From 8fd872b3a8227dc730e2ccc715d8d2c7bdb050aa Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:24:28 +0200 Subject: [PATCH 01/33] Create .readthedocs.yaml --- .readthedocs.yaml | 11 +++++++++++ 1 file changed, 11 insertions(+) create mode 100644 .readthedocs.yaml diff --git a/.readthedocs.yaml b/.readthedocs.yaml new file mode 100644 index 0000000..59980f9 --- /dev/null +++ b/.readthedocs.yaml @@ -0,0 +1,11 @@ +# Build documentation in the "docs/" directory with Sphinx +sphinx: + configuration: docs/conf.py + +# Optionally, 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 + From 4a589968ca77410d3ac052d1505f927f3501e408 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:25:11 +0200 Subject: [PATCH 02/33] Update .readthedocs.yaml --- .readthedocs.yaml | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 59980f9..f72c324 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -1,3 +1,15 @@ +# Read the Docs configuration file +# 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-24.04 + tools: + python: "3.13" + # Build documentation in the "docs/" directory with Sphinx sphinx: configuration: docs/conf.py @@ -8,4 +20,3 @@ sphinx: # python: # install: # - requirements: docs/requirements.txt - From 038da6266a8fdae6a64e54774b877817a4d78a7b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:33:02 +0200 Subject: [PATCH 03/33] Create conf.py --- docs/source/conf.py | 35 +++++++++++++++++++++++++++++++++++ 1 file changed, 35 insertions(+) create mode 100644 docs/source/conf.py diff --git a/docs/source/conf.py b/docs/source/conf.py new file mode 100644 index 0000000..1f2f2d4 --- /dev/null +++ b/docs/source/conf.py @@ -0,0 +1,35 @@ +# docs/conf.py + +import os +import sys +from datetime import datetime + +# -- Path setup -------------------------------------------------------------- +# Make your module importable by adding the project root to sys.path +sys.path.insert(0, os.path.abspath('..')) + +# -- Project information ----------------------------------------------------- +project = 'Circe' +author = 'Rémi Trimbour' +copyright = f'{datetime.now().year}, {author}' +release = '0.3.8-alpha' # Or dynamically pull from package version + +# -- General configuration --------------------------------------------------- +extensions = [ + 'sphinx.ext.autodoc', # Automatically generate documentation from docstrings + 'sphinx.ext.napoleon', # Support for NumPy/Google style docstrings + 'sphinx.ext.viewcode', # Add links to highlighted source code + 'sphinx.ext.intersphinx' # Link to other projects' documentation +] + +templates_path = ['_templates'] +exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] + +# -- Options for HTML output ------------------------------------------------- +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = "furo" + +html_title = "CIRCE" +html_static_path = ['_static'] From 99c020285d018592882c1ad786f3f0d9ed395839 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:35:19 +0200 Subject: [PATCH 04/33] Rename docs/source/conf.py to docs/conf.py --- docs/{source => }/conf.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename docs/{source => }/conf.py (100%) diff --git a/docs/source/conf.py b/docs/conf.py similarity index 100% rename from docs/source/conf.py rename to docs/conf.py From ae603a9489fcbd1c1aef5dd2b0381bd1d4301696 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:37:50 +0200 Subject: [PATCH 05/33] Update .readthedocs.yaml --- .readthedocs.yaml | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index f72c324..c17b30c 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -20,3 +20,10 @@ sphinx: # python: # install: # - requirements: docs/requirements.txt +python: + install: + - method: pip + path: . + extra_requirements: + - docsbuild + - sphinx From 3c7d7b0fb056bbe69de2174762762f30e4d50a2d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:38:49 +0200 Subject: [PATCH 06/33] Create index.rst --- docs/index.rst | 15 +++++++++++++++ 1 file changed, 15 insertions(+) create mode 100644 docs/index.rst diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 0000000..b4c85e8 --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,15 @@ +Welcome to Circe’s documentation! +================================= + +.. toctree:: + :maxdepth: 2 + :caption: Contents + + modules + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` From cf1d8a604c7cd3cc703157ef0087d239f1dd8261 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:39:12 +0200 Subject: [PATCH 07/33] Create modules.rst --- docs/modules.rst | 7 +++++++ 1 file changed, 7 insertions(+) create mode 100644 docs/modules.rst diff --git a/docs/modules.rst b/docs/modules.rst new file mode 100644 index 0000000..15316dc --- /dev/null +++ b/docs/modules.rst @@ -0,0 +1,7 @@ +Circe API Reference +=================== + +.. automodule:: circe + :members: + :undoc-members: + :show-inheritance: From 1989f018b18f6bb7458329fbf28ee6bf51a64020 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 16:56:11 +0200 Subject: [PATCH 08/33] Update .readthedocs.yaml --- .readthedocs.yaml | 30 +++++++----------------------- 1 file changed, 7 insertions(+), 23 deletions(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index c17b30c..9138a7f 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -1,29 +1,13 @@ -# Read the Docs configuration file -# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details +version: "2" -# Required -version: 2 - -# Set the OS, Python version, and other tools you might need build: - os: ubuntu-24.04 + os: "ubuntu-22.04" tools: - python: "3.13" - -# Build documentation in the "docs/" directory with Sphinx -sphinx: - configuration: docs/conf.py + python: "3.10" -# Optionally, 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 python: install: - - method: pip - path: . - extra_requirements: - - docsbuild - - sphinx + - requirements: docs/requirements.txt + +sphinx: + configuration: docs/source/conf.py From a1d51bd34fdca4791e8fd25e5f5d888e356420df Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:00:57 +0200 Subject: [PATCH 09/33] Delete docs/modules.rst --- docs/modules.rst | 7 ------- 1 file changed, 7 deletions(-) delete mode 100644 docs/modules.rst diff --git a/docs/modules.rst b/docs/modules.rst deleted file mode 100644 index 15316dc..0000000 --- a/docs/modules.rst +++ /dev/null @@ -1,7 +0,0 @@ -Circe API Reference -=================== - -.. automodule:: circe - :members: - :undoc-members: - :show-inheritance: From 226d42fe93bc6f10375fcf903bf9861f6d2776ca Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:03:53 +0200 Subject: [PATCH 10/33] Update conf.py --- docs/conf.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/conf.py b/docs/conf.py index 1f2f2d4..0af5d68 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -19,7 +19,8 @@ 'sphinx.ext.autodoc', # Automatically generate documentation from docstrings 'sphinx.ext.napoleon', # Support for NumPy/Google style docstrings 'sphinx.ext.viewcode', # Add links to highlighted source code - 'sphinx.ext.intersphinx' # Link to other projects' documentation + 'sphinx.ext.intersphinx', # Link to other projects' documentation + "nbsphinx" ] templates_path = ['_templates'] From 66818d5f2a95dadfb03967bc960580e9e7340185 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:05:11 +0200 Subject: [PATCH 11/33] Update .readthedocs.yaml --- .readthedocs.yaml | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 9138a7f..b2e0b21 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -5,9 +5,14 @@ build: tools: python: "3.10" +# We recommend specifying your dependencies to enable reproducible builds: +# https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html python: install: - - requirements: docs/requirements.txt + - method: pip + path: . + extra_requirements: + - docsbuild sphinx: configuration: docs/source/conf.py From 56c8809efc5a8956093209fb1c4889b7b5b72c8c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:11:35 +0200 Subject: [PATCH 12/33] Update .readthedocs.yaml --- .readthedocs.yaml | 1 - 1 file changed, 1 deletion(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index b2e0b21..b54587a 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -10,7 +10,6 @@ build: python: install: - method: pip - path: . extra_requirements: - docsbuild From 6b5960f994ba01f0e275a00f49c2e98d262cf0ca Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:19:11 +0200 Subject: [PATCH 13/33] Update .readthedocs.yaml --- .readthedocs.yaml | 1 + 1 file changed, 1 insertion(+) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index b54587a..1a6b9d4 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -10,6 +10,7 @@ build: python: install: - method: pip + - requirements: docs/requirements.txt extra_requirements: - docsbuild From 7b8299f5c7e1fe9f5edea52169ccb8f13b957d80 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:20:49 +0200 Subject: [PATCH 14/33] Create requirements.txt --- docs/requirements.txt | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 docs/requirements.txt diff --git a/docs/requirements.txt b/docs/requirements.txt new file mode 100644 index 0000000..66316d4 --- /dev/null +++ b/docs/requirements.txt @@ -0,0 +1,5 @@ +sphinx>=7 +sphinx-rtd-theme +myst-parser +sphinx-autodoc-typehints +sphinx-copybutton From 8d4024b2b2073cdf007a4e229067e6ae36781df5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:21:38 +0200 Subject: [PATCH 15/33] Update .readthedocs.yaml --- .readthedocs.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 1a6b9d4..5e64e6f 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -10,7 +10,7 @@ build: python: install: - method: pip - - requirements: docs/requirements.txt + requirements: docs/requirements.txt extra_requirements: - docsbuild From 48fc7a175c8c8db6fc9ced6a6f390b4e00d958df Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:22:09 +0200 Subject: [PATCH 16/33] Update .readthedocs.yaml --- .readthedocs.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 5e64e6f..a9e95cb 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -10,7 +10,7 @@ build: python: install: - method: pip - requirements: docs/requirements.txt + requirements: docs/requirements.txt extra_requirements: - docsbuild From 799f07477e9d409d83dc8d437da5d73a4cf4641c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:23:52 +0200 Subject: [PATCH 17/33] Update .readthedocs.yaml --- .readthedocs.yaml | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index a9e95cb..7eea647 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -9,10 +9,7 @@ build: # https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html python: install: - - method: pip - requirements: docs/requirements.txt - extra_requirements: - - docsbuild + requirements: docs/requirements.txt sphinx: configuration: docs/source/conf.py From 8602ff524c5fa34edd8a347175ef4bc4faea5f6b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:24:06 +0200 Subject: [PATCH 18/33] Update .readthedocs.yaml --- .readthedocs.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 7eea647..6b21616 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -9,7 +9,7 @@ build: # https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html python: install: - requirements: docs/requirements.txt + requirements: docs/requirements.txt sphinx: configuration: docs/source/conf.py From 3de083fdcbb0b0216b5a5b979b3f50c69b4764fc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:25:39 +0200 Subject: [PATCH 19/33] Update .readthedocs.yaml --- .readthedocs.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 6b21616..b59b416 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -9,7 +9,7 @@ build: # https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html python: install: - requirements: docs/requirements.txt + - requirements: docs/requirements.txt sphinx: - configuration: docs/source/conf.py + configuration: docs/conf.py From 8f8f771d4d4f24a8672a9f9951fb0a86dc4d18c5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:27:49 +0200 Subject: [PATCH 20/33] Update conf.py --- docs/conf.py | 1 - 1 file changed, 1 deletion(-) diff --git a/docs/conf.py b/docs/conf.py index 0af5d68..568bc86 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -20,7 +20,6 @@ 'sphinx.ext.napoleon', # Support for NumPy/Google style docstrings 'sphinx.ext.viewcode', # Add links to highlighted source code 'sphinx.ext.intersphinx', # Link to other projects' documentation - "nbsphinx" ] templates_path = ['_templates'] From 6c4db60f6858eb90aadea608ca2432044439c188 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Thu, 4 Sep 2025 17:29:33 +0200 Subject: [PATCH 21/33] Update conf.py --- docs/conf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/conf.py b/docs/conf.py index 568bc86..6bfe78a 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -29,7 +29,7 @@ # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # -html_theme = "furo" +html_theme = "sphinx_rtd_theme" html_title = "CIRCE" html_static_path = ['_static'] From 2a9746ffb828b8ddb38413fc4b798e77c39ad35c Mon Sep 17 00:00:00 2001 From: r-trimbour Date: Sat, 6 Sep 2025 23:22:03 +0200 Subject: [PATCH 22/33] updated the structure of the repo by creating utils.py --- circe/__init__.py | 11 ++- circe/ccan_module.py | 2 +- circe/circe.py | 225 +------------------------------------------ circe/draw.py | 2 +- circe/metacells.py | 5 +- circe/utils.py | 224 ++++++++++++++++++++++++++++++++++++++++++ 6 files changed, 236 insertions(+), 233 deletions(-) create mode 100644 circe/utils.py diff --git a/circe/__init__.py b/circe/__init__.py index d799d6b..bf6b37f 100644 --- a/circe/__init__.py +++ b/circe/__init__.py @@ -1,8 +1,9 @@ -from circe.circe import extract_atac_links, \ - compute_atac_network, \ - add_region_infos, \ - sliding_graphical_lasso, \ - subset_region +from circe.circe import compute_atac_network, \ + sliding_graphical_lasso +from circe.utils import add_region_infos, \ + subset_region, \ + sort_regions, \ + extract_atac_links from circe.draw import plot_connections from circe.ccan_module import find_ccans, add_ccans diff --git a/circe/ccan_module.py b/circe/ccan_module.py index f40feaa..6c24a29 100644 --- a/circe/ccan_module.py +++ b/circe/ccan_module.py @@ -1,7 +1,7 @@ import pandas # For DataFrame manipulation import networkx # For graph creation and manipulation import numpy # For numerical operations -from .circe import extract_atac_links +from .utils import extract_atac_links def find_ccan_cutoff(connection_df, tolerance_digits=2, seed=42): diff --git a/circe/circe.py b/circe/circe.py index 233cf38..3937f33 100644 --- a/circe/circe.py +++ b/circe/circe.py @@ -15,6 +15,7 @@ from functools import reduce from circe import quic_graph_lasso # Graphical Lasso implementation from circe.metrics import cov_with_appended_zeros +from circe.utils import cov_to_corr from dask.distributed import Client, as_completed # Parallel execution from joblib import Parallel, delayed, parallel_config import asyncio @@ -27,160 +28,6 @@ message=r".*is_categorical_dtype is deprecated and will be removed in a future version.*") -def cov_to_corr(cov_matrix, tol=1e-20): - """ - Optimized version: Convert covariance matrix to correlation matrix, - with a tolerance for small diagonal elements. - - Parameters - ---------- - cov_matrix : np.array - Covariance matrix. - tol : float, optional - Tolerance for diagonal elements. Default is 1e-20. - - Returns - ------- - correlation_matrix : np.array - Correlation matrix. - """ - # Diagonal elements (standard deviations) - d = np.sqrt(cov_matrix.diagonal()) - - # Adjust small values in d to avoid instability - d[d < tol] = 1 - - # Calculate correlation matrix using broadcasting for efficiency - correlation_matrix = cov_matrix / d[:, None] / d[None, :] - - # Set diagonal to 1 - np.fill_diagonal(correlation_matrix, 1) - - return correlation_matrix - - -def subset_region(adata, chromosome, start, end): - """ - Subset anndata object on a specific region. - - Parameters - ---------- - adata : anndata object - anndata object with var_names as region names. - chromosome : str - Chromosome name. - start : int - Start position of the region. - end : int - End position of the region. - - Returns - ------- - anndata : anndata object - anndata object subsetted on the region defined by chr, start and end. - """ - - if len([True for i in adata.var.columns - if i in ["chromosome", "start", "end"]]) < 3: - raise KeyError( - """ - 'chr', 'start' and 'end' columns are not present in var. - Please use 'add_region_infos' function to add these informations - to your adata object. - """ - ) - - # subset per chromosome - adata = adata[:, adata.var['chromosome'] == chromosome] - # subset on region window - adata = adata[:, ( - (start <= adata.var['start']) - & (adata.var['start'] <= end)) + ( - (start <= adata.var['end']) - & (adata.var['end'] <= end))] - - return adata - - -def add_region_infos(adata, sep=("_", "_"), inplace=False): - """ - Get region informations from the var_names of adata object. - e.g. chr1_12345_12346 -> 'chromosome' : chr1, - 'start' : 12345, - 'end' : 12346 - These info will be added to var of anndata object. - adata.var['chromosome'] : chromosome - adata.var['start'] : start position - adata.var['end'] : end position - - Parameters - ---------- - adata : anndata object - anndata object with var_names as region names. - sep : tuple, optional - Separator of region names. The default is ('_', '_'). - - Returns - ------- - adata : anndata object - anndata object with region informations in var. - """ - # Check if user wants to modify anndata inplace or return a copy - if inplace: - pass - else: - adata = adata.copy() - regions_list = adata.var_names - - # Replace sep[1] with sep[0] to make it easier to split - regions_list = regions_list.str.replace(sep[1], sep[0]) - - # Split region names - regions_list = regions_list.str.split(sep[0]).tolist() - - # Check if all regions have the same number of elements - if set([len(i) for i in regions_list]) != set([3]): - raise ValueError( - """ - Not all regions have the same number of elements. - Check if sep is correct, it should be ({}, {}), - with only one occurence each in region names. - """.format( - sep[0], sep[1] - ) - ) - - # Extract region informations from var_names - region_infos = pd.DataFrame( - regions_list, index=adata.var_names, - columns=["chromosome", "start", "end"] - ) - - # Convert start and end to int - region_infos["start"] = region_infos["start"].astype(int) - region_infos["end"] = region_infos["end"].astype(int) - - # Add region informations to var - adata.var["chromosome"] = region_infos["chromosome"] - adata.var["start"] = region_infos["start"] - adata.var["end"] = region_infos["end"] - - adata = sort_regions(adata) - # Return anndata if inplace is False - if inplace: - pass - else: - return adata - - -def sort_regions(adata): - """ - Sort regions by chromosome and start position. - """ - ord_index = adata.var.sort_values(["chromosome", "start"]).index - return adata[:, ord_index] - - def compute_atac_network( adata, window_size=None, @@ -302,76 +149,6 @@ def compute_atac_network( ) -def extract_atac_links( - adata, - key=None, - columns=['Peak1', 'Peak2', 'score'] -): - """ - Extract links from adata.varp[key] and return them as a DataFrame. - Since atac-networks scores are undirected, only one link is returned for - each pair of regions. - - Parameters - ---------- - adata : anndata object - anndata object with var_names as variable names. - key : str, optional - key from adata.varp. The default is None. - If None, and only one key is found in adata.varp, will use this key. - Otherwise if several keys are found in adata.varp, will raise an error. - columns : list, optional - Columns names of the output DataFrame. - The default is ['Peak1', 'Peak2', 'score']. - - Returns - ------- - DataFrame - DataFrame with columns names given by 'columns' parameter. - """ - - if key is None: # if only one key (I guess often), no need to precise key - # maybe replace by a default one later - if len(list(adata.varp)) == 1: - key = list(adata.varp)[0] - else: - raise KeyError( - "Several keys were found in adata.varp: {}, ".format( - list(adata.varp)) + - "please precise which keyword use (arg 'key'))" - ) - else: - if key not in list(adata.varp): - raise KeyError("The key you provided ({}) is not in adata.varp: {}" - .format(key, list(adata.varp)) - ) - - # Convert to COO format if needed - converted = False - if isinstance(adata.varp[key], sp.sparse.csr_matrix): - adata.varp[key] = adata.varp[key].tocoo() - converted = True - - links = pd.DataFrame( - [(row, col, data) for (row, col, data) in zip( - [i for i in adata.varp[key].row], - [i for i in adata.varp[key].col], - adata.varp[key].data) - if row < col], - columns=columns - ).sort_values(by=columns[2], ascending=False) - - links[columns[0]] = [adata.var_names[i] for i in links[columns[0]]] - links[columns[1]] = [adata.var_names[i] for i in links[columns[1]]] - links = links.reset_index(drop=True) - - # Convert back to CSR format if it was converted - if converted: - adata.varp[key] = adata.varp[key].tocsr() - - return links - - def calc_penalty(alpha, distance, unit_distance=1000, s=0.75): """ Calculate distance penalties for graphical lasso, based on the formula diff --git a/circe/draw.py b/circe/draw.py index 2cedb5e..c3713d3 100644 --- a/circe/draw.py +++ b/circe/draw.py @@ -5,7 +5,7 @@ import pandas as pd import numpy as np import warnings -from .circe import extract_atac_links, subset_region +from .utils import subset_region, extract_atac_links def plot_genes( diff --git a/circe/metacells.py b/circe/metacells.py index 1d63e43..7b3eb56 100644 --- a/circe/metacells.py +++ b/circe/metacells.py @@ -60,8 +60,8 @@ def compute_metacells( raise ValueError("adata.X contains empty regions." + "Please filter them before computing metacells." + "You can use sc.pp.filter_genes(adata, min_counts=1) to do so.") - lsi(adata) if dim_reduction == 'lsi': + lsi(adata) key_dim_reduction = f"X_{dim_reduction}" sc.pp.neighbors(adata, use_rep=key_dim_reduction, metric=metric) elif dim_reduction in adata.obsm.keys(): @@ -127,7 +127,8 @@ def compute_metacells( # Create a new AnnData object from it metacells_AnnData = ad.AnnData(np.array(metacells_values)) metacells_AnnData.var_names = adata.var_names - metacells_AnnData.obs_names = [f"metacell_{i}" for i in range(len(metacells_values))] + metacells_AnnData.obs_names = [f"metacell_{i}" for i in range( + len(metacells_values))] metacells_AnnData.var = adata.var.copy() metacells_AnnData.varp = adata.varp.copy() diff --git a/circe/utils.py b/circe/utils.py new file mode 100644 index 0000000..4b13cf7 --- /dev/null +++ b/circe/utils.py @@ -0,0 +1,224 @@ +import numpy as np +import pandas as pd +import anndata as ad +import scipy as sp + +def cov_to_corr(cov_matrix, tol=1e-20): + """ + Optimized version: Convert covariance matrix to correlation matrix, + with a tolerance for small diagonal elements. + + Parameters + ---------- + cov_matrix : np.array + Covariance matrix. + tol : float, optional + Tolerance for diagonal elements. Default is 1e-20. + + Returns + ------- + correlation_matrix : np.array + Correlation matrix. + """ + # Diagonal elements (standard deviations) + d = np.sqrt(cov_matrix.diagonal()) + + # Adjust small values in d to avoid instability + d[d < tol] = 1 + + # Calculate correlation matrix using broadcasting for efficiency + correlation_matrix = cov_matrix / d[:, None] / d[None, :] + + # Set diagonal to 1 + np.fill_diagonal(correlation_matrix, 1) + + return correlation_matrix + + +def subset_region(adata: ad.AnnData, chromosome, start, end): + """ + Subset anndata object on a specific region. + + Parameters + ---------- + adata : anndata object + anndata object with var_names as region names. + chromosome : str + Chromosome name. + start : int + Start position of the region. + end : int + End position of the region. + + Returns + ------- + anndata : anndata object + anndata object subsetted on the region defined by chr, start and end. + """ + + if len([True for i in adata.var.columns + if i in ["chromosome", "start", "end"]]) < 3: + raise KeyError( + """ + 'chr', 'start' and 'end' columns are not present in var. + Please use 'add_region_infos' function to add these informations + to your adata object. + """ + ) + + # subset per chromosome + adata = adata[:, adata.var['chromosome'] == chromosome] + # subset on region window + adata = adata[:, ( + (start <= adata.var['start']) + & (adata.var['start'] <= end)) + ( + (start <= adata.var['end']) + & (adata.var['end'] <= end))] + + return adata + + +def add_region_infos(adata: ad.AnnData, sep=("_", "_"), inplace=False): + """ + Get region informations from the var_names of adata object. + e.g. chr1_12345_12346 -> 'chromosome' : chr1, + 'start' : 12345, + 'end' : 12346 + These info will be added to var of anndata object. + adata.var['chromosome'] : chromosome + adata.var['start'] : start position + adata.var['end'] : end position + + Parameters + ---------- + adata : anndata object + anndata object with var_names as region names. + sep : tuple, optional + Separator of region names. The default is ('_', '_'). + + Returns + ------- + adata : anndata object + anndata object with region informations in var. + """ + # Check if user wants to modify anndata inplace or return a copy + regions_list = adata.var_names + + # Replace sep[1] with sep[0] to make it easier to split + regions_list = regions_list.str.replace(sep[1], sep[0]) + + # Split region names + regions_list = regions_list.str.split(sep[0]).tolist() + + # Check if all regions have the same number of elements + if set([len(i) for i in regions_list]) != set([3]): + raise ValueError( + """ + Not all regions have the same number of elements. + Check if sep is correct, it should be ({}, {}), + with only one occurence each in region names. + """.format( + sep[0], sep[1] + ) + ) + + # Extract region informations from var_names + region_infos = pd.DataFrame( + regions_list, index=adata.var_names, + columns=["chromosome", "start", "end"] + ) + + # Convert start and end to int + region_infos["start"] = region_infos["start"].astype(int) + region_infos["end"] = region_infos["end"].astype(int) + + # Add region informations to var + adata.var["chromosome"] = region_infos["chromosome"] + adata.var["start"] = region_infos["start"] + adata.var["end"] = region_infos["end"] + + adata = sort_regions(adata) + # Return anndata if inplace is False + if inplace: + pass + else: + return adata + + +def sort_regions(adata: ad.AnnData): + """ + Sort regions by chromosome and start position. + """ + ord_index = adata.var.sort_values(["chromosome", "start"]).index + return adata[:, ord_index] + + + +def extract_atac_links( + adata: ad.AnnData, + key=None, + columns=['Peak1', 'Peak2', 'score'] +): + """ + Extract links from adata.varp[key] and return them as a DataFrame. + Since atac-networks scores are undirected, only one link is returned for + each pair of regions. + + Parameters + ---------- + adata : anndata object + anndata object with var_names as variable names. + key : str, optional + key from adata.varp. The default is None. + If None, and only one key is found in adata.varp, will use this key. + Otherwise if several keys are found in adata.varp, will raise an error. + columns : list, optional + Columns names of the output DataFrame. + The default is ['Peak1', 'Peak2', 'score']. + + Returns + ------- + DataFrame + DataFrame with columns names given by 'columns' parameter. + """ + + if key is None: # if only one key (I guess often), no need to precise key + # maybe replace by a default one later + if len(list(adata.varp)) == 1: + key = list(adata.varp)[0] + else: + raise KeyError( + "Several keys were found in adata.varp: {}, ".format( + list(adata.varp)) + + "please precise which keyword use (arg 'key'))" + ) + else: + if key not in list(adata.varp): + raise KeyError("The key you provided ({}) is not in adata.varp: {}" + .format(key, list(adata.varp)) + ) + + # Convert to COO format if needed + converted = False + if isinstance(adata.varp[key], sp.sparse.csr_matrix): + adata.varp[key] = adata.varp[key].tocoo() + converted = True + + links = pd.DataFrame( + [(row, col, data) for (row, col, data) in zip( + [i for i in adata.varp[key].row], + [i for i in adata.varp[key].col], + adata.varp[key].data) + if row < col], + columns=columns + ).sort_values(by=columns[2], ascending=False) + + links[columns[0]] = [adata.var_names[i] for i in links[columns[0]]] + links[columns[1]] = [adata.var_names[i] for i in links[columns[1]]] + links = links.reset_index(drop=True) + + # Convert back to CSR format if it was converted + if converted: + adata.varp[key] = adata.varp[key].tocsr() + + return links From 5d28c775f46f6529b1af1389702ccb07cda8749e Mon Sep 17 00:00:00 2001 From: r-trimbour Date: Sat, 6 Sep 2025 23:24:20 +0200 Subject: [PATCH 23/33] updated dependencies to keep anndata < 0.12 --- setup.py | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.py b/setup.py index aca1f5b..3de3043 100644 --- a/setup.py +++ b/setup.py @@ -94,6 +94,7 @@ def build_extensions(self): 'scikit-learn>=1.6', 'joblib>=1.1.0', 'scanpy>=1.8.1', + 'anndata<0.12', 'rich>=10.12.0', 'dask', 'distributed', From 7def9551e6b62412ae59b23cc41838d7bc840dea Mon Sep 17 00:00:00 2001 From: r-trimbour Date: Sun, 7 Sep 2025 00:26:47 +0200 Subject: [PATCH 24/33] updated extract_atac_links to not depend on coo_matrix anymore --> needed for anndata>=0.12 --- circe/utils.py | 122 +++++++++++++++++------------ setup.py | 4 +- tests/test_network/test_network.py | 46 ++++++++++- 3 files changed, 117 insertions(+), 55 deletions(-) diff --git a/circe/utils.py b/circe/utils.py index 4b13cf7..1607c45 100644 --- a/circe/utils.py +++ b/circe/utils.py @@ -153,72 +153,90 @@ def sort_regions(adata: ad.AnnData): return adata[:, ord_index] - def extract_atac_links( adata: ad.AnnData, key=None, - columns=['Peak1', 'Peak2', 'score'] + columns=('Peak1', 'Peak2', 'score') ): """ - Extract links from adata.varp[key] and return them as a DataFrame. - Since atac-networks scores are undirected, only one link is returned for - each pair of regions. + Extract upper-triangular links (row < col) from adata.varp[key] into a DataFrame. + Works natively with CSR/CSC. If another format is found, it is converted to CSR + on the fly (without mutating adata). Parameters ---------- - adata : anndata object - anndata object with var_names as variable names. + adata : AnnData + Object with var_names as variable names. key : str, optional - key from adata.varp. The default is None. - If None, and only one key is found in adata.varp, will use this key. - Otherwise if several keys are found in adata.varp, will raise an error. - columns : list, optional - Columns names of the output DataFrame. - The default is ['Peak1', 'Peak2', 'score']. + Key from adata.varp. If None and only one key exists, that one is used. + columns : tuple[str, str, str] + Output column names (Peak1, Peak2, score). Returns ------- - DataFrame - DataFrame with columns names given by 'columns' parameter. + pandas.DataFrame + DataFrame with columns given by `columns`, sorted by descending score. """ - - if key is None: # if only one key (I guess often), no need to precise key - # maybe replace by a default one later - if len(list(adata.varp)) == 1: - key = list(adata.varp)[0] + # ----- choose key ----- + if key is None: + keys = list(adata.varp) + if len(keys) == 1: + key = keys[0] else: raise KeyError( - "Several keys were found in adata.varp: {}, ".format( - list(adata.varp)) + - "please precise which keyword use (arg 'key'))" + "Several keys were found in adata.varp: {}. " + "Please specify which key to use (arg 'key').".format(keys) ) + elif key not in adata.varp: + raise KeyError(f"The key you provided ({key}) is not in adata.varp: {list(adata.varp)}") + + mat = adata.varp[key] + + # ----- ensure sparse, prefer CSR/CSC ----- + if not sp.sparse.issparse(mat): + # fall back to CSR if a dense array sneaks in + mat = sp.sparse.csr_matrix(mat) + + fmt = mat.getformat() + if fmt == "csr": + # Filter to strict upper triangle without converting to COO + # (row < col) by using triu in CSR, then extract indices fast. + u = sp.sparse.triu(mat, k=1, format="csr") + indptr, indices, data = u.indptr, u.indices, u.data + # build row indices aligned with data in O(nnz) + rows = np.repeat(np.arange(u.shape[0], dtype=np.int64), np.diff(indptr)) + cols = indices + + elif fmt == "csc": + # Do the same in CSC + u = sp.sparse.triu(mat, k=1, format="csc") + indptr, indices, data = u.indptr, u.indices, u.data + # in CSC, indices are row indices; build column indices + cols = np.repeat(np.arange(u.shape[1], dtype=np.int64), np.diff(indptr)) + rows = indices + else: - if key not in list(adata.varp): - raise KeyError("The key you provided ({}) is not in adata.varp: {}" - .format(key, list(adata.varp)) - ) - - # Convert to COO format if needed - converted = False - if isinstance(adata.varp[key], sp.sparse.csr_matrix): - adata.varp[key] = adata.varp[key].tocoo() - converted = True - - links = pd.DataFrame( - [(row, col, data) for (row, col, data) in zip( - [i for i in adata.varp[key].row], - [i for i in adata.varp[key].col], - adata.varp[key].data) - if row < col], - columns=columns - ).sort_values(by=columns[2], ascending=False) - - links[columns[0]] = [adata.var_names[i] for i in links[columns[0]]] - links[columns[1]] = [adata.var_names[i] for i in links[columns[1]]] - links = links.reset_index(drop=True) - - # Convert back to CSR format if it was converted - if converted: - adata.varp[key] = adata.varp[key].tocsr() - - return links + # Other formats: convert once to CSR (local copy), then proceed + u = sp.sparse.triu(mat.tocsr(), k=1, format="csr") + indptr, indices, data = u.indptr, u.indices, u.data + rows = np.repeat(np.arange(u.shape[0], dtype=np.int64), np.diff(indptr)) + cols = indices + + # ----- build DataFrame ----- + df = pd.DataFrame({ + columns[0]: rows, + columns[1]: cols, + columns[2]: data + }) + + # map indices -> peak names (vectorized) + var_names = np.asarray(adata.var_names) + df[columns[0]] = var_names[df[columns[0]].to_numpy()] + df[columns[1]] = var_names[df[columns[1]].to_numpy()] + + # sort by score desc and reset index + df = df.sort_values( + by=columns[2], + ascending=False, + kind="mergesort").reset_index(drop=True) + return df diff --git a/setup.py b/setup.py index 3de3043..5415292 100644 --- a/setup.py +++ b/setup.py @@ -68,7 +68,7 @@ def build_extensions(self): setup( name='circe-py', - version='0.3.8', + version='0.3.9', description='Circe: Package for building co-accessibility networks from ATAC-seq data.', long_description=long_description, long_description_content_type='text/markdown', @@ -94,7 +94,7 @@ def build_extensions(self): 'scikit-learn>=1.6', 'joblib>=1.1.0', 'scanpy>=1.8.1', - 'anndata<0.12', + 'anndata', 'rich>=10.12.0', 'dask', 'distributed', diff --git a/tests/test_network/test_network.py b/tests/test_network/test_network.py index 390e396..cd9d86d 100644 --- a/tests/test_network/test_network.py +++ b/tests/test_network/test_network.py @@ -1,9 +1,12 @@ import pytest import circe as ci +import circe.downloads import anndata as ad import scipy as sp import numpy as np import pandas as pd +import matplotlib.pyplot as plt + import matplotlib.pyplot as plt @@ -154,7 +157,11 @@ def test_network_atac(): with pytest.raises(Exception): ci.extract_atac_links(atac) - # Test if many varp keys are present and good one given + # Test if many varp keys are present and good one given, on a dense and csc matrix formats + atac.varp["atac_network2"] = sp.sparse.csc_matrix(atac.varp["atac_network2"]) + atac_df = ci.extract_atac_links(atac, key="atac_network2") + + atac.varp["atac_network2"] = atac.varp["atac_network2"].toarray() atac_df = ci.extract_atac_links(atac, key="atac_network2") # Test if key given is wrong @@ -185,3 +192,40 @@ def test_network_atac(): # Test if wrong start or end column name is given with pytest.raises(Exception) as ValueError: ci.draw.plot_connections(atac_df, "chr1", 0, 0, sep=('_', '_')) + + # Download gene annotations + genes_df = ci.downloads.download_genes() + + fig, ax = plt.subplots(1, figsize=(20, 6)) + ci.draw.plot_connections_genes( + connections=atac_df, + genes=genes_df, + chromosome="chr1", + start=50_000, + end=350_000, + gene_spacing=30_000, + y_lim_top=-0.01, + abs_threshold=0.0, + track_spacing=0.01, + track_width=0.01, + legend=True, + ax=ax + ) + + with pytest.raises(Exception) as ValueError: + ci.draw.plot_connections_genes( + connections=atac_df, + genes=genes_df, + chromosome="chr100", + start=50_000, + end=350_000, + ) + + with pytest.raises(Exception) as ValueError: + ci.draw.plot_connections_genes( + connections=atac, + genes=genes_df[-5:], + chromosome="chr1", + start=350_000, + end=50_000, + ) \ No newline at end of file From f517bc1b707d4cdf1f67f24b3a513891ab49fb8a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Trimbour?= <77151348+r-trimbour@users.noreply.github.com> Date: Sun, 7 Sep 2025 00:48:49 +0200 Subject: [PATCH 25/33] Update codecov.yaml --- .github/workflows/codecov.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/codecov.yaml b/.github/workflows/codecov.yaml index 7cbfdae..30baeee 100644 --- a/.github/workflows/codecov.yaml +++ b/.github/workflows/codecov.yaml @@ -24,7 +24,7 @@ jobs: - name: Run tests and collect coverage run: | pip install -e . --config-settings editable_mode=compat - pip install pytest-cov + pip install pytest-cov pybiomart python -c 'import os; os.chdir("tests/"); import circe.pyquic; print(circe.pyquic)' pytest -s --cov "circe" - name: Upload coverage to Codecov From 764e73cab92e0585e2a26e083d7c68af44bc60de Mon Sep 17 00:00:00 2001 From: r-trimbour Date: Sun, 7 Sep 2025 23:10:09 +0200 Subject: [PATCH 26/33] add structure readthedocs website --- docs/Makefile | 20 + docs/make.bat | 35 + .../circe_explained/1_circe_installation.rst | 47 + .../circe_explained/1_circe_summary.rst | 31 + docs/source/circe_explained/2_algorithm.rst | 68 + .../circe_explained/circe_preprocessing.md | 20 + docs/source/circe_explained/circe_scores.md | 1 + docs/source/conf.py | 29 + docs/source/examples/1_Minimal_example.ipynb | 1053 +++++++++++++ docs/source/examples/2_Detailed_example.ipynb | 1401 +++++++++++++++++ .../Visualize co-accessible DNA regions.ipynb | 902 +++++++++++ docs/source/index.rst | 181 +++ 12 files changed, 3788 insertions(+) create mode 100644 docs/Makefile create mode 100644 docs/make.bat create mode 100644 docs/source/circe_explained/1_circe_installation.rst create mode 100644 docs/source/circe_explained/1_circe_summary.rst create mode 100644 docs/source/circe_explained/2_algorithm.rst create mode 100644 docs/source/circe_explained/circe_preprocessing.md create mode 100644 docs/source/circe_explained/circe_scores.md create mode 100644 docs/source/conf.py create mode 100644 docs/source/examples/1_Minimal_example.ipynb create mode 100644 docs/source/examples/2_Detailed_example.ipynb create mode 100644 docs/source/examples/Visualize co-accessible DNA regions.ipynb create mode 100644 docs/source/index.rst diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..d0c3cbf --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,20 @@ +# 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) diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 0000000..747ffb7 --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,35 @@ +@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/source/circe_explained/1_circe_installation.rst b/docs/source/circe_explained/1_circe_installation.rst new file mode 100644 index 0000000..0a092a8 --- /dev/null +++ b/docs/source/circe_explained/1_circe_installation.rst @@ -0,0 +1,47 @@ +Installation +------------ + +CIRCE requires Python 3.8+ and can be installed via pip or from source. It is recommended to use a virtual environment or a conda environment to manage dependencies. + + +The package can be installed using pip: + +.. code-block:: python + + pip install circe-py + +and from github + +.. code-block:: python + + pip install "git+https://github.com/cantinilab/circe.git" + + +Essential dependencies +~~~~~~~~~~~~~~~~~~~~~~~~~~ +Since CIRCE depends on `lapack `__ and `blas `__ to compute the graphical lasso, you may need to install these libraries first. + +It means that you might not be able to use CIRCE in a standard Windows environment without WSL or similar. +For that, you can use a singularity or docker container, such as provided here (`singularity `__). + +If you are working in a conda environment and are encountering any issue with the installation you can try installing these dependencies via: + +.. code-block:: bash + + conda install conda-forge::lapack + conda install libfortran=3 + + conda install gxx_linux-64 + +IF you are not workign with conda, +on Ubuntu, you can do this via: + +.. code-block:: bash + + sudo apt-get install libblas-dev liblapack-dev + +On macOS, you can use Homebrew: + +.. code-block:: bash + + brew install openblas diff --git a/docs/source/circe_explained/1_circe_summary.rst b/docs/source/circe_explained/1_circe_summary.rst new file mode 100644 index 0000000..c721821 --- /dev/null +++ b/docs/source/circe_explained/1_circe_summary.rst @@ -0,0 +1,31 @@ +How does CIRCE work? +=============== + +Intuition +--------- +Accessible regulatory regions that tend to be co-accessible across cells are candidates for +cis-regulatory interactions. CIRCE estimates these relationships using a graphical lasso model +that **penalizes long-range pairs** according to genomic distance and computes within a local +**sliding window** (e.g., ±500 kb) to keep problems tractable. + +Main steps +---------- +1. **Dimensionality & neighbors**: compute LSI; optionally use UMAP/t-SNE only for visualization. + Nearest neighbors are determined in LSI space to avoid distortions from low-dim embeddings. +2. **Metacells (optional)**: group similar cells to reduce sparsity and scale (trade-offs discussed below). +3. **Distance-aware graphical lasso**: within each genomic window of peaks, estimate a sparse + inverse covariance with a **power-law distance penalty**. The penalty strength is chosen by + sampling windows so that long-range pairs remain sparse. +4. **Networks (CCANs)**: transform co-accessibility to a graph and call modules with Louvain. + +Implementation notes +-------------------- +- Uses a QUIC-based graphical model implementation that supports pairwise penalties. +- Stores results in the input ``AnnData``; co-accessibility is kept as a sparse matrix. +- Designed for scverse compatibility and parallel CPU execution. + +Practical defaults +------------------ +- Window size: ~500 kb for human/mouse cis interactions. +- Distance-decay exponent: species-specific (e.g., ~0.75 human/mouse; ~0.85 Drosophila). +- Penalty scaling: chosen by random-window search to ensure sparsity of long-range edges. diff --git a/docs/source/circe_explained/2_algorithm.rst b/docs/source/circe_explained/2_algorithm.rst new file mode 100644 index 0000000..c1ce828 --- /dev/null +++ b/docs/source/circe_explained/2_algorithm.rst @@ -0,0 +1,68 @@ +Overview and algorithm +=================================== + +What is CIRCE? +-------------- +CIRCE predicts **cis-regulatory interactions** (co-accessibility links between peaks) from +single-cell ATAC-seq. It follows the algorithm of Cicero [1] but is implemented natively in Python, +integrates with the scverse/AnnData stack, and is engineered for speed and scale. + +The algorithm in 10 lines +------------------------- +#. **Inputs**: a sparse peak × cell matrix ``X`` in ``AnnData`` (``adata.X``) and genomic + coordinates for peaks in ``adata.var`` (chrom, start, end). +#. **Optional metacells**: group similar cells to reduce sparsity/size (trade-off: slight + performance drop vs single-cell inputs). +#. **LSI + neighbors**: compute LSI on TF–IDF-like transforms; determine neighbors in **LSI + space** (not in UMAP/t‑SNE) to avoid metric distortion. +#. **Genomic windowing**: split each chromosome into overlapping windows (e.g., ±500 kb) so + each optimization is small and locality-aware. +#. **Empirical covariance**: for peaks inside a window, compute a covariance surrogate across + cells (or metacells); optionally neighbor-aggregate counts to stabilize estimates. +#. **Distance‑aware graphical lasso**: estimate a sparse precision matrix ``Θ`` by minimizing a + penalized likelihood, where **penalties grow with genomic distance** so long‑range pairs are + discouraged: + + .. math:: + + \min_{\Theta \succ 0} \; \tfrac{1}{2} \mathrm{tr}(S\Theta) - \log\det\Theta + + \sum_{i]``; each nonzero is a peak‑pair score. +- **Networks**: CCAN membership and per‑module summaries (size, density, representative peaks). +- **Tables**: exportable dataframe with (Peak1, Peak2, score, distance, chromosome, window_id). + +Notes & limitations +------------------- +- Co‑accessibility is **not causality**; validate with orthogonal assays (e.g., PC‑HiC). +- Metacells reduce runtime/sparsity but can slightly degrade validation; single‑cell inputs + performed best in our benchmarks. +- Long ranges (>500 Kb) are intentionally penalized and very long ranges (> 500Kb) are fully ignored with default parameters; tune if your biology requires larger spans. + + + +Sources +------------------- +[1] Pliner et al., *Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data*, Mol Cell, 2018. \ No newline at end of file diff --git a/docs/source/circe_explained/circe_preprocessing.md b/docs/source/circe_explained/circe_preprocessing.md new file mode 100644 index 0000000..1731391 --- /dev/null +++ b/docs/source/circe_explained/circe_preprocessing.md @@ -0,0 +1,20 @@ +Preprocessing choices +================================= + +Single-cell vs metacells +------------------------ +- **Single-cell inputs** typically yield **better validation** versus PC-HiC interactions. +- **Metacells** can reduce compute and sparsity but showed a small AUC drop in the tested defaults. + +Binarization & count correction +------------------------------- +- Simple **binarization** of counts did not notably improve predictions over raw counts. +- The traditional **Cicero count correction** decreased performance in benchmarks. + +Neighbors space +--------------- +- Build neighbors in **LSI space** rather than low-dimensional UMAP/t-SNE to preserve distances. + +Matrix format tips +------------------ +- For very large atlases, store your peak-by-cell matrix as **CSC** to accelerate column extraction. diff --git a/docs/source/circe_explained/circe_scores.md b/docs/source/circe_explained/circe_scores.md new file mode 100644 index 0000000..afec206 --- /dev/null +++ b/docs/source/circe_explained/circe_scores.md @@ -0,0 +1 @@ +# Understanding CIRCE's scores \ No newline at end of file diff --git a/docs/source/conf.py b/docs/source/conf.py new file mode 100644 index 0000000..3cf6110 --- /dev/null +++ b/docs/source/conf.py @@ -0,0 +1,29 @@ +# 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 + +project = 'CIRCE' +copyright = '2025, Remi Trimbour' +author = 'Remi Trimbour' +release = '0.3.8' + +# -- General configuration --------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration + +extensions = ["myst_nb"] +jupyter_execute_notebooks = "off" + +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 = 'furo' +html_static_path = ['_static'] \ No newline at end of file diff --git a/docs/source/examples/1_Minimal_example.ipynb b/docs/source/examples/1_Minimal_example.ipynb new file mode 100644 index 0000000..3435513 --- /dev/null +++ b/docs/source/examples/1_Minimal_example.ipynb @@ -0,0 +1,1053 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "091be986-ff7a-4697-9c5a-7f8094642cda", + "metadata": {}, + "source": [ + "# **Minimal example - networks and metacells**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "18bcf460-6d87-487c-8433-7fa9f898970a", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import circe as ci\n", + "import scanpy as sc\n", + "import scipy as sp" + ] + }, + { + "cell_type": "markdown", + "id": "56049b45", + "metadata": {}, + "source": [ + "## 0. Import (or create) data" + ] + }, + { + "cell_type": "markdown", + "id": "3972a885-0c5c-4378-81c2-26b7cfdee1f6", + "metadata": { + "tags": [] + }, + "source": [ + "#### Create fake AnnData" + ] + }, + { + "cell_type": "markdown", + "id": "1d0ec88e-0410-4e5c-a2d1-beb196b02b16", + "metadata": {}, + "source": [ + "This data doesn't contain strong correlation between fake regions, the score will then be low. \n", + "\n", + "It will still allow us to demonstrate how to use Circe. :)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "79295862-9df3-4fa4-a32c-0931c73c705f", + "metadata": {}, + "outputs": [], + "source": [ + "atac = sc.datasets.blobs(n_centers=8, n_variables=2_000, n_observations=300, random_state=1)\n", + "atac.X = np.random.poisson(lam=0.2, size=atac.X.shape)\n", + "cell_names = [f\"cell_{i}\" for i in range(1, atac.shape[0]+1)]\n", + "# number of chr_start_end region names\n", + "region_names = [[f\"chr{i}_{str(j)}_{str(j+399)}\" \n", + " for j in range(1, 10000*400+1, 10000)] \n", + " for i in range(1, 6)]\n", + "regions_names = [item for sublist in region_names for item in sublist]\n", + "# select a random number of regions per cell, and make it 0\n", + "for i in range(atac.shape[0]):\n", + " num_regions = np.random.randint(500, 1000)\n", + " region_indices = np.random.choice(len(regions_names), num_regions, replace=False)\n", + " atac.X[i, region_indices] = 0\n", + "\n", + "atac.var_names = regions_names\n", + "atac.obs_names = cell_names" + ] + }, + { + "cell_type": "markdown", + "id": "5f4fbec1", + "metadata": {}, + "source": [ + "## 1. Preprocess the data" + ] + }, + { + "cell_type": "markdown", + "id": "50a80d79-8423-473a-9810-6dc35b7e9900", + "metadata": { + "tags": [] + }, + "source": [ + "#### 1.1. Filter the data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "30d98f97-b3b5-4d21-ae8f-4de6c9797f29", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "sc.pp.filter_genes(atac, min_cells=30)\n", + "sc.pp.filter_cells(atac, min_genes=20)" + ] + }, + { + "cell_type": "markdown", + "id": "e52b2c18", + "metadata": {}, + "source": [ + "_Make sure to all your features (peaks) are expressed in at least 1 of the cells:_" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "af47d8e1", + "metadata": {}, + "outputs": [], + "source": [ + "sc.pp.filter_genes(atac, min_counts=1)" + ] + }, + { + "cell_type": "markdown", + "id": "56bbfdba-4447-4778-b4d7-83be18c8923f", + "metadata": { + "tags": [] + }, + "source": [ + "### 1.2. Add region position in AnnData.obs" + ] + }, + { + "cell_type": "markdown", + "id": "42c7fb90-ff33-4058-b1a0-aaf99ef0719f", + "metadata": {}, + "source": [ + "Let's first run `add_region_infos` that will **add coordinate annotations** `chr`, `start`, `end` as columns in `atac.var` slot" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "2feb1282-0e2b-4e10-bb8b-8f448e4ca2a6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " n_cells n_counts chromosome start end\n", + "chr1_1_400 34 38 chr1 1 400\n", + "chr1_10001_10400 31 31 chr1 10001 10400\n", + "chr1_20001_20400 34 36 chr1 20001 20400" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ci.add_region_infos(atac, inplace=True)\n", + "atac.var.head(3)" + ] + }, + { + "cell_type": "markdown", + "id": "6d5c7a34-66cc-4587-b8d5-e485dc975fd8", + "metadata": { + "tags": [] + }, + "source": [ + "### 2. Compute pseudocells" + ] + }, + { + "cell_type": "markdown", + "id": "b38f6946-9c5d-4462-be04-04a930dc5bd2", + "metadata": {}, + "source": [ + "**Compute metacells** is an interesting step to reduce sparsity in our data, since scATAC-seq data have usually a lot of dropouts." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2d8f7966-3f9c-4d73-bd67-5bef4fabd53f", + "metadata": { + "scrolled": true, + "tags": [] + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bfd769df251344f48141c7d2ee30269e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "metacells = ci.metacells.compute_metacells(atac)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "85c4ee0a-eab8-4516-b37a-39504615484d",
+   "metadata": {},
+   "source": [
+    "You can also use your own dimensionality reduction space, that would be stored in the atac.obsm slot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "72d6916a-8006-4b98-a5ed-645167dbab79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "atac.obsm[\"dim_reduction_name\"] = atac.X"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "3ca0b58c-6e96-4847-8a42-f79e011df286",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using adata.obsm['dim_reduction_name'] to identify neighboring cells\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "40a350f9b140462b9289791ebb168378",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "AnnData object with n_obs × n_vars = 300 × 1568\n",
+       "    var: 'n_cells', 'n_counts', 'chromosome', 'start', 'end'"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ci.metacells.compute_metacells(atac, dim_reduction=\"dim_reduction_name\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23c4e2ef-c346-4c63-9efb-8e4bbeb95cb2",
+   "metadata": {},
+   "source": [
+    "### 3. Calculate co-accessibility"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44cf4011-9929-432e-9d8c-59e903e4cb88",
+   "metadata": {},
+   "source": [
+    "#### 3.A. Human datasets"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8cab636-4a10-40cd-a347-5f3e3269f16e",
+   "metadata": {},
+   "source": [
+    "We can finally **compute all the cis co-accessibility scores** ! 
\n",
+    "The default way is to **indicate your organism** if among the one known by Circe.
\n",
+    "The atac network is stored automatically as a sparse matrix in `atac.varp[\"atac_network\"]`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "85035bc6-5fa6-4cef-839f-7a9f12926753",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "629efb5ef5d64625a809a2d82492be9e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "14101746ec6e4fb1add5cdd914e6302e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calculating co-accessibility scores...\n",
+      "Concatenating results from all chromosomes...\n"
+     ]
+    }
+   ],
+   "source": [
+    "ci.compute_atac_network(\n",
+    "    metacells,\n",
+    "    njobs=3, verbose=0,\n",
+    "    window_size=100000,\n",
+    "    unit_distance=1000,\n",
+    "    distance_constraint=50000,\n",
+    "    s=0.75,)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aad0c904-effe-43a0-b504-d12089176550",
+   "metadata": {},
+   "source": [
+    "### 4. Extract connections"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "735f7800-4f9a-4526-853c-d878f031dbf5",
+   "metadata": {},
+   "source": [
+    "#### 4.A.Get the whole genome cis-coaccessible network\n",
+    "\n",
+    "You can **extract connections** from the atac.varp slot (sparse matrix), as a `DataFrame object` with `extract_atac_links`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0a26c332-5a1e-4b10-bf0b-3e6339dace60",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Peak1Peak2score
0chr1_1480001_1480400chr1_1540001_15404000.377099
1chr4_1600001_1600400chr4_1680001_16804000.323789
2chr4_10001_10400chr4_90001_904000.298156
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                  Peak1                 Peak2     score\n",
+       "0  chr1_1480001_1480400  chr1_1540001_1540400  0.377099\n",
+       "1  chr4_1600001_1600400  chr4_1680001_1680400  0.323789\n",
+       "2      chr4_10001_10400      chr4_90001_90400  0.298156"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circe_network = ci.extract_atac_links(metacells) #atac)\n",
+    "circe_network.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07516731-4de2-48c6-bd59-5fcffca34084",
+   "metadata": {},
+   "source": [
+    "#### 4.B. Subset the AnnData object to a given window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8a1bc5a-dfc0-4437-aed6-2e6606165378",
+   "metadata": {},
+   "source": [
+    "If you're interested in a specific genomic region only, you can also **subset your anndata object** on this specific window"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "f699ad6c",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "subset_atac = ci.subset_region(metacells, \"chr1\", 10_000, 200_000).copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "39d41ca4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Peak1Peak2score
0chr1_70001_70400chr1_130001_1304000.092886
1chr1_60001_60400chr1_90001_904000.000373
2chr1_100001_100400chr1_190001_1904000.000067
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                Peak1               Peak2     score\n",
+       "0    chr1_70001_70400  chr1_130001_130400  0.092886\n",
+       "1    chr1_60001_60400    chr1_90001_90400  0.000373\n",
+       "2  chr1_100001_100400  chr1_190001_190400  0.000067"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circe_network_subset = ci.extract_atac_links(subset_atac)\n",
+    "circe_network_subset.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1c66dcfb-1a1d-4309-bf57-ee9b4ee1f3b4",
+   "metadata": {},
+   "source": [
+    "### 5. Plot co-accessibility scores in a window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a2beae63-65f4-4642-a876-e01a271db740",
+   "metadata": {},
+   "source": [
+    "You can pass either your `anndata` object or your freshly extracted `dataframe` into `plot_connections` to **visualize all Circe scores**.
\n",
+    "**Blue edges** correspond to positive co-accessibility scores, while **yellow ones** are for negative scores"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "7e256844-e050-49fc-b811-191b0cf17561",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.plot_connections(\n",
+    "    circe_network,\n",
+    "    chromosome=\"chr2\",\n",
+    "    start=10_000,\n",
+    "    end=200_000,\n",
+    "    sep=(\"_\",\"_\"),\n",
+    "    abs_threshold=0.01\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "0c3bef89",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.plot_connections(\n",
+    "    metacells,\n",
+    "    chromosome=\"chr2\",\n",
+    "    start=10_000,\n",
+    "    end=200_000,\n",
+    "    sep=(\"_\",\"_\"),\n",
+    "    abs_threshold=0.01\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdcb097f-a019-4caa-8b0d-b393bc737156",
+   "metadata": {},
+   "source": [
+    "### 6. Find cis-coaccessible connected modules"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "366c168b-3f25-41a8-96f3-ae876f20715e",
+   "metadata": {},
+   "source": [
+    "In addition to pairwise co-accessibility scores, Circe can also be used to **define cis co-accessibility modules** (called CCANs by Cicero), which are modules of sites that are highly co-accessible with one another. We use the Louvain community detection algorithm (Blondel et al., 2008) to find clusters of sites that tended to be co-accessible.
\n",
+    "- The function `find_ccans` takes as input a `connection data frame` or the `anndata object` once again, and outputs a data frame with CCAN assignments for each input peak.
\n",
+    "- You can also use `add_ccans` to directly add CCAN assignments to your anndata object as `anndata.var['CCAN']`. The regions that aren't assigned to a CCAN will contain `None`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "7e1f81d1-bb58-48aa-8d67-ec4720cad498",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Coaccessibility cutoff used: 0.01\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
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+       "    \n",
+       "  \n",
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+       "      \n",
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+       "    \n",
+       "  \n",
+       "
n_cellsn_countschromosomestartendCCAN
chr1_1_4003438chr11400None
chr1_10001_104003131chr11000110400None
chr1_20001_204003436chr12000120400None
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                  n_cells  n_counts chromosome  start    end  CCAN\n",
+       "chr1_1_400             34        38       chr1      1    400  None\n",
+       "chr1_10001_10400       31        31       chr1  10001  10400  None\n",
+       "chr1_20001_20400       34        36       chr1  20001  20400  None"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metacells = ci.add_ccans(metacells)\n",
+    "metacells.var.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "9c795c97-91fd-4512-89c8-b931296c7abc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CCAN\n",
+       "0      14\n",
+       "75     14\n",
+       "162    12\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metacells.var['CCAN'].value_counts().head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b02d2de-2d7c-41ad-85cc-34c1179e2c90",
+   "metadata": {},
+   "source": [
+    "#### 6.B. Plot only a CCAN module"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df4a6121-0aad-4563-925d-bdd0b06e96de",
+   "metadata": {},
+   "source": [
+    "If you're interested in a specific CCAN module, you can use `circe.draw.plot_ccan` function, precising its CCAN name. Only the connections between **regions belonging to this CCAN module will be plotted**."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "4d2d830d-c3f8-4417-b441-697a8eb43c4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This CCAN module is on the chromosome: chr3\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/rtrimbou/ATACNet/circe/circe/draw.py:244: UserWarning: varp parameter is ignored for DataFrame input.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.draw.plot_ccan(\n",
+    "    metacells,\n",
+    "    ccan_module=metacells.var['CCAN'].value_counts().index[1],\n",
+    "    sep=('_', '_'),\n",
+    "    abs_threshold=0,\n",
+    "    figsize=(15,5),\n",
+    "    only_positive=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46a807ab-4eaa-4951-9f45-eae267bc2ab7",
+   "metadata": {},
+   "source": [
+    "### 7.Coordinates overlap between co-accessible regions and gene bodies"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17d516e3-76b7-454c-b4d5-f8494c549014",
+   "metadata": {},
+   "source": [
+    "To better understand the role of specific regions and modules, you can additionally plot **gene bodies** falling into your window of interest.\n",
+    "
 You need first to load gene coordinates as a dataframe, or to download them through `circe.downloads.download_genes`. This functions will require to install the `pybiomart` package Then you can use `ci.draw.plot_connections_genes`, using gene infos and either your AnnData object or the dataframe of Circe's results to compare these locations. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "4e614cf2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: pybiomart in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (0.2.0)\n",
+      "Requirement already satisfied: future in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (1.0.0)\n",
+      "Requirement already satisfied: pandas in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (2.2.3)\n",
+      "Requirement already satisfied: requests in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (2.32.3)\n",
+      "Requirement already satisfied: requests-cache in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (1.2.1)\n",
+      "Requirement already satisfied: numpy>=1.22.4 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (1.26.4)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2.9.0.post0)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2025.1)\n",
+      "Requirement already satisfied: tzdata>=2022.7 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2025.1)\n",
+      "Requirement already satisfied: charset_normalizer<4,>=2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (3.4.1)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (3.10)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (2.2.1)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (2024.12.14)\n",
+      "Requirement already satisfied: attrs>=21.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (25.1.0)\n",
+      "Requirement already satisfied: cattrs>=22.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (24.1.2)\n",
+      "Requirement already satisfied: platformdirs>=2.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (4.3.6)\n",
+      "Requirement already satisfied: url-normalize>=1.4 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (1.4.3)\n",
+      "Requirement already satisfied: exceptiongroup>=1.1.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from cattrs>=22.2->requests-cache->pybiomart) (1.2.2)\n",
+      "Requirement already satisfied: typing-extensions!=4.6.3,>=4.1.0 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from cattrs>=22.2->requests-cache->pybiomart) (4.12.2)\n",
+      "Requirement already satisfied: six>=1.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from python-dateutil>=2.8.2->pandas->pybiomart) (1.17.0)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install pybiomart"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0e6fc9fa-98e0-4b95-a95e-92be187a138f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import circe.downloads\n",
+    "genes_df = ci.downloads.download_genes()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "094a89c8-8eda-4bae-86cf-cad7a39a276a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "fig, ax = plt.subplots(1, figsize = (20, 6))\n",
+    "ci.draw.plot_connections_genes(\n",
+    "    connections=metacells,\n",
+    "    genes=genes_df,\n",
+    "    chromosome=\"chr1\",\n",
+    "    start=50_000,\n",
+    "    end=350_000,\n",
+    "    gene_spacing=30_000,\n",
+    "    y_lim_top=-0.01,\n",
+    "    abs_threshold=0.0,\n",
+    "    track_spacing=0.01,\n",
+    "    track_width=0.01,\n",
+    "    legend=True,\n",
+    "    ax=ax\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af6228fc-9bb2-4fda-9467-b739d8d6a54b",
+   "metadata": {},
+   "source": [
+    "### 7. Work in progress! Happy to get feedbacks :)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79257a67-9d1e-4b22-8dc6-40a95b1b1ede",
+   "metadata": {},
+   "source": [
+    "If you feel any function could be useful for you on others, don't hesitate to write me at `remi.trimbour@pasteur.fr` or to submit an issue on `github.com/cantinilab/Circe`."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "circe_local",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/source/examples/2_Detailed_example.ipynb b/docs/source/examples/2_Detailed_example.ipynb
new file mode 100644
index 0000000..8efa10a
--- /dev/null
+++ b/docs/source/examples/2_Detailed_example.ipynb
@@ -0,0 +1,1401 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "091be986-ff7a-4697-9c5a-7f8094642cda",
+   "metadata": {},
+   "source": [
+    "# **Infer cis co-accessibility network**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "1b067826-34bf-4f3e-808f-6752527ee714",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Name: circe-py\n",
+      "Version: 0.3.8\n",
+      "Summary: Circe: Package for building co-accessibility networks from ATAC-seq data.\n",
+      "Home-page: https://github.com/cantinilab/circe\n",
+      "Author: Remi-Trimbour\n",
+      "Author-email: remi.trimbour@pasteur.fr\n",
+      "License: GPL-3.0-only\n",
+      "Location: /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages\n",
+      "Editable project location: /home/rtrimbou/ATACNet/circe\n",
+      "Requires: anndata, attrs, Cython, dask, distributed, joblib, numpy, pandas, rich, scanpy, scikit-learn\n",
+      "Required-by: \n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip show circe-py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "18bcf460-6d87-487c-8433-7fa9f898970a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import circe as ci\n",
+    "import scanpy as sc\n",
+    "import scipy as sp"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56049b45",
+   "metadata": {},
+   "source": [
+    "## 0. Import (or create) data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3972a885-0c5c-4378-81c2-26b7cfdee1f6",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### Create fake AnnData"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d0ec88e-0410-4e5c-a2d1-beb196b02b16",
+   "metadata": {},
+   "source": [
+    "This data doesn't contain strong correlation between fake regions, the score will then be low. \n",
+    "\n",
+    "It will still allow us to demonstrate how to use Circe. :)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "79295862-9df3-4fa4-a32c-0931c73c705f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "atac = sc.datasets.blobs(n_centers=8, n_variables=2_000, n_observations=300, random_state=1)\n",
+    "atac.X = np.random.poisson(lam=0.2, size=atac.X.shape)\n",
+    "cell_names = [f\"cell_{i}\" for i in range(1, atac.shape[0]+1)]\n",
+    "# number of chr_start_end region names\n",
+    "region_names = [[f\"chr{i}_{str(j)}_{str(j+399)}\" \n",
+    "                 for j in range(1, 10000*400+1, 10000)] \n",
+    "                for i in range(1, 6)]\n",
+    "regions_names = [item for sublist in region_names for item in sublist]\n",
+    "# select a random number of regions per cell, and make it 0\n",
+    "for i in range(atac.shape[0]):\n",
+    "    num_regions = np.random.randint(500, 1000)\n",
+    "    region_indices = np.random.choice(len(regions_names), num_regions, replace=False)\n",
+    "    atac.X[i, region_indices] = 0\n",
+    "\n",
+    "atac.var_names = regions_names\n",
+    "atac.obs_names = cell_names"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f4fbec1",
+   "metadata": {},
+   "source": [
+    "## 1. Preprocess the data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "50a80d79-8423-473a-9810-6dc35b7e9900",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### 1.1. Filter the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "30d98f97-b3b5-4d21-ae8f-4de6c9797f29",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "sc.pp.filter_genes(atac, min_cells=30)\n",
+    "sc.pp.filter_cells(atac, min_genes=20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e52b2c18",
+   "metadata": {},
+   "source": [
+    "_Make sure to all your features (peaks) are expressed in at least 1 of the cells:_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "af47d8e1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sc.pp.filter_genes(atac, min_counts=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56bbfdba-4447-4778-b4d7-83be18c8923f",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### 1.2. Add region position in AnnData.obs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "42c7fb90-ff33-4058-b1a0-aaf99ef0719f",
+   "metadata": {},
+   "source": [
+    "Let's first run `add_region_infos` that will **add coordinate annotations** `chr`, `start`, `end` as columns in `atac.var` slot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "2feb1282-0e2b-4e10-bb8b-8f448e4ca2a6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
n_cellsn_countschromosomestartend
chr1_20001_204003132chr12000120400
chr1_30001_304003845chr13000130400
chr1_40001_404003232chr14000140400
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                  n_cells  n_counts chromosome  start    end\n",
+       "chr1_20001_20400       31        32       chr1  20001  20400\n",
+       "chr1_30001_30400       38        45       chr1  30001  30400\n",
+       "chr1_40001_40400       32        32       chr1  40001  40400"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ci.add_region_infos(atac, inplace=True)\n",
+    "atac.var.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d5c7a34-66cc-4587-b8d5-e485dc975fd8",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### 2. Compute pseudocells"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b38f6946-9c5d-4462-be04-04a930dc5bd2",
+   "metadata": {},
+   "source": [
+    "**Compute metacells** is an interesting step to reduce sparsity in our data, since scATAC-seq data have usually a lot of dropouts."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2d8f7966-3f9c-4d73-bd67-5bef4fabd53f",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d83e721b9ccf492a80df169a7d2ed8ef",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "metacells = ci.metacells.compute_metacells(atac)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "85c4ee0a-eab8-4516-b37a-39504615484d",
+   "metadata": {},
+   "source": [
+    "You can also use your own dimensionality reduction space, that would be stored in the atac.obsm slot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "72d6916a-8006-4b98-a5ed-645167dbab79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "atac.obsm[\"dim_reduction_name\"] = atac.X"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3ca0b58c-6e96-4847-8a42-f79e011df286",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using adata.obsm['dim_reduction_name'] to identify neighboring cells\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e4541a5016514e84804e227da8c08a60",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "AnnData object with n_obs × n_vars = 299 × 1644\n",
+       "    var: 'n_cells', 'n_counts', 'chromosome', 'start', 'end'"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ci.metacells.compute_metacells(atac, dim_reduction=\"dim_reduction_name\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23c4e2ef-c346-4c63-9efb-8e4bbeb95cb2",
+   "metadata": {},
+   "source": [
+    "### 3. Calculate co-accessibility"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44cf4011-9929-432e-9d8c-59e903e4cb88",
+   "metadata": {},
+   "source": [
+    "#### 3.A. Human datasets"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8cab636-4a10-40cd-a347-5f3e3269f16e",
+   "metadata": {},
+   "source": [
+    "We can finally **compute all the cis co-accessibility scores** ! 
\n",
+    "The default way is to **indicate your organism** if among the one known by Circe.
\n",
+    "The atac network is stored automatically as a sparse matrix in `atac.varp[\"atac_network\"]`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "85035bc6-5fa6-4cef-839f-7a9f12926753",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3aa87a59bb904be0b15ac7957653a14c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1d742e87b9364053bf350b7e21a73ad3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calculating co-accessibility scores...\n",
+      "Concatenating results from all chromosomes...\n"
+     ]
+    }
+   ],
+   "source": [
+    "ci.compute_atac_network(\n",
+    "    metacells,\n",
+    "    njobs=3, verbose=0,\n",
+    "    window_size=100000,\n",
+    "    unit_distance=1000,\n",
+    "    distance_constraint=50000,\n",
+    "    s=0.75,)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "6b817a44",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "circe_network = ci.extract_atac_links(\n",
+    "    metacells)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9b5bfc6e-e0ae-4ffa-9ef3-d47648549483",
+   "metadata": {},
+   "source": [
+    "#### 3.B. Other organisms"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "92e27ea5-f8a8-4348-aaec-c8eb13b378cb",
+   "metadata": {},
+   "source": [
+    "##### If your organism is **not** \"human\", \"mouse\" or \"drosophila\", human default values will be used for:\n",
+    "`s`, `window_size` and `distance_constraint`.\n",
+    "Distance constraint is usually half of the window size.\n",
+    "\n",
+    "If you know their values,\n",
+    "you can also specify yourself the following parameters that are organism-specific."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "343cff05-6b69-4e58-9e71-144e15122adb",
+   "metadata": {},
+   "source": [
+    "#### 3.C. Use of sparse matrix"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "69f7dc04-4e27-4b18-a368-8306078e6e46",
+   "metadata": {},
+   "source": [
+    "1. Circe can also work with `sparse covariance matrix`.
"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "415223fa-1643-47cf-a1d8-bc8ae52578fd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "atac.X = sp.sparse.csr_matrix(atac.X)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "447e0022-56cc-4585-bf0e-0f651a85ac01",
+   "metadata": {},
+   "source": [
+    "2. Connections can also be stored externally from your `AnnData` object using `sliding_graphical_lasso`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "1825591f-5177-4429-8791-54ef15537e66",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/rtrimbou/ATACNet/circe/circe/circe.py:958: UserWarning: \n",
+      "                No organism, nor value passed for the parameters: ['window_size', 'distance_constraint', 's'],\n",
+      "                using default values.\n",
+      "                The default values are defined from human and mouse data,\n",
+      "                you might want to change them if you are working with\n",
+      "                another organisms.\n",
+      "\n",
+      "                Default values used:\n",
+      "                {'window_size': 500000, 'distance_constraint': 250000, 's': 0.75}\n",
+      "\n",
+      "                You can check how to define them in https://cole-trapnell-lab.github.io/cicero-release/docs_m3/#important-considerations-for-non-human-data.\n",
+      "                \n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "503b574acac84d2d80df6abc8e346413",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "63d2d036c0964d8991e7545dc8111e1d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calculating co-accessibility scores...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/rtrimbou/ATACNet/circe/circe/circe.py:1114: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  chr_var.loc[:, map_indices] = np.arange(len(chr_var), dtype=np.int64)\n",
+      "/home/rtrimbou/ATACNet/circe/circe/circe.py:1114: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  chr_var.loc[:, map_indices] = np.arange(len(chr_var), dtype=np.int64)\n",
+      "/home/rtrimbou/ATACNet/circe/circe/circe.py:1114: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  chr_var.loc[:, map_indices] = np.arange(len(chr_var), dtype=np.int64)\n",
+      "/home/rtrimbou/ATACNet/circe/circe/circe.py:1114: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  chr_var.loc[:, map_indices] = np.arange(len(chr_var), dtype=np.int64)\n",
+      "/home/rtrimbou/ATACNet/circe/circe/circe.py:1114: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  chr_var.loc[:, map_indices] = np.arange(len(chr_var), dtype=np.int64)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Concatenating results from all chromosomes...\n"
+     ]
+    }
+   ],
+   "source": [
+    "final_score = ci.sliding_graphical_lasso(\n",
+    "    metacells,\n",
+    "    n_samples=50,\n",
+    "    n_samples_maxtry=100,\n",
+    "    max_alpha_iteration=500,\n",
+    "    verbose=0\n",
+    ")\n",
+    "\n",
+    "# You can then add it in a second time\n",
+    "metacells.varp['atac_network'] = final_score"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aad0c904-effe-43a0-b504-d12089176550",
+   "metadata": {},
+   "source": [
+    "### 4. Extract connections"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "735f7800-4f9a-4526-853c-d878f031dbf5",
+   "metadata": {},
+   "source": [
+    "#### 4.A.Get the whole genome cis-coaccessible network\n",
+    "\n",
+    "You can **extract connections** from the atac.varp slot (sparse matrix), as a `DataFrame object` with `extract_atac_links`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "0a26c332-5a1e-4b10-bf0b-3e6339dace60",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
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+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Peak1Peak2score
0chr1_2770001_2770400chr1_3210001_32104000.325869
1chr1_1010001_1010400chr1_1320001_13204000.304926
2chr4_2580001_2580400chr4_2750001_27504000.300668
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                  Peak1                 Peak2     score\n",
+       "0  chr1_2770001_2770400  chr1_3210001_3210400  0.325869\n",
+       "1  chr1_1010001_1010400  chr1_1320001_1320400  0.304926\n",
+       "2  chr4_2580001_2580400  chr4_2750001_2750400  0.300668"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circe_network = ci.extract_atac_links(metacells) #atac)\n",
+    "circe_network.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07516731-4de2-48c6-bd59-5fcffca34084",
+   "metadata": {},
+   "source": [
+    "#### 4.B. Subset the AnnData object to a given window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8a1bc5a-dfc0-4437-aed6-2e6606165378",
+   "metadata": {},
+   "source": [
+    "If you're interested in a specific genomic region only, you can also **subset your anndata object** on this specific window"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "f699ad6c",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "subset_atac = ci.subset_region(metacells, \"chr1\", 10_000, 200_000).copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "39d41ca4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Peak1Peak2score
0chr1_110001_110400chr1_130001_1304000.049829
1chr1_130001_130400chr1_180001_1804000.048972
2chr1_80001_80400chr1_150001_1504000.033743
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                Peak1               Peak2     score\n",
+       "0  chr1_110001_110400  chr1_130001_130400  0.049829\n",
+       "1  chr1_130001_130400  chr1_180001_180400  0.048972\n",
+       "2    chr1_80001_80400  chr1_150001_150400  0.033743"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circe_network_subset = ci.extract_atac_links(subset_atac)\n",
+    "circe_network_subset.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1c66dcfb-1a1d-4309-bf57-ee9b4ee1f3b4",
+   "metadata": {},
+   "source": [
+    "### 5. Plot co-accessibility scores in a window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a2beae63-65f4-4642-a876-e01a271db740",
+   "metadata": {},
+   "source": [
+    "You can pass either your `anndata` object or your freshly extracted `dataframe` into `plot_connections` to **visualize all Circe scores**.
\n",
+    "**Blue edges** correspond to positive co-accessibility scores, while **yellow ones** are for negative scores"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "7e256844-e050-49fc-b811-191b0cf17561",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.plot_connections(\n",
+    "    circe_network,\n",
+    "    chromosome=\"chr2\",\n",
+    "    start=10_000,\n",
+    "    end=200_000,\n",
+    "    sep=(\"_\",\"_\"),\n",
+    "    abs_threshold=0.01\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0c3bef89",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.plot_connections(\n",
+    "    metacells,\n",
+    "    chromosome=\"chr2\",\n",
+    "    start=10_000,\n",
+    "    end=200_000,\n",
+    "    sep=(\"_\",\"_\"),\n",
+    "    abs_threshold=0.01\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdcb097f-a019-4caa-8b0d-b393bc737156",
+   "metadata": {},
+   "source": [
+    "### 6. Find cis-coaccessible connected modules"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "366c168b-3f25-41a8-96f3-ae876f20715e",
+   "metadata": {},
+   "source": [
+    "In addition to pairwise co-accessibility scores, Circe can also be used to **define cis co-accessibility modules** (called CCANs by Cicero), which are modules of sites that are highly co-accessible with one another. We use the Louvain community detection algorithm (Blondel et al., 2008) to find clusters of sites that tended to be co-accessible.
\n",
+    "- The function `find_ccans` takes as input a `connection data frame` or the `anndata object` once again, and outputs a data frame with CCAN assignments for each input peak.
\n",
+    "- You can also use `add_ccans` to directly add CCAN assignments to your anndata object as `anndata.var['CCAN']`. The regions that aren't assigned to a CCAN will contain `None`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "f8ef9ec3-d93f-4dfe-b92c-6aaae9f7e921",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Coaccessibility cutoff used: 0.02\n",
+      "Number of CCANs generated: 70\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
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+       "    \n",
+       "  \n",
+       "  \n",
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+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
PeakCCAN
0chr1_2910001_29104000
1chr1_3360001_33604000
2chr1_3400001_34004000
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                   Peak  CCAN\n",
+       "0  chr1_2910001_2910400     0\n",
+       "1  chr1_3360001_3360400     0\n",
+       "2  chr1_3400001_3400400     0"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ccans = ci.find_ccans(circe_network, seed=0)\n",
+    "ccans.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "7e1f81d1-bb58-48aa-8d67-ec4720cad498",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Coaccessibility cutoff used: 0.03\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
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+       "      \n",
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+       "    \n",
+       "  \n",
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+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
n_cellsn_countschromosomestartendCCAN
chr1_20001_204003132chr12000120400None
chr1_30001_304003845chr13000130400None
chr1_40001_404003232chr14000140400None
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                  n_cells  n_counts chromosome  start    end  CCAN\n",
+       "chr1_20001_20400       31        32       chr1  20001  20400  None\n",
+       "chr1_30001_30400       38        45       chr1  30001  30400  None\n",
+       "chr1_40001_40400       32        32       chr1  40001  40400  None"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metacells = ci.add_ccans(metacells)\n",
+    "metacells.var.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "9c795c97-91fd-4512-89c8-b931296c7abc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CCAN\n",
+       "35    52\n",
+       "37    42\n",
+       "8     36\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metacells.var['CCAN'].value_counts().head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "538af36a-102d-475d-80cb-4e7aaa1212ed",
+   "metadata": {},
+   "source": [
+    "With default `coaccess_cutoff_override=None`, the function will determine and report an appropriate co-accessibility score cutoff value for CCAN generation based on the number of overall CCANs at varying cutoffs. You can also set `coaccess_cutoff_override` to be a numeric between 0 and 1, to override the cutoff-finding part of the function. This option is useful if you feel that the cutoff found automatically was too strict or loose, or for speed if you are rerunning the code and know what the cutoff will be, since the cutoff finding procedure can be slow. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "38c8d848-287b-4200-b7be-434b65bf0dbf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Coaccessibility cutoff used: 1e-07\n",
+      "Number of CCANs generated: 37\n"
+     ]
+    }
+   ],
+   "source": [
+    "ccans = ci.find_ccans(circe_network, seed=0, coaccess_cutoff_override=1e-7)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b02d2de-2d7c-41ad-85cc-34c1179e2c90",
+   "metadata": {},
+   "source": [
+    "#### 6.B. Plot only a CCAN module"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df4a6121-0aad-4563-925d-bdd0b06e96de",
+   "metadata": {},
+   "source": [
+    "If you're interested in a specific CCAN module, you can use `circe.draw.plot_ccan` function, precising its CCAN name. Only the connections between **regions belonging to this CCAN module will be plotted**."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "4d2d830d-c3f8-4417-b441-697a8eb43c4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This CCAN module is on the chromosome: chr3\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/rtrimbou/ATACNet/circe/circe/draw.py:244: UserWarning: varp parameter is ignored for DataFrame input.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.draw.plot_ccan(\n",
+    "    metacells,\n",
+    "    ccan_module=metacells.var['CCAN'].value_counts().index[1],\n",
+    "    sep=('_', '_'),\n",
+    "    abs_threshold=0,\n",
+    "    figsize=(15,5),\n",
+    "    only_positive=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46a807ab-4eaa-4951-9f45-eae267bc2ab7",
+   "metadata": {},
+   "source": [
+    "### 7.Coordinates overlap between co-accessible regions and gene bodies"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17d516e3-76b7-454c-b4d5-f8494c549014",
+   "metadata": {},
+   "source": [
+    "To better understand the role of specific regions and modules, you can additionally plot **gene bodies** falling into your window of interest.\n",
+    "
 You need first to load gene coordinates as a dataframe, or to download them through `circe.downloads.download_genes`. This functions will require to install the `pybiomart` package Then you can use `ci.draw.plot_connections_genes`, using gene infos and either your AnnData object or the dataframe of Circe's results to compare these locations. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "4e614cf2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: pybiomart in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (0.2.0)\n",
+      "Requirement already satisfied: future in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (1.0.0)\n",
+      "Requirement already satisfied: pandas in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (2.2.3)\n",
+      "Requirement already satisfied: requests in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (2.32.3)\n",
+      "Requirement already satisfied: requests-cache in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pybiomart) (1.2.1)\n",
+      "Requirement already satisfied: numpy>=1.22.4 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (1.26.4)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2.9.0.post0)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2025.1)\n",
+      "Requirement already satisfied: tzdata>=2022.7 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from pandas->pybiomart) (2025.1)\n",
+      "Requirement already satisfied: charset_normalizer<4,>=2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (3.4.1)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (3.10)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (2.2.1)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests->pybiomart) (2024.12.14)\n",
+      "Requirement already satisfied: attrs>=21.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (25.1.0)\n",
+      "Requirement already satisfied: cattrs>=22.2 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (24.1.2)\n",
+      "Requirement already satisfied: platformdirs>=2.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (4.3.6)\n",
+      "Requirement already satisfied: url-normalize>=1.4 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from requests-cache->pybiomart) (1.4.3)\n",
+      "Requirement already satisfied: exceptiongroup>=1.1.1 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from cattrs>=22.2->requests-cache->pybiomart) (1.2.2)\n",
+      "Requirement already satisfied: typing-extensions!=4.6.3,>=4.1.0 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from cattrs>=22.2->requests-cache->pybiomart) (4.12.2)\n",
+      "Requirement already satisfied: six>=1.5 in /home/rtrimbou/miniconda3/envs/circe_local/lib/python3.10/site-packages (from python-dateutil>=2.8.2->pandas->pybiomart) (1.17.0)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install pybiomart"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "0e6fc9fa-98e0-4b95-a95e-92be187a138f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import circe.downloads\n",
+    "genes_df = ci.downloads.download_genes()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "094a89c8-8eda-4bae-86cf-cad7a39a276a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "fig, ax = plt.subplots(1, figsize = (20, 6))\n",
+    "ci.draw.plot_connections_genes(\n",
+    "    connections=metacells,\n",
+    "    genes=genes_df,\n",
+    "    chromosome=\"chr1\",\n",
+    "    start=50_000,\n",
+    "    end=350_000,\n",
+    "    gene_spacing=30_000,\n",
+    "    y_lim_top=-0.02,\n",
+    "    abs_threshold=0.0,\n",
+    "    track_spacing=0.01,\n",
+    "    track_width=0.01,\n",
+    "    legend=True,\n",
+    "    ax=ax\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af6228fc-9bb2-4fda-9467-b739d8d6a54b",
+   "metadata": {},
+   "source": [
+    "### 7. Work in progress! Happy to get feedbacks :)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79257a67-9d1e-4b22-8dc6-40a95b1b1ede",
+   "metadata": {},
+   "source": [
+    "If you feel any function could be useful for you on others, don't hesitate to write me at `remi.trimbour@pasteur.fr` or to submit an issue on `github.com/cantinilab/Circe`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6492d7d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "circe_local",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/source/examples/Visualize co-accessible DNA regions.ipynb b/docs/source/examples/Visualize co-accessible DNA regions.ipynb
new file mode 100644
index 0000000..1574666
--- /dev/null
+++ b/docs/source/examples/Visualize co-accessible DNA regions.ipynb	
@@ -0,0 +1,902 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "091be986-ff7a-4697-9c5a-7f8094642cda",
+   "metadata": {},
+   "source": [
+    "# **Visualize cis co-accessible regions**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "18bcf460-6d87-487c-8433-7fa9f898970a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import circe as ci\n",
+    "import scanpy as sc\n",
+    "import scipy as sp"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56049b45",
+   "metadata": {},
+   "source": [
+    "## 0. Import (or create) data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3972a885-0c5c-4378-81c2-26b7cfdee1f6",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### Create fake AnnData"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d0ec88e-0410-4e5c-a2d1-beb196b02b16",
+   "metadata": {},
+   "source": [
+    "This data doesn't contain strong correlation between fake regions, the score will then be low. \n",
+    "\n",
+    "It will still allow us to demonstrate how to use Circe. :)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "79295862-9df3-4fa4-a32c-0931c73c705f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "atac = sc.datasets.blobs(n_centers=8, n_variables=2_000, n_observations=300, random_state=1)\n",
+    "atac.X = np.random.poisson(lam=0.2, size=atac.X.shape)\n",
+    "cell_names = [f\"cell_{i}\" for i in range(1, atac.shape[0]+1)]\n",
+    "# number of chr_start_end region names\n",
+    "region_names = [[f\"chr{i}_{str(j)}_{str(j+399)}\" \n",
+    "                 for j in range(1, 10000*400+1, 10000)] \n",
+    "                for i in range(1, 6)]\n",
+    "regions_names = [item for sublist in region_names for item in sublist]\n",
+    "# select a random number of regions per cell, and make it 0\n",
+    "for i in range(atac.shape[0]):\n",
+    "    num_regions = np.random.randint(500, 1000)\n",
+    "    region_indices = np.random.choice(len(regions_names), num_regions, replace=False)\n",
+    "    atac.X[i, region_indices] = 0\n",
+    "\n",
+    "atac.var_names = regions_names\n",
+    "atac.obs_names = cell_names"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f4fbec1",
+   "metadata": {},
+   "source": [
+    "## 1. Preprocess the data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "50a80d79-8423-473a-9810-6dc35b7e9900",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### 1.1. Filter the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "30d98f97-b3b5-4d21-ae8f-4de6c9797f29",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "sc.pp.filter_cells(atac, min_genes=20)\n",
+    "sc.pp.filter_genes(atac, min_cells=30)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56bbfdba-4447-4778-b4d7-83be18c8923f",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### 1.2. Add region position in AnnData.obs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "42c7fb90-ff33-4058-b1a0-aaf99ef0719f",
+   "metadata": {},
+   "source": [
+    "Let's first run `add_region_infos` that will **add coordinate annotations** `chr`, `start`, `end` as columns in `atac.var` slot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "2feb1282-0e2b-4e10-bb8b-8f448e4ca2a6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
n_cellsn_countschromosomestartend
chr1_1_4003132chr11400
chr1_30001_304003135chr13000130400
chr1_40001_404003233chr14000140400
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                  n_cells  n_counts chromosome  start    end\n",
+       "chr1_1_400             31        32       chr1      1    400\n",
+       "chr1_30001_30400       31        35       chr1  30001  30400\n",
+       "chr1_40001_40400       32        33       chr1  40001  40400"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ci.add_region_infos(atac, inplace=True)\n",
+    "atac.var.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23c4e2ef-c346-4c63-9efb-8e4bbeb95cb2",
+   "metadata": {},
+   "source": [
+    "### 2. Calculate co-accessibility"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8cab636-4a10-40cd-a347-5f3e3269f16e",
+   "metadata": {},
+   "source": [
+    "We can finally **compute all the cis co-accessibility scores** ! 
\n",
+    "The default way is to **indicate your organism** if among the one known by Circe.
\n",
+    "The atac network is stored automatically as a sparse matrix in `atac.varp[\"atac_network\"]`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "85035bc6-5fa6-4cef-839f-7a9f12926753",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "46a995adbfff4d4c902b09e7e5e9c82c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "acbc18d0fbfb4a10b316f86ef7d4d9f9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calculating co-accessibility scores...\n",
+      "Concatenating results from all chromosomes...\n"
+     ]
+    }
+   ],
+   "source": [
+    "ci.compute_atac_network(\n",
+    "    atac,\n",
+    "    njobs=3, verbose=0,\n",
+    "    window_size=100000,\n",
+    "    unit_distance=1000,\n",
+    "    distance_constraint=50000,\n",
+    "    s=0.75,)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aad0c904-effe-43a0-b504-d12089176550",
+   "metadata": {},
+   "source": [
+    "### 4. Extract connections"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "735f7800-4f9a-4526-853c-d878f031dbf5",
+   "metadata": {},
+   "source": [
+    "#### 4.A.Get the whole genome cis-coaccessible network\n",
+    "\n",
+    "You can **extract connections** from the atac.varp slot (sparse matrix), as a `DataFrame object` with `extract_atac_links`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "0a26c332-5a1e-4b10-bf0b-3e6339dace60",
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Peak1Peak2score
0chr4_290001_290400chr4_300001_3004000.154638
1chr3_3340001_3340400chr3_3380001_33804000.153625
2chr3_3140001_3140400chr3_3170001_31704000.152573
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                  Peak1                 Peak2     score\n",
+       "0    chr4_290001_290400    chr4_300001_300400  0.154638\n",
+       "1  chr3_3340001_3340400  chr3_3380001_3380400  0.153625\n",
+       "2  chr3_3140001_3140400  chr3_3170001_3170400  0.152573"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circe_network = ci.extract_atac_links(atac)\n",
+    "circe_network.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07516731-4de2-48c6-bd59-5fcffca34084",
+   "metadata": {},
+   "source": [
+    "#### 4.B. Subset the AnnData object to a given window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8a1bc5a-dfc0-4437-aed6-2e6606165378",
+   "metadata": {},
+   "source": [
+    "If you're interested in a specific genomic region only, you can also **subset your anndata object** on this specific window"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "f699ad6c",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "subset_atac = ci.subset_region(atac, \"chr1\", 10_000, 200_000).copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "39d41ca4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Peak1Peak2score
0chr1_100001_100400chr1_170001_1704000.064061
1chr1_150001_150400chr1_160001_1604000.054190
2chr1_150001_150400chr1_170001_1704000.026427
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                Peak1               Peak2     score\n",
+       "0  chr1_100001_100400  chr1_170001_170400  0.064061\n",
+       "1  chr1_150001_150400  chr1_160001_160400  0.054190\n",
+       "2  chr1_150001_150400  chr1_170001_170400  0.026427"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circe_network_subset = ci.extract_atac_links(subset_atac)\n",
+    "circe_network_subset.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1c66dcfb-1a1d-4309-bf57-ee9b4ee1f3b4",
+   "metadata": {},
+   "source": [
+    "### 5. Plot co-accessibility scores in a window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a2beae63-65f4-4642-a876-e01a271db740",
+   "metadata": {},
+   "source": [
+    "You can pass either your `anndata` object or your freshly extracted `dataframe` into `plot_connections` to **visualize all Circe scores**.
\n",
+    "**Blue edges** correspond to positive co-accessibility scores, while **yellow ones** are for negative scores"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7e256844-e050-49fc-b811-191b0cf17561",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.plot_connections(\n",
+    "    circe_network,\n",
+    "    chromosome=\"chr2\",\n",
+    "    start=10_000,\n",
+    "    end=200_000,\n",
+    "    sep=(\"_\",\"_\"),\n",
+    "    abs_threshold=0.01\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "0c3bef89",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.plot_connections(\n",
+    "    atac,\n",
+    "    chromosome=\"chr2\",\n",
+    "    start=10_000,\n",
+    "    end=200_000,\n",
+    "    sep=(\"_\",\"_\"),\n",
+    "    abs_threshold=0.01\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdcb097f-a019-4caa-8b0d-b393bc737156",
+   "metadata": {},
+   "source": [
+    "### 6. Find cis-coaccessible connected modules"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "366c168b-3f25-41a8-96f3-ae876f20715e",
+   "metadata": {},
+   "source": [
+    "In addition to pairwise co-accessibility scores, Circe can also be used to **define cis co-accessibility modules** (called CCANs by Cicero), which are modules of sites that are highly co-accessible with one another. We use the Louvain community detection algorithm (Blondel et al., 2008) to find clusters of sites that tended to be co-accessible.
\n",
+    "- The function `find_ccans` takes as input a `connection data frame` or the `anndata object` once again, and outputs a data frame with CCAN assignments for each input peak.
\n",
+    "- You can also use `add_ccans` to directly add CCAN assignments to your anndata object as `anndata.var['CCAN']`. The regions that aren't assigned to a CCAN will contain `None`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "f8ef9ec3-d93f-4dfe-b92c-6aaae9f7e921",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Coaccessibility cutoff used: 0.0\n",
+      "Number of CCANs generated: 160\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
PeakCCAN
0chr3_3180001_31804001
1chr3_3220001_32204001
2chr3_3170001_31704001
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                   Peak  CCAN\n",
+       "0  chr3_3180001_3180400     1\n",
+       "1  chr3_3220001_3220400     1\n",
+       "2  chr3_3170001_3170400     1"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ccans = ci.find_ccans(circe_network, seed=0)\n",
+    "ccans.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "71d59d82",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Coaccessibility cutoff used: 0.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "atac = ci.add_ccans(atac, seed=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "9c795c97-91fd-4512-89c8-b931296c7abc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CCAN\n",
+       "24     15\n",
+       "164    15\n",
+       "45     15\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "atac.var['CCAN'].value_counts().head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "538af36a-102d-475d-80cb-4e7aaa1212ed",
+   "metadata": {},
+   "source": [
+    "With default `coaccess_cutoff_override=None`, the function will determine and report an appropriate co-accessibility score cutoff value for CCAN generation based on the number of overall CCANs at varying cutoffs. You can also set `coaccess_cutoff_override` to be a numeric between 0 and 1, to override the cutoff-finding part of the function. This option is useful if you feel that the cutoff found automatically was too strict or loose, or for speed if you are rerunning the code and know what the cutoff will be, since the cutoff finding procedure can be slow. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "38c8d848-287b-4200-b7be-434b65bf0dbf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Coaccessibility cutoff used: 1e-07\n",
+      "Number of CCANs generated: 41\n"
+     ]
+    }
+   ],
+   "source": [
+    "ccans = ci.find_ccans(circe_network, seed=0, coaccess_cutoff_override=1e-7)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b02d2de-2d7c-41ad-85cc-34c1179e2c90",
+   "metadata": {},
+   "source": [
+    "#### 6.B. Plot only a CCAN module"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df4a6121-0aad-4563-925d-bdd0b06e96de",
+   "metadata": {},
+   "source": [
+    "If you're interested in a specific CCAN module, you can use `circe.draw.plot_ccan` function, precising its CCAN name. Only the connections between **regions belonging to this CCAN module will be plotted**."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "4d2d830d-c3f8-4417-b441-697a8eb43c4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This CCAN module is on the chromosome: chr4\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/rtrimbou/ATACNet/circe/circe/draw.py:244: UserWarning: varp parameter is ignored for DataFrame input.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ci.draw.plot_ccan(\n",
+    "    atac,\n",
+    "    ccan_module=atac.var['CCAN'].value_counts().index[1],\n",
+    "    sep=('_', '_'),\n",
+    "    abs_threshold=0,\n",
+    "    figsize=(15,5),\n",
+    "    only_positive=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46a807ab-4eaa-4951-9f45-eae267bc2ab7",
+   "metadata": {},
+   "source": [
+    "### 7.Coordinates overlap between co-accessible regions and gene bodies"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17d516e3-76b7-454c-b4d5-f8494c549014",
+   "metadata": {},
+   "source": [
+    "To better understand the role of specific regions and modules, you can additionally plot **gene bodies** falling into your window of interest.\n",
+    "
 You need first to load gene coordinates as a dataframe, or to download them through `circe.downloads.download_genes`. This functions will require to install the `pybiomart` package Then you can use `ci.draw.plot_connections_genes`, using gene infos and either your AnnData object or the dataframe of Circe's results to compare these locations. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4e614cf2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pip install pybiomart"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "0e6fc9fa-98e0-4b95-a95e-92be187a138f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import circe.downloads\n",
+    "genes_df = ci.downloads.download_genes()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "094a89c8-8eda-4bae-86cf-cad7a39a276a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "fig, ax = plt.subplots(1, figsize = (20, 6))\n",
+    "ci.draw.plot_connections_genes(\n",
+    "    connections=atac,\n",
+    "    genes=genes_df,\n",
+    "    chromosome=\"chr1\",\n",
+    "    start=50_000,\n",
+    "    end=350_000,\n",
+    "    gene_spacing=30_000,\n",
+    "    y_lim_top=-0.01,\n",
+    "    abs_threshold=0.0,\n",
+    "    track_spacing=0.01,\n",
+    "    track_width=0.01,\n",
+    "    legend=True,\n",
+    "    ax=ax\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af6228fc-9bb2-4fda-9467-b739d8d6a54b",
+   "metadata": {},
+   "source": [
+    "### 7. Work in progress! Happy to get feedbacks :)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79257a67-9d1e-4b22-8dc6-40a95b1b1ede",
+   "metadata": {},
+   "source": [
+    "If you feel any function could be useful for you on others, don't hesitate to write me at `remi.trimbour@pasteur.fr` or to submit an issue on `github.com/cantinilab/Circe`."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "circe_local",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/source/index.rst b/docs/source/index.rst
new file mode 100644
index 0000000..f26c6ca
--- /dev/null
+++ b/docs/source/index.rst
@@ -0,0 +1,181 @@
+.. circe documentation master file, created by
+   sphinx-quickstart on Thu Sep  4 18:21:17 2025.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+.. image:: ../../logo.svg
+   :alt: CIRCE-logo Remi-Trimbour 2024
+   :align: center
+
+CIRCE: Cis-regulatory interactions between chromatin regions
+============================================================
+
+.. toctree::
+   :maxdepth: 2
+   :hidden:
+   :glob:
+   :caption: CIRCE explained
+
+   circe_explained/*
+
+.. toctree::
+   :maxdepth: 2
+   :hidden:
+   :glob:
+   :caption: Examples
+
+   examples/*
+
+.. image:: https://github.com/cantinilab/circe/actions/workflows/codecov.yaml/badge.svg
+   :target: https://github.com/cantinilab/circe/actions/workflows/codecov.yaml
+   :alt: Unit Tests
+
+.. image:: https://github.com/cantinilab/Circe/actions/workflows/wheels.yml/badge.svg
+   :target: https://github.com/cantinilab/Circe/actions/workflows/wheels.yml
+   :alt: Wheels
+
+.. image:: https://codecov.io/gh/cantinilab/circe/graph/badge.svg?token=0OIFAP28D7
+   :target: https://codecov.io/gh/cantinilab/circe
+   :alt: codecov
+
+.. image:: https://img.shields.io/pypi/v/circe-py?color=blue
+   :target: https://img.shields.io/pypi/v/circe-py
+   :alt: PyPI version
+
+.. image:: https://static.pepy.tech/badge/circe-py/month
+   :target: https://pepy.tech/project/circe-py
+   :alt: Downloads
+
+
+CIRCE is a Python package for inferring **co-accessibility networks from
+single-cell ATAC-seq data**, using `skggm `_
+for the graphical lasso and `scanpy `_ for data processing.
+
+It is based on the pipeline and hypotheses presented in the manuscript
+*Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data*
+by Pliner et al. (2018).
+The original R package Cicero is available
+`here `_.
+
+
+Installation
+------------
+
+The package can be installed using pip::
+
+   pip install circe-py
+
+or directly from GitHub::
+
+   pip install "git+https://github.com/cantinilab/circe.git"
+
+
+Minimal example
+---------------
+
+.. code-block:: python
+
+   import anndata as ad
+   import circe as ci
+
+   # Load the data
+   atac = ad.read_h5ad('atac_data.h5ad')
+   atac = ci.add_region_infos(atac)
+
+   # Compute the co-accessibility network
+   ci.compute_atac_network(atac)
+
+   # Extract the network and find CCANs modules
+   circe_network = ci.extract_atac_links(atac)
+   ccans_module = ci.find_ccans(atac)
+
+
+Visualisation
+-------------
+
+.. code-block:: python
+
+   fig, ax = plt.subplots(1, figsize = (20, 6))
+   genes_df = ci.downloads.download_genes()
+
+   ci.draw.plot_connections_genes(
+       connections=atac,  # Main parameters
+       genes=genes_df,
+       chromosome="chr1",
+       start=50_000,
+       end=300_000,
+       gene_spacing=30_000,
+       abs_threshold=0.0,
+       y_lim_top=-0.01,   # Visual parameters
+       track_spacing=0.01,
+       track_width=0.01,
+       ax=ax
+   )
+
+.. image:: https://github.com/cantinilab/circe/raw/main/Figures/circe_figure_genes_access.png
+   :align: center
+
+
+Comparison to Cicero R package
+------------------------------
+
+Metacalls computation might create differences, but scores will be identical applied to the same metacalls (cf comparison plots below).
+It should run significantly faster than Cicero (e.g.: running time of 5 sec instead of 17 min for dataset 2).
+
+If you have any suggestion, don't hesitate! This package is still a work in progress :)
+
+On the same metacells obtained from Cicero code.
+
+All tests can be found in the `circe benchmark repo `_.
+
+
+Real dataset 2 - subsample of 10x PBMC (2021)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+- Pearson correlation coefficient: 0.999958
+- Spearman correlation coefficient: 0.999911
+
+.. image:: https://github.com/cantinilab/circe/raw/main/Figures/correlation_real_dataset2.png
+   :align: center
+   :width: 480
+
+Performance on real dataset 2:
+
+- Runtime: ~100x faster
+- Memory usage: ~5x less
+
+.. image:: https://github.com/cantinilab/circe/raw/main/Figures/perf_real_dataset2.png
+   :align: center
+   :width: 480
+
+
+Coming
+------
+
+- ~~**Calculate metacells !**~~
+- ~~Add stats on similarity on large datasets.~~
+- ~~Add stats on runtime, memory usage.~~
+- Implement multithreading use (should speed up even more).
+- ~~Fix seed for reproducibility.~~
+
+
+Usage
+-----
+
+It is currently developed to work with AnnData objects.
+Check ``Example1.ipynb`` for a simple usage example.
+
+
+Citation
+--------
+
+Trimbour Rémi (2025).
+*Circe: Co-accessibility network from ATAC-seq data in Python (based on Cicero package).*
+Package version 0.3.6.
+
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Contents
+
+   examples/*

From 37a2d2491116d0649b4825dec1db0200b9c85ada Mon Sep 17 00:00:00 2001
From: r-trimbour 
Date: Sun, 7 Sep 2025 23:17:47 +0200
Subject: [PATCH 27/33] update path to sphinx  conf.py

---
 .readthedocs.yaml |  2 +-
 docs/conf.py      | 35 -----------------------------------
 docs/index.rst    | 15 ---------------
 3 files changed, 1 insertion(+), 51 deletions(-)
 delete mode 100644 docs/conf.py
 delete mode 100644 docs/index.rst

diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index b59b416..fce1e1a 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -12,4 +12,4 @@ python:
     - requirements: docs/requirements.txt
 
 sphinx:
-  configuration: docs/conf.py
+  configuration: docs/source/conf.py
diff --git a/docs/conf.py b/docs/conf.py
deleted file mode 100644
index 6bfe78a..0000000
--- a/docs/conf.py
+++ /dev/null
@@ -1,35 +0,0 @@
-# docs/conf.py
-
-import os
-import sys
-from datetime import datetime
-
-# -- Path setup --------------------------------------------------------------
-# Make your module importable by adding the project root to sys.path
-sys.path.insert(0, os.path.abspath('..'))
-
-# -- Project information -----------------------------------------------------
-project = 'Circe'
-author = 'Rémi Trimbour'
-copyright = f'{datetime.now().year}, {author}'
-release = '0.3.8-alpha'  # Or dynamically pull from package version
-
-# -- General configuration ---------------------------------------------------
-extensions = [
-    'sphinx.ext.autodoc',    # Automatically generate documentation from docstrings
-    'sphinx.ext.napoleon',   # Support for NumPy/Google style docstrings
-    'sphinx.ext.viewcode',   # Add links to highlighted source code
-    'sphinx.ext.intersphinx', # Link to other projects' documentation
-]
-
-templates_path = ['_templates']
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
-
-# -- Options for HTML output -------------------------------------------------
-# The theme to use for HTML and HTML Help pages.  See the documentation for
-# a list of builtin themes.
-#
-html_theme = "sphinx_rtd_theme"
-
-html_title = "CIRCE"
-html_static_path = ['_static']
diff --git a/docs/index.rst b/docs/index.rst
deleted file mode 100644
index b4c85e8..0000000
--- a/docs/index.rst
+++ /dev/null
@@ -1,15 +0,0 @@
-Welcome to Circe’s documentation!
-=================================
-
-.. toctree::
-   :maxdepth: 2
-   :caption: Contents
-
-   modules
-
-Indices and tables
-==================
-
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`

From 06d6810988ac32491706e56f37e9a6ad857a0165 Mon Sep 17 00:00:00 2001
From: r-trimbour 
Date: Sun, 7 Sep 2025 23:19:59 +0200
Subject: [PATCH 28/33] add myst_nb dependency for notebook rendering

---
 docs/requirements.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/requirements.txt b/docs/requirements.txt
index 66316d4..c297f31 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -3,3 +3,4 @@ sphinx-rtd-theme
 myst-parser
 sphinx-autodoc-typehints
 sphinx-copybutton
+myst_nb
\ No newline at end of file

From 6413d2f25d5efb0c04016287de928238f804e1a3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Trimbour?=
 <77151348+r-trimbour@users.noreply.github.com>
Date: Sun, 7 Sep 2025 23:21:00 +0200
Subject: [PATCH 29/33] Update requirements.txt

---
 docs/requirements.txt | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/requirements.txt b/docs/requirements.txt
index c297f31..9904c69 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -3,4 +3,5 @@ sphinx-rtd-theme
 myst-parser
 sphinx-autodoc-typehints
 sphinx-copybutton
-myst_nb
\ No newline at end of file
+myst_nb
+furo

From 3bdd8b33f8e7995d8d6d9e183be6aa47ab8e78b5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Trimbour?=
 <77151348+r-trimbour@users.noreply.github.com>
Date: Sun, 7 Sep 2025 23:25:18 +0200
Subject: [PATCH 30/33] Update sphinx root path to be recognised by rtd

---
 docs/source/conf.py | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/docs/source/conf.py b/docs/source/conf.py
index 3cf6110..aea1bfa 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -11,6 +11,17 @@
 author = 'Remi Trimbour'
 release = '0.3.8'
 
+# -- Path setup --------------------------------------------------------------
+
+# If extensions (or modules to document with autodoc) are in another directory,
+# add these directories to sys.path here. If the directory is relative to the
+# documentation root, use os.path.abspath to make it absolute, like shown here.
+#
+import os
+import sys
+
+sys.path.insert(0, os.path.abspath("../../"))
+
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
 
@@ -26,4 +37,4 @@
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
 
 html_theme = 'furo'
-html_static_path = ['_static']
\ No newline at end of file
+html_static_path = ['_static']

From 01f86f4ffedda0851252becef50d68ab6c4568ee Mon Sep 17 00:00:00 2001
From: r-trimbour 
Date: Fri, 19 Sep 2025 18:12:47 +0200
Subject: [PATCH 31/33] add celloracle example and loosened pandas dependency

---
 Examples/circe_celloracle_tutorial.ipynb | 1994 ++++++++++++++++++++++
 circe_celloracle_environment.yml         |  229 +++
 2 files changed, 2223 insertions(+)
 create mode 100644 Examples/circe_celloracle_tutorial.ipynb
 create mode 100644 circe_celloracle_environment.yml

diff --git a/Examples/circe_celloracle_tutorial.ipynb b/Examples/circe_celloracle_tutorial.ipynb
new file mode 100644
index 0000000..706428f
--- /dev/null
+++ b/Examples/circe_celloracle_tutorial.ipynb
@@ -0,0 +1,1994 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8f689fa2-a29d-48d5-971d-548ddf504334",
+   "metadata": {},
+   "source": [
+    "# Building CellOracle base-GRN with CIRCE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "b954cc7e-7300-49e9-8fb7-9f5ba7d135cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# pip celloracle\n",
+    "# pip muon\n",
+    "# pip circe"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b3cd88d-c5c3-46b0-9b42-224e40b0b2a2",
+   "metadata": {},
+   "source": [
+    "The base GRN of **[CellOracle](https://morris-lab.github.io/CellOracle.documentation/)** are based on cis-accesibility networks obtained from scATAC-seq data. **CIRCE** now allows users to build the base GRN using a single Python environment.
_When CellOracle got published, **[Cicero](https://cole-trapnell-lab.github.io/cicero-release/)**, implemented in R, was the current state-of-the-art method to obtain these networks._ ([Tutorial: base GRN CellOracle¹](https://morris-lab.github.io/CellOracle.documentation/tutorials/base_grn.html))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c1997756-f4c6-435a-9455-cea7996185a7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "which: no R in (/opt/gensoft/exe/Jupyter-Notebook/7.4.4/venv/bin:/opt/gensoft/exe/bedtools/2.31.1/scripts:/opt/gensoft/exe/bedtools/2.31.1/bin:/opt/gensoft/exe/Jupyter-Notebook/7.4.4/bin:/opt/gensoft/adm/Modules/bin:/opt/gensoft/adm/Modules/4.4.0/bin:/opt/hpc/slurm/current/bin:/opt/hpc/slurm/current/sbin:/opt/gensoft/exe/apptainer/1.3.5/scripts:/opt/gensoft/exe/apptainer/1.3.5/bin:/opt/gensoft/exe/apptainer/1.4.1/scripts:/opt/gensoft/exe/apptainer/1.4.1/bin:/opt/gensoft/exe/gcc/10.4.0/bin:/pasteur/appa/homes/rtrimbou/miniconda3/envs/snakemake/bin:/pasteur/appa/homes/rtrimbou/miniconda3/envs/snakemake/condabin:/pasteur/appa/homes/rtrimbou/.local/bin:/pasteur/appa/homes/rtrimbou/bin:/opt/gensoft/adm/Modules/bin:/opt/hpc/slurm/current/bin:/opt/hpc/slurm/current/sbin:/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import celloracle as co"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c57d5258-18f2-47e1-b99f-565a39de98fd",
+   "metadata": {},
+   "source": [
+    "## 1. Import scATAC-seq data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "44094b2b-1644-4eaf-93c1-0fb0ca80091c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import muon as mu\n",
+    "import circe as ci"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "87d65099-2c7a-486c-88a3-072a83352400",
+   "metadata": {},
+   "source": [
+    "The data of this tutorial can be downloaded at [____](www.wikipedia.org)\n",
+    "If you have any trouble to install both CellOracle and CIRCE in the same environement, you try this conda env configuration : [CIRCE+CellOracle](https://www.wikipedia.org)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d03b12f1-bdba-4236-aef9-a60077d6ca58",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = mu.read_h5mu(\"pbmc10x/pbmc10x.h5mu\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3a24cbd5-27cf-4cdc-8645-bb0f1aa8339f",
+   "metadata": {},
+   "source": [
+    "## 2. Inferring DNA regions network from CIRCE\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "93547e1a-3b00-42ba-bd8d-c88315d0f9bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "atac = data[\"atac\"]\n",
+    "atac, atac.var_names[:3]\n",
+    "atac.var_names = atac.var_names.str.replace('-', '_')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "72189143-9255-45c3-94b1-c83fb03837fd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "atac = ci.add_region_infos(atac, sep=('_', '_'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0791dfa3-b9f0-4b51-a893-d8b493c93513",
+   "metadata": {},
+   "source": [
+    "#### 2.a. Compute CIRCE metacells"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1b13dc7b-3ddf-4414-8a38-78644e515b70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#atac = ci.metacells.compute_metacells(atac)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e4061d6e-e8a8-4683-b438-fcb195001703",
+   "metadata": {},
+   "source": [
+    "#### 2.b. Infer DNA region interactions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "7efae4dd-c349-4070-a621-5b72dc072a9e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
Calculating alpha ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0:00:45 0:00:00\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "Calculating alpha \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[33m0:00:45\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2025-09-19 09:12:45,763 - INFO - Remove client Client-e3ecd7f5-9527-11f0-a7a7-3ceceff9f2fe\n",
+      "2025-09-19 09:12:45,767 - INFO - Received 'close-stream' from tcp://127.0.0.1:48784; closing.\n",
+      "2025-09-19 09:12:45,768 - INFO - Remove client Client-e3ecd7f5-9527-11f0-a7a7-3ceceff9f2fe\n",
+      "2025-09-19 09:12:45,769 - INFO - Close client connection: Client-e3ecd7f5-9527-11f0-a7a7-3ceceff9f2fe\n",
+      "2025-09-19 09:12:45,771 - INFO - Retire worker addresses (stimulus_id='retire-workers-1758265965.7718186') (0,)\n",
+      "2025-09-19 09:12:45,781 - INFO - Received 'close-stream' from tcp://127.0.0.1:48782; closing.\n",
+      "2025-09-19 09:12:45,781 - INFO - Remove worker addr: tcp://127.0.0.1:36253 name: 0 (stimulus_id='handle-worker-cleanup-1758265965.7818978')\n",
+      "2025-09-19 09:12:45,782 - INFO - Lost all workers\n",
+      "2025-09-19 09:12:46,305 - INFO - Closing scheduler. Reason: unknown\n",
+      "2025-09-19 09:12:46,306 - INFO - Scheduler closing all comms\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calculating co-accessibility scores...\n",
+      "Concatenating results from all chromosomes...\n"
+     ]
+    }
+   ],
+   "source": [
+    "ci.compute_atac_network(atac)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b75f687-e01a-41f5-b666-b9dd81e776c0",
+   "metadata": {},
+   "source": [
+    "#### 2.c. Format network output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "6b7f1045-1694-4e4c-96e4-1aef0b45c9b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "circe_network = ci.extract_atac_links(atac)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "794dedb4-0371-451a-83b6-2e7c624eecef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
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+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
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+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
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+       "      \n",
+       "    \n",
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+       "      \n",
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+       "    \n",
+       "    \n",
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+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Peak1Peak2coaccess
0chr16_54012525_54013025chr16_54013534_540140340.669024
1chr3_133264089_133264589chr3_133264946_1332654460.602914
2chr2_109479794_109480294chr2_109481034_1094815340.467789
3chr5_49599487_49599987chr5_49600285_496007850.452878
4chr2_88192716_88193216chr2_88193738_881942380.446659
............
6129848chr9_129777081_129777581chr9_129869007_129869507-0.146761
6129849chr22_38570096_38570596chr22_38953902_38954402-0.148798
6129850chr18_48896769_48897269chr18_48940694_48941194-0.148916
6129851chr22_50469821_50470321chr22_50542441_50542941-0.150171
6129852chr17_82126673_82127173chr17_82216598_82217098-0.162922
\n",
+       "
6129853 rows × 3 columns
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                            Peak1                     Peak2  coaccess\n",
+       "0         chr16_54012525_54013025   chr16_54013534_54014034  0.669024\n",
+       "1        chr3_133264089_133264589  chr3_133264946_133265446  0.602914\n",
+       "2        chr2_109479794_109480294  chr2_109481034_109481534  0.467789\n",
+       "3          chr5_49599487_49599987    chr5_49600285_49600785  0.452878\n",
+       "4          chr2_88192716_88193216    chr2_88193738_88194238  0.446659\n",
+       "...                           ...                       ...       ...\n",
+       "6129848  chr9_129777081_129777581  chr9_129869007_129869507 -0.146761\n",
+       "6129849   chr22_38570096_38570596   chr22_38953902_38954402 -0.148798\n",
+       "6129850   chr18_48896769_48897269   chr18_48940694_48941194 -0.148916\n",
+       "6129851   chr22_50469821_50470321   chr22_50542441_50542941 -0.150171\n",
+       "6129852   chr17_82126673_82127173   chr17_82216598_82217098 -0.162922\n",
+       "\n",
+       "[6129853 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circe_network = circe_network.rename(\n",
+    "    columns = {\"score\": \"coaccess\"}\n",
+    ")\n",
+    "circe_network"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1ffbbfbb-0ab1-4e45-a01d-1301d7d3a94d",
+   "metadata": {},
+   "source": [
+    "## 3. Connect DNA region to gene bodies"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "db5da2cb-fbfd-4842-8225-07e5cb53d2c4",
+   "metadata": {},
+   "source": [
+    "This notebook section correspond to the CellOracle documentation: [Annotate Transcription Starting Sites²](https://morris-lab.github.io/CellOracle.documentation/notebooks/01_ATAC-seq_data_processing/option1_scATAC-seq_data_analysis_with_cicero/02_preprocess_peak_data.html#2.-Annotate-transcription-start-sites-(TSSs)%C2%B6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19b6cd1e-b115-45fd-a365-7eb97535f39d",
+   "metadata": {},
+   "source": [
+    "#### 3.1. TSS informations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "d7b596b5-9bf7-4a40-954a-a82715c87463",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!module load bedtools"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b463f3f7-7c92-4635-9978-e9ae6c81453d",
+   "metadata": {},
+   "source": [
+    "⚠️**You need to have bedtools available !**\n",
+    "
Otherwise, you should encounter \n",
+    ">`NotImplementedError: \"intersectBed\" does not appear to be installed or on the path, so this method is disabled.  Please install a more recent version of BEDTools and re-import to use this method.`\n",
+    "\n",
+    "If you're on a HPC, you might just have to load the package before launching the notebook: `module load bedtools`\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "af571587-3f9a-424d-9854-52e6ca84dc2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "que bed peaks: 215676\n",
+      "tss peaks in que: 6780\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
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+       "      \n",
+       "      \n",
+       "      \n",
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+       "    \n",
+       "  \n",
+       "  \n",
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+       "      \n",
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+       "      \n",
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+       "    \n",
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+       "      \n",
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+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
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+       "      \n",
+       "      \n",
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+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
chrstartendgene_short_namestrand
6775chr1748341204834620GP1BA+
6776chr1748353844835884GP1BA+
6777chr193548463535485135GRAMD1A+
6778chr7100545748100546248MUC3A+
6779chr7100546509100547009MUC3A+
\n",
+       "
"
+      ],
+      "text/plain": [
+       "        chr      start        end gene_short_name strand\n",
+       "6775  chr17    4834120    4834620           GP1BA      +\n",
+       "6776  chr17    4835384    4835884           GP1BA      +\n",
+       "6777  chr19   35484635   35485135         GRAMD1A      +\n",
+       "6778   chr7  100545748  100546248           MUC3A      +\n",
+       "6779   chr7  100546509  100547009           MUC3A      +"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from celloracle import motif_analysis as ma\n",
+    "# Make sure to specify the correct reference genome here\n",
+    "tss_annotated = ma.get_tss_info(peak_str_list=atac.var_names.values, ref_genome=\"hg19\")\n",
+    "\n",
+    "# Check results\n",
+    "tss_annotated.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "41bba7cd-ad0a-45e1-923a-6a8489c2d9cf",
+   "metadata": {},
+   "source": [
+    "#### 3.2. Integrate TSS informations with cis-coaccessible network"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "fd8e0f57-d26c-4098-a807-68105e851a29",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(173536, 3)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
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+       "      \n",
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+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
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+       "    \n",
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+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
peak_idgene_short_namecoaccess
0chr10_101291541_101292041LINC014751.000000
1chr10_101291541_101292041NKX2-31.000000
2chr10_101292051_101292551LINC014750.145072
3chr10_101292051_101292551NKX2-31.000000
4chr10_101297817_101298317LINC014750.000032
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                     peak_id gene_short_name  coaccess\n",
+       "0  chr10_101291541_101292041       LINC01475  1.000000\n",
+       "1  chr10_101291541_101292041          NKX2-3  1.000000\n",
+       "2  chr10_101292051_101292551       LINC01475  0.145072\n",
+       "3  chr10_101292051_101292551          NKX2-3  1.000000\n",
+       "4  chr10_101297817_101298317       LINC01475  0.000032"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "integrated = ma.integrate_tss_peak_with_cicero(\n",
+    "    tss_peak=tss_annotated,\n",
+    "    cicero_connections=circe_network)\n",
+    "print(integrated.shape)\n",
+    "integrated.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8d993597-5cf1-4752-948a-f6918bd6c8b9",
+   "metadata": {},
+   "source": [
+    "#### 3.3. Filtering peak connections on a specific threshold"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e4c88138-fa07-4a68-9545-a368c9744cca",
+   "metadata": {},
+   "source": [
+    "⚠️ **As noted in [Nourisa et al, 2024 - bioXriv](https://www.biorxiv.org/content/10.1101/2024.10.16.618746v1), the threshold of 0.8 might be too high to keep any enhancer - promoter connections.**\n",
+    "
You can plot the distribution of your score, to realise how many connections you're keeping."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "933f41f3-dd3f-4042-ae7c-09785896c984",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "682ef950-0fc2-4e55-9409-ec5b0090157c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       ""
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "default_threshold = 0.8\n",
+    "\n",
+    "threshold = circe_network.coaccess.quantile(0.95) # TO CHOOSE, e.g. 5% of the connections\n",
+    "\n",
+    "fig, ax = plt.subplots(1)\n",
+    "circe_network.coaccess.plot.hist(ax=ax, bins=50, label=\"DNA co-accessibility scores\")  # score distribution\n",
+    "ax.vlines(threshold, 0, ax.get_ylim()[1], colors=\"green\", label=\"DNA co-accessiblity scores - top 5%\")  # threshold line\n",
+    "ax.vlines(default_threshold, 0, ax.get_ylim()[1], colors=\"red\", label=\"DNA co-accessiblity scores - above 0.8)\")  # threshold line\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "95e82bc6-c3ab-41d9-8973-550f017d10c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "peaks = integrated[integrated.coaccess >= threshold]\n",
+    "peaks = peaks[[\"peak_id\", \"gene_short_name\"]].reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cbb9c2de-f0b2-4964-8496-3ef3faa899fd",
+   "metadata": {},
+   "source": [
+    "### 4. Finding TF binding sites"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "19c54a6d-f7d7-4438-b14f-7d858dfdde1f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.20.0'"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import celloracle as co\n",
+    "from celloracle import motif_analysis as ma\n",
+    "from celloracle.utility import save_as_pickled_object\n",
+    "co.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d228e7d4-9600-4152-a220-f9faa466d054",
+   "metadata": {},
+   "source": [
+    "#### 4.1. Download genome - UCSC version"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "361e6700-3d5a-439b-939a-5c5f562f7847",
+   "metadata": {},
+   "source": [
+    "You need a genome sequence in order to identify the TF motifs present in the DNA regions. Genomepy manage the installation by default, but you can also "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "7a953e1f-0349-4576-9d67-5e81019b072b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Fasta(\"/pasteur/appa/homes/rtrimbou/.local/share/genomes/hg19/hg19.fa\")"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import genomepy\n",
+    "\n",
+    "# This link should be your genome of interest location.\n",
+    "fa = \"https://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/latest/hg19.fa.gz\"\n",
+    "\n",
+    "genomepy.install_genome(\n",
+    "    name=fa,\n",
+    "    provider=\"URL\",\n",
+    "    localname=\"hg19\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9d1f77dd-ae45-4748-b3fb-3d9699381c97",
+   "metadata": {},
+   "source": [
+    "⚠️ **If your reference genome file are installed in non-default location**, please speficy the location using the parameter genomes_dir in the following functions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5eebb456-c951-4900-8de4-101fe3fba1df",
+   "metadata": {},
+   "source": [
+    "Check that the genome has been well downloaded."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "1f369957-9150-494c-8472-9f7cb308c914",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "hg19 installation:  True\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Make sure reference genome has been correctly installed.\n",
+    "ref_genome = \"hg19\"\n",
+    "\n",
+    "genome_installation = ma.is_genome_installed(ref_genome=ref_genome,\n",
+    "                                             genomes_dir=None)\n",
+    "print(ref_genome, \"installation: \", genome_installation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "519a5e8f-549e-42e0-b623-85c75254ca3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Peaks before filtering:  20089\n",
+      "Peaks with invalid chr_name:  0\n",
+      "Peaks with invalid length:  0\n",
+      "Peaks after filtering:  20089\n"
+     ]
+    }
+   ],
+   "source": [
+    "peaks = ma.check_peak_format(peaks, ref_genome, genomes_dir=None)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "863c6dd3-4bd3-47da-8149-3edd67708577",
+   "metadata": {},
+   "source": [
+    "#### 4.2. Scanning for TF motifs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "a8d46b45-8ba0-46bc-8719-b903d5e98d9f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Instantiate TFinfo object\n",
+    "tfi = ma.TFinfo(peak_data_frame=peaks,\n",
+    "                ref_genome=ref_genome,\n",
+    "                genomes_dir=None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "878feafb-9220-4b80-bc76-3f1bfc947ea6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "No motif data entered. Loading default motifs for your species ...\n",
+      " Default motif for vertebrate: gimme.vertebrate.v5.0. \n",
+      " For more information, please see https://gimmemotifs.readthedocs.io/en/master/overview.html \n",
+      "\n",
+      "Initiating scanner... \n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2025-09-19 09:28:31,050 - DEBUG - using background: genome hg19 with size 200\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calculating FPR-based threshold. This step may take substantial time when you load a new ref-genome. It will be done quicker on the second time. \n",
+      "\n",
+      "Motif scan started .. It may take long time.\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "866def8a07b5470b9804148ce143703e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Scanning:   0%|          | 0/13948 [00:00\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
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+       "      \n",
+       "      \n",
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+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
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+       "      \n",
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+       "      \n",
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+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
seqnamemotif_idfactors_directfactors_indirectscoreposstrand
0chr10_101291541_101292041GM.5.0.RFX.0001Rfx5ARID2, Rfx6, Rfx8, RFX6, Rfx3, RFX5, RFX8, Rfx...10.4841022601
1chr10_101291541_101292041GM.5.0.Nuclear_receptor.0005NR4A2, NR1A4, RXRA, NR1H4, FXRNr1h5, Nr1h4, Nr1h3, NR1H38.070402454-1
2chr10_101291541_101292041GM.5.0.Nuclear_receptor.0005NR4A2, NR1A4, RXRA, NR1H4, FXRNr1h5, Nr1h4, Nr1h3, NR1H37.7741844541
3chr10_101291541_101292041GM.5.0.Mixed.0008ZBTB33, NR2C29.3228074481
4chr10_101291541_101292041GM.5.0.C2H2_ZF.0020Egr1, EGR4, EGR2, Egr3, EGR3, EGR1Egr1, Egr4, EGR4, EGR2, Egr3, EGR3, EGR15.9765151241
\n",
+       ""
+      ],
+      "text/plain": [
+       "                     seqname                      motif_id  \\\n",
+       "0  chr10_101291541_101292041               GM.5.0.RFX.0001   \n",
+       "1  chr10_101291541_101292041  GM.5.0.Nuclear_receptor.0005   \n",
+       "2  chr10_101291541_101292041  GM.5.0.Nuclear_receptor.0005   \n",
+       "3  chr10_101291541_101292041             GM.5.0.Mixed.0008   \n",
+       "4  chr10_101291541_101292041           GM.5.0.C2H2_ZF.0020   \n",
+       "\n",
+       "                       factors_direct  \\\n",
+       "0                                Rfx5   \n",
+       "1      NR4A2, NR1A4, RXRA, NR1H4, FXR   \n",
+       "2      NR4A2, NR1A4, RXRA, NR1H4, FXR   \n",
+       "3                                       \n",
+       "4  Egr1, EGR4, EGR2, Egr3, EGR3, EGR1   \n",
+       "\n",
+       "                                    factors_indirect      score  pos  strand  \n",
+       "0  ARID2, Rfx6, Rfx8, RFX6, Rfx3, RFX5, RFX8, Rfx...  10.484102  260       1  \n",
+       "1                         Nr1h5, Nr1h4, Nr1h3, NR1H3   8.070402  454      -1  \n",
+       "2                         Nr1h5, Nr1h4, Nr1h3, NR1H3   7.774184  454       1  \n",
+       "3                                      ZBTB33, NR2C2   9.322807  448       1  \n",
+       "4           Egr1, Egr4, EGR4, EGR2, Egr3, EGR3, EGR1   5.976515  124       1  "
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Check motif scan results\n",
+    "tfi.scanned_df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5633010a-c7bf-4a88-91a6-36a390068b1b",
+   "metadata": {},
+   "source": [
+    "#### 3.3. Filtering low score TF - peak links"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "d5070eae-16d1-4f1e-a1a4-55ffa3aef835",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Filtering finished: 2673574 -> 581057\n",
+      "1. Converting scanned results into one-hot encoded dataframe.\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6a9fc3a1d4ce48248d71f356f5e5bdeb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/13922 [00:00\n",
+       "\n",
+       "\n",
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+       "      \n",
+       "    \n",
+       "  \n",
+       "
peak_idgene_short_name9430076C15RIKAC002126.6AC012531.1AC226150.2AFPAHRAHRRAIRE...ZNF784ZNF8ZNF816ZNF85ZSCAN10ZSCAN16ZSCAN22ZSCAN26ZSCAN31ZSCAN4
0chr10_101291541_101292041LINC014750.00.00.00.00.00.00.00.0...0.00.00.00.00.00.00.00.00.00.0
1chr10_101291541_101292041NKX2-30.00.00.00.00.00.00.00.0...0.00.00.00.00.00.00.00.00.00.0
2chr10_101292051_101292551LINC014750.00.00.00.00.00.00.00.0...0.00.00.00.00.00.00.00.00.00.0
3chr10_101292051_101292551NKX2-30.00.00.00.00.00.00.00.0...0.00.00.00.00.00.00.00.00.00.0
4chr10_101380430_101380930SLC25A280.00.00.00.00.00.00.00.0...0.00.00.00.00.00.00.00.00.00.0
\n",
+       "
5 rows × 1095 columns
\n",
+       ""
+      ],
+      "text/plain": [
+       "                     peak_id gene_short_name  9430076C15RIK  AC002126.6  \\\n",
+       "0  chr10_101291541_101292041       LINC01475            0.0         0.0   \n",
+       "1  chr10_101291541_101292041          NKX2-3            0.0         0.0   \n",
+       "2  chr10_101292051_101292551       LINC01475            0.0         0.0   \n",
+       "3  chr10_101292051_101292551          NKX2-3            0.0         0.0   \n",
+       "4  chr10_101380430_101380930        SLC25A28            0.0         0.0   \n",
+       "\n",
+       "   AC012531.1  AC226150.2  AFP  AHR  AHRR  AIRE  ...  ZNF784  ZNF8  ZNF816  \\\n",
+       "0         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
+       "1         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
+       "2         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
+       "3         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
+       "4         0.0         0.0  0.0  0.0   0.0   0.0  ...     0.0   0.0     0.0   \n",
+       "\n",
+       "   ZNF85  ZSCAN10  ZSCAN16  ZSCAN22  ZSCAN26  ZSCAN31  ZSCAN4  \n",
+       "0    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
+       "1    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
+       "2    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
+       "3    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
+       "4    0.0      0.0      0.0      0.0      0.0      0.0     0.0  \n",
+       "\n",
+       "[5 rows x 1095 columns]"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = tfi.to_dataframe()\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "646b4d43-5bcd-4227-a827-09078c8c3637",
+   "metadata": {},
+   "source": [
+    "## 5. Save the CellOracle base GRN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "addd6008-84dd-4ed5-89d6-ed9ef600941c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.to_parquet(\"base_GRN_dataframe.parquet\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b6a1e027-f934-434c-b576-7d2e004dab71",
+   "metadata": {},
+   "source": [
+    "## 6. Fitting CellOracle GRN"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01162033-73b1-4bdd-be0e-fcaa42d646b4",
+   "metadata": {},
+   "source": [
+    "This notebook section follows the CellOracle documentation: [GRN model construction and network analysis³](https://morris-lab.github.io/CellOracle.documentation/tutorials/networkanalysis.html)\n",
+    "\n",
+    "⚠️ **We shortened this part of the workflow to demonstrate the use of CIRCE for CellOracle GRN.** 
For all details on scRNA-seq data preprocessing, please refer to [CellOracle - scRNA-seq data preparation](https://morris-lab.github.io/CellOracle.documentation/tutorials/scrnaprocess.html#a-scrna-seq-data-preprocessing-with-scanpy)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "02272305-c0ba-436b-a7ce-f20db85efe09",
+   "metadata": {},
+   "source": [
+    "During both data preprocessing and GRN inference, we make use of an `Oracle object`. This object leverages its built-in functions to calculate and store all required information for these steps. To start, we create a new Oracle instance and provide it with our gene expression dataset `anndata` along with the transcription factor information (the base GRN)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "3b63d236-6fb8-4e4b-94af-a6b69365462f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rna = data[\"rna\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "8096ac0e-ef57-4f16-a607-523e6b95cab0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Random downsampling into 30K cells if the anndata object include more than 30 K cells.\n",
+    "n_cells_downsample = 30000\n",
+    "if rna.shape[0] > n_cells_downsample:\n",
+    "    # Let's dowmsample into 30K cells\n",
+    "    sc.pp.subsample(rna, n_obs=n_cells_downsample, random_state=123)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "41c006b0-4c9a-4cb6-ba3d-b7d32bc5c153",
+   "metadata": {},
+   "source": [
+    "#### 6.1. Create the CellOracle object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "fd39425f-d255-4ce9-aee1-21db810f958b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Instantiate Oracle object\n",
+    "oracle = co.Oracle()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d5c5dd8f-e84a-43e6-a8c3-f99f49066089",
+   "metadata": {},
+   "source": [
+    "#### 6.2. Preprocess RNA data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "3cc09566-5538-4558-8edd-a47a89365f7f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING: adata.X seems to be already log-transformed.\n",
+      "WARNING: Package 'fa2-modified' is not installed, falling back to layout 'fr'.To use the faster and better ForceAtlas2 layout, install package 'fa2-modified' (`pip install fa2-modified`).\n",
+      "18410 genes were found in the adata. Note that Celloracle is intended to use around 1000-3000 genes, so the behavior with this number of genes may differ from what is expected.\n",
+      "WARNING: adata.X seems to be already log-transformed.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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WkJCQkPh/iWSISdwTLLt2cbNrNzJGjb5rm3nN11h37aZsy2aqbd9GxJQpAJTv2IEnMxPb0aN37C/XaomZNxd11aqUbdxI/IdLiP/0E+xnzlKyfDmFH36IJzcXv9t9x/vyXn+Daw0bIdNokQcGYmjVGgC/y0XxZ59hO3QQv8WC/fhx9E2bUrTkQwremUPhe+9RtmkTxZ8tR/D7AShdtx53WjrKqEgEjwfB56P6zp0oIyNBEAh/ZkrFUQUAXCm3yBw3nrShwwBwZ2SQPW1aZVK+ZfcevLm5WPfuxe9yiZ41QBEYSLUd26m+60fUCQn/9n2QkJCQkLi3SKFJiXuC32YDQcBvtd61LXjow3gK8gnq3/+O8dh5c7Hs2YNp0ODKMZ/VhnnlChShobhTU3GnpiJMex5j+/Z48/PxmUtQhoVxs3MX9C1aED55EurERJRhYbhu3ABBwHbgAJqqVTH16wtA+dZtFC5chEylIvLVVzA0awaAoXVrHOfOoaldh5xp0wHQ1KqJsW1btPXqYujQAcHrJee55zB27Ur8ksWV3jkqDKnIF17ANGAAfpsd+5GjqOPjATB/tZryTZtxXb2GsWNHImfOQJOcjFyv53q79iiDg0natBG5VosiMLDy/B1nz5I7azamfn0JHTWK8m3bcF65SthTTyLXav+Dd0xCQkJC4o9AMsQk/nBKN2ygfNNmIqZPR1szGQBT376oq1RBlZCA7dhxsqdOxfTgg0TOmI6mRg3iFy8GRBFV6759hD35JILPR/Hyz7Hu3UvV9euRqVSYV6+mcOEilDExREybhkyrwXH+PJa9PxEy6lGCBg6kdN06AJzXrpH+yHDUVapQbcd2Yt6dR/nWbRTMmYM3L4+cmS+gioggeMRwNHVqo6vfgJChQyvPI3TMaELHjEbw+bAfO4Y3Px/rT/uwHjiA+YsvUYSHEfbEBOyHD6OKExPzq679Dm9BAdo6dQCxeMB+5AiOS5dI2rG9MidN16QJsjVrxFAmoI6Px1dqrqzu9Lpc+B2Ou4wry65duK5epWydl5CRI8l+fhr4fKiTkgjq3+9fvmc+i4XiTz5B36IFxvbt/+V5JCQkJCT+PpIhJvFvYT1wAGVkJNrk5N/cp3jZMtw3b1G2YQPa6dMqx3UNGwJgPnUSX1ERll0/4snNJWjwIIxt2wKQN/s1PDk5KEJC0datA14v3sJCrjZthqFVS8KffprSxAQC77uP0DGjse7fT+b4xwHQ1qqJoXVrggYMwHn1GuaVKwGQBwdTum49mmpJhI4ehTIsFFdKCsUfiUZP8MND7qiOtB48hOXHHwl7cgKqyEhyX34F64EDhD76KEUffSTupFSiCDQR8sgwTA/1J6VnL8wrVpLwxRcYWrbAZ7Eg1+lAoaDgvQXg92Ns165Szd9vtyG43bh/IeqqiokFILD3gwQNHozj7FmMbdsiU6sr9wkZNQrB5yegW1dkcjnBjwzDefkyhlb/WKD271H67XcUf7qM0vXfk3zo4L81l4SEhITEbyMZYhL/Mj8bPXK9nhpHjyD/hYHwSyKeew7L9u0EP3K7WtGTn48qMhKA0FGjkOv12I+fwLJzJ57CwkpDLHjkCMq3bsWdnU1At65U+XoNpZs2Ubp6Da6r19DVr0/1nTsBMYcse8ozyPR6tDVroggPJ33ESNRVq2Lq34/yrVvRNWkCfh+5L76ITK+n5skTmHr3xu9yYTt8GIUxAHX16nesP/+tt3CnpKAIDCBoyMPYT55EsNtBLkPfqhWaatUIm/AEcqMRwe/Hsn27mNMlk4EMbMePk/HYWHT16lFlzWoiZ8zAeekS3qJi8l57DU3t2uTNmo2hfTvCJkzAZ7HgunGTsPHjCB48CEVQEJmPP4F13z5Cx40lYurUyrUpw8KInD4Nx8VLFCx4n7Dx41GGhd11Dwrmz8dbUEDUq68i1+v/4b01duxA+datGDt1/If7SkhISEj860iGmMS/jDIqCrlejyox8e/2XQzo1ImATp0qXxcuWkTRhx9VGhVyvR59kyZoqtfAdesWzjNnMH/9DcEPDyF01ChcN25Qtm493uxsEld8SebEpwEI7NsHweOhZOUqNNWriR4nQK7TETNvHs6LF7GfOIH95EkiZ84g+fAh8t58S/SMKZUYmjfHuncvADKNFue58wBYfvgRd3o6ISNHINdq0TVsgDsjA8eVqxR364axUyfCxo/D1KcPMrUaQRAqlfbLNm8h9wXRyEvathVNlSpi5aPHgzszE7/TScjIEfhtNq41rcg969ABfD7w+dE3aUL68BHiml94gZCRI8RrHRkhfo++W/ICIG/WLJwXLyI4HUTOnHnHNm9hIcWfLhOvWa9eGDveaVz57XYc586hb9YMmUoFiLlnzitXMLRtg6+8HOv+Axg7dURhNP69R0JCQkJC4nciVU1K/Mtok5OpcfQIVdetBUGgfOcPeLKzf3N/v9NJ0aef4rxyFQBvcQkA5Tt2kjZ4iOgdqlYNBIH8d96pFGoN7NEDdfVqmPr0Fl/37IkqIYHAHj0o3/kDBXPnkvnURAxt26Jr0gRfcTFFixcT0KUzpv79kZsCKapQ2g/o3AlVbCxBgwcRMe15sp6aSNZTE1EEBmBo1w5T//7kvPSSWBn5/fcACG6PGBKtkMHwWS3oW7VGplZTMP89rtarT9mmTQDIjQbkJhP65s3QVKkCgOnBBwif+iy+4mLSh4leQbnBQOi4cQR0705g797oGjUk9KknK+Yw3vE9d/ZsSr9bS9RrswkZNuxXr23ggw+grlIFY+culWPWAwfJePxxPDk5hE16mqCHh6Bv1equ9+a+9BIZo8eIIdMKnNevgyDgvHaNvNdeJ+e558h/8y3xPrrd+H6lyEJCQkJC4vcjecQk/iUEtxuUyspwZMmKFeS/9TaaGtVJ2rz5rv0LP/wQ+7Hj2I8dQxEURPyyZeibiWr5zqtXQSZDYTQS/fpr3DxyBMHhwH72HCVfrkBuMJC0aRMyufh/Q9SLL8CLL+DOyMC8ejWKsDAMrVohUyoJGjgQb0kJtsOHSR0wEEPXLvhLyzB/t5aQUaMwtGmD4PVSunoNyvBwVIkJyNVqFBGRxC1ZjFyjQabVYD96DOeVq6Q89BCR06YhU6mQGQ0EjxhO/muvk9qnD9X37sFx8QL4fDgvXcZbWETBvHmY+vbB2LEjtsOHMbRpA4Dr5i0QBLxFRZXXJGLqswCkDhyE8+JFLFu3YmjalLhFC7GdOo155UpkKhWua6JR5M3L+837ETpqFKGjRuHJziZjzGPoW7bEduQI9qNHUQQEEvvuvF99n7eoCMeFCwAogoNvr23KFHT16mFo04bStWsBUFdLQnC7SendG29BIVW/+xbN34RxJSQkJCR+H5IhJvG7caWkkDZoMKrYWKquX4dMqUSdmAgKBTKtDp/VhsJowHHxEo4zZ9C3aUPRog8AUERGENi1K8Z2Yg6YJy+vsjIw/PnnsezZg+DzEXD/fWiqViF/9mwAQkaOQJ2YiOPCBbKnPkdAt24oQ4JxnD6NIiSE6DffoPiLL9A1bEjcwvdJ7dsPb2Eh0fPmUb55C97sbHJefhlFQAAKkwlvURFFHyxGplIR/9lnpPTqhTIkhKStW4h+9VUArrdth6+4GMvuPVj27sVfVkboE0+IYqp6PfazZzG0bUvgAw9i6tmD4uWfA+DOziH72amgUFBj/z6UoaHY9u8HQFchheF3OisrIENGj6J07VpMD4mJ+zK1GvvhQ1j37MF1/ToJny/HcfYcirAwcl54kdCxY9EkVa28H46LlyjbsIGQR0di3fsTtsOHcZw7R9ySJZgDAwkZPapy35JVX+EtKCD86YnIVCose/bgycwChQJVYgJZkyYT/swUUc6jTx8Awp54gqL7BnKgwEeDbAu+wiIEh0PsOCAhISEh8W8hGWISvxtvXh5+mw13ZiaCx4NMqcTYsSOG9u2x/fQTBfPfJfrVV8maOBFvXh4RM6YTPGwYPouFyJdfwnn2LH6bDbnBgGXPXmQ6HcrwMLS1alK+cSO43QheL85r1wns1RN1laqoExNxpaZSvnUbnowMzF9/jalPb0wDB2Js24bSb7+j4J05KMLCSD54gMiXX8KyazeCzUrooyMp+uRTnOcv4CsuxjRoIKFPPC7mcqnVFC5YgGC343G7KVjwPpHTpyGTyQgZOZLCBQso/eYbAnr1xHHyFIEPPkDIiOEgk3GzU2cEtxtleDilq1eTsHIFhrZt8ZaVkXfzJsq4ODzZ2RS+vxBFaCg+sxm/zUbh4iUULV5MxIzphI4ahemBBzA98AAgNgSXazUEDRqE/cwZHKdOk/Pc81T55mtShz2C8/RpHOfPk7RpY6WHsGDOHOwnTuC324mcPg1Xagq6xk2wHT2COjEBbe3a4n0rKiK/onuAvnkzjO3bo0muiaZWLQJ79aR48WJcN26iiokhcsb0O+55qUcJ+CjzK6m7di2+UjP6Jk3+4bNiO3oMdUI8qpiY/+ATKCEhIfHXQcoRk/jdGNq0If7TTwno3p2U3n1wnBeT3HV1xD/4mmrVcFy6hKF9exThYegbNSLypRcxtGlD3ksvkzn+cXJffgWA8m1bERwODC1boQwOJnjkCMImT0Jbvz4Fb7+N7fgJggYNxJ2dTWrffpSsXElAj/sR7HZKv/6GoAEDELxeNHXroIyJJqCLmCNlP3Ua+5EjFC54H9NDA/CVluIrLkZTuxaBD/Ymd+YLCE4n6uRkHKdOif0fvV7MX3yBOzUNx8VLCIIfRVAQmuRkbEeP4cnKwnleDOPJ1GoMrVujCAvDW1iI88oVfMXF4PeR/9pr+EpLCerTm6KPllL63Xcog4MJ7NWT8IlP4bolSlS4b90CRC2wqw0bkT1tOtmTJ5P5xAQK5s0Tc8QEAW+pGb/TiSo0VHzfzZu4U1Mr70fQwAFo6tTG1PtBFCYT2jp1KFqyhOKlH1P86TKcly4DoAgNJWjwYIwdO+ItKcF++gyFCxbgunoVT2YWYU89hbFrV4IGD7rjfhd/9hkBTwyiVnkK9RMD0CRVvcMIEwThV5+T8h07yBg1irQhD/8bT5uEhITEXxvJIybxdxH8fgrmzwe/gKZWLeR6HYHdu2Ns347cV1/Bm5OL/fhxdA0aED5pEmETJpD32uvkv/EmoWMfo9q2bfjKyrD88CO5M2eCQgFA+c6daD6uSdQLL1D08SdoatXEnZlJ+sNDkalUxC5ahDIiAmVMDDc7d8HYtStynQ7B5yPiuedQBAaiCA6mcMEC7MePEzpuHDX27AHAce4clp07kWk0mAYPouz79Wjr1sVnNhO/ZAmKsDBUMTF4cnNRBgeha9wYTe3a6OrXR24woAgLJa3rEPwWC5GvzSZk8GAyxozBVlSEr6yUm126oggMJPLll3Fev05gnz6YHuhF8fLPKf36a1SJichNJrT16iE3BmA7dAifpZyEz5cjUyqJnjWLgG7dMHbsJK73/AUElwvXrZuoq1RB8Pmw/Cg2Odc1b07o+PEULV2K5ccfUYSFYerTG3XV26FJU9++mPr2rXxd9v0GPOnpqJOS0DVqhDIinIwxj6FKTCD6tdnYjhwhY/QYZCoVIWMfw3nlCrqGDZDrdBg7dbxjbhC9WvLcLIIObEd1X+s7tpVu2EDuSy+LFbCTJ9+xTRkaKuqrhYf/Zx5GCQkJib8gkiEm8XdxXb9OyWfL7xjT7voRdVwcce+9R9nWbVgPHkQREkLQQw9h2bWLsq1io2pkMlL69sObk4MqNgZFaGilvlf5xo3YT50k6KH+WH78EcvOnSjfXyBqbwHa2rWosX8f2dOmiaFMSznVfvwBb4kZ60/7KF3/PYZWrdDUrIn95Ek0yTXwu1xkTXgST2Eh+HzIAwPxFRdTMGcuyphoauzZg+DxkDN9BqrEBNypqVh/3IUiPBzHmTNEPDeVkNGjSR00GL/FgkyvRx0bR0q//igCA9E1akTBnLmAKPlgO3QIb24unsxMjB07kv/OOwCoYmOpvnMHjgsXyX/nHQS3G9eNm/htNmQ6He7UVAJ79EBWYZSGPfE4qthYDG1aY937E77yMjxFRTiOHcdx4gSlpkBMD/YGpRJL807c6DKKji4/Rp3o0PYWFVGychUB3bujq1cXQfAj02qJfPEF9E2bYtm3D9vhw3D4MBFTn0MVH48iJARVdDTutHT85eVYdu3Gun8/+P0oTCYCunevlOSInvUqll27CKzIGfslzouXwOut9BT+EnlAAAiC2OfTbv+n9MskJCQk/teQDDGJX8WdmYnt4EECevYiaOjDCA4HjkuXket1+ErL8AUFoWvUiNKNG7EfPYb92HH0zZpRunETgt2OtnFjwqZMwbxOVKj35OUTPmkSnqxMQidMQNewAQFduuC8fBmZUolMp0PftClJWzZT/Okyipcvx3HiJI5LlwDQt2yJIjCQtIeH4k5JEdeYkUHkCzMp/f57Sr74Em3deqLBAUS/9RaGVi3x5OejCA2tFIh13bpF+bZtABi7dcNbWIA7PQOZWo22fgOynp6E67IYyoucMQO5TouroqpTU6MGICbc65s0IWTUo6iiItE2bszN++7HZzYDYGgjeo2cFy/gLy9HptcTt/B9/C4XOZMmYT92nJDHxhAy8lGyJj2NpkoVYubMwZ2ZSf5bokRE4lerCOzWneJPPiF46FCMbdui69qNH7eeJmLedEr69ML4yCAse/ZSMHcu7rQ0bIcOUeW7b3Fdu47gdGI7cpTMx5/A2KE9oePHo05MQGE0oDAaqHHoIGUbNopVlUFBGDp2FA3GmzfJnjSZwD69iX71VUpWr8bQogUhjz4KiL09C99/H229ugT160f4lCliB4P2He5+iCpClrLfCF16CwtRSt4yCQmJ/3EkQ0ziV8mZPgPH6dO4s7IqqwihQvNr4EA0tWtT5ZuvUZiCRC+WIOCzWHBX5D8ZmjVDrlBQbesWyjZuRJtck4wxYwDQN29eqYdV/NlyBLcbTa1aKMPDsR07Tum3396xFlViIt78fLHXosEAQOiTEzC2ayfmelmtuG7dQhUTTfTbbyO4nBhat0IRGooqJuaOFj0/a4Opq1cj5t15ZI1/HH9pKYrgYAwtW1AwZ464/g4dyHvlFYKGPkzEtGmUrFyJMiwM05DBFLz+Bo6TJwkaOICwCRPE/LGMDJDLiftwCYYKwVSZRgOAXKPB2L49qYOH4KzIp5NrNDjOncV57jzOc+eRGwMIGTMabZ06YlizVi38bjea6tXwW0TNLoXHRZ0zO3GcO4q7NAceGUThggW409KQBwZi6v0gMpmMhE8+xp2Zhd9qAa8Xd1o64ZMmiRptFbjT0sRQMVBl7Vp09eoSMvRhipYupfD9hXiysilZvZrC+e9RbDSiqVaNmLliUYB51SpQKjH17YvCaEDXqBFy3e0emLajR8mZ+QJBDz1Ete3bkOv1d3nDCha8T/HHHxP21FOEPz3x9z2cEhISEn8hpGR9CUDUBSv+/Atsx44DoG/aFJlOV9kPEsCyZy+WH3+sfF2yfDnFS5eirlKFKt99i65uXfTNmiPT6TC0rdDPunoVZVg47ox0AOQmE4b27XFnZXG9fXscZ84Q+vjjhE+cSOGiRcgDAwjs05ugRx4hYvo0Yt6dhyc7m9JvvyPt4aGYHupP9d27iJg0CfvxEzjOnUMeEEDkCzMp27gJdbUkfBYLNzt3IfPxx+84R1dKCo4LFwHQ1a9P2uDB2I+L5xv+nNg2KP6Tj4n/9FPU1ZIA8GRkoqlRHW9uLrajRyuNIrnBAHI5hR9+iCo2hqjXXyNs0iQK3l/IzTZtcWdkoI6PR6ZSoUpIwO9yoU5IAEBVtSrK2DgCOncmqKKpuPmrr8h7dRbOy5dRmEzIDQbKNmzEvHoNOdOnYz18mNSHBuD4bg361q2JeFZcrypRnDN46MOEPPoopeu/J33ESFxXrxA8bBixixaib9WK1H79ya2QAgHw22zomzdH17Qp6iqJleOqxEQUQUFiFWyLFqhiY/G7XDjOnaP488/R1qmDoW1bQseNRSaTYdm9m5QHe5P2C6FZ2+EjeHNzsezahTohAWVYGIIgkFHooMzuAcBbUHDHdwkJCYn/VSSPmAQAZZs2UTBnDnK9npqnTxEx9Vkipj6LIAjkz5mLr7RUVI/3+Qh/birBDz+M4/RpUKtBJhN7KwIxb79FzNtieM1rNpMxdhz4fGjq1gVAV68eyuBgrBcv4Ssswl9aRsIXX5D/1luUrV+P4+w5EpZ/Rsnq1TjOniWyXz9CHhlG+Y6duK5do/iTTwkeOBDB78fUvx+umzfFasxZs0SRWZmsMs/MX2654xwL3p2P4/RpDG3aoK5SlbLvN4BKhUKvJ++VV9EkJKBv3hy/3Y75iy/R1KpF0JDBGNq1Q9ugAZ6sTPxOB8jl6Jo2pXDhIso3b8Z5/gJyg4HyrVtBLge/H8fZc5j69CbmvflkT55Car/+JG3biiIsDPMXX1C0eDH4vISOfQzb4cOooqIwdu0q6q61aA6I/R6LP/8cX0EBuTNmiqE+v5/QMaMxtm8PiMUUAL7ycgCxIlMQcN24gUyhIPC++8Q8LgC/GCK07N5N1lMTUVerRsKnnyCTy/GVl2M/eQrr/v34SkuxHztG2OPjqb57F5bduylZsZLSr7/BefESVdd+d/uiysT/5WQyGT6LBfOarzF2aI/cYEDfsgWFiz5A17gxRTWbcialHI1KTq+m4US98jKBPe5H3/Lfa04uISEh8WdHMsT+x7EdOYI7PR1dkyaoEhLQN216x3ZPdg4ln4tCpaoqVfDb7QT26InCaMTYoQNB/fpR+u23FMydR8IXn1OyYiW6hg3Rt2iOJysLucEg5h5duoQyOhqfzYZl714COncmZv67qKKixPBW0yZYdu5ElZgo5kq9/gYIAvomTYicORP7mbN48/PR1qvL9bbtUIaHEzJqFJadO1EnVUXfsiWOs2cR/H7kGg3Rb7+FKjwCT34BqsgICubPx7pnD8rwcAIe6IUqLIygwYPR1EymaOnH4PPhs4iGmzs9XTRmrl4le9Jkqq5fhzslBb/VStk334oJ7RV5Z/bjx9G3bYPr+g0ATIMGYd21i5wZM1BGRSK43OD3405NxfLjj4SOGC6KxP7wA3mvvErAAw/gSU/HV1xM2JNPItNocKelAVBSYYQpQkIIGjiAwP79KVr0Ae6MDAAyJzyJ7cABQsePJ2T4I+S89BLqhESi33xD7F9ZQfiUyQT2uL8yx+1n40lwOLjZtRuaGjVQxcdj3b2boIeHED55EoE9ewJQbHGjaduRYI8X+/HjqGJisB09huPMaUJGjSKgS2eStm1DGREu5vZ9/DGamjVJ2riBkpWrKPrwQ+QmE+G79qOUywgxir0s5Todhg4d8JeXg/Z2WFNCQkLifw3JEPsfxu92kzH+cfB4iF24kOo/7KzcJggCZRs3oo6LI/SJx3GnpmHZKW73FRWSv2oV+ubNMPXtg/PyZQzt21G6bh2F772HPCBAFBtVKPCXl6OuXh25Xi+KtJ49i3n1GnxlZWLoq0Lo05ORid9mw7Z/P6qoKBAEZGo1Ad26AaAMCxOPbS7FX16O22rFfuY0gseD7eAhdPXqYTtwAHWVKlT9fj3e/HxSeotNuavt+hF3ttgnUlu/HiXLPsOdmkrwI4+Q//obaOrXJ/SxMWjr1UPwevEWFGDs0hn7pUv4i4opmP8eQoV4qqZBfez7D1D+/fcEdOxA0tYt3OrZE7/NRuKqleiaNOHmvn0gCBQuXIi3sAhVfByevHwUQUH4/QK2w4eRqdXIAwII7NkDn9lMYPdu2E+dxFdSQuk33xL+5JOgVFXej6BBg3BcvEj55s2Ub96MqW9fnDduiBWLly5hO36csrXrxJ3lcrS1a+O8do2wJydg6tULT34+2jp18JWVgVxG1c2bcF27Rs5zz+O321FVNBMv27CRhE8/QV2lCoVlbg5eMaOUy2ivUpG0fRvqhARutG2Hz2xGbjASMnJEpcq/oXUryjZuJKBrV/F1m9ZoatVC36wZzrdn06pqFcLHjas8p7zZsyn9+huiZs0i+OEhALhSU/Hm52P4lZ6YEhISEn9FJEPsfxi5Wo2xXTvsJ45T8N58NDWqo0kSc6Ose/eSO2MmMpWK5BPHEfx+3FlZKEwmbKdOU/LFF5R+/z01jx3FV1ZG0QeLiZg2DVVcHILfLzbIVqkwdu2CJimJsk2bMfXvj7Z2LQByZ8xEGR2NtlYtQkYMp+TLL5EbDISMGY2mRg3U1aoRNHAgll27KfzgA8KfmYLt0CEcJ0/ePgGfD23dujjOnMFx4QKK4GCMnTsj1+luhyhlMqz796Nr2BDLtm1Y9x8QK/VkMlCK8hGe9HQK3plD2frviZg+XUxGByJnzSJ/1ixsR46gjI7Ga7MR0KEjQlk5zitXUEVHI3g8+K02BJcLeUAArpQUZEoliuBgHOfOg9dLzPx3we8nY9Ro9C1b4isuRqZSUX33LtIfGY7rxg2CBw/C0LYtRYs+QHC5cF69SvDQhyn9+mt8JSU4LlzA0LIlxs6dUSfE47p+HW2tWlizsrAdOkTYU08S2KsnPosV24EDuLOyRCPt3HnMq77CV1JCzPx3Kdu0Cdu+/YSOG0f4lMl4i4sxtGuHJikJ6949eLJzcFy4iL55c9RKGXIZqOzl5Dw9CUPTJiSuXIGpT2+sBw9VhhVLv99A/uuvE/bUU9T4aW/l7dFUq0bShu8p37GD7CnPABA6bFhlwYWnwjj+uVG84PGQNljUb4v/eCnGiqIHCQkJib8ykiH2F0TweEAmQ6a8fXu9ZjNpDz+MXK2hytdrKv8Yxn/0IdeaNsOTnoH9+Ak0SUl4CgoomDMXmVqNrnFjZGo1ls2bcV26hDwoiOhXXsa6a1dlQ2uZQayIc169irFjR8xffYUqPp7Y+e+ia9CAnOkz8ObnY/7qK6LffAP8fso2bsKbl4c1NxfHhQsITicyg4HgIUPImvg07lu3cJw/h+Dx4Csuxn7kKIb27XBcuIiubh2UkVGUrlkjnpxGA243vrIyArp2xXHhIsqQYKrt3EH289PInT4DQ5fOyLRaBKcTb24uid+vR1u1KuavvxHDYzIZqpgYyreJGmjqxESCBg4Atwt5YCAB3bqTMXo0+a+/TsSM6SR88TlyrRZ3VjbKiAjU8fEow8K42bUbgtMJQORLL+Izl6KKjcN+4jj4/fgtFmIXLcSbX0DmhCfFnDNAplTiLS6pvF/uvDzyRo9BFRND8IjhBHTtiuB2o61bF13DhuQ8Pw1Pdjaq+Hg8mZnkvfEGSevXI/h8WH/6CWVCAubln2Ps0gWf1YrTakUVE4MqSvR8KaOjKF72GYULFqBr2pQqX60idvFi8l59FeuhQwQNHoTJaKRn03CyvzmIQ/Ajj4vD7fXjfGwKcc9NR6MSvYT2k2J7JevBAwR074Y6IaFSbV8mk4n9OHv3Rl0lsfK5A4idNxf76dMY27UTB5RKUdvM45FkLSQkJP5nkAyxvxjeoiJS+vVHplaRtHEjioAAcTw/H096BshkeM1mXMeOUbpuvaiGP2Uy1j17MXYTQ0quGzfEPCm5nNj3FyCTyxG8XvEAPp9YJblmNZ6CAnJmvoChRQvcV69RvmkT8Z98jOPcOYIGD0LXoAEA4c8+g/PyZVw3blD67XckLPsUfYsWlKxYiTszE0uFAGzQyJGkPTwUV1oaqipVxLUrVSjCwvCVlhI9by5FH35E6apVIJcT9Mgw5GoNQcMfIW3AQPylpWQ88TiC1YbcZKLG/n1oqlbFcfIkjtNnxJZGSUkY27cj85HhyINMyAABCB49msipz1KyYiUAgb17I9jt+ErLyH/rbaw99+GvyCGz7NyJ48xZol5/jcIF7+FJT8eTnU3Z5i1iSFajIfLFFwjs1YubHTpStGQJiau/IvaDRegaNMCdmiq2HrpwAV2L5iR8+im+0lLSRo9BptOhqV4duVottjcqKiLw/vuRKRSUbthA0eLFyI1Ggh95BMsPP2Dq34/C9xYgU1R8lP1+5AYjnhs3KPv+e8q3bqXG8WP4LRZU4eHoGjUibPIkCufPx3H6DACqmBj8DgeO06crhVmdFy9iaNUKtVLOjTodcXy4hRrVwilMt5Be6CQmREPL5CAAIp57DnVCAkUfLeXWAw8Sv2Ejh8qMCEDn+qFoAgKInScK4TrOnQNA17AhiqAg9C1akDHmMWQaDXEfLqHqurUIbvcdBpuEhITEXxnJEPuL4TObxZ6Hcjl+i6XSEHNnZCDTaDB27YI6Lo7sKc/gvHgRZXgY9iNHcaenU/rNN4Q/9RSGNm2ImvUqfrsD28FDBD74gBjug0o1eICy9esp+/57se1O/374ysqRKZXEf/IxfosFweejZOVK1AkJyPV6ZGo1poceAiDj0VG4btwg5t13UQYHY161SiwK8HrA6yNg8GBKlt9W9LcVF3OzjSjKKlOp0DdvRtTMmXgLCnClphLyyCMULVmC4HAiU6tQVOSpRb02G33rVuQ8OxXkcsKenIBMqaLkyxX4fT7w+0GhILB7N2QKBbqGDQmf+iyBvXtzq/t9+Gw2ACw7fwC/n5AxoylZLhYvqJOSKN+6DRQKwiZPouCdd0AmI+rNNyj+aCne/HzkQSYEQRCNjiZNENxubnXrjuDxoGvRgshnn0FdpQql69aDw4E8NJSYOXMoXrYM5HIElwvr3r0EDRmCvmVLNDVrom/ZgohnphD+9EQse/YQ2KcPEc9MAcTK0JIvv8TYuTPKyEg01aqJPSeXLiXiuamEjh2LQqOhbP33IAhEv/02gX16k//aa5R+8y2aGjUI6HE/+ubNK699TOENCtQhxIZpKSr3QKGTIIOKki+/xHHuHJEvvUTQ4MEUL/8cnE48MgV2t1jN6fb6Kz1n7vR00oaKMhfVdmxHnZCAOzUNe0W42Zubi7pKFWSq27lxEhISEn91JEPsL4amRg0SV3wp6ldVJMIDOM6cRXC58OblA2CsSKgOHjYMRVAQZevWY/72OxRBQYQ88ghBgwZxrVlzBIcDd1oaxs6difvwQ5ShIfhdLuQaDYG9emE/dRpjp46oYmPJemIC1n37UJhM+MrKCH9mCoXvzq+Uk0AQkMkrfq4Im/rKSgl+eAiWXbvQ1a+Ptm5dCt9/n5IVKzB264bf4cDQpg32o0exHTgAMhmK0FDili5FplSS+sgj+HLzkAUGitNGRaFrUJ/oWbMq/6DL5HJQq1EnJJD74ksIfj+xixbiunWLooWLQKWiaOlSYufPJ+upp/CZzQg+P36nE7xeFOHhGNq0wX3rFsZOnSoNMUVkBJrkZLR16hA8cCCWLVtRmEx4bqXgycykZNVXRM+ehaF1a2RaLWmPDMdvsaBv1RL7seO4Ll3CZ7Nx68EHUccnEPXWWziOHyP3xRdxnDmDOikJbb165M+dh/nb7wjo1RNtrVqET5qE8+pV0oc9gt/lEnPlatcmdPQoqLi8CpOJGvt+AiB76nMAuDMyxe+ZmQR064YqIQHTgw+Q++qrlYn+xo4dCH/qKUrXraP4s+WEPPooildfJRpQf/cd1erXo2qoCrlKxZV354PHg75FS4IfHkLgA72w7t6DpqyY9nXqIggQoLv9K0YeGIgiJATB6cRx+TLqhAR09esR9eoryNRq1FWq/Gc+BBISEhJ/IiRB178g+ubN0TVqBIiJ0JkTnkQRGkrkyy8R887b+EpLKVqyBOfFi/hKzERMmSLmEuXnY9m+A6DSOyQ3GilasoT0oUORaTWkDx9Bar/+WPb+RNHHHxP92mxCHnkEbY0aKMLDUVerVml4aapXR52cjCI0FAQBXcOGOC5d5mrDRsgrDKfSteuwnzxF9d27UMXEUPTppyijojB26kjwkMGiYr0gEPXqK4RPniSG6/LyKJz/XsU6xT/0gkPMtfJmZ2PZvgPLvv0Uf/YZzhs3yJk2HTweImfOQKbVIlOpEHx+gocOFYVcPR5s+/ZjXr0aX2kpMp0WdWIC+naiB85XWEhg925UXfsd+kaNUFRUcDqOHiN42FDKNmygeOlSgocNQ10tCVP/fmhq18ZfVkbBvHdFw7SkBMfp07iuX8eVnoHg94tVokeP4r55C+u+fcjkMso2bMRx5gzaBvUx9X4Q0wO9EJxOPFlZFL23gLKNGyn65BOypjyD325HJpejbdoU55UrZE15RgwpAz6Hg+Lln5M99TnCnplC5Cuv4Csvx7J7N7kvvyIK83q9yFQqPFlisnzo+PFoatQg9+VXKP1+A+6UFOynTqFv3Qpdkyaoq1bBceEC11u0JH3ko0ROm0Zg794E3H8fANaf9uHNzydn5guE6mSEm9SAKB5rPXAQhcFA1Kuv4LdaxWrNCm9j8NChBA0Y8Ad9Gv7LCAKcXQ3ph+/1SiQkJP4kSB6xvzjlO3Zi3bsX+8mTVN/3E7nTZ+D3etHWqYO3sBB1hTJ72FNPoggJJrBHT4qWfozr5k3iFi3Eb7GQ+tAAMcTmciN4PHhyc8mbNQtvfj7OixdRxcQSMWM6vpISfIWFxH/yMeqqVcmbNRtvTg5Rs17FfuoUISNGkPvyKwguF4qAAJRRUbhu3iRv1izkBj22Y8cQbDZ8Hg+mBx+kZMUKPJmZFC5cSNGiRSSuWIFl9x6cFy9SunYtQUOGENCtK+WbtyA3GvCkZ6CpUwdfaSm506YBEHj5CoqwUHxl5RQuXISxXTu8RYXkPPMMhnbtiH79Naz79iM4nZTt/AEEAUV4OCVfrsB59iy6hg2R6XRkTXyaoIEDMbRpjSoqCl9REeq4WNxpouHjuHWLki9XAGA7fhzPrRQUoaGEjB4FgCo6mrgPFmHZ+xNl69aBUkns+wswdOqE+avVCHY73rx85CYT+iZN8FssFC5cRMTzzxP/8VJUcXGU7/wBd1oqntQ0PGlpqBITUUaEEzJiBNmTJgMQMmY0qmvXCejSRWxh5PdjaNMaT1YWlh07sB0+TMiYMeK9r+geEPvefBxnzmDs0IHrLVvht9sJGTcOfaOGBA8bdodn1Z2egeBw4Lp2jYBuXXGnpeHJzkEZHEzouLHkz35N1EUrK6uUHMl9+WXKt20n5NGRhIwciSohAXVCArKKcPdfimvbYMMEUGhgRgao/kMaabnnIfMYNB7xn5tTQkLi/wWSIfYXx9S3D9YDB7AfO0bG6NE4z4m9DqusW4umWjVKvvgCbb36GNu1JWLyZPwuF4Xvvw+AOzUVbYP6VN+/j9K1a8meOhV9mzbYDx/G6/WibdwY55kzuK5dJ7BPHxQmE4Lfj6ZmTVSRkTjOn8dvtYIgej3Ma74m7OmJuG/eQnC7CX9yAvlz5+I4cxa/3UHse/PJGD0Gb34+eW++ha+wUOwzWViI4HBQsuJLMa8tKoqI558ja9Ik3Ddvom/dGvuRI6hr1KDqt99wo6uoPYZSiTszE0PbdqhioilauKiy1yOICemFHyzGceLEHdfMV1iENyMTRXg4qiqJlUn6pWvXUrp2LfLgYAAcFy4SMupRBEHAvHJlpaq+rEJzzFdcjLeggBuduxDQuTNhE59CEARUsTHo6tbF0KEDvvJylEFBeNxu7CdP4i8rw2c2I6sQOS1cuBBVfDzyIBOuy1dIXLECuV6HIigIV1oajhMnKLKL3kC50UjEM8+gTkikbP16QseMxlNQQEDXrqhiYylZvhx/eTkKUyB+h4O8WbPR1q6Nrn59ZGo1hR8tRabXoUlKImTYUNwZmeS//Q4h48Zh+2kvgtdH2ORJRNmsyAMCKVq8GHdKCpadO9HVq4vpoYeQyWQogkNwXrtGzoO9MT30UKUHMVswcqFIQ5vN29BrFPwtzitXyH/zLQL79iF40KD/xOP/3ye8FgTEQFgNUGr+c/N+MxxK08HrhDZP/+fmlZCQuOdIhthfHGVYGMZOHbEfPYq/rJyI6dPB70NXty7mr7+h8P2FlW2NgEqvjjI2FuelSzgvXSJ84kTKt+9AsNtx3bqF3GDAeF93Yt9+m5IVK/EWF+POSMdXUoIiJARVZCSu1FQxdywxEVd6GuY1a3CcPo23qBB9o0YUzJ0r5nM1aYLgclG2cSPBQwYT2Ls3JcuWVYatAjp3RpWYSMkXX4ghToUCU+/e2E+cwH3zJqhU6OrXw370KJpq1ZAplQR0aE/pd2vR1qmD8/x5nOfPo2/ViuARI3CnpuDOzBK9NqWlqJOqooqLw5OVVXnNFMHBeL1eEATKN24i9KmnCOjZi9znnwfEkKvfYsF+7BjujAxMffuC348qNhZtndpETJ9O7ksvYz95UuwIkJuLZc8enNeu4Th1ivBnnsHYsSM502dQtmkTUa+/jrpKIvZTp0Amw3bwoNg/8/XXyH/5Fby5uQgFBQgOB7mvvkqVlSuIfv017KfPULz8M7R16+G6fBlFaCgylYriz5fjSc9A16gRsXPnYt2/H1dKKuqaNXFfu0b51q3INRr8Nht+ux37yZNkjhtf2bzd2LEjquhocl98Cdvhw/idTjE/DzB26ULh+wvxmc1EPP88nvw8QkaOoGDhQoo/Wkrkyy8h12rEfUpLsR08SNWNGwgaM5YdaQKCw0epzfOrhljZ5i3YT54U8wZ/wxDz+wUuZFhQKeTUiTf+5z4o/ylCq8HUK//5eat1hiubIbbZf35uCQmJe4pkiP3FKd+xg4I5c9HWr0fc4iUoI8KxHz+B12xG36K56G3R6XBnZaGOi6sU11SGhSGTyQjs2QNlaCjevDwAfPlisn9A584AhIwcAYBl3z5xe2kpnpwcChctwrJ9B6rEBDzpGSijolAnJopir2VlKIKD8VksWH74AW2TJqirVcN25Ahhj49HsNtQJSSgCAwk9+VXUMXE4MnMxHkhiJh5czH16kV2RdNrfD7cGZkkHzuK6+ZNvCUlRL7wAoa27ZCZAsl/5VU8mZm4rl9HptPiLSkBBLEq1Gol+JFHsB0+jLeoCEOrVkRMn0bO89PA58XYuTO2Awex7t2LTCHH0L49rps3Kz1o2rp1UVerRvGyZeiaNSNmzjs4L11CJpeT+MXnFC5eQtHixWJxwcL3KVm5Cgcg+Hzc7NoNr9kMgoCvqJC8zz/HfesWIaMexXb0KKhUOI4eBSDs6Yloqlcnc9x4XJcvYz16FEPLVsh1WrTJyQguF36VmpuPvUTauSIaz3gR+/rvMHbuhOB2kznhSfD5CBkzmvKSEgK6dcPYuTNpAwaSOeFJEj79BLnJhNxoQFO9BiEjxHsa8tgYUMgxduuKMiJCLAqoVRN5YAC+8nK8JcVEPvccMrUa1w2xxZPr5k2KP/kUb34+xo4diXhuKjKZDG1UBK00LmwuH9HBGsxff0PJihVEzpyJsb2oIxYyYjh+SzkB9/f4zee5xOohJU/0ACaGazFo7/GvsLwLEJQI2sBf335xPQTGQsK/2VOz90LxS0JC4i+HZIj9RSnbuFEUNo2NAUHAb7Nj+eEHBK9HNMwaNKDqt9+gjIzAcfIURUuXEvPGG0TOnIGxQ3sK5r+HJysLwe2hfMdOggYMwHboEKrERDy5uRjaions5T/8QOH7CwkePryytZFMoyGw1wPYj59AXaUq+AVM/fpi+eFHrDt/wAqEjB5F2YaN+Gw21HGxlH33HeUbN1Lz7Bms+w/gycoSKzt9PgSfD3lAAI6z53CcnYonPYPoN99AERyM+auvcF29Qun3Gyh4+23USUlU27YVVWwMWU9PwpuXh751K+xHjmLb+1Pl9dHWro0yLEzULbt2DUCUttDpcF66BIJAYK9eyDQazBVewph5c/FZreTPfg2USqqs/Y7iT5eB14vr6lXKNm+h6P330SQnk7RpI9oG9UEmw2c247fbCRo8CJ/VQtGiReIiFApCRo0i8MEHcaem4cnMxNCuPZ7sHCz7fsJ5VVyX4HLjrwg/KiMiyJ48BVVEBIrQEJwXLhLYtw/KVm1xxFcHhw9veDTW3XuwHzpM6JMToOL6BQ97hIgpU0Clwn7smKgN5/OhjIgg+dBBsTpzxQoKlUrilyzG2LYt5q9Wk//qLMKnTCHsiccBSNqwgRtdu1Hy2XLUcXEEDx1K9OuvY7u/B8aOHVBFR2Pd+xMRzz+HPCCA7Oeex9ihPVF9+tx+PrdsFsOaP/5YaYipoqOJfv31v/tcBxtVJIRrUSnkv+pV8wsCxeUego0qlArZ7/vQ/DPknhNDj8ZwMSl/wwSIaw5jd929741dsHa0mC82PRXUv9BGyzkLHgcktr7zPVknYecLYi5YkxH/+fVLSEj8v0OqmvwTI3g85Lz4Irkvv3xbcLWCnJdexrxqFQq9gYQvvsDvcpH/5puikQEoQ0IACBowEGVEBK7rN/Dk5iJTqbDs2YPCFEhAjx6g0ZA9ZQrlO3aQuGol1j17sB8+TPkWUYS1bJP4B9W2fz/Vd++i2q4fUYaGojAa8BUXY9u3D/x+TA8+SMB93SslJRRBwWLFIlC+bTsoFAgeD84rV5AHBFS2J9K3bo0qMhK/xYJMLyr4Fy5aRNmWrcj1eqLeeB2QUfD22+K8AQHYz5whbdBgvEVFoNFgP3IURUgIARWNrJHJUNeoQdFnn4lGmFxO+PPP48nNI2vi02LlG6CMjKo0wmR6negpEwQUISEY27UTPT116wDgt1pFRX2FAlViIllPP03Z2nXITSbw+8l78y0yRj5a2Rw8sE8fQkaOpOSLL8h47DGi336LyFdfRW7QYz97FtweFCYTsR8sInTsY/gt5eI6dDrwevHb7QTcfz+q2FiUYeHUWDSfVjWDaF7dRJBeiUytRmbQ4y8rA0DXpDG+0lKutWzFre73kTFqNNo6dUjashl1fDwypRJ1gli4oQwNJe+117AdPYpMI1Y+yrS3853kOh0B7dujCAtDWbcBKXl2nLoAjO3bkdK7D+ZVXxH34RI01atT9v0GyrdsIX/evDuez6iXXiJ07GOEPTmhcszvdlP06adYDx76zWdeIZfRqGogDaoEIJPdbWhdzrRy8IqZ07fKfnOO38LnF7A6vb+ywQs/vgLfT4CPO8CnnSsuhPLO739LSFXQh0F0Q1D+IsHekgfLusHnPUWP2i85/62YlH/i09+9fgkJiX+Pr776ii5dulC/fn0GDRrE+V/kFP+RSB6xPzHO69cpW7cegODhw9HWrAmAz2IRjRenE0O7tqhjYwno2IHyHTtRV6mCIjgYfWuxqXJQ/37kv/46zvPnsfy4C2PnTpVzJq5aiTsnV5yztBTB60URFITPbMadkYFl926su3ejio8nYtrzyFQqSteuw3XjBqHjx6Fv2xb7kSN4srPFXLOnnqLks+UIHg+l69cjuFzIjEYEqxXUavD58BYW4S0pQRYQgHWX6GWImSfmk/k9btzXb6Br2oS8V18V87J+kd9laN9eTMBfvBhUKlQREUS8MJPspyehjIok5u23KIqLRVOjBsVLP6Z09RqUMTFEzphO4H33kTpoMK6LF1FVqUJgt66oE+IJnzoV56WLWH4U12I7dozY9xdQ8tly8ufOpeTzLyqEavsTNuEJwh4fj+tWCmkDBwIQMWMG6rhYsp6eBEDA/fdjaNkCRUgI/nILJStWoIqJIffFFyn7fgMyrZaA+++nfONGfGYzqpgYfBYLyuhoElauwHnpEgXvzMHQuROe9HRkajUln32GTC4neuqz4oMRVpWgAQ/hvHadoIcfRl2tOsqwMNHD6XDgLSqivHknMgY9ht4URZjdTuEHi9HWqUPyieMUfbSUkuXLsZ84QdV163A/PQn8Pm717IW+WTNCRj2K3Ggk4bPPuKmL5kaahWCjijaBVryFhQCiARgcTOCDD+K4cAFjhw53PLvaWrXQ1qp1x1j55i0Uzn8PmUZDrXNnf/WZTy90cPpWOdWidDSocnc4UK0Q/7dUKX///5jHr5eSV+qmUdUAqkbqf3HQg3CoIiwok9/2bDUYDDGNxdDjrxFaDZ65dHeVo9oAhjBwWUD1Cy+Zywo5p8X5ur76u9cvIfFXwecXOJ5aQoHFSUSAlhZVQ1DI/wAP9y/Ytm0bb7/9NrNnz6Zhw4Z8+eWXPPbYY+zYsYPQ0NA/9NiSIfYnRlu7NqHjxoJMjiY5GRDzjxznL1QaJz8r4Ue98gpRr7xCzgsv4jObsR08ROijjwIQ+crLlH63FufNmwQNHEDEc1PxWazoGjcWBUMRWyT5zGZU8XG4U1MR3C48eXlijlNpKWXr12PZsxd3SgoAzkuXiFuymMJFH4AgEHCfqDUV9dprmNeurcx/MrRrh+3gQfRNGhPx/PMog4PxFRWBz0dg3z5i/lp2Dpbt2yvPO+rFFyjfuAm5yYQgiAru2saNKxPK7YdEDSd1tWqooqKQBwbiunwF26FDREydiq+8HEdFKx9/WRkBnTrhd7tRJybgM5cg12iwnznLtUaNEXw+tPXqgs8nNhDf+QOe9AxcV68iP3sWmVotJvcXl5D78suEjRuHr9SMIjQEX3EJ7vR0XDduiF4+IGzMaLImPo3j3Dl0zZujb9GCsCcnkDFiJCCGHiOnPQ+Cn/JNm8l8/AnUiYk4Tp0i4rmpeAoKxOt77rx4rdVqUChwZ2Vi/vobdI0boUpMxPz1N+DzUbz8c8q+/x7Bbif+00+I+3AJyqgoTtgDsXtVXN93iuIXxovnJ5cT+8EiAnr0wH7qFOq4OKyHDxPQqRPmb77FnZqKt7BQ1CPbuRNPdjahby0gVSEjPFCFOiGBxFWrQPBXirOq42KJX7L4n3qeHTXqQWJVApo2vmM8rcCO3w9JUXosdtFjVW73/eocybEG4sK06NS/3xDz+e/8DsCB9+DAuxDbVPRstX0GDL/4pRxW47cnvL4T1gyFOn1h0Oe3xzUBEJQger7OfgVdXxbHi29AVkUFryn+d69fQuKvwI6LuczefJncMmflWLRJy6u969CjXvQfdtzPP/+cwYMHM6BC03D27Nn89NNPrFu3jvHjx/9hxwXJEPtTI5PLiZg6tfK1r6yMlH79wesldPy4iibPUZXbLbt2oYwIJ+ypJzF27145bnrgAXJnvoDj1CkEp5PYuXN+8Z7dABg7dkQZHo7gcgMg1xvQ1KhRKWdRvOwz5KFiuBO5HOelSxQuXETZ998DYiVi4P33YXrwAewnT+A4ehSZXo88OAhVQgLBw4bhKy4m64kJBA0cgLZ2HcyrV2Pq25fybdvE8zUYUBiNFH74kdhAu6wMfD7CpkymeMmHAGibNMabnSNW7O3fj+Bw4C8tFddgMgGQNuRh3Kmpt9eakkLZ2nWV4VYAVCrweABwZ2YR/dZbuNPSsO7di6lvH4oLC9E1bEj0m2/gun6djEdHAWDdvQe/zUb41Kn4LRY8hQWUf78Bbf36ON9/k4675jHLUUIcVCb9F1XIXch0OjwZGRR9/DEhI0ZgO3AQfbOmWH8SCyEsP/2Et6iY8GefRRERQdm6dQgOB7rGjTCvXFUpxhvQswcx77yN/eQpSr/6SjwfhYLiTz8lsFcvsidPIeT+3mgefxbTl98g+Hwoo6Pxmc1kPzWRmHnzCJ/4FJnjxlO+YwfJRw5j6tcXT0E+cp0OddWquDMzMPXvT2CIlt4hoscn1+zihiaRWnEGfuFP+qc56QrCO/tzGvjzyBg3HlPfvsi73s+ZFFE+JNioona8kSCDirDA326D9Fu5Y26PH6367m0/07KmCYvdR0jAL+ZOOwhuG0Q1gAcX/L4TKroBgg8Kr929LaqBaHRF1L49FtMY7n8H8i+A4j/wq1kQ4ND7IFdBm4n//nwSEn8wOy7mMmHVaYS/Gc8rczJh1Wk+Gt7kDzHG3G43ly5d4vHHH68ck8vltGnThjNnzvzHj/e3SIbYXwifxYI3Px8EAVO/fmiSkiq3+V0usiZPqUzcLlmxkqSNG1DFxCBTqTB264b1xx8p37SJgK5dMX/1FaHjxomeEkAVG0PurFmVHjIEgeynJ+ErK0PbqBEBnTph6t+f9JEj8WRmooyKxHrgQKXSfsny5dgO7Cdp82Zk6oq8I50Oy+YtAJSs+gplWCjewkIcV66gCAzEdf065jWrUUREAGBs0wbLjz/iLSwk9OmJlCz9GHlAAL6SEgSPB0VwMIlffEHx0qUUffgRitBQDJ07Yz9xAhRyFBERmL/9VvTkgdhY3GQi47Gx+IuLxUrO0lLxD5jHQ9DwRyhd9RV+s5mALp0pWb0ad1YWrpu3xPy3gwcp/fprDB07EjZxIqhUmFetApcLQ+vWqGJjcF27hvvmLYKHDmWvvQizvYxvG4WxaM5CnOfO47h4UewNCmiqV8N54SLIZGjr1iX5yGExBLxjJwCOy1fAbsd25Aj2I0fQNWmC8+JFnFeugEIh6ph5PHiLitHWrUvg/feLlaSlZpSmIOzHT+B3OBE8Hsr3b+OJBuWsfnwYMe1aENS/P5mPP4Hj3DlUsbGoYmNQV68mPh86HXKVCvvRY6L8xrPPYOrVC5n6TmMoNd9OscVDWr6DCNPdGlq5JU6yil3UiTf8arVjQpiWwnI3qk1bsB04gLeggMRevYg0qfEJAkadAoVcRlzY7xc0PXZNDDs2r276zferFHJCAv7Gk9Z7oSjSGlkPLm0QvVu/kpsGwNk1oler43RRQ6zlE2CKg9gmd+/7wLvQ4527DS6vQ/SS5ZyFJ/9Ndf6cM7Brlvhzje4QXvPfm09C4g/E5xeYvfnyXUYYgIDYvW325st0rxP1Hw9Tms1mfD7fXSHI0NBQUiqiPH8kkiH2J8eTX4B1z24Ce/ZEHRdH4qqVWHbvwbx6DRHPTEFuEHNQZGo1yqgofOXlCE4ngs+H324HoHz7dtSxMRg6dkSdkEDZ5k3Yjx9HptOhrVWLiGnPozAFkfvii+JBlUqKly0j4P77sO0/gPPsWYIHDsBxTtTMwu8Hv4CvqIjgoQ+jCA6h4J13UCUkAhAxdSqKwEB8dgdl336LKj5e9A5VJMlrq1cnZPRobIcO47x8GW3degTNnoW6ShWsBw+ibdCAoL790NWshaF1K1w3b2JesRKf2Uz51q0gr/B6+P0EdutK4XvvgdeL88IFCua9i+BwENCzJ5bt2/H8fCGVSlRVquA7cwZFWBgB3boSOnYs9oOHUAQFkT7mMbEHpcOB4HGjiotDplRSuHARll27ifvwQ1w3rlNUkSPlun6NtCFD0NWrR9XvvgWgj99P6Mr1hH+7n8Ls+ehbtaJs7Vq0DRsS/9kyMfRXYsb85QoElwvLDz8S0LUrxi6dse7Zi65OHYzt2+POEntG+qzW2w+CzwcKBeHTnqdw7jzSBg0mYcWXOK9cQRUdTdiTEzCv+oqQ8eOwF+Tz3I0NeHxeUl96AU25H1OfPoQ9/TSla79DEWQSr3ut2niys7neshWJX35ZqZTvycml9OuvQamk1tkzyCr6htaOM6JR2ake/ev+sEuZViwOH1q1nPqJYqjW4/Mjl8lQyGU0rCrmfLmDhlNYVkpe407cOl9M61pBGP9NmQqXR4w3urz+f7Dn3xAUD83HwTsJ4LbAoC+hbj9xW8EVuLYdmo4Sk/E3TAAEiKoPdfuLRlZsUyjPEUORP+N1iQKtbhsM/fpO6Yuo+qBQQ2xFeNacDp/3Et8/aosYKj3xKfRdIhpXf4/wWlCzFyhUEFz1zm22Iji2VNz+a4aihMR/meOpJXeEI/8WAcgtc3I8tYTW1f7YnK3/NpIh9icnb9YsrHv34rh0iZg33kDXoAHpjwwHQUBbry5B/foBULZ+Pd4KjbCI55/H0LoVmurVsZ85KzaF9vsJmzwZ++HDaBs1JLD3g6hi4yheuhSZWk3ohCeQBwVhaNcO+9GjCB4P+iZNKpPY3dnZ2L77DsHtxtipI2ETn8Z2+DDBw4ZRuGABgtst5plZLGRPnoLt8GEUJhPhU6fiunEdb1ERfpsNwW4HmZziT5chVPxvZDt6FMsPPxA0eBCCw4EnPZ20wYPxlZQQOmECjgvn0bdsCQoFuTNfQNeiBcjl+MxmHBcuEL90Ke6UFJThEZUq+UGDBmFo0Vz0ct24KVYwfv45KBToGtQnZNQosh5/An3z5mhq1yL/tdeR6XREvvwSCFC+aTPIZChjYtC3aM6t++4DjQZjp07IdDrcGRkVxQeF2I4fp+jDjwgdM5r6tZuQxxZct25iOyRWB8oATdWqZD42tvK++srK8ZWUYDt0iMB+fbHu2YtMoSDs8fHkvfGGuE9xEZ5gE8UNkmk5fjJyo2jcFOlE7TLrgQNi66TcXPRNm2Js1w53RgbmyVN4t6QE7/DBKFP241MoEJxOChcuxHHqFDKVCuf5C7hu3ECm0SC4XLjTUol9bz4+80v4nS6xH2atmpVGGIihwyaGQI7fKMPp8dMqOQiN6raHqWasgcwiJ4nhYmsjm9PLngslqBQyujUMRVmRaK9OTCR67lxOnChAcPootXp/0xATBOHO6skD8+HEZ9BnEVQXOyx4vH4igjRUidCTGPELb1jxLcg+BXUfutsz5bbDwQViuLBWL4iqT5FThdpYg0qzaeNT4vvtxXD/m9BsjBiGTBSlXfD74ZNOYC+CYd9BspgnSXkO3PhB/LnwGsQ3v33cGt3hpYLbXrfiG1CeBdZ80XC7vl38OeWnf2yIqfUwdM2vbzv0Phz+AK7vgCcO/v15JCT+CxRYftsI+1f2+z0EBwejUCgorohO/ExxcTFhFf+A/pFIhtifHH3TJtgOH0Zf0eRbplSib9kSb1ERxnbtcJw7h/3UafRt24jSB4JAwbx5hE+ZjOPCRfJefVVs1h0fj6+kGPuJEzguXgSvl+jXX0dbvz66Ro0wf7Uaf2kpli1biJgxneBBg8iZNQu8XrT16xP+5JPomzajeJkoP+DKzkauUKKrXw91zWQM7dsTOvYxCubPx3ZYDLnIIyLInz0bgJgF7xHQqTOOc+dQBAeT2revOP7efArfX4i/rAz7qdOEjB2LoXVrsieJVYjFH30knrdeT+SM6dgPH8adlipqgimVBHbvjqegEHWVKihDQ9DUro3ryhXy58yhyqqVGDt3pvTbb0XJCEEAnw/r3p+Qa3W4rl3DlZJC8owjeAsL0davjzoqCueNmwCo4uKo/uMPWPbvp2TlKuReL9Fvv0XO9OkUL/0YY9eueHJzyX9nDq7Ll/Hm5+PJyiJ86rPYDh/Bm5dPYN++hE2YgM9iFUVsQ0KIeedtVNHR5IeGYD98GE+mWHhhP3WKnBdfRB4UBIDfYuXD+eP5KesiL+jKGFmzKQDJBw9w68HeFL2/EH27tnhz83BeuYq+SWMc587hq/DaBWTlk7VsAY1DE1CGiz0rzQoFQQMH4mnVmrJNmwgaPAi8XgLuvx+ZXF7pFUvauOFXn0eXx09OiRi+LrN77ghRxofpiA8TjbDcEicWhw+vT8DvF/D5wZd6E+eVqwT26olcoaB1zSCsDh8xoXeHOb0+P3sulODzCXSuH3I79+vqVijPhlt7Kw2x6zk2rufYMemVVIn8RX/LrwZByS3RkGo14c4DXPgO9s8VPV0v5VM8aCMHLplR5EPPWL9YlVmzp2hUJVXIWdR6AM6sEqUu+i8VjSlDGDjLQBcE++bBmRWiN6vvEtGw+qUR9jO/NCyrd4OHPoWAaNFz1vdD0RgTBPjiQXjgPQhP/tV78Zv4fVBwVazYrN3nH+8vIfFfICLgn0s5+Gf3+z2o1Wrq1q3LkSNH6NZN/L3h9/s5cuQIw4cP/48f72+RDLE/OaFjxxI69rYnxXHuHPaKikS/1UrWpMl48/OJmDGdWmdOkz1tGuWbNuPJya1s5qxJSiJuyRLRI+V0YdmzB19xMZb9+wmf9DSCz4e+aRPy35mDNy8P+4kTeIuLsWzZiqZuXULHjcN18yaC20XgAw9gP3oMT4WxUrjkQxwnTwJiL0TL9u0oQkIIfngIythY8l58CQBviZnC9xcQNnEi7vR0kMuRGwwEdOmCsU0bUoc8jPvmTVwxMSCjsgUSIIYVo6MJGjAAy+7d2Pbtx7r/AMrQUAreW4B5zRoEQSD0sTEYu3XDdeUK7mvXuNn9PnGeiqT88GefofS7tXgyM7Hu3w+ANjkZ+9GjlG/bhv3YMRynz6BrJraZkWs1FH+2nIJ58zB07IgyNBTrnj0oKjxT9mPH8FutqOLjMHTujPPCBQSPB/fNm0RMfZaC9xZQvnEj9qNH0TVujCcjA03VqmiqVMFbVITzwkXcKam409JFId30dMrWrSdk9Gj0zZuja9yYfos30s1ejrN+b3ylpfidTlRRUagTEvAWFeGpaOdUvmM7+iaNCezRA3dGBt7CQpY0CmLtte8ZV/8+hk7/gvIffiD+o4/QN24MjRuT2bo+qPXEB4RRMGcuPrOZqNmzkGt/+xehVq2gabVAXB4/4YFqrE4v51ItRAapqR4thsmtTi9Hr4s6X82qBWIyqNCo5Nx4bCze/Hz8djvBQwYTGaQhMujXj+P2CticYv6i65dJ+H0Ww7Wt0Oyxyn3DA9VkFDqJDv4bgy6mEZRl3Zkw/zNhNSEkqdKYUyvlKBUy0cMnq/DEdXgeOjx/+z35l8DnguzT4muZDMbvEw0uQyhseRZKM+Dmbug++9dP7OxqMKeJ8yoqcvAaDL69PaKW+LWgHpRlwqXvodP0iotih92zIbQ6tBj36/ODaDze/FH8OaHVb+8nIfFfpEXVEKJNWvLKnL+aJyYDokyilMUfwejRo5k+fTr16tWjQYMGfPnllzgcDh566KE/5Hi/RDLE/mJoqlfH0KYNMq0Wr9WKvlkz7KdPo2/alLKNG9HWqYuxS1f85WXoW7Sgyvp1ZIwbz41OnYic9jwRU59FGRlJ0eLFWHbtEmUjBIGkzZtI2rSR/LffESshf9oHgoDr0iVypk5FUCjA6STuow9RV6mCOy0NTf16lS2TZAYDjorqE02NGoRPmkRKRZmwoWMHCufPR7Db8dlsaKpXB78fweXCefkypd+tJaBLF8xrVouVkBUFA8rYWEIfG0P+a6/jTk/HnZmJ/egxkMvRJFWlbMNGqFD6x+2m+KOlaBs0QF2tGt78fAS3GzweDB06oDAaCB48GMEvULxkCQgCyogInJcukf/OO3gys/CZSwFQBAaiqVWLwN698btEN7mvqAjbvn2Uff89Nc+cxmsuwX7kKMqYGKJff53yrVuxFRWhiosj4P77yZ83D8ex4yCTITcaxarEjAxMFR/6/LfewnnuHASZOBSpIj4ogNqxbbAdPoz522+pdeokrpRUEj/5BIBEIrn1wIP4y8vZ8cpYjg2ozfy5rxOUXYh5zRq8xcU4Ll5CV68u4U89BYD80FdgvoZBpcV+9gyCw0H51i1oalTnoq+Mh7fOw6DSsrvDJEq++AIAU7++GFr/jRo8cOx6KYXlbtrWCiYh/LbXKafYRUGZmzK7t9IQ06rkaFVyXB4/Xr9AoF78NaStVw9bWRmaGtX/4XOu1yhoXycYn1/AZPhF0UBkHfHL5xET1Y1RRLR6gp5Nw++eZOByMXwol0PaITiyGNpOFo2T7c9BSYrYvggI0Cnp2SQcu8vLztNF6DQKOtcPQf5L71WrCaAOgAvfwnejRE+WSit+bXlWbNjd6klo8ihsfU7sH1nrgdvvd5ZV5JkhSmX8ctvf0nOOGN5sOur22PUdYt4XQKNhcGiR2AmgzwdiJwCAzBOQfRK6vybqmP0cRpWQuMco5DJe7V2HCatOI4M7jLGfP2Wv9q7zh+mJ9erVi5KSEhYtWkRhYSG1a9dm2bJlUmhS4vcjNxhIWP4Zrlu3SOnTF5lSSfVdP+J3uciZPgMQVd3LN21CU7s2cR9+iFBejuDxkPfKq1j37CXqtdlYdu/GZ7Ui8/tBqUAZHo4iMBBj1y6iIebzEfBAL+yHj6AIFasdBcBvsSB4vQTcdx9hk54m9cHeAETOmI5l+3a8+fmoYmNxXLiIXCN6VoztO+C6fAW/UknZ2nWgVKKuUR33jZvkz5mD89x55EYj2saNcRw9BkDQ8OEE3tcdffPm4Bco375d9HzJZOD34y0xEzRkCMrwcMxr1iCPjMSbn4/z/HlkajVVt26heOlSytatx3nhAslHDouNq5d+jCo2Fk9WFrrGjfGZzRi6dgWHg8DefVAY9JRt3oJ1zx5KiopI2rIZY5s2KEJDyRz/OD6zGefFiwQ99BD2o8fw22zoGjUSDaFz51GEhZL15FPomjZFFR9P6OPjKduwkYK580j44nNUEREIbjeqKlWQ6XT89Hg/3iedcLWR3R0nk/viS+hbtgBAk1SV6DffRPB40NSqheDxIPj9/JhyklsRBk5YcujbpCUlK1di2b4Dv8VCyKOPUrjgfUJGj+LVnkMZ1+A+4gPCcX2YTOEHH4h6ctevo584juWLD3O+bhy6h+MImzgRn9mMvmnTymct31bKyO3vEWEIYlDYUHw+OWV2L8FG0TASBAHN2zNIvpFK4ILFgGgMKBVygoxK8sxuii0eqkaK84U98QTu1NQKXbl/nEAeFqi+/cKSBzd+FKsatYGQsk/M8QIxcT4g8jc+MBU5bIcXiYaMTC4aYiHVRA9XcJXKXZUKGS63F49PwOfw4PMLyH/ZRqk8BzKPQEZFtWO3Wbfff2aV6C1rOxmubBQT7i9vFI0tv19sa+SyQKNHRK9Z/N/pTeksF0Onpvg7zyupk5h8H1pdDKnumwMIsKQ59PtIDKWueVjMWev1rriW3HNiIYAu+NePZSsSiwtMvyJa6ygVvX5a02+vVULid9CjXjQfDW9yl45Y1H9BRwxg+PDh/5VQ5N8itTj6E+MrLa1stvzLMdvhw8g0GuRaLXKjUayYjIjA0K4dusaNReNFJsN15Qqla9aQ8PlyjJ07AaBOTEAVEYE3Lw9vZiYBPXpQfedOFBV5SYHduhExbRr6Vq2IfP55ahw+hKF9O/xlZQh+P86bN/FkZeG4ILaGMA0cQMD992Hq25fYBQsIm/gUZevXk/HYYyiCgtDWrUvRxx/jLSzEb7WiCA9Hm5xMyOjRaOvXJ2jQYDFh3OMRG40LAvbjxylds4bsZ57Fm58v9qE8dQrzlysIq9CBcZ4/T/TsWWiSquIrLsaTm0v4lCliKyW3m7S+/Shbtx5VQjxBAweKbZPWrReLHOrWIWjow7hu3MDQrh1yZJR+8y1FH3yAIiiIkEdHooqLw1dUREqvB3Bcviy2CdJq8ZWWYtm1C3d6BshkyFQqBL+fvFmzcV2/jtxgBEBepz5Fi78lr15D7KdO4U5JqRTDzZkxg+IPPyJ80iSat+xKiEpPu4T6YlXsl18Q/uSTlfdb17AByrBQ5AY9SZs3U3XTJl62RrLwtIv7Y+sDEDRwILrGjQkeMoSyjRtxXrxI2bp1KORy4gNE40hTrRqGbl0RZDJsISZCr2cQbHPTNduJWq5AUzOZkFGPVkqPAFwpyiHdUsjp/FtUi1WRHKMnIVyL3+Wi/Mcf8ebnY9+7F3n6LYJyxFD1vsyLdPrmBa44z1En3kjdBGPlfLZDB3GnpFC2cdM/fvh/eFkMz2WIhjkbJ8KmiWJoThBAHww1ekDT0WCM+MfztZkkGjEuC7zfADrNhBmZUPvBO3YLT99I61Pj6XB8JCrF3/z63PM6nP9GNIR6vXuHEceQldD5Rag/CGo9KHqimo+FjKNQfBOOfQRnV4k9JkdtEXPLfov0Q2JI8vAisJfcHteHiMn5970uVg4/uACMkeAww82KXpg1e4rK/XHN4cJasWXTF3eeIxfWwo6ZUJoJHzSFRY2h6Oad+1jyYGEDWNgQrIX/+PpKSPyT9KgXzcHpXVgzrhULH27EmnGtODi9yx9uhN1LJI/Yn5jUwUPwZGQQt/QjAjp1AiBz4kQcJ08R8fxzVN+7B+eVK5Rv30HQgIcI7HE/rhs3RVHVM6cpX/89MpWK4uWfY937E0GDBhI5cybeoiJ8ZjMA9lMnMX/9NcEPP1x5XPuxY9iPHqVoyRJCx47FV1zxx8DjIXjgQDwZmVh27CD94aEIfj+C203B3HmYV63C2LULMr0ef3k51j177jifiOefI2TECCw//ICmZk08GRn4iooqQ5H2EycxdOiA4PGITaudTm5264a2Vm2ChgwRW/f8sJOQMWNABvYzZzB264ahYwfcaekUvP02qoQEPDk5CBVSGYG9HiB07GNcbyYmTZsGPCSK2Pp8+K1WrIWFmB7qX3ne2c9Opcqa1QQNHkzhe+/hKymhZMVKQoYNI3r2LCw/7kIRHk7BW28hDwgg8atVosZZQjw5Rdm0fHw8EZMncWn3CYqup3ElVMWuAfVo4wtkWFo6muRk/BWiub7SUozDn+Azl4ukDU/gzsrCsnMnpv79UYaEIAgCaY8Mx19WRuyC9wjs2RPBYcf03RZMgP/yFWjaFGPbtjjOnsXyw48Yho/EioagYYP5W/Ykh/L2022QBxo4OnAYMpUSXdOmlH63lrxXX0UVH0/1H8Vqv8wiB+bcUB6rNpCmCRHczPThF+zEh+mwvz8f84qVGLt2JWrxYm449RTVq0sAcDD7Mnl2Mz9knmBMw053HD/4kUcQrKUYwi1QnguBf+cX75XNYo7U7tkwcqMowXBrD0Q3gt2vwcH3oMXj0Gvu3/0MVVKlLSS2gTejRS2vnDNiLhaIIcPP7he9ZQ/MJ8py9k6P1ebJUHgdGj4sVlG2nyqGBkE0gpQ6SL5f/AJRjX/0Nlg9BH56SzTQ2j0r5pLF/Ury/t+S1FmU1AiKF42v36LZaPGcvn1UDGMW34LOL4gJ+lENRM8biHIZLivknYf4VrDhSdF7FxgLgv/21y/xOsWcNJlM/FlC4j+IQi77y0lU/D0kQ+xPimXXLgSPR/S6/KL0XhkiPryKkFAUgYFkT5qMr6wMwe8j//U3KmQt6hHz2muEjR6Nunp1ChctwrpnD97iYvxuN4rQUIJHjMB+4gTOs+fIv3adoMGDyZkxA09ODvrmzbEdO4YyMpLsqVNxXryEoUMHQh4ZhjohgdBxY7Hu3YsyIgJfSQl+nw9Ptlj5Z92zV8y/SkhAJpOhiozEfvw4yogIQkePpmTlKvLffBNFeHhldZ9pwABsRw5j7NCevJdfAcT+k96iYgrmzMGbn4/D7cadlobgduOKiMS2bx8lX64Qw4zp6ZXXJ/DBB7CfPIU7IwOfwwEyUBiNhE99Fk9GBsHDh4u5ZYh5bYLNhjIqitAnHqd46cd4i4sR/H7Cxo9DU7sWWeMfF8/R6UTXoAG6Bg04e3wf7wxrwv12PQwcBHI5n70xmk1ZZ3leyKHvrhR07y8kMbEaqgXvUNS4Nk1/SCdv1izsx48T++48XDdukBGio3zjWowFTvLnvYvgdmM/ehTbsePEzn+XCUe+pFegnGSXBlWc2BJHlZBAyKhROK9fq2yw7rNYKPpAbDOUU7sVmQ9NxGLU0thioWD+fLT16rG/UTxymYwQvYnp35wn++AzxC1aiEytxl9eDkol1oh4yh1eAnVKPF7RkG0e0pi2cUHsKinG5xNQKWSo40XNLHV8PJZ6Lcm+VU52mpVv03cQoTcxpUkfuiY05HxaOVanj6bVTGhUchQBAYRXuQEX18KWGxBURZSOSOp09wfgwfdhZV/RO3Rzt2hgdJopGgY7Zor7eOy/70Mlk8GAZXDw/UpNO0A0CguviD8bwmDG7ecJjwNOfQkI0HI8TKpQ4S6+JeZibXxaNJieOn5b3w4g9/xtA0YTAAmt4eoWMWzoc4uVnDF3tnqqRKWFnnPFXLTUg1C13a/v53WLIcqSW+KcOWdg/7viufR6V0zon3QGjFGwdrQYmu38ErR5Wmy/VKcv1HtIXGdI0p1zB1cRZS9kMvH8foklD74ZIfba7PfRbwvgSkhIAJIh9qfEdvgwWROfFnOd1q9DW1us+vLk51caSAEVLYwMbdtiO34cfaNGhIwahevGDTQ1k0kbPARlTDRxixYRPmkSJcs+w7pnL7kvv4Kubl2iXnyBrKlT8eTkEDJyJN68PFE7i9uVmkWLF6OuloRMryf44YcxduwIgFynR3C7caenU+XrNci0WgS3G8HjwZWRgeBwIgN8hYWEPvYY9tOn0dSqie3oMZzXroJMJvbOTErCefEi5Zs3U+W7b1HFxVH69TfIdDqKln2GJyWFyJdfQp2QQOY4sReYpk5tQseMxnn5Mr7CQjzp6Wjr10NTvQa6Jo0RnE4cx48DoIqPw3X9OrmvziLqlZcr+3ImfPE52U9Pwm+3o2/ThqB+/XBdF0PAnsxM/DYbioAAlMEhYjGAQgGCgO3oUQo/WMyG/o05Gx+I3RhBq63HkAEOj+jVs3lc4rnJZCjTb9Fo8za2jHwCc8Y3FB8+ja5RQ1w3b3HO4Gf0jwuoPagRb36wG9v+/QR064ZMp8O2fz/ZU57hTJdA9g9tgMoPI5zXmEY9Cpzl6Jo2oeSLL8g4e47k48ewnxCrVhUhIZg6tCO3yE9YoIry7Vu4vm0jYd+tZfpz7dEoVByoP5Lsd7ZhvZGFp6CAA75iopPjyFi2HYegRFfixBOoJkCnpH2dYAL1SlRKOfc1CuNyUSYfXtjE8AEPktyvL4qAAJxuH5FBasyeEj4/KYbHjg17F71Cx5ZrhZjKL+M//jG0Hgs1ukHV9mKul88Lxz+GW7th7G74ehhog2Dwl2I1YVJHMVG9NBMSKrxTP//B7/66mBcW3ejOD86GJ0V1/GFfQ9VfNCHPvywaE5oAMKdC9glRv6txhVcrohZ0nSXKYvytQaLUigr6fg/UrEiud1ng446iACyIul/L7wN9OAxZBc5SWNZVNI4e/koMVS5pCYVXRWPtzCrRCzd6u+jR8nng60fAVgiPrBUrMM+tgY0VIepHN995Pj+z5mHx+rWfKhpbdfrB+W+h6LroDftqsBjGVOvFcwfxe8fn756r8JrohWw6+navzZ89hn9L1gnIOi5+7/UuaCrCzxfXQfph6PLSb+ekSUj8DyIZYn8yzN98S8ny5ciNRtQJCWhqiE2HHWfPUrZ5C/7ycvx2O367DYXRQOx78yvfq61TBwDr/v04L1+GK1fwl5ejCArC1L8/9pMnKd+4kfKNG1GEhIitdXw+vMXF3OzaDV3zZhjbtsNx8SLlFa2JtHXqUm2r2KMx7823cF2/TsiYMWKTa7WKnBdfxH0rBX3TptiPi1WCKJViUr/TifPyJUz9+oJcQcaoUeJ2QcCTnU3ktOfJmT4Dwe3GX14u5jdduoQ8JASZICB4PNgOHkTRowemgQMoW7sO19Vr6Fu0oMae3ZTv/AFPbi76ZmLFaN7Lr6Br0QKZ0YhgtYrSDhUaXQB+SzlRs2ahqV4dX4WsRUD37qjj4sTzUSpFhf4rVzC0aIGuXl0SPv0UmVaDXKej9NvvcJw6RYKvkNajejG6XleSNozEk5vLxE8/oX/bRnRq/ABymRzl0ME4v/4WuclESp+++G02qq5bi/PyZdIGDaKwYxNkrU2YwwNRNqiP88IF3AX5RE6fTt6sWSiCg1nWdChrNy1nl9bOxaIM3j+1kaXnd/CUsTb3GcReoDKlEr9NVOCXBwUx7eInOL0evmowlZUxAh9OaEVvZyBhOqgeFE1Ak6ZEvjATucHAYcHMU3uWolOq2dTrLUrKfUSaNOy9KIaiuzYI5UzhTZZd2Mlj9e/j/VObOFuYgs3j5JXWQ8XnQ62gTa1gylxqOufXJ84YhkkjVk82qhqAadcadCnbwWMWDbGmo8Sv3HOiMVJ/IBRcFj1fIBo1pjjxOem98Nc/JAolxLcQw4TfjRINpJ7vQMYR8NjEuX82XM5/C+vHiQr44/aIXqDU/be1wUD0jh14F9xWMXTYcMjtbefWiPldxih4oOKzJleJumF+L/ReJJZ8ra+Qk7AVisUEAVHi+YXVFD1uzcbAua9FY+nKFjHsV3hNNMTsxXBDbHNFwSVx7WHJ8HNtWdoB2PY8tH4Kmoy8vTZnqfg9MBaaV8h5PPieGM69uE40LMNqiGK0/ZaK4crsk78eFt48Wbx+1nzoNe/Xr/vPJPcQja2QJNEI83lE43nzFHCVQ2gNaPXE359DQuJ/CMkQ+5Nh/vpr3OnpmIYMJmb2bS2i7KnP4cnOJmjIEIIGDUIVcTtB2We1IZPLkCmVlG3egq5xIyJnzkAZFY3f5cK6cSORL8wEuZyUB3uLjaeXfUrcwvdx3rghqt0LAvgFwp54nKv1G4hhUUCmViEIAs5LlzGvXAmA4/RpUChQx0Tjuio2PNbWq4e3sBB3djYyjYb4jz7Eb7GQNUH8r15ZoWmma94c961beNLSKPlqNTHz5pL9zLMUfrCYkMfGINNoUCckEPvuPMyr11CyfDnWffuRqVQoQkIInzwZv8VCSp++osp/+/YUzp+POlkUvXScOlXp+Qrs0wdBBpbdeyj95hsA5IEmIqZMRpucjPPSJYoWf0DZ2rXELf0IdVwc3uLiymvryc8nc8IEBL+fatu2EjbhCS5dPom21EKcR87nF3dzICiaJ65Z8R87QXipE98YuGhOY3hiMVVeH8yGHsMxr1qFzOVCplYjq6gkbWBXMLx2Z8xOC0/19VPYPYQvwzqQ1H8Ixk5iA3b/pMkM272bB9q3oMpjo1h8RjSOl1ivUO3rJXSq0ggAU+/eWMODyQxUceXYlwgI5NrMWJSiB0letzYHO4wCxGT6srY16VOtJXGluRhVWqqYIokJ1nKs+CilJUHo1RF43W5cu39ghT6DA9mXUcmV9K7WnHK3nWhDCIM3z2FMvW70qCpWWZo0Bj7qdrvIAKBqpB7ajIDcn+6uyotuCI98B3kXxLyl+98SPWKmuH/ug+LzivINpRmiJ6fnO2I7ocxj0OAX+Y5uP3rA45ehArGC0BQPZ1ZCjfsgrLpo9FXtKBopUfXuPE5IkugVC6txe8xjF8OCGiNU7wL6UNGY0ofeNnCePi0aal/2hqyTMOwbGL9X3DZuL7xfH7ZMgeBEqNZFzHcrvAIxFdWk8c3hmUtipebpL0Vv2rlvbhtiXhcExoEuRJTL+JlTX4rGpyFc7CjQbIw4rlDCoYViaDSyLrR75s7zrNlT1Der1uW3r3nB1Yrrob6tr7ZjJhz9SBS4bTsJUg+Ic/0tKT+BIUKUHpGQ+B9DMsT+RDivXcd17RoytZqQvymxDehxP5YffiRowEPo6tWtHPfk55PSuw8ytZrgIUMoWrIEdbVqVNsq/tFOHzES+4kTBJ08he3IEZThYWIj7xo18JrNOM6exXbgIKFPPE5gjx6AmFRt2fcTntQ0XFevkTXxaay7d6Nt3Bi/2Yw7M1P0ellF0dXAvn3A5yNuyRLShgxBcDpRhoaiadZM9MSdOoknQ+yfGP3mG2RPmoSvuBi5Wo1l9x4EhwPnpUu4rl8XtcXOncNx6hS+khKUsTF4s3MQXC4EjQZ19Wrc6tWrsoBA8ItJxro6tXGnpyOTyRCcToxduxL62GOkPvRQZWNzRVgYpV9/jeBwcHTUA5g3+6hyJZOqly6ROXYc7owMNDWTOX/0KmXlATQKFpBpNMh8PmQqFer4eOLyyoh3ujBeyuW7SDNHcq8SVrML7afM5Gaj+8m/VIIixILb7yXbUYpbo6ba1i34XS4+yj7Gd9ZDvLR8PnVuFZD99VfsbhCNWq7ErZThqFeLoo8/IaC7KDLqOHsWAFlyNU7m32Ri4wfZmXYai8fJ/LObmXFkFSt7/h97fxne1qFt+8M/kS1bMjNj2GFmZmigadMG2pQh2WXGlBnSNuW0adokDTMzM5uZmWRLFuv9MO042e05597/e3ru7j6Zz6PHtrS0SLLW0Bhjjvkkib5hTM/ZSKO1iRf63Eqwpw8dA6Jo4xfOyJiudAuSOYRVTQYe3rcEp8tFuM6fXqFtOHXnx6iUSg4VXuXlY7+iVig5fssiioZNpMpiYe7it9HE9uDuTiPxJZTA2E5sLtvE5ao8VmccZVxcT44Wp3ChIod7k0bjqZFQVbPdikqpQtNYLizL1XXiJ1JfF7q6cpYAp7HvCNvTUk21sPUJCO4IQ5/983+WSyshZaMY5Wf+LAb+koswdQlsf1oS+O9YSYrveOoGbccjKJqBRz4RwHRxJdhNcHmVSGg974Y7Vvz5doI7gLu3rLuuQICcuR5MzZ2E5nrxlbUk9+9dBI0VMvRb4yGP45JIipby8JX11OVL16PLBWd/FOCWvAF6zJXlfCLk5hUqz+l8XQNG+VWJyQCRWQPaiEyZOFpkww5ThCU7+L7kp035Aka8JH67mEES/xE/tHV9Ax+Tm8Mu8mJEzxtfq6Ofwd7XIOlWuPXHG/cDlzxn8uc3BuC2VO5h+OUW0HjCM1ngpvvzc32zbta/ad0EYn+jUqjEj6TU6dCEhWOvrZUYCG8for/7lpBn/vgh5zSacDY2olCpcIuLQ6HV4tG1K41HjlK3bh3qsDDxObm5YSsqwl5RQduzZ0jv0xfDlq2og4PB6cR85QrV33yLz8xbqV+zFtRqfG6/nfrff4fkZADs5WXYS0oBiPn5Z9wiwrEWFFL6yitYs7MFFLmaJ0i6WudI2ktL8ejZE12/ftSvXo0lNQ2ljw+eAwdS8fbbAPjPn4/PlFuo+vIrXBYLVd99jzU7G/f27bFTgrZrV8LffYea5ctxVFWjCgoi8vPP8OjWjcAH7sdWUYnfnXfiqK+nbt16Ah9+GIVahUKpRKHVNsu5JlAq0SYlscyaia2tFw/quxDafwJVXy8BpxNLahplniFkV+eytuQij6/+maiaJmwlJSjUatzDwmly2bEPH0RM4SnyGyqI/WkdytQitD4x0LETw6M60zUwlktVedy96zNy68v5YPDd7Mm7SGVTPZ8eXcWnS8+wAAhQuDH5lrtxtUsk/PvfWXHlAB0vHGXk4h9wWW00uqu5J7AMx6Gl3NZ2IA02M95unhhtZqwOO5cr86gw1qFWKFEqFPQJiCPk8BksTl/cExJo4xvGohOr6BvWlglxvegWFE+NuYEYb2H9VM05WwarCa1KQ6JvODovH1Tdu3JYWcekxE7McLPjcDkpqbVgsjoZGzqMIL0nt7aVsNCnDi2l3mLE113H3I7DyauvYMaWdwn08GbL+Cdw63WvDKi+/sJedA5q8uR3z+Yoh5V3CODp+5AAkuQNAg6uf15LhXYWNih2kICGpWOk8y9rn3RXmqqg6AyxnbqRau1Agq4WNjQzzCNfA5cDLvwmnjG7WXxWIIDJaW/tVrRbRW5zWKXzEMA/Du7dIyzP/rdg5Ktyn6FUujkBkqZJav/kxTJq6exS6DJTHlOq4KEjss4WUNLvEUnsT7hOMgWRLzN3C8C5Ps8rrDsMflo6IoPai0n/wFsCsuZva10u56Dsf8EJCYntdY/Ed9TlSyDt9an+ALtfFim22xyY+lXr/Q5b80/rjctP/15A8/ll4j8b+/YfXyt9KLjpRUJVuf3x8Zt1s/7N6yYQ+xuVe2IiCXt2o3B3x7BjO4at27CkSDeXvaYGTWgoIEGa9spKNMHBuMfHEbtmNQqNBm3btvhMEkNx3u2zaLp0Cd+ZM2l/+RIoFLglxOMenyDDp61WVH5+hL/3Lk6zBcPOnbJusxmVvz8qPz/qN24EhEkKXLiQ8tdeA8D39tuwl5dhPHQIv3lzUQcF4TKbcW/bBqfdjmef3rjHi+lZN3QIhs1bUAcGEPjQg5S+9joAnj17UvH22yjc3WV2ZnU1hQ8/RPjHH+GorsFeXU3Nzz/jc8stWDp0wGEwYK+upm7lKlAoCHzk4WuhoPbqGgrvvReFhwdtjx1FP3iw3F9bi1tiAgqtB+ZLl7BolCg3rcM/qj1vlGXg+P5hfPNKaKhTEPrii9hra7Hm5KJV1/Jl5XHyjMWolRYefX4pLpOJwIULsObm8vy8HmSlbOHhjqPpYfck5Ic3cdTU0LUpH9vi5eQ2NtDmobFcqsqj3FhLvcXI80eWYXXacVOqKfPxwNk1CVVWLndsv4Kf71lCh07g5y6hLIlsR4BLwyg3NwyfLqU4uxitchdWp4VB/gnkhlYwJKITY2K7U9BQxbOHfqLW0shbA+cwMLwDbqvWU/bRx7jFxZGwYztbcs6wIesE+wouMjWxHzPaDECncSfI88aQzs1ZpzA7bER4BaBSa1jz0AR+TT3IgdQtnK/IRq1QsmXKG/jpdMQGBzLFvTUdf3pif46XpNI/vD2YaqgxN2C0mXE4HVjU7rhN+uSPb/ZTX4OxXGIiut4uoaeZe8FplYyw7nOFjbIaBcS0nygsUkuFd4PncuHyGkjdLKOPyi6LByw0CQpPQ/e5BGrcGNzRH+pMIjEqlBKq6hUCxmpIXg/RA2SdTbXwRS+R/R45LtvTB8GDh6V78npZLbIXrH9AOhZ9o2WkkXcYDHlWGMCY5k5HU7WY+ksuNHc5usl2jn4mMmALKzXmzT//UNjwEJScF5Zt1CLY9YLs34QPpYu08JTsW4v0e70EfOgDCZ9tP0mWbSmvMBn95OEPhz8UoNTCwrUAwxYDfkv1e0S22wImr60rFLzFdnDNs1aeIgPHe80XL19QW2HClJo/Dl+/WTfrf0HdfNf/zaoFbFV+/InkTI0YgX7kiGv3A1R88CE1P/2Ee4cO2EtLifx6Cdo2bWQ+XnNnWcAD91O7ejW+s26n4cABKj/6mIAHH0TXry9Fjz0GTichL7+EboBchHT9+uIzaSKefftizcvHnJZK9c/LsKam4tmrF34zpmNJSwWni5CXXiS9R0+w27FVVMjsS6USS34BmM1Ys7Jx2e3k3XY71oICXCYTDbt20zT3EqGvvoImMkJCPRUKSY1v15a6FStxNjZiSU8n6NFHKVq4EKfBgPHYMYxHjwLg0aULSr0eZ2MjFe9/gDUrG1tpKQEP3I/S0xMXkDFsOLG/LEORmEDtpfNYUqVLc9+47vySqGXQr5/yvGcnOnTqSNOo8dT8shzj8eMYT54AF8SuXo13+zYoP/wRTZCeBJ9Q1gxNxL+8jntGjsRlNtMxpIlceylBG3YSuPEI3nPm4BYfh37QILI/eBeA/nXjefDWN7A67OwruMwXF7Zgczp4pe9t9AptS7sHI2i6eJGKrVvZN7orvWqK6TFgND570ukX0YGihioeyVuKu9oDk7UJFy7Knn6Gz6bPJ2D8WGrMDXQPiiPaOwhjjZlE3zBC3fSUl5YKuO0l3q2ugbF0DIhicnxvLlTk8NIx8fntCYgmylvCXp0uJ/kNlagUSkbHdAOgjZ9cXDsERFJgqMRgM7Hw0Ff8NuEp1mUf4XJVLi/0mYmfVs9zfWSUFYc/hP1v0WPw0ywb9wS+7jq83K4bwt1SJ76SoNOofjC8GSDkHxUQpnITQ3uLF2rLY3DuZ5nROOgJiVtoqdLLsL55DuvC89B9tvwe1lVu11dTjTBfSg3XhquMf09uICGnB98HS72AwqosSbfvNhuC2v35P+vgp2TkUEv8hrlemLjI3hJBAQIgx7wtxnm7WYDY6R/g2GdwdT08cUWWO79cAOe491q7RAHajJY8tbghIkFeG3E0G9K2iO+r03SY+RMYyoTpsjQKkKpIkWU9fOXWUtO/k9R8U5UweiAZaPpgMeF3u1OAY+4R6XIFOPoxHPkYcg/BfXta11VXKFEXt6+AxJHNy34i566hRDLgQGTa68vZnF12E5jdrP8FdfNd/jcpS24uzsZGPDpLWnrQU0/SeOAgprNnMZ08ib5//2tDvO3N+VvW/HwBOXv3UXDvfWjbtCH291UAeI0ciddI+WCs+XkZ1vx8an9fhc+0qcT+upymlBSsxcWY09LQtm+Py2qlbs0aTGfOUr95M/byctybuzA1YWEo1GqZt3jsOCofbxQqFarQEPxunYH56lUsaWnULVtG6KLX8ezZE5fFgiU7G5fFgteYMah8fPDo0gWFmxvmtHRs+fkovb0l+HXPXrRJnTCdPIXpvOQ0+c2Zi9PURMC992AtLMCWX4A1N5eYX5eTP3sO6rAwan/7DZBu0cRjR8no2w9MJhrPnWdeyu8UGipZufABvK+k0/noSWZUBzPldCHVHAalknZnTqPt0oXip58Bq0guzsZGbJu38fEv5zEG+lL964M81sUf8OfWqFA+7x2INyrWvX8Ca1UltTo3dkWpmDF5NG7ueta8fg/VeZnsqjvF9B8u8tKAO3mg71j6h7fnvVNrePPUahYNuJN2/hF4dOvGXlUlH55dT2DOUZ7rM4NTd34EwP6Cy4QUlPHQ7kwM82ZSXlZIj5xqrPkFpNYUMmvLB3i7e7J9+mso7U48Ne5cXv4Dbr+tQKnTEfamMCyvHP+NrLpSOvlHE6D1pmNAFDaHg7HrXmN6m/68NWgudqeDanMDDpcTHzdPAG5vN5hpEe1x2/MKc8LbMz4nnay6Ukoaa3jv9BrsLic9QxK5vd3g1jdxnfgAqS+kb3C8sE9/VueWCbhoP6kVxBSdAaVa2KXrL9oxgwQklV2WLCyvUJEqvcKlk9AzAPzi5P7ry+WCcz+JB6v9RAjrIl6wiyskaf6uzcLkmOtF1ss9DNUZYuAftQj2vCqDs6uzJcF+/1siP/a6RwDK9mfEuF52WcYX3bNLvGdnl4Lyl1aGSaEQf1zJeeksHP2GgJ7UTeLjaqmzS2WZK2tuBGLDX5Sb3SLs4IDHBLRm7JS5lyBdmrYm2N8svcYNlm7UiZ9IR2lL0CzISKOvB4jEeM8uAXj60FZ5WKEQ0LjuXnk9ns4UH52pWv6O7HXjed7ymHjTet4NHZrjPXreLTJt3BDY+aLIy9eParIa4ZtBIgM/ePjPxyvdrJv131xnzpzhxx9/5OrVq1RWVvLVV18xatSo/5Ft3wRif4NyGAzkzrgVl8lE7JrVeHTujLZdOyzZOTiPHgWnE6fZgqO+HpWPD2FvLMLnlikofXywpKSg9PbGZTJhzszEdOkSnl1vZAOCHnuMpnPnMF+6TM1PPxNwz3zqt22j+ptvadi2nfhNGzGePEnDHsmBcouLBcCSkoLf/ffhrK+nbsNGTBcv4jSZMB47jstiwSOpM+rgYIIef4zS518AdzfK33mXgPvvJ2jBo8T8+iu2khIM27djKy6maulSFEoVun59ady9G6fBgPfEifhMn0bjvv2YTp7CXlYGgK5vH0xnzlD51Vf43DKV2pUrUQcH03jwILohQwh97VWqv/2Wmp9+pmrJEvxuvw2VXo+jpgZz8lWq2xmxuRzUTh1LQKWB4AYLtyTX4FIoUGi15EwYjNVYQdcxY1B9o6fwoYdxWa1UL11KwD3zcaqUlPpqCdN60ze0LWEePpx46G7Wj5CuOGOEiw239qStmx8Z1nyuHF/J4IhOrGjKQR3mhtLhIPLoRfJPldBh5e90DozBXS0BrCtTDzMwvAMXKnLQabR4abRUmQ08c/gn4nxC8NPqeerQj8zKrCGhrAHV2gOsefJW6qI70X7abO7c9i4Wp51as5H5Wz7m3qUHiLHAi+NieMZHi75Xa1BoG99wcuvLWZN5jDWZx9h0y8tsyjpJZl0J58qz5fVWafh90rOcK8viqUM/0jEgmp/HPY5bxk64tJI4hZJFt2+iuqmBDgFRPNlrGlcq866xZ9dq3HsSbRDUDj5pLzLXQ0eFhUrbKn6uihSoSgeVuwSLttTRz8Sb1eNuASwtZTcL42JrEgC2+xXpbuw2BwpPCth7Kv3G54B4o7Y+IY8/nSXZWJXpAkCqM8Vc3vlWAUDHF4v/qt8jMpYoIEHAS9llkQ8zd8syAEkz5FgqUyVbTKmRqInPu4rvLG6YRFIAOB2y/YQR4kVrGcAd1kXOCwgQPPKx5KJF9JTOwz+r74ZBVSbc8gUc/1yiOx48LMfgGy2+syHPSndlS+ejp3+rlHjkE2EsR78JChWgkLFRET3gli9v3JZ/vABd73DxfeUcFFZSoRRWMnmjSMN+sQL6is60HlvpZWEj52+DJQMkjkOpulF6tRql8cFpb44ruQnE/teV0yH/g43l8mUpZsCNgch/QZlMJtq1a8eMGTNYsGDBX7qtf66bQOxvUAqNBpWvDw5AqRdvRsmLL2LNysZ31iz858ym+rvvqN+4kbB338V32tRrPijPLl0AZKj3y6+QP+sO4jZuQNuuVU5xi4zAvWMHbCUlKPU6GSF05gwKjQbPgQOwlZfjcrnwveMOnA0NGLZKxyUqFZiaqFu9hvqNm4hevpzSl19C4eGBbtAgHAYDObdMxdnQQPSynzHs2k3dihVUL12K94QJKNQq3Du0p+GxxwAJqgWIXrYMr9GjsdfVYti2DWthoXReAgp161u2ZtkynA0NKNQaHJWVVH/33bXHdAMG4DH3bio0YfjlXEHp5UXgww9j2LWLhk2b+UCn4eRrD7E1+zQLRg1FfeAA9vJyAMzvvcpTJbtRbf+IvTPfInTAAAJfeoHK1xZxUmtmap/eLHxmDGWOJuY1e6sm+CWScflzJno7CJt8C+UjY8CUj87XD3+DnYuVuVyuyqNrUBwDwttzvyqG7Zc+ZWY3T4bs+5qvRz3C4uEPMH7966TVFvHenh/ZW5+Hh9qNI7e/x/DVL9Foa6LUWIO+tpEpR7I41S6E22L7crpdEMsLz7DTw5sDHh402SU81ler46qhhCORHsQcLySw7XheejyI5/rMoMBQgUKh4IEuY9Fp3DlTnoXZbuXbyzuujX9qAYYgGWOZtSUYrE1crszFuWoOSp8I6DQNe2hXPj2/mTqLkc7BcdyT9MdvkVUGK1a7kvD2E+RibKwUL5SlAU5/L3JV7GC5IKvcJbbB67osq7ihApCSpsnzSi7KfReWS2dez/kw+TNY1swiRfQQpsY7TJialmqslCyx4I4Q3EmYMq2PhMgOfka6Lb3DocNkkcfO/CDP6zBZ2KqW7sa4ocLoBLWTeY+Jo4UR0/oIGFFqhGmL6iMM0uIegEv20T8OavPh++ES2fDgIRj5yo0nrDxFGDe7VeRFz0B4NvsP5xWQ/WwsF+Dn5gVd7xRgmrwJOk4GpXTFMuIlAU27XhQjf2Crj4/84xK7UX4FHj0JBz+E80sFuE369EYgq1RL5lpLFEdwR7l5hcGVdbDreZm3ufCcnIuWKIwLv8KmR8X3d+9ukZcv/nYj8wcigd6zS94bEf/18Peb9W9WKZth53MSzdJS3uEw7n3oOOU/ft7/nzV06FCGDh36Xy/4F9RNIPY3KKWHBwnbt8vMQi+v5vFGdtRhYfhMnoR7YiK2EnnT2kqK//D82lWrULi7o/Lzw2kyYa+pJffWmej698f3tpkUP/Y42qQk4nftpOyVV6n68ivsFRUAeI8YQeHDD2NJSSX42WdRBwZgTk7GLS4Oe3k5mqgodEOH4Nm9B7biIqyZMhxY4eaGy2pF6eODQqNBqdcT9Ng/JB7CZKLkuecwX7mC3113oYmMxN7QgK5Hd8kfi4sl4tNPMOzaRdOZs6gDA1E4m307ztaZdyGvvkLVV0vEgwZoIiNR6HRY09MxnjhBTe+x1AwYi2PURJRaLf5z5+B720zyZt5GeG0ta2pSaayw0LFPFPMO7Kfk+eexl5Xj27k7fjXH0Krd0Gu0NNmtfBOj4PenBmNTq+haX8Ybo+/nTFkmq9OPUmtpxDlwLhOWLeOJ6nK+0JQSFtSeT/xGMSiiI0abmZFrX8blcvHu4HnE+4hMZn1oPo6TqzhekkZ6TRHt/CN5oMs49uxZQ7/Vmzhza3cSA6I5XJxMg60JgOKGGjr+tINZh3OYo4gg7tvXob6cvsetDIvqjFqpYv2UF6lqMtBgbWJtxlHubncbUQuDWZbUiQX7vuHZwz+jUihRKZV0CYzlbHkWk+J7U9RQxfbccwyN6IRW7UZ2XSnJVQXsL7zM+fIs3ho4l4+G3kNsVQrK7cLMpDxwknD/KPwqP8Jos1yTLgEBXNn7sHSbz9EUCy5gSCclAWFdYPqPwhAplBJkCgJqwrvD0+kSZdDcsUlFmvidQKSzjQ+LVDjiFRj7roz6aYm3uHO1MEOr7hRw4rDIB/rYt4VpWdJXWKYHDorhHiBlE6yeJ8Dt2VyR0tK2ibG/GdSSNEMyvwpPSwTG5oUiby48K8zPnLWtx+0VKmzcmR+E+QnrJl2UancBYSD7ZKoWsGE1/rHzc8MDkqHWeaZ0gLabIPc77PDLFDHTz9/emqsW0klyvsK7y6Dy3S+LbytrN9x/sNVrte8NYcvUWum0VGkE+Ez+DNJ3CIN27HMBYQGJ0kF6PQhrKJdB4C6njG3yjRJZ8ZET8njWPgGhQX+Sut8CiFt+9nvoPw52/WeJ82b976iUzfK/2OLTbClDqdx/2y9/KRj7f1U3gdjfpJRaLWjF4Fv9/Q/Y8vPxnTkTz55iuo74/DOaLl68xoS1lOnMGcpeF29I/K5dqAMCqF+/HvPVq1gLCnCLjcWckoIlMxP/hx/CdPYsOJ34zZuLJjQMj549cYuOwZKWjsvppOTZ50CjwT0pCXNyMgo3N2JXrsBeW0vW0GEA+N93H0pPTwzbtxPyysu4x8RQ+/vvaELDCLj/fqq//VaS/YGGXTuxl1eAy0XAvffistnIGjESj65dif3tV3R9+6Ly9aXs7bdBoUATLZ1xjvp6XGYztrw8ADwHDSLys88ofuIJrOnpOBsbiAzQUtNgJSa41VNkyczCXluDfsAA5lcrOV1eRIjzMu80VDP7pacpMVbz8N6PGRPTjcd6TOGJgz+gQMHh4mQ8tZ480nkMazKOsb/gMp8Nv5+MmmJOlWXQxjeMbZTw8oWN17Z1+s6P8Xb3JLOuBKfLxcSzRSidm+FeGcc0q/1gvrq4jWpzA3vyL+ICPjy7ngAPBQeSQgnFnay6Up47/DNKwNddz8HCKxzq7kmstSPre2h4Kf0IM9sO4qle0/jm0g7qLEbKjLU82WsqFytz2JF3HlOklTe6deehHZ9S1SSMjgJQuBSMj+uJyWZhfFxPXju2AqVCwaSEPpyvzMFst5JnqOC7yzuxOR0cKU5mVvshOMI7sKvwPEqVGwt3LaZTQDQbp7yEyW7BT3tdN936B6AyFY3FiHfQw1hsTjzdVQI+tj0p3YLjPxDTNgoZfm23iDSmdhf2puyKBJK2HSdslKVBWCQQf1afByR2oaU0WmFqWkAYSDzDf1aGUtmmb7TMSfxtpgCNe/dKEGn2QZkF2VAm4NHSIEARlwCailSJluhym4AWl0vAoL1JfHHbnxXW7u7t0ql49DNh12b+IrLbnw3ubjtO9it5o2yjd3Myv7VBGhlcDtmGT6Qk/ucdk/vKr8o624yFtO1yXt8OhTtWirG/3yMiIyaMgMXdZd2PXZT19Gnehr7ZTxc7WC56hlI5J34x8npdGwLefLE010vzQmRPMeS/WNwKLKuyBKiq1JKn1n6SGP5byuW6OYvyZkk5HcKE/TMIg+b7FLDzeWGa/2KZ8n+6bgKxv0nZystRenig8vYmcOFC6tevw3/e3GuPl73xBqbTZ4j+/rtro4wA3BIT0XbqhFKvRxMYgFKnw2f6dOyVlWh7dEft70/AIw/jkdSZ6sVfgNOJUq/DdOIE0T/9hEKhIOLTTySPrMFAzQ8/oPD2wnzhAgp3d3xumULRE0/gNXwE6tBQHHV1+M26nfK338GalUXpCy8S8uwzVH8t3VwRS75C4eGBOjQUW24u9soqvKdMxmW24J6UhGHLFum2LC3FVlqKQqvFdOGCxFIA5swMGo8coeSZZ3GYzSh1OpxGIx6dk1Dpdah8fQFQ+fri76VhWGeZi1dgENP7rcm1BFdWUX/kCLf07sOIXcm8+3gUp1MzqLU00jEgGovDxpWqfA4XJXOkOAU3pZporyCGRHZidGx3Zm/7iHqribPlWSgUCkx2C8dL0zBYZci0m1LN/V3G4u3uybnyLI6VpDLKoue+fVk07fuUd3X1jBo2lXWZxzFYTYyK7sadHYZyuiwDq8NOjVZDaccQoAmt3Q2Hy8kTvabRIyie2TtkjE71yG5Yakt49fgKLlbmYnHY2F94mSPFydicDuJ8QtC1dOYBp0rTOVWWgQL4YviDLDzwLQ6Xk/7h7ZndYRhGmxmjzYzT5cLH3ZOVE5+hsKGKnbnnsDkdtPOLIFznT53FyPbcc7xhsBLoIevXqjW4N99I3iDm9uEvyQemxYAyfigj4gJa38xWlRju7WbxDk3+XHwg7l6wpB/UF4v0tfIOkcs8/OC25fBRG1g2CeZskLiGSyukAzAgTuTMMz+IjNZpKty/TwzzBScgtNkTaaqWuZW1ufDrreLFmr1GOhRdDuhwi2wrrJvIn34x8ONoYZr0QTL7sTpTJEmrEQ68LZ2NJ5dIc4HNJGBGoZB8MEu9sGpbH5djNRTJqCabEXY8Iz6r23+BNfPF5B933ZeoES9L5+NXfQX0nFwinrohT8OcdSLnrrtXRhO1HSNAq75QJFKQdf3jvDzfaYP9b8rxd50l8mnBScDVDKquu/CZDRItofUVTxnISKjyK+Lnmvy5MJGhSa1xIb/dJgzgpE/lOFpA2LHFsOcV6HK7dGLueU2Aom+0xGV8O0Tyxx483Dq/8mb976384zfKkX8ol8j8+cdv/F/5N6ibQOxvUObUVHJvux21nx8Je3ajHzQQ/aCBNyxjOn4CR309TcnJaDt2pOnKFQw7d+I/7y5CXnyB/Lvnkzd3LvHr16PS6wh+6kmqvv6a4s8X4z1hPMH/+AfW3BwAnI1GLJlZWHNzUQcGgt1O04XzeHTvTpsjh7HX15M1ZCg4ndStW4/5yhXMKSkkbNuKy+lE6e6O19gxNB44gL2kBKfRiG7QINSBgZS++ioum42Izz7FfPkyAGWvvCrHcPYszqYmlF5euCwWskaPQeXtjbZT86QAlQp7QSGNBw/itFjAbsd78mQaDhxA17s3AGfmTSClRyCPjb3n2rmxFhWxfMvX7NHWkBHoR/fxHUkN9qR3v2506hXPZJ0HNWUXGe+TgId/CCqFEm93T6K9ApkZ14+Rl4rp02U8De3iuHXzu9RbTYyM7srt7QZxMVUGamvVbvQNacvSq3uxOu2MixVvy2MHvqeqycDLfW5BN7ie9PoSVjRkknx+M1VNBmxOB2k1hWTWllLcINMA1EolgyO6Eu8TysS43ty69T0+PruB5eOf5KW+t7EseR8ZtSUk+oaRVVdKgaGKBd0mklJdSDu/CCpM9TicTtpruvN4XAAdonSkNmRwV8cRdAqMpmdoAqE6P8qNdczf+Tk7ZyxCp9EyJrY7m7JP8eWFbayY+DSJvmGcKJGcumBPXx7Y+xVdg+J4rMdkNEoVXYPieK73DILdPcRQHthOxuyUX4XLv8uA7mHPQ/r2G+cXunnC3A0i/3mFShddTa5cqA0lwiSZqiG6H5Rdhcg+8g3YM0DAjqefPJZ/TIz5aZtlLFFTjUiWbnoou9T6rdlmkk7GX6ZIB+WIl6CxDHJq5Vt4z/myj+3GC6PWfY4cT9pWYXtUbhI54R3WegzlyWLsLzotPrCmWjHlN1YIcFszTxL3O00XZq02Vxip8O5w6luJ6LA2ys/k9eKZu/7iYmkUULjwnAzp/rU5lqPtOAl1bQFW+UcFiF3f+Xh93bFKlr26TrxhnabJxAKnXQZyt594IwgquQgNpQJMzXXgEy6douPek3N8aRXsfkmS+hfKe/9aFIfG88Zt20zN/4AyYYP+C8QT1nWWvFa1eYBL2EtznfjaQpNE/sw/Jvv2Z2G9N+vfsxrL/3uX+xvVTSD2NyiXzQYOBy6L5QaP1PXlPWkiDfv2o22eqVj25luYL1/GZbHi2bcP2GzYKypvyBK7Jgk0xwgE3HsvvnfeSd6sO7CXlKAOkhypis8+o+bHpehHjSTqyy/RBAbi2bcPphMnUfn7ox8xAqWnJ/lz5xG6aBHadm3xnToVS0oqposX0Q8Zgu+MGTgajTSMGAFOJ466evSDBqEOCMB08hROk5HGY8fBahViWqEAhQKn2Yy1WHxvfvPmYjpxEltxCbGrf0ehUuEeH4+f3crOvPP0aqjixXOrcbpcdK7NYbK/tNxXfPwxA44fJGdKN4a2jeKr3laMNjPpeacA+OHXAj5MyeGIM5Dcrgk4XE6yaku5b8+XjNOEEvL1Kgp/3cj9T4+gsslwjSHr/euT3Ho8ly+vljMg6R4+bTgHQK+QRNr4hVPUUE2ibxg15gaqXVZK3niKstoSknLOUmNuoIN/JCqFkuz6Mn5NOYCbSk2f0LZUNxnYW3CJ6YmeBHl6E6H3p9xUR4CHF8OjurAq7TAA93cWo71W7caPV3eTW1+O0+mk0WbmfEU2byclEaINYVvmcTaX7ibE05cdeefoHdKGxcMf4Lat71PVZKDebMRD70ZSYAybsk9xuSqPz89v5qle03i613TCdP44XE6OFCfj665jQHgHzs35FLcW79CVteI9UqjEe+UXI92FIGzT/rcgopewVC21+2XxYhmKxZ+0/y24ulbiKEa8LGGtOYcEENTmSejnlC8FTJRcFDA1/EUZz3NxBQx9Tjrtus+BTzoIAzWhmZmL6gffDhb2x9oIsUNFQnRYRfoc9pzcDn8o6zMUyy15owAsEIkxpnnfGyvlW7lXGIx6A/yamaHvR0rExMRPRPLT+sp2Co63Jsb7RsPAx+X3jrcACtlG3+u8UuZ6+LK3DP5+5Lh0k3aaLv8TgW3lM2D0m1B6Ubxj5vobU/VB1qn1FU/aqNcF5CSMEGATM0C8buZ6MUHbLcKwhXeHDQ/KOR/wWGtArVLZOqIp+4Cwj+HNnbdOhwTeJowUgHV9DXlWthnSPJ+zKkOaFGxN0jk5b5OwdfoQ+LSTSMkPHYUdz8kg88FPyVSCm/W/o/Qh//Uy/zfL/Y3qJhD7G5RHly7Eb96E0ssbpcefBGACjUePYi8ro/HQIdSBgVhyslG4u6MfMRz9gAGofllG44EDpCV1JvT111AHBqKJiiJu4washYXkTLmFgPvvw2vMGGy5ubisVpqSUzCeOEHjfhlGrNLrqd+yBa8xY4j46CPqt25FP2wYTRcuUPnZ59jLyih88EHcIiOJ/HoJjUeOYM3NJWvsOLzHjSP8nbeJ37wJQ3UFpY8+hr2qitiVK4n4WLKxmtIzMJvMuJmNoFKj1Osofe55LJmZ+N5xBwHz5lH7089Y0tLwv2seuv79Afj60g6+vbyTniEJzOkwjPSaYvqEtb12brxHjyby3HmeXn4SOMmm7Zsw+Xvz8bmN6DVa2s8exW8Xd/G1rgKyKni13yxy68tYnnoQnX8g6pAQ6vp3x+50oEDB+0Pu5kRJGk5cHO8SxbwCJztUtWzOPA1AoIc3b55YxW9ph4jxDsbpcnGpKo9vLu8EXER7BZHfUEmeoYLFw+5nf9EVtCo3VqQdIkznx4NdxvPT1T2k1xYz+PfnCdB60WS3cqDgCltyTpNdX8bMtgO5JVHypEasfokSYw1+7nomxPeipLGGYyWprCtfS2FDFQPD2xPs4UNVkwGHy0lRY/W1EUYOl5Mr1fmsSD9Et6B4RkZ3YV/BZX5O3sft7QZzoPAK759ZR6Q+gIO3vUNKVQGr048ys+31jKxCfEDRAyTJXeMhfwP4JwjQD2x9PbAaha3SeIj3CgQcpG4WsBTTXy7wET3EWL7tSYg9LYb90gtw2ipyl5undN71e0TWV5UlLFGX2yUyIWGEBJgWn4VqaSLB6YRTS0AXIiyM1lukuW1Pw9nmDslxH0BUf8n6Wj5N4jRSNkrCP4jEaCiS42ppKAAJQHU5RWJ9MrXVP7a5OYYjopd0Ku55Rbozq7PFgzZn/Y0+KbtVAlUd1lYj/8yfWh/f8rhkoA18QjK/3PQw8WMBt/0elr83LxBpc+RrAv7uWCns4q6X5LXJPSws2ZCnJaJj90sC3GIHQXa9sFEt5bC3mv0ThsPL5a37m30ADr4jv3e7U3xgLaVUClvYUqmbob5AAHZ0v9apAWaDnDOrUli1wLaQd/TG98zN+vevmAHyxcBQyp/7xBTyeEv8y39zGY1GCgoKrv1dVFREamoqPj4+hDdndP5VdROI/U3KPTHxD/c5zWbKXl+EyteX0EVvYDxyGL+5c7GkZ+BqNIJajUeSfBvV9elDzU8/g8OB6dRpDNu2gctF7Jo1NOzegyUjg/pNm/GZPJmAhx+i6vPF1Pz0E/bKSuzl5fjfew+mc+ep37iJwNxcfG+fRfWSr6la/AVOoxF1WBhe48fTsGMH9rIyip95FmtuLmg0uEwmDNu24XfHHXxmSmVZyn4eStAztqyMkueeI+CB+/GdOpUUVQgFFjNd4rzQvPI4xuPH8b/nHjTh4fjNuh2n2UzgwgW4zGY8e/emyW5lY9YJfN11qBRKInWBHC5KpnNgLHvyLnKlKo8R0V05H2DkvrUrKL/3H9jctHgGRBLq48lXIx9if8FlHm/cw6VEN3A6iND7k2eo4IEu4+gWnEBSYAwxEx5l4f5vqcm/SIinL08c/OFaUGmRXoXbml/ZfmIl9RYjCmBn3vlrr1F7uzv/KPYmccBQHjaUU9VkIL+hknifUIobq3n68E90DIgm2NMHf62eKQl9mdV+MLPaD2b8+tdxuJxUNUcmnC7LIK2mCICewQnsy79En7C26DRaNEoV7w2eR5mpju8v72JB90ksubQdq8OOzs2d94bchUappqihihBPX7zdPOgeHI9GqaassYbvLu9Cp9Gya/oijpekYXc6xBvmH4GH2o0uQXF4qN1YeOA7HC4nYXp/Bkd0lDFA6+8XFmX4y61J9tH9RS7TBUqm17DnWt+4p76R7C2/uFZwc03qOyNgSakSE/73I0QqO/S+SJjWRpE0P+kgctmmRyX0dfLnAkpwwYKzwsoVnBQgpXKHWSsEcKRvo3bteupK4gh+5gl0/vGy7RYQFjMQTn4l3qXe90pmVlX6jf94GbuF4eq/QEzuxioBVjN+lOfF9JeMspocmPSZxDWo3FrzsOKGiBTqpof3Y+T8RHSHk19Li77NJOxQaBdhBtO2y6zGgY8LeCpufn8ZK4T5QwGZuwR0Jm+U9YMAn0sr4c410GaUsIm5h6DDVGEsO97SOpnAM1AAW/Z+2YeW0NjfZgpom7tRjgtaQZjVJExhZG/wjZGRSC1VeBp2viCvWVA7eR3CuwtYa2k8AGHjtN7iZ3PYpHFh0ifS5frPafs369+7lCp5762eh7QTXQ/Gmt9z4977y4z6V69eZd68edf+fvddmYIybdo03nvvvb9kmy11E4j9jcpeVUXVkiXohw1DP2QITRcuXJv36D9vLvqWod9t26Dw8JCg14YGVN7eAIS9sQjDrgFYcnPRxMSgUCrRREYQtHABan9/vMaPp279BtR+fgC4HA5CXniexkOH8Z93F66mJsyXLmHYtYv6bdtwNDTIh7Jaja5PH8Lff4+6QQNRaDTUN2eNBT74AA379mNJTaXyi8Xk39YNgKZ5t+GlO0vD7t3UrVkrUqZdZFdjfhGaI0cA+DGwiU1het4ovEr0wldQh4WSuG8fCoWCpRe38cWFrbTzi+DLEQ+SXlvMppxTlBpr2ZZzBicuDhclU2tpRK/REv3yEkx2Mz5mFy+d+xarw47VYedseRax3sG4qzTUWYz8krKfcmMtu/Iv4OOu49is9xkT0520miL0Gg/KTXWcLEknQu9P/7D2ROgDeK7PDFakHmJ95gmsTjtqhQp3lZoFhwqx7z9IYWYuL77xIqdLM6g2NzCjzQAe2rcEm9PB+YpsNEoVNqeDOouRRmsTGbUldPKPJr++gi4BsRQ0VtEvrB1HipIJ0flypSqf39IOMSq6K1l1pbhwsbfgErXmRuwuJzvzzhOpD6SdfwS/pR1iVfoRjs56n+ePLKOksYZHuk3gQoV4Ap/qOZVIfSADwtrj5eZBgk8Y/SvOEbV2HnHj3+PMnZ/w5cWtrEk/Rr+wdpQYa2jr2/wN0V0v0QnlV2HLQki6VboKPQOFzdr5gjzm7gXjmpmTmIEi60X1hdoCyRA718z4DH6ylWWK6Al3bZXE/GOfCTOUe1hyu3CJ78rlEMCTukXuU7m1+opaGgA0OmGq/ONh4BPUf3MBc3oGhj1H0AU0we9zBBS2HScA5avesryxQpibjB2yrwCXV8PZH5vZquYh33tflzyzxNESY2FpENAHIn3eu1vAY8pmAZ7d7pQ4jH3NIaZ1+XIM1VkSxdECQFpM9Ec+FlbPXC/NB0q1eOxihwgY1HiIkd87QsBVYFthE3c8L/vSMuOx6yzxsPWYI341kC5OkLmP5ckirRacFHZP6y37bzfLvrUAsZba94bMBE0cDbf+eONjF36VfXY5pOvV2ihdnndvbV1m10vikZuyuHVkVUvdBGH/O6vjFImo+NMcsff+0uiKvn37kp6e/l8v+BfUTSD2N6ralauoXbGSxkOHSdy3F8+ePfGbPRuVry9Os5nKL7/C97aZrR4wpxOXw4G9qoqG/fvxHjsWl9lM3W8rUAcFkXjkMPbaWlAoCHnhecreeJPaFSvQDR1C3KaNqAICaNi2Db/bb0MTEkzoq6/if999ZI8cBS4XoW++gUfnzri3a3dtm74zmucKKhTohw7D745ZePboQeVXS/CbdQcvVJfRb3cu424Zgv+zz6AODMSnOay1d6IPdUY7bicuUgIodDpOWSupd1q4YConGnA1mTGnpuJIjONYcSoapYowTz8e3vc1Oo2Wp3pMxdPNHXtVFdll+QQltuVwUTKjY7uzMvkQv2cdYLK9D3vyLwLQLSiOpIAYeoQkkFVXSnptMTqNFofLiVqhwtfNE6vDxuSEPkxO6MNLR38htaaQ/AbJWbu38xhUSiVt/SLIqivD6rQDMD9pJA92GYfNbQtZJ46x0c/C/gPf4XS5+HDIfAZEdCBCF0CuoZwewfEkBcZS2ljD7A5DWbD/W06WphOm88OJi8FRnXi020Q+PLMeJy7clBr2FUijQ6jOj7cHzWVL9inWZBzDX+vFLQl9Sa0uJKe+jM4B0XhpPAj08Eav0eJ0Cdjt4B/JgPD2BGi9OVmWTlFjFZeqcqkyG7hanc8b5WdQ22rh0irOd9c1y6qwfPyTbM4+TZ6hghCdr4CeeZvE42M3w6DHhSX6pKN4gQY/KXJT5xmtb+TofuKJ2vuaXPirMsDdR7xW55eLJ2z4iwI4UjaJsdw3Bnyimw3eCpi1Usz1kb0F7O1qnkkZ0Uu2u3ScSBhB7YVlW3+fAJne9xE+uzO16b3wH9ZBwAEu2ceIHrDpEZEmqzMkr2z8hzB7rVwUXC5pnzdVi3SncoPl02U/0raKbAcCFKd8Ifvadpxkfq2aLdsJSJCMrJ8mCFAd+rx0WjaUCduVcxhKzor365avZH3DnofT3wlBENpFHlOo4Ov+Ahz7PghnfxI5N7Ct+NIiewvb5BUu/q2mWgGA3e688UPl1p/Ew9Z2vBxXwggx5a9sZioH/ENAZGCbP34gBTdnhQV3gIxdAr4je4rZPnm9nJ/Bz0C7cSLThnW58fkVqXJOKtL+uO6b9b+3Ok6R/6//4WT9/5d1E4j9jcpr7BiMJ0/iPXYMIKGpoa9IJk/+3fMxnTyJvbycsDffIOLDDzCeOInKx4eSl16ice8+mi5dwv+uu9Bu34F+2DCcFgs5k6fgqK0ldtVKtB07gFKJtmNHtO3aUfPrb5S/+x6qwEDaHj1C9U8/Yzx+nLA3FoFag++0qdhra2m6cBHPHq1jc4ynTlPyzLOg0eAzaSK6AQOo6dyGJpUb6pffoO+FfOxBJ3GbdQehr0qiuPH0adyioylUGHm24QhjPvgHt604xIKfjpA6bRj3zJ6P1eRP+euLyJ8zl7J1P3C+QpLG53cexfmKXCK9/Sk11bL+xD5+/v4cfSw24tatZcLgXixPOcDvWcKylTRWMySyE4eLkkmvKabJYeVqdT4joyTmwGgzs7fgEo/1mMxXF7YxfM3L9A5JxNddh8km2VTdg+LxcfdkxuZ3eanvbejctFypygNgQdeJ3N15FHqNFm6/jTPt9BTnX8DZLCtuzDpJmbGWUJ0veYYKKkwGfks9yNKxj9HWL0KeB3QOjKXcWIezuUFjWpv+ZNaW0C+sHR+cXQ9AmM6f3qGJxHoHk1JTRKO1iU3Zp4j2CmJEVBc6BcawKec0DbYmXMD6KS9Sa24kVOfH80eW0Wgz80yvaWiUajoHxhChD2Dx8AeoKewCNcnQ7xGS9KGMjumGt8vOjuzTrMk4SkpVPuvGLRTGydMfpn8vbEtoZ5Gs3HRgM9F4+gLO7k/jHSF5dzgd2CxW6ivrCAT5kHXTycxDzwDY9oRc+JM3SDCoSi0AaujzwhyBsLAJI0T+K7sigaTVWeIZC+kEWXuFOSq5IEBIcR7ih8sIo8zduNUVENJpGuz6SLY/a4V0Zq66Q0BbcEcBSWWXZbbjuZ8EDHqFSlNA1j4Y8w580UMYn6Tp8Jy89hz7XOZQdp0lUq3aTQCKf7zsf8EpAWKmasAlZvq180XinbdJLj4g+9+SL9ZmtDQoHHhLgNXwFySbrCpDmLekWyUiA+T8R/SQrsvGUvGxrZ0vkuTMZXKRK7ko7Nm2J+UczVkn++kdJqDQ0iDgTest3aY12c0zLvvd+IHU827oegcUnYWfJwjwejpTZNWWINzQJLmAdrsDbGaRkj38JUdt2reSFXe9H+3/tC6ukAaDsW//ZZ6hm/X/sJSqf7uIiv+sbgKxv1Fp27Yl9rdf//Qxr1GjsBbkox08hNxyE45PPsWWk4PS2wuPLl1pPHgITUQkpjNniP7lF1R6nURAALhcVH61hIB5c2l/9QqKZmnIo1s31KGh6AcPAqDqm29w1tejGzAAv9tvw5KZSfGzz2FJTSV00ev43S7fojURESi9vVEHBKD08CC7rpSpm95Gq3Zjx5OPEdyxA96TJl3bd8OOHRQ/8STq0FBOfPY0RY3V7FeqGD68H6Hrqujf9xb0bh6Ye/RAqdPhFhdH/6gk5ncaRYjOl0i3GF5IfIaoQHf21Mg8zDJfLWdjQphvNfHEwTVk1BajAAK03lyszEWtVPFY9yn8eHU3OGQ/FAoFz/Wewftn1qFVafg97Qh2l5N6i5G9BZcA6IIXG/cZiH3zVp7M3onJbrlmsrc4bCT4hLLk8nZWZRzh+9ELaOcfwSPdJvBw1/E8cfAHjhancKwklWMlqeya8QYmm5nZ2z/G4XJSaapn0YmV6N086BmSiNPlxImLE6XpLGQyib5hfDdmASabhWUp+yk31fHVxW18cm4jqyY+w6k7P+LhvV9zuOgqBQ2VeLt7svTqHjk2wOKwcbgomcUXtrCg2yT8tHrsTgeDIztxT9Loa6zmmNjuYMyHQ4tAF4jnqNf5wlsDW5/lcuJE0rximVl8AD76Eh44IGBm7T1yAQ7pKBfsfg9j2/oWhb+nwbLH0fy8BI+O7eC74WzKiCK/XsvomR/Q5ZZ5cjFeeYcAlPEfgC4INjwkDM/EjyXwtb5QOhrdvSBxlLBl538RIDT1G7kYH/5QTPX/uCCG8LQtwtQ8XyASKsh+GislakPlJrdVd0LfhwUcXFol8xwbK4SN679APFnGSmF+vEKlAcE/VlivssvQcapIfOd+bgUrKZvh8hq4e5tIehE9BNDkH4UBj4r8krJJJM8NDwEuSbY3VTW/Gf/p23+nqXDhF5FQnU5hGjN3ywiik1+L/FdfKN2nNdkCrmavkwvapkdFajWUiN9s1R3CehmrJCrk8u+SFTbwMfGXuXvB3PXSwNAClAb8488/lNTu4n3z8Jdzo/EED1946Jg87hfTumzhSZEsQYJ4faNaZ13+V1V6WZjOFu/a2Z+ETb28+iYQu1l/+7oJxP5Nyn/ObPznzOZ8dj35uQ3E9huJt9OJfvAQPHt0J/CB+8m97XbMly9jLysn+KknUbq7E795E+UffIhh40Ys2dm02bMbAKfVikdSJ9oclI7Jug0bcZlMaJOS8LllCoUPPYzp9GnUzd0kFR9/gmf//rhHR+NsMOA0GLA2NWGvq0PhpqCfbx86eLXF1GBGlZGBNjeXOm8PMmpL6OrnByoV6uBg7uo4ApVCSYJPGPMOfIfrjjasTIylIbmGyIBIvHYeJrfKgq8Z5ieNwttNy+dHj9BW25l6k53nek9nRpv+vBOxgpNVOTTUXqLAIDLiy/1up2elndl5W1Cr1IyJ7U5mXTH7Cy5jdtg4WpxMUaNcCD01WspMdcR4BxPnLe3SVU0GRq0/hutsFlt//Jh208fSaDNzuiyDMqNkgJlsFpwuF1VNBmZsfhd3tYYlIx7m55R9NNmtNNrMAAwM70CUVwCPH/gBk91ClD6Q1RlHOV2Wce017Rcq80CvVudjsJjwdvfEbLcyccMias2N3NNxFMvTDuBwObE4RBJ14cLhchKpDyRKH8jVqnzclGp6h7bhqYM/klZbRIWpnoNFV9gy9RUsDhs+7rpr21yVdhijzcI9JWdR2Juagz8RlgvoUnaOFY3bBAg57SLD+cWK0buxXFgUgH6PolJ4or3wGx7afLQ7p0LGcGgsw2UPArS4Tv8IoU2tKe21BeK1GvaCSHgVKQI0Ri8S+REkmX3aN1B0Tlgcn2hhpBpKBUwo1CKLDnlG/GT+cQIOHHbYt0gYKVuT7OvTWbDmbgEwhmK5oLdc1PWhMgh71Z0SE+EXK7leX/YWCXbOekmR7z5blk/bKuvwDhdj+/oHxHR/5kdh+ka/Iab1zrfJ8nteEZBjNwtTdeY7kT1tzZlb1kYBSi1diE67xHPUFUDJOZEem2Vmcg60RoN81lnuP/Au3LpUfF+GYmHGut4h4EWhFBZy3LsiiWbtExbR5Ww1+l/4TVgwc52Axcp0+GaQeLnGvi0MXkWKdFn6xUrsRGFzSCxI3Mg/V3R/CXz1DBAQ1lLXd2X+WTVWwA8jW8Nfw7pII0hLh+zNull/81L+14vcrL9DWfPyMJ46jZ9eg0IBnnffR8LOHTdIhrq+fVDqdHh0b71P7e+P760zQKHAXliI8cQJKj76iPQuXaldvfrack3nz8usS19fHDU114zE+mHSgu40GCh98SUAVP7+1E+6g7KHX8Hh7km8byi3RIwlzjOOitNpGDZvoeLTz7hv9xfcu3sxk/I3s+TNeUT8soz9hZfZlnMGu9NOjHcQkfoATuYVUd1gI6vUSGa5mYp6K7vTsxny+/M8dXApy3I38FvRanwCG1AqlLTxDaewqQ6AUJ0vCoUCBaA9fQHXAwv59oezTIjrycQNi0irKcLssNHeLwKzw0ZmbQkbprzI58PuZ2J8L/INFRwsukJKdQF+Wh0J029n1+wRfBjaxNeXtlNgqECJgmpzIwoUdA+JZ1hkZzxUGpRKJU12K/N3f86hoqucLssgtjk2Iq2mCJPNwr5mps3qtHG6LAO1QkWYzo9xsT24O2kk3m4eeKjcGLXmZY6XpGJ3OqgzG7E67ThwYXMKneepEYN6gNYLgGGRSVQ2GRgY3oFuQXFEeQVxuDiZClM9d7YfyjO9pgtDmXuee3Yt5nx5Fu+eWsPrJ1Zy6OjXFKr1MPFTkY9AZhCO/6D1Qt1ukgxmjukvrMijp8SE/81guaibqlDqvIh7eSqhPQzS82Q1wtDnmdrdwdwRerp6pkv3YNq25jejm0iNl1YK0FBrhR2DVsmupTOv/IoAqro8kRGvrhegZGuUkUY1OcLWdZom4aGFp+D4YomdCO4ox5N3GHL2iwQ68RPpANz4iLBoVRnSiVh6kWsdW2qtSIzuPrB3kXRuZuyW5SN7w9AXJPvq8EfiyYrsA1fXiH/NO1yee/wLeSy0iwCikCRhjfKOCghTamR7CqVIiN8OlQDYgDayPhCTf94xMfwDRPWGnyYK+Lr/AHgESNDspVUiDQa0kX3+bqh45h6/Ih2Mv8+R/+MhTwvTlr1f0vDrCsUrZ66TMNe4IbI+i0HyvQB+myFTDlqGoq+/X9jGwx/+xx9SandJ379+xFHeMXgnHFb8J4BK4yGsq9ZHXmMQwF6TLe+1m3Wz/uZ1kxH7NyiXzUbuzNtwNjQQueQrOn/wIfbqasxr13LF6oPN4aRPGx/8Zs3CmpePo7b2hud7duuGe5s22EpLUQcEYM7MBMCSlXVtmeCnnsS9XTvqt24lZ9JkQl57DdN9T3BBH0kHT18sK5ah7dQJW2kpmrAwym59EBeQX1aH9rGFtPcNoO6Rl9BGRWIe0JffxnZApZBcrjJTLeXUYXBZ2Zx9msy6Un5JPUCtuZHb2w1maepGRgYOZVh8HOW2JhqcKn7PkiHQh4qusrD7JMwOK1o3JW+d/J2z5VkUNzNU7f2jeL7PTF47/hs/FZ/lRW8tfn6B7GiOmNBrPPB39yLKKwiVUsV9SWPIqivlmcM/MSyyM50CoskzlFPRVE9FcT3HFUockU46+MdTX1NEmanu2jkaEtkJUHCw6Art/SOZGNebAwWXOF+ZQzu/CIZGJvHdlV3N+xWBVu1G58BYihurabQKU2Z3OSg11vLBkPm8cWIlcT6hNFhM5BjKuVCew4DwDrzYdyavHP+N5an7ebTbRNxUasL1/uTUlVFqlNf2RGka2fVlhHj6Um6q40x5Jk/2nIqH2o25HYfzzaUdNFib2JF7jhJjDSUN1eQ1VBCicWdpwUHU5fvEEN8iLf0yFSpTIaSz/O20igx35keRopJmyPgfp11S8o98Iuno/RcKQ9RUJ56PdfeiqU4hOMZPwIbZIJ2EDWWSi3Xm++ZEdoWwRdn7YcACATq1ea2MVVhXCO8p7ND+t2RbIO3v7SYIU7L2HmGLyq5I+rxCKYDjoWPSmVmVKUDP3Rs+ShQgmX9MWMBHT8OYtyTT6ORXsu3qbHj4uBzjkv7CIOUcFK+S0yqBszW5whQ5bSJHGiuFkbu8GrY9JWAmIBHGvClM0pGPYMzbIo1ajSJXWupFJsw9JEDQbrlxiHbuIQFuT6bIsPOr60WeLDotA7+HvyBp+hk7YcBCAcwftQFzLaRvE4N/S1BtY7lIwqGdpQu1sVwkxnYTr3nqKDwFT6QIGIrqK8G1Lblsns2p/EHtBCz/R9lfjRXi5cvcK0PCQ5vfR2lbRdIuu9q67Irb5TWbt0maBNy9YOF5kaFbuimHPCvnqusdf769m3Wz/kZ1E4j9Tau8zoLLBaF+7qBSoQkNxWq1ovTywlZaistiobGqjiKbMCV1Rjts3kzDnj00XbqE74zp19alUKuJ27SRig8/JOeWqQQ9+ww+k6fgNXLEtWVUvr74z5mNYeeO5ueoKPePxmK0UzpxLvWdRhD7/BzqVq8mYecOOkbr2ZedxraVi3nqpASdau/5B5mekZyeNZUNxbvwd+o5Nut99p/dS7sXP6Zxz8M88/m7JPqGUWas5UJFDqk1hUxt04uMugx2lZSyI+8cWpUGs8OGAgV6N0++v7ILs93Kd5d34gKUzQzG4IiOOFxOlqfsx8ddR1YY3PNwPzr4RmCok9ZoLzctNZYG9hRcBKDB1sSyZJF5ai2NrJvyAl9e2MqXF7cR5umHv1ZPibGGJ3pO5fXjKyhpBnx9QttS1WRgWGQSlypySKspIq2mCH93L8bF9uT5PjNYlrwfgCAPb8bG9mTI78/zUJfxzOs0gndPrWFNxlGSAmPpFZKISqEks64UgG9GPcIHZ9bzU/Jehkd3YUhUEu38IojQB3C0KIWChkp+Sd5PtbmBuzqOoKihijkdhrPk0jYqTHX0DElgRFQXvN09GRbZmfUZx/ns/GYA7u00ih+T95LXUIGvm457uo5D7cwTkBLcofUN5xUieVodp4iJvM8DcuHd9qQ8HtVP5LqyywKEavPkAh7eTczfqZtFbhz6gnQRtgyObqqBQU/IrTYPtj8pgG/sO3LxrkiVmZF5R4WhKbkgQG39/cL0xA2VC7VXKIT1EFN4S8p84ihZPmWjMG8upwChghMQO1Au8o+ckvDTmmwZ1RPWTeI2fhwlUwIydgkQA/FbGSuFbZu/XZipk1+JjKkPkkaBpWMl2mLU65KXFTcMVs2SeI3BT0ozgGeASKTJGwTQpG8Tn9mvM4Q56zFXglltTQL62k8SH1l9gYDFqgxZh7u3NCh0vV1kxKLTMrdy2jfS4FB8VsBUeFfJWsveB1fWCRCb+IkMT28/WY5twkfyel1cKeBuxMvCoKGAoA7isetzv7wviptHG035QmRhEOBot8jr8M914B3Jges8U/ZT4wnPZDWD3CWyzOTP5afD3irZll1p7dZUu924zu6zW2VhEGZNpbkxQPZm3ay/Sd0EYn/DamyyczytDoCRXQPw9lATt34dTosVlV5H7O+rcNTVoevZhS5lJmx2JwFeGuy33II5PeOanAjgcjqpW70aTViYMGAuF/bSUgLnz8d07hwolXheJ2VGf/st1sJCtO3b08Nkp6zaROP5C9Sgx4Wi2fCtoG24joXHN1EY5cGM28bTK6kfrpgQrqQWMigoFr8TLtISPPjg7HqeV8RTWllNU209bd19ebb3dEoba/Fx16HXaPF117E89QC+7jrUCiVTE/txoSIHp8vJO4Pm8fC+r7E7HViddhTAbW0HsirjKEeKU2iwmsmqK2V0dDea7BaOlqRS0FiFs9nLomo2RbfxDaNDQBRHipPJri8D4JV+t1Npqqe4sYYofSCFjVX4e3hRazHyxYUt7JzxOhM3vEFhQxVnyzNxulzUWYx4XDcfr8bSwM68cwR4eFHSWA2Al5sHR4tTqDE38t6ZtewruESnwGhMdiv5hgpOl2VcY/RA5liWNFZjdtjIriulY0AUm6a+TJPdSt8VT2F12FvEM9yUanbf+gYAX1/ajgu4UplPpD6QTdmnGBbZmSNFwj70CE5gfufRrM86Sa2lEa1aQ0j5JTIGPk3bhEGtb7jT34v8N+Zt6P8IDH5a2InqLGEoNHoBBhptK4OWOFLYM3dvWNFsyM7YKeyZoUSee8sSuXh/mChxFkOelswvm1HM6knTYcezMkKp251iLG8okwsuCCBTqsULZjFAjKcY61tiJAYsEFnt2yHgMkObcZC5U2YtvlAostx3Q8Uj1n8BDHoSfp4o4Kc2T9YRO1i6Ej39xaT/VW/Z9+nfC5i78Isc+7Rv5XHfGDHcn1sGhz5s7Qj0jZYuyiurJUpDoZLMscheAtjKLgMuAXEpm8A7EoLbySgjlVq8WWe+F8YupAvc9rOAMBDgOeo1YQDbjpV16kNlnuaZ7+GWLyVWxFTVmtd1fpnse9EZePQk5B4UkOlyyk+7RfalxbjfUoFt5DgOvCWdmx2myGt64iuZI1l+VXxc11dLHpTNLO8HnygJ2dUFyPkCib0AOda5GwTwdZwqsqybTkZX/UdVkSavm0IJj11sHUZ+s27W36RuArG/YblrlOi1KlyAViM2P4VGg0ojFyht+1YZIypQS0axkUqDleDwcCI/+/SGdTUePkzZ64tApSJ+x3bMly7hNWoUlpwc8ufMBYUCr9GjCXr8Mdzj4lDqdGjbt8flcqFzNOG75kcc331Hm+FjCNuyDQ93NZoQ8UH9OPYxfk87zBPK3fTSF/K0pZi30j4lyK7ky1WHiIv04ZU7u3PbhEE4XniMuMROqLy9uWfX55wpy0SjVGGyW5nVbjAKFNRZjHQPjuepXtPo89tTuHCx+MIW1k1+AbVSydRNb1PZZKDOYqJHcAJWh50p8X3IqivhanUBy8c/wZi1r2K0WxgR3YU47xDu6TSK6VveJbOulHB9AIeKrqJWqIj2DuK2re8zKb43m7NP4+3mQbCHDynVBShQkOAbhptKw/xOo3jj5Cra+kWgVqi4Wp2PrtmvFeThTWWTAU+1O6vSDuNwOQny8Canvpx+Ye0ZH9uTHXnnOFWWQceAaO5NGk25qY6tOWc4UZLGw13Hc6Uyn4/PbrjGAFaY6vjm0g6y68p4tf8sfhn3BI8f+J4yUx0KFHQLjsfmdGB12LA3+8d83HV0Doxla84ZugXHoVGqyK4v45X+t+OmVKHXaKmzNOJnN/F4QRY++WmcagZiNqeD+pStBFoaxOhtt4gPrLFcpDtbk1xgbU0CxMquQHmKZHC5HDgGP4sKpDvRZpJb1zuEOYkfJhEQdrMwT30fAg8fAXkRPQUQDHhMfFYnl8jIngvLxaC/4Jwk6Rv2CTtnrJJZlSkb4a4t4jPr+7BkmikUrQ0BID6s+mLp9lNp5AKed0xASbVEojDydfnp5gkzfpDQ2ZNLxKOmUMo4oLZjRCa8uEJYu/nbRdK0GJpz1IzNMRWIdHdppXivlGphvgISRZ70iZC/79snIam5h0SyNFUJ6B2wQCRaXbCc9/LLMnEgYYSwbKGdBRCHdhbzPEhA66H35Xz1uEsA6cRPBACuvksArT5UMr7qi2D9g3J+et0rDRgJw4UR9PATIAQCXFfOktdYoxMWsDJdGKy2E+T+fw5mBZjwoQC22EFy7Eq1SMMefvD45T8u39I0UXhagDgIE+gf9+cfiJ7+IjGr3QXo3ayb9Term0Dsb1gatZLR3aSbyulyUV5nwU+vwU39x96LnDITmaUmiqrNjOshxmen2Uzxk0+hUCkJeuZZ3BIScIuMxC0yEvdo+Tap8vFBFRiAo66ehl27UPn4SH5Yc5W9+ip1a9biNVoSus8Yczl5YSX/+Hw7+t69CX//PQobKjnZ3AXYYG0Sg7nLSaXKRUq0H94dk7gvaQx7Cy6y1HmJ0RYFHzv6kVVbis3poFtwPIUNVUxL7E+XoFheOvorYTp/zpdn83SvqXx4dgNHilM4UHCZaW36k+AbRmWTgZ355xkU0ZGM2mLeOLUKgEabGavDTt+wtpQYa9Eo1WzOPkWdxUh5s8+rZ0giZcZaOgZEcbWqQBgus5EwnR/zOo5gQ9ZJKprqubvTCJ7vcysACb5hBHl40y0ojk4B0XSqjqaDfwTLUg5gtdsAmNdxBFtyTtNoMzOr3WBWZxwj2NOHZ3pNY2/BRWxOB5l1JcxoMwCqBCxUmOoI0HqRWlNItbkBrcoNs8PKh2c3XHsNhkYlMSyq8zU59tFuE3n84Pe094/k29GP0mgX39ni4fcT7R3EhLie+HuImX9D5gmmbXqH4VGdKWzuFF2Y0J2nk4/Rzq31Y+GTsxvZZvPl8YQpTB/7jlzAqzMF2PjFCRjI3i/AYeRr8ONYsBkxekRhq6/k8JFSpjx0VDxMF3+T2Ihp3zS/OQ8JCFMoRcqrSG1lTwqOSx6XdxSglO2FNBvPO04R5i0gQYBJy6zJnIMCrA6+J2DGbBCmqu14cPMQGS5rr4CATzvJ/MUHDkk0wrJm5mrMO9KpmDRDjtUrVFi2fcIyMvgZuH15qwRXXyw/W0CCwyqG9rkbwWGWIFYQEKP1BhRiur9rCyzuJh2Nd22VsU8t0wE8A4RtS9kkvqqCE3I+ACZ/IV4zl7M1NHX6t3D6Bzk2S6MEzA58HM4slekAqZsFUP7QHPvhlPclDxwU037LEG5jlUwNOLtUMsIKTwkIbSm7RTosnTZhBDtOhe+HCws26Akx9mftk+23mOpBQGLbMa1/V2bAofeg650yeuk/qqB2MgS+ZWrAf1T6YPHLofjPuy9v1s36F62b79q/eaUXGUkrNhLi48aADn5/eFylUqBzVxEdJCGhLpuN6qVLadwvfqXAhQtJ2CZjR1x2OxWfL0bl60vA/Ltps38/hh07qVuzBt/p0wABcQ379mHJzQXAvU0ieXMm887VdbhqsphXU0HVqSM4G6r48uJWrlTlMSiiAyGevlytKiDRN4ysulLSXluIl7snvm4eKJqFtQCtF88c/pmKpnqmJvYjQufPmbJMvrm8g69HPcKI6K6cKEnjwb1foVVpuK/TaC5U5vDGqVWsyTxGl6BYTpamo0RB58AYLpRn33Au/LVeLB37GAqFgv4rnqHW0sjhoqvoNVqmJPTlzvZDuFqVz4askzzUZRyP9ZjCgv0CGq5W5TM+tgd59eX8kryfmW0HkuAbxrGSFCqbDKzJOMYq1xHe6307aYZKcuvL8XXXoUTBD1d2sWP664TofNmVd4FyUx2fnd+Mu1KDh9odu7WJssZanjgoF70JcT1xV7nx3eXdVJsbSPAJ5a1Bc3n75GrAxajobuwpuMjylAOY7JZrQNJNpcbmdJBeU4yXmydrJz9Po9WMn1bP6LWvolGqWDr2H5wpz6LWLON5zpRlEakP5NFuExjRpj9n+sxDdd0ga79GGx7VCq4Onch0fbBcaFtiE2wmiYwAMZW/FyUymULJkTYLWHXyIMPcmpmamEECHAISxAxvNkDyOnlueA8BHg1lcsHVBYr8plABTpi/E7b8Q+Svce+IIb6uoDWZvb5IGgEshlZPlaFU2J6MneLBApj0ObxcIUyasVI8bhG9IG6QxCqcXQrnf4YFZ2Dd/SIjTv5cIidCu4h8eORDMcOXXhLzuk1iPVA3m8j3vSG+sXYTZD+Kz0tTwaAnhOFqP1GiLHa/JMfrcgoDWJkhx4JCJM5Rr4tcGtUHVt8t6/bwhZ7zpOMz95AM+VaqJG+tOQT4mmzrtIl37Phi8aKVXJRldQHiEWuslNwynyjxbD14SCIpvhsqwDh1i+xv9n7xvrlcwnL6xYpMmHSrANqOU8UDGD8MfrlFtt1mtATa/kd1+luZIlCd/Z8DMa0PzN/2Hz9+fbUc9826Wf8f6ttvv2X37t3k5OSg1Wrp3r07Tz/9NPHx8f8j278JxP7m5d4sTbq7tV48CyqbaGiyE+Gv5Wq+XHAjA+SDunblKqoWf4HS15fAhx5E27a1y8l09izV30pcgffYMWjCw/Ho2oWaX37BsGMnHt26Udk8DNyzb18iv/oS/ZAhBKhVPK1TEOKmJ1DZm5lcxLp+ES/2nYlWpSFaH8yK9EMAfDvqUQ4WXaFPaFsebwYee299k8ERHXn1+G/XzO959eWcKZPuzRpzI/UWI77uOiL10qVldtgI1fszNziWcweyyagtpktQLCqFko4BUXx9ace14+oRFE+o3o/+K59hSkIfnu9zK2F6f2otjdSajZye/TG59eUMXPUcyuZQ028u72RMTHce6DKWM2WZbMsVg7Kvuw6jzUxGbQkljTVsyjrFoIiOlGekkOfupGHLVn4JNaFUKHi06wQ+OrsBm8tJdn0pazKPcbEi99p+vX92HV0CY+gV2vZa8GqkPgCHy8X9ncdQaqyhsqme7Poy3j+9ltSaQhwuJ0/3ns7vGUcoNdZytTIPf60XC7pNJNEvDACr084/9n1LhFcAx4pTKTfVYnU4xFN3ag3nKrK5vd1g3ho4l5ePLafR1kSCbxhFDVXcvvUDwvX+rJz4DCoUWJdvYIzJyKQhLQOrh0q6fAtTY6oW1iqooxjqPWLgiRS+3/YhyR386NSxOYDTWCHMS+GpVh9WSwemUiVdfCUXhCEylEgOlVItf2fvE/BmbxJfUkOJ5GyNeUO8WLV5AsRGvynr94sRZufg+9BhsrAz7SaI4dxQKhlWWh8BKdn74MEjEi0BUJUlIK+2+XVK2yHs0Jz1AgZDuwjz9ut0AWKjF4mkeXGFSLUt6f8+kQI8DcXSSRjUHn4YIfsa3EFGOTltkpkWkiQdjVofmLdF9rOlK/OOVdL5KSdK8smmfi3rqM6SW1RfAVMgQLauEL4eKGxZj7ulYaIleX/mMul2/W64SM15R8V3NuRZGPGSALOC42K+txjh7DLxa415U44HhOFqAetDnxFgmH9cGNGqDJlmcOpbOP4lTPhAGLLrq8ddrUCsMuPPM8fStgnoH/aCSKD/XFn7hMFrGRp/s/6tyuF0crY8i8qmeoI8fKSBSflHxee/q06fPs3s2bPp3LkzDoeDTz75hHvvvZdt27bh6en5l223pW4Csb95xYd6Eu7vfg2QOZwuzmUbANBpVei0Klyu6wBb27Yo3N3RDxhAwN1337Auj86d0Y8aiTk1jYJ77yPq++8wnjiJ+epVLNnZeD35DIagSEB8aI19u4PLjpdCwz1J8s22NjoJ1bqrKBw2BoS353JlHivSDxHrHcyIqC68dep3qpoMzGwzgDEx3dGp3akw1dNkt3CxUi5+c9sPZ0X6IRwuJ4m+YVyqzOWjsxtY0H0SP17dQ7egOPIMFSxL2cfsDsNwV2mwOGxcrcrH4XJSbqwDoK1vOP0jOlDT1MCWHOncLGqsYnf+hWavF8xqP5gJ6xfRP6wdFocNT7U7KoUSh8tJVZOBxSMeYH/BJZ47soxO/tGMiO7MO6fX8sKRZQyJTKK82ZtV7gnzDuSgGT0BrSIfrVrD2oxjWJpnT54tz+aHKxKW2ze0LVq1G4eKrlLZZGDp1T24qzTc3m4wKdUF7Mo7j07tTvfgeE6WpgPg5eZJl6BYSow1pFYX8kyv6bx9ajXV5gaabBZmtBmAm0rNS31nsjXnLAeKrsjr3XxupsRLN1mMTzCZdTImaXz6WvRuJozd5tIlKJbjJalUmxswWJuwJW9CfeZ7/AOjsFYbaHNoDlyNF1+TuV6GPB/6QJig3vfK/We+E8+QxcAgQxYlDhf9VHYJFS06J2+ygDbiJVKqJf+q/Ir4rt6PFX9RcEeJfzjykcynzNglkt6cdQL8MnaJ/Bc7SDK8qrMkm6vHXMkMO/yhmPeVagGLZ34Q1iq8ueFk/f0iHbYk15cnC0jp8wASq+gUebXFT5a5U9gjfRCMeAV+n93MAiqFOQrtBm5eIk2a6ySOAcTk3/t++T1rLyyfKn6v1M3QZZbEcVxaJUxiyQVh6EDOR2mzb8phlRmVQ5+VRPqabEnBH/maAKZuc6SDc8s/xLM27EUZju7hC9YG8cL1mi+drZF9RG5tSf7vNFXApqFZWj39raTWt7Cdge0ELJ/9AWqzxWfX/1FhJfe/KcfWcmFcPU/YwuEvtcrOKZulyzNj1x+BWHAHAeV2s3Ti/hkQ2/aUhPR6h0k47/VlrIbfbpV99Q7/XzUK539D7c67wDunVt8QDRTq6cuLfW+TqR9/Qf344483/P3ee+/Rv39/kpOT6d2791+yzevrZqDr37yaLl+m4qEHaNgrwYYqpYK4EA8CvTWE+rqj1SgxWRwUVYtfSNevL+0uXiDw/Q/Zf7maY4fTKH7+BRr270ep0xH83HPYS0qw5uZivpqMzy1TCHj4ISI+/pjz2QaudhyJbfMRSu69jVFrX+GWTW/haJ6FmFlbwqITK5nXcSST43vjrtLg3uzZGB/Xk4e7TaDMWEuT3cr7ZzcQ5RWI0W7hzu0fcbQ4hWd7TUejVLM87QD9wtoR5xPCgPD2aJQq4n1C2ZBxgp1550mvKUav0VLYUMUPV3bzYp+ZPNRl3LVz4mwOm+0d1oZHuo6nxCiG6aGRSeQbKtmecxatSoNOoyW1upAyUy0bsk+iViqZ1W7wtYHfFytyOFqcwrbcszRYm3Diom9YO3zddZgdNg4UXGZ+x5HEeAfhUsD+Kf143ZGByW5hRFQXKpoEEI+I6sL9ncdcS+hPri7g29GPsnP669eS9i0OG2szjjIooiO9QhI5VZZxjSXzULtxvCSVZ3pNx8fNk/fPrONYSSpKhfLacamVKpKrC/j03GaSqwuu3b960rMsHv4Am3NOsznnNAm+YZye/QnjQ+Lg5BIS8g6wLf0w6zKOMyC8A58Nv59l4x7H4/S3UHCcO+KuMve5J1Ba6sQLdGW1BJ1eXQ+pW4WlMlW1jv7pMAW0vjxRdYYTResYbKuBH0ZDmsRloNaKid1uliiLJ1PFCwTCRjUfE/6JgEIYtzM/inRZlSERDYFtJC4jbZuAjf6PynMaSiUOw1wPnW8XdixusAAfi0HATksgaYfJYuYHAQV+cdK1qVCKzyiuWaJTusHSMeK9KjwpwCf/uDBeDaUCpJ7Lhbs2C8uk1opXKn6oAIzuc1uPu9tsGPmqyHttxzZHV+yQ2z27Jbdt7xsCirrcIYb4gETJRGvp4hz0hEixB98Vlmr8+8J8ab1lfTaTMHT37xd5cMVt0vFafFaYvdLL0gXbfrKwkLV50vxgrpfu1DnrJJbixJdyXjpNE8Bzfjl0ulX2KbiTrO/QhyJLRvSUfWjJBgM571H9YNBTf/zQUmnEFzftO5Fv/6z6LxA5u8Mtf3xM6y0soF+cnJ+b9W9Tu/Mu8NiB724AYQDlpjoeO/Adu/Mu/I/sR0NDAwA+Pj7/I9u7yYj9Dcpic3IouQaVUsHQTn6oVa34uXb1aozHj+NsasK72TjfNdaLgkozJovjmtSmVCquPUehUNBotlFvshO0bgWGXRsxnTmD14gR1K9eDS4XqoAAvEaPQqFS4ffoQjRqJX4FjVQYzPj5e1Niq8HpcmF12Km1NGJ12FmecoCdeefxUF+lyW5Fq3anjW847w++iykJfVEoFNyS0I+1mcfIrCnmVGk60V4iO5Sb6gnT+zM0MokrVXkSTmqqZXRMNzZPfYVpm96+BjwUCgVFjdXo1O5UNRnYknManUZLWTMT1jEgiuTqAjZmnWRj1il+Hf8kxY3VmGwWDhVdxWAxYXPaMTtsTIjvhb+HF8eKU/HV6mjnH0kbv3BqmxqoMjfw4dkN9ApOQKNUcbUqHz+tF3M7DOeHK7tRKhT8knqAT4fdy9TEfuwvuHzN+K5QKPh0+L3ct+tLTpamsybjGLmG8muvQZmxlm05AvBAmCuT3YrJZqHCVE9JYzUu4Nne0/ni/FYcLid5hnIyasXMrtdoWTbuce7Y9iE788+TvamMHiEJmOwWPNVu3Js0mvs7j+FiZS5rM8XonegbhsFios9vT/Jgl3HcO/ZdNhdmcLy+kpIru5iRsYZxVZkyGieiJxSeRFGdjSp7r8huWl9hq7Q+4k+yGEReHPQkfD9MJL0BCwVohXaRGIXEkQIa1Fq58F5dK4Or+z4EXtJde8087nII2AMBOlG9JVqi22zJFLPIhyONFQLQGkrluZdWCntjltcfNx00d67iEyXA5PIqCZUN6iA5ZXX5sg9J02Uo9++zRXLsdQ90mi7r7nk3/DROPGn73mgdCD7mHfGKGYqFdVNpRE5tkNw3Rr8p5yhzjzQOgASW7nlZGKUed8GUxcJ0nftZOv5M1bIPHr5yTtuMFvm1+1y5z8Nfji9umMyOrM4UufbWpRK26uYJW5sz3ZpqhQHMmSfNDPHDoOd88ZGtmi1MVbtJAmJDOkreWvYBAXnuemH8KlIkoqLjNJEHgztCZA+Z26lSyyilugJhxSZ/Jon5zZ81WBrkNQc4/5OAz3+uqN4C5r4eIPNE/3leZMcpcoyNZTcyZtnNkxDu2fnHdd6sv3U5nE7eObW6hYu+oZrdk7xzeg0jo7v+pTKl0+nknXfeoUePHrRt+yds7V9QN4HY36DMVgdGs0QRWGzOG4BYwN1342oy4zvz1mv3FVdbOJ9jQKWEge19aefyJMjH/YZ1Bni50SPeG6upEjug9vUFwHviREwXLuAzaTIKlYrLeQayy5roGuvF1rJd/JK2n/eC7mJyQh82TX0JnVrLtE3vUNNkoF94ewI9vBkS0enaSJ/fUg+iVWmYnNCH5KoCOgZGoct1x+ywEeMdzBM9JhPi6cec7R+zPfcsi4c/wJyOw9iUdYpKUx0FhkqOFCVjddivTZpp7x9JkKcPWpWGfQWX8HXXsbfgEgoUJPqGEeDhzVsD5/Dwvq8BMFhN2F1O6iyNhHr6UmsxEusdQq6hnNXpR0mvLSZU58fO6YsYvfYVyk11DI1MItDDm3WZx6/NkTTbrRwsvMKSS9txuJz4uHnisMtsyWlt+vPhWfHQqBRKbm0zEH8PPSqlEpVSiaW5gzLKK5DPhz/A3Ts/I89QQZCHD5VN9XQNjGNoVBIRej++u7ILlULJJ0PvpXtIAh+ckfUeKrzK1MR+GMxGpiX2J943lD5hbTlQcJnMuhKa7BZe73cHabVFTE7ow578i7xw9JdrrOQtCX25WpWPwdrEidJ07h2zkFmdq6m8sJVxER3glzGAiyvnVtA5ur8Ytt31wtDEDREmyOmAR07K77mHREorOC6xAQqldPylbJaB2yDeK4sBlBqsFgs15w8Q6tEgpn2nUy7kLf6ssG6y/uKzMibo4SMwawUs7i4X95GvtjYLfJYk3ZInl4hkWZkuXiiQHKnxH0DsUMjeI8BC5S4X+/DuMnOy5ILIW0+lSQeluV6e6xcnA8itDZDQbCT3jpBz0FIevgJspn3bOjMx7xjgku2UX5W4C1ONgD6FSkBnC9vnsIq/qcNk8UodfKf52O1iin/oiMiNV9cIYLxvj7wOpko49bX4oo58Iuzexoelc7PvAwK6QPxi9UXSiJA4CkYtap0BmjBMmERzrYBYv3hZFy6Z62k1CrPVdjxk7JD4ixeLWyMsVGoZuO0XJ/Jv3DC5vwWE7V0kTQhdZgn4PfIxJI6WOZqmarh3j8iNIL66ihRhVv8ZiJ1YIiC1+JzMsQRpzlg+Tc7jPy7eOFD8Zv3t62x51h+YsOvLhXyBPVueRd+wvw4gLVq0iMzMTFasWPGXbeOf66Y0+TcoH52Gvm196N/Ol5zyJvZfrqahSbxHith4Sh56haKoVlnA21ONu0aJt6eawyl1nMqox+744/eMmGAPAoYOktDW/v3Jv3s+jYePkPfuc8x1T2dj1kkamwGg0eIguboAh8vJoaKrDFr1HKvSDhPg4YXNaceJi2MlqVQ1Gegd2oZqcwOZtSX4a70YEpmEw+Vi7o5PeOPEKprsVqwOG0vH/oPvruxm/q7P6RIcR7jOn/b+Edy/+ws2ZJ1Aq3ZjZ955lqceYGBER5wuFz2DE/h53ON8PPQetueepdFmZkhkEtFeQbhwkVVXyoasE9dAGMCqtCM8ceAH3jm9lhpzIxaHjYnxvWjjF056rXhkIvWBuKnUmO3W5r8DeKzHFKL0gagVKsbG9sCJi4/PbuDepNGMjO7KrHaDUStVlJnquFCRQ51FOugcLicP7V2CXuPB7hlvsHP66xQ2CFMW5OFDx4AowvUBKIDKpnr6h7Xng6F3U9RYxZMHf0StUBKg9WJYVGccTgfdggSonCrN4L3BdxGq92Pq5rf54sJWPh9+P92C4vFQuzE/aRTJNYWsSj/CmydWEaLzRYECi8NO75A22J0OeoW24fk+t/J6/zsBiNAHMCyqMzpPP2rGf8g33p24MzuF1DPLhDlpycyK7ic5Vp4B8vfoN8C3ObKhOlsM4i6njMS5JJEhxA8XVkkfCk4bpRve4re8bmQFTRev1g8jZLne9wnT0nWWdOgBVKVJyrrTITlldqsAiAkfyHacdpyGUnDacam1wtg5mpm1oHYCdrYsFG8ViCdr9yvy+60/icSGS8JelWoZFt52nLBTgYmSSRXSUZaPHSTetphBAvCOL5ZQ1sMfigfqyz4ypqfNWOmo3PmieLncdMJ+Tf9OJNse80UyLDgpcypLLggwVCgFhIEweI0VYrKPGyrnD4TVAon86PeogFJ9iJyfylS49LtImJ6BwiAe+VjM9eXJAmjWNueDTfkCns0RL1f7Sa2Duv1ipXv1pwmw5TE5h56BkqavcodNCyTdvyJNPHW5h2D6D9I4kd7cGNNQLgD00gpZd1B78AqTUNiyK8JutkisICzawMfk9s/VZaZIm30ebL1PFySg2Df6xniM/6psZvh5Enw3rHW00836l6vKpvr/1uX+v9Qbb7zBwYMHWbZsGaGhfzIl4i+qm4zYv3DZHS6SCxrw9lQTFyKdG2ez6rE5XFTUW/HyUFNWaxH/V7VQu4lhOrw91UzoGURehYnaxgaUytYvrP9c/nNm4zf7TmqWLcN08iTm1FR2tNeQVVfK5uzTfDOyD+V1Zny9lHwYOJ/jJamUGyV09HBRMq/2v4Nl4x5HqVTy2P7vyakvI6eujEe6jKe8qZ7X+s/Crbm1vFNANBm1xdzRfijpNcWYbGZy6sowO2yUGWspNdayKfsUNqfMoMTlItE3jDkdhmFx2DhSnEx6bTE7cs+xLGUfQR7CivUPb0ffsLYsS95Hak0RydUFWB12IvUBNNia2JF3jgidP/VWE402MxPievFAl3HE+4Tw5KGlBGi9iPcJwe50sLD7JN45vYb9hVd4vu9Mqs0NmOwWEnxDCdB6UW1uILW6iO/HLuC5wz9jdzo4X56Nu0qN0+VEp3bDaLdSa2nkSlV+8/xJmicOQEZtMQNXPku3oHgS/cLJrC2hZ0gCoTo/rlTl4QScLif1VhNvnPydzdmnUCAsmwsXRpsZo80CgNFmpspk4HxlNk6XizCdHyabFTeVmhBPXz4/v4VQnQ+lxjoUCvj8whY0ShWX5i2+JvOeLE3n8QPfo1Gq2D3jDbaVlBJitxJSlyvymtoDg8XIsqJshty5ka5BsXKRP/S+ACyQOYo95kmn4oXlrcb44A7C0tyxAk5/T8nFMrr4FuIRPhgq10N1Dlib4PAHAkaOfCwSpptenqtSC/v0yHEx5J/+TuSqpnpQurG3JA57cVv8uo+lv4evgBIQKfHqOgGMdguMe1fYl+pM2de6QpFPQTxf496Ti/W+10Wi8wyQ53n6w4NHRXoMbi8AZfcrwmSBgILzv4jh/PxykdjiBjePVdokgOvpdJED07bKtkI6C9ByWIXlG/iYsEdnvpf7Si/KMO0FZwQ8bnpEBpUPeVrYo+KzsKQfLDgrY5Dqi4UlS7pVGEFjpQwZ73ybeLm6zGoeQ+US1iluiLBtReflQ8Eu0jgJI+R4gtqJib/0onj/DCVy3i4sl+V63i1smc0EOGVwOMgsyIAEkTENxXLuHzgor6dCIen8TXUioW54SJojInvJ7Z8r/4TMD+3/qEiULaULhCeShXVb0k8AbkuA7X9UZoMA0hZvYHX2n2/zZv0/ryCP/zM/1v/pcv835XK5ePPNN9mzZw/Lly8nKirqv30b/1ndBGL/gmWyODBZHDRZHeSUywdldJAHdocLvVaFQqEgpjkXLMzPnehALeV1FtKLTYCCjlF6AHKbnxvm545KqaCmQcCb5p+CX612F6rxU9AX5OPq1Y2F3Qfir/Ui3ieUIyVX+Pz8FgoMFSzoNokJ8b041dzJl+Abxpbs0zxz+CfGxHQnxNOXnPoyaiwNnCzNoLKpnhFRXfjgzDo6BkTzy/gnUKDglk1vk1FbTI25AbPDRoJPKF5uHpQaJWbBTaVGpVCyt/CyLJ/Yj/PNmWCNNjPPH/n5mmdAp9Hy9KGf+G38U7zSbxYL938rwa2hbck3VOKpdkev8aC4sRr3ZkC4PfcswZ4+GKzCYFWbG1idcZRgT1/MditOlwuT3czj+78jQh/AhPhe3Js0mjqziWUp+zhZlkajtYnHe0zhcFEyh4qucl/nMbw9aC5Op4tXjgsL88yhpbw1aC7xPiFYm9maRpuZRpuZw8VXsTUDBxUyrDynrhx/rRcv9ZnJttyzrMuUQdbuSjUuXDQ5rJwoScNfqyfRN5zb2w5iU/YpnC4Xeo0Hw0Pbsif/ElaHncy6UlJrCgGI9Q7hrYFzePzAD3QKjLkGwnA6iMZOkMtGiK2RQJeNLdNeFaDwUVvABR0msUwdwld2d7Yd+5Wdt77Z+saJ7CVgIveQXLydDmGWBj8tfquTS8QY/sRVmPYN/dKiUIQZICYcEn8U+fGncXLRB3mu0w53/A4JQyX7qjZXBlBHDxDWJ7q/DI5GQXv7SYrdmvBRN8GqO4WB6n2/gJrN5+GxKyLpefq3epbcvQTYgMRKdJomnrAzP8i6E0YIIErbLj63H0YIA/foaen8dFgElD1fCF/1FV9YQKKAseXT4Lk8GPAPAWHXjzcCYYPStuICtlQPQL31NBMWDhF2MPeQGNOrM0VWTNnUyh4deEfYyFGvw0/jhdVZPQ9i+guQC+kMB94WVrCmOTvPaYfe98gYo/jhkLNf/GnbnhSp1OVofR2D2sk+Fp8TBs0/HsZ/KLlqvebLeRr6nJyXyD5wZzPj2VQr3ZUtHaoAw56XGZy/TBJptKlW2LtOU+XxFlDaVNe6nn+u88sg/6gAuOuBGMh9GTsE7OUe+a+B2JbHBIglDJfX+SYI+5etXiGJhHr6Um6q+1OfmAII0fnRK+S/v0Fj0aJFbN26lSVLlqDT6aislC5mLy8vtFrtf/v2/rluArF/sXK5XBy4Uo3V7qJXgjehfm54e6hRKRUUV5upNYqEoVQoaGyyczm/gXB/LTqtioIqM8E+rcNx40M8uVhYxfHqK3hq+5BS0ESAl4ZebXW4qdSolapr22uyOjnQN559pbv5oDSOtqoevHT8Q5y48FC5YXbY+OjcBrblnmFsbA9AvFeVzZ2BlU31+LsLAKwxN9JobcLqsHO1Op/8hkqKjTV0X/44QyI7cU/SKBafl+4+JQra+kVwoUIuIKk1hbw7aB5PHVqKUqFgZHRXvr+8iyWXtnNn+6HsL7iMSqlkWmI/duSeI7u+jNSaQgasfIYwvf+1f1IPtRtlplpUKHi53ywWnVyJTqOlvV8kl6pyUStUlBpbZYo2vmF8eVGiBz4aeg+ljTV8fG4jAMEePrx58nf0Gi2eancCPLz44cpuduSeo9YiOW3FjdXUm018cHYdsd7BNNrMVDUZOFGSxuLzm8msK2V8bE8KDBVUmg24XBCg1RPrE8LnF7dc2w+ny8negkvsL7x8bbh5UlAsk+J7s+jEymb2Sk2Tw8qd2z/mwa7j6BQQzbvlB1G8G8HCyV/iTOjLqJhuvHBkGY02My6Xk+iaTNarayDprtY32+9zCE/fwZGWj72Gp2S496H3BVy0GQvlyUzqMJxtmReZWHhALuYDHhO5K2u/mM6tRgkuxQnzNotcd+b71lE+bvK+UCSOlGiJgAQBCpWpst3AtgKQrCa5L3OXdEn+NEGYK42nyGOWeqht9kylbCb60HtEBwGDhsDGleAbC8NfFECh9ZbRQUqVSJx9HhRgcWW1bDMkCR4WoMuul6RLMKy7sDBuOhl6fewLeVztKdlZt/8COYelc/PIJ61NBtVZ8jOyl+xrxk5hAlvS95PlfYTVBFH9qK01kpmqJNK2HywPiYSXe0jM7zFDIO+QMHdTvxbfVvlViaVYcBbuPyBA9ODbEotRkSYMUl2usIhj35H9v7hSvHsNZZAwUrbfQot7hYoMXHpZgFLxWWEjA9rKMZmq5PUf/17re2X4iwKc348Vc37SdIkuCeko5nn1dRerlhmYDWUCelM2CRA78ZV4C4M6iBydf0K2O2CBSK/pO2HzQkiaJqn7Pa97r15f078T5rL3vX/++PnlAp573tXq4Ysb9ufjl27Wv0yplEpe7Hsbjx34DgXcAMZaBJ0X+8z8S4z6K1euBGDu3Lk33P/uu+8yffr0//bt/XPdBGL/YqVQKNBqVNgddnRaFf3btXohwv3dqW30wNtTjVKpoKDKTHmdlYYmB2O7B9I+Un/DumKCPZi88wOsDjsh2iBUhGJ2WBiw8nVivIPZeMtLzduU5essjThcTrIqawlV+BHqEYRTYeOjYfdwujSdry5uJ9E3nPs6jyHBJ5SOAdGE6f1o5xeBj7sH9+xajJ+7nn90n4y3uyfFDdV0CozGX+tFdm0pqzKOkFxVwBcjHmR1+lFKjLXclzSaEmMtZaY63FUapib2o61fBB5qN6wOO3vyL1LTJN1ylaZ6gj19MNrMzGo/hBVpEhI7JroHW3NPYzaUX+sSPVh09VoeWKlJAFeNuYGW5tFDRVfJrCshUh9IUWMVhQ3VqJUqOgZEYbCY+Pjcxmtjhd47s/Zad+OsdoO5s8NQZmx+D1uzr0etVBLi6cuTByWLxs9dT6eAaBxOBzl1pVQ1778LFysnPUuPXx/H7nRQ2VTPsOguTEnoQ1FDNd5uHoyL7cnnFyTqYUhkErvzL+BwOvjk7EZ83Dxp6x9Bv7B2rM88QXFjNclVBayb8gL7vjmEUeNHd3MN7w9ZwMmi5GvRGN7unrDzOSi7glOpQjHuPZFK64sAF0T35yefjvx6bC2v91Ux+OxSuZAFJEDGTuKKz7EzNAnqr0BNX7lYmxvAbgL/WLh/nwSD5h2DX2dAWHMqvl8c3LdXWCkQSS95g0hTVqMwNW1GSwemywnuPsKiVGfBj6OFeWoxkLdETEz4CLY9LSAjtLOY3N28JO6i7JKk6Fdlitm+6IwArIydMGuVxF40lAho6DxTzN9r7hZ/lNZXsrC+6ieZZPnHW4NUh70o/iSVRliqrdd5mtTuItH6xcqw6itrBIiCeKKcztb0/QGPgsOOz47nua1tBFGqIpndOHejNAOUXpARSiqNZGdpvQUQrpwl220sl1max7+S2YsVKeLHihsKQW2g+zxhIcuuSoyH1qd1xuPIV5qZuywJ1D3yMczfISD46wHCgu58XkDV5MUyHeDSKpksENlLHr+6XsBw/nEBYmWX5fUEmXnp4SfS3+CnJHHfYZV1tPjc0nfIfsUMFIZq7XzIkogW4ocJSDdWyHvp/oOgbv1SeUOFdZXbn1VFKmxeIL9H9BQv48DHhRW9Wf/yNSa2O58Pf+APOWIhOj9e7DPzL8sRS09P/0vW+39aN4HYv2AN6+yPw+m6YXZkUZWZ6gYrHaL01+6PDfbAZHEQ5uf+H62KO9oP5WJFDv1iI/DT+HKmIg2zw0aJsQa7y4lGqWJ45wCsdicDHHeQ3zCSDj7xHM7O5fcJzxPkLaNbeoUkMrvDMN4+tZqPz27geEkahQ1VrJz4NOF6f3LqyjBYm1AplHio3Wi0mnlw71cEenjz3egFfH5+Mz5unnwx4kGKG6vJrS8nTOfH/V3G8cV5AR5atYbBER0pM9bh566/lrKfXF3I/E4jWZa8H2fz96RjxSl8PfIR0mqLmN5mAEE6b06VpF9jqEDmLzoQtmtyQh+2Zp+hwWom2iuQYVFJlBirCdX5kBQYzc688wBE6AJo6xeOWqEi0MObMmMNTc0Gfn+tnlXpR8iuKyPeJwS9RktaTRG9w9pyoiQNFy7cVRr83PVsyz1LoIc3Vc2MIcDAiA4YbWbclGocTicuXFSZ6vlgyHwmr36B8xV1NNmtlBpr8XbzYPGIB6g01fPKsV9psDXRMSCazoExfHFhK0Mjk+gf1p75SSM5VZrBo+5xqMLieMQ9mkcddvptuItumnguugcQ6x0MYfdiPrOUB4uLMGx+h7WTX0A1e61EP+x9jV0heoq1QewrvMzFhOnENRYxofgCSrVWDNtxQyQQNHG0MB6hnQTo5B4Rye7SCgkxddqkI9DlEJktZaNciG1m8UiBgCpTVXPn5WGRA8uuSlSBzQSZ5wCXmOqrswUwnv9ZZMrM3dItV3AC+i8UtujXaQKkQAaOe/iKcV+lEdbFYYPtTwmYUajE1K71ln2vTBPmptNUYfnM9cI+WY1yrKZq8Y7lHRGfU/QAMeArVGLI9wqRLlJTtfiajn4i+zHkGYn1UCoFbKZsBt8YiYZRqYgKD4DSImHsVGox2JtqhJ3KOQBN1XI++z4sjKJSLUxX0Tlw2SGihyTaX/hN2DSNpyTl739Ltu/hL6Cn4KSEyA5+WnxzTod4rYwuWUYX2MxYlssxOG2yrQu/yrlJ2ypAbPU8qEiGxDGSwJ+2Te4L6ybyYXAH6W6tyZGYkpbE+9GLWj+MJn0Ka++Rjtp9i1pN+n0fkp9Dn5Eu3NzD4mNrCYf9vynfGDlvLlfr/M+bIOxvVWNiuzMyuuv/aLL+/+u6CcT+BUulVKC6LvcL4EKOAbvThd5DTUKoUP+e7ip6JfpQZ7RxKqOOuBAPgq+LqXC5XEwMHstofydhOm9USgXDopNYOvYfhOr80CglXbzaXMeegotMju9Dn1Axvb97Zi1jKrqzeMQDNNmtHCq6isIFm7Mlod5T7Y7JbmF/wWUWX9hKlFcgk+P7sCXnNPfsWkypsRYXLqqbGqgzN2K0WXBTqQnT+7El+zS1lkZUViWXKnMYGdONPQWX0GkkCqPEWIO+eXaeu0qD2WEl2MMHjUqNAgjV+fHckWUEengzr+MIqkz1nCnNIKWmkPZ+kXQOjMXssHGlMpdai5HsujLuSxrDjtxzWB12Chqq6BPWjk4B0dfGLIXp/Cg11uLl5sGp0gzsLgdFjVW8O2gedeZGjpemMdpdzU9ZZ3AaK0hvrKdXSCKrJz/HpYpcPr8g8mKCTyizOgym0lzP2JgebMw6SVZ9KTHewXhpPJiz/WPsTgcqhYJX+t3JlMQ+1JoMdKu4gE6lZ6F3d7oEjaF7cAIAGpWa8OaxTrXmBgzNnZlGm5lDRVcpNdawaMBs9BotjTYzX1zewV0dBmMx1lDrL0GpAR7e/Ojujd+oDzh19Bc8DBVYnXY8vEIkpyplE4uaCthjLmViKYy3uRGtDGKi8ZS8kbL2CVsy6VMBYeZ6YTtAjO2nvhF2JmawLBM/DL4ZJGCmqtmztHmhyIKBbaEmT1LhUzaK56r/AmE4dr8ikpmpSgz15cmSsB/YTkYUpW8XeezVasnqOr9MQBTItnwihREK7S5g79cZwgidXwYegSKluXvJ3+eXiRdt+MsCbFryviKbGbmofmK6bwmbbSiD326T/b39N2H5xrwhkmlVOmz+hwAhrzBhx/o82CrRlafI845+JrMTXygSdqu+WABV5h4ZiK5QShAtyLZLLkhnpLVRgJ+5XmIq2o2XWAuNp4CV74bJ/hSfF7bPaZM8t+JzAqpSt4gcWZsHuCQOwuUSCVihFJ+bQiVNFUqNSKX9F0iAbr/msFy/WAG/XWYK81We0trpObg5tFXlBij+vKPRXC8+N0vzFxOlWti0mlzpzgR5Xmg3AWItkw+uL1ONPKf9JAHA11fqFpFzR74Gd2/943Nv1t+qVErlXxpR8a9WN4HYv0CZLA6ySo1EBXrgp//z4bVtwj2pMtgI9f0j+5VVaqKkxoLV7rwBiDVZnWSXyYU7JsiDoGb/2IDwDjc8//UTK0Wqqy3hzYFzOFYi3h1z88X2o7Mb+C31IIPCO9A3tC3dguOZnNCHMmMtLkRyc+FiRHQXtuacQalQ4MJFv7B2vN7/TsJ0fkR7B9FobaLebOJosaw/XOfHA3u+IsY7GKVCQU59GT7uOhQoeL7PrXQMiEYB5BsqWJtxHIvDhofajTxDBQBVTQa+vridT85tpEtgLPE+oaTVFhGi8+VIUTKuZvbs9/TD3NVpBLumL2Lejk8pNlbz8pHlzGovo1G6B8dztSofgJLGavYWXATATanmhaO/8HSvaXw/ZiGsu5/bCtdxMHYcl5RBFBgqmbfjU6rNDdfO5cNdx/Nb6iF6hiRSbzWRUy9A4c0Bs/kpeS/Z9WUMiejEbe0GsTbzOEGeXqzOOMZBXRyzzUV8U1uDVWXkwa7jWXxhC0subqd/WDvGxfbgQOEV1mYe591B8zDZLZwtz6KosZofr+5mxYSnuX3bB7gp1Xx5dR8/h4xlWmg8Q/1jqG4y8HPyPgaEt+ebUY+g13hQ2FBJW78IGQJ9zy7afdGTdvXp0KYv73adicPlRKF5QC64Rz9tfkPVyc/9b0k2V3Q/AS7HzCIpmutg6xPCdFibuxLDu4lf6coa+dtcD06rmD6szexlQKIwcxd/FbAwf5swaHteFdmv4xRhctK3g9YLvughMmXOfgESo9+GPS8JEwfSCWiul+d0mQUdb5FOTk9/8VT9PEHYnz2vSiI+CNj0jRFjt8spw7ZNVWDQw4xmb1lGc4hoVYYAKJsZis5KtIOhSLLUEkaKvNZUI8Ds0iqR8fYniwE9/7gAkiX9RNZ8/IqY45UaAVB2M7xYCrteFP/W3tcEtMz8RdZ18N3WAeQKJbxSBfM2SaPAqa8FGDodAmZiB0m3Zdp2MfHPXivnPbQzLJssy1RmCIByueT4/eNama3blotvTaOVbky1e2vjwcB/yO8tI5NsZpE9cckxXF9lV+GHkQK4WholkmbCT2Pldco5IKGt55fDicUCtCZ/xh9q98sCWLP3w6zfbnxs/9viL/SJksHwN+tm/Y3q35fr+xtVerGR7LImLuc3/IfLxId60jlWj04r3xTNVgfH02pJKWwkPtSTEF832oTpri1/Oa+BCzkGEsM8SQj1IMBLAF5hVROZJUZcrlYrZJ/QNug0WnqFtKHW3MjhomQAZrSRkMUYb0m/L2io4lRZBrXmRhJ9wxgU8f9j772jmzqw7f+PumS5995tsA3G9N57SQikh5DeJr1O2mTSe8+kJ6RXUoAEEmro3YDBuODee7csWf33x5FtCGTee9/fzLyZtzhreRlLV/fqFnS39t5nn3TyPABmUlQ6AXpv7hq5mG8W/pknJyzjL+MuZl35Qa7d8DrV3S209nZz7cY32Fmbx4jQRC5Lm45SocBLrWVu3HCmRQ/lrhHnMj9hJI/s/pKCtmrSgmKYlzASL09S+ojQJKKMgSiAEL0fBo2AS6VCyUWp0kHV1tvNc5OvZHp0JgDt1h7m//gYxR11PD9FDMCNlg4+Oi5joQJ03rw89Vr8tF7sqisgLTCG+fEjGRchbIhWqebZA9/zZvhk2jMvQzvichwuJy29XXRae1AgzJ2XWk9lVxPba47zSd4WPsjdgAs3erWWF7N/JC0ohqyQBGpNrawp3c+26lzeO7aBRD/5du8/7kZ2NVdyoKGI8s5GKjoloHNv/QnOSx6Hn4dh+ThPZmx+Pu8uKrua+LpwB+8fW4/FYaPbbunPLFP7RqJTavi57CAGtZaJkelMixnKMwdWcu7qp/ilLFsuAHOLZIYBNBeypPBbLrA1CAtyYp1IhonTxWsD0jmn0gsDtvlxuWk3Hh8IcT34EaAQNil5hmc2o1uYrXPflB+TjJ3CL0b8V3pPS7rB37OOD8Q3pdIISDrwvgCW6NEiUdYelLiFoRdIZMSIq2CWp6OzpRAu+05A4icLpLOzT5767koBYYYAYbK+XQ5vjREQcsEKuPAT8VzlfifdmjP+KvMWi9YLgJr3vIAwgC/PlxmSfUGqEZlQvk3k05wvZSZj3o8SAeFhn2kpEjbLZRcg2t0oXrwLPxaJ8MQ6kQQXvCiAyuUQoBQzRtg8EJZM6y2vUygl18vaJft0/gfS4Vi2VbZvboOVywXE9HZKDMjLadKsoDYIa3fbYbgjZ0DK0xjl/JVtk67Rry8VMOWwDjQmqHUiVeevEdlVrRMJNjDJcxx2wIvJ0ghhaRNwZu0SiXTmXyEsTQDulPtElgWPZxFZTnWGL6TRoweOxe9r/M1yfYQOOv25/07VHxv4onG2zta/uM4yYv8GFR2kp91kJy7E8IfL7Mxvp8vsYEyKH1FBeho6bDR22GjqsJEWbWTC4AE5wOlyn8KERQeLzGe1u8guEWmg1d7K2NgYXj28huquFrZd9Aw+Wtn++SkTaO81MdHDnGUGxxNhDCDI4EOtqZUhwXHYnA7Wlh2krEMYny6rmZs2vUWv006IwZd9DSd4ZM+XaJQq7C4nV6TPYG3ZgX7f12Vp0xgdlsLIsESu2/A3Pmn7jVFhyTy292vCvfxx4+ZgQxEfHNvAgsRR0snoee2HuRv5rmg3DreDdqswLxlBsTg8Lfm5LZVEGAMIMBi5bsgcPjy+kQ5rDy9nr0KnEuAW4x1MtamFtMAYonyCeCtnHZ02M75aLy4bPJU4v1BWntjJ8dZK3s75hQ4Pw/MmMKm+ApCZli7cGDV6zPZe3Nh57cjPnJc8jiFBcXx0fBMWh4058cP59sROeuxWLA4r9T3tjI8czJy44SxNGU+cbygapZpjzeXcMmwBCoUCo0ZHZVczQXofVAolFruNMKM/TZbO/iiM0RGpXD90DrWmNn4tPwTAJYOmcO+oJRxoKOKH4j18VySp5AsSRnFtZCL0tKD0zN5UOiWPDN9I8WNV7RPwU7kbDn0sOVTTHxLD+ZT7BoY8D5onSfEH3x9IpHfY5GY74Q7JE8MtN+3OGjGc4xYJ8/trJFD0mKd7cdTVklG1/QWY94JELvR2igSl1ovMeWylSHvzPxGW58D7IlF21Uqn39cXi7w252mJKNAYYNUNHhnMLcALxETfN9Ra7yeMU0+LbK/S00GZvnjAgN5RKRlnzYUC+sKGyLr3vyfvty9tHoX8VOwSWS/tXJlNmXaOMHqjrhHJsqNK/Gl/GykvU6pBZ4Tdr4sny+kQybejSjo8+4Bt1uXyWMYSj7+uTUzuraXyd/QYmSww/Ap5/4nTpbtUqYYvlgob2JeYX7lXjqVCKczhgfdFGlXrJPVe7wvXbpBB5xU7ZPtqPVz5s3jETp79WLQeNj0i67or/9Q4iqPfCotWshnmPg3XbBDAHZQ0sExgAqy+SZo8rlon7F1klsyRPFMNXijAtqP69OdMTfKFYNsL4uH7n9Sx7ySgNzxTphqcrbP1L66zQOzfoEL8tMzIDPq7y/Q5xvo6HKMCdXT2GPA3avrDQvtKpVQwPNGXbouDiMABqVKrVhAZqCOvuY4nt6/g2qHTef+YdHjNiR9OSkAkFruV1SX7CNR7o/WMxjnQUEx9Tztmu5Uo7yCifYL4PP83XsxeRaJfGB/MuY0E31AONhSjddgYFpLAqpJ9gCTWJwdEcNvwReS3VtHZW8pjEy9jbHgqc394FKfbRbxvKNauJsK8/AFYmDCagvYaDjWUUm1q4cuC7eyuzeeZSVdw/aY3qTO1cdngqfhqvXj32K+oFUq+LNxGjE8wlw2eSqiXHyuLdrG27CDxnkHb/jojw0IS+ucuXjx4EuUdTWypPsrn+Vv7j1GPvZe7t68gyT+c/NZTP/D9dUY6rD3srS8EhJ1bkjKOwQHRdNrM3LLlHaxOB25krmMf6JwaNYRDDcWkB8cS7zlOLrebZyZfwdP7VrKqZC9KFLhwc6ixFJvTTo/dSl5rVb/3674dH/cDzW6bmQ0Vh5kVm8XtI85Fo1RxiamVnOZyak2teGl0JPtH9r//BQmjeDgqgZJ3Z+Cj9+ZTUwONKi8STZOh1CbM0ZClAhzUOpHvSjaJDwBtKdkAAQAASURBVMdmEmnK66Tr88QvAgxAJEmfcOlCbC8Xb1FougSRupySaH7LAQEiGi+5+fY0DQRsxk8Wf1ZPk6S8B8bL47UCLBl/m0ibIIBAYxDpsyZbTOi7X5d5lqVbhSmZcKsAypwvxWc06wmJOSjfKQOw+zLU7J4g09S5EsHQF0ILMP52kfMaj8s6faMkbmHL4+KrihopLKLZI4We87pIji2FkmPWWiIALjAJbj8sXq+tT8n7mf7ggLdqzA0i7x35QpiyvtL7CSgD8cYlTRNmSu8/ME8zY4k0Ibid8ttpEzP+nCcETC19TyTTuiMQNVpiObxDZFD4rleFUYsdL0C5vRwZsN4ir+3tlEHnhgD40x6RjtU6OUd/GwHDLxdwemK9PKf3g1cGC+Bc5JGxJ9wqDF7CFPlboRxgBfuqtUTAmsXTIDF4kfjf+qpgrfjSpv5ZtlGxS5i28p3SDdnnwQOZilDw8x8PEf99VR+QdY29UZolwONxO1tn619fZ4HYv3l1Wxwcr+wmIcxAsK8WH4OcMo1aybAEX0BkSoVCgU4zoDQbjFYC/bSnmP4VCgVjU/35ouZbrE4rwe4E/jLsekp6C1lXls3mqhyuSJ/ucXzJaKCc5jLuGH4uCmBN6X5KOur5sXgvs6NHo1GqGewfx8TIwTy9fyVNntEThe21BOq9mR4zlK3VuViddq5a/xqXpU3lrZk34acz0tDTjs0zW+/6zDlUd7VwdcYs7h21BG+tgdFf3g1Agm8otaY2jjZXsKZ0PzHewTSbu3C53eyuy+f8lAmUdTZwvKWKKVEZXJ85l1cOrSbWJ4SRYUn4a41UdDWiVihZVy5SXFZIAtcNncvqkn38ULIHBTA1eijbanJxul04nS5Gh6VQZ2ojMziewUEx5DSVcffIxXxZsI2fyw6iVCgJ9fJjSfJ4lv/6CrXdbcT6hFLcUUdlZxNba3IBCPXyQ6NWU9LZQInHLwYiN6YGRPWPVBpe2oq+187xoTHYgFlxw1AooLyjkR21eUT5BDE8JIFDTSVUd7eypfIorxxaQ6e1hx/PfYiZsZnkNJezt66Qrwt38HPpAWpNrUyKTOf5yVfy7s6PeDtiPn5uO9sy4wivK8BUuAPvE1+LBHfpVyIHzXkSPjsPcMuNeOfLAhJC0+U5t3uAzQoZLNEVIOyM2wkvJgngcjsBhQC4dXdL992Iq+RG7bQJ69HbKaxKkydPrO6wMB6jr/NERgRDUKIAQZtJ1vHNZTKKxxgMKGU7854HX09m16ZHBdhMe1A6+zb/VdiuMdcJQ+RyiBw663HpvowcLjdlc6vkfK29S/bFaZWA2fSl0F0rcQwHV4jHyWGF6Q+LZ6unWRi9qj3CRK3+k7B2oekCbjuqBdgawwRE6nwgeiwU/iTgDYQ9AwFHGgN8eaHHu7dRHnfa5L17BYksaQgQpsnaLZLjkc8EpM58RJL+tz4j4a+DF3oM+goZFF6xW17bXS/HMu1cmXMJMq6ob+ZnV53IreZWYbHUOkmoP/yZgLa8VcLK2bph7KOyvtpDAoC/WSbH1jsEwofIcSjdKhKu3h/uLR6IpUiZA+evkFiLLY/L+eq7nkDAfG+nNGGM+5Psz6S7JYbkZBAGsq0bt5/6WE+LnNuU2adLnT9cK18mFAppNgjPHMh9O1tn619cZ4HYv3lVNVto6LDR3evsH3N0cpmtTjYfbUWhgNnDhLU4Wl/PDduex09vZPMFT/aPGOqrl6deS159CxU1CrTAQ2OyuGv7+4CMj1i/9HG8tXpmffcIZoeV4aFJXJ85l/SgWG7Y9Ca/lGUz2X8Sj6c+TJi/jl/KD/FlwXY0ShWPjLuEJ/d+Q7vVxHnJ4xgUEIVOpeZYSyXvHV3PuIhB+OmMVHY14/Akyz+2+ytMDivlnY08OPZCOqwmDGotOqWaco8xf0bMUD7N+w0F8NPiv3Ddpr9Ra2plavQQtlQdxe5ysLJoN7tq86nsbibCGMCP5z7EVwXb2VJ9DJO9l16nnQCdN+/OvoU9dQU8sPNTvDV6/jx6KT+VHkStUOJwuwgx+GJzOeiw9rCjNo9mSycFbTU8d+B7np50BWa7jS3VR1lfcZhzEkaT01SGG2iydOCt0fPS1GvosJrIba5gRGgiaYHRnJc8DpvTzoaKIxg1OpL8Igg2+GLU6Hh5ytV82/wBu5PU3B03Dqe/L063i/tGLWXop7fidLu4dshsLho0iUvWvkB1dysqpZI6Uyt2l5NzVj3B6PAUdCoNVqedx/d+jVapxk/rxeLksawp3c9b5UdAoUDrFYRyxoN8dc+tJFj3Mz0MD6g5qcb9SSS80dcJs+S0SzcjSKdjyWZhD87/SB6rPwYfzARcAnQcVrnpznkGhi6VmYyFayXiQKkEJ3LjNIYMJN6DxCm0VwgDNfluYa0OfSJsWmuxACybSUCP0wYoJe7ixLqBcM+SzcLslO8U0AjCYplbJI6i6FeRWSOGiTTXVSe5Wm6nMFvHPPJanyF+69MCOHR+8vyaW0T+nHKPAJu2Uk/npkJAlNspcxVvPyJ+tzdGyDKJM6S5YOszA+OV+mTdqBFwolH2zWkT/5ilQ45bySaRM+8uEPDz/lR5z8Mvl6iL2PFicg9MlHOy7x0BRkUbBOiZGjwJ/wphr0JSBdQ15AoI6wOMmRdA7vci1465Hha9Jg0UJVsg61LxmZVtE6l45qOyrePfy+8pfxZAu+mvcp4DE6WLtmSzANaU2dJEoPeTztERl8v1kbdK1qfzkXUnzzr1Ohz7J3k8ZY78rdbBrEcFYG19RtiviMzTPhP767urhHmd9qAk/p9cGUvE35YwTf4+WTI9W2frX1xngdi/ecWHemG2OokMPPOYBbebfuO9GzhQ1EmbScOEgAkcMR3CdZIpv6+0KjVd7nZqrCbiAwLRqEKZHTsMpULB+SkT2FqTy7HmCi5KncSmqhzifMSsnxEci5/OC5vTQbO7hjeLfuKilKksGTQKb42eBL9whgbH9Wd5zYkbznOTr6Smu4VbtrzLifZabt3yLnq1lotSJ6FVqrG5HCT5R8hsy7IDONwuumxmGQyucDA7Ngur087DYy/mnNVP0uuwseSnZ7gwdQI2p5PL0qZyuKmUPXWF2F0OOmxmpkYPYVJUOgt+fJxuu0WiKyoOUWtqJSMojkf3fMXM2EwUyMihJ/et7A9nDfOM2FhdvI9hIfHYXc5+ie9ocwVX/PoKN2bO42BjEV02C+/lbuhPgI7xDibU6I/JZqHJ3ElmcBwfHt9EcUc9782WGIBZ3z1CjamFKO8gXju8hpKOeuwuJ8rMDKg/QYmyl5+O7ECn0rDj4md5aOxFnGivZX6C+IqGhyZxtLmcvNYqAnTejI8czJrS/RxpLuerBfdypKmMVw6tJsEvjO/PeQCFQsEX+dvkWtLpWRkTh9blRKPT84l+MMeyLuW2RXef2rWTOhdS52K2dOLVNzR75ZUio9V5IhIihsMv9wqoqD8qN3eNAbIuEw+VoxcCYuSx5NmSN+UTAb/8WW6eByU2hCn3C9jrqpGb4ZL35ObbWSOM029PDgBFhwXmPivgK2+1gLmOapGwXA6RmaY/LOxKpXjj8I2WENe4SeJV66qVG/+rQ4T1umaDpK+bmmD7SwKyQgYLcGs4Bn6R0tEYPlQM8KYGCV4F2WeQ9T1QBe9JFy6WNgmktffK6B+FSlg9gK56KPWwPvGT4IfrRa69cSd862H7/GJhz2sCZEDAmXeoAD+nXSS+yfdAwRpYfbM0UQw9X4JZQQBNaLr8u3ijgMj7K+GrC+G3J4SxCksXYJixRIBpZ62wRCCD1zuqoHq//N5/Up6XT6QAR5cT9r0r50TnI7L2lifF6D944UCsiFeggLR7CmVftz0twNQ7VIanx3siT4JTBWidXNMflJ/f186XJaakeBPcsPX05/vKPw7Y5fn9u5r9hPyAHNOOqrNg7Gz9r9VZIPZvXka9itEp/qc81tZtx+50Eeavw6hXMWtYEKDAoFVh1KtoM9m5NmsaMcHz0XtkgNt+e489dYWsmHMbWaGJrCndzS/lh5gclc45mbfx9IHv6LZZGBWWzEvZq7G7HKQHxVBrauWLgm1MiRlCRZ2T+5JuJyPWyNelm+h1WcnvKOOhoCVkhSSyqy6f7TV5TIgcDCgI0HnT1tvN8ZZKxkcOoqyzkRNttbhwo0DBdZlz2FF9nCsyZlDf087L2asx260cqBe/zAUpE/muaBcu3NT3tPHTeY+waNUT9DptfF6wjYmRaZR3NvaHpk6OTKfG1Iq/zsiSlPG8eWQtbrebc5JGk9tSQa2plYONRViddrRKFW9Mv4E7t32IWqnkvlEXYtTqmRU7jOW/voKP1sD8hFFEewexp66A4y1VHGkqxe5y8NrhnzA7rEQZg7gqYybddgtmu5WjTeWsrzzM8vWv0G2z4OuRTw43lXLTprcYHppErG8wblysLT8IiJfsvORxDA2J560j6/iuaDf+OiNDguOYvvJhfLQGfln6KN02C3WmVu4fcz5/Gjafid/8GbvLyYaKw+hUGl6eeg3V3c0EGXzYv+xl1AolFocNL42ODg8w/qJ8Jb5FJlApGXfvPTy99ln2t5czdftrZE29S3w/Hy+A8KG8mHENK45v4q8jbuWypn3iyWotlguwD9R8PG/gotR6w9XrYYOHeQjPFPnR1CRDrF0OCEmH5nzJLht6IfhEUKifRIWphkmazXgnzZAb7KGPBUBMvN2TSeWBiSlzxEPkEyFG+ZixwvpsfBjqDgkQ6wsiNQSKP6ngZ2H3IoeLPKXzkfXpfcXA7h0Kt+fAy4OhqxqCL4Np90PFnoE5iZ8sknT7UdfI+9AHwAcz5FuQTwQMXyb719f1FzVK5mS6HdIw4HYKgzXxTvHA1ecImEqZLaGoIIO07zgq0uru16SBInWBgNK8VTLEe/ersq6M80X6qzsifxevl+MRPUZAaulvAuKWfS+vP/qVAEmDp3N086PCap37N/j5TllP1V7pCvWPFSDqGyVAtKlQ3m/YEHnt0a/EsxWYIECy4ZgAt95OuT7cLgGOS94VebT+qHRp9nnUUMh5CPdMX4gYJpJk1R7pYk2dK+vrK1OzSNvRo+V66LsOTvwqIPLv1eI3JcqiryP3j2rVjeKvm/ecsMFn62z9i+ssEPtfLrvDxaHSLrx0KobGeZ9mvP99We0uduS34XbDlIwAgny0GPUDp3Fkki+RoS7+vOsjBgdG85dxF2O1uyhsqaPH3ktRex1ZoYnckrUQH60XFw+Sb/E3Zs5jT10hM2OzsDhsHGkqY3HSWL4q3MGlaVMBaGy3gktLYZWDVMZx57AgFqbIqJEeT3ZQvamNj+bewZbKo1z6y4uEGfxo9HjHxkUMYl/9CbzUOiKMAYR7BTAtZij3bP+IufEjyLvqTUZ/eQ82l4N58SMINvjgwo1KoSTSO4hI70C+XfRnPsjdwNqyg5jsvdy9bQWN5g6Wp09nWHAC9+74iMquJsKM/kR6B1JnasPqdPQf1wCdkQZzB7+WH8Kg0eN0u/DXeTM7LosI70Aqu5ooaq8D4FBjKSqFkj2XvsC3J3ZxuKmUBQmjSfQLY39DEZcMmsIPxbu5ZPAUor2D2VJ1VM6p04FGqWJIcCwLE0bz8O7P2VZznG01xwFYvfhhHt3zJWa7jc8X3I3ZbmVfXSEVXY2Y7BYWJoxiTtxwdtcW4HK76LZaOO+np+m0mvl03p1kN5ZwZfoMviveQ6e1B7XHgN4XTrt2yV852FDE43u/4eqMWVw2eColHfW4vSzYK3fRFjiI+KAozkkYSW/eGgbt+BZCkwG3mMFrD1MRJabp8tBhMOZSeHeiXGAqrYyoiR0nXYqFv0DNfnld9ocyXggEZLwzQbKjAuLFz5Q8SzoRVRq5SQLbbrqCnvY2AqZeyNigFDF1H1spN8+ag3BvifjGsj+Ctkp4I0ukumPfCli4YZvIbIGJwoxlXiTy5qQ7RVZzO0WS+/4qODJTQErqXIlsKN8p8tSYG+GiT2HVn6QbMjRNYjnayyVywyOhE5QEtx2Rx498BihEMvSN8Mye9Bjs5zwl8Rd1h2W/rV3yngYvFPnPbhEwkzpvIKj2q4vgvtKBwFPfaEmZd3vW6XZKN+Dhz4RRPP6DbMcvViTGxjw5FuGZcow6awQcjbxS9rmn2TPhwCIRG00nINjhkVKPC+j0CoJrNwpI9AoUUNVVI8dv7tMiB1o6oGy7ALHILPkdmCjn9LLvxNDfZ9D3ixL2qrtOzo25Wa4xS7sEw6bMESAXMlje7/Ef5Jq5/EdpwACROgt+EuDVB8SSpkvcxn9VCsV/DcJAvIEwkH0Hwu4d/UaaHv6rweJn6z++vvrqK77++mtqa2sBSElJ4eabb2bq1Kn/ku2fBWL/y9XSbae+XWIEBkUZ0Wn+PhBTqxR461X02pwU1fYQGeQ8JfZCoVCQ3VxEdmMJh5tKuX3YErbldnBr/J9w+VdxTrJIXFFeoUz1nktniwp3oJvrhs7huqHixbhp2HxcbhfXb3yThp42UvwjaO814RPcRaI6nMPVDWxq2cHlQ8cR45Etg/Q+ZPpkMEw5g/zqbuwuJwoUGLUG0gw+9Nit7KuXeV7XDJnFmznrWFeezeVp0wHQqzSYbL0MDY7D5XaxPH06N2x6EwUKxkUMIsRLPlAHBUYR6vl3fmsVlw6eyubKHGbGDKPW1IpaoUShUPD+sQ39sya/KtzOvvoT+OuMvDPzZq7e+Dq+Wi/OSxrL4cYSSjrquWjtC+y4+Fme3rcSX60Xk6MyKGitItInCG+Ngc2VOQDUmlo40lTK0OA4vircxtbqXGq6W1EqFBxrqWBMeAqz47L4qfQA5yaN5dykMTRZOnjv6AacbieTozJI8o/g20X395+zZeteorSzgduyFjIqLIWfSvezrjybO0ecy+y4LO7evoIuqxmVQkFOczlvHPkZBaDydKHdOnwRWaGJpAfF0GTu5N7tH5EaEAlAeVcjLx1axYaKw3RHjmC32YD3gZ9Z2t7CzcPPIaFpB5AijFF3gzAlidN4KiiVc+pPMC1mqLAsgUli4LaZhEFRKMSftFHmlZI0Q+StrlrJ4eppka641hKRvqY/LDdle4/cVD3ddWOXXETZ9rUMqvkQPl0hqfPGEEnFP/69SFaZF3lYk72yrdKtgEIYIO9QWPwWPB8n7+2Sr2S8zo/XSzo+DDBBndWAWyS+N0fJvEy7SViyiCxP96An7qKvCy9xqrBNGx6Um/PGvwiQS18sIG7DQ8IObnlcthE2RIDckc+FGZr2kAxR3/CQpMjnrxGwUrRBfG0T75Tj4bQLSJr3PAy5QJgyc4t4mC75WgCPyyVG95/uEAC1fLUAzoZjcm52vCQZYhqjgKj2cmGlglLE+K5QidEdwC9CxjVN/4uAovw18vo3R8FNu8UMn3mJ5JzNeky8XCjgs3Nl1mZAvHjYQI5F/CRI+Z3HC8Sf5egVFnGfgG/mehoEVt8kIHTq/ZKbVrJZAP3JEqW1WxjGrEtPX/c/qi5YIUA2evTAY4VrBYT2BeOerX9puZ1OzNmHcDQ3ow4JwWvUSBSqM0xb+AdVeHg49957L3FxcbjdblavXs0tt9zCqlWrSElJ+adtt6/OArH/papr60WjUhLqpyUp3AsvnfKUrkcQ9iu3spsQXy1xoQK2VEoFMzODKKrtIb+mh/Yex2n5Y3PihlOSWc+ggCiUCiUutxulQsH8+JGoPTfvdpOdTrODTrMDu9ON1e5kR14b3gY1U9ID6HXYOdBQhN3lpKi9jlcOraako56Xpl5DKRXsaTtAW24dBv35vJWzjnnxI+jWGVEoFGyvKOJvpSt4YuIypkcP5dG9X6FRqjBqdEQYAzkveRy/VhymtKOen0v388uSR4nxDeHL/K3sqz+BQaXl6X0r6bFbUSoU7K4r4J2jv3Br1kI6rWbWlomsZ3c5GRmWxOf5W7lz2wd0eDLFNAo1UcZALk2bQqQxiJSASIraavHS6Lhg7XM8Mu5i8lur2V1XwKPjL+XKX1+ly9bD1upj7K4rwOl2MSFyENdlzuGtI2tZU7qfYy0VAIR7+bOzNp+SjnqCDb6e9+HoT+eP8QmhqL2O3JZKXjz4I4/u/pJbshZhdzlwud1clja1f7SU2W7F5nIQ7xdGWWcD7xz9lbdm/qkfYPU67PhqvDjSVIobeHTcJUyLyWRL1VEJ1I1M5+7tK3jjyM/Mix/Jj+c+xORvHqCwrYY5ccN5auLlrC09QJfV3M/QHWwsxul28Vn+VupMbbx50Wdy0TQch4/miu8p6zIC9N7M8/jSqM0Ws75CJR6jvvDXds/sSJUWlv0gwKW7HibdJRJXY55kO+14Ubr9Rl4toMM7TOIZ9r3F8OznGT7/HthjENBl7RJ2CLf8HTVKttHnORp1jSfOwi3dkBW7IW6CsDl2swDAvigI3yhhrFpLJEm+qw4u+kLYMVu3ADlziwC2Vk8qvEIFIWmw7XlhlPR+AkL8YwUg1h6C9irxZOWvGejqG+QJjrWZ4N3JAi5aiiSs9OjXsl9Hv5bnY8bC/OflPep9ZbtOqwBArwB5zBgk702pkm6+14cJc2PrFtbQGCbrqz0kKfOfLBLw0FoCS98XKTnrMtlGsWewNgpJ/u+qF9/Up4tk/VmXildr019lG/VHIW68+L5SPTEWhz+XYdrGEPGfxYyR8Ue9HdKcYekYCOMFOef73hlo+NAYhRGNyJJuVRiYD6r3k+Ny4w5Zn3+snG9zm+SUwUAsxj+jtMbTQ2KXvi+M6ujr/nnbPVtnrK6NG2l85lkcDQNd5urwcMIeehDfOXP+KducMWPGKX/fddddfP311+Tk5JwFYv9Xq63bzv6iThTAvBHBZMb7nHG56hYL1S29NLRb+4EYCOsVE2Kgw+wgzP/07Bu9WsvdI8/r/3tWZhAKhQK9Vm7wVruLnPJu1CoFmfEyRLy1247N4abDZMflBi+NjvtGLaW1t5vpMUN54/A6FChwOVQsSBjJ4aZSliaPZ+WJXWQ3lmBxWDnRVsvE8EzarJ14q3xQmAM53ljXL9l9NOc2lAol92z/iLKOejRKFQaNjq8Ld3Df6CWUeMJhjRod+W1ikPfVetFh7cHqsDPyi7tICxTWRwHcOWIxzx34HrfHc9ZXT064jA9yN/LmkXV8u+jPbK3OJb+tmhjvYJxuFztr8thSfQyQ/LTBQdHkt1az4vgmnG4XRrWeh3d/0T9/8khTKSCs312jlhBmDOTNnLU0mjuI9QlhRkwmGytzcOHmh+I9rDr3IZQKJTuqj2N1OXjl8Or+JoBXD63h2xM7eWDMhSxb9xIdVhM/nPMgVd3NFLfXcaK9lqUp48lvreKTvM0UtlX3NwOMNXgRZvDhqwX3criplKvXv45GqcJPZ8RPJ360ZydfwS9l2RS0VuN2u9nXIKBk96Uv4Gvt5AZ7I9t9kngz+wcW1u8F6+Uyp9AQgFPjjQM1aqUW1bp7IecruOgzmRPZXSc+JRQyyue3p0Ui0/qIRKVUwvbnpFuuar/cvOc+Izd7GJDoarM9F/d+KN0mDFndUYlHqDsiv8MyhF1b9r2wKZ8ult8z/gKT7hGJ7tNzhFkq+AniJwq466gUEJGxBHpaxVy/9y0BQ2q9MGOpc4XNaS0RWS96tBi1088VVrDuCOx9c6CD0WGV/UycJpLcgpdEYrR0Qu0Rmemo1sl7W3ObeMNwCzM25V7Z19sOC4P1/nSRG7VGaWJ4f5q8l/mertLueghOhk/PFcN/+nkSGWLr8QzkdsqxD8sQJu1rz1zKEVcKu1WxU/xxTQUDXaTtFZDvCagddbV4puY9I0Bn48OeYeLeEBUNV/wkfqmP5wmz+Ov9Amxv3C4gFkRGXPad7PO8ZyST7IulIkde+bMsf/xHyRgztwoQ13gJuLrgI8+AcU8tflPM+D9cB5sfk+3HjReZd8vjIhknz5L9/lcb6SOGyc/Z+pdW18aN1N5x50DHs6ccjY3y+Ouv/dPAWF85nU7Wr1+P2Wxm+PDh//UL/gF1Foj9L5SXTolBq0SrVqJRK/9wuahAPS1ddkJ8TwdbXjoVY1P9/+52ujzs0YzYTMKNAf2P250ueu2SMB7kLeuOCNAxOtkPp8LKnrp8IoyBPHvge5QKBRemTuKWxGuo7uwgWhVOVqgf3y26n/dzNxDs5cuS5PG43S7yWquptTTy8dw7OFTaiaVHR0lvTf92b9v6AT32XsK8/HED945cwrMHv+fzgq1MiRlCelAMFMPsuCwUCiWBem/ezFkn+6vWYXHYKO9sYHJUOi63G6NGR31POxqFislR6eysy6e910SNqVXiMdxOnt6/kjhPqKvZYSXY4MstwxfiBrbV5HL1+teIMIp05aczolGqiPAOoKSjHrVSxazYYaiVKjZV5jAjJpNvCnewt76AKVEZ7Ks/way4YXxVuJ1Om5lAvTeLk8aRFhSDj8ZAvbmdYIMvLZYuJkamkdda1f/jozHQZOnA5XZjdtp4a8ZNbK85zrHmclIDokj0CyfZP4KNldKhd3dQMPEfz+TokGVcZdEQ5R2Iw+0kTO/P5oue6mfZJkWl83PpATZV5dBhNXHdkDn46rxY8MNj/K1+I2NMVSzIvJgF5d/KSam/AeIn4jCE8PbxYbjcbuYfy2NQ1V6w93B041rU+ulkuDaJ72n0tQKqdrwg0uTyH4VN6O0UYNNeJcbr7c9KrlZfx9+kuwTU+EYLqApK8pj/FSJrlm/zJM37yM1358tyk/cOk+dAmKDR18u2+uZU1h6WUTozH5X3Mfo6eGusMEwgrMa4P8l2zK0CcDKWyvs/sU66/nJXwn0lItPteV08aEXrAffAdvJ/ErZGoRQj/a/3S/K9yyGJ8vk/ScOAMUSA0483SCZW9scQO1aS7xtzxRA/5saBod71RwUUVe0VKXHx27I9pVpAXt9sx+t/E2nzp9sF0Bb+DGFDxS/VWiwdkCDr7/NomdtkjFFgkni42srhnYkCcM0tA56orjrZr5ixAhBRCKAyNclxtHZLl2bkcDl3z0SJB/DSr6UjEwbk3w0PSwRI4nTxsGUtk9iPuqNyniKGwXWeblClSvavvUKuky7x5/SPjOpphst/+MPPt7P1f6vcTieNzzx7GgiTJ92gUND4zLP4zJz5T5EpT5w4wSWXXILVasXLy4u33nqL5OTkf/h2zlRngdj/Qum1KuaNCOn/29TrQKWUrseTy6BTMW6Q/xnXUdpgxmRxkBHrg1p1Zl/ZK4dW882JnWytPiZDq4HjLZU0mTuZkjEYtxtsDhe1rb1EBemJDtaz/Ne3OdhQzA1D5xJkkPE63lo9mbFqNHVufmpYT7MqhVifEF49tAaANYsf5toNfwNgacoEQrz8GBatJ7eym6FhqeT0DCPMy58DDcVUdDUyOTqDJcnjaLN0A6BWqOi1W/mlPJvL06ZxuKmUe0ctYUJkGuHGANy4CfHIHjang521+QDcMHQu1w2dw4e5G/mp7ACvTbuOBL9wLv/l5f4U+iNN5bw1409YHDbWlR3EjZtGcydOtwuX243VYSctMJq81ir8dUZ0Kg0zYjIp7WigvqedmzLn8fDuLzCqdXxXvLs/aywrJBGby8HeukI6PWbfxydcxuw4+QZV7glvnRmbydKUCZhsvfxYshcFChYljiK/tRqX2828+BEMDRapxuq083PZQQJ0Bbwx4waeO/A9c+NGEOMbzPaibWSHTmNurwWLw02LuZu3ZtxEckAEJpuFl7NXMSIsGbVSyfGWSoYEx3FB6iSmRGdQZ2rjlUOrOagOYLSyDkXiNDF193aK6d7Wg3rP35gwPpniZi2Rg9Ig5VPq965h8xcSD5B8wUx0eV9LF96sxwQ41B2RmIar18sMw+L1MOF2kcVAJKyU2XKj3/SIBLr2DX3+7DzxRYEAIZVWZEOtUSROEBAwfJmwZ6YmSdRfuVx8O2nnSF5L2VYBS72d0sG48kqJteiske7MIefLuB9Hr4ANt1vAy44XB4ZTp50rv3XeEmkQkiaAoTEPPl8q8pxCIQBq2GWyDu9QkdQGzZcROeXbxRvXUS1mdKddPG773pImhlEeics7VADZpLth6gPiH6vaOzACaeVyeT0I4LOa4OfbRXpNmQvWTmixyHsDyfz6eL4AqJhxsPAled225wdywtpK5X0f+0a8Y43HJZIDBPDZTNI16h0C124WoPfLfXL8086VyQsgx2HfO5Jz1lQgwG7L42LmP+8dWSZuvLCUKXNk/mNf9TQK2Gotk/FHQckSG/L+dJEtL/lyIBU/aabIzkMvPPUDzdQkzQoZS85GTfwfLHP2oVPkyNPK7cbR0IA5+xDGsWP+eLn/x0pISGD16tV0d3ezYcMG7r//fr744ot/CRg7C8T+l6vTbGfrsTbUKgVzhwefxpBVNlmoarGQGeeDn1E+PO1OF8cqBMQE+2qJCjpzxtjw0CRWl+xjZFgyZruV74p283L2KmwuBx/NvZ0xYYNYl92Myw0TVAoCfTR0W2X0S0NPO79d+DQKhULYFh1sqivkm6Jt/Fy+j72XvsCcuCz21Z/g5s3vEO8XSpfdTIjBhyVrnmZsxCAeGHMBGyoOs7nqKD5aA5sveJLxX93H90W7mRSVTkOP3HB0ag2rS/eT7THOd1h7WFW8j3ERgyhoq8HmdFDeub9/v5Ykj8ds72VkeDJjIlJRoKDR3EGb1USWzotuz/iatMBoLkidxNGWctaWHQAgNSCScC9/ClsFELgBlUKJn9aLOlMbJnsvO2vy8NV5oVWqKWqvQ6VQ4q/3psdkxQ1EGgOZEp1OdXczl6VNQ4mCqq4mHtr1OQcbinlo7EVYnDbP9qLw0RgINvgSqPdGgYI/jz6fLVXHWHF8IwsSRvXv1776E6iVKs5PHc+6soPktVahVqq4eshMPszdCIZIkpOn8lpYCkn+EaR4DPlfFmzj++I9rCvPJj0ohtLOBhYkjOSxvV+hVWnYMGEpX828Ab0xGEVQzOkXyuHPYduzjDIEMurJcs+DwQSOOpfILYfRBEShThwKeV+LpJc0U0YPbXpEAJTeb6Dbz2YaAGIHPhCTeYs0aaAxigy36xVoLhC/19ibYMUcYZu2PiVgq8/jlXG+3OyvWD3wXvPl3/tzWxkZ3oHaZhK/065XBFyYGgQw9Xpk0KkPeCQ8+UaNd6h0Od6yX4znlg4Z5VSXAx/NE2ByZy5c/KXMhHRYZLSOpV32841hIrVZ2gT8Wbtltmb9UQFT3fUyo/OCjwZ8bQ4rDFkiRvm1dwoQSp0v0mWfnOgfL8ulzJblFCrpINT5DIyTmniHSJK+keJPq9wtzKFCJUb/6v0DI5z6XtMn2YekwsJXRTpOniVATqWTfW8qFIm42yV5Z94hwnZW7vGEwXqqLke6SQPiYfkqAdi9HbJtpw3wks7M4VcIWDu5MpbIvrSWyhxQjRdc6THEK5TiHeurQx9LJ+zBFcLu6Txy5m9PweFP5Zhdseb06/j/bzUVynaHLD19HNPZ+qeXo7n5H7rc/7S0Wi1xcfKleMiQIeTm5vLZZ5/xxBNP/FO2d3KdBWL/y6VAgULhmSF5BmKruL6HbouTqpZehho1uNxuNColKRFemHqdBPpoOFLWhV6jJC3G+5TXLk4ey+LksYCwY+8f24BercVXbSDSGIRSqcDPS02P1YkCWH+oBZ1LDOhKpZIDDUX8dfeXXDJ4CjdkzmVqTAbrK1JI8g/j9cM/c33mXDZXHaXLZuHladdSa2rlQH0RBW01VHe38MCYC9hSJV4slULFtRv/xvjIwbT3msgMimO9Z1B1uJe/J07DQJR3IG/n/MKhphJKOxr4smAbALNixa+xLG0aH+dtwe5ycHljKSgUjIlIZW3pAZ7Y+w0H6otI8Y+kuKOOLpuZJ/d9Q5J/OBMi0yhsq6aovY53j/5KenAsTdWdmB1W9tQLq9U3B7KgvYYPZt9GkMGbpT9J8vur067jcFMpzx34niZzBztr82nt7eaDYxtYu+SvvHpoNd02Cz+VHuChsRf1B+nuri3gyX3fMjs2i/ZeE25gR00e++oLqe5u4fui3cyJH87qkn3sqz/hmTag4KfSA8T5hmBQa1lbdpAr0mbwWcFvfFSwnR+TJ/SDsPzWat4/toEIYwCXp01jZFgyq0v2MSduOJsqc8DpwPnZeYyIGk7VhV9w5a+vMikqnesz58pFUrZNJEBjiEhynbXCsPhFozMEcKn/WkhfAunnwIm1AnC668VH5egVBiwsfSDioWqf/O20yU2/swZGXO2RK58TL9PS9yUba9Ldwopc/qNss2Kn3HgzL4bAZOl8tLRJ1+DgBbL+pR/y6aZ2WjqdhDtaiItOFTaoo1L8X4HnQ/RounZ/gquhFv/WooEA1ekPyQ32wAcSTXDBRxIyuvUZ6Ug0BAhA0Brh3UkCwibcLmDkm2WScWYzAUphonqaYegF0iW567WBIdkOC3y7TDxPSTPk5r72brjwM9lGb4dIf+FDxIv1fDyY98K5b4rBvmqfHFtLO9jM9Ay5mvxaN4PKcvDd/ZqAxcXvCBBTaQVUfnWxSHvvTIZ5T8P85+SYJU6Tc2EIgJdSRfaLmwAZ50kjg8YgY6MA4sZ5ctaAqfcJ47npUWFPW4vF0+ewyPvSGCWzbcxN0qVq8BcpVKmCzxaLFHvNegFthb/IuUmeJQ0UhkDx3UWPhEu/lQ5Nv+iBD64p9wqjWLYN3hkvHjuVRiItijZIR+s/oz4/T65tu1liP87Wv7TUISH/9UL/g+X+/5bL5cJms/1LtnUWiP0vl6+XmtlZwaiUCjSq0/1iQ+N8qGntJSnci6YOK3tPdBARoGOMxx/W2GGlokkYoPgww2nyZl8NC07AoNZy6eAp3DNyCSqlbGva0CAA2kx2HC43S8LP4cLYhYxOCObr0o3U9bSxqfIIN2TOJcYnhFenXctd2z4ku7GELpuZD2bfRpfNzN66E7x+5CcA4nxDqOxq5ofiPdSaWgFQKhQcb6lkXMQgnptyJXU9bayvOAzAc5Ovwlujp8fWi80zNLvXYSPeN5Trh85hW81xOnp7WL34YUIMvnxRsA27y8H9Oz+l0dyB0+1iVuwwFEC8byh5rcIGRHsHU2tqo7SjgQtSJtLrsGF1Oggy+PJV4XaUCgUvTLqaTVU5eKl13Jg5lyNNZTSZO0nwC8NLrUWtUOFwO3G4nAR4vplnhsRzedp0jjSVUdXdzF93f8kQj7zYZTXjdLkI8/JncGAU8X6hUA05zTIGKc4nhFlxw4j0DqTF0t2f0fbmkbU4XE6mRQ8hWO+L2WHFZOtlX9cJ9tWf4Nelj1HSWcfeuhPcsuVdNl74JBqlisONpTSaOzCotYyPTCM9KIas0EQAfjrvETSF6wiq+IJWp527tn1IXmsVJ9prB4BYyRZhkSKGycDugjUCajprRKar3i+S27p7BFh1VMHGRyT88sQ6kaBeSJIb7rBLpZMP4LrfoLddWCK/aAFeP98h4aD73pXZln0VkSk+rvocYUO66uCizyWHytYjPjEQduy3p5g0NYvqXT8RpjeBOlxYos5q8SMZg+lpb+PjyvG4XW6uKsnBPzBJGgrGizzPvrfFRF60UfatcJ3EVEy6S0CL3lfS/DurRcbs6+Z02mS/j3wOB96TTj6XQ4z5flGybq8geZ+45VhpvQWw9TRDo3wpwe0WgAnSqYhbcrvCh0ljRI5Hplv2PXgFsf279RTs3UOd2ZvF3uECXAbNg5v3yfEt/Q3G3SRypKMF1j8gYGLyPZ4DbPR82ERJE8Pet2TfxtwIv9wjcqVCJR2oraUi+7ndAoTsPcII/vpneZ+zHpcO0fzVEu6q8RLTfp//TGMQSdNulmto//uQ84UwYhd+IqD1/nI59nveFEZU9bvbkMMq0nPJJgH+LocAsfTF8vPPqsjhUNYpDQln619eXqNGog4Px9HYeGafmEKBOiwMr1Ej/+Hbfvnll5kyZQoRERH09PSwdu1aDhw4wIoVK/7h2zpTnQVi/wblpftjGjzMX0eYv+Tq1LdZcbmh0+zofz7IR0tMsDyvPYPxv9vioKallwnhQziy/PU/3E6gt4YpGQHkVWlo7bbT0Orixsx5lHU0oFNrMNl72V6dyz3bP2JQQBRJfuHMiR/BxKg01pcf4vUjP6FAwaDAKIxqPZVdzWyoOMyhxhLSg2K4b9RS3spZx776Eyz/5RVWLXoEg1qLw+Wkx97LlqocNlXlEO0dxMpF94uMp1Bwedo0PszdhBs3FV1NbKrMwewQI3Z7r4lggy9u3OS1VOEGbE4nqQFRtFq6uSJjBq2Wbko66znWVMFhT/djtHcQM2OHkREUi1vh7jfEv39sI0EGX6q7W+i09hCo98Zbq6PDaubxvV+zKFFyhlxumJ8wkpKOej7I3cDq0n1EegcS6xNCVqh4x34qPYAbN7NisnhywjIazB28nfMLZoeVqq5mxkcOZnzkwAf+PaOWsKHiMPeOWkp+axV6lYZJUWn8VCq+ttKOem7JWsjeuhNYnDaONpXhpzNyYepE1lccJruxmD9tfpt3Z91MWlAMO2vz+bZwBzdnLYTbDnPFlhWUtlaRERTLDX0gDAR86H2FZfhwprAqY28SpmXjX2DCrQI01t4py/tEyk1848Ow7Ef49b4B4/fVv0okgdMmwE6lFjDySobcoOc9JyChZLMkpnt7vtl+cb74vi76VLxb3Q3CzFy/VWQvvbC0ZK+gdO9vmPQxTH3sSxQ/XCsZWusfhIu/6B+FpNjzBiqXHadKh/Lwx+KRip8kGVwNx4X1A1wh6RzoTsd73FKGxE0QULT7dZj/grzfyBFg7RFmbt7zEtAakSXGfBCQ8MYI6cjs61IcfrlMHrCZRFIr8Cw75kbpMLW0i4TaN1cxYhjSSNAGny8eAGh6P5Epqw8SV/U55eoE4oYOg65SmZf525OSvdVVD99fLa+Z9zys9+TTHf5cGhku+Fj2e9NfRQIcf7OMFmoqkGiQw574Eo2XZ86lQ4CQ0y6S8L53ReJNmCLvffjlcpx1PuKL8wqCp8LkvTp6AbcwnNZu8ZQ1e2Rp36iBa85ph28ulW35RoiPr68ajst0B6VaIlFCBnkaCP4FdenX/abws/WvL4VKRdhDD0p3pEJxKhjznJOwhx78pxj1W1tbuf/++2lqasLHx4dBgwaxYsUKJk6c+A/f1pnqLBD7D6qEcANOl4vK5l4Ka0wMjvZGrZJYiuI6M9BFVoIvhTUmfL3UxIYYyK3oprHTRo/Vyahk6XCyOe3UmFpJ9As/Zf1BPlrSY7wpbTCTEmnESw07asUUPDd+BG294kvTqTSsOe8vAFR0NrG27CDeGgOZIXHcmrWI1SX7uGTwZNp6u9lRk0eX1Uyv0870mEyyG0votJnZerwNX5UfjY5mbt7yNuenTCTKO4gbMufx0K7PaLZ0Ee8TSl5rJdcOmY1GpWJ69FBePbQakFiLLpuZySEZvD79elYW7eKV7NV8kr8ZvUqL2WGlsquZapP4CTJD4/mt5hhWpx2r085bM2/izSNr+fOOT/oZvK9P7MCg1mJx2CjrbCAjOJZLBk3l3WO/UtxRxzlJo0kPiiU9KAaFQkF9Tzt2l5No7yCcbhdV3c20W03cbllEpHcgBrWWN4+uQ6VQsvGCJ1hTso8aUys7a/MJNPhw5a+vEu0TzIo5t/Nd0W6yG4tZnj6dnKZyep12NlceZVrMEGq6W8kIiiXCO5DVix+i2dzF8l9fRaNSse2iZ7glawF3bP2ARnMH9+/8lJ/O+wvvHf2V7MYSvLUGnpt8JTemTSZ66+MkhPoQED9i4KR7BUrgKohk1O0ZEp37HeCG6mxQamHkNTJ3MXKExBWASDkdFfLvOU/KDX/OUzLI+8D7ctPvrBVWxWWXOAa1TqTBlwdJR1zOlwLCcAsYuXaT+LZ8IwSsfThDAMx1m7Gkns+aFTm4Ab+GXuIXvQrfXi6M3ua/SjbZ/OfxKvqeaxIbcE+8C2P3CejxE08WCLPntIJCSVVVC7u//RWAxBGj8WoqlGXqjggLBOI9qzssjFb9URm91AcMVRp5326XsIljbxLPVV/1gRy/WFjwgrBNej8Bl5+fJ8B19LXCQO5+XZ6ztEmm1zxPzpi5hQzfOjJCzXD4loGZlY358OWFMqYoeZZInaEZki+mUksHZnu5gOagJDnmdrMwSsMvl25HlQbG3CBSLAqRGluKJcetp0WAcN6Pso+L35LX9ZVvhBjsd70m57a9Em7aJefXECDsZ+0hkWFBjl1f1WQLYFfrIOp37IZXoPxojNJt2ieV/v8pa7esz6MCUJMtwNA34vRl/x9BWFv7CQyGEAz6wP/R6xxOK263E43a6/9pu//XynfOHHj9tdNzxMLC/qk5Ys8888w/Zb3/3ToLxP6DSqlQ4AZMvU4qmiwMjhapTOX58FApFdS19VJcL1180cF6IgJ1dFscRAQMpFXftW0FW6qO8si4i1mWNu2UbQT7agk+KS7j1qyF7K4roLitlpuzFpDqH8lHeZuZ8d3DfDjnNj4+voXNVUcZGhzHRamTeGLf1xS21aJTaXh43EVUd7fwRcE2HtvzFT+d9xc2VhyhvKOZ412F3DrsHB7P/pRQgz+fF0h3nkGlpaq7GZvTQZ2yFYfbhU6lRqvSMPzzOwj2kpvglOgM7E4HS5LHUdhWw8WDJvPx8c102sykBkbR2NPOmPAU7ht1PoebSjk3aQxeGh1P7vuWD3I3sihxDDnNEkga7hVImMGfBnMHj46/lFZLFwsTR9Fi6eK9Y+sBuH34OXx8fAv+OiMTo9Ko6Gxiu2dk0blJY7lk8GS2VB0lyjuIAw3F1JokbT9I541WrcFHY+CFKVezqzafy9OmkdNcRo2plTpTG6O+vAuX24XN6aCovY4LUyfwUd4mehxWlqdPJ9k/kot+fh5fnRcrF/0Zo8aAQa3F5rRzw6a3+HL+Pbwx4wYe3Pkps+KGUdJRT1V3MxHGAJZ7JhecqzBDWwG5pkaKMpczNmYoVB8QRmnEVXLzvs7TMZf7nYCIuIlyU931snTsnfOqdEeCMCgdFXITD00f6Dys3AU7X5J/py+WGAe3S4CFb4QY9He9JrlapibxT+GW2IlRHman12P876oRRk2hBEsbuthM4rJGEtSRTUTLZhh6r8hdx76V2ZBtJTImZ8l7eJVtk/W94Ylc6AuhTT9XwMmoawnb/AQx3ul4Z87F4OMr7y1lzkAQauVe6by0mWQd/rEiy1VL4weWTrg1WyS4H68TOS0kTfxzE24TYAgSYNpaCt9dCfFTJHqi7ogwTG6XgDCQnLbcleKV2/+OjEFKmCLvSestoEhhkCyzXzwZZVV7ByIevrpEuhPTl8hgbmvXQG7X0g9kZNSoa4Th+myxjI26r0SYuxVzJJetZLOcF7tZQNSsRwVEmdtl/fOfExm6r8bc4GlGWDqQ2n9spTCBBT/B0g8FSMdPHnjN4U+FRY2ffOq6QBoR7i6Qc67S8EdVduQgR9avZcIFlxGRMugPl6N4swDLpBlw+fcSKPz1JeAdLoPI/wfAq7puJ73WdpLiFqI8yczf0HyIw7lvodP6MXPSq//t9dkdFnbsewin08qkMY/jZTjd+2R3WKip30VI4BC8jWcAjv8Hy3fOHHxmzvyXJuv/b9dZIPYfUm63G4VCQUKYF3anm1A/AUtmqxOLzcmIRF9iQvRY7S6CfTX4eanptblICPMiIezUb1s2T2yAre9G8bv6rmgXZR2N3DniXP40bAHvHv2VI01lJAVEsDBhNDdsfgub08HxlkqWpoynvLMRq9PGnds+ZHRYChlBsUwIGEd1i4VLB0+hoK2aGTGZ+OmMjIlI5WhLOdmmfTyb8QTzU4bQaO5g4SrpTOm0mzGqdUyJGsLDYy/kxs1v8dbRX1ArlLhwk+AbRnpgDGvLDjIhIo17tn9Ej8NKqn8kOpWG16dfz192fUG33cLW6lzCvPyJ8g6k09pDk7kTJQpcbhfba4+zq7YAgP0NJ1AqFLjc7v4JAmqlksL2WoaHJtJp7aG918Sn+ZLVtDh5HD+V7aett5sgvQ+3ZC0kr7WKko56SjrquSZjFgrA5Xbz2ITLWF9xmFcPr+HytGlUd7eQ21LJ5KgMnpl0BStP7OoHhABeai0J/uE8Nv4yWnu7GBs+iOOtlTSY22m2dNJts/D+sfXYnA4cbhd5LVW0W02MixjE1oue6T9/TeZO9CottaZWBgdGo0qdR/OIa7m0tRfH5rf54ZwHyfjifLlZq3R8pouiqL2WB8ZcgHeHhOmi0kiEQOPxAW/OmBtEPtIa5WZZsklu8FuflliLqJEwaKGwGj4RAxERlnaRGqoPyExCU4P4smLGCHNiCIAPZ8lrCn4Sf9PMv4qZXWMAv2iUwPm33w4vJsHOXRAxWIBV/CQJW938uBjzh10KMx6Grc/K9r2CxT8GMnx6/C1QfxTD1qe4KO4YnPuEbPO7K8EvBsZcJ/vYUUFdwVGqi2yM8K9Cc+7LAmT2vi0s2f53JK5h6zNQcwBaSmTuYvk2AS+dNTDrCTH2564U0NlaCuevEEbIJ1yS7NV6zxggTxxG9kfCvI26Roz7xRvlvS9fLYn774mvkEELB5g+kMHeTXlixPcOkwaIQ59IJMXOl8T7pPOWLDedrxzX5kKJpzjnDQmVHXm1MHv1OZK7NukuWXef0T961EBQLYh8nb1Cll3wgud9zZfuydB0GZ+U+bsYiol3Aoo/NsSfPOLoDyr7px+pzs/Fy8f37wOxzipwO3G1ldLRfoJAna/44QwB/yMQZrN1k1v4MQB+PvGEBmf2P6fV+KBQqNBp/c74WofTisNhQa/zP+Vxl8uO3WHG5XLgcPae8bWlFWspq/qVOt8EJo565L/9fv/TS6FS/VMiKv5d6ywQ+w+obouD7XlteOtUTB0SyJDYAbq+pN5MZXMvHT0O4kLFrD85PZCj5V1sONJCeoyRQVGndlO+Pv0GSjvqGRoSz4aKw+ysyePOkYsJNvhicdh4ZPeXAAwLiWdewkiWpIwnp6kco0aPSqnkwzm38ejur3hk1xd8tuBuPpxzKxetFSllVtww5kZOYu+JDrLbu1gwMowvF8gHd4e1h0ONxcT6hHBD5lxeOPgDixLHkOgXxpCgWDptZpp7Omm39lDcUcue+kKMHilGo1LjdNi4ZuhsshtK2FZznD31Bf37VNQhyd+SMSbegpKOet7yBMJurc6lpKOeJcnjuW34ItRKFRsrjqBRqthbX4hBpcXudlJvasfqtPPh8U3kt1YzN34EdpeDT/N/Y3BAFKPDU/mqYDv5rVXMjsui2dzJDZve5OWp15DsH0FJRz21PS1MikqnpruF7TV5rCuXOIdum4W1ZQep7Gqioaedt4/+wvWZc1mYOIpaUyvV3S1Mjs4A4JLBwiA0mTtJD4rlrRk34a01EOLlR25LBQ63k3nxIzg3aewpYb0Ai5PG0mW18HXhDm7f+j4PjLmA5WnTud4dhItafLVeBBk8walVe7GFZ/LMhncBGBORyrm9nbIil1Nu6hnnDazc1CR5VABX/SIs1/73hUEr3ijRDycb8QMThWlpKxGT/IaHBlLYwTM0OgF+vFEAnbdHLu/2hHqeHJ8A0p1nCBAJr2yrgJmABDHfNxcIk1P0q3QkxowRsKH3g5dSBNz1gYiIYWLCby6Egp9xD5qPQqGSANTGPJj3LOStYu3aZrrbY1DGjGZ0X65VymzyNvxAWUc4C1ffirK7RjoLp9wH6+6WZdxuuQ6LNwozF5AAY28W83/qnIFlsleIAb7mgAxPX/SqHKeagzJTM2as+KVcTvFUVe6VsNTy7dBw1BMToYfsTySk1jtczldNtodV0go47QuPXfSapPePu0VCd1fdJBJp9X6RSQ0BcrxWzBaQfslXcg7mPC2guw/Q9pXKw56fzF7pfCTE9Y8qdDAseeePn/9v1LjzL8Xg68fIRUv+/oIjrwbfKPbVrKHjyPNkpd9A5D2FZ5Q8W9oK8DaGo9cFnPacRmMkKnwCvdZ2/P0ST3ku0D+VmZNeRaU6HUC63S52HXgUS28r40bcT4DfQCaVTuvLpNGP4XTZ8PU+NVbG5XKgVKoJ8E9BU7eD4ID0v7+fZ+s/us4Csf+A6ul1Yne46XQ6cLpAfRJDGxOsp73Hftq8SZtDwIjVfnr3iZdGx9CQeACe2reSZksn0T7B3DRsPga1livTZ1DW2cCYiFQA/jr+UiZ/cz+3bHmXT+bewbjIwXTaerC6HFR2NWFx2ChqFyBkcdgwGsDL4MagVVJlauSz/C1cPGgyrZZuDjcJ+3OwoZg1pfs52lzOlwvupcXSTYO5nTCjRFmYbb08vOtzor2DWL/0cYwaHV02M0n+EQz1G8Qon9E8duRd1Gqo627FT+/NNUNm8lL2akCGiM+KHUZNdzN5rdX4agyoFEqK22sJNviiVal5aeo1LP/1FVxuNyPDknll+nW8k/MLlV1NzIjN5K2cX5gVO4w9dYXkt1Zzc9ZCpkRnkPX5HQCcmziGnGbJ3SrtbOhPty/vaOKDObfxxN6v+apwB6FeflwyaApTojNo6zVxUepEVpXso9bUyqGGEl6cenX/uWk0dzD12wfx1xm5dshs/rzzEyZHpXPp4CncufUDlqdP5/XpN5DdWMKixFEcbCjh68LtTInK4NqNfyPWJ4QlKeNZXbKPYIMP9T1txPqEYHXaKe9sxIWbUIMfv5Qf4poL5Ru+FrhjyCxOlO1mitIhsQcVO08FYCA5Up8tFtYqOMUDdsZKx9yRLwRYtJYKiBh6oXixghIlGmPKnwU4gUhVIMvnfCmS35R7xf809GLxlMX9gUlWqRJgcPRrAScrZktyfEelAJWkGfJ3W5mAMLtFzPog+zTxzoEuvbnPwtGv2VodRs4Xr3HepU+TcOhBGT1053FY9AqpbR9QsnMjMbEh4jMCCE5hV0MUpvY2hoXEEetlkXFOCZNFurW0Syfhz3eJVLvhQTk+hgBhDXe8JB6lgHhhlE4uvxhpamgrl/Pgcgh7ZjfDlidESh7mMbp31YuMq/MRdg75f+80dWOIHgV3HAWHbcDMP+yyAY9Z4hQ48pmwV+vukhDd0t/kXGQtk8DV5hPyfkBmXJZsli7T4SeBsbnPCLMV/HdYqZPL1Czjsv5fxgfVHpYmg2GXEDskk9ghmf/lSzq7K1FHZ0FXNorucjRaH8mS8zznZQhBo/aipn43xwpW4GUIY9r4Z8+wJgVDBl+JSnlmuVSr8T7tsea2PEw9ddjtFtxuJ86+aQ8n1Znkxpy896lvOsjIobcSFpzF7Cl/+y/382z9Z9dZIPYfUOEBOsak+GHQqU5L0Q/w1jA143SD6OAoI42dVlq6bLhcbpTKgdf12pwU1ZmJDNRxfeYctlUfZ178gGn2wbGnSglKFPhpveix92LUCuD7fP7dlHY0MDsuC4fbxfK06awp3c9rh3+i02rm0/wteKl1TIhMY2PlEep72nl31s3cmrWQcGMAEcZAjrdUoFKo+K5oF6kBkbRZu6k1tbLi+CYmRqWJD8rl4O5tH/Lo+EukYzMwmvNDLqTTrOaN8fcRE67ivaO/MiNmGKMjUui29XKgvohladOYFJ3en/7vr/fG6XZxvLWKh3Z9xgNjLmDliZ1UdjWhRMHUmCF0WntYcVwGJC9Pm85CTwL+UxMv5/EJl6JVabA4bMyIyaSqu5mfyg4Q6uXH8rTpjAhNot4TUBtq9OO3qmN8XbgTpULJoIBofqs+xvjIwXw093YABgVGkxEUy5LkcQC43C5WFe/D4XLSaO6g2dJJsYfla7f2sL+hmHarifUVh1maMp6lKePpddi4afNb2F1ObsycR0VXE9XdLcT1NOBoLickaQqHLn8VvVpYiy8W3MNneVv4uewgn+Zt4Zohs/rP8Z+68qBgBbTsllyqtHNkZuA3y4SxCU4WibLPfN3HaBVvkjgHgIs/l264tjIBHoMXyLxK7zDxSY28SsCDwyr+qZJNsOYW6SJ8oEoM77nfy41d65HTK/fBhgfEKN43gLnxuACRnhZAIbJeyGABNylzBHh4h0sXnEojTQhZl0kq/NtjBQAGp4jHq3ofDT0X4HI6aS4vJkGlEdbN06k3bdFMppXdCwUbofpckSJdLpaMUdPSoMS/txQcrRL1oFDA1b+AtZtet5birkhi1U6M0eNQH1sp44fKt0nHI8AdxzyBpb4i6WZ/LP6ysTcNyHwAtx2S/d37FrSV4UyZz/EmP7S+gaT1xWbETcTeVMrHJVn03nwVy597ncDSlQLeAhLlOKXMlmULf5HU/6vWCmO58xV5rL1SYima8mWkktMuDRggMSdmz/zO4cukWWD1nwTITXvgtM+fP6wPpotH77KVki12hnI67GT/vIrA6BhSRo8feOKzxcLSKVUyhP7Qp9IUMvcZkbl/Vx1d5ezJfgqVSsu0cc/LmFSteEz7gJefR/KTxxXodX64XE6KylehURtJihPpd9/h5+jsrmTciD/j73sqI9bSlofL7SQ0aAAYulwOso++htvtJCP1cvz9kvDziftvHaJuUw1utxOTuZ5Q/h8A69n6j6uzQOw/pP4oPd9idXK0optQPy2J4QNeMKvDhd3hpsvpwO50ozsJiBXXmyltMNPcZeOKzBlckT6j/zmb08Gu2jyGhyYRoPfG5nRww6Y3UStVrDr3Ib4q3M4NG9/kbzNuIN4vlId3f87Fgybz8LiLMDusbKg4TGlnPUqFEp1Kw+LksTSZReqavvJh3phxA8M9OVfXDZ3Lg7s+42BDMcevfJOvCrfzcvYqQML0Nl/wJBO/uZ8mcyffnNhJjamVRnMntw1ehsvtJiJAz0fHf+HjvC2sLtmHWqnmpsy5HGkuI6e5nPvHnE9dj8QBTI0ewpiIVN7O+YW1ZQdJ9JOQ13ePrUerVDMzNoun9n1DqMGPjOBYjFo97x/bAMC8hBG0WrppNLdjczr4rfoYPhoDGqWaUWHJXJkxE4VCQXpgDHvqC9lWfZy58SNw4ybZL5xWSxf5bdX8Wp7dv+8JfmF02czM/fFRXphyNUoUPLz7c/QqDdcPncMHuRv5vmg3K+bcRnpQLEqFArOtl++Kd3P+T8+y85Ln0ChVTIpKp6yzkanRGQTovBnqNDFi1ZU4lBpqz324H4QBDA2O48FRi8nqKiM6faGAno5KYYlS5kha+9ALBi6ubc9JKn5ggnRDDrtUYip2viIm+Bu2CYCIyBLZ69vlYrYGSeBPmSPm+eQ5sPoW6V4r8CSie4fA9heFZYoZIz6pX/8srExnNZz3Nqy+WZgvt0uAWx8QG3qhrGvcTSKZ/S1LYjcm3QW+kdjQU2FLJK6hBJ3TLmOCYidIcG1njQC3jkoBIbhZuGgsVZZABhU8IxEO6UukM7KjWkb9RA4XkBfhudHWHCS06gdCQY5d5W7Zz50vSaSEfxydyhi2lnnjdqdzZdQs/O8tAnuvMFixEyRbzS9GpMIDHwhIsnbD7tfE6wVyfnwiZKg5iHF+1qNUHz3M5t/y8FLZiB0/H2N8Jix6BefUR7Heci0Omw17b+/AoO6o4TL30svzhW3LEyLj+kTA3Kdh8t1y7ArXweqb5BwUbzwVKM1/XvxhmZfI30XrxUdmajwFiLVUV1JXVEjG1Bmo1GdgjzQGkUzVZ/48Ayjav4dd33yGQqnkjs9/RKX23KbiJoqEGibyPTlfCSjPW9UPxNxuF9V1O/HxjkKj8Ual1KBRG1GrdadIh0qFyvNb1h0SNJRZk15DrTbQ3llMWeUvAESEjsbLEIzJXI/LZcNsaTkFiJktTRzIeQVwM3nME/h4SzCtUqkmLDiLLlMNwYFD0Gi8KCpbTWjwMPx9E/5w3wESYudhd/QQFzX97y53tv7v1Fkg9m9ULV02vPUq9H8Qynqmqmnrpb5dmK/EcC+cLjcOp5tgXy1jUv3QqZXoNKfmi0UF6mjpshH7OzkT4O2cdbx7bD0TItP4aO7tdFp72F9fhBs3bVYTW6tzabea2FGTR21PK+vKsqk3tfPxvDt4etJyXG43q0r2MjIsmbdn3oSfzsjM2GFMX/kQzZZOshtKUCoUZATFEurljxIF/jojCgXsrMmj12nHT+vF81OuJsjgy5ToDHbU5HGivZYr02cyNCSObS27KO9sZKz+Ymq7W9Eo1TjdbtotnTyfvYoEvzCC9D4sShjNVwXbqepu5tkD37H70hdYkbsRnUrD+IjBGDU6GbrtsPLe0V/YXCUt9q8MmU1aYAyXDZ6Czekg2hjEpetexOV289dxlxDnE8Kk6AxGh6Vw17YP6bD28NHcO5gcncGe+kKazB1cNGgSUd6BpAZEUdXdzKriveytO8E1G17n3Vm3oFWpKWyrxeV2U9Quvi2lQkGsbwjTYoayIncT7dYefizZy8Qo8YcsTZ3AqpK9+Oq8WLLmGZrMnXx3zv10Ws1cvPZ5Ag0+bJ5+JQq1Ho3ej/gAkZUcThcVTRZC/XQE7niRZYfegZ4KMWfjFlP1oPliDu+oEsCg0UsS/fHvxWcDwkQkTPGEe3qyrwITJJai/qisa/mPwuzET5bwzht3iJz0tjB/DPLIbXarBL76Rg+MMBq8SOIT+pLTG44JCIsZi3P6X9j09qsolCpmX38LyvG3iI+screY+ltLIWUOZpubHcH3krdzO4ONFSw8f4UArqgRMhbHO0xYPGOIeORaS/CNGcuQV9LA1IA9cDCW2Ln4gsh1JZtB64v7+q3UFuYRHBuP3hgir+8bsL37dQ+wUAggq9pH2LBLuCX9KC6NF5oAHwF474wXNvDmfcIQgoDd3JUCeJevEv+X3lfA0A/XClv4Z0/shaciB6WRMWYkM03vov58Jty0G0JS0fv4sfyFN3BVHyKo8D0ZkJ4yRwCM7iTpbPI9ss2T4ygUCkhbhPu3aBTNBSJLngzE/KIHjPsg10pvh0iVJ9XqF5+ks7EBm8XMiPnnojyp083tdvOr83w6rfWcG5jZFzN7WkUNSiM0IYmQuIQBEAYyXL1/XS5aJt+EX9lwtONv7X+8rnE/x098ikqlY86Ut5kx8WWUSvVp/q3I8HH4+sZj0AVgsbRQULqSsKAsoiIm4OebQHjIKDQar/44ivEjHqTH3EBocFb/OpxOK51dIm+63S50vzPjD0q6AJ3WD7VaT2Hp95RV/kJj82Emj/3jkTkNTYc4VvAhWo0PCTGz/3C5s/V/q84CsX+Tqmnp5WBJJ0adijnDg8+4TJfZQa/NSaj/wIdKTJCezh5Hf+TE1txWTL1OJqcHEBUo3zrdbjctXXb8jGq0aiWBPlqmexL1f19RPvJ4tLf8DvHy480ZN9JuNTEmPJUgvS/1Pe00mzu4MHUSRxrL2FdfyJcF21iWNo258cM52lzO0uTx+Onko/bZA9/T0NPOooTRVHQ18vKhVcyLH8HipLG4cONwO3G63Vw0aBI7avPotJn5NG8Ls+KyuDFzHi3mLoYGxfFp/haC9T60ePLMpkRnsKuuALvLwaXJk/myYDs2p51Hxl3MhMg0nC4X1d2SIzY2YhC5zZW0WLpx42Z77XHePforMd7BVJtaKOts5MmJy6juamFt2UGUCiW3ZC0ku7EEL42eyVEyPHtm3DAu86ThrzyxCzduak1tVHY1sSxtKp3WHmbHDecvuz5ndck+3phxIzNiM3E4nXxfvIfijjrae02EGf15fMKlfHtiJ9cOmc3je7/B5XYT4xPCyLBkrhs6h/dzN9Bs7uof4n2woRiH28U5iWN45+iv2F0Oak1t6FQCRO1OJ8q9b8sYmqHX9huSS0uraS46RGXMFGZ6/DH4RQuz1FEprJa5TYz0IOBi8MLTjfog4OryH8RAHpggoO23JwG3dCoaAoRhOblCBsO0B0Xqmv6w5Dk5rKD3ETasr4KS5D2bW+Tvi7+ULsuEKfSufRjb4eMUdwczYsG5hMTGw/fXiAdr8r1w3ts0VZTx1cN3o9bJde8fETXA8LWWQlCKvL89b4iP6/rfRGp0u+ly++CwdvPZ/nA48CbXvDYU38yLJRW+qYDKz+/nh3X5RA3O4JLFQyRXzNIuo5FwS2fm9Vtk3VX7QO+HymlBpXCJrBc5fCAotW/YOYgMCuKbqzsCn50jBvhrNnimEsQI4PzbSPG+Xf0rWr2BeTffCa9+AHYbtFfILEkgIDwS1t8gfjibGc576/T/5GfqZAR+fesVavf5sGDJfUSO+9Pprzu5DP4yeQFwOhyc2LODiJRBRA8egrmzgyPrf2b/j9+y7JlX8Q8XH5TNYqZg725wu6k/upfk408IIL3k64GML8A3OJTlz/0dsz9QVvkrJ2p+xsc/jvz7HyIwKoYL/vIUPt7RaDTe+PsmolAocLkcFJZ+R0hQJuEhI05Zh7eXNIbUNGygoSmbjs5SoiImoFbpGDH05lOW1WiMhARlojip0/L4iS+obdhNTMQUhqZddcryDc2HOZz7Jr4+cUwa/SihgUNpaMomImz0390vnc4PpUKNVuNDS1sewYEZf3f5s/V/o84CsX+T0qjlP7hWfeaWaofTzbbjrThdMDHNn1A/AWN6rao/qNXtdmNzuHG7we4YMOmXNpjJrTQR6K1h/GB/th9vQ6VUMCUjAPXvxipdmDqJOXHD8dV60dDTTllnAzPjhtFk7uTaDW8QoDcSaQwkJSCacRGDyAiOpa6njcK2GjZV5vDaoTXcnLWARYmjaevtprq7hZwmGe/TZTMTq5esnPUVhwnU+/Dx3Dv4MHcjV69/nbdm3shj4y/lQEMRK45v4tfyQ/x20dP8uPghDjWW8GPJXkK8/Oi292J12rG7nMyNH05BSzXXDZlLdXcLLZYuMkMSqOhs4rbf3iXZPxI/nZHjLZVcs/F1/jx6KbE+IRzxNA1EegdyfspEhvmnMSIqhmcOfsO3J3Z6stDU7G8o4qbMeQTovWm2dOJ0uTjcWEpFVxMXpE7A6XLy+L5vWLLmGa7PnMu7x9ZzoKGYXocNh9tFUXstM2IzqfVIpDqVhjCjPwBvHFnLhorDON1u7hu1hCT/cBYnyWzQu0YuJj04lru2fsDFPz/PpgufIt8zuqm6u4XP599FW283Yz0NFT8veQRfrRfqzR7z90k5R4lbrmJQ42HqVI/D/LvFL9XTIun4I67sNy/bx96CuaEMZ/BYTnEdOqyw8kox31/8hQz97oul0OgF7DQXyuNnKoXidB+RUgMjrjg1qiB/DTTl4875GsWoa+QmHRAHe97EeOI75sd6ETT4VoJj4rBbe7EoAvBBgSJYjoHNYsbpcKDWubnp/S+w9/bS09GO0d4kA7Q1XsJGuV3iE/Mkdxcd2MPP2eFEJIxHpWn0HD41GAOF+XLn4W/K58qEQzRr7JDxiMRC1GZLPMKf9kr3psshEu7EO0V6zbwYdr0O310h+3r1ejHGb38elrwn4MMzHB6XXcCc3l/Yr5BBcE8hBbu3c+CJp5mkdZLUe0SOu9ZLAGVoujRG5K8e6MQEyT6zdp0RbPVVS3Ul5s7OUwzv7XW1dNp0VCtS6T2aw/YvPmL0OUsZMn2AmanOzyVv+xbGnnchARHiT8vZsJZtn31IQGQ017z6LtOuvI53brgcl8NBfXEh/uERdDY14OXrz4Jb76GruYnEUIXIoy1F0ghwEuPXV1ZbJ06nDZ3Wj6rabQT4J/fLgv3sk02Nqb0Ni6kbp91OU8sx7HYTLs9xrarbTnXdDppbc08DYn0VFT6BLlM1YSexXQA95kb0ukCa245xOPdtQgIzGJ018CWjL47i90wYgNsl0UAuz+/AgEFMG//cH5yNgQrwS2b6xJfYtvd+DuS8zOisewj5HRirrNmKxdpKasJ5KJVnb+H/F+rsWfw3qTB/HfNHBKM5w5giU68DlVKBl06Fxer6Q+nyeJUJnUbJsDhvwgN0pz2v1SixWJ2YemVAs9XuOg2IAf1M1rJfXqbW1MoLU67C4XKxu64ApWcy+UuHfmRa7BCemLCMGTGZjApP5ubN71La2cDasoMsShzNsl9epryzkXER0lFV1tnAmzNuwmTvZXXJPrptFoIMPuyukxiKE+21XDxoMrtqC9CrNIyLSKWis4l4v1BGhiWz7cJn+LnsAN8V7abW1Eq4lz8rT0gC+raaY2ytzpXj0FxBbU8bxR31aFVqDi1+jQlf3YvL7SbSGMjMuGFMjk4n3i+UJnMHg/QZNDRoOdTbyTmJoylorWZpyni2Vh9DgYJo72A+yN2I0+0iu7GYv+7+kl6nHS+1lhZLFwoUeGl0hHrCZoMMPtw/WoJk+5og0oOi0as0eGn0FLXXoVOpifIWuHOirQalUhi4/nNu72VkaBIqhRKH28Wx5nIeHX8pk6MzmB2bha/u1Gy4Hnsvz+xfybKhVzJz1LUSp+ApjX84NCqIjPF0wPmEiym8bJuY5z1dcAVpD1IaYMa/XsH0k0nZ9kqJhACRrH57Esp3igyZMEWGeP9P68MZ0Fwkg6E93qvm+Aup2rSZup5AFrlcKPpYksELcBxfQ161C3tvLwqFgs0fvEX+zg6Gz3qcGcMuBiA6bQiXP/saBh9fzB3tfPHgnWi9jFz/xENoUUrn4aobJTHe5RAGDrCZJQDZ4VZw7RsfoFAoJOAV4Lx3oHgT/gc/BL2ZIGOtyHx98y+3PSchp8UbYPNjEgsxz5PSHTWSo02+1NelMnWUP4aeZslMqz0k8RjGYJj9pIwaSp0rgPjeov4w07qiQvas/IKOplYK0heRtPwSkUujR8n0gZ4W6bz0SIxVx4+hMxoJG3axDOL+g7L39vLVw/dgt/Zy0V+fISZDjv+59zxEXXEhSSPHsun9v9FWW03Brm2nALEdX35CQ8kJVCo13kFBHFzzA1nzz0Gl0RCeKNEMeqM3MelDqTx2hMI9O9AYvFjz4pOEJSZz+bOvyYpcLgmm9Ys5IwhzOCzs2PcXHM5e4mNmU161Hr0ugBkTX5ZzHTGR0KBM1GovAt3b8AsNQ63V9pvxtVpfHI5eXG4n/r6JRIaNPeOxcLvd5Bd/hamnnrTki/of7zPzBwWkEx4yEnDTa+s86XUuIkJHExc1A70+AKfT5gGLKfj7JhARNgajVzgG/anKQ31TNkfzPyA+ehaDk88MlLUabwz6YCy9Leh/l01ms5vIK5LmmAC/5NPA49n6z6yzQOzfqM4EsDp67GzLbUOjVjAnKxilUoFKeWbWrLzRjNMFNqf4xCw2Jz4GNWUNMhQ8KlCHn1HDmBQ/lEoFWrWSXfntqFWK/sdOrghjAI097QQbfBkWkkBhWzVxvqG8d2w9TpcLJQrePbaeUWHJfHx8C8UddYR5+fPnUTICx0djQIGCRQmjqepqpsbUyltH1/HMpOXE+YTw+pGfKe9q5JlJV3CksZQbN77FwsTRbK7KAWBjZQ6rS/fzxfx7yG+txmTv5bXDa1ACSf6RbKzM4bohcyjrbOCn0gMMDoxmanQGo8NTiTS1olaqwA2tli7Unm+OFV1NrC8/xKf5v2FQa9lTV8iEsArOCbwAo17J8fZabhtxDj+X7mdrdS6XDZ7KvMSR9Drt9Dh6mZ8wik/zfqOso4Fggy/vH9uAGzdz44ZzfspEpkYPZUfNcd47tp67R56H1hOVEOrlT6/TTq/TzsVrn8fudLBq8cPsrikgu7GEj3I39Xerfpi7kZeyV/GnYfOJ9A6iqruZXqedAL0356dMOOO5//bETvbUFWJ12pm54N5Tn7zoc5HR+mY7Aoy+noLOVhKGnEOfbTrS4x38fRQKIaly03TaxWvVUuIZa1OBJWoiit9fuyd+FaP59IcE7NQfFaanaIP8e/YTIhXae8Q87wFiPQ4d2xri0HmBy+XsH0xPYCL5SfdwYPvL+NR9DVdch5e/ZD0Zin6EN7+QqQB6P8I8YKC5UmJFFCCS3rLvZJZjxU749X5Y+FL/2x0yfTaBUTEEREZhaM6RbK9Jd8v78o2UmI6GY7K+aQ/Ki859A1ackHy0gysGDPbV++CdSTDnCUiawdb9tTjtYYRrx5OVNB1m/EXmdXrmYqL3hRHLB47dSQzh+rdfpaOhnoiUQUy88R4o+0HiLoIHibm/vVzmgMZNoL74BN89+RAqjYYbl4/GcORdOOcNjtSoaa2pZuqyq9Ho5Uwr1Wp8goLpbmvFy28gM8s7MIjUsdIYMOHCZRh8/UifMoP6khPs+PJjUsZMoLWmCrVWy6CJU9i/aiV2ay92i4U7PvsBhVLJts8+oK2ulkETJtPZ1EDquEk47SLFOmy2gf1UKiXo9r9Rft5x6HUBhAZn0dVdRWtHITGRU9F6YlAGT5pCbuHHtBceYsig5YQEDUWn9aW4fDWlFWvx9Ykj/mS/1b53xSO38GVcYRk0t+bidjvpMlX1p9u7XHbPbxuxUdMweoWh1fph6qnH2xhBYclKyqs3Ehc1g4xBl1NZ+xuFJSvR6wKZMVGuLV+fWKy2LvKLviI0eBjBgRl0dpXjctlp7Siks7vyjJ2UCoWSYenXUlO/F7VKzpnV1kXeiS/w800gNmo6lt5WAv1S/lvH72z9z+v999/n5Zdf5oorruDhhx/+p2/vLBD7DymFQvF3QRjA6BR/6tt6CfXTsruwnbZuO6OT/dBplJitzn7Tfl8HZmu3jeYu+XC02JwY9adeDp/Mu5Mee28/Q/bQWPnGeGHqJJwuF+9k/8anhVv4sXgPL065mq3Vx1iePoNE/3A+Or6Ztt5uXphyFeckjeHbop3U9bShVqpQKpTE+soHXkevicVJY6nvacPitJHbUsFj4y+luruF1cV7MbutbK3O5YPcDfjrjER5B9FslmiHGlMLP5/3COvKsnn1sHTjZQTFUN3dgkGtRaNU4Xa7+eDYBkaHp9DQ084bR34mwhhAjamVrJAEvDV6QryNFCl3oXXF8uS+b1ErlJyfKjckX62Bq9e/Rm5LJS9PvQaNUoXJZsHitLG7roCHx13E2rKDXOnpPA02+PLUvpWYHVZSA6JYni6dT4F6H56euJyq7ma+PbETp9uFSqnk4sGT+b5oN3NPmv9Y1SW+ti2VR7E7HTww+gLO88Rc/FFdnTELm9PJdL/ZbDnWysTB/nxeuJnddQU8MWFZ//Huq0/rSnjWBNNqK3g3TR4L9tUyI/PM3sFTbppX/gRN+Zjj57I5pwUFCmZnBQ2AsS1PSASCd5h4zFbMEQ+UrRtwy9gdh1WS4Qcv6F9tfNZILnr0WbwDg1Btf04A0XnvwqB5pI2fzOA916J1mqBkM1OWXc3IsUPw/nI2tCAMXdqi/nWFxCVwzWvvo9Hp0OoNkDQNFr4iKfhFv4rXbdaj/ctHpnoGsP/wgsy+VGpkjqNKI12hY2+SuZmDPEn23fUCwgBGXSvbTp4FO18Wxiv3B0iawaSLl1N7ooCU0eMkVqOlWKIbag/DD9d5wlKfPOMhHzxxKoW7txMSn0jets1MGDkYpUorGVzjb/F0eMrEAy8/P3RGIwYfX9TVu6G3E3vpLn77UuZnRg9Ox2610tXSxLill3DlS2/hdNhxOV3Ul5zALySMbx79MzqjNxc/+hy+IaGMWrQErd7A9i8+oib/OObOTuy9FpQqNUFRMUQNTscvJJTxF15GdX4uQVGxHFrn+X84dRbLn38DpUqNWqOhPGcWdScKaCwrISwxGbvNSt62LcSkDyUoeiDM1Om0U1i6EoM+iCnjnsLptOFlCCEyXBit7fseosfcgNNpJTn+HAA6uyuoa9wHQGLsPIxewlb6+yWjVhsICkg79cBmrxBJNH8NqsjhjBp2J2ZzE2HBw/sXiQ0dR9jeT1A7elAoFAT6p7J1z31YbV2MG/EAbk9odN/vQL8U9LqA0xiqypotVNRspqn1GNPGP0dy/Dl4GUIoq9rA7oOPk5VxE5FhY2jrKEKl1OLnGw9AYcl3tLYX4HCYGZZ+LY3Nh2lozqah+TBzp76Nqi9I9/9ouZ1umnOht9WNPkhByFBQqP743vePrGPHjvHNN98waNB/MxvvH1Bngdi/efkbNczOCkKtUlLX1otGpTyj7AigVEBlcy8NHTYMGrloXW43k9MDJMLid92Tgd4ahsTK4PDfgzAAtVLVD8IAcpsr+CR/C1emz8TbGYqPPZYEr1jmpw4hLTCG3y58GoVCgdVh55vCHdSYWsltqWBewkhyWyoBiPMAgpFhwlzUmFo52FDEtUNmo1dpmRKdQUpAJPWmNr4r2k2olx9To4ewpnQfEyLTSA+M4ZkD32FQa3l9+vVc8eur1PW0MS9+BKUd9fxQvJdep51wrwACdd5cljaNF7N/BGBu/HCOtVQQ6uXP+MjBNPZ0YLL3sqZ0PwAPjL6ABL8wEv3CuWHoHNaVHeSH4j2EGHz7j0GLpQuzw4a3Rs+MmEwivANZX36YzZU5/Lzkr/jrjIyLSOW36tz+RgEQWTYtKIbzUydwVcZMbE4HYUZ/Ev3CuSxtKnvrCnli7zfcNGw+4yIG0dDTTrWphXpzO62e5oQ/KrfbjcYewL3DLmNvYQc2HHRZHHx4fBOd1h42Vx09JTMMQOGRmP+fPtoCE4Td+mQh7qxPQKnklNjgyffA0W88kplbzOcGP5h4m8QNqFTiN+uuP23VMW2b4Vi2dG9a2qFqDwyah8bgBf4RYkzX+aFQKPBOGQOXfgs7XoRvl4k/a8JtwrapdfiFRp+68tHXSpNB3irxb/VVewV8eo50V46/Vd5v6lx4MVmaGm7aJa8r/FnAz7KV4B8nTQ5KDQyaJ0xWymzpnvztKZm9CIyaPJpR9vVQvRkK1sqMzbojEjLbVipZbWcAYhZTN41lxYQnp3Bsk8jC8VnPE/1w44CxfcGL/cv7hYZz03tfoFQqUXZWwon1aLIuZUjdZ3S1NBGWlMJHd9wAQHhSCkkjx6JUqfj2sQeoKTjOyEXn0V5fh0KhpNfUTXdbC9/89X58goNZ8sBjOOw20ifPwO1yofPyoqmijL3ffYVCoUTnZSR77SqSRo1l1nW30F5fS1B0LO/ddCV6b2+uevltqnKP0t3aTGVuDmGJyRxau5rd335OUHQsV738dv9+tLQdp7JmCwDREZNOm78Y4JeM1daJv+9AQr1eF4BSqUGpUPdLkwChQZnMmfIWTa3H6OgqH4iNWPASnPgFxkpDgl7rh59PHArFSZ+P1fvQHfdE6Yy+HvyiUSiUKBQKFAolackXExU+gdr63azfdgNZ6Tf2y6YnV3jISJrbjhMRKiZ9tVpPbNQ0qut2AKBSaujqrmLf4edQKFRMn/Aiep0/kWHjsNo6+8394aGjaG7Lo7n1GNv2PsCUcU+jUZ/e9f5/oWp2uMl504Wl/+PTjSEEsm5VEj3lnwvGenp6uO+++3jqqad4553/f9Mf/id1Foj9B5RRr6a120Z2iQxDnjciGMMZZEy1Sm6vapWCiWkBmG0u/I2S5aM7A5OmUChIiTy9idzpcnO4tAuFAkYk+vZLlu8dW8/mqqNY7DaeGX8dMd4hPD36FvZ07mDqyge5dshs7hu9lL8dWUtVdzPR3kGckziGh3d9xnlJY3G63fxSdohn93/PB7NvZVZsFttrcnn2wPfcmDmPl7JXcaChiPdm30K7tYcumxmzvZd4v1B2XCxG1/ePyhDuhQmjmBI9hFjfEJotnZyTOIbSznp+KT/EOYljeGLvN9T1tGFz2lmUOBqDWofJJl6gwQHR/HXCJVyz4Q0ARoQmoVWpWZA4isyQeB7Y+Skf5G7C7LBicdi4IXMeL0QOxluj5+vCHTRbOlGgIMI7kG6bhU5bD0oU9Nh78dcZCTaIr6Ohp4PSjnp8tV4sXfMMVqeDVYsfYnBgNI3mDp4/8APzEkYwLCSBJ/d9S1lnA0aNjh+K99DWa+KKtOnMictCo1Rzoq2GQYGnAouWLhs55V34eqmpbbWiVikYm+qH1e4ixFfL4xMu40D9if7Q2JPriowZjI0YhM7py57CdtJjvPuvlf9WHf8Br4YDzG7/AGY8fOr1OPSCU/PI7s4HtZ6WplZWfp5DaLyCCxa9NhDC2V4hAaGp8wTEuBzSXZl12cBIHYUCbtqJu7eLA5u3o8tvImvuQgFBfYGyCpV42N6ZIIDozlzJznK7hQlz9Eqy/cgrZUrAxwskG80YAh1VuDprqRv2ENGX/yCzK23d0FFJ3rb1tP66nSn+eLLHEEnx+t8G9nHz4xJ4qjWKPLn1aUieKQOuj30rnZSXfCVhtwqVrGfGXyB+Mm6XC7vNKsydp2oL8ig7fBCAtEnTcDochCUksfv7rzmy/ifm/unO/rBTq7kHlUaLWuM5f4GJMP5mmivLOb5tM2qNFp3BiyHT59BaU8XG9/5GSNxaLnj4SdQ6+VLX0VBPSFwCoxYtwTswiLa6WlxOB5bOTvxCwph9/a3kbFhHSFw84cmplOdk4+XnT0h8IsZAYVH13j74hYXTVluNqa0Vm8WMy+HAYbez4NZ7qMo7yrDZwoBGJA9C52UkJkMk3dr6PVTX7yA54TzCQ0dh0AefMa2+o6sch8NCd08NwYHCdDk88xpRuGlpK+BY4UdEhIxiaNpVtLWfIPvoayiVamZOfA2NxkuuO8+119R6jOyjr2HQBzN9wkkhurHjaUkYQ4ejE1vLXtIDLmXymCewOyx4GURW9vOJI+/EF7hcDjq7KwgPHXna+/X1iSXIfzCdXRXYHZZ+8DRuxP1YbZ14GUKx9Lah0XijVulQe2I2YiInExM5MChdq/EmJWExjc2HsTtMuFw2QNZl6qlHrTacMsvS1FOPXueP+j8MrNXscLP3Uddpj1uaYe+jLsY//s8FY0888QRTp05lwoQJZ4HY2Tq9vPVqvPUqNGol2jMY+gGCfLTMzAykqcuOy83/7MZ6UnVbHNS0SldcSoQXfp71LEubRo+9lzERqbyZ+yPXDZ1DuNGXtXuFsWmxCFBM9A9HgYLpMZmsrzjMT6UHSPILZ93SRxnz5d102SwUddRxRcZ0NlflUNbZQF1PG27cNJk7APBS61ArVGhUKlQnfVOt9LBMZocVt9vNzcMWkOAXyuW/vkplVxNvTL+BaTFD8dV6caChiOXp0/vnVf7VM0PT32Ck2+Lg7oxlXD+0hbERKSg92/j2xE6quptR1it4bdr13L71fZ7ev5Kfz3uEW7a8S15rFbNjszgveRzBBl98tV58veA+1EoVChTUmlq5f8z5jIlIpaC1moWrnmBJ8jh8dV6YbL0YNTrae018eGwjnxds5WBjMd+f8wDL0qbyU+kB5sWPxKjRs6s2n0vTpvJT6X7ezFnHpsoc1px36jic+nYr3RYnLjfoNEoCvTVEBg4EZc6LH8G8kyTP39egwCi2HW+j3WTHoLUwPPF/cL0segXyVuM15gbQ/UHunaVDYg48fqjWmiNYuruoLSrE9dATKPs6Oz9bLGDsnNdh/gt0FR3AkHUlGr+wU9enMVBbUsqubz4DIGH4KPxCw+CCj4QFC0vHVJaNFwoUSs0Aw9FSJHMYAdLOhZjRcGylZJBZOuBPu6kdfAu7N+yg/qUXuP2z71Ho/TyJ7dMo+3otRfX+mGLuZMHo5fBKBoSlw7LvsPf2Ym0oxnvXK7L+mX8VSTbFk8GVeYmAvvRzBTQ25kueGApJzA9K4sdnH6UqN4cl9z9K/LARdLe2UHJoP6ljJxIzZBhZcwbk26rjR7H29FBbkEfK6PE0VZTx9V/uxScklJlX30RdUQEjF52H1dzDhvfeQKlUovXyYt+P3xCRkkpC1gh+fvU5agvy6G5tYeHt92Hp7uKTu2/G5XTQ2dIEQEzGUNQ6PbZeCyUH9uB0ONj22QeotTru+PwHdnzxMebODsITk0keNY6ywwcJT0xh8wdv0tnUiM5o5NInX0Rr8MLg7UN0+hCi04cA4HD0ogt3ctMHn/QDhfKaTXR1V1Jdu53w4BFEhJ0+8Nlq60Kv86fH3IDRENr/eJepGp3Wj/iYOZh7m3A4zLS0SgOQXh+ARm1Eo/GmsSWHyLAxWG1dHCv4iED/FPz9kgEFCoWKhuZDtHeUkJxwLhq1gabxV1NRs5lUjS/dPbU0NecQE3VqbtqgpAs4mv8BvdaOM/4XsNlNlFUJoxkZNpawkOF0dlXQ3lVKTOQUAAz6QCaO+itajQ/qvzPw3GxpZOjgq/H3je8fMN43PUCjMTJjwouoVDoamg5x+Phb/dEZ/ynldgoT9vcq500XUROV/xSZct26deTn5/P999//w9f9X9VZIPYfUjqNktlZwdidLg4Wd6LTKMlK8Dkl1wagtMFCeZOFxg4rEwafPrz2v1N+XmoGRxtxu6GurRezzUVEgI7xkYMZHzmYpWueIb+tGqVCwUNjL2JpyngmRKYxMSqdJnMniX5h5Cx/HZ1aw9HmcnKay7gwdRIAK+bewfMHvufNI2t5a+ZNvDH9BoIMPkQYA4jxCWaUR7JUejxxaqWKHnsvAXr5dvzgmAsYFzGIKdEZfJi7kZcPrWZipIxDUqBA70nzHh6ayFs56/j2xE4+mXcnTpeLZP8Ivj/nATKCYvntWBtdFgfpMVH9IKzbZiG/tZrhIYlcO3Q2fzuyFj+tF2HGAMKNAST5h1PQVs05SWOYGTeMso4GLlr7PBHGQN6bfTMLVz2Oy+3ml6WPsihxNCfaagCRh9cvfRyHy8kPxXt4/uAPzIsfwaCAqH62alnaNJalTQMgIziWm4aJF2lMeCrfF+1hWszQ/vPzQ/EejBo906OyUCggMkBHoM+AZ8TldrGuLJtk/wjSgmKwOVxYrM5+QH1ypUUbqWyykHTSVIb+9bjc5FR0o1JAZvzvrrXwoQMG9TPVhoelM3Pec+DJpEodO5H5t9xNQETUAAgDyffqrIWAeMo6jaz6eTVhx5/j8mdfBaCmMA+dl5GQ2HhC4xOJzxqJ1uCFj4+XsF1qnQAj4NevVtN6YgQZM+Yzwupm/7fvkTJqLDEjrxZfmqcxwD78arrK8tGOXoaPQoF+8p/o2t1IUvIgFKYm+HCWMHM37WTa8msJjUsgbfJ0aNwNXTXQ04zbYePzB+6go7GeixZeR7SvTaTNyfcM7FtwMlx+0ge7T7g0DyjVwsQBHQ11uJxOulqaMHd1sv7tV6k6fpSAiCjOuftBzF2dqNQadF5ezLv5TsoPH8QYEEh7Qx2W7i4cdhs97W388uZLmDs70Oj1GP38aSwtRqFQMOmSK9j4ruRynXvfX5h2xfWodTo+vO1a/MIiuPqVd5hz423s+OJj9nz7BRqNlpLsffgEBtHT0UZAZDQqtRr/8AhC4hLZ9+O3xA4ZhsNmI37YCAp3b6f6+FHaa6sZsfA8ivbtInn0eELjTx0F1Ff5xV9RU7+LqPDxDEsX7+HgpIuoa9xLY/MR6pv243I7iI6YdNK16GTXgUex2roYPewuQoKG9D9X33QQq62DblMVQ9OuprGwhr0f/oQl52UW3HoPMye9xp7spzhW8CG91jY0GiOt7fm0dxYzb9p7TBv/LBqND1t334vDacFgCCY+eiZpKZeSEDsPgz6QPdlP09FVitXeTXrKJf3btvS20Gtto65xH+mpl2G39/QzZiBM1qCkC7H0tvRngh3K/Ru91nZwu4iPmd3foRkeMpIRQ2+hsuY3XG7nKYGuzW15HM59C6VSzaxJAxlrIpcqPZMC5HPMjYAZt9t5xuP/71rNuZwkR565LM2yXGjWP3bb9fX1PP3003z00UfodH8Mhv9ZdRaI/YdVu8lOfbsMjx0cbTxNovT3VqNokhmUPb0Ocspl/NGZJMg/KoVCQVq0N5VNFg6XdaFUmDl3TGj/jfiiQZP4vngP8xNGsbpkHw/s/JRhIQnMisti/g+P0WBu580ZNzIrLouHdn5GWWcjNw1bQLO5k59L93OirZZuu4UjTWVcljaV4vY65v7wKN4aA5suFL/Mjpo8rs6YRae1h1nfP8LDYy8i3BjAurKD3DliMX46Iz6euZc+WgPPjL+OnLJuQj153TangwMNxdhdDorb63gzZx2FbTXcnLWAIcFxBPlqaDJ3cduetwkwePHZvLs5UF/E1mrpjms0d3CivRa1QsmP5z6Iy+1ifMRgbsicS7J/ZP8yJnsvNaYWHC6XB9C5+iM+7hyxmGjvYIrb63gpexW3DV9EvSdPzOV29zNcDpeTJ/d9i93l4LHxl/V3WgKMjxzMzksG8odymsp4eJdIcb9d+DRDYiUCo8vsIK+qm5hgA4c7j/LnHZ/gqzVwYNkrbD/ehqnXyZhUv/6Q374K89cR5n/mD572HjuVTdJxmxjuhY/hf/Bx0V5x6m9AoVSSPmXG6csu+06Gc2u9sO/dCW43NovIyPUlJ/j20ftRa7Tc8O6nGLx9OP/Bx0U6fDFB4jOW/9i/qojkQdTk5xKUmsWhX9Zw5NefqTyWw9WvnCoz7N+6j/3bHYTX7GHZ6AvxDQ5h3s13ETkoTWIufMJFavxoHj7THmDsktvkhYHnwjlvyFBspRqbxSzS4pDLIGsknU2NuF2u/hDT08orkNo5X+AfHoFRL36mCx95mrztv5G3/TeK9u6i6vhR9N4+jFx4Hm11tXx+/+3ovLy45vX3CQiPpMHXj7WvPY/OaGTZM69y8WPPYfQP4NiWDZQfySZ2yDB2ff0ZSpWKsUsvJmnkGOKzRuJ02PnpxacIjolj6uXX4HI66TV143a7CEtIkq7KLqg9kU9tYT7+YRHc+vFK9q9aye6VXzD9yhtoqSpn97efEzs0i2vf+AAA/7AIGstKqDp+lOL9u7n0iRdRqlR0tTTz08vPEBwTJwG0fYfAw2Z5ncRqBQemERyYxkHba7R1nMDbGElV7TYqa38jPeUyAv1TUSjUKBQK1Go9lbVbqWvYT8agZaQlXwwmI+66EBSDlah7A3A7XbR4OmeVShU+3tF091TjbYwkKGAwpp469LpAqmq3ExU+AZVKQ3zMTJrb8qip201HZynD0q/rT9YPCRpKl6mK1vYC7A4zGrV8cYkIG0OvtQ0f7xj2HXqW7p5aRg+7k5CggS8pffMqW9ryqa7bgZ9PQn+sBoDNLoqC1daFqaeOvKIv5FLzS+k373vpQ9BovDHog1AqB750+fnEMW3886hUWlQq+aIVEToa7zER6PWnzyD+d67eVvd/vVD/cv9YRiwvL4/W1lb+P/bOOkySwtz6v2q36elxd5cdW3cXlkWW4O4QJFggEDwJAQLBIVhwd3dYWHebHZ8dd+mxdqn6/qjZnm1mdtncm9x7k2/P8/AM213W3dVVp9/3vOecdNJJgcf8fj/btm3j9ddfp7y8HKXyEJX/fwKOErF/M0SaNWTHG9CqFRPqxFKjDaRE6REEgboOOz1DHgbtXrLijbT0OukZ8lCYbDqiGKVIsxqLUUWYUR1UDTk9dx6n585j0O5lb4csuD7QPgzVGuh1DhEyGtrsFf1ISHj9Pl6p/IFXKtcQbwznipKVnJwtWzGIkogoSfglP0gSTUM9/GnL2wCBClnr6LRh/WAnscYwbp52MqfnzmNOQgGxRgv7O104XNDY4yQ30YRWpeaJRZfS5xxhcXIxO7r302sfpiQyA7fPyy77VozhOlqqe2i1CQy4bcxJyOfsvAX82FrO/Vvf5/TcecxLyEelUPL0nm94ZOcn5IUn8uEJ8jjzzPhcnlt2NVF6MxISlxcdw7LUUuJG/cF8op97tr6Dxy+bOsYaw/jtlNXMiMtlauzY6HnjUDdv16yT39uceRRFpR7yM0kNjSE/PAmjRkeELiTweFOPk65BD3a3n4yEOELUeoqiZHHyAY2fQvjHLl5hJjUZsQaUCjDp/sGL0AlPyvqrzCWHXqavDj64FNIXBCYY22sq0egNzDnjPAD0IaFyeyskBJXmoEmxwWbZQqO/DoAfXnqGnsb9HPubm5h92tkIgkDX/jpa9+2RK1kHYaS/j/bqfSjVahLz5RvmV397lNpN65h24inMPeM8uHonfHoN7HlDnqKcNUrEFApZY9a+E+Gjyzn72kuwa+OJSc/ENmDlpRuuQBL9nP/Q0+hMJpQqFWrtGPmtWv8jXzz+IGFx8Vz4yLO0Ve5DYzDQ19xIR00lUSlpqHU6UopKKVq8nN6WJvxeLx6XC9EvVzjMkdEolErcdjuv//46fv3s6yhVMklxOx14nA56mhsQ/X5CwiPRmUwsv+w3dDXU01axD1NEJKklkznzT39lqKeLrvo63v/z7XicThaefwkZk2fQWVcDArjtdnqa9oMk0dvcSHrpFBp3bSejbCpbP36P6g0/seyy31C8bCX12zbR07hfns50NtBZ3UB3Qx09TftZeumVgezJzNRVpCQuCpAZAL/oBUliavG1SJKEIAhU1r7JiK2Nzp5tRITlMnfa3QzbWunq2UFX73acrn46ureQm3EyO19dh23AigItZStPICQikris3MD2Y6JK6e7dwfBIE7FRZRRkn8Xazbdic3Ti9drISD2W7PSTsJgz2b73EYZtTeRnnxnQqSXEzqKu8SNGbK2M2NoIt2Tj9TqwOToC05tVdW8BkvxaJkBd4ycMDNWSEDubJXMeCTyelrQMsykFc0gSSoWW6IhiRMmH0ThG5o2GaJbMeTRwHe6zVuEX3cRElgTI4sE4kHn57wRdhAD8MhmTl/vnYsaMGXz66adBj91yyy2kp6dzySWX/EtJGBwlYv92UAgCBckhh13mwJc1OUqPzeUnKlS+gZU3j+DxSZgNKrKPoEJm1KkOGYUkSRLrKgcw+zN5ceHNFCfIcSFLU0qI0IeQNqrveXvVTfQ4hsgJTyBKb+bb5t2Y1HoWJRehGf0FF6E3c/GkZSxLKcWk0bOhQx65N6p1PDDvAsr7mpmfWEhJ1B4+bdhKliWeTR3VzIzPJXE0kiktRo/HJxI9+lr/Xv4tD2z/gMuLViAIAteUnEiBYi62HoG3h+T2YJTezAPzLsCk0RNrDGPY7aDPOUyvcxiP6GNaTBaLkosByAlPRK1QUhgZ7Ptj0Rio6G/h9cofqbS24vS5+U2ZfGHWKFWURWdQ3ttEWmgMS5KL0SjVLEouCtqGxmvh1vwr6RUaKYhIPuxnYtEa+eAEOYpo2OHDOuwiLlxHeowel8dPYqQOoy6UO7JvJkQv23fMLwjD5RUxTTAZezgoBIGi1OBzzeeXaOh2EBmiDmqHjoPeEmQnAeD1uHnj1htw2UY4688PY6r/Djp2ygL2USLWvHc3HqcDa1sLTJ+FJSaWy5+RqzuCoGD9W69iCgunZNk5shN9TD6i6Gf3158jiSIt+/aQWlyGIAjEZmRx1p8fpre5kY3vvk7J8lUYzKFU/PQ9bVUVGC1hzD/7QgC0+lFRsyDww4vPkFY6hbRlf5JbmVkr5NBytQ6O+YucWvDTX6D2S0weO6bTZe2hQqFAqVIh+gWG+3p4+cYr0ZvMXPDI06g1o0kYRhOCoEBnCpGrfXffjFKt5le//wNqnY6ipcfw7h9vpWbjWjKnziB31jzO+ctjaHQ6dEaZFMTn5DF51Wp2fP4RxtAw3v3TrYSER9LdWI+tv4+v/vYIkiix4LyLKViwmK+efJiq9T8yffVpLDz/EiYtWj76UgU+f+wBlCoV4QlJDHZ1YolNYP3br2EfHADktumSi68kY/J04rJz2frhO8w7+0Ly5izghWsvZaCzg/3bN1N27Ikk5hUSnZbBoKOWHXsfQ6XUM/v0s4lISA4KAJckiX01r+Jw9DC56GqUCg3rtt6OX/Qyd9rd6LSypCI/+0y2fP8cW7/6kahfzyImLYOWjh/p7N5CaEgqkeGFpCbKaQ7x2Xk07d2JJSGG6oa3icjOIzRqTGM4MFSPz++if6A68FiYJRun20qoOZW6xk/wem3kZJxMdvpJ6LXhQcMCBn0kGSmrGBiqQ6sJo3r/e3R2b8Hp6qcg+2xSEhcxa/KtuNwDaLUWquvfJTqymHBLdmAb6cnLaW7XkJK4EI9nhO6+XcRElaFRmwKDBwBZaSfQ3L4Gp7MXrSaU2saPiAwvCCQDOF1Wtu5+EJCYPeWOQNXs3x1Rk0Afdfj2pD5KXu6fDZPJRHZ2dtBjBoMBi8Uy7vF/BY4Ssf8gSJLE/i4HOo2SxAgdWrWC0nS5/WEd8ZIea2DQ7iUxQnfIbTR0OdjXYqMw2UT6BLqhAxAEAYtBxaDDR35UPIbRia1n9n6FV/TzQ8teTs+dS5jORJ9zGJvXxaSoVAwqLfv6m3mlcg23z5AtBO7f+j6fNmylYbCL4ug06gbkKlucMYw4U3igwrQyfQq5EYkc+4GccffFSXcGCJ9GpWBSyhhpaBkV9TePenJ5/RI+nwSCxKT4VGINFibHZHJcxpgo+O3a9XzVtBOAh+ZfzMr0sSmohUmT2Hvu4+M0eRd8/Sg2r4s5ozq1SQdVswRB4KUV1x7yPTyA8mYbJimKGclpKBUKPD6RmnY7UWYNUaEaKlpsGHXKIB2XJEn8VGHF55coy5AwaJRMy7YA0Gl14RMlRpx+WUKlVGA6KEFBFCW21w/h9UtMzjCzp2kEtVKgNN087vX9HI3dDipabOg1ClaURU24jF+UqG23E6JXkRg5dq657Xb621qQRJGR/l5MpWeDrRuSZwaWOe7a39FaWR7k5n6gotS4ewdbPpQrpdkzZmMY9SBTACuv/i29zY3EZebw/G8uRqlUceEjz2AItfDts0/QWV+Dy25j0fmXkTdnAV3760gvmxLYx5JLrmTaiadSufYHtn71Kft3bOWSJ/4u69tat8mZk4B/8kV0DUJs2YUoPTZ8JecFLqKGUAsXPvqs/Pr6evF5PLhsI4g+H4wSsbTSKVz4yDO01VQErB/0IWZiM7NJGq3OJeYV0rW/juby3UQkJsu5mgehafcOtn38HoJCwcxTzuLzR+8H4ITf3kZfazOb3nsD0e/HHBWDQqHEMSw7wu/88pOAD1jx0mMwWCxoDUZEv5/8uYsoWbGKn159nur1awiNjmXGr04nNlO+CRXMX8zWj9+j4qfvadi1nbw5C1h66dU07NxG6THHU791E21V+2ivrqR09VIUCg0GfRTTTzxt3Dnl97vo7N4KSAwNNxJqTsXtGUaSRLw+R4CIWcxpNHzZgmNokPaqfcSkZaDTWEaF+UtJiJ3Jrq8+ZccXH7Pogss47vpbaGj5iub67+ns3hoUaZSZehx6bXhQy3BS7nlMyj0Pp6ufrbtl64noyFIyU1chSSL7al5FkkQKss9CoVBhHaxmYKieqro36OnfE9jOgYEDjSYEjSaEmv3v09DyJd19u5k/457AcjFRpcREyV5luyqeobN7C/0D1ZQUXBr0/tQ2fkhvfzk+v5NQUwot7Wvo6t0ReD0atRGTMR6fz0GvdR8aTcg4B/9/RwhKgZKrFBNOTR5AyVX/GqH+/zaOErH/IPQMeShvtgEQZdYEfMN6hzysrxpArRQ4ZnLUYU1h+4Y9+EWJ/hHPYYkYwNyC8EAb4QDunHkGe3ubWJkmk5jPGrbx259eYFJkCu8edzMXFC7hg7qNQQ7x0+OyWdO6l2RzFA9ul717Hl14CQ6vm3O/fJhry46nLEaOownXhRBnCgMJ7tz4Os3DvbxyzHWkmMf0Jnavi/2DneSEJfD7Ubf6EL2K+YVhNA13URAdjyAIfNG4g9Ny5zItVr7ZvF+7QX5dCflBJOwAJiIp02Kz2dXTwA1TVpMXkTTu+SNBXqKJnmF3QL/V3OOkvtNBS6+T0nQz+7tkvVRypC4QgSUIAiF6FcMOH7XtdmwuPyVpIaTFGIgL1zE9G4xa5bi0BACnR6TdKusM261uOkb/PyfBGOQnd6Dq6XD7mZsfjlGnJNKswaBVEBd2aDLfaXVT3W4HIC5cGzjfTGHhnHLbn3A5HAx2dyEICmKX3BW0bmRyKpE/Ix4Au7/+HFEUSSudgiksHL05OPold9Y8cmfNY7C7C8nvxw+IonxBz54xG8fwIOmlU2H7C4Sue4gTV/4JClYE1lcolFhiYsmaPoumvTvJnnZQgkFCmSzCV+n46cu17PrqMyYtXk5aye/59K77yJtTzjFX3YDTNsLXf3uE0JhYFp1/GWfd8xBagwGtQa4+9zY3olRr2PXVp+z++jPSJ0/jsmdeobWinP3bt5AxeRofP3gPkiSRXjqVfT98w1BXJ6feea/8eYgiVet/RGMwYImJwxwdQ+a06RQuXMa+Nd/w46vPc/Fjz5OQm89QdxeZU+RBkFXX/o6tH79HZ201PU0NRKXILWtzZDQzfnUaP736Ahvfe4Mpx60md/YCettriJ8dS9LkLKo3rmXDW68y65QzEf1+TOERlC6XK51J+ZMC5DFjynSy98whNiMLizmVBTPuw+t3BH1nyn/4hsHuTmaefCalhb/G4ewhwlKAc2SYuOipdPZsw+7oIsSYgMPZg04bzvHX/572mkqy5k5j+57H6OnfDYBxNLC7dvMGhrq72L99C+mlU4mOLKGnbzc6bXggNFuSRHr6dhNmyQqYvR4MnTac1MQleLx2wkJl3daIvYOW9jXy64yfh8WcRnzsTLw+B0nx8xEUKtQqA5kpx2IwRAdtLyayhI7urTic3ewof5LJk64ct0+DThb0D400Bz3uF71YzBl4vQ6S4uah10fSa60gOnKsiq5Uapk3/Y9U1LxGbcMHWAdqmFZ6A/8JSJwnMPNuxc98xPgf8xE7GK+++ur/2L6OErH/IFiMasKMKnQaZVB4uFoloBDkrMlfkgkVpYYQEaIhIeLIJkd+Tk5Ozp7NyaOu9DBeUnlcxrSgKtTB67h8HpqHe1AIChYmTeLCrx9je3c979VtCBAxi9bI9yf/CbfPy9Q3bsAr+qgf6AwiYs3DvWzvll3Pq/rbeL78G07Ons3XTTt5YvfnnJQ1k5/D5nURotFj0Rq5rEi+QVttXrbVDREfrg2qth2Mp5b8+ojeJ1GUaLe6CDOpx7UIM+IMZMSNkd7YMC3tVjcRJhURIWriwrQYR61LDsb8gjAkCTbVDGJz+YNsTeLDD02UjDolxakh+PwSadG60cxR2dR32OGjf8RDcpQeUZSw2rxIkpx3atQpCTOpWV46cSXsACLMasJD1Jj1qnGkP6mgiNotG/jisQdQabVc/eI7KCbQXwz39eIcHiImPZOu/XV8/4Istj/ht7cRlZI6ISne9N6bdO2v5bS77sdoCcMUJldSo9MyQRDobqgn1f45DLXi2fsR+1oU5M9dhM4kt6B6W5oAOPOPckSNNJp32dvawgcft5OYW4B5tMKn1uqwdrQjSSL97a0AtFWWB7y/Zp96NrEZYzrA/rYWXv3dNShVKmadKnujRSYm43E4+Oj+PyBJIsuvuI7mvbsAWHTBZXTWVZMzax6i6EehUFK7ZQNfPvkQKq2WReddyppXnmf3l5+RM2su+9Z8g+j3I0kSSfmT0BlNOEeGMZhD6ayrYdvH76FQqrjy72+g0Y+da3lzFtLdsD9AqBJy8sg/uZi2znXsLX+JwS1aBrs7qdm8gabd2/H7fGiNY7KG/c1f0Nu/j0m553HcdWPB7pt33ovD1cfUkuuJCi/A43TwzTOyb19sehZZ02Wi++H9d9OwcxuZx2aiTvQzNNyEx2NjX83LxESWMrnoahJy86lt+Iie/t0oFCpCTEkY9TKhWnzh5dRsWkfclDi+W38tWaknkJt5Ghu3/5GO7i0snPUAA4O17Kl8DpVSx9J5T447dwRBID/7TPm8s7XS3rmB5ISFWMwZjNjb8PnkgRWDLhKv18GIvXUcuZIkkZr976NS6clMXUVMVClNrd8w/DOidQDm0Wgjp6sXUfQFwrsra9+kteNHEuPmBiZDZ5TdNOE2LKGZtHWuJyQkiR17HyciLDc4yunfFInzBBJmK/7XnPX/N3CUiP2bo93qoq7dTl6SiRiLlgUTaLosRnWgEvZLgm2dRhlECkBuNe1pGkGjEihIMv1i++pgHJs+lZzwRExqHcNuR1BYtd3lo3fYQ1KkHrvXyc3rXibOFM5t00+VdV1lx/Ne7QYuKgy+uAiCgE6t4fllV7O1s4Y5Cfmjxyni8LnJj0jirplnoFQo+KB+I1817aR5pJecsAQAvH4/H55wK4MuO6mhMoH7uH4z5X3NGNU6powK6fuGPDjcfjr6XYckYkeK/aMt3xC9kiXFkYddNkSvIjlSx56mETx+iRk5lsBzkiRhd/kx6pSjLt8wM8eCx3foMHiArbWD9Ax5mJUXRrhJHVTtzE8a08Jsrh3E7vLj80tkxRuZnRuG0+M/5GTlRNBrlMwvOPTEVnh8IjqjCUtcPBVrvydv9oIgIb7f5+XVm6/BNTLMqXf8mZj0TJLyJ+Hzevn4wT+h0eu59KmX0RqCW7Wb3n8TSRQJiYiiYP5izFHyZ9u4eztD3V3UbF7P9Jv+AuXv8vXaDmornmWgs53FF/6aoZ4uXrv5GgAufOQZuvbX8fljD1Cy/FiiktOw9ffRuGs7V77wFgULlhIWG4d9eIj6bZuIzZSjUNJKpzJ51Wr8Xi8b332D6atPxTBauVNptKi0WtRaLZMWLyepsJimXdsRRZGYjEycw0OExcaDICAIAhlTZlCwYAmv3vQbNr77Oufc/xgRicloDUb8Ph+7v/0Cr8tJ+ZpvOe2u+zj/r09hCLUgCAKNu7bzwX13YY6K5qw/P8zGd15HpdUSm56FbcBK05pvKViwBK3BiNESxsqrbsDa0RYgniZFKq7+NXRVVLDijLuxxMZRuHApiXkFdNRUkTl17IdMQ8tXeL02uvt2kZ48VmE8EP3jttsgHDR6A8XLjmWwq4OEvILAcs4R2XsQr4r87LNIjJtDfaMck+TzuwLLCYISgz6G9OTlGKUM3r7jVlKLy5hz+jlEJqeyp/I5PJ5hevv3Ehtdhl4XiUqlC7TxFAo1KpUeUfQeNh6oqu4t+geq8Hjt+Pwu/H431sEaIsPz6bNW4vYM0t23OyDQH7a1UtvwIZbQjIBfWFz0NNo75ep6fOz4H31er4PW9p+wmDPITj8JhUJFR/cW2jrXo9PK35sD+jSXexBJEicU5CfEziAhdgaNrd/Q2PIV/QPV/xFEDGTSJVtU/OeSr4NxlIj9m6Op28mA3UdLr3PCm6XHJzLi9BFxOGH1L6B/xDNmYxBjwHAoA89DIFxn4pgP7kaURD5bfQcxBgsAW+uGGLT7cLpFOqUGfhi1jrhk0jL29jYxPS6b++edT7djkPO/eoS88CR+N+1Xge1u6Kjk2b1f0263ct/c87j8uyfZ2FHN35b8mtNzZbPEcG0IDUPdnJAxneWppSxOLiY3PAGNUo3loPimOQn5lESlMy1urIqhUgokRWpJjzl8i/ZIYDaoUAjBJrvWES8S0oSfjdsrt9XcnmC9RFWbnZp2O+mxeopTZf2fQiH84hRs34gXr19iyO4l3HRo49ZIswaPV67cASgVAmbDf/8y4XbYqdm0nvSyqUQmpXDlC2/x6s3X8M3Tj2Hr72fmyWcElhUEBRq9HrfNRk9TI0kFRZx65730t7Xy2s3XoNEbUIxq3lor9rLji0+YfuIpLL3kKuq2bmLPt1+w78dvueL5N9Do9Ew74WTUWh0Zk6fJIeQLbibK+jZNDV0k5MqkQKXRypUiQUCt1dHb3IgkirRXVzL71LPxeT1Ep2bIuYPxCXg9brZ/8j5d9bV01dcy76zzUWu0LDjnIp6/+iLZ1NRgZNYpcqUlNDqGZZdexXd/f4rtn35Iy77ddNbVMGLtQ6lSEZmchik8HK3BgEKhRKXR4HbYGeqV7TAcQ4NEp6ZTvPQYtn78Hj63m7C4BKztrWx4+1XmnH4uG999g+TCosDrUKo1dNZV07W/FgSBE268jQ/v/wMdNZUM9/UGBhV+eu3v7Pj8YyYfeyILzr2YqMhJdH7pwe8XeeePv2fFFdcRFhvPlFWrYdXqoM+1MOdc+q2VREUED6DMmXon3770GG8/80eWX34NhQuXsvjCy+mzViBoxvyt5l12Opt+ehRVXD8mQzwjtjYaWr5CqdRRki9rp9yeYeoaZcnC0HAzHTXtdDfUMdzbzZzT5cD0nIxTMBriiY+ZhlYTGuSSr9VaEEUvLvcAfQOV4/IgD0ZC7CzcHrlVmpa0lF5rBckJCwDISD0WtdoUtH5z2w/09O3G5R4gLnoaKpUOgz6S2Oip9FsriIsaL3EYHG6gb6ACgBCjbIXT0Pwlw7YWUhIXj8YcheP2DLN28+8RJT/zpv9pXNzTAcTHzGB4pJlwS+6Ezx/F/30cJWL/5ihINmHodo6rYh3ApupBrDYvxakhpMcacHnkFtZE2qFDISJEQ6RZzYjTj83lOyQRu3fre+zq3s+D8y8MCpl2+7w4vG4kScTjHxvtjghRM+zwYTGqyAjN58LCJcQbI3hx33e8XPkDi5OLeXLx5WzuqGFzZw1bu2r57ZTVKBUKaqzteEdtIQZtfuo77bTbrPglkQ7bQGAfi1OKqR1o546NryMIwiGd5lPM0by16sbAv/tHPOxpkv19fmlK9UgQY9EGebHZXX7WVliRgCXFEeM8unISjUSEqLH8jDT5/FLgr8vjD0zB/hJm5VoYtPtIjjp0yxLkSKuy0QGPYaePnyqsCAIsL4lE/w8S8IOx9vUX2fvdV6SXTWX17+QJybjMHPrbWohOCzb+VCiVzDzpDL5++hHWvv4CpStWoVAqiUhM4pKnXkSl0QQE/Fs/fo+mPTtRqlQcd93NJOYXBkKsXXYbG999g+zps5l6wq+oWrsGtU5PeHwCM046jRknycMiPU0NvPuH3xOdnskJN/wejd7A9JNOw2kbYe+3X/LRX/7IaXfdF3SM615/iV1ffUpodAxlK08MTEUCFC9dOWpqOhYtNdLfx4Z3XsNtt9NcvousabOwWa2ExsSx9zs5tmvxhZdzyRMvUNv0Pmt3/o7Swss57c778Hk8AXPUKcedhEKlIqNsGq1V+9j68XskFxaz78fv2P31Z9RsXMsVz7/Bybf+idCoKMxRMcw+9WzMUdHojCaSC4vpb2smKjWNZ6+6EAGB5EnyZLDP68Fm7yAkIp5Ln3qJ9++9k/bqCrrqa8idJf+wcTh7qK5/j7joKcTFTCMuegodXZtYt+U2ivMvJSFWfs1qtRFbp/z9GbH2AdDWuZ7y6hcx6KNZMPM+Bob2s7fuaUISTSTGzSbcksWIvR1BUKJW6VGp5WuaRm0iMW4Ovf37aO38CVNUChGlRsKSw+RritPJjs8+J6WoBIM+CsfwEHVbNpI1fRYGcyhajZm0pGW0dKylouZ1LOb0oExKkFuLdkc3CbGzSIyTpRV1jR/j93sCsUMatYnM1GOD1ktJXIzN3oHD1Udi3JzAFOek3HMP+V2IDM8nM/V4tJpQtFq5YpqT8SvauzaRmrhkAuG9xOFsHbQac8AY9yj+PXGUiP2bw2JUHzaaRj3aV1cpBTqsLrbUDhFl1jAn/8hd9w/ofNxekdY+F9GhE7ep3q5ei8vvZVNndYCI1Xc6cHnUfHj870GApJAoXB4/Oo2SolQzRalmmnqcfLPTyslJx5Aea+DVSlkkmxgit/CWpZayrr2CaH0oSoWC9e2VXPzN48ToLTw777f09Ogpb7bx3NKr2T/UwdyEgqDj2tRZw4jHybauusNG/hwMk06F2aBCoxQOGSl1AAM2LxIEKk11Ax1c9u2TlMak89f5FwWWO0DCBu1eWnpdaNQCMPH2FYJA9AQVzsIUE/HhWkINKr7Z3YfHJ4e6S5K83fRYQ+Dzcrr9/FRhRadRMi8/bMLIq64BN+1WF3mJpnEEW60U0Kjkdrbyv6nPiM3IZt+abwNTeABLLr6CxRf9esJWd1LBJKJS0ohKTsXn9SC6/AH7hs66GpILixEEganHn4xSpaLs2BMACIuN54rnZNK95uXn2PnFx7RW7CVz6gw2vvM6UcmpnPvAE0H76m9rwWW30VFTSUtFOZlTpqPWaInLyGbvt1/i87jZ8flHdNbVsOjCyzGYQwmNlsXiWdNnU3bMcUHbm3r8r5h6/K+CHqvZtI7Brk6UGg3HXHkD4fEJTDvhZCRJQqlUojOFEBIxKuC2NyKKHoaGm8jOPTFoO/oQM7NPPVt+TzOzmXrcSbjcA4z09NOws5DU4sl01tXw/j23owsJ4dInX6Rk1fLAJOLsU89i9qlnMdDZjs3aDxJMPf4kihavoMP5HWu33EZe5umkJS9j5VU3sOPLTxju66W3pYmo5FRa2tfS1budoZHmQAyR2yO3Fz1e+e/QcBO1jR8x84JVTO07iZRieVJQbrcJgfabQqGSq59qI3lZpyNKfhpbviYxbg45GSejVMjnqyAoKMq7kKq6t2npWENYRCrR05rRqGV7ll1ffcbm99+kat0PXPz43/nhhaep2bSOtqp9HPsb+cdVSuISGlu/xe934XYP0j9Qxb7ql0lPWUlm6iqq6t6iqe070lNWkptxMjZ7J3WjLdKoiElEhP2s2vTd3dC5G/MJT2EOSWZgqI6Ork1EhOXSb60iMX5ugMBJksj2vY/hcluZWnw9Oq2F7PTgzzUqYhJREZPk7Mu9j5GevJyk+HnMm3HPaGvy338q8igOjaNE7D8cM3IsOD0iRp2SptH2osv7j0dfFCaH0NLnJPMwk5QPzr+Qja0NLIyTy/Fur0h5s/yreKY5nFiLlspWGzXtdnISjAFtUt+wB69fomdIntQ8J38hJ2bOCDjnO31uvm7aiVf0syy1FLVCJZMDhcBnbesoMBQxLS6bhBATCSHjtRT3zDmbNS3lHJMyFY9PRK0UcHnFCQ1xD0CrVrC4SL74SZLEoN1LqEE1jjTYXT5+2idXtpaWRGDSqdjb10SH3cpgix2H2097v4ukSF2gfbi7YZgBu4/0GD2TUkLGVScdbj/VbTYSInTEjL5ndR12JmeEkhipI9KsQZQklAoBQZBQKAQ2VA3g80uolAJpo61Um8uP0yPi8op4fCIqpQLVzwjVvpYRRpx+tCoFhT/Twek1yoBFxeEmbY8EkxYto3Dh0gmF0hMhNDqGc//yOG6HgxeuvQyP08m5f3mcLx5/gM66GhacewmTjz0BS0wsHbXVfPvM45x97yOoNJrANrOmz6J13x4KFyzBEhuPWqsL0icdQO6seQz3drP+rVf5+IE/cuEjzxAWl0DypBKWXHwlubPn8dTF8tRg8qRiihavYPKxJ1CwYHGAHIqiH0mUUKqCL6ld9bUoNRry5iygp3E/yYXFhMfLWsWGXdtorShnxkmnBSYrAUoLLqd/oIqE2Jk4hgYRFAr0IcEVnAMYsbezYdvdqFQGfnXrfTTt2s1HD8jpFAqlktrGj2hq/4qMlFXkZIy5hofFJVC85Bj2fPsF5d9/w4JzL6Zj7zcA+Lxutn78HtEpafQ27qe1shy1RsMxV92AX5QnbLVqM9Ub1xKdms6Uot8wbGslIixP9gjb8zZD3hp8PgczJ/8+sM+2ro2AFCA1B1zhVUodSoWa3v5yOro3A2AyxFHb+CFZaSeSnrwc62Adja1fIwhKcjJ+RXL8fFRqI509W4nJSyI8PpHsmXPkil6CGYVSRXy2vB+P18aO8scxGePJTluNOSSZlo6fRn3FqshMXYVf9ADQ11/BXs8w+VlnEhVRRG9/OZW1bzB3+h/G3nRRhA2PguSH/d+Tkb8KpVJLXPRUdu97hhF7Gx6vLUC2vD4Hvf3lgMSIrS0onPvn6OrZjt3RSUfXZpLi56HThlHb8BEut5WC7LNQKoN/nHX2bGdP5fOkJi4mN/OUwOMNLV8hSVLA1f8o/m/jKBH7D4dCIWAcdUVPjdZj0imPOKpm0O7FOuIlJVpPmEkd0A0dCtmGHEZUcWyttbFqigGNSiAtRo/LIxIRIq/r8viD/gIUJpsINapIPGjS7wAJAzkAPCkkigGXjWiDhXhTON+e/Eee2PUZH9Zvpjmqh/OmHrrSlRQSxUkZ8/hhbz9KhZP4cC1NPS5yE4w43H7CfiZe/znKm23s73KQHqOnOC34hqhSKtCM2oSoR3VLx2dMx+XzkBueyJ7GYboGPQw7fEzOlNsQiZE6vH4nYYcIZd/f5aC514XV5iXGoqV/xIM4mvvplySSI3UoBIHFRRH4/BJ6rZKEcC19I94gvVlUqIapmaFo1Qr2NI3QaXUzPcdCXNjYxTwzzkhrn5OkSB29Qx6sNi+ZcWNVtf8uATsYhyJdw329NO3ZSe7seWh0+qDn/D4vbrsdv9eL1+XEaJErO4ZQ+b0c6e/DOTKM2+HA63YFif4TcwuCql+/eeWgzMfWbbDxMZh5FZ2uUAxmCxGJSSiUqsA+3rzjRmz9fWiNRuafczFd9TWo1BraqitIzC0IkDCvx82rN12Nc2SEc+5/FHOkPCTQ29LE67fdgFKp5JInX2Th+Zfy1h03seurzzj97vv56qlHcA4PYQy1MOW4k5BEkfVvv4okisw94zxGrH28dP0VKFRKLnzk2YDwv7HlG2yOTvIyT0MS/YiiD6/Xzo7yJxjao8IxNEhcVi6rb76Tulb5NXtGq1YH4wBpHB4N+i4tuIwRewdtO+pZ98YzKNVqVl37OxRqJUVL5Ru6WiUTxoEqO5s+/wshEVFc+tSLRIbLAzNV69aw642NxEy3MPW44wP7crr6cbtlyYBSocZm72D73scJt2RTlHcBAOFhuaQkLkarCWXI1ozf76a57XvCQjPZU/l3lAoNen0USqUWoyGW5rYfqGl4D502nAsefhpJEvl23dX4Ipyc8egdAd8tu6ObEZs82RpqlqcVc9JPwmSIJTpSrtYVZJ9NVHgRO/c9wbCtmbiY6STFz6W3fy8ery34jVMo4IQnoHMv5J+ITmsiN+Nk/KODAEqlljDLmNZUozYxedJVuNwDgbzJQyEr7QQ06hDiR1u8bs8Q9U2fABAbNZnoSLmNLEnSaNW0AVH0MDBUF9jGiK2N6vp3ALkNGhqSwlH838ZRIvb/GSLNRy7a31wziNMjIkkcUoN2MEJG7Qr0agXdg25iLFpKfkZcitPMxIfrAm7/IE9qZsUd2ulfp9Lw+eo7RqtAMtlJMEVweu482m1WTs+Z+4vHJoryfwCuUQF8/4iH3mEvrf0u0mL0/9A0qF+U8PkltGoFy0sj2dM4zNoKK9OzLZgNqkCA937JgdXmDXq9maOvdUfDMN1DHqZmBXtiJUfqGLR7SYqUScnkjFC6BtyUN4/QbnWjFAQSRz3F1KPf4FCDmlCjOqAXa+93IUkEDFX3No0gIWvTDkZqtJ7UaHk/n2/vweOTq2pRoRp2NwwTF6497Gfzz8BXTz5Ea2U51vZWFpx7cdBzBnMo59z/KF63m6iUNI677hacI8MBspSQm8/qm+9EZww5ZNXI5/Hw2aOyeHvVNTfJZG3DI1D9GaLXxbtf+fF5PZxw4+1kTpkeWC8kLALH4ADGUAu5s+bRXp3BW3fehEKp5LKnXwkQI6/LxVBPD6Lfh31wIEDEZA8xAyqNlppN69CZzFg72kAQcAwPUrx0JU17dpBWOhWbo4uhjj62fvQuADkz5wYmJCVJCsQb+f1uqurfAmT/q6y045g5+VY27biH/oFKCpZcSIglhuyZc9CbQoiJLKWtcwNu7wgVP31PT+N+Zp9+Dhqdnrlnnk9SYTFJ+bJNglKpxWJOQ8rVEJGYTFxWDrF5KZjtAzQMvkWceCdZaSfg9dlpHtyFUq0mKjUt6L02R8fiG1EgNscFBXPvLH+KoZFGUhIXkZ5yDK0da3E4u3F7BgNEbMTWRmR4ATGRJXT1bKejaxNOVx+dPVtxunrQ66KYN/2PiKKPtVvvwOmyolCoCTXLxyAICoz6WGz2dvS6CPqslXT1bicjZRVFeRehUuoCLT7rUB31zZ/j93vISD0WhUJFbHQZmanH4faMEG7JRqlQM6PsFlRKLZt33odeF0VR3oVylFTesTSbDcT5hgjRyoS8u3cng8MNgBDkqA/gcPUxYmvF53cGRTv9HHpdRFBlS6sJJTP1OFzugaD26I7yx+ntL6e04HIKc84NIngGQwyxUZORkDAZ4g+5r6P4v4OjROwoDomoUA1dA24spiM7TcJMamblhrKucpCN1YPMzLGgUgpB5E+pEIgNO3IrBJB//fUNe7EYVRxkEE9xVBqvHHPdEW3DbFCxqDgCpSCgVQv0j3gx61XsbR4hzKQ+LAmblGIiOUoXIDmSJLGmvB+by8/c/DAiQjS0W934/BKdAy5MOmOg3ZgRawhyxD+AgOheHC/CDTWqmZs/1mI1aJWkxxroHHAz5PCNE+cP2r3sHW0BR5k1CII8kQoQolcSalQzM9fCoN0bVA37ORIjdPQMeYg0q+nod9E/4sXh9v/LiVhcVg7tNVXEHOS7dTDC48dy8xRKZYCEHUB66dRx69gHB6j46XtyZ83DZbexf7vc8hrobEdQKKhsNDI5agqGWVcRU/cF1vZW7INWnr3yAsqOOZ4pq1Zz2t3343E50Zvklq1SpUKt0xMSERHkxWUwh7Lqmhv56unH+PGVv3P6XfchKBSYI6O59KmXqPjpe3544Wn0IWaOu+5mFCoVncPriJ8RxexTH8I6WMfazXehUYWQM282fp+byORUlCoV5z7wOHVNH7G/80MmhZ6HUqklI+U4Glq+pK7xQyzmNKIiCinIOQens4+k5BlEWgrQ6PT09u+jev87gIjN3sHap79FEkUiU1KZtHAZKo0mQDwHhuqprn+H5ISFJMTN5Py/PgVAn7UCn9+JzdFBr7WCmMgievr2gMVK0eVZREeNEbF1b76Mc2SYy55+JVAt7LNWsLfqBTTqEARBAY4QBru7AuaoZpNcrfH6nGzeeS+i6GNayY2YjAkYDbGEhqSSlXoCKqWOyPBChkdaGBjaj9fnBEQS4xai1YQgSSKCoGDWlFsRRT9KpZq1W27HZm9HodCQl3mqvP9R9Fkr8HiG6ejZwv7mz4mMKKSs8Aqy04OnQsMtWXT37sI6WAvUkZ99JmqVntrGj2jt+AnrYG3A5yvcko3FnIHJmBDQt4Hctq6qe3N0mZzAMMCIrR2DPnJcu/EAHM4e6ps+Iz5mRqDiGDi/HV1Ikh+3Z4iUxEVBzykVasomMJE9iv+7OErEjuKQmJwR+ssL/QwmnQqjVolKKbCpZhCARUXhhBoO39Y8HKrb7FS324mxaJiVe2RDBh6fyMBoJeqAd5r5oJbsAauP6aOxQIeDIAgBobtflKhoGcHhliuFXp+EX5RIi9Zjc/mobLXTN+xldl7wce7tbeKpPV9wdt4C5iTkk5NgJCpUE/S+DNm99I+2gidqCc7IsVDXIevODiZjJp2KGItMdo06WcBs0ikRRSkgwDdolb9oO3Jw21WnVmJ3+YkL/8dI8z8Kx/AQzeW7SZ5UTPb02Ydd1utyse/Hb0kuLCEi8fApBmtfe4HKdWtor6lk9U13MP8ceWgiKiWNH158hl27O2hKyefc9Pmcfvd8/D4vX//tUUb6eqnbuokpq1ajVKkCJAzGIoLC4hJRqYPPZ6Vag8dhp7uhjt7eSnoGd5GRshK9LoL4rFz0IWaSC4vJniFP/23bM+o5FTM18CNAUChQ5TehkLxYh6qJiihEHSpgde+CLkhOWEBYaAbZ6SfS1bsNh7MX9Wi8TkrCQga7OumorubdP92GOTKKSRfmYXd0YTFnUFJwKcrjv6C7oZ604sm0Ve1jz7dfMu2Ek4lKSaO9ayMDQ/W43AMkHOR9NTTSgkKhQRQ91DV+SExkEYW559Hc+i09/XtpaV9DbuapOAaGx6p5M+aSUlQCQPeotYNGHUJexBW8f88daI1v8OtnXwv4jnm8NsqrXkKl1CMpZGF6S8eP2B1dCAio1YYAQfpu3XV4vEOjWq8Utu99BACnqw+1yiCL/JVq/H4PyQkLaOtcT1vHOnr79zJn6t0oR/Nts9JOQKcNQxS9VFd/yN61G9D251Awf3HQ5zo4tB+3Z5jM1BMw6qNQq/Q0t63B47Wh00YQGz1mT+HzubA5OhBFb4AYgpzakJ1+EiO21kBrsbVjLeXVLxERlsf00huZCI2t39LWuZ5hWytzwu8Mem5a8fUM2VoOa8VxFP8+OErEjuKfCp1GybLSSLw+kR/29uOXQHvQVKDPL7GldhBBkEnQAcJR1yGTreLUEJKjgnVCBzRY2sNML9pdPjbVDBJqUDM1K5RtdUP0DHmChgIOB6fbj1+SMOlU2F1+1lVaMWqVzMkPC6qW9Q552N8lDz3MzAnFoFOyc/8wbf0u9Br5+NxeEVGSkEZ1Xd2DHt5o/YEfW8tx+TzMSchHEIRx/mFbaoewu/34RInseCP1nXZqOxwUp4aQEKGjrc9FVZsdhUCQFYZKKTArNwyvb1SUrxBwuP2IEgzafUFt0SNFS5+Tlj4XCoVwWJf+/y7621robqgHQcA5Mhxww58I2z59n03vvTnh5OPPkZBfSO2WjRhDLQCyB9YoipetxD5gJW/eWCXhs0f+Qv22TaSVTmHeWRdMuM3U4jLqtm3CPmjF43QEVcXSy6Zy7DU3YY6Morb5bYZtLSgEJfnZZ9LtXkvmORYmF8mTnf11vajckcSk5LHnq+/Y+uE7zL/oXHKmzWf91rtwe4bw+uSIqBBjApmpq7DZu9i88z7iY2ZQnH8Rc6bexVB/J2/ffAdag5FpJ5zCl0/+lYikFES/D7fDTnrSsahVBtKTV2DQRzHjlFPo6NqCUi+x6b03adm3B0EQWHn1b4mOKKal/Uecrn6Gba2YTUl0dG2mZv97gIROG0Zq4hJAbpelJq8gxJSEQR/NE60DtLm8rDz+ZHy2YRJyx6o3ff37AIiNnoJeNKNUqzGEhiEoFDiGh7BZ+/HquunukzNel89/GqVSQ2LsbGy2NuJjxixA3J4hfH4HIBBqTiMyPJ/4mJm43AO0da4HIDqyGL0uivXb7kKtMjAp9wK27n4A0enFL7oDRGykZwCtI5n4nDzad7RQu+9rvq15IoiISZLElt0P4ve7yUw5DpMxHo/XRkWtHH0zueg3xESW0N23G6M+Gqd7AJ/Pic3RhV/0BqYmATJTVwWdS5Ikjf49dK5iQuwsRmxtJMWNl17o9ZH4RS87yp8gPmY68THTJ9jCURwpHn/8cZ54IviakpaWxldfffU/sv+jROwo/iVQqxQsK41EkgiaCrS5fPQMyRNKdrc/UKXqHfbg80v0jXjHEbGMWAPxYVp0o0SnpddJ34iXgiRTIE/TavOO+pz5mSyZA8seIEcTobLVht3lIz/JxA/lVvyixKKiCBwHTRv6RClgAdI37BklJlr0GiXRoRq+2NGH1y8hIFfZkiJ16DVKvt3dj9cvIgAen8Ti2Nl4RS9n5s0/5PFEh2pot7oCNhhdAx7cXpGeIQ8JEToizGpCDapAK3XI4aV70ENatB6FQuC7vf24vSLz88MI0atwevwYtId+/S6PHwkmnB71HDCU9Y6/UQzZvfjEiY1of46eITcujzjuMz2ApPxJLL7oCvQh5sOSMID47Dy0RmPA9+qwkMDncVO5bg3LLvtN4OHOuhrCExI57vpbAHDZbGz95L2A11VSQRGRSWPiZp/PSUXtGxgN0aSWzMPndtNVX0tz+W6yDs6jhIDX1lBdPm7PEFHhcmyQdaAGn99FV+9Owi05fPnYo4h+H/GXL6V131o8Tietu2tw9jlRRKuRp+vaIQbszm46e3agVGiQJD/DthYAlEoNnmE3Nms/9sEBNn8gt76UKhVn3/sIhlALIRGRREbkBI6vruEjmtq+oyssj8nHngiCQPFSOTi9z1qJWmVEodCwr/plSgsuxzpUC0gYdFHMmnIbGk0IHq+Njdv/iCh6mTXldiR9Evetl8nWkmWrWRElRyp98cSD5MycizrTBM4eVCo9DqmBi598Dp3ejEKh5PXfX8dwbw/H33gzSfHzCTEm4LY5WPv6UyRPKmbq3OsRRR+dPdsIC83C53Mgij4EQcBkiEUQFJQUXIIkiVTWvYnXa8diTmfE3jG6rAezKZGpJTegVhkCbvUel5PXb7kOr9vFaXfdR+a06Qz0tBEXUxr0eQqCQIQll4GhOuqbP6Wh5UsWzPoLyQkLcLr6CQ/NorNnO7v2PYVaZWTJ3MeYXPQbdNqwIBL2c3h9Dprbvsegj6ak4LJDLmcxpzGj7HdBjw2PtKAfrcy1dq6jp283Dkf3fxwRE0U/7VUV2AYHMFnCSMgrQKH4r/sYHgmysrJ48cUXA/9WThC99q/CUSJ2FP8yHIjgORgWo5qi1BAUQnCrsCTNTIfVTVKkjmGHj64BN6kx+oDH1sFmonsaR/CJEqEGVUB/lRCuw5UiYtbL1hZl6WYKkkwBy4hBuxe3V8RiVLO1bhCDRklLnxyhEh2qDQRp+PwisWFaJmeY0WuUgUnIQbuXdZUDCAKsKI0MbNekVzHs8FKWbqamw4EA5CWZcHnkilRqtA67y09pWibH5o3dFH1+ifVVA/hF2QdMo1JQlBZCYqQu0AYtSQuh3eoOiOlNOhXzCsLpHnTj8YnsqB9myOHD6xPJTTThF+UqnAQsKooYF8h+MNxeke/29OMXJZYURwSFfTP6GqJCNeMmZV0ePz/usyJKsGhSOKGHmPwEuT28sWoQCdBpFIf0nytZtvKQ2zgYqcVlXPXC2xM+11Fbxe6vP2fKcScRnZpOyqRi4rJyAhYGALu/+YLv//4UCbn5nH63LN7f9fWnbPv4PUIiozjzT38N+Jw5hofwOJ04hTbau+S4ml2vyzqzpMIihMgBevr2BFpNAG6Hg5G+Hrr7duH2DDEwXE9U5CSiIotpbvuOnr49FGSfScmylbTXVhCfl0tyYTH12zfTsm8P6996hexFZWQtXkFqklx9Ghyqx+7oRKFQE27JxeHsCVSsWmyfkXZsHBZFGbs+/RwEgazV6fT5tpAffua498hiTkeh0BAWmkV6+lTSy2RtnSSJNLV9B0gIOHF7Bqhp+IDe/nLiYmaQm34SGo3covX73WjUIfh8TpwuK57hJq5LzqLV7WdumEx0mvfuYrCrk+qNa7nglL/h8Y6wfe8jjNjacCUO4W0JIbVkMiqNVvYR05rIyj2P7t5drP34SSp+2sT+7ZvJn7uQ+qbPqG/6hLDQLGZOvoUZZTcjCAr0+rGYMEFQEBmWT1Pb9wyONNPa/iPhoTnkZJ6CRhOC09lLx1A9hszT0GhCUKpUmMLDsVmtKHQSu+ufQZsrkT9tfGt8SvE1OF1W1m+9E5VKT29/Bd29u8hIXYVabUSvi0Ch0GA0xCIIwhG1Ct3uQUbsbQD4fA44jJ3FwWjr3MDeqr9jMWcwa8qtJMfPx+nqIz76P4uE1W3ZyA8vPYtt9McRgCk8kkXnXxrIKP1XQKlUEhV1+BzdfxWOErGj+B/HROJ1g1ZJ5uhk5qbqAQbsPtw+ccKMx5xEI33DniDhuUIhBInKPT6Z6GhVCqZnh7K2wopfhNxEI33DXsBLXqIRp0ckIUKHzeWntsNORbONuQXh4yo4WrViNEhd4Pu9/WTHG8mKNzK/IAxRgtY+J8MOH3aXj5J0M/MLwxl2+NjZMIxSIaBWBRMit1fWsIE8yagxKUb9whwkRGiZlmXBpFeRkxD8Fd3XMkJjt2zBERumxe0ViTJrUCpkOwvvQU77giDg84u09buJCdWMc8Yf7Y5M6NmtEIQAcXJ5/FhtXmLDtCiVAlq1Ap9fGhdC/nOolLLXm0+UGHb4JiRidR12rDYvJWnmQHUz8B55hhH9nqCb7qGw6b03adqzE7/fz3HX/o7Q6FjO/NNfg5ZRa7Wjf8darell06jbuonsabOIy5KJss/r5ZUbr8IxPMSpd91DQuwsjPoYNnz5NQCxBUnUNr2PIChZNv+pgDD7nT/cQk/jfqacuQxznJbo0ZtyfMw0unt3BuwUcleW4kzeTHXby8yachtlxxyPRqenq76WtOy55GaO5QXGx8zA4xkhJCSZ3fuexuuzMzBYT4gxAetgLbpEP9k5JagUejShCqz2H7HaIT15BSrByFt3/A6v28Xpf/gL8bEzArYIuyueZWConinF1xBiTKAo70Ja2n/EaIhFpw1j2NaC12fH63QG3n+3Z5h1W+9EkvxMKbqObXseRhTdnJl7PkkZ8wLHXHrM8UhIGNJEmtt/ID15OVHhhbjdg7TvbGLPhz+RXFjEWX9+CJdtBHNkNKLoY+e+J/GEeonPzyR76gJ8PicmQywgYDTEIkki4aO2EF09OzDoozCHJAPQ2Po11sFalEotPX1ycPqBHyGVdW8iil4s5nRSEhehVKk578En8Xu9KNQChq4o/H43jS1fExs9hZjIEgaG9uPzOYiKmIReF86iOQ8hoKC8+iXcniF6+/aQmrgYizmNJXMewed3/+I5egAmYzxZaSfS2SPr/EzG4MlGSRLZtvthHK4+ppfeGMiZPKA5O/DXaIihrPCKI97vvwPqtmzkk4f+PO5xm7WPTx76M8df//t/GRlrbm5mzpw5aLVaSkpKuOGGG4iP/5+ZOj1KxI7i/xxiw7Q4PDLBmAjZ8Uay4w8/yTfi9DHi9DOCrLky6lQ43X4SwrRIEph0yiCyZRr1WjvQ0uy0umjpc5GfZCJEr0KvUXJMWRR7mkZo6nHSPeghK96IIAgoBUiK1FPX4cDm8gesO5QKAZm6jYdRp2R6diiDdi/7uxxkxxsD1Te1UoEoSgzafVhMqqCg9gPHadIpyU8yBenf9Boleg10D7rxixLx4Tqq2uzUdzqINAdPYmrVCpYUR9DQ7WBzzSCl6WZ6hzwMOXzjSNHm2iEGbF7yk0zkJBhZWiK3nH9uDvtzKAQBs1GFdcQ7YXqAJElUtNiQgOhQV8CIFuSW4Nott+HzOZkz9U5CTIlB6za2fktjy9cUZJ9FTFQppccch+j3UTLqd+Xx2kCSApUcgIL5i0nILcAUPuZSHpOWwbn3PzbhsSGBUqFhUtb5eLwjnHTLLL7/+1OMdAxjjI0j1JwUNB134AYZG11GzrQ5gcf3fPITtp5w0i6X43FE0T/61xdYJjF/EvPPuYjsGWPrVa3/kY7aKmafdo5cxRmagilRR2LcHARBwfTSG7E7ukiInU7imTMRRR/V+zVo1EZGbO2MDHTR09wAkkT5D19TsGAxfSM7MYek0t23C7/fzdBwIyHGBLSaUAaH9zM4vJ/Fcx6ms76afZs30ti8gZKCS9DoDUiSPyBE31fzEqLoRqXUExqSGjjmXmsF5VUvETupjKa272FQnibMzTyV3MxTqVr/I/tUG4jLykOj0wd84zp7thFuycVrsrNs2ZXUNHzIN2uvoqTgUhbOeoBNO+5hzcYbmTPtbqyDtezc9yRKpZalc59AoVCSlXYirR1ryUhZSVhoBqLoCxxXQuxseq3lQcepVKlRqtT09O0hPmYGouinoeVzrIM1WMzpbN55H5LkZ+bkW1EqNXR0bSIlcTE5Gb/CaIghOmKsErq78ll6+vZQWnBZIG2gp38v1XVvk5a8gqT48Rovm70Dm72dprbvgqqqIIed9w9WIUkiI/a2ABFLiJ1JaEjqhAHg/wkQRT8/vPTsYZdZ8/KzZEyd/k9vUxYVFXHvvfeSlpZGb28vTz75JGeddRaffvopJtMva4z/uzhKxI7i/xxyE03kJv73Tv5Is4aydDMalYBBq2LRpPCAXi1/gnZaSrSeGIsmQECq2uwMOXzoNIqgcO38JBMGrYLuQQ9f7exlTn4YJp0qaMrR5vIT5hNp73cxLctCeIh6QiISH66joctJ77CsmZuSGUpihBaDVsmeJrny9XMT2cw4IynR+gBp+znsLj8bqwcBWDhJicWoQhAICvre3+Wgtc9FSVoIXQMeRpx+Ovpd1I8OIcSFuceR1AGbN2AMfCQmr1Xr1oBCwewZc3G4xQnzMAVBID8R2js+RytMBn6m/TogaJ5g+929u3C5rfT0lxMTVUp66VRSi0tRKFSjYcm3Iko+5k2/J+jGZYmJpau+Fr/fT0JO3rjtej1uPn3oXiKTU+UA7ORUtu76K30DFaRHnsL+7VsAOGPZg4G2Z29zIxVrf2DFFdciKBREJIxNdLrsNnZ8JgdW581bSNbUmSTEzpDba9qx4/roL3+gv60F+4CVKcfJDvjfPPs4PrebiIRkbANWtnz4LnGZOUwqlTMyw0IzCAvNCGxj15efsf7Nd5h15pnU6h4FJFbccCk1321n/Zuv0GXdhjq1H7XKSGrCEoZtLcRGTZHfF3M6EWG5OF1WOrq3YTJnoo/UEBKvAUH+BHTaMOZO+yMSIlV1b2F3dFOUfxHmkGQkSaS+6TP6B6pxufuxDtYSE1mKX/QGVXzy5iwgb84C+b32yeebzd7OnsrnAIFFsx9Epw3D4ewBJBzOXkJDUnG5B+V1vHYM+mhUSj0mY3zghtxT0cVwiwZ/lIoNT35JSEQkGTceiyAoGRpuwOXqZ+emV1m0Inj6cOe+vyGKHjLTTiDckkNsVBkqpQ6DPhqvdwSd1sK2HY9jc7fg8dooyrsQlVLH+m13kp58DLmZp+B2DwFSIOoJZId8m6OTjq5NJMXPpbtvN7X7PyAjZSXxsTPISFmJICjHWU8AqFUGphRdi8ttDegMD8BkjBu3/H8K2qsqgtqRE2Gkv4/2qgqSCooOu9w/ivnzx7S7ubm5FBcXs3DhQr788ktOOeWUw6z5z8FRInYU/7FIiR4jExPp1X4O3UGi9ZwEIy19TtKig9uoWrWCzDgj1W12RAmGHT5Mo/qqWblhDDq8xIdpA5YbJp2SpSWHbq2lx+qRkAI6sANarQNVsInC2Q9FwuTjEzAbVPj9EnqNEotRTWKELkgr1tAlV+7a+12UpIfQNeAmM86IQadiaAKvsckZZkrSQlAdZr8Ho7eliS+ekNuC56emBxGTA3ANSGgtIHi34LStp6a+ivjoMSKmUumZN/1P+EU3Br1skLr29Rdp3rublVf/lsKcc+js2UZygnwB3b73Mfr69zGl+DpMxjh8fjlk3ucLbhkN9/Xy5h03Iooi5z/4JBGJcmtLEkUadm1HqVLRuGt70Doen+ysrg/XMX31qfg8bmIzxzzPfnzleVr27cE1MsyKK4J97XRGEwvOvYSh3i7SiicjiSJ2Vw97Kp8FSUCrNRMXPRWDxYK1o43wg96raSecTHtNBe6IakS9A6VGiWi2MmJvx2SIp6L2NdzuQbKTT2PL++/T3VCHz+uhd38ThpJYUPrJLJ6Pd0BJ4+4dhBiSQAthoZnsb/kcgP6BKmKiSlGrDcTHzKC8+iWq699i9pQ7MWfKFWmHpweNTvYL8/tddHRvpiD7bPyiB53GAsg+ZHWNHwGQlriMhPjZCB49xtAwFBOInt3uIdZuuQ2AGWU3YzTEoVEbUY8K6pPNxzJc8ymhmQUYDTFMKfoNfdZKFAo1RkMMS+c9HqhAin4/Xz7xEJIkIokivc2N9LU047bb0YeYCdeX0FlbT+OmXRTmNgQC1N2eYUJDUvB67STEzCA77YTA8c2b/idAYtdXn1O7aR8xU8OIjZ5CR9fmQAyT3dEFyDqyEVvbaMSTyKYd92J3dJEUN5eUUa1fR/cWRuxttHdvIj52BuaQZEoKDh3UfcAM1+nqZ2f5k4SYEinKu/CQy/8nwDY48E9d7r8Ds9lMamoqLS0t//J9wVEidhRHMSESInQkRExs26BUyHYRdrc/iLQYdcpA1SjaoqG133XIbRxAfLhuQnuISSkmUqP1hOj/sRK8SjmWkXkAPxfsF6eF0Gl1kxFrQKdRBqYfJ9LuHVj/cG1Iv1tCqR173hwZTWxmNoIgBIKsD0bdByK7H5dIP14g+5Iy+qz7iImaPG45rTbYx678h29w2UZo3ruTspUnkJV2PH6/F4ezjxFbG6Lkw+7sIjI8j9aP7bgdNpIVFaROExgabiQueioavR5DqAW/z0dfSzO1WzYwZdVqKn78nu9f+BsRicksPF+eZItKTgVkzyabo5NQUxpb6+7CZbPhstkCzvp5cxcy1NeBMm4Yh7MHgz6a7oZ6dnzxMaUrVjF5NJB855efsublZ5lx8smoovWIog+Xe4DOnh10VNchiSIepyPwemf+6gyGRprZsO1ueT8XJ+D3u7AO1KBRmWhpXwOArUbFnm8+R6M3sPjCX+P3+fjxieeISk1nwSwzSpWK1NLJlC08FUtMLJIkoVCosDt62PLGZyiF71hxxXVER5YQGz0FS0gaJmMCKqUOn9/F/ubP6bNWUFJwGY0tX2MdrMHu6KXXuge1ysj8mfdhNiUTHVGMSqUnQjOVLW9+wt7vviRr2iyOv2EsbxLAZu1nx7fv4I1yyq19pZb5M+4JWmbrBx/RuGs73h41x113M919u2jtWIvd2c3U4mv5/oVn6Kyr5rjrbsESE0vpilX0NDdQesxxmKOiMVosqEa/i9m5x1L/bSVJGQQR3Zr97zEwVEdURBFGQ0zgcY/Xxq59T6PThqHWJjFU4yLCmEjYMZl8u/ZqQCI9eQXpKfKQiVZjRjtquOrzexi2NSOKPmKjp2A2yfvLTjsRrcYcZEXhcPbSa91HQsxMlEotfr8blSr4WjAwVM/QSBPDthYKc85FofjPvWWbfmbU/N9d7r8Du91Oa2vr/5h4/z/3Uz2Ko/gXIipUw+G+ohEhGpYdphL2SxAEYcJ23pFC9Eq0r5eILBTQRwWTqOhQ7SEnGNvWSog+ieRFR1b96twkseE2kYS5MPMu+canNRg4656HgpbrGXSjUMgpC87R7oOzTyLElBgUDD0RJL+E6IOVV/+WjppKCheOidm373mY/sFq8jLPQKcLCwjio+Kyaa3cR2RiMtv3PILD2YPXayM1aSkXP/48kgRPX3Y2brsdnSmE0KgYBIWC0OgYyo45Lmj/Gk0I4ZoQRqx9tOzbA4C1oy1AxAoXLKFf+z12ZzOb1zzNopV3sOXDd6jbuhG33cbq38ntsJ6m/SBJ9DW1Ea2YSXhSIqpomzyBeNYIA7v8xGbIU5t7q16gf6CayUW/ITF8EdUb1mLWppG9OJfEuNkolVrysk7HOlBLt7OSqKwkciYvpGT5sdRu2QCCEHC33/jeG9j6+6jKXMPMk89AEASK8y+iZtf3bNr4MAAzTz6D8PjEgPhbkiQ0GjNeh4vh4bZRPVkDCbEzsTu60KhNiKIfv9+Dx+ngh78/h9ESxoJzL+bJi07HbZd90Jwjw3xw3130tTRzyu1/Iiwugc0fvsOebz4nsTSLlVf9FsMEwxiTFi/HZRth0uhnHRaaRUfXZsIt2XKw+A9f4/f5aKssxxITy8LzLw2sW7p8FRu2/YH9619meslvCQ/L4fjrx86xrv11fPrwvaTMTUMVpyciLLhF3dGyk/6BSgCWzHmUpIIiQiIi5CDxmBk4Xb2kJS8P2GEcDJVSy/TS38ltxYixtqLREEN+1hlBy+6pfI6BoXqczl7cnmHauzZRUnAZ8aM6M4CYyFIyU4/DHJL8H03CABLyCjCFRx62PRkSEUlC3uHzOv8ruP/++1m4cCHx8fH09PTw+OOPo1AoWLVq1S+v/E/AP/TJ9vT0sGnTJiwWCzNnzkRzUMCuw+HghRde4KqrrvqnH+RRHMVR/GOoflOi4kWJ8HyJxU8eWVXN1i6x6U7ZN8ycLGHJ/GUtmK1dQhJhuFn+d+sPIsMtkHeWgEItrz9k97JhVLe2tNiCrexBwrKGKC6+GZB1Ur39++ju20lm6nHotGO/eCVR4rvLRUbaYNHjZaSdFlw58/llCxKVSktc9JTA46t/d2fAvqPTlYrLbcVklAX/SpWa2oYPiS6MxdHuIbmgiIjEZE554GaqG96gvulTMlNlMiaKfta/+QoanZ4Zvzqd466/BZfNRmJuAY7hIT66/w8Yw8LJXDqNrqr32L95B5MKGilethKX3UZsRjY7v/yUkuUrWXDuxSTmFeJxOVnz4jMoVSquee1Dtux6AEHnoeikuVhiZQ1QZ88O/H4nre0/4Wk10Lq2A6PFydLzr2XNS8+jMxqZc/q52OydoLeTc1Iu08tOBSB7+mwuffLFQDB64YKlVPz0XYDkgdyW2z/wJpFTjKSnLg3ESImin31rviMiMZk5U+/ks0f+QnntLmacvZL0lGMZGm7C7RmitXMt08tuwqCLpHHfRjo6tzCy0c2U41YTk55FZ101c8+6gLDYOD68/w+IPh+9LU2ExSWQNXUmrfv2kFO6hBBTwujxDKFWGfH73ewsfxKNPoTT//AXFAolkiTicPaSk3kKqYmy4epx199CT2MDubPH+/L1WStxuvqRJD8uzyDdvbsIC80MDG60V1cw3NtD4xoflz39CgC1WzZgbWslNjOLD+57kMR50cw84Vw0mhA0MWMDHz9vJ/p8TjbvvB9JEplRdjNqtWFUt5fBLyEsNIuhkRZCzek0tnwNSPQPVAURsd0Vz9Ddt5vJk/7z76sKhZJF51864dTkASw879J/iZ9YV1cX119/PYODg4SHhzN58mTeeecdwsP/ZwYjjpiI7d27l4suughRFPH5fMTExPDkk0+SlSVrJRwOB08++eRRInYUR/EPoGfExc7mARbnxRxW+zURJFHCPQi68PGEKSQJUIA55ciDzHXhoIsE0Qu6KImJ5z2DkblaQB8tEJYNfo/E5nskEMGcDEmL5PW1agU6tQKlQkCBm6GRRiRJxCP0coCIVda9gd3RhUplIDfj5INeI9g6wO8CZx9YMoP3P63kBoZtbXT2bMXT9DkZqccGnvv+708x0NXJsb+5kZKCSwOaIrdnmPqmTzGVQOnyM3Ha5JzOYUcjXp+DPmslem0EbZ3rsTCZbZ+8D0DO7HnEZmTz7XNP4LKNEJ2aTmd9DQgCCy+4jMYf60hMd1K/bTMlK1ax+qY7ePyCU5FEkZDISLKmzkSpVrPhxWcwWMJIL50iDyxknU579+YAyQBITphPY8tXtHWuZ0rpLWx493WUGg2tFfvY842s7ypcuIzs9NXodeEYlam8ctPVxKRnsvzya4Jawh21VYz09VK57gfSSmUiq1JqMRqiUE01UFg4VmGs2biOb599HJVWy29eehfHwDDeIR/CUCQqpRaTMRaTMR7voJINL7xPwaLFNI98TOKyUEJsUwgJj+SU2/6EJEl89/yT/PD3v5E9cy5JkwqIzI5CkiRSikq44OGnA/vs6d/L9j2PEhaaQVbaavoHq/G7RNJij8USmUxX525qaj9CqVEQG1WGThtGxuTpZEwey8m02TtJjJtNd+8udu57ErXaxPTSm+gfqKa+6ZOgKKGipccgiiIJOaPtRK+Xzx6WydS0E05GEkUGy/0k/XrMkuNQcHmGAia7LrcVtXp8e79/oIaOrk2kp6zEaIgOPJ6beUog4NtkjGP91rto7fiJpPh5WEaDzB2uXkDC6Tq8iP0/BVnTZ3H89b8f5yMWEhHJwvP+dT5iDz/88L9ku0eKIyZiDz/8MEuWLOGee+7B4XDw4IMPcvbZZ/Piiy+Sn5//yxs4iv8v0T7o5P4vq1maH8Nxxf9cTxa/KDHg8BBp+ufkIfpFiYqOIfLizP8wKfqv4orXdrK9eYDrl2bzm8XjQ689NgmXFczJ40nRtr9INH8tMfl6gfTjgo83aaGC+NkSSs2REzGXFQ5c70eaBXRHMJgkKAUSD7pfpR0jMNwkETlpbL86jZIVZTIxEASBqcXX4faMEBE2ZnCbmriUju5NxEePVQMAFCqBRU/A/raPccYbgBVBz6vVRnx+Z0AvlRg/F63GjMfpYM+3cp5je1VF0AVcrTKQmXo89pEevvzL03hdLk678z4yM1bJYdBeG/tbvsRmb8cQE0vu7PlodHpCo2PY/fUXNO3eQXtVBVe/9A4Lzr0YoyUMc0Qkq665iddvvZ6N776O22Fn/jkXkTF5OgOd7cSkyRWStspyPC4ncdm5LL/8Ghp2biM0Ooa8zFMZsbXT3rWJ+JjpJMXPo89aQXhoFv09+/G53dj6+wlPSKBg0WJ0BjMas5qN2/+IThuG26aXReqtLUSnppMza16gdTrl2BNxOLsQEjsZsbcTYkxAqdQyb/qfef331/HSs7/h5Nv+RNX6H+ltasRoCZM1fgoFJ950O92N+0ktkl3ny7/+nopPm4hITKK1Ygf2oQGSVyXidPUxeekYgZaHY+Rz0hwZhTu8is27PiAv83TSkpcFfYZerx156lA+J1KijuH7B9+i6Z3fcsYfH+DDPzyI1+Ng5hVLEUQN7/7pNlRqNcdddwtKtYotux5EFD0olRrZYFVQYdBFEhGWi8PZC4BeJ59/1sFayqtfJql4LvHJ8tSrSq2WrT1amylZvoqcWfMwhUfg9dppbv+R6MginD1uPn/8QbKmzmD26efQ2rmWEGMC4ZZsyiZdhSSJ4yxWDqB6/zsMDTciKBQU5pwbeNztGQqEoRt0kei0YXi9dtSqMWueqcXXMTTSTHTEP3dK8P8ysqbPImPq9P9xZ/3/TRwxEauoqOCOO+5AoVBgMpm46667iI+P5/zzz+f555//HzM+O4p/L7y9rZVP9nSwo3ngkERMFCWa+u2kRcq+XJUdw9z7ZRW/KkvkxNKEQ277ytd38lVFF4+eXsIJJcHL3ftlFS9vbOKR00pYURhHXfcIb25t5awZyWRETWyNcc/nVbywoZGzpidzz+pJEy7zz0ZapJEdLQOkRBh46sd6AK5YMFb2+f4KEVsrzPmzgriZwaTK1S/bCjitE29bqRHw2mS3fU3IxIRMkiRq35ZQ6iDjeIGM4wW8TggfNaT3DEvsfVYishBSVxyenIqSROSVXibrNOMGBA7+d2T4eI1HSuJCUhIXTrhdv6WersbP6KqHMEMeG157i/CEJGadIrvHR1hyiIuehl4XjlYjW31o9AaWX34Ng92dpE+eGthWR/dWdlc8Q1L8fIoKLmBX2HZGrP3oQuT204FJuJyMU7DZO8hIW8Gkgmjsjm66G+pxDA9SMH8xyYXFCAqFHBWEXFX54M93MNLXi9ESRkpRKYIgcMJvbw16LXNOP5fw+CQyp86gfttmPn7wT2j0Bq584U227XkIl3sAv99NcsIC5k67m8raN6gffJWys+aRnb2K6tZXkbKrKSy+HoezB6erH5d7kJIZVzDHei77d27lhxefobOxmqQFUVhC00krnceeOoHhvi66u8rZveVbYrNyyJo6E9tAP6LfT3vjLsp/+AYkKcg00xBqIa1kMi379vLDi08j+v04hgaJz8kjrXQKmVNnkJU7C50pZNxnvuiCyyheegzacBVVdXIE08/F6CD7Y+l1ERj1MQiCgqS4BYj+N0Dy43E6cNsdSJJIZtKJDHR00FK+G4Dhvh7C4xOJCMtleKQZsykJkzGexXMfRanQ4HYPYdBHsXTuE6hGw9F7+nZjd3TS3rUpEDoOsPTSK/H7PajVhkA1sbr+XRpavqSrdzvq9nwGOtqoWv8T6Quzqah5FaVSS0bKKkTRS1ba8ROeuwCpiUtoaf+RhNgx5/72rk3sqXyOmKjJTJ50JSAwa8rtKJWaoHgkl8uKJSQtQGr/f4FCofynW1T8X8Y/pBFzu4NHwS+99FKUSiUXXXQRf/7zofu6R/H/L04qTaCyY4hlBbGHXOauTyt4ZVMzVy/K5IZlOby7o5V1dX20WB18tLudS+emMytzvKC3Z0TWB/UMj3e13t40gMsrsqt1kBWFcdz/VQ3fVXXTOeTkb2ePn9ADOFAEG3Z6/wuv9L+GB04p5q7jC2jud3DNW7sBmJ8dRUG8XM0I3Nom4FEz7lBgrYKY0ZfTs1NCZYDwXHlh95DEV+eJiD5Y/oICQ/T4jVirYO8zMqGLmSJQdl3wBb/lB4nGzyWav4XUFeNWD8Ld9R0809bLNSkx3JJ+5H5HPX17qG34kPSUlUH6GJD9whpbvyXMkoNRH0VXTSM1m9YBMPX4k1BrdahUekoLLx+33YNF/Qdgs3cAEjZ7G0qVmnMfkB3WtQYDfr+H0oLL8XhtJCcsDBCLhpavqK5/h+b3HTj6bMz41RmYI6Op2bSenJmyAatzeIjWynIA5p9zMT+9+nds1n4mLRqt/rhcsK8cfUpKYIrSZbeh0moJjYkGJELNaXj77ZiMCePiqaJzExju7aVxdyWmXBGnq4+k+LnkZZ5B30AlDlcX01efikqjobepAW2yk9bOtbR3bSQucgZNn/Ti9/qIEOrY+93XqDRarnn1faZcOIfG2nV4IutIX56C5NAEEdcDqN+2if62FiJTUpl75vkULlzKYFcnb91xE5vefYOLn3gBpUpFw65trHnxWSYfeyIly4/FEGVk7ZZbQYIZZbfg6ZN45caryJ2zgGknnIzo97Ptk/cJjYkld5asYTNHRnHO/Y9S0/ABff5NnHXvX0ESCI+Xf2wtPP9SlCp1QNc2tfjaoGNVj5KuzTv/gt3ZyaTcCwKmqmnJKxAEJTFRY7mSkiSxftvdOJzdzCi7GYtZtreIDM+no3szMZGlJBcswe/1klxYhDkkDJ02DJMxgdoGuW0dHTEJy0Gebn6/FxBRKrUkxM4kIXZm0DEe8BzzeIYOMi92MWfa3aj0MhHr6tnBzn1PotNGsGj2A+M+k6P4z8ERE7GsrCx27dpFbm5u0OMHdGPXX3/9P/3gjuJfi50tA3h8IjPSI3554f8iUiONPH/e+Av7wXB4/EF/z5+VyqDDS3O/nR9relEIwoRE7PnzpvLBzjYsevW4G9cjp5Wwtq6XE0crZSeVJdA24Dhshe3YSXE8t66Rryu7sdo9hBs18kW6vo/cWDNRIUfeAr33yyp2NQ/y0GnFJIbJupGarhESwvSYtMFfO6NWRUa0kWMnxSFJEu33GWju87PgUQWLn1LgGoCQpPEkShMiEDvKWwZqJH66QURQwaq3FejCBUQv+ByyzupQCSyhaRAzFVQ6MI5O8A+3SGy8QySyUKDgPIHOzRJRRb/c4hzxy5/fiM9/hO+SjPauTQzbWmjvXD+OiB2IrkmInU1R3oWsff0lBIWS3NnzUGt1o1YDf0Ovi2BS7gUTZmvaHd1s2nEPBn0M00p/i8kQS/hoW1SlVqNSq+nq3cmufU8RFz2NkoJL6e0vp6Hla7JSj8PvdzNQ5UStVxESGUVcZjbv/ulWRL8ffcifSS4sIiQikuOuvwW3w057VSX9bS1UrvthjIjt2Q27d0FjA5wiG7LGpGWw6g+XUr3/LXZXPkuYbzpm4xT6a3t5+ZHfUrRkBYsuuIyEuNkofSaeuf08AObnn8WedzbQGL2fyCkaevv34HYPMGfaXUw+9kQGQn/E7WnCbEomLnoqSrWa2IxsrO1tZE+fQ29zEwmjwwYqRwxJOcW4+nxoU9oRBDfCBN510048BZVGQ/aMOcRmyC30it0fIHHAq03C43Ky47OPGezupGbTOkqWH4tSqUap1CCgwGiIoWrHx/S2NOFb8y3TTjiZ/Tu2sP6tV0AQSC+bitPbg0ZtQmWWGPTuZbATkicvoruyDZ3RhDkqmrJjDl19AplY1W/dRM/+ZoxxmqB0Ba3GTE7Gr36+Bm73IKLow+MZCTwaGV7AotljMVkHKrAAi2b/FVH0U179IqLoJcSUHHjO67WzdsttiKKPudP/EDR8cgBpSUsJMSUSakrGL3rxeEcQRb+cPTkKuYonoFEfPkXkKP79ccRE7MQTT2Tr1q2cccYZ45675JJLkCSJt9566596cEfxr0PHoJNTnt6EKEl8dc08cmLHZzoeKd7d3spjP9TxuxW5rCoaaz8+v66Bt7a1cs+JhaiUCv6+voGL56ZTlhx8YbpndSGnT02iJMkCQEqEkYdPK2FXywDPrm3gojmycLWyYxi3z09pchh7Wgf5rqqbp3/aj9cvYdarg6puSeEGzpqeEvj3yklxrJw0cZVmwO5Br1ESYdJi1qkw69Xo1bIe4ZVNzdz5SQWFCWY+u3p8VMkBbNrfj06toHT0tb24vgmPX2RdXR9nTEvmw11tXPf2HkqTLXx4xfhwYa1KyZNnleEekvj0RVEWqbdCdJnABFPy49cPA40Z1CZQ6UH0SegjBZY9r0D0T0zkAFR6gXl/CdZe9O2VGGkGR7fElN8qmHvfkWkz7o5L4JTYcKaYjfTslvAMQ+K8XyZwWeknotGEkBQ/XhydmrQclVJPevJyADrrq5FEP/oQMz6Ph13r3qVfqAIgN/PUCS0F7I5uPF4bPr8Lye9H6YhEE20OWsY6UIskidgcnYAcodQ/UIlGbSQn+Qy61j4HyNOYKUWlRKdlMNLfhyVWPudE0U9cQQpaZQSb3n0DpVrN1ONlzdTwSAuV4jckxOhISvr5jxIfgiBg67Gy5tk/gCRRvOQYRL+fpr278Ht9hIakIPr9ZE6dgX1gAL0ihppNrwNwzqL7GQptIjFuLBopxJjIgK+OgpyzCQuV29wHQs57+/cRucxNdJyRzx97gJby3RQtWcHeH74iYpKBWSdeGLBJcAwP8d3zTxKTlsn01acy76wLAPD7fLhsIwiWETJOCycxaSZKlZrvnv8bLft2E5mUwuIL5QqlThvGwpl/AQTUagOlxxyP3+8nvVSecI1KTSc6LYPIpBRGnC1s2XU/apWRhbMexFcbx3DXAJXWjWx69w0ik1M574EnDnsudfXsYHfFM6idCbR8PkhcdgYxi0vGLWcdrGVouInkxIWsffUl2qoczD337EDc0LCtjYGhOhLj5gTFWB0MhUJJcf7F4x73ix48XtuoobCThq7N1Dd/TmH22YGsT0FQEHVQi372lDvxi55AdibIFblFs/+KWjWxv99R/OfgiInYKaecclir/0svvZRLL730kM8fxf8thOhUxJp1uH0iYaORP19XdPHED/VcuySLxXkxSJJEv/2XxfBf7eui1erkm4ruICL24a526ntsfFfVTWOfne+qevD5JZ49d0rQ+lqVkimp48eES5PDAm3EnmEXJz65Aa8o8uU1c7nxvT3UdttIDNPj9Ytkx/zXiOSO5gFOf3YTaZFGvrluPltvXYJCEAKRRNEhWgQBog7zHlR0DHHGc5tRKQQ23LyIGLOOh04rprxtiOOL47F3Skjb9ChF4RfnELWhAnPvV+AakIguO/zSfo8s1o8sEjCnCBz3vgJBgMH9sOYakbAsmHu/gs1/EFHqBKbfKqBQCYy0SBhiOaSQP2WZgGcEwrKPXOi/7wWRqldh0iUG/MfA2htkMrnwMUWQcH8iGPUxFGSfNe5xSRKprH0Nl3swoOdZ8evraNi1jfy5i9jx+Uesf/t9khfEMeP4cyYkYQDRkUWUFv4anTacta+9wu6vP6P0mONYNGrc6vYM09L+AwCpCUuob/yUpPj5qNVG0pNXoDeFUrhwKSP9fcRl5aBUqTj19j/T1VAXyK2sqHmV1s61JEUuxjE0iN/n45unH2PSoqWET9ZidTbhjo1nYLAPy769JBfK+pf0lJX4JR9+j5eIhHZEv5/pJ59OT3MjnXXV/PjK8yy5+AoUSiUJOfn89NoLpJVNpXjpSkKjY4iOLSA6duyGPtTTRfXrjUQkpRO2IBOr18frHf0cExVKpkHHwFAdPp+D/oEqwmLjaCnfjUanJz4rD8kukpo2jx2ff0RP435iM3Oo27KRui0bmXbCyQgK+Tvx/j2301q1j5XXXkvx5Dx6dltp2LkNU7ye5FUWoswZRI6a4YI8UNFeXUl/eyuFC5cw78zzA8999vB99DY1Muf0c1GpdCgElVwJkqDux70gSSSkO8ZFRx1A/bbN1G3ZwOzTzkEfYqajaS+i5EMfreTYq28iPnt8jBXISQw+nwOlUkPt5vXYrP0M7h+E0bmzHXsfw+nqw+/3BH4ETHR+lle/hMdrozj/kkBLVKcNY/aU2xElHyZjPJV1b8rv+WBNgIj9HAdsPH4OndYy4eNH8Z+Ff5pDnNvt5rXXXuOiiy76Z23yKP6FCNGpWXvTQkRJQq1UyBXNrS2Utw/x3o42FufFcNcnFby8qZnbV+UHqlJunx+tKrhCctuqfPLjzUSatFzw4lZuPiaPnNgQ/rx6El9XdJEdG0JqpBGvX+LC0e0cjK2NVt7a2sKvF2SQNUqoOgadvLq5mRNLEsiJDUGvURJu1OD0+jHr1Bw7KR63r40HTi5mWtp/3etlyOnB65fot3kQRQmdOvi1HTMpjkkJoWxttFLRMRTQbh2MSJOWCKMGg1YZaDuuKooPkNJv7/Tjr7Pw0qkLKbtw/K/rmrdFKl+RKP2NQOpyBboCH6c8vh5pl8RnV80l1KBG9EtsvlvEPQSz/6RAEyJQ955E+XMSxgSJqb9VEFUiEx5bh4TfBUONMFAv0bkZQGLSxQI9u0R2/FUidhrMvX98pcvZL9G9TSLzRAGV/siJmF0uJGHrALURQtPBNQg1b4lsvEMmhBMRu84tEhtvF0lZJjDlt78sSA6NjqF0uWyyGJOeiUqjxaIonrCadjDiouVKlKD4Tv57ECVWKuT2lc/noqNnC33WfcRFT6W08NeBZZZffk3Q9r544q/Ub9vEjJNOY/Zp5yBKo0HeKie/uvMu9n23hsqfvqd2y0ZOP+EefF4Hng4d3z77BEqVihV3nYeEm7TkldQ3fgJIrLzlWqIjZYKWmFdAZ101IRGR9A/UUN/0Kf19sklq9fof8bicHHvNTfg8HkTRPxaeXVdDX2sz1o42/D4fD++u5LXeEb6LjebjsizSU1ai0ZiJDMvHNC2Owe4utn/2IXNOP5fpq09FFP38+OrfQZIIS0hCoVIhCAKtVeXEZ+Wh0mhwDA+BJOF3ing7Dax//VEEhYIlt5+EsUuDqOzB5/GgGvWZlESR9+65HZ/HjUanI3f2fDrrauhtacJllytH7UPf0VHtZsbkWzAZ4lCptCy56Nf0Njcx+5QzmXvGeajU4787a19/gYHODkzhEbRU7KWrvpZZF5xIccGJExrFHkBsVBn9A9VYQjNZde3NtFXto3jpysDzkWH5dPXuCNhITASXe5C2zvUADA03Ehk+5h4gCEo0o8SsMOc8unt3khD3r7FeOIp/f/xDRMxqtbJnzx7UajUzZ85EqVTi9Xp54403ePbZZ/H5fEeJ2P9ROD1+drcOMiU1LGDNoFQIKEdvSFe8vpO1tb0szIni+qWyaLZzSBbDdw3J4by/e28v7+5o5fEzyji2aKzNlxZp5IZlOax4ZC3VXSOkRZq447h8ipMs2D0+znxuC1qVgkvnpbOxvo9pqeFBGYoPflPD1kYrCoXAg6fIrYFHvqvlne1t7Gkd5I1LZhCiU/PjjQsQJYlhp48L56RyzRJZq1LbPcLa2l5Om5pEiG7iNsLB+Hh3Ow99W8sNy3I4vjie9y6fSZxFH3RMgw4PoXo1ogQNvXbsHj+tVgdfV3TzU00Pfz21mMxomTTGmHVs/v1iFIIwYSB2eI7AUKNERrEOo3b88727JXwO6NsLqcuh3+amdUDWivTZ3YQa1Lit0C5r1Nn1hEjxZQrCcgRUBgm3FX68TmT6bQLJixUkzJOY9UcFpgQwp0LhxXK70pQg0LVVFub7R+cROjZIbHtAJGu1QP55CrbdJ9K9HQbroeQq+Vhr3hGpe1ei7FoF8bODj7/pK5GBWph0GSTOUxAzVa60LX1OJnkfn+DHMwzN34lUvQZ5ZwcTssE6CdEL7eskCi+UgjzRBEHBnGl34/XagyJoDqC5fDc+j4fYzOygxweHG9ld8QyxUZPJzTwFm6OLbbsfwhySwoJzL6dwwVIik8fa1iqVjvkz7kOS/LR3bcQ6WINf9I3b38HQGmXdTu2WjaQUlTIp9zzMpmSq6t+kV7OPhef9kfC4BFKLy9DrwpmUdz6DYZ3sjPoWS1wM+1s+QRAEoiNKiAjLw+0ZItScGtj+vLMuYMqq1RhCLewsf4r+gUoiivJZkX4dm95/E5u1n+bdO/ni8Qdx2+2c+5fH6GlqoLVyHzNPOZPY9CwGuzsJe+QOLlZpCLnlfvm1KrUBv7KaTeuRRoPVNXqZNDTs2IZKrSE0JpaMydPY/P6biH4/7/7hVtInT2P1TXdwyu33YO1oIyE3nz07X8McG0FsWj4ZqcfQVrOXmrU1+GueZemlV7HmpWdp2LmNmPQMhrq7iExOpX7bZr544kG8LhcLz7+U6Ix09rY9AiMiNntHgPwcTIwOhWknnELNpnXkz1tMw2hGqCUkaxwJq964lua9u5l92tns/vozfB4/88+6F4VSiTmHcQHwk/LOZ1Le+Yfdt14XTl7WGXg8I0SEjWmnR2xtrN92FwqFmoWzHsCgjxxn2XEUR3EwjpiIbd++ncsvvxybzYYgCBQWFnLvvfdy5ZVXolQqueqqq1i9evW/8liP4ghw20fl7Gwe5KmzykiNHBN53vzBXj7e3cHFc9K4bdXYL7eeERe/fm0ntd0j+CWYlx1FVkwIbp+fWZkRLMiJ4uTJckugpnsEUYL9vbZx+3V5/Vw+P4Pvqro5Z+bYTS4+VI9ZpyLCpOHxH2R7hoW50QEtFcCFs1Px+UX2tQ/xx88quX1VPisKY9neNIBOreSSV7Zz30mTiDBp2dM6yK/+tpEYs44fb1yAWqngurd3U9ExzIDDw43LcxlyenlxQyPzsqPG6dEAvijvpLnfwZflnRxfHD+uLfr6lmZu/XAfZ05P5s+rJ/Her2fS3O9geUEst320jz6bhzXVvQEiBuODuEVR4jdv7aJzyMWzl02m7DrNhCJogLLrFLSvk0heIj+fHmXilQunIUkErDb0UQJTfydQ+YpEyzeg1kmUXadg9edKvr/Sz0A1aC0CG271070T5j8oEJomby/3DPB75H1lrlYQkS+hi5RvwD27JTxD0LVNIv88uR3ZvVPCkgkNn4k0fyvhc8pmquXPiWy5F2b/QUF0mYAkSWx/QHbWt2QJpB0j4HNJtPwgElMmoLUIzP2LgsFaiZbvJXr3gFInMf33Y+9D9qkCdR9IuAeg/kOJwouC3yON2nTIlmNfa7McGdTaTPWbIh0bZE1bH5U4nD109mwlN/MUhkeacbr6cHsGZfIzGvrc39aC0zZCYm4BSqUaUKPVWhBFLz19u2RPp0MIpZdddjUj/b20lO9h+2cfcmLe7YSaU3F2+fFKPnRzQpi++tSgddzKLjLPDCcteTE2ewc+nwu1xkT/gKxx8/mcAfsNkK0jADJSViJPVaaTWjqPyKQUWvbtIXvmHLZ/9iE+nxeXzcZ3zz+FY2iQaSeewpqXn0VvDkWQIFQhcIZRyaeP3E/KpGKKFq+gfvsWPnvkPlRaLef/9W9EJMrf8baqcnweNx6ng9DoGM5/8Cn2/vA12z5+D6ejj+/XX0dW2okk58+n11pB5/BPJJygZNHsS9Fpw5BaY3F01DIc1QMgt/0GrBQvW8mUVavZ/fXnfP/C31Dr5MzPpPxJ9Pt2ACJ6XRQKWzhbP36PkmUr0ejHtFFO2wgKhRKtIVgvVbhwKYULl47aXNjRGowk5hWw84uPWfv6i8w/92JKl69izUvP4hgaRGswsOPzj+Rzb8acQ7YujxRpSeMncxUKNYKgQqnQBmwnqureptdaTknB5ZgP4Td2FP//4oiJ2KOPPsr8+fO57LLL+PDDD3nxxRe58sorue6661ix4hfm2o/inwJJkviptpfsmBDiLfoJl3l3extun8iWxv4gIhaqVwf9PYBdLYPsaB5AAB45rZjjimWtwgvrm7j/q2qyok2cOSp6/9vZZWxvGmB5QSw9wy5ueHcPkxJCuX5pNiseWUvHoIsPrphF2kH7TY00svP2pUiSxM0f7GPI6eHG9/aQGRXC384uQxAEVhTGMezycdN7e6nvsXHbsXksyo1hblYUWbfKppzHFMZyUlkidT0j+EQJm9vH6I955mdH0TXkYnpaxOixN/Lo93V8sruDH367IHAs25usJIUb+P3KPDKiTJw2dbzmBKB9wBn0NzfWTG6sfIN84JRiNu/v57RpY+v6RYmHvq3BoFFx5UJZHD3k9PJ5eSeSBHvbh1iYIztq+5wSPhfowgSqXhMZaoSy6wSyfhVM5OZmBSdZuqwSyUsFvA6oe18ibpZMWL6p6OLh9DouPzOTmMlxbP2z7EI/1CQRUSAv8+N1ItYqmP+QgshCgY6NEpWvSBRdJpJzBig0kLZc3v+kSxQUXighKAW+Pt/PcDOkHiOL7pu+kvDZwVoje5O5ByRyzxSw1kjETpX3te95ibr3JWKnS8y9T0l4jkB4joAhRkKlF8n82W81pUYg70yB/Z9JKLWMm349HFb8+lpa9u0hc+oMvj5bwtkH7eslsk5fBJJIRLh8k42LnorXa0fhN/DTay+SO2seYXEJvPb76/C53Zz+hwcCFZHI8AIS4+Zg0EehVhtpavue/oEqCrLPCpp+UyiUzDr5LDQ6PVNWnQSAXhlDy2eDiP5+Kgs+IyoplaiIwsA6PX17cLr6aa7fSFnRrwkJj8TjtaHVhALSOFG2bcCKKSycUHMqouSnZv+7DA7vJzqimKnHy5N/J991J/sbvkUR6mTKqtU07tpOaHQMg12dDPf2cNafH8ZgDqVqw0/UblpHy95dFC1egWNoEKVaQ1RyGuEJY8Rgxq/OoGLtGkb6etn15adMX30q3fvrEBQKEhbEYPfsp6d/D8kJ87GY04mOLJFDrzWh7PziY/pa5Kwr54g8fbjq2ptpq64geVoWG7ffg8GShkKpJLmwiGWX/YbOumoMMfK5HhVRyFdPPsRAZyeiz0fG1Bmsf/NlUksms+6Nl1FrtVzw8NOsf+tV6rZs4Pgbbg18bvbBQWwD/UiiiHN4mPbaavw+Hx01VZQuX8X0E0+hYdd2ipeuxO/zMdzXgyiKR3Se/aMwGmJYOOsvKBSqwGfa3rUJj3eY/oHKo0TsKMbhiIlYbW0td955J5mZmVxzzTW89NJL3HjjjSxZsuRfeXz/8fD4xIAw/OeQJIm7PqmgfdDJX08t4at9nfzu/XJSIwz8eOPE5pdPnz2Z8vYhTiiRvYge/q4OSZK4c1U+l8xNJyk8+GK/ODea3y7LJincEDBFHXR4qOocQqNUMDll7OYTF6onwminvsdGRccQ6+r62FDfx9WLMhlwePH4RYZd4z24VKPVor+eWsxX+7q4/LUdNPY5cHlF9Bq5hXVcUTyNfXYK4s1saxrgwpe2sawghj+eWEhN13BgIvK7SvmXdlGCOfC+3bQil5tWjLUG5udE8cmeDlaNGsh2DDpZW9fLze+Xk2DRsyg3mm1NVn41eeIL4nVLsylLDmNKanA17eWNTfx9fSN3H1+A+aAW6M6WAZ5csx+QLTBSI42EGTU8cloJHYMu5o2SKtEv8c3FIs5emP+QwL6/y0wyfiaBalhN1wgqpUBGlIn9n4g4umW91ZZ7RnVd9ynJOmnsmD7Z00FV7zAf17Vxwuw45j2oYGi/RNLCMTIz0irHFjm6JQb10F8p73ekDbb/RaJrC4QkyA7+zj6J5CUKhpvk6lTXVsg7R8AQLZAwR6J3r4QuXGLtTXKU0fyHFBReNHb+mkeLoY5uaP5GJGWZ/JwxHvr2yftb+pyEQjV2fOnHC+x9TmLf3yVC0wTixw+VTgijJYy8OQsAmHy9RNd2ifTjBFQqPXEx0wNj/4KgICVxEd89/xR7vv2CjtoqTr3jXkyWcOxDg+hDxiqbKqWWorwLA/+u3f8BPr+TcEs2aUlj7aU+awVWdrDsqivQ68IRRT87Pv8IvTkUpUmkyfoBTVaBGWW/w2JOR6FQkZV+Ij6bgp8e+YA9ql9z8WPPYQi1sHCWPNHYvHcPHqeTnJlz+Om1F9j+6QfMPu0cZpx0Gnqd/COju3cX3b076W/qROuPQojrxaaqpKpugHnH30PunPk07trBogsuxxIbiy5ChdEURt7s+XTtryNlUjG2ASs/vvwsfq+HwoVLaW77DqVSS1L8PHRGE9qlx/OQOZmacBPTgeHeHiRRJFQsJCG9iPrvqnn0wV9x4m9vZ0rRbwDwul2seVmeLE2fMp2Zq2WLjoTcfBJy8ymvfonB4f0IoQJXvfg2Ko2Wd/5wC22V+5h16lnMX3k/W3beR9xKNb5PI2mrrqB26wZ6mxoZ7OrE53YjiSKiz0fjru04hgbpqK0iISePga4OXrvlGoyhFpb/+jpM4REULVpGcsEksqbLJ1PZyhMoWyn7t00+9kReuPZSGndu54JHniYsdmzAqL+9lTUvPUv2jDkULV5O4+4dbPnwHaavPpW0kon9ByfCwZVNgJKCyxgYqiMp7pdjk47ifwfd3d088MADrFu3DqfTSUpKCn/+85+ZNOlfb+59xERsaGiIsDD5xqTT6dDpdGRnZ//CWkdxOPxU28vFL29jWf7/Y++tw+M2tG7vnwbssT1mZsbYThx2OHG4waZNkzQpQ0opMzMzM6dpmJk5DtpOzMyMwyB9f8gZ16ftec+5t+d+931v1/Pkia2RZjRjjbS099prBfHxtYN/93inwcr3J+Q7zNMV7QR5uqBUCA5fqt+i22Rl/sfHkIANd45Go1aSX9/NB/tKAJg2IIjU0N8LzVVKBXdP6h+t8+2xSjbnNBDl68prC/rcjU9XtrPkq1No1AoOPjSBG0dHkRLsgYuTiq33jKFVZ+7XcjRa7KiVgoOIAUxJCeTZ2SkYLHZadWbWnK3lZFkbb16dzqPTk+g2WfnxRBU6s43sinbeWTio374pFKBSCAyP/nPvs4NFLYxP8OeeSXGUt+iY/v4R1AoBpSDg4+bE+nO16C12TpW3O1p/5S06PjlYxtVDwhgR48vklD5N0uacen45VU2XyUp1u4E9BU2MT/B3aMrSQj25Ij0YrZOqH9H9R7d/RLDqZFIk2gTSl0N3JQ7H/PIWHTM/OIJSIbDvjgmce1cWO8fMFkACc8fv3+uDUxPR6p0Z3R2GVSfhEQmiVUCS+jxgJ32ooKcavOJh+2IRUYSBdwpEz4SjT8jrWLolDr0rIdmgq9JO4c/y+lO+6BP0e0QJOHnAlqtlEqbxgX+8uY+ZrcCiE8n7QuL8hxKRU+Vg8Jr9Elad3CK1m0HxmzOPQi17mBnb4DfT+/8UlUYzn1Y3c02wD4M93AjOFByfY1tHEafOv4HG2YeJo153tIcSRo6hJj8PrZcPXc2N3PDOJ9htNofQ/bcw9nRTmXueuIj5dBvKCQkcQVtdDTazmcCYOPJLVqHT16FSaUiOW0jNpTxObVgNwA3PfkRe5WfY7WZOnnsNf990hg28D0m04eURgyAo5Kpfb+VPoVDR09bK+teeA0nCw/9t9B1yXEJHYwNb33+D0KQUJk14l5z8L9DrWzj05U/YDCLznnoMH68kQnun8XZ9+j5VuefJmDEb51gdR09/QmRYFgMSrmXWioepLy3iq7tvQlAq8QkNxyPMnfySrwDw9U5CrfSkKy4VfbeNbJv8t7/6mVdoKClE5eRMVNhg9p5ejc1spqYgj8j0QQA0lpXg4uGJ1seXGXfcj0arpbG0mE1vv0zM4GGMunYhnU2NmMo0MEBOWvDwk6vEHn4BiHYzJnMHqAQm3HQjW16TDUxjBg8nffJ0PPwDKDtzig1vvEDmgkVYTEYSRsl2MqaeHixGI6JdJCg2np+euI+upkbmPPSkI+bpMvZ88RHVl3LRuGkRFArUmv5O/4VHD1KVe57OpgbSs6aRs2cHdYWXyNmz498iYv8IP59k/Hz+99qg/y9BEiXMFV2IPRYU7k44R3v+qbTjr0BXVxeLFy9mxIgRfPnll3h7e1NVVYWn5++vmf8J/Fti/dLSUlpaWhy/V1RUYDAY+q3zj4avf+PPUdasw2qXKGzs7rd8a249h4paeHh6Is/PGUBdp5FxCf44qRScfWoyH+4v4ZlNF3lmVoqD5LT0mClr0ff+bMLTRU18oJarhoQhStLv7B1yazvZntfITWOiCHDvOxmJokS30UqQp4YFg/tfZf20zmidlLhpVKiUAs/O7hubD/dxpaixh5e25nNPVjwtPSbmfnSMIE8NO+8b129AINjTheU/neXbYxWYrSI9ZhsHCpuZlxHKpLcPYbbaeWxGkqOdZ7La2Xi+jsxYX8pb9NhESXbMf+8w92bF06a3MCM1CF+tM9VtBgf5nJ4ahK+bE6IoolCq2H3/WMJ8XDlZ3s6+/Caauk106C14uznxxeFy1p6tpaJVz7o7+k83fX20gpyaTq5ICyYr0Z8DxS0MfGE36+8YRXygOxq1ko+XDKasReeY9qxpN/D6Ven9KmcKtcCULxSYOmUBf8AgOYLo0IMiggLin1HgqlaiVilw81TgfYWZja2VRM8MZvxEL7RhEro6CW1o3wnJvcGVERuTMBmgIkjC2A7Fv0rEzBIY8qC8njZUQBsKFz62I9pA6QRhEwQOPyTSWQ7DHhWInCJQf1xE3wAaPwGQEO1yVSs4U3BEJKlcwT0ULDrI+kyBq79AZ6lEzify5GPkNAGbQcIzBqJmyNscelCu7MUvkB9Xu/U/oepq5KodgM3Y/ztStVvWqQ28U+HQvAG8V9nEqsZ2ig0mNmTINxLnuw3sbeviSu1lQ9n+raeI1HSiM4ZydusGdO1tLHn5bZSqPx7u2PPFR5RkH2fglBlMvuUujD3d/PTYfdisFpa++h5RYVnUNR4nJHAEW99/g5Ls4wTHJ+ETEop3YDijvZ/j4LY3wbsLq1XWVB4/+zJmSxeznr6LoMDBDpKQu28XpWdO4hsWjt1qxdM/kCm33k3y2Im01dVw6IevKDt7Sm6xZTyM1WyiceeT2CwW9EHJFFiSkM4eYfNTiwhNGoBCqSQwOo72Tnmiz2SSSd26V5+l5lIuot2OxlnD0lff5fSWtTRdsJM4YwAaZx+2f/gOtpPHuH7eMkaHhSCJIh5+/uz67H2q8y4wcsEiLGZ5iOe3BLbk1HGM3V0olEoHuakvLkDX3kbRiaOMWXQ9Zz4/gWi3I+qcGTJzHm211aRNmsaA8fLwwLBBD1KTl8f2t94jKC6BmMHDyFzQ51u569P3aCovJTguEYVSyee3LWPSjbeTMX02i154E2dXVzRaLWpnDQgCarUTZWdPoVSqiOolUYXHD2ExGpl00x14BQbz1d03Ezt4OLMfeByAtKzp9LS1EjtUDhTPvGoxGjctGTNm/+Fx8jf+ehgvttK5pQx7l8WxTOnphNfsWFxS/3wS9n8HX375JUFBQbz66quOZeHhfyxd+U/g3yJiN9xwg2PKBuD222UfHkEQHNqOgoKCv3YP/4fhdGU7L2zJZ/HwCK7LjCTAw5n0UK9+67ywJZ/mHjNRfm4OzdFltOrMfH20EoB5GaEOMXqsv5ZvbhiKJOEQkauVCscU4m+RV9vFrT+coanbjNlm70eojpS28u3xSgQBrh0Z2W+7aD835maE8vOpap7eeOl3UUGPrMulXW8h0ENDaqgneoudhi4TVrvYT8zup3VCrRQI9NBwz6Q4Tld2cOWQMExWO3qzDatdxGixE9DrZP/ZoTLe21tCaqgH7y0axNGSVrbmNlDY2MOrOwqpbjeQXdHOB4szCPN24cbRUXQbbSQHuXPVZydwc1bz3Y3DiA1wx2ixk1fbybHSVspa9ejNNp6alcLVQ8Mpb9WzrPc9t/SYmffxMdw1KkbF+lLVqicrOYBZ6SF8dbQSo9XO4i9PkhLiyfc3DqO8Vc+0dw+jUgqYrKLj7zOtt6Vqttm5WNfNoHAvXAP7CIW+CTqK5J87tzjz8+AJRE9T4K5RczThEltbK6nZ18Gmu0Zz+BGRptMSwx4ViJquwKqXOPiAiGSTK0lBIwUqtsqvbbP0fU8vw9IlE6zwSeDiK7cmRQuo3QQEpcDED/qqX4EZEvk/iGS/KhGRBSOe6iViGoFp3ytAgvrjULFVxKqXaD4Ppg4JbZhAwU/yc4T2Tlh6RMqB4i7+0JIjkzSFsu8zcA0ErwQwtYHKVeK3eU6FKyW6q6Byp8TAO/qWXxXkTaHexNLgvsrofYXVFOlN2CIDuWfESzg5uf8uoy9iQDr5h/cTNUiuQNcV5lN+Lpshs+b3q574hoVTkg2CQklt/kUCYmLRaLWYDQacXd0IDJxAROgEAJoryhBtNpJGjXW0vwpOHSR39Slcg53Iel1u32mcfbBYdXgHhuPm1Vc5PrF2Jbr2NkYtvJbMBYvp7qnm1LlX8PMZgKFLwic0jIFT5QlCk17H6uceQ1AqWfTCG0zOqaLYYOLhM9mg12GzmLnv540IgsChk7I3mmBxxWa10tlYj2i3M+rqJaROnIrKyZmT61YjiSKqYbGypsnZGZVoJ3T7KkpMJi5Z78PF3YPqizkAuPv6MXzJVNqEU7iEmBzvYdDUKzi/cwv6jna+vOtGwgekM235vRQcPURjWTH7vvmUpDETyD+0jwu7tuHq6U1TeSmtNVVMvf0e+fORAmktOoDdZsXZ1a0fCWuqKMPQ1YF/ZDRDZ89n/7efA9DZ1EhTeSndLU0kjRqHSadj1r0Po9a4YNbr+eGRe0AQuOWDL/EMCGLOg0/SWFZC2sQp5B3Yjd1qpamyzPE6Hn7+TL/z/r7vQXQs0++8j7/xfwbGi620/fR7DmHvstD2UwG+S5P/I2Rs//79jBkzhhUrVnD69GkCAwNZsmQJCxcu/K83/gvwLxOxffv2/Sf34/8ZbM2pJ6+uC+F0NUtGRPQzQL2MuyfFsa+gmVnpwXQaLIgS+Lj1tqn8tMxKD6axy0TiP1S5JiX1H/HvMlp5eE0Okb6uPHlF36Tkg2su0NRtxttVzdSU/hmQqSEeZER4EeSh+Z2wH3AI8XtMNowWO2abnW15DUxJCeT6zCgOFTczKTmA749XMijci6dmJWMTJYqbehxVuaFRPpx5cgouTkqcVAqmp8pWGB4aNTvuHcvTGy/y/r4SjpW28vL8NNJCPXFWKRgS4c2lum6+PFLOomHhDIn0xl2j4pMDZQ4tm0LRV6nrNFioajNgsYucqWwnwseVLTn1vLW7GBe1khBPDeMS/GnpMXPvqvO4a9QMi/JGFCXqO43UdRpRCOCkVNBptHK6sp0rB4exZnkm23Ib+PRQGcdKW3lxaz4LBoehVipwViu4a0IclW163t9Xwr6CJt64aiCPr89j/bk6bhsXwxMzk7HaRT7YV0KYtwuZT4bRUwf530mAitgRCgiCqQMCOZzfyoxI+Ri5HFNk1cskS6kB7ziZzI19TYFbsICyt7jZm11Nd6VM1rzjIfM5BWETBQIHg6AQGPmswPn3JZovSISO7V+l8ogU8E4UqNkv4RENZ94UMbZJjHxKgVor0F4scvw5CeyydUXUdIGwCQKe0RAwWK6cufTOG4x5TYHNJLF5rmxVofEGu1nC2VsgJFNA6Swg2WQiVr4F0m+XqDsiW2+k3a6g5oDsa3YZOpudVouNXwfG4KnuO4XNC/BidUM7vmvcyK51Y8yrCviHQzhm8DDu/PJnx++7P/+A9vpaBIWCMYuucywffc0y4oaP5qfH7yVn93Zu/uALlr75DiqFBmfXvmEUvaGJqKs8iLWFMGjsLMfyyLRBRKQOxD8qGrO1C2dnDzKHPO4Ilt7d2oWfk4rBHm6MW3ID5efPkDJ2EgAdXaUYTa00NJ0mb1MlAAFRco5hT1srLdXyMl17O2O8tTRaLMTNu4bS1y5SlXeBlqoKAqJiyBhwO6f3/8jBrzfSOLKDq59+hbKyPZidqrGruxEEP0ZdfS3H1/zMiXUrGTB+ElNuvZvBs2az6cOn6Kk14x7gQ3NZJUgSvqHhpGdNp7B0DTUnTOScOUBU8HTcffzwDgklbdJUaooK6ayrpvT0SWbe8xCJo8bSWFaMX1gEGTMCsg5EAAEAAElEQVTm0Fwhk570rOlIop3AGPlGs+LCWda/9hz+EVFMvuVOojOGUXMpl9rCSwy5Yh41F3PoaWtDEiU8/AKYdsd91F7KI2rQED67fSkWo1GOI/vlB3TtbVzz/Ou0VJXj6uWNxk2Li7uH4+8SmTYIgIGTZ9DZ2EDFudMUnzxKT1sbPW0tjPkHz7LmynIKjh4kY/osRzv1b/z1kESJzi1l/3Sdzi3laFJ8//I2ZU1NDb/88gs33ngjy5cvJy8vj5deegm1Wv1/xA3iXyZioaF/ntH3N/513D4+FkEQmD1QJh+/ZFfz0f5SHp/ZFw90XWYU12VG0aYzM/7Ng9jsInseGE9Ir9fV0dJWOg1WNl6oc8T4NPeYUAiCwwXfZhf5/nglu/ObALh7UryDWM1IDcZgqeXtqwcSF6BlT34TExL92XC+jqc2XuTerPh+lbjmHhM5NV1MTPTnlrExrMqu4WhpK18eKae2w8DqM7UcKmrhi+uGcu/keLqMVn7o1ba16yws2niS/IZuPl7S5z/m6dp3olv29SkKGnpYddsI4gLcGZ/oz8mKds5UdXD9N9mcfCKLopdmAHDXz+do6jZT3KTj06VD2JbbgL+7M86/GXj4cF8JdZ1Gnp09gNXLM1l5qoqXtxey81ITL89PJdbfjbHx/jw3RyZsOTWd1HYYETAy8tX9zBsUwitXpvH+okH4aZ1xc1ax8Xydw9S2qdtEcVMP92bF89PJSr45VomPmxNHHp2ISiHg5erEpgt1rDtXR3FjD6/MT8OptyJY3yn33g4WtTjsPHKeDSbYrqLlvITKTa5WAaRIvtyxewzKg2AeK5FyvcCRRyUqd0L8ArmqlPWpXMUS7RK1hyScPQUQJLQhcoWqq0K2hmjJlVuSIb06KrtForMEdLVQ3iSRuFDi6BMi7hECA+8UMLdD4kIF8VfKUUVbFsiVtrZ8cPKQ2HenhKAAz3gIn6DALajvxDj+bXmf6o5K6OpE4q8SULsoCB0j0lEiYWiRyPscUEjMXqtA4y0QM0ugYodE2HiBqt0Sp1+XcPaGOeuVjn0GyOsx8F5VE9taupgf4MWnA6Icj90fFcTtLoFse0KkDeiuAL9/orOtPyER4XMLCsW3xA4Z8bvH3X190Xr7oFAqqWzcRV3rIZLjFxHt2ifa7+yuwGRpQ6Ho6ndx0Pr4cvXTL3P+4mcczX6WhJgFxEVdgUKh4niHjuvyKnASBLY49aB1dWPAhMl8e//tBCck0dFQT9jgGIZctQiy9qBra8PTX77J8o+IYtZ9j6FQKvAJCeUV4JWEMCwmIz+HhGI1m3Hz8mb35x/Q1dJMQFQMkk1CqVbjGRCIsaqcrq5KKqsOMCgthoAoWbOm6NWtKZRKOppq8B2uJniKH94R/gRER6P2FolJHIckisRFzeLIh1vpbmzi3PbNjF96E4Ig0DV3KU8XVDPP2sWdzjaOr1lJetY0Bk2bhbG7i6OrfiDr5jsIS5K/d5kLFjvc+s16PUgSXc1NpE2ahkKp5Ocn7sfQ1YmTxoX0KTOwWa2EJQ9AtNtpKCkkLCUVJAm/yBjaairx8PPHZrUgIdFYWsTBH75CUCi44e1PHFYYF3Zto+DYIbJuWk5AVAw9rS10NNZz8cAeKi6cBSB8QDqxQ/oyTw98/wW1+Rcx6XRMW77izw+o38Bs0Pcj7H/jv4a5oqtfO/KPYO8yY67oQhPr9Ze+tiRJpKamOjKzU1JSKCkpYdWqVf93EbFHHnmEZ555Bq1WFjcXFhYSGxuL+g/cjv/GnyPEy8VBAEC2H6jrNPZWwPqqYyarnYNFLRgtNiTk6crCxm5OV7QzIdGf7PJ2RzZjXaeRKe8cQqkQ2P/gBPzdnXljVxFfHC4n0scVq13knl/O8/X1Q2XfrSkJ3N9r2rr4i5OcKG9jRa+uy2ITOV3Z3m+fb//xLOerO3lkeiJ3TohjTLwfTd0mBoV74ad1Zv25WpJ+k1Xp6aLmpXmp7C9sJvs3z3X5OvXZoTJqOww8dUUKKoXA6cp2TFaRokYdcQHu3DYuFqtd5P29JY5K1+Prc9lX0MzL89NIDHLnysHyjcHGC3XUdRrZdamRGanBmKx23t5TDEBWciBTUgKpatOz+kwtzmoFflpn9j04wbFPLT1m/N2d+WzpEPYVNLHmbC1VbQbGvXEQi83O7vvHo1EreGZWikOc/+H+Ui7UdBLgoeHG0dHsutRIcrAHvm5ODuuFGanB1E4zEh+gRaVUMDzah1Wna9h5sRGbXWRIpDdj4vwI93Hh6yPlfHuskjdvSXdUByVJwq62o9IIqN1kEmU3Ckg2CUMzrDpZzY/ZcurByBhfStZJ5H4q4RkL87YK7FsusXWhyLi3YPADAl6xcvvxMg4/LNKaC6FjIXKqgvZC6CqXK2hN5ySs3TDuLQWBQwQ0PpCxQtaC5f8kEjgYlM5ytuWE9wQKfpQQFPKUpaCQ1+soFjn7thw47hYkEDYeRj6jYP89dvI+Bxc/0IbD5TzmuPkKh7VF5U6Z9P1DV5ECnZFpZ4pR9H7Gca79hdYg71PAYDlz859FK1l0EseeEkHMYNrrQwiK//26rh6e3PbxtwCcu/QJADXFZwnyzsRFK++4bI3Rg9Yt9Hdt0Kra/fTo63p/E+lpb+WXpx5G5eGB7/QbCGmsZO8GWSg/Yv412G02WqurMOl6aC/1xNcniYTheta9+iyrnn2UWz/6GgAPf3+cNP0Hdpw0Ltz47mcAmHQ68vbvBiBj+mxC4pOwWOSpw6S4qzl3/EcOv78JwzQNFw/uRbTbGLrgGlw9vajMPc+WN95ErXFmwasP46EN5+DxRzFYWrAV6jn8yToyps9m+KxruHR4P4mZsmBe39nBhbZORKAlIJSiHT9SeeEs3S1NzLjrAc5s3cCFXVupLypg2evvk7NnB/u+/pTMqxeTuWAx3iHy99liNNBaU0Xu3p0o1U5off3pbmsBSWLklfIk5vE1P3Ni7S9EpA6kp72NzsZ6Fj7zCge++xJjdxdZN99B9OBhnFj7CxqtFuff+JGd27GZjoY6ik4cISAqhjGLr8Pdz5+0rGl4BYfQ09pKWHLf+Vnf2YGrhxfewaEkjvzXxnkP//wtpzevY8J1tzDkinl/ul610UyR3sRkX49/2bLlfzLEnn9Owv7d9f4d+Pv7Exsb229ZTEwMu3bt+stf64/wLxOxLVu28OijjzqI2JIlS9i0adP/UUHbf1d8tL+Eo6WtvL4gnUjf/ndJz84eQHJwDXWdRr46IodiAzy/JZ9fsquZkhLIYzOSiPJzY8KbB6hsM/DYjCTeuybD8RyiKGETZW+nyxq+y6HVMQFuHChsob7LRJvOQpCnBkmS2HC+jig/NyJ8XDlR3ka4tws3j46m22hjW14DH+4r4Z4sWQQd4ePKhZpOfN2cmfvxMTw0Ks48PRlnlZLGLhMvb1Py7bFKlmZGOoT/i4dH8Mymi+wvhFfmpzI82pe4AC2dBguv7SgEYFy8P1MHBPHzLSPJqe3khxOVHC1t5f4p8by1uxhJgqW9mq0DhS0095ipaTewone/TpS1sSe/CXdnFdcMC2fYK3uJ8HHl7omx1HeaGBUrl5bmDgrFYLHz+Po8rv7sBAd6vcU69Bay3j6IySay675xTEkJZGZaMEGeGuZ+dAybKLI9r4EXt+UzNSWQj5cMZslXp6jtMDAu3o/rR0WSFOSBwWLn5u/PcPOYaJ7uNcv9+EAppc06rh0hjwEOi/IhJdiDlBAPVEoFPm5O/HTLCPbkN/HWriJ6zDZOV3Y4iNhN353maGkrX70+jPgeXyw6CBktMP4dBa6BsGxjDZfqu9maW0+i3YfOEkAAjwgBlbOApUeegMx+GSw9EpM/FdDVSxT8JBGRJWDvlfcEZwqEjhEQ7RID7xRwC4GcT2Snf3Xv9cvUIRE4RMDQAm3bJSydMGu1AoVKFtkXrZKJU/gkAa9YWZxv6QafZHlC9LfDYsZW+f+UGyDmCvkYNXdJGBpli4vTr4v0asvxT+9/cXJVKnBRKtAqFewamkCQsxNtFhuLc8vwU6v4IS2GhhMSzefk9W0mCZVGfg6LVcfpnHdRq1wZmn4vahclQcPkFq7nn6fYOCo26ck3seNkHWf2H8NQpHHoiBQKJVHhU7CLVsoqt+HhHom/bypGUxuXimWxXGri9YSHjKOu8BI9bS0IHW2sFFsdJMw3PJKhs+fjGx6Bk7eSsrr1hAZmArI/FoCit6LaVF7KyicfROXkzG2ffkdN8z7Mli5S4pfQJQpcm1OOj1rFQ7evwNDSRNTAwXx221LMBj0KhYLk0eOxVwVg7RHRtbcRMWAgZWdOEhKfzDf3L8ek60bl5ITW248AvwzObttIh6EJZ18lPU2yT1dTeSkTlt0s+3UV5qP18eXb+2/HR6HijSdeY2p4CM1tmbTXVuMVFIzdasVmteAVGEz6ZNlzsrbgIpIk0lAsCyT9I6MYMms+giDg6R9Azp7tAGh9/Ti3bRPOLq6MulrOI3X3lXveus52upubkEQRq8mE3SZb57h6eNLd3ITZoMds0NPT1opngFxRHLlgEQd/+JKOepkg+4SEkblgMS3VFUy8/rbfEaKDP3xF8cmjJIwY7RD8/1fobGro9/+fYcGFMmpMFt5JCmdJ8J9Pgf+/AoW701+63r+DwYMHU1FR0W9ZZWXl/7FO4L9MxH4r0v+j3/+nQ2+2cfP3p1ErFXx53dDfZRL+EURR4nhZG58fLqfHZGNvQbOjvXUZUX5uJAV78MnBMjZdqGfpyEg0aiVuvf5aUT6uDouFUXF+dBobHJWwyzDb7ER4uzIs2psAD5kINffIV1ovjZoX56Xi5aImyFN+bOfFRh5YnYNGrSDv2ak8cUWyo215OSsxv6FvkvO9awbx0rxUipt6yKnpBGDSW4cI93Hh9SvTsYoSAhJ2UcJqF/lwXwkhXi7cODqaS/VdTEoKJMhTQ5fByuacepaOiKTTaCGzlygNifSmqdvEqYp2sivbeXxGEmPi/Chq7OGpjXm8efVAvrhuCGerOlg8vM/fQB4QAa1GhYtaicUmynqvyQnk1nahN9tw630/QZ4aBEH+m7y+s5AVvZYdkgT0ElilQmBikqwB2XLPGKx2kVMV7UgS1HeaMFjtnKvqwCZK3DI2xmHy2mGQ79B0JjkWx2S1837v5ObUAYHMHRRKuI8r2+8d69j3i3VdVLcZuHOlzBruzYrn5rF9x0ZpizxRm3fGQPMPPrgFS8xcqSQgQ75QPDMrhc059dwyNobTD4l0lUHCQhh4h3zBnvy5Al2dyJFHQLSBsUOi/ghU7pDoLJUY/7YCXS34JPdaKCgFEq6Wfw4cLLvpa3wE7BaJ3Tf3Zly+KGCdJRA6tm+K0iNKlImMAtwjZKG9b4rcCs1YocAnqe/CZtVJDu2as0df9ejAPSI9NbLLfv0xedm4NwX80gQaT0s0nZGNYyM9nfn+UjK6UvBMUIE/FOiN5PYYEYB2qw1JUuIeASGjcJAwAJ2+ga5u+URrtnTLsUO3KMj9XKQlpy/V4I9gNhgoOXWMhnP1SCKo/8Duor7xJEXl61AonJg+4TM0zt6EBI7EatURHDhcbt0pc4ifHUdS8nzC4gZSPjkW55gekuJno3HTkjx6PIWla7ApO2kzXMCom86+bz5FEARGX7+QwyefxEOVhFrjgkarxSbqKa3cLB/f/kMoUURxvkeeYn979ESCnOXvdGBsPI2lxfiEyFPQWTcvJyFzNOED0lE7yVKGnrZWOhvrkURR1o2tXcmWt1/BbrNRU9BKatYkxiy9kwD/gYQPSKe+pIhjq2WiGRgTh2gXUdpMBO7ZwPqz2cy+/zH8IqM5vvpnWmuqKT5xBEFQkDJO9j80dnfJH5wCfn3+MVLGTWLCspvJ3rSWbx+8k0HTZ9NYUkh7fR0adw/CU9IwdHWy75vPCI5LYNF7X7LqvlsBGLvkBsJTBxIQHUtAdCxxwzLZ8+VHuHn7EjEgDXe/PnG3oFBi7O6m9MxJRx7mxjdfoK4wnwnX3cqQK+ZSV5jPvm8/I33SNMIHpFNx/gzhqb8fevotvqhpps5s5YmYYKbevoLkMRP+S+IW7eJEg9lCuPNfTyz+O8I52hOlp9M/bU8qPZ1xjv7rLSWuv/56Fi9ezGeffcaMGTPIzc1l9erVvPDCC3/5a/0R/rLQ7//pqGjVc7JcvlWv7TASF/DHsSu/xWeHy3hjZxEJAVquzPDlqsF/bCA6MNSTGalBDisEgNxa+UT12/zDV+an8cp8WfTSZbTyzdEKxif6k1PTSWmLjhadmVevlH2/Qjzli4XBYmdSL7mY8f4R4gO0rMiKw0/rRFKQB2qVkru/P8PFui5empdKVnIAw6N9GJfgT2mzjrgALYIg4K5RMyTSh5fmpVLfaeSTg2U0dpvwdFWz5/5xCMi2FPsKmvigV/t04ZkpvLStgCs/OcZX1w/j51NV/HyqmvEJ/nx/U58Gw2oX+fFkJT5uau7NisfDRc2PN49g8juHKG3WseVCPZNTArlhVJTjjnXnxUbuXXWeBYPDeHJmMt5uTqxZnkmQh4a9+U3c8fM5Qr1c+PHm4QR6aJiYGMAnSwZz98pzfHqwjChfV64ZFsHeB8djsYkO/6+mbhN3/nyOhEB3Xr0yjZRgD8pbdJyv7qSiRc/3Nw2nqdvEuAT5rvxcdQdnq2SDryGRXgBo1EqenpVCaXMPWcm/z0gsbdYx56OjKAWBEC8NWmcVt42LcZDGLoOVeyfF4+qkIsMcyDGFfNOzbqqdQXcJxM5VkBHhTYKTF4IFwsZKWPUSwSP7yI1rgIC5Q4Fok6tVGk+BqGnQVS4RNUNAV89vhxMBuTJ18gUR1wCBoY9cflD2/0IE0Q4J1wi4BcoJAcWrJZy95HBxgM5i0NWJZNwnUHuw1zPMIlGxTcIvTcArTiBuvlyZ802VKNss4RXXO2AggGeUROw8cA8XCBwqv5czb9kxNstTl8Mfg4a1ChCh6ZxE1DSB0V5aXokPxddJRYCzmvVv2bGbQHtV/zfn4xXPgMRlqJUuuGjkSKvKnRJNZ+TUgpDREieeF1E6wcinFSjUfdsfWfktOXt2oHKWSUtIQp9Fj9nShSja8PaKR+Psg9ZNlhcIgoJBA25D196Gob0bzwAXauoPoQqx4RIs4OrpRczoNKrKj1B0/CjhQRNROznj7ZyG0JmNn9dIjqz8DgkJhVqN0d6AztCAXWPj9k+/R1AI6NrbiY6YQWdLFehdyQx34+X4UHzVKgcJA7j6qZdorali3avPEhKXyOwHHicybRAbXn8Bi8HAlY8/z+kt65BEkZRxk2RhuyRh6O7CLyKKgMg4Rs5ditpZQ2LmWAqPHcIzMFj2QZMklCoVN7z9CSCx/tXnMPZ0U5N/kcYSudrl4edHYEw8Pr0atr1ffozK2RmVszOSXZT1Vz09pE2cStnZbPQd7QiC7OVmMRoYs/h6wgekk7t3J8Unj1J6+gSkjWLXuLlE6jpYMWM2DSWFFBw5AEDapGlcPLCn9+epKBTyOXXdK89Qk3+R9MkzCB+Qhs0qEzFNb5tZ09vtKT51jJbKcvIO7GbZa++TnjXtd9/h36LNYuOZ0noARntpmernSfxw2QKnxWLlhbJ6xnm7c3VQ/yi1VQNjMdpF3FT/9U39/wsQFAJes2P/cGryMrxmx/xH/MTS09P56KOPeOedd/j4448JCwvjiSeeYM6cOX/5a/0R/rd8xMrLy9Hr9f3W+Z/qI5Ya6smL81JxUgr/EgkD8HOTT9wJQe48Pzf1D9fJqenk6s9OEO7jwsdL+kxdB0d6c6G2k/Qwrz/c7uujFXywr4QtufVsuXsMHXoLJpvILd+f4YmZSdyTFY/RaueTg2U0dJu4fVwsBQ3dFDf18MZV6Zx5Ss5Is4sSZyo7MFrt3LvqAjZRYs3yTN7ZU8Qv2TXcmxXP/VMSOFDYTLfJytKRkXywrwRPFzW3jYvBy9WJbXkNfLCvhCevSGFsnB9j4/0I9XLB00XN3oImOg1Wztd0MCTSm/Xn6hge3f+EdKaynZPlcuUpvneycktOPcOivJmUFMDBoma+PV7Ji3MHsCwzCoC8uk7MNpGyFh0qpcBbu4oYEeNDuI8r1e0GlAoBhQCT3j7EwHAvnpyZzB0/n0OlEMgI9yS7op0tOQ28t2hQPxPW7Ip2zlZ1cL66g+fmpKBWKNhb0ERTt5ntFxt4fEZfn62m3cDVn53ALspE6bdtjcuVz1u+P01BQw8/3TLCMXGqdVahdVbhpFKyY8W4foMLAHeuPMux0jYemJLAzKxg5myQ2POCGbFBTVs+xM4FfaPEzutl/7EZPylIuf736QxWg5wZae6BE8+LjHlFwYT3lOgbJHYsFZEk8B8EQx9UoA0VaM+nt60nkb5cwNkTkAQuZ0k1ZsOJZ0RCx4L/QIFL30k4eUD0FQKCAqr2SZRtkKcduytlUX/StQK5n0q4Bklc8YuSjBXyflbsEDn3roTaTWLWWgUNJyROvSxbWwy+t++9hI4VKF0nUb1XIuU6gRGPC3SWQ9h4AWObxPGnRAaE+TK8N78yeoZA60UJ/wyB4jUieV9JMnmdoyAytH8aRdx8AXM3RGQJdFdC4yl5ub4R3H+juAiIjkUQFAycPJO4oSNkkThgteo5fPIp7HYzA1NuxWRux2TuwGhqx0Xjg1HXw3cP3onNYmbZGx+SMeAOunqqCAmUzVeT4xeRu/IczSUXcLX9zPilN5G7cy/5ewtoDOuhvbYWgIXPvUZQXDT5r5ykpKyUxKeqKD55lLPbNpE0ejyFxw5xWnOKOz7/kas89BSU/kqtOIawYFnTZDEayN64Bl1bK+W6HiRJoqetjarc84DsJm/slivgGq07A6fOxDcsHCcXF356XG7BdjU14uEXQPamtZxYu5KAqFg8AwIxGwy4efvgonXn7PZNDJt7FRajoTcwfBUAfuFR5O7dhSjaKTp+mPwjB1Cq1dz30wa6W5o5tvonOhsb2PnJe0y+9U6Kjh4mZfwkksdMoOZSHk4uLqx/9VlGXrWYlLETCYxLoGDdt4yoqsLz5vtQOzkTkpDEoGlXOLImxyy+no6GOgJj+0zHW6oqsFstBMbGc3z1T+z65D0Wv/QWs+9/HENXJzaLmc+WX4dnQBCDZ84l4V/UhPmoldwS5kedycpIr/7XhjWNHaxp7GBfW/fviJhCEP4mYf8Al1Q/fJcm/4GPmDNes2P+Yz5iABMnTmTixD9OrPlP428fsX8Dy37jq3WpvgurXfpdm/C3WDgsnAmJ/vj2TjL+EToMFix2kTadGVGSUPSWKR6bkcRjM5IobOxm4ecnmJ0ezLLMKBq7TAS4OzM+wZ8tOfXMGRjC+nO1VLYZOF/dQU2HkfhALY9OTyI9zAulQiApyJ1pAwJ5YmYS0X5a6jqN7L7UxKJh4Xi7OfHLbSM5UNjEpgv1sg+YuwZzrxeWyWanscvETd+fRpJk7dm3xyroMlrpNsqajH0FzTR1mzlQ2MycgSF8c8Mwuo1WBEHg6+uHklvbRU27kfPVHex5YFy/ZIBT5W3c9J383DeOjmJUrB96s417V51HlOSWnbtGjSCAv3vf53jXxDjCvF1xVin44nA5Hx0o5ceTanKencroOD+OPDKRj/aXsjK7GptdxMdNjauTkkAPDd/dMJyBL+zuff12rkgPRhQlvjlWga/WiXuz4okL0OKsUrLzYgNN3WYUQt/fX2+28fj6PHzcnPDXOtNhsGC2iRwpaeXqoX1X8MZuIweKWrCLEvn13Q4iFuSp4fjjWSgFgTNV7ewvbObuiXGOv+FlAn/ZR+10cxuPSucZFh/CTdODyHo7j0XxUfgK4bKgXZLQN9JvchHg1CsSplZAAYjQXiCbwapcwdkLTB3Qch6q9koMuF4gcDikXC+L84t+kXAJkHALFoiZA54xAr2+pNhMEDBYwCNaImiowMA7e8nVNhEECZ/kXqsNASq2Sajd5d933WRnwrsKnD0FvOMFND4SXvGgbwBBKSDZJUz/kB4w4AaBuiMSdrPsMRYxWUGYTc6ztOqgvRDaiyWGPCCgcsFB9ADy8kREC7RdhNg/uLHVhgoMfxzOvi0b5aZcJwenu4f3/xzTs6YTOzIDu2TBQ9tfE9tdo0ehEXF29sLVJQCVUoOTWkt13UEkq9JRdRQEBR4ucZgaBBSCip72VrTevoTFDaK5tAa/cPnYShmXRWtNNU7hekQPDT4+sYQlpiAoFPTU92Azm1n9/ONEDexre6mdNTi5uLDulWeImRVBu64Io6kVD/dIPLRhnNq4hoKjB3H382fmPQ+BJNHZUOfY3jsomKm330PqxCmEJaciCALhA+TK+sgFi6gruMSmt19h3LU3EhAVg1KlIjghiaCYOHQd7bj7+HL45285s3UDbl7eLP/8RyRRZMiseShVas7v2ILFaKC9vpbowcOIz88jNFHWUmp9fEmdMIXVLzxOfXEBA6dM5/yuLZzbuRnPgCB8QsNpLCumu7mJgOg4Ztz9IBaTkYPffYmXJDLHIh8wSpWarJvu6PtMnJy4dHAvZr2OSTcuZ+MbLxIQHUfqhCyiBw3l8I9fY7NaMOl0KFUq3H39KDl9An1HOyZdDzPvfpBVzzyMs5uWa195RzaJ/RMIgsBL8f27HVVGMypBYHaAFyc7dYzzcf+Trf/GP8Il1Q9Niu//UWf9/7/xt4/Yn6C0Wccv2bLX12WN1mU0dpmY9/ExbKLE7vvGOao4f4TLmq1/RGWrnuNlbbTqZHOouAD3flFAl7Elp57sinaauk2YbSIvbStg8fBwXr0y3SE6T3p6ByaryNVDwki32lk8TNZRTU8NovDF6Q4z1dvGyVMhCz87QXal/JzPzRlAfaeR9/eVEu3nypmnpuCkUvDqgjSWZkYyMMwLq11kULgXXUYrx8pa6TBY8XZVc+cE2eJi+bhYmrpNjO9t1y37+hTZFe18df1QxsT5MyTSh8SndmC2iWzLbWDHxUbCvF1YNjKSa744iUIAN2clS3r1X65OSuZlhHKxrov395WgVgrse2A8Mf5aekxWHl2XS7CnC0lB7jywOodAD5mwdBmtlLfoiPHXsjmnnpXZ1UT5urLy1hGIIpx+cjKFjT10Gi28cVU65S2ySSvIRrYvbZNvIm4eE83MNFk0nxDojg8aArq1uLW4gDecqmhjc47cilh9+0gWfn4SgHZ9f23DMxsvYRclhkX5kBnji8lqd7SeL2vxntiQR027EU8XNT+drKJVZ+HZ2Sk8PTsFF50TxjYJTxc1FhcbVcEtHKoXKGvR8521nD0/RqBQypWp8i0iabcJJC3uO4YCh0D9UYidJ08nho6Xlzt7Csz8RUHNQZGKLWAzQOkmO0qVwIAb5OrUuXcvTy5KSCKMfkWORPJLkwO8cz6WCB4ukL687/Wir1AQOV1CoRSwGSU2zBJBhKSlUPiTHNGkqwNnT/CKE5j+g4Kt14jsvkVk8qcKJryvwE3+2Dn2pJ3mHBj/lgJrj+y4X3cE4ubJLcXcz+QMp9SbBbRhAiqXvpN08wWJ6j0SiYsEAjLkIQKQdYCiVQ4avwybQSaLAPFXKn7npwZgtRk4euY57HYLo4c9g6e7TJrq8ouo3NyMWqPBY3YkEzJfA6Cto5CLRT8AAkteewOVwgUPvwB+ff4xavMvEpE2iOq8CwydfSUTb7iNsdfeSF3hJda+/DTD5izginse4psHbwOFyOQbZmMwtdDSlse8x55k7YvPYdbr8A4JZebohzmx9hci0zPQd7ZTV5SPd1QA3gPj6egqIfv8m0we+z6hSSlotO4kj5mAJEl8cP3VhA9IIywlFVcPL87v2kpwfCIxGcMc79lus3Js9c9ovX1xcffArNdRnXeBWfc9yoof1lF2NpvNb78MQHBcIrm9U5o2qwWTXkdJ9nHObFmPxk2LSS8z+HkPPYVXQBBzHpBztbpbmvnx8ftwdfdg+LyrcdG64+bti91mQxJFWqsraaupJnJgBrq2VjwDZc/DqtzzRKYPIjgukZhBQ7l0aB/ewaH9Wsai3e74v6G0iObKMoTqCmbf/yhqZw1LX30PfVenIzQcIG7oSKbfeT+egUEYu7vQdbSj7+rEbDA4iJjNamXNi09i1utY+Oyrv4tQAig3mJmQXYhaIXBqZAo/pMf8bp2/8c8hKIS/3KLi/2b8x3zEnnvuOVasWIGPj89/vfL/hXhjZyG785uo6zDy2bL+oksXJyU+bk6YrPZ+jvH/DDXtBt7dU8wV6cFkJQdy9y/nuFjX7dBvBXpoMFhsLPj0BEaLjfV3jsbHzYnrMqP49XQNTV2ydxVAq67/Bf/xGclkV7bzyPSkflUj4Hf7V9NuID3Mk/JWPaPj5DKvRq1AEMDVSeUI0nZWKUkO8mD1mRpGxfqy4c7RdBosLPz8BB4aFfdPTsBZraC0WceegkYu1XfzycFS5mWE0tJjRpTg88Pl3PL9GT5YnMHbCwdyoboTs83OhZpOcmo7uWFUFM4qBQHuzmy+ewyPrMvFYLHx2dIhvLNwEKXNPcz+8Bj+7k6EeMmat+yKdrbnyYrvDxYPQqkQCPd2RUBAlEQu1XejUStJDHRHrRQYHOHNW7uK+fFkFbeOjebLIxVonVWcfCKL5m4T4988QEKgO+9eM4jkYA8KGrr5+mgFycHuTE8NJsZfyzOXJmDSiWzLbmRqkDejYv0YF++HTZSI8XcjytcVk1Xk3qx4qtr0jsnYlBAP9hQ0MSzKm5Gv7SPMy4U9D4xH2Xtnd7n6qFYomJoSRFO3mcPFLQyL8sGp3YkdN4uoNDBzpQfZT2ShUSvRm238cLxStuzY1U5Eiw/GVplIWHr+4aATBax6idaL8nRg6QY5cNvJXUDpJBA+QcHp10VaL16uckt4RIuo3MAtSDaK9YyT3fe94uQ7f98UOP6sSN1heYuAuWY+OlXMqFg/ZqYF010B5963EzFJIPMZBY3ZEoU/yf5oGXeDb0of0TF3SSid5OdXOoF3Qt9jrZfApoeuConYeQItORJBw+THdXXy/irUkLz099+/3M9EOorkSKnB9/U9fvghkdY8GP+2wmFtoXYTGPaorJkLljuG6Gx2znTrGe3ljlohIAhKVEqX3oGOPmG1m7cPamdnPAOCUPS2mERJItfqjcItFg+VQHHtKoL8B+PBFNw8ZSsWSZRJrqFTruao1GrO79xKVe55jD3dTL/jfkSriFKpws9zALkFn9LRVUp0+DQWPf86B3/4ijNb1hOZnkFHfS1dTQ1c+fjzFB47xPAZVyG4mTl1/k28PGQCEJMxjDu/WsmqZx7h3I7N2CxmWqoruf2T78jZs4O9X32MoFCw8JlXCEuW265VeRc4vWmt430OnjmXYbPltPnsTWs59uuPaLRatD5++EdFExgVQ01+Hma9ntaaKtpqquSopdh4QhNTUGtcaKmqwNXTi4Aoeb962tsw9XRjMRgYOGUmHn7yjdwNb39KVc45Dq+U/d3a6+sQ7XaayktJnTCZvV99gqGrk/AB6ZSeOcXOT95F5ezMPd+tRqFQ0lhWQmN5KdPuuI/EzDEoVWqGzppPcfZxjv36IxOuuxWvoGC8goL7HTeCIDjilgCybr6TIz9/y+Z3XmHxC28iCALGni7qiwtAkuhoqP9DIqYU5H8qQeB/cBHnb/yF+I+J9Tdv3szNN9/835aIzc8IparNwNxBv3e+93RRc+jhidz6/Rkmv3OI724czpj4f967/vFkFevP15Fb10VWciBDI30oa9Zz7YgIXpyXSqC7M43dJgobu3un9Iz4uDnh6+aE0WLHZBMZnxAgbxvlTafBQl5dF6Ni/bh+VBTXj4qiucfE6Nf2465RsfGu0Y7qi95s481dRYT7uPLWriJsomzXEOrtwtGSVkbF+nH44Yn4avtP73x6sJQP9peSHubJ5rvHUNaip7hJvrvNSgnkth/Pcri4hRWT4siM8WV+r7fXL7eNpLRZx9u7ixElKGnScf+UBKL93Jj1oSxSf2HuAIZG+XCql2A0d5vZ02s+++i6XO6aGMeOvEaMVjt+WmfHewn20iAg64SHRPpw9qnJaJ1VFDf18N7eYu755TxRvq4cfHgihS/OQKkQuPm704AsgteoFbiolXx9pJwoPzeaus10GKx4aNRsu2cMj6/Po7Cxm4fW5PL10Up23DuW8e8o+ORAOV9eLGZtlxdrlmdytLQVUYJjpW0cfHgi1W0Gst45iEIQOPTwRII8Ndw3OYG7J8aRXdHOJwfLaNWZOVHWitZZxYf7S/F0UXOmqoMQTw2Hilto7jax/s5RBHpo6K6WEAQJk1XkcEkbkwfLhF2jVpIR5kNOTSfSOk/KOyWSl8oTj37p/f58qHqdUixdYGju/bm7z7tL6SQQNU2gq1w2Z1Vp4Oy7El2lspUEEgQPF0i9uY/MSJJEnRxhSOg42FJSx08nq9mW28DMtGBqDki0XZRJ1owfFLj4Q+UuCY0XeEQLWA0SalcBQ7PErhslRAvEXSkHijefk+iukoiZIzD+LQVd5RLaUKg9JJG8VOHI2Iy+QkF7gUjQiD+oXukkomfJRrWN2RKmdgmNj7xed5Vsp6Grl4cHTO0SRx4TcfGH0S8oHD5rKwqq2d7axV0RATwdG4JK6cz4kS8jijacnPqq3/W6fcQs9SB9wDUOQfinNS28WNbAKK9reN0rn5KKjRiMzZz76SiG7i4WvfAGNfkXSR47kaRRfVO0I+ZfTfXFHJoryig7e4olL72Nk4sLbl7e+Hon06Ovw9srHj//SPwioqjKPY93UAhabx/0nR34hUcybfm9juebOu4TBEHg7LaNlJ/LZuINt9FcWY7NYmbIFfNImyQL0CNS03F21WI26Di5/leuelImYiEJyfhFRNJaU42+ox3PgCC0PvKUs9hLJE06HSadjkuH9jHiymvobm0hLDmFgKgYfn32UQBSJ04hadQ4jq3+iZPrVuF3eD/Xv/WxfPwkJjNo2iwu7NrK7s8/4KonXwTAKzCIc3U1WIxGulubmXnPQxz47nNydm9DpVYx5Ip5VFw4Q9ywTCTRjqunF36R0XxT385Ad1caNq6hJPs4VpOR1AmTAfAICKS7uYm8A3toral2DClcFuiDnI3p4R+I1lu+Zrn7+mIxGWmprMBusyEIAk4aV+Y9/BRmvb5fNe23iHRx5sTIFJQC+Kj/nof7G/81/mNHyX93e4sZacHMSAv+08c1aiVV7QZsokRNh+FP15MkiVt/OEtBQzfDory5prdteNWQMBYND3dYIACEebvy7Q3DMFlFUkPlOy2VUsGa5aOobtcT4ePG/E+OEerlQoCHMyfL23l4WqLDBb++0+SI5ekyWh3kZXteA98dr0QhgLtGBTYFaqWCF7fm89PJajLCvXhsRpJDtK432yhq6iE11BONWuHIsxwS6c2zs1No6DLhp3XCYpPL/z1mG7/cNtLxPgLcNTR3mx2WFwPDvDhe1kqkrxvuGhWuahWbLtTz48kqPl82BI1aSYSvK6/MT+OX7Cq25zXSY7Jx1ZAwBOBcdSdv7irk4WlJ+Lk54+0mZ1VqnVQOoftj6/PIre1CQNZgfXaojHHx/kT5uZIW5snIGF+uHxXFE1ckM+WdQ7y7t4QnZybx5lXp7MpvJO25XXy2bAivX5XOmtM15NTm0tlrS+EdL5DQpYFyWfJjsYnMHRRKVZseSZIY9vJeZqUH46RUoFQI5NV1MuvDi8xKD+a5OQMYFefHujtG8dauIpZ+nU1KsAf5Dd2khnowOMKLqQOCeHdPMWabyO5LjSzLjMIjQkB/bwNv7C/Ec7Uazz1+hI4RCBkt8FDPcMpPiLhFCThHQsRkAScPWQvl/5sp+8ttPmcvGHKlQMFKiYodEmm3yITj+DN2WnJg3BsKvBPlZVsXyn9ThRqGPyEQNr4/2REEgeGPCXSWwIAbBUINgRwoaibJ6Mupl0WSrgWrTt5PkCtgs1YrqDkksm+5hF+axJjXFBhbJETZ7YOOYpDsMikSrbIpa0SWAq84gdOvizSeAptRJCRTPp5LN0h0lkLy0v771l4ocWCFiDYErAaw6qGnGnqHJJnwnoLuSgjp1WB3lkFnifyv9rBE+ET5+YIsah76KpZgXxXiOxIKlYBK5YIkiRSWrUUhKIiPno/R1IpCJWC29AnbvHu/cz5qJRpLGLZmLR5B6Zy/sAaAM5vXU3rmJOEpaaRNnOLYLjgukdghwyk+eZTja1ZSfPIo173xIWe3beLIyu8Zv+xmgvzlYZ7x197IgPFZ+IaF88UdN6Dv7ODigT2MmL8Qqded3qu3jXd6y3r0He1c2L2dBU88j76zk8TMMX37GxzK3Eee4ugvPzjMRyVRpCT7OGa9ASSJsAFppGdNo6OhjsbSYtKzpnF220ZsZhOi3Y6bpxf5h/bR1dyIm7cPThoXhs+9ivb6WiLTZb/D8JR08vbvJnxAOmteegq/8EgmXn8rvmHy+bCu8BKnNq7B0z8Ar6AQRi5YhJuXN3HDM/EJCcWjN1nApNcz4bpbGT73Ksd7uOOLn/ixvpWnimrxUinZPW0WXS1NKFVqDN1duHp4kjp+MoauLrwCg9j5ybsAtNVWE5oka9VKTh1n8zuvoHH3wEnjwsgF15A2cSqz738MD/9AlCoVPzxyD50N9Sx64Y0/TGL4LX47tfo3/sZ/hb/p+m9gFyU6DZZ/Kq7/LX6+ZQRFjT0OnRHApgt1rD5Tw+MzkkkN9cRsEzlU3IzVLvH0rBSmpwZR1tJrX6AQOPzIRII9XdCbbVhsIuPi/XloTQ4/nqzk4yWD8XJ1IjHInSg/197WnkiLzkxKiEzg/H+zr5fqu1g2MpLpqUEEemi4WNdFWYuO8Qn+jE/wR+uswkOj4paxMYT7uOLjKlfAztd0cv232RS8MB1BELjj53McLm7hiZlJbLhztKMtCHJo+fa8Rqx2kTkDQzhZ3s4v2dU8MyvFMTW4+1Ijt/14lggfVw4/MpGRr+yjsdvE6wvSUCsUdJssZFfKPmfT3zuCt6uaPQ+MZ8mICEK8NLy+s4hBYV4cKWnlivRgtuY2UN4iT+cGeGg4/tgkBEFun+rNNtr1FqamBNLSY+aJmckUNnbz2o5CNp6vY86gEN7bW0KEjyu3jovBSeXEnEGh7C9sJjPWj9RQT74+WoHZJnKprouJiQF0GGUCZrTYHe/78n3FhZpOpr93mMZuE2uXj2LnpUZaesycrmznyKOTUAjwzbEKWnVmDhQ18xyyS/fgCC8ud4nHxvsR4ePK4uHhDAr3xtNVjY+bE+eqOpg9sK8CO2a4N2srXJhZm0DlTonmXJGQ0Sr8UqFqj4BfGgx5QL7w777ZTlc5DH1YIHqm/EIho+DSN7LpqqlT9vCq3CWRdov8/C05coWs6YLkIGIJCwVyPpbQN4BroNzCLFotV0Di5wscfkQ2ax3/tgKVi0Ckixs/3zSCtVNEqiXZ+HXw/f3bhRofAbWLAMi6rl03yKatQx8Cfb1A1AzZ9T9kFHSUyCHg594XCRkl4BElt0WTl/WRrsZsCase2vIlAof2LTd1yBUvUweMel7A0gMdxRLHnhbJWCEQPFIg5xORnE9kn7XAoRA1Q6Byh8SpV2QLC6WTwH3KEA7VS1Av69ouZ2Z29VRRXiUbjQYFDGdw6p00VlWhP5GMwVXCNVBgSbAvE33c8VUq2PvZOkqOlGNMceWKex/B1NODm7c39SWFRA7KwGBsxdWlr5J+xYqHiR0xlKPbPsbY0YEkSTSUFGK32WgoKSJj+mwA9MYmWs0ncTE6M3zuVZRkn6Dw+CHqiwvkatKOLYy88hpGX7OMrBuXk71pDTm7t6Nrb2Pew09jMDZjMnfi4yVPFBYdP0J9UT4l2SfY/dn7aH39aCwtRqFUkjZpGqOuXoLKyYkNr78gTyLGxGGzmJlxz0MoFApaqytJnTSFopNHaSotpq22msyr5G0cx4BWyw1vf0LFhbOc37mF6os5dDbWYzYYSBw1jqLjh8nbt5Ou5ia5zfjtanQd7Rz47gsm3Xg7pWdO9k5EpvLxzYtJz5rG2CU3OJ5/gFrAT7SSqVETkToAk66H5ooyfMLC0bhpCUlIZvRC2RBWoVRS2tbBHvcArhUl1AoBZzc3BIUCSRTpbmmiNPsESZnj0Pr4ERgThySK9LS1YLNa6Olow3Chi+D4RDRuckWtq7mR3Z9/QPiAgY4EgL/xN/5V/E3EfoMVq86zLbeBdxYO5Mo/8fz6LcJ9XPtZHwB8daSCvLouVp+pITXUk3a9BVcnFa5OSsYnyCddrbMKd40atVJukxktdia/c4gOg4Wfbh7B+vPyRFNObRfjE/xZ8OlxChq6WXXbSNYsz+SLw+WUNevYfPdoh73FxbountxwEYDrR0UiihLXfH4CvcXOh4sz+P6m4Qx7eS8tPWYifN24I0DLmHh/WnUW9hc2Ee2ndRApF7V8IS1p1vHK9kJSgj0cZqTBvf5kIZ4uDIv0IcLHlUHhXgiCwOeHylAIAolB7r2aM5kkBHlqaOkxcamumy6TFVGUeHZ2Cp0GKx/sL6FNL3GxrguVUmBCYgATEgOY+f5h8ht6WJARysdLBjMmzo+LdV2E+7j2CyOf+/Exylp0/HDTcNw1au755TxzB4UQ4O7E4EgvRkT5EOrlwtQU+Y7619PVdBmt6M02XtiSzy+3jeSFuQM4UtLiSDWYNiCIQ8UtjIv358cTlWzJbeDerHjGJ/iTGuLBL6drsNol6jqNRPm68fC0RCYnBzqC2QsbZLFWeliffuTroxUcLW1jSKQXj8+UWxo3fXeaG787zadLh5AZ48v3xyt5dXshr18l9xhj/LVsvnsML31dTFuBhCLexBVEog2Vo44qtoH/IJHwCQJOnoAATh7y37A1T8LcLXt5oYPIyQKiFQIG9RGXtNsEzr4lUfizRPx8mYQkXKWgZJ1dJm07JSq2i1T1pnx4xcrkDQm6q8FfPvQ48riIUg3+GRAyqi/LMv97OfMy+goFUdMV+KRInH1bxNjrgNN8DgIyQBsib5P5nHy8XPxGpGyjRONJCX2T/HqX/fQsOkl25xfkKKPfQhss67yiZwmEjpaP4SOP2bHqoOUC+CTK1hQA5k5wchdIWQZtFyU8ovpE/E4DRN58sgS1QmCGdzwg75eHNhx3bTii3YqLsw9qtSsNq1Oo3ivRni8y+iV5PU+TgW8eXYEkSsQOGUHG9NlEpg9y7Gf88FGcznmPgyceIT35JsKC+ypUZvdyQiZ44OeZht1mI2n0eEKTU0jMHOdYp6hsLU2t5+nqqGXkzIfwDY9k7UtP0VpT7ah2dbU0s+alp4geOJjEUeNoLCtBqXZCFG0cO/0iVpueYQMfwN83FbtVvvHoaW1B19GOUafDzdsH/4goptx2N4IgINrtBETF0N3ShKG7C9Fmo7Wqgtx9uzB2dyEoFChVKqxmM+tfew6TTsfSV9/FOziUgqMH2f7hWwRExbLoxTcYOvtKTLoeh9fXvIefxjsoBAmRCzu34R8Zjd1q5cKurQBU5+Vg6ulGEiUaSoow6XqoyrtAX2MX9Hu3cuPGNfhHRsOwDxk4ZSYlp45ht1o59OPXaL19WPTCG7h6eJE8ZgJXHsmjo7gWpQDLQvyISB3I7Z9+j9looODIAVLGTmTbh29SduYUYxZdx4j5C7n2lXfpaW2l5lIOJ9f/SvSgIVz5+PMAlJ05RfXFXBrLSv8mYn/j38bfROw3aO6WqzTNPebfPaY323h640WCvTQ8PO3PvdIemZ7IhnN13DRa9pGq7TA6LvxGq4iLkyzMP/7YJBSCgIuTkh6TlR6TDbNNxEml4LUr02jqNjMmzg9Jkqhq02O2iTR0mchKDmB/YTN2UaK63eAgYmHeLoR5u+DqpCTM2xWFQiDIU0NVmwE3Z/kCcePoKPYVNDOll5Tc9uMZOg1WfNzUnChvY2tuPbPSQ/hw8WDqO40UNHSz5kwtpc06PthXwoqseJ6elcJdE+No7DIx/9PjpAR78MHiDC7Vd/Fqb3TRzvvG8unSwRTU96A321izPJOfT1bx3JZ8PDQqVt46ktRQTz7aX8K4eH9uHhPFdd9kY7aJbL57NHl1XeQ39OCuUbFkZARDIn3YeL6O+369wIAQD7at6DsFm212JAmq2wyUNsv6NaPFztQBQfx0shq1QoHVLpJT24nZauex9XmO6laHwUKPycodP52jTW9hWJQvCkHg8Q25XDsiktvHxzpipU6UtTlMaJdmRnKirI03dxVS0WrgnklxJAa5Y7DY2JPfRGDvpGx+fTfrz9Vy5eAwx5Skr5szVrtIQUM3dR0GREk2kdWbbVyq76aosYdX5qZy7l1Z7zT8cQUeUQLvJJ/BT+XE5Ep3UkO8cQmQq1mnXpQwNsvZjb5p4J8OzeckDj0oi+4nfihgaoemc5BynYBCJZONxmyJkrUSKEDtQm/JT35s1AsKWi5IFK+Vn9s9UvbV8k4EhVJ26rfqQBLlCldbvkz4IiYJlG2WcA2UUDoLFK6UP+iwibIuzCNCQOydMwmbANV7oXqvRNg4CbVWfu36E7L3mW8KBA6H9gK5KuUWLFG5U8IvDdRuINnlaUeNj+Qgcvk/SDSclPcrZJREVxkMukegYTBEThVw9hIY96ZM0C5bVLgFC4x7S4GglCtsZ98Wsc0wU+1rRgBarTa0vUJ8m81Ij64GgPbOIgL9MwgcAo2ncQwSABh1Peg7OxAEgYk33IpnQNDvzhP23owpm83Yb7mnRxR1jcfx9Uti39efcPHAHgZOndlPFB4SlEldZQ65u0/gKx0nbngmE2+4HTcvL2IyhpGeNZ2G0mIKjhyguaKMu77+heiMoXgFBiEICgTRCSQD2OVjcvItd5I2aRoBMTEcX72S05vXISgUzHvkGQRBYO9XH5O7bxez7n2EK1Y8TGdzI0dXfs+pDasJiIrB1cOTuKEjiR0yggu7t5F/aD92mxV9VyfewaEolL2XGQHWvfwMnv4BFJ2UIxQSRo4lZshwOhrqOPTTN4QkJDPxhttoq6th6vIVdDTUkzppKsHxiVjNJirOnyF1wmSGzlnQ73OLTBtE/pEDhCalUJl7nuFzr2L43KtoLCuh6MQR/MIi+WrFrQRExrDs9feZ6OvBsY4eBrn33UiLdjt7v/yYoNh4vINDUanlGytVb/qAd1AI3kEhtNfL/m5u3n2xRCnjsuhorHcMO3xe08yRDh2vJYQRpvnbOf9v/HP8TcR+g8+XDSWvrouxcb8X3p8oa3NUqm4aHf279uWtP5zhdGU7P908gneuGeRYPjzah+fnDGB/YROFDd2MivPjxxOVfLi/lKdmpTBnYAjuGjXbVoyhx2QjNdTzdyau6+8czaW6LrKSA3BWKfls6RDKeiNwBr+4h7smxhHqpaG2w4gg4DAY1Zvt2ESJ0xUdjInz584JcQ7LCYAZqUEcK21Do1LQabDirlHTZbCy+kwNk1MCmZEWzLUjIvj5VDWrz9RQ32nkjgmxRPq6cbK8DZ3ZRn5DN6IoEeuvZWpKIApBINrPjZu/O0Ndp5Hiph7evWYQgyO98XRRMzLGh9RQT0xWO2/tlsO5Zw0Mxk/rTLfRirerE8reylykrysPrs4hLcyLGanyxcxJpcBss3PnT+ew2EXeuXoQi788yfNb8tm2YgzDon0YG+fnsKKoajfQ3GOm02DFLkksHy8b205M9OfHk9VMfOsgbs4qVEYBNycl2y82UtNuZHteA8vHxzoyO89XdyCKEkdLWzlZ3sa3xyowWkUEcBj8vrajkB9OVDElJZDrMyP5/kQV7+4p5srBYVwzLJzRcX4EeWp4ZtNFfsmu4doRETw+MxlfNyfe2V3MvEEhzEoPwdQmULlDbge2XwkrsuLZebGR/IZu1h6sx1bpxYgnFJRuEKk9DGp3qJaLC7QVgIuvHMqt8QGfJIFtC+VWoGSH2DkC+gaJ8m0i3ZXgnSRrpQ6skEhaIlG2WSTtFgWuAQIKpYRbKAy6U8AnWaAtX8I7Ua6GKZ0lNl8p4eIL494Q0NXJ2ZQXv5bJ2fQfIHCo7NWldu0jKSOfFzC3yZmWlh4RbYjgIGF1RySOPyOidpNNYfN/gDGvKAgeIXD+A5HSDRJBI2D69wqOPyNSuRNEq8SIp+Tto2YI6BslYmYpuPSNnKsZNV1g2KO/tfToryvT1UvsulFEoYbo6XLwuftWDd++GYVKEIhy6fueOzm5Exc1G6OpHV8fWVsUNV1BlByfiM0okfuFhFdsKNc88yqCUtmPhOkMjaiVLjg7ezIkfQWV1bspKl+PzWYiLlpuO0aFZREZOglBEChTyAkV+UcOMOaa6xzC8uCAoXQedaGnqhFRtCMIAoOmzaT09Em+vPsmXDw8WfDkC5zdugFjTw+VuecJjktg3zefERgdR9GaBizGHixpa5h4w214BgTSVltN7r6dJIwYzelNaxGtVsd+N1eWI4kiBUcPseOjdxg+/2rceyccnVxc8fDzR+2sIXffTvL27cI7OJTJt9yFT0gYzZXlRKQNJGXcJNy8vDm9eR11RfmkTpxCQ3EhIxcspOTUMc7vlKtfzm6u/PzEA0iiyPVvfUzaxKny3y0mjvzD+8netBYEgaiBg/ENDaenvZVt77+Bf2Q0t370NZ/csoQLu7Yx75FnKDt7itqCSyx4/HnaaqupuHAGq0W+yf4kJZKetlYaCy4gDh2BQqGkMvccNZdyqSu8xNglNzDj7gcZtXApPr2B5Oe69KxqbGf5mCzuGDFKTiDohUar7edj9k5lE102O1ubO1ke0Sdd+Rt/44/wLxOx9957j7vvvhuV6o83qa+v58knn+Tbb78FYM6cObi5uf3huv9/w2YX2XShngGhHv3E8j5uTg4vLIAdeQ206i0sHRHB6Dg/Fg8PJ8TTpR8J23ShjvPVnZwsa6PHbKOwoZv15+roNFh45co0NGolRU09HCpuparNwMPTkthf2Exzj5lDRS3M6dUE/TYMXBSlftFGbToz9/16gfhAd3bcO5YpKYFMIZBH1+bSrrdwqLiFt65OZ1iUN9F+brg5qzhc3MKcQcFcquvmi8NlHC9rZdPdcttCZ7ax5MuTiJLEthVj+GBfCSIQ5KHh3b3FfHe8kj35Taxenskj02RLjB15jaw6XYNCITAyxpdH1uRwRVoQd02MRwJWZVezdGSkI/pnZloQ3x2vZMfFRhKDylg2MpId94516M00aiWPzUiitFnH9AFBzBkYgl2UcHVS4df7+Va06NFb7DR0mXj/mkEcfGgCgR4y4dxXKI8B3jwmGhcnJQLg6apmVlowCoXAK1emMjzah6c25uHr5sRj05PYmtPAA1MSsNklesxWXt5eiMUmcteEOL4/Ucnyn8/x080jcNeoHFXDpt7MzmNlbdR3GXlg9QVadRZ8XJ0QBDu/3pZJWm8LMr6XkMUHaPHtbVO26S18e6yCF7fm89iMJG4bF4vJKmvP3DVqJiQG8Ni6XA4UtzA4wovJva878A4Bc4+E7wC5UvXivFS25NQz9HwUtYckWi/Jk4iTPxfwjpcdW42t4BkjUbMfsj4VHG75Sme5iuQdL1C9V+TUy7LpasxsAW0YdBRKdFdDwc8inSVQvk2eXtQ3yEL/I49JeMXKAvmUGwQmfijQmguWLglrD+R+JjHsUQVqN/BLk7VS2hCBwGFyi9TYJuHiK3Dpe5H87yTSboOkZAVJixRYeuSbhuZzEnVHRRTOcvXN3AWI0FEk4hmtwCsOUMjvQe0mEDVdwNQmC+zbCyU6y2TSFTRMJs4dxf/isFBv1iii3NJUqOX2qt/lvus/ICFmPiDHIhWsEwkbLzhsN2oPS5RtlInogj0DUCgFqnIvsPuLD0gYOwK9fzZqtRuTRr2JWuWKxarDbjfT1llEHLMdryEIAjs/eY/y82cAsJpMWIyGfhN+1zz3Gt2tLXj0it2P/vIDpzevA+RsTJXaCScXF4w93Zj1Os7v3Erevl1cFPYwbO4C8vbtouzsKWxWC1c9+SL7v/0cm8WM1tcPpUqNJEkYu7vQ9zrOK1QqJEHAZrVQfTGXgMgoxiy6jsLjh6ktuIizVkv8sExKTh1nwPgsIlLT+eqem+lqbiJl/CTyD+/H1dOL0QuX4hEgTyZeOriXHR+9g7uvH92tzcQMHcG021fwwyP3YLdYyD+yj7Iz2Uy9fQUhCUmEpaTi5u2DvqOdo7/+SOKocdReyqOuMJ/6okImXHcrHv6BdFhq0Xr7UHT8MBajkbrCfNInT2fpa+87LDIANrz+PC1VFYxfdjNDZ80nKXMcbTXVBMbEIQgCSpXKQcIAXiyv50SnHoso8V5yX+btH+Gl+FCOdei46h/c9P/G3/gj/MtEbOPGjRw8eJA33niDhISEfo+tWrWKN954g8GD+0Qbzz///F+3l38xVp+p5YkNeQS4O5P95OQ/XKelx8ydK88hSRDr78aoWD8WDg3vJ1wH2WrBZBVZPiGWGD83hkX78NDaXECejBwVJ2+XX9/FhZou7lp5jh9uHMbQKB+uHvJ7Hdqq7Gqe2JDHPZPkaKEek5WSph5sokRLj9mRYADw8PREov3diPPXYrKIrFku55vVtBu4/ttsJAmemJnEsbI2Cht7OFjUzITEABq7TI4sy/pOE+vP1dGmt3CkpIXMWF82XahjXK+ezdNVzfgEfzbn1BPt58qCwWFsyanHZBOp7zRhtNr4qbftqFYK5L8gG8g+eUUKRqud1adrifZzI+udQxjMdrbfO5Y1Z2o4VNzC+4syWD4+9nefwdbcenn60UPD0sxIEgPdsYkSoiTh4qQk1l/LfZPj+epIBZ8fKufIwxMx20Wu/fIUHQYrW+4Zjc0uEejhjNUub/f2nmIau03UdxlZeaoak9XOx0sy2JPfxEvbC+iVkmO1i9w3OQGrXSSvtovVt2fy9u5iBoV7EebtyqJhEWzLa6CiVR4e8PpNPNGyzCi6jFbyG7rJjPVFo5anKLfk1CNKcn5oq87M7vwm1EqBRcPCkSSJcQl+tOstLBkRgSRJHCpuIXS8C3f/cAbTm3a23jOWIZHeDIn0pjVGosAg0ngGTK3w84YG7ngohJgr5KrPqVdEqvdItObB6JcUXPzGjr5Bbs35JAu05MmVNtEGQx6Qt+kqE6naLWE1QMQUgYSFcuRPja9ER4msp1L1HvYdxRKmdgH/gQKjX1Fw6iXZm6v+uExARDskXiMgKAQufi072wcOkYibJ9Db1ZOHB9olDj8qG766+EucflPE0AjJ1wkMuEHA3AHVByRyPpIoWScye52CqOmCw107coqCyClgaJLYeYOI3QSCQo44ar4g0VYgMfg+Ae9EOPyInegZAuETf+85pg2VjWUrbCaWNtUyZboHKyJlMtyYLVG1RyLlegH3MPl1i1eLNJ2T0HhD5U4583Lyp71ayOECQSPtSCNWkVtoJC3pBipyztLd0kzluRwCpitQCEout4ATYq7EzS2YQN/fB0qXnTmNSdfD0NlXkjByNB7+/asqzq5uHNdYuONQLkuCfbmqN4g8auAQBk6bSd6+Xcy852HKz53GZrVycv2vAKRPns7YxdfjHRTMvm8+c1TsRi+8lpLsEyiQ9WB2m5XN77xCQ0kRKicnRJuNhOGZRKUNoru1mdOb1uLm7cP4a2/k/K5txA0dSfiAdG7+4Ev2fv0pK596EEGhBEEgNHEAnY2NxGQMZcT8hQDk7tuJJIqYdDpm3PUAbl4+DJk1D1cPT5a9/gH5h/aRs2c7Xc1NnN+5pXdYYRb5S+5CvWMdQ7Im09FYT/WlXAaMzyJq4GCUKhVzHniCygtn8QkJY+5DT9FYVkLKuEkAePgHcOTnbwlJTCF1wmS8Q8JoranCK1AeL1ZrNEy4Tp5kqb6Yw6kNvzJs9gJHePd1IX6Y7XZmmNuxWYNRqf98MvLqIJ/fRRr9jf97MWnSJOrq6n63fMmSJTz77LP/8df/l4nY1q1beeGFF1iwYAF33303t956K42NjTzxxBPk5eXx6KOPcs01/z1EiolB7rg5KRkS6f2n63i7qhkX70+rzkxioDt78pu49YczBHloOPlEn+nf7eNiOVPVzrKRkYT2krT7JsfTabAyNEr+Ig4K9+KpK1K47cczeLs6kRHpzbjEvhPrc5svcbikhY+XDOZifReiBHl1XUiSxBUfHKW2w8BzswcwZUBgvzxDP60zmTG+zPvkGG5OKk48Pgl3jRpvNyei/dyw2kWuHhLOybI29he18OauIl7ZXkCkrxsfLh6EhCysf39RBtkVbQwK9+LD/aXcOCqK9efqkCS4JyuededqKW/RMzDciyGR3sQHahGA745XsuDTEzgpBaJ8XYn2c+uXI/3SvDRSQzyp6zBi7yVSkiSx7lwtrTqZ+CUGufPDiUre2FnEk1ckc/WQMDbl1CMBycHuXD00HK2zirtWnmNbrlzRqm434K5RoTPbOFvdwamKNj46UEZZiw5Rgk0X6nltRyHxAVrumRTHwmFhLPxMdr//+VQVXUYbVpvIE+vzyIyVdR5h3i6syIp32IY8uSGP1WdqWT4+lk+XDqFNZ8ZktfPQtESWjozk3lXn8XN3JthTQ25tJ9kV7Vw7IoJ39sjeaeMT/LlmaDjfn6jCYLXz4JR4hkXLryUgIAgCeouNF7cW8M2xCuZnhOKsUvLr6RoeW59HqJeGhi4TogStOjPNPSb8tM4EpmoY+7qS8zuNfPhzJYdaK/A+bWNLTj3LRkYxYHAgjaf6WnBx8+RJsOgr5N87S2TK6fqb63rYOIHq/RKBGQJDHlRgaJbIflVCUELmMyCoZYsHUwc0HIeLnhLDHhEIyRQY9oiC5gsSwZmw/x4JS6dcGfKKE8hYIdB2EYctxOD7BULGCLj6S1z4SMQ9FOxW2WYj5gqB2sMSoWPkz0blItFZ3Kth08q+cX8UcbLvLpmEqVxlt36A0g0izWdBqZboqhRoOg3mTonwP4mRcwsSOFDVzeluPVUms4OI5X0lVwid3CFjRZ8OzaqHmLly5S4yS6C9s5jzFz8lOHAEQ57J4uCJA+iaIDxkPCPmXY2zqytRGYOp69mJk5MHCoV82lWrXYkKy/rd/lh0EmGdX2O32Bk63Qk3/74Lvmi3c2LdKtx9fSmOGYjCZkVa9x1iQgw3vf8FngGB7P7sAy4d2kdwfBINJbJu083bB5Nej6unF3abFaNOh81ioezMSabcehfJYydyeOV31BcXMHPFw4QmJLPmxScBGDFvIQExscRkDKPoxFHObN2Ad3AoA8Zn4eLhSUNJITs/eY9bP/4GSRLJ3bsDSRQZNG0WQ2fNxzMgkLRJcqB3R2M9XgFBHF31IwBjFi0j78Bu8vbvIiA6Ft/QcM5t30T2xjX4hIQxbM4Czm7fROGxQ7h4erJJ8sZ55AySKorpzj1DyanjhCalkDRajo3Y9el71BZcpKulifFLbyIitY/kFh47RN7+3RQcO0RAVAye/gHc+M6neAeH0t3SzKXD+xgwLgsP/wAu7NpG9cVcVE7ODiI2P9CbgEPbOLluFfYxE+S4qH8Tdkni1fIGXBQKHoz+vXbwb8iQJJH2zmLM5k6cnb3w8UpAEP418/T/Faxduxa7vW9KvqSkhBtvvJHp06f/x17zt/iXiZhWq+WNN95g6tSpPPvss2zfvp3a2lrS09PZvHnzv+28//8nhkR6c+mFf/4Bq5QKhzgbZP8tpULoVwGRJIlukxVPFzUemr6P8vZxsaw5W0N1u564ANkA8oP9pbTrrYyN98ddo+aX7Gra9RbuGB/L5hw54/FkeRuPzUhmYJgXExID6DJaMdvsiBLEBrgR6uXCkZIWPj9Uzp0TYxkV64ebsxJnpQJ3jcrhoq91VrH/wQmO/XlgaiKCIJAc7MFHB0opa9Hz3jWDcOsVkMcHahkT78ezmy5yqLiF/PpuWnRmNuXUM2tgCBfrukgP8+TxGfKQQlmzjoDeWCEBcHNWsTQzkpe2FrBi1Xk+uXYIHXoLP56o5J29JQB8tDiD6nYDWo2K9xdlcKqincW9kUYnymS92cpT1ewvbOaJGcl8crCUrXmNRPtreXBqIubedt6Fmk72Fzbj7qzi3WsGEu7tyueHy8mr62J4lDd3TIhDZ5YNqspadHy4v5Rwb1emDZBbpS09Ft6+Op1fT9eSXSkHjS8cGsbqM7X8cKLKkRV52f1eqYBtufXcu+o84T5u7L1/HIu+OEF1u4GfbhmBSqngjp/OUddpRJQknpszgNzaLqYPCGZ0nB9WUWJ0rB/3rTqPSCmfXjuYlbeOwEWtZPGXJ+nojUU6XtbKhvN1XDU4DKVCINpPy7vXZGC22ekwWFjy5Sn8tE6cfDwLlVJB+lQNQUYbs83BXKju5GR5O1a7xLo7gh2apa4KOUNx9EsKnNzl9+OXJkcFBWT0kZqQ0QILdiscJF8SZT2ZZIcjj8pi/Z4qeV1nbwj+jZFq2HjZa+zEcyKWTnCPgLh5csSRe5hA9AwwtkDhNpHIKQLhEwROvSRRcwAChsD4t+RqUvJSAddAkeq9Eu7hUHNAomo3CCqY8qVsb6Grk8j9vK8dmP1abwyTCtKXC3QUyaHhSUsUKJQS8QtkfzVLt1wR/Ge4NsSXZouVsd59hq2JiwSKVsmB4ypXWTuXsUKg+QKk3ijgfF8v8asswmzpoqUth5T4RYQEjqRHV4urxh8XFw8yFyymtf0SzZU58vctei4umr5qiSRJ9LS2OKpeVh1Yu9RIkorGwmpi/fsicipzz3Fy3S8A3Pr5j4QodTTmnuJE7ikGTpnJyXW/0lxZjqunF3HDRmI1GXF20zLvkaf5esWtnFi7ErVGQ1R6BhfDIvANCcNqNtHZUC8nB6jVhKekIUkinU0NAATHJyEoFOTs2UH5+TN0NTUQmjwAs0GP1WxBEOSJSUGQUwjGL72Jgz98xYVdW0mdOAVPAsk/vJ+dn7yL1tuH2z/7ATdPL8x6PV5BwRSdOALAmS3rqMo9T8r4LDRuWuKGjWTskhvobmmmuaqC4LgEfnJy59yXW+g+dxK3uASC4xMJS07lyC/fM2z2AoLiEqgvLiQwpk8LazEZcdK4EDd0JJUXzhKaNID9335OXeElzHo9U267m0M/fk3xqWO0VFUw54EnGDF/IUq1msEz+oeUXjbuVSj/18K6z3Ub+KhallXMC/Qi1vXPMyz/X0Vj81nyS1ZiMvf582mcvUmJX0JQwJB/suX/Ov7ReP6LL74gIiKC4cOH/8kWfy3+bbH+oEGDSEhI4MSJE7i4uHDHHXf8tyJh/w6q2wzc/cs5MsK9eH5uKicen4SHpo+IyfqfSkBuQ05Kku+kPz9cxnt7S0gKcmfnffLY+dVDwmjTmZmXEUpDl5HH1+cBkBHhxcdLBnOuuoNFwyJwcVIS7efG1HcP0WOy4evmxKa7RjMw3Iu6TiNfHCrnaGkrbs5KRsX68evpGkw2kRtGRVHWouP741Vo1AomJPo79ic11JOvbxiGKEr4uzsT7uPiIGGv7yzk04Nl3JsVz/Wjomg3WJmaEkBJs56Jif7sutTIhZoufN2cGBnj64g5stolPlycQWqIB/euusDrvROTnQZZ5Pvy9gLWnq3FX+tEbICW7Mp2fjhRxaHiFn69PdMRrwTw3BzZZf+9vcW9hMqHycmB7MlvZHi0/AV5ZtYAZqQFkxnjw9MboaxVx1u7ivnl1pEsHBqOp4uKQeHenK5sZ/mEWNYuz+Tt3UUUNelICfFgzqBgXNUKSlr0PLw2lxmpwdybFc/CYeEUNnSz7lwdLT1majsMhHm78uLcVKYmB7GvsIm7Vp7vfW8WREnCYhMRJbDZJc5Vd+DhosJsc2JIpE+/KuuBomZMVju78xuxihJqpcBtP57F21XNrvvHYbKKSMCHizP4YF8xTd1mdGYr55+ZgpuTykEGT53r5LEL49BrzUiihEmUMytfmZ8GQFGZjrSVcXg0qrDdKKHSyNudfl2O+rF0Q9BIqNwhkXStwJU7++4sS9aKFK+VyFihIETubOMWJDDtOwUNJ0UufAhI4D8IdPUQNBRCe90W2vIl6o5IJFwt4J0AtUdkEqbxETj6hJ2GE3Jod2eZRN0ReShg5NMCsXMFTJ0SCQvk/ShcKWLqkChZD4jgGQ1Wg4RHtDyNqHbtDRXfcfl5JOLmQ3u+PKgwZ72C7deKWHvkyln0FQpGPvObAYGn5Z8NTRItuRJh44V+eZMgO6C/+A/BzRGTFHSVixT+LNF4SqJkdgfrAjt45q4QnN36LqBR4VNRKJzw9ZZvVDq6SjCa2igrPEy411w8owV8vBKJDp+Gk1rbj4QBcmD2lvWMmH8NYxYtwy1IYNy7Ehtff5mNH53mKq+XiEwaAMePEu7kRGR6BlofXzw9PFk4OpN9hZPR+vji5uXNqQ2rEe02ptx2N+lZ0/sZnwbGxFGVe57sTWsZMnMugdGxFBw5gOY7LSGJKSBJOGlc0Hr7IIkiKeOz6G5pJiA6hs+XX4fdZmPC9bfiHRRE8clj1BVcIj1rOjd/8AWiKHFy3SriR4zmwq5tALi4ezhc6l09vVCoVPiEyp/xta++h9VkxMXdg8m33sXpTes4v3MLXc1NjFl0Hcve+IDjq3+m7OwpZt33qOM9jAWCJk7iSEM16VNmEj88kx8fXSH7jzk5MX7pTYy79kYkSUQU7eQfPsCuT99j4JQZTL7lLuY/KreZnF1dMXR3ET88E4CYIcOpLy5wGLUGxsThGRDI6c3rmHr7Coc+b+SCRcQPz8Q75L+2N/ojpGldWBDojatS0W8Q5G/IaGw+y7mLH/9uucncwbmLHzM49a7/GBm7DIvFwubNm7nxxhv7daD+k/i3iNjWrVt58cUXSUpKYvv27axdu5abbrqJJUuW8OCDD+Ls/N/nwFqVXU1jt4m7J8b9Ydg2wMnyNnJruyhs7OH5uakEuPe/e/HTOvPkzGQKGrvZkdcotx0jvBkc4Y2HRsWoWJlsdOgt+Lg5seXuMSgUAnZRYmKiP0dLW3l3TzGrb890tMgAzlV30NFLaLpNNqL83Chu6uGKD46gUStlw1Z3Z9Ke20Wkrzx+3dht4p3dxQ4R+6+nayh6aYbjOW12kWVfZ1PfZWTVb1zwW3qtOpp7zNhFiTcWpOOsUvDkxjw+O1TGU1ekUNdhdBAnFycl0b5uVLcb2FvQRFZSgGOC8/7J8Zyv7mTuR0eZlR6Cs0rBreNiuG1cLBvP1/LjySpOVbTz+PpcXr0yHVGUMNtEAj00qBQCo+P8cFEpGBLpzWs7CxGAaD83JEli4ecnaOw28d2Nw/hwSQYDn9+N1S7xw4lKvjpawYhoHw4Vt9LSY8bTRc32vAZyarv49NrBeLqoGf7yPrzdnBga6Y0oycHtlyOfXp6fipNSQWO3iR+OV7Itr5GspADWnqvF0GvqOj7Bn1euTANB4OohYfhonRmX4M/cj45S0NDDnIHB3P7jWTIivHj3mkFonVW8tC2fVp2F6N6/0cTEAPYXNmETJY6VtrLzvrEYLXZ5CONiAyXNemo7jJgsdrROKkqbe4jx0xJh8aTaLOJnc+Hm785ysrKNVxeksfZMLZNTAhnpEshW7xLSOwKZ2hWIqvcw9RxhY61YgTbCn9avvGi7BAoVxC8ABPCMFqg7KmFogoZTEt2V8qRh6i3QXiAQNFxg8mcCbsFyWPe+O0UqtkPC1fJU49l3RLrK5Apa+m0CjWdky4uQUZftKCTUWplMtV6UEC0Sx56yM+RBhaMSZmiRyPtSFtYHjwS7WY5mOv06oIBxb0LbJbnSFT1DoKdaJlLBIwTaLkrYrXLlLnCwnEfpFf/nJ87jz4l0FIK+QbbyAGg4KXHmTZHYeQIpy35/HkhaLFfVgoYJzK5sothgIr7BmYejgzjbZWCklxtOSmdiIqY5tokOn0p9/TmK3xxCYZPIhA8EDA0K4kcv7BdOfhkmXU/v/92OZX6pAir/OpQtKpxd3aCuFgoLUQNXPfgkaOQ/stpZQ9bNy9nx8Tvs+Pgdsm65k+aKMhIz+yxedO1t6NrbyFywmOq8HNloVQDP3gqcZ0AQkt2OT2g4o65eAoCgUNBSVUFLZTllZ7MJTkimva6GmMHD8A4KQa1x5dT6VeTu20nqpClcOrSfnN3bqMq74IhAGj7vanraWnHz8ubkulWINhsp42VNrmS3c2rjGgKjYyk5dZyS7OP4RUZjNRox6XVcOryPS4f2UV9c+DsX+/jho4gfPoqz2zbx0Y3XEJKYjFrj4ggtN/Z08+OjKxAEBQkj5RiFjob++p/ksRPRtbdxeaRjwPisfjmTVpOJUxtWA5A4aiyJmWOxSxJf1rQQ5eLN9D8ZWvuvoFEq+Dgl8n9p2//pkCSR/JKV/3Sd/JJfCPTP+I+2Kffu3UtPTw/z58//j73GP+JfPpruuecejh49ygMPPMCyZcsAeOSRR5g8eTKPP/44hw4d4rXXXiMjI+M/trN/FVp1Zh7rrUgNCpfbgH+EOYNCqO00khbaP9j1t+75t46L4YFfL7DmXC21HUZ+uW0k4xL8yX2u78R8yw9nOFvVwVNXJHPL2BiUCoFrhkVwoKiFnJpOrHYJJ1XfCfq6zChqO4z8fKqawZFeeLqoaewyIUmgEATeuCqdu34+R4/JRlKQB3dPjGNCYgCHi1uo6zJiMNsZl+DHurO1bMtr4MkrkvHTOnOqos2hoVo+PpaVp6q5VNfFEzOS0GpUTHn3MCNjfPB2cWLHJdn5cunISF6cJ3vj5NZ28vGBUm4dF83Da/PYdKGeZSMjWXvHKKrbDQyN9Oa9fSVIEjw0LbEfEfTVOjv8uy4bnl771SnOVnXwzsKBPLv5EgCrb88kzMcFJ6WAJNHb7hBw7Z2MfG1HIXEBWr67YTj1XXI7EMBiF1k0LJzteQ2YbSJmm+hYvvpMDd0mGwaLjcZO2bdp6oBAh+/ZtAFBDI70wmwTcXFSUdcpT2W6OqkQRYm3Fw4kKzkQjVrJRwdKeX9/KSqFwJIREVwzLAKbWEWEryubcxo4UNhM6rO7eGV+KismxXGouBUvVzUVbQYMVjsvzkvl8fUXeWB1DvnPT+dCeyeX6ut4bUE6JU06LtZ388ymS4R5u/DV0QpuHRvNEzOTGfIQ2IwK3inpwWIX2X2xkRPlbVS06mkaZCI7oJbW2E6e8A/k1R0F2O0SnpFqdhaVkZdbz69XT6TUSSRoBOy5TQQBZvyoIHiUTJiSlsDZtyVsRqjaI09SNp+D2evkE563m0TiNQIKJ7lVKYkSLv6ykD90jIDNCK25MinqroLhjwqkXAfZr8oGrFmfCGy/VgIRQsdIhIyRBwBc/CBuvkDlLonGbBj3pkDOp7I2zCsGKrZLXPpGIngkjHlVyagX+lpCHSWgr4fSjRKZz/3+xGzpllCocZAfr1iBzmIJz+i+71rTWQlTu0zIUuTTGpJdcuROdldB+HgB10CBJ7TBbGzu4IZQPx4qrGFDcye3hfnzQnz/jkBU+BRCPCez0yhi18Cl7ySaz0DsHFkn19qeT0dXCdHh01CpNGTddIds3Jo0gLPbNnJ+5xYm33wny17/gJaaKpory/AdOQZ1QiJotQ4SBnIc0Z4vPqbk1HEARl55DemTpiJJEnabFYVSxc9P3I+uo50xi68nafR4XNw9+PD6hWTdfAd3fv0LLlp3vnvwTtrramgoLSYxcyy5+3bS3Sxnv6qdnWmpLMds0NNaXYl3UAjD513F2a0bsJpNtNfVET1oMGVnTxGdMZSUcZNoKitm01uvICgEbn7/Syxmefq4sbSYAeMmUXD0IGe3bkChVBI3XC7FWgx6uluauXhgD0OumEtTeSlJo8bRabVxR34VQc5q3kkMRxAEzu/cwom18kW7uaIcv4hI/CJkgmPS9aDraEdAIG3SNLzjEtnlHsCJTh2ZXnJl6+KBvZxc/yvObm7c/c2vvzt2etpb8QuPws3b20Hwdrd28VxZPUoBTif44e/rh9r5v24trm1sZ1NzJ8/GhRD3dyvyT9HeWdyvHflHMJnbae8sdlSf/xNYt24d48aNIzAw8D/2Gv+If5mItbS0sGHDBqKiovotHzx4MJs2beKtt95i2bJlXLx48a/ex78cPq5OLBgcRlO3iUHhXn+6nkatZNGwcFZlVxPr70aMv/wl/uJwOZfqu1l7tpbUUE+uHhpOVbuBZZl/fKdzOYaosLGHVp0ZP60ztb35lKNi/XBSKThT2c6j63JZMCSMOyfEER+gxS5K1LTLxCExyJ39D05Ao1bgoVHzyvw0duc3cWVGKN69Vglerk4MCvNi+fhYovzcHGakSUHuPDI9iZvHRPPlkQre31vC8vGx/HqmhoLGHoZ1GhnQG5kkilDeOxE4MtqHIyWt3PPLed67ZhAbztex61ITOpON28fHYLTY0WpU3PzdGdJCPZk2IIgPF2fQ3G0mwN0Zm110VBuTgz2ID9BS0aZHlCTsokR5qw6LXcRotTN7YAg6k5WUEA9UCgGjVSZS56o6CPVyYeNdo9lX2MT9v+ZQ2NjDc3MGMLo3aH1AiCeRvq692rsa3tlTzNOzUsiM8SWvrpMfTsgCp0XDI6hqM1DQIMdSWWwijd0mrHY7x0rbAFnLplEryYz1JcbfDZtdcjjmV7XpeXd3EQDBnhre2VPMI9MSWTIiArsoEe7tyspT1eTUdvH8lnwifFzZtmIs687Vsu5cHbF+bmQlBTIkso4YPzdsosh135ySK3s3DWfpyEhe3VHAzkuNDImUj0uTVUQQBEytApe+k3ggcxjapQYGR3rh6+7M+AR/Aj2cOV7ayrUjIylu7uHzQ+UAvLtwIPEBWqanBvVquZTkF/VgVMqpDoJCIPdzmRw1X5AQrXKlK+MeyPlEFsBbeiSc3AWK10rUn5QY8oCsJWvJk2iU5x9w8Qe1VmDk/8feX0a5cWbv+vBVJWxmZibbbWZmjAOGMDMn4zDDhJl5QhOOE9uxY8cUM7O73e1mZlKLoer98Mhqd5zMnPM7M+d/3szstbzaLZWqpGrp0a69733dD0uUfKnSVaYSO1LGEAxdpSqqByxNEkNvE6J/XSCsXKgQWQiTX9Iw+Bao+1XFbQWnWSQ/KDDwGpneesGX0Bj7V5JcFjFMoA+CuDFnfuZMtSobrlXQB8PsT2W0Ronhy2SG3qHitsCx9xViR0rkXyphDO9zBDj0mkLFCsEm0wdJbL1L7GPBcpnZUSHMjhIXZRF6sXQWm8XFgOxtYRx6XcHSKEC8cz6XURU4+a1K635B7wc4XPQOTpcZrdaftKQZaPV6UgYOBqB093Z6WluoPLSf1MHD2PjBW7RWVWDu7GDs4ov6vcbeznbMnZ2c2L4ZgKFzFxIWJ5LCrx6+m9aaSpY+8gx6/wCknm6ObVpHT0szIdExuJ0OGk+eoGDSNNa+9QqSJJE7bhJDvTZK+1Z+j8NqYfCseeSMmcCu777CZbeLSUhApzfgHxJKT2szdcXHmH3DbUSnZvDpPbdyZP0aFj3wJDo/P1RFVJQTsvNor6mi4cRxSnZsYcMHbxIQGk7ywEHMuv42xi66kN3Lv8JuNpM2ZASRSSnMu/Uu1r39Cpu6zGwOFzq5W4O10NpEyc5tOKwWYjKyaak4SUtlOXazme7mJqLTMxh51nnUFonp9a0J2bxU2cTXvTUcGCssx1IGDSY6NYPkgULMv/v7r6g6cpBZ199GeHwCRzeuo72uGkXxoPMmvoVB/gwI9GNQVRFfvv0g8Tn5XPD4c2e++X4TL1W3UGlzkBNg5MGMeBrsTtqcbgYH+//Tx/4nhcPR/S/d7n8SDQ0N7Ny5k9dff/3fdozfi//lROyLL75Aln+/HGg0GnnwwQeZNWvW797//1rIssSLS84cGf+9eH5dKT8cauBYQw9/u0II9+6encuKQw1cMS4VgDEZEXx/w9g/3MebFw3l5i8O8t2BemwuD29eOJReuxCU67TinG4qaaWizcKPhxq4cXImF45KISxAz4B4sfC3mOxc9OFuwv31fHbVKJLC/RmYEMK817axcEgC98zO5emfT3CothtJknj63IFcPzmDz3bVEBGox6OoLB2RzC/FLQzxJp8Xj0rGTydz1fg0PIrK/EFxXD42leggIwdru5g3KI5z3tpBt9XFvqpOrhiXRm2nlVB/PTdOyiTEX8eKww00dNtoNztQFJX5g+J58ZdSZr2yjcXDE3nqnIHYXB7WFTVzw+QMUQlqMgm0xXVjKGsxExNswOmd8NR7z8eA+GCON5po7Lbx6a5qHllZxJ3Ts7hsTCpZMYFEBhrotbtY/M4uFFVlUnYUI1LDGZkWxraydgxaiUs/2kO72YkETMuL5obJmaw93kxZi5nKNgu3TMsCwGR3MasgBoNWgyRJlDSbCPbTMjgpFJdHoardQmSgnkXv7EJRIUCvoa7Lxtu/VrBwcDy5scFoZImzChOYnhfD3/fU8tL6k1S1W7C5PIzPjCQ9MoA2swODVkOQUYtWI2HUygxJCqOuy0paZAATs6PYVtbOhhMtzB4Qx/1z8302SVovZi4pIJDBuQHc+uUhPIpomd6//BjHG03Ud1lZMjyJS0an4FZU5hfGMz06AXN933txR0sbLww8SUSgnvOjp5I+V6GnSsUvTKLtsKguav1kbO0K1haoWKGSd7FEzXqV3hpo2qkSNUgiNBNiR4pkrfxHBa1Bwj9OpatEVNNyzlfRBwuSvaVJof24StxIiYyzJKrXKqgKWEXBhcYdgp4fmChachNfBEenaI3GjpSIG6Xi/5uL0+4yfDiMln0qbotK9NC+ZM3cqOJxCH2c6u57nKyRKFuuUPKFSv0WlTmfa8i9oO9xXSdVVEWAXePHikEAfYjQnoHQxWn0cGV8JB/Ut7O928z+HgsjQwNxmVXKl4tz2HYEEiZImN0e3hpdT8o4PYtzBCYhIXYsbZ1FRIblnbFWzLj6Jsr27mTwzHli25x8OhvqiUnP6rfdkfVr2PDBW+SOm8SAKTORZIlJF19J6a7tGAOD6Gioxe1w0NPawphFF7Dr2y9IyM2nPSiE0ecupXjbr7gcDt+0IKrKiIWLqT5ykIzho5h86dWU7d3FyIWLAfALDqaj3kP53l2gqnQ01DHnlmV889i9FP26nuxRYwkMj8Dea8JptaIzGtEbDJi7OinZuZWhc8/C1msib/xkmivKUFUVl9POiW2/EpeZw5DZC6g+chCnzUpPSyMANUcOUnlwH8qhA9z+5NvE+xn45cllmDvaGbPoQqKSUxh93gXUFx/DLyiEQ2t/Ys8PXxMxbDSexjq6mxoo3rqRSQuW8E1zJ3O9bLj22mq2ffkJo85ZTPZoIXg8+PNKbL0mKg/sITz+XAZNm01PazOxI8f5znm8Uc+GETkU2xr4GXA7z3Rg+b24Pz2OVW3dXBIfgUtRmbG/lE6Xh28LM5gQHvTPd/AfEgZD6L90u/9JLF++nIiICCZPnvxvO8bvxf9yIvZHSdjpMWLEiP+jJ/N/O/ZVd2KyuZiW98clyBn5Meyr7vSZdb/4SynnDEnsR8//Z6GRJYanhrG+uMXX5rxtWhZ+Og27qzooauzhmgnpyJLE1Lxoeu2Ccj89L4YX1pWSGhlAVnQgdZ026jptzHx5K5uWTWJnRTuNPXZ+KWrmntm5XDYmFY1Uw6Jh4qr4x0MNFDWaKGo04afTcuGoZLbc1TfD/8IvpbSYHGwuaeVwXTc/HW2iqcfOgPhgLh6dgk4j8+LiQi7/2z4+31PLouFJNPfYOVTbTX58MDdNyWR2QSx3zcphWEqYD0J7irH1w8EG9lZ1Mi4jki/21jI4KZSzCuN8lj+BBi0pEQEMe2I9HRYnbo/KZWNTAWHuTaOJdrMDk82NqsIvxa0c805wXjw6hRaTnZJm0eY82WLms901fHjZCC4eLSyI2s1OdDIMSwnnnYuHodPIrDnaKLRmO6sJMup4/KdiLh2TgsOtsK6oBZPNxa8n2/ilqIWLRglMxZpjzdw9K4deu9DtBRu1jE6PICbEyBd7aqlsszBnQCwPrTjOomGJPLeokL/vqaHF5GBdUTMBei2V7RZqO62cPbiDX0uF2WJBfAgN3TaWzczxeZbOGRBLsFHLBSOTfbZIANmLZOLHioSkrM3CuiKRxZS3mn2ifq0suGWPzS+garWKqVRixwMKjm4hWE+aKnP+yCQ6rU7yYoOZ8dIWIoL0fPbqKHQamcE3KUgaoR1LnSPRsE0lbrTY97A7ZRp3qGQshI03eHBaYPhfJFoPqRR/AqAy9S2J1NkQkiESHhDTmccPSZz4TKVuk8qsv2mIGS4x9kkIiIXt9/WNjHvssOo8hfhxgoEGULNe4ei7KgVXSIRlQscJlbS5EpGDYMBVEpZmQfOXdQrnrJaRdV646iaxz/BcfOR+t02ls0QkkA3b+rAap8foh4W9U+JkIeif/bGoRJZ+Ldqjm24W52jWl3oWxYRh9SgUBAlsjS5QYujtkhhq8Mqatnb1srxFtFuuS48iVKclL+t8gpq2c+TEh+Rlnk9EWI7v+FEpacIv0RtTr7iOqVdcd8bztJoEB9Bu7uW8++8Sr/nEcX565RkkWWbJI09j7+0lc8RoVr38DJ2N9YTGxXPhX19EVVV+fOFJVEUhKX8gc268g57WFmqOHqR46yaqjxwkPCEJjUaLX1AwB1b/SNPJEoKjoskZO4Efnn0MVVGYe8syIuKT6Giow9TWSvrQESx99Bl0BiOBYeHkT5pGxf49gDAWn3vLX9BodV4qfiLHNv1CXbGQiHTU1/m0cqeqVJkjxjBw2izaa2soqDpK4Yw5fBUVg7W7m7qiI9SfKCIyKZXCGXOQZJnmSjGh/avZSfqUsxhee4JB0+cQEuTPtlF9Se/RjeuoPLiP3o52XyI287pbqSs+RurEaaxp62ZyTBxb5l3CF02dPFnfxtWJfSDY/IlTiUhMJiTmfw0/MT86lPnRoYDAV4RoNfS6FZ911n9DRHhoNkZD2D9sTxoN4T6z+n91KIrC8uXLOfvss/8QXP/viv8Yi6PTQaggdGIXvLcbt6Ly/Q1j/5Ap5lZULh+byuJhSTz+UzFrjjVT1W71kddB2N90W11MyY2mrdfBG5vKmJoX04/SX9lmwa2olLUIP0RZllh/ooUDNV1EBxl4blEhy2bl8MG2Ss59ayc3Ts5gQEIIH2yvAqDosVksm5nDC7+U0m0T05rbytq5clwa5w4VidfZQxI4e0ifXiUjMpDdlZ1IkgCPfrO/jvmD4vD3tlUmZUex4UQr+fHBpEUFUt5mxuVW+GRXDc0mO+9eMpzEMH/azQ5cHpWadgvnj0jmp6NiwrDD7ODhFUWsPtbEc+cNYnR6BF0WJz8fb/adu+YeO/nxwei1MhVtZg7XdZMS4e/T5XkUlR6bSHBsXmH8u1sq2FneziVjUvjLzBycHoURaeG4PAr3LT+G0buAZUYHcdX4NH460oC/QcfQ5FAu/lAs/KtuHkdLj53vDtbTY3ej08iUtfQSH+bHgdpuSppMvLOlnBNNJr7ZV0tapGg7j0wLx+72EGTUYnd5fGJ9SZJYfesELv1wDw3ddpaODOH6SRnkPbwWVYVgPy2KChVtFnqsLiRJQpYgOsjA+MxIrhyXSnmbmdQIf26akkFsiB87K9pp6LaxrqiZ7w7UY/Y6M7gUlaTWMM4fmUzcKIk7vj5MZZuZy8am0lXp4rIxKTw4Lw9FVRmQEMJT5w7k6gnpZMeI11C9VuXgKyq6IJXgZHBZwD9GwmlS2b1MZpR/FoYbuilrNVPeJiZdNY16IgdJaAyw+VYP8WMlZn6goXqtwuG3FAZdJ5E8XUJFpbMUUGHHQ4KsH1EgmFqH31TR6mHo7TInPleo3aQy4i6ZmGGS8JScJBK3rcsUglKg4DKZpt2igjT1DYGFOP6Byumdh6bdYO+Apl0qRR+r2NuhYbuK1gDD75ZxmQWVXwwPqDh6FEY9KBM/TqLtqIqshw03eBh1v8yxDxQatkLuhRIzP/z9L0H/aAlJVjnwksqga4XXZe0GAJWESaIVqjGA0U/ijd8RXWcslPu1KrMOB3FHXSL+0zyE6vqW27rGrZh6a6gu303EiJwz9vOPwmmz4nY6GH/+pQyeNc93e0hMLEERUfiHhBKbkY1Go8HU3sa4pZcQGB7BoGmiY7H5k/fQ6vQ+n8j2uhqGzz+H4m2bKNmxhbD4RPb8IHRTWaPHUVd8HI/bRVL+QNIGDyNv/GTaa2tIyM2ns7GBttoq9q36nsGz5vm8FgEmXHAZo887n9cvXYyqKoTFJRCVkkpITCzVRw/hHxpGUGQ0W//+MYsefILw+ESQpH6A1Zi0TI5tXEdLZTmFM+aw5JGncNkd/PTqswA0lBax6eN3GTp3IZMvuYqfYtJZZ5W4Iz2OuQv7zs3pUThzLpbuLvIm9F2UZo4YTeaI0dxQVM0Prd1cGh9Bu1OUUk/9PD1Ox2P874RGktg4IheLx0OU/o+BsP+JIUky+VkX/u7U5KnIz7rg3ybU37lzJ42NjZx33nn/fON/cfxHJGLPrS3h/W2VPL+o0JeoBBq0pEcF0GlxER/6+wLKDrOD2746hKoK4vqS4YnUd1k5e3CCT//UbXWy9N3dOD0K314/hm1l7Xyyq4ZNpa2sv2MS722tpCA+mKggoROLDOozgL15aiZf7qnl8rF9V8DVHaKadKSum7MK45maG01ssJGl7+0iNtiP764fQ4ifjis+3kd9lw2NLPHdgTpeWCyuIp9YXcwNkzK5cFQy47Mi+fveWiTg013V7K7s5FBtF48sKMCo03DFuDRWHmnkvuXHWHf7RPIuH8EXe2pxeRTOGZLAJzuriQk2+myFajqt3DY9i12V7Xy8sxq3otBhEeX5TquT2g4rvQ4XAxNCqO2wkhrpzy3TMpmSE8PFo1N4dGURX++r5fVNFSSG+WN3KRyo6SInNoiqdgsTvDT/fdWd2N0KDpfANHgUFY+iMDknii13TfaZah+t72Z7eTstvU7mp0Xw4Lx8tp5sw+xwU9NhZXx2JN8cqKet10631cn817fhcKuMSA1jdkEsT60RYv3p+aIKNSU3ilkFcby3tZJum4sv99by5oVDKW3pZUhSKJIk8ZeZOTy+qpimbjtGnYazCuNZcbiRzKhA3rpoKMNTwvj2QB3NPXaC/bRMzIrC6VEobjKxu7KTdwOrfG3xKTlRZEUHMS4zgiXvCsHVuUMSKC+zEfBTBDtXKcxZJYZDFBWWfXsEYSOq8tnuGp8nqU4jkxMbxOG6bradbOOc9BSMkRqiCyVG3i/hcYLWKLwiu0XRgHmh4Tx33iDCAvQYe/SsvVFBkiBrkUT7MehtVPGPUTjxdxVzPex7VsVUpZJ/qcT4p2RcVpXa9Sqth6HwRhlZAxuuF7o+aytUrxOPa9qtUnCFzNwvROLTuEO0/lxmoe3KOBta9sGJz1XGPCYRkScTcprZQuosaNgK1jaIHS7RtFul9YC478g7CrHDJeZ+ocHaprJ6iTh+Vwk+TdyP8z24LNC8T/Wy1FQszSpum4rGAPueU7F3qox+WEbvrZwdekPF2QPBKcIGKnm6wGm07IV5X8tYmlSOf6iSNrcPInsqLjtWydbOXr4uzCDfEsDhpyCdMKaN6//lkRywlNYNO6nZP5P8d4QF1P9qHN+8nr0/focxMIhR5yzBabdhM5kIiY7h2rf+RuPJEkxtrRxcs4Ij69cw4cLLmXLZNb7HVx06gMthJ23IcDZ88CaW7i7qTxynvvgYs66/TZDoVYXezg6aTpZQOH02fsEh5I2fhMNqQaPTMXDaLIIjo8kdO4G6oqNkjeyTZmz/6jNKdm5h7s1/IT47j4LJ0+hoqKN8/y5Wv/Ycg6bPpnirKFlqDUbcTgcel5srXn7njNeaPKCQtCEjSMoXCZ4sazD4+7Pgjntpr63m5J6dqIpCa2U5e1d8R9rWTfxw5c2MTov7w/MXkZDEgjvuBaCjoY7O+joyR45BkiSSvUiJZKOehzLiOWSyMjY08A/39XtxyGRlbXsP1yRGEanXnlEE8NfI+P/BpP5/esRGD2PogJt+hyMWTn7WBf9WdMX48eMpLS39t+3/H8WfMhGzOt0YtRpfq+ywdzLxWEOPLxEz6jT8csck34fE6nTzzb46xmVGkhUj+vah/npm5ceyu6qDZ9eW0m528voFQ5n72jYeXlnET7eMJyJQT2qkP229DmKDjcwZEMv2sjbmDoxj5eFGXlp/Er1W5qdbxrOuqNlnIg0CZzDlNxObD8zNJyLAwKsby7jwgz3svX8aOyo6+GJvLUWNJp5fJL48H19YwKaSVo7W92Cyu9le3kZzj4O6ThsrjzQwIz+GoSlhDEkOJT0ykKggA3urOvl6Xx2H63r4+bYJdFqc2F0KrSYHbkXlkg/2UtrSy1PnDMRPr+WRlQeRJZiYFUVDl43vD9azaFgijd02YXYdFchdM3MpauohOzqIic9vxuFWWHPrBK7//AAHa7vZU9nFlBxRPXz0rAJOtvSys6KDhi4b72ytxOlWuGVqJtNyo9lT2cnNXxzijunZTMyOYorXjun9bZV8uL2KsRkRXDomlcdXFbNsVg6XfbSXLquLcRmRnFUYj04rMyM/hi/21vHetiomecX84QF6dBoJ7yAll4xOYUFhPF/tr6O2w4rF4eb5daXoNTJbBrfTbXMRaBAasQCDlqHJolqqKCqbSlrptrn4pbiZ69rSae4R02DlbWYcboWn1pzgvjm5jEgNY0JWFEvf28XR+h5unpqJy6OyeHgiJ5pM/HCogUvHpHDHjGy+2FMLQE5MIE/PLmT1xwoeJ8SOB3+DhjcuHMrJll72VXXS4rW5qumweidp+xb5O74+TFW7BWU63PZtn6boFM4iIl9i+F0SlW4TuzodLBkh4LX2ThV9kNciaB4oTpG87X5cTEamzhbVNFOVsEaKGy1hbYG4kRLaAHzH948WSVhHkcqIu0W1K+s8CVVRqd8KIekCHjvtLRn/GNDoJZKnyVT8qGBuAHunMAPfcL1CYAJMfE7GbZNQ3CrmBpj+toQky5T/qNB6UKVmLdSsVYkcoOCySBTeBE6TRJRX/lm9ViF6mCD3p86W0BrB3CS8OA0hgqlWs05U5LpKhEk5CLRFyz7hY6kPlMhZCuuvUYU+rlCi5Auo3aDSW6cy8fn+lbUjJhs2RaXM6mBYZABRhQLJEfgb1GJYeDrqtlR0BlFhw2yGinLIygb/fyziTikcSkx6pk/g/8UDf6GjoY7z7nsMndGPrx6+C53BSMogcb+t19Tv8bJGC5JEZEoqueMmUnlwP06bFY/bza+ffUjt8aPMvvF2dnzzOTu//TtBEZH0drRTunMrky+9mmMb1yFJMoXTZxMcFU3qoCFEpaT69n9y9zZ6WpqpOXqY+Ow8Zl1/G11NDWz/WtD0jQFBjFl0AaoKeeMn0VZTTUdDLTHpGQLV4Q27xcxXj9yNy+Fg2pXX93sNeqMf8dl5opWbnErywEK+/+vDdNXX4jqyFwry/+E5PBVfP3ovNlMPc27+C/kTpnBfehw3JkUR4q1eTvwfaLiWldZSZLbjVBQuiY9k3oGTpPgZWD0sC83/JS7V/z9HbPQwYqKG/F8l6/9/HX+6RGxnRTuXfbSXUWkRfH61EGq8uKSQrSfbmD8o/oztT32JvLulklc39oewamSJdy4ZxqMri/h4ZzXhAXosTjf1XVZcHuH9GB/qx7rbJ6KofTT25TcKgWdNh4WC+GAGJ4WyqaSVE029tJud3D69f4+7rtPKL8UtnDc0gVB/PZNzonjr13KCjFpkSWJCZiSPLMinuNHE/Ne38/jCAqblxTA1N4bNJa0cb+hhxZFGylvNTM+LZm9VJxOe28S62yfyxoVDcboV0iIDKEwM4Ya/H6THKmju4zIj+era0UQHGTDqNEQHGyhr7SUqyEBeXBB5ccHEhxh5cF4eU17cwtH6Ho7UddPW60QFYkOM1HZa+duOas4bmoC/XoOqQm2nhZzYIJLC/FkyvA98+POxJvZVdzIpK5IPt1ehkyXG5UTz3tZK3thcTna0qIztrGjn8bMKmPLiFlpMdm6dloVOI1GYFMqbm8s51tADEoxKi2BfdSdDkkO59rMDjEgN49GzCmg2OVg6Qgj/gwyiKgXCtqrd7MStqFz1yX5aTQ4f6iIp3I+cmCCfLivQoOWC93fz9bVjSA73Z+GbO7C7PLT2OtBIEq9fMIRLP9pLfZeNc4cmcN+cPM55awf1XTaqO6y8d8lwgv10/G1HFQ63SHZPDXRc+P5udlZ00Glx8sLiQpxu0f6MCDQgaUCjB49H5U7Lds5aHc0D8/L5dn8dOyo6eGh+PpeOSUEjyxys7WLxO7t4eelgksL9mTcwjpVHGhmfFcEfRcx0hdmP78KxU+Hzq0YRtjOctkMqU16RCIiT0BgkhtwqfBar16lE5EuMuEfml2s8yFqIHyeMvH+9XcEvCub+XQZvLuIfIxIxjVEicqD4B1D1s8L+51SMEbDgOw3heafZdA2QGHyLhM5fgGSbdqlYm8HWLhKYhIkw5jGZgDjVZ3GUOku0UK3NKoZwKPlSpWKFSvYSicIbxGLtcarse04FFUY9JKHzF4+NyJVoO6giySqOLomhd0jYOyH6NOpOWJYkXoe3eB2YKJI0SQOyTsXWruIfK5K738Y3gzMoMtuYHxWCXVGY/EpfolZvd+JQFDL8jfhHS8z7RkaSRbWSdduhugo6OmDqmbZHADQ3w+5dRBQUcPHTr/hudrucoKq4XS6CIqLQGgwYAgKISkknf+I0Mob1p4O7HDZQVWp6ejk6cQGXnH8F+t5udn77Bcc3/0Lxtk3MuPZmUgYMpnjrJmIzsnFYDhCemETGsJFUjRhNe30tb119IQOnzWLfyu8xBgVz0wdfYOnuIiw2gaiUNIbOFVT6mqOH+e6phwiOiubCJ18kNiMLVVU5vO4nTO1tHP7lJ+qLj9Pd1MiUy68FwOZR2NTaKRJElxu300GF1c76dhMXxIUTotPS7XLzcGULgzMGURAeyczrbqHiwF6GzTv7d09fu9PNWQfLCNDIrBiahb9GJio5hcaTpb52KOBLwv6ncW5MOE6lg5mRIVTbHHS5PdgsNuyKQsD/kMj/nxaSJP9bERX/r8WfLhGr77Lh8qg+wThAXIgfS0ck02lx0mUV5PTfRoifliCjlvGnEd9PxSML8rl2YrrP8Pub68Zgdrgp9E4fSpKE5rQ1udVk55YvD5EdE8TqWwVYsardzGe7asiLPfMK697lR9lR3kFVu5knzx7IkOQwdtw7lUCDFlmWeGTFcX441EBCqB8N3TZ+ONTARzuqyI8L4YPtlUQEGIgMFN8acwbEsbOiA7c3Ubzso7043Aprb5/InIFxLL9xLImnGZcPTQ7j3u/FmPe7Fw/jQK0oB0cHGfn5NvHcv9pbS0q4PxOzxfTfK+cPxu7yMKsgllu/PMT64hZ67S42LZuMyy3AscVNJs4qjGPLyTaSwv3ZUtrGTV8cRFGhpdeB3a2glSUeWZDP0vd2YXF4uHt2Dp/vruGrfXU43QJr4VFVRqWFc8uTc5AkieEpLTzzcwkbT7QyISuSdy8ZxkHvc24xOVj4xg4eXziAWQWx7KroYFR6ODPzY5j96jZ6rC5ePX8wr20so6LNglEnE2jQUtpsYtvdUylvNXPVJ/uYlhvN/ppO7C6Fky29+Ok11HZakRBC/chAA2MyIokNNtLcY2fxsCTu+u4IDV02zhmSQGywkaFPrmdGXgx3z87hvuXH+Wx3DXfOyCYsQM/ZQxJo63Uwb5BY/C8fl8bQlDAyogLRG4QJ9Wu/lNNywMKRuh6WH6xne3k7ABpJtCKvGJfGMz+X4HArbC1rQ1EFyf+lJYUMSxE08+33e+gogkkvyr4WWsc+iTgpgE6jjfhQI0e+EdiIloNga1OpWqMw6gGRzKiqSD5URcXWKqph+19QyTlf3Ke4YN9zCt2VEDUQwnJg+N19BtkAikfFGA6yHkLP9HcHIOtcGafJi70YLfYRECPhNEFvMfTWqux6VGXwzQpZ58ocfkOlao1K8nSJUQ/IHHhZAQQm49Qx249B+nwBoo0e3Pd8Bl4jEzNcYcudKhUrhZn4KfunU3HgZQVTlZiUHHSdhNYo+SpfRX9TaDssEByB8WcmYtkBRrIDjFx6tJKNnSY+GZjO9IhgulxuJu8twa4obByRS06A0Zcc4nBAQiI0NcIpl5K6OqivgyFD+7hhJ0uhpVmc/Ky+i7kLHn+ehhNFZAwdgSTLXP/Opyx/5jF2ffcFQ+Ys8NHjVUVBkmUufOIFulubuc6i40BVMx0uN09kJTL96hvQ+/lRdfgA+1Z+z+hzl1I4Yy7bvviY3HETmXfr3QAsXPYgr1++BKfNiiEgkIjEZF91rmjLRioP7cM/RLTy17//hg95gQpxWUIPV7JjC5s/eR+NVsvws86jpaJc0P298Uh5A582drLkmnt4KCWaiMRkLjtwkv0mK01OF49lJrC6rYdvmrv4vqWLKxIiic/OIz77zEnUU1Fvd1JpcyABnS43/ho9ix96Co/bjVOSuam4hiCthqeyEnwav2qbg2Sj3vf7b8Ps9uBW1X76v5uSo7kpua/T8eGAVOIMun5J2PauXp6saOLapCjOjfljz+P/xn9G/OkSscXDEgn315Pzm4TH6nQz8+UtdFtdrLx5PPlebhbA+uIWHv/pBNFBBh6cf2ZJu9fhJjKwzzVgSHL/D06LyU50kMFXXdtd1cmeqk72VnfywLw8jDoNRY0mGrptNPbYsDk9+On7PpTjMiM5Vt/D6PQIrE43l3+0D0VVfV6XOyo6MNndnJsezqwBsfTaXfx0tInyVjOyJKHXSHx17Whq2q04FYV1t0/E6VGIDDCg08p4VGGvA/jabMWNJr49UMe4jAiWHxLU6UXDE7nq4/04PQrLbxzr2/ajHVXUdFqRJIkZr2zF4VL4+fYJSJLE8UbR9hiZGu6zf5qRH0Njj42fjzez8kgTAQYtLV4D6/gQI+9fOpzixh5e21TO2qJmNi+bjFtRCTbqOFrfw+bSNlp7HV4Mg8Ko9L4Kz7S8GJp67Dz443Hcisqid3YR6q9j3e0TeOKnYmo7reysaOfCUcm8t7WCzaVtVHdYaDU5cCkqQUYt1e2C4TY+I5INJa3sqerE6VY4XNdNTYeV2k4rLy0u5J7lx3j65xI2/2Uyf7t8BCa7i9u+OozJ7mZ9cTOH6rrxKCoqYihBRfDe3tlSgaoKt4OZ+bEsP9iAn07LrV8d4qJRySwZnsQSr6flqTDb3cx8eStLRyRx67Qsbl6YTkyCjmn5MTy/tgSXRyU7OpCLRvcJxF9ZOpjDdd2cPTiBpe/toqjRxJqDzeRowghKkmg/KoT6PZWqLxE7/Arc2D6WvMsgLVKD7i7oOK6SOlPi1zsVnCZoPy5alXiEnZAky0x7S2bjjSJBsbXCzA9ldIEqa8734h7KxXNKmiJR+o2wBRpyq0TVapW2IzDuSYm4MTIN21V2P6GQcZZEzvmiEqb1k9h8q4KpBkY/LJE2RySCPy31YGsVk4+o0O09RoC3sH2q3TfkVonUWRCe4zXm/kTlxGcqcWNh0ovic9a0R+XQqwpZ50rEjZXQBaoYwrxtwd9E2hyJ6rXCgPy3kTJTGKSb62Hv0wqzP/39CkeVzYFHhVqbg1aHi4MmC3pZwq1K6E7/Ui8ugm1boWAAnLcY9u8DgwG2bwOLRSRhQ4aKbQsHiyQsu39Ffffyrzm87ieGLziXSRdficE/gPQhw+lqaiC5QPRpu5ub+PsDdxIUGcVFf32JwPAIZte00ORwMTlcrIUarY7AsHC6Gus5tHYVo89disclBmk87v6C9SUPP0VHfS154ycz6myBuHBYrXS3NBGdlsGAydOp2L+HoxvWAnDJc68TFNF3kRubkSXE+6npjF96CeOXXoLZ7WHmfqHRmVZ9nIu2biDy3It8U6STw4OptDkY59VszYwMZn5nCAU2aHx0FwGj4gidm8YfxeBgf94vSMVPI5No7NPqarRaDnWZ+d473XpDUhQpfgaerWzi5ZoWrk6M5Mnf2F8B9LjcjNsjkutNI3J8+rLfxjwvNuP0+K65i8O9Vj5rbP9vIvbf+PMlYpIkMf20icbTQ3xp4qOxn4oQPx1aWfKBO0+P4w09nPf2TpLC/fnl9ok+3dmpePvXCp5dW8IV41J5ZIGABX61txatRuKq8Wm8vOEk0/NimJ4Xw/WTMsiICuiXhAHcODmTGyeLKZyyll72VncCUNtpJS8umOzoQMpbzSSH+3PleKFL6rI4aTI5mJYXwD2zcwnx03H16v3sr+nikQX5XDYmlUdXFTEiJZwH5uWSEhHQ75hPrSlme3kHpU0mbvXytIYkhZIYJqpuz60t4a9nD8StqDw4L581x5q4cGQyPxxqQFVVnF4TboOX+3V6YquoKt1WYYYeZBRaq5TB/sSH+jEyLZykcH9WHmmkyIunuH5SBo3dNl5ZX8a8QXEMTgpFq5G45MO9AEzOiWZEap8/38WjU5ieF0Njt43z39tNmL+eXrubQG8ieGr68vpJGTg9ig/W+ux5AylvNTMiLYypudHMyo9hT1UnDrdCQ7eNhYPjuee7o3hUlfouKx5Fxep041IUpuRGU91uISncj2CjjpFp4QxNDqXZZCc9MpBPrxrJjrJ2nG6FslYxGXvthHQiAg18e/1Y7lt+jC/31tJrd5MU7k9Nh5U5A2J9yfvWMjFBufZ4M7dOy2JtUROPrCqiqNHEfXPz2FvVyclWM+/8WuHjn80siGVKbjRGnYbHzipg9dFmRv6UxdrXFUY/LBH/gJnueoXkaaGAgLOmL4D6zRIln0NPqcL4pzUkTRbPYdQDMi37BR5C1oMxAsJzxX2BCRLD75Jp3quSNk/CGCYBEmMeU+mpEswx1SMRliVI8k4TtB4SIntVgdYjKode9+AXDYpTsL/KfxAatDmfy76E6HQPSP9oYRiuMULhzZA2S9yXd5FM5kLVh6WoXKVy6DWVAVcK83CD1wjDENK3r6ZdKpYmqF6vkrVIZsH3YsBA0vxOVWuxTPbivt9r1ivIGkiaKqMPEcbpbjskTj7zsdZWlfIfVd6blE5dhp3pEcFM3VdKicXOY5nxnB0dRozhtGm5XoFsoLtbJGUnS0ULMr9AtCqTUwRlWZYhJAQmTT7jmIo3SVI8fSiQUecsYdQ5S3y/m9pbsZt7cTnsuJ1OKg/uZUlkNLd4AaenYuDUWZi7OkkeMAgQ3oqpg4cSmZzab7uY9MwzJgeLt27k2MZ16P38GTJ7AbZeE1kjxxKRlEJ0Sv8EKSw2nitfebffbQ0OF0d7vc4XxUeIb6ljSHURIBATy9JiWZbWh4yI0uv4YEAaPWur6XV4cFR2n3FufhsLvBgJEBWyjxvaWRQbxsiQAK5LiiJEqyHFm1D1es9nr1dcavUoaCXQe1FOTlXF4vHgUFRsSv/vlH8Wt6XEYJAllsaF//ON/xt/+vjTJWI/HKonyKA7Ixnz12tZd8dErA4PqZH9k5KRaeHsuX+azwj79Oi0OHG4FVpMdtyKiv43idjpXo0gph0P1nTh9qhUtJrZcKKVDcUtbPzLZO6d07/nvfZ4ExtPtLJsVg4xwUYUReXHww1My42mICGYO785wsz8GGzepOdgbRdvPLGei0cls3BIIpd9tJddFR1YHW6GpYYT4icW+GCjlpZeu48of9nYVFIjA7n9q0Psr+nio8tHkBkdxPbyDnZXdfK3K0dic3p45ucSbpmayR3fHGF3ZSeL3t5Jl83Fp1eO5JnzxML8yx0TufD9PSx6ZxdvXDiEbquYkpyR37dARgcZMGhl5g2MxeFWeebnEl49fzDnDRNXlZtLWxmVFs5lY1Ko67Jy59eHMehkvtxbx+G6LpbfOA6Lw82ErEiaeuwsfmcX105M5/65ebSbHXx3oJ6Pd1QTaNSyedkkrvh4H4ve2cXiYYkE6DUM9yZtyRH+pEUEoNfIBBp1DE4KZdYr2wAw2Vw8vaYEnVbGrSjYnB50GsHZWlvUTEFCCLdMzSQ1IsBXDf37nhrqOm1kx2jQSDJPnD2A3FiRgP5S1Myd3x5hYEIIAxNCONbQw0vrTzK/MB6b08PlY1IwO9ycNySBJe/swuL08PZFQ5kzULQnb5iUgU4jMTlH6NlqOqyoKlR1WIgJNjImI5LlB+s52dorYJhuhRkvb6Xd7GDFzeNIaAlj4uYQbFbv+7bXxUUbduBRVNZPnkSMK4D1Vyto/SH3fDj8Jphq+7/Xg1MkglP63t/JUyVxLKuKzl8iYbz411GsUvKFQs6SU7eJCwvFo2JrE6bd4bkSWedJKE4JUw20HlKxNIlJxWF/EcL5PX8VlkooMPkVGUc3BMT1HX/yKzI/LRGtwJhhki/xAvr9v7sMUAVjrGG7SCQTJ0oYT5PK5V8qUbdJTI22HFCJGSaGCPY+o2BrVxl8o8Sx91UiB0nkXtAnCu4uV9n7lPiSDc1Wqd2gUv0zBCbBgCvPFA8XfyLaplEntMx8WWSEMXodJy12Uv0M/ZMwgOEjoL1dtCHj4iAxCdLTKUpK421jJA8dPUpMWSlMnQ6Z/RMfu0fh6aomMuYs4sKpM/4hUiF5QCEL73qIgNBQGkqKWPniU2gNBm768Cu0ur7nZAwM7Ddhueb1F+ioq+Hsex5GFynabV83daKXJc6JCWPjR+/QUVfDkOtu52RiFnHZub4qnF9QMAvuvI//1RQlJ8DIO14kyLCYxZTGxzB8/h/7/bU5Xbxd28b8YeFkh+ghPYQel/sfarxOmG181yJsqp6vauKb5i6O9lr5ZnAmj2X2n6h4JCOBuZEhDA0OoNbmYPr+UkK0Wn4dmUOARkOUXseGETk4FJWcgN+fvP+92Ntt5rGKRi6Nj2RocMA/f8B/408ff6pE7GBtF3d8fQRJgp33TiUuxA+H24NeI2xZooOMqIEq935/lPouG69dMMRXBdtZ0cH2snbump3Trw05MTuKr68dzbGGHs55awf3zM5l4ml8sHvn5DIpJ4rhXg7ZAz8ew+5WmJITxY1TMqnvsvVje50ej68qprHHTmKYP7dNz+JEs4k3N1cAkBDmx4kmE91WJ2tvn8jB2i52VXTQaWlmy8k2JmZHMTErEoNWw4+HG1lxpJGSx2fz6a4a7v7+GDdOzuDeObl0mB2MSheJyfriFixOD4fruhmaHMrHO0UF0aOofHegnk921bDiSCNPnzuQkmYTG0+00mN3oT2tahDmr6fVZMfi9HDFx/sB6LA4sLk8PqH7p7tqcLgVum0u1hwTTLHDtd1MyI5ifXEL13y6nyCDlh9vGsu0l7YCcOOkDOJD/XzJWoBBy2dXjeLhFccpbzXTYhLTiY+sLGL10SYA5F5QgVA/PZIEcaFGrC4PX++r5YbJGXy0vYrP99SSGxvEm/PzmfPKNgwamWl50ZS3WVARCdCsgljy44Op7RBG5h3mPk6bXiszb1Ach2q7aTc7GZkWzpLhSZz79g4q2iy8e8kwJIR9laqKatyLSwr5y7dHmJIdxb7qTi56fw+Dk0P55jqh1cmPD6akqbffBYHZ6ebjndV8ta+ODXdO4qYpmWgkicm50TR222gxidbnqiNNXDshg5+ONlLTKbKu5h4H/OBP2yGIGqNgWdKBUmgg5Kgel0ch0KDFbQK3A/aE1uOK1zL2iXiQVXqq+nsvAiguleq1KuH5Eie/Van5RWXU/RLJ00Xiceh1YZ6temDwzSDJEqVfKxx9R/C8TNWQPE1UpDpLVYo/U0iaDAWXS8SNkQjLFscLTlUxhEDTHlEhy7+8//OQNRIFl0o07lJJmuqtfq1WOPyGyoCrJLIXiedTeINExABoPaCy8yGFlJkSI++T8ThUNt8u8BVTX5O9lk1C6waCun9qarJ8hWCWtR5Wyb0AHD0qkiSgs2HZIOvAL0KYf9duUEkY3/c824+plH6tkLNUJnGSMDhPntb3Wv4+KB1zUxOhlm6I7O9bi0aDz4TV44F58wF4taiala3d3NzUTIyqQmcH0D/RWt9h4t06AQeumDAQWf7HQvDM4WJ4qaO+DkNAAGFxCWj+gXjc7XJRumsbqqKwv7SM20pbidJpKbaIz2KBUcvhX1aDqvLT+s38kpjLvVct48JUcVFm9yjM3H+SDpebdcOz+7UDT4VLUSmx2CgI9EOWJM4+1aaLCSMpf+A/fD1v1bbydl0bW7pMrBmVzYQ9JbSVuFg7PKdfYtTkcBKh06KXZR4tb2RLVy+tThcLokI50GP1HfPb5k5cisqF8RFY3B5m7j+JxaPwy/BsutweTG4Fh+LC7lEJ8J62jNO8I01uD00O1xlJ2d5uM5U2B0tiw5Elie9aujhgsqLSfkZFzOZR+KG1i3Ghgb7K3H/jzx9/qkQsJdyfrOhAgv10hPnrOd7Qw+J3dpEdG8SKm8Qko8nm5qt9whvlQE2XD8z66MoiOixOUiMDGJkWzqojjVwzMZ2EUD9GpUfw2qYyihpN/Hi4oV8iptfK/cCt5wxJxOGq5dqJ6ZhsLj65ciRRgQae/vkEGknirlk5vnbUDZMz+KW4hQWFoiqSHRPE0uFJKKrKbdOyCDRoGZcZSYifjik50VS0mhmcFMJ9c3K5+MM92F0Kr54/GEkSlHaDTkNDtw2PorKxpJXnzhvEgNMMy++Zncs3++vIjg4k0KglQK8hKtiAxeFmel4MG060MCFLJJVP/lRMbIiRGyZncOmHe7l/bh5Xjk/DqNPw9sXDeOKnYspazczIj2FcRgT3Lz/GtRPTGZAQQrV3UCIi0MCjC/I5VNfNFR/vZe7AeK6blI5RK5MQ5kdGdBC3TcvC4nDz/aF6WkwOUMW06alW6uVjU9l4ohWb04OqqgxPCWPd8WYGJoZw54xsEsP8+ezqkXRanGw80YoqBuUAMbiwo7yDi0YnIwFI4u/11LkDcXoUdld2cNJL5gd4dm0JLSYHyeH+3DQ5g8o2Mf2p08g88MMxylrNXDcpndzYIB+2orTZxEvry9BrJP569gCm5UcjSxK1HVY+3FFNZJCwbzp9eOTDOWPYeKuH5mckcl9RaTc7ueSDPfTa3d4pTg+7Ktp5cf1JPttdw+XjUtleLpLCqTnRZMUE+trbOo1Ecrg/gZcKzdaBgnqe21FM0gk/tt49GVUVSS3BkPDXXu768ThfrYTVF4VQfLsfskZl7hcyfpGSD4VRsULl8Jsq/jGidYgKZuE6Q8N2FX0gBKeJluN30xUGXS/RLa4f0PqJluYpsnzNLyrtR8Ftgxnvydg7VdZd6cEvAsY/I9NxXGit3FbhWZl3cf9kLGOhTMbCvt/bjwoCf9sRlexF4jZdoETaHAlbuxDtB3gH4Bwm6Crte/7T35Wxd+JLPA2hEsOWSdjaIGOhaK1GDgBbu8rayxUkhE/l9Hf7kpWIAvH6Tn4DscOFrVLpVwqNOwFVYeB1MsOXyb6JUQCt00HomlWixXjW2aLydXpMmy7akcnJvpsui4+gw+mmNWMyuXYTpJ856TA2NJBp4cFk+BsI+N+gtEckJnHTB18i/RO3FK1Ox8JlD9DZ2IApu4C249V0uzwMCvQTOqvAAObceAcdDXXUDxiBpqO3XxJi8ShU2Ry4VJUmh+t3E7FlpXV83dzJbSkx3Jf+x+yv0+Orpg4OmqzMjgxmc2cvS2LDcSsqnS43NkXF5PZg9SjU2h1UWB1cfbyasaGBfD8kk3NiQml0OJkZEUxBoB87Rgtxf4XVzi0nRIl4QJAfkTot1Xah82txuigM8mflkEwCtRqfz+hvY+HBMk5Y7Hw4INWnC3MpKkuOVGBXVAI1GuZHh/qE/Of9jjbstZoWXq5pYUiQPz8P//cQ5P8b/+/FnyoRiwg0sP7OSb7f67ts2FweKtvMeBQVjSwR4q/j2fMGUt9l87WBAG6aksmvJ9uYNzCOW786xOG6btyKwp0zcvh4ZzWLhyWRGRXIwsHxvLpBaJkyo88E/V01Po2rxqfx2e4aHvrxODkxQbywuNBnxHyW15sQ4JIxqVwyJtX32C2lbUQFGbhxSgb+ei3XTcrg8r/t5Z0tFbx/6TCe/rnEa5ZtJSdGoB4GJISwcLCouCmKyg2TM0CFj3dVs/idXRx5ZKbPv3H9iRaON5r4cEc1r18whOU3jmXhmzuY9co2vr52NPMGxrGgMJ7jDSYsTg9NPXaq2624FZXDdd1AnyZu4eB4bp6ayayCWK75dD/bytpRgdcvGMJ1kzLYW9XJtRPSSQr3p2v9SdwKFDX2EBdsxN+gpardQmWbmUmnWnGdVraVtfHryTYe+PE4d87I5tZpWZxs6RVDDt02rv/8AFeOS8Ojqhyq7fYVEiQkNhS38NCKIiICdPzoxYe8t7WS4iYTqgrpUYFsXjaZ3RUdbC1r56zCePZXd/Hprhp+LW0jOyaIuBAjKRH+hPrpuPzjfXx65ShGpoXTaXHS2C3guZlRgdzx9WEsTg8F8cEsKEzgw+3V6DUSD/x4nN1V8TyxsMA7ZaWSHx9MmL+OUD8ddi+gtrcO3CaJliKFNYdbMbtdPqP1z68aSXSQkfAAA1pZIjrYgIyETiNxVmG8D9x75fg03txUjsujsquyg7EZEYx6wB+lIhjjAZnBSWHonBp2PaZgCFEYeZ9EQWEAg/aHYNRqiIswUuYnphk1BtGu236fQuJkiYwFQswePURi4DUSHUXgF63i7FXZ81cFjx2G3i7Ar6iiNTjkNomYYWCqUVGcks8+KHuxhMeOr0LUUwWmKmHs7TLD7idEEhYQDwkT/zljqfBGifBc4eN4KtqPq1SsVMlZIpF5tuSbgvSPEvBZt1VgOAAMIaC4VdqPQ0QepM/rS0aGLxPgVlO1iiIIL77q2ekh9HBg61ABieylMioK6QslNlwnzs+U17zJWP0ecDmEvstmg8C+KmiH083jFY2MCg3gwrT+GqpxYUGMCwvC4vHwer3MWIuDYSHe5drthtZWImJi+Hther/H9bQ2Yzebz2hT1tgcvFDdzNnRYUyLCEaSZbZ29vK3hnZuT42hMOj32WUZw0aR4WVovpOfQrxBx8jTAKf5E6cCMAF4XlHRnibdiNBr+XFIJl1uDyNCfr8Fd2rrDqeLB8vquTIhinT/f1wJuru0HqeqUhDox68jc3EqCq/UtPCX1BhGhQQyNCSARYfK2d5tZmlsGCrQ7dXRnR8XwflxEUzbV0Kx2c4Xg9KZEhFMvEHP2NBAnIpCmp+BIK2GbwszsSkKx3ptrGjt5q60WAz/IHmVfvMTQCdLjA4J5ITFRm6gSFJT/Aw8l5N0xuMBCgKN6CWJIf81BP+Pij9VIvbbmD0glg8vG05yuL+P8QWwdETyGdteOT6NK8eLxfCCkUm4FYWzChN4d0sF73rp+KtvncB9y4/y5d469lR18MU1o/vtw+H2YPBemcYGG5EliA81svFECykR/gxNDuPVDWVovR6OHkVl0Ts7RUXohrHc8uUhbC4PcaFGLhqVQnmrmUO13QBsKmkjzF9HZKCB6XkxXDAyGUVRKW4ycf1nB7h4dArvb6tkR3k7jy0sIMioJT0qEJ1Gwu7y8JdvjuBWVMZmRDBnQCzFTT2sO96M26PicHl4dGUROyo6KG4yMTknmglZkcLCJy6YcZmRzCqIYUd5O809Qkxrd3k4qzCeL/bWMtTblr3EO9F3/sgkFg9PJCncn4+2V/HqxjJGpIZR3mph9qvbcLg8uBWV6g4LV38i2publ00mKWwYV3+6DwCzQyyc9V3ieAadzLqiFkL9dUzKFoDZAu+AwN3fHeHHw6JkE2jUEeovNC8WrzWJxbsvVVVZ9t0RVBVSI/yZnhfDr6VthAXoWX6ogcQwP7bfM5Vxz2zC7lIobTYxMi0ci0NUqgDWFTVT1mom2Kjlntm5pEUG8OmVI3l0VRFtZidaWcJPr/Hp+vZVddFldWGyu+m1uzHqNMSPg7azmviyohp5g4ukMIETGZUezsi0CJ5dW8LWk218fd1oBiaEcsfXh3F5VGwuURU8xbT7+voxHKzp4r7lR/HXa/lh0lR6Pg5l1Tkz8dgk6reptOwHUAlbbCM8QcvKm/t6avO+Ee03rZ9ET4WC4hJtNo1OwFRP8b4Uj8rG61X0wSqps6CrDGKGSyRNEXyt+LECfBpVCPueUQGV+PES0YOFJVBPlcrxv6lMzJOJHgpD75Dwi5AwhEgkT5Vo3K0y5mEZfRC4LCq6gD9ABTSoHHlbIWG8hF9k3zbFnyi07BfJ0eiHvOgNReXgyyoOk8rIe8Vt3eUqzftULC0qlSsgeYbEqPslGrarHHhJIes8icqfhM5t1IMSoZkS/tFnPpcpr8r01olzABA1SCJqkAaPU8UYrmLvFEbhWNuh5EfxoFk3QHBSn3s48ENrF183d7KqTVxUvFPXyqOZCUyL6Bt8+bihg79WNpFg0HHglLB++zYoLYEBA2Fc39/T5bDz2T234bBaOP+x50jI7ZsA/6i+nW+buyhpbad7xwqCo6J5Z/hsdnSb8dfIvJCTxIYOE+PCAgn/A43V2TFhKKrKDUXVNDhcfDQgjcjTqkPa3+hnrR6FTH8D79a38XpNC6/mJZPqbbd5LC4kWeL5nCSuTozkr5VNbO7spcPp5v6MeH5s6WJJbLhPU3dXaR2r27qZHxWKU1WJ1WuZGSnO0/oOEy9VtyAB5RNEO9PLbmZESCAXxUWQ4W/kq6YOvmnu4rHMeMxuBRWwKmJLP43M8iH9k9exYYFY3B4ytgk/zMIg/35i/9/GiqFZNDtcZHmrgg12Jx/Ut/FARhwD/yDRPT2+be7kthO1XJsYxaNZvy9n+W/8OeNPnYgB/9DQG2Dt8Wa0cv9Jy6Ujkn3JmltRWFvU7GM+TcmJZuvJdmb+ZhhgV0UHl320l3GZEfztipHMyI/h0EMzQYLCx34B4IIRyTyzVtjqXDUujahgg69i09BtIzcuiLpOK35aDWuONTF3YBxPnD2AIIOWAzVdtJudxAQbCTJquee7o4T662jttbO2qJlOq5O2XkHIl5A4/PBMX/JZ0tzL6mNCV3XNhDRu/PtBAvQaLE4Po9LCefa8gaw53syB2i6GpYTz5Opi6jptDE4KZVxmJBeOSuazXdU8tKKI/LhgziqMZ+WRRh768Tif76lFluDQQzMJ8T6fGS9tFSLxOyfSZhZDDDqNTLfNiSwJ1Mb3B+q57avDBBq1GLUago066rqsbCtrR6eRuGR0Ms09dnZVionHlPAAwgP1XDI6les/P0B9l41dlR3MLuibPLxqfBp3zMjG5vRw498PACoPzc/jl6IW0iIDmJgdxaCEECxOD0lh/rSaumjstpEbG8S4jAgKvG3cT64cwQfbqnjip2JMdjc3Tcnks6tG0m118c1+0daOCTb6WtR/XXOCQ7XdzCqI4blFg0Qrc24eq4428vHOKq4an8a0vGgi/fVYOj1ct3w/dS4ryYP9OGdIKoqqolTpWbS1gLJIha+O19JldXG4rodhKeE8ND+fQYkhnD0kgd2VnTy2qhiAPfdPI8RPx/PrSvHTa2jdLtFbBye/BmuLSlieMMZu89iY88kWQv107Lh3Ku5WmbLlKqmzJcKyxLnLPFfCEAp1W4TY3NKiMv4pGY1eQvauEk4TyDqJaW/2VQVOh5r2VKmEZoMxFEq/UrC1SoSkS3SeEPfveUqh9SCMf0omLBvqt6jkXgRZi2XcFlh9voI+COZ8JqP169vv4TcUuspUQjOhcYdAaqTO7vvsZZ0ro3oUMhb0PcbWBpU/iZJp21yVuFESe54S+I1T5H29t7DTelDF0QXNe1Q8dpHQGUL7eGjd5So9lYJbJskS/jESikelq1QlLKfvmBq9xKy/yShuBCNMCYWofPA4ISCmXxIGMC8qhG1dvYwJCWR5SxdlVgdF5ZVMO9ErUBVBQYwJDSDZqGfO6doyvb7/T29IsgZDQABul5OnG7uI1DbwqFeAvjQunBMWG/Paqqk+chCA6+ctIVArc01iFM9UNvFufRvTI4L5fFD/Ktvp0eP28GNrNypwyGRhxm81b96wehQm7DlBp8uDLIk25YYOEzaPwv6aTp5c34lGLxP7l+EMCPJnaWw4rU4X58aE8cDJen7pMFFqsfv8PLd09tLp8lBrE6XKYSEBRHu9GkeGBDA6JMDXonUoCvenx+Kv0ZAf2MdMfLeujRMWO981d7F6WDYNDucfVgJPRa3d6ft/8u+0Vk+PIK2GoNNaxK/UtPBZo2ijrhia5Tsvnza0Myo08IyqV7HZhgIcN9v+4XH+G//68Hg8vP7666xcuZL29naio6M555xzuPHGG/vZU/274k+fiP2jKGk2cf3nwrhu87LJpP1mmnLryTaKm0ysv2OSr703syCWmQWxWJ1unl5zgoKEEM4qjKe6w4LTo3DSa+oNEOKtzCybmU1Vu5WLRidT32Xli7213PTFQX69azJPnD2AF9aW8vzaUl/1667vj+BR4ItrRvmqTGMzI+gwOyhvNfPGpnK+9iYELyweRI/VxSVjU8mOCWJzSQt6jdD7dFtdPLu2lNzYQMIDdN6pUPGmCvHTYXF62FPVyS/FLbg9KlvvmoLV6cFsdxMeoPe1PCvazKwragEgJtiA3Vvtsbs9ZEUHEh/qh1Enzo9Gknzi/g6zg0nZUYxOj2BocignW3qRJYkhyWE88VMxvXY35w5J4Gh9N3/bWc2FI5PRyTIajYS/XusDtw6ID+JEUy+GLg0qKmH+Opp67JS1mLntq7UsHpbImlsnkBcXRLfVxcyXt/oSQK0ss6eqE61GYmZBLCtuHs9DPx7n0o/2MiZDaEtqO63IksR7WytJjQjgwlHJSBI4PSqf7qpm4eB47v7+KHWdNm6Zmklxk4kLR/VVVZcMT8JsdxMX4seaY00sHJzAuMxIPtpRRY/NjdXpYWxGJNvv89C0R6UnS0NNmJWnzh3IOC9AOHl7LHU7ZfZ9a+flRwezr7qTpV4LohC3gcsGpWMMltBrZAYnhRIRoEdu1HHiYR0fDp7OoDvBWSHTfkBF8lMwRsjEjxYG154mN5T25QHFnyrU/CL4YvFjJVAhe4lMykwJvygVp0khIBaWz1LIvVBi4DUy+VdA0w7BCXPbVFwW+lWlAPY/Jwy7o4cIdIW5QWXOZzIj7pWQNXD8IwGP7SpTqd0osBN+UQIkm3epaAO67UJ7Vr1WofWwSkAslC0HVFF5S5oC8eP7HZa4MRJxY8QX4M5HPLQfhYnPyySMh4btUPqNStwoiCwASwPEjpIYca+Ev5e5mX+ZhF8UJIyXsDSLSlrLftUHgt3yF8FXU1VB9XfbVNZfq+C2wNQ3ZCIK+idjp4j8yFoovIQ/ijiDnk8GiqRnYngQ37d0cf2hHdAh4L2Mn8DQ4AD2jhGVrTq7k2O9VmaNHoNmwEB+capsOVnPX9JiCddp0ep0XP7CW6xvbueZqnaoa+OW5Bgi9FryA/34ZnAmHncKO9sbCImKYVB8NDPixUk40isGPzL+oC1o8yhcebwKt6ryYk4iHS4PU0+r3LU5XVRYHYz2ti1dikKX24NdUXggPY42p5slseFM2HMCvx4HqrcipSoqqqoyLyrUJ5rf1mVGBuyK4tv/2NAA6pqdzI8K4e60WLSSRN72Y6T7GVkzLIsfh/ZZet16opYVrd3clxZHgEamxuZkYngQj2TG821zJzLQ/A+SMKeicFNxLW5V5YnMBOINOgyydMa5KbPYWXKkggGBfnz2O8nr/KhQ9vZYWBTbpwX7W0M7T1Q0kmjUsX9Mf3TIXWlx5Af6MSHsf99W6c8WHlVld7eZVqebaL2W0aGB/1Z7qPfff58vv/ySZ599lszMTI4fP859991HUFAQl1566b/tuKfiT5WItfbasTg8ZyRUANu89PHThfVxwX5kRgeilSWfKfepUFWVaz7dj8OtEBGgZ/FvAJw/HWni3a2VaGWJBYPimJEfw/cH6hl9Gnz0VNw8tW+RWDgkgc/31NJrd9HQbSVQr6Xb5mJfdSdXjE2ly+rkUF0XDV12Tjb3MjZDfFFHBxnx02s43mhCliUuGiWSumXfHmXxsESfZ+U7Wyqp77Jh8Yrbv9xbi1EnY3cpdFldXDE+hSk5URQmhfLQiuMUN5r4pbiF/dVd1HdZmZwTTZfVhV4jkxTmh93l4Y1N5Wwvb2dkajjvXzocs8PNWeXtTMuNwU+vYXNJKwMeXcf8QfG8vHQwvy6bjEdVmffadtp6Hbx90VCKGk0MTgrF6PXafHnpYLaebKPT7GT5oQY+3VXNgPhgrC4PRmTqOq1sK28nwKBh1oA4ytssSBIseH0HWdGB7Ll/Gp/vrsGjqByp72F3ZQe3fHkQi9NNuzcJu2VqJvMHxRMWoGfJ8CS2nmxjWEoYX+8X5P5hKWHcPCWDD7ZXodPISBKEB4jk+d7ZeawraqHF5OCrvXXIkoQkCVulv8wUdHCr0823++sZlxnBYwsLWPzOLj7eCSNSw3luXQlNPXYSw/y4anwqIGx7UCUmxsZwzNHC7soOxmVGYnd5WBN7kuZ4DaWhHWzMHMNk79/T0qSy7goFWQtz/i4TEqBjRGoYa4uaKdplx9ZmRNkvE2zU0GRSWRNYzrqYMh6ePwjPx/HUblKY8V4wKxdPQu/UYtRpULyWSg4THHlLVI2ihwroa/QQiamvazj4qhC+m2pUrG2iyjr6YYnABIm1l3owN8Ckl2SiCvsWx/QFEs17VXIvlDCEQaJX85U6SyTpIRkqLftUeioEBBaEvyWAzk9i5gcSWj/QBUgcfkPB1TffQPpZkHm2sGD6vfA4VTR6idaDQnvWtFvFLd4G9Ml6JDxOlYZt4jXX/6oybJlMWJZE7gVivw3bBW+scqVK7oUC2xGRD23HICRVbCNpRDVNcYH2XyTlye9qI99PCwMGQHExR6LjWbT1KOfEhPn0RBceqaDM6uDJrASuToxi2Y7jtDrdxBp03JIiKvQ6o5GpSfFc6YQEo/4MYblGq2PCBZf1u82hKGzuNDElPIh7vGbZ9XYn+3sszIsKRSdL1NmdbO4Ugy0PZ8Sf0WpbdLiCUoudV3KTOD8ugm63hxi9lmSjgZtT+roHL+QksbWrF/+hwfSoCm5/Led6Re4rhmQyMMifGpsDBaiwOnyPa3S4UIH36tu4KjGKeIMOk1uh1GLHpaoYJAmPqvLbd8fcA2V0uNx8UJDK/OhQdnVbeLWmhS1dvWwa+fsWOh/Wt7GqrRuA3AAjjQ4Xt6XEEPibgYgis40mh4sulxuPqp6RKMQbdLyTn0LeaVW50SEBxBt0zIroqyS2OV20O93kBfqxOPa/XLHVbd08WNZAk8Pluy3OoOPJrITfheP+K+LQoUNMmzaNyZMnA5CYmMjq1as5evTov+V4v40/TSJmcQgyea/dzYqbxvWbFqxut3DpR3tRVVh/x0SfqXeIv44Np4n7Tw9Jklg4OJ5Dtd0kh/tz9Sf7GJcZyRXjhI5sfFYko9LCKUwSVh6/FLWwv6aLw3XdLJuVc8b+THYX+6o6GZ8VyadXjuSaT/cz55XtrL9zIk+dM5DsmECGp4bT1GPjoR+PU9NhY/2JFi4fl4bd5WHB69vptDiZOyCOi8ckMzYjkpfWn2TLyXZaevsWrMFJobSbxeTfxpIWBiQEM29gPBGBesL89Ww80UZxYw8DE0N4aclgAK78eC96jczAhBDWFwsd1n2zc7nmswPsrujgrlk5HG/oITJIj83l4bWN5XRbnUz3tn0P1nbh8qgUN5pQVZXXN5XTY3MR7q+ny+Lkp6NNrD7WxDlDEnh5qThmRlQgZrubHeXtFCaGcKS+hzc3lxOg1xDqr+dwfTfNPXb8dRouG5vK0hFJrDnaxKOrirG7PUQGGrhhcgYpEf58tbeOx38q9p2DxxcW4PIoXDomFZ1G5sbJmXy4rZIv99Uxb1Acb104lPe3VfLxzmpyYoKwu4Td0u57pxFo1HLZR3vx12tYNiub9UUtnDM0gRGpYfx0tIns2EBvglvHnsoOVhxpJDc2iK+uHU1BfDASEO4vEr/iRhP1XTbuW36Mb68fy4RnZYoP2rhvo9CcnGgSrgQv/lLKp4erCcjQEGTUUd1hJSHUj5u/OEiI1cg4JR/FA4ffUqjdAKsmNtNss3FiaDPTb0ojNBee/KkYp0fBWmiHTig9YGe4Wfg12ttVSu4xorgg/E2V4FQxSBCaKZIWe6fANZwuMx50rZggjBkucfgNwc/qLFEZ91cZl01UrVxWle4KCE4VqIkBV8rkLFXZdo+CrBPm4CBMxU01ED1EonGHSvVaMIRBzoVCxH/KqPv0FkD+5RLN+1TcFrHtkFtkZO3vJ2FFHysUf6Iy+GaJYXdI1G5Wad6v0n4E4sbAmEdkHD0qCZMEYDZ9nsyRdxQsjdC4U/W1ZwEyzhJU/d5aOPq2yrC/SIx/WoOqqrQeEK/FGC5akB6nQHRYmlTqt6mkzpL6QWT/l6OjHdasFiXLYcNgxky2dlrp9fSyq/u0CrtWgwZI8+qsrkmMYkOHidm/aQ8aNTJPZZ9Jgv+jqLY5Wdsu3ovlVjuDgvy5/FgVx802Hkh3cl1SFAdMFu5KiyFMq2VgkD+bOkx0uNy+xCFcp0ECwrz6skMmK1U2J/V2Fy5FReeVScyIDGFGZAifNrRzd1k90zqCOGmxe6ccnXhUWNchnsuppBDgtbwUnqps5JvmLh4oq6d+8mD+NiCVBKMegyzT5nQxfV8pBllmzbAsbkmOJj/AyOq2LnrdHmK9WrMJYYF819xJtF7LfSfreTgjHj+NyNRNbg86JJ6oEDKOhdGhmLwXLbu7zczYV8rYsEAey0zg8fJGVrV1c2tyNNMigs9IwlocLqbvL8WtqmwZmUumF3MxLCSANcOymX/wJPv3W/hhSCbT95XS4nTz3eAMxv+HV8NWt3Vz9fHqM9hzzQ4XVx+v5oPTJlL/lTFkyBC++eYbqqqqSEtLo6SkhAMHDnDvvff+y4/1e/GnScQkSbTFZIl+wnyA8EA9KeH+eFTVV/kqbe5FlvAlZb8Xzy0SYpL3t1ay4UQr+6q7fIlYfKgfX3u5UCAGA/ZUdTDY6z/521j2zRF+KW7h6vFpXD0h3eddppElX5vL7HAzy5tMzh0Yxw2TMrj6k/0cruui0+JEUeHaSem+Y1wzPo36TivT82MobzXzwA/HmOxlmu2t7uTz3bWE+Om4fGwqq440kh0TyLWf7UdVhdXRqSrf3qounB5F6LqKWzA73KhARasZp0chxE+HyS6YYKkRAXy0owqARcMSGZYaxt93C3DsrdOzaOi28fHOagA+vmI4AxNC+Xx3LauPNdFlEXoLu8vDT0ebeObnE7SbnZw3NIHSll7y4oI5e0gC5w1NRK+VOVTbzYrDjSx5Zxerb53AG17G2v1zxMj5axvL+OFgA+OzIjlU183lY1IZkRbOz8eaWH6ogYYuO/MGxbH4nZ2+1nJUoIEhyaHMHxTHnqpO6ruEh+SD8/KJCTFysLaLLScFm+me2bnkx4VQ3Gjizc3llDT3EuqvY3xWFPf/cAxZgiCjQIyE+gs/umMNPXy+p4arJ6TjdCvc8c1hksJF9cAYLqFm2XFvUNFrJG6dmsmWk22khIsKrsuj0myys7OinUGJoWwsaQXgqhfTSYvxZ9djCihwV3Qhrck9TO5NJnmGRK3dzAefi7/JxxeMIOGv0RR0xpB/uUT8GAE2FS1HMIZB6kyJiAKIKpT4+SIF1Q09lRDjnY5TVRVHDyRPE+fMP0ZF1gnSfc06lUkvSmIYYKvKji8U0udLDPuLeD+bG6CjSOzH2gpBSfDrHQq9tcJDMnGyRNsRFVsHlH4B1iZha+Q0qRx+SyE8BzLPkcleJPvwFH8UTrNK90nRYgXBL6vfInwmo4cKC6S0uTIeB/x8iYLihJkfyQTGS2j8RFKYeXb/tUIXIBGUCL21IJ22Olb8KOj9oZkw430NWj9RvQM48JIYFuitheHL/kkiZm4WfwTtaRV4f38ICACXC/bvh+YWrpk9lxCtxtfqW9HaxX6TlQidxifmvyUlxlcJ+228VN3Mtq5eXslN7sej+rC+DYtH4ZbkaF/imxNg5MmsBNyKyiBvpSs3wMgJi43sACMf1LfzeEUjaX56RocG8nZtK09UNKIgqj7jwoJ4LCOeMJ2WJO+x5keF8limiyx/oy8J6/e38448b+rs5aK4CKZHBDM7KoROl5tMfwP+GplJ4UHU2hwEazXEGnQ8lBGPxaMQptWQsfUo50SH8UKuWMPanW5anG40EtgVlZwAP6btL6XR4WL1sCxfBW98WBC/jswla9sxfu0yMz4skHlRoezpNrPosGgzXhwfwQmznUcy4gnRaigM9qfZ7uSpqmaqbQ6vz2U3dXYnARoNo06bIm1zuljT1sOEsEACNRqcioLfbyYta2wO6u0umhwuet0eDLIsPGT/L2iR/l8Oj6ryYFnD7wKAT10mPlTWwOzIkH95m/Laa6/FbDYzZ84cNBoNHo+HO+64g7POOutfepw/ij9NIuav17L+zknYXB4STjO1Bgg26vj1rim+32s7rMx7bRuSBL/eNYWEUD92lrcTFWT43cTs7CEJ7K3uICHU38da+m2EB+iJCTayrqiZ2QNiCfPXY3d5CPUXgpFThuHBRh2xIUY2L5uMikpcSN9z1UgSBp0Gu0vhtmlZZEUHsqO8HZvLw61TMxmcHNov0fvxSCPLDzXwS3EL101MZ09VJ0WNJswON6kR/gxKDGF8ZiRvbC7jzc0VDE0OZWZ+LCeaTIzJ6GuhPnPeQPZXdzExO4qXN5QRbNQyPT+GMRkRlDT3MiMvhop2M6sON7K/upMLRiZh0AqCfUVbL0gSWlkiMdSPxDB/JudE8WtpG5tOtDE5J4bxWRG8vAG2lLXR1GPjyz21vLapnIgAPTHBBmo7rUQGGthc2upjvF0xLo3pjlSMFRGUhTUiAf56DRoJ9td0MSAhhHVFLTT22IkL8ePXZZN5d0sFof7CVglAr5W45tN9KF6W1trbxnK4rothT25g7sBY9j0wnXPe2oHVZeOVjWW8sbmcFTeN4945uZjtblYcaeCtzRU43Arnj0hCliSm58UQH+pHRlQAGllm7oBYbp4qpq0CDBrve1Hje99MzYvGT5a58uN91HRY+GjxKD6fPJ6YIRqWfXeEI3XdPDgvj2MPz2LN8g4qtd0sGpZIt9XJrPwYCpNCyR/gz66KDnLvDsJTpiNhYjj7ngnj+GaVyj12Vg84ycLB8QQbdYzOjECfB5ZGSJ8npgsf+vE4u4Z28MbSIUjaINZeoqCqMOcziXFPynQUq/1E98feVSn9WiX3IomBV8v0VKooLmjcCRUrVC8wVaLuV7Fkth5RsXepGMMkPA4IToHYkRJBSWKfxnDorQejVwA/9A6ZLXcqaIwQP1Ycs36bSs06ldr1kHF232fs8JsK3eUqox6Qz9Ck7XpUofUA5F4Eox4QHpKVq0Q7N3uRTNwYsb2jWzx/xQOqF0dR/r1K816IHQnxY8S0ZtdJiBoETm8RSunrjGCMkEBS8YvkjIgZLtF1UiV66Jn39YumQ1D0DQQnwsib+m7384eLLoGyMti+FeLjMWpkLk3wHszjIberg2BUXzXst/HXikYOmKy8npdMglHP27Wt9HoU1neYuDrRi4ixOXigTPjKjg4J8GEoPKrqq0rZPQpGjcwb+Sk8lhnP6rYe4vRa/GSJCJ2WL5s60UkSI0MCaHW6yfA38qY3MZsfFcKTWYnoZYlwnZbrkqIpNtswuT0E/6atd1l8JN80dXLUbKPK5mB2lKjq2T0KzQ4XOklid7eZi49VEq3X8W5+KtV2B+8XpPJmbSsWj8Kenr5qYYPDxaAgPy6IDSfRqMfs9lBlc2BXVHrcnn7HDtJqWBobznGzleFesn2r041LVSmz2nkqO7GfkH5JbDgWjwebojLci+GYEh7E182dJBn7OyXce7Ke1W09LIkNY8/oPDyqSqPDxUsltVyREMmAIH9GhQbybkEKYVotMQY9G0fk0OP2/C5n7T8pdneb+7UjfxsqokW9u9vMuH9x5fDnn39m1apVvPjii2RmZnLixAmefvppn2j/3x1/mkQM6OcVWdJs4oNtVVw8OuWMKpVRJ4svdVnCqJXZWd7OhR/swV+v4cCDM87wgowKMnCotpv1xa0UJoVwzpAzy/6KovLh9io8isq2k228t62K2g4r314/hsKkUKbmRvHxzmo+31PDzVMziQ050xLDT69hwx2TsLs9xASL+z+7aiTHG3o43tCDn17L1Ny+K+Ax6RHkxgYxOj2CC0Yl09Jrx+5UWHW0kfGZUTy2sIDbvjpEaXMvWlmiMCmUT3ZWo6iwo7yDdUVFmO1uPrh8OPMHxVPe2ovJ7kKWBPIiJSIARYVDdd3cNyePrSfb2FvdRWywkacvHITd5WHR28Ku57XzB1PoPc9JYWIR++FwA/fNzSM9MpC8uGCCjVrCA/QkhfujlSUGJoRgdrg5VNuNW1EZnR6Ozelh4Km28qpghncEc254DLIs8fNtE3h0ZREfbq/iRJOJV5YOZmtZG5eMTuHFX07yya4aDtV18+ON43wVqfe3VSEBV45N49rP9vv23dxjJyrIwE+3jOd4Qw+XeFvXD684jqJCU4+dw3XdRAcZcHkUrp6QTqBBy9zXtuGn0/DNdaMZ9+xmTrb0MigphKm5MT5MxukDG9WfajjyjYtfh7ehoHLwUQl3VSAxt0jEBRs5Kgk/05b1DWRvS6QgNBL9Qpm7vz3G9op2ooONfLqrhkdWFlGYGMKKm8fTbnbgSvQgaQzs9jSx5ngzCwfHc0duAWvOU3xVm1Px4+EGeu1uPri3g1suCxS6LFVUkUMzJZ8huMuscuBlld5akWA5vazbvItkNAYVWatSu0GwwgAGXiNwD+Y6qF6rknuBRPmPog3pF6VSvVahuwLGPi6heiQMoWKIpP2oirVFVJxqN6vUbfEw5BaJ0EyRBPVUQmiGwGaULVdBERZJKTP6J2KiDagSENtH/c9ZKiFpFEy1qi8RM4RKTH5ForscAr0fXUuTaK/aWsW19p4nFZp2i5ZozAgxOZlzQd+xEidKnPWD7Ju0bD+mcvJbQdMX/874OJ8ZbgEB/u30pO+27OwzDL0B2LmDnOIiirKzkYcO/t1dv1PXhktV+bWzl4viI3gpN5k9PWYWewXwNo9CvEHPWdGhmN0eCk7TLVXbHHzaKKaTL0uI9DG/Xqpu4cOGdiaFBbF6WDYaCZ6pbGZosH+/Stwp795et4dRu4sJ0MjsHp3Pxg4TNxTXMNArQLcrCo9nJqCVJb5tEUmYQZZ4La9v8MWhqNgVBZckYfcoKKoQ/p9/pAKroqCXJK5NisKpqPzU2s3zVU3clRbHe3WtHO21keFn4YrEKAK1GlYOzaLV6e7X7is22zj/SAVmtwerovJNcye3pMSwIDqUK7si+aixncuPVXJk3ADv81E40GNleIg/95wGnC212rEpKvtMVs49Tdc1LDiA9e0mhgcH+DRld5bWsbqthzanm0+9ov6F0WGUWGy8XtPCxfER//FJGIhk+F+53f9OPPfcc1x77bXMmzcPgJycHBobG3n33Xf/m4j9n8Qbm8r56WgTrb0OPr1yZL/7ooONbL93KhIQZNQRFeTEX68hPtQP3e+YAIOg3vfau0gO7xsEWFfUzIrDDfxlZg4ZUYG8tKSQokYTcwbG8fTPJTg9Cl1W0Y4z6rRofIwpN346rc9A/L2tFXy7v56nzh3I8JQwPFaxsKmqyue7azha3+MDfl46JoVeu5u6LisjUsNZe/tE3/N58uyBDH1iPQ63QkKYHx0WBz957YA+u3IkE7KjMGg1FDX2kB0TyD3fi9bXK+tPcv2kDO7/4TiDk0K5Z3YuiWH+WJ1uFry+HbPDzTfXjfExvTqtTjaVtDAxK4qYYCM1HRbWHG9m/qB4LE43k3Mi+Wx3Db12Nx0WB9/ur2dYSigPzc9nxaFG7v7+KOcNTaCpx87+mi7GZ0Ywd2A8HWYHuys7OVDTxfDUcPIulljxZQcvlhTxXv1gBiWGMjE7ilVHG9lX3cmH26t8mrMFhXEcqu3i/JHJyN7hi1mvbMWglXl+0SB+PNzIyRYz6ZGBfHLlSLKjAylr6SUrJojxWVE8NC8PjSzxyEqhNRuXEUFssJEH5ZHIxf6Etcu0hvXSaRGsMI0scd7QRGoarQyICmVDcQsRgQayogLRaySaemzEhfjRXa5i9Gi5P2IohgkOIlfoaK4CQzC8efZQeqxOhv91A/G9ZrL844kokFl9gUJQRCj62E6GJIeier/oTHY3qqqy4PXtNPXY+eStkYywGSjaEcqlY1KxVAlNmKmWfpXbdy4exnevdDK0MQFLszDZVlXwi5A4+a2HjmKJIbdKtB5UqdskjjXyQUjyiu0jCiTGFEhUr1Wo3aDSU+XdvyyRf5lE8x6VxEli28RJ0LxP6Lr2PS+SqNBMiahClV8vV3CYYPIrEgWXS2gD4Mib4ngDrhDTiNZmofkadJ3gig26Fhw9wjvS1qZSu1HYB/lFCQZY4Q39mWI9Vapvn2E5CtGDRYJ2+HWVjiJw9Qr7JcUNoVmQJtZdLwRWRWuAo+8BKvTWSAR5cU7WVpUtyxQCYmDCMzIlXyk07QRVVRj3RP8LtwMvK7QdURn7mNzn3enohfJ1IvvMO+9315g/DKO4KNMZ/X4/iQNez0vmUK+Vs72cqwXRoT7m1SNlDbxb38ZLOUm8V5B6xmMz/I0sS43F6lEYelolaEiwP4YmiTCdhqn7Skn107N7dH6/x1ZY7ZwVHcrk8CBUFeYePIlLUVFOE6+7VZW36sRac25MGMNDAhgS5E+UXkuny809J+t9yIwgrYb1w3LQayS6XB4+GZjGkGB/riuqYX+PhaO9wpLIXyNzwmqntcHNstRYInRaUv30XJskqn/fNXfydl0rD6THA/BTazfPVjUxNjSQVqcbnSQRrtP4KlyKqpITaCBKr+03DfrAyQY+b+rgsvgInj0NwnpNYhRdLg8Tw/pDvW9MjuZGLzn/VFwUF0Gzw8XF8f0Hue4sqeOgyUq7081j/+WGEf0HjgX/0+3+d8Jut5/R6dJoNL61998df9pE7MKRybSaHD78w29DI0mYHW6CjDqyYoI48OAMdBoJreb3ycl/v3oULo/q0xoBvLz+JCXNvcQEGzl7cAI7yzu4ekIaQUYdK28eT3OPjcp2CzvL2xmbGcm2u6dQ0tzL4MfXMzwlnC+vFUDY5QcbKGs1s6G4hdVHm/h4ZzUPz8/nrMJ4H6h0RGoo4zOjCTBomf7SFpp67P1MowF+PNRAp8WJTiMxMTuS6CAjzy8aRLvZybjMSC76YDfHG0x8c90YEsP8GJYcSnFTLx/tqMbuVthb1Qnga+1qZZmIQD1uRSHUX8fS4Un8fLyZ7eUd7Krs5OBDM3hoQT5X/G0fa483U99tZem7u+kwO7lvTi5ZMYFoZIlXN5YBMDAhhD2V4hhNPXbOGZJARICeED8dK480EOT1qixrNfPe1goqPRZ+zm+ix+am06svW1AYT7vZwWOritlf04lHUTlY28X2snYcboUB8SFsKG7hru+OYLK78Sgq8aF+3DM7F5dHJKjjMyO5/vMDrC9u4ZEF+fjpNDz+0wkGJARz67RMXt9Yzo6KDpbfOJbm+/yxNAryvDxDDENMz4smNsSPa5WBHF2hcrIVbpIP4nArjM2I4L1tVRQ39fLWxUM5Mb2O/DFRnDM7Bq2fxN+VGlZHtpCdk02yHEp4oIEH5uVzvKGHmc+paLtl1l7qYao5g+cezyIoQWZ9sUCHVLVbuHf5MbSy0ELqNTKvbCijss1CU4+NYZPDkCSJpr0q1WtU0uaJhWVcZiSD7omg7aioKmn04vbiTxSKPgZQiSiAuFF97/eAaJGsbbjBg6NbYBqSp0k4TBCaLvkWrZQZEpnnSMjeCxhrs0h2WvZBzhKJ7nKV0Cz45UqvwTfg6BQJHICqCO2W0wSDb5Eo+btK43boLldQ3GKQYMorYlry8JsK9VtUOkthzCMSkkbytQqLP1PoOK4y+FaJ8DzoPAEHXlKZ86m43y/S21qMEnR/c4OY2HTbJfSBMOIeiQFXC4xFdzn0VKvsf0EhcgCMfVwjHlMn8BduG+QslkFRyF4sY24UfpxpcwRjrHajGDJoO6L2M1EXZUhA8xvj738WI0Ziz8qhVqvnVL2sy+VGK0mCW9Vr4mzZxdmZv/9lftJq7/fz92JUSABXF1VjUxSe9gr9F8WGsyg2nE0dJla0dqOTJA6aLD6j6iqrg8l7S9FKsHt0PjEGHVtH5mGUJUJ1Ws6KDqUgMJcYvZbnqlqwK4oPGZEX6McD6XHcXlLHQZO4yDwl1J4SHsRdaXHMP1iGnyxxaGwB86JC2Nlt5qP6dh7OTODCuHDKrXZanG5WtXbzQ2s3IPRhAN80d1JktrO8pYupEcGsbOumzOogVKvhhZwk8gKMDAsJoNXhosrq4Ke2bv5a2cT40EBezu2r0AV51/syq50Lj1TwfE4SCUY9q1q7KbHY+aihnTn/QDzuVlSMssx3gzN9QwGnYlZECI12FxPD/7MF+qdidGggcQYdzd4J2d+GhJieHB0a+Dv3/p/FlClTeOedd4iPj/e1Jv/2t79x3nn/mxdN/8P40yZiYzMjGZMRwUMrjvPV3lpeWjqYED+xAKqqyrzXtlHXZeOb60YzLCXc1478Iw2YJEnofzO1dcvULH441MCFI5N5/KditpUJPddrFwwhKdyfkuZe7vn+GDqNxNFHZhEf6seuig5cHpWaDguqqvLculIyogOZlB3FtRPTuW+5mKhr7LbRbevrl98zO4/hqaIEHuBNWF7ecLJfIhbqr0OWYFBiKNvL2vl8dy0PzM3lr2tOcNMXBzlY04XNpVDW2ktdp5UDXm5ZmL+OjKgAhiSFMmtADAatzJpjTUzPi2Hd7RNxuIVg/8H5+Vw9IZ1LPtxDQpgfgQYtEzIjuWlKhqh+mZ3YXB5cisLw1HCGpYShqiqTs6P49WQbD68owuFWuHRMCiNTw7n5y0PEBBsw2dzYXB7un5vLgsEJjEgJY8wzmwB4/KwCbC4PT64+QVuvg8XDk7h4dAp6reBpvfBLKW//WoG/XoPV6WFTSSsmu4suq4v8uGAeWZDPkOQweqwutpxs49fSNkanh+PxLtg7ytoJ9GrKmrrtVLVZyI0NosfmQlIh6Aozac1BZJ4j8deNdRyu66bX7uLmqVn8vbWcXwtauUUzkAtGJHOwtoupudHsqxaVrNc3lvH+tiryYuv52U9ULj/bW0NJWy+rjgT6WrlXjU/jh0P1FFf3wlehNMR18XXICVpPxnNTQibjMiNYPCyRtUXNfL2vjpunZHL+yCQsDg/dVvEeCfBeJTrNUL0GqteoJE1VfWDUoCSJk9+oFH+sMPYJmfBcidYj4hzog0RlSnVLjHlUpnqdwu7HFQpvknxejT2VKrEjZHKW9H0GGneq7HhIIWYoTHxefH6aD6ho/ARINn2++OJxdKsge5MQFXobVKIGS7QdVQlKkCj/UeH4hyoDr5UouEJm290KGkOfRqujREWjFxT/1kPi52/jxGdCB9Z6APIultnxgNLH88I7ENArUbdJZf/zCklTISJf4sTnKlnnCTskWSsE+SkzJRw9sPcpleZ9oHrcxCYcYOxdsWgik9EFSkQNhqjB4jXveMBD407orYPRD0mMfUymq7S/7g5DEIy5U/RD/bxcqebDULsDMudA+B9DVAEur27n165eXshJYkJYIFP2lRKgkdkxLIvg774FpxPOWghx8Wc89rW8ZHZ0mZkZEYzF7fldX8qDJis9bg/bu3r73V5isXlbjXncWFzD3ANlPJwRR4ROx6AgP/SyhE6S0HrXTIeikGA04FFVri2qptnh4pOB6Tzurfi8XN3MO3VtvJCTxJLYcPSyTJ6XRN/mFENCrU43oVoNRlkiQKNBL8ucHR3GKzUtdDjdbOnsZVJ4EBpJYkOHiW6XmxuSojB7FIZ5K3qBGg1aCV/F6r60OLZ39bLPZOXShEiGhQRgcXuYtLcEk8fDbcmi1Rr2G1eBhzPiuTwhkqn7SrF4FH5u7+HqxCiuToyi16NwdWJ/0eCq1m6Wt3TxQEYcmf5Gnqhs5N26Ns6JDiXRqCdEq/HhPG5LjeG2VPH/Tm9i/Vst3X9SaCRJoFmOV59aKnxx6pP0RFbCv4Un9uCDD/Lqq6/y2GOP0dHRQXR0NEuXLuWmm2765w/+F8SfNhED6LK6+Hy3MHI9UNPp01cpKpgdHjyKitUphJw2p4f5r2+jrdfBB5cNZ2TamTyw38a8QXHMGxTHsfoeIgMNDE4K9UE4AX4+JqpZ2dFBlLf28tOxJi4fk8pHlw8nKzqIijYzb/8qJgG/unY0a441cd2kDJaOSGJ8ViQGrcZHsf92f50vEbttWia3fHmYhi6bz0MTBKT19unZnDc0gXHPbgZgQHwwX+4VAvi/nj2AAIOWeQPjsLsUhiaHEmjQ8ulVo1j4xnaO1PdQkBDMjX8/yP6aLm6fnsWtU7N4Y1M5sgR3zMgmNsTIqlvGc8mHe5j32ja+vGY00/NiOOetnXy1r46VNwufx9zYYOq7BIbh3GGJ/HqyDYNWxuVRmJgVhVEnuF16jczziwex4nAjm0tauXNmDrEhRqbnRWN2uDl7aAKPrSymvNXMisONpEYGEKDX8OzPJQQZdSwaJq7eR6eFkxMXLAYJdBoMWpmxGZG8u7WSG/9+kM+vGsWQpFAO1nbz7f563rxwKBtONHPLl4cBeGh+Hk/8dIJVR5v48caxFCSEMPzJDfTYXLx7yTDyAmIpTBT6svouGxaHmzWmWtoDHbRPaefRqQLO+PCK44QH6JmcE01RYw8ApS291HVZeGLVCVQVlgxPZMmIRDwO4e/YaXZxT8hxUm0hXFM0knjCsUa6iAwUmYS/XsvziwvJlcM4csjCgsJ4EsP8ueHzA3RanIzPjGRKbjSNO1UOvKiiC4KU6VI/Oj1A3a8qLjO0HRNU+LZDwrw7KAkatooqUNp8ieLPBPOsu0zc11sLrQchdkTfvlRVFV6LiqDYg4Bzth8R7VHtafMyhlCJKa9KHHhFpfM42NtFcrblTgXVA1FDxHbly1XC81X84qC3BrLPh7BMiT1Pqsg6lQXfy77k7lR0FAsngIIrJCzNkDRVAFXjRoPGT/hKylqJzhIx+WjvVvE4ACTqNot2pccmbJfKf1Sp+FGwzmZ/IqYtQ9IkpJaDUPIjCX4GGPmoeA9sUTn6rkLeRRLx4yW6K1Tf4EHMMImYYb/zZWH8DYW+fi+Y6qHp4D9NxNzeFolbVX2ielVVcaqAwQAezxmkfUVVOW62kRfgx9kxYVxfVM3K1m7e/w0C4IaiaorMNu5Oi+13e4/LzZz9J7EpKquHZhGoEUnCqtYeDvVaOT82nD2j89FIIoF5q7aVx72i/Wezk1jT1oMKHOu1opclbj5Ri4yg8+/uNrMgOpSdXWaerGjkbwPTuCw+ggw/A7mBRhrsLuyKil1x0+Z0keJnIEAj0wY0OZzU2BwsiArlaK+NxTHhHOi1kOFnRC/3VbDcKrR49UTBWg2hWi1dLg+Bp1WmXKqKqsL0yGAuio8gRt+/WilJEpE6LdMjgnEqKufGhHGwx0K4TtvPgeDzxg48qspHDe2UWuxE6rTcnxFHiDexsikKr9eK9uxZ0aEknzZ0UWtzMGVfKUZZZseoXEJPSwZrbA42dfayOCbsDI7ZnzHmRYXywYDU3+WIPfFv5IgFBgbywAMP8MADD/xb9v/P4k+ZiLk9Cg/+eByHW+Gh+Xm09ToZn9kHctXIEqtvHU9br8PHG+u1u6hqt6CocOPnB9n/0Iw/3H9br4Ov9tYyZ6Aw/r71q0NUtVu4c3oWMcEGVFWlpsPK5lLxDTU9P8bbSuvCbHfz13O8fmiKyuVjU7G7POyt6uSl9SfJiApg418m+46VGiGu8FYeaaLD4uT9S4WwXivLpEQE9EN1XPvZAdp6HQQZtdwyNdPHowKQJQTval8d8aF+hAfoOOitiK0+2sgV49L4Ym8ti4Yl8eWeWvbXdLGppJURqeG8sbkcgMp2CzdOziTEX8e+6i4AqjosRAUaCNBrMOo1JIf542/Q8vL6k7y6sYyrx6fx4Px8BiWEEBGgx6WohAfoeevXclQVDDoN8wfF8/W+OnZVdvLprhpMNhcbTrSileHX0lauGp9KRKAeo1bD4nd2kRkViMnuxu5SuGRMCucMSSAp3J8VhxsY9fRGzh2SwKojTXy4vQpJArtL4XhjD4XeRGxvVSe9DhcpEQHMLojFo6osGZbI2uMtlDSbWPLubj6/eqSvDf3axjIq2sx8f6Aeg1YmPsTIG5vKGZYSSmKYPxeOTuZ4Qw+/FLfwixcCe6Cmk5SIAAINGvz0WuxOhV+8LcbMmEBmvryNR0cOIuBQPKAjd3QYfgUKOYWgC5JYN3cc7qMG6rf06a8iP01gggn8pkgQC2fnJFJdY2NiehSTn9/MUEMUY9Q8/MKFkP70cFlEEgYga1Sq14n/+0XA8LtkEiYqlHwOq85VGH6XhK0NErzyw4oVEDlAwFAlWTj2rL9GwW2HEfeBxyHh7FXRB0lMfF7GVKsSkQ/HPlBImS7RVaay9ymRqEx4ViZmmJhgDE4BR7fAWrTuhwMvirZk5nlQb4OYoRIuK2gDwS9cmJMDHP9Iof2Yyoh7ZI69p9B2RFgtjbhH/L06S1Wadott8y+BkDTRhm3eC3FjYcitAqPRsE2cl1Nm44mThE5O1sLKcxVGP+yl5vfGi7JhaJ/MoWGHAL/Wb1OZ8IyGtDl/uFz8cWTNhsaDkDL+n276ycA0Km0OH4Zh44gcjLJMpJ8BFi8VRuB+/afFn65s4vXaVi6MC+el3GQqvaDUalufbY9LUVnV1o1bhXQ/AzkBfUNEBlkmQCOjqAphOi2fDkqj2eFiRWs3h3utDAjy6+c1eUq0X2l1sLyli7fyU2h2uJgUHsQL1c00OVyk+xl4PDOeJbHh9Lo9/NLRQ6vTzb4eC25F5VCvlaHB/qT66SkINIIqUWNzkuJn4PvBmZRZ7bQ63YzafYKp4UGsHZ7NytZuvmkW69HViZEEaDV8NCCtH9X+rtI6Km0Ozo0J9bUS/TWyGAgASsx2hsb/vjH5+/VtrGjtJt3PQIXVwYKDZQRqZI6MLSBAq6HUYmdZqbjYfSg9jq1dvXzd3MGa9h52j87jvJgwwnUa7iipI1SrPUOYb/cOKCiqius3mqRbT9Syp8dCrc3BI3/Qev6zxbyoUGZHhvxfJev/fx1/ykSsusPqwyBcMiaFoclhZ2wTE2z0TSaCEPDfPDWTNzeXMzDxTP+0w3XdvLW5nMvHpbLqSBNf7q1lZ0UHr184hOl50fx0tImSll5eeqmM6yalY3G46bK6SAzz44bJGUQGGei2uZg9INa3z8/31BBs1PLQ/Hz2VHYQ4qcjJtjIoyuLWDYrh0CDllumZeFwK7z7/2Pvv+PjqO/tf/w5s32lVa+r3qxmufeCcTc2GEzvvUMAhwABQiAhkFBCL6H33g2YZnDvVa6SrN67tL3P/P54r1c2NklubvL53t+9Po+HHrJ3Z2dmd1YzZ16v8zpnTT2rqntw+0NEGbScVJHOdW9vZ0NdH29dMYHcpCgm5iUIoXtOQuQ9tPS7SIzSkWwx8u6WZj7Z0UZjn4u3r5zI+Nx4tjYOcNtHlWy/Zx7zylP59QeVkVbd7lYbLf1uzhiTyZaGPr7a3cGA28+LF43jbxeOxekLMiY7PtLO7XP6+eGAEPF/v68TEBmcF7y8ib+cPoIvd3dw77K9/HpuMeXWWAxamXE58Xy0rYXJ+YnEm/XEmbQ88UMNKRYDGlnipvd2saA8jYfOGMFTP9UAkBZr5M6FxTi8wtj1690dyLJE24AHVRVaKr1WVNyePHcUH21r5baPd7OoQnz2/mCIk55YS5/Lz7tXTWRKQRIbanvZ2tgfOTatAx4un5rDQ9/WEG/W89G2Vhp6XSwYnsZNs4pY+NRaAD69fgqxZh3nv7ybfe12lozOYHhGLFMLE1n45FpU4NPrp1KUauGvZ42k2+Hj0x2t4nuqtXPJbRmoITjrlMMEWoCjxcC39wj7+RmPSyRVSMTkwkA1RFvFCcn8SRKXb07igNRIo92NPaqDJXdkodsSzWeLFCb+TiJ7liAn61p66CvRkCfHYKuT6T8gql1T7pfRGiUShkl4+kR7Tx8tofhVvr1IJXuuxGlfybi7VL48U0EXBdMfknB3ii5bxwZRHererjL5Pg2qIqYZ97+p0vitMIFNGx9uW9mErYXPprLmNgVDPMx+XkKjlxmIUpBkYcA66noNo64favmVXypRepHIeQSo/kBF8UPnFpWsWeAdgJzD7pvih4nYIlkrKloA1qkSjjaV/JMlrJPFZ1KwWKJgMdR9obDjSYXRN8rMfFrmu0tEpFHfXlVUtizpcMJdRxyf3PnQtQUMcUedKv55xGaLn3+EQICor76kQgnByYvBYDjCrR2dTvz8DNLPfr9Zkc+jDR182zPIiQkWyqNNBFWVJJ0WWzDEyJ9lH7Z4/fQeijNTFAyyTI7JwE05qdyQnYJGkthmc/JMczcGWeap0myyjXqu3t/EPbVt/Di+mCXhqc1rMpPRIDE/KYbhFjMP1LXzdHM3V2UkkW0ycGF6ItO3VNHi9SMhPNI+HVXIqA37OLuyjuVjiojWavi2105MuKLVHwjS5vXzfkcfIy0mTkqKjbRdi6KMFEUZ2eNwU+XyUhpl5JteG2v7nTza0Mlv8kRG7WUZSbzT0cdDDR3MTowhTqfhjupWojQy9xdlIEsSU+KihRt+UgwxWg2msD3HoZDzbKOeGfEWgqrKpZlJzEqMYc62avyKwo99NswaDfOSYnl5eN4xD++wKCM/ji/GIMkk/6wiNykumj1OT2So4P8KNJL0b7eo+J+M/5VErDAlmqVzhuENhhiVGfdPvaa228Hzq+ow6bScNS6LAx12StOHpmdeXlvP9/u78ARCXDQph1XV3VjjjIx/YAWzS1LYeOfsiL7L6w/ROuDBYtRy7Yx8jDoNZekW5pWlUm4VBKnb7uX3Xwjny2WV7ajAil+fwKQ//8SGuj5yE82cPT6LB74+wHtbmjl7XCYnVaRH9GEAmxv6sXkC7G+3c8sHu6jvcfHaZeOpyIxlb5uNdQd7+XRnK0FFTM71On20DHi4eHIOBq2GB5ZUcNqz60mPNaLTSGxvGuTbMIFaOqeI9kEvC0ekc+6EbFZWd/Pn5QfY3jjAiY+u4sdbZxAT9tAJKSql6RZqupwUpVh4fEUNBzodxJq0NPa7cHWEWHGgiwMddgIhlZ3NA1w7I58zxmayt83G+1tbkCTYfOdsFjyxhn53gLsWlqCRZe7/aj/ZiWZu+WAnK6t7OGNMBn8+fQQzH11F26CHXqePP30tUqUfP3skZ43L5JbZRRh1GiRJIiFKz/1fief9QYWHzxhBQUo0N7+/E41HwqDVsKyynQ+2NjMqK5YBV4ArpuXx7MpaGnpd/PWskSwakc5Xu9v5zUe7+XZvJ7+ZN4yLJuXgC4ZINOup7nRwykgrLl+Qs8ZlYtRp8PpDhGVodNm9DEu1cMbYTN7Y0MjBbidmvYZTR1k5562fmJSfyFOMpuUnhfrlKiOulrHVCdKjMcDqpSoZ01VmPqlBCajIOnEBiCuCzi0wz5xN4mSVF1bXcdGqdTzeMxtUHU5hGYUaUnnjlQ62mbu5eG4WVxUU4+pUyF0goTVK1H+psP0xldTxUHq+TFQGDHwjXuvtVVFDwuA14ICQV0wYnviERMgvphRbV6tYsiTRbrxVtBuj0sGcJvIbW1apRFlh3B1iv+1Nou2JBO4u2PpQCFeY2PlsQ3+TGmN4ktEsXrP1LyHSp0hMuEOi7wBkzYI1t4nW6UAtER8vSZLIPxl+vE6hZWWI2c/JNH6r4mqD3t3CN+xwNP8kLDja1glNmKNFtDaHnf2zO/DqZdC2DSrOw95UjM8GHRv/qdPLfw9uF3SLaioOh2hFHoa32/vY43BzT4H1iPbVb/PTOTU1nuKwq3uaQceGQRf1Hh9fdA1QHm3CHVLoC4QIqCoD/uARPmUKKiOiTWgkiSyjnu96bTS4fVyVlYxGkvi+18bFexoiy/8qO4W5SbHMTrDQFnbUP4Rbqlr4rtdGabSR4RYzDR6RBuJXVa4KTzpGa2RkID78Hj4OV7nMGpl4nZYH6zv4smeQGfEWojUy+xweXm3t4ad+B3FaDZdkJHHOrjrSDDoeLxG+f2fuqsMWDPFUaTZLc1J5rKmLT7r6+VVOCpsHXVyZmcyr7b24/UHafH4aPSrvd4obsisyk8kPm8uunVASIXm7ppSjl2UM4TaoSSPzwaiCyHstjTaxekIJ3b4Ap+8S0pPVE0qOqDb+HCVRpmM+fmd+OnceZptxHP878b+SiAHcPKfomI8risqFr2ymsdfFB9dMjrieS5KEFL53vP6dHZh0GrbfMwdzuPR++TQRNXTZ1DymFibR5fCxurobVYXucMTQHxaXc+bYTPKTzIz50wpUFVJjxB/Y7R/vpq7HhSxJ/GZ+MUnRBs4am0nboIeNdX3CrG7Qy/UnFrCxro8/f3OAF9bUkxpjRFEhLdbEzOIUFEXl7c1NpMeaePPyCdz2cSUPf1eNSTc0bADwq/dEu1QrSwQVlWve2s6C4Wl8GE4DuOiVzdR0Ofj42slY40zc+lElyRYDN84sxGLU4gmEGPT4CYbE+mYWp5ARZ2L+42vwO33sa7OTbDEQY9Ly6HfVbG0c4ObZRZRZY/hmj7DMGJeTwLDUaD7Y2oJZr+HuhWWMyopneEYMnXYv724W+j1rrJGsBDNxZj3JFiODngAFSdHMLkvlzLGZbGvs58U19QAMz4hFr5VFFQ5IjNYzvSgJjSzxwHLh1J+dYKau28mC4eksGJ5G+6AY15tamMSpo62c/9JmtLLEyxeP5baPKul2+HD6guQlRdHU72bFgS5cPkGk4qN07Gge4C/fVBFv1pFsMZAcbWBSfiLZCSZOeWYdDl+Qz6+fyrUzClhW2c5N7+0kJ8GEXiPhD6kcbiw+KT+R/OQoJuUnsrGuj26HL+LkX/2hykA1NCxX6doGAZeo7nj7BRFRQ0MkDCCpTAZVoeVLmauvLGDZrnY8ASfWm7xk2AwRzVLNRyqLtg1nUoKTGSMl4tMlZvxVg7dfZcPvQyhhWx41BAM1KquWquQtEm1EjUHl81MUYgtg0r0StnoVrRGSKsLt0gpRmeo7oFIkiXajrV74dI2+WcI6VWLnk2FfMpsEWZA8Qjjx6y0Sqgp9+8TzpRdL5J0kseclha5tKuNulyi/VGawVuWnGxSCHvD0q5zykQZbo8KyU8VEJhKYh5QHgHD19/SKzy7gErotR6tK0gix300/KDR+J7zPfDaIzoLSC2DPS+L1UelHa+wYbBYTBPZW8k4qIeCAxOH/D9olsXEwZy6EFEg6UhyuqCq3V7egIOwmzk0f0rbKknSEX5grGAo7uUucHLa2SNRrWTamCEcwxJjDqi4HnG4WbD+IBKybWIpGkrh8bwMhFbJMehYlx2EOE6cEnZYrM5MojzYhSZII2K5t55p9jWw+LLBcAdq8Qvfz1+IsTkuJZ1JsFF91DzIjwYIz3CZ0hEQl+JmWbjyKytKcZPLMBs5Oi6fJ6+PMtDh2OdwgScxLiqU7EGR6vIUddjerw8MG9xRYqXJ5IgkBJVFG5ifGgAQzE2K452Abb7b3cW5aAh+MLMAZVBgTE0VQUbkqM4kojYY8k5632nu5rbqVyXFRfDZaXFNidUdfNj/p7KfK5eXW3DSMGplCs5FUvY4iswEVSPuZ5YInpPBuRx+T4qKPOEbH8X8T/2uJ2C/BGwyxtbGfQEjlYLcjQsQKkqNZffuJtA14OP+lzYBK24An4rQ/Jjuely8RauXaLgf3fL4XgN+fXMqpozLwBkI4vEHG5sQTCClcN6MAnUZmZrG4QpwxNpPPd7Yxq1R4zMiyxCNniQil1TU9OL0Boo1als4ZxsziQU5/fgM9Dh+vXDKOmi4nJ4Xbal/v7eD3X+xDlmDHPXNp7nPj8oe4cloe507IojBF7O8hw9obZxXSZffy3pYW2gY9LJ07DH9QYXNDP/6gQnO/my67jy/CNhlb755DnFlH0d2iJDK3rJuEKB39rgBnjs1kYn4Cm+r7eWJFDVsa+jHpNUzME0MEgfAJdEpBEl/v6SAQUmgb9NDvDvDV7g7OGZ9Nr9PHqc+spyA5mr+cXkHLgJubZw+L6LHs3gCKCrbwCTvWpGNvmyiTJEXrIxFTvqCCivCLe/XS8eQkRrH0g12sqenhYJeTZZXtrDjQzbyyVO5ZVMrGuj7e3dLMy+saaB/0oKhCRH/In80aayQ9xoBRJ3PehGzG5sbTvC+A7y0zP+TX0uv0Myw1mu+XzuCjbS3c9vFuEqP0mPQiCcGgk6ntduDxh5AksJj0tNuEXYA3ID4Xd7eKZmMU3149g9NeXce7m5u5aFIOS8YI7UfhJSovf9uEdWoC5RWxtK5WqbhKYu2dIvtw/zsKvj6JpBEifiiuUIjto9Kh74DKjRumYp2nMHakjoOfKHx+isrI6yRWdXcSTwqFxUZK04cqHm3rVNrWCmurmU/LxOZB1buCFLl7RKC1t0/4e9nqoW6ZEPh7ehVKzpOxZIkWZddWsT5Xh8S8V2RqPgxR/7WIRDIni0nMgEslNh9cncKANf9kmaYfFOo+h2HnhIcBxklEpUnUfyVagz07oehMif1vCRJmToOxvxbfk4FqERyeUAonPCKHfcCGkFgmMf5OidrPVPa9rjJmqcTwK2QIeKC/nZoPcxisldAYVBxNgARas8TYWyFnvkTKKLGegx8rNP2oMvYWmfiK82CgDtJGo9WELTgaVsL+ASg+mSPGNA/HYBPsfA2SiqEi7BLrd8Hut0V6eMV5Q+nnv4SCwmM+LEsSt+SmssfhiUQf/RKcIYWBYJCgCodv7ZCLvKKqbLG50MsSp+84iF8V1SiNBCZZYlFyHLUuLyFFZafdzbR4C9smlxGn02IOtws/7xrg5dZeTLLE5MNsBt4ekc9uu4u+gJjMnBZv4eSUOC7aXc8PfXbOTI3n9Qqh6zovLYFql5eTkmKpc/v4vMtGtFbLgqQY7i/MYGJcNCfEx9Dq9TMQDPFkSTZf9gzyeEMnZ6fGMyEummaPjzN31WEI218khMnT7eH8yp/CeZZbbE5uy0sjI6zb0soSJyfHsc/pIagS0SUdmgpt9/o5dWctaXodn44uRCdLBBSVXx1oRkFEQ52eGs9gMES8TsvaiaXHPBavtvVyf137Mb3ZjuP/Hv7PETGzXsubl0+kbdDDzOIjjffSY02kx5ow62UGPUFW1/QcFXm0s3mAc1/cRJxZR0VGLGePzybaoGX+42uo63Hy7lWT+HZvJ6+ub+C0UVY6bF6a+txcf2Ih158oTqa+YIhzXtjEgNvPR9dOZsawZB7+toob3t3JpVNyuSCcPRlUVBzeIKeNFhfqvW02bv2gEr1GYlphEjFGHa9fPoGLXtnMy+samFGcHCFibYNiojLOpOOyqXks392BPRyyXZYew50nlYj9Lk/DF1S4YGI21jgTyRYDWxv6DnvHKle+sQ1Fhax4E1dMy8flCzGvLJWtjf24/SEael18fsNURoQHH04eaeWLynbWHOzlpOGpXDQph3MnZOH0BXn8hxpUYMDt59wJR+tjbpldxJ+WH6CpzxV5zBWebA0qKnU9TgqSo7lhZiF/+aaKuh4Xn+5oY+ncYfzptOE8v6oOZ3hSyukL0uv08fB31di9wchI9B8WlxFr0nPqKCvbGgdYcaCbfrefdpuXc8dncVJFOnZvgLq1buQNMKYnl/QLtfiDCn/+5gAzhompz/KMWJ45fzTeQAi7J8D8J9ai18gs/9U0+t0Bbv+4kjHZ8cwqEd+zbY8qdG0FWyN4Q+I9TSlIjGgYVwSbedtXxY8rjGy8czbZs8X7txcM8lp0NYuaM0n/MY3GHyBtgoopWWL+q6ISWvl8CG8v9G+V4Sro2a0S8kLvHng+tBffWJVb5xcB+QzWilzHjGlC5J5YJsT4AOWXiynGLQ+orPyVQsW1YEyE1PFgShCWE80rREVp/msyUVbImQ+mJEgoOdR6lHA0q1S9KwT6YthA4puLQjjbYcajMimjJbY9IjRpsfmiilb9oUJShYYJd8n07lbJXSix52WF5h8gbaII/o7OENsYd7tM5xYxyKAzS7g6VVpWCusJU6JYRpJhoAoGqgSh1VuAyrdgsIHx5y9g46vTSB4hwsjNyVKEzB0+HVq3TMXRAq1rVOKvSgTzYdPUAQ/UfS/+nVQMKeVHfZ8BcLSLUdLBxiMfO/R/v0vsbPUysFghd8ax1/MLuD3vn2tdVTrcxGo1LEyOY7jFfNTzzzR382B9B2MsZrwqmGWJn8YNI90gSMqL5bnsdbiZs60GnSSxbXIZ1jCBuelAE7vsHpL0Glq8fk5NieOJwxzz0ww6dksSS6tb0EkSVdOHs3nQxQ9hQiTE+aZIdejsXbV0+YPMTLDQ4PXxQUc/jzd24gwpfDKqgKnxFi7cXc8ep4c/Flr5ptfGNoeb/CgDF1oTafYIz7B4neaorEeAO/LTeb2tl3qP0Jg1ePxYDTruKrBy3u563CGFKI2G89MTGWsxR6Yc6z0+Wrx+Wr1+bEExZOAIKVyemcQ+p4ep8RZurmrmw84BnijJOqJCeTjGxphJ0GmY8TMd1DNNXTzc0MmDwzKPMoA9jv+9+D9HxIAjchYPocPm4ft9XSweaeXhM0eyqb6fs8ZmHbVc26AHX1DBrNfw1hVCYK2qKv1uP0FFxe4JEG8W2qk4s54lz62n1+k/wnzV5gmwu3UQRRW5lykW4xE2GiFFZVFFGl/v6eSBr/fz1HljaB3wIEngDynoNMLZ3RdUGJMdT1a8mZYB9xERT8+eP4btTQOcMSaTz3e1odPKqIjXX/r6VipbBvnjqeVIksRTPx7knc3NPLBkOBvr+jjvpU2YdDKjsuKxe4KMyIzD4Q2QnxxNssXA3LJUdjQPcNLwNFZV9zC5ICkSI6UoKrtbBhmTLSYUv9nbxftXT+Kr3R1MLUhkfnkaVZ12nrtg7DGPzc6WQRzeIKtrelk6txiAS6fksmJ/F/W9Ln7zYSXvXzOJiyfn8PC3VYCoZgF8tK2FZ1bWYjFouGl2EckWAykxRoalWtjbZmPRiHTG5yVw7vihC8RT543m/S0ttAy4+WxHG/lJoj1z6atb2NE3yJVTyrl8UQ7JE/Mo/t03KGp4+vSqSeSnRBNj1BFj1DFQr7K0cgpNiQNY48x8tquWtkEvMSZXxJcueYRE+84gT9ZW8eCvK9jW1M/bm5vISjDj9odoH/RgjTUypyyVdzY3sat5kLsXlbJ/TCvVG3tRNX7uHpuGoxmWLVGY8ahM8iix7gExx0DaRDGtmFAsQr0zToCbP62gKq2fsyZk4XeqbPqjgqMFfAMw/zVxkdrzkoKzDcb+RiJtnIwhPoTfIQxMvX2iOrXofZlhZ6siQDsAslZYTjR9J1p7FVeKfchbJNG7TyXghsE6lbgCsY8hP6AM+YOVnC/RsUlo06LSoPhsMRRw8BOFlNGCYDlbRYXOnCpFSBiIVIC8k4b+v/MphY6NIvh7wp0SjhaVbY8KfVnZJeBsh4RiQCcIiN8dhbMV9r0Gp3975IW6/iuFmo9URl4vM2apTPt6laIzjtGC1JkgbxZ4+iHh2BUrADImCBPXmMOi0RIKoOgkUREzWKB9O3Tthq49kDP9H1fI/gWs6nfQFwhR7Tq2saslrIGqcnm5ISuZC61J5JiP1KMl6rUk6DREaTREa2S6fQFebOnms65BAqrKGWnpVFjMXGo9OpRTmNBCjkmPSZaJ1WrQAllGHbfmDg0xdfsC2IMhJODi9ESGR5sYHm3i9ppWDBKR6laWUc8+p4cojQZfSGV4tImbwh5d2SYDlVPL0SBR5fJEAr0XJMeyJCWeRL2W3xdaWdnvwGrQ80ij0ODNTYxlRLSJFq+fkTEmvu4Z5Jp9jVxsTRIZlBYzMqAAK/rsLK1qQQW+GlPEn4rE8W0NV/PbvAE8IYUtNheT4qIimjIQIvz908T0vDukcPHuehTArJHwqyrb7a7jROz/EP5PErFj4e7P9vJTVTcHOuz85YwRzCtPO2qZl9fW8+dvqjh/QhZXTh/ykJEkiS9vnEa7zcOY7HjmlKVy+thM0mMMrKnpxuYOkBIzdELb22bjnPFZTMxLjHiD/W5RKaeMTGdH0yALnlzL8AzRZuh3+1ny3HoG3AFevGgsT503ipve28UPB7o50GlnTHY8X980HV8whEaW+GhbC9OLkplamMTUwiQ+3t7KPV/sw6TT8O0t0ylJi+HpH4UdRVOfG4CaLqGrWF3dTX5SFJIE8WY95dYY/vjVfoZnxDCzOCXSegyEFC59dQt2b5Db5hdzw8yhi1Bl6yBPh+0uzhqbQZRey/f7u3h1XQPvb2lmSkESL18yLlK5A7ju7e1srO/jlUvG8fVu0SI9VBUEqO12MjYnnh6nj50tg9z20W5umClav4qqMjw8ITqtKJnhGTFMLUjitFFWnvrxINkJZj66djKP/VDD0z8JAf7hRMys13L5tDzu/mwPg54AX+/p4OoZBRjDmrvhZ+qwjhYVnUun5HGgw06v08/SDyoZmRXHFzcI3zRNvYFUt54MOZpYs5Y0iyCHeUlmmr5XaPhGpeIaiT/W/ITbH+LkgXi+3dcpkg62tfDFrnZsngD3nFzG5ZNzKfrdNwRVldHZ8Vw6JZf6HX6KN1tJPEXC3qSihsA7IHISxZdQ/PLboP5LQV5O/UKia7tK9HspjNekIM2T2P6mIGEA5VeI7McD7yhUvSseyzwRWlepSBLMfkEiOl3ClKSSMlrC3qjSsUllzt+EfsoYLxFbALJexRADO55UqLhKIrFMQpLA3gBN36u4R4kg7jnPS/gGJWLzxc4WLBaGqgPVMPt5YTJ78GNRNezbr1J0hsqYpZA1UyZtIvhsKnoL7HtdxVanMu42GUPcoSqWRP8BlbhCqHpPIbYQFD9IBtE63f28wohrJYrPOg8CLqJtFlLHKcQXwZrbQpiSJMbdJiYzm38UreC2NWIbKaP/jg6s4JdtbgBo3wb2diicD9rDSI0kQ85QPBnJZZA+Rkxo/gdI2BttveSaDPw2L42FYfuGHn8AvSRFNE+XZSSxYcDBlz02ttrd3FM4tL/tXj/X7GuiNNrIrinlyEhoZYkH6zt4pa2XVJ2WGQkWrstKjnh5fdDRz4o+O/cWWskw6Fg74CSoQpJOiyxJDLeYyDTq6QkEqff4KAgPFWwcdOJRVGRgTGwU85Nj+dWBZmzBENPjo+nyBzjY7ePl4bk4giG+6bWxw+FGBqyHTR0eIj5VLi+DwRCbbE7WDTrZ6/DwRGk256Uncl56Ip6Qwg6HG6tey0V76hkMhnhteC4lUSa+6BLWHpUOca40aWRmJcbQ4PYxPjaKCbFR9PqDkQEDgJfKc9lhdzEzIYZfV4vq2KUZSfxl2NEZxQDNXh/rBoW3zEcjC5ibGMvisIbvOP5v4DgRC2NCXgKb6vsixOim93ayr90W0R8BVLbaCCkqnoBCbmIUPQ4fyRZxskqLNR4R5J0RZ+KtjY3U97opTrUwIjOOlVXdlGfEcPWb2wkqKtOLhH4sEFJ4Y0MjJWkxkSi55GgDY3PiGHAFMFt0uPwhUmKMjMqKo9PmxeMPkWDWsat5gBvf28m8sjQ0Mry0toEpBYlcMS2PR76r5rTRVqyxRkbnxFOSJshdfpKZHc0DVLYMsr1pgEn5idT1OPl+fzfjcxNZeeuJxJv1rKrpRiNBr8PHy+sacAdCPLikgtXVPdi9ov1XkmZhS0M/Y7Lj0GpkStNjWFSRTkhRuG1BCTe8s4OtjQNkxJkIhBS+3tMhJhlPG44/qNDv8rO5oZ9Bd4CaLgfJFiOeoJs/f1PFnjYbvz+5jCvf2IY/pLCwIo3lezqRJfhwWysOX5CilOjIJGphSjS/XVBKUrSe51fV8fmudup6XMwYlkxxmgVZEpmhh2DzBLj6zW3EmnRcOyOfhl4Xi0daufz1reQnR/Hn0yt4ZV0Dr29o5JnzR3PnwhI21ffxxS4xjugPiiqmyxfkHamapCWx5GWY+dvqAXqdYoDD4Q1S85HKYC18/5YddyhEYrSe00dnkBZj5PNdbVw6OZfKlkEqW218vbudEzpzmNdURHuKjbllqSRbDNxsHkWjTeiiZj8j42wDQ0mQ/e1OyqwxFJ8j0Vup0l8l2ohRqRI6CySUSliyVGLyYNezYgggOgvyT5bInCbTs0tl3yvi88ieB8kjYdP9wqi19hMYdyuUXSwuaD9eF6K/CryDEiOvFV/U1LESS76R+HSuSt8+lfhCUREbca1My0qV3JPghysUVAWiUmWsU4dIjbNDRWcGVYKajxQkSaLiGtHajM6GL88QFhfzXpZoXS28yDJnQusqQBVDAjnzxPoKl8gULoG1vw3RuVm0XOc8L6ONgt0viBsIWQfIGjDEYE4RaQCdW1Sq3lMA4exvjIdRN8o0r1ApXPILBMwzAM1rIW3U37efUBXY/6nY2RgrWI8RCXAIOhOUn/XLz/83UOlwc0eNsExZN7GEQrORereP2VuriNJo2DipNFINW5AUy5c9NqpdXuyBIE80dTM21oxfUdlqd7Hd7uIiayKfdglycVJyLN/32WjxBviwa4Bb89LICbfx/lzfQac/QFm0EXswxMddA0yMjeKBMCHZ6/DQ4fPjU6HXH6Qg3C19KxxAPjPBwnsdfTzU0MnF1kSKo4zMT4zl/EpRPfp6TBEmjczcxBiuyEjixz47Zev38umowiMGD05PjWcgEOKFlm66/EEmxYnnBgNB7q1tZ6TFxMPDMvndwTZUVIwSpBv0rOiz8257H6ckx/L7wgzavH7+UNfO4pQ4zg4HfT9cnMXcrdUs3lnL5kmlRGs1JOq1zE0S56TEMMlN1P2yGWtJlInHirNQgOkJFqbzf8e24TgEjhOxMK6dUcC1M8QIckhR+WZvB4GQyq6WwQgR+8PicqYWJLJgeBq3f7Kbj7e38sCS4Vww8dh5lskWI5IE1jgjT6yo4dmVdZxYnMz88jRqu52MCFdyvtjVzp++PoBBK1N1/wIm5SeSHG1g8l9+RFHh5UvGMSk/keiwdcXVJxTwwNf7OfHR1UzOT6R1wMO3ezu4fUEJGlmiIiOWZZXtVHU62FjXz4Y7Z3PTezuZ8MAKXrtsPNfMKCCgqJw9LpOLXtmM2x9iuFWQNEmC3KQoVFXl1fWNmPRazhmfzXf7Ojm5Ip3tTQNsrO9lQl4CeYlRfLGrjWWVHVx9Qj53LSzFqNNw4aQcLnplM9ua1pEeJqdL5w5DURS+3dfF+eFq1xVvbGXtwV7uWFCCRhIDEctvzuSF1XU8vuIg3+/v4qJJOcwfnsa+dhu3zy/mV7OKKEiOpn3QQ7fDx+KRQ5EuX+/u4IZ3dyBLQsQ8OiuOy6cJcf/JI6yckJ5C6zcy9kaVmFyJrQ39bA7na967uDys7+vgpyrhzqhWPQAA/VZJREFUgH3bvGLe3dxMUFG5b9l+shNMvLq+MRKVdej4fbW7ndc2NaKVJZQOFUWFx84eyTPnj2ZSfiIH81xoNuvhhBDaryVGZcbRuU4iqSmRe6clsvJylcLcVCqjbSgqRGVIzOrKx1oEyRYNzT8quLtVJv5OIrFcaLbMqRLzH99IdZeDJ04bzVh3mrB/GIS5L4qTvhJSGahRcbaLkOvC0yUGD6qUXiCRO1+Qq44tgqSY02D87cJNftLvYNOfVBq/EROSvkGVEddKpE+SsLeo9O5RcTSrWLJFlmTVu5A9R2w7baJ4rPJ5hfRJEjE5EulTVNwdAeLyQsDQBXL38yp+h7ChaPkJQKVwiczYWyV696oEnCpBr5BXeXrFazzdUHQmBF1gnXY0UUobLzFQrZI6DuKLxfOT7pFxdUJM9tHLp4yFsotFZqUxPmwLUiBF2qnHROMqaNsiKl3jr/3l5SQZ8k6E3ppfrnKpCrRtFWOfh7vru7qhaa0gb3HHPr/8sygwGZgcF4U3pHLDviYuzkhiTIwZv6oiK8Kl3yTLaGWJHJMBrQTJei2fdA3wXEs35naZT0YVYJAkCs0GHqzvYGW/g25/kGfLcvh+XDGn7azFJMusG3By+s5afpufzh35aazos3NmWgIP1YtJ6rJoE65giC02J0t21iIj8XJ5NhMPE/bPSozhgMvLeemC8KmIRIHVE0po9vh4q70Pj6Kwos/O401dnJwsPLo+W7cHr6KyYdCJW1GYFtZfyZKEWSPT6gugk6SIbuv9jn4+6Ozno044OTmWV9rEl+zV4bmMijFzz8FWugJBOnwBsox6Hm/sZFn3IJsHnREiFlJVQqgEVDHx+XP8vsDKlZnJkWGAw9HtC3BWZR2pei3vjiiI+JIdx/89HCdix4BGlnj5kvHsaRVap0NIiNJHBOZddqGz6Lb7eHdzM8sq27j3lPIjvMcWDE/jxpmF6DQScWbxh5gea+LPp1ccsb1uu5ekaD0nFCUjSRLDM2Jp6nORmxSFNdbE7JIUJEmi2+7l1GfXE2PUMSJLbCcn0cSEvCI+39XGW5ua2HPvPDQaiY5Bj7DIGCfuPldVd2P3BnlpTT1PnDuaJ88dDQhLh8qWQeE91m7ns51tXD41D4cvwL42G0FFZXhGLEvnDmNvm41r395O64CHG2cW8pv5xdz9mfBOax1w88n2VtJjjVz4ymYUFUKKwsuXjKPH4aOux8nNH+1hQXla5DM6lJOo10o8seIgf/m2ii9/NY1rZhSg18o8s7KWeY+voSIzlow4E2mxpkjLMDcpiqfPG83BLgcnP72WGcOSObE4BVkSEVaKqnLPKWURIfx7W5p5/6t25m0tpWxbNDOf0vDAcuEvdt7IbNJMgjCadFpOKEpiblkqLQMeLpmSw/tbWlhxoIvseHP4GBo5eUQ6WQlmmvvcnDAsmSkFiRSlWlhV1U1QUZmQl0BmvJmVVd1c9v1WchLNrJ46k70T5qNVJD5bqIACQZ9EwAVeOxAtPkdtuY+CFz2Myhffver3RUUNSWXzn8A6RWXqA5pIqsLOhyGxIsTyaftpUGyM7B9HVoKZbQ+LMGqAoBeiM8FnhwNvq+TOh8Falc7N4juYXCGx43ERFzT+DonM6aIF2vitCOuOyYOyS2SaV4bo3w/1X4uJzOoPhEg+ZTTMeEwcm+afFBxNEHCojLxWZuofgI3PQJUNoq+FGDF8kj1bwm9XyTtJJiZHRA8lhIfMQmEZkyQJLVrx2aKl2b1LoeZ94ZCvM4eHA5qFwWtcoUTRGTJFZ4jWZt0yhbxFIuQ85meFq6BH5cDbKvHDRL7lMVH/k5iSLDtDWPsfQupIEU309ypch2AdDw2rYN9HEJ0utGJVX0BSCWRPhe59UPU5SBqY+QdRsQNB9jp2Cv3Z2Kv+8Xb+DqK1Gj4bXcTdNa280tbLG+29XGAt5qfxJXhCIWZvq0YnSfw0vphxsVHsnFJOlEZDjz/AhO5BJsVG0ejx41NVmrx+rslKptXrj7TP4nVaVk8oAeCKvQ20+QJ82jXAzAQLj5dkE6PV8FBxJmekxtPtD7B4Zy3ZRj1mWUYnH23cOSPBwn6nh3SDjoeKM5mbFMOi5Di8IYUF22sYDIR4tDiT7vBQziG3si/HFLHH4ebmqhZ8isqd+WmURpmYlyRaffucnkjo+GddA9xX106qXsuVmcmkGPTcV2Clwx9gTmIMiqoy2mLmpuwUzgiTrjPTEtjrPHI6tSzaxJoJJZg18jFzIm+pamF1v4M3R+Qx4mcDEtUuL9UuLwddMBgMHZFScBz/7+F0OnnyySdZsWIFfX19lJWVcddddzFixIj/+LaPH/lfwNSCRO76dA9PrDjIx9dNiYjRD+GZ88awq3WQqQWJzHtiDfU9LpZVth9BxKo67Tz9k9BL3T6/mKum53PrvCP9zWq7nTz8XTUAV0zPw+kLcsmrW+h1+mjqc9Mx6I2IvdttXjpsXrodPl6+dCyLR2Tg9AWJMel48seDNPW5WVPbw83v7WJkVlzEMwzg4sk5PLOyji92tbNoRDqzS1KRZYmXLhYXk2/3dvDB1hb2tdu567M9zC9PIxg2ZByVFUfrgJvTnl1PSFHJTjAzMzwJeP+pw5lRnMzVb25n+Z5OfntSMYoKCVEiJeCx72t46MwRbKoX7YYuh5duh5f3t7Twh8XlBBWVcmsMz6+qwxuQ6LJ7KbfGctnUPF5b34jXH2J3q7CvaOl3U5Rq4bt9nazY30VdjxOHN8jBbicdg16uO7EwYqJammbhite38sblExiRGcfzq+po9rtJyWlj7jRx0TDrNUiA54soflyhMO15lSvf3EogpHLx5BzOfXETTl9QkLJ+N7EmHc0DbkrSLKRYjPzlmyq+2t3OV7+azq3zinlvSzNN/WJoIjP+kD+dkG+19Lu58s2ttA0I0n3DvLEM1sOuzHbG/S6FYbHpDO7qY2ZxCoufWU+n3csrl4zjhKwUsucKV31zqkr3dvA7YPmeDg502Jkck8LwgVRsfQHWx7bjDym0DnjISjATcIkPI/8U4WgfdAOqqFx9Mj9ETK6YVkweKUT6a+9QQAVXO0y+T7QtVy0V9/kpo8S6hl8mU/m8QuMPKtmzVXLmQd9+SJ8kvqMH3lHo3KZSdKZE+mTY8mcFvz3I1HluJCXIYI0HT0glfaJE0CusM7TmofbnIZhTQBclKnWyHoIe8Par6Exi9lUfJdG3X6VlpULdMlHxm/eyTGyehKdHGMuGvILE5S2UqP1Moe8AjLpBwhArdGBV74oMy8wZv9A2alojynE9BwRpOoSEfJj4qyOXPbhcZEdWnCtI1iHozGBOEjtoiBGVtP5acHaJdVrSwRgP0WlDJAwEyXP3Q+akY+/bv4DTUuPYYXdzXbaQRBRHGalxeenxB5ElkQEZq9NG3N1zTAZeKs+lzu1jUlwUq/rtdPuDzEyM4ezDpgF/6LVx1b5GzklL4N4CKyVRRr7vtfH72nY6fAEmx0WzYdDJ0pxUttmFlitZr+X7ccPQSBIWrYYr9jawedDFB6MKeKqpiy+6B+kLBHlvZAHnhbflUxT0kgyE+HV1K+enJ7Bi3DAKzUaaPD4eqOtgbmIMmQY9nf4Af64X5tSbJpWSazLw4GEarR6/uAnMNOr5VU4qzzR14VEU7i2wIksSL7X0cE9tG8OjTdxVIKruWUY9Dw3L4ueFq0Pathavn3N21ZFj0vPOiHzkcCh5XyDIDrv7KCI2PcHCX4uzSNZrj5Own0FVVXrtAbyBEEadhqQYXeQ6+J/C7373Ow4ePMjDDz9MSkoKy5Yt47LLLmP58uWkpqb+R7d9/Oj/AhRV2EyEVBV/8Oiic6xZR3aCmQ+3tXLHghJWVnVz8eQjWwj5SdGcMtJKIKTwyHfVqEBFZuwR7bSMOBOT8xMJhBTe29yMyx9ie5NwlD53fFaE8IAgRC9dPI5og5as+CheXdfIa+sbWVCexmNnj8Ss1+ILhPAFFWq7hfizw+bh4W+rmZAXz/zyVHY0D3LVm9v5/cllkbYdQEKUgdxEM/W9bnqdfkrTLUQbtOg0EgadzJ62QVQVjDoNn1w3JaKNU1SVe8MJAUUp0Zw/MYcKayy7W2089F01NV1OHlgynMun5jEs1UJJmoXHfzgYjojq5f2rBVn846nDuf6dHdz83i623zMXo07Dn5YM55o3txNr0pGfHMVAuIL2+y/20mX3Rfb9wknZNPW6ufrNbdy+oJhOm5dPtrfi8ofY325nRGYcc0pTeHV9I4OjBhl2trjof3ztFM57YjOfcwC1P8R0VwEn6/PYqu+gOC2GrAQTB7ucnDs+i9mlqQy6/cx7Yg2f72rntFFW9FqZUVlxtDf7OOdvGwmqKqOy4iLH95PtrcRH6fj13GH89YcattT3CxsNCR6/O8T9X+3ni9XtLKpI59nZY3g5byJr71DQJLWgkSUURWXt3SH6dksULhFWFMOvlChYLPHyVhcj+tLQxgjj1fhhBt6zTaLP6YtMBU+8W6Z9gyqMW+9RiR8G81+X2fqwQv9+UXWyZEPxeTIavcSk38t0bVVJC6ctmZKHnNHtLbDvjRDWSYJA+W3QX6Xi7RPErf5rlWFnQ9V7KkEXZE6DmCyJpu8VQEvvkhuxpDlZcVkGqqIw+28yjd8JD6/2DSLfsfFbMZ1oSoadTytEZ4s4JVkjseNvCg1fq1inwcL3ZMzJ8N0VovKmMYLWOBQ0/tOvBAnTRUP8MHHy3vWsGHBIHiH0calZ+0gszCRx9N/x3io7HQYahYj+cDg7BbmSDzt99teHLSqajyRiWgNM+bX4d9ceCAUgfZywuwCxnmm3i1LlpicFWRt1CcTn//2257+AF1p62Olws6x7kMUpolI8LMrIZ6MLUVWOCKI+hNN2HqTB4+eZ0myWddvwKApfdA9yZeaQg+4epwevorLd7ibbZOC2vHRUoMUbYFJcNEurWugLBEnV67guO4VdU8qJ1YmboAt3C3F8vduLM6Syx+HmYmsivf4gl2ck8WprD/ZgiJtyUjHIMqsmFPNQfQevtfehkyT2Ob282NpDvFbL8l4be5weNk0qpdcf4MxddehlieSwTuvhhg6eb+7msZJsrspMpizaRGmUiTq3lz+FW6czE2IYFxtFhlGHjCBfh9Dm9XPCliq0ksT6iaXoJFha1UKWUc8fijKocnqo9/ho9vpwhxSitRreqshjp8PNqclHxuat6LNz4/4mLrQmcsHx6cgj0NbvZXejA69/6Lpr1MuMyLWQkfDL6QT/HXi9Xr7//nuee+45xo8X/jW/+tWvWLlyJe+++y5Lly79j2z3EI4TsZ/hUG6iXiuz/Obp9Dh8LKtsp7JlkKtOyD9i2Rvf3cG+dju3zCniL2eI8qWiqMjhWya9VkZRVNbX9jKnLJV+l58JuQn0OX2c++ImYkw63rlyIu9dPYndrYMsfmY9AL+eO4yEKD3nT8iOrOvxH2o42O3gwSUVkTbnoUDvA512oo1aHjpjBLIkJgHzk4UW54OtLXy2s42NdX2suu1Ebn5/Jz/s70IjSzi8ASzhmKKnfzpIfa+b8vQYHjt7JF12L06f8N56Z1MzTl+AkKqSEW+MkDCXL4g/pESI6v2nDSfGqOOR72vY3TrIWWMzmV2aijZs9vhTVTeXvb6VK6bmYY01hrVyDn7/xT5GZcVh1MlY40wRrYRRq0FFDDPsbB7kjk92U2aN4dzx2Xy0vQV/UOGSKblcPCmXkX8Ufk6XT81Dr5Fx+UOkxRgpSrXQ2OuKTGmGDotdOdBpZ1e/IL1Zp6hsvl9lys5hXHVZMVkJMiBSCdbV9jK7NJU4s544k45uu4/Pd7UzvyyVP51WwddXBEiKisIb4+fX0aMYfMzIqm47t26pRJZg/W9nkRJjoCw9ht1tNhKjDCRFGxifm8D3+7oYnysuioO1YKuD65sm47m9jave2s40k5VTGUF/FfQfAI1epfQCmXnuPJJrQd+nknaX+LzGxsUf8f3s2w+bH1AjeYg6C8TkSEy6R2b33xRaV4MhHtInhu0lvLDjCRWNESbfq7DtURVzmijquNolurer2BtUpj0oM1CtkneSRH8VNK1QyZoZ3odfS/RWQs484cs1+ibhXJ80Np6Qy0B0sp2A14gp0ci4W2U6NqkMO0ti0x8UuncKF/zyyyS6tol9drZIGMoAVJAEsYpKE9vKmSPR9L3KqJslEool9NHh7008eHpgyh9k4grFYyOuFrFIGdMk8DuJ6nmXWecAoy8Dhh3jTACkjhA/h6NpDRz8BlKGw4gLBCnb/a5ot1rHHk3aQgFRztPoYc974n2MvEhMSR4OZ2f4p0v4k+n//dmCcxNj2WZzMzfxSFKwvMfGS609PFGSzTnpCUc8l6LX0eTxk6DTcndBOpsHXSwOT10ewjlpCfzYZ2deuGVnCwTZMOBkYlwUsxJiuCwjiZX9duYkxrDN5sIoS6QYdLR7/awZEDeMjxRn0uj2MyEmivwoI1PjLTR7fFwUjlCaGBeNWSOTqtfx4LBMLs1MptBsoHTdHuxBhVtyUjg5OZaFyXFoJIlUgz5ipuoIhljT72DzgJjG3G53sSQ1PqIhi9VqODM1Ho+iUBb2MVuYHEfV9Ap0EqwbcDAuJoqAquJXVBRJJaiqbLO5Wd4rqvVLc1OZkxjDo8VZpOm17HN6GB1jZkxsFO919lO2fh9PlmZHtGVbbS4GgyHWhJMAjkOgrd/LlhrbUY97/QpbamxMGMZ/hIwFg0FCoRCGn8WHGQwGduzY8W/f3s9xnIgdhr+truPhb6u495RyLpmSS4rFSHWngxdWi3idU0Zaj5iMHJ+bQH2Pi5HhPMuX19bzwPID3HVSaYS0bW7ox+ENMrM4JSJS3940wMFuJ5IkdFJpsRrK0mO4cFI2WllmWEo017+7g1XV3bx8yXi8gRBP/ngQgNFZ8cwsSaEwJZorp+eTlxTFFW9so6nPzU2zisiMN2ExaiNk6bRRGays6mZ3q41zXtzEZ9dNYVllG7d8UMl7W5r59hYxQn/V9HyqOh3s67Dz8tp6fj2vmCfOHcXS93fx0LdVvHzxWOaVpTIh7KI/4PIz57HVBBWVd66ciEaWKE2PYXvTAJ02L4oK04clR0LOFUVlT+sgIUVFklSumVHAhLwEllV2sKGuj+Z+N9t/Nxe9VkaWJa54fSv72u28fPE4PIEgb25soqrTwde7O7h9QTHegJi4NOk0GHQy6bFG7J4AGfHiRKqRJfKSojjj+Q1EG7Rsvms2ZdYY8pOjeHFNHZ/vbOfqE/LQyhBr0nPOlAwqN/gAA6bwzf6c0hSiDRpSY4yc/beN/GZ+MZ9eP5VnfjrI31bXR/Rq8Zkyv1k3jUl/lDj4oYpvAPT1JqyxRjrsXh746gBPnTMabz9UTIyLfH8unJTDhZNysHsDnP23jUQbtNx+wxgsaTo+Dk+lBnK9nHiexIZ7BaEqvTgsKM+V0RgUEsOCdFVVaV8P0Rki6NrZrlL1rmg1agygu7+LZ/Y0YmooYUJeAqUXytgaFMwpsGppiJHXy8haCPqEfrx7h4qzVRi1zntFxCH5BoUYPrFM/LSuUal+T2HMzTJpE8R+ZM+SyZ4l4phATDMegta2mwVXLkOVtEhJ94dNYAVXyVso4Xeq5MwVRGvi3RIBt3DI792j0vC10LvnnzzUnii9UKb0wiP/hvv2q6gqjLgGUsYMLXuoCio+LDOkVoDPAZaMo08EAI2rwd13tGN+OEIs8ru/XsQQBFww/Jyj17P9JaEnG3mx2KanX4iatr8MWZOHTGCjraC3iAraLzn0/zdxTnoCZ6XFs6LPTovXH6n2HHB5UCHiL9bs8eFVVIZFGfloVAF/qmvn+ZZunijJZnq8hUcbO7nImkhFuNX2Ta+N7XY3B1xebs5N44DLyyabK7KuMTFmbshOocHj45QdB9EeZgb7QnkO9mCIDIOe26pbebejjz1Th6OVJawGPUtS4rAFQ9gCIZbsrCVJp2X9xBK+6B5gSlw0t+Wms3bAwUXWJHoDQS7f08CmQScPFw95QF63v4kVfXauyEhiQXIcA4EgK/vszAwTxy5/gCdLsyMu+ocQo9VwR3ULb4SjkJ4ozWb1hBJavT5q3V5OTLBwVWYS2UYDceGq24XWRG6vbuHN9j4utibycHEWdW4fKtDgHqri/yo7hWS99ihD1//LUFWV3Y1/n5juaXRgjTf829uU0dHRjB49mueee478/HySkpL46quv2LVrF9nZf2cy+t+E40TsMOxpFVNrhzRJAKOz41lQnkZitJ4Uy5Fs+b7F5dy3eMhNe2+bDVWFve1Dr3/z8gnsbbNx+pihE/7YnHgePXMEe9vtdDu8pMUa+amqm/3tdpbOHUZ9jwtFhdYBD22DHpKi9dxzchmVLYM8/G0VD39XxU+3nkhWgpkTi1NYVJHOyupuvtrTjoTEQ99WMa0wibevnEhDn4usBDOVrTbsngCyLGEMnzQ8/hAfb2/l9NEZnDAsmROKkvlkRyvtNi8fbG1myegM3s1LoNfpQ1Hh+/1d/HCgi8WjrNg9gUgc0RsbGkmPM9HS7+bqt7aTFK3n/asnMSl/qOR+7oub2NNm56ZZhei1Mvcu20duopnXLhvP8t3tTMhLjASah8JVKF9QYU/rIH9bU0+yxcAd84tZX9fHaaMyMGg1fL6zjWlFSTh9QbodPkKKyklPruXOk0rYe998mvtdnPrseuKjdHTaPQy3xqDVyLyxoYm2QQ+13S42/HY2Rr2GM57bQK3i5MHfjyRvZibvbm7m6Z9qGZEZy8qqbrY09vPB1hb+evZIfntSKY19br6obGdCfgLn35fNU9/XcuXWDu67eAQVNTHkLdRy1d58/vDlfna32djwe2E4OuFOiZx5ghTYPAHe2dxEWoyBLY1ievO+27xkJEZxlS+P97c2s7fdRluPF7/NgKyDuLAHV9JwiSXLZaRw9bB1NWz6g4IuGk5dJlP7mUr3DmFVMetpmUs+aGJr0wDvb21mQl4CcYUSC97Q8P3lIWwNsP53Cgtel5n7gozGIFqDkgzDzhVeY5IGxv3mSB1Xw3KF/irRUjxExECYw1a9rzLuNxJ5Jx32mpThdG1ysfvr8RQFFLLnSHx/hYK7B2Y/JzP3RbGsqqpkzxl6XVQ6mFJE167uC5XEcpWGr1VMSRIjb5COOCk3/yh8yVQFhp09tGnfoIqnT0xEIslQcf7Qk301QjSfNwuMsWKyofZb8VziMEgdPrRs7gxIKIKoMFvPGCdakr9kY3FImBfyDsUb7ftQDAGoyhAR8w4I8Z/fKUidJu7Y6/tv4u32Pm6vaaXAZGD9JFExerY0h3WDTk5KiqU/EOTErdX4FIUfxxdTEmXi9bY+/KrKyn4HawYcLOsepNXr52JrEj2BACcnx7FhwBmxhZgYG8UfC63EarU819LNOx39nJuWwO15aVi0GqI0MmaNTJPHxxddg8xPiiVBp8UgSyTrdWjCh1MrSzxfnku920ezx4dWAotW5taqFr7qtfGOvo/KqcMjoeHLe2y0+QJ812vj3kIry7pFQHhS+HyXbzZglGXuqe3CJMs0zBjBy609/O5gG2elxTM+JgpbMMSN2SmR79Qh89j48E1XhlHH/G3VOEIKH4ws4P6io73BosIdgEO/XyjPYYvNxdzDRP7RWs0R7d3jQGjCDmtHHgsev0KvPUBy7L//ZuXhhx/mrrvu4oQTTkCj0VBWVsaiRYvYt2/fv31bP8dxInYY/nhqOaOy4tjS2MdbGxu5aHIu0QYtf7vo2C7wP8d9i8uZUpjE3NIhYV+ZNYYyawx722z85Zsqzh6fxeKRViRJ4vUNjXyyvZU9f5jPO5ub2dE8yPtbW3j63NFkJ5pp6/cw9S8/MaUgkXevmkSPw8eq6m5UiPiNaWSJpGg9bn+IVdU9nDZKED63X8T7XPvWdnxBhRtmFnDZ1DwCIYVN9X2cPS6TZbva+c1HlRi0MqeMtPLQGRVcPDmH05/fwMfbW9FrZFBhemESo7PjKUiOIiFKzzM/1fLmxiZumlVIVoKZ2z7eDcDjZ48M748IxfYFQ9z7xT5iTTrqep34QwoFKdGkWoyY9RqyEszsbrVR2+OitsfF708p462NTexqGeTJc0dx16d7eHZVHUFFpcfh4/2tLTx85kiscSaW7+lgT5uNR76t5pVLx/POlRN55LtqtjcN0NTvxqTXUJwWw+Y75/DR9hZm/3UNi0daefycUfSFPb5yEs2kxBhp36BSSBx1spOUNB31PU7WHhRB3DFGHcGQQrRBy+KRIhnhYJeDnnDQe7fdhyRJfFLZSnO/mw39XaiJXaRXmbhwUo6YcM2Io/pmcbz8h93wPbeqlhdW11OWHsO547P4YGsLDyw/wHUnFnLxq5txeoMoKnjzPUy6x4gxSeKgzcFFj21mbE48L148jv1vKnRsUik+W0JjhJhcYTAcVyBc5ZPKwRArcdv8Yj77oYvJKwrY3a9QcY0gMAVLJHY8puLpBmcbkVaeo1nwBK0edj6pUveFyuibJAqXyHTvVNlwr0LqWMg/RTrKdX7goPAhs9UBXpsgPgYLGCy0NM5isEml5mOV9Mng6RMcxTcoXlv1nsKel1VG3yhFqmmmJImTP9BQ9a7CnpdEZVAsr1JygfD+OoTicyRUhUirFASx++FqBU+P0NMdThoBqP4qHK5pFG73WmPYMb8PEo/hmB8zpPFEo4e8mUcvcwjDzxdCfkV4zhEKgLNb9HsPN3SNzRIVNY0BjHGiIudoh5JTI2kA/w5kGfVoJcgz6VnZZ2eExUyKQcfpqeJD3GZzIgE6ScIQttx4ojSbnXYXp6XEkWHQ0eLxszglnsv2NqACH48y8GpFHh909FOxfi+/zUvn6iyhbW30iL+TVIOOJq8fRzBEtCwRpZF5oWWA5b02Kh1utk8pp3JKOSaNfASxXjfg4KxddWQa9WybVIZPVZm4SUw7T4w9sn17kTWRkKoyPjaKRxs6eb6lhylx0Xw8qoDf5qeTZtBR5/ZSYDKQotfiCSkMBETlud0b4PZO4bU2LjYqkpN5R34651sTyTQICYdWkrBoNHgUlbhjTEmCsKy40JpIflhzl6zXsehn7dzjOBreQOjfutx/FdnZ2bz99tu43W6cTicpKSnccsstZGUdnbDz78ZxInYYEqMNyLLED/u72VjXz0WTc494fm+bjYe+reKscVlHCO5BTMVpNRJnjzvyoPU5fSRE6flwWwvranuxeQIsHmmlJN1CQpSesTnxfLu3k/ZBDycUJXHz7CJkWWJERiyN4UBqp0+cLJItBtbePotHvq9i+sMreeTMkcQYtbQMeLh6eh7nTsgmPzmaA5123trYxM3v7+T0MZnsbB7gzLFZJEUb2NrYz+sbGgGYkJtAfa+T4jRRHtdqZIZnxDKlIJH6Hhd9Tj9bGvvZ1tTP704u48dbTwTgste2AOANKiweZeWVdQ30OHyUW2PZdOdsLEaRy3jei5vY0TwIwLtXTsQTCDG7NJVV1d24/SHW1fZy/6nlzCtLZViqBaNOw0PfVkXsH0KqyJd8cMlwnvrxIHvb7by3pYk7Tipl8UgrO5oG+LGqm8qWQSblJ/LaZePZUNvHjGFDd5qxZl3kD3dXyyBLnltPfnI0zf1uhmfE0rJKZdMfFOZbhvPAu6UkROu5+NUtrKnpYeHwNH5/ShnTH1pJQFHpc/lp6Xez8Km1qKrKo2eNYMlocUf8yJkjWF3TQ6rFyN3hQPgFw9M4Y2wmXdtVPN3iTi/jBCJZpGOz4yMTlaeOsqICzf0e9rXbsHuCxJq0PHXuGFFZzBeve/mLevpcfjbWiSnU2s9FK9TZISYCA25BPAZqRDHGJrrqjM1JIC4ljh0HVQ42qNR8pDL8SomYbImYXBXr5CESBjBmqcRAlTBnXX9POLS8K/yd3q8ScAiiteBNcbF2dajseEIhbaLEhN+GcyAnDsCGJ4Q1w9TfgD6a0oskBg6qDB6EnU/BnOdlvAMijglEmDeKCCTf/1aIojMkSi+QGaxT6duvYk6BzBmgqkLUf8j76xDMKRJjbj7yMUmSRLdPFhOYRyF7KnTugrSRQ48dyzE/6BU6L23YfFX+hWnL3mro3gv5s0W1baAOXF1CQ+azg0MYAmOIFkRV1gpNWNoo8bgSgtrvAFVU5Kz/3I3gP4OZiTFUT6vgtbZezttdz4TYKJaNEZPciqpyyd5G3CGFh4dlkheONxplMfN8czcPNXRwf1EmMxNj8PtDrNcY2WMU05cAP/Xb6fEHWdFnjwjQb89L4yJrIlajnvWH9FBhonVOugj3np8kKkVvtvexbsDBo8VZkcGBQx1gRVVJNehQgSUpcfT4AzxUfOS51qiRuTZbEMBmrx+tJPZdliTSwkSqwGzEotWw0ebi5gNNPFycxeS46EiEkj0QYni0iaCiRrSqhwv2FVW0MkOI3MmRMUeTZEmSIpOUx/HPw/h3TG//leX+VZjNZsxmMzabjXXr1nHbbbf9R7cHx4nYUVg80hq5sP8cH21rYe3BXgbc/iOIWH2PkwVPrEWvlVlz+8xI5uObGxv5/Rf7uGBiNldOz8fpDbIk3KIst8ay4x5xsr/stS0c7HYyLNXCsFQL9T1OFj61FotRx9tXToyYrYIgFo29blRVRBOtPdjLgQ47ISWZe5ft444FJYzIiEWSxNTm/acd1lYBjDoZjSRh1Mu8cdl4TIYjvwIaWeKUEVZu/2Q3q2t6mDEsmelFSejCZfbr39nO1sZ+7lhQwmVTczFoNXQ7fPS7/Kw52MOV0/PpdnhZX9sbIWGnjbIypXAoe25YqgWDVsQTgcSLYQsNly/I4pFWvIEQi0damV2awoArQEVmLFkJZl5d18Bbm5qpbLXxwdWTeWVdAx02D7d9XMkbl08gPdbEnNIUzn1xE+2DHj66bgqt/W6CIZU3L5/ADe9sp7nfze8WlXLZ1Dw8gRDvDDYhWxIpyDaTEC2O24LyNOq6ncwtT2XRU+tAgjNGZ/DbT/cwKjOOKIMWVYUThiXzZWU7d322hxtmFnLtiQVMe+gnJAQJO5Q52hZj4/PxDZxsycWUEMebnzeypaEfTyAEkiCbZ4/LoiA5muEZsSRG66nqsPP2pmZeXS/C3AEeXH6A5n43s0tSuGm2uHiOu02ibplKVLrKpj+IzzehWBJRRWuE/9ch5MyV6N+v0r4R/HboP6DStCaEvVGO+HcB9O1T2PB74c2VMkZiwp0yvXsguUJcFYedKaGLgu6dKl+eGWLq/TLdu1Q6t4hqWP4iicThElrDIUKkRq6oUWkSGdOFsawuCizZEpZwVy/kV/H2D7Uiu3dAx0aV0gtg/xsK7evBOgVGXv9fPxHPeVEm0N2NufkV2JkeFumHkTlR/Pwcjg5BkAwxQ//vC4d6Fs4HU/zRrwFRAXOFq15Zk4VGLDIlmQjDzxWVMY0BNjwqqmpTbxOVOBAEr+gk6NghNGX/ZkRpNRFiknpYJJAsSUyOjabS4Wb8YdWmtQMO9jg91Hl8mGSZ2YkxFCxr5o79fcSdkk90eB0LEmNZ1j1Im9cPCLuJedtq6PEH+HbsMKbGW1g7sYR4rZa+QJBknZaXhudGtvN0UxeOkMJ3vXaKo4zcfbCVSzOS+GHcMNYNOKn3+Gjy+PmyZ5C5ibHCv6zfwWV7GzgzNf4IXdiS1HhOS4k7ppZoXKyZ3Q43y3psSJLEC+ViH14M/95hc3HGrjrGx5r5cJSoiNa5vdxV08aC5FjOTEvggMtzxGd0HP99JMXoMOrlv9ueNOllkmJ0v/j8fwdr14ob7Ly8PJqbm3n44YfJz8/n9NNP/49s73AcJ2I/Q7LFwFPnjT7mc5dOzcPmCbBkzJG6AFkS2XqyBDa3n2d+qmVaUSIdNiF+7bB5yUuKIivBzB++3M9DZ1QQDKmMyo7DoNXwm/nFWONMXDolFwBPIIQ/qODyBnh/SzPZCWZuXzA0Ev/YOSPZWNfH/PI0xmTH8cmONpr6XNR0OclJbOZPp1WwaEQ65p950/iCIZbv6URRVWQkXlnfwMb6Ph5cUoEvqPD5zjYumpzDl5Ui77G2x0GHzUev0xfJ1tzS0I/TFyLOrIvcmTx0RgVf7GznlHDr7sKXN1PT5aQgOYq6HhcDbj+3f1zJjTMLeXB5FVnxpvA0pEqX3UtuOGj7ke+q+XRnGycWJxNn1hFr0kX8uEZmxXH6mExWVvegqnD1W9tQFIVQSKWmy8nO5kHSK0y4/CF2tQwSDIeP37tsH90OH2eNzSQz3syBTgctAx40ssTTPx3khU31lM6ysPzm6XTZvdz8/k7KrbGs/+0sbJ4Av/98H4oKuclR+IMKTf0uPp4+k4F9EvGyhm1N/bj9ITbV93HR5BwhjpdF5uYfvtzPfYvLeW7DQdbL3UTlhDhPM45b5hSxtbGfPa027l5UwuySVAZWaknvTSblImHXUJwWg8qQcTDAeRn5fNbQwam9xYwMG/oGnNC5CXr3QsZ00fqMK4CmH0RYd9ta4Lfi9VqThKdPkLDoDBizVOamv+4nJSEeZwGMJxO/Q2X1rYKEyQaoel8hZZSYfFx/l8romxRy5koUnCJx4B1hX9G3XyV3voSjWcQrrbldoXc3jL4plqj4paSOk5ENFtrWiapW2UUS2bMkotKP/Pvy9guLDoCSC4TbftADqqKSt1DG06eQd/J/MYfR3gYtG9BlTUFn6hMf0IBX9F3/XqbjQANsf1GYmU3/rahaxeVAwTxBmH6JhIGYqGxeD0iizTjyZxMFhypvzi6xH0poqPRzCLHZgtA5OyF9tLC5+DfizLQETkyIiWifDuGdkflHLXtWWgJd/gD1bh9PNXfzVY+NZeHc2UNDGQAKKirCnBTAE1JocPvwqyodvgDZJgOFZiNr+x2cu7uO8mgT348rjrz+keIsNg46OTMtnocbOjno9vFp1wCDgRCPNHbyUVc/56cnElSh1i3+LiodbtwhhU2Drsh6bq9uYeOgk1eG5zEsykiXL0CsVoMxfDP5p6JM0g167q9rJ8eoJ6Co6GSJdQMODrp9mGUJj6Kw1+mJrPPzrkFWDzg46PayY8qQLvhwPN3UhSMY4o789KOE/8fxjyFJEiNyLcecmjyEilzLf8xPzOFw8Nhjj9HZ2UlcXBzz5s1j6dKl6HT/GeJ3OI4Tsf8C8pKieOLco0laVoKZ608sID85mm/2ibbTV7vbWf/bWUzITWBMjjhpf7qzlZZ+jxBwt9o4b0I2fz69gnJrLA8sGXLbL7fGsvzm6exqHuS3n4or0+XT8kiKFuX6FIuRsvQYWgc8LBiezoLh6ayp6eHTHa1cPjWPQbefp36sZWphIrMP06u9uaGJ51fVkR5r5MNrJnPqs+vpd/l54oca6ntdVLbaaB/0sLZWRH2cPMLKO5ubI5OSAG9cPoF97XZOH51BbbeT1BgDWxr6+WpPB0jwzPljSI0xcrDLSVK0gboeF2sO9qKqgrB+u0+YLL535US8QYXR2fEEQgo6jUxZusjaLEyOZsYjq/AFQ3x903Q+3dHKg8uruGFmAd8vPYF4s47Jf/6RoAI3zCwgSq9lS0M/+9ptzCtLJTfJTHa8mZve30mUQYs11shH21sjRozW8ORrSaogMwc6HexoHqCpz82m+n421ffzzd4OXrhwHC9dMo5Om5dTR1kpTrVQlGqh8jKZgBPi0lVuO6mEohQLc8pSiTHqWHHrDN7c0MQzK2v5ancHk/ITInqyQ8Me43MTKE6zcLDLQXOfB1efQtVfxQUtsUwibQKMrs7khlYjC08asho4IZBFUlUm/f1umvvcZCeaicmW0JpUEophyh+HLqo588DVKUT9A9UqPhsE3NC1TWQujrlFxhgvIRX7eCdUyXPDhO2CRi8ilHyDQuy+/3VRlbKG/Uw7t6rsekYlZQxM/ZNM3z6V/JOFe/34O8QHfPBjcSGu+QhcHbEMv0Ki9ELY8qBC0CPMWgtPGyJBAZfK7hdU4otg4u8kgh4wJkgofgVnG9R9qWJKlJj97D9ZCXN2CnPVrEnQ8BP07BdtxREXCJd8c/KRJMwzAN5BiM8TbcU974kKliQLJ/xIsLos9GAhP2z9mzBpHXOFyIk8HGoobAS7H4oW/PJ+egcEAUsoPHodGgPE5YIpkSNEcP9G/NxE9JueQe6rbefGnBQusibR5vXzalsvZ6TGc3teOjvtbqpcXk5LiSNhTDLBbjdKehRvtvUyMS6aM9ISSDXoKAi3NF9p7WVmooWz0xKOiDAaDIYIqdDrC7DT7qYiWljWnJBg4ZQUYT9xS04q0RqZU1Li6PEHMWtkJsZGc4k1kWqXlzHhic2rM5NJ0GmZFBfFlkEnBWYjn3YN4AwpbBp00uULcE6lIH0/jB8ifTdkp3BhegJ/qGsnd00lfyvL5Yb9TfhVledLs3mpPJdhUUPtxQutibT6/Mw5THB/OJo8Ph445EWWGBPRmB3Hfw0ZCUYmDOMoHzGTXqbiP+gjBrBw4UIWLlz4H1v/38NxIvZvwDd7O3h8xUF0GollN05lxf4uZpemotPIRxiyPnb2KNbW9ODwBdndasNiHPr4P9/ZRrLFwNTCJNoHPVz0yhYSo/ScPS6LzHhThIQBNPcJnZKExPvXTGK4NVZMPYa1UX9bXcer6xtYVtnOujuSWPDEGpy+IPefNpxog5bpRUlkJZi5/9ThvLO5ic92tWPSaciMNyHLEjfOKqTf5efXc4u5e9GRfkfl1liiDVpeWFPPI99VU5xq4dTRok17qCX72qXjOffFTWxt7OeuhSX4gwp72mxcP7OAHc0D1HQ5Wb63k5vnFDHlLz+hlSW+u+UEWgbcjMiIZWZJMq+ub0BRiSQMADT2uRmWaqGl340syZh0wjessc/FGc9vBKDH4aO224XXrxAIqQRDKlqjRJRevL+XLxlPVoI4ic8tT0WnkQiEVN7Z1MwDSyqo7nLw3uZm2ge9bKzr5emfanH4gph1GiwmHbmJZlxLVLp3qKRNlLCYdZw/Koddz6g4cxV0Zj0jvizkrmlmehMcXPv2kAfNoalQSZL44oZp/Onr/by2vpHKlkHuPHEynVug/muF1PEynZsgty2J4H4JZojXl5wv8cq+Wn4KtrDj+wSeOm808cUSi7+QcHcO3SXufEqhdY3K5PtkYnNh2ekKSgBG/0oSk5eFEGWFH68Pcd3w0Tz0uxC77tHwVVuImU/IzHpGonsnJI0Qov34YSJEu2umit8uiJmrU7RAE4olVEVl3+sKshaGnSWIlCEO4ouFNCo6PDCcvxgav4Wm71WyZ6noY8ITn2tU6r9UQYYTH5eo/xKKz4HJf5Dx21S2P6aCpHLKxzLGhPD7bN0s/LyKTjq6rVj7PfQeENWvzImCgWZMEETq57FEqgpbnhWTiiMvEhW0kA9cPTD1dlH9+rkWzGcHW5P4t6cfdD+zwMiaInxAko9ROek5IGwzMsaLihiqGAr4OXa+KvY/Y4LYvr0N2jZD1lSI/s+4fH/ba6fJ6+erbhsXWZN4rLGTdzr62WF38dnoIkbHmFk1oYQ323q5orqZ+4sy+Ly1hz/Vd1BoNrBuYmnEm6vXH+SRRnHTdcFhLvxtXj+zEi18OaaIt9v7OGl7DVdkJDEhLopr9zVxUlIsr1bkkWrQcXeBlQfr2tk46GLl+GJyTAZ+6rPzZnsf70h9LEyJI0ar4UJrIu+29/Hr6hbKo428OjyPXQ43Z6cl8GO/HYUhJ/3DEavTst/pJRSusM1JjBExSDFR5JuPnJBPNeh4vOSXbQwyjXouSE/AHlQiMUrH8a8hI8GINd7w/9xZ//9LHCdi/waMyIijIDmK4jQLpemxfHr91GMuNz43gfG5CaiqyqVTcskOE4L1tb3c8sEuNLLE9t/NoX3QQ4/DR7/TzztXTiTxMBL244EuDnTYwxorOP25DZxYnMzrl03g+32d1PW4mFmSzA/7u5hVksLBLgeNYSKjKCp7/zA/sq5FI9LJSjBx7oubGJkZR7RRy6c72jh1lDWSRflzBEIKpzy9DnvY50pRVa4/sZDTRmXg8Qf51Xs7OX10BgNuP4oKcWb9EQMMJxQlU9PlxKCVGXQH6HP5kCUJhy/AGxsasXuDHOhw8N5VkwiEVNJijNw0u4jpRUlkxpvxB5WIKaskSQRDKtsaB5iUn0BxqoVrZxRg1GlYMDwNg1bDcysP8mNVD9OLknjriiMv2G0DHlItRloHPUwrSsKk13DnSaXML0/jw60trKzuJtqoJaAoPPHjQfZ32Lnn5DKuuDyPlVO6uemHRm6eM4yEmhhWrO9l94FOTtXlozloYmy5lfOrhclseoyRe08po77XxZzHVvOX0ysYl5vArJIUvt/XxfzhaaS6JFpXqbStg/6+ICN+LbPjAaHD8g6oVDttpMcamX6+mR+XhVhW2c7UwkTOGZ/Ntoeg+UeFEddJFJ8tTFK9fbDvdYVpf5KIzhCh2WkTJXLmi+nKhq9V+g8IMf/wy3T07lFQg2BvhIZvVNrWQuESYf6qhlSUoPAIU1WVaKtEjNUF7TWQUs7AQT373xDHJKliaOJy2FkyWTNVtj2qMlirUHy2TM0HCv02GKiB1DAnSp8oYZ0ich/3vylinFRFhHV7B8RAgiEO9IcXI/prBWEaqD+aiFnHiApX+mghdk/8BcNW8SUSE51BLyiKsKcwWCC+QFhZHAvmJGFFEQpGcjOPgCFGTDv+HH4XVL4FqCK7Mnua2MaxrC/MSYJAGuPE/+u+F/q0oPdI641/I+7IS8Nq0LEkPEG5KDmOLTYXZ6QeafL6UEMnfYEgY2LMjI4xY9HITI6LZmWfnU+6Brg1N408s4FbclJYN+BEF76Aru53cF5lHcVRRlZOKGFZtzBT1koSnb4AKtDuO5IwvdLWiyuk8FO/g8syDJREGSk0G4jSyOy0u5iRIL4Uh5z6g4rKr6ubuTU3DaNGpshsRAL6A0G6fAFSw9q4dzv6iNNqeHl4LlttLhYlx6KXf7lV3ezxsd3u5uTkOHTHCOfWSBJ//TtE7Tj+a5Ak6T9iUfE/FceJ2L+ILyvb2d9h5+bZRWQnmiMThf8If/2+mpfXNvDoWSPJSRTaKKNOxmLUkpNoJsqgZViaBa0sXN3re10RIubwBrj6re2EFJWnzhtNp83Dg8ursHsC+IIhrntnByFFxe4JcMW0PBZWpDPo9hNrEhYM43ITjtqfEZlx7LlvPh9ua+HeL/YRpddEpg4PtQxBTH+e9tx6jFqZJIsBX1DhiXNGMrVILGuNM3HvF3v5srKd+h4nb14+kVXV3Zw5JpPtTQNsqu/j0im5nDAsmW/2dpIWa6QwJZqPrpmMRpao7XZi9waxGLWcMz4Li1FH64CbaQ+txKCVuWZGAde+vYP55an8blEZr1w6jvzkaGq6Hfz5myokCZ49fwzt7+kY/10phXfJhAq8bG4YwKzXsHSOuBjf9dkevtjZxgsXjeOnqm5aBz0Up1k4Paz7C/lVEvbHMtjWxMb2fhYMT+PhM0dw64eV7O+wRwT4z66sZVvTAPFmPX9ZNJJvyqtoVhzklWg5s7yEknMlZn6Xwt52G29cPoGC5GgWPLGG2m4nKw50U2qMx3FfAn/JnMHU6RLLzhBEJm6Rl8mPr6E0JpYLmwTBWLami9s3bictxsimu2bzwdYWNtX34/KFIvsMQ0HZY26RWHuHIDQ9eyTmvSIsHWTt0AUkZ66YgkwoldCaJCb9XsI3qNL8k8JgnVgmyiomMFdcp+BoEX5kcYWidcrOjwQxcLQRW3AyWTNF9uP2x1Um3C2E+ollEnteEhOWXdtUKq6SGXe7hLcfUg4zoDcmSEx9QFSdOjaqoCoUnHrIJV9i3ivHaEkGw/qdYxmypgwXPz9HX42opOXNOpJATbgBdr0Fe96BsjP/cb5jwCPahbFZRz++6zXR3x15SbiteRi0RtGG9NkhOkVUug5NSv4cY68Urc9D5q4ZE8R7/meCxv9FWI167sgfEu7NSoxh1jFacfcWWlnV7+CstATSDDoOniDSB+ZurWaP00OMVsODwzIpizbzRFM3l+5toHb6CDwhBQVwhvVlfyjM4LzUBPJ6/ehTLQwzGxluObJFe2pKHLsdHhaGJyutRj1vVOQxbXMV51bWs35iKflmA4uS49gxpYzfH2zjyx4b3/baOC89kSiNjEUrY5BlDGECtWXQya+rWpCAHVPKIsTz7+GyvQ3sc3ppzffzq5z/bO7gcfzfw3Ei9i8gpKjc8sEuQopKYXI0Z4w92tTvcKyq7ubznW3cMmdYZFpuR/MAi0aIk97rG5pweIOkxRjRacQ0oTXOyIDLT4rFgNsvqkSjMmOZWZxMc7+b8bnxRBuS6bL5WDLGikGrYfFIK/vabTy/WlxJv7xxGg5fgDtPKmHxKOtR4n2A/e12VlZ3s7/Djj+kMKskjdPHZPKbjyr5bGcbz18whnnlaexps9HS70ECfvrNDL7b28m7W1ooTY8lJhyTdO6EbBr73Jw1LpPHfqjhkx2ttA16+GJXO22DHiRJ+G61DXr4fGcbV07PZ1xuAl12byQb02LURvbTG1DwBEIEQgpNfeJ5myfAvMfXEFQUvrvlBMrSYxiVFUdqjIE4s55tGxW8fdC9S8WQEcTtD4pKY1M/eq3MloZ+XP4Qla2DXDQ5hx6nj1NHWrnmrW0c6HBwT+w4Bt83owzXIUVBSZqFGKOO0Vlx/LC/i+/3d7K3zcbO5gGiDRphKdLSzbWn5vLR9hbOmW1lZJYgrz/3n1tYkU7boIe0GAO2OpHR6O4WhR1jrLCbCBV78a9VkLrEZyrrIK1Ii2azRIxJfC7PnTGWr550MPpAPEyDCXfJ9FQKywp7s4rPLoiZxggJpSDJ0hGSKFVVOfC2StAD6ZOE7mvjfSpx+SJm6dBrXe2iMuVsFyTP3SPamuJApUPfQYhOR6OXmHAnfHqSyHM88KaKIV4lZYwsfL4SIDZfaMEiBq87XxftvTFXRXy5fINi36f8UUYXdYw2RMAj/LUSi4Ye+3nbsG6FIFzlZ0JUypHPNayCwQbhXl9+mNtrwCMOBIiK0z/CrtfA1gKlSwRBOgR3r3gcRPvRfNiNj71dTGCOufwfr18JQVelqJQdEumnlA+Zv/5/jLPTEiJRPYdjdmIMiqpyXjgmqTzaiNWgozTKhFdRWN47yOUZSSzNFURGliSs6zrpW9OGeXQKM88pPmJ97pDCux1ianTjoIvTUgUpTdBpsYYrW4cPG6Qb9NxbmEFRlJFZCTHcVdPKSUmxbJ9cjixBlEYsW2A2UhZlJE6njRi2AjzT1MWnXQM8WpLFmJgjJyJLo0xUu7wRq44fem38ub6DG3NSIx5sx3Ec/yqOE7F/ARpZ4uLJOexrs0cClv8eHvmumn3tduLMeh49aySrqrs5bfTQHfn88lR2tQwwv1zEAW1vHKBlwENmnImcxCiueH0rP1Z1c9v8Yl6+ZDyqKmJc/vJtFa+sb6CydZCPr5vC4+eMwuMPcdYLG3CFJxuXPLeeoKKSFmtEliRWVfdww8yCSJXt1x/uoqrTweVTc7nvlDIWVghyWNVpJ6SoHOx2Mq8c1h4UAv6UGAPZCVG8ur6RboePr3a3c+MscWEsTY/hjcvFhWlVlTBEbRlwc/KIdL7Z28mUgiQy4kz8WNXN3nY73+zpYEphEnMeW43HH2J2SQo/VnVz/1di2rAwJZrlN03nyR9reGdzC2eNy+SW2UUsfGotfi/8+sNKXrt0PJ/fIFrBP+zvouV0L9OcmRQsltCZLXxxwzR+2N/FA8urSIzW88HVk9jSMMDpYzIwaGUy4kysqOpixYFuQopKe7adKI2Z7ngnql9EUMHQ9OJ3+7oOG3CTeGFNPS+va2DPffNYWJHGD/u7yE2MItasY7BWxVavkj1bQtJIHOx24vAGWVfbxyUX5zL2VomodAldlMTcl8REoSU7gVft04kO6Wk9IHTleWlRPHR6BUV1aXx1VojsuVpMa+OoQqXkPBVdtETHBpW6ZSrd21WGnSODpBCbRyR/8XA426DqXfEmMk+U8NuFd1fADSOvl2jfqNKzE7p2qMgamdnPyri7hH3W5gcUis+ViCtcgJo7l/ZNMnEalag0iakPyHTvVKj5AGgSwwKxeRLxw2DVLQrmNJWT3gqnAdiaBOlxdUaI2PbHFNrWQu8iGPcbCToroXktFCwQxqotG6FptSApk24RFhE/r0q1bhJ6r97qo4lY3onQahI6q8NRv0K0MqPThafYIagKNK0VNhQZ44ceP2RGJv+s4hWbBSVLxPs6VLED0T7d/pJYz/Q7xQRm9z5o3w6F8yA67cj1tGwQE5Pm5KHAcBAVsqDvP5JD+d9Fty/A081dhFQIhKUDBWZjZMLw864BPuwUrcjfFRzmwRj+W5IMR1c9DbLETdkp1Lp9zEgYigKK12nZOlloV2VJYo/DzR01rZyeGs+VmcncnpfOA3XtvNrWy9oBRyRz8hAS9VpeHJ7LJ50D9PmDWMM+Ye939lPr9vF9r/0oIvZMWQ6Pl2RH2pKfdw+y3+Xlo87+40TsOP7bOE7E/kXce8o/f3d69Qn5fLy9lbPGZZKVYD7KKPbkEVZOHjF0cgoqgmgpqqheGPXiJGXWa/AGQpz89DoGXH5unVdMtEHLxPyhu9OaLgcaWebyadlY40yMy42npd9DQXI05720idYBD7EmHTfPKSKkqGTEm+hx+JhTmnqE19ffLhzL9qYBqjoczP7rKq6dUUCsSUeX3cdjP1Rz7ynlrK7p5uzxx3YdHpMTx8c7WvluXxfV9y/gzoVDJ8OY8JDCwW4nUwoT0coSEhAdFrOvrOqmdcDNM+ePoTjNgil815oUbSAj3sz7V0/ipCfXsatlkN1tNmYMS6bf5eeat7ahqPD2FVGUmJOo7XYgyzCrNIXnV9cy4PLTOuCJZH629Lv5W7h6eAilE42MP1vmBOdIVtX0RIjpXYtKmVGczAdbW6ntdnDjrELSYozc+mElJWkxmHQafvvJHpZVtrNxdB+PnTOKNbcp+AbF9TNvocQdC4rJSzRTuMXKF4sVpj0ok1QhTuy9e2HNb1T0MSp+exR9Esx7VcKSIbHw2a1UdTr4c3cC2l4jPptKwWKJqAzY+rDCQA0UnythShIh3qYkWPS+TMin0lOpRsxSDyHaCkVnSgTdIutRM0LGnKISZQVTokTBYpWGb1QSy2Dvqwqx+RJZJ0qs/nWI7p1iHRPvlqhfLrHjcYXoTJj1jMyeFxX0MTBmKcgaidg8sd2QX3CakBdQ4cA7CjUf3MXYy5vJTBsyOosrkGhbpw5V3dq3CpF6xw5BxJJLhFFqSrmoav2chIGYihxsOHYL75f0YknFgrj93Dh1oPHIqKNDmrFRlxxd8TqElHJY95B43cRficqhRi9MbbUGIhOYDT8J53xj7NF6sqhkQdZ+rj/b+ryYCB1zpZjw/B8Ei1ZDkdmILRiKEJvDMSsxhjNT4yk0GzCH5Q6OdW0417ZhHJ6IeWwqru1dmEenIMkSTzV18ef6Du4vyuDqrBTur2tnangyEwQBO4QvuwfZYXdjD4YisUGnpMSxftD5iyTpnoNtrOx30OL180xZDgCPFmfxQ5+dq34heuhwbdhvctNI0Gk4L/0f34gfx3H8IxwnYv8hDLj8PPxdFZPyEzl1VAanjjp2uLCqqtzxyW46bF6ePm80cWY9JwxL5oelJ5AULcJNnzhnFL+ZV0xWvAm7N0hTn4tASKU4zcItc4rwBRWRByhJfLW7ncqWQXyBEBdNyuH9qydHtnXRpByW7+1kXrloDSyrbOPHA91E6TXotDJ3fLyba2bkk58cTWa8mcx4Mw9/+xNtgx66HT7mlqby8Y5WYow6Fo1Ij7RWa7ocXPHGVsblJPD4OaNo6Xfz52+q0GskTg3HOdV0OfipqpvzJmTz5uUTuHfZPh77oQZvIMTym6ZzwcubWXOwhz+dWs7vvthHU7+b2m4nsSYd187I5+LJOVRkiAvhtkZxZ23UyUwLk8cYo5aphUl02b0MS42m2+Fl4VPrCIZECzMvKYqaLief7WxjQ10fN88uwu4NMDwjhuwEM4oKvkCIDEcsratVsmYaI0MGnTYvq2u6WTTCKo7nM+t55Ntq5pSl0m7zUpQqvG3KrTF8ubudMmsMAy4/cp6CtlpHbDgfMjPezOzSVL5430aJ00R/jcq6YDs5iWayDHHiWm0Gm8aLXxtCSjAj67RkJ5ip6XIQf6GH7DYT+SdLGOPFtOKnrwjPL70FSi+S2PG4Su9uhVM+0fDlGQreftHqq0vtpXXAw3kTspBkibJLRIVLDgf7HSKEa+8I0XcATnxMxtagcuAtFUlWyZguU3SmqLQVLBbLRlslJI2KJVMI9A+5+MfmQ8m54YvWvo9IDXUz728XYEiORdJIdG1X8DtkupvyyJRknG0qm/6okFguccYPcmSfKFwA7duEqB3AYoVJN/39P7zkUvHzX0Fymfj5OSzpQrSvM4M+WniD+WzCS8ycANVfilZkxXlDvmKyVlhRBL3CggIgJhOm3SEI2aFWav4cQTCzJh+5Ta8N9n0ktldymhD4d+0WBM/vFIw24OJ/GkwamVUTSo75nCMY4r7aNkZazFyVlYwaVBj45CD+DiE3IKTS+/IeVF8IZImo0SnscYgg8r0OD0FF5d2Ofr7usUWI2OG4MjOZVq+feo+P9zr6OC89kREWM8vH/vKQxqLkOGrdPhYkDQ1kTIqLZtI/aTuRZzYcM2fyOI7jX8FxIvYfwqc723hvSwtf7e6IkLBnV9bS3Ofm3sVlER3UgDvAh9tExtnO5sGI3UVR6lApXqeRcXgDVNy3lhGZsXxwzWRsngBxZh1/+lrkrk0pSGR0djxXTMvHFwgxs+RoQek1Mwq4ZkZB5P+l6TEkRRsYlRXHw99WsbVxABWVP51WgVaW+HpPBx02D6Oy4jh3fBZLntuAQSssOfa2CS3axZNyaOpz09LvocfeQUVGLCXpFhzeIHqNzN2LxEXxNx9VsrvVxoDLz50LS4kKv/9dLYNcfUI+rQMe/CGF4vQYlozO4GCXAxWVuY+vRlFgxa9nIIfvSMflJpCdYGZaURKa8GNajXzEVOR7W5rQaST0Gi1mg5YXLxrH9qYB7vxsD/6gQl5SFN/s7WRvm52MOBPnjM9iWm4yX52mEvKpaPQq1qli3bd9XMnag71UdTq4+oR86nqcKCpEhyt1uYnmyOd7wcQcvtzdzrkvbaJa7+CB3w8noUTccfuDCue8uBFvisIfZ2iozYdbPtiFUSez9775LHpfpjfgZfqTqwAo657IlJgk/nbhWFz+ENXPyPR0qOSdBDufUtGaYPpDEvYmlTfcVQSaNIyxFGLJAU+PKvzA7KCYQ1z++laCikpqjIHhrhTW3qGQNAJOfHyoJaSqKr37IOgCe6OopCWWq8QVCpNZ6xSwThla3pQMC94U7VVJkhh3m0TNRyq1n0LIpzJuaRA6dgIqsTktkBAnjt+tMs0rFGLyhFlr9y6hb7M1qoy+6TAxW0ym+Pl3w++CbS8I0jTumnCl6mdQFeEvNvoyQZ78Lqj5SjwXlwdJJUL4r4agv06Ef4NY15RbhXP+wW8AVWjJDJYj1/9LhNHvEj3ioE+UEuu+F2S07yCMv07s0/+watg/wne9tojW69KMJNROF+6dQpMXd3oh5pHJ9L9bha/ZgS5V/C09VJzJnMQYTkqOxRYMsWbAwQnxFhRfCEkjIWmHvicpBh1ZJgOfdg9ia+r6p6pUF1oTudB6vJp1HP8zcJyI/ZvQ0u/m1g8rGZ8Xz23zS5hfnsrqmh6mhjVkNk+AR76rBmBmSTILhotqUkKUnjtPKuHpn2r509f7mZifcExRfWOfG08gRFWngzHZ4u47EFI4eUQ63oBCSZqYKkqLNeLyK1z+xlaePHf0EVFM3+zpYF+7nRtnFWLUaShJi2Hb7+YARNz0J+UnMvqP35OXHMW0wiQUFfQaGZNeQ7/Ljy+oYPMEeGtjE1/v7sDmDvDaZeNx+YM8/VMtf/xqP7+ZV8xLF48jxWJgY10fUQYts0pS6LB5I+3P+cNT+WBbCxvq+ggqKh9cM4l97XbMeg0b6/rotHv5encHOo2MT1W4b9k+Hjy9grRYI6XpMay5XQQtu/1BLnttKwAvXjwWuycobCg+FXmPL140FpNOgz+oMKUwkSi9BrNOw9TCRKIMWnodPqo7HVz++jbuXlhCQVEujmaIDl//nb4gFRkxbKzrw+0P0dTn5tERE9jzYZDJagrX/aEAS3hYoX3Qw1VvbmNfuz3iERdj1NFh87CtcYB5ZamMyIijqs1BajCKvBSJhCg9JWkWtBoZV1SAXTUD/GbeMFz+EBPyEtjfbufh76o4qzwb99eiZbJ7WYB9X4awBA3kniQTyPXxyl8aABh5Xjw9Lyay8haFBa/L+B0qkk5iWlESTX1uitMseDarqAq4O4/8jkmSRPHZEv3VKtZpoDVKzHpGEC81pOJoBUu2WK53j8rKmxUMcXDyBxKSDvIWyigBhZqPVDKmSrSs1RJqP5esSX1oDqs4RWdIdG6Ffa+rjLwOCk6V8PRA/LB/s09QwCMqWD/XYPlsYvIASRAfjQ52vSH8vMZcKSwjDn4r9GkZE6H0NFEVy5wstGRxucL2ouI8kRt5eEYliMqXuw86tov/Z005ts0FCB+z/oNCz2aME3q5sVeJdRgsEJsjtHLxueJ5YxzUfC20cMPPOfZ06P8wzE6M4ZTkOEqjjehkCdUajWWWqMxGjU9DkiSSLjvyfSTotJwTFv3HaDW8O7KAQLebjgc2obHoSV069ggydqE1kTavn4XJQxWukNOPHPW/23/qOP534DgR+zdhVU0PWxr72dNm47b5JWTGm3nz8qGJqliTjptnF9Hc72Za0ZEahKmFSfz5myrcvUFsnsARRGxn8wDdDh+njEhHJ0sUpAyVznUamWfOH8PP0djnQlWhqXeohaGqKr96bydBRSUn0cyskhR+81Elw9IsLJ0zjJfXNWD3BJCQcPlDNPS4eOeKSRSmWJhSkMgXu9opTrNw4aQcxucmIEsw6Alw2dRcdBqZy6bmUdPl5Lt9HTz5Yw0ZcSb+etZIrntnB7IEG347m1vmDLUKRmXFMzYnntQYA/FmPSFF5ZwXNhFUFG6aXcTulkHOm5DN1ScUMOORlfxU3c2yyjauPqHgiPfa0u9hc4O4277x3Z2sPdjLHxeXM788lR6Hj1HZcZz05Bp6HD7uWFDCgDuARpaIN+tZPNLK4pFWrn9nO039bhr63FQsHWRWOGd0VXU3V7yxjelFSTx7/miueXsHn+1o4/OxcwgNygS9REiYqqo8v6qWfe12JOCMMZlcMyOf9FgTpz67nsqWQW6dO4z3Lp/EZycp2NeBKU/4xr28toEPtjazvraPZZXtnD0uk4fPFBf397Y0s6q6hz6nn6duT6GrIciV9asIjFV5znoC0VYTFtnEreNK8XTAhPxENsvQljLAGS9VM+pgJuV7M3nkkfEkjwpfkBbAwU9DDNZB13aV1LGHtFwq+15XQYX29ZA9e+hz3vGESv1XKqUXSQy/XELWCi4ia4nIngAKTpUpCEuePl0QIuQrJxQnUTDsSI8mY7jDJOlAY5Aov/Q/cLHc/qLQVFWcD6lDyRVYrFBxAWi0osUY9AlfMlUReZLGuKH3FPktQcniI9efVAIJBUfbVIAgf3mzBNEK+cS0Z9bkITuKQ+jYDvs/Eb5iU8PhwvGHxQwlFsK4q4+sDNqahfDQ1iKI2s+rbf/DEP+zTElJloidl/uLyx+Ovver8FYPkHRZOSgqql8h5PDj3NCOIS8WfZZ471lGfUTrBeDc3MHgZ7WYx6WScObf8ZE7juP4H4DjROzfhCWjM2juczE6+5cnaJbOPfqE0Of0kRCl59VLx2HUaUi1GNna2E+5NUaQkxc34Q8qvHPlRE6qSD/GWgV6HD5eW9/A/PI0nr9gDDuaB46IN5IkiQsn5bC7dZDJBYmsq+1lZXUPK6t7uGBiNntaB1FUyE4089ql40mPMxJr1nFm2JrjhdV1NPa5mRQeDFhxoJstDX2ce5hY/8+nV7B4pJXzXtpEn8tPaqyRrAQTMUYdcWYdf/xyP29vbuKpc0ezYHgan1w3JfJao1ZDjEmHLxhiY10f+9rt2D1BchKjuHthKetqeyMt3kBI4YkVNVjjTMwuScUaazwiecDpC3LO+CzK0mPpsvkYcAuzyNHZcdx/ajnWOBOWcKXq3c3N3DKniJnFKdz28W4+3t7KJ9dO5v6vDpAWayCkqDT3uSlJj8Eaa6QgJZrSJVqSC4U2Sw2pSBqJP361n7c2NZMVb+K6EwsjAwEAw1Ki2dM6SEFKNBq9RPYcCVuDSmK5xNbGAR5YLtrLV04TLaeC5CGyfcmUXAbcfk5NzSEhT8IwOYT/UQW0UHKxJCYQgdz3cvD2AxUyp3wKD6zsZOemQfpUhbJgJp5eEagd9IiKlN8BKODuFsHrABq9ROFpYt8ipC2MUNhnUwn/TiiVWPiujKtbZftfVQpOE077APVfKqiqGAjo3aOSNuFokjX5XpkdTyvsekrFb1Mov/S/mCH5T+GwaCIlJCpJkgzDFooKV9sWQbqi04QA3zMoyBWAzyW8wjInH3vVqgpbnhGWFeOuObqFKklQMFf8e82DwiVfkoQJbHTqkBWFIUbs07GyK5UQbH5GaMLGXCE8yEBUwvproW2bmOocdclQqPj/MvjqbaieIIF2J9GTrCRfOwJvzQC25Q3IFh3Wu4c83zz7+nCsayN2bjYhm4gVC9n9/1/t+nH8/xm2bt3KK6+8wt69e+np6eHZZ59lzpw5kedVVeWpp57io48+wm63M2bMGO677z5yc3P/29s+TsT+TYg2aI+KA/pHcHgDzHlsNS5fiOU3T6MwxcJjP9Tw1I8HWVCextPnj6YoJZr2QQ9Z4fDrkKLS0OuiMOVIUekLq+t4eV0Daw728NWvpkdan1127/+PvfOOj6M+t/53ZrZ39V4syZZ77wVjMGB67zfUhEAgIQkpN4XclDf1pvfGTSCdAIEECL0YjHHvRa6yrL6SVtvblPeP32qltWRjQk/28BFrzczObNPOmec5zzk8v7eXc6dX8MULhic9u4JxLpwpxOe1hU7uuWEe4YTKnLoC9vWEueOPm1naVMIXzhfP6fPnTubJXd3810Jx1bmxdYBEWmfr0UHOmVbBxtYBqgrsLGos4tfXz+WzD+3gtt9v5pmPL8dqEu2tzW0BUqrOzo4gq6bmtou8DjOrP3Uqmm6w5BvPEUmqHPCHmVbt5ar5tVw1v5Ynd3Xzq9WHWD6hhJ88L6YdHVcqdAYTdIcSvPqZ0zkyEGN3Z5CbfruR5jI3ixqLSKk6TSUu5o8rYlqVjxf39RJOpPnOU/t4YFM7W48O8qULplCZaXv+c2c361sHqC9ycM/1c5lY4aHKZ+eVzwyXiA4/anDkaYPmq8BVbbB3q7ArOHNKOdcsqMUwDO7feBTf+gIW/G0qN98+leapMi3dYWZ/yoluSFz+8zX0hJLMrvXRkPRxblszt314AkVVw3+WTaUuvnHqLJ64TudpdM7+vY1nPi4yjyp9w+aXjlKhB7MVgtUrccvyBnQMzqypZMK1MkVT4PGrddJRWPkLmVO/JxM6DOXHeJfO+ohM6xM6T79fZ+rNEg3nyfRuNlDjBvM/K8K6s8csk9j2M532FyERMFj2DYXgoUwkEXDmPTLT3p9LsHTNINAiYpO0uAQYJANj/328Ycz9oHhRnCWietQuYrComissKwYPi5LepIth4JCYYBxqY/XuEKwzdFQQp3RM2GcUT8rYbRhCWK+rQkSf+yRhxx9F23PmdVA2VUxl6ioceloQrxVfFrdFE2D53aMrZSAei8kmhP9HXhb7nHG9CB+vmi9IGIZ4bP+mKL5hCqn2MM454qLSWu9FMslEN/Rgm5BLXiNrO0kdDhJd303B5c1Y6jxYa97d1cI8jgNDF1PLqZCI1Cioz82HfQsQi8Vobm7m0ksv5Y477hi1/le/+hW/+93v+MY3vkF1dTU/+MEPuPnmm3n88cexWsfQmb4O5InYOwgDQax0wyBjNo0r46fjtJowKzKPfWRZdiIS4PMP7+RP60UVZ2Srb+XkMl7Y5+fsqeWs+v5qVN3gwVsX86kHtvPiPj+7u0J8+UKhw9jXE+bKX7yKaYSYfkXzsOfSKwf62NcToSuY4L/PnojFJDOjxke510aFV5z8v3vFTFbv93PRzCqe3NXNB3+3iVK3lfWfW4nXbqY3nKQ/miKcUDkYilJf7OBHV89izYE+fE4zk+5+gsvmVPOVi6byo2f384vVh/jGpdM4b3olf/ngIvb1hDl/eiUD0RROq4LVpPD7V48IN3unmbl1BUwod3P+9Er6IylqCh2UemyUemwEM+3HmkIH1y2qYyCa4uKMb9tXHtvNH9e1cf6MSs6fXsH6wwOcPbWChhIXa/77NAB6w0kO+CPYzQpz6wpJahq6bmSHBdr6Y2ARf3iSDJu+bXC2MpWLb6vmwlWi7fzsnl4+/eAOrt8/k6mag1CLxLefauEnzx/k6vm1fOLMCezsDGVTEiLf9XJgJ+gJmaIR1lGqpvPjl/czzjIOm1lBsZIl5SMx62MSsS4omS4eY5XHzn/Pm4qrSvyuxg1RIJLEJ++b63bTHUzw7Vkzsoa8Q+jeIEK/u9cbNJwHO+/R6d8tpizrzsitbjWcL2PlILUrTUA9zkoonQNmcxhP929g0A0zb8xOC27/mcH+B0VQ+JyPi+pgyTESqzcNwTaRBekoEu3I6oXCRsJZKiYxZQWq5wuN1pEXxX3KpomJxRnvE23KIef71hfhyGrh/7XwI6IS5igGT81wFW0I6agI/AYId0PzBdCM0Jf5dwu/sq5NsPcR0b5sOJ0xIcniWGoyk4cZF3YevkwLrvEsQS6P9Uv7N4Kl0oWlMvei01LtpvJzC0Zt6zmjjqjHgnt5NZIiYW8ew14kj3c/endCy6NCyzkEqxeaz3tLNZHLly9n+fLlY64zDIP77ruP2267LVsl+9a3vsXixYt55plnOPfcc9/QsfNE7C1AbzjBdfesp8xj457r52JShpm8rht89fE9aLrB3edN5umPLyeR1rJxR7ec0shZU8rx2c2c/YOXSKkaD962GJ9DXDFHkyLjMZHWc465sKGIZz6+nNa+KP/75D4AOoMxZtT4WHOgj2lVXpKqRkt3mEKnBafVhM2sZKtVI3HFvBpW7+/jub29fPhPm/nF++ZywY9fpiuY4P9umMtpE8uoKXRw7YI6dN1g29FBFFnKmsTOqy/kp9fOxmc38+Subj73t50sbizijx9YyFXza/nhs/uJpzU2tGZcsw/1E0mq/GldG3fdv42PnD6e21c0se5QP9f+eh0Tytw8fucyPnFmM5VeO7u7QuzoCHL53GpMiswNc8eh2IYf/8rJZWz9whk4LSZkWeKHVw/nZg7le1pNMmdOKefMjInuYCzFuT98GUmCxz6yjMP+KPt7IwRjaV7Y5+fyOdX87+Uz+NP6Nj7z0A7OmFjGd++dg7tWIh3RiXSaqXOXsvUbMOUmYS1SXWCn/bRu3ldTQe2pEs+uyUQR6TpFLiu/u2k+gVia+eMKOXSmTjpqsL+xh+v/Zzs3Lann42c2s+lIgJ9vPoB1ymGeuPMUbCNImGEY7Py1gZowOPQo6ClY/h2D0tkSm75ncPgxg6k3S0z6LxmTXWLVb4WuLe5Kcd+vRGj1ptYA5ZuKSQ7C9FskZLPEjFslfI1Qu1Ii2m0Q2C/4S91wlZ5EwECNQdlEP2WB/4MEEP8EJnshy7+twEA/bO4Vong1LsgNwx6ockYbVj7CJ/VNhZaCrb8VV9YWN5ROzvXrKp0sfkAQnOKJ4st+4DAcelIQpPpThrcvmiCqZENas57tolqWCgPn5x7b6hHO/elo7oSjzQfzM1fae/4mHluo48TPQ7GIn5nXQbBd5GgOoeNVYRbb9hJMvep1vDj/nrDWebDWjY5kyuM9hN6dsP0Po5cng2L59GvfkQGV9vZ2/H4/ixcPy2ncbjczZsxgy5YteSL2bsS+7gh7u8Ps6wkTSqgUOofbDi09Ye55WUy4XTK7iunVvlH3rytycqQ/yt7uEIYBnYMJfA4Lf9nQxt+3dXLutHI+edbYmpD6Yif/c95kvvHEXv77wR08csdSPrZyPJIk8fG/bOWhLR3csaKJtZ85HUWSSOs6n/vbDqZXe7lyntA1OSwmFjYU8tzeXmIpkWfotJqQJbLmqkN4eGsHP33hIE6rwsO3D39Ih4xQjwyItslIA8ZbTmmg1G1lQUYU/81Lp/PMnh52doRIqv1szBC0QCyNqhv0RYTeY0aNjxk1Pq78hWgxSZJE+4sGa7+sU3uaxILPSQzGUvSEkjSXu9nVKa6oplQOT1LduryRP69r44FN7ZwyoYQF4wrRdINYSqMzKNqLgWiK0yaWklR1it2CXPaGxWMYIsIxVcVdK57T7I8Jov3kDRqhI2ArBqvXxg+tpzLj/RKKVWz36bMmctbkMn710mGu/fWr/PTaOXjtgpk0nC/TcD78v0cDRJIqaw/1Z5/zRTMrcdvM1FXm5vCFWocd8p2V4rvKnvHkHTJ2H2nwbvVJdDyms/ePJr60fA4d1QFm+4p46tdiHxULJMrmgr1EYuI14jEffV5H1wQXGPJD05IGT92kkwrByh/Z8VlcBLoqUHc7KBnyRC1shEmXCAJmGa5oTLtFov4sCfdbmY9s6ILpFY2HaJ/wAxsLR9eKSlfzeUJnBbDjT2LisWc7VIwgPYWNsORT4t9Rv2gXls+Asulj77ti1tjLhzD+7Ew1LfN3vP0PEGoXdhkjK1y6JiKVEiGRPymP+PurXSYY8vF0bHnk8V6CoYtK2InQ8qjw/HuL25THwu8XSTFFRbmWJ0VFRfT19b3h/eeJ2FuAJU1FfOWiqZS6rTkkDGBCmZsbFtejGwaTK45/9VbutfGjq2dhkiUmV4rtDvrFFGQ4qWX9s+IpjR0dQebUFWSXVRbYSao6B/1RVE3PVuSG1iuylHWxf2R9B39Y18ZfNkhcMbcGSZJQNZ2X9/dRV+jgKxcJXdnf71hCMJ7OtiaHUOG1YTXJTKn0jqquqZrO1fNr8drNJNPDprM2s8JV88WZeM2BPsq9Nm5cMo5gLM3MWh9nTCojEE3x1K5ubl5az81Lh6fINrYOMDFjZLuosZi9f9SJS2nu9R9GO1DCZ/62gyP9Mb5xyTQ+97CwsHj+rlOpLRquJHmdFqRADF03OO3bL6DqBs98fDm/v3kBEkLs/5s1rZR5rfy/C6ewIF2ObY2X/gUGNy8dx6zaAiaUjTZ+nHitRNuzBpVL4IWPCHJTPl/4bwGEEmn+5++72dEhCOKuziCLG4fTDKJdBqe3NlK82M45S4QmxmZWuHRONb9cfYh1hwdyIrU8tdB4gUQ6ZlA8HaqWCqNXgHmfkqg9TRRltKSRJYPtLxhEO2FCdwkz9VJS1dB0CSQDUHRMWIQaN1j/dRF/NOsjErbCEW3JzD8NxUVi8qd59itgqLDyF8awDUXV6HKXJEl46kctfvMQ6hDTkp4aQVxGQk0IkjVkJeHfLdhrX8vwVXbTWUI4X3GMyz4ILy9JEW3M/n1QPmtsI9iTgckmBPuyIoT/fS0ZTVpHLhFTE8KnDIQTv3XEd0Zxs2i7dmwQJrL/xi3KPP4DEGjNbUeOhWRQbFfYcOLt3mPIE7G3AJIk8b6FdaOWJ1WN7mAiRzQ/FhJpjTO/t5r+SJK/f1i4igfjaWbV+vjeFTNYNmHY/uITD2zjse1dfOjURj61SmhVXtov2PtNS+sxKTJ/Wt/Gj587wH+fPZH3L2tgQpkLVdNZc7CfuXWFnDaxlJk1PlTdQDd0okmNlw70YRjQPpCgvsiFw2IimtR4clc3p00sxZwhd8/u6SWp6iTV3Fbp+sMDvO+edSxuLGLd4QFiKQ2rWSYYT9NQ7GRBQxEvtPRyw2824Laa2HT3GXgdZlxWhV+9dIjqAjsPbenAJEvcfd7w6/WFR3axuyvE4f4oz+3t5c6Lx/Nwsp3HWw6x+f5OnFYFSYKOwRgWRcZmlnEck2P3l1sWMpjRkQntnSBNSzIeZ+sO9ZPSdMIJFUmWKFhdTKAFjjxjUDRFZk5dAZGkys4/aEQOScy+U8Likag7Q6buDGGGWn+2gZaUKJk5fNyW7nCWhN0+pZn5tbkall2/NWh/ysSkObXUXjD8mH+zppWX9vfhsppyiJikSMz+mMTaL2ps/i4M7IZ5nxbrFKvEgYd1ejbC4EGYcZsgRzM/LNP2tEEybLDvLwbd6+Cs3yj0bDKIdIJvhDuIYhEh35GOYef9oX2f/lOJrT82aF9tMOm/ZBwlYhDA6uOdRcwv2pLhTMvP0IVo3uoeDhqfdIkgic0XiMrXEGGMDYjqk7NMCPxHItINW/4PkISzfrR3bEPWwGFo+TtUzoPaxbnrBo8IImUvEORp78NgdsGSu0QlLNozusJmcYq2ad9e6Nk5Wo928Cno2SGqdDOvy1mV6ogw8JcW7FOLTtouIo883jGkQm/udm8iSkrE90F/fz+lpcMXPP39/UycOHaixOtBnoi9jbjlvk28uM/Pty6bno3PGQtpTccfThJPa9nQ6bvu38Yze3q45ZQGLp49PCrvzlS2XLbht7I9EM/sRxCMJ3d10zEY5/m9vZyfMXj94XP7+eGz+zllQgn33TSfUCLN8m89T1LV+eedy/j5f82hN5xkSdPwif/2P2xmfesAH1s5gRsW1/PygT7mjyvk0e1dnDm5jI7BON95qoWzp1bQF0mSVHX2doeZXOGhpSdMRyDOVx/fg8Uks/tLZ1HitmIzy1QV2DHJEr2hBHfdvw3dgC+cN5lzp1Uwq9YHiJbgIX+Uq+bX8Kd1bby8v4/V+/qYWO7hgrNKeSHYyZmTy7hleSP9kSSX/Xwt8bTGHac15VhbgKgylXsF0Xn2ruVoupEzgbigoYh/3LGUQpcFq0lhxm0Gbc8ZNF8pyMiR/ijn/eBlvvDSSsCgfB7UrxLrYr0GT9+iY+iw6l4Js2OYwMwfV8gXz59MaJ2Jiv+rZFsvzLlr+HHVrJAI7DdwVcOWH+pMuVHC4pa4fUUTTquJDywTeqNXvqARPAzT3i+x8x4DeykgiUnEkYMd3nESPZsMvOMgHTF44WM6SHDq92VCrRL9O3Xqz5To3Wqw+hM6ig0ueEjoyUAQvdN/quTscwihwxKdaww61xiMv0xi1e9kDE1YYLwtCBwW4d/1pwrt1RDKZoi2xVB1aMefhbZr8mXD8UJDt86SXKF8uEOI8OMBMeE4sg1ocQkNmaxAzUKx/4F9QgM2ovVK7y5B2ro25RKx/n2w5TeZ4O/PiizKobgiXROVrdYXBGkcekyhDkEU7RnCbh4hhMw+3+liIKB8dIs0sS+A2hsjtlnLE7E83v2wnKS+72S3exNRXV1NSUkJa9euZdIkcQEWiUTYtm0bV1999Rvef56IvY2Ip4XeKpG5PR7cNjP/+LBoBc6pEyPaVT5b5ja3NfjVi6dx26mNWbE/wPevnMn6wwOcmpmE/J/zpzCjugOnReGrj+3mrjObKfMIclKa0UBFkyq94SSaYRCIpTlryjFu5AiPsQ1HBqgrcvCpB7fx5K4erltUx6ufFSeObz2xl4c2d7ClbZBnP74cl9XEpAoPTaUuvvrYbv64vo0Sl4WJFR4O90WZUull891nYFFk4mmNs76/GsOAGTVezplWwU1Lh4XOt/5+Ey/t7+OL50/mnx89ha89voddnUFm1Hj54bMHOHtqBXeuHM9fNrTxmzWtzK3zsbE1QKHDwpO7ullzoI+PrZxAwTGt4r5Ikm890cKV82qyurZEWuNvWzqoKbRz45JxlMyQcoKzQ3GVSFrl8XF7uXncBCqXDv8ZKRYxXWjocOs/1rO9e5A/3bKQ7z29jz1dYX7//gWEd9ppQbjbD0HTDQZqQ6z8tYe/n6+jxgxcVTD+Uok5dQXZz4GWMuhcK9qAbc8ZhI8CElz8uMRztxvs+b3B6T+XcZRIzPiQzLQPGMhm4Q02eEAcK9Zr0L1BkMcJl8mE2wxMDhFZNCSmH4mxnMlLZ0PD+RKOUrLtUEbPfbx12PdYpuol5xqtSlJuVSkVztxGYeYNorXhKBZVJD2dqwMrnQLN54v1skmYp+19RFSlmlaJvMihY7Q8IqwxrF7htB9sEw769aeALA+3OrW0ENQPBX+bnYIoVi8UJGv8OaKt2LFDkLWBg8NErOUfooJXvUCYvdrG8BornXpc8bJrUQVGWsPWdHxvwzzyeNegoF78PZ2oPWn1iu3eAkSjUdra2rK/t7e3s2fPHrxeL5WVlVx33XX87Gc/o66uLmtfUVpamuM19q8iT8TeRtxz/VwO9EZOaPo6hKbSXP+bL14whY+OQSQUWcqSsPs3HuVwX5SPrhyfnQYEGFfs5EMrGpl49xMYBkyt8nLtgjrOmlJOYWYas8Jr58HbFpPSdMq9Nr7wyE7m1BXkhJX/72XT+eIFU3BZTbT0hIEeqgvs/G1LO0ubSqgrdDCvvoDL59Qgy1K2+gbw4OYOBqIpvnDeZO5b28oZ31vNb26Yl83WTGk6siShyBJfv3g65d7cq3/TiExJgM+eI65K/rGtk79n4pk+cMo4HtzUwd7MZKg/kuJ//rELl0VhIJamymfng8sbeWhzO8F4mhsW1/Pn9Ud5cZ+fgWgqS8RW7/Pzf2syAxWzqvE6ctnJtGovD922GJfVxPiy3HVWnzA6NXSDz397kEhSpaU7zOr9faRUnYe3dPDRD4yn5lQJ74g24Fce3c1vX2nlxiX1XH7VJPxbDHrHDVIUdeXoDBWLxNKvyUTaDWpOBU8dVCyU0BIQOmJgaBDrAUeJqI6lwsJbzDtOYuEXhAFsKgS7fytYYNUSA3etxAV/k+nZYLDuqwZTbgRP7fErW23P6VhcEnM+/vYKZnNQvUC0946NFzoWM94HoU6hKZFkQbLiA8KTC0Rla8iMVZIFmQKh22pbMyKmaJGovGlp4RtWuxT8ewR52/hLUdmSzaIK1rQKkhkCuP8xkUlZPhOWfUYcW0sKs9chw1fIVLY6hbZtCBUzxbRFydThqtjrgGwzvaFKmJHWMXQd2Xr804ShG4RfbEe2K7gWVh53uzzyeE1IshicGWtqcgjN571lQv2dO3dy3XXD7f2vf/3rAFx88cV84xvf4AMf+ADxeJwvfOELhEIh5syZw69//es37CEGeSL2tsJtM58UCRsLkiSNImEjEUupfOqB7QBMq/JmScUQrCaFm5eMo6UnnBWIj2zZ7eoM8oNn93PlvBr+vrWD+9Ye4f6NR3OImCQNi/w/vWoid6xo4rtP7+Nrj+9lYrmbvd1hil1Wrpg3uu368ZUT+N+n9nKoL4IsSUjAo9s7mT+uEKfVhNWksLipmP5IkppC+6j7/+y/5tAeiI8ysl0xsZQr5lbjtpn57SutfPyMCTy9p4dEWmNPV4gF44qYUePjhZZezpxSTlcwzsfv3wbA5AoPNYV2ipwWLpw5fBJZ0FDEmZOFRcexJOyVA3386LkDfHB5Q/a93N4+iMtqoiHjiC/ZDG65byPlXhs3LK7noplVFLssfOC+Tfzg2f3MrS9gWfMxGqQMDAMmv0/mwcnt3HX/NprL3Dz5sVNytimfJ8E8QZSm3jS8/NTvyaRCUDxVrNvyA4ODjxjM+JDEhMtlalaILzA1blC5GExOSbQ1EQRv5291ggdE4WXWR8Q+Dv5dp38XzPiQhNUr0bfTYN1XDJANzvuLjL34bWpFHovCRmEfoZ+4uozZIWKC+vaKKcmGlcJJ31sntGT24wQ/H30FDj4pKljVC4bbn1t/KypcU68S0UMgLC0G9g9bVez9O3SsE9WuoTaK1QP9LbDrr4L4zb8993gmG0y8KHdZ9ULxA+KxyuZhw9m3GEZao/u7m9CjKqUfmYW5ePhvcihNAiDVGiL0ZCsAtuZCTAVjtE/zyONkUTpVWFS8Az5iCxYsoKWl5bjrJUnizjvv5M4773zTj50nYu9xxFIqDosJh8XErBofXcEEM2q8Y277+fOOP+H1+1fbeG5vL/3RFD+9djZP7uphXv2Jr8KdVhPN5W4kCZrL3Bz0R7CbZbqDiVEVrYSqEYyrPLmrh2fvWs6K/32eBzd30Fzu5pZTGukNJ7LB4zvag9lw8CHYzMooEgYi0eBbl83g/B+9zI6OIB88pYHzpldw8U9fAeBTq5ppKHFx26mi/OQPJ1jSWERSFUHpX3t8D/3RFK39YiI1GE9zpD/KL6+bO+Zz/t2rR1h7qB+7ReHU5lJ2dgS58CdrsJkUXv3M6XgdZgZiKZ5vEQMTDSVO/JEkC8YVUVvo4GggRpFz9BXU3edN5rI51UzKTNIOea+6bSf/JzpSUA+QGBAaQaHjGtZ5mewSS746uo9oqOKgBSO0p1t/bKCnxURl4wUSrkpwVQlrrrdNqqGlRFtPHvGYj7wkKmKhTliQ8eYKdYptXGWj99G6WjjpW1ww5XKonAORntx9joTFDUjCPHVk5UpLDd/27BCty/pTYPEnhrcZctpPRYRNRdU8MSzQvVUsl445pn+30KXVLBJX+8eSrv79ggAWjodZN7z26/UmwFAN9EgaI62jx9KAIGKxrb0M/KUF16JKfBc0Yq50Yp1QgGxTUDxvvDKQRx6UThXTyG+zs/47iTwRew8grYkooenVuRYRf9nQxqcf3MENi+u547QmthwdBMR0XpVvtPv6iXDjknpC8TSXz62mymfn9+8f7Vw9Fq6YW8PFs6owKzKOBxX+tOEon3xgG7+7eQGJtMZANEWlz841C2pJqjoFDjP3bzjKBTMreaGlL1udq/Da+eL5kxmIpbP+YidCOJHmil+8KqKEbl3EGZNFyPeSpmImlLk5ZUIJZlnimT09LElrTKn0ktZ0zv/RGvyRJH+9dRFeh5lPnz2Rv23u4P0Zi4zr7lnHtvYg37psOpfOruY7T7XgtJq4fYXI+Xv/hPHMfWw8DfXifXBZTdjNCl67GbNJnDhL3TZ+fM0s+iMpOgNxrvnVOlZNKefxO5dx4CmV3m8rBG418DUBhhDFK7LE1KphAv23rR0YCIH/8bC5LUBDsTNr9nv4MZ1gK0y9WcJkk5j0PomOlwz828RE5Uh7CjVusO5rOmanxLxPSkiKJC5Ajdyiy9T3S/TvNKhaKhbaCiXO/v3wZ1BPGwT2CfImK29BtSbcBRt+JsTsCz48/GVcMUusG5p4jPaK7EdJhqWfyrV5ABFrpFhES1FXYc9DYrm3etg9fyTKpoLtg+A9pro76yYxmemthT0Pi5Zk/z6oO0XcHl0rjlG9cLhCNhTKXT5TOPyPHC5QE7Dt94Ah2o+GLlozpVNh+jVim/iAWB57435FJwvZbqL0w7PQ4yrW2uHXMt0dBQNSXYJsyjYTJTcNVynUvjiyw4TsGENsmEceJwtJ/rezqDgR8kTsPYCvPraH377SyhVzq/nWZcOamEN9oopz0B+h2GXl1uWNdAXjLBj32kQGRDXt9j9sxmKS+dHVs/nJtbNf+05jYMjKYm59IQ9sbs+27N53zzo2Hgnw8/+aw1lTyrl9RRMLvvYMPaEkd583mec/kVtmvmHJuJzfVU3nwc3tTKrwZI1v9/eEeWBTO8vGF7OnS4wx9wQTfOT08dxySgOt/VGcVhP33TSfnzx/gK89vpdxxU6e/8SpGAaoaQNdM2h9Smf2+2FxY3GOl5fVLEiGzaywpS3AT18QHk7nTKtgXLETxz4Xnm6D6LPArcJAd+1nTkdRZcyqDJnu8XnTRavzV6sPATAQTWFWZPY8rLGlz4/176UMbJHRErDylzL2olwSMzSUUVM4NqG+f8NRPvXgdqZUenjsI8vQUgYbv2OAAYXNwhXfWy9RdYqBlgDvMd9pgX3Q+TKAwZTrJZwVsOL7MqE2qFwyvF3zFTKh+SKWqPECkS85Elt+aHDoUYOmSyRmffgtIGLJkBDVxwOCjEiyiPzxVMO8W0Xe49bfCssJk1WI7I+dOIgHhJM9iFalbIK6ZaIiVtgkiFngsKh+DWU+7vkbdG4UVhXjVgzvy2wXJExLC12XvXA4wPvIaiG2N1nHdrqP9kLXFtHqHDqOYhFX//F+QdJ6tgNGLumqmicqdMczpn0TkGwNYmgGtkbf8FMtHf3Z85xei6nMia1hdNU9cXCQvl/vQPFaKf/0vDGHPPLII4/RyBOx9wCcI/InR+JjKycwo9rHgnGF7OwI8uHTmnK2ae2L8qV/7OKMySKIeiS6gwkO90WyLbSjgRiNJaNbf2Ph9j9sZuvRQe69aV7OUMGlc6q5dM6wtUY4oWIYEEmo2WUrJ5Xx3N5e5tYNa+VCiTRuq2nUF/dDWzr49IM78NrNbPufMwH4f4/t4cV9frpDCX7xvjkYhsH4MvEYPvSHzTy3t5cvnj+ZG5aMQ5FFa+/UjB7LYpL5QdUStj6YwtbugmP8PgHuu2k+vaEktUUOEmmN86ZX4LSYsBy0s+EencaLYbBHp7ciSCJdgM2s4DBMPHmzTjqqc+avZZwV4nn0hBKcPa2cKVWerHnvn5u3s76gD0fhBMZ3N2Dowkz1WKnS1y+ZxgfKJxJebyIx3hieTMxg6H0e0uwpFokJV0iEDhuUzhHbymaJxV8arl7t+JVOrBfmfFyieBpMvk7C7CT7eN21uY73akJMZe74pfAji/fB/M/kPg55iE+8VV2p4maYfbOocMkmGGyFTb8eJmL+3cIMdeAQnPJZQdSGSE6sL0OwxmUqadJwRa1p1fC/W/4uKlnlM4YJ1MgW5FjY+Wdx7PHniGodCCsNxSYc78fCvsdE1SwxCFOvFMskWcQpOQqFTqx2iSB3nuG/IyR5OI7pTUKyNUj/7/dgn1KEe0UN/l9uBwPK7pyNudw5ant1IIEeV7FUuXDOKkULJdFTGrJljNaukfnJ87A88jgp5InYewCfOLOZy+bUUHdMdcRmVjhnWgW/e/UIdz88nOc4hEe2dvJ8i5+W7nAOEdvcFuDyn6+lwmvj06uasZuVkyZhhmHw7N4eEmmdHR3BUdOdI/GnDyzkcH+U2SMGFL568bScbf6xrZOP/HkLF8yo5AdX5cbCTK7wUOi0MH+EVu3CmZV0DMY5b3olZ0zO1QIZhtBEDcbS9IYSfPOJFgwDzh0xuDD3chuulJXyBWOfJWxmJevCbzMr/PgaUSV88iaN0GGwuCV+6tvMS9v7+KCvgc+cMwk9LXSlelp0qkDYYpz+nRdJaTrPfGx5tn04sdHJ+t4+GqZZOfX7MloKfE2jH4skSbT8VCHaKawlpt6Uu8250yuYUbMiZ+Bi0jUS+/4qDFiPdTpIBo1sHFLNConKxRJTbjzxmXLtF3W610HNCnBVQ9UyCf92gw3f0Kk7Q2LKjTIzb5dovOAtjCzSNVF9MmfIQSIEhibadSDIU6RLiO9NxwjFt/9BeHo1nik0XJIkNGJD1a5p1wqCY8589kf6gU2+TExQ6ml49QeiilW9kFEYmo4EUV0rbBr7eUT9Qhtm8+UKjjs3w+4RAn5JHq6wvYnQUxrBfx7GXOrAtaiSVFsYPZImsS+A9+xxKF4rhqojO4eriYZuIMkSelKj5webMVIaJbfNAFXH/+sdmIrtlH98WEtpa/RR9vE5yA4zkvz6WJie1JDM8uu+Xx55/DsgT8TeA5AkiXHFo69Sh2AaEV00ElfOq+FIf5TTJuVGnyTTOppukEhrfGBZQ04o+VjQdYOWnjATytwossS9N86npSfM+dMr2dEe5IFNR7lp6bgcLzOAAqeFrmCCVd9fzRmTy7jrzOF8zK5gnN+uaSWp6sIpIJNJORJTq7ys+fRp3PaHTdz82w385NrZXDK7mktGGNqOxGfOmcTLB/r41UuHuGJeNXNqCwjEUtQXOxmIpvjLhqOsmlrOjA8d/7U8HpqvkGh9yqDuTInG3S5e2t9HQ4nYj8UNc+6ScJYNk6qhd+LY08qXL5zKf589EYfltf/0mi6UOPq8QfUpY5+cqjMB4ENTbPseED5i7S8arLpPofUJHWuBRMUCMfE49WaJWC+UzYG2Z3UOPmIw7QPyKJH/EIY05UVTJRZ+QXxGdv6fTrQLjr4obC4kWcIzOkTizcPh58RPYZOojJVPh8FDYEiCpJkdwil/JLQUHH5BvDFypuVnHXHBEOoQbc5Il3C5t/lEjqTNJ/a592FBwCZdCvv/Kchc56ZcIjb1KtESbXtJ3G+keWukR+xXGTHl3PIPMVlZMSeXaA0NCxwr4H+TkdgzQHRtFwCOOWW4FlUimWQsdR5km4nyTwqt3RARSuwP0HfvLuxTiim8bAKy3YSmGcgWBTWmgg56Qhtl9msueX3aVBDGs32/3YVtvI/iG4dJqh5Xie/uxz6p8A1pzmJbe0kcGMS7qh7FdfzJ8zzyeKeQJ2L/Brh6fi3z6guyJ+YhlHttfPfKmaO2X9RYxD/vXEaR0/KaJAzga4/v4dcvH+aGxfV88YIpLGgoygrqv/7PPbxysJ9IUuM7V4z2dHpxn5+93WEGY+kcIvbDZw/wp/VtzKsr4NfXzWVGjS+7LpHW+NAfNiMBH1rRyAuZ9mnbQIwJZbkVuEe3d/KZh3Zw6/JGzp9eiSxJyJKE1aTwwG3DJ8fPP7yD37/axov7evnzLa8/JLl+lUz9KvHvLzZN4dOrJmLPtGV232ew+14D33ioO0Nn/GUSRS4rz921HPUY135gTBIW9xvsuMegcpFE9XJxYptwhcyEK8T6zrUGhiqqUiPx6pd1Ol42WPo1mYqFEu2rDepWCrf8Dd8UNhPnPyBhK5ApnCTRvlqnfTUcfMSgfxe0Pmkcl4gt+h+ZSIfwIBvChCskZLPI0HxbMCRsH7pNhoQvF0DpJCiaMPo+XVuh9XmhFTvty6PXjz9HtDPrl8PL3xTTjUOxR7F+US2DjEHrctESLZsmWoqpqMiqVMzDWjRDE74juio0XrsfEO3QIXsLEJW3SI+o3I1E+YyMgH/sSec3C7HtfjDLOGaWZNuJrsXDli3HVqLSPTFQDdIdESSzTNnH5mCoOorTTNofx7WsCtfSqhwSpg4kiK7vxjG7NEdfZmg66c4o5irXmBUvNZAA3UDti+csH/zHQWKbe0nMKKHo6n89Rmbw7wfRYyrmUgfuU8a+iMsjj3cSeSL2b4ITtQjHwqQTBI4fC1UXLS0tczsSV8ytIRhPc9Gssc0cr11YSyylsuiYScizp5azoXWAi2dXs/KYFuMhv8iRBPjkqmbuPm8yJlkaRcIA1h0aIJxQWXOgj9tXNPHNS6cjSVB0TKzR0qYSntjZw2kT35xgZPsIbcxQ12xwPwzuNygYLzImSz2iVebfbrDndzoTLpezBGbHr3XaVxss+KxM4USJQ48ZHHnSwL/VoHp5bnUk0mGw5rPCgPWMX8v4GodPZoEDwl5i0/d0qpdLrPqtuG+838BVIywp/nGpwcw79Mzjg8P/NJh2i8yRJw2arzo+oVIsEt7c+QksLonJ73sb20dV80QFyWQfegAixzEVFqL5sVDYKFp9vjFKdYYhzFzTUfDVin0MHBTeYiAMXhtWClLlqRatwgnniPboS18XBqtzbhETkdOvES1HT5WYfOzbA9VDJP+Yv5XqhWIcf+9Dokw6MhD92FzLk4SeUIms6cQ63pcz2TgWkvsCkNax1g8TPj2pEXr6COaM7msIan+c6JYerON9+C4Ych02kMwyeizNwB/3gAHWJh8m7/DfWeipVmJb/aS7IjmVrcG/HyS6rhvXkkp85zcSebULDAPXIvGd4ZxXjuK2YK7IrVSbK1wg9eYsVwMJJIuC4jz5Cpn7tFqS+wPYpxa/9sZ55PEOIE/E8nhN3H3eZC6ZXZUVnO/sCLK5LcCV82q4aFYVF82qOu59PTYzV82v5U/r2ijz2rJatFMmlPD4R5ax5mAf4UQat234i3VypYczJpVxqC+C02Li5hFRRy3dYToGY5w2UZC3u86cwLhiJ2dMLuOQP8LH7t+KYcCUSm+O79iqqeWsmjo6tunNwITLZSoW6mz7ucHAXtj5G53FX5axejOmqA8b9GwEJJ3y+YIotT1rEOuGno0GhRMlak+X6N9tUL1sNMmxFoipR10FxzE8ctnXZfb+Uefw47D/AYPpmSKMvUji7PsU1n5RJ9plEGgR4nyTHerPkiholiiZ/h7R45gdohLWs11kSU6+ZOztIt1w8BlBco41TB2CJGUc8pPQvh4sDlj++dxcyZH5k1E/7H9cTDaabaLtOTSZoFgECQNhaWHoQmi/4CNjO+GP9Bd7ExB5pZPQ00dQNvVQ8SlB7PS4SuBv+zGVOPCeMUxEi2+cQrorimPmMOmLb/cTebkDZAnHzJJsdSt5MIjaEUU1yZhLHKjBJD3f24xkkij76Gxsk4rQgkkslbm6UvvUYlLtEezTStCiaQb+0oKp0AZDVTBFIt0dZfBhkbVlqfNgqRRVMvvk0ZPe7mVVuJZUZqtoqY4IvT/ZiuwwUfHpeUjmk2vnupdW4V56/O8oQ9VBlvL6tDzeMeSJWB6vCUWWsvYRAB/83SY6BuOkNSOHJB0P//vEXh7e2smuziC/uXF+dvl3nmrhF6sPccbkMn51jIHq+tYBgvE0T+7q5v3LhPdCWtO59GevEEmq3HP9XE6fVIbPYclmUgbjaeoKHegGlLjeqjG+seGukZn/GYNHztdJDkD/zmEbiOarJJCg6aLhL/oFn5Xp3WzQdHFmYrFG4pRvjX1iMTskzrxneF28TxC+ykXgqpKYeYeM2W1Q2Dz6vrM/JlE+X7Q0LW4p65j/rsRY2qohtPwDendCqF3os2L9wv2+Yg54MtXYtlfAv0uYQBY3i2233iuMUKdeMbyvebeJdRt/Ln6vXSbyJPc8KCpkDSOy47q2CFf+aC8s/KggYhYX9OyEzg3QdJZoLc68QWRflkw+vvHk9GvFcQsbx17/OmFt8qFs6sExbZhcJfYHiG8X1hfu5dXZNqS1wYe1wYehGVldl21CAdYmH5ZqV06L0TGrBDWYxFIliJaR1DASKoYigW5QdPVEAo8cIPxSB96z67P3tU8tzlad4rv6Se4LkAQq7l6IY1YJlmoPaDqWeg96NI3seW29Vg45Mozsj2GIwmK6J4rssryuCtlIpP0xen+8FcVroewjs5FM/76moXm8e5H/1OXxurG0qZgip4WZI3RdJ8JZU8qpLXRw9jGxS2WZ1l25Z3QsypcvnMLV82tyhPkmWQwtOCzKKN0VgNdu5oVPrmD1p1aMiiZ6PdDTBjvv0Tn8mP7aG4+AxSUx95MSJVcluGHdat5/7wZ03aBggsTCu3NF8cXTJCZfL2N2vn5itOZzOq/crbPvAdH+MtklZtw6HGE0ElavxLhzZCzudzEBA+jaDK9+H7b8Zuz1BQ2iElWQMUQ7/KwgYgceH96mZiEUT4L6jO9XqF1Unwb25+5LVgThGne60HL1tYif/v1C5D8E/x4h6C+aKOwuFMvwZGXrC8KKomOD+N1eIKYhT+T+bbZD0fh/2SHcUHXiewfQM3Yw1loPFZ+ch2EY9P5iG+pgAltzIc755XjPGTfKWiLdG6Pzy2vp/dEWDN1A8Vrxnj0OU6kDY4TsQDIreM+oy1apkocGAXDOK0PxWEkeCRLb2ENkdTvaYHLMx2prLsB9ajW+S5qIbenF/9PthJ5qRTIrGJqB6o8TXSOSNNI9UQxt7L+1yLouur62jtg2P5ZqN2V3zaXso3OQLQqJfQF6vrdZPB9jtGziZKCHUxhJDS2QPO5jyOM/Axs2bODWW29l6dKlNDc388wzz+Ssf+qpp7jppptYsGABzc3N7Nmz5007dr4ilsfrxjcvm/66tj97WsUoEgZw09JxnD+jkuIxJpkunFmVk3MJYnr0kduXkNb1nISBNxtd62DP78UXe9VyA1mBZ2/T0dJw+k+HW44jMXjQwF0N486RObQnwr57IxzsixJLa1mvr5EwdIPONeBrGvbxGom+HQarP6VTsVBi0f/knrhdVRKBAwbO8uOTq0inwbqv6BRNlZh5+3vgemvoRGoc52RYs0j8DKF8JoS7RUVsCO5KmDkc2ktlpsrqGUOgLUlQMkkQusHDMPdWoeMaGbp98CnR7qxZLMT6I9F4hiCPNa9/8ONfRfCpI0RWt2ObVEjx9cOTl5GXO0AzSO4bxDm/nIJLxo+6b6ojQvDJVoykhuqPg6aDrOD/5XaMpIYkSThmja2fTHcJTxYtmCLySifmKifOBeXIDnM2W9LQDAYfPYgkSXjPa0AyyXhXiUp1INOKHBLjW+s9qN1RLNVuQs8fJfRkK46ZJRReNVqQn9jdjxZKkdg7gGNGSU7mJbKoNCNL/7J5rLXBR/HNU5FdlhOGm+fx9kI3dLoT7cS0KA7FSbmtGvktjjiKxWI0Nzdz6aWXcscdd4y5fvbs2Zx99tl8/vOff1OPnf/k5fGOosT9+lqIsixhPV4+4JuE4mlQOgdcFcLwNNYDoTbAgLhf5M+OxP4HdLb+xKBiESz9msKK5lK+fOEUqnz2MUkYwKFHDTZ/z8BVRU5k0BAGDwpH/P7do6/0F9wtMecTEmbH8U8+vZtE+zJ42GDmGHIpQzPoXAsFE8BR+i6ollXOEXqrYw3QjoeiCWNPTI6EbBrb+2sIztIMwZLFsY8V99evEGRrpLB+CMXN4udthOIdvmAZ/PtB3CtqUNwWCq9oJtURxj5DtChTnRFSR8M455RlW23BJ1tJ7gtgqffgu6Axq6+y1ntIHgljKju+7YT3nHFY6jyogSSDfz+I4rFQ8dncCLR0V2TYHmNeOYrbTPi5o9iaC/CeMw5rozfr2u87twHfuQ3Z+wE5FbmR8F3QSGyrH1O5g65vrscxsxTvWfUA2Jp8lH9ibo732b8C2/ixP3PJIyHSHRGc88vzLcu3EYei+3hl4Fmi2rCW0qm4WFx4Og3O1/ibfwNYvnw5y5cvP+76iy66CID29vY3/dh5IpZHHsfA6pVY/u1hcuQsh2XflNHTY5uvHgtZlrhuUf0Jt3FVSUgm47hGqA3nS5hsUNCce7whzzDzGOfNw4/raEloulim9gzhGXbs/Ydw4G8GW39i4G0gR3/2psK/B3b9VbQMG8987e1db80wxXGhmGHaNcdfXz5d/LyDiG3zE3r6CJ4zanEvqcIxo4Ten20jsWcAyargPasex4wSHDOGdWL99+1GG0xipHXcS6tIHBzEXOnESKh4TqvNEdmPnG400hrp7hjmjGYstq2X6LpuPKvqcc4uI9kWIrq2E+uEAqKbeoht8+M7dxzmMifmCpeww5AlzGUOws+1EXmlk/iefio+PT9Hx2ZoOkZKR7abcJ9ei625cEw3fwBTkR3P6bWEnjmCFkgS39GXJWJD608WeixNui/+mhOmQ+j7zS6MhAomCdf8ty5eKo9hHIru42n/I6OWR7UIT/sf4QwufEvJ2DuFPBHLI4+TQPm84xOw8ZfJlMwSrcmTRdkciYsflbMRQcdCViTqV+Uec+tPdPY/ZLDgMxK1K3Ov0CMdBhv/V1QVCicaFE4SBq7Hg7NSQpJFRe4tw2CrsHvoP3ByROw/GIZhEFndjmRRsrYOICYb1b44se19OGaUorgsuBZVEtvmP64dg7XRR2JPP5YaN1ooSd89O0CHwqsnnjB2qP/PLSR29eM5qx7PihoiL3eSOhomtqkHa60HxWmm6H2TsdZ56P7ORlR/nFiFE+/Z45AUaYTVBdgmFxFZ24lkVtCTak7br/cnW0n3xCi5ZTrWOg+WmlxbmuSREIk9/biWVmUNWF1Lq0CRsDWdZMV0DPh/s4v00TC+S5pOiljZJxWSPDSIpWZs4pbYH0D1x3EurMhPXL4J0A2dVwaePeE2rww8R72j6S1vU77dyBOxPPJ4EzDS2+tkoVhf330GDxigw+BBqF2Zu85eAuULQEtwUnFDlYslLnpURhk9J/HmYdwKkRH5Wi3E/0CkOiJogwnsUwSZSrWFCf6zFQDbhIJspcd79jhMxXac84arhe6lwtYhvtWPoek5FR5D07FUu3DOL8da50FPaZhKHOjxNIEH92GkdIpvmoptwmhCIylSzq1nVT2xzb24llVjpHV6frQFI6FR/IFpeFeNI76zD+eC0YRGCyZJ7OlHj6roUZVUeyTbljQMAy2YAs1Aj+TmeKr9cRSPlcBD+1F7YmCI5w8g20x4VtRm9x96/ij2acU5IeWvBdkiZ25PrgJceOXxW8+GZtD3212gGchOE44Zb44/4X8yuhPtOe3IsRDVwnQn2qm0v1WZau8M8kQsjzzeI1jwWZmezUbWeX8kFIvEsm+8vhajyf4WX8UPhVjnkQMjreP/+TaMtE7RDVOwTxStOeuEAmSLjOITuklD1Rn8x0H0pIb71JqcfSR2DzDwlxYwyVR9cVFWwxTb0svgIweRrApVX1qMbFEo/9gcDN2g5web0QIJ0v1xpFYZa72XgftbSLVHKL5uMoVXNKOurMu64tsafcMESjNQXBZUNYlsN2Fp9GGfMtr7CyDwtwMk9g5grnFjG+/DOm5YVClJEqW3z0QNJHJIVGxLLwN/acHa6MU5u4zoph5sY3iLAYTXdBB9tYvE/gBoBqZSB8U3TnlNwX7xDVPRwinhbXYCqINJgk8cxj65CMf0sc12JUXCPqmQdFcUS9XrM9POY2zEtOibut17CXkilkce7xHYSyTqz8q3QN7LUAcSyG4zpjIHal88Swpkq0LJTVNzttVCKRItAUBYTxgJldDzR/GsqMFUakd2mjGXOSBTwYqu7ybtj6N4LZgrXXR/ZyOmQhvu02qJbeml6L8mo4dT+H+5HWSJ8v+eR2ybX0xctoVwFpeh+KwM/HkvssOM97wG0A3iO/uw1Hkou3O2CAa3D582EgcCRDf04DmtBnNZJnu13kPiwCCuBeU455YL77JMgDiAqdA2igwZaT17615ejXv56D5/8tAgplIHjuklpFpDmMqdxNZ3o4VThF9oxzm//IR+YpJZfk0SBhDd0E18q59Ua+i4RAyg6L8mH3edGkgQ396HY3Ypijufb3kycCgnlwF8stu9l5AnYnnkkce7EoZuCI1OtRvZ9tZ8VR0bWv2vQouk6P3xViSLQukdM8dsf0Ve7WTw4YPYpxVTdscs1MEE/X/Yi7nETuEVw20wPaGKSku9h4LLJ2AkNax1Hvru202qNUTk1S4Kr55I5d1iIjTZFiJ1OJhtbZbcNgM9lqb/3t2o/XH0uEqqLQyagWdlLbLLjGw3odhNFF+fcdzPEI5UW5jYVpHt6lpWRWyrn9CTrZgrncLw1JyrzQk93UbqSAjZolBw6XgMTSfRMoDJa8E2oQA1kKD3R1uQHWbK7pw1pht+ujuKbUoRpRVOTCVji+8j67oY/NsBzBVOyu6cTemHZmLoBtYaN5FXOwk92YoWSIxp3fF64ZxVSrojctyK38lg8JGDJPYOkO6NUXh5vjV/Mii3VeNUXCdsTzoVN+W2tyYvNBqN0tbWlv29vb2dPXv24PV6qaysZHBwkK6uLnp7Rfze4cOHASguLqak5F+LKRtCnojlkUce70qEnz9K6OkjWMf7KLl52mvfAVHNiLzahe+8hpyW2FiIbell4K/7cJ9SlfW8+lehBVPC3FQCPaaOScT0hJa5FYasqaNh0kfDpNvD+C5qyt6n/3e7SR4M4j1nXE5Itef0WmS7Qqo1RNdXXqXk1hmYK5z0/XoHRkrHXOlEtpkwlzmQrAq+i5pQCqyku2PoSQ3HrBIUr5WKzy7IVqdsEwpy9GLWcR5cSyrRE0LbZS5ziEnIzFSjYRjENvdiKrJhrffiXlZFxCLjnF+efY6p1hAYkO6NI1lk9JiKntTQUzrKMUQsvruf/vt2oxTZqPjkGDYhGShOM0ggu4YrXpIs4ZxXjh5XCQeOovgsDD52CPfSKhTvv56sYSq2U3zDlDHXadE04ReOitftOLYXANbxPlJtIaxNvn/5cfynQZZkFheePubU5BAWF572lgn1d+7cyXXXDfsQfv3rXwfg4osv5hvf+AbPPfccn/nMZ7LrP/axjwFwxx138OEPf/gNHTtPxPLII493BHosTXh1O9bxBWOKrof8oZQxDH+Ph+j6btIdEWLb/K9JxFIdEdANUkfDr+txjwVLlYui6yYjWWRMvmESYOgG8e1+zOVO3MursdZ5siHWtomFuM+oxVziyCFuQ9W/1NEwPT/eQsHF47FUubBUuSi4ZDydX3kVI62jhVNieb2XdEeEwiuac2wgXAsr0CIpBn6/B0PTkSwyRlobsyqV6owQ396Ha3EF7lNr6Pr6OmKbeim5bQaVX14MqmgdJnb3E/jrPjBJVH1xcU6sEQjCVHzjVKKbeois6aDgoiZhmGozZduGRlonvqcfa4NXaNuk4QGB48E+tZiKzy5AdphId0fBJGfNXd2nVOM+pZren2wldTSMoeoUXNj0mu+ZGkySagthn1ycc3xD1UU7tt6DyZfbyoy+2kXkpQ7iO/qo+O/5x+4yC/eSKtxL3sqR5H9PNDgncAYXjuEj5mZx4WlvqXXFggULaGlpOe76Sy65hEsuOU7O7RtEnojlkUce7wgir3YRfqGd2Fb/qJOaoeqovTHcy6vxjPCNei14z2sgtrV3TI3RsfCcUYe5zIF1jAlCEBOIyYNBLHXuk3Jdt08uItUZIbEvkK0yxbb0EvjrPmSHicovLMqSQ0PV6f3hFrRImrI7Zubsp/CaiWihFH337ETtiwtSkMl9RJJwzCkDA+wTRbC47/wGIi93ZHVWIyEpMpJVwUiC/1c7kawKJR+cTmxTD/ZJRVnriMFHDpI6EkKPp/Gd14i5woUeSWMqsDL48AFiG3souHwCqW4hlFa8VlCE11jgoQO4T63Bs0IMFJiKbMR390NaJ9bUN4qQBJ9uJbK6A+uEAkpumipMWV2vbcqquC2ke6L0/GAzkkmm/NPzsiRdC6VAllB81uPaehyL/vt2k+6I4FlVj2fEMET4pXZCTx7BXOWi7MOzcu5jm1xEfE9/dto1jzcfDc4J1Dua3nZn/XcSeSKWRx55vCOwTSwkvqNvTC1O8nCQyCsii9C1uHLMVlPk1S6i67rwnd+ItUEQHGudB2udsHOI7+4n/PxR3CtrsTcXZu9nGAbxHX2jbCGORfCpI0RebMc2pYji9x1fmD0EPani/5mYhiz+wDRsjT7MpQ4kizLKK8tIaaiBBKiGmOQbYUwqKTKmAhu+i5qEn9biYV+x5OFgNqPRvbwak9dK+LmjxLb0ovbFKflArgGtbDdR/om5pLuj+H+xHUPVCb/UQezVLhK7Byj76GwAHDNL0KNp0j0xOr/yKsU3T82+jmq/iCZS++IYkbR4nWs9SJJE8nAII6mRPDgIK2oIv9xB8NFDWGrcQlg/Y7R2xlziyNza0ZMqkTWdmKtcOOeUveZrnGwNgSQhmeUct/vo+i5SR0IoPutJW1qYS+ykOyO5sUkgpkZlstVFPZYWvm2Ti7BUOCm7Y9ZYu8vjTYQsyf92FhUnQp6I5fFvh65EO4/3PECtvYEzSi94Q/uKqmG2hTbQ4Gim3Da61dCb7OKx7vuptNdxVulFb+hY/2mwVLoou1MQAT2lgSGmBwEsdR7sM0pQXGZkz9ityeimHtJdUWI7/FkilrN+fbcwJN3QnUPE4jv7GPjjXiSLQuUXFx3XjHOo2vJaU2+po2HCL7XjXFiJUmBDCyZRMo/ZUuOm8kuLRg0ESBaFkg/OwEioWOuHH3t0fTd6QsW1rApbkw9roxcjoy0D0QK1TihAcZjQBpPENvZgn1aM2hfHmTEp1cIpMdloGAz8dR+SRaHgkvGUfmgmklkW4v0Dg9hnDpMk16JKXIsq6fraOoyURrormiViJp+VFGIgwXdBo9BHZapxiseCZJGzVhNGUjxW2WXOEamHnmsj/GI7BZeMxzmvHPuMEmSLIjR9r3SCDI7ZpaALDZq52o2lInc6ToukiKzpBN0Q9x8xwGGfXkLyUDBbDUscGCRwfwuOeeV4zzgmuiqDwqsmUnDp+FGtWvuUYqq+sgRJycRD/bOV6IZuEi2BrHZMC6WQnabsNiAsPtCNUQMNeeTxWsgTsTz+7TCQ8qMaaXqTncfdRjd0BtMDFJiLTjg1tzW4np3hzXQl2rm08joSWpxn/Y/iNLlYXrSKgZSflJGiJ9Ex6r6BVB9H461MdE/HcjwL/f9wJA8NkmgJEN3Ug6EZlH90NorXimxR8JxRR2xTD1ogOabtgO/8BuLb+3AvG1uL4zmzDsVjyakoAZiKhZjdXOEck4SpAwkUrxX3MhEpJLtP3DYLv3CU+K5+jJQuKky6QfiFowweClJw2YRRjz3dE6X3J9swFdkoHdH6UgcSBB7aD4Cl1o213svg3w4QXd8tCMz8ctT+BOmOCHKDl8CD+1B747hPq6H09plo4RTRLT0E7t+HpcaN95xxxLf3AeA+tYZUV4RUWxjfOeMo/8TcUc/D0A1sEwvRE2pOpVDO5MEqTjN6LI2lzpO1sEgeDmKkdFJHQiQrnbhX1GBt9GIeEaMEENvaKypnrUHxmmY0cbbmAqzjfViq3UiSRGR9F4OPHETxWij98CxkhxlJlojv6qf/97sxlTqwNRfgWphrJGsudVByy3A1MHlwUNh/7O4/LhEDRpGw6JZejJSGa4RRraXOTXRLL5Z6QUxj2/0M/Gkv1vEFWcsRI60Ln7ZIirIPz3pd0Ut55JEnYnm8p9Cf8rMu8CITnFNock0ac5tJ7hmYZTPFluO3nV7uf4Y9kW3M8i5kfsGy427X4GymK9nORJeY2utNdtGeaAVgQcFyJrimIkkyxZbRztrP9j1Gf6qXpJ5gXsHS1/Es//0Q2+5n8JEDuJfX5EwC9v+5BT2Uykbv6EmNoVNj8LFDJPYMoPbHKbpm9HttrfWMyg00DAMMMVFnqXRhGcPOwFLhpPJ/xq6Ehdd0EPzHIRyzSim8sjlb2ToRnIsr0VMariWVYp+yRPilDoykJlqLIzRSekojur5btCb746AZkHkciteCbXIRRlLNtsXUQCJ7G93UI3Rc0bTw6VpcSWxLL7YJBWjhFN3f3oih6mCAHk1jqfXgXlGDZBHC9p7vbQLNwFLtzhIZLZJCC6WwVLpItYaIru8Wy1clhc2FRcF7dj2uBeUYEnR/dxOSJFH+ibkoXisFFzUR39lPaPVR4tv8FL1v8qhWc7onitor2pvHtioVjzVnItZc6UKyKcg+K11fXYdtUhHF101Gi6QgkwvuXFRJ/+/24FpWhWtBBfG9A8gOU85nwbWkkkTLAEqBLZvP+lpQ++ME/iLE2pZKV7ad7Jwr/NCy72FMzb7GkEkLCCVRB5Og6miRdJ6I5fG6kCdiebyn0BLZwdH4YaJqJIeIaYZKVI3gMfuQJZkJrqmj7htRQ7TGDjDeORkdIWzWDW3UdiNRYavmssrrs79X2+uZ7V2Ey+TGrgitS/MYxwKosdUTVcNjtjQBVD3Ns32PoaCwouQcFOktCt9+G6An1BN6fSUPDKJHVRL7AjgXVmAkNBSPBeesUuJ7+vGsrMNUZM+6uqf74igeC0qhDfvUYvSURvDRQyiFtqywWh1MEtvai3NWKYrXiqEZ9P54C2ogSentM7JapCGo/XF6f74NU7F9lJZqCEZcWEvocRUjrRFZ14213oOl+vju6UMO9Fo0TWxHH/aJhRRcOl4Ygs7O1T2FnmkjsqYTU6kDz2k1RDf34JxbjqRISIpM8XW5WrTCqyYKny6XBf9PtwKi0mcbXyCqXplqjxZKgW4AhqimNfqQZCknINtzRh2ptjD2EY71vT/ZihZIUnTdZKxNPiz1HmSnmci6LiIvtuO7oBHX4kpMRXbUYBJJFlOOQ+TRVGTHOa+M6OYe1LgGZomBP+9FKbBlj634rFhq3BiGgbnCSWJ/AD2SxjFr+OJFj6UJPn0EW6OPqi8uFlqzI2G0UBIA14IKTEU2zGVOgk+2iiGGbX7MpQ76f7sLFInKzy1AdojqpRZIku6Mku6MovbFsmazJ0LaH0f2WlBcluP6mYGYRjWX2jFl9hl4cD+xjT24T6/F2uDNtnRB/F3Ed/Vjm1h4QrPZPP6zkSdiebynMMU9i7gWo8mZWyH5Z89DdCSOcFrxuYx35Z7MAql+3CYvq/uf4mj8MIF0H8uKzmCyewbFluMLhHVDZ2doMz5zIbWOBkCISE9U3dIMDVVPY1VsLChczoLC5cfddiDdR2tMtKLmpBdRYBH6lrSeYmtwPeW2Kmrsb8zf6u3A4N8PEnmlE99FTaNaRkPwnCmIlm1KIb0/3II6kKDkg9Pxnj0umyc4Ev2/3YXaF8d7fgOO6SXEd/ZlqzWuBRXIdhPBRw8S39lPujNC0TWTMDSdtD8uqhKDSUxFdvp+uwttMEHxzdNI++Po4TSpuIqh6khjeH25T6vF2uDDXOUisraL4OOHUXzWE1oVDCFwfwuJlgCuZVX4zm0Y05XdUu0S4dUTCwk8chAjrmb9sI7FwP0txHf0UXT9ZMyldszVLiSTjGtp1SifMsVjoeyuOcS29RH652FSR8N4zqjLqfoZaV14l3VHkawKoWeOCF2TJFzn0+1hUq0h8broovyU6hq2EDB5rZR/ci5Ioo0a29yDZZwX/y+3o3islH96Lun26LAh7NIqYXthkim9fSYgfLj6frMTdJA9lqywPrqxh+jaLuKZMHPXkkrMZQ7S3VF6f7oV73kN2cBv18IKJKuCa145kkVBdpqQXZac99Nc5cK1vBpJkTBlyH1874Agc8cQ9CEEHz+EHkzhnFn6mgbC1gZf9t/aYHL4uGUOEdXU4MU5r5zBRw9ldXxF145dwc8jjzwRy+M9Ba+5gNNLzhu1PG2kcm6HsDu8lZf6n6bGPo5yazVdiXbKrFUokkKpdWzSMITW2H7WBp5HRubG2jsxySaiapiNg69Q72iiztE46j5/7/oTfakezi2/gkpbzRh7HUaJpZx5vqUokpIlYQB7IzvYHFyLNWzjhto3ZhT4diA7VTcQzy7LVrB8Vjyn1aK4LLiXV2PohjA01Y2ssHssmCudqIFEtkIme63IDhOmMmdWn2SdUEDycChrFSFbFEpvnY4WSmEbX4AaSpI8EAA9497eXEDhlc0Ymk7vj7dgm1iE75xjSKBuoKc1MAyhhXJbsE0qFC0/RcrqCWM7/EQ39OBdVY8lo4cyFduhJSBujwPH9JIsQdMGEyQPBUfpqYaQagtjpHXSXVFsTQWU3joD/y+30/vDLZR8cPqoIQKTz4ZrfjlqbwxzpRM9mmbgT3sxlToouKiJxN4B9HBK6KeCSSIvdYAM5Z+ah6nARronimSWUTwWCi5pYuDPLcQ29GAqsmGp8WBr9GWP2fujrWjBJM6F5aAa6LE0isOMPN4nooYKrOjRND0/2IxsM1H+qbnIVhOyTcFc5UaLpLLTioZuiHDy8uEpS0mSsI0vIPjPw6Q7o8S3+rHWekj3xen9+XZki4x3ZR2y3UTF5xaOajPrcRXHjJLsexPb7mfgj3uzNiJjwbWoktjmXuzTXp81hX1GCaYCK+4V1UTXdRPb0kt8Vz/OeeVYKpzEIMffLY88jkWeiOXxrsbe8A5SepJpnjknFNWfU3oZg+oAZdZcYbZuDLcgZ/sWMtu38ITHC6tBklqCYmsZJdZyCszFFJiLMMniT2VXeCt7I9vpTLRliVg4HWRz8FWanJOIamF09DGDadf0P8fu8FZWlpzHOOcEJEliinvWqG2rbfUUWUqpstWR0OL0p/xU2mrelCietwIFVzSTOhzMTtKBaEUOVbCcCyqybRlJlij7yCyhSxqj3acnNQxVFxWuEfmEqUNB9JiK6o+J7WJp9JhKyQenYy51iPsltew+tVCK3u9vRrIouE+rxTahAEmScMwqJfRcG2pvnFi8dxQRCz7ZSuSlDuxTiih632QqP7eA5OEgHV98BWu9l5L3Cz1T+IV20h0RooU2LBc1kTwSQg0kKbppCvYJhYyFZFsIPZTKTvYVXTMJPaHS++OtGJpO6R2zctpXRddPJnUkjCMz3ajHMlFFZAYKxpjmlO2m7LRibLuf5KEgycNBfOeOo/DyCSRaBnDOryC6sQfZacY+rQhTgRgmMJc5qfj8QtEmNcnZ9mP4uXaMlEbhNROzJNI+tUiQjTnlOGaWEt3YQ/jlDjwrarMxQ6muKBgGhqZn9V16TEXrj4MsYSgS4dXtqINJopnJSdfi3Da+77wGYtv8uIYGMjRdkHhV5FeGnmsj0RKg4NLxWdIOmZbrQIKi6yZjn1wkgtRN8glJ8tDkKED/H/aQ7opSfOOUE+q9tGiawYf2C1+3aSU4phWTPBTM+sW5llThXFiZ1ajpQ1Ol1veuDCGPNx95IpbHuxZhNciL/U8AUGItpyKTMRZKD/Jw1x9wm71cWH4NsiRjVWyUKZWj9jHVM5syaxU+8/HjSIag6mke7LyPpJ7gwvKrKbdVc0XVjTnbNDkn0pPsoNExMbtse2gjeyPb6Ut1c2HFtYTSAYospewMbabeMR6XSZCD3mQnOhr+VA/jMg7RD3f/kcF0P2eVXky9Q7iBF1iKsrq0v3X9nt5kF4sLT2OaZ87rfQnfFihOc5ZcJNtCKF4r1kYfjlmlKD7rKG2M4rGieEb7ghlpjZ7vbkKLpin78MysrkePq4CBY15Z1kgz9KzQWiX2DFDywen0/nAzaiBJya3TsdZ60FOaqLxJEo7pxTkkNr67HwDnvNFt6SFx/kjLjHRvDFRD3GbgPbOO6MaerM4p/GI7id39YBhjEjEtroqwbdWg+Kap2SqeHk2LiqIBejiV81qZSxw5bTTJJCHZTaDpKG4zoWfbMJc5xjQwNTSd2JZeFJ8V96nVSGZF+KYVVCBbTYSea8OIq6Peh5EEYUifFnq2jXRXNCfhwHd+I77zxYVIYn+A2MYeAByzyrLJApIi4V5Ri2PWcKtPT2ri/ZQkkvsHCT4u8vpkt9BlSWaZyKudhJ87ivc80d4d2QY0lzkp+5jIvFScZiKvdKJH0iT29OcQMcmccezPeI1Zaz1U/c9CyNhNqP1xAn87gK25cNTUraHp4jOiGaQ6IickYrLdhG1iIVowibnCieK2jPKcGyJhWiQlBiYMKPvYnHwYeB5Z5IlYHu9aOBQXdfYmUnqCQvPwySaoBojrMZLJJKqhYpFO/IVWYn1to0gASZIxSxbSpDEfx26i0FLC+eVX5Swb75pMX6qHZtc03CYPbpOHF/qeyAwWtHJ2mYjFOL3kPDoTbTQ6T14rYpfFycUmv3NTWIYqtFfH+jodi/jeAfp/uwvZZabicwsovLJ51DaRVzsJv9iO77xGkUOYEW0HHj5A8sAgWiwNmp6tHICoUkVf7cI63pd1k7c2+Yht92ercHpCy2l3SpKISFIKbSheK3pSI/DQ/pwpSFOxHUPVSR4OYq33IJkV3MuqccwszXF6T7QMAMKragi25kKCT7Ti/+V2Sj4wTZzMdQP3slxHf0Mz6P2JGCAwFdnRw6kcOwtTkZ3im6Zi6MZrtq/0tI6REs8zvqOP0NNHQCbH82ooxFwLpUjsEY/bXObEUHV6vr8ZLZgUQeJxFSTGTBVQ++P0/34Plho3riWVFF47EcVmygrhc56fYWAYBrYpRWK4wjv8+vb/YQ9qTwxJljCfLsw5zcV2XKdWI8ky9uYCouM8gvC0hVH1TIzSngHx+PcO5Ojs9KTK4MMHUQpt2SGFgkvHkzwwOEpjV/qhmejRdM5rPdKqIrajj+SBQdLd0VFETFJkim8QYeiKzzYqGF4dTBJZ3Y59RgnWOg/F1+fmUqb9MSKvdIrW5Ii2s5HS0eNa5t/Dn+9UZ4S+X+/AMsa+8nj7sGHDBu655x527tyJ3+/nJz/5CStXrgQgnU7z/e9/n9WrV3P06FFcLheLFy/mrrvuoqzs5M4vJ0KeiOXxroUiKawqu3jU8hr7OFaWnI9Tcf3L/lyqnqYz0U6lrZotwXVsD21kRfHZXFF1I6qRxq4MnxQPR/ezLbSeub4lVNvrR+2r1FrBhRXX5CyrsFVzMLo3W8UD8Jh9eMy+nO0uqriWmBqhwDLaXR7gzNKLiGsxnKaxdURvBwYe2Ed8qx/PmXV4Thvb7dowDGSbArIkvJ+O00aN7+xHCySJbfcT3+HPirZjW/0YCRXPylpsk4qGI33IVKkkckiUfVIR9s8Nv2ZKgRUjpWXJQro7ih4W7UtUnWRrkPg2ISIvu2sORlrHUuki8PABoq924ZhTlm3pHVupGCI5phHLDUM44qMZ6FEV+5SiMbMtDVXPVtQsU4souGT8qNfmeOHRhmYQevoIssOE+xThol96+0zQDGS3hdjOfizlzuzj00Ipen68BdmqUPrhWRRcOp7Yzj789+zAd2ETWiiVjUGS7CZkq5JTRQJBdgKPHCDdFSXdGyO6vhvJbqLiM8PDCv2/202yLUTxTdNIHQ4y+PeDWGrdoypB1gYv2mASS60bPZZGi6kYKY3I8+0AOKYXU/rBGSTbQvh/vh09oWWTEmK1/lEVy+T+QWJbegFwL61CtpuwTypC8ViJburBmfH+Sh4KYmv0juk9pw4kCD1zBOuEApzzy7GO94352tvGFxDd2EPw8cN4VtbiWTnsRRZZ3U7klU6SbaExXfZDz7YR3+oXSQcZa47YNj+qP0bpbTNAkXKqbOnuKHpMJXkoOOZj+Y+ErkN3F8Ri4HBAeQXIb61RbiwWo7m5mUsvvZQ77rgjZ10ikWD37t3cdtttTJw4kVAoxFe/+lVuu+02HnrooTd87DwRy+M9h/Z4KwDlI0hOOB1EkU04lONXFYLpAEfjh5ngmsorA8/REtnBRNd0BtMDqEaanmQnDc5mzOSeiHeHt9KT7GRveMeYRGwsNLumUmtv4HBsH3EtlrW6OBZW2YrVMrpNNwRZkt9REgZk9T1Dk3THovcX20h3RSm9dQYVn52PbFWI7egj9MwRPCvrcGTEz+neGJ6VtSTqPDjnlqINJtHCKcwldor+axKpo2EUt5nIyx14z67Pts1Uv2jdaYEkoefaiG3ppeCyCVmbAEM3UP1xjLSOOhDHUuXCNkmQHqXQhmEIg0/rhAKsDd6cdp/sEF+B8jHtU0PVSR4cxFLvFRmGhTbsU4eJnyRJlN4xEy2QPGG4uGxVcM4rJ7q2i8TegeMSVD2h0n/fbqHxumYikiKTbA0SfuEoAKZSOwN/asFS686e3MtGTCKmu6JIVhk9lEKXwciYssZ29Im2anuY0g9nqkQFNgxVQ1N1jIQKI6YNY1t6Se4bBEXCe24DwccOIZlkRj7sxIFBjKRGujOSHZwYIsB6QiXwtwOYiu0UXNhEwYVNGIZB9zc3oAUzNhkNXkGsM9o0a60Hx8wSYpt7RZWzuRDP6aMJv3VCAY65ZSgeC8EnDmMd58Uxs5SBP+0V8UtpHbUvTmxzL8755Vmt2khE1nYS29xLqiNC+cdyW/1aOJVLwoee8zHvmX16MckjoePGYzlnlaL641nvMSOtM/DnvWAgYp+OmaZ1zCwFHczlY39H/Mfh0CF45WWIjtDOOp2weCk0NLxlh12+fDnLl4895e52u/nNb36Ts+zuu+/m8ssvp7Ozk8rK0bKY14M8EcvjXY+RrYGYFuXxngcwMHAqLspt1Qyk+niw817MsoVrqm/BIo9NbJ7ve5yeZCcRNZwlbA7FySzvAo7GD4+yvRjC/IJluMKeURqtmBrBgOMSpVcGnuNAdA+d8aOsLD3/uM9vd3gbe8JbWVR42mtOWr4TKLx8AulTqjFXjia5hm6Q7oiKWBx/HEemvRbb2ovaEyO2tVcImFuD+H+xHdlppuK/5yOZZFEdyEB2mrHWe+j65gbRviuxZ6tvrsWV6HEV1+JKBh89hOqPk9gzQPJQENmu4FpYSeltM1D74timFJE8EiK+qx/3sioUt0V4Yq3uQDLLWSf0IXjPrBdTfsdkWQ4+dojo2i7s00uI7+rLts9GVjJMPhsm3+iqS7oniuK2IDvMwt8LA9u0Ipwzj9/CSHdGsxURLZzC5LNhqXaLlp/DjB5TMZIaqaPhUfftv3cXqbYw3vMaKLphCrJFyZLYgkuaSOwZEG72DjOUQHogAYaEJIFxDLe2TSjEUu/HOs6Le3EljqlFaFE1q60CKL55KunuqCAQGJQ3eEEWWjEtns5WHt3LqkbZQEhmOccBX4umGfjjHmSnBddpNahdUbq/tQHveQ24l1ZhqDqpjgiWGjeyRaHwsgmE13SIfM2tfhwzS7FNLCS2TTzmoYqf4rGgDiZRvJYc8uuYXUa6K5rjYQaiihV6+gjuU6vxrhIDHN4zxVTmsdta672jwsBzXsPmQmwjIrUks4xzbjnp3hjWes+o7SVZwjn3jbe3/i1w6BA8/eTo5dGoWH7GWW8pGXs9iEQiSJKExzP6PX29yBOxPN610AyNv3X9nqga5qKKa/GaC7DKVootZST0OG6Tb9R9xq7ZCFTYahhI+SmzVjLOOZ4p7llZEjXFPItNg6/gT/awvPjMnNZkibWc5dbcq9+oGuEvHb/GAK6sujkryB+JMmslh6Itr2mT0RLeQV+ql0PRlnclEZNMcrZVaGgG0fVdImomYxpa8sHpqP3xnIqR96x6TD4rjvnlBB7cT6pb+FFJijRcaUAQOSOh0vP9zRi6gWtZFanDoRwHdkuNO5vxV3DZeBJ7B7BUu+m/bzcgTnyGqiPZFCRJYvBh0VrDMPCd24CtyYel1p2NqDkWJp+NyLouEi0BfOc3YCqwZYmM4rFQfN1k4nsHMDQ9e1EQWdNBbGcfBRc25Wi74nv66b93N6ZiO+WfmEv4xaNE13ZjrnKNGW6efY7jPHjPGYdsN6F4rfTdtxttIE7RjVMxea3ZCVLTWB5YmelG2WHKauhAVGL6f7sbLZbOmrgmDwfx37MDa62HgssnYDqGgJoKbZTeOkyQo5t6CT3ZinNRBbLDTHJ/gILLJ+CaX0H45XaCj4rWXeLAIKnWEJ4z6nDOK8dUbMuSsOSBQVAk3KfWZL3AhpA6GiZ5UBDQirsXEnhgHzA0oAGBvx0gtqkH1ylV+M4RJ2D75CISeweyIn7feQ34zmtAi6axGYK4R9Z20v2N9biWV+Mb4VNnqXBmJ19HYsg4VgsO29+EnjpCbKsfbTB50totQ9Nz8ieHUHDp6OpcHsdA10Ul7ER4ZQ3U17/lbcrXQjKZ5Nvf/jbnnnsuLtcb71jkiVge71pohspgqh8NjYgawmsuQJFMXFL5vpztPCYvl1feiEW2YD1ONSyUHkQ3NC6quJZCizjJj6xkGYbBpsFXMDA4Emtionv0l3UuDIzM/42MS79mqPSleim1VKCj0Z3oYJxzAlM8M0+4p8WFp3EgupcZ3rkk9SRpPYnL9Mavsv4VaNE0/p9vQzLJlNw2Y5RxaHy7n8FHDoJJpurLi0WUUJUrR9OlhVIoPiu+8xvRY2miG4SNhe+S8TimFmVPVOGXOgg+fgj3KdXZCBv75CI8y49PRodijfSEinVCgdClKTK9P9sGmkHp7TNxzCkjtrEbc4WT3p9sxT61iNIPzRy1r6FWprnMSejpI+iRNLEaN54VNXhW1OCcWyZE+7pB3+/2EF3bhWwzYZ9aTHhNJ9pAgtiOPrwjRfZD1ZfMecI+tZjkwUGcs0VVxTAMAn/dh9qfoOi/JmVbYZIkZaOf9KRGYm8/6JDYO4BrQQWSLGUqUOI9Cjy0H0uFE8/KOtTMNOdQNQhADSbRBhNCn6YbpAMJwms6SbeHQTVQ++OYCmxo0TSp1hC25oLshOFI6LF05lYVOr64SqIlgOKyEHqqDYBUezj7PJQC66i2Ynx3P1p/guTBwVH7t40vwH16LZJZJvxiO+7TanEvqxItYcgGaEsmmWRbCHOpA1OBLScWaQh9v9lJuj2C76KmbPyQHklj6IZoXwYSFF8/ZcxpRd95jdgmFeWEx9smFpI4mGvLciKEX2wn+M/DeFbV4zm1hvCaDmIbe/Bd1JTjtp/HcdDdlduOHAvRiNiucuy0krcD6XSaO++8E8Mw+NKXvvSm7DNPxPJ418IiW7mg4mpiWoQq+9jBvaH0IA923odNsXF55Y1jbgOwcXAN+6O7GUj1cW755aPWS5LE0qKV9CV7aMhYS5wITpObK6puQtVTpHRxFf1i35Psj+5mlnchDY4JHIztBWCWdwFFY2RRDqHMVkmZrRLd0PlT+6+IamEurLhmlCfa2wFtMCk0WVLmJKaopPviWQd0c7ULpcAqQprHyGpMHgnh/8V2TIU2yu6aQ6ojgm1aMZJZInloEEuNG4vDLNqHu/vBEFNoJbfOAIOsfktPaQQe3I/iMuM9rwFJkojv7if4xGHcy2twzimj8NLxDD52iMSuPkw+K3pcRXabcS+twr20itCzbaSOhtHCKdxjkLu+3+0muS+A7+ImvGePI7E/gLncgRZJobgswydsRcJS5xZh2xlrBt8FjSJH8pgkAfvEQso+MRclM3VpHeel7KPDLW0jqQnBuQGptlDWjkMNJAg+0Yp9ShGO6SUUXj2JwIP7GHzkQE7uIYgpzsSufhK7+3GvEB5piQODWQ81Pa7S891NGGmNgkvGI9vNKC4LkdVCJO9eUZPd38Cf95LcP4j71Bq8q+oJv9yBNpjEu6qexIFBkoeDeM6ow7WsimTmd+fcMvRoGiMtJv9cp9ZirXWjX5AWWr5gMtvqNQwDS6UTY375mKkLoefaSOwdQHFbSOwdIN0dzWkfD0UsJfYN4P/pNqwN3pzW5kgM6dSGjH/tM0rwnT8OI6ES39knXvOOSLZqGHhoP7HtIh/T1ujLqSaC0G4Nkd+TQbpbkAg1cxvb2EO6K0p8Z1+eiJ0MYrHX3ub1bPcWIJ1O89GPfpTOzk7uvffeN6UaBnkilse7HK/V1kvocVJGEk1VUQ0VE2PnuTU6J9KX6mH8cYLCASa7Z0LmfGcYBkfiByg0l4yadByC2+ThH91/oTPRxilFZyKPyIrsT/mZ6V2AWbKckISNhIGBZqiZW1FRsysOvCfhgfZmwVLlovDaSUhmGVOhja5vrkcLJCm8qhnHzFLMJQ4qPj123E/y0CDqQEK40ydUDN2g795doBqYyhyoPTEwoOCiJuGppRm4TqnCvbwm65+lBZPoSQ1tMDmsNVpejeKxEt/uF0as2/w455QR29pLfLuwIaj4/EIwDCRFRu2LE93Yg31KIXosnaPXycHQ8IFm4FxQhmRR6L93N0qhjYpPzcvZ1FrnIXUwSPjZNqzXTxEVQMMYJfIHso7xIAYUYpt7cM6vwFQo2nWFVzaj9iewTRxuVUY3dBPf5id1NIxjegn2SYUMmmSMpJZNIxjKLLRPLiI5rwxtIMHA/S0UXDIeLZQcrmhJwnPM0CQstR7MpQ4MQ7R9jZRGfG8/4eePUnj1REyFNpKIlqQWSRF89JB4vk0+ohu6SbdHhN7NomAd50XxWJBtJuI7BYm2NnqxjWj5dn97IxgGZR+fg6nARmyrn8CDB5BdZgqPEc8bukFkTQdGQsM8uwxTqX1UKLgkS5hLHaSOhMRbltTQkyqydfSpq/j6yeiRNJhkur7yKgCOWaXYJxZSePVEtMFk1r8NxHSlkdBIt4dHRC11kzgwiO+chuyUrqEZxHf1YalxZ81vx4LvgkasEwqyhM53URPxHX3ZSme6NyYsVfKZk2PDcZLDCie73ZuMIRJ25MgR7rvvPgoK3rzv5TwRy+NdibAaYu3Ac9TaG5joHvsKGARRO7/8KqyyFZtyfK+tOkcjUTXMztAWvKZCymyi2jSQ6mNPeDtTPDPxmYdP2C2RHbzY/yRuk5drqm8BIK2nWRd4Ea+5YExz1VOKzmSGZx47w5t4of9V6h1NnFU62n7jeFAkhcsqryehJ0hoMR7p+SMWycL7aj6ESX77vrwdIyJeFLcFLZjM8dUaC4l9Afr+byeSzUTJh2Zg8lqRFRnH1GJS7RFciyqIb+8TzvYvHkXxWTGSGrYpxQQfP4x9ahHWRh/d39+MkVApuXU6riWVIEtE1gp7Cc+Z9cgeK845gtjaZ5aSOBTEVGQT5COjGxl8/DCJ3f2o/XGc88uRvcLewFRgy2k9FV03GdUfz7ZVZasCEqLdOQJ6SsuK2oeqLv337SZ1NIz37PqcapuhG4SebUO2m3AvrSL42CESLQG0wSSFVwkT4LGqLI7ZZaQ7oyLgPKkReqoV94oabBMKMJc4GHhgX05moffMerq+ug4QNhGDjxxEMkmUf2oestWE58x6Ims68P9iO6UfmoGpyI7vXKGx6vnRFvGeHQhgpHXKPjkXc5FdkLXFlaiDSaz1HkwZM15nppLlv2cH6fYIBZdNyGqqckSZhvifYQwvNxXawCTn2GToKY10V5RUVwQjoSHZFHwXNJww39E5r5xka5DYpl4Cf91H0X8ND9bocZX+3+9GdprFayyBc365eB614spqrNzPovdNItkawpkJZjc0g8HHDmHENSwVLtzLBYGKrOkg+PhhzOUOyj46R7RrTfKotr1sN+U8T2udJ1sJSxwcpO/XO1A8Fso/PX/MavJ/PMorxHTkidqTTpfY7i1ANBqlra0t+3t7ezt79uzB6/VSUlLCRz7yEXbv3s0vfvELNE3D7xcXil6vF4vljZnz5olYHu9KHIjs5nBsP92JjuMSMX+yG9VQxxS4D6YHWDvwPA2OZprdotWxO7KN/lQvB2N7s0RsfWA1R+IHiWlhzii9MHt/KfOfR/Fllx2NH2JXWJzEml3TsMgWVpVeTEgNUpTRnRVYiig0i38P3Z4s+pI9SJJMkaWE/lQvimTCrjhzKm1vN0o+OB09oeVcxetxlf4/7hEnviuakWRJVIZMMpJVZuCPe3GfVoNrfgWFV03EMIS9hHN+BZGXO4i80I7stlDxuQWEnjxCbFMPqSMhyu6chWSSMWQJyWLCd34j/X/cQ3x7H+nuKMXXT8F7Vh2RV7vQImlsjT7UnhjJFpEnmTwwiGdlLY7pxag9UZQCG3337ESyyBgpkRVZ9cVFWWNP2aJkSZjaH8dS66b8v+ejOHK/Fvt+vYNUWxjfRU0454uhDaXACu1hlGOmJpOHRdUMRAyQfXoJan/iNfMLzcV2Ci4bT+TlDsLPHyWyphMkcH1VBMxnMwszprqK24JnVT2JlgG0cCobSyTJEqHn2gg/fzS7b3UgganILsiTIlNyyzThOfaDzaAaKB4L5lInjtml+C4Yzk+Vy005FhBDFTfJLOM+tQZLlQvziJgqETw+V8QaJTX0lIa1zkPVFxcR2+4n0TKArbmQgb+0kNjVj31WKSgS1nrva4ZsA9mkhWMnXFMdkazgXz83heK1UnDJeJKHg2jR9JhGtEP7G9onCI2ZkdAw17qxj6jMmUodIEuYypyke6L0/GgrittM+V1zc3R10c09BO7fh7nKNWqqUhpphZHnYGNDloVFxVhTk0NYvOQtE+rv3LmT6667Lvv717/+dQAuvvhi7rjjDp577jkALrzwwpz73XfffSxYsOANHTtPxPJ4V2K8awr9KT819uGJp474EayyjWJrGVE1wsNdf0BH57LK60e1/1oiO2mLH2IwPZAlYksKT+dQtIXpnnk5xwmroVHWFesCqzEwcpZX2eoY5xiP11SQNZI1y5YsCRvCFM8sJrqno7wOAjWYHuChrt8hIXF19S0UWUp5X/VtKJIJWXpnJoSim3pIHgriPbs+Z3mqI0xy/yAA+tnjULxWLFUuKj+/gMDfDhDf5iexqx/XfHHlGnrqCOHnj+JcVIFzfgXm8h7MtR4iqzuwTSog1R7GPr0YyaxQ/vE5GCkte7K1ZypqQzE+sa1+gv84hGSWqfrKEtFSC6dI98RES3JLLyU3TsUxs5RUR4To2k6UjH7MXOqAMQTpiQOD9N2zA6VguCWppzTCL7ZjrXWLwG9ExSy6oZvE3gG85zVQcPH4rI/WECzVLmyTCpEdZhSPFeecMpxzTs6aIPJyJ+EX2jEV27GO92GpcmUrJ8dmFgLYmnyEnmgldThEya0ic1N2mLPVS9uUImHvML6AdG+Mnh9uRrYqlH9yHuYSB95V40i2Bom80gWqjmSRcUwvEdYd67spvHpijm6q5OapaKEUpiI7an+c8Op2ERF0yrCfn8lrzRISS52H0ttmkGoLE7h/H0hQ8bkF2UqSpcIp2pUm8ZxGZouOBfcp1Thml2bbwVo4RejpI1jH+/CsqkdxmLOfm+ShIP5fbkeyKFR8fsGo6hWICwojrWdbkNpgEgxwzSvPxjSB0P1VfXmxGBg4EgJVF3YiupHDqbJEdYzPmLXBR/kn5p7Q7DgPhDXFGWeN4SPmEiTsLbSuWLBgAS0tLcddf6J1bxR5IpbHuxIukzvHe6s70cGjPfejoPC+mg9hls04FBeqkc7G/zzvf5y+VA9nlV7MZPcMImqIcY5h4X2FrTrH6R6g0dlMo3N0FE+hpYTuZEeOPsuq2Diz9KLs76qusjm4lgJz0Sgip+ppnut/FI/Jx4LCsU0CR8IsWbDIVmRkTJIpe7x3EoP/OISRUDGXO7LRPYZhEN3Ui+K14FxcmVOdkG0mvOeMw+SzCnLzu90ivDsT52KkdSwVTso+Oofen28jtr4b1+LKrJ1A6Nk2jJSG56x69ITKwJ9bRCvnk3OzJy9TiV20hZxm9JRG8funocdS+H+1E0wyyZZA1kjWUuWi4u6FSIqcQ2BGwTDAEEL6dH8cc5Gd2KYews+2EbEpVHx6PupAAkuVi86vvooeTmOpdSNZFIL/PIzv3IZsWLRsNVF8/RS0UJLohm7h3/Ua1Z50X5yBP+/FVGzHVObAObs02+5MHgoSWd+F59QaJJsiKjaZKU1TiQNrkw9JkbBUuZHMMoZhZE1gnXPKsrYViX0DoBkYmpFtGw4NNfj/byfpzgiSRab7fzcIB/ykRuqImFL0/3wbSpEN16KMn1uRnfjOfpIHg6S7YzlETLyew//UomnSfTERNeUW+rKCyybgPr02R0sX2+5n4M8tuBZVZDMsx4IWTuP/xXZsEwqQXWai67uJ7xmg8nO5FQnZaRJ5lB7LmO+9ntLo/u5G9JhK2UdmYS5z4jm7HnRybFiGkM2srPNQevtMZIdpFLlzTC/BUunKySkdiRNlVuYxAg0NwqLibXbWfyeRJ2J5vCfgUJxYZCt22YEimTDJJq6qfj9goEgmdEPnQHQPOjo9yU7GuyZzesl5Y+7raPwwLsVNgaWYvmQPrbEDTPXMzmrMtgbX0Z3sYHHBaZTbjj8m3Rrbz5agEAU3OJtzKmAdiTYOxYQn0kzfwuPaagzBaXJxTfUHkeC4OZdvNzwra0keGMy21dSBBFooSXyrmPozF9mJrO0EWRIangODWKpdWCcUEH6xnXRHBD2awntOA/bpJViqXOgJFdlmwtZciOqPY20Umq20PyayEwHbpEKMpEZibybjcWYJak8Mx5wy0WJUdbTBJJ1feAXH3DI8K2uFhUOGAKj9CZKtQSw1HuG0vrUXx8wSjKQ+pgu+bXwBnrPqCD15hL5f7qD4A9MIv9SBZDcJuw3bcAvTd24Dib0DOOeUMfjoIVANkkdCWSI2hMCD+0m0BEh3RSm4qOmEr3NyX4B0ewTVH6fqS4tz1oWeOSKMXg0xLWkkNUo/NBNzlYvAg/swNIOiayYimWWRcfhSh2i9ymo2NcBI6wQfOwwGeM+uz1bxDN0g1R6m+H2TkMwK0c09qP0J0S4c70MLJUl1R9BCKbRImoHDYgpYdpjAJOGYUzqmtYPisyI7TJgrnQTubyHREsjxAYPcgQZA+L7pBsmjYdL+GKZi+5iVo+TBQVR/nFhcpeTWGSTHsJfQQiniewYouWMm5iL7mL5e6Iaw+9ANDNUgsraTwUdEVJPjNdrIIydYj8VQfunAA/vEhcm54/IVsH8FsvyOWlS83cgTsTzeE/CYfVxX8yEk5GyrbiTxkSWZ2b7FdCfaqbMfv3x9NH6Yx3sewCyZua7mDl7sf4K+VC9pI82iwlMB6Ep0oBkq/lQ3MOO4+6qw1VBuraLIUjqqDVlrH8cU9yw8Jh9W2Ypu6KwdeB4Dg8WFp43ZbkxoMXR0fPLJ+Ra91RiqmIDIIOz5wWZRsTqjTojavVb6f78HEKP70bUimLv4pql4zqwj3RVFi6RRPFasdR4ir3Yx+PABXEsq8Z3fiGfFsLbPVGTHOb8cI6VhqXKDDO5Ta1A8FgYfOYjaE0OPqbhX1OA5q45UW5jEngHU3hgmn42i66egx9IiXml7H/6fb8e1rIp0R4TkoSDRjT0YMRXfJU3ZlulIWGo9oIgoo1RrCG0gAbJEdEMPmGQKLhRkaqSlgffscUgWGdfS6tH7q3HnWEoYhkH/vbtR++MU3zw1x5HfMacMLZTCXDN6FN61tEoQ3fllYsovrSOZZfRomvj2PkBopGzjC4Tb/JZeLOM8lH5oBrLNRM+Pt6CHhaGrOpjMmdQMPXOE8HNHsU8vpuiaSThmlKDHVGSXmcCfW7LP13thI3o0TbI1iBFVia7vJrl/EOeCchzThtvyan+c0DNtGAjfseSBwUyOZiCnGqSFUvT+fBuy00zpB6cjmWQ8p9VgKraTPDRIz3c24V5Rg/es+lGvx9BnRLLIRNd2Unhl8yhfsOA/DxPb0kvqSOi4RqyyzUTZR+dgJFXMZc6sF5t0Elq110KqLURsYw8ArkUV+UpYHq+JPBHL4z0DRTrxx3V7aAMpPcn+6B6meMaOIHEqLkySGbfJiyzJNDgmktKT1I4gb6cUnUlrbD+NzoknPN6R+AG6kx2UW0dfuZlkM0uLVmZ/D6T72BneDIgcypIxnPr/2vkbdEPniqqb3lbLipOBJEvINgVNM7BPKcJUaMPQhc0BGYsBECJySZIwVJ34jj7SvbFspp/aHxe3fXFSR8PEdvhxL60W7aOMNijdHUMLJkGR0IJJLDVubI0+oqGUaAfKEp4VtRiqLlzXt/QSfqld6Jb8cZyLKlBfEH5ZkkXBMasUNZQC3UCLq8h2M7GtvcgOc46VgbXem6382acWoUfrSR0NE9/ZjzqQEM79x2h/oq92EdvYizaYGuXW7llZlxMUbaR00R7URZxRYvcA0Q3d+C5sxFrvxVLtov+Pe0ktzG3N2ScXZduLkk2BSAotmsZc7hTTi5EU1kYf8Z19xFsGUAqsuBZVorgsoi3YGQEdXFc250yMAtmhhaHnldgXwFLjxlrnQe2OokdVrPVeQs+1kTocyoZfh545QvLAIOaqXOIYeaWT2JZeTKUOvOc1YG30CdPZs+rQw+msP5s6EEcbSKAFEuhxVXxmzArOOWUkDwvRvZHUxvwcyhYFz2m1dH93E2pvDMkk4x3hnA8ikzKxP4Ct+cR/Q0IHJirVjlmlWMZ5UFxvvBptqfOIJAKbKU/C8jgp5IlYHu8pPN7zAIFUH+eVXzmKrIx3TqYj0TZqitIwhC+XSTZRaCnh+prbkSUFWZKZ6Z2PRbaQ0hMApPQk20MbKLdW59hhrAusJqqGWVZ0RrZ1GEj1AzCQ7iesBnnW/ygllgqWFJ026nEXmkuY5pmDYRhj+orJkpyZjpTe0SnJ40EyK5R9fC6GqhN6qlWIua9opvjmqcQ29qB4rUIUnZlQM1e6kGwKtiZfdh/es+qx1nmwjPNmXdBRDXwXNArt2eYe0eprDZJqD4uqxtEwRddPJra1l9AzbVgzsUqSSRY+YLrIgAw9dQQjrZPqipI+GkYptOI9QxChyLou0u0R3GfUorjN+H++HSQovWMmoaeOYBnnxT6pkPjWjG/ZEuFtZmg6wSdbiazuoP93uym+UYjVU0fD2CYVimk6iRzLAhAtP/+vtqMNJCj54AzhH2ZVKL5+CmoggW1iIb0/2kK6K0p0fTfWei+pjojIsxwjSzKLlJbVsgE5+YSxbX6MmIpS7sQxvYTYtl6CTx7BdUoNlkrnKBKmDiaFx9aUIkxFdpKtQfrv3Q2KRMVnF2TzFgFMhXZSh0MoGQG7pdZDwZXNOEfYcBiagewyY6lz41xYiXNWKamjYdJ9cYy4Su/PtiI7zFR8ej7Wei+FVzcjO8ykjoRI98RwL69GMskUXNSEc24ZlpoTG6A6F5QT29ybHeLIWTerFOeskzdizT7PMXJD/xVIynAFNY88TgZ5IpbHewaaodERb0NHoz/lH0XERlagRuLhrj8wkPZzQfnVlFjLczy5OhJHeHngGQCus93Owehetoc2slfazjjnnYAIGt8aFJ5NTc5J1DpE9Wx+wSmUWSupstdxJHaQnmQn/mQ3iwtXjNKFSJLE4sLRBG0IdsXB1VUfwEDPybl8uxHb0Ucq46Z+7ESgbFUwTDKp7igYQtcl7x8k8OB+kKHy7kXZylZ8mx8joaFloma0aBrZomCfWkxiXwDZakIpsWeF0am2MO5TqpHMsmg7vdqNZFNwn1qN2hdHj6mkOiIYCZVUdxRLnRfveQ1Y6j0Yqk6yNYjss+KcWYLaFcUxIxMHFEmhuC2kJeHaL1kUJLuCyWcleThEoiVA8lAQ9/JqPCtr0WJpAg8fwFzqoPDK5qyBp54hP32/20064x/mWlqNfWqx8B8bASOtkWoLg2ag+mPCSwtyjGV9FzUReGAfsc29mMscuFfUiO3MMp1fW4dzdmkOGQIouLKZ/nt3E36pI1slG0I601obsreI7+xHG0ig9sbwraonvneAwIP7cC2qxDG7jJ7vbASg7BNzkRRJ6LpcZmSnOef5GJqOqUxckMR3C/uJvt/sBENUlKyZKKLIq52EnjyCqdiOc1YpybYQ/p9uQ7IoFN2QO8gC4JhRiqHpdNy9BnQwFdlwzCxFMsnZfZ4I7iVVuJe8NRqidE+U0LNtOOeW51RN88jjrUKeiOXxnoEiKZxbfjmhdIBxjrFDdCNqmM2DrzDOOYEa+zgMw2BQHUA1VMJqKNsSDKtBWmMHqLbVU2QuwWlyY5Vt1NjHCXJlG24rqXqaensTNsVOpW04R88sm2nKOPU3OicSUgcptpQiSRId8TYOx/Yxy7swJ9NyCDE1gl1x5hC2ExnSvl0IPLgfI6GiFNqy+rCR8P98G+mOCO6VtXhOrUGLpjEV21F8ViSrQnhNh5iOrHOLYOZ6L6mjYXp/vg1TkY2yj81h4K/70MMpvGfXY23wocfSWaf9klumZYOXFa8V59xy1GCSgismYCq2M/j3g8S2+nEtrcJ3XgOuBRX0/mQrejiNc0pxjoYr9MJRQk+04lpaRcXnFqC4LOL5xTXkSjPO2aWovTEsdR4kSRK5kG1hoq90ke6M4Lu4CdeiSsyVLsxlouplKrSRbg8jWU10fW0dsk2h9M7ZORN0kiJT9L5J6HHtuK7+1joPplIHqj+OkdaRLQrOeeUEnz6CnhGbH0vEjMw0Y7o9jKHpaJE04ReO4phWgrXeg9ofz2iyMrqzSCqrw0seGEQPp0nsHcAxpyzrZTX06TP5bFR8dkGOfYShG/T8cIuIvIJMe1Z4xhmakdN2M5c6QJEwVzrRkxqDfz8oTHbtCtYaD+V3zSVxMEjXN9bhPrUG97JqJEXGMUu0I00lb/yzH9vWS2RNJ95V9dlA8H8FkZc7iW/vG+XEn0cebxXyRCyPdz1UXWVvZDtl1ioqbTVjGrgOYWdoM3si2+lKdnBllZhYuqj8WsJqMFvJAljd9xTtiVYmuaZzWdUN2eVecwEXVVybs8+n/X+nL9XDXN8STPLYfzJm2cz8gmXZ39cMPEsg3YdJMrEwMwQwhF2hLbw88AzNrmmcWrzqdbwSbz3cy6pIHBjEPmmYQASfaEUdiFNwyXjUQRFhZC51YOgGaneUso/ORjLJpPviBP8hInJKbptB8U1TMTQdPa6CZoj4GR1cC8qJ7x3ANrGQ2NZeYtv9mApt6DEVxWfD2uAT5K7QRnzvAP337sJc7abs9pkipxFyqnXec8eJjMSAmJa01ntFVSrT5tNCSRSXBSOtoQ4mkGyiMic7zFnD0sTBQfp+tQPZZcZ9Vh3mYgeyRSG6qQctkMBSLch04VXNGJc0ofrj6NG08KJKapAhYoK8bEYdSFB628zjvs5aOCWqeE4zjkUV9P9pL2p/nMIrm0Wc0HjfqPvYphRReFUzpswkYGR1O9G1XaRaQ5TdORvfRU1ZYh96+gjpjgix7X4sNW48p9Ugu8zYJxdh8lop/8RcABTP8DRvDgnTDFKdYaHX0w285zfgnFtO8kBAvI/k+mXZxhdQ9ZUlGKpO/293ibYzIr1AMsuYiuykX2xHj6ok9gWydiiKy4w2kCD4z9ZROjsQsoLQk63oMRXfBY1jenQNIfJqF6m2MNFNvW+IiDkXVqCFklnz3jzyeKuRJ2J5vOuxO7yVtYHncSkerq35ICCmH5/ufYTxriksKzoju22Tc2LGvmI4U7LAUkSBRbRyVF2lJ9lJha2G3sztsQik+vhH918ospRybvnllForCKT6TjozEmCKeyb7IrvGFPzHtEwosBY56f29XfCcXovn9OGqnx5Xs75UjukllN42M1t5GfjzXmJb/TgXVVBwYROmAiv26cUYKR3JptD7/c1gQNlHZ2OfUYIWSqHH0zlC9r57d6MNJMQ05Jl1QuivG0gWGdluwkiqYIAeTf//9u48Ss66zvf4+1lqX7u7qvcknaSzJ52VEDbZZVEgiDigojIgzEV0hovr1es4zqJnlMMd58zRcUYFFZxRERRwVBRXRDEEErLvS3d6re7qrr3qqee5fzzVT3ellyQQaCLfF4eTk9qru0/q27/f9/f5Uk4VCWxosudHjoss8LRFSD9zjNzuIfvvt0YYenQf+e0JvEtqqbmhUmztSzpBtMcn3Su6CqqdGh++cBaKqmDmDIa+Z0eQuJqD+JbWoSgKikfH3RoidttyFI9WfWrPsiiPlMCwMBI5FI82Iaph9OtqZQ0sBcxUidzWfnsAel+O0IWtWJbF8M8OYZVM+3SmqqAoStV4JN/KOIXDIwTOsgsGRVEwEjnye4bwLq7FzJScFR3V7yJ80SyMZJ6Bb+7Au7Bm0iHco5KP7yfzh2786+rxr25wZjF65kfxrYih13oZemwfRn+WuvcsQ496UFSF4jH7lCpA+Io5eFrsU6O5nQnQFMKXz656D3rcBwpTroiVkwVSlcMXvo54Vc/h8SJXzSW7qZfg8blmp8jdEsTTHmXkqcOoQbcM7BavOinExOtevacJn+qn1dfmXNZf6KVklejOd1bdNuZp4Lqmm6d8rN8N/pzd6ZdYGlrFrXP+etLbDJYGyJlZegpdmJbJBXWXc37tZc5qQ76c4yd9P8CvBbgsfu2kURTLwqudk5umZWJhOREXa6Pn0uhtod796sxMO51Un07kqjaMwTyulgBa2O30PKmVAmS0EFE0lbp32gWwmTfQarz2dpZHdQZ4F/Ynnf4ts1hGj/tQ/TqBdQ3O1zf5+H4yz3YTvLCV6FVzQVcZ+q/d9HxxE572KPntCcxcmfhfLmfoB3spHB4hdPEszELZjntgbMXM1Rwkty1B8WiK0MWz8K+px8yX6f2XzYQvme3kf7niPvxnNeJdVOusDBmZop36blhOuv54o9uA4ymaSsMHV2EkCwx9bw/l4QKx21c4hcwoV72f+J0doCq4GwPUvnMJ5cE83spKpDGQI/W0XQD7lscmLQY8s8M03L0aq2wfcHC3hhj87h6Kh0cIvqmFpo+vpzxcIPXrTvyr4mgRD9kX+8nvSNi3maYQGx2uqfpcVa9d9erUvWsJVqlM19/+HkwoHh1Bj9oxFu7ZYQLnNqN6NMIXjxX0g/+9GytfJnrNvKotTf/KOJ7FteiV04rlVJH074/hWxHD3RxEi3oInNuEmSrhaZu+IPLMDuOZXX2b8nCBwqFhfMti066mHS+zqRejN0tuR0IKMfGqk0JMvO41elt4z+wPVF3WEV6HV/PR5GklZYxgmCVn1Ws6o8GqHtVLvpzjd4mfE/M0sCqy3rnNPP8iLooZRPVap8jqLnSyOfl7OsLrURWF3sIxAPJmDv80zfWGafDIsQfJmVne1nQLYVcUVVGrRjdN5mjuIMnSIMtCq2dsxNGo0IWzyO0apOefN+GZGyF+hz37M3L1XEIX2PET5bQ9Zsg7P0pu+wCJ7+wisL6R6Fvno6gKNW9bQH5/kmJ3Bu8Ce/5fbuuAPSdSBa1m3Im18mgyq0l2Sz/5fUks00RBxb8iRnmk6KwCZV/os4M5Sybxv1zuPIS7LUzIqxG+dDZdn34GDAtXY4DI1XNJPrrP6ZcaLcTSz3aT/WMPhd1D+JfWYRYM+r70AhgWKFTFGlhlk2JnGndrcNKwUL3ON/Z+LCh2pvDMi1T1A1olEz3ud2Z4Hh8iqtf5CGxoquSqjfUYGoN5+r+6Fa3GS/z9K1BUheH/OUj6d1341zbgmReh1JNxCpLkEwfIvTRAsStF3TuXEFjTgNGTwbOghvQzXZT6c0Sunovq1uyRQT87jHdRDdFr2+1xVJXmf6tkMvSDvShuleh17Sgujbp3LcUYyOFbOvbay8kCmed6UFTsGI1KyrxvWYz8zgTKuNXDcqZE7/3Pg2nRcM9atJCbkaePkHm2m8L+JPV3rYKyRW7rAGamRPG85pNq5B8v8dBOikdShC/LVcWJnEjN2xaQ254gdIFd2BcOJMn8qZfQxbMmnJIV4pWSQkyckXRVZ2loJYVynoc7/52SVeKG5vdMuX1oWiZ/Sv4Onxrg5pb3E3ZF2ZV6if3ZXezP7mJl+Czng1JRFBYFl1fdf/vIC3Tlj6AqGlfV38CGmovwa4FpizCAsmWQMoYpUyZbzhB2RU/43kzL5Ce9P8CsnKBsP0Ge2WvBTBfBslcsRimK4nzQDnxtG6XuDNHr2+2ZfYZF6WjaWV0KrG8k9btOclv6UVSFyJvb8C6I4pkXwdUaJLe1HyORJ3TRLKLXzSdwViN6c4Bjn/49lC3CV9q3Lw8Xqf+rDhRNJbcjgWVauOeE8Y+LKzCzJQYf3gWWvUoSvng2hcMjeNsj9N6/GTNbIrChyfmQBTvNP7d9AN8yu6hQVAXNp1Mul4i9b2lV/EPyiQNknu0mcHYjNddPfmhEURUaPrSavn/fysj/HELRVeeUn2WN9ZHF7+yYsIozev/jE/nNbIn0H45RThYop4p2sKnXHuUDoLhVIle04Vtax8ivjqL4dDwLohT2J7FMi9Rvuwhd0GIPYi+V6fq/vwfAMzeMf2U9mT/1kPlTD7ndgzQvj1UVgMWulNOfF7ygFT3iwRjK45kfqRohZCTzUDZBUauGW1ulMmbWILupl0BHvOoyLMteQQ258S2to7A3iX906LZS6V1TgEnmUBa7M2hhN1rAVZk5msHbPrZS6WoIUDyasqNGToFnTrhqJWz4Z4cpHhoBVaH2xoUUDiQZ+OZO/B2xqsHoQrwcUoiJM5qiqGiKTtkqozJ1/lZPvtOJoJgftGdLzvUvoDt/lJin4YRjSFZHzkZVVJaFVqMoCisjZ024zUgpiaIohPSxD22P5uW6pndRMHPTjksaT1VU2vztJIr9xN0nNzD6dHG2uWaFqk4CBtY1otV4Mfqy5PcNVX3YAfagaQW0gAv/6nr0Gi+ulgDpP3TjW1qHFnbb+VYv9jt9S7ldg3gW1hDY0Ej33/3BHpvU6Me3LIZ7Vggzb+BdXEs5U8K/Ks7Q9/dS2JckdMksIm+2A1cpW3ZPma6S2z1I8kf7CZ7bjHdJHeVkHlezPXKp9F+7GfjOLnvLTcEu9MZtkbmbgzR8aA1W2bJf1+wQde9ZxsA3tpH6TRfeBWM9aU4QauVPYzCPFvFMmGmo+l3otfbXrLqPzC6qKFtYOeOkvzdDP9xPbks/7rawHS/i1e2xU8MFoje0E1hbORH8uy7y2xNYxTLx21bgbgrS928vkt+WwLuoBle9H8WlEbp4FqW+LJ7K99LXEadwYBhXa5DEwzur4hvcs8ME39SK6lZxxXykftvF8JMH7Py4T4ytJue3JcACrdZT9Z4DZzdRTpUInjs2CkqPeqm/e5XdO5guQdze7h09SACVrd6/WYNZKDtRIqNy2xMkvrUDvc5L40fOov8/X8LozVZNT6i5YQHR66Zv8j8ZwfNayGiK08BfPGpHqRT2J1/R4woBUoiJM5xbdfMXLbfx28RTPD3wBG+u31hVCI2KexqZ61+IR/US1OzfdD2al4vjV5/U88Q8DVPOrgRIlYb5btfXURSFm1puJ6CPzaOLe069mIp7GunKH2Gg2PuapuyPPHWI1K868S2vo+7dx+U/WRbJH+4HVaF5XHirZVloEQ+euRE88yJ2FMP6Rga/t4fs873k9wwRe8/SqiZ9YyhP8tF9APZ8v9X1GIm8PWqoYvC7e8jvSBA8vwU96nUCRS3DpNSXJXTxLLSox2ngzu9IUE7kyb00QN3NiykcSaH6XVjFstMMX3PjQjxzI06f24T3//QRUr84gqc9SnBDE2a6ROHgCMVjKXLbBwme3UTkqjYC6xrQYz7Sz3SRfPwAvlVx6m4aW7m0DJO+L2/BTJeo/9Bq3E1jq0uKqlD/wdWUR+yMs54vbkKP++wThtP8QuBq8JPDTtsf7dtKP9NFdnMfpWMZgmfZxUfwvGasYtkpevQGP94ltSi6il7rpZwqMvi9PbibA8RuGfseu2I+4revYOjRveS2DmAM5p1CTFEVolePbae754RQQ248C6NYZdPZovWva6DUnyWwtvpn3js/OqFPDuwC+NgDf8QcKVL37iWTBrSqfpfzs1ZFr6yUVYosLey2i97j0vFfaREG9tbx+O3j4HnNKB7thH1rQpwMKcTEGc+lujmY3YOJSU++i1CwuhAbLA6wdWQTqyLrqfdUNygfyOzhpZFNnBU9n2af3VzcWzjG0/1PMj+wmPU1F7Bl+Dn6Cj2cX3cZPm3yLQ5FUVAUFaXy3yvVmTtEwcxzLH/khKOWTifVZ3/gjf/gG/2g1WN+tKjHXv0ZF/o5uuUEUDiSwlc50eieEyK7pW/SZmct7MG3IoaZM3A3B/G+I2qnsBfHjbapNMiPFmA1NyzAu6SWwW/tJPPHHgLrG8lt6ccV96HX+QhfOseOg+iI28GrnWnCV7YRvmgWgbMbyfypl3Km6BRhxc4UuZ2DBM9tdnq19Ij9XFrEg3dZHTU3LkSv8zL8xEEKB4YxU0Wi18xHr/XaJyvz9us9fmXLzBuUuu3xQpON69GjXvSol9z2BMZAzh6jVDJR3BqWZZHbNoCr3o+rYWzrO3zJbEIXtJLbPkDvlzYTuXIu/rUNlHoy+NeMFT6e2WE8lRmLpf4sRm+2qsjL7xmisGeIwt4hwm9uq4qtAAisb8IYKhA4qxGzULZz5Spfl8KREVxxf+WgwCp6v7SZnr1JGu5Zg5kxSP+mk+DZTZMWVFPRAi7MdGnyYmsavkW1NH7kLNTK9y72vuWYudIpjSkqp4oTZlWeDEVXpz/sIMQpkEJMnPFUReXy+usYKg4wL7BowvUvDP+BfZmdZIwUb2m8seq67akX6Cl0sSv9klOIdeUOM2Ik2Z/ZyVnR8/nj0G+wsGj1tbEk1DHpawjqYW5qud2OGJimb6xslflt4inA4oK6N08YFj7qTXVXcDC7d0Kv2qstdGErvo6Y88Hb/7WXKBwcIX77cjxtEZo+vn7CfQr7hvCtjKPXevGOy78Krm8iuL6Jwf/eTdff/p7Ye5c5vVaKplD3rrGIESORo/f+51FUhcaPrMMYsGMYUBX8q+tJP3uM/N4kgbMaQFfQIm7yuwYpjxQpHBjGMy+KFnbjXViDZVq44n5KXWln+9EqWfYIoYMj8Cb7OYce2UupO4NlmPbpTOxeNu+yOlSfjqIozsqOb0UMYyiPe06Y7s//0d4yu2ctoYtn2X1uzdXfcy3oJnbbCsys4TSYW5ZVteJVThfR631EN85Hr/U5W8G5F/sZ/O/dqH6d5k+fU/W4iksls6mX0rEM2Rf6qP2LRcTfP/nPJED/V1/CTBWpuXHh2HtZHqPYmbKLxWNpZzB55rkejME84ctmOwcfer64CWMwR/z2Dkp9WZKP7cM9O0T9XasoZw27x0stYxVMMs91k32xn2Jn+pQKMTwaWBZWeeLJ1BMZv7KpaMopFWHDPzlE6ldHnRmaQswUKcTEn4U2fztt/snnuy0OriBtjLA0tGrCdeujF7AzvZWV4bGer+XhNVhYtHjnOKOJ+gs9U6b5jzo+QT9tjLA3vYMFwaUE9coptlKC3emX7OcJrSFW2bYcLg2hKy7nMcKu6KR9aK+F8b04pZ4sGCZGIj/pibXycIHB7+wGIH5nh7NFlfp1J5nnuom+bQGFwyNYhTL5g8NOIWaZlcKou1IIaKp9X1UBVUGr9aGF3ahhN6pHY/hnh7FyBsVOuy8sfEUbetRLYd8QgcrKRLErbc+R1BSaPrEerc5LbtsA3vkRIlfPxdUcwL88RmZTDyO/PIpnVgizWMa3qIbCoWGGHt1HYF0jgbMb6fvSZsyiSf1dK9GCboLnNBM8p5lSb8YuPhTF7lvy6Xjmjn1dxhdb47fi0n/sJvnDfYQvn0P44tmYxbJ9cCBXov6uVU4xBKDHfCgu1TmxeLzIVXPJbOqZcsSPVTKdBn5Xo59CroTiUun9txfxzAoRvXY+rno/yR/up7A3SfOnNmDmDYZ+sBcA96wgvmUxe0ZrwbBX9UplZxV09E93U4D4HR0oLtXuAVzTQKk7g29FfNLXNRVzpHIQZKR44htPw6pEbpyo33NUeaRQ+XPq5039upP87kGib1swaR6cEKeDFGLiz16Lbw4tvsl/423wNtPgba66zK16WBs9F7BPPcbcDSwNrTrlGIlnB3/JgeweBop9XF5/LWAP/14d2QDgnPAcLA7wyLEH0RUX72y9A492eoYPnw7xO1ZQ6sk6MyGPpwZdeBbWYGZLVSfTspVTkPldg8Teu5T+r20j9YsjeOdHSP2qk8L+JO454arm+/q/WY1VMp1Vjab/c7bzeJHL55Dfn6RUmXNJ2cLdEqw62af6dRSvjurVQFVI/fwIAN5FNQTWNNirZRbkXhqgnMjDrBBNH7GL3eSTBzB6s2Q39+JbUUepN2sXB8NF5/Wknuki99IANTcuxFXvR4+OpdKDffgg8a0d+FfXU/v2hVXXlTrTlcyt0RBfC4tKTMdxhYN7Vojmvzt3wpahc31LEHfL5L90pH7byfCTB51VnvhtK7AMk+wLfZSOpigdSxO5Zh7u1hBq0OVkoalencDZjRiDedyVgju7qRcrVcK3IuaMavLMCTsnZYGqItRV7yd268QV3MzzvZR6s0Qun+0ccBgvfkcHRl/2FY0TKmdK9H1pM6gKDR9aM2FO6mSiG9vtkNj5U0dipH7biZkukd8+gOvCqSd6CPFKSCEmxDR+M/Az9mS20xFexzm1F5/SfWf55tGd76zKDFMUhTZ/O935TgzLwKW4Kj1lSqXP7JX3l51OrrgfK19m+McHCZ3f4mxZgt1fU+rJELt1GYqiMPCNbRS70sTfv8LOYdqRIHhuM6pft08rmhZmZVXLKplYJbt3SnGpWGWLgf/cRnm4QP3/Wlm1QmQZJqlfH6WcKlF36zI0n151fW5nAhQF3+Jamj+5HhQFRVeJvGWuvUKztI5ST4beL21GcWnEbl+OqznonIDLbunDzBoEzmvGvzKOHvUSu3U5xnChquhIP3OM8mAez/wogTUTD2CUejJQtih1piZcF7l6Lu7ZIWciQPKx/VgZw768ZeIs0smKMKts2SOLWoKTZlmV+rJOoTc6BBzsfib/qri9tdocRFEUu9j71Iaq+4cutMcgjW6RGgP2jEkzP9b/Ntkhh8LhERIP7cS/PEb02vnVr9kwGfr+HrDA3RyoStV3HjPqmVDUniozU3JWtsxs6aQKMbC3M48vhMer2dhOfl8S/zoZdyRePVKICTENXa00cSuTNxKPlJL8NvEUc/zzWR5eU3Xd4tAKvJpvQh/YU30/Il0ewcJiVWQ9Ne46bm69HU3Rcauv7APp1ZD80X6KR1NYhknNdWMrMU5cwPXtBM5qpHBgGKtkUurJ4l8Zx90SxCqZGH1ZGu5ejTFcwDM7jH67l1JPBu+yGJk/HKPYmcYYzGHl7ZmU4xv2sy/2MfTEfiiaYFmoLrWqCCv1ZUk8uAOAhnvX4orbBcrIzw+T2dRLzY0LUb06Za0IqoKiK5SOpOzxQ5W4iaFH9mEVy0Svne9keul1Xga+uYPhJw7Q+NGz0AIue6blL46guKtXRod+uI9SZ5qadyxEC7knPUmn+nS7+T1nMPLLoxR77EKp6nDCCWT+2E3yR/vRar00fbR627rUm6H3Xzaj6CrR69snBMQqLo3Im9uqvm6FfUn86xpQ3ZoTBeGaZc/0BAhfPgdXa7Bq1avYlbZDXDtizi8NxUPD9qDyXYMTCjFFVwme20ypN4tnklOTp4ur3m+PnFKVqliS8SzLcgasAyQf3Uf2hT5nRNdkfMtjp9bvJsTLIIWYENM4v/YyVoTXEtEn3zbZn9lNZ/4QiWLfhEIsUezjp32PAjghsmD3sx3M7qXJMzYTb7SH7PXIv7Yeq1Se8IHkxAWE3CiqQuz9KzD6clVzHBMP7SS/a5DodfPHxgk1BnA12v1P6We7KQ/m0Wu9xG5bzsCDO0g+foD6u1aiuDTyu4ew0gae9ijRa+ZhGRaD/7WL4HktuGeF0EJuZ16h0Z+jsDdJ4OwmctsSlJMFCnuTeOdHccX9dvGiqfTetwkza+BuDRF6UyuhC1spHBx2xgsB9vanZYGlOE3kiqJQOpapREU02tEYlkXmuR673+1wisC66aNKUr/pJPXLo+j1fureuxTvwtppbz+eq9GP4lKdAeTjKZUeO8Wl4u+In3BFaPDhnZR6sphZe/anZVROf1YKw5FfHSX7Qh81NyxwtmYt06L/37dgFU1q1SVOsRc4pxlUFc/cyX+Go9fMn/TyqZQzJRRVOelVrVHHZ9sdL/HAdvJ7k8RuXYZ3QY1z2nL0xKwQM0UKMSGmoSgKUdfUH5aLQssZNoaq5mCO8mtBwnoUXdGrYi/Oq7uU8+oufTVe7qsiuKGZ4IbmCZfH3rfcTkSvfJBNNuvPMu0+KKsytqicKpJ88gDe9iiBdY2EL51N7qUB/GsbsHIG5kgRc6TI8M+PVDK75qLX++0tw1oviW/tILc9gZkvE3vfMlSfTuO967DKFl1/a48yUgM6NTcuJL97sCpiQAvbq43hK9rs1aCVccycQeHgMKpfd64Hu2G+8d51FLtS9Pzzn/AuqKH2xoV4FtbY0RWVIkFRFOpuXkzxWBr/yhOvnHjao2Q39+FbEcO35MQjuaruOy9K82fPnXT7Wo/5aPjwWuDkChhPew3GcNHJbfOvrEev8zlbj9nnezH6c+R3DjrfU0VVcLUEKXVncI0b0q26taopBafCzBt2flxle9ZI5um9fzOKptBw77pXVCRlt/ST2zZA5Mo29DofpYEcmBbGYB6AyFvmErygxYksGWUkcow8dRjfqnonikWIV5MUYkK8An4twEWxKye9zqf5ubn1/a/xK3rtKJoy4YOycGSEwW/vtDO4rmun7t1LMPpzzgdt9oU+ci/2k989ZJ9QXNtQFf5Z+64lZP5wjPSvOzH6ssTeuwwUGPnFEaLXziNwTjNmziB4bjOWaTHy00OgKISvmINvSR3FY2lcLSFcMR96jYeRnx/BMz+Kq9HP4Hf34JkbJnzZHFSPhgWUjqUp7EsCUH5LsepDWa/1kt87ZI9r6s6g+l1V8ywBCoeGKVdWlaZqrh/POz9K0yfWk/j2Dnru20Ts1uVThstO+jWfop/JMkwG/mMb5ZEi9XevOuE8xOhb5xF967yqy8Zv+da8fSH5nYPOEPVR9XeunBDD8Ur0f20bpaMpat6+gMC6xkrvoIlVVsZmjk6hnCkx8I1tqD6d2HuXTQhuHf7ZIcqJPHqdj8iVbcRvW0GpO+OsfCqKQqkzjdGfrVpNSz9bieHozkghJl4TUogJIU6b4qERyiNF8jsH4Tp7tWR8M7pvZdye+zgub2w8/4oYGKY9QHxRDWaxzMhPDgHgXViDf2XcSdIvdqVJ/brTedzxuWQAmU29pH9/jOyWPsKXzaF4eMQOWdVUUr84gnt2iPhfrSR8ZRua3zVhZQTsUUiqz57n2P355/DMjVD7F3ZWnWVaDHxtm9135NHwr6ynnCkx+NBOtLCbmncsmrzp3jDJ7RgE06LYlTqlQmwqVtmkPFLAKpqYmdKE643BPEYi55ySPJHjZy2OdzoPlIz26Y0WUa64n4a/Xg2aWnVQYjJGX9Y+jYrdrK8d9/2LXDaH7EsDznaxXuut+loXO1MkvrUDFGj6+Hrn/oF1DZR6M5MeyBDi1SCFmBDitAlsaAJFmbRfqNhpD18eP1ZnlGValIfs1Qv/6vqqId7hy+fYqxaLqosIV6Mf/7oGu58ooNPzxU0oXo36OztQXBrepXXkdiTsAm5NPUaygGdWyNkuxYLCwWHCF00eS2BmS/R9eQuKrhI4q5FysmCf0KxQVAVPe5TSsTSuygijYmeKwoFhACLXzJ90a03RVWLvW4bRn3WGjI8yEjnUkLtqzufJUD069R9YhZkpVTXXj+r78hbMVJHamxePDdR+HYjftpzycBF9XEbX6DQByzAxs8aUBZlnboTo9e2oPn1CEQZM+Dk6nhbxoEXtKRHKuO1cV2OA+G0rXu5bEuKUSSEmhDhtRvuFLMOk2JXG1RxAURQn38qzsGbC9h5A8rF9ZJ7rsYNaYz6Gf3KQ8MWzCaxrIHzp7EmfS9FUJ6+rcGTEjltQoJw10CMarpiP+r9aCdhbolgWnoU1qG4NM2eQfHQfiQe30/LZ8yZ9fCNZwOi3H9PTHrXzt46LmohVRgmN8i6oIfzmOWhhz7T9Td6FNXBcbpZzcrElSMMHV09536mMH4d0PL3GQzFbOuEq02tNcWlVRdh4/V/dSvFoirr3LcO3aPItwuDZYz2AxaMpctsGCJ7fcsKxRaNTAkIXtBCcIhhXiNeKFGJCiNNu6NF9ZJ/vJXTxLCJXtDmJ+1MNYB7NqrLyBrltduBqbpu9rTTy9BHKwwWib51nn6TcM0TqN52ELp7lpNd7ZoepvXkxilebsMVomRaD390Nll2sBNY22IO/Yz7cs+2+KGMoT+LBHeiNfmd4t7s5SO27lmCZdt/SVEn24ymqQviS2WS39tP9uecIXTKrqliYzujpTMs49VE/JxK/cyVWqYzqfW3/ybdnbmZwt4VPeUvTzBpgTZzjOZXRGBGrZE6I0Thebms/hQPDGIN5KcTEjJNCTAjxqgue24ynPTplP1TN2xcSPKcZxafbDda1Xvxr7J6rkZ8dBsC7qBbf0jrSz3RR2JdE9elOIVbqz+JuCztF2MCD2ykdyxC7bTmuej/B81sodaXxtkcpdqUpdqVouGcNiqZS7M5Q6k5T6slQ6stgvX0hiq5iWRa+xbX0/8dWikfGGspPRn7XIOXhArntiZMuxPwdcfSY7xWHm05G0RQU7bX/5z7x0E4Ke5PO8HWwTzOqfv2E/WrxOzswBvNT9qodz7+6nkzRxLvsxKdRA2c3UR4pOgG7QswkKcSEEKddzdvaCZ7XXDUvcbqTfKpbQ6/30/P557AMk/q7VzvhrKGLZlFO5lG8GiNPHyF4XguKVyf0JjuHrdidoe9fN6O4NZo+vh7FrZHfm7Sb/rvTdiG2ocnpver91xcw0yU7K8y0SP5wP+4FUSJXz0WP+5xVu4FvbKewP4leeR1oJz/iKnJFG3qtF98kSfLTcTdPzAg7k42uwI1GahQODjP4nV2g2iOsphvSrYXcJ9xiLI8UKR5N4V1SS+i8lpNatRx97Jq3TT87VojXihRiQojTTtHUkyoqLNMCq7Jio6uofh0zX7bnRVZErmwDoOf+5zF6s4QunkXdzYvHPZc9KFzRVFDs7cH4bcsp9WXxrYiP9V61Bmm4ezWe+VEKe4dwNwftIeLYJwFHC7tRRl8WyhbBsxvxtEedwvBkaBEP4csmn2/6RlJ70yLKV811VkL1Oi9ajQc16HaKtPJIgcymXvyr6qtWTPP7kug1nimT8gEGvrWD0tFU1YqbEGcaKcSEEDPCzBv0/r/NWIZJw1+vQQu5afywHc46WS+Tb3mMTKYb9bhVFD3uo+6WZbib/Kge+36euRHn9KBZmWlplezeq/FFnHtWyO4Xq5u4ZRp//woKB4dxt0dxRV8/g9jPFGaxTPKxfWhRjzNeSQt7aPrY+qrbDf/PIbIv9FE8kiL2PvvwQ25HgsQ3d6D6dZo+tWHKjDa91kup8/REgAgxU05+rV0IIU4jM29QHilgZkqYWTv7SnFpUzaU+5bVYaZLDD+5H2O44FyeevooiW9sI/nEgUnvNxrY6ls6eT+QqzGA4rJX4KzKYHIAxaORfPwAvV98HiORq7pPOV3EGMqf/Jt9AyrsS5Ld3Efq6aOU08Upb+ddVIMacleNmFKDLtAVtIhn2qDc2psW0fyZc/B3vH4iOYQ4VbIiJoSYEXrUS/zOlVA2p41eGKWF3Hafl+e4Ym30c3qq1PmSedwNp5Z4cDv5PUPUvWcp7lmjSfPVCe9moUzv/c9j5ss0fHC1MzdTVPO0R/Gva0CPeqbtBfOvqsd/XC+dZ3aY5k9tQHFNv1agKAqKRz7GxJlNfoKFEDPmZE/EjXLPDuGeE0L1jPWQhS+ZjXdJXdX8w/Fq376A4rnN6A0n7vEyhgpgQXm4iLbETeP/XotVto7b+rIqQ8HtFbT8niGST+wneH4LwfUnd0LyjUB1a07O28u6/2sctSHETJGfdCHEGSG3I0F+e4L8rkHCb6puzHY3Tb0qpbg08jsHSX15C5Fr5k17si5+23KKPRk7cBUmTWxXPToN96zFKpbR63wMPbIXoy9H9oU+KcSEEKdMCjEhxBnBtzxG8fCIE8J6Kkr9WQA7KX8aWsSDL+KxB4r/+iha2D3pzMHxsQqhS2ej+PXX1eggIcSZQwoxIcQZQQu4qH3Hopd139obFpBfGT/pAM/C3qGxYeOLaqcdV6RHPUSvmvuyXpcQQkghJoT4s6f6Xad0ss7VGsLdFkaLeJwwUiGEeDXIvzBCCHEcLeByBoYLIcSrSXLEhBBCCCFmiBRiQgghhBAzRAoxIYQQQogZIoWYEEIIIcQMkUJMCCGEEGKGSCEmhBBCCDFDpBATQgghhJghUogJIYQQQswQKcSEEEIIIWaIFGJCCCGEEDNECjEhhBBCiBkihZgQQgghxAyRQkwIIYQQYoboM/GklmUBkE6nZ+LphRBCCPEyjH5uj36Oi1duRgqxTCYDwIUXXjgTTy+EEEKIVyCTyRAKhWb6ZfxZUKwZKGtN06Svr49AIICiKK/10wshhBDiZbAsi0wmQ319Paoq3U2nw4wUYkIIIYQQQpr1hRBCCCFmjBRiQgghhBAzRAoxIYQQQogZIoWYEEIIIcQMkUJMiDewcrnMTTfdxN133111eSqV4sILL+T++++f9v6dnZ0sWrRowv8f/vCHJ71+/fr1vPvd72bTpk1Vj7N3714++MEPcskll7Bo0SIeeOCB0/o+hRDi9WpGcsSEEK8Pmqbxuc99jo0bN/KjH/2Ia6+9FoC///u/JxKJ8IEPfOCkHueBBx6gvb3d+bvX6530+qGhIb7yla9w55138tOf/pRYLAZALpejtbWVK6+8ks997nOn6d0JIcTrnxRiQrzBzZ07l3vvvZd/+Id/YMOGDWzdupUf//jHfP/738ftdp/UY0SjUeLx+Amvj8fj3HnnnTz55JNs2bKFSy+9FICOjg46OjoAuO+++175mxJCiDOEFGJCCG655RaeeuopPvrRj7Jnzx7uuusuFi9efNqfJ5/P89hjjwHgcrlO++MLIcSZRgoxIQSKovCZz3yGq6++moULF3LHHXec0v1vuummqpTthx56iKVLl064PpfLYVkWy5Yt45xzzjltr18IIc5UUogJIQB45JFH8Pl8dHZ20tPTQ2tr60nf9/7772f+/PnO35uamiZcP2/ePPbu3csXvvAFPv/5z8uKmBBCIKcmhRDA5s2befDBB/nKV75CR0cHn/zkJzmV6WdNTU3MmTPH+f/43rKmpiba2tq4/PLLueeee7j77rspFoun+20IIcQZRwoxId7gcrkcn/jEJ7j55pvZsGED//iP/8jWrVv5zne+86o835VXXommaTz88MOvyuMLIcSZRAoxId7g7rvvPizL4t577wWgtbWVj33sY3zhC1+gs7PztD+foijccsstfPWrXyWXywFQLBbZuXMnO3fupFgs0tvby86dOzl8+PBpf34hhHg9kUJMiDew5557jocffph/+qd/wufzOZffdNNNrFmz5pS3KE/W9ddfj2EYfPvb3wagr6+PjRs3snHjRvr7+/n617/Oxo0b+dSnPnXan1sIIV5PFOvV+FdWCCGEEEKckKyICSGEEELMEImvEEJM6dOf/jSPP/74pNddc801fPazn32NX5EQQvx5ka1JIcSUEokE6XR60uuCwSB1dXWv8SsSQog/L1KICSGEEELMEOkRE0IIIYSYIVKICSGEEELMECnEhBBCCCFmiBRiQgghhBAzRAoxIYQQQogZIoWYEEIIIcQMkUJMCCGEEGKGSCEmhBBCCDFD/j9FAZ8/jlyMOgAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import scanpy as sc\n",
+    "import numpy as np\n",
+    "from scipy import sparse\n",
+    "\n",
+    "# 1) Keep a copy of the *raw counts* in a layer\n",
+    "rna.layers[\"raw_count\"] = rna.X.copy()\n",
+    "\n",
+    "# 2) (Optional) Now you can normalize/log for your own analyses without touching raw_count\n",
+    "sc.pp.normalize_total(rna, target_sum=1e4)\n",
+    "sc.pp.log1p(rna)\n",
+    "\n",
+    "# 2.a) Keep the normalized counts in a layer\n",
+    "rna.layers[\"normalized_count\"] = rna.X.copy()\n",
+    "\n",
+    "# 3) Neighbors + clustering for 'louvain_annot'\n",
+    "sc.pp.pca(rna)\n",
+    "sc.pp.neighbors(rna)\n",
+    "sc.tl.louvain(rna, key_added=\"louvain_annot\")  # or sc.tl.leiden(..., key_added=\"louvain_annot\")\n",
+    "rna.obs[\"louvain_annot\"] = rna.obs[\"louvain_annot\"].astype(\"category\")\n",
+    "\n",
+    "# 4) ForceAtlas2 embedding (Scanpy's draw_graph)\n",
+    "sc.tl.draw_graph(rna)  # creates rna.obsm[\"X_draw_graph_fa\"]\n",
+    "\n",
+    "# 5) Point .X to the unscaled counts for Oracle (optional, Oracle will read from layers below)\n",
+    "rna.X = rna.layers[\"raw_count\"].copy()\n",
+    "\n",
+    "# 6) Import to Oracle\n",
+    "oracle.import_anndata_as_raw_count(\n",
+    "    adata=rna,\n",
+    "    cluster_column_name=\"louvain_annot\",\n",
+    "    embedding_name=\"X_draw_graph_fr\",\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a15bff20-be62-4cd9-9c99-de347f27edb6",
+   "metadata": {},
+   "source": [
+    "#### 6.3. Load prior base GRN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "7cf9f92c-7b8e-427d-b248-a1df8eecf567",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TF dict already exists. The old TF dict data was deleted. \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# You can load TF info dataframe with the following code.\n",
+    "oracle.import_TF_data(TF_info_matrix=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7047c1fd-9dde-43b5-b815-77d17d05d683",
+   "metadata": {},
+   "source": [
+    "#### 6.4. Calculate KNN for cell proximity and trajectories"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2f67191f-007c-4c78-8ce7-70aa5aaa059c",
+   "metadata": {},
+   "source": [
+    "Compute PCA and select a small number of components."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "c679567d-8e86-40d5-9e76-b21efaa6b2e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Perform PCA\n",
+    "oracle.perform_PCA()\n",
+    "\n",
+    "# Select important PCs\n",
+    "plt.plot(np.cumsum(oracle.pca.explained_variance_ratio_)[:100])\n",
+    "n_comps = np.where(np.diff(np.diff(np.cumsum(oracle.pca.explained_variance_ratio_))>0.002))[0][0]\n",
+    "plt.axvline(n_comps, c=\"k\")\n",
+    "plt.show()\n",
+    "print(n_comps)\n",
+    "n_comps = min(n_comps, 50)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "00cf4cfe-18d6-4c4b-af6a-8caf31b9fbe2",
+   "metadata": {},
+   "source": [
+    "Defining a number of neighbors for KNN imputation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "8492dbca-be4a-4173-abb2-b1a30d16febe",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "cell number is :9631\n",
+      "Auto-selected k is :240\n"
+     ]
+    }
+   ],
+   "source": [
+    "n_cell = oracle.adata.shape[0]\n",
+    "print(f\"cell number is :{n_cell}\")\n",
+    "\n",
+    "k = int(0.025*n_cell)\n",
+    "print(f\"Auto-selected k is :{k}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0fdb2df3-462c-4c2f-830f-19a23a5290dc",
+   "metadata": {},
+   "source": [
+    "Computing k-nearest neighbors."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "id": "d51e804e-41eb-43cc-beaf-32d750ba1ec5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "oracle.knn_imputation(n_pca_dims=n_comps, k=k, balanced=True, b_sight=k*8,\n",
+    "                      b_maxl=k*4, n_jobs=4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "420fbbf0-9757-49c8-9000-ecbd2380e449",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Check clustering data\n",
+    "sc.pl.draw_graph(oracle.adata, color=\"louvain_annot\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d7120e3-d5a0-41d7-b5db-9eee21a3eac7",
+   "metadata": {},
+   "source": [
+    "#### 6.5. Inferring  cluster-specific GRN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "id": "1679cb2d-c702-4849-8c3e-8e3b524478b3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0a797a2d0784402b8ed2c73548b86385",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/13 [00:00 circe_celloracle_env.yml"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "celloracle_env",
+   "language": "python",
+   "name": "celloracle_env"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/circe_celloracle_environment.yml b/circe_celloracle_environment.yml
new file mode 100644
index 0000000..54c0922
--- /dev/null
+++ b/circe_celloracle_environment.yml
@@ -0,0 +1,229 @@
+name: celloracle_env
+channels:
+  - defaults
+dependencies:
+  - _libgcc_mutex=0.1=main
+  - _openmp_mutex=5.1=1_gnu
+  - bzip2=1.0.8=h5eee18b_6
+  - ca-certificates=2025.9.9=h06a4308_0
+  - expat=2.7.1=h6a678d5_0
+  - ld_impl_linux-64=2.40=h12ee557_0
+  - libffi=3.4.4=h6a678d5_1
+  - libgcc-ng=11.2.0=h1234567_1
+  - libgomp=11.2.0=h1234567_1
+  - libstdcxx-ng=11.2.0=h1234567_1
+  - libuuid=1.41.5=h5eee18b_0
+  - libxcb=1.17.0=h9b100fa_0
+  - libzlib=1.3.1=hb25bd0a_0
+  - ncurses=6.5=h7934f7d_0
+  - openssl=3.0.17=h5eee18b_0
+  - pip=25.2=pyhc872135_0
+  - pthread-stubs=0.3=h0ce48e5_1
+  - python=3.10.18=h1a3bd86_0
+  - readline=8.3=hc2a1206_0
+  - setuptools=78.1.1=py310h06a4308_0
+  - sqlite=3.50.2=hb25bd0a_1
+  - tk=8.6.15=h54e0aa7_0
+  - wheel=0.45.1=py310h06a4308_0
+  - xorg-libx11=1.8.12=h9b100fa_1
+  - xorg-libxau=1.0.12=h9b100fa_0
+  - xorg-libxdmcp=1.1.5=h9b100fa_0
+  - xorg-xorgproto=2024.1=h5eee18b_1
+  - xz=5.6.4=h5eee18b_1
+  - zlib=1.3.1=hb25bd0a_0
+  - pip:
+      - anndata==0.10.8
+      - anyio==4.10.0
+      - appdirs==1.4.4
+      - argon2-cffi==25.1.0
+      - argon2-cffi-bindings==25.1.0
+      - array-api-compat==1.12.0
+      - arrow==1.3.0
+      - asttokens==3.0.0
+      - async-lru==2.0.5
+      - attrs==25.3.0
+      - babel==2.17.0
+      - beautifulsoup4==4.13.5
+      - biofluff==3.0.4
+      - biopython==1.85
+      - biothings-client==0.4.1
+      - bleach==6.2.0
+      - celloracle==0.20.0
+      - certifi==2025.8.3
+      - cffi==2.0.0
+      - charset-normalizer==3.4.3
+      - circe-py==0.3.8
+      - click==8.2.1
+      - cloudpickle==3.1.1
+      - colorama==0.4.6
+      - comm==0.2.3
+      - configparser==7.2.0
+      - contourpy==1.3.2
+      - cycler==0.12.1
+      - cython==3.1.4
+      - dask==2025.9.1
+      - debugpy==1.8.17
+      - decorator==5.2.1
+      - defusedxml==0.7.1
+      - diskcache==5.6.3
+      - distributed==2025.9.1
+      - docopt-ng==0.9.0
+      - et-xmlfile==2.0.0
+      - exceptiongroup==1.3.0
+      - executing==2.2.1
+      - fastjsonschema==2.21.2
+      - feather-format==0.4.1
+      - filelock==3.19.1
+      - fonttools==4.60.0
+      - fqdn==1.5.1
+      - fsspec==2025.9.0
+      - ftpretty==0.4.0
+      - genomepy==0.16.2
+      - gimmemotifs==0.17.2
+      - goatools==1.5.2
+      - h11==0.16.0
+      - h5py==3.14.0
+      - htseq==2.0.9
+      - httpcore==1.0.9
+      - httpx==0.28.1
+      - idna==3.10
+      - igraph==0.11.9
+      - importlib-metadata==8.7.0
+      - ipykernel==6.30.1
+      - ipython==8.37.0
+      - ipywidgets==8.1.7
+      - isoduration==20.11.0
+      - iteround==1.0.4
+      - jedi==0.19.2
+      - jinja2==3.1.6
+      - joblib==1.5.2
+      - json5==0.12.1
+      - jsonpointer==3.0.0
+      - jsonschema==4.25.1
+      - jsonschema-specifications==2025.9.1
+      - jupyter==1.1.1
+      - jupyter-client==8.6.3
+      - jupyter-console==6.6.3
+      - jupyter-core==5.8.1
+      - jupyter-events==0.12.0
+      - jupyter-lsp==2.3.0
+      - jupyter-server==2.17.0
+      - jupyter-server-terminals==0.5.3
+      - jupyterlab==4.4.7
+      - jupyterlab-pygments==0.3.0
+      - jupyterlab-server==2.27.3
+      - jupyterlab-widgets==3.0.15
+      - kiwisolver==1.4.9
+      - lark==1.2.2
+      - legacy-api-wrap==1.4.1
+      - llvmlite==0.44.0
+      - locket==1.0.0
+      - logomaker==0.8.7
+      - loguru==0.7.3
+      - loompy==3.0.8
+      - louvain==0.8.2
+      - markdown-it-py==4.0.0
+      - markupsafe==3.0.2
+      - matplotlib==3.10.6
+      - matplotlib-inline==0.1.7
+      - mdurl==0.1.2
+      - mistune==3.1.4
+      - msgpack==1.1.1
+      - mudata==0.3.2
+      - muon==0.1.7
+      - mygene==3.2.2
+      - mysql-connector-python==9.4.0
+      - natsort==8.4.0
+      - nbclient==0.10.2
+      - nbconvert==7.16.6
+      - nbformat==5.10.4
+      - nest-asyncio==1.6.0
+      - networkx==3.4.2
+      - norns==0.1.6
+      - nose==1.3.7
+      - notebook==7.4.5
+      - notebook-shim==0.2.4
+      - numba==0.61.2
+      - numpy==1.26.4
+      - numpy-groupies==0.11.3
+      - openpyxl==3.1.5
+      - overrides==7.7.0
+      - packaging==25.0
+      - palettable==3.3.3
+      - pandas==2.3.2
+      - pandocfilters==1.5.1
+      - parso==0.8.5
+      - partd==1.4.2
+      - patsy==1.0.1
+      - pexpect==4.9.0
+      - pillow==11.3.0
+      - platformdirs==4.4.0
+      - prometheus-client==0.22.1
+      - prompt-toolkit==3.0.52
+      - protobuf==6.32.1
+      - psutil==7.1.0
+      - ptyprocess==0.7.0
+      - pure-eval==0.2.3
+      - pyarrow==21.0.0
+      - pybedtools==0.12.0
+      - pybigwig==0.3.24
+      - pycparser==2.23
+      - pydot==4.0.1
+      - pyfaidx==0.9.0.3
+      - pygments==2.19.2
+      - pynndescent==0.5.13
+      - pyparsing==3.2.4
+      - pysam==0.23.3
+      - python-dateutil==2.9.0.post0
+      - python-json-logger==3.3.0
+      - pytz==2025.2
+      - pyyaml==6.0.2
+      - pyzmq==27.1.0
+      - qnorm==0.9.0
+      - referencing==0.36.2
+      - requests==2.32.5
+      - rfc3339-validator==0.1.4
+      - rfc3986-validator==0.1.1
+      - rfc3987-syntax==1.1.0
+      - rich==14.1.0
+      - rpds-py==0.27.1
+      - scanpy==1.11.4
+      - scikit-learn==1.7.2
+      - scipy==1.15.3
+      - seaborn==0.13.2
+      - send2trash==1.8.3
+      - session-info2==0.2.2
+      - six==1.17.0
+      - sniffio==1.3.1
+      - sortedcontainers==2.4.0
+      - soupsieve==2.8
+      - stack-data==0.6.3
+      - statsmodels==0.14.5
+      - tblib==3.1.0
+      - terminado==0.18.1
+      - texttable==1.7.0
+      - threadpoolctl==3.6.0
+      - tinycss2==1.4.0
+      - tomli==2.2.1
+      - toolz==1.0.0
+      - tornado==6.5.2
+      - tqdm==4.67.1
+      - traitlets==5.14.3
+      - types-python-dateutil==2.9.0.20250822
+      - typing-extensions==4.15.0
+      - tzdata==2025.2
+      - umap-learn==0.5.7
+      - uri-template==1.3.0
+      - urllib3==2.5.0
+      - velocyto==0.17.17
+      - wcwidth==0.2.13
+      - webcolors==24.11.1
+      - webencodings==0.5.1
+      - websocket-client==1.8.0
+      - widgetsnbextension==4.0.14
+      - xdg==6.0.0
+      - xlsxwriter==3.2.9
+      - xxhash==3.5.0
+      - zict==3.0.0
+      - zipp==3.23.0
+prefix: /pasteur/appa/homes/rtrimbou/miniconda3/envs/snakemake/envs/celloracle_env

From 71061d65710fe964abff6aa0df4d7f4857473d15 Mon Sep 17 00:00:00 2001
From: r-trimbour 
Date: Fri, 19 Sep 2025 18:23:02 +0200
Subject: [PATCH 32/33] loosen pandas dependency requirements

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 5415292..cd85398 100644
--- a/setup.py
+++ b/setup.py
@@ -90,7 +90,7 @@ def build_extensions(self):
     install_requires=[
         'Cython',
         'numpy<2.0.0',
-        'pandas>=2.1.1',
+        'pandas',
         'scikit-learn>=1.6',
         'joblib>=1.1.0',
         'scanpy>=1.8.1',

From 1dc028776c4d6af0d20d7b9e816e968218dc00b7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?R=C3=A9mi=20Trimbour?=
 <77151348+r-trimbour@users.noreply.github.com>
Date: Fri, 19 Sep 2025 18:33:52 +0200
Subject: [PATCH 33/33] Update pyproject.toml

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 9eb249a..11d6c36 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 # Project information -- not used kept for readability
 [tool.poetry]
 name = "circe-py"
-version = "0.3.8"
+version = "0.3.9"
 description = "Circe: Package for building co-accessibility networks from ATAC-seq data."
 authors = ["Rémi Trimbour "]
 packages = [{include = "circe"}]