJVD+o5IzlkJvXglyNOGSuquEmFT1dyS//1mBtr3RM6tsUhiOhmejIxv5D24yx7VBRFAA4/I8RVL+vwXtMLlJKM9qQEzcSWtEHZe8+bBjfo+qzlxfllDlVGOnsyuXNUN08EuPEsnbNaiOHg/TSADK1AurujSI3rwViSmXvYrxeKcpfqeeOrQuh6nAWmsSb2sXAhrA9td1AsT70TxHUvq3BfUIuol3Tdkv/BYhn1n2y+Fh5TjPST+8pam8jSX5NYUws3ns9oXGW85bbJdl8e8MZePfeYnt/uvqEdfw5B5/COyC538qNSR8VaMiDost4DltGlVT0s5f+C0RxhElFlQx+98K/fvySikp7D+Ccb0RNxogqgtX+Jooxd0ZNNLb6u6No+HUU1Q+1QdrTxRY6AEm4WfVoO+Q5zSUTMmWWBIrkhWmnNLpRR7rQia8NkQy9eReuVerS+zih3mkScRFXPdIG3p5RMGJYkx7SezXeRcqKGgHntk7G06YTEnXmDEID2UEoIdZFgWdzO+r/JwrHzk6oM2eg4Vfk/97H2+HZ3M6kCqmhrbs3WhR7Vf/wy0ULHSr3Shc6AND041Z4d448gRelR5WivQ036ZyxHGPrzfSj+KKpTNLR+hs735CYqxy9DQBScy9m/5d9xCE6eFUIfdeFi353/O51Rqlp+rGZ4w6Y5aSlpIbqh9sQX0sW28Jz+9F4V9R2ANNEYvRr3yIN0RjrNObOKOreyiE1lnDSq3aQepE/M6XoOgCKBnHjZ+NCBwDq3kyz/9vJRtNkdbnPknulr7ioSBKTUniGSl4ZWzoV8bUh2zg/CuO1jW2l/kEiw10qqaid9HQp2CVts+KDWOgMJcvt2LWP2YehJEtL4eTnw6ZzjXLnpcrdSjNNrQhC+8wlpu8obckK2s9z8/1IrQjaPnd2gR/K7GYkVwYZTZmpFeXvnV3kL2o/xraQm+9HYjU5n1IWswv9rEzpe2aWELlto6xuKaSWB1ncpvEaRiizmwtj0pECHdm1tYPQ1foKW5+0zdjFCQJA9UESy2gnCW20IbXvFA9G1vYtz2mGPCdP287Hs8hzW8rSk0vROK1JMykySwLILAng+FcjjPonz22B/ulLTM9lTa9A24r1e8CcPNPYVvo3EltrbaPHvxIpem5qb6hdpwsd2hb5rAZvj2qi0BuRXeCHlFDZuJeb74c8p9mUVJQeZ4RzQEbVkQIFn3/hAFIrCOXcaGOdOzoZ5Sq1PIjEmhCrP6MNoM9NKXZM/j1/XzpO9F9LaFNG+uTgVSFkF/gx+f+1ovqhNtv40trfEDU2a6yt3bHGDT45MoWVhXGhQ+srN68F6WUBiGnF1GfVWTOQWRyAI6Yis4RQIh0Jst9u1xZofRkXOvTdx9xbSLsQW0/GjHLjBgAI551t/lyCykaTdQNAYmYxZW00KEXVL9W3rBhqjkJju0+FxsZidkb691eACo2tggoqqKCCCiqooIIK/pbxMZaeHjGN7bOf+Wc4XjQn17SqUlndiNSdb1SDKaVm9GG55Y1ubStK0XZKPVup73PzCQ2NeqCYS/oDfMdSOWlK5ZoxupmH81y9nwubvHMfBY2C3nN65BY0RI/a/mb3POXqfLj3LPWeRtqQ9ZjTpdxVDtZcSScvnYCXfkcol87Fc0t6TkvBSBEdLqxlxOopfDMa2o6VpUyNlsY21DX+FmDXt0vR2Iz9dyiBCOO1jbSbcrQVCnlOM3SRh+oiQh19m8K26p1WqDNngAoBWKkro6Hc0WuMpj3bPt+sGVDcArLbzJRNu1xlgD0Vyo6mG1tHlDOrHm23vVap69u1+cTqIDw9OeR8Ukl7Z0cLsraHw7dHMOZleciklqdiVyn6W8ahq/OnI+67VGX0Lx3G/GKUjmwHa18upfh5umGksRlhpfeP1MaWsxXapdNPia440vmYFcIF50L909tF3+uRaeBaX0b3nEl49ek7RkRjG6ov2CkingrofM+o4HsqNLbLIv88Khrb863f+fjR2Pjfv1L0nbi3q6wqEK0EYyV/0JO/UqA0hHINcqj4hOEgu5AsIowDrOupjmFlvM0sDpTM0m2F1W1bSqbZaEB7ry8oVw2V0Roo0AcAmBY6f20YakCmbvmhqEQjRdWj7aYyBEpTfspBnttiVpYzUGrohIRSIRy/K9AQR7rQAcwUUTv3+0gyN0tRMkC4t3QMSWMDhq+IVgHBcNUigUL/7d8YZhPb3LwWRnMyUqGyC/3s2nShk1kSAP/8AZO9t9apPLcF0p4uOHZ2wv1kB1IrgkxVqlz9K7ObQRc6gJm6on/6kpILHWOf0C4zUzhy1URRq/rhtmHTRazQLp3OykV4dr/t5L/UgsDzRHtRe7aj6foebGNjIr0W7d+EDjRECgaDcmHVo+2QPaKtvaNlZV3oJFYHixa+k77bWvReufl+Mj4Z6tGoyGh8bvr/cuqk1LYInYUNVO3S6cy+KJc3l61fu4UOpZ5ZoV02ndld6zG5+X6klxFKXnJlsIiuZgSl1ctzW0z9ILM4YEuVtdL0Sy107GBd6NB+qlzeDP3TlzBqk/F96LMPRXsyolTKCCu93wqqMlhqzKQLHet4l1kSYAud06VMOVLYLXQAgGsl9Dj303kq+HRCddPOmjis6xrL4sSNZvXh4S50qGrdUKDzPaOi4anR2PTR/Y0QP/vZz3DWWWfB5XIhGAyio6P03Oyee+4Bx3GmP5drZAsyYBSLnQoqqKCCCiqooIIKKqjg4wNOG93fSPDwww/jtttuw7e+9S3s378f06ZNw7x589DT01PyHJ/Ph2PHjrG/999/f8TvNurFjnYpWT0mVgcxsCEMuYrHyc+HR7TjWw7pOcVBxjSXBl05x68Mld0FtttRcm3tKATMWnYjcvPMOzWpFUHb69NA7FLeF3pfGvxIgwYzS8w0DDkypShYNLEmRPT7t3eyHY/0skDpwOEmwVTm2YWFIF7r+2UX+pFeGmCeK+Xy5mEFbdOcQ+WQnTmlaNdW+MR5Q55nhNGD0Hdd2Jz3In9to6iB1FrwXhy/1RxsnJx/MQuITi8LFIkhGHcf6Y4e3SVx7NpnGyw5EljL1dNdSPgmzynsYCdWB5Gb7y8K9jaCloO0ex/bkc3N98O1tcMUSAmQnBBGJBdczNoj3f1j7XM1CRY3BrXagdKY2D3mtZjaMRWAoP0itnQq+jeGMbByatG1kmNFU1umz0Tza8WWTkXWx6HnS0MHj1MMXh0ytZX4kqlIrAmhb1MY8pxmHP8quZa1TuJXhsraK9p/ej9X2GWjghSHb4+Y8gbF14Zw4kbyW/ctESTWhHDkm+S+J24s2MXM4kJfTi0P2ga82/V1Y1+m18rNazHZp8Sa0LDabXppwNSnHbv2scBnNZ9zRp7bUrSrT3eVAZiUpIz0HIC0U+NOrueJdtZe+Kx5ZKQ79crlzUg1FVIF0t1p6o3hXnypZB+hfUK7bDo0gbR/2ia9j7dDnTkD2YV+0y75UN5bK1PB6AE32n01cCEAe7EIWrdW7wPt89b70fZkHVfcT3aYki4aQcdJ53NmQRmr0pf+6UvQe0PY5NEx7vxLqeHNWBw7O03JgQGS48fY/6ioT3YBsVE01xFA+qDxHWi+MCNUtwD3FiLukGkQTc9cihJlHCNL7Z7zzx8AtbvSni6SJyxvfxw7OyG7ebie6oCzX2Hlbeclcj/ZwWiAxnJ2be0oSphqfR5jPjC7+YP38faifg3kPVz5XEKpFUHI1QK4F1+C6ymi9qe6iAczsSZU2O23ePaU2cXjvfF5jN4sOw/s4FUh07wss4RQp6Td+0iurvz7WHPeMdtnaG80jwxg9jLa9UvjM6eXBYbMLZaad3HRdwMbCjaYzqv4qZ8EN30K+KmfJH+XfIodb7Q1qXFC0TNrFxKhA5r7jY4Rrqc64Ni1DyduIoIRrgHdZEflOc3MVhjnJJnFAdM4TCm/TPBhvt/kxaP9zdhOaPvP1J1CKP6H4Nn5wQ9+gM997nPYtGkTPvWpT+HOO++Ex+PB3XffXfIcjuMwbtw49tfU1DTiVxv1Yifd5CCTyLEC4xpXH1EweLaI9BWkQ9DEa8bGH18bQv/GgmsvsySA9NIA+q4LY/DqEJQwaXCpfDLQ7psjhSSiCQ0nbipcyzmgIFNbMLT0uBM3htG/MYyqR9tNg39mMXFRCxmNNRL2b/44zZA8z5hIr/eGMJuQZWoFnLiJJObr+VIE8qfJ9/2rpqL3hjBUB4fERBH9nyDFS13BWR+PI9+M4OTV0/L3KqisUNd41SOFZI6yV4Ayu5kkNn2sHcmVQZYwjGLsz1pZgsrcvBaIaRXObZ1ILQ+a6BLJlUE4t3fCvaWDLQzEZ7qYcbZzeRsHMKvRzy70syRlAMCrZNJjnKipb76F7MLCIF5uIpZd5DfRcervjrKyAQBeJh3KyH83Jvgc98NWkxHkFZJh3PNEO9xPdhTx5o1uXztVraH4/daBirZbgEz6M/UCq8fE6iBSTSJ7T2lPV6G+H20nSmZ1DgxeHcLANWGW3Vu7bDqb7A1cEza5+9ONpH8kJ7mJYV1IjCGlwihBMgkTMgVDNHAeSfoo5r/L1PNIN/K2VIWBDWGisLSIKPz0XyDh4L9EMHBNGKmxZFIavzKEo1+PwPcAkc2mCXB9W15B3T1R1D5eoLxmF/jRv5HEbWTqeKRWBNHzpQhSTZKJ4ufb8gqcMR1jf1asrpi+wjyIHfsaacc0GZs+7QIAROGu6pE21P9PFNKeLpYJ3ErZrH64jSR2XBrA4FXFbZP2HyN1s/5u8n9Pt87KuvY+ojZJs803/bgVVY+0YeL3yH3H3BmFe0thk8X7GKE2eTa3FyVUpL/TMrM+C0DogINXheDYtY8lcjW+01Bwb+lgA2t6aQCJNSG20UD7grR7H+vz6aUFNTLjBMq6+KD0nOTKIIx0NCOkPV0migadvIrPdMH3QJuJLha/MsQWKNmFfvC/f4nc10BlMi5E6XUAwPdAG+svwnP7kasW2AYdQMpz8OpQYdNujXmccO4gNlSZ3cwSlNIFnHHykphI+oJWYn5B38d4fcVNYplMyQbHikyuOjVWRHpZgCVT7NsUxombwsgsCcCxax+O/n0E+qcvwfFbI1Bc5YdwSonmXnzJpPoGFOoytj5URHU1Pm85GhpA2j9NBgsU2kGmntgoY79z7CxWELX2AWn3PpIWYmcneIVMTo0bYVTF68SNRFUwtTxIFoQZndkrO2oUnexmF/iZ/aULkeTKoG0CV2lPF6vD7EJ/gepcXUhWHlsXgjKb0O0Sq4OQ5zRj4JowXE8R2i6ljZNYKnKP/o1h1o5Sy4MYvCrE7INj1z4oLs5U7qkmqfCsY3nEJ4lsItzw6ygrQ8GwmXDixjASa0I4+YUwcvPJYt+xs5OV5eBVIajOwrtm6yQMXEPmYdmawvvRtlDz2zbwCrE3xgVFbF0IuXkt7LfGu6KmibyQ1UGTigKFjQi7OYdqaM90MZpsElnd0fEsu8iPxILiRQ0AeHYVFGLFSYR6VntflG24sM2RV/4I/cDr0F75I/l76Q/sPGprAKBmx58AAI43DhV+f+Nd8l1eedg4RqSXBeDpIfVQ/VAb+jYVFlrSni6IKbVIYdjYBxJrCptwtC/JXh6aSBLfS3u62AaCcSNFdvNQZjej+rGR09YZTkGNLRaLmf6y2WzR5XO5HLq6ujBnzhz2Hc/zmDNnDqLR0pvqiUQCZ555JiZPnoylS5fi9dfLJ4y1Q4XGVkEFFVRQQQUVVFBBBX/D4HR9VH8AMHnyZNTU1LC/7373u0XXP3nyJFRVLfLMNDU14fjx47bP9IlPfAJ33303tmzZgvvvvx+apiESieDw4cMjfbeRqbHNxFKInFTyuPTSAOQnd41aFYkqaVw85yto2nvE9Ft8bQiOQdXkOh5uci47DJW8EjCr1gxX/aOUIgdV4hiNapSdEpFdQrFSqj12MCrElHu//o3hklS2j1KNrVxS0Wkzb8GY54+WuEJx3Q+lolLqntZkuAAwPXwzqmsnmXY0jWVoVGSx3tf4XJnFAYAr7MAalW2M6ium98qr633Q9ZJeGoDi4k2eBNZ3r/gKmvYc+VCSig51jb81WOufYqgy0T5ziWk3ExjalgxXCatUYsFSoIps6swZ0AWOCOCUeRajAiWlslnz1JRSqRxqDKCeH6tq1AfR1oaj2mh93uHaO6Bgg+yS4VrHguFgNOfYIbM4gMTAYbz0wo9xyaW3oPH35D1ou5HntiDdKMJ7NAfVJRS1pVJ1WCrpL02+CJiTWxpRqr2wa9ioFBa915IAhLQK2SdC5wseW4rhKgQOldzUqpgG2Ku4KbOboUn8iPqiFb2RCTjwYnFidSNOfiGMxrvM8wVaR+qsGUiOd8BzXIYmcUVjsM7DNM+hHiK79z9VNbah8EElFTWq8dE+NNR4PhJVvtjiaeh46p9HpcY2q/n2UamxPdv1XRw6dMh0P6fTCafTaTr26NGjmDhxIlpbWxEOF7zyX//61/H888+jvX1o8Q5ZlnHhhRdi3bp1+M53vjPs5xwxua//mgD6Zwq44IZ9OP7VCMbd0coqjMoXxq64CHh6L7KzpiBVPxmHF2jgnComPyJCruLZAPnOf4QxZr+Ok9M4VL0PgAOcP98OAMhVEadTclUQiotjndlqWOwMzZFvREwJFwGSmXrSv7Wi9/owNAmoPqLC9RShc6QbeQhZHe5eHel6DmPujJLM9hkd1Q+1oefLEThiOnqcR4D/JhOIgQ1huE8qcG7vxLEbpwF3ku/7rw2DV3QM3hJhCSUpYmc50GD43LduGhKTJ0F1AZO/04rjX40gVwO4egG5Cpj4vVbWyIWMxgarvk1h5Go4jLujFQPXhKELQGISB10EvId1DH4pAsUDuE7qiJ/FQcgANe9qkN0c3H0qUo0CUhM4uLt19P59BJlGHa5eDlX/sQ0AcGLDNNT8oZolFk01cagDcXsrHg7OQR3Hw0D1uzxSJw4DD+zFR4X0sgAGzhUx/vvmsnY+9zpQxggVUSlGKZ1qN9hL0T9AXTYZR78egZAhtCa60EmsCUFxcajOT+iUfIwErdv+Cxzw+sikx7W1A5klARz9hwg8x3Xwig4fCLXT1a8hfmMY1YdVZiQP3x5B7Vsq0leHwP1mh+3zHvqnCMa8oozofeW5Lcj5BNNgLcXVkupY7qdfM5X94PKp8D15CPKcZhz9rANn/gspi8ySAJJNAhp+FUV80VRg29DtiNKvVImDI6GB08Hsw9FbpgI//uja4l8Cyk1kykk304VO36YwPCfztvFsCbzNxIWi+qE2HP9KBON+1IrBq0OoOpyD8Nx+tkHU8+UI3Cc0OAdVQvEZL6Hu3sK16ACvXTYd6TEO1r5OTHehakwQnF6YIDq3dyK7yA9N4iAmVGQaJDZRTEx0IHNzBHV/lqHzQN8nJYx/Jj/ZzGqQdu/D4VlOnPms+fl7vhiBI67Dkf8cWxcyUWcBssiR5zRDyU860ksJdVv78/vAs3sRXzIVvq2E3nL0HyKY8J+tOHx7BJoTcJ0AXH0au6Y8twUnLnFgwn+04t3vhuE9zCHdpGPMAQ0D5wvwvasSqvL5AiZ+r9UkBzxwTRiqE9AFwDevBUJOQ3yyE9kjB4E9e5m9e+uHIUzaq7FUD5kGCY64Cp3nUHdPlE3Suw3j08kvhMHLgLoiCGe/bJrkd1vGsf5rw3D3qsjW8Mj5OIzJf997fRi8QqjZzgENvEomqMdvjYDPATkf0PCGgiMzybhe9yqHhl9H2fVzej+APC0obzs0iWOTPbq9KqCwWBm8KgQppUNMmZXqUiuCSDXyaPzvKJlAC4Seadf+6UJnYEMYzpgKTgUGzxJZAld5TjNiZzrQ8OuoaWFkVClUZjcjWyvCEVch7d7HFid8TiObWnOaoTl5ZBf4wWk6FI+A5DgeY35hjssABwhpDbrIId0goO6eKBKrg9AFDke+EUHjqwUZ8P6NYVQdzkF1kyTSqRVBOPtk5GpEKC4evKpDRD4etVaAmNEhJTW4nupg7You1OjCbuCaMKqO5hCf7DBtbho3fKUX83OCeReDq5sET3cO6bEOOAYVNqYa7UVsfQjeYzkIWQ2ZJQFICYUlSjdCu2w64pMEViYUUkyBtKeLSebTBWx2kR8na7uB+0+PveenfhLaK38c8Xknrp2GTNUkjP15oY8olzezzZZD/ycCTiXKhhSeze1soevc1onY+pBtmRz9B1LnRrz1wxDG/f/snXd4FFXbxu/Zkt4bqZDQeycNkSZdpXekKCiICKioCAICgoUX5AUUeBEB6SC9f0R6EroICEpPAiSE9LLJtuf7Y5jJ9pZNw/ld117ZzM6cc2bm9POc+0kAJIVqPG8qQegCNlzNusJlv2VO2Q1CAKwUHODM2Dw8PMwOrvz8/CAWi5GWlqZ1PC0tDYGBgRZFJ5VK0aJFC9y9e9eqZApmbAICAgICAgICAgL/YkpjxmYJDg4OaNWqFeLiSgaparUacXFxWis9plCpVLh+/TqCgoKsvTf7mrEBJct/LaM+gM8Fw3Z45q7VXM6uLNhr2dSS8y0xR7OXGQHALqnT1sNWL/+Wt+lQca82KD5wzKwZm6n0FL0RCZFcbdJ8Rdf0pjRORSuCijQvbNJlMly9Q6HefuSlMWPTNH2pCpgyY7PWOWfWqBitFRlLobbNwZz7Q+uYrkmOpnmG5nddU0/HTDkKAx0hUhE/s8vVfYZMQDLHxMD9sULPnwyftheOA805NuRmv7lnVtgvCgoXBsyv+nWlPetjSzGX542ZxwCs6I6uaAFg2ITLlCNMQ2jObhtCc5Xk2fuxcFpxsNKZoGq2wdaaYr6sWGLGZimWbCMwhbX9MaMOTqObAon6/iMtMWOryH6qpgNmTUrjVLRT888hETuav0AzPlUxfv/jG4vj27ZtG0aNGoVVq1YhMjISP/zwA7Zv347bt2+jWrVqGDlyJEJCQvg9P3PnzkV0dDRq166N7OxsfP/999izZw8uX76Mhg0bmomtBJtXdjQlAgv7RvEKOZoKXpLzrKMwTqFLU9GLkzw05gCMU7kwhzkZQl3FD04+VVOtRVNS1RqMyUGbo6iTvqy2LnrO3AxIMpZlw8q0amT+JAvgFNg01X00nZoC+nmgYECUUXU4Y/fMKbxoYkhhi9sjY6iS1ZLe1FCj0aS4YyMU9otC2qRYk46/zEmwl9ZxqSWS4fZGS65b4/7++Z+OU0kXEYq8RUj+WFstx5yqE8BKTwPAs4mxePyhvnS1sfDuf1PyLtJHNYOsD+vsTjNvPfvAvJy1JQ5NH34dg5TpxsNK+7Akb6R9WHJeYb8oPPk0ls+rnKLf489jTToA5NSTNOu6x5+VhGsozZpKhbpoDnTMyY4DsHqgY8pJoMuu81oyzZp26JrfuYGOsnMrOO2/AObcH3D97Ty/B0OzHjDUmff5JcHoQAdgHQfmjIg268FdLGdtOrhn5rLrvFFHi5pp4uTOLUXXBYG9MDbQAWBwoAOwSni67aruQMdYu80h+d20o3HNfTKaJkC2YK0TYnN9Bg7NNtjUQMfWfgCHvety3brE0vvVRdddg+K1VhDLTTu3NYTRPl4pBjq6yPpE4smnpsucMdlyQwMdrbBj6+gdy+jHKn9y/VRD/Q+TYWqosRmSrTdH0euRMKZ4WdzNeoflPOUgPT148GAsWrQIs2bNQvPmzfHHH3/gyJEjvGhBUlISnj59yp+flZWFcePGoUGDBujZsydyc3MRHx9v1UAHsGHPjoCAgICAgICAgIDAS4QaAGP2LP1rrOSDDz7ABx98YPC3kydPav2/ZMkSLFmyxPpIdChTM7bSqLFVpuVsDkNpKxgQBdUObXMdxWutoHYQwfHQRYOKK+bu0ZhCDIe1JgWamDJhseXZV1Y1Nnunx1ozNqceXUtt9qC5MdRSOEWn8ngv3CoZt8FSN05b1diYoT3gvjWxUpmxVTWsVWN7WdEtQ0WvR0IsV1tdrnSpLHmNNxmPmQSfxKfmL6hATJmCaT5P525doHQW6bVTxsx2DKGrxKZpFmkpqo4toRYzkBQqWZNHHTMoQ/Wzun0LqKQii+KyRjnVVBpNqcaZw5gpo9HzbTRjU3VgVdh0BUAMYUxFT5eqqsZWVnCm1qUxY+vc+FObzNjibnxnVXwVgdUrO0XdW8Ht6J/IHhkDiUyNYk8RinwZeN5XQS1hoHBjIF3NKqoVd2wEnHzCvwTOXjtrdAycslV8hs4cwzobzHw7BpKf2Ws5lZuMsTFQuDMIXBKPzLdZ5THf/yXg2fuxCPgxHqmTWUUdztkfwJrASAsI3usSkD4hBion9nouHenjY6ByZCBSAt535FBLGJCIgdJFBIULg4IgBt7/qKCWMmBUhGIPEcQKoCAjBTgQh7zXm8LjYDIyx8RA6cJA2aMJcDgOWQOaQswE80pyhaNYRTeuA5o/MAp51cWQP0wGdsaxJjuuIfDYkmhQwpKzAX/+bgycM9WQu4ngvS4BLrvPs47TXBg4Z6pBDOuckrOBNSRFySF3FyHr01gEXCpGbrgDfNYmmBw8FQyI4uM1RebQZijyCYXSBXB+Tvz56eNjIAtg4JQJkAhwSVMjL0wEtRSQFrBKZZlvx0DhxkBSQFA5Myj2BJwyCUV+DNwfEvJDGUjzAbUUcHusRibzBNgSx6t88c+rRxsUyx4DJ+KQOaQZinxDwagJaimDIn+CWxJrupE+IYZVCPJkIC1gx/oOuQRJMSE3TAyREpAFAG4pBHERkFMHEF9KAfbGIXNoM8g9QsC8UC3x/TkBOSOikZ/9GNjPdi4LujcBfMRwAOv00D1ZCYcjF1HYLwoOOUoQw5rp5A9i36H3ugTkDouGpIggkhOUzgzcdpyH9NglfiCR/Rar8uecoURuDSmcMtVw/e08skbFIL86A687arhvTeS9POf0bQrsZp+RoyKwxMt9vyjIfEVwT1ai2EsMtRiQ+YkQuFRf1SV/UDQKA0Tw/keu1ahnvh0DaSFB7saA6dUGuTVEEA2KRiaeANvikDmoGURMMLCtRBEudUosPB8oee/qjBrIDxLDMVsNqYxQmPcYOPZC6bC2CAVTYoG/koCjcZDF1AESLqKgexM4SoLgePAi0j6MhetTFS/Vm/FODKRr2LojfVQzKBxDkFsTcMxgoHQBAq4qkVtDgoDl8Xj8WSxESkBSSKzTQhcGCjdWSUpcBPjdUCKlowhO6SK4J6sBAnLqiFB9TjyevR+LIn8ABDhlAg45BK9fE/DsA1YBsciHUPPzBKRNYlV4An6M5x0Nu6WqkF1bDJUD4HNbhZyaYpAIcMgmuD9W4VkrCarPiUfmmBgUhDJwyGZVGT0eqpHZkIHrE6DIh4GkiI3fIYegdGXgmEVs3L6s8qLCDRBdTQb2lQx2FK80Qn5IdbhtT+QVKAN/YFXUpIXE5skCNRyOXMSzD2Lh/Y8cRT4SOGUq+Xf//N0Y1iN4thJqMQOZn4TPK7r1V/6gaDjkqvh877KLrf+luUrkhTnwHsK5DiQ3CcOphRW9HgmVEwNJoRokZuthcZEaCg8xJPkqSI9fhrJzK2Q2cETA8ni+45g3OBrSQjWKvMXw2pAAubsYBS/ytLx7G+REsEpbXF2ZOzQaLmkKfn9JxrgYvlxzcJ2vwr5RcMxm1crUresDl+KQMbwZPDYnsQqZHgy877CKWboTVunjY+CSrobcXQRGzTohlRayap/FPdpA5SyCWgw45rDtqNqBgcpBVKIW9lYMlM5sneWUQZAUERSuDIqesG2SJOEvPH+vJ/xWl7wPhZsIChcRXNJZ1VDNjq2ia2sUeUsgKVbr7YECgKcfxSJosbZ5GS+zPzQajrkq/vyMsTEAAS4ZKogUBJGCoHATw2XXedZkWcS22Son7SljzcFPQfcmwJE45PRpCkclA+e9FyDv3gbFXmI45KkAAlSOIiiHse/rWUtHuD5h84bXhgRkjYrhn6mkmCDNZx03Kh1FcMhTwfEQq3qlFjOsiuqLvJo/KBoqB2i1l1wezA9xgFOmCszxa8gbHA2xguDYsSXknhIUeYnh/FwF6Yu6x/fnBOQNiYZEpuYdFRcEiuG3KoEfaHGKb8QwkPmJ4HW3mDVnZlj1NecMtrzIu7WGwo2972JPMUjMwPmZAiondgI18+0YuD5VQqRg1d4023tF19YoCJRCWqiGuJhYx6YvyqaycysUBkjBEFv/iuVqPj/I+kRC5i2Gcyar3FfkLeL7VPmDoqFwZuC9PoFXY9OF28vmuTERucOi4ZShBEMAiRgUe4mhcmDglKVina1msQqiBQOi4JwmR26EE7w2JCB7ZAzv2DV7JNveEcOmVaR64XB9YBQcs1iFtqJOjYHf45AxrBnUkhAoXQC3Jyqk+acCP2urtMm7t4HCVQTX386DadEIdFXjPqKbAmoCLlwv2TcY2QQ4fxoAkNOlLvB/F6GsFwr8/ZdWuAXdm8DjaAqfBwDWRL3IRwJpoZp9ll4iKJ0ZNm/KyCK5cQ7OvYisTyQKAsR8+TakHAmwE+EFrnLg170Wx6GFDWZpVp9fQQhmbAICAgICAgICAgL/Zl7iwY5dzdi4GRFrlhF1ZwTLyzzAFhOhslJjK+gfBafMEv8GphR0ABjVZdfEnMM/Ti1H3r0NSMRuxiwvMzZzZnqlibOymLGZi9vSpXpDWOJI11h6zTmoM4XZfGknp6K6Zmw1Y4bhfsJmvXB0nTDa493bw7SkMmCNGZshVSRLTIYMOSIFDOcTU6vNFYlmPcj50WFUJRv7jam1ZUYH4UrCMn0nw+WUfzjzpbIyY9OsYyxxdqqJUdWrFxiq/02VXUPh6TpZVLzWCowaegpwppxF6/6m7NQKJGH4fgHXhhb2feF/SKc8mKsPgZLVMEuU+gyZ+Zlzdq37u2a/Rtd0T/OZqTqwm9gNlXHdPMyFqXitFWT/d1zrPak6tESxt5S3DOGsRDTN64x9N4SsdyQcsxX8+zZlfpgZGYgr55dXSTM2rs61VeXTWN5Tdm4FHE+03Yytwce2mbHd+s/LZ8amfqUpcI5VWZP1iUSRpxiyAAa+NxTIDxYDA6KQ5vEU+DkOyqgGwIVU5A5lTQskBSoU+UnhvjWRd6LIyXrmhEvgdV+JXDwF9sVB3q4RcsKrsyZFPiJIC1nTKM651LP3Y+GcoUZhgIh3AAawzrZArIJQyvRYOGYT76jq2fusM0alEwMSA+7dWqPYWwJJkRpKR3apUaQkKB1Zh2fZb8WgyI+B1x0llC4iFD9LAk6UmE8VDIhCkbcIhc9SgD3sEryDOgh5IWJIigCFG4OA5fG8R+HUybFQuAPMn8nAXtaMzWNfMqQFahT5SCHp1Qb5gRL4/sw6f2PUJSo4XKHIG8wOdLJGx7DmCQcv8o0R14Hm1GG4/UJc41LYNwqMmqBwFcExS4Xct2Pgda8IhdUcoZu9+U7Ai0JpzuY5p19TOCiCkFudzVKcwk72yBjI3VkzFM6RK8B2ulVShl/SzR4ZA3ExQeYr0lLnKewXBWIASZEamfWkcMogiNex5kpFnRrD48RjvoIt6B8FWXYKcDwOeb2aQuQaDJUjA7WENRXjGoaMd1gzRpKwpkxqCeC/MgFPPomFUwbBMU+NIm8RXJ6pkFNTAkkhgf5mnQhmDm4Gj+1JSJ0cC6dMgmOuCkXeYhRksmZuAJD7ZlM4KQLhcOQiMsbFwDFbDbcd5/nGk7vXJ9Ni4XNbCZUja65TGCCBY64aLrvOQ9m5FfKDHSCVsWZUjBqQFqiQEy6F32rW7M0hV43c6hKQhDUH5O4vZ0Q0FI+SgNOsyWVO8zCEfR2vpaCWOzQacg8G4mLWfEnmJ4LHIyUKAyQo9mbNPp9+HAu3x6x53LOJsRAXEfLfi4HLMzUYNcF57wU8+TQW0lyCRAbI0pKBw3Fw/r8bUHZ+DQUOacDhOMheawwKCmPNRRnA7YkCeaFSSIoIcnfWtKUg6zGwlS0TTA0RsmfEQvEwBdgYB7kne47stcZwkweg2EfK2/Nz+fPJtFjeKW7eG00hcgmB2/ZEyHpHosibNRHhTJs4NDsKOcOj4bkpkW/ks9+KgVRWYiLKmSmkj4+B/8qSMJ6/GwO/1Qm8KS4H53A5cwzrbNHrV9bUJqcu4PKEgUMeQeUIMCqgIIhB2NfaJkOF/VhnylxZ58w5JEWE3AgRpPmAx0MlZL5iqB0AqAGxnI0nZ3g0mI2GncpyPJsYC7enKjavuYoheTFw0TTHyBkeDZd0pd6kkKJrazAq0vPozZVDpwMX9AZLnhsTkTs0Gs7pCsgCpPxkDdexkvWORLGHmHV22KsNoAYkMhUKgh0gkRFcdp9H/qBoiOVqSPJVIDEDtYMIGY0kCPkmHtS2OfJqOLFmVCrweY1EYJ0aaqQlb3A0xHJCTk0x/K8WAyhR23Lee0FLdVDtIIIIbCet2EsKRk1wyFVClPsYAFDQowmUQWEgMSDzZ+B/jTXDyRwTA0bNtkPcM+U6jfkDo6CWsu/22cRYOOaooRYzKPZhyx1n5p0TIYHfn8UoDJCiMIA1Nc0bEo28UBG87qvgAiDv9aa8GZu8R1coXFkzOXGRGgo3ESQy4jtFOcOj4ZjDmtJJZWpk15QgaHG8nhmzrHckVI4ivTYBYNt8hbNIz4SG63wV9o2CtEClJfMq794GagnDp0OkND6/ypkF5YyIhkRGKPQXweu+gg9P1ocdjGo6EpV3aw1JoQq5EU4QDY0GiQGHfNY8z2n/BeQMZ9+3WM7WWVmjYyAtYOtkWe9ISGRqyN1ZUyuHfDXvwFTuzvDtbsbYGKgbxMAhj+D8XIVCfwkYIjiBrUvZ+lmNwgAxfNayfQeXZwrebNfx4EW9Nu/ZxFi4pqmgcBGxJsxK1sFtwYAo1mzPgYHHlkR+gip9fAykBS/K+IvJA6f9rOmn0omB0omBywvTOm6bgfRFfnfMYc3yJWAHYLnVJXDOILjpPH+ubOjCDcQyX2sMHI9DYbcm8DiWArWEjbfojUgwKuLzkdxDAvSJhErKgMQMxP2ioHRkICkmuICtexWuIkhkaoBhnb4WvREJhYsI4mIJCkfGwCFfDXGxGhljY+CUxZpty/pEwjm1CEj8E0U+bF8ja2BTMOIQFAaI4PlQicLiJ8BR485GmdaNISoohurWHaPnaD2TTnWA3y9CVScUuMMOdtQNIoBbFyFv1wg4+0Sr3uSeL5dXuEkUtYQB8+K9um9NRHGvNuwemxfmhSTWNqfMfot9Bi67zyPz7Ri4pJf0n7iylDckGpIiNq/Lu7Vm68XOLYA4G83YykmgoCIQnIoKCAgICAgICAgICLyUlIsam7HNVJZcW5koT6ei1pI8MxZh80vnr8CWdD3tFoqbR36w+/t68kksghcZvp/SmLElzY5FwBWlSdMAvWtmxcLrK9NO7wyZsVWkI7rS5DFLzDMsidNWMzZ7OBV1eLMb0ptK9FZMjKkPaR5/NjEWLulqg6aWuuah+QOjkNlQDJ+/VMgPESPwB/08W/RGJHLDJPyKZdEbkZC7ieCYo+JXkjRXmbhNqSlfxMIltUR8hVsh1iX7LXZzfMCKeBT3aoPUKAm8vzxUrmps1ihl2YoxJ4SaJqHybq3BEEpMeWwwV7aEimqndPOfbjoMqX9WFLI+kZDmqfRWALn8rYmh51lapbGqjDETUWvRNXk2Z8asqdZq6Fxb8n1ZvUdjaXncMwy3Di6xKo1Mmyagi9cNhl9RamyaYkEc5hyxFvdsA/HBeJvN2F6r+5FNZmzH/1n88pmxpX4QBe9UKfJDxCgMJER8wap5KVwYFPmwJmWKdo2AMyUNrVhRMp568mksQGDNZ/JZxa3g7+KRMp1VSJInpQBbWdMXjzjWVCBzTAycs1QoqMaqF/n/lMDvDwJYkyuZvxTu2xJR0J81EVA6MZAWqJEXJmYbv1xCbi0g4LIaxR4iOOaqIc1XITdcCrWUgVhG8P05gTevyxgXg2JPBsGL4g02mHmDo1EQKIL7YxVk2Y+B/2Pv15SNLdeB51RE0kc2g8evScgYy6pbeWxORNHrkcgLFUOkAlSODEBAwIp4pH0YC0YJ3nTPIY/gkq6E0lkEtYSBSxrxDjwd8lVgVIDCVYSCamIE/MiaMIkUhCIfMZSODIq9GfjeUiA/UAK3p0qQmEGmUyqwnb0PrqOuacaWVd8Rzs/VYNSsMkrG2Bi4/u8Qf3+8SYpG54M7lj0yBsVeDAIuFaAg1JnvSMq7tUZ+sJQ3AZJ3a43CAClUL8pbYb8oSApZlainH8WiyI/gO73EjE1Vozq81yUgdWosvG8rgEPHSt7REFYRKqueFIFLSjqhTvsv8Pel2YHkVPoCl7KqW8XegFgBSGSAIqYhkFCSp/MHRUPpyPCVkaJtI+BciRqbExOEgmoSOKDE1KmwXxQK/UWQyACXNAUcjl7C049YUzGRkqCWsCYO+QOjoHQW8R0CXh3ohbmipkd7zhM8oN2xk7/aCDgdB1mXJvA4nqKVDzmTLUN25JrlKuOdGDhls2vUSmcGjArw2JKIvMGsCZzv/0oqYnn3NpAXPAZOlzyjghcqhZlDmkHlHMIr9D2ZFgvHTOKX/e8sj4LLoSfAQcOmB5wZgaxLEyirh/Gdf84MxHXneS01tqwBTVHjtwsI26+/P4Ab0HDvXdY7EkpnEXzXJPB53iNJiSIv1qksZy6S8Q5r0hryrfZgRi1hUP0r9hhnEsJ1SLlnyZVB7r3J3UV6e+6UTgzfUfXakIDiHm0QuiCed4wr79ba4ECnYEAU1FK2jgBYc5kaB4FcnfM4s5O0SbEQFxOv6pM2iVWzVLgycM5Q8yYR3PMVFxPkHqzZncyfQegC9j5cnikh92QVo+TuYrZO1zCHSp/AKlV6PFLxNunp42MglgMggMSsWZ7XvSItNbbskTFwTypGfogDij1FcMpWQyIjyPxEcE9SQNGVrS+UTuDNCR1ylFods4JqUqjGvnAyS4DjoGjIfBh435Gj2FsC153snoKUDk4IOy5Dkb+DXqeOe1fcPgfu/+KebaByEqE4Mxk48cJsdVg0CquJADUQuJRty1xSCSRi1cG4ib4H38TA/T5YNT0AuRFs3lF1aIliHylya4jhnqSCzFdUoro0LBrpLRj4/smq7DllUYl58sAoyDJZs11lTEPk1qzBm8YFrIhH/sAoiFSsGbhrKquAxeVNU3sGOTM2uRujpXL6ZFosgr+P59+l/8oEvi4BSgadXD1kLHynLBX/vjiVLOw8onVO2qRYLfN0Q6RMj0XAVYXehFJhvyjkB4r5yYXMMayKq0u6CgpXtuzxg8boprxTybuLo1HjCGu2yZm3KV1EkLuK4PaYVW2Ve0n4/Fz0eiRIDD2JbO79yLu1xvNmDgj+Tv8+OAU+7hk4HLmoNTlmbqCjaRLNtRNZo1mls6x6Ej5OtSODtA9jUe2/7P/F7iLejEyapwQ3QcG9O8174c41hCK2EZDwhL0PJxEcsxTID3WAtKDElI1rX8QnrvCTIdwxzXs1NLmWPTIGKgfw9XJWHSmroqhxnTKqAXBev81wzGNNHKlZXeDPdACsgqjP2gTWRJVhHV9nNmTNgZ3TWdW3gq6xcHtMkBYSpAUq5DGpvMKq0ffwelMU1g2D9z8KpHSQoNY0VjktuReh7jjtfPn4s1i4pbAKbQCrrOmcoYbKgUFhNQbuyWzfNODHeH67hrx7G2TXlPJ52eHoJX5iO21SLOSeQNj8eKROjYV7MlvXZg5uA2wT1Nh0EdTYBAQEBAQEBAQEBP7NqAmsXw0rr6kCWD3Y8bqrhOvRK1CMjEG1/7KbSWW+Irg9VsJzE7sJVbqZ3RyreLF5S1NtwvtvJZz3XkDu0Gg45Kvhs5Yd0bulsBv0sJWdpXY+fgNgvPnN9s57LkD5YjZD3q01AHYGRaQigMAv3bv+dh4FA6LgvY6d+XJ+TvzMhy/YVaAiHwd+9tpP497yB0XDJU3Jnvs/dpNhMScaANZXBc6ym9QDC9UIXMrOokmesLPfsi5N4LH/AvIHRkFaoIbCTQy37Yl49kEsApbHw/WpGk8/joX4yiMAgEu6GsrOreC7JgGqjqw6itOBC3B6kZ7coay2v6Jra3j/LeeXL93BzgxBBLjuZGf8HfLA+0zgcADgipINotJ8FTw3as82qPtEwvHQRRS9EQmf7df4447phdDMwnJP1keJJr5rErRmkDmTHJHGSh53TNNsQXNTpMPRS/DR+d8BgNeL/zVnXDm/D1ycTr/fgAfzGPLubfiVm2KNsDhzj8CSxSd+Fp57lpqz5ZobzzVFEgB2SVsTXRMnTf8Drkeuw4FJgQOXziw2f4hlarinsIIDuvek6siq2nAqOc4ZSt7XiOvO81pL2k7ZJZtzlS4SdhOqjnmLw2nD/hAA8DOxRd5irU3IxT3baG1Odcwjtjz1j+I3mHNwqzqaSk0qR+2dja6HWbMAn63X4NizGn+cmx0ueoPdCB52hFCYyZa73N5NwbiEQO5e4q/L/Xd2I6nz/10HvRXKh+PyTAWFswiKrq3h+3NJXvTe+SfwwrTAmCka9941ZzK5GUOn/SVlkNswqul3RRND5rnce+DqGG41iVuN89icqLdarKt2xZmecO/KmOmC687zcDX4izbSAjUUXVvzs+XcKku1ZfHszGoW+yzUrzTnrwlYwYpeuKQDWXUk8HighqpDSzjmqlHkK+afjSP0zWW87sghPX4Zqo4t+dlY/5WszxGGABCrnFXYNwouYOPOHRYNl2fsbLPj65FwylZB6SSCpFAFr7usWqWia2u4pcihdnzhT+rFpnvntGL+OTFdX/i5KFCDRGzYbmCV1cRFbP5WuEpQY3Y8K8RSqNZSY3PeewGyagy8AYjkauQNiWZXdXqUqFQpX9QH8lcbwW9zIjjjjeKebRC6MF7PeXPR65GI+DxBa0XF68VvhdUc2JWAkTFQOrO+07JGx4BRsZvRpYWREMkJLs8Ixd4SOGazZcUhTw318Rt8HJxlALfKx+Upzdl5zbqZW4HQFdcw5nTa9y8F/12zruTuj/PXQwwDXUN3TfM6TcsHhyMX4QAgrXNjII6dRZf1iWTFS7q3gcxXzK5C6yiEKTu3QuhCdqYfYFW7cmo5wD1FCWmuEu5q4utM5yzWp5+sdyQc8ti6mCujObVc4JnIrmjX/ogVA3F+IVAhPXYJUgAOHVuiyFcKkZLguvO8ls8WTdEXRdfWIFGJAIHD0UsIPqptDibrEwliGIiL1Pwxrt7h/sq7tYZaKtJzfqtu1wJqqQiS3y9D/aLn5rWBFStQOrL5xnnvBTAv6lXFa63gkK2Ey4uykjuMzccF/aPglFGiLlfcqw0fR+6w6BeiHiXv2hDS+JsA4w3HwxdR9HokCoIdXqxYsPlLs13QtEQA2LwiKVRp+SXSReUIMEr22QHg6y3OV1NxrzaQHDimdx1guO3jVii5FSQnsP0orXMAiJo3hPoP1lTNXafN10TRohZw9SLcD/wJDyYZhX2jEHCZUPQGWw5CxFFadYCsdyS87qr4NkHerTUcClhfVJlvx8DjoVqrLeHaVxKzfZHcF/6lir0l/HYFiYxQbRl7XuCSF/7chkWDKS4ymm6zvMQrO2W6Z6dxtylwCA3TWgrnMLaMzkl6Nm/3IfzOPtE7V9PMhoNTDrMWbmmTQ96tNVRO+p6bAbZjVpiWZBepw8q6L6m8pKdLy8sgPV3WGEovZ6KpaWppzAbYnOSpoXOs3bOjeb2pPTu60tO6HUlT9/xvxRrpaQHrKYu8Zq3Ec/7AKKi3H3kp8rxQdqsGuu9JV6WVU/bTbFcUr7UCiRm9dkZTdvn5ezFwe8KqjeUOi0aRt4jfg1jsIYZzBmteqGnGZq891ObutaL27OjCmaeaQ0kK2/fs1PwQEpGVe3bUxTh+/78v354dAQEBAQEBAQEBAYGXiJd4Zccm6emC/lFa/xf2jTJ4nsvR6wZXdYp7tjG4qlPYLwqSBHbk7HCGXYrklgU5dFd1inu00VrVyRodY+FdQC9tDkcvwXkv64dFF6f9FyA5f8visC1F2bkVvxSvi6Jra9PXdmpl9/RYSsr02AqLuypiKF/mD4o2cKY2nBmnyXP6658jf7WR3jHvdayvF241RdHVuLJLkbdY71jGOzGQd2uNvMHRkPU2v/JjNL0v7slp/wUoXjOfh50TSvwh5A+MMriqY66sCAiUNZpmnrpo+u4xhu6qjrlrrFkFepngzF9Lg7pdC63/VR1aQtbHdLjFPUvaaUNp0K2DOHN7WyjP+kzV0fy966KIZdsXXd97LrtZvzGa7Yr0+GWD7Yzm9ga/VQl8e+KxOREBK+Ih79YajgcvwmNLIm/OpylGUdSpsVVpLgtUbRoYbH/tjbx7G61VHUvqE5tQk22fKoDVgx1F5xZ6Aw5Nh2TmyBoVY9DDtKbdqCZO+y+YLPi6nuQ5xSeANVOr7EjiLhuVJ9a015V3a63XYbbUdO/ZB/YfmIQutEzmWrNRSJ/Apt9YJ58bZKZOiTV4jq2Nh7GKIfutGK2KKu3DWIMD9+fv6ecjYwNUY2jmSw5D+0l0MeRdWdNOHGAnAPKGsM8reySbVmN7djRtp01J8upKwwLsvhWHo5fgvi3RqF2/MTTLMKeeBug3lqaQvdZYr4PHDZyskRfOGFfyPjm1M2PkDyz7hswY5dGI6mJpvs4dGo3MMSXPkVOC5OD2npkiZ4TxZ1/cg02HsjM7GOZs9zXD5/K6MQoGRJntNBb3bGPynnXrA910aGLKvYI1Uu5cp9oW+XdAO89aMplgKcba6PKe+LJ1kkUT0Zmr/Hf1K80hPnnFqHoch2a/xVAadOsgh6OXzE5WGWvTjNVnpgYllpQ5Q4hPmL93XaTxJe2LbhnRlRq3FVMSywC7Z7c0qNu/GPBGNwXTpglEjeubPF9VJ1TvWJGvhO8PGysf9kC3j2isbuDqS5shtW2fKoBgxiYgICAgICAgICDwb0YwYytB4aJv3mLxta+10ppZ1sTx4EW47DqP4o765je87xArZ/Y1zdSMze4bmvkzprxUkTgcvWRwdcAQurNJuipqupR6NsAEmjNg/j+ZTj/33N1TVAZXPYzN9FDb5qbTYGQWxOvXBK1Vymr/jTe4SmnIv0lZOgs1N0NkaFXFfSur8GVoRcYSskbZtgrKpdXUjDegP1NpSRlTtNOuC5yP68/kaa58UbO6ZsMEoOUfiFM7M4bbjvN6K2m6mLt3TXKHmTdd5NBdQbcH5u7F0nztsSVRS8FL15GlJQ5GOTU3Q3Ar9twssa4fHPHJK2bzuuvO82ZX/BwPXTR5z7r1gSmHjPbCkOWDNWiuflqzcqqLbj2k65OLw++G0uY4KgPmfNpwSqm2YGhlXnMlxNzqhW78plZgytqprzGsseypTIhOvVjdS/wTdPE61DdumzxffCdF75jrEVZx1N6rOrr1NL8KBe3VWs6ig6PUq2qCGVsJLvvZwqlr82oJxipezZfneELb/EbTDMpYxcDtXdG0qdXFWIfXXGNoaDDE2ataSlkubxqCd3r24tmZM02x17IzYNmA1Jz5lqEGwhTMuT+sOr+yY6xTYY7SeIo3NglhDseDF5E+PkavE2iuU62LwUmOM8blsw3BXPvHqvNNoTk5Ys5kz5oOsEOu6SV/S8qPtc9WE2vND8sTXVM4Afti7V4XS+she5iVVWbEJ0o3iNA1lbV2cCA+caVC9+dWBBVpPmwLagljc7ttCN16mh+YQbsfreluwpL9vWbhVnas/VQBBDM2AQEBAQEBAQEBgX8zBBvM2MokJXbHJjU2QHuDny665ieG0By5m1pq15w1yn7LsKkNt1G/tMv/hjA0W665Oc8S7DniN4bmpmsO7tmVhcmVsVU0zdU3XfMyQzOLpVGseZkpS9NCe8G9T10Hg4D1Kwi6K7oVja2bw0sbriVmLZV5dcbU6ro5dE3hygpO/EATawVHqiL2XoEpb4uFssCeAg7GTOXNmcpagi1+BMuSoo62K6HZokxYnlBsM6uvMVcnG6tfrClD5voE1lrEGOQlXtmxebBjCkvMT4xlZlmXJkav8fo1ARnjWPlbU0o+mhjqYGs2yMW92phdMrWHzJ+hTr215nCa6CqveN0ttjkswDITB03zGUsGlrrmZYYaW0s6d/9G7GlaWFZovs/8QdFQRjUo1/i5civITlceymLCicNeEyO6Cp6AdRNCpdnDAWjfh7WSv5WJ8pjEK2sMTbRa0t4rurbWO09zIsPek3imZM2NYc+BnC5OJ7T3T1qqBKfq2NLkhA/33OTdWpvsk9hroC1uUEfvGBN/zS5ha2KsfrGmDBnrE9i1DlGrbftUAQQzNgEBAQEBAQEBAYF/M4IaW/nh/H/XTf7u+z/W14cpJR9zaM4+Oh68aHbJ1B4mLYZWMKw1h9PE3sorlpg4VGbzGYHyR3PmzW17op7T3Yzh5s0B7OEgsDTCDOVNmTmDKyds9eVhDyrLKnBpN6xrOVzMVfHf/w2mdLpUZH4yhiXtvfTYJZPn2Tuv6vpwsmQzuqntAfaodzWxtD9iruxwz83h6CWTfRJ7rSqqbt0xf9K/CcGMTZvKZDZiTqVEt8BU9c6GMYxVIpaa+wGs00ZNdJfOzTlgBOykCFIJUcQ0BADIOles12ZjSly6EpSlxZLG0NwA2XeTaXOAnOHRFg2yZTH6pgZA5fMgz0lQm3oXxjpI5aE+VBoVNw5rJ1lkfSLNSsO/bFgzaNHci6Fr6mKurbImz9ii5sU55S7LvFnaSTt7DRCNhVOWpmClobT7MzTr3Zdh75U5bMknira2bzMoT6x1CGuSl1h6WjBjExAQEBAQEBAQEPgXQ6QGkXV7cKw9v6KwaWWnMpmNWKtSUlYqS5UVa8z9dJ02uqQptMOyQFXGLooglRBpwl8AAInM/CwGtwpkK5ozbborZcZMCTm9fXvNdJZWuUnTCZoxzOWn4g7szJpzgmlTA2tWL8sSzt+Opu8DSymPVSpjeYdbkdJ0dmiMojciLXq3AJsXnfdc0BMqKewbZVARTfeYIRMnRdfWFsdvK5orKup2LazeAGwv9UtzbZU1ecaadpJbAeSccts7b1q7eV/TkkT33Rt61orXWlXYOzOUFkPkDovWUy7kyiH3fDTLo6GVOcVrrfgVeEOrgLauSummy5Qlj6FyrInu+zIk7mGp4Ef+IOvqeU0n07a8X4esIq3/VXVC+e8F7QxbG5gia7T1jrvLfdWNbFjVeZnN2MoL3UJmzlSHK6S6BTDjnZJMVp7OubiOp73NAJ6/Z3mhKehvfdyyLqypluT3y5B3a21TITVE0RuRNsk6mkPevY1Vz6Q0WLLPihsY2YqmPbK1g8eyarStRdMJmjVweQ8AHE8af9aaDTI3oNds3KoS1sg1l1blyZApGzdIM+XskKtTnfZfsPjdGsuLLrvPG1RE0z1myMRJeuySVvy2mOaZk57WHGSIzly1q5mIpe2PpZ11XdNjW8gdFo3Mt2P4zrHmoLi4Z4laaWk6XpptuSX7WTTfq8JVzH+3JO9Jj182+84svRdu34s1e4u45yjv1trovhnHLJWeciFXDrnn47L7PD+YMTRYlR6/zE9KGRoYm9qzo5UWnf0vmulSdG1tcnLb8fBFrXerO2Gi+74MmdtbugfOnDNyXUrrZJr+uqf1v/hOCv/d9Yz1e3281xl23G1KUlrlUM5d9Jd4z45gxiYgICAgICAgICDwb0atBhgrzdKqiBmb1YOdvIFtkNfYBdXnxLOzPsESiOWA14YEpE+IAYkYPPN9AHwVh7zXm0JZLRTZ9QDvW0B2fcDrFuCSrkR6MykcswjSAsAxVwXnvRfw/L0Y5Gc/BrbGAWBn8eTdWsPh6CUoO7VCbg0R5ONioHBj4J6kQn6IGG5PVCj2EMFnbQI/I6F0FaF4aDQ8tiTi6UexYIhd3fH9OUFrhiRjXAyKPRkEL4pH8pex8L2pQkGACP4rE5AyPRY+f6uQWU8MzwdquG9NRObQZsAWNm1PP4qFyhEIXRjPbmQ7xx4veiMSxR4iZDVkED4jAU8/ikXQ4niDzzKnX1NkNwuD2yOCa6oSRb5iEMNAUkxQuDBQOQJ+q9jZgIfzYhD+JfvdIY+QMyIanhsT8WRaLLz/USInXILApew7yWwghXM6QaQkFHmJkDEnFq6PCTI/Bu7JahQEi+D6RI1iLxGULgAxgKQQcP7vQb00Ohy9BAfN9z8kGu5bE3H/uxh4/gPkFjwGNsdZlHesNY2Sd2+jNztc3KsNcOAYgBd+ihKeoNhLDL9VCSju0QaK7MdAvOH0FL0RidwaEgQsZ9+HqVkrQ3FbypP3m8LpQSAcjlxExrgYOGar4baDnaVz2n8BTz+KhWM28WYiBQOi4JxajMftXRD2dTxSpscidGE8il6PhMxXDPdkOfJDHOCcqYTCVYzccBEkBQAYQCwjeCQrtO4jZ0Q0mF8PAwAyBzeDx/YkpE+IAQgoCAUcMxm4PlXDY0siCvtG4VkrEcJnJuDpx7EI+k9JXs19UYa4dAPsjDM3a5oyPRb+fyrgePAiOwO576jB55HTtyk89iQjfUIM/H/Sn916/Hks3Beyec/5/24AjLfW77KYOkDCRWT3bwqPXcl4/m4M/FaXhMOVBVtn8mS9Iw2aeMm7tYbcQ1zmJmamfNM8+TQWwd+VvBOHo5f4+9UlfXyMQQevHNx9at7vw/kxCDteDJWjCA5HL0HWJxKMChAXq6GWMHA8dJFPA5cfskbFwDmTVRHLrimBWE5wTVXDMUuB3HBHeK9L0Co/uUOjoXRiwKgBt8dyKNwlcMhR8nVx6pRYeP+tgOPhi8gcEwOfXxJQ9Hok5B4iqMUMnDOUyKorhecDJbLqSKB0BUQKwPsfFVx3nkfGOzFwe6pEXqiEzxfKTq2QGu0I9yQ1GDWgcGEAAuReDLz/UULerTWetXKA62OCwpVBwI/xKO7Vhp/lLu7RBionEWQ+Ivj+zPp38/1fAv9OmGtJwJGSeqawbxSKvNl2KHtkDPJDGYQuiEfWqBh4ry95J5rtD1eXcsi7t0FeiASyauy1qg4tkdbGCQFX2PfjeOgif01hvyhICtWQuacBADKHNINTTjXkVpcgPwwI/zIBqZNjIVICng8UUDmK+JW7h1/HIHxGAv/sA39g772wmhSeGunKfDuGbVdfpC+3ugSid2IgC2DgmEXwSFbiabQEkkIGoQvj8fy9GEhkgEOeGhKZGnIPMfJDRBDJAddUFfLejkFBMAPfv1Qo9BNBWkBQOjNQOTBwWsGWf3m7RpD5hfJ1zLMPYhGwPB5PpsUi+Pt4yLu3gcJNBMcsJQoCpSisJoLzc4LXBjbPOB24gJwR0XDIV8N5zwVkj4yBWE5weq6ALEAKtZhBkR8DqIFAsCIpainDz7oX9I+CzFcEv9XsO3fKUvOr6/mDoiEuVkPlKILChb1G2bkVCgOkcEsuQkGoE3LDRQi4VAx1uxbIruUA1wFRcN15HpljYkBiwOW5CsUeYnhtSEDq1Fi4J6sgzVcjL0QC358TUNA/Cq6/nUfekGiIiwkuu88j+60YeP2agGcfxMIhh+D1awKfHrfticgZEY2CYBEcMwiOeQS37YkoGBAFcTHBaf8FZI2Ogfe6BGSNioHSmXUCrerQEuKTV5AxNgbOmWq47DoPVceWEJ+4opWXpccu4enHsZAUELzuypERkA5sKsn32W/FQFJMoG6twRBQGCCCclg0iAEcCtTIrC+BexJbl4AA50wlX8byhkQjP1gEl2dqKFwZkAgo8mXgd0PJv3+u/DybGIuAFfFQt2+B9KbOcH6uhvLeQ+B8HOSvNgLOPNGr76hZXeDPdK1j4gZ1eAU2pkUjiORKkJiB+s/betdbQsawZvDYkgQASJ8QA5UTg8Al8XjwTQwiPmffE1cvZ42OAYkApyw15G4iOGcqUeQt5utyrl5//m4MRArA55cEvsxmjolBfnUGgYlyZNdxQMDyeKRNikW1ZfF8m/zkk1i4PVFD/LwAOLrXpvthV2leTulphsiylObm5sLT0xMd0BsSRmr6XMrCBcQhEp3hodNxMRtPKa4ta4ylzdo0V9Z75NLVpMtkVDv+mD9e3KONQbMTzWvK815MxVlW6TEXLvc7gErxXivDe7EmDbrnFgyIgmrHEVxAHGrGDMP9hM1mw6ms5aoi0MyPQOXIky8TlSWvVZZ0lBZj96Hs1Mrqfbn/drhBizVoTmIZgpu8qEz5zV79MVHT+gYHO1w4jdAGN3ERNdEQ98GaqHPHyuI5mOpvWYKSFDiJvcjJyYGHh4dF13D9+04uQyBhHMxfoBWfHL8XbrUqvopAMGMTEBAQEBAQEBAQ+DfzEq/s2G33U96QaIOb/nKGR5v0F2BOMcRW51e5Q6N5PwGpU2P549yGfV2xA1NptHaTv64/GmObITm1KYA1qcofGIWi1yORPt7wZvus0TH889DcMKn5DLkNgtz9FfSPMqhiorlRVndTofP/aauylWaWAShbPw26voAqG3mDS9JnaGN01ugYyLu34fOY5rvS/J79FpsnuI273IZqdfsWyHgnRi8/y1+13UeApb6oskeyacodpv8OrNl0rwknUKBwLqmazKmxlTfFPdvg2cRYk+dw70nz/RtD8xzumZYlOSOijW64Nqfmx6XPlAqTOT9sucOi+es5wQWuPtJ8FqoOLfnNu8U925jc3G9M5Un3PrnwNPO4oXB160zN56Ibl2b9aao+0nwuWuFp1uU6z0538zL3vMwpWHHp59oGatvcYFsq6xPJquP1asOrgcl6RyJrlPF8yD27vCHRBsPk7kGz7de69xf3IO/exmg+5MqP7qqOun0LFAyIMingwN0HoF2e5N3b8HVV/sCSdtFQfi3uUfI8uGdtrq+iWwdzdbZuujTVCDm1TXNKiMpOraB4rZVF9Sq3qlP0RiT/nMyVa0OrOlweUHRtzZuk6vqe4Z6Jbj2n2+eRd2ttMK/oqh3qCrAoXmul1T4aC780qP+8DaaV9n2JG9YF07AWAEAWyyqvyRuElcQf9eJYO9PtrOZzzxodo9U31MwfXDkp6B+l1d/SbFst9aWX37cUIjYvsZ8duw123LcmGvRq65KmgNOBC0YbKmOKIVwmMrXPw1QF4bElkd8TEbikxObd9Td9eVhzFQh3DYci1nQGt0SiGWDVprh7kB67BLcd5+F04AJv38nBVQbe6xL456GpVCQ9fpkvCC67zyNnBGvvy6VdU8UkYxwbrmYjYkqFyR6U5Z4Hbt9JZUPWm21o3LeVPHtDg0bvdQlwOHKRz2Nu2xP5waHme+PstLm9Fpr7iXx/ToD71kStxsThtL6Sme6g01iDYak8u9eGBOQPjILH5hey1xoDLGmB0qIwdOEG2tz9VkYcD11EwArD+/A4uPek+f6NYck59sRzYyK4+kNXzUwtYQBod8A1z/HawL4XToXJUAPM7R/T7fhnjYpB/qBouKQp+LLgcPQSnn0Qy9dH7tsS+XwpPnkFkjj2uOOhi1p1liWqdOITVyA+eQXybq316njNPG7ITIore1ynVFysKvmuYyKkWX/qerrXRHNfnWb51arLdfYQcvfPpZ9T6jJnpsSln2tfmXN/8G0H17Zkj4zhO7mOBy/yamDOey9o7TPShXt27lsTtZ1Tvng+3D14bkqE04ELyBgXo33vR1/sxT1yEYXVWJMZzU6jrE8k5O4iFL0RyXcWC/pHIWdENDLrObFp1OmcZ46J4fsYLrvO851vpyxVSbxHLvJ1lduO85DI1MgfFK33zHOHRsPxcMnzEJ+4YnCwoNsB15Wc163DxDJ2I7emGiG3H8hQG1zYN4of7Ep+vwzp8ctwPHRRa9CVPTJGKx1cWc0dFo1iDxEcspX8vRe9EYnCflHIfiuG3V/yooxzfQLNQSIAg3lA6czWD5mDmyFvcDSfvzTrsOfvxfB9QW6wKS5WIy9ErBcHp3ZY3KsN8gZHs3lD41lLj1/Wah9lfSyXvrcGuqzdXqr++odXY3OOZyfbHG4l8787nn9x7IwJxdAebVDsJebrSO91CVp9Q838wZUp19/Oa020cPkVYPOXpisKLo8/f1d7UO22uxSuYYhYwQGrPv+ywY6AgICAgICAgICAQNWD1GTTx1pWrFiB8PBwODk5ISoqChcumJ5g3bFjB+rXrw8nJyc0adIEhw4dsjrOMh/scCN/azcZmhoxc0gKVWbPsRRrnI1a4mtFE0MrXhzGVlU0Ndkt8fOgOavkuTHRaLicopAhjPlssJefnbLC2L1yKz66JjfWOiczhiHzLQ7nvRf03pspMwj1K83577orYabMdzT9GJhTu3PbcV7LPMVUvjSG7oy6Zlo1V5M002WNk9Xc3k0B6JuAvMxorjpwKyfmsNW8VxdjjkY1VxuMnSM9dsmkA1WPLYla+cV7fQLctifyqxUAQLHNeHVE7p5M5UtuNlrXV4uplQ6Ho5dKlDqdxUbPMwQ3Ay8+caXU5rymMGX+JusTaVKxz1q4toXLa4bqT3POIg1h7PkYanO498etCGi29857LsBzI7tq5HCEXUF0/e08PDcmwm91gkHfY153i7T6GO7bEiHrE6lXJ2quWErzlAZ9txhanRMXsX0NzqStoH8Ubz1hCEMrj7rPx5wposvu81plhU+3hjWM14YEOOSV9IMkL1aPxHKC56aSFVyAbR9cdp2H168J8P8pgf+Nez/cSpZefBorX5zjcZ9t14yuSHMKslz6ALY+8V+ZoBWHZh3mePBiSV7QWPXUbDPzB0XDeQ/r58uWtstWFC1q2XSd4+GLcN+aaLWTaUv9CXHPS1OZtNRYvaqjtlp6etu2bfjoo48we/ZsXLlyBc2aNUO3bt3w7Nkzg+fHx8dj6NCheOedd3D16lX06dMHffr0wY0bNwyeb4xKs7Kj6yneEixxTmYJ9mxIqjJcRaaLMWdYuhhy8Ff0RqTBPTvmnOuZ6szp2g0DhgceXCOu28hY65zMGJpLzJZgysmb6OwfRn/TbMTN7Ycwh65pgu7+MkNY6xBQF00nqwUDokyaIHns/ROAYTM2ZVQDq+M2Rll7prbG2aXcne2AG8vznJmKLR1Qa7Fm0kdzgG4Mc/mFib9WErcF0vSGHI1ag6X3Z48JEVOTIbqYMn+z1alpaQbEZTmwsxbpsUtmTc1FZ7SdVyq6tjb43DTzjzV5SXzyCqTHL/ODatffzpvMS5bUk6YG6NbU85qDEe67tc6ozaFrxlfUsfTObE0NRDk020xz7bbuhIE1TqZFTetDXK82xLUj9H5TOpvvJpd1e8Jh7/eqS3ms7CxevBjjxo3DmDFj0LBhQ6xcuRIuLi5Yu3atwfOXLl2K7t27Y9q0aWjQoAHmzZuHli1bYvny5VbFa7EaG6dQrYTCrFiDCkr+r5IUFoWvVBRBSQqbri0vjKXN2jRX1nu0JV2a1zAv3qEmSkURlGJG/7iyCDARh9JAWCXXFuulU1XG+cdcuNzvZRG3JkplERg75jGV3PhzLm2chtKgVBSBUaog0gnP0LncMTVezKqq5KbvxYp3r1QUQVyGZc9U/jV2rrFrNH8XazxHS56F5v/2zpNqZZHee3xZsPT5mnquKivygK2YSoc1ebCiMfc8rS2vltZZlZXKln6lgi3r/HtSmq6LbUGlLAJZEaZee6PbB1AVW5xGkaoYjEoJqFRQ6bY/KvZ/NUpWMPg26UXcZd2eWIMSbDos9CqjfS0VW71Sw8WXm5urddzR0RGOjo5ax+RyOS5fvozp06fzx0QiEV577TUkJBieVE9ISMBHH32kdaxbt27Ys2ePVekEWUhycjKnSSd8hI/wET7CR/gIH+EjfISP8KmEn+TkZEu79ySTySgwMNDmuNzc3PSOzZ49Wy+ex48fEwCKj4/XOj5t2jSKjIw0mDapVEqbN2/WOrZixQoKCAiw+P6IiCxe2QkODkZycjLc3d3BMIyllwkICAgICAgICAgIlDFEhLy8PAQHB1t8jZOTEx48eAC5XG5znLrjAt1VnYrG4sGOSCRCaGhoWaZFQEBAQEBAQEBAQMBGPD09rb7GyckJTk5OZZCaEvz8/CAWi5GWlqZ1PC0tDYGBgQavCQwMtOp8Y1QagQIBAQEBAQEBAQEBgZcPBwcHtGrVCnFxcfwxtVqNuLg4xMQYVmCNiYnROh8A/u///s/o+caweGVHQEBAQEBAQEBAQEDAFj766COMGjUKrVu3RmRkJH744QcUFBRgzJgxAICRI0ciJCQECxcuBABMnjwZ7du3x3/+8x/06tULW7duxaVLl7B69Wqr4hUGOwICAgICAgICAgICZcrgwYORnp6OWbNmITU1Fc2bN8eRI0dQrVo1AEBSUhJEohKjs9jYWGzevBkzZ87EF198gTp16mDPnj1o3Ng6+XOGyAZ9OgEBAQEBAQEBAQEBgUqOlSs7lquwhT21fQyV/KbNl5Y9Ad0MHmba26Cx/mRcKRNTNvy6dL9V54+4s6iMUmKaGR+GGDy+4PDmMovzHXIw+fvPb/5UZnHbwpJ3jpd7nC6Xv9H6/9S8ORZfW/dH7bz0bONRAMBelwMWXd96rqAUyfH8J9Zfguf9ATiY36SCU/Ny8nbLfyo6CQCAoVvLrs4rT/ZOqegUCJhjRY91FZ0ELSg11/APT6x3VG+IYx8/AgAEjhwEAGj2SxvM6B0AAKj7ceXtrI5s925FJ6FSIQgUCAgICAgICAgICAi8lAiDHQEBAQEBAQEBAQGBlxJhsCMgICAgICAgICAg8FIiDHYEBAQEBAQEBAQEBF5KhMGOgICAgICAgICAgMBLiTDYERAQEBAQEBAQEBB4KREGOwICAgICAgICAgICLyXCYEdAQEBAQEBAQEBA4KVEGOwICAgICAgICAgICLyUMEREFZ0IAQEBAQEBAQEBAQEBeyOs7AgICAgICAgICAgIvJQIgx0BAQEBAQEBAQEBgZcSYbAjICAgICAgICAgIPBSIgx2BAQEBAQEBAQEBAReSoTBjoCAgICAgICAgIDAS4kw2BEQEBAQEBAQEBAQeCkRBjsCAgICAgICAgICAi8lwmBHQEBAQEBAQEBAQOClRBjsCAgICAgICAgICAi8lAiDHQEBAQEBAQEBAQGBl5KXcrAjl8tx+vRpbN26FQCQl5eHvLy8Ck6VQGUiKSkJCQkJFZ0MAQEBAQEBARsQ+noClsIQEZk76cmTJxYFFhwczH+vU6cOGIYxe80///xjUdiWcvnyZfTr1w8BAQG4ffs28vLycPToUfzvf//Dzp07bQ5XoVBg8+bNuHbtGvLz87V+W716Nf89OzsbS5cuNXjesWPHbI6/PHj33XctOk/zfq1BrVZj5cqV2LFjB54/f47r16/j9OnTSElJwbBhw8olbffv38eQIUPw8OFDyGQy5OXl4bfffsO+ffuwfv16q+LNy8vDlStXkJGRAR8fH63fzOVrW8qUPbFH+SzNO9m8eTP/fe/evUavbdasGf/9iy++sCi+iiQpKQmPHz9GTExMRSel0hIfH2/RebGxsWWckvKhKtzvggULLDqvKpTB8qSi+jlVgS5dulj0bGztF1nS17O27HHlYO/evVCr1XrnPXr0CDVq1ECLFi34Y7b2hwTKF4klJ4WGhoJhGJgaFzEMA5VKxf+/Zs2a0qfOBsaPH49ly5bhzTffhLe3NwDg1VdfxejRo0sV7siRI3H9+nX06tULISEhRs8bMmQIlEol+vfvDxcXl1LFqYlUKjVZcRARGIaBXC63OQ5T92UPPvvsM1y5cgWffPIJRowYAQCoUaMGJk2aZHawY6+0jR07FqNGjcLEiRP5/NG1a1dMmTLF6njXrFkDX19fdO/eHePGjbMqHbaUKXuiWT4TExOxZcsWTJo0CWFhYUhKSsKKFSswdOhQk2GYejZz587lv69bt07vd6VSCQBo3749bt++bTQcrgxZ0mhWJNYOou2FsXpBrVbzjbVEIsG5c+eQnZ2NLl26lFlaLGX48OFmz2EYBvfv3y+H1JQ9VeF+79y5Y/acyl4GK4KK6udUBbg2vqywpK9nbdm7c+eOwfZKk/T0dFy6dAlz5syxKr3l0YcTMI5FKztVCR8fH2RkZIBhGPj4+CAzMxMqlQoBAQHIyMiwOVxPT08kJyfDw8PD5HkeHh54/vw5HBwcbI7LEI8ePbLovBo1atg1XnsSFBSEv//+Gx4eHvD29kZWVhYAwMvLC9nZ2eWSBm9vb2RmZmrlDyKCr68vMjMzrQrLw8MD2dnZEImqtjVogwYNcOLECQQGBvLHnj59ik6dOuHWrVs2hVkW+bU0K4NlTadOndC/f39+EJ2VlYW8vDw0bNgQycnJZRavoef8008/Yc+ePRg+fDi+//57XL9+HTKZDKNGjcL58+fLLC0CAgIC5UVZ9PUWLFiAhw8fYv369Rg1apTWb6mpqbh58yY2bNgAAGjbtq1VYb8MfbiqjEUrO7ZQUcviTZo0wd69e9GnTx/+2IEDB7SWHW2hbt26yM3NNTvYiYyMxJ07d9CoUaNSxadLeRSAsja3cHR05Gf0uRmO1NRU+Pr6llvaatWqhYSEBK3zzp07h3r16lkdb5s2bbBy5Uo0b968SpvcpKenQywWax0Ti8V49uyZyevs9U4sNelbsmSJzSuDZc3Vq1cRFxcHoCRvu7m5oaCgoEzjNVQvbN68GRcuXEBgYCAWL16MGjVqgIgsmr0X+HdS0Wa1VRXB/M84mqbKprC17i6Lvt61a9cAsBNr9+7d448zDAMPDw98/PHHeP78Ofz9/fn2z9K2XxjEVCwWDXZssb2sqIZ1+fLl6NGjB1auXInCwkL06dMHV69excGDB0sVbq9evdCtWzeMHTsW1apV0/pNs7A2atQIXbp0wcCBA/XOK02FV9b7aYCyN7cYNWoUBg0ahPnz54OI8Mcff2DGjBl4++23yy1t//nPf9CnTx/069cPRUVFmDJlCnbs2MFvcLQm3vT0dJw4cQLOzs5655l7D2Vtz2wNw4cPR5cuXfDRRx8hLCwMycnJWLJkiVkzBFPP5vnz5wDYdzJkyBC939esWQOGYSAWi6FQKIyGwz0jhmEQEBDArwxy1KhRw+IZs7LE2kG0vTBUL2RkZOCLL76ARCKBTCbDu+++i++//x5ubm5lmhZL+bftc6gK91vRZrVVFWECwTj/+9//zJ7DMIzNgx1L+nrWlr0dO3bwZeD333/XO2/37t0AWJO0kJAQq/pD5dGHEzCORYMdW2wvf/nlF6uvsQdNmjTB33//jQMHDqBz584ICQnBhg0bzK7ImOPUqVMICAjAvn37tI7rFtbc3Fx069YNubm5yM3NLVWcmpT1fhoAePDgQZmGP3v2bPznP//BmDFjIJfLMXjwYIwZMwbTpk0rt7S1b98eV65cwaZNmzBmzBgEBATg3LlzCA8Ptzrer776yuZ0lLU9szUsWbIEK1euxLp16/D06VMEBQVh3LhxeO+990xeV5pnM3nyZAAwuleKQ3M2LDw83OaVwbLG2kG0vTBULzRq1AiXLl1C165dwTAMfH19MXXqVPTv379M02Ip/7Z9DlXhfg1txhYwT0X1c6oCJ06cKNPwLenrWVv21Go1OnbsiOzsbDg5OcHJyQlyuRz3798HwzCIiIjgtyhYe3/l0YcTME657dm5ceMGdu3ahbS0NKxYsQK3b9+GTCYrtXmZLps3b0afPn3sKg7wb0UulyMxMRFPnjzBkCFDeElHd3f3Ck6Z7Wn75ptv8Pnnn+sd/+677/Dpp5+WWbz/Bkr7bNRqNVJTUxEcHGxQ1Wz27Nk4d+4c5s+fjx49euDEiROYMWMGYmJiMHPmzDK5J2tITk7G5s2bkZSUhJCQEAwbNszoILosKSoqwscff4x169ZBJpPByckJo0aNwuLFi+Hs7Fzu6RGomgjKgtZTXv2cqkh6ejoOHz6M1NRUfPrpp0hJSYFarUb16tVtCu/999/Hjz/+qHf8gw8+wPLly0uV1gYNGuDYsWMICwvD66+/DqVSidDQUPz111/48MMPhba/KkJWolKpaMWKFdShQwdq3LgxERGdOnWKNm3aZPSa9evXU0hICH3yySfk4eFBRERXrlyh9u3bWxu9WTp27Ehubm7Uv39/2r59OxUWFtotbLlcTjdv3qTTp0/TqVOn+I8uaWlpdPDgQdqwYQOtX7+e/9iTgwcP0pgxY6hXr15ERHThwgU6duyY3cK/dOkSVa9enVq3bk1ubm5ERHTkyBHq37+/zWFu2rTJ4Gfnzp2UkJBACoWizNPm7u5u8Li3t7dN8f7444/UvHlzmjt3Ln311Vf8xxpsKVP2hIu/Y8eONsdv7p2Yyq/p6ek0YMAAkkql5OzsTG3atCFPT09ycHAgIqKdO3fSyJEjSaVS0XfffUf169cnFxcXqlu3Li1cuJCUSqXdnkVVR/c5Hz16lI4ePVrBqTJOYWEhTZs2jcLDw/myeeTIEVqyZEnFJqyMqAr3e+/ePWrTpg35+/vzZZkrgwLGKc9+TlXjyJEj5O/vTwMGDODz/ZkzZ6hHjx42h2ltW25N2XN3d6d79+5R69atCQABIJFIxH8WLlxY6v5QWffhBLSxerDz8ccfU6dOnejAgQPk5eVFREQPHjygpk2bGr2mVq1a9PfffxMR8dcoFAry9fW1Jc1mSU1NpeXLl1O7du3Iw8ODhgwZQrt37y5VmCdPnqTAwEAKCgoiiURCQUFBJJVKqUGDBlrn7dixg9zc3CgmJoYcHBz4v127di1V/Jp888031LhxY1q+fDl5enoSEdGtW7coMjLSbnG0bt2a9u7dS0Ql76ywsJACAwNtDrN9+/bk4OBA1atXp5iYGKpevTo5ODhQ27ZtKSQkhMLCwujSpUtlkjZuYOXs7EybN2/WGmx9/fXXVLt2bavjXbZsGXl6epKTkxM5OTnR0KFDycPDg9566y1LHgePLWXKnnzyySeljt/UOzGXX3v37k2fffYZ5ebmkkQioeXLl1NGRgaJRCIiIsrNzaXQ0FBKTk42GLex4+XJa6+9Rl26dNH7vP766/Tee+/R4cOHyzwN3HN2cnIy+JwtGdCXN6NHj6bhw4fT9evX+Xzz5MkTqlevXgWnrGyoCvfbsWNHWr58ORGVlGWuDAoYp7z7OVWJhg0bUmJiIhGVPJvi4mLy9/e3Oqyvv/6avv76a3JycuK/c59x48ZRkyZNDF5nTdmrUaMGRUdHU2hoKDEMQwzDEADy8PAghmHI1dW1VP2h8ujDCWhj9WAnMDCQcnJyiKgk0xIR/8IMERAQwM/acw1uaTvOlnL//n3q3Lkz33GylWbNmtGaNWuIqOS+f/jhB5o9e7bWeXXr1uU7Ntx5O3fupPfee69U8WsSFhZGT58+1YpDrVbbtTPj7e1NarWa/05EpFQqycfHx+Ywx48fTz/++KPWsZ9++okmTJhAREQLFy6kqKioMklbhw4dqEOHDiQWi/nvHTp0oI4dO9LgwYPp7NmzVscbHh5OFy5cIB8fHz7/nz59mgYMGGA2LE1sKVP2xB7xm3on5vKrr68vvzrDMAwfDsMwWueWZlWurJk5cyZVr16dvvzyS1q1ahV9+eWXFB4eTp9//jlNnz6dAgIC6Ntvvy3TNHDP2c3NTe85FxQUlKrslhX+/v5UVFRERNrvsbzyfnlTFe7Xy8tLryzbu315GanIfk5lx9fXVy9PyeVymwY7o0ePptGjR5NUKuW/jx49msaMGUOfffYZP+DUxZqy9/PPP/MrOitWrOAHO+3ateMHP6XpD5VHH05AG6sHOzVq1KCMjAwiKskwT58+pZo1axq9ZtiwYfTpp5+SUqnkr5kxYwaNGjXKhiSbR6lU0qFDh2jUqFHk7e1NMTEx9MMPP5QqTHd3d73CqlKpKCAgQO88Dh8fH74TZ89MHBwczJvnceFmZ2dTWFiY3eJ49dVX+dUwLo49e/ZQ586dbQ7T09NTz+RIqVTylU1xcTG//F9WaZs3b551iTYRr4eHBx+vv78/FRcXExFZdA+a2FKm7Ik94jf1Tszl10aNGtHNmzeJiEgsFtO5c+fo2rVrJBaLiYg1d4iOjuZNajRJSUkhPz8/a2/Z7rRq1Yr++ecfrWP//PMPtWrViohYM7/w8PAyTYNYLKbatWuTWCwmkUhEderUoVq1apFEIiEvL68yq29LQ506dfiVOS5v3Lt3j+rXr1+RySozqsL9tmrVis6dO0dEJWnkyqCAccq7n1OV6NWrF79ayD2bn376ifr06WNzmNZuDbC27LVo0YIYhqGMjAySSCQEgPbs2UNisZjEYnGp+kPl0YcT0Mbqwc6sWbOoc+fOlJCQQF5eXnT16lXq2bMnzZ8/3+g1mZmZ1KtXL3J1dSWxWExeXl7Uo0cPyszMLFXiDTFmzBjy9fWlVq1a0XfffUcPHz60S7h169alx48fExFRy5Yt6ejRo3TlyhW9jlaTJk34Tk/btm1pzZo1tGvXLgoJCbFLOoiIJk6cSMOHD6enT5+St7c3ZWdn05gxY2jKlCl2i+PPP/+kkJAQ6tatGzk6OlLv3r2pevXqdP36dZvDbNKkCf3yyy9ax9atW8fvE3n+/Lne4NHeaXv33Xfp9OnTNqVfN14vLy8KDAyk69evU5cuXWj27Nm0ZMkSqlWrllXh2lKm7Imx+K0ZGJp6J+by644dOygsLIwWLlxIzs7O5ObmRh4eHuTg4ECTJ08mACSRSEgkEpFUKtX6iMVimjFjRlk9Govx8vKigoICrWN5eXn8QF6tVpOrq2uZpqFPnz702muvkZOTE7m5udGBAweoR48eNGDAALp161aZxm0ry5cvp6ZNm9KWLVvIw8ODdu/eTa1bt6aVK1dWdNLKhKpwvydPniR/f3967733yNnZmSZPnkzBwcE215v/Fsqzn1PVSEpKombNmlG9evVIKpVSs2bNqEmTJpSUlGRzmF27dqUNGzZQXl6eRedbW/aOHz9OIpGInJ2d+cEO99fT07NU/aHy6MMJaGOTQIGtm4RTU1PpwoUL/KChLJg/fz7duXPH7uGuXbuWN0/bvXs3XwB0N7cdOHCAbxTOnDlDERER5O/vT1u3brVbWmQyGb3//vvk4uJCDMOQs7MzjR8/3q5iDERE+fn5tHXrVvruu+9o06ZNvKmTrSQmJlJISAjVrl2b2rdvT7Vr16aQkBDelvfkyZO0bNmyMk3b7NmzqW7duhQWFkbTpk2jP/74w6p70Ix37ty5dObMGSIiunnzjUzmHAABAABJREFUJnXs2JFat25NcXFxVoVZ0Rvv7RW/sXdiSX49f/48jR8/nnr27ElDhw6lCRMm0Pvvv09ff/01nTlzhh48eEB169alhw8f8p9Hjx7pDTAqisGDB1OPHj3o7Nmz9ODBAzp79iz16tWLBg8eTETs5lPd/X32hnvOTk5OZVov2Jvt27dT9+7dqWHDhtS1a1fasmVLRSepTKkK95ucnEzffPMNXwYfPHhQ0UmqMpRHP6cqolarKTExkbZv307nzp0rdfv2yy+/UNeuXcnd3Z0GDhxIe/bsIblcbvIaS8set0fbz8+PN2fjPgEBAbRq1apS9YfKqw8nUEK5SE+fO3cOQUFBqFmzJn/swYMHePr0aZX1PC+Xy1FcXFzhsoPp6enw8/OzyHGWNWRlZcHBwQGurq78sYKCAigUCnh5edkcrlwuR3x8PNLS0hAYGIiYmBhet74803b58mVs3boV27Ztg7u7O4YPH46hQ4ciIiKiTOOtjKSkpCA0NNTi44aw9NmUJr8mJiYiOjra6uvKg4KCAsyaNQu7du1CamoqAgMD0a9fP3z11Vdwc3NDSkoKiouLUatWrTJPi4eHB5o1a4aRI0di4MCBVTpvCghUFV7Gfo69uHPnDjw8PLQcraelpSE3Nxd16tQpVdhpaWnYuXMntmzZgtu3b6Nfv34YOnQoOnbsaHOYzZs3x6RJk/DOO+/A29sb9+/fx9dffw0XFxfMnTsXgP3a/rLqwwnoYO3oaNmyZXTlyhWtY5cvX6YVK1YYvaZu3bp6iknJycl2U6Bp3rw5/7127dpUp04dgx97kJOTQ48fP9b66FJQUEDXrl2jc+fOaX3sxc6dO/k9Dhw3btygXbt22S2OqKgounr1qtaxK1euUExMjN3isBV7pU2tVtOxY8eocePGJJVKydfXlzp27EiXL1+2ON4DBw5QvXr19OS0rcGWMmVP7LHx39Q7MZdfR44cyZePjh070pkzZ+jcuXM0evRoImJFHzp37kwRERFUs2ZNmjFjhl54AiX1QkFBAW3evJneeOMNcnFxocjISNq+fTu/ObcyMX36dH5llyMxMbFSmCaWBVXhfrkyqAlXBgWMU9b9nKpM06ZN9YQD/v77b2rWrJldws/OzqY1a9ZQo0aNyM/Pjxo3bky1atWiQ4cO8edYU/bc3d2pY8eONGTIEHJ1daWoqCi6fPkyeXl5UZMmTejTTz8tVX+oPPpwAtpYPdgJDg7Ws5HMzc2l4OBgo9d4eHjwm/s51Gq10U6WtWhWzCdPnjT6KQ2HDx+mGjVqkEgk4tU4GIbRU3n7+eefyc3NjapVq0bh4eH8JyIiolTxa1KjRg16/vy51rH09HS7boA2tsne2s33miQnJ1OfPn3I399fS7PeWqW80qYtMTGRPvzwQwoODqaoqCj673//S8+ePSOFQkH/+9//jG4S1A1/3rx55OzsbFDhzRpsKVP2xB4b/029E3P5VVPIg1OC0pRsValU/MDr3LlzNGnSJAoMDKTmzZvTd999Vymkp4nKx7+WKQw95zt37pCvry81btyYPDw8aOTIkQZ9g1UUmgpJHDKZzKK9e1WRqnC/mmpsHJplUMAwZd3PqcoYewaleTaFhYW0detWevPNN8nLy4sGDx5M+/bt4xXxjh07ptWGWVP26tatS56eniQWi6lhw4bk4uJCV65cIV9fX3J3dyeJREJEtveHyqMPJ6CN1YMdX19fXnWKo6ioyGRF2Lp1a60RNhE7eGjRooW10Ztl8+bNBo+X1i46NDSU1q1bRzKZzOR5AQEBdOLEiVLFZQ4vLy89e1eFQmFX+dI6derQX3/9pXXsr7/+KpVCWLdu3eidd96h27dvk6enJ/399980YsQIqzfnliZtERERVLt2bZo1a5aeehaHMdUh3Xh9fHzo4MGDpVZNs6VM2QOJREJSqdQuG/9NvRNz+TU4OJjfxFujRg1KSUmhjIwMXrI1OTlZbwCqUqno6NGj1LhxYxKLxfTqq6/S+vXrK8zBaHn41zKH7nNOT0+nZcuWkVgspsDAQPrwww9p0aJF1KBBAxo7dmy5pcsUAQEBevuu8vPzK4XCXllQFe6XK4OaGCqDAtqUZz+nqtG4cWNKSEjQOpaYmFiqfYweHh7UuXNnWrt2LeXm5ho8h9szSWRd2Vu7di0FBAQQANq2bRsxDENisZhmz55NISEhBKBU/aHy6MMJaGP1YKdXr140d+5crWPz5s2j7t27G70mLi6OPDw8aMSIEfTll1/SiBEjyMvLy+qN3JZQVr44goOD+RkDU9SsWdPsgKi0tG/fntauXat1bN26dfTKK6/YLY6lS5dS7dq1ac2aNRQXF0c///wz1a1bl5YuXWpzmN7e3vzMCleo8/LyrK4wSpO2+Ph4q9NtLN7g4GCqVatWqZ4JkW1lyh48fPjQbhv/Tb0Tc/l1woQJ9MYbb9C9e/do5syZ1Lx5c4qNjaVhw4ZRXFwcxcTE0MyZM/lrr169Sp9++ilVr16dWrZsSYsXL6adO3dS586deW/U5U15+NcyB/ec169fT926dSMvLy+KiYmhhg0bajWsubm5Za4MZynDhg2jcePG8XWmTCaj8ePHa3VSXiaqwv1++eWXFBUVRXFxcXTv3j2DZVBAn/Ls51Q1tm7dSn5+fjRz5kz6+eef6csvv6SAgIBSTULrDsjNYW3Z+/LLL0ksFlP37t3piy++oKCgIKpZsybVqlWLnJycStUfKo8+nIA2Vg92Hjx4QA0bNqTq1atTu3btqHr16tSoUSOzai3379+nr7/+miZMmEALFiywu7oLty/GxcWF4uPjtfbKbNq0qdTen1etWkUff/wxZWdnmzxvz549NGrUKPrjjz/M7u2xlatXr1JAQAC98sor9NZbb9Err7xC1apV09szUVo2btxIXbp0oQYNGlDXrl2NrppZiqa5Vu3atenu3buUmZlp01K2rWkrra2sZryRkZEUGRlJu3fvLtX+LFvLVGXD2Dsxl18LCgpo7NixvIqYRCIhT09PcnZ2pnr16tGCBQtIoVDQnDlzqF69ehQREUFffPGF3kpSUVFRhXXiy8O/ljm45+zl5UVt27almJgYo/XCvn37yi1dpkhPT6cuXbqQo6MjhYWFkZOTE3Xr1k3PxONloSrcr1KppPnz51OdOnX0yqCAacq6n1OVOXv2LI0bN4569OhB7777bqn3MVu719XasqdUKmnQoEG8CptYLOadizZt2rRU/aHy6sMJlGCTGptKpcL58+eRkpKCsLAwREZGQiwW21k6wTo4Fa2kpCRUr16dP84wDKpVq4ZPP/0Uffv2tTn8xMREDB48GCkpKfy9EhEYhoFcLufP27dvH8aNG4f09HSt6xmGgUqlsjl+XXJzc3HgwAH+HfTq1QseHh52C78s+PDDD/HKK69g0KBB+Prrr/HTTz/BwcEBsbGx2LhxY7mkITw8HJcvX4avry9/7Pnz52jTpg0ePHhgVVirV6/GlClT4OHhAWdnZ/44wzC4f/++VWFVZJlSKBT46aefcPbsWWRkZECzSvj999/tEocl+ZWIkJ6eDn9/f4PKNO+99x5GjBiBdu3aGY3n2rVraNasmV3SbA1NmzbFb7/9hjp16uCVV17BmDFj4OPjg0mTJiElJaXc0lEV6wUAePLkCZ/moKCgik5OmfNvu18BAXsTEhKCv//+G25ubvyxvLw81K9fH48fPzZ6nbGyJ5VKDbY7arUaarWa/z8pKclilVJTVNW6uqpSLtLT5cm4cePwv//9z+7h1qpVC6NGjcKgQYO0OrYAUKNGDf57cHAwFi5ciMGDB8PJycnu6XiZOHXqFPLz89G9e/dy69h7e3vj+fPnWvEplUr4+fkhOzvbqrB8fHywe/dutG/f3s6pLF/ee+89XL58Ge+++y4+/vhj/Oc//8GPP/6Ifv36YdasWRWdPJ7KLP198OBBeHh4oF27djh79ixGjhyJ/Px8LFu2DIMHDy7XtHTq1Alz587FK6+8wh87c+YMvvrqKxw/frxc0yIgICBQFvj5+eHJkydariuKi4sRFBSEzMxMq8N79OiRRedp9vcEqg4v3WCnrPD19UV6ejpEIpHJ84KCgpCcnAyJRFJOKROwhg4dOmDUqFEYM2YMf2z9+vVYs2YNzpw5Y1VYERERuHXrVpUf1FarVg1//vknqlWrBk9PT+Tk5ODRo0cYOHAgLly4UNHJ44mOjsbKlSvRvHlz/tjVq1cxceJExMfHV1zCKhleXl7IysrSmqVUq9Xw8/OzqRMgICAgUNl4/fXXERUVhS+//JI/Nn/+fJw7dw6HDx+2WzxZWVnw9va2W3gCFcNLMdhp0aIFrl69CgCoU6eOUedM//zzj81xfPXVV/D09MSUKVNMnrd69WrcvXsXM2bMgKenp83xvYw8evQIc+bMwbVr15Cfn6/1W2nejTX88ccf6NatG+rWrYuIiAg8ePAAd+7cwZEjR7Q60Zbw448/4uzZs/jss8/g7++v9VtwcLAdU122+Pv74+nTp5BIJAgLC8Off/4Jd3d3+Pj4IDc3t6KTx+Ph4WEwPdwAraIpKCjAvXv39PJ2eTsUDA8Px7lz5xASEsIfS0lJQWxsLJKSkso1LQICAgJlwcOHD9GrVy/k5+ejRo0aePjwITw8PHDgwAGEh4eXKuzs7Gx8+OGH2LFjB4qLi+Hk5ISBAwdiyZIl8PHxsc8NCJQrFg92zp07h7Zt21oVuLHOib05e/Ysb7Jx6tQpo+eVxtyoTp06ePjwIdzd3eHn56f1m2ZHXSqVQqVSgWEYk3t7bIWIcP/+fYSHh5eJ6VevXr1w8OBBu4cLADExMahbty6GDBkCFxcXrd/K0xTMXrayxlb5LN2fZUuZKgt69OiBDz74AL169cKoUaPw/PlzuLi44MmTJzh37pxVYanVaqSmpiI4OBgpKSl2sW3mqFu3Lvbu3YsGDRrwx27duoXXX38d9+7ds1s8trBhwwZMnDgRLi4uWnnblv1bpWXWrFk4duwYFixYgPDwcDx8+BAzZ85E586dMW/evHJNiwDLli1bMHTo0IpOhkAZUF79nKpIkyZNcP369TILv6z2uvbu3Rtubm6YO3cugoOD0b59e9SuXRv5+fnYt2+fzeHau00UsByLBzu2FGh3d3fk5eXZlDB7IZfLwTAMpFJpqcKxdBBlyu7TXraerq6uyMvLM2tSZwtlWXF7eHggOzvbpnS/++67Fp23evVqi85LS0vDkydPEBwcjGrVqll0jb33QlSWRjI7OxtqtRo+Pj7Iz8/H4sWLkZeXh8mTJ1tcMT9//hwTJkzA3r174eDggPz8fLi4uODDDz/EN998Y/S6jIwMjB07Fl5eXpBKpUhKSkJKSgq8vb1Rv359rVXaxo0bY9myZfj8888RERGBhw8f4ttvv8XEiRPx4Ycflvo5lIbg4GCsX78eXbp0qbA0cB0LlUqFb775BuvXr0dKSgrUajVmz56NadOmVTrzWk6QAmDFJeLi4tCwYUN07969glNmXypLWTfH9evXcfv2bbRs2RK1atXCihUrcPToUTRs2BCzZs3Sm6QSqBz9nMpKWT8btVqNixcv8m1569atTQ52nj17hkuXLukJ8YwcOVLrPE9PT7zxxht4//33ERsbi5o1a+L48eNo0KAB3njjDezcudOm9FaVeuClxFLZNkNe1s1REZ6DP/30U7p48SIREe3fv5+cnZ3J1dWV9u/fX+5pKSs6depUZhKFZfnOBg4caLP39jlz5lj0Mcfjx4+pY8eO5ODgQIGBgeTg4EAdOnSwSLPf3p7FbSlTlZXevXvTZ599Rrm5ubyfGVdXV4qIiDB6zY4dO8jV1ZWXme7WrRu5uLiQRCIhZ2dnioqKohEjRpCnpydNnDiRiOwvh24vgoKCKlya11B+UiqV5Sp/bSknTpwgPz8/EolEVKtWLdq+fTt5enpSmzZtyM3Njb7//vuKTqJdqQplffny5eTt7U2vvvoq+fv709SpU6lp06Y0bdo0atasWaVxRFvZqIh+TlWhLJ/NrVu3qE6dOhQaGkrR0dEUEhJCderU0XMtwWGN4+fmzZsTwzDk6OhIderUoQkTJvAS1ABo2rRpNrkUqQr1wMuKxSs7Li4uOHr0KEyd/uqrr2r9LxKJjO6foRemXfaUYwZYgYD79+/D2dkZrVq1wuzZs+Hp6YmJEyfixo0bNofbpUsXo/dy7Ngx/ntZ7RnSZNKkSdi2bRv69++P0NBQrfi++OKLUoUtkUj03qMu1sgRa67IFBYWYs+ePejcubPeaoqlKzKl5c0330RERAQWLFgAV1dXFBQUYObMmbhz5w4OHDhg8lrdvRCcVKVCodBbObTEZNGWMmUvFi1ahE8++QQAsGDBAqPnWZqf/Pz8kJaWBrFYDB8fH2RmZsLd3R0Mwxgtd506dcLatWvx6quvIi4uDt26dUObNm2wePFi+Pv7o2PHjkhOTkZiYiJmzJiBuLg462+0nFizZg1u3ryJ2bNnl7syHFc3nTx5Eh06dADAbqpNTU1FdnY2vL29sXHjxjLLS7bQsmVLTJs2DYMHD8bGjRvx3nvv4cSJE4iOjsbFixcxePDgcjf/K0ucnZ2xevVqk2Vdd3a5vImIiMDBgwfRsGFDXLt2DS1btkRSUhJCQkLw9OlTtGjRAqmpqRWaxspIRfRzqgpisdisRYut5bxjx47o1asXPv74Y/75L168GHv37jVoiVOvXj0sXboU3bt3h7e3N7KysvDbb7/h//7v/7By5UqtdnDevHkoKipCixYtkJycjOfPn+uFxzCM1e/W3d0df/31l8l6QNN1ioD9sHiwIxaLUa9ePaMviWEY/PXXX1rH3NzczNrSW2pCZCncZuXU1FQ0b96cr5xLu3y4fv16rf/T0tLw888/Y9iwYZg9ezZ/XLeQpaam4r///S8GDBiAqVOn2hy/JppKYrr88ssvpQrb2dkZ69atM3mONVK6X331lUXnaT5DS7B0OVoXX19fpKamag1O5HI5goKCkJGRYfJa3b0Q58+fx6JFixAbG4tPPvkEqamp+Pbbb9G9e3eLzO5sKVP2YsKECfjpp58A2Cc/NW7cGNu3b0fDhg35wQ5nrujo6GjwmqKiIq17d3Nzg0QiQXp6OqRSKW8CUVxcjICAAOTk5GDDhg3YsmULb7YwdOjQCuskavplIKIy3atnivXr14OIMGHCBKxcuRInT57Eb7/9hvbt2yMiIgIuLi5Yt24d5s6da7E5aFmjKSpBRHB1dUVhYSH/+8tmGiSVStGlSxeTZf3QoUPlnCptdNtIc/8LsFREP6eq4OrqanZyNCoqyqawfXx8kJ6ermW2plKp4Ofnh6ysLL3zNfOvr68vnj17pjU5p9kOrlu3DnXq1EFRURGaN2+O/fv3o2/fvrh8+TK6d+9uduLCGCKRCE5OTibrAc16UMCOWLoEZMtyZEUs777yyiv0zTff0IQJE+jtt98mIqInT55QUFCQ3eO6d+8eRUdHmz0vLS2NGjdubPf4y4KqsCRvzXK0Lg0aNKD4+HitYwkJCVSvXj2z11riWTw3N5dq1apl0X1UhWdtKTt27KCwsDBauHAhubm50ZIlS4hhGNq9e7fRa3Tv39vbm7p3706jRo2ipKQkcnNzo0ePHtGYMWOoe/fuNHfuXKpbty6tWrWKjhw5QqtWraL69evT3Llzy/juDPPw4UOLPuXF/fv3iYiodu3a9Oeff2r9dv36dYvzZXlg6N2b+r2qUxXu59/2TuyF8FyMU5bPpkWLFrRnzx6tY/v27aPmzZsbPL9Jkyb0zz//EBFR27Ztac2aNbRr1y4KCQnROxcAFRQU0NixY8nJyYkAkJOTE/Xp04c2b95MAEipVFqdZsGMreIo092qVAGq1mvXrsWsWbMglUrx3XffAQDi4+Px1ltv2T0uf39/3Lp1y+x5RGR3L+qHDh3Czp078ezZMxw4cAAXL15EdnZ2qTdIl/U7++WXX7Bt2zY8ffoUQUFBGDx4MEaPHm3UDMAQM2bMwI4dO/jl6Pj4eH452hzz589Hjx490LdvX1SvXh2PHj3C3r17sWbNGrPXisVizJgxAzNmzDB6TmpqqsFZpcqMsRlbbsbLEgYMGIDq1avjl19+wauvvoq//voLzs7O6NOnj9FrZDIZunbtyv+fn58PmUyGI0eOYMOGDSAi1KlTB3369MH69esRGRmJM2fOICwsjL+mR48eaNu2rZavhfLCkHlGamoqn7cDAwPLNT379u1Dhw4dkJ2djaysLEREREAikWDDhg1o3ry51U5zy5KioiI9E1fufyJCcXFxRSWtTKiIttBaCgoKULduXf7/3Nxc/n8iEmacjVAV3m1FUZbPZunSpejduzeaNWvGt+V//vkn9uzZY/D8hQsXIjU1FXXq1ME333yj5fjZEJMmTUJaWhratm2LuLg4MAyDw4cPIyEhAQDQoEED7NmzBw0bNrQ4zdb0cwTsi8VmbI0bN7Z6z0tycrJWx6Qqo7uvQSaT4eDBg6hZs6aWMoeumYhMJsPJkyfx+uuv82ZDpeXbb7/Fxo0bMX78eMyYMQPZ2dm4ffs2Ro0ahfPnz5cq7M2bN2PYsGF2Sacu06ZNw+HDhzF16lSEhYUhOTkZP/zwA7p164ZFixZZHI655Whz3L59Gzt37uRNoQYMGID69esbPPf8+fP8Mruu48rJkyfzlZeXlxdkMhmuXr2Kzz77zKLOty1lqiwwZDJUWFiIsLAws6Z91oaria5pqCZqtRp5eXn44IMPeHO4oKAg/P3331oy4dnZ2ahfv36F7yV49OgRRo4cicTERPj6+iIjIwNRUVH49ddfy83jdlhYGG7cuIHx48cjLi4OkyZNQlhYGBYvXoxmzZpBoVBg69at5ZIWc1hi3mqtaWtlpmfPnhVupmYOU4qjHOXpIqCq8DL1c+yNpluQsiAzMxOHDh3i2/IePXrA19fX5vBSU1MRGBjIm9WKxWKtPTkikQhubm4QiUT48ssvje4PMsbLZp5blXgpnIpqolAosHDhQj27/s8//xwODg42h6u7r8HV1RXNmjXDW2+9BScnJ/64biPOnWdPSdrq1avjwoULCAwM5DfaERF8fX0rtYd0f39/XL9+XWvG++nTp2jatCnS09MtDqdp06b47bffUKdOHbzyyisYM2YMfHx8MGnSJLuvoGkOSCIiIrR+03QeuWjRIri6uqJp06Zas6OVGU5M4/79+6hZs6bWb+np6ejdu7fZ/Vsc48aNMzhr5ejoiJCQELz55ptGZ8C4BgYAnjx5YjSOr7/+Grdu3cKcOXMQFhaGpKQkzJs3D/Xq1cOKFSssSmdZ0aFDB0RFRWHOnDlwdnaGTCbDV199hfj4eJw+fbpc0sDtg3n48CHq1asHAFAqlVCr1Rg+fDiWLVsmeAIXEBD411JYWIi7d+8adfzMDUbq1auHO3fugGEYqNVqrXNFIhFUKpXJ/UEClY+XbrAzefJkXL58GbNmzUKNGjXw6NEjzJ8/Hy1atMDSpUsrOnl2ISQkBHfv3oWzszO/mpGTk4MmTZpUag/p9erVw9mzZ3m/GgArNNCuXTv8/fffFodz8OBBeHh4oF27djh79qzWcrQ58YTs7GwsXboU165d06vwNFX1/g2cOnUKRISePXvi8OHD/HGGYRAQEGB0tcsQH3zwATZt2oQ33ngDoaGhSElJwf79+zF48GDk5uZi3759+Omnnwyak2rOdnHKRrrVErdxc+7cudi2bRs/kTF48GB8+eWXWhMOFYGHhwcyMzO1/NgoFAr4+PiU20wep3B29+5d3LhxA1u2bMGdO3fQtm1bg2pCAgICAlWVR48eYc6cOQbbckPKt2vXrsXkyZPh6uoKZ2dn/rghx8+61iM1atRARkYG8vLy+Anl/fv3Y9asWbh69aq9b02gDHjpBjshISG4ceOG1gxmZmYmGjdubHLW2BIePHiA69ev6xUsXbOvU6dOGSyApZWF5vjggw+QnZ2NRYsWoWHDhnjw4AGmTp0KT09PLFmyxC5xlAXff/89tm7diilTpiA0NBTJyclYtmwZBg0ahLZt2/LncbMsZUH37t2hVCrRv39/PQd5o0aNMnltr169cPDgQf5/hUKBzZs3Y+7cuejcubPWueUlpW0P1Gp1qR3Udu7cGQsWLNBS1rlw4QKmT5+OuLg4HD9+HBMnTrRqUFuV6Nu3L95991306NGDP3bkyBGsXr0au3btKpc0nD9/HlOmTMHff/+N6dOn4/3338fevXtx6NAhbNy4sVzSICAgIFAexMTEoG7duhgyZIheW27I3LJatWrYtm0bL89viqZNm6JJkybYtGkTXnnlFbRt2xbfffcdHBwcEBERgcDAQH5/UGWS9BcwjlWDHZVKhXXr1mHEiBFG5WQNMX78eAwfPhzt2rWzKZHWUL16dZw/fx5BQUH8sSdPniAyMrJUJk7ffPMNvvrqKzRt2lSrYDEMoyWtOGnSJGzfvh0dOnTQO2/t2rU2x69JUVERPv74Y6xbtw4ymQxOTk4YNWoUlixZUuEz3KbQNQMzhKFZFkOYW442hoeHB54/f26TSaPuRv6hQ4fi+vXruHv3LqZPn651blXab8AN2gwN0C0dtHl5efGS0RxyuRz+/v7IyckBEcHd3V0vfGOkpaXhyZMnCAkJQUBAAH/c0gmH8mbYsGHYtWsXYmNj+f1o8fHx6N+/P1xdXfnzymMQvG7dOmzZsgUJCQno3r07hg8fjp49e+r5ghIof86dO6c1scMRHx9fppM8AuVHYWGhnksEwXeK/fHw8EB2drbFE3W1atXCzZs3LeojHTx4EIMGDUJBQQFvPfLgwQNMnDgRa9euxerVq0u9P0igfLF6ZYfbI2INc+bMwZYtWyCTyTBkyBAMHz4czZo1syoMS5k9ezZ27dqFTz75BNWrV0dSUhL+85//oG/fvhb7fDFEQEAATpw4gUaNGpk8z8fHB9evX+cdT5Y16enp8PPzs7vKR3Z2NubOnYuzZ8/qVdwV7ezPmuVoXV577TUsXbrU7HvUhBOdWL9+vdbqz7p169CuXTvIZDI98QJrsdVvkD3gBm29evXSmyGzdNDWvXt3hIWFYc6cOQgODsaTJ08wd+5cPHz4EEePHsX169fRs2dPbN68Wev+2rZti06dOuHYsWNwdHTEkydPMGLECJw9e5bf6N+2bVts3LgRv/76q0UTDhVBWfmTspZr167h3LlzvMnFzZs3cePGDRQUFKBfv34YOnQoOnbsWKZpsAbOHPHfgj2UD8uLpKQkPH78GDExMRWdlCrB9evXMXLkSPz555/8MYZh4ODg8K9XsktJScGHH37I9yc0sdXh6qBBg/DBBx9YvLKyd+9e7N69G1OnTtUypQegVQdxYlRz585Fz5490bx5cxw8eBDt27dHdnY2EhMT+Xf8wQcfYPny5VannZuE6tu3L9zc3Ky+XsB6rJaeHjx4MH799VerpJznzJmDOXPm4PLly9i6dSveeOMNuLu7Y/jw4Rg6dKhFM/7WxBUaGopff/2Vb0gnTZqEd955p1Thurm56W3iNkRgYKBeh7EsuHv3Lnbu3MnL3A4YMAC1a9e2W/jvvvsu8vPzMX/+fAwYMAA7d+7EokWLtMx0bCEnJwdHjhzRUk/RVNeyhOnTp2P//v0WLUfr0qhRI3Tp0gUDBw7Uc/RmzMxQc+Cq+d3f3x+vvfYaxo0bZ3U6NNm5cyfGjBmDJk2a4PLly2jVqhUuX76MDh06lMtg59ChQ0hOTrb6PWiyYcMGTJgwAeHh4VCr1RCLxXjzzTexYcMGnDp1CgMGDAARoVOnTvD398fz589Ru3Zt/PXXX0hOToZCoYCjoyPGjx+PJk2aYP/+/XB1dUVBQQFmzpyJ9957DxcuXMClS5esGqiWF5VhJW/58uWYOXMmevbsid27d6Nv3744c+YMGjVqhLy8POzevRsJCQmQyWRYtmxZqcuyPahfvz5at26NYcOGYcCAAfDy8qroJJUJnAm1Wq3G06dPtQb8Dx8+LJV4jr25f/8+hgwZgocPH0ImkyEvLw+//fYb9u3bZ1JB8d/O+PHj0bt3byQkJCAoKAhPnz7FrFmzUKtWrYpOWoUzduxYhIaG4syZM4iKisKFCxcwb968Uim1OTg4oGfPnujcubNeW25oBZ2Tjt6wYYPecc0B1507dwCwZfXAgQMoKirC5cuXoVKp4O/vj23btvHnbt682abBzpAhQ7Bx40ZMnDhRWH0vJ6xe2enUqRPOnj2LWrVqITQ0VGtFwZIN3kSE48eP46OPPuJlZJs2bYpFixahZcuW1t9BGaK5x2ffvn04ceIEpk+frmVWA7CNFUdiYiL27t2LKVOm6BVAe5kpbNq0Ce+//z7efPNN3mRm//79WL58OUaMGGGXOPz8/PDgwQO4u7vDy8sL2dnZeP78Odq3b4+bN2/aFGZ8fDzeeOMN1KtXDzVq1EBSUhJu376N/fv3W/VsrFmO1kVXVY/DEjPDU6dO4fHjx/z///zzD3bs2IGxY8fqvWtrzKrq1auHpUuX8n6DsrKyeL9BK1eutDgcW2nTpg12796N0NDQUoelUqnw/Plz+Pn58Z6tmzdvzk84cPe3dOlSZGVlYc6cOVixYgWOHz+O6dOno1u3bvjjjz/4Sj84OBhyuRxBQUHw9PTEzZs3tVbzKhMbNmzQU4Esj8EqR0REBH777Tc0aNAAvr6+6NKlC37//Xd4eXnhxx9/RI8ePSCRSPB///d/GDZsmFUKiGVFYWEh9u7diy1btuDEiRN47bXXMGzYMLz55ptWmUpXdowJbwDsXoJZs2ZhwoQJFZAyfTp16oT+/ftj4sSJfHnNy8tDw4YNkZycXNHJq7R4eXkhIyMDYrGYf25yuRw1a9a0u0poVcPHxwdPnz6Fo6Mj35/Iz89Hs2bNcO/ePZvCNLWabmjyKTg4GAsXLsTgwYPN9h3Wrl2L999/n1ezJCKIxWKo1Wr4+PhgxIgRKCws1FrlsYW0tDTs3LkTW7Zswe3btyvl6vvLgtWDHVMzO6Y2eJ8/fx6bN2/Gzp07ERYWhuHDh2PIkCHw9vbGunXrMHfuXLspidnDcSVguoHiYBjGIntcS/eiWEJ4eDi2bNmiZV6QmJiIwYMH49GjR3aJo1q1anj06BGcnJwQHh6OxMREeHp6olq1agbNMCyhTZs2mDZtGgYNGsQf27FjB7799ltcunTJ4nAsXY62B7p+dj744AOD53l6evLfrTWrKq3foNIyZ84cuwzaFAoF7ty5o2eK9/rrryMnJwcMw/D3pFarERQUhLS0NC2ba+46hmHAMAySk5Nx+fJlTJ06FZ988onRCYeKNoWaN28eNm7ciI8//phXgVyyZAmGDRtWbg5POelpT09PyGQyrFixAkOGDEFoaChycnK0zh0yZEil8bnDwQ3yly5diqSkJPTp0wfvvPPOS7UBuFu3bjh69GhFJ8Mk3t7eyMzM1CqvVcG1QUUTHh6OK1euwMfHB40bN8avv/4KPz8/NGnSpFI59K0IQkJC8Pfff8PNzQ116tTBkSNH4OPjgxo1atjcn7CWoKAgJCcnaylm6sK5QahWrRpWrFiBYcOGQaFQAADfNhYUFEAul2Pq1Kl4++23S+1qIicnBzt37sSSJUuQlpaGwMDASrX6/tJA5UBERATVrl2bZs2aRf/884/Bc6Kjo+0S1yeffEKNGjWiNWvW0NGjR2nNmjXUuHFj+vjjj+0SfmWgWrVqJJfLtY4VFRVRQECA3eLo168fbdq0iYiIJk+eTC1atKCYmBjq0aOHzWF6eXmRUqnUOqZUKsnLy8uqcPbu3UsBAQHEMIzWRyQSWXT96dOnafz48fTmm2/S+PHj6dSpU0bPbdSoEf89PDzc4CciIsKq9OvSpEkTvly0bduW1qxZQ7t27aKQkJBShWspHTp0MPjp2LGjxWGcPHmSAgMDKSgoiCQSCQUFBZFUKqUGDRpQ3bp16fHjx0RE1LJlSzp69ChduXKF/Pz89ML57bffyNPTk0aPHk2zZs0iAARA713b8t7Lkho1alBSUpLWsaSkJAoLCyu3NLRp04YuXbpE8+bNo06dOtHs2bNpyZIlVKtWrXJLg62kp6fTjz/+SK+88goFBgbShx9+SIsWLaIGDRrQ2LFjKzp5/ypatWpF586dIyIib29vIiI6c+aM3drol5UFCxbQ7t27iYho9erV5OrqSh4eHvTJJ59UbMIqAZMmTaJt27YREdH8+fMpJCSEIiIiaPjw4aUKd/369dS9e3dq2rQpde/endavX2/03FWrVtG0adMoOzvb6Dlubm5ERFSzZk1iGIZvf3Q/Li4upUp3YWEhbd26ld58803y8vKiwYMH0759+0ihUBAR0bFjxwy2jwK2Y/Vgp7CwkKZNm0bh4eHk7u5ORERHjhyhJUuWGDxfpVLRV199RUVFRaVKqKX4+fnR06dPtY49efLkpco4P/30E7399tuUlJREarWaHj16RGPHjqWVK1eWSXxKpZLWr19Py5cvp7y8PJvDadeuHS1fvlzr2IoVK6ht27ZWhRMUFETr1q0jmUxmdRpWrVpF/v7+NH36dFq5ciV98cUXVK1aNVq1apXZa7mKyN4cOHCATp8+TURspyIiIoL8/f1py5YtZRJfWdCsWTNas2YNERE/eP3hhx9o9uzZtHbtWjp8+DAREe3evZucnZ1JIpHQ4sWL+euLi4vp1KlTtGXLFrp16xbNnDmT3nnnHZo3bx7dunWr/G/ISgIDAyknJ0frWFZWFlWrVq3c0nD+/Hm6evUqeXl50c2bN6ljx47UunVriouLK7c0WMv69eupW7du5OXlRcOHD6dDhw5pTYjk5uaSq6trBabQvjx8+JBGjx5NLVq0oDp16mh9KgsnT54kf39/eu+998jZ2ZkmT55MwcHBfB0lYBkPHz6kGzduVHQyKiWnTp2iAwcOkEqlsjmMuXPnUt26dWnVqlV05MgRWrVqFdWvX5/mzp1r8HyJRMJPjkmlUpJKpSSRSEgqleqdu2fPHho0aBDVr1+f1q5dS5cvX+Y/v/zyCzVq1IgeP37MT+JZi4eHB3Xu3JnWrl1Lubm5Bs8ZPHiwTWELGMbqwc7o0aNp+PDhdP36db5T8+TJE6pXr57Ra7hBUXlQt25devbsmdaxtLQ0qlu3brmloazRLLTch2EYvuAaK8DWsHDhQoPHv/32W5vDvHnzJtWsWZMiIiLo1VdfpYiICIqIiKDr169bFU5gYKDNA4/atWvTn3/+qXXs+vXrZme/lUolOTk5UXFxsU3xVnauX79OX331Fb3//vtERHTr1i26cuWKxde7u7uTWq0mopLZYJVKZXC1sbi4WKuCv3TpElWvXp1at27Nz6wdOXKE+vfvr3etSqWihIQE2rVrFyUmJpaqsbQn77//PnXs2JFOnTpF9+/fp5MnT1Lnzp3551mevPfee7Rhw4Zyj9cWunbtShs2bKD8/Hyj5+zbt68cU1S2REdH08iRI+nQoUN08uRJrU9lIikpib755ht6//336euvv6YHDx5UdJIqPT179jR4/I033ijnlFQ+JkyYYPD4xIkTbQ7T2tX0hw8fGv3osmvXLqOrOpqWBrZYFSiVSpo3b55Nk7UCtmP1np2AgAAkJyfD0dFRa08Bt+nMEAMGDMCECRP0HC+WBZXBcWVZY+m+nBo1atgch70lUtVqNU6cOIHIyEhcu3aN38QdFRVltQLJ6tWrcffuXcyYMUNrr4wl+Pv7IyUlRWvzs0wmQ1hYmFkv823atMH27dvtqh4IVLwc7YYNG/DFF19g6NChWL16NXJycnD16lVMnToVJ0+etCiMevXq4cSJEwgODkarVq2wcOFC+Pv7o2vXrggMDMT169f1rmnevDn++OMPtGnTBl9++SXefPNNeHp64qOPPsKVK1dw5MgRLedw33//Pfr16weFQoHQ0FCkpKRAKpVi586daNGihb0eh00UFxdj7ty52LZtG+8faNCgQfjyyy/L1ffVw4cP8eabb+Kvv/5CtWrV4OPjAwC83zFLRGTKC5VKpSU7/m/AWt8gFYHg88c2Kroer8yUxbMJCgriRa44srOzUb9+faSmppq9/vTp0xCLxQb9XnF7QNu2bYtHjx6hY8eOvPPt06dPIzIyEkuXLrUp3YBtLlwESofVg526devi999/R2hoKJ9R79+/j169euHWrVsGrxk2bBj27NmD9u3b6ym42dvJnj0dV/4b2bx5MwBWKvLnn3/Wk0j95ZdfeGlGazFW4VmLVCqFSqUCwzC84hcRgWEYyOVyk9cOHToUIpEICxcuRFhYGJKSkjBz5kwoFAqzG7ZnzZqFrVu34p133tHLx6Vxaunu7o68vDytY4WFhQgLC9PzSVAW1K5dG4cOHULdunX5SlipVCIwMNDsAJDjl19+QVBQELp37449e/bwGzu///57fPnll3r3x8l4ZmZmwsfHBxkZGWAYBlKpFO3bt0ffvn3x2WefYcWKFfw1S5cuxdtvv60lErFixQqsWbMGV69etc/DsAGVSoUxY8bgf//7X4V22ufPn48FCxYgKChIT8r4888/B2BaRKYiqFmzJq5fv67lePVlxlrfIBVBrVq1oFQqMXDgQAwZMgStW7eu6CRVaoz5YQPYicm8vLxS+2GrqnA+a+bNm6cn1PLw4cNSqZlNnDgRt27dwpw5c/i2fN68eahXr55Wu8HRvn17LFiwAG3btsU333yDpUuXQiqVYvz48XpuJ4KCgjBlyhR8/vnn+N///ocGDRrw7X1ubi7efvttLbVeaxk/fjzatm1rlQsXgdJh9WBnxYoVWL16NaZPn4733nsP69evx9dff42xY8fivffeM3iNtRKBVYWkpCSEhITwHW5jnD59Gk2aNIG3t7fNcXXp0sUiNbnSztxykodnzpxBu3bt+OMMwyAgIACTJk0yOBNiCfZa4TO1smVuNSs7OxsTJ07Ezp07oVQqIZVKMWDAACxbtszs+zEmB6mpvrZhwwZER0dbpNBSp04dfuCt68MpPT0dvXv3xrp168yGU1qqVauGx48fQyKR8BMYMpkMNWvWxNOnT20KUy6Xo3v37pBIJDh58qSeT6SUlBSEh4fj0KFDaN++PaZOnYo+ffqAYRgUFxfj8OHDWLZsGY4fP85f4+npiczMTK3yplQq4ePjU26KPsYIDQ3FgwcPKtRPgq+vL+Lj41GvXr0KS4O1aMqOh4SEaNVxFa2wVxaMGDECe/bssdg3SEVx4cIF7NixAzt27IBYLMagQYMwaNCgCl9BrYxw/ZsFCxZodZq5NnPAgAHw8/OrqORVKJyrh02bNmH48OH8ce7ZlEbNTHc1PTg4GIMHDza6mu7r64v09HSIRCJERETg6NGjcHNzQ1RUlJ6k+urVq/Hpp58iJycHAQEBcHBwQHZ2NuRyOS9FzbXZ//zzj9VpL60LFwHrsXqwA7BywWvXruU7+2+//TaGDBlSFukrFd988w0/o1kWiEQihIeHY/r06SYdS4pEInh4eGDixIn4+uuvbYrLUmdu9pq5nT9/PmbOnGmXsDjKc4XPHGq1mvcHY0+TkoiICGRmZuL111/Hpk2bTJ576tQpEBF69uyJw4cP88e5hqB+/fp2S5cphg0bhrCwMCxYsIBfbZk5cyZSUlKsGmylp6fj8OHDePr0KT777DMsWbIEarUaM2fO1PIXxN1fp06d4ODggOvXr6NHjx5o3Lgxjh07hg4dOuDevXs4ePAgGjduzF/37rvvonXr1vxMKgCsWbMGFy9exKpVq+zyLGxl1apVuHbtGubMmaMni11eNGrUCPHx8fD09MS+fft4b+WaVbw5X1LljbGyp+vo72WhKk78JSYmYubMmThx4sRL+U7sxalTp7TMbgVK2LBhQ7n6HDOEr68vnj59irt376Jv3774+++/QUTw9PTUmyzjrEcMdY+9vb1Ro0YN/PDDDwBg0zu31YWLgO3YNNixhYpwuGcvsyljPHr0CMnJyTh79qzZQVVKSgrOnj1bKQeFxuA6r6mpqfj000+RkpICtVptkV8hQ5Smoe/duzf27t0LwPQqlyWzIoWFhbh79y7y8/O1jhuyU7fU/EDzWqVSiUuXLiE6Otqiazlb4IoiKysLb731Fk6ePImioiK4u7sjJiYGmzZtsng18ujRo3jrrbfQvn17HD16FLm5uTh79iwWLFiAFStWmDQvXbBgAeRyOW7fvo2UlBTcvHkTQ4YMQVhYmNZ5cXFxOH36NKpXr87v2UlOTsarr76q9fwqYmZM07RS0z+XJaaV9iIhIQGLFy8GEeHcuXPo0qULduzYgYEDB+LkyZMYMGAAFi9eXC5pEaj63Lp1C9u2bcO2bduQl5eHgQMHYsmSJRWdrErNoUOHsHPnTjx79gwHDhzAxYsXkZ2djS5dulR00iqcGzduYNeuXUhLS8OKFStw+/ZtyGSyUq0WPnz4EH/++adeW27IrHzYsGEoLCxERkYGOnfujDlz5uCvv/5Cnz59+NUZzjSNcwLL+X+8ceMGXFxc4OzsjPDwcDRu3Bi//PKLzekWKH9sGuxY67SzohzuGdoL8TKgVquxcuVK7NixA8+fP8f169dx+vRppKSklGrviCamOq+HDh2ySxzWsHnzZv7eSjMrsnbtWkyePBmurq5wdnbmjxvbx6XbSX/8+DEYhoGvry8/ax4aGlqqPWAymQyzZ8/Gjh07kJGRgdzcXBw9ehS3bt3ClClTbA7XElQqFdatW4fhw4cjJyeHX6211oSoUaNGWLt2LaKiouDt7Y0VK1ZAqVTigw8+0FrV0WXYsGGoX7++loNcjsTERH7AyDCMxTNoFTEzVhrTSnuxevVqTJkyBcXFxQgKCoJUKsWjR48QHh6Offv2YcqUKVpmgZUFtVqNixcv8sIOrVq1MmsaXJW5du0azp07p7fqNmvWrApMVQlz587F9u3b8fz5c/Tv3x+DBw9Gu3btrHbK/W/j22+/xcaNGzF+/HjMmDED2dnZuH37NkaNGoXz589XdPIqFHuI4OjC7VFs2rSpXltuyKl3UVER1q9fD6lUirfeegtSqRQnT57E06dPMXToUADQm6jiUKvVvKNrAKVe4VQoFFi4cKHeAsDnn3+ut99SwD5YPdiZNm0aDh8+jKlTpyIsLAzJycn44Ycf0K1bNyxatMjgNeHh4Thz5ozWTG1ycjLatm2LpKSk0t2BCRYuXIjp06fbfD23Wd8cDx8+tOg83U1wtvLJJ5/g6tWr+OijjzBixAhkZWXh4cOH6N27N65du2aXOHQ7r1lZWZDL5QgNDcWzZ89sCvOLL75A7969ERUVxR87f/489u/fj/nz59sl3eaoVq0atm3bpreHxBLmzp2L3377Da1atYJEIoFSqcSVK1cgkUjQsmVLrXOtMcsbM2YMFAoFPv/8c7Rr1w5ZWVl4+vQpOnbsiNu3b1udTmuxhzKMn58f0tPTea/rzZo1AxEhPj7e6B4vrlF6GVSMsrKy4ODgoLXRvqCgAAqFAl5eXuWSBh8fH+zevRt9+vRBZmYmGIZBUFAQ7t69CxcXF4PmGhXN7du38eabb/KCHMnJyXBxccGePXvQsGHDik6e3Vm+fDlmzpyJnj17Yvfu3ejbty8OHjyI3r17Y8OGDRWdPADAuHHjMHjwYHTq1KlSq8ZVNqpXr44LFy4gMDCQr1OJCL6+vlWmHisr7CGCo0tZ7lFs3749oqOjceLECXh7eyMuLo4f4Dg4OKB79+78njtbTPAnT56My5cvY9asWfwCwPz589GiRYtSqbwJGMfqwY6/vz+uX7+OwMBA/tjTp0/RtGlTpKenG7ymtBKBFYWxDemaMAxj0cwtwzB2s5fXfJ6aHVVT8t/Wott5zczMhEKhQEhIiM2DHU3Zco6ioiLUqFEDaWlpVoV16tQpXLt2TW/52tyAslatWrh586ZNcsB+fn6YOHGiVgdApVJh0aJF+Oyzz7TOtcb+3hY5d3tiD2WY119/HT169MDEiRP5e1i5ciWOHj2K3bt3G7zGmFLP/fv3ce7cOTx+/BjDhg3D4MGD0bFjRygUCmzevNnge6/ozd3R0dFYuXIlmjdvzh+7evUqJk6cWG5KTBEREbh16xa6deuG+fPno127dujXrx98fHzg7u6O33//3W6TIfaiY8eO6NWrFz7++GN+1nTx4sXYu3cvTp06VcGpsz8RERH47bff0LJlS758nzlzBv/973+xY8eOik6eQCkICQnB3bt34ezszNeBOTk5aNKkSZlO6lYFykIER3OPoiVkZ2dj7ty5Bvcy6lpm+Pr6wtHREQUFBSgoKECLFi1w9+5d5OXlQaVSwcPDAx999BEA2/bahYSE4MaNG1pm4pmZmWjcuHGpVN4EjCOx9gIfHx89EwOxWMz7czBEv3790KdPHz2JwP79+1ufYhNkZmZiyZIl+P333/nN5506dcKUKVPg6+trdXgnTpywa/rshaOjI5RKJQDwHYTU1FSb7tEY0dHR+PHHHzFx4kT+2M8//2yzEhtgeNOxSqWCWq22KpxJkyZh+/bt6NChA1xcXLTCN8fixYsxfvx4TJ06Ff7+/lq/mTPd8vb2RnR0NHr06MEfO3LkCIKDg0u1udjLywvp6ekIDQ3lj92/f5/3jVLW/PPPP1i7di0WLFhgszLMTz/9hDfeeAPLli1Dfn4+mjdvDrVajYMHDwIwvP/rjz/+gKurK1QqFS9nfuPGDdy8eRPNmzfHsGHDIJfLMWLECEyZMgUXLlzA33//jZ49eyIkJMT+D6IU/PXXX1oDHQBo0aIFbt68WW5pmDZtGt5++218+umnkEgkePLkCWbOnInvvvsOOTk52LhxY7mlxVKuXbuG48ePa+W5yZMnY968eRWYqrIjMzOTXwV2cHCAXC5Hu3bt8Prrr1douuy5J/LfSt++fTFu3DjewiUnJwdTp061ez+nKvLaa69hxowZ/AQXAHz99dfo1q2bzWGuWbMGY8eOxfDhw/VEYQztv3333XeRn5+P+fPnY8CAAdi5cycWLVqk1Z5rIpFIkJubi/DwcBw7dgy1a9eGg4MDPDw88OzZs1K1+WKxGEVFRVrHioqKhJXUMsTqwc7YsWPRvXt3PaedY8eO1ZrB1Mxsixcvxty5c3ltck2JQHvx8OFDtGvXDv7+/ujTpw+qVauGtLQ07N27F7/88gvOnj2L8PBwu8WniaUjcXtJqY4aNQqDBg3C/PnzQUT4448/MGPGDLz99tt2CR8w33m1hddeew1TpkzBf//7Xzg5OaGoqAiffPKJ1VLUmzZtwvXr123q8DIMg8OHD+uZjFii/vTf//4XAwYMQP369REQEIC0tDT8/fff+Oqrr/Rm761xyjd58mT06tUL06dPh0qlwp49e/D111+X+X4djlGjRpV6n0tYWBiuXr2K8+fPIzk5GSEhIYiKioJYLNbb//Xpp5/i4cOHyM/Px/bt29GxY0derCQ4OBhXr17VMk0YMWIEOnToAJlMhsePH1dKnyyBgYG4desWGjRowB+7detWuUrOcv6HtmzZotVZ5fL2mTNnyi0tlhIeHo4DBw6gd+/e/LFDhw6VWV1d0dSrVw9//PEHmjdvjubNm2PBggXw8vLSm3gpbwYPHsx/HzFiRAWmpOqyaNEifPzxx6hVqxZkMhmCgoIwatQoLFy4sKKTVuEsX74cb731Fjw9PVFUVARvb29eBMdWrl+/joMHD+LMmTMW7b/9/fff8eDBA7i7u0MkEqFr165o2bIl7/pAk27duuHWrVtITk6GSqVC3759oVKpIJPJ4OnpCYZhSrVPesyYMejatSs++eQTVK9eHUlJSfjPf/6Dd955x/oHIWAZZCXh4eFmPxEREdYGW2oGDBhAkydPNvjbhx9+SP369bM6TIlEQlKp1OiH+51hGBKJRMQwjNGPSCQq5R2WoFKp6LvvvqP69euTi4sL1a1blxYuXEhKpdJucRARqdVqSkxMpO3bt9O5c+dKHX56ejp16dKFHB0dKSwsjJycnKhbt270/Plzq8Jp0KABZWZm2pSGoKAgWrduHclkMpuur169Ovn5+ZG3tzf5+flR9erV7ZL/t2/fTt27d6eGDRtSly5daMuWLTalrzLSsGFDSkxMJCIiLy8vIiIqLi4mf39//pz8/Hy6du0aVatWjY4fP07nzp2jc+fOERFRbm4uVa9enTp16kS3bt0q/xuwgKVLl1Lt2rVpzZo1FBcXRz///DPVrVuXli5dWu5pqV27Nj169Ejr2KFDhygoKKjc02KO06dPk7e3N3Xo0IFGjhxJ7du3J29vbzp16lRFJ61MOH/+PF25coWIiG7evEkdO3ak1q1bU1xcXAWnTMCePHv2jNRqdUUno9KRmppKFy5coMePH5c6LG9vbzp58qTF5wcEBPDtfo0aNejp06dUWFhI7u7ueufKZDJauXIlxcbGkqOjIzk5OZGPjw/16NGDxGIxtW7dmhITE6lBgwY23YtarabVq1dT586dqUGDBtS5c2davXo1qVQqq8MSsIxyk562RiLQFnx8fHDv3j2DUrkZGRmoXbu21ZuwTSksaVJeakvljVqtxoULF3jVvcjISLsssz5+/BiPHz9GWFiYTaZanE3/lClT9BzzmVtRCQoKQnJyMiQSqxc1X1rsoQb3xx9/YMqUKVplnF4o2nh4eJjc//Xrr7/i/fffh4uLC5RKJT97JpFIsGnTJnz77bfo2bMn2rZti7fffhstW7bUc8JqL/GP0rBp0yasX78eKSkpCAsLw+jRo3mVn/Jk9+7d+PzzzxEXF4fQ0FBs374dU6dOxf79+/WENCoDmZmZOHToEL/q36NHD7ua5ApYT2VXjKus3L17Fzt37uTbzAEDBqB27doVnaxKQU5ODu+HLSgoCD169LB4v40huD2Klu6/7d+/P/r3749hw4ZhypQpOH36NJycnODl5WVQYValUkEikfDqbAD0lNqICCKRyGp1tnPnzhncEhAfH2+VVYiA5ZTLYMdaiUBb8PDwwJMnT+Dm5qb3W15eHkJCQuyiRKRWq5GammrWJC0pKQmPHz82KKlrDx48eIDr16+X2eDx2rVr6NevH5RKJUJCQpCSkgKpVIrffvtNb2+CtXBa95pZzxrfPcZ8thhbvtZk9erVuHv3LmbMmGF1Rfvo0SPMmTNHa4M8EaGoqAjff/89hgwZwkudu7u7WxW2tXLu9sQeanCNGzdG3759MWzYMK19VAAwceJEk+IFwcHBWL9+Pbp06WJyMK2ZX0aPHs1/t6f4x8vC1q1bMWfOHLz99ttYsWIFjh49Wm5OagW0OX/+PK9AaUqsorJ0cqqCYlxlZNOmTXj//ffx5ptv8sqC+/fvx/Lly//1poHHjx/HwIED0aRJE377w82bN7F9+3a89tprNoX5448/4uzZs/jss8+s3n+rUqmwceNG5OfnY+TIkXrtdXZ2Nr744gusWrUKjo6OkMlkcHR0BMMwUCqVUCgUSE1NRdu2bXHv3j2r0/4yKJBWOSxZ/rHUnMsYPj4+dPv27VItQZmja9eu9O233xr87ZtvvqEuXbqUKvz09HQaMGAASaVScnV1JSKivXv30meffaZ13r1796hNmzbk7+9Pbm5uRES0c+dOGjlyZKni12ThwoXk5OREkZGR1KFDB/7TsWNHu8XRokULWrZsmdax5cuXU/PmzW0O888//6TmzZuTSCTiP2KxmJydnUubXIuRSCS8WaGl+ZcjOjqaRo4cSYcOHaKTJ0/SqlWrqFq1alSvXj3+XR85coT69+9vVZo++eQTatSoEa1Zs4aOHj1Ka9asocaNG9PHH39s0z1ai7///7N35nE1pv//f502Sfu+l0jZkhENIWQpW1HaNBFjZ4TJ2JXdDBkztrEOg1C27MZnUlJkDC1kifZ9V4rqnPv3h1/3t+NUzn5OuZ6PRw+57vtc1/u+z+nc1/u63u/XW4f68OEDRVGfQgMaUVNT47oPVVXVFsM2srKyqD59+lBWVlaUvLw81adPH6p3795UVlYWRVGfQgvr6+u/OIaKigpVWFjItU3i5unTp9TevXupDRs2UCEhIfSPOMjNzeX42bJlC6Wnp0fFxsbSbdJGeno6NX36dKpv376UpaUl2097oWfPnvTv0hT63RLm5ubU48ePKYr6v++AmJgYysPDQ4JWST9mZmZUXFwcW1t8fDxlamoqIYukBysrK+rSpUtsbZcvX6a6devGd5+iTBmYMmUKpa2tTenp6VGysrLUt99+S3Xq1IkaNWoUpaSkRD158oQaO3YstWnTJp76bfwe7tSpE5WXl8f2fR0bG0vp6ekJbDuhebja2RE0nItXiUB+SExMhKOjI0aOHAlXV1fo6+ujoKAAly9fxp07d3D37l2BdiTc3NxgbW2N1atXw9TUFOXl5SgrK4OdnR3bbsKIESPg7u6OBQsW0LLQVVVV6NGjB7Kzs4VwpZ+kiqOiotCzZ0+h9NccampqKCsrY1Pea2hogKamJt87ZA4ODhg1ahRWrFgBAwMD5OfnY926dejSpQvmzJnDc3/87BAJUvxRVVUVFRUV9O5D//79sXbtWkycOJF+r/mR0+RHzl2YdOvWDf/88w+MjY3plaW3b99i3LhxSE1N5aqP+fPnY9iwYfD09Gz2OEVRzYoXAJ9UdZ49e4b169e3WpPGzs4OkZGRQhP6ECZ79uzB2rVr4eLiIpHV8KbF8D6naeiFoMXwhI2dnR1sbW3h4eHBtusPgOsism2JhoYGqQ+hVVNTQ2VlJYBPz5qcnBwoKCiwtRM40dfXR3Z2NuTl5em2jx8/wtTUlOfSCu0NTU1NFBUVsX32GxoaoKurK9KdjNmzZ3N13uelC7S1tVFXVwddXV28efMGnTp1goKCAsrLy8FgMCAnJ4cNGzYgKCiIpwLIrX1P6+npYd26dZg3bx7X/RG4h+8wNm7DuQAgPj4eoaGhXEsE8surV68QEhJCS09raWlhxIgRWLduncAhHNra2igsLKRltluqhaKhoUEX9Gs8jxJyYTELCws8e/aMY3IgTGbPng07Ozu2L4vDhw/j0aNH+OOPP/jqU11dHaWlpZCVlWUrVGphYYGcnByu+0lOToa/vz+SkpLoNgaDAQUFBdTU1PBlGzd4enpi4cKFGDp0KIBPX+ClpaVs7zWTyYSuri5KS0u57tfKygqxsbFsW/FFRUUYMmQIXr58KfTr+Jy9e/fi4MGDWLlyJebMmYPjx49j8+bN+P7777l2Qp2cnBAbGwtra2uOPKovydXKy8uDyWSCwWDQ8c+NX0vy8vL0RH3lypW4cOECZs6cyfE9IqzwTX4h9VP4Q11dHWVlZV+F5CqTyYSysjIqKyulukr6gAEDcPDgQdja2mL06NEYNGgQ1NXVsWfPHqSlpUnaPKnlwIEDePToEYKDg+lQrY0bN8LOzo6vxbz2xLp160BRFNauXUtLrm/atAkMBgMhISEiG5fbvj+XkdbT00PPnj3h7++PFStWYN++fVBWVoabmxtu3LgBQLDFmDFjxuDWrVt8v57AOzw7OyUlJZg3bx4uX74MBQUFVFdXIzIyEnFxcdi2bVuzrzl48CACAwOhqqrKlUSgNNKrVy+cO3cOPXr0oCe2SUlJ8Pf3x9OnT+nz7Ozs8Ntvv2HQoEH0ebGxsQgKCkJ8fDzf4zeVt46MjERUVBRWrlzJMekTZNW7aX0FJpOJmJgYmJqawtjYGDk5OcjKyoKjoyPu3LnDV//m5ub477//oKmpiV69euGvv/6CtrY2evfuzVPxTGHvEHGLn58fLl26BCcnJ+jp6eHKlSvo3bs3zM3NERERgbKyMly+fBm///77F+9R09j9+/fv48yZMxxy7p6enggKChLZ9TQlPDwcR48eRVZWFoyNjREQEABvb2+uX3/8+HG2/zeV0GxtIltXV8e22zZixAi4urpi3LhxUFRUZKs91DRPpynCzP3jF7Iazh/z5s3DyJEjv5paJP3798e5c+dazDuUBhISEqCgoABbW1s8f/4cCxcuRFVVFbZv344RI0ZI2jypQl5eni1ZvXHRphGKoiAnJ4e6ujpJmSgxLC0t2e5NRkYG5OXloaOjg5KSEtTV1aFz58549eqVhC3lxN3dHe/fv0dSUhL09PSQkZEBGRkZKCgoYOjQobRUfocOHWBkZAQ7Ozup37H92uHZ2eE2nKspmpqauHjxosTCEm7evImtW7cKVJE7IiICS5cuxfz587F582Zs3LgRe/bswY4dO+Dm5kafFx0djSlTpmDy5Mk4ceIEZs+ejfDwcJw5cwZDhgzhe/zWtj8bETRM5fMJa0vwW5Nl69at6N69O9zc3HDo0CEsWbIEsrKymDNnDn7++Weu+xHWDhGvfL5KVFhYiJMnT9KTW2dnZzx58gTXrl1Dr169Wu2Lm8mOKBcD3N3dcf78eQCfQrAaa7QIi6YOTGRkJCIjI7FixQq6qPAvv/yCCRMmsI2blZUFGxubNrnSL02r4dnZ2fjhhx8QGxvLsZssbWFshYWFGDhwIFRVVTkWbtpjAct169bhzJkzmDlzJkcBX0nvThJ452tXbG0Nbudb4pwXRkVFcQgBDR8+vNlzAwIC6N2XoqIiMJlMyMjIQFZWFrKysmCxWOjfvz/tCF28eBH9+vXjyo6Kigps2LABsbGxHKH4bWUDoK3Bs7PDbThXU3iVCOSHgoIC/Pjjj3j69Cm6du2K3377DVlZWfjhhx9QWlqKRYsW4ccffxRojISEBBw7dgxZWVkwMjJCQEBAs2prOTk5OHXqFH2er69vuy2SJwiZmZmorq7mOfdIWDtEwuD9+/e4evUq/V6PHz8eqqqqYrWBHzQ0NFBUVAR5efkWlWG+xI4dO+i/qaaVsT/n8OHDePr0Kdt9qayshK2tLdLT0/H27Vt4e3sjIyMDFRUV+Pnnn2FiYoLIyEg2B9zZ2RlTp07F5MmTpa6wqDSthjs7O8PY2BhBQUGwt7dHQkICNm7ciMGDB0tdOM2QIUOgpKSESZMmcYTlClroVhppaWIlDbuTTRG12md7pyVpYcKn+VHTHXtxsWPHDoSGhmLmzJm0Wt7Ro0cRGBjYYgRF4/Pn+PHjMDExQc+ePXHkyBH4+vpCT08PSUlJ2LdvH7Zt24ZLly7hwYMHXNni6emJ6upqBAYGwsPDAxEREdixYwdcXFw4CpwShAPPzg634VxNEUQikFvc3NxQW1sLNzc3XLhwAQUFBaipqUFISAh8fHx4SiIjsMPvZFhUCGuHiFdYLBYOHDiA8PBwlJSUICYmBgkJCSgtLaUnAe/fv0d9fX2rifatsW3bNqxYsUKIVjfPd999h/j4eFhYWODu3bsYNmxYs+e1tro+b9487N+/H8CnVbDmYDAYuH79Ou7fv48uXbrQ7WlpaXBwcEBhYSGbqIeqqiq0tLRQUVGB6upqth2wlStX4syZM4iPj6cdn7Fjx7IlBBM+7aTn5+ejQ4cO9CJUdXU1+vTpw5dMqihRUVFBeXk5CQGRIrZt24aQkBDY2NiwychLm0MmzUjbM1OaEOTeNA3nb43m5pWGhoaIioqClZUV3fby5UsMGzYM+fn5zYoZZGVlIT09Ha9fv8aMGTNQWlqKSZMmYf/+/YiNjaWfVXV1ddDR0eE6ZFlbWxvp6elQUVGhv6NLSkrg6OiIZ8+ecdUHgUd4lW8LDw+nTExMqK1bt1LKysrUrl27qC5dulAXL15sWfJNhBKBjWhra1Pv3r2jKIqiysrKKAaDQb18+VJo/fv7+9MV3Ru5f/8+NX36dLa24cOHU/fu3WNri4mJoZycnIRmi7hplFUWlMePH9MV0nmVfW6NjIwMKiUlpcXjgkqnN7Js2TJqxIgR1NWrVyl1dXXK3t6eunbtGmVjY0Of899//1EDBw7k+1qaq+YsKmJiYqi//vqLUlRUpP78889mf4TB5s2bKWNjYyokJIQ6evQoFRISQpmYmNCynerq6rRstaysLDVz5kzq+vXrlLKyMnX37l36p5GCggJqz549lIODA6WlpUXNmjWL+ueff4RiqyCkp6dTly9fpk6dOsX2I24MDQ2pqqoqiqIoqmvXrlRaWhpVVlYm1s8Wt7i7u3N8r7Z36urqqGfPnlExMTFUdHQ0/SMt6OjotPp9SvgywnpmtkcEuTeN88aW5pStzStNTU2p6upqtrZ3797R0uDBwcFsPyNHjqR0dXWpsWPHUgwGg3J1daUWLFhA9evXj1JTU6P+/PNPqlevXhRFUVRJSQmlq6vL9XXo6upStbW1FEV9kizPz8+nampqpPI7ur3Alxobt+Fc4uTz1YLGXA5hoaWlhaKiIg4pZn19fZSUlLCN26jG1giLxYK2tnabLRaloqJCF8sUBCsrK0ydOhWenp4cISuijGkWVly1gYEBXr58CVVVVWhoaIDFYqGyspIjhFOQpHRh3esvsXTpUoSGhgIATp8+zVd4Ci+rbNevX+eoLD527FgA7KIejXlncXFxrYp6VFZWIiIiArt27UJhYSH09fVRW1uL33//HS4uLjxfi6CIo3Ayt/zwww8YPHgwPD09sXnzZuzfvx8KCgoYNGgQTp48KVZbvsTUqVMRGRkJJycnjpydz+Vg2wPR0dHw9vYGg8FAcXExnazdtWtXPH/+XNLmARCP2md7Z+zYsbh+/bqkzZBKevXqhZSUFLGPu2fPHly7dg2rVq2ihYC2b9+OsWPHYtKkSfR5jbtCpqammDp1KlRUVBASEgJFRUXIysqivLwcnTp1grq6Os6fPw97e3tER0cjOTmZ69xXd3d3uLu7w9fXF4GBgYiJiYGioiLU1dXJ50ZE8C09zSt1dXV48OAB8vLyBKo03xKKiopYt24d/f9NmzZhzZo1bOesWrWK7/6NjIyQkpICDQ0Nuq2srAw9e/Zkq6libm6O+/fvw8jIiG7LycnBoEGDkJWVxff4jbBYLERFRWHIkCFSLV/aHNra2igqKmpzyeeNNM0V0tTUhLa2Ng4fPoyAgAA6PCg1NRXjx4/nO1xo69atWLlypTDNbpamDhq/YQXCEs1oKupx+PBhjBkzBk+fPuUQ9aitrUVkZCROnz6NmJgYjBkzBlOnToWLiwvk5OTw999/w9fXVyy1iT5HS0sLcXFxbCES0kJ0dDSqq6vh7OwsdeG8rUnDfi4H2x6wtbXFokWLMHPmTHpBbvfu3SgvL0dwcLCkzQPwSUJZFGqfBIIk4Wbe0fR5pa2tDU1NTXz48AG5ublwcnJChw4dEBUVRQtuCWMOxmQycfLkSVRXV8Pf319oc2ICOzw7O/X19Th9+jQSExM5khdbWol7/PgxJk+eDF1dXbx48QJVVVW4desWDh06hIiICP6tb0JLOQONMBgMHD16lO/+58+fj5ycHPz6668wNzdHRkYGli5dCgMDAzpvAfiktnP79m1s2bKFPm/NmjVwcnLCxo0b+R6/KeKKBy4qKsK///7LoRbi7+/PV3/BwcFQV1dHYGCgkCzknfr6ejre9vPr+tIK/Pr163H//n1s2rQJLi4umDVrFvbu3YvRo0dj0aJFyMjIwPbt27FgwQL88MMPor4UgXBxcUFNTQ2srKzw559/tijrLOzV9ZY+u42iHr///jsKCgrQrVs3jiTWhw8fon///pg6dSo8PDyafSh4e3vjzJkzQrWZG8RROJnQ9lFVVUVlZSVbbS4WiwUDAwOpKTzZ0qRQGovSShuRkZHNPlsEmXu0FxITE3H//n2Oe9N0kZoXRKlotmPHDqxfvx4WFhbw9/fHunXroKamBg0NDXTt2hVr1qyBnZ2d1C0eEVqGZ2fHx8cHycnJGDduHFvyItDySpywKs1LkpqaGixevBgnT55EXV0dOnToAH9/f+zcuZNNGYrJZGLbtm04fvw4cnJyYGpqimnTpiEoKEhoSbgeHh6YN28enJychNJfc0RERCAgIAC9e/fG48eP0a9fPzx+/BjDhg3juxjWmzdvMHLkSFRWVkJbW5vtmLi09ufMmYPHjx9j9uzZWLZsGXbu3Il9+/Zh8uTJX/zSZbFY2LlzJ1s9GltbW5SVlSE3NxcmJiaYPn06fHx8eLJJEjKUtbW1iIiIQFZWFjZs2NDirqewV9e/FKb3ufz569ev6d9dXFzYwkObIszixPwgrsLJ3NC0vkVTGmtCuLm5YdasWVLxoP5c9CM5ORkxMTHIyclpl8pfVlZWiIqKgqGhIfr164etW7dCR0cHo0ePlsiOJEF4rF69GqdOnYKvry92795Nzxc8PDzokOGvlT179mDt2rVwcXHBxYsXMWnSJFy7dg2urq44ceIEX32KUtHM0NAQN2/exMKFC/Ho0SN8+PCB/k7t0aMHcnNzoaOjg0uXLqFHjx5c9dmcAEJztMfwXWmAZ2dHTU0N2dnZPMnrCqvSPK+8efMGFEWhS5cuLU6SeIWiKDrWWlh98oqvry8uXboER0dHjloNwvpDsbKywu7du+Hs7Ew7qOfPn8fff/+NAwcO8NWnjY0NBgwYAA8PD454cHFp7TfKRerp6dG5NZmZmZgyZQoSEhLEYsPnSFqGUlyhc0Dzzs6IESOwYcMGDB48GHl5eTA0NMS9e/cQEhLCFg7YUsicNBQnlqbCyT///DPOnDmDhQsX0rHp+/btg7u7O7S1tREaGooJEybgl19+EatdzfHjjz/iyZMnWLp0Kfz8/FBeXo6MjAy4uroiMTFR0uYJnWPHjsHAwADOzs64dOkSfH19UV9fj19++UWiO94EwTE2NkZ0dDS6dOlChwmnpKQgMDCQ70Lc7YXOnTvj/Pnz+Oabb+h7c+/ePfz2228IDw/nq09RKpqZmZnh+fPn6NatG16+fAlnZ2c4Ozvj4MGDePbsGaytrbFs2TJcvnyZ63pCrYXsNqU9hu9KAzw7O/3798fFixd50kl3dHTEkiVL4ObmRjs73Faa55b58+dj3759AD7JBbq6uiItLQ0MBgNmZmaIjIyU6qrVvCCOOPem4UZNxRma1lbiFTU1NZSXl0s0Z0dHRwf5+fmQk5ODiYkJkpKSoKKiAk1NzWbDq06fPs1Vv4KsQktChrKgoAD6+voAWhcaEEeMflNRD1VVVdjZ2cHb2xvLly8Xe90kfpF04eSm9OjRA1FRUdDT06PbCgoKMHz4cKSmpiItLQ3Dhg0TaQFebvlc9KNRVKa1um3tibq6Onz8+JHE6bcDmn6PGRgYIC0tDUpKSlBTU/vqZaibivY0FuFWUFAQSMxHT08PmZmZUFRUhLm5OR48eAA1NTXo6enxfb/j4uIAfIpsiYuLQ0pKCg4dOoTvv/8eNjY2GDRoEAYOHIhZs2YhKSkJNjY2QhXCIogOruKqmk74xo0bhzFjxuD7779ne5gCLU/49uzZAxcXFxw4cAA1NTVwc3OjK80Li5MnT9LOzpIlS+Do6IjHjx8DAIKCgrBkyRJcunRJaONJEnF4/ubm5nj9+jUsLS3RvXt3/Pnnn9DU1OQIXeQFHx8fXLx4Ee7u7kK0lDfs7Oxw69YtjBs3DiNGjICfnx+UlJTQu3fvZs8/dOgQ/TuLxUJcXBwMDAxgbGyMnJwc5Ofnw8HBQSBnR1ZWlq4Vo66ujoKCAnoHVVRYWlrSOyyNu4Ofr3sIM0a/tfwvNTU15OXlwcjICAUFBbh8+TKOHj2Kd+/eYdKkSfD19cXEiRPRoUMHodgiCtTU1GBvby9pMwB8utefh8zKysqiqKgIwCe1LWmZfHXo0AENDQ0AQO9QFxQUQEtLS5JmiYzZs2fD29sbw4cPB4PBgIKCQpsTmiE0j42NDWJjYzFkyBAMHDgQixcvhoqKSrtZZBUEKysrPH36FLa2trC1tcWWLVugrq7OUXeRFwYPHowLFy7A19cXbm5uGDt2LBQVFTF48GC++5w6dSoAICMjg25rfLY/ePCArWiomZkZ+vTpw9c4rS2itsfwXWmAq52dlqo+s3X0BYlVUVeabxoeY2BggNevX0NZWZke28LCQmoSQIWBsJP9PufatWtQVVXFkCFDEBsbC39/f1RXV+P333+Hl5cXX306OTkhNjYW3bt358hraK14pTCpqKgAi8WCpqYmqqurERoaiqqqKixevPiLu5Xz5s1Dz5492eQl9+7di5SUFDaRCl5pqzKU3EpPx8XFtZr/1ZKox6BBg2BtbY3du3cjKysLbm5umDlzJoYOHSriK+MdcRRO5paFCxciPj4eS5YsgbGxMXJzc/Hrr7/C3t4ee/bswf/+9z8sX76cXgySJJ+LfkRFRWH16tUYNGgQVq9eLWnzhM6GDRtw7tw5lJSUwN3dHV5eXlL5eSbwTmO4qoWFBfLy8rBmzRpUVVVh3bp1LS6mfS0kJCRAQUEBtra2eP78ORYuXIiqqips374dI0aMELh/JpOJU6dOoaqqSmiKZhs2bEBeXh5iYmJQWlqKsrIyUBQFeXl59OnTB69evcKlS5f4+vv9fE5dWFhIF9qOiooS2HYCJ2KTnhY1nTp1wp07d8BisTBlyhRkZGTQK2YNDQ0thilxA5PJRHBwMNasWdPq6jKTyURAQAAOHTok0lXoPXv2YM2aNRg7dqzQkv3EwefJ502ZNm2aGC3hD3V1dZSWlnLUWtLW1hZayE1bkqFsKj3dNG/s8/937dq11fyv5kQ9PDw8oK+vj7NnzyItLQ2enp4wNTXFkSNH4ODgwLbjJg1Ik4IVk8nEvn37cOHCBTpccfLkyZg3bx7k5ORQXV0NFosl1MUmfmlO9CMgIABBQUFSIaAgKlJSUnDu3DmcO3cO1dXV8PDwwK+//ippswgEwv9HW1sbBQUFAIALFy6gsrISWVlZ2LlzJw4ePAgXFxeh7kCfOHECT548wa5du4TWJ+H/EIuzk5GRgZCQkGblqoWlwmVubs42wQoLC8O3334L4NP24+zZs5GUlMR3/zo6OigoKPjiA9jY2Bhv374VaWiCKJL9muP9+/d48+YNx3smaeUrQZg2bRrmzJnDdg1xcXE4dOgQjh071upr+/TpgwULFtCqKiNGjED//v1x48YN+rPVmFgv7QmpLSl2fQ63f5+HDh1CbGws1q1bBxMTE2RlZWHz5s1wcHDA0qVLuc7/OnHiBE6fPo2HDx9i3LhxmDp1KkaPHk3/3VVVVcHAwIDjM0kgtEUePnyI1atXIyoqisg6twOio6ObnecIUuOvvZCeno7k5GSOe8Nv2FZTYZtGhPn8tbS0xG+//QYnJyeoqanhyJEj0NTUxPz585GYmCj0hUgWiwUtLS2SAyQixOLs2NnZwdbWVmIqXNnZ2aiqquJaIrA5goODIS8vj5UrV7aaYP/HH38gMTERwcHBHKFawkIUyX6fc+LECSxYsABKSkpseTrSoHwlCE0n2400NDRAX18fJSUlrb720aNHcHd3h7y8PIyNjREbGwtDQ0NcuHAB/fv3B/DpC0tbW5snEYeKigrs3r272YekqML7mirIPHjwAGFhYVi0aBHtqOzduxc+Pj5Yvnw5V/0ZGhoiPT2dbUezUV5eR0cH58+fh6WlJQYPHoyAgABoampi0aJFHEnyY8aMgZ+fHyZPnswm6d6UK1euYMKECXxc9ddBo5xzREQEiouLpV7OOSMjA0lJSUKbBEk7jx8/xrlz5xAeHg4ZGRl4enrCy8uL7/h/gnSwaNEinDt3DsOGDeN4Zn7tdXa2bduGkJAQ2NjYcNybL9W3a4mmghCN8PP8bYkbN27Aw8MDTCYTTCYTLBYLysrK+PHHH5GYmChQjcjPQ8Bra2tx5swZnDx5EqmpqYKaTmgGsTg76urqKCsrk4gKV2pqKqysrAQe29LSEhkZGVBUVIS+vj7bH1jT1W95eXkwmUwwGAyOMJ+6ujqBbGhkwIABOHjwIGxtbTF69GgMGjQI6urq2LNnD9LS0oQyhqGhIY4fP45Ro0YJpT9pwcjICCkpKdDQ0KDbysrK0LNnT65qPtXX1yM+Ph75+fkIDAxEfHw8zM3N6eM5OTkYNGgQsrKyuLbJ2dkZDQ0NcHd35xCAEEd4X/fu3REVFUWrswFAfn4+RowYwfUXr6mpKS5cuAA7Ozu67fHjx3Bzc8OBAweEnv9FaJmgoCD8999/bULOedOmTdiyZQtsbGw4JLv5nQRJM126dEFDQwM8PDzg7e1NL5IQ2j6amppITk6GkZGRpE2ROnR1dREVFYWePXsKrU9zc3Pcv3+f7X7z8/xtjb59+8LR0REJCQmIj4/H9OnTYWZmhp07d9LlGvjZtWs6NwQAJSUl2NraIjQ0FAMGDBCK7QR2hFPl8gtIUoXLyckJiYmJAql+AMDhw4e5Ok9YzkZr7Nmzh/4j+fXXX+lkP2EXo+JGmKKt4erqimnTpuHXX3+lk+GXLl0KNzc3rl4vLy9PJyQ+e/YM3t7eHIn1vDoocXFxKCkpkZgqU3FxMUd4ZlP1Lm4IDg6Gk5MT3N3dYWJiguzsbFy4cAGhoaEYN24cfd7gwYM5dgZJsTXhcvLkSVrOuRFzc3NkZmZK0Krm2bVrF548eQIrKytJmyIWTpw4AQcHB0mbQRAB+vr6AqmVtmeUlZVhYWEh1D79/f3h7u4u8PO3NTIzM7Fr1y7MmDGDFnTJyMhAXV0dXr9+zXetRRaLJTQbCdzB884OPxWvCwsLMXDgQKiqqopMhUteXr7ZD15DQwNkZWWFtrPCYrFQUFDwRYWlrKws5ObmYuDAgQKPKQkOHz6MZ8+eYf369VBXVxe4PyaTCUtLS6SmpkpUQrimpoaubF1XV4cOHTrA398fO3fubDFsqiWaS6yfNm0agoKCOKR/W2PkyJHYvXu3UFe9eGHx4sWIjo7G0qVLaUdl165dGDp0KHbv3s11PykpKbhw4QLy8/NhYGAAd3d3+ppqamqQlpbWbP4XKbYmXMzNzfHff/9BU1OTzosqKCiAg4MDW5FWaaBnz56Ii4uDmpqapE0RG+0xF/JrpbEuC/ApHPjy5csIDAzkKMvxNb63TUO1IiMjERUVhZUrV3LMAflVqxTW87c1xFEjkiAeeHZ2mguRyMzMxMSJE1sMkRgyZAiUlJQwadIkjpwdYXnhLi4uqK6uxvbt2+ltTYqiMGDAAFy/fh06OjowMzPju/+SkhLMmzcPly9fhoKCAqqrqxEZGYm4uDhs27aNPu/t27fw9vZGRkYGamtrUVVVhfPnzyMyMrJVNbIv0fRLtTUE+VJt6jBSFEWH4zWu+gsajtejRw/ExMRAW1ubbxuFBUVRKC4uho6ODt+rM4KwZcsW+vfCwkKEh4djypQpHA9JcSS2Ns3xaHRUPDw8MGfOHKEoYh09ehSLFy9Gp06d6L//iooKMBgM/Pjjj62+liT28k5bknOOj49HaGgopk6dyjEJao8TxPaaC/m1wk0Nna/1vf08VKs5JKFWyQvJyclwcXFBr1698M8//8DIyAiFhYUYP3485s2bx3f0S0uL8x06dICRkRHc3Nywdu1anhdgCS3Ds7PDT8VrFRUVlJeXC83bbonLly9jzZo18PX1xY8//gh5eXkYGBggMTFRYLEANzc3WFtbY/Xq1TA1NUV5eTnKyspgZ2fH9kU2YsQIuLu7Y8GCBfT9aRRHEKRIpDi+VLkNc+HXafzll19w8eJFBAYGwsjIiO2PXZQTm0b5XaD12jDcrDA9fPiQLh7ZmgP6pesJCAj44ljSntj6ww8/4LfffgPQeija5cuXcfbsWQwbNoxu4+b6AXxRIY/ASVuScz548CACAwOhqqrKkbPTHieI7TUXkkAQB8J6/nIDRVF4+/Yt9PT0MHfuXERGRsLJyQnDhg1DSUkJjh49isDAQAQFBfHc9549e3D16lUsX74cxsbGyM7Oxs6dOzF69Gj06NEDGzZsgJWVFY4cOSLwdRA+wbOzw0+IhIeHB5YuXSqWlbqPHz9i27ZtCA8Px8aNG7FgwQI8ffpUYGdHW1sbhYWFHJK5nzt5TRVCGs+jKApaWlpCUQgRNwUFBfRqf9MEdn5oyWET9cSmacHZllabWlph+tw5GjFiBJ043ShtDoBtEtleJ2qfs3XrVjpJs7VQtBMnTuDZs2dQVFQUl2mENoKmpiYuXrwoFlVOacDQ0BBZWVkiX/gjSIbKykrcuHGDfmaOHTtWKupZSQMsFgsJCQnIz8+HoaEh+vfvz7NwVK9evZCSkgJANPOJz5/3Xbt2xatXr2BnZ4dz586ha9euAD79Hb98+RLDhg3jStjocywsLDjkq9+9e4c+ffogPT0dBQUF6NOnDwoLC/m6DgInPH/jTps2DZ6enti0aRMoisLTp0+xevVqzJgxo8XXdOjQAWPGjIGTkxOH0yHspOMOHTpg/fr1mDZtGpYuXYoPHz4IRQVOX18fL1++ZJOvTkpKYlPiAj6p7cTHx7M5dvfv329zCbiZmZnw9/fHgwcPoKWlhdLSUtjb2+Ovv/7ie2cnPT1dyFZyR6OjA/CeGGhsbMzhHBkbG7OdI4yt+KioKJw9e5Z+SHp5eUm9QESjowO0nk9ja2uLuXPnYsmSJRxCIY27afX19Xj9+jVKS0vZ7jWpLs8fbUXOWU1NjV6p/RrYsGEDgoKChJYLSZAe7ty5gylTpqBXr1507uP8+fNx7tw5jBw5UtLmSZTExERMnjwZ9fX1MDY2Rk5ODuTl5REREYG+ffty3U+jowOIZj7R9HnPYDDAYrFgamoKiqIwbNgwOhqFyWTC0NCQb1Gh9+/fo7S0lM3ZKS0txfv37wF8Wlz/8OGD4BdEoOFLoIDXEInWVn3bStJxREQEli5divnz52Pz5s3YuHEj9uzZgx07drApeUVHR2PKlCmYPHkyTpw4gdmzZyM8PBxnzpzBkCFDhGJLS/GeAIQmbz1s2DDY29sjODgYHTt2RG1tLUJCQhAXF4eYmBiB+q6pqeGY1JqamgpqMl/ExMRATk6Or13HcePG4dq1axztEydORGRkJNf97NixA6GhoZg5cyb9kBRki1xS3Lt3D6dPn0ZeXh4MDQ3h4+ODoUOHIjIyErNmzUJxcTHb+Y1OYnR0NLy9vcFgMOg8qpKSEnTt2hXPnz+X0NW0XdqSnPO+ffsQGxuLn376qUVHuD3RtDSBsHIhCdKBtbU1tm/fDldXV7otMjISQUFBePnypQQtkzzffPMNZsyYgYULF9Jte/fuxeHDh/HkyRO++iwrK4OioiKUlJTAZDJx6tQpyMnJwcfHRyh5uIcOHcLOnTtRXFwMa2tr5OXlQUFBAWZmZjAzM0NeXh7Gjh2LSZMm0a/h9jtrw4YNOHr0KL7//nsYGxsjNzcXR44cwfTp07Fu3TpcvnwZv/76K6KiogS+DsInxFJnR1zk5uYiNDQU9+/fR3l5OTQ0NDB48GAEBgZyrMbzQ0JCAo4dO4asrCwYGRkhICCgWbW17OxsnD59mj7P19eXYwdIED7PrSkoKMD27dvh7OzMtYzvl1BVVUVZWRlbuEV9fT00NTXZdkp4ITk5Gf7+/khKSqLbGAwGFBQUUFNTI7DN3ODo6IgtW7bAwcEB27Ztw+7duyEvL4+5c+fynAyvqqqKd+/ecbQ3DXPkBkNDQ0RFRbHt/gmyRc4rDx48YAvJ44eDBw9izZo1+P7772FmZoasrCwcOXIEGzZsQHBwMLZu3QovL69mQ9lsbW2xaNEizJw5E+rq6pg9ezaOHDmC6upqfPz4Ebdu3UJqaioCAwMFsvFrQUtLC3FxcW1iN7mlXXdpT1zml9byIgUR0CFIHk1NTRQVFbE9MxsaGqCrq9smQ9iFiZqaGsrKyjiKeWtqajb7DOUGe3t7/PHHH7C1tcXy5ctx8+ZNyMvLY8iQIfj1118FttnQ0BAjR46ErKws/vzzT47jnztUvH5nXblyBRcuXKBziidPnkyKZYsSike6du1KrV27lkpJSeH1pSIlMzOT0tHRofr160cFBwdTBw4coNavX0/Z2dlROjo6VEZGhqRNFCnv3r2junTpIrT+3NzcqOvXr7O13bhxg5o0aRLffQ4aNIhav349VVtbS6mrq1O1tbVUUFAQdeDAAUHN5RotLS2KyWRSFEVR5ubm1MuXL6nc3FzK2Nj4i68tLy+nlixZQuno6FAqKioUAEpFRYVSUVGhZs2aRc2aNYsaPXo0NXDgQJ5sMjU1paqrq9na3r17R5mamvLUD7907tyZsrCwoFavXk09e/aMrz66du1KJSUlsbUlJydTXbp0ofT19an6+voWX6uiokKxWCyKoihKQUGBmjp1KpWYmEgxGAyKoigqLy+PsrKy4suur5EePXpQFRUVkjaDQPiqWLt2LbVmzRrq48ePFEVR1MePH6m1a9dS69atk7BlkmfWrFnUH3/8wdZ26NAhavbs2Xz3qa6uTj83DAwMqJycHKq8vJzS19cXyNZGTExMqEePHrG1/fvvv1zNFQjSB887O9HR0Th37hzOnz8PLS0teHl5wcvLS+KriLNmzUJdXV2z8s4BAQGQlZXlujBoI03lgVsjIyODq/NEWRTx9evX+Pbbb1FaWiqU/nx9fXHhwgUMGjSIDq2Ki4uDu7s7mxwiL9ekrq6O0tJSyMrK0kp1dXV1sLCwQE5OjlDs/hJaWlrIz89HWloaJk2ahJcvX4KiKKipqX1xhcnT0xPV1dXQ1tbG2bNnQVEUTExMYGlpiYEDB4LBYEBXVxceHh48yWvv2bMH165dw6pVq2hllu3bt/O9Rc4P8fHxCAsLQ3h4OPT19eHr6wsfHx+ud0R1dHSQk5PDVkOptrYWJiYm2LJlC9LS0rB69epm66lYWVkhKioKhoaGkJeXx8WLF2FkZIR+/frROVatqT0S2Pna5JylHVdXV1y+fBkAMGrUqBZDbIRVc44gGSwtLZGRkQF5eXk6FLeuro4jkf7Vq1cSslByODk5ISYmBqampnTOTnZ2NoYOHcq2u8vL34COjg4yMjLw/PlzzJ49G0+ePAGTyYSGhgbfu0VNOXr0KJYsWYJBgwahuLgYRUVFKCwsxOLFi/Hzzz8L1HdtbS3Wr1+P8PBwlJaW4t27dySCQcTwHcbGYrEQFRWF8PBwXLx4EQYGBnj69KmQzeOeLl264Pbt2+jSpQvHsbS0NIwePZpnhQ5u5YG5DT8QVn7S5w/M2tpaPHnyBD/99BPWrl0rlDFEUeixqZJfr1698Ndff0FbWxu9e/cW20TW19eXzhlycnJCcHAwnj9/Djc3ty8+hLS1tZGeng4VFRWoq6vj8uXL6NmzJxwdHfHs2TO+beJGQENcYT0sFgt37tzBsmXLkJqaCgcHB8ycORNTp05tVbbYx8cHMjIy2Lp1K0xMTJCVlYU1a9agvr4e58+fbzVP4dixYzAwMICzszMMDQ1RXl6OhoYGKCgo4P3793j79i3GjRuH1NRUkV9/e+Brk3OWdk6fPk0LQ7RWa02Yld8J4ic6Opqr874W5cGmcFtjkJe/gR9++AEPHjxAVVUV5s6di8WLF+Pff//FjBkz2ELlBeHHH3/EwYMHYWlpCSMjIxgaGuLKlSsC59MGBASgvr4eK1aswJAhQ1BeXo78/HwMHz4cL168EIrtBHYEytnJyMjA2bNncfr0aeTn56OoqEiYtvGEqqoqKisrm101Y7FYUFNT4zvXRNr4/IujU6dOsLGxQbdu3SRkEXds3boV3bt3h5ubGw4dOoQlS5ZAVlYWc+bMEXilhFs+fPiA48ePQ15eHt999x3k5eVx9+5d5Ofnw8fHp9XX6unpITw8HEOHDoW5uTl+//13KCsrY/z48fj777/Zzm2LK+hPnz5FWFgYzpw5A21tbfj5+cHU1BT79++HoqIirl692uJrKyoqsGDBAkRERKChoQHy8vLw8PDA77//3uoq2+cLBXv37sUff/yBJUuWIDAwEMePH8fmzZvx/fffY86cOUK71vbM1ybnTCAQvj4oisLt27chLy+PESNGAAAeP36MyspK+v+CIqp8Wl1dXWRnZ6NDhw6tljIhCA+enZ3s7GycO3cOZ8+exZs3b+Dm5gYvLy84OTm1uPJbX1+P/fv3IzY2lkOFS1jqQC0li3N7vDlaK0DZFG7D2KR9Anz69GmuzhOWfG1mZiaqq6vRs2dPofTHDzExMZCVlYWDg8MXz3V3d0dCQgKys7MRGBiI/fv3g8FgQEZGBnp6evR5bW0FPSQkBGFhYairq4OPjw/8/PzQvXt3+vjHjx+hpaXFIWPcCJPJRHBwMFavXg0FBQWUlJRAW1ubZ8n3d+/eobq6GleuXMHZs2eRm5sLc3NzBAQEwNvbW6Br/Jro3LkzUlNTSV0jAkHEcCsIJMoQdmmF2zQAXoWBGmlOjU1WVha+vr58q7F9Xig7LCwMHh4ekJeXp8+pq6tDVFQU10XYm6Nbt274559/YGxsTDs7JIJBtPBcZ6dXr16YOHEi1q5dC2dnZ7YPQUssXLgQjx8/xuzZs7Fs2TLs3LkT+/btw+TJk/kyujnev3/f4s4GRVF8qX01V2PlcxgMBleyycKcAE+bNg1z5sxhc57i4uJw6NAhgSrOHzp06IvnMBgMoTk7klAfEkSN7fz58/TvO3fuhI2NDWpra+Hv78+ml88NlpaWXH0hiyO+Oy8vD4cOHWpRGr1Dhw64f/9+i6+XlZXFgQMHEBwcDBkZGY48kYyMDISEhCAxMZHDYXr16hVu376N2bNnIzs7GywWi74vDAaDlmyNi4uT+sUCaSEoKAgzZsz4auScCQRJYWRkJGkTpJbXr1+LtH8XFxdajW3lypW0GtujR4/4VmMzMDCgfzcyMsKQIUMQGxuLIUOG0NFDcXFxWL58OdtiOK/fq4sXL8a4ceOwcuVKMJlMXLp0CZs3byb5OiKE552dDx8+8LxiqKenh6SkJOjp6UFNTQ2VlZXIzMzElClTkJCQwFNfLcFNvGx7CevQ0tJCUVERh4yjvr4+SkpKJGgZJ9I0qQc+3bvi4mLIyMigc+fOuHXrFpSVlWFvb4/s7Gyu+2EymVBWVkZlZSVfhcXaW3x3cHAw5OXlsXLlSo4dHTs7O9ja2sLDw4MthwT4dH0WFhZYuXIl/Pz8oKenJxQ576+Zr03OmUAgfH1oaGigrKwMDAYDhoaGePToETp16oTu3bsLrWSDKPNpw8PDOepVkggG0cHVzk54eDimTJkCALhw4UKL57W04s9isaClpQXgUzhZeXk5jIyMhJqI1VYmhcJAUVER7969g4aGBt327t07rnbZeEXQAqC8KuCJg4aGBqSlpUFBQQHdunUDRVGorKz84usqKiqwe/dueodCQUEBTk5O6NixI89KSpL+vLamCtUUbq/r1KlTyMjIwLZt26Cvr8/Wd1FRERISElp8cFRWVsLFxQXl5eVgsVjIz89n+7ylp6fzXan6a6RRwY5AIIiXoqIi/PvvvxzPTH9/fwlaJR3U19fj9evXHPdm6NChfPUnJyeHmpoaPH/+HHp6ejAyMgKTycT79++FZTKio6ObLZQtCEwmEyNGjMDt27fpeTVB9HDl7Bw7dox+U1oKdWotvMnOzg63bt3CuHHjMGLECPj5+UFJSQm9e/fm0+zmbbxz5w5OnTrFcczPzw+jRo3iWe2GW8nQ4uJiugpwazsZwtq9cHV1xbRp0/Drr7/C3NwcGRkZWLp0Kdzc3ITSPyC8AqCSntR/zpgxY+Dp6YnS0lJakCA1NRX6+vpffK23tzcaGhrg7u4OJSUldOzYEQ8fPsTQoUNx6tQptved11C/yMjIZnPajh49ylM/3OLn5yfU/lpzas+cOYOLFy/C3d292eOBgYEwNTWlQ0Y/Dw3R09MTmpIhgSBuSF7H10FERAQCAgLQu3dvPH78GP369cPjx48xbNiwr97ZiY6Ohre3NxgMBoqLi2lp7q5du+L58+d89enj44Phw4fTamwA8OTJE6EVcG9aKNvW1hZZWVnw9PTEhg0bBCreLisri+zsbDQ0NLCVaiCIFoHU2LiloqICLBYLmpqaqK6uRmhoKKqqqhAYGCi0mNf+/fvj+PHj6NGjB8ex1NRU+Pv749GjRzz1ya1kaJcuXTB48GAArYcnCWviX1NTg8WLF+PkyZOoq6tDhw4d4O/vj507d7LVwBEEBwcHjBo1CitWrICBgQHy8/Oxbt06dOnShW9VrPr6emzduhVhYWFsKyUrVqwQ28q9IGpsqqqqKCkpoW0dPnx4s+cxGAyehDdWr16NU6dOwdfXF7t376bfWw8PD4SGhnJ/cVJKYWEhBg4cCFVVVY58ntu3b9P1KZSVlVFXV8f2nfA11qQgtC9EIeNPkD6srKywe/duODs703Xkzp8/j7///hsHDhyQtHkSxdbWFosWLcLMmTPpe7N7926Ul5cjODiYrz5FrcZmaWmJCxcusC3Kp6SkwM3NDWlpaQL1vXfvXty5cwcrV66EkZER20IpyasUDTw7O71790ZycjJHu62tbYt1dsLCwpqdSJ45c0ZoMYpfiukXNOa/pVylwsJCNiWuRiWqz3nx4gWsra35Hr85KIqiV0n4VR9pCVEUAF28eDEeP36MdevWwczMDJmZmdi0aRP69u2L3bt3C9V+UTBy5Ejs3r1b6OpxxsbGiI6ORpcuXWjpyZSUFAQGBuLOnTtCHasRYSvvfR7i15Ta2looKSlh0qRJHDk706ZNE8sCAYFAIIiSpoqvTfNqSb4he2mQxvvBYrFgYGCAwsJCSZvXLK0VyhY0N5rkVYofnp0dFRUVjno1TCYTOjo6Lf5BtyT7LMwvAR0dHSQnJzcbjpSfn4/evXsL9AEdNWoUrl27xrYDkZGRgdGjR7OtPvft2xdRUVFQV1en2x4/fgxXV1e+nQQAKCgooK+tNUlsYa0KiKIAqJGREVJSUthyjcrKytCrVy+uZb4FpaKiAhs2bGg2ZOxLanmLFy/GqVOnMGLECLZrADiLofGiHNY00dLAwABpaWlQUlKCmpqaUCpBN0dLu1JN4WWHytnZmS3ErykLFy5EeXk55OS+HDUryPtDILQFSF5H+8TGxgbnz5+HpaUlBg8ejICAAGhqamLRokUCPfvbA1ZWVoiKioKhoSH69euHrVu3QkdHB6NHj0ZxcTFffebk5OCHH36gnxVNEYbD0Fqh7DNnzgjcP0G8cC093Ziz8vHjR4wePZrtWE5ODr799luO18TFxQH4lDAbHx/P9sWekZEhtJCrRvvWrVvXbNxzSEgIh828YmtrC1dXV0RGRkJeXh4vXrzAmDFjsHbtWrbzZs6ciZEjR+Kff/6Bqqoq7t27By8vLxw5ckSg8S0tLWknsyVJbGGuCsyZMwcxMTFwc3PD4sWLMWTIELoAKL/Iysriw4cPbG0fPnzguR6LIMyePRvV1dXYtGkTPDw8EBERgR07dsDFxeWLr3337h0+fvyIGzdu0G2N+UtXrlyhJy/GxsY8TcxtbGxoecuBAwdi8eLFUFFRQefOnXm/QC6JiooSan9xcXFsIX5NuXLlChISEtgcwM/rGTRy584dNDQ0oFevXnj69CmuXr3K9ftDIEg7JK+j/bJ161YUFBTA0tIS27Ztg7+/P6qrq/H7779L2jSJs2LFCiQlJcHQ0BBr166Fm5sb6uvr8csvv/Dd5/fffw9jY2Pcu3cP9vb2SEhIwMaNG+mUAkHZv38/FixYAEtLS7ZC2fv37xdK/wTxwvXOzvHjx0FRFObNm8cWf8pgMKCrq4sRI0ZwTHQaJ2tZWVlsCl4MBgN6enpYvnw5Jk2aJIzrQFZWFgYOHAh9fX24urpCX18fBQUFiIyMREFBAeLi4nhSEWuOH374ARkZGVi9ejUmT56M0NBQeHl5cZy3Y8cOREREYOnSpVi8eDHOnTvXYg2TtoIwCoCuX78eFy5cwI8//ghTU1NkZWVh586dmDRpEtdx7YKira2N9PR0qKio0CFjJSUlcHR0xLNnz3jqa8OGDXj//j2Cg4PRsWNH1NbWIiQkBJ06deJwgluj0TGysLBAXl4e1qxZg6qqKqxbt06oIh5fQhDlvdZC/KZOnYrIyEg4OTnROTtPnz6Fra0tDh48yPbeb9++HYGBgejQoQO2bt2KDx8+8P3+EAjSBsnrIBA+Feb8+PEjz/XpmqKpqYn8/Hx06NCBfpZXV1ejT58+ePPmjdBsZbFYfBfKJkgPPIexpaen87ziPGvWLK4KVgpKcXExQkNDERUVhdLSUmhpaWHEiBFYsmQJR3E9fpkzZw5OnTqF8PDwVlebN2/ejN27d+PmzZv45ptvhDJ2W4eiKBw+fBhnz56lBQq8vLwwc+ZMsX2J6OnpITMzE4qKijA3N8eDBw+gpqbWYn2Xz7l37x4tRXn79m1cu3aNLRmyvr4e+vr6HNvq0gy/yntNK2QXFhbSEvVNc9iAT/ekJT5Pyhb0/SEQpBmS10EgCAcjIyO8fPkSysrKsLS0xM2bN6GpqQkzMzOhPCvEkX5BEB8819mJj49HfHx8s+e1lMx86NAh1NXV4cGDB8jLy4O3tzcdkiWIZ/85Ojo62Lp1q9D6a05GmsViQUZGBosXL8bixYsBfHIAPz+PoiiwWCx8++23oCgKDAYDdXV1fNsi7LookoDBYGDWrFmYNWuWxGwYPHgwLly4AF9fX7i5uWHs2LFQVFTkauv7cynKe/fuwd3dHdu3b6dDsf73v/9x5PNIO3PnzoWrqyvi4+M5lPda4/MK2WPGjMG7d+84HhDHjh37og0ZGRlISkqCmZkZli1bBgcHB3Tv3p2n94dAkHbMzc3x+vVrWFpaonv37vjzzz+hqanJkedGIBBax93dHdevX4enpyemT58OR0dHKCgoYOLEiULpv7l9gJqaGqGLQRHEA1c7O2PHjsX169cB8Ce3+/jxY0yePBm6urp48eIFqqqqcOvWLRw6dAgRERECmC9auK1yz62uu5mZGd+2tCZ93RReawmJExaLhQMHDiAiIgLFxcVITk5GTEwMcnJyeK5LIwyYTCZOnjyJ6upq+Pv7f9Hx/lyK8saNG5gyZQqYTCY8PT2RlZWF//77D2FhYRg7dqw4LkEoCEN5LycnB8bGxi22JyYm4v79+xxhcuvWrcOmTZuwZcsW2NjYcKi1TZ8+nev3h0CQdq5duwZVVVUMGTIEsbGxbHkdzYVEEwgE7oiOjkZ1dTWcnZ0hKyvLdz+Ni9xv376FhYUF27Hi4mK4urrizz//FNBagrgRS52d/v37Y+3atZg4cSI9maqtrYWFhQXy8/NFPTxBSggKCsJ///2HpUuXws/PD+Xl5cjIyICrqysSExMlbd4XaU6KMisrCz179sSaNWtgYGCAsWPHNis9Ls0IQ3mvtS3/DRs2YM2aNRg7diwuXryISZMm4dq1a3B1dcWJEyegpaWFuLg4WFlZCfnKCAQCgUDgnujoaFAUhbFjx7KJETXmpwu7hAhBPPDs7Lx48QKamprQ1dWlC4TKyckhMDCwxa14TU1NlJaWsmmsM5lM6OrqtqncBkki7LooksDAwAAvX76Eqqoq7fQCoJMLRYWwKpi3VynKrVu3onv37nBzc8OhQ4ewZMkSWnnv559/5qqP5iTpc3NzYWtrC2VlZZw/fx7ffPMN/V7fu3cPv/32G8LDw9GzZ0/ExcVBTU2t1Xo90hyiSSBwQ0xMDMzMzGBmZoaCggKsWrUKcnJy2LhxI0euG6Htc+LECXz77bfo1q2bpE2ROmJiYtC7d2+ewr7FGc6fnZ0NExMTgfshSAc8Ozt9+vRBeHg4unXrhtmzZyM9PZ1Wwzh58mSzr3F0dMSSJUvg5uZGOzuXL1/G77//LrKiie0NYddFkQRNdxAaPwcFBQVwcHAQqnrK5wirgnlFRQUWLFiAiIgINDQ0QE5ODsbGxlBWVkZtbS3buU1rL/HDjBkzMHjwYEybNk2gLXl+4EV5T15enpY8/9xOFouFFStW4Pfff0dlZSUAQFdXFzk5OVBQUICamhoqKysRHx+P0NBQTJ06Fdu2bQOTycSwYcPQoUMHWFpa0v1Jc4gmgcAN3bt3x+3bt2FiYgIvLy8oKChASUkJeXl5uHLliqTNIwiZzp07o6ysDOPHj8epU6ckbY5UISMjA1VVVSxYsACbN2/m6jXiDOdXVVWFnZ0dfH194eHhwVY7kdD24NnZaZygMJlM6Ovr4+XLl7RyUlFRUbOvSU5OhouLC3r16oW7d+/C2dkZT548wbVr19CrVy+hXEhrSHLiSPg/1q9fj/v372PTpk1wcXFBVFQUVq9ejUGDBmH16tWSNo9rGqUoXV1d0a1bN3h7e3Psajo6Ogo0RkBAAHJycpCfn4+UlBSB+hIlmZmZoCgKY8aMYVtNYzAY0NbWhpKSEgYMGICDBw/C1tYWo0ePxqBBg6Curo49e/YgLS0NBw8eRGBgIFRVVVFUVARTU1MwGAw6bppAaC80hnvW1dVBX18fOTk5kJeXb3MKjgTuaWhowL///ttsLcKvnZycHMTGxsLb21vSpnBQU1ODy5cvIywsDFFRURg5ciR8fX0xceJEtlB2QhuB4hEDAwOqqKiIioqKogYOHEhRFEXV1dVRqqqqrb6uurqaOnPmDPXzzz9Tp06doiorK3kdmm+mT59OjRw5kurZs6fYxhQ1FRUV1JkzZ6jQ0FDqzJkzVEVFhaRN+iJMJpP6+eefKWtra0pJSYnq1q0btXXrVqqhoUFsNvz+++/Uf//9x9b2+PFjau/evc2en5+fT/+em5vL9qOsrExlZ2dTubm5IrNXHPfmyZMnlKOjI6WhoUHJy8tT8vLylJycHCUvL891H/Hx8S0ee/jwIX3Pnz17Rg0fPpyys7Oj/ve//1EURVEaGhrU3bt3KYqiKCcnJyolJUWAqyEQpBczMzPqzZs31OXLl6kRI0ZQFEVRtbW1lJqammQNIwgNJpMp0mcC4RMrV66kHjx4wNb24MEDavXq1UIfq6ysjDp06BDVq1cvSlVVlfL396eio6OFPg5BdPC8s7N582b88ccfqKurw86dOzF16lRER0cjKCgICQkJrb62oKAA+fn5MDAwgL6+vkBOGj80F2rTGs1JTzdHc9LTTaGEID3dlLi4OEyYMAFWVlYwMzNDVlYWXrx4gStXrrBVqSdw0lSbv5GqqipYW1sjNzeX4/ymuSgyMjJgMBi0mljjvzIyMmAymQLZJQ5p9pbo1asXJk2aBF9fX44dKm4VBC0sLMBgMODj4wNfX1/06NGD6/E7d+6M1NRUKCoqYvHixS3W61m1ahXXfRII0sjRo0exZMkSyMjIICwsDM7Ozrh27Rp+/vlnrtU/CdJJSUkJ5s2bh8uXL0NBQQHV1dWIjIxEXFwctm3bJmnzJEptbS3Wr1+P8PBwlJaW4t27d7h16xZSU1MRGBjIV5+6urrIzs5m22X58OEDzMzMUFhYKCTLP72v4eHhOH36NNLS0uDp6QlTU1McOXIEDg4OYqkhSRAcvtTYXr58CTk5OboOx6tXr/Dx48cWq71nZmbC398fDx8+pMUK7O3t8ddffwkkxyxqpEl6uin9+/dHUFAQPD096bbw8HBs374d//77r1DGEAWWlpbw8fGBl5cXV/kgokBbWxt5eXlQUFCg2z5+/AgDAwOeC4X5+fnh0qVLcHJy4piYf0nsoCmSlmZvFAYQtH5AXFwczpw5g/DwcOjr68PX1xc+Pj6IiYlp9vwOHTrAyMgIjx49Qnx8PH766Se2QqUA2Jwvbur1EAjSTmOh3sbPdlFREVgslkQWAAnCw83NDdbW1li9ejVMTU1RXl6OsrIy2NnZffXhuAEBAaivr8eKFSswZMgQlJeXIz8/H8OHD8eLFy/46lNPTw/p6elsz4j379/D3NwcxcXFAtt84sQJnD59Gg8fPsS4ceMwdepUjB49ml4wr6qqgoGBAYeQDkE64cvZqaysxM2bN5GXlwdDQ0M4OztDTU2txfOHDRsGe3t7BAcHo2PHjqitrUVISAji4uJanAjxArc7MIImjUsLGhoaKCkpYdulYjKZ0NbWphXOpJHo6GicO3cO58+fh5aWFry8vODl5SVWyeHx48fD3t4ea9eupds2bdqE+/fvs8lMNsf8+fOxb98++v+NwgfXrl3DuHHj2M79kthBUyQtzT5//nwMGzaMzXkWBBaLhTt37mDZsmVITU2FsrIy3r9/D0NDQxgZGSE3NxcFBQXo378/MjIykJub2+zfb6PwAYHQnnj79i3Cw8Pp56eHh8cXC/gSpB9tbW0UFhZCVlaWFuABRK822hZougsjrHszdepUdOrUCb/99hsUFRXx4cMHLFmyBOXl5UJRRx0zZgz8/PwwefJkdOrUqdlzrly5ggkTJgg8FkH08OzsNIZQWVtbw9TUlKsQKlVVVZSVlUFOTo5uq6+vh6amJodcLT9wuwMjaNJ4ZGQkYmNjOQojHj16lP69vr4e+/fvb/Y8YSmlDR06FF5eXliwYAHdtm/fPpw+fRqxsbFCGUOUsFgsREVFITw8HBcvXoSBgQGePn0qlrEzMjIwbtw4VFdXw8zMDJmZmVBRUcHVq1e/uEPXWi0ZXneFPn+9JKXZnZycEBsbC2tra44dKl4lPJ8+fYqwsDCcOXMG2tra8PPzw82bN5GZmYmuXbvi6tWrAIADBw4gKSkJe/bswezZs5GUlESHwaanpyM5OZljxUyaZdUJBG6IjIyEn58fxo8fT4cgX716FSdOnICrq6ukzSMIQK9evXDu3Dn06NGD/h5PSkqCv7+/2J5v0kq3bt3wzz//wNjYmL43b9++xbhx45CamspXnyUlJfD19UVMTAx0dXVRXFwMR0dHnDp1ClpaWkK+AkKbh9ckHzs7O+rs2bNsbefOnaP69evX4mvc3Nyo69evs7XduHGDmjRpEq/DS4xVq1ZRZmZm1MqVKyklJSVq5cqVlImJCbVkyRK282bPnk3169eP+uOPPyhlZWXqjz/+oPr06UOFhIQIzZaUlBTKwsKC6ty5MzV06FCqc+fOVOfOnank5GShjSFq0tPTqW3btlE2NjaUjo6OWMduaGig7t+/T509e5aKi4v7ogjA5s2bqc2bN1OKior075s3b6Y2btxIOTg4UJ06daJ69epFURRFRUdHU6dOneLJnqFDh1IXL16kKOpTsj5FUdSlS5coJycn3i+OD/78888Wf7glODiYsrKyojp37kytWrWKev78OX1MTU2Nev/+PdWpUye6raGhgU7KVlFRoQVOtm7dSikqKlIDBgyghg0bRv8MHz5cOBdLIEiQnj170mIcjURHR1M9evSQkEUEYREeHk6ZmJhQW7dupZSVlaldu3ZRXbp0ob/bv2b27NlD2djYUGFhYZSqqip18eJFys7Ojjpw4IDAfefm5lIPHz6k8vLyhGDp/zF8+HDq3r17bG0xMTFiey4ThAvPOzvchlA1LeRYXV2NCxcuYNCgQTAxMUF2djbi4uLg7u4uFO35z+P8W0KQBGdjY2NER0ejS5cu9NZrSkoKAgMD2WoF6enpISkpCXp6erRMd2ZmJqZMmfJFAYfWePz4Mfr160f/v76+Hg8fPqRDIezt7SEvL893/+IgOzsb586dw9mzZ/HmzRu4ubnBy8sLTk5OUi0JHhAQAAA4deoUpk6dSrc/evQI1dXVWLVqFX766SeUl5cjIyMDrq6uSExM5Lp/SUuzC4M5c+bAz88PQ4YM4ThmY2ODpUuXom/fvujTpw+AT/USduzYgeTkZEycOBH37t1DeXk5dHV1ERUVJbGcLgJBlGhqaqKwsJDtu7q+vh66urpSHYJM4I6EhAQcO3YMWVlZMDIyQkBAAAYOHChps6SC8PBwHD16FFlZWTA2NkZAQIDQJKe3bduGFStWCKWvRtTV1VFeXs4WYs1isaCtrS1QJAdBMvDs7HAbQiWsQo7c0DgZ/RKCJDhraGigrKwMDAYDBgYGSEtLg5KSEtTU1NhCm3R0dJCfnw85OTmYmJggKSkJKioq0NTUbDYEiluahlAZGhoiLy+P774khZqaGiZOnAhPT084OztLvXP2OSdOnIC/vz/9fwMDA7x8+RKqqqp0rg3AXxzy+/fvcfXqVfohOX78eKiqqgrTfDZ27NiBH3/8EUDriwXcLBAwmUxYWloiNTW12foDDx8+hLu7Ozp27Ejn7NTW1uL8+fOwt7fHyJEjERMTAycnJ9y/fx8eHh50yCsvQg8EgrQzbtw49O7dGyEhIejQoQPq6uqwfv16PH369Is5gwTpJjc3F0ZGRpI2Qyr5+PGjSGvTtBRiLgjm5ua4f/8+23uak5ODQYMGISsrS6hjEUSP3JdPYefAgQOYMGECdu7cCRMTE2RlZYHBYCAyMpLtPGE4MdwiDpUmGxsbxMbGYsiQIRg4cCAWL14MFRUVdO7cme08Ozs73Lp1C+PGjcOIESPg5+cHJSWlFpXquEVXVxdHjhxB9+7d6arzzfmp0iw9XVhYCEVFRUmbwTf+/v54//493rx5Q+eTxMXFQVVVlV79KSgo4Dle+PTp0/Qul7h48+YN/fvr168F6ktWVhaKioqoqqpq9oFmb2+Pt2/fIj4+HgUFBdDX18fAgQNpRbwhQ4bQO0KysrJISEjA4MGD0alTJzan3tDQUCA7CQRJ88cff8DHxwcaGhrQ0dFBcXExvvnmG6EkVBMkS/fu3dGnTx94eXnB09MTurq6kjZJatDV1cXEiRPh7e2N0aNHC32hk8c1e67w9/eHu7s7tmzZAnNzc2RkZGDNmjWYNm2a0MciiB6+1NgECaHq3bs3kpOTeTaUF1JSUnDhwgUUFhZi7969ePHiBWpra9G3b1+++2yUjrSwsEBeXh7WrFmDqqoqrFu3js2RqaioAIvFgqamJqqrqxEaGoqqqiosXrwYxsbGfI8fGxuL9evXIysrC+np6TAxMeE4Rxorzp8+fZqr89pC8vlff/2F+fPnQ0lJCUpKSigvL8fHjx+hoaGB2tpaREVFYfXq1Rg0aBBWr17Ndb8jRozAo0ePMGbMGHh5eWH8+PHo2LGjCK9E+Pzyyy+4ePEiAgMDYWRkxLb1z4sDLiMj02w7UWYjtCdycnLo56cgzwWC9FBbW4urV6/i3LlzuHnzJvr37w8vLy+4u7tDW1tb0uZJlMzMTJw7dw7nzp1jC2EfOXKkUELYt27dipUrVwrB0v+DyWRi27ZtOH78OHJycmBqaopp06YhKCiITWyL0Dbgy9lhsVhISEigC4QOGDCgxUnK54hiu7EpJ06cwKpVq+Dj44ODBw+isrIST548wZIlS3D37l2++mQymQgODsaaNWta3YplMpkICAjAoUOHRLpl26tXL6SkpIisf2EyfPjwL57DYDCEplQnSgwNDXH8+HGMGjUKwKe/g507d3LEIQcFBfH8BV5YWIiIiAicPXsWiYmJGDt2LLy8vODm5iaCK+GkpqYGaWlpHApo3Doqn+9wNsKNA85isXDgwAGEh4ejpKQEycnJiImJQU5OTptwggkEbrl//z4MDAxgYWFBt6WnpyM/P1+qd+UJvPH+/XtcuXIF+/fvx4MHD/Dx40dJmyQ1vH37FufOncOZM2eQl5eHoqIiSZtE+Arg2dlJTEzE5MmT0dDQACMjI+Tk5EBeXh7nz5+Hra3tF1/ftCK9KOjatSuuX7+Obt260XkUDQ0N0NfXR0lJCd/96ujooKCg4IuTWGNjY7x9+5ataCWhfWBoaIisrCyRr+qkp6dj1qxZiIqKEstuxtGjR7F48WJ06tSJbUdJXDuFP/74I548eYKlS5fCz8+Pb6EHAkHasbKywv/+9z+23ZycnByMHDmS7+KKBOmisrISFy9exNmzZxEbG4uRI0fi4sWLkjZLKqAoCtHR0Th79izOnz8PIyMjPHnyhK++MjMzERwcjMTERI5FOmHVVCwqKsK///7LUUakae4uoW3As7PzzTffYMaMGVi4cCHdtnfvXhw+fJirD212dnazIVjCQk9PD7m5uZCTk6P13IVRoDE4OBjy8vJYuXJlq7tYf/zxBxITExEcHExidlugpqaG48vD1NRUghZxx+HDh3H+/PlWi4w1wuuOBJPJxO3bt3H27FlERkbC2toaXl5eWLx4sSAmc4Wenh7Onj2LYcOGCdRPcXExbty4gYKCAixfvhw5OTlgsVhffG/l5eVRWloKVVVVyMrK0gUW37x5w1Zssb0UBSZ8vaipqaGiooItzJOiKA6hG0Lb46+//sLZs2cRExODoUOHwtPTE25ubiIVmmkr3Lt3D+fOnUNERARbQfFu3brx3efAgQPRrVs3eHt7Q0lJie2YoDUVASAiIgIBAQHo3bs3rYb7+PFjDBs2DLdu3RK4f4KY4VWrWlVVlaMuSX19PaWiotLq6+rq6qhnz55RMTExVHR0NP0jbHx9fanly5dTDQ0NdM2S1atXU9OmTROo365du1JycnKUsrIy1bVrV8rS0pL+aYqcnBzFYDAoGRkZSk5OjpKXl6f//dpJSkqibG1tKRkZGfpHVlaW6tixo6RN4wo5OTkKAAWAYjAYFIPBoP8/cOBAysTEhJKTk6McHR156jcgIIDS0tKi+vXrR/38889URkaGaC6gBSwsLKja2lqB+rh58yalo6NDeXh40N8F9+7do1xcXL74Wj09Paq0tJSiKIpSVlam7t69S50/f54yMDCg7t69S/8QCG0dOzu7ZmvO9e3bV0IWEYTFyJEjqUOHDtHfZYT/o2vXrtTq1auppKQkofWpoqJCMZlMofX3Od26daNu3LhBURRFqaurUxRFUREREdScOXNENiZBdPAcj+Pl5YUjR46w1dH5888/4ePj0+JroqOj4e3tDQaDgeLiYujo6KCkpARdu3bF8+fPeffQWmHPnj347rvvoKamhg8fPkBDQwMDBw4UuJ7P4cOHuTovLS1NoHFaIycnp00ns86dOxeurq6Ij4+HgYEB8vPzsW7dOrbVe2nm8/d29erV6NatG6ZNmwYzMzMAn3Y5ec2n6tKlCx48eICuXbsKzVZeCA0Nxdy5c7FkyRLo6OiwHeNWAW3p0qW4cuUK7O3toaGhAQAYMGAA/v333y++ds6cOfD09MSmTZsgJycHNTU1/Pzzz1iwYIFQVugIBGlh+/btmDRpEiZOnIjOnTsjPT0dV69exfnz5yVtGkFA/v77b0mbILUIqvjZHM7OzoiNjcXQoUOF3jcA5Ofnw9nZGcAn4Rwmkwl3d3fMmjULBw4cEMmYBNHBcxibk5MTYmJiYGpqCmNjY+Tk5CA7OxtDhw5lC++6ffs2/butrS0WLVqEmTNn0nk0u3fvRnl5OYKDg4V2MU0pLCyka5a0F8laUYs7iBp1dXWUlpZCVlaW/hzU1dXBwsICOTk5kjaPa7KyspCbmwsXFxf6ehppaGiAtrY2z3V2JElkZCRmzZqF4uJitnZeFNC0tbVRXFwMBoNBh4/W19fDyMjoiwmowhR6IBCknbdv3+LMmTPIycmBiYkJfHx8YG5uLmmzCHzwww8/4LfffgPAXkj9c77GemHCrOXWHH5+frh06RKcnJygp6fHdkwY99vGxgbnz5+HpaUlBg8ejICAAGhqamLRokVtar5C+ATPOzv+/v48J2e9ffsWM2bMAAA6VnnRokUwMDAQurPTVO2m8Q9AGGo3o0aNYouzbkpTx87S0rLF8wTNOeDRL5U61NXVUVlZCU1NTToxUVtbmyO5UFp5+/YtvL29kZGRQeeBLViwALW1tTh+/DiAT7uc3OQf9e3bl85xE+Vnhhvmzp2Ln3/+GV5eXnzXQfr222+xb98+tmLDR44cgYODwxdfKyMjg6CgIAQFBfE1NoHQlrCwsOB7gkeQLgwMDOjfSUFRdoRZy605LC0tRfrM2Lp1KwoKCmBpaYlt27bB398f1dXV+P3330U2JkF08CU9zStWVlaIioqCoaEh+vXrh61bt0JHRwejR4/mWE0WxliiULtpnMw2UlhYiCNHjsDX15etgGp0dDTbeQUFBfjtt9/g4eGBJUuW8D0+8EnJ7vnz5606PdKc6L9161Z0794dbm5uOHToEJYsWQJZWVnMmTMHP//8s6TN+yIjRoyAu7s7FixYAA0NDdy+fRuTJ09Gfn4+HBwckJOTg/r6epw/fx79+/dvta/Y2FgMHjwYAOdnpiniCOMyMDBAdna2QCpz2dnZmDBhAj58+IC3b9+iR48eYLFYuHbt2hcFSVqqxdShQwcYGRnBzs6O1DUgtAu4XTQjtD1aCjNv6+HnBEJ7QCBnh9uwqmPHjsHAwADOzs64dOkSfH19UV9fj19++QWBgYH8Dt8s4lS7efv2LaZOnYr4+PhWzysqKoKTk5PAxVRlZGSgqKjYorPDYDBQU1Mj0BjiJDMzE9XV1ejZs6ekTeEKDQ0NlJWVsYVq1dXVQUtLC4cPH4aBgQEGDhzIc3XosLCwZnPezpw5A29vb2GZ3yIHDx5EWloaVq9eDTU1Nb77oSgKCQkJdPiovb09V2Fow4YNQ3x8PPT19WFkZITc3FwUFBSgf//+yMjIgIyMDC5evIh+/frxbRuBIA1wu2hGaHu0NB9qfFZ8zYjq3pw4cQJhYWF0gV4fHx+hykILWn+OID0I5OzwWzOnrq4OHz9+hIqKCr9Dt0j//v2xYcMGuLi40G03b97EqlWr8N9//wl1rKqqKpiYmHwxP6OwsBDW1tYoLy8XaDxR1ygitI6dnR1+++03DBo0iP6Sjo2NRVBQ0Bcd3taQ9ENSXl4eTCYTDAaDdk4oigKDwUBdXZ3Ix583bx6sra2Rl5eHN2/eYNGiRYiJicGePXvAZDJhaGgIBQUFrsQOCIS2BreLZgTpprnnc25uLmxtbYUewdLWaO7e1NTUwMTEBKWlpXz1uXHjRpw8eRLLli2DmZkZMjMzsWvXLvj6+mLt2rUC2yzp+nME4SLW2JB3796xechVVVVCFw8QldrN5wl2tbW1uHbtGkaOHMnWPmvWLLZdpdraWty9exdeXl4CjQ+gxfAHgnjYuXMn3NzcMHnyZHz48AGBgYEIDw/HmTNn+OovLi4OwKcaO/Hx8Ww7dhkZGV+s5SMMKIpCamoqAPC8IyUswsLC4ObmBhaLBWVlZUyYMAE//fQTampqcOfOHaxatQr37t2TiG0EgqjR0dGh/wYJbQ95eXlazOXzYuIsFgsrVqyQkGWSpzEftba2lqOmTnFxMVxdXfnu+8iRI7h37x5bmLSLiwscHByE4uysXLkSV65cEbj+HEE6EEvOzu3btzF79mxkZ2ezTeh4UXvihfT0dISFhQlV7SYgIIDt/506dUKfPn3w3XffsSV1h4SENHveqFGjBBofIDs70kB2djZOnz5Nh2r5+vry/dnq3LkzgE/qbk1zrRgMBvT09LB8+XJMmjRJGGa3SqdOnVBVVdVqsVxRYmNjg8zMTBQWFoLJZEJFRQW//fYb/vjjDyQnJyMlJQV9+vQRyXcFgSBOWlo0s7CwQEREhISsIghCZmYmKIrCmDFj2PKuGAwGtLW1OQpefk1ER0eDoiiMHTsWN27coNsZDAZ0dXVhbW3Nd98GBgZ4+fIlW9HWiooKWFtbo6CgQCC7gU8lIZ49e8a3aA9BuhDY2Zk5cyZ27drVapVgCwsLrFy5En5+fmzbgW0JbpMP79+/36wCVVxcHInzbOOI6j2cNWsWDh06JPR+ucXJyQk7d+6Era2tRMZ/+PAhBg4ciC5dusDIyAj37t2DgYEBzp8/D3t7e0RHR2PMmDH48OGDROwjEIQFt4tmBEJ7gsViCX0xbcGCBUhNTUVwcDBMTEyQlZWFjRs3wsrKCnv37hW4/8uXL+PixYsC1Z8jSA9cOzst6aRv374dCxYsgLKycotymlpaWiguLpbYyrEw4DavQtL5FwTR0aVLFzQ0NGDKlCnw9vaGnZ2dpE0SCosWLcLZs2fh7u4OY2NjtnBJcUnk2tjYIDg4GPX19ZCRkYGrqysdEvLq1Su4uLiwSZkSCASCpCF1dlpG1HV2Pn78iA0bNuDs2bO0QIGXlxfWrl0rlIUDYdSfI0gPXOfsrF27FgMGDED37t3ZQtHq6+vx9u3bVrdqAwMDERoaSn/w2yLN+YS5ubl0QndeXh6ATysY+fn5HPkXn8fyEtoeb968QUJCAsLDw+Hh4QFZWVl4enrC09MTffv25akvaaqzU11djXHjxuHDhw9IS0sT+XjNcejQIVhaWkJTU5Pj2OvXr0ldEkK7ISMjA0lJSRwKT76+vhKyiMAvpM5Oy3BTZ0eQPOQOHTpg8+bN2Lx5M999tIYw6s8RpAeud3bi4+OxdOlSfPvttwgJCaHD1gwMDJCYmAhdXV2285tO4CiKQkZGBpSVlTm2A8UxmROEpsmHn8voNiYfbtq0CTIyMmAwGM06RXp6eli3bh3mzZsnLrMJYuDBgwdYs2YNoqKieF7pkaY6OwQCQTxs2rQJW7ZsgY2NDYfC0z///CNBywiEtkd6ejqSk5NFsnAgjPpzBOmBp5wdiqJw8OBB7N69G0uWLMH3338PIyMjPH36lMPZaW0C1xRhTea4rfnDK7wmH44ZMwa3bt0Suh0E6SE1NRVnz57F2bNnUVVVhSlTpmDXrl1C67+urg4MBkOs6mjXr19HREQEioqKcPXqVTx69AgVFRVCEdYgEAif0NLSQlxcHKysrCRtCkHInDt3DjY2NrC2tsbLly8xb948yMrKYs+ePV/9+x0TEwMzMzOYmZmhoKAAq1atgqysLDZt2gQ9PT2++ty2bRtCQkJgY2PDNg8T1sKBsOrPEaQDvgQKSktLsWbNGjx69AivXr1CWloah7PTEuXl5dDQ0ODZ0C9BlMoIombDhg04d+4cSkpK4O7uDi8vLwwZMkRgSfCffvoJU6ZMgZ2dHa5evQpPT0/IyMjgzJkzGD9+vJCsb5nt27fj5MmTmDt3LlavXo2Kigq8ePEC06ZNw8OHD0U+PoHwtdCzZ0/ExcWRyVM7xMLCAg8ePICuri7Gjh0LGxsbKCsr486dO7h7966kzZMo3bt3x+3bt2FiYgIvLy8oKChASUkJeXl5uHLlCl996urqIioqSmRFySVdf44gXARSY3v69Cmio6MxZ86cVmMaKyoq8MMPPyAiIgIfP35Ehw4d6NXw5mL0+UFUOzuN1NfXY//+/YiNjUVpaSlbuFrTVYSKigps2LCh2fNIIaq2zaxZs+Dl5YURI0YIVWzDwMAAb9++RceOHdGvXz+sX78eampqWLBgAVJSUoQ2TkuYmpoiISEB+vr60NDQQHl5OSiKgpaWFhHVIBCESHx8PEJDQzF16lSOBUKi1tm2aZyDvH//HsbGxigqKoKsrCy0tLQELije1mm8N3V1ddDX10dOTg7k5eWhr6/Pd1FRCwsLPHv2TGQKv5mZmS0eMzMzE8mYBNHBczBiaWkpHj16RO/Q+Pn5fTF5a9q0aVBWVkZycjItERgSEoLp06cjMjKSb+ObUl1dzZFT00ijNy6IgsbChQvx+PFjzJ49G8uWLcPOnTuxb98+TJ48me282bNno7q6Gps2bYKHhwciIiKwY8cOuLi48D02QToQlTx0TU0NOnbsiIKCAuTm5mLixIkAPtXfEQdMJpNeaW7cpXr37h2UlZXFMn5LiGoXmECQFMnJybh27Rru3btHqrK3MwwNDfHgwQM8f/4cDg4OkJeXl2j9MmlCU1MTb9++RUpKCvr27QslJSV8+PBBoDnZ8uXLMX36dKxcuZJj4UAY0tCfOzQxMTGQlZVttrQIoQ1A8cDKlSspBQUFSk5OjtLX16fk5OSoDh06UD/99FOrr1NVVaU+fPjA1lZTU0OpqanxMnyrdOrUiSooKGj1RxB0dXXpPlRVVSmKoqiMjAyqf//+bOdpaWlR7969oyiKoq+vuLiY6tGjh0DjEyRPRkYGNX36dKpv376UpaUl248gDB48mNq2bRs1b948asaMGRRFUVReXh5lYGAgDLO/yIIFC6ipU6dS+fn5lIaGBlVRUUEFBARQgYGBYhm/KeXl5dR3331HKSoqUgwGg+rYsSPl7+9PlZaWit0WAkHYaGhoUHfv3pW0GQQRcOXKFUpfX58yNTWlEhISKIqiqNOnT1NjxoyRsGWS58iRI5Sqqiqlrq5O3bhxg6Ioirp69So1dOhQvvtkMBjN/sjIyAjF5qFDh1KxsbEURVHU1q1bKX19fcrExITavHmzUPoniBeunZ0///yTMjQ0pCIjI6mGhgaKoiiqoaGBioyMpIyMjKhjx461+FpHR0fq0aNHbG3//vsv5ejoyJfRzaGioiK0vppDW1ubqq+vpyiKooyNjamysjKqvr6eY1xdXV2qtraWoiiKMjMzo/Lz86mamhqR20cQPd9++y3l7+9PXb9+nbp79y7bjyC8evWK8vb2pr777jsqPz+foiiKioiIoJYvXy4Ms79IbW0tNX/+fEpJSYl2MObOnUvV1NSIZfymTJw4kfL19aXS0tKojx8/Uq9fv6b8/PyoCRMmiN0WAkHYmJub088HQvunrq6Oqqurk7QZUsH79++p9+/f0/8vLCykn3fSiKamJsVkMimK+vR3+/LlSyo3N5cyNjaWsGUEfuA6Z2fo0KEIDAzkCNsCgAsXLmDXrl24d+9es6/94YcfcPLkSbi5ucHExATZ2dm4fPkypk6dCn19ffo8QWppiFqgwMXFBQsXLsS4ceMwbdo0lJSU0Al29+/fp89zd3eHu7s7fH19ERgYiJiYGCgqKkJdXR3Xr18XmX0E0aOqqoqKiop2HZZQXFwMbW1tgUUX+EVNTQ1FRUXo0KED3VZbWwsDAwNUVFRIxCYCQVjs27cPsbGx+Omnn0hV9nbIvXv3cPr0abrIpY+PD4YOHSpps6SCt2/fIjw8nL43Hh4e6NKli6TNahEtLS3k5+cjLS0NkyZNwsuXL0FRFNTU1ESaH04QDVw7O5qamsjMzISKigrHsaqqKpiamraYhBcQEPBlQxgMHD16lBtTmiU7OxsmJiZ8v/5LVFRUgMViQVNTE9XV1QgNDUVVVRUWL14MY2PjZl/DZDJx8uRJVFdXw9/fv9l7R2g7eHp6YuHChUJ/eNXX12Pr1q0ICwtje0iuWLFCLMVoWxL30NTUFLtAwbBhw7Bjxw7Y2dnRbY8fP8ayZcu+ekUjQtunpYUSUpW97XPw4EGsWbMG33//PczMzJCVlYUjR45gw4YNmD17tqTNkyiRkZHw8/PD+PHj6Xtz9epVnDhxAq6urpI2r1l8fX1RU1OD0tJSODk5ITg4GM+fP4ebm5vU14ckcMK1s6OmpobKysoWj4taDY1AkDR+fn64dOkSnJycOGoDHDx4kO9+Fy9ejMePH2PdunUwMzNDZmYmNm3ahL59+2L37t2Cmv1FmtsVrampgYmJCd9KOfwijl1gAoFAEDaWlpa4cOECevfuTbelpKTAzc0NaWlpErRM8vTq1Qt79+5lq6sYExODefPm4dmzZxK0rGU+fPiA48ePQ15eHt999x3k5eVx9+5d5Ofnw8fHR9LmEXiEa2enY8eOOHr0KFo6/fvvv0dNTQ39/7i4OK4MaCtym/X19Th9+jQSExM5qvU2nehWVFRg9+7dzZ7XtCgpoe0REhLS4rH169fz3a+RkRFSUlLYlMfKysrQq1cv5OXl8d3vl7C0tKRVoCwsLNiOFRcXw9XVFX/++afIxm8OcewCEwgEgrDR0dFBTk4ORwiuiYkJSkpKJGiZ5NHU1ERhYSFboez6+nro6up+9bLcBPHAtbMzbNiwL8bxR0VF0b937tz5y4O3IblNHx8fJCcnY9y4cWzVegH2ia6zszMaGhrg7u7Ocd60adPEYiuhbWFqaoqHDx/CwMCAbsvLy8OAAQOQk5MjsnGjo6NBURTGjh2LGzdu0O0MBgO6urqwtrYW2dgEAoHQnvDx8YGMjAy2bt1Kl9hYs2YN6uvrcebMGUmbJ1HGjRuH3r17IyQkBB06dEBdXR3Wr1+Pp0+fsj17pAlSM7F9IVBRUWlk7ty5mDp1KoYMGSLUftXU1JCdnQ1VVdVWz1NVVUVJSYlYci0I4ufEiRMcuTX+/v4C9bl+/XpcuHABP/74I0xNTZGVlYWdO3di0qRJre4mCQsWiyU1ogunT59u8Zivr68YLSEQCATuqaiowIIFCxAREYGGhgbIy8vDw8MDv//++1dfLywnJwc+Pj54/PgxdHR0UFRUhH79+uHMmTMt5jxLGk9PT1RXVyMwMJCjZuKSJUskbR6BR7h2drKysvDPP/9g+vTpHMf+/PNPODk5iVQggFuCg4MRFhaG2tpaeHt7Y+rUqejTp4/A/fbv3x8XL1784h/myJEjsXv3bvTs2VPgMQnSxcaNG3Hy5EksW7aMzq3ZtWsXfH19sXbtWr77pSgKhw8fxtmzZ2knysvLCzNnzpQaJ0RcDB8+nO3/hYWFSEtLg4ODA9vOMYFAIEgjLBYLJSUl0NbW/uq+v79ETk4O/YyTVienEW1tbaSnp0NFRQXq6uqoqKhASUkJHB0dpTbPiNAyXDs7AQEBcHBwwPfff89x7NixY4iJicGxY8eafW12djZ++OEHxMbGcqg7iUqB5vHjxzhz5gzOnj0LFRUVTJ06FT4+PlyF1zVHcHAwwsPD8f3333MkpzddcV68eDHCw8MxZcoUjvNIUnXbxtzcHPfu3WNz6rOzs+Hg4ICsrCwJWta+OXHiBJ48eYJdu3ZJ2hQCgUBokbS0NERERCA/Px8GBgbw8PBA165dJW2WVFBZWYkbN27Q98bFxQVqamqSNqtF9PT0kJmZCUVFRZibm+PBgwdQU1ODnp4eEeNqg3Dt7JibmyM1NRUdO3bkOFZbWwtra2tkZmY2+1pnZ2cYGxsjKCgI9vb2SEhIwMaNGzF48GDMmTNHsCtoBYqicOfOHSxduhQvX76EqqoqbGxssGPHDnzzzTc89fX5inMjDAYD//zzD/3/lhKsSVJ128fAwID+HDVSUVEBa2trFBQUCNT3sWPHcPbsWfpB4OXlhenTp0us3o00wWKxoKWlRRJZCQSC1HLq1CnMnz8fEydOpJUkr1y5gj179sDPz0/S5kmUO3fuYMqUKejduzeMjY2RnZ2NZ8+e4dy5cxg5cqSkzWsWUjOxfcG1s6OsrIyysrJmc1Hq6uro+jPNoampifz8fHTo0IHeDqyurkafPn3w5s0bwa6gGR4+fIjTp08jIiICJiYmmDp1Kry9vaGhoYE///wTGzZsICvxBJ5ZsGABUlNTERwcTCegbty4EVZWVti7dy/f/QYFBeHGjRtYsmQJ/ZD89ddfMWbMGOzYsUOIVyD9fK4+V1tbizNnzuDkyZNITU2VkFUEAoHQOubm5ggLC8PAgQPptgcPHsDLy6vFheCvBWtra2zfvp2tpk5kZCSCgoLw8uVLCVrGHaRmYtuHa2fHxsYGv/zyC8aMGcNx7NatWwgKCkJSUlKzrzUyMsLLly+hrKwMS0tL3Lx5E5qamjAzMxP6dqCFhQVkZWXh6+sLPz8/WFpacpwzcOBAxMfHC3VcQvvn48eP2LBhA51bY2RkBE9PT6xduxaKiop896ujo4Pk5GS2OjL5+fmwsbFBcXGxMEznmREjRsDBwQFLly4Va3KtjIwMGAwGrXyjpKQEW1tbhIaGYsCAAWKzg0AgEHhBX18f2dnZbPLKHz9+hKmpKQoLCyVomeTR1NREUVER5OTk6LaGhgbo6uqKvXA14etE7sunfGLRokWYMWMGDhw4gHHjxkFGRgYsFgvXrl3D/PnzW60z4u7ujuvXr8PT0xPTp0+Ho6MjFBQUMHHiRKFcRCMsFgvTp0/HTz/9xKZ1/znE0SHwQ4cOHbB582Zs3rxZqP1qampCVlaWrU1WVhaamppCHYcXHB0dkZOTg9GjR+PRo0diG5fFYoltLAKBQBAWwcHBmDt3LoKDg+lQrY0bN2LDhg2SNk3iLFy4ECEhIVi7di0UFBRQV1eHTZs2YdGiRZI2jY3Zs2dzdZ4gRcQJkoEn6elNmzZh69atqK+vh7a2NkpKSiAvL49Vq1Zh9erVXA8aExODqqoqODs7c0zyBEVVVZUkjxFEwp49e+Dg4IC+ffvSbf/99x8ePHiA+fPn893vL7/8gjNnziAwMJB+SP7+++/w9PSEg4MDfV5bKcArKCwWC48ePaJ3z/r16yf07wkCgUAQJvLy8mAymWx5lhRFQVZWlt6tZjAYqKurk6CVksHS0hIZGRmQl5eHjo4OSkpKUFdXxyEY9erVKwlZ+AluSz0IUkScIBl4rrNTWVmJ+Ph4lJaWQktLCwMHDpQqRQ0PDw/MmzcPTk5OQu33/v37bBPPRuLi4r6aSejXTtNwzEaqqqpgbW2N3NxcvvttbwV4BeHFixeYOHEiampq6PwlJSUlXLp0CT169JC0eQQCgdAs3OblmJmZidgS6SM6Opqr8xwdHUVsCeFrpd0VFfX19cWlS5fg6OgIY2NjtlUWQbYeW9ox0tTUZIs5ra+vx+nTp5GYmMgh2EC2Pts22trayMvLYxPp+PjxIwwMDNpc3LG8vHyrSm+SWoUcPnw4xo0bh2XLltH2hYaG4vLly1w/MAkEAkGStLQ4SvhUa0faa+w0EhUVxaGS2pIyL0G64Tpnp61gZWWFn376SWj9NapDsVgs5Ofno6lvmJGRwaFO5+vri5cvX2Ls2LEwMjISmh0EyfPtt99i+/btbAVEf/nlF9jb2wttjG3btmHFihVC668l0tLSRD4GPyQmJuLOnTtsjtjixYuxceNGCVpFIBAI3OPi4kLC6VugR48ebeLe7NixA6GhoZg5cya++eYbZGdnw8/PD4GBgQgKCpK0eQQeaXc7O8Lmc3Wopujp6WHdunWYN28e3aauro7c3Fx06tRJnGYSxEBGRgbGjRuH6upqmJmZITMzEyoqKrh69SrMzc2FMsbXnnP2zTffYP369WwSpVeuXMG6devw5MkTCVpGIBAI3KGiooKqqipJmyGVtJV7Y2hoiKioKFhZWdFtL1++xLBhw5Cfny9Bywj80O52doBPFdfDwsKQl5cHQ0ND+Pj4wN/fn6++GtWhxowZg1u3bn3x/H79+iE7OxvW1tZ8jUeQXszNzZGUlISHDx8iJycHJiYmGDBggFCT58W19iCtqjO7d++Gq6sr+vTpA1NTU2RmZiIpKQmXLl0Sqx0EAoHAL0OGDJG0CVJLW8lZkpeX5wi3MzQ0bLbWJEH6kZizIyMjAwcHB6xbtw6jRo0SWr8bN27EyZMnsWzZMnr1fevWrcjMzGQLP+IVbhwd4FMVZVdXVwwcOBC6urpsx1atWsX3+ATpQFZWVqSCFOL6jEhjiCVFUTA0NMSLFy9w+/Zt5OXlYdSoUXBxcYGWlpakzSMQCASuuH79uqRNkFpSUlIkbQJXBAUFwcPDA6tWraJVUrdv347ly5ezFb82NDSUoJUEbpFYGFt0dDRycnIQGxuL/fv3C61fc3Nz3Lt3DyYmJnRbdnY2HBwckJWVxXe/mZmZCA4OblZ4oKlc4qxZs3D16lU4OjqiY8eOdDuDwcDRo0f5Hp/w9ZCamgorKyvIyMhI2hSx06lTJ1RVVX2V104gENoP3bt3R2xs7Fe9UENRFA4fPoznz59j9OjRcHFxwZ49e/C///0PvXv3xsqVK9nmSdIEN88gBoMBJpMpBmsIgtLucnYMDAzw8uVLqKqq0m0VFRWwtrZGQUEB3/0OHDgQ3bp1g7e3N5SUlNiONZVLVFVVRVpaGseuDoHALYaGhkhMTISOjo7Yxrx+/ToiIiJQVFSEq1ev4tGjR6ioqBDqris3ODk5YefOnbC1tRXruAQCgcAPo0ePbrY9JiYG3377LRQUFHD79m0xWyUd/PDDD4iJicGYMWNw48YNfPvtt3j58iU8PT0REREBCwsLHDlyRNJmEr4CxBbGdv36dYSHh6O4uFikk6nJkyfDzc0NwcHBMDExQVZWFjZu3Ah3d3eB+n327Bnu37//RW+/W7duaGhoEGgswtdBS/LPDQ0NMDQ0FJv08/bt23Hy5EnMnTuXLg6soqKChQsXit3Z6dGjB0aPHg13d3cO6XgSBkogEKSNpKQkdOvWDTNmzKC/ryiKQkJCAiZPnixVdQjFTXh4OFJSUqClpUUXzS4oKICOjg68vb3Rs2dPSZtI+EoQy87O55OpiooKvHjxAtOmTcPDhw+FOtbHjx+xYcMGnD17lhYo8PLywtq1a6GoqMh3v56enli4cCGGDh3a6nnr16/HhQsXMHPmTI7dHV9fX77HJ7Q/XFxcUF1dje3bt9M5NBRFYcCAAbh+/Tp0dHTEksxpamqKhIQE6OvrQ0NDA+Xl5aAoClpaWmKvHxQQENDisWPHjonREgKBQPgy7969w/r16xEfH4+dO3fS9XUMDAyQmJj4VUd5aGlpITc3F4qKiqiuroaGhgZqamogLy+PhoYG6OrqtrkadYS2iVicHWmaTPFCU8WqmpoaXLp0CU5OTtDT02M7r6liVUsFpxgMBv755x/RGEpos1y+fBlr1qyBr68vfvzxR8jLy4v9IWlkZIS0tDR07NiRLpJbWVmJ3r17C5TnRiAQCF8LKSkpWLx4MfT09PDLL7+gf//+ePr06Vft7EyZMgUfPnyAm5sbIiMj8e7dO9jZ2WH27Nk4evQo/vvvP67FnwgEQRBLGBuTyaS3chu3ed+9ewdlZWWRjJeRkYGkpCQOIQFed1Y+V6zippBUVFQUT2MQvm5cXV3h7OyMbdu2oW/fvti4cWOzoW2iZNKkSZg1axZ27NgBAKisrMSSJUsEDv3kh9OnTzfb3qFDBxgZGcHOzg5ycu1SMZ9AILRhevXqhf/97384c+YMnJycpHohV1wcPHgQ69evx+XLlzFnzhzY2tpiypQp2L9/P/r370/ydQhiQyw7OwsXLkRFRQV27NiBHj16ID09HUuWLIGamhp27dol1LE2bdqELVu2wMbGhkMNTVQ7KwUFBdDX1wcANknCzyEShYTWyMjIwNKlS3H37l28evUK2traYhn3w4cPWLZsGf7880/U1tZCUVER06ZNQ2hoqNiVcoYNG4b4+Hjo6+vDyMgIubm5KCgoQP/+/ZGRkQEZGRlcvHgR/fr1E6tdBAKBwC01NTV4/fo1evXqJdQ6bAQCgT/E4uy0NJnatWuXQHk0zaGlpYW4uDi2qrfCYMuWLc22d+jQAWvWrEFOTg60tLQgIyMDBoPBURySSBQS2gLFxcXQ1tYW++5SI/PmzYONjQ3mzZtHtx04cABJSUnYt28ftm3bhkuXLuHBgwcSsY9AIBA+h6IoXL16Fffv30d5eTk0NDQwePBgjBs3TmLfpdICuTcEaUDs0tOinkz17NkTcXFxQldA8fb2xsWLF2Fvbw9jY2Pk5OTg4cOHmDBhAvLy8pCcnIyIiAiMGTNGqOMS2je5ubkIDQ3leBA0KteIg/Pnz6N79+7o0aMH3fbs2TO8evUKkyZNEosNjairq6O0tJRtNZTJZEJLSwsVFRWoq6uDjo4OKisrxWoXgUAgNEdtbS1GjRqFxMRE2NnZQV9fH/n5+Xj8+DH69OmDv//+W2pryYgacm8I0oJYKveNHj0aR48eRUVFBXR0dETqzR8+fBjff/89Ll26hLi4OLYfQWhoaMD58+cRExOD06dPIyYmBhcuXACDwUBcXBwOHDjAVU4PgdBIVlYW+vbti+joaLi4uGDp0qVwdnZGdHQ0vvnmG2RmZorFjmXLlnGIbujp6WHp0qViGb8ppqam+Ouvv9jaTp48SRcJrqqqEvpuMIFAIPDL9u3b0dDQgNevXyMqKgphYWG4e/cuXr9+DRaLhW3btknaRIlB7g1BWhDLzs6JEydw9uxZREdHw9HREV5eXnBzc2Mr/CksDh48iMDAQKiqqnLk7Lx9+5bvftXU1FBWVsa24tzQ0AAtLS3o6uqCwWAgLS0NXbt2bbGPV69e8T0+of0xa9Ys1NXV4fjx4xzHAgICICsri8OHD4vcDg0NDZSUlHB8trW1tVFRUSHy8Zvy8OFDuLu7o2PHjnTOTm1tLc6fPw97e3tER0cjOTkZCxcuFKtdBAKB0Bw2NjY4dOgQ7O3tOY49fPgQs2bNQlJSkgQskzzk3hCkBbGGsZWXl+PChQsIDw/H/fv34eTkhEuXLgl1DE1NTVy8eBGOjo5C7XfQoEFwdnbGypUraY34bdu24erVq9i+fTuKioowf/58/PjjjwgLC8OiRYvooqZ79+6Fj48Pli9fLlSbCG2bLl264Pbt2+jSpQvHsbS0NIwePVogB51bhg0bhmnTprHVuDl+/DgOHz6Me/fuiXz8z6mrq0N8fDwt/DFw4EAoKCiI3Q4CgUD4EmpqaiguLm72O6qurg5aWlqoqqqSgGWSh9wbgrQg9pyd2tpaREZGYt++fXjw4AE+fvwo1P47d+6M1NRUoYe6pKWlwcfHB8+fP4eOjg6Ki4vRvXt3hIWFwdLSEgkJCcjJycHq1asRFRVFq7MBQH5+PkaMGIHU1FSh2kRo26iqqqKysrLZsE4WiwU1NTWxPAiePn2KMWPGoFu3bujcuTPS09Px+vVr3Lx5E7a2tiIfn0AgENoqampqreYQful4e4bcG4K0IDY1tmvXruHs2bO4desW7Ozs4OXlBXd3d2hpaQl1rH379iE2NhY//fQTdHR02I4JQ/o5IyMDhYWF0NfXb7a6vba2NlJTU9nGLioqQvfu3VFaWirw+IT2g6qqKt69e8f3cWHy7t07XL16FTk5OTAxMcG4ceNEEmZKIBAI7QkFBQVMnz692WMUReHEiRNCX9RtK5B7Q5AWxOLsqKqqok+fPvD09MSUKVPYdj2EjYxM85oL4pJ+Xrx4MaKjo7F06VKYmJggOzsbu3btwtChQ7F7926Rj09oO8jKyjYbwgZ8ehCkp6ejoaFBzFYRCAQCgVtCQkK+eM769evFYIn0Qe4NQVoQi7OTk5MjNhldYaKpqUlXQZaXl+cIN6IoCgwGA3V1dXQbi8XCgQMHEBERgfz8fBgYGMDDwwNz5swhxcUIbERHR3/xHGHnnhEIBAKBQCB8TYjM2Xn48CGtwNGa7POgQYOEPnZdXR0ePHiAvLw8eHt703kPKioqPPWTnZ1NS962JgPcXDgbgUAgEAiE9s39+/dx9epVbN26lePYqlWrMH78eJHMc9oC5N4QpAWROTu9evVCSkoKgE+iAc0OLqAcdHM8fvwYkydPhq6uLl68eIGqqircunULhw4dQkREBF99MplMjBgxArdv30aHDh24fl3v3r2RnJzM15iE9s+xY8dw584dnDp1iuOYn58fRo0ahWnTpols/La640ogEAjSgrOzM5YtW4ZRo0ZxHPvf//6HX375BTdv3pSAZZKH3BuCtCB2NTZR079/f6xduxYTJ06EhoYGysvLUVtbCwsLC+Tn5/Pdr4WFBZKSkqCsrMz1a8SZYE5oe/Tv3x/Hjx9Hjx49OI6lpqbC398fjx49Etn45PNJIBAIgmFgYIC8vLxmVTUpioKBgQEKCgokYJnkIfeGIC00n80vZMaNG9ds+8SJE4U+1ps3bzBhwgQAoP/AFBQU2PJq+GHZsmX47rvvkJCQgNzcXOTl5dE/LdHO/EiCkHnz5k2zjg4AdO/eHW/evBHp+OTzSSAQCIJRXV3dYomAqqoq1NTUiNki6YHcG4K0ICeOQVoqTBgbGyv0sXr37o3Lly/Dzc2Nbrt69Sr69u0rUL+LFi0CAFy+fJmtvTWVt+fPnws0JqF9IysrSxfO/Jz8/PwWlQWFSXZ2dqtOj6mpqchtIBAIhLZK//798ddff2HBggUcx06ePIl+/fpJwCrpgNwbgrQgUmdn9uzZAICPHz/SvzeSmZkJa2troY+5Z88euLi44MCBA6ipqYGbmxuePHmCa9euCdQvi8Xi6fz09HTcuXMHAODk5AQLCwuBxie0P0aNGoV169bh4MGDHMdCQkIwevRokY7//v17WFlZtejsMBgMsvJGIBAIrRAcHIyxY8fi7du3cHV1hb6+PgoKCnD58mUcPHgQ169fl7SJEoPcG4K0INKcnUaN9S1btmDVqlX/NyiDAV1dXXh4eEBbW1vo475//x5Xr15FVlYWjIyMMH78eKEUSGSxWEhISEB+fj4MDQ3Rv39/evXdyckJO3bsQN++fXHlyhX4+fnB0dERDAYDMTEx+OuvvzB+/HiBbSC0H7KysjBw4EDo6+uzPQgiIyNRUFCAuLg4ke6sqKiotBhiQCAQCATuuHv3LlatWoWHDx/SJSns7e2xZcsWDBs2TNLmSRRybwjSgFgECqKjo9t8vZDExERMnjwZ9fX1MDY2Rk5ODuTl5REREYG+fftCQ0MDZWVlYDAYsLW1xW+//YahQ4cC+CS/OHv2bDx79kzCV0GQNoqLixEaGoqoqCiUlpZCS0sLI0aMwJIlS6CjoyPSsYlAAYFAIAiPmpoalJeXQ0NDA0pKSpI2R6og94YgSdpdnZ2MjAyEhIQgMTER1dXVbMdevXrFd7/ffPMNZsyYgYULF9Jte/fuxeHDh/HkyRPo6+sjNTUVGhoa0NHRQX5+PuTkPkUJMplMqKurk1V0glRBdnYIBAKBQCC0d9pdnR07OzvY2trCw8MDHTt2ZDsmyO6SmpoaysrKICsrS7c1NDRAU1MT7969Q1BQEPLy8vDHH39g3bp10NDQwJo1a0BRFLZu3YqoqCg6h4dAIBAIBAKBQCCInnZXZ0ddXR1lZWVCV7KaPXs27Ozs2IQWDh8+jEePHuGPP/4Ak8nEihUrcPz4cejr6yMlJQUKCgoAPimShIWFkQKOBAKBQCAQCASCGBGLs1NWVgZFRUUoKSmByWTi1KlTkJOTg4+PT7PFpgRh3rx5GDlyJNzd3QXua9SoUbR9TCYTMTExMDU1pXN2srKy4OjoyLZjU15ejuTkZOTm5qJjx47o1asXunbtKrAtBAKBQCAQCAQCgTfE4uzY29vjjz/+gK2tLZYvX46bN29CXl4eQ4YMwa+//irUsQoLCzFw4ECoqqpCV1eX7djt27d56uv48eNcnTdt2jSe+iUQmvLgwQN8++23kjaDQCAQCDywZcsWrs5rqkb7tUDuDUGaEIuz01SpzNDQEI8ePUKnTp3QvXt35OfnC3WsIUOGQElJCZMmTeLI2RGlU3L//n04ODgA+FSZ/tdff8WFCxdAURRcXV2xbNkysRSJJLQ9LCwswGAw4OPjA19fX/To0UPsNtTX1+P169coLS1lq7vTqChIIBAIBHYCAgLo32tra3HhwgXY29vDxMQE2dnZSEhIwOTJkxEWFiZBKyUDuTcEaUKkRUXpQeTkUFNTg+fPn0NPTw9GRkZgMpl4//690Md6+vQpysvLaSU0UdCcZK+LiwvdtmnTJpw7dw5r1qwBg8HA5s2bUVNTg/Xr14vMJkLb5e3bt4iPj0dYWBicnJygr68PX19f+Pj4iCXPKzo6Gt7e3mAwGCguLoaOjg5KSkrQtWtXPH/+XOTjEwgEQlvk2LFj9O8eHh4IDw+Hq6sr3RYZGYkTJ05IwjSJQ+4NQZoQy87ODz/8gAcPHqCqqgpz587F4sWL8e+//2LGjBlISkoS6lgeHh5YunSp0CWtm9KcZG/TNisrK1y+fBnW1tYAgNevX8PZ2Rlv3rwRmU2E9gGLxcKdO3ewbNkypKamwsHBATNnzsTUqVPZlACFia2tLRYtWoSZM2dCQ0MD5eXl2L17N8rLyxEcHCySMQkEAqE9oaamhtLSUraF1oaGBmhpaaGyslKClkkecm8IkkYszg5FUbh9+zbk5eUxYsQIAMDjx49RWVlJ/19YTJ06FZGRkXBycuLI2Tl48KBQxmjO2Wm626Ovr4+CgoIvvoZAaMrTp08RFhaGM2fOQFtbG35+fjA1NcX+/fuhqKiIq1evimRcVVVVVFZWgsFgQFNTE2VlZWCxWDAwMEBhYaFIxiQQCIT2xODBgzF8+HCsXbsWCgoKqKurw6ZNm3Dnzp1Waw1+DZB7Q5A0YgljYzAYGDVqFB49eoSLFy/C0NAQdnZ2Ilmp7tatG3788Ueh99uU5pyW9+/fo1u3bqAoCpWVlXj16hW6desGAMjJyYGamppIbSK0XUJCQhAWFoa6ujr4+Pjg5s2b6N69O318/Pjx0NLSEtn4BgYGyM/Ph6GhITp37ozbt29DR0cHLBZLZGMSCARCe+LEiRPw8fHBzp076VDgXr164dSpU5I2TeKQe0OQNGLZ2Xnx4gUmTpyI2tpaGBsbIzs7G0pKSrh06ZJEkrF54f3791BQUIC8vDyAT0IE169fBwCMHTuWFiWIjo5me521tTX09PToY48fP8bSpUvFaDmhrTBnzhz4+flhyJAhLZ6TmJiIPn36iGT8Y8eOwcDAAM7Ozrh06RJ8fX1RX1+Pn3/+GUuWLBHJmAQCgdAeycrKQn5+PgwMDGBqaippc6QKcm8IkkIszs7w4cMxbtw4LFu2jK5bExoaisuXL3M4CdJGv379cPz4cfTq1QuHDx/GqlWr6GTuc+fOYdOmTZg5c6akzSS0UZhMJiwtLZGamooOHTpI2hwAQF1dHT5+/AgVFRVJm0IgEAhthuLiYty4cQP5+fn46aefkJOTAxaLRSb2IPeGIFnE4uxoamqiuLiYLWyNyWRCW1sb5eXloh5eIJrm4nTv3h3nzp1D7969AQCpqakYP348LTyQm5uL0NBQ3L9/H+Xl5dDQ0ICDgwOWLFkiFlUtQtukR48eiImJgba2tkTG7927N5KTkznabW1t8fTpU/EbRCAQCG2MW7du4bvvvoOjoyNu3bqFd+/eITY2Flu2bKGjQb5WyL0hSBqx5OyYm5vj6tWrbLKD169fh7m5uTiGFwh1dXXk5ubCyMgI5eXlsLKyoo916dIFxcXFAD5tz9rZ2cHU1BQTJkyAvr4+8vPzce3aNfz111949OgRzMzMJHUZBCkmICAAEydORGBgIIyMjOjdTwAiVRVsJCMjg6ONyWQiKytL5GMTCARCe2Dp0qW4cuUK7O3toaGhAQAYMGAA/v33XwlbJnnIvSFIGrHs7Ny7dw+urq7o06cPTE1NkZmZiaSkJFy6dEnqixb+/PPPuH37Ng4dOoTw8HC8fv2arpezefNmFBcXIyIiArNmzUJdXR2OHz/O0UdAQABkZWVx+PBhcZtPaAN07ty52XYGg4G3b9+KbNxRo0aBwWDg7t27GDZsGNuxnJwcmJubk1U3AoFA4AJtbW0UFxezqVrW19fDyMgIRUVFkjZPopB7Q5A0YtnZGTJkCNLS0nD9+nXk5eVh1KhRcHFxEYnCVH19Pfbv34/Y2FiOavD//PMPz/0tX74cnTp1wuDBg1FTU4PKykocPXoUCgoK8PDwwJEjR+i+b9++3Wwfq1evxujRo/m7IEK7Jz09XSLj+vn5gaIo3Lt3D1OnTqXbGQwGdHV1hS4LTyAQCO2Vb7/9Fvv27cOCBQvotiNHjtAiRl8z5N4QJI1YdnYaKSgooJU49PX1RTLGnDlz8PjxY8yePRvLli3Dzp07sW/fPkyePBnr1q3ju18Wi4WcnBzk5uaiY8eO6NatG5SUlOjjTWuVNPdaNTU1UmeH0CKVlZW4efMm8vLyYGhoCBcXF6iqqopl7PT09BZ3lwgEAoHwZbKzszFhwgR8+PABb9++RY8ePcBisXDt2jWYmJhI2jyJQu4NQdKIxdnJzMyEv78/Hj58CE1NTZSWlsLe3h5//fWX0PNY9PT0kJSUBD09PaipqaGyshKZmZmYMmUKEhIShDpWU5oKGfBznPD1EhcXhwkTJsDKygpmZmbIysrCixcvcOXKFbHk7LBYLBw4cADh4eEoKSlBcnIyYmJikJOTA19fX5GPTyAQCO0BiqKQkJCArKwsGBkZwd7eXiT1BNsi5N4QJIlYnJ1hw4bB3t4ewcHB6NixI2praxESEoK4uDjExMQIdSwdHR3k5+dDTk4OJiYmSEpKgoqKCjQ1NflyNsLCwuDj4wMAqK2txYoVK3DhwgVQFAVXV1f88ssvUFJSgqysLLp06dJsHxRFIT09HQ0NDQJdG6F90r9/fwQFBcHT05NuCw8Px/bt28WSwBkUFIT//vsPS5cuhZ+fH8rLy5GZmYmJEyciMTFR5OMTCARCW2fLli3w9vaGhYWFpE2ROsi9IUgasTg7qqqqKCsrg5zc/6UI1dfXQ1NTU+ihXS4uLli4cCHGjRuHadOmoaSkBEpKSsjLy8P9+/d57q/pjsySJUvw9OlTbNu2DQwGA6tWrUKvXr3w66+/clUvyNHRkefxCe0fDQ0NlJSUSEya3cDAAC9fvoSqqio0NDToMdXV1VFRUSHy8QkEAqGtM2PGDFy6dAkWFhbw8vKCp6cnUWD9/5B7Q5A0YnF2Jk2ahNmzZ8PFxYVuu3nzJg4ePIgLFy4IdayKigqwWCxoamqiuroaoaGhqKqqomV9eUVFRYV2yDp37oyYmBg6xjQvLw/ffvstkeglCMTQoUPh5eXFlry5b98+nD59GrGxsSIf39zcHP/99x80NTVppZyCggI4ODjQNaQIBAKB0Dr19fW4desWzp07hytXrsDa2hpeXl4IDAyUtGkSh9wbgiQRi7Pj6+uLCxcuYNCgQTAxMUF2djbi4uLg7u6OTp060ecdPHhQ4LGahp015cyZM/D29ua5v6Y7O8bGxsjOzmYTIWh0ho4dO4Y7d+7g1KlTHH34+flh1KhRmDZtGs/jE9o/z58/x4QJE0BRFP33AQCRkZHo1auXyMdfv3497t+/j02bNsHFxQVRUVFYvXo1Bg0ahNWrV4t8fAKBQGhvpKenY9asWYiKigKTyZS0OVIFuTcEcSMWZyckJISr8xrr1whCS0IAjSvWvCIjIwM5OTlQFAUWi4XHjx/D1tYWAJCWloZRo0YhPT0d/fv3x/Hjx9GjRw+OPlJTU+Hv749Hjx7xPD7h66C+vh4PHjxAfn4+DA0NYW9vD3l5ebGMzWKxsHPnThw9ehRZWVkwNjZGQEAAgoKCSAIpgUAgcElj3b2zZ8/i6dOnGDt2LLy8vNgKqn+tkHtDkCRilZ4WJXFxcQCA0aNH4++//2arr5ORkYGffvqJXjHnhczMTLb/a2tr07tRjx49QlpaGnx8fL7oTPHrbBEIBAKBQJBuRowYgX///RejR4+Gl5cXxo8fj44dO0raLKmA3BuCpBG7s9O7d28kJycLvd/GOiFZWVkwNTWl2xkMBvT09LB8+XJMmjRJ6OM2oqOjg+Tk5GbrB+Xn56N3794oKSkR2fiEtkujElpSUhKqq6sBfFLwYzAYqKurE4sNUVFROHv2LF0Hy8vLC8OHDxfL2AQCgdDWOXXqFFxdXaGsrCxpU6QOcm8Ikkbszo6o683MmjULhw4dEmqfiYmJ2LBhA+7fv4/y8nJoaGjAwcEBa9eupUPafH19oays3Gze0dy5c/Hu3TucPn1aqHYR2gdWVlaYOnUqPD09OVa7xKFYs2PHDoSGhmLmzJl0ztDRo0cRGBiIoKAgkY9PIBAIBAKBICrE7uw0VTcTFXV1dXjw4AHy8vLg7e1Nj6eiosJzXykpKbC3t4ezszMmTpwIfX195Ofn48qVK7h58ybi4+NhY2ODrKwsDBw4EPr6+nB1dYW+vj4KCgoQGRmJgoICxMXFse04EQiNaGtro6ioCDIyMhIZ39DQEFFRUf+vvTuPirr6/wf+HBAUZR2QbdgEN9z1ox8UNBRzRdwVUFJRTMslXFMqFzKXSktzywLFDDTIBZfCvkkokkl+XBOXZBkQUGQTEwQZfn94nJ8ElDLDvIeZ5+OczqH7fvO+T+4x4zX3vu9Fu3bt5G03b95E//79kZOTI0gmIiJ19+LydD09vWqbFwGqn6FXJxwbUicqL3YyMzPlWzc3hAsXLmDs2LGwtLTEjRs3UFJSgri4OHz11VeIiYl55ef5+/vDzs4On3zySY1ry5YtQ0ZGBqKiogA8ewFv06ZNiI+PR35+PszNzeHl5YUFCxagZcuWCv9spJlWrVoFU1NTwbbgdHR0xPXr16vtjFhSUoJOnTrVeGeNiIieefH3mX/6u1Ibz5Th2JA6afBi5+bNm7hx4wZ69+4NKysrXLp0CQkJCejcuTO8vLyU3l+vXr3wwQcfYOTIkfIDEktLS+Hs7FyvT6kdHByQlJQEOzu7Gtfu3r0LNzc3ZGVlKSM6aak7d+7g9ddfR3FxMSwsLKpdu3XrVoP0mZ2dLf/64MGDOH78OEJCQuTbq2/YsAHDhw+vdvYPERHVVFlZCS8vL5w8eRJNmzYVOo5a4diQOmjQYicsLAwLFiyAq6ur/BeoZcuWwd3dHWfOnMHixYuxePFipfYpFouRn58PkUgkn0atrKyEpaUl8vPzX/l5/7bsThXL8kizdenSBf/9738xfvz4Gu/seHp6NkifOjo6EIlE+Kf//EUiEc9AICJ6Cc7Ozrhy5Qpfwq8Fx4aE1qQhH75u3TokJCSge/fuOH/+PPr27YsLFy6gc+fOuH79Ory9vZVe7HTu3BlHjhzB6NGj5W3Hjh1D9+7d6/W8v68zfdXrRP8mIyMDly5dUuk7OzKZTGV9ERFpukWLFuGNN97A8uXLIZFIqv1uYGtrK2Ay4XFsSGgNOrNjYmKC4uJiAM+mMps1a4by8nL5H/QXryvL1atXMWzYMHTq1Am//PILhg4diosXL+L48eP1Oo3++aGitXl+0Cg//SZFzJ49G4MGDcK4ceOEjoKoqCj4+/sLHYOIqFGp68MqzpBzbEh4DVrs9O3bF8OGDYOfnx+++eYb7N27Fxs3bsSYMWNw9OhRrFixAhcvXlR6v3/99ReOHTsGqVQKiUSCESNGwNjYuF7PepkXtPmCHSli4MCBSExMhKurKywtLatdO3nypEqzNPTW8ERERESq1KDFzuXLl/HGG28gIyMD8+bNw9ChQ+Ht7Q1DQ0M8fvwY3333HQYNGtQgfefm5soPSKztoM+XVVVVhZKSklqLpYcPH8LIyOhfl7JNnz4dffv2xdSpU6Grq1vvLKSZIiIi6rw2depUFSbhO2hERPWlzGMvNA3HhoSk8q2nCwsLcefOHbRt27besy3/JCMjA1OmTMFvv/0m36zAzc0N33zzTb1mYDZu3IirV69iz549Na4FBgaiS5cuWLBgwT8+IzAwEFlZWcjJycG1a9deOQORqrz11lvYsWOH0DGIiBoVZR97oUk4NiQ0lRQ7+fn5SE5ORmFhIcRiMXr27Alzc/MG6at///5wc3PDqlWrYGBggNLSUqxevRpJSUk4ffr0Kz+vS5cuOHr0aK2FUkZGBkaMGIGrV6++1LMqKys5s0M1lJaWYuXKlYiOjkZ+fj4ePnyIuLg4pKSkCHb2DhERvTxlH3uhSTg2JLQGL3ZCQkKwceNGyGQyWFhY4MGDB9DV1UVwcDDWr1+v9P6MjY1RUFBQbVOBiooKiMXiei3PMTU1RVFRUZ3Xa9tkgdO19CoCAwNRUVGBZcuWoV+/figsLEROTg4GDBiAGzduNHj/FRUV2LFjBxITE5Gfn19tO+pTp041eP9ERI2dso+90CQcGxJag+51GxERgYiICMTExKCsrAw5OTkoKytDdHQ09u3bV+vSMEUNHDgQP/30U7W2n3/+ud7vBjVv3hzp6em1XktLS0Pz5s2rtV24cAFt2rTBokWLMHPmTABAUlISAgMD69U/ab7jx48jLCwMnTp1kr//ZWNjg9zcXJX0P3fuXOzduxevv/46zp8/Dz8/PxQUFKB///4q6Z+IqLF7fuzFixQ59kKTcGxIaA06s/Paa68hODgYY8eOrXHt4MGD+Oyzz3DmzBmF+3nzzTflXz969AgHDx6Eu7s77O3tkZmZiaSkJIwbNw7ffvvtKz971qxZyMnJQUxMDPT19eXtT548gZ+fH6ysrLBz5055O6dr6VW1bdsWp06dgp2dnfxTr9TUVHh7eyMlJaXB+7eyssKVK1dgZWUln6nMyMjAhAkTcP78+Qbvn4iosVP2sReahGNDQmvQYkcsFiMjI6PW5VslJSVwcHBAYWGhwv2sXr36pe5buXLlKz+7oKAAnp6eKCgowJAhQ2BtbY3c3FycPHkS5ubm+OWXX2BmZia/n9O19Kq2bduGXbt2Yfny5Zg1axYiIiLw0UcfISgoCLNmzWrw/lu2bImcnBw0adIE9vb2uHLlCoyMjCAWi7kNNRHRS1LmsReahmNDQlLZoaK1aSxnepSVlSEiIgLx8fHIz8+Hubk5vLy8MGXKFDRr1qzavZ6enliwYAFGjx4tL3aOHDmCL774Av/3f/8n0E9A6i46Ohrh4eHy/xFMnz4dfn5+Kul72LBhmDt3Lry9vTF16lQ8ePAAzZs3R3Z2Ns6ePauSDEREREQNoUGLHQMDA4SHh6OuLoKCgvD48eOG6h6dO3d+6Z3SlIXTtdTYFBUVQSaTQSwW49GjR9i0aRNKSkrwzjvvwM7OTuh4RERqqU2bNv96zh4A3Lp1SwVp1AvHhtRJgxY7/fv3/9c/7PHx8Q3VvWAzR5yupVeVkJCAy5cv49GjR9XaQ0JCBEpERET/JCEhQf71uXPnEBUVhXnz5sHe3h5SqRTbtm2Dv78/li5dKmBKYXBsSJ2o/FBRVRLiNPjIyEiMHj26xi5tRHV5++23cejQIXh6esLAwEDeLhKJEB4e3uD9V1RUIDIystZia9euXQ3ePxFRY+fq6or4+HhYW1vL23JycuDl5aWSjWbUGceGhNbk32+pP6lUilOnTmHatGk1ru3ZswcDBw6Evb19g/V//fr1Bnt2Xb7++mvMmjULQ4YMga+vL0aMGFHtF1iiv4uKisLNmzdhaWkpSP9TpkzB1atX4e3tDYlEIkgGIqLGLC8vr8ah4bq6urh//75AidQHx4aE1qDFzsqVK+Hh4VHrtaqqKqxYsQK7d+9Wer8VFRW4ffs28vPzkZaWJm9/7bXXlN7X3506dQr37t1DTEwMvvjiCwQFBWH48OHw9fXF6NGjG7x/anxat26Np0+fCtb/iRMnkJmZyaWWRET1NHnyZAwaNAgLFy6UH3vx2WefISAgQOhoguPYkNAadBmbk5MTUlJSap3ZKC0tRfv27ZGRkaHUPhMSEuDn5weRSIS8vDy0bNkSDx48QOvWrZU+0+Pl5QUPDw8sXLiw2vbTL0pLS8PMmTMRHx+PyspKpfZPmuHWrVuYP38+hg4dWmN2Z9KkSQ3ef69evXDo0CFuRkBEVE8ymQw7d+5ETEwMcnJyYGNjg/Hjx2PWrFk1ZjW0DceGhNagxY6hoSEKCgqqHcb5XHl5uXz3J2Xq1q0b5s2bhxkzZsgP9dy8eTMKCwuxatUqpfa1evVqZGVl4dKlS0hOTpa3V1ZW4uTJkzhw4ABiY2PRvn17+Pr64p133lFq/6QZVq5ciY8//hhdu3at8c7OqVOnGqTPyMhI+de3bt1CdHQ0goKCYGVlVe0+VRRbRERERA2lQYudLl264JNPPsGQIUNqXIuLi8OSJUtw5coVpfZpbGyM4uLiaod6ymQy2NjY4N69e0rtqzbTp09HbGwsnJyc4Ovri4kTJ8LR0bHB+6XGy8TEBMnJyWjbtq3K+hwwYMC/3tOQxRYRkaYS4tiLxoJjQ0Jo0Hd25s2bh+nTp2Pnzp3w9vaGjo4OZDIZjh8/jrfffhsrV65Uep82NjbIycmBra0tWrVqhZMnT6Jly5aQyWQKPzsvLw8//PADcnJy8O677yIrKwsymQwODg7ye1xcXHDu3Dm0bt1a4f5IO0gkkhozKg2tIbd8JyLSZspenq9JODYkhAbfenrNmjVYt24dKioqYGFhgQcPHkBPTw8hISF47733lN7f7t27YWNjg6FDh+Lw4cOYNGkSKioq8MknnyA4OLjez42Li8OUKVPw2muvIS4uDg8fPkRiYiLWrl2LEydOKO8HIK3z6aef4sSJE5g/f36Nd3bc3d1VkuHPP/+ssZ6aBTsR0asT4tiLxoJjQ0JQyTk7xcXF+PXXX5Gfnw9zc3P06dMHJiYmDd0tgGfvBj158gRGRkYKPadjx44IDw+Hm5ub/F2g8vJy2NnZQSKR4OLFiwD++dRgnhRMtWnVqlWt7SKRCKmpqQ3e/7fffou3334bI0eOlO+Uc/ToUWzdupW75RARvaLMzMwGPVajMePYkBA09lDRhw8f1tj8wNbWtt7Ps7CwQF5eXrV3gSoqKiCRSHDw4EH07dsXQPVTg//O09Oz3v0TNRQnJydERUWhT58+8rZz587B19eXSw6IiF7C6dOn4ejoCEdHR+Tm5iIkJAS6urpYs2aNypcpqxuODQlNR+gAynby5Ek4OTnBzMwMdnZ28n8U/SShd+/e2L59e7W2sLAweHh4yAsdAMjOzoanp2eNf3JychTqn6ihlJWVoWfPntXaunfvjrKyMoESERE1LrNmzYKOzrNfqd555x1UVFRAR0cHQUFBAicTHseGhKZxMzvOzs5Yvnw5AgICaj3fp74yMzPh4+ODsrIypKamokOHDvLNFl4spIyNjfHw4cMa3/98NohI3ezcuRPJyclYtWoV7OzskJmZiQ8//BA9e/bErFmzhI5HRKT2nv+/v7y8HFZWVrh79y709PRgbW2N/Px8oeMJimNDQmvQ3diEUFxcjBkzZsg/RVAWe3t7XLx4EefPn4dUKoVEIoGbm5v8QKykpCQAz87Y+fXXX/FiDZmeno4WLVooNQ+RssybNw+VlZXYs2ePvK2qqgp79uzBvHnzUFVVBZFIhPLycuFCEhGpMbFYjNTUVFy7dg09evRA8+bNUVZWxsPEwbEh4WlcsRMcHIxNmzZh8eLFSn3u2rVr4efnBzc3N7i5udW4PnnyZADPlgS9eBCjSCSClZUVtmzZotQ8pBmeFxkBAQFo2rSpIBn+/PNPQfolItIUK1asQPfu3aGjo4OoqCgAwM8//4yuXbsKnEx4HBsSmkYsY3txB7Sqqiqkp6fD0NAQLVu2rHafIruhTZ8+HYcPH4azs/M/HhY6c+ZMfPXVV/Xuh7TP8939iIio8Xr8+DEAoHnz5gCA+/fvQyaTwdraWshYaoFjQ0LSiGLnn3ZAe5Giu6FVVFQgLi4O3333HY4ePYr27dvD19dXofN7iGbPng0PDw+88cYbKutz0KBBdW6R/qKTJ0+qIA0RUeP2fCl7bVR1Xpq64tiQ0DSi2KlLYWEhzMzMGuTZaWlpmDlzJuLj49GlSxees0P15uXlhcTERLi4uMDOzq7an5+GKjYiIiJe6r6pU6c2SP9ERJrk7+elPXjwAE+ePIGdnZ1KzktTZxwbEprGvbNTVFSE+fPnIyYmBk+ePEHTpk0xYcIEfPbZZxCLxQo9Oy8vDzExMThw4AAuXbqE4cOH4+DBgzA3N5ff8/XXXyv6I5CWmTp1qsqLChYxRETKk5aWVu3fKysrsX79eujp6QmUSH1wbEhoGjezM2rUKBgaGiI0NBT29vaQSqVYvXo1iouLERsbW+/nenl54ffff8fgwYPh6+uLESNGvNTW1uXl5RCJRPyPmtTa5cuXcfbsWeTn51fbSXDFihUCpiIiarwqKythbW2NvLw8oaOoHY4NqZLGHSr6yy+/IDw8HC4uLtDX10fr1q2xa9cunD59WqHnzpgxA9nZ2YiJicGECRPqLHTeffdd/P777wCAY8eOwdTUFGZmZjh27JhC/ZPmqqioQGhoKFxdXWFiYgJXV1eEhoaqbKvnrVu3wtPTE4mJiVi7di1u3LiBjRs3cpc2IqJ6evr0KaKiouQv5NP/x7EhVdO4ZWzdu3fH1atXq50If/36dXTr1k2h5z7fWvrf7N27F6tWrQIArFy5Evv374eJiQnmzJmDESNGKJSBNNPixYtx4cIFbN68GY6OjsjIyMCaNWuQn5+PzZs3N3j/GzduxKlTp9CjRw+YmpoiMjISZ86c4XbpREQvSU9Pr9r7lpWVlbCxscGuXbsETKUeODYkNI1bxjZ//nzs27cPo0ePhr29PTIzM3HkyBFMnjy52haHISEh//ossViMgoICADX/YwVQ62GLJiYmKC4uRm5uLrp164bc3FwA//8EYaK/k0gkuHbtWrXNNAoKCtCpUydkZ2c3eP/P/8wCgKWlJbKysqCvr1+tnYiI6paRkVHt31u0aAELCwuB0qgXjg0JTeNmdkpKSjBq1ChUVVVBKpUCAEaOHImSkhKUlJQAwEttuQs8e4/huZdd0tOlSxds2LABGRkZ8Pb2BgDk5OTA0NDwVX4M0iK6urooKyur1lZWVgYdHdWsMm3Xrh0uXbqEbt26oVu3bli7di1MTU1rnFNFRES1q+3cPXqGY0NC07hiZ/fu3Up7lr29vfzrqKgoLFu2rMY9H3/8MZYuXSr/9/DwcKxYsQJ6enr4+OOPATzbY16VZ6hQ4xIYGIjBgwdj8eLFcHBwgFQqxcaNGzFjxgyV9L9161b5159//jnmzp2LkpISLjEgInpJ6enpWL16NS5fvoxHjx5Vu6btx05wbEhoGrGM7Z8OrHqRIodX1bUM7cWlbkT1UVVVha+//hoHDhxAdnY2bG1t4evrixkzZqhsdoeIiOqvZ8+e6NatG8aPH19jAyNFDzRv7Dg2JDSNKHb+fmBVbUQiUb0Or4qMjAQABAUFISwsrNq2vOnp6di9ezdu374tb6uoqMC6desQFRUl/8XV398fy5Ytg76+/iv3T5rv7Nmz8PDwqNGelJTE06WJiBoBU1NTFBQU8AOqWnBsSGgaUew0pAEDBgAAzpw5g379+snbRSIRLC0tMW/evGq/qL7zzju4cOECVqxYUW1nre7du6tkZy1qfDhrSETUuL311lt4/fXXMW7cOKGjqB2ODQmNxc5LWrNmDd5///1/vU/onbWo8Xj+56Ft27a4fft2tVnDtLQ0jBs3Tr6bHxERqa979+6hT58+MDY2hqWlZbVrJ0+eFCiVeuDYkNA0boOCzMxMzJ8/H4mJiTU+Fa+srKz3c58XOo8fP65xyryDg4P8a6F31qLGw87ODiKRCFVVVZBIJNWuWVlZYeXKlQIlIyKiVzF+/Hi0adMGY8aMqfPQcW3FsSGhaVyxM3PmTNjZ2SExMRFubm44f/48PvzwQ/Tt21eh5167dg1vvPEGrly5Im8TiUTQ19fH48eP5W1C76xFjYdMJgMADBkyBHFxcQKnqS40NBR9+/aFl5eX0FGIiNTepUuXUFhYiCZNNO7XKoVxbEhoGreMTSwWIycnB02bNoWpqSmKiorw6NEjdO3aFXfu3Kn3cz08PDBo0CAsW7YMNjY2yMnJwYoVK+Di4oJZs2bJ7+POWvSqCgsLoa+vjxYtWsjb/vrrL1RUVMDU1FSQTAMGDEBWVhasrKyQmJgoSAYiosZi/PjxWLhwITeVqQXHhoSmccWORCLBzZs3YWhoiDZt2uDHH3+EWCyGo6NjrS+BvyxTU1Pk5+dDV1cXZmZmKCwsRHl5OZydnZGVlaXEn4C0Te/evbFz505069ZN3nbx4kXMmTPnpbdVbyi5ubmwtrYWNAMRkbqbPHkyYmNjMXDgwBrvpWj7mWUcGxKaxs0pjhs3DidOnMDEiRMxbdo0eHp6Ql9fHyNHjlTouaampiguLoZYLIZEIsHFixdhYWFR44As4NnBpgcOHEBOTg5sbGzg6+uLadOmQSQSKZSBNNP169erFToA0L17d/zxxx8qzSGVSnH37l306dNH3sZCh4jo37Vt2xaLFy8WOoZa4tiQ0DRuZufvTp8+jZKSEgwdOhS6urr1fs66devg6uqK0aNH46uvvsKCBQugq6uLWbNm4eOPP5bft2TJEvzwww9YsGAB7O3tkZmZic8//xxDhgzBp59+qowfiTRM27ZtceTIEbi6usrbUlJSMGLECIWWXr6s1NRU+Pn5IT09HaWlpSgpKcH333+P2NhYRERENHj/RESNXXl5Oc/SqwPHhoSm8cVOQ8nIyMCjR4/QsWPHau0tW7bE1atXq30inpOTgy5duiAvL0/VMakR2LJlC7744gssW7YMrVq1Qnp6OjZs2IA5c+Zg/vz5Dd6/l5cXxo0bhzlz5siXaJaUlKBDhw7IzMxs8P6JiBo7MzMzjBkzBpMnT4aXlxdXcryAY0NCY7GjZO3atUNiYiJatmwpb7t//z769euHmzdvCpiM1Nm3336LiIgIZGVlwd7eHtOmTYO/v79K+jYzM0NBQQFEIpH8INOqqiqYm5vzUFMiopeQlpaG/fv3IyoqCg8ePICvry8mTZqEXr16CR1NcBwbEhqLnZekp6dX66cRTZs2hUQiwejRo/HBBx9g+/bt2L9/P4KDg2FnZ4fMzEx88cUXmDhxIjw8POTfx11JSF307NkTW7Zsgbu7u7zYSUxMxJIlS/Drr78KHY+IqFH5448/EBUVhcjISDRp0gT+/v4IDAyEk5OT0NEEx7EhIWjcBgUN5bPPPsOxY8ewdOlSeRGzceNGDB48GB06dEBoaCjmz5+PU6dOAQBWrFhR7fu3b9+O7du3A3h2Pk9qaqrKfwZSTzKZDDt37kRMTAzy8vJw9epVnD59GllZWZg0aVKD979x40aMHj0aY8eORVlZGYKDgxEdHY39+/c3eN9ERJqksrISUqkUGRkZKC4uRt++fVFQUAA3NzfMmTOnxu8G2oRjQ0LhzM5LcnZ2xuXLl2FkZCRve/jwIbp27Yq0tDTk5uaia9euuHfvnoApqTFasmQJ/ve//2HhwoUICAhAYWEhMjIyMHLkSFy+fFklGTIzMxEZGQmpVAqJRIJJkybxkzYiopd0+vRpREZG4vvvv0e7du0wefJk+Pr6QiwWA3i2jX/btm0VOgKjseLYkNC0YmZHR0cHHh4eWLFiBQYNGlSvZ/z111/Iz8+vVuzk5+fjr7/+AgBYWFigrKys2vesX78ey5Ytq39w0gr79u3DzZs3YWxsLG9zdHRERkaGSvpPSkqCu7s73n33XZX0R0Skad58800EBATg/PnzaNWqVY3r1tbWWLdunQDJhMexIaFpxcxOQkICsrKykJiYiB07dtTrGaGhoQgPD0dQUBDs7Oxw9+5dhIWFYdq0aVixYgWOHDmCzz//HPHx8fLvMTY25icV9K+cnJzwv//9D2KxWP7OTG5uLjw8PFSy9bSLiwuePn2KCRMmwM/PDz179mzwPomIiIhUQSuKHWU5evQoDh48KD9VfuzYsfDx8anzfiMjI5SUlKgwITVGK1euxNmzZ7FmzRoMGzYM8fHxeO+99+Du7o733ntPJRnOnz+P6OhoREdHQ1dXFxMnTsTEiRPRvXt3lfRPRNSYVVRUIDIyEpcvX65x2PiuXbsESqUeODYkNI0sdk6cOIHo6Gjk5eXh2LFjSE5ORlFRUb2XsNXXunXrsHz5cpX2SY2PTCbDxo0bER4eDqlUCjs7OwQGBmLJkiUKHYRbX+fOncP777+P+Ph4VFZWqrx/IqLGxt/fH1evXoW3tzeaN29e7drKlSsFSqUeODYkNI0rdjZs2IB9+/Zh9uzZeO+991BUVIQbN25g6tSp+O233+r93NLSUqxcuRLR0dHIz8/Hw4cPERcXh5SUFAQHB9f6PU+ePAHwbHtqohctXLgQmzZtAgDExsZi5MiRAicCUlJScODAARw4cAAlJSWYMGECPvvsM6FjERGpPRMTE2RmZlZ795Ke4diQ0HSEDqBs27Ztw08//YQ5c+bIz8Vp164dbt++rdBz3377bWRnZ+Po0aPyT9u7dOmCnTt3Ani2tfStW7cAANnZ2Xj99dfRokULGBoaYvDgwcjJyVGof9Is4eHh8q8DAgIETPLsfbROnTphwIAByMvLw5dffonMzEwWOkREL4m7idWNY0NC07iZHYlEgj///BMGBgbyl72Li4vRuXNnSKXSej/X0tISmZmZaNq0qfy5AGBqaoqioiLY2Njg9u3bMDQ0xNixY2Fvby+fnv3www9x584dxMbGKuVnpMZv2LBhePz4Mdq1a4c9e/Zg2rRptd6nivXMM2fOhK+vL7y8vKCjo3GffxARNYjIyEj517du3UJ0dDSCgoJgZWVV7T5VnJembjg2pE40rtiZO3cuioqK8Omnn6JDhw5IS0vDggULYGJiotAn1W3btsWpU6dgZ2cnL3ZSU1Ph7e2NlJQUGBkZoaioCLq6urCyskJmZib09fUBPHs5z8rKSl4gEZWWliImJgZSqRShoaEICQmp9T6uZyYiUk8DBgz413tEIpH8sHFtwrEhdaJx5+x8+umnWLRoEVxcXFBaWgobGxtMnTpV4T3c33nnHXh7e2P58uWorKzE4cOH8dFHH8nf13F3d0d0dDT8/Pzg4uKCa9euoUePHgCevQthYmKi6I9GGuTLL7+U/9kRiUR1FjsNZdSoUThy5AgAYNCgQfIln3938uRJVcYiImo0Xjxqgqrj2JA60biZnRfl5eXBwsKizl/kXlV0dLR8xyyJRILp06fDz88PwLNp2uHDh8PDwwNmZmbYu3cvxowZA5FIhNjYWGzbtg0TJkxQSg5q/ExMTFBcXAxAmPOYIiMj5csHIiIi6rxv6tSpqopERNRo1fX3+IvL3rUVx4aEpnHFzuDBg+Hn54exY8fC1NRUpX0/efIEu3fvxvnz53H37l0YGBigU6dOCAgIQPv27VWahdSbu7s7nJ2d0aFDB4SGhmLFihW13qeKGZ+zZ8/Cw8OjRntSUhLc3d0bvH8iosautnP1Hj9+DHt7e+Tn5wuUSj1wbEhoGreMLSAgAAcOHMD8+fPh6ekJX19fjB49WilbHiYkJNR6KNbzX0ibNm2K2bNnY/bs2Qr3RZrt0KFD2LVrF9LS0iCTyWrdLVBZM5L/ZtiwYbV+6jZixAh+6kZE9A/atGkDkUiE0tJStG3bttq1vLw8jBo1SqBkwuPYkLrQuJmd5woLC3Hw4EFER0fj7NmzGDhwIA4fPlzv582bNw/fffcd+vfvX+1QLJFIVG0b4drIZDLs27cPU6ZMqXf/pLneeust7NixQ+X9ZmdnA3i2+cbt27fx4l8FaWlpGDduHHJzc1Wei4iosUhISEBVVRWGDx+OH374Qd4uEolgaWmp1as6ODakLjS22AGe7XgVGxuL7du349y5c/JDPutDLBbj6tWrkEgkr/y9T548QfPmzXkaPdUpLy8PP/zwA3Jzc7F06VJkZWVBJpPBwcGhwfrU0dGBSCRCbX8FWFlZYcWKFXjrrbcarH8iIk0hk8m4dX8dODYkNI1bxlZWVobjx4/jwIEDiIuLQ8+ePTF58mQcPHhQoedaW1tXm9H5u9DQ0DqvVVRUKNQ3aba4uDi88cYb8PT0RFxcHJYuXYr09HSsXbsWJ06caLB+ZTIZAGDIkCGIi4trsH6IiDQdf5mvG8eGhKZxMzvGxsbo2rUrJk6ciAkTJsDa2lopz920aROOHDmC4ODgGodiubu7Q19fH+PHj691i+nKykqEhYVxZodq1bFjR4SHh8PNzQ1mZmYoLCxEeXk57OzscP/+faHjERERETVaGlfsZGVlwc7OTunPbdWqVa3tIpEIqamp+M9//oPVq1djxIgRNe4pKytD8+bN5Z+kE73IwsICeXl5EIlE8q04KyoqIJFIGqzY4Tk7REREpA00Yhnbb7/9Bjc3NwCAVCqFVCqt9T5FttFNS0v7x+szZ86ss5jR09PDypUr6903abbevXtj+/btmDNnjrwtLCys1u2glcXX11f+dUBAQIP1Q0SkTaRSKe7evYs+ffoIHUXtcGxIKBoxs9OpUydcu3YNwL/PwCjD+vXrsWzZMqU8iygzMxM+Pj4oKytDamoqOnToAJlMhuPHj8Pe3l7oeERE9C9SU1Ph5+eH9PR0lJaWoqSkBN9//z1iY2P/8eBmbcCxIaFpRLGjav904n1+fj6Sk5NRWFgIMzMz9OrVC+bm5ipOSI1NVVUVzp8/D6lUColEAjc3N+jq6qqk782bN6N///7o2rUrzp07B39/fzRp0gTffPMNevfurZIMRESNmZeXF8aNG4c5c+bI370sKSlBhw4dkJmZKXQ8QXFsSGgaV+x4e3vj+PHjNdpHjhyJ2NhYpfRR22nAwLPDRTdu3AiZTAYLCws8ePAAurq6CA4Oxvr165XSN5Gy2dvb49q1azAxMcFrr70GX19fGBoaYuvWrUhOThY6HhGR2jMzM0NBQUG1dy+rqqpgbm6u9Yczc2xIaBq3H+CZM2dqbU9MTFRaHyEhITXaIiIiEBERgZiYGJSVlSEnJwdlZWWIjo7Gvn37sGfPHqX1T6RMDx8+hImJCQoLC/HHH3/grbfewtSpU3Hr1i2hoxERNQouLi749ddfq7WdPXsW7dq1EyiR+uDYkNA0YoMCAHjzzTcBPDvA8/nXz2VkZCj1pN6FCxfiyZMnaNq0qbwtLCwMX3zxBXx8fORturq68PHxQUVFBT777DNMmzZNaRmIlMXFxQVRUVH4888/8frrr0NHRwcFBQXQ19cXOhoRUaOwceNGjB49GmPHjkVZWRmCg4MRHR2N/fv3Cx1NcBwbEprGzOxIJBJIJJJqX0skEtjZ2WHMmDH1XsK2fft2+Sfc2dnZeP3119GiRQsYGhpi8ODByMnJAQBcu3YNgwYNqvUZgwYNkm+gQKRuduzYgS1btuCnn37CmjVrAAA//vgjhgwZInAyIqLGwdPTExcuXECrVq0QGBgIS0tLnD17Fv369RM6muA4NiQ0jXtnJyEhAZ6enkp7no2NDW7fvg1DQ0OMHTsW9vb28m2kP/zwQ9y5cwexsbEwMTFBcXFxnc/5p00NiIiIqPFKSkpS6HgLTcaxIaFpRLHz4jk7SUlJdd5Xn//YjIyMUFRUBF1dXVhZWSEzM1O+vKeiogJWVlYoKCiAgYEBwsPDUddwBgUF4fHjx6/cP5Eq7N27F1FRUcjOzoatrS38/f0xZcoUoWMRETUKLi4uePr0KSZMmAA/Pz/07NlT6Ehqg2NDQtOId3ZmzJghXyY2efLkWu+p7zk77u7uiI6Ohp+fH1xcXHDt2jX06NEDAJCSkgITExMAgJubG3bt2lXnc54XY0Tq5sMPP8S+ffuwaNEiODo6QiqVYt26dcjIyMAHH3wgdDwiIrV3584dnD9/HtHR0Rg/fjx0dXUxceJETJw4Ed27dxc6nqA4NiQ0jZjZaUi3bt3C8OHD4eHhATMzM+zduxdjxoyBSCRCbGwstm3bhgkTJggdk6jenJyccObMmWoHmGZmZsLDwwNSqVTAZEREjdO5c+fw/vvvIz4+HpWVlULHUSscG1I1jdmg4LmCggL5crHKykrs3bsXkZGRdS4v+zdt27bFH3/8gT59+uDhw4fo1asX8vPzYW1tjdOnT8sLHalUWuf20nv27OHBWaS2njx5Ip+hfM7IyAjl5eUCJSIiapxSUlKwatUqBAYG4saNG5g/f77QkdQGx4aEonEzO25ubvjyyy/RrVs3LF26FD/++CP09PTQr18/fP755w3Wb2BgIDw8PBAUFFTj2u7du3H69Gns3r27wfonqq85c+bI/ydkb28PqVSKDz/8EO3atcO2bduEjkdEpPZCQ0Px3Xff4cGDBxg3bhx8fX3Rr18/iEQioaMJjmNDQtO4YufFk3ptbW2RnJyMFi1awNXVVb5NtLLIZDLs27cPU6ZMgZOTE1JSUmBgYFDjvtLSUrRv3x4ZGRlK7TSFUToAABzGSURBVJ9IGZ48eYLQ0FAcOHBAvkGBr68vPvjgAzRr1kzoeEREam/mzJnw9fWFl5cXdHQ0btGMQjg2JDSNK3ZatmyJ9PR0XL9+HW+++SYuXryIyspKmJmZKX3r5ydPnqB58+aorKyEoaFhnQcxlpeXQywW49GjR0rtn4iIiIiI6qYRu7G9yN/fHwMGDEBJSQlmz54NALh48SKcnJzq9bzQ0NA6r1VUVMi/dnZ2Rnx8fK0HMcbHx8PZ2ble/ROpQnx8PA4cOICcnBzY2NjA19cXAwYMEDoWEZHaGjVqFI4cOQLg2eHhdS3LOnnypCpjqQWODakTjSt2Nm/ejJMnT0JPTw9eXl4Anm07Xd/3ddasWYPx48fXeIEbQLVdRObNm4fp06dj586d8Pb2ho6ODmQyGY4fP463335bfhApkbr59NNPsWnTJsyYMQM9evRAZmYmAgICEBwcjCVLlggdj4hILfn6+sq/DggIEDCJ+uHYkDrRuGVswLN3aZKTk+XvH/Ts2RO6urr1etZ//vMfrF69GiNGjKhxraysDM2bN4dMJgPwrDBat24dKioqYGFhgQcPHkBPTw8hISF47733FPqZiBqKra0t4uPj0a5dO3nbzZs30b9/f6W/50ZERESkSho3s3Pjxg2MHDkSpaWlsLOzQ2ZmJpo3b47Dhw+jQ4cOr/y8mTNnyouZv9PT06s2Y/P+++9j3rx5+PXXX5Gfnw9zc3P06dOn1lkhInWhp6cHOzu7am22tra1vn9GRES1u3z5Ms6ePYv8/Pxqx12sWLFCwFTqgWNDQtK4mZ0BAwbA29sbixYtkq8R3bRpE44cOYKEhASB0xGpn61bt+L48eMICQmRf0CwYcMGDB8+HGPGjJHfZ2trK2BKIiL1tXXrVrz//vsYPnw4Dh06hDFjxuD48eMYNWoU9u7dK3Q8QXFsSGgaV+yIxWLk5eVVW7ZWWVkJCwsLFBYW1vu5+fn5SE5ORmFhIczMzNCrVy+Ym5srIzKRoF5mK1CRSMSTromI6tCqVSt8//336NGjB0xNTVFUVIQzZ85gy5YtiI6OFjqeoDg2JDSN2/DcyckJx44dq9Z24sSJeu/GBgAhISGwtbWFj48PFi5cCB8fH0gkEixbtkzBtETCk8lk//oPCx0ioroVFBSgR48eAAB9fX2Ul5ejX79+3G0MHBsSnsa9s7N582aMGjUKXbt2hYODAzIyMnDlyhUcPny4Xs+LiIhAREQEYmJiMHz4cOjq6qKyshInTpzAW2+9hfbt22PatGlK/RmIhBIVFQV/f3+hYxARNSrt2rXDpUuX0K1bN3Tr1g1r166FqakpWrZsKXQ0wXFsSGgat4wNePYpwokTJ+S7sQ0bNqzeS85ee+01BAcHY+zYsTWuHTx4EJ999hnOnDmjaGQitWBsbKz0w3eJiDTd+fPnoa+vj27duuH69euYO3cuSkpKsGHDBvkxGNqKY0NC08hiBwByc3PlByRaW1vX+zlisRgZGRkwMjKqca2kpAQODg4KvQtEpE6MjIxQUlIidAwiIiIipdC4ZWwZGRmYMmUKfvvtN4jFYuTn58PNzQ3ffPMNHB0dX/l5lZWVtRY6wLNfDPkuA2kSHv5GRFQ/aWlpuHr1Kh49elStfdKkSQIlUh8cGxKSxs3s9O/fH25ubli1ahUMDAxQWlqK1atXIykpCadPn37l5xkYGCA8PBx1DVNQUBAeP36saGwiIiJqpNavX4/Vq1ejS5cuaN68ubxdJBLh1KlTAiYTHseGhKZxxY6xsTEKCgrQpMn/n7SqqKiAWCyu1/Kc/v37y8/rqUt8fPwrP5dIaLm5uVi0aBGuX7+OIUOG4IMPPsCUKVNw6tQpdO7cGWFhYWjTpo3QMYmI1J6lpSXi4+PRsWNHoaOoHY4NCU3jlrENHDgQP/30E4YNGyZv+/nnnzFo0KB6Pe+XX35RUjIi9TJr1iyIxWKsXbsWUVFR8PT0RL9+/ZCYmIiwsDDMmTOHW4MSEb0EQ0NDODs7Cx1DLXFsSGgaN7MzadIkHDx4EO7u7rC3t0dmZiaSkpIwbtw4tGjRQn7frl27Xup5UqkUp06dqnV76T179mDgwIGwt7dXVnwilTE3N8e9e/fQpEkTlJaWwsTEBCUlJWjatCnKy8thY2OD/Px8oWMSEam9nTt3Ij4+HsuXL4elpWW1a7a2tgKlUg8cGxKaxhU7q1evfqn7Vq5c+VL3BQYGwsPDA0FBQTWu7d69G6dPn8bu3btfKSOROrC1tUVycjIkEgnS09Ph7OyMBw8eQCwWo7CwEK6ursjNzRU6JhGR2tPRqf2MdpFIpPUbGXFsSGgaV+wom5OTE1JSUmBgYFDjWmlpKdq3b4+MjAwBkhEp5r333sO3336Lfv364datW+jVqxdSUlLg5+eH7777Do6Ojvj666+FjklERERUbxpd7HTu3BlXr15V6BmGhoYoKCiAvr5+jWvl5eUQi8U1tlIkaiy+//57ZGRkYPz48bC2tsaqVatw5coV9OzZE++++26tRT4RERFRY6HRxY4yToPv0qULPvnkEwwZMqTGtbi4OCxZsgRXrlxRqA8iIiIiIlK+2hdSaghl1HHz5s3D9OnTcfToUchkMgCATCbD0aNHERQUhPnz5yvcB5FQ7t69i0WLFqF3795o164devfujcWLFyMrK0voaEREREQK07itp190/fp1hZ8xc+ZM3Lt3D35+fqioqICFhQUePHgAPT09hISE1LpxAVFjIJVK0bNnTzg4OMDHxwfW1tbIycnB8ePHsXfvXiQnJ8PR0VHomERERET1plHL2G7evIkbN26gd+/esLKywqVLl5CQkIDOnTvDy8tLoWcXFxfj119/RX5+PszNzdGnTx+YmJgoKTmR6s2cORPl5eWIiIiocS0wMBC6urrcoICIiIgaNY0pdsLCwrBgwQK4uroiMzMTGzZswLJly+Du7o4zZ85g8eLFWLx4sdAxidSGi4sLTp48CRcXlxrX/vzzTwwePBipqakCJCMiIiJSDo0pdlq3bo3o6Gh0794d58+fR9++fXHhwgV07twZ169fh7e3N9LS0oSOSaQ2jI2NUVxcDJFIVOOaTCaTHzJKRERE1FhpTLFjYmKC4uJiAEBlZSWaNWuG8vJy+S9yL14non/frVAZuxkSERERCUljNijo3LkzPvroI/j5+eGbb76Bvb09Dh8+jDFjxuDo0aNwdnYWOiKRWvnrr7/Qtm3bWq9VVVXh8ePHKk5EREREpFwaM7Nz+fJlvPHGG8jIyMC8efMwdOhQeHt7w9DQEI8fP8Z3332HQYMGCR2TSG0kJCT86z2enp4qSEJERETUMDSm2KlNYWEh7ty5g7Zt28LY2FjoOEREREREpEIad6hofn4+fvzxR0RFReH8+fNo1aoVCx2iWuzevRuTJ0+u9VpAQECtW1ITERERNSYaNbMTEhKCjRs3QiaTyQ//1NXVRXBwMNavXy90PCK10qtXL0RERKBDhw41rqWkpGDKlClITk4WIBkRERGRcmjMzE5ERAQiIiIQExODsrIy5OTkoKysDNHR0di3bx/27NkjdEQitXLnzp1aCx0AcHV1xZ07d1SciIiIiEi5NKbYCQsLwxdffAEfHx/o6uoCAHR1deHj44MtW7YgLCxM4IRE6kVXVxe5ubm1XsvJyYGOjsb89UBERERaSmOWsYnFYmRkZMDIyKjGtZKSEjg4OKCwsFCAZETqadKkSTA0NMSuXbtqXJs9ezYePnyIyMhIAZIRERERKYfGFDv/dmgoD0gkqk4qlaJPnz6wtrbGqFGjYG1tjdzcXMTGxiI3NxdJSUlwcHAQOiYRERFRvWnMoaLl5eWIiopCXbXb06dPVZyISL05ODjg0qVL2LRpE06cOIH8/HyYm5tj8ODBWLBgAVq2bCl0RCIiIiKFaMzMTv/+/SESif7xnvj4eBWlISIiIiIioWlMsUNERERERPQijdluSSqV1rm99J49e5CZmanaQEREREREJCiNKXZWrlxZ53s5VVVVWLFihYoTERERERGRkDRmGZuTkxNSUlJgYGBQ41ppaSnat2+PjIwMAZIRqbdz586hd+/eQscgIiIiUjqNKXYMDQ1RUFAAfX39GtfKy8shFovx6NEjAZIRqTdnZ2eIRCL4+/tj0qRJ6NChg9CRiIiIiJRCY5axOTs717nbWnx8PJydnVWciKhxSE1Nxb59+/Dw4UMMHDgQ3bt3xyeffIKsrCyhoxEREREpRGOKnXnz5mH69Ok4evQoZDIZAEAmk+Ho0aMICgrC/PnzBU5IpL769OmDLVu24O7du9iwYQP27t0LJycneHp6Yu/evaisrBQ6IhEREdEr05hlbACwZs0arFu3DhUVFbCwsMCDBw+gp6eHkJAQvPfee0LHI1Jrly5dQlRUFPbv3w8LCwsEBATAwcEBO3bsQLNmzXDs2DGhIxIRERG9Eo0qdgCguLgYv/76q/w0+D59+sDExEToWERqa/Xq1YiKikJ5eTn8/f0REBAAV1dX+fUnT57A3Nyc77wRERFRo9NE6ADKZmJigqFDhwodg6jRyM7OxldffYV+/frVer1p06Y4e/asilMRERERKU7jZnaI6OVVVlaiTZs2SElJQdOmTYWOQ0RERKRUGrNBARG9Ol1dXTRr1gwlJSVCRyEiIiJSOo1bxkZEryYwMBAjR45EcHAwJBIJRCKR/Jq7u7uAyYiIiIgUw2VsRFquVatWtbaLRCKkpqaqOA0RERGR8rDYISIiIiIijcRlbESE4uJi/Pjjj8jOzoatrS2GDRsGY2NjoWMRERERKYQzO0RaLikpCT4+PmjXrh0cHR0hlUpx48YNHD16lO/sEBERUaPGYodIy/Xq1QtLlizBxIkT5W3R0dHYsGEDfv/9dwGTERERESmGxQ6RljMzM8ODBw+gq6srb6usrISFhQUKCwsFTEZERESkGJ6zQ6TlOnfujJ07d1Zr+/LLL9GxY0eBEhEREREpB2d2iLTc9evX4ePjg6qqKtjb2yMzMxMAEBsbi06dOgmcjoiIiKj+WOwQESoqKnDu3Dnk5OTA1tYWbm5u0NPTEzoWERERkUJY7BARERERkUbiOztEWu5///sf+vfvD7FYDH19fejr60NPTw/6+vpCRyMiIiJSCGd2iLRcu3btMHnyZEycOBEGBgbVrjk6OgqUioiIiEhxLHaItJyFhQXu378PHR1O9BIREZFm4W83RFpu7ty52LJli9AxiIiIiJSOMztEWu7OnTt4/fXXUVxcDAsLi2rXbt26JVAqIiIiIsU1EToAEQlrzJgxGDhwIMaPH1/jnR0iIiKixowzO0RazsTEBIWFhXxnh4iIiDQOf7sh0nL+/v44dOiQ0DGIiIiIlI4zO0RabuDAgUhMTISrqyssLS2rXTt58qRAqYiIiIgUx3d2iLTclClTMGXKFKFjEBERESkdZ3aIiIiIiEgj8Z0dIi1XWlqKpUuXolWrVjA2NgYAxMXF4fPPPxc2GBEREZGCWOwQabm3334b2dnZOHr0KHR1dQEAXbp0wc6dOwVORkRERKQYLmMj0nKWlpbIzMxE06ZNIRaLUVBQAAAwNTVFUVGRsOGIiIiIFMCZHSItZ2pqiry8vGptqampsLGxESgRERERkXKw2CHScu+88w68vb2xf/9+VFZW4vDhw/D19UVwcLDQ0YiIiIgUwmVsRITo6GiEh4dDKpVCIpFg+vTp8PPzEzoWERERkUJY7BARERERkUbioaJEhISEBFy+fBmPHj2q1h4SEiJQIiIiIiLFsdgh0nJvv/02Dh06BE9PTxgYGMjbRSKRgKmIiIiIFMdlbERazszMDDdv3oSlpaXQUYiIiIiUiruxEWm51q1b4+nTp0LHICIiIlI6zuwQablbt25h/vz5GDp0aI3ZnUmTJgmUioiIiEhxfGeHSMt9++23SEhIQFFRUY13dljsEBERUWPGmR0iLWdiYoLk5GS0bdtW6ChERERESsV3doi0nEQigZWVldAxiIiIiJSOy9iItNz06dMxZswYzJ8/v8Y7O+7u7gKlIiIiIlIcl7ERablWrVrV2i4SiZCamqriNERERETKw2KHiIiIiIg0Et/ZISIiIiIijcRih4iIiIiINBKLHSIiIiIi0kgsdoi0WGVlJcLCwvDkyROhoxAREREpHTcoINJyZmZmKCwsFDoGERERkdJxZodIy/n6+uKbb74ROgYRERGR0nFmh0jLeXl5ITExES4uLrCzs4NIJJJfO3nypIDJiIiIiBTTROgARCSsqVOnYurUqULHICIiIlI6zuwQEREREZFG4js7RFquoqICoaGhcHV1hYmJCVxdXREaGory8nKhoxEREREphMvYiLTc4sWLceHCBWzevBmOjo7IyMjAmjVrkJ+fj82bNwsdj4iIiKjeuIyNSMtJJBJcu3YNZmZm8raCggJ06tQJ2dnZAiYjIiIiUgyXsRFpOV1dXZSVlVVrKysrg44O/3ogIiKixo3L2Ii0XGBgIAYPHozFixfDwcEBUqkUGzduxIwZM4SORkRERKQQLmMj0nJVVVX4+uuvceDAAWRnZ8PW1ha+vr6YMWMGZ3eIiIioUWOxQ6Tlzp49Cw8PjxrtSUlJcHd3FyARERERkXKw2CHScsbGxnj48GGNdrFYjIKCAgESERERESkH39kh0lLPd1qTyWTIycnBi597pKWlQV9fX6hoRERERErBYodIS9nZ2UEkEqGqqgoSiaTaNSsrK6xcuVKgZERERETKwWVsRFpuyJAhiIuLEzoGERERkdKx2CHScoWFhdDX10eLFi3kbX/99RcqKipgamoqXDAiIiIiBXFfWSItN2zYMNy+fbta261btzB8+HCBEhEREREpB2d2iLRcXbuxmZiYoLi4WIBERERERMrBmR0iLWdtbY2UlJRqbSkpKbCwsBAoEREREZFycDc2Ii03d+5cjBw5EsuWLUOrVq2Qnp6ODRs24J133hE6GhEREZFCuIyNiPDtt98iIiICWVlZsLe3x7Rp0+Dv7y90LCIiIiKFsNghIiIiIiKNxHd2iLScTCbD9u3b4eXlhc6dOwMATp8+jcjISIGTERERESmGxQ6Rlnv33Xfx/fffY9GiRcjKygIAODo6YsOGDQInIyIiIlIMl7ERaTkbGxvcvHkTxsbGMDMzQ2FhIQDA1NQURUVFwoYjIiIiUgBndoi0XNOmTfH06VMAgEgkAgDk5ubC3NxcyFhERERECmOxQ6Tlpk6diokTJ+LcuXOoqqrCpUuXMGPGDEyfPl3oaEREREQK4TI2Ii0nk8mwceNGhIeHQyqVws7ODoGBgViyZAl0dXWFjkdERERUbyx2iLTQwoULsWnTJgBAbGwsRo4cKXAiIiIiIuVjsUOkhV7cfMDY2BgPHz4UNhARERFRA2gidAAiUr0+ffrA09MT7dq1Q1lZGd58881a79u1a5eKkxEREREpD4sdIi108OBBxMTEQCqVQiQSQSKRCB2JiIiISOlY7BBpoS+//BLBwcEAnm03HRISImwgIiIiogbAd3aItJCJiQmKi4sB8J0dIiIi0lyc2SHSQh07dkRAQAA6dOiA8vJyrF27ttb7OONDREREjRmLHSItdOjQIezatQtpaWmQyWS4fft2jXtEIpEAyYiIiIiUh8vYiLTcW2+9hR07dggdg4iIiEjpWOwQEfLy8vDDDz8gNzcXS5cuRVZWFmQyGRwcHISORkRERFRvOkIHICJhxcXFoWPHjjh69CjWrFkDAEhPT8fs2bMFTkZERESkGM7sEGm5jh07Ijw8HG5ubjAzM0NhYSHKy8thZ2eH+/fvCx2PiIiIqN44s0Ok5e7du4f//ve/AP7/pgTcnICIiIg0AYsdIi3Xu3dvbN++vVpbWFgYPDw8BEpEREREpBxcxkak5TIzM+Hj44OysjKkpqaiQ4cOkMlkOH78OOzt7YWOR0RERFRvLHaICFVVVTh//jykUikkEgnc3Nygq6srdCwiIiIihbDYISIiIiIijcR3doiIiIiISCOx2CEiIiIiIo3EYoeIiIiIiDQSix0iIiIiItJILHaIiBq5adOmYfTo0fJ/79+/P4KDgwXLQ0REpC5Y7BARaTEnJyd8/vnnQscgIiJqECx2iIiIiIhII7HYISJSAzKZDB9//DFat26Npk2bwsHBAR999BEAIDMzExMnToSpqSnEYjFGjRqF9PR0hfvs378/MjIysGDBAohEIohEIvz1118wNjZGTExMtXsPHz6MFi1aoKSkBOnp6RCJRNi/fz/c3d3RrFkzdOrUCQkJCdW+59q1axg2bBgMDQ1hZWWFN954Aw8ePFA4NxER0ctisUNEpAaWL1+O9evX44MPPsD169cRGRkJKysrVFRUYMiQITAyMsKZM2dw9uxZGBoaYujQoSgvL1eoz4MHD8LOzg6hoaHIyclBTk4OWrRoAT8/P+zevbvavbt378b48eNhZGQkb1uyZAkWLVqEixcvok+fPvDx8UF+fj4AoKioCF5eXujevTt+//13/Pjjj7h37x4mTpyoUGYiIqJX0UToAERE2q6kpASbN2/G1q1bMXXqVACAi4sL+vbti3379kEmk+Hrr7+GSCQC8KzwMDU1xS+//ILBgwfXu1+xWAxdXV0YGRnB2tpa3h4UFAR3d3fk5OTAxsYG9+/fx4kTJ/B///d/1b5/7ty5GDduHABgx44d+PHHHxEWFoalS5di69at6N69O9auXSu/Pzw8HPb29rh16xbatm1b79xEREQvizM7REQCS0lJwZMnTzBw4MAa1y5fvow///wTRkZGMDQ0hKGhIcRiMcrKynDnzp0GyfPf//4XHTt2REREBABg3759cHR0xGuvvVbtvj59+si/btKkCXr27ImUlBR57vj4eHlmQ0NDtG/fHgAaLDcREdHfcWaHiEhgBgYGdV579OgR/vOf/+Dbb7+tca1ly5YNlikoKAjbtm3DsmXLsHv3bgQGBspnll7Go0eP4OPjgw0bNtS4ZmNjo8yoREREdeLMDhGRwNq0aQMDAwP8/PPPNa716NEDt2/fhqWlJVq3bl3tHxMTE4X71tfXR2VlZY32gIAAZGRkYMuWLbh+/bp8ed2Lzp07J//66dOnuHDhAlxdXeW5//jjDzg5OdXI3aJFC4VzExERvQwWO0REAmvWrBneffddLF26FHv37sWdO3dw7tw5hIWFYfLkybCwsMCoUaNw5swZpKWl4ZdffsH8+fORlZWlcN9OTk44ffo07t69W22nNDMzM4wdOxZLlizB4MGDYWdnV+N7t23bhkOHDuHGjRuYM2cOCgsLMX36dADAnDlzUFBQAH9/fyQnJ+POnTuIi4tDYGBgrcUVERFRQ2CxQ0SkBj744AMsWrQIK1asgKurK3x9fXH//n00b94cp0+fhoODA8aOHQtXV1fMmDEDZWVlMDY2Vrjf0NBQpKenw8XFpcayuBkzZqC8vFxewPzd+vXrsX79enTt2hWJiYmIjY2FhYUFAMDW1hZnz55FZWUlBg8ejM6dOyM4OBimpqbQ0eH/eoiISDVEVVVVVUKHICIi9fPNN99gwYIFyM7Ohr6+vrw9PT0drVq1wsWLF9GtWzfhAhIREf0LblBARETVPH78GDk5OVi/fj1mzZpVrdAhIiJqTLiWgIhIQ505c6ba1s9//6cuH3/8Mdq3bw9ra2ssX75chYmJiIiUi8vYiIg0VGlpKe7evVvn9datW6swDRERkeqx2CEiIiIiIo3EZWxERERERKSRWOwQEREREZFGYrFDREREREQaicUOERERERFpJBY7RERERESkkVjsEBERERGRRmKxQ0REREREGun/AecgfFysbvC6AAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sc.pl.heatmap(adata_test, markers, groupby='cell_type', swap_axes=True, vmax=3.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING: Gene labels are not shown when more than 50 genes are visualized. To show gene labels set `show_gene_labels=True`\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sc.pl.heatmap(generated_adata, markers, groupby='cell_type', swap_axes=True, vmax=3.0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see from the heatmaps that the generated cells have very realistic gene expression profiles compared to the original data, which is promising. It indicates that the cell generation of our C2S model is accurate, and the linear model is able to reconstruct gene expression effectively.\n", - "\n", - "Now, we will move on to visualizing a joint UMAP of generated and original ground truth cells, so that all cells are in the same joint space." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Combined UMAP in shared space\n", - "Now, we create a combined AnnData object and run PCA, neighbors, and UMAP:" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "metadata": {}, - "outputs": [], - "source": [ - "del adata_test.uns\n", - "del adata_test.obsm\n", - "del adata_test.varm\n", - "del adata_test.obsp\n", - "\n", - "del generated_adata.uns\n", - "del generated_adata.obsm\n", - "del generated_adata.varm\n", - "del generated_adata.obsp" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type', 'tissue', 'batch_condition', 'organism', 'sex', 'data_label'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "adata_test" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 2978 × 23944\n", - " obs: 'cell_type', 'data_label'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "generated_adata" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [], - "source": [ - "adata_test.obs[\"data_label\"] = \"Original Data\"\n", - "generated_adata.obs[\"data_label\"] = \"C2S Generated Data\"" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(2978, 23944)\n", - "3.3575494\n", - "209.48633\n", - "1.9250746\n", - "0.008749011\n" - ] - } - ], - "source": [ - "print(adata_test.X.shape)\n", - "print(adata_test.X.max())\n", - "print(adata_test.X[0].sum())\n", - "print(adata_test.X[0].max())\n", - "print(adata_test.X[0].mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(2978, 23944)\n", - "2.2378533\n", - "193.574\n", - "2.2378533\n", - "0.008084447\n" - ] - } - ], - "source": [ - "print(generated_adata.X.shape)\n", - "print(generated_adata.X.max())\n", - "print(generated_adata.X[0].sum())\n", - "print(generated_adata.X[0].max())\n", - "print(generated_adata.X[0].mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 5956 × 23944\n", - " obs: 'cell_type', 'data_label'" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "concat_adata = anndata.concat([adata_test, generated_adata], axis=0)\n", - "concat_adata" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 5956 × 23944\n", - " obs: 'cell_type', 'data_label'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'" - ] - }, - "execution_count": 73, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "concat_adata.var = adata_test.var.copy()\n", - "concat_adata" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Counter({'Original Data': 2978, 'C2S Generated Data': 2978})" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Counter(concat_adata.obs[\"data_label\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [], - "source": [ - "sc.tl.pca(concat_adata)" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": {}, - "outputs": [], - "source": [ - "sc.pp.neighbors(concat_adata)" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [], - "source": [ - "sc.tl.umap(concat_adata)" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AnnData object with n_obs × n_vars = 5956 × 23944\n", - " obs: 'cell_type', 'data_label'\n", - " var: 'gene_name', 'ensembl_id', 'n_cells', 'mt', 'n_cells_by_counts', 'mean_counts', 'pct_dropout_by_counts', 'total_counts'\n", - " uns: 'pca', 'neighbors', 'umap'\n", - " obsm: 'X_pca', 'X_umap'\n", - " varm: 'PCs'\n", - " obsp: 'distances', 'connectivities'" - ] - }, - "execution_count": 78, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "concat_adata" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/anndata/_core/anndata.py:1230: ImplicitModificationWarning: Trying to modify attribute `.obs` of view, initializing view as actual.\n", - "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n", - "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/anndata/_core/anndata.py:1230: ImplicitModificationWarning: Trying to modify attribute `.obs` of view, initializing view as actual.\n", - "/home/sr2464/.conda/envs/cell2sentence/lib/python3.8/site-packages/scanpy/plotting/_tools/scatterplots.py:394: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n", - "/tmp/tmp.cdyXGrsOEn/ipykernel_784881/2650716503.py:19: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all axes decorations.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 5))\n", - "ax = sc.pl.umap(\n", - " concat_adata[concat_adata.obs[\"data_label\"] == \"Original Data\", :],\n", - " color=\"cell_type\",\n", - " size=8,\n", - " title=\"Original Human Immune Tissue Data\",\n", - " show=False,\n", - " legend_loc=None,\n", - " ax=ax1,\n", - ")\n", - "sc.pl.umap(\n", - " concat_adata[concat_adata.obs[\"data_label\"] == \"C2S Generated Data\", :],\n", - " color=\"cell_type\",\n", - " size=8,\n", - " title=\"C2S Generated Data\",\n", - " show=False,\n", - " ax=ax2,\n", - ")\n", - "plt.tight_layout()\n", - "plt.show()\n", - "plt.close()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that the generated data by our C2S model (right) comes very close to the original data (left), which is promising for the potential of C2S to generate realistic data. These cells are being visualized after conversion back to expression vectors from generated cell sentences, so we can also observe that we did not lose too much information in our data by going to cell sentences and back to expression vectors. This allows us to leverage the strengths and generation ability of LLMs without losing too much information." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.8.19 ('cell2sentence': conda)", - "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": "3.8.19" - }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "30854c2c12e6a68630235fdae2d040378c6582e0cbda77c6d9a96d02c39a5866" - } - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} ->>>>>>> 593fb74 (Peft feature implemented) From 19299ffe0d30a52e9f6bbfd84c687bd52ed6bbe5 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:30:09 +0000 Subject: [PATCH 10/19] Added the description for the 10th tutorial in README file --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 59a58b8..558874b 100644 --- a/README.md +++ b/README.md @@ -89,7 +89,7 @@ The following notebooks provide guides on common workflows with C2S models. For | [c2s_tutorial_7_custom_prompt_templates.ipynb](tutorials/c2s_tutorials_7_custom_prompt_templates.ipynb) | Custom Prompt Templates with C2S PromptFormatter class | [c2s_tutorial_8_multi_cell_tissue_prediction.ipynb](tutorials/c2s_tutorial_8_multi_cell_tissue_prediction.ipynb) | Classifying the Tissue based on Multiple cell sentences | [c2s_tutorial_9_natural_language_interpretation.ipynb](tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb) | Use the C2S model to generate insightful summaries for different sets of cells -| [c2s_tutorial_10_perturbation_response_prediction.ipynb](tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb)| +| [c2s_tutorial_10_perturbation_response_prediction.ipynb](tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb)| Use the C2S model to perform perturbation based on pre-cell sentences and treatment ## Model Zoo From e7a2e069832d8cf50d4e59d26068862761223ed0 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:36:10 +0000 Subject: [PATCH 11/19] Fixed the tutorial 7 path in readme --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 558874b..0bc99a7 100644 --- a/README.md +++ b/README.md @@ -86,7 +86,7 @@ The following notebooks provide guides on common workflows with C2S models. For | [c2s_tutorial_4_cell_type_prediction.ipynb](tutorials/c2s_tutorial_4_cell_type_prediction.ipynb) | Cell type prediction using C2S models | [c2s_tutorial_5_cell_generation.ipynb](tutorials/c2s_tutorial_5_cell_generation.ipynb) | Cell generation conditioned on cell type | [c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb](tutorials/c2s_tutorial_6_cell_annotation_with_foundation_model.ipynb) | Cell type annotation with foundation model -| [c2s_tutorial_7_custom_prompt_templates.ipynb](tutorials/c2s_tutorials_7_custom_prompt_templates.ipynb) | Custom Prompt Templates with C2S PromptFormatter class +| [c2s_tutorial_7_custom_prompt_templates.ipynb](tutorials/c2s_tutorial_7_custom_prompt_templates.ipynb) | Custom Prompt Templates with C2S PromptFormatter class | [c2s_tutorial_8_multi_cell_tissue_prediction.ipynb](tutorials/c2s_tutorial_8_multi_cell_tissue_prediction.ipynb) | Classifying the Tissue based on Multiple cell sentences | [c2s_tutorial_9_natural_language_interpretation.ipynb](tutorials/c2s_tutorial_9_natural_language_interpretation.ipynb) | Use the C2S model to generate insightful summaries for different sets of cells | [c2s_tutorial_10_perturbation_response_prediction.ipynb](tutorials/c2s_tutorial_10_perturbation_response_prediction.ipynb)| Use the C2S model to perform perturbation based on pre-cell sentences and treatment From 0c03c1c7dd0c697aa4fd0ea63747c76b7b0965dd Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:39:05 +0000 Subject: [PATCH 12/19] removed duplication in readthedocs.yaml file --- .readthedocs.yaml | 42 ------------------------------------------ 1 file changed, 42 deletions(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 07be3bb..2fb5427 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -40,45 +40,3 @@ python: - requirements: docs/requirements.txt - method: pip path: . -# Read the Docs configuration file for Sphinx projects -# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details - -# Required -version: 2 - -# Set the OS, Python version and other tools you might need -build: - os: ubuntu-22.04 - tools: - python: "3.12" - # You can also specify other tool versions: - # nodejs: "20" - # rust: "1.70" - # golang: "1.20" - -# Build documentation in the "docs/" directory with Sphinx -sphinx: - configuration: docs/source/conf.py - # You can configure Sphinx to use a different builder, for instance use the dirhtml builder for simpler URLs - # builder: "dirhtml" - # Fail on all warnings to avoid broken references - # fail_on_warning: true - -# Optionally build your docs in additional formats such as PDF and ePub -# formats: -# - pdf -# - epub - -# Optional but recommended, declare the Python requirements required -# to build your documentation -# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html -# python: -# install: -# - requirements: docs/requirements.txt - -# Declare the Python requirements required to build your documentation -python: - install: - - requirements: docs/requirements.txt - - method: pip - path: . \ No newline at end of file From 01dcb4793dca37540b255bbe054f8a65180db750 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:41:26 +0000 Subject: [PATCH 13/19] Removed duplication in csmodel.rst --- docs/source/csmodel.rst | 27 +-------------------------- 1 file changed, 1 insertion(+), 26 deletions(-) diff --git a/docs/source/csmodel.rst b/docs/source/csmodel.rst index 58f5aa7..ab75469 100644 --- a/docs/source/csmodel.rst +++ b/docs/source/csmodel.rst @@ -19,29 +19,4 @@ The class contains utilities for model generation and cell embedding with a Hugg .. autofunction:: csmodel.CSModel.embed_cells_batched -.. autofunction:: csmodel.CSModel.push_model_to_hub -======= -CSModel -======= - -A CSModel object is a wrapper around a Cell2Sentence model, which tracks the path of the model -saved on disk. When needed, the model is loaded from the path on disk for inference or finetuning. -The class contains utilities for model generation and cell embedding with a Huggingface backend. - -.. autofunction:: csmodel.CSModel - -.. autofunction:: csmodel.CSModel.__init__ - -.. autofunction:: csmodel.CSModel.__str__ - -.. autofunction:: csmodel.CSModel.fine_tune - -.. autofunction:: csmodel.CSModel.generate_from_prompt - -.. autofunction:: csmodel.CSModel.generate_from_prompt_batched - -.. autofunction:: csmodel.CSModel.embed_cell - -.. autofunction:: csmodel.CSModel.embed_cells_batched - -.. autofunction:: csmodel.CSModel.push_model_to_hub +.. autofunction:: csmodel.CSModel.push_model_to_hub \ No newline at end of file From 0f5bd2ead67d30bed293929676d363330dd5c472 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:42:50 +0000 Subject: [PATCH 14/19] Removed duplication in csmodel.rst --- src/cell2sentence/tests/small_data.csv | 3 ++- src/cell2sentence/tests/small_data_diffgenes.csv | 1 + 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/src/cell2sentence/tests/small_data.csv b/src/cell2sentence/tests/small_data.csv index cf2ee95..76f2bff 100644 --- a/src/cell2sentence/tests/small_data.csv +++ b/src/cell2sentence/tests/small_data.csv @@ -1,4 +1,5 @@ ,cell1,cell2,cell3,cell4,cell5 g1,0,3,0,1,3 g2,0,0,1,1,2 -g3,3,1,0,0,1 \ No newline at end of file +g3,3,1,0,0,1 +g4,1,0,0,0,0 \ No newline at end of file diff --git a/src/cell2sentence/tests/small_data_diffgenes.csv b/src/cell2sentence/tests/small_data_diffgenes.csv index 1f60060..76f2bff 100644 --- a/src/cell2sentence/tests/small_data_diffgenes.csv +++ b/src/cell2sentence/tests/small_data_diffgenes.csv @@ -2,3 +2,4 @@ g1,0,3,0,1,3 g2,0,0,1,1,2 g3,3,1,0,0,1 +g4,1,0,0,0,0 \ No newline at end of file From 34e5122229db3009a7d34fdac90ac592849ac01e Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 12:46:09 +0000 Subject: [PATCH 15/19] changed line 87 in csmodel.py to os.makedirs --- src/cell2sentence/csmodel.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/cell2sentence/csmodel.py b/src/cell2sentence/csmodel.py index d71f9bd..b761e59 100644 --- a/src/cell2sentence/csmodel.py +++ b/src/cell2sentence/csmodel.py @@ -84,8 +84,7 @@ def __init__( print("Using device:", self.device) # Create save path - if not os.path.exists(save_dir): - os.mkdir(save_dir) + os.makedirs(save_dir,exist_ok=True) self.save_path = os.path.join(save_dir, save_name) # Avoid mutable default for modules From 9216bf8e1aa07c21cb45997a923acc9c6c2bb902 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 13:15:08 +0000 Subject: [PATCH 16/19] Created proper test to check if peft layers are loading correctly --- src/cell2sentence/tests/test_csmodel.py | 22 +++++++++++++++++++--- 1 file changed, 19 insertions(+), 3 deletions(-) diff --git a/src/cell2sentence/tests/test_csmodel.py b/src/cell2sentence/tests/test_csmodel.py index b25c3b1..b984459 100644 --- a/src/cell2sentence/tests/test_csmodel.py +++ b/src/cell2sentence/tests/test_csmodel.py @@ -14,7 +14,7 @@ # Pytorch, Huggingface from transformers import AutoModelForCausalLM from transformers.models.gpt_neox.modeling_gpt_neox import GPTNeoXForCausalLM - +from peft import PeftModel # Local imports import cell2sentence as cs from cell2sentence.csmodel import CSModel @@ -66,5 +66,21 @@ def test_csmodel_created_correctly(self): assert self.csmodel.save_path == os.path.join(self.save_dir, self.save_name) def test_layers_are_created_correctly(self): - model = AutoModelForCausalLM.from_pretrained(self.csmodel.save_path, trust_remote_code = True) - print(model) + from peft import PeftModel, AutoPeftModelForCausalLM + + # Load the model back from disk using PEFT's loading method + loaded_model = AutoPeftModelForCausalLM.from_pretrained( + self.csmodel.save_path, + trust_remote_code=True, + is_trainable=False + ) + + # Verify it loaded as a PEFT model + assert isinstance(loaded_model, PeftModel), "Model is not a PeftModel" + + # Verify that LoRA layers are present in the loaded model + lora_modules = [name for name, module in loaded_model.named_modules() if "lora" in name.lower()] + assert len(lora_modules) > 0, "No LoRA layers found in the reloaded model modules" + + # Ensure the active adapter is set (typical for LoRA) + assert hasattr(loaded_model, "active_adapter"), "No active adapter found on the PEFT model" From fc907051ca734feb199dfde5e74d02c28a57cd92 Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sat, 14 Mar 2026 13:21:01 +0000 Subject: [PATCH 17/19] Modified the model loading in fine_tune method under CSModel to load the peft model correctly --- src/cell2sentence/csmodel.py | 20 ++++++++++++++------ 1 file changed, 14 insertions(+), 6 deletions(-) diff --git a/src/cell2sentence/csmodel.py b/src/cell2sentence/csmodel.py index b761e59..8c50fb0 100644 --- a/src/cell2sentence/csmodel.py +++ b/src/cell2sentence/csmodel.py @@ -19,7 +19,7 @@ # Pytorch, Huggingface imports import torch from transformers import AutoTokenizer, AutoModelForCausalLM, Trainer, TrainingArguments -from peft import LoraConfig, get_peft_model +from peft import LoraConfig, get_peft_model, AutoPeftModelForCausalLM from huggingface_hub import login # Local imports @@ -81,6 +81,7 @@ def __init__( self.model_name_or_path = model_name_or_path # path to model to load self.save_dir = save_dir self.device = "cuda" if torch.cuda.is_available() else "cpu" + self.peft = peft print("Using device:", self.device) # Create save path @@ -182,11 +183,18 @@ def fine_tune(self, # Load model print("Reloading model from path on disk:", self.save_path) - model = AutoModelForCausalLM.from_pretrained( - self.save_path, - cache_dir=os.path.join(self.save_dir, ".cache"), - trust_remote_code=True - ) + if not self.peft: + model = AutoModelForCausalLM.from_pretrained( + self.save_path, + cache_dir=os.path.join(self.save_dir, ".cache"), + trust_remote_code=True + ) + else: + model = AutoPeftModelForCausalLM.from_pretrained( + self.save_path, + cache_dir=os.path.join(self.save_dir, ".cache"), + trust_remote_code=True + ) model = model.to(self.device) # Tokenize data using LLM tokenizer From 881dda4a1a669669161e9bacc207d0f538bad38b Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sun, 15 Mar 2026 01:28:23 +0000 Subject: [PATCH 18/19] Changed the Trainer argument type back to tokenizer --- src/cell2sentence/csmodel.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/cell2sentence/csmodel.py b/src/cell2sentence/csmodel.py index 8c50fb0..38eb580 100644 --- a/src/cell2sentence/csmodel.py +++ b/src/cell2sentence/csmodel.py @@ -275,7 +275,7 @@ def data_collator(examples): data_collator=data_collator, train_dataset=train_dataset, eval_dataset=eval_dataset, - processing_class=self.tokenizer #changed argument from tokenizer to processing_class as per modern documentation + tokenizer=self.tokenizer #changed argument from tokenizer to processing_class as per modern documentation ) trainer.train() print(f"Finetuning completed. Updated model saved to disk at: {output_dir}") From d9d62db673b9e7bfad1ad715db2559ae5d322dad Mon Sep 17 00:00:00 2001 From: Krishna Harsha Mamillapalli Date: Sun, 15 Mar 2026 01:49:03 +0000 Subject: [PATCH 19/19] Fixed the broken link for python3.10.20 in README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 0bc99a7..2cc0637 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,7 @@ [![Code License: Apache 2.0](https://img.shields.io/badge/license-Apache%20License%202.0-blue)](https://www.apache.org/licenses/LICENSE-2.0) [![PyPI version](https://badge.fury.io/py/cell2sentence.svg)](https://badge.fury.io/py/cell2sentence) [![DOI:10.1101/2025.04.14.648850](http://img.shields.io/badge/DOI-10.1101/2025.04.14.648850-B31B1B.svg)](https://doi.org/10.1101/2025.04.14.648850) -[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/release/python-310020/) +[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/release/python-31020/) ![cell2sentence workflow image](c2s_overview_figure.png)