From eb7a4a7cbcede1c1c898cb64effc34ae5e0b9a6e Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Mon, 30 Jan 2023 19:31:15 +0100 Subject: [PATCH 01/31] Poetry update --- poetry.lock | 129 ++++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 1 + 2 files changed, 129 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 8fd736a..be60bf1 100644 --- a/poetry.lock +++ b/poetry.lock @@ -181,6 +181,14 @@ python-versions = "*" [package.dependencies] pycparser = "*" +[[package]] +name = "cfgv" +version = "3.3.1" +description = "Validate configuration and produce human readable error messages." +category = "dev" +optional = false +python-versions = ">=3.6.1" + [[package]] name = "click" version = "8.1.3" @@ -238,6 +246,14 @@ category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +[[package]] +name = "distlib" +version = "0.3.6" +description = "Distribution utilities" +category = "dev" +optional = false +python-versions = "*" + [[package]] name = "exceptiongroup" version = "1.1.0" @@ -271,6 +287,18 @@ python-versions = "*" [package.extras] devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"] +[[package]] +name = "filelock" +version = "3.9.0" +description = "A platform independent file lock." +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.extras] +docs = ["furo (>=2022.12.7)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] +testing = ["covdefaults (>=2.2.2)", "coverage (>=7.0.1)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"] + [[package]] name = "fqdn" version = "1.5.1" @@ -279,6 +307,17 @@ category = "main" optional = false python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" +[[package]] +name = "identify" +version = "2.5.17" +description = "File identification library for Python" +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.extras] +license = ["ukkonen"] + [[package]] name = "idna" version = "3.4" @@ -772,6 +811,17 @@ category = "main" optional = false python-versions = ">=3.5" +[[package]] +name = "nodeenv" +version = "1.7.0" +description = "Node.js virtual environment builder" +category = "dev" +optional = false +python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*" + +[package.dependencies] +setuptools = "*" + [[package]] name = "notebook" version = "6.5.2" @@ -904,6 +954,21 @@ python-versions = ">=3.6" dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] +[[package]] +name = "pre-commit" +version = "3.0.2" +description = "A framework for managing and maintaining multi-language pre-commit hooks." +category = "dev" +optional = false +python-versions = ">=3.8" + +[package.dependencies] +cfgv = ">=2.0.0" +identify = ">=1.0.0" +nodeenv = ">=0.11.1" +pyyaml = ">=5.1" +virtualenv = ">=20.10.0" + [[package]] name = "prometheus-client" version = "0.16.0" @@ -1141,6 +1206,19 @@ nativelib = ["pyobjc-framework-Cocoa", "pywin32"] objc = ["pyobjc-framework-Cocoa"] win32 = ["pywin32"] +[[package]] +name = "setuptools" +version = "67.0.0" +description = "Easily download, build, install, upgrade, and uninstall Python packages" +category = "dev" +optional = false +python-versions = ">=3.7" + +[package.extras] +docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"] +testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"] +testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"] + [[package]] name = "six" version = "1.16.0" @@ -1277,6 +1355,23 @@ python-versions = ">=3.6" [package.extras] dev = ["flake8 (<4.0.0)", "flake8-annotations", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-noqa", "flake8-requirements", "flake8-type-annotations", "flake8-use-fstring", "mypy", "pep8-naming"] +[[package]] +name = "virtualenv" +version = "20.17.1" +description = "Virtual Python Environment builder" +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +distlib = ">=0.3.6,<1" +filelock = ">=3.4.1,<4" +platformdirs = ">=2.4,<3" + +[package.extras] +docs = ["proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-argparse (>=0.3.2)", "sphinx-rtd-theme (>=1)", "towncrier (>=22.8)"] +testing = ["coverage (>=6.2)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=21.3)", "pytest (>=7.0.1)", "pytest-env (>=0.6.2)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.6.1)", "pytest-randomly (>=3.10.3)", "pytest-timeout (>=2.1)"] + [[package]] name = "wcwidth" version = "0.2.6" @@ -1325,7 +1420,7 @@ python-versions = ">=3.7" [metadata] lock-version = "1.1" python-versions = "3.10.*" -content-hash = "aa1a3db0fd895e57ab4fecf1079538df2f3e21b29b4162177799e66c3fa3503d" +content-hash = "ad79d685ac33f8f41aeec9837d0c55fc1d5b97728042d3c2dd92e95e8725b676" [metadata.files] anyio = [ @@ -1461,6 +1556,10 @@ cffi = [ {file = "cffi-1.15.1-cp39-cp39-win_amd64.whl", hash = "sha256:70df4e3b545a17496c9b3f41f5115e69a4f2e77e94e1d2a8e1070bc0c38c8a3c"}, {file = "cffi-1.15.1.tar.gz", hash = "sha256:d400bfb9a37b1351253cb402671cea7e89bdecc294e8016a707f6d1d8ac934f9"}, ] +cfgv = [ + {file = "cfgv-3.3.1-py2.py3-none-any.whl", hash = "sha256:c6a0883f3917a037485059700b9e75da2464e6c27051014ad85ba6aaa5884426"}, + {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"}, +] click = [ {file = "click-8.1.3-py3-none-any.whl", hash = "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"}, {file = "click-8.1.3.tar.gz", hash = "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e"}, @@ -1501,6 +1600,10 @@ defusedxml = [ {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"}, {file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"}, ] +distlib = [ + {file = "distlib-0.3.6-py2.py3-none-any.whl", hash = "sha256:f35c4b692542ca110de7ef0bea44d73981caeb34ca0b9b6b2e6d7790dda8f80e"}, + {file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"}, +] exceptiongroup = [ {file = "exceptiongroup-1.1.0-py3-none-any.whl", hash = "sha256:327cbda3da756e2de031a3107b81ab7b3770a602c4d16ca618298c526f4bec1e"}, {file = "exceptiongroup-1.1.0.tar.gz", hash = "sha256:bcb67d800a4497e1b404c2dd44fca47d3b7a5e5433dbab67f96c1a685cdfdf23"}, @@ -1513,10 +1616,18 @@ fastjsonschema = [ {file = "fastjsonschema-2.16.2-py3-none-any.whl", hash = "sha256:21f918e8d9a1a4ba9c22e09574ba72267a6762d47822db9add95f6454e51cc1c"}, {file = "fastjsonschema-2.16.2.tar.gz", hash = "sha256:01e366f25d9047816fe3d288cbfc3e10541daf0af2044763f3d0ade42476da18"}, ] +filelock = [ + {file = "filelock-3.9.0-py3-none-any.whl", hash = "sha256:f58d535af89bb9ad5cd4df046f741f8553a418c01a7856bf0d173bbc9f6bd16d"}, + {file = "filelock-3.9.0.tar.gz", hash = "sha256:7b319f24340b51f55a2bf7a12ac0755a9b03e718311dac567a0f4f7fabd2f5de"}, +] fqdn = [ {file = "fqdn-1.5.1-py3-none-any.whl", hash = "sha256:3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014"}, {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"}, ] +identify = [ + {file = "identify-2.5.17-py2.py3-none-any.whl", hash = "sha256:7d526dd1283555aafcc91539acc061d8f6f59adb0a7bba462735b0a318bff7ed"}, + {file = "identify-2.5.17.tar.gz", hash = "sha256:93cc61a861052de9d4c541a7acb7e3dcc9c11b398a2144f6e52ae5285f5f4f06"}, +] idna = [ {file = "idna-3.4-py3-none-any.whl", hash = "sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2"}, {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"}, @@ -1685,6 +1796,10 @@ nest-asyncio = [ {file = "nest_asyncio-1.5.6-py3-none-any.whl", hash = "sha256:b9a953fb40dceaa587d109609098db21900182b16440652454a146cffb06e8b8"}, {file = "nest_asyncio-1.5.6.tar.gz", hash = "sha256:d267cc1ff794403f7df692964d1d2a3fa9418ffea2a3f6859a439ff482fef290"}, ] +nodeenv = [ + {file = "nodeenv-1.7.0-py2.py3-none-any.whl", hash = "sha256:27083a7b96a25f2f5e1d8cb4b6317ee8aeda3bdd121394e5ac54e498028a042e"}, + {file = "nodeenv-1.7.0.tar.gz", hash = "sha256:e0e7f7dfb85fc5394c6fe1e8fa98131a2473e04311a45afb6508f7cf1836fa2b"}, +] notebook = [ {file = "notebook-6.5.2-py3-none-any.whl", hash = "sha256:e04f9018ceb86e4fa841e92ea8fb214f8d23c1cedfde530cc96f92446924f0e4"}, {file = "notebook-6.5.2.tar.gz", hash = "sha256:c1897e5317e225fc78b45549a6ab4b668e4c996fd03a04e938fe5e7af2bfffd0"}, @@ -1755,6 +1870,10 @@ pluggy = [ {file = "pluggy-1.0.0-py2.py3-none-any.whl", hash = "sha256:74134bbf457f031a36d68416e1509f34bd5ccc019f0bcc952c7b909d06b37bd3"}, {file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"}, ] +pre-commit = [ + {file = "pre_commit-3.0.2-py2.py3-none-any.whl", hash = "sha256:f448d5224c70e196a6c6f87961d2333dfdc49988ebbf660477f9efe991c03597"}, + {file = "pre_commit-3.0.2.tar.gz", hash = "sha256:aa97fa71e7ab48225538e1e91a6b26e483029e6de64824f04760c32557bc91d7"}, +] prometheus-client = [ {file = "prometheus_client-0.16.0-py3-none-any.whl", hash = "sha256:0836af6eb2c8f4fed712b2f279f6c0a8bbab29f9f4aa15276b91c7cb0d1616ab"}, {file = "prometheus_client-0.16.0.tar.gz", hash = "sha256:a03e35b359f14dd1630898543e2120addfdeacd1a6069c1367ae90fd93ad3f48"}, @@ -2024,6 +2143,10 @@ send2trash = [ {file = "Send2Trash-1.8.0-py3-none-any.whl", hash = "sha256:f20eaadfdb517eaca5ce077640cb261c7d2698385a6a0f072a4a5447fd49fa08"}, {file = "Send2Trash-1.8.0.tar.gz", hash = "sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d"}, ] +setuptools = [ + {file = "setuptools-67.0.0-py3-none-any.whl", hash = "sha256:9d790961ba6219e9ff7d9557622d2fe136816a264dd01d5997cfc057d804853d"}, + {file = "setuptools-67.0.0.tar.gz", hash = "sha256:883131c5b6efa70b9101c7ef30b2b7b780a4283d5fc1616383cdf22c83cbefe6"}, +] six = [ {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"}, {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"}, @@ -2081,6 +2204,10 @@ uri-template = [ {file = "uri_template-1.2.0-py3-none-any.whl", hash = "sha256:f1699c77b73b925cf4937eae31ab282a86dc885c333f2e942513f08f691fc7db"}, {file = "uri_template-1.2.0.tar.gz", hash = "sha256:934e4d09d108b70eb8a24410af8615294d09d279ce0e7cbcdaef1bd21f932b06"}, ] +virtualenv = [ + {file = "virtualenv-20.17.1-py3-none-any.whl", hash = "sha256:ce3b1684d6e1a20a3e5ed36795a97dfc6af29bc3970ca8dab93e11ac6094b3c4"}, + {file = "virtualenv-20.17.1.tar.gz", hash = "sha256:f8b927684efc6f1cc206c9db297a570ab9ad0e51c16fa9e45487d36d1905c058"}, +] wcwidth = [ {file = "wcwidth-0.2.6-py2.py3-none-any.whl", hash = "sha256:795b138f6875577cd91bba52baf9e445cd5118fd32723b460e30a0af30ea230e"}, {file = "wcwidth-0.2.6.tar.gz", hash = "sha256:a5220780a404dbe3353789870978e472cfe477761f06ee55077256e509b156d0"}, diff --git a/pyproject.toml b/pyproject.toml index 872aa3f..02e7375 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,6 +16,7 @@ tqdm = "^4.64.1" [tool.poetry.group.build.dependencies] blackcellmagic = "^0.0.3" +pre-commit = "^3.0.2" [build-system] -- 2.49.0 From ef9fdf39ca9e0ca49271ac110be1d4498cb9a509 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Tue, 31 Jan 2023 20:31:57 +0100 Subject: [PATCH 02/31] Added functionality to execute a turn --- main.ipynb | 171 +++++++++++++++++++++++++++++++++++++++++++---------- 1 file changed, 141 insertions(+), 30 deletions(-) diff --git a/main.ipynb b/main.ipynb index ee4eec0..9013f86 100644 --- a/main.ipynb +++ b/main.ipynb @@ -58,35 +58,27 @@ "cell_type": "code", "execution_count": 5, "metadata": {}, - "outputs": [], - "source": [ - "def get_new_games(number_of_games:int):\n", - " empty = np.zeros([number_of_games, 8,8], dtype=int)\n", - " empty[:, 3:5, 3:5] = np.array([[-1,1], [1, -1]])\n", - " return empty" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, "outputs": [ { "data": { - "text/plain": "array([[[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]],\n\n [[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]],\n\n [[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 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{}, "output_type": "execute_result" } ], "source": [ - "get_new_games(10)" + "def get_new_games(number_of_games:int):\n", + " empty = np.zeros([number_of_games, 8,8], dtype=int)\n", + " empty[:, 3:5, 3:5] = np.array([[-1,1], [1, -1]])\n", + " return empty\n", + "get_new_games(1)[0]" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -100,37 +92,43 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 7, "metadata": {}, + "outputs": [], + "source": [ + "def get_new_games(number_of_games:int):\n", + " empty = np.zeros([number_of_games, 8,8], dtype=int)\n", + " empty[:, 3:5, 3:5] = np.array([[-1,1], [1, -1]])\n", + " return empty" + ] + }, + { + "cell_type": "code", + "execution_count": 8, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "8.58 ms ± 214 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "82.7 ms ± 2.17 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "17.2 ms ± 3.53 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "169 ms ± 33.2 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { "data": { "text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])" }, - "execution_count": 16, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def get_new_games(number_of_games:int):\n", - " empty = np.zeros([number_of_games, 8,8], dtype=int)\n", - " empty[:, 3:5, 3:5] = np.array([[-1,1], [1, -1]])\n", - " return empty\n", - "\n", "def recursive_steps(_array, rec_direction, rec_position, step_one=True):\n", " rec_position = rec_position + rec_direction\n", " if np.any((rec_position >= 8) | ( rec_position < 0)):\n", " return False\n", - " next_field = _array[rec_position[0], rec_position[1]]\n", + " next_field = _array[tuple(rec_position.tolist())]\n", " if next_field == 0:\n", " return False\n", " if next_field == -1:\n", @@ -152,17 +150,20 @@ "%timeit get_possible_turns(get_new_games(10))\n", "%timeit get_possible_turns(get_new_games(100))\n", "get_possible_turns(get_new_games(3))[:1]" - ] + ], + "metadata": { + "collapsed": false + } }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "outputs": [ { "data": { "text/plain": "(array([2, 2, 2]), array([2, 2, 2]))" }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -178,7 +179,117 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, + "outputs": [], + "source": [ + "def move_possible(board:np.ndarray, move: np.ndarray) -> bool:\n", + " if np.all(move == -1):\n", + " return np.all(get_possible_turns(board))\n", + " return any(recursive_steps(board[:, :], direction, move) for direction in DIRECTIONS)\n", + "\n", + "def moves_possible(boards:np.ndarray, moves: np.ndarray) -> np.ndarray:\n", + " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", + " for game in range(boards.shape[0]):\n", + " if np.all(moves[game] == -1):\n", + " arr_moves_possible[game, :, :] = np.all(get_possible_turns(boards[game, : , :]))\n", + " arr_moves_possible[game, :, :] = any(recursive_steps(boards[game, :, :], direction, moves[game]) for direction in DIRECTIONS)\n", + " return arr_moves_possible" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 11, + "outputs": [ + { + "data": { + "text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 0, 0, 0, 0],\n [ 0, 0, 0, -1, -1, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])" + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "class InvalidTurn(ValueError):\n", + " pass\n", + "\n", + "\n", + "def to_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", + "\n", + " def _do_directional_move(board: np.ndarray, rec_move: np.ndarray, rev_direction, step_one=True) -> bool:\n", + " rec_position = rec_move + rev_direction\n", + " if np.any((rec_position >= 8) | (rec_position < 0)):\n", + " return False\n", + " next_field = board[tuple(rec_position.tolist())]\n", + " if next_field == 0:\n", + " return False\n", + " if next_field == 1:\n", + " return not step_one\n", + " if next_field == -1:\n", + " if _do_directional_move(board, rec_position, rev_direction, step_one=False):\n", + " board[tuple(rec_position.tolist())] = 1\n", + " return True\n", + " return False\n", + "\n", + " def _do_move(_board: np.ndarray, move: np.ndarray) -> None:\n", + " if _board[tuple(move.tolist())] != 0:\n", + " raise InvalidTurn\n", + " action = False\n", + " for direction in DIRECTIONS:\n", + " if _do_directional_move(_board, move, direction):\n", + " action = True\n", + " if not action:\n", + " raise InvalidTurn()\n", + " _board[tuple(move.tolist())] = 1\n", + "\n", + " for game in range(boards.shape[0]):\n", + " _do_move(boards[game], moves[game])\n", + "boards = get_new_games(10)\n", + "to_moves(boards, np.array([[2,3]] * 10))\n", + "boards = boards * -1\n", + "boards[0]" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 12, + "outputs": [], + "source": [ + "to_moves(get_new_games(10), np.array([[2,3]] * 10))" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 13, + "outputs": [ + { + "data": { + "text/plain": "array([[4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3]])" + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.array([[4,3]] * 10)" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 13, "outputs": [], "source": [], "metadata": { -- 2.49.0 From 6899b759cf805ee2d671192168b0b31d0ab1131f Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Wed, 1 Feb 2023 00:03:27 +0100 Subject: [PATCH 03/31] Add pre commit game --- .pre-commit-config.yaml | 83 +++++++++++++++++++ test_main.ipynb | 172 ++++++++++++++++++++++++++++++++++++++++ 2 files changed, 255 insertions(+) create mode 100644 .pre-commit-config.yaml create mode 100644 test_main.ipynb diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..7934f57 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,83 @@ +default_language_version: + python: python3.10 + +repos: +- repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.4.0 + hooks: + - id: end-of-file-fixer + exclude: (.txt$|.ipynb$) + - id: trailing-whitespace + exclude: (.txt$|README.md$) + - id: check-yaml + - id: check-json + - id: check-toml + - id: check-xml + # - id: check-added-large-files + # args: [--enforce-all] + - id: name-tests-test + - id: detect-private-key + - id: check-case-conflict + - id: check-symlinks + - id: check-docstring-first + +- repo: https://github.com/psf/black + rev: 22.12.0 + hooks: + - id: black + args: [--config=pyproject.toml] + - id: black-jupyter + args: [--config=pyproject.toml] + +- repo: https://github.com/seandstewart/pre-commit-poetry-export + rev: f0501a85959a71c26b964d9542a78d1033af083e + hooks: [] + # - id: export-requirements + # - id: export-requirements-dev + +- repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks + rev: v2.6.0 + hooks: + - id: pretty-format-ini + args: [--autofix] + - id: pretty-format-toml + args: [--autofix] + - id: pretty-format-yaml + args: [--autofix] + exclude: (docker-compose.yaml$) + +- repo: https://github.com/jendrikseipp/vulture + rev: v2.7 # or any later Vulture version + hooks: + - id: vulture + +- repo: https://github.com/domdfcoding/flake2lint + rev: v0.4.2 + hooks: + - id: flake2lint + +- repo: https://github.com/PyCQA/flake8 + rev: 6.0.0 + hooks: + - id: flake8 + args: [--config=.flake8] + +- repo: https://github.com/pre-commit/mirrors-mypy + rev: v0.991 + hooks: + - id: mypy + +- repo: https://github.com/frnmst/md-toc + rev: 8.1.8 + hooks: + - id: md-toc + +- repo: https://gitlab.com/smop/pre-commit-hooks + rev: v1.0.0 + hooks: + - id: check-poetry + +- repo: https://github.com/Lucas-C/pre-commit-hooks-java + rev: 1.3.10 + hooks: + - id: validate-html diff --git a/test_main.ipynb b/test_main.ipynb new file mode 100644 index 0000000..05e51b8 --- /dev/null +++ b/test_main.ipynb @@ -0,0 +1,172 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [ + { + "data": { + "text/plain": "array([[0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.]])" + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.zeros((5,5))\n", + "a" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [ + { + "data": { + "text/plain": "array([[ 0., 0., 0., 0., 0.],\n [ 0., 0., 0., 0., 0.],\n [ 0., 0., 10., 0., 0.],\n [ 0., 0., 0., 0., 0.],\n [ 0., 0., 0., 0., 0.]])" + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a[2,2] = 10\n", + "a" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 4, + "outputs": [], + "source": [ + "index_array = np.array([2,2], dtype=int)" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 5, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "234 ns ± 7.47 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)\n", + "311 ns ± 2.15 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)\n" + ] + } + ], + "source": [ + "%timeit a[tuple(index_array.tolist())]\n", + "%timeit a[index_array[0], index_array[1]]" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 6, + "outputs": [], + "source": [ + "def array_change(array):\n", + " array[1] = 1" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 12, + "outputs": [ + { + "data": { + "text/plain": "array([[ 0., 0., 0., 0., 0.],\n [ 1., 1., 1., 1., 1.],\n [ 0., 1., 10., 0., 0.],\n [ 1., 1., 1., 1., 1.],\n [ 0., 0., 0., 0., 0.]])" + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "array_change(a[2:])\n", + "a" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 10, + "outputs": [ + { + "data": { + "text/plain": "array([[ 0., 0., 0., 0., 0.],\n [ 1., 1., 1., 1., 1.],\n [ 0., 1., 10., 0., 0.],\n [ 0., 0., 0., 0., 0.],\n [ 0., 0., 0., 0., 0.]])" + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + } + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} -- 2.49.0 From 7cacd0ef6413fb0043b104fc64ecb2f0f9a9c624 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Wed, 1 Feb 2023 00:12:03 +0100 Subject: [PATCH 04/31] Added functionality to execute a turn --- .pre-commit-config.yaml | 1 + poetry.lock | 2698 ++++++++++++++++++++++----------------- pyproject.toml | 20 +- 3 files changed, 1551 insertions(+), 1168 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 7934f57..f55e5e6 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -42,6 +42,7 @@ repos: args: [--autofix] - id: pretty-format-toml args: [--autofix] + exclude: ((pyproject.toml)|(poetry.lock)$) - id: pretty-format-yaml args: [--autofix] exclude: (docker-compose.yaml$) diff --git a/poetry.lock b/poetry.lock index be60bf1..1dde137 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,10 +1,1087 @@ 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terminal text." +name = "colorama" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" +version = "0.4.6" [[package]] -name = "comm" -version = "0.1.2" -description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." category = "main" +description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." +name = "comm" optional = false python-versions = ">=3.6" +version = "0.1.2" [package.dependencies] traitlets = ">=5.3" @@ -223,124 +1300,172 @@ traitlets = ">=5.3" test = ["pytest"] [[package]] -name = "debugpy" -version = "1.6.6" -description = "An implementation of the Debug Adapter Protocol for Python" category = "main" +description = "Python library for calculating contours of 2D quadrilateral grids" +name = "contourpy" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" +version = "1.0.7" + +[package.dependencies] +numpy = ">=1.16" + +[package.extras] +bokeh = ["bokeh", "chromedriver", "selenium"] +docs = ["furo", "sphinx-copybutton"] +mypy = ["contourpy[bokeh]", "docutils-stubs", "mypy (==0.991)", "types-Pillow"] +test = ["Pillow", "matplotlib", "pytest"] +test-no-images = ["pytest"] [[package]] -name = "decorator" -version = "5.1.1" -description = "Decorators for Humans" category = "main" +description = "Composable style cycles" +name = "cycler" +optional = false +python-versions = ">=3.6" +version = "0.11.0" + +[[package]] +category = "main" +description = "An implementation of the Debug Adapter Protocol for Python" +name = "debugpy" +optional = false +python-versions = ">=3.7" +version = "1.6.6" + +[[package]] +category = "main" +description = "Decorators for Humans" +name = "decorator" optional = false python-versions = ">=3.5" +version = "5.1.1" [[package]] -name = "defusedxml" -version = "0.7.1" -description = "XML bomb protection for Python stdlib modules" category = "main" +description = "XML bomb protection for Python stdlib modules" +name = "defusedxml" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +version = "0.7.1" [[package]] -name = "distlib" -version = "0.3.6" -description = "Distribution utilities" category = "dev" +description = "Distribution utilities" +name = "distlib" optional = false python-versions = "*" +version = "0.3.6" [[package]] -name = "exceptiongroup" -version = "1.1.0" -description = "Backport of PEP 654 (exception groups)" category = "main" +description = "Backport of PEP 654 (exception groups)" +name = "exceptiongroup" optional = false python-versions = ">=3.7" +version = "1.1.0" [package.extras] test = ["pytest (>=6)"] [[package]] -name = "executing" -version = "1.2.0" -description = "Get the currently executing AST node of a frame, and other information" category = "main" +description = "Get the currently executing AST node of a frame, and other information" +name = "executing" optional = false python-versions = "*" +version = "1.2.0" [package.extras] tests = ["asttokens", "littleutils", "pytest", "rich"] [[package]] -name = "fastjsonschema" -version = "2.16.2" -description = "Fastest Python implementation of JSON schema" category = "main" +description = "Fastest Python implementation of JSON schema" +name = "fastjsonschema" optional = false python-versions = "*" +version = "2.16.2" [package.extras] devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"] [[package]] -name = "filelock" -version = "3.9.0" -description = "A platform independent file lock." category = "dev" +description = "A platform independent file lock." +name = "filelock" optional = false python-versions = ">=3.7" +version = "3.9.0" [package.extras] docs = ["furo (>=2022.12.7)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] testing = ["covdefaults (>=2.2.2)", "coverage (>=7.0.1)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"] [[package]] -name = "fqdn" -version = "1.5.1" -description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers" category = "main" -optional = false -python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" - -[[package]] -name = "identify" -version = "2.5.17" -description = "File identification library for Python" -category = "dev" +description = "Tools to manipulate font files" +name = "fonttools" optional = false python-versions = ">=3.7" +version = "4.38.0" + +[package.extras] +all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=14.0.0)", "xattr", "zopfli (>=0.1.4)"] +graphite = ["lz4 (>=1.7.4.2)"] +interpolatable = ["munkres", "scipy"] +lxml = ["lxml (>=4.0,<5)"] +pathops = ["skia-pathops (>=0.5.0)"] +plot = ["matplotlib"] +repacker = ["uharfbuzz (>=0.23.0)"] +symfont = ["sympy"] +type1 = ["xattr"] +ufo = ["fs (>=2.2.0,<3)"] +unicode = ["unicodedata2 (>=14.0.0)"] +woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"] + +[[package]] +category = "main" +description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers" +name = "fqdn" +optional = false +python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" +version = "1.5.1" + +[[package]] +category = "dev" +description = "File identification library for Python" +name = "identify" +optional = false +python-versions = ">=3.7" +version = "2.5.17" [package.extras] license = ["ukkonen"] [[package]] -name = "idna" -version = "3.4" -description = "Internationalized Domain Names in Applications (IDNA)" category = "main" +description = "Internationalized Domain Names in Applications (IDNA)" +name = "idna" optional = false python-versions = ">=3.5" +version = "3.4" [[package]] -name = "iniconfig" -version = "2.0.0" -description = "brain-dead simple config-ini parsing" category = "main" +description = "brain-dead simple config-ini parsing" +name = "iniconfig" optional = false python-versions = ">=3.7" +version = "2.0.0" [[package]] -name = "ipykernel" -version = "6.20.2" -description = "IPython Kernel for Jupyter" category = "main" +description = "IPython Kernel for Jupyter" +name = "ipykernel" optional = false python-versions = ">=3.8" +version = "6.20.2" [package.dependencies] appnope = {version = "*", markers = "platform_system == \"Darwin\""} @@ -364,12 +1489,12 @@ pyside6 = ["pyside6"] test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"] [[package]] -name = "ipytest" -version = "0.13.0" -description = "Unit tests in IPython notebooks" category = "main" +description = "Unit tests in IPython notebooks" +name = "ipytest" optional = false python-versions = ">=3.6" +version = "0.13.0" [package.dependencies] ipython = "*" @@ -377,12 +1502,12 @@ packaging = "*" pytest = ">=5.4" [[package]] -name = "ipython" -version = "8.8.0" -description = "IPython: Productive Interactive Computing" category = "main" +description = "IPython: Productive Interactive Computing" +name = "ipython" optional = false python-versions = ">=3.8" +version = "8.8.0" [package.dependencies] appnope = {version = "*", markers = "sys_platform == \"darwin\""} @@ -412,20 +1537,20 @@ test = ["pytest (<7.1)", "pytest-asyncio", "testpath"] test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.20)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"] [[package]] -name = "ipython-genutils" -version = "0.2.0" -description = "Vestigial utilities from IPython" category = "main" +description = "Vestigial utilities from IPython" +name = "ipython-genutils" optional = false python-versions = "*" +version = "0.2.0" [[package]] -name = "ipywidgets" -version = "8.0.4" -description = "Jupyter interactive widgets" category = "main" +description = "Jupyter interactive widgets" +name = "ipywidgets" optional = false python-versions = ">=3.7" +version = "8.0.4" [package.dependencies] ipykernel = ">=4.5.1" @@ -438,23 +1563,23 @@ widgetsnbextension = ">=4.0,<5.0" test = ["jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"] [[package]] -name = "isoduration" -version = "20.11.0" -description = "Operations with ISO 8601 durations" category = "main" +description = "Operations with ISO 8601 durations" +name = "isoduration" optional = false python-versions = ">=3.7" +version = "20.11.0" [package.dependencies] arrow = ">=0.15.0" [[package]] -name = "jedi" -version = "0.18.2" -description = "An autocompletion tool for Python that can be used for text editors." category = "main" +description = "An autocompletion tool for Python that can be used for text editors." +name = "jedi" optional = false python-versions = ">=3.6" +version = "0.18.2" [package.dependencies] parso = ">=0.8.0,<0.9.0" @@ -465,12 +1590,12 @@ qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"] [[package]] -name = "jinja2" -version = "3.1.2" -description = "A very fast and expressive template engine." category = "main" +description = "A very fast and expressive template engine." +name = "jinja2" optional = false python-versions = ">=3.7" +version = "3.1.2" [package.dependencies] MarkupSafe = ">=2.0" @@ -479,20 +1604,20 @@ MarkupSafe = ">=2.0" i18n = ["Babel (>=2.7)"] [[package]] -name = "jsonpointer" -version = "2.3" -description = "Identify specific nodes in a JSON document (RFC 6901)" category = "main" +description = "Identify specific nodes in a JSON document (RFC 6901)" +name = "jsonpointer" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +version = "2.3" [[package]] -name = "jsonschema" -version = "4.17.3" -description = "An implementation of JSON Schema validation for Python" category = "main" +description = "An implementation of JSON Schema validation for Python" +name = "jsonschema" optional = false python-versions = ">=3.7" +version = "4.17.3" [package.dependencies] attrs = ">=17.4.0" @@ -511,12 +1636,12 @@ format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validat format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"] [[package]] -name = "jupyter" -version = "1.0.0" -description = "Jupyter metapackage. Install all the Jupyter components in one go." category = "main" +description = "Jupyter metapackage. Install all the Jupyter components in one go." +name = "jupyter" optional = false python-versions = "*" +version = "1.0.0" [package.dependencies] ipykernel = "*" @@ -527,12 +1652,12 @@ notebook = "*" qtconsole = "*" [[package]] -name = "jupyter-client" -version = "8.0.1" -description = "Jupyter protocol implementation and client libraries" category = "main" +description = "Jupyter protocol implementation and client libraries" +name = "jupyter-client" optional = false python-versions = ">=3.8" +version = "8.0.1" [package.dependencies] jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" @@ -546,12 +1671,12 @@ docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphi test = ["codecov", "coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"] [[package]] -name = "jupyter-console" -version = "6.4.4" -description = "Jupyter terminal console" category = "main" +description = "Jupyter terminal console" +name = "jupyter-console" optional = false python-versions = ">=3.7" +version = "6.4.4" [package.dependencies] ipykernel = "*" @@ -564,12 +1689,12 @@ pygments = "*" test = ["pexpect"] [[package]] -name = "jupyter-core" -version = "5.1.5" -description = "Jupyter core package. A base package on which Jupyter projects rely." category = "main" +description = "Jupyter core package. A base package on which Jupyter projects rely." +name = "jupyter-core" optional = false python-versions = ">=3.8" +version = "5.1.5" [package.dependencies] platformdirs = ">=2.5" @@ -581,12 +1706,12 @@ docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", " test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] [[package]] -name = "jupyter-events" -version = "0.6.3" -description = "Jupyter Event System library" category = "main" +description = "Jupyter Event System library" +name = "jupyter-events" optional = false python-versions = ">=3.7" +version = "0.6.3" [package.dependencies] jsonschema = {version = ">=3.2.0", extras = ["format-nongpl"]} @@ -602,12 +1727,12 @@ docs = ["jupyterlite-sphinx", "myst-parser", "pydata-sphinx-theme", "sphinxcontr test = ["click", "coverage", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "pytest-cov", "rich"] [[package]] -name = "jupyter-server" -version = "2.1.0" -description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." category = "main" +description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." +name = "jupyter-server" optional = false python-versions = ">=3.8" +version = "2.1.0" [package.dependencies] anyio = ">=3.1.0,<4" @@ -634,12 +1759,12 @@ docs = ["docutils (<0.20)", "ipykernel", "jinja2", "jupyter-client", "jupyter-se test = ["ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.4)", "pytest-timeout", "requests"] [[package]] -name = "jupyter-server-terminals" -version = "0.4.4" -description = "A Jupyter Server Extension Providing Terminals." category = "main" +description = "A Jupyter Server Extension Providing Terminals." +name = "jupyter-server-terminals" optional = false python-versions = ">=3.8" +version = "0.4.4" [package.dependencies] pywinpty = {version = ">=2.0.3", markers = "os_name == \"nt\""} @@ -650,65 +1775,94 @@ docs = ["jinja2", "jupyter-server", "mistune (<3.0)", "myst-parser", "nbformat", test = ["coverage", "jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-cov", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"] [[package]] -name = "jupyterlab-pygments" -version = "0.2.2" +category = "main" description = "Pygments theme using JupyterLab CSS variables" -category = "main" +name = "jupyterlab-pygments" optional = false python-versions = ">=3.7" +version = "0.2.2" [[package]] -name = "jupyterlab-widgets" -version = "3.0.5" +category = "main" description = "Jupyter interactive widgets for JupyterLab" -category = "main" +name = "jupyterlab-widgets" optional = false python-versions = ">=3.7" +version = "3.0.5" [[package]] -name = "markupsafe" -version = "2.1.2" +category = "main" +description = "A fast implementation of the Cassowary constraint solver" +name = "kiwisolver" +optional = false +python-versions = ">=3.7" +version = "1.4.4" + +[[package]] +category = "main" description = "Safely add untrusted strings to HTML/XML markup." -category = "main" +name = "markupsafe" optional = false python-versions = ">=3.7" +version = "2.1.2" [[package]] -name = "matplotlib-inline" -version = "0.1.6" -description = "Inline Matplotlib backend for Jupyter" category = "main" +description = "Python plotting package" +name = "matplotlib" +optional = false +python-versions = ">=3.8" +version = "3.6.3" + +[package.dependencies] +contourpy = ">=1.0.1" +cycler = ">=0.10" +fonttools = ">=4.22.0" +kiwisolver = ">=1.0.1" +numpy = ">=1.19" +packaging = ">=20.0" +pillow = ">=6.2.0" +pyparsing = ">=2.2.1" +python-dateutil = ">=2.7" +setuptools_scm = ">=7" + +[[package]] +category = "main" +description = "Inline Matplotlib backend for Jupyter" +name = "matplotlib-inline" optional = false python-versions = ">=3.5" +version = "0.1.6" [package.dependencies] traitlets = "*" [[package]] -name = "mistune" -version = "2.0.4" +category = "main" description = "A sane Markdown parser with useful plugins and renderers" -category = "main" +name = "mistune" optional = false python-versions = "*" +version = "2.0.4" [[package]] -name = "mypy-extensions" -version = "0.4.3" -description = "Experimental type system extensions for programs checked with the mypy typechecker." category = "dev" +description = "Experimental type system extensions for programs checked with the mypy typechecker." +name = "mypy-extensions" optional = false python-versions = "*" +version = "0.4.3" [[package]] -name = "nbclassic" -version = "0.5.1" -description = "Jupyter Notebook as a Jupyter Server extension." category = "main" +description = "Jupyter Notebook as a Jupyter Server extension." +name = "nbclassic" optional = false python-versions = ">=3.7" +version = "0.5.1" [package.dependencies] +Send2Trash = ">=1.8.0" argon2-cffi = "*" ipykernel = "*" ipython-genutils = "*" @@ -722,7 +1876,6 @@ nest-asyncio = ">=1.5" notebook-shim = ">=0.1.0" prometheus-client = "*" pyzmq = ">=17" -Send2Trash = ">=1.8.0" terminado = ">=0.8.3" tornado = ">=6.1" traitlets = ">=4.2.1" @@ -733,12 +1886,12 @@ json-logging = ["json-logging"] test = ["coverage", "nbval", "pytest", "pytest-cov", "pytest-jupyter", "pytest-playwright", "pytest-tornasync", "requests", "requests-unixsocket", "testpath"] [[package]] -name = "nbclient" -version = "0.7.2" -description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." category = "main" +description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." +name = "nbclient" optional = false python-versions = ">=3.7.0" +version = "0.7.2" [package.dependencies] jupyter-client = ">=6.1.12" @@ -752,12 +1905,12 @@ docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphi test = ["ipykernel", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"] [[package]] -name = "nbconvert" -version = "7.2.9" -description = "Converting Jupyter Notebooks" category = "main" +description = "Converting Jupyter Notebooks" +name = "nbconvert" optional = false python-versions = ">=3.7" +version = "7.2.9" [package.dependencies] beautifulsoup4 = "*" @@ -786,12 +1939,12 @@ test = ["ipykernel", "ipywidgets (>=7)", "pre-commit", "pytest", "pytest-depende webpdf = ["pyppeteer (>=1,<1.1)"] [[package]] -name = "nbformat" -version = "5.7.3" -description = "The Jupyter Notebook format" category = "main" +description = "The Jupyter Notebook format" +name = "nbformat" optional = false python-versions = ">=3.7" +version = "5.7.3" [package.dependencies] fastjsonschema = "*" @@ -804,33 +1957,34 @@ docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-al test = ["pep440", "pre-commit", "pytest", "testpath"] [[package]] -name = "nest-asyncio" -version = "1.5.6" -description = "Patch asyncio to allow nested event loops" category = "main" +description = "Patch asyncio to allow nested event loops" +name = "nest-asyncio" optional = false python-versions = ">=3.5" +version = "1.5.6" [[package]] -name = "nodeenv" -version = "1.7.0" -description = "Node.js virtual environment builder" category = "dev" +description = "Node.js virtual environment builder" +name = "nodeenv" optional = false python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*" +version = "1.7.0" [package.dependencies] setuptools = "*" [[package]] -name = "notebook" -version = "6.5.2" -description = "A web-based notebook environment for interactive computing" category = "main" +description = "A web-based notebook environment for interactive computing" +name = "notebook" optional = false python-versions = ">=3.7" +version = "6.5.2" [package.dependencies] +Send2Trash = ">=1.8.0" argon2-cffi = "*" ipykernel = "*" ipython-genutils = "*" @@ -843,7 +1997,6 @@ nbformat = "*" nest-asyncio = ">=1.5" prometheus-client = "*" pyzmq = ">=17" -Send2Trash = ">=1.8.0" terminado = ">=0.8.3" tornado = ">=6.1" traitlets = ">=4.2.1" @@ -854,12 +2007,12 @@ json-logging = ["json-logging"] test = ["coverage", "nbval", "pytest", "pytest-cov", "requests", "requests-unixsocket", "selenium (==4.1.5)", "testpath"] [[package]] -name = "notebook-shim" -version = "0.2.2" -description = "A shim layer for notebook traits and config" category = "main" +description = "A shim layer for notebook traits and config" +name = "notebook-shim" optional = false python-versions = ">=3.7" +version = "0.2.2" [package.dependencies] jupyter-server = ">=1.8,<3" @@ -868,99 +2021,111 @@ jupyter-server = ">=1.8,<3" test = ["pytest", "pytest-console-scripts", "pytest-tornasync"] [[package]] -name = "numpy" -version = "1.24.1" -description = "Fundamental package for array computing in Python" category = "main" +description = "Fundamental package for array computing in Python" +name = "numpy" optional = false python-versions = ">=3.8" +version = "1.24.1" [[package]] -name = "packaging" -version = "23.0" -description = "Core utilities for Python packages" category = "main" +description = "Core utilities for Python packages" +name = "packaging" optional = false python-versions = ">=3.7" +version = "23.0" [[package]] -name = "pandocfilters" -version = "1.5.0" -description = "Utilities for writing pandoc filters in python" category = "main" +description = "Utilities for writing pandoc filters in python" +name = "pandocfilters" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +version = "1.5.0" [[package]] -name = "parso" -version = "0.8.3" -description = "A Python Parser" category = "main" +description = "A Python Parser" +name = "parso" optional = false python-versions = ">=3.6" +version = "0.8.3" [package.extras] qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] testing = ["docopt", "pytest (<6.0.0)"] [[package]] -name = "pathspec" -version = "0.11.0" -description = "Utility library for gitignore style pattern matching of file paths." category = "dev" +description = "Utility library for gitignore style pattern matching of file paths." +name = "pathspec" optional = false python-versions = ">=3.7" +version = "0.11.0" [[package]] -name = "pexpect" -version = "4.8.0" -description = "Pexpect allows easy control of interactive console applications." category = "main" +description = "Pexpect allows easy control of interactive console applications." +name = "pexpect" optional = false python-versions = "*" +version = "4.8.0" [package.dependencies] ptyprocess = ">=0.5" [[package]] -name = "pickleshare" -version = "0.7.5" -description = "Tiny 'shelve'-like database with concurrency support" category = "main" +description = "Tiny 'shelve'-like database with concurrency support" +name = "pickleshare" optional = false python-versions = "*" +version = "0.7.5" [[package]] -name = "platformdirs" -version = "2.6.2" -description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." category = "main" +description = "Python Imaging Library (Fork)" +name = "pillow" optional = false python-versions = ">=3.7" +version = "9.4.0" + +[package.extras] +docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinxext-opengraph"] +tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"] + +[[package]] +category = "main" +description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." +name = "platformdirs" +optional = false +python-versions = ">=3.7" +version = "2.6.2" [package.extras] docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] test = ["appdirs (==1.4.4)", "covdefaults (>=2.2.2)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"] [[package]] -name = "pluggy" -version = "1.0.0" -description = "plugin and hook calling mechanisms for python" category = "main" +description = "plugin and hook calling mechanisms for python" +name = "pluggy" optional = false python-versions = ">=3.6" +version = "1.0.0" [package.extras] dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] [[package]] -name = "pre-commit" -version = "3.0.2" -description = "A framework for managing and maintaining multi-language pre-commit hooks." category = "dev" +description = "A framework for managing and maintaining multi-language pre-commit hooks." +name = "pre-commit" optional = false python-versions = ">=3.8" +version = "3.0.2" [package.dependencies] cfgv = ">=2.0.0" @@ -970,91 +2135,102 @@ pyyaml = ">=5.1" virtualenv = ">=20.10.0" [[package]] -name = "prometheus-client" -version = "0.16.0" -description = "Python client for the Prometheus monitoring system." category = "main" +description = "Python client for the Prometheus monitoring system." +name = "prometheus-client" optional = false python-versions = ">=3.6" +version = "0.16.0" [package.extras] twisted = ["twisted"] [[package]] -name = "prompt-toolkit" -version = "3.0.36" -description = "Library for building powerful interactive command lines in Python" category = "main" +description = "Library for building powerful interactive command lines in Python" +name = "prompt-toolkit" optional = false python-versions = ">=3.6.2" +version = "3.0.36" [package.dependencies] wcwidth = "*" [[package]] -name = "psutil" -version = "5.9.4" -description = "Cross-platform lib for process and system monitoring in Python." category = "main" +description = "Cross-platform lib for process and system monitoring in Python." +name = "psutil" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +version = "5.9.4" [package.extras] test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"] [[package]] -name = "ptyprocess" -version = "0.7.0" -description = "Run a subprocess in a pseudo terminal" category = "main" +description = "Run a subprocess in a pseudo terminal" +name = "ptyprocess" optional = false python-versions = "*" +version = "0.7.0" [[package]] -name = "pure-eval" -version = "0.2.2" -description = "Safely evaluate AST nodes without side effects" category = "main" +description = "Safely evaluate AST nodes without side effects" +name = "pure-eval" optional = false python-versions = "*" +version = "0.2.2" [package.extras] tests = ["pytest"] [[package]] -name = "pycparser" -version = "2.21" -description = "C parser in Python" category = "main" +description = "C parser in Python" +name = "pycparser" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +version = "2.21" [[package]] -name = "pygments" -version = "2.14.0" -description = "Pygments is a syntax highlighting package written in Python." category = "main" +description = "Pygments is a syntax highlighting package written in Python." +name = "pygments" optional = false python-versions = ">=3.6" +version = "2.14.0" [package.extras] plugins = ["importlib-metadata"] [[package]] -name = "pyrsistent" -version = "0.19.3" -description = "Persistent/Functional/Immutable data structures" category = "main" +description = "pyparsing module - Classes and methods to define and execute parsing grammars" +name = "pyparsing" optional = false -python-versions = ">=3.7" +python-versions = ">=3.6.8" +version = "3.0.9" + +[package.extras] +diagrams = ["jinja2", "railroad-diagrams"] [[package]] -name = "pytest" -version = "7.2.1" -description = "pytest: simple powerful testing with Python" category = "main" +description = "Persistent/Functional/Immutable data structures" +name = "pyrsistent" optional = false python-versions = ">=3.7" +version = "0.19.3" + +[[package]] +category = "main" +description = "pytest: simple powerful testing with Python" +name = "pytest" +optional = false +python-versions = ">=3.7" +version = "7.2.1" [package.dependencies] attrs = ">=19.2.0" @@ -1069,66 +2245,66 @@ tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""} testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"] [[package]] -name = "python-dateutil" -version = "2.8.2" -description = "Extensions to the standard Python datetime module" category = "main" +description = "Extensions to the standard Python datetime module" +name = "python-dateutil" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +version = "2.8.2" [package.dependencies] six = ">=1.5" [[package]] -name = "python-json-logger" -version = "2.0.4" -description = "A python library adding a json log formatter" category = "main" +description = "A python library adding a json log formatter" +name = "python-json-logger" optional = false python-versions = ">=3.5" +version = "2.0.4" [[package]] -name = "pywin32" -version = "305" -description = "Python for Window Extensions" category = "main" +description = "Python for Window Extensions" +name = "pywin32" optional = false python-versions = "*" +version = "305" [[package]] -name = "pywinpty" -version = "2.0.10" -description = "Pseudo terminal support for Windows from Python." category = "main" +description = "Pseudo terminal support for Windows from Python." +name = "pywinpty" optional = false python-versions = ">=3.7" +version = "2.0.10" [[package]] -name = "pyyaml" -version = "6.0" +category = "main" description = "YAML parser and emitter for Python" -category = "main" +name = "pyyaml" optional = false python-versions = ">=3.6" +version = "6.0" [[package]] -name = "pyzmq" -version = "25.0.0" -description = "Python bindings for 0MQ" category = "main" +description = "Python bindings for 0MQ" +name = "pyzmq" optional = false python-versions = ">=3.6" +version = "25.0.0" [package.dependencies] cffi = {version = "*", markers = "implementation_name == \"pypy\""} [[package]] -name = "qtconsole" -version = "5.4.0" -description = "Jupyter Qt console" category = "main" +description = "Jupyter Qt console" +name = "qtconsole" optional = false python-versions = ">= 3.7" +version = "5.4.0" [package.dependencies] ipykernel = ">=4.1" @@ -1145,12 +2321,12 @@ doc = ["Sphinx (>=1.3)"] test = ["flaky", "pytest", "pytest-qt"] [[package]] -name = "qtpy" -version = "2.3.0" -description = "Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6)." category = "main" +description = "Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6)." +name = "qtpy" optional = false python-versions = ">=3.7" +version = "2.3.0" [package.dependencies] packaging = "*" @@ -1159,31 +2335,31 @@ packaging = "*" test = ["pytest (>=6,!=7.0.0,!=7.0.1)", "pytest-cov (>=3.0.0)", "pytest-qt"] [[package]] -name = "rfc3339-validator" -version = "0.1.4" -description = "A pure python RFC3339 validator" category = "main" +description = "A pure python RFC3339 validator" +name = "rfc3339-validator" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +version = "0.1.4" [package.dependencies] six = "*" [[package]] -name = "rfc3986-validator" -version = "0.1.1" -description = "Pure python rfc3986 validator" category = "main" +description = "Pure python rfc3986 validator" +name = "rfc3986-validator" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +version = "0.1.1" [[package]] -name = "scipy" -version = "1.10.0" -description = "Fundamental algorithms for scientific computing in Python" category = "main" +description = "Fundamental algorithms for scientific computing in Python" +name = "scipy" optional = false python-versions = "<3.12,>=3.8" +version = "1.10.0" [package.dependencies] numpy = ">=1.19.5,<1.27.0" @@ -1194,12 +2370,12 @@ doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx ( test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"] [[package]] -name = "send2trash" -version = "1.8.0" -description = "Send file to trash natively under Mac OS X, Windows and Linux." category = "main" +description = "Send file to trash natively under Mac OS X, Windows and Linux." +name = "send2trash" optional = false python-versions = "*" +version = "1.8.0" [package.extras] nativelib = ["pyobjc-framework-Cocoa", "pywin32"] @@ -1207,12 +2383,12 @@ objc = ["pyobjc-framework-Cocoa"] win32 = ["pywin32"] [[package]] -name = "setuptools" -version = "67.0.0" +category = "main" description = "Easily download, build, install, upgrade, and uninstall Python packages" -category = "dev" +name = "setuptools" optional = false python-versions = ">=3.7" +version = "67.0.0" [package.extras] docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"] @@ -1220,36 +2396,54 @@ testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-202 testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"] [[package]] -name = "six" -version = "1.16.0" -description = "Python 2 and 3 compatibility utilities" -category = "main" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" - -[[package]] -name = "sniffio" -version = "1.3.0" -description = "Sniff out which async library your code is running under" category = "main" +description = "the blessed package to manage your versions by scm tags" +name = "setuptools-scm" optional = false python-versions = ">=3.7" +version = "7.1.0" + +[package.dependencies] +packaging = ">=20.0" +setuptools = "*" +tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""} +typing-extensions = "*" + +[package.extras] +test = ["pytest (>=6.2)", "virtualenv (>20)"] +toml = ["setuptools (>=42)"] [[package]] -name = "soupsieve" -version = "2.3.2.post1" -description = "A modern CSS selector implementation for Beautiful Soup." category = "main" +description = "Python 2 and 3 compatibility utilities" +name = "six" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" +version = "1.16.0" + +[[package]] +category = "main" +description = "Sniff out which async library your code is running under" +name = "sniffio" +optional = false +python-versions = ">=3.7" +version = "1.3.0" + +[[package]] +category = "main" +description = "A modern CSS selector implementation for Beautiful Soup." +name = "soupsieve" optional = false python-versions = ">=3.6" +version = "2.3.2.post1" [[package]] -name = "stack-data" -version = "0.6.2" -description = "Extract data from python stack frames and tracebacks for informative displays" category = "main" +description = "Extract data from python stack frames and tracebacks for informative displays" +name = "stack-data" optional = false python-versions = "*" +version = "0.6.2" [package.dependencies] asttokens = ">=2.1.0" @@ -1260,12 +2454,12 @@ pure-eval = "*" tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"] [[package]] -name = "terminado" -version = "0.17.1" -description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library." category = "main" +description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library." +name = "terminado" optional = false python-versions = ">=3.7" +version = "0.17.1" [package.dependencies] ptyprocess = {version = "*", markers = "os_name != \"nt\""} @@ -1277,12 +2471,12 @@ docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"] test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"] [[package]] -name = "tinycss2" -version = "1.2.1" -description = "A tiny CSS parser" category = "main" +description = "A tiny CSS parser" +name = "tinycss2" optional = false python-versions = ">=3.7" +version = "1.2.1" [package.dependencies] webencodings = ">=0.4" @@ -1292,28 +2486,28 @@ doc = ["sphinx", "sphinx_rtd_theme"] test = ["flake8", "isort", "pytest"] [[package]] -name = "tomli" -version = "1.2.3" -description = "A lil' TOML parser" category = "main" +description = "A lil' TOML parser" +name = "tomli" optional = false python-versions = ">=3.6" +version = "1.2.3" [[package]] -name = "tornado" -version = "6.2" -description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." category = "main" +description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." +name = "tornado" optional = false python-versions = ">= 3.7" +version = "6.2" [[package]] -name = "tqdm" -version = "4.64.1" -description = "Fast, Extensible Progress Meter" category = "main" +description = "Fast, Extensible Progress Meter" +name = "tqdm" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7" +version = "4.64.1" [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} @@ -1325,43 +2519,43 @@ slack = ["slack-sdk"] telegram = ["requests"] [[package]] -name = "traitlets" -version = "5.8.1" -description = "Traitlets Python configuration system" category = "main" +description = "Traitlets Python configuration system" +name = "traitlets" optional = false python-versions = ">=3.7" +version = "5.8.1" [package.extras] docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"] test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"] [[package]] -name = "typing-extensions" -version = "4.4.0" +category = "main" description = "Backported and Experimental Type Hints for Python 3.7+" -category = "dev" +name = "typing-extensions" optional = false python-versions = ">=3.7" +version = "4.4.0" [[package]] -name = "uri-template" -version = "1.2.0" -description = "RFC 6570 URI Template Processor" category = "main" +description = "RFC 6570 URI Template Processor" +name = "uri-template" optional = false python-versions = ">=3.6" +version = "1.2.0" [package.extras] dev = ["flake8 (<4.0.0)", "flake8-annotations", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-noqa", "flake8-requirements", "flake8-type-annotations", "flake8-use-fstring", "mypy", "pep8-naming"] [[package]] -name = "virtualenv" -version = "20.17.1" -description = "Virtual Python Environment builder" category = "dev" +description = "Virtual Python Environment builder" +name = "virtualenv" optional = false python-versions = ">=3.6" +version = "20.17.1" [package.dependencies] distlib = ">=0.3.6,<1" @@ -1373,36 +2567,36 @@ docs = ["proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-argparse (>=0.3.2)", "sp testing = ["coverage (>=6.2)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=21.3)", "pytest (>=7.0.1)", "pytest-env (>=0.6.2)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.6.1)", "pytest-randomly (>=3.10.3)", "pytest-timeout (>=2.1)"] [[package]] -name = "wcwidth" -version = "0.2.6" +category = "main" description = "Measures the displayed width of unicode strings in a terminal" -category = "main" +name = "wcwidth" optional = false python-versions = "*" +version = "0.2.6" [[package]] -name = "webcolors" -version = "1.12" +category = "main" description = "A library for working with color names and color values formats defined by HTML and CSS." -category = "main" +name = "webcolors" optional = false python-versions = ">=3.7" +version = "1.12" [[package]] -name = "webencodings" -version = "0.5.1" -description = "Character encoding aliases for legacy web content" category = "main" +description = "Character encoding aliases for legacy web content" +name = "webencodings" optional = false python-versions = "*" +version = "0.5.1" [[package]] -name = "websocket-client" -version = "1.5.0" -description = "WebSocket client for Python with low level API options" category = "main" +description = "WebSocket client for Python with low level API options" +name = "websocket-client" optional = false python-versions = ">=3.7" +version = "1.5.0" [package.extras] docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"] @@ -1410,821 +2604,9 @@ optional = ["python-socks", "wsaccel"] test = ["websockets"] [[package]] -name = "widgetsnbextension" -version = "4.0.5" -description = 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+requires = ["poetry-core"] + [tool.poetry] -name = "reversi" -version = "0.1.0" -description = "" authors = ["Philipp Horstenkamp "] +description = "" +name = "reversi" readme = "README.md" +version = "0.1.0" [tool.poetry.dependencies] -python = "3.10.*" +ipytest = "^0.13.0" jupyter = "^1.0.0" +matplotlib = "^3.6.3" numpy = "^1.24.1" pytest = "^7.2.1" -ipytest = "^0.13.0" +python = "3.10.*" scipy = "^1.10.0" tqdm = "^4.64.1" [tool.poetry.group.build.dependencies] blackcellmagic = "^0.0.3" pre-commit = "^3.0.2" - - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" -- 2.49.0 From 4928463d8058fb1eff7815ba91f1c04d6cad564a Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Wed, 1 Feb 2023 00:13:35 +0100 Subject: [PATCH 05/31] Added functionality to plot a set of otello boards. --- main.ipynb | 635 +++++++++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 542 insertions(+), 93 deletions(-) diff --git a/main.ipynb b/main.ipynb index 9013f86..c1abc67 100644 --- a/main.ipynb +++ b/main.ipynb @@ -18,7 +18,8 @@ "import numpy as np\n", "from typing import Final\n", "from scipy.ndimage import binary_dilation\n", - "from tqdm.auto import tqdm" + "from tqdm.auto import tqdm\n", + "import matplotlib.pyplot as plt" ] }, { @@ -28,16 +29,27 @@ "outputs": [], "source": [ "ENEMY: Final[int] = -1\n", - "PLAYER: Final[int] = 1" + "PLAYER: Final[int] = 1\n", + "BOARD_SIZE: Final[int] = 8" ] }, { "cell_type": "code", "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { - "text/plain": "array([[-1, -1],\n [-1, 0],\n [-1, 1],\n [ 0, -1],\n [ 0, 1],\n [ 1, -1],\n [ 1, 0],\n [ 1, 1]])" + "text/plain": [ + "array([[-1, -1],\n", + " [-1, 0],\n", + " [-1, 1],\n", + " [ 0, -1],\n", + " [ 0, 1],\n", + " [ 1, -1],\n", + " [ 1, 0],\n", + " [ 1, 1]])" + ] }, "execution_count": 4, "metadata": {}, @@ -49,10 +61,7 @@ " [[i, j] for i in range(-1, 2) for j in range(-1, 2) if j != 0 or i != 0], dtype=int\n", ")\n", "DIRECTIONS" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", @@ -61,7 +70,16 @@ "outputs": [ { "data": { - "text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])" + "text/plain": [ + "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0]])" + ] }, "execution_count": 5, "metadata": {}, @@ -69,10 +87,12 @@ } ], "source": [ - "def get_new_games(number_of_games:int):\n", - " empty = np.zeros([number_of_games, 8,8], dtype=int)\n", - " empty[:, 3:5, 3:5] = np.array([[-1,1], [1, -1]])\n", + "def get_new_games(number_of_games: int):\n", + " empty = np.zeros([number_of_games, BOARD_SIZE, BOARD_SIZE], dtype=int)\n", + " empty[:, 3:5, 3:5] = np.array([[-1, 1], [1, -1]])\n", " return empty\n", + "\n", + "\n", "get_new_games(1)[0]" ] }, @@ -83,9 +103,29 @@ "outputs": [], "source": [ "test_number_of_games = 3\n", - "assert get_new_games(test_number_of_games).shape == (test_number_of_games, 8, 8 )\n", - "np.testing.assert_equal( get_new_games(test_number_of_games).sum(axis=1), np.zeros([test_number_of_games, 8, ]))\n", - "np.testing.assert_equal( get_new_games(test_number_of_games).sum(axis=2), np.zeros([test_number_of_games, 8, ]))\n", + "assert get_new_games(test_number_of_games).shape == (\n", + " test_number_of_games,\n", + " BOARD_SIZE,\n", + " BOARD_SIZE,\n", + ")\n", + "np.testing.assert_equal(\n", + " get_new_games(test_number_of_games).sum(axis=1),\n", + " np.zeros(\n", + " [\n", + " test_number_of_games,\n", + " 8,\n", + " ]\n", + " ),\n", + ")\n", + "np.testing.assert_equal(\n", + " get_new_games(test_number_of_games).sum(axis=2),\n", + " np.zeros(\n", + " [\n", + " test_number_of_games,\n", + " 8,\n", + " ]\n", + " ),\n", + ")\n", "assert np.all(get_new_games(test_number_of_games)[:, 3:4, 3:4] != 0)\n", "del test_number_of_games" ] @@ -96,29 +136,84 @@ "metadata": {}, "outputs": [], "source": [ - "def get_new_games(number_of_games:int):\n", - " empty = np.zeros([number_of_games, 8,8], dtype=int)\n", - " empty[:, 3:5, 3:5] = np.array([[-1,1], [1, -1]])\n", - " return empty" + "def plot_othello_board(board, ax=None):\n", + " size = 3\n", + " plot_all = False\n", + " if ax is None:\n", + " plot_all = True\n", + " fig, ax = plt.subplots(figsize=(size, size))\n", + "\n", + " ax.set_facecolor(\"green\")\n", + " for i in range(BOARD_SIZE):\n", + " for j in range(BOARD_SIZE):\n", + " if board[i, j] == -1:\n", + " color = \"white\"\n", + " elif board[i, j] == 1:\n", + " color = \"black\"\n", + " else:\n", + " continue\n", + " ax.scatter(j, i, s=300 if plot_all else 150, c=color)\n", + " for i in range(-1, 8):\n", + " ax.axhline(i + 0.5, color=\"black\", lw=2)\n", + " ax.axvline(i + 0.5, color=\"black\", lw=2)\n", + " ax.set_xlim(-0.5, 7.5)\n", + " ax.set_ylim(7.5, -0.5)\n", + " ax.set_xticks(np.arange(8))\n", + " ax.set_xticklabels(list(\"ABCDEFGH\"))\n", + " ax.set_yticks(np.arange(8))\n", + " ax.set_yticklabels(list(\"12345678\"))\n", + " if plot_all:\n", + " plt.tight_layout()\n", + " plt.show()" ] }, { "cell_type": "code", "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_othello_boards(boards: np.ndarray) -> None:\n", + " assert boards.shape[0] < 70\n", + " plots_per_row = 4\n", + " rows = int(np.ceil(boards.shape[0] / plots_per_row))\n", + " fig, axs = plt.subplots(rows, plots_per_row, figsize=(12, 3 * rows))\n", + " for game_index, ax in enumerate(axs.flatten()):\n", + " if game_index >= boards.shape[0]:\n", + " fig.delaxes(ax)\n", + " else:\n", + " plot_othello_board(boards[game_index], ax)\n", + " plt.tight_layout()\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "17.2 ms ± 3.53 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "169 ms ± 33.2 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "8.49 ms ± 143 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "80.9 ms ± 537 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { "data": { - "text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])" + "text/plain": [ + "array([[[False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, True, False, False, False, False],\n", + " [False, False, True, False, False, False, False, False],\n", + " [False, False, False, False, False, True, False, False],\n", + " [False, False, False, False, True, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False]]])" + ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -126,7 +221,7 @@ "source": [ "def recursive_steps(_array, rec_direction, rec_position, step_one=True):\n", " rec_position = rec_position + rec_direction\n", - " if np.any((rec_position >= 8) | ( rec_position < 0)):\n", + " if np.any((rec_position >= BOARD_SIZE) | (rec_position < 0)):\n", " return False\n", " next_field = _array[tuple(rec_position.tolist())]\n", " if next_field == 0:\n", @@ -136,78 +231,100 @@ " if next_field == 1:\n", " return not step_one\n", "\n", + "\n", "def get_possible_turns(boards: np.ndarray) -> np.ndarray:\n", - " _poss_turns = (boards == 0) & binary_dilation(boards == -1, np.array([[[1,1,1],[1,0,1],[1,1,1]]]))\n", + " _poss_turns = (boards == 0) & binary_dilation(\n", + " boards == -1, np.array([[[1, 1, 1], [1, 0, 1], [1, 1, 1]]])\n", + " )\n", " for game in range(boards.shape[0]):\n", - " for idx in range(8):\n", - " for idy in range(8):\n", + " for idx in range(BOARD_SIZE):\n", + " for idy in range(BOARD_SIZE):\n", "\n", " position = idx, idy\n", " if _poss_turns[game, idx, idy]:\n", - " _poss_turns[game, idx, idy] = any(recursive_steps(boards[game, :, :], direction, position) for direction in DIRECTIONS)\n", + " _poss_turns[game, idx, idy] = any(\n", + " recursive_steps(boards[game, :, :], direction, position)\n", + " for direction in DIRECTIONS\n", + " )\n", " return _poss_turns\n", "\n", + "\n", "%timeit get_possible_turns(get_new_games(10))\n", "%timeit get_possible_turns(get_new_games(100))\n", "get_possible_turns(get_new_games(3))[:1]" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, + "metadata": {}, "outputs": [ { "data": { - "text/plain": "(array([2, 2, 2]), array([2, 2, 2]))" + "text/plain": [ + "(array([2, 2, 2]), array([2, 2, 2]))" + ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def evaluate_boards(array: np.ndarray):\n", - " return np.sum(array == 1, axis=(1,2)), np.sum(array == -1, axis=(1,2))\n", - "evaluate_boards(get_new_games(3))" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": 10, - "outputs": [], - "source": [ - "def move_possible(board:np.ndarray, move: np.ndarray) -> bool:\n", - " if np.all(move == -1):\n", - " return np.all(get_possible_turns(board))\n", - " return any(recursive_steps(board[:, :], direction, move) for direction in DIRECTIONS)\n", + " return np.sum(array == 1, axis=(1, 2)), np.sum(array == -1, axis=(1, 2))\n", "\n", - "def moves_possible(boards:np.ndarray, moves: np.ndarray) -> np.ndarray:\n", - " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", - " for game in range(boards.shape[0]):\n", - " if np.all(moves[game] == -1):\n", - " arr_moves_possible[game, :, :] = np.all(get_possible_turns(boards[game, : , :]))\n", - " arr_moves_possible[game, :, :] = any(recursive_steps(boards[game, :, :], direction, moves[game]) for direction in DIRECTIONS)\n", - " return arr_moves_possible" - ], - "metadata": { - "collapsed": false - } + "\n", + "evaluate_boards(get_new_games(3))" + ] }, { "cell_type": "code", "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def move_possible(board: np.ndarray, move: np.ndarray) -> bool:\n", + " if np.all(move == -1):\n", + " return np.all(get_possible_turns(board))\n", + " return any(\n", + " recursive_steps(board[:, :], direction, move) for direction in DIRECTIONS\n", + " )\n", + "\n", + "\n", + "def moves_possible(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", + " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", + " for game in range(boards.shape[0]):\n", + " if np.all(moves[game] == -1):\n", + " arr_moves_possible[game, :, :] = np.all(\n", + " get_possible_turns(boards[game, :, :])\n", + " )\n", + " arr_moves_possible[game, :, :] = any(\n", + " recursive_steps(boards[game, :, :], direction, moves[game])\n", + " for direction in DIRECTIONS\n", + " )\n", + " return arr_moves_possible" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, "outputs": [ { "data": { - "text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 0, 0, 0, 0],\n [ 0, 0, 0, -1, -1, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])" + "text/plain": [ + "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 0, 0, 0, 0],\n", + " [ 0, 0, 0, -1, -1, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0]])" + ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -218,8 +335,9 @@ "\n", "\n", "def to_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", - "\n", - " def _do_directional_move(board: np.ndarray, rec_move: np.ndarray, rev_direction, step_one=True) -> bool:\n", + " def _do_directional_move(\n", + " board: np.ndarray, rec_move: np.ndarray, rev_direction, step_one=True\n", + " ) -> bool:\n", " rec_position = rec_move + rev_direction\n", " if np.any((rec_position >= 8) | (rec_position < 0)):\n", " return False\n", @@ -247,54 +365,385 @@ "\n", " for game in range(boards.shape[0]):\n", " _do_move(boards[game], moves[game])\n", + "\n", + "\n", "boards = get_new_games(10)\n", - "to_moves(boards, np.array([[2,3]] * 10))\n", + "to_moves(boards, np.array([[2, 3]] * 10))\n", "boards = boards * -1\n", "boards[0]" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": 12, - "outputs": [], - "source": [ - "to_moves(get_new_games(10), np.array([[2,3]] * 10))" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "to_moves(get_new_games(10), np.array([[2, 3]] * 10))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { - "text/plain": "array([[4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3],\n [4, 3]])" + "text/plain": [ + "array([[4, 3],\n", + " [4, 3],\n", + " [4, 3],\n", + " [4, 3],\n", + " [4, 3],\n", + " [4, 3],\n", + " [4, 3],\n", + " [4, 3],\n", + " [4, 3],\n", + " [4, 3]])" + ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "np.array([[4,3]] * 10)" - ], - "metadata": { - "collapsed": false - } + "np.array([[4, 3]] * 10)" + ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, + "metadata": {}, "outputs": [], - "source": [], - "metadata": { - "collapsed": false - } + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def create_test_game():\n", + " test_array = []\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 0, 2, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 0, 0, 0],\n", + " [0, 0, 0, 2, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 0, 0, 0],\n", + " [0, 0, 1, 1, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 0, 0, 0],\n", + " [0, 0, 2, 1, 1, 0, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 2, 1, 1, 0, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 2, 1, 1, 0, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 1, 1, 0, 0],\n", + " [0, 0, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 0, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 0, 2, 2, 1, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 1, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 0, 2, 2, 1, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 1, 1, 1, 1, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [2, 2, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 1, 1, 1, 0],\n", + " [2, 2, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 1, 1, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 2, 0, 0],\n", + " [0, 0, 0, 2, 2, 1, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 2, 1, 0, 0],\n", + " [0, 0, 0, 2, 2, 1, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 2, 2, 2, 0],\n", + " [0, 0, 0, 2, 2, 2, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 1, 2, 2, 0],\n", + " [0, 0, 0, 2, 2, 1, 1, 0],\n", + " [2, 2, 2, 1, 1, 1, 1, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 1, 2, 2, 0],\n", + " [0, 0, 0, 2, 2, 1, 2, 0],\n", + " [2, 2, 2, 2, 2, 2, 2, 2],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array.append(\n", + " np.array(\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 1, 2, 2, 0],\n", + " [0, 0, 0, 2, 1, 1, 2, 0],\n", + " [2, 2, 2, 2, 1, 2, 2, 2],\n", + " [0, 2, 0, 1, 1, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " )\n", + " )\n", + " test_array = np.array(test_array)\n", + " test_array[test_array == 2] = -1\n", + " assert np.all(np.diff(np.count_nonzero(create_test_game(), axis=(1, 2))) == 1)\n", + " return test_array\n", + "\n", + "\n", + "plot_othello_boards(create_test_game()[-3:])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "np.diff(create_test_game(), axis=0).shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { -- 2.49.0 From 545f37af0769dacb26280ab1d4b1404b79d55bfe Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Mon, 6 Feb 2023 03:00:13 +0100 Subject: [PATCH 06/31] Game engine could now work. --- main.ipynb | 1367 ++++++++++++++------ poetry.lock | 3294 +++++++++++++++++++++++++++--------------------- pyproject.toml | 5 +- 3 files changed, 2849 insertions(+), 1817 deletions(-) diff --git a/main.ipynb b/main.ipynb index c1abc67..629e1fc 100644 --- a/main.ipynb +++ b/main.ipynb @@ -1,5 +1,14 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Deep Reversi AI\n", + "\n", + "The game is not" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -9,6 +18,13 @@ "%load_ext blackcellmagic" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Imports" + ] + }, { "cell_type": "code", "execution_count": 2, @@ -16,10 +32,19 @@ "outputs": [], "source": [ "import numpy as np\n", + "import abc\n", "from typing import Final\n", "from scipy.ndimage import binary_dilation\n", "from tqdm.auto import tqdm\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "from abc import ABC" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Constants" ] }, { @@ -63,6 +88,13 @@ "DIRECTIONS" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating new boards" + ] + }, { "cell_type": "code", "execution_count": 5, @@ -134,7 +166,18 @@ "cell_type": "code", "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def plot_othello_board(board, ax=None):\n", " size = 3\n", @@ -164,7 +207,10 @@ " ax.set_yticklabels(list(\"12345678\"))\n", " if plot_all:\n", " plt.tight_layout()\n", - " plt.show()" + " plt.show()\n", + "\n", + "\n", + "plot_othello_board(get_new_games(1)[0])" ] }, { @@ -190,16 +236,33 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "metadata": { + "tags": [] + }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "8.49 ms ± 143 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "80.9 ms ± 537 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" - ] - }, + "data": { + "text/plain": [ + "array([[[1, 1, 1],\n", + " [1, 0, 1],\n", + " [1, 1, 1]]])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "SURROUNDING: Final = np.array([[[1, 1, 1], [1, 0, 1], [1, 1, 1]]])\n", + "SURROUNDING" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ { "data": { "text/plain": [ @@ -213,13 +276,13 @@ " [False, False, False, False, False, False, False, False]]])" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def recursive_steps(_array, rec_direction, rec_position, step_one=True):\n", + "def recursive_steps(_array, rec_direction, rec_position, step_one=True) -> bool:\n", " rec_position = rec_position + rec_direction\n", " if np.any((rec_position >= BOARD_SIZE) | (rec_position < 0)):\n", " return False\n", @@ -233,9 +296,14 @@ "\n", "\n", "def get_possible_turns(boards: np.ndarray) -> np.ndarray:\n", - " _poss_turns = (boards == 0) & binary_dilation(\n", - " boards == -1, np.array([[[1, 1, 1], [1, 0, 1], [1, 1, 1]]])\n", - " )\n", + " try:\n", + " _poss_turns = boards == 0\n", + " _poss_turns &= binary_dilation(boards == -1, SURROUNDING)\n", + " except RuntimeError as err:\n", + " print(boards)\n", + " print(boards == -1)\n", + " print(\"err\")\n", + " raise err\n", " for game in range(boards.shape[0]):\n", " for idx in range(BOARD_SIZE):\n", " for idy in range(BOARD_SIZE):\n", @@ -249,14 +317,14 @@ " return _poss_turns\n", "\n", "\n", - "%timeit get_possible_turns(get_new_games(10))\n", - "%timeit get_possible_turns(get_new_games(100))\n", + "# %timeit get_possible_turns(get_new_games(10))\n", + "# %timeit get_possible_turns(get_new_games(100))\n", "get_possible_turns(get_new_games(3))[:1]" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -265,7 +333,7 @@ "(array([2, 2, 2]), array([2, 2, 2]))" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -280,35 +348,84 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "def move_possible(board: np.ndarray, move: np.ndarray) -> bool:\n", " if np.all(move == -1):\n", - " return np.all(get_possible_turns(board))\n", + " return not np.any(get_possible_turns(np.reshape(board, (1, 8, 8))))\n", " return any(\n", " recursive_steps(board[:, :], direction, move) for direction in DIRECTIONS\n", " )\n", "\n", "\n", - "def moves_possible(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", - " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", - " for game in range(boards.shape[0]):\n", - " if np.all(moves[game] == -1):\n", - " arr_moves_possible[game, :, :] = np.all(\n", - " get_possible_turns(boards[game, :, :])\n", - " )\n", - " arr_moves_possible[game, :, :] = any(\n", - " recursive_steps(boards[game, :, :], direction, moves[game])\n", - " for direction in DIRECTIONS\n", - " )\n", - " return arr_moves_possible" + "assert move_possible(get_new_games(1)[0], np.array([2, 3])) is True\n", + "assert move_possible(get_new_games(1)[0], np.array([3, 2])) is True\n", + "assert move_possible(get_new_games(1)[0], np.array([2, 2])) is False\n", + "assert move_possible(np.zeros((8, 8)), np.array([3, 2])) is False\n", + "assert move_possible(np.ones((8, 8)) * 1, np.array([-1, -1])) is True\n", + "assert move_possible(np.ones((8, 8)) * -1, np.array([-1, -1])) is True\n", + "assert move_possible(np.ones((8, 8)) * 0, np.array([-1, -1])) is True" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def moves_possible(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", + " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", + " for game in range(boards.shape[0]):\n", + " if np.all(moves[game] == -1):\n", + " try:\n", + " arr_moves_possible[game] = not np.any(\n", + " get_possible_turns(np.reshape(boards[game], (1, 8, 8)))\n", + " )\n", + " except Exception as err:\n", + " print(test)\n", + " raise err\n", + " else:\n", + " arr_moves_possible[game] = any(\n", + " recursive_steps(boards[game, :, :], direction, moves[game])\n", + " for direction in DIRECTIONS\n", + " )\n", + " return arr_moves_possible\n", + "\n", + "\n", + "np.testing.assert_array_equal(\n", + " moves_possible(np.ones((3, 8, 8)) * 1, np.array([[-1, -1]] * 3)),\n", + " np.array([True] * 3),\n", + ")\n", + "\n", + "np.testing.assert_array_equal(\n", + " moves_possible(get_new_games(3), np.array([[2, 3], [3, 2], [3, 2]])),\n", + " np.array([True] * 3),\n", + ")\n", + "np.testing.assert_array_equal(\n", + " moves_possible(get_new_games(3), np.array([[2, 2], [1, 1], [0, 0]])),\n", + " np.array([False] * 3),\n", + ")\n", + "np.testing.assert_array_equal(\n", + " moves_possible(np.ones((3, 8, 8)) * -1, np.array([[-1, -1]] * 3)),\n", + " np.array([True] * 3),\n", + ")\n", + "np.testing.assert_array_equal(\n", + " moves_possible(np.zeros((3, 8, 8)), np.array([[-1, -1]] * 3)), np.array([True] * 3)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -316,15 +433,15 @@ "text/plain": [ "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, -1, 0, 0, 0, 0],\n", - " [ 0, 0, 0, -1, -1, 0, 0, 0],\n", - " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 1, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", " [ 0, 0, 0, 0, 0, 0, 0, 0]])" ] }, - "execution_count": 12, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -334,7 +451,7 @@ " pass\n", "\n", "\n", - "def to_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", + "def do_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", " def _do_directional_move(\n", " board: np.ndarray, rec_move: np.ndarray, rev_direction, step_one=True\n", " ) -> bool:\n", @@ -353,6 +470,8 @@ " return False\n", "\n", " def _do_move(_board: np.ndarray, move: np.ndarray) -> None:\n", + " if np.all(move == -1):\n", + " return\n", " if _board[tuple(move.tolist())] != 0:\n", " raise InvalidTurn\n", " action = False\n", @@ -363,52 +482,632 @@ " raise InvalidTurn()\n", " _board[tuple(move.tolist())] = 1\n", "\n", + " boards = boards.copy()\n", " for game in range(boards.shape[0]):\n", " _do_move(boards[game], moves[game])\n", + " return boards\n", "\n", "\n", "boards = get_new_games(10)\n", - "to_moves(boards, np.array([[2, 3]] * 10))\n", - "boards = boards * -1\n", - "boards[0]" + "do_moves(boards, np.array([[2, 3]] * 10))[0]" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ - "to_moves(get_new_games(10), np.array([[2, 3]] * 10))" + "class GamePolicy(ABC):\n", + "\n", + " IMPOSSIBLE: np.ndarray = np.array([-1, -1], dtype=int)\n", + "\n", + " @abc.abstractproperty\n", + " def policy_name(self) -> str:\n", + " raise NotImplementedError()\n", + "\n", + " @abc.abstractmethod\n", + " def internal_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " raise NotImplementedError()\n", + "\n", + " def get_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " policies = self.internal_policy(boards)\n", + " possible_turns = get_possible_turns(boards)\n", + " poss_turns_debug = possible_turns[0]\n", + " policies[possible_turns == False] = -1.0\n", + " max_indices = [\n", + " np.unravel_index(policy.argmax(), policy.shape) for policy in policies\n", + " ]\n", + " policy_vector = np.array(max_indices)\n", + " # todo check if no turn is possible and return [-1, -1]\n", + " a1 = np.all(policy_vector[:] == 0, 1)\n", + " a2 = policies[:, 0, 0] == -1.0\n", + " no_turn_possible = np.all(policy_vector == 0, 1) & (policies[:, 0, 0] == -1.0)\n", + " if np.any(no_turn_possible):\n", + " cases = np.where(no_turn_possible)\n", + " print(cases)\n", + " print(\"Test\")\n", + "\n", + " policy_vector[no_turn_possible] = GamePolicy.IMPOSSIBLE\n", + " return policy_vector" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "class RandomPolicy(GamePolicy):\n", + " @property\n", + " def policy_name(self) -> str:\n", + " return \"random\"\n", + "\n", + " def internal_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " random_values = np.random.rand(*boards.shape)\n", + " return random_values\n", + " # return np.argmax(random_values, (1, 2))\n", + "\n", + "\n", + "rndpolicy = RandomPolicy()\n", + "assert rndpolicy.policy_name == \"random\"" + ] + }, + { + "cell_type": "code", + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[4, 3],\n", - " [4, 3],\n", - " [4, 3],\n", - " [4, 3],\n", - " [4, 3],\n", - " [4, 3],\n", - " [4, 3],\n", - " [4, 3],\n", - " [4, 3],\n", - " [4, 3]])" + "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0]])" ] }, - "execution_count": 14, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "np.array([[4, 3]] * 10)" + "def single_turn(current_boards: np, policy: GamePolicy) -> np.ndarray:\n", + " policy_results = policy.get_policy(current_boards)\n", + " poss = moves_possible(current_boards, policy_results)\n", + " if not np.all(poss):\n", + " false_values = np.where(poss == False)\n", + " bad_boards = current_boards[false_values]\n", + " bad_policy = policy_results[false_values]\n", + " print(\"test\")\n", + "\n", + " try:\n", + " assert np.all(moves_possible(current_boards, policy_results)), (\n", + " current_boards[(moves_possible(current_boards, policy_results) == False)],\n", + " policy_results[(moves_possible(current_boards, policy_results) == False)],\n", + " np.where(moves_possible(current_boards, policy_results) == False),\n", + " )\n", + " except AssertionError as err:\n", + " raise err\n", + "\n", + " return do_moves(current_boards, policy_results)\n", + "\n", + "\n", + "single_turn(get_new_games(10), RandomPolicy())[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(array([1], dtype=int64),)\n", + "Test\n", + "(array([1], dtype=int64),)\n", + "Test\n", + "(array([0, 4, 5, 7, 8], dtype=int64),)\n", + "Test\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[[[ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " ...,\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.]],\n", + "\n", + " [[ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 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0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.]],\n", + "\n", + " [[ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " ...,\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.],\n", + " [ 0., 0., 0., ..., 0., 0., 0.]]]])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def simulate_game(\n", + " nr_of_games: int,\n", + " policies: tuple[GamePolicy, GamePolicy],\n", + ") -> np.ndarray:\n", + " history_stack = np.zeros((70, nr_of_games, 8, 8))\n", + " current_boards = get_new_games(nr_of_games)\n", + " index_counter = 0\n", + " for i in range(60):\n", + " policy_index = i % 2\n", + " policy = policies[policy_index]\n", + " if policy_index == 0:\n", + " current_boards = current_boards * -1\n", + " try:\n", + " current_boards = single_turn(current_boards, policy)\n", + " except RuntimeError as err:\n", + " print(\"Err\")\n", + " print(history_stack)\n", + " raise err\n", + " if policy_index == 0:\n", + " current_boards = current_boards * -1\n", + "\n", + " history_stack[index_counter] = current_boards\n", + " index_counter += 1\n", + " return history_stack\n", + "\n", + "\n", + "simulate_game(10, (RandomPolicy(), RandomPolicy()))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 0, -1, 0, 0],\n", + " [ 0, 0, 1, 1, 1, 1, 0, 0],\n", + " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", + " [ 0, 0, -1, -1, -1, 0, 0, 0],\n", + " [ 0, 0, 1, -1, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0]],\n", + "\n", + " [[ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, -1, -1, -1, 0],\n", + " [ 0, 0, 1, 0, -1, 0, 0, 0],\n", + " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 1, -1, -1, 0],\n", + " [ 0, 0, -1, 0, 0, 1, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0]]])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr = np.array(\n", + " [\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, -1, 0, -1, 0, 0],\n", + " [0, 0, 1, 1, 1, 1, 0, 0],\n", + " [0, 0, 0, -1, 1, 0, 0, 0],\n", + " [0, 0, -1, -1, -1, 0, 0, 0],\n", + " [0, 0, 1, -1, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, -1, -1, -1, 0],\n", + " [0, 0, 1, 0, -1, 0, 0, 0],\n", + " [0, 0, 0, 1, -1, 0, 0, 0],\n", + " [0, 0, 0, -1, 1, -1, -1, 0],\n", + " [0, 0, -1, 0, 0, 1, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " ]\n", + ")\n", + "arr" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[False, False, True, True, True, True, True, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, True, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, True, False, False, True, True, False, False],\n", + " [False, False, False, True, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False]],\n", + "\n", + " [[False, False, False, False, True, False, True, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, True, False, True],\n", + " [False, False, True, False, False, False, False, True],\n", + " [False, False, False, True, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False]]])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_possible_turns(arr)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "moves_possible(arr, RandomPolicy().get_policy(arr))" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 4],\n", + " [4, 7]], dtype=int64)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "RandomPolicy().get_policy(arr)" ] }, { @@ -416,7 +1115,251 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "import numpy as np\n", + "\n", + "\n", + "def create_test_game():\n", + " test_array = [\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 0, 2, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 0, 0, 0],\n", + " [0, 0, 0, 2, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 0, 0, 0],\n", + " [0, 0, 1, 1, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 0, 0, 0],\n", + " [0, 0, 2, 1, 1, 0, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 2, 1, 1, 0, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 2, 1, 1, 0, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 1, 1, 0, 0],\n", + " [0, 0, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 0, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 0, 2, 2, 1, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 1, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 0, 2, 2, 1, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [0, 1, 1, 1, 1, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 2, 2, 0, 0],\n", + " [2, 2, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 1, 1, 1, 0],\n", + " [2, 2, 2, 2, 2, 2, 0, 0],\n", + " [0, 2, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 1, 1, 1, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 2, 2, 2, 0, 0],\n", + " [0, 0, 0, 2, 2, 1, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 2, 1, 0, 0],\n", + " [0, 0, 0, 2, 2, 1, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 2, 2, 2, 0],\n", + " [0, 0, 0, 2, 2, 2, 1, 0],\n", + " [2, 2, 2, 1, 2, 2, 0, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 1, 2, 2, 0],\n", + " [0, 0, 0, 2, 2, 1, 1, 0],\n", + " [2, 2, 2, 1, 1, 1, 1, 0],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 1, 2, 2, 0],\n", + " [0, 0, 0, 2, 2, 1, 2, 0],\n", + " [2, 2, 2, 2, 2, 2, 2, 2],\n", + " [0, 2, 0, 1, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 2, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 2, 1, 2, 2, 0],\n", + " [0, 0, 0, 2, 1, 1, 2, 0],\n", + " [2, 2, 2, 2, 1, 2, 2, 2],\n", + " [0, 2, 0, 1, 1, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " [\n", + " [0, 0, 0, 0, 2, 0, 0, 0],\n", + " [0, 0, 2, 2, 0, 2, 0, 0],\n", + " [0, 0, 0, 2, 1, 2, 2, 0],\n", + " [0, 0, 0, 2, 1, 1, 2, 0],\n", + " [2, 2, 2, 2, 1, 2, 2, 2],\n", + " [0, 2, 0, 1, 1, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 2, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ],\n", + " ]\n", + " test_array = np.array(test_array)\n", + "\n", + " # swapp 2 by one. 2 was only there for homogenous formating and easier readability while coading.\n", + " test_array[test_array == 2] = -1\n", + " assert np.all(\n", + " np.count_nonzero(test_array, axis=(1, 2))\n", + " == np.arange(4, 4 + test_array.shape[0])\n", + " )\n", + "\n", + " # validated that only one stone is added per turn\n", + " zero_array = test_array == 0\n", + " diff = zero_array != np.roll(zero_array, 1, axis=0)\n", + " turns = np.where(diff[1:])\n", + " arr = np.array(turns)[0]\n", + " assert len(arr) == len(set(arr))\n", + "\n", + " return test_array" + ] }, { "cell_type": "code", @@ -424,308 +1367,6 @@ "metadata": {}, "outputs": [], "source": [ - "def create_test_game():\n", - " test_array = []\n", - " test_array.append(\n", - " np.array(\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 2, 0, 0, 0],\n", - " [0, 0, 0, 2, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " )\n", - " )\n", - " test_array.append(\n", - " np.array(\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 2, 0, 0, 0],\n", - " [0, 0, 0, 2, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " )\n", - " )\n", - " test_array.append(\n", - " np.array(\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 2, 0, 0, 0],\n", - " [0, 0, 1, 1, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " )\n", - " )\n", - " test_array.append(\n", - " np.array(\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 2, 0, 0, 0],\n", - " [0, 0, 2, 1, 1, 0, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " )\n", - " )\n", - " test_array.append(\n", - " np.array(\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 2, 0, 0, 0],\n", - " [0, 0, 2, 1, 1, 0, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 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0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " )\n", - " )\n", - " test_array.append(\n", - " np.array(\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 1, 0, 0],\n", - " [0, 0, 0, 2, 1, 2, 2, 0],\n", - " [0, 0, 0, 2, 2, 1, 2, 0],\n", - " [2, 2, 2, 2, 2, 2, 2, 2],\n", - " [0, 2, 0, 1, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " )\n", - " )\n", - " test_array.append(\n", - " np.array(\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 1, 0, 0],\n", - " [0, 0, 0, 2, 1, 2, 2, 0],\n", - " [0, 0, 0, 2, 1, 1, 2, 0],\n", - " [2, 2, 2, 2, 1, 2, 2, 2],\n", - " [0, 2, 0, 1, 1, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " )\n", - " )\n", - " test_array = np.array(test_array)\n", - " test_array[test_array == 2] = -1\n", - " assert np.all(np.diff(np.count_nonzero(create_test_game(), axis=(1, 2))) == 1)\n", - " return test_array\n", - 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[package.extras] @@ -1221,24 +171,24 @@ python2 = ["typed-ast (>=1.4.3)"] uvloop = ["uvloop (>=0.15.2)"] [[package]] -category = "dev" -description = "IPython magic command to format python code in cell using black." name = "blackcellmagic" +version = "0.0.3" +description = "IPython magic command to format python code in cell using black." +category = "dev" optional = false python-versions = ">=3.6.2,<4.0.0" -version = "0.0.3" [package.dependencies] black = ">=21.9b0,<22.0" jupyter = ">=1.0.0,<2.0.0" [[package]] -category = "main" -description = "An easy safelist-based HTML-sanitizing tool." name = "bleach" +version = "6.0.0" +description = "An easy safelist-based HTML-sanitizing tool." +category = "main" optional = false python-versions = ">=3.7" -version = "6.0.0" [package.dependencies] six = ">=1.9.0" @@ -1248,50 +198,66 @@ webencodings = "*" css = ["tinycss2 (>=1.1.0,<1.2)"] [[package]] +name = "certifi" +version = "2022.12.7" +description = "Python package for providing Mozilla's CA Bundle." category = "main" -description = "Foreign Function Interface for Python calling C code." +optional = false +python-versions = ">=3.6" + +[[package]] name = "cffi" +version = "1.15.1" +description = "Foreign Function Interface for Python calling C code." +category = "main" optional = false python-versions = "*" -version = "1.15.1" [package.dependencies] pycparser = "*" [[package]] -category = "dev" -description = "Validate configuration and produce human readable error messages." name = "cfgv" +version = "3.3.1" +description = "Validate configuration and produce human readable error messages." +category = "dev" optional = false python-versions = ">=3.6.1" -version = "3.3.1" [[package]] -category = "dev" -description = "Composable command line interface toolkit" +name = "charset-normalizer" +version = "3.0.1" +description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." +category = "main" +optional = false +python-versions = "*" + +[[package]] name = "click" +version = "8.1.3" +description = "Composable command line interface toolkit" +category = "dev" optional = false python-versions = ">=3.7" -version = "8.1.3" [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} [[package]] -category = "main" -description = "Cross-platform colored terminal text." name = "colorama" +version = "0.4.6" +description = "Cross-platform colored terminal text." +category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" -version = "0.4.6" [[package]] -category = "main" -description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." name = "comm" +version = "0.1.2" +description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." +category = "main" optional = false python-versions = ">=3.6" -version = "0.1.2" [package.dependencies] traitlets = ">=5.3" @@ -1300,12 +266,12 @@ traitlets = ">=5.3" test = ["pytest"] [[package]] -category = "main" -description = "Python library for calculating contours of 2D quadrilateral grids" name = "contourpy" +version = "1.0.7" +description = "Python library for calculating contours of 2D quadrilateral grids" +category = "main" optional = false python-versions = ">=3.8" -version = "1.0.7" [package.dependencies] numpy = ">=1.16" @@ -1318,97 +284,97 @@ test = ["Pillow", "matplotlib", "pytest"] test-no-images = ["pytest"] [[package]] -category = "main" -description = "Composable style cycles" name = "cycler" +version = "0.11.0" +description = "Composable style cycles" +category = "main" optional = false python-versions = ">=3.6" -version = "0.11.0" [[package]] -category = "main" -description = "An implementation of the Debug Adapter Protocol for Python" name = "debugpy" +version = "1.6.6" +description = "An implementation of the Debug Adapter Protocol for Python" +category = "main" optional = false python-versions = ">=3.7" -version = "1.6.6" [[package]] -category = "main" -description = "Decorators for Humans" name = "decorator" +version = "5.1.1" +description = "Decorators for Humans" +category = "main" optional = false python-versions = ">=3.5" -version = "5.1.1" [[package]] -category = "main" -description = "XML bomb protection for Python stdlib modules" name = "defusedxml" +version = "0.7.1" +description = "XML bomb protection for Python stdlib modules" +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" -version = "0.7.1" [[package]] -category = "dev" -description = "Distribution utilities" name = "distlib" +version = "0.3.6" +description = "Distribution utilities" +category = "dev" optional = false python-versions = "*" -version = "0.3.6" [[package]] -category = "main" -description = "Backport of PEP 654 (exception groups)" name = "exceptiongroup" +version = "1.1.0" +description = "Backport of PEP 654 (exception groups)" +category = "main" optional = false python-versions = ">=3.7" -version = "1.1.0" [package.extras] test = ["pytest (>=6)"] [[package]] -category = "main" -description = "Get the currently executing AST node of a frame, and other information" name = "executing" +version = "1.2.0" +description = "Get the currently executing AST node of a frame, and other information" +category = "main" optional = false python-versions = "*" -version = "1.2.0" [package.extras] tests = ["asttokens", "littleutils", "pytest", "rich"] [[package]] -category = "main" -description = "Fastest Python implementation of JSON schema" name = "fastjsonschema" +version = "2.16.2" +description = "Fastest Python implementation of JSON schema" +category = "main" optional = false python-versions = "*" -version = "2.16.2" [package.extras] devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"] [[package]] -category = "dev" -description = "A platform independent file lock." name = "filelock" +version = "3.9.0" +description = "A platform independent file lock." +category = "dev" optional = false python-versions = ">=3.7" -version = "3.9.0" [package.extras] docs = ["furo (>=2022.12.7)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] testing = ["covdefaults (>=2.2.2)", "coverage (>=7.0.1)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"] [[package]] -category = "main" -description = "Tools to manipulate font files" name = "fonttools" +version = "4.38.0" +description = "Tools to manipulate font files" +category = "main" optional = false python-versions = ">=3.7" -version = "4.38.0" [package.extras] all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=14.0.0)", "xattr", "zopfli (>=0.1.4)"] @@ -1425,54 +391,55 @@ unicode = ["unicodedata2 (>=14.0.0)"] woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"] [[package]] -category = "main" -description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers" name = "fqdn" +version = "1.5.1" +description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers" +category = "main" optional = false python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" -version = "1.5.1" [[package]] -category = "dev" -description = "File identification library for Python" name = "identify" +version = "2.5.17" +description = "File identification library for Python" +category = "dev" optional = false python-versions = ">=3.7" -version = "2.5.17" [package.extras] license = ["ukkonen"] [[package]] -category = "main" -description = "Internationalized Domain Names in Applications (IDNA)" name = "idna" +version = "3.4" +description = "Internationalized Domain Names in Applications (IDNA)" +category = "main" optional = false python-versions = ">=3.5" -version = "3.4" [[package]] -category = "main" -description = "brain-dead simple config-ini parsing" name = "iniconfig" +version = "2.0.0" +description = "brain-dead simple config-ini parsing" +category = "main" optional = false python-versions = ">=3.7" -version = "2.0.0" [[package]] -category = "main" -description = "IPython Kernel for Jupyter" name = "ipykernel" +version = "6.21.1" +description = "IPython Kernel for Jupyter" +category = "main" optional = false python-versions = ">=3.8" -version = "6.20.2" [package.dependencies] appnope = {version = "*", markers = "platform_system == \"Darwin\""} comm = ">=0.1.1" -debugpy = ">=1.0" +debugpy = ">=1.6.5" ipython = ">=7.23.1" jupyter-client = ">=6.1.12" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" matplotlib-inline = ">=0.1" nest-asyncio = "*" packaging = "*" @@ -1489,12 +456,12 @@ pyside6 = ["pyside6"] test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"] [[package]] -category = "main" -description = "Unit tests in IPython notebooks" name = "ipytest" +version = "0.13.0" +description = "Unit tests in IPython notebooks" +category = "main" optional = false python-versions = ">=3.6" -version = "0.13.0" [package.dependencies] ipython = "*" @@ -1502,12 +469,12 @@ packaging = "*" pytest = ">=5.4" [[package]] -category = "main" -description = "IPython: Productive Interactive Computing" name = "ipython" +version = "8.9.0" +description = "IPython: Productive Interactive Computing" +category = "main" optional = false python-versions = ">=3.8" -version = "8.8.0" [package.dependencies] appnope = {version = "*", markers = "sys_platform == \"darwin\""} @@ -1518,7 +485,7 @@ jedi = ">=0.16" matplotlib-inline = "*" pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""} pickleshare = "*" -prompt-toolkit = ">=3.0.11,<3.1.0" +prompt-toolkit = ">=3.0.30,<3.1.0" pygments = ">=2.4.0" stack-data = "*" traitlets = ">=5" @@ -1537,20 +504,20 @@ test = ["pytest (<7.1)", "pytest-asyncio", "testpath"] test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.20)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"] [[package]] -category = "main" -description = "Vestigial utilities from IPython" name = "ipython-genutils" +version = "0.2.0" +description = "Vestigial utilities from IPython" +category = "main" optional = false python-versions = "*" -version = "0.2.0" [[package]] -category = "main" -description = "Jupyter interactive widgets" name = "ipywidgets" +version = "8.0.4" +description = "Jupyter interactive widgets" +category = "main" optional = false python-versions = ">=3.7" -version = "8.0.4" [package.dependencies] ipykernel = ">=4.5.1" @@ -1563,23 +530,23 @@ widgetsnbextension = ">=4.0,<5.0" test = ["jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"] [[package]] -category = "main" -description = "Operations with ISO 8601 durations" name = "isoduration" +version = "20.11.0" +description = "Operations with ISO 8601 durations" +category = "main" optional = false python-versions = ">=3.7" -version = "20.11.0" [package.dependencies] arrow = ">=0.15.0" [[package]] -category = "main" -description = "An autocompletion tool for Python that can be used for text editors." name = "jedi" +version = "0.18.2" +description = "An autocompletion tool for Python that can be used for text editors." +category = "main" optional = false python-versions = ">=3.6" -version = "0.18.2" [package.dependencies] parso = ">=0.8.0,<0.9.0" @@ -1590,12 +557,12 @@ qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"] [[package]] -category = "main" -description = "A very fast and expressive template engine." name = "jinja2" +version = "3.1.2" +description = "A very fast and expressive template engine." +category = "main" optional = false python-versions = ">=3.7" -version = "3.1.2" [package.dependencies] MarkupSafe = ">=2.0" @@ -1604,20 +571,31 @@ MarkupSafe = ">=2.0" i18n = ["Babel (>=2.7)"] [[package]] +name = "json5" +version = "0.9.11" +description = "A Python implementation of the JSON5 data format." category = "main" -description = "Identify specific nodes in a JSON document (RFC 6901)" -name = "jsonpointer" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -version = "2.3" +python-versions = "*" + +[package.extras] +dev = ["hypothesis"] [[package]] +name = "jsonpointer" +version = "2.3" +description = "Identify specific nodes in a JSON document (RFC 6901)" category = "main" -description = "An implementation of JSON Schema validation for Python" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" + +[[package]] name = "jsonschema" +version = "4.17.3" +description = "An implementation of JSON Schema validation for Python" +category = "main" optional = false python-versions = ">=3.7" -version = "4.17.3" [package.dependencies] attrs = ">=17.4.0" @@ -1636,12 +614,12 @@ format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validat format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"] [[package]] -category = "main" -description = "Jupyter metapackage. Install all the Jupyter components in one go." name = "jupyter" +version = "1.0.0" +description = "Jupyter metapackage. Install all the Jupyter components in one go." +category = "main" optional = false python-versions = "*" -version = "1.0.0" [package.dependencies] ipykernel = "*" @@ -1652,12 +630,12 @@ notebook = "*" qtconsole = "*" [[package]] -category = "main" -description = "Jupyter protocol implementation and client libraries" name = "jupyter-client" +version = "8.0.2" +description = "Jupyter protocol implementation and client libraries" +category = "main" optional = false python-versions = ">=3.8" -version = "8.0.1" [package.dependencies] jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" @@ -1671,12 +649,12 @@ docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphi test = ["codecov", "coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"] [[package]] -category = "main" -description = "Jupyter terminal console" name = "jupyter-console" +version = "6.4.4" +description = "Jupyter terminal console" +category = "main" optional = false python-versions = ">=3.7" -version = "6.4.4" [package.dependencies] ipykernel = "*" @@ -1689,12 +667,12 @@ pygments = "*" test = ["pexpect"] [[package]] -category = "main" -description = "Jupyter core package. A base package on which Jupyter projects rely." name = "jupyter-core" +version = "5.2.0" +description = "Jupyter core package. A base package on which Jupyter projects rely." +category = "main" optional = false python-versions = ">=3.8" -version = "5.1.5" [package.dependencies] platformdirs = ">=2.5" @@ -1706,36 +684,33 @@ docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", " test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] [[package]] -category = "main" -description = "Jupyter Event System library" name = "jupyter-events" +version = "0.5.0" +description = "Jupyter Event System library" +category = "main" optional = false python-versions = ">=3.7" -version = "0.6.3" [package.dependencies] -jsonschema = {version = ">=3.2.0", extras = ["format-nongpl"]} -python-json-logger = ">=2.0.4" -pyyaml = ">=5.3" -rfc3339-validator = "*" -rfc3986-validator = ">=0.1.1" -traitlets = ">=5.3" +jsonschema = {version = ">=4.3.0", extras = ["format-nongpl"]} +python-json-logger = "*" +pyyaml = "*" +traitlets = "*" [package.extras] cli = ["click", "rich"] -docs = ["jupyterlite-sphinx", "myst-parser", "pydata-sphinx-theme", "sphinxcontrib-spelling"] -test = ["click", "coverage", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "pytest-cov", "rich"] +test = ["click", "coverage", "pre-commit", "pytest (>=6.1.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "pytest-cov", "rich"] [[package]] -category = "main" -description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." name = "jupyter-server" +version = "2.2.1" +description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." +category = "main" optional = false python-versions = ">=3.8" -version = "2.1.0" [package.dependencies] -anyio = ">=3.1.0,<4" +anyio = ">=3.1.0" argon2-cffi = "*" jinja2 = "*" jupyter-client = ">=7.4.4" @@ -1759,12 +734,28 @@ docs = ["docutils (<0.20)", "ipykernel", "jinja2", "jupyter-client", "jupyter-se test = ["ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.4)", "pytest-timeout", "requests"] [[package]] +name = "jupyter-server-fileid" +version = "0.6.0" +description = "" category = "main" -description = "A Jupyter Server Extension Providing Terminals." +optional = false +python-versions = ">=3.7" + +[package.dependencies] +jupyter-events = ">=0.5.0,<0.6.0" +jupyter-server = ">=1.15,<3" + +[package.extras] +cli = ["click"] +test = ["jupyter-server[test] (>=1.15,<3)", "pytest", "pytest-cov"] + +[[package]] name = "jupyter-server-terminals" +version = "0.4.4" +description = "A Jupyter Server Extension Providing Terminals." +category = "main" optional = false python-versions = ">=3.8" -version = "0.4.4" [package.dependencies] pywinpty = {version = ">=2.0.3", markers = "os_name == \"nt\""} @@ -1775,44 +766,121 @@ docs = ["jinja2", "jupyter-server", "mistune (<3.0)", "myst-parser", "nbformat", test = ["coverage", "jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-cov", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"] [[package]] +name = "jupyter-server-ydoc" +version = "0.6.1" +description = "A Jupyter Server Extension Providing Y Documents." category = "main" -description = "Pygments theme using JupyterLab CSS variables" -name = "jupyterlab-pygments" optional = false python-versions = ">=3.7" + +[package.dependencies] +jupyter-server-fileid = ">=0.6.0,<1" +jupyter-ydoc = ">=0.2.0,<0.4.0" +ypy-websocket = ">=0.8.2,<0.9.0" + +[package.extras] +test = ["coverage", "jupyter-server[test] (>=2.0.0a0)", "pytest (>=7.0)", "pytest-cov", "pytest-timeout", "pytest-tornasync"] + +[[package]] +name = "jupyter-ydoc" version = "0.2.2" +description = "Document structures for collaborative editing using Ypy" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +y-py = ">=0.5.3,<0.6.0" + +[package.extras] +test = ["pre-commit", "pytest", "pytest-asyncio", "websockets (>=10.0)", "ypy-websocket (>=0.3.1,<0.4.0)"] [[package]] +name = "jupyterlab" +version = "3.6.1" +description = "JupyterLab computational environment" category = "main" -description = "Jupyter interactive widgets for JupyterLab" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +ipython = "*" +jinja2 = ">=2.1" +jupyter-core = "*" +jupyter-server = ">=1.16.0,<3" +jupyter-server-ydoc = ">=0.6.0,<0.7.0" +jupyter-ydoc = ">=0.2.2,<0.3.0" +jupyterlab-server = ">=2.19,<3.0" +nbclassic = "*" +notebook = "<7" +packaging = "*" +tomli = {version = "*", markers = "python_version < \"3.11\""} +tornado = ">=6.1.0" + +[package.extras] +test = ["check-manifest", "coverage", "jupyterlab-server[test]", "pre-commit", "pytest (>=6.0)", "pytest-check-links (>=0.5)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "requests", "requests-cache", "virtualenv"] + +[[package]] +name = "jupyterlab-pygments" +version = "0.2.2" +description = "Pygments theme using JupyterLab CSS variables" +category = "main" +optional = false +python-versions = ">=3.7" + +[[package]] +name = "jupyterlab-server" +version = "2.19.0" +description = "A set of server components for JupyterLab and JupyterLab like applications." +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +babel = ">=2.10" +jinja2 = ">=3.0.3" +json5 = ">=0.9.0" +jsonschema = ">=4.17.3" +jupyter-server = ">=1.21,<3" +packaging = ">=21.3" +requests = ">=2.28" + +[package.extras] +docs = ["autodoc-traits", "docutils (<0.20)", "jinja2 (<3.2.0)", "mistune (<3)", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinxcontrib-openapi"] +openapi = ["openapi-core (>=0.16.1)", "ruamel-yaml"] +test = ["codecov", "ipykernel", "jupyterlab-server[openapi]", "openapi-spec-validator (>=0.5.1)", "pytest (>=7.0)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"] + +[[package]] name = "jupyterlab-widgets" -optional = false -python-versions = ">=3.7" version = "3.0.5" +description = "Jupyter interactive widgets for JupyterLab" +category = "main" +optional = false +python-versions = ">=3.7" [[package]] -category = "main" -description = "A fast implementation of the Cassowary constraint solver" name = "kiwisolver" -optional = false -python-versions = ">=3.7" version = "1.4.4" - -[[package]] +description = "A fast implementation of the Cassowary constraint solver" category = "main" -description = "Safely add untrusted strings to HTML/XML markup." -name = "markupsafe" optional = false python-versions = ">=3.7" -version = "2.1.2" [[package]] +name = "markupsafe" +version = "2.1.2" +description = "Safely add untrusted strings to HTML/XML markup." category = "main" -description = "Python plotting package" +optional = false +python-versions = ">=3.7" + +[[package]] name = "matplotlib" +version = "3.6.3" +description = "Python plotting package" +category = "main" optional = false python-versions = ">=3.8" -version = "3.6.3" [package.dependencies] contourpy = ">=1.0.1" @@ -1827,42 +895,41 @@ python-dateutil = ">=2.7" setuptools_scm = ">=7" [[package]] -category = "main" -description = "Inline Matplotlib backend for Jupyter" name = "matplotlib-inline" +version = "0.1.6" +description = "Inline Matplotlib backend for Jupyter" +category = "main" optional = false python-versions = ">=3.5" -version = "0.1.6" [package.dependencies] traitlets = "*" [[package]] -category = "main" -description = "A sane Markdown parser with useful plugins and renderers" name = "mistune" -optional = false -python-versions = "*" version = "2.0.4" - -[[package]] -category = "dev" -description = "Experimental type system extensions for programs checked with the mypy typechecker." -name = "mypy-extensions" +description = "A sane Markdown parser with useful plugins and renderers" +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "mypy-extensions" +version = "0.4.3" +description = "Experimental type system extensions for programs checked with the mypy typechecker." +category = "dev" optional = false python-versions = "*" -version = "0.4.3" [[package]] -category = "main" -description = "Jupyter Notebook as a Jupyter Server extension." name = "nbclassic" +version = "0.5.1" +description = "Jupyter Notebook as a Jupyter Server extension." +category = "main" optional = false python-versions = ">=3.7" -version = "0.5.1" [package.dependencies] -Send2Trash = ">=1.8.0" argon2-cffi = "*" ipykernel = "*" ipython-genutils = "*" @@ -1876,6 +943,7 @@ nest-asyncio = ">=1.5" notebook-shim = ">=0.1.0" prometheus-client = "*" pyzmq = ">=17" +Send2Trash = ">=1.8.0" terminado = ">=0.8.3" tornado = ">=6.1" traitlets = ">=4.2.1" @@ -1886,12 +954,12 @@ json-logging = ["json-logging"] test = ["coverage", "nbval", "pytest", "pytest-cov", "pytest-jupyter", "pytest-playwright", "pytest-tornasync", "requests", "requests-unixsocket", "testpath"] [[package]] -category = "main" -description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." name = "nbclient" +version = "0.7.2" +description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." +category = "main" optional = false python-versions = ">=3.7.0" -version = "0.7.2" [package.dependencies] jupyter-client = ">=6.1.12" @@ -1905,12 +973,12 @@ docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphi test = ["ipykernel", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"] [[package]] -category = "main" -description = "Converting Jupyter Notebooks" name = "nbconvert" +version = "7.2.9" +description = "Converting Jupyter Notebooks" +category = "main" optional = false python-versions = ">=3.7" -version = "7.2.9" [package.dependencies] beautifulsoup4 = "*" @@ -1939,12 +1007,12 @@ test = ["ipykernel", "ipywidgets (>=7)", "pre-commit", "pytest", "pytest-depende webpdf = ["pyppeteer (>=1,<1.1)"] [[package]] -category = "main" -description = "The Jupyter Notebook format" name = "nbformat" +version = "5.7.3" +description = "The Jupyter Notebook format" +category = "main" optional = false python-versions = ">=3.7" -version = "5.7.3" [package.dependencies] fastjsonschema = "*" @@ -1957,34 +1025,33 @@ docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-al test = ["pep440", "pre-commit", "pytest", "testpath"] [[package]] -category = "main" -description = "Patch asyncio to allow nested event loops" name = "nest-asyncio" +version = "1.5.6" +description = "Patch asyncio to allow nested event loops" +category = "main" optional = false python-versions = ">=3.5" -version = "1.5.6" [[package]] -category = "dev" -description = "Node.js virtual environment builder" name = "nodeenv" +version = "1.7.0" +description = "Node.js virtual environment builder" +category = "dev" optional = false python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*" -version = "1.7.0" [package.dependencies] setuptools = "*" [[package]] -category = "main" -description = "A web-based notebook environment for interactive computing" name = "notebook" +version = "6.5.2" +description = "A web-based notebook environment for interactive computing" +category = "main" optional = false python-versions = ">=3.7" -version = "6.5.2" [package.dependencies] -Send2Trash = ">=1.8.0" argon2-cffi = "*" ipykernel = "*" ipython-genutils = "*" @@ -1997,6 +1064,7 @@ nbformat = "*" nest-asyncio = ">=1.5" prometheus-client = "*" pyzmq = ">=17" +Send2Trash = ">=1.8.0" terminado = ">=0.8.3" tornado = ">=6.1" traitlets = ">=4.2.1" @@ -2007,12 +1075,12 @@ json-logging = ["json-logging"] test = ["coverage", "nbval", "pytest", "pytest-cov", "requests", "requests-unixsocket", "selenium (==4.1.5)", "testpath"] [[package]] -category = "main" -description = "A shim layer for notebook traits and config" name = "notebook-shim" +version = "0.2.2" +description = "A shim layer for notebook traits and config" +category = "main" optional = false python-versions = ">=3.7" -version = "0.2.2" [package.dependencies] jupyter-server = ">=1.8,<3" @@ -2021,111 +1089,111 @@ jupyter-server = ">=1.8,<3" test = ["pytest", "pytest-console-scripts", "pytest-tornasync"] [[package]] -category = "main" -description = "Fundamental package for array computing in Python" name = "numpy" +version = "1.24.1" +description = "Fundamental package for array computing in Python" +category = "main" optional = false python-versions = ">=3.8" -version = "1.24.1" [[package]] -category = "main" -description = "Core utilities for Python packages" name = "packaging" +version = "23.0" +description = "Core utilities for Python packages" +category = "main" optional = false python-versions = ">=3.7" -version = "23.0" [[package]] -category = "main" -description = "Utilities for writing pandoc filters in python" name = "pandocfilters" +version = "1.5.0" +description = "Utilities for writing pandoc filters in python" +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -version = "1.5.0" [[package]] -category = "main" -description = "A Python Parser" name = "parso" +version = "0.8.3" +description = "A Python Parser" +category = "main" optional = false python-versions = ">=3.6" -version = "0.8.3" [package.extras] qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] testing = ["docopt", "pytest (<6.0.0)"] [[package]] -category = "dev" -description = "Utility library for gitignore style pattern matching of file paths." name = "pathspec" +version = "0.11.0" +description = "Utility library for gitignore style pattern matching of file paths." +category = "dev" optional = false python-versions = ">=3.7" -version = "0.11.0" [[package]] -category = "main" -description = "Pexpect allows easy control of interactive console applications." name = "pexpect" +version = "4.8.0" +description = "Pexpect allows easy control of interactive console applications." +category = "main" optional = false python-versions = "*" -version = "4.8.0" [package.dependencies] ptyprocess = ">=0.5" [[package]] -category = "main" -description = "Tiny 'shelve'-like database with concurrency support" name = "pickleshare" +version = "0.7.5" +description = "Tiny 'shelve'-like database with concurrency support" +category = "main" optional = false python-versions = "*" -version = "0.7.5" [[package]] -category = "main" -description = "Python Imaging Library (Fork)" name = "pillow" +version = "9.4.0" +description = "Python Imaging Library (Fork)" +category = "main" optional = false python-versions = ">=3.7" -version = "9.4.0" [package.extras] docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinxext-opengraph"] tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"] [[package]] -category = "main" -description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." name = "platformdirs" +version = "2.6.2" +description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." +category = "main" optional = false python-versions = ">=3.7" -version = "2.6.2" [package.extras] docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] test = ["appdirs (==1.4.4)", "covdefaults (>=2.2.2)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"] [[package]] -category = "main" -description = "plugin and hook calling mechanisms for python" name = "pluggy" +version = "1.0.0" +description = "plugin and hook calling mechanisms for python" +category = "main" optional = false python-versions = ">=3.6" -version = "1.0.0" [package.extras] dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] [[package]] -category = "dev" -description = "A framework for managing and maintaining multi-language pre-commit hooks." name = "pre-commit" +version = "3.0.3" +description = "A framework for managing and maintaining multi-language pre-commit hooks." +category = "dev" optional = false python-versions = ">=3.8" -version = "3.0.2" [package.dependencies] cfgv = ">=2.0.0" @@ -2135,102 +1203,102 @@ pyyaml = ">=5.1" virtualenv = ">=20.10.0" [[package]] -category = "main" -description = "Python client for the Prometheus monitoring system." name = "prometheus-client" +version = "0.16.0" +description = "Python client for the Prometheus monitoring system." +category = "main" optional = false python-versions = ">=3.6" -version = "0.16.0" [package.extras] twisted = ["twisted"] [[package]] -category = "main" -description = "Library for building powerful interactive command lines in Python" name = "prompt-toolkit" +version = "3.0.36" +description = "Library for building powerful interactive command lines in Python" +category = "main" optional = false python-versions = ">=3.6.2" -version = "3.0.36" [package.dependencies] wcwidth = "*" [[package]] -category = "main" -description = "Cross-platform lib for process and system monitoring in Python." name = "psutil" +version = "5.9.4" +description = "Cross-platform lib for process and system monitoring in Python." +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -version = "5.9.4" [package.extras] test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"] [[package]] -category = "main" -description = "Run a subprocess in a pseudo terminal" name = "ptyprocess" +version = "0.7.0" +description = "Run a subprocess in a pseudo terminal" +category = "main" optional = false python-versions = "*" -version = "0.7.0" [[package]] -category = "main" -description = "Safely evaluate AST nodes without side effects" name = "pure-eval" +version = "0.2.2" +description = "Safely evaluate AST nodes without side effects" +category = "main" optional = false python-versions = "*" -version = "0.2.2" [package.extras] tests = ["pytest"] [[package]] -category = "main" -description = "C parser in Python" name = "pycparser" +version = "2.21" +description = "C parser in Python" +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -version = "2.21" [[package]] -category = "main" -description = "Pygments is a syntax highlighting package written in Python." name = "pygments" +version = "2.14.0" +description = "Pygments is a syntax highlighting package written in Python." +category = "main" optional = false python-versions = ">=3.6" -version = "2.14.0" [package.extras] plugins = ["importlib-metadata"] [[package]] -category = "main" -description = "pyparsing module - Classes and methods to define and execute parsing grammars" name = "pyparsing" +version = "3.0.9" +description = "pyparsing module - Classes and methods to define and execute parsing grammars" +category = "main" optional = false python-versions = ">=3.6.8" -version = "3.0.9" [package.extras] diagrams = ["jinja2", "railroad-diagrams"] [[package]] -category = "main" -description = "Persistent/Functional/Immutable data structures" name = "pyrsistent" +version = "0.19.3" +description = "Persistent/Functional/Immutable data structures" +category = "main" optional = false python-versions = ">=3.7" -version = "0.19.3" [[package]] -category = "main" -description = "pytest: simple powerful testing with Python" name = "pytest" +version = "7.2.1" +description = "pytest: simple powerful testing with Python" +category = "main" optional = false python-versions = ">=3.7" -version = "7.2.1" [package.dependencies] attrs = ">=19.2.0" @@ -2245,66 +1313,74 @@ tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""} testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"] [[package]] -category = "main" -description = "Extensions to the standard Python datetime module" name = "python-dateutil" +version = "2.8.2" +description = "Extensions to the standard Python datetime module" +category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" -version = "2.8.2" [package.dependencies] six = ">=1.5" [[package]] -category = "main" -description = "A python library adding a json log formatter" name = "python-json-logger" +version = "2.0.4" +description = "A python library adding a json log formatter" +category = "main" optional = false python-versions = ">=3.5" -version = "2.0.4" [[package]] +name = "pytz" +version = "2022.7.1" +description = "World timezone definitions, modern and historical" category = "main" -description = "Python for Window Extensions" -name = "pywin32" optional = false python-versions = "*" -version = "305" [[package]] +name = "pywin32" +version = "305" +description = "Python for Window Extensions" category = "main" -description = "Pseudo terminal support for Windows from Python." +optional = false +python-versions = "*" + +[[package]] name = "pywinpty" +version = "2.0.10" +description = "Pseudo terminal support for Windows from Python." +category = "main" optional = false python-versions = ">=3.7" -version = "2.0.10" [[package]] -category = "main" -description = "YAML parser and emitter for Python" name = "pyyaml" +version = "6.0" +description = "YAML parser and emitter for Python" +category = "main" optional = false python-versions = ">=3.6" -version = "6.0" [[package]] -category = "main" -description = "Python bindings for 0MQ" name = "pyzmq" +version = "25.0.0" +description = "Python bindings for 0MQ" +category = "main" optional = false python-versions = ">=3.6" -version = "25.0.0" [package.dependencies] cffi = {version = "*", markers = "implementation_name == \"pypy\""} [[package]] -category = "main" -description = "Jupyter Qt console" name = "qtconsole" +version = "5.4.0" +description = "Jupyter Qt console" +category = "main" optional = false python-versions = ">= 3.7" -version = "5.4.0" [package.dependencies] ipykernel = ">=4.1" @@ -2321,12 +1397,12 @@ doc = ["Sphinx (>=1.3)"] test = ["flaky", "pytest", "pytest-qt"] [[package]] -category = "main" -description = "Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6)." name = "qtpy" +version = "2.3.0" +description = "Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6)." +category = "main" optional = false python-versions = ">=3.7" -version = "2.3.0" [package.dependencies] packaging = "*" @@ -2335,31 +1411,49 @@ packaging = "*" test = ["pytest (>=6,!=7.0.0,!=7.0.1)", "pytest-cov (>=3.0.0)", "pytest-qt"] [[package]] +name = "requests" +version = "2.28.2" +description = "Python HTTP for Humans." category = "main" -description = "A pure python RFC3339 validator" +optional = false +python-versions = ">=3.7, <4" + +[package.dependencies] +certifi = ">=2017.4.17" +charset-normalizer = ">=2,<4" +idna = ">=2.5,<4" +urllib3 = ">=1.21.1,<1.27" + +[package.extras] +socks = ["PySocks (>=1.5.6,!=1.5.7)"] +use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] + +[[package]] name = "rfc3339-validator" +version = "0.1.4" +description = "A pure python RFC3339 validator" +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" -version = "0.1.4" [package.dependencies] six = "*" [[package]] -category = "main" -description = "Pure python rfc3986 validator" name = "rfc3986-validator" +version = "0.1.1" +description = "Pure python rfc3986 validator" +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" -version = "0.1.1" [[package]] -category = "main" -description = "Fundamental algorithms for scientific computing in Python" name = "scipy" +version = "1.10.0" +description = "Fundamental algorithms for scientific computing in Python" +category = "main" optional = false python-versions = "<3.12,>=3.8" -version = "1.10.0" [package.dependencies] numpy = ">=1.19.5,<1.27.0" @@ -2370,12 +1464,12 @@ doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx ( test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"] [[package]] -category = "main" -description = "Send file to trash natively under Mac OS X, Windows and Linux." name = "send2trash" +version = "1.8.0" +description = "Send file to trash natively under Mac OS X, Windows and Linux." +category = "main" optional = false python-versions = "*" -version = "1.8.0" [package.extras] nativelib = ["pyobjc-framework-Cocoa", "pywin32"] @@ -2383,12 +1477,12 @@ objc = ["pyobjc-framework-Cocoa"] win32 = ["pywin32"] [[package]] -category = "main" -description = "Easily download, build, install, upgrade, and uninstall Python packages" name = "setuptools" +version = "67.1.0" +description = "Easily download, build, install, upgrade, and uninstall Python packages" +category = "main" optional = false python-versions = ">=3.7" -version = "67.0.0" [package.extras] docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"] @@ -2396,12 +1490,12 @@ testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-202 testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"] [[package]] -category = "main" -description = "the blessed package to manage your versions by scm tags" name = "setuptools-scm" +version = "7.1.0" +description = "the blessed package to manage your versions by scm tags" +category = "main" optional = false python-versions = ">=3.7" -version = "7.1.0" [package.dependencies] packaging = ">=20.0" @@ -2414,36 +1508,36 @@ test = ["pytest (>=6.2)", "virtualenv (>20)"] toml = ["setuptools (>=42)"] [[package]] -category = "main" -description = "Python 2 and 3 compatibility utilities" name = "six" +version = "1.16.0" +description = "Python 2 and 3 compatibility utilities" +category = "main" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" -version = "1.16.0" [[package]] -category = "main" -description = "Sniff out which async library your code is running under" name = "sniffio" +version = "1.3.0" +description = "Sniff out which async library your code is running under" +category = "main" optional = false python-versions = ">=3.7" -version = "1.3.0" [[package]] -category = "main" -description = "A modern CSS selector implementation for Beautiful Soup." name = "soupsieve" +version = "2.3.2.post1" +description = "A modern CSS selector implementation for Beautiful Soup." +category = "main" optional = false python-versions = ">=3.6" -version = "2.3.2.post1" [[package]] -category = "main" -description = "Extract data from python stack frames and tracebacks for informative displays" name = "stack-data" +version = "0.6.2" +description = "Extract data from python stack frames and tracebacks for informative displays" +category = "main" optional = false python-versions = "*" -version = "0.6.2" [package.dependencies] asttokens = ">=2.1.0" @@ -2454,12 +1548,12 @@ pure-eval = "*" tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"] [[package]] -category = "main" -description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library." name = "terminado" +version = "0.17.1" +description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library." +category = "main" optional = false python-versions = ">=3.7" -version = "0.17.1" [package.dependencies] ptyprocess = {version = "*", markers = "os_name != \"nt\""} @@ -2471,12 +1565,12 @@ docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"] test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"] [[package]] -category = "main" -description = "A tiny CSS parser" name = "tinycss2" +version = "1.2.1" +description = "A tiny CSS parser" +category = "main" optional = false python-versions = ">=3.7" -version = "1.2.1" [package.dependencies] webencodings = ">=0.4" @@ -2486,28 +1580,28 @@ doc = ["sphinx", "sphinx_rtd_theme"] test = ["flake8", "isort", "pytest"] [[package]] -category = "main" -description = "A lil' TOML parser" name = "tomli" +version = "1.2.3" +description = "A lil' TOML parser" +category = "main" optional = false python-versions = ">=3.6" -version = "1.2.3" [[package]] -category = "main" -description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." name = "tornado" +version = "6.2" +description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." +category = "main" optional = false python-versions = ">= 3.7" -version = "6.2" [[package]] -category = "main" -description = "Fast, Extensible Progress Meter" name = "tqdm" +version = "4.64.1" +description = "Fast, Extensible Progress Meter" +category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7" -version = "4.64.1" [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} @@ -2519,43 +1613,56 @@ slack = ["slack-sdk"] telegram = ["requests"] [[package]] -category = "main" -description = "Traitlets Python configuration system" name = "traitlets" +version = "5.9.0" +description = "Traitlets Python configuration system" +category = "main" optional = false python-versions = ">=3.7" -version = "5.8.1" [package.extras] docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"] test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"] [[package]] -category = "main" -description = "Backported and Experimental Type Hints for Python 3.7+" name = "typing-extensions" +version = "4.4.0" +description = "Backported and Experimental Type 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b/pyproject.toml @@ -4,10 +4,10 @@ requires = ["poetry-core"] [tool.poetry] authors = ["Philipp Horstenkamp "] -description = "" +description = "A Deep Learning implementation of the game Reversi aka. Otello. This is a Jupyter implementation only because it was requested in such a format for a class in my master’s degree. Enjoy the read or ignore it." name = "reversi" readme = "README.md" -version = "0.1.0" +version = "0.1.1" [tool.poetry.dependencies] ipytest = "^0.13.0" @@ -18,6 +18,7 @@ pytest = "^7.2.1" python = "3.10.*" scipy = "^1.10.0" tqdm = "^4.64.1" +jupyterlab = "^3.6.1" [tool.poetry.group.build.dependencies] blackcellmagic = "^0.0.3" -- 2.49.0 From 1298f328505525ba684415c531b83a59f7427800 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 13:49:39 +0100 Subject: [PATCH 07/31] Added some images for the documentation. --- 8-directions.png | Bin 0 -> 6494 bytes Startaufstellung.png | Bin 0 -> 67019 bytes computer-score.png | Bin 0 -> 23845 bytes reversi_example.png | Bin 0 -> 86637 bytes 4 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 8-directions.png create mode 100644 Startaufstellung.png create mode 100644 computer-score.png create mode 100644 reversi_example.png diff --git a/8-directions.png b/8-directions.png new file mode 100644 index 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@@ python-versions = ">=3.7" [package.dependencies] colorama = {version = "*", markers = "platform_system == \"Windows\""} +[[package]] +name = "cloudpickle" +version = "2.2.1" +description = "Extended pickling support for Python objects" +category = "main" +optional = false +python-versions = ">=3.6" + [[package]] name = "colorama" version = "0.4.6" @@ -398,6 +406,39 @@ category = "main" optional = false python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" +[[package]] +name = "gym" +version = "0.26.2" +description = "Gym: A universal API for reinforcement learning environments" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +cloudpickle = ">=1.2.0" +gym_notices = ">=0.0.4" +numpy = ">=1.18.0" + +[package.extras] +accept-rom-license = ["autorom[accept-rom-license] (>=0.4.2,<0.5.0)"] +all = ["ale-py (>=0.8.0,<0.9.0)", "box2d-py (==2.3.5)", "imageio (>=2.14.1)", "lz4 (>=3.1.0)", "matplotlib (>=3.0)", "moviepy (>=1.0.0)", "mujoco 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version = "23.0" @@ -1587,6 +1676,53 @@ category = "main" optional = false python-versions = ">=3.6" +[[package]] +name = "torch" +version = "1.13.1" +description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration" +category = "main" +optional = false +python-versions = ">=3.7.0" + +[package.dependencies] +nvidia-cublas-cu11 = {version = "11.10.3.66", markers = "platform_system == \"Linux\""} +nvidia-cuda-nvrtc-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""} +nvidia-cuda-runtime-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""} +nvidia-cudnn-cu11 = {version = "8.5.0.96", markers = "platform_system == \"Linux\""} +typing-extensions = "*" + +[package.extras] +opt-einsum = ["opt-einsum (>=3.3)"] + +[[package]] +name = "torchaudio" +version = "0.13.1" +description = "An audio package for PyTorch" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +torch = "*" + +[[package]] +name = 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--git a/.idea/reversi.iml b/.idea/reversi.iml index d0876a7..7fb2c58 100644 --- a/.idea/reversi.iml +++ b/.idea/reversi.iml @@ -5,4 +5,11 @@ - \ No newline at end of file + + + + + -- 2.49.0 From c6a9b70be41a98ca2a0ef7739617f36cb8dd0a3f Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 13:59:46 +0100 Subject: [PATCH 10/31] Some initial docstrings added. --- main.ipynb | 912 ++++++++++++++++------------------------------------- 1 file changed, 272 insertions(+), 640 deletions(-) diff --git a/main.ipynb b/main.ipynb index 629e1fc..9fa3e38 100644 --- a/main.ipynb +++ b/main.ipynb @@ -4,9 +4,46 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Deep Reversi AI\n", + "# Deep Otello AI\n", "\n", - "The game is not" + "The game reversi is a very good game to apply deep learning methods to.\n", + "\n", + "Othello also known as reversi is a board game first published in 1883 by eiter Lewis Waterman or John W. Mollet in England (each one was denouncing the other as fraud).\n", + "It is a strickt turn based zero-sum game with a clear Markov chain and now hidden states like in card games with an unknown distribution of cards or unknown player allegiance.\n", + "There is like for the game go only one set of stones with two colors which is much easier to abstract than chess with its 6 unique pieces.\n", + "The game has a symmetrical game board wich allows to play with rotating the state around an axis to allow for a breaking of sequences or interesting ANN architectures, quadruple the data generation by simulation or interesting test cases where a symetry in turns should be observable if the AI reaches an \"objective\" policy.\n", + "\n", + "## The game rules\n", + "\n", + "Othello is played on a board with 8 x 8 fields for two player.\n", + "The board geometry is equal to a chess game.\n", + "The game is played with game stones that are black on one siede and white on the other.\n", + "![Othello game board example](reversi_example.png)\n", + "The player take turns.\n", + "A player places a stone with his or her color up on the game board.\n", + "The player can only place stones when he surrounds a number of stones with the opponents color with the new stone and already placed stones of his color.\n", + "Those surrounded stones can either be horizontally, vertically and/or diagonally be placed.\n", + "All stones thus surrounded will be flipped to be of the players color.\n", + "Turns are only possible if the player is also changing the color of the opponents stones. If a player can't act he is skipped.\n", + "The game ends if both players can't act. The player with the most stones wins.\n", + "If the score is counted in detail unclaimed fields go to the player with more stones of his or her color on the board.\n", + "The game begins with four stones places in the center of the game. Each player gets two. They are placed diagonally to each other.\n", + "\n", + "\n", + "![Startaufstellung.png](Startaufstellung.png)\n", + "\n", + "## Some strategies\n", + "\n", + "As can be easily understood the placement of stones and on the bord is always a careful balance of attack and defence.\n", + "If the player occupies huge homogenous stretches on the board it can be attacked easier.\n", + "The boards corners provide safety from wich occupied territory is impossible to loos but since it is only possible to reach the corners if the enemy is forced to allow this or calculates the cost of giving a stable base to the enemy it is difficult to obtain.\n", + "There are some text on otello computer strategies which implement greedy algorithms for reversi based on a modified score to each field.\n", + "Those different values are score modifiers for a traditional greedy algorithm.\n", + "If a players stone has captured such a filed the score reached is multiplied by the modifier.\n", + "The total score is the score reached by the player subtracted with the score of the enemy.\n", + "The scores change in the course of the game and converges against one. This gives some indications of what to expect from an Othello AI.\n", + "\n", + "![ComputerPossitionScore](computer-score.png)\n" ] }, { @@ -35,7 +72,6 @@ "import abc\n", "from typing import Final\n", "from scipy.ndimage import binary_dilation\n", - "from tqdm.auto import tqdm\n", "import matplotlib.pyplot as plt\n", "from abc import ABC" ] @@ -49,79 +85,117 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "ENEMY: Final[int] = -1\n", - "PLAYER: Final[int] = 1\n", - "BOARD_SIZE: Final[int] = 8" + "BOARD_SIZE: Final[int] = 8 # defines the board side length as 8\n", + "PLAYER: Final[int] = 1 # defines the number symbolising the player as 1\n", + "ENEMY: Final[int] = -1 # defines the number symbolising the enenemy as 1" ] }, + { + "cell_type": "markdown", + "source": [ + "The directions array contains all the numerical offsets needed to move along one of the 8 directions in a 2 dimensional grid. This will allow an iteration over the game board.\n", + "![8-directions.png](8-directions.png \"Offset in 8 directions\")" + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([[-1, -1],\n", - " [-1, 0],\n", - " [-1, 1],\n", - " [ 0, -1],\n", - " [ 0, 1],\n", - " [ 1, -1],\n", - " [ 1, 0],\n", - " [ 1, 1]])" - ] + "text/plain": "array([[-1, -1],\n [-1, 0],\n [-1, 1],\n [ 0, -1],\n [ 0, 1],\n [ 1, -1],\n [ 1, 0],\n [ 1, 1]])" }, - "execution_count": 4, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "DIRECTIONS: Final[np.ndarray] = np.array(\n", - " [[i, j] for i in range(-1, 2) for j in range(-1, 2) if j != 0 or i != 0], dtype=int\n", + " [[i, j] for i in range(-1, 2) for j in range(-1, 2) if j != 0 or i != 0],\n", + " dtype=int,\n", ")\n", + "DIRECTIONS.setflags(write=False)\n", "DIRECTIONS" ] }, { "cell_type": "markdown", - "metadata": {}, "source": [ - "## Creating new boards" - ] + "Another constant needed is the initial start square at the center of the board." + ], + "metadata": { + "collapsed": false + } }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, + "execution_count": 23, "outputs": [ { "data": { - "text/plain": [ - "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", - " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0]])" - ] + "text/plain": "array([[-1, 1],\n [ 1, -1]])" }, - "execution_count": 5, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def get_new_games(number_of_games: int):\n", + "START_SQUARE: Final[np.ndarray] = np.array(\n", + " [[ENEMY, PLAYER], [PLAYER, ENEMY]], dtype=int\n", + ")\n", + "START_SQUARE.setflags(write=False)\n", + "START_SQUARE" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating new boards\n", + "\n", + "The first function implemented and tested is a function to generate the starting environment as a stack of games.\n", + "As described above i simply placed a 2 by 2 square in the center of an empty stack of boards." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])" + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def get_new_games(number_of_games: int) -> np.ndarray:\n", + " \"\"\"Generates a stack of initialised game boards.\n", + "\n", + " Args:\n", + " number_of_games: The size of the board stack.\n", + "\n", + " Returns: The generates stack of games as a stack n x 8 x 8.\n", + "\n", + " \"\"\"\n", " empty = np.zeros([number_of_games, BOARD_SIZE, BOARD_SIZE], dtype=int)\n", - " empty[:, 3:5, 3:5] = np.array([[-1, 1], [1, -1]])\n", + " empty[:, 3:5, 3:5] = START_SQUARE\n", " return empty\n", "\n", "\n", @@ -130,7 +204,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -162,17 +236,27 @@ "del test_number_of_games" ] }, + { + "cell_type": "markdown", + "source": [ + "## Visualisation tools\n", + "\n", + "In this section a visualisation help was implemented for debugging of the game and a proper display of the results.\n", + "For this visualisation ChatGPT was used as a prompted code generator that was later reviewed and refactored by hand to integrate seamlessly into the project as a whole." + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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QMGQMzVBl26QOxUX0xRdfICYmBvHx8Zg5cyauXLmixrhIbd9D3TutAvJpIa3s9PQw9UB8VLyq0YOiB6G7qbuqGRQ8iorokUcewYYNG7B7924UFhbiyy+/xGOPPYa6Ot9/o51OJxwOR4uF7gJql5BHK7/u26/4qAbPEdjUOSg6xSMj4+bubkpKCh555BEMGDAA27dvR1ZW60e2Wq1WvPnmm4GNkoLPJS7HZDRpEq1VDgUuoH+W7rvvPvzgBz9ARUWFz3Xy8/Nht9u9i81mCySSgiVUXI7zhlOTaK1yKHABFVF9fT0uXbqEvn37+lzHZDLBbDa3WOguoNWvoZWcipoKuKVgH7zUkltyo6LG9z+QdHdRVES//vWvcfDgQVRWVuKTTz7BM888g9DQUEyfPl2t8ZFawqD+HVF9XLeowdmAy99cVjX6Us0lXreoE1FURFevXsX06dORmJiIn/zkJ4iMjMTRo0cRFRWl1vhITbFQ9ziifr6/vevMLlWPIyo5W6LKtkkdit6s3rp1q1rjIBEGQ76ekBqk5u37sOrgKuSOz1UlOiw0DIUHClXZNqmD55rpWU/IFzUL9l6RoXm7bVy5sby6HKXnSoO+V9TkakLpudLg3fSRNMEi0ruxCP7fgpDm7bZj3qZ5aHI1BfXs+yZXE+ZtmheU7ZF2WER6FwFgTJC3+Sg69EZ45beVyN2SG9Sz73O25PCysZ0Qi4iAJACjgrSthwAkdnz1osNFeHXHqwDg956R53mLdyzGusPr/NoGicWL55NsBOR7Xx2BfD0hJZ1ggPxP2qNQVEIeS3YtwdeOr7F8+nIYQ42KToZtcjWhydWEnC05LKFOjHtEdFMSgP8DENP8uL1XTJ7vxzQ/z48S8ig6XIQhrw/B/gv7AaDdN7E9399/YT+SX09mCXVy3COiliIAZODmfc2uotUTV2GGfJxQEO9rVvltJZ5a9pT3vmYZQzPuOEHWLblxqeYSSs6WoPBAIT8d6yJYRNS6npBfagGa3+m1vLoceVvzkIc83ulVJwxSsD477SCHwwGLxSI/uFfLZMj34ZYgv6QI11G26HzOXZ9zb5T/sNvt7Z5jKnaPqFFQrqTTbNH5nLs4ovPbIbaIuEekj3zOXZ9zV1B84oooHMAMjTOLIf9w9JYtOp9z1+fcN0Muwg7gx/dEJByLiIiEYxERkXAsIiISjkVERMKxiIhIOBYREQnHIiIi4RQX0VdffYVZs2YhMjIS4eHhGDZsGMrKytQYGxHphKIjq2tra5Gamoq0tDSUlJQgKioKX3zxBXr2DNJ1IIhIlxQV0dtvv43Y2FisX7/e+7WBAwcGfVBEpC+KXpp9+OGHeOihhzBt2jRER0djxIgRWLNmTZvPcTqdcDgcLRYiolspKqLLly+jsLAQDz74IPbs2YMFCxYgNzcXGzdu9Pkcq9UKi8XiXWJjYwMeNBF1LYqKyO12Y+TIkViyZAlGjBiBX/3qV/jlL3+JVatW+XxOfn4+7Ha7d7HZbAEPmoi6FkVF1LdvXwwZMqTF1wYPHowrV674fI7JZILZbG6xEBHdSlERpaam4uLFiy2+9vnnn2PAgAFBHRQR6YuiInrppZdw9OhRLFmyBBUVFSguLsbf/vY3ZGdnqzU+ItIBRUU0evRo7NixA1u2bMHQoUPx1ltvYdmyZZg5c6Za4yMiHVB8qdjMzExkZmaqMRYi0imea0ZEwrGIiEg4FhERCcciIiLhWEREJByLiIiEYxERkXAsIiISziBJkqRloMPhgMVikR/cq2Uy5PtwSwAMkO8Frpds0fmcuz7n3ij/Ybfb2z3ZXfGR1UHVKChX0mm26HzOXRzR+e0QW0TcI9JHPueuz7krKD5xRRQOYIbGmcWQfzh6yxadz7nrc+6bIRdhB/DNaiISjkVERMKxiIhIOBYREQnHIiIi4VhERCQci4iIhGMREZFwioooLi4OBoPhjoW3EyKiQCg6svrEiRNwuVzex2fPnsWECRMwbdq0oA+MiPRDURFFRUW1eLx06VIMGjQIjz/+eFAHRUT64ve5Zt9//z02bdqEl19+GQaDwed6TqcTTqfT+9jhcPgbSURdlN9vVn/wwQe4fv065syZ0+Z6VqsVFovFu8TGxvobSURdlN9FVFRUhIyMDMTExLS5Xn5+Pux2u3ex2Wz+RhJRF+XXS7N///vf2Lt3L95///121zWZTDCZTP7EEJFO+LVHtH79ekRHR2Py5MnBHg8R6ZDiInK73Vi/fj1mz54No1HsBR6JqGtQXER79+7FlStXMHfuXDXGQ0Q6pHiXJj09HRrf+IOIujiea0ZEwrGIiEg4FhERCcciIiLhWEREJByLiIiEYxERkXAGSeODghwOBywWi/zgXi2TwXugc+6cu5Ya5T/sdjvMZnObq4o9R6NRUK6k02zR+Zy7OKLz2yG2iLhHpI98zl2fc1dQfOKKKBzADI0ziyH/cPSWLTqfc9fn3DdDLsIO4JvVRCQci4iIhGMREZFwLCIiEo5FRETCsYiISDgWEREJxyIiIuEUFZHL5cJrr72GgQMHIjw8HIMGDcJbb73Fa1gTUUAUHVn99ttvo7CwEBs3bkRycjLKysrw/PPPw2KxIDc3V60xElEXp6iIPvnkE0ydOtV7Y8W4uDhs2bIFx48fV2VwRKQPil6aPfroo9i3bx8+//xzAMDp06dx+PBhZGRkqDI4ItIHRXtEixYtgsPhQFJSEkJDQ+FyuVBQUICZM2f6fI7T6YTT6fQ+djgc/o+WiLokRXtE27dvx+bNm1FcXIxPP/0UGzduxB//+Eds3LjR53OsVissFot3iY2NDXjQRNS1KCqi3/zmN1i0aBF+9rOfYdiwYfj5z3+Ol156CVar1edz8vPzYbfbvYvNZgt40ETUtSh6adbY2IiQkJbdFRoaCrfb7fM5JpMJJpPJv9ERkS4oKqIpU6agoKAA/fv3R3JyMj777DP8+c9/xty5c9UaHxHpgKIiWr58OV577TUsXLgQNTU1iImJwbx58/C73/1OrfERkQ4oKqKIiAgsW7YMy5YtU2k4RKRHPNeMiIRjERGRcCwiIhKORUREwrGIiEg4FhERCcciIiLhWEREJJxB0vg6r3a7Hffdd5/8IFzLZLS8D7eeskXnc+5iskXnN2dfv34dFoulzVUVHVkdDHV1dTcffOd7PdXpNVt0Pueuu/y6urp2i0jzPSK3242qqipERETAYDAoeq7D4UBsbCxsNhvMZrNKI7w78zl3/WWLzg80W5Ik1NXVISYm5o6rdtxO8z2ikJAQ9OvXL6BtmM1mIX8p7oZ8zl1/2aLzA8lub0/Ig29WE5FwLCIiEq5TFZHJZMLrr78u7IqPIvM5d/1li87XMlvzN6uJiG7XqfaIiKhrYhERkXAsIiISjkVERMJ1qiI6cuQIQkNDMXnyZM0y58yZA4PB4F0iIyMxceJE/Otf/9JsDNeuXUNOTg7i4+NhMpkQGxuLKVOmYN++farm3jr3sLAw3H///ZgwYQLWrVvX5r3s1Mi/dZk4caLq2W3lV1RUqJ597do15OXlISEhAd26dcP999+P1NRUFBYWorGxUbXcOXPm4Omnn77j6wcOHIDBYMD169dVye1URVRUVIScnBwcOnQIVVVVmuVOnDgR1dXVqK6uxr59+2A0GpGZmalJdmVlJUaNGoWPP/4Y77zzDs6cOYPdu3cjLS0N2dnZqud75l5ZWYmSkhKkpaUhLy8PmZmZuHHjhmb5ty5btmxRPbet/IEDB6qaefnyZYwYMQKlpaVYsmQJPvvsMxw5cgS//e1vsXPnTuzdu1fVfBE0P8XDX/X19di2bRvKyspw7do1bNiwAYsXL9Yk22QyoU+fPgCAPn36YNGiRXjsscfwzTffICoqStXshQsXwmAw4Pjx4+jevbv368nJyZrc2PLWuT/wwAMYOXIkfvjDH2L8+PHYsGEDfvGLX2iWL4KI/IULF8JoNKKsrKzF7zw+Ph5Tp05FVzziptPsEW3fvh1JSUlITEzErFmzsG7dOiG/kPr6emzatAkJCQmIjIxUNeu///0vdu/ejezs7BZ/IT28l1PR2BNPPIHhw4fj/fffF5Lflf3nP/9BaWmpz985AMUni3cGnaaIioqKMGvWLADy7rLdbsfBgwc1yd65cyd69OiBHj16ICIiAh9++CG2bdvW7hnFgaqoqIAkSUhKSlI1xx9JSUmorKxUPefWn71nWbJkieq5vvKnTZumap7nd56YmNji67179/aO4ZVXXlF1DK39zDMyMlTN7BQvzS5evIjjx49jx44dAACj0Yif/vSnKCoqwrhx41TPT0tLQ2FhIQCgtrYW7777LjIyMnD8+HEMGDBAtdy7eRdckiRN/mW+9Wfv0atXL9VzfeX72ktR2/Hjx+F2uzFz5kw4nU5Vs1r7mR87dsy7I6CGTlFERUVFuHHjBmJiYrxfkyQJJpMJK1as6PClBvzVvXt3JCQkeB+vXbsWFosFa9aswR/+8AfVch988EEYDAZcuHBBtQx/lZeXq/6mLXDnz15rWucnJCTAYDDg4sWLLb4eHx8PAAgPV/8yi63N+erVq6pm3vUvzW7cuIG///3v+NOf/oRTp055l9OnTyMmJkbTT1A8DAYDQkJC8N136l7yrlevXnjqqaewcuVKNDQ03PF9tT5Kbc/HH3+MM2fO4NlnnxWS35VFRkZiwoQJWLFiRau/867qrt8j2rlzJ2pra5GVlXXHns+zzz6LoqIizJ8/X9UxOJ1OXLt2DYD80mzFihWor6/HlClTVM0FgJUrVyI1NRUPP/wwfv/73yMlJQU3btzARx99hMLCQpSXl6ua75m7y+XC119/jd27d8NqtSIzMxPPPfecqtm35t/KaDSid+/eqmeL8u677yI1NRUPPfQQ3njjDaSkpCAkJAQnTpzAhQsXMGrUKNFDDD7pLpeZmSlNmjSp1e8dO3ZMAiCdPn1atfzZs2dLALxLRESENHr0aOm9995TLfN2VVVVUnZ2tjRgwADpnnvukR544AHpxz/+sbR//35Vc2+du9FolKKioqQnn3xSWrduneRyuVTNvj3/1iUxMVH1bE/+1KlTNcm6XVVVlfTCCy9IAwcOlMLCwqQePXpIDz/8sPTOO+9IDQ0NquX6mvP+/fslAFJtba0qubwMCBEJd9e/R0REXR+LiIiEYxERkXAsIiISjkVERMKxiIhIOBYREQnHIiIi4VhERCQci4iIhGMREZFwLCIiEu7/Adbt5Eva9bHJAAAAAElFTkSuQmCC\n" }, "metadata": {}, "output_type": "display_data" @@ -180,13 +264,24 @@ ], "source": [ "def plot_othello_board(board, ax=None):\n", - " size = 3\n", + " \"\"\"Plots a single otello board.\n", + "\n", + " If a matplot axis object is given the board will be plotted into that axis. If not an axis object will be generated.\n", + "\n", + " Args:\n", + " board: The bord that should be plotted. Only a single games is allowed. A numpy array of the form 8x8 is expected.\n", + " ax: If needed the\n", + "\n", + " Returns:\n", + "\n", + " \"\"\"\n", " plot_all = False\n", " if ax is None:\n", + " fig_size = 3\n", " plot_all = True\n", - " fig, ax = plt.subplots(figsize=(size, size))\n", + " fig, ax = plt.subplots(figsize=(fig_size, fig_size))\n", "\n", - " ax.set_facecolor(\"green\")\n", + " ax.set_facecolor(\"#006400\")\n", " for i in range(BOARD_SIZE):\n", " for j in range(BOARD_SIZE):\n", " if board[i, j] == -1:\n", @@ -215,7 +310,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -235,20 +330,16 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": { "tags": [] }, "outputs": [ { "data": { - "text/plain": [ - "array([[[1, 1, 1],\n", - " [1, 0, 1],\n", - " [1, 1, 1]]])" - ] + "text/plain": "array([[[1, 1, 1],\n [1, 0, 1],\n [1, 1, 1]]])" }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -260,23 +351,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([[[False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, True, False, False, False, False],\n", - " [False, False, True, False, False, False, False, False],\n", - " [False, False, False, False, False, True, False, False],\n", - " [False, False, False, False, True, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False]]])" - ] + "text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])" }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -324,31 +406,42 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "(array([2, 2, 2]), array([2, 2, 2]))" - ] + "text/plain": "(array([2, 2, 2]), array([2, 2, 2]))" }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def evaluate_boards(array: np.ndarray):\n", - " return np.sum(array == 1, axis=(1, 2)), np.sum(array == -1, axis=(1, 2))\n", + "def board_evaluation_final(array: np.ndarray):\n", + " score1, score2 = np.sum(array == 1, axis=(1, 2)), np.sum(array == -1, axis=(1, 2))\n", + " player_1_won = score1 > score2\n", + " player_2_won = score1 < score2\n", + " score1_final = 64 - score2[player_1_won]\n", + " score2_final = 64 - score1[player_2_won]\n", + " score1[player_1_won] = score1_final\n", + " score2[player_2_won] = score2_final\n", + " return score1, score2\n", "\n", "\n", - "evaluate_boards(get_new_games(3))" + "def board_evaluation(array: np.ndarray):\n", + " score1, score2 = np.sum(array == 1, axis=(1, 2)), np.sum(array == -1, axis=(1, 2))\n", + " return score1, score2\n", + "\n", + "\n", + "board_evaluation(get_new_games(3))\n", + "board_evaluation_final(get_new_games(3))" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -371,7 +464,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -379,13 +472,9 @@ " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", " for game in range(boards.shape[0]):\n", " if np.all(moves[game] == -1):\n", - " try:\n", - " arr_moves_possible[game] = not np.any(\n", - " get_possible_turns(np.reshape(boards[game], (1, 8, 8)))\n", - " )\n", - " except Exception as err:\n", - " print(test)\n", - " raise err\n", + " arr_moves_possible[game] = not np.any(\n", + " get_possible_turns(np.reshape(boards[game], (1, 8, 8)))\n", + " )\n", " else:\n", " arr_moves_possible[game] = any(\n", " recursive_steps(boards[game, :, :], direction, moves[game])\n", @@ -412,36 +501,21 @@ " np.array([True] * 3),\n", ")\n", "np.testing.assert_array_equal(\n", - " moves_possible(np.zeros((3, 8, 8)), np.array([[-1, -1]] * 3)), np.array([True] * 3)\n", + " moves_possible(np.zeros((3, 8, 8)), np.array([[-1, -1]] * 3)),\n", + " np.array([True] * 3),\n", ")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 1, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 1, 1, 0, 0, 0],\n", - " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0]])" - ] + "text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 1, 0, 0, 0, 0],\n [ 0, 0, 0, 1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])" }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -488,13 +562,12 @@ " return boards\n", "\n", "\n", - "boards = get_new_games(10)\n", - "do_moves(boards, np.array([[2, 3]] * 10))[0]" + "do_moves(get_new_games(10), np.array([[2, 3]] * 10))[0]" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -502,7 +575,8 @@ "\n", " IMPOSSIBLE: np.ndarray = np.array([-1, -1], dtype=int)\n", "\n", - " @abc.abstractproperty\n", + " @property\n", + " @abc.abstractmethod\n", " def policy_name(self) -> str:\n", " raise NotImplementedError()\n", "\n", @@ -513,20 +587,13 @@ " def get_policy(self, boards: np.ndarray) -> np.ndarray:\n", " policies = self.internal_policy(boards)\n", " possible_turns = get_possible_turns(boards)\n", - " poss_turns_debug = possible_turns[0]\n", " policies[possible_turns == False] = -1.0\n", " max_indices = [\n", " np.unravel_index(policy.argmax(), policy.shape) for policy in policies\n", " ]\n", " policy_vector = np.array(max_indices)\n", - " # todo check if no turn is possible and return [-1, -1]\n", - " a1 = np.all(policy_vector[:] == 0, 1)\n", - " a2 = policies[:, 0, 0] == -1.0\n", + "\n", " no_turn_possible = np.all(policy_vector == 0, 1) & (policies[:, 0, 0] == -1.0)\n", - " if np.any(no_turn_possible):\n", - " cases = np.where(no_turn_possible)\n", - " print(cases)\n", - " print(\"Test\")\n", "\n", " policy_vector[no_turn_possible] = GamePolicy.IMPOSSIBLE\n", " return policy_vector" @@ -534,7 +601,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -549,56 +616,10 @@ " # return np.argmax(random_values, (1, 2))\n", "\n", "\n", - "rndpolicy = RandomPolicy()\n", - "assert rndpolicy.policy_name == \"random\"" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", - " [ 0, 0, 0, 1, 1, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 1, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0]])" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def single_turn(current_boards: np, policy: GamePolicy) -> np.ndarray:\n", - " policy_results = policy.get_policy(current_boards)\n", - " poss = moves_possible(current_boards, policy_results)\n", - " if not np.all(poss):\n", - " false_values = np.where(poss == False)\n", - " bad_boards = current_boards[false_values]\n", - " bad_policy = policy_results[false_values]\n", - " print(\"test\")\n", - "\n", - " try:\n", - " assert np.all(moves_possible(current_boards, policy_results)), (\n", - " current_boards[(moves_possible(current_boards, policy_results) == False)],\n", - " policy_results[(moves_possible(current_boards, policy_results) == False)],\n", - " np.where(moves_possible(current_boards, policy_results) == False),\n", - " )\n", - " except AssertionError as err:\n", - " raise err\n", - "\n", - " return do_moves(current_boards, policy_results)\n", - "\n", - "\n", - "single_turn(get_new_games(10), RandomPolicy())[0]" + "rnd_policy = RandomPolicy()\n", + "assert rnd_policy.policy_name == \"random\"\n", + "rnd_policy_result = rnd_policy.get_policy(get_new_games(1))\n", + "assert np.any((5 >= rnd_policy_result) & (rnd_policy_result >= 3))" ] }, { @@ -610,325 +631,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "(array([1], dtype=int64),)\n", - "Test\n", - "(array([1], dtype=int64),)\n", - "Test\n", - "(array([0, 4, 5, 7, 8], dtype=int64),)\n", - "Test\n" + "123 ms ± 4.08 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { "data": { - "text/plain": [ - "array([[[[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 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0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]]],\n", - "\n", - "\n", - " [[[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 1., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " ...,\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 1., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]]],\n", - "\n", - "\n", - " [[[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 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0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " ...,\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]],\n", - "\n", - " [[ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " ...,\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.],\n", - " [ 0., 0., 0., ..., 0., 0., 0.]]]])" - ] + "text/plain": "array([[[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n ...,\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]]])" }, "execution_count": 18, "metadata": {}, @@ -936,63 +644,39 @@ } ], "source": [ - "def simulate_game(\n", - " nr_of_games: int,\n", - " policies: tuple[GamePolicy, GamePolicy],\n", - ") -> np.ndarray:\n", - " history_stack = np.zeros((70, nr_of_games, 8, 8))\n", - " current_boards = get_new_games(nr_of_games)\n", - " index_counter = 0\n", - " for i in range(60):\n", - " policy_index = i % 2\n", - " policy = policies[policy_index]\n", - " if policy_index == 0:\n", - " current_boards = current_boards * -1\n", - " try:\n", - " current_boards = single_turn(current_boards, policy)\n", - " except RuntimeError as err:\n", - " print(\"Err\")\n", - " print(history_stack)\n", - " raise err\n", - " if policy_index == 0:\n", - " current_boards = current_boards * -1\n", + "def single_turn(\n", + " current_boards: np, policy: GamePolicy\n", + ") -> tuple[np.ndarray, np.ndarray]:\n", + " policy_results = policy.get_policy(current_boards)\n", "\n", - " history_stack[index_counter] = current_boards\n", - " index_counter += 1\n", - " return history_stack\n", + " assert np.all(moves_possible(current_boards, policy_results)), (\n", + " current_boards[(moves_possible(current_boards, policy_results) == False)],\n", + " policy_results[(moves_possible(current_boards, policy_results) == False)],\n", + " np.where(moves_possible(current_boards, policy_results) == False),\n", + " )\n", + "\n", + " return do_moves(current_boards, policy_results), policy_results\n", "\n", "\n", - "simulate_game(10, (RandomPolicy(), RandomPolicy()))" + "%timeit single_turn(get_new_games(100), RandomPolicy())\n", + "single_turn(get_new_games(100), RandomPolicy())[0]" ] }, { "cell_type": "code", "execution_count": 19, - "metadata": { - "tags": [] - }, + "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "10.8 s ± 339 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + }, { "data": { - "text/plain": [ - "array([[[ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, -1, 0, -1, 0, 0],\n", - " [ 0, 0, 1, 1, 1, 1, 0, 0],\n", - " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", - " [ 0, 0, -1, -1, -1, 0, 0, 0],\n", - " [ 0, 0, 1, -1, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0]],\n", - "\n", - " [[ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, -1, -1, -1, 0],\n", - " [ 0, 0, 1, 0, -1, 0, 0, 0],\n", - " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", - " [ 0, 0, 0, -1, 1, -1, -1, 0],\n", - " [ 0, 0, -1, 0, 0, 1, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0]]])" - ] + "text/plain": "(array([[[[ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n ...,\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 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0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.]],\n \n ...,\n \n [[ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n ...,\n [ 0., 0., 1., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.]],\n \n [[ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n ...,\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.]],\n \n [[ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 1., 0., 0.],\n ...,\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.],\n [ 0., 0., 0., ..., 0., 0., 0.]]],\n \n \n ...,\n \n \n [[[-1., -1., -1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n ...,\n [ 1., 1., 1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., -1., 1.],\n ...,\n [-1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.]],\n \n [[ 0., -1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.],\n ...,\n [ 1., -1., 1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n ...,\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., -1., 1., ..., 1., 1., 1.],\n ...,\n [ 1., -1., 1., ..., 1., -1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]],\n \n [[ 1., 1., 1., ..., -1., -1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., -1., 1., ..., 1., -1., -1.],\n ...,\n [ 1., -1., 1., ..., -1., 1., -1.],\n [ 1., 1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., -1., -1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n ...,\n [ 1., -1., 1., ..., 1., 1., 1.],\n [ 1., -1., -1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., -1.]]],\n \n \n [[[-1., -1., -1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n ...,\n [ 1., 1., 1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., -1., 1.],\n ...,\n [-1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.]],\n \n [[ 0., -1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.],\n ...,\n [ 1., -1., 1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n ...,\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., -1., 1., ..., 1., 1., 1.],\n ...,\n [ 1., -1., 1., ..., 1., -1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]],\n \n [[ 1., 1., 1., ..., -1., -1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., -1., 1., ..., 1., -1., -1.],\n ...,\n [ 1., -1., 1., ..., -1., 1., -1.],\n [ 1., 1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., -1., -1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n ...,\n [ 1., -1., 1., ..., 1., 1., 1.],\n [ 1., -1., -1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., -1.]]],\n \n \n [[[-1., -1., -1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n ...,\n [ 1., 1., 1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., -1., 1.],\n ...,\n [-1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.]],\n \n [[ 0., -1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.],\n ...,\n [ 1., -1., 1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n ...,\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., -1., 1., ..., 1., 1., 1.],\n ...,\n [ 1., -1., 1., ..., 1., -1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]],\n \n [[ 1., 1., 1., ..., -1., -1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n [ 1., -1., 1., ..., 1., -1., -1.],\n ...,\n [ 1., -1., 1., ..., -1., 1., -1.],\n [ 1., 1., -1., ..., -1., -1., -1.],\n [ 1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., -1., -1., ..., -1., -1., -1.],\n [ 1., 1., 1., ..., 1., -1., -1.],\n [ 1., 1., 1., ..., 1., 1., 1.],\n ...,\n [ 1., -1., 1., ..., 1., 1., 1.],\n [ 1., -1., -1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., -1.]]]]),\n array([[[ 4., 2.],\n [ 4., 2.],\n [ 3., 5.],\n ...,\n [ 5., 3.],\n [ 4., 2.],\n [ 3., 5.]],\n \n [[ 5., 4.],\n [ 3., 2.],\n [ 2., 5.],\n ...,\n [ 5., 2.],\n [ 3., 2.],\n [ 2., 5.]],\n \n [[ 4., 5.],\n [ 2., 4.],\n [ 5., 3.],\n ...,\n [ 5., 1.],\n [ 2., 2.],\n [ 5., 3.]],\n \n ...,\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]],\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]],\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]]]))" }, "execution_count": 19, "metadata": {}, @@ -1000,119 +684,46 @@ } ], "source": [ - "arr = np.array(\n", - " [\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, -1, 0, -1, 0, 0],\n", - " [0, 0, 1, 1, 1, 1, 0, 0],\n", - " [0, 0, 0, -1, 1, 0, 0, 0],\n", - " [0, 0, -1, -1, -1, 0, 0, 0],\n", - " [0, 0, 1, -1, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, -1, -1, -1, 0],\n", - " [0, 0, 1, 0, -1, 0, 0, 0],\n", - " [0, 0, 0, 1, -1, 0, 0, 0],\n", - " [0, 0, 0, -1, 1, -1, -1, 0],\n", - " [0, 0, -1, 0, 0, 1, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " ]\n", - ")\n", - "arr" + "SIMULATE_TURNS = 70\n", + "\n", + "\n", + "def simulate_game(\n", + " nr_of_games: int,\n", + " policies: tuple[GamePolicy, GamePolicy],\n", + ") -> tuple[np.ndarray, np.ndarray]:\n", + "\n", + " board_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 8, 8))\n", + " action_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 2))\n", + " current_boards = get_new_games(nr_of_games)\n", + " for turn_index in range(SIMULATE_TURNS):\n", + " policy_index = turn_index % 2\n", + " policy = policies[policy_index]\n", + " board_history_stack[turn_index] = current_boards\n", + " if policy_index == 0:\n", + " current_boards = current_boards * -1\n", + " current_boards, action_taken = single_turn(current_boards, policy)\n", + " action_history_stack[turn_index] = action_taken\n", + "\n", + " if policy_index == 0:\n", + " current_boards = current_boards * -1\n", + "\n", + " return board_history_stack, action_history_stack\n", + "\n", + "\n", + "%timeit simulate_game(100, (RandomPolicy(), RandomPolicy()))\n", + "simulate_game(10, (RandomPolicy(), RandomPolicy()))" ] }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": 20, - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[[False, False, True, True, True, True, True, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, True, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, True, False, False, True, True, False, False],\n", - " [False, False, False, True, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False]],\n", - "\n", - " [[False, False, False, False, True, False, True, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, True, False, True],\n", - " [False, False, True, False, False, False, False, True],\n", - " [False, False, False, True, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False]]])" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "get_possible_turns(arr)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([ True, True])" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "moves_possible(arr, RandomPolicy().get_policy(arr))" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0, 4],\n", - " [4, 7]], dtype=int64)" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "RandomPolicy().get_policy(arr)" - ] - }, - { - "cell_type": "code", - "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1363,25 +974,46 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": "
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\n" + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plot_othello_boards(create_test_game()[-3:])" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "array = create_test_game()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Sources\n", + "\n", + "* Game rules and example board images [https://en.wikipedia.org/wiki/Reversi](https://en.wikipedia.org/wiki/Reversi)\n", + "* Game rules and example game images [https://de.wikipedia.org/wiki/Othello_(Spiel)](https://de.wikipedia.org/wiki/Othello_(Spiel))\n", + "* Game strategy examples [https://de.wikipedia.org/wiki/Computer-Othello](https://de.wikipedia.org/wiki/Computer-Othello)\n", + "* Image for 8 directions [https://www.researchgate.net/journal/EURASIP-Journal-on-Image-and-Video-Processing-1687-5281](https://www.researchgate.net/journal/EURASIP-Journal-on-Image-and-Video-Processing-1687-5281)" + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [] -- 2.49.0 From edc5e78dc305584222b79bf3329cd9fe8d2c4b0b Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 14:06:46 +0100 Subject: [PATCH 11/31] Added a toc --- main.ipynb | 29 +++++++++++++++++++++++++---- 1 file changed, 25 insertions(+), 4 deletions(-) diff --git a/main.ipynb b/main.ipynb index 9fa3e38..6af3342 100644 --- a/main.ipynb +++ b/main.ipynb @@ -11,7 +11,25 @@ "Othello also known as reversi is a board game first published in 1883 by eiter Lewis Waterman or John W. Mollet in England (each one was denouncing the other as fraud).\n", "It is a strickt turn based zero-sum game with a clear Markov chain and now hidden states like in card games with an unknown distribution of cards or unknown player allegiance.\n", "There is like for the game go only one set of stones with two colors which is much easier to abstract than chess with its 6 unique pieces.\n", - "The game has a symmetrical game board wich allows to play with rotating the state around an axis to allow for a breaking of sequences or interesting ANN architectures, quadruple the data generation by simulation or interesting test cases where a symetry in turns should be observable if the AI reaches an \"objective\" policy.\n", + "The game has a symmetrical game board wich allows to play with rotating the state around an axis to allow for a breaking of sequences or interesting ANN architectures, quadruple the data generation by simulation or interesting test cases where a symetry in turns should be observable if the AI reaches an \"objective\" policy." + ] + }, + { + "cell_type": "markdown", + "source": [ + "\n", + "## Content\n", + "\n", + "* [The game rules](#the-game-rules) A short overview over the rules of the game.\n", + "* [Some common Otello strategies](#some-common-otello-strategies) introduces some easy approaches to a classic Otello AI and defines some behavioral expectations." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ "\n", "## The game rules\n", "\n", @@ -32,7 +50,7 @@ "\n", "![Startaufstellung.png](Startaufstellung.png)\n", "\n", - "## Some strategies\n", + "## Some common Othello strategies\n", "\n", "As can be easily understood the placement of stones and on the bord is always a careful balance of attack and defence.\n", "If the player occupies huge homogenous stretches on the board it can be attacked easier.\n", @@ -44,7 +62,10 @@ "The scores change in the course of the game and converges against one. This gives some indications of what to expect from an Othello AI.\n", "\n", "![ComputerPossitionScore](computer-score.png)\n" - ] + ], + "metadata": { + "collapsed": false + } }, { "cell_type": "code", @@ -167,7 +188,7 @@ "## Creating new boards\n", "\n", "The first function implemented and tested is a function to generate the starting environment as a stack of games.\n", - "As described above i simply placed a 2 by 2 square in the center of an empty stack of boards." + "As described above I simply placed a 2 by 2 square in the center of an empty stack of boards." ] }, { -- 2.49.0 From 218c2876cf80a11b65c4fde4e2ed391e3cf11948 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 14:32:24 +0100 Subject: [PATCH 12/31] Added a section abot imports and dependencies and some initial design decisions for the game. --- main.ipynb | 55 ++++++++++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 47 insertions(+), 8 deletions(-) diff --git a/main.ipynb b/main.ipynb index 6af3342..ad5161d 100644 --- a/main.ipynb +++ b/main.ipynb @@ -21,7 +21,9 @@ "## Content\n", "\n", "* [The game rules](#the-game-rules) A short overview over the rules of the game.\n", - "* [Some common Otello strategies](#some-common-otello-strategies) introduces some easy approaches to a classic Otello AI and defines some behavioral expectations." + "* [Some common Otello strategies](#some-common-otello-strategies) introduces some easy approaches to a classic Otello AI and defines some behavioral expectations.\n", + "* [Initial design decisions](#initial-design-decisions) an explanation about some initial design decision and assumptions\n", + "* [Imports and dependencies](#imports-and-dependencies) explains what libraries where used" ], "metadata": { "collapsed": false @@ -67,6 +69,23 @@ "collapsed": false } }, + { + "cell_type": "markdown", + "source": [ + "## Initial design decisions\n", + "\n", + "At the beginning of this project I made some design decisions.\n", + "The first onw was that I do not want to use a gym library because it limits the data formats accessible.\n", + "I choose to implement the hole game as entry in a stack in numpy arrays to be able to accommodate interfacing with a neural network easier and to use scipy pattern recognition tools to implement some game mechanics for a fast simulation cycle.\n", + "I chose to ignore player colors as far as I could instead a player perspective was used. Which allowed to change the perspective with a flipping of the sign. (multiplying with -1).\n", + "The array format should also allow for data multiplication or the breaking of strikt sequences by flipping the game along one the for axis, (horizontal, vertical, transpose along both diagonals).\n", + "\n", + "I wanted to implement different agents as classes that act on those game stacks." + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", "execution_count": 1, @@ -80,12 +99,32 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Imports" + "## Imports and dependencies\n", + "\n", + "The following direct dependencies where used for this project:\n", + "```toml\n", + "jupyter = \"^1.0.0\"\n", + "matplotlib = \"^3.6.3\"\n", + "numpy = \"^1.24.1\"\n", + "pytest = \"^7.2.1\"\n", + "python = \"3.10.*\"\n", + "scipy = \"^1.10.0\"\n", + "tqdm = \"^4.64.1\"\n", + "jupyterlab = \"^3.6.1\"\n", + "torchvision = \"^0.14.1\"\n", + "torchaudio = \"^0.13.1\"\n", + "```\n", + "* `Jupyter` and `jupyterlab` on pycharm was used as a IDE / Ipython was used to implement this code.\n", + "* `matplotlib` was used for visualisation and statistics.\n", + "* `numpy` was used for array support and mathematical functions\n", + "* `tqdm` was used for progress bars\n", + "* `scipy` contains fast pattern recognition tools for images. It was used to make an initial estimation about where possible turns should be.\n", + "* `torch` supplied the ANN functionalities." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -101,7 +140,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Constants" + "## Constants\n", + "\n", + "Some general constants needed to be defined. Such as board game size and Player and Enemy representations. Also, directional offsets and the initial placement of blocks." ] }, { @@ -112,7 +153,7 @@ "source": [ "BOARD_SIZE: Final[int] = 8 # defines the board side length as 8\n", "PLAYER: Final[int] = 1 # defines the number symbolising the player as 1\n", - "ENEMY: Final[int] = -1 # defines the number symbolising the enenemy as 1" + "ENEMY: Final[int] = -1 # defines the number symbolising the enemy as -1" ] }, { @@ -284,7 +325,7 @@ } ], "source": [ - "def plot_othello_board(board, ax=None):\n", + "def plot_othello_board(board, ax=None) -> None:\n", " \"\"\"Plots a single otello board.\n", "\n", " If a matplot axis object is given the board will be plotted into that axis. If not an axis object will be generated.\n", @@ -293,8 +334,6 @@ " board: The bord that should be plotted. Only a single games is allowed. A numpy array of the form 8x8 is expected.\n", " ax: If needed the\n", "\n", - " Returns:\n", - "\n", " \"\"\"\n", " plot_all = False\n", " if ax is None:\n", -- 2.49.0 From a837bc2d61c1c0ebe550136f9840b3efee330a0f Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 14:46:39 +0100 Subject: [PATCH 13/31] Added a docstring to the board plot function --- main.ipynb | 35 +++++++++++++++++++---------------- 1 file changed, 19 insertions(+), 16 deletions(-) diff --git a/main.ipynb b/main.ipynb index ad5161d..5b76f0e 100644 --- a/main.ipynb +++ b/main.ipynb @@ -80,7 +80,10 @@ "I chose to ignore player colors as far as I could instead a player perspective was used. Which allowed to change the perspective with a flipping of the sign. (multiplying with -1).\n", "The array format should also allow for data multiplication or the breaking of strikt sequences by flipping the game along one the for axis, (horizontal, vertical, transpose along both diagonals).\n", "\n", - "I wanted to implement different agents as classes that act on those game stacks." + "I wanted to implement different agents as classes that act on those game stacks.\n", + "\n", + "Since computation time is critical all computational have results are saved.\n", + "The analysis of those is then repeated in real time. If a recalculation of such a section is required the save file can be deleted and the code should be executed again." ], "metadata": { "collapsed": false @@ -124,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -147,7 +150,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -168,14 +171,14 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": "array([[-1, -1],\n [-1, 0],\n [-1, 1],\n [ 0, -1],\n [ 0, 1],\n [ 1, -1],\n [ 1, 0],\n [ 1, 1]])" }, - "execution_count": 26, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -200,13 +203,13 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 5, "outputs": [ { "data": { "text/plain": "array([[-1, 1],\n [ 1, -1]])" }, - "execution_count": 23, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -312,13 +315,13 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": "
", - "image/png": 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\n" + "image/png": "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\n" }, "metadata": {}, "output_type": "display_data" @@ -329,11 +332,11 @@ " \"\"\"Plots a single otello board.\n", "\n", " If a matplot axis object is given the board will be plotted into that axis. If not an axis object will be generated.\n", + " The image generated will be shown directly.\n", "\n", " Args:\n", " board: The bord that should be plotted. Only a single games is allowed. A numpy array of the form 8x8 is expected.\n", - " ax: If needed the\n", - "\n", + " ax: If needed a matplotlib axis object can be defined that is used to place the board as a sublot into a bigger context.\n", " \"\"\"\n", " plot_all = False\n", " if ax is None:\n", @@ -341,7 +344,7 @@ " plot_all = True\n", " fig, ax = plt.subplots(figsize=(fig_size, fig_size))\n", "\n", - " ax.set_facecolor(\"#006400\")\n", + " ax.set_facecolor(\"#66FF00\")\n", " for i in range(BOARD_SIZE):\n", " for j in range(BOARD_SIZE):\n", " if board[i, j] == -1:\n", @@ -691,7 +694,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "123 ms ± 4.08 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "110 ms ± 7.6 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { @@ -731,12 +734,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "10.8 s ± 339 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "9.34 s ± 430 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] 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-1., -1., ..., -1., -1., 1.],\n [-1., -1., 1., ..., -1., -1., 1.],\n ...,\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.]],\n \n [[-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., 1., -1., ..., 1., -1., -1.],\n ...,\n [ 1., 1., 1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n ...,\n \n [[-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n ...,\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[-1., -1., -1., ..., -1., 1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., -1., 1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., -1., 1.],\n ...,\n [-1., -1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., -1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]]],\n \n \n [[[ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., -1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., 1., 1., -1.],\n [-1., -1., -1., ..., -1., 1., -1.],\n [-1., -1., -1., ..., 1., 1., 1.]],\n \n [[-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., 1.],\n [-1., -1., 1., ..., -1., -1., 1.],\n ...,\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.]],\n \n [[-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., 1., -1., ..., 1., -1., -1.],\n ...,\n [ 1., 1., 1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n ...,\n \n [[-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n ...,\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[-1., -1., -1., ..., -1., 1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., -1., 1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., -1., 1.],\n ...,\n [-1., -1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., -1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]]],\n \n \n [[[ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., -1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., 1., 1., -1.],\n [-1., -1., -1., ..., -1., 1., -1.],\n [-1., -1., -1., ..., 1., 1., 1.]],\n \n [[-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., 1.],\n [-1., -1., 1., ..., -1., -1., 1.],\n ...,\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.]],\n \n [[-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., 1., -1., ..., 1., -1., -1.],\n ...,\n [ 1., 1., 1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n ...,\n \n [[-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n ...,\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[-1., -1., -1., ..., -1., 1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., -1., 1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., -1., 1.],\n ...,\n [-1., -1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., -1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]]]]),\n array([[[ 3., 5.],\n [ 5., 3.],\n [ 5., 3.],\n ...,\n [ 5., 3.],\n [ 5., 3.],\n [ 3., 5.]],\n \n [[ 2., 3.],\n [ 5., 4.],\n [ 5., 4.],\n ...,\n [ 5., 4.],\n [ 5., 4.],\n [ 4., 5.]],\n \n [[ 3., 2.],\n [ 6., 5.],\n [ 3., 5.],\n ...,\n [ 2., 5.],\n [ 5., 5.],\n [ 5., 6.]],\n \n ...,\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]],\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]],\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]]]))" }, "execution_count": 19, "metadata": {}, @@ -1040,7 +1043,7 @@ { "data": { "text/plain": "
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\n" 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zPZJET@6^lh{PmYo+O{1L>f=VxbaXIpGBnNBgE^a*`goF|cRRx)rtz(K#XeBodd1qW ziT=OVu4c!H7zW#Ml9|q`2-ph}LgM`&4EDeQD4m&2Vw;1LG}C1f2YRfks%ldw`F<4u zd`c;V5CahrHa^M9#zrj3egh)PDfQ$qyJ6hIv)gjFwbE0#oO9DO$EZz_%%zm4r>{>> zUsBr7=eMWRA|f$PkB^UW4(IcmlJdT9B4v4)f)Bs0KYSqa==5$jAh`gdirxSWdr}lZ z1f62TksLvi%*=+On({uE=TZt{nCF>}p4tkD1fQ#2-Lx#NOcXqtb*P(ov5te6P3N`? zU)R;%)hx-jlamG5yp3~)W>80Qw zKYm)42fMb$7>Ow5=ajbZ-@lboVvOV=r40b4X)>f%ITNA5_QGaaMiEg|qN+G3!h#MR z6;*^pR;dbwg$ox%SF(wUK^PG+h7e<1_f$#siuj_#-~dX=iZ@eh>t)t1yRzdoAevrD zkrhR%-c~vrno6yKaLxgc2&HX_{0u=WK+ljokia-56$9RdU|b_4;euRz&>y z^K!jj9v;r`-o5|u`NO)deT>yuS56{jo`cnD=d`IRkq3Yf=6&ChWu9k5NGS<}5xPcI zIEU!GfW-iT_m Date: Sun, 12 Feb 2023 16:35:53 +0100 Subject: [PATCH 15/31] Added a text implementing the search for possible turns. --- main.ipynb | 48 +++++++++++++++++++++++++++++++++++++++++------- 1 file changed, 41 insertions(+), 7 deletions(-) diff --git a/main.ipynb b/main.ipynb index 5b76f0e..31c7575 100644 --- a/main.ipynb +++ b/main.ipynb @@ -391,6 +391,27 @@ " plt.show()" ] }, + { + "cell_type": "markdown", + "source": [ + "## Find possible actions to take\n", + "\n", + "The frist step in the implementation of an AI like this is to get an overview over the possible actions that can be taken in a situation.\n", + "Here was the design choice taken to first find fields that are empty and have at least one neighbouring enemy stone.\n", + "This was implemented with element wise check for a stone and a binary dilation marking all fields neighboring an enemy stone.\n", + "For that the `SURROUNDING` mask was used. Both aries are then element wise combined using and.\n", + "The resulting array contains all filed where a turn could potentially be made. Those are then check in detail.\n", + "The previous element wise operations on the numpy array increase the spead for this operation dramatically.\n", + "\n", + "The check for a possible turn is done in detail by following each direction step by step as long as there are enemy stones in that direction.\n", + "If the board end is reached or en empty filed before reaching a field occupied by the player that direction does not surround enemy stones.\n", + "If one direction surrounds enemy stone a turn is possible.\n", + "This detailed step is implemented as a recursion and need to go at leas one step to return True." + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", "execution_count": 10, @@ -408,7 +429,9 @@ } ], "source": [ - "SURROUNDING: Final = np.array([[[1, 1, 1], [1, 0, 1], [1, 1, 1]]])\n", + "SURROUNDING: Final = np.array(\n", + " [[[1, 1, 1], [1, 0, 1], [1, 1, 1]]]\n", + ") # defines the binary dilation mask to check if a field is next to an enemy stones\n", "SURROUNDING" ] }, @@ -427,15 +450,26 @@ } ], "source": [ - "def recursive_steps(_array, rec_direction, rec_position, step_one=True) -> bool:\n", + "def _recursive_steps(board, rec_direction, rec_position, step_one=True) -> bool:\n", + " \"\"\"Check if a player can place a stone on the board specified in the direction specified and direction specified.\n", + "\n", + " Args:\n", + " board: The board that should be checked for a playable action.\n", + " rec_direction: The direction that should be checked.\n", + " rec_position: The position that should be checked.\n", + " step_one:\n", + "\n", + " Returns:\n", + "\n", + " \"\"\"\n", " rec_position = rec_position + rec_direction\n", " if np.any((rec_position >= BOARD_SIZE) | (rec_position < 0)):\n", " return False\n", - " next_field = _array[tuple(rec_position.tolist())]\n", + " next_field = board[tuple(rec_position.tolist())]\n", " if next_field == 0:\n", " return False\n", " if next_field == -1:\n", - " return recursive_steps(_array, rec_direction, rec_position, step_one=False)\n", + " return _recursive_steps(board, rec_direction, rec_position, step_one=False)\n", " if next_field == 1:\n", " return not step_one\n", "\n", @@ -456,7 +490,7 @@ " position = idx, idy\n", " if _poss_turns[game, idx, idy]:\n", " _poss_turns[game, idx, idy] = any(\n", - " recursive_steps(boards[game, :, :], direction, position)\n", + " _recursive_steps(boards[game, :, :], direction, position)\n", " for direction in DIRECTIONS\n", " )\n", " return _poss_turns\n", @@ -512,7 +546,7 @@ " if np.all(move == -1):\n", " return not np.any(get_possible_turns(np.reshape(board, (1, 8, 8))))\n", " return any(\n", - " recursive_steps(board[:, :], direction, move) for direction in DIRECTIONS\n", + " _recursive_steps(board[:, :], direction, move) for direction in DIRECTIONS\n", " )\n", "\n", "\n", @@ -540,7 +574,7 @@ " )\n", " else:\n", " arr_moves_possible[game] = any(\n", - " recursive_steps(boards[game, :, :], direction, moves[game])\n", + " _recursive_steps(boards[game, :, :], direction, moves[game])\n", " for direction in DIRECTIONS\n", " )\n", " return arr_moves_possible\n", -- 2.49.0 From 108ea026b106b616953fd9ecbfb593ce62821242 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 16:53:08 +0100 Subject: [PATCH 16/31] Reformatted the function checking for possible turns. --- main.ipynb | 170 ++++++++++++++++++++--------------------------------- 1 file changed, 64 insertions(+), 106 deletions(-) diff --git a/main.ipynb b/main.ipynb index 31c7575..c760046 100644 --- a/main.ipynb +++ b/main.ipynb @@ -95,6 +95,7 @@ "metadata": {}, "outputs": [], "source": [ + "\n", "%load_ext blackcellmagic" ] }, @@ -131,6 +132,7 @@ "metadata": {}, "outputs": [], "source": [ + "import itertools\n", "import numpy as np\n", "import abc\n", "from typing import Final\n", @@ -315,7 +317,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -437,14 +439,22 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 16, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8.78 ms ± 868 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "82.7 ms ± 585 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + ] + }, { "data": { "text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])" }, - "execution_count": 11, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -457,10 +467,10 @@ " board: The board that should be checked for a playable action.\n", " rec_direction: The direction that should be checked.\n", " rec_position: The position that should be checked.\n", - " step_one:\n", + " step_one: Defines if the call of this function is the firs or not. Should be kept to the default value for proper functionality.\n", "\n", " Returns:\n", - "\n", + " True if a turn is possible for possition and direction on the board defined.\n", " \"\"\"\n", " rec_position = rec_position + rec_direction\n", " if np.any((rec_position >= BOARD_SIZE) | (rec_position < 0)):\n", @@ -475,49 +485,43 @@ "\n", "\n", "def get_possible_turns(boards: np.ndarray) -> np.ndarray:\n", - " try:\n", - " _poss_turns = boards == 0\n", - " _poss_turns &= binary_dilation(boards == -1, SURROUNDING)\n", - " except RuntimeError as err:\n", - " print(boards)\n", - " print(boards == -1)\n", - " print(\"err\")\n", - " raise err\n", - " for game in range(boards.shape[0]):\n", - " for idx in range(BOARD_SIZE):\n", - " for idy in range(BOARD_SIZE):\n", + " \"\"\"Check where turns are possible on a board.\n", "\n", - " position = idx, idy\n", - " if _poss_turns[game, idx, idy]:\n", - " _poss_turns[game, idx, idy] = any(\n", - " _recursive_steps(boards[game, :, :], direction, position)\n", - " for direction in DIRECTIONS\n", - " )\n", + " Args:\n", + " boards: A stack of boards to check.\n", + "\n", + " Returns:\n", + " A stack of game boards containing boolean values showing where turns are possible for the player.\n", + " \"\"\"\n", + " _poss_turns = boards == 0 # checks where fields are empty.\n", + " _poss_turns &= binary_dilation(\n", + " boards == -1, SURROUNDING\n", + " ) # checks where fields are next to an enemy filed an empty\n", + " for game, idx, idy in itertools.product(\n", + " range(boards.shape[0]), range(BOARD_SIZE), range(BOARD_SIZE)\n", + " ):\n", + " position = idx, idy\n", + " if _poss_turns[game, idx, idy]:\n", + " _poss_turns[game, idx, idy] = any(\n", + " _recursive_steps(boards[game, :, :], direction, position)\n", + " for direction in DIRECTIONS\n", + " )\n", " return _poss_turns\n", "\n", "\n", - "# %timeit get_possible_turns(get_new_games(10))\n", - "# %timeit get_possible_turns(get_new_games(100))\n", - "get_possible_turns(get_new_games(3))[:1]" + "%timeit get_possible_turns(get_new_games(10)) # checks turn possibility evaluation time for 10 initial games\n", + "%timeit get_possible_turns(get_new_games(100)) # check turn possibility evaluation time for 100 initial games\n", + "get_possible_turns(get_new_games(3))[:1] # shows a singe game" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": "(array([2, 2, 2]), array([2, 2, 2]))" - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "def board_evaluation_final(array: np.ndarray):\n", - " score1, score2 = np.sum(array == 1, axis=(1, 2)), np.sum(array == -1, axis=(1, 2))\n", + "def board_evaluation_final(boards: np.ndarray) -> tuple[np.ndarray, np.ndarray]:\n", + " score1, score2 = np.sum(boards == 1, axis=(1, 2)), np.sum(boards == -1, axis=(1, 2))\n", " player_1_won = score1 > score2\n", " player_2_won = score1 < score2\n", " score1_final = 64 - score2[player_1_won]\n", @@ -527,18 +531,22 @@ " return score1, score2\n", "\n", "\n", - "def board_evaluation(array: np.ndarray):\n", - " score1, score2 = np.sum(array == 1, axis=(1, 2)), np.sum(array == -1, axis=(1, 2))\n", + "def board_evaluation(boards: np.ndarray) -> tuple[np.ndarray, np.ndarray]:\n", + " score1, score2 = np.sum(boards == 1, axis=(1, 2)), np.sum(boards == -1, axis=(1, 2))\n", " return score1, score2\n", "\n", "\n", + "def board_score(boards: np.ndarray) -> tuple[np.ndarray]:\n", + " return np.sign(np.sum(boards, axis=(1, 2)))\n", + "\n", + "\n", "board_evaluation(get_new_games(3))\n", "board_evaluation_final(get_new_games(3))" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -561,7 +569,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -605,18 +613,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 1, 0, 0, 0, 0],\n [ 0, 0, 0, 1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])" - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "class InvalidTurn(ValueError):\n", " pass\n", @@ -664,7 +663,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -698,7 +697,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -721,25 +720,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "110 ms ± 7.6 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" - ] - }, - { - "data": { - "text/plain": "array([[[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n ...,\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, 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-1., -1., ..., -1., -1., -1.]],\n \n [[-1., -1., -1., ..., -1., 1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., -1., 1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., -1., 1.],\n ...,\n [-1., -1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., -1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]]],\n \n \n [[[ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., -1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., 1., 1., -1.],\n [-1., -1., -1., ..., -1., 1., -1.],\n [-1., -1., -1., ..., 1., 1., 1.]],\n \n [[-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., 1.],\n [-1., -1., 1., ..., -1., -1., 1.],\n ...,\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.]],\n \n [[-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., 1., -1., ..., 1., -1., -1.],\n ...,\n [ 1., 1., 1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n ...,\n \n [[-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n ...,\n [-1., -1., -1., ..., -1., -1., -1.],\n [-1., -1., 1., ..., -1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[-1., -1., -1., ..., -1., 1., -1.],\n [ 1., 1., 1., ..., 1., 1., -1.],\n [-1., 1., 1., ..., -1., 1., -1.],\n ...,\n [-1., 1., -1., ..., -1., 1., -1.],\n [-1., -1., 1., ..., 1., -1., -1.],\n [-1., -1., -1., ..., -1., -1., -1.]],\n \n [[ 1., 1., 1., ..., 1., 1., 1.],\n [-1., -1., -1., ..., -1., 1., 1.],\n [-1., -1., -1., ..., 1., -1., 1.],\n ...,\n [-1., -1., 1., ..., 1., 1., 1.],\n [ 1., 1., 1., ..., -1., 1., 1.],\n [ 1., 1., 1., ..., 1., 1., 1.]]]]),\n array([[[ 3., 5.],\n [ 5., 3.],\n [ 5., 3.],\n ...,\n [ 5., 3.],\n [ 5., 3.],\n [ 3., 5.]],\n \n [[ 2., 3.],\n [ 5., 4.],\n [ 5., 4.],\n ...,\n [ 5., 4.],\n [ 5., 4.],\n [ 4., 5.]],\n \n [[ 3., 2.],\n [ 6., 5.],\n [ 3., 5.],\n ...,\n [ 2., 5.],\n [ 5., 5.],\n [ 5., 6.]],\n \n ...,\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]],\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]],\n \n [[-1., -1.],\n [-1., -1.],\n [-1., -1.],\n ...,\n [-1., -1.],\n [-1., -1.],\n [-1., -1.]]]))" - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "SIMULATE_TURNS = 70\n", "\n", @@ -813,14 +780,14 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1071,25 +1038,16 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": "
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\n" - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plot_othello_boards(create_test_game()[-3:])" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1110,7 +1068,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": {}, "outputs": [], "source": [] -- 2.49.0 From a9e65564c43b27c3d8ea5f3a75af7d7022f50c8b Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 18:03:54 +0100 Subject: [PATCH 17/31] Added a docstring to the plot_boards function. --- main.ipynb | 42 ++++++++++++++++++++++++++++-------------- 1 file changed, 28 insertions(+), 14 deletions(-) diff --git a/main.ipynb b/main.ipynb index c760046..51c4e53 100644 --- a/main.ipynb +++ b/main.ipynb @@ -309,7 +309,8 @@ "## Visualisation tools\n", "\n", "In this section a visualisation help was implemented for debugging of the game and a proper display of the results.\n", - "For this visualisation ChatGPT was used as a prompted code generator that was later reviewed and refactored by hand to integrate seamlessly into the project as a whole." + "For this visualisation ChatGPT was used as a prompted code generator that was later reviewed and refactored by hand to integrate seamlessly into the project as a whole.\n", + "White stones represent the player, black stones the enemy. A single plot can be used as a subplot when the `ax` argument is used." ], "metadata": { "collapsed": false @@ -340,6 +341,7 @@ " board: The bord that should be plotted. Only a single games is allowed. A numpy array of the form 8x8 is expected.\n", " ax: If needed a matplotlib axis object can be defined that is used to place the board as a sublot into a bigger context.\n", " \"\"\"\n", + " assert board.shape == (8, 8)\n", " plot_all = False\n", " if ax is None:\n", " fig_size = 3\n", @@ -347,18 +349,17 @@ " fig, ax = plt.subplots(figsize=(fig_size, fig_size))\n", "\n", " ax.set_facecolor(\"#66FF00\")\n", - " for i in range(BOARD_SIZE):\n", - " for j in range(BOARD_SIZE):\n", - " if board[i, j] == -1:\n", - " color = \"white\"\n", - " elif board[i, j] == 1:\n", - " color = \"black\"\n", - " else:\n", - " continue\n", - " ax.scatter(j, i, s=300 if plot_all else 150, c=color)\n", - " for i in range(-1, 8):\n", - " ax.axhline(i + 0.5, color=\"black\", lw=2)\n", - " ax.axvline(i + 0.5, color=\"black\", lw=2)\n", + " for x_pos, y_pos in itertools.product(range(BOARD_SIZE), range(BOARD_SIZE)):\n", + " if board[x_pos, y_pos] == -1:\n", + " color = \"white\"\n", + " elif board[x_pos, y_pos] == 1:\n", + " color = \"black\"\n", + " else:\n", + " continue\n", + " ax.scatter(y_pos, x_pos, s=300 if plot_all else 150, c=color)\n", + " for x_pos in range(-1, 8):\n", + " ax.axhline(x_pos + 0.5, color=\"black\", lw=2)\n", + " ax.axvline(x_pos + 0.5, color=\"black\", lw=2)\n", " ax.set_xlim(-0.5, 7.5)\n", " ax.set_ylim(7.5, -0.5)\n", " ax.set_xticks(np.arange(8))\n", @@ -380,7 +381,17 @@ "outputs": [], "source": [ "def plot_othello_boards(boards: np.ndarray) -> None:\n", + " \"\"\"Plots multiple boards into subplots.\n", + "\n", + " The plots are shown directly.\n", + "\n", + " Args:\n", + " boards: Plots the boards given into subplots. The maximum number of boards accepted is 70.\n", + " \"\"\"\n", + " assert len(boards.shape) == 3\n", + " assert boards.shape[1:] == (BOARD_SIZE, BOARD_SIZE)\n", " assert boards.shape[0] < 70\n", + "\n", " plots_per_row = 4\n", " rows = int(np.ceil(boards.shape[0] / plots_per_row))\n", " fig, axs = plt.subplots(rows, plots_per_row, figsize=(12, 3 * rows))\n", @@ -485,7 +496,7 @@ "\n", "\n", "def get_possible_turns(boards: np.ndarray) -> np.ndarray:\n", - " \"\"\"Check where turns are possible on a board.\n", + " \"\"\"Analyses a stack of boards.\n", "\n", " Args:\n", " boards: A stack of boards to check.\n", @@ -493,6 +504,9 @@ " Returns:\n", " A stack of game boards containing boolean values showing where turns are possible for the player.\n", " \"\"\"\n", + " assert len(boards.shape) == 3\n", + " assert boards.shape[:2] == (BOARD_SIZE, BOARD_SIZE)\n", + "\n", " _poss_turns = boards == 0 # checks where fields are empty.\n", " _poss_turns &= binary_dilation(\n", " boards == -1, SURROUNDING\n", -- 2.49.0 From fc7f9dbb4d143dbd586f2a62865db6e216163609 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 18:54:28 +0100 Subject: [PATCH 18/31] Added a docstring to the function checking if a move is possible. --- main.ipynb | 166 +++++++++++++++++++++++++++++++++++++++++------------ 1 file changed, 129 insertions(+), 37 deletions(-) diff --git a/main.ipynb b/main.ipynb index 51c4e53..d350229 100644 --- a/main.ipynb +++ b/main.ipynb @@ -152,13 +152,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "BOARD_SIZE: Final[int] = 8 # defines the board side length as 8\n", "PLAYER: Final[int] = 1 # defines the number symbolising the player as 1\n", - "ENEMY: Final[int] = -1 # defines the number symbolising the enemy as -1" + "ENEMY: Final[int] = -1 # defines the number symbolising the enemy as -1\n", + "EXAMPLE_STACK_SIZE: Final[int] = 1000 # defines the game stack size for examples" ] }, { @@ -450,22 +451,22 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "8.78 ms ± 868 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "82.7 ms ± 585 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "9.43 ms ± 1 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "1 s ± 179 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { "data": { "text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])" }, - "execution_count": 16, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -504,8 +505,11 @@ " Returns:\n", " A stack of game boards containing boolean values showing where turns are possible for the player.\n", " \"\"\"\n", - " assert len(boards.shape) == 3\n", - " assert boards.shape[:2] == (BOARD_SIZE, BOARD_SIZE)\n", + " assert len(boards.shape) == 3, \"The number fo input dimensions does not fit.\"\n", + " assert boards.shape[1:] == (\n", + " BOARD_SIZE,\n", + " BOARD_SIZE,\n", + " ), \"The input dimensions do not fit.\"\n", "\n", " _poss_turns = boards == 0 # checks where fields are empty.\n", " _poss_turns &= binary_dilation(\n", @@ -523,40 +527,31 @@ " return _poss_turns\n", "\n", "\n", + "# some simple testing to ensure the function works after simple changes\n", + "# this testing is complete, its more of a smoke-test\n", + "test_array = get_new_games(3)\n", + "expected_result = np.zeros_like(test_array, dtype=bool)\n", + "expected_result[:, 4, 5] = expected_result[:, 2, 3] = True\n", + "expected_result[:, 5, 4] = expected_result[:, 3, 2] = True\n", + "np.testing.assert_equal(get_possible_turns(test_array), expected_result)\n", + "\n", + "\n", "%timeit get_possible_turns(get_new_games(10)) # checks turn possibility evaluation time for 10 initial games\n", - "%timeit get_possible_turns(get_new_games(100)) # check turn possibility evaluation time for 100 initial games\n", - "get_possible_turns(get_new_games(3))[:1] # shows a singe game" + "%timeit get_possible_turns(get_new_games(EXAMPLE_STACK_SIZE)) # check turn possibility evaluation time for EXAMPLE_STACK_SIZE initial games\n", + "\n", + "# shows a singe game\n", + "get_possible_turns(get_new_games(3))[:1]" ] }, { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "cell_type": "markdown", "source": [ - "def board_evaluation_final(boards: np.ndarray) -> tuple[np.ndarray, np.ndarray]:\n", - " score1, score2 = np.sum(boards == 1, axis=(1, 2)), np.sum(boards == -1, axis=(1, 2))\n", - " player_1_won = score1 > score2\n", - " player_2_won = score1 < score2\n", - " score1_final = 64 - score2[player_1_won]\n", - " score2_final = 64 - score1[player_2_won]\n", - " score1[player_1_won] = score1_final\n", - " score2[player_2_won] = score2_final\n", - " return score1, score2\n", - "\n", - "\n", - "def board_evaluation(boards: np.ndarray) -> tuple[np.ndarray, np.ndarray]:\n", - " score1, score2 = np.sum(boards == 1, axis=(1, 2)), np.sum(boards == -1, axis=(1, 2))\n", - " return score1, score2\n", - "\n", - "\n", - "def board_score(boards: np.ndarray) -> tuple[np.ndarray]:\n", - " return np.sign(np.sum(boards, axis=(1, 2)))\n", - "\n", - "\n", - "board_evaluation(get_new_games(3))\n", - "board_evaluation_final(get_new_games(3))" - ] + "Besides the ability to generate an array of possible turns there needs to be a functions that check if a given turn is possible.\n", + "On is needed for the action space validation. The other is for validating a players turn." + ], + "metadata": { + "collapsed": false + } }, { "cell_type": "code", @@ -565,6 +560,17 @@ "outputs": [], "source": [ "def move_possible(board: np.ndarray, move: np.ndarray) -> bool:\n", + " \"\"\"Checks if a turn is possible.\n", + "\n", + " Checks if a turn is possible. If no turn is possible to input array [-1, -1] is expected.\n", + "\n", + " Args:\n", + " board: A board where it should be checkt if a turn is possible.\n", + " move: The move that should be taken. Expected is the index of the filed where a stone should be placed [x, y]. If no placement is possible [-1, -1] is expected as an input.\n", + "\n", + " Returns:\n", + " True if the move is possible\n", + " \"\"\"\n", " if np.all(move == -1):\n", " return not np.any(get_possible_turns(np.reshape(board, (1, 8, 8))))\n", " return any(\n", @@ -572,6 +578,7 @@ " )\n", "\n", "\n", + "# Some testing for this function and the underlying recursive functions that are called.\n", "assert move_possible(get_new_games(1)[0], np.array([2, 3])) is True\n", "assert move_possible(get_new_games(1)[0], np.array([3, 2])) is True\n", "assert move_possible(get_new_games(1)[0], np.array([2, 2])) is False\n", @@ -581,6 +588,91 @@ "assert move_possible(np.ones((8, 8)) * 0, np.array([-1, -1])) is True" ] }, + { + "cell_type": "markdown", + "source": [ + "## Reword functions\n", + "\n", + "For any kind of reinforcement learning is a reword function needed. For otello this would be the final score, the information who won or changes to the score. A combination of those three would also be possible.\n", + "It is probably not be possible to weight the current score to high in a reword function since that would be to close to a classic greedy algorithm. But some influce would increase learning behavior.\n", + "In the next section are all three reword functions implemented to be combined and weight later on as needed." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 24, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "177 µs ± 3.97 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "29.7 µs ± 106 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "31.2 µs ± 269 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" + ] + } + ], + "source": [ + "def final_boards_evaluation(boards: np.ndarray) -> np.ndarray:\n", + " \"\"\"Evaluates the board at the end of the game.\n", + "\n", + " All unused fields are added to the score of the player that has more stones with his color up.\n", + " This score only applies to the end of the game.\n", + " Normally the score is represented by the number of stones each player has.\n", + " In this case the score was combined by building the difference.\n", + "\n", + " Args:\n", + " boards: A stack of game bords ot the end of the game.\n", + "\n", + " Returns:\n", + " the combined score for both player.\n", + " \"\"\"\n", + " score1, score2 = np.sum(boards == 1, axis=(1, 2)), np.sum(boards == -1, axis=(1, 2))\n", + " player_1_won = score1 > score2\n", + " player_2_won = score1 < score2\n", + " score1_final = 64 - score2[player_1_won]\n", + " score2_final = 64 - score1[player_2_won]\n", + " score1[player_1_won] = score1_final\n", + " score2[player_2_won] = score2_final\n", + " return score1 - score2\n", + "\n", + "\n", + "def evaluate_boards(boards: np.ndarray) -> np.ndarray:\n", + " \"\"\"Counts the stones each player has on the board.\n", + "\n", + " Args:\n", + " boards: A stack of boards for evaluation.\n", + "\n", + " Returns:\n", + " the combined score for both player.\n", + " \"\"\"\n", + " return np.sum(boards, axis=(1, 2))\n", + "\n", + "\n", + "def evaluate_who_won(boards: np.ndarray) -> np.ndarray:\n", + " \"\"\"Checks who won or is winning a game.\n", + "\n", + " Args:\n", + " boards: A stack of boards for evaluation.\n", + "\n", + " Returns:\n", + " The information who won for both player. 1 meaning the player won, -1 means the opponent lost. 0 represents a patt.\n", + " \"\"\"\n", + " return np.sign(np.sum(boards, axis=(1, 2)))\n", + "\n", + "\n", + "_boards = get_new_games(EXAMPLE_STACK_SIZE)\n", + "%timeit final_boards_evaluation(_boards)\n", + "%timeit evaluate_boards(_boards)\n", + "%timeit evaluate_who_won(_boards)" + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", "execution_count": null, -- 2.49.0 From 115f0c3195c1a26517a08f69b5d9bb8166645821 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 20:05:48 +0100 Subject: [PATCH 19/31] Moved the function that checks a whole stack of actions if they are possible on a stack of boards. --- main.ipynb | 263 +++++++++++++++++++++++++++++++++++++++++------------ 1 file changed, 204 insertions(+), 59 deletions(-) diff --git a/main.ipynb b/main.ipynb index d350229..c196bde 100644 --- a/main.ipynb +++ b/main.ipynb @@ -159,7 +159,10 @@ "BOARD_SIZE: Final[int] = 8 # defines the board side length as 8\n", "PLAYER: Final[int] = 1 # defines the number symbolising the player as 1\n", "ENEMY: Final[int] = -1 # defines the number symbolising the enemy as -1\n", - "EXAMPLE_STACK_SIZE: Final[int] = 1000 # defines the game stack size for examples" + "EXAMPLE_STACK_SIZE: Final[int] = 1000 # defines the game stack size for examples\n", + "IMPOSSIBLE: Final[np.ndarray] = np.array([-1, -1], dtype=int)\n", + "IMPOSSIBLE.setflags(write=False)\n", + "SIMULATE_TURNS: Final[int] = 70" ] }, { @@ -588,13 +591,71 @@ "assert move_possible(np.ones((8, 8)) * 0, np.array([-1, -1])) is True" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def moves_possible(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", + " \"\"\"Checks if a stack of moves can be executed on a stack of boards.\n", + "\n", + " Args:\n", + " boards: A board where the next stone should be placed.\n", + " moves: A stack stones to be placed. Each move is formatted as an array in the form of [x, y] if no turn is possible the value [-1, -1] is expected.\n", + "\n", + " Returns:\n", + " An array marking for each and every game and move in the stack if the move can be executed.\n", + " \"\"\"\n", + " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", + " for game in range(boards.shape[0]):\n", + " if np.all(\n", + " moves[game] == -1\n", + " ): # can be all or any. All should be faster since most times neither value will be -1.\n", + " arr_moves_possible[game] = not np.any(\n", + " get_possible_turns(np.reshape(boards[game], (1, 8, 8)))\n", + " )\n", + " else:\n", + " arr_moves_possible[game] = any(\n", + " _recursive_steps(boards[game, :, :], direction, moves[game])\n", + " for direction in DIRECTIONS\n", + " )\n", + " return arr_moves_possible\n", + "\n", + "\n", + "np.testing.assert_array_equal(\n", + " moves_possible(np.ones((3, 8, 8)) * 1, np.array([[-1, -1]] * 3)),\n", + " np.array([True] * 3),\n", + ")\n", + "\n", + "np.testing.assert_array_equal(\n", + " moves_possible(get_new_games(3), np.array([[2, 3], [3, 2], [3, 2]])),\n", + " np.array([True] * 3),\n", + ")\n", + "np.testing.assert_array_equal(\n", + " moves_possible(get_new_games(3), np.array([[2, 2], [1, 1], [0, 0]])),\n", + " np.array([False] * 3),\n", + ")\n", + "np.testing.assert_array_equal(\n", + " moves_possible(np.ones((3, 8, 8)) * -1, np.array([[-1, -1]] * 3)),\n", + " np.array([True] * 3),\n", + ")\n", + "np.testing.assert_array_equal(\n", + " moves_possible(np.zeros((3, 8, 8)), np.array([[-1, -1]] * 3)),\n", + " np.array([True] * 3),\n", + ")" + ] + }, { "cell_type": "markdown", "source": [ "## Reword functions\n", "\n", - "For any kind of reinforcement learning is a reword function needed. For otello this would be the final score, the information who won or changes to the score. A combination of those three would also be possible.\n", - "It is probably not be possible to weight the current score to high in a reword function since that would be to close to a classic greedy algorithm. But some influce would increase learning behavior.\n", + "For any kind of reinforcement learning is a reword function needed.\n", + "For otello this would be the final score, the information who won or changes to the score.\n", + "A combination of those three would also be possible.\n", + "It is probably not be possible to weight the current score to high in a reword function since that would be to close to a classic greedy algorithm.\n", + "But some direct influence would increase the learning speed.\n", "In the next section are all three reword functions implemented to be combined and weight later on as needed." ], "metadata": { @@ -674,48 +735,16 @@ } }, { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "cell_type": "markdown", "source": [ - "def moves_possible(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", - " arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n", - " for game in range(boards.shape[0]):\n", - " if np.all(moves[game] == -1):\n", - " arr_moves_possible[game] = not np.any(\n", - " get_possible_turns(np.reshape(boards[game], (1, 8, 8)))\n", - " )\n", - " else:\n", - " arr_moves_possible[game] = any(\n", - " _recursive_steps(boards[game, :, :], direction, moves[game])\n", - " for direction in DIRECTIONS\n", - " )\n", - " return arr_moves_possible\n", + "## Execute a chosen action\n", "\n", - "\n", - "np.testing.assert_array_equal(\n", - " moves_possible(np.ones((3, 8, 8)) * 1, np.array([[-1, -1]] * 3)),\n", - " np.array([True] * 3),\n", - ")\n", - "\n", - "np.testing.assert_array_equal(\n", - " moves_possible(get_new_games(3), np.array([[2, 3], [3, 2], [3, 2]])),\n", - " np.array([True] * 3),\n", - ")\n", - "np.testing.assert_array_equal(\n", - " moves_possible(get_new_games(3), np.array([[2, 2], [1, 1], [0, 0]])),\n", - " np.array([False] * 3),\n", - ")\n", - "np.testing.assert_array_equal(\n", - " moves_possible(np.ones((3, 8, 8)) * -1, np.array([[-1, -1]] * 3)),\n", - " np.array([True] * 3),\n", - ")\n", - "np.testing.assert_array_equal(\n", - " moves_possible(np.zeros((3, 8, 8)), np.array([[-1, -1]] * 3)),\n", - " np.array([True] * 3),\n", - ")" - ] + "After an evaluation what turns are possible there needs to be a function that executes a turn.\n", + "This next sections does that." + ], + "metadata": { + "collapsed": false + } }, { "cell_type": "code", @@ -724,13 +753,60 @@ "outputs": [], "source": [ "class InvalidTurn(ValueError):\n", - " pass\n", - "\n", - "\n", + " \"\"\"\n", + " This error is thrown if a given turn is not valid.\n", + " \"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "95.1 ms ± 3.5 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + ] + }, + { + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ "def do_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", + " \"\"\"Executes a single move on a stack o Othello boards.\n", + "\n", + " Args:\n", + " boards: A stack of Othello boards where the next stone should be placed.\n", + " moves: A stack of stone placement orders for the game. Formatted as coordinates in an array [x, y] of the place where the stone should be placed. Should contain [-1,-1] if no new placement is possible.\n", + "\n", + " Returns:\n", + " The new state of the board.\n", + " \"\"\"\n", + "\n", " def _do_directional_move(\n", " board: np.ndarray, rec_move: np.ndarray, rev_direction, step_one=True\n", " ) -> bool:\n", + " \"\"\"Changes the color of enemy stones in one direction.\n", + "\n", + " This function works recursive. The argument step_one should always be used in its default value.\n", + "\n", + " Args:\n", + " board: A bord on which a stone was placed.\n", + " rec_move: The position on the board in x and y where this function is called from. Will be moved by recursive called.\n", + " rev_direction: The position where the stone was placed. Inside this recursion it will also be the last step that was checked.\n", + " step_one: Set to true if this is the first step in the recursion. False later on.\n", + "\n", + " Returns:\n", + " True if a stone could be flipped.\n", + " All changes are made on the view of the numpy array and therefore not included in the return value.\n", + " \"\"\"\n", " rec_position = rec_move + rev_direction\n", " if np.any((rec_position >= 8) | (rec_position < 0)):\n", " return False\n", @@ -746,16 +822,32 @@ " return False\n", "\n", " def _do_move(_board: np.ndarray, move: np.ndarray) -> None:\n", + " \"\"\"Executes a turn on a board.\n", + "\n", + " Args:\n", + " _board: The game board on wich to place a stone.\n", + " move: The coordinates of a stone that should be placed. Should be formatted as an array of the form [x, y]. The value [-1, -1] is expected if no turn is possible.\n", + "\n", + " Returns:\n", + " All changes are made on the view of the numpy array.\n", + " \"\"\"\n", " if np.all(move == -1):\n", + " if not move_possible(_board, move):\n", + " raise InvalidTurn(\"An action should be taken. A turn is possible.\")\n", " return\n", + "\n", + " # noinspection PyTypeChecker\n", " if _board[tuple(move.tolist())] != 0:\n", - " raise InvalidTurn\n", + " raise InvalidTurn(\"This turn is not possible.\")\n", + "\n", " action = False\n", " for direction in DIRECTIONS:\n", " if _do_directional_move(_board, move, direction):\n", " action = True\n", " if not action:\n", - " raise InvalidTurn()\n", + " raise InvalidTurn(\"This turn is not possible.\")\n", + "\n", + " # noinspection PyTypeChecker\n", " _board[tuple(move.tolist())] = 1\n", "\n", " boards = boards.copy()\n", @@ -764,8 +856,28 @@ " return boards\n", "\n", "\n", - "do_moves(get_new_games(10), np.array([[2, 3]] * 10))[0]" - ] + "%timeit do_moves(get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE))[0]\n", + "plot_othello_board(\n", + " do_moves(\n", + " get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE)\n", + " )[0]\n", + ")" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "## An abstract reversi game policy\n", + "\n", + "For an easy use of policies an abstract class containing the policy generation / requests an action in an inherited instance of this class.\n", + "This class filters the policy to only propose valid actions. Inherited instance do not need to care about this." + ], + "metadata": { + "collapsed": false + } }, { "cell_type": "code", @@ -774,33 +886,66 @@ "outputs": [], "source": [ "class GamePolicy(ABC):\n", - "\n", - " IMPOSSIBLE: np.ndarray = np.array([-1, -1], dtype=int)\n", + " \"\"\"\n", + " A game policy. Proposes where to place a stone next.\n", + " \"\"\"\n", "\n", " @property\n", " @abc.abstractmethod\n", " def policy_name(self) -> str:\n", + " \"\"\"The name of this policy\"\"\"\n", " raise NotImplementedError()\n", "\n", " @abc.abstractmethod\n", - " def internal_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " def _internal_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " \"\"\"The internal policy is an unfiltered policy. It should only be called from inside this function\n", + "\n", + " Args:\n", + " boards: A board where a policy should be calculated for.\n", + "\n", + " Returns:\n", + " The policy for this board. Should have the same size as the boards array.\n", + " \"\"\"\n", " raise NotImplementedError()\n", "\n", - " def get_policy(self, boards: np.ndarray) -> np.ndarray:\n", - " policies = self.internal_policy(boards)\n", + " def get_policy(\n", + " self, boards: np.ndarray, epsilon: float = 1\n", + " ) -> tuple[np.ndarray, np.ndarray]:\n", + " assert len(boards.shape) == 3\n", + " assert boards.shape == (BOARD_SIZE, BOARD_SIZE)\n", + "\n", + " # todo possibly change this function to only validate the purpose turn and\n", + "\n", + " policies = self._internal_policy(boards)\n", + " raw_policy = policies.copy()\n", + " if epsilon < 1:\n", + " policies = policies + np.random.rand(*boards.shape)\n", + "\n", + " # todo talk to team about backpropagation epsilon for greedy factor\n", + "\n", " possible_turns = get_possible_turns(boards)\n", " policies[possible_turns == False] = -1.0\n", " max_indices = [\n", " np.unravel_index(policy.argmax(), policy.shape) for policy in policies\n", " ]\n", " policy_vector = np.array(max_indices)\n", - "\n", + " max_policy = policy_vector\n", " no_turn_possible = np.all(policy_vector == 0, 1) & (policies[:, 0, 0] == -1.0)\n", "\n", - " policy_vector[no_turn_possible] = GamePolicy.IMPOSSIBLE\n", - " return policy_vector" + " policy_vector[no_turn_possible] = IMPOSSIBLE\n", + " max_policy[no_turn_possible] = 0\n", + " return policy_vector, raw_policy" ] }, + { + "cell_type": "markdown", + "source": [ + "## A first policy" + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", "execution_count": null, @@ -854,7 +999,7 @@ "metadata": {}, "outputs": [], "source": [ - "SIMULATE_TURNS = 70\n", + "\n", "\n", "\n", "def simulate_game(\n", -- 2.49.0 From 29bbd834679693d076405be0dfa869627aa06dac Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sun, 12 Feb 2023 20:40:38 +0100 Subject: [PATCH 20/31] Uses html instead of md to include images. --- main.ipynb | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/main.ipynb b/main.ipynb index c196bde..4e13d9c 100644 --- a/main.ipynb +++ b/main.ipynb @@ -50,7 +50,7 @@ "The game begins with four stones places in the center of the game. Each player gets two. They are placed diagonally to each other.\n", "\n", "\n", - "![Startaufstellung.png](Startaufstellung.png)\n", + "\"Startaufstellung.png\"\n", "\n", "## Some common Othello strategies\n", "\n", @@ -63,7 +63,7 @@ "The total score is the score reached by the player subtracted with the score of the enemy.\n", "The scores change in the course of the game and converges against one. This gives some indications of what to expect from an Othello AI.\n", "\n", - "![ComputerPossitionScore](computer-score.png)\n" + "\"ComputerPossitionScore\"\n" ], "metadata": { "collapsed": false @@ -857,6 +857,7 @@ "\n", "\n", "%timeit do_moves(get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE))[0]\n", + "\n", "plot_othello_board(\n", " do_moves(\n", " get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE)\n", -- 2.49.0 From 9b011b548eb08ca5b5f4f5f977db2b7b1f31612c Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Mon, 13 Feb 2023 00:42:25 +0100 Subject: [PATCH 21/31] Fixed a bug in the assignment of invalid turns. Added lots of documentation. --- main.ipynb | 410 +++++++++++++++++++++++++++++++++++++++++------------ 1 file changed, 320 insertions(+), 90 deletions(-) diff --git a/main.ipynb b/main.ipynb index 4e13d9c..792eacd 100644 --- a/main.ipynb +++ b/main.ipynb @@ -95,6 +95,7 @@ "metadata": {}, "outputs": [], "source": [ + "from multiprocessing import Pool\n", "\n", "%load_ext blackcellmagic" ] @@ -152,7 +153,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -162,7 +163,8 @@ "EXAMPLE_STACK_SIZE: Final[int] = 1000 # defines the game stack size for examples\n", "IMPOSSIBLE: Final[np.ndarray] = np.array([-1, -1], dtype=int)\n", "IMPOSSIBLE.setflags(write=False)\n", - "SIMULATE_TURNS: Final[int] = 70" + "SIMULATE_TURNS: Final[int] = 70\n", + "VERIFY_POLICY: Final[bool] = True" ] }, { @@ -454,22 +456,22 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "9.43 ms ± 1 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "1 s ± 179 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "9.31 ms ± 1.67 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "831 ms ± 25.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { "data": { "text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])" }, - "execution_count": 23, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -558,7 +560,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -593,7 +595,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -664,15 +666,15 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 14, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "177 µs ± 3.97 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "29.7 µs ± 106 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "31.2 µs ± 269 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" + "172 µs ± 7.68 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "29.9 µs ± 1.08 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "31.6 µs ± 1.01 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" ] } ], @@ -748,7 +750,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -760,13 +762,13 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 16, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "95.1 ms ± 3.5 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "89.4 ms ± 3.1 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { @@ -874,7 +876,7 @@ "## An abstract reversi game policy\n", "\n", "For an easy use of policies an abstract class containing the policy generation / requests an action in an inherited instance of this class.\n", - "This class filters the policy to only propose valid actions. Inherited instance do not need to care about this." + "This class filters the policy to only propose valid actions. Inherited instance do not need to care about this. This super class also manges exploration and exploitation with the epsilon value." ], "metadata": { "collapsed": false @@ -882,7 +884,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -891,6 +893,20 @@ " A game policy. Proposes where to place a stone next.\n", " \"\"\"\n", "\n", + " def __init__(self, epsilon: float):\n", + " \"\"\"\n", + "\n", + " Args:\n", + " epsilon: the epsilon / greedy value. Should be between zero and one. Set the mixture of policy and exploration. One means only the policy is used. Zero means only random policies are used. All mixtures inbetween between are possible.\n", + " \"\"\"\n", + " if 0 > epsilon > 1:\n", + " raise ValueError(\"Epsilon should be between zero and one.\")\n", + " self._epsilon: float = epsilon\n", + "\n", + " @property\n", + " def epsilon(self):\n", + " return self._epsilon\n", + "\n", " @property\n", " @abc.abstractmethod\n", " def policy_name(self) -> str:\n", @@ -909,39 +925,179 @@ " \"\"\"\n", " raise NotImplementedError()\n", "\n", - " def get_policy(\n", - " self, boards: np.ndarray, epsilon: float = 1\n", - " ) -> tuple[np.ndarray, np.ndarray]:\n", + " def get_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " \"\"\"Calculates the policy that should be followed.\n", + "\n", + " Calculates the policy that should be followed.\n", + " This function does include the usage of epsilon to configure greediness and exploration.\n", + "\n", + " Args:\n", + " boards: A set of boards that show the environment where the policy should be calculated for.\n", + "\n", + " Returns:\n", + " A vector of indices. Should be formatted as an array of the form [x, y]. The value [-1, -1] is expected if no turn is possible.\n", + " \"\"\"\n", " assert len(boards.shape) == 3\n", - " assert boards.shape == (BOARD_SIZE, BOARD_SIZE)\n", + " assert boards.shape[1:] == (BOARD_SIZE, BOARD_SIZE)\n", "\n", - " # todo possibly change this function to only validate the purpose turn and\n", + " if self.epsilon <= 0:\n", + " policies = np.random.rand(*boards.shape)\n", + " else:\n", + " policies = self._internal_policy(boards)\n", + " if self.epsilon < 1:\n", + " policies = policies * self.epsilon + np.random.rand(*boards.shape) * (\n", + " 1 - self.epsilon\n", + " )\n", "\n", - " policies = self._internal_policy(boards)\n", - " raw_policy = policies.copy()\n", - " if epsilon < 1:\n", - " policies = policies + np.random.rand(*boards.shape)\n", - "\n", - " # todo talk to team about backpropagation epsilon for greedy factor\n", + " # todo talk to team about backpropagation of score and epsilon for greedy factor\n", "\n", + " # todo possibly change this function to only validate the purpose turn and not all turns\n", " possible_turns = get_possible_turns(boards)\n", " policies[possible_turns == False] = -1.0\n", " max_indices = [\n", " np.unravel_index(policy.argmax(), policy.shape) for policy in policies\n", " ]\n", " policy_vector = np.array(max_indices)\n", - " max_policy = policy_vector\n", + " no_turn_possible_1 = np.all(policy_vector == 0, 1)\n", + " zero_pos = policies[:, 0, 0] == -1.0\n", " no_turn_possible = np.all(policy_vector == 0, 1) & (policies[:, 0, 0] == -1.0)\n", "\n", - " policy_vector[no_turn_possible] = IMPOSSIBLE\n", - " max_policy[no_turn_possible] = 0\n", - " return policy_vector, raw_policy" + " policy_vector[no_turn_possible, :] = IMPOSSIBLE\n", + " return policy_vector" ] }, { "cell_type": "markdown", "source": [ - "## A first policy" + "## A first policy\n", + "\n", + "To quantify the quality of a game AI there needs to be some benchmarks.\n", + "The easiest benchmark is to play against a random player.\n", + "The easiest player to use as a benchmark is the random player.\n", + "For this and testing purpose the random policy was implemented." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 18, + "outputs": [], + "source": [ + "class RandomPolicy(GamePolicy):\n", + " \"\"\"\n", + " A policy playing a random turn by setting epsilon to 0.\n", + " \"\"\"\n", + "\n", + " def __init__(self, epsilon: float):\n", + " _ = epsilon\n", + " super().__init__(epsilon=0)\n", + "\n", + " @property\n", + " def policy_name(self) -> str:\n", + " return \"random\"\n", + "\n", + " def _internal_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " pass\n", + "\n", + "\n", + "rnd_policy = RandomPolicy(1)\n", + "assert rnd_policy.policy_name == \"random\"\n", + "assert rnd_policy.epsilon == 0\n", + "\n", + "rnd_policy_result = rnd_policy.get_policy(get_new_games(10))\n", + "assert np.any((5 >= rnd_policy_result) & (rnd_policy_result >= 3))" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "## Putting the game simulation together\n", + "Now it's time to bring all together for a proper simulation." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "### Playing a single turn\n", + "\n", + "The next function needed is used to request a policy, verify that the turn is legit and place a stone and turn enemy stones if possible." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.02 s ± 58.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", + "949 ms ± 43.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + }, + { + "data": { + "text/plain": "
", + "image/png": 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zdSdtjv7669s/biYbb0y+/LLWnbrZ3H8y1D0fKNvZuTiXZG1OypL0pCez0ptZ6U1jl4970pOT85pcklvzylw0pfN1FLAnJXRDCRmAMnn8RCkspQr3wBXJHe9ufdzc9tTX3f712y9p3W5/yVD3fKBcr8xF+V+5LEkyKwc85XW3f/28XD6lD6x0FLAnJXRDCRmA8nj8REkspQq2aW3rjteJ2y9JNt868zPUPR8o1/E5I+fl8o5ue14uz/F56aQz6ChgT0rohhIyAOXx+InSTGop9eEPfziNRiPvete7pigOu7r/8qTR4at+NXpbt5/pGeqez8yln/Z/Z+fijOaJjm47miem5Ld9OopO6Kf9XwndUEIGZiYdtX/z+InSdLyUuuuuu/J3f/d3Wbx48VTm4de2bGy92Nu+TmXcm+a25CdfTrZM4s0S6s5Q93xmLv20/zs0C3Jylu7zlPO9mZUDsjivzaGZ33EGHUUn9NP+r4RuKCEDM5OO2r95/ESJOlpKbdmyJcuXL8+nPvWpHHrooVOdibTeDrMxySdXNnqSdVfN3Ax1z2dm0k/d4SW5YMe7xHSqmbG8JBd2fHsdRbv0U3cooRtKyMDMo6P2fx4/UaKOfhxWrFiRc845J6985Sv3ed2RkZEMDw/vdmHfhtZPzfcZ3jBzM9Q9n5lJP3WHI3P8FHyXZo7IcR3fWkfRLv3UHUrohhIyMPNMtKP008zl8RMlavuZnJ/97Gfz3e9+N3fdddeErr9q1ap84AMfaDtYt3visZ1vh9mp5mjyq0n8N6LuDHXPZ+bRT93jaZmTnkm+V0dPZuWg9Hd8ex1FO/RT9yihG0rIwMzSTkfpp5nL4ydK1NZP5ODgYN75znfm2muvzdOe9rQJ3WblypUZGhracRkc9OTPiThgTtKYNbnv0ZiVHNh5X9Seoe75zCz6qbv8Mo9lbJKnn49lNL9I549odBQTpZ+6SwndUEIGZo52O0o/zVweP1Gits6Uuueee/LII4/k+c9//o4/Gx0dza233pqPf/zjGRkZyaxZu/+E9fX1pa+vb2rSdpGBqTizMkl/52dW1p6h7vnMLPqpuzySqTj3u5GfpfNzv3UUE6WfuksJ3VBCBmaOdjtKP81cHj9RorbOlHrFK16RBx54IPfee++Oywte8IIsX748995775MeUNG5RRckzcktsdMcSxZ1/hp0tWeoez4zi37qLrdlTRqTPP28kZ7cls5fJVNHMVH6qbuU0A0lZGDm0FHdw+MnStTWmVJz5szJSSedtNufHXLIITn88MOf9OdMzuyFycKlyeCNnb1dZqM3WfiaZPaCmZuh7vnMLPqpuzyawTyQG3JSlnT0tsajeSIP5Ct5NA91nEFHMVH6qbuU0A0lZGDm0FHdw+MnSjTJN2NkOp1ySWd31KT14m+LL575GeqeD5Tr67msowdUSetFOm/OFZPOoKOAPSmhG0rIAJTH4ydKM+ml1C233JKPfexjUxCF8eaekZx2WWe3Pe2jrdvP9Ax1z2dm00/7t/X5dr6Qzh6V/FPenfX59qQz6Cg6pZ/2byV0QwkZmLl01P7L4ydK40ypwp180c47bGMfT7bc/vXTLmvdbn/JUPd8oFw354odD6xG88RTXnf717+Qi6fkt3zb6ShgT0rohhIyAOXx+ImSWEoVrtFonZ64bG3rubNptN4Cc/vbaO74uNH6+rK1res3GvtPhrrnA2W7OVfkspyRB/KVjGUso9mW0WxLM2MZzRMZzbaMZSwP5Cu5LGdM6QOqREcBe1ZCN5SQASiTx0+Uoq0XOqc+c89oXbYMJuuuSoY3JL8aTg7sb70d5qILp//F3urOUPd8oFzr8+2sz7dzaObnJbkwR+S4HJT+/CLD+Vk25LZcNakX5ZwIHQXsSQndUEIGoDweP1ECS6kZZvaC5NT3dXeGuucD5Xo0D+Ur+WCtGXQUsCcldEMJGYDyePxEnTx9DwAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUazWazWeXA4eHhDAwMJI3kkHlVTm55fHPSHEsaPcnBc6ufL4MMpWWoe36SbN2UpJkMDQ2lv7+/nhCpv5+SMo5H3Rnqni+DDOOV0FH6SYZS5stQVgb91FLCsZBBhlLml5Jhov1U31IKYJxillIAe1DEP/oA9kA/AaXaVz/1Vphld86UkkGGIjLUPT/ZuUUvht/0df3PpAwy7KqojtJPXZ+h7vkylJVBP7WUcCxkkKGU+aVkmGg/1baUOvioZPlD1c+9dn6y9aetA1PHfBlkKC1D3fOT5Jp5reIsRV39lJRxPOrOUPd8GWQYr6SO0k8y1D1fhrIy6KeWEo6FDDKUMr+UDBPtJy90DgAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHL1vfseM9aWjcm6NcnQ+uSJx5ID5iQDxyeLLkhmL5z++YdmQV6SC3Jkjs/TMie/zGN5JOtzW9bk0QxOfwCgWHX3UykZgPKU0A0eQwF7UkI/ydC9LKWYsE1rk/svTzbe0HprySRpjiaNWa2P73l/cvTSZPElydwzpn7+8TkjZ+finJylaWYsSdKTnoz9+uOleX/uz5dzcy7P+nx76gMAxaq7n0rJAJSnhG7wGArYkxL6SQY8fY99ajaT+y5LbjgzGbwxSbN1J22O/vrr2z9uJhtvTL78stadutmcugxn5+JckrU5KUvSk57MSm9mpTeNXT7uSU9OzmtySW7NK3PR1A0HilVCP5WQAShPKd3gMRQwXgn9JAPbWUqxTw9ckdzx7tbHzW1Pfd3tX7/9ktbtpsIrc1H+Vy5LkszKAU953e1fPy+Xe1AFXaDufiolA1CeErrBYyhgT0roJxnYrq2l1Pvf//40Go3dLieccMJ0ZaMAm9a27niduP2SZPOtk5t/fM7Iebm8o9uel8tzfF46uQDMGPqp+9TdT6VkYGbQUd2lhG7wGIqJ0k/dpYR+koFdtX2m1IknnpjNmzfvuPzrv/7rdOSiEPdfnjQ6fOWxRm/r9pNxdi7OaJ7o6LajecJv+rqMfuoudfdTKRmYOXRU9yihGzyGoh36qXuU0E8ysKu2D0Nvb2+OOuqo6chCYbZsbL3YWzp8zmxzW/KTLydbBpPZC9q//aFZkJOzND0dPst0Vg7I4rw2h2Z+Hs1DHX0PZhb91D3q7qdSMjCz6KjuUEI3eAxFu/RTdyihn2RgvLb/S7V+/frMmzcvxx57bJYvX56NGzdORy4KsG7Nzncf6FSjJ1l3VWe3fUku2PEOMZ1qZiwvyYWT+h7MHPqpe9TdT6VkYGbRUd2hhG7wGIp26afuUEI/ycB4bZ0p9Vu/9VtZs2ZNFi1alM2bN+cDH/hAXvrSl+b73/9+5syZs8fbjIyMZGRkZMfnw8PDk0tMZYbWT833Gd7Q2e2OzPFTML2ZI3LcFHwfSqefukvd/VRKBmaOdjtKP81cJXSDx1C0Qz91jxL6SQbGa2sptWTJkh0fL168OL/1W7+Vo48+Op///OfzB3/wB3u8zapVq/KBD3xgcimpxROP7Xw7zE41R5NfdfjfqadlTsennW/Xk1k5KP2T+h7MDPqpu9TdT6VkYOZot6P008xVQjd4DEU79FP3KKGfZGC8Sf3X6ulPf3p+4zd+Ixs27H1FuHLlygwNDe24DA4OTmYkFTpgTtKYNbnv0ZiVHNjh45lf5rGMTfLU87GM5hfRFt1IP+3f6u6nUjIwc+2ro/TTzFVCN3gMxWTop/1XCf0kA+NNaim1ZcuW/Md//Efmzp271+v09fWlv79/twszw8BUnPmdpL/DM78fyVScV9nIz+K8ym6kn/ZvdfdTKRmYufbVUfpp5iqhGzyGYjL00/6rhH6SgfHaWkpdcsklWbt2bR588MHcdttt+Z3f+Z3MmjUrb3jDG6YrHzVadEHSnNwv2dIcSxZ1+BqZt2VNGpM89byRntwWr0DXDfRTd6m7n0rJwMyho7pHCd3gMRTt0E/do4R+koHx2vqv1UMPPZQ3vOENWbRoUX73d383hx9+eG6//fYcccQR05WPGs1emCxcmjTaeuWxnRq9ydHLOn+bzEczmAdyQ0bzREe3H80TuT9f8lbGXUI/dZe6+6mUDMwcOqp7lNANHkPRDv3UPUroJxkYr63D8NnPfna6clCoUy5JNn65s9s2R5PFF09u/tdzWU7Jazu6bU9m5eZcMbkAzBj6qfvU3U+lZGBm0FHdpYRu8BiKidJP3aWEfpKBXU3uvF72e3PPSE67rLPbnvbR1u0nY32+nS+ks3v8P+XdWZ9vTy4AUKy6+6mUDEB5SugGj6GAPSmhn2RgV5ZS7NPJF+28w+7rFMftXz/tstbtpsLNuWLHg6p9nYa+/etfyMV+wwddoO5+KiUDUJ4SusFjKGBPSugnGdjOUop9ajRapycuW5ssfE2SRustMLe/jeaOjxutry9b27p+ozF1GW7OFbksZ+SBfCVjGctotmU029LMWEbzREazLWMZywP5Si7LGR5MQZcooZ9KyACUp5Ru8BgKGK+EfpKB7Tp8aS+60dwzWpctg8m6q5LhDcmvhpMD+1tvh7nowul9sbf1+XbW59s5NPPzklyYI3JcDkp/fpHh/Cwbcluu8oKc0KXq7qdSMgDlKaEbPIYC9qSEfpIBSynaNntBcur76pv/aB7KV/LB+gIAxaq7n0rJAJSnhG7wGArYkxL6SYbu5el7AAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKtdoNpvNKgcODw9nYGAgaSSHzKtycsvjm5PmWNLoSQ6eW/18GWQoLUPd85Nk66YkzWRoaCj9/f31hEj9/ZSUcTzqzlD3fBlkGK+EjtJPMpQyX4ayMuinlhKOhQwylDK/lAwT7af6llIA4xSzlALYgyL+0QewB/oJKNW++qm3wiy7c6aUDDIUkaHu+cnOLXox/Kav638mZZBhV0V1lH7q+gx1z5ehrAz6qaWEYyGDDKXMLyXDRPuptqXUwUclyx+qfu6185OtP20dmDrmyyBDaRnqnp8k18xrFWcp6uqnpIzjUXeGuufLIMN4JXWUfpKh7vkylJVBP7WUcCxkkKGU+aVkmGg/eaFzAAAAACpnKQUAAABA5SylAAAAAKhcfS90DgD7oS0bk3VrkqH1yROPJQfMSQaOTxZdkMxeWHc6AAAoh6UUAEyBTWuT+y9PNt7QeqeTJGmOJo1ZrY/veX9y9NJk8SXJ3DNqiwkAAMXw9D0AmIRmM7nvsuSGM5PBG5M0W8uo5uivv77942ay8cbkyy9rLa+apbyFNwAA1MRSCgAm4YErkjve3fq4ue2pr7v967df0rodAAB0M0spAOjQprWtBVMnbr8k2Xzr1OYBAICZpO2l1E9/+tO88Y1vzOGHH56DDjooJ598cu6+++7pyAbQFv1E1e6/PGl0+OqMjd7W7ekeOgoolX4C6tLWQ+lHH300p59+es4666zceOONOeKII7J+/foceuih05UPYEL0E1XbsrH1oubp8LWhmtuSn3w52TKYzF4wpdEokI4CSqWfgDq1tZT6yEc+kgULFuSqq67a8WfHHHPMlIcCaJd+omrr1rTeZW/7C5p3otGTrLsqOfV9UxaLQukooFT6CahTW0/f+9KXvpQXvOAFOe+883LkkUfmec97Xj71qU895W1GRkYyPDy82wVgquknqja0fmq+z/CGqfk+lK3djtJPQFX0E1CntpZSP/7xj7N69eocf/zx+epXv5q3vOUtecc73pGrr756r7dZtWpVBgYGdlwWLPAcBWDq6Seq9sRjkztLKmnd/lcey3eFdjtKPwFV0U9AndpaSo2NjeX5z39+Lr300jzvec/L//f//X/5P//n/+Rv//Zv93qblStXZmhoaMdlcHBw0qEBxtNPVO2AOUlj1uS+R2NWcmD/1OShbO12lH4CqqKfgDq1tZSaO3dunvvc5+72Z7/5m7+ZjRs37vU2fX196e/v3+0CMNX0E1UbOH5qvk//cVPzfShbux2ln4Cq6CegTm0tpU4//fSsW7dutz/70Y9+lKOPPnpKQwG0Sz9RtUUXJM2xyX2P5liy6MIpiUPhdBRQKv0E1KmtpdSf/Mmf5Pbbb8+ll16aDRs25Lrrrsvf//3fZ8WKFdOVD2BC9BNVm70wWbg0abT1PrY7NXqTo5cls70UR1fQUUCp9BNQp7aWUi984Qtz/fXX5zOf+UxOOumkfPCDH8zHPvaxLF++fLryAUyIfqIOp1ySNLd1dtvmaLL44qnNQ7l0FFAq/QTUqe3f7y5dujRLly6djiwAk6KfqNrcM5LTLktuv6T925720dbt6R46CiiVfgLq0taZUgDA7k6+qLWYSvb9VL7tXz/tstbtAACgm1lKAcAkNBqtp+EtW5ssfE2SRtKY1boku3zcaH192drW9RuNOlMDAED9Onx5VgBgV3PPaF22DCbrrkqGNyS/Gk4O7E/6j2u9y54XNQcAgJ0spQBgCs1ekJz6vrpTAABA+Tx9DwAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUazWazWeXA4eHhDAwMJI3kkHlVTm55fHPSHEsaPcnBc6ufL4MMpWWoe36SbN2UpJkMDQ2lv7+/nhCpv5+SMo5H3Rnqni+DDOOV0FH6SYZS5stQVgb91FLCsZBBhlLml5Jhov1U31IKYJxillIAe1DEP/oA9kA/AaXaVz/1Vphld86UkkGGIjLUPT/ZuUUvht/0df3PpAwy7KqojtJPXZ+h7vkylJVBP7WUcCxkkKGU+aVkmGg/1baUOvioZPlD1c+9dn6y9aetA1PHfBlkKC1D3fOT5Jp5reIsRV39lJRxPOrOUPd8GWQYr6SO0k8y1D1fhrIy6KeWEo6FDDKUMr+UDBPtJy90DgAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5dpaSj372c9Oo9F40mXFihXTlQ9gwnQUUCr9BJRKPwF16m3nynfddVdGR0d3fP79738/Z599ds4777wpDwbQLh0FlEo/AaXST0Cd2lpKHXHEEbt9/uEPfzjPec5z8rKXvWxKQwF0QkcBpdJPQKn0E1CntpZSu/rVr36Va665JhdddFEajcZerzcyMpKRkZEdnw8PD3c6EmDCJtJR+gmog34CSqWfgKp1/ELnX/ziF/Pzn/88F1xwwVNeb9WqVRkYGNhxWbBgQacjASZsIh2ln4A66CegVPoJqFrHS6krr7wyS5Ysybx5857yeitXrszQ0NCOy+DgYKcjASZsIh2ln4A66CegVPoJqFpHT9/7yU9+kptvvjn//M//vM/r9vX1pa+vr5MxAB2ZaEfpJ6Bq+gkolX4C6tDRmVJXXXVVjjzyyJxzzjlTnQdg0nQUUCr9BJRKPwF1aHspNTY2lquuuirnn39+ens7fp10gGmho4BS6SegVPoJqEvbS6mbb745GzduzJvf/ObpyAMwKToKKJV+Akqln4C6tL0Gf9WrXpVmszkdWQAmTUcBpdJPQKn0E1CXjt99DwAAAAA6ZSkFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFC5RrPZbFY5cHh4OAMDA0kjOWRelZNbHt+cNMeSRk9y8Nzq58sgQ2kZ6p6fJFs3JWkmQ0ND6e/vrydE6u+npIzjUXeGuufLIMN4JXSUfpKhlPkylJVBP7WUcCxkkKGU+aVkmGg/1beUAhinmKUUwB4U8Y8+gD3QT0Cp9tVPvRVm2Z0zpWSQoYgMdc9Pdm7Ri+E3fV3/MymDDLsqqqP0U9dnqHu+DGVl0E8tJRwLGWQoZX4pGSbaT7UtpQ4+Kln+UPVzr52fbP1p68DUMV8GGUrLUPf8JLlmXqs4S1FXPyVlHI+6M9Q9XwYZxiupo/STDHXPl6GsDPqppYRjIYMMpcwvJcNE+8kLnQMAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKtbWUGh0dzXvf+94cc8wxOeigg/Kc5zwnH/zgB9NsNqcrH8CE6CegZDoKKJV+AurU286VP/KRj2T16tW5+uqrc+KJJ+buu+/OhRdemIGBgbzjHe+YrowA+6SfgJLpKKBU+gmoU1tLqdtuuy3nnntuzjnnnCTJs5/97HzmM5/JnXfeOS3hACZKPwEl01FAqfQTUKe2nr73kpe8JN/4xjfyox/9KEly33335V//9V+zZMmSaQkHMFH6CSiZjgJKpZ+AOrV1ptR73vOeDA8P54QTTsisWbMyOjqaD33oQ1m+fPlebzMyMpKRkZEdnw8PD3eeFmAv9BNQsnY7Sj8BVdFPQJ3aOlPq85//fK699tpcd911+e53v5urr746l112Wa6++uq93mbVqlUZGBjYcVmwYMGkQwOMp5+AkrXbUfoJqIp+AurU1lLq3e9+d97znvfk93//93PyySfnf//v/50/+ZM/yapVq/Z6m5UrV2ZoaGjHZXBwcNKhAcbTT0DJ2u0o/QRURT8BdWrr6XuPP/54enp232PNmjUrY2Nje71NX19f+vr6OksHMEH6CShZux2ln4Cq6CegTm0tpZYtW5YPfehDWbhwYU488cR873vfyxVXXJE3v/nN05UPYEL0E1AyHQWUSj8BdWprKfU3f/M3ee9735u3vvWteeSRRzJv3rz80R/9Ud73vvdNVz6ACdFPQMl0FFAq/QTUqa2l1Jw5c/Kxj30sH/vYx6YpDkBn9BNQMh0FlEo/AXVq64XOAQAAAGAqWEoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyjWazWazyoFDQ0N5+tOfniQ5eG6Vk1sefzhJM0kjOfio6ufLIENpGeqenySPb279789//vMMDAzUEyL191NSyPHwMymDDLtnKKCj9JMMpcyXobAM+ilJIcdCBhkKmV9Mhgn2U+VLqYceeigLFiyociQwQwwODmb+/Pm1zddPwFOps6P0E/BU9BNQqn31U+VLqbGxsWzatClz5sxJo9Fo+/bDw8NZsGBBBgcH09/fPw0JZZgpGeqeL8PUZWg2m3nssccyb9689PTU96xi/STD/pSh7vn7U4YSOmqy/ZTUfzzqni+DDKVl0E871X0sSshQ93wZZJjqDBPtp97JhOxET0/PlGzx+/v7azs4MpSVoe75MkxNhjqftredfpJhf8xQ9/z9JUPdHTVV/ZTUfzzqni+DDKVl0E871X0sSshQ93wZZJjKDBPpJy90DgAAAEDlLKUAAAAAqNyMW0r19fXlL/7iL9LX1ydDl2eoe74MZWUoQQl/DzLIUMp8GcpT999F3fNlkKG0DHXPL0kJfxd1Z6h7vgwy1JWh8hc6BwAAAIAZd6YUAAAAADOfpRQAAAAAlbOUAgAAAKByM2op9Z3vfCezZs3KOeecU/nsCy64II1GY8fl8MMPz6tf/ercf//9lWd5+OGH8/a3vz3HHnts+vr6smDBgixbtizf+MY3pn32rn8PBxxwQJ75zGfm7LPPzqc//emMjY1N+/zxGXa9vPrVr65k/r5ybNiwoZL5Dz/8cN75znfmuOOOy9Oe9rQ885nPzOmnn57Vq1fn8ccfn/b5F1xwQV73utc96c9vueWWNBqN/PznP5/2DKXRUfppfI66Oqrufkrq7Sj99GT6ST+Nz6GfPIYqhX7ST+Nz6Kfu6qcZtZS68sor8/a3vz233nprNm3aVPn8V7/61dm8eXM2b96cb3zjG+nt7c3SpUsrzfDggw/m1FNPzTe/+c189KMfzQMPPJCbbropZ511VlasWFFJhu1/Dw8++GBuvPHGnHXWWXnnO9+ZpUuXZtu2bZVm2PXymc98ppLZ+8pxzDHHTPvcH//4x3ne856Xr33ta7n00kvzve99L9/5znfyp3/6p7nhhhty8803T3sGnqzbO0o/PTlHnR1VVz8lOqpE+kk/jc+hn/RTKfSTfhqfQz91Vz/11h1gorZs2ZLPfe5zufvuu/Pwww9nzZo1+fM///NKM/T19eWoo45Kkhx11FF5z3vek5e+9KX52c9+liOOOKKSDG9961vTaDRy55135pBDDtnx5yeeeGLe/OY3V5Jh17+HZz3rWXn+85+f0047La94xSuyZs2a/OEf/mGlGepUV463vvWt6e3tzd13373bz8Gxxx6bc889N95Us3o6Sj/tLUdd6sygo8qin/TT3nLURT+xnX7ST3vLURf9VL0Zc6bU5z//+ZxwwglZtGhR3vjGN+bTn/50rQdly5Ytueaaa3Lcccfl8MMPr2Tm//zP/+Smm27KihUrdvsh3e7pT396JTn25OUvf3lOOeWU/PM//3NtGbrFf//3f+drX/vaXn8OkqTRaFScim7vKP3EdjqqPPpJP9Gin8qjn/QTLd3cTzNmKXXllVfmjW98Y5LWKXVDQ0NZu3ZtpRluuOGGzJ49O7Nnz86cOXPypS99KZ/73OfS01PNX+OGDRvSbDZzwgknVDKvXSeccEIefPDBSmbteiy2Xy699NJKZj9VjvPOO2/aZ27/OVi0aNFuf/6MZzxjR44/+7M/m/YcyZ6Pw5IlSyqZXZpu7yj9tLsSOqqOfkrK6Sj9tJN+0k+70k/191Oio7bTT/ppV/qpO/tpRjx9b926dbnzzjtz/fXXJ0l6e3vze7/3e7nyyitz5plnVpbjrLPOyurVq5Mkjz76aD75yU9myZIlufPOO3P00UdP+/zST9drNpuVbW93PRbbHXbYYZXMfqoce9tqV+HOO+/M2NhYli9fnpGRkUpm7uk43HHHHTseXHQLHaWfxiuho0rqp6T6jtJPLfpJP42nn57MY6h66Cf9NJ5+erJu6KcZsZS68sors23btsybN2/HnzWbzfT19eXjH/94BgYGKslxyCGH5Ljjjtvx+T/8wz9kYGAgn/rUp/JXf/VX0z7/+OOPT6PRyA9/+MNpn9WJH/zgB5W9CNz4Y1GXOnIcd9xxaTQaWbdu3W5/fuyxxyZJDjrooMqy7On//0MPPVTZ/FLoKP00XgkdVVeGUjpKP7XoJ/00nn6qv58SHZXop0Q/jaefurOfin/63rZt2/KP//iPufzyy3PvvffuuNx3332ZN29eLe+4tl2j0UhPT09+8YtfVDLvsMMOy2//9m/nE5/4RLZu3fqkr9f59rHf/OY388ADD+T1r399bRm6xeGHH56zzz47H//4x/f4c0C1dFSLfmI7HVUO/dSin9hOP5VDP7XoJ7br5n4q/kypG264IY8++mj+4A/+4Enb8te//vW58sor88d//MeVZBkZGcnDDz+cpHVq58c//vFs2bIly5Ytq2R+knziE5/I6aefnhe96EX5y7/8yyxevDjbtm3L17/+9axevTo/+MEPpj3D9r+H0dHR/Nd//VduuummrFq1KkuXLs2b3vSmaZ+/a4Zd9fb25hnPeEYl8+v2yU9+Mqeffnpe8IIX5P3vf38WL16cnp6e3HXXXfnhD3+YU089te6IXUNH7aSfnpxjVzpKR1VNP+2kn56cY1f6ST9VTT/tpJ+enGNX+qkL+qlZuKVLlzZf85rX7PFrd9xxRzNJ87777pv2HOeff34zyY7LnDlzmi984Qub//RP/zTts8fbtGlTc8WKFc2jjz66eeCBBzaf9axnNV/72tc2v/Wtb0377F3/Hnp7e5tHHHFE85WvfGXz05/+dHN0dHTa54/PsOtl0aJFlczfNce5555b6cxdbdq0qfm2t72tecwxxzQPOOCA5uzZs5svetGLmh/96EebW7dunfb5e/v//61vfauZpPnoo49Oe4YS6KjddXs/jc9RV0fV3U/NZr0dpZ9a9NPu9JN+2s5jqPrpp93pJ/20XTf2U6PZLPzV1QAAAADY7xT/mlIAAAAA7H8spQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5XqrHjg2NpZNmzZlzpw5aTQaVY8HCtRsNvPYY49l3rx56empb1eun4A9KaGj9BOwJ/oJKNVE+6nypdSmTZuyYMGCqscCM8Dg4GDmz59f23z9BDyVOjtKPwFPRT8BpdpXP1W+lJozZ86Ojw+eW/X05PGHkzSTNJKDj6p+vgwylJah7vlJ8vjm1v/u2g91qLufkkKOh59JGWTYPUMBHaWfZChlvgyFZdBPSQo5FjLIUMj8YjJMsJ8qX0ptP6Xz4LnJGzdVPT25dn6y9afJIfOS5Q9VP18GGUrLUPf8JLlmXqu06j7lu+5+Sso4HnVnqHu+DDKMV0JH6ScZSpkvQ1kZ9FNLCcdCBhlKmV9Khon2kxc6BwAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJVreyl16623ZtmyZZk3b14ajUa++MUvTkMsgPbpJ6BU+gkolX4C6tT2Umrr1q055ZRT8olPfGI68gB0TD8BpdJPQKn0E1Cn3nZvsGTJkixZsmQ6sgBMin4CSqWfgFLpJ6BObS+l2jUyMpKRkZEdnw8PD0/3SIAJ0U9AqfQTUCr9BEylaX+h81WrVmVgYGDHZcGCBdM9EmBC9BNQKv0ElEo/AVNp2pdSK1euzNDQ0I7L4ODgdI8EmBD9BJRKPwGl0k/AVJr2p+/19fWlr69vuscAtE0/AaXST0Cp9BMwlab9TCkAAAAAGK/tM6W2bNmSDRs27Pj8P//zP3PvvffmsMMOy8KFC6c0HEA79BNQKv0ElEo/AXVqeyl1991356yzztrx+UUXXZQkOf/887NmzZopCwbQLv0ElEo/AaXST0Cd2l5KnXnmmWk2m9ORBWBS9BNQKv0ElEo/AXXymlIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgco1ms9mscuDw8HAGBgaSRnLIvContzy+OWmOJY2e5OC51c+XQYbSMtQ9P0m2bkrSTIaGhtLf319PiNTfT0kZx6PuDHXPl0GG8UroKP0kQynzZSgrg35qKeFYyCBDKfNLyTDRfqpvKQUwTjFLKYA9KOIffQB7oJ+AUu2rn3orzLI7Z0rJIEMRGeqen+zcohfDb/q6/mdSBhl2VVRH6aeuz1D3fBnKyqCfWko4FjLIUMr8UjJMtJ9qW0odfFSy/KHq5147P9n609aBqWO+DDKUlqHu+UlyzbxWcZairn5KyjgedWeoe74MMoxXUkfpJxnqni9DWRn0U0sJx0IGGUqZX0qGifaTFzoHAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKBybS2lVq1alRe+8IWZM2dOjjzyyLzuda/LunXrpisbwITpJ6BkOgoolX4C6tTWUmrt2rVZsWJFbr/99nz961/PE088kVe96lXZunXrdOUDmBD9BJRMRwGl0k9AnXrbufJNN9202+dr1qzJkUcemXvuuSdnnHHGlAYDaId+Akqmo4BS6SegTm0tpcYbGhpKkhx22GF7vc7IyEhGRkZ2fD48PDyZkQATop+Aku2ro/QTUBf9BFSp4xc6Hxsby7ve9a6cfvrpOemkk/Z6vVWrVmVgYGDHZcGCBZ2OBJgQ/QSUbCIdpZ+AOugnoGodL6VWrFiR73//+/nsZz/7lNdbuXJlhoaGdlwGBwc7HQkwIfoJKNlEOko/AXXQT0DVOnr63tve9rbccMMNufXWWzN//vynvG5fX1/6+vo6CgfQLv0ElGyiHaWfgKrpJ6AObS2lms1m3v72t+f666/PLbfckmOOOWa6cgG0RT8BJdNRQKn0E1CntpZSK1asyHXXXZd/+Zd/yZw5c/Lwww8nSQYGBnLQQQdNS0CAidBPQMl0FFAq/QTUqa3XlFq9enWGhoZy5plnZu7cuTsun/vc56YrH8CE6CegZDoKKJV+AurU9tP3AEqkn4CS6SigVPoJqFPH774HAAAAAJ2ylAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqFyj2Ww2qxw4PDycgYGBpJEcMq/KyS2Pb06aY0mjJzl4bvXzZZChtAx1z0+SrZuSNJOhoaH09/fXEyL191NSxvGoO0Pd82WQYbwSOko/yVDKfBnKyqCfWko4FjLIUMr8UjJMtJ/qW0oBjFPMUgpgD4r4Rx/AHugnoFT76qfeCrPszplSMshQRIa65yc7t+jF8Ju+rv+ZlEGGXRXVUfqp6zPUPV+GsjLop5YSjoUMMpQyv5QME+2n2pZSBx+VLH+o+rnXzk+2/rR1YOqYL4MMpWWoe36SXDOvVZylqKufkjKOR90Z6p4vgwzjldRR+kmGuufLUFYG/dRSwrGQQYZS5peSYaL95IXOAQAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOXaWkqtXr06ixcvTn9/f/r7+/PiF784N95443RlA5gw/QSUTEcBpdJPQJ3aWkrNnz8/H/7wh3PPPffk7rvvzstf/vKce+65+bd/+7fpygcwIfoJKJmOAkqln4A69bZz5WXLlu32+Yc+9KGsXr06t99+e0488cQpDQbQDv0ElExHAaXST0Cd2lpK7Wp0dDRf+MIXsnXr1rz4xS+eykwAk6KfgJLpKKBU+gmoWttLqQceeCAvfvGL88tf/jKzZ8/O9ddfn+c+97l7vf7IyEhGRkZ2fD48PNxZUoB90E9AydrpKP0EVEk/AXVp+933Fi1alHvvvTd33HFH3vKWt+T888/Pv//7v+/1+qtWrcrAwMCOy4IFCyYVGGBv9BNQsnY6Sj8BVdJPQF3aXkodeOCBOe6443Lqqadm1apVOeWUU/LXf/3Xe73+ypUrMzQ0tOMyODg4qcAAe6OfgJK101H6CaiSfgLq0vFrSm03Nja22+mb4/X19aWvr2+yYwDapp+Akj1VR+knoE76CahKW0uplStXZsmSJVm4cGEee+yxXHfddbnlllvy1a9+dbryAUyIfgJKpqOAUuknoE5tLaUeeeSRvOlNb8rmzZszMDCQxYsX56tf/WrOPvvs6coHMCH6CSiZjgJKpZ+AOrW1lLryyiunKwfApOgnoGQ6CiiVfgLq1PYLnQMAAADAZFlKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMo1ms1ms8qBw8PDGRgYSBrJIfOqnNzy+OakOZY0epKD51Y/XwYZSstQ9/wk2bopSTMZGhpKf39/PSFSfz8lZRyPujPUPV8GGcYroaP0kwylzJehrAz6qaWEYyGDDKXMLyXDRPupvqUUwDjFLKUA9qCIf/QB7IF+Akq1r37qrTDL7pwpJYMMRWSoe36yc4teDL/p6/qfSRlk2FVRHaWfuj5D3fNlKCuDfmop4VjIIEMp80vJMNF+qm0pdfBRyfKHqp977fxk609bB6aO+TLIUFqGuucnyTXzWsVZirr6KSnjeNSdoe75MsgwXkkdpZ9kqHu+DGVl0E8tJRwLGWQoZX4pGSbaT17oHAAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOXqe/c9ZqxDsyAvyQU5MsfnaZmTX+axPJL1uS1r8mgGp33+lo3JujXJ0PrkiceSA+YkA8cniy5IZi+c9vHAXpRw35QBKFXdj58S/QTsmX6iTpZSTNjxOSNn5+KcnKVpZixJ0pOejP3646V5f+7Pl3NzLs/6fHvK529am9x/ebLxhtZbWyZJczRpzGp9fM/7k6OXJosvSeaeMeXjgb0o4b4pA1Cquh8/JfoJ2DP9RAk8fY8JOTsX55KszUlZkp70ZFZ6Myu9aezycU96cnJek0tya16Zi6ZsdrOZ3HdZcsOZyeCNSZqtomqO/vrr2z9uJhtvTL78slaxNZtTFgHYgxLumzIAJavz8VOin4C900+UwlKKfXplLsr/ymVJklk54Cmvu/3r5+XyKSuuB65I7nh36+Pmtqe+7vav335J63bA9CnhvikDUKq6Hz8l+gnYM/1ESSa1lPrwhz+cRqORd73rXVMUh9IcnzNyXi7v6Lbn5fIcn5dOav6mta3y6cTtlySbb53UeGYw/TS9SrhvysBMpZ/2f3U/fkr0E53TUfs3/URpOl5K3XXXXfm7v/u7LF68eCrzUJizc3FG80RHtx3NE5Pept9/edLo8JXPGr2t29N99NP0K+G+KQMzkX7qDnU/fkr0E53RUfs//URpOlpKbdmyJcuXL8+nPvWpHHrooVOdiUIcmgU5OUv3eUrn3szKAVmc1+bQzO/o9ls2tl7wbl+nc+5Nc1vyky8nW6p5wwgKoZ+mXwn3TRmYifRTd6j78VOin+iMjtr/6SdK1NFSasWKFTnnnHPyyle+cqrzUJCX5IId78LQqWbG8pJc2NFt163Z+Q4MnWr0JOuumtz3YGbRT9OvhPumDMxE+qk71P34KdFPdEZH7f/0EyVq+6S5z372s/nud7+bu+66a0LXHxkZycjIyI7Ph4eH2x1JTY7M8VPwXZo5Isd1dMuh9VMwPsnwhqn5PpRPP1WjhPumDMw0+ql71P34KdFPtK+djtJPM5d+okRt7SgHBwfzzne+M9dee22e9rSnTeg2q1atysDAwI7LggULOgpK9Z6WOemZ5Bs09mRWDkp/R7d94rGdbwnaqeZo8iv/newK+qk6Jdw3ZWAm0U/dpe7HT4l+oj3tdpR+mrn0EyVq6yfynnvuySOPPJLnP//56e3tTW9vb9auXZv/+3//b3p7ezM6+uSfrpUrV2ZoaGjHZXDQkz9nil/msYxN8vTOsYzmF+msMQ6YkzRmTWp8GrOSAzvvTGYQ/VSdEu6bMjCT6KfuUvfjp0Q/0Z52O0o/zVz6iRK19fS9V7ziFXnggQd2+7MLL7wwJ5xwQv7sz/4ss2Y9+aerr68vfX19k0tJLR7JVJxb2cjP0tm5lQNTcXZpkv7Ozy5lBtFP1SnhvikDM4l+6i51P35K9BPtabej9NPMpZ8oUVtnSs2ZMycnnXTSbpdDDjkkhx9+eE466aTpykhNbsuaNCZ5emcjPbktnb0K3aILkubkFvlpjiWLOn8dPmYQ/VSdEu6bMjCT6KfuUvfjp0Q/0R4d1T30EyWa5Ovesz97NIN5IDdkNE90dPvRPJH786U8moc6uv3shcnCpUmj7Zfjb2n0JkcvS2Z7mjtMqRLumzIApar78VOin4A900+UqMMfhZ1uueWWKYhBqb6ey3JKXtvRbXsyKzfniknNP+WSZOOXO7ttczRZfPGkxjPD6afpU8J9UwZmMv20f6v78VOin5gcHbX/0k+UxplSPKX1+Xa+kM7u9f+Ud2d9vj2p+XPPSE67rLPbnvbR1u2BqVfCfVMGoFR1P35K9BOwZ/qJ0lhKsU8354odxbWvUz23f/0LuXhKtuhJcvJFO0trX6d5bv/6aZe1bgdMnxLumzIApar78VOin4A900+UxFKKCbk5V+SynJEH8pWMZSyj2ZbRbEszYxnNExnNtoxlLA/kK7ksZ0xpYTUarVM0l61NFr4mSaP1NqDb30p0x8eN1teXrW1dv9GYsgjAHpRw35QBKFmdj58S/QTsnX6iFJN+TSm6x/p8O+vz7Rya+XlJLswROS4HpT+/yHB+lg25LVdN6kXv9mXuGa3LlsFk3VXJ8IbkV8PJgf2ttwRddKEXvIM6lHDflAEoVd2PnxL9BOyZfqIEllK07dE8lK/kg7XNn70gOfV9tY0H9qKE+6YMQKnqfvyU6Cdgz/QTdfL0PQAAAAAqZykFAAAAQOUspQAAAACoXKPZbDarHDg8PJyBgYGkkRwyr8rJLY9vTppjSaMnOXhu9fNlkKG0DHXPT5Ktm5I0k6GhofT399cTIvX3U1LG8ag7Q93zZZBhvBI6Sj/JUMp8GcrKoJ9aSjgWMshQyvxSMky0n+pbSgGMU8xSCmAPivhHH8Ae6CegVPvqp/refc+ZUjLIUESGuucnO7foxfCbvq7/mZRBhl0V1VH6qesz1D1fhrIy6KeWEo6FDDKUMr+UDBPtp9qWUgcflSx/qPq5185Ptv60dWDqmC+DDKVlqHt+klwzr1Wcpairn5IyjkfdGeqeL4MM45XUUfpJhrrny1BWBv3UUsKxkEGGUuaXkmGi/eSFzgEAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFSuvnffY8basjFZtyYZWp888VhywJxk4Phk0QXJ7IX7//xSMgBPVsJ989AsyEtyQY7M8Xla5uSXeSyPZH1uy5o8msFqQgDFKaGfSsgAlKeEbighA/WwlGLCNq1N7r882XhD660lk6Q5mjRmtT6+5/3J0UuTxZckc8/Y/+aXkgF4shLum8fnjJydi3NylqaZsSRJT3oy9uuPl+b9uT9fzs25POvz7ekJARSnhH4qIQNQnhK6oYQM1MvT99inZjO577LkhjOTwRuTNFtF0Rz99de3f9xMNt6YfPllrWJpNveP+aVkAJ6slPvm2bk4l2RtTsqS9KQns9KbWelNY5ePe9KTk/OaXJJb88pcNLUBgOKU0E8lZADKU0I3lJCBMlhKsU8PXJHc8e7Wx81tT33d7V+//ZLW7faH+aVkAJ6shPvmK3NR/lcuS5LMygFPed3tXz8vl1tMwX6uhH4qIQNQnhK6oYQMlMFSiqe0aW3rzt+J2y9JNt86s+eXkgF4shLum8fnjJyXyzu67Xm5PMfnpZMPARSnhH4qIQNQnhK6oYQMlKOtpdT73//+NBqN3S4nnHDCdGWjAPdfnjQ6fOWxRm/r9jN5fikZ2Df91H1KuG+enYszmic6uu1onnC2VBfRUd2lhH4qIQMzg37qLiV0QwkZKEfbPwonnnhibr755p3foNdrpe+vtmxsveBcOnzebnNb8pMvJ1sGk9kLZt78UjIwcfqpe5Rw3zw0C3Jylqanw5OOZ+WALM5rc2jm59E81FkIZhQd1R1K6KcSMjCz6KfuUEI3lJCBsrT9SLq3tzdHHXXUjssznvGM6chFAdat2fkOCJ1q9CTrrpqZ80vJwMTpp+5Rwn3zJblgx7vsdaqZsbwkF07qezBz6KjuUEI/lZCBmUU/dYcSuqGEDJSl7R+H9evXZ968eTn22GOzfPnybNy48SmvPzIykuHh4d0uzAxD66fm+wxvmJnzS8nAxOmn7lHCffPIHD8FCZo5IsdNwfdhJmino/TTzFVCP5WQgZlFP3WHErqhhAyUpa2l1G/91m9lzZo1uemmm7J69er853/+Z1760pfmscce2+ttVq1alYGBgR2XBQucYzdTPPHYzrfk7FRzNPlVh/+dqnt+KRmYGP3UXUq4bz4tczp+6t52PZmVg9I/qe/BzNBuR+mnmauEfiohAzOHfuoeJXRDCRkoS1uPppcsWZLzzjsvixcvzm//9m/n//2//5ef//zn+fznP7/X26xcuTJDQ0M7LoODg5MOTTUOmJM0Zk3uezRmJQd2+O+tuueXkoGJ0U/dpYT75i/zWMYm+fS9sYzmF/Goqhu021H6aeYqoZ9KyMDMoZ+6RwndUEIGyjKpV7B7+tOfnt/4jd/Ihg17P3eur68vfX19kxlDTQam4pkpSfo7fGZK3fNLyUBn9NP+rYT75iOZivPPG/lZnH/ejfbVUfpp5iqhn0rIwMyln/ZfJXRDCRkoy6Sed7Bly5b8x3/8R+bOnTtVeSjIoguS5uROAkhzLFnU4Wv41j2/lAx0Rj/t30q4b96WNWlM8ul7jfTktnilzm6ko/ZfJfRTCRmYufTT/quEbighA2Vp69H0JZdckrVr1+bBBx/Mbbfdlt/5nd/JrFmz8oY3vGG68lGj2QuThUuTRofn0zV6k6OXdf5WnXXPLyUDE6OfuksJ981HM5gHckNG80RHtx/NE7k/X8qjeajzEMwYOqp7lNBPJWRg5tBP3aOEbighA2Vpayn10EMP5Q1veEMWLVqU3/3d383hhx+e22+/PUccccR05aNmp1ySNLd1dtvmaLL44pk9v5QM7Jt+6j4l3De/nssyKwd0dNuezMrNuWLyIZgRdFR3KaGfSsjAzKCfuksJ3VBCBsrR1n7ys5/97HTloFBzz0hOuyy5/ZL2b3vaR1u3n8nzS8nAvumn7lPCfXN9vp0v5OKcl8vbvu0/5d1Zn29PPgQzgo7qLiX0UwkZmBn0U3cpoRtKyEA5JvdiGHSFky9qlUay79Mst3/9tMtat9sf5peSAXiyEu6bN+eKfCGtX9nt66l827/+hVzsLCnYz5XQTyVkAMpTQjeUkIEyWEqxT41G6xTJZWuTha9J0mi9Def2t/Lc8XGj9fVla1vXbzT2j/mlZACerJT75s25IpfljDyQr2QsYxnNtoxmW5oZy2ieyGi2ZSxjeSBfyWU5w0IKukAJ/VRCBqA8JXRDCRkoQ4cvL0Y3mntG67JlMFl3VTK8IfnVcHJgf+stORddOL0vOFf3/FIyAE9Wwn1zfb6d9fl2Ds38vCQX5ogcl4PSn19kOD/LhtyWq7yoOXShEvqphAxAeUrohhIyUC9LKdo2e0Fy6vu6d34pGYAnK+G++WgeylfywXpDAMUpoZ9KyACUp4RuKCED9fD0PQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJVrNJvNZpUDh4eHMzAwkDSSQ+ZVObnl8c1Jcyxp9CQHz61+vgwylJah7vlJsnVTkmYyNDSU/v7+ekKk/n5KyjgedWeoe74MMoxXQkfpJxlKmS9DWRn0U0sJx0IGGUqZX0qGifZTfUspgHGKWUoB7EER/+gD2AP9BJRqX/3UW2GW3TlTSgYZishQ9/xk5xa9GH7T1/U/kzLIsKuiOko/dX2GuufLUFYG/dRSwrGQQYZS5peSYaL9VNtS6uCjkuUPVT/32vnJ1p+2Dkwd82WQobQMdc9PkmvmtYqzFHX1U1LG8ag7Q93zZZBhvJI6Sj/JUPd8GcrKoJ9aSjgWMshQyvxSMky0n7zQOQAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMrV9+57AABAZbZsTNatSYbWJ088lhwwJxk4Pll0QTJ7Yd3pgG6mn7qXpRQAAOzHNq1N7r882XhD6+3Bk6Q5mjRmtT6+5/3J0UuTxZckc8+oLSbQhfQTnr4HAAD7oWYzue+y5IYzk8EbkzRb/9hrjv7669s/biYbb0y+/LLWPw6bzRpDA11BP7GdpRQAAOyHHrgiuePdrY+b2576utu/fvslrdsBTCf9xHZtL6V++tOf5o1vfGMOP/zwHHTQQTn55JNz9913T0c2gLboJ6BkOooqbVrb+gdcJ26/JNl869TmoWz6iSrpJ3bV1mtKPfroozn99NNz1lln5cYbb8wRRxyR9evX59BDD52ufAATop+Akukoqnb/5Umjd99nIOxJo7d1e6/f0h30E1XTT+yqraXURz7ykSxYsCBXXXXVjj875phjpjwUQLv0E1AyHUWVtmxsvWhwOnztlea25CdfTrYMJrMXTGk0CqSfqJJ+Yry2nr73pS99KS94wQty3nnn5cgjj8zznve8fOpTn5qubAATpp+AkukoqrRuzc53sepUoydZd9W+r8fMp5+okn5ivLZ+HH784x9n9erVOf744/PVr341b3nLW/KOd7wjV1999V5vMzIykuHh4d0uAFNNPwEla7ej9BOTMbR+ar7P8Iap+T6UTT9RJf3EeG09fW9sbCwveMELcumllyZJnve85+X73/9+/vZv/zbnn3/+Hm+zatWqfOADH5h8UoCnoJ+AkrXbUfqJyXjisZ1vq96p5mjyK7uGrqCfqJJ+Yry2zpSaO3dunvvc5+72Z7/5m7+ZjRs37vU2K1euzNDQ0I7L4OBgZ0kBnoJ+AkrWbkfpJybjgDlJY9bkvkdjVnJg/9TkoWz6iSrpJ8Zr60yp008/PevWrdvtz370ox/l6KOP3utt+vr60tfX11k6gAnST0DJ2u0o/cRkDBw/Nd+n/7ip+T6UTT9RJf3EeG2dKfUnf/Inuf3223PppZdmw4YNue666/L3f//3WbFixXTlA5gQ/QSUTEdRpUUXJM2xyX2P5liy6MIpiUPh9BNV0k+M19ZS6oUvfGGuv/76fOYzn8lJJ52UD37wg/nYxz6W5cuXT1c+gAnRT0DJdBRVmr0wWbg0abT1nIidGr3J0cu83Xq30E9UST8xXts/CkuXLs3SpUunIwvApOgnoGQ6iiqdckmy8cud3bY5miy+eGrzUDb9RJX0E7tq60wpAACgfHPPSE67rLPbnvbR1u0BpoN+YleWUgAAsB86+aKd//Db11Nltn/9tMtatwOYTvqJ7SylAABgP9RotJ7msmxtsvA1SRqtt1Lf/nbsOz5utL6+bG3r+o1GnamBbqCf2K7DlxcDAABmgrlntC5bBpN1VyXDG5JfDScH9rfeVn3RhV40GKiHfsJSCgAAusDsBcmp76s7BcCT6afu5el7AAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKtdoNpvNKgcODw9nYGAgaSSHzKtycsvjm5PmWNLoSQ6eW/18GWQoLUPd85Nk66YkzWRoaCj9/f31hEj9/ZSUcTzqzlD3fBlkGK+EjtJPMpQyX4ayMuinlhKOhQwylDK/lAwT7af6llIA4xSzlALYgyL+0QewB/oJKNW++qm3wiy7c6aUDDIUkaHu+cnOLXox/Kav638mZZBhV0V1lH7q+gx1z5ehrAz6qaWEYyGDDKXMLyXDRPuptqXUwUclyx+qfu6185OtP20dmDrmyyBDaRnqnp8k18xrFWcp6uqnpIzjUXeGuufLIMN4JXWUfpKh7vkylJVBP7WUcCxkkKGU+aVkmGg/eaFzAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAULm2llLPfvaz02g0nnRZsWLFdOUDmDAdBZRKPwGl0k9AnXrbufJdd92V0dHRHZ9///vfz9lnn53zzjtvyoMBtEtHAaXST0Cp9BNQp7aWUkccccRun3/4wx/Oc57znLzsZS+b0lAAndBRQKn0E1Aq/QTUqePXlPrVr36Va665Jm9+85vTaDSmMhPApOkooFT6CSiVfgKq1taZUrv64he/mJ///Oe54IILnvJ6IyMjGRkZ2fH58PBwpyMBJmwiHaWfgDroJ6BU+gmoWsdnSl155ZVZsmRJ5s2b95TXW7VqVQYGBnZcFixY0OlIgAmbSEfpJ6AO+gkolX4CqtbRUuonP/lJbr755vzhH/7hPq+7cuXKDA0N7bgMDg52MhJgwibaUfoJqJp+Akqln4A6dPT0vauuuipHHnlkzjnnnH1et6+vL319fZ2MAejIRDtKPwFV009AqfQTUIe2z5QaGxvLVVddlfPPPz+9vR2/JBXAtNBRQKn0E1Aq/QTUpe2l1M0335yNGzfmzW9+83TkAZgUHQWUSj8BpdJPQF3aXoO/6lWvSrPZnI4sAJOmo4BS6SegVPoJqEvH774HAAAAAJ2ylAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVazSbzWaVA4eHhzMwMJA0kkPmVTm55fHNSXMsafQkB8+tfr4MMpSWoe75SbJ1U5JmMjQ0lP7+/npCpP5+Sso4HnVnqHu+DDKMV0JH6ScZSpkvQ1kZ9FNLCcdCBhlKmV9Khon2U31LKYBxillKAexBEf/oA9gD/QSUal/91Fthlt05U0oGGYrIUPf8ZOcWvRh+09f1P5MyyLCrojpKP3V9hrrny1BWBv3UUsKxkEGGUuaXkmGi/VTbUurgo5LlD1U/99r5ydaftg5MHfNlkKG0DHXPT5Jr5rWKsxR19VNSxvGoO0Pd82WQYbySOko/yVD3fBnKyqCfWko4FjLIUMr8UjJMtJ+80DkAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAACoXFtLqdHR0bz3ve/NMccck4MOOijPec5z8sEPfjDNZnO68gFMiH4CSqajgFLpJ6BOve1c+SMf+UhWr16dq6++OieeeGLuvvvuXHjhhRkYGMg73vGO6coIsE/6CSiZjgJKpZ+AOrW1lLrtttty7rnn5pxzzkmSPPvZz85nPvOZ3HnnndMSDmCi9BNQMh0FlEo/AXVq6+l7L3nJS/KNb3wjP/rRj5Ik9913X/71X/81S5Ys2ettRkZGMjw8vNsFYKrpJ6Bk7XaUfgKqop+AOrV1ptR73vOeDA8P54QTTsisWbMyOjqaD33oQ1m+fPleb7Nq1ap84AMfmHRQgKein4CStdtR+gmoin4C6tTWmVKf//znc+211+a6667Ld7/73Vx99dW57LLLcvXVV+/1NitXrszQ0NCOy+Dg4KRDA4ynn4CStdtR+gmoin4C6tTWmVLvfve78573vCe///u/nyQ5+eST85Of/CSrVq3K+eefv8fb9PX1pa+vb/JJAZ6CfgJK1m5H6SegKvoJqFNbZ0o9/vjj6enZ/SazZs3K2NjYlIYCaJd+Akqmo4BS6SegTm2dKbVs2bJ86EMfysKFC3PiiSfme9/7Xq644oq8+c1vnq58ABOin4CS6SigVPoJqFNbS6m/+Zu/yXvf+9689a1vzSOPPJJ58+blj/7oj/K+971vuvIBTIh+Akqmo4BS6SegTm0tpebMmZOPfexj+djHPjZNcQA6o5+AkukooFT6CahTW68pBQAAAABTwVIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByjWaz2axy4NDQUJ7+9KcnSQ6eW+XklscfTtJM0kgOPqr6+TLIUFqGuucnyeObW//785//PAMDA/WESP39lBRyPPxMyiDD7hkK6Cj9JEMp82UoLIN+SlLIsZBBhkLmF5Nhgv1U+VLqoYceyoIFC6ocCcwQg4ODmT9/fm3z9RPwVOrsKP0EPBX9BJRqX/1U+VJqbGwsmzZtypw5c9JoNNq+/fDwcBYsWJDBwcH09/dPQ0IZZkqGuufLMHUZms1mHnvsscybNy89PfU9q1g/ybA/Zah7/v6UoYSOmmw/JfUfj7rnyyBDaRn00051H4sSMtQ9XwYZpjrDRPupdzIhO9HT0zMlW/z+/v7aDo4MZWWoe74MU5OhzqftbaefZNgfM9Q9f3/JUHdHTVU/JfUfj7rnyyBDaRn00051H4sSMtQ9XwYZpjLDRPrJC50DAAAAUDlLKQAAAAAqN+OWUn19ffmLv/iL9PX1ydDlGeqeL0NZGUpQwt+DDDKUMl+G8tT9d1H3fBlkKC1D3fNLUsLfRd0Z6p4vgwx1Zaj8hc4BAAAAYMadKQUAAADAzGcpBQAAAEDlLKUAAAAAqJylFAAAAACVm1FLqe985zuZNWtWzjnnnMpnX3DBBWk0Gjsuhx9+eF796lfn/vvvrzzLww8/nLe//e059thj09fXlwULFmTZsmX5xje+Me2zd/17OOCAA/LMZz4zZ599dj796U9nbGxs2uePz7Dr5dWvfnUl8/eVY8OGDZXMf/jhh/POd74zxx13XJ72tKflmc98Zk4//fSsXr06jz/++LTPv+CCC/K6173uSX9+yy23pNFo5Oc///m0ZyiNjtJP43PU1VF191NSb0fppyfTT/ppfA795DFUKfSTfhqfQz91Vz/NqKXUlVdembe//e259dZbs2nTpsrnv/rVr87mzZuzefPmfOMb30hvb2+WLl1aaYYHH3wwp556ar75zW/mox/9aB544IHcdNNNOeuss7JixYpKMmz/e3jwwQdz44035qyzzso73/nOLF26NNu2bas0w66Xz3zmM5XM3leOY445Ztrn/vjHP87znve8fO1rX8ull16a733ve/nOd76TP/3TP80NN9yQm2++edoz8GTd3lH66ck56uyouvop0VEl0k/6aXwO/aSfSqGf9NP4HPqpu/qpt+4AE7Vly5Z87nOfy913352HH344a9asyZ//+Z9XmqGvry9HHXVUkuSoo47Ke97znrz0pS/Nz372sxxxxBGVZHjrW9+aRqORO++8M4cccsiOPz/xxBPz5je/uZIMu/49POtZz8rzn//8nHbaaXnFK16RNWvW5A//8A8rzVCnunK89a1vTW9vb+6+++7dfg6OPfbYnHvuuWk2m5Vn6nY6Sj/tLUdd6sygo8qin/TT3nLURT+xnX7ST3vLURf9VL0Zc6bU5z//+ZxwwglZtGhR3vjGN+bTn/50rQdly5Ytueaaa3Lcccfl8MMPr2Tm//zP/+Smm27KihUrdvsh3e7pT396JTn25OUvf3lOOeWU/PM//3NtGbrFf//3f+drX/vaXn8OkqTRaFScim7vKP3EdjqqPPpJP9Gin8qjn/QTLd3cTzNmKXXllVfmjW98Y5LWKXVDQ0NZu3ZtpRluuOGGzJ49O7Nnz86cOXPypS99KZ/73OfS01PNX+OGDRvSbDZzwgknVDKvXSeccEIefPDBSmbteiy2Xy699NJKZj9VjvPOO2/aZ27/OVi0aNFuf/6MZzxjR44/+7M/m/YcyZ6Pw5IlSyqZXZpu7yj9tLsSOqqOfkrK6Sj9tJN+0k+70k/191Oio7bTT/ppV/qpO/tpRjx9b926dbnzzjtz/fXXJ0l6e3vze7/3e7nyyitz5plnVpbjrLPOyurVq5Mkjz76aD75yU9myZIlufPOO3P00UdP+/zST9drNpuVbW93PRbbHXbYYZXMfqoce9tqV+HOO+/M2NhYli9fnpGRkUpm7uk43HHHHTseXHQLHaWfxiuho0rqp6T6jtJPLfpJP42nn57MY6h66Cf9NJ5+erJu6KcZsZS68sors23btsybN2/HnzWbzfT19eXjH/94BgYGKslxyCGH5Ljjjtvx+T/8wz9kYGAgn/rUp/JXf/VX0z7/+OOPT6PRyA9/+MNpn9WJH/zgB5W9CNz4Y1GXOnIcd9xxaTQaWbdu3W5/fuyxxyZJDjrooMqy7On//0MPPVTZ/FLoKP00XgkdVVeGUjpKP7XoJ/00nn6qv58SHZXop0Q/jaefurOfin/63rZt2/KP//iPufzyy3PvvffuuNx3332ZN29eLe+4tl2j0UhPT09+8YtfVDLvsMMOy2//9m/nE5/4RLZu3fqkr9f59rHf/OY388ADD+T1r399bRm6xeGHH56zzz47H//4x/f4c0C1dFSLfmI7HVUO/dSin9hOP5VDP7XoJ7br5n4q/kypG264IY8++mj+4A/+4Enb8te//vW58sor88d//MeVZBkZGcnDDz+cpHVq58c//vFs2bIly5Ytq2R+knziE5/I6aefnhe96EX5y7/8yyxevDjbtm3L17/+9axevTo/+MEPpj3D9r+H0dHR/Nd//VduuummrFq1KkuXLs2b3vSmaZ+/a4Zd9fb25hnPeEYl8+v2yU9+Mqeffnpe8IIX5P3vf38WL16cnp6e3HXXXfnhD3+YU089te6IXUNH7aSfnpxjVzpKR1VNP+2kn56cY1f6ST9VTT/tpJ+enGNX+qkL+qlZuKVLlzZf85rX7PFrd9xxRzNJ87777pv2HOeff34zyY7LnDlzmi984Qub//RP/zTts8fbtGlTc8WKFc2jjz66eeCBBzaf9axnNV/72tc2v/Wtb0377F3/Hnp7e5tHHHFE85WvfGXz05/+dHN0dHTa54/PsOtl0aJFlczfNce5555b6cxdbdq0qfm2t72tecwxxzQPOOCA5uzZs5svetGLmh/96EebW7dunfb5e/v//61vfauZpPnoo49Oe4YS6KjddXs/jc9RV0fV3U/NZr0dpZ9a9NPu9JN+2s5jqPrpp93pJ/20XTf2U6PZLPzV1QAAAADY7xT/mlIAAAAA7H8spQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHL/P+MeJ8jHvWnsAAAAAElFTkSuQmCC\n" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def single_turn(\n", + " current_boards: np, policy: GamePolicy\n", + ") -> tuple[np.ndarray, np.ndarray]:\n", + " \"\"\"Execute a single turn on a board.\n", + "\n", + " Places a new stone on the board. Turns captured enemy stones.\n", + "\n", + " Args:\n", + " current_boards: The current board before the game.\n", + " policy: The game policy to be used.\n", + "\n", + " Returns:\n", + " The new game board and the policy vector containing the index of the action used.\n", + " \"\"\"\n", + " policy_results = policy.get_policy(current_boards)\n", + "\n", + " # if the constant VERIFY_POLICY is set to true the policy is verified. Should be good though.\n", + " # todo deactivate the policy verification after some testing.\n", + " if VERIFY_POLICY:\n", + " assert np.all(moves_possible(current_boards, policy_results)), (\n", + " current_boards[(moves_possible(current_boards, policy_results) == False)],\n", + " policy_results[(moves_possible(current_boards, policy_results) == False)],\n", + " np.where(moves_possible(current_boards, policy_results) == False),\n", + " )\n", + " return do_moves(current_boards, policy_results), policy_results\n", + "\n", + "\n", + "%timeit single_turn(get_new_games(EXAMPLE_STACK_SIZE), RandomPolicy(1))\n", + "VERIFY_POLICY = False # type: ignore\n", + "%timeit single_turn(get_new_games(EXAMPLE_STACK_SIZE), RandomPolicy(1))\n", + "VERIFY_POLICY = True # type: ignore\n", + "plot_othello_boards(\n", + " single_turn(get_new_games(EXAMPLE_STACK_SIZE), RandomPolicy(1))[0][:8]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Simulate a stack of games\n", + "This function will simulate a stack of games and return an array of policies and histories." ], "metadata": { "collapsed": false @@ -951,63 +1107,58 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Exception in thread Thread-5 (_handle_workers):\n", + "Traceback (most recent call last):\n", + " File \"C:\\Program Files\\Python310\\lib\\threading.py\", line 1016, in _bootstrap_inner\n", + " self.run()\n", + " File \"C:\\Program Files\\Python310\\lib\\threading.py\", line 953, in run\n", + " self._target(*self._args, **self._kwargs)\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\pool.py\", line 516, in _handle_workers\n", + " cls._maintain_pool(ctx, Process, processes, pool, inqueue,\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\pool.py\", line 340, in _maintain_pool\n", + " Pool._repopulate_pool_static(ctx, Process, processes, pool,\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\pool.py\", line 329, in _repopulate_pool_static\n", + " w.start()\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\process.py\", line 121, in start\n", + " self._popen = self._Popen(self)\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\context.py\", line 336, in _Popen\n", + " return Popen(process_obj)\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\popen_spawn_win32.py\", line 93, in __init__\n", + " reduction.dump(process_obj, to_child)\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\reduction.py\", line 60, in dump\n", + " ForkingPickler(file, protocol).dump(obj)\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\synchronize.py\", line 104, in __getstate__\n", + " h = context.get_spawning_popen().duplicate_for_child(sl.handle)\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\popen_spawn_win32.py\", line 99, in duplicate_for_child\n", + " return reduction.duplicate(handle, self.sentinel)\n", + " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\reduction.py\", line 79, in duplicate\n", + " return _winapi.DuplicateHandle(\n", + "PermissionError: [WinError 5] Zugriff verweigert\n" + ] + } + ], "source": [ - "class RandomPolicy(GamePolicy):\n", - " @property\n", - " def policy_name(self) -> str:\n", - " return \"random\"\n", - "\n", - " def internal_policy(self, boards: np.ndarray) -> np.ndarray:\n", - " random_values = np.random.rand(*boards.shape)\n", - " return random_values\n", - " # return np.argmax(random_values, (1, 2))\n", - "\n", - "\n", - "rnd_policy = RandomPolicy()\n", - "assert rnd_policy.policy_name == \"random\"\n", - "rnd_policy_result = rnd_policy.get_policy(get_new_games(1))\n", - "assert np.any((5 >= rnd_policy_result) & (rnd_policy_result >= 3))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def single_turn(\n", - " current_boards: np, policy: GamePolicy\n", - ") -> tuple[np.ndarray, np.ndarray]:\n", - " policy_results = policy.get_policy(current_boards)\n", - "\n", - " assert np.all(moves_possible(current_boards, policy_results)), (\n", - " current_boards[(moves_possible(current_boards, policy_results) == False)],\n", - " policy_results[(moves_possible(current_boards, policy_results) == False)],\n", - " np.where(moves_possible(current_boards, policy_results) == False),\n", - " )\n", - "\n", - " return do_moves(current_boards, policy_results), policy_results\n", - "\n", - "\n", - "%timeit single_turn(get_new_games(100), RandomPolicy())\n", - "single_turn(get_new_games(100), RandomPolicy())[0]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "\n", + "from tqdm.notebook import tqdm\n", "\n", "\n", "def simulate_game(\n", " nr_of_games: int,\n", " policies: tuple[GamePolicy, GamePolicy],\n", ") -> tuple[np.ndarray, np.ndarray]:\n", + " \"\"\"Simulates a stack of games.\n", "\n", + " Args:\n", + " nr_of_games: The number of games that should be simulated.\n", + " policies: The policies that should be used to simulate the game.\n", + "\n", + " Returns:\n", + " A stack of board histories and actions.\n", + " \"\"\"\n", " board_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 8, 8))\n", " action_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 2))\n", " current_boards = get_new_games(nr_of_games)\n", @@ -1026,21 +1177,88 @@ " return board_history_stack, action_history_stack\n", "\n", "\n", - "%timeit simulate_game(100, (RandomPolicy(), RandomPolicy()))\n", - "simulate_game(10, (RandomPolicy(), RandomPolicy()))" + "simulation_results = simulate_game(1, (RandomPolicy(1), RandomPolicy(1)))" ] }, { "cell_type": "code", "execution_count": null, - "metadata": {}, "outputs": [], - "source": [] + "source": [ + "\n", + "%timeit simulate_game(100, (RandomPolicy(1), RandomPolicy(1)))\n", + "# simulate_game(EXAMPLE_STACK_SIZE, (RandomPolicy(1), RandomPolicy(1)))" + ], + "metadata": { + "collapsed": false + } }, { "cell_type": "code", "execution_count": null, - "metadata": {}, + "outputs": [], + "source": [ + "policies_to_use = RandomPolicy(1), RandomPolicy(1)\n", + "with Pool(3) as pool:\n", + " results = pool.map(simulate_game, [100, policies_to_use])" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "is_executing": true + } + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "a = np.array(\n", + " [\n", + " [\n", + " [-1, -1, -1, -1, 0, 0, 0, 0],\n", + " [1, 1, -1, 1, 1, 0, 0, 0],\n", + " [1, 1, -1, 1, 1, 1, 0, 0],\n", + " [0, 1, -1, 1, 1, 1, 0, 0],\n", + " [0, 1, 1, 1, 1, 1, 0, 0],\n", + " [-1, 1, 1, 1, 1, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " ]\n", + " ],\n", + " dtype=int,\n", + ")\n", + "a" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "is_executing": true + } + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "is_executing": true + } + }, + "outputs": [], + "source": [ + "RandomPolicy(1).get_policy(a)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "is_executing": true + } + }, "outputs": [], "source": [ "import numpy as np\n", @@ -1291,7 +1509,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "pycharm": { + "is_executing": true + } + }, "outputs": [], "source": [ "plot_othello_boards(create_test_game()[-3:])" @@ -1300,7 +1522,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "pycharm": { + "is_executing": true + } + }, "outputs": [], "source": [ "array = create_test_game()" @@ -1321,7 +1547,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "pycharm": { + "is_executing": true + } + }, "outputs": [], "source": [] } -- 2.49.0 From 0c81f2d00631d8c00ac88fc7427883c83fa64907 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Mon, 13 Feb 2023 03:37:00 +0100 Subject: [PATCH 22/31] Added a reword function for q learning. --- main.ipynb | 1147 ++++++++++++++++++++++++++++++---------------------- 1 file changed, 662 insertions(+), 485 deletions(-) diff --git a/main.ipynb b/main.ipynb index 792eacd..d58f61c 100644 --- a/main.ipynb +++ b/main.ipynb @@ -16,6 +16,7 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "\n", "## Content\n", @@ -24,13 +25,11 @@ "* [Some common Otello strategies](#some-common-otello-strategies) introduces some easy approaches to a classic Otello AI and defines some behavioral expectations.\n", "* [Initial design decisions](#initial-design-decisions) an explanation about some initial design decision and assumptions\n", "* [Imports and dependencies](#imports-and-dependencies) explains what libraries where used" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "\n", "## The game rules\n", @@ -64,13 +63,11 @@ "The scores change in the course of the game and converges against one. This gives some indications of what to expect from an Othello AI.\n", "\n", "\"ComputerPossitionScore\"\n" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Initial design decisions\n", "\n", @@ -84,18 +81,19 @@ "\n", "Since computation time is critical all computational have results are saved.\n", "The analysis of those is then repeated in real time. If a recalculation of such a section is required the save file can be deleted and the code should be executed again." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "pycharm": { + "is_executing": true + } + }, "outputs": [], "source": [ - "from multiprocessing import Pool\n", + "\n", "\n", "%load_ext blackcellmagic" ] @@ -133,6 +131,7 @@ "metadata": {}, "outputs": [], "source": [ + "from multiprocessing import Pool\n", "import itertools\n", "import numpy as np\n", "import abc\n", @@ -169,13 +168,11 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "The directions array contains all the numerical offsets needed to move along one of the 8 directions in a 2 dimensional grid. This will allow an iteration over the game board.\n", "![8-directions.png](8-directions.png \"Offset in 8 directions\")" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", @@ -184,7 +181,16 @@ "outputs": [ { "data": { - "text/plain": "array([[-1, -1],\n [-1, 0],\n [-1, 1],\n [ 0, -1],\n [ 0, 1],\n [ 1, -1],\n [ 1, 0],\n [ 1, 1]])" + "text/plain": [ + "array([[-1, -1],\n", + " [-1, 0],\n", + " [-1, 1],\n", + " [ 0, -1],\n", + " [ 0, 1],\n", + " [ 1, -1],\n", + " [ 1, 0],\n", + " [ 1, 1]])" + ] }, "execution_count": 4, "metadata": {}, @@ -202,20 +208,22 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "Another constant needed is the initial start square at the center of the board." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { - "text/plain": "array([[-1, 1],\n [ 1, -1]])" + "text/plain": [ + "array([[-1, 1],\n", + " [ 1, -1]])" + ] }, "execution_count": 5, "metadata": {}, @@ -228,10 +236,7 @@ ")\n", "START_SQUARE.setflags(write=False)\n", "START_SQUARE" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", @@ -250,7 +255,16 @@ "outputs": [ { "data": { - "text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])" + "text/plain": [ + "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0]])" + ] }, "execution_count": 6, "metadata": {}, @@ -311,16 +325,14 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Visualisation tools\n", "\n", "In this section a visualisation help was implemented for debugging of the game and a proper display of the results.\n", "For this visualisation ChatGPT was used as a prompted code generator that was later reviewed and refactored by hand to integrate seamlessly into the project as a whole.\n", "White stones represent the player, black stones the enemy. A single plot can be used as a subplot when the `ax` argument is used." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", @@ -329,8 +341,10 @@ "outputs": [ { "data": { - "text/plain": "
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\n" 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\n", + "text/plain": [ + "
" + ] }, "metadata": {}, "output_type": "display_data" @@ -410,8 +424,27 @@ " plt.show()" ] }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def drop_duplicate_boards(boards: np.ndarray) -> np.ndarray:\n", + " \"\"\"Drop boards that follow each other and are duplicates will be dropped.\n", + "\n", + " Args:\n", + " boards: A set of boards to be reduced.\n", + "\n", + " Returns:\n", + " A sequence of boards where boards that where equal are dropped.\n", + " \"\"\"\n", + " return boards[~np.all(boards == np.roll(boards, axis=0, shift=1), axis=(1, 2))]" + ] + }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Find possible actions to take\n", "\n", @@ -426,23 +459,24 @@ "If the board end is reached or en empty filed before reaching a field occupied by the player that direction does not surround enemy stones.\n", "If one direction surrounds enemy stone a turn is possible.\n", "This detailed step is implemented as a recursion and need to go at leas one step to return True." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": { "tags": [] }, "outputs": [ { "data": { - "text/plain": "array([[[1, 1, 1],\n [1, 0, 1],\n [1, 1, 1]]])" + "text/plain": [ + "array([[[1, 1, 1],\n", + " [1, 0, 1],\n", + " [1, 1, 1]]])" + ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -456,22 +490,31 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "9.31 ms ± 1.67 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "831 ms ± 25.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "8.02 ms ± 181 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "800 ms ± 5.98 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { "data": { - "text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])" + "text/plain": [ + "array([[[False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, True, False, False, False, False],\n", + " [False, False, True, False, False, False, False, False],\n", + " [False, False, False, False, False, True, False, False],\n", + " [False, False, False, False, True, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False]]])" + ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -550,17 +593,15 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "Besides the ability to generate an array of possible turns there needs to be a functions that check if a given turn is possible.\n", "On is needed for the action space validation. The other is for validating a players turn." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -595,7 +636,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -650,6 +691,7 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Reword functions\n", "\n", @@ -659,22 +701,20 @@ "It is probably not be possible to weight the current score to high in a reword function since that would be to close to a classic greedy algorithm.\n", "But some direct influence would increase the learning speed.\n", "In the next section are all three reword functions implemented to be combined and weight later on as needed." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "172 µs ± 7.68 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "29.9 µs ± 1.08 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "31.6 µs ± 1.01 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" + "174 µs ± 6.34 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "31.6 µs ± 1.6 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "30.8 µs ± 1.58 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" ] } ], @@ -731,26 +771,21 @@ "%timeit final_boards_evaluation(_boards)\n", "%timeit evaluate_boards(_boards)\n", "%timeit evaluate_who_won(_boards)" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Execute a chosen action\n", "\n", "After an evaluation what turns are possible there needs to be a function that executes a turn.\n", "This next sections does that." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -762,19 +797,22 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "89.4 ms ± 3.1 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "91.5 ms ± 5.4 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { "data": { - "text/plain": "
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\n" 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\n", + "text/plain": [ + "
" + ] }, "metadata": {}, "output_type": "display_data" @@ -865,26 +903,21 @@ " get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE)\n", " )[0]\n", ")" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## An abstract reversi game policy\n", "\n", "For an easy use of policies an abstract class containing the policy generation / requests an action in an inherited instance of this class.\n", "This class filters the policy to only propose valid actions. Inherited instance do not need to care about this. This super class also manges exploration and exploitation with the epsilon value." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -957,9 +990,7 @@ " max_indices = [\n", " np.unravel_index(policy.argmax(), policy.shape) for policy in policies\n", " ]\n", - " policy_vector = np.array(max_indices)\n", - " no_turn_possible_1 = np.all(policy_vector == 0, 1)\n", - " zero_pos = policies[:, 0, 0] == -1.0\n", + " policy_vector = np.array(max_indices, dtype=int)\n", " no_turn_possible = np.all(policy_vector == 0, 1) & (policies[:, 0, 0] == -1.0)\n", "\n", " policy_vector[no_turn_possible, :] = IMPOSSIBLE\n", @@ -968,6 +999,7 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## A first policy\n", "\n", @@ -975,14 +1007,12 @@ "The easiest benchmark is to play against a random player.\n", "The easiest player to use as a benchmark is the random player.\n", "For this and testing purpose the random policy was implemented." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, + "metadata": {}, "outputs": [], "source": [ "class RandomPolicy(GamePolicy):\n", @@ -1008,49 +1038,44 @@ "\n", "rnd_policy_result = rnd_policy.get_policy(get_new_games(10))\n", "assert np.any((5 >= rnd_policy_result) & (rnd_policy_result >= 3))" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Putting the game simulation together\n", "Now it's time to bring all together for a proper simulation." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Playing a single turn\n", "\n", "The next function needed is used to request a policy, verify that the turn is legit and place a stone and turn enemy stones if possible." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "1.02 s ± 58.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", - "949 ms ± 43.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "982 ms ± 33.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", + "881 ms ± 13.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { "data": { - "text/plain": "
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\n" 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\n", + "text/plain": [ + "
" + ] }, "metadata": {}, "output_type": "display_data" @@ -1095,57 +1120,31 @@ }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Simulate a stack of games\n", "This function will simulate a stack of games and return an array of policies and histories." - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, + "execution_count": 21, + "metadata": { + "scrolled": false + }, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "Exception in thread Thread-5 (_handle_workers):\n", - "Traceback (most recent call last):\n", - " File \"C:\\Program Files\\Python310\\lib\\threading.py\", line 1016, in _bootstrap_inner\n", - " self.run()\n", - " File \"C:\\Program Files\\Python310\\lib\\threading.py\", line 953, in run\n", - " self._target(*self._args, **self._kwargs)\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\pool.py\", line 516, in _handle_workers\n", - " cls._maintain_pool(ctx, Process, processes, pool, inqueue,\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\pool.py\", line 340, in _maintain_pool\n", - " Pool._repopulate_pool_static(ctx, Process, processes, pool,\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\pool.py\", line 329, in _repopulate_pool_static\n", - " w.start()\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\process.py\", line 121, in start\n", - " self._popen = self._Popen(self)\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\context.py\", line 336, in _Popen\n", - " return Popen(process_obj)\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\popen_spawn_win32.py\", line 93, in __init__\n", - " reduction.dump(process_obj, to_child)\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\reduction.py\", line 60, in dump\n", - " ForkingPickler(file, protocol).dump(obj)\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\synchronize.py\", line 104, in __getstate__\n", - " h = context.get_spawning_popen().duplicate_for_child(sl.handle)\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\popen_spawn_win32.py\", line 99, in duplicate_for_child\n", - " return reduction.duplicate(handle, self.sentinel)\n", - " File \"C:\\Program Files\\Python310\\lib\\multiprocessing\\reduction.py\", line 79, in duplicate\n", - " return _winapi.DuplicateHandle(\n", - "PermissionError: [WinError 5] Zugriff verweigert\n" - ] + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "from tqdm.notebook import tqdm\n", - "\n", - "\n", "def simulate_game(\n", " nr_of_games: int,\n", " policies: tuple[GamePolicy, GamePolicy],\n", @@ -1159,8 +1158,8 @@ " Returns:\n", " A stack of board histories and actions.\n", " \"\"\"\n", - " board_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 8, 8))\n", - " action_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 2))\n", + " board_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 8, 8), dtype=int)\n", + " action_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 2), dtype=int)\n", " current_boards = get_new_games(nr_of_games)\n", " for turn_index in range(SIMULATE_TURNS):\n", " policy_index = turn_index % 2\n", @@ -1177,359 +1176,541 @@ " return board_history_stack, action_history_stack\n", "\n", "\n", - "simulation_results = simulate_game(1, (RandomPolicy(1), RandomPolicy(1)))" + "simulation_results = simulate_game(1, (RandomPolicy(1), RandomPolicy(1)))\n", + "plot_othello_boards(\n", + " drop_duplicate_boards(np.reshape(simulation_results[0], (-1, 8, 8)))\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "outputs": [], + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8.08 s ± 262 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + } + ], "source": [ - "\n", "%timeit simulate_game(100, (RandomPolicy(1), RandomPolicy(1)))\n", - "# simulate_game(EXAMPLE_STACK_SIZE, (RandomPolicy(1), RandomPolicy(1)))" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": null, - "outputs": [], - "source": [ - "policies_to_use = RandomPolicy(1), RandomPolicy(1)\n", - "with Pool(3) as pool:\n", - " results = pool.map(simulate_game, [100, policies_to_use])" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "is_executing": true - } - } - }, - { - "cell_type": "code", - "execution_count": null, - "outputs": [], - "source": [ - "a = np.array(\n", - " [\n", - " [\n", - " [-1, -1, -1, -1, 0, 0, 0, 0],\n", - " [1, 1, -1, 1, 1, 0, 0, 0],\n", - " [1, 1, -1, 1, 1, 1, 0, 0],\n", - " [0, 1, -1, 1, 1, 1, 0, 0],\n", - " [0, 1, 1, 1, 1, 1, 0, 0],\n", - " [-1, 1, 1, 1, 1, 0, 0, 0],\n", - " [0, 0, 0, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ]\n", - " ],\n", - " dtype=int,\n", - ")\n", - "a" - ], - "metadata": { - "collapsed": false, - "pycharm": { - "is_executing": true - } - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "pycharm": { - "is_executing": true - } - }, - "outputs": [], - "source": [ - "RandomPolicy(1).get_policy(a)" + "simulation_results = simulate_game(10, (RandomPolicy(1), RandomPolicy(1)))" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "pycharm": { - "is_executing": true + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(70, 10, 8, 8)\n", + "(70, 10, 2)\n" + ] } - }, + ], + "source": [ + "print(simulation_results[0].shape)\n", + "print(simulation_results[1].shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": {}, "outputs": [], "source": [ - "import numpy as np\n", - "\n", - "\n", - "def create_test_game():\n", - " test_array = [\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 2, 0, 0, 0],\n", - " [0, 0, 0, 2, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 2, 0, 0, 0],\n", - " [0, 0, 0, 2, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 2, 0, 0, 0],\n", - " [0, 0, 1, 1, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 2, 0, 0, 0],\n", - " [0, 0, 2, 1, 1, 0, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 2, 0, 0, 0],\n", - " [0, 0, 2, 1, 1, 0, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 2, 0, 0, 0],\n", - " [0, 0, 2, 1, 1, 0, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 2, 0, 0, 0],\n", - " [0, 0, 2, 2, 2, 2, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 0, 0, 0],\n", - " [0, 0, 0, 1, 1, 1, 0, 0],\n", - " [0, 0, 2, 2, 2, 2, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 2, 0, 0],\n", - " [0, 0, 0, 1, 2, 2, 0, 0],\n", - " [0, 0, 2, 2, 2, 2, 0, 0],\n", - " [0, 2, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 2, 0, 0],\n", - " [0, 0, 0, 1, 2, 2, 0, 0],\n", - " [0, 0, 2, 2, 1, 2, 0, 0],\n", - " [0, 2, 0, 0, 0, 1, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 2, 0, 0],\n", - " [0, 0, 0, 1, 2, 2, 0, 0],\n", - " [0, 0, 2, 2, 1, 2, 0, 0],\n", - " [0, 2, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 2, 0, 0],\n", - " [0, 0, 0, 1, 2, 2, 0, 0],\n", - " [0, 1, 1, 1, 1, 2, 0, 0],\n", - " [0, 2, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 0, 0, 0],\n", - " [0, 0, 0, 2, 0, 2, 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[0, 0, 2, 1, 0, 1, 0, 0],\n", - " [0, 0, 0, 2, 1, 2, 2, 0],\n", - " [0, 0, 0, 2, 2, 1, 2, 0],\n", - " [2, 2, 2, 2, 2, 2, 2, 2],\n", - " [0, 2, 0, 1, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " [0, 0, 2, 1, 0, 1, 0, 0],\n", - " [0, 0, 0, 2, 1, 2, 2, 0],\n", - " [0, 0, 0, 2, 1, 1, 2, 0],\n", - " [2, 2, 2, 2, 1, 2, 2, 2],\n", - " [0, 2, 0, 1, 1, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " [\n", - " [0, 0, 0, 0, 2, 0, 0, 0],\n", - " [0, 0, 2, 2, 0, 2, 0, 0],\n", - " [0, 0, 0, 2, 1, 2, 2, 0],\n", - " [0, 0, 0, 2, 1, 1, 2, 0],\n", - " [2, 2, 2, 2, 1, 2, 2, 2],\n", - " [0, 2, 0, 1, 1, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 2, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0],\n", - " ],\n", - " ]\n", - " test_array = np.array(test_array)\n", - "\n", - " # swapp 2 by one. 2 was only there for homogenous formating and easier readability while coading.\n", - " test_array[test_array == 2] = -1\n", - " assert np.all(\n", - " np.count_nonzero(test_array, axis=(1, 2))\n", - " == np.arange(4, 4 + test_array.shape[0])\n", + "board_history, action_history = simulation_results" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", + " [-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ],\n", + " [ 0. , 0. , 0. , 0. , 0. , 0.1, 0.1, 0. , 0. , 0. ],\n", + " [-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ],\n", + " [ 0.1, 0.1, 0. , 0.1, 0.1, 0. , 0. , 0.1, 0. , 0. ],\n", + " [-0. , -0.1, -0. , -0.1, -0.1, -0.1, -0.1, -0. , -0. , -0.1],\n", + " [ 0.1, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", + " [-0.1, -0. , -0.1, -0.1, -0.1, -0. , -0.1, -0. , -0. , -0.1],\n", + " [ 0. , 0. , 0. , 0. , 0. , 0.1, 0. , 0. , 0. , 0. ],\n", + " [-0.1, -0. , -0.1, -0.1, -0.1, -0. , 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} + ], + "source": [ + "def calcualte_direct_score(board_history: np.ndarray) -> np.ndarray:\n", + " boards_evaluated = np.reshape(\n", + " evaluate_boards(np.reshape(board_history, (-1, 8, 8))), (SIMULATE_TURNS, -1)\n", " )\n", + " direct_score = boards_evaluated - np.roll(boards_evaluated, shift=-1, axis=0)\n", + " direct_score[-1] = 0\n", + " return direct_score / 64\n", "\n", - " # validated that only one stone is added per turn\n", - " zero_array = test_array == 0\n", - " diff = zero_array != np.roll(zero_array, 1, axis=0)\n", - " turns = np.where(diff[1:])\n", - " arr = np.array(turns)[0]\n", - " assert len(arr) == len(set(arr))\n", "\n", - " return test_array" + "assert len(calcualte_direct_score(board_history).shape) == 2\n", + "assert calcualte_direct_score(board_history).shape[0] == SIMULATE_TURNS\n", + "calcualte_direct_score(board_history).shape\n", + "calcualte_direct_score(board_history).round(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.4, 0.4, 0.1, 0.1, 0.3, 0.5, -0.2, -0.2, -0.1, -0.3])" + ] + }, + "execution_count": 200, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def caluclate_final_evaluation_for_histoy(board_history: np.ndarray) -> np.ndarray:\n", + " final_evaluation = final_boards_evaluation(board_history[-1])\n", + " return final_evaluation / 64\n", + "\n", + "\n", + "assert len(caluclate_final_evaluation_for_histoy(board_history).shape) == 1\n", + "caluclate_final_evaluation_for_histoy(board_history).shape\n", + "caluclate_final_evaluation_for_histoy(board_history).round(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 1, 1, 1, 1, 1, -1, -1, -1, -1])" + ] + }, + "execution_count": 156, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def calulate_who_won(board_history: np.ndarray) -> np.ndarray:\n", + " who_won = evaluate_who_won(boards[-1])\n", + " return who_won\n", + "\n", + "\n", + "calulate_who_won(board_history)" + ] + }, + { + "cell_type": "code", + "execution_count": 172, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " True],\n", + " [ True, True, True, True, True, True, True, True, True,\n", + " 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} + ], + "source": [ + "def history_changed(board_history: np.ndarray) -> np.ndarray:\n", + " return ~np.all(np.roll(boards, shift=1, axis=0) == boards, axis=(2, 3))\n", + "\n", + "\n", + "history_changed(board_history)" + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(70, 10)" + ] + }, + "execution_count": 189, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def get_gamma_table(board_history, gamma_value):\n", + " unchanged = history_changed(board_history)\n", + " gamma_values = np.ones_like(unchanged, dtype=float)\n", + " gamma_values[unchanged] = 0.8\n", + " return gamma_values\n", + "\n", + "\n", + "get_gamma_table(board_history, 0.8).shape" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", + " [-0. , -0. , -0. , -0. , -0. , 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+ " 1 - who_won_fraction + final_score_fraction\n", + " )\n", + " direct_score[-1] += calulate_fina_score(board_history) * final_score_fraction\n", + " direct_score[-1] += calulate_who_won(board_history) * who_won_fraction\n", + " return direct_score\n", + "\n", + "\n", + "calculate_q_reword(board_history).round(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'rewords' is not defined", + "output_type": "error", + "traceback": [ + "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[1;32mIn[181], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mrewords\u001B[49m\n\u001B[0;32m 2\u001B[0m evaluate_boards(boards)\u001B[38;5;241m.\u001B[39mshape\n", + "\u001B[1;31mNameError\u001B[0m: name 'rewords' is not defined" + ] + } + ], + "source": [ + "rewords\n", + "evaluate_boards(boards).shape" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "pycharm": { - "is_executing": true - } - }, + "metadata": {}, "outputs": [], "source": [ - "plot_othello_boards(create_test_game()[-3:])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "pycharm": { - "is_executing": true - } - }, - "outputs": [], - "source": [ - "array = create_test_game()" + "def calculate_simple_rewords()" ] }, { @@ -1547,11 +1728,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "pycharm": { - "is_executing": true - } - }, + "metadata": {}, "outputs": [], "source": [] } -- 2.49.0 From ea2180b08b09bbceda87d0156864c4ddcbbca50a Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Thu, 16 Feb 2023 02:18:04 +0100 Subject: [PATCH 23/31] Added statistical analysis --- main.ipynb | 802 +++++++++++++++++++++++++++-------------------------- 1 file changed, 414 insertions(+), 388 deletions(-) diff --git a/main.ipynb b/main.ipynb index d58f61c..7839561 100644 --- a/main.ipynb +++ b/main.ipynb @@ -86,13 +86,12 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "pycharm": { - "is_executing": true - } - }, + "metadata": {}, "outputs": [], "source": [ + "\n", + "import os.path\n", + "import warnings\n", "\n", "\n", "%load_ext blackcellmagic" @@ -131,14 +130,19 @@ "metadata": {}, "outputs": [], "source": [ - "from multiprocessing import Pool\n", "import itertools\n", "import numpy as np\n", "import abc\n", "from typing import Final\n", "from scipy.ndimage import binary_dilation\n", "import matplotlib.pyplot as plt\n", - "from abc import ABC" + "from abc import ABC\n", + "from tqdm.notebook import tqdm\n", + "import plotly.graph_objects as go\n", + "from plotly.subplots import make_subplots\n", + "from scipy.spatial import Delaunay\n", + "from KDEpy import FFTKDE\n", + "from ipywidgets import widgets" ] }, { @@ -341,7 +345,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -497,8 +501,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "8.02 ms ± 181 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "800 ms ± 5.98 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "9.11 ms ± 144 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "920 ms ± 10.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { @@ -520,7 +524,12 @@ } ], "source": [ - "def _recursive_steps(board, rec_direction, rec_position, step_one=True) -> bool:\n", + "def _recursive_steps(\n", + " board: np.ndarray,\n", + " rec_direction: np.ndarray,\n", + " rec_position: np.ndarray,\n", + " step_one: int = 0,\n", + ") -> int:\n", " \"\"\"Check if a player can place a stone on the board specified in the direction specified and direction specified.\n", "\n", " Args:\n", @@ -534,14 +543,16 @@ " \"\"\"\n", " rec_position = rec_position + rec_direction\n", " if np.any((rec_position >= BOARD_SIZE) | (rec_position < 0)):\n", - " return False\n", + " return 0\n", " next_field = board[tuple(rec_position.tolist())]\n", " if next_field == 0:\n", - " return False\n", + " return 0\n", " if next_field == -1:\n", - " return _recursive_steps(board, rec_direction, rec_position, step_one=False)\n", + " return _recursive_steps(\n", + " board, rec_direction, rec_position, step_one=step_one + 1\n", + " )\n", " if next_field == 1:\n", - " return not step_one\n", + " return step_one\n", "\n", "\n", "def get_possible_turns(boards: np.ndarray) -> np.ndarray:\n", @@ -569,7 +580,7 @@ " position = idx, idy\n", " if _poss_turns[game, idx, idy]:\n", " _poss_turns[game, idx, idy] = any(\n", - " _recursive_steps(boards[game, :, :], direction, position)\n", + " _recursive_steps(boards[game, :, :], direction, position) > 0\n", " for direction in DIRECTIONS\n", " )\n", " return _poss_turns\n", @@ -620,7 +631,7 @@ " if np.all(move == -1):\n", " return not np.any(get_possible_turns(np.reshape(board, (1, 8, 8))))\n", " return any(\n", - " _recursive_steps(board[:, :], direction, move) for direction in DIRECTIONS\n", + " _recursive_steps(board[:, :], direction, move) > 0 for direction in DIRECTIONS\n", " )\n", "\n", "\n", @@ -660,7 +671,7 @@ " )\n", " else:\n", " arr_moves_possible[game] = any(\n", - " _recursive_steps(boards[game, :, :], direction, moves[game])\n", + " _recursive_steps(boards[game, :, :], direction, moves[game]) > 0\n", " for direction in DIRECTIONS\n", " )\n", " return arr_moves_possible\n", @@ -712,9 +723,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "174 µs ± 6.34 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "31.6 µs ± 1.6 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "30.8 µs ± 1.58 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" + "191 µs ± 2.27 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n", + "33 µs ± 1.4 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "33.8 µs ± 345 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" ] } ], @@ -804,12 +815,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "91.5 ms ± 5.4 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "89.6 ms ± 3.13 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { "data": { - "image/png": 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\n", 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" ] @@ -1066,13 +1077,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "982 ms ± 33.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", - "881 ms ± 13.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "1.03 s ± 19 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", + "990 ms ± 29.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { "data": { - "image/png": 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ULEpXujIj3ZmR7jR2+rgrXTk1b8ry3JnX59JJm91sJg9dkdxydtJ/a5Jmq6iaw//z/W0fN5MNtyY3v6ZVbM3mpEUAClVCP5SQAdhVCfdLGYCS1fn4LtFP7GApxX69Ppfmf+WKJMmMHLTP6277/gW5ctKK65Grkns+2Pq4uXXf1932/buXt24HHNhK6IcSMgC7KuF+KQNQqrof3yX6iR0spdinE3NWLsiV47rtBbkyJ+bVE5q/cU2rfMbj7uXJpjsnNB4oWAn9UEIGYFcl3C9lAEpV9+O7RD+xqwktpT7xiU+k0Wjk/e9//yTFoTTn5gMZzrPjuu1wnp3wNv3hK5PGOF/5rNHduj2dST8d+ErohxIyMP3op6lVwv1SBqYzHXVgq/vxXaKf2NW4l1L33Xdf/uqv/ioLFy6czDwU5PDMy6lZvN9TOvdmRg7Kwrw5h2fuuG6/eUPrBe/2dzrn3jS3Jj+9OdlczRtGUBD9dOAroR9KyMD0o5+mVgn3SxmYznTUga3ux3eJfmJ341pKbd68OUuXLs3nPve5HH744ZOdiUK8KhdtfxeG8WpmJK/KxeO67drVO96BYbwaXcnaayf2M5he9FNnKKEfSsjA9KKfpl4J90sZmK501IGv7sd3iX5id+P6dVi2bFnOO++8vP71r9/vdYeGhjI4OLjLhenh6Jw4CT+lmaNywrhuObBuEsYnGVw/OT+H6UE/dYYS+qGEDEwv+mnqlXC/lIHpaqwdpZ+mr7of3yX6id21/UzOL37xi/ne976X++67b0zXX7lyZT760Y+2HYz6PSez0jXB18Lvyowckt5x3fbZp3e8Jeh4NYeTX/rvZMfQT52jhH4oIQPTh36qRgn3SxmYjtrpKP00fdX9+C7RT+yurd/I/v7+vO9978sNN9yQ5zznOWO6zYoVKzIwMLD90t/vyZ/TxX/n6YxM8PTOkQznFxlfYxw0K2nMmND4NGYkB4+/M5lG9FNnKaEfSsjA9KCfqlPC/VIGppt2O0o/TV91P75L9BO7a+tMqQceeCBPPvlkXvrSl27/2vDwcO688858+tOfztDQUGbM2PU3rKenJz09PZOTlko9mck4t7KRn2V851b2TcbZpUl6x392KdOIfuosJfRDCRmYHvRTdUq4X8rAdNNuR+mn6avux3eJfmJ3bZ0p9brXvS6PPPJIHnzwwe2Xl73sZVm6dGkefPDB3f5CxfR2V1anMcHTOxvpyl0Z36vQLbgoaU5skZ/mSLJg/K/DxzSinzpLCf1QQgamB/1UnRLulzIw3eiozlH347tEP7G7ts6UmjVrVk455ZRdvnbYYYflyCOP3O3rTH9PpT+P5JackkXjetvQ4TybR/JPeSqPjWv+zPnJ/MVJ/63je8vQRncy/03JzHnjGs80o586Swn9UEIGpgf9VJ0S7pcyMN3oqM5R9+O7RD+xuwm+GSMHum/kinEVVtJ6Ebzbc9WE5p+2fHxllbReAG/hByY0HihYCf1QQgZgVyXcL2UASlX347tEP7GrCS+l7rjjjlx99dWTEIUSrct38ncZ373+7/PBrMt3JjR/9lnJGVeM77ZnfKp1ezqXfjqwldAPJWRgetJPU6eE+6UMTHc66sBV9+O7RD+xK2dKsV+356rtxTWcZ/d53W3f/7t8YFK26Ely6qU7Squxnyecbvv+GVe0bgcc2ErohxIyALsq4X4pA1Cquh/fJfqJHSylGJPbc1WuyFl5JP+UkYxkOFsznK1pZiTDeTbD2ZqRjOSR/FOuyFmTWliNRusUzSVrWs8fTqP1NqDb3kp0+8eN1veXrGldv9GYtAhAoUrohxIyALsq4X4pA1CyOh/fJfqJHdp6oXM627p8J+vynRyeuXlVLs5ROSGHpDe/yGB+lvW5K9dO6EXv9mf2Wa3L5v5k7bXJ4Prkl4PJwb2ttwRdcLEXvINOVUI/lJAB2FUJ90sZgFLV/fgu0U9YSjEOT+Wx/FM+Vtv8mfOS0z9S23igYCX0QwkZgF2VcL+UAShV3Y/vEv3UyTx9DwAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUazWazWeXAwcHB9PX1JY3ksDlVTm55ZlPSHEkaXcmhs6ufL4MMpWWoe36SbNmYpJkMDAykt7e3nhCpv5+SMo5H3Rnqni+DDKOV0FH6SYZS5stQVgb91FLCsZBBhlLml5JhrP1U31IKYJRillIAe1DEgz6APdBPQKn210/dFWbZlTOlZJChiAx1z092bNGL4V/6Ov53UgYZdlZUR+mnjs9Q93wZysqgn1pKOBYyyFDK/FIyjLWfaltKHXpMsvSx6ufeMDfZ8njrwNQxXwYZSstQ9/wkuX5OqzhLUVc/JWUcj7oz1D1fBhlGK6mj9JMMdc+XoawM+qmlhGMhgwylzC8lw1j7yQudAwAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqFx9777HtLV5Q7J2dTKwLnn26eSgWUnficmCi5KZ8w/8+aVkAHZXwn3z8MzLq3JRjs6JeU5m5b/zdJ7MutyV1Xkq/dWEAIqjn4BSldBPJWSgHpZSjNnGNcnDVyYbbmm9tWSSNIeTxozWxw9clhy7OFm4PJl91oE3v5QMwO5KuG+emLNybj6QU7M4zYwkSbrSlZH/+XhxLsvDuTm358qsy3emJgRQHP0ElKqEfiohA/Xy9D32q9lMHroiueXspP/WJM1WUTSH/+f72z5uJhtuTW5+TatYms0DY34pGYDdlXLfPDcfyPKsySlZlK50ZUa6MyPdaez0cVe6cmrelOW5M6/PpZMbACiOfgJKVUI/lZCBMlhKsV+PXJXc88HWx82t+77utu/fvbx1uwNhfikZgN2VcN98fS7N/8oVSZIZOWif1932/QtypQd+cIDTT0CpSuinEjJQhraWUpdddlkajcYul5NOOmmqslGAjWtad/7xuHt5sunO6T2/lAzsn37qPCXcN0/MWbkgV47rthfkypyYV088BNOCjuos+onpRD91lhL6qYQMlKPtM6VOPvnkbNq0afvln//5n6ciF4V4+MqkMc5XHmt0t24/neeXkoGx0U+dpYT75rn5QIbz7LhuO5xnnY3QYXRU59BPTDf6qXOU0E8lZKAcbf8qdHd355hjjpmKLBRm84bWC85lnM/bbW5Nfnpzsrk/mTlv+s0vJQNjp586Rwn3zcMzL6dmcbrG+Uz4GTkoC/PmHJ65eSqPjS8E04qO6gz6ielIP3WGEvqphAyUpe3/Uq1bty5z5szJ8ccfn6VLl2bDhg1TkYsCrF294x0QxqvRlay9dnrOLyUDY6efOkcJ981X5aLt72I1Xs2M5FW5eEI/g+lDR3UG/cR0pJ86Qwn9VEIGytLWmVK/9mu/ltWrV2fBggXZtGlTPvrRj+bVr351fvCDH2TWrFl7vM3Q0FCGhoa2fz44ODixxFRmYN3k/JzB9dNzfikZGBv91FlKuG8enRMnIUEzR+WESfg5lK7djtJP05d+YrrRT52jhH4qIQNlaWsptWjRou0fL1y4ML/2a7+WY489Nl/+8pfzO7/zO3u8zcqVK/PRj350YimpxbNP73hLzvFqDie/HOd/p+qeX0oGxkY/dZYS7pvPyaxxPzVmm67MyCHpndDPYHpot6P00/Sln5hu9FPnKKGfSshAWSb0X6vnPve5+ZVf+ZWsX7/3NeWKFSsyMDCw/dLf3z+RkVTooFlJY8bEfkZjRnLwOP8+U/f8UjIwPvrpwFbCffO/83RGJvj0mJEM5xfxt6pOtL+O0k/Tl35iutNPB64S+qmEDJRlQkupzZs359/+7d8ye/bsvV6np6cnvb29u1yYHvom48zvJL3jPPO77vmlZGB89NOBrYT75pOZjPPPG/lZnH/eifbXUfpp+tJPTHf66cBVQj+VkIGytLWUWr58edasWZNHH300d911V37jN34jM2bMyNve9rapykeNFlyUNCf2j2xpjiQLxvkamXXPLyUDY6OfOksJ9827sjqNCT49ppGu3BWv1NkJdFTn0E9MN/qpc5TQTyVkoCxt/dfqsccey9ve9rYsWLAgv/mbv5kjjzwyd999d4466qipykeNZs5P5i9OGm298tgOje7k2CXjf6vOuueXkoGx0U+dpYT75lPpzyO5JcN5dly3H86zeThf9XbrHUJHdQ79xHSjnzpHCf1UQgbK0tavwhe/+MWpykGhTluebLh5fLdtDicLPzC955eSgf3TT52nhPvmN3JFTsubx3XbrszI7blq4iGYFnRUZ9FPTCf6qbOU0E8lZKAcEzuvlwPe7LOSM64Y323P+FTr9tN5fikZgN2VcN9cl+/k7zK+vxn9fT6YdfnOxEMAxdFPQKlK6KcSMlAOSyn269RLd5TG/k6z3Pb9M65o3e5AmF9KBmB3Jdw3b89V2x/47e+pMtu+/3f5gLMQ4ACnn4BSldBPJWSgDJZS7Fej0TpFcsmaZP6bkjRab8O57a08t3/caH1/yZrW9RuNA2N+KRmA3ZVy37w9V+WKnJVH8k8ZyUiGszXD2ZpmRjKcZzOcrRnJSB7JP+WKnOUBH3QA/QSUqoR+KiEDZRjny4vRiWaf1bps7k/WXpsMrk9+OZgc3Nt6S84FF0/tC87VPb+UDMDuSrhvrst3si7fyeGZm1fl4hyVE3JIevOLDOZnWZ+7cq0XDYYOpJ+AUpXQTyVkoF6WUrRt5rzk9I907vxSMgC7K+G++VQeyz/lY/WGAIqjn4BSldBPJWSgHp6+BwAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKNZrPZrHLg4OBg+vr6kkZy2JwqJ7c8sylpjiSNruTQ2dXPl0GG0jLUPT9JtmxM0kwGBgbS29tbT4jU309JGcej7gx1z5dBhtFK6Cj9JEMp82UoK4N+ainhWMggQynzS8kw1n6qbykFMEoxSymAPSjiQR/AHugnoFT766fuCrPsyplSMshQRIa65yc7tujF8C99Hf87KYMMOyuqo/RTx2eoe74MZWXQTy0lHAsZZChlfikZxtpPtS2lDj0mWfpY9XNvmJtsebx1YOqYL4MMpWWoe36SXD+nVZylqKufkjKOR90Z6p4vgwyjldRR+kmGuufLUFYG/dRSwrGQQYZS5peSYaz95IXOAQAAAKicpRQAAAAAlbOUAgAAAKBy9b3QOQAAANDxNm9I1q5OBtYlzz6dHDQr6TsxWXBRMnN+3emYSpZSAAAAQOU2rkkevjLZcEvrneKSpDmcNGa0Pn7gsuTYxcnC5cnss2qLyRTy9D0AAACgMs1m8tAVyS1nJ/23Jmm2llHN4f/5/raPm8mGW5ObX9NaXjWbNYZmSlhKAQAAAJV55Krkng+2Pm5u3fd1t33/7uWt23FgsZQCAAAAKrFxTWvBNB53L0823Tm5eahX20upxx9/PG9/+9tz5JFH5pBDDsmpp56a+++/fyqyAbRFPwEl01FAqfQTVXr4yqQxzle3bnS3bs+Bo61fhaeeeipnnnlmzjnnnNx666056qijsm7duhx++OFTlQ9gTPQTUDIdBZRKP1GlzRtaL2qecb42VHNr8tObk839ycx5kxqNmrS1lPrkJz+ZefPm5dprr93+teOOO27SQwG0Sz8BJdNRQKn0E1Vau7r1LnvbXtB8PBpdydprk9M/MmmxqFFbT9/76le/mpe97GW54IILcvTRR+clL3lJPve5z+3zNkNDQxkcHNzlAjDZ9BNQsnY7Sj8BVdFPVGlg3eT8nMH1k/NzqF9bS6mf/OQnWbVqVU488cR87Wtfyzvf+c68973vzXXXXbfX26xcuTJ9fX3bL/PmOccOmHz6CShZux2ln4Cq6Ceq9OzTEztLKmnd/pd2oQeMtpZSIyMjeelLX5rLL788L3nJS/L//X//X/7P//k/+cu//Mu93mbFihUZGBjYfunv759waIDR9BNQsnY7Sj8BVdFPVOmgWUljxsR+RmNGcnDv5OShfm0tpWbPnp0Xv/jFu3ztV3/1V7Nhw4a93qanpye9vb27XAAmm34CStZuR+knoCr6iSr1nTg5P6f3hMn5OdSvraXUmWeembVr1+7ytR//+Mc59thjJzUUQLv0E1AyHQWUSj9RpQUXJc2Rif2M5kiy4OJJiUMB2lpK/cEf/EHuvvvuXH755Vm/fn1uvPHG/PVf/3WWLVs2VfkAxkQ/ASXTUUCp9BNVmjk/mb84aXSP7/aN7uTYJclML2V2wGhrKfXyl788N910U77whS/klFNOycc+9rFcffXVWbp06VTlAxgT/QSUTEcBpdJPVO205Ulz6/hu2xxOFn5gcvNQr7b3k4sXL87ixYunIgvAhOgnoGQ6CiiVfqJKs89KzrgiuXt5+7c941Ot23PgaOtMKQAAAICJOPXS1mIq2f9T+bZ9/4wrWrfjwGIpBQAAAFSm0Wg9DW/JmmT+m5I0ksaM1iXZ6eNG6/tL1rSu32jUmZqpMM6XFwMAAAAYv9lntS6b+5O11yaD65NfDiYH9ya9J7TeZc+Lmh/YLKUAAACA2sycl5z+kbpTUAdP3wMAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFC5RrPZbFY5cHBwMH19fUkjOWxOlZNbntmUNEeSRldy6Ozq58sgQ2kZ6p6fJFs2JmkmAwMD6e3trSdE6u+npIzjUXeGuufLIMNoJXSUfpKhlPkylJVBP7WUcCxkkKGU+aVkGGs/1beUAhilmKUUwB4U8aAPYA/0E1Cq/fVTd4VZduVMKRlkKCJD3fOTHVv0YviXvo7/nZRBhp0V1VH6qeMz1D1fhrIy6KeWEo6FDDKUMr+UDGPtp9qWUocekyx9rPq5N8xNtjzeOjB1zJdBhtIy1D0/Sa6f0yrOUtTVT0kZx6PuDHXPl0GG0UrqKP0kQ93zZSgrg35qKeFYyCBDKfNLyTDWfvJC5wAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVK6tpdQLX/jCNBqN3S7Lli2bqnwAY6ajgFLpJ6BU+gmoU3c7V77vvvsyPDy8/fMf/OAHOffcc3PBBRdMejCAdukooFT6CSiVfgLq1NZS6qijjtrl80984hN50YtelNe85jWTGgpgPHQUUCr9BJRKPwF1amsptbNf/vKXuf7663PppZem0Wjs9XpDQ0MZGhra/vng4OB4RwKM2Vg6Sj8BddBPQKn0E1C1cb/Q+Ve+8pX8/Oc/z0UXXbTP661cuTJ9fX3bL/PmzRvvSIAxG0tH6SegDvoJKJV+Aqo27qXUNddck0WLFmXOnDn7vN6KFSsyMDCw/dLf3z/ekQBjNpaO0k9AHfQTUCr9BFRtXE/f++lPf5rbb789//AP/7Df6/b09KSnp2c8YwDGZawdpZ+AquknoFT6CajDuM6Uuvbaa3P00UfnvPPOm+w8ABOmo4BS6SegVPoJqEPbS6mRkZFce+21ufDCC9PdPe7XSQeYEjoKKJV+Akqln4C6tL2Uuv3227Nhw4ZccsklU5EHYEJ0FFAq/QSUSj8BdWl7Df6GN7whzWZzKrIATJiOAkqln4BS6SegLuN+9z0AAAAAGC9LKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyjWazWazyoGDg4Pp6+tLGslhc6qc3PLMpqQ5kjS6kkNnVz9fBhlKy1D3/CTZsjFJMxkYGEhvb289IVJ/PyVlHI+6M9Q9XwYZRiuho/STDKXMl6GsDPqppYRjIYMMpcwvJcNY+6m+pRTAKMUspQD2oIgHfQB7oJ+AUu2vn7orzLIrZ0rJIEMRGeqen+zYohfDv/R1/O+kDDLsrKiO0k8dn6Hu+TKUlUE/tZRwLGSQoZT5pWQYaz/VtpQ69Jhk6WPVz71hbrLl8daBqWO+DDKUlqHu+Uly/ZxWcZairn5KyjgedWeoe74MMoxWUkfpJxnqni9DWRn0U0sJx0IGGUqZX0qGsfaTFzoHAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlWtrKTU8PJwPf/jDOe6443LIIYfkRS96UT72sY+l2WxOVT6AMdFPQMl0FFAq/QTUqbudK3/yk5/MqlWrct111+Xkk0/O/fffn4svvjh9fX1573vfO1UZAfZLPwEl01FAqfQTUKe2llJ33XVXzj///Jx33nlJkhe+8IX5whe+kHvvvXdKwgGMlX4CSqajgFLpJ6BObT1971WvelW++c1v5sc//nGS5KGHHso///M/Z9GiRVMSDmCs9BNQMh0FlEo/AXVq60ypD33oQxkcHMxJJ52UGTNmZHh4OB//+MezdOnSvd5maGgoQ0ND2z8fHBwcf1qAvdBPQMna7Sj9BFRFPwF1autMqS9/+cu54YYbcuONN+Z73/terrvuulxxxRW57rrr9nqblStXpq+vb/tl3rx5Ew4NMJp+AkrWbkfpJ6Aq+gmoU1tLqQ9+8IP50Ic+lN/+7d/Oqaeemv/9v/93/uAP/iArV67c621WrFiRgYGB7Zf+/v4JhwYYTT8BJWu3o/QTUBX9BNSprafvPfPMM+nq2nWPNWPGjIyMjOz1Nj09Penp6RlfOoAx0k9AydrtKP0EVEU/AXVqaym1ZMmSfPzjH8/8+fNz8skn5/vf/36uuuqqXHLJJVOVD2BM9BNQMh0FlEo/AXVqayn1F3/xF/nwhz+cd73rXXnyySczZ86c/N7v/V4+8pGPTFU+gDHRT0DJdBRQKv0E1KmtpdSsWbNy9dVX5+qrr56iOADjo5+AkukooFT6CahTWy90DgAAAACTwVIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVK7RbDabVQ4cGBjIc5/73CTJobOrnNzyzBNJmkkayaHHVD9fBhlKy1D3/CR5ZlPrf3/+85+nr6+vnhCpv5+SQo6H30kZZNg1QwEdpZ9kKGW+DIVl0E9JCjkWMshQyPxiMoyxnypfSj322GOZN29elSOBaaK/vz9z586tbb5+Avalzo7ST8C+6CegVPvrp8qXUiMjI9m4cWNmzZqVRqPR9u0HBwczb9689Pf3p7e3dwoSyjBdMtQ9X4bJy9BsNvP0009nzpw56eqq71nF+kmGAylD3fMPpAwldNRE+ymp/3jUPV8GGUrLoJ92qPtYlJCh7vkyyDDZGcbaT90TCTkeXV1dk7LF7+3tre3gyFBWhrrnyzA5Gep82t42+kmGAzFD3fMPlAx1d9Rk9VNS//Goe74MMpSWQT/tUPexKCFD3fNlkGEyM4yln7zQOQAAAACVs5QCAAAAoHLTbinV09OTP/mTP0lPT48MHZ6h7vkylJWhBCX8OcggQynzZShP3X8Wdc+XQYbSMtQ9vyQl/FnUnaHu+TLIUFeGyl/oHAAAAACm3ZlSAAAAAEx/llIAAAAAVM5SCgAAAIDKTaul1He/+93MmDEj5513XuWzL7roojQaje2XI488Mm984xvz8MMPV57liSeeyHve854cf/zx6enpybx587JkyZJ885vfnPLZO/85HHTQQXn+85+fc889N5///OczMjIy5fNHZ9j58sY3vrGS+fvLsX79+krmP/HEE3nf+96XE044Ic95znPy/Oc/P2eeeWZWrVqVZ555ZsrnX3TRRXnLW96y29fvuOOONBqN/PznP5/yDKXRUfppdI66Oqrufkrq7Sj9tDv9pJ9G59BP/g5VCv2kn0bn0E+d1U/Tail1zTXX5D3veU/uvPPObNy4sfL5b3zjG7Np06Zs2rQp3/zmN9Pd3Z3FixdXmuHRRx/N6aefnm9961v51Kc+lUceeSS33XZbzjnnnCxbtqySDNv+HB599NHceuutOeecc/K+970vixcvztatWyvNsPPlC1/4QiWz95fjuOOOm/K5P/nJT/KSl7wkX//613P55Zfn+9//fr773e/mD//wD3PLLbfk9ttvn/IM7K7TO0o/7Z6jzo6qq58SHVUi/aSfRufQT/qpFPpJP43OoZ86q5+66w4wVps3b86XvvSl3H///XniiSeyevXq/PEf/3GlGXp6enLMMcckSY455ph86EMfyqtf/er87Gc/y1FHHVVJhne9611pNBq59957c9hhh23/+sknn5xLLrmkkgw7/zm84AUvyEtf+tKcccYZed3rXpfVq1fnd3/3dyvNUKe6crzrXe9Kd3d37r///l1+D44//vicf/758aaa1dNR+mlvOepSZwYdVRb9pJ/2lqMu+olt9JN+2luOuuin6k2bM6W+/OUv56STTsqCBQvy9re/PZ///OdrPSibN2/O9ddfnxNOOCFHHnlkJTP/67/+K7fddluWLVu2yy/pNs997nMrybEnr33ta3PaaaflH/7hH2rL0Cn+8z//M1//+tf3+nuQJI1Go+JUdHpH6Se20VHl0U/6iRb9VB79pJ9o6eR+mjZLqWuuuSZvf/vbk7ROqRsYGMiaNWsqzXDLLbdk5syZmTlzZmbNmpWvfvWr+dKXvpSurmr+GNevX59ms5mTTjqpknntOumkk/Loo49WMmvnY7Htcvnll1cye185Lrjggimfue33YMGCBbt8/XnPe972HH/0R3805TmSPR+HRYsWVTK7NJ3eUfppVyV0VB39lJTTUfppB/2kn3amn+rvp0RHbaOf9NPO9FNn9tO0ePre2rVrc++99+amm25KknR3d+e3fuu3cs011+Tss8+uLMc555yTVatWJUmeeuqpfPazn82iRYty77335thjj53y+aWfrtdsNivb3u58LLY54ogjKpm9rxx722pX4d57783IyEiWLl2aoaGhSmbu6Tjcc8892/9y0Sl0lH4arYSOKqmfkuo7Sj+16Cf9NJp+2p2/Q9VDP+mn0fTT7jqhn6bFUuqaa67J1q1bM2fOnO1fazab6enpyac//en09fVVkuOwww7LCSecsP3zv/mbv0lfX18+97nP5c/+7M+mfP6JJ56YRqORH/3oR1M+azx++MMfVvYicKOPRV3qyHHCCSek0Whk7dq1u3z9+OOPT5IccsghlWXZ0///xx57rLL5pdBR+mm0EjqqrgyldJR+atFP+mk0/VR/PyU6KtFPiX4aTT91Zj8V//S9rVu35m//9m9z5ZVX5sEHH9x+eeihhzJnzpxa3nFtm0ajka6urvziF7+oZN4RRxyRX//1X89nPvOZbNmyZbfv1/n2sd/61rfyyCOP5K1vfWttGTrFkUcemXPPPTef/vSn9/h7QLV0VIt+YhsdVQ791KKf2EY/lUM/tegntunkfir+TKlbbrklTz31VH7nd35nt235W9/61lxzzTX5/d///UqyDA0N5YknnkjSOrXz05/+dDZv3pwlS5ZUMj9JPvOZz+TMM8/MK17xivzpn/5pFi5cmK1bt+Yb3/hGVq1alR/+8IdTnmHbn8Pw8HD+4z/+I7fddltWrlyZxYsX5x3veMeUz985w866u7vzvOc9r5L5dfvsZz+bM888My972cty2WWXZeHChenq6sp9992XH/3oRzn99NPrjtgxdNQO+mn3HDvTUTqqavppB/20e46d6Sf9VDX9tIN+2j3HzvRTB/RTs3CLFy9uvulNb9rj9+65555mkuZDDz005TkuvPDCZpLtl1mzZjVf/vKXN//+7/9+ymePtnHjxuayZcuaxx57bPPggw9uvuAFL2i++c1vbn7729+e8tk7/zl0d3c3jzrqqObrX//65uc///nm8PDwlM8fnWHny4IFCyqZv3OO888/v9KZO9u4cWPz3e9+d/O4445rHnTQQc2ZM2c2X/GKVzQ/9alPNbds2TLl8/f2///b3/52M0nzqaeemvIMJdBRu+r0fhqdo66Oqrufms16O0o/teinXekn/bSNv0PVTz/tSj/pp206sZ8azWbhr64GAAAAwAGn+NeUAgAAAODAYykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACrXXfXAkZGRbNy4MbNmzUqj0ah6PFCgZrOZp59+OnPmzElXV327cv0E7EkJHaWfgD3RT0CpxtpPlS+lNm7cmHnz5lU9FpgG+vv7M3fu3Nrm6ydgX+rsKP0E7It+Akq1v36qfCk1a9as7R8fOrvq6ckzTyRpJmkkhx5T/XwZZCgtQ93zk+SZTa3/3bkf6lB3PyWFHA+/kzLIsGuGAjpKP8lQynwZCsugn5IUcixkkKGQ+cVkGGM/Vb6U2nZK56Gzk7dvrHp6csPcZMvjyWFzkqWPVT9fBhlKy1D3/CS5fk6rtOo+5bvufkrKOB51Z6h7vgwyjFZCR+knGUqZL0NZGfRTSwnHQgYZSplfSoax9pMXOgcAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVa3spdeedd2bJkiWZM2dOGo1GvvKVr0xBLID26SegVPoJKJV+AurU9lJqy5YtOe200/KZz3xmKvIAjJt+Akqln4BS6SegTt3t3mDRokVZtGjRVGQBmBD9BJRKPwGl0k9AndpeSrVraGgoQ0ND2z8fHByc6pEAY6KfgFLpJ6BU+gmYTFP+QucrV65MX1/f9su8efOmeiTAmOgnoFT6CSiVfgIm05QvpVasWJGBgYHtl/7+/qkeCTAm+gkolX4CSqWfgMk05U/f6+npSU9Pz1SPAWibfgJKpZ+AUuknYDJN+ZlSAAAAADBa22dKbd68OevXr9/++b//+7/nwQcfzBFHHJH58+dPajiAdugnoFT6CSiVfgLq1PZS6v77788555yz/fNLL700SXLhhRdm9erVkxYMoF36CSiVfgJKpZ+AOrW9lDr77LPTbDanIgvAhOgnoFT6CSiVfgLq5DWlAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUazWazWeXAwcHB9PX1JY3ksDlVTm55ZlPSHEkaXcmhs6ufL4MMpWWoe36SbNmYpJkMDAykt7e3nhCpv5+SMo5H3Rnqni+DDKOV0FH6SYZS5stQVgb91FLCsZBBhlLml5JhrP1U31IKYJRillIAe1DEgz6APdBPQKn210/dFWbZlTOlZJChiAx1z092bNGL4V/6Ov53UgYZdlZUR+mnjs9Q93wZysqgn1pKOBYyyFDK/FIyjLWfaltKHXpMsvSx6ufeMDfZ8njrwNQxXwYZSstQ9/wkuX5OqzhLUVc/JWUcj7oz1D1fBhlGK6mj9JMMdc+XoawM+qmlhGMhgwylzC8lw1j7yQudAwAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQubaWUitXrszLX/7yzJo1K0cffXTe8pa3ZO3atVOVDWDM9BNQMh0FlEo/AXVqaym1Zs2aLFu2LHfffXe+8Y1v5Nlnn80b3vCGbNmyZaryAYyJfgJKpqOAUuknoE7d7Vz5tttu2+Xz1atX5+ijj84DDzyQs846a1KDAbRDPwEl01FAqfQTUKe2llKjDQwMJEmOOOKIvV5naGgoQ0ND2z8fHBycyEiAMdFPQMn211H6CaiLfgKqNO4XOh8ZGcn73//+nHnmmTnllFP2er2VK1emr69v+2XevHnjHQkwJvoJKNlYOko/AXXQT0DVxr2UWrZsWX7wgx/ki1/84j6vt2LFigwMDGy/9Pf3j3ckwJjoJ6BkY+ko/QTUQT8BVRvX0/fe/e5355Zbbsmdd96ZuXPn7vO6PT096enpGVc4gHbpJ6BkY+0o/QRUTT8BdWhrKdVsNvOe97wnN910U+64444cd9xxU5ULoC36CSiZjgJKpZ+AOrW1lFq2bFluvPHG/OM//mNmzZqVJ554IknS19eXQw45ZEoCAoyFfgJKpqOAUuknoE5tvabUqlWrMjAwkLPPPjuzZ8/efvnSl740VfkAxkQ/ASXTUUCp9BNQp7afvgdQIv0ElExHAaXST0Cdxv3uewAAAAAwXpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVazSbzWaVAwcHB9PX15c0ksPmVDm55ZlNSXMkaXQlh86ufr4MMpSWoe75SbJlY5JmMjAwkN7e3npCpP5+Sso4HnVnqHu+DDKMVkJH6ScZSpkvQ1kZ9FNLCcdCBhlKmV9KhrH2U31LKYBRillKAexBEQ/6APZAPwGl2l8/dVeYZVfOlJJBhiIy1D0/2bFFL4Z/6ev430kZZNhZUR2lnzo+Q93zZSgrg35qKeFYyCBDKfNLyTDWfqptKXXoMcnSx6qfe8PcZMvjrQNTx3wZZCgtQ93zk+T6Oa3iLEVd/ZSUcTzqzlD3fBlkGK2kjtJPMtQ9X4ayMuinlhKOhQwylDK/lAxj7ScvdA4AAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKBy9b37HtPW5g3J2tXJwLrk2aeTg2YlfScmCy5KZs6vOx0AAABj5fEddbKUYsw2rkkevjLZcEvrrSWTpDmcNGa0Pn7gsuTYxcnC5cnss2qLCQAAwH54fEcJPH2P/Wo2k4euSG45O+m/NUmzVVbN4f/5/raPm8mGW5ObX9Mqt2azxtAAAADsxuM7SmIpxX49clVyzwdbHze37vu6275/9/LW7QAAACiHx3eUpK2l1KpVq7Jw4cL09vamt7c3r3zlK3PrrbdOVTYKsHFNq4DG4+7lyaY7JzcP7I1+Akqmo4BS6afO4vEdpWlrKTV37tx84hOfyAMPPJD7778/r33ta3P++efnX/7lX6YqHzV7+MqkMc5XHmt0t24PVdBPQMl0FFAq/dRZPL6jNG39Oi5ZsmSXzz/+8Y9n1apVufvuu3PyySdPajDqt3lD60XvMs7nDje3Jj+9Odncn8ycN6nRYDf6CSiZjgJKpZ86h8d3lGjcryk1PDycL37xi9myZUte+cpXTmYmCrF29Y53YRivRley9tpJiQNjpp+AkukooFT66cDm8R0lavvEvUceeSSvfOUr89///d+ZOXNmbrrpprz4xS/e6/WHhoYyNDS0/fPBwcHxJaVyA+sm5+cMrp+cnwP7o5+AkrXTUfoJqJJ+6gwe31GitvekCxYsyIMPPph77rkn73znO3PhhRfmX//1X/d6/ZUrV6avr2/7Zd485/lNF88+veNtQcerOZz80n+nqIh+AkrWTkfpJ6BK+qkzeHxHidpeSh188ME54YQTcvrpp2flypU57bTT8ud//ud7vf6KFSsyMDCw/dLf3z+hwFTnoFlJY8bEfkZjRnJw7+Tkgf3RT0DJ2uko/QRUST91Bo/vKNE4X3d/h5GRkV1O3xytp6cnPT09Ex1DDfpOnJyf03vC5PwcaJd+Akq2r47ST0Cd9NOByeM7StTWUmrFihVZtGhR5s+fn6effjo33nhj7rjjjnzta1+bqnzUaMFFyQOXTexnNEeSBRdPRhrYN/0ElExHAaXST53D4ztK1NZS6sknn8w73vGObNq0KX19fVm4cGG+9rWv5dxzz52qfNRo5vxk/uKk/9bW23+2q9GdzH+TtwulGvoJKJmOAkqlnzqHx3eUqK2l1DXXXDNVOSjUacuTDTeP77bN4WThByY3D+yNfgJKpqOAUumnzuLxHaVp+4XO6Syzz0rOuGJ8tz3jU63bAwAAUD+P7yiNpRT7deqlO4qrsZ9z67Z9/4wrWrcDAACgHB7fURJLKfar0WidprlkTes5xGm03gp029uJbv+40fr+kjWt6zcadaYGAABgNI/vKElbrylFZ5t9VuuyuT9Ze20yuD755WBycG/rbUEXXOxF7wAAAKYDj+8ogaUUbZs5Lzn9I3WnAAAAYKI8vqNOnr4HAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgco1ms9mscuDg4GD6+vqSRnLYnContzyzKWmOJI2u5NDZ1c+XQYbSMtQ9P0m2bEzSTAYGBtLb21tPiNTfT0kZx6PuDHXPl0GG0UroKP0kQynzZSgrg35qKeFYyCBDKfNLyTDWfqpvKQUwSjFLKYA9KOJBH8Ae6CegVPvrp+4Ks+zKmVIyyFBEhrrnJzu26MXwL30d/zspgww7K6qj9FPHZ6h7vgxlZdBPLSUcCxlkKGV+KRnG2k+1LaUOPSZZ+lj1c2+Ym2x5vHVg6pgvgwylZah7fpJcP6dVnKWoq5+SMo5H3Rnqni+DDKOV1FH6SYa658tQVgb91FLCsZBBhlLml5JhrP3khc4BAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUrr5332Pa2rwhWbs6GViXPPt0ctCspO/EZMFFycz5B/58YM9KuG/KAOxJCfdLGYBSldANJWSgHpZSjNnGNcnDVyYbbmm9tWSSNIeTxozWxw9clhy7OFm4PJl91oE3H9izEu6bMgB7UsL9UgagVCV0QwkZqJen77FfzWby0BXJLWcn/bcmabaKojn8P9/f9nEz2XBrcvNrWsXSbB4Y84E9K+G+KQOwJyXcL2UASlVCN5SQgTJYSrFfj1yV3PPB1sfNrfu+7rbv3728dbsDYT6wZyXcN2UA9qSE+6UMQKlK6IYSMlCGCS2lPvGJT6TRaOT973//JMWhNBvXtO7843H38mTTndN7PtOXfppaJdw3ZWC60k9Tq4T7pQxMZzrqwFZCN5SQgXKMeyl133335a/+6q+ycOHCycxDYR6+MmmM85XHGt2t20/n+UxP+mnqlXDflIHpSD9NvRLulzIwXemoA18J3VBCBsoxrqXU5s2bs3Tp0nzuc5/L4YcfPtmZKMTmDa0XnNvf6ZR709ya/PTmZHP/9JzP9KSfpl4J900ZmI7009Qr4X4pA9OVjjrwldANJWSgLONaSi1btiznnXdeXv/61092HgqydvWOd0AYr0ZXsvba6Tmf6Uk/Tb0S7psyMB3pp6lXwv1SBqYrHXXgK6EbSshAWdo+ae6LX/xivve97+W+++4b0/WHhoYyNDS0/fPBwcF2R1KTgXWT83MG10/P+Uw/+qkaJdw3ZWC60U/VKOF+KQPTUTsdpZ+mrxK6oYQMlKWtHWV/f3/e97735YYbbshznvOcMd1m5cqV6evr236ZN2/euIJSvWef3vGWnOPVHE5+Oc7/TtU9n+lFP1WnhPumDEwn+qk6JdwvZWC6abej9NP0VUI3lJCBsrS1lHrggQfy5JNP5qUvfWm6u7vT3d2dNWvW5P/+3/+b7u7uDA/v/tu1YsWKDAwMbL/093vy53Rx0KykMWNiP6MxIzm4d3rOZ3rRT9Up4b4pA9OJfqpOCfdLGZhu2u0o/TR9ldANJWSgLG09fe91r3tdHnnkkV2+dvHFF+ekk07KH/3RH2XGjN1/u3p6etLT0zOxlNSi78TJ+Tm9J0zP+Uwv+qk6Jdw3ZWA60U/VKeF+KQPTTbsdpZ+mrxK6oYQMlKWtM6VmzZqVU045ZZfLYYcdliOPPDKnnHLKVGWkJgsuSpojE/sZzZFkwcXTcz7Ti36qTgn3TRmYTvRTdUq4X8rAdKOjOkcJ3VBCBsoywde950A2c34yf3HSaPvl8Fsa3cmxS5KZ43yaed3zgT0r4b4pA7AnJdwvZQBKVUI3lJCBsozzV2GHO+64YxJiUKrTlicbbh7fbZvDycIPTO/5TG/6aeqUcN+UgelMP02dEu6XMjDd6agDVwndUEIGyuFMKfZp9lnJGVeM77ZnfKp1++k8H9izEu6bMgB7UsL9UgagVCV0QwkZKIelFPt16qU7SmN/p1lu+/4ZV7RudyDMB/ashPumDMCelHC/lAEoVQndUEIGymApxX41Gq1TJJesSea/KUmj9Tac297Kc/vHjdb3l6xpXb/RODDmA3tWwn1TBmBPSrhfygCUqoRuKCEDZZjwa0rROWaf1bps7k/WXpsMrk9+OZgc3Nt6S84FF0/tC87VPR/YsxLumzIAe1LC/VIGoFQldEMJGaiXpRRtmzkvOf0jnTsf2LMS7psyAHtSwv1SBqBUJXRDCRmoh6fvAQAAAFA5SykAAAAAKmcpBQAAAEDlGs1ms1nlwMHBwfT19SWN5LA5VU5ueWZT0hxJGl3JobOrny+DDKVlqHt+kmzZmKSZDAwMpLe3t54Qqb+fkjKOR90Z6p4vgwyjldBR+kmGUubLUFYG/dRSwrGQQYZS5peSYaz9VN9SCmCUYpZSAHtQxIM+gD3QT0Cp9tdP9b37njOlZJChiAx1z092bNGL4V/6Ov53UgYZdlZUR+mnjs9Q93wZysqgn1pKOBYyyFDK/FIyjLWfaltKHXpMsvSx6ufeMDfZ8njrwNQxXwYZSstQ9/wkuX5OqzhLUVc/JWUcj7oz1D1fBhlGK6mj9JMMdc+XoawM+qmlhGMhgwylzC8lw1j7yQudAwAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqFx9777HtLV5Q7J2dTKwLnn26eSgWUnficmCi5KZ86d+/uGZl1flohydE/OczMp/5+k8mXW5K6vzVPqnPgBQrLr7KdFRwJ7pJ6BU+ok6WUoxZhvXJA9fmWy4pfXWkknSHE4aM1ofP3BZcuziZOHyZPZZkz//xJyVc/OBnJrFaWYkSdKVroz8z8eLc1kezs25PVdmXb4z+QGAYtXdT4mOAvZMPwGl0k+UwNP32K9mM3noiuSWs5P+W5M0W2XVHP6f72/7uJlsuDW5+TWtcms2Jy/DuflAlmdNTsmidKUrM9KdGelOY6ePu9KVU/OmLM+deX0unbzhQLFK6KdERwG7009AqfQTJbGUYr8euSq554Otj5tb933dbd+/e3nrdpPh9bk0/ytXJElm5KB9Xnfb9y/IlUoLOkDd/ZToKGDP9BNQKv1ESSyl2KeNa1oFNB53L0823Tmx+SfmrFyQK8d12wtyZU7MqycWAChW3f2U6Chgz/QTUCr9RGnaWkpddtllaTQau1xOOumkqcpGAR6+MmmM85XHGt2t20/EuflAhvPsuG47nGdt0juIfuo8dfdToqMYOx3VWfQT04l+6iz6idK0/et48skn5/bbb9/xA7q9VvqBavOG1oveZZzPHW5uTX56c7K5P5k5r/3bH555OTWL0zXOE/pm5KAszJtzeObmqTw2rp/B9KKfOkfd/ZToKNqnozqDfmI60k+dQT9RorZ/E7q7u3PMMcdsvzzvec+bilwUYO3qHe/CMF6NrmTtteO77aty0fZ3YBivZkbyqlw8oZ/B9KGfOkfd/ZToKNqnozqDfmI60k+dQT9RorZ/JdetW5c5c+bk+OOPz9KlS7Nhw4Z9Xn9oaCiDg4O7XJgeBtZNzs8ZXD++2x2dEydhejNH5YRJ+DlMB/qpc9TdT4mOon3tdJR+mr70E9ORfuoM+okStbWU+rVf+7WsXr06t912W1atWpV///d/z6tf/eo8/fTTe73NypUr09fXt/0yb944z/Ojcs8+veNtQcerOZz8cpz/nXpOZo37tM5tujIjh6R3Qj+D6UE/dZa6+ynRUbSn3Y7ST9OXfmK60U+dQz9RorZ+GxYtWpQLLrggCxcuzK//+q/n//2//5ef//zn+fKXv7zX26xYsSIDAwPbL/39/RMOTTUOmpU0ZkzsZzRmJAePsy/+O09nZIKndo5kOL+If73pBPqps9TdT4mOoj3tdpR+mr70E9ONfuoc+okSTegV7J773OfmV37lV7J+/d7P3+vp6UlPT89ExlCTvsk4szJJ7zjPrHwyk3F+aSM/ywTOL2Xa0k8Htrr7KdFRTMz+Oko/TV/6ielOPx249BMlmtB5c5s3b86//du/Zfbs2ZOVh4IsuChpTmyJneZIsmCcr0F3V1anMcFTOxvpyl2ZwCvxMW3ppwNb3f2U6CgmRkcduPQT051+OnDpJ0rU1m/D8uXLs2bNmjz66KO566678hu/8RuZMWNG3va2t01VPmo0c34yf3HSGOf5dI3u5Ngl43+70KfSn0dyS4bz7LhuP5xn83C+6q1CO4R+6ix191Oio2iPjuoc+onpRj91Dv1EidpaSj322GN529velgULFuQ3f/M3c+SRR+buu+/OUUcdNVX5qNlpy5Pm1vHdtjmcLPzAxOZ/I1dkRg4a1227MiO356qJBWDa0E+dp+5+SnQUY6ejOot+YjrRT51FP1GatnakX/ziF6cqB4WafVZyxhXJ3cvbv+0Zn2rdfiLW5Tv5u3wgF+TKtm/79/lg1uU7EwvAtKGfOk/d/ZToKMZOR3UW/cR0op86i36iNBN7Micd4dRLW8WV7P9Uz23fP+OK1u0mw+25Kn+X1kp+f6d5bvv+3+UDNujQAerup0RHAXumn4BS6SdKYinFfjUardM0l6xJ5r8pSaP1VqDb3k50+8eN1veXrGldv9GYvAy356pckbPySP4pIxnJcLZmOFvTzEiG82yGszUjGckj+adckbOUFXSIEvop0VHA7vQTUCr9REnG+RJndKLZZ7Uum/uTtdcmg+uTXw4mB/e23hZ0wcUTe9G7/VmX72RdvpPDMzevysU5KifkkPTmFxnMz7I+d+VaL3gHHarufkp0FLBn+gkolX6iBJZStG3mvOT0j9Q3/6k8ln/Kx+oLABSr7n5KdBSwZ/oJKJV+ok6evgcAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByjWaz2axy4ODgYPr6+pJGcticKie3PLMpaY4kja7k0NnVz5dBhtIy1D0/SbZsTNJMBgYG0tvbW0+I1N9PSRnHo+4Mdc+XQYbRSugo/SRDKfNlKCuDfmop4VjIIEMp80vJMNZ+qm8pBTBKMUspgD0o4kEfwB7oJ6BU++un7gqz7MqZUjLIUESGuucnO7boxfAvfR3/OymDDDsrqqP0U8dnqHu+DGVl0E8tJRwLGWQoZX4pGcbaT7UtpQ49Jln6WPVzb5ibbHm8dWDqmC+DDKVlqHt+klw/p1Wcpairn5IyjkfdGeqeL4MMo5XUUfpJhrrny1BWBv3UUsKxkEGGUuaXkmGs/eSFzgEAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDl2l5KPf7443n729+eI488MoccckhOPfXU3H///VORDaAt+gkomY4CSqWfgLp0t3Plp556KmeeeWbOOeec3HrrrTnqqKOybt26HH744VOVD2BM9BNQMh0FlEo/AXVqayn1yU9+MvPmzcu11167/WvHHXfcpIcCaJd+Akqmo4BS6SegTm09fe+rX/1qXvayl+WCCy7I0UcfnZe85CX53Oc+N1XZAMZMPwEl01FAqfQTUKe2llI/+clPsmrVqpx44on52te+lne+851573vfm+uuu26vtxkaGsrg4OAuF4DJpp+AkrXbUfoJqIp+AurU1tP3RkZG8rKXvSyXX355kuQlL3lJfvCDH+Qv//Ivc+GFF+7xNitXrsxHP/rRiScF2Af9BJSs3Y7ST0BV9BNQp7bOlJo9e3Ze/OIX7/K1X/3VX82GDRv2epsVK1ZkYGBg+6W/v398SQH2QT8BJWu3o/QTUBX9BNSprTOlzjzzzKxdu3aXr/34xz/Oscceu9fb9PT0pKenZ3zpAMZIPwEla7ej9BNQFf0E1KmtM6X+4A/+IHfffXcuv/zyrF+/PjfeeGP++q//OsuWLZuqfABjop+AkukooFT6CahTW0upl7/85bnpppvyhS98Iaeccko+9rGP5eqrr87SpUunKh/AmOgnoGQ6CiiVfgLq1NbT95Jk8eLFWbx48VRkAZgQ/QSUTEcBpdJPQF3aOlMKAAAAACaDpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAACoXKPZbDarHDg4OJi+vr6kkRw2p8rJLc9sSpojSaMrOXR29fNlkKG0DHXPT5ItG5M0k4GBgfT29tYTIvX3U1LG8ag7Q93zZZBhtBI6Sj/JUMp8GcrKoJ9aSjgWMshQyvxSMoy1n+pbSgGMUsxSCmAPinjQB7AH+gko1f76qbvCLLtyppQMMhSRoe75yY4tejH8S1/H/07KIMPOiuoo/dTxGeqeL0NZGfRTSwnHQgYZSplfSoax9lNtS6lDj0mWPlb93BvmJlsebx2YOubLIENpGeqenyTXz2kVZynq6qekjONRd4a658sgw2gldZR+kqHu+TKUlUE/tZRwLGSQoZT5pWQYaz95oXMAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQubaWUi984QvTaDR2uyxbtmyq8gGMmY4CSqWfgFLpJ6BO3e1c+b777svw8PD2z3/wgx/k3HPPzQUXXDDpwQDapaOAUuknoFT6CahTW0upo446apfPP/GJT+RFL3pRXvOa10xqKIDx0FFAqfQTUCr9BNRp3K8p9ctf/jLXX399LrnkkjQajcnMBDBhOgoolX4CSqWfgKq1dabUzr7yla/k5z//eS666KJ9Xm9oaChDQ0PbPx8cHBzvSIAxG0tH6SegDvoJKJV+Aqo27jOlrrnmmixatChz5szZ5/VWrlyZvr6+7Zd58+aNdyTAmI2lo/QTUAf9BJRKPwFVG9dS6qc//Wluv/32/O7v/u5+r7tixYoMDAxsv/T3949nJMCYjbWj9BNQNf0ElEo/AXUY19P3rr322hx99NE577zz9nvdnp6e9PT0jGcMwLiMtaP0E1A1/QSUSj8BdWj7TKmRkZFce+21ufDCC9PdPe6XpAKYEjoKKJV+Akqln4C6tL2Uuv3227Nhw4ZccsklU5EHYEJ0FFAq/QSUSj8BdWl7Df6GN7whzWZzKrIATJiOAkqln4BS6SegLuN+9z0AAAAAGC9LKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFC5RrPZbFY5cHBwMH19fUkjOWxOlZNbntmUNEeSRldy6Ozq58sgQ2kZ6p6fJFs2JmkmAwMD6e3trSdE6u+npIzjUXeGuufLIMNoJXSUfpKhlPkylJVBP7WUcCxkkKGU+aVkGGs/1beUAhilmKUUwB4U8aAPYA/0E1Cq/fVTd4VZduVMKRlkKCJD3fOTHVv0YviXvo7/nZRBhp0V1VH6qeMz1D1fhrIy6KeWEo6FDDKUMr+UDGPtp9qWUocekyx9rPq5N8xNtjzeOjB1zJdBhtIy1D0/Sa6f0yrOUtTVT0kZx6PuDHXPl0GG0UrqKP0kQ93zZSgrg35qKeFYyCBDKfNLyTDWfvJC5wAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKBybS2lhoeH8+EPfzjHHXdcDjnkkLzoRS/Kxz72sTSbzanKBzAm+gkomY4CSqWfgDp1t3PlT37yk1m1alWuu+66nHzyybn//vtz8cUXp6+vL+9973unKiPAfuknoGQ6CiiVfgLq1NZS6q677sr555+f8847L0nywhe+MF/4whdy7733Tkk4gLHST0DJdBRQKv0E1Kmtp++96lWvyje/+c38+Mc/TpI89NBD+ed//ucsWrRor7cZGhrK4ODgLheAyaafgJK121H6CaiKfgLq1NaZUh/60IcyODiYk046KTNmzMjw8HA+/vGPZ+nSpXu9zcqVK/PRj350wkEB9kU/ASVrt6P0E1AV/QTUqa0zpb785S/nhhtuyI033pjvfe97ue6663LFFVfkuuuu2+ttVqxYkYGBge2X/v7+CYcGGE0/ASVrt6P0E1AV/QTUqa0zpT74wQ/mQx/6UH77t387SXLqqafmpz/9aVauXJkLL7xwj7fp6elJT0/PxJMC7IN+AkrWbkfpJ6Aq+gmoU1tnSj3zzDPp6tr1JjNmzMjIyMikhgJol34CSqajgFLpJ6BObZ0ptWTJknz84x/P/Pnzc/LJJ+f73/9+rrrqqlxyySVTlQ9gTPQTUDIdBZRKPwF1amsp9Rd/8Rf58Ic/nHe961158sknM2fOnPze7/1ePvKRj0xVPoAx0U9AyXQUUCr9BNSpraXUrFmzcvXVV+fqq6+eojgA46OfgJLpKKBU+gmoU1uvKQUAAAAAk8FSCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgco1ms9mscuDAwECe+9znJkkOnV3l5JZnnkjSTNJIDj2m+vkyyFBahrrnJ8kzm1r/+/Of/zx9fX31hEj9/ZQUcjz8Tsogw64ZCugo/SRDKfNlKCyDfkpSyLGQQYZC5heTYYz9VPlS6rHHHsu8efOqHAlME/39/Zk7d25t8/UTsC91dpR+AvZFPwGl2l8/Vb6UGhkZycaNGzNr1qw0Go22bz84OJh58+alv78/vb29U5BQhumSoe75Mkxehmazmaeffjpz5sxJV1d9zyrWTzIcSBnqnn8gZSihoybaT0n9x6Pu+TLIUFoG/bRD3ceihAx1z5dBhsnOMNZ+6p5IyPHo6uqalC1+b29vbQdHhrIy1D1fhsnJUOfT9rbRTzIciBnqnn+gZKi7oyarn5L6j0fd82WQobQM+mmHuo9FCRnqni+DDJOZYSz95IXOAQAAAKicpRQAAAAAlZt2S6menp78yZ/8SXp6emTo8Ax1z5ehrAwlKOHPQQYZSpkvQ3nq/rOoe74MMpSWoe75JSnhz6LuDHXPl0GGujJU/kLnAAAAADDtzpQCAAAAYPqzlAIAAACgcpZSAAAAAFTOUgoAAACAyk2rpdR3v/vdzJgxI+edd17lsy+66KI0Go3tlyOPPDJvfOMb8/DDD1ee5Yknnsh73vOeHH/88enp6cm8efOyZMmSfPOb35zy2Tv/ORx00EF5/vOfn3PPPTef//znMzIyMuXzR2fY+fLGN76xkvn7y7F+/fpK5j/xxBN53/velxNOOCHPec5z8vznPz9nnnlmVq1alWeeeWbK51900UV5y1vestvX77jjjjQajfz85z+f8gyl0VH6aXSOujqq7n5K6u0o/bQ7/aSfRufQT/4OVQr9pJ9G59BPndVP02opdc011+Q973lP7rzzzmzcuLHy+W984xuzadOmbNq0Kd/85jfT3d2dxYsXV5rh0Ucfzemnn55vfetb+dSnPpVHHnkkt912W84555wsW7askgzb/hweffTR3HrrrTnnnHPyvve9L4sXL87WrVsrzbDz5Qtf+EIls/eX47jjjpvyuT/5yU/ykpe8JF//+tdz+eWX5/vf/36++93v5g//8A9zyy235Pbbb5/yDOyu0ztKP+2eo86OqqufEh1VIv2kn0bn0E/6qRT6ST+NzqGfOqufuusOMFabN2/Ol770pdx///154oknsnr16vzxH/9xpRl6enpyzDHHJEmOOeaYfOhDH8qrX/3q/OxnP8tRRx1VSYZ3vetdaTQauffee3PYYYdt//rJJ5+cSy65pJIMO/85vOAFL8hLX/rSnHHGGXnd616X1atX53d/93crzVCnunK8613vSnd3d+6///5dfg+OP/74nH/++Wk2m5Vn6nQ6Sj/tLUdd6sygo8qin/TT3nLURT+xjX7ST3vLURf9VL1pc6bUl7/85Zx00klZsGBB3v72t+fzn/98rQdl8+bNuf7663PCCSfkyCOPrGTmf/3Xf+W2227LsmXLdvkl3ea5z31uJTn25LWvfW1OO+20/MM//ENtGTrFf/7nf+brX//6Xn8PkqTRaFScik7vKP3ENjqqPPpJP9Gin8qjn/QTLZ3cT9NmKXXNNdfk7W9/e5LWKXUDAwNZs2ZNpRluueWWzJw5MzNnzsysWbPy1a9+NV/60pfS1VXNH+P69evTbDZz0kknVTKvXSeddFIeffTRSmbtfCy2XS6//PJKZu8rxwUXXDDlM7f9HixYsGCXrz/vec/bnuOP/uiPpjxHsufjsGjRokpml6bTO0o/7aqEjqqjn5JyOko/7aCf9NPO9FP9/ZToqG30k37amX7qzH6aFk/fW7t2be69997cdNNNSZLu7u781m/9Vq655pqcffbZleU455xzsmrVqiTJU089lc9+9rNZtGhR7r333hx77LFTPr/00/WazWZl29udj8U2RxxxRCWz95Vjb1vtKtx7770ZGRnJ0qVLMzQ0VMnMPR2He+65Z/tfLjqFjtJPo5XQUSX1U1J9R+mnFv2kn0bTT7vzd6h66Cf9NJp+2l0n9NO0WEpdc8012bp1a+bMmbP9a81mMz09Pfn0pz+dvr6+SnIcdthhOeGEE7Z//jd/8zfp6+vL5z73ufzZn/3ZlM8/8cQT02g08qMf/WjKZ43HD3/4w8peBG70sahLHTlOOOGENBqNrF27dpevH3/88UmSQw45pLIse/r//9hjj1U2vxQ6Sj+NVkJH1ZWhlI7STy36ST+Npp/q76dERyX6KdFPo+mnzuyn4p++t3Xr1vzt3/5trrzyyjz44IPbLw899FDmzJlTyzuubdNoNNLV1ZVf/OIXlcw74ogj8uu//uv5zGc+ky1btuz2/TrfPvZb3/pWHnnkkbz1rW+tLUOnOPLII3Puuefm05/+9B5/D6iWjmrRT2yjo8qhn1r0E9vop3Lopxb9xDad3E/Fnyl1yy235Kmnnsrv/M7v7LYtf+tb35prrrkmv//7v19JlqGhoTzxxBNJWqd2fvrTn87mzZuzZMmSSuYnyWc+85mceeaZecUrXpE//dM/zcKFC7N169Z84xvfyKpVq/LDH/5wyjNs+3MYHh7Of/zHf+S2227LypUrs3jx4rzjHe+Y8vk7Z9hZd3d3nve851Uyv26f/exnc+aZZ+ZlL3tZLrvssixcuDBdXV2577778qMf/Sinn3563RE7ho7aQT/tnmNnOkpHVU0/7aCfds+xM/2kn6qmn3bQT7vn2Jl+6oB+ahZu8eLFzTe96U17/N4999zTTNJ86KGHpjzHhRde2Eyy/TJr1qzmy1/+8ubf//3fT/ns0TZu3NhctmxZ89hjj20efPDBzRe84AXNN7/5zc1vf/vbUz575z+H7u7u5lFHHdV8/etf3/z85z/fHB4envL5ozPsfFmwYEEl83fOcf7551c6c2cbN25svvvd724ed9xxzYMOOqg5c+bM5ite8Yrmpz71qeaWLVumfP7e/v9/+9vfbiZpPvXUU1OeoQQ6aled3k+jc9TVUXX3U7NZb0fppxb9tCv9pJ+28Xeo+umnXekn/bRNJ/ZTo9ks/NXVAAAAADjgFP+aUgAAAAAceCylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcv8/fkssLgy6ok8AAAAASUVORK5CYII=\n", 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gPCV0QwkZqIelFGO2aW3y4BXJxptaby2ZJM2hpDGz9fF9lyZHL0kWXZLMOWP/mw+U6/ickbPzgZycJWlmOEkyIzMy/D8fL8mleTBfy625IuvzvSnJoKOA0ZTQDSVkAMpTQjeUkIF6efoe+9RsJg9cntx0ZtJ3c5JmqyiaQ//z/e0fN5ONNydfe02rWJrN/WM+ULaz84FckrU5KYszIzMyM12Zma40dvl4Rmbk5Lwpl+T2vD4XT+p8HQWMpoRuKCEDUJ4SuqGEDJTBUop9eujK5K4Ptj5ubtv7dbd//85LWrfbH+YD5Xp9Ls7/yuVJkpk5YK/X3f7983LFpC6mdBQwmhK6oYQMQHlK6IYSMlAGSyn2atPa1p1/PO68JNl8+/SeD5Tr+JyR83LFuG57Xq7I8Xn1hDPoKGA0JXRDCRmA8pTQDSVkoBwTWkp94hOfSKPRyPvf//5JikNpHrwiaYzzlccaXa3bT+f5TF/6af93dj6QoTwzrtsO5ZlJOVtKRzEe+mn/V0I3lJCB6UlH7d9K6IYSMlCOcS+l7rnnnvzN3/xNFi1aNJl5KMiWja0XnNvX6ZR70tyW/PxryZZxvuFV3fOZvvTT/u/QzM/JWbLPp+ztycwckEV5cw7NvHFn0FGMh37a/5XQDSVkYHrSUfu3ErqhhAyUZVxLqS1btmTZsmX57Gc/m0MPPXSyM1GIdWt2vgPCeDVmJOuumZ7zmZ70U2d4VS7Y8S5749XMcF6VC8d9ex1Fu/RTZyihG0rIwPSjo/Z/JXRDCRkoy7h+HZYvX55zzjknr3/96/d53cHBwQwMDOx2YXroXz85P2dgw/Scz/SknzrDkTl+En5KM0fkuHHfWkfRLv3UGUrohhIyMP2MtaP00/RVQjeUkIGytP1Mzi984Qv5wQ9+kHvuuWdM11+5cmU++tGPth2M+j3z1M635Byv5lDyq3H+d6ru+Uw/+qlzPCezM2OC79UxIzNzUHrGfXsdRTv0U+cooRtKyMD00k5H6afpq4RuKCEDZWnrEX1fX1/e97735frrr89znvOcMd1mxYoV6e/v33Hp6/Pkz+nigNlJY+bEfkZjZnLgOP/OV/d8phf91Fn+O09leIJP3xvOUH6Z8T+i0VGMlX7qLCV0QwkZmD7a7Sj9NH2V0A0lZKAsbZ0pdd999+Xxxx/PS1/60h1fGxoayu23356rr746g4ODmTlz99+w7u7udHd3T05aKtU7Gc+OSdIzzmfH1D2f6UU/dZbHMxnnfjfyi4z/3G8dxVjpp85SQjeUkIHpo92O0k/TVwndUEIGytLWmVKve93r8tBDD+X+++/fcXnZy16WZcuW5f7773/WAyqmt4UXJM2JnYiQ5nCycJyvI1z3fKYX/dRZ7siaNCb49L1GZuSOjP9VMnUUY6WfOksJ3VBCBqYPHdU5SuiGEjJQlrbOlJo9e3ZOOumk3b52yCGH5PDDD3/W15n+Zi1IFixJ+m4e31t2NrqSBW9KZs2fnvOZXvRTZ3kifXkoN+WkLM7MHND27YfyTB7K1/NEHhl3Bh3FWOmnzlJCN5SQgelDR3WOErqhhAyUZYJvxsj+7pRLxlcWSesF6BZ9YHrPB8r1rVw+roVU0nqR81tz5YQz6ChgNCV0QwkZgPKU0A0lZKAcE15K3XbbbbnqqqsmIQolmnNGctrl47vtaZ9q3X46z2d600/7t/X5Xr6c8T0q+Yd8MOvzvQln0FGMl37av5XQDSVkYPrSUfuvErqhhAyUw5lS7NPJF+8sjcY+nvC5/funXd663f4wHyjXrblyx2JqKM/s9brbv//lfGBSzpLaTkcBoymhG0rIAJSnhG4oIQNlsJRinxqN1imSS9e2nr+bRuttOLe/leeOjxut7y9d27p+o7F/zAfKdmuuzOU5Iw/l6xnOcIayLUPZlmaGM5RnMpRtGc5wHsrXc3nOmNSFVKKjgNGV0A0lZADKU0I3lJCBMrT1Qud0tjlntC5b+pJ11yQDG5JfDSQH9rTeknPhhVP7gnN1zwfKtT7fy/p8L4dmXl6VC3NEjstB6ckvM5BfZEPuyDUTelHzsdBRwGhK6IYSMgDlKaEbSshAvSylaNus+cmpH+nc+UC5nsgj+Xo+VmsGHQWMpoRuKCEDUJ4SuqGEDNTD0/cAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUrtFsNptVDhwYGEhvb2/SSA6ZW+Xklqc3J83hpDEjOXhO9fNlkKG0DHXPT5Ktm5I0k/7+/vT09NQTIvX3U1LG8ag7Q93zZZBhpBI6Sj/JUMp8GcrKoJ9aSjgWMshQyvxSMoy1n+pbSgGMUMxSCmAURfylD2AU+gko1b76qavCLLtzppQMMhSRoe75yc4tejH8S1/H/07KIMOuiuoo/dTxGeqeL0NZGfRTSwnHQgYZSplfSoax9lNtS6mDj0qWPVL93OvnJVsfbR2YOubLIENpGeqenyTXzW0VZynq6qekjONRd4a658sgw0gldZR+kqHu+TKUlUE/tZRwLGSQoZT5pWQYaz95oXMAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVq+/d95i2tmxM1q1J+tcnzzyVHDA76T0+WXhBMmvB1M8/NPPzqlyQI3N8npPZ+e88lcezPndkTZ5I39QHAIpVdz+VkKHu+cDoSrhvegwFjEY/USdLKcZs09rkwSuSjTe13loySZpDSWNm6+P7Lk2OXpIsuiSZc8bkzz8+Z+TsfCAnZ0maGU6SzMiMDP/Px0tyaR7M13Jrrsj6fG/yAwDFqrufSshQ93xgdCXcNz2GAkajnyiBp++xT81m8sDlyU1nJn03J2m2yqo59D/f3/5xM9l4c/K117TKrdmcvAxn5wO5JGtzUhZnRmZkZroyM11p7PLxjMzIyXlTLsnteX0unrzhQLFK6Ke6M9Q9HxhdKfdNj6GAkfQTJbGUYp8eujK564Otj5vb9n7d7d+/85LW7SbD63Nx/lcuT5LMzAF7ve7275+XK5QWdIC6+6mEDHXPB0ZXwn3TYyhgNPqJkrS1lLr00kvTaDR2u5xwwglTlY0CbFrbKqDxuPOSZPPtE5t/fM7IebliXLc9L1fk+Lx6YgGYNvRT56m7n0rIUPd8xk5HdZYS7pseQzFW+qmz6CdK0/aZUieeeGI2b9684/LP//zPU5GLQjx4RdIY5yuPNbpat5+Is/OBDOWZcd12KM/YpHcY/dRZ6u6nEjLUPZ/26KjOUcJ902Mo2qGfOod+ojRt/zp2dXXlqKOOmoosFGbLxtaL3mWczx1ubkt+/rVkS18ya377tz8083NylmTGOJ9lOjMHZFHenEMzL0/kkXH9DKYX/dQ56u6nEjLUPZ/26ajOUMJ902Mo2qWfOoN+okRt/yasX78+c+fOzbHHHptly5Zl48aNU5GLAqxbs/NdGMarMSNZd834bvuqXLDjHRjGq5nhvCoXTuhnMH3op85Rdz+VkKHu+bRPR3WGEu6bHkPRLv3UGfQTJWrrTKnf+I3fyJo1a7Jw4cJs3rw5H/3oR/PqV786P/rRjzJ79uxRbzM4OJjBwcEdnw8MDEwsMZXpXz85P2dgw/hud2SOn4TpzRyR4ybh51A6/dRZ6u6nEjLUPZ/2tNtR+mn6KuG+6TEU7dBPnUM/UaK2llKLFy/e8fGiRYvyG7/xGzn66KPzpS99Kb/3e7836m1WrlyZj370oxNLSS2eeWrn24KOV3Mo+dU4/zv1nMwe92md283IzByUngn9DKYH/dRZ6u6nEjLUPZ/2tNtR+mn6KuG+6TEU7dBPnUM/UaIJ/TY897nPza/92q9lw4Y9r0pXrFiR/v7+HZe+vr6JjKRCB8xOGjMn9jMaM5MDx9kX/52nMjzBUzuHM5Rfxt+4OpF+2r/V3U8lZKh7PhOzr47ST9NXCfdNj6GYCP20/9JPlGhCS6ktW7bk3/7t3zJnzpw9Xqe7uzs9PT27XZgeeifjzMokPeM8s/LxTMb5pY38Ip6b0on00/6t7n4qIUPd85mYfXWUfpq+SrhvegzFROin/Zd+okRtLaUuueSSrF27Ng8//HDuuOOO/NZv/VZmzpyZt73tbVOVjxotvCBpTmyJneZwsnCcr0F3R9akMcFTOxuZkTviVXw7gX7qLHX3UwkZ6p5Pe3RU5yjhvukxFO3QT51DP1Gitn4bHnnkkbztbW/LwoUL89u//ds5/PDDc+edd+aII46YqnzUaNaCZMGSpNHWK4/t1OhKjl46/rcLfSJ9eSg3ZSjPjOv2Q3kmD+ar3iq0Q+inzlJ3P5WQoe75tEdHdY4S7pseQ9EO/dQ59BMlauvX8Qtf+MJU5aBQp1ySbPza+G7bHEoWfWBi87+Vy3NK3jyu287IzNyaKycWgGlDP3WeuvuphAx1z2fsdFRnKeG+6TEUY6WfOot+ojQTO2+O/d6cM5LTLh/fbU/7VOv2E7E+38uXM77m+4d8MOvzvYkFAIpVdz+VkKHu+cDoSrhvegwFjEY/URpLKfbp5It3Fte+TvXc/v3TLm/dbjLcmit3lNa+TvPc/v0v5wM26NAB6u6nEjLUPR8YXQn3TY+hgNHoJ0piKcU+NRqt0zSXrk0WvClJo/VWoNvfTnTHx43W95eubV2/0Zi8DLfmylyeM/JQvp7hDGco2zKUbWlmOEN5JkPZluEM56F8PZfnDGUFHaKEfqo7Q93zgdGVct/0GAoYST9RknG+xBmdaM4ZrcuWvmTdNcnAhuRXA8mBPa23BV144dS+YO76fC/r870cmnl5VS7METkuB6Unv8xAfpENuSPXeME76FB191MJGeqeD4yuhPumx1DAaPQTJbCUom2z5ienfqS++U/kkXw9H6svAFCsuvuphAx1zwdGV8J902MoYDT6iTp5+h4AAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKNZrNZrPKgQMDA+nt7U0aySFzq5zc8vTmpDmcNGYkB8+pfr4MMpSWoe75SbJ1U5Jm0t/fn56ennpCpP5+Sso4HnVnqHu+DDKMVEJH6ScZSpkvQ1kZ9FNLCcdCBhlKmV9KhrH2U31LKYARillKAYyiiL/0AYxCPwGl2lc/dVWYZXfOlJJBhiIy1D0/2blFL4Z/6ev430kZZNhVUR2lnzo+Q93zZSgrg35qKeFYyCBDKfNLyTDWfqptKXXwUcmyR6qfe/28ZOujrQNTx3wZZCgtQ93zk+S6ua3iLEVd/ZSUcTzqzlD3fBlkGKmkjtJPMtQ9X4ayMuinlhKOhQwylDK/lAxj7ScvdA4AAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAq1/ZS6tFHH83b3/72HH744TnooINy8skn5957752KbABt0U9AyXQUUCr9BNSlq50rP/HEEzn99NNz1lln5eabb84RRxyR9evX59BDD52qfABjop+AkukooFT6CahTW0upT37yk5k/f36uueaaHV875phjJj0UQLv0E1AyHQWUSj8BdWrr6Xtf/epX87KXvSznnXdejjzyyLzkJS/JZz/72b3eZnBwMAMDA7tdACabfgJK1m5H6SegKvoJqFNbS6mf/exnWbVqVY4//vh84xvfyDvf+c68973vzbXXXrvH26xcuTK9vb07LvPnz59waICR9BNQsnY7Sj8BVdFPQJ3aWkoNDw/npS99aS677LK85CUvyf/3//1/+T//5//kr//6r/d4mxUrVqS/v3/Hpa+vb8KhAUbST0DJ2u0o/QRURT8BdWprKTVnzpy8+MUv3u1rv/7rv56NGzfu8Tbd3d3p6enZ7QIw2fQTULJ2O0o/AVXRT0Cd2lpKnX766Vm3bt1uX/vpT3+ao48+elJDAbRLPwEl01FAqfQTUKe2llJ/9Ed/lDvvvDOXXXZZNmzYkBtuuCF/+7d/m+XLl09VPoAx0U9AyXQUUCr9BNSpraXUy1/+8tx44435/Oc/n5NOOikf+9jHctVVV2XZsmVTlQ9gTPQTUDIdBZRKPwF16mr3BkuWLMmSJUumIgvAhOgnoGQ6CiiVfgLq0taZUgAAAAAwGSylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAq12g2m80qBw4MDKS3tzdpJIfMrXJyy9Obk+Zw0piRHDyn+vkyyFBahrrnJ8nWTUmaSX9/f3p6euoJkfr7KSnjeNSdoe75MsgwUgkdpZ9kKGW+DGVl0E8tJRwLGWQoZX4pGcbaT/UtpQBGKGYpBTCKIv7SBzAK/QSUal/91FVhlt05U0oGGYrIUPf8ZOcWvRj+pa/jfydlkGFXRXWUfur4DHXPl6GsDPqppYRjIYMMpcwvJcNY+6m2pdTBRyXLHql+7vXzkq2Ptg5MHfNlkKG0DHXPT5Lr5raKsxR19VNSxvGoO0Pd82WQYaSSOko/yVD3fBnKyqCfWko4FjLIUMr8UjKMtZ+80DkAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJVrayn1whe+MI1G41mX5cuXT1U+gDHTUUCp9BNQKv0E1KmrnSvfc889GRoa2vH5j370o5x99tk577zzJj0YQLt0FFAq/QSUSj8BdWprKXXEEUfs9vknPvGJvOhFL8prXvOaSQ0FMB46CiiVfgJKpZ+AOrW1lNrVr371q1x33XW5+OKL02g09ni9wcHBDA4O7vh8YGBgvCMBxmwsHaWfgDroJ6BU+gmo2rhf6PwrX/lKnnzyyVxwwQV7vd7KlSvT29u74zJ//vzxjgQYs7F0lH4C6qCfgFLpJ6Bq415KrV69OosXL87cuXP3er0VK1akv79/x6Wvr2+8IwHGbCwdpZ+AOugnoFT6CajauJ6+9/Of/zy33npr/vEf/3Gf1+3u7k53d/d4xgCMy1g7Sj8BVdNPQKn0E1CHcZ0pdc011+TII4/MOeecM9l5ACZMRwGl0k9AqfQTUIe2l1LDw8O55pprcv7556era9yvkw4wJXQUUCr9BJRKPwF1aXspdeutt2bjxo256KKLpiIPwIToKKBU+gkolX4C6tL2GvwNb3hDms3mVGQBmDAdBZRKPwGl0k9AXcb97nsAAAAAMF6WUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlWs0m81mlQMHBgbS29ubNJJD5lY5ueXpzUlzOGnMSA6eU/18GWQoLUPd85Nk66YkzaS/vz89PT31hEj9/ZSUcTzqzlD3fBlkGKmEjtJPMpQyX4ayMuinlhKOhQwylDK/lAxj7af6llIAIxSzlAIYRRF/6QMYhX4CSrWvfuqqMMvunCklgwxFZKh7frJzi14M/9LX8b+TMsiwq6I6Sj91fIa658tQVgb91FLCsZBBhlLml5JhrP1U21Lq4KOSZY9UP/f6ecnWR1sHpo75MshQWoa65yfJdXNbxVmKuvopKeN41J2h7vkyyDBSSR2ln2Soe74MZWXQTy0lHAsZZChlfikZxtpPXugcAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVK6tpdTQ0FA+/OEP55hjjslBBx2UF73oRfnYxz6WZrM5VfkAxkQ/ASXTUUCp9BNQp652rvzJT34yq1atyrXXXpsTTzwx9957by688ML09vbmve9971RlBNgn/QSUTEcBpdJPQJ3aWkrdcccdOffcc3POOeckSV74whfm85//fO6+++4pCQcwVvoJKJmOAkqln4A6tfX0vVe96lX59re/nZ/+9KdJkgceeCD//M//nMWLF09JOICx0k9AyXQUUCr9BNSprTOlPvShD2VgYCAnnHBCZs6cmaGhoXz84x/PsmXL9nibwcHBDA4O7vh8YGBg/GkB9kA/ASVrt6P0E1AV/QTUqa0zpb70pS/l+uuvzw033JAf/OAHufbaa3P55Zfn2muv3eNtVq5cmd7e3h2X+fPnTzg0wEj6CShZux2ln4Cq6CegTm0tpT74wQ/mQx/6UH73d383J598cv73//7f+aM/+qOsXLlyj7dZsWJF+vv7d1z6+vomHBpgJP0ElKzdjtJPQFX0E1Cntp6+9/TTT2fGjN33WDNnzszw8PAeb9Pd3Z3u7u7xpQMYI/0ElKzdjtJPQFX0E1CntpZSS5cuzcc//vEsWLAgJ554Yn74wx/myiuvzEUXXTRV+QDGRD8BJdNRQKn0E1CntpZSf/VXf5UPf/jDede73pXHH388c+fOzR/8wR/kIx/5yFTlAxgT/QSUTEcBpdJPQJ3aWkrNnj07V111Va666qopigMwPvoJKJmOAkqln4A6tfVC5wAAAAAwGSylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAqZykFAAAAQOUazWazWeXA/v7+PPe5z02SHDynysktTz+WpJmkkRx8VPXzZZChtAx1z0+Spze3/vfJJ59Mb29vPSFSfz8lhRwPv5MyyLB7hgI6Sj/JUMp8GQrLoJ+SFHIsZJChkPnFZBhjP1W+lHrkkUcyf/78KkcC00RfX1/mzZtX23z9BOxNnR2ln4C90U9AqfbVT5UvpYaHh7Np06bMnj07jUaj7dsPDAxk/vz56evrS09PzxQklGG6ZKh7vgyTl6HZbOapp57K3LlzM2NGfc8q1k8y7E8Z6p6/P2UooaMm2k9J/cej7vkyyFBaBv20U93HooQMdc+XQYbJzjDWfuqaSMjxmDFjxqRs8Xt6emo7ODKUlaHu+TJMToY6n7a3nX6SYX/MUPf8/SVD3R01Wf2U1H886p4vgwylZdBPO9V9LErIUPd8GWSYzAxj6ScvdA4AAABA5SylAAAAAKjctFtKdXd358/+7M/S3d0tQ4dnqHu+DGVlKEEJfw4yyFDKfBnKU/efRd3zZZChtAx1zy9JCX8WdWeoe74MMtSVofIXOgcAAACAaXemFAAAAADTn6UUAAAAAJWzlAIAAACgctNqKfX9738/M2fOzDnnnFP57AsuuCCNRmPH5fDDD88b3/jGPPjgg5Vneeyxx/Ke97wnxx57bLq7uzN//vwsXbo03/72t6d89q5/DgcccECe//zn5+yzz87nPve5DA8PT/n8kRl2vbzxjW+sZP6+cmzYsKGS+Y899lje97735bjjjstznvOcPP/5z8/pp5+eVatW5emnn57y+RdccEHe8pa3POvrt912WxqNRp588skpz1AaHaWfRuaoq6Pq7qek3o7ST8+mn/TTyBz6yWOoUugn/TQyh37qrH6aVkup1atX5z3veU9uv/32bNq0qfL5b3zjG7N58+Zs3rw53/72t9PV1ZUlS5ZUmuHhhx/Oqaeemu985zv51Kc+lYceeii33HJLzjrrrCxfvrySDNv/HB5++OHcfPPNOeuss/K+970vS5YsybZt2yrNsOvl85//fCWz95XjmGOOmfK5P/vZz/KSl7wk3/zmN3PZZZflhz/8Yb7//e/nj//4j3PTTTfl1ltvnfIMPFund5R+enaOOjuqrn5KdFSJ9JN+GplDP+mnUugn/TQyh37qrH7qqjvAWG3ZsiVf/OIXc++99+axxx7LmjVr8qd/+qeVZuju7s5RRx2VJDnqqKPyoQ99KK9+9avzi1/8IkcccUQlGd71rnel0Wjk7rvvziGHHLLj6yeeeGIuuuiiSjLs+ufwghe8IC996Utz2mmn5XWve13WrFmT3//93680Q53qyvGud70rXV1duffee3f7PTj22GNz7rnnxptqVk9H6ac95ahLnRl0VFn0k37aU4666Ce200/6aU856qKfqjdtzpT60pe+lBNOOCELFy7M29/+9nzuc5+r9aBs2bIl1113XY477rgcfvjhlcz8r//6r9xyyy1Zvnz5br+k2z33uc+tJMdoXvva1+aUU07JP/7jP9aWoVP853/+Z775zW/u8fcgSRqNRsWp6PSO0k9sp6PKo5/0Ey36qTz6ST/R0sn9NG2WUqtXr87b3/72JK1T6vr7+7N27dpKM9x0002ZNWtWZs2aldmzZ+erX/1qvvjFL2bGjGr+GDds2JBms5kTTjihknntOuGEE/Lwww9XMmvXY7H9ctlll1Uye285zjvvvCmfuf33YOHChbt9/XnPe96OHH/yJ38y5TmS0Y/D4sWLK5ldmk7vKP20uxI6qo5+SsrpKP20k37ST7vST/X3U6KjttNP+mlX+qkz+2laPH1v3bp1ufvuu3PjjTcmSbq6uvI7v/M7Wb16dc4888zKcpx11llZtWpVkuSJJ57IZz7zmSxevDh33313jj766CmfX/rpes1ms7Lt7a7HYrvDDjusktl7y7GnrXYV7r777gwPD2fZsmUZHBysZOZox+Guu+7a8eCiU+go/TRSCR1VUj8l1XeUfmrRT/ppJP30bB5D1UM/6aeR9NOzdUI/TYul1OrVq7Nt27bMnTt3x9eazWa6u7tz9dVXp7e3t5IchxxySI477rgdn//d3/1dent789nPfjZ/8Rd/MeXzjz/++DQajfzkJz+Z8lnj8eMf/7iyF4EbeSzqUkeO4447Lo1GI+vWrdvt68cee2yS5KCDDqosy2j//x955JHK5pdCR+mnkUroqLoylNJR+qlFP+mnkfRT/f2U6KhEPyX6aST91Jn9VPzT97Zt25a///u/zxVXXJH7779/x+WBBx7I3Llza3nHte0ajUZmzJiRX/7yl5XMO+yww/Kbv/mb+fSnP52tW7c+6/t1vn3sd77znTz00EN561vfWluGTnH44Yfn7LPPztVXXz3q7wHV0lEt+ontdFQ59FOLfmI7/VQO/dSin9iuk/up+DOlbrrppjzxxBP5vd/7vWdty9/61rdm9erV+cM//MNKsgwODuaxxx5L0jq18+qrr86WLVuydOnSSuYnyac//emcfvrpecUrXpE///M/z6JFi7Jt27Z861vfyqpVq/LjH/94yjNs/3MYGhrKf/zHf+SWW27JypUrs2TJkrzjHe+Y8vm7ZthVV1dXnve851Uyv26f+cxncvrpp+dlL3tZLr300ixatCgzZszIPffck5/85Cc59dRT647YMXTUTvrp2Tl2paN0VNX000766dk5dqWf9FPV9NNO+unZOXalnzqgn5qFW7JkSfNNb3rTqN+76667mkmaDzzwwJTnOP/885tJdlxmz57dfPnLX978h3/4hymfPdKmTZuay5cvbx599NHNAw88sPmCF7yg+eY3v7n53e9+d8pn7/rn0NXV1TziiCOar3/965uf+9znmkNDQ1M+f2SGXS8LFy6sZP6uOc4999xKZ+5q06ZNzXe/+93NY445pnnAAQc0Z82a1XzFK17R/NSnPtXcunXrlM/f0///7373u80kzSeeeGLKM5RAR+2u0/tpZI66Oqrufmo26+0o/dSin3ann/TTdh5D1U8/7U4/6aftOrGfGs1m4a+uBgAAAMB+p/jXlAIAAABg/2MpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlbOUAgAAAKByllIAAAAAVM5SCgAAAIDKWUoBAAAAUDlLKQAAAAAq11X1wOHh4WzatCmzZ89Oo9GoejxQoGazmaeeeipz587NjBn17cr1EzCaEjpKPwGj0U9AqcbaT5UvpTZt2pT58+dXPRaYBvr6+jJv3rza5usnYG/q7Cj9BOyNfgJKta9+qnwpNXv27B0fHzyn6unJ048laSZpJAcfVf18GWQoLUPd85Pk6c2t/921H+pQdz8lhRwPv5MyyLB7hgI6Sj/JUMp8GQrLoJ+SFHIsZJChkPnFZBhjP1W+lNp+SufBc5K3b6p6enL9vGTro8khc5Nlj1Q/XwYZSstQ9/wkuW5uq7TqPuW77n5KyjgedWeoe74MMoxUQkfpJxlKmS9DWRn0U0sJx0IGGUqZX0qGsfaTFzoHAAAAoHKWUgAAAABUzlIKAAAAgMpZSgEAAABQOUspAAAAACpnKQUAAABA5SylAAAAAKicpRQAAAAAlWt7KXX77bdn6dKlmTt3bhqNRr7yla9MQSyA9uknoFT6CSiVfgLq1PZSauvWrTnllFPy6U9/eiryAIybfgJKpZ+AUuknoE5d7d5g8eLFWbx48VRkAZgQ/QSUSj8BpdJPQJ3aXkq1a3BwMIODgzs+HxgYmOqRAGOin4BS6SegVPoJmExT/kLnK1euTG9v747L/Pnzp3okwJjoJ6BU+gkolX4CJtOUL6VWrFiR/v7+HZe+vr6pHgkwJvoJKJV+Akqln4DJNOVP3+vu7k53d/dUjwFom34CSqWfgFLpJ2AyTfmZUgAAAAAwUttnSm3ZsiUbNmzY8fm///u/5/77789hhx2WBQsWTGo4gHboJ6BU+gkolX4C6tT2Uuree+/NWWedtePziy++OEly/vnnZ82aNZMWDKBd+gkolX4CSqWfgDq1vZQ688wz02w2pyILwIToJ6BU+gkolX4C6uQ1pQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlGs1ms1nlwIGBgfT29iaN5JC5VU5ueXpz0hxOGjOSg+dUP18GGUrLUPf8JNm6KUkz6e/vT09PTz0hUn8/JWUcj7oz1D1fBhlGKqGj9JMMpcyXoawM+qmlhGMhgwylzC8lw1j7qb6lFMAIxSylAEZRxF/6AEahn4BS7aufuirMsjtnSskgQxEZ6p6f7NyiF8O/9HX876QMMuyqqI7STx2foe75MpSVQT+1lHAsZJChlPmlZBhrP9W2lDr4qGTZI9XPvX5esvXR1oGpY74MMpSWoe75SXLd3FZxlqKufkrKOB51Z6h7vgwyjFRSR+knGeqeL0NZGfRTSwnHQgYZSplfSoax9pMXOgcAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHJtLaVWrlyZl7/85Zk9e3aOPPLIvOUtb8m6deumKhvAmOknoGQ6CiiVfgLq1NZSau3atVm+fHnuvPPOfOtb38ozzzyTN7zhDdm6detU5QMYE/0ElExHAaXST0Cdutq58i233LLb52vWrMmRRx6Z++67L2ecccakBgNoh34CSqajgFLpJ6BObS2lRurv70+SHHbYYXu8zuDgYAYHB3d8PjAwMJGRAGOin4CS7auj9BNQF/0EVGncL3Q+PDyc97///Tn99NNz0kkn7fF6K1euTG9v747L/PnzxzsSYEz0E1CysXSUfgLqoJ+Aqo17KbV8+fL86Ec/yhe+8IW9Xm/FihXp7+/fcenr6xvvSIAx0U9AycbSUfoJqIN+Aqo2rqfvvfvd785NN92U22+/PfPmzdvrdbu7u9Pd3T2ucADt0k9AycbaUfoJqJp+AurQ1lKq2WzmPe95T2688cbcdtttOeaYY6YqF0Bb9BNQMh0FlEo/AXVqaym1fPny3HDDDfmnf/qnzJ49O4899liSpLe3NwcddNCUBAQYC/0ElExHAaXST0Cd2npNqVWrVqW/vz9nnnlm5syZs+PyxS9+caryAYyJfgJKpqOAUuknoE5tP30PoET6CSiZjgJKpZ+AOo373fcAAAAAYLwspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKtdoNpvNKgcODAykt7c3aSSHzK1ycsvTm5PmcNKYkRw8p/r5MshQWoa65yfJ1k1Jmkl/f396enrqCZH6+ykp43jUnaHu+TLIMFIJHaWfZChlvgxlZdBPLSUcCxlkKGV+KRnG2k/1LaUARihmKQUwiiL+0gcwCv0ElGpf/dRVYZbdOVNKBhmKyFD3/GTnFr0Y/qWv438nZZBhV0V1lH7q+Ax1z5ehrAz6qaWEYyGDDKXMLyXDWPuptqXUwUclyx6pfu7185Ktj7YOTB3zZZChtAx1z0+S6+a2irMUdfVTUsbxqDtD3fNlkGGkkjpKP8lQ93wZysqgn1pKOBYyyFDK/FIyjLWfvNA5AAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqFxbS6lVq1Zl0aJF6enpSU9PT175ylfm5ptvnqpsAGOmn4CS6SigVPoJqFNbS6l58+blE5/4RO67777ce++9ee1rX5tzzz03//Iv/zJV+QDGRD8BJdNRQKn0E1CnrnauvHTp0t0+//jHP55Vq1blzjvvzIknnjipwQDaoZ+AkukooFT6CahTW0upXQ0NDeXLX/5ytm7dmle+8pWTmQlgQvQTUDIdBZRKPwFVa3sp9dBDD+WVr3xl/vu//zuzZs3KjTfemBe/+MV7vP7g4GAGBwd3fD4wMDC+pAD7oJ+AkrXTUfoJqJJ+AurS9rvvLVy4MPfff3/uuuuuvPOd78z555+ff/3Xf93j9VeuXJne3t4dl/nz508oMMCe6CegZO10lH4CqqSfgLq0vZQ68MADc9xxx+XUU0/NypUrc8opp+Qv//Iv93j9FStWpL+/f8elr69vQoEB9kQ/ASVrp6P0E1Al/QTUZdyvKbXd8PDwbqdvjtTd3Z3u7u6JjgFom34CSra3jtJPQJ30E1CVtpZSK1asyOLFi7NgwYI89dRTueGGG3LbbbflG9/4xlTlAxgT/QSUTEcBpdJPQJ3aWko9/vjjecc73pHNmzent7c3ixYtyje+8Y2cffbZU5UPYEz0E1AyHQWUSj8BdWprKbV69eqpygEwIfoJKJmOAkqln4A6tf1C5wAAAAAwUZZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVs5QCAAAAoHKNZrPZrHLgwMBAent7k0ZyyNwqJ7c8vTlpDieNGcnBc6qfL4MMpWWoe36SbN2UpJn09/enp6ennhCpv5+SMo5H3Rnqni+DDCOV0FH6SYZS5stQVgb91FLCsZBBhlLml5JhrP1U31IKYIRillIAoyjiL30Ao9BPQKn21U9dFWbZnTOlZJChiAx1z092btGL4V/6Ov53UgYZdlVUR+mnjs9Q93wZysqgn1pKOBYyyFDK/FIyjLWfaltKHXxUsuyR6udePy/Z+mjrwNQxXwYZSstQ9/wkuW5uqzhLUVc/JWUcj7oz1D1fBhlGKqmj9JMMdc+XoawM+qmlhGMhgwylzC8lw1j7yQudAwAAAFA5SykAAAAAKmcpBQAAAEDlLKUAAAAAqFx9777HtHVo5udVuSBH5vg8J7Pz33kqj2d97siaPJG+KZ+/ZWOybk3Svz555qnkgNlJ7/HJwguSWQumfDxQsLr7KdFRwOj0E1Aq/USdLKUYs+NzRs7OB3JylqSZ4STJjMzI8P98vCSX5sF8LbfmiqzP9yZ9/qa1yYNXJBtvar21ZZI0h5LGzNbH912aHL0kWXRJMueMSR8PFKzufkp0FDA6/QSUSj9RAk/fY0zOzgdySdbmpCzOjMzIzHRlZrrS2OXjGZmRk/OmXJLb8/pcPGmzm83kgcuTm85M+m5O0mwVVXPof76//eNmsvHm5GuvaRVbszlpEYCC1dlPiY4C9kw/AaXST5TCUop9en0uzv/K5UmSmTlgr9fd/v3zcsWkFddDVyZ3fbD1cXPb3q+7/ft3XtK6HbB/q7ufEh0FjE4/AaXST5RkQkupT3ziE2k0Gnn/+98/SXEozfE5I+flinHd9rxckePz6gnN37S2VT7jceclyebbJzSeaUw/7f/q7qdERzE++mn/p5+YznTU/k0/UZpxL6Xuueee/M3f/E0WLVo0mXkozNn5QIbyzLhuO5RnJrxNf/CKpDHOVz5rdLVuT+fRT52h7n5KdBTt00+dQT8xXemo/Z9+ojTjWkpt2bIly5Yty2c/+9kceuihk52JQhya+Tk5S/Z5SueezMwBWZQ359DMG9ftt2xsveDdvk7n3JPmtuTnX0u2VPOGERRCP3WGuvsp0VG0Tz91Bv3EdKWj9n/6iRKNaym1fPnynHPOOXn9618/2XkoyKtywY53YRivZobzqlw4rtuuW7PzHRjGqzEjWXfNxH4G04t+6gx191Oio2iffuoM+onpSkft//QTJWr7pLkvfOEL+cEPfpB77rlnTNcfHBzM4ODgjs8HBgbaHUlNjszxk/BTmjkix43rlv3rJ2F8koENk/NzKJ9+6hx191Oio2iPfuoc+onpqJ2O0k/Tl36iRG3tKPv6+vK+970v119/fZ7znOeM6TYrV65Mb2/vjsv8+fPHFZTqPSezM2OCb9A4IzNzUHrGddtnntr5lqDj1RxKfuW/kx1BP3WWuvsp0VGMnX7qLPqJ6abdjtJP05d+okRt/Ubed999efzxx/PSl740XV1d6erqytq1a/N//+//TVdXV4aGnv3btWLFivT39++49PV58ud08d95KsMTPL1zOEP5ZcbXGAfMThozJzQ+jZnJgePvTKYR/dRZ6u6nREcxdvqps+gnppt2O0o/TV/6iRK19fS9173udXnooYd2+9qFF16YE044IX/yJ3+SmTOf/dvV3d2d7u7uiaWkFo9nMs6tbOQXGd+5lb2TcXZpkp7xn13KNKKfOkvd/ZToKMZOP3UW/cR0025H6afpSz9RoraWUrNnz85JJ52029cOOeSQHH744c/6OtPfHVmTJbl0Qj+jkRm5I+N7FbqFFyT3TWx8msPJwvG/Dh/TiH7qLHX3U6KjGDv91Fn0E9ONjuoc+okSTfB179mfPZG+PJSbMpRnxnX7oTyTB/PVPJFHxnX7WQuSBUuSRtsvx9/S6EqOXprM8jR32O/U3U+JjgJGp5+AUuknSjTOX4WdbrvttkmIQam+lctzSt48rtvOyMzcmisnNP+US5KNXxvfbZtDyaIPTGg805x+2r/V3U+JjmL89NP+TT8x3emo/Zd+ojTOlGKv1ud7+XLGd6//h3ww6/O9Cc2fc0Zy2uXju+1pn2rdHtg/1d1PiY4CRqefgFLpJ0pjKcU+3ZordxTXvk713P79L+cDk7JFT5KTL95ZWvs6zXP790+7vHU7YP9Wdz8lOgoYnX4CSqWfKImlFGNya67M5TkjD+XrGc5whrItQ9mWZoYzlGcylG0ZznAeytdzec6Y1MJqNFqnaC5dmyx4U5JG621At7+V6I6PG63vL13bun6jMWkRgILV2U+JjgL2TD8BpdJPlGLCrylF51if72V9vpdDMy+vyoU5IsfloPTklxnIL7Ihd+SaCb3o3b7MOaN12dKXrLsmGdiQ/GogObCn9ZagCy/0gnfQqerup0RHAaPTT0Cp9BMlsJSibU/kkXw9H6tt/qz5yakfqW08ULC6+ynRUcDo9BNQKv1EnTx9DwAAAIDKWUoBAAAAUDlLKQAAAAAq12g2m80qBw4MDKS3tzdpJIfMrXJyy9Obk+Zw0piRHDyn+vkyyFBahrrnJ8nWTUmaSX9/f3p6euoJkfr7KSnjeNSdoe75MsgwUgkdpZ9kKGW+DGVl0E8tJRwLGWQoZX4pGcbaT/UtpQBGKGYpBTCKIv7SBzAK/QSUal/9VN+77zlTSgYZishQ9/xk5xa9GP6lr+N/J2WQYVdFdZR+6vgMdc+XoawM+qmlhGMhgwylzC8lw1j7qbal1MFHJcseqX7u9fOSrY+2Dkwd82WQobQMdc9PkuvmtoqzFHX1U1LG8ag7Q93zZZBhpJI6Sj/JUPd8GcrKoJ9aSjgWMshQyvxSMoy1n7zQOQAAAACVs5QCAAAAoHKWUgAAAABUzlIKAAAAgMrV9+57TFtbNibr1iT965NnnkoOmJ30Hp8svCCZtWD/n19KBuDZSrhvlpABKE8J3VBCBqA8JXSDDJ3LUoox27Q2efCKZONNrbeWTJLmUNKY2fr4vkuTo5ckiy5J5pyx/80vJQPwbCXcN0vIAJSnhG4oIQNQnhK6QQY8fY99ajaTBy5Pbjoz6bs5SbN1J20O/c/3t3/cTDbenHztNa07dbO5f8wvJQPwbCXcN0vIAJSnhG4oIQNQnhK6QQa2s5Rinx66Mrnrg62Pm9v2ft3t37/zktbt9of5pWQAnq2E+2YJGYDylNANJWQAylNCN8jAdpZS7NWmta073njceUmy+fbpPb+UDMCzlXDfLCEDUJ4SuqGEDEB5SugGGdhVW0upSy+9NI1GY7fLCSecMFXZKMCDVySNcb7yWKOrdfvpPL+UDOybfuo8Jdw3S8jA9KCjOksJ3VBCBqYH/dRZSugGGdhV24fhxBNPzK233rrzB3R5rfT91ZaNrRd7yzifM9vclvz8a8mWvmTW/Ok3v5QMjJ1+6hwl3DdLyMD0oqM6QwndUEIGphf91BlK6AYZGKntp+91dXXlqKOO2nF53vOeNxW5KMC6NTvffWC8GjOSdddMz/mlZGDs9FPnKOG+WUIGphcd1RlK6IYSMjC96KfOUEI3yMBIbR+K9evXZ+7cuTn22GOzbNmybNy4ca/XHxwczMDAwG4Xpof+9ZPzcwY2TM/5pWRg7PRT5yjhvllCBqaXdjpKP01fJXRDCRmYXvRTZyihG2RgpLaWUr/xG7+RNWvW5JZbbsmqVavy7//+73n1q1+dp556ao+3WblyZXp7e3dc5s93ftt08cxTO98Oc7yaQ8mvxvnfqbrnl5KBsdFPnaWE+2YJGZg+2u0o/TR9ldANJWRg+tBPnaOEbpCBkdpaSi1evDjnnXdeFi1alN/8zd/M//t//y9PPvlkvvSlL+3xNitWrEh/f/+OS19f34RDU40DZieNmRP7GY2ZyYE903N+KRkYG/3UWUq4b5aQgemj3Y7ST9NXCd1QQgamD/3UOUroBhkYaUKvYPfc5z43v/Zrv5YNG/Z83lp3d3e6u7snMoaa9B4/OT+n57jpOb+UDIyPftq/lXDfLCED09e+Oko/TV8ldEMJGZi+9NP+q4RukIGRJvTyXlu2bMm//du/Zc6cOZOVh4IsvCBpDk/sZzSHk4UXTs/5pWRgfPTT/q2E+2YJGZi+dNT+q4RuKCED05d+2n+V0A0yMFJbS6lLLrkka9euzcMPP5w77rgjv/Vbv5WZM2fmbW9721Tlo0azFiQLliSNcZ5P1+hKjl46/rfJrHt+KRkYG/3UWUq4b5aQgelDR3WOErqhhAxMH/qpc5TQDTIwUltLqUceeSRve9vbsnDhwvz2b/92Dj/88Nx555054ogjpiofNTvlkqS5bXy3bQ4liz4wveeXkoF900+dp4T7ZgkZmB50VGcpoRtKyMD0oJ86SwndIAO7ams3+IUvfGGqclCoOWckp12e3HlJ+7c97VOt20/n+aVkYN/0U+cp4b5ZQgamBx3VWUrohhIyMD3op85SQjfIwK4m9JpSdIaTL27dYZN9n+K4/funXd663f4wv5QMwLOVcN8sIQNQnhK6oYQMQHlK6AYZ2M5Sin1qNFqnJy5dmyx4U5JG6y0wt7+N5o6PG63vL13bun6jsX/MLyUD8Gwl3DdLyACUp4RuKCEDUJ4SukEGthvnS3vRieac0bps6UvWXZMMbEh+NZAc2NN6O8yFF07ti73VPb+UDMCzlXDfLCEDUJ4SuqGEDEB5SugGGbCUom2z5ienfqRz55eSAXi2Eu6bJWQAylNCN5SQAShPCd0gQ+fy9D0AAAAAKmcpBQAAAEDlLKUAAAAAqJylFAAAAACVazSbzWaVAwcGBtLb25s0kkPmVjm55enNSXM4acxIDp5T/XwZZCgtQ93zk2TrpiTNpL+/Pz09PfWESP39lJRxPOrOUPd8GWQYqYSO0k8ylDJfhrIy6KeWEo6FDDKUMr+UDGPtp/qWUgAjFLOUAhhFEX/pAxiFfgJKta9+6qowy+6cKSWDDEVkqHt+snOLXgz/0tfxv5MyyLCrojpKP3V8hrrny1BWBv3UUsKxkEGGUuaXkmGs/VTbUurgo5Jlj1Q/9/p5ydZHWwemjvkyyFBahrrnJ8l1c1vFWYq6+ikp43jUnaHu+TLIMFJJHaWfZKh7vgxlZdBPLSUcCxlkKGV+KRnG2k9e6BwAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDl6nv3PQDYD23ZmKxbk/SvT555KjlgdtJ7fLLwgmTWgrrTAZ1MPwFQGkspAJgEm9YmD16RbLyp9fa7SdIcShozWx/fd2ly9JJk0SXJnDNqiwl0IP0EQKk8fQ8AJqDZTB64PLnpzKTv5iTN1l/2mkP/8/3tHzeTjTcnX3tN6y+HzWaNoYGOoJ8AKJ2lFABMwENXJnd9sPVxc9ver7v9+3de0rodwFTSTwCUru2l1KOPPpq3v/3tOfzww3PQQQfl5JNPzr333jsV2QDaop+o2qa1rb/AjcedlySbb5/cPJRNR1El/UQ79BNQl7ZeU+qJJ57I6aefnrPOOis333xzjjjiiKxfvz6HHnroVOUDGBP9RB0evCJpdO37DITRNLpat/f6LZ1BR1E1/cRY6SegTm0tpT75yU9m/vz5ueaaa3Z87Zhjjpn0UADt0k9UbcvG1osGZ5yvvdLclvz8a8mWvmTW/EmNRoF0FFXST7RDPwF1auvpe1/96lfzspe9LOedd16OPPLIvOQlL8lnP/vZqcoGMGb6iaqtW7PzXazGqzEjWXfNvq/H9KejqJJ+oh36CahTW/+5+tnPfpZVq1bl+OOPzze+8Y28853vzHvf+95ce+21e7zN4OBgBgYGdrsATDb9RNX610/OzxnYMDk/h7K121H6iYnQT7RDPwF1auvpe8PDw3nZy16Wyy67LEnykpe8JD/60Y/y13/91zn//PNHvc3KlSvz0Y9+dOJJAfZCP1G1Z57a+bbq49UcSn7lsXxHaLej9BMToZ9oh34C6tTWmVJz5szJi1/84t2+9uu//uvZuHHjHm+zYsWK9Pf377j09fWNLynAXugnqnbA7KQxc2I/ozEzObBncvJQtnY7Sj8xEfqJdugnoE5tnSl1+umnZ926dbt97ac//WmOPvroPd6mu7s73d3d40sHMEb6iar1Hj85P6fnuMn5OZSt3Y7ST0yEfqId+gmoU1tnSv3RH/1R7rzzzlx22WXZsGFDbrjhhvzt3/5tli9fPlX5AMZEP1G1hRckzeGJ/YzmcLLwwkmJQ+F0FFXST7RDPwF1amsp9fKXvzw33nhjPv/5z+ekk07Kxz72sVx11VVZtmzZVOUDGBP9RNVmLUgWLEkabZ1zvFOjKzl6qbdb7xQ6iirpJ9qhn4A6tf2fqiVLlmTJkiVTkQVgQvQTVTvlkmTj18Z32+ZQsugDk5uHsukoqqSfaId+AurS1plSAMBOc85ITrt8fLc97VOt2wNMBf0EwHRgKQUAE3DyxTv/4revp8ps//5pl7duBzCV9BMApbOUAoAJaDRaT3NZujZZ8KYkjdZbqW9/O/YdHzda31+6tnX9RqPO1EAn0E8AlG6cL38IAOxqzhmty5a+ZN01ycCG5FcDyYE9rbdVX3ihFw0G6qGfACiVpRQATKJZ85NTP1J3CoBn008AlMbT9wAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFSu0Ww2m1UOHBgYSG9vb9JIDplb5eSWpzcnzeGkMSM5eE7182WQobQMdc9Pkq2bkjST/v7+9PT01BMi9fdTUsbxqDtD3fNlkGGkEjpKP8lQynwZysqgn1pKOBYyyFDK/FIyjLWf6ltKAYxQzFIKYBRF/KUPYBT6CSjVvvqpq8Isu3OmlAwyFJGh7vnJzi16MfxLX8f/Tsogw66K6ij91PEZ6p4vQ1kZ9FNLCcdCBhlKmV9KhrH2U21LqYOPSpY9Uv3c6+clWx9tHZg65ssgQ2kZ6p6fJNfNbRVnKerqp6SM41F3hrrnyyDDSCV1lH6Soe75MpSVQT+1lHAsZJChlPmlZBhrP3mhcwAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFC5tpZSL3zhC9NoNJ51Wb58+VTlAxgzHQWUSj8BpdJPQJ262rnyPffck6GhoR2f/+hHP8rZZ5+d8847b9KDAbRLRwGl0k9AqfQTUKe2llJHHHHEbp9/4hOfyIte9KK85jWvmdRQAOOho4BS6SegVPoJqNO4X1PqV7/6Va677rpcdNFFaTQak5kJYMJ0FFAq/QSUSj8BVWvrTKldfeUrX8mTTz6ZCy64YK/XGxwczODg4I7PBwYGxjsSYMzG0lH6CaiDfgJKpZ+Aqo37TKnVq1dn8eLFmTt37l6vt3LlyvT29u64zJ8/f7wjAcZsLB2ln4A66CegVPoJqNq4llI///nPc+utt+b3f//393ndFStWpL+/f8elr69vPCMBxmysHaWfgKrpJ6BU+gmow7ievnfNNdfkyCOPzDnnnLPP63Z3d6e7u3s8YwDGZawdpZ+AquknoFT6CahD22dKDQ8P55prrsn555+frq5xvyQVwJTQUUCp9BNQKv0E1KXtpdStt96ajRs35qKLLpqKPAAToqOAUuknoFT6CahL22vwN7zhDWk2m1ORBWDCdBRQKv0ElEo/AXUZ97vvAQAAAMB4WUoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyjWazWazyoEDAwPp7e1NGskhc6uc3PL05qQ5nDRmJAfPqX6+DDKUlqHu+UmydVOSZtLf35+enp56QqT+fkrKOB51Z6h7vgwyjFRCR+knGUqZL0NZGfRTSwnHQgYZSplfSoax9lN9SymAEYpZSgGMooi/9AGMQj8BpdpXP3VVmGV3zpSSQYYiMtQ9P9m5RS+Gf+nr+N9JGWTYVVEdpZ86PkPd82UoK4N+ainhWMggQynzS8kw1n6qbSl18FHJskeqn3v9vGTro60DU8d8GWQoLUPd85Pkurmt4ixFXf2UlHE86s5Q93wZZBippI7STzLUPV+GsjLop5YSjoUMMpQyv5QMY+0nL3QOAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKtfWUmpoaCgf/vCHc8wxx+Sggw7Ki170onzsYx9Ls9mcqnwAY6KfgJLpKKBU+gmoU1c7V/7kJz+ZVatW5dprr82JJ56Ye++9NxdeeGF6e3vz3ve+d6oyAuyTfgJKpqOAUuknoE5tLaXuuOOOnHvuuTnnnHOSJC984Qvz+c9/PnffffeUhAMYK/0ElExHAaXST0Cd2nr63qte9ap8+9vfzk9/+tMkyQMPPJB//ud/zuLFi/d4m8HBwQwMDOx2AZhs+gkoWbsdpZ+AqugnoE5tnSn1oQ99KAMDAznhhBMyc+bMDA0N5eMf/3iWLVu2x9usXLkyH/3oRyccFGBv9BNQsnY7Sj8BVdFPQJ3aOlPqS1/6Uq6//vrccMMN+cEPfpBrr702l19+ea699to93mbFihXp7+/fcenr65twaICR9BNQsnY7Sj8BVdFPQJ3aOlPqgx/8YD70oQ/ld3/3d5MkJ598cn7+859n5cqVOf/880e9TXd3d7q7uyeeFGAv9BNQsnY7Sj8BVdFPQJ3aOlPq6aefzowZu99k5syZGR4entRQAO3ST0DJdBRQKv0E1KmtM6WWLl2aj3/841mwYEFOPPHE/PCHP8yVV16Ziy66aKryAYyJfgJKpqOAUuknoE5tLaX+6q/+Kh/+8Ifzrne9K48//njmzp2bP/iDP8hHPvKRqcoHMCb6CSiZjgJKpZ+AOrW1lJo9e3auuuqqXHXVVVMUB2B89BNQMh0FlEo/AXVq6zWlAAAAAGAyWEoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFSu0Ww2m1UO7O/vz3Of+9wkycFzqpzc8vRjSZpJGsnBR1U/XwYZSstQ9/wkeXpz63+ffPLJ9Pb21hMi9fdTUsjx8Dspgwy7Zyigo/STDKXMl6GwDPopSSHHQgYZCplfTIYx9lPlS6lHHnkk8+fPr3IkME309fVl3rx5tc3XT8De1NlR+gnYG/0ElGpf/VT5Ump4eDibNm3K7Nmz02g02r79wMBA5s+fn76+vvT09ExBQhmmS4a658sweRmazWaeeuqpzJ07NzNm1PesYv0kw/6Uoe75+1OGEjpqov2U1H886p4vgwylZdBPO9V9LErIUPd8GWSY7Axj7aeuiYQcjxkzZkzKFr+np6e2gyNDWRnqni/D5GSo82l72+knGfbHDHXP318y1N1Rk9VPSf3Ho+75MshQWgb9tFPdx6KEDHXPl0GGycwwln7yQucAAAAAVM5SCgAAAIDKTbulVHd3d/7sz/4s3d3dMnR4hrrny1BWhhKU8OcggwylzJehPHX/WdQ9XwYZSstQ9/ySlPBnUXeGuufLIENdGSp/oXMAAAAAmHZnSgEAAAAw/VlKAQAAAFA5SykAAAAAKmcpBQAAAEDlptVS6vvf/35mzpyZc845p/LZF1xwQRqNxo7L4Ycfnje+8Y158MEHK8/y2GOP5T3veU+OPfbYdHd3Z/78+Vm6dGm+/e1vT/nsXf8cDjjggDz/+c/P2Wefnc997nMZHh6e8vkjM+x6eeMb31jJ/H3l2LBhQyXzH3vssbzvfe/Lcccdl+c85zl5/vOfn9NPPz2rVq3K008/PeXzL7jggrzlLW951tdvu+22NBqNPPnkk1OeoTQ6Sj+NzFFXR9XdT0m9HaWfnk0/6aeROfSTx1Cl0E/6aWQO/dRZ/TStllKrV6/Oe97zntx+++3ZtGlT5fPf+MY3ZvPmzdm8eXO+/e1vp6urK0uWLKk0w8MPP5xTTz013/nOd/KpT30qDz30UG655ZacddZZWb58eSUZtv85PPzww7n55ptz1lln5X3ve1+WLFmSbdu2VZph18vnP//5SmbvK8cxxxwz5XN/9rOf5SUveUm++c1v5rLLLssPf/jDfP/7388f//Ef56abbsqtt9465Rl4tk7vKP307Bx1dlRd/ZToqBLpJ/00Mod+0k+l0E/6aWQO/dRZ/dRVd4Cx2rJlS774xS/m3nvvzWOPPZY1a9bkT//0TyvN0N3dnaOOOipJctRRR+VDH/pQXv3qV+cXv/hFjjjiiEoyvOtd70qj0cjdd9+dQw45ZMfXTzzxxFx00UWVZNj1z+EFL3hBXvrSl+a0007L6173uqxZsya///u/X2mGOtWV413vele6urpy77337vZ7cOyxx+bcc89Ns9msPFOn01H6aU856lJnBh1VFv2kn/aUoy76ie30k37aU4666KfqTZszpb70pS/lhBNOyMKFC/P2t789n/vc52o9KFu2bMl1112X4447LocffnglM//rv/4rt9xyS5YvX77bL+l2z33ucyvJMZrXvva1OeWUU/KP//iPtWXoFP/5n/+Zb37zm3v8PUiSRqNRcSo6vaP0E9vpqPLoJ/1Ei34qj37ST7R0cj9Nm6XU6tWr8/a3vz1J65S6/v7+rF27ttIMN910U2bNmpVZs2Zl9uzZ+epXv5ovfvGLmTGjmj/GDRs2pNls5oQTTqhkXrtOOOGEPPzww5XM2vVYbL9cdtlllczeW47zzjtvymdu/z1YuHDhbl9/3vOetyPHn/zJn0x5jmT047B48eJKZpem0ztKP+2uhI6qo5+ScjpKP+2kn/TTrvRT/f2U6Kjt9JN+2pV+6sx+mhZP31u3bl3uvvvu3HjjjUmSrq6u/M7v/E5Wr16dM888s7IcZ511VlatWpUkeeKJJ/KZz3wmixcvzt13352jjz56yueXfrpes9msbHu767HY7rDDDqtk9t5y7GmrXYW77747w8PDWbZsWQYHByuZOdpxuOuuu3Y8uOgUOko/jVRCR5XUT0n1HaWfWvSTfhpJPz2bx1D10E/6aST99Gyd0E/TYim1evXqbNu2LXPnzt3xtWazme7u7lx99dXp7e2tJMchhxyS4447bsfnf/d3f5fe3t589rOfzV/8xV9M+fzjjz8+jUYjP/nJT6Z81nj8+Mc/ruxF4EYei7rUkeO4445Lo9HIunXrdvv6sccemyQ56KCDKssy2v//Rx55pLL5pdBR+mmkEjqqrgyldJR+atFP+mkk/VR/PyU6KtFPiX4aST91Zj8V//S9bdu25e///u9zxRVX5P77799xeeCBBzJ37txa3nFtu0ajkRkzZuSXv/xlJfMOO+yw/OZv/mY+/elPZ+vWrc/6fp1vH/ud73wnDz30UN761rfWlqFTHH744Tn77LNz9dVXj/p7QLV0VIt+YjsdVQ791KKf2E4/lUM/tegntuvkfir+TKmbbropTzzxRH7v937vWdvyt771rVm9enX+8A//sJIsg4ODeeyxx5K0Tu28+uqrs2XLlixdurSS+Uny6U9/Oqeffnpe8YpX5M///M+zaNGibNu2Ld/61reyatWq/PjHP57yDNv/HIaGhvIf//EfueWWW7Jy5cosWbIk73jHO6Z8/q4ZdtXV1ZXnPe95lcyv22c+85mcfvrpednLXpZLL700ixYtyowZM3LPPffkJz/5SU499dS6I3YMHbWTfnp2jl3pKB1VNf20k356do5d6Sf9VDX9tJN+enaOXemnDuinZuGWLFnSfNOb3jTq9+66665mkuYDDzww5TnOP//8ZpIdl9mzZzdf/vKXN//hH/5hymePtGnTpuby5cubRx99dPPAAw9svuAFL2i++c1vbn73u9+d8tm7/jl0dXU1jzjiiObrX//65uc+97nm0NDQlM8fmWHXy8KFCyuZv2uOc889t9KZu9q0aVPz3e9+d/OYY45pHnDAAc1Zs2Y1X/GKVzQ/9alPNbdu3Trl8/f0//+73/1uM0nziSeemPIMJdBRu+v0fhqZo66Oqrufms16O0o/tein3ekn/bSdx1D100+700/6abtO7KdGs1n4q6sBAAAAsN8p/jWlAAAAANj/WEoBAAAAUDlLKQAAAAAqZykFAAAAQOUspQAAAAConKUUAAAAAJWzlAIAAACgcpZSAAAAAFTOUgoAAACAyllKAQAAAFA5SykAAAAAKmcpBQAAAEDl/n/5yCv6wQ736AAAAABJRU5ErkJggg==\n", 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" ] @@ -1135,7 +1146,7 @@ "outputs": [ { "data": { - "image/png": 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krgfOgSW7tHloY2qil/INfv0xrZ80d0lJbEohB54X3Ka5ol2ae50kL/go0MGPEx167gVfX9EefL/nuUw9+TAPwKlYFzYwDxiJ6yHAebCDucBIXA+cA2t2abNa1aQDelJZZZXRgDIakK+sMupXRgPKKqsDelKtappUG1KSFPItzpBEtU3Bo7dLOrhNSh+S3kpLZ1UHHwvauIY3vYsC8wCcinVhA/OAkbgeApwHO5gLjMT1wDmwpEN71KE9mq45WqI1mqn5mqpqvaG0XtMh7dW2SfGm5uNhUwp5q6yXLrvNdQowD8CpWBc2MA8YieshwHmwg7nASFwPnANLjuuwntSdrmNEipfvAQAAAAAAIHJsSgEAAAAAACBybEoBAAAAAAAgcmxKAQAAAAAAIHJsSgEAAAAAACBynu/7fpQDptNp1dTUSJ50Tl2UIwdePyL5WclLSdNqox+fDGSwlsH1+JJ0sluSL/X09Ki6utpNCLnvJ8nGfLjO4Hp8MpBhLAsdRT+Rwcr4ZLCVgX4KWJgLMpDByvhWMuTaT+42pQBgDDObUgAwDhN/6QOAcdBPAKyaqJ/KI8wyGndKkYEMJjK4Hl8a3kU3g3/pS/w1SQYyjGSqo+inxGdwPT4ZbGWgnwIW5oIMZLAyvpUMufaTs02pabOlVYejH/fBOdLJV4OJcTE+GchgLYPr8SXpgbqgOK1w1U+SjflwneH/s3f/QVZe933H33d30eoHu2usSBGEhcgGo0YCjSzbkdEYy7FwjQx2OjFtM3hi5CRtY5w4Fag1nYkr17VxRsA4Uztq68rgjmTLlqfOWGjkRNgxkCH6mUiQxiFLU4nFoErT4l1AEoJ7n/7x6O4uK2D33rv3Od+79/2a2fFKu8+ej89zzkfS4dl7U49vBjOMF6mj7CczpB7fDLEy2E+5CPfCDGaIMn6UDJPtJ1/oXJIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYVL9+57alknDsGB7TA0AKePw4we6FsIi9bCzHmp00lqZ/aTpKjsJ0lR2U8aaxb9LGUtV7KQi+nhVY7zIgPsZTvHGJzy8TyU0qQd2QX7tsChHflbSwJkZSh15p8/fRfMXwlLNsDsZcliSmpD9pOkqOwnSVHZTxprIctYznoWs5KMCgAddFB5/fOV3MU+HmInWxhgz5SN66/vaUJZBs9uhh23wOAjQJaXVVZ+/evVzzM49Ag89N683LIsYWhJbcF+khSV/SQpKvtJ4y1nPRvYxXWsoIMOOumiky5KYz7voIPF3MYGdnMrd0zZ2B5KaUL7t8Ljd+afZ2cu/L3Vrz+2Ib9OkprJfpIUlf0kKSr7SWPdyh18lM0AdDLjgt9b/fpqtkzZwVRNh1K/+Iu/SKlUesPHunXrpiSM4jmyKy+gejy2AY7unto80oXYUe3FflIrsZ/ai/2kVmI/tRf7SWMtZBmr2VLXtavZwkLe03CGmg6lnnzySY4ePTry8eijj+ZhVq9uOIhi2rcFSnW+8lipK79eKood1V7sJ7US+6m92E9qJfZTe7GfNNZy1lPmdF3Xljk9JU9L1bQcr7jiirP++ktf+hJvfetbee9739twEMVz4lD+onfU+bvD2Rl4/iE4MQgz+6c0mnROdlT7sJ/Uauyn9mE/qdXYT+3DftJYs+hnMSvpqPNVnTqZwRI+zCzmcozDdeeo+zWlXnvtNe677z4+8YlPUCqV6g6guA5sH30XhnqVOuDAtimJI9XEjpre7Ce1MvtperOf1Mrsp+nNftJYS1k78i579cqosJTbG/oZdT64B3/yJ3/Cz372M9auXXvB7zt16hSnTp0a+evh4eF6h1TBhgam5ucMH5yanyPVYjIdZT+1LvtJrcx+mt7sJ7Uy+2l6s5801pUsnIKfknEFCxr6CXWfk957772sWLGCOXPmXPD7Nm3aRF9f38hHf7/P+bWK08dH3xa0XlkZXvOfU0pgMh1lP7Uu+0mtzH6a3uwntTL7aXqznzTWxfTU/at7VR10cgm9Df6MOjz//PPs3LmT3/qt35rwezdu3MjQ0NDIx+DgYD1DKoEZPVDqbOxnlDrhosbWqFSzyXaU/dS67Ce1Kvtp+rOf1Krsp+nPftJYr3KcSoO/vlehzCs0dkpZ16/vbdu2jSuvvJIPfehDE35vd3c33d3d9QyjxPqm4mk+oLexp/mkmk22o+yn1mU/qVXZT9Of/aRWZT9Nf/aTxnqRqfh9zhIv0djvc9b8pFSlUmHbtm18/OMfp6ur7pekUgtYtBayxg5OySqwqLHXPZNqYke1B/tJrch+ag/2k1qR/dQe7CeNtZftlBr89b0SHeylsVe+rznBzp07OXToEJ/4xCcaGljxzZwH81ZCqc5/LpW6YP4q3y5UxbKj2oP9pFZkP7UH+0mtyH5qD/aTxjrGIPvZQZnTdV1f5jT7+D7HONxQjpoPpT7wgQ+QZRlve9vbGhpYreH6DZCdqe/arAxL1k9tHmkidlT7sJ/Uauyn9mE/qdXYT+3DftJYj7KZTmbUdW0Hnexka8MZGntWS9Pe7GVw0+b6rr3p7vx6SWoG+0lSVPaTpKjsJ401wB4epL6Txu9yJwPsaTiDh1Ka0OI7Rotrokc9q1+/aXN+nSQ1k/0kKSr7SVJU9pPG2snWkYOpiX6Vr/r1B1k/JU9JgYdSmoRSKX9Mc9UumHcbUMrfCrT6dqIjn5fyr6/alX9/qZQytaR2YD9Jisp+khSV/aTxdrKVzSxjPw9ToUKZM5Q5Q0aFMqcpc4YKFfbzMJtZNmUHUgC+tYImbfay/OPEIBzYBsMH4bVhuKg3f1vQRbf7oneS0rCfJEVlP0mKyn7SWAPsYYA9zGIuS7mdK1jAJfTyCsO8xEH2sq3hFzU/Fw+lVLOZ/XDjZ1OnkKQ3sp8kRWU/SYrKftJYxzjMw3y+sPH89T1JkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVrpRlWVbkgMPDw/T19UEJLptT5Mi5l49CVoFSB1w6u/jxzWCGaBlSjw9w8giQwdDQEL29vWlCkL6fIMb9SJ0h9fhmMMN4ETrKfjJDlPHNECuD/ZSLcC/MYIYo40fJMNl+SncoJUnjhDmUkqRzCPEffZJ0DvaTpKgm6qeuArOczSelzGCGEBlSjw+jp+hh+Cd9bb8mzWCGsUJ1lP3U9hlSj2+GWBnsp1yEe2EGM0QZP0qGyfZTskOpS6+CNYeLH/f+uXDyp/mNSTG+GcwQLUPq8QHum5MXZxSp+gli3I/UGVKPbwYzjBepo+wnM6Qe3wyxMthPuQj3wgxmiDJ+lAyT7Sdf6FySJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYWr6VCqXC7zB3/wB1x99dVccsklvPWtb+Xzn/88WZY1K58kTYr9JCkyO0pSVPaTpJS6avnmP/zDP+See+7hG9/4Btdeey1PPfUUt99+O319ffze7/1eszJK0oTsJ0mR2VGSorKfJKVU06HU3r17+chHPsKHPvQhAH7xF3+Rb33rWzzxxBNNCSdJk2U/SYrMjpIUlf0kKaWafn1v6dKl/PCHP+Tv//7vAXj22Wf5i7/4C1asWHHea06dOsXw8PBZH5I01ewnSZHV2lH2k6Si2E+SUqrpSanPfOYzDA8Pc80119DZ2Um5XOYLX/gCa9asOe81mzZt4nOf+1zDQSXpQuwnSZHV2lH2k6Si2E+SUqrpSanvfOc73H///Xzzm9/kr/7qr/jGN77B5s2b+cY3vnHeazZu3MjQ0NDIx+DgYMOhJWk8+0lSZLV2lP0kqSj2k6SUanpS6s477+Qzn/kM//yf/3MAFi9ezPPPP8+mTZv4+Mc/fs5ruru76e7ubjypJF2A/SQpslo7yn6SVBT7SVJKNT0p9fLLL9PRcfYlnZ2dVCqVKQ0lSbWynyRFZkdJisp+kpRSTU9KrVq1ii984QvMmzePa6+9lr/+679m69atfOITn2hWPkmaFPtJUmR2lKSo7CdJKdV0KPWf/tN/4g/+4A/45Cc/yYsvvsicOXP4l//yX/LZz362WfkkaVLsJ0mR2VGSorKfJKVU06FUT08PX/7yl/nyl7/cpDiSVB/7SVJkdpSkqOwnSSnV9JpSkiRJkiRJ0lTwUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhStlWZYVOeDQ0BBvetObALh0dpEj515+AciAElx6VfHjm8EM0TKkHh/g5aP5//7sZz+jr68vTQjS9xMEuR+uSTOY4ewMATrKfjJDlPHNECyD/QQEuRdmMEOQ8cNkmGQ/FX4odfjwYfr7+4scUlKLGBwcZO7cucnGt58kXUjKjrKfJF2I/SQpqon6qfBDqUqlwpEjR+jp6aFUKtV8/fDwMP39/QwODtLb29uEhGZolQypxzfD1GXIsozjx48zZ84cOjrS/Vax/WSG6ZQh9fjTKUOEjmq0nyD9/Ug9vhnMEC2D/TQq9b2IkCH1+GYww1RnmGw/dTUSsh4dHR1Tcorf29ub7OaYIVaG1OObYWoypPy1vSr7yQzTMUPq8adLhtQdNVX9BOnvR+rxzWCGaBnsp1Gp70WEDKnHN4MZpjLDZPrJFzqXJEmSJElS4TyUkiRJkiRJUuFa7lCqu7ubf//v/z3d3d1maPMMqcc3Q6wMEUSYBzOYIcr4Zogn9VykHt8MZoiWIfX4kUSYi9QZUo9vBjOkylD4C51LkiRJkiRJLfeklCRJkiRJklqfh1KSJEmSJEkqnIdSkiRJkiRJKlxLHUr95V/+JZ2dnXzoQx8qfOy1a9dSKpVGPi6//HI++MEPsm/fvsKzvPDCC/zu7/4ub3nLW+ju7qa/v59Vq1bxwx/+sOljj52HGTNm8PM///MsX76cr3/961QqlaaPPz7D2I8PfvCDhYw/UY6DBw8WMv4LL7zApz/9aRYsWMDFF1/Mz//8z3PzzTdzzz338PLLLzd9/LVr1/Krv/qrb/j7P/7xjymVSvzsZz9reoZo7Cj7aXyOVB2Vup8gbUfZT29kP9lP43PYT/47VBT2k/00Pof91F791FKHUvfeey+/+7u/y+7duzly5Ejh43/wgx/k6NGjHD16lB/+8Id0dXWxcuXKQjM899xz3HjjjfzoRz/i7rvvZv/+/fzgBz/gfe97H+vWrSskQ3UennvuOR555BHe97738elPf5qVK1dy5syZQjOM/fjWt75VyNgT5bj66qubPu4//MM/cMMNN/Bnf/ZnfPGLX+Sv//qv+cu//Ev+zb/5N+zYsYOdO3c2PYPeqN07yn56Y46UHZWqn8COish+sp/G57Cf7Kco7Cf7aXwO+6m9+qkrdYDJOnHiBN/+9rd56qmneOGFF9i+fTv/7t/9u0IzdHd3c9VVVwFw1VVX8ZnPfIb3vOc9vPTSS1xxxRWFZPjkJz9JqVTiiSee4LLLLhv5+9deey2f+MQnCskwdh5+4Rd+gbe//e3cdNNNvP/972f79u381m/9VqEZUkqV45Of/CRdXV089dRTZ62Dt7zlLXzkIx/BN9Usnh1lP50vRyopM9hRsdhP9tP5cqRiP6nKfrKfzpcjFfupeC3zpNR3vvMdrrnmGhYtWsTHPvYxvv71rye9KSdOnOC+++5jwYIFXH755YWM+f/+3//jBz/4AevWrTtrkVa96U1vKiTHufzKr/wK119/Pf/jf/yPZBnaxf/9v/+XP/uzPzvvOgAolUoFp1K7d5T9pCo7Kh77yX5Szn6Kx36yn5Rr535qmUOpe++9l4997GNA/kjd0NAQu3btKjTDjh07mDlzJjNnzqSnp4fvf//7fPvb36ajo5hpPHjwIFmWcc011xQyXq2uueYannvuuULGGnsvqh9f/OIXCxn7QjlWr17d9DGr62DRokVn/f2f+7mfG8nxb//tv216Djj3fVixYkUhY0fT7h1lP50tQkel6CeI01H20yj7yX4ay35K309gR1XZT/bTWPZTe/ZTS/z63oEDB3jiiSf43ve+B0BXVxf/7J/9M+69915uueWWwnK8733v45577gHg2LFj/PEf/zErVqzgiSeeYP78+U0fP/rjelmWFXZ6O/ZeVL35zW8uZOwL5TjfqXYRnnjiCSqVCmvWrOHUqVOFjHmu+/D444+P/MtFu7Cj7KfxInRUpH6C4jvKfsrZT/bTePbTG/nvUGnYT/bTePbTG7VDP7XEodS9997LmTNnmDNnzsjfy7KM7u5uvvKVr9DX11dIjssuu4wFCxaM/PV/+2//jb6+Pr72ta/xH//jf2z6+AsXLqRUKvF3f/d3TR+rHj/5yU8KexG48fcilRQ5FixYQKlU4sCBA2f9/be85S0AXHLJJYVlOdf//8OHDxc2fhR2lP00XoSOSpUhSkfZTzn7yX4az35K309gR4H9BPbTePZTe/ZT+F/fO3PmDP/9v/93tmzZwjPPPDPy8eyzzzJnzpwk77hWVSqV6Ojo4JVXXilkvDe/+c3843/8j/nqV7/KyZMn3/D1lG8f+6Mf/Yj9+/fza7/2a8kytIvLL7+c5cuX85WvfOWc60DFsqNy9pOq7Kg47Kec/aQq+ykO+ylnP6mqnfsp/JNSO3bs4NixY/zmb/7mG07Lf+3Xfo17772Xf/Wv/lUhWU6dOsULL7wA5I92fuUrX+HEiROsWrWqkPEBvvrVr3LzzTfzrne9i//wH/4DS5Ys4cyZMzz66KPcc889/OQnP2l6huo8lMtl/s//+T/84Ac/YNOmTaxcuZLf+I3faPr4YzOM1dXVxc/93M8VMn5qf/zHf8zNN9/MO97xDu666y6WLFlCR0cHTz75JH/3d3/HjTfemDpi27CjRtlPb8wxlh1lRxXNfhplP70xx1j2k/1UNPtplP30xhxj2U9t0E9ZcCtXrsxuu+22c37t8ccfz4Ds2WefbXqOj3/84xkw8tHT05O9853vzL773e82fezxjhw5kq1bty6bP39+dtFFF2W/8Au/kH34wx/O/vzP/7zpY4+dh66uruyKK67Ibr311uzrX/96Vi6Xmz7++AxjPxYtWlTI+GNzfOQjHyl0zLGOHDmSfepTn8quvvrqbMaMGdnMmTOzd73rXdndd9+dnTx5sunjn+///5//+Z9nQHbs2LGmZ4jAjjpbu/fT+BypOip1P2VZ2o6yn3L209nsJ/upyn+HSs9+Opv9ZD9VtWM/lbIs+KurSZIkSZIkadoJ/5pSkiRJkiRJmn48lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuG6ih6wUqlw5MgRenp6KJVKRQ8vKaAsyzh+/Dhz5syhoyPdWbn9JOlcInSU/STpXOwnSVFNtp8KP5Q6cuQI/f39RQ8rqQUMDg4yd+7cZOPbT5IuJGVH2U+SLsR+khTVRP1U+KFUT0/PyOeXzi56dHj5BSADSnDpVcWPbwYzRMuQenyAl4/m/zu2H1JI3U8Q5H64Js1ghrMzBOgo+8kMUcY3Q7AM9hMQ5F6YwQxBxg+TYZL9VPihVPWRzktnw8eOFD063D8XTv4ULpsDaw4XP74ZzBAtQ+rxAe6bk5dW6ke+U/cTxLgfqTOkHt8MZhgvQkfZT2aIMr4ZYmWwn3IR7oUZzBBl/CgZJttPvtC5JEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgpX+LvvSY06cQgObIehATh9HGb0QN9CWLQWZs5LnU5Su0vdUbPoZylruZKFXEwPr3KcFxlgL9s5xmDzA0gKK3U/gR0l6dzsp/bloZRaxpFdsG8LHNoBpdef8cvKUOrMP3/6Lpi/EpZsgNnLksWU1KZSd9RClrGc9SxmJRkVADrooPL65yu5i308xE62MMCeqQ8gKazU/QR2lKRzs5/kr+8pvCyDZzfDjltg8BEgy4sqK7/+9ernGRx6BB56b15sWZYwtKS2EaGjlrOeDeziOlbQQQeddNFJF6Uxn3fQwWJuYwO7uZU7pm5wSWFF6CewoyS9kf2kKg+lFN7+rfD4nfnn2ZkLf2/1649tyK+TpGZL3VG3cgcfZTMAncy44PdWv76aLf5LldQGUvcT2FGSzs1+UlXNh1K7d+9m1apVzJkzh1KpxJ/8yZ80IZaUO7IrL596PLYBju6e2jyKzX5S0VJ31EKWsZotdV27mi0s5D2NBdCk2U8qWup+AjuqVdhPKpr9pLFqPpQ6efIk119/PV/96lebkUc6y74tUKrzlc9KXfn1ah/2k4qWuqOWs54yp+u6tsxp/6SvQPaTipa6n8COahX2k4pmP2msmpfCihUrWLFiRTOySGc5cSh/wTvq/L3h7Aw8/xCcGISZ/VMaTUHZTypS6o6aRT+LWUlHnb+J38kMlvBhZjGXYxyu62do8uwnFSl1P4Ed1UrsJxXJftJ4vqaUwjqwffQdGOpV6oAD26YkjiSdJXVHLWXtyDvE1CujwlJub+hnSIondT+BHSXp3OwnjVfnQ3OTd+rUKU6dOjXy18PDw80eUtPE0MDU/Jzhg1PzczT92E9qROqOupKFUzB6xhUsmIKfo6lmP6kRqfsJ7KjpzH5SI+wnjdf0J6U2bdpEX1/fyEd/v79Hpck5fXz0LUHrlZXhNf85qfOwn9SI1B11MT11P3Ze1UEnl9Db0M9Qc9hPakTqfgI7ajqzn9QI+0njNf1QauPGjQwNDY18DA4ONntITRMzeqDU2djPKHXCRXaFzsN+UiNSd9SrHKfS4KPnFcq8gif3EdlPakTqfgI7ajqzn9QI+0njNf3X97q7u+nu7m72MJqG+qbiqUqg16cqdR72kxqRuqNeZCqefy/xEv6Oc0T2kxqRup/AjprO7Cc1wn7SeDU/KXXixAmeeeYZnnnmGQD+9//+3zzzzDMcOnRoqrOpzS1aC1ljB9hkFVjk68+1DftJRUrdUXvZTqnBB55LdLAX3w2iCPaTipS6n8COaiX2k4pkP2m8mu/EU089xQ033MANN9wAwB133MENN9zAZz/72SkPp/Y2cx7MWwmlOp/nK3XB/FX1v1WoWo/9pCKl7qhjDLKfHZQ5Xdf1ZU6zj+/7VsYFsZ9UpNT9BHZUK7GfVCT7SePVvBRuueUWsixrRhbpDa7fAIcequ/arAxL1k9tHsVmP6loqTvqUTZzPR+u69oOOtnJ1sYCaNLsJxUtdT+BHdUq7CcVzX7SWE1/oXOpEbOXwU2b67v2prvz6yWpWVJ31AB7eJD6/s3su9zJAHsaCyAprNT9BHaUpHOznzSWh1IKb/Edo6U10WOe1a/ftDm/TpKaLXVH7WTryL9UTfQYevXrD7LeP+GT2kDqfgI7StK52U+q8lBK4ZVK+SOaq3bBvNuAUv42oNW3Eh35vJR/fdWu/PtLpZSpJbWLCB21k61sZhn7eZgKFcqcocwZMiqUOU2ZM1SosJ+H2cwy/2VKahMR+gnsKElvZD+pqs6XF5OKN3tZ/nFiEA5sg+GD8NowXNSbvyXoott9UXNJ6aTuqAH2MMAeZjGXpdzOFSzgEnp5hWFe4iB72eYLckptKnU/gR0l6dzsJ3kopZYzsx9u9M1AJAWVuqOOcZiH+Xy6AJLCSt1PYEdJOjf7qX3563uSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXCnLsqzIAYeHh+nr64MSXDanyJFzLx+FrAKlDrh0dvHjm8EM0TKkHh/g5BEgg6GhIXp7e9OEIH0/QYz7kTpD6vHNYIbxInSU/WSGKOObIVYG+ykX4V6YwQxRxo+SYbL9lO5QSpLGCXMoJUnnEOI/+iTpHOwnSVFN1E9dBWY5m09KmcEMITKkHh9GT9HD8E/62n5NmsEMY4XqKPup7TOkHt8MsTLYT7kI98IMZogyfpQMk+2nZIdSl14Faw4XP+79c+HkT/Mbk2J8M5ghWobU4wPcNycvzihS9RPEuB+pM6Qe3wxmGC9SR9lPZkg9vhliZbCfchHuhRnMEGX8KBkm20++0LkkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKl+7d91SXE4fgwHYYGoDTx2FGD/QthEVrYea89siQevwoGWbRz1LWciULuZgeXuU4LzLAXrZzjMFiQkhjRNgXZojRDREySGOl3pdmGBWhHyJkkKoi7Esz5CJ0Q4QMRfNQqkUc2QX7tsChHfnbOgJkZSh15p8/fRfMXwlLNsDsZdMzQ+rxo2RYyDKWs57FrCSjAkAHHVRe/3wld7GPh9jJFgbY05wQ0hgR9oUZYnRDhAzSWKn3pRlGReiHCBmkqgj70gy5CN0QIUMq/vpecFkGz26GHbfA4CNAlm/SrPz616ufZ3DoEXjovfmmzrLpkyH1+FEyACxnPRvYxXWsoIMOOumiky5KYz7voIPF3MYGdnMrd0xtAGmMCPvCDLkI3RAhg1QVYV+aYVSEfoiQQYIY+9IMoyJ0Q4QMKXkoFdz+rfD4nfnn2ZkLf2/1649tyK+bLhlSjx8lw63cwUfZDEAnMy74vdWvr2bLtCstxRFhX5ghRjdEyCCNlXpfmmFUhH6IkEGqirAvzZCL0A0RMqTmoVRgR3blG68ej22Ao7tbP0Pq8aNkWMgyVrOlrmtXs4WFvKfxENIYEfaFGWJ0Q4QM0lip96UZRkXohwgZpKoI+9IMuQjdECFDBDUdSm3atIl3vvOd9PT0cOWVV/Krv/qrHDhwoFnZ2t6+LVCq81W/Sl359a2eIfX4UTIsZz1lTtd1bZnT0+ok/Xzsp2JF2BdmiNENETK0AjuqOKn3pRlGReiHCBmis5+KE2FfmiEXoRsiZIigpkOpXbt2sW7dOh577DEeffRRTp8+zQc+8AFOnjzZrHxt68Sh/MXeJnqU8XyyM/D8Q3CigRfoT50h9fhRMsyin8WsnPBxzvPpZAZL+DCzmFt/iBZgPxUnwr4wQ4xuiJChVdhRxUi9L80wKkI/RMjQCuynYkTYl2bIReiGCBmiqOlQ6gc/+AFr167l2muv5frrr2f79u0cOnSIp59+uln52taB7aPvPlCvUgcc2Na6GVKPHyXDUtaOvANDvTIqLOX2hn5GdPZTcSLsCzPE6IYIGVqFHVWM1PvSDKMi9EOEDK3AfipGhH1phlyEboiQIYo6H5rLDQ0NAfDmN7/5vN9z6tQpTp06NfLXw8PDjQzZNoYGpubnDB9s3Qypx4+S4UoWTkGCjCtYMAU/p3XYT80TYV+YIUY3RMjQqibqKPupPqn3pRlGReiHCBlakf3UHBH2pRlyEbohQoYo6j6jrFQq/P7v/z4333wz11133Xm/b9OmTfT19Y189Pf31ztkWzl9fPTtMOuVleG1Bv4ZkTpD6vGjZLiYHjoafE+CDjq5hN6GfkYrsZ+aK8K+MEOMboiQoRVNpqPsp/qk3pdmGBWhHyJkaDX2U/NE2JdmyEXohggZoqh7FtatW8ff/M3f8MADD1zw+zZu3MjQ0NDIx+BgA7/82UZm9ECps7GfUeqEixpYo6kzpB4/SoZXOU6lwUc7K5R5hfb5Uyz7qbki7AszxOiGCBla0WQ6yn6qT+p9aYZREfohQoZWYz81T4R9aYZchG6IkCGKun5971Of+hQ7duxg9+7dzJ174RfW6u7upru7u65w7axvKp7mA3obeJovdYbU40fJ8CJT8YxriZdo4BnXFmI/NV+EfWGGGN0QIUOrmWxH2U/1Sb0vzTAqQj9EyNBK7KfmirAvzZCL0A0RMkRR05NSWZbxqU99iu9973v86Ec/4uqrr25Wrra3aC1kjR2cklVgUQOve5Y6Q+rxo2TYy3ZKDT7aWaKDvTTwaoAtwH4qToR9YYYY3RAhQ6uwo4qRel+aYVSEfoiQoRXYT8WIsC/NkIvQDREyRFHTLKxbt4777ruPb37zm/T09PDCCy/wwgsv8MorrzQrX9uaOQ/mrYRSnS9FX+qC+atgZgO/4p06Q+rxo2Q4xiD72UGZ03VdX+Y0+/g+xzhcf4gWYD8VJ8K+MEOMboiQoVXYUcVIvS/NMCpCP0TI0Arsp2JE2JdmyEXohggZoqjpUOqee+5haGiIW265hdmzZ498fPvb325WvrZ2/QbIztR3bVaGJetbP0Pq8aNkeJTNdDKjrms76GQnWxsPEZz9VKwI+8IMMbohQoZWYEcVJ/W+NMOoCP0QIUN09lNxIuxLM+QidEOEDBHU/Ot75/pYu3Ztk+K1t9nL4KbN9V1709359a2eIfX4UTIMsIcHqa99v8udDLCn8RDB2U/FirAvzBCjGyJkaAV2VHFS70szjIrQDxEyRGc/FSfCvjRDLkI3RMgQQWO/xKimW3zH6Iad6BHH6tdv2pxfN10ypB4/SoadbB0prYke86x+/UHWT5sTdMUTYV+YIUY3RMggjZV6X5phVIR+iJBBqoqwL82Qi9ANETKk5qFUcKVS/njiql0w7zaglL8FZvVtNEc+L+VfX7Ur//5SafpkSD1+lAyQl9ZmlrGfh6lQocwZypwho0KZ05Q5Q4UK+3mYzSybVmWleCLsCzPkInRDhAxSVYR9aYZREfohQgYJYuxLM4yK0A0RMqRU58uLqWizl+UfJwbhwDYYPgivDcNFvfnbYS66vbEXe2uFDKnHj5JhgD0MsIdZzGUpt3MFC7iEXl5hmJc4yF62TYsXvFPriLAvzBCjGyJkkMZKvS/NMCpCP0TIIFVF2JdmyEXohggZUvFQqsXM7IcbP9veGVKPHyXDMQ7zMJ9PG0IaI8K+MEOMboiQQRor9b40w6gI/RAhg1QVYV+aIRehGyJkKJq/vidJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTClbIsy4occHh4mL6+PijBZXOKHDn38lHIKlDqgEtnFz++GcwQLUPq8QFOHgEyGBoaore3N00I0vcTxLgfqTOkHt8MZhgvQkfZT2aIMr4ZYmWwn3IR7oUZzBBl/CgZJttP6Q6lJGmcMIdSknQOIf6jT5LOwX6SFNVE/dRVYJaz+aSUGcwQIkPq8WH0FD0M/6Sv7dekGcwwVqiOsp/aPkPq8c0QK4P9lItwL8xghijjR8kw2X5Kdih16VWw5nDx494/F07+NL8xKcY3gxmiZUg9PsB9c/LijCJVP0GM+5E6Q+rxzWCG8SJ1lP1khtTjmyFWBvspF+FemMEMUcaPkmGy/eQLnUuSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcMnefU+t68QhOLAdhgbg9HGY0QN9C2HRWpg5b/qPDzCLfpaylitZyMX08CrHeZEB9rKdYwwWkiHCPEjRRNgXqTPYT1JMEfZFhAx2lKKJsCZTi7AnImSIsBYizEPRPJTSpB3ZBfu2wKEdUHr9GbusDKXO/POn74L5K2HJBpi9bPqND7CQZSxnPYtZSUYFgA46qLz++UruYh8PsZMtDLCnKRkizIMUTYR9kTqD/STFFGFfRMhgRymaCGsytQh7IkKGCGshwjyk4q/vaUJZBs9uhh23wOAjQJZvkKz8+tern2dw6BF46L35hsqy6TF+1XLWs4FdXMcKOuigky466aI05vMOOljMbWxgN7dyx5SOH2UepEgi7IsIGewnKZ4I+yJCBrCjFE/qNZlahD0RIQOkXwtR5iElD6U0of1b4fE788+zMxf+3urXH9uQXzcdxge4lTv4KJsB6GTGBb+3+vXVbJnS0oowD1I0EfZF6gz2kxRThH0RIYMdpWgirMnUIuyJCBkirIUI85BaTYdS99xzD0uWLKG3t5fe3l7e/e5388gjjzQrmwI4sitf9PV4bAMc3d3a40P+OOdqttR17Wq2sJD3NJwhwjxEZz+1nwj7InUG+6l12FHtJcK+iJDBjmoN7dRPEdZkahH2RIQMEdZChHmIoKZDqblz5/KlL32Jp59+mqeeeopf+ZVf4SMf+Qj/83/+z2blU2L7tkCpzlceK3Xl17fy+JA/0lnmdF3Xljk9JSfpEeYhOvup/UTYF6kz2E+tw45qLxH2RYQMdlRraKd+irAmU4uwJyJkiLAWIsxDBDUdSq1atYrbbruNhQsX8ra3vY0vfOELzJw5k8cee6xZ+ZTQiUP5C61N9Bjh+WRn4PmH4ESdb1SQenzI34FhMSsnfJzzfDqZwRI+zCzm1p0hwjy0AvupvUTYF6kz2E+txY5qHxH2RYQMdlTraJd+irAmU4uwJyJkiLAWIsxDFHW/plS5XOaBBx7g5MmTvPvd757KTAriwPbRV/6vV6kDDmxrzfEBlrJ25B0Y6pVRYSm31319hHloNfbT9BdhX6TOYD+1LjtqeouwLyJksKNa03TupwhrMrUIeyJChghrIcI8RFHzw2L79+/n3e9+N6+++iozZ87ke9/7Hr/0S7903u8/deoUp06dGvnr4eHh+pKqcEMDU/Nzhg+25vgAV7JwChJkXMGCuq+OMA+twn5qHxH2ReoM9lPrqaWj7KfWFWFfRMhgR7WWduinCGsytQh7IkKGCGshwjxEUfPZ3KJFi3jmmWd4/PHH+Z3f+R0+/vGP87d/+7fn/f5NmzbR19c38tHf399QYBXn9PHRt6KsV1aG1+r851Tq8QEupoeOBt+ksoNOLqG37usjzEOrsJ/aR4R9kTqD/dR6auko+6l1RdgXETLYUa2lHfopwppMLcKeiJAhwlqIMA9R1HwnLrroIhYsWMCNN97Ipk2buP766/mjP/qj837/xo0bGRoaGvkYHJwGv/TYJmb0QKmzsZ9R6oSL6tyrqccHeJXjVBp8tLNCmVeovy0izEOrsJ/aR4R9kTqD/dR6auko+6l1RdgXETLYUa2lHfopwppMLcKeiJAhwlqIMA9R1Pla76MqlcpZj2+O193dTXd3d6PDKIG+qXiqEeit86nG1OMDvMhUPFdZ4iXqf64ywjy0Kvtp+oqwL1JnsJ9a34U6yn5qXRH2RYQMdlRrm479FGFNphZhT0TIEGEtRJiHKGp6Umrjxo3s3r2b5557jv3797Nx40Z+/OMfs2bNmmblU0KL1kLW2AEyWQUW1fn6b6nHB9jLdkoNPtpZooO91P8KdBHmoRXYT+0lwr5IncF+ai12VPuIsC8iZLCjWke79FOENZlahD0RIUOEtRBhHqKo6U68+OKL/MZv/AaLFi3i/e9/P08++SR/+qd/yvLly5uVTwnNnAfzVkKpzufpSl0wfxXMrPPXzFOPD3CMQfazgzKn67q+zGn28X2OcbjuDBHmoRXYT+0lwr5IncF+ai12VPuIsC8iZLCjWke79FOENZlahD0RIUOEtRBhHqKoaQruvffeZuVQUNdvgEMP1XdtVoYl61t7fIBH2cz1fLiuazvoZCdbG84QYR6is5/aT4R9kTqD/dQ67Kj2EmFfRMhgR7WGduqnCGsytQh7IkKGCGshwjxE0Ngza5r2Zi+DmzbXd+1Nd+fXt/L4AAPs4UHq2/Hf5U4G2NNwhgjzIEUTYV+kzmA/STFF2BcRMthRiibCmkwtwp6IkCHCWogwDxF4KKUJLb5jdLNM9Hhh9es3bc6vmw7jA+xk60hpTfSYZ/XrD7J+Sv80JcI8SNFE2BepM9hPUkwR9kWEDHaUoomwJlOLsCciZIiwFiLMQ2oeSmlCpVL+aOCqXTDvNqCUv/1k9S0sRz4v5V9ftSv//lJpeoxftZOtbGYZ+3mYChXKnKHMGTIqlDlNmTNUqLCfh9nMsin/B1eUeZAiibAvImSwn6R4IuyLCBnAjlI8qddkahH2RIQMkH4tRJmHlOp8WS21o9nL8o8Tg3BgGwwfhNeG4aLe/K0oF93e3BdaSz0+5I95DrCHWcxlKbdzBQu4hF5eYZiXOMhetjX9xQ8jzIMUTYR9kTqD/STFFGFfRMhgRymaCGsytQh7IkKGCGshwjyk4qGUajazH278bPuOD3CMwzzM55NmiDAPUjQR9kXqDPaTFFOEfREhgx2laCKsydQi7IkIGSKshQjzUDR/fU+SJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmFK2VZlhU54PDwMH19fVCCy+YUOXLu5aOQVaDUAZfOLn58M5ghWobU4wOcPAJkMDQ0RG9vb5oQpO8niHE/UmdIPb4ZzDBehI6yn8wQZXwzxMpgP+Ui3AszmCHK+FEyTLaf0h1KSdI4YQ6lJOkcQvxHnySdg/0kKaqJ+qmrwCxn80kpM5ghRIbU48PoKXoY/klf269JM5hhrFAdZT+1fYbU45shVgb7KRfhXpjBDFHGj5Jhsv2U7FDq0qtgzeHix71/Lpz8aX5jUoxvBjNEy5B6fID75uTFGUWqfoIY9yN1htTjm8EM40XqKPvJDKnHN0OsDPZTLsK9MIMZoowfJcNk+8kXOpckSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLh0r37nupy4hAc2A5DA3D6OMzogb6FsGgtzJzXHhlm0c9S1nIlC7mYHl7lOC8ywF62c4zB5gcIkkGKJnU3RMmQuh9Sjy9FFKEbImSI0A8R5kGKxH2Zcx7al4dSLeLILti3BQ7tyN/WESArQ6kz//zpu2D+SliyAWYvm54ZFrKM5axnMSvJqADQQQeV1z9fyV3s4yF2soUB9kx9gCAZpGhSd0OUDKn7IfX4UkQRuiFChgj9EGEepEjclznnQf76XnBZBs9uhh23wOAjQJZvkKz8+tern2dw6BF46L35hsqy6ZVhOevZwC6uYwUddNBJF510URrzeQcdLOY2NrCbW7lj6gYPlEGKJEI3RMgA6fsh9fhSNBG6IUIGSN8PUeZBisR9mXMeBB5Khbd/Kzx+Z/55dubC31v9+mMb8uumS4ZbuYOPshmATmZc8HurX1/NliktrQgZpGhSd0OUDKn7IfX4UkQRuiFChgj9EGEepEjclznnQVUeSgV2ZFe+6Ovx2AY4urv1MyxkGavZUte1q9nCQt7TWIAgGaRoUndDlAyp+yH1+FJEEbohQoYI/RBhHqRI3Jc550FjNXQo9aUvfYlSqcTv//7vT1EcjbVvC5TqfNWvUld+fatnWM56ypyu69oyp6fkJD1CBtXOfmqu1N0QJUPqfkg9vupjPzVXhG6IkCFCP0SYB9XOjmoe92XOedBYdR9KPfnkk/yX//JfWLJkyVTm0etOHMpfaG2ixwjPJzsDzz8EJxp4o4LUGWbRz2JWTvg45/l0MoMlfJhZzK0vQJAMqp391FypuyFKhtT9kHp81cd+aq4I3RAhQ4R+iDAPqp0d1Tzuy5zzoPHqOpQ6ceIEa9as4Wtf+xqzZs2a6kwifyvKUoO/XFnqgAPbWjfDUtaOvANDvTIqLOX2uq+PkEG1sZ+aL3U3RMmQuh9Sj6/a2U/NF6EbImSI0A8R5kG1saOay32Zcx40Xl23Yt26dXzoQx/i1ltvnfB7T506xfDw8FkfmtjQwNT8nOGDrZvhShZOwegZV7Cg7qsjZFBt7KfmS90NUTKk7ofU46t29lPzReiGCBki9EOEeVBtJttR9lN93Jc550Hj1fxblA888AB/9Vd/xZNPPjmp79+0aROf+9znag7W7k4fH30rynplZXitgX9GpM5wMT10NPha/B10cgm9dV8fIYMmz34qRupuiJIhdT+kHl+1sZ+KEaEbImSI0A8R5kGTV0tH2U/1cV/mnAeNV9NqGBwc5NOf/jT3338/F1988aSu2bhxI0NDQyMfg4P+4uVkzOiBUmdjP6PUCRc18N8aqTO8ynEqDT7aWaHMK9TfFhEyaHLsp+Kk7oYoGVL3Q+rxNXn2U3EidEOEDBH6IcI8aHJq7Sj7qT7uy5zzoPFqelLq6aef5sUXX+Ttb3/7yN8rl8vs3r2br3zlK5w6dYrOzrPvbnd3N93d3VOTto30TcVTjUBvA7+VkTrDi0zFc5UlXqL+5yojZNDk2E/FSd0NUTKk7ofU42vy7KfiROiGCBki9EOEedDk1NpR9lN93Jc550Hj1fSk1Pvf/37279/PM888M/Lxjne8gzVr1vDMM8+84V+oVL9FayFr7ACZrAKLGnj92tQZ9rKdUoOPdpboYC/1vwJdhAyaHPupOKm7IUqG1P2QenxNnv1UnAjdECFDhH6IMA+aHDuqGO7LnPOg8WpaDT09PVx33XVnfVx22WVcfvnlXHfddc3K2JZmzoN5K6FU86t+5UpdMH8VzOxv3QzHGGQ/Oyhzuq7ry5xmH9/nGIfrCxAkgybHfipO6m6IkiF1P6QeX5NnPxUnQjdEyBChHyLMgybHjiqG+zLnPGi8Bt8IUc10/QbIztR3bVaGJetbP8OjbKaTGXVd20EnO9naWIAgGaRoUndDlAyp+yH1+FJEEbohQoYI/RBhHqRI3Jc550FjNXwo9eMf/5gvf/nLUxBF481eBjdtru/am+7Or2/1DAPs4UHq2/Hf5U4G2NNYgCAZVB/7qXlSd0OUDKn7IfX4qp/91DwRuiFChgj9EGEeVB87qjnclznnQWP5pFRwi+8Y3SwTPV5Y/fpNm/PrpkuGnWwdKa2JHvOsfv1B1k/pEwARMkjRpO6GKBlS90Pq8aWIInRDhAwR+iHCPEiRuC9zzoOqPJQKrlTKHw1ctQvm3QaU8refrL6F5cjnpfzrq3bl318qTa8MO9nKZpaxn4epUKHMGcqcIaNCmdOUOUOFCvt5mM0sa8p/bEXIIEUSoRsiZID0/ZB6fCmaCN0QIQOk74co8yBF4r7MOQ8CqPOlvVS02cvyjxODcGAbDB+E14bhot78rSgX3d78F1pLnWGAPQywh1nMZSm3cwULuIReXmGYlzjIXrY1/QV7I2SQokndDVEypO6H1ONLEUXohggZIvRDhHmQInFf5pwHeSjVYmb2w42fbe8MxzjMw3w+XYAgGaRoUndDlAyp+yH1+FJEEbohQoYI/RBhHqRI3Jc556F9+et7kiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKlwpy7KsyAGHh4fp6+uDElw2p8iRcy8fhawCpQ64dHbx45vBDNEypB4f4OQRIIOhoSF6e3vThCB9P0GM+5E6Q+rxzWCG8SJ0lP1khijjmyFWBvspF+FemMEMUcaPkmGy/ZTuUEqSxglzKCVJ5xDiP/ok6RzsJ0lRTdRPXQVmOZtPSpnBDCEypB4fRk/Rw/BP+tp+TZrBDGOF6ij7qe0zpB7fDLEy2E+5CPfCDGaIMn6UDJPtp2SHUpdeBWsOFz/u/XPh5E/zG5NifDOYIVqG1OMD3DcnL84oUvUTxLgfqTOkHt8MZhgvUkfZT2ZIPb4ZYmWwn3IR7oUZzBBl/CgZJttPvtC5JEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgqX7N33VJ8Th+DAdhgagNPHYUYP9C2ERWth5rxiMsyin6Ws5UoWcjE9vMpxXmSAvWznGINNH985iJNBGsu9mUs9DxHmIEIGaazU+xJi7AvnIRdhHqSqCOvRfZlzHtLwUKpFHNkF+7bAoR1Qev35tqwMpc7886fvgvkrYckGmL2sORkWsozlrGcxK8moANBBB5XXP1/JXezjIXayhQH2TPn4zkGcDNJY7s1c6nmIMAcRMkhjpd6XEGNfOA+5CPMgVUVYj+7LnPOQlr++F1yWwbObYcctMPgIkOWLMyu//vXq5xkcegQeem++mLNsanMsZz0b2MV1rKCDDjrpopMuSmM+76CDxdzGBnZzK3dM2djOQawMUpV7MxdhHlLPQZQMUlWEfQnp94XzkIsyDxLEWY/uy5zzkJ6HUsHt3wqP35l/np258PdWv/7Yhvy6qXIrd/BRNgPQyYwLfm/166vZMmUb1jmIk0Eay72ZSz0PEeYgQgZprNT7EmLsC+chF2EepKoI69F9mXMeYqjpUOquu+6iVCqd9XHNNdc0K1vbO7IrX3D1eGwDHN3deIaFLGM1W+q6djVbWMh7GhrfOYiTITr7qVjuzVzqeYgwBxEytAI7qjip9yXE2BfOQy7CPERnPxUnwnp0X+achzhqflLq2muv5ejRoyMff/EXf9GMXCJ/LK9U56t+lbry6xu1nPWUOV3XtWVON3yK7BzEydAK7KfiuDdzqechwhxEyNAq7KhipN6XEGNfOA+5CPPQCuynYkRYj+7LnPMQR81T0NXVxVVXXdWMLBrjxKH8Rc6o83dFszPw/ENwYhBm9tf3M2bRz2JW0lHnb3l2MoMlfJhZzOUYh2u+3jmIk6FV2E/FcG/mUs9DhDmIkKGV2FHNl3pfQox94TzkIsxDq7Cfmi/CenRf5pyHWGq+CwMDA8yZM4e3vOUtrFmzhkOHDjUjV9s7sH30VffrVeqAA9vqv34pa0fefaBeGRWWcntd1zoHcTK0CvupGO7NXOp5iDAHETK0Ejuq+VLvS4ixL5yHXIR5aBX2U/NFWI/uy5zzEEtNT0r98i//Mtu3b2fRokUcPXqUz33uc7znPe/hb/7mb+jp6TnnNadOneLUqVMjfz08PNxY4jYxNDA1P2f4YP3XXsnCKUiQcQUL6rrSOYiToRXYT8Vxb+ZSz0OEOYiQoVXU2lH2U31S70uIsS+ch1yEeWgF9lMxIqxH92XOeYilpkOpFStWjHy+ZMkSfvmXf5n58+fzne98h9/8zd885zWbNm3ic5/7XGMp29Dp46NvA1mvrAyvNfDPiIvpqfuRxqoOOrmE3rqudQ7iZGgF9lNx3Ju51PMQYQ4iZGgVtXaU/VSf1PsSYuwL5yEXYR5agf1UjAjr0X2Zcx5iaehOvOlNb+Jtb3sbBw+e/3hu48aNDA0NjXwMDg42MmTbmNEDpc7GfkapEy5q4N/zX+U4lQYfa6xQ5hXq2ynOQZwMrch+ah73Zi71PESYgwgZWtVEHWU/1Sf1voQY+8J5yEWYh1ZkPzVHhPXovsw5D7E0dCh14sQJ/tf/+l/Mnj37vN/T3d1Nb2/vWR+aWN9UPFEI9DbwGxEvMhXPFJZ4ifqeKXQO4mRoRfZT87g3c6nnIcIcRMjQqibqKPupPqn3JcTYF85DLsI8tCL7qTkirEf3Zc55iKWmQ6kNGzawa9cunnvuOfbu3cs/+Sf/hM7OTn7913+9Wfna1qK1kDV2eEtWgUUNvHbsXrZTavCxxhId7KW+V19zDuJkaAX2U3Hcm7nU8xBhDiJkaBV2VDFS70uIsS+ch1yEeWgF9lMxIqxH92XOeYilpjtx+PBhfv3Xf51FixbxT//pP+Xyyy/nscce44orrmhWvrY1cx7MWwmlml71a1SpC+avauztIY8xyH52UOZ0XdeXOc0+vl/322Q6B3EytAL7qTjuzVzqeYgwBxEytAo7qhip9yXE2BfOQy7CPLQC+6kYEdaj+zLnPMRS0xQ88MADzcqhc7h+Axx6qL5rszIsWd94hkfZzPV8uK5rO+hkJ1sbGt85iJMhOvupWO7NXOp5iDAHETK0AjuqOKn3JcTYF85DLsI8RGc/FSfCenRf5pyHOBp7Zk1NNXsZ3LS5vmtvuju/vlED7OFB6lvt3+VOBtjT0PjOQZwM0ljuzVzqeYgwBxEySGOl3pcQY184D7kI8yBVRViP7suc8xCHh1LBLb5jdKFO9Ghf9es3bc6vmyo72TqyYSd6xLH69QdZP2V/+u0cxMkgjeXezKWehwhzECGDNFbqfQkx9oXzkIswD1JVhPXovsw5DzF4KBVcqZQ/lrdqF8y7DSjlb/1YffvIkc9L+ddX7cq/v1Sa2hw72cpmlrGfh6lQocwZypwho0KZ05Q5Q4UK+3mYzSyb0o3qHMTKIFW5N3MR5iH1HETJIFVF2JeQfl84D7ko8yBBnPXovsw5D+nV+bJaKtrsZfnHiUE4sA2GD8Jrw3BRb/42kItub/6LnA2whwH2MIu5LOV2rmABl9DLKwzzEgfZy7amvlitcxAngzSWezOXeh4izEGEDNJYqfclxNgXzkMuwjxIVRHWo/sy5zyk5aFUi5nZDzd+Nm2GYxzmYT6fbHznIE4GaSz3Zi71PESYgwgZpLFS70uIsS+ch1yEeZCqIqxH92XOeUjDX9+TJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4UpZlmVFDjg8PExfXx+U4LI5RY6ce/koZBUodcCls4sf3wxmiJYh9fgAJ48AGQwNDdHb25smBOn7CWLcj9QZUo9vBjOMF6Gj7CczRBnfDLEy2E+5CPfCDGaIMn6UDJPtp3SHUpI0TphDKUk6hxD/0SdJ52A/SYpqon7qKjDL2XxSygxmCJEh9fgweooehn/S1/Zr0gxmGCtUR9lPbZ8h9fhmiJXBfspFuBdmMEOU8aNkmGw/JTuUuvQqWHO4+HHvnwsnf5rfmBTjm8EM0TKkHh/gvjl5cUaRqp8gxv1InSH1+GYww3iROsp+MkPq8c0QK4P9lItwL8xghijjR8kw2X7yhc4lSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuHTvvteCThyCA9thaABOH4cZPdC3EBathZnzUqcrjvMQwyz6WcparmQhF9PDqxznRQbYy3aOMZg6ngrmvsw5DzHYTxrLfZlzHuJI3VGuhVi8H85BJKn7CYpfDx5KTcKRXbBvCxzakb+lIkBWhlJn/vnTd8H8lbBkA8xelixm0zkPMSxkGctZz2JWklEBoIMOKq9/vpK72MdD7GQLA+xJGVUFcF/mnIcY7CeN5b7MOQ9xpO4o10Is3g/nIJLU/QTp1oO/vncBWQbPboYdt8DgI0CW35Ss/PrXq59ncOgReOi9+U3MsoShm8B5iGM569nALq5jBR100EkXnXRRGvN5Bx0s5jY2sJtbuSN1ZDWJ+zLnPMRhP6nKfZlzHmJJ2VGuhVi8H85BNKn/HSr1evBQ6gL2b4XH78w/z85c+HurX39sQ37ddOI8xHArd/BRNgPQyYwLfm/166vZ4n/4TVPuy5zzEIP9pLHclznnIY7UHeVaiMX74RxEkrqfIP168FDqPI7syie6Ho9tgKO7pzZPKs5DDAtZxmq21HXtarawkPdMcSKl5L7MOQ8x2E8ay32Zcx7iSN1RroVYvB/OQSSp+wlirIeaD6V++tOf8rGPfYzLL7+cSy65hMWLF/PUU081niSYfVugVOcrbpW68uunA+chhuWsp8zpuq4tc7ptnkawnyY2nfal8xCD/TR57dBR7suc8xBH6o5qlbXQDv0ErXM/msk5iCN1P0GM9VDTodSxY8e4+eabmTFjBo888gh/+7d/y5YtW5g1a1bjSQI5cSh/ca+JHl07n+wMPP8QnGjxNxhyHmKYRT+LWTnh45zn08kMlvBhZjF3ipPFYj9NznTZl85DDPbT5LVDR7kvc85DHKk7qlXWQjv0E7TO/Wgm5yCO1P0EcdZDTYdSf/iHf0h/fz/btm3jXe96F1dffTUf+MAHeOtb39pYimAObB99tfl6lTrgwLYpiZOM8xDDUtaOvANDvTIqLOX2KUoUk/00edNhXzoPMdhPk9cOHeW+zDkPcaTuqFZZC+3QT9A696OZnIM4UvcTxFkPNUX4/ve/zzve8Q5Wr17NlVdeyQ033MDXvva1C15z6tQphoeHz/qIbmhgan7O8MGp+TmpOA8xXMnCKfgpGVewYAp+Tlz2U21afV86DzHYT5NXa0fZT63LeYgjdUe1ylpoh36C1rkfzeQcxJG6nyDOeqjpUOof/uEfuOeee1i4cCF/+qd/yu/8zu/we7/3e3zjG9847zWbNm2ir69v5KO/v7+xxAU4fXz07Q/rlZXhtdbo5/NyHmK4mB46GnxPgg46uYTeKUoUk/00edNhXzoPMdhPk1drR9lPrct5iCN1R7XKWmiHfoLWuR/N5BzEkbqfIM56qGkWKpUKb3/72/niF7/IDTfcwL/4F/+C3/7t3+Y//+f/fN5rNm7cyNDQ0MjH4GD8X0Cd0QOlzsZ+RqkTLmrxf8d2HmJ4leNUGny0s0KZV5je//SwnyZvOuxL5yEG+2nyau0o+6l1OQ9xpO6oVlkL7dBP0Dr3o5mcgzhS9xPEWQ81HUrNnj2bX/qlXzrr7/2jf/SPOHTo0Hmv6e7upre396yP6Pqm4kk6oLfFfxvBeYjhRabiucoSLzG9n7O1n2rT6vvSeYjBfpq8WjvKfmpdzkMcqTuqVdZCO/QTtM79aCbnII7U/QRx1kNNh1I333wzBw4cOOvv/f3f/z3z589vLEUwi9ZC1tihJVkFFrX467Y6DzHsZTulBh/tLNHBXqb3KxLaT5M3Hfal8xCD/TR57dBR7suc8xBH6o5qlbXQDv0ErXM/msk5iCN1P0Gc9VDTLPzrf/2veeyxx/jiF7/IwYMH+eY3v8l//a//lXXr1jWWIpiZ82DeSih11Xd9qQvmr4KZrfHr1eflPMRwjEH2s4Myp+u6vsxp9vF9jnF4ipPFYj9NznTZl85DDPbT5LVDR7kvc85DHKk7qlXWQjv0E7TO/Wgm5yCO1P0EcdZDTYdS73znO/ne977Ht771La677jo+//nP8+Uvf5k1a9Y0liKg6zdAdqa+a7MyLFk/tXlScR5ieJTNdDKjrms76GQnW6c4UTz20+RMp33pPMRgP01Ou3SU+zLnPMSRuqNaYS20Sz9Ba9yPZnMO4kjdTxBjPdT8vNjKlSvZv38/r776Kj/5yU/47d/+7cZTBDR7Gdy0ub5rb7o7v346cB5iGGAPD1Lfjv8udzLAnilOFJP9NLHptC+dhxjsp8lrh45yX+achzhSd1SrrIV26CdonfvRTM5BHKn7CWKsh8Z+iXGaW3zH6A2a6JG26tdv2pxfN504DzHsZOtIaU30mGf16w+yvm2eQmg37suc8xCD/aSx3Jc55yGO1B3lWojF++EcRJK6nyD9evBQ6gJKpfxxtFW7YN5tQCl/y8Pq2yaOfF7Kv75qV/79pVLK1FPPeYhjJ1vZzDL28zAVKpQ5Q5kzZFQoc5oyZ6hQYT8Ps5ll/gffNOa+zDkPcdhPqnJf5pyHWFJ2lGshFu+HcxBN6n+HSr0e6nxJq/Yye1n+cWIQDmyD4YPw2jBc1Ju//eGi29vjxd6chxgG2MMAe5jFXJZyO1ewgEvo5RWGeYmD7GVbW7xosHLuy5zzEIP9pLHclznnIY7UHeVaiMX74RxEkrqfIN168FCqBjP74cbPpk6RnvMQwzEO8zCfTx1DQbgvc85DDPaTxnJf5pyHOFJ3lGshFu+HcxBJ6n6C4teDv74nSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMKVsizLihxweHiYvr4+KMFlc4ocOffyUcgqUOqAS2cXP74ZzBAtQ+rxAU4eATIYGhqit7c3TQjS9xPEuB+pM6Qe3wxmGC9CR9lPZogyvhliZbCfchHuhRnMEGX8KBkm20/pDqUkaZwwh1KSdA4h/qNPks7BfpIU1UT91FVglrP5pJQZzBAiQ+rxYfQUPQz/pK/t16QZzDBWqI6yn9o+Q+rxzRArg/2Ui3AvzGCGKONHyTDZfkp2KHXpVbDmcPHj3j8XTv40vzEpxjeDGaJlSD0+wH1z8uKMIlU/QYz7kTpD6vHNYIbxInWU/WSG1OObIVYG+ykX4V6YwQxRxo+SYbL95AudS5IkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXDp3n1PLevEITiwHYYG4PRxmNEDfQth0VqYOS91OhVpFv0sZS1XspCL6eFVjvMiA+xlO8cYTB1Pbch+UpX9pGjsJ1XZT4rGftJYRXeUh1KatCO7YN8WOLQjf2tJgKwMpc7886fvgvkrYckGmL0sWUwVYCHLWM56FrOSjAoAHXRQef3zldzFPh5iJ1sYYE/KqGoT9pOq7CdFYz+pyn5SNPaTxkrVUf76niaUZfDsZthxCww+AmR5WWXl179e/TyDQ4/AQ+/Nyy3LEoZW0yxnPRvYxXWsoIMOOumiky5KYz7voIPF3MYGdnMrd6SOrGnMftJY9pMisZ80lv2kSOwnjZeyozyU0oT2b4XH78w/z85c+HurX39sQ36dppdbuYOPshmATmZc8HurX1/NFv/FSk1jP6nKflI09pOq7CdFYz9prNQdVdOh1C/+4i9SKpXe8LFu3bopCaN4juzKC6gej22Ao7unNo/SWcgyVrOlrmtXs4WFvGeKE72RHdVe7CdV2U+Kxn5Slf2kaOwnjRWho2o6lHryySc5evToyMejjz6ah1m9uuEgimnfFijV+cpjpa78ek0Py1lPmdN1XVvmdCF/2mdHtRf7SVX2k6Kxn1RlPyka+0ljReiompbjFVdccdZff+lLX+Ktb30r733vexsOonhOHMpf9I46f3c4OwPPPwQnBmFm/5RGU8Fm0c9iVtJR52/8djKDJXyYWczlGIenON0oO6p92E+qsp8Ujf2kKvtJ0dhPGitKR9X9mlKvvfYa9913H5/4xCcolUp1B1BcB7aPvgtDvUodcGDblMRRQktZO/IODPXKqLCU26co0cTsqOnNflKV/aRo7CdV2U+Kxn7SWFE6qs4H9+BP/uRP+NnPfsbatWsv+H2nTp3i1KlTI389PDxc75Aq2NDA1Pyc4YNT83OUzpUsnIKfknEFC6bg50zOZDrKfmpd9pOq7CdFYz+pyn5SNPaTxorSUXWfk957772sWLGCOXPmXPD7Nm3aRF9f38hHf7/P+bWK08dH3xa0XlkZXvOfUy3vYnrqfqyzqoNOLqF3ihJNbDIdZT+1LvtJVfaTorGfVGU/KRr7SWNF6ai6Ejz//PPs3LmT3/qt35rwezdu3MjQ0NDIx+DgYD1DKoEZPVDqbOxnlDrhouL+OaomeZXjVBp8tLNCmVco5p9gk+0o+6l12U+qsp8Ujf2kKvtJ0dhPGitKR9X163vbtm3jyiuv5EMf+tCE39vd3U13d3c9wyixvql4mg/oLe6JYzXJi0zFs74lXqKYZ30n21H2U+uyn1RlPyka+0lV9pOisZ80VpSOqvlJqUqlwrZt2/j4xz9OV1fdL0mlFrBoLWSNHZySVWBRca/NqCbZy3ZKDT7aWaKDvTT/VRHtqPZgP6nKflI09pOq7CdFYz9prCgdVXOCnTt3cujQIT7xiU80NLDimzkP5q2EUp3/XCp1wfxVvl3odHCMQfazgzKn67q+zGn28f2mvp1xlR3VHuwnVdlPisZ+UpX9pGjsJ40VpaNqPpT6wAc+QJZlvO1tb2toYLWG6zdAdqa+a7MyLFk/tXmUzqNsppMZdV3bQSc72TrFic7Njmof9pOq7CdFYz+pyn5SNPaTxorQUY09q6Vpb/YyuGlzfdfedHd+vaaHAfbwIPX9U+i73MkAe6Y4kdqd/aQq+0nR2E+qsp8Ujf2ksSJ0lIdSmtDiO0aLa6JHPatfv2lzfp2ml51sHSmtiR7zrH79QdYX9qd8aj/2k6rsJ0VjP6nKflI09pPGSt1RHkppQqVS/pjmql0w7zaglL8VaPXtREc+L+VfX7Ur//5SKWVqNctOtrKZZeznYSpUKHOGMmfIqFDmNGXOUKHCfh5mM8v8Fyo1lf2ksewnRWI/aSz7SZHYTxovZUf51gqatNnL8o8Tg3BgGwwfhNeG4aLe/G1BF93ui961iwH2MMAeZjGXpdzOFSzgEnp5hWFe4iB72VbIi3JKVfaTquwnRWM/qcp+UjT2k8ZK1VEeSqlmM/vhxs+mTqEIjnGYh/l86hjSCPtJVfaTorGfVGU/KRr7SWMV3VH++p4kSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKV8qyLCtywOHhYfr6+qAEl80pcuTcy0chq0CpAy6dXfz4ZjBDtAypxwc4eQTIYGhoiN7e3jQhSN9PEON+pM6QenwzmGG8CB1lP5khyvhmiJXBfspFuBdmMEOU8aNkmGw/pTuUkqRxwhxKSdI5hPiPPkk6B/tJUlQT9VNXgVnO5pNSZjBDiAypx4fRU/Qw/JO+tl+TZjDDWKE6yn5q+wypxzdDrAz2Uy7CvTCDGaKMHyXDZPsp2aHUpVfBmsPFj3v/XDj50/zGpBjfDGaIliH1+AD3zcmLM4pU/QQx7kfqDKnHN4MZxovUUfaTGVKPb4ZYGeynXIR7YQYzRBk/SobJ9pMvdC5JkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMLVdChVLpf5gz/4A66++mouueQS3vrWt/L5z3+eLMualU+SJsV+khSZHSUpKvtJUkpdtXzzH/7hH3LPPffwjW98g2uvvZannnqK22+/nb6+Pn7v936vWRklaUL2k6TI7ChJUdlPklKq6VBq7969fOQjH+FDH/oQAL/4i7/It771LZ544ommhJOkybKfJEVmR0mKyn6SlFJNv763dOlSfvjDH/L3f//3ADz77LP8xV/8BStWrDjvNadOnWJ4ePisD0maavaTpMhq7Sj7SVJR7CdJKdX0pNRnPvMZhoeHueaaa+js7KRcLvOFL3yBNWvWnPeaTZs28bnPfa7hoJJ0IfaTpMhq7Sj7SVJR7CdJKdX0pNR3vvMd7r//fr75zW/yV3/1V3zjG99g8+bNfOMb3zjvNRs3bmRoaGjkY3BwsOHQkjSe/SQpslo7yn6SVBT7SVJKNT0pdeedd/KZz3yGf/7P/zkAixcv5vnnn2fTpk18/OMfP+c13d3ddHd3N55Uki7AfpIUWa0dZT9JKor9JCmlmp6Uevnll+noOPuSzs5OKpXKlIaSpFrZT5Iis6MkRWU/SUqppielVq1axRe+8AXmzZvHtddey1//9V+zdetWPvGJTzQrnyRNiv0kKTI7SlJU9pOklGo6lPpP/+k/8Qd/8Ad88pOf5MUXX2TOnDn8y3/5L/nsZz/brHySNCn2k6TI7ChJUdlPklKq6VCqp6eHL3/5y3z5y19uUhxJqo/9JCkyO0pSVPaTpJRqek0pSZIkSZIkaSp4KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwpWyLMuKHHBoaIg3velNAFw6u8iRcy+/AGRACS69qvjxzWCGaBlSjw/w8tH8f3/2s5/R19eXJgTp+wmC3A/XpBnMcHaGAB1lP5khyvhmCJbBfgKC3AszmCHI+GEyTLKfCj+UOnz4MP39/UUOKalFDA4OMnfu3GTj20+SLiRlR9lPki7EfpIU1UT9VPihVKVS4ciRI/T09FAqlWq+fnh4mP7+fgYHB+nt7W1CQjO0SobU45th6jJkWcbx48eZM2cOHR3pfqvYfjLDdMqQevzplCFCRzXaT5D+fqQe3wxmiJbBfhqV+l5EyJB6fDOYYaozTLafuhoJWY+Ojo4pOcXv7e1NdnPMECtD6vHNMDUZUv7aXpX9ZIbpmCH1+NMlQ+qOmqp+gvT3I/X4ZjBDtAz206jU9yJChtTjm8EMU5lhMv3kC51LkiRJkiSpcB5KSZIkSZIkqXAtdyjV3d3Nv//3/57u7m4ztHmG1OObIVaGCCLMgxnMEGV8M8STei5Sj28GM0TLkHr8SCLMReoMqcc3gxlSZSj8hc4lSZIkSZKklntSSpIkSZIkSa3PQylJkiRJkiQVzkMpSZIkSZIkFa6lDqX+8i//ks7OTj70oQ8VPvbatWsplUojH5dffjkf/OAH2bdvX+FZXnjhBX73d3+Xt7zlLXR3d9Pf38+qVav44Q9/2PSxx87DjBkz+Pmf/3mWL1/O17/+dSqVStPHH59h7McHP/jBQsafKMfBgwcLGf+FF17g05/+NAsWLODiiy/m53/+57n55pu55557ePnll5s+/tq1a/nVX/3VN/z9H//4x5RKJX72s581PUM0dpT9ND5Hqo5K3U+QtqPspzeyn+yn8TnsJ/8dKgr7yX4an8N+aq9+aqlDqXvvvZff/d3fZffu3Rw5cqTw8T/4wQ9y9OhRjh49yg9/+EO6urpYuXJloRmee+45brzxRn70ox9x9913s3//fn7wgx/wvve9j3Xr1hWSoToPzz33HI888gjve9/7+PSnP83KlSs5c+ZMoRnGfnzrW98qZOyJclx99dVNH/cf/uEfuOGGG/izP/szvvjFL/LXf/3X/OVf/iX/5t/8G3bs2MHOnTubnkFv1O4dZT+9MUfKjkrVT2BHRWQ/2U/jc9hP9lMU9pP9ND6H/dRe/dSVOsBknThxgm9/+9s89dRTvPDCC2zfvp1/9+/+XaEZuru7ueqqqwC46qqr+MxnPsN73vMeXnrpJa644opCMnzyk5+kVCrxxBNPcNlll438/WuvvZZPfOIThWQYOw+/8Au/wNvf/nZuuukm3v/+97N9+3Z+67d+q9AMKaXK8clPfpKuri6eeuqps9bBW97yFj7ykY/gm2oWz46yn86XI5WUGeyoWOwn++l8OVKxn1RlP9lP58uRiv1UvJZ5Uuo73/kO11xzDYsWLeJjH/sYX//615PelBMnTnDfffexYMECLr/88kLG/H//7//xgx/8gHXr1p21SKve9KY3FZLjXH7lV36F66+/nv/xP/5Hsgzt4v/+3//Ln/3Zn513HQCUSqWCU6ndO8p+UpUdFY/9ZD8pZz/FYz/ZT8q1cz+1zKHUvffey8c+9jEgf6RuaGiIXbt2FZphx44dzJw5k5kzZ9LT08P3v/99vv3tb9PRUcw0Hjx4kCzLuOaaawoZr1bXXHMNzz33XCFjjb0X1Y8vfvGLhYx9oRyrV69u+pjVdbBo0aKz/v7P/dzPjeT4t//23zY9B5z7PqxYsaKQsaNp946yn84WoaNS9BPE6Sj7aZT9ZD+NZT+l7yewo6rsJ/tpLPupPfupJX5978CBAzzxxBN873vfA6Crq4t/9s/+Gffeey+33HJLYTne9773cc899wBw7Ngx/viP/5gVK1bwxBNPMH/+/KaPH/1xvSzLCju9HXsvqt785jcXMvaFcpzvVLsITzzxBJVKhTVr1nDq1KlCxjzXfXj88cdH/uWiXdhR9tN4EToqUj9B8R1lP+XsJ/tpPPvpjfx3qDTsJ/tpPPvpjdqhn1riUOree+/lzJkzzJkzZ+TvZVlGd3c3X/nKV+jr6yskx2WXXcaCBQtG/vq//bf/Rl9fH1/72tf4j//xPzZ9/IULF1Iqlfi7v/u7po9Vj5/85CeFvQjc+HuRSoocCxYsoFQqceDAgbP+/lve8hYALrnkksKynOv//+HDhwsbPwo7yn4aL0JHpcoQpaPsp5z9ZD+NZz+l7yewo8B+AvtpPPupPfsp/K/vnTlzhv/+3/87W7Zs4Zlnnhn5ePbZZ5kzZ06Sd1yrKpVKdHR08MorrxQy3pvf/Gb+8T/+x3z1q1/l5MmTb/h6yreP/dGPfsT+/fv5tV/7tWQZ2sXll1/O8uXL+cpXvnLOdaBi2VE5+0lVdlQc9lPOflKV/RSH/ZSzn1TVzv0U/kmpHTt2cOzYMX7zN3/zDaflv/Zrv8a9997Lv/pX/6qQLKdOneKFF14A8kc7v/KVr3DixAlWrVpVyPgAX/3qV7n55pt517vexX/4D/+BJUuWcObMGR599FHuuecefvKTnzQ9Q3UeyuUy/+f//B9+8IMfsGnTJlauXMlv/MZvNH38sRnG6urq4ud+7ucKGT+1P/7jP+bmm2/mHe94B3fddRdLliyho6ODJ598kr/7u7/jxhtvTB2xbdhRo+ynN+YYy46yo4pmP42yn96YYyz7yX4qmv00yn56Y46x7Kc26KcsuJUrV2a33XbbOb/2+OOPZ0D27LPPNj3Hxz/+8QwY+ejp6cne+c53Zt/97nebPvZ4R44cydatW5fNnz8/u+iii7Jf+IVfyD784Q9nf/7nf970scfOQ1dXV3bFFVdkt956a/b1r389K5fLTR9/fIaxH4sWLSpk/LE5PvKRjxQ65lhHjhzJPvWpT2VXX311NmPGjGzmzJnZu971ruzuu+/OTp482fTxz/f//8///M8zIDt27FjTM0RgR52t3ftpfI5UHZW6n7IsbUfZTzn76Wz2k/1U5b9DpWc/nc1+sp+q2rGfSlkW/NXVJEmSJEmSNO2Ef00pSZIkSZIkTT8eSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXBdRQ9YqVQ4cuQIPT09lEqlooeXFFCWZRw/fpw5c+bQ0ZHurNx+knQuETrKfpJ0LvaTpKgm20+FH0odOXKE/v7+ooeV1AIGBweZO3dusvHtJ0kXkrKj7CdJF2I/SYpqon4q/FCqp6dn5PNLZxc9Orz8ApABJbj0quLHN4MZomVIPT7Ay0fz/x3bDymk7icIcj9ck2Yww9kZAnSU/WSGKOObIVgG+wkIci/MYIYg44fJMMl+KvxQqvpI56Wz4WNHih4d7p8LJ38Kl82BNYeLH98MZoiWIfX4APfNyUsr9SPfqfsJYtyP1BlSj28GM4wXoaPsJzNEGd8MsTLYT7kI98IMZogyfpQMk+0nX+hckiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYUr/N33pEadOAQHtsPQAJw+DjN6oG8hLFoLM+cVk2EW/SxlLVeykIvp4VWO8yID7GU7xxgsJoSkkFJ3lP0k6XxS9xPYUZLOzX5qXx5KqWUc2QX7tsChHVB6/Rm/rAylzvzzp++C+SthyQaYvaw5GRayjOWsZzEryagA0EEHldc/X8ld7OMhdrKFAfY0J4SkkFJ3lP0k6XxS9xPYUZLOzX6Sv76n8LIMnt0MO26BwUeALC+qrPz616ufZ3DoEXjovXmxZdnU5ljOejawi+tYQQcddNJFJ12UxnzeQQeLuY0N7OZW7pjaAJJCitBR9pOkc4nQT2BHSXoj+0lVHkopvP1b4fE788+zMxf+3urXH9uQXzdVbuUOPspmADqZccHvrX59NVssLakNpO4o+0nS+aTuJ7CjJJ2b/aSqmg+ldu/ezapVq5gzZw6lUok/+ZM/aUIsKXdkV14+9XhsAxzd3XiGhSxjNVvqunY1W1jIexoPoUmxn1S01B1lP7UO+0lFS91PYEe1CvtJRbOfNFbNh1InT57k+uuv56tf/Woz8khn2bcFSnW+8lmpK7++UctZT5nTdV1b5rQn6QWyn1S01B1lP7UO+0lFS91PYEe1CvtJRbOfNFbNS2HFihWsWLGiGVmks5w4lL/gHXX+3nB2Bp5/CE4Mwsz++n7GLPpZzEo66vxN105msIQPM4u5HONwfSE0afaTipS6o+yn1mI/qUip+wnsqFZiP6lI9pPG8zWlFNaB7aPvwFCvUgcc2Fb/9UtZO/IODPXKqLCU2xv6GZLiSd1R9pOk80ndT2BHSTo3+0nj1fnQ3OSdOnWKU6dOjfz18PBws4fUNDE0MDU/Z/hg/ddeycIpSJBxBQum4OdoqtlPakTqjrKfpjf7SY1I3U9gR01n9pMaYT9pvKY/KbVp0yb6+vpGPvr763zGTm3n9PHRtwStV1aG1xr45+TF9NT9WGdVB51cQm9DP0PNYT+pEak7yn6a3uwnNSJ1P4EdNZ3ZT2qE/aTxmn4otXHjRoaGhkY+BgcHmz2kpokZPVDqbOxnlDrhoga64lWOU2nw0c4KZV7BP0GKyH5SI1J3lP00vdlPakTqfgI7ajqzn9QI+0njNf3X97q7u+nu7m72MJqG+qbiqUqgt4GnKl9kKp4vLfESDTxfqqaxn9SI1B1lP01v9pMakbqfwI6azuwnNcJ+0ng1Pyl14sQJnnnmGZ555hkA/vf//t8888wzHDp0aKqzqc0tWgtZYwfYZBVY1MDrz+1lO6UGHygs0cFeGnglPk2a/aQipe4o+6m12E8qUup+AjuqldhPKpL9pPFqvhNPPfUUN9xwAzfccAMAd9xxBzfccAOf/exnpzyc2tvMeTBvJZTqfJ6v1AXzV9X/VqEAxxhkPzsoc7qu68ucZh/f961CC2I/qUipO8p+ai32k4qUup/Ajmol9pOKZD9pvJqXwi233EKWZc3IIr3B9Rvg0EP1XZuVYcn6xjM8ymau58N1XdtBJzvZ2ngITYr9pKKl7ij7qXXYTypa6n4CO6pV2E8qmv2ksZr+QudSI2Yvg5s213ftTXfn1zdqgD08SH3N913uZIA9jYeQFFLqjrKfJJ1P6n4CO0rSudlPGstDKYW3+I7R0proMc/q12/anF83VXaydaS0JnrMs/r1B1nvCbrUBlJ3lP0k6XxS9xPYUZLOzX5SlYdSCq9Uyh/RXLUL5t0GlPK3Aa2+lejI56X866t25d9fKk1tjp1sZTPL2M/DVKhQ5gxlzpBRocxpypyhQoX9PMxmlllWUpuI0FH2k6RzidBPYEdJeiP7SVV1vryYVLzZy/KPE4NwYBsMH4TXhuGi3vwtQRfd3tgL3k3GAHsYYA+zmMtSbucKFnAJvbzCMC9xkL1s8wXvpDaVuqPsJ0nnk7qfwI6SdG72kzyUUsuZ2Q83Jn4zkGMc5mE+nzaEpJBSd5T9JOl8UvcT2FGSzs1+al/++p4kSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKV8qyLCtywOHhYfr6+qAEl80pcuTcy0chq0CpAy6dXfz4ZjBDtAypxwc4eQTIYGhoiN7e3jQhSN9PEON+pM6QenwzmGG8CB1lP5khyvhmiJXBfspFuBdmMEOU8aNkmGw/pTuUkqRxwhxKSdI5hPiPPkk6B/tJUlQT9VNXgVnO5pNSZjBDiAypx4fRU/Qw/JO+tl+TZjDDWKE6yn5q+wypxzdDrAz2Uy7CvTCDGaKMHyXDZPsp2aHUpVfBmsPFj3v/XDj50/zGpBjfDGaIliH1+AD3zcmLM4pU/QQx7kfqDKnHN4MZxovUUfaTGVKPb4ZYGeynXIR7YQYzRBk/SobJ9pMvdC5JkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCpXv3PdXlxCE4sB2GBuD0cZjRA30LYdFamDmvPTKkHh9gFv0sZS1XspCL6eFVjvMiA+xlO8cYbJsM0lgR9qYZYnRDhAzSWKn3pRlGReiHCBmkqgj70gy5CN0QIUPRPJRqEUd2wb4tcGhH/raOAFkZSp3550/fBfNXwpINMHvZ9MyQenyAhSxjOetZzEoyKgB00EHl9c9Xchf7eIidbGGAPdM2gzRWhL1phhjdECGDNFbqfWmGURH6IUIGqSrCvjRDLkI3RMiQir++F1yWwbObYcctMPgIkOWbNCu//vXq5xkcegQeem++qbNs+mRIPX7VctazgV1cxwo66KCTLjrpojTm8w46WMxtbGA3t3LH1AYIkkGqirA3zZCL0A0RMkhVEfalGUZF6IcIGSSIsS/NMCpCN0TIkJKHUsHt3wqP35l/np258PdWv/7Yhvy66ZIh9fgAt3IHH2UzAJ3MuOD3Vr++mi1TWhgRMkhjRdibZojRDREySGOl3pdmGBWhHyJkkKoi7Esz5CJ0Q4QMqXkoFdiRXfnGq8djG+Do7tbPkHp8yB+lXM2Wuq5dzRYW8p5pkUEaK8LeNEOMboiQQRor9b40w6gI/RAhg1QVYV+aIRehGyJkiKCmQ6lNmzbxzne+k56eHq688kp+9Vd/lQMHDjQrW9vbtwVKdb7qV6krv77VM6QeH/LHKcucruvaMqen5BQ7Qobo7KdiRdibZojRDREytAI7qjip96UZRkXohwgZorOfihNhX5ohF6EbImSIoKZDqV27drFu3Toee+wxHn30UU6fPs0HPvABTp482ax8bevEofzF3iZ6lPF8sjPw/ENwooEX6E+dIfX4kL/7wWJWTvgo5fl0MoMlfJhZzG3pDK3AfipOhL1phhjdECFDq7CjipF6X5phVIR+iJChFdhPxYiwL82Qi9ANETJEUdOh1A9+8APWrl3Ltddey/XXX8/27ds5dOgQTz/9dLPyta0D20fffaBepQ44sK11M6QeH2Apa0fe/aBeGRWWcntLZ2gF9lNxIuxNM8TohggZWoUdVYzU+9IMoyL0Q4QMrcB+KkaEfWmGXIRuiJAhijofmssNDQ0B8OY3v/m833Pq1ClOnTo18tfDw8ONDNk2hgam5ucMH2zdDKnHB7iShVOQIOMKFrR0hlZkPzVPhL1phhjdECFDq5qoo+yn+qTel2YYFaEfImRoRfZTc0TYl2bIReiGCBmiqPuMslKp8Pu///vcfPPNXHfddef9vk2bNtHX1zfy0d/fX++QbeX08dG3w6xXVobXGvhnROoMqccHuJgeOhp8P4AOOrmE3pbO0Grsp+aKsDfNEKMbImRoRZPpKPupPqn3pRlGReiHCBlajf3UPBH2pRlyEbohQoYo6p6FdevW8Td/8zc88MADF/y+jRs3MjQ0NPIxONjAL3+2kRk9UOps7GeUOuGiBtZo6gypxwd4leNUGnysskKZV6i/NSNkaDX2U3NF2JtmiNENETK0osl0lP1Un9T70gyjIvRDhAytxn5qngj70gy5CN0QIUMUdf363qc+9Sl27NjB7t27mTv3wi+s1d3dTXd3d13h2lnfVDzNB/Q28DRf6gypxwd4kal4vrTES9T/fGmEDK3Efmq+CHvTDDG6IUKGVjPZjrKf6pN6X5phVIR+iJChldhPzRVhX5ohF6EbImSIoqYnpbIs41Of+hTf+973+NGPfsTVV1/drFxtb9FayBo7OCWrwKIGXvcsdYbU4wPsZTulBh+rLNHBXup/Jb4IGVqB/VScCHvTDDG6IUKGVmFHFSP1vjTDqAj9ECFDK7CfihFhX5ohF6EbImSIoqZZWLduHffddx/f/OY36enp4YUXXuCFF17glVdeaVa+tjVzHsxbCaU6X4q+1AXzV8HMBn7FO3WG1OMDHGOQ/eygzOm6ri9zmn18n2McbukMrcB+Kk6EvWmGGN0QIUOrsKOKkXpfmmFUhH6IkKEV2E/FiLAvzZCL0A0RMkRR06HUPffcw9DQELfccguzZ88e+fj2t7/drHxt7foNkJ2p79qsDEvWt36G1OMDPMpmOplR17UddLKTrdMiQ3T2U7Ei7E0zxOiGCBlagR1VnNT70gyjIvRDhAzR2U/FibAvzZCL0A0RMkRQ86/vnetj7dq1TYrX3mYvg5s213ftTXfn17d6htTjAwywhwepr/m+y50MsGdaZIjOfipWhL1phhjdECFDK7CjipN6X5phVIR+iJAhOvupOBH2pRlyEbohQoYIGvslRjXd4jtGN+xEjzhWv37T5vy66ZIh9fgAO9k6UhgTPWJZ/fqDrJ/S0+sIGaSxIuxNM8TohggZpLFS70szjIrQDxEySFUR9qUZchG6IUKG1DyUCq5Uyh9PXLUL5t0GlPK3wKy+jebI56X866t25d9fKk2fDKnHr9rJVjazjP08TIUKZc5Q5gwZFcqcpswZKlTYz8NsZllTiiJCBqkqwt40Qy5CN0TIIFVF2JdmGBWhHyJkkCDGvjTDqAjdECFDSnW+vJiKNntZ/nFiEA5sg+GD8NowXNSbvx3motsbe7G3VsiQenzIH7EcYA+zmMtSbucKFnAJvbzCMC9xkL1sa/qLzUXIII0VYW+aIUY3RMggjZV6X5phVIR+iJBBqoqwL82Qi9ANETKk4qFUi5nZDzd+tr0zpB4f4BiHeZjPt30GaawIe9MMMbohQgZprNT70gyjIvRDhAxSVYR9aYZchG6IkKFo/vqeJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSClfKsiwrcsDh4WH6+vqgBJfNKXLk3MtHIatAqQMunV38+GYwQ7QMqccHOHkEyGBoaIje3t40IUjfTxDjfqTOkHp8M5hhvAgdZT+ZIcr4ZoiVwX7KRbgXZjBDlPGjZJhsP6U7lJKkccIcSknSOYT4jz5JOgf7SVJUE/VTV4FZzuaTUmYwQ4gMqceH0VP0MPyTvrZfk2Yww1ihOsp+avsMqcc3Q6wM9lMuwr0wgxmijB8lw2T7Kdmh1KVXwZrDxY97/1w4+dP8xqQY3wxmiJYh9fgA983JizOKVP0EMe5H6gypxzeDGcaL1FH2kxlSj2+GWBnsp1yEe2EGM0QZP0qGyfaTL3QuSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMIle/e9VjSLfpaylitZyMX08CrHeZEB9rKdYwymjleYE4fgwHYYGoDTx2FGD/QthEVrYea86T8+xFgLEeZBcURYkxFE2BepM0RYCxEyKA7XQy51N0TJEGE9RMigOFwPMbohQoYIayFChqJ5KDUJC1nGctazmJVkVADooIPK65+v5C728RA72cIAe1JGbaoju2DfFji0A0qvP2OXlaHUmX/+9F0wfyUs2QCzl02/8SHGWogwD4ojwpqMIMK+SJ0hwlqIkEFxuB5yqbshSoYI6yFCBsXheojRDREyRFgLETKk4q/vTWA569nALq5jBR100EkXnXRRGvN5Bx0s5jY2sJtbuSN15CmXZfDsZthxCww+AmR5UWTl179e/TyDQ4/AQ+/NiyXLpsf4VanXQpR5UByp12QEEfZFhAwR1kKEDIrD9RCjGyJkgBjrIUIGxdHu6yFCN0TIADHWQoQMKXkodQG3cgcfZTMAncy44PdWv76aLdNukezfCo/fmX+enbnw91a//tiG/LrpMD7EWAsR5kFxRFiTEUTYF6kzRFgLETIoDtdDLnU3RMkQYT1EyKA4XA8xuiFChghrIUKG1Go6lLrnnntYsmQJvb299Pb28u53v5tHHnmkWdmSWsgyVrOlrmtXs4WFvGeKE6VxZFe++evx2AY4uru1x4cYayHCPERnP02O/ZSbqn2ROkOEtRAhQytol45yPeRSd0OUDBHWQ4QM0bVLP4HrAWJ0Q4QMEdZChAwR1HQoNXfuXL70pS/x9NNP89RTT/Erv/IrfOQjH+F//s//2ax8ySxnPWVO13VtmdPT5uRy3xYo1fnKY6Wu/PpWHh9irIUI8xCd/TQ59lNuqvZF6gwR1kKEDK2gXTrK9ZBL3Q1RMkRYDxEyRNcu/QSuB4jRDREyRFgLETJEUNOh1KpVq7jttttYuHAhb3vb2/jCF77AzJkzeeyxx5qVL4lZ9LOYlRM+Pnc+ncxgCR9mFnOnOFmxThzKX3Buoscpzyc7A88/BCfqfJOA1ONDjLUQYR5agf00OfZTbir2ReoMEdZChAytoh06yvWQS90NUTJEWA8RMrSCdugncD1AjG6IkCHCWoiQIYq6X1OqXC7zwAMPcPLkSd797ndPZabklrJ25BXv65VRYSm3T1GiNA5sH30HhHqVOuDAttYcH2KshQjz0Grspwuzn3KN7ovUGSKshQgZWtF07SjXQy51N0TJEGE9RMjQaqZrP4HrAWJ0Q4QMEdZChAxR1PzQ3P79+3n3u9/Nq6++ysyZM/ne977HL/3SL533+0+dOsWpU6dG/np4eLi+pAW6koVT8FMyrmDBFPycdIYGpubnDB9szfEhxlqIMA+twn6aLPupqpF9kTpDhLUQIUMrqaWj7KfWlbobomSIsB4iZGgV072fwPUAMbohQoYIayFChihqPqNctGgRzzzzDI8//ji/8zu/w8c//nH+9m//9rzfv2nTJvr6+kY++vv7GwpchIvpoaPBNybsoJNL6J2iRGmcPj76lpz1ysrwWp3/nEo9PsRYCxHmoVXYT5NjP+Ua3RepM0RYCxEytJJaOsp+al2puyFKhgjrIUKGVjHd+wlcDxCjGyJkiLAWImSIouZZuOiii1iwYAE33ngjmzZt4vrrr+eP/uiPzvv9GzduZGhoaORjcDD+C9u8ynEqDT5KV6HMK7T2KcCMHih1NvYzSp1wUZ37JPX4EGMtRJiHVmE/TY79lGt0X6TOEGEtRMjQSmrpKPupdaXuhigZIqyHCBlaxXTvJ3A9QIxuiJAhwlqIkCGKOl/zflSlUjnr8c3xuru76e7ubnSYQr3IVDxTWOIlWvv3pfqm4olCoLfOJwpTjw8x1kKEeWhV9tP52E9VjeyL1BkirIUIGVrZhTrKfmpdqbshSoYI6yFChlY13foJXA8QoxsiZIiwFiJkiKKmJ6U2btzI7t27ee6559i/fz8bN27kxz/+MWvWrGlWviT2sp1Sg4/SlehgL639ytKL1kLW2OEtWQUW1fnaa6nHhxhrIcI8tAL7afLsp1yj+yJ1hghrIUKGVtEOHeV6yKXuhigZIqyHCBlaQTv0E7geIEY3RMgQYS1EyBBFTbPw4osv8hu/8RssWrSI97///Tz55JP86Z/+KcuXL29WviSOMch+dlDmdF3XlznNPr7PMQ5PcbJizZwH81ZCqc7n6UpdMH8VzKzz18xTjw8x1kKEeWgF9tPk2E+5qdgXqTNEWAsRMrSKdugo10MudTdEyRBhPUTI0AraoZ/A9QAxuiFChghrIUKGKGpaCvfee2+zcoTzKJu5ng/XdW0Hnexk6xQnSuP6DXDoofquzcqwZH1rjw8x1kKEeYjOfpoc+yk3VfsidYYIayFChlbQLh3lesil7oYoGSKshwgZomuXfgLXA8TohggZIqyFCBkiaOx5sWlsgD08SH2r/bvcyQB7pjhRGrOXwU2b67v2prvz61t5fIixFiLMg+KIsCYjiLAvUmeIsBYiZFAcrodc6m6IkiHCeoiQQXG4HmJ0Q4QMEdZChAwReCh1ATvZOrJIJnqsrvr1B1k/bU4sqxbfMVoaEz1mWf36TZvz66bD+BBjLUSYB8URYU1GEGFfpM4QYS1EyKA4XA+51N0QJUOE9RAhg+JwPcTohggZIqyFCBlS81BqAjvZymaWsZ+HqVChzBnKnCGjQpnTlDlDhQr7eZjNLJtWi6OqVMofkVy1C+bdBpTyt+GsvpXnyOel/OurduXfXypNj/GrUq+FKPOgOFKvyQgi7IsIGSKshQgZFIfrIUY3RMgAMdZDhAyKo93XQ4RuiJABYqyFCBlSqvPlxdrLAHsYYA+zmMtSbucKFnAJvbzCMC9xkL1smxYvMDaR2cvyjxODcGAbDB+E14bhot78LTkX3d7cF9NOPT7EWAsR5kFxRFiTEUTYF6kzRFgLETIoDtdDLnU3RMkQYT1EyKA4XA8xuiFChghrIUKGVDyUqsExDvMwn08dI7mZ/XDjZ9t3fIixFiLMg+KIsCYjiLAvUmeIsBYiZFAcrodc6m6IkiHCeoiQQXG4HmJ0Q4QMEdZChAxF89f3JEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLhSlmVZkQMODw/T19cHJbhsTpEj514+ClkFSh1w6ezixzeDGaJlSD0+wMkjQAZDQ0P09vamCUH6foIY9yN1htTjm8EM40XoKPvJDFHGN0OsDPZTLsK9MIMZoowfJcNk+yndoZQkjRPmUEqSziHEf/RJ0jnYT5KimqifugrMcjaflDKDGUJkSD0+jJ6ih+Gf9LX9mjSDGcYK1VH2U9tnSD2+GWJlsJ9yEe6FGcwQZfwoGSbbT8kOpS69CtYcLn7c++fCyZ/mNybF+GYwQ7QMqccHuG9OXpxRpOoniHE/UmdIPb4ZzDBepI6yn8yQenwzxMpgP+Ui3AszmCHK+FEyTLaffKFzSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFS7du++pLrPoZylruZKFXEwPr3KcFxlgL9s5xmAhGU4cggPbYWgATh+HGT3QtxAWrYWZ85o/vnMgxeTezKWehwhzEEHq+6BYIqyHCHvTeYghwn1QHBHWQ4R96TzEUfS98FCqRSxkGctZz2JWklEBoIMOKq9/vpK72MdD7GQLA+xpSoYju2DfFji0I39rSYCsDKXO/POn74L5K2HJBpi9bOrHdw6kmNybudTzEGEOIkh9HxRLhPUQYW86DzFEuA+KI8J6iLAvnYc4Ut0Lf32vBSxnPRvYxXWsoIMOOumiky5KYz7voIPF3MYGdnMrd0zp+FkGz26GHbfA4CNAlm/SrPz616ufZ3DoEXjovfmmzrKpy+AcSDG5N3Mp5yHKHESQej0qltTrIcredB5iSH0fFEvq9RBlXzoPcaS8Fx5KBXcrd/BRNgPQyYwLfm/166vZMqWLZP9WePzO/PPszIW/t/r1xzbk100F50CKyb2ZSz0PEeYggtT3QbFEWA8R9qbzEEOE+6A4IqyHCPvSeYgj9b3wUCqwhSxjNVvqunY1W1jIexrOcGRXvvHq8dgGOLq7sfGdAykm92Yu9TxEmIMIUt8HxRJhPUTYm85DDBHug+KIsB4i7EvnIY4I96KhQ6kvfelLlEolfv/3f7/hIHqj5aynzOm6ri1zekpOLvdtgVKdrzxW6sqvb4RzoHrZT83l3sylnocIcxBB6vtQK/upuSKshwh703mIIcJ9qJUd1TwR1kOEfek8xBHhXtR9KPXkk0/yX/7Lf2HJkiUNh9AbzaKfxayc8PG58+lkBkv4MLOYW3eGE4fyF3ub6FHG88nOwPMPwYk6X6DfOVC97Kfmcm/mUs9DhDmIIPV9qJX91FwR1kOEvek8xBDhPtTKjmqeCOshwr50HuKIcC+gzkOpEydOsGbNGr72ta8xa9ashgLo3JayduQV7+uVUWEpt9d9/YHto+8+UK9SBxzYVt+1zoHqYT81n3szl3oeIsxBBKnvQy3sp+aLsB4i7E3nIYYI96EWdlRzRVgPEfal8xBHhHsBdR5KrVu3jg996EPceuutE37vqVOnGB4ePutDE7uShVPwUzKuYEHdVw8NTEEEYPhgfdc5B6qH/dR87s1c6nmIMAcRpL4PtbCfmi/CeoiwN52HGCLch1pMtqPsp/pEWA8R9qXzEEeEewFQ829RPvDAA/zVX/0VTz755KS+f9OmTXzuc5+rOVi7u5geOhp8HfoOOrmE3rqvP3189O0w65WV4bU6/znlHKhW9lMx3Ju51PMQYQ4iSH0fJst+KkaE9RBhbzoPMUS4D5NVS0fZT/WJsB4i7EvnIY4I9yL/GTUYHBzk05/+NPfffz8XX3zxpK7ZuHEjQ0NDIx+Dgy3+i5cFeZXjVBp8lK5CmVeof6fM6IFSZ0MRKHXCRXWuUedAtbCfiuPezKWehwhzEEHq+zAZ9lNxIqyHCHvTeYghwn2YjFo7yn6qT4T1EGFfOg9xRLgXUOOTUk8//TQvvvgib3/720f+XrlcZvfu3XzlK1/h1KlTdHaefXe7u7vp7u5uKGQ7epGpeKawxEvU/0xh31Q8zQf01vk0n3OgWthPxXFv5lLPQ4Q5iCD1fZgM+6k4EdZDhL3pPMQQ4T5MRq0dZT/VJ8J6iLAvnYc4ItwLqPFJqfe///3s37+fZ555ZuTjHe94B2vWrOGZZ555w79QqX572U6pwUfpSnSwl/pffW3RWsgaOzglq8CiOl/3zDlQLeyn4rg3c6nnIcIcRJD6PkyG/VScCOshwt50HmKIcB8mw44qRoT1EGFfOg9xRLgXUOOhVE9PD9ddd91ZH5dddhmXX3451113XUNBdLZjDLKfHZQ5Xdf1ZU6zj+9zjMN1Z5g5D+athFLNrzyWK3XB/FUws7++650D1cJ+Ko57M5d6HiLMQQSp78Nk2E/FibAeIuxN5yGGCPdhMuyoYkRYDxH2pfMQR4R7AXW++56K8Sib6WRGXdd20MlOtjac4foNkJ2p79qsDEvWNza+cyDF5N7MpZ6HCHMQQer7oFgirIcIe9N5iCHCfVAcEdZDhH3pPMQR4V40fCj14x//mC9/+csNB9EbDbCHB6lvtX+XOxlgT8MZZi+DmzbXd+1Nd+fXN8I5UCPsp+Zxb+ZSz0OEOYgg9X2oh/3UPBHWQ4S96TzEEOE+1MOOao4I6yHCvnQe4ohwL3xSKridbB1ZJBM9Vlf9+oOsn9I/VVl8x+iGnegRx+rXb9qcXzcVnAMpJvdmLvU8RJiDCFLfB8USYT1E2JvOQwwR7oPiiLAeIuxL5yGO1PfCQ6kWsJOtbGYZ+3mYChXKnKHMGTIqlDlNmTNUqLCfh9nMsin/B1iplD+euGoXzLsNKOVvgVl9G82Rz0v511ftyr+/VJq6DM6BFJN7M5dyHqLMQQSp16NiSb0eouxN5yGG1PdBsaReD1H2pfMQR8p7UedLe6loA+xhgD3MYi5LuZ0rWMAl9PIKw7zEQfayrekvgjh7Wf5xYhAObIPhg/DaMFzUm78d5qLbm/tib86BFJN7M5d6HiLMQQSp74NiibAeIuxN5yGGCPdBcURYDxH2pfMQR6p74aFUiznGYR7m80kzzOyHGz+bbnznQIrJvZlLPQ8R5iCC1PdBsURYDxH2pvMQQ4T7oDgirIcI+9J5iKPoe+Gv70mSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcKUsy7IiBxweHqavrw9KcNmcIkfOvXwUsgqUOuDS2cWPbwYzRMuQenyAk0eADIaGhujt7U0TgvT9BDHuR+oMqcc3gxnGi9BR9pMZooxvhlgZ7KdchHthBjNEGT9Khsn2U7pDKUkaJ8yhlCSdQ4j/6JOkc7CfJEU1UT91FZjlbD4pZQYzhMiQenwYPUUPwz/pa/s1aQYzjBWqo+ynts+QenwzxMpgP+Ui3AszmCHK+FEyTLafkh1KXXoVrDlc/Lj3z4WTP81vTIrxzWCGaBlSjw9w35y8OKNI1U8Q436kzpB6fDOYYbxIHWU/mSH1+GaIlcF+ykW4F2YwQ5Txo2SYbD/5QueSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXLp331NdThyCA9thaABOH4cZPdC3EBathZnziskwi36WspYrWcjF9PAqx3mRAfaynWMMNn38CHNgBumNIqzJ1P0E6ech9fhRMkhjRViT9pMZFFPqvZl6/CgZIuxLM6ThoVSLOLIL9m2BQzvyt3UEyMpQ6sw/f/oumL8SlmyA2cuak2Ehy1jOehazkowKAB10UHn985XcxT4eYidbGGDPlI8fYQ7MIL1RhDWZup8g/TykHj9KBmmsCGvSfjKDYkq9N1OPHyVDhH1phrT89b3gsgye3Qw7boHBR4AsX5xZ+fWvVz/P4NAj8NB788WcZVObYznr2cAurmMFHXTQSReddFEa83kHHSzmNjawm1u5Y8rGjjAHZpDeKMqaTNlPkH4eUo8fJYM0VpQ12e79ZAZFlXpvph4/QoYI+9IMMXgoFdz+rfD4nfnn2ZkLf2/1649tyK+bKrdyBx9lMwCdzLjg91a/vpotU1ZcEebADNIbRViTqfsJ0s9D6vGjZJDGirAm7SczKKbUezP1+FEyRNiXZoihpkOpu+66i1KpdNbHNddc06xsbe/IrnzB1eOxDXB0d+MZFrKM1Wyp69rVbGEh72lo/AhzYIbWYD8VK8KaTN1PkH4eUo8fJUMrsKOKE2FN2k9maCXt1E+p92bq8aNkiLAvzRBHzU9KXXvttRw9enTk4y/+4i+akUvkj+WV6nzVr1JXfn2jlrOeMqfrurbM6YZP0yPMgRlah/1UnAhrMnU/Qfp5SD1+lAytwo4qRoQ1aT+ZodW0Sz+l3pupx4+SIcK+NEMcNU9BV1cXV111VTOyaIwTh/IXOaPO3xXNzsDzD8GJQZjZX9/PmEU/i1lJR52/5dnJDJbwYWYxl2Mcrvn6CHNghtZiPxUjwppM3U+Qfh5Sjx8lQyuxo5ovwpq0n8zQitqhn1LvzdTjR8kQYV+aIZaaV+PAwABz5szhLW95C2vWrOHQoUPNyNX2DmwffdX9epU64MC2+q9fytqRd2GoV0aFpdxe17UR5sAMrcV+KkaENZm6nyD9PKQeP0qGVmJHNV+ENWk/maEVtUM/pd6bqcePkiHCvjRDLDU9KfXLv/zLbN++nUWLFnH06FE+97nP8Z73vIe/+Zu/oaen55zXnDp1ilOnTo389fDwcGOJ28TQwNT8nOGD9V97JQunIEHGFSyo68oIc2CG1mE/FSfCmkzdT5B+HlKPHyVDq6i1o+yn+kRYk/aTGVpNu/RT6r2ZevwoGSLsSzPEUtOh1IoVK0Y+X7JkCb/8y7/M/Pnz+c53vsNv/uZvnvOaTZs28bnPfa6xlG3o9PHRt4GsV1aG1xr4Z8TF9NT9aGdVB51cQm9d10aYAzO0DvupOBHWZOp+gvTzkHr8KBlaRa0dZT/VJ8KatJ/M0GrapZ9S783U40fJEGFfmiGWhlbkm970Jt72trdx8OD5j+c2btzI0NDQyMfg4GAjQ7aNGT1Q6mzsZ5Q64aL6+4JXOU6lwcc7K5R5hfp2SoQ5MEPrsp+aJ8KaTN1PkH4eUo8fJUOrmqij7Kf6RFiT9pMZWt107afUezP1+FEyRNiXZoiloUOpEydO8L/+1/9i9uzZ5/2e7u5uent7z/rQxPqm4slKoLf+Jyt5kal4prDES9T3TGGEOTBD67KfmifCmkzdT5B+HlKPHyVDq5qoo+yn+kRYk/aTGVrddO2n1Hsz9fhRMkTYl2aIpaZDqQ0bNrBr1y6ee+459u7dyz/5J/+Ezs5Ofv3Xf71Z+drWorWQNXaITVaBRfW/Bh172U6pwcc7S3Swl/pefS3CHJihddhPxYmwJlP3E6Sfh9TjR8nQKuyoYkRYk/aTGVpNu/RT6r2ZevwoGSLsSzPEUtOKPHz4ML/+67/OokWL+Kf/9J9y+eWX89hjj3HFFVc0K1/bmjkP5q2EUk2v+jWq1AXzVzX29pDHGGQ/Oyhzuq7ry5xmH9+v++1CI8yBGVqH/VScCGsydT9B+nlIPX6UDK3CjipGhDVpP5mh1bRLP6Xem6nHj5Ihwr40Qyw1HUo98MADHDlyhFOnTnH48GEeeOAB3vrWtzYrW9u7fgNkZ+q7NivDkvWNZ3iUzXQyo65rO+hkJ1sbGj/CHJihNdhPxYqwJlP3E6Sfh9TjR8nQCuyo4kRYk/aTGVpJO/VT6r2ZevwoGSLsSzPE0dize2qq2cvgps31XXvT3fn1jRpgDw9S32r/LncywJ6Gxo8wB2aQ3ijCmkzdT5B+HlKPHyWDNFaENWk/mUExpd6bqcePkiHCvjRDHB5KBbf4jtGFOtGjfdWv37Q5v26q7GTrSHFN9Khn9esPsn5KTtEhxhyYQXqjCGsydT9B+nlIPX6UDNJYEdak/WQGxZR6b6YeP0qGCPvSDDF4KBVcqZQ/lrdqF8y7DSjlb/1YffvIkc9L+ddX7cq/v1Sa2hw72cpmlrGfh6lQocwZypwho0KZ05Q5Q4UK+3mYzSyb0sKKMAdmkN4oyppM2U+Qfh5Sjx8lgzRWlDXZ7v1kBkWVem+mHj9Chgj70gwx1PmyWira7GX5x4lBOLANhg/Ca8NwUW/+NpCLbm/+i5wNsIcB9jCLuSzldq5gAZfQyysM8xIH2cu2hl70biIR5sAM0htFWJOp+wnSz0Pq8aNkkMaKsCbtJzMoptR7M/X4UTJE2JdmSMtDqRYzsx9u/GzaDMc4zMN8Ptn4EebADNIbRViTqfsJ0s9D6vGjZJDGirAm7SczKKbUezP1+FEyRNiXZkjDX9+TJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4UpZlmVFDjg8PExfXx+U4LI5RY6ce/koZBUodcCls4sf3wxmiJYh9fgAJ48AGQwNDdHb25smBOn7CWLcj9QZUo9vBjOMF6Gj7CczRBnfDLEy2E+5CPfCDGaIMn6UDJPtp3SHUpI0TphDKUk6hxD/0SdJ52A/SYpqon7qKjDL2XxSygxmCJEh9fgweooehn/S1/Zr0gxmGCtUR9lPbZ8h9fhmiJXBfspFuBdmMEOU8aNkmGw/JTuUuvQqWHO4+HHvnwsnf5rfmBTjm8EM0TKkHh/gvjl5cUaRqp8gxv1InSH1+GYww3iROsp+MkPq8c0QK4P9lItwL8xghijjR8kw2X7yhc4lSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuHTvvteCThyCA9thaABOH4cZPdC3EBathZnzUqcrjvMQYw7MoLG8FznnIcYcmEFjeS9yzkMuwjykzpB6fJ3N++EcVEWYh3bM4KHUJBzZBfu2wKEd+VsqAmRlKHXmnz99F8xfCUs2wOxlyWI2nfMQYw7MoLG8FznnIcYcmEFjeS9yzkMuwjykzpB6fJ3N++EcVEWYh3bO4K/vXUCWwbObYcctMPgIkOU3JSu//vXq5xkcegQeem9+E7MsYegmcB5izIEZNJb3Iuc8xJgDM2gs70XOechFmIfUGVKPr7N5P5yDqgjzYAYPpS5o/1Z4/M788+zMhb+3+vXHNuTXTSfOQ4w5MIPG8l7knIcYc2AGjeW9yDkPuQjzkDpD6vF1Nu+Hc1AVYR7M4KHUeR3ZlU90PR7bAEd3T22eVJyHGHNgBo3lvcg5DzHmwAway3uRcx5yEeYhdYbU4+ts3g/noCrCPJghV/Oh1E9/+lM+9rGPcfnll3PJJZewePFinnrqqcaTBLNvC5TqfMWtUld+/XTgPMSYAzNMjv00semyL8F5gBhzYIbJa4eOapV70WzOQy7CPKTOkHr8yWqHfoLWuR/N5BzkIsyDGXI1HUodO3aMm2++mRkzZvDII4/wt3/7t2zZsoVZs2Y1niSQE4fyF/ea6NG188nOwPMPwYnBqc1VNOchxhyYYXLsp8mZDvsSnAeIMQdmmLx26KhWuRfN5jzkIsxD6gypx5+sdugnaJ370UzOQS7CPJhhVE2HUn/4h39If38/27Zt413vehdXX301H/jAB3jrW9/aWIpgDmwffbX5epU64MC2KYmTjPMQYw7MMDn20+S1+r4E5wFizIEZJq8dOqpV7kWzOQ+5CPOQOkPq8SerHfoJWud+NJNzkIswD2YYVVOE73//+7zjHe9g9erVXHnlldxwww187Wtfu+A1p06dYnh4+KyP6IYGpubnDB+cmp+TivMQYw7MMDn2U21aeV+C8wAx5sAMk1drR9lPrct5yEWYh9QZUo8/We3QT9A696OZnINchHkww6iaDqX+4R/+gXvuuYeFCxfyp3/6p/zO7/wOv/d7v8c3vvGN816zadMm+vr6Rj76+/sbS1yA08dH3/6wXlkZXmuNfj4v5yHGHJhhcuynyWv1fQnOA8SYAzNMXq0dZT+1LuchF2EeUmdIPf5ktUM/Qevcj2ZyDnIR5sEMo2o6lKpUKrz97W/ni1/8IjfccAP/4l/8C377t3+b//yf//N5r9m4cSNDQ0MjH4OD8X8BdUYPlDob+xmlTriod2rypOI8xJgDM0yO/TR5rb4vwXmAGHNghsmrtaPsp9blPOQizEPqDKnHn6x26CdonfvRTM5BLsI8mGFUTYdSs2fP5pd+6ZfO+nv/6B/9Iw4dOnTea7q7u+nt7T3rI7q+hVPzc3oXTM3PScV5iDEHZpgc+6k2rbwvwXmAGHNghsmrtaPsp9blPOQizEPqDKnHn6x26CdonfvRTM5BLsI8mGFUTYdSN998MwcOHDjr7/393/898+fPbyxFMIvWQlZp7GdkFVh0+5TEScZ5iDEHZpgc+2nyWn1fgvMAMebADJPXDh3VKvei2ZyHXIR5SJ0h9fiT1Q79BK1zP5rJOchFmAczjKrpUOpf/+t/zWOPPcYXv/hFDh48yDe/+U3+63/9r6xbt66xFMHMnAfzVkKpq77rS10wfxXMbI1frz4v5yHGHJhhcuynyZkO+xKcB4gxB2aYvHboqFa5F83mPOQizEPqDKnHn6x26CdonfvRTM5BLsI8mGFUTYdS73znO/ne977Ht771La677jo+//nP8+Uvf5k1a9Y0liKg6zdAdqa+a7MyLFk/tXlScR5izIEZJmY/Tc502ZfgPECMOTDD5LRLR7XCvSiC85CLMA+pM6QefzLapZ+gNe5HszkHuQjzYIZcTYdSACtXrmT//v28+uqr/OQnP+G3f/u3G08R0OxlcNPm+q696e78+unAeYgxB2aYHPtpYtNlX4LzADHmwAyT1w4d1Sr3otmch1yEeUidIfX4k9UO/QStcz+ayTnIRZgHM+RqPpRqJ4vvGL1BEz3SVv36TZvz66YT5yHGHJhBY3kvcs5DjDkwg8byXuSch1yEeUidIfX4Opv3wzmoijAPZvBQ6oJKpfxxtFW7YN5tQCl/y8Pq2yaOfF7Kv75qV/79pVLK1FPPeYgxB2bQWN6LnPMQYw7MoLG8FznnIRdhHlJnSD2+zub9cA6qIsyDGaDOl7RqL7OX5R8nBuHANhg+CK8Nw0W9+dsfLrq99V/sbTKchxhzYAaN5b3IOQ8x5sAMGst7kXMechHmIXWG1OPrbN4P56Aqwjy0cwYPpWowsx9u/GzqFOk5DzHmwAway3uRcx5izIEZNJb3Iuc85CLMQ+oMqcfX2bwfzkFVhHloxwz++p4kSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSClfKsiwrcsDh4WH6+vqgBJfNKXLk3MtHIatAqQMunV38+GYwQ7QMqccHOHkEyGBoaIje3t40IUjfTxDjfqTOkHp8M5hhvAgdZT+ZIcr4ZoiVwX7KRbgXZjBDlPGjZJhsP6U7lJKkccIcSknSOYT4jz5JOgf7SVJUE/VTV4FZzuaTUmYwQ4gMqceH0VP0MPyTvrZfk2Yww1ihOsp+avsMqcc3Q6wM9lMuwr0wgxmijB8lw2T7Kdmh1KVXwZrDxY97/1w4+dP8xqQY3wxmiJYh9fgA983JizOKVP0EMe5H6gypxzeDGcaL1FH2kxlSj2+GWBnsp1yEe2EGM0QZP0qGyfaTL3QuSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwqV79z21rBOH4MB2GBqA08dhRg/0LYRFa2HmvNTpVKRZ9LOUtVzJQi6mh1c5zosMsJftHGMwdTy1IftJVfaTorGfVOVaUDSuSY1V9HrwUEqTdmQX7NsCh3bkby0JkJWh1Jl//vRdMH8lLNkAs5cli6kCLGQZy1nPYlaSUQGggw4qr3++krvYx0PsZAsD7EkZVf+fvbsPsvK87/v/PruLVg/srrEsRRBAkQ1GjQQaWbYjozGWY+EaGexkYtpmcGPkpL82lhOnArWmM3HlujbOCBh3ake//lwZ3JFs+WHqjIVGToQdAxmCnhIJ0jhkaSqzGFRpWrwLSFrB2fv3x62zuyBgz+N9fc+e92tmJ0c+e+/1yXV9r6/Qxb336RD2J1XYnxSN/UkV1oKisSY1Wap68Nf3NKUsg2c3wfZbYehRIMuLMyu/9n7ldQaHHoWH35MXc5YlDK2WWc461rOT61lBF11000M3PZQmve6ii8Xcznp2cRt3pY6sacz+pMnsT4rE/qQKa0HRWJOaLHU9eCilKe3fAo/fnb/OTl/4eyvv712fX6fp5Tbu4iNsAqCbGRf83sr7q9nsf/ipZexPqrA/KRr7kyqsBUVjTWqy1PVQ06HUL/3SL1EqlV73deeddzYnjcI5sjMvuHrsXQ9HdzU3j9JZyDJWs7mua1ezmYW8u8mJXs8e1VnsT6qwPyka+5Mq2qEW7E+dpR1qUsWJUA81HUo9+eSTHD16dPzrscceA2D16tWNJ1FI+zZDqc4nj5V68us1PSxnHWVO1XVtmVOF3I1gj+os9idV2J8Ujf1JFe1QC/anztIONaniRKiHmoa/4oorzvjnL37xi7zlLW/hPe95T+NJFM6JQ/lDzqjzd0Wz0/DTh+HEEMyc19RoKtgs5rGYlXTV+Ru/3cxgCR9iFnM5xuEmp5tgj+oc9idV2J8Ujf1JFe1SC/anztEuNaliRKmHup8p9eqrr/LAAw/w8Y9/nFKpVH8ChXVg28RT9+tV6oIDW5sSRwktZe34p1jVK2OMpdzRpERTs0dNb/YnVdifFI39SRXtWAv2p+mtHWtSrROlHuq8UQv+5E/+hJ///OesXbv2gt83OjrK6Ojo+D+PjIzUO6QKNjzYnJ8zcrA5P0fpXMnCJvyUjCtY0ISfU51qepT9qX3Zn1Rhf1I09idVtGMt2J+mt3asSbVOlHqo+1zs/vvvZ8WKFcyZM+eC37dx40YGBgbGv+bN8z6/dnHq+MTHQNYrK8Or/nuq7V1MX92/GlPRRTeX0N+kRFOrpkfZn9qX/UkV9idFY39SRTvWgv1pemvHmlTrRKmHuv4U99Of/pQdO3bwO7/zO1N+74YNGxgeHh7/GhoaqmdIJTCjD0rdjf2MUjdcVNyf89Uir3CcsQZ/PWaMMi9TzL/Bqu1R9qf2ZX9Shf1J0difVNFutWB/mv7arSbVWlHqoa5f39u6dStXXnklH/zgB6f83t7eXnp7e+sZRokNNOM3IoD+4n4jQi3yAs24t7PEixRzr2+1Pcr+1L7sT6qwPyka+5Mq2q0W7E/TX7vVpForSj3UfKfU2NgYW7du5WMf+xg9PXU/kkptYNFayBr7y2eyMVhU3LNj1SJ72EapwV+PKdHFHlr/VER7VGewP6nC/qRo7E+qaKdasD91hnaqSbVelHqo+U9xO3bs4NChQ3z84x9vbGSFN3M+zF8JpTr/vVTqgatX+XGh08ExhtjPdsqcquv6MqfYx/db+nHrFfaozmB/UoX9SdHYn1TRTrVgf+oM7VSTar0o9VDzodT73/9+sizjrW99a2Mjqy3csB6y0/Vdm5Vhybrm5lE6j7GJbmbUdW0X3exgS5MTnZs9qnPYn1Rhf1I09idVtEst2J86R7vUpIoRoR4au99d097sZXDzpvquvfne/HpND4Ps5jvU13W+y90MsrvJidTp7E+qsD8pGvuTKqwFRWNNarII9eChlKa0+K6JQp3q1r7K+zdvyq/T9LKDLeP/4TfVr8pU3v8O6wq7C0Gdx/6kCvuTorE/qcJaUDTWpCZLXQ8eSmlKpVJ+W96qnTD/dqCUf/Rj5eMjx1+X8vdX7cy/v1RKmVqtsoMtbGIZ+3mEMcYoc5oyp8kYo8wpypxmjDH28wibWOZ/8Kml7E+azP6kSOxPqrAWFI01qclS14MfraCqzV6Wf50YggNbYeQgvDoCF/XnHwO56A4fetcpBtnNILuZxVyWcgdXsIBL6OdlRniRg+xhayEPDZYq7E+qsD8pGvuTKqwFRWNNarJU9eChlGo2cx7c9JnUKRTBMQ7zCJ9LHUMaZ39Shf1J0difVGEtKBprUpMVXQ/++p4kSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKV8qyLCtywJGREQYGBqAEl80pcuTcS0chG4NSF1w6u/jxzWCGaBlSjw9w8giQwfDwMP39/WlCkL4/QYz1SJ0h9fhmMMPZIvQo+5MZooxvhlgZ7E+5CGthBjNEGT9Khmr7U7pDKUk6S5hDKUk6hxD/0SdJ52B/khTVVP2pp8AsZ/JOKTOYIUSG1OPDxCl6GP5NX8fXpBnMMFmoHmV/6vgMqcc3Q6wM9qdchLUwgxmijB8lQ7X9Kdmh1KVXwZrDxY/74Fw4+bN8YVKMbwYzRMuQenyAB+bkjTOKVP0JYqxH6gypxzeDGc4WqUfZn8yQenwzxMpgf8pFWAszmCHK+FEyVNuffNC5JEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCpfu0/ckSZIkqcOcOAQHtsHwIJw6DjP6YGAhLFoLM+enTiep0xXdozyUkiRJkqQWO7IT9m2GQ9vzj2kHyMpQ6s5fP30PXL0SlqyH2cuSxZTUoVL1KH99T5IkSZJaJMvg2U2w/VYYehTI8v/Qy8qvvV95ncGhR+Hh9+T/YZhlCUNL6hipe5SHUpIkSZLUIvu3wON356+z0xf+3sr7e9fn10lSq6XuUR5KSZIkSVILHNmZ/8dbPfauh6O7mptHkiaL0KNqOpQql8v84R/+Iddccw2XXHIJb3nLW/jc5z5H5r2lkhKzP0mKzB4ldaZ9m6FU51N8Sz359a1mf5I6V4QeVdPwf/RHf8R9993H17/+da677jqeeuop7rjjDgYGBvj93//9xtNIUp3sT5Iis0dJnefEofyBwdR5tpOdhp8+DCeGYOa8pkY7g/1J6kxRelRNh1J79uzhwx/+MB/84AcB+KVf+iW++c1v8sQTT9SfQJKawP4kKTJ7lNR5DmzLP8Gq8rDgepS64MBWuOkzTYv1OvYnqTNF6VE1/fre0qVL+eEPf8jf//3fA/Dss8/yF3/xF6xYseK814yOjjIyMnLGlyQ1m/1JUmS19ij7k9T+hgeb83NGDjbn55yP/UnqTFF6VE13Sn36059mZGSEa6+9lu7ubsrlMp///OdZs2bNea/ZuHEjn/3sZxtLKUlTsD9JiqzWHmV/ktrfqeON3YEA+fWvtvjMx/4kdaYoPaqmO6W+/e1v8+CDD/KNb3yDv/qrv+LrX/86mzZt4utf//p5r9mwYQPDw8PjX0NDQ40llqRzsD9JiqzWHmV/ktrfjD4odTf2M0rdcFF/c/Kcj/1J6kxRelRNd0rdfffdfPrTn+af/bN/BsDixYv56U9/ysaNG/nYxz52zmt6e3vp7e1tLKUkTcH+JCmyWnuU/UlqfwMLm/Nz+hc05+ecj/1J6kxRelRNd0q99NJLdHWdeUl3dzdjY2ONpZCkBtmfJEVmj5I6z6K1kDW4xbMxWHRHU+Kcl/1J6kxRelRNd0qtWrWKz3/+88yfP5/rrruOv/7rv2bLli18/OMfbyyFJDXI/iQpMnuU1Hlmzof5K2Ho0fyj02tV6oH5tzf2UevVsD9JnSlKj6rpUOo//+f/zB/+4R/yiU98ghdeeIE5c+bwL//lv+Qzn2nhZ5RKUhXsT5Iis0dJnemG9XDo4fquzcqwZF1z85yL/UnqXBF6VE2HUn19fXzpS1/iS1/6UuMjS1IT2Z8kRWaPkjrT7GVw8ybYu772a2++N7++1exPUueK0KNqeqaUJEmSJKl6i+/K/6MP8l93uZDK+zdvyq+TpFZL3aM8lJIkSZKkFimV8l9xWbUzf/4Kpfxj1CsfxT7+upS/v2pn/v2lUsrUkjpF6h5V06/vSZIkSZJqN3tZ/nViCA5shZGD8OoIXNSff6T6ojta/1BzSTqfVD3KQylJkiRJKsjMeXCTzxCXFFTRPcpf35MkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4UpZlmVFDjg8PMwb3vAGAC6dXeTIuZeeBzKgBJdeVfz4ZjBDtAypxwd46Wj+f3/+858zMDCQJgTp+xMEWQ9r0gxmODNDgB5lfzJDlPHNECyD/QkIshZmMEOQ8cNkqLI/FX4odfjwYebNm1fkkJLaxNDQEHPnzk02vv1J0oWk7FH2J0kXYn+SFNVU/anwQ6mxsTGOHDlCX18fpVKp5utHRkaYN28eQ0ND9Pf3tyChGdolQ+rxzdC8DFmWcfz4cebMmUNXV7rfKrY/mWE6ZUg9/nTKEKFHNdqfIP16pB7fDGaIlsH+NCH1WkTIkHp8M5ih2Rmq7U89jYSsR1dXV1NO8fv7+5MtjhliZUg9vhmakyHlr+1V2J/MMB0zpB5/umRI3aOa1Z8g/XqkHt8MZoiWwf40IfVaRMiQenwzmKGZGarpTz7oXJIkSZIkSYXzUEqSJEmSJEmFa7tDqd7eXv79v//39Pb2mqHDM6Qe3wyxMkQQYR7MYIYo45shntRzkXp8M5ghWobU40cSYS5SZ0g9vhnMkCpD4Q86lyRJkiRJktruTilJkiRJkiS1Pw+lJEmSJEmSVDgPpSRJkiRJklS4tjqU+su//Eu6u7v54Ac/WPjYa9eupVQqjX9dfvnlfOADH2Dfvn2FZ3n++ef5vd/7Pd785jfT29vLvHnzWLVqFT/84Q9bPvbkeZgxYwa/8Au/wPLly/na177G2NhYy8c/O8Pkrw984AOFjD9VjoMHDxYy/vPPP8+nPvUpFixYwMUXX8wv/MIvcMstt3Dffffx0ksvtXz8tWvX8mu/9muv+99//OMfUyqV+PnPf97yDNHYo+xPZ+dI1aNS9ydI26PsT69nf7I/nZ3D/uSfoaKwP9mfzs5hf+qs/tRWh1L3338/v/d7v8euXbs4cuRI4eN/4AMf4OjRoxw9epQf/vCH9PT0sHLlykIzPPfcc9x000386Ec/4t5772X//v384Ac/4L3vfS933nlnIRkq8/Dcc8/x6KOP8t73vpdPfepTrFy5ktOnTxeaYfLXN7/5zULGnirHNddc0/Jx/+Ef/oEbb7yRP/uzP+MLX/gCf/3Xf81f/uVf8m/+zb9h+/bt7Nixo+UZ9Hqd3qPsT6/PkbJHpepPYI+KyP5kfzo7h/3J/hSF/cn+dHYO+1Nn9aee1AGqdeLECb71rW/x1FNP8fzzz7Nt2zb+3b/7d4Vm6O3t5aqrrgLgqquu4tOf/jTvfve7efHFF7niiisKyfCJT3yCUqnEE088wWWXXTb+v1933XV8/OMfLyTD5Hn4xV/8Rd72trdx88038773vY9t27bxO7/zO4VmSClVjk984hP09PTw1FNPnVEHb37zm/nwhz+MH6pZPHuU/el8OVJJmcEeFYv9yf50vhyp2J9UYX+yP50vRyr2p+K1zZ1S3/72t7n22mtZtGgRH/3oR/na176WdFFOnDjBAw88wIIFC7j88ssLGfP//t//yw9+8APuvPPOM4q04g1veEMhOc7lV3/1V7nhhhv47//9vyfL0Cn+z//5P/zZn/3ZeesAoFQqFZxKnd6j7E+qsEfFY3+yPylnf4rH/mR/Uq6T+1PbHErdf//9fPSjHwXyW+qGh4fZuXNnoRm2b9/OzJkzmTlzJn19fXz/+9/nW9/6Fl1dxUzjwYMHybKMa6+9tpDxanXttdfy3HPPFTLW5LWofH3hC18oZOwL5Vi9enXLx6zUwaJFi87439/0pjeN5/i3//bftjwHnHsdVqxYUcjY0XR6j7I/nSlCj0rRnyBOj7I/TbA/2Z8msz+l709gj6qwP9mfJrM/dWZ/aotf3ztw4ABPPPEE3/ve9wDo6enhn/7Tf8r999/PrbfeWliO9773vdx3330AHDt2jD/+4z9mxYoVPPHEE1x99dUtHz/67XpZlhV2ejt5LSre+MY3FjL2hXKc71S7CE888QRjY2OsWbOG0dHRQsY81zo8/vjj43+46BT2KPvT2SL0qEj9CYrvUfannP3J/nQ2+9Pr+WeoNOxP9qez2Z9erxP6U1scSt1///2cPn2aOXPmjP9vWZbR29vLl7/8ZQYGBgrJcdlll7FgwYLxf/6v//W/MjAwwFe/+lX+43/8jy0ff+HChZRKJf7u7/6u5WPV4yc/+UlhD4E7ey1SSZFjwYIFlEolDhw4cMb//uY3vxmASy65pLAs5/r///Dhw4WNH4U9yv50tgg9KlWGKD3K/pSzP9mfzmZ/St+fwB4F9iewP53N/tSZ/Sn8r++dPn2a//bf/hubN2/mmWeeGf969tlnmTNnTpJPXKsolUp0dXXx8ssvFzLeG9/4Rv7xP/7HfOUrX+HkyZOvez/lx8f+6Ec/Yv/+/fzGb/xGsgyd4vLLL2f58uV8+ctfPmcdqFj2qJz9SRX2qDjsTzn7kyrsT3HYn3L2J1V0cn8Kf6fU9u3bOXbsGL/927/9utPy3/iN3+D+++/nX/2rf1VIltHRUZ5//nkgv7Xzy1/+MidOnGDVqlWFjA/wla98hVtuuYV3vvOd/If/8B9YsmQJp0+f5rHHHuO+++7jJz/5ScszVOahXC7zv//3/+YHP/gBGzduZOXKlfzWb/1Wy8efnGGynp4e3vSmNxUyfmp//Md/zC233MLb3/527rnnHpYsWUJXVxdPPvkkf/d3f8dNN92UOmLHsEdNsD+9Psdk9ih7VNHsTxPsT6/PMZn9yf5UNPvTBPvT63NMZn/qgP6UBbdy5crs9ttvP+d7jz/+eAZkzz77bMtzfOxjH8uA8a++vr7sHe94R/bd73635WOf7ciRI9mdd96ZXX311dlFF12U/eIv/mL2oQ99KPvzP//zlo89eR56enqyK664Irvtttuyr33ta1m5XG75+GdnmPy1aNGiQsafnOPDH/5woWNOduTIkeyTn/xkds0112QzZszIZs6cmb3zne/M7r333uzkyZMtH/98////+Z//eQZkx44da3mGCOxRZ+r0/nR2jlQ9KnV/yrK0Pcr+lLM/ncn+ZH+q8M9Q6dmfzmR/sj9VdGJ/KmVZ8KerSZIkSZIkadoJ/0wpSZIkSZIkTT8eSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXA9RQ84NjbGkSNH6Ovro1QqFT28pICyLOP48ePMmTOHrq50Z+X2J0nnEqFH2Z8knYv9SVJU1fanwg+ljhw5wrx584oeVlIbGBoaYu7cucnGtz9JupCUPcr+JOlC7E+SopqqPxV+KNXX1zf++tLZRY8OLz0PZEAJLr2q+PHNYIZoGVKPD/DS0fz/Tu4PKaTuTxBkPaxJM5jhzAwBepT9yQxRxjdDsAz2JyDIWpjBDEHGD5Ohyv5U+KFU5ZbOS2fDR48UPTo8OBdO/gwumwNrDhc/vhnMEC1D6vEBHpiTN63Ut3yn7k8QYz1SZ0g9vhnMcLYIPcr+ZIYo45shVgb7Uy7CWpjBDFHGj5Kh2v7kg84lSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLjCP31PatSJQ3BgGwwPwqnjMKMPBhbCorUwc34xGWYxj6Ws5UoWcjF9vMJxXmCQPWzjGEPFhJAUUuoeZX+SdD6p+xPYoyDGOkjRRNgX9qdc0WvhoZTaxpGdsG8zHNoOpdfu8cvKUOrOXz99D1y9Epash9nLWpNhIctYzjoWs5KMMQC66GLstdcruYd9PMwONjPI7taEkBRS6h5lf5J0Pqn7E9ijIMY6SNFE2Bf2p1yqtfDX9xRelsGzm2D7rTD0KJDlmyMrv/Z+5XUGhx6Fh9+Tb6Ysa26O5axjPTu5nhV00UU3PXTTQ2nS6y66WMztrGcXt3FXcwNICilCj7I/STqXCP0J7FFR1kGKJMq+6PT+BOnXwkMphbd/Czx+d/46O33h7628v3d9fl2z3MZdfIRNAHQz44LfW3l/NZunZdOSdKbUPcr+JOl8UvcnsEdBjHWQoomwL+xPudRrUfOh1K5du1i1ahVz5syhVCrxJ3/yJ81JIp3DkZ15wddj73o4uqvxDAtZxmo213XtajazkHc3HkJVsT+paKl7lP2pfdifVLTU/QnsURBjHaZif1LRIuwL+1MuwlrUfCh18uRJbrjhBr7yla80Pro0hX2boVTnk89KPfn1jVrOOsqcquvaMqem3Ul6ZPYnFS11j7I/tQ/7k4qWuj+BPQpirMNU7E8qWoR9YX/KRViLmodfsWIFK1asaHxkaQonDuUPWaPO31XNTsNPH4YTQzBzXn0/YxbzWMxKuur8TdduZrCEDzGLuRzjcH0hVDX7k4qUukfZn9qL/UlFSt2fwB4FMdahGvYnFSnCvrA/5SKsBfhMKQV2YNvEU//rVeqCA1vrv34pa8c/gaFeGWMs5Y6GfoakeFL3KPuTpPNJ3Z/AHgUx1kGKJsK+sD/lIqwF1HGnVK1GR0cZHR0d/+eRkZFWD6lpYniwOT9n5GD9117JwiYkyLiCBU34OWo2+5MakbpH2Z+mN/uTGpG6P4E9CmKsQyvYn9SICPvC/pSLsBZQwJ1SGzduZGBgYPxr3rwW3nuqaeXU8YmPoaxXVoZXG/j35MX01X1bZ0UX3VxCf0M/Q61hf1IjUvco+9P0Zn9SI1L3J7BHQYx1aAX7kxoRYV/Yn3IR1gIKOJTasGEDw8PD419DQ0OtHlLTxIw+KHU39jNK3XBRA73iFY4z1uCtnWOUeZlgf5oQYH9SY1L3KPvT9GZ/UiNS9yewR0GMdWgF+5MaEWFf2J9yEdYCCvj1vd7eXnp7e1s9jKahgWbcVQn0N3BX5Qs0457GEi8S7L5rAfYnNSZ1j7I/TW/2JzUidX8CexTEWIdWsD+pERH2hf0pF2EtoI47pU6cOMEzzzzDM888A8D/+l//i2eeeYZDhw41lkQ6y6K1kDV2gE02BosaeP7cHrZRavCGwhJd7MEnVBbB/qQipe5R9qf2Yn9SkVL3J7BHQYx1qIb9SUWKsC/sT7kIawF1HEo99dRT3Hjjjdx4440A3HXXXdx444185jOfaSyJdJaZ82H+SijVeT9fqQeuXtXYx1MeY4j9bKfMqbquL3OKfXy/rT8qtJ3Yn1Sk1D3K/tRe7E8qUur+BPYoiLEO1bA/qUgR9oX9KRdhLaCOX9+79dZbybKssVGlKt2wHg49XN+1WRmWrGs8w2Ns4gY+VNe1XXSzgy2Nh1BV7E8qWuoeZX9qH/YnFS11fwJ7FMRYh6nYn1S0CPvC/pSLsBYtf9C51IjZy+DmTfVde/O9+fWNGmQ336G+3fZd7maQ3Y2HkBRS6h5lf5J0Pqn7E9ijIMY6SNFE2Bf2p1yEtfBQSuEtvmtio0x1a2Hl/Zs35dc1yw62jDetqW7zrLz/HdZNmxN0SeeXukfZnySdT+r+BPYoiLEOUjQR9oX9KZd6LTyUUnilUn5b4KqdMP92oJR/9GTl4yvHX5fy91ftzL+/VGpujh1sYRPL2M8jjDFGmdOUOU3GGGVOUeY0Y4yxn0fYxLJp16wknVuEHmV/knQuEfoT2KOirIMUSZR90en9CdKvRZ2PtJKKN3tZ/nViCA5shZGD8OoIXNSffwzlojta/yDIQXYzyG5mMZel3MEVLOAS+nmZEV7kIHvY2vYPvJNUn9Q9yv4k6XxS9yewR0GMdZCiibAv7E+5VGvhoZTazsx5cFPiDwM5xmEe4XNpQ0gKKXWPsj9JOp/U/QnsURBjHaRoIuwL+1Ou6LXw1/ckSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuFKWZVmRA46MjDAwMAAluGxOkSPnXjoK2RiUuuDS2cWPbwYzRMuQenyAk0eADIaHh+nv708TgvT9CWKsR+oMqcc3gxnOFqFH2Z/MEGV8M8TKYH/KRVgLM5ghyvhRMlTbn9IdSknSWcIcSknSOYT4jz5JOgf7k6SopupPPQVmOZN3SpnBDCEypB4fJk7Rw/Bv+jq+Js1ghslC9Sj7U8dnSD2+GWJlsD/lIqyFGcwQZfwoGartT8kOpS69CtYcLn7cB+fCyZ/lC5NifDOYIVqG1OMDPDAnb5xRpOpPEGM9UmdIPb4ZzHC2SD3K/mSG1OObIVYG+1MuwlqYwQxRxo+Sodr+5IPOJUmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLh0n76nupw4BAe2wfAgnDoOM/pgYCEsWgsz53dGhtTjA8xiHktZy5Us5GL6eIXjvMAge9jGMYY6JoM0WYS9aYYYvSFCBmmy1PvSDBMi9IcI8yBVRKhHM+TsT2l4KNUmjuyEfZvh0Pb8Yx0BsjKUuvPXT98DV6+EJeth9rLpmSH1+AALWcZy1rGYlWSMAdBFF2OvvV7JPezjYXawmUF2T9sM0mQR9qYZYvSGCBmkyVLvSzNMiNAfIsyDVBGhHs2Qsz+l5a/vBZdl8Owm2H4rDD0KZHlxZuXX3q+8zuDQo/Dwe/JizrLpkyH1+BXLWcd6dnI9K+iii2566KaH0qTXXXSxmNtZzy5u467mBgiSQaqIsDfNkIvQGyJkkCoi7EszTEjdH6LMgwQx6tEME+xP6XkoFdz+LfD43fnr7PSFv7fy/t71+XXTJUPq8QFu4y4+wiYAuplxwe+tvL+azU1tWhEySJNF2JtmiNEbImSQJku9L80wIUJ/iDAPUkWEejRDzv4Ug4dSgR3ZmRdcPfauh6O72j9D6vEhv51zNZvrunY1m1nIu6dFBmmyCHvTDDF6Q4QM0mSp96UZJkToDxHmQaqIUI9myNmf4qjpUGrjxo284x3voK+vjyuvvJJf+7Vf48CBA63K1vH2bYZSnU/9KvXk17d7htTjQ35LZ5lTdV1b5lRTTtIjZIjO/lSsCHvTDDF6Q4QM7cAeVZzU+9IMEyL0hwjzEJ39qTgR6tEMOftTHDUdSu3cuZM777yTvXv38thjj3Hq1Cne//73c/LkyVbl61gnDuUPOZvqFr7zyU7DTx+GEw18SEDqDKnHh/wTGBazcsrbOc+nmxks4UPMYm5bZ2gH9qfiRNibZojRGyJkaBf2qGKk3pdmmBChP0SYh3ZgfypGhHo0Q87+FEtNh1I/+MEPWLt2Lddddx033HAD27Zt49ChQzz99NOtytexDmybeOp+vUpdcGBr+2ZIPT7AUtaOfwJDvTLGWModbZ2hHdifihNhb5ohRm+IkKFd2KOKkXpfmmFChP4QYR7agf2pGBHq0Qw5+1Msdd4slhseHgbgjW9843m/Z3R0lNHR0fF/HhkZaWTIjjE82JyfM3KwfTOkHh/gShY2IUHGFSxo6wztyP7UOhH2phli9IYIGdrVVD3K/lSf1PvSDBMi9IcI89CO7E+tEaEezZCzP8VS99nc2NgYf/AHf8Att9zC9ddff97v27hxIwMDA+Nf8+bNq3fIjnLq+MTHQNYrK8OrDfw7InWG1OMDXEwfXQ1+HkAX3VxCf1tnaDf2p9aKsDfNEKM3RMjQjqrpUfan+qTel2aYEKE/RJiHdmN/ap0I9WiGnP0plrpX4s477+Rv/uZveOihhy74fRs2bGB4eHj8a2hoGvzSYwFm9EGpu7GfUeqGixr4c37qDKnHB3iF44w1eGvnGGVepv5uESFDu7E/tVaEvWmGGL0hQoZ2VE2Psj/VJ/W+NMOECP0hwjy0G/tT60SoRzPk7E+x1PXre5/85CfZvn07u3btYu7cCz/cq7e3l97e3rrCdbKBZtxRCPQ38BsRqTOkHh/gBZpxX2WJF6n/vsoIGdqJ/an1IuxNM8ToDREytJtqe5T9qT6p96UZJkToDxHmoZ3Yn1orQj2aIWd/iqWmO6WyLOOTn/wk3/ve9/jRj37ENddc06pcHW/RWsgaO7wlG4NFDTw7NnWG1OMD7GEbpQZv7SzRxR7qfwJdhAztwP5UnAh70wwxekOEDO3CHlWM1PvSDBMi9IcI89AO7E/FiFCPZsjZn2KpaSXuvPNOHnjgAb7xjW/Q19fH888/z/PPP8/LL7/cqnwda+Z8mL8SSnU+ir7UA1evgpkN/Ip36gypxwc4xhD72U6ZU3VdX+YU+/g+xzjc1hnagf2pOBH2phli9IYIGdqFPaoYqfelGSZE6A8R5qEd2J+KEaEezZCzP8VS06HUfffdx/DwMLfeeiuzZ88e//rWt77Vqnwd7Yb1kJ2u79qsDEvWtX+G1OMDPMYmuplR17VddLODLdMiQ3T2p2JF2JtmiNEbImRoB/ao4qTel2aYEKE/RJiH6OxPxYlQj2bI2Z/iqPnX9871tXbt2hbF62yzl8HNm+q79uZ78+vbPUPq8QEG2c13qG/Hf5e7GWT3tMgQnf2pWBH2phli9IYIGdqBPao4qfelGSZE6A8R5iE6+1NxItSjGXL2pzga+0VKtdziuyYKdapb+yrv37wpv266ZEg9PsAOtow3ralu86y8/x3WNfUOgAgZpMki7E0zxOgNETJIk6Xel2aYEKE/RJgHqSJCPZohZ3+KwUOp4Eql/La8VTth/u1AKf/ox8rHR46/LuXvr9qZf3+pNH0ypB6/Ygdb2MQy9vMIY4xR5jRlTpMxRplTlDnNGGPs5xE2sawl/7EVIYNUEWFvmiEXoTdEyCBVRNiXZpiQuj9EmQcJYtSjGSbYn9Kr87FaKtrsZfnXiSE4sBVGDsKrI3BRf/4xkIvuaP1DzlJnSD0+5Ld5DrKbWcxlKXdwBQu4hH5eZoQXOcgetrb8gb0RMkiTRdibZojRGyJkkCZLvS/NMCFCf4gwD1JFhHo0Q87+lJaHUm1m5jy46TOdnSH1+ADHOMwjfK7jM0iTRdibZojRGyJkkCZLvS/NMCFCf4gwD1JFhHo0Q87+lIa/vidJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwpWyLMuKHHBkZISBgQEowWVzihw599JRyMag1AWXzi5+fDOYIVqG1OMDnDwCZDA8PEx/f3+aEKTvTxBjPVJnSD2+Gcxwtgg9yv5khijjmyFWBvtTLsJamMEMUcaPkqHa/pTuUEqSzhLmUEqSziHEf/RJ0jnYnyRFNVV/6ikwy5m8U8oMZgiRIfX4MHGKHoZ/09fxNWkGM0wWqkfZnzo+Q+rxzRArg/0pF2EtzGCGKONHyVBtf0p2KHXpVbDmcPHjPjgXTv4sX5gU45vBDNEypB4f4IE5eeOMIlV/ghjrkTpD6vHNYIazRepR9iczpB7fDLEy2J9yEdbCDGaIMn6UDNX2Jx90LkmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMKl+/S9NjSLeSxlLVeykIvp4xWO8wKD7GEbxxhKHa8wJw7BgW0wPAinjsOMPhhYCIvWwsz503/8KBmsR01mPeQi7M3UGVKPD9ajzmQ95CLsTTPkrElNZj3E2JdmyHViPXooVYWFLGM561jMSjLGAOiii7HXXq/kHvbxMDvYzCC7U0ZtqSM7Yd9mOLQ9/2hJgKwMpe789dP3wNUrYcl6mL1s+o0fJYP1qMmsh1yEvZk6Q+rxwXrUmayHXIS9aYacNanJrIcY+9IMuU6uR399bwrLWcd6dnI9K+iii2566KaH0qTXXXSxmNtZzy5u467UkZsuy+DZTbD9Vhh6FMjyTZqVX3u/8jqDQ4/Cw+/JN3WWTY/xo2QA61Fnsh5i7M3UGVKPX2E9ajLrIcbeNMMEa1KTdXo9RNiXZpjQ6fXoodQF3MZdfIRNAHQz44LfW3l/NZunXZHs3wKP352/zk5f+Hsr7+9dn183HcaPksF61GTWQy7C3kydIfX4YD3qTNZDLsLeNEPOmtRk1kOMfWmGnPVY46HUfffdx5IlS+jv76e/v593vetdPProo63KltRClrGazXVdu5rNLOTdTU6UxpGd+carx971cHRXe48fJYP1ODX7U3WmUz1E2JupM6QeH6zHanVKj7IechH2phly1uTUOqU/gfUAMfalGXLWY66mQ6m5c+fyxS9+kaeffpqnnnqKX/3VX+XDH/4w/+N//I9W5UtmOesoc6qua8ucmjYnl/s2Q6nOJ4+VevLr23n8KBmsx6nZn6ozneohwt5MnSH1+GA9VqtTepT1kIuwN82Qsyan1in9CawHiLEvzZCzHnM1HUqtWrWK22+/nYULF/LWt76Vz3/+88ycOZO9e/e2Kl8Ss5jHYlZOefvc+XQzgyV8iFnMbXKyYp04lD/sbapbGc8nOw0/fRhO1PkhAanHj5LBeqyO/ak606UeIuzN1BlSjw/WYy06oUdZD7kIe9MMOWuyOp3Qn8B6gBj70gw563FC3c+UKpfLPPTQQ5w8eZJ3vetdzcyU3FLWjj/xvl4ZYyzljiYlSuPAtolPH6hXqQsObG3P8aNksB5rZ3+6sOlQDxH2ZuoMqccH67Fe07VHWQ+5CHvTDDlrsnbTtT+B9QAx9qUZctbjhJpvWNu/fz/vete7eOWVV5g5cybf+973+OVf/uXzfv/o6Cijo6Pj/zwyMlJf0gJdycIm/JSMK1jQhJ+TzvBgc37OyMH2HD9KBuuxevanarV/PUTYm6kzpB4frMda1dKj7E/tK8LeNEPOmqzedO9PYD1AjH1phpz1OKHm88FFixbxzDPP8Pjjj/O7v/u7fOxjH+Nv//Zvz/v9GzduZGBgYPxr3rx5DQUuwsX00dXgBxN20c0l9DcpURqnjk98HGa9sjK8Wue/p1KPHyWD9Vg9+1N1pkM9RNibqTOkHh+sx1rV0qPsT+0rwt40Q86arN50709gPUCMfWmGnPU4oeZZuOiii1iwYAE33XQTGzdu5IYbbuA//af/dN7v37BhA8PDw+NfQ0MN/OJlQV7hOGMN3ko3RpmXaY+/NTifGX1Q6m7sZ5S64aI690nq8aNksB6rZ3+qznSohwh7M3WG1OOD9VirWnqU/al9RdibZshZk9Wb7v0JrAeIsS/NkLMeJ9T5vPkJY2NjZ9y+ebbe3l56e3sbHaZQL9CM+/lKvEgD9/MFMNCMOwqB/jrvKEw9fpQM1mP97E/n0/71EGFvps6QenywHht1oR5lf2pfEfamGXLWZP2mW38C6wFi7Esz5KzHCTXdKbVhwwZ27drFc889x/79+9mwYQM//vGPWbNmTavyJbGHbZQavJWuRBd7aODJZwEsWgtZY4e3ZGOwqM5nr6UeP0oG67E69qfqTYd6iLA3U2dIPT5Yj7XohB5lPeQi7E0z5KzJ6nRCfwLrAWLsSzPkrMcJNc3CCy+8wG/91m+xaNEi3ve+9/Hkk0/yp3/6pyxfvrxV+ZI4xhD72U6ZU3VdX+YU+/g+xzjc5GTFmjkf5q+EUp3305V64OpVMLPOXzNPPX6UDNZjdexP1Zku9RBhb6bOkHp8sB5r0Qk9ynrIRdibZshZk9XphP4E1gPE2JdmyFmPE2pahvvvv79VOcJ5jE3cwIfquraLbnawpcmJ0rhhPRx6uL5rszIsWdfe40fJYD1Ozf5UnelUDxH2ZuoMqccH67FandKjrIdchL1phpw1ObVO6U9gPUCMfWmGnPWYa+x+sWlskN18h/oq7bvczSC7m5wojdnL4OZN9V1787359e08fpQM1qMmsx5yEfZm6gypxwfrUWeyHnIR9qYZctakJrMeYuxLM+Ssx5yHUhewgy3jRTLVbXWV97/DumlzYlmx+K6JDTvVLY6V92/elF83HcaPksF61GTWQy7C3kydIfX4YD3qTNZDLsLeNEPOmtRk1kOMfWmGnPXoodSUdrCFTSxjP48wxhhlTlPmNBljlDlFmdOMMcZ+HmETy6ZVcVSUSvntiat2wvzbgVL+EZiVj9Ecf13K31+1M//+Uml6jB8lA1iPOpP1EGNvps6QevwK61GTWQ8x9qYZJliTmqzT6yHCvjTDhE6vxzof7dVZBtnNILuZxVyWcgdXsIBL6OdlRniRg+xh67R4wNhUZi/Lv04MwYGtMHIQXh2Bi/rzj8NcdEdjD3uLPn6UDNajJrMechH2ZuoMqccH61Fnsh5yEfamGXLWpCazHmLsSzPkOrkePZSqwTEO8wifSx0juZnz4KbPdO74UTJYj5rMeshF2JupM6QeH6xHncl6yEXYm2bIWZOazHqIsS/NkOvEevTX9yRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4UpZlWZEDjoyMMDAwACW4bE6RI+deOgrZGJS64NLZxY9vBjNEy5B6fICTR4AMhoeH6e/vTxOC9P0JYqxH6gypxzeDGc4WoUfZn8wQZXwzxMpgf8pFWAszmCHK+FEyVNuf0h1KSdJZwhxKSdI5hPiPPkk6B/uTpKim6k89BWY5k3dKmcEMITKkHh8mTtHD8G/6Or4mzWCGyUL1KPtTx2dIPb4ZYmWwP+UirIUZzBBl/CgZqu1PyQ6lLr0K1hwuftwH58LJn+ULk2J8M5ghWobU4wM8MCdvnFGk6k8QYz1SZ0g9vhnMcLZIPcr+ZIbU45shVgb7Uy7CWpjBDFHGj5Kh2v7kg84lSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuHSfvqe6zGIeS1nLlSzkYvp4heO8wCB72MYxhgrJcOIQHNgGw4Nw6jjM6IOBhbBoLcyc3/rxnYM4GSKsheKIUA/uixhzECFD6nVQLBHqwX2RizAPqTNEWAfFEaEeUu8JcB4iZSh6LTyUahMLWcZy1rGYlWSMAdBFF2OvvV7JPezjYXawmUF2tyTDkZ2wbzMc2p5/tCRAVoZSd/766Xvg6pWwZD3MXtb88Z2DOBkirIXiiFAP7osYcxAhQ+p1UCwR6sF9kYswD6kzRFgHxRGhHlLvCXAeImVItRb++l4bWM461rOT61lBF11000M3PZQmve6ii8Xcznp2cRt3NXX8LINnN8H2W2HoUSDLN0hWfu39yusMDj0KD78n31BZ1rwMzkGMDJB+LRRL6npwX8SYgwgZIH09KpbU9eC+yEWYhwgZUq+DYkldDxH2BDgPUTJA2rXwUCq427iLj7AJgG5mXPB7K++vZnNTi2T/Fnj87vx1dvrC31t5f+/6/LpmcA7iZIiwFoojQj24L2LMQYQMqddBsUSoB/dFLsI8pM4QYR0UR4R6SL0nwHmIlCH1WngoFdhClrGazXVdu5rNLOTdDWc4sjMv+nrsXQ9HdzU2vnMQJ0OEtVAcEerBfRFjDiJkSL0OiiVCPbgvchHmIXWGCOugOCLUQ+o9Ac5DpAwR1qKhQ6kvfvGLlEol/uAP/qDhIHq95ayjzKm6ri1zqiknl/s2Q6nOJ4+VevLrG+EcxMkQYS1qYX9qrQj14L6IMQcRMqReh1rZn1orQj24L3IR5iF1hgjrUCt7VOtEqIfUewKch0gZIqxF3YdSTz75JP/lv/wXlixZ0nAIvd4s5rGYlVPePnc+3cxgCR9iFnPrznDiUP6gtaluIzyf7DT89GE4UecD+p2DOBkirEUt7E+tFaEe3Bcx5iBChtTrUCv7U2tFqAf3RS7CPKTOEGEdamWPap0I9ZB6T4DzEClDhLWAOg+lTpw4wZo1a/jqV7/KrFmzGgqgc1vK2vEn3tcrY4yl3FH39Qe2TTz5v16lLjiwtb5rnYM4GSKsRbXsT60XoR7cFzHmIEKG1OtQC/tT60WoB/dFLsI8pM4QYR1qYY9qrQj1kHpPgPMQKUOEtYA6D6XuvPNOPvjBD3LbbbdN+b2jo6OMjIyc8aWpXcnCJvyUjCtYUPfVw4NNiACMHKzvOucgToYIa1Et+1PrRagH90WMOYiQIfU61ML+1HoR6sF9kYswD6kzRFiHWlTbo+xP9YlQD6n3BDgPkTJEWAuAmn+D8aGHHuKv/uqvePLJJ6v6/o0bN/LZz3625mCd7mL66GrwOfRddHMJ/XVff+r4xEdR1isrw6t1/nvKOYiTIcJaVMP+VIwI9eC+iDEHETKkXodq2Z+KEaEe3Be5CPOQOkOEdahWLT3K/lSfCPWQek+A8xApQ4S1yH9GDYaGhvjUpz7Fgw8+yMUXX1zVNRs2bGB4eHj8a2iogV967CCvcJyxBm+lG6PMy9RfpTP6oNTdUARK3XBRnTXqHMTJEGEtpmJ/Kk6EenBfxJiDCBlSr0M17E/FiVAP7otchHlInSHCOlSj1h5lf6pPhHpIvSfAeYiUIcJaQI13Sj399NO88MILvO1tbxv/38rlMrt27eLLX/4yo6OjdHefObO9vb309vY2FLITvUAz7ucr8SL138830Iy7+YD+Ou/mcw7iZIiwFlOxPxUnQj24L2LMQYQMqdehGvan4kSoB/dFLsI8pM4QYR2qUWuPsj/VJ0I9pN4T4DxEyhBhLaDGO6Xe9773sX//fp555pnxr7e//e2sWbOGZ5555nV/oFL99rCNUoO30pXoYg/1P/ls0VrIGjs4JRuDRXU+98w5iJMhwlpMxf5UnAj14L6IMQcRMqReh2rYn4oToR7cF7kI85A6Q4R1qIY9qhgR6iH1ngDnIVKGCGsBNR5K9fX1cf3115/xddlll3H55Zdz/fXXNxREZzrGEPvZTplTdV1f5hT7+D7HOFx3hpnzYf5KKNX85LFcqQeuXgUz59V3vXMQJ0OEtZiK/ak4EerBfRFjDiJkSL0O1bA/FSdCPbgvchHmIXWGCOtQDXtUMSLUQ+o9Ac5DpAwR1gLq/PQ9FeMxNtHNjLqu7aKbHWxpOMMN6yE7Xd+1WRmWrGtsfOcgToYIa6E4ItSD+yLGHETIkHodFEuEenBf5CLMQ+oMEdZBcUSoh9R7ApyHSBkirEXDh1I//vGP+dKXvtRwEL3eILv5DvVV2ne5m0F2N5xh9jK4eVN91958b359I5yDOBkirEWt7E+tE6Ee3Bcx5iBChtTrUA/7U+tEqAf3RS7CPKTOEGEd6mGPao0I9ZB6T4DzEClDhLXwTqngdrBlvEimuq2u8v53WNfUv1VZfNfEZpnq9sLK+zdvyq9rBucgToYIa6E4ItSD+yLGHETIkHodFEuEenBf5CLMQ+oMEdZBcUSoh9R7ApyHSBlSr4WHUm1gB1vYxDL28whjjFHmNGVOkzFGmVOUOc0YY+znETaxrOn/AiuV8lsDV+2E+bcDpfzjJysfYTn+upS/v2pn/v2lUvMyOAcxMkD6tVAsqevBfRFjDiJkgPT1qFhS14P7IhdhHiJkSL0OiiV1PUTYE+A8RMkAadeizsdqqWiD7GaQ3cxiLku5gytYwCX08zIjvMhB9rC15Q9BnL0s/zoxBAe2wshBeHUELurPP4py0R2NPWhtKs5BnAwR1kJxRKgH90WMOYiQIfU6KJYI9eC+yEWYh9QZIqyD4ohQD6n3BDgPkTKkWgsPpdrMMQ7zCJ9LmmHmPLjpM+nGdw7iZIiwFoojQj24L2LMQYQMqddBsUSoB/dFLsI8pM4QYR0UR4R6SL0nwHmIlKHotfDX9yRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuFKWZVmRA46MjDAwMAAluGxOkSPnXjoK2RiUuuDS2cWPbwYzRMuQenyAk0eADIaHh+nv708TgvT9CWKsR+oMqcc3gxnOFqFH2Z/MEGV8M8TKYH/KRVgLM5ghyvhRMlTbn9IdSknSWcIcSknSOYT4jz5JOgf7k6SopupPPQVmOZN3SpnBDCEypB4fJk7Rw/Bv+jq+Js1ghslC9Sj7U8dnSD2+GWJlsD/lIqyFGcwQZfwoGartT8kOpS69CtYcLn7cB+fCyZ/lC5NifDOYIVqG1OMDPDAnb5xRpOpPEGM9UmdIPb4ZzHC2SD3K/mSG1OObIVYG+1MuwlqYwQxRxo+Sodr+5IPOJUmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLh0n77XhmYxj6Ws5UoWcjF9vMJxXmCQPWzjGENmKCjDiUNwYBsMD8Kp4zCjDwYWwqK1MHN+y4c3g0JKvS/NMCH13kw9fpQMiiPCvjRDLsLeNIOiSb03U49vBjOkzuChVBUWsozlrGMxK8kYA6CLLsZee72Se9jHw+xgM4PsNkOLMhzZCfs2w6Ht+UdbAmRlKHXnr5++B65eCUvWw+xlTR/eDAop9b40w4TUezP1+FEyKI4I+9IMuQh70wyKJvXeTD2+GcwQJYO/vjeF5axjPTu5nhV00UU3PXTTQ2nS6y66WMztrGcXt3GXGZqcIcvg2U2w/VYYehTI8j9AZOXX3q+8zuDQo/Dwe/I/cGRZ0yKYQSF1em+IkiH13kw9fpQMiiX1vjRDLsLeNIMiSr03U49vBjNEyuCh1AXcxl18hE0AdDPjgt9beX81m5u6QGaA/Vvg8bvz19npC39v5f296/PrmsUMiib1vjTDhNR7M/X4UTIojgj70gy5CHvTDIom9d5MPb4ZzBAtQ02HUvfccw+lUumMr2uvvbYpQaJZyDJWs7mua1ezmYW82wxNyHBkZ/6HgnrsXQ9HdzU0vBnaiP2pOtOlN0TJkHpvph4/SoZ20Ck9KsK+NEMuwt40Q3volP4E6fdm6vHNYIaIGWq+U+q6667j6NGj419/8Rd/0XCIiJazjjKn6rq2zKmmnBqaIb91ulTnk89KPfn1jTJD+7A/TW269IYoGVLvzdTjR8nQLjqhR0XYl2bIRdibZmgfndCfIP3eTD2+GcwQMUPNh1I9PT1cddVV419vetObGg4RzSzmsZiVU966dj7dzGAJH2IWc83QQIYTh/IHUU51m/X5ZKfhpw/DiQY+IMAM7cX+NLXp0BuiZEi9N1OPHyVDO5nuPSrCvjRDLsLeNEN7me79CdLvzdTjm8EMETNAHYdSg4ODzJkzhze/+c2sWbOGQ4cONRQgoqWsHX/afL0yxljKHWZoIMOBbROfjFKvUhcc2Fr/9WZoL/an6rR7b4iSIfXeTD1+lAztZLr3qAj70gy5CHvTDO1luvcnSL83U49vBjNEzABQ082sv/Irv8K2bdtYtGgRR48e5bOf/Szvfve7+Zu/+Rv6+vrOec3o6Cijo6Pj/zwyMtJQ4CJcycIm/JSMK1hghgYyDA82YXhg5GD915qhfdifatHevSFKhtR7M/X4UTK0i1p7lP3JDO3cn8zQXjqhP0H6vZl6fDOYIWIGqPFQasWKFeOvlyxZwq/8yq9w9dVX8+1vf5vf/u3fPuc1Gzdu5LOf/WxDIYt2MX10NfjBhF10cwn9Zmggw6njEx/VW6+sDK828O9JM7QP+1P12r03RMmQem+mHj9KhnZRa4+yP5mhnfuTGdpLJ/QnSL83U49vBjNEzJD/jAa84Q1v4K1vfSsHD57/rw82bNjA8PDw+NfQUPxfyn6F44w1eBvbGGVepv5/g5kBZvRBqbuh4Sl1w0UN7BEztC/70/m1e2+IkiH13kw9fpQM7WqqHmV/MkM79ycztLfp2J8g/d5MPb4ZzBAxAzR4KHXixAn+5//8n8yePfu839Pb20t/f/8ZX9G9QDPu9S3xIvXf62sGGGjG3YRAfwN3E5qhfdmfLqS9e0OUDKn3Zurxo2RoV1P1KPuTGdq5P5mhvU3H/gTp92bq8c1ghogZoMZDqfXr17Nz506ee+459uzZw6//+q/T3d3Nb/7mbzYUIpo9bKPU4G1sJbrYQ/1PRTQDLFoLWWMHt2RjsKiB566ZoX3Yn6rX7r0hSobUezP1+FEytItO6FER9qUZchH2phnaRyf0J0i/N1OPbwYzRMwANR5KHT58mN/8zd9k0aJF/JN/8k+4/PLL2bt3L1dccUVDIaI5xhD72U6ZU3VdX+YU+/g+xzhshgYyzJwP81dCqaYnn00o9cDVq2DmvPquN0N7sT9VZzr0higZUu/N1ONHydAuOqFHRdiXZshF2JtmaB+d0J8g/d5MPb4ZzBAxA9R4KPXQQw9x5MgRRkdHOXz4MA899BBvectbGgoQ1WNsopsZdV3bRTc72GKGJmS4YT1kp+u7NivDknUNDW+GNmJ/qs506Q1RMqTem6nHj5KhHXRKj4qwL82Qi7A3zdAeOqU/Qfq9mXp8M5ghYobG7tWaxgbZzXeo799C3+VuBtlthiZkmL0Mbt5U37U335tf3ygzKJrU+9IME1LvzdTjR8mgOCLsSzPkIuxNMyia1Hsz9fhmMEPEDB5KXcAOtowv0FS3tFXe/w7rmnJaaIYJi++a+MPEVLdfV96/eVN+XbOYQdGk3pdmmJB6b6YeP0oGxRFhX5ohF2FvmkHRpN6bqcc3gxmiZfBQago72MImlrGfRxhjjDKnKXOajDHKnKLMacYYYz+PsIllTS0OM+RKpfzW6VU7Yf7tQCn/eN7KR/yOvy7l76/amX9/qdS0CGZQSJ3eG6JkSL03U48fJYNiSb0vzZCLsDfNoIhS783U45vBDJEy1PnYv84yyG4G2c0s5rKUO7iCBVxCPy8zwoscZA9bG364lxmmNntZ/nViCA5shZGD8OoIXNSff1Tvojta/yBKMyia1PvSDBNS783U40fJoDgi7Esz5CLsTTMomtR7M/X4ZjBDlAweStXgGId5hM+ZIXGGmfPgps8kG94MCin1vjTDhNR7M/X4UTIojgj70gy5CHvTDIom9d5MPb4ZzJA6g7++J0mSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMKVsizLihxwZGSEgYEBKMFlc4ocOffSUcjGoNQFl84ufnwzmCFahtTjA5w8AmQwPDxMf39/mhCk708QYz1SZ0g9vhnMcLYIPcr+ZIYo45shVgb7Uy7CWpjBDFHGj5Kh2v6U7lBKks4S5lBKks4hxH/0SdI52J8kRTVVf+opMMuZvFPKDGYIkSH1+DBxih6Gf9PX8TVpBjNMFqpH2Z86PkPq8c0QK4P9KRdhLcxghijjR8lQbX9Kdih16VWw5nDx4z44F07+LF+YFOObwQzRMqQeH+CBOXnjjCJVf4IY65E6Q+rxzWCGs0XqUfYnM6Qe3wyxMtifchHWwgxmiDJ+lAzV9icfdC5JkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCpfv0vTZ04hAc2AbDg3DqOMzog4GFsGgtzJyfOl1xnIcYc2AGTTaLeSxlLVeykIvp4xWO8wKD7GEbxxhKHa8w1mSMOTCDJrM/5azJXIR5SJ0h9fg6kz3KmqyIMA+dmMFDqSoc2Qn7NsOh7flHKgJkZSh156+fvgeuXglL1sPsZclitpzzEGMOzKDJFrKM5axjMSvJGAOgiy7GXnu9knvYx8PsYDOD7E4ZtaWsyRhzYAZNZn/KWZO5CPOQOkPq8XUme5Q1WRFhHjo5g7++dwFZBs9ugu23wtCjQJYvSlZ+7f3K6wwOPQoPvydfxCxLGLoFnIcYc2AGnW0561jPTq5nBV100U0P3fRQmvS6iy4Wczvr2cVt3JU6ctNZkzHmwAw6m/3JmqyIMA+pM6QeX6/X6T3KmsxFmAczeCh1Qfu3wON356+z0xf+3sr7e9fn100nzkOMOTCDJruNu/gImwDoZsYFv7fy/mo2T7s/VFmTMebADJrM/pSzJnMR5iF1htTj60z2KGuyIsI8mMFDqfM6sjOf6HrsXQ9HdzU3TyrOQ4w5MIMmW8gyVrO5rmtXs5mFvLvJidKwJmPMgRk0mf0pZ03mIsxD6gypx9eZ7FHWZEWEeTBDruZDqZ/97Gd89KMf5fLLL+eSSy5h8eLFPPXUU40nCWbfZijV+cStUk9+/XTgPMSYAzNUp1P603LWUeZUXdeWOTVt/qavHWqy1SLMgRmq1wk9yv6Ua5eabLUI85A6Q+rxq9UJ/QnsUdA+NdlqEebBDLmaDqWOHTvGLbfcwowZM3j00Uf527/9WzZv3sysWbMaTxLIiUP5w72munXtfLLT8NOH4USbf1iD8xBjDsxQnU7pT7OYx2JWTnm7+fl0M4MlfIhZzG1ysmK1Q022WoQ5MEP1OqFH2Z9y7VKTrRZhHlJnSD1+tTqhP4E9CtqnJlstwjyYYUJNh1J/9Ed/xLx589i6dSvvfOc7ueaaa3j/+9/PW97ylsZSBHNg28TT5utV6oIDW5sSJxnnIcYcmKE6ndKflrJ2/BNi6pUxxlLuaFKiNNqhJlstwhyYoXqd0KPsT7l2qclWizAPqTOkHr9andCfwB4F7VOTrRZhHswwoaYI3//+93n729/O6tWrufLKK7nxxhv56le/esFrRkdHGRkZOeMruuHB5vyckYPN+TmpOA8x5sAM1emU/nQlC5vwUzKuYEETfk467VCTrRZhDsxQvVp7lP2pfbVLTbZahHlInSH1+NXqhP4E9ihon5pstQjzYIYJNR1K/cM//AP33XcfCxcu5E//9E/53d/9XX7/93+fr3/96+e9ZuPGjQwMDIx/zZs3r7HEBTh1fOLjD+uVleHV9ujP5+U8xJgDM1SnU/rTxfTR1eBnVHTRzSX0NylRGu1Qk60WYQ7MUL1ae5T9qX21S022WoR5SJ0h9fjV6oT+BPYoaJ+abLUI82CGCTXtyrGxMd72trfxhS98gRtvvJH/5//5f/gX/+Jf8P/+v//vea/ZsGEDw8PD419DQ/F/AXVGH5S6G/sZpW64qH37FeA8QIw5MEN1OqU/vcJxxhq89XyMMi/T3n+aaIeabLUIc2CG6tXao+xP7atdarLVIsxD6gypx69WJ/QnsEdB+9Rkq0WYBzNMqOlQavbs2fzyL//yGf/bP/pH/4hDhw6d95re3l76+/vP+IpuoBl3dgL97XtnJ+A8QIw5MEN1OqU/vUAz7rMt8SLtfd91O9Rkq0WYAzNUr9YeZX9qX+1Sk60WYR5SZ0g9frU6oT+BPQrapyZbLcI8mGFCTYdSt9xyCwcOHDjjf/v7v/97rr766sZSBLNoLWSNHaKTjcGi9n0GHuA8QIw5MEN1OqU/7WEbpQZvPS/RxR7a+wmV7VCTrRZhDsxQvU7oUfanXLvUZKtFmIfUGVKPX61O6E9gj4L2qclWizAPZphQ06781//6X7N3716+8IUvcPDgQb7xjW/w//1//x933nlnYymCmTkf5q+EUk9915d64OpVMLM9fr36vJyHGHNghup0Sn86xhD72U6ZU3VdX+YU+/g+xzjc5GTFaoeabLUIc2CG6nVCj7I/5dqlJlstwjykzpB6/Gp1Qn8CexS0T022WoR5MMOEmg6l3vGOd/C9732Pb37zm1x//fV87nOf40tf+hJr1qxpLEVAN6yH7HR912ZlWLKuuXlScR5izIEZptZJ/ekxNtHNjLqu7aKbHWxpcqI0otdkESLMgRmq0yk9yv6Ua4eaLEKEeUidIfX41eiU/gT2KGiPmixChHkwQ67m+xdXrlzJ/v37eeWVV/jJT37Cv/gX/6LxFAHNXgY3b6rv2pvvza+fDpyHGHNghup0Sn8aZDffob5/A3yXuxlkd5MTpdEONdlqEebADNXrhB5lf8q1S022WoR5SJ0h9fjV6oT+BPYoaJ+abLUI82CGXGO/VDvNLb5rYoGmuqWt8v7Nm/LrphPnIcYcmEGT7WDL+B+qproNvfL+d1g3Lf6GbzJrMsYcmEGT2Z9y1mQuwjykzpB6fJ3JHmVNVkSYBzN4KHVBpVJ+O9qqnTD/dqCUf+Rh5WMTx1+X8vdX7cy/v1RKmbr5nIcYc2AGnW0HW9jEMvbzCGOMUeY0ZU6TMUaZU5Q5zRhj7OcRNrFsWv1hqsKajDEHZtDZ7E/WZEWEeUidIfX4er1O71HWZC7CPJgB6nykVWeZvSz/OjEEB7bCyEF4dQQu6s8//nDRHe3/sLdqOA8x5sAMmmyQ3Qyym1nMZSl3cAULuIR+XmaEFznIHra29QM5q2VNxpgDM2gy+1POmsxFmIfUGVKPrzPZo6zJigjz0MkZPJSqwcx5cNNnUqdIz3mIMQdm0GTHOMwjfC51jOSsyRhzYAZNZn/KWZO5CPOQOkPq8XUme5Q1WRFhHjoxg7++J0mSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTClbIsy4occGRkhIGBASjBZXOKHDn30lHIxqDUBZfOLn58M5ghWobU4wOcPAJkMDw8TH9/f5oQpO9PEGM9UmdIPb4ZzHC2CD3K/mSGKOObIVYG+1MuwlqYwQxRxo+Sodr+lO5QSpLOEuZQSpLOIcR/9EnSOdifJEU1VX/qKTDLmbxTygxmCJEh9fgwcYoehn/T1/E1aQYzTBaqR9mfOj5D6vHNECuD/SkXYS3MYIYo40fJUG1/SnYodelVsOZw8eM+OBdO/ixfmBTjm8EM0TKkHh/ggTl544wiVX+CGOuROkPq8c1ghrNF6lH2JzOkHt8MsTLYn3IR1sIMZogyfpQM1fYnH3QuSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwqX79D21rROH4MA2GB6EU8dhRh8MLIRFa2Hm/NTpVCRrITeLeSxlLVeykIvp4xWO8wKD7GEbxxhKHa+jWJOqsBYm2KNisCZVYS1MsD/FYE1qsqLrwUMpVe3ITti3GQ5tzz9aEiArQ6k7f/30PXD1SliyHmYvSxZTBbAWcgtZxnLWsZiVZIwB0EUXY6+9Xsk97ONhdrCZQXanjDrtWZOqsBYm2KNisCZVYS1MsD/FYE1qslT14K/vaUpZBs9ugu23wtCjQJYXZ1Z+7f3K6wwOPQoPvycv5ixLGFotYS1MWM461rOT61lBF11000M3PZQmve6ii8Xcznp2cRt3pY48LVmTqrAWzmSPSs+aVIW1cCb7U3rWpCZLXQ8eSmlK+7fA43fnr7PTF/7eyvt71+fXaXqxFnK3cRcfYRMA3cy44PdW3l/NZv9Q1QLWpCqshQn2qBisSVVYCxPsTzFYk5osdT3UdCj1S7/0S5RKpdd93Xnnnc1Jo3CO7MwLrh5718PRXc3No3TaoRaK6FELWcZqNtd17Wo2s5B3Ny1Lp2uHmlQx2qEWivozlD0qhnaoSRWjHWrB/tRZ2qEmVZwI9VDTodSTTz7J0aNHx78ee+wxAFavXt14EoW0bzOU6nzyWKknv17TQzvUQhE9ajnrKHOqrmvLnPJv+pqoHWpSxWiHWijqz1D2qBjaoSZVjHaoBftTZ2mHmlRxItRDTYdSV1xxBVddddX41/bt23nLW97Ce97znsaTKJwTh/KHnE11C9/5ZKfhpw/DCT84o+21Sy20ukfNYh6LWTnl7ebn080MlvAhZjG3KXk6WbvUpFqvXWqhiD9D2aNiaJeaVOu1Sy3YnzpHu9SkihGlHup+ptSrr77KAw88wMc//nFKpVJjKRTSgW0TT92vV6kLDmxtShwl1I610IoetZS1458QU6+MMZZyR1PydLJ2rEm1RjvWQqv+DGWPiqEda1Kt0Y61YH+a3tqxJtU6Ueqhzhu14E/+5E/4+c9/ztq1ay/4faOjo4yOjo7/88jISL1DqmDDg835OSMHm/NzlE471kI1ParW/nQlC5uQLOMKFjTh53S2dqxJtUY71kIr+hPYo6Jox5pUa7RjLdifprd2rEm1TpR6qPtc7P7772fFihXMmTPngt+3ceNGBgYGxr/mzZtX75Aq2KnjEx8DWa+sDK96Dtn22rEWqulRtfani+mjq8EPLe2im0vob+hnqD1rUq3RjrXQiv4E9qgo2rEm1RrtWAv2p+mtHWtSrROlHurqDD/96U/ZsWMHv/M7vzPl927YsIHh4eHxr6EhfwG1Xczog1J3Yz+j1A0X+e+OttdutVBtj6q1P73CccYavPV8jDIv47/JG9VuNanWabdaaFV/AntUFO1Wk2qddqsF+9P01241qdaKUg91/fre1q1bufLKK/ngBz845ff29vbS29tbzzBKbKAZd9kC/d5l2/barRaq7VG19qcXaMY9riVexHueG9VuNanWabdaaFV/AntUFO1Wk2qddqsF+9wVPxkAAQAASURBVNP01241qdaKUg813yk1NjbG1q1b+djHPkZPT92PpFIbWLQWssb+QoNsDBb5PMK210610MoetYdtlBq89bxEF3vw6ZCNaqeaVGu1Uy20+s9Q9qgY2qkm1VrtVAv2p87QTjWp1otSDzV3hh07dnDo0CE+/vGPNzaywps5H+avhFKd/14q9cDVq2CmjxFre+1UC63sUccYYj/bKXOqruvLnGIf3+cYh5ucrPO0U02qtdqpFlr9Zyh7VAztVJNqrXaqBftTZ2inmlTrRamHmg+l3v/+95NlGW9961sbG1lt4Yb1kJ2u79qsDEvWNTeP0mmXWmh1j3qMTXQzo65ru+hmB1uanKhztUtNqvXapRaK+DOUPSqGdqlJtV671IL9qXO0S02qGBHqobF7KDXtzV4GN2+q79qb782v1/RgLeQG2c13qK/7fpe7GWR3kxN1LmtSFdbCBHtUDNakKqyFCfanGKxJTRahHjyU0pQW3zVRqFPd2ld5/+ZN+XWaXqyF3A62jP+haqrb0Cvvf4d1/g1fC1iTqrAWJtijYrAmVWEtTLA/xWBNarLU9eChlKZUKuW35a3aCfNvB0r5Rz9WPj5y/HUpf3/Vzvz7S6WUqdUK1sKEHWxhE8vYzyOMMUaZ05Q5TcYYZU5R5jRjjLGfR9jEMv8w1SLWpCqshTPZo9KzJlVhLZzJ/pSeNanJUteDH5+nqs1eln+dGIIDW2HkILw6Ahf15x8DuegOH3rXKayF3CC7GWQ3s5jLUu7gChZwCf28zAgvcpA9bPWBnAWxJlVhLUywR8VgTarCWphgf4rBmtRkqerBQynVbOY8uOkzqVMoAmshd4zDPMLnUscQ1qQmWAsT7FExWJOqsBYm2J9isCY1WdH14K/vSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXClLMuyIgccGRlhYGAASnDZnCJHzr10FLIxKHXBpbOLH98MZoiWIfX4ACePABkMDw/T39+fJgTp+xPEWI/UGVKPbwYznC1Cj7I/mSHK+GaIlcH+lIuwFmYwQ5Txo2Sotj+lO5SSpLOEOZSSpHMI8R99knQO9idJUU3Vn3oKzHIm75QygxlCZEg9Pkycoofh3/R1fE2awQyThepR9qeOz5B6fDPEymB/ykVYCzOYIcr4UTJU25+SHUpdehWsOVz8uA/OhZM/yxcmxfhmMEO0DKnHB3hgTt44o0jVnyDGeqTOkHp8M5jhbJF6lP3JDKnHN0OsDPanXIS1MIMZoowfJUO1/ckHnUuSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcMk+fU9S+ztxCA5sg+FBOHUcZvTBwEJYtBZmzk+dTlInsz9Jisr+JCmyonuUh1KSanZkJ+zbDIe2Q+m1+y2zMpS689dP3wNXr4Ql62H2smQxJXUg+5OkqOxPkiJL1aP89T1JVcsyeHYTbL8Vhh4FsrxRZeXX3q+8zuDQo/Dwe/LGlmUJQ0vqCPYnSVHZnyRFlrpHeSglqWr7t8Djd+evs9MX/t7K+3vX59dJUivZnyRFZX+SFFnqHlXToVS5XOYP//APueaaa7jkkkt4y1vewuc+9zkyj/Glae/Izrz51GPveji6q7l5zmZ/kjpX9P4E9iipU9mfJEUWoUfV9EypP/qjP+K+++7j61//Otdddx1PPfUUd9xxBwMDA/z+7/9+42kkhbVvM5R6pj49P5dST359K5+PYH+SOlf0/gT2KKlT2Z8kRRahR9V0KLVnzx4+/OEP88EPfhCAX/qlX+Kb3/wmTzzxRGMpJIV24lD+wDvq/Auz7DT89GE4MQQz5zU12jj7k9SZ2qE/gT1K6kT2J0mRRelRNf363tKlS/nhD3/I3//93wPw7LPP8hd/8ResWLGi/gSSwjuwbeITGOpV6oIDW5sS55zsT1Jnaof+BPYoqRPZnyRFFqVH1XSn1Kc//WlGRka49tpr6e7uplwu8/nPf541a9ac95rR0VFGR0fH/3lkZKT+tJKSGB5szs8ZOdicn3Mu9iepM7VDf4Lae5T9SWp/9idJkUXpUTWdi33729/mwQcf5Bvf+AZ/9Vd/xde//nU2bdrE17/+9fNes3HjRgYGBsa/5s1r4b2nklri1PGJjwStV1aGV1v4Zxb7k9SZ2qE/Qe09yv4ktT/7k6TIovSomg6l7r77bj796U/zz/7ZP2Px4sX883/+z/nX//pfs3HjxvNes2HDBoaHh8e/hoaGGkssqXAz+qDU3djPKHXDRf3NyXMu9iepM7VDf4Lae5T9SWp/9idJkUXpUTX9+t5LL71EV9eZ51jd3d2MjY2d95re3l56e3vrSycphIGFzfk5/Qua83POxf4kdaZ26E9Qe4+yP0ntz/4kKbIoPaqmO6VWrVrF5z//eR555BGee+45vve977FlyxZ+/dd/vbEUkkJbtBay85/tVCUbg0V3NCXOOdmfpM7UDv0J7FFSJ7I/SYosSo+q6U6p//yf/zN/+Id/yCc+8QleeOEF5syZw7/8l/+Sz3zmM42lkBTazPkwfyUMPZp/9GetSj0w//bWfpyx/UnqTO3Qn8AeJXUi+5OkyKL0qJoOpfr6+vjSl77El770pcZGldR2blgPhx6u79qsDEvWNTfP2exPUueK3p/AHiV1KvuTpMgi9Kiafn1PUueavQxu3lTftTffm18vSa1gf5IUlf1JUmQRepSHUpKqtviuiaZVmuI+y8r7N2/Kr5OkVrI/SYrK/iQpstQ9ykMpSVUrlfJbNFftzH9/mFL+MaCVjxIdf13K31+1M//+UillakmdwP4kKSr7k6TIUveomp4pJUmQ36Y5exmcGIIDW2HkILw6Ahf15x8JuuiO1j+UU5LOxf4kKSr7k6TIUvUoD6Uk1W3mPLjJD2aRFJD9SVJU9idJkRXdo/z1PUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBWulGVZVuSAw8PDvOENbwDg0tlFjpx76XkgA0pw6VXFj28GM0TLkHp8gJeO5v/35z//OQMDA2lCkL4/QZD1sCbNYIYzMwToUfYnM0QZ3wzBMtifgCBrYQYzBBk/TIYq+1Phh1KHDx9m3jw/61TS6w0NDTF37txk49ufJF1Iyh5lf5J0IfYnSVFN1Z8KP5QaGxvjyJEj9PX1USqVar5+ZGSEefPmMTQ0RH9/fwsSmqFdMqQe3wzNy5BlGcePH2fOnDl0daX7rWL7kxmmU4bU40+nDBF6VKP9CdKvR+rxzWCGaBnsTxNSr0WEDKnHN4MZmp2h2v7U00jIenR1dTXlFL+/vz/Z4pghVobU45uhORlS/tpehf3JDNMxQ+rxp0uG1D2qWf0J0q9H6vHNYIZoGexPE1KvRYQMqcc3gxmamaGa/uSDziVJkiRJklQ4D6UkSZIkSZJUuLY7lOrt7eXf//t/T29vrxk6PEPq8c0QK0MEEebBDGaIMr4Z4kk9F6nHN4MZomVIPX4kEeYidYbU45vBDKkyFP6gc0mSJEmSJKnt7pSSJEmSJElS+/NQSpIkSZIkSYXzUEqSJEmSJEmFa6tDqb/8y7+ku7ubD37wg4WPvXbtWkql0vjX5Zdfzgc+8AH27dtXeJbnn3+e3/u93+PNb34zvb29zJs3j1WrVvHDH/6w5WNPnocZM2bwC7/wCyxfvpyvfe1rjI2NtXz8szNM/vrABz5QyPhT5Th48GAh4z///PN86lOfYsGCBVx88cX8wi/8Arfccgv33XcfL730UsvHX7t2Lb/2a7/2uv/9xz/+MaVSiZ///OctzxCNPcr+dHaOVD0qdX+CtD3K/vR69if709k57E/+GSoK+5P96ewc9qfO6k9tdSh1//3383u/93vs2rWLI0eOFD7+Bz7wAY4ePcrRo0f54Q9/SE9PDytXriw0w3PPPcdNN93Ej370I+69917279/PD37wA9773vdy5513FpKhMg/PPfccjz76KO9973v51Kc+xcqVKzl9+nShGSZ/ffOb3yxk7KlyXHPNNS0f9x/+4R+48cYb+bM/+zO+8IUv8Nd//df85V/+Jf/m3/wbtm/fzo4dO1qeQa/X6T3K/vT6HCl7VKr+BPaoiOxP9qezc9if7E9R2J/sT2fnsD91Vn/qSR2gWidOnOBb3/oWTz31FM8//zzbtm3j3/27f1doht7eXq666ioArrrqKj796U/z7ne/mxdffJErrriikAyf+MQnKJVKPPHEE1x22WXj//t1113Hxz/+8UIyTJ6HX/zFX+Rtb3sbN998M+973/vYtm0bv/M7v1NohpRS5fjEJz5BT08PTz311Bl18OY3v5kPf/jD+KGaxbNH2Z/OlyOVlBnsUbHYn+xP58uRiv1JFfYn+9P5cqRifype29wp9e1vf5trr72WRYsW8dGPfpSvfe1rSRflxIkTPPDAAyxYsIDLL7+8kDH/7//9v/zgBz/gzjvvPKNIK97whjcUkuNcfvVXf5UbbriB//7f/3uyDJ3i//yf/8Of/dmfnbcOAEqlUsGp1Ok9yv6kCntUPPYn+5Ny9qd47E/2J+U6uT+1zaHU/fffz0c/+lEgv6VueHiYnTt3Fpph+/btzJw5k5kzZ9LX18f3v/99vvWtb9HVVcw0Hjx4kCzLuPbaawsZr1bXXnstzz33XCFjTV6LytcXvvCFQsa+UI7Vq1e3fMxKHSxatOiM//1Nb3rTeI5/+2//bctzwLnXYcWKFYWMHU2n9yj705ki9KgU/Qni9Cj70wT7k/1pMvtT+v4E9qgK+5P9aTL7U2f2p7b49b0DBw7wxBNP8L3vfQ+Anp4e/uk//afcf//93HrrrYXleO9738t9990HwLFjx/jjP/5jVqxYwRNPPMHVV1/d8vGj366XZVlhp7eT16LijW98YyFjXyjH+U61i/DEE08wNjbGmjVrGB0dLWTMc63D448/Pv6Hi05hj7I/nS1Cj4rUn6D4HmV/ytmf7E9nsz+9nn+GSsP+ZH86m/3p9TqhP7XFodT999/P6dOnmTNnzvj/lmUZvb29fPnLX2ZgYKCQHJdddhkLFiwY/+f/+l//KwMDA3z1q1/lP/7H/9jy8RcuXEipVOLv/u7vWj5WPX7yk58U9hC4s9cilRQ5FixYQKlU4sCBA2f8729+85sBuOSSSwrLcq7//w8fPlzY+FHYo+xPZ4vQo1JliNKj7E85+5P96Wz2p/T9CexRYH8C+9PZ7E+d2Z/C//re6dOn+W//7b+xefNmnnnmmfGvZ599ljlz5iT5xLWKUqlEV1cXL7/8ciHjvfGNb+Qf/+N/zFe+8hVOnjz5uvdTfnzsj370I/bv389v/MZvJMvQKS6//HKWL1/Ol7/85XPWgYplj8rZn1Rhj4rD/pSzP6nC/hSH/Slnf1JFJ/en8HdKbd++nWPHjvHbv/3brzst/43f+A3uv/9+/tW/+leFZBkdHeX5558H8ls7v/zlL3PixAlWrVpVyPgAX/nKV7jlllt45zvfyX/4D/+BJUuWcPr0aR577DHuu+8+fvKTn7Q8Q2UeyuUy//t//29+8IMfsHHjRlauXMlv/dZvtXz8yRkm6+np4U1velMh46f2x3/8x9xyyy28/e1v55577mHJkiV0dXXx5JNP8nd/93fcdNNNqSN2DHvUBPvT63NMZo+yRxXN/jTB/vT6HJPZn+xPRbM/TbA/vT7HZPanDuhPWXArV67Mbr/99nO+9/jjj2dA9uyzz7Y8x8c+9rEMGP/q6+vL3vGOd2Tf/e53Wz722Y4cOZLdeeed2dVXX51ddNFF2S/+4i9mH/rQh7I///M/b/nYk+ehp6cnu+KKK7Lbbrst+9rXvpaVy+WWj392hslfixYtKmT8yTk+/OEPFzrmZEeOHMk++clPZtdcc002Y8aMbObMmdk73/nO7N57781OnjzZ8vHP9///n//5n2dAduzYsZZniMAedaZO709n50jVo1L3pyxL26PsTzn705nsT/anCv8MlZ796Uz2J/tTRSf2p1KWBX+6miRJkiRJkqad8M+UkiRJkiRJ0vTjoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrXU/SAY2NjHDlyhL6+PkqlUtHDSwooyzKOHz/OnDlz6OpKd1Zuf5J0LhF6lP1J0rnYnyRFVW1/KvxQ6siRI8ybN6/oYSW1gaGhIebOnZtsfPuTpAtJ2aPsT5IuxP4kKaqp+lPhh1J9fX3jry+dXfTo8NLzQAaU4NKrih/fDGaIliH1+AAvHc3/7+T+kELq/gRB1sOaNIMZzswQoEfZn8wQZXwzBMtgfwKCrIUZzBBk/DAZquxPhR9KVW7pvHQ2fPRI0aPDg3Ph5M/gsjmw5nDx45vBDNEypB4f4IE5edNKfct36v4EMdYjdYbU45vBDGeL0KPsT2aIMr4ZYmWwP+UirIUZzBBl/CgZqu1PPuhckiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYUr/NP3pEadOAQHtsHwIJw6DjP6YGAhLFoLM+cXk2EW81jKWq5kIRfTxysc5wUG2cM2jjFUTIgAIqyFctZkHKn3hbWQS70OmmBNxhFhX1gPMdZBE6zJGCLsC2shV/RaeCiltnFkJ+zbDIe2Q+m1e/yyMpS689dP3wNXr4Ql62H2stZkWMgylrOOxawkYwyALroYe+31Su5hHw+zg80Msrs1IQKIsBbKWZNxpN4X1kIu9TpogjUZR4R9YT3EWAdNsCZjiLAvrIVcqrXw1/cUXpbBs5tg+60w9CiQ5ZsjK7/2fuV1BocehYffk2+mLGtujuWsYz07uZ4VdNFFNz1000Np0usuuljM7axnF7dxV3MDBBBlLZSzJmOIsC+shRjroAnWZAxR9kWn10OUddCETq/JCKLsC2sh/Vp4KKXw9m+Bx+/OX2enL/y9lff3rs+va5bbuIuPsAmAbmZc8Hsr769m87RrWhHWQjlrMo7U+8JayKVeB02wJuOIsC+shxjroAnWZAwR9oW1kEu9FjUfSu3atYtVq1YxZ84cSqUSf/Inf9KcJNI5HNmZF3w99q6Ho7saz7CQZaxmc13XrmYzC3l34yECiLAWU+mU/mRNxpF6X1gLudTrUA3709SmU01GEGFfWA8x1mEqndKfwJqMIsK+sBZyEdai5kOpkydPcsMNN/CVr3yl8dGlKezbDKU6n3xW6smvb9Ry1lHmVF3Xljk1bU7SI6zFVDqlP1mTcaTeF9ZCLvU6VMP+NLXpVJMRRNgX1kOMdZhKp/QnsCajiLAvrIVchLWoefgVK1awYsWKxkeWpnDiUP6QNer8XdXsNPz0YTgxBDPn1fczZjGPxaykq87fdO1mBkv4ELOYyzEO1xcigAhrUY1O6E/WZByp94W1kEu9DtWyP01tutRkBBH2hfUQYx2q0Qn9CazJKCLsC2shF2EtwGdKKbAD2yae+l+vUhcc2Fr/9UtZO/4JDPXKGGMpdzT0M1KLsBbKWZNxpN4X1kIu9TpogjUZR4R9YT3EWAdNsCZjiLAvrIVchLWAOu6UqtXo6Cijo6Pj/zwyMtLqITVNDA825+eMHKz/2itZ2IQEGVewoAk/J50Ia9EK7difrMk4Uu8LayGXeh1axf6kRkTYF9ZDjHVohXbsT2BNRhFhX1gLuQhrAQXcKbVx40YGBgbGv+bNa+G9p5pWTh2f+BjKemVleLWBf09eTF/dt3VWdNHNJfQ39DNSi7AWrdCO/cmajCP1vrAWcqnXoVXsT2pEhH1hPcRYh1Zox/4E1mQUEfaFtZCLsBZQwKHUhg0bGB4eHv8aGhpq9ZCaJmb0Qam7sZ9R6oaLGugVr3CcsQZv7RyjzMsE+9NEjSKsRSu0Y3+yJuNIvS+shVzqdWgV+5MaEWFfWA8x1qEV2rE/gTUZRYR9YS3kIqwFFPDre729vfT29rZ6GE1DA824qxLob+Cuyhdoxj2NJV4k2H3XNYqwFq3Qjv3Jmowj9b6wFnKp16FV7E9qRIR9YT3EWIdWaMf+BNZkFBH2hbWQi7AWUMedUidOnOCZZ57hmWeeAeB//a//xTPPPMOhQ4caSyKdZdFayBo7wCYbg0UNPH9uD9soNXhDYYku9tDeT6iMsBbV6IT+ZE3GkXpfWAu51OtQLftTdaZDTUYQYV9YDzHWoRqd0J/Amowiwr6wFnIR1gLqOJR66qmnuPHGG7nxxhsBuOuuu7jxxhv5zGc+01gS6Swz58P8lVCq836+Ug9cvaqxj6c8xhD72U6ZU3VdX+YU+/h+W39UKMRYi2p0Qn+yJuNIvS+shVzqdaiW/Wlq06UmI4iwL6yHGOtQjU7oT2BNRhFhX1gLuQhrAXUcSt16661kWfa6r23btjWWRDqHG9ZDdrq+a7MyLFnXeIbH2EQ3M+q6totudrCl8RABRFiLqXRKf7Im40i9L6yFXOp1qIb9aWrTqSYjiLAvrIcY6zCVTulPYE1GEWFfWAu5CGvR8gedS42YvQxu3lTftTffm1/fqEF28x3q223f5W4G2d14iAAirIVy1mQcqfeFtZBLvQ6aYE3GEWFfWA8x1kETrMkYIuwLayEXYS08lFJ4i++a2ChT3VpYef/mTfl1zbKDLeNNa6rbPCvvf4d10+YEvSLCWihnTcaRel9YC7nU66AJ1mQcEfaF9RBjHTTBmowhwr6wFnKp18JDKYVXKuW3Ba7aCfNvB0r5R09WPr5y/HUpf3/Vzvz7S6Xm5tjBFjaxjP08whhjlDlNmdNkjFHmFGVOM8YY+3mETSybds0K4qyFctZkDBH2hbUQYx00wZqMIcq+6PR6iLIOmtDpNRlBlH1hLaRfizofaSUVb/ay/OvEEBzYCiMH4dURuKg//xjKRXe0/kGQg+xmkN3MYi5LuYMrWMAl9PMyI7zIQfawte0feFeNCGuhnDUZR+p9YS3kUq+DJliTcUTYF9ZDjHXQBGsyhgj7wlrIpVoLD6XUdmbOg5sSfxjIMQ7zCJ9LGyKACGuhnDUZR+p9YS3kUq+DJliTcUTYF9ZDjHXQBGsyhgj7wlrIFb0W/vqeJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSClfKsiwrcsCRkREGBgagBJfNKXLk3EtHIRuDUhdcOrv48c1ghmgZUo8PcPIIkMHw8DD9/f1pQpC+P0GM9UidIfX4ZjDD2SL0KPuTGaKMb4ZYGexPuQhrYQYzRBk/SoZq+1O6QylJOkuYQylJOocQ/9EnSedgf5IU1VT9qafALGfyTikzmCFEhtTjw8Qpehj+TV/H16QZzDBZqB5lf+r4DKnHN0OsDPanXIS1MIMZoowfJUO1/SnZodSlV8Gaw8WP++BcOPmzfGFSjG8GM0TLkHp8gAfm5I0zilT9CWKsR+oMqcc3gxnOFqlH2Z/MkHp8M8TKYH/KRVgLM5ghyvhRMlTbn3zQuSRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgqX7tP3VJcTh+DANhgehFPHYUYfDCyERWth5vzOyJB6fIBZzGMpa7mShVxMH69wnBcYZA/bOMZQIRkizIM0mfsiRgbXQXo990WcDK6FdCb3RJwMEdaiEzN4KNUmjuyEfZvh0Pb8Yx0BsjKUuvPXT98DV6+EJeth9rLpmSH1+AALWcZy1rGYlWSMAdBFF2OvvV7JPezjYXawmUF2tyRDhHmQJnNfxMjgOkiv576Ik8G1kM7knoiTIcJadHIGf30vuCyDZzfB9lth6FEgyzdpVn7t/crrDA49Cg+/J9/UWTZ9MqQev2I561jPTq5nBV100U0P3fRQmvS6iy4Wczvr2cVt3NXU8aPMgzSZ+yJGBtdBej33RYwM4FpIZ3NPxMgA6dfCDB5Khbd/Czx+d/46O33h7628v3d9ft10yZB6fIDbuIuPsAmAbmZc8Hsr769mc1M3a4R5kCZzX8TI4DpIr+e+iJPBtZDO5J6IkyHCWpjBQ6nQjuzMN1499q6Ho7vaP0Pq8SG/jXE1m+u6djWbWci7G84QYR6kydwXMTK4DtLruS/iZHAtpDO5J+JkiLAWZsjVdCi1ceNG3vGOd9DX18eVV17Jr/3ar3HgwIGGQ+jc9m2GUp1P/Sr15Ne3e4bU40N+K2OZU3VdW+ZUU06QI8xDdPanYrkvYmRwHdqHPao47os4GVyL9mB/Ko57Ik6GCGthhlxNh1I7d+7kzjvvZO/evTz22GOcOnWK97///Zw8ebLhIDrTiUP5w96mupXxfLLT8NOH4UQDD8dPnSH1+JB/8sBiVk55G+P5dDODJXyIWcytO0OEeWgH9qfiuC9iZHAd2os9qhjuizgZXIv2YX8qhnsiToYIa2GGCTUdSv3gBz9g7dq1XHfdddxwww1s27aNQ4cO8fTTTzcUQq93YNvEpw/Uq9QFB7a2b4bU4wMsZe34Jw/UK2OMpdxR9/UR5qEd2J+K476IkcF1aC/2qGK4L+JkcC3ah/2pGO6JOBkirIUZJtR501xueHgYgDe+8Y3n/Z7R0VFGR0fH/3lkZKSRITvG8GBzfs7IwfbNkHp8gCtZ2IQEGVewoO6rI8xDO7I/tY77IkYG16G9TdWj7E/1cV/EyeBatC/7U2u4J+JkiLAWZphQ9xnl2NgYf/AHf8Att9zC9ddff97v27hxIwMDA+Nf8+bNq3fIjnLq+MTHYdYrK8OrDfw7InWG1OMDXEwfXQ1+HkAX3VxCf93XR5iHdmN/ai33RYwMrkP7qqZH2Z/q476Ik8G1aE/2p9ZxT8TJEGEtzDD5Z9Tpzjvv5G/+5m946KGHLvh9GzZsYHh4ePxraGia/1J2k8zog1J3Yz+j1A0XNVAfqTOkHh/gFY4z1uAtjWOUeZn6u2aEeWg39qfWcl/EyOA6tK9qepT9qT7uizgZXIv2ZH9qHfdEnAwR1sIME+r69b1PfvKTbN++nV27djF37oUfatXb20tvb29d4TrZQDPupAP6G7iTLnWG1OMDvEAz7i8t8SL1318aYR7aif2p9dwXMTK4Du2p2h5lf6qP+yJOBtei/difWss9ESdDhLUww4Sa7pTKsoxPfvKTfO973+NHP/oR11xzTUOD6/wWrYWssUNLsjFY1MAzx1JnSD0+wB62UWrwlsYSXeyh/ifxRZiHdmB/Ko77IkYG16G92KOK4b6Ik8G1aB/2p2K4J+JkiLAWZphQU4I777yTBx54gG984xv09fXx/PPP8/zzz/Pyyy83FEKvN3M+zF8JpTofRV/qgatXwcwGfsU7dYbU4wMcY4j9bKfMqbquL3OKfXyfYxyuO0OEeWgH9qfiuC9iZHAd2os9qhjuizgZXIv2YX8qhnsiToYIa2GGCTUdSt13330MDw9z6623Mnv27PGvb33rWw2F0LndsB6y0/Vdm5Vhybr2z5B6fIDH2EQ3M+q6totudrCl4QwR5iE6+1Ox3BcxMrgO7cMeVRz3RZwMrkV7sD8Vxz0RJ0OEtTBD5efUIMuyc36tXbu24SB6vdnL4OZN9V1787359e2eIfX4AIPs5jvU1/m+y90MsrvhDBHmITr7U7HcFzEyuA7twx5VHPdFnAyuRXuwPxXHPREnQ4S1MEOusV8gVMstvmtiw051i2Pl/Zs35ddNlwypxwfYwZbxzTrV7Y2V97/DuqacHFdEmAdpMvdFjAyug/R67os4GVwL6UzuiTgZIqyFGTyUCq9Uym9PXLUT5t8OlPKPwKx8jOb461L+/qqd+feXStMnQ+rxK3awhU0sYz+PMMYYZU5T5jQZY5Q5RZnTjDHGfh5hE8ua2iggzjxIk7kvYmRwHaTXc1/EyACuhXQ290SMDJB+LcwAdT5eTEWbvSz/OjEEB7bCyEF4dQQu6s8/DnPRHa1/CGPqDKnHh/z2xkF2M4u5LOUOrmABl9DPy4zwIgfZw9aGH/Q2lQjzIE3mvoiRwXWQXs99ESeDayGdyT0RJ0OEtejkDB5KtZmZ8+Cmz3R2htTjAxzjMI/wuaQZIsyDNJn7IkYG10F6PfdFnAyuhXQm90ScDBHWohMz+Ot7kiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSpcKcuyrMgBR0ZGGBgYgBJcNqfIkXMvHYVsDEpdcOns4sc3gxmiZUg9PsDJI0AGw8PD9Pf3pwlB+v4EMdYjdYbU45vBDGeL0KPsT2aIMr4ZYmWwP+UirIUZzBBl/CgZqu1P6Q6lJOksYQ6lJOkcQvxHnySdg/1JUlRT9aeeArOcyTulzGCGEBlSjw8Tp+hh+Dd9HV+TZjDDZKF6lP2p4zOkHt8MsTLYn3IR1sIMZogyfpQM1fanZIdSl14Faw4XP+6Dc+Hkz/KFSTG+GcwQLUPq8QEemJM3zihS9SeIsR6pM6Qe3wxmOFukHmV/MkPq8c0QK4P9KRdhLcxghijjR8lQbX/yQeeSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXLpP32tDs5jHUtZyJQu5mD5e4TgvMMgetnGModTxCnPiEBzYBsODcOo4zOiDgYWwaC3MnD/9x4+SwXrUZNZDLsI8pO4PqceHGOugOKyHXIR5iNAfImSIsBaKw3qIMQcRekOEDBHWomgeSlVhIctYzjoWs5KMMQC66GLstdcruYd9PMwONjPI7pRRW+rITti3GQ5tzz9aEiArQ6k7f/30PXD1SliyHmYvm37jR8lgPWoy6yEXYR5S94fU40OMdVAc1kMuwjxE6A8RMkRYC8VhPcSYgwi9IUKGCGuRir++N4XlrGM9O7meFXTRRTc9dNNDadLrLrpYzO2sZxe3cVfqyE2XZfDsJth+Kww9CmT5Js3Kr71feZ3BoUfh4ffkmzrLpsf4UTKA9agzWQ+51POQuj+kHr8i9TooFushl3oeIvSHCBkg/VooFush/RxE6A0RMkD6tUjNQ6kLuI27+AibAOhmxgW/t/L+ajZPuyLZvwUevzt/nZ2+8PdW3t+7Pr9uOowfJYP1qMmsh1yEeUjdH1KPDzHWQXFYD7kI8xChP0TIEGEtFIf1EGMOIvSGCBkirEVqNR1K3XfffSxZsoT+/n76+/t517vexaOPPtqqbEktZBmr2VzXtavZzELe3eREaRzZmW+8euxdD0d3tff4UTJYj1OzP1VnOtVDhHlI3R9Sjw8x1qEddEqPsh5yEeYhQn+IkCHCWkTXKf0JrAeIMQcRekOEDBHWIoKaDqXmzp3LF7/4RZ5++mmeeuopfvVXf5UPf/jD/I//8T9alS+Z5ayjzKm6ri1zatqcXO7bDKU6nzxW6smvb+fxo2SwHqdmf6rOdKqHCPOQuj+kHh9irEM76JQeZT3kIsxDhP4QIUOEtYiuU/oTWA8QYw4i9IYIGSKsRQQ1HUqtWrWK22+/nYULF/LWt76Vz3/+88ycOZO9e/e2Kl8Ss5jHYlZOefvc+XQzgyV8iFnMbXKyYp04lD/sbapbGc8nOw0/fRhO1PkhAanHj5LBeqyO/ak606UeIsxD6v6QenyIsQ7tohN6lPWQizAPEfpDhAwR1qIddEJ/AusBYsxBhN4QIUOEtYii7mdKlctlHnroIU6ePMm73vWuZmZKbilrx594X6+MMZZyR5MSpXFg28SnD9Sr1AUHtrbn+FEyWI+1sz9d2HSohwjzkLo/pB4fYqxDO5quPcp6yEWYhwj9IUKGCGvRbqZrfwLrAWLMQYTeECFDhLWIouYb1vbv38+73vUuXnnlFWbOnMn3vvc9fvmXf/m83z86Osro6Oj4P4+MjNSXtEBXsrAJPyXjChY04eekMzzYnJ8zcrA9x4+SwXqsnv2pWu1fDxHmIXV/SD0+xFiHdlJLj7I/ta8I8xChP0TIEGEt2sV0709gPUCMOYjQGyJkiLAWUdR8Prho0SKeeeYZHn/8cX73d3+Xj33sY/zt3/7teb9/48aNDAwMjH/NmzevocBFuJg+uhr8YMIuurmE/iYlSuPU8YmPw6xXVoZX6/z3VOrxo2SwHqtnf6rOdKiHCPOQuj+kHh9irEM7qaVH2Z/aV4R5iNAfImSIsBbtYrr3J7AeIMYcROgNETJEWIsoap6Fiy66iAULFnDTTTexceNGbrjhBv7Tf/pP5/3+DRs2MDw8PP41NNTAL14W5BWOM9bgrXRjlHmZ9vhbg/OZ0Qel7sZ+RqkbLqpzn6QeP0oG67F69qfqTId6iDAPqftD6vEhxjq0k1p6lP2pfUWYhwj9IUKGCGvRLqZ7fwLrAWLMQYTeECFDhLWIos7nzU8YGxs74/bNs/X29tLb29voMIV6gWbcz1fiRRq4ny+AgWbcUQj013lHYerxo2SwHutnfzqf9q+HCPOQuj+kHh9irEM7u1CPsj+1rwjzEKE/RMgQYS3a1XTrT2A9QIw5iNAbImSIsBZR1HSn1IYNG9i1axfPPfcc+/fvZ8OGDfz4xz9mzZo1rcqXxB62UWrwVroSXeyhgSefBbBoLWSNHd6SjcGiOp+9lnr8KBmsx+rYn6o3Heohwjyk7g+px4cY69AuOqFHWQ+5CPMQoT9EyBBhLdpBJ/QnsB4gxhxE6A0RMkRYiyhqmoUXXniB3/qt32LRokW8733v48knn+RP//RPWb58eavyJXGMIfaznTKn6rq+zCn28X2OcbjJyYo1cz7MXwmlOu+nK/XA1atgZp2/Zp56/CgZrMfq2J+qM13qIcI8pO4PqceHGOvQLjqhR1kPuQjzEKE/RMgQYS3aQSf0J7AeIMYcROgNETJEWIsoalqG+++/v1U5wnmMTdzAh+q6totudrClyYnSuGE9HHq4vmuzMixZ197jR8lgPU7N/lSd6VQPEeYhdX9IPT7EWId20Ck9ynrIRZiHCP0hQoYIaxFdp/QnsB4gxhxE6A0RMkRYiwgau19sGhtkN9+hvkr7LnczyO4mJ0pj9jK4eVN91958b359O48fJYP1qMmsh1yEeUjdH1KPDzHWQXFYD7kI8xChP0TIEGEtFIf1EGMOIvSGCBkirEUEHkpdwA62jBfJVLfVVd7/DuumzYllxeK7JjbsVLc4Vt6/eVN+3XQYP0oG61GTWQ+5CPOQuj+kHh9irIPisB5yEeYhQn+IkCHCWigO6yHGHEToDREyRFiL1DyUmsIOtrCJZeznEcYYo8xpypwmY4wypyhzmjHG2M8jbGLZtCqOilIpvz1x1U6YfztQyj8Cs/IxmuOvS/n7q3bm318qTY/xo2QA61Fnsh5yqechdX9IPX5F6nVQLNZDLvU8ROgPETJA+rVQLNZD+jmI0BsiZID0a5FanY/26iyD7GaQ3cxiLku5gytYwCX08zIjvMhB9rB1WjxgbCqzl+VfJ4bgwFYYOQivjsBF/fnHYS66o7GHvUUfP0oG61GTWQ+5CPOQuj+kHh9irIPisB5yEeYhQn+IkCHCWigO6yHGHEToDREyRFiLVDyUqsExDvMIn0sdI7mZ8+Cmz3Tu+FEyWI+azHrIRZiH1P0h9fgQYx0Uh/WQizAPEfpDhAwR1kJxWA8x5iBCb4iQIcJaFM1f35MkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhSlmWZUUOODIywsDAAJTgsjlFjpx76ShkY1DqgktnFz++GcwQLUPq8QFOHgEyGB4epr+/P00I0vcniLEeqTOkHt8MZjhbhB5lfzJDlPHNECuD/SkXYS3MYIYo40fJUG1/SncoJUlnCXMoJUnnEOI/+iTpHOxPkqKaqj/1FJjlTN4pZQYzhMiQenyYOEUPw7/p6/iaNIMZJgvVo+xPHZ8h9fhmiJXB/pSLsBZmMEOU8aNkqLY/JTuUuvQqWHO4+HEfnAsnf5YvTIrxzWCGaBlSjw/wwJy8cUaRqj9BjPVInSH1+GYww9ki9Sj7kxlSj2+GWBnsT7kIa2EGM0QZP0qGavuTDzqXJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4dJ9+p7qMot5LGUtV7KQi+njFY7zAoPsYRvHGCokw4lDcGAbDA/CqeMwow8GFsKitTBz/vQf3wwTItSj4ohQD+6LGHMQIUPqdVAsEerBfZGLMA+pM0RYB8URoR5S7wlwHiJlKHotPJRqEwtZxnLWsZiVZIwB0EUXY6+9Xsk97ONhdrCZQXa3JMORnbBvMxzann+0JEBWhlJ3/vrpe+DqlbBkPcxeNv3GN8OECPWoOCLUg/sixhxEyJB6HRRLhHpwX+QizEPqDBHWQXFEqIfUewKch0gZUq2Fv77XBpazjvXs5HpW0EUX3fTQTQ+lSa+76GIxt7OeXdzGXU0dP8vg2U2w/VYYehTI8g2SlV97v/I6g0OPwsPvyTdUlk2P8c1wptT1qFhS14P7IsYcRMgA6etRsaSuB/dFLsI8RMiQeh0US+p6iLAnwHmIkgHSroWHUsHdxl18hE0AdDPjgt9beX81m5taJPu3wON356+z0xf+3sr7e9fn102H8c0wIUI9Ko4I9eC+iDEHETKkXgfFEqEe3Be5CPOQOkOEdVAcEeoh9Z4A5yFShtRr4aFUYAtZxmo213XtajazkHc3nOHIzrzo67F3PRzd1d7jm2FChHpUHBHqwX0RYw4iZEi9DoolQj24L3IR5iF1hgjroDgi1EPqPQHOQ6QMEdaioUOpL37xi5RKJf7gD/6g4SB6veWso8ypuq4tc6opJ5f7NkOpziePlXry69t5fDNMiFCPtbA/tVaEenBfxJiDCBlSr0Ot7E+tFaEe3Be5CPOQOkOEdaiVPap1ItRD6j0BzkOkDBHWou5DqSeffJL/8l/+C0uWLGk4hF5vFvNYzMopb587n25msIQPMYu5dWc4cSh/0NpUtxGeT3YafvownKjzAf2pxzfDhAj1WAv7U2tFqAf3RYw5iJAh9TrUyv7UWhHqwX2RizAPqTNEWIda2aNaJ0I9pN4T4DxEyhBhLaDOQ6kTJ06wZs0avvrVrzJr1qyGAujclrJ2/In39coYYyl31H39gW0TT/6vV6kLDmxtz/HNMCFCPVbL/tR6EerBfRFjDiJkSL0OtbA/tV6EenBf5CLMQ+oMEdahFvao1opQD6n3BDgPkTJEWAuo81Dqzjvv5IMf/CC33XbblN87OjrKyMjIGV+a2pUsbMJPybiCBXVfPTzYhAjAyMH2HN8MEyLUY7XsT60XoR7cFzHmIEKG1OtQC/tT60WoB/dFLsI8pM4QYR1qUW2Psj/VJ0I9pN4T4DxEyhBhLQBq/g3Ghx56iL/6q7/iySefrOr7N27cyGc/+9mag3W6i+mjq8Hn0HfRzSX01339qeMTH0VZr6wMr9b576nU45thQoR6rIb9qRgR6sF9EWMOImRIvQ7Vsj8VI0I9uC9yEeYhdYYI61CtWnqU/ak+Eeoh9Z4A5yFShghrkf+MGgwNDfGpT32KBx98kIsvvriqazZs2MDw8PD419BQA7/02EFe4ThjDd5KN0aZl6m/Smf0Qam7oQiUuuGiOms09fhmmBChHqdifypOhHpwX8SYgwgZUq9DNexPxYlQD+6LXIR5SJ0hwjpUo9YeZX+qT4R6SL0nwHmIlCHCWkCNd0o9/fTTvPDCC7ztbW8b/9/K5TK7du3iy1/+MqOjo3R3nzmzvb299Pb2NhSyE71AM+7nK/Ei9d/PN9CMu/mA/jrv5ks9vhkmRKjHqdifihOhHtwXMeYgQobU61AN+1NxItSD+yIXYR5SZ4iwDtWotUfZn+oToR5S7wlwHiJliLAWUOOdUu973/vYv38/zzzzzPjX29/+dtasWcMzzzzzuj9QqX572EapwVvpSnSxh/qffLZoLWSNHZySjcGiOp97lnp8M0yIUI9TsT8VJ0I9uC9izEGEDKnXoRr2p+JEqAf3RS7CPKTOEGEdqmGPKkaEeki9J8B5iJQhwlpAjYdSfX19XH/99Wd8XXbZZVx++eVcf/31DQXRmY4xxH62U+ZUXdeXOcU+vs8xDtedYeZ8mL8SSjU/eSxX6oGrV8HMee05vhkmRKjHqdifihOhHtwXMeYgQobU61AN+1NxItSD+yIXYR5SZ4iwDtWwRxUjQj2k3hPgPETKEGEtoM5P31MxHmMT3cyo69ouutnBloYz3LAestP1XZuVYcm69h7fDBMi1KPiiFAP7osYcxAhQ+p1UCwR6sF9kYswD6kzRFgHxRGhHlLvCXAeImWIsBYNH0r9+Mc/5ktf+lLDQfR6g+zmO9RXad/lbgbZ3XCG2cvg5k31XXvzvfn17Ty+GSZEqMda2Z9aJ0I9uC9izEGEDKnXoR72p9aJUA/ui1yEeUidIcI61MMe1RoR6iH1ngDnIVKGCGvhnVLB7WDLeJFMdVtd5f3vsK6pf6uy+K6JzTLV7YWV92/elF83HcY3w4QI9ag4ItSD+yLGHETIkHodFEuEenBf5CLMQ+oMEdZBcUSoh9R7ApyHSBlSr4WHUm1gB1vYxDL28whjjFHmNGVOkzFGmVOUOc0YY+znETaxrOn/AiuV8lsDV+2E+bcDpfzjJysfYTn+upS/v2pn/v2l0vQY3wxnSl2PiiV1PbgvYsxBhAyQvh4VS+p6cF/kIsxDhAyp10GxpK6HCHsCnIcoGSDtWtT5WC0VbZDdDLKbWcxlKXdwBQu4hH5eZoQXOcgetrb8IYizl+VfJ4bgwFYYOQivjsBF/flHUS66o7EHrUUf3wwTItSj4ohQD+6LGHMQIUPqdVAsEerBfZGLMA+pM0RYB8URoR5S7wlwHiJlSLUWHkq1mWMc5hE+lzTDzHlw02c6d3wzTIhQj4ojQj24L2LMQYQMqddBsUSoB/dFLsI8pM4QYR0UR4R6SL0nwHmIlKHotfDX9yRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuFKWZVmRA46MjDAwMAAluGxOkSPnXjoK2RiUuuDS2cWPbwYzRMuQenyAk0eADIaHh+nv708TgvT9CWKsR+oMqcc3gxnOFqFH2Z/MEGV8M8TKYH/KRVgLM5ghyvhRMlTbn9IdSknSWcIcSknSOYT4jz5JOgf7k6SopupPPQVmOZN3SpnBDCEypB4fJk7Rw/Bv+jq+Js1ghslC9Sj7U8dnSD2+GWJlsD/lIqyFGcwQZfwoGartT8kOpS69CtYcLn7cB+fCyZ/lC5NifDOYIVqG1OMDPDAnb5xRpOpPEGM9UmdIPb4ZzHC2SD3K/mSG1OObIVYG+1MuwlqYwQxRxo+Sodr+5IPOJUmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLh0n77XhmYxj6Ws5UoWcjF9vMJxXmCQPWzjGEMdk+HEITiwDYYH4dRxmNEHAwth0VqYOb/140eYAzPEyaBchLWIkCF1f4L085B6fDPEk3pfpB7fDBMi7AszpB8/kgj7InWG1ONHyRBhX5ghTQYPpaqwkGUsZx2LWUnGGABddDH22uuV3MM+HmYHmxlk97TNcGQn7NsMh7bnHy0JkJWh1J2/fvoeuHolLFkPs5c1f/wIc2CGOBmUi7AWETKk7k+Qfh5Sj2+GeFLvi9Tjm2FChH1hhvTjRxJhX6TOkHr8KBki7AszpM3gr+9NYTnrWM9OrmcFXXTRTQ/d9FCa9LqLLhZzO+vZxW3cNe0yZBk8uwm23wpDjwJZ3qyy8mvvV15ncOhRePg9eXPLsuZlSD0HZoiVQbkIa5E6Q4T+BOnnIfX4Zogl9b5IPb4ZzhRhX5gh/fhRRNgXqTOkHj9KBoixL8yQPoOHUhdwG3fxETYB0M2MC35v5f3VbG7qAkXIsH8LPH53/jo7feHvrby/d31+XTNEmAMzxMmgXIS1iJAhdX+C9POQenwzxJN6X6Qe3wwTIuwLM6QfP5II+yJ1htTjR8kQYV+YIUaGmg6l7rnnHkql0hlf1157bVOCRLOQZaxmc13XrmYzC3n3tMhwZGfegOqxdz0c3dXY+BHmwAxxMlyI/ak606keUvcnSD8Pqcc3Q/WK6lGp90Xq8c0wIcK+MEP68avRKf0pQobU40fJEGFfmCFOhprvlLruuus4evTo+Ndf/MVfNBwiouWso8ypuq4tc6opp4YRMuzbDKU6nzxW6smvb0SEOTBDnAxTsT9NbTrVQ+r+BOnnIfX4ZqhNET0q9b5IPb4ZJkTYF2ZIP361OqE/RciQevwoGSLsCzPEyVDzoVRPTw9XXXXV+Neb3vSmhkNEM4t5LGbllLeunU83M1jCh5jF3LbOcOJQ/tC7qW7pPJ/sNPz0YThR5wP6I8yBGeJkqIb9aWrTpR5S9ydIPw+pxzdD7Vrdo1Lvi9Tjm2FChH1hhvTj12K696cIGVKPHyVDhH1hhjgZoI5DqcHBQebMmcOb3/xm1qxZw6FDhxoKENFS1o4/bb5eGWMs5Y62znBg28SnMNSr1AUHttZ3bYQ5MEOcDNWwP1VnOtRD6v4E6ech9fhmqF2re1TqfZF6fDNMiLAvzJB+/FpM9/4UIUPq8aNkiLAvzBAnA0BNN+79yq/8Ctu2bWPRokUcPXqUz372s7z73e/mb/7mb+jr6zvnNaOjo4yOjo7/88jISEOBi3AlC5vwUzKuYEFbZxgebEIEYORgfddFmAMzxMkwFftTLdq/HlL3J0g/D6nHN0Ntau1R9fSn1Psi9fhmmBBhX5gh/fjV6oT+FCFD6vGjZIiwL8wQJwPUeCi1YsWK8ddLlizhV37lV7j66qv59re/zW//9m+f85qNGzfy2c9+tqGQRbuYProa/GDCLrq5hP62znDq+MTHgtYrK8Ordf53foQ5MEOcDFOxP1VvOtRD6v4E6ech9fhmqE2tPaqe/pR6X6Qe3wwTIuwLM6Qfv1qd0J8iZEg9fpQMEfaFGeJkyH9GA97whjfw1re+lYMHz39UumHDBoaHh8e/hoYa+AXUgrzCccYavI1tjDIvU/9ujZBhRh+UuhuKQKkbLqqzRiPMgRniZKiV/en8pkM9pO5PkH4eUo9vhsZM1aPq6U+p90Xq8c0wIcK+MEP68es1HftThAypx4+SIcK+MEOcDNDgodSJEyf4n//zfzJ79uzzfk9vby/9/f1nfEX3As24r7HEi9R/X2OEDAPNuJsP6K/zbr4Ic2CGOBlqZX+6kPavh9T9CdLPQ+rxzdCYqXpUPf0p9b5IPb4ZJkTYF2ZIP369pmN/ipAh9fhRMkTYF2aIkwFqPJRav349O3fu5LnnnmPPnj38+q//Ot3d3fzmb/5mQyGi2cM2Sg3exlaiiz3U/wS4CBkWrYWssYNTsjFYVOdzzyLMgRniZJiK/al606EeUvcnSD8Pqcc3Q22K6FGp90Xq8c0wIcK+MEP68avVCf0pQobU40fJEGFfmCFOBqjxUOrw4cP85m/+JosWLeKf/JN/wuWXX87evXu54oorGgoRzTGG2M92ypyq6/oyp9jH9znG4bbOMHM+zF8JpZqePDah1ANXr4KZ8+q7PsIcmCFOhqnYn6ozXeohdX+C9POQenwz1KaIHpV6X6Qe3wwTIuwLM6Qfv1qd0J8iZEg9fpQMEfaFGeJkgBoPpR566CGOHDnC6Ogohw8f5qGHHuItb3lLQwGieoxNdDOjrmu76GYHW6ZFhhvWQ3a6vmuzMixZ19j4EebADHEyXIj9qTrTqR5S9ydIPw+pxzdD9YrqUan3RerxzTAhwr4wQ/rxq9Ep/SlChtTjR8kQYV+YIU6Gxu7VmsYG2c13qG/HfZe7GWT3tMgwexncvKm+a2++N7++ERHmwAxxMigXYS0iZEjdnyD9PKQe3wzxpN4Xqcc3w4QI+8IM6cePJMK+SJ0h9fhRMkTYF2aIk8FDqQvYwZbxBZrqlrbK+99hXVP/RiNChsV3TTSuqW71rLx/86b8umaIMAdmiJNBuQhrESFD6v4E6ech9fhmiCf1vkg9vhkmRNgXZkg/fiQR9kXqDKnHj5Ihwr4wQ4wMHkpNYQdb2MQy9vMIY4xR5jRlTpMxRplTlDnNGGPs5xE2sawl//JInaFUym/TXLUT5t8OlPKPAq18nOj461L+/qqd+feXSs3LkHoOzBArg3IR1iJ1hgj9CdLPQ+rxzRBL6n2RenwznCnCvjBD+vGjiLAvUmdIPX6UDBBjX5ghfYY6H3HWWQbZzSC7mcVclnIHV7CAS+jnZUZ4kYPsYWvLH0AYIcPsZfnXiSE4sBVGDsKrI3BRf/6xoIvuaOyhd1OJMAdmiJNBuQhrESFD6v4E6ech9fhmiCf1vkg9vhkmRNgXZkg/fiQR9kXqDKnHj5Ihwr4wQ9oMHkrV4BiHeYTPdXyGmfPgps+kGz/CHJghTgblIqxFhAyp+xOkn4fU45shntT7IvX4ZpgQYV+YIf34kUTYF6kzpB4/SoYI+8IMaTL463uSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXCnLsqzIAUdGRhgYGIASXDanyJFzLx2FbAxKXXDp7OLHN4MZomVIPT7AySNABsPDw/T396cJQfr+BDHWI3WG1OObwQxni9Cj7E9miDK+GWJlsD/lIqyFGcwQZfwoGartT+kOpSTpLGEOpSTpHEL8R58knYP9SVJUU/WnngKznMk7pcxghhAZUo8PE6foYfg3fR1fk2Yww2ShepT9qeMzpB7fDLEy2J9yEdbCDGaIMn6UDNX2p2SHUpdeBWsOFz/ug3Ph5M/yhUkxvhnMEC1D6vEBHpiTN84oUvUniLEeqTOkHt8MZjhbpB5lfzJD6vHNECuD/SkXYS3MYIYo40fJUG1/8kHnkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKly6T99rQ7OYx1LWciULuZg+XuE4LzDIHrZxjKFCMpw4BAe2wfAgnDoOM/pgYCEsWgsz5xcSIUSG1CLMgRk0mf0pTobUIsyBGTSZ/SlOhggizEPqDKnH15lS96gI9RAhQwQR5qETM3goVYWFLGM561jMSjLGAOiii7HXXq/kHvbxMDvYzCC7W5LhyE7YtxkObc8/1hEgK0OpO3/99D1w9UpYsh5mL2tJhBAZUoswB2bQZPanOBlSizAHZtBk9qc4GSKIMA+pM6QeX2dK3aMi1EOEDBFEmIdOzuCv701hOetYz06uZwVddNFND930UJr0uosuFnM769nFbdzV1PGzDJ7dBNtvhaFHgSwvjKz82vuV1xkcehQefk9eSFk2vTKkFmEOzKCz2Z9iZEgtwhyYQWezP8XIEEGEeUidIfX4er2UPSpCPUTIEEGEeTCDh1IXdBt38RE2AdDNjAt+b+X91WxuatPavwUevzt/nZ2+8PdW3t+7Pr9uOmVILcIcmEGT2Z/iZEgtwhyYQZPZn+JkiCDCPKTOkHp8nSl1j4pQDxEyRBBhHszgodR5LWQZq9lc17Wr2cxC3t1whiM788Wux971cHRXwxFCZEgtwhyYQZPZn+JkSC3CHJhBk9mf4mSIIMI8pM6QenydKXWPilAPETJEEGEezJCr+VDqZz/7GR/96Ee5/PLLueSSS1i8eDFPPfVU40mCWc46ypyq69oyp5pykr5vM5TqfOpXqSe/fjpkSC3CHJihOvanqdmfmpshtQhzYIbqdUKPsj/FyRBBhHlInSH1+NXqhP4E6XtUhHqIkCGCCPNghlxNh1LHjh3jlltuYcaMGTz66KP87d/+LZs3b2bWrFmNJwlkFvNYzMopb+c8n25msIQPMYu5dWc4cSh/wNhUt8+dT3YafvownGjgAyMiZEgtwhyYoTr2p+rYn5qXIbUIc2CG6nVCj7I/xckQQYR5SJ0h9fjV6oT+BOl7VIR6iJAhggjzYIYJNR1K/dEf/RHz5s1j69atvPOd7+Saa67h/e9/P295y1saSxHMUtaOfwJDvTLGWModdV9/YNvEE+/rVeqCA1vrvz5ChtQizIEZqmN/qp79qTkZUoswB2aoXif0KPtTnAwRRJiH1BlSj1+tTuhPkL5HRaiHCBkiiDAPZphQU4Tvf//7vP3tb2f16tVceeWV3HjjjXz1q1+94DWjo6OMjIyc8RXdlSxswk/J+P/Zu/8gq+77vv/Pu7to9YPdNZZRBGFRZINRY4FGlp3KaIzlWCRGBjuZhLYZ3BilzbeNceIEUGM6E1eta5OMgHFbO2rryuCO5F/yRBkLVUqEHQMZop+pBGkcsjSRWAyqNC3eBSQh2D3fP47u7rIC9v48n/fd+3zM7Hitu2ffL3/O+7yNPpx77mwW1Hz00EADIgDDh2o/NkKG1CKsgRkq43yqhvOpERlSi7AGZqhctTPK+VSbCP0QIUMEEdYhdYbU9SvVDvMJ0s+oCP0QIUMEEdbBDOOq2pT6u7/7O+655x4WLlzIn/zJn/Abv/Eb/NZv/RZf+9rXLnjM5s2b6evrG/vq7++vL3EBLqWHjjqfAd9BJ5fRW/PxZ06MfwRjrbIReL2O/4+IkCG1CGtghso4nyrnfGpMhtQirIEZKlftjHI+1SZCP0TIEEGEdUidIXX9SrXDfIL0MypCP0TIEEGEdTDDuKquytHRUd797nfzhS98gRtvvJH/7//7//j1X/91/vN//s8XPGbTpk0MDQ2NfQ0Oxn8D6mucYLTOWztHGeFVaj87M3qg1FlXBEqdcEntf64LkSG1CGtghso4nyrnfGpMhtQirIEZKlftjHI+1SZCP0TIEEGEdUidIXX9SrXDfIL0MypCP0TIEEGEdTDDuKo2pebMmcNP//RPn/PP/sE/+AccPnz4gsd0d3fT29t7zld0L9GI+9hKvEzt97H1NeLuUqC39jvgQ2RILcIamKEyzqdqOJ8akSG1CGtghspVO6OcT7WJ0A8RMkQQYR1SZ0hdv1LtMJ8g/YyK0A8RMkQQYR3MMK6qTalbbrmFgwcPnvPP/vZv/5ZrrrmmvhTB7GMHpTpv7SzRwT5qf+LXorWQ1beRTzYKi2p/VmiIDKlFWAMzVMb5VDnnU2MypBZhDcxQuXaYUc6nOBkiiLAOqTOkrl+pdphPkH5GReiHCBkiiLAOZhhX1VX5O7/zOzz++ON84Qtf4NChQ3z961/nv/7X/8q6devqSxHMcQY5wE5GOFPT8SOcYT/f5ThHas4wcz7MXwmlrtqOL3XBNatgZh1v8Y6QIbUIa2CGyjifKuN8alyG1CKsgRkq1w4zyvkUJ0MEEdYhdYbU9SvVDvMJ0s+oCP0QIUMEEdbBDOOq2pR673vfy4MPPsg3vvENrr/+ej73uc/xxS9+kTVr1tSXIqDH2EInM2o6toNOdrGt7gw3bITsbG3HZiOwZEPdEUJkSC3CGphhas6nyjifGpshtQhrYIbKtMuMcj7FyRBBhHVInSF1/Uq0y3yC9DMqQj9EyBBBhHUwQ67q+xdXrlzJgQMHeO211/jhD3/Ir//6r9efIqAB9vIAta3wd7iTAfbWnWHOMrh5S23H3nx3fvx0yJBahDUwQ2WcT1NzPjU2Q2oR1sAMlWuHGeV8ipMhggjrkDpD6vqVaof5BOlnVIR+iJAhggjrYIZcfW+qneZ2sW1saE11m2f59QfY0JC/5StbvH68Saa6ra78+s1b8uOmU4bUIqyBGTSR8ylOhtQirIEZNJHzKU6GCCKsQ+oMqevrXKlnVIR+iJAhggjrYAY3paa0i21sYRkHeJhRRhnhLCOcJWOUEc4wwllGGeUAD7OFZQ39AxVAqZTfErdqN8y/HSjlH7tY/ujGse9L+eurduc/XypNrwypRVgDM2gy51OMDKlFWAMzaDLnU4wMEURYh9QZUtfXm6WcURH6IUKGCCKsgxmgxkdatZcB9jLAXmYxj6XcwWwWcBm9vMowL3OIfWyv66GclZizLP86OQgHt8PwIXh9GC7pzT+CcdEdzX/gXIQMqUVYAzNoIudTnAypRVgDM2gi51OcDBFEWIfUGVLX17lSz6gI/RAhQwQR1qGdM7gpVYXjHOFhPpc0w8x+uOmzSSOEyJBahDUwgyZyPsXJkFqENTCDJnI+xckQQYR1SJ0hdX2dK/WMitAPETJEEGEd2jGDb9+TJEmSJElS4dyUkiRJkiRJUuHclJIkSZIkSVLh3JSSJEmSJElS4dyUkiRJkiRJUuFKWZZlRRYcHh6mr68PSnDF3CIr5145BtkolDrg8jnF1zeDGaJlSF0f4NRRIIOhoSF6e3vThCD9fIIY5yN1htT1zWCGySLMKOeTGaLUN0OsDM6nXIRzYQYzRKkfJUOl8yndppQkTRJmU0qSziPEv/RJ0nk4nyRFNdV86iowy7m8U8oMZgiRIXV9GN9FD8O/6Wv7njSDGSYKNaOcT22fIXV9M8TK4HzKRTgXZjBDlPpRMlQ6n5JtSl1+Naw5Unzd++fBqR/lJyZFfTOYIVqG1PUB7pubD84oUs0niHE+UmdIXd8MZpgs0oxyPpkhdX0zxMrgfMpFOBdmMEOU+lEyVDqffNC5JEmSJEmSCuemlCRJkiRJkgrnppQkSZIkSZIK56aUJEmSJEmSCpfu0/eqNIt+lrKWq1jIpfTwGid4iQH2sYPjDKaO11ZOHoaDO2BoAM6cgBk90LcQFq2FmfNTp1OR7IWc8ykOe1Jl9sI4Z1QM9qTK7IVxzqcY7ElNVHQ/hN+UWsgylrOBxawkYxSADjoYfeP7ldzFfh5iF1sZYG/KqNPe0d2wfysc3pl/tCRANgKlzvz7Z+6Ca1bCko0wZ1mymCqAvZBzPsVhT6rMXhjnjIrBnlSZvTDO+RSDPamJUvVD6LfvLWcDG9nN9ayggw466aKTLkoTvu+gg8Xczkb2cBvrU0eelrIMntsCO2+FwUeALG/ObOSN18vfZ3D4EXjoA3kzZ1nC0GoKe2Gc8ykGe1Jl9sK5nFHp2ZMqsxfO5XxKz57URKn7Ieym1G2s55fZAkAnMy76s+XXV7PVodUEB7bBE3fm32dnL/6z5dcf35gfp+nFXsg5n+KwJ1VmL4xzRsVgT6rMXhjnfIrBntREqfsh5KbUQpaxmq01HbuarSzk/Q1O1L6O7s4brhaPb4RjexqbR+nYCznnUxz2pMrshXHOqBjsSZXZC+OcTzHYk5ooQj9UtSn1Uz/1U5RKpTd9rVu3rv4kEyxnAyOcqenYEc64k95A+7dCqcYnj5W68uM1PbRCLxQxo5xPcbRCT6oYrdAL/hmqvbRCT6oYrdALzqf20go9qeJE6IeqNqWeeuopjh07Nvb12GOPAbB69er6k7xhFv0sZuWUt3NeSCczWMJHmcW8hmVqVycP5w85m+oWvgvJzsILD8FJPzij5bVKLzR7Rjmf4miVnlTztUov+Geo9tEqPanma5VecD61j1bpSRUjSj9UtSk1e/Zsrr766rGvnTt38o53vIMPfOAD9aWYYClrxz6BoVYZoyzljgYlal8Hd4w/db9WpQ44uL0hcZRQq/RCs2eU8ymOVulJNV+r9IJ/hmofrdKTar5W6QXnU/tolZ5UMaL0Q403asHrr7/Offfdx/r16ymVShf8udOnT3P69Omx/z48PHzR33sVC2uNNEHGbBY04Pe0t6GBxvye4UON+T1KpxV7oZIZ5XxqXa3Yk2qOVuyFZswncEZF0Yo9qeZoxV5wPk1vrdiTap4o/VDzvtgf//Ef8+Mf/5i1a9de9Oc2b95MX1/f2Fd/f/9Ff/5Seuio8/nrHXRyGb11/Q7BmRPjHwNZq2wEXp/6/6cUXCv2QiUzyvnUulqxJ9UcrdgLzZhP4IyKohV7Us3Rir3gfJreWrEn1TxR+qHmyXDvvfeyYsUK5s6de9Gf27RpE0NDQ2Nfg4MXf8Pha5xgtM5bO0cZ4VW8Uuo1owdKnfX9jlInXOL/d7S8VuyFSmaU86l1tWJPqjlasReaMZ/AGRVFK/akmqMVe8H5NL21Yk+qeaL0Q01v33vhhRfYtWsXf/RHfzTlz3Z3d9Pd3V3x736JRtxDVuJlvKewXn2NuMsW6PUu25bXar1Q6YxyPrWuVutJNU+r9UKz5hM4o6JotZ5U87RaLzifpr9W60k1V5R+qOlOqe3bt3PVVVfxkY98pL7q57GPHZTqvLWzRAf78Olr9Vq0FrL6/kKDbBQW+TzCltdqvdCsGeV8iqPVelLN02q94J+hpr9W60k1T6v1gvNp+mu1nlRzRemHqifD6Ogo27dv5xOf+ARdXTU/J/2CjjPIAXYywpmajh/hDPv5Lsc50uBk7WfmfJi/Eko1nuZSF1yzCmZO/TZzBddKvdDMGeV8iqOVelLN1Uq94J+h2kMr9aSaq5V6wfnUHlqpJ9V8Ufqh6k2pXbt2cfjwYX7t136tvsoX8Rhb6GRGTcd20MkutjU4Ufu6YSNkZ2s7NhuBJRsam0fptEovNHtGOZ/iaJWeVPO1Si/4Z6j20So9qeZrlV5wPrWPVulJFSNCP1S9KfVzP/dzZFnGO9/5zvqrX8AAe3mA2v7XfYc7GWBvgxO1rznL4OYttR1789358ZoeWqUXmj2jnE9xtEpPqvlapRf8M1T7aJWeVPO1Si84n9pHq/SkihGhH+p7Y28T7WLb2NCa6jbP8usPsMEd9CZYvH68Uae6ta/8+s1b8uM0vdgLOedTHPakyuyFcc6oGOxJldkL45xPMdiTmih1P4TdlIJ8aG1hGQd4mFFGGeEsI5wlY5QRzjDCWUYZ5QAPs4VlDqsmKZXy2/JW7Yb5twOl/KMfyx8fOfZ9KX991e7850ullKnVDPbCOOdTDPakyuyFczmj0rMnVWYvnMv5lJ49qYlS90Pjn2LXYAPsZYC9zGIeS7mD2SzgMnp5lWFe5hD72O4D7woyZ1n+dXIQDm6H4UPw+jBc0pt/DOSiO3zoXbuwF3LOpzjsSZXZC+OcUTHYkyqzF8Y5n2KwJzVRqn4IvylVdpwjPMznUscQeSPe9NnUKRSBvZBzPsVhT6rMXhjnjIrBnlSZvTDO+RSDPamJiu6H0G/fkyRJkiRJ0vTkppQkSZIkSZIK56aUJEmSJEmSCuemlCRJkiRJkgpXyrIsK7Lg8PAwfX19UIIr5hZZOffKMchGodQBl88pvr4ZzBAtQ+r6AKeOAhkMDQ3R29ubJgTp5xPEOB+pM6SubwYzTBZhRjmfzBClvhliZXA+5SKcCzOYIUr9KBkqnU/pNqUkaZIwm1KSdB4h/qVPks7D+SQpqqnmU1eBWc7lnVJmMEOIDKnrw/guehj+TV/b96QZzDBRqBnlfGr7DKnrmyFWBudTLsK5MIMZotSPkqHS+ZRsU+ryq2HNkeLr3j8PTv0oPzEp6pvBDNEypK4PcN/cfHBGkWo+QYzzkTpD6vpmMMNkkWaU88kMqeubIVYG51Muwrkwgxmi1I+SodL55IPOJUmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVDg3pSRJkiRJklS4ZJ++J6n1nTwMB3fA0ACcOQEzeqBvISxaCzPnp04nqZ05nyRF5XySFFnRM8pNKUlVO7ob9m+Fwzuh9Mb9ltkIlDrz75+5C65ZCUs2wpxlyWJKakPOJ0lROZ8kRZZqRvn2PUkVyzJ4bgvsvBUGHwGyfFBlI2+8Xv4+g8OPwEMfyAdbliUMLaktOJ8kReV8khRZ6hnlppSkih3YBk/cmX+fnb34z5Zff3xjfpwkNZPzSVJUzidJkaWeUVVtSo2MjPB7v/d7XHvttVx22WW84x3v4HOf+xyZ2/jStHd0dz58avH4Rji2p7F5JnM+Se0r+nwCZ5TUrpxPkiKLMKOqeqbUH/zBH3DPPffwta99jXe96108/fTT3HHHHfT19fFbv/Vb9aeRFNb+rVDqmnr3/HxKXfnxzXw+gvNJal/R5xM4o6R25XySFFmEGVXVptS+ffv42Mc+xkc+8hEAfuqnfopvfOMbPPnkk/WlkBTaycP5A++o8S/MsrPwwkNwchBm9jc02hjnk9SeWmE+gTNKakfOJ0mRRZlRVb19b+nSpXzve9/jb//2bwF47rnn+PM//3NWrFhRewJJ4R3cMf4JDLUqdcDB7Q2Jc17OJ6k9tcJ8AmeU1I6cT5IiizKjqrpT6jOf+QzDw8Ncd911dHZ2MjIywuc//3nWrFlzwWNOnz7N6dOnx/778PBw7WklJTE00JjfM3yoMb/nfJxPUntqhfkE1c8o55PU+pxPkiKLMqOq2hf79re/zf3338/Xv/51/vIv/5Kvfe1rbNmyha997WsXPGbz5s309fWNffX3N/HeU0lNcebE+EeC1iobgdeb+GcW55PUnlphPkH1M8r5JLU+55OkyKLMqKo2pe68804+85nP8E/+yT9h8eLF/NN/+k/5nd/5HTZv3nzBYzZt2sTQ0NDY1+DgYH2JJRVuRg+UOuv7HaVOuKS3MXnOx/kktadWmE9Q/YxyPkmtz/kkKbIoM6qqt++98sordHScu4/V2dnJ6OjoBY/p7u6mu7u7tnSSQuhb2Jjf07ugMb/nfJxPUntqhfkE1c8o55PU+pxPkiKLMqOqulNq1apVfP7zn+fhhx/m+eef58EHH2Tbtm384i/+Yn0pJIW2aC1kF97bqUg2CovuaEic83I+Se2pFeYTOKOkduR8khRZlBlV1Z1S/+k//Sd+7/d+j09+8pO89NJLzJ07l3/xL/4Fn/3sZ+tLISm0mfNh/koYfCT/6M9qlbpg/u3N/Thj55PUnlphPoEzSmpHzidJkUWZUVVtSvX09PDFL36RL37xi/VVldRybtgIhx+q7dhsBJZsaGyeyZxPUvuKPp/AGSW1K+eTpMgizKiq3r4nqX3NWQY3b6nt2Jvvzo+XpGZwPkmKyvkkKbIIM8pNKUkVW7x+fGiVprjPsvz6zVvy4ySpmZxPkqJyPkmKLPWMclNKUsVKpfwWzVW78/cPU8o/BrT8UaJj35fy11ftzn++VEqZWlI7cD5Jisr5JCmy1DOqqmdKSRLkt2nOWQYnB+Hgdhg+BK8PwyW9+UeCLrqj+Q/llKTzcT5Jisr5JCmyVDPKTSlJNZvZDzf5wSySAnI+SYrK+SQpsqJnlG/fkyRJkiRJUuHclJIkSZIkSVLh3JSSJEmSJElS4dyUkiRJkiRJUuFKWZZlRRYcGhriLW95CwCXzymycu6VF4EMKMHlVxdf3wxmiJYhdX2AV47l//njH/+Yvr6+NCFIP58gyPmwJ81ghnMzBJhRziczRKlvhmAZnE9AkHNhBjMEqR8mQ4XzqfBNqSNHjtDf72edSnqzwcFB5s2bl6y+80nSxaScUc4nSRfjfJIU1VTzqfBNqdHRUY4ePUpPTw+lUqnq44eHh+nv72dwcJDe3t4mJDRDq2RIXd8MjcuQZRknTpxg7ty5dHSke1ex88kM0ylD6vrTKUOEGVXvfIL05yN1fTOYIVoG59O41OciQobU9c1ghkZnqHQ+ddUTshYdHR0N2cXv7e1NdnLMECtD6vpmaEyGlG/bK3M+mWE6Zkhdf7pkSD2jGjWfIP35SF3fDGaIlsH5NC71uYiQIXV9M5ihkRkqmU8+6FySJEmSJEmFc1NKkiRJkiRJhWu5Tanu7m7+zb/5N3R3d5uhzTOkrm+GWBkiiLAOZjBDlPpmiCf1WqSubwYzRMuQun4kEdYidYbU9c1ghlQZCn/QuSRJkiRJktRyd0pJkiRJkiSp9bkpJUmSJEmSpMK5KSVJkiRJkqTCuSklSZIkSZKkwrXUptRf/MVf0NnZyUc+8pHCa69du5ZSqTT2deWVV/LhD3+Y/fv3F57lxRdf5Dd/8zd5+9vfTnd3N/39/axatYrvfe97Ta89cR1mzJjBT/zET7B8+XK++tWvMjo62vT6kzNM/Prwhz9cSP2pchw6dKiQ+i+++CKf/vSnWbBgAZdeeik/8RM/wS233MI999zDK6+80vT6a9eu5Rd+4Rfe9M9/8IMfUCqV+PGPf9z0DNE4o5xPk3OkmlGp5xOknVHOpzdzPjmfJudwPvlnqCicT86nyTmcT+01n1pqU+ree+/lN3/zN9mzZw9Hjx4tvP6HP/xhjh07xrFjx/je975HV1cXK1euLDTD888/z0033cT3v/997r77bg4cOMCjjz7KBz/4QdatW1dIhvI6PP/88zzyyCN88IMf5NOf/jQrV67k7NmzhWaY+PWNb3yjkNpT5bj22mubXvfv/u7vuPHGG/nTP/1TvvCFL/A//+f/5C/+4i/4V//qX7Fz50527drV9Ax6s3afUc6nN+dIOaNSzSdwRkXkfHI+Tc7hfHI+ReF8cj5NzuF8aq/51JU6QKVOnjzJt771LZ5++mlefPFFduzYwb/+1/+60Azd3d1cffXVAFx99dV85jOf4f3vfz8vv/wys2fPLiTDJz/5SUqlEk8++SRXXHHF2D9/17vexa/92q8VkmHiOvzkT/4k7373u7n55pv50Ic+xI4dO/jn//yfF5ohpVQ5PvnJT9LV1cXTTz99Th+8/e1v52Mf+xhZlhWeqd05o5xPF8qRSsoMzqhYnE/OpwvlSMX5pDLnk/PpQjlScT4Vr2XulPr2t7/Nddddx6JFi/j4xz/OV7/61aQn5eTJk9x3330sWLCAK6+8spCa/+///T8effRR1q1bd06Tlr3lLW8pJMf5/OzP/iw33HADf/RHf5QsQ7v4v//3//Knf/qnF+wDgFKpVHAqtfuMcj6pzBkVj/PJ+aSc8yke55PzSbl2nk8tsyl177338vGPfxzIb6kbGhpi9+7dhWbYuXMnM2fOZObMmfT09PDd736Xb33rW3R0FLOMhw4dIssyrrvuukLqVeu6667j+eefL6TWxHNR/vrCF75QSO2L5Vi9enXTa5b7YNGiRef887e97W1jOX73d3+36Tng/OdhxYoVhdSOpt1nlPPpXBFmVIr5BHFmlPNpnPPJ+TSR8yn9fAJnVJnzyfk0kfOpPedTS7x97+DBgzz55JM8+OCDAHR1dfGP//E/5t577+XWW28tLMcHP/hB7rnnHgCOHz/OH/7hH7JixQqefPJJrrnmmqbXj367XpZlhe3eTjwXZW9961sLqX2xHBfa1S7Ck08+yejoKGvWrOH06dOF1DzfeXjiiSfG/nDRLpxRzqfJIsyoSPMJip9Rzqec88n5NJnz6c38M1Qazifn02TOpzdrh/nUEptS9957L2fPnmXu3Llj/yzLMrq7u/nSl75EX19fITmuuOIKFixYMPbf/9t/+2/09fXxla98hX//7/990+svXLiQUqnE3/zN3zS9Vi1++MMfFvYQuMnnIpUUORYsWECpVOLgwYPn/PO3v/3tAFx22WWFZTnf//4jR44UVj8KZ5TzabIIMypVhigzyvmUcz45nyZzPqWfT+CMAucTOJ8mcz6153wK//a9s2fP8t//+39n69atPPvss2Nfzz33HHPnzk3yiWtlpVKJjo4OXn311ULqvfWtb+Xnf/7n+fKXv8ypU6fe9HrKj4/9/ve/z4EDB/ilX/qlZBnaxZVXXsny5cv50pe+dN4+ULGcUTnnk8qcUXE4n3LOJ5U5n+JwPuWcTypr5/kU/k6pnTt3cvz4cf7ZP/tnb9ot/6Vf+iXuvfde/uW//JeFZDl9+jQvvvgikN/a+aUvfYmTJ0+yatWqQuoDfPnLX+aWW27hZ37mZ/h3/+7fsWTJEs6ePctjjz3GPffcww9/+MOmZyivw8jICP/n//wfHn30UTZv3szKlSv51V/91abXn5hhoq6uLt72trcVUj+1P/zDP+SWW27hPe95D3fddRdLliyho6ODp556ir/5m7/hpptuSh2xbTijxjmf3pxjImeUM6pozqdxzqc355jI+eR8KprzaZzz6c05JnI+tcF8yoJbuXJldvvtt5/3tSeeeCIDsueee67pOT7xiU9kwNhXT09P9t73vjf7zne+0/Takx09ejRbt25dds0112SXXHJJ9pM/+ZPZRz/60ezP/uzPml574jp0dXVls2fPzm677bbsq1/9ajYyMtL0+pMzTPxatGhRIfUn5vjYxz5WaM2Jjh49mn3qU5/Krr322mzGjBnZzJkzs5/5mZ/J7r777uzUqVNNr3+h//1/9md/lgHZ8ePHm54hAmfUudp9Pk3OkWpGpZ5PWZZ2Rjmfcs6nczmfnE9l/hkqPefTuZxPzqeydpxPpSwL/nQ1SZIkSZIkTTvhnyklSZIkSZKk6cdNKUmSJEmSJBXOTSlJkiRJkiQVzk0pSZIkSZIkFc5NKUmSJEmSJBXOTSlJkiRJkiQVzk0pSZIkSZIkFc5NKUmSJEmSJBXOTSlJkiRJkiQVzk0pSZIkSZIkFc5NKUmSJEmSJBXOTSlJkiRJkiQVzk0pSZIkSZIkFc5NKUmSJEmSJBXOTSlJkiRJkiQVzk0pSZIkSZIkFa6r6IKjo6McPXqUnp4eSqVS0eUlBZRlGSdOnGDu3Ll0dKTbK3c+STqfCDPK+STpfJxPkqKqdD4Vvil19OhR+vv7iy4rqQUMDg4yb968ZPWdT5IuJuWMcj5Juhjnk6SopppPhW9K9fT0jH1/+Zyiq8MrLwIZUILLry6+vhnMEC1D6voArxzL/3PifEgh9XyCIOfDnjSDGc7NEGBGOZ/MEKW+GYJlcD4BQc6FGcwQpH6YDBXOp8I3pcq3dF4+Bz5+tOjqcP88OPUjuGIurDlSfH0zmCFahtT1Ae6bmw+t1Ld8p55PEON8pM6Qur4ZzDBZhBnlfDJDlPpmiJXB+ZSLcC7MYIYo9aNkqHQ++aBzSZIkSZIkFc5NKUmSJEmSJBXOTSlJkiRJkiQVzk0pSZIkSZIkFa7wB523sln0s5S1XMVCLqWH1zjBSwywjx0cZzB1vLZx8jAc3AFDA3DmBMzogb6FsGgtzJxfTAZ7IRfhXChnT+YirEPqDKnrR+F8isOezEVYBzPE4HyKxZ6MsQZmiKPoGeWmVAUWsozlbGAxK8kYBaCDDkbf+H4ld7Gfh9jFVgbYmzLqtHZ0N+zfCod3QumNe/yyESh15t8/cxdcsxKWbIQ5y5qTwV7IRTgXytmTuQjrkDpD6vpROJ/isCdzEdbBDDE4n2KxJ2OsgRniSDWjfPveFJazgY3s5npW0EEHnXTRSRelCd930MFibmcje7iN9akjTztZBs9tgZ23wuAjQJZfHNnIG6+Xv8/g8CPw0AfyiynLGpvDXohzLpSzJ3MR1iF1htT1I3A+xWJP5iKsgxnScz7F0+49CTHWwAwxpJ5RbkpdxG2s55fZAkAnMy76s+XXV7N1WjZqSge2wRN35t9nZy/+s+XXH9+YH9co9kIuwrlQzp7MRViH1BlS14/C+RSHPZmLsA5miMH5FIs9GWMNzBBH6hlV9abUnj17WLVqFXPnzqVUKvHHf/zHjUkSzEKWsZqtNR27mq0s5P0NTtSeju7OG74Wj2+EY3vqz2Av5CKci6k4n6Y2nXoywjqkzpC6fhTOpzjsyVyEdTBDDM6nWOzJGGtghjgizKiqN6VOnTrFDTfcwJe//OX6qwe2nA2McKamY0c4M+12T1PZvxVKNT75rNSVH18veyEX4VxMxfk0tenUkxHWIXWG1PWjcD7FYU/mIqyDGWJwPsViT8ZYAzPEEWFGVV1+xYoVrFixov7Kgc2in8WspKPGdzd2MoMlfJRZzOM4Rxqcrn2cPJw/ZI0a36uanYUXHoKTgzCzv7bfYS/kIpyLSjifpjZdejLCOqTOkLp+FM6nOOzJXIR1MEMMzqdY7MkYa2CGOKLMKJ8pdR5LWTv21P1aZYyylDsalKg9Hdwx/tT/WpU64OD22o+3F3IRzoVy9mQuwjqkzpC6fhTOpzjsyVyEdTBDDM6nWOzJGGtghjiizKgab9Sq3OnTpzl9+vTYfx8eHm52ybpdxcIG/JaM2SxowO9pX0MDjfk9w4dqP9ZeyEU4F83gfGpdEdYhdYbU9aNwPsVhT+YirIMZYnA+xWJPxlgDM8QRZUY1/U6pzZs309fXN/bV39/Ee08b5FJ6ar6Vr6yDTi6jt0GJ2tOZE+MfQ1mrbARer+P/J+2FXIRz0QzOp9YVYR1SZ0hdPwrnUxz2ZC7COpghBudTLPZkjDUwQxxRZlTTN6U2bdrE0NDQ2Nfg4GCzS9btNU4wWuftfKOM8CrB/h+kxczogVJnfb+j1AmX1DEr7IVchHPRDM6n1hVhHVJnSF0/CudTHPZkLsI6mCEG51Ms9mSMNTBDHFFmVNPfvtfd3U13d3ezyzTUSzTiPrYSLxPsXtsW09eIuyqB3jruqrQXchHORTM4n1pXhHVInSF1/SicT3HYk7kI62CGGJxPsdiTMdbADHFEmVFV3yl18uRJnn32WZ599lkA/v7v/55nn32Ww4cP15ckkH3soFTnTWQlOtiHTyWsx6K1kNW3gU02CovqeP6cvZCLcC4q4XyqzHToyQjrkDpD6vpROJ/isCdzEdbBDDE4n2KxJ2OsgRniiDKjqj4TTz/9NDfeeCM33ngjAOvXr+fGG2/ks5/9bH1JAjnOIAfYyQhnajp+hDPs57st/fGQEcycD/NXQqnG+/lKXXDNqvo+ntJeyEU4F5VwPk1tuvRkhHVInSF1/SicT3HYk7kI62CGGJxPsdiTMdbADHFEmVFVb0rdeuutZFn2pq8dO3bUlySYx9hCJzNqOraDTnaxrcGJ2tMNGyE7W9ux2Qgs2VB/BnshF+FcTMX5NLXp1JMR1iF1htT1o3A+xWFP5iKsgxlicD7FYk/GWAMzxBFhRjX9QeetaoC9PEBtK/wd7mSAvQ1O1J7mLIObt9R27M1358fXy17IRTgXytmTuQjrkDpD6vpROJ/isCdzEdbBDDE4n2KxJ2OsgRniiDCj3JS6iF1sG2vUqW7tK7/+ABumza5pFIvXj18oU91aWH795i35cY1iL+QinAvl7MlchHVInSF1/SicT3HYk7kI62CGGJxPsdiTMdbADHGknlFuSk1hF9vYwjIO8DCjjDLCWUY4S8YoI5xhhLOMMsoBHmYLy6Zdg0ZQKuW3Ba7aDfNvB0r5R0+WP75y7PtS/vqq3fnPl0qNzWEvxDkXytmTuQjrkDpD6voROJ9isSdzEdbBDOk5n+Jp956EGGtghhhSz6gaH2nVXgbYywB7mcU8lnIHs1nAZfTyKsO8zCH2sb3lH3LWCuYsy79ODsLB7TB8CF4fhkt684+hXHRH8x8EaS/kIpwL5ezJXIR1SJ0hdf0onE9x2JO5COtghhicT7HYkzHWwAxxpJpRbkpV4ThHeJjPpY7R9mb2w02JPwzEXshFOBfK2ZO5COuQOkPq+lE4n+KwJ3MR1sEMMTifYrEnY6yBGeIoekb59j1JkiRJkiQVzk0pSZIkSZIkFc5NKUmSJEmSJBXOTSlJkiRJkiQVrpRlWVZkweHhYfr6+qAEV8wtsnLulWOQjUKpAy6fU3x9M5ghWobU9QFOHQUyGBoaore3N00I0s8niHE+UmdIXd8MZpgswoxyPpkhSn0zxMrgfMpFOBdmMEOU+lEyVDqf0m1KSdIkYTalJOk8QvxLnySdh/NJUlRTzaeuArOcyzulzGCGEBlS14fxXfQw/Ju+tu9JM5hholAzyvnU9hlS1zdDrAzOp1yEc2EGM0SpHyVDpfMp2abU5VfDmiPF171/Hpz6UX5iUtQ3gxmiZUhdH+C+ufngjCLVfIIY5yN1htT1zWCGySLNKOeTGVLXN0OsDM6nXIRzYQYzRKkfJUOl88kHnUuSJEmSJKlwbkpJkiRJkiSpcG5KSZIkSZIkqXBuSkmSJEmSJKlw6T59TzWZRT9LWctVLORSeniNE7zEAPvYwXEGC8lw8jAc3AFDA3DmBMzogb6FsGgtzJw//etDjPNgBkUToR/MkL6+GRRRhH4wgxmi1FcsEfrBDGZImcFNqRaxkGUsZwOLWUnGKAAddDD6xvcruYv9PMQutjLA3qZkOLob9m+Fwzvzj5YEyEag1Jl//8xdcM1KWLIR5iybfvUhxnkwg6KJ0A9mSF/fDIooQj+YwQxR6iuWCP1gBjNEyODb91rAcjawkd1czwo66KCTLjrpojTh+w46WMztbGQPt7G+ofWzDJ7bAjtvhcFHgCzfDMpG3ni9/H0Ghx+Bhz6Qbx5l2fSoX5b6PJhBEUXoBzOkr28GRRShH8xghij1FUuEfjCDGaJkcFMquNtYzy+zBYBOZlz0Z8uvr2ZrQ5vkwDZ44s78++zsxX+2/PrjG/PjpkN9iHEezKBoIvSDGdLXN4MiitAPZjBDlPqKJUI/mMEMkTK4KRXYQpaxmq01HbuarSzk/XVnOLo73+CpxeMb4die1q4PMc6DGRRNhH4wQ/r6ZlBEEfrBDGaIUl+xROgHM5ghWoaqNqU2b97Me9/7Xnp6erjqqqv4hV/4BQ4ePFh3CJ3fcjYwwpmajh3hTEN2LvdvhVKNTx4rdeXHt3J9iHEezDA151OxIvSDGdLXN0PlnFHFidAPZjBDlPqVcD4VJ0I/mMEM0TJUtSm1e/du1q1bx+OPP85jjz3GmTNn+Lmf+zlOnTpVdxCdaxb9LGbllLfPXUgnM1jCR5nFvJoznDycP1R8qrfMXUh2Fl54CE7W+ID+1PUhxnkwQ2WcT8WJ0A9mSF/fDNVxRhUjQj+YwQxR6lfK+VSMCP1gBjNEywBVbko9+uijrF27lne9613ccMMN7Nixg8OHD/PMM8/UFUJvtpS1Y0+8r1XGKEu5o+bjD+4Y/5S7WpU64OD21qwPMc6DGSrjfCpOhH4wQ/r6ZqiOM6oYEfrBDGaIUr9SzqdiROgHM5ghWgaAGt8YlRsaGgLgrW996wV/5vTp05w+fXrsvw8PD9dTsm1cxcIG/JaM2Syo+eihgQZEAIYPtWZ9iHEezFAb51PzROgHM6Svb4b6TDWjnE+1idAPZjBDlPq1cj41R4R+MIMZomWAOh50Pjo6ym//9m9zyy23cP3111/w5zZv3kxfX9/YV39/f60l28ql9NBR53PoO+jkMnprPv7MCchG6opANgKv1/j/U6nrQ4zzYIbqOZ+aK0I/mCF9fTPUrpIZ5XyqTYR+MIMZotSvhfOpeSL0gxnMEC1D/jtqtG7dOv7qr/6Kb37zmxf9uU2bNjE0NDT2NThYxwN+2shrnGC0zlvpRhnhVWrfkZnRA6XOuiJQ6oRLauzR1PUhxnkwQ/WcT80VoR/MkL6+GWpXyYxyPtUmQj+YwQxR6tfC+dQ8EfrBDGaIlgFqfPvepz71KXbu3MmePXuYN+/iD7Xq7u6mu7u7pnDt7CUa8d61Ei9T+3vX+hpxNx/QW+PdfKnrQ4zzYIbqOJ+aL0I/mCF9fTPUptIZ5XyqTYR+MIMZotSvlvOpuSL0gxnMEC0DVHmnVJZlfOpTn+LBBx/k+9//Ptdee21dxXVh+9hBqc5b6Up0sI/an/K9aC1k9W2cko3Cohqfe5a6PsQ4D2aojPOpOBH6wQzp65uhOs6oYkToBzOYIUr9SjmfihGhH8xghmgZoMpNqXXr1nHffffx9a9/nZ6eHl588UVefPFFXn311bpC6M2OM8gBdjLCmZqOH+EM+/kuxzlSc4aZ82H+SijV+Dj8Uhdcswpm1vg289T1IcZ5MENlnE/FidAPZkhf3wzVcUYVI0I/mMEMUepXyvlUjAj9YAYzRMsAVW5K3XPPPQwNDXHrrbcyZ86csa9vfetbdYXQ+T3GFjqZUdOxHXSyi211Z7hhI2Rnazs2G4ElG1q7PsQ4D2aYmvOpWBH6wQzp65uhcs6o4kToBzOYIUr9SjifihOhH8xghmgZqn773vm+1q5dW3cQvdkAe3mA2nZVvsOdDLC37gxzlsHNW2o79ua78+NbuT7EOA9mmJrzqVgR+sEM6euboXLOqOJE6AczmCFK/Uo4n4oToR/MYIZoGep7A6Gabhfbxppkqtvqyq8/wIaG/q3K4vXjG0NTvZWu/PrNW/LjpkN9iHEezKBoIvSDGdLXN4MiitAPZjBDlPqKJUI/mMEMkTLU+LQeFWkX23iBp7iN9Szho2RvfGxjBx2MMgKUKNHBAR5mF9sa/jcqpVL+NrjZ74X9W+GFh6D0xnZmNgKlzje+H4X5t+c/24g7lKLUL0t9HsygiCL0gxnS1zeDIorQD2YwQ5T6iiVCP5jBDFEyuCnVIgbYywB7mcU8lnIHs1nAZfTyKsO8zCH2sb3pD0Gcsyz/OjkIB7fD8CF4fRgu6YXeBfmn3NXzUPHo9SHGeTCDoonQD2ZIX98MiihCP5jBDFHqK5YI/WAGM0TI4KZUiznOER7mc0kzzOyHmz7bvvUhxnkwg6KJ0A9mSF/fDIooQj+YwQxR6iuWCP1gBjOkzOAzpSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUuFKWZVmRBYeHh+nr64MSXDG3yMq5V45BNgqlDrh8TvH1zWCGaBlS1wc4dRTIYGhoiN7e3jQhSD+fIMb5SJ0hdX0zmGGyCDPK+WSGKPXNECuD8ykX4VyYwQxR6kfJUOl8SrcpJUmThNmUkqTzCPEvfZJ0Hs4nSVFNNZ+6CsxyLu+UMoMZQmRIXR/Gd9HD8G/62r4nzWCGiULNKOdT22dIXd8MsTI4n3IRzoUZzBClfpQMlc6nZJtSl18Na44UX/f+eXDqR/mJSVHfDGaIliF1fYD75uaDM4pU8wlinI/UGVLXN4MZJos0o5xPZkhd3wyxMjifchHOhRnMEKV+lAyVzicfdC5JkiRJkqTCuSklSZIkSZKkwrkpJUmSJEmSpMK5KSVJkiRJkqTCpfv0vRY0i36WsparWMil9PAaJ3iJAfaxg+MMpo5XmNTrcPIwHNwBQwNw5gTM6IG+hbBoLcyc3/TyYTKkPg+KxX7IRViH1PMhwhpEyKA47IdchHVIPZ8gxjpEyKA47IcYa+B8ipOhaG5KVWAhy1jOBhazkoxRADroYPSN71dyF/t5iF1sZYC9KaM2Vep1OLob9m+Fwzvzj7YEyEag1Jl//8xdcM1KWLIR5ixrePkwGVKfB8ViP+QirEPq+RBhDSJkUBz2Qy7COqSeTxBjHSJkUBz2Q4w1cD7FyZCKb9+bwnI2sJHdXM8KOuigky466aI04fsOOljM7WxkD7exPnXkpki5DlkGz22BnbfC4CNAlg+qbOSN18vfZ3D4EXjoA/lgy7KGRQiRAexHnct+yKVehwjzIfUaRMmgOOyHXOp1iDCfIP06RMmgOOyH9GvgfIqVISU3pS7iNtbzy2wBoJMZF/3Z8uur2TrtmiT1OhzYBk/cmX+fnb34z5Zff3xjflyjRMiQ+jwoFvshF2EdUs+HCGsQIYPisB9yEdYh9XyCGOsQIYPisB9irIHzKU6G1KralLrnnntYsmQJvb299Pb28r73vY9HHnmkWdmSWsgyVrO1pmNXs5WFvL/BidJIvQ5Hd+fDpxaPb4Rje+oqHyZD6vPQCpxPlZlO/RBhHVLPhwhrECFDK2iXGWU/5CKsQ+r5BDHWIUKG6NplPoH9ADHWwPkUJ0MEVW1KzZs3j9///d/nmWee4emnn+Znf/Zn+djHPsb/+l//q1n5klnOBkY4U9OxI5yZNjuXqddh/1Yo1fjks1JXfny9ImRIfR5agfOpMtOpHyKsQ+r5EGENImRoBe0yo+yHXIR1SD2fIMY6RMgQXbvMJ7AfIMYaOJ/iZIigqk2pVatWcfvtt7Nw4ULe+c538vnPf56ZM2fy+OOPNytfErPoZzErp7x97kI6mcESPsos5jU4WbFSr8PJw/kD76a6nfNCsrPwwkNwso4PKYiQIfV5aBXOp8pMl36IsA6p50OENYiQoVW0w4yyH3IR1iH1fIIY6xAhQytoh/kE9gPEWAPnU5wMUdT8TKmRkRG++c1vcurUKd73vvc1MlNyS1k79sT7WmWMspQ7GpQojdTrcHDH+Ccw1KrUAQe31358hAypz0Mrcj5d3HTohwjrkHo+RFiDCBla0XSdUfZDLsI6pJ5PEGMdImRoNdN1PoH9ADHWwPkUJ0MUVd80d+DAAd73vvfx2muvMXPmTB588EF++qd/+oI/f/r0aU6fPj3234eHh2tLWqCrWNiA35IxmwUN+D3ppF6HoYEGlAeGD9V+bIQMqc9DK3E+Var1+yHCOqSeDxHWIEKGVlLNjHI+ta4I65B6PkGMdYiQoVVM9/kE9gPEWAPnU5wMUVS9R7lo0SKeffZZnnjiCX7jN36DT3ziE/z1X//1BX9+8+bN9PX1jX319/fXFbgIl9JDR50fTNhBJ5fR26BEaaRehzMnxj8StFbZCLxex/9PRsiQ+jy0EudTZaZDP0RYh9TzIcIaRMjQSqqZUc6n1hVhHVLPJ4ixDhEytIrpPp/AfoAYa+B8ipMhiqpX4ZJLLmHBggXcdNNNbN68mRtuuIH/8B/+wwV/ftOmTQwNDY19DQ7W8ebPgrzGCUbrvJVulBFepTX+1uBCUq/DjB4oddZVnlInXFLHdRohQ+rz0EqcT5WZDv0QYR1Sz4cIaxAhQyupZkY5n1pXhHVIPZ8gxjpEyNAqpvt8AvsBYqyB8ylOhihqfOb9uNHR0XNu35ysu7ub7u7uessU6iUacU9hiZep457CAFKvQ18j7mgEeuu4ozFChtTnoZU5ny6k9fshwjqkng8R1iBChlZ2sRnlfGpdEdYh9XyCGOsQIUOrmm7zCewHiLEGzqc4GaKo6k6pTZs2sWfPHp5//nkOHDjApk2b+MEPfsCaNWualS+JfeygVOetdCU62EcdT18LIPU6LFoLWX2bx2SjsKiOZ79FyJD6PLQK51PlpkM/RFiH1PMhwhpEyNAq2mFG2Q+5COuQej5BjHWIkKEVtMN8AvsBYqyB8ylOhiiqWoWXXnqJX/3VX2XRokV86EMf4qmnnuJP/uRPWL58ebPyJXGcQQ6wkxHO1HT8CGfYz3c5zpEGJytW6nWYOR/mr4RSjffzlbrgmlUws463uUfIkPo8tArnU2WmSz9EWIfU8yHCGkTI0CraYUbZD7kI65B6PkGMdYiQoRW0w3wC+wFirIHzKU6GKKpqhXvvvbdZOcJ5jC3cwEdrOraDTnaxrcGJ0ki9DjdshMMP1XZsNgJLNtRVPkyG1OehFTifKjOd+iHCOqSeDxHWIEKGVtAuM8p+yEVYh9TzCWKsQ4QM0bXLfAL7AWKsgfMpToYI6rtfbBobYC8PUFu3f4c7GWBvgxOlkXod5iyDm7fUduzNd+fH1ytChtTnQbHYD7kI65B6PkRYgwgZFIf9kIuwDqnnE8RYhwgZFIf9EGMNnE9xMkTgptRF7GLbWJNMdVtd+fUH2DBtdizLUq/D4vXjQ2uq2zzLr9+8JT+uUSJkSH0eFIv9kIuwDqnnQ4Q1iJBBcdgPuQjrkHo+QYx1iJBBcdgPMdbA+RQnQ2puSk1hF9vYwjIO8DCjjDLCWUY4S8YoI5xhhLOMMsoBHmYLy6ZVc0yUch1KpfwWzVW7Yf7tQCn/GNDyR4mOfV/KX1+1O//5UqlhEUJkAPtR57IfcqnXIcJ8SL0GUTIoDvshl3odIswnSL8OUTIoDvsh/Ro4n2JlSKnGx4u1lwH2MsBeZjGPpdzBbBZwGb28yjAvc4h9bJ8WDxibSup1mLMs/zo5CAe3w/AheH0YLunNPxJ00R31PfCuVTKkPg+KxX7IRViH1PMhwhpEyKA47IdchHVIPZ8gxjpEyKA47IcYa+B8ipMhFTelqnCcIzzM51LHSC71Oszsh5s+m6x8mAypz4NisR9yEdYh9XyIsAYRMigO+yEXYR1SzyeIsQ4RMigO+yHGGjif4mQomm/fkyRJkiRJUuHclJIkSZIkSVLh3JSSJEmSJElS4dyUkiRJkiRJUuFKWZZlRRYcHh6mr68PSnDF3CIr5145BtkolDrg8jnF1zeDGaJlSF0f4NRRIIOhoSF6e3vThCD9fIIY5yN1htT1zWCGySLMKOeTGaLUN0OsDM6nXIRzYQYzRKkfJUOl8yndppQkTRJmU0qSziPEv/RJ0nk4nyRFNdV86iowy7m8U8oMZgiRIXV9GN9FD8O/6Wv7njSDGSYKNaOcT22fIXV9M8TK4HzKRTgXZjBDlPpRMlQ6n5JtSl1+Naw5Unzd++fBqR/lJyZFfTOYIVqG1PUB7pubD84oUs0niHE+UmdIXd8MZpgs0oxyPpkhdX0zxMrgfMpFOBdmMEOU+lEyVDqffNC5JEmSJEmSCuemlCRJkiRJkgrnppQkSZIkSZIK56aUJEmSJEmSCpfu0/dUk1n0s5S1XMVCLqWH1zjBSwywjx0cZ7CQDCcPw8EdMDQAZ07AjB7oWwiL1sLM+c2v7xrEyRDhXCiOCP3gdeEaRMqgXISeNEMuwnXhOqSvr3Ol7snU9aNkiHBduA5pMrgp1SIWsozlbGAxK8kYBaCDDkbf+H4ld7Gfh9jFVgbY25QMR3fD/q1weGf+0ZIA2QiUOvPvn7kLrlkJSzbCnGWNr+8axMkQ4Vwojgj94HXhGkTKoFyEnjRDLsJ14Tqkr69zpe7J1PWjZIhwXbgOaTP49r0WsJwNbGQ317OCDjropItOuihN+L6DDhZzOxvZw22sb2j9LIPntsDOW2HwESDLL9Js5I3Xy99ncPgReOgD+UWdZY3L4BrEyADpz4ViSd0PXheuQbQMitGTZhiX+rpwHWLU17jUPZm6fpQMkP66cB1iZHBTKrjbWM8vswWATmZc9GfLr69ma0Ob5MA2eOLO/Pvs7MV/tvz64xvz4xrBNYiTIcK5UBwR+sHrwjWIlEG5CD1phlyE68J1SF9f50rdk6nrR8kQ4bpwHWJkcFMqsIUsYzVbazp2NVtZyPvrznB0d37h1eLxjXBsT331XYM4GSKcC8URoR+8LlyDSBmUi9CTZshFuC5ch/T1da7UPZm6fpQMEa4L1yFOhro2pX7/93+fUqnEb//2b9cdRG+2nA2McKamY0c405Cdy/1boVTjk8dKXfnx9XAN4mSIcC6q4Xxqrgj94HXhGkTKUI3pPJ8i9KQZchGuC9chff1aOKPOrxE9mbp+lAwRrgvXIU6GmjelnnrqKf7Lf/kvLFmypO4QerNZ9LOYlVPePnchncxgCR9lFvNqznDycP6wt6luZbyQ7Cy88BCcrPEB/a5BnAwRzkU1nE/NFaEfvC5cg0gZqjGd51OEnjRDLsJ14Tqkr18LZ9SF1duTqetHyRDhunAd4mSAGjelTp48yZo1a/jKV77CrFmz6gqg81vK2rEn3tcqY5Sl3FHz8Qd3jH/6QK1KHXBwe23HugZxMkQ4F5VyPjVfhH7wunANImWo1HSfTxF60gy5CNeF65C+frWcUVOrpydT14+SIcJ14TrEyQA1bkqtW7eOj3zkI9x2221T/uzp06cZHh4+50tTu4qFDfgtGbNZUPPRQwMNiAAMH6rtONcgToYI56JSzqfmi9APXheuQaQMlZru8ylCT5ohF+G6cB3S169WpTOqFecTpO/J1PWjZIhwXbgOcTIAVP0uym9+85v85V/+JU899VRFP79582b+7b/9t1UHa3eX0kNHnc+h76CTy+it+fgzJ8Y/DrNW2Qi8XuP/T7kGcTJEOBeVcD4VI0I/eF24BpEyVKId5lOEnjRDLsJ14Tqkr1+NamZUK84nSN+TqetHyRDhunAd4mTIf0cVBgcH+fSnP83999/PpZdeWtExmzZtYmhoaOxrcLCON162kdc4wWidt9KNMsKr1H6lzOiBUmddESh1wiU19qhrECdDhHMxFedTcSL0g9eFaxApw1TaZT5F6Ekz5CJcF65D+vqVqnZGteJ8gvQ9mbp+lAwRrgvXIU4GqPJOqWeeeYaXXnqJd7/73WP/bGRkhD179vClL32J06dP09l57tnt7u6mu7u7rpDt6CUacU9hiZep/Z7CvkbczQf01ng3n2sQJ0OEczEV51NxIvSD14VrECnDVNplPkXoSTPkIlwXrkP6+pWqdka14nyC9D2Zun6UDBGuC9chTgao8k6pD33oQxw4cIBnn3127Os973kPa9as4dlnn33TH6hUu33soFTnrXQlOthH7U9fW7QWsvo2TslGYVGNzz1zDeJkiHAupuJ8Kk6EfvC6cA0iZZhKu8ynCD1phlyE68J1SF+/Us6oytXTk6nrR8kQ4bpwHeJkgCo3pXp6erj++uvP+briiiu48soruf766+sKonMdZ5AD7GSEMzUdP8IZ9vNdjnOk5gwz58P8lVCq+sljuVIXXLMKZvbXdrxrECdDhHMxFedTcSL0g9eFaxApw1TaZT5F6Ekz5CJcF65D+vqVckZVpt6eTF0/SoYI14XrECcD1PjpeyrGY2yhkxk1HdtBJ7vYVneGGzZCdra2Y7MRWLKhvvquQZwMEc6F4ojQD14XrkGkDMpF6Ekz5CJcF65D+vo6V+qeTF0/SoYI14XrECdD3ZtSP/jBD/jiF79YdxC92QB7eYDauv073MkAe+vOMGcZ3LyltmNvvjs/vh6uQZwMEc5FtZxPzROhH7wuXINIGao1XedThJ40Qy7CdeE6pK9fK2fUmzWiJ1PXj5IhwnXhOsTJ4J1Swe1i21iTTHVbXfn1B9jQ0L9VWbx+/IKd6hbH8us3b8mPawTXIE6GCOdCcUToB68L1yBSBuUi9KQZchGuC9chfX2dK3VPpq4fJUOE68J1iJHBTakWsIttbGEZB3iYUUYZ4SwjnCVjlBHOMMJZRhnlAA+zhWUN/z+wUim/PXHVbph/O1DKPwKz/DGaY9+X8tdX7c5/vlRqXAbXIEYGSH8uFEvqfvC6cA2iZVCMnjTDuNTXhesQo77Gpe7J1PWjZID014XrECNDjY/2UtEG2MsAe5nFPJZyB7NZwGX08irDvMwh9rG96Q9BnLMs/zo5CAe3w/AheH0YLunNPw5z0R31PextKq5BnAwRzoXiiNAPXheuQaQMykXoSTPkIlwXrkP6+jpX6p5MXT9KhgjXheuQNoObUi3mOEd4mM8lzTCzH276bLr6rkGcDBHOheKI0A9eF65BpAzKRehJM+QiXBeuQ/r6OlfqnkxdP0qGCNeF65Amg2/fkyRJkiRJUuHclJIkSZIkSVLh3JSSJEmSJElS4dyUkiRJkiRJUuHclJIkSZIkSVLhSlmWZUUWHB4epq+vD0pwxdwiK+deOQbZKJQ64PI5xdc3gxmiZUhdH+DUUSCDoaEhent704Qg/XyCGOcjdYbU9c1ghskizCjnkxmi1DdDrAzOp1yEc2EGM0SpHyVDpfMp3aaUJE0SZlNKks4jxL/0SdJ5OJ8kRTXVfOoqMMu5vFPKDGYIkSF1fRjfRQ/Dv+lr+540gxkmCjWjnE9tnyF1fTPEyuB8ykU4F2YwQ5T6UTJUOp+SbUpdfjWsOVJ83fvnwakf5ScmRX0zmCFahtT1Ae6bmw/OKFLNJ4hxPlJnSF3fDGaYLNKMcj6ZIXV9M8TK4HzKRTgXZjBDlPpRMlQ6n3zQuSRJkiRJkgrnppQkSZIkSZIK56aUJEmSJEmSCuemlCRJkiRJkgqX7tP3qnTyMBzcAUMDcOYEzOiBvoWwaC3MnG+Gdsowi36WsparWMil9PAaJ3iJAfaxg+MMNj+AGUJliCD1NWGGWBlSXxep65shntTXRer6ZhgX4bowQ/r6kUS4LlJnSF0/SoYI14UZ0mQIvyl1dDfs3wqHd+YfZwiQjUCpM//+mbvgmpWwZCPMWWaG6ZxhIctYzgYWs5KMUQA66GD0je9Xchf7eYhdbGWAvY0PYIZQGSJIfU2YIVaG1NdF6vpmiCf1dZG6vhnGRbguzJC+fiQRrovUGVLXj5IhwnVhhrQZwr59L8vguS2w81YYfATI8gskG3nj9fL3GRx+BB76QH5BZZkZpmOG5WxgI7u5nhV00EEnXXTSRWnC9x10sJjb2cgebmN944qbIVyG1CJcE2aIkwHSXxep65shltTXRer6ZjhXhOvCDOnrRxHhukidIXX9KBkgxnVhhvQZwm5KHdgGT9yZf5+dvfjPll9/fGN+nBmmV4bbWM8vswWATmZc9GfLr69ma0MvFDPEyRBB6mvCDLEypL4uUtc3Qzypr4vU9c0wLsJ1YYb09SOJcF2kzpC6fpQMEa4LM8TIEHJT6ujuvOlr8fhGOLbHDNMlw0KWsZqtNR27mq0s5P31BTBDqAwRpL4mzBArQ+rrInV9M8ST+rpIXd8M4yJcF2ZIXz+SCNdF6gyp60fJEOG6MEOcDFVtSt11112USqVzvq677rq6Q0y2fyuUanzaVakrP94M0yPDcjYwwpmajh3hTEN2b80QJ8PFOJ/MkCJD6usidX0zVK5dZlTq+mYYF+G6MEP6+pVol/kUIUPq+lEyRLguzBAnQ9V3Sr3rXe/i2LFjY19//ud/XneIiU4ezh+0NtVthBeSnYUXHoKTdTwU3gwxMsyin8WsnPIWwgvpZAZL+CizmFdbADOEylAJ55MZisyQ+rpIXd8M1ZvuMyp1fTOMi3BdmCF9/WpM9/kUIUPq+lEyRLguzBAnA9SwKdXV1cXVV1899vW2t72trgCTHdwx/uT/WpU64OB2M7R6hqWsHXvqf60yRlnKHTUfb4Y4GSrhfDJDkRlSXxep65uhetN9RqWub4ZxEa4LM6SvX43pPp8iZEhdP0qGCNeFGeJkgBo2pQYGBpg7dy5vf/vbWbNmDYcPH77oz58+fZrh4eFzvi5maKDaROc3fKj2Y80QI8NVLGxA9YzZLKj5aDPEyVAJ55MZisyQ+rpIXd8M1atmRlU7nyD9dZG6vhnGRbguzJC+fjWm+3yKkCF1/SgZIlwXZoiTAarclPqH//AfsmPHDh599FHuuece/v7v/573v//9nDhx4oLHbN68mb6+vrGv/v7+i9Y4c2L8oyhrlY3A61PPRjMEz3ApPXTU+Sz+Djq5jN6ajzdDnAxTcT6ZoegMqa+L1PXNUJ1qZ1S18wnSXxep65thXITrwgzp61eqHeZThAyp60fJEOG6MEOcDPnvqMKKFStYvXo1S5Ys4ed//uf5H//jf/DjH/+Yb3/72xc8ZtOmTQwNDY19DQ5e/A2oM3qg1FlNqjcrdcIldayLGWJkeI0TjNZ5O+EoI7xK7VPTDHEyTMX5ZIaiM6S+LlLXN0N1qp1R1c4nSH9dpK5vhnERrgszpK9fqXaYTxEypK4fJUOE68IMcTIA1Pjc/dxb3vIW3vnOd3Lo0IXv3+vu7qa7u7vi39nXiDvIgN467iAzQ4wML9GI+0tLvEzt95eaIU6GajmfzNDsDKmvi9T1zVCfqWZUtfMJ0l8XqeubYVyE68IM6evXajrOpwgZUtePkiHCdWGGOBmghmdKTXTy5En+9//+38yZM6euEBMtWgtZfZt1ZKOwqI5nbZkhRoZ97KBU5+2EJTrYR+1P4jNDnAzVcj6ZodkZUl8XqeuboT7TcUalrm+GcRGuCzOkr1+r6TifImRIXT9KhgjXhRniZIAqN6U2btzI7t27ef7559m3bx+/+Iu/SGdnJ7/yK79SV4iJZs6H+SuhVOM9XKUuuGYVzJz6rc1mCJ7hOIMcYCcjnKnp+BHOsJ/vcpwjtQUwQ6gMU3E+maHoDKmvi9T1zVCddphRqeubYVyE68IM6etXqh3mU4QMqetHyRDhujBDnAxQ5abUkSNH+JVf+RUWLVrEP/pH/4grr7ySxx9/nNmzZ9cVYrIbNkJ2trZjsxFYssEM0yXDY2yhkxk1HdtBJ7vYVl8AM4TKcDHOJzOkyJD6ukhd3wyVa5cZlbq+GcZFuC7MkL5+JdplPkXIkLp+lAwRrgszxMlQ1abUN7/5TY4ePcrp06c5cuQI3/zmN3nHO95Rd4jJ5iyDm7fUduzNd+fHm2F6ZBhgLw9Q2+T7DncywN76ApghVIaLcT6ZIUWG1NdF6vpmqFy7zKjU9c0wLsJ1YYb09SvRLvMpQobU9aNkiHBdmCFOhvreQNhEi9ePXyxT3V5Yfv3mLflxZpheGXaxbexCmerWwvLrD7ChoX+zZIY4GSJIfU2YIVaG1NdF6vpmiCf1dZG6vhnGRbguzJC+fiQRrovUGVLXj5IhwnVhhhgZwm5KlUr5rYGrdsP824FS/vGT5Y+wHPu+lL++anf+86WSGaZjhl1sYwvLOMDDjDLKCGcZ4SwZo4xwhhHOMsooB3iYLSxryv+JmyFOhtQiXBNmiJMB0l8XqeubIZbU10Xq+mY4V4Trwgzp60cR4bpInSF1/SgZIMZ1YYb0GWp8xFlx5izLv04OwsHtMHwIXh+GS3rzj6JcdEd9D1ozQ+tkGGAvA+xlFvNYyh3MZgGX0curDPMyh9jH9qY/CNIMcTJEkPqaMEOsDKmvi9T1zRBP6usidX0zjItwXZghff1IIlwXqTOkrh8lQ4TrwgxpM4TflCqb2Q83fdYMZoDjHOFhPpcugBlCZYgg9TVhhlgZUl8XqeubIZ7U10Xq+mYYF+G6MEP6+pFEuC5SZ0hdP0qGCNeFGdJkCPv2PUmSJEmSJE1fbkpJkiRJkiSpcG5KSZIkSZIkqXBuSkmSJEmSJKlwpSzLsiILDg8P09fXByW4Ym6RlXOvHINsFEodcPmc4uubwQzRMqSuD3DqKJDB0NAQvb29aUKQfj5BjPOROkPq+mYww2QRZpTzyQxR6pshVgbnUy7CuTCDGaLUj5Kh0vmUblNKkiYJsyklSecR4l/6JOk8nE+SoppqPnUVmOVc3illBjOEyJC6Pozvoofh3/S1fU+awQwThZpRzqe2z5C6vhliZXA+5SKcCzOYIUr9KBkqnU/JNqUuvxrWHCm+7v3z4NSP8hOTor4ZzBAtQ+r6APfNzQdnFKnmE8Q4H6kzpK5vBjNMFmlGOZ/MkLq+GWJlcD7lIpwLM5ghSv0oGSqdTz7oXJIkSZIkSYVzU0qSJEmSJEmFc1NKkiRJkiRJhXNTSpIkSZIkSYVzU0qSJEmSJEmFS/bpe63o5GE4uAOGBuDMCZjRA30LYdFamDnfDEVmSC3CGphBE0U4F2aIIcIamEETRTgXZogjwjqkzpC6vs6V+nykrh8lQwSz6Gcpa7mKhVxKD69xgpcYYB87OM5g22Qouh/clKrA0d2wfysc3gmlN+4ty0ag1Jl//8xdcM1KWLIR5iwzQzMzpBZhDcygiSKcCzPEEGENzKCJIpwLM8QRYR1SZ0hdX+dKfT5S14+SIYKFLGM5G1jMSjJGAeigg9E3vl/JXeznIXaxlQH2TtsMqfrBt+9dRJbBc1tg560w+AiQ5SclG3nj9fL3GRx+BB76QH4Ss8wMjc6QWoQ1MIMminAuzBBDhDUwgyaKcC7MEEeEdUidIXV9nSv1+UhdP0qGKJazgY3s5npW0EEHnXTRSRelCd930MFibmcje7iN9dMuQ+p+cFPqIg5sgyfuzL/Pzl78Z8uvP74xP84Mjc2QWoQ1MIMminAuzBBDhDUwgyaKcC7MEEeEdUidIXV9nSv1+UhdP0qGCG5jPb/MFgA6mXHRny2/vpqtDd0UipAhdT9UvSn1ox/9iI9//ONceeWVXHbZZSxevJinn366MWkCObo7X+haPL4Rju0xQ6MypBZhDcxQGefT1KZTP0TIkFqENTBD5dphRkU4F2aII8I6pM6Qun6l2mE+Qfrzkbp+lAwRLGQZq9la07Gr2cpC3j8tMkToh6o2pY4fP84tt9zCjBkzeOSRR/jrv/5rtm7dyqxZs+pPEsz+rVCq8Ylbpa78eDM0JkNqEdbADFNzPlVmOvVDhAypRVgDM1SmXWZUhHNhhjgirEPqDKnrV6Jd5hOkPx+p60fJEMFyNjDCmZqOHeFMQ+5UipAhQj9UVf4P/uAP6O/vZ/v27WP/7Nprr60/RTAnD+cP96LG90hmZ+GFh+DkIMzsN0M9GVKLsAZmqIzzqTLTpR8iZEgtwhqYoXLtMKMinAszxBFhHVJnSF2/Uu0wnyD9+UhdP0qGCGbRz2JW0lHj04w6mcESPsos5nGcIy2bIUo/VLUC3/3ud3nPe97D6tWrueqqq7jxxhv5yle+Unv1oA7uGH/afK1KHXBw+9Q/Z4bYIqyBGSrjfKrcdOiHCBlSi7AGZqhcO8yoCOfCDHFEWIfUGVLXr1Q7zCdIfz5S14+SIYKlrB37hLtaZYyylDtaOkOUfqgqwt/93d9xzz33sHDhQv7kT/6E3/iN3+C3fuu3+NrXvnbBY06fPs3w8PA5X9ENDTTm9wwfMkO9GVKLsAZmqIzzqTqt3g8RMqQWYQ3MULlqZ5TzyQytPJ8gxjqkzpC6fqXaYT5B+vORun6UDBFcxcIG/JaM2Sxo6QxR+qGqt++Njo7ynve8hy984QsA3HjjjfzVX/0V//k//2c+8YlPnPeYzZs382//7b+tL2XBzpwY//jDWmUj8Hod89kMMURYAzNUxvlUuenQDxEypBZhDcxQuWpnlPPJDK08nyDGOqTOkLp+pdphPkH685G6fpQMEVxKT81vmyvroJPL6G3pDFH6oapVmDNnDj/90z99zj/7B//gH3D48OELHrNp0yaGhobGvgYHB2tLWqAZPVDqrO93lDrhktr7wwxBRFgDM1TG+VS56dAPETKkFmENzFC5ameU88kMrTyfIMY6pM6Qun6l2mE+Qfrzkbp+lAwRvMYJRut869woI7xK7bsxETJE6Yeq7pS65ZZbOHjw4Dn/7G//9m+55pprLnhMd3c33d3dtaVLpK8Rd9IBvbXfSWeGICKsgRkq43yqTqv3Q4QMqUVYAzNUrtoZ5XwyQyvPJ4ixDqkzpK5fqXaYT5D+fKSuHyVDBC/RiPetlXiZ2t+3FiFDlH6o6k6p3/md3+Hxxx/nC1/4AocOHeLrX/86//W//lfWrVtXX4pgFq2FrL5NS7JRWFT7M8fMEESENTBDZZxPlZsO/RAhQ2oR1sAMlWuHGRXhXJghjgjrkDpD6vqVaof5BOnPR+r6UTJEsI8dlOp861yJDvZR+xO+I2SI0g9VrcJ73/teHnzwQb7xjW9w/fXX87nPfY4vfvGLrFmzpr4UwcycD/NXQqmq+8jGlbrgmlX1fSyiGWKIsAZmqIzzqTLTpR8iZEgtwhqYoXLtMKMinAszxBFhHVJnSF2/Uu0wnyD9+UhdP0qGCI4zyAF2MsKZmo4f4Qz7+S7HOdLSGaL0Q9VbcytXruTAgQO89tpr/PCHP+TXf/3X60sQ1A0bITtb27HZCCzZYIZGZUgtwhqYoTLOp6lNp36IkCG1CGtghsq1w4yKcC7MEEeEdUidIXX9SrXDfIL05yN1/SgZIniMLXQyo6ZjO+hkF9umRYYI/VDf/WLT2JxlcPOW2o69+e78eDM0JkNqEdbADJoowrkwQwwR1sAMmijCuTBDHBHWIXWG1PV1rtTnI3X9KBkiGGAvD1Dbjsp3uJMB9k6LDBH6wU2pi1i8fvwETXVLW/n1m7fkx5mhsRlSi7AGZtBEEc6FGWKIsAZm0EQRzoUZ4oiwDqkzpK6vc6U+H6nrR8kQwS62jW0KTfU2uvLrD7ChIXcoRcqQuh/clLqIUim/HW3Vbph/O1DKP/Kw/LGJY9+X8tdX7c5/vlQyQ6MzpBZhDcygiSKcCzPEEGENzKCJIpwLM8QRYR1SZ0hdX+dKfT5S14+SIYpdbGMLyzjAw4wyyghnGeEsGaOMcIYRzjLKKAd4mC0sa+hmUJQMqfuhxkdatZc5y/Kvk4NwcDsMH4LXh+GS3vzjDxfd0fyHvZkhhghrYAZNFOFcmCGGCGtgBk0U4VyYIY4I65A6Q+r6Olfq85G6fpQMEQywlwH2Mot5LOUOZrOAy+jlVYZ5mUPsY3tdDxRvlQyp+sFNqSrM7IebPmuGCBlSi7AGZtBEEc6FGWKIsAZm0EQRzoUZ4oiwDqkzpK6vc6U+H6nrR8kQwXGO8DCfa/sMRfeDb9+TJEmSJElS4dyUkiRJkiRJUuHclJIkSZIkSVLh3JSSJEmSJElS4UpZlmVFFhweHqavrw9KcMXcIivnXjkG2SiUOuDyOcXXN4MZomVIXR/g1FEgg6GhIXp7e9OEIP18ghjnI3WG1PXNYIbJIswo55MZotQ3Q6wMzqdchHNhBjNEqR8lQ6XzKd2mlCRNEmZTSpLOI8S/9EnSeTifJEU11XzqKjDLubxTygxmCJEhdX0Y30UPw7/pa/ueNIMZJgo1o5xPbZ8hdX0zxMrgfMpFOBdmMEOU+lEyVDqfkm1KXX41rDlSfN3758GpH+UnJkV9M5ghWobU9QHum5sPzihSzSeIcT5SZ0hd3wxmmCzSjHI+mSF1fTPEyuB8ykU4F2YwQ5T6UTJUOp980LkkSZIkSZIK56aUJEmSJEmSCuemlCRJkiRJkgrnppQkSZIkSZIKl+7T96o0i36WsparWMil9PAaJ3iJAfaxg+MMFpLh5GE4uAOGBuDMCZjRA30LYdFamDm/kAghuA4qsxdyzqc4XAeV2QvjUs8oz0XOdVCZvTAu9XwCzwe4BpG04zURflNqIctYzgYWs5KMUQA66GD0je9Xchf7eYhdbGWAvU3JcHQ37N8Kh3fmH6kIkI1AqTP//pm74JqVsGQjzFnWlAghuA4qsxdyzqc4XAeV2QvjUs8oz0XOdVCZvTAu9XwCzwe4BpG08zUR+u17y9nARnZzPSvooINOuuiki9KE7zvoYDG3s5E93Mb6htbPMnhuC+y8FQYfAbL8pGQjb7xe/j6Dw4/AQx/IT2KWNTRGcq6DyuyFcc6nGFwHldkL50o5ozwXOddBZfbCufwzVHquQSztfk2E3ZS6jfX8MlsA6GTGRX+2/Ppqtjb0BB3YBk/cmX+fnb34z5Zff3xjftx04jqozF7IOZ/icB1UZi+MSz2jPBc510Fl9sK41PMJPB/gGkTiNRF0U2ohy1jN1pqOXc1WFvL+ujMc3Z0vdC0e3wjH9tQdIQTXQWX2Qs75FIfroDJ7YVzqGeW5yLkOKrMXxqWeT+D5ANcgEq+JXFWbUj/1Uz9FqVR609e6devqTzLBcjYwwpmajh3hTEN2DfdvhVKNT9wqdeXHTweug8paoReKmFHOpzhcB5W1Qi+0y5+hWuFcFMF1UFkr9EK7zCdojfPRbK5BHF4Tuao2pZ566imOHTs29vXYY48BsHr16vqTvGEW/Sxm5ZS3rl1IJzNYwkeZxbyaM5w8nD/ca6pb1y4kOwsvPAQni3k4ftO4DiprlV5o9oxyPsXhOqisVXqhHf4M1SrnotlcB5W1Si+0w3yC1jkfzeQaxOE1Ma6qTanZs2dz9dVXj33t3LmTd7zjHXzgAx+oL8UES1k79rT5WmWMspQ7aj7+4I7xp83XqtQBB7fX9ztScx1U1iq90OwZ5XyKw3VQWav0Qjv8GapVzkWzuQ4qa5VeaIf5BK1zPprJNYjDa2JcjTdqweuvv859993H+vXrKZVKF/y506dPc/r06bH/Pjw8fNHfexULa400QcZsFtR89NBAAyIAw4ca83tScR1U1oq9UMmMcj61LtdBZa3YC82YT5B+RrXiuWgG10FlrdgL03U+QWuej0ZzDeLwmhhX877YH//xH/PjH/+YtWvXXvTnNm/eTF9f39hXf3//RX/+UnroqPP56x10chm9NR9/5sT4xx/WKhuB16eez6G5DiprxV6oZEY5n1qX66CyVuyFZswnSD+jWvFcNIProLJW7IXpOp+gNc9Ho7kGcXhNjKt5Fe69915WrFjB3LlzL/pzmzZtYmhoaOxrcPDibzh8jROM1nkb2ygjvErtKzOjB0qddUWg1AmX1N4fIbgOKmvFXqhkRjmfWpfroLJW7IVmzCdIP6Na8Vw0g+ugslbshek6n6A1z0ejuQZxeE2Mq+ntey+88AK7du3ij/7oj6b82e7ubrq7uyv+3S/RiHvISrxM7feQ9TXiTjqgt/Y76UJwHVTWar1Q6YxyPrUu10FlrdYLzZpPkH5Gtdq5aBbXQWWt1gvTeT5B652PZnAN4vCaGFfTnVLbt2/nqquu4iMf+Uh91c9jHzso1XkbW4kO9lH707YWrYWsvk1LslFYVPszx0JwHVTWar3QrBnlfIrDdVBZq/XCdP4zVKudi2ZxHVTWar0wnecTtN75aAbXIA6viXFVr8Lo6Cjbt2/nE5/4BF1dNT8n/YKOM8gBdjLCmZqOH+EM+/kuxzlSc4aZ82H+SijV+D+v1AXXrIKZU7+9OjTXQWWt1AvNnFHOpzhcB5W1Ui9M9z9DtdK5aCbXQWWt1AvTfT5Ba52PZnEN4vCaGFf1ptSuXbs4fPgwv/Zrv1Zf5Yt4jC10MqOmYzvoZBfb6s5ww0bIztZ2bDYCSzbUHSEE10FlrdILzZ5Rzqc4XAeVtUovtMOfoVrlXDSb66CyVumFdphP0Drno5lcgzi8JnJVb0r93M/9HFmW8c53vrP+6hcwwF4eoLb/dd/hTgbYW3eGOcvg5i21HXvz3fnx04HroLJW6YVmzyjnUxyug8papRfa4c9QrXIums11UFmr9EI7zCdonfPRTK5BHF4TufrexNhEu9g2doKmuqWt/PoDbGjIbmHZ4vXjJ2iqW9rKr9+8JT9uOnEdVGYv5JxPcbgOKrMXxqWeUZ6LnOugMnthXOr5BJ4PcA0i8ZoIvCkF+QnawjIO8DCjjDLCWUY4S8YoI5xhhLOMMsoBHmYLyxp6YgBKpfx2tFW7Yf7tQCn/yMPyxyaOfV/KX1+1O//5UqmhMZJzHVRmL4xzPsXgOqjMXjhXyhnluci5DiqzF87ln6HScw1iafdrovFPsWuwAfYywF5mMY+l3MFsFnAZvbzKMC9ziH1sr+vhXpWYsyz/OjkIB7fD8CF4fRgu6c0//nDRHe3xsDfXQWX2Qs75FIfroDJ7YVzqGeW5yLkOKrMXxqWeT+D5ANcgkna+JsJvSpUd5wgP87mkGWb2w02fTRohBNdBZfZCzvkUh+ugMnthXOoZ5bnIuQ4qsxfGpZ5P4PkA1yCSdrwmQr99T5IkSZIkSdOTm1KSJEmSJEkqnJtSkiRJkiRJKpybUpIkSZIkSSpcKcuyrMiCw8PD9PX1QQmumFtk5dwrxyAbhVIHXD6n+PpmMEO0DKnrA5w6CmQwNDREb29vmhCkn08Q43ykzpC6vhnMMFmEGeV8MkOU+maIlcH5lItwLsxghij1o2SodD6l25SSpEnCbEpJ0nmE+Jc+SToP55OkqKaaT10FZjmXd0qZwQwhMqSuD+O76GH4N31t35NmMMNEoWaU86ntM6Sub4ZYGZxPuQjnwgxmiFI/SoZK51OyTanLr4Y1R4qve/88OPWj/MSkqG8GM0TLkLo+wH1z88EZRar5BDHOR+oMqeubwQyTRZpRziczpK5vhlgZnE+5COfCDGaIUj9Khkrnkw86lyRJkiRJUuHclJIkSZIkSVLh3JSSJEmSJElS4dyUkiRJkiRJUuHclJIkSZIkSVLhkn36nqTWd/IwHNwBQwNw5gTM6IG+hbBoLcycnzqdpHbmfJIUlfNJUmRFzyg3pSRV7ehu2L8VDu+E0hv3W2YjUOrMv3/mLrhmJSzZCHOWJYspqQ05nyRF5XySFFmqGeXb9yRVLMvguS2w81YYfATI8kGVjbzxevn7DA4/Ag99IB9sWZYwtKS24HySFJXzSVJkqWeUm1KSKnZgGzxxZ/59dvbiP1t+/fGN+XGS1EzOJ0lROZ8kRZZ6RlW1KTUyMsLv/d7vce2113LZZZfxjne8g8997nNkbuNL097R3fnwqcXjG+HYnsbmmcz5JLWv6PMJnFFSu3I+SYoswoyq6plSf/AHf8A999zD1772Nd71rnfx9NNPc8cdd9DX18dv/dZv1Z9GUlj7t0Kpa+rd8/MpdeXHN/P5CM4nqX1Fn0/gjJLalfNJUmQRZlRVm1L79u3jYx/7GB/5yEcA+Kmf+im+8Y1v8OSTT9aXQlJoJw/nD7yjxr8wy87CCw/ByUGY2d/QaGOcT1J7aoX5BM4oqR05nyRFFmVGVfX2vaVLl/K9732Pv/3bvwXgueee48///M9ZsWJF7QkkhXdwx/gnMNSq1AEHtzckznk5n6T21ArzCZxRUjtyPkmKLMqMqupOqc985jMMDw9z3XXX0dnZycjICJ///OdZs2bNBY85ffo0p0+fHvvvw8PDtaeVlMTQQGN+z/Chxvye83E+Se2pFeYTVD+jnE9S63M+SYosyoyqal/s29/+Nvfffz9f//rX+cu//Eu+9rWvsWXLFr72ta9d8JjNmzfT19c39tXf38R7TyU1xZkT4x8JWqtsBF5v4p9ZnE9Se2qF+QTVzyjnk9T6nE+SIosyo6ralLrzzjv5zGc+wz/5J/+ExYsX80//6T/ld37nd9i8efMFj9m0aRNDQ0NjX4ODg/UlllS4GT1Q6qzvd5Q64ZLexuQ5H+eT1J5aYT5B9TPK+SS1PueTpMiizKiq3r73yiuv0NFx7j5WZ2cno6OjFzymu7ub7u7u2tJJCqFvYWN+T++Cxvye83E+Se2pFeYTVD+jnE9S63M+SYosyoyq6k6pVatW8fnPf56HH36Y559/ngcffJBt27bxi7/4i/WlkBTaorWQXXhvpyLZKCy6oyFxzsv5JLWnVphP4IyS2pHzSVJkUWZUVXdK/af/9J/4vd/7PT75yU/y0ksvMXfuXP7Fv/gXfPazn60vhaTQZs6H+Sth8JH8oz+rVeqC+bc39+OMnU9Se2qF+QTOKKkdOZ8kRRZlRlW1KdXT08MXv/hFvvjFL9ZXVVLLuWEjHH6otmOzEViyobF5JnM+Se0r+nwCZ5TUrpxPkiKLMKOqevuepPY1ZxncvKW2Y2++Oz9ekprB+SQpKueTpMgizCg3pSRVbPH68aFVmuI+y/LrN2/Jj5OkZnI+SYrK+SQpstQzyk0pSRUrlfJbNFftzt8/TCn/GNDyR4mOfV/KX1+1O//5UillakntwPkkKSrnk6TIUs+oqp4pJUmQ36Y5ZxmcHISD22H4ELw+DJf05h8JuuiO5j+UU5LOx/kkKSrnk6TIUs0oN6Uk1WxmP9zkB7NICsj5JCkq55OkyIqeUb59T5IkSZIkSYVzU0qSJEmSJEmFc1NKkiRJkiRJhXNTSpIkSZIkSYUrZVmWFVlwaGiIt7zlLQBcPqfIyrlXXgQyoASXX118fTOYIVqG1PUBXjmW/+ePf/xj+vr60oQg/XyCIOfDnjSDGc7NEGBGOZ/MEKW+GYJlcD4BQc6FGcwQpH6YDBXOp8I3pY4cOUJ/v591KunNBgcHmTdvXrL6zidJF5NyRjmfJF2M80lSVFPNp8I3pUZHRzl69Cg9PT2USqWqjx8eHqa/v5/BwUF6e3ubkNAMrZIhdX0zNC5DlmWcOHGCuXPn0tGR7l3FziczTKcMqetPpwwRZlS98wnSn4/U9c1ghmgZnE/jUp+LCBlS1zeDGRqdodL51FVPyFp0dHQ0ZBe/t7c32ckxQ6wMqeuboTEZUr5tr8z5ZIbpmCF1/emSIfWMatR8gvTnI3V9M5ghWgbn07jU5yJChtT1zWCGRmaoZD75oHNJkiRJkiQVzk0pSZIkSZIkFa7lNqW6u7v5N//m39Dd3W2GNs+Qur4ZYmWIIMI6mMEMUeqbIZ7Ua5G6vhnMEC1D6vqRRFiL1BlS1zeDGVJlKPxB55IkSZIkSVLL3SklSZIkSZKk1uemlCRJkiRJkgrnppQkSZIkSZIK56aUJEmSJEmSCtdSm1J/8Rd/QWdnJx/5yEcKr7127VpKpdLY15VXXsmHP/xh9u/fX3iWF198kd/8zd/k7W9/O93d3fT397Nq1Sq+973vNb32xHWYMWMGP/ETP8Hy5cv56le/yujoaNPrT84w8evDH/5wIfWnynHo0KFC6r/44ot8+tOfZsGCBVx66aX8xE/8BLfccgv33HMPr7zyStPrr127ll/4hV940z//wQ9+QKlU4sc//nHTM0TjjHI+Tc6Rakalnk+QdkY5n97M+eR8mpzD+eSfoaJwPjmfJudwPrXXfGqpTal7772X3/zN32TPnj0cPXq08Pof/vCHOXbsGMeOHeN73/seXV1drFy5stAMzz//PDfddBPf//73ufvuuzlw4ACPPvooH/zgB1m3bl0hGcrr8Pzzz/PII4/wwQ9+kE9/+tOsXLmSs2fPFpph4tc3vvGNQmpPlePaa69tet2/+7u/48Ybb+RP//RP+cIXvsD//J//k7/4i7/gX/2rf8XOnTvZtWtX0zPozdp9Rjmf3pwj5YxKNZ/AGRWR88n5NDmH88n5FIXzyfk0OYfzqb3mU1fqAJU6efIk3/rWt3j66ad58cUX2bFjB//6X//rQjN0d3dz9dVXA3D11Vfzmc98hve///28/PLLzJ49u5AMn/zkJymVSjz55JNcccUVY//8Xe96F7/2a79WSIaJ6/CTP/mTvPvd7+bmm2/mQx/6EDt27OCf//N/XmiGlFLl+OQnP0lXVxdPP/30OX3w9re/nY997GNkWVZ4pnbnjHI+XShHKikzOKNicT45ny6UIxXnk8qcT86nC+VIxflUvJa5U+rb3/421113HYsWLeLjH/84X/3qV5OelJMnT3LfffexYMECrrzyykJq/r//9/949NFHWbdu3TlNWvaWt7ylkBzn87M/+7PccMMN/NEf/VGyDO3i//7f/8uf/umfXrAPAEqlUsGp1O4zyvmkMmdUPM4n55Nyzqd4nE/OJ+XaeT61zKbUvffey8c//nEgv6VuaGiI3bt3F5ph586dzJw5k5kzZ9LT08N3v/tdvvWtb9HRUcwyHjp0iCzLuO666wqpV63rrruO559/vpBaE89F+esLX/hCIbUvlmP16tVNr1nug0WLFp3zz9/2treN5fjd3/3dpueA85+HFStWFFI7mnafUc6nc0WYUSnmE8SZUc6ncc4n59NEzqf08wmcUWXOJ+fTRM6n9pxPLfH2vYMHD/Lkk0/y4IMPAtDV1cU//sf/mHvvvZdbb721sBwf/OAHueeeewA4fvw4f/iHf8iKFSt48sknueaaa5peP/rtelmWFbZ7O/FclL31rW8tpPbFclxoV7sITz75JKOjo6xZs4bTp08XUvN85+GJJ54Y+8NFu3BGOZ8mizCjIs0nKH5GOZ9yzifn02TOpzfzz1BpOJ+cT5M5n96sHeZTS2xK3XvvvZw9e5a5c+eO/bMsy+ju7uZLX/oSfX19heS44oorWLBgwdh//2//7b/R19fHV77yFf79v//3Ta+/cOFCSqUSf/M3f9P0WrX44Q9/WNhD4Cafi1RS5FiwYAGlUomDBw+e88/f/va3A3DZZZcVluV8//uPHDlSWP0onFHOp8kizKhUGaLMKOdTzvnkfJrM+ZR+PoEzCpxP4HyazPnUnvMp/Nv3zp49y3//7/+drVu38uyzz459Pffcc8ydOzfJJ66VlUolOjo6ePXVVwup99a3vpWf//mf58tf/jKnTp160+spPz72+9//PgcOHOCXfumXkmVoF1deeSXLly/nS1/60nn7QMVyRuWcTypzRsXhfMo5n1TmfIrD+ZRzPqmsnedT+Duldu7cyfHjx/ln/+yfvWm3/Jd+6Ze49957+Zf/8l8WkuX06dO8+OKLQH5r55e+9CVOnjzJqlWrCqkP8OUvf5lbbrmFn/mZn+Hf/bt/x5IlSzh79iyPPfYY99xzDz/84Q+bnqG8DiMjI/yf//N/ePTRR9m8eTMrV67kV3/1V5tef2KGibq6unjb295WSP3U/vAP/5BbbrmF97znPdx1110sWbKEjo4OnnrqKf7mb/6Gm266KXXEtuGMGud8enOOiZxRzqiiOZ/GOZ/enGMi55PzqWjOp3HOpzfnmMj51AbzKQtu5cqV2e23337e15544okMyJ577rmm5/jEJz6RAWNfPT092Xvf+97sO9/5TtNrT3b06NFs3bp12TXXXJNdcskl2U/+5E9mH/3oR7M/+7M/a3rtievQ1dWVzZ49O7vtttuyr371q9nIyEjT60/OMPFr0aJFhdSfmONjH/tYoTUnOnr0aPapT30qu/baa7MZM2ZkM2fOzH7mZ34mu/vuu7NTp041vf6F/vf/2Z/9WQZkx48fb3qGCJxR52r3+TQ5R6oZlXo+ZVnaGeV8yjmfzuV8cj6V+Weo9JxP53I+OZ/K2nE+lbIs+NPVJEmSJEmSNO2Ef6aUJEmSJEmSph83pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVLiuoguOjo5y9OhRenp6KJVKRZeXFFCWZZw4cYK5c+fS0ZFur9z5JOl8Iswo55Ok83E+SYqq0vlU+KbU0aNH6e/vL7qspBYwODjIvHnzktV3Pkm6mJQzyvkk6WKcT5Kimmo+Fb4p1dPTM/b95XOKrg6vvAhkQAkuv7r4+mYwQ7QMqesDvHIs/8+J8yGF1PMJgpwPe9IMZjg3Q4AZ5XwyQ5T6ZgiWwfkEBDkXZjBDkPphMlQ4nwrflCrf0nn5HPj40aKrw/3z4NSP4Iq5sOZI8fXNYIZoGVLXB7hvbj60Ut/ynXo+QYzzkTpD6vpmMMNkEWaU88kMUeqbIVYG51Muwrkwgxmi1I+SodL55IPOJUmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVLjCH3TeymbRz1LWchULuZQeXuMELzHAPnZwnMHU8QqTeh1S14+SIYKTh+HgDhgagDMnYEYP9C2ERWth5vzU6dqLPZmLsA6pM6SuH4XzKQ57MhdhHcwQg/MpFnsyxhqYIY6iZ5SbUhVYyDKWs4HFrCRjFIAOOhh94/uV3MV+HmIXWxlgb8qoTZV6HVLXj5IhgqO7Yf9WOLwTSm/cb5mNQKkz//6Zu+CalbBkI8xZlixmW7AncxHWIXWG1PWjcD7FYU/mIqyDGWJwPsViT8ZYAzPEkWpG+fa9KSxnAxvZzfWsoIMOOumiky5KE77voIPF3M5G9nAb61NHborU65C6fpQMqWUZPLcFdt4Kg48AWT6ospE3Xi9/n8HhR+ChD+SDLcsShp7G7MlchHVInSF1/QicT7HYk7kI62CG9JxP8bR7T0KMNTBDDKlnlJtSF3Eb6/lltgDQyYyL/mz59dVsnXaNmnodUtePkiGCA9vgiTvz77OzF//Z8uuPb8yPU2PZk7kI65A6Q+r6UTif4rAncxHWwQwxOJ9isSdjrIEZ4kg9o6relNqzZw+rVq1i7ty5lEol/viP/7gxSYJZyDJWs7WmY1ezlYW8v8GJ0ki9DqnrR8kQwdHd+fCpxeMb4diexuY5H+fT1KZTT0ZYh9QZUtePwvkUhz2Zi7AOZojB+RSLPRljDcwQR4QZVfWm1KlTp7jhhhv48pe/XH/1wJazgRHO1HTsCGemze5p6nVIXT9Khgj2b4VSjU+hK3Xlxzeb82lq06knI6xD6gyp60fhfIrDnsxFWAczxOB8isWejLEGZogjwoyquvyKFStYsWJF/ZUDm0U/i1lJR43vbuxkBkv4KLOYx3GONDhdcVKvQ+r6UTJEcPJw/sA7anzfcHYWXngITg7CzP6GRjuH82lq06UnI6xD6gyp60fhfIrDnsxFWAczxOB8isWejLEGZogjyozymVLnsZS1Y0/dr1XGKEu5o0GJ0ki9DqnrR8kQwcEd45/AUKtSBxzc3pA4bc2ezEVYh9QZUtePwvkUhz2Zi7AOZojB+RSLPRljDcwQR5QZVeONWpU7ffo0p0+fHvvvw8PDzS5Zt6tY2IDfkjGbBQ34PemkXofU9aNkiGBooDG/Z/hQY35PozifWleEdUidIXX9KJxPcdiTuQjrYIYYnE+x2JMx1sAMcUSZUU2/U2rz5s309fWNffX3N/He0wa5lJ6ab+Ur66CTy+htUKI0Uq9D6vpRMkRw5sT4R4LWKhuB14P9mcX51LoirEPqDKnrR+F8isOezEVYBzPE4HyKxZ6MsQZmiCPKjGr6ptSmTZsYGhoa+xocHGx2ybq9xglG67ydb5QRXiXY/4NUKfU6pK4fJUMEM3qg1Fnf7yh1wiXB5rbzqXVFWIfUGVLXj8L5FIc9mYuwDmaIwfkUiz0ZYw3MEEeUGdX0t+91d3fT3d3d7DIN9RKNuI+txMsEu9e2SqnXIXX9KBki6GvEHa5Ab7A7XJ1PrSvCOqTOkLp+FM6nOOzJXIR1MEMMzqdY7MkYa2CGOKLMqKrvlDp58iTPPvsszz77LAB///d/z7PPPsvhw4frSxLIPnZQqvMmshId7KO1n0qYeh1S14+SIYJFayGr7y8TyEZhUZOfBeh8qsx06MkI65A6Q+r6UTif4rAncxHWwQwxOJ9isSdjrIEZ4ogyo6o+E08//TQ33ngjN954IwDr16/nxhtv5LOf/Wx9SQI5ziAH2MkIZ2o6foQz7Oe7Lf3xkJB+HVLXj5IhgpnzYf5KKNV4b2WpC65Z1dyPMwbnUyWmS09GWIfUGVLXj8L5FIc9mYuwDmaIwfkUiz0ZYw3MEEeUGVX1ptStt95KlmVv+tqxY0d9SYJ5jC10MqOmYzvoZBfbGpwojdTrkLp+lAwR3LARsrO1HZuNwJINjc1zPs6nqU2nnoywDqkzpK4fhfMpDnsyF2EdzBCD8ykWezLGGpghjggzqukPOm9VA+zlAWpb4e9wJwPsbXCiNFKvQ+r6UTJEMGcZ3LyltmNvvjs/Xo1hT+YirEPqDKnrR+F8isOezEVYBzPE4HyKxZ6MsQZmiCPCjHJT6iJ2sW2sUae6ta/8+gNsmDa7pmWp1yF1/SgZIli8fnxoTXWbZ/n1m7fkx6mx7MlchHVInSF1/SicT3HYk7kI62CGGJxPsdiTMdbADHGknlFN//S9VreLbbzAU9zGepbwUbI3Pjqygw5GGQFKlOjgAA+zi23TZsd0stTrkLp+lAyplUr5LZqz3wv7t8ILD0Hpja3tbGT8I0WzUZh/e/6z/g1f89iTuQjrkDpD6voROJ9isSdzEdbBDOk5n+Jp956EGGtghhhSzyg3pSowwF4G2Mss5rGUO5jNAi6jl1cZ5mUOsY/tLf+Qs0qkXofU9aNkiGDOsvzr5CAc3A7Dh+D1YbikN/9I0EV3NP+hnMrZk7kI65A6Q+r6UTif4rAncxHWwQwxOJ9isSdjrIEZ4kg1o9yUqsJxjvAwn0sdI7nU65C6fpQMEczsh5um1weztCx7MhdhHVJnSF0/CudTHPZkLsI6mCEG51Ms9mSMNTBDHEXPKJ8pJUmSJEmSpMK5KSVJkiRJkqTCuSklSZIkSZKkwrkpJUmSJEmSpMKVsizLiiw4PDxMX18flOCKuUVWzr1yLP8ow1IHXD6n+PpmMEO0DKnrA5w6CmQwNDREb29vmhCkn08Q43ykzpC6vhnMMFmEGeV8MkOU+maIlcH5lItwLsxghij1o2SodD6l25SSpEnCbEpJ0nmE+Jc+SToP55OkqKaaT10FZjmXd0qZwQwhMqSuD+O76GH4N31t35NmMMNEoWaU86ntM6Sub4ZYGZxPuQjnwgxmiFI/SoZK51OyTanLr4Y1R4qve/88OPWj/MSkqG8GM0TLkLo+wH1z88EZRar5BDHOR+oMqeubwQyTRZpRziczpK5vhlgZnE+5COfCDGaIUj9Khkrnkw86lyRJkiRJUuHclJIkSZIkSVLh3JSSJEmSJElS4dyUkiRJkiRJUuHSffqeajKLfpaylqtYyKX08BoneIkB9rGD4wy2RYbU9c0QK4PiiNAPZkhf3wyKKEI/mMEMZScPw8EdMDQAZ07AjB7oWwiL1sLM+U0vr2BS96MZzDBZ0TPKTakWsZBlLGcDi1lJxigAHXQw+sb3K7mL/TzELrYywN5pmSF1fTPEyqA4IvSDGdLXN4MiitAPZjBD2dHdsH8rHN6Zf0w7QDYCpc78+2fugmtWwpKNMGdZw8srmNT9aAYzTJZqRvn2vRawnA1sZDfXs4IOOuiki066KE34voMOFnM7G9nDbayfdhlS1zdDrAyKI0I/mCF9fTMoogj9YAYzAGQZPLcFdt4Kg48AWf4vetnIG6+Xv8/g8CPw0AfyfzHMsoZFUDDtfk2YIVaG1DPKTangbmM9v8wWADqZcdGfLb++mq0NbdTUGVLXN0OsDIojQj+YIX19MyiiCP1gBjOUHdgGT9yZf5+dvfjPll9/fGN+nKaf1P1oBjNMlnpGuSkV2EKWsZqtNR27mq0s5P0tnyF1fTPEyqA4IvSDGdLXN4MiitAPZjBD2dHd+b+81eLxjXBsT13lFUzqfjSDGSaLMKOq2pTavHkz733ve+np6eGqq67iF37hFzh48GD9KXRey9nACGdqOnaEMw3ZPU2dIXV9M8TKcDHOp2JF6AczpK9vhso5o4oToR/MYIay/VuhVONTfEtd+fHN5nwqTup+NIMZJoswo6ralNq9ezfr1q3j8ccf57HHHuPMmTP83M/9HKdOnao/ic4xi34Ws3LKW/gupJMZLOGjzGJey2ZIXd8MsTJMxflUnAj9YIb09c1QHWdUMSL0gxnMUHbycP7A4KneDnMh2Vl44SE42eQP3HI+FSN1P5rBDJNFmVFVbUo9+uijrF27lne9613ccMMN7Nixg8OHD/PMM8/Ul0JvspS1Y0/dr1XGKEu5o2UzpK5vhlgZpuJ8Kk6EfjBD+vpmqI4zqhgR+sEMZig7uGP8E6xqVeqAg9vr+x1TcT4VI3U/msEMk0WZUTXeqJUbGhoC4K1vfesFf+b06dOcPn167L8PDw/XU7JtXMXCBvyWjNksaNkMqeubIVaGajmfmidCP5ghfX0z1GeqGeV8qk2EfjCDGcqGBhpQHhg+1JjfUynnU3Ok7kczmGGyKDOq5n2x0dFRfvu3f5tbbrmF66+//oI/t3nzZvr6+sa++vv7ay3ZVi6lh446n0PfQSeX0duyGVLXN0OsDNVwPjVXhH4wQ/r6ZqhdJTPK+VSbCP1gBjOUnTkx/pHqtcpG4PUC93ycT82Tuh/NYIbJosyomldh3bp1/NVf/RXf/OY3L/pzmzZtYmhoaOxrcLDJb4qeJl7jBKN13s43ygivUnuHpM6Qur4ZYmWohvOpuSL0gxnS1zdD7SqZUc6n2kToBzOYoWxGD5Q66ypPqRMuKW7P3PnURKn70QxmmCzKjKrp7Xuf+tSn2LlzJ3v27GHevIs/WKu7u5vu7u6awrWzl2jEvXQlXqb2e+lSZ0hd3wyxMlTK+dR8EfrBDOnrm6E2lc4o51NtIvSDGcxQ1teId+cAvQW9u9j51Fyp+9EMZpgsyoyq6k6pLMv41Kc+xYMPPsj3v/99rr322vqq64L2sYNSnbfzlehgH7U/dSx1htT1zRArw1ScT8WJ0A9mSF/fDNVxRhUjQj+YwQxli9ZCVt+NEGSjsKi5n8PgfCpI6n40gxkmizKjqlqFdevWcd999/H1r3+dnp4eXnzxRV588UVeffXV+lLoTY4zyAF2MsKZmo4f4Qz7+S7HOdKyGVLXN0OsDFNxPhUnQj+YIX19M1THGVWMCP1gBjOUzZwP81dCqcaPlip1wTWrYGaTH9nkfCpG6n40gxkmizKjqtqUuueeexgaGuLWW29lzpw5Y1/f+ta36kuh83qMLXQyo6ZjO+hkF9taPkPq+maIleFinE/FitAPZkhf3wyVc0YVJ0I/mMEMZTdshOxsbcdmI7BkQ13lK+J8Kk7qfjSDGSaLMKOqfvve+b7Wrl1bfxK9yQB7eYDazvJ3uJMB9rZ8htT1zRArw8U4n4oVoR/MkL6+GSrnjCpOhH4wgxnK5iyDm7fUduzNd+fHN5vzqTip+9EMZpgswoyq702MarpdbBtr1Klu7Su//gAbGvq3vqkzpK5vhlgZFEeEfjBD+vpmUEQR+sEMZihbvH78X/qmeptM+fWbt+THafpJ3Y9mMMNkqWdUje8eVJF2sY0XeIrbWM8SPkr2xkdHdtDBKCNAiRIdHOBhdrGtKX/jmzpD6vpmiJVBcUToBzOkr28GRRShH8xgBoBSKX+Ly+z3wv6t8MJDUHrj1oBsZPwj2bNRmH97/rNF3CGldNr9mjBDrAypZ5SbUi1igL0MsJdZzGMpdzCbBVxGL68yzMscYh/bm/6Q1tQZUtc3Q6wMiiNCP5ghfX0zKKII/WAGM5TNWZZ/nRyEg9th+BC8PgyX9OYfqb7ojuY/1FxxpO5HM5hhslQzyk2pFnOcIzzM59o6Q+r6ZoiVQXFE6AczpK9vBkUUoR/MYIaymf1w02eTlVcwqfvRDGaYrOgZ5TOlJEmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVDg3pSRJkiRJklS4UpZlWZEFh4eH6evrgxJcMbfIyrlXjkE2CqUOuHxO8fXNYIZoGVLXBzh1FMhgaGiI3t7eNCFIP58gxvlInSF1fTOYYbIIM8r5ZIYo9c0QK4PzKRfhXJjBDFHqR8lQ6XxKtyklSZOE2ZSSpPMI8S99knQezidJUU01n7oKzHIu75QygxlCZEhdH8Z30cPwb/ravifNYIaJQs0o51PbZ0hd3wyxMjifchHOhRnMEKV+lAyVzqdkm1KXXw1rjhRf9/55cOpH+YlJUd8MZoiWIXV9gPvm5oMzilTzCWKcj9QZUtc3gxkmizSjnE9mSF3fDLEyOJ9yEc6FGcwQpX6UDJXOJx90LkmSJEmSpMK5KSVJkiRJkqTCuSklSZIkSZKkwrkpJUmSJEmSpMKl+/S9FjSLfpaylqtYyKX08BoneIkB9rGD4wymjleY1Otw8jAc3AFDA3DmBMzogb6FsGgtzJzf9PJA+jWIkkFx2A+5COuQekZFWIMIGRSH/ZCLsA6p55MZYtTXuVJfm6nrR8kQ4bowQ5oMbkpVYCHLWM4GFrOSjFEAOuhg9I3vV3IX+3mIXWxlgL0pozZV6nU4uhv2b4XDO/OPtgTIRqDUmX//zF1wzUpYshHmLGt4eSD9GkTJoDjsh1yEdUg9oyKsQYQMisN+yEVYh9TzyQwx6utcqa/N1PWjZIhwXZghbQbfvjeF5WxgI7u5nhV00EEnXXTSRWnC9x10sJjb2cgebmN96shNkXIdsgye2wI7b4XBR4AsvziykTdeL3+fweFH4KEP5BdTljUsAhCjFyJkUBz2Qy71OkSYUanXIEoGxWE/5FKvQ4T5ZIb09fVmqa/N1PUjZIhwXZghRgY3pS7iNtbzy2wBoJMZF/3Z8uur2Trt/mCVeh0ObIMn7sy/z85e/GfLrz++MT+uUVKvQZQMisN+yEVYh9QzKsIaRMigOOyHXIR1SD2fzBCjvs6V+tpMXT9KhgjXhRliZKhqU+qee+5hyZIl9Pb20tvby/ve9z4eeeSRxiQJZiHLWM3Wmo5dzVYW8v4GJ0oj9Toc3Z03fC0e3wjH9tRVHki/BlEyROd8qsx06ocI65B6RkVYgwgZWkG7zCj7IRdhHVLPJzPEqF+JdplPkP7aTF0/SoYI14UZ4mSoalNq3rx5/P7v/z7PPPMMTz/9ND/7sz/Lxz72Mf7X//pf9ScJZjkbGOFMTceOcGba/G1f6nXYvxVKNT75rNSVH1+v1GsQJUN0zqfKTKd+iLAOqWdUhDWIkKEVtMuMsh9yEdYh9XwyQ4z6lWiX+QTpr83U9aNkiHBdmCFOhqo2pVatWsXtt9/OwoULeec738nnP/95Zs6cyeOPP15/kkBm0c9iVk55K+OFdDKDJXyUWcxrcLJipV6Hk4fzh6xNdQvhhWRn4YWH4GQdHxiReg2iZGgFzqfKTJd+iLAOqWdUhDWIkKFVtMOMsh9yEdYh9XwyQ4z6lWqH+QTpr83U9aNkiHBdmCFOBqjjmVIjIyN885vf5NSpU7zvfe+rL0UwS1k79ukDtcoYZSl3NChRGqnX4eCO8af+16rUAQe313586jWIkqHVOJ8ubjr0Q4R1SD2jIqxBhAytaLrOKPshF2EdUs8nM8SoX4vpOp8g/bWZun6UDBGuCzPEyQBQ9Y1aBw4c4H3vex+vvfYaM2fO5MEHH+Snf/qnL/jzp0+f5vTp02P/fXh4uLakBbqKhQ34LRmzWdCA35NO6nUYGmhAeWD4UO3Hpl6DKBlahfOpUq3fDxHWIfWMirAGETK0kmpmlPOpdUVYh9TzyQwx6ldjus8nSH9tpq4fJUOE68IMcTJADXdKLVq0iGeffZYnnniC3/iN3+ATn/gEf/3Xf33Bn9+8eTN9fX1jX/39/XUFLsKl9NBR5wcTdtDJZfQ2KFEaqdfhzInxj6GsVTYCr9fx/5Op1yBKhlbhfKrMdOiHCOuQekZFWIMIGVpJNTPK+dS6IqxD6vlkhhj1qzHd5xOkvzZT14+SIcJ1YYY4GaCGTalLLrmEBQsWcNNNN7F582ZuuOEG/sN/+A8X/PlNmzYxNDQ09jU42OQ3RTfAa5xgtM7bGkcZ4VVa428NLiT1OszogVJnXeUpdcIldfzZNvUaRMnQKpxPlZkO/RBhHVLPqAhrECFDK6lmRjmfWleEdUg9n8wQo341pvt8gvTXZur6UTJEuC7MECcD1PD2vclGR0fPuX1zsu7ubrq7u+stU6iXaMR9bCVepoB7bZso9Tr0NeLuUqC3jncBpF6DKBlalfPpQlq/HyKsQ+oZFWENImRoZRebUc6n1hVhHVLPJzPEqF+P6TafIP21mbp+lAwRrgszxMkAVd4ptWnTJvbs2cPzzz/PgQMH2LRpEz/4wQ9Ys2ZNfSmC2ccOSnXe1liig30U+FTCJki9DovWQlbfRj7ZKCyq43mpqdcgSoZW4Hyq3HTohwjrkHpGRViDCBlaRTvMKPshF2EdUs8nM8SoX6l2mE+Q/tpMXT9KhgjXhRniZIAqN6VeeuklfvVXf5VFixbxoQ99iKeeeoo/+ZM/Yfny5fWlCOY4gxxgJyOcqen4Ec6wn+9ynCMNTlas1Oswcz7MXwmlGu/nK3XBNatgZh1vc0+9BlEytALnU2WmSz9EWIfUMyrCGkTI0CraYUbZD7kI65B6PpkhRv1KtcN8gvTXZur6UTJEuC7MECcDVLkpde+99/L8889z+vRpXnrpJXbt2jXthlXZY2yhkxk1HdtBJ7vY1uBEaaRehxs2Qna2tmOzEViyoa7yQPo1iJIhOudTZaZTP0RYh9QzKsIaRMjQCtplRtkPuQjrkHo+mSFG/Uq0y3yC9Ndm6vpRMkS4LswQJ0N99+5NYwPs5QFqW+HvcCcD7G1wojRSr8OcZXDzltqOvfnu/Ph6pV6DKBkUh/2Qi7AOqWdUhDWIkEFx2A+5COuQej6ZIUZ9nSv1tZm6fpQMEa4LM8TJ4KbURexi29gFO9UtjuXXH2DDtPlbvrLU67B4/fiFMtWtheXXb96SH9coqdcgSgbFYT/kIqxD6hkVYQ0iZFAc9kMuwjqknk9miFFf50p9baauHyVDhOvCDDEyuCk1hV1sYwvLOMDDjDLKCGcZ4SwZo4xwhhHOMsooB3iYLSybdn+gKku5DqVSflvgqt0w/3aglH/0ZPnjK8e+L+Wvr9qd/3yp1LAIQIxeiJBBcdgPudTrEGFGpV6DKBkUh/2QS70OEeaTGdLX15ulvjZT14+QIcJ1YYYYGWp8pFV7GWAvA+xlFvNYyh3MZgGX0curDPMyh9jH9pZ/KGclUq/DnGX518lBOLgdhg/B68NwSW/+MZSL7mj+gyBTr0GUDIrDfshFWIfUMyrCGkTIoDjsh1yEdUg9n8wQo77OlfraTF0/SoYI14UZ0mZwU6oKxznCw3wudYzkUq/DzH646bPJygPp1yBKBsVhP+QirEPqGRVhDSJkUBz2Qy7COqSeT2aIUV/nSn1tpq4fJUOE68IMaTL49j1JkiRJkiQVzk0pSZIkSZIkFc5NKUmSJEmSJBXOTSlJkiRJkiQVrpRlWVZkweHhYfr6+qAEV8wtsnLulWOQjUKpAy6fU3x9M5ghWobU9QFOHQUyGBoaore3N00I0s8niHE+UmdIXd8MZpgswoxyPpkhSn0zxMrgfMpFOBdmMEOU+lEyVDqf0m1KSdIkYTalJOk8QvxLnySdh/NJUlRTzaeuArOcyzulzGCGEBlS14fxXfQw/Ju+tu9JM5hholAzyvnU9hlS1zdDrAzOp1yEc2EGM0SpHyVDpfMp2abU5VfDmiPF171/Hpz6UX5iUtQ3gxmiZUhdH+C+ufngjCLVfIIY5yN1htT1zWCGySLNKOeTGVLXN0OsDM6nXIRzYQYzRKkfJUOl88kHnUuSJEmSJKlwbkpJkiRJkiSpcG5KSZIkSZIkqXBuSkmSJEmSJKlwbkpJkiRJkiSpcMk+fa8VnTwMB3fA0ACcOQEzeqBvISxaCzPnm6GoDLPoZylruYqFXEoPr3GClxhgHzs4zmDzA5B+DSDGOkTIoFyEnjRDLvV14RrEyaBchJ40Qy7CdeE6xFgDjUt9PlL3oxnGpe4FaM91cFOqAkd3w/6tcHgnlN64tywbgVJn/v0zd8E1K2HJRpizzAzNyrCQZSxnA4tZScYoAB10MPrG9yu5i/08xC62MsDexgcg/RpAjHWIkEG5CD1phlzq68I1iJNBuQg9aYZchOvCdYixBhqX+nyk7kczjEvdC9De6+Db9y4iy+C5LbDzVhh8BMjyk5KNvPF6+fsMDj8CD30gP4lZZoZGZ1jOBjaym+tZQQcddNJFJ12UJnzfQQeLuZ2N7OE21jeuODHWANKvQ5QMitGTZhiX8rpwDWJlUIyeNMO41NeF6xBnDZSLcD5SX5dmyEXoBXAd3JS6iAPb4Ik78++zsxf/2fLrj2/MjzND4zLcxnp+mS0AdDLjoj9bfn01Wxt6saZeA4ixDhEyKBehJ82QS31duAZxMigXoSfNkItwXbgOMdZA41Kfj9T9aIZxqXsBXAeoc1Pq93//9ymVSvz2b/92Y9IEcnR3vtC1eHwjHNtjhkZkWMgyVrO1pmNXs5WFvL++AKRfA4ixDhEyVMP5dH7TZTZEyZD6unAN4mSohvPp/KbTbIiQIcJ14TrEWINqOaPOb7r8u40Zcql7AVyHspo3pZ566in+y3/5LyxZsqT+FAHt3wqlGp+4VerKjzdD/RmWs4ERztR07AhnGrKDnHoNIMY6RMhQKefThU2X2RAlQ+rrwjWIk6FSzqcLm06zIUKGCNeF6xBjDarhjLqw6fLvNmbIpe4FcB3KatqUOnnyJGvWrOErX/kKs2bNqj9FMCcP5w/3murWtQvJzsILD8HJOh6Ob4b8kwcWs3LK2xgvpJMZLOGjzGJebQFIvwYQYx0iZKiU8+nipsNsiJIh9XXhGsTJUCnn08VNl9kQIUOE68J1iLEG1XBGXdx0+HcbM+RS9wK4DhPVtCm1bt06PvKRj3DbbbfVVz2ogzvGnzZfq1IHHNxuhnoyLGXt2CcP1CpjlKXcUfPxqdcAYqxDhAyVcj5NrdVnQ5QMqa8L1yBOhko5n6Y2HWZDhAwRrgvXIcYaVMMZNbVW/3cbM+RS9wK4DhNVfaPWN7/5Tf7yL/+Sp556qqKfP336NKdPnx7778PDw9WWLNzQQGN+z/AhM9ST4SoWNqB6xmwW1Hx06jWAGOsQIUMlnE+Va+XZECVD6uvCNYiToRLOp8q1+myIkCHCdeE6xFiDSlUzo1pxPkH685G6H80wLnUvgOswUVX7YoODg3z605/m/vvv59JLL63omM2bN9PX1zf21d/fX1PQIp05Mf7xh7XKRuD1OuazGeBSeuio8wMiO+jkMnprPj71GkCMdYiQYSrOp8q1+myIkiH1deEaxMkwFedT5abDbIiQIcJ14TrEWINKVDujWnE+QfrzkbofzTAudS+A6zBRVavwzDPP8NJLL/Hud7+brq4uurq62L17N//xP/5Hurq6GBl58/+iTZs2MTQ0NPY1OFjQm6LrMKMHSp31/Y5SJ1xSx59vzQCvcYLROm9pHGWEV6n9Kkm9BhBjHSJkmIrzqXKtPhuiZEh9XbgGcTJMxflUuekwGyJkiHBduA4x1qAS1c6oVpxPkP58pO5HM4xL3QvgOkxU1dv3PvShD3HgwIFz/tkdd9zBddddx+/+7u/S2fnm/0Xd3d10d3fXl7JgfY24kw7oreOdAGaAl2jE/YQlXqb2+wlTrwHEWIcIGabifKpOK8+GKBlSXxeuQZwMU3E+VafVZ0OEDBGuC9chxhpUotoZ1YrzCdKfj9T9aIZxqXsBXIeJqrpTqqenh+uvv/6cryuuuIIrr7yS66+/vr4kgSxaC1l9m5Zko7CojmemmgH2sYNSnbc0luhgH7U/eS31GkCMdYiQYSrOp8q1+myIkiH1deEaxMkwFedT5abDbIiQIcJ14TrEWINKOKMq1+r/bmOGXOpeANdhojqftT49zZwP81dCqerHwOdKXXDNKphZx9urzQDHGeQAOxnhTE3Hj3CG/XyX4xypLQDp1wBirEOEDMpF6Ekz5FJfF65BnAzKRehJM+QiXBeuQ4w10LjU5yN1P5phXOpeANdhoro3pX7wgx/wxS9+sd5fE84NGyE7W9ux2Qgs2WCGRmR4jC10MqOmYzvoZBfb6gtA+jWAGOsQIUO1nE9vNl1mQ5QMqa8L1yBOhmo5n95sOs2GCBkiXBeuQ4w1qIUz6s2my7/bmCGXuhfAdSjzTqkLmLMMbt5S27E3350fb4b6MwywlweordO/w50MsLe+AKRfA4ixDhEyKBehJ82QS31duAZxMigXoSfNkItwXbgOMdZA41Kfj9T9aIZxqXsBXIcyN6UuYvH68RM01S1t5ddv3pIfZ4bGZdjFtrGLdarbG8uvP8CGhv7Nd+o1gBjrECGDchF60gy51NeFaxAng3IRetIMuQjXhesQYw00LvX5SN2PZhiXuhfAdQA3pS6qVMpvR1u1G+bfDpTyjzwsf2zi2Pel/PVVu/OfL5XM0OgMu9jGFpZxgIcZZZQRzjLCWTJGGeEMI5xllFEO8DBbWNbwf8mIsAaQfh2iZFCMnjTDuJTXhWsQK4Ni9KQZxqW+LlyHOGugXITzkfq6NEMuQi+A61DjI63ay5xl+dfJQTi4HYYPwevDcElv/vGHi+5o/gMIzZDf3jjAXmYxj6XcwWwWcBm9vMowL3OIfWxv+oNqU68BxFiHCBmUi9CTZsilvi5cgzgZlIvQk2bIRbguXIcYa6Bxqc9H6n40w7jUvQDtvQ5uSlVhZj/c9FkzpM5wnCM8zOfSBSD9GkCMdYiQQbkIPWmGXOrrwjWIk0G5CD1phlyE68J1iLEGGpf6fKTuRzOMS90L0J7r4Nv3JEmSJEmSVDg3pSRJkiRJklQ4N6UkSZIkSZJUODelJEmSJEmSVLhSlmVZkQWHh4fp6+uDElwxt8jKuVeOQTYKpQ64fE7x9c1ghmgZUtcHOHUUyGBoaIje3t40IUg/nyDG+UidIXV9M5hhsggzyvlkhij1zRArg/MpF+FcmMEMUepHyVDpfEq3KSVJk4TZlJKk8wjxL32SdB7OJ0lRTTWfugrMci7vlDKDGUJkSF0fxnfRw/Bv+tq+J81gholCzSjnU9tnSF3fDLEyOJ9yEc6FGcwQpX6UDJXOp2SbUpdfDWuOFF/3/nlw6kf5iUlR3wxmiJYhdX2A++bmgzOKVPMJYpyP1BlS1zeDGSaLNKOcT2ZIXd8MsTI4n3IRzoUZzBClfpQMlc4nH3QuSZIkSZKkwrkpJUmSJEmSpMK5KSVJkiRJkqTCuSklSZIkSZKkwqX79L0qnTwMB3fA0ACcOQEzeqBvISxaCzPnm6GdMsyin6Ws5SoWcik9vMYJXmKAfezgOIPND2CGUBkiSH1NmGFchJ5MnSF1fTPEk/raTF0/SoYIPWmGGBki9GMUEdYidYbU/WgGM0xW9DURflPq6G7YvxUO78w/zhAgG4FSZ/79M3fBNSthyUaYs8wM0znDQpaxnA0sZiUZowB00MHoG9+v5C728xC72MoAexsfwAyhMkSQ+poww7gIPZk6Q+r6Zogn9bWZun6UDBF60gwxMkToxygirEXqDKn70QxmmCzVNRH27XtZBs9tgZ23wuAjQJYvSDbyxuvl7zM4/Ag89IF8AbPMDNMxw3I2sJHdXM8KOuigky466aI04fsOOljM7WxkD7exvnHFzRAuQ2oRrgkzjIvQk6kzpK5vhlhSX5up60fJADF60gzpM0TpxwgirEWEDO1+TZghVobU10TYTakD2+CJO/Pvs7MX/9ny649vzI8zw/TKcBvr+WW2ANDJjIv+bPn11Wxt6MVqhjgZIkh9TZhhXISeTJ0hdX0zxJP62kxdP0qGCD1phhgZIvRjFBHWInWG1P1oBjNMlvqaCLkpdXR3/j+yFo9vhGN7zDBdMixkGavZWtOxq9nKQt5fXwAzhMoQQeprwgzjIvRk6gyp65shntTXZur6UTJE6EkzxMgQoR+jiLAWqTOk7kczmGGy1NcEVLkpddddd1Eqlc75uu666+pPMcn+rVCq8WlXpa78eDNMjwzL2cAIZ2o6doQzDdlBNkOcDBfjfGq/DBF6MnWG1PXNULl2mVGp60fJEKEnzRAjQ4R+nEq7zKcIGVL3oxnMMFnqawJquFPqXe96F8eOHRv7+vM///P6U0xw8nD+YK2pbhu7kOwsvPAQnKzjwfRmiJFhFv0sZuWUtzFeSCczWMJHmcW82gKYIVSGSjif2idDhJ5MnSF1fTNUb7rPqNT1o2SI0JNmiJEhQj9WarrPpwgZUvejGcwwWeproqzqTamuri6uvvrqsa+3ve1t9SWY5OCO8Se916rUAQe3m6HVMyxl7dgnD9QqY5Sl3FHz8WaIk6ESzqf2yRChJ1NnSF3fDNWb7jMqdf0oGSL0pBliZIjQj5Wa7vMpQobU/WgGM0yW+pooqzrCwMAAc+fO5e1vfztr1qzh8OHDF/3506dPMzw8fM7XxQwNVJvo/IYP1X6sGWJkuIqFDaieMZsFNR9thjgZKuF8ap8MEXoydYbU9c1QvWpmVLXzCdJfm6nrR8kQoSfNECNDhH6s1HSfTxEypO5HM5hhstTXRFlVm1L/8B/+Q3bs2MGjjz7KPffcw9///d/z/ve/nxMnTlzwmM2bN9PX1zf21d/ff9EaZ06Mf/RgrbIReH3q2WiG4BkupYeOOp/F30Enl9Fb8/FmiJNhKs6n9soQoSdTZ0hd3wzVqXZGVTufIP21mbp+lAwRetIMMTJE6MdKtMN8ipAhdT+awQyTpb4myqpahRUrVrB69WqWLFnCz//8z/M//sf/4Mc//jHf/va3L3jMpk2bGBoaGvsaHLz4Gw5n9ECps5pUb1bqhEvq+LOlGWJkeI0TjNZ5S+MoI7xK7VeJGeJkmIrzqb0yROjJ1BlS1zdDdaqdUdXOJ0h/baauHyVDhJ40Q4wMEfqxEu0wnyJkSN2PZjDDZKmvibIan7Oee8tb3sI73/lODh268P1a3d3ddHd3V/w7+xpxFxvQW8dd+GaIkeElGnE/YYmXqf1+QjPEyVAt59P0zhChJ1NnSF3fDPWZakZVO58g/bWZun6UDBF60gwxMkTox1pMx/kUIUPqfjSDGSZLfU2U1XW/2MmTJ/nf//t/M2fOnPpSTLBoLWT1bRiSjcKiOp5XaoYYGfaxg1KdtzSW6GAftT95zQxxMlTL+TS9M0ToydQZUtc3Q32m44xKXT9Khgg9aYYYGSL0Yy2m43yKkCF1P5rBDJOlvibKqlqFjRs3snv3bp5//nn27dvHL/7iL9LZ2cmv/Mqv1JdigpnzYf5KKNV4D1epC65ZBTOnfmuzGYJnOM4gB9jJCGdqOn6EM+znuxznSG0BzBAqw1ScT+2VIUJPps6Qur4ZqtMOMyp1/SgZIvSkGWJkiNCPlWiH+RQhQ+p+NIMZJkt9TZRVtSl15MgR/n/27j+4rvq+8//zXsmIH5YUh9jFrmVKYsW0xWYoSb/UTBTS4DYQOWmn8e52yDamuzvbxs2mtc023pnNsksSN0X2ZLdJ2W6W2NkhP8mUDpiFFqeJccc1v7pgd5u6cluwHJuF2XUk24CR7j3fPw7SlYVt3Xvuvef9urqvx4wmAuno/eJz3p93zIeje3/1V3+VFStW8E/+yT/h8ssvZ//+/SxcuLC+FDNcuxmSiWzXJiVYtckZ5kqGxxiig3mZri3SwW621xfAGaQyXIjnU/tlUOjJ6AzR9Z2heu0yo6Lrq2RQ6Eln0Mig0I+zaZf5pJAhuh+dwRlmit4TUOOh1De/+U2OHTvGmTNnOHr0KN/85jd5xzveUX+KGRYPwA1D2a694e70emeYGxmG2cv9ZOv073AHw+ytL4AzSGW4EM+n9sug0JPRGaLrO0P12mVGRddXyaDQk86gkUGhH2fTLvNJIUN0PzqDM8wUvSegzteUaqaVGyuLM9vjZJNfv2Eovc4Z5laG3Wyf2qyzPd44+fX72dTQ//LtDDoZFETvCWeoUOjJ6AzR9Z1BT/TejK6vkkGhJ51BI4NCP6pQWIvoDNH96AzOMFP0npA9lCoU0kfB1u6BZbcChfTtBiffsnDq80L69bV70u8vFJxhLmbYzXaGGOAgD1OmTIkJSkyQUKbEOCUmKFPmIA8zxEBT/iXDGXQyRFPYE85QodCT0Rmi6zuDlui9GV1fJQNo9KQzxGdQ6UcFCmuhkKHd94QzaGWI3hMZX9IqP4sH0o9TI3BoB4wdhtfH4KKe9K0HV9ze/Bf/cwaNDMPsZZi9LGApq7mdhSznEnp4lTFe5jD72NH0F6p1Bp0MCqL3hDNUKPRkdIbo+s6gJ3pvRtdXyaDQk86gkUGhH1UorEV0huh+dAZnmClqT8gfSk2a3wfXf9oZnAFOcJSHuSsugDNIZVAQvSecoUKhJ6MzRNd3Bj3RezO6vkoGhZ50Bo0MCv2oQmEtojNE96MzOMNMee8J2V/fMzMzMzMzMzOzucuHUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrkrJEmS5FlwbGyM3t5eKMBlS/KsnHrlOCRlKBTh0sX513cGZ1DLEF0f4PQxIIHR0VF6enpiQhA/n0DjfkRniK7vDM4wk8KM8nxyBpX6zqCVwfMppXAvnMEZVOqrZKh2PsUdSpmZzSBzKGVmdg4S/9JnZnYOnk9mpmq2+dSZY5az+UkpZ3AGiQzR9aFyii7D/6Wv7XvSGZxhOqkZ5fnU9hmi6zuDVgbPp5TCvXAGZ1Cpr5Kh2vkUdih16RVw29H8635tKZz+YXpjIuo7gzOoZYiuD3DfknRwqoiaT6BxP6IzRNd3BmeYSWlGeT45Q3R9Z9DK4PmUUrgXzuAMKvVVMlQ7n/xC52ZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpa7sHffa0WnjsChnTA6DOMnYV439PbDivUwf5kz5Jkh2gL6WM16FtHPxXTzGid5iWH2sZMTjLRNBveCDoV74Z7UoHAfFDK4F3Qo3Av3pA6FexGdwb2gJfp+RPcjxK+BCoV7oZAh737woVQVju2BA9vgyC4ovPFsWVKCQkf6+TN3wpWDsGozLB5whmZmiNbPAGvYxEoGSSgDUKRI+Y3PB7mTAzzEbrYxzN45m8G9oEPhXrgnNSjcB4UM7gUdCvfCPalD4V5EZ3AvaIm+H9H9CPFroELhXihkiOoH//reBSQJPDcEu26CkUeAJL0pSemNr09+nsCRR+Ch96Y3MUmcodEZFKxhE5vZwzXcQpEiHXTSQSeFaZ8XKbKSW9nM49zMxjmXwb2gQ+VeuCc1RN8HhQzuBR0q98I9qSP6XkRncC9oUbgf0XtCYQ1URN8LhQzR/eBDqQs4uB2euCP9PJm48PdOfn3/5vQ6Z2hshmg3s5GPMARAB/Mu+L2TX1/HtoYODIUM7gUdCvfCPalB4T4oZHAv6FC4F+5JHQr3IjqDe0FL9P2I7keIXwMVCvdCIUN0P9R8KPXDH/6Qj370o1x++eVccsklrFy5kqeffroxaYQc25MudBb7N8Pxx52hURmi9TPAOrZlunYd2+jnPXMiQyv0gufT7Bp1L9yTGhTug0KGVumFdphRCvfCPalD4V5EZ2iVXmiH+QTx9yO6HyF+DVQo3AuFDAr9UNOh1IkTJ7jxxhuZN28ejzzyCH/zN3/Dtm3bWLBgQf1JxBzYBoWMr7hV6Eyvd4bGZIi2hk2UGM90bYnxhpxiK2RQ7wXPp+o06l64JzUo3AeFDK3QC+0yoxTuhXtSh8K9iM7QCr3QLvMJ4u9HdD9C/BqoULgXChkU+qGm8p///Ofp6+tjx44dU3/vqquuqj+FmFNH0hf3IuPvSCYT8MJDcGoE5vc5Qz0Zoi2gj5UMUsz4m64dzGMVH2IBSznB0ZbN0Aq94PlUnUbcC/ekBoX7oJChVXqhHWaUwr1wT+pQuBfRGVqlF9phPkH8/YjuR4hfAxUK90Ihg0o/1LQCDz74IO9617tYt24dixYt4rrrruPLX/5y9uqiDu2svNp8VoUiHNox+/c5g7bVrJ9694OsEsqs5vaWztAKveD5VL1674V7UoPCfVDI0Cq90A4zSuFeuCd1KNyL6Ayt0gvtMJ8g/n5E9yPEr4EKhXuhkEGlH2qK8A//8A/cc8899Pf386d/+qf85m/+Jv/m3/wbvvrVr573mjNnzjA2NnbWh7rR4cb8nLHDzlBvhmiL6G/AT0lYyPKWztAKveD5VJt67oV7UoPCfVDI0Cq9UOuM8nzKxj2pQ+FeRGdolV5oh/kE8fcjuh8hfg1UKNwLhQwq/VDTr++Vy2Xe9a538bnPfQ6A6667jr/+67/mv/7X/8rHPvaxc16zdetW/uN//I/1pczZ+MnK2x9mlZTg9TrmszNouJjuzI9UTirSwSX0tHSGVugFz6fq1Xsv3JMaFO6DQoZW6YVaZ5TnUzbuSR0K9yI6Q6v0QjvMJ4i/H9H9CPFroELhXihkUOmHmlZh8eLF/NRP/dRZf+8nf/InOXLkyHmv2bJlC6Ojo1MfIyMj2ZLmaF43FDrq+xmFDrgoe384g4jXOEm5zscqy5R4lew7VSFDK/SC51P16r0X7kkNCvdBIUOr9EKtM8rzKRv3pA6FexGdoVV6oR3mE8Tfj+h+hPg1UKFwLxQyqPRDTU9K3XjjjRw6dOisv/d3f/d3XHnllee9pquri66urmzpgvQ24kk6oCf7k3TOIOIlGvFMY4GXyf5Mo0KGVugFz6fa1HMv3JMaFO6DQoZW6YVaZ5TnUzbuSR0K9yI6Q6v0QjvMJ4i/H9H9CPFroELhXihkUOmHmp6U+p3f+R3279/P5z73OQ4fPszXv/51/tt/+29s2LChvhRiVqyHpL5DS5IyrMj+mmPOIGIfOynU+VhlgSL7yP7qbwoZWqEXPJ+qV++9cE9qULgPChlapRfaYUYp3Av3pA6FexGdoVV6oR3mE8Tfj+h+hPg1UKFwLxQyqPRDTavw7ne/mwceeIBvfOMbXHPNNdx111184Qtf4LbbbqsvhZj5y2DZIBRqeo6sotAJV66t720RnUHDCUY4yC5KjGe6vsQ4B3gw89t0qmRohV7wfKpOI+6Fe1KDwn1QyNAqvdAOM0rhXrgndSjci+gMrdIL7TCfIP5+RPcjxK+BCoV7oZBBpR9qPpobHBzk4MGDvPbaa/zgBz/gX/2rf1VfAlHXboZkItu1SQlWbXKGRmWI9hhDdDAv07VFOtjN9jmRoRV6wfNpdo26F+5JDQr3QSFDq/RCO8wohXvhntShcC+iM7RKL7TDfIL4+xHdjxC/BioU7oVCBoV+qO95sTls8QDcMJTt2hvuTq93hsZkiDbMXu4n2277DncwzN45kcG9oEPhXrgnNSjcB4UM7gUdCvfCPalD4V5EZ3AvaIm+H9H9CPFroELhXihkUOgHH0pdwMqNlRs02yNtk1+/YSi9zhkamyHabrZPDYzZHrGc/Pr9bGrI6bVSBveCDoV74Z7UoHAfFDK4F3Qo3Av3pA6FexGdwb2gJfp+RPcjxK+BCoV7oZAhuh98KHUBhUL6ONraPbDsVqCQvuXh5NsmTn1eSL++dk/6/YWCMzQ6g4LdbGeIAQ7yMGXKlJigxAQJZUqMU2KCMmUO8jBDDDR0UKhkcC/oULkX7kkN0fdBIYN7QYfKvXBP6oi+F9EZ3AtaFO5H9J5QWAMV0fdCIUN0P2R8Sav2sngg/Tg1Aod2wNhheH0MLupJ3/5wxe3Nf7E3Z9AwzF6G2csClrKa21nIci6hh1cZ42UOs48ddb3YXKtkcC/oULgX7kkNCvdBIYN7QYfCvXBP6lC4F9EZ3Ataou9HdD9C/BqoULgXChmi+sGHUjWY3wfXf9oZFDJEO8FRHuauts/gXtChcC/ckxoU7oNCBveCDoV74Z7UoXAvojO4F7RE34/ofoT4NVChcC8UMuTdD/71PTMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHJXSJIkybPg2NgYvb29UIDLluRZOfXKcUjKUCjCpYvzr+8MzqCWIbo+wOljQAKjo6P09PTEhCB+PoHG/YjOEF3fGZxhJoUZ5fnkDCr1nUErg+dTSuFeOIMzqNRXyVDtfIo7lDIzm0HmUMrM7Bwk/qXPzOwcPJ/MTNVs86kzxyxn85NSzuAMEhmi60PlFF2G/0tf2/ekMzjDdFIzyvOp7TNE13cGrQyeTymFe+EMzqBSXyVDtfMp7FDq0ivgtqP51/3aUjj9w/TGRNR3BmdQyxBdH+C+JengVBE1n0DjfkRniK7vDM4wk9KM8nxyhuj6zqCVwfMppXAvnMEZVOqrZKh2PvmFzs3MzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHLnQykzMzMzMzMzM8td3Lvv1WgBfaxmPYvo52K6eY2TvMQw+9jJCUZyyXDqCBzaCaPDMH4S5nVDbz+sWA/zl+USQYLXQYPCfVDIoEBhPilkUOCe1KBwHxQyqIieD9H1VbgndUTfi+j6ShTmg0KGaO5JHQr3Iu8M8odS/Qywhk2sZJCEMgBFipTf+HyQOznAQ+xmG8PsbUqGY3vgwDY4sit9S0WApASFjvTzZ+6EKwdh1WZYPNCUCBK8DhoU7oNCBgUK80khgwL3pAaF+6CQQUX0fIiur8I9qSP6XkTXV6IwHxQyRHNP6lC4F1EZpH99bw2b2MweruEWihTpoJMOOilM+7xIkZXcymYe52Y2NrR+ksBzQ7DrJhh5BEjSm5KU3vj65OcJHHkEHnpvehOTpKExwnkdNCjcB4UMKqLnk0qGaO5JDQr3QSGDkuj5EF1fgXtSR/S9iK6vRmE+KGSI5J7UoXAvojPIHkrdzEY+whAAHcy74PdOfn0d2xo6MA5uhyfuSD9PJi78vZNf3785vW4u8TpoULgPChkUKMwnhQwK3JMaFO6DQgYV0fMhur4K96SO6HsRXV+JwnxQyBDNPalD4V5EZ5A8lOpngHVsy3TtOrbRz3vqznBsT7rQWezfDMcfrzuCBK+DBoX7oJBBgcJ8UsigwD2pQeE+KGRQET0fouurcE/qiL4X0fWVKMwHhQzR3JM6FO6FQoaaDqV+4id+gkKh8KaPDRs21J9kmjVsosR4pmtLjDfkFPvANihkfMWtQmd6/VzgddCgcB8UMswmjxmlMJ8UMihohZ5sBwr3QSHDbNrlz1DR9VW0Qk+2i+h7EV2/Gu0yn1QyRGuFnmwXCvdCIUNNh1JPPfUUx48fn/p47LHHAFi3bl39Sd6wgD5WMjjro5Tn08E8VvEhFrA0c4ZTR9IX95rt0bXzSSbghYfgVIu/WYPXQYPCfVDIUI1mzyiF+aSQQUGr9ORcp3AfFDJUox3+DBVdX0Wr9GQ7iL4X0fWr1Q7zSSVDtFbpyXagcC8UMkCNh1ILFy7kiiuumPrYtWsX73jHO3jve99bX4ppVrN+6t0Pskoos5rbM19/aGfl1eazKhTh0I76fkY0r4MGhfugkKEazZ5RCvNJIYOCVunJuU7hPihkqEY7/Bkqur6KVunJdhB9L6LrV6sd5pNKhmit0pPtQOFeKGQAyPigFrz++uvcd999bNy4kUKhcN7vO3PmDGfOnJn667GxsQv+3EX0Z400TcJClme+enS4ARGAscON+TlRvA4aFO6DQoZaVTOjWnE+KWRQ0Io9ORcp3AeFDLVqxnyC+PkQXV9FK/bkXBV9L6LrZzFX55NKhmit2JNzlcK9UMgAdbzQ+Z/8yZ/wox/9iPXr11/w+7Zu3Upvb+/UR19f3wW//2K6Kdb5+utFOriEnszXj5+svP1hVkkJXp99PkvzOmhQuA8KGWpVzYxqxfmkkEFBK/bkXKRwHxQy1KoZ8wni50N0fRWt2JNzVfS9iK6fxVydTyoZorViT85VCvdCIQPUcSh17733csstt7BkyZILft+WLVsYHR2d+hgZufAvHL7GScp1PlZZpsSrZF+Zed1Q6KgrAoUOuKh15xXgdVChcB8UMtSqmhnVivNJIYOCVuzJuUjhPihkqFUz5hPEz4fo+ipasSfnquh7EV0/i7k6n1QyRGvFnpyrFO6FQgbI+Ot7L7zwArt37+aP//iPZ/3erq4uurq6qv7ZL9GIZ8gKvEz2Z8h6G/FkJ9DTuk92Al4HFQr3QSFDLaqdUa04nxQyKGi1npyrFO6DQoZaNGs+Qfx8iK6votV6ci6LvhfR9Ws1l+eTSoZordaTc5nCvVDIABmflNqxYweLFi3igx/8YH3Vz2EfOynU+VhlgSL7yP5qWyvWQ1LfITpJGVa07mvgAV4HFQr3QSFDLZo1oxTmk0IGBa3Wk3OVwn1QyFCLufxnqOj6KlqtJ+ey6HsRXb9Wc3k+qWSI1mo9OZcp3AuFDJDhUKpcLrNjxw4+9rGP0dmZ+XXSz+sEIxxkFyXGM11fYpwDPMgJjmbOMH8ZLBuEQsZ/vEInXLkW5s/+69XSvA4aFO6DQoZqNXNGKcwnhQwKWqkn5zKF+6CQoVpz/c9Q0fVVtFJPznXR9yK6fi3m+nxSyRCtlXpyrlO4FwoZIMOh1O7duzly5Ai//uu/Xl/lC3iMITqYl+naIh3sZnvdGa7dDMlEtmuTEqzaVHcECV4HDQr3QSFDNZo9oxTmk0IGBa3Sk3Odwn1QyFCNdvgzVHR9Fa3Sk+0g+l5E169WO8wnlQzRWqUn24HCvVDIUPOh1C/8wi+QJAnvfOc7669+HsPs5X6y/dN9hzsYZm/dGRYPwA1D2a694e70+rnA66BB4T4oZKhGs2eUwnxSyKCgVXpyrlO4DwoZqtEOf4aKrq+iVXqyHUTfi+j61WqH+aSSIVqr9GQ7ULgXChnq+6XaJtrN9qmBMdsjlpNfv59NDT29XrmxcoNme6Rt8us3DKXXzSVeBw0K90EhgwKF+aSQQYF7UoPCfVDIoCJ6PkTXV+Ge1BF9L6LrK1GYDwoZorkndSjci+gMsodSkA6MIQY4yMOUKVNighITJJQpMU6JCcqUOcjDDDHQ8EFRKKSPo63dA8tuBQrpWx5Ovm3i1OeF9Otr96TfXyg0NEY4r4MGhfugkEFF9HxSyRDNPalB4T4oZFASPR+i6ytwT+qIvhfR9dUozAeFDJHckzoU7kV0hsa/il2DDbOXYfaygKWs5nYWspxL6OFVxniZw+xjR9NfbG7xQPpxagQO7YCxw/D6GFzUk7794Yrb2+PF3rwOGhTug0IGBQrzSSGDAvekBoX7oJBBRfR8iK6vwj2pI/peRNdXojAfFDJEc0/qULgXURnkD6UmneAoD3NXaIb5fXD9p0MjSPA6aFC4DwoZFCjMJ4UMCtyTGhTug0IGFdHzIbq+Cvekjuh7EV1ficJ8UMgQzT2pQ+Fe5J1B+tf3zMzMzMzMzMxsbvKhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe4KSZIkeRYcGxujt7cXCnDZkjwrp145DkkZCkW4dHH+9Z3BGdQyRNcHOH0MSGB0dJSenp6YEMTPJ9C4H9EZous7gzPMpDCjPJ+cQaW+M2hl8HxKKdwLZ3AGlfoqGaqdT3GHUmZmM8gcSpmZnYPEv/SZmZ2D55OZqZptPnXmmOVsflLKGZxBIkN0faicosvwf+lr+550BmeYTmpGeT61fYbo+s6glcHzKaVwL5zBGVTqq2Sodj6FHUpdegXcdjT/ul9bCqd/mN6YiPrO4AxqGaLrA9y3JB2cKqLmE2jcj+gM0fWdwRlmUppRnk/OEF3fGbQyeD6lFO6FMziDSn2VDNXOJ7/QuZmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeUu7N33zFrZqSNwaCeMDsP4SZjXDb39sGI9zF8WnS4/XofUAvpYzXoW0c/FdPMaJ3mJYfaxkxOMRMezNuN9mfI6VHhGmRLvTa/BdJ5PpsR7M5X3OvhQyqwGx/bAgW1wZBcU3njOMClBoSP9/Jk74cpBWLUZFg+ExWw6r0OqnwHWsImVDJJQBqBIkfIbnw9yJwd4iN1sY5i9kVGtDXhfprwOFZ5RpsR702swneeTKfHeTEWtg399z6wKSQLPDcGum2DkESBJN2hSeuPrk58ncOQReOi96YZOksDQTeB1qFjDJjazh2u4hSJFOuikg04K0z4vUmQlt7KZx7mZjdGRbY7yvkx5Hc7mGWUqvDe9BjN5PpkK781U9Dr4UMqsCge3wxN3pJ8nExf+3smv79+cXjeXeB1SN7ORjzAEQAfzLvi9k19fxzb/ocqawvsy5XWo8IwyJd6bXoPpPJ9MifdmKnodajqUKpVK/Pt//++56qqruOSSS3jHO97BXXfdRTLXjgrNpjm2J910WezfDMcfb2yeKOrrkNd86meAdWzLdO06ttHPexqax9qb+r7MSyusg2eUtaNW2JvN1gpr4Plk7agV9mYeFNahpkOpz3/+89xzzz188Ytf5Ac/+AGf//zn+f3f/33+4A/+oP4kZqIObINCxldfK3Sm188F6uuQ13xawyZKjGe6tsS4/0ufNZT6vsxLK6yDZ5S1o1bYm83WCmvg+WTtqBX2Zh4U1qGm8vv27ePDH/4wH/zgBwH4iZ/4Cb7xjW/w5JNP1p/ETNCpI+kLvZHxPxQlE/DCQ3BqBOb3NTRarlphHfKYTwvoYyWDFDP+5nMH81jFh1jAUk5wtGG5rD21wr7MQ6usg2eUtZtW2ZvN1Cpr4Plk7aZV9mazqaxDTVNh9erVfPe73+Xv/u7vAHjuuecs4j4sAAEAAElEQVT4i7/4C2655ZbsCcyEHdpZeeeBrApFOLSjIXHCtMI65DGfVrN+6h1iskoos5rbG5TI2lkr7Ms8tMo6eEZZu2mVvdlMrbIGnk/WblplbzabyjrU9KTUpz71KcbGxrj66qvp6OigVCrx2c9+lttuu+2815w5c4YzZ85M/fXY2Fj2tGY5Gx1uzM8ZO9yYnxOlFdYhj/m0iP4GJE1YyPIG/Bxrd62wL/PQKutQ64zK8ucnzyhT0ip7s5laZQ08n6zdtMrebDaVdajpXOzb3/42X/va1/j617/OX/3VX/HVr36VoaEhvvrVr573mq1bt9Lb2zv10dfXws+3WdsZP1l5K8yskhK83uJnsa2wDnnMp4vpzvzY+aQiHVxCT10/wwxaY1/moVXWodYZleXPT55RpqRV9mYztcoaeD5Zu2mVvdlsKutQ02S44447+NSnPsU/+2f/jJUrV/LP//k/53d+53fYunXrea/ZsmULo6OjUx8jIyP1JTbL0bxuKHTU9zMKHXBRi///ZyusQx7z6TVOUq7z0fMyJV6lxf8fzCS0wr7MQ6usQ60zKsufnzyjTEmr7M1mapU18HyydtMqe7PZVNahpl/fe+WVVygWzz7H6ujooFw+/4Dp6uqiq6srWzqzYL2NeNIY6GnxJ41bYR3ymE8v0YhnXAu8TIs/62sSWmFf5qFV1qHWGZXlz0+eUaakVfZmM7XKGng+Wbtplb3ZbCrrUNOTUmvXruWzn/0sDz/8MM8//zwPPPAA27dv55d/+ZfrS2EmasV6SOr7jzokZVjR4q/J2ArrkMd82sdOCnU+el6gyD5a/FURTUIr7Ms8tMo6eEZZu2mVvdlMrbIGnk/WblplbzabyjrUNBn+4A/+gI985CN8/OMf5yd/8ifZvHkz//pf/2vuuuuu+lKYiZq/DJYNQqGmZworCp1w5drWfqtQaI11yGM+nWCEg+yixHim60uMc4AH/VbG1hCtsC/z0Crr4Bll7aZV9mYztcoaeD5Zu2mVvdlsKutQ06FUd3c3X/jCF3jhhRd49dVX+fu//3s+85nPcNFFF9WXwkzYtZshmch2bVKCVZsamyeK+jrkNZ8eY4gO5mW6tkgHu9ne0DzW3tT3ZV5aYR08o6wdtcLebLZWWAPPJ2tHrbA386CwDvU9Q2nWBhYPwA1D2a694e70+rnA65AaZi/3k236foc7GGZvgxNZO/O+THkdKjyjTIn3ptdgOs8nU+K9mVJYBx9KmVVh5cbKZp3t8cbJr98wlF43l3gdUrvZPvWHqtkeQ5/8+v1s8n/hs6bwvkx5HSo8o0yJ96bXYDrPJ1PivZmKXgcfSplVoVBIH01cuweW3QoU0re/nHwLzanPC+nX1+5Jv79QiEzdeF6Hit1sZ4gBDvIwZcqUmKDEBAllSoxTYoIyZQ7yMEMM+A9T1jTelymvw9k8o0yF96bXYCbPJ1PhvZmKXoeML2ll1p4WD6Qfp0bg0A4YOwyvj8FFPelbYa64vfVf8K4aXofUMHsZZi8LWMpqbmchy7mEHl5ljJc5zD52+AU5LTfelymvQ4VnlCnx3vQaTOf5ZEq8N1NR6+BDKbMM5vfB9Z+OThHP65A6wVEexu9Cahq8L1NehwrPKFPivek1mM7zyZR4b6byXgf/+p6ZmZmZmZmZmeXOh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma5KyRJkuRZcHR0lLe85S0AXLo4z8qpV14EEqAAl16Rf31ncAa1DNH1AV45nv7vj370I3p7e2NCED+fQOR+uCedwRnOziAwozyfnEGlvjOIZfB8AkTuhTM4g0h9mQxVzqfcD6WOHj1KX18bvJ+imdVsZGSEpUuXhtX3fDKzC4mcUZ5PZnYhnk9mpmq2+ZT7oVS5XObYsWN0d3dTKBRqvn5sbIy+vj5GRkbo6elpQkJnaJUM0fWdoXEZkiTh5MmTLFmyhGIx7reKPZ+cYS5liK4/lzIozKh65xPE34/o+s7gDGoZPJ8qou+FQobo+s7gDI3OUO186qwnZBbFYrEhp/g9PT1hN8cZtDJE13eGxmSI/LW9SZ5PzjAXM0TXnysZomdUo+YTxN+P6PrO4AxqGTyfKqLvhUKG6PrO4AyNzFDNfPILnZuZmZmZmZmZWe58KGVmZmZmZmZmZrlruUOprq4u/sN/+A90dXU5Q5tniK7vDFoZFCisgzM4g0p9Z9ATvRbR9Z3BGdQyRNdXorAW0Rmi6zuDM0RlyP2Fzs3MzMzMzMzMzFruSSkzMzMzMzMzM2t9PpQyMzMzMzMzM7Pc+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLXUsdSv3lX/4lHR0dfPCDH8y99vr16ykUClMfl19+OR/4wAc4cOBA7llefPFFPvGJT/D2t7+drq4u+vr6WLt2Ld/97nebXnv6OsybN48f+7EfY82aNXzlK1+hXC43vf7MDNM/PvCBD+RSf7Ychw8fzqX+iy++yCc/+UmWL1/OxRdfzI/92I9x4403cs899/DKK680vf769ev5pV/6pTf9/e9///sUCgV+9KMfNT2DGs8oz6eZOaJmVPR8gtgZ5fn0Zp5Pnk8zc3g++c9QKjyfPJ9m5vB8aq/51FKHUvfeey+f+MQnePzxxzl27Fju9T/wgQ9w/Phxjh8/zne/+106OzsZHBzMNcPzzz/P9ddfz5//+Z9z9913c/DgQR599FHe9773sWHDhlwyTK7D888/zyOPPML73vc+PvnJTzI4OMjExESuGaZ/fOMb38il9mw5rrrqqqbX/Yd/+Aeuu+46/uzP/ozPfe5z/K//9b/4y7/8S/7tv/237Nq1i927dzc9g71Zu88oz6c354icUVHzCTyjFHk+eT7NzOH55PmkwvPJ82lmDs+n9ppPndEBqnXq1Cm+9a1v8fTTT/Piiy+yc+dO/t2/+3e5Zujq6uKKK64A4IorruBTn/oU73nPe3j55ZdZuHBhLhk+/vGPUygUePLJJ7nsssum/v5P//RP8+u//uu5ZJi+Dj/+4z/Oz/zMz3DDDTfw/ve/n507d/Iv/+W/zDVDpKgcH//4x+ns7OTpp58+qw/e/va38+EPf5gkSXLP1O48ozyfzpcjSmQGzygtnk+eT+fLEcXzySZ5Pnk+nS9HFM+n/LXMk1Lf/va3ufrqq1mxYgUf/ehH+cpXvhJ6U06dOsV9993H8uXLufzyy3Op+f/+3//j0UcfZcOGDWc16aS3vOUtueQ4l5//+Z/n2muv5Y//+I/DMrSL//t//y9/9md/dt4+ACgUCjmnsnafUZ5PNskzSo/nk+eTpTyf9Hg+eT5Zqp3nU8scSt1777189KMfBdJH6kZHR9mzZ0+uGXbt2sX8+fOZP38+3d3dPPjgg3zrW9+iWMxnGQ8fPkySJFx99dW51KvV1VdfzfPPP59Lren3YvLjc5/7XC61L5Rj3bp1Ta852QcrVqw46++/7W1vm8rxu7/7u03PAee+D7fccksutdW0+4zyfDqbwoyKmE+gM6M8nyo8nzyfpvN8ip9P4Bk1yfPJ82k6z6f2nE8t8et7hw4d4sknn+SBBx4AoLOzk3/6T/8p9957LzfddFNuOd73vvdxzz33AHDixAn+8A//kFtuuYUnn3ySK6+8sun11R/XS5Ikt9Pb6fdi0lvf+tZcal8ox/lOtfPw5JNPUi6Xue222zhz5kwuNc91H5544ompP1y0C88oz6eZFGaU0nyC/GeU51PK88nzaSbPpzfzn6FieD55Ps3k+fRm7TCfWuJQ6t5772ViYoIlS5ZM/b0kSejq6uKLX/wivb29ueS47LLLWL58+dRf//f//t/p7e3ly1/+Mp/5zGeaXr+/v59CocDf/u3fNr1WFj/4wQ9yexG4mfciSkSO5cuXUygUOHTo0Fl//+1vfzsAl1xySW5ZzvXPf/To0dzqq/CM8nyaSWFGRWVQmVGeTynPJ8+nmTyf4ucTeEaB5xN4Ps3k+dSe80n+1/cmJib4H//jf7Bt2zaeffbZqY/nnnuOJUuWhLzj2qRCoUCxWOTVV1/Npd5b3/pWfvEXf5EvfelLnD59+k1fj3z72D//8z/n4MGD/Mqv/EpYhnZx+eWXs2bNGr74xS+esw8sX55RKc8nm+QZpcPzKeX5ZJM8n3R4PqU8n2xSO88n+Seldu3axYkTJ/gX/+JfvOm0/Fd+5Ve49957+Y3f+I1cspw5c4YXX3wRSB/t/OIXv8ipU6dYu3ZtLvUBvvSlL3HjjTfysz/7s/yn//SfWLVqFRMTEzz22GPcc889/OAHP2h6hsl1KJVK/J//83949NFH2bp1K4ODg/zar/1a0+tPzzBdZ2cnb3vb23KpH+0P//APufHGG3nXu97FnXfeyapVqygWizz11FP87d/+Lddff310xLbhGVXh+fTmHNN5RnlG5c3zqcLz6c05pvN88nzKm+dThefTm3NM5/nUBvMpETc4OJjceuut5/zaE088kQDJc8891/QcH/vYxxJg6qO7uzt597vfnXznO99peu2Zjh07lmzYsCG58sork4suuij58R//8eRDH/pQ8r3vfa/ptaevQ2dnZ7Jw4cLk5ptvTr7yla8kpVKp6fVnZpj+sWLFilzqT8/x4Q9/ONea0x07diz5rd/6reSqq65K5s2bl8yfPz/52Z/92eTuu+9OTp8+3fT65/vn/973vpcAyYkTJ5qeQYFn1NnafT7NzBE1o6LnU5LEzijPp5Tn09k8nzyfJvnPUPE8n87m+eT5NKkd51MhScRfXc3MzMzMzMzMzOYc+deUMjMzMzMzMzOzuceHUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlzodSZmZmZmZmZmaWOx9KmZmZmZmZmZlZ7nwoZWZmZmZmZmZmufOhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnrzLtguVzm2LFjdHd3UygU8i5vZoKSJOHkyZMsWbKEYjHurNzzyczORWFGeT6Z2bl4PpmZqmrnU+6HUseOHaOvry/vsmbWAkZGRli6dGlYfc8nM7uQyBnl+WRmF+L5ZGaqZptPuR9KdXd3T31+6eK8q8MrLwIJUIBLr8i/vjM4g1qG6PoArxxP/3f6fIgQPZ9A5H64J53BGc7OIDCjPJ+cQaW+M4hl8HwCRO6FMziDSH2ZDFXOp9wPpSYf6bx0MXz0WN7V4WtL4fQP4bIlcNvR/Os7gzOoZYiuD3DfknRoRT/yHT2fQON+RGeIru8MzjCTwozyfHIGlfrOoJXB8ymlcC+cwRlU6qtkqHY++YXOzczMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy13uL3TeyhbQx2rWs4h+Lqab1zjJSwyzj52cYCQ6Xm6i1yG6vkoGBaeOwKGdMDoM4ydhXjf09sOK9TB/WXS69uKeTCmsQ3SG6PoqPJ90uCdTCuvgDBo8n7S4JzXWwBl05D2jfChVhX4GWMMmVjJIQhmAIkXKb3w+yJ0c4CF2s41h9kZGbarodYiur5JBwbE9cGAbHNkFhTeet0xKUOhIP3/mTrhyEFZthsUDYTHbgnsypbAO0Rmi66vwfNLhnkwprIMzaPB80uKe1FgDZ9ARNaP863uzWMMmNrOHa7iFIkU66KSDTgrTPi9SZCW3spnHuZmN0ZGbInodouurZIiWJPDcEOy6CUYeAZJ0UCWlN74++XkCRx6Bh96bDrYkCQw9h7knUwrrEJ0hur4Czyct7smUwjo4QzzPJz3t3pOgsQbOoCF6RvlQ6gJuZiMfYQiADuZd8Hsnv76ObXOuUaPXIbq+SgYFB7fDE3eknycTF/7eya/v35xeZ43lnkwprEN0huj6KjyfdLgnUwrr4AwaPJ+0uCc11sAZdETPqJoPpR5//HHWrl3LkiVLKBQK/Mmf/EljkojpZ4B1bMt07Tq20c97GpwoRvQ6RNdXyaDg2J50+GSxfzMcf7yxec7F82l2c6knFdYhOkN0fRWeTzrckymFdXAGDZ5PWtyTGmvgDDoUZlTNh1KnT5/m2muv5Utf+lL91YWtYRMlxjNdW2J8zpyeRq9DdH2VDAoObINCxlehK3Sm1zeb59Ps5lJPKqxDdIbo+io8n3S4J1MK6+AMGjyftLgnNdbAGXQozKiay99yyy3ccsst9VcWtoA+VjJIMeNvN3Ywj1V8iAUs5QRHG5wuP9HrEF1fJYOCU0fSF7wj4+8NJxPwwkNwagTm9zU02lk8n2Y3V3pSYR2iM0TXV+H5pMM9mVJYB2fQ4PmkxT2psQbOoENlRvk1pc5hNeunXnU/q4Qyq7m9QYliRK9DdH2VDAoO7ay8A0NWhSIc2tGQOG3NPZlSWIfoDNH1VXg+6XBPphTWwRk0eD5pcU9qrIEz6FCZURkf1KremTNnOHPmzNRfj42NNbtk3RbR34CfkrCQ5Q34OXGi1yG6vkoGBaPDjfk5Y4cb83MaxfOpdSmsQ3SG6PoqPJ90uCdTCuvgDBo8n7S4JzXWwBl0qMyopj8ptXXrVnp7e6c++vqa+Oxpg1xMd+ZH+SYV6eASehqUKEb0OkTXV8mgYPxk5S1Bs0pK8LrYn1k8n1qXwjpEZ4iur8LzSYd7MqWwDs6gwfNJi3tSYw2cQYfKjGr6odSWLVsYHR2d+hgZGWl2ybq9xknKdT7OV6bEq4j9P0iNotchur5KBgXzuqHQUd/PKHTARWJz2/OpdSmsQ3SG6PoqPJ90uCdTCuvgDBo8n7S4JzXWwBl0qMyopv/6XldXF11dXc0u01Av0Yjn2Aq8jNiztjWKXofo+ioZFPQ24glXoEfsCVfPp9alsA7RGaLrq/B80uGeTCmsgzNo8HzS4p7UWANn0KEyo2p+UurUqVM8++yzPPvsswD84z/+I88++yxHjhypL4mQfeykUOdDZAWK7KO1X5Uweh2i66tkULBiPST1/ccEkjKsaPJrAXo+VWcu9KTCOkRniK6vwvNJh3sypbAOzqDB80mLe1JjDZxBh8qMqvlOPP3001x33XVcd911AGzcuJHrrruOT3/60/UlEXKCEQ6yixLjma4vMc4BHmzpt4eE+HWIrq+SQcH8ZbBsEAoZn60sdMKVa5v7dsbg+VSNudKTCusQnSG6vgrPJx3uyZTCOjiDBs8nLe5JjTVwBh0qM6rmQ6mbbrqJJEne9LFz5876koh5jCE6mJfp2iId7GZ7gxPFiF6H6PoqGRRcuxmSiWzXJiVYtamxec7F82l2c6knFdYhOkN0fRWeTzrckymFdXAGDZ5PWtyTGmvgDDoUZlTTX+i8VQ2zl/vJtsLf4Q6G2dvgRDGi1yG6vkoGBYsH4IahbNfecHd6vTWGezKlsA7RGaLrq/B80uGeTCmsgzNo8HzS4p7UWANn0KEwo3wodQG72T7VqLM92jf59fvZNGdOTSdFr0N0fZUMClZurAyt2R7znPz6DUPpddZY7smUwjpEZ4iur8LzSYd7MqWwDs6gwfNJi3tSYw2cQUf0jGr6u++1ut1s5wWe4mY2sooPkbzx1pFFipQpAQUKFDnIw+xm+5w5MZ0peh2i66tkiFYopI9oLnw3HNgGLzwEhTeOtpNS5S1FkzIsuzX9Xv8XvuZxT6YU1iE6Q3R9BZ5PWtyTKYV1cIZ4nk962r0nQWMNnEFD9IzyoVQVhtnLMHtZwFJWczsLWc4l9PAqY7zMYfaxo+Vf5Kwa0esQXV8lg4LFA+nHqRE4tAPGDsPrY3BRT/qWoCtub/6LclrKPZlSWIfoDNH1VXg+6XBPphTWwRk0eD5pcU9qrIEz6IiaUT6UqsEJjvIwd0XHCBe9DtH1VTIomN8H18+tN2ZpWe7JlMI6RGeIrq/C80mHezKlsA7OoMHzSYt7UmMNnEFH3jPKryllZmZmZmZmZma586GUmZmZmZmZmZnlzodSZmZmZmZmZmaWOx9KmZmZmZmZmZlZ7gpJkiR5FhwbG6O3txcKcNmSPCunXjmevpVhoQiXLs6/vjM4g1qG6PoAp48BCYyOjtLT0xMTgvj5BBr3IzpDdH1ncIaZFGaU55MzqNR3Bq0Mnk8phXvhDM6gUl8lQ7XzKe5QysxsBplDKTOzc5D4lz4zs3PwfDIzVbPNp84cs5zNT0o5gzNIZIiuD5VTdBn+L31t35PO4AzTSc0oz6e2zxBd3xm0Mng+pRTuhTM4g0p9lQzVzqewQ6lLr4DbjuZf92tL4fQP0xsTUd8ZnEEtQ3R9gPuWpINTRdR8Ao37EZ0hur4zOMNMSjPK88kZous7g1YGz6eUwr1wBmdQqa+Sodr55Bc6NzMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9yFvfueZbOAPlaznkX0czHdvMZJXmKYfezkBCNtkSG6vjNUnDoCh3bC6DCMn4R53dDbDyvWw/xluUQwIQo96Qzx9VUyeD7ZdAo96QzOMMnzyaaL7kdncIaZ8p5RPpRqEf0MsIZNrGSQhDIARYqU3/h8kDs5wEPsZhvD7J2TGaLrO0PFsT1wYBsc2QWFN563TEpQ6Eg/f+ZOuHIQVm2GxQNNiWBCFHrSGeLrq2TwfLLpFHrSGZxhkueTTRfdj87gDDNFzSj/+l4LWMMmNrOHa7iFIkU66KSDTgrTPi9SZCW3spnHuZmNcy5DdH1nSCUJPDcEu26CkUeAJB1USemNr09+nsCRR+Ch96aDLUkaGsOERPekM2jUV8jg+WQzRfekMzjDJM8nm6nd94QzaGWInlE+lBJ3Mxv5CEMAdDDvgt87+fV1bGtoo0ZniK7vDBUHt8MTd6SfJxMX/t7Jr+/fnF5nc49CTzpDfH2VDJ5PNp1CTzqDM0zyfLLpovvRGZxhpugZVdOh1NatW3n3u99Nd3c3ixYt4pd+6Zc4dOhQY5LYm/QzwDq2Zbp2Hdvo5z0tnyG6vjNUHNuTDp8s9m+G44/XHeGCPJ/ypdCTzhBfXyWD+nwCz6g8KfSkMzjDJM8nmy66H53BGWZSmFE1HUrt2bOHDRs2sH//fh577DHGx8f5hV/4BU6fPl1/EnuTNWyixHima0uMN+T0NDpDdH1nqDiwDQoZX4Wu0Jle30yeT/lS6ElniK+vkkF9PoFnVJ4UetIZnGGS55NNF92PzuAMMynMqJrKP/roo2f99c6dO1m0aBHPPPMMAwN+Nb5GWkAfKxmkmPE3LDuYxyo+xAKWcoKjLZkhur4zVJw6kr7gHRl/bziZgBceglMjML8v28+YjedTfhR60hni66tkaIX5BJ5ReVHoSWdwhkmeTzZddD86gzPMpDKj6npNqdHRUQDe+ta31vNj7BxWs37qVfezSiizmttbNkN0fWeoOLSz8g4MWRWKcGhHfT+jFp5PzaPQk84QX18lQyvOJ/CMahaFnnQGZ5jk+WTTRfejMzjDTCozKuODWlAul/nt3/5tbrzxRq655przft+ZM2c4c+bM1F+PjY1lLdlWFtHfgJ+SsJDlLZshur4zVIwONyACMHa4MT9nNp5PzaXQk84QX18lQ6vNJ6huRnk+ZaPQk87gDJM8n2y66H50BmeYSWVGZT4X27BhA3/913/NN7/5zQt+39atW+nt7Z366Otr4rOnc8jFdGd+lG9SkQ4uoadlM0TXd4aK8ZOVtwTNKinB6zn9mcXzqbkUetIZ4uurZGi1+QTVzSjPp2wUetIZnGGS55NNF92PzuAMM6nMqEyr8Fu/9Vvs2rWL733veyxduvSC37tlyxZGR0enPkZGRjIFbTevcZJynY/zlSnxKtk7JDpDdH1nqJjXDYWOuiJQ6ICLss/Mqnk+NZ9CTzpDfH2VDK00n6D6GeX5lI1CTzqDM0zyfLLpovvRGZxhJpUZVdOv7yVJwic+8QkeeOABvv/973PVVVfNek1XVxddXV2ZA7arl2jEs3QFXib7s3TRGaLrO0NFbyOeLgV6sj9dOivPp/wo9KQzxNdXydAK8wlqn1GeT9ko9KQzOMMkzyebLrofncEZZlKZUTU9KbVhwwbuu+8+vv71r9Pd3c2LL77Iiy++yKuvvlpfCnuTfeykUOfjfAWK7CP7q45FZ4iu7wwVK9ZDUt9BPkkZVmR/Hb5ZeT7lR6EnnSG+vkqGVphP4BmVF4WedAZnmOT5ZNNF96MzOMNMKjOqplW45557GB0d5aabbmLx4sVTH9/61rfqS2FvcoIRDrKLEuOZri8xzgEezPz2kAoZous7Q8X8ZbBsEAoZ3xqh0AlXrm3u2xl7PuVHoSedIb6+SoZWmE/gGZUXhZ50BmeY5Plk00X3ozM4w0wqM6qmQ6kkSc75sX79+vpS2Dk9xhAdzMt0bZEOdrO95TNE13eGims3QzKR7dqkBKs21R3hwjU8n3Kl0JPOEF9fJYP6fALPqDwp9KQzOMMkzyebLrofncEZZlKYUfU9L2ZNNcxe7ifbXf4OdzDM3pbPEF3fGSoWD8ANQ9muveHu9HqbOxR60hni66tk8Hyy6RR60hmcYZLnk00X3Y/O4AwzKcwoH0qJ2832qUad7dG+ya/fz6aGnJqqZIiu7wwVKzdWhtZsj3lOfv2GofQ6m3sUetIZ4uurZPB8sukUetIZnGGS55NNF92PzuAMM0XPqIy/PWh52s12XuApbmYjq/gQyRtvHVmkSJkSUKBAkYM8zG62N+TEVC1DdH1nSBUK6SOaC98NB7bBCw9B4Y2j7aRUeUvRpAzLbk2/1/+Fb26L7kln0KivkMHzyWaK7klncIZJnk82U7vvCWfQyhA9o3wo1SKG2cswe1nAUlZzOwtZziX08CpjvMxh9rGjrhc5a4UM0fWdoWLxQPpxagQO7YCxw/D6GFzUk74l6Irbm/+inKZDoSedIb6+SgbPJ5tOoSedwRkmeT7ZdNH96AzOMFPUjPKhVIs5wVEe5q62zhBd3xkq5vfB9Z8OjWBCFHrSGeLrq2TwfLLpFHrSGZxhkueTTRfdj87gDDPlPaP8mlJmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlrpAkSZJnwbGxMXp7e6EAly3Js3LqlePpWxkWinDp4vzrO4MzqGWIrg9w+hiQwOjoKD09PTEhiJ9PoHE/ojNE13cGZ5hJYUZ5PjmDSn1n0Mrg+ZRSuBfO4Awq9VUyVDuf4g6lzMxmkDmUMjM7B4l/6TMzOwfPJzNTNdt86swxy9n8pJQzOINEhuj6UDlFl+H/0tf2PekMzjCd1IzyfGr7DNH1nUErg+dTSuFeOIMzqNRXyVDtfAo7lLr0CrjtaP51v7YUTv8wvTER9Z3BGdQyRNcHuG9JOjhVRM0n0Lgf0Rmi6zuDM8ykNKM8n5whur4zaGXwfEop3AtncAaV+ioZqp1PfqFzMzMzMzMzMzPLnQ+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMchf37nstaAF9rGY9i+jnYrp5jZO8xDD72MkJRpwhpwynjsChnTA6DOMnYV439PbDivUwf1nTyzuDWAYF0XvCGbQyRO+L6PrOoCd6X0TXd4YKhX3hDPH1lSjsi+gM0fVVMijsC2eIyeBDqSr0M8AaNrGSQRLKABQpUn7j80Hu5AAPsZttDLPXGZqU4dgeOLANjuxK39oSIClBoSP9/Jk74cpBWLUZFg80vLwziGVQEL0nnEErQ/S+iK7vDHqi90V0fWeoUNgXzhBfX4nCvojOEF1fJYPCvnCG2Az+9b1ZrGETm9nDNdxCkSIddNJBJ4VpnxcpspJb2czj3MxGZ2hwhiSB54Zg100w8giQpJsjKb3x9cnPEzjyCDz03nQzJUnDIjiDUAYV7b4vnaEiel9E13cGTdH7Irq+M6QU9oUzxNdXE70vFDJE11fIoLAvnEEjgw+lLuBmNvIRhgDoYN4Fv3fy6+vY1tAN6wxwcDs8cUf6eTJx4e+d/Pr+zel1jeIMOhkURO8JZ9DKEL0vous7g57ofRFd3xkqFPaFM8TXV6KwL6IzRNdXyaCwL5xBI4MPpc6jnwHWsS3TtevYRj/vcYYGZDi2J234LPZvhuOP11XeGcQyKIjeE86glSF6X0TXdwY90fsiur4zVCjsC2eIr69EYV9EZ4iur5JBYV84g06Gmg6l7rnnHlatWkVPTw89PT383M/9HI888kj9KQStYRMlxjNdW2K8IafIzpA+FljI+Mpnhc70+no5g06GC8lrPkXvCWfQyhC9L6LrO0P12mVGRdd3hgqFfeEM8fWr0S7zSSFDdH2VDAr7whl0MtR0KLV06VJ+7/d+j2eeeYann36an//5n+fDH/4w//t//+/6kwhZQB8rGZz1Ucbz6WAeq/gQC1jqDHVkOHUkfZG12R4hPJ9kAl54CE7V8YYRzqCTYTZ5zKfoPeEMWhmi90V0fWeoTTvMqOj6zlChsC+cIb5+tdphPilkiK6vkkFhXziDTgao8VBq7dq13HrrrfT39/POd76Tz372s8yfP5/9+/fXl0LMatZPvftAVgllVnO7M9SR4dDOyqv+Z1UowqEd2a93Bp0Ms8ljPkXvCWfQyhC9L6LrO0Nt2mFGRdd3hgqFfeEM8fWr1Q7zSSFDdH2VDAr7whl0MgBkfFALSqUS999/P6dPn+bnfu7nzvt9Z86c4cyZM1N/PTY2lrVkbhbR34CfkrCQ5c5QR4bR4QaUB8YOZ7/WGXQy1KJZ8yl6TziDVobofRFd3xmyq2ZGZfnzU/S+iK7vDBUK+8IZ4utnMVfnk0KG6PoqGRT2hTPoZIAML3R+8OBB5s+fT1dXF7/xG7/BAw88wE/91E+d9/u3bt1Kb2/v1EdfX19dgfNwMd0U63wN+CIdXEKPM9SRYfxk5W0os0pK8Hod56DOoJOhGs2eT9F7whm0MkTvi+j6zlC7WmZUlj8/Re+L6PrOUKGwL5whvn4t5vp8UsgQXV8lg8K+cAadDJDhUGrFihU8++yzPPHEE/zmb/4mH/vYx/ibv/mb837/li1bGB0dnfoYGWnyL0U3wGucpFznY41lSrxK9rvjDDCvGwoddZWn0AEXZZ+ZziCUoRrNnk/Re8IZtDJE74vo+s5Qu1pmVJY/P0Xvi+j6zlChsC+cIb5+Leb6fFLIEF1fJYPCvnAGnQyQ4df3LrroIpYvTx/Xu/7663nqqaf4z//5P/NHf/RH5/z+rq4uurq66kuZs5doxHNsBV4m+3NszgC9jXi6FOjJ/nSpMwhlqEaz51P0nnAGrQzR+yK6vjPUrpYZleXPT9H7Irq+M1Qo7AtniK9fi7k+nxQyRNdXyaCwL5xBJwNkeFJqpnK5fNbvFM8F+9hJoc6lKVBkH9lf8csZYMV6SOo7yCcpw4rsr8PnDEIZsmj0fIreE86glSF6X0TXd4b6zbUZFV3fGSoU9oUzxNevx1ybTwoZouurZFDYF86gkwFqPJTasmULjz/+OM8//zwHDx5ky5YtfP/73+e2226rL4WYE4xwkF2UGM90fYlxDvAgJzjqDHVkmL8Mlg1CIePL8Rc64cq1ML+OlzFzBp0Ms8ljPkXvCWfQyhC9L6LrO0Nt2mFGRdd3hgqFfeEM8fWr1Q7zSSFDdH2VDAr7whl0MkCNh1IvvfQSv/Zrv8aKFSt4//vfz1NPPcWf/umfsmbNmvpSCHqMITqYl+naIh3sZrszNCDDtZshmch2bVKCVZvqKu8MYhkuJK/5FL0nnEErQ/S+iK7vDNVrlxkVXd8ZKhT2hTPE169Gu8wnhQzR9VUyKOwLZ9DJUNOh1L333svzzz/PmTNneOmll9i9e/ecPJACGGYv95Nthb/DHQyz1xkakGHxANwwlO3aG+5Or6+XM+hkuJC85lP0nnAGrQzR+yK6vjNUr11mVHR9Z6hQ2BfOEF+/Gu0ynxQyRNdXyaCwL5xBJ0Pdryk1l+1m+9SGne0Rx8mv38+mhpweO0PFyo2VjTLbo4WTX79hKL2uUZxBJ4OC6D3hDFoZovdFdH1n0BO9L6LrO0OFwr5whvj6ShT2RXSG6PoqGRT2hTNoZPCh1Cx2s50hBjjIw5QpU2KCEhMklCkxTokJypQ5yMMMMdDQjeoMqUIhfSxw7R5YditQSN96cvLtK6c+L6RfX7sn/f5CoWERnEEog4p235fOUBG9L6LrO4Om6H0RXd8ZUgr7whni66uJ3hcKGaLrK2RQ2BfOoJEh40tatZdh9jLMXhawlNXczkKWcwk9vMoYL3OYfeyo68XenKE6iwfSj1MjcGgHjB2G18fgop70bShX3N78F4J0Bp0MCqL3hDNoZYjeF9H1nUFP9L6Iru8MFQr7whni6ytR2BfRGaLrq2RQ2BfOEJvBh1I1OMFRHuYuZwjOML8Prv90WHlnEMugIHpPOINWhuh9EV3fGfRE74vo+s5QobAvnCG+vhKFfRGdIbq+SgaFfeEMMRn863tmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlrpAkSZJnwbGxMXp7e6EAly3Js3LqleOQlKFQhEsX51/fGZxBLUN0fYDTx4AERkdH6enpiQlB/HwCjfsRnSG6vjM4w0wKM8rzyRlU6juDVgbPp5TCvXAGZ1Cpr5Kh2vkUdyhlZjaDzKGUmdk5SPxLn5nZOXg+mZmq2eZTZ45ZzuYnpZzBGSQyRNeHyim6DP+XvrbvSWdwhumkZpTnU9tniK7vDFoZPJ9SCvfCGZxBpb5KhmrnU9ih1KVXwG1H86/7taVw+ofpjYmo7wzOoJYhuj7AfUvSwakiaj6Bxv2IzhBd3xmcYSalGeX55AzR9Z1BK4PnU0rhXjiDM6jUV8lQ7XzyC52bmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlzodSZmZmZmZmZmaWOx9KmZmZmZmZmZlZ7sLefa8VnToCh3bC6DCMn4R53dDbDyvWw/xl+WRYQB+rWc8i+rmYbl7jJC8xzD52coKRtsgQXR/cC5MU1sFSCv3gDBoZFPZl9BqAxjpYSqEfnEEng8LejF4HhTWwiuh+iK7vDBUKe7Md18GHUlU4tgcObIMju6DwxrNlSQkKHennz9wJVw7Cqs2weKA5GfoZYA2bWMkgCWUAihQpv/H5IHdygIfYzTaG2TsnM0TXB/fCJIV1sJRCPziDRgaFfRm9BqCxDpZS6Adn0MmgsDej10FhDawiuh+i6ztDhcLebOd18K/vXUCSwHNDsOsmGHkESNKbkpTe+Prk5wkceQQeem96E5OksTnWsInN7OEabqFIkQ466aCTwrTPixRZya1s5nFuZmNjAwhkiK7vXkiprIOlovvBGTQyqOzL6Pugsg6Wiu4HZ9DJoLI3Padtuuh9EV3fGVIqe7Pd18GHUhdwcDs8cUf6eTJx4e+d/Pr+zel1jXIzG/kIQwB0MO+C3zv59XVsa2ijRmeIrg/uhUkK62AphX5wBo0MCvsyeg1AYx0spdAPzqCTQWFvRq+DwhpYRXQ/RNd3hgqFvel1qPNQ6vd+7/coFAr89m//dmPSCDm2J13oLPZvhuOP15+hnwHWsS3TtevYRj/vafkM0fXBvTBJYR1qMZfnk0I/OINGBoV9Gb0GoLEOtfB8Ore5si+doUJhb0avg8Ia1Moz6tzmyr/bOENKYW96HVKZD6Weeuop/uiP/ohVq1bVn0LQgW1QyPiKW4XO9Pp6rWETJcYzXVtivCGnp9EZouuDe2GSwjpUa67PJ4V+cAaNDAr7MnoNQGMdquX5dH5zZV86Q4XC3oxeB4U1qIVn1PnNlX+3cYaUwt70OqQyHUqdOnWK2267jS9/+cssWLCg/hRiTh1JX9xrtkfXzieZgBceglN1vDj+AvpYyeCsj/CdTwfzWMWHWMDSls0QXR/cC5MU1qFac30+KfSDM2hkUNiX0WsAGutQLc+nC5sL+9IZKhT2ZvQ6KKxBLTyjLmwu/LuNM6QU9qbXoSLTodSGDRv44Ac/yM0331xfdVGHdlZebT6rQhEO7ch+/WrWT73qflYJZVZze8tmiK4P7oVJCutQrbk+nxT6wRk0Mijsy+g1AI11qJbn0+xafV86Q4XC3oxeB4U1qIVn1Oxa/d9tnCGlsDe9DhU1P6j1zW9+k7/6q7/iqaeequr7z5w5w5kzZ6b+emxsrNaSuRsdbszPGTuc/dpF9DcgQcJClrdshuj64F6YpLAO1WiH+aTQD86gkUFhX0avAWisQzU8n6rV2vvSGSoU9mb0OiisQbVqmVGtOJ8gvh+i6ztDhcLe9DpU1HQuNjIywic/+Um+9rWvcfHFF1d1zdatW+nt7Z366OvryxQ0T+MnK29/mFVSgtfrmM8X002xzjdHLNLBJfS0bIbo+uBemKSwDrNpl/mk0A/OoJFBYV9GrwForMNsPJ+q1+r70hkqFPZm9DoorEE1ap1RrTifIL4fous7Q4XC3vQ6VNS0Cs888wwvvfQSP/MzP0NnZyednZ3s2bOH//Jf/gudnZ2USm/+J9qyZQujo6NTHyMjOf1SdB3mdUOho76fUeiAi7L3B69xknKdj/OVKfEq2TskOkN0fXAvTFJYh9m0y3xS6Adn0MigsC+j1wA01mE2nk/Va/V96QwVCnszeh0U1qAatc6oVpxPEN8P0fWdoUJhb3odKmr69b33v//9HDx48Ky/d/vtt3P11Vfzu7/7u3R0vPmfqKuri66urvpS5qy3EU/SAT3Zn6TjJRrxLF2Bl8n+LF10huj64F6YpLAOs2mX+aTQD86gkUFhX0avAWisw2w8n2rR2vvSGSoU9mb0OiisQTVqnVGtOJ8gvh+i6ztDhcLe9DpU1PSkVHd3N9dcc81ZH5dddhmXX34511xzTX1JhKxYD0l9h5YkZViR/TXH2MdOCnU+zlegyD6yv+pYdIbo+uBemKSwDrNpl/mk0A/OoJFBYV9GrwForMNsPJ+q1+r70hkqFPZm9DoorEE1PKOq1+r/buMMKYW96XWoqPO11uem+ctg2SAUan4Z+FShE65cC/Pr+PXqE4xwkF2UGM90fYlxDvAgJzjashmi64N7YZLCOlhKoR+cQSODwr6MXgPQWAdLKfSDM+hkUNib0eugsAZWEd0P0fWdoUJhb3odKuo+lPr+97/PF77whXp/jJxrN0Myke3apASrNtWf4TGG6GBepmuLdLCb7S2fIbo+uBcmKaxDrebqfFLoB2fQyKCwL6PXADTWoVaeT282V/alM1Qo7M3odVBYgyw8o95srvy7jTOkFPam1yHlJ6XOY/EA3DCU7dob7k6vr9cwe7mfbHf5O9zBMHtbPkN0fXAvTFJYB0sp9IMzaGRQ2JfRawAa62AphX5wBp0MCnszeh0U1sAqovshur4zVCjsTa9DyodSF7ByY+UGzfZI2+TXbxhKr2uU3WyfatTZHu2b/Pr9bGrIqalKhuj64F6YpLAOllLoB2fQyKCwL6PXADTWwVIK/eAMOhkU9mb0OiisgVVE90N0fWeoUNibXgcfSl1QoZA+jrZ2Dyy7FSikb3k4+baJU58X0q+v3ZN+f6HQ2By72c4QAxzkYcqUKTFBiQkSypQYp8QEZcoc5GGGGGhog6pkiK7vXkiprIOlovvBGTQyqOzL6Pugsg6Wiu4HZ9DJoLI3Padtuuh9EV3fGVIqe7Pd1yHjS1q1l8UD6cepETi0A8YOw+tjcFFP+vaHK25v/gsQDrOXYfaygKWs5nYWspxL6OFVxniZw+xjR10vctYKGaLrg3thksI6WEqhH5xBI4PCvoxeA9BYB0sp9IMz6GRQ2JvR66CwBlYR3Q/R9Z2hQmFvtvM6+FCqBvP74PpPx2Y4wVEe5q62zhBdH9wLkxTWwVIK/eAMGhkU9mX0GoDGOlhKoR+cQSeDwt6MXgeFNbCK6H6Iru8MFQp7sx3Xwb++Z2ZmZmZmZmZmufOhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe4KSZIkeRYcGxujt7cXCnDZkjwrp145DkkZCkW4dHH+9Z3BGdQyRNcHOH0MSGB0dJSenp6YEMTPJ9C4H9EZous7gzPMpDCjPJ+cQaW+M2hl8HxKKdwLZ3AGlfoqGaqdT3GHUmZmM8gcSpmZnYPEv/SZmZ2D55OZqZptPnXmmOVsflLKGZxBIkN0faicosvwf+lr+550BmeYTmpGeT61fYbo+s6glcHzKaVwL5zBGVTqq2Sodj6FHUpdegXcdjT/ul9bCqd/mN6YiPrO4AxqGaLrA9y3JB2cKqLmE2jcj+gM0fWdwRlmUppRnk/OEF3fGbQyeD6lFO6FMziDSn2VDNXOJ7/QuZmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrmLe/e9Gp06Aod2wugwjJ+Eed3Q2w8r1sP8Ze2TYQF9rGY9i+jnYrp5jZO8xDD72MkJRtoiQ3R9lQwK/aiQQYHCOihkUNgXzhBfHzT6USGDiui1iK4PGvvCGXQyRPdkdH0lCmsRnUFhTziDTobofozIIH8odWwPHNgGR3alb2cIkJSg0JF+/sydcOUgrNoMiwfmboZ+BljDJlYySEIZgCJFym98PsidHOAhdrONYfbOyQzR9VUyKPSjQgYFCuugkEFhXzhDfH3Q6EeFDCqi1yK6PmjsC2fQyRDdk9H1lSisRXQGhT3hDDoZovsxMoPsr+8lCTw3BLtugpFHgCRdkKT0xtcnP0/gyCPw0HvTBUySuZUBYA2b2MweruEWihTpoJMOOilM+7xIkZXcymYe52Y2NjaAQIbo+goZFPpRIYMChXVQyADx+8IZNOor9KNCBhXRaxFdf1L0vnAGnQzRPRldX4nCWihkiN4TzqCTQaEfozPIHkod3A5P3JF+nkxc+Hsnv75/c3rdXMpwMxv5CEMAdDDvgt87+fV1bGvoZonOEF1fJYNCPypkUKCwDgoZFPaFM8TXB41+VMigInotouuDxr5wBp0M0T0ZXV+JwlpEZ1DYE86gkyG6HxUySB5KHduT/kNmsX8zHH98bmToZ4B1bMt07Tq20c97Wj5DdH2VDAr9qJBBgcI6KGRQ2BfOEF8fNPpRIYOK6LWIrg8a+8IZdDJE92R0fSUKaxGdQWFPOINOhuh+VMlQ06HUnXfeSaFQOOvj6quvrj/FDAe2QSHjq10VOtPr50KGNWyixHima0uMN+QENzpDdH2VDAr9qJDhQjyf8s2gsC+cIb4+aPSjQobZtMuMiq4PGvvCGXQyRPdkdP1qtMt8UsigsCecQSdDdD+qZKj5Samf/umf5vjx41Mff/EXf1F/imlOHUlfWGu2x8bOJ5mAFx6CU3W8OL5ChgX0sZLBWR8jPJ8O5rGKD7GApS2bIbq+SgaFflTIUA3Pp3wyKOwLZ4ivDxr9qJChWnN9RkXXB4194Qw6GaJ7Mrp+Leb6fFLIoLAnnEEnQ3Q/qmSADIdSnZ2dXHHFFVMfb3vb2+pLMMOhnZVXes+qUIRDO1o7w2rWT73yf1YJZVZze8tmiK6vkkGhHxUyVMPzKZ8MCvvCGeLrg0Y/KmSo1lyfUdH1QWNfOINOhuiejK5fi7k+nxQyKOwJZ9DJEN2PKhkgw6HU8PAwS5Ys4e1vfzu33XYbR44cueD3nzlzhrGxsbM+LmR0uNZE5zZ2OPu1ChkW0d+ABAkLWd6yGaLrq2RQ6EeFDNXwfMong8K+cIb4+qDRjwoZqlXLjKp1PkH8WkTXB4194Qw6GaJ7Mrp+Leb6fFLIoLAnnEEnQ3Q/qmSAGg+l/r//7/9j586dPProo9xzzz384z/+I+95z3s4efLkea/ZunUrvb29Ux99fX0XrDF+svLWg1klJXh99tkoneFiuinW+Tr0RTq4hJ6WzRBdXyWDQj8qZJiN51N+GRT2hTPE1weNflTIUI1aZ1St8wni1yK6PmjsC2fQyRDdk9H1q9UO80khg8KecAadDNH9qJIBajyUuuWWW1i3bh2rVq3iF3/xF/mf//N/8qMf/Yhvf/vb571my5YtjI6OTn2MjFz4Fw7ndUOho5ZUb1bogIuy94dEhtc4SbnORwrLlHiV7B0SnSG6vkoGhX5UyDAbz6f8MijsC2eIrw8a/aiQoRq1zqha5xPEr0V0fdDYF86gkyG6J6PrV6sd5pNCBoU94Qw6GaL7USUDQMbXWU+95S1v4Z3vfCeHD5//ea2uri66urqq/pm9jXiSDujJ/iSdRIaXaMSzdAVeJvuzdNEZouurZFDoR4UMtfJ8al4GhX3hDPH1QaMfFTJkMduMqnU+QfxaRNcHjX3hDDoZonsyun5Wc3E+KWRQ2BPOoJMhuh9VMkCG15Sa7tSpU/z93/89ixcvri/FNCvWQ1LfoSVJGVZkf80xiQz72EmhzkcKCxTZR/ZXHYvOEF1fJYNCPypkqJXnU/MyKOwLZ4ivDxr9qJAhi7k4o6Lrg8a+cAadDNE9GV0/q7k4nxQyKOwJZ9DJEN2PKhmgxkOpzZs3s2fPHp5//nn27dvHL//yL9PR0cGv/uqv1pdimvnLYNkgFDI+w1XohCvXwvzZf7VZOsMJRjjILkqMZ7q+xDgHeJATHG3ZDNH1VTIo9KNChtl4PuWXQWFfOEN8fdDoR4UM1WiHGRVdHzT2hTPoZIjuyej61WqH+aSQQWFPOINOhuh+VMkANR5KHT16lF/91V9lxYoV/JN/8k+4/PLL2b9/PwsXLqwvxQzXboZkItu1SQlWbZobGR5jiA7mZbq2SAe72d7yGaLrq2RQ6EeFDBfi+ZRvBoV94Qzx9UGjHxUyzKZdZlR0fdDYF86gkyG6J6PrV6Nd5pNCBoU94Qw6GaL7USVDTYdS3/zmNzl27Bhnzpzh6NGjfPOb3+Qd73hH/SlmWDwANwxlu/aGu9Pr50KGYfZyP9nu8ne4g2H2tnyG6PoqGRT6USHDhXg+5ZtBYV84Q3x90OhHhQyzaZcZFV0fNPaFM+hkiO7J6PrVaJf5pJBBYU84g06G6H5UyVDfL1I20cqNlcWZ7XGyya/fMJReN5cy7Gb71GaZ7fHCya/fz6aGnNyqZIiur5JBoR8VMihQWAeFDAr7whni64NGPypkUBG9FtH1QWNfOINOhuiejK6vRGEtojMo7Aln0MkQ3Y8KGWQPpQqF9FGwtXtg2a1AIX27wcm3LJz6vJB+fe2e9PsLhbmVAdLNMsQAB3mYMmVKTFBigoQyJcYpMUGZMgd5mCEGGrpJVDJE11fIoNCPChkUKKyDQgaI3xfOoFFfoR8VMqiIXovo+pOi94Uz6GSI7sno+koU1kIhQ/SecAadDAr9GJ0h40ta5WfxQPpxagQO7YCxw/D6GFzUk7714Irbm//ifwoZhtnLMHtZwFJWczsLWc4l9PAqY7zMYfaxo64XWmuFDNH1VTIo9KNCBgUK66CQQWFfOEN8fdDoR4UMKqLXIro+aOwLZ9DJEN2T0fWVKKxFdAaFPeEMOhmi+zEyg/yh1KT5fXD9p53hBEd5mLvaOkN0fZUMCv2okEGBwjooZFDYF84QXx80+lEhg4rotYiuDxr7whl0MkT3ZHR9JQprEZ1BYU84g06G6H6MyCD763tmZmZmZmZmZjZ3+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsd4UkSZI8C46NjdHb2wsFuGxJnpVTrxyHpAyFIly6OP/6zuAMahmi6wOcPgYkMDo6Sk9PT0wI4ucTaNyP6AzR9Z3BGWZSmFGeT86gUt8ZtDJ4PqUU7oUzOINKfZUM1c6nuEMpM7MZZA6lzMzOQeJf+szMzsHzycxUzTafOnPMcjY/KeUMziCRIbo+VE7RZfi/9LV9TzqDM0wnNaM8n9o+Q3R9Z9DK4PmUUrgXzuAMKvVVMlQ7n8IOpS69Am47mn/dry2F0z9Mb0xEfWdwBrUM0fUB7luSDk4VUfMJNO5HdIbo+s7gDDMpzSjPJ2eIru8MWhk8n1IK98IZnEGlvkqGaueTX+jczMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMchf27nut6NQROLQTRodh/CTM64beflixHuYvyyfDAvpYzXoW0c/FdPMaJ3mJYfaxkxOM5JJBYR2iKayBe8GmU7gX7kkNCmvgXrDpFO6Fe1KHwjpEZ4iub2eLvh8K80khg4LoXmjXDD6UqsKxPXBgGxzZBYU3ni1LSlDoSD9/5k64chBWbYbFA83J0M8Aa9jESgZJKANQpEj5jc8HuZMDPMRutjHM3qZkUFiHaApr4F6w6RTuhXtSg8IauBdsOoV74Z7UobAO0Rmi69vZou+HwnxSyKAguhfaPYN/fe8CkgSeG4JdN8HII0CS3pSk9MbXJz9P4Mgj8NB705uYJI3NsYZNbGYP13ALRYp00EkHnRSmfV6kyEpuZTOPczMbG1pfZR0iqayBe8EmqdwL92Q8lTVwL9gklXvhntSgsA7RGaLr29kU7kf0fFLJEE2hF5zBh1IXdHA7PHFH+nkyceHvnfz6/s3pdY1yMxv5CEMAdDDvgt87+fV1bGvo0FBYh2gKa+BesOkU7oV7UoPCGrgXbDqFe+Ge1KGwDtEZouvb2aLvh8J8UsigILoXnCFV86HUD3/4Qz760Y9y+eWXc8kll7By5UqefvrpxqQRcmxPutBZ7N8Mxx+vP0M/A6xjW6Zr17GNft5TdwaFdYimsAbuhep4Ps3OPZnyfHIvTMqzF9phRincC/ekDoV1iM4QXb9a7TCfIP5+KMwnhQwKonvBGSpqOpQ6ceIEN954I/PmzeORRx7hb/7mb9i2bRsLFiyoP4mYA9ugkPEVtwqd6fX1WsMmSoxnurbEeENOshXWIZrCGrgXZuf5VB33ZMrzyb0wKa9eaJcZpXAv3JM6FNYhOkN0/Wq0y3yC+PuhMJ8UMiiI7gVnqKip/Oc//3n6+vrYsWPH1N+76qqr6k8h5tSR9MW9yPg7kskEvPAQnBqB+X3ZfsYC+ljJIMWMv2HZwTxW8SEWsJQTHM30MxTWIZrCGrgXquP5VB33ZMrzyb0wKa9eaIcZpXAv3JM6FNYhOkN0/Wq1w3yC+PuhMJ8UMiiI7gVnOFtN3fjggw/yrne9i3Xr1rFo0SKuu+46vvzlL2evLurQzsqrzWdVKMKhHbN/3/msZv3UOyBklVBmNbdnvl5hHaIprIF7oTqeT9VzT6Y8n9wLk/LohXaYUQr3wj2pQ2EdojNE169WO8wniL8fCvNJIYOC6F5whrPVFOEf/uEfuOeee+jv7+dP//RP+c3f/E3+zb/5N3z1q1897zVnzpxhbGzsrA91o8ON+Tljh7Nfu4j+BiRIWMjyzFcrrEM0hTVwL1TH86k27smU55N7YVKze6HWGeX5lI17UofCOkRniK5frXaYTxB/PxTmk0IGBdG94Axnq+nX98rlMu9617v43Oc+B8B1113HX//1X/Nf/+t/5WMf+9g5r9m6dSv/8T/+x/pS5mz8ZOXtD7NKSvB6HfP5YrozP1Y5qUgHl9CT+XqFdYimsAbuhep4PlXPPZnyfHIvTMqjF2qdUZ5P2bgndSisQ3SG6PrVaof5BPH3Q2E+KWRQEN0LznC2mjpy8eLF/NRP/dRZf+8nf/InOXLkyHmv2bJlC6Ojo1MfIyMj2ZLmaF43FDrq+xmFDriojr36Gicp1/loZZkSr5K9QxTWIZrCGrgXquP5VD33ZMrzyb0wKY9eqHVGeT5l457UobAO0Rmi61erHeYTxN8PhfmkkEFBdC84w9lqelLqxhtv5NChQ2f9vb/7u7/jyiuvPO81XV1ddHV1ZUsXpLcRTzUCPXU81fgSjXiWrsDLZH+WTmEdoimsgXuhOp5PtXFPpjyf3AuTmt0Ltc4oz6ds3JM6FNYhOkN0/Wq1w3yC+PuhMJ8UMiiI7gVnOFtNT0r9zu/8Dvv37+dzn/schw8f5utf/zr/7b/9NzZs2FBfCjEr1kNS3wEySRlW1PH6b/vYSaHORysLFNlH9lcdU1iHaApr4F6ojudT9dyTKc8n98KkPHqhHWaUwr1wT+pQWIfoDNH1q9UO8wni74fCfFLIoCC6F5zhbDV15Lvf/W4eeOABvvGNb3DNNddw11138YUvfIHbbrutvhRi5i+DZYNQqOk5sopCJ1y5tr63RTzBCAfZRYnxTNeXGOcAD9b1Vp0K6xBNYQ3cC9XxfKqOezLl+eRemJRXL7TDjFK4F+5JHQrrEJ0hun612mE+Qfz9UJhPChkURPeCM5yt5mPSwcFBDh48yGuvvcYPfvAD/tW/+lf1JRB17WZIJrJdm5Rg1ab6MzzGEB3My3RtkQ52s73uDArrEE1hDdwL1fF8mp17MuX55F6YlGcvtMOMUrgX7kkdCusQnSG6frXaYT5B/P1QmE8KGRRE94IzVNT37N4ctngAbhjKdu0Nd6fX12uYvdxPtrv8He5gmL11Z1BYh2gKa+BesOkU7oV7UoPCGrgXbDqFe+Ge1KGwDtEZouvb2aLvh8J8UsigILoXnKHCh1IXsHJj5QbN9kjb5NdvGEqva5TdbJ8aGrM9Zjn59fvZ1NATbIV1iKawBu4Fm07hXrgnNSisgXvBplO4F+5JHQrrEJ0hur6dLfp+KMwnhQwKonvBGVI+lLqAQiF9HG3tHlh2K1BI3/Jw8m0Tpz4vpF9fuyf9/kKhsTl2s50hBjjIw5QpU2KCEhMklCkxTokJypQ5yMMMMdDwYaGyDpFU1sC9YJNU7oV7Mp7KGrgXbJLKvXBPalBYh+gM0fXtbAr3I3o+qWSIptALzgAZX9KqvSweSD9OjcChHTB2GF4fg4t60rc/XHF781+AcJi9DLOXBSxlNbezkOVcQg+vMsbLHGYfO5r+gnMK6xBNYQ3cCzadwr1wT2pQWAP3gk2ncC/ckzoU1iE6Q3R9O1v0/VCYTwoZFET3Qrtn8KFUDeb3wfWfjs1wgqM8zF2hGRTWIZrCGrgXbDqFe+Ge1KCwBu4Fm07hXrgndSisQ3SG6Pp2tuj7oTCfFDIoiO6Fds3gX98zMzMzMzMzM7Pc+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsd4UkSZI8C46NjdHb2wsFuGxJnpVTrxyHpAyFIly6OP/6zuAMahmi6wOcPgYkMDo6Sk9PT0wI4ucTaNyP6AzR9Z3BGWZSmFGeT86gUt8ZtDJ4PqUU7oUzOINKfZUM1c6nuEMpM7MZZA6lzMzOQeJf+szMzsHzycxUzTafOnPMcjY/KeUMziCRIbo+VE7RZfi/9LV9TzqDM0wnNaM8n9o+Q3R9Z9DK4PmUUrgXzuAMKvVVMlQ7n8IOpS69Am47mn/dry2F0z9Mb0xEfWdwBrUM0fUB7luSDk4VUfMJNO5HdIbo+s7gDDMpzSjPJ2eIru8MWhk8n1IK98IZnEGlvkqGaueTX+jczMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3MW9+16NFtDHataziH4uppvXOMlLDLOPnZxgpG0yKDh1BA7thNFhGD8J87qhtx9WrIf5y+Z+fRUK66CQQYHCbFDIoEChJxUyRFNYA4UMKqLnQ3R9FQo96QwaGaLrK1GYDwoZoimsgcK+cIaYDPKHUv0MsIZNrGSQhDIARYqU3/h8kDs5wEPsZhvD7J2zGRQc2wMHtsGRXelbSwIkJSh0pJ8/cydcOQirNsPigblXX4XCOihkUKAwGxQyKFDoSYUM0RTWQCGDiuj5EF1fhUJPOoNGhuj6ShTmg0KGaAproLAvnCE2g/Sv761hE5vZwzXcQpEiHXTSQSeFaZ8XKbKSW9nM49zMxjmZIVqSwHNDsOsmGHkESNLmTEpvfH3y8wSOPAIPvTdt5iSZG/VVKKyDQgYVCrNBIUM0hZ5UyBBNYQ0UMiiJng/R9RUo9KQzaGSIrq9GYT4oZIgWvQYK+8IZNDLIHkrdzEY+whAAHcy74PdOfn0d2xq6WRQyKDi4HZ64I/08mbjw905+ff/m9Lq5UF+FwjooZFCgMBsUMihQ6EmFDNEU1kAhg4ro+RBdX4VCTzqDRobo+koU5oNChmgKa6CwL5xBI4PkoVQ/A6xjW6Zr17GNft4zJzIoOLYnbbgs9m+G44+3dn0VCuugkEGBwmxQyKBAoScVMkRTWAOFDCqi50N0fRUKPekMGhmi6ytRmA8KGaIprIHCvnAGnQw1HUr9xE/8BIVC4U0fGzZsqD/JNGvYRInxTNeWGG/ICa5CBgUHtkEh4yuPFTrT61u5vgqFdVDIMJs8ZpTCbFDIoEChJxUyRFNYA4UMs2mXP0NF11eh0JPOoJEhun412mU+qWSIprAGCvvCGXQy1HQo9dRTT3H8+PGpj8ceewyAdevW1Z/kDQvoYyWDsz5GeD4dzGMVH2IBS1s6g4JTR9IXOZvtEb7zSSbghYfgVMY3bIiur0JhHRQyVKPZM0phNihkUKDQkwoZoimsgUKGarTDn6Gi66tQ6Eln0MgQXb9a7TCfVDJEU1gDhX3hDDoZoMZDqYULF3LFFVdMfezatYt3vOMdvPe9760vxTSrWT/1yv9ZJZRZze0tnUHBoZ2VV93PqlCEQztas74KhXVQyFCNZs8ohdmgkEGBQk8qZIimsAYKGarRDn+Giq6vQqEnnUEjQ3T9arXDfFLJEE1hDRT2hTPoZADI+KAWvP7669x3331s3LiRQqFw3u87c+YMZ86cmfrrsbGxC/7cRfRnjTRNwkKWZ75aIYOC0eHG/Jyxw61ZX4XCOihkqFU1M8rzqXUp9KRChmgKa6CQoVbNmE8QPx+i66tQ6Eln0MgQXT+LuTqfVDJEU1gDhX3hDDoZoI4XOv+TP/kTfvSjH7F+/foLft/WrVvp7e2d+ujr67vg919MN8U6X3+9SAeX0JP5eoUMCsZPVt4GMqukBK/P/v9TkvVVKKyDQoZaVTOjPJ9al0JPKmSIprAGChlq1Yz5BPHzIbq+CoWedAaNDNH1s5ir80klQzSFNVDYF86gkwHqOJS69957ueWWW1iyZMkFv2/Lli2Mjo5OfYyMXPgXDl/jJOU6HyksU+JVsq+MQgYF87qh0FHfzyh0wEUZZ1Z0fRUK66CQoVbVzCjPp9al0JMKGaIprIFChlo1Yz5B/HyIrq9CoSedQSNDdP0s5up8UskQTWENFPaFM+hkgIy/vvfCCy+we/du/viP/3jW7+3q6qKrq6vqn/0SjXiGrMDLZH+GTCGDgt5GPN0J9GR8ujO6vgqFdVDIUItqZ5TnU+tS6EmFDNEU1kAhQy2aNZ8gfj5E11eh0JPOoJEhun6t5vJ8UskQTWENFPaFM+hkgIxPSu3YsYNFixbxwQ9+sL7q57CPnRTqfKSwQJF9ZH+1LYUMClash6S+g3SSMqzI+Dp40fVVKKyDQoZaNGtGKcwGhQwKFHpSIUM0hTVQyFCLufxnqOj6KhR60hk0MkTXr9Vcnk8qGaIprIHCvnAGnQyQ4VCqXC6zY8cOPvaxj9HZmfl10s/rBCMcZBclxjNdX2KcAzzICY62dAYF85fBskEoZLzNhU64ci3Mn/3XzCXrq1BYB4UM1WrmjFKYDQoZFCj0pEKGaAproJChWnP9z1DR9VUo9KQzaGSIrl+LuT6fVDJEU1gDhX3hDDoZIMOh1O7duzly5Ai//uu/Xl/lC3iMITqYl+naIh3sZvucyKDg2s2QTGS7NinBqk2tXV+FwjooZKhGs2eUwmxQyKBAoScVMkRTWAOFDNVohz9DRddXodCTzqCRIbp+tdphPqlkiKawBgr7whl0MtR8KPULv/ALJEnCO9/5zvqrn8cwe7mfbP903+EOhtk7JzIoWDwANwxlu/aGu9PrW7m+CoV1UMhQjWbPKIXZoJBBgUJPKmSIprAGChmq0Q5/hoqur0KhJ51BI0N0/Wq1w3xSyRBNYQ0U9oUz6GSo7xdKm2g326c2y2yPF05+/X42NfT0WiGDgpUbK40626N9k1+/YSi9bi7UV6GwDgoZFCjMBoUMChR6UiFDNIU1UMigIno+RNdXodCTzqCRIbq+EoX5oJAhmsIaKOwLZ9DIIHsoBelmGWKAgzxMmTIlJigxQUKZEuOUmKBMmYM8zBADTRkUChmiFQrpY3lr98CyW4FC+taPk28fOfV5If362j3p9xcKc6O+CoV1UMigQmE2KGSIptCTChmiKayBQgYl0fMhur4ChZ50Bo0M0fXVKMwHhQzRotdAYV84g0aGxr+KXYMNs5dh9rKApazmdhaynEvo4VXGeJnD7GNH019sTiGDgsUD6cepETi0A8YOw+tjcFFP+jaQK25v7gsxRtdXobAOChkUKMwGhQwKFHpSIUM0hTVQyKAiej5E11eh0JPOoJEhur4ShfmgkCGawhoo7AtniM0gfyg16QRHeZi72j6Dgvl9cP2n27e+CoV1UMigQGE2KGRQoNCTChmiKayBQgYV0fMhur4KhZ50Bo0M0fWVKMwHhQzRFNZAYV84Q0wG6V/fMzMzMzMzMzOzucmHUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrkrJEmS5FlwbGyM3t5eKMBlS/KsnHrlOCRlKBTh0sX513cGZ1DLEF0f4PQxIIHR0VF6enpiQhA/n0DjfkRniK7vDM4wk8KM8nxyBpX6zqCVwfMppXAvnMEZVOqrZKh2PsUdSpmZzSBzKGVmdg4S/9JnZnYOnk9mpmq2+dSZY5az+UkpZ3AGiQzR9aFyii7D/6Wv7XvSGZxhOqkZ5fnU9hmi6zuDVgbPp5TCvXAGZ1Cpr5Kh2vkUdih16RVw29H8635tKZz+YXpjIuo7gzOoZYiuD3DfknRwqoiaT6BxP6IzRNd3BmeYSWlGeT45Q3R9Z9DK4PmUUrgXzuAMKvVVMlQ7n/xC52ZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpa7sHffq9UC+ljNehbRz8V08xoneYlh9rGTE4xEx7M2c+oIHNoJo8MwfhLmdUNvP6xYD/OXRafLj9ch5flkSrwvU16HCs8oU+K96TWYzvNJg+9Dynszlfc6yB9K9TPAGjaxkkESygAUKVJ+4/NB7uQAD7GbbQyzNzKqtYFje+DANjiyCwpvPGeYlKDQkX7+zJ1w5SCs2gyLB8JiNp3XIeX5ZEq8L1NehwrPKFPivek1mM7zSYPvQ8p7MxW1DtK/vreGTWxmD9dwC0WKdNBJB50Upn1epMhKbmUzj3MzG6Mj2xyVJPDcEOy6CUYeAZJ0gyalN74++XkCRx6Bh96bbugkCQzdBF6HCs8nU+F9mfI6nM0zylR4b3oNZvJ80uD74L05KXodZA+lbmYjH2EIgA7mXfB7J7++jm1zcrNYvIPb4Yk70s+TiQt/7+TX929Or5tLvA4pzydT4n2Z8jpUeEaZEu9Nr8F0nk8afB9S3pup6HWo6VCqVCrx7//9v+eqq67ikksu4R3veAd33XUXSYOPCvsZYB3bMl27jm30856G5rH2dmxPuumy2L8Zjj/e2DxR1NfB88nakfq+zEsrrINnlLWjVtibzdYKa+D51F58H1KtsDfzoLAONR1Kff7zn+eee+7hi1/8Ij/4wQ/4/Oc/z+///u/zB3/wB/UnmWYNmygxnunaEuNz7gTXYh3YBoWMr75W6EyvnwvU18HzydqR+r7MSyusg2eUtaNW2JvN1gpr4PnUXnwfUq2wN/OgsA41ld+3bx8f/vCH+eAHPwjAT/zET/CNb3yDJ598sv4kb1hAHysZpJjxNws7mMcqPsQClnKCow3LZe3p1JH0hd7I+B+Kkgl44SE4NQLz+xoaLVetsA6eT9ZuWmFf5qFV1sEzytpNq+zNZmqVNfB8ah++D6lW2ZvNprIONXXj6tWr+e53v8vf/d3fAfDcc8/xF3/xF9xyyy3ZE8yswfqpV/7PKqHMam5vUCJrZ4d2Vt55IKtCEQ7taEicMK2wDp5P1m5aYV/moVXWwTPK2k2r7M1mapU18HxqH74PqVbZm82msg41PSn1qU99irGxMa6++mo6OjoolUp89rOf5bbbbjvvNWfOnOHMmTNTfz02NnbBGovoryXSeSQsZHkDfo61u9HhxvycscON+TlRWmEdPJ+s3bTCvsxDq6xDrTOq1vkEnlGmpVX2ZjO1yhp4PrUP34dUq+zNZlNZh5rOxb797W/zta99ja9//ev81V/9FV/96lcZGhriq1/96nmv2bp1K729vVMffX0Xfq7rYrozP044qUgHl9BT188wAxg/WXkrzKySErw++/9XS2uFdfB8snbTCvsyD62yDrXOqFrnE3hGmZZW2ZvN1Cpr4PnUPnwfUq2yN5tNZR1q6sg77riDT33qU/yzf/bPWLlyJf/8n/9zfud3foetW7ee95otW7YwOjo69TEyMnLBGq9xknKdjxSWKfEqLd4hJmFeNxQ66vsZhQ64qLXndkusg+eTtZtW2Jd5aJV1qHVG1TqfwDPKtLTK3mymVlkDz6f24fuQapW92Wwq61DTr++98sorFItnn2N1dHRQLp+/sbu6uujq6qq6xks04hmyAi/T4s/SmYTeRjzhCvS09hOuLbEOnk/WblphX+ahVdah1hlV63wCzyjT0ip7s5laZQ08n9qH70OqVfZms6msQ01PSq1du5bPfvazPPzwwzz//PM88MADbN++nV/+5V+uL8U0+9hJoc5HCgsU2UeLv+qYSVixHpL6/mMCSRlWtPZrAbbEOng+WbtphX2Zh1ZZB88oazetsjebqVXWwPOpffg+pFplbzabyjrU1JF/8Ad/wEc+8hE+/vGP85M/+ZNs3ryZf/2v/zV33XVXfSmmOcEIB9lFifFM15cY5wAPtvRbVJqO+ctg2SAUanqmsKLQCVeube23CoXWWAfPJ2s3rbAv89Aq6+AZZe2mVfZmM7XKGng+tQ/fh1Sr7M1mU1mHmg6luru7+cIXvsALL7zAq6++yt///d/zmc98hosuuqi+FDM8xhAdzMt0bZEOdrO9oXmsvV27GZKJbNcmJVi1qbF5oqivg+eTtSP1fZmXVlgHzyhrR62wN5utFdbA86m9+D6kWmFv5kFhHep7dq9JhtnL/WT7p/sOdzDM3gYnsna2eABuGMp27Q13p9fPBV6HlOeTKfG+THkdKjyjTIn3ptdgOs8nDb4PKe/NlMI6SB5KAexm+9Rmme3xwsmv38+mOXNya1pWbqxs1tkeb5z8+g1D6XVzidch5flkSrwvU16HCs8oU+K96TWYzvNJg+9DynszFb0OsodSkG6WIQY4yMOUKVNighITJJQpMU6JCcqUOcjDDDEw5zaJ6SgU0kcT1+6BZbcChfTtLyffQnPq80L69bV70u8vFCJTN57XocLzyVR4X6a8DmfzjDIV3pteg5k8nzT4PnhvTopeh4wvaZWfYfYyzF4WsJTV3M5ClnMJPbzKGC9zmH3saPkXWrPWsXgg/Tg1Aod2wNhheH0MLupJ3wpzxe2t/4J31fA6pDyfTIn3ZcrrUOEZZUq8N70G03k+afB9SHlvpqLWQf5QatIJjvIwjXsHCLN6zO+D6z8dnSKe1yHl+WRKvC9TXocKzyhT4r3pNZjO80mD70PKezOV9zpI//qemZmZmZmZmZnNTT6UMjMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy10hSZIkz4Kjo6O85S1vAeDSxXlWTr3yIpAABbj0ivzrO4MzqGWIrg/wyvH0f3/0ox/R29sbE4L4+QQi98M96QzOcHYGgRnl+eQMKvWdQSyD5xMgci+cwRlE6stkqHI+5X4odfToUfr62uD9FM2sZiMjIyxdujSsvueTmV1I5IzyfDKzC/F8MjNVs82n3A+lyuUyx44do7u7m0KhUPP1Y2Nj9PX1MTIyQk9PTxMSOkOrZIiu7wyNy5AkCSdPnmTJkiUUi3G/Vez55AxzKUN0/bmUQWFG1TufIP5+RNd3BmdQy+D5VBF9LxQyRNd3BmdodIZq51NnPSGzKBaLDTnF7+npCbs5zqCVIbq+MzQmQ+Sv7U3yfHKGuZghuv5cyRA9oxo1nyD+fkTXdwZnUMvg+VQRfS8UMkTXdwZnaGSGauaTX+jczMzMzMzMzMxy50MpMzMzMzMzMzPLXcsdSnV1dfEf/sN/oKuryxnaPEN0fWfQyqBAYR2cwRlU6juDnui1iK7vDM6gliG6vhKFtYjOEF3fGZwhKkPuL3RuZmZmZmZmZmbWck9KmZmZmZmZmZlZ6/OhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe5a6lDqL//yL+no6OCDH/xg7rXXr19PoVCY+rj88sv5wAc+wIEDB3LP8uKLL/KJT3yCt7/97XR1ddHX18fatWv57ne/2/Ta09dh3rx5/NiP/Rhr1qzhK1/5CuVyuen1Z2aY/vGBD3wgl/qz5Th8+HAu9V988UU++clPsnz5ci6++GJ+7Md+jBtvvJF77rmHV155pen1169fzy/90i+96e9///vfp1Ao8KMf/ajpGdR4Rnk+zcwRNaOi5xPEzijPpzfzfPJ8mpnD88l/hlLh+eT5NDOH51N7zaeWOpS69957+cQnPsHjjz/OsWPHcq//gQ98gOPHj3P8+HG++93v0tnZyeDgYK4Znn/+ea6//nr+/M//nLvvvpuDBw/y6KOP8r73vY8NGzbkkmFyHZ5//nkeeeQR3ve+9/HJT36SwcFBJiYmcs0w/eMb3/hGLrVny3HVVVc1ve4//MM/cN111/Fnf/ZnfO5zn+N//a//xV/+5V/yb//tv2XXrl3s3r276Rnszdp9Rnk+vTlH5IyKmk/gGaXI88nzaWYOzyfPJxWeT55PM3N4PrXXfOqMDlCtU6dO8a1vfYunn36aF198kZ07d/Lv/t2/yzVDV1cXV1xxBQBXXHEFn/rUp3jPe97Dyy+/zMKFC3PJ8PGPf5xCocCTTz7JZZddNvX3f/qnf5pf//VfzyXD9HX48R//cX7mZ36GG264gfe///3s3LmTf/kv/2WuGSJF5fj4xz9OZ2cnTz/99Fl98Pa3v50Pf/jDJEmSe6Z25xnl+XS+HFEiM3hGafF88nw6X44onk82yfPJ8+l8OaJ4PuWvZZ6U+va3v83VV1/NihUr+OhHP8pXvvKV0Jty6tQp7rvvPpYvX87ll1+eS83/9//+H48++igbNmw4q0knveUtb8klx7n8/M//PNdeey1//Md/HJahXfzf//t/+bM/+7Pz9gFAoVDIOZW1+4zyfLJJnlF6PJ88nyzl+aTH88nzyVLtPJ9a5lDq3nvv5aMf/SiQPlI3OjrKnj17cs2wa9cu5s+fz/z58+nu7ubBBx/kW9/6FsViPst4+PBhkiTh6quvzqVera6++mqef/75XGpNvxeTH5/73OdyqX2hHOvWrWt6zck+WLFixVl//21ve9tUjt/93d9teg4493245ZZbcqmtpt1nlOfT2RRmVMR8Ap0Z5flU4fnk+TSd51P8fALPqEmeT55P03k+ted8aolf3zt06BBPPvkkDzzwAACdnZ3803/6T7n33nu56aabcsvxvve9j3vuuQeAEydO8Id/+IfccsstPPnkk1x55ZVNr6/+uF6SJLmd3k6/F5Pe+ta35lL7QjnOd6qdhyeffJJyucxtt93GmTNncql5rvvwxBNPTP3hol14Rnk+zaQwo5TmE+Q/ozyfUp5Pnk8zeT69mf8MFcPzyfNpJs+nN2uH+dQSh1L33nsvExMTLFmyZOrvJUlCV1cXX/ziF+nt7c0lx2WXXcby5cun/vq///f/Tm9vL1/+8pf5zGc+0/T6/f39FAoF/vZv/7bptbL4wQ9+kNuLwM28F1EicixfvpxCocChQ4fO+vtvf/vbAbjkkktyy3Kuf/6jR4/mVl+FZ5Tn00wKMyoqg8qM8nxKeT55Ps3k+RQ/n8AzCjyfwPNpJs+n9pxP8r++NzExwf/4H/+Dbdu28eyzz059PPfccyxZsiTkHdcmFQoFisUir776ai713vrWt/KLv/iLfOlLX+L06dNv+nrk28f++Z//OQcPHuRXfuVXwjK0i8svv5w1a9bwxS9+8Zx9YPnyjEp5Ptkkzygdnk8pzyeb5Pmkw/Mp5flkk9p5Psk/KbVr1y5OnDjBv/gX/+JNp+W/8iu/wr333stv/MZv5JLlzJkzvPjii0D6aOcXv/hFTp06xdq1a3OpD/ClL32JG2+8kZ/92Z/lP/2n/8SqVauYmJjgscce45577uEHP/hB0zNMrkOpVOL//J//w6OPPsrWrVsZHBzk137t15pef3qG6To7O3nb296WS/1of/iHf8iNN97Iu971Lu68805WrVpFsVjkqaee4m//9m+5/vrroyO2Dc+oCs+nN+eYzjPKMypvnk8Vnk9vzjGd55PnU948nyo8n96cYzrPpzaYT4m4wcHB5NZbbz3n15544okESJ577rmm5/jYxz6WAFMf3d3dybvf/e7kO9/5TtNrz3Ts2LFkw4YNyZVXXplcdNFFyY//+I8nH/rQh5Lvfe97Ta89fR06OzuThQsXJjfffHPyla98JSmVSk2vPzPD9I8VK1bkUn96jg9/+MO51pzu2LFjyW/91m8lV111VTJv3rxk/vz5yc/+7M8md999d3L69Omm1z/fP//3vve9BEhOnDjR9AwKPKPO1u7zaWaOqBkVPZ+SJHZGeT6lPJ/O5vnk+TTJf4aK5/l0Ns8nz6dJ7TifCkki/upqZmZmZmZmZmY258i/ppSZmZmZmZmZmc09PpQyMzMzMzMzM7Pc+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHLnQykzMzMzMzMzM8udD6XMzMzMzMzMzCx3PpQyMzMzMzMzM7Pc+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLXWfeBcvlMseOHaO7u5tCoZB3eTMTlCQJJ0+eZMmSJRSLcWflnk9mdi4KM8rzyczOxfPJzFRVO59yP5Q6duwYfX19eZc1sxYwMjLC0qVLw+p7PpnZhUTOKM8nM7sQzyczUzXbfMr9UKq7u3vq80sX510dXnkRSIACXHpF/vWdwRnUMkTXB3jlePq/0+dDhOj5BCL3wz3pDM5wdgaBGeX55Awq9Z1BLIPnEyByL5zBGUTqy2Socj7lfig1+UjnpYvho8fyrg5fWwqnfwiXLYHbjuZf3xmcQS1DdH2A+5akQyv6ke/o+QQa9yM6Q3R9Z3CGmRRmlOeTM6jUdwatDJ5PKYV74QzOoFJfJUO188kvdG5mZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnucn+h81a2gD5Ws55F9HMx3bzGSV5imH3s5AQj0fFyE70O0fVVMpw6Aod2wugwjJ+Eed3Q2w8r1sP8ZblEkMhgKYWeVKCwDtEZouuDxmxQyGAp96QzOINWfTtb9IxS6AdncIbIDD6UqkI/A6xhEysZJKEMQJEi5Tc+H+RODvAQu9nGMHsjozZV9DpE11fJcGwPHNgGR3ZB4Y1nHZMSFDrSz5+5E64chFWbYfFAUyJIZLCUQk8qUFiH6AzR9UFjNihksJR70hmcQau+nS16Rin0gzM4g0IG//reLNawic3s4RpuoUiRDjrpoJPCtM+LFFnJrWzmcW5mY3Tkpoheh+j6ChmSBJ4bgl03wcgjQJIOiaT0xtcnP0/gyCPw0HvToZIkcyuDVUT3pAqFdYjOEF1fYTYoZLAK96QzOINOfXuzyBml0A/O4AxKGXwodQE3s5GPMARAB/Mu+L2TX1/Htjn3L37R6xBdXyXDwe3wxB3p58nEhb938uv7N6fXzaUMllLoSQUK6xCdIbo+aMwGhQyWck86gzNo1bezRc8ohX5wBmdQyuBDqfPoZ4B1bMt07Tq20c97GpwoRvQ6RNdXyXBsT7rxs9i/GY4/XncEiQyWUuhJBQrrEJ0huj5ozAaFDJZyTzqDM2jVt7NFzyiFfnAGZ1DLUPOh1OOPP87atWtZsmQJhUKBP/mTP6k/haA1bKLEeKZrS4zPmacRotchur5KhgPboJDxFeAKnen1cyHDbDyfZuf5lJor8yG6PmjMBoUMs/F8mp170hnmYobo+tVol/kE8TNKoR+cwRnUMtR8KHX69GmuvfZavvSlL9VfXdQC+ljJ4KyPc55PB/NYxYdYwNIGJ8tX9DpE11fJcOpI+mJzsz1KeT7JBLzwEJyq481DFDJUw/Npdp5PqbkwH6Lrg8ZsUMhQDc+n2bknnWGuZYiuX612mE8QP6MU+sEZnEEtA2Q4lLrlllv4zGc+wy//8i/XV1nYatZPvQNDVgllVnN7gxLFiF6H6PoqGQ7trLz7QVaFIhzakf16hQzV8HyqjudTqtXnQ3R90JgNChmq4flUHfekM8ylDNH1q9UO8wniZ5RCPziDM6hlAMj4oFb1zpw5w5kzZ6b+emxsrNkl67aI/gb8lISFLG/Az4kTvQ7R9VUyjA43IAIwdjj7tQoZmsHzqXUprEN0huj6oDEbFDI0g+dTNgr94AzOoFK/WVpxPkH8jFLoB2dwBrUMkMMLnW/dupXe3t6pj76+vmaXrNvFdFOsc2mKdHAJPQ1KFCN6HaLrq2QYP1l5O86skhK8XsefFxQyNIPnU+tSWIfoDNH1QWM2KGRoBs+nbBT6wRmcQaV+s7TifIL4GaXQD87gDGoZIIdDqS1btjA6Ojr1MTLS5F+KboDXOEm5zkc7y5R4FbH/B6lR9DpE11fJMK8bCh11RaDQARfVcQahkKEZPJ9al8I6RGeIrg8as0EhQzN4PmWj0A/O4Awq9ZulFecTxM8ohX5wBmdQywA5/PpeV1cXXV1dzS7TUC/RiOfYCryM2LO2NYpeh+j6Khl6G/GkMdBTx29rKWRoBs+n1qWwDtEZouuDxmxQyNAMnk/ZKPSDMziDSv1macX5BPEzSqEfnMEZ1DJADk9KtaJ97KRQ59IUKLKPJr8qYZNFr0N0fZUMK9ZDUt9/1CEpw4o6XtdaIYOlFHpSgcI6RGeIrg8as0Ehg6Xck87gDFr17WzRM0qhH5zBGdQyQIZDqVOnTvHss8/y7LPPAvCP//iPPPvssxw5cqS+JEJOMMJBdlFiPNP1JcY5wIOc4GiDk+Ureh2i66tkmL8Mlg1CIeNzjYVOuHItzK/j1/0VMlTD82l2nk+puTAfouuDxmxQyFANz6fZuSedYa5liK5frXaYTxA/oxT6wRmcQS0DZDiUevrpp7nuuuu47rrrANi4cSPXXXcdn/70p+tLIuYxhuhgXqZri3Swm+0NThQjeh2i66tkuHYzJBPZrk1KsGpT3REkMszG82l2nk+puTIfouuDxmxQyDAbz6fZuSedYS5miK5fjXaZTxA/oxT6wRmcQS1DzYdSN910E0mSvOlj586d9acRMsxe7ifbCn+HOxhmb4MTxYheh+j6KhkWD8ANQ9muveHu9Pq5kGE2nk+z83xKzZX5EF0fNGaDQobZeD7Nzj3pDHMxQ3T9arTLfIL4GaXQD87gDGoZ/JpSF7Cb7VNDa7bHPCe/fj+b5sxTCJOi1yG6vkqGlRsrA2O2Rywnv37DUHrdXMpgKYWeVKCwDtEZouuDxmxQyGAp96QzOINWfTtb9IxS6AdncAalDD6UmsVutjPEAAd5mDJlSkxQYoKEMiXGKTFBmTIHeZghBubcv/BNil6H6PoKGQqF9PHItXtg2a1AIX0Lzsm38Zz6vJB+fe2e9PsLhbmVwSqie1KFwjpEZ4iurzAbFDJYhXvSGZxBp769WeSMUugHZ3AGpQwZX9KqvQyzl2H2soClrOZ2FrKcS+jhVcZ4mcPsY0fLv2hwNaLXIbq+SobFA+nHqRE4tAPGDsPrY3BRT/p2nCtub/4LYipksJRCTypQWIfoDNH1QWM2KGSwlHvSGZxBq76dLXpGKfSDMziDQgYfStXgBEd5mLuiY4SLXofo+ioZ5vfB9cGvP6mQwVIKPalAYR2iM0TXB43ZoJDBUu5JZ3AGrfp2tugZpdAPzuAMkRn863tmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlrpAkSZJnwbGxMXp7e6EAly3Js3LqleOQlKFQhEsX51/fGZxBLUN0fYDTx4AERkdH6enpiQlB/HwCjfsRnSG6vjM4w0wKM8rzyRlU6juDVgbPp5TCvXAGZ1Cpr5Kh2vkUdyhlZjaDzKGUmdk5SPxLn5nZOXg+mZmq2eZTZ45ZzuYnpZzBGSQyRNeHyim6DP+XvrbvSWdwhumkZpTnU9tniK7vDFoZPJ9SCvfCGZxBpb5KhmrnU9ih1KVXwG1H86/7taVw+ofpjYmo7wzOoJYhuj7AfUvSwakiaj6Bxv2IzhBd3xmcYSalGeX55AzR9Z1BK4PnU0rhXjiDM6jUV8lQ7XzyC52bmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlzodSZmZmZmZmZmaWOx9KmZmZmZmZmZlZ7sLefc+yWUAfq1nPIvq5mG5e4yQvMcw+dnKCkbbIEF0f4NQROLQTRodh/CTM64beflixHuYvyyWCM5gchb3pDBr70hlMTfS+BI2e9DpoZIiub1q8L1Neh/bN4EOpFtHPAGvYxEoGSSgDUKRI+Y3PB7mTAzzEbrYxzN45mSG6PsCxPXBgGxzZBYU3njNMSlDoSD9/5k64chBWbYbFA02J4AwmR2FvOoPGvnQGUxO9L0GjJ70OGhmi65sW78uU18EZ/Ot7LWANm9jMHq7hFooU6aCTDjopTPu8SJGV3MpmHudmNs65DNH1kwSeG4JdN8HII0CSbtCk9MbXJz9P4Mgj8NB70w2dJM7Q6AymJXpvOoPGvnQGUxQ9G1R60usQnyG6vunxvkx5HZwBfCgl72Y28hGGAOhg3gW/d/Lr69jW0A0bnSG6PsDB7fDEHennycSFv3fy6/s3p9c5Q2MzmA6FvekMGvvSGUxN9L4EjZ70OmhkiK5vWrwvU14HZ5hU06HU1q1befe73013dzeLFi3il37plzh06FBjktib9DPAOrZlunYd2+jnPS2fIbo+pI8x7t+c7dr9m+H443VHcIYqeD7lS2FvOoPGvnSG6nhG5Sd6X4JGT3odNDJE16+G51N+vC9TXgdnmK6mQ6k9e/awYcMG9u/fz2OPPcb4+Di/8Au/wOnTp+tPYm+yhk2UGM90bYnxhpwiR2eIrg/po4mFjK++VuhMr3eGxmS4EM+nfCnsTWfQ2JfOUB3PqPxE70vQ6Emvg0aG6PrV8HzKj/dlyuvgDNPVVP7RRx8966937tzJokWLeOaZZxgY8KvxNdIC+ljJIMWMv2HZwTxW8SEWsJQTHG3JDNH1IX3ngSO7gIy/L5tMwAsPwakRmN+X7Wc4Q3U8n/KjsDedQWNfOkP1PKPyEb0vQaMnvQ4aGaLrV8vzKR/elymvgzPMVNdrSo2OjgLw1re+tZ4fY+ewmvVT7z6QVUKZ1dzeshmi60P6VpiFunZJev2hHdmvd4ZsPJ+aR2FvOoPGvnSG7DyjmiN6X4JGT3odNDJE18/K86k5vC9TXgdnmCnjg1pQLpf57d/+bW688Uauueaa837fmTNnOHPmzNRfj42NZS3ZVhbR34CfkrCQ5S2bIbo+wOhwAyIAY4ezX+sMtfN8ai6FvekMGvvSGbKpZkZ5PmUTvS9Boye9DhoZoutn4fnUPN6XKa+DM8yU+Vxsw4YN/PVf/zXf/OY3L/h9W7dupbe3d+qjr6+Jz57OIRfTnfmRxklFOriEnpbNEF0fYPxk5a0ws0pK8Hod/1/tDLXzfGouhb3pDBr70hmyqWZGeT5lE70vQaMnvQ4aGaLrZ+H51DzelymvgzPMlKkbfuu3fotdu3bxve99j6VLl17we7ds2cLo6OjUx8jISKag7eY1TlKu87HGMiVeJXuHRGeIrg8wrxsKHXVFoNABF2Wfmc5QI8+n5lPYm86gsS+doXbVzijPp2yi9yVo9KTXQSNDdP1aeT41l/dlyuvgDDPV9Ot7SZLwiU98ggceeIDvf//7XHXVVbNe09XVRVdXV+aA7eolGvEsXYGXyf4sXXSG6PoAvY14uhToyf50qTNUyfMpPwp70xk09qUzVK/WGeX5lE30vgSNnvQ6aGSIrl8tz6d8eF+mvA7OMFNNT0pt2LCB++67j69//et0d3fz4osv8uKLL/Lqq6/Wl8LeZB87KdT5WGOBIvvI/qpj0Rmi6wOsWA9JfQf5JGVYkf11+JyhSp5P+VHYm86gsS+doXqeUfmI3peg0ZNeB40M0fWr5fmUD+/LlNfBGWaqqRvuueceRkdHuemmm1i8ePHUx7e+9a36UtibnGCEg+yixHim60uMc4AHM79NpkKG6PoA85fBskEoZHxLgEInXLm2vrfIdIbqeD7lR2FvOoPGvnSG6nlG5SN6X4JGT3odNDJE16+W51M+vC9TXgdnmKmmQ6kkSc75sX79+vpS2Dk9xhAdzMt0bZEOdrO95TNE1we4djMkE9muTUqwalPdEZyhmhqeT7lS2JvOoLEvnaHKOp5RuYnel6DRk14HjQzR9auq4/mUG+/LlNfBGaar77k5a6ph9nI/2e7yd7iDYfa2fIbo+gCLB+CGoWzX3nB3er0zNCaD6VDYm86gsS+dwdRE70vQ6Emvg0aG6Pqmxfsy5XVwhul8KCVuN9unNuxsjzhOfv1+NjXk9FglQ3R9gJUbK5t1tscbJ79+w1B6nTM0NoPpUNibzqCxL53B1ETvS9DoSa+DRobo+qbF+zLldXCGST6UagG72c4QAxzkYcqUKTFBiQkSypQYp8QEZcoc5GGGGGjoRlXJEF2/UEgfTVy7B5bdChTSt7+cfAvNqc8L6dfX7km/v1BwhkZnMC3Re9MZNPalM5ii6Nmg0pNeh/gM0fVNj/dlyuvgDAAZX9LK8jbMXobZywKWsprbWchyLqGHVxnjZQ6zjx11vdhbK2SIrg/p44mLB+DUCBzaAWOH4fUxuKgnfSvMFbc3/8UoncHUKOxNZ9DYl85gaqL3JWj0pNdBI0N0fdPifZnyOjiDD6VazAmO8jB3tXWG6PqQbsbrPx0awRlMjsLedAaNfekMpiZ6X4JGT3odNDJE1zct3pcpr0P7ZvCv75mZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpa7QpIkSZ4Fx8bG6O3thQJctiTPyqlXjkNShkIRLl2cf31ncAa1DNH1AU4fAxIYHR2lp6cnJgTx8wk07kd0huj6zuAMMynMKM8nZ1Cp7wxaGTyfUgr3whmcQaW+SoZq51PcoZSZ2Qwyh1JmZucg8S99Zmbn4PlkZqpmm0+dOWY5m5+UcgZnkMgQXR8qp+gy/F/62r4nncEZppOaUZ5PbZ8hur4zaGXwfEop3AtncAaV+ioZqp1PYYdSl14Btx3Nv+7XlsLpH6Y3JqK+MziDWobo+gD3LUkHp4qo+QQa9yM6Q3R9Z3CGmZRmlOeTM0TXdwatDJ5PKYV74QzOoFJfJUO188kvdG5mZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnu4t59r0YL6GM161lEPxfTzWuc5CWG2cdOTjDiDG2U4dQROLQTRodh/CTM64beflixHuYva3p5ZxDLoCB6TziDVobofRFd3xn0RO+L6PrOUKGwL5whvr4ShX0RnSG6vkoGhX3hDDEZ5A+l+hlgDZtYySAJZQCKFCm/8fkgd3KAh9jNNobZ6wxzOMOxPXBgGxzZlb61JUBSgkJH+vkzd8KVg7BqMyweaHh5ZxDLoCB6TziDVobofRFd3xn0RO+L6PrOUKGwL5whvr4ShX0RnSG6vkoGhX3hDLEZpH99bw2b2MweruEWihTpoJMOOilM+7xIkZXcymYe52Y2OsMczJAk8NwQ7LoJRh4BknRzJKU3vj75eQJHHoGH3ptupiRpWARnEMqgot33pTNURO+L6PrOoCl6X0TXd4aUwr5whvj6aqL3hUKG6PoKGRT2hTNoZJA9lLqZjXyEIQA6mHfB7538+jq2NXSzOINGhoPb4Yk70s+TiQt/7+TX929Or2sUZ9DJoCB6TziDVobofRFd3xn0RO+L6PrOUKGwL5whvr4ShX0RnSG6vkoGhX3hDBoZJA+l+hlgHdsyXbuObfTzHmeYIxmO7UkbPov9m+H443WVdwaxDAqi94QzaGWI3hfR9Z1BT/S+iK7vDBUK+8IZ4usrUdgX0Rmi66tkUNgXzqCToaZDqXvuuYdVq1bR09NDT08PP/dzP8cjjzxSf4oZ1rCJEuOZri0x3pATXGfQyHBgGxQyvvJZoTO9vl7OoJPhQjyfnCEiQ/S+iK7vDNVrlxkVXd8ZKhT2hTPE169Gu8wnhQzR9VUyKOwLZ9DJUNOh1NKlS/m93/s9nnnmGZ5++ml+/ud/ng9/+MP87//9v+tP8oYF9LGSwVkfIzyfDuaxig+xgKXO0OIZTh1JX2RttkcIzyeZgBceglN1vGGEM+hkmI3nkzPknSF6X0TXd4batMOMiq7vDBUK+8IZ4utXqx3mk0KG6PoqGRT2hTPoZIAaD6XWrl3LrbfeSn9/P+985zv57Gc/y/z589m/f399KaZZzfqpV/7PKqHMam53hhbPcGhn5VX/syoU4dCO7Nc7g06G2Xg+OUPeGaL3RXR9Z6hNO8yo6PrOUKGwL5whvn612mE+KWSIrq+SQWFfOINOBoCMD2pBqVTi/vvv5/Tp0/zcz/3ceb/vzJkznDlzZuqvx8bGLvhzF9GfNdI0CQtZnvlqZ9DIMDrcgPLA2OHs1zqDToZaeD45Qx4ZovdFdH1nyK6aGVXrfIL4fRFd3xkqFPaFM8TXz2KuzieFDNH1VTIo7Atn0MkAGV7o/ODBg8yfP5+uri5+4zd+gwceeICf+qmfOu/3b926ld7e3qmPvr6+C/78i+mmWOfrrxfp4BJ6Ml/vDBoZxk9W3oYyq6QEr8/+/5PO0AIZquH55Ax5ZojeF9H1naF2tcyoWucTxO+L6PrOUKGwL5whvn4t5vp8UsgQXV8lg8K+cAadDJDhUGrFihU8++yzPPHEE/zmb/4mH/vYx/ibv/mb837/li1bGB0dnfoYGbnwLxy+xknKdT5SWKbEq2RfGWfQyDCvGwoddZWn0AEXZZ+ZziCUoRqeT86QZ4bofRFd3xlqV8uMqnU+Qfy+iK7vDBUK+8IZ4uvXYq7PJ4UM0fVVMijsC2fQyQAZfn3voosuYvny9HG966+/nqeeeor//J//M3/0R390zu/v6uqiq6ur6p//Eo14hqzAy2R/hswZNDL0NuLpUqAn+9OlziCUoRqeT86QZ4bofRFd3xlqV8uMqnU+Qfy+iK7vDBUK+8IZ4uvXYq7PJ4UM0fVVMijsC2fQyQAZnpSaqVwun/U7xfXax04KdcYqUGQf2V9tyxk0MqxYD0l9B/kkZViR/XX4nEEoQxaeT87QzAzR+yK6vjPUb67NqOj6zlChsC+cIb5+PebafFLIEF1fJYPCvnAGnQxQ46HUli1bePzxx3n++ec5ePAgW7Zs4fvf/z633XZbfSmmOcEIB9lFifFM15cY5wAPcoKjztDiGeYvg2WDUMj4cvyFTrhyLcyf/dfcnaEFMszG88kZ8s4QvS+i6ztDbdphRkXXd4YKhX3hDPH1q9UO80khQ3R9lQwK+8IZdDJAjYdSL730Er/2a7/GihUreP/7389TTz3Fn/7pn7JmzZr6UszwGEN0MC/TtUU62M12Z5gjGa7dDMlEtmuTEqzaVFd5ZxDLcCGeT84QkSF6X0TXd4bqtcuMiq7vDBUK+8IZ4utXo13mk0KG6PoqGRT2hTPoZKjpUOree+/l+eef58yZM7z00kvs3r274cMKYJi93E+2f7rvcAfD7HWGOZJh8QDcMJTt2hvuTq+vlzPoZLgQzydniMgQvS+i6ztD9dplRkXXd4YKhX3hDPH1q9Eu80khQ3R9lQwK+8IZdDLU/ZpSzbKb7VObZbbHCye/fj+bGnJy6wxaGVZurGyU2R4tnPz6DUPpdY3iDDoZFETvCWfQyhC9L6LrO4Oe6H0RXd8ZKhT2hTPE11eisC+iM0TXV8mgsC+cQSOD7KEUpJtliAEO8jBlypSYoMQECWVKjFNigjJlDvIwQww0dJM4g06GQiF9LHDtHlh2K1BI33py8u0rpz4vpF9fuyf9/kKhYRGcQSiDinbfl85QEb0vous7g6bofRFd3xlSCvvCGeLrq4neFwoZousrZFDYF86gkSHjS1rlZ5i9DLOXBSxlNbezkOVcQg+vMsbLHGYfO+p6oTVnaJ0MiwfSj1MjcGgHjB2G18fgop70bShX3N78F4J0Bp0MCqL3hDNoZYjeF9H1nUFP9L6Iru8MFQr7whni6ytR2BfRGaLrq2RQ2BfOEJtB/lBq0gmO8jB3OYMzML8Prv90WHlnEMugIHpPOINWhuh9EV3fGfRE74vo+s5QobAvnCG+vhKFfRGdIbq+SgaFfeEMMRmkf33PzMzMzMzMzMzmJh9KmZmZmZmZmZlZ7nwoZWZmZmZmZmZmufOhlJmZmZmZmZmZ5a6QJEmSZ8GxsTF6e3uhAJctybNy6pXjkJShUIRLF+df3xmcQS1DdH2A08eABEZHR+np6YkJQfx8Ao37EZ0hur4zOMNMCjPK88kZVOo7g1YGz6eUwr1wBmdQqa+Sodr5FHcoZWY2g8yhlJnZOUj8S5+Z2Tl4PpmZqtnmU2eOWc7mJ6WcwRkkMkTXh8opugz/l76270lncIbppGaU51PbZ4iu7wxaGTyfUgr3whmcQaW+SoZq51PYodSlV8BtR/Ov+7WlcPqH6Y2JqO8MzqCWIbo+wH1L0sGpImo+gcb9iM4QXd8ZnGEmpRnl+eQM0fWdQSuD51NK4V44gzOo1FfJUO188gudm5mZmZmZmZlZ7nwoZWZmZmZmZmZmufOhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe7C3n2vFS2gj9WsZxH9XEw3r3GSlxhmHzs5wYgz5JQhuj7AqSNwaCeMDsP4SZjXDb39sGI9zF+WSwSvg51FoR+cQSODwr6MXgPQWAdLKfSDM+hkUNib0eugsAZWEd0P0fWdoUJhb7bjOvhQqgr9DLCGTaxkkIQyAEWKlN/4fJA7OcBD7P7/2bv/4Lrq+87/z3slI35YUhxiil3LlMSKaYvNUJIuawaFNDiNiZw0U7y7HbKN6e7OtqHZtLbYhp3ZLLskcbNInuw2KdvNEjs7kCYh03TALLQ4TYw7Lj+7YPfb1JXbguXYLMyuI9kGjHTv+f5xuLqysKV7z70675d0X48ZTRWk6/cr7/fnvGtOjq4YYpi9zjBHGaLrAxzdA/uH4PAuKLz5nGFSgkJb+vmzd8Jl/bB2AJb1zUkE98HOoHAenEEjg8J1Gd0D0OiDpRTOgzPoZFC4NqP7oNADq4o+D9H1naFK4dps5T74x/dmsZ6tDLCHK9lAkSJttNNGO4UpnxcpsoabGOBxbmSLM8xBhuj6SQLPD8KuG2DkESBJL9Ck9ObXK58ncPgReOh96QWdJE2N4T7YGaLPgzNoZFC5LqPnoNIHS0WfB2fQyaBybXpP21TR10V0fWdIqVybrd4H35SawY1s4WYGAWhj0YzfW/n6JoaaekicIb4+wIHt8OTt6efJxMzfW/n6EwPp65rFfbCpFM6DM2hkULguo3sAGn2wlMJ5cAadDArXZnQfFHpgVdHnIbq+M1QpXJvuQ4M3pX73d3+XQqHAb/3WbzUnjZBe+tjEUKbXbmKIXq53hiZkiK4P6WOMTwxke+0TA3Ds8YYjuA8ZeD+d3ULZDc6QUrguo3sAGn2oh/fT2S2U69IZqhSuzeg+KPSgXt5RZ7dQ/t3GGVIK16b7kMp8U+rpp5/mD/7gD1i7dm3jKQStZyslxjO9tsR4U+5cOkN8fUgfTSxkfPe1Qnv6+ka5D/Xxfjq3hbIbnCGlcF1G9wA0+lAr76dzWyjXpTNUKVyb0X1Q6EE9vKPObaH8u40zpBSuTfchlemm1MmTJ7nlllv46le/ypIlSxpPIWYJPayhf9bH586ljUWs5SMsYYUzNJAhuj6kv3ng8K7ZH2M8l2QCXnwITjbwixLch/p4P81sIewGZ0gpXJfRPQCNPtTK+2lmC+G6dIYqhWszug8KPaiHd9TMFsK/2zhDSuHadB+qMt2Uuu222/jwhz/MjTfe2Fh1UevYPPmO91kllFnHrc7QQIbo+pD+KsxC5ucJU4UiHNyR/fXuQ328n2Y333eDM6QUrsvoHoBGH2rl/TS7+X5dOkOVwrUZ3QeFHtTDO2p28/3fbZwhpXBtug9VdT+o9c1vfpO//Mu/5Omnn67p+0+fPs3p06cn//PY2Fi9JXN3Cb1N+FMSlrLKGRrIEF0fYHS4CRGAsUPZX+s+1M77qVbzezc4Q0rhuozuAWj0oRbeT7Wa39elM1QpXJvRfVDoQa3q2VHzcT9B/HmIru8MVQrXpvtQVdd9sZGRET796U9z//33c/7559f0mm3bttHd3T350dPTkylons6nk2KDv5iwSBsX0OUMDWSIrg8wfqL6qzCzSkrwRgP/v9p9qI33U+3m+25whpTCdRndA9Dow2y8n2o3369LZ6hSuDaj+6DQg1rUu6Pm436C+PMQXd8ZqhSuTfehqq4uPPvss7z88sv83M/9HO3t7bS3t7Nnzx7+63/9r7S3t1MqvfW/0R133MHo6Ojkx8hITj8U3YDXOUG5wUfpypR4jezTcYb4+gCLOqHQ1lAECm1wXvZd4T7UyPupdvN9NzhDSuG6jO4BaPRhNt5PtZvv16UzVClcm9F9UOhBLerdUfNxP0H8eYiu7wxVCtem+1BV14/vfeADH+DAgQNn/LNbb72VK664gt/5nd+hre2t/406Ojro6OhoLGXOXqYZz7EVeIXsz7E5Q3x9gO5mPFUJdGV/qtJ9qJH3Uz3m925whpTCdRndA9Dow2y8n+oxv69LZ6hSuDaj+6DQg1rUu6Pm436C+PMQXd8ZqhSuTfehqq4npTo7O7nyyivP+Ljooou4+OKLufLKKxtLImQfOyk0+ChdgSL7yP6OX84QXx9g9WZIGruBTVKG1dnff859qJH3U+3m+25whpTCdRndA9Dow2y8n2o3369LZ6hSuDaj+6DQg1p4R9Vuvv+7jTOkFK5N96GqwfdaX5iOM8IBdlFiPNPrS4yznwc5zhFnaCBDdH2AxSthZT8U6v6VAKlCO1y2ERY38KP27oNNpXAenEEjg8J1Gd0D0OiDpRTOgzPoZFC4NqP7oNADq4o+D9H1naFK4dp0H6oavin1gx/8gC996UuN/jFyHmOQNhZlem2RNnaz3RmakCG6PsBVA5BMZHttUoK1WxuO4D5k5P30VgtlNzhDSuG6jO4BaPShXt5Pb7VQrktnqFK4NqP7oNCDLLyj3mqh/LuNM6QUrk33IeUnpc5hmL08QLYOf4fbGWavMzQhQ3R9gGV9cO1gttdee3f6+ka5DzaVwnlwBo0MCtdldA9Aow+WUjgPzqCTQeHajO6DQg+sKvo8RNd3hiqFa9N9SPmm1Ax2s33ykMz2WF3l6w+wtSl3LJ1Bpz7Ami3Vi3W2xxsrX792MH1ds7gPNpXCeXAGjQwK12V0D0CjD5ZSOA/OoJNB4dqM7oNCD6wq+jxE13eGKoVr033wTalZ7WY7g/RxgIcpU6bEBCUmSChTYpwSE5Qpc4CHGaSvqYfDGXTqFwrpo4kb98DKm4BC+usvK79Cc/LzQvr1jXvS7y8UmhrDfbAzRJ8HZ9DIoHJdRs9BpQ+Wij4PzqCTQeXa9J62qaKvi+j6zpBSuTZbvQ8Z39KqtQyzl2H2soQVrONWlrKKC+jiNcZ4hUPsY0dDbzDmDPOjPqSPJy7rg5MjcHAHjB2CN8bgvK70V2GuvnXu34zSfbCpFM6DM2hkULguo3sAGn2wlMJ5cAadDArXZnQfFHpgVdHnIbq+M1QpXJut3AfflKrDcY7wMHc5Q3CG6PqQXozXfDY0gvtgZ1A4D86gkUHhuozuAWj0wVIK58EZdDIoXJvRfVDogVVFn4fo+s5QpXBttmIf/ON7ZmZmZmZmZmaWO9+UMjMzMzMzMzOz3PmmlJmZmZmZmZmZ5c43pczMzMzMzMzMLHeFJEmSPAuOjY3R3d0NBbhoeZ6VU68eg6QMhSJcuCz/+s7gDGoZousDnDoKJDA6OkpXV1dMCOL3E2jMIzpDdH1ncIbpFHaU95MzqNR3Bq0M3k8phVk4gzOo1FfJUOt+irspZWY2jcxNKTOzs5D4lz4zs7PwfjIzVbPtp/Ycs5zJT0o5gzNIZIiuD9W76DL8v/S1/Jl0BmeYSmpHeT+1fIbo+s6glcH7KaUwC2dwBpX6Khlq3U9hN6UuvBRuOZJ/3ftXwKkfpYOJqO8MzqCWIbo+wH3L08WpImo/gcY8ojNE13cGZ5hOaUd5PzlDdH1n0Mrg/ZRSmIUzOINKfZUMte4nv9G5mZmZmZmZmZnlzjelzMzMzMzMzMwsd74pZWZmZmZmZmZmufNNKTMzMzMzMzMzy13cb9+r08nDcHAnjA7D+AlY1AndvbB6Myxe2ToZltDDOjZzCb2cTyevc4KXGWYfOznOSEtkiK6vkkHhPCpkUKDQB4UMCteFM8TXV8mgcE2oiO5FdH3QOJPO4AwVCteECoVeRGeIPo/O4AzT5X1NyN+UOroH9g/B4V3przMESEpQaEs/f/ZOuKwf1g7Asr6Fm6GXPtazlTX0k1AGoEiR8puf93Mn+3mI3QwxzN4FmSG6vkoGhfOokEGBQh8UMihcF84QX18lg8I1oSK6F9H1QeNMOoMzVChcEyoUehGdIfo8OoMzTBd1Tcj++F6SwPODsOsGGHkESNKGJKU3v175PIHDj8BD70sbmCQLKwPAerYywB6uZANFirTRThvtFKZ8XqTIGm5igMe5kS3NDSCQIbq+QgaF86iQQYFCHxQyQPx14Qwa9RUyqFwTCqJ7EV2/IvpMOoMzVKhcEwoUeqGQodWvCWfQyhB9TcjelDqwHZ68Pf08mZj5eytff2Igfd1CynAjW7iZQQDaWDTj91a+vomhph7U6AzR9VUyKJxHhQwKFPqgkEHhunCG+PoqGRSuCRXRvYiuDxpn0hmcoULhmlCh0IvoDNHn0RmcYbroa0LyptTRPel/ySyeGIBjjy+MDL30sYmhTK/dxBC9XD/vM0TXV8mgcB4VMihQ6INCBoXrwhni66tkULgmVET3Iro+aJxJZ3CGCoVrQoVCL6IzRJ9HZ3CG6aKvCajzptSdd95JoVA44+OKK65oPMU0+4egkPHdrgrt6esXQob1bKXEeKbXlhhvyt3T6AzR9VUyKJxHhQwz8X7KN4PCdeEM8fVVMihcE7NplR0VXR80zqQzOEOFwjUxm1bZTwoZos+jMzjDdNHXBGR4Uupnf/ZnOXbs2OTHn//5nzeeYoqTh9M31prtsbFzSSbgxYfgZANvTK+QYQk9rKF/1kf4zqWNRazlIyxhxbzNEF1fJYPCeVTIUAvvp3wyKFwXzhBfXyWDwjVRq4W+o6Lrg8aZdAZnqFC4Jmq10PeTQobo8+gMzjBd9DVRUfdNqfb2di699NLJj3e84x2NJZjm4M7qO71nVSjCwR3zO8M6Nk++635WCWXWceu8zRBdXyWDwnlUyFAL76d8MihcF84QX18lg8I1UauFvqOi64PGmXQGZ6hQuCZqtdD3k0KG6PPoDM4wXfQ1UVF3hOHhYZYvX8473/lObrnlFg4fPjzj958+fZqxsbEzPmYyOlxvorMbO5T9tQoZLqG3CQkSlrJq3maIrq+SQeE8KmSohfdTPhkUrgtniK+vkkHhmqhVPTuq3v0E8b2Irg8aZ9IZnKFC4Zqo1ULfTwoZos+jMzjDdNHXREVdN6X+0T/6R+zcuZNHH32Ue+65h3/4h3/g+uuv58SJE+d8zbZt2+ju7p786OnpmbHG+Inqrx7MKinBG7PvRukM59NJscH3oS/SxgV0zdsM0fVVMiicR4UMs/F+yi+DwnXhDPH1VTIoXBO1qHdH1bufIL4X0fVB40w6gzNUKFwTtWiF/aSQIfo8OoMzTBd9TVTU1YUNGzawadMm1q5dyy/+4i/yv/7X/+LHP/4x3/72t8/5mjvuuIPR0dHJj5GRmX/gcFEnFNrqSfVWhTY4L/tsJDK8zgnKDT7OV6bEa2Q/IdEZouurZFA4jwoZZuP9lF8GhevCGeLrq2RQuCZqUe+Oqnc/QXwvouuDxpl0BmeoULgmatEK+0khQ/R5dAZnmC76mqjI+D7rqbe97W28+93v5tChcz+v1dHRQUdHR81/ZncznmIDurI/xSaR4WWa8SxdgVfI/ixddIbo+ioZFM6jQoZ6eT/NXQaF68IZ4uurZFC4JrKYbUfVu58gvhfR9UHjTDqDM1QoXBNZLMT9pJAh+jw6gzNMF31NVDT0vNjJkyf5u7/7O5YtW9ZYiilWb4aksRuGJGVYnf39viQy7GMnhQYf5ytQZB/Z33UsOkN0fZUMCudRIUO9vJ/mLoPCdeEM8fVVMihcE1ksxB0VXR80zqQzOEOFwjWRxULcTwoZos+jMzjDdNHXREVdXRgYGGDPnj288MIL7Nu3j4997GO0tbXxK7/yK42lmGLxSljZD4WMz3AV2uGyjbB49h9tls5wnBEOsIsS45leX2Kc/TzIcY7M2wzR9VUyKJxHhQyz8X7KL4PCdeEM8fVVMihcE7VohR0VXR80zqQzOEOFwjVRi1bYTwoZos+jMzjDdNHXREVdN6WOHDnCr/zKr7B69Wr+yT/5J1x88cU88cQTLF26tLEU01w1AMlEttcmJVi7dWFkeIxB2liU6bVF2tjN9nmfIbq+SgaF86iQYSbeT/lmULgunCG+vkoGhWtiNq2yo6Lrg8aZdAZnqFC4JmbTKvtJIUP0eXQGZ5gu+pqAOm9KffOb3+To0aOcPn2aI0eO8M1vfpN3vetdjaeYZlkfXDuY7bXX3p2+fiFkGGYvD5Btyt/hdobZO+8zRNdXyaBwHhUyzMT7Kd8MCteFM8TXV8mgcE3MplV2VHR90DiTzuAMFQrXxGxaZT8pZIg+j87gDNNFXxPQ4HtKzaU1W6rNme1xssrXrx1MX7eQMuxm++RBne3RvsrXH2BrU+6aqmSIrq+SQeE8KmRQoNAHhQwK14UzxNdXyaBwTaiI7kV0fdA4k87gDBUK14QKhV5EZ4g+j87gDNNFXxOyN6UKhfRRsI17YOVNQCH9dYOVX1k4+Xkh/frGPen3FwoLKwOkB3WQPg7wMGXKlJigxAQJZUqMU2KCMmUO8DCD9DX1gKpkiK6vkEHhPCpkUKDQB4UMEH9dOINGfYUMKteEguheRNeviD6TzuAMFSrXhAKFXihkaPVrwhm0MkRfExnf0io/y/rSj5MjcHAHjB2CN8bgvK70Vw+uvnXu3/xPIcMwexlmL0tYwTpuZSmruIAuXmOMVzjEPnY09CZn8yFDdH2VDArnUSGDAoU+KGRQuC6cIb6+SgaFa0JFdC+i64PGmXQGZ6hQuCZUKPQiOkP0eXQGZ5gu6pqQvylVsbgHrvmsMxznCA9zV0tniK6vkkHhPCpkUKDQB4UMCteFM8TXV8mgcE2oiO5FdH3QOJPO4AwVCteECoVeRGeIPo/O4AzT5X1NyP74npmZmZmZmZmZLVy+KWVmZmZmZmZmZrnzTSkzMzMzMzMzM8udb0qZmZmZmZmZmVnuCkmSJHkWHBsbo7u7Gwpw0fI8K6dePQZJGQpFuHBZ/vWdwRnUMkTXBzh1FEhgdHSUrq6umBDE7yfQmEd0huj6zuAM0ynsKO8nZ1Cp7wxaGbyfUgqzcAZnUKmvkqHW/RR3U8rMbBqZm1JmZmch8S99ZmZn4f1kZqpm20/tOWY5k5+UcgZnkMgQXR+qd9Fl+H/pa/kz6QzOMJXUjvJ+avkM0fWdQSuD91NKYRbO4Awq9VUy1Lqfwm5KXXgp3HIk/7r3r4BTP0oHE1HfGZxBLUN0fYD7lqeLU0XUfgKNeURniK7vDM4wndKO8n5yhuj6zqCVwfsppTALZ3AGlfoqGWrdT36jczMzMzMzMzMzy51vSpmZmZmZmZmZWe58U8rMzMzMzMzMzHLnm1JmZmZmZmZmZpY735QyMzMzMzMzM7Pchf32vfno5GE4uBNGh2H8BCzqhO5eWL0ZFq/MJ8MSeljHZi6hl/Pp5HVO8DLD7GMnxxlpmQzRFM6CM9hUCrNQ2A0KGaL5LKQU+mAphVkonEmFDAp8HjR6YFXR84g+jyoZFESfBdCYRd598E2pGhzdA/uH4PAuKLz5bFlSgkJb+vmzd8Jl/bB2AJb1zU2GXvpYz1bW0E9CGYAiRcpvft7PneznIXYzxDB7F2yGaApnwRlsKoVZKOwGhQzRfBZSCn2wlMIsFM6kQgYFPg8aPbCq6HlEn0eVDAqizwJozCKqD/7xvRkkCTw/CLtugJFHgCQdSlJ68+uVzxM4/Ag89L50iEnS3Bzr2coAe7iSDRQp0kY7bbRTmPJ5kSJruIkBHudGtjQ3gEiGSApnwRlsKpVZKOwGhQyRfBZSKn0wnVlEn0mVDNF8HnR6YCmFeSjsBoUM0RTOAsTPIroPvik1gwPb4cnb08+TiZm/t/L1JwbS1zXLjWzhZgYBaGPRjN9b+fomhpp6UBUyRFM4C85gUynMQmE3KGSI5rOQUuiDpRRmoXAmFTIo8HnQ6IFVRc8j+jyqZFAQfRZAYxbRfaj7ptSPfvQjPv7xj3PxxRdzwQUXsGbNGp555pnmpBFydE/a6CyeGIBjjzeeoZc+NjGU6bWbGKKX6xdEhmgKZ8EZauP9NDvvp+ZmiOazkFLoQy1aYUcpzELhTCpkUODzoNGDWrTCfoL4eUSfR5UMCqLPAmjMQqEPdd2UOn78ONdddx2LFi3ikUce4a//+q8ZGhpiyZIljScRs38IChnfcavQnr6+UevZSonxTK8tMd6Uu6cKGaIpnAVnmJ33U228n5qbIZrPQkqhD7NplR2lMAuFM6mQQYHPg0YPZtMq+wni5xF9HlUyKIg+C6AxC4U+1FX+i1/8Ij09PezYsWPyn11++eWNpxBz8nD65l5k/BnJZAJefAhOjsDinmx/xhJ6WEM/xYw/YdnGItbyEZawguMcmbcZoimcBWeojfdTbbyfmpchms9CSqEPtWiFHaUwC4UzqZBBgc+DRg9q0Qr7CeLnEX0eVTIoiD4LoDELhT5AnU9KPfjgg7znPe9h06ZNXHLJJVx99dV89atfzV5d1MGd1Xebz6pQhIM7Zv++c1nH5sl33c8qocw6bp3XGaIpnAVnqI33U+28n5qTIZrPQkqhD7VohR2lMAuFM6mQQYHPg0YPatEK+wni5xF9HlUyKIg+C6AxC4U+QJ03pf7+7/+ee+65h97eXv7kT/6E3/iN3+Df/Jt/w9e//vVzvub06dOMjY2d8aFudLg5f87YoeyvvYTeJiRIWMqqeZ0hmsJZcIbaeD/Vx/up8QzRfBZSCn2oRb07yvspG4UzqZBBgc+DRg9q0Qr7CeLnEX0eVTIoiD4LoDELhT5AnT++Vy6Xec973sMXvvAFAK6++mr+6q/+iv/23/4bn/jEJ876mm3btvEf/+N/bCxlzsZPVH/9YVZJCd5oYD+fT2fmR/kqirRxAV3zOkM0hbPgDLXxfqqd91NzMkTzWUgp9KEW9e4o76dsFM6kQgYFPg8aPahFK+wniJ9H9HlUyaAg+iyAxiwU+gB1Pim1bNkyfuZnfuaMf/bTP/3THD58+JyvueOOOxgdHZ38GBkZyZY0R4s6odDW2J9RaIPzGrhWX+cE5QYf5ytT4jWynxCFDNEUzoIz1Mb7qXbeT83JEM1nIaXQh1rUu6O8n7JROJMKGRT4PGj0oBatsJ8gfh7R51Elg4LoswAas1DoA9T5pNR1113HwYMHz/hnf/u3f8tll112ztd0dHTQ0dGRLV2Q7mY8SQd0NfBU48s041m6Aq+Q/Vk6hQzRFM6CM9TG+6k+3k+NZ4jms5BS6EMt6t1R3k/ZKJxJhQwKfB40elCLVthPED+P6POokkFB9FkAjVko9AHqfFLqt3/7t3niiSf4whe+wKFDh/jGN77Bf//v/53bbrutsRRiVm+GpLGbliRlWN3A+7/tYyeFBh/nK1BkH9nfdUwhQzSFs+AMtfF+qp33U3MyRPNZSCn0oRatsKMUZqFwJhUyKPB50OhBLVphP0H8PKLPo0oGBdFnATRmodAHqPOm1Hvf+16++93v8od/+IdceeWV3HXXXXzpS1/illtuaSyFmMUrYWU/FOp6jqyq0A6XbWzs1yIeZ4QD7KLEeKbXlxhnPw829Ks6FTJEUzgLzlAb76faeD81L0M0n4WUQh9q0Qo7SmEWCmdSIYMCnweNHtSiFfYTxM8j+jyqZFAQfRZAYxYKfYA6b0oB9Pf3c+DAAV5//XV++MMf8q/+1b9qLIGoqwYgmcj22qQEa7c2nuExBmljUabXFmljN9sXRIZoCmfBGWrj/TQ776fmZojms5BS6EMtWmFHKcxC4UwqZFDg86DRg1q0wn6C+HlEn0eVDAqizwJozEKhD409L7aALeuDawezvfbau9PXN2qYvTxAtil/h9sZZu+CyBBN4Sw4g02lMAuF3aCQIZrPQkqhD5ZSmIXCmVTIoMDnQaMHVhU9j+jzqJJBQfRZAI1ZKPTBN6VmsGZLdUCzPdJW+fq1g+nrmmU32ycP6myP9lW+/gBbm3oHWyFDNIWz4Aw2lcIsFHaDQoZoPgsphT5YSmEWCmdSIYMCnweNHlhV9Dyiz6NKBgXRZwE0ZhHdB9+UmkGhkD6OtnEPrLwJKKS/8rDyaxMnPy+kX9+4J/3+QqG5OXaznUH6OMDDlClTYoISEySUKTFOiQnKlDnAwwzSNyfLQiFDJIWz4Aw2lcosFHaDQoZIPgsplT6Yziyiz6RKhmg+Dzo9sJTCPBR2g0KGaApnAeJnEd2HjG9p1VqW9aUfJ0fg4A4YOwRvjMF5XemvP1x969y/AeEwexlmL0tYwTpuZSmruIAuXmOMVzjEPnbM+RvOKWSIpnAWnMGmUpiFwm5QyBDNZyGl0AdLKcxC4UwqZFDg86DRA6uKnkf0eVTJoCD6LIDGLKL64JtSdVjcA9d8NjbDcY7wMHe1fIZoCmfBGWwqhVko7AaFDNF8FlIKfbCUwiwUzqRCBgU+Dxo9sKroeUSfR5UMCqLPAmjMIu8++Mf3zMzMzMzMzMwsd74pZWZmZmZmZmZmufNNKTMzMzMzMzMzy51vSpmZmZmZmZmZWe4KSZIkeRYcGxuju7sbCnDR8jwrp149BkkZCkW4cFn+9Z3BGdQyRNcHOHUUSGB0dJSurq6YEMTvJ9CYR3SG6PrO4AzTKewo7ydnUKnvDFoZvJ9SCrNwBmdQqa+Sodb9FHdTysxsGpmbUmZmZyHxL31mZmfh/WRmqmbbT+05ZjmTn5RyBmeQyBBdH6p30WX4f+lr+TPpDM4wldSO8n5q+QzR9Z1BK4P3U0phFs7gDCr1VTLUup/CbkpdeCncciT/uvevgFM/SgcTUd8ZnEEtQ3R9gPuWp4tTRdR+Ao15RGeIru8MzjCd0o7yfnKG6PrOoJXB+ymlMAtncAaV+ioZat1PfqNzMzMzMzMzMzPLnW9KmZmZmZmZmZlZ7nxTyszMzMzMzMzMcuebUmZmZmZmZmZmlru4375XpyX0sI7NXEIv59PJ65zgZYbZx06OM9IyGRRE9+HkYTi4E0aHYfwELOqE7l5YvRkWr5zz8s4glkFB9DWhkkGBQh+ir4vo+uA5qImeR3R9FQp9ULguFDJEz0KhByqiZ6GSIZpCDxSuC4U+KGTIexbyN6V66WM9W1lDPwllAIoUKb/5eT93sp+H2M0Qw+xdsBkURPfh6B7YPwSHd6W/2hIgKUGhLf382Tvhsn5YOwDL+ppe3hnEMiiIviZUMihQ6EP0dRFdHzwHNdHziK6vQqEPCteFQoboWSj0QEX0LFQyRFPogcJ1odAHhQxRs5D+8b31bGWAPVzJBooUaaOdNtopTPm8SJE13MQAj3MjWxZkBgWRfUgSeH4Qdt0AI48ASXpxJKU3v175PIHDj8BD70svpiRpWgRnEMqgQmE3KGRQEN2H6Osiun5Fq89BTfQ8ouuriO6DwnWhkAH8d1kl0deFSoZo0T1QuS6i+6CQIXoWsjelbmQLNzMIQBuLZvzeytc3MdTUASlkUBDdhwPb4cnb08+TiZm/t/L1JwbS1zWLM+hkUBB9TahkUKDQh+jrIro+eA5qoucRXV+FQh8UrguFDNGzUOiBiuhZqGSIptADhetCoQ8KGaJnIXlTqpc+NjGU6bWbGKKX6xdEBgXRfTi6Jz3wWTwxAMceb6i8M4hlUBB9TahkUKDQh+jrIro+eA5qoucRXV+FQh8UrguFDNGzUOiBiuhZqGSIptADhetCoQ8KGRRmUddNqZ/6qZ+iUCi85eO2225rPMkU69lKifFMry0x3pS7hgoZFET3Yf8QFDK+81mhPX19o5xBJ8Ns8thR0deESgYFCn2Ivi6i64PnUKtW+TtUdH0VCn1QuC4UMkTPQqEHs2mV/aSSIZpCDxSuC4U+KGRQmEVdN6Wefvppjh07Nvnx2GOPAbBp06bGk7xpCT2soX/WR9fOpY1FrOUjLGHFvM6gILoPJw+nb7I22yOE55JMwIsPwckGfkmBM+hkqMVc76joa0IlgwKFPkRfF9H1wXOoRyv8HSq6vgqFPihcFwoZomeh0INatMJ+UskQTaEHCteFQh8UMijMAuq8KbV06VIuvfTSyY9du3bxrne9i/e9732NpZhiHZsn320+q4Qy67h1XmdQEN2Hgzur7/qfVaEIB3dkf70z6GSoxVzvqOhrQiWDAoU+RF8X0fXBc6hHK/wdKrq+CoU+KFwXChmiZ6HQg1q0wn5SyRBNoQcK14VCHxQyKMwCIOODWvDGG29w3333sWXLFgqFwjm/7/Tp05w+fXryP4+Njc34515Cb9ZIUyQsZVXmVytkUBDdh9HhJpQHxg5lf60z6GSoVy07yvtp/lLoQ/R1EV0fPIes5mI/Qfw8ouurUOiDwnWhkCF6Fgo9qNdC3U8qGaIp9EDhulDog0IGhVlAA290/sd//Mf8+Mc/ZvPmzTN+37Zt2+ju7p786OnpmfH7z6eTYoPvv16kjQvoyvx6hQwKovswfqL6ayizSkrwxuz/f9IZ5kGGetWyo7yf5i+FPkRfF9H1wXPIai72E8TPI7q+CoU+KFwXChmiZ6HQg3ot1P2kkiGaQg8UrguFPihkUJgFNHBT6t5772XDhg0sX758xu+74447GB0dnfwYGZn5Bw5f5wTlBh9jK1PiNbJ3RiGDgug+LOqEQltD5Sm0wXkN/P8NZ9DJUK9adpT30/yl0Ifo6yK6PngOWc3FfoL4eUTXV6HQB4XrQiFD9CwUelCvhbqfVDJEU+iBwnWh0AeFDAqzgIw/vvfiiy+ye/du/uiP/mjW7+3o6KCjo6PmP/tlmvEMWYFXyP4MmUIGBdF96G7GE41AVwNP2DqDToZ61LqjvJ/mL4U+RF8X0fXBc8hirvYTxM8jur4KhT4oXBcKGaJnodCDeizk/aSSIZpCDxSuC4U+KGRQmAVkfFJqx44dXHLJJXz4wx9urPpZ7GMnhQYfYytQZB/Z321LIYOC6D6s3gxJYzePScqwuoH3InQGnQz1mKsdFX1NqGRQoNCH6Osiuj54Dlks5L9DRddXodAHhetCIUP0LBR6UI+FvJ9UMkRT6IHCdaHQB4UMCrOADDelyuUyO3bs4BOf+ATt7ZnfJ/2cjjPCAXZRYjzT60uMs58HOc6ReZ1BQXQfFq+Elf1QyHjMCu1w2UZYPPuPuTvDPMhQq7ncUdHXhEoGBQp9iL4uouuD51Cvhf53qOj6KhT6oHBdKGSInoVCD2q10PeTSoZoCj1QuC4U+qCQQWEWkOGm1O7duzl8+DC/9mu/1ljlGTzGIG0syvTaIm3sZvuCyKAgug9XDUAyke21SQnWbm2ovDOIZajFXO+o6GtCJYMChT5EXxfR9cFzqEcr/B0qur4KhT4oXBcKGaJnodCDWrTCflLJEE2hBwrXhUIfFDIozKLum1If/OAHSZKEd7/73Y1XP4dh9vIA2f7bfYfbGWbvgsigILoPy/rg2sFsr7327vT1jXIGnQy1mOsdFX1NqGRQoNCH6Osiuj54DvVohb9DRddXodAHhetCIUP0LBR6UItW2E8qGaIp9EDhulDog0IGhVk09kOMc2g32ycHNNsjbZWvP8DWpt69VsigILoPa7ZUL5TZHi2sfP3awfR1zeIMOhkURF8TKhkUKPQh+rqIrg+eg5roeUTXV6HQB4XrQiFD9CwUeqAiehYqGaIp9EDhulDog0KG6FnI3pSCdECD9HGAhylTpsQEJSZIKFNinBITlClzgIcZpG9OFoVCBgWRfSgU0scCN+6BlTcBhfRXT1Z+feXk54X06xv3pN9fKDQtgjMIZVChsBsUMiiI7kP0dRFdv6LV56Ameh7R9VVE90HhulDIAP67rJLo60IlQ7ToHqhcF9F9UMgQPYvmv4tdkw2zl2H2soQVrONWlrKKC+jiNcZ4hUPsY8ecv9mcQgYF0X1Y1pd+nByBgztg7BC8MQbndaW/hnL1rXP/RpDOoJNBQfQ1oZJBgUIfoq+L6PrgOaiJnkd0fRUKfVC4LhQyRM9CoQcqomehkiGaQg8UrguFPihkiJqF/E2piuMc4WHuavkMCqL7sLgHrvlsWHlnEMugIPqaUMmgQKEP0ddFdH3wHNREzyO6vgqFPihcFwoZomeh0AMV0bNQyRBNoQcK14VCHxQy5D0L6R/fMzMzMzMzMzOzhck3pczMzMzMzMzMLHe+KWVmZmZmZmZmZrnzTSkzMzMzMzMzM8udb0qZmZmZmZmZmVnuCkmSJHkWHBsbo7u7Gwpw0fI8K6dePQZJGQpFuHBZ/vWdwRnUMkTXBzh1FEhgdHSUrq6umBDE7yfQmEd0huj6zuAM0ynsKO8nZ1Cp7wxaGbyfUgqzcAZnUKmvkqHW/RR3U8rMbBqZm1JmZmch8S99ZmZn4f1kZqpm20/tOWY5k5+UcgZnkMgQXR+qd9Fl+H/pa/kz6QzOMJXUjvJ+avkM0fWdQSuD91NKYRbO4Awq9VUy1Lqfwm5KXXgp3HIk/7r3r4BTP0oHE1HfGZxBLUN0fYD7lqeLU0XUfgKNeURniK7vDM4wndKO8n5yhuj6zqCVwfsppTALZ3AGlfoqGWrdT36jczMzMzMzMzMzy51vSpmZmZmZmZmZWe58U8rMzMzMzMzMzHLnm1JmZmZmZmZmZpa7uN++V6cl9LCOzVxCL+fTyeuc4GWG2cdOjjMSHa+leBZw8jAc3AmjwzB+AhZ1QncvrN4Mi1dGp8uP+5DyNaHDs9C4LhXmoNAHFQrzMM+hQuHajJ6FQg9URM/CUgpzcAadDHnvKPmbUr30sZ6trKGfhDIARYqU3/y8nzvZz0PsZohh9kZGXfA8Czi6B/YPweFd6a/XBEhKUGhLP3/2TrisH9YOwLK+sJhzzn1I+ZrQ4VloXJcKc1DogwqFeZjnUKFwbUbPQqEHKqJnYSmFOTiDToaoHSX943vr2coAe7iSDRQp0kY7bbRTmPJ5kSJruIkBHudGtkRHXrBafRZJAs8Pwq4bYOQRIEkv0KT05tcrnydw+BF46H3pBZ0kgaHngPtQ1erXhJJWn4XKdRk9B5U+qIieh6U8B51rM3IWKj1Q4etCg8IcnEEjQ/SOkr0pdSNbuJlBANpYNOP3Vr6+iSEvrTngWcCB7fDk7ennycTM31v5+hMD6esWEvch5WtCh2ehcV0qzEGhDyoU5mGeQ4XCtRk9C4UeqIiehaUU5uAMOhmid1RdN6VKpRL//t//ey6//HIuuOAC3vWud3HXXXeRNPk2fi99bGIo02s3MUQv1zc1TyvzLNLHGJ8YyPbaJwbg2OPNzRNFvQ/eT63Hs9C4LhXmoNCH2XhHtRbPIaVwbUbPQqEHs/F+ai0Kc3AGnQwKO6qum1Jf/OIXueeee/jyl7/MD3/4Q774xS/yn//zf+b3fu/3Gk8yxXq2UmI802tLjPtOehN5FumjiYWM775WaE9fvxCo98H7qfV4FhrXpcIcFPowG++o1uI5pBSuzehZKPRgNt5PrUVhDs6gk0FhR9V1U2rfvn189KMf5cMf/jA/9VM/xc0338wHP/hBnnrqqcaTvGkJPayhf9ZH186ljUWs5SMsYUXTMrUqzyL9zQOHd83+GOO5JBPw4kNwcp7/8pD50Afvp9biWWhclwpzUOhDLbyjWofnkFK4NqNnodCDWng/tQ6FOTiDTgaVHVXXTal169bxve99j7/9278F4Pnnn+fP//zP2bBhQ2MpptZg8+S7zWeVUGYdtzYpUevyLNJfhVmo6yp5q0IRDu5oSpww86EP3k+txbPQuC4V5qDQh1p4R7UOzyGlcG1Gz0KhB7XwfmodCnNwBp0MKjuqrge1PvOZzzA2NsYVV1xBW1sbpVKJz3/+89xyyy3nfM3p06c5ffr05H8eGxubscYl9NYT6RwSlrKqCX9Oa/MsYHS4OX/O2KHm/DlR5kMfvJ9ai2ehcV0qzEGhD7Wod0fVu59AYx7mOVQoXJvRs1DoQS28n1qHwhycQSeDyo6q677Yt7/9be6//36+8Y1v8Jd/+Zd8/etfZ3BwkK9//evnfM22bdvo7u6e/Ojp6Zmxxvl0UmzwlwIWaeMCuhr6M8yzABg/Uf1VmFklJXhj9v9fLW0+9MH7qbV4FhrXpcIcFPpQi3p3VL37CTTmYZ5DhcK1GT0LhR7UwvupdSjMwRl0MqjsqLq6cPvtt/OZz3yGf/bP/hlr1qzhn//zf85v//Zvs23btnO+5o477mB0dHTyY2Rk5h84fJ0TlBt8jK1MideY53cBBHgWsKgTCm2N/RmFNjhvnv//z/nQB++n1uJZaFyXCnNQ6EMt6t1R9e4n0JiHeQ4VCtdm9CwUelAL76fWoTAHZ9DJoLKj6vrxvVdffZVi8cz7WG1tbZTL525mR0cHHR0dNdd4mWY8Q1bgFeb5z0sJ8CyguxlPVQJd8/xJ4/nQB++n1uJZaFyXCnNQ6EMt6t1R9e4n0JiHeQ4VCtdm9CwUelAL76fWoTAHZ9DJoLKj6npSauPGjXz+85/n4Ycf5oUXXuC73/0u27dv52Mf+1hjKabYx04KDT7GVqDIPub5O0sL8Cxg9WZIGruBTVKG1fP8PRnnQx+8n1qLZ6FxXSrMQaEPtfCOah2eQ0rh2oyehUIPauH91DoU5uAMOhlUdlRdXfi93/s9br75Zj75yU/y0z/90wwMDPCv//W/5q677mosxRTHGeEAuygxnun1JcbZz4Mc50jTMrUqzwIWr4SV/VCo65nCqkI7XLYRFs/+o/bS5kMfvJ9ai2ehcV0qzEGhD7XwjmodnkNK4dqMnoVCD2rh/dQ6FObgDDoZVHZUXTelOjs7+dKXvsSLL77Ia6+9xt/93d/xuc99jvPOO6+xFNM8xiBtLMr02iJt7GZ7U/O0Ms8CrhqAZCLba5MSrN3a3DxR1Pvg/dR6PAuN61JhDgp9mI13VGvxHFIK12b0LBR6MBvvp9aiMAdn0MmgsKMae15sjgyzlwfI9t/uO9zOMHubnKh1eRawrA+uHcz22mvvTl+/ELgPKV8TOjwLjetSYQ4KfVChMA/zHCoUrs3oWSj0QEX0LCylMAdn0MmgsKMkb0oB7Gb75IBme6St8vUH2Oo76HPAs4A1W6oX62yPN1a+fu1g+rqFxH1I+ZrQ4VloXJcKc1DogwqFeZjnUKFwbUbPQqEHKqJnYSmFOTiDToboHSV7UwrSAQ3SxwEepkyZEhOUmCChTIlxSkxQpswBHmaQPi+rOdTqsygU0kcTN+6BlTcBhfTXX1Z+hebk54X06xv3pN9fKESmbj73oarVrwklrT4Llesyeg4qfVARPQ9LeQ4612bkLFR6oMLXhQaFOTiDRoboHZXxLa3yM8xehtnLElawjltZyiouoIvXGOMVDrGPHX7Du5x4Funjicv64OQIHNwBY4fgjTE4ryv9VZirb53/b2peC/ch5WtCh2ehcV0qzEGhDyoU5mGeQ4XCtRk9C4UeqIiehaUU5uAMOhmidpT8TamK4xzhYZr3GyAsO88ivRiv+Wx0injuQ8rXhA7PQuO6VJiDQh9UKMzDPIcKhWszehYKPVARPQtLKczBGXQy5L2jpH98z8zMzMzMzMzMFibflDIzMzMzMzMzs9z5ppSZmZmZmZmZmeXON6XMzMzMzMzMzCx3hSRJkjwLjo6O8ra3vQ2AC5flWTn16ktAAhTgwkvzr+8MzqCWIbo+wKvH0v/74x//mO7u7pgQxO8nEJmHz6QzOMOZGQR2lPeTM6jUdwaxDN5PgMgsnMEZROrLZKhxP+V+U+rIkSP09LTI7zo1s7qMjIywYsWKsPreT2Y2k8gd5f1kZjPxfjIzVbPtp9xvSpXLZY4ePUpnZyeFQqHu14+NjdHT08PIyAhdXV1zkNAZ5kuG6PrO0LwMSZJw4sQJli9fTrEY91PF3k/OsJAyRNdfSBkUdlSj+wni5xFd3xmcQS2D91NV9CwUMkTXdwZnaHaGWvdTeyMhsygWi025i9/V1RU2HGfQyhBd3xmakyHyx/YqvJ+cYSFmiK6/UDJE76hm7SeIn0d0fWdwBrUM3k9V0bNQyBBd3xmcoZkZatlPfqNzMzMzMzMzMzPLnW9KmZmZmZmZmZlZ7ubdTamOjg7+w3/4D3R0dDhDi2eIru8MWhkUKPTBGZxBpb4z6InuRXR9Z3AGtQzR9ZUo9CI6Q3R9Z3CGqAy5v9G5mZmZmZmZmZnZvHtSyszMzMzMzMzM5j/flDIzMzMzMzMzs9z5ppSZmZmZmZmZmeXON6XMzMzMzMzMzCx38+qm1F/8xV/Q1tbGhz/84dxrb968mUKhMPlx8cUX86EPfYj9+/fnnuWll17iU5/6FO985zvp6Oigp6eHjRs38r3vfW/Oa0/tw6JFi/iJn/gJ1q9fz9e+9jXK5fKc15+eYerHhz70oVzqz5bj0KFDudR/6aWX+PSnP82qVas4//zz+Ymf+Amuu+467rnnHl599dU5r79582Z+6Zd+6S3//Ac/+AGFQoEf//jHc55BjXeU99P0HFE7Kno/QeyO8n56K+8n76fpObyf/HcoFd5P3k/Tc3g/tdZ+mlc3pe69914+9alP8fjjj3P06NHc63/oQx/i2LFjHDt2jO9973u0t7fT39+fa4YXXniBa665hj/7sz/j7rvv5sCBAzz66KO8//3v57bbbsslQ6UPL7zwAo888gjvf//7+fSnP01/fz8TExO5Zpj68Yd/+Ie51J4tx+WXXz7ndf/+7/+eq6++mj/90z/lC1/4Av/7f/9v/uIv/oJ/+2//Lbt27WL37t1znsHeqtV3lPfTW3NE7qio/QTeUYq8n7yfpufwfvJ+UuH95P00PYf3U2vtp/boALU6efIk3/rWt3jmmWd46aWX2LlzJ//u3/27XDN0dHRw6aWXAnDppZfymc98huuvv55XXnmFpUuX5pLhk5/8JIVCgaeeeoqLLrpo8p//7M/+LL/2a7+WS4apffjJn/xJfu7nfo5rr72WD3zgA+zcuZN/+S//Za4ZIkXl+OQnP0l7ezvPPPPMGefgne98Jx/96EdJkiT3TK3OO8r76Vw5okRm8I7S4v3k/XSuHFG8n6zC+8n76Vw5ong/5W/ePCn17W9/myuuuILVq1fz8Y9/nK997WuhQzl58iT33Xcfq1at4uKLL86l5v/7f/+PRx99lNtuu+2MQ1rxtre9LZccZ/MLv/ALXHXVVfzRH/1RWIZW8X//7//lT//0T895DgAKhULOqazVd5T3k1V4R+nxfvJ+spT3kx7vJ+8nS7Xyfpo3N6XuvfdePv7xjwPpI3Wjo6Ps2bMn1wy7du1i8eLFLF68mM7OTh588EG+9a1vUSzm08ZDhw6RJAlXXHFFLvXqdcUVV/DCCy/kUmvqLCofX/jCF3KpPVOOTZs2zXnNyjlYvXr1Gf/8He94x2SO3/md35nzHHD2OWzYsCGX2mpafUd5P51JYUdF7CfQ2VHeT1XeT95PU3k/xe8n8I6q8H7yfprK+6k199O8+PG9gwcP8tRTT/Hd734XgPb2dv7pP/2n3Hvvvdxwww255Xj/+9/PPffcA8Dx48f5/d//fTZs2MBTTz3FZZddNuf11R/XS5Ikt7u3U2dR8fa3vz2X2jPlONdd7Tw89dRTlMtlbrnlFk6fPp1LzbPN4cknn5z8y0Wr8I7yfppOYUcp7SfIf0d5P6W8n7yfpvN+eiv/HSqG95P303TeT2/VCvtpXtyUuvfee5mYmGD58uWT/yxJEjo6Ovjyl79Md3d3LjkuuugiVq1aNfmf/8f/+B90d3fz1a9+lc997nNzXr+3t5dCocDf/M3fzHmtLH74wx/m9iZw02cRJSLHqlWrKBQKHDx48Ix//s53vhOACy64ILcsZ/vvf+TIkdzqq/CO8n6aTmFHRWVQ2VHeTynvJ++n6byf4vcTeEeB9xN4P03n/dSa+0n+x/cmJib4n//zfzI0NMRzzz03+fH888+zfPnykN+4VlEoFCgWi7z22mu51Hv729/OL/7iL/KVr3yFU6dOveXrkb8+9s/+7M84cOAAv/zLvxyWoVVcfPHFrF+/ni9/+ctnPQeWL++olPeTVXhH6fB+Snk/WYX3kw7vp5T3k1W08n6Sf1Jq165dHD9+nH/xL/7FW+6W//Iv/zL33nsvv/7rv55LltOnT/PSSy8B6aOdX/7ylzl58iQbN27MpT7AV77yFa677jp+/ud/nv/0n/4Ta9euZWJigscee4x77rmHH/7wh3OeodKHUqnE//k//4dHH32Ubdu20d/fz6/+6q/Oef2pGaZqb2/nHe94Ry71o/3+7/8+1113He95z3u48847Wbt2LcVikaeffpq/+Zu/4ZprromO2DK8o6q8n96aYyrvKO+ovHk/VXk/vTXHVN5P3k95836q8n56a46pvJ9aYD8l4vr7+5ObbrrprF978sknEyB5/vnn5zzHJz7xiQSY/Ojs7Eze+973Jt/5znfmvPZ0R48eTW677bbksssuS84777zkJ3/yJ5OPfOQjyfe///05rz21D+3t7cnSpUuTG2+8Mfna176WlEqlOa8/PcPUj9WrV+dSf2qOj370o7nWnOro0aPJb/7mbyaXX355smjRomTx4sXJz//8zyd33313curUqTmvf67//t///vcTIDl+/PicZ1DgHXWmVt9P03NE7ajo/ZQksTvK+ynl/XQm7yfvpwr/HSqe99OZvJ+8nypacT8VkkT83dXMzMzMzMzMzGzBkX9PKTMzMzMzMzMzW3h8U8rMzMzMzMzMzHLnm1JmZmZmZmZmZpY735QyMzMzMzMzM7Pc+aaUmZmZmZmZmZnlzjelzMzMzMzMzMwsd74pZWZmZmZmZmZmufNNKTMzMzMzMzMzy51vSpmZmZmZmZmZWe58U8rMzMzMzMzMzHLnm1JmZmZmZmZmZpY735QyMzMzMzMzM7Pc+aaUmZmZmZmZmZnlzjelzMzMzMzMzMwsd74pZWZmZmZmZmZmufNNKTMzMzMzMzMzy1173gXL5TJHjx6ls7OTQqGQd3kzE5QkCSdOnGD58uUUi3H3yr2fzOxsFHaU95OZnY33k5mpqnU/5X5T6ujRo/T09ORd1szmgZGREVasWBFW3/vJzGYSuaO8n8xsJt5PZqZqtv2U+02pzs7Oyc8vXJZ3dXj1JSABCnDhpfnXdwZnUMsQXR/g1WPp/526HyJE7ycQmYfPpDM4w5kZBHaU95MzqNR3BrEM3k+AyCycwRlE6stkqHE/5X5TqvJI54XL4ONH864O96+AUz+Ci5bDLUfyr+8MzqCWIbo+wH3L06UV/ch39H4CjXlEZ4iu7wzOMJ3CjvJ+cgaV+s6glcH7KaUwC2dwBpX6Khlq3U9+o3MzMzMzMzMzM8udb0qZmZmZmZmZmVnufFPKzMzMzMzMzMxy55tSZmZmZmZmZmaWu9zf6Hw+W0IP69jMJfRyPp28zgleZph97OQ4I7lkOHkYDu6E0WEYPwGLOqG7F1ZvhsUrc4kQniG6vjNoZbCU95MzqNR3BpvO+8kZnEGrvp0pekcpnAdncIbIDL4pVYNe+ljPVtbQT0IZgCJFym9+3s+d7OchdjPEMHvnJMPRPbB/CA7vgsKbz7clJSi0pZ8/eydc1g9rB2BZ35xECM8QXd8ZtDJYyvvJGVTqO4NN5/3kDM6gVd/OFL2jFM6DMziDQgb/+N4s1rOVAfZwJRsoUqSNdtpopzDl8yJF1nATAzzOjWxpav0kgecHYdcNMPIIkKQHIym9+fXK5wkcfgQeel96kJJk4WSIru8MWhmsyvvJGRTqO4OdjfeTMziDTn17q8gdpXAenMEZlDL4ptQMbmQLNzMIQBuLZvzeytc3MdTUpXVgOzx5e/p5MjHz91a+/sRA+rqFkiG6vjNoZbCU95MzqNR3BpvO+8kZnEGrvp0pekcpnAdncAalDL4pdQ699LGJoUyv3cQQvVzfcIaje9JhZ/HEABx7vOEI4Rmi6zuDVgZLeT85g0p9Z7DpvJ+cwRm06tuZoneUwnlwBmdQy1D3TanHH3+cjRs3snz5cgqFAn/8x3/ceApB69lKifFMry0x3pQ76fuHoJDxXb8K7enr53uG6PrOoJVhNt5Ps/N+WlgZous7Q+28n2bn/eQMCzFDdP1atMp+gvgdpXAenMEZ1DLUfVPq1KlTXHXVVXzlK19pvLqoJfSwhv5ZH+c8lzYWsZaPsIQVmTOcPJy+wdhsj8+dSzIBLz4EJxv4hRHRGaLrO4NWhlp4P83O+2nhZIiu7wz18X6anfeTMyy0DNH1a9UK+wnid5TCeXAGZ1DLABluSm3YsIHPfe5zfOxjH2ussrB1bJ78DQxZJZRZx62ZX39wZ/Ud77MqFOHgjuyvj84QXd8ZtDLUwvupNt5PCyNDdH1nqI/3U228n5xhIWWIrl+rVthPEL+jFM6DMziDWgaAjA9q1e706dOcPn168j+PjY3NdcmGXUJvE/6UhKWsyvzq0eEmRADGDmV/bXSG6PrOoJVhLng/ZaNwHpwhvr4zzC3vp2wUzoMzOINK/bkyH/cTxO8ohfPgDM6glgFyeKPzbdu20d3dPfnR09Mz1yUbdj6dFBtsTZE2LqAr8+vHT1R/BWNWSQneaOD/R0RniK7vDFoZ5oL3UzYK58EZ4us7w9zyfspG4Tw4gzOo1J8r83E/QfyOUjgPzuAMahkgh5tSd9xxB6Ojo5MfIyNz/EPRTfA6Jyg3+GhnmRKvkX06izqh0NZQBAptcF72v9eFZ4iu7wxaGeaC91M2CufBGeLrO8Pc8n7KRuE8OIMzqNSfK/NxP0H8jlI4D87gDGoZIIcf3+vo6KCjo2OuyzTVyzTjObYCr5D9ObbuZjxdCnRlfwI+PEN0fWfQyjAXvJ+yUTgPzhBf3xnmlvdTNgrnwRmcQaX+XJmP+wnid5TCeXAGZ1DLADk8KTUf7WMnhQZbU6DIPrK/49fqzZA0diOfpAyrs79XaHiG6PrOoJXBUt5PzqBS3xlsOu8nZ3AGrfp2pugdpXAenMEZ1DJAhptSJ0+e5LnnnuO5554D4B/+4R947rnnOHz4cGNJhBxnhAPsosR4pteXGGc/D3KcI5kzLF4JK/uhkPFZtkI7XLYRFjfwI97RGaLrO4NWhlp4P83O+2nhZIiu7wz18X6anfeTMyy0DNH1a9UK+wnid5TCeXAGZ1DLABluSj3zzDNcffXVXH311QBs2bKFq6++ms9+9rONJRHzGIO0sSjTa4u0sZvtDWe4agCSiWyvTUqwdmvDEcIzRNd3Bq0Ms/F+mp3308LKEF3fGWrn/TQ77ydnWIgZouvXolX2E8TvKIXz4AzOoJah7ptSN9xwA0mSvOVj586djacRMsxeHiBbh7/D7Qyzt+EMy/rg2sFsr7327vT18z1DdH1n0MowG++n2Xk/LawM0fWdoXbeT7PzfnKGhZghun4tWmU/QfyOUjgPzuAMahn8nlIz2M32yaU122Oela8/wNam/K98FWu2VA/JbI/VVb5+7WD6uoWSIbq+M2hlsJT3kzOo1HcGm877yRmcQau+nSl6RymcB2dwBqUMvik1i91sZ5A+DvAwZcqUmKDEBAllSoxTYoIyZQ7wMIP0NfUvVACFQvpI3MY9sPImoJD+2sXKr26c/LyQfn3jnvT7C4WFkyG6vjNoZbAq7ydnUKjvDHY23k/O4Aw69e2tIneUwnlwBmdQypDxLa1ayzB7GWYvS1jBOm5lKau4gC5eY4xXOMQ+djT0ppy1WNaXfpwcgYM7YOwQvDEG53Wlv4Jx9a1z/yaI0Rmi6zuDVgZLeT85g0p9Z7DpvJ+cwRm06tuZoneUwnlwBmdQyOCbUnU4zhEe5q7QDIt74JrPhkYIzxBd3xm0MljK+8kZVOo7g03n/eQMzqBV384UvaMUzoMzOENkBv/4npmZmZmZmZmZ5c43pczMzMzMzMzMLHe+KWVmZmZmZmZmZrnzTSkzMzMzMzMzM8tdIUmSJM+CY2NjdHd3QwEuWp5n5dSrxyApQ6EIFy7Lv74zOINahuj6AKeOAgmMjo7S1dUVE4L4/QQa84jOEF3fGZxhOoUd5f3kDCr1nUErg/dTSmEWzuAMKvVVMtS6n+JuSpmZTSNzU8rM7Cwk/qXPzOwsvJ/MTNVs+6k9xyxn8pNSzuAMEhmi60P1LroM/y99LX8mncEZppLaUd5PLZ8hur4zaGXwfkopzMIZnEGlvkqGWvdT2E2pCy+FW47kX/f+FXDqR+lgIuo7gzOoZYiuD3Df8nRxqojaT6Axj+gM0fWdwRmmU9pR3k/OEF3fGbQyeD+lFGbhDM6gUl8lQ637yW90bmZmZmZmZmZmufNNKTMzMzMzMzMzy51vSpmZmZmZmZmZWe58U8rMzMzMzMzMzHLnm1JmZmZmZmZmZpa7sN++Z9mcPAwHd8LoMIyfgEWd0N0LqzfD4pWtkWEJPaxjM5fQy/l08joneJlh9rGT44zMfQDie+AMpkjhPChkiN5RCj1wBptKYRbOkIreT6DRh+gM0fWVKJzJ6AzR9Z2hSuHabMUMvik1TxzdA/uH4PAuKLz5fFtSgkJb+vmzd8Jl/bB2AJb1LcwMvfSxnq2soZ+EMgBFipTf/LyfO9nPQ+xmiGH2Nj8A8T1wBlOkcB4UMkTvKIUeOINNpTALZ0hF7yfQ6EN0huj6ShTOZHSG6PrOUKVwbbZyBv/4nrgkgecHYdcNMPIIkKQHIym9+fXK5wkcfgQeel96kJJkYWVYz1YG2MOVbKBIkTbaaaOdwpTPixRZw00M8Dg3sqV5xdHogTOYGoXzoJABYneUQg+cwaZSmIUzVPnvUPEZouuriT6TChmi6ztDSuHadAbflJJ3YDs8eXv6eTIx8/dWvv7EQPq6hZLhRrZwM4MAtLFoxu+tfH0TQ01dWtE9cAZTpHAeFDJE7yiFHjiDTaUwC2dIRe8n0OhDdIbo+koUzmR0huj6zlClcG06Q503pbZt28Z73/teOjs7ueSSS/ilX/olDh482Jwk9hZH96TDzuKJATj2+PzP0EsfmxjK9NpNDNHL9Y0FIL4HzlAb76d8KZwHhQzRO0qhB85Qm1bZUQqzcIZU9H4CjT5EZ4iuX4u89pPCmYzOEF3fGaoUrk1nSNV1U2rPnj3cdtttPPHEEzz22GOMj4/zwQ9+kFOnTjWexN5i/xAUMr7rV6E9ff18z7CerZQYz/TaEuNNuZMe3QNnqI33U74UzoNChugdpdADZ6hNq+wohVk4Qyp6P4FGH6IzRNevRV77SeFMRmeIru8MVQrXpjOk6ir/6KOPnvGfd+7cySWXXMKzzz5LX98Cfze+nJ08nL7BGBl/TjOZgBcfgpMjsLhnfmZYQg9r6KeY8adM21jEWj7CElZwnCOZ/ozoHjhD7byf8qNwHhQyRO8ohR44Q+1aYUcpzMIZUtH7CTT6EJ0hun6t8thPCmcyOkN0fWeoUrg2naGqofeUGh0dBeDtb397I3+MncXBndV3vM+qUISDO+ZvhnVsnvwNDFkllFnHrZlfH90DZ8jO+2nuKJwHhQzRO0qhB86Q3ULcUQqzcIZU9H4CjT5EZ4iun9Vc7CeFMxmdIbq+M1QpXJvOUJXxQS0ol8v81m/9Ftdddx1XXnnlOb/v9OnTnD59evI/j42NZS3ZUkaHm/PnjB2avxkuobcJ1ROWsirzq6N74AzZeD/NLYXzoJAhekcp9MAZsqllR83H/aQwC2dIRe8n0OhDdIbo+lnM1X5SOJPRGaLrO0OVwrXpDFWZ74vddttt/NVf/RXf/OY3Z/y+bdu20d3dPfnR0zOHz54uIOMnqr+CMaukBG808HfY6Azn05n5sc6KIm1cQFfm10f3wBmy8X6aWwrnQSFD9I5S6IEzZFPLjpqP+0lhFs6Qit5PoNGH6AzR9bOYq/2kcCajM0TXd4YqhWvTGaoynYbf/M3fZNeuXXz/+99nxYoVM37vHXfcwejo6OTHyMhIpqCtZlEnFNoa+zMKbXBe9ms1PMPrnKDc4KOdZUq8RvarJLoHzlA/76e5p3AeFDJE7yiFHjhD/WrdUfNxPynMwhlS0fsJNPoQnSG6fr3mcj8pnMnoDNH1naFK4dp0hqq6fnwvSRI+9alP8d3vfpcf/OAHXH755bO+pqOjg46OjswBW1V3M55qBLqyP9UYnuFlmvE8YYFXyP48YXQPnKF23k/5UTgPChmid5RCD5yhdvXuqPm4nxRm4Qyp6P0EGn2IzhBdv1Z57CeFMxmdIbq+M1QpXJvOUFXXk1K33XYb9913H9/4xjfo7OzkpZde4qWXXuK1115rLIW9xerNkDR2A5mkDKuzv/9beIZ97KTQ4KOdBYrsI/s7r0X3wBlq5/2UH4XzoJAhekcp9MAZatcKO0phFs6Qit5PoNGH6AzR9WuVx35SOJPRGaLrO0OVwrXpDFV1nYZ77rmH0dFRbrjhBpYtWzb58a1vfauxFPYWi1fCyn4oZHwr+kI7XLaxsV/NGJ3hOCMcYBclxjO9vsQ4+3kw868KhfgeOEPtvJ/yo3AeFDJE7yiFHjhD7VphRynMwhlS0fsJNPoQnSG6fq3y2E8KZzI6Q3R9Z6hSuDadoaqum1JJkpz1Y/PmzY2lsLO6agCSiWyvTUqwduv8z/AYg7SxKNNri7Sxm+2NBSC+B85QYw3vp1wpnAeFDNE7SqEHzlBjnRbZUQqzcIZU9H4CjT5EZ4iuX1OdnPaTwpmMzhBd3xmqFK5NZ0g19tyczallfXDtYLbXXnt3+vr5nmGYvTxAtpP+HW5nmL2NBSC+B85gihTOg0KG6B2l0ANnsKkUZuEMqej9BBp9iM4QXV+JwpmMzhBd3xmqFK5NZ0j5ppS4NVuqh2S2x+oqX792MH3dQsmwm+2TS2u2xzwrX3+ArU25g14R3QNnMEUK50EhQ/SOUuiBM9hUCrNwhlT0fgKNPkRniK6vROFMRmeIru8MVQrXpjP4ppS8QiF9JG7jHlh5E1BIf+1i5Vc3Tn5eSL++cU/6/YXCwsqwm+0M0scBHqZMmRITlJggoUyJcUpMUKbMAR5mkL6mLivQ6IEzmBqF86CQAWJ3lEIPnMGmUpiFM1T571DxGaLrq4k+kwoZous7Q0rh2nQGyPiWVpa3ZX3px8kROLgDxg7BG2NwXlf6KxhX3zr3b4IYnWGYvQyzlyWsYB23spRVXEAXrzHGKxxiHzsaesO7WkT3wBlMkcJ5UMgQvaMUeuAMNpXCLJwhFb2fQKMP0Rmi6ytROJPRGaLrO0OVwrXZyhl8U2qeWdwD13y2tTMc5wgPc1dcAOJ74AymSOE8KGSI3lEKPXAGm0phFs6Qit5PoNGH6AzR9ZUonMnoDNH1naFK4dpsxQz+8T0zMzMzMzMzM8udb0qZmZmZmZmZmVnufFPKzMzMzMzMzMxy55tSZmZmZmZmZmaWu0KSJEmeBcfGxuju7oYCXLQ8z8qpV49BUoZCES5cln99Z3AGtQzR9QFOHQUSGB0dpaurKyYE8fsJNOYRnSG6vjM4w3QKO8r7yRlU6juDVgbvp5TCLJzBGVTqq2SodT/F3ZQyM5tG5qaUmdlZSPxLn5nZWXg/mZmq2fZTe45ZzuQnpZzBGSQyRNeH6l10Gf5f+lr+TDqDM0wltaO8n1o+Q3R9Z9DK4P2UUpiFMziDSn2VDLXup7CbUhdeCrccyb/u/Svg1I/SwUTUdwZnUMsQXR/gvuXp4lQRtZ9AYx7RGaLrO4MzTKe0o7yfnCG6vjNoZfB+SinMwhmcQaW+SoZa95Pf6NzMzMzMzMzMzHLnm1JmZmZmZmZmZpY735QyMzMzMzMzM7Pc+aaUmZmZmZmZmZnlLu6379VpCT2sYzOX0Mv5dPI6J3iZYfaxk+OMtEyGk4fh4E4YHYbxE7CoE7p7YfVmWLwylwjhfVDogTPoZFAQfU2oZFA4D+5DfH1n0BN9XSjMQiFD9BxAow/OEF9ficJ1EZ1B4TxE9wA0+uAMMRnkb0r10sd6trKGfhLKABQpUn7z837uZD8PsZshhtm7YDMc3QP7h+DwrvTXOgIkJSi0pZ8/eydc1g9rB2BZ35xECO+DQg+cQSeDguhrQiWDwnlwH+LrO4Oe6OtCYRYKGaLnABp9cIb4+koUrovoDArnIboHoNEHZ4jNIP3je+vZygB7uJINFCnSRjtttFOY8nmRImu4iQEe50a2LLgMSQLPD8KuG2DkESBJD0ZSevPrlc8TOPwIPPS+9CAlSVNjhPZBoQfOoJNBRfRuUMigch5avQ/R9Z1Bk///dnwG8H5yBo36aqKvi+gMKucheg4KfXAGjQyyN6VuZAs3MwhAG4tm/N7K1zcx1NSLRSHDge3w5O3p58nEzN9b+foTA+nrmiW6Dwo9cAadDAqirwmVDArnwX2Ir+8MeqKvC4VZKGSIngNo9MEZ4usrUbguojMonIfoHoBGH5xBI4PkTale+tjEUKbXbmKIXq5fEBmO7kmHncUTA3Ds8YYjhPdBoQfOoJNBQfQ1oZJB4Ty4D/H1nUFP9HWhMAuFDNFzAI0+OEN8fSUK10V0BoXzEN0D0OiDM+hkqOum1D333MPatWvp6uqiq6uLf/yP/zGPPPJI4ymmWc9WSoxnem2J8abcwVXIsH8IChnf9avQnr6+UdF9UOiBM+hkmIn3U74ZFM6D+xBf3xlq1yo7SmEWChmi5wAafXCG+Pq1aJX9pJBB4TxE9wA0+uAMOhnquim1YsUKfvd3f5dnn32WZ555hl/4hV/gox/9KP/f//f/NZ7kTUvoYQ39sz5GeC5tLGItH2EJK+Z1hpOH0zcYm+3xuXNJJuDFh+BkA78sIboPCj1wBp0Ms/F+yi+DwnlwH+LrO0N9WmFHKcxCIUP0HECjD84QX79WrbCfFDIonIfoHoBGH5xBJwPUeVNq48aN3HTTTfT29vLud7+bz3/+8yxevJgnnniisRRTrGPz5Dv/Z5VQZh23zusMB3dW3/E+q0IRDu7I/vroPij0wBl0MszG+ym/DArnwX2Ir+8M9WmFHaUwC4UM0XMAjT44Q3z9WrXCflLIoHAeonsAGn1wBp0MABkf1IJSqcQDDzzAqVOn+Mf/+B+f8/tOnz7N6dOnJ//z2NjYjH/uJfRmjTRFwlJWZX61QobR4SZEAMYOZX9tdB8UeuAMOhnq4f00txkUzoP7EF/fGbKrZUfVu58g/rpQmIVChug5gEYfnCG+fhYLdT8pZFA4D9E9AI0+OINOBsjwRucHDhxg8eLFdHR08Ou//ut897vf5Wd+5mfO+f3btm2ju7t78qOnp2fGP/98Oik2+P7rRdq4gK7Mr1fIMH6i+isYs0pK8Mbs/z/inKL7oNADZ9DJUAvvp3wyKJwH9yG+vjPUr54dVe9+gvjrQmEWChmi5wAafXCG+Pr1WOj7SSGDwnmI7gFo9MEZdDJAhptSq1ev5rnnnuPJJ5/kN37jN/jEJz7BX//1X5/z+++44w5GR0cnP0ZGZv6Bw9c5QbnBRwrLlHiN7J1RyLCoEwptDUWg0AbnZd8X4X1Q6IEz6GSohfdTPhkUzoP7EF/fGepXz46qdz9B/HWhMAuFDNFzAI0+OEN8/Xos9P2kkEHhPET3ADT64Aw6GSDDj++dd955rFqVPq53zTXX8PTTT/Nf/st/4Q/+4A/O+v0dHR10dHTU/Oe/TDOeISvwCtmfIVPI0N2MJyuBruxPVob3QaEHzqCToRbeT/lkUDgP7kN8fWeoXz07qt79BPHXhcIsFDJEzwE0+uAM8fXrsdD3k0IGhfMQ3QPQ6IMz6GSADE9KTVcul8/4meJG7WMnhQZjFSiyj+zvtqWQYfVmSBq7iU1ShtXZ34MuvA8KPXAGnQxZeD/NTQaF8+A+xNd3hsYttB2lMAuFDNFzAI0+OEN8/UYstP2kkEHhPET3ADT64Aw6GaDOm1J33HEHjz/+OC+88AIHDhzgjjvu4Ac/+AG33HJLYymmOM4IB9hFifFMry8xzn4e5DhH5nWGxSthZT8UMr4VfaEdLtsIi2f/Ee9ziu6DQg+cQSfDbLyf8sugcB7ch/j6zlCfVthRCrNQyBA9B9DogzPE169VK+wnhQwK5yG6B6DRB2fQyQB13pR6+eWX+dVf/VVWr17NBz7wAZ5++mn+5E/+hPXr1zeWYprHGKSNRZleW6SN3WxfEBmuGoBkIttrkxKs3dpwhPA+KPTAGXQyzMT7Kd8MCufBfYiv7wy1a5UdpTALhQzRcwCNPjhDfP1atMp+UsigcB6iewAafXAGnQx13ZS69957eeGFFzh9+jQvv/wyu3fvbvqyAhhmLw+Q7b/dd7idYfYuiAzL+uDawWyvvfbu9PWNiu6DQg+cQSfDTLyf8s2gcB7ch/j6zlC7VtlRCrNQyBA9B9DogzPE169Fq+wnhQwK5yG6B6DRB2fQydDwe0rNld1sn7xYZnu8sPL1B9jalDu3ShnWbKkektkeq6t8/drB9HXNEt0HhR44g04GBdHXhEoGhfPgPsTXdwY90deFwiwUMkTPATT64Azx9ZUoXBfRGRTOQ3QPQKMPzqCRQfamFKQXyyB9HOBhypQpMUGJCRLKlBinxARlyhzgYQbpa+pFopKhUEgfidu4B1beBBTSX7tY+dWNk58X0q9v3JN+f6HQ1BihfVDogTPoZFARvRsUMqich1bvQ3R9Z9Dk/78dnwG8n5xBo76a6OsiOoPKeYieg0IfnEEjQ8a3tMrPMHsZZi9LWME6bmUpq7iALl5jjFc4xD52NPRGa/Mlw7K+9OPkCBzcAWOH4I0xOK8r/RWMq2+d+zdBjO6DQg+cQSeDguhrQiWDwnlwH+LrO4Oe6OtCYRYKGaLnABp9cIb4+koUrovoDArnIboHoNEHZ4jNIH9TquI4R3iYu1o+w+IeuOazoRHC+6DQA2fQyaAg+ppQyaBwHtyH+PrOoCf6ulCYhUKG6DmARh+cIb6+EoXrIjqDwnmI7gFo9MEZYjJI//iemZmZmZmZmZktTL4pZWZmZmZmZmZmufNNKTMzMzMzMzMzy51vSpmZmZmZmZmZWe4KSZIkeRYcGxuju7sbCnDR8jwrp149BkkZCkW4cFn+9Z3BGdQyRNcHOHUUSGB0dJSurq6YEMTvJ9CYR3SG6PrO4AzTKewo7ydnUKnvDFoZvJ9SCrNwBmdQqa+Sodb9FHdTysxsGpmbUmZmZyHxL31mZmfh/WRmqmbbT+05ZjmTn5RyBmeQyBBdH6p30WX4f+lr+TPpDM4wldSO8n5q+QzR9Z1BK4P3U0phFs7gDCr1VTLUup/CbkpdeCncciT/uvevgFM/SgcTUd8ZnEEtQ3R9gPuWp4tTRdR+Ao15RGeIru8MzjCd0o7yfnKG6PrOoJXB+ymlMAtncAaV+ioZat1PfqNzMzMzMzMzMzPLnW9KmZmZmZmZmZlZ7nxTyszMzMzMzMzMcuebUmZmZmZmZmZmljvflDIzMzMzMzMzs9yF/fa9+WgJPaxjM5fQy/l08joneJlh9rGT44zkkuHkYTi4E0aHYfwELOqE7l5YvRkWr8wlQngfouuD51Ch0AcFCrNQyKBwHhT6EJ3Bc0gp9EFF9DwUZqGQIXoOKhk8C40eqIieBcTPQ6EHzpCKPgvQmn3wTaka9NLHerayhn4SygAUKVJ+8/N+7mQ/D7GbIYbZOycZju6B/UNweBcU3ny+LSlBoS39/Nk74bJ+WDsAy/rmJEJ4H6Lrg+dQodAHBQqzUMigcB4U+hCdwXNIKfRBRfQ8FGahkCF6DioZPAuNHqiIngXEz0OhB86Qij4L0Np98I/vzWI9WxlgD1eygSJF2minjXYKUz4vUmQNNzHA49zIlqbWTxJ4fhB23QAjjwBJejCS0ptfr3yewOFH4KH3pQcpSZoaI7wP0fU9h5RKHxREz0Ihg8p5iO5DdAbPIaXSBxWtfiYVMkD8daGQwbPQ6YEKn8n4HjhDSuEsgPvgm1IzuJEt3MwgAG0smvF7K1/fxFBTD8mB7fDk7ennycTM31v5+hMD6euaJboP0fXBc6hQ6IMChVkoZFA4Dwp9iM7gOaQU+qAieh4Ks1DIED0HlQyehUYPVETPAuLnodADZ0hFnwVwH6DBm1K/+7u/S6FQ4Ld+67eak0ZIL31sYijTazcxRC/XN5zh6J502Fk8MQDHHm84QngfouuD51Ch0Id6zNV+UpiFQgaF86DQh+gMnkNKoQ/1mMu/P0XPQ2EWChmi56CSwbPQ6EG9FvLfoaLnodADZ0hFnwVwHyoy35R6+umn+YM/+APWrl3beApB69lKifFMry0x3pQ7l/uHoJDxXb8K7enrGxXdh+j64DlUKPShVnO5nxRmoZBB4Two9CE6g+eQUuhDreb670/R81CYhUKG6DmoZPAsNHpQj4X+d6joeSj0wBlS0WcB3IeKTDelTp48yS233MJXv/pVlixZ0ngKMUvoYQ39sz4+dy5tLGItH2EJKzJnOHk4fYOx2R6fO5dkAl58CE428Ab90X2Irg+eQ4VCH2o1l/tJYRYKGRTOg0IfojN4DimFPtRqrv/+FD0PhVkoZIieg0oGz0KjB/VY6H+Hip6HQg+cIRV9FsB9mCrTTanbbruND3/4w9x4442NVRe1js2T73ifVUKZddya+fUHd1bf8T6rQhEO7sj++ug+RNcHz6FCoQ+1msv9pDALhQwK50GhD9EZPIeUQh9qNdd/f4qeh8IsFDJEz0Elg2eh0YN6LPS/Q0XPQ6EHzpCKPgvgPkxV94Na3/zmN/nLv/xLnn766Zq+//Tp05w+fXryP4+NjdVbMneX0NuEPyVhKasyv3p0uAkRgLFD2V8b3Yfo+uA5VCj0oRZzvZ8UZqGQQeE8KPQhOoPnkFLoQy3y+PtT9DwUZqGQIXoOKhk8C40e1KqeHTUf9xPEz0OhB86Qij4L4D5MVdd9sZGRET796U9z//33c/7559f0mm3bttHd3T350dPTkylons6nk2KDv5iwSBsX0JX59eMnqr+CMaukBG80cA8wug/R9cFzqFDow2zy2E8Ks1DIoHAeFPoQncFzSCn0YTZ5/f0peh4Ks1DIED0HlQyehUYPalHvjpqP+wni56HQA2dIRZ8FcB+mqqsLzz77LC+//DI/93M/R3t7O+3t7ezZs4f/+l//K+3t7ZRKb/1vdMcddzA6Ojr5MTKS0w9FN+B1TlBu8FG6MiVeI/t0FnVCoa2hCBTa4LzsZzS8D9H1wXOoUOjDbPLYTwqzUMigcB4U+hCdwXNIKfRhNnn9/Sl6HgqzUMgQPQeVDJ6FRg9qUe+Omo/7CeLnodADZ0hFnwVwH6aq68f3PvCBD3DgwIEz/tmtt97KFVdcwe/8zu/Q1vbW/0YdHR10dHQ0ljJnL9OM59gKvEL259i6m/E0H9CV/Wm+8D5E1wfPoUKhD7PJYz8pzEIhg8J5UOhDdAbPIaXQh9nk9fen6HkozEIhQ/QcVDJ4Fho9qEW9O2o+7ieIn4dCD5whFX0WwH2Yqq4npTo7O7nyyivP+Ljooou4+OKLufLKKxtLImQfOyk0+ChdgSL7yP6OX6s3Q9LYjVOSMqzO/r5n4X2Irg+eQ4VCH2aTx35SmIVCBoXzoNCH6AyeQ0qhD7PJ6+9P0fNQmIVChug5qGTwLDR6UItW+TtU9DwUeuAMqeizAO7DVA2+1/rCdJwRDrCLEuOZXl9inP08yHGOZM6weCWs7IdC3W9Fnyq0w2UbYXEDb+EV3Yfo+uA5VCj0QYHCLBQyKJwHhT5EZ/AcUgp9UBE9D4VZKGSInoNKBs9CowcqomcB8fNQ6IEzpKLPArgPUzV8U+oHP/gBX/rSlxr9Y+Q8xiBtLMr02iJt7GZ7wxmuGoBkIttrkxKs3dpwhPA+RNcHz6FCoQ/1mov9pDALhQwK50GhD9EZPIeUQh/qNVd/f4qeh8IsFDJEz0Elg2eh0YMsFurfoaLnodADZ0hFnwVwHyr8pNQ5DLOXB8jW4e9wO8PsbTjDsj64djDba6+9O319o6L7EF0fPIcKhT4oUJiFQgaF86DQh+gMnkNKoQ8qouehMAuFDNFzUMngWWj0QEX0LCB+Hgo9cIZU9FkA96HCN6VmsJvtk4dktsfqKl9/gK1NuWNZsWZL9ZDM9lhd5evXDqava5boPkTXB8+hQqEPChRmoZBB4Two9CE6g+eQUuiDiuh5KMxCIUP0HFQyeBYaPVARPQuIn4dCD5whFX0WwH0A35Sa1W62M0gfB3iYMmVKTFBigoQyJcYpMUGZMgd4mEH6mno4AAqF9JG4jXtg5U1AIf21i5Vf3Tj5eSH9+sY96fcXCk2NEd6H6PqeQ0qlDwqiZ6GQQeU8RPchOoPnkFLpg4pWP5MKGSD+ulDI4Fno9ECFz2R8D5whpXAWwH3I+JZWrWWYvQyzlyWsYB23spRVXEAXrzHGKxxiHzsaeoOxWizrSz9OjsDBHTB2CN4Yg/O60l/BuPrWuX8TxOg+RNcHz6FCoQ8KFGahkEHhPCj0ITqD55BS6IOK6HkozEIhQ/QcVDJ4Fho9UBE9C4ifh0IPnCEVfRagtfvgm1J1OM4RHuau0AyLe+Caz4ZGCO9DdH3wHCoU+qBAYRYKGRTOg0IfojN4DimFPqiInofCLBQyRM9BJYNnodEDFdGzgPh5KPTAGVLRZwFasw/+8T0zMzMzMzMzM8udb0qZmZmZmZmZmVnufFPKzMzMzMzMzMxy55tSZmZmZmZmZmaWu0KSJEmeBcfGxuju7oYCXLQ8z8qpV49BUoZCES5cln99Z3AGtQzR9QFOHQUSGB0dpaurKyYE8fsJNOYRnSG6vjM4w3QKO8r7yRlU6juDVgbvp5TCLJzBGVTqq2SodT/F3ZQyM5tG5qaUmdlZSPxLn5nZWXg/mZmq2fZTe45ZzuQnpZzBGSQyRNeH6l10Gf5f+lr+TDqDM0wltaO8n1o+Q3R9Z9DK4P2UUpiFMziDSn2VDLXup7CbUhdeCrccyb/u/Svg1I/SwUTUdwZnUMsQXR/gvuXp4lQRtZ9AYx7RGaLrO4MzTKe0o7yfnCG6vjNoZfB+SinMwhmcQaW+SoZa95Pf6NzMzMzMzMzMzHLnm1JmZmZmZmZmZpY735QyMzMzMzMzM7Pc+aaUmZmZmZmZmZnlLu6379Xp5GE4uBNGh2H8BCzqhO5eWL0ZFq90hjwzLKGHdWzmEno5n05e5wQvM8w+dnKckTmv7x7oZFCYhQKFPvg8pNwHjR4oZIieg5LoXkTXV8ng6yKl0IfoDApzUKHQi+gM0fUh/poA90EpQ96zkL8pdXQP7B+Cw7vSX2cIkJSg0JZ+/uydcFk/rB2AZX3OMJcZeuljPVtZQz8JZQCKFCm/+Xk/d7Kfh9jNEMPsbXp990Ang8IsFCj0wech5T5o9EAhQ/QclET3Irq+SgZfFymFPkRnUJiDCoVeRGeIrg/x1wS4D0oZomYh++N7SQLPD8KuG2DkESBJG5KU3vx65fMEDj8CD70vbWCSOEOzMwCsZysD7OFKNlCkSBvttNFOYcrnRYqs4SYGeJwb2dK02u6BTgaVWURT6YPPQ8p9iO+BQgaFOaiI7kV0fZUM4OuiIroP0RlU5qBAoRfRGaLrV0Rfl+6DToboWcjelDqwHZ68Pf08mZj5eytff2IgfZ0zNDfDjWzhZgYBaGPRjN9b+fomhpp2sbgHOhkUZqFAoQ8+Dyn3QaMHChmi56AkuhfR9VUy+LpIKfQhOoPCHFQo9CI6Q3R9iL8mwH1QyhA9C8mbUkf3pP8ls3hiAI497gzNytBLH5sYyvTaTQzRy/UN1XcPdDIozEKBQh98HlLug0YPFDJEz0FJdC+i66tk8HWRUuhDdAaFOahQ6EV0huj6EH9NgPuglEFhFnXdlLrzzjspFApnfFxxxRWNp5hm/xAUMr7bVaE9fb0zNCfDerZSYjzTa0uMN3wH1z3QyaAwi5m00n7yeUi5Dxo9UMgQPYdatMqOiq6vksHXRUqhD9EZFOYwm1bZTwoZoutD/DUB7oNSBoVZ1P2k1M/+7M9y7NixyY8///M/bzzFFCcPp2+sNdtjY+eSTMCLD8HJBt6Y3hlSS+hhDf2zPkZ4Lm0sYi0fYQkrMr3ePdDJoDCLWrTCfvJ5SLkPGj1QyBA9h3os9B0VXV8lg6+LlEIfojMozKFWC30/KWSIrg/x1wS4D0oZFGYBGW5Ktbe3c+mll05+vOMd72gswTQHd1bf6T2rQhEO7nCGRjOsY/PkO/9nlVBmHbdmeq17oJNBYRa1aIX95POQch80eqCQIXoO9VjoOyq6vkoGXxcphT5EZ1CYQ60W+n5SyBBdH+KvCXAflDIozAIy3JQaHh5m+fLlvPOd7+SWW27h8OHDM37/6dOnGRsbO+NjJqPD9SY6u7FD2V/rDKlL6G1CgoSlrMr0SvdAJ4PCLGrRCvvJ5yHlPmj0QCFD9BzqUc+Oqnc/QXwvouurZPB1kVLoQ3QGhTnUaqHvJ4UM0fUh/poA90Epg8IsoM6bUv/oH/0jdu7cyaOPPso999zDP/zDP3D99ddz4sSJc75m27ZtdHd3T3709PTMWGP8RPVXD2aVlOCN2XejM8zifDopNvhe+EXauICuTK91D3QyKMxiNq2yn3weUu6DRg8UMkTPoVb17qh69xPE9yK6vkoGXxcphT5EZ1CYQy1aYT8pZIiuD/HXBLgPShkUZgF13pTasGEDmzZtYu3atfziL/4i/+t//S9+/OMf8+1vf/ucr7njjjsYHR2d/BgZmfkHDhd1QqGtnlRvVWiD87LPxhne9DonKDf4SGGZEq+R7ZS6BzoZFGYxm1bZTz4PKfdBowcKGaLnUKt6d1S9+wniexFdXyWDr4uUQh+iMyjMoRatsJ8UMkTXh/hrAtwHpQwKswDI+D7rqbe97W28+93v5tChcz+v1dHRQUdHR81/ZncznmIDurI/xeYMb3qZZjzPV+AVsj3P5x7oZFCYRb0W6n7yeUi5Dxo9UMgQPYesZttR9e4niO9FdH2VDL4uUgp9iM6gMIcsFuJ+UsgQXR/irwlwH5QyKMwCMryn1FQnT57k7/7u71i2bFljKaZYvRmSxm4YkpRhdfb3+3KGN+1jJ4UGHyksUGQf2d75zD3QyaAwi3ot1P3k85ByHzR6oJAheg5ZLcQdFV1fJYOvi5RCH6IzKMwhi4W4nxQyRNeH+GsC3AelDAqzgDpvSg0MDLBnzx5eeOEF9u3bx8c+9jHa2tr4lV/5lcZSTLF4Jazsh0LGZ7gK7XDZRlg8+482O8MsjjPCAXZRYjzT60uMs58HOc6RTK93D3QyKMxiNq2yn3weUu6DRg8UMkTPoVatsKOi66tk8HWRUuhDdAaFOdSiFfaTQobo+hB/TYD7oJRBYRZQ502pI0eO8Cu/8iusXr2af/JP/gkXX3wxTzzxBEuXLm0sxTRXDUAyke21SQnWbnWGZmV4jEHaWJTptUXa2M32huq7BzoZFGYxk1baTz4PKfdBowcKGaLnUItW2VHR9VUy+LpIKfQhOoPCHGbTKvtJIUN0fYi/JsB9UMqgMIu6bkp985vf5OjRo5w+fZojR47wzW9+k3e9612Np5hmWR9cO5jttdfenb7eGZqTYZi9PEC2k/YdbmeYvQ3Vdw90MijMYiattJ98HlLug0YPFDJEz6EWrbKjouurZPB1kVLoQ3QGhTnMplX2k0KG6PoQf02A+6CUQWEWjf0Q4xxas6XanNkeJ6t8/drB9HXO0NwMu9k+ebHM9nhh5esPsLUpd27BPVDKoDALBQp98HlIuQ8aPVDIED0HJdG9iK6vksHXRUqhD9EZFOagQqEX0Rmi60P8NQHug1KG6FnI3pQqFNJHwTbugZU3AYX01w1WfmXh5OeF9Osb96TfXyg4Q7MzQHqxDNLHAR6mTJkSE5SYIKFMiXFKTFCmzAEeZpC+pl4k7oFOBpVZRFPpg89Dyn2I74FCBoU5qIjuRXR9lQzg66Iiug/RGVTmoEChF9EZoutXRF+X7oNOhuhZZHxLq/ws60s/To7AwR0wdgjeGIPzutJfPbj61rl/8z9nSA2zl2H2soQVrONWlrKKC+jiNcZ4hUPsY0dDb7Q2G/dAJ4PCLBQo9MHnIeU+aPRAIUP0HJRE9yK6vkoGXxcphT5EZ1CYgwqFXkRniK4P8dcEuA9KGaJmIX9TqmJxD1zzWWdQyHCcIzzMXWH13QOdDAqzUKDQB5+HlPug0QOFDNFzUBLdi+j6Khl8XaQU+hCdQWEOKhR6EZ0huj7EXxPgPihlyHsWsj++Z2ZmZmZmZmZmC5dvSpmZmZmZmZmZWe58U8rMzMzMzMzMzHLnm1JmZmZmZmZmZpY735QyMzMzMzMzM7PcFZIkSfIsODY2Rnd3NxTgouV5Vk69egySMhSKcOGy/Os7gzOoZYiuD3DqKJDA6OgoXV1dMSGI30+gMY/oDNH1ncEZplPYUd5PzqBS3xm0Mng/pRRm4QzOoFJfJUOt+ynuppSZ2TQyN6XMzM5C4l/6zMzOwvvJzFTNtp/ac8xyJj8p5QzOIJEhuj5U76LL8P/S1/Jn0hmcYSqpHeX91PIZous7g1YG76eUwiycwRlU6qtkqHU/hd2UuvBSuOVI/nXvXwGnfpQOJqK+MziDWobo+gD3LU8Xp4qo/QQa84jOEF3fGZxhOqUd5f3kDNH1nUErg/dTSmEWzuAMKvVVMtS6n/xG52ZmZmZmZmZmljvflDIzMzMzMzMzs9z5ppSZmZmZmZmZmeXON6XMzMzMzMzMzCx3cb99bx46eRgO7oTRYRg/AYs6obsXVm+GxSudIc8M0RR6sIQe1rGZS+jlfDp5nRO8zDD72MlxRnLJoNAHSynMwmdSg0IPfBZsKoVZ+EzqUOhD9HlQ6IFVRc8j+jxCfA9UKPShFc+Db0rV4Oge2D8Eh3elv1IRIClBoS39/Nk74bJ+WDsAy/qcYS4zRFPoQS99rGcra+gnoQxAkSLlNz/v50728xC7GWKYvXOSQaEPllKYhc+kBoUe+CzYVAqz8JnUodCH6POg0AOrip5H9HmE+B6oUOhDK58H//jeDJIEnh+EXTfAyCNAkg4lKb359crnCRx+BB56XzrEJHGGZmeIptKD9WxlgD1cyQaKFGmjnTbaKUz5vEiRNdzEAI9zI1uaWl+lD6YzC5/JeCo98FmwCpVZ+ExqUOlD5HlQ6YGlFObh/aRBpQ+tfh58U2oGB7bDk7ennycTM39v5etPDKSvc4bmZoim0IMb2cLNDALQxqIZv7fy9U0MNXVpKfTBUgqz8JnUoNADnwWbSmEWPpM6FPoQfR4UemBV0fOIPo8Q3wMVCn3wechwU+pHP/oRH//4x7n44ou54IILWLNmDc8880xz0gg5uidtdBZPDMCxx52hWRmiKfSglz42MZTptZsYopfrG86g0IfZeD/Nzmcy5f3ks1CR51lohR2lMAufSR0KfYg+Dwo9qEUr7CeIn0f0eYT4HqhQ6IPPQ6qum1LHjx/nuuuuY9GiRTzyyCP89V//NUNDQyxZsqTxJGL2D0Eh4ztuFdrT1ztDczJEU+jBerZSYjzTa0uMN+VOukIfZuL9VBufyZT3k89CRV5noVV2lMIsfCZ1KPQh+jwo9GA2rbKfIH4e0ecR4nugQqEPPg+pusp/8YtfpKenhx07dkz+s8svv7zxFGJOHk7f3IuMPyOZTMCLD8HJEVjc4wyNZIim0IMl9LCGfooZf9q2jUWs5SMsYQXHOZLpz1Dow2y8n2rjM5nyfvJZqMjrLLTCjlKYhc+kDoU+RJ8HhR7UohX2E8TPI/o8QnwPVCj0weehqq4OPPjgg7znPe9h06ZNXHLJJVx99dV89atfzV5d1MGd1Xebz6pQhIM7Zv8+Z9Cm0IN1bJ78DQxZJZRZx62ZX6/Qh9l4P9XOZzLl/eSzUJHHWWiFHaUwC59JHQp9iD4PCj2oRSvsJ4ifR/R5hPgeqFDog89DVV0R/v7v/5577rmH3t5e/uRP/oTf+I3f4N/8m3/D17/+9XO+5vTp04yNjZ3xoW50uDl/ztghZ2g0QzSFHlxCbxMSJCxlVeZXK/RhNt5P9fGZTHk/+SxUzPVZqHdHeT9l4zOpQ6EP0edBoQe1aIX9BPHziD6PEN8DFQp98HmoquvH98rlMu95z3v4whe+AMDVV1/NX/3VX/Hf/tt/4xOf+MRZX7Nt2zb+43/8j42lzNn4ieqvP8wqKcEbDexnZ9Cg0IPz6cz8WGdFkTYuoCvz6xX6MBvvp9r5TKa8n3wWKvI4C/XuKO+nbHwmdSj0Ifo8KPSgFq2wnyB+HtHnEeJ7oEKhDz4PVXV1YdmyZfzMz/zMGf/sp3/6pzl8+PA5X3PHHXcwOjo6+TEyMpItaY4WdUKhrbE/o9AG52U/H84gQqEHr3OCcoOPdpYp8RrZt4VCH2bj/VQ7n8mU95PPQkUeZ6HeHeX9lI3PpA6FPkSfB4Ue1KIV9hPEzyP6PEJ8D1Qo9MHnoaquJ6Wuu+46Dh48eMY/+9u//Vsuu+yyc76mo6ODjo6ObOmCdDfjSTqgK/uTdM4gQqEHL9OM5yoLvEL25yoV+jAb76f6+EymvJ98Firm+izUu6O8n7LxmdSh0Ifo86DQg1q0wn6C+HlEn0eI74EKhT74PFTV9aTUb//2b/PEE0/whS98gUOHDvGNb3yD//7f/zu33XZbYynErN4MSWM3LUnKsDr7e445gwiFHuxjJ4UGH+0sUGQf2d+BTqEPs/F+qp3PZMr7yWehIo+z0Ao7SmEWPpM6FPoQfR4UelCLVthPED+P6PMI8T1QodAHn4equrrw3ve+l+9+97v84R/+IVdeeSV33XUXX/rSl7jlllsaSyFm8UpY2Q+Fup4jqyq0w2UbG/u1iM6gQaEHxxnhALsoMZ7p9SXG2c+DmX9VKGj0YTbeT7XxmUx5P/ksVOR1FlphRynMwmdSh0Ifos+DQg9q0Qr7CeLnEX0eIb4HKhT64PNQVfetuf7+fg4cOMDrr7/OD3/4Q/7Vv/pXjSUQddUAJBPZXpuUYO1WZ2hWhmgKPXiMQdpYlOm1RdrYzfaGMyj0YTbeT7PzmUx5P/ksVOR5FlphRynMwmdSh0Ifos+DQg9q0Qr7CeLnEX0eIb4HKhT64POQaux5sQVsWR9cO5jttdfenb7eGZqTIZpCD4bZywNku+K/w+0Ms7fhDAp9sJTCLHwmNSj0wGfBplKYhc+kDoU+RJ8HhR5YVfQ8os8jxPdAhUIffB5Svik1gzVbqgOa7ZG2ytevHUxf5wzNzRBNoQe72T65tGZ7zLPy9QfY2pQ76BUKfbCUwix8JjUo9MBnwaZSmIXPpA6FPkSfB4UeWFX0PKLPI8T3QIVCH3wefFNqRoVC+jjaxj2w8iagkP7Kw8qvTZz8vJB+feOe9PsLBWdodoZoKj3YzXYG6eMAD1OmTIkJSkyQUKbEOCUmKFPmAA8zSF9TlxXo9MF0ZuEzGU+lBz4LVqEyC59JDSp9iDwPKj2wlMI8vJ80qPSh1c9Dxre0ai3L+tKPkyNwcAeMHYI3xuC8rvTXH66+de7f7M0ZNCj0YJi9DLOXJaxgHbeylFVcQBevMcYrHGIfOxp6w7taKPTBUgqz8JnUoNADnwWbSmEWPpM6FPoQfR4UemBV0fOIPo8Q3wMVCn1o5fPgm1J1WNwD13zWGRQyRFPowXGO8DB3hWZQ6IOlFGbhM6lBoQc+CzaVwix8JnUo9CH6PCj0wKqi5xF9HiG+ByoU+tCK58E/vmdmZmZmZmZmZrnzTSkzMzMzMzMzM8udb0qZmZmZmZmZmVnufFPKzMzMzMzMzMxyV0iSJMmz4NjYGN3d3VCAi5bnWTn16jFIylAowoXL8q/vDM6gliG6PsCpo0ACo6OjdHV1xYQgfj+BxjyiM0TXdwZnmE5hR3k/OYNKfWfQyuD9lFKYhTM4g0p9lQy17qe4m1JmZtPI3JQyMzsLiX/pMzM7C+8nM1M1235qzzHLmfyklDM4g0SG6PpQvYsuw/9LX8ufSWdwhqmkdpT3U8tniK7vDFoZvJ9SCrNwBmdQqa+Sodb9FHZT6sJL4ZYj+de9fwWc+lE6mIj6zuAMahmi6wPctzxdnCqi9hNozCM6Q3R9Z3CG6ZR2lPeTM0TXdwatDN5PKYVZOIMzqNRXyVDrfvIbnZuZmZmZmZmZWe58U8rMzMzMzMzMzHLnm1JmZmZmZmZmZpY735QyMzMzMzMzM7Pcxf32vTotoYd1bOYSejmfTl7nBC8zzD52cpyRlslw8jAc3AmjwzB+AhZ1QncvrN4Mi1fmEiE8Q3R90DgLChkUZqFAYRYKGRTOg/ug0QOFDNFzUBI9j+j6WR4oEgAAtBdJREFUoHEe3IeUQh+iMyjMQUX0LBQyKJyH6B6A+6CUIe9ZyN+U6qWP9WxlDf0klAEoUqT85uf93Ml+HmI3Qwyzd8FmOLoH9g/B4V3pr3UESEpQaEs/f/ZOuKwf1g7Asr45iRCeIbo+aJwFhQwKs1CgMAuFDArnwX3Q6IFChug5KImeR3R90DgP7kNKoQ/RGRTmoCJ6FgoZFM5DdA/AfVDKEDUL6R/fW89WBtjDlWygSJE22mmjncKUz4sUWcNNDPA4N7JlwWVIEnh+EHbdACOPAEl6MJLSm1+vfJ7A4UfgofelBylJFk6G6PoV0WdBIYPKLBREz0Ihg8p5cB/ie6CQQWEOSqLnEV1f5Ty4D6noPkRnUJmDCp8HjfMQPQf3QSdD9Cxkb0rdyBZuZhCANhbN+L2Vr29iqKkDUshwYDs8eXv6eTIx8/dWvv7EQPq6hZIhuj5onAWFDAqzUKAwC4UMCufBfdDogUKG6DkoiZ5HdH3QOA/uQ0qhD9EZFOagInoWChkUzkN0D8B9UMoQPQvJm1K99LGJoUyv3cQQvVy/IDIc3ZMOO4snBuDY4w1HCM8QXR80zoJCBoVZKFCYhUIGhfPgPmj0QCFD9ByURM8juj5onAf3IaXQh+gMCnNQET0LhQwK5yG6B+A+KGVQmEVdN6V+6qd+ikKh8JaP2267rfEkU6xnKyXGM722xHhT7hoqZNg/BIWM7/pVaE9fP98zRNcHjbOgkEFhFrPJY0cpzEIhg8J5cB80eqCQIXoOtWiVv0NF1weN8+A+pBT6EJ1BYQ6zaZX9pJBB4TxE9wDcB6UMCrOo66bU008/zbFjxyY/HnvsMQA2bdrUeJI3LaGHNfTP+ujaubSxiLV8hCWsmNcZTh5O32BstsfnziWZgBcfgpMNvEF/dIbo+qBxFhQyKMyiFnO9oxRmoZBB4Ty4Dxo9UMgQPYdatcLfoaLrg8Z5cB9SCn2IzqAwh1q0wn5SyKBwHqJ7AO6DUgaFWUCdN6WWLl3KpZdeOvmxa9cu3vWud/G+972vsRRTrGPz5LvNZ5VQZh23zusMB3dW3/E+q0IRDu7I/vroDNH1QeMsKGRQmEUt5npHKcxCIYPCeXAfNHqgkCF6DrVqhb9DRdcHjfPgPqQU+hCdQWEOtWiF/aSQQeE8RPcA3AelDAqzAMj4oBa88cYb3HfffWzZsoVCoXDO7zt9+jSnT5+e/M9jY2Mz/rmX0Js10hQJS1mV+dUKGUaHmxABGDuU/bXRGaLrg8ZZUMigMIt61bKjvJ+yUTgP7oNGDxQyRM8hi7nYTxA/j+j6oHEe3IeUQh+iMyjMoV4LdT8pZFA4D9E9APdBKYPCLKCBNzr/4z/+Y3784x+zefPmGb9v27ZtdHd3T3709PTM+P3n00mxwfdfL9LGBXRlfr1ChvET1V/BmFVSgjdm//8Rshmi64PGWVDIoDCLetWyo7yfslE4D+6DRg8UMkTPIYu52E8QP4/o+qBxHtyHlEIfojMozKFeC3U/KWRQOA/RPQD3QSmDwiyggZtS9957Lxs2bGD58uUzft8dd9zB6Ojo5MfIyMw/cPg6Jyg3+BhbmRKvkb0zChkWdUKhraEIFNrgvOxnNDxDdH3QOAsKGRRmUa9adpT3UzYK58F90OiBQoboOWQxF/sJ4ucRXR80zoP7kFLoQ3QGhTnUa6HuJ4UMCuchugfgPihlUJgFZPzxvRdffJHdu3fzR3/0R7N+b0dHBx0dHTX/2S/TjGfICrxC9mfIFDJ0N+NpPqAr+9N84Rmi64PGWVDIoDCLetS6o7yfslE4D+6DRg8UMkTPoV5ztZ8gfh7R9UHjPLgPKYU+RGdQmEM9FvJ+UsigcB6iewDug1IGhVlAxielduzYwSWXXMKHP/zhxqqfxT52UmjwMbYCRfaR/d22FDKs3gxJYzdOScqwOvv7noVniK4PGmdBIYPCLOoxVztKYRYKGRTOg/ug0QOFDNFzqNdC/jtUdH3QOA/uQ0qhD9EZFOZQj4W8nxQyKJyH6B6A+6CUQWEWkOGmVLlcZseOHXziE5+gvT3z+6Sf03FGOMAuSoxnen2JcfbzIMc5Mq8zLF4JK/uhkLHFhXa4bCMsnv1HvGUzRNcHjbOgkEFhFrWayx2lMAuFDArnwX3Q6IFChug51GOh/x0quj5onAf3IaXQh+gMCnOo1ULfTwoZFM5DdA/AfVDKoDALyHBTavfu3Rw+fJhf+7Vfa6zyDB5jkDYWZXptkTZ2s31BZLhqAJKJbK9NSrB2a8MRwjNE1weNs6CQQWEWtZjrHaUwC4UMCufBfdDogUKG6DnUqhX+DhVdHzTOg/uQUuhDdAaFOdSiFfaTQgaF8xDdA3AflDIozKLum1If/OAHSZKEd7/73Y1XP4dh9vIA2f7bfYfbGWbvgsiwrA+uHcz22mvvTl8/3zNE1weNs6CQQWEWtZjrHaUwC4UMCufBfdDogUKG6DnUqhX+DhVdHzTOg/uQUuhDdAaFOdSiFfaTQgaF8xDdA3AflDIozKKxH2KcQ7vZPjmg2R5pq3z9AbY25W6hUoY1W6qHZLbH6ipfv3Ywfd1CyRBdHzTOgkIGhVkoUJiFQgaF8+A+aPRAIUP0HJREzyO6PmicB/chpdCH6AwKc1ARPQuFDArnIboH4D4oZYiehexNKUgHNEgfB3iYMmVKTFBigoQyJcYpMUGZMgd4mEH6mjoYlQyFQvpI3MY9sPImoJD+2sXKr26c/LyQfn3jnvT7C4WFkyG6fkX0WVDIoDILBdGzUMigch7ch/geKGRQmIOS6HlE11c5D+5DKroP0RlU5qDC50HjPETPwX3QyRA9i+a/i12TDbOXYfayhBWs41aWsooL6OI1xniFQ+xjR0Nv7jVfMizrSz9OjsDBHTB2CN4Yg/O60l/BuPrWuX8TxOgM0fVB4ywoZFCYhQKFWShkUDgP7oNGDxQyRM9BSfQ8ouuDxnlwH1IKfYjOoDAHFdGzUMigcB6iewDug1KGqFnI35SqOM4RHuauls+wuAeu+WxohPAM0fVB4ywoZFCYhQKFWShkUDgP7oNGDxQyRM9BSfQ8ouuDxnlwH1IKfYjOoDAHFdGzUMigcB6iewDug1KGvGch/eN7ZmZmZmZmZma2MPmmlJmZmZmZmZmZ5c43pczMzMzMzMzMLHe+KWVmZmZmZmZmZrnzTSkzMzMzMzMzM8tdIUmSJM+CY2NjdHd3QwEuWp5n5dSrxyApQ6EIFy7Lv74zOINahuj6AKeOAgmMjo7S1dUVE4L4/QQa84jOEF3fGZxhOoUd5f3kDCr1nUErg/dTSmEWzuAMKvVVMtS6n+JuSpmZTSNzU8rM7Cwk/qXPzOwsvJ/MTNVs+6k9xyxn8pNSzuAMEhmi60P1LroM/y99LX8mncEZppLaUd5PLZ8hur4zaGXwfkopzMIZnEGlvkqGWvdT2E2pCy+FW47kX/f+FXDqR+lgIuo7gzOoZYiuD3Df8nRxqojaT6Axj+gM0fWdwRmmU9pR3k/OEF3fGbQyeD+lFGbhDM6gUl8lQ637yW90bmZmZmZmZmZmufNNKTMzMzMzMzMzy51vSpmZmZmZmZmZWe58U8rMzMzMzMzMzHIX99v36rSEHtaxmUvo5Xw6eZ0TvMww+9jJcUai47WU6FlE13eGqpOH4eBOGB2G8ROwqBO6e2H1Zli8MpcIEhRmYSmFWURniK6vksH7qUphHqYxB2fQyOD9VBU9C0spzMEZdDLkvaPkb0r10sd6trKGfhLKABQpUn7z837uZD8PsZshhtkbGXXBi55FdH1nqDq6B/YPweFd6a8ZBUhKUGhLP3/2TrisH9YOwLK+OYkgQWEWllKYRXSG6PoqGbyfqhTmYRpzcAaNDN5PVdGzsJTCHJxBJ0PUjpL+8b31bGWAPVzJBooUaaOdNtopTPm8SJE13MQAj3MjW6IjL1jRs4iu7wypJIHnB2HXDTDyCJCkiyopvfn1yucJHH4EHnpfutiSpKkxJETPwqoUZhGdIbq+QgbvpzNFz8NSCnNwhvgM3k9nUjgPpjEHZ9DIEL2jZG9K3cgWbmYQgDYWzfi9la9vYshLaw5EzyK6vjNUHdgOT96efp5MzPy9la8/MZC+biFRmIWlFGYRnSG6vkoG76cqhXmYxhycQSOD91NV9CwspTAHZ9DJEL2j6ropVSqV+Pf//t9z+eWXc8EFF/Cud72Lu+66i6TJt/F76WMTQ5leu4kherm+qXlaWfQsous7Q9XRPenyyeKJATj2eMMRZuT91HoUZhGdIbq+Sgb1/QTeUa1GYQ7OoJHB+6kqehaWUpiDM+hkUNhRdd2U+uIXv8g999zDl7/8ZX74wx/yxS9+kf/8n/8zv/d7v9d4kinWs5US45leW2Lcd9KbKHoW0fWdoWr/EBQyvgtdoT19/Vzyfmo9CrOIzhBdXyWD+n4C76hWozAHZ9DI4P1UFT0LSynMwRl0MijsqLpuSu3bt4+PfvSjfPjDH+anfuqnuPnmm/ngBz/IU0891XiSNy2hhzX0z/ro2rm0sYi1fIQlrGhaplYVPYvo+s5QdfJw+oZ3sz3OeS7JBLz4EJycw18Y4f3UWhRmEZ0hur5Khvmwn8A7qpUozMEZNDJ4P1VFz8JSCnNwBp0MKjuqrptS69at43vf+x5/+7d/C8Dzzz/Pn//5n7Nhw4bGUkytwebJd5vPKqHMOm5tUqLWFT2L6PrOUHVwZ/U3MGRVKMLBHY39GTPxfmotCrOIzhBdXyXDfNhP4B3VShTm4AwaGbyfptQQOA+mMQdn0MmgsqPqelDrM5/5DGNjY1xxxRW0tbVRKpX4/Oc/zy233HLO15w+fZrTp09P/uexsbEZa1xCbz2RziFhKaua8Oe0tuhZRNd3hqrR4SZEAMYONefPORvvp9aiMIvoDNH1VTLMh/0E9e+oevcTaMzDNObgDBoZvJ+qomdhKYU5OINOBpUdVdd9sW9/+9vcf//9fOMb3+Av//Iv+frXv87g4CBf//rXz/mabdu20d3dPfnR09MzY43z6aTY4C8FLNLGBXQ19GdY/Cyi6ztD1fiJ6q8EzSopwRuz/50lM++n1qIwi+gM0fVVMsyH/QT176h69xNozMM05uAMGhm8n6qiZ2EphTk4g04GlR1VVxduv/12PvOZz/DP/tk/Y82aNfzzf/7P+e3f/m22bdt2ztfccccdjI6OTn6MjMz8A4evc4Jyg4+xlSnxGnO8vVtA9Cyi6ztD1aJOKLQ1FIFCG5w3h3+P8H5qLQqziM4QXV8lw3zYT1D/jqp3P4HGPExjDs6gkcH7qSp6FpZSmIMz6GRQ2VF1/fjeq6++SrF45n2strY2yuVzN7Ojo4OOjo6aa7xMM54hK/AKc/ycawuInkV0fWeo6m7G06VA1xw+ce391FoUZhGdIbq+Sob5sJ+g/h1V734CjXmYxhycQSOD91NV9CwspTAHZ9DJoLKj6npSauPGjXz+85/n4Ycf5oUXXuC73/0u27dv52Mf+1hjKabYx04KDT7GVqDIPub4HQFbQPQsous7Q9XqzZA0diOfpAyr5/C9Kb2fWovCLKIzRNdXyTAf9hN4R7UShTk4g0YG76eq6FlYSmEOzqCTQWVH1dWF3/u93+Pmm2/mk5/8JD/90z/NwMAA//pf/2vuuuuuxlJMcZwRDrCLEuOZXl9inP08yHGONC1Tq4qeRXR9Z6havBJW9kOhrmcrqwrtcNlGWDz7Ww5k5v3UWhRmEZ0hur5Khvmwn8A7qpUozMEZNDJ4P1VFz8JSCnNwBp0MKjuqrptSnZ2dfOlLX+LFF1/ktdde4+/+7u/43Oc+x3nnnddYimkeY5A2FmV6bZE2drO9qXlaWfQsous7Q9VVA5BMZHttUoK1WxuOMCPvp9ajMIvoDNH1VTKo7yfwjmo1CnNwBo0M3k9V0bOwlMIcnEEng8KOaux5sTkyzF4eINt/u+9wO8PsbXKi1hU9i+j6zlC1rA+uHcz22mvvTl+/ECjMwlIKs4jOEF1fJYP3U5XCPExjDs6gkcH7qSp6FpZSmIMz6GRQ2FGSN6UAdrN9ckCzPdJW+foDbPUd9DkQPYvo+s5QtWZLdWnN9phn5evXDqavW0gUZmEphVlEZ4iur5LB+6lKYR6mMQdn0Mjg/VQVPQtLKczBGXQyRO+ojD89mI/dbOdFnuZGtrCWj5C8+SsTixQpUwIKFChygIfZzXbfPZ9D0bOIru8MqUIhfURz6Xth/xC8+BAU3ry1nZSqv1I0KcPKm9LvXUj/C99U0bOwKoVZRGeIrq+QwfvpTNHzsJTCHJwhPoP305kUzoNpzMEZNDJE7yjpm1KQPtI2zF6WsIJ13MpSVnEBXbzGGK9wiH3s8Bve5SR6FtH1naFqWV/6cXIEDu6AsUPwxhic15X+StDVt879m3IqUJiFpRRmEZ0hur5KBu+nKoV5mMYcnEEjg/dTVfQsLKUwB2fQyRC1o+RvSlUc5wgP07zfAGHZRc8iur4zVC3ugWs+GxpBgsIsLKUwi+gM0fVVMng/VSnMwzTm4AwaGbyfqqJnYSmFOTiDToa8d5Tse0qZmZmZmZmZmdnC5ZtSZmZmZmZmZmaWO9+UMjMzMzMzMzOz3PmmlJmZmZmZmZmZ5a6QJEmSZ8HR0VHe9ra3AXDhsjwrp159CUiAAlx4af71ncEZ1DJE1wd49Vj6f3/84x/T3d0dE4L4/QQi8/CZdAZnODODwI7yfnIGlfrOIJbB+wkQmYUzOINIfZkMNe6n3G9KHTlyhJ6eFvldp2ZWl5GREVasWBFW3/vJzGYSuaO8n8xsJt5PZqZqtv2U+02pcrnM0aNH6ezspFAo1P36sbExenp6GBkZoauraw4SOsN8yRBd3xmalyFJEk6cOMHy5cspFuN+qtj7yRkWUobo+gspg8KOanQ/Qfw8ous7gzOoZfB+qoqehUKG6PrO4AzNzlDrfmpvJGQWxWKxKXfxu7q6wobjDFoZous7Q3MyRP7YXoX3kzMsxAzR9RdKhugd1az9BPHziK7vDM6glsH7qSp6FgoZous7gzM0M0Mt+8lvdG5mZmZmZmZmZrnzTSkzMzMzMzMzM8vdvLsp1dHRwX/4D/+Bjo4OZ2jxDNH1nUErgwKFPjiDM6jUdwY90b2Iru8MzqCWIbq+EoVeRGeIru8MzhCVIfc3OjczMzMzMzMzM5t3T0qZmZmZmZmZmdn855tSZmZmZmZmZmaWO9+UMjMzMzMzMzOz3PmmlJmZmZmZmZmZ5W5e3ZT6i7/4C9ra2vjwhz+ce+3NmzdTKBQmPy6++GI+9KEPsX///tyzvPTSS3zqU5/ine98Jx0dHfT09LBx40a+973vzXntqX1YtGgRP/ETP8H69ev52te+RrlcnvP60zNM/fjQhz6US/3Zchw6dCiX+i+99BKf/vSnWbVqFeeffz4/8RM/wXXXXcc999zDq6++Ouf1N2/ezC/90i+95Z//4Ac/oFAo8OMf/3jOM6jxjvJ+mp4jakdF7yeI3VHeT2/l/eT9ND2H95P/DqXC+8n7aXoO76fW2k/z6qbUvffey6c+9Skef/xxjh49mnv9D33oQxw7doxjx47xve99j/b2dvr7+3PN8MILL3DNNdfwZ3/2Z9x9990cOHCARx99lPe///3cdtttuWSo9OGFF17gkUce4f3vfz+f/vSn6e/vZ2JiItcMUz/+8A//MJfas+W4/PLL57zu3//933P11Vfzp3/6p3zhC1/gf//v/81f/MVf8G//7b9l165d7N69e84z2Fu1+o7yfnprjsgdFbWfwDtKkfeT99P0HN5P3k8qvJ+8n6bn8H5qrf3UHh2gVidPnuRb3/oWzzzzDC+99BI7d+7k3/27f5drho6ODi699FIALr30Uj7zmc9w/fXX88orr7B06dJcMnzyk5+kUCjw1FNPcdFFF03+85/92Z/l137t13LJMLUPP/mTP8nP/dzPce211/KBD3yAnTt38i//5b/MNUOkqByf/OQnaW9v55lnnjnjHLzzne/kox/9KEmS5J6p1XlHeT+dK0eUyAzeUVq8n7yfzpUjiveTVXg/eT+dK0cU76f8zZsnpb797W9zxRVXsHr1aj7+8Y/zta99LXQoJ0+e5L777mPVqlVcfPHFudT8f//v//Hoo49y2223nXFIK972trflkuNsfuEXfoGrrrqKP/qjPwrL0Cr+7//9v/zpn/7pOc8BQKFQyDmVtfqO8n6yCu8oPd5P3k+W8n7S4/3k/WSpVt5P8+am1L333svHP/5xIH2kbnR0lD179uSaYdeuXSxevJjFixfT2dnJgw8+yLe+9S2KxXzaeOjQIZIk4YorrsilXr2uuOIKXnjhhVxqTZ1F5eMLX/hCLrVnyrFp06Y5r1k5B6tXrz7jn7/jHe+YzPE7v/M7c54Dzj6HDRs25FJbTavvKO+nMynsqIj9BDo7yvupyvvJ+2kq76f4/QTeURXeT95PU3k/teZ+mhc/vnfw4EGeeuopvvvd7wLQ3t7OP/2n/5R7772XG264Ibcc73//+7nnnnsAOH78OL//+7/Phg0beOqpp7jsssvmvL7643pJkuR293bqLCre/va351J7phznuqudh6eeeopyucwtt9zC6dOnc6l5tjk8+eSTk3+5aBXeUd5P0ynsKKX9BPnvKO+nlPeT99N03k9v5b9DxfB+8n6azvvprVphP82Lm1L33nsvExMTLF++fPKfJUlCR0cHX/7yl+nu7s4lx0UXXcSqVasm//P/+B//g+7ubr761a/yuc99bs7r9/b2UigU+Ju/+Zs5r5XFD3/4w9zeBG76LKJE5Fi1ahWFQoGDBw+e8c/f+c53AnDBBRfkluVs//2PHDmSW30V3lHeT9Mp7KioDCo7yvsp5f3k/TSd91P8fgLvKPB+Au+n6byfWnM/yf/43sTEBP/zf/5PhoaGeO655yY/nn/+eZYvXx7yG9cqCoUCxWKR1157LZd6b3/72/nFX/xFvvKVr3Dq1Km3fD3y18f+2Z/9GQcOHOCXf/mXwzK0iosvvpj169fz5S9/+aznwPLlHZXyfrIK7ygd3k8p7yer8H7S4f2U8n6yilbeT/JPSu3atYvjx4/zL/7Fv3jL3fJf/uVf5t577+XXf/3Xc8ly+vRpXnrpJSB9tPPLX/4yJ0+eZOPGjbnUB/jKV77Cddddx8///M/zn/7Tf2Lt2rVMTEzw2GOPcc899/DDH/5wzjNU+lAqlfg//+f/8Oijj7Jt2zb6+/v51V/91TmvPzXDVO3t7bzjHe/IpX603//93+e6667jPe95D3feeSdr166lWCzy9NNP8zd/8zdcc8010RFbhndUlffTW3NM5R3lHZU376cq76e35pjK+8n7KW/eT1XeT2/NMZX3Uwvsp0Rcf39/ctNNN531a08++WQCJM8///yc5/jEJz6RAJMfnZ2dyXvf+97kO9/5zpzXnu7o0aPJbbfdllx22WXJeeedl/zkT/5k8pGPfCT5/ve/P+e1p/ahvb09Wbp0aXLjjTcmX/va15JSqTTn9adnmPqxevXqXOpPzfHRj34015pTHT16NPnN3/zN5PLLL08WLVqULF68OPn5n//55O67705OnTo15/XP9d//+9//fgIkx48fn/MMCryjztTq+2l6jqgdFb2fkiR2R3k/pbyfzuT95P1U4b9DxfN+OpP3k/dTRSvup0KSiL+7mpmZmZmZmZmZLTjy7yllZmZmZmZmZmYLj29KmZmZmZmZmZlZ7nxTyszMzMzMzMzMcuebUmZmZmZmZmZmljvflDIzMzMzMzMzs9z5ppSZmZmZmZmZmeXON6XMzMzMzMzMzCx3villZmZmZmZmZma5800pMzMzMzMzMzPLnW9KmZmZmZmZmZlZ7nxTyszMzMzMzMzMcuebUmZmZmZmZmZmljvflDIzMzMzMzMzs9z5ppSZmZmZmZmZmeXON6XMzMzMzMzMzCx3villZmZmZmZmZma5a8+7YLlc5ujRo3R2dlIoFPIub2aCkiThxIkTLF++nGIx7l6595OZnY3CjvJ+MrOz8X4yM1W17qfcb0odPXqUnp6evMua2TwwMjLCihUrwup7P5nZTCJ3lPeTmc3E+8nMVM22n3K/KdXZ2Tn5+YXL8q4Or74EJEABLrw0//rO4AxqGaLrA7x6LP2/U/dDhOj9BCLz8Jl0Bmc4M4PAjvJ+cgaV+s4glsH7CRCZhTM4g0h9mQw17qfcb0pVHum8cBl8/Gje1eH+FXDqR3DRcrjlSP71ncEZ1DJE1we4b3m6tKIf+Y7eT6Axj+gM0fWdwRmmU9hR3k/OoFLfGbQyeD+lFGbhDM6gUl8lQ637yW90bmZmZmZmZmZmufNNKTMzMzMzMzMzy51vSpmZmZmZmZmZWe58U8rMzMzMzMzMzHKX+xudz2dL6GEdm7mEXs6nk9c5wcsMs4+dHGcklwwnD8PBnTA6DOMnYFEndPfC6s2weGUuEcIzRNd3Bq0MlvJ+cgaV+s5g03k/OYMzaNW3M0XvKIXz4AzOEJnBN6Vq0Esf69nKGvpJKANQpEj5zc/7uZP9PMRuhhhm75xkOLoH9g/B4V1QePP5tqQEhbb082fvhMv6Ye0ALOubkwjhGaLrO4NWBkt5PzmDSn1nsOm8n5zBGbTq25mid5TCeXAGZ1DI4B/fm8V6tjLAHq5kA0WKtNFOG+0UpnxepMgabmKAx7mRLU2tnyTw/CDsugFGHgGS9GAkpTe/Xvk8gcOPwEPvSw9SkiycDNH1nUErg1V5PzmDQn1nsLPxfnIGZ9Cpb28VuaMUzoMzOINSBt+UmsGNbOFmBgFoY9GM31v5+iaGmrq0DmyHJ29PP08mZv7eytefGEhft1AyRNd3Bq0MlvJ+cgaV+s5g03k/OYMzaNW3M0XvKIXz4AzOoJTBN6XOoZc+NjGU6bWbGKKX6xvOcHRPOuwsnhiAY483HCE8Q3R9Z9DKYCnvJ2dQqe8MNp33kzM4g1Z9O1P0jlI4D87gDGoZ6r4p9fjjj7Nx40aWL19OoVDgj//4jxtPIWg9Wykxnum1Jcabcid9/xAUMr7rV6E9ff18zxBd3xm0MszG+2l23k8LK0N0fWeonffT7LyfnGEhZoiuX4tW2U8Qv6MUzoMzOINahrpvSp06dYqrrrqKr3zlK41XF7WEHtbQP+vjnOfSxiLW8hGWsCJzhpOH0zcYm+3xuXNJJuDFh+BkA78wIjpDdH1n0MpQC++n2Xk/LZwM0fWdoT7eT7PzfnKGhZYhun6tWmE/QfyOUjgPzuAMahkgw02pDRs28LnPfY6PfexjjVUWto7Nk7+BIauEMuu4NfPrD+6svuN9VoUiHNyR/fXRGaLrO4NWhlp4P9XG+2lhZIiu7wz18X6qjfeTMyykDNH1a9UK+wnid5TCeXAGZ1DLAJDxQa3anT59mtOnT0/+57Gxsbku2bBL6G3Cn5KwlFWZXz063IQIwNih7K+NzhBd3xm0MswF76dsFM6DM8TXd4a55f2UjcJ5cAZnUKk/V+bjfoL4HaVwHpzBGdQyQA5vdL5t2za6u7snP3p6eua6ZMPOp5Nig60p0sYFdGV+/fiJ6q9gzCopwRsN/P+I6AzR9Z1BK8Nc8H7KRuE8OEN8fWeYW95P2SicB2dwBpX6c2U+7ieI31EK58EZnEEtA+RwU+qOO+5gdHR08mNkZI5/KLoJXucE5QYf7SxT4jWyT2dRJxTaGopAoQ3Oy/73uvAM0fWdQSvDXPB+ykbhPDhDfH1nmFveT9konAdncAaV+nNlPu4niN9RCufBGZxBLQPk8ON7HR0ddHR0zHWZpnqZZjzHVuAVsj/H1t2Mp0uBruxPwIdniK7vDFoZ5oL3UzYK58EZ4us7w9zyfspG4Tw4gzOo1J8r83E/QfyOUjgPzuAMahkghyel5qN97KTQYGsKFNlH9nf8Wr0ZksZu5JOUYXX29woNzxBd3xm0MljK+8kZVOo7g03n/eQMzqBV384UvaMUzoMzOINaBshwU+rkyZM899xzPPfccwD8wz/8A8899xyHDx9uLImQ44xwgF2UGM/0+hLj7OdBjnMkc4bFK2FlPxQyPstWaIfLNsLiBn7EOzpDdH1n0MpQC++n2Xk/LZwM0fWdoT7eT7PzfnKGhZYhun6tWmE/QfyOUjgPzuAMahkgw02pZ555hquvvpqrr74agC1btnD11Vfz2c9+trEkYh5jkDYWZXptkTZ2s73hDFcNQDKR7bVJCdZubThCeIbo+s6glWE23k+z835aWBmi6ztD7byfZuf95AwLMUN0/Vq0yn6C+B2lcB6cwRnUMtR9U+qGG24gSZK3fOzcubPxNEKG2csDZOvwd7idYfY2nGFZH1w7mO21196dvn6+Z4iu7wxaGWbj/TQ776eFlSG6vjPUzvtpdt5PzrAQM0TXr0Wr7CeI31EK58EZnEEtg99Taga72T65tGZ7zLPy9QfY2pT/la9izZbqIZntsbrK168dTF+3UDJE13cGrQyW8n5yBpX6zmDTeT85gzNo1bczRe8ohfPgDM6glME3pWaxm+0M0scBHqZMmRITlJggoUyJcUpMUKbMAR5mkL6m/oUKoFBIH4nbuAdW3gQU0l+7WPnVjZOfF9Kvb9yTfn+hsHAyRNd3Bq0MVuX95AwK9Z3Bzsb7yRmcQae+vVXkjlI4D87gDEoZMr6lVWsZZi/D7GUJK1jHrSxlFRfQxWuM8QqH2MeOht6UsxbL+tKPkyNwcAeMHYI3xuC8rvRXMK6+de7fBDE6Q3R9Z9DKYCnvJ2dQqe8MNp33kzM4g1Z9O1P0jlI4D87gDAoZfFOqDsc5wsPcFZphcQ9c89nQCOEZous7g1YGS3k/OYNKfWew6byfnMEZtOrbmaJ3lMJ5cAZniMzgH98zMzMzMzMzM7Pc+aaUmZmZmZmZmZnlzjelzMzMzMzMzMwsd74pZWZmZmZmZmZmuSskSZLkWXBsbIzu7m4owEXL86ycevUYJGUoFOHCZfnXdwZnUMsQXR/g1FEggdHRUbq6umJCEL+fQGMe0Rmi6zuDM0ynsKO8n5xBpb4zaGXwfkopzMIZnEGlvkqGWvdT3E0pM7NpZG5KmZmdhcS/9JmZnYX3k5mpmm0/teeY5Ux+UsoZnEEiQ3R9qN5Fl+H/pa/lz6QzOMNUUjvK+6nlM0TXdwatDN5PKYVZOIMzqNRXyVDrfgq7KXXhpXDLkfzr3r8CTv0oHUxEfWdwBrUM0fUB7lueLk4VUfsJNOYRnSG6vjM4w3RKO8r7yRmi6zuDVgbvp5TCLJzBGVTqq2SodT/5jc7NzMzMzMzMzCx3villZmZmZmZmZma5800pMzMzMzMzMzPLnW9KmZmZmZmZmZlZ7nxTyszMzMzMzMzMchf22/fqtYQe1rGZS+jlfDp5nRO8zDD72MlxRpyhhTJE1wc4eRgO7oTRYRg/AYs6obsXVm+GxStzieAMQhTOpDM4Q4XCdekMWqLPZHR9Z9DKoHBtRmeIrq9E4UxGZ4iu7wxVCtdmK2aQvynVSx/r2coa+kkoA1CkSPnNz/u5k/08xG6GGGavMyzgDNH1AY7ugf1DcHgXFN58zjApQaEt/fzZO+Gyflg7AMv65iSCMwhROJPO4AwVCtelM2iJPpPR9Z1BK4PCtRmdIbq+EoUzGZ0hur4zVClcm62cQfrH99azlQH2cCUbKFKkjXbaaKcw5fMiRdZwEwM8zo1scYYFmiG6fpLA84Ow6wYYeQRI0gs0Kb359crnCRx+BB56X3pBJ4kzNDuDiugz6QzOUKFwXTqDnujrIrr+/9/e3QfJVd13/n/3zIjhQTNjGUtBikYELFnEQaIIdlYRxRjHyDFYsuMy2t0U/gWR3a1NrHidILGxtmq9ZLFRHI8oJ7HDZh0sOQWObVwhBWIhQU4slFLEk2OkbBxllAQ0ssRC7YoZiQcx031/f1xaIwSamb7d0+c7Pe9XVVcauq/Oh+/39LH65N7bZoiTIcJnM3WG1ONHk3pORsiQenwz5CJ8Ns0QeFPqGm7mevoBaGfWuO+tvr6WLQ2dqGaIkSH1+AD77oDHbsmfZ6Pjv7f6+p6N+XFmaGyGCCLMSTOYoSrC59IMsaSek6nHN0OsDBE+m6kzpB4/kghzMnWG1OObYUyEz6YZatyU2rx5M+9973vp6upi3rx5/MIv/AL79+9vTJJTLKGPtWwpdOxatrCEq8zQIhlSjw/5aYx7NhY7ds9GOPJo3RHMMAmuT2aYiRkifC7NMDkzZY1KPb4ZYmWI8NlMnSH1+JMxU9anCBlSj2+GMRE+m2bI1bQptXPnTtavX8+ePXt45JFHGBkZ4YMf/CAvvfRS/UlOsYoNlBkpdGyZkYbsnpohRobU40N+amKp4N3XSh358WZoTIbxuD6ZYSZmiPC5NMPkzJQ1KvX4ZoiVIcJnM3WG1ONPxkxZnyJkSD2+GcZE+GyaIVfT8A8//PAb/nnbtm3MmzePp556ir6+xtzpag69LGM1bQWvLGxnFsv5CHNYyFEOmWEaZ0g9PuS/PHBwO1DwetlsFJ59AI4PwuzeYn+GGSbH9ckMMy1DhM+lGSZvJqxRqcc3Q6wMET6bqTOkHn+yZsL6FCFD6vHNMCbCZ9MMY+q6p9TQ0BAAb3/72+v5Y95gJetO3nW/qIwKK7nJDNM8Q+rxIf8pzFJdn5L8+P1bix9vhmJcn8zQ6hkifC7NUFwrrlGpxzdDrAwRPpupM6Qev6hWXJ8iZEg9vhnGRPhsmmFMwRO1oFKp8Ou//utceeWVXHrppWd834kTJzhx4sTJfx4eHh73z53HkqKRTpExl8WFjzZDjAypxwcYGmhABGD4QPFjzVA71yczzIQMET6XZihmMmtUresTpJ+Tqcc3Q6wMET6bqTOkHr+IVl2fImRIPb4ZxkT4bJphTOF9sfXr1/N3f/d3fPOb3xz3fZs3b6anp+fko7d3/PO6zqar8Kl8VW20cw7dhY83Q4wMqccHGDk29lOYRWVleG3i/602QwO5PplhJmSI8Lk0QzGTWaNqXZ8g/ZxMPb4ZYmWI8NlMnSH1+EW06voUIUPq8c0wJsJn0wxjCs2GX/u1X2P79u381V/9FQsXLhz3vZs2bWJoaOjkY3BwcNz3v8oxKnWezlehzCsUr4wZYmRIPT7ArC4otdcVgVI7nFV8zTRDjVyfzDBTMkT4XJqhdpNdo2pdnyD9nEw9vhliZYjw2UydIfX4tWrl9SlChtTjm2FMhM+mGcbUdPlelmV86lOf4r777uN73/seF1100YTHdHZ20tnZOekxnqcR55CVeIHi55CZIUaG1OMD9DTi7FKgu/jZpWaYJNcnM8y0DBE+l2aYvFrXqFrXJ0g/J1OPb4ZYGSJ8NlNnSD3+ZM2E9SlChtTjm2FMhM+mGcbUdKbU+vXrufvuu/nGN75BV1cXzz33HM899xyvvPJKfSlOsZttlOo8na9EG7spfrctM8TIkHp8gKXrIKtvI5+sAkuL34fPDJPk+mSGmZYhwufSDJM3E9ao1OObIVaGCJ/N1BlSjz9ZM2F9ipAh9fhmGBPhs2mGMTXNhjvvvJOhoSGuvvpq5s+ff/LxrW99q74UpzjKIPvYTpmRQseXGWEv9xf+eUgzxMmQenyA2Ytg0WooFfxJgFIHXLimvp/INMPkuD6ZYaZliPC5NMPkzYQ1KvX4ZoiVIcJnM3WG1ONP1kxYnyJkSD2+GcZE+GyaYUxNm1JZlr3lY926dfWlOM0j9NPOrELHttHODu4wQ4tkSD0+wGUbIRstdmxWhuUb6o5ghsmM4fpkhhmYIcLn0gyTHGeGrFGpxzdDrAwRPpupM6Qef1LjzJD1KUKG1OObYUyEz6YZcvWdNzdFBtjFvRT7r/sOtzDALjO0SIbU4wPM74MV/cWOXfHF/HgzNCZDBBHmpBnMUBXhc2mGWFLPydTjmyFWhgifzdQZUo8fSYQ5mTpD6vHNMCbCZ9MMuZCbUgA7uOPkRJ3o1L7q6/eyoSG7pmaIlSH1+ADLbh77sE50emP19RX9+XFmaGyGCCLMSTOYoSrC59IMsaSek6nHN0OsDBE+m6kzpB4/kghzMnWG1OObYUyEz6YZAm9KQT5R++ljHw9SoUKZUcqMklGhzAhlRqlQYR8P0k9fQyeoGWJlSD1+qZSfmrhmJyy6DijlP39Z/QnNk89L+etrdubvL5XM0OgMUaSek2YwQ1WEz6UZ4kn9uUg9vhniZIjw2UydIfX40aSekxEypB7fDLkIn00zQMFbWjXPALsYYBdzWMhKbmIuizmHbl5hmBc4wG621nWTMzNMnwypx4f89MT5fXB8EPZvheED8NownNWd/xTm0pum/maUZogjwpw0gxmqInwuzRBL6jmZenwzxMoQ4bOZOkPq8SOJMCdTZ0g9vhnGRPhszuQM4Telqo5yiAe5zQxmSD4+5B/GKz6bNIIZAokwJ81ghqoIn0szxJJ6TqYe3wyxMkT4bKbOkHr8SCLMydQZUo9vhjERPpszMUPoy/ckSZIkSZLUmtyUkiRJkiRJUtO5KSVJkiRJkqSmc1NKkiRJkiRJTVfKsixr5oDDw8P09PRACc5b0MyRcy8fgawCpTY4d37zxzeDGaJlSD0+wEuHgQyGhobo7u5OE4L06xPE6EfqDKnHN4MZThdhjXJ9MkOU8c0QK4PrUy5CL8xghijjR8kw2fUp3aaUJJ0mzKaUJL2FEF/6JOktuD5Jimqi9amjiVneyDOlzGCGEBlSjw9ju+hh+P/pm/Fz0gxmOFWoNcr1acZnSD2+GWJlcH3KReiFGcwQZfwoGSa7PiXblDr3ArjhUPPHvWchvPSjvDEpxjeDGaJlSD0+wN0L8oUzilTrE8ToR+oMqcc3gxlOF2mNcn0yQ+rxzRArg+tTLkIvzGCGKONHyTDZ9ckbnUuSJEmSJKnp3JSSJEmSJElS07kpJUmSJEmSpKZzU0qSJEmSJElNl+7X92o0h15Wso55LOFsuniVYzzPALvZxlEGZ0yG4wdh/zYYGoCRYzCrC3qWwNJ1MHtRUyIkr0OEGpghToYIUn8momSIMB+sQ/rxzRBP6s9F6vEhxnywDmaIMn4kET4XqTNEmA+pawAx6mCGNBnCb0otoY9VbGAZq8moANBGG5XXn6/mVvbyADvYwgC7WjbD4Z2wdwsc3J7/rCNAVoZSe/78qVvhwtWwfCPM75uSCMnrEKEGZoiTIYLUn4koGSLMB+uQfnwzxJP6c5F6fIgxH6yDGaKMH0mEz0XqDBHmQ+oaQIw6mCFthtCX761iAxvZyaVcSxtttNNBOx2UTnneRhvLuI6NPMo13NxyGbIMnu6H7VfD4ENAlk+MrPz669XnGRx8CB54Xz6RsqyhMZLWIUINzBAnQxSp14YIGaLMh5leh9TjmyGm1J+L1ONHmQ/WwQwRxo8m9ecidYYo8yF1HyLUwQwxMoTdlLqGm7mefgDamTXue6uvr2VLQz8sETLsuwMeuyV/no2O/97q63s25sc1Suo6RKiBGeJkiCD1ZyJKhgjzwTqkH98M8aT+XKQeH2LMB+tghijjRxLhc5E6Q4T5kLoGEKMOZoiRIeSm1BL6WMuWQseuZQtLuKolMhzemTe7iD0b4cijdUdIXocINTBDnAwRpP5MRMkQYT5Yh/TjmyGe1J+L1ONDjPlgHcwQZfxIInwuUmeIMB9S1wBi1MEMcTLUtCl15513snz5crq7u+nu7uZnf/Zneeihh+pPcZpVbKDMSKFjy4w0ZAc3Qoa9W6BU8K5fpY78+HqlrkOEGpghTobxuD41N0OE+WAd0o9vhsmbKWtU6vEhxnywDmaIMv5kzJT1KUKGCPMhdQ0gRh3MECdDTZtSCxcu5Ld/+7d56qmnePLJJ/m5n/s5PvrRj/K///f/rj/J6+bQyzJWT3ga4Zm0M4vlfIQ5LJzWGY4fzG8wNtHpc2eSjcKzD8DxOn4sIXUdItTADHEyTMT1qXkZIswH65B+fDPUZiasUanHhxjzwTqYIcr4kzUT1qcIGSLMh9Q1gBh1MEOcDFDjptSaNWu47rrrWLJkCe9617v4/Oc/z+zZs9mzZ099KU6xknUn7/xfVEaFldw0rTPs3zZ2x/uiSm2wf2vx41PXIUINzBAnw0Rcn5qXIcJ8sA7pxzdDbWbCGpV6fIgxH6yDGaKMP1kzYX2KkCHCfEhdA4hRBzPEyQBQ8EQtKJfL3Hvvvbz00kv87M/+7Bnfd+LECU6cOHHyn4eHh8f9c+expGikU2TMZXHhoyNkGBpoQARg+EDxY1PXIUINzBAnQy1cn6Y2Q4T5YB3Sj2+G4iazRtW6PkH6z0Xq8SHGfLAOZogyfhGtuj5FyBBhPqSuAcSogxniZIACNzrft28fs2fPprOzk1/5lV/hvvvu493vfvcZ379582Z6enpOPnp7e8f988+mi7Y677/eRjvn0F34+AgZRo6N/QRjUVkZXpv4fyPOKHUdItTADHEyTIbrU3MyRJgP1iH9+GaoXS1rVK3rE6T/XKQeH2LMB+tghijj16LV16cIGSLMh9Q1gBh1MEOcDFBgU2rp0qX84Ac/4LHHHuNXf/VXufHGG/n7v//7M75/06ZNDA0NnXwMDo5/weGrHKNS5ymFFcq8QvHKRMgwqwtK7XVFoNQOZxVfL5LXIUINzBAnw2S4PjUnQ4T5YB3Sj2+G2tWyRtW6PkH6z0Xq8SHGfLAOZogyfi1afX2KkCHCfEhdA4hRBzPEyQAFLt8766yzWLw4P13viiuu4IknnuB3f/d3+cM//MO3fH9nZyednZ2T/vOfpxHnkJV4geLnkEXI0NOIMyuB7uJnViavQ4QamCFOhslwfWpOhgjzwTqkH98Mtatljap1fYL0n4vU40OM+WAdzBBl/Fq0+voUIUOE+ZC6BhCjDmaIkwEKnCl1ukql8oZriuu1m22U6oxVoo3dFL/bVoQMS9dBVt8mNlkFlha/B13yOkSogRniZCjC9WlqMkSYD9Yh/fhmqF+rrVGpx4cY88E6mCHK+PVotfUpQoYI8yF1DSBGHcwQJwPUuCm1adMmHn30UZ555hn27dvHpk2b+N73vscNN9xQX4pTHGWQfWynzEih48uMsJf7OcqhaZ1h9iJYtBpKBW9FX+qAC9fA7Ikv8T6j1HWIUAMzxMkwEden5mWIMB+sQ/rxzVCbmbBGpR4fYswH62CGKONP1kxYnyJkiDAfUtcAYtTBDHEyQI2bUs8//zy/9Eu/xNKlS/nABz7AE088wZ//+Z+zatWq+lKc5hH6aWdWoWPbaGcHd7REhss2QjZa7NisDMs31B0heR0i1MAMcTKMx/WpuRkizAfrkH58M0zeTFmjUo8PMeaDdTBDlPEnY6asTxEyRJgPqWsAMepghjgZatqUuuuuu3jmmWc4ceIEzz//PDt27Gj4YgUwwC7updh/3Xe4hQF2tUSG+X2wor/YsSu+mB9fr9R1iFADM8TJMB7Xp+ZmiDAfrEP68c0weTNljUo9PsSYD9bBDFHGn4yZsj5FyBBhPqSuAcSogxniZKj7nlJTZQd3nPywTHR6YfX1e9nQkJ3bSBmW3Tw2SSY6ra76+or+/LhGSV2HCDUwQ5wMEaT+TETJEGE+WIf045shntSfi9TjQ4z5YB3MEGX8SCJ8LlJniDAfUtcAYtTBDDEyhN2UgvzD0k8f+3iQChXKjFJmlIwKZUYoM0qFCvt4kH76GvohiZKhVMpPiVuzExZdB5Tyn12s/nTjyeel/PU1O/P3l0oNjZG0DhFqYIY4GaJIvTZEyBBlPsz0OqQe3wwxpf5cpB4/ynywDmaIMH40qT8XqTNEmQ+p+xChDmaIkaHgLa2aZ4BdDLCLOSxkJTcxl8WcQzevMMwLHGA3W+u60dp0yTC/L38cH4T9W2H4ALw2DGd15z/BuPSmqb8JYuo6RKiBGeJkiCD1ZyJKhgjzwTqkH98M8aT+XKQeH2LMB+tghijjRxLhc5E6Q4T5kLoGEKMOZkibIfymVNVRDvEgt834DLN74YrPJo2QvA4RamCGOBkiSP2ZiJIhwnywDunHN0M8qT8XqceHGPPBOpghyviRRPhcpM4QYT6krgHEqIMZ0mQIffmeJEmSJEmSWpObUpIkSZIkSWo6N6UkSZIkSZLUdG5KSZIkSZIkqenclJIkSZIkSVLTlbIsy5o54PDwMD09PVCC8xY0c+Tcy0cgq0CpDc6d3/zxzWCGaBlSjw/w0mEgg6GhIbq7u9OEIP36BDH6kTpD6vHNYIbTRVijXJ/MEGV8M8TK4PqUi9ALM5ghyvhRMkx2fUq3KSVJpwmzKSVJbyHElz5JeguuT5Kimmh96mhiljfyTCkzmCFEhtTjw9guehj+f/pm/Jw0gxlOFWqNcn2a8RlSj2+GWBlcn3IRemEGM0QZP0qGya5PyTalzr0AbjjU/HHvWQgv/ShvTIrxzWCGaBlSjw9w94J84Ywi1foEMfqROkPq8c1ghtNFWqNcn8yQenwzxMrg+pSL0AszmCHK+FEyTHZ98kbnkiRJkiRJajo3pSRJkiRJktR0bkpJkiRJkiSp6dyUkiRJkiRJUtOl+/W9Gs2hl5WsYx5LOJsuXuUYzzPAbrZxlMGmZDh+EPZvg6EBGDkGs7qgZwksXQezFzUlQog6pM6QenxwLlRFqEME9iIXoQ5mcC5URahDFKn7EaEXqWtghjHOhxg1iCJ1LyB9PyLUwAy51HMBZmYdwm9KLaGPVWxgGavJqADQRhuV15+v5lb28gA72MIAu6Ykw+GdsHcLHNye/6QiQFaGUnv+/Klb4cLVsHwjzO+bkggh6pA6Q+rxwblQFaEOEdiLXIQ6mMG5UBWhDlGk7keEXqSugRnGOB9i1CCK1L2A9P2IUAMz5FLPBZjZdQh9+d4qNrCRnVzKtbTRRjsdtNNB6ZTnbbSxjOvYyKNcw80NHT/L4Ol+2H41DD4EZHlTsvLrr1efZ3DwIXjgfXkTs6yhMZLXIUKG1OM7F3JR6hCBvcilroMZnAtVUeoQhXMy/Zw0Q875EKcGUTgn09fADLkIcwGsQ9hNqWu4mevpB6CdWeO+t/r6WrY0tEH77oDHbsmfZ6Pjv7f6+p6N+XGNEqEOqTOkHh+cC1UR6hCBvchFqIMZnAtVEeoQRep+ROhF6hqYYYzzIUYNokjdC0jfjwg1MEMu9VwA6wB1bkr99m//NqVSiV//9V9vTJrXLaGPtWwpdOxatrCEq+rOcHhnXugi9myEI4/WHSFEHVJnSD0+OBeqItShFq5Pb62V5qQZnAtVEepQi6lanyB9PyL0InUNzDDG+RCjBrXy71BvrRH9iFADM+RSzwWwDlWFN6WeeOIJ/vAP/5Dly5fXn+I0q9hAmZFCx5YZaciu4d4tUCp4x61SR358vSLUIXWG1OODc6EqQh0my/XpzFppTprBuVAVoQ6TNZXrE6TvR4RepK6BGcY4H2LUoBb+HerMGtGPCDUwQy71XADrUFVoU+r48ePccMMNfPWrX2XOnDn1pzjFHHpZxuoJT107k3ZmsZyPMIeFhTMcP5jf3GuiU9fOJBuFZx+A43XcHD9CHVJnSD0+OBeqItRhslyfxtcqc9IMzoWqCHWYrKlcnyB9PyL0InUNzDDG+RCjBrXw71Djq7cfEWpghlzquQDW4VSFNqXWr1/Phz/8Ya655pr6Rn8LK1l38m7zRWVUWMlNhY/fv23sbvNFldpg/9bix0eoQ+oMqccH50JVhDpMluvTxFphTprBuVAVoQ6TNZXrE6TvR4RepK6BGcY4H2LUoBb+HWpi9fQjQg3MkEs9F8A6nKrmE7W++c1v8v3vf58nnnhiUu8/ceIEJ06cOPnPw8PD475/HktqjfQWMuayuPDRQwMNiAAMHyh+bIQ6pM6QenxwLlRFqMNkuD5N3nSfk2ZwLlRFqMNkTPX6BOn7EaEXqWtghjHOhxg1mKxa1qjpuD5B+n5EqIEZcqnnAliHU9W0LzY4OMinP/1p7rnnHs4+++xJHbN582Z6enpOPnp7e8d9/9l00VbnjwK20c45dBc+fuTY2M8fFpWV4bWJ1+czilCH1BlSjw/OhaoIdZiI69PktcKcNINzoSpCHSbSjPUJ0vcjQi9S18AMY5wPMWowGbWuUdNxfYL0/YhQAzPkUs8FsA6nqqkKTz31FM8//zw//dM/TUdHBx0dHezcuZPf+73fo6Ojg3L5zf9FmzZtYmho6ORjcHD8Cw5f5RiVOk9jq1DmFYpXZlYXlNrrikCpHc4qPj9C1CF1htTjg3OhKkIdJuL6NHmtMCfN4FyoilCHiTRjfYL0/YjQi9Q1MMMY50OMGkxGrWvUdFyfIH0/ItTADLnUcwGsw6lqunzvAx/4APv27XvDv7vpppu45JJL+M3f/E3a29/8X9TZ2UlnZ+ekx3ieRpxDVuIFip9D1tOIM+mA7uJn0oWoQ+oMqccH50JVhDpMxPWpNtN9TprBuVAVoQ4Tacb6BOn7EaEXqWtghjHOhxg1mIxa16jpuD5B+n5EqIEZcqnnAliHU9V0plRXVxeXXnrpGx7nnXce559/Ppdeeml9SV63m22U6jyNrUQbuyl+t62l6yCrb9OSrAJLi99zLEQdUmdIPT44F6oi1GEirk+T1wpz0gzOhaoIdZhIM9YnSN+PCL1IXQMzjHE+xKjBZPh3qMmrpx8RamCGXOq5ANbhVHXea73xjjLIPrZTZqTQ8WVG2Mv9HOVQ4QyzF8Gi1VCq+TbwuVIHXLgGZk98efUZRahD6gypxwfnQlWEOkRgL3IR6mAG50JVhDpEkbofEXqRugZmGON8iFGDKFL3AtL3I0INzJBLPRfAOpyq7k2p733ve3zpS1+q9495g0fop51ZhY5to50d3FF3hss2QjZa7NisDMs31B0hRB1SZ0g9PjgXqiLUoVauT2/WSnPSDM6Fqgh1qNVUrE+Qvh8RepG6BmYY43yIUYMi/DvUmzWiHxFqYIZc6rkA1qEq3JlSAAPs4l6K/dd9h1sYYFfdGeb3wYr+Yseu+GJ+fL0i1CF1htTjg3OhKkIdIrAXuQh1MINzoSpCHaJI3Y8IvUhdAzOMcT7EqEEUqXsB6fsRoQZmyKWeC2AdqkJuSgHs4I6TDZrolLbq6/eyoSG7hVXLbh5r0ESntFVfX9GfH9coEeqQOkPq8cG5UBWhDhHYi1yEOpjBuVAVoQ5RpO5HhF6kroEZxjgfYtQgitS9gPT9iFADM+RSzwWwDhB4UwryBvXTxz4epEKFMqOUGSWjQpkRyoxSocI+HqSfvoY2BqBUyk9HW7MTFl0HlPKfPKz+bOLJ56X89TU78/eXSg2NkbwOETKkHt+5kItShwjsRS51HczgXKiKUoconJPp56QZcs6HODWIwjmZvgZmyEWYC2AdCt7SqnkG2MUAu5jDQlZyE3NZzDl08wrDvMABdrO1rpt7Tcb8vvxxfBD2b4XhA/DaMJzVnf/84dKbpv4GhBHqkDpD6vHBuVAVoQ4R2ItchDqYwblQFaEOUaTuR4RepK6BGcY4H2LUIIrUvYD0/YhQAzPkUs8FmNl1CL8pVXWUQzzIbUkzzO6FKz6bNEKIOqTOkHp8cC5URahDBPYiF6EOZnAuVEWoQxSp+xGhF6lrYIYxzocYNYgidS8gfT8i1MAMudRzAWZmHUJfvidJkiRJkqTW5KaUJEmSJEmSms5NKUmSJEmSJDWdm1KSJEmSJElqulKWZVkzBxweHqanpwdKcN6CZo6ce/kIZBUotcG585s/vhnMEC1D6vEBXjoMZDA0NER3d3eaEKRfnyBGP1JnSD2+GcxwughrlOuTGaKMb4ZYGVyfchF6YQYzRBk/SobJrk/pNqUk6TRhNqUk6S2E+NInSW/B9UlSVBOtTx1NzPJGnillBjOEyJB6fBjbRQ/D/0/fjJ+TZjDDqUKtUa5PMz5D6vHNECuD61MuQi/MYIYo40fJMNn1Kdmm1LkXwA2Hmj/uPQvhpR/ljUkxvhnMEC1D6vEB7l6QL5xRpFqfIEY/UmdIPb4ZzHC6SGuU65MZUo9vhlgZXJ9yEXphBjNEGT9KhsmuT97oXJIkSZIkSU3nppQkSZIkSZKazk0pSZIkSZIkNZ2bUpIkSZIkSWq6dL++V6PjB2H/NhgagJFjMKsLepbA0nUwe5EZmplhDr2sZB3zWMLZdPEqx3ieAXazjaMMTvn41iBOhgi9iCBCLyJkiDAfrEOMGkTIkLoPkaTuR4ReRMiQug9gHaJkiNCHKFL3AtL3I/X4EKMPZoiTodlzMvym1OGdsHcLHNye/5whQFaGUnv+/Klb4cLVsHwjzO8zw1RmWEIfq9jAMlaTUQGgjTYqrz9fza3s5QF2sIUBdjV8fGsQJ0OEXkQQoRcRMkSYD9YhRg0iZEjdh0hS9yNCLyJkSN0HsA5RMkToQxSpewHp+5F6fIjRBzPEyZBqToa9fC/L4Ol+2H41DD4EZHlBsvLrr1efZ3DwIXjgfXkBs8wMjc4AsIoNbGQnl3ItbbTRTgftdFA65XkbbSzjOjbyKNdwc8PGtgZxMkTpRQSpexEhQ5T5YB3S1yBChgh9iGSm/+92hAzg56IqdR1SZ4jShyhSz4fU/Ug9flXqPpghTobUczLsptS+O+CxW/Ln2ej4762+vmdjfpwZGpvhGm7mevoBaGfWuO+tvr6WLQ37sFiDOBki9CKCCL2IkCHCfLAOMWoQIUPqPkSSuh8RehEhQ+o+gHWIkiFCH6JI3QtI34/U40OMPpghTobUczLkptThnfl/ZBF7NsKRR83QqAxL6GMtWwodu5YtLOGqusa3BnEyROhFBBF6ESFDhPlgHWLUIEKG1H2IJHU/IvQiQobUfQDrECVDhD5EkboXkL4fqceHGH0wQ5wMEeZkTZtSt956K6VS6Q2PSy65pP4Up9m7BUoF73ZV6siPN0NjMqxiA2VGCh1bZqTuHVxrECdDhF6Mp1nrU4ReRMgQYT5Yhxg1iJAhdR8mY6asURF6ESFD6j6AdYiSIUIfJjJT1idI34/U40OMPpghToYIc7LmM6V+6qd+iiNHjpx8/PVf/3X9KU5x/GB+Y62JThs7k2wUnn0AjtdxY3oz5ObQyzJWT3ga4Zm0M4vlfIQ5LCx0vDWIkyFCLyZjqtenCL2IkCHCfLAOMWoQIUPqPtSi1deoCL2IkCF1H8A6RMkQoQ+T1errE6TvR+rxIUYfzBAnQ4Q5CQU2pTo6OrjgggtOPt7xjnfUl+A0+7eN3em9qFIb7N9qhnozrGTdyTv/F5VRYSU3FTrWGsTJEKEXkzHV61OEXkTIEGE+WIcYNYiQIXUfatHqa1SEXkTIkLoPYB2iZIjQh8lq9fUJ0vcj9fgQow9miJMhwpyEAptSAwMDLFiwgIsvvpgbbriBgwcPjvv+EydOMDw8/IbHeIYGak301oYPFD/WDLl5LGlAgoy5LC50pDWIkyFCLyZjqtenCL2IkCHCfLAOMWoQIUPqPtSiljWq1vUJ0vcjQi8iZEjdB7AOUTJE6MNktfr6BOn7kXp8iNEHM8TJEGFOQo2bUv/qX/0rtm3bxsMPP8ydd97Jv/zLv3DVVVdx7NixMx6zefNmenp6Tj56e3vHHWPk2NhPDxaVleG1iddGM0zgbLpoq/Ne+G20cw7dhY61BnEyROjFRJqxPkXoRYQMEeaDdYhRgwgZUvdhsmpdo2pdnyB9PyL0IkKG1H0A6xAlQ4Q+TMZMWJ8gfT9Sjw8x+mCGOBkizEmocVPq2muvZe3atSxfvpyf//mf53/9r//Fiy++yLe//e0zHrNp0yaGhoZOPgYHx7/gcFYXlNprSfVmpXY4q3hvzPC6VzlGpc5TCiuUeYVis9QaxMkQoRcTacb6FKEXETJEmA/WIUYNImRI3YfJqnWNqnV9gvT9iNCLCBlS9wGsQ5QMEfowGTNhfYL0/Ug9PsTogxniZIgwJwEK3mc997a3vY13vetdHDhw5vO1Ojs76ezsnPSf2dOIs9iA7uJnsZnhdc/TiPP5SrxAsfP5rEGcDBF6UaupWJ8i9CJChgjzwTrEqEGEDKn7UNREa1St6xOk70eEXkTIkLoPYB2iZIjQhyJacX2C9P1IPT7E6IMZ4mSIMCehwD2lTnX8+HH+6Z/+ifnz59eX4hRL10FW34YhWQWWFr/flxlet5ttlOo8pbBEG7spduczaxAnQ4Re1Goq1qcIvYiQIcJ8sA4xahAhQ+o+FNWKa1SEXkTIkLoPYB2iZIjQhyJacX2C9P1IPT7E6IMZ4mSIMCehxk2pjRs3snPnTp555hl2797Nxz72Mdrb2/nFX/zF+lKcYvYiWLQaSgXP4Sp1wIVrYPbElzabYQJHGWQf2ykzUuj4MiPs5X6OcqjQ8dYgToYIvZhIM9anCL2IkCHCfLAOMWoQIUPqPkzWTFijIvQiQobUfQDrECVDhD5MxkxYnyB9P1KPDzH6YIY4GSLMSahxU+rQoUP84i/+IkuXLuVf/+t/zfnnn8+ePXuYO3dufSlOc9lGyEaLHZuVYfkGMzQqwyP0086sQse20c4O7qhrfGsQJ0OEXoynWetThF5EyBBhPliHGDWIkCF1HyZjpqxREXoRIUPqPoB1iJIhQh8mMlPWJ0jfj9TjQ4w+mCFOhghzsqZNqW9+85scPnyYEydOcOjQIb75zW/yzne+s/4Up5nfByv6ix274ov58WZoTIYBdnEvxWbad7iFAXbVNb41iJMhQi/G06z1KUIvImSIMB+sQ4waRMiQug+TMVPWqAi9iJAhdR/AOkTJEKEPE5kp6xOk70fq8SFGH8wQJ0OEOVnfRYxTaNnNY8WZ6HSy6usr+vPjzNDYDDu44+SHZaLTC6uv38uGhuzcgjWIlCFCLyKI0IsIGSLMB+sQowYRMqTuQySp+xGhFxEypO4DWIcoGSL0IYrUvYD0/Ug9PsTogxniZEg9J8NuSpVK+alga3bCouuAUv5zg9WfLDz5vJS/vmZn/v5SyQyNzgD5h6WfPvbxIBUqlBmlzCgZFcqMUGaUChX28SD99DX0Q2IN4mSI0osIUvciQoYo88E6pK9BhAwR+hDJTP/f7QgZwM9FVeo6pM4QpQ9RpJ4PqfuRevyq1H0wQ5wMqedkwVtaNc/8vvxxfBD2b4XhA/DaMJzVnf/04NKbpv7mf2bIDbCLAXYxh4Ws5Cbmsphz6OYVhnmBA+xma103WpuINYiTIUIvIojQiwgZIswH6xCjBhEypO5DJKn7EaEXETKk7gNYhygZIvQhitS9gPT9SD0+xOiDGeJkSDUnw29KVc3uhSs+a4YIGY5yiAe5Ldn41iBOhgi9iCBCLyJkiDAfrEOMGkTIkLoPkaTuR4ReRMiQug9gHaJkiNCHKFL3AtL3I/X4EKMPZoiTodlzMuzle5IkSZIkSWpdbkpJkiRJkiSp6dyUkiRJkiRJUtO5KSVJkiRJkqSmc1NKkiRJkiRJTVfKsixr5oDDw8P09PRACc5b0MyRcy8fgawCpTY4d37zxzeDGaJlSD0+wEuHgQyGhobo7u5OE4L06xPE6EfqDKnHN4MZThdhjXJ9MkOU8c0QK4PrUy5CL8xghijjR8kw2fUp3aaUJJ0mzKaUJL2FEF/6JOktuD5Jimqi9amjiVneyDOlzGCGEBlSjw9ju+hh+P/pm/Fz0gxmOFWoNcr1acZnSD2+GWJlcH3KReiFGcwQZfwoGSa7PiXblDr3ArjhUPPHvWchvPSjvDEpxjeDGaJlSD0+wN0L8oUzilTrE8ToR+oMqcc3gxlOF2mNcn0yQ+rxzRArg+tTLkIvzGCGKONHyTDZ9ckbnUuSJEmSJKnp3JSSJEmSJElS07kpJUmSJEmSpKZzU0qSJEmSJElNl+7X96ah4wdh/zYYGoCRYzCrC3qWwNJ1MHtRczLMoZeVrGMeSzibLl7lGM8zwG62cZTBpmSIUIfUItTAuRBHhF6YIeecjFED50IsqfsRoRepawAx6hBBhDqkng8RahBF6l5A+n5EqIEZzHCqZn8m3JSahMM7Ye8WOLg9/0lFgKwMpfb8+VO3woWrYflGmN83NRmW0McqNrCM1WRUAGijjcrrz1dzK3t5gB1sYYBdU5IhQh1Si1AD50IcEXphhpxzMkYNnAuxpO5HhF6krgHEqEMEEeqQej5EqEEUqXsB6fsRoQZmMMOpUn0mvHxvHFkGT/fD9qth8CEgy5uSlV9/vfo8g4MPwQPvy5uYZY3NsYoNbGQnl3ItbbTRTgftdFA65XkbbSzjOjbyKNdwc0PHj1KHlKLUwLkQR+pemCHnnIxTA+dCLCn7EaUXzskYotTBz0QcfjbT18AMZjhV6s+Em1Lj2HcHPHZL/jwbHf+91df3bMyPa5RruJnr6QegnVnjvrf6+lq2NHSiRqhDahFq4FyII0IvzJBzTsaogXMhltT9iNCL1DWAGHWIIEIdUs+HCDWIInUvIH0/ItTADGY4VerPRM2bUj/60Y/4xCc+wfnnn88555zDsmXLePLJJxuTJpDDO/NCF7FnIxx5tP4MS+hjLVsKHbuWLSzhqrozRKhDahFq4FyYnGasTxF6YYbcdJiTUy1CDZwLkzcT1qgIvUhdA4hRhwgi1CH1fIhQg8mYCesTpO9HhBqYwQynSv2ZgBo3pY4ePcqVV17JrFmzeOihh/j7v/97tmzZwpw5c+pPEszeLVAqeMetUkd+fL1WsYEyI4WOLTPSkN3TCHVILUINnAsTa9b6FKEXZshFn5PNEKEGzoXJmSlrVIRepK4BxKhDBBHqkHo+RKjBRGbK+gTp+xGhBmYww6lSfyagxhudf+ELX6C3t5etW7ee/HcXXXRR/SmCOX4wv7kXBa+RzEbh2Qfg+CDM7i32Z8yhl2Wspq3gFZbtzGI5H2EOCznKoUJ/RoQ6pBahBs6FyWnG+hShF2bITYc5OdUi1MC5MHkzYY2K0IvUNYAYdYggQh1Sz4cINZiMmbA+Qfp+RKiBGcxwqtSfiaqaKnD//ffznve8h7Vr1zJv3jwuv/xyvvrVrxYfPaj928buNl9UqQ32b534fWeyknUn77pfVEaFldxU+PgIdUgtQg2cC5PTjPUpQi/MkJsOc3KqRaiBc2HyZsIaFaEXqWsAMeoQQYQ6pJ4PEWowGTNhfYL0/YhQAzOY4VSpPxNVNUX453/+Z+68806WLFnCn//5n/Orv/qr/Kf/9J/4+te/fsZjTpw4wfDw8Bse0Q0NNObPGT5Q/Nh5LGlAgoy5LC58dIQ6pBahBs6FyWnG+hShF2bITYc5OdUi1MC5MHm1rlFF/v6Uuh8RepG6BhCjDhFEqEPq+RChBpMxE9YnSN+PCDUwgxlOlfozUVXT5XuVSoX3vOc93H777QBcfvnl/N3f/R3/43/8D2688ca3PGbz5s381m/9Vn0pm2zk2NjPHxaVleG1Ovbfzqar8Kl8VW20cw7dhY+PUIfUItTAuTA5zVifIvTCDLnpMCenWoQaOBcmr9Y1qsjfn1L3I0IvUtcAYtQhggh1SD0fItRgMmbC+gTp+xGhBmYww6lSfyaqaqrC/Pnzefe73/2Gf/eTP/mTHDx48IzHbNq0iaGhoZOPwcHBYkmbaFYXlNrr+zNK7XBW8fnBqxyjUufpfBXKvELxGRKhDqlFqIFzYXKasT5F6IUZctNhTk61CDVwLkxerWtUkb8/pe5HhF6krgHEqEMEEeqQej5EqMFkzIT1CdL3I0INzGCGU6X+TFTVdKbUlVdeyf79+9/w7/7xH/+RCy+88IzHdHZ20tnZWSxdIj2NOJMO6C5+Jh3P04hz6Uq8QPFz6SLUIbUINXAuTE4z1qcIvTBDbjrMyakWoQbOhcmrdY0q8ven1P2I0IvUNYAYdYggQh1Sz4cINZiMmbA+Qfp+RKiBGcxwqtSfiaqazpT6jd/4Dfbs2cPtt9/OgQMH+MY3vsH//J//k/Xr19eXIpil6yCrb9OSrAJLi99zjN1so1Tn6Xwl2thN8buORahDahFq4FyYnGasTxF6YYbcdJiTUy1CDZwLkzcT1qgIvUhdA4hRhwgi1CH1fIhQg8mYCesTpO9HhBqYwQynSv2ZqKqpCu9973u57777+JM/+RMuvfRSbrvtNr70pS9xww031JcimNmLYNFqKNV0HtmYUgdcuKa+n0U8yiD72E6ZkULHlxlhL/cX/nlIiFGH1CLUwLkwOc1YnyL0wgy56TAnp1qEGjgXJm8mrFERepG6BhCjDhFEqEPq+RChBpMxE9YnSN+PCDUwgxlOlfozUVXz1tzq1avZt28fr776Kj/84Q/5D//hP9SXIKjLNkI2WuzYrAzLN9Sf4RH6aWdWoWPbaGcHd9SdIUIdUotQA+fC5DRjfYrQCzPkpsOcnGoRauBcmLyZsEZF6EXqGkCMOkQQoQ6p50OEGkzGTFifIH0/ItTADGY4VerPBBTYlJop5vfBiv5ix674Yn58vQbYxb0U6/J3uIUBdtWdIUIdUotQA+dCHBF6YYacczJGDZwLsaTuR4RepK4BxKhDBBHqkHo+RKhBFKl7Aen7EaEGZjDDqVJ/JsBNqXEtu3msQROd0lZ9fUV/flyj7OCOkxN1olP7qq/fy4aG7JpWRahDahFq4FyII0IvzJBzTsaogXMhltT9iNCL1DWAGHWIIEIdUs+HCDWIInUvIH0/ItTADGY4VerPhJtS4yiV8tPR1uyERdcBpfwnD6s/m3jyeSl/fc3O/P2lUmNz7OAO+uljHw9SoUKZUcqMklGhzAhlRqlQYR8P0k9fQycoxKlDSlFq4FyII3UvzJBzTsapgXMhlpT9iNIL52QMUergZyIOP5vpa2AGM5wq9Wei4C2tZpb5ffnj+CDs3wrDB+C1YTirO//5w6U3Tf0NCAfYxQC7mMNCVnITc1nMOXTzCsO8wAF2s7Wum5xNRoQ6pBahBs6FOCL0wgw552SMGjgXYkndjwi9SF0DiFGHCCLUIfV8iFCDKFL3AtL3I0INzGCGU6X6TLgpVYPZvXDFZ9NmOMohHuS2pBki1CG1CDVwLsQRoRdmyDknY9TAuRBL6n5E6EXqGkCMOkQQoQ6p50OEGkSRuheQvh8RamAGM5yq2Z8JL9+TJEmSJElS07kpJUmSJEmSpKZzU0qSJEmSJElN56aUJEmSJEmSmq6UZVnWzAGHh4fp6emBEpy3oJkj514+AlkFSm1w7vzmj28GM0TLkHp8gJcOAxkMDQ3R3d2dJgTp1yeI0Y/UGVKPbwYznC7CGuX6ZIYo45shVgbXp1yEXpjBDFHGj5JhsutTuk0pSTpNmE0pSXoLIb70SdJbcH2SFNVE61NHE7O8kWdKmcEMITKkHh/GdtHD8P/TN+PnpBnMcKpQa5Tr04zPkHp8M8TK4PqUi9ALM5ghyvhRMkx2fUq2KXXuBXDDoeaPe89CeOlHeWNSjG8GM0TLkHp8gLsX5AtnFKnWJ4jRj9QZUo9vBjOcLtIa5fpkhtTjmyFWBtenXIRemMEMUcaPkmGy65M3OpckSZIkSVLTuSklSZIkSZKkpnNTSpIkSZIkSU3nppQkSZIkSZKaLt2v79VoDr2sZB3zWMLZdPEqx3ieAXazjaMMzpgMxw/C/m0wNAAjx2BWF/QsgaXrYPaipkRIXgdrECdDhF5EEKEXETJEmA/WIUYNImRI3YdIUvcjQi8iZEjdB7AOUTJE6EMUqXsB6fuRenywD1UR6hAhQ7N7EX5Tagl9rGIDy1hNRgWANtqovP58NbeylwfYwRYG2NWyGQ7vhL1b4OD2/GcdAbIylNrz50/dCheuhuUbYX7flERIXgdrECdDhF5EEKEXETJEmA/WIUYNImRI3YdIUvcjQi8iZEjdB7AOUTJE6EMUqXsB6fuRenywD1UR6hAhQ6pehL58bxUb2MhOLuVa2mijnQ7a6aB0yvM22ljGdWzkUa7h5pbLkGXwdD9svxoGHwKyfGJk5ddfrz7P4OBD8MD78omUZQ2NkbQO1iBOhii9iCB1LyJkiDIfrEP6GkTIEKEPkcz0/92OkAH8XFSlrkPqDFH6EEXq+ZC6H6nHr5rpfahKXYcIGVL3Iuym1DXczPX0A9DOrHHfW319LVsa2qAIGfbdAY/dkj/PRsd/b/X1PRvz4xoldR2sQZwMEXoRQYReRMgQYT5Yhxg1iJAhdR8iSd2PCL2IkCF1H8A6RMkQoQ9RpO4FpO9H6vHBPlRFqEOEDKl7EXJTagl9rGVLoWPXsoUlXNUSGQ7vzJtdxJ6NcOTRuiMkr4M1iJMhQi8iiNCLCBkizAfrEKMGETKk7kMkqfsRoRcRMqTuA1iHKBki9CGK1L2A9P1IPT7Yh6oIdYiQIUIvatqU+omf+AlKpdKbHuvXr68/ySlWsYEyI4WOLTPSkF3DCBn2boFSwbt+lTry4+uVug7WIE6GCL2YSDPWqAi9iJAhwnywDjFqECFD6j5Mxkz5O1SEXkTIkLoPYB2iZIjQh4nMlPUJ0vcj9fhgH6oi1CFChgi9qGlT6oknnuDIkSMnH4888ggAa9eurT/J6+bQyzJWT3jq2pm0M4vlfIQ5LJzWGY4fzG8wNtHpc2eSjcKzD8DxOm7Qn7oO1iBOhgi9mIypXqMi9CJChgjzwTrEqEGEDKn7MFkz4e9QEXoRIUPqPoB1iJIhQh8mYyasT5C+H6nHB/tQFaEOETJE6AXUuCk1d+5cLrjggpOP7du38853vpP3ve999aU4xUrWnbzbfFEZFVZy07TOsH/b2B3viyq1wf6txY9PXQdrECdDhF5MxlSvURF6ESFDhPlgHWLUIEKG1H2YrJnwd6gIvYiQIXUfwDpEyRChD5MxE9YnSN+P1OODfaiKUIcIGSL0AqDgiVrw2muvcffdd3PzzTdTKpXO+L4TJ05w4sSJk/88PDw87p87jyVFI50iYy6LCx8dIcPQQAMiAMMHih+bug7WIE6GCL2o1WTWKNenYiLMB+sQowYRMqTuQxFTsT5B+n5E6EWEDKn7ANYhSoYIfahVq65PkL4fqccH+1AVoQ4RMkToBdRxo/M/+7M/48UXX2TdunXjvm/z5s309PScfPT29o77/rPpoq3O+6+30c45dBc+PkKGkWNjP8FYVFaG1yb+34gzSl0HaxAnQ4Re1Goya5TrUzER5oN1iFGDCBlS96GIqVifIH0/IvQiQobUfQDrECVDhD7UqlXXJ0jfj9Tjg32oilCHCBki9ALq2JS66667uPbaa1mwYMG479u0aRNDQ0MnH4OD419w+CrHqNR5GluFMq9QvDIRMszqglJ7XREotcNZxedo8jpYgzgZIvSiVpNZo1yfiokwH6xDjBpEyJC6D0VMxfoE6fsRoRcRMqTuA1iHKBki9KFWrbo+Qfp+pB4f7ENVhDpEyBChF1Dw8r1nn32WHTt28Kd/+qcTvrezs5POzs5J/9nP04hzyEq8QPFzyCJk6GnE2XxAd/Gz+ZLXwRrEyRChF7WY7Brl+lRMhPlgHWLUIEKG1H2o1VStT5C+HxF6ESFD6j6AdYiSIUIfatHK6xOk70fq8cE+VEWoQ4QMEXoBBc+U2rp1K/PmzePDH/5wfaO/hd1so1TnaWwl2thN8bttRciwdB1k9W2cklVgafH7niWvgzWIkyFCL2oxVWtUhF5EyBBhPliHGDWIkCF1H2rVyn+HitCLCBlS9wGsQ5QMEfpQi1ZenyB9P1KPD/ahKkIdImSI0AsosClVqVTYunUrN954Ix0dhe+TfkZHGWQf2ykzUuj4MiPs5X6OcmhaZ5i9CBathlLBEpc64MI1MHviS7zPKHUdrEGcDBF6MVlTuUZF6EWEDBHmg3WIUYMIGVL3oRat/neoCL2IkCF1H8A6RMkQoQ+T1errE6TvR+rxwT5URahDhAwRegEFNqV27NjBwYMH+eVf/uX6Rh7HI/TTzqxCx7bRzg7uaIkMl22EbLTYsVkZlm+oO0LyOliDOBki9GIypnqNitCLCBkizAfrEKMGETKk7sNkzYS/Q0XoRYQMqfsA1iFKhgh9mIyZsD5B+n6kHh/sQ1WEOkTIEKEXNW9KffCDHyTLMt71rnfVP/oZDLCLeyn2X/cdbmGAXS2RYX4frOgvduyKL+bH1yt1HaxBnAwRejEZU71GRehFhAwR5oN1iFGDCBlS92GyZsLfoSL0IkKG1H0A6xAlQ4Q+TMZMWJ8gfT9Sjw/2oSpCHSJkiNCL+i5inEI7uONkgyY6pa36+r1saMhuYaQMy24emyQTnVZXfX1Ff35co6SugzWIkyFCLyKI0IsIGSLMB+sQowYRMqTuQySp+xGhFxEypO4DWIcoGSL0IYrUvYD0/Ug9PtiHqgh1iJAhdS/CbkpB3qB++tjHg1SoUGaUMqNkVCgzQplRKlTYx4P009fQxkTJUCrlp8St2QmLrgNK+c8uVn+68eTzUv76mp35+0ulhsZIWgdrECdDlF5EkLoXETJEmQ/WIX0NImSI0IdIZvr/bkfIAH4uqlLXIXWGKH2IIvV8SN2P1ONXzfQ+VKWuQ4QMqXvR+LvYNdgAuxhgF3NYyEpuYi6LOYduXmGYFzjAbrbWdXOv6ZJhfl/+OD4I+7fC8AF4bRjO6s5/gnHpTVN/E8TUdbAGcTJE6EUEEXoRIUOE+WAdYtQgQobUfYgkdT8i9CJChtR9AOsQJUOEPkSRuheQvh+pxwf7UBWhDhEypOpF+E2pqqMc4kFum/EZZvfCFZ9NGiF5HaxBnAwRehFBhF5EyBBhPliHGDWIkCF1HyJJ3Y8IvYiQIXUfwDpEyRChD1Gk7gWk70fq8cE+VEWoQ4QMze5F6Mv3JEmSJEmS1JrclJIkSZIkSVLTuSklSZIkSZKkpnNTSpIkSZIkSU3nppQkSZIkSZKarpRlWdbMAYeHh+np6YESnLegmSPnXj4CWQVKbXDu/OaPbwYzRMuQenyAlw4DGQwNDdHd3Z0mBOnXJ4jRj9QZUo9vBjOcLsIa5fpkhijjmyFWBtenXIRemMEMUcaPkmGy61O6TSlJOk2YTSlJegshvvRJ0ltwfZIU1UTrU0cTs7yRZ0qZwQwhMqQeH8Z20cPw/9M34+ekGcxwqlBrlOvTjM+QenwzxMrg+pSL0AszmCHK+FEyTHZ9SrYpde4FcMOh5o97z0J46Ud5Y1KMbwYzRMuQenyAuxfkC2cUqdYniNGP1BlSj28GM5wu0hrl+mSG1OObIVYG16dchF6YwQxRxo+SYbLrkzc6lyRJkiRJUtO5KSVJkiRJkqSmc1NKkiRJkiRJTeemlCRJkiRJkpou3a/v1WgOvaxkHfNYwtl08SrHeJ4BdrONowymjtc0xw/C/m0wNAAjx2BWF/QsgaXrYPaimZEh9fhmiJUhAtenXIT5YIb045shntRrVIRemMEMkTKkHj+S1OsTpO9H6vHNYIbUGcJvSi2hj1VsYBmryagA0EYbldefr+ZW9vIAO9jCALtSRp1Sh3fC3i1wcHv+s44AWRlK7fnzp26FC1fD8o0wv681M6Qe3wyxMkTg+pSLMB/MkH58M8STeo2K0AszmCFShtTjR5J6fYL0/Ug9vhnMECVD6Mv3VrGBjezkUq6ljTba6aCdDkqnPG+jjWVcx0Ye5RpuTh254bIMnu6H7VfD4ENAlk+MrPz669XnGRx8CB54Xz6Rsqx1MqQe3wyxMkTh+hRjPpgh/fhmiCnlGhWhF2YwQ6QMqcePJvXfoVL3I/X4ZjBDtAxhN6Wu4Waupx+AdmaN+97q62vZ0nJf/PbdAY/dkj/PRsd/b/X1PRvz41olQ+rxzRArQwSuT7kI88EM6cc3Qzyp16gIvTCDGSJlSD1+JKnXJ0jfj9Tjm8EM0TLUtClVLpf5r//1v3LRRRdxzjnn8M53vpPbbruNrMHb+EvoYy1bCh27li0s4aqG5knl8M682UXs2QhHHp3+GVKPb4ZYGcbj+tRcEeaDGdKPb4bJmylrVIRemMEMkTKkHn8yZsr6BOn7kXp8M5ghYoaaNqW+8IUvcOedd/LlL3+ZH/7wh3zhC1/gd37nd/j93//9+pOcYhUbKDNS6NgyIy1zNsLeLVDqKHZsqSM/frpnSD2+GWJlGI/rU3NFmA9mSD++GSZvpqxREXphBjNEypB6/MmYKesTpO9H6vHNYIaIGWralNq9ezcf/ehH+fCHP8xP/MRPcP311/PBD36Qxx9/vP4kr5tDL8tYPeHpnGfSziyW8xHmsLBhmVI4fjC/wdhEp8+dSTYKzz4Ax+v40YrUGVKPb4ZYGSbi+tQ8EeaDGdKPb4bazIQ1KkIvzGCGSBlSjz9ZM2F9gvT9SD2+GcwQMQPUuCm1cuVKvvvd7/KP//iPADz99NP89V//Nddee219KU4dg3Unf4GhqIwKK7mpQYnS2L9t7I73RZXaYP/W6Zsh9fhmiJVhIq5PzRNhPpgh/fhmqM1MWKMi9MIMZoiUIfX4kzUT1idI34/U45vBDBEzANR0otZnPvMZhoeHueSSS2hvb6dcLvP5z3+eG2644YzHnDhxghMnTpz85+Hh4XHHmMeSWiKdQcZcFjfgz0lnaKAxf87wgembIfX4ZoiVYSKuT80TYT6YIf34ZqhNrWtUresTpF+jIvTCDGaIlCH1+JM1E9YnSN+P1OObwQwRM0CNZ0p9+9vf5p577uEb3/gG3//+9/n6179Of38/X//61894zObNm+np6Tn56O3tHXeMs+mirc4fBWyjnXPoruvPSG3k2NhPMBaVleG1if83ImyG1OObIVaGibg+NU+E+WCG9OOboTa1rlG1rk+Qfo2K0AszmCFShtTjT9ZMWJ8gfT9Sj28GM0TMADVuSt1yyy185jOf4d/+23/LsmXL+P/+v/+P3/iN32Dz5s1nPGbTpk0MDQ2dfAwOjn/B4asco1LnqZ0VyrzCFK/eU2xWF5Ta6/szSu1wVh3ffVNnSD2+GWJlmIjrU/NEmA9mSD++GWpT6xpV6/oE6deoCL0wgxkiZUg9/mTNhPUJ0vcj9fhmMEPEDFDj5Xsvv/wybW1v3Mdqb2+nUjnzAtPZ2UlnZ+ekx3ieRpxDVuIFpvg81ynW04gzXIHuOq4SSp0h9fhmiJVhIq5PzRNhPpgh/fhmqE2ta1St6xOkX6Mi9MIMZoiUIfX4kzUT1idI34/U45vBDBEzQI1nSq1Zs4bPf/7zPPjggzzzzDPcd9993HHHHXzsYx+rL8UpdrONUp2ndpZoYzdTfEfAKbZ0HWT1/T8TyCqwtI77KafOkHp8M8TKMBHXp+aJMB/MkH58M9RmJqxREXphBjNEypB6/MmaCesTpO9H6vHNYIaIGaDGTanf//3f5/rrr+eTn/wkP/mTP8nGjRv5j//xP3LbbbfVl+IURxlkH9spM1Lo+DIj7OV+jnKoYZlSmL0IFq2GUk3nso0pdcCFa2D2xJd4h82QenwzxMowEden5okwH8yQfnwz1GYmrFERemEGM0TKkHr8yZoJ6xOk70fq8c1ghogZoMZNqa6uLr70pS/x7LPP8sorr/BP//RPfO5zn+Oss86qL8VpHqGfdmYVOraNdnZwR0PzpHLZRshGix2blWH5humfIfX4ZoiVYTyuT80VYT6YIf34Zpi8mbJGReiFGcwQKUPq8SdjpqxPkL4fqcc3gxkiZqjvHMopMsAu7qXYf913uIUBdjU4URrz+2BFf7FjV3wxP366Z0g9vhliZYjA9SkXYT6YIf34Zogn9RoVoRdmMEOkDKnHjyT1+gTp+5F6fDOYIWKGkJtSADu44+SiNdFpntXX72VDy5yFULXs5rFJMtFpddXXV/Tnx7VKhtTjmyFWhghcn3IR5oMZ0o9vhnhSr1ERemEGM0TKkHr8SFKvT5C+H6nHN4MZomUIuykF+aLVTx/7eJAKFcqMUmaUjAplRigzSoUK+3iQfvpa7gsfQKmUnxK3Zicsug4o5T+7WP3pxpPPS/nra3bm7y+VWidD6vHNECtDFK5PMeaDGdKPb4aYUq5REXphBjNEypB6/GhS/x0qdT9Sj28GM0TLUPCWVs0zwC4G2MUcFrKSm5jLYs6hm1cY5gUOsJut0/6mwZMxvy9/HB+E/Vth+AC8Ngxndec/wbj0pqm/CWLqDKnHN0OsDBG4PuUizAczpB/fDPGkXqMi9MIMZoiUIfX4kaRenyB9P1KPbwYzRMkQflOq6iiHeJDbUsdIbnYvXPHZmZ0h9fhmiJUhAtenXIT5YIb045shntRrVIRemMEMkTKkHj+S1OsTpO9H6vHNYIbUGUJfvidJkiRJkqTW5KaUJEmSJEmSms5NKUmSJEmSJDWdm1KSJEmSJElqulKWZVkzBxwaGuJtb3sbAOfOb+bIuZefAzKgBOde0PzxzWCGaBlSjw/w8pH8/7744ov09PSkCUH69QmC9MM5aQYzvDFDgDXK9ckMUcY3Q7AMrk9AkF6YwQxBxg+TYZLrU9M3pQ4dOkRv7wz5rVNJNRkcHGThwoXJxnd9kjSelGuU65Ok8bg+SYpqovWp6ZtSlUqFw4cP09XVRalUqvn44eFhent7GRwcpLu7ewoSmmG6ZEg9vhkalyHLMo4dO8aCBQtoa0t3VbHrkxlaKUPq8VspQ4Q1qt71CdL3I/X4ZjBDtAyuT2NS9yJChtTjm8EMjc4w2fWpo56QRbS1tTVkF7+7uztZc8wQK0Pq8c3QmAwpL9urcn0yQytmSD1+q2RIvUY1an2C9P1IPb4ZzBAtg+vTmNS9iJAh9fhmMEMjM0xmffJG55IkSZIkSWo6N6UkSZIkSZLUdNNuU6qzs5P/9t/+G52dnWaY4RlSj2+GWBkiiFAHM5ghyvhmiCd1LVKPbwYzRMuQevxIItQidYbU45vBDKkyNP1G55IkSZIkSdK0O1NKkiRJkiRJ05+bUpIkSZIkSWo6N6UkSZIkSZLUdG5KSZIkSZIkqemm1abU3/zN39De3s6HP/zhpo+9bt06SqXSycf555/Phz70Ifbu3dv0LM899xyf+tSnuPjii+ns7KS3t5c1a9bw3e9+d8rHPrUOs2bN4sd+7MdYtWoVX/va16hUKlM+/ukZTn186EMfasr4E+U4cOBAU8Z/7rnn+PSnP83ixYs5++yz+bEf+zGuvPJK7rzzTl5++eUpH3/dunX8wi/8wpv+/fe+9z1KpRIvvvjilGeIxjXK9en0HKnWqNTrE6Rdo1yf3sz1yfXp9ByuT/4dKgrXJ9en03O4Ps2s9WlabUrdddddfOpTn+LRRx/l8OHDTR//Qx/6EEeOHOHIkSN897vfpaOjg9WrVzc1wzPPPMMVV1zBX/7lX/LFL36Rffv28fDDD/P+97+f9evXNyVDtQ7PPPMMDz30EO9///v59Kc/zerVqxkdHW1qhlMff/Inf9KUsSfKcdFFF035uP/8z//M5Zdfzl/8xV9w++2387d/+7f8zd/8Df/5P/9ntm/fzo4dO6Y8g95spq9Rrk9vzpFyjUq1PoFrVESuT65Pp+dwfXJ9isL1yfXp9ByuTzNrfepIHWCyjh8/zre+9S2efPJJnnvuObZt28Z/+S//pakZOjs7ueCCCwC44IIL+MxnPsNVV13FCy+8wNy5c5uS4ZOf/CSlUonHH3+c88477+S//6mf+il++Zd/uSkZTq3Dj//4j/PTP/3TrFixgg984ANs27aNf//v/31TM6SUKscnP/lJOjo6ePLJJ98wDy6++GI++tGPkmVZ0zPNdK5Rrk9nypFKygyuUbG4Prk+nSlHKq5PqnJ9cn06U45UXJ+ab9qcKfXtb3+bSy65hKVLl/KJT3yCr33ta0mbcvz4ce6++24WL17M+eef35Qx/9//+388/PDDrF+//g2TtOptb3tbU3K8lZ/7uZ/jsssu40//9E+TZZgp/u///b/8xV/8xRnnAUCpVGpyKs30Ncr1SVWuUfG4Prk+Kef6FI/rk+uTcjN5fZo2m1J33XUXn/jEJ4D8lLqhoSF27tzZ1Azbt29n9uzZzJ49m66uLu6//36+9a1v0dbWnDIeOHCALMu45JJLmjJerS655BKeeeaZpox1ai+qj9tvv70pY4+XY+3atVM+ZnUeLF269A3//h3veMfJHL/5m7855Tngrftw7bXXNmXsaGb6GuX69EYR1qgU6xPEWaNcn8a4Prk+ncr1Kf36BK5RVa5Prk+ncn2amevTtLh8b//+/Tz++OPcd999AHR0dPBv/s2/4a677uLqq69uWo73v//93HnnnQAcPXqUP/iDP+Daa6/l8ccf58ILL5zy8aOfrpdlWdN2b0/tRdXb3/72pow9Xo4z7Wo3w+OPP06lUuGGG27gxIkTTRnzrfrw2GOPnfzLxUzhGuX6dLoIa1Sk9Qmav0a5PuVcn1yfTuf69Gb+HSoN1yfXp9O5Pr3ZTFifpsWm1F133cXo6CgLFiw4+e+yLKOzs5Mvf/nL9PT0NCXHeeedx+LFi0/+8x/90R/R09PDV7/6VT73uc9N+fhLliyhVCrxD//wD1M+VhE//OEPm3YTuNN7kUqKHIsXL6ZUKrF///43/PuLL74YgHPOOadpWd7qv//QoUNNGz8K1yjXp9NFWKNSZYiyRrk+5VyfXJ9O5/qUfn0C1yhwfQLXp9O5Ps3M9Sn85Xujo6P88R//MVu2bOEHP/jBycfTTz/NggULkvziWlWpVKKtrY1XXnmlKeO9/e1v5+d//uf5yle+wksvvfSm11P+fOxf/uVfsm/fPj7+8Y8nyzBTnH/++axatYovf/nLbzkP1FyuUTnXJ1W5RsXh+pRzfVKV61Mcrk851ydVzeT1KfyZUtu3b+fo0aP8u3/37960W/7xj3+cu+66i1/5lV9pSpYTJ07w3HPPAfmpnV/+8pc5fvw4a9asacr4AF/5yle48sor+Zmf+Rn++3//7yxfvpzR0VEeeeQR7rzzTn74wx9OeYZqHcrlMv/n//wfHn74YTZv3szq1av5pV/6pSkf/9QMp+ro6OAd73hHU8ZP7Q/+4A+48sorec973sOtt97K8uXLaWtr44knnuAf/uEfuOKKK1JHnDFco8a4Pr05x6lco1yjms31aYzr05tznMr1yfWp2Vyfxrg+vTnHqVyfZsD6lAW3evXq7LrrrnvL1x577LEMyJ5++ukpz3HjjTdmwMlHV1dX9t73vjf7zne+M+Vjn+7w4cPZ+vXrswsvvDA766yzsh//8R/PPvKRj2R/9Vd/NeVjn1qHjo6ObO7cudk111yTfe1rX8vK5fKUj396hlMfS5cubcr4p+b46Ec/2tQxT3X48OHs137t17KLLroomzVrVjZ79uzsZ37mZ7IvfvGL2UsvvTTl45/pv/+v/uqvMiA7evTolGeIwDXqjWb6+nR6jlRrVOr1KcvSrlGuTznXpzdyfXJ9qvLvUOm5Pr2R65PrU9VMXJ9KWRb87mqSJEmSJElqOeHvKSVJkiRJkqTW46aUJEmSJEmSms5NKUmSJEmSJDWdm1KSJEmSJElqOjelJEmSJEmS1HRuSkmSJEmSJKnp3JSSJEmSJElS07kpJUmSJEmSpKZzU0qSJEmSJElN56aUJEmSJEmSms5NKUmSJEmSJDWdm1KSJEmSJElqOjelJEmSJEmS1HRuSkmSJEmSJKnp3JSSJEmSJElS07kpJUmSJEmSpKbraPaAlUqFw4cP09XVRalUavbwkgLKsoxjx46xYMEC2trcK5ckSZKkmaDpm1KHDx+mt7e32cNKmgYGBwdZuHBh6hiSJEmSpCZo+qZUV1fXyefnzm/26PDyc0AGlODcC5o/vhnMEC1D6vEBXj6S/99T1wdJkiRJUmtr+qZU9ZK9c+fDJw43e3S4ZyG89CM4bwHccKj545vBDNEypB4f4O4F+caUl/RKkiRJ0szhzVskSZIkSZLUdG5KSZIkSZIkqenclJIkSZIkSVLTuSklSZIkSZKkpmv6jc6LOn4Q9m+DoQEYOQazuqBnCSxdB7MXmWEmZUg9vhliZZAkSZIkTU/hN6UO74S9W+Dgdii9fl5XVoZSe/78qVvhwtWwfCPM7zNDK2dIPb4ZYmWQJEmSJE1vYS/fyzJ4uh+2Xw2DDwFZ/qU3K7/+evV5Bgcfggfel39JzjIztFqG1OObIVYGSZIkSVJrCLspte8OeOyW/Hk2Ov57q6/v2ZgfZ4bWypB6fDPEyiBJkiRJag0hN6UO78y/yBaxZyMcedQMrZIh9fhmiJVBkiRJktQ6at6UevTRR1mzZg0LFiygVCrxZ3/2Zw0PtXcLlAre7arUkR9vhtbIkHp8M8TKIEmSJElqHTVvSr300ktcdtllfOUrX5mKPBw/mN88eaJLg84kG4VnH4Djg2aY7hlSj2+GWBkkSZIkSa2l5k2pa6+9ls997nN87GMfm4o87N829mteRZXaYP9WM0z3DKnHN0OsDJIkSZKk1lLwYpzJO3HiBCdOnDj5z8PDw+O+f2igMeMOHyh+rBliZEg9vhliZZAkSZIktZYpv9H55s2b6enpOfno7e0d9/0jx8Z+Xr6orAyvjb/3ZYZpkCH1+GaIlUGSJEmS1FqmfFNq06ZNDA0NnXwMDo5/U5lZXVBqr2/MUjuc1V38eDPEyJB6fDPEyiBJkiRJai1TfvleZ2cnnZ2dk35/z5LGjNu9uPixZoiRIfX4ZoiVQZIkSZLUWqb8TKlaLV0HWaW+PyOrwNKbzDDdM6Qe3wyxMkiSJEmSWkvNm1LHjx/nBz/4AT/4wQ8A+Jd/+Rd+8IMfcPDgwYYEmr0IFq2GUsFzuEodcOEamD3+ravMMA0ypB7fDLEySJIkSZJaS82bUk8++SSXX345l19+OQA333wzl19+OZ/97GcbFuqyjZCNFjs2K8PyDWZolQypxzdDrAySJEmSpNZR86bU1VdfTZZlb3ps27atYaHm98GK/mLHrvhifrwZWiND6vHNECuDJEmSJKl1hLunVNWym8e+AE90yVD19RX9+XFmaK0Mqcc3Q6wMkiRJkqTWEHZTqlTKL/dZsxMWXQeU8p+Ur/4s/cnnpfz1NTvz95dKZmi1DKnHN0OsDJIkSZKk1lDwtsXNM78vfxwfhP1bYfgAvDYMZ3XnPy+/9Kapv3myGWJkSD2+GWJlkCRJkiRNb+E3papm98IVjbuXuhmmcYbU45shVgZJkiRJ0vQU9vI9SZIkSZIktS43pSRJkiRJktR0bkpJkiRJkiSp6dyUkiRJkiRJUtOVsizLmjng8PAwPT09UILzFjRz5NzLRyCrQKkNzp3f/PHNYIZoGVKPD/DSYSCDoaEhuru704SQJEmSJDVVuk0pSTqNm1KSJEmSNHN0JBvZM6XMYIYQGVKPD2NnSkmSJEmSZo5km1LnXgA3HGr+uPcshJd+lH/5TjG+GcwQLUPq8QHuXpBvjkmSJEmSZg5vdC5JkiRJkqSmc1NKkiRJkiRJTeemlCRJkiRJkprOTSlJkiRJkiQ1nZtSkiRJkiRJarpkv75Xqzn0spJ1zGMJZ9PFqxzjeQbYzTaOMtiUDMcPwv5tMDQAI8dgVhf0LIGl62D2oqZECFGH1BlSjw8x5oIZJEmSJEnTWfhNqSX0sYoNLGM1GRUA2mij8vrz1dzKXh5gB1sYYNeUZDi8E/ZugYPbofT6uWVZGUrt+fOnboULV8PyjTC/b0oihKhD6gypx4cYc8EMkiRJkqRWEPryvVVsYCM7uZRraaONdjpop4PSKc/baGMZ17GRR7mGmxs6fpbB0/2w/WoYfAjI8i/eWfn116vPMzj4EDzwvvyLepY1NEbyOkTIkHr8CHPBDJIkSZKkVhJ2U+oabuZ6+gFoZ9a4762+vpYtDd2M2HcHPHZL/jwbHf+91df3bMyPa5QIdUidIfX4EGMumEGSJEmS1Epq2pTavHkz733ve+nq6mLevHn8wi/8Avv37294qCX0sZYthY5dyxaWcFXdGQ7vzL9MF7FnIxx5tO4IIeqQOkPq8SHGXDCDJEmSJKnV1LQptXPnTtavX8+ePXt45JFHGBkZ4YMf/CAvvfRSQ0OtYgNlRgodW2akIWfI7N0CpYJ33Cp15MfXK0IdUmdIPT7EmAtmkCRJkiS1mpq+Yj788MNv+Odt27Yxb948nnrqKfr6GnM34zn0sozVtBW8srCdWSznI8xhIUc5VOjPOH4wv4EzBe+Dk43Csw/A8UGY3Vvsz4hQh9QZUo8PMeaCGSRJkiRJraiue0oNDQ0B8Pa3v70hYQBWsu7kL6sVlVFhJTcVPn7/trFfFCuq1Ab7txY/PkIdUmdIPT7EmAtmkCRJkiS1ooIX40ClUuHXf/3XufLKK7n00kvP+L4TJ05w4sSJk/88PDw87p87jyVFI50iYy6LCx89NNCACMDwgeLHRqhD6gypx4cYc8EMkiRJkqRWVPjch/Xr1/N3f/d3fPOb3xz3fZs3b6anp+fko7d3/Gt3zqar8OVaVW20cw7dhY8fOTb2E/dFZWV4bfz9t3FFqEPqDKnHhxhzwQySJEmSpFZU6Bv/r/3ar7F9+3b+6q/+ioULF4773k2bNjE0NHTyMTg4OO77X+UYlTov2apQ5hWKf/ud1QWl9roiUGqHs4rvhYSoQ+oMqceHGHPBDJIkSZKkVlTT5XtZlvGpT32K++67j+9973tcdNFFEx7T2dlJZ2fnpMd4nkZcJ1TiBYpfJ9TTiKvGgO7iV42FqEPqDKnHhxhzwQySJEmSpFZU05lS69ev5+677+Yb3/gGXV1dPPfcczz33HO88sorDQu0m22U6rxkq0Qbuyl+R+Wl6yCr7wQdsgosLX5/7RB1SJ0h9fgQYy6YQZIkSZLUimr6xn/nnXcyNDTE1Vdfzfz5808+vvWtbzUs0FEG2cd2yowUOr7MCHu5n6McKpxh9iJYtBpKBW8DX+qAC9fA7PFvnzWuCHVInSH1+BBjLphBkiRJktSKatqUyrLsLR/r1q1raKhH6KedWYWObaOdHdxRd4bLNkI2WuzYrAzLN9QdIUQdUmdIPT7EmAtmkCRJkiS1mvqujZoiA+ziXop9g/0OtzDArrozzO+DFf3Fjl3xxfz4ekWoQ+oMqceHGHPBDJIkSZKkVhNyUwpgB3ec3IyY6PKt6uv3sqEhZ8ZULbt57Ev4RJctVV9f0Z8f1ygR6pA6Q+rxIcZcMIMkSZIkqZWE3ZSCfDOinz728SAVKpQZpcwoGRXKjFBmlAoV9vEg/fQ1dBMCoFTKLzlasxMWXQeU8p+1L7W//nr1eSl/fc3O/P2lUkNjJK9DhAypx48wF8wgSZIkSWolBW9b3DwD7GKAXcxhISu5ibks5hy6eYVhXuAAu9la142sJ2N+X/44Pgj7t8LwAXhtGM7qzn/ifulNU38D5wh1SJ0h9fgQYy6YQZIkSZLUCsJvSlUd5RAPclvSDLN74YrPJo0Qog6pM6QeH2LMBTNIkiRJkqaz0JfvSZIkSZIkqTW5KSVJkiRJkqSmc1NKkiRJkiRJTeemlCRJkiRJkpqulGVZ1swBh4eH6enpgRKct6CZI+dePgJZBUptcO785o9vBjNEy5B6fICXDgMZDA0N0d3dnSaEJEmSJKmp0m1KSdJp3JSSJEmSpJmjI9nInillBjOEyJB6fBg7U0qSJEmSNHMk25Q69wK44VDzx71nIbz0o/zLd4rxzWCGaBlSjw9w94J8c0ySJEmSNHN4o3NJkiRJkiQ1nZtSkiRJkiRJajo3pSRJkiRJktR0bkpJkiRJkiSp6dL9+l6N5tDLStYxjyWcTRevcoznGWA32zjK4IzJcPwg7N8GQwMwcgxmdUHPEli6DmYvakqE5HWIUAMzxMkgSZIkSZqewm9KLaGPVWxgGavJqADQRhuV15+v5lb28gA72MIAu1o2w+GdsHcLHNwOpdfPb8vKUGrPnz91K1y4GpZvhPl9UxIheR0i1MAMcTJIkiRJkqa30JfvrWIDG9nJpVxLG22000E7HZROed5GG8u4jo08yjXc3HIZsgye7oftV8PgQ0CWf/nPyq+/Xn2ewcGH4IH35ZsFWdbQGEnrEKEGZoiTQZIkSZLUGsJuSl3DzVxPPwDtzBr3vdXX17KloZshETLsuwMeuyV/no2O/97q63s25sc1Suo6RKiBGeJkkCRJkiS1hpCbUkvoYy1bCh27li0s4aqWyHB4Z/6Fvog9G+HIo3VHSF6HCDUwQ5wMkiRJkqTWUdOm1J133sny5cvp7u6mu7ubn/3Zn+Whhx5qeKhVbKDMSKFjy4w05AydCBn2boFSwbt+lTry4+uVug4RamCGOBkkSZIkSa2jpk2phQsX8tu//ds89dRTPPnkk/zcz/0cH/3oR/nf//t/NyzQHHpZxuoJLxM7k3ZmsZyPMIeF0zrD8YP5TaQnukTqTLJRePYBOF7Hj+GlrkOEGpghTgZJkiRJUmupaVNqzZo1XHfddSxZsoR3vetdfP7zn2f27Nns2bOnYYFWsu7kL7sVlVFhJTdN6wz7t439qllRpTbYv7X48anrEKEGZoiTQZIkSZLUWgpejAPlcpl7772Xl156iZ/92Z894/tOnDjBiRMnTv7z8PDwuH/uPJYUjXSKjLksLnx0hAxDAw2IAAwfKH5s6jpEqIEZ4mSQJEmSJLWWms992LdvH7Nnz6azs5Nf+ZVf4b777uPd7373Gd+/efNmenp6Tj56e3vH/fPPpou2Ou+/3kY759Bd+PgIGUaOQVauKwJZGV4bfw9wXKnrEKEGZoiTQZIkSZLUWmrecVi6dCk/+MEPeOyxx/jVX/1VbrzxRv7+7//+jO/ftGkTQ0NDJx+Dg+PfVOZVjlGp85KxCmVeofi33wgZZnVBqb2uCJTa4azi+2LJ6xChBmaIk0GSJEmS1FpqvnzvrLPOYvHi/HKsK664gieeeILf/d3f5Q//8A/f8v2dnZ10dnZO+s9/nkZcJ1TiBYpfJxQhQ08jrpwDuotfQZi8DhFqYIY4GSRJkiRJraXOWxdDpVJ5wz2j6rWbbZTqjFWijd0Uv6NyhAxL10FW30lKZBVYWvxe68nrEKEGZoiTQZIkSZLUWmracdi0aROPPvoozzzzDPv27WPTpk1873vf44YbbmhYoKMMso/tlBkpdHyZEfZyP0c5NK0zzF4Ei1ZDqeCt6EsdcOEamD3+LbzGlboOEWpghjgZJEmSJEmtpaZNqeeff55f+qVfYunSpXzgAx/giSee4M///M9ZtWpVQ0M9Qj/tzCp0bBvt7OCOlshw2UbIRosdm5Vh+Ya6IySvQ4QamCFOBkmSJElS66hpU+quu+7imWee4cSJEzz//PPs2LGj4RtSAAPs4l6KfYP9DrcwwK6WyDC/D1b0Fzt2xRfz4+uVug4RamCGOBkkSZIkSa2j7ntKTZUd3HFyM2Siy8eqr9/LhoacoRQpw7KbxzYCJrp0qvr6iv78uEZJXYcINTBDnAySJEmSpNYQdlMK8s2QfvrYx4NUqFBmlDKjZFQoM0KZUSpU2MeD9NPX0M2gKBlKpfyypzU7YdF1QAlK7fkDTnleyl9fszN/f6nU0BhJ6xChBmaIk0GSJEmS1BoK3ra4eQbYxQC7mMNCVnITc1nMOXTzCsO8wAF2s7WuG4pPlwzz+/LH8UHYvxWGD8Brw3BWN3Qvzn/VbKpvIp26DhFqYIY4GSRJkiRJ01v4TamqoxziQW6b8Rlm98IVn00aIXkdItTADHEySJIkSZKmp9CX70mSJEmSJKk1uSklSZIkSZKkpnNTSpIkSZIkSU3nppQkSZIkSZKazk0pSZIkSZIkNV0py7KsmQMODw/T09MDJThvQTNHzr18BLIKlNrg3PnNH98MZoiWIfX4AC8dBjIYGhqiu7s7TQhJkiRJUlOl25SSpNO4KSVJkiRJM0dHspE9U8oMZgiRIfX4MHamlCRJkiRp5ki2KXXuBXDDoeaPe89CeOlH+ZfvFOObwQzRMqQeH+DuBfnmmCRJkiRp5vBG55IkSZIkSWo6N6UkSZIkSZLUdG5KSZIkSZIkqenclJIkSZIkSVLTpfv1vRrNoZeVrGMeSzibLl7lGM8zwG62cZTBpmQ4fhD2b4OhARg5BrO6oGcJLF0Hsxc1JUKIOqTOkHp8cC5URaiDJEmSJGl6Cr8ptYQ+VrGBZawmowJAG21UXn++mlvZywPsYAsD7JqSDId3wt4tcHA7lF4/tywrQ6k9f/7UrXDhali+Eeb3TUmEEHVInSH1+OBcqIpQB0mSJEnS9Bb68r1VbGAjO7mUa2mjjXY6aKeD0inP22hjGdexkUe5hpsbOn6WwdP9sP1qGHwIyPIv3ln59derzzM4+BA88L78i3qWNTRG8jpEyJB6fOdCLkodJEmSJEnTX9hNqWu4mevpB6CdWeO+t/r6WrY09Ev4vjvgsVvy59no+O+tvr5nY35co0SoQ+oMqccH50JVhDpIkiRJklpDXZtSv/3bv02pVOLXf/3XGxQnt4Q+1rKl0LFr2cISrqo7w+Gd+ZfpIvZshCOP1h0hRB1SZ0g9PjgXqiLUQZIkSZLUOgpvSj3xxBP84R/+IcuXL29kHiC/RKnMSKFjy4w05MyQvVugVPCOW6WO/Ph6RahD6gypxwfnQlWEOkiSJEmSWkehTanjx49zww038NWvfpU5c+Y0NNAcelnG6gkvTzqTdmaxnI8wh4WFMxw/mN/AeaLLk84kG4VnH4DjdfwAWoQ6pM6QenxwLlRFqIMkSZIkqbUU2pRav349H/7wh7nmmmsanYeVrDv5i2JFZVRYyU2Fj9+/bewXxYoqtcH+rcWPj1CH1BlSjw/OhaoIdZAkSZIktZaaL8b55je/yfe//32eeOKJSb3/xIkTnDhx4uQ/Dw8Pj/v+eSypNdJbyJjL4sJHDw00IAIwfKD4sRHqkDpD6vHBuVAVoQ6SJEmSpNZS07kPg4ODfPrTn+aee+7h7LPPntQxmzdvpqen5+Sjt7d33PefTRdtdf4oYBvtnEN34eNHjo39xH1RWRleG3//bVwR6pA6Q+rxwblQFaEOkiRJkqTWUtM33aeeeornn3+en/7pn6ajo4OOjg527tzJ7/3e79HR0UG5/OZvrZs2bWJoaOjkY3Bw/JvKvMoxKnVeqlShzCsU//Y7qwtK7XVFoNQOZxXfAwhRh9QZUo8PzoWqCHWQJEmSJLWWmi7f+8AHPsC+ffve8O9uuukmLrnkEn7zN3+T9vY3f2vt7Oyks7Nz0mM8TyOuEyrxAsWvE+ppxNVSQHfxq6VC1CF1htTjg3OhKkIdJEmSJEmtpaYzpbq6urj00kvf8DjvvPM4//zzufTSSxsSaDfbKNV5qVKJNnZT/I7KS9dBVt+JKWQVWFr8vtIh6pA6Q+rxwblQFaEOkiRJkqTWUufvaTXeUQbZx3bKjBQ6vswIe7mfoxwqnGH2Ili0Gko13wY+V+qAC9fA7PFvnzWuCHVInSH1+OBcqIpQB0mSJElSa6l7U+p73/seX/rSlxoQZcwj9NPOrELHttHODu6oO8NlGyEbLXZsVoblG+qOEKIOqTOkHh+cC1UR6iBJkiRJah3hzpQCGGAX91LsG+x3uIUBdtWdYX4frOgvduyKL+bH1ytCHVJnSD0+OBeqItRBkiRJktQ6Qm5KAezgjpNfwie6bKn6+r1saMgZIVXLbh77Ej7RZUvV11f058c1SoQ6pM6QenxwLlRFqIMkSZIkqTWE3ZSC/Et4P33s40EqVCgzSplRMiqUGaHMKBUq7ONB+ulr6JdvgFIpv+RozU5YdB1Qyn/WvvT6jwyefF7KX1+zM39/qdTQGMnrECFD6vGdC7kodZAkSZIkTX8Fb1vcPAPsYoBdzGEhK7mJuSzmHLp5hWFe4AC72VrXDZwnY35f/jg+CPu3wvABeG0YzurOf+J+6U1TfwPnCHVInSH1+OBcqIpQB0mSJEnS9BZ+U6rqKId4kNuSZpjdC1d8NmmEEHVInSH1+OBcqIpQB0mSJEnS9BT68j1JkiRJkiS1JjelJEmSJEmS1HRuSkmSJEmSJKnp3JSSJEmSJElS05WyLMuaOeDw8DA9PT1QgvMWNHPk3MtHIKtAqQ3Ond/88c1ghmgZUo8P8NJhIIOhoSG6u7vThJAkSZIkNVW6TSlJOo2bUpIkSZI0c3QkG9kzpcxghhAZUo8PY2dKSZIkSZJmjmSbUudeADccav649yyEl36Uf/lOMb4ZzBAtQ+rxAe5ekG+OSZIkSZJmDm90LkmSJEmSpKZzU0qSJEmSJElN56aUJEmSJEmSms5NKUmSJEmSJDVdul/fq9EcelnJOuaxhLPp4lWO8TwD7GYbRxlsSobjB2H/NhgagJFjMKsLepbA0nUwe1FTIoTIkLoXqcc3w5gI81GSJEmSND2F35RaQh+r2MAyVpNRAaCNNiqvP1/NrezlAXawhQF2TUmGwzth7xY4uB1Kr59blpWh1J4/f+pWuHA1LN8I8/umJEKIDKl7kXp8M4yJMB8lSZIkSdNb6Mv3VrGBjezkUq6ljTba6aCdDkqnPG+jjWVcx0Ye5Rpubuj4WQZP98P2q2HwISDLv3hn5ddfrz7P4OBD8MD78i/qWdZaGSB9L1KPb4ZclPkoSZIkSZr+wm5KXcPNXE8/AO3MGve91dfXsqWhX8L33QGP3ZI/z0bHf2/19T0b8+NaKUPqXqQe3wxjIsxHSZIkSVJrCLkptYQ+1rKl0LFr2cISrqo7w+Gd+ZfpIvZshCOP1h0hRIbUvUg9vhnGRJiPkiRJkqTWUdOm1K233kqpVHrD45JLLml4qFVsoMxIoWPLjDTkzJC9W6BU8I5bpY78+FbIkLoXqcc3w5gI81GSJEmS1DpqPlPqp37qpzhy5MjJx1//9V83NNAcelnG6gkvTzqTdmaxnI8wh4WFMxw/mN/AeaLLk84kG4VnH4DjdfwAWoQMqXuRenwzjIkwHyVJkiRJraXmTamOjg4uuOCCk493vOMdDQ20knUnf1GsqIwKK7mp8PH7t439olhRpTbYv7X48REypO5F6vHNMCbCfJQkSZIktZaav2YODAywYMECLr74Ym644QYOHjw47vtPnDjB8PDwGx7jmceSWiO9hYy5LC589NBAAyIAwweKHxshQ+pepB7fDGMizEdJkiRJUmupaVPqX/2rf8W2bdt4+OGHufPOO/mXf/kXrrrqKo4dO3bGYzZv3kxPT8/JR29v77hjnE0XbXXef72Nds6hu/DxI8fGfuK+qKwMr42//xY+Q+pepB7fDGMizEdJkiRJUmup6Zvutddey9q1a1m+fDk///M/z//6X/+LF198kW9/+9tnPGbTpk0MDQ2dfAwOjn9TmVc5RqXOS5UqlHmF4t9+Z3VBqb2uCJTa4aziewAhMqTuRerxzTAmwnyUJEmSJLWWgr+llXvb297Gu971Lg4cOPM1OZ2dnXR2dk76z3yeRlwnVOIFil8n1NOIq6WA7uJXS4XIkLoXqcc3w5gI81GSJEmS1Frquibo+PHj/NM//RPz589vVB52s41SnZcqlWhjN8XvqLx0HWT1nZhCVoGlxe8rHSJD6l6kHt8MYyLMR0mSJElSa6npm+7GjRvZuXMnzzzzDLt37+ZjH/sY7e3t/OIv/mLDAh1lkH1sp8xIoePLjLCX+znKocIZZi+CRauhVPA8slIHXLgGZo9/+6zwGVL3IvX4ZhgTYT5KkiRJklpLTZtShw4d4hd/8RdZunQp//pf/2vOP/989uzZw9y5cxsa6hH6aWdWoWPbaGcHd9Sd4bKNkI0WOzYrw/INdUcIkSF1L1KPb4YxEeajJEmSJKl11LQp9c1vfpPDhw9z4sQJDh06xDe/+U3e+c53NjzUALu4l2LfYL/DLQywq+4M8/tgRX+xY1d8MT++FTKk7kXq8c0wJsJ8lCRJkiS1jvpuVDOFdnDHyS/hE122VH39XjY05IyQqmU3j30Jn+iyperrK/rz41opQ+pepB7fDGMizEdJkiRJUmsIuykF+ZfwfvrYx4NUqFBmlDKjZFQoM0KZUSpU2MeD9NPX0C/fAKVSfsnRmp2w6DqglP+sfan99derz0v562t25u8vlVorA6TvRerxzZCLMh8lSZIkSdNfwdsWN88AuxhgF3NYyEpuYi6LOYduXmGYFzjAbrbWdQPnyZjflz+OD8L+rTB8AF4bhrO685+4X3rT1N/AOUKG1L1IPb4ZxkSYj5IkSZKk6S38plTVUQ7xILclzTC7F674bNIIITKk7kXq8c0wJsJ8lCRJkiRNT6Ev35MkSZIkSVJrclNKkiRJkiRJTeemlCRJkiRJkprOTSlJkiRJkiQ1nZtSkiRJkiRJarpSlmVZMwccHh6mp6cHSnDegmaOnHv5CGQVKLXBufObP74ZzBAtQ+rxAV46DGQwNDREd3d3mhCSJEmSpKZKtyklSadxU0qSJEmSZo6OZCN7ppQZzBAiQ+rxYexMKUmSJEnSzJFsU+rcC+CGQ80f956F8NKP8i/fKcY3gxmiZUg9PsDdC/LNMUmSJEnSzOGNziVJkiRJktR0bkpJkiRJkiSp6dyUkiRJkiRJUtO5KSVJkiRJkqSmS/frezWaQy8rWcc8lnA2XbzKMZ5ngN1s4yiDTclw/CDs3wZDAzByDGZ1Qc8SWLoOZi9qSoQQdUidIfX4ZhgT4TMhSZIkSZqewm9KLaGPVWxgGavJqADQRhuV15+v5lb28gA72MIAu6Ykw+GdsHcLHNwOpdfPLcvKUGrPnz91K1y4GpZvhPl9UxIhRB1SZ0g9vhnGRPhMSJIkSZKmt9CX761iAxvZyaVcSxtttNNBOx2UTnneRhvLuI6NPMo13NzQ8bMMnu6H7VfD4ENAln/xzsqvv159nsHBh+CB9+Vf1LOsoTGS1yFChtTjmyEX5TMhSZIkSZr+wm5KXcPNXE8/AO3MGve91dfXsqWhX8L33QGP3ZI/z0bHf2/19T0b8+MaJUIdUmdIPb4ZxkT4TEiSJEmSWkPNm1I/+tGP+MQnPsH555/POeecw7Jly3jyyScbGmoJfaxlS6Fj17KFJVxVd4bDO/Mv00Xs2QhHHq07Qog6pM6QenwzjInwmZAkSZIktY6aNqWOHj3KlVdeyaxZs3jooYf4+7//e7Zs2cKcOXMaGmoVGygzUujYMiMNOTNk7xYoFbzjVqkjP75eEeqQOkPq8c0wJsJnQpIkSZLUOmr6ivmFL3yB3t5etm7devLfXXTRRQ0NNIdelrGatoJXFrYzi+V8hDks5CiHCv0Zxw/mN3Cm4H1wslF49gE4Pgize4v9GRHqkDpD6vHNMCbCZ0KSJEmS1Fpq+pZ7//338573vIe1a9cyb948Lr/8cr761a82NNBK1p38RbGiMiqs5KbCx+/fNvaLYkWV2mD/1onfdyYR6pA6Q+rxzTAmwmdCkiRJktRaavqa+c///M/ceeedLFmyhD//8z/nV3/1V/lP/+k/8fWvf/2Mx5w4cYLh4eE3PMYzjyW1RDqDjLksLnz00EADIgDDB4ofG6EOqTOkHt8MYyJ8JiRJkiRJraWmy/cqlQrvec97uP322wG4/PLL+bu/+zv+x//4H9x4441veczmzZv5rd/6rUmPcTZdhS9TqmqjnXPoLnz8yLGxn7gvKivDa+Pvv40rQh1SZ0g9vhnGRPhMSJIkSZJaS03fdOfPn8+73/3uN/y7n/zJn+TgwYNnPGbTpk0MDQ2dfAwODo47xqsco1LnpUoVyrxC8W+/s7qg1F5XBErtcFbxPYAQdUidIfX4ZhgT4TMhSZIkSWotNZ0pdeWVV7J///43/Lt//Md/5MILLzzjMZ2dnXR2dk56jOdpxHVCJV6g+HVCPY24WgroLn61VIg6pM6QenwzjInwmZAkSZIktZaazpT6jd/4Dfbs2cPtt9/OgQMH+MY3vsH//J//k/Xr1zcs0G62UarzUqUSbeym+B2Vl66DrL4TU8gqsLT4faVD1CF1htTjm2FMhM+EJEmSJKm11PRN973vfS/33Xcff/Inf8Kll17Kbbfdxpe+9CVuuOGGhgU6yiD72E6ZkULHlxlhL/dzlEOFM8xeBItWQ6mm88jGlDrgwjUwu7dwhBB1SJ0h9fhmGBPhMyFJkiRJai01n36xevVq9u3bx6uvvsoPf/hD/sN/+A8ND/UI/bQzq9CxbbSzgzvqznDZRshGix2blWH5hrojhKhD6gypxzfDmAifCUmSJElS66jvmqApMsAu7qXYN9jvcAsD7Ko7w/w+WNFf7NgVX8yPr1eEOqTOkHp8M4yJ8JmQJEmSJLWOkJtSADu44+SX8IkuW6q+fi8bGnJGSNWym8e+hE902VL19RX9+XGNEqEOqTOkHt8MYyJ8JiRJkiRJrSHsphTkX8L76WMfD1KhQplRyoySUaHMCGVGqVBhHw/ST19Dv3wDlEr5JUdrdsKi64BS/rP2pfbXX68+L+Wvr9mZv79UamiM5HWIkCH1+GbIRflMSJIkSZKmv4K3LW6eAXYxwC7msJCV3MRcFnMO3bzCMC9wgN1sresGzpMxvy9/HB+E/Vth+AC8Ngxndec/cb/0pqm/gXOEOqTOkHp8M4yJ8JmQJEmSJE1v4Telqo5yiAe5LWmG2b1wxWeTRghRh9QZUo9vhjERPhOSJEmSpOkp9OV7kiRJkiRJak1uSkmSJEmSJKnp3JSSJEmSJElS07kpJUmSJEmSpKYrZVmWNXPA4eFhenp6oATnLWjmyLmXj0BWgVIbnDu/+eObwQzRMqQeH+Clw0AGQ0NDdHd3pwkhSZIkSWqqdJtSknQaN6UkSZIkaeboSDayZ0qZwQwhMqQeH8bOlJIkSZIkzRzJNqXOvQBuONT8ce9ZCC/9KP/ynWJ8M5ghWobU4wPcvSDfHJMkSZIkzRze6FySJEmSJElN56aUJEmSJEmSms5NKUmSJEmSJDWdm1KSJEmSJElqunS/vlejOfSyknXMYwln08WrHON5BtjNNo4y2JQMxw/C/m0wNAAjx2BWF/QsgaXrYPaipkQIkSF1L6xBnAwReiFJkiRJmp7Cb0otoY9VbGAZq8moANBGG5XXn6/mVvbyADvYwgC7piTD4Z2wdwsc3A6l188ty8pQas+fP3UrXLgalm+E+X1TEiFEhtS9sAZxMkTohSRJkiRpegt9+d4qNrCRnVzKtbTRRjsdtNNB6ZTnbbSxjOvYyKNcw80NHT/L4Ol+2H41DD4EZPkX76z8+uvV5xkcfAgeeF/+RT3LWisDpO2FNYiTIUovJEmSJEnTX9hNqWu4mevpB6CdWeO+t/r6WrY09Ev4vjvgsVvy59no+O+tvr5nY35cK2VI3QtrECdDhF5IkiRJklpDyE2pJfSxli2Fjl3LFpZwVd0ZDu/Mv0wXsWcjHHm07gghMqTuhTWIkyFCLyRJkiRJraOmTamf+ImfoFQqvemxfv36hoZaxQbKjBQ6tsxIQ84M2bsFSgXvuFXqyI9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" ] @@ -1146,8 +1157,7 @@ ], "source": [ "def simulate_game(\n", - " nr_of_games: int,\n", - " policies: tuple[GamePolicy, GamePolicy],\n", + " nr_of_games: int, policies: tuple[GamePolicy, GamePolicy], tqdm_on: bool = False\n", ") -> tuple[np.ndarray, np.ndarray]:\n", " \"\"\"Simulates a stack of games.\n", "\n", @@ -1161,14 +1171,14 @@ " board_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 8, 8), dtype=int)\n", " action_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 2), dtype=int)\n", " current_boards = get_new_games(nr_of_games)\n", - " for turn_index in range(SIMULATE_TURNS):\n", + " for turn_index in tqdm(range(SIMULATE_TURNS)) if tqdm_on else range(SIMULATE_TURNS):\n", " policy_index = turn_index % 2\n", " policy = policies[policy_index]\n", - " board_history_stack[turn_index] = current_boards\n", + " board_history_stack[turn_index, :, :, :] = current_boards\n", " if policy_index == 0:\n", " current_boards = current_boards * -1\n", " current_boards, action_taken = single_turn(current_boards, policy)\n", - " action_history_stack[turn_index] = action_taken\n", + " action_history_stack[turn_index, :] = action_taken\n", "\n", " if policy_index == 0:\n", " current_boards = current_boards * -1\n", @@ -1184,139 +1194,197 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "8.08 s ± 262 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "9.48 s ± 330 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] } ], "source": [ - "%timeit simulate_game(100, (RandomPolicy(1), RandomPolicy(1)))\n", - "simulation_results = simulate_game(10, (RandomPolicy(1), RandomPolicy(1)))" + "%timeit simulate_game(100, (RandomPolicy(1), RandomPolicy(1)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Statistical examination of the natural action space and result\n", + "As for many project some evaluation of the project is in order.\n", + "\n", + "1. What is the expected distribution of scores\n", + "2. What is the expected distribution of possible actions\n", + " a. over time\n", + " b. ober space\n", + "\n", + "The easiest and most robust way to analyse this is when analyzing randomly played games." ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(70, 10, 8, 8)\n", - "(70, 10, 2)\n" + "(70, 100, 8, 8)\n", + "(70, 100, 2)\n" ] } ], "source": [ - "print(simulation_results[0].shape)\n", - "print(simulation_results[1].shape)" + "if not os.path.exists(\"rnd_history.npy\") and not os.path.exists(\"rnd_action.npy\"):\n", + " rnds = RandomPolicy(1), RandomPolicy(1)\n", + " simulation_results = simulate_game(100, rnds, tqdm_on=True)\n", + " _board_history, _action_history = simulation_results\n", + " np.save(\"rnd_history.npy\", _board_history)\n", + " np.save(\"rnd_action.npy\", _action_history)\n", + "else:\n", + " _board_history = np.load(\"rnd_history.npy\")\n", + " _action_history = np.load(\"rnd_action.npy\")\n", + "print(_board_history.shape)\n", + "print(_action_history.shape)" ] }, { "cell_type": "code", - "execution_count": 118, + "execution_count": 84, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(70, 100, 8, 8)\n", + "(70, 100, 2)\n" + ] + } + ], "source": [ - "board_history, action_history = simulation_results" + "print(_board_history.shape)\n", + "print(_action_history.shape)" ] }, { "cell_type": "code", - "execution_count": 199, - "metadata": { - "scrolled": false - }, + "execution_count": 113, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0.1, 0.1, 0. , 0. , 0. ],\n", - " [-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ],\n", - " [ 0.1, 0.1, 0. , 0.1, 0.1, 0. , 0. , 0.1, 0. , 0. 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, 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ]])" + "(70, 100)" ] }, - "execution_count": 199, + "execution_count": 113, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def calcualte_direct_score(board_history: np.ndarray) -> np.ndarray:\n", + "__board_history = _board_history.copy()\n", + "__board_history[1::2] = __board_history[1::2] * -1\n", + "poss_turn = np.sum(\n", + " get_possible_turns(__board_history.reshape((-1, 8, 8))).reshape(70, -1, 8, 8),\n", + " axis=(2, 3),\n", + ")\n", + "poss_turn.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mean_possiblilites = np.mean(poss_turn, axis=1)\n", + "plt.title(\n", + " f\"Mean turn possible per turn {np.prod(np.extract(mean_possiblilites, mean_possiblilites))}\"\n", + ")\n", + "plt.plot(mean_possiblilites)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bcb93d3e5e0b4c5ea594ad05ce99838d", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(IntSlider(value=35, description='turn', max=70), Output()), _dom_classes=('widget-intera…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "@interact(turn=(0, 70))\n", + "def poss_turn_count(turn):\n", + " plt.hist(poss_turn[turn])" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(70, 100)\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[ 0.046875, 0.046875, 0.046875, ..., 0.046875, 0.046875,\n", + " 0.046875],\n", + " [-0.046875, -0.046875, -0.046875, ..., -0.046875, -0.046875,\n", + " -0.046875],\n", + " [ 0.046875, 0.046875, 0.046875, ..., 0.046875, 0.046875,\n", + " 0.046875],\n", + " ...,\n", + " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", + " 0. ],\n", + " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", + " 0. ],\n", + " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", + " 0. ]])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def calculate_direct_score(board_history: np.ndarray) -> np.ndarray:\n", " boards_evaluated = np.reshape(\n", " evaluate_boards(np.reshape(board_history, (-1, 8, 8))), (SIMULATE_TURNS, -1)\n", " )\n", @@ -1325,339 +1393,185 @@ " return direct_score / 64\n", "\n", "\n", - "assert len(calcualte_direct_score(board_history).shape) == 2\n", - "assert calcualte_direct_score(board_history).shape[0] == SIMULATE_TURNS\n", - "calcualte_direct_score(board_history).shape\n", - "calcualte_direct_score(board_history).round(1)" + "assert len(calculate_direct_score(_board_history).shape) == 2\n", + "assert calculate_direct_score(_board_history).shape[0] == SIMULATE_TURNS\n", + "print(calculate_direct_score(_board_history).shape)\n", + "calculate_direct_score(_board_history)" ] }, { "cell_type": "code", - "execution_count": 200, + "execution_count": 62, "metadata": {}, "outputs": [ { "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "36fb809b8d9e42b79512d6d788b2008f", + "version_major": 2, + "version_minor": 0 + }, "text/plain": [ - "array([ 0.4, 0.4, 0.1, 0.1, 0.3, 0.5, -0.2, -0.2, -0.1, -0.3])" + "interactive(children=(IntSlider(value=35, description='turn', max=70), Output()), _dom_classes=('widget-intera…" ] }, - "execution_count": 200, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "def caluclate_final_evaluation_for_histoy(board_history: np.ndarray) -> np.ndarray:\n", + "from ipywidgets import interact\n", + "import matplotlib.pyplot as plt\n", + "\n", + "\n", + "@interact(turn=(0, 70))\n", + "def hist_direct_score(turn):\n", + " score_history = calculate_direct_score(_board_history) * 64\n", + " score_history[1::2] = score_history[1::2] * -1\n", + " # print(score_history[turn])\n", + " plt.title(f\"Histogram of turn {turn} by {'white' if turn % 2 == 0 else 'black'}\")\n", + " plt.hist(score_history[turn], density=True)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(100,)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def calculate_final_evaluation_for_history(board_history: np.ndarray) -> np.ndarray:\n", " final_evaluation = final_boards_evaluation(board_history[-1])\n", " return final_evaluation / 64\n", "\n", "\n", - "assert len(caluclate_final_evaluation_for_histoy(board_history).shape) == 1\n", - "caluclate_final_evaluation_for_histoy(board_history).shape\n", - "caluclate_final_evaluation_for_histoy(board_history).round(1)" + "assert len(calculate_final_evaluation_for_history(_board_history).shape) == 1\n", + "print(calculate_final_evaluation_for_history(_board_history).shape)\n", + "_final_eval = calculate_final_evaluation_for_history(_board_history)\n", + "plt.title(\"Histogram over the score distribtuion\")\n", + "plt.hist((_final_eval * 64), density=True)\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 156, + "execution_count": 68, "metadata": {}, "outputs": [ { "data": { + "image/png": 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\n", "text/plain": [ - "array([ 1, 1, 1, 1, 1, 1, -1, -1, -1, -1])" + "
" ] }, - "execution_count": 156, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "def calulate_who_won(board_history: np.ndarray) -> np.ndarray:\n", - " who_won = evaluate_who_won(boards[-1])\n", + "def calculate_who_won(board_history: np.ndarray) -> np.ndarray:\n", + " who_won = evaluate_who_won(board_history[-1])\n", " return who_won\n", "\n", "\n", - "calulate_who_won(board_history)" + "plt.title(\"Histogram over the win distribtuion\")\n", + "plt.hist(calculate_who_won(_board_history), density=True, bins=3)\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 172, + "execution_count": 82, "metadata": { - "scrolled": true + "scrolled": false }, "outputs": [ { "data": { + "image/png": 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True, True, True, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, False, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, True, True,\n", - " True],\n", - " [ True, False, True, True, True, False, True, True, True,\n", - " True],\n", - " [ True, True, True, True, True, True, True, False, True,\n", - " True],\n", - " [False, False, False, False, False, False, False, False, False,\n", - " False],\n", - " [False, True, False, False, False, True, False, False, False,\n", - " False],\n", - " [False, False, False, False, False, True, False, False, False,\n", - " False],\n", - " [False, False, False, False, False, False, False, False, False,\n", - " False],\n", - " [False, False, False, False, False, False, False, False, False,\n", - " False],\n", - " [False, False, False, False, False, False, False, False, False,\n", - " False],\n", - " [False, False, False, False, False, False, False, False, False,\n", - " False],\n", - " [False, False, False, False, False, False, False, False, False,\n", - " False],\n", - " [False, False, False, False, False, False, False, False, False,\n", - " False]])" + "
" ] }, - "execution_count": 172, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ "def history_changed(board_history: np.ndarray) -> np.ndarray:\n", - " return ~np.all(np.roll(boards, shift=1, axis=0) == boards, axis=(2, 3))\n", + " return ~np.all(\n", + " np.roll(board_history, shift=1, axis=0) == board_history, axis=(2, 3)\n", + " )\n", "\n", "\n", - "history_changed(board_history)" + "plt.title(\"Share of turns skipped\")\n", + "plt.plot(1 - np.mean(history_changed(_board_history), axis=1))\n", + "# plt.yscale('log',base=10)\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 189, + "execution_count": 125, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(70, 10)" + "(70, 100)" ] }, - "execution_count": 189, + "execution_count": 125, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def get_gamma_table(board_history, gamma_value):\n", + "def get_gamma_table(board_history, gamma_value: float):\n", " unchanged = history_changed(board_history)\n", " gamma_values = np.ones_like(unchanged, dtype=float)\n", - " gamma_values[unchanged] = 0.8\n", + " gamma_values[unchanged] = gamma_value\n", " return gamma_values\n", "\n", "\n", - "get_gamma_table(board_history, 0.8).shape" + "get_gamma_table(_board_history, 0.8).shape" ] }, { "cell_type": "code", - "execution_count": 204, + "execution_count": 126, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "array([[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0.1, 0.1, 0. , 0. , 0. ],\n", - " [-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ],\n", - " [ 0.1, 0.1, 0. , 0.1, 0.1, 0. , 0. , 0.1, 0. , 0. ],\n", - " [-0. , -0.1, -0. , -0.1, -0.1, -0.1, -0.1, -0. , -0. , -0.1],\n", - " [ 0.1, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [-0.1, -0. , -0.1, -0.1, -0.1, -0. , -0.1, -0. , -0. , 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-0.1, -0.1, -0.3, -0. ],\n", - " [ 0.1, 0. , 0. , 0.1, 0.1, 0. , 0.1, 0.1, 0.2, 0. ],\n", - " [-0.4, -0. , -0.1, -0.1, -0.1, -0.1, -0.2, -0. , -0.2, -0. ],\n", - " [ 0. , 0. , 0.1, 0.1, 0. , 0. , 0.1, 0.4, 0.1, 0.1],\n", - " [-0.1, -0.1, -0. , -0.2, -0.2, -0.2, -0.2, -0.1, -0.1, -0. ],\n", - " [ 0.1, 0. , 0.2, 0.1, 0.1, 0. , 0.3, 0.1, 0.1, 0. ],\n", - " [-0.1, -0.1, -0.2, -0.4, -0.1, -0.2, -0.3, 0. , -0. , -0.1],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , -0.2, 0. , 0. , 0. , -0.1, 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0.1, 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ],\n", - " [ 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, -0.4, -0.4, -0.4, -0.4]])" - ] - }, - "execution_count": 204, - "metadata": {}, - "output_type": "execute_result" + "ename": "NameError", + "evalue": "name 'calulate_fina_score' is not defined", + "output_type": "error", + "traceback": [ + "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[1;32mIn[126], line 25\u001B[0m\n\u001B[0;32m 20\u001B[0m combined_score[turn \u001B[38;5;241m-\u001B[39m \u001B[38;5;241m1\u001B[39m] \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m values\n\u001B[0;32m 22\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m combined_score\n\u001B[1;32m---> 25\u001B[0m np\u001B[38;5;241m.\u001B[39mmax(\u001B[43mcalculate_q_reword\u001B[49m\u001B[43m(\u001B[49m\u001B[43m_board_history\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mgamma\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;241;43m0.8\u001B[39;49m\u001B[43m)\u001B[49m, axis\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m1\u001B[39m)\n", + "Cell \u001B[1;32mIn[126], line 16\u001B[0m, in \u001B[0;36mcalculate_q_reword\u001B[1;34m(board_history, who_won_fraction, final_score_fraction, gamma)\u001B[0m\n\u001B[0;32m 12\u001B[0m combined_score \u001B[38;5;241m=\u001B[39m np\u001B[38;5;241m.\u001B[39mzeros_like(gama_table)\n\u001B[0;32m 13\u001B[0m combined_score \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m calculate_direct_score(board_history) \u001B[38;5;241m*\u001B[39m (\n\u001B[0;32m 14\u001B[0m \u001B[38;5;241m1\u001B[39m \u001B[38;5;241m-\u001B[39m who_won_fraction \u001B[38;5;241m+\u001B[39m final_score_fraction\n\u001B[0;32m 15\u001B[0m )\n\u001B[1;32m---> 16\u001B[0m combined_score[\u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m] \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m \u001B[43mcalulate_fina_score\u001B[49m(board_history) \u001B[38;5;241m*\u001B[39m final_score_fraction\n\u001B[0;32m 17\u001B[0m combined_score[\u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m] \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m calculate_who_won(board_history) \u001B[38;5;241m*\u001B[39m who_won_fraction\n\u001B[0;32m 18\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m turn \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28mrange\u001B[39m(SIMULATE_TURNS \u001B[38;5;241m-\u001B[39m \u001B[38;5;241m1\u001B[39m , \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m, \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m):\n", + "\u001B[1;31mNameError\u001B[0m: name 'calulate_fina_score' is not defined" + ] } ], "source": [ @@ -1670,40 +1584,152 @@ " assert who_won_fraction + final_score_fraction <= 1\n", " assert final_score_fraction >= 0\n", " assert who_won_fraction >= 0\n", + "\n", " gama_table = get_gamma_table(board_history, gamma)\n", - " direct_score = calcualte_direct_score(board_history) * (\n", + " combined_score = np.zeros_like(gama_table)\n", + " combined_score += calculate_direct_score(board_history) * (\n", " 1 - who_won_fraction + final_score_fraction\n", " )\n", - " direct_score[-1] += calulate_fina_score(board_history) * final_score_fraction\n", - " direct_score[-1] += calulate_who_won(board_history) * who_won_fraction\n", - " return direct_score\n", + " combined_score[-1] += calulate_fina_score(board_history) * final_score_fraction\n", + " combined_score[-1] += calculate_who_won(board_history) * who_won_fraction\n", + " for turn in range(SIMULATE_TURNS - 1, -1, -1):\n", + " values = gama_table[turn] * combined_score[turn]\n", + " combined_score[turn - 1] += values\n", + "\n", + " return combined_score\n", "\n", "\n", - "calculate_q_reword(board_history).round(1)" + "np.max(calculate_q_reword(_board_history, gamma=0.8), axis=1)" ] }, { "cell_type": "code", - "execution_count": 181, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'rewords' is not defined", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[1;32mIn[181], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mrewords\u001B[49m\n\u001B[0;32m 2\u001B[0m evaluate_boards(boards)\u001B[38;5;241m.\u001B[39mshape\n", - "\u001B[1;31mNameError\u001B[0m: name 'rewords' is not defined" - ] - } - ], + "outputs": [], "source": [ "rewords\n", "evaluate_boards(boards).shape" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import torch.optim as optim" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "BATCH_SIZE = 1000\n", + "\n", + "\n", + "class DQLNet(nn.Module):\n", + " def __init__(self):\n", + " super().__init__()\n", + " self.fc1 = nn.Linear(BATCH_SIZE, 64)\n", + " self.fc2 = nn.Linear(BATCH_SIZE, 64)\n", + "\n", + " def forward(self, x):\n", + " if isinstance(x, np.ndarray):\n", + " x = torch.from_numpy(x).float()\n", + " x = torch.flatten(x, 1)\n", + " print(x)\n", + " x = self.fc1(x)\n", + " print(x)\n", + " x = F.relu(x)\n", + " print(x)\n", + " # x = self.dropout1(x)\n", + " x = self.fc2(x)\n", + " x = F.relu(x)\n", + " # x = self.dropout2(x)\n", + " x = torch.reshape(x, (BATCH_SIZE, 8, 8))\n", + " return x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "DQLNet().fc1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ones = np.ones((1000, 8, 8), dtype=float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "DQLNet().forward(ones)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "t = torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])\n", + "torch.flatten(t)\n", + "torch.tensor([1, 2, 3, 4, 5, 6, 7, 8])\n", + "torch.flatten(t, start_dim=1)\n", + "torch.tensor([[1, 2, 3, 4], [5, 6, 7, 8]])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "class DQLearningWinner(GamePolicy):\n", + "\n", + " # network =\n", + "\n", + " @property\n", + " def policy_name(self):\n", + " return \"DQL-Winner\"\n", + "\n", + " def _internal_policy(boards) -> np.ndarray:\n", + " pass" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "DQLearningWinner(0.9)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, -- 2.49.0 From aa7eb02389c2daa0969bcd2c9fba77e455d3aaae Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Fri, 17 Feb 2023 01:47:18 +0100 Subject: [PATCH 24/31] added kdepy and plotly --- poetry.lock | 410 ++++++++++++++++++++++++++++++++----------------- pyproject.toml | 3 +- 2 files changed, 268 insertions(+), 145 deletions(-) diff --git a/poetry.lock b/poetry.lock index 8a5acd0..7b48fe4 100644 --- a/poetry.lock +++ b/poetry.lock @@ -441,7 +441,7 @@ python-versions = "*" [[package]] name = "identify" -version = "2.5.17" +version = "2.5.18" description = "File identification library for Python" category = "dev" optional = false @@ -468,7 +468,7 @@ python-versions = ">=3.7" [[package]] name = "ipykernel" -version = "6.21.1" +version = "6.21.2" description = "IPython Kernel for Jupyter" category = "main" optional = false @@ -485,7 +485,7 @@ matplotlib-inline = ">=0.1" nest-asyncio = "*" packaging = "*" psutil = "*" -pyzmq = ">=17" +pyzmq = ">=20" tornado = ">=6.1" traitlets = ">=5.4.0" @@ -497,21 +497,28 @@ pyside6 = ["pyside6"] test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"] [[package]] -name = "ipytest" -version = "0.13.0" -description = "Unit tests in IPython notebooks" +name = "ipympl" +version = "0.9.3" +description = "Matplotlib Jupyter Extension" category = "main" optional = false -python-versions = ">=3.6" +python-versions = "*" [package.dependencies] -ipython = "*" -packaging = "*" -pytest = ">=5.4" +ipython = "<9" +ipython-genutils = "*" +ipywidgets = ">=7.6.0,<9" +matplotlib = ">=3.4.0,<4" +numpy = "*" +pillow = "*" +traitlets = "<6" + +[package.extras] +docs = ["Sphinx (>=1.5)", "myst-nb", "sphinx-book-theme", "sphinx-copybutton", "sphinx-thebe", "sphinx-togglebutton"] [[package]] name = "ipython" -version = "8.9.0" +version = "8.10.0" description = "IPython: Productive Interactive Computing" category = "main" optional = false @@ -532,7 +539,7 @@ stack-data = "*" traitlets = ">=5" [package.extras] -all = ["black", "curio", "docrepr", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.20)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"] +all = ["black", "curio", "docrepr", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"] black = ["black"] doc = ["docrepr", "ipykernel", "matplotlib", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"] kernel = ["ipykernel"] @@ -542,7 +549,7 @@ notebook = ["ipywidgets", "notebook"] parallel = ["ipyparallel"] qtconsole = ["qtconsole"] test = ["pytest (<7.1)", "pytest-asyncio", "testpath"] -test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.20)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"] +test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"] [[package]] name = "ipython-genutils" @@ -691,21 +698,24 @@ test = ["codecov", "coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-co [[package]] name = "jupyter-console" -version = "6.4.4" +version = "6.5.1" description = "Jupyter terminal console" category = "main" optional = false python-versions = ">=3.7" [package.dependencies] -ipykernel = "*" +ipykernel = ">=6.14" ipython = "*" jupyter-client = ">=7.0.0" -prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" +prompt-toolkit = ">=3.0.30" pygments = "*" +pyzmq = ">=17" +traitlets = ">=5.4" [package.extras] -test = ["pexpect"] +test = ["pexpect", "pytest"] [[package]] name = "jupyter-core" @@ -744,7 +754,7 @@ test = ["click", "coverage", "pre-commit", "pytest (>=6.1.0)", "pytest-asyncio ( [[package]] name = "jupyter-server" -version = "2.2.1" +version = "2.3.0" description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." category = "main" optional = false @@ -899,6 +909,19 @@ category = "main" optional = false python-versions = ">=3.7" +[[package]] +name = "kdepy" +version = "1.1.0" +description = "Kernel Density Estimation in Python." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +matplotlib = ">=2.2.0" +numpy = ">=1.14.2" +scipy = ">=1.0.1" + [[package]] name = "kiwisolver" version = "1.4.4" @@ -917,7 +940,7 @@ python-versions = ">=3.7" [[package]] name = "matplotlib" -version = "3.6.3" +version = "3.7.0" description = "Python plotting package" category = "main" optional = false @@ -928,10 +951,10 @@ contourpy = ">=1.0.1" cycler = ">=0.10" fonttools = ">=4.22.0" kiwisolver = ">=1.0.1" -numpy = ">=1.19" +numpy = ">=1.20" packaging = ">=20.0" pillow = ">=6.2.0" -pyparsing = ">=2.2.1" +pyparsing = ">=2.3.1" python-dateutil = ">=2.7" setuptools_scm = ">=7" @@ -948,7 +971,7 @@ traitlets = "*" [[package]] name = "mistune" -version = "2.0.4" +version = "2.0.5" description = "A sane Markdown parser with useful plugins and renderers" category = "main" optional = false @@ -956,11 +979,11 @@ python-versions = "*" [[package]] name = "mypy-extensions" -version = "0.4.3" -description = "Experimental type system extensions for programs checked with the mypy typechecker." +version = "1.0.0" +description = "Type system extensions for programs checked with the mypy type checker." category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.5" [[package]] name = "nbclassic" @@ -1131,7 +1154,7 @@ test = ["pytest", "pytest-console-scripts", "pytest-tornasync"] [[package]] name = "numpy" -version = "1.24.1" +version = "1.24.2" description = "Fundamental package for array computing in Python" category = "main" optional = false @@ -1254,15 +1277,26 @@ tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "pa [[package]] name = "platformdirs" -version = "2.6.2" +version = "3.0.0" description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." category = "main" optional = false python-versions = ">=3.7" [package.extras] -docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"] -test = ["appdirs (==1.4.4)", "covdefaults (>=2.2.2)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"] +docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.22,!=1.23.4)"] +test = ["appdirs (==1.4.4)", "covdefaults (>=2.2.2)", "pytest (>=7.2.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"] + +[[package]] +name = "plotly" +version = "5.13.0" +description = "An open-source, interactive data visualization library for Python" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +tenacity = ">=6.2.0" [[package]] name = "pluggy" @@ -1278,7 +1312,7 @@ testing = ["pytest", "pytest-benchmark"] [[package]] name = "pre-commit" -version = "3.0.3" +version = "3.0.4" description = "A framework for managing and maintaining multi-language pre-commit hooks." category = "dev" optional = false @@ -1414,11 +1448,11 @@ six = ">=1.5" [[package]] name = "python-json-logger" -version = "2.0.4" +version = "2.0.6" description = "A python library adding a json log formatter" category = "main" optional = false -python-versions = ">=3.5" +python-versions = ">=3.6" [[package]] name = "pytz" @@ -1567,7 +1601,7 @@ win32 = ["pywin32"] [[package]] name = "setuptools" -version = "67.1.0" +version = "67.3.2" description = "Easily download, build, install, upgrade, and uninstall Python packages" category = "main" optional = false @@ -1614,11 +1648,11 @@ python-versions = ">=3.7" [[package]] name = "soupsieve" -version = "2.3.2.post1" +version = "2.4" description = "A modern CSS selector implementation for Beautiful Soup." category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" [[package]] name = "stack-data" @@ -1636,6 +1670,17 @@ pure-eval = "*" [package.extras] tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"] +[[package]] +name = "tenacity" +version = "8.2.1" +description = "Retry code until it succeeds" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.extras] +doc = ["reno", "sphinx", "tornado (>=4.5)"] + [[package]] name = "terminado" version = "0.17.1" @@ -1762,7 +1807,7 @@ test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"] [[package]] name = "typing-extensions" -version = "4.4.0" +version = "4.5.0" description = "Backported and Experimental Type Hints for Python 3.7+" category = "main" optional = false @@ -1794,20 +1839,20 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] [[package]] name = "virtualenv" -version = "20.17.1" +version = "20.19.0" description = "Virtual Python Environment builder" category = "dev" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" [package.dependencies] distlib = ">=0.3.6,<1" filelock = ">=3.4.1,<4" -platformdirs = ">=2.4,<3" +platformdirs = ">=2.4,<4" [package.extras] -docs = ["proselint (>=0.13)", "sphinx (>=5.3)", "sphinx-argparse (>=0.3.2)", "sphinx-rtd-theme (>=1)", "towncrier (>=22.8)"] -testing = ["coverage (>=6.2)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=21.3)", "pytest (>=7.0.1)", "pytest-env (>=0.6.2)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.6.1)", "pytest-randomly (>=3.10.3)", "pytest-timeout (>=2.1)"] +docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"] +test = ["covdefaults (>=2.2.2)", "coverage (>=7.1)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23)", "pytest (>=7.2.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)"] [[package]] name = "wcwidth" @@ -1835,7 +1880,7 @@ python-versions = "*" [[package]] name = "websocket-client" -version = "1.5.0" +version = "1.5.1" description = "WebSocket client for Python with low level API options" category = "main" optional = false @@ -1892,7 +1937,7 @@ test = ["mypy", "pre-commit", "pytest", "pytest-asyncio", "websockets (>=10.0)"] [metadata] lock-version = "1.1" python-versions = "3.10.*" -content-hash = "ae8280fcb4c41f6a84fac982ffe5baa5e37930f91df7e43fcc92fa88367bfd60" +content-hash = "70ad716cf2af3d060355d2f419fa295002e6fa9d474842b892e0e886d9d9a3d9" [metadata.files] aiofiles = [ @@ -2278,8 +2323,8 @@ gym-notices = [ {file = "gym_notices-0.0.8-py3-none-any.whl", hash = "sha256:e5f82e00823a166747b4c2a07de63b6560b1acb880638547e0cabf825a01e463"}, ] identify = [ - {file = "identify-2.5.17-py2.py3-none-any.whl", hash = "sha256:7d526dd1283555aafcc91539acc061d8f6f59adb0a7bba462735b0a318bff7ed"}, - {file = "identify-2.5.17.tar.gz", hash = "sha256:93cc61a861052de9d4c541a7acb7e3dcc9c11b398a2144f6e52ae5285f5f4f06"}, + {file = "identify-2.5.18-py2.py3-none-any.whl", hash = "sha256:93aac7ecf2f6abf879b8f29a8002d3c6de7086b8c28d88e1ad15045a15ab63f9"}, + {file = "identify-2.5.18.tar.gz", hash = "sha256:89e144fa560cc4cffb6ef2ab5e9fb18ed9f9b3cb054384bab4b95c12f6c309fe"}, ] idna = [ {file = "idna-3.4-py3-none-any.whl", hash = "sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2"}, @@ -2290,15 +2335,16 @@ iniconfig = [ {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"}, ] ipykernel = [ - {file = "ipykernel-6.21.1-py3-none-any.whl", hash = "sha256:1a04bb359212e23e46adc0116ec82ea128c1e5bd532fde4fbe679787ff36f0cf"}, - {file = "ipykernel-6.21.1.tar.gz", hash = "sha256:a0f8eece39cab1ee352c9b59ec67bbe44d8299f8238e4c16ff7f4cf0052d3378"}, + {file = "ipykernel-6.21.2-py3-none-any.whl", hash = "sha256:430d00549b6aaf49bd0f5393150691edb1815afa62d457ee6b1a66b25cb17874"}, + {file = "ipykernel-6.21.2.tar.gz", hash = "sha256:6e9213484e4ce1fb14267ee435e18f23cc3a0634e635b9fb4ed4677b84e0fdf8"}, ] -ipytest = [ - {file = "ipytest-0.13.0-py3-none-any.whl", hash = "sha256:7c28ec2f0a3df7df2147b90bea8f0d4ec81fac6ef726af4d36a3271043da7c73"}, +ipympl = [ + {file = "ipympl-0.9.3-py2.py3-none-any.whl", hash = "sha256:d113cd55891bafe9b27ef99b6dd111a87beb6bb2ae550c404292272103be8013"}, + {file = "ipympl-0.9.3.tar.gz", hash = "sha256:49bab75c05673a6881d1aaec5d8ac81d4624f73d292d154c5fb7096f10236a2b"}, ] ipython = [ - {file = "ipython-8.9.0-py3-none-any.whl", hash = "sha256:9c207b0ef2d276d1bfcfeb9a62804336abbe4b170574ea061500952319b1d78c"}, - {file = "ipython-8.9.0.tar.gz", hash = "sha256:71618e82e6d59487bea059626e7c79fb4a5b760d1510d02fab1160db6fdfa1f7"}, + {file = "ipython-8.10.0-py3-none-any.whl", hash = "sha256:b38c31e8fc7eff642fc7c597061fff462537cf2314e3225a19c906b7b0d8a345"}, + {file = "ipython-8.10.0.tar.gz", hash = "sha256:b13a1d6c1f5818bd388db53b7107d17454129a70de2b87481d555daede5eb49e"}, ] ipython-genutils = [ {file = "ipython_genutils-0.2.0-py2.py3-none-any.whl", hash = "sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8"}, @@ -2342,8 +2388,8 @@ jupyter-client = [ {file = "jupyter_client-8.0.2.tar.gz", hash = "sha256:47ac9f586dbcff4d79387ec264faf0fdeb5f14845fa7345fd7d1e378f8096011"}, ] jupyter-console = [ - {file = "jupyter_console-6.4.4-py3-none-any.whl", hash = "sha256:756df7f4f60c986e7bc0172e4493d3830a7e6e75c08750bbe59c0a5403ad6dee"}, - {file = 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"sha256:32d2dd0376772d01b6cb9fc996f3c8b57a357089dec328ed4b6553d037eaf815"}, ] +tenacity = [ + {file = "tenacity-8.2.1-py3-none-any.whl", hash = "sha256:dd1b769ca7002fda992322939feca5bee4fa11f39146b0af14e0b8d9f27ea854"}, + {file = "tenacity-8.2.1.tar.gz", hash = "sha256:c7bb4b86425b977726a7b49971542d4f67baf72096597d283f3ffd01f33b92df"}, +] terminado = [ {file = "terminado-0.17.1-py3-none-any.whl", hash = "sha256:8650d44334eba354dd591129ca3124a6ba42c3d5b70df5051b6921d506fdaeae"}, {file = "terminado-0.17.1.tar.gz", hash = "sha256:6ccbbcd3a4f8a25a5ec04991f39a0b8db52dfcd487ea0e578d977e6752380333"}, @@ -3164,8 +3286,8 @@ traitlets = [ {file = "traitlets-5.9.0.tar.gz", hash = "sha256:f6cde21a9c68cf756af02035f72d5a723bf607e862e7be33ece505abf4a3bad9"}, ] typing-extensions = [ - {file = "typing_extensions-4.4.0-py3-none-any.whl", hash = "sha256:16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e"}, - {file = "typing_extensions-4.4.0.tar.gz", hash = "sha256:1511434bb92bf8dd198c12b1cc812e800d4181cfcb867674e0f8279cc93087aa"}, + {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"}, + {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"}, ] uri-template = [ {file = "uri_template-1.2.0-py3-none-any.whl", hash = "sha256:f1699c77b73b925cf4937eae31ab282a86dc885c333f2e942513f08f691fc7db"}, @@ -3176,8 +3298,8 @@ urllib3 = [ {file = "urllib3-1.26.14.tar.gz", hash = "sha256:076907bf8fd355cde77728471316625a4d2f7e713c125f51953bb5b3eecf4f72"}, ] virtualenv = [ - {file = "virtualenv-20.17.1-py3-none-any.whl", hash = "sha256:ce3b1684d6e1a20a3e5ed36795a97dfc6af29bc3970ca8dab93e11ac6094b3c4"}, - {file = "virtualenv-20.17.1.tar.gz", hash = "sha256:f8b927684efc6f1cc206c9db297a570ab9ad0e51c16fa9e45487d36d1905c058"}, + {file = "virtualenv-20.19.0-py3-none-any.whl", hash = "sha256:54eb59e7352b573aa04d53f80fc9736ed0ad5143af445a1e539aada6eb947dd1"}, + {file = "virtualenv-20.19.0.tar.gz", hash = "sha256:37a640ba82ed40b226599c522d411e4be5edb339a0c0de030c0dc7b646d61590"}, ] wcwidth = [ {file = "wcwidth-0.2.6-py2.py3-none-any.whl", hash = "sha256:795b138f6875577cd91bba52baf9e445cd5118fd32723b460e30a0af30ea230e"}, @@ -3192,8 +3314,8 @@ webencodings = [ {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"}, ] websocket-client = [ - {file = "websocket-client-1.5.0.tar.gz", hash = "sha256:561ca949e5bbb5d33409a37235db55c279235c78ee407802f1d2314fff8a8536"}, - {file = "websocket_client-1.5.0-py3-none-any.whl", hash = "sha256:fb5d81b95d350f3a54838ebcb4c68a5353bbd1412ae8f068b1e5280faeb13074"}, + {file = "websocket-client-1.5.1.tar.gz", hash = "sha256:3f09e6d8230892547132177f575a4e3e73cfdf06526e20cc02aa1c3b47184d40"}, + {file = "websocket_client-1.5.1-py3-none-any.whl", hash = "sha256:cdf5877568b7e83aa7cf2244ab56a3213de587bbe0ce9d8b9600fc77b455d89e"}, ] wheel = [ {file = "wheel-0.38.4-py3-none-any.whl", hash = "sha256:b60533f3f5d530e971d6737ca6d58681ee434818fab630c83a734bb10c083ce8"}, diff --git a/pyproject.toml b/pyproject.toml index 53ebe39..c301d16 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,7 +10,6 @@ readme = "README.md" version = "0.1.1" [tool.poetry.dependencies] -ipytest = "^0.13.0" jupyter = "^1.0.0" matplotlib = "^3.6.3" numpy = "^1.24.1" @@ -22,6 +21,8 @@ jupyterlab = "^3.6.1" torchvision = "^0.14.1" torchaudio = "^0.13.1" gym = "^0.26.2" +kdepy = "^1.1.0" +plotly = "^5.13.0" [tool.poetry.group.build.dependencies] blackcellmagic = "^0.0.3" -- 2.49.0 From c33c5931f3ff2d064a8b02cde52a83d9d8cf96fb Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Fri, 17 Feb 2023 01:47:49 +0100 Subject: [PATCH 25/31] Added npy files to LFS config. --- .gitattributes | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitattributes b/.gitattributes index 44da889..9fac708 100644 --- a/.gitattributes +++ b/.gitattributes @@ -2,3 +2,4 @@ *.png filter=lfs diff=lfs merge=lfs -text *.csv filter=lfs diff=lfs merge=lfs -text *.xlsx filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text -- 2.49.0 From ef20f3f68a743263dca72261b87f9e4e937dc797 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Fri, 17 Feb 2023 02:16:24 +0100 Subject: [PATCH 26/31] Added a statistical example of the game. --- rnd_action.npy | 3 +++ rnd_history.npy | 3 +++ 2 files changed, 6 insertions(+) create mode 100644 rnd_action.npy create mode 100644 rnd_history.npy diff --git a/rnd_action.npy b/rnd_action.npy new file mode 100644 index 0000000..05e43f3 --- /dev/null +++ b/rnd_action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d62557d24445a722965c036e89e215f8455005db1d2d93d2d4e1f405842942b6 +size 1400128 diff --git a/rnd_history.npy b/rnd_history.npy new file mode 100644 index 0000000..d03365e --- /dev/null +++ b/rnd_history.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5f90a1798481235a54aa10b3cc11131adc02c92d27b5a639081cbce22905289e +size 44800128 -- 2.49.0 From dfe3b3aa5978bd1ef9d8d83bbd78f292d36ada65 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Fri, 17 Feb 2023 03:04:19 +0100 Subject: [PATCH 27/31] Added a greedy policy --- main.ipynb | 559 +++++++++++++---------------------------------------- 1 file changed, 139 insertions(+), 420 deletions(-) diff --git a/main.ipynb b/main.ipynb index 7839561..5924f9a 100644 --- a/main.ipynb +++ b/main.ipynb @@ -85,7 +85,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -135,14 +135,10 @@ "import abc\n", "from typing import Final\n", "from scipy.ndimage import binary_dilation\n", - "import matplotlib.pyplot as plt\n", "from abc import ABC\n", "from tqdm.notebook import tqdm\n", - "import plotly.graph_objects as go\n", - "from plotly.subplots import make_subplots\n", - "from scipy.spatial import Delaunay\n", - "from KDEpy import FFTKDE\n", - "from ipywidgets import widgets" + "from ipywidgets import interact\n", + "import matplotlib.pyplot as plt" ] }, { @@ -156,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -180,27 +176,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 30, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[-1, -1],\n", - " [-1, 0],\n", - " [-1, 1],\n", - " [ 0, -1],\n", - " [ 0, 1],\n", - " [ 1, -1],\n", - " [ 1, 0],\n", - " [ 1, 1]])" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "DIRECTIONS: Final[np.ndarray] = np.array(\n", " [[i, j] for i in range(-1, 2) for j in range(-1, 2) if j != 0 or i != 0],\n", @@ -219,21 +197,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 31, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[-1, 1],\n", - " [ 1, -1]])" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "START_SQUARE: Final[np.ndarray] = np.array(\n", " [[ENEMY, PLAYER], [PLAYER, ENEMY]], dtype=int\n", @@ -254,27 +220,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 32, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", - " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 0, 0, 0, 0, 0, 0]])" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "def get_new_games(number_of_games: int) -> np.ndarray:\n", " \"\"\"Generates a stack of initialised game boards.\n", @@ -295,7 +243,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -340,22 +288,11 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 34, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "def plot_othello_board(board, ax=None) -> None:\n", + "def plot_othello_board(board: np.ndarray, ax=None) -> None:\n", " \"\"\"Plots a single otello board.\n", "\n", " If a matplot axis object is given the board will be plotted into that axis. If not an axis object will be generated.\n", @@ -400,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -430,7 +367,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -467,24 +404,11 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 37, "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[[1, 1, 1],\n", - " [1, 0, 1],\n", - " [1, 1, 1]]])" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "SURROUNDING: Final = np.array(\n", " [[[1, 1, 1], [1, 0, 1], [1, 1, 1]]]\n", @@ -494,35 +418,9 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 38, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "9.11 ms ± 144 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "920 ms ± 10.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[[False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, True, False, False, False, False],\n", - " [False, False, True, False, False, False, False, False],\n", - " [False, False, False, False, False, True, False, False],\n", - " [False, False, False, False, True, False, False, False],\n", - " [False, False, False, False, False, False, False, False],\n", - " [False, False, False, False, False, False, False, False]]])" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "def _recursive_steps(\n", " board: np.ndarray,\n", @@ -555,7 +453,7 @@ " return step_one\n", "\n", "\n", - "def get_possible_turns(boards: np.ndarray) -> np.ndarray:\n", + "def get_possible_turns(boards: np.ndarray, tqdm_on: bool = False) -> np.ndarray:\n", " \"\"\"Analyses a stack of boards.\n", "\n", " Args:\n", @@ -574,11 +472,14 @@ " _poss_turns &= binary_dilation(\n", " boards == -1, SURROUNDING\n", " ) # checks where fields are next to an enemy filed an empty\n", - " for game, idx, idy in itertools.product(\n", + " iterate_over = itertools.product(\n", " range(boards.shape[0]), range(BOARD_SIZE), range(BOARD_SIZE)\n", - " ):\n", - " position = idx, idy\n", + " )\n", + " if tqdm_on:\n", + " iterate_over = tqdm(iterate_over, total=np.prod(boards.shape))\n", + " for game, idx, idy in iterate_over:\n", " if _poss_turns[game, idx, idy]:\n", + " position = idx, idy\n", " _poss_turns[game, idx, idy] = any(\n", " _recursive_steps(boards[game, :, :], direction, position) > 0\n", " for direction in DIRECTIONS\n", @@ -612,7 +513,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -647,7 +548,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -716,19 +617,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "191 µs ± 2.27 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n", - "33 µs ± 1.4 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "33.8 µs ± 345 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" - ] - } - ], + "outputs": [], "source": [ "def final_boards_evaluation(boards: np.ndarray) -> np.ndarray:\n", " \"\"\"Evaluates the board at the end of the game.\n", @@ -796,7 +687,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -808,27 +699,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "89.6 ms ± 3.13 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def do_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", " \"\"\"Executes a single move on a stack o Othello boards.\n", @@ -928,7 +801,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1022,7 +895,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1031,7 +904,7 @@ " A policy playing a random turn by setting epsilon to 0.\n", " \"\"\"\n", "\n", - " def __init__(self, epsilon: float):\n", + " def __init__(self, epsilon: float = 0):\n", " _ = epsilon\n", " super().__init__(epsilon=0)\n", "\n", @@ -1051,6 +924,42 @@ "assert np.any((5 >= rnd_policy_result) & (rnd_policy_result >= 3))" ] }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "class GreedyPolicy(GamePolicy):\n", + " \"\"\"\n", + " A policy playing always one of the strongest turns.\n", + " \"\"\"\n", + "\n", + " def __init__(self, epsilon: float = 1):\n", + " _ = epsilon\n", + " super().__init__(1)\n", + "\n", + " @property\n", + " def policy_name(self) -> str:\n", + " return \"greedy_policy\"\n", + "\n", + " def _internal_policy(self, boards: np.ndarray) -> np.ndarray:\n", + " policies = np.random.rand(*boards.shape)\n", + " for game, idx, idy in itertools.product(\n", + " range(boards.shape[0]), range(BOARD_SIZE), range(BOARD_SIZE)\n", + " ):\n", + "\n", + " if _poss_turns[game, idx, idy]:\n", + " position = idx, idy\n", + " policies[game, idx, idy] += np.sum(\n", + " _recursive_steps(boards[game, :, :], direction, position)\n", + " for direction in DIRECTIONS\n", + " )\n", + " return policies" + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "markdown", "metadata": {}, @@ -1070,28 +979,9 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1.03 s ± 19 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", - "990 ms ± 29.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def single_turn(\n", " current_boards: np, policy: GamePolicy\n", @@ -1139,37 +1029,29 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "metadata": { "scrolled": false }, - "outputs": [ - { - "data": { - "image/png": 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cK7RRSzSgRGVJUlFFld/8fED36KAe1W5t06D2NSXD8T3SwW3S0V3p2zpKUlKSCh3p58/dI103IC3dJM1b3pQI4X2Iri95rIMD+uCDc5Fy6EN0Bod1cEAffESfCcljPzj0wSGDw1pEowcVDnsyOoPDfojugUsGh7VwENUHfn1vGiu0UZu0RzdqpYoqqkOd6lCnChM+L6qoJbpLm7RXd2pDQ+snifTCVmnXHdLQ45KSdGMkpTe/PvZ5Ih19XHr0A+lGSpKGxgjvQ3R9l3WIRh+8cC5S0X2IzuCyDtHog5foc+myH6L74JDBZS0i0YMLRe/J6Awu+6Hd10HyWYto0X3gptQU7tQGfVxbJUkdmjXl9459fbW2NfSwHNouPXV3+nlyfurvHfv6gU3pdY0S3Yfo+pLHOjigDz44FymHPkRncFgHB/TBR/SZkDz2g0MfHDI4rEU0elDhsCejMzjsh+geuGRwWAsH0X2o6abUfffdp6VLl6qnp0c9PT16//vfr8cff7wxScz0a7lWa1uma1drm/p1e90Zju9JFzuLA5ukE3vrjhDeh+j6ksc6OHDvA/OpOjPpXDj0ITqDwzo4aIU+tMuMij4Tksd+cOiDQwaHtYjWCj3Iaz457MnoDA77IboHLhkc1sKBQx9quim1YMEC/d7v/Z6ee+45Pfvss/qZn/kZfexjH9P/+l//q/4kZlZoo0o6l+naks415A7uwW1SIeOrfhU60+vrFd2H6PqSxzo4cO8D86k6M+lcOPQhOoPDOjhohT60y4yKPhOSx35w6INDBoe1iNYKPchrPjnsyegMDvshugcuGRzWwoFDH2q6KbVq1Srddddd6u/v17vf/W59/vOf1+zZs3XgwIH6kxiZoz4t0cC0jxFeSodmaak+qjlakDnDmaPpC4xN9/jcpSTnpZcelc7U8UYF0X2Iri95rIODVugD86k6M+VcOPQhOoPDOjholT60w4yKPhOSx35w6INDBoe1iNYqPchjPjnsyegMDvshugcuGRzWwoFLHzK/plSpVNKDDz6os2fP6v3vf399Kcws09rxV/7PKlFZy7Qu8/WHd1Ze8T6rQlE6vCP79dF9iK4veayDg1brA/NpajPhXDj0ITqDwzo4aMU+zNQZFX0mJI/94NAHhwwOaxGtFXvQrPnksCejMzjsh+geuGRwWAsHLn2o+UGtQ4cO6f3vf79ef/11zZ49Ww8//LB+8id/8pLfPzo6qtHR0fG/HhkZyZY0R9eovwF/SqK5WpT56uHBBkSQNHIk+7XRfYiuL3msg4NW6QPzqVqtfy4c+hCdwWEdHLRSH2qZUcynbBz2g0MfHDI4rEW0VupBs+eTw56MzuCwH6J74JLBYS0cuPSh5vtiixcv1vPPP6+nnnpKv/qrv6pPfvKT+tu//dtLfv+WLVvU29s7/tHX11dX4Dxcrm4V63xjwqI6dIV6Ml9/7nTlLRizSkrSG3X8DBvdh+j6ksc6OGiVPjCfqjMTzoVDH6IzOKyDg1bqQy0zivmUjcN+cOiDQwaHtYjWSj1o9nxy2JPRGRz2Q3QPXDI4rIUDlz7UvBsuu+wyLVq0SLfccou2bNmim266SX/wB39wye/fvHmzhoeHxz+Ghvx/8fJ1nVa5zkcKyyrpNWVfnVndUqGjrggqdEiXZT+r4X2Iri95rIODVukD86k6M+FcOPQhOoPDOjhopT7UMqOYT9k47AeHPjhkcFiLaK3Ug2bPJ4c9GZ3BYT9E98Alg8NaOHDpQ8bXWa8ol8sXPL45WVdXl7q6uuotk6uTasRzbAW9ouzPsfU24qlGST3Zn2oM70N0fcljHRy0ah+YT5fS+ufCoQ/RGRzWwUEr92GqGcV8ysZhPzj0wSGDw1pEa+UeNHo+OezJ6AwO+yG6By4ZHNbCgUsfanpSavPmzdq7d69efPFFHTp0SJs3b9b3v/99rVmzpr4UZvZrpwp1PlJYUFH7lf0VvxavlZL6biArKUuLs7/+W3gfoutLHuvgoBX6wHyq3kw4Fw59iM7gsA4OWqUP7TCjos+E5LEfHPrgkMFhLaK1Sg/ymE8OezI6g8N+iO6BSwaHtXDg0oeadsPJkyf1y7/8y1q8eLE+9KEP6ZlnntGf/dmfacWKFfWlMHNKQzqkXSrpXKbrSzqng3pEp3Qsc4bZC6WFA1Ih47NshU7pulXS7DpegiK6D9H1JY91cNAKfWA+VWemnAuHPkRncFgHB63Sh3aYUdFnQvLYDw59cMjgsBbRWqUHecwnhz0ZncFhP0T3wCWDw1o4cOlDTTel7r//fr344osaHR3VyZMntXv37hn1w9RET2qrOjQr07VFdWi3tted4aZNUnI+27VJSVq6se4I4X2Iri95rIMD9z4wn6ozk86FQx+iMzisg4NW6EO7zKjoMyF57AeHPjhkcFiLaK3Qg7zmk8OejM7gsB+ie+CSwWEtHDj0ob7n5mawQe3TQ8rW4e/obg1qX90Z5i2Xbt2a7dpb702vr1d0H6LrSx7r4IA++OBcpBz6EJ3BYR0c0Acf0WdC8tgPDn1wyOCwFtHoQYXDnozO4LAfonvgksFhLRw49IGbUlPYre3jh2W6xwvHvv6QNjbkzu2YJRsqm2S6x+rGvn7r1vS6RonuQ3R9yWMdHNAHH5yLlEMfojM4rIMD+uAj+kxIHvvBoQ8OGRzWIho9qHDYk9EZHPZDdA9cMjishYPoPnBTahq7tV1btVyH9JjKKquk8yrpvBKVVdI5lXReZZV1SI9pq5Y39JBIUqGQPhK3ao+08C5JhfRtF8feunH880L69VV70u8vFBoaI7wP0fVd1iEaffDCuUhF9yE6g8s6RKMPXqLPpct+iO6DQwaXtYhEDy4UvSejM7jsh3ZfB8lnLaJF9yHjS1q1l0Ht06D2aY4WaJnWaa4W6Qr16DWN6BUd0X7tqOuF1qoxb3n6cWZIOrxDGjkivTEiXdaTvgXj4nXNf6G16D5E15c81sEBffDBuUg59CE6g8M6OKAPPqLPhOSxHxz64JDBYS2i0YMKhz0ZncFhP0T3wCWDw1o4iOoDN6VqcErH9Jg+F5phdp90y2dDI4T3Ibq+5LEODuiDD85FyqEP0Rkc1sEBffARfSYkj/3g0AeHDA5rEY0eVDjsyegMDvshugcuGRzWwkHefeDX9wAAAAAAAJA7bkoBAAAAAAAgd9yUAgAAAAAAQO64KQUAAAAAAIDcFZIkSfIsODIyot7eXqkgXTU/z8qpV09ISVkqFKUr5+VfnwxkcMsQXV+Szh6XlEjDw8Pq6emJCaH4+SR5rEd0huj6ZCDDZA4zivlEBpf6ZPDKwHxKOawFGcjgUt8lQ7XzKe6mFABMYnNTCgAuwuJf+gDgIphPAFxNN586c8xyIZ6UIgMZLDJE15cqd9Ft8F/62n5PkoEME1nNKOZT22eIrk8GrwzMp5TDWpCBDC71XTJUO5/Cbkpdea205lj+db++QDr7w3RhIuqTgQxuGaLrS9ID89PB6SJqPkke6xGdIbo+GcgwmdOMYj6RIbo+GbwyMJ9SDmtBBjK41HfJUO184oXOAQAAAAAAkDtuSgEAAAAAACB33JQCAAAAAABA7rgpBQAAAAAAgNzFvftejeaoT8u0VteoX5erW6/rtE5qUPu1U6c0lEuGM0elwzul4UHp3GlpVrfU2y8tXivNXphLBIs+RGeIri957AUy+GBPphz6QAaPvUAGL+zJ+B6QocJhP0RniK7vxGFPRmeIrk+GCoez2Y4Z7G9K9Wu5VmijlmhAicqSpKKKKr/5+YDu0UE9qt3apkHta0qG43ukg9uko7vSt1SUpKQkFTrSz5+7R7puQFq6SZq3vCkRLPoQnSG6vuSxF8jggz2ZcugDGTz2Ahm8sCfje0CGCof9EJ0hur4Thz0ZnSG6PhkqHM5mO2ew/vW9FdqoTdqjG7VSRRXVoU51qFOFCZ8XVdQS3aVN2qs7taGh9ZNEemGrtOsOaehxSUm6KEnpza+PfZ5IRx+XHv1AuohJ0tAY4X1wyBBd32EvkMELezIV3QcyeOwFMvhp9z0pMRtcMjjsh+gM0fXdRO9JhwzR9cmQcjibZDC+KXWnNujj2ipJ6tCsKb937Ourta2hG/XQdumpu9PPk/NTf+/Y1w9sSq9rFIc+RGeIri957AUy+GBPphz6QAaPvUAGL+zJ+B6QocJhP0RniK7vxGFPRmeIrk+GCoezSQbTm1L9Wq7V2pbp2tXapn7dXneG43vSRmdxYJN0Ym/dESz6EJ0hur7ksRfI4IM9mXLoAxk89gIZvLAn43tAhgqH/RCdIbq+E4c9GZ0huj4ZKhzOJhlSdd2U+r3f+z0VCgX9xm/8Rv1JJlihjSrpXKZrSzrXkLunB7dJhYyvuFXoTK+vl0MfojNE15c89gIZasd8ujjm08zK4LAXyFC7Zs0niT0pxfeADBUO+yE6Q3T9LGbyz1DRGaLrk6HC4WySIZX5ptQzzzyjP/qjP9LSpUvrTzHBHPVpiQamfYTvUjo0S0v1Uc3RgswZzhxNX9xrukfXLiU5L730qHSmjjcJcOhDdIbo+pLHXiBD7ZhPl8Z8mjkZHPYCGWrXrPkksSel+B6QocJhP0RniK6fxUz+GSo6Q3R9MlQ4nE0yVGS6KXXmzBmtWbNGX/nKVzRnzpz6EkyyTGvHX3U/q0RlLdO6zNcf3ll5tfmsCkXp8I7s1zv0ITpDdH3JYy+QoTbMp+kxn2ZGBoe9QIbaNHM+SexJKb4HZKhw2A/RGaLr12qm/wwVnSG6PhkqHM4mGSoyRVi/fr0+8pGP6M4775z2e0dHRzUyMnLBx1SuUX+WSJMkmqtFma8eHmxABEkjR7Jf69CH6AzR9SWPvUCG2jCfqsN8av0MDnuBDLVp5nyS2JNSfA/IUOGwH6IzRNevVbUzqhXnk0OG6PpkqHA4m2SoqPm3Bx988EH99V//tZ555pmqvn/Lli363d/93ar//MvVrWKdr79eVIeuUE/m68+drrz9YVZ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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def simulate_game(\n", - " nr_of_games: int, policies: tuple[GamePolicy, GamePolicy], tqdm_on: bool = False\n", + " nr_of_games: int,\n", + " policies: tuple[GamePolicy, GamePolicy],\n", + " tqdm_on: bool = False,\n", ") -> tuple[np.ndarray, np.ndarray]:\n", " \"\"\"Simulates a stack of games.\n", "\n", " Args:\n", " nr_of_games: The number of games that should be simulated.\n", " policies: The policies that should be used to simulate the game.\n", + " tqdm_on: Switches tqdm on.\n", "\n", " Returns:\n", " A stack of board histories and actions.\n", " \"\"\"\n", - " board_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 8, 8), dtype=int)\n", - " action_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 2), dtype=int)\n", + " board_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 8, 8), dtype=np.int8)\n", + " action_history_stack = np.zeros((SIMULATE_TURNS, nr_of_games, 2), dtype=np.int8)\n", " current_boards = get_new_games(nr_of_games)\n", " for turn_index in tqdm(range(SIMULATE_TURNS)) if tqdm_on else range(SIMULATE_TURNS):\n", " policy_index = turn_index % 2\n", @@ -1194,17 +1076,9 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "9.48 s ± 330 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" - ] - } - ], + "outputs": [], "source": [ "%timeit simulate_game(100, (RandomPolicy(1), RandomPolicy(1)))" ] @@ -1226,25 +1100,16 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(70, 100, 8, 8)\n", - "(70, 100, 2)\n" - ] - } - ], + "outputs": [], "source": [ "if not os.path.exists(\"rnd_history.npy\") and not os.path.exists(\"rnd_action.npy\"):\n", " rnds = RandomPolicy(1), RandomPolicy(1)\n", - " simulation_results = simulate_game(100, rnds, tqdm_on=True)\n", + " simulation_results = simulate_game(10_000, rnds, tqdm_on=True)\n", " _board_history, _action_history = simulation_results\n", - " np.save(\"rnd_history.npy\", _board_history)\n", - " np.save(\"rnd_action.npy\", _action_history)\n", + " np.save(\"rnd_history.npy\", np.astpye.astype(np.int8))\n", + " np.save(\"rnd_action.npy\", _action_history.astype(np.int8))\n", "else:\n", " _board_history = np.load(\"rnd_history.npy\")\n", " _action_history = np.load(\"rnd_action.npy\")\n", @@ -1252,20 +1117,18 @@ "print(_action_history.shape)" ] }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", - "execution_count": 84, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(70, 100, 8, 8)\n", - "(70, 100, 2)\n" - ] - } - ], + "outputs": [], "source": [ "print(_board_history.shape)\n", "print(_action_history.shape)" @@ -1273,116 +1136,55 @@ }, { "cell_type": "code", - "execution_count": 113, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(70, 100)" - ] - }, - "execution_count": 113, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "__board_history = _board_history.copy()\n", - "__board_history[1::2] = __board_history[1::2] * -1\n", - "poss_turn = np.sum(\n", - " get_possible_turns(__board_history.reshape((-1, 8, 8))).reshape(70, -1, 8, 8),\n", - " axis=(2, 3),\n", - ")\n", + "if not os.path.exists(\"turn_possible.npy\"):\n", + " __board_history = _board_history.copy()\n", + " __board_history[1::2] = __board_history[1::2] * -1\n", + "\n", + " _poss_turns = get_possible_turns(\n", + " __board_history.reshape((-1, 8, 8)), tqdm_on=True\n", + " ).reshape((70, -1, 8, 8))\n", + " np.save(_poss_turns, \"turn_possible.npy\")\n", + " del __board_history\n", + "_poss_turns = np.load(\"turn_possible.npy\")\n", + "poss_turn = np.sum(_poss_turns, axis=(2, 3))\n", "poss_turn.shape" ] }, { "cell_type": "code", - "execution_count": 122, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "mean_possiblilites = np.mean(poss_turn, axis=1)\n", + "mean_possibilities = np.mean(poss_turn, axis=1)\n", "plt.title(\n", - " f\"Mean turn possible per turn {np.prod(np.extract(mean_possiblilites, mean_possiblilites))}\"\n", + " f\"Mean turn possible per turn {np.prod(np.extract(mean_possibilities, mean_possibilities))}\"\n", ")\n", - "plt.plot(mean_possiblilites)\n", - "plt.show()" + "plt.plot(mean_possibilities)\n", + "plt.show()\n", + "del mean_possibilities" ] }, { "cell_type": "code", - "execution_count": 114, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "bcb93d3e5e0b4c5ea594ad05ce99838d", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(IntSlider(value=35, description='turn', max=70), Output()), _dom_classes=('widget-intera…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "@interact(turn=(0, 70))\n", + "@interact(turn=(0, 69))\n", "def poss_turn_count(turn):\n", " plt.hist(poss_turn[turn])" ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(70, 100)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[ 0.046875, 0.046875, 0.046875, ..., 0.046875, 0.046875,\n", - " 0.046875],\n", - " [-0.046875, -0.046875, -0.046875, ..., -0.046875, -0.046875,\n", - " -0.046875],\n", - " [ 0.046875, 0.046875, 0.046875, ..., 0.046875, 0.046875,\n", - " 0.046875],\n", - " ...,\n", - " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", - " 0. ],\n", - " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", - " 0. ],\n", - " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", - " 0. ]])" - ] - }, - "execution_count": 52, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "def calculate_direct_score(board_history: np.ndarray) -> np.ndarray:\n", " boards_evaluated = np.reshape(\n", @@ -1401,30 +1203,11 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "36fb809b8d9e42b79512d6d788b2008f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(IntSlider(value=35, description='turn', max=70), Output()), _dom_classes=('widget-intera…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "from ipywidgets import interact\n", - "import matplotlib.pyplot as plt\n", - "\n", - "\n", - "@interact(turn=(0, 70))\n", + "@interact(turn=(0, 69))\n", "def hist_direct_score(turn):\n", " score_history = calculate_direct_score(_board_history) * 64\n", " score_history[1::2] = score_history[1::2] * -1\n", @@ -1436,27 +1219,9 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(100,)\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def calculate_final_evaluation_for_history(board_history: np.ndarray) -> np.ndarray:\n", " final_evaluation = final_boards_evaluation(board_history[-1])\n", @@ -1473,20 +1238,9 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def calculate_who_won(board_history: np.ndarray) -> np.ndarray:\n", " who_won = evaluate_who_won(board_history[-1])\n", @@ -1500,22 +1254,11 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": null, "metadata": { "scrolled": false }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def history_changed(board_history: np.ndarray) -> np.ndarray:\n", " return ~np.all(\n", @@ -1531,20 +1274,9 @@ }, { "cell_type": "code", - "execution_count": 125, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(70, 100)" - ] - }, - "execution_count": 125, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "def get_gamma_table(board_history, gamma_value: float):\n", " unchanged = history_changed(board_history)\n", @@ -1558,22 +1290,9 @@ }, { "cell_type": "code", - "execution_count": 126, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'calulate_fina_score' is not defined", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[1;32mIn[126], line 25\u001B[0m\n\u001B[0;32m 20\u001B[0m combined_score[turn \u001B[38;5;241m-\u001B[39m \u001B[38;5;241m1\u001B[39m] \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m values\n\u001B[0;32m 22\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m combined_score\n\u001B[1;32m---> 25\u001B[0m np\u001B[38;5;241m.\u001B[39mmax(\u001B[43mcalculate_q_reword\u001B[49m\u001B[43m(\u001B[49m\u001B[43m_board_history\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mgamma\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;241;43m0.8\u001B[39;49m\u001B[43m)\u001B[49m, axis\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m1\u001B[39m)\n", - "Cell \u001B[1;32mIn[126], line 16\u001B[0m, in \u001B[0;36mcalculate_q_reword\u001B[1;34m(board_history, who_won_fraction, final_score_fraction, gamma)\u001B[0m\n\u001B[0;32m 12\u001B[0m combined_score \u001B[38;5;241m=\u001B[39m np\u001B[38;5;241m.\u001B[39mzeros_like(gama_table)\n\u001B[0;32m 13\u001B[0m combined_score \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m calculate_direct_score(board_history) \u001B[38;5;241m*\u001B[39m (\n\u001B[0;32m 14\u001B[0m \u001B[38;5;241m1\u001B[39m \u001B[38;5;241m-\u001B[39m who_won_fraction \u001B[38;5;241m+\u001B[39m final_score_fraction\n\u001B[0;32m 15\u001B[0m )\n\u001B[1;32m---> 16\u001B[0m combined_score[\u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m] \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m \u001B[43mcalulate_fina_score\u001B[49m(board_history) \u001B[38;5;241m*\u001B[39m final_score_fraction\n\u001B[0;32m 17\u001B[0m combined_score[\u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m] \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m calculate_who_won(board_history) \u001B[38;5;241m*\u001B[39m who_won_fraction\n\u001B[0;32m 18\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m turn \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28mrange\u001B[39m(SIMULATE_TURNS \u001B[38;5;241m-\u001B[39m \u001B[38;5;241m1\u001B[39m , \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m, \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m):\n", - "\u001B[1;31mNameError\u001B[0m: name 'calulate_fina_score' is not defined" - ] - } - ], + "outputs": [], "source": [ "def calculate_q_reword(\n", " board_history: np.ndarray,\n", @@ -1590,7 +1309,7 @@ " combined_score += calculate_direct_score(board_history) * (\n", " 1 - who_won_fraction + final_score_fraction\n", " )\n", - " combined_score[-1] += calulate_fina_score(board_history) * final_score_fraction\n", + " combined_score[-1] += calulate_final_score(board_history) * final_score_fraction\n", " combined_score[-1] += calculate_who_won(board_history) * who_won_fraction\n", " for turn in range(SIMULATE_TURNS - 1, -1, -1):\n", " values = gama_table[turn] * combined_score[turn]\n", -- 2.49.0 From e199c9ab5524c5026bca30c78c65dcf5c8b50807 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sat, 18 Feb 2023 00:03:13 +0100 Subject: [PATCH 28/31] Reworked some plots --- main.ipynb | 599 +++++++++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 515 insertions(+), 84 deletions(-) diff --git a/main.ipynb b/main.ipynb index 5924f9a..89f351a 100644 --- a/main.ipynb +++ b/main.ipynb @@ -85,7 +85,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -126,7 +126,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 97, "metadata": {}, "outputs": [], "source": [ @@ -138,7 +138,9 @@ "from abc import ABC\n", "from tqdm.notebook import tqdm\n", "from ipywidgets import interact\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd" ] }, { @@ -152,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 98, "metadata": {}, "outputs": [], "source": [ @@ -176,9 +178,27 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-1, -1],\n", + " [-1, 0],\n", + " [-1, 1],\n", + " [ 0, -1],\n", + " [ 0, 1],\n", + " [ 1, -1],\n", + " [ 1, 0],\n", + " [ 1, 1]])" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "DIRECTIONS: Final[np.ndarray] = np.array(\n", " [[i, j] for i in range(-1, 2) for j in range(-1, 2) if j != 0 or i != 0],\n", @@ -197,9 +217,21 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-1, 1],\n", + " [ 1, -1]])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "START_SQUARE: Final[np.ndarray] = np.array(\n", " [[ENEMY, PLAYER], [PLAYER, ENEMY]], dtype=int\n", @@ -220,9 +252,27 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, -1, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 1, -1, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 0, 0, 0, 0, 0, 0, 0, 0]])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def get_new_games(number_of_games: int) -> np.ndarray:\n", " \"\"\"Generates a stack of initialised game boards.\n", @@ -243,7 +293,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -288,9 +338,20 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def plot_othello_board(board: np.ndarray, ax=None) -> None:\n", " \"\"\"Plots a single otello board.\n", @@ -337,7 +398,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -367,7 +428,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -404,11 +465,24 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 11, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[1, 1, 1],\n", + " [1, 0, 1],\n", + " [1, 1, 1]]])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "SURROUNDING: Final = np.array(\n", " [[[1, 1, 1], [1, 0, 1], [1, 1, 1]]]\n", @@ -418,9 +492,35 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8.86 ms ± 584 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "860 ms ± 12.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[[False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, True, False, False, False, False],\n", + " [False, False, True, False, False, False, False, False],\n", + " [False, False, False, False, False, True, False, False],\n", + " [False, False, False, False, True, False, False, False],\n", + " [False, False, False, False, False, False, False, False],\n", + " [False, False, False, False, False, False, False, False]]])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def _recursive_steps(\n", " board: np.ndarray,\n", @@ -513,7 +613,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -548,7 +648,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -617,9 +717,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "182 µs ± 6.7 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "34.4 µs ± 1.82 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "32.2 µs ± 743 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" + ] + } + ], "source": [ "def final_boards_evaluation(boards: np.ndarray) -> np.ndarray:\n", " \"\"\"Evaluates the board at the end of the game.\n", @@ -687,7 +797,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -699,9 +809,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "86.7 ms ± 1.18 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def do_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n", " \"\"\"Executes a single move on a stack o Othello boards.\n", @@ -801,7 +929,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -895,7 +1023,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -926,7 +1054,8 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, + "metadata": {}, "outputs": [], "source": [ "class GreedyPolicy(GamePolicy):\n", @@ -955,10 +1084,7 @@ " for direction in DIRECTIONS\n", " )\n", " return policies" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", @@ -979,9 +1105,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.02 s ± 31.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", + "1.01 s ± 35 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def single_turn(\n", " current_boards: np, policy: GamePolicy\n", @@ -1029,11 +1174,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": { "scrolled": false }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def simulate_game(\n", " nr_of_games: int,\n", @@ -1076,9 +1232,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "10.5 s ± 737 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + } + ], "source": [ "%timeit simulate_game(100, (RandomPolicy(1), RandomPolicy(1)))" ] @@ -1092,17 +1256,35 @@ "\n", "1. What is the expected distribution of scores\n", "2. What is the expected distribution of possible actions\n", + "\n", " a. over time\n", + " \n", " b. ober space\n", "\n", - "The easiest and most robust way to analyse this is when analyzing randomly played games." + "The easiest and robustest way to analyse this is when analyzing randomly played games." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For this pupose we played a sample of 10k games and saved them for later analysis." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 99, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(70, 10000, 8, 8)\n", + "(70, 10000, 2)\n" + ] + } + ], "source": [ "if not os.path.exists(\"rnd_history.npy\") and not os.path.exists(\"rnd_action.npy\"):\n", " rnds = RandomPolicy(1), RandomPolicy(1)\n", @@ -1119,26 +1301,27 @@ }, { "cell_type": "markdown", - "source": [], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": null, "metadata": {}, - "outputs": [], "source": [ - "print(_board_history.shape)\n", - "print(_action_history.shape)" + "For those 10k games the possible actions where evaluated and saved for each and every turn in the game." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 107, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(70, 10000, 8, 8)" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "if not os.path.exists(\"turn_possible.npy\"):\n", " __board_history = _board_history.copy()\n", @@ -1146,45 +1329,246 @@ "\n", " _poss_turns = get_possible_turns(\n", " __board_history.reshape((-1, 8, 8)), tqdm_on=True\n", - " ).reshape((70, -1, 8, 8))\n", - " np.save(_poss_turns, \"turn_possible.npy\")\n", + " ).reshape((SIMULATE_TURNS, -1, 8, 8))\n", + " np.save(\"turn_possible.npy\", _poss_turns)\n", " del __board_history\n", "_poss_turns = np.load(\"turn_possible.npy\")\n", - "poss_turn = np.sum(_poss_turns, axis=(2, 3))\n", - "poss_turn.shape" + "_poss_turns.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Those possible turms then where counted for all games in the history stack." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 108, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(70, 10000)" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "mean_possibilities = np.mean(poss_turn, axis=1)\n", - "plt.title(\n", - " f\"Mean turn possible per turn {np.prod(np.extract(mean_possibilities, mean_possibilities))}\"\n", - ")\n", - "plt.plot(mean_possibilities)\n", - "plt.show()\n", - "del mean_possibilities" + "count_poss_turns = np.sum(_poss_turns, axis=(2, 3))\n", + "count_poss_turns.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And the po" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 119, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d4dc3ee2dff24deaaacebbf4e7e9dddf", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(IntSlider(value=34, description='turn', max=69), Output()), _dom_classes=('widget-intera…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ + "mean_possibilitie_count = np.mean(count_poss_turns, axis=1)\n", + "std_possibilitie_count = np.std(count_poss_turns, axis=1)\n", + "\n", + "\n", "@interact(turn=(0, 69))\n", "def poss_turn_count(turn):\n", - " plt.hist(poss_turn[turn])" + " fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 7))\n", + " fig.suptitle(\n", + " f\"Action space size analysis\\nThe total size is estimated to be around {np.prod(np.extract(mean_possibilitie_count, mean_possibilitie_count)):.4g}\"\n", + " )\n", + " ax1.hist(count_poss_turns[turn], density=True)\n", + " ax1.set_title(f\"Histogram of the action space size for turn {turn}\")\n", + " ax1.set_xlabel(\"Action space size\")\n", + " ax1.set_ylabel(\"Action space size probability\")\n", + " ax2.set_title(f\"Mean size of the action space per turn\")\n", + " ax2.set_xlabel(\"Turn\")\n", + " ax2.set_ylabel(\"Average possible moves\")\n", + "\n", + " ax2.errorbar(\n", + " range(70),\n", + " mean_possibilitie_count,\n", + " yerr=std_possibilitie_count,\n", + " label='=\"Mean action space size with error bars',\n", + " )\n", + " ax2.scatter(turn, mean_possibilitie_count[turn], marker=\"x\")\n", + " ax2.legend()\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It is interesting to see that the action space for the first player (white) is much smaller than for the second palyer." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 124, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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Total mean actionspace
white5.687159e+18
black3.753117e+20
\n", + "
" + ], + "text/plain": [ + " Total mean actionspace\n", + "white 5.687159e+18\n", + "black 3.753117e+20" + ] + }, + "execution_count": 124, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "white = mean_possibilitie_count[::2]\n", + "black = mean_possibilitie_count[1::2]\n", + "df = pd.DataFrame(\n", + " [\n", + " {\n", + " \"white\": np.prod(np.extract(white, white)),\n", + " \"black\": np.prod(np.extract(black, black)),\n", + " }\n", + " ],\n", + " index=[\"Total mean actionspace\"],\n", + ").T\n", + "del white, black\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7002a64f4eb740c7bcbb4810783e70fa", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(IntSlider(value=34, description='turn', max=69), Output()), _dom_classes=('widget-intera…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "@interact(turn=(0, 69))\n", + "def turn_distribution_heatmap(turn):\n", + " turn_possibility_on_field = np.mean(_poss_turns[turn], axis=0)\n", + "\n", + " uniform_data = np.random.rand(10, 12)\n", + " sns.heatmap(\n", + " turn_possibility_on_field,\n", + " linewidth=0.5,\n", + " square=True,\n", + " annot=True,\n", + " xticklabels=\"ABCDEFGH\",\n", + " yticklabels=list(range(1, 9)),\n", + " )\n", + " plt.title(f\"Headmap of where stones can be placed on turn {turn}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(70, 10000)\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[ 0.046875, 0.046875, 0.046875, ..., 0.046875, 0.046875,\n", + " 0.046875],\n", + " [-0.046875, -0.046875, -0.046875, ..., -0.046875, -0.046875,\n", + " -0.046875],\n", + " [ 0.046875, 0.046875, 0.046875, ..., 0.078125, 0.046875,\n", + " 0.046875],\n", + " ...,\n", + " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", + " 0. ],\n", + " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", + " 0. ],\n", + " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", + " 0. ]])" + ] + }, + "execution_count": 126, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def calculate_direct_score(board_history: np.ndarray) -> np.ndarray:\n", " boards_evaluated = np.reshape(\n", @@ -1201,21 +1585,66 @@ "calculate_direct_score(_board_history)" ] }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "679fea405f704503ae407321cab3779a", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(IntSlider(value=34, description='turn', max=69), Output()), _dom_classes=('widget-intera…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "score_history = calculate_direct_score(_board_history) * 64\n", + "score_history[1::2] = score_history[1::2] * -1\n", + "\n", + "\n", + "@interact(turn=(0, 69))\n", + "def hist_direct_score(turn):\n", + " fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 7))\n", + " fig.suptitle(\n", + " f\"Action space size analysis\\nThe total size is estimated to be around {np.prod(np.extract(mean_possibilitie_count, mean_possibilitie_count)):.4g}\"\n", + " )\n", + "\n", + " ax1.set_title(\n", + " f\"Histogram of turn {turn} by {'white' if turn % 2 == 0 else 'black'}\"\n", + " )\n", + "\n", + " ax1.hist(score_history[turn], density=True)\n", + " ax1.set_xlabel(\"Action space size\")\n", + " ax1.set_ylabel(\"Action space size probability\")\n", + " ax2.set_title(f\"Mean size of the action space per turn\")\n", + " ax2.set_xlabel(\"Turn\")\n", + " ax2.set_ylabel(\"Average possible moves\")\n", + "\n", + " ax2.errorbar(\n", + " range(70),\n", + " mean_possibilitie_count,\n", + " yerr=std_possibilitie_count,\n", + " label='=\"Mean action space size with error bars',\n", + " )\n", + " ax2.scatter(turn, mean_possibilitie_count[turn], marker=\"x\")\n", + " ax2.legend()\n", + " plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "@interact(turn=(0, 69))\n", - "def hist_direct_score(turn):\n", - " score_history = calculate_direct_score(_board_history) * 64\n", - " score_history[1::2] = score_history[1::2] * -1\n", - " # print(score_history[turn])\n", - " plt.title(f\"Histogram of turn {turn} by {'white' if turn % 2 == 0 else 'black'}\")\n", - " plt.hist(score_history[turn], density=True)\n", - " plt.show()" - ] + "source": [] }, { "cell_type": "code", @@ -1309,7 +1738,9 @@ " combined_score += calculate_direct_score(board_history) * (\n", " 1 - who_won_fraction + final_score_fraction\n", " )\n", - " combined_score[-1] += calulate_final_score(board_history) * final_score_fraction\n", + " combined_score[-1] += (\n", + " calculate_final_evaluation_for_history(board_history) * final_score_fraction\n", + " )\n", " combined_score[-1] += calculate_who_won(board_history) * who_won_fraction\n", " for turn in range(SIMULATE_TURNS - 1, -1, -1):\n", " values = gama_table[turn] * combined_score[turn]\n", -- 2.49.0 From c0943e43096a8d613591b9471844ec9d16f8c713 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sat, 18 Feb 2023 00:12:29 +0100 Subject: [PATCH 29/31] Added the points per score at turn label. --- main.ipynb | 146 ++++++++++++++++++++++++++++++++++++------------- poetry.lock | 93 ++++++++++++++++++++++--------- pyproject.toml | 1 + 3 files changed, 178 insertions(+), 62 deletions(-) diff --git a/main.ipynb b/main.ipynb index 89f351a..1c4a510 100644 --- a/main.ipynb +++ b/main.ipynb @@ -1373,13 +1373,13 @@ }, { "cell_type": "code", - "execution_count": 119, + "execution_count": 145, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d4dc3ee2dff24deaaacebbf4e7e9dddf", + "model_id": "b098bb4da154488b8b4c22722833e8c0", "version_major": 2, "version_minor": 0 }, @@ -1414,7 +1414,7 @@ " range(70),\n", " mean_possibilitie_count,\n", " yerr=std_possibilitie_count,\n", - " label='=\"Mean action space size with error bars',\n", + " label=\"Mean action space size with error bars\",\n", " )\n", " ax2.scatter(turn, mean_possibilitie_count[turn], marker=\"x\")\n", " ax2.legend()\n", @@ -1587,18 +1587,18 @@ }, { "cell_type": "code", - "execution_count": 130, + "execution_count": 146, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "679fea405f704503ae407321cab3779a", + "model_id": "75ffc8765b074cd0b4495ac6075bb6b8", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(IntSlider(value=34, description='turn', max=69), Output()), _dom_classes=('widget-intera…" + "interactive(children=(IntSlider(value=29, description='turn', max=59), Output()), _dom_classes=('widget-intera…" ] }, "metadata": {}, @@ -1610,7 +1610,7 @@ "score_history[1::2] = score_history[1::2] * -1\n", "\n", "\n", - "@interact(turn=(0, 69))\n", + "@interact(turn=(0, 59))\n", "def hist_direct_score(turn):\n", " fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 7))\n", " fig.suptitle(\n", @@ -1618,39 +1618,43 @@ " )\n", "\n", " ax1.set_title(\n", - " f\"Histogram of turn {turn} by {'white' if turn % 2 == 0 else 'black'}\"\n", + " f\"Histogram of scores on turn {turn} by {'white' if turn % 2 == 0 else 'black'}\"\n", " )\n", "\n", " ax1.hist(score_history[turn], density=True)\n", - " ax1.set_xlabel(\"Action space size\")\n", - " ax1.set_ylabel(\"Action space size probability\")\n", - " ax2.set_title(f\"Mean size of the action space per turn\")\n", + " ax1.set_xlabel(\"Points made\")\n", + " ax1.set_ylabel(\"Score probability\")\n", + " ax2.set_title(f\"Points scored at turn\")\n", " ax2.set_xlabel(\"Turn\")\n", - " ax2.set_ylabel(\"Average possible moves\")\n", + " ax2.set_ylabel(\"Average points scored\")\n", "\n", " ax2.errorbar(\n", - " range(70),\n", - " mean_possibilitie_count,\n", - " yerr=std_possibilitie_count,\n", - " label='=\"Mean action space size with error bars',\n", + " range(60),\n", + " np.mean(score_history, axis=1)[:60],\n", + " yerr=np.std(score_history, axis=1)[:60],\n", + " label=\"Mean socre at turn\",\n", " )\n", - " ax2.scatter(turn, mean_possibilitie_count[turn], marker=\"x\")\n", + " ax2.scatter(turn, np.mean(score_history, axis=1)[turn], marker=\"x\", color=\"red\")\n", " ax2.legend()\n", " plt.show()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 147, "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def calculate_final_evaluation_for_history(board_history: np.ndarray) -> np.ndarray:\n", " final_evaluation = final_boards_evaluation(board_history[-1])\n", @@ -1658,7 +1662,6 @@ "\n", "\n", "assert len(calculate_final_evaluation_for_history(_board_history).shape) == 1\n", - "print(calculate_final_evaluation_for_history(_board_history).shape)\n", "_final_eval = calculate_final_evaluation_for_history(_board_history)\n", "plt.title(\"Histogram over the score distribtuion\")\n", "plt.hist((_final_eval * 64), density=True)\n", @@ -1667,9 +1670,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 148, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def calculate_who_won(board_history: np.ndarray) -> np.ndarray:\n", " who_won = evaluate_who_won(board_history[-1])\n", @@ -1683,11 +1697,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 149, "metadata": { "scrolled": false }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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Uo0cP2Ww2vf32200es3btWp1//vlyuVw688wz9dJLL7WgqAAAoD0KOIyUlJRoyJAhmjdvXrP237Vrl8aNG6eLL75YW7du1fTp03XbbbdpxYoVARcWAAC0PwFfKO/yyy/X5Zdf3uz9FyxYoL59++rJJ5+UJJ1zzjn66KOP9Pvf/17Z2dn1HlNRUaGKigr//aKiokCLCQDAacUYo2OllTp4vEIHiyt06HiFisqrVOXxqspj5D7xtcrrVaXHyBgjc+I4r5GMkaq3tMyU0X2V1qVD8E4oACG/am9eXp6ysrJqbMvOztb06dMbPCY3N1cPP/xwiEsGAIB1vF6jNz/5Tv/38R7tP1auwyUVqvS0PEy01lVDerTfMJKfn6+UlJQa21JSUlRUVKSysjLFxsbWOWbmzJnKycnx3y8qKlJaWlqoiwoAQFh8/l2hZr3zubbsPVbnscQO0eoW51JSnEvxsVGKctjldNgVZbcpymFXtMOmKLtddptkt9tkk2Sz2WSz6cT3LStTSnxMa06pVUIeRlrC5XLJ5XJZXQwAAILqSIlbv12xTYs27pUxUgenQ9MuOVNjzkxSt04ude3okjMq8ia6hjyMpKamqqCgoMa2goICxcfH19sqAgBAe+PxGr328R79buU3KiyrlCSNH9pDMy8/R6kJ1rVItBUhDyOZmZlatmxZjW2rVq1SZmZmqF8aAADLVXm8+snzH2vDriOSpAGpnfTI+EEa1beLxSVrOwIOI8ePH9eOHTv893ft2qWtW7eqS5cu6t27t2bOnKnvvvtOr7zyiiTpzjvv1DPPPKNf/OIXmjJlij744AP95S9/0dKlS4N3FgAAtFF/335IG3YdUQenQzMuH6CfjOqtKEfkdcU0JuDa2LRpk4YNG6Zhw4ZJknJycjRs2DDNmjVLkrR//37t3bvXv3/fvn21dOlSrVq1SkOGDNGTTz6p559/vsFpvQAAtCdLtvxbkvTjEWmamJlOEKmHzRhj3TyiZioqKlJCQoIKCwsVHx9vdXEAAGiWwrJKjXz0fbmrvHr3njEa1DPB6iKFVXM/v4lnAACEyLLP9std5VX/lDid24N/phtCGAEAIETe2FzdRXPd+b1ka+kCIBGAMAIAQAjsOVyiTXuOym6TrhnW0+ritGmEEQAAQuCNLd9Jksac1c3S1U1PB4QRAACCzOs1enOLr4uGVpGmEEYAAAiyjbuP6N9HyxTnitJlA1OtLk6bRxgBACDI3jzRRXPFeamKdTosLk3bRxgBACCIyis9WvrZfknVs2jQNMIIAABBtOKLfB2vqFKvzrEamc71Z5qDMAIAQBD5umh+dH4v2e2sLdIchBEAAIKkoKhcf99+UJL0I9YWaTbCCAAAQfLO1u/kNdKIPp2VntTR6uKcNggjAAAEgTFGb2w+2UWD5iOMAAAQBF98X6RtBcVyRtk1bnB3q4tzWiGMAAAQBH/71/eSpEsHpighNtri0pxeCCMAAATB3sOlkqRRTOcNGGEEAIAgOHzcLUlKinNZXJLTD2EEAIAgOFRSIUnq0tFpcUlOP4QRAACC4EiJr2WEMBIowggAAK1U6fHqWGmlJKkr3TQBI4wAANBKR0+0ithtUiIzaQJGGAEAoJUOnwgjXTo6uR5NCxBGAABoJd9Mmq4d6aJpCcIIAACtdJiZNK1CGAEAoJX8LSPMpGkRwggAAK3kaxlhwbOWIYwAANBKR04ZwIrAEUYAAGilQ3TTtAphBACAVjp8vLqbhtk0LUMYAQCglXzdNLSMtAxhBACAVjq5zghhpCUIIwAAtEJFlUfFFVWS6KZpKcIIAACt4OuiibLbFB8bZXFpTk+EEQAAWuHUBc9sNq5L0xKEEQAAWuHQcd9S8HTRtBRhBACAVvB10yQxk6bFCCMAALQCM2lajzACAEArHCqhm6a1CCMAALTCEZaCbzXCCAAArXCYMSOtRhgBAKAVDjObptUIIwAAtMJhrkvTaoQRAABawTebJomWkRYjjAAA0EKl7iqVVXokSV1oGWkxwggAAC3kaxVxRdnV0emwuDSnL8IIAAAtdHImjYvr0rQCYQQAgBY64l/wjC6a1iCMAADQQodY8CwoCCMAALTQyevSMJOmNQgjAAC0kK+bhpaR1iGMAADQQlyxNzgIIwAAtNAh/+qrdNO0BmEEAIAW8nfT0DLSKoQRAABa6DCzaYKCMAIAQAsYY/xhhHVGWocwAgBACxyvqJLb45XE1N7WalEYmTdvntLT0xUTE6OMjAxt2LCh0f3nzp2rs88+W7GxsUpLS9N9992n8vLyFhUYAIC2wNcq0tHpUCzXpWmVgMPI4sWLlZOTo9mzZ2vLli0aMmSIsrOzdeDAgXr3f+211zRjxgzNnj1bX331lV544QUtXrxYv/zlL1tdeAAArHLYtxQ840VaLeAwMmfOHN1+++2aPHmyBg4cqAULFqhDhw568cUX691//fr1Gj16tH7yk58oPT1dl112mW666aYmW1MAAGjLWH01eAIKI263W5s3b1ZWVtbJJ7DblZWVpby8vHqPueCCC7R582Z/+Ni5c6eWLVumK664osHXqaioUFFRUY0bAABtyckr9tIy0lpRgex86NAheTwepaSk1NiekpKir7/+ut5jfvKTn+jQoUMaM2aMjDGqqqrSnXfe2Wg3TW5urh5++OFAigYAQFgdPs4Ve4Ml5LNp1q5dq8cee0x//OMftWXLFr355ptaunSpfv3rXzd4zMyZM1VYWOi/7du3L9TFBAAgIIdZfTVoAmoZSUpKksPhUEFBQY3tBQUFSk1NrfeYBx98ULfccotuu+02SdJ5552nkpIS3XHHHXrggQdkt9fNQy6XSy4XP1wAQNvFdWmCJ6CWEafTqeHDh2v16tX+bV6vV6tXr1ZmZma9x5SWltYJHA5H9RQoY0yg5QUAoE04zBV7gyaglhFJysnJ0aRJkzRixAiNGjVKc+fOVUlJiSZPnixJmjhxonr27Knc3FxJ0lVXXaU5c+Zo2LBhysjI0I4dO/Tggw/qqquu8ocSAABON8ymCZ6Aw8iECRN08OBBzZo1S/n5+Ro6dKiWL1/uH9S6d+/eGi0hv/rVr2Sz2fSrX/1K3333nbp166arrrpKjz76aPDOAgCAMDs5ZoSWkdaymdOgr6SoqEgJCQkqLCxUfHy81cUBAEQ4r9eo/6/eU5XX6J8zxyo1IcbqIrVJzf385to0AAAEqKi8UlXe6v/lmdrbeoQRAAACdOjEeJH4mCg5o/gobS1qEACAAB1hjZGgIowAABAg3+qrrDESHIQRAAACdIiZNEFFGAEAIEBHTowZ6cIaI0FBGAEAIEC+1Ve5Ym9wEEYAAAgQ16UJLsIIAAAB8rWMdGE2TVAQRgAACJCvZSSJlpGgIIwAABAg33VpujBmJCgIIwAABMDjNTpayhV7g4kwAgBAAI6WumWMZLNJnTtEW12cdoEwAgBAAHzjRRJjoxXl4GM0GKhFAAAC4JtJw3VpgocwAgBAAFhjJPgIIwAABMB/kTxm0gQNYQQAgAAcKWEmTbARRgAACABX7A0+wggAAAHwd9MwZiRoCCMAAATA303DbJqgIYwAABAAZtMEH2EEAIAAHGbMSNARRgAAaCZ3lVeFZZWSmE0TTIQRAACayXeBPIfdpoRYrksTLIQRAACaqehEq0inmCjZ7TaLS9N+EEYAAGimskqPJKlDtMPikrQvhBEAAJqpzF0dRmKchJFgIowAANBM/pYRwkhQEUYAAGim8hNhJJZumqAijAAA0Ey+lpEYwkhQEUYAAGimMrdXEi0jwUYYAQCgmUrdVZKkWMaMBBVhBACAZmLMSGgQRgAAaCbGjIQGYQQAgGbyjRlham9wEUYAAGimMrppQoIwAgBAM/nHjNAyElSEEQAAmsk3m4YxI8FFGAEAoJnKKllnJBQIIwAANFO5m26aUCCMAADQTAxgDQ3CCAAAzVTGANaQIIwAANBMZW5aRkKBMAIAQDMxtTc0CCMAADRTKS0jIUEYAQCgGYwxXJsmRAgjAAA0Q0WV1/893TTBRRgBAKAZfINXJbppgo0wAgBAM/i6aJxRdjnsNotL074QRgAAaAYWPAsdwggAAM3AGiOhQxgBAKAZWH01dAgjAAA0g69lhGm9wUcYAQCgGU6OGeGjM9ioUQAAmsG3FHwHZ5TFJWl/WhRG5s2bp/T0dMXExCgjI0MbNmxodP9jx45p6tSp6t69u1wul/r3769ly5a1qMAAAFiBbprQCTjeLV68WDk5OVqwYIEyMjI0d+5cZWdna9u2bUpOTq6zv9vt1qWXXqrk5GQtWbJEPXv21J49e5SYmBiM8gMAEBYMYA2dgMPInDlzdPvtt2vy5MmSpAULFmjp0qV68cUXNWPGjDr7v/jiizpy5IjWr1+v6OhoSVJ6enrrSg0AQJgxZiR0AqpRt9utzZs3Kysr6+QT2O3KyspSXl5evcf89a9/VWZmpqZOnaqUlBQNGjRIjz32mDweT737S1JFRYWKiopq3AAAsBLrjIROQGHk0KFD8ng8SklJqbE9JSVF+fn59R6zc+dOLVmyRB6PR8uWLdODDz6oJ598Uv/zP//T4Ovk5uYqISHBf0tLSwukmAAABJ1/zAjdNEEX8rYmr9er5ORkPfvssxo+fLgmTJigBx54QAsWLGjwmJkzZ6qwsNB/27dvX6iLCQBAo1gOPnQCGjOSlJQkh8OhgoKCGtsLCgqUmppa7zHdu3dXdHS0HI6TP7xzzjlH+fn5crvdcjqddY5xuVxyuVyBFA0AgJAq80/tJYwEW0AtI06nU8OHD9fq1av927xer1avXq3MzMx6jxk9erR27Nghr9fr3/bNN9+oe/fu9QYRAADaonJaRkIm4G6anJwcPffcc3r55Zf11Vdf6a677lJJSYl/ds3EiRM1c+ZM//533XWXjhw5onvvvVfffPONli5dqscee0xTp04N3lkAABBirDMSOgFP7Z0wYYIOHjyoWbNmKT8/X0OHDtXy5cv9g1r37t0ru/1kxklLS9OKFSt03333afDgwerZs6fuvfde3X///cE7CwAAQox1RkLHZowxVheiKUVFRUpISFBhYaHi4+OtLg4AIAKNf+YjffrvQr0waYTGnpPS9AFo9uc3K7cAANAMzKYJHcIIAADN4AsjrDMSfIQRAACaocxdPSuUqb3BRxgBAKAZmNobOoQRAACaYIxhzEgIEUYAAGiC2+OVx1s9+ZQxI8FHGAEAoAnl7pOriNMyEnyEEQAAmuDroomy2xTt4KMz2KhRAACawHiR0CKMAADQBN91aVgKPjQIIwAANIHr0oQWYQQAgCawxkhoEUYAAGhC6YlumhjCSEgQRgAAaAIDWEOLMAIAQBPKGcAaUoQRAACaQMtIaBFGAABoArNpQoswAgBAE/zrjNAyEhKEEQAAmlBOy0hIEUYAAGgCU3tDizACAEATGMAaWoQRAACacDKM8LEZCtQqAABN8K0z0sEZZXFJ2ifCCAAATfC1jMQwgDUkCCMAADSBMSOhRRgBAKAJrDMSWoQRAACacHIFVj42Q4FaBQCgCWWsMxJShBEAAJrAmJHQIowAANAE33LwTO0NDcIIAACNqPR4VekxkmgZCRXCCAAAjfC1ikhSDANYQ4JaBQCgEb7xInab5HTwsRkK1CoAAI04dY0Rm81mcWnaJ8IIAACNOLnGCONFQoUwAgBAI1hjJPQIIwAANKLMP62XMBIqhBEAABpRzoJnIUcYAQCgEWVuryS6aUKJMAIAQCNK3VWSGMAaSoQRAAAaQTdN6BFGAABoBBfJCz3CCAAAjfCPGaGbJmQIIwAANMI/tZeWkZAhjAAA0IhyVmANOcIIAACNYAXW0COMAADQiFIGsIYcYQQAgEb4r9pLN03IEEYAAGgE64yEHmEEAIBG+GbTMGYkdAgjAAA0wtdNw1V7Q4cwAgBAI5jaG3qEEQAAGsFy8KFHGAEAoBGlrDMScoQRAAAaUUY3TcgRRgAAaIDHa+Suqr5QHt00odOiMDJv3jylp6crJiZGGRkZ2rBhQ7OOW7RokWw2m6655pqWvCwAAGHlG7wqEUZCKeAwsnjxYuXk5Gj27NnasmWLhgwZouzsbB04cKDR43bv3q2f//znuvDCC1tcWAAAwqnslDASE01nQqgEXLNz5szR7bffrsmTJ2vgwIFasGCBOnTooBdffLHBYzwej26++WY9/PDDOuOMM1pVYAAAwsW/FHy0QzabzeLStF8BhRG3263NmzcrKyvr5BPY7crKylJeXl6Dxz3yyCNKTk7WT3/602a9TkVFhYqKimrcAAAIN9YYCY+AwsihQ4fk8XiUkpJSY3tKSory8/PrPeajjz7SCy+8oOeee67Zr5Obm6uEhAT/LS0tLZBiAgAQFKVu1hgJh5B2gBUXF+uWW27Rc889p6SkpGYfN3PmTBUWFvpv+/btC2EpAQCo38nr0jBeJJSiAtk5KSlJDodDBQUFNbYXFBQoNTW1zv7ffvutdu/erauuusq/zeutniIVFRWlbdu2qV+/fnWOc7lccrlcgRQNAICgY42R8Ago6jmdTg0fPlyrV6/2b/N6vVq9erUyMzPr7D9gwAB99tln2rp1q/929dVX6+KLL9bWrVvpfgEAtGnlvovkRQf0vzsCFHDt5uTkaNKkSRoxYoRGjRqluXPnqqSkRJMnT5YkTZw4UT179lRubq5iYmI0aNCgGscnJiZKUp3tAAC0Nf5uGlpGQirgMDJhwgQdPHhQs2bNUn5+voYOHarly5f7B7Xu3btXdjt9awCA09/Ji+TxuRZKLWp3mjZtmqZNm1bvY2vXrm302JdeeqklLwkAQNiVMZsmLIh6AAA0wB9G6KYJKcIIAAANODm1lzASSoQRAAAacHLMCGEklAgjAAA0wLccfAe6aUKKMAIAQAN8Y0bopgktwggAAA1gBdbwIIwAANAALpQXHoQRAAAaUM4A1rAgjAAA0ACWgw8PwggAAA1gBdbwIIwAANCA8kqvJKb2hhphBACABrDoWXgQRgAAaADrjIQHYQQAgHp4vYZ1RsKEMAIAQD0qqrz+7+mmCS3CCAAA9fC1ikh004QaYQQAgHr4wogzyi6H3WZxado3wggAAPXwDV5lWm/oEUYAAKgHS8GHD2EEAIB6sMZI+BBGAACoRylrjIQNYQQAgHr4r0vDmJGQI4wAAFAPxoyED2EEAIB6+MaM0E0TeoQRAADqwdTe8CGMAABQD2bThA9hBACAepRzkbywIYwAAFAPpvaGD2EEAIB60E0TPoQRAADqUe5fZ4SPylCjhgEAqActI+FDGAEAoB7+MOKMsrgk7R9hBACAeviXg6dlJOQIIwAA1OPk1F4+KkONGgYAoB5M7Q0fwggAAPVgAGv4EEYAAKgHK7CGD2EEAIB6+C+UF81smlAjjAAAUIsxxt9NE8MA1pCjhgEAqMXt8cprqr9nzEjoEUYAAKjF10UjMZsmHAgjAADU4uuiiXbYFO3gozLUqGEAAGopY42RsCKMAABQC2uMhBdhBACAWnxrjHRgjZGwIIwAAFBLmdsriW6acCGMAABQSxmrr4YVYQQAgFpK3VWSGDMSLoQRAABqKWcAa1gRRgAAqMU/tZdumrAgjAAAUEtZZfUAVlpGwoMwAgBALWVM7Q0rwggAALUwZiS8CCMAANTCcvDhRRgBAKCWUjfrjIQTYQQAgFropgmvFoWRefPmKT09XTExMcrIyNCGDRsa3Pe5557ThRdeqM6dO6tz587KyspqdH8AAKy2v7BMktQ1zmlxSSJDwGFk8eLFysnJ0ezZs7VlyxYNGTJE2dnZOnDgQL37r127VjfddJPWrFmjvLw8paWl6bLLLtN3333X6sIDABAKuw6VSJLOSIqzuCSRwWaMMYEckJGRoZEjR+qZZ56RJHm9XqWlpemee+7RjBkzmjze4/Goc+fOeuaZZzRx4sRmvWZRUZESEhJUWFio+Pj4QIoLAEBAjpa4NezXqyRJXz3yn4wbaYXmfn4H1DLidru1efNmZWVlnXwCu11ZWVnKy8tr1nOUlpaqsrJSXbp0aXCfiooKFRUV1bgBABAOOw8dlyT1SIghiIRJQGHk0KFD8ng8SklJqbE9JSVF+fn5zXqO+++/Xz169KgRaGrLzc1VQkKC/5aWlhZIMQEAaLGdB0900XSjiyZcwjqb5vHHH9eiRYv01ltvKSYmpsH9Zs6cqcLCQv9t3759YSwlACCS7TwxXqRvUkeLSxI5ogLZOSkpSQ6HQwUFBTW2FxQUKDU1tdFjf/e73+nxxx/X+++/r8GDBze6r8vlksvlCqRoAAAExc6D1d00Z3QjjIRLQC0jTqdTw4cP1+rVq/3bvF6vVq9erczMzAaPe+KJJ/TrX/9ay5cv14gRI1peWgAAQsw/k4ZumrAJqGVEknJycjRp0iSNGDFCo0aN0ty5c1VSUqLJkydLkiZOnKiePXsqNzdXkvSb3/xGs2bN0muvvab09HT/2JK4uDjFxfGDBgC0HR6v0e7DpZKkM+imCZuAw8iECRN08OBBzZo1S/n5+Ro6dKiWL1/uH9S6d+9e2e0nG1zmz58vt9ut66+/vsbzzJ49Ww899FDrSg8AQBB9d7RM7iqvnFF29UiMtbo4ESPgdUaswDojAIBwWLvtgG5duFH9U+K08r6LrC7OaS8k64wAANCe+af1svJqWBFGAAA44eTgVcaLhBNhBACAE3yrr7LGSHgRRgAAOIHVV61BGAEAQFKpu0r7C8slMa033AgjAADo5HiRzh2i1bmj0+LSRBbCCAAAoovGSoQRAAB0smWEwavhRxgBAEBcIM9KhBEAACTtPMSCZ1YhjAAAIp4xRrsOsuCZVQgjAICId/B4hYorqmSzSX26drC6OBGHMAIAiHi+VpFenWPlinJYXJrIQxgBAEQ8xotYizACAIh4zKSxFmEEABDx/FfrZY0RSxBGAAARj9VXrUUYAQBEtEqPV3uPlEpi9VWrEEYAABFt35FSVXmNYqMdSo2Psbo4EYkwAgCIaL4umr5JHWW32ywuTWQijAAAItrOQ9Uzafoyk8YyhBEAQETzzaTpx3gRyxBGAAAR7VtfNw0tI5YhjAAAItouVl+1HGEEABCxissrdbC4QhItI1YijAAAIpZvJk1SnEvxMdEWlyZyEUYAABHL30VDq4ilCCMAgIjlv0AeM2ksRRgBAESsb2kZaRMIIwCAiLXrIDNp2gLCCAAgInm9xj9mhJk01iKMAAAiUkFxucoqPXLYberdpYPVxYlohBEAQET64OsDkqQzu8Up2sHHoZWofQBAxDHG6KV/7JYk/XhkmrWFAWEEABB5/rHjsLYfOK6OToduGNHL6uJEPMIIACDivLR+lyTp+uG9WHm1DSCMAAAiyp7DJVp9YrzIxAvSrS0MJBFGAAAR5uX1e2SMdFH/burXjfVF2gLCCAAgYhyvqNLrm/ZJkiaPTre2MPAjjAAAIsabW/6t4ooqnZHUUf9xVjeri4MTCCMAgIjg9Z6cznvr6HTZ7TZrCwQ/wggAICJ8uP2gdh4qUSdXlH50PtN52xLCCAAgIiw80Spyw4g0xbmirC0MaiCMAADavW8PHte6bw7KZpMmXdDH6uKgFsIIAKDde2X9bknS2AHJ6tOVK/S2NYQRAEC7VlReqSWb/y1Jmjy6r8WlQX0IIwCAdm3xhn0qcXt0VnKcLujX1erioB6EEQBAu7Xii3z9dsU2SdXTeW02pvO2RQwnBgC0S29/8p3++/VP5fEaXXFeqiaMSLO6SGgAYQQA0O689vFePfD2ZzJGuu78XvrNdecpykFnQFtFGAEAtCvP/32n/mfpV5KkW37QRw9ffS6rrbZxhBEAQLtgjNHTH+zQnFXfSJLuvKif7v/PsxknchogjAAATnvllR49uXKbnvv7LknSzy/rr6kXn0kQOU0QRgAAp61vDx7Xax/v1ZLN/1ZhWaUk6cErB+qnY1hP5HRCGAEAnFbcVV6t+rJA//fxHq3/9rB/e8/EWP1/2WfrmmE9LSwdWoIwAgA4LXx78Lhe3/RvLdn8bx06XiFJstukSwYk6+aMPvqP/t3kYKDqaYkwAgBos4rLK7X0X/v1+uZ/a/Oeo/7tyZ1cunFkmiaM6q2eibEWlhDB0KJJ1/PmzVN6erpiYmKUkZGhDRs2NLr/66+/rgEDBigmJkbnnXeeli1b1qLCAgDaF2OMyis9Olri1vfHyrTjwHF9/l2h1mw7oJy/bNWoR1drxpufafOeo3LYbRo7IFkL/ut8/WPGJcq57GyCSDsRcMvI4sWLlZOTowULFigjI0Nz585Vdna2tm3bpuTk5Dr7r1+/XjfddJNyc3N15ZVX6rXXXtM111yjLVu2aNCgQUE5CQBA8Blj5PZ4VV7pVUWlR2WVHlVUeeWu8qqiyqtKT/X37hPfl1V6VFxepeLyShVXVKm4vErHy6t0vKJKpe4qlbmrn6PU7VF5pcd/32saL0e/bh11w4g0/WhYTyXHx4Tn5BFWNmNME2+DmjIyMjRy5Eg988wzkiSv16u0tDTdc889mjFjRp39J0yYoJKSEr377rv+bT/4wQ80dOhQLViwoN7XqKioUEVFhf9+UVGR0tLSVFhYqPj4+ECK26gXPtqlfx8tDdrztQXGSGVuj0rcVSp1e1RSceKru0per1FMtEOuaIdiouyKdToUE+WQK9quKq9RZZVXbk/NPzBeI0U5bIp22BXtsCnKbvd/7zVGHq9RlffEV0/1VyOjKLvdf1yU3aboKLui7TbZG5hmZ1T9h89rTn5vTjzg8Rp5je928r4xks0mOU48r91mk8Mu//dWMqounzGqLqvvnAL6bWttGerWqSR/GXxVZLfZZLNJNkk2m0311dypPxNz6s+oGefjex2bzSZ7E6/TUl5j5DHVZfK/X7zV26Xqc5RNJ16/+nx95+0rm00nHrfZapyrt4F6q32Mx/d74PXW+b2o8npV6TGq9Hhr3Jd871+d8h4+8fNooILstpO/V86o6q9RJ+77f3c9Ru4qjyo9Ru4qr4yM//ntdslhs8lury6/16i6zJ5TyuytPq68yhPW96wzyq7YaIdiox3q4HIoo28X3TAiTcPSEpmie5oqKipSQkJCk5/fAbWMuN1ubd68WTNnzvRvs9vtysrKUl5eXr3H5OXlKScnp8a27Oxsvf322w2+Tm5urh5++OFAitYiS//1vbbsPRby1wGA053dJsVEOxQT7ZDTYZczqvqfEmeUQ84ou5wOm2KiHeoUE6VOrmjFxUSpU0yU4lzVXzs4o9TBWR00Yp3Vtw7RUYpx2tXBGaWYKDvLtUewgMLIoUOH5PF4lJKSUmN7SkqKvv7663qPyc/Pr3f//Pz8Bl9n5syZNQKMr2Uk2K4b3kuZ7exy0jbZqn/JnQ51dEapg6v6a6zTIYfdpvJKj8orvSe+Vt8qqrxynPgvK9phl+vEV6fDLrtdqvSc/O/OXeVVldeoyuOV3W5TlN0mh91+4mv1fUmqPLFPlae6mbfKU/2f4In2jnr5WjNq/6dut9uq/5OzSXb7yRYQm2z+1hKv18jjaz3xNvYq4WOTJH9rwKnnFMYy+P97P/nftq9Nwqi69eDUVo7Gas4mX+vCiee0nzyvhvies7qF4dTWleD+hGw68T6x12xh8E2s8L++zMlymIZbsPw/r1rnKtV/jIz8r1/798Fht8npqP6gjXL4vq9uZZTkb/XzeKt/Hr73cUO8XnOyleVEC4vv99MXEny/y9UhwS6bTf6WIs+J3xHvifJH2W2n/C5Xl8tX5phou2JOtKBGO2y0TiBk2uRsGpfLJZfLFfLXuTmjT8hfAwAANC6gNrGkpCQ5HA4VFBTU2F5QUKDU1NR6j0lNTQ1ofwAAEFkCCiNOp1PDhw/X6tWr/du8Xq9Wr16tzMzMeo/JzMyssb8krVq1qsH9AQBAZAm4myYnJ0eTJk3SiBEjNGrUKM2dO1clJSWaPHmyJGnixInq2bOncnNzJUn33nuvLrroIj355JMaN26cFi1apE2bNunZZ58N7pkAAIDTUsBhZMKECTp48KBmzZql/Px8DR06VMuXL/cPUt27d6/s9pMNLhdccIFee+01/epXv9Ivf/lLnXXWWXr77bdZYwQAAEhqwTojVmjuPGUAANB2NPfzm0ndAADAUoQRAABgKcIIAACwFGEEAABYijACAAAsRRgBAACWIowAAABLEUYAAICl2uRVe2vzrctWVFRkcUkAAEBz+T63m1pf9bQII8XFxZKktLQ0i0sCAAACVVxcrISEhAYfPy2Wg/d6vfr+++/VqVMn2Wy2oD1vUVGR0tLStG/fvoheZp56oA4k6sCHeqAOJOrAp7X1YIxRcXGxevToUeO6dbWdFi0jdrtdvXr1Ctnzx8fHR/SbzYd6oA4k6sCHeqAOJOrApzX10FiLiA8DWAEAgKUIIwAAwFIRHUZcLpdmz54tl8tldVEsRT1QBxJ14EM9UAcSdeATrno4LQawAgCA9iuiW0YAAID1CCMAAMBShBEAAGApwggAALAUYQQAAFgqosPIvHnzlJ6erpiYGGVkZGjDhg1WFylkPvzwQ1111VXq0aOHbDab3n777RqPG2M0a9Ysde/eXbGxscrKytL27dutKWyI5ObmauTIkerUqZOSk5N1zTXXaNu2bTX2KS8v19SpU9W1a1fFxcXpuuuuU0FBgUUlDo358+dr8ODB/hUVMzMz9d577/kfj4Q6qO3xxx+XzWbT9OnT/dvaez089NBDstlsNW4DBgzwP97ez/9U3333nf7rv/5LXbt2VWxsrM477zxt2rTJ/3h7//uYnp5e571gs9k0depUSeF5L0RsGFm8eLFycnI0e/ZsbdmyRUOGDFF2drYOHDhgddFCoqSkREOGDNG8efPqffyJJ57QU089pQULFujjjz9Wx44dlZ2drfLy8jCXNHTWrVunqVOn6p///KdWrVqlyspKXXbZZSopKfHvc9999+lvf/ubXn/9da1bt07ff/+9fvSjH1lY6uDr1auXHn/8cW3evFmbNm3SJZdcovHjx+uLL76QFBl1cKqNGzfqf//3fzV48OAa2yOhHs4991zt37/ff/voo4/8j0XC+UvS0aNHNXr0aEVHR+u9997Tl19+qSeffFKdO3f279Pe/z5u3Lixxvtg1apVkqQbbrhBUpjeCyZCjRo1ykydOtV/3+PxmB49epjc3FwLSxUeksxbb73lv+/1ek1qaqr57W9/69927Ngx43K5zJ///GcLShgeBw4cMJLMunXrjDHV5xwdHW1ef/11/z5fffWVkWTy8vKsKmZYdO7c2Tz//PMRVwfFxcXmrLPOMqtWrTIXXXSRuffee40xkfFemD17thkyZEi9j0XC+fvcf//9ZsyYMQ0+Hol/H++9917Tr18/4/V6w/ZeiMiWEbfbrc2bNysrK8u/zW63KysrS3l5eRaWzBq7du1Sfn5+jfpISEhQRkZGu66PwsJCSVKXLl0kSZs3b1ZlZWWNehgwYIB69+7dbuvB4/Fo0aJFKikpUWZmZsTVwdSpUzVu3Lga5ytFznth+/bt6tGjh8444wzdfPPN2rt3r6TIOX9J+utf/6oRI0bohhtuUHJysoYNG6bnnnvO/3ik/X10u93605/+pClTpshms4XtvRCRYeTQoUPyeDxKSUmpsT0lJUX5+fkWlco6vnOOpPrwer2aPn26Ro8erUGDBkmqrgen06nExMQa+7bHevjss88UFxcnl8ulO++8U2+99ZYGDhwYUXWwaNEibdmyRbm5uXUei4R6yMjI0EsvvaTly5dr/vz52rVrly688EIVFxdHxPn77Ny5U/Pnz9dZZ52lFStW6K677tLPfvYzvfzyy5Ii7+/j22+/rWPHjunWW2+VFL7fhaigPRNwGpk6dao+//zzGn3kkeTss8/W1q1bVVhYqCVLlmjSpElat26d1cUKm3379unee+/VqlWrFBMTY3VxLHH55Zf7vx88eLAyMjLUp08f/eUvf1FsbKyFJQsvr9erESNG6LHHHpMkDRs2TJ9//rkWLFigSZMmWVy68HvhhRd0+eWXq0ePHmF93YhsGUlKSpLD4agzGrigoECpqakWlco6vnOOlPqYNm2a3n33Xa1Zs0a9evXyb09NTZXb7daxY8dq7N8e68HpdOrMM8/U8OHDlZubqyFDhugPf/hDxNTB5s2bdeDAAZ1//vmKiopSVFSU1q1bp6eeekpRUVFKSUmJiHo4VWJiovr3768dO3ZEzPtAkrp3766BAwfW2HbOOef4u6wi6e/jnj179P777+u2227zbwvXeyEiw4jT6dTw4cO1evVq/zav16vVq1crMzPTwpJZo2/fvkpNTa1RH0VFRfr444/bVX0YYzRt2jS99dZb+uCDD9S3b98ajw8fPlzR0dE16mHbtm3au3dvu6qH+ni9XlVUVERMHYwdO1afffaZtm7d6r+NGDFCN998s//7SKiHUx0/flzffvutunfvHjHvA0kaPXp0nSn+33zzjfr06SMpcv4+StLChQuVnJyscePG+beF7b0QtKGwp5lFixYZl8tlXnrpJfPll1+aO+64wyQmJpr8/HyrixYSxcXF5pNPPjGffPKJkWTmzJljPvnkE7Nnzx5jjDGPP/64SUxMNO+8847517/+ZcaPH2/69u1rysrKLC558Nx1110mISHBrF271uzfv99/Ky0t9e9z5513mt69e5sPPvjAbNq0yWRmZprMzEwLSx18M2bMMOvWrTO7du0y//rXv8yMGTOMzWYzK1euNMZERh3U59TZNMa0/3r47//+b7N27Vqza9cu849//MNkZWWZpKQkc+DAAWNM+z9/nw0bNpioqCjz6KOPmu3bt5v/+7//Mx06dDB/+tOf/PtEwt9Hj8djevfube6///46j4XjvRCxYcQYY55++mnTu3dv43Q6zahRo8w///lPq4sUMmvWrDGS6twmTZpkjKmevvbggw+alJQU43K5zNixY822bdusLXSQ1Xf+kszChQv9+5SVlZm7777bdO7c2XTo0MFce+21Zv/+/dYVOgSmTJli+vTpY5xOp+nWrZsZO3asP4gYExl1UJ/aYaS918OECRNM9+7djdPpND179jQTJkwwO3bs8D/e3s//VH/729/MoEGDjMvlMgMGDDDPPvtsjccj4e/jihUrjKR6zysc7wWbMcYEr50FAAAgMBE5ZgQAALQdhBEAAGApwggAALAUYQQAAFiKMAIAACxFGAEAAJYijAAAAEsRRgAAgKUIIwAAwFKEEQAAYCnCCAAAsNT/D0AC278nYjwFAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def history_changed(board_history: np.ndarray) -> np.ndarray:\n", " return ~np.all(\n", @@ -1703,9 +1728,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 150, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(70, 10000)" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def get_gamma_table(board_history, gamma_value: float):\n", " unchanged = history_changed(board_history)\n", @@ -1719,9 +1755,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 151, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.06513542, 0.02282552, 0.08712565, 0.05031332, 0.1214854 ,\n", + " 0.06314092, 0.14037841, 0.0759323 , 0.16290323, 0.08841437,\n", + " 0.18861413, 0.10899313, 0.19318856, 0.10964757, 0.20731361,\n", + " 0.13148691, 0.22510605, 0.13292382, 0.23539045, 0.12585808,\n", + " 0.23848829, 0.15176572, 0.26641954, 0.17761089, 0.28060736,\n", + " 0.16112694, 0.31286326, 0.17623532, 0.28714693, 0.16549503,\n", + " 0.33439531, 0.19199073, 0.29858216, 0.20875418, 0.33700629,\n", + " 0.1993395 , 0.36539974, 0.24731134, 0.36773293, 0.24404735,\n", + " 0.42837075, 0.28564118, 0.41564522, 0.28406984, 0.41368105,\n", + " 0.2341238 , 0.39596409, 0.26595149, 0.39103311, 0.38067557,\n", + " 0.47846166, 0.30745852, 0.4819794 , 0.38419044, 0.5611122 ,\n", + " 0.524575 , 0.546425 , 0.466925 , 0.601625 , 0.570625 ,\n", + " 0.570625 , 0.35625 , 0.36875 , 0.36875 , 0.38125 ,\n", + " 0.38125 , 0.38125 , 0.38125 , 0.38125 , 0.39715854])" + ] + }, + "execution_count": 151, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def calculate_q_reword(\n", " board_history: np.ndarray,\n", @@ -1754,9 +1814,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 152, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'rewords' is not defined", + "output_type": "error", + "traceback": [ + "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[1;32mIn[152], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mrewords\u001B[49m\n\u001B[0;32m 2\u001B[0m evaluate_boards(boards)\u001B[38;5;241m.\u001B[39mshape\n", + "\u001B[1;31mNameError\u001B[0m: name 'rewords' is not defined" + ] + } + ], "source": [ "rewords\n", "evaluate_boards(boards).shape" diff --git a/poetry.lock b/poetry.lock index 7b48fe4..b59552a 100644 --- a/poetry.lock +++ b/poetry.lock @@ -496,26 +496,6 @@ pyqt5 = ["pyqt5"] pyside6 = ["pyside6"] test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"] -[[package]] -name = "ipympl" -version = "0.9.3" -description = "Matplotlib 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= "^0.0.3" -- 2.49.0 From 80abd6147520255b2a068715ab65720e369a23c5 Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sat, 18 Feb 2023 00:21:26 +0100 Subject: [PATCH 30/31] Added the analysis of possible turn --- turn_possible.npy | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 turn_possible.npy diff --git a/turn_possible.npy b/turn_possible.npy new file mode 100644 index 0000000..9af73dc --- /dev/null +++ b/turn_possible.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:46271cb4d4da2865cf483df84e89a76793af2cfaf7731d2a0f500c9f12916c16 +size 44800128 -- 2.49.0 From 0c9cf50bc5ec11e74ffcb234ccd1a17d9bda93ec Mon Sep 17 00:00:00 2001 From: Philipp Horstenkamp Date: Sat, 18 Feb 2023 14:33:56 +0100 Subject: [PATCH 31/31] Some debugging of the q reword function --- main.ipynb | 481 +++++++++++++++++++++++++++++++++++++++-------------- 1 file changed, 352 insertions(+), 129 deletions(-) diff --git a/main.ipynb b/main.ipynb index 1c4a510..6235ed3 100644 --- a/main.ipynb +++ b/main.ipynb @@ -126,7 +126,7 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -140,7 +140,12 @@ "from ipywidgets import interact\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", - "import pandas as pd" + "import pandas as pd\n", + "\n", + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import torch.optim as optim" ] }, { @@ -154,7 +159,7 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -343,7 +348,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -353,7 +358,11 @@ } ], "source": [ - "def plot_othello_board(board: np.ndarray, ax=None) -> None:\n", + "def plot_othello_board(\n", + " board: np.ndarray,\n", + " action: np.ndarray | None = None,\n", + " ax=None,\n", + ") -> None:\n", " \"\"\"Plots a single otello board.\n", "\n", " If a matplot axis object is given the board will be plotted into that axis. If not an axis object will be generated.\n", @@ -371,14 +380,16 @@ " fig, ax = plt.subplots(figsize=(fig_size, fig_size))\n", "\n", " ax.set_facecolor(\"#66FF00\")\n", + " if action is not None:\n", + " ax.scatter(action[0], action[1], s=350 if plot_all else 200, c=\"red\")\n", " for x_pos, y_pos in itertools.product(range(BOARD_SIZE), range(BOARD_SIZE)):\n", - " if board[x_pos, y_pos] == -1:\n", + " if board[x_pos, y_pos] == PLAYER:\n", " color = \"white\"\n", - " elif board[x_pos, y_pos] == 1:\n", + " elif board[x_pos, y_pos] == ENEMY:\n", " color = \"black\"\n", " else:\n", " continue\n", - " ax.scatter(y_pos, x_pos, s=300 if plot_all else 150, c=color)\n", + " ax.scatter(x_pos, y_pos, s=280 if plot_all else 140, c=color)\n", " for x_pos in range(-1, 8):\n", " ax.axhline(x_pos + 0.5, color=\"black\", lw=2)\n", " ax.axvline(x_pos + 0.5, color=\"black\", lw=2)\n", @@ -388,12 +399,15 @@ " ax.set_xticklabels(list(\"ABCDEFGH\"))\n", " ax.set_yticks(np.arange(8))\n", " ax.set_yticklabels(list(\"12345678\"))\n", + " ax.set_xlabel(\n", + " f\"W{np.sum(board == ENEMY)} / {np.sum(board == 0)} / B{np.sum(board == PLAYER)}\"\n", + " )\n", " if plot_all:\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "\n", - "plot_othello_board(get_new_games(1)[0])" + "plot_othello_board(get_new_games(1)[0], action=np.array([3, 3]))" ] }, { @@ -402,7 +416,7 @@ "metadata": {}, "outputs": [], "source": [ - "def plot_othello_boards(boards: np.ndarray) -> None:\n", + "def plot_othello_boards(boards: np.ndarray, actions: np.ndarray | None = None) -> None:\n", " \"\"\"Plots multiple boards into subplots.\n", "\n", " The plots are shown directly.\n", @@ -414,6 +428,11 @@ " assert boards.shape[1:] == (BOARD_SIZE, BOARD_SIZE)\n", " assert boards.shape[0] < 70\n", "\n", + " if actions is not None:\n", + " assert len(actions.shape) == 2\n", + " assert actions.shape[1] == 2\n", + " assert boards.shape[0] == actions.shape[0]\n", + "\n", " plots_per_row = 4\n", " rows = int(np.ceil(boards.shape[0] / plots_per_row))\n", " fig, axs = plt.subplots(rows, plots_per_row, figsize=(12, 3 * rows))\n", @@ -421,18 +440,21 @@ " if game_index >= boards.shape[0]:\n", " fig.delaxes(ax)\n", " else:\n", - " plot_othello_board(boards[game_index], ax)\n", + " action = actions[game_index] if actions is not None else None\n", + " plot_othello_board(boards[game_index], action=action, ax=ax)\n", " plt.tight_layout()\n", " plt.show()" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 58, "metadata": {}, "outputs": [], "source": [ - "def drop_duplicate_boards(boards: np.ndarray) -> np.ndarray:\n", + "def drop_duplicate_boards(\n", + " boards: np.ndarray, actions: np.ndarray | None\n", + ") -> tuple[np.ndarray, np.ndarray | None]:\n", " \"\"\"Drop boards that follow each other and are duplicates will be dropped.\n", "\n", " Args:\n", @@ -441,7 +463,13 @@ " Returns:\n", " A sequence of boards where boards that where equal are dropped.\n", " \"\"\"\n", - " return boards[~np.all(boards == np.roll(boards, axis=0, shift=1), axis=(1, 2))]" + " non_duplicates = ~np.all(boards == np.roll(boards, axis=0, shift=1), axis=(1, 2))\n", + " return (\n", + " boards[non_duplicates],\n", + " np.roll(actions, axis=0, shift=1)[non_duplicates]\n", + " if actions is not None\n", + " else None,\n", + " )" ] }, { @@ -499,8 +527,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "8.86 ms ± 584 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "860 ms ± 12.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "9.82 ms ± 375 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "984 ms ± 20.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { @@ -724,9 +752,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "182 µs ± 6.7 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "34.4 µs ± 1.82 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", - "32.2 µs ± 743 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" + "193 µs ± 2.65 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n", + "35.1 µs ± 335 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n", + "38 µs ± 1.58 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n" ] } ], @@ -816,12 +844,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "86.7 ms ± 1.18 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + "101 ms ± 2.58 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -913,7 +941,8 @@ "plot_othello_board(\n", " do_moves(\n", " get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE)\n", - " )[0]\n", + " )[0],\n", + " action=np.array([2, 3]),\n", ")" ] }, @@ -1112,13 +1141,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "1.02 s ± 31.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", - "1.01 s ± 35 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "1.11 s ± 35.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", + "1.14 s ± 73.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] }, { "data": { - "image/png": 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" ] @@ -1174,14 +1203,14 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 27, "metadata": { "scrolled": false }, "outputs": [ { "data": { - "image/png": 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sk3q7pIFT0rQqqaZBalwnVS5wnQ5AnNFPAKyinwBYZaGfZqley7VOc9Wgc1SlN3VKJ9SlA2rTSfWEEwJOsCiFjB1tlw5tlbp3Bx8tKUl+SvLKgucv3C4tbJaWtEi1Tc5iAogh+gmAVfQTAKss9FODmrRSm7RYzfKVliQllFD67efNul2HtEt7tVVd2l+cEHCKt+9hSr4vvdQq7b5a6tkjyQ/Kyk+9/frQc1/q3iPt+lBQbr7vMDSAWKCfAFhFPwGwyko/rdQmtahdl2iVEkqoTOUqU7m8Uc8TSmixrlOL9ulabSxsAJjAotT/Z+/eg6y87/uOv8/uotWF3TVWUARhkWWDUSOBxpbtyGiM5Vi4RgI7nYS2GTwRUpy2MU6cCtSazsSV69o4I2CcqR21dWVwR/JNntpjoZETYcdAhqBbIkEahyxNJRaDKk2LdwFJCHaf/vGwF5bLnuvz+54979fMjlfaffb78Z7f76Plx7PnaFL7NsOT9+bvZ6cv/rkjH9+zLr9OkhrJfpIUlf0kKaoI/XQb9/AbbASgnWkX/dyRj69kkwdTU1BFh1JvectbKJVK57ytWbOmUfmU2OEdeQFVY886OLKzvnmki7GjWov9pGZiP7UW+0nNxH5qLRH6aT5LWMmmqq5dySbm877aQyiMig6lnn76aY4cOTL69sQTTwCwcuXKhoRTens3QanKZx4rdeTXS0Wxo1qL/aRmYj+1FvtJzcR+ai0R+mkpaxniVFXXDnHKu6WmmIqW48yZM8/65y9+8Yu87W1v4/3vf39dQymG4wfzJ72jyt8dzk7Di4/C8X6Y3lvXaNJ52VGtw35Ss7GfWof9pGZjP7WOCP00g14Wspy2Kp9JqJ1pLOIjzGAORzlUXQiFUvVzSr3xxhs89NBD3H333ZRKpXpmUhD7t469CkO1Sm2wf0td4kgVsaOmNvtJzcx+mtrsJzUz+2lqi9BPi1k9+ip71coYZjF31fQ1FEeVN+7B97//fX7+85+zevXqi37eyZMnOXny5Og/Dw4OVjtSBRvoq8/XGTxQn68jVaKcjrKfmpf9pGZmP01t9pOamf00tUXop6uYX4cEGTOZV4evowiqPid98MEHWbZsGbNnz77o523YsIGenp7Rt95e70NuFqeOjb0saLWyIXjD/04pgXI6yn5qXvaTmpn9NLXZT2pm9tPUFqGfLqWr6l/dG9FGO5fRXdPXUBxVrYYXX3yR7du38/GPf3zSz12/fj0DAwOjb/39/dWMVALTuqDUXtvXKLXDJfaFClZuR9lPzct+UrOyn6Y++0nNyn6a+iL00+scY7jGX98bZojX8OR+qqjq1/e2bNnCVVddxR133DHp53Z2dtLZ2VnNGCXWU487K4Fu76xUwcrtKPupedlPalb209RnP6lZ2U9TX4R+epl6/A5hiVfwd5yniorvlBoeHmbLli3ceeeddHRU/ZRUagILVkNW2yE22TAs8DnoVCA7qjXYT2pG9lNrsJ/UjOyn1hChn3azlVKNv75Xoo3d+GoQU0XFq2H79u0cPHiQu+++uxF5FMj0uTB3OZSq/O9SqQOuWeHLGatYdlRrsJ/UjOyn1mA/qRnZT60hQj8dpZ99bGOIU1VdP8Qp9vIDjnKo+hAKpeJDqQ996ENkWcbb3/72RuRRMDeug+x0dddmQ7BobX3zSJOxo1qH/aRmYz+1DvtJzcZ+ah0R+ukJNtLOtKqubaOd7WyuPYTCqO2+OU15s5bAzRuru/bm+/PrJakR7CdJUdlPkqKK0E997OIRqjvd+i730seu2kMoDA+lNKmF94wV12S3eo58/OaN+XWS1Ej2k6So7CdJUUXop+1sHj2YmuxX+UY+/ghrvUtqCvJQSpMqlfLbNFfsgLm3A6X8pUBHXk509P1S/vEVO/LPL5VSppbUCuwnSVHZT5KiitJP29nMRpawj8cYZpghTjPEaTKGGeIUQ5xmmGH28RgbWeKB1BTlSyuobLOW5G/H+2H/Fhg8AG8MwiXd+cuCLrjLJ+WUlIb9JCkq+0lSVBH6qY9d9LGLGcxhMXcxk3lcRjevMcgrHGA3W3xS8ynOQylVbHov3PSZ1Ckk6Vz2k6So7CdJUUXop6Mc4jE+lzaEkvDX9yRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4UpZlWZEDBwcH6enpgRJcMbvIyblXj0A2DKU2uHxW8fPNYIZoGVLPBzhxGMhgYGCA7u7uNCFI308Q4/FInSH1fDOYYaIIHWU/mSHKfDPEymA/5SI8FmYwQ5T5UTKU20/pDqUkaYIwh1KSdB4h/tAnSedhP0mKarJ+6igwy9m8U8oMZgiRIfV8GDtFD8O/6Wv5NWkGM4wXqqPsp5bPkHq+GWJlsJ9yER4LM5ghyvwoGcrtp2SHUpdfDasOFT/34Tlw4mf5A5NivhnMEC1D6vkAD83OizOKVP0EMR6P1BlSzzeDGSaK1FH2kxlSzzdDrAz2Uy7CY2EGM0SZHyVDuf3kE51LkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwFR1KDQ0N8Yd/+Idce+21XHbZZbztbW/jc5/7HFmWNSqfJJXFfpIUmR0lKSr7SVJKHZV88h/90R/xwAMP8PWvf53rr7+eZ555hrvuuouenh5+//d/v1EZJWlS9pOkyOwoSVHZT5JSquhQavfu3Xz0ox/ljjvuAOAtb3kL3/zmN3nqqacaEk6SymU/SYrMjpIUlf0kKaWKfn1v8eLF/OhHP+Lv//7vAXj++ef5i7/4C5YtW3bBa06ePMng4OBZb5JUb/aTpMgq7Sj7SVJR7CdJKVV0p9SnP/1pBgcHue6662hvb2doaIjPf/7zrFq16oLXbNiwgc9+9rM1B5Wki7GfJEVWaUfZT5KKYj9JSqmiO6W+853v8PDDD/ONb3yDv/qrv+LrX/86Gzdu5Otf//oFr1m/fj0DAwOjb/39/TWHlqSJ7CdJkVXaUfaTpKLYT5JSquhOqXvvvZdPf/rT/PN//s8BWLhwIS+++CIbNmzgzjvvPO81nZ2ddHZ21p5Uki7CfpIUWaUdZT9JKor9JCmliu6UevXVV2lrO/uS9vZ2hoeH6xpKkiplP0mKzI6SFJX9JCmliu6UWrFiBZ///OeZO3cu119/PX/913/N5s2bufvuuxuVT5LKYj9JisyOkhSV/SQppYoOpf7Tf/pP/OEf/iGf+MQnePnll5k9ezb/8l/+Sz7zmc80Kp8klcV+khSZHSUpKvtJUkoVHUp1dXXxpS99iS996UsNiiNJ1bGfJEVmR0mKyn6SlFJFzyklSZIkSZIk1YOHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXCnLsqzIgQMDA7zpTW8C4PJZRU7OvfoSkAEluPzq4uebwQzRMqSeD/Dqkfx/f/7zn9PT05MmBOn7CYI8Hq5JM5jh7AwBOsp+MkOU+WYIlsF+AoI8FmYwQ5D5YTKU2U+FH0odOnSI3t7eIkdKahL9/f3MmTMn2Xz7SdLFpOwo+0nSxdhPkqKarJ8KP5QaHh7m8OHDdHV1USqVKr5+cHCQ3t5e+vv76e7ubkBCMzRLhtTzzVC/DFmWcezYMWbPnk1bW7rfKrafzDCVMqSeP5UyROioWvsJ0j8eqeebwQzRMthPY1I/FhEypJ5vBjPUO0O5/dRRS8hqtLW11eUUv7u7O9mDY4ZYGVLPN0N9MqT8tb0R9pMZpmKG1POnSobUHVWvfoL0j0fq+WYwQ7QM9tOY1I9FhAyp55vBDPXMUE4/+UTnkiRJkiRJKpyHUpIkSZIkSSpc0x1KdXZ28u///b+ns7PTDC2eIfV8M8TKEEGE74MZzBBlvhniSf29SD3fDGaIliH1/EgifC9SZ0g93wxmSJWh8Cc6lyRJkiRJkpruTilJkiRJkiQ1Pw+lJEmSJEmSVDgPpSRJkiRJklS4pjqU+su//Eva29u54447Cp+9evVqSqXS6NuVV17Jhz/8Yfbu3Vt4lpdeeonf+73f461vfSudnZ309vayYsUKfvSjHzV89vjvw7Rp0/jFX/xFli5dyte+9jWGh4cbPn9ihvFvH/7whwuZP1mOAwcOFDL/pZde4lOf+hTz5s3j0ksv5Rd/8Re55ZZbeOCBB3j11VcbPn/16tX82q/92jn//ic/+QmlUomf//znDc8QjR1lP03MkaqjUvcTpO0o++lc9pP9NDGH/eTPUFHYT/bTxBz2U2v1U1MdSj344IP83u/9Hjt37uTw4cOFz//whz/MkSNHOHLkCD/60Y/o6Ohg+fLlhWZ44YUXuOmmm/jxj3/M/fffz759+/jhD3/IBz7wAdasWVNIhpHvwwsvvMDjjz/OBz7wAT71qU+xfPlyTp8+XWiG8W/f/OY3C5k9WY5rr7224XP/4R/+gXe84x382Z/9GV/4whf467/+a/7yL/+Sf/Nv/g3btm1j+/btDc+gc7V6R9lP5+ZI2VGp+gnsqIjsJ/tpYg77yX6Kwn6ynybmsJ9aq586Ugco1/Hjx/n2t7/NM888w0svvcTWrVv5d//u3xWaobOzk6uvvhqAq6++mk9/+tO8733v45VXXmHmzJmFZPjEJz5BqVTiqaee4oorrhj999dffz133313IRnGfx9+6Zd+iXe+853cfPPNfPCDH2Tr1q18/OMfLzRDSqlyfOITn6Cjo4NnnnnmrHXw1re+lY9+9KP4oprFs6PspwvlSCVlBjsqFvvJfrpQjlTsJ42wn+ynC+VIxX4qXtPcKfWd73yH6667jgULFvCxj32Mr33ta0kflOPHj/PQQw8xb948rrzyykJm/r//9//44Q9/yJo1a85apCPe9KY3FZLjfH71V3+VG2+8kf/xP/5Hsgyt4v/+3//Ln/3Zn11wHQCUSqWCU6nVO8p+0gg7Kh77yX5Szn6Kx36yn5Rr5X5qmkOpBx98kI997GNAfkvdwMAAO3bsKDTDtm3bmD59OtOnT6erq4sf/OAHfPvb36atrZhv44EDB8iyjOuuu66QeZW67rrreOGFFwqZNf6xGHn7whe+UMjsi+VYuXJlw2eOrIMFCxac9e9/4Rd+YTTHv/23/7bhOeD8j8OyZcsKmR1Nq3eU/XS2CB2Vop8gTkfZT2PsJ/tpPPspfT+BHTXCfrKfxrOfWrOfmuLX9/bv389TTz3F9773PQA6Ojr4Z//sn/Hggw9y6623FpbjAx/4AA888AAAR48e5U/+5E9YtmwZTz31FNdcc03D50e/XS/LssJOb8c/FiPe/OY3FzL7YjkudKpdhKeeeorh4WFWrVrFyZMnC5l5vsfhySefHP3holXYUfbTRBE6KlI/QfEdZT/l7Cf7aSL76Vz+DJWG/WQ/TWQ/nasV+qkpDqUefPBBTp8+zezZs0f/XZZldHZ28uUvf5menp5CclxxxRXMmzdv9J//23/7b/T09PDVr36V//gf/2PD58+fP59SqcTf/d3fNXxWNX76058W9iRwEx+LVFLkmDdvHqVSif3795/179/61rcCcNlllxWW5Xz//w8dOlTY/CjsKPtpoggdlSpDlI6yn3L2k/00kf2Uvp/AjgL7Ceynieyn1uyn8L++d/r0af77f//vbNq0ieeee2707fnnn2f27NlJXnFtRKlUoq2tjddee62QeW9+85v5x//4H/OVr3yFEydOnPPxlC8f++Mf/5h9+/bx67/+68kytIorr7ySpUuX8uUvf/m860DFsqNy9pNG2FFx2E85+0kj7Kc47Kec/aQRrdxP4e+U2rZtG0ePHuW3f/u3zzkt//Vf/3UefPBB/tW/+leFZDl58iQvvfQSkN/a+eUvf5njx4+zYsWKQuYDfOUrX+GWW27hPe95D//hP/wHFi1axOnTp3niiSd44IEH+OlPf9rwDCPfh6GhIf7P//k//PCHP2TDhg0sX76c3/qt32r4/PEZxuvo6OAXfuEXCpmf2p/8yZ9wyy238K53vYv77ruPRYsW0dbWxtNPP83f/d3fcdNNN6WO2DLsqDH207k5xrOj7Kii2U9j7Kdzc4xnP9lPRbOfxthP5+YYz35qgX7Kglu+fHl2++23n/djTz75ZAZkzz//fMNz3HnnnRkw+tbV1ZW9+93vzr773e82fPZEhw8fztasWZNdc8012SWXXJL90i/9UvaRj3wk+/M///OGzx7/fejo6MhmzpyZ3XbbbdnXvva1bGhoqOHzJ2YY/7ZgwYJC5o/P8dGPfrTQmeMdPnw4++QnP5lde+212bRp07Lp06dn73nPe7L7778/O3HiRMPnX+j//5//+Z9nQHb06NGGZ4jAjjpbq/fTxBypOip1P2VZ2o6yn3L209nsJ/tphD9DpWc/nc1+sp9GtGI/lbIs+LOrSZIkSZIkacoJ/5xSkiRJkiRJmno8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE6ih44PDzM4cOH6erqolQqFT1eUkBZlnHs2DFmz55NW1u6s3L7SdL5ROgo+0nS+dhPkqIqt58KP5Q6fPgwvb29RY+V1AT6+/uZM2dOsvn2k6SLSdlR9pOki7GfJEU1WT8VfijV1dU1+v7ls4qeDq++BGRACS6/uvj5ZjBDtAyp5wO8eiT/3/H9kELqfoIgj4dr0gxmODtDgI6yn8wQZb4ZgmWwn4Agj4UZzBBkfpgMZfZT4YdSI7d0Xj4LPna46Onw8Bw48TO4YjasOlT8fDOYIVqG1PMBHpqdl1bqW75T9xPEeDxSZ0g93wxmmChCR9lPZogy3wyxMthPuQiPhRnMEGV+lAzl9pNPdC5JkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJVfCi1c+dOVqxYwezZsymVSnz/+99vQCxJqpz9JCkq+0lSVPaTpJQqPpQ6ceIEN954I1/5ylcakUeSqmY/SYrKfpIUlf0kKaWOSi9YtmwZy5Yta0QWSaqJ/SQpKvtJUlT2k6SUfE4pSZIkSZIkFa7iO6UqdfLkSU6ePDn6z4ODg40eKUllsZ8kRWU/SYrKfpJUTw2/U2rDhg309PSMvvX29jZ6pCSVxX6SFJX9JCkq+0lSPTX8UGr9+vUMDAyMvvX39zd6pCSVxX6SFJX9JCkq+0lSPTX81/c6Ozvp7Oxs9BhJqpj9JCkq+0lSVPaTpHqq+FDq+PHjHDhwYPSf//f//t8899xzvPnNb2bu3Ll1DSdJlbCfJEVlP0mKyn6SlFLFh1LPPPMMH/jAB0b/+Z577gHgzjvvZOvWrXULJkmVsp8kRWU/SYrKfpKUUsWHUrfeeitZljUiiyTVxH6SFJX9JCkq+0lSSg1/onNJkiRJkiRpIg+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4UpZlWZEDBwcH6enpgRJcMbvIyblXj0A2DKU2uHxW8fPNYIZoGVLPBzhxGMhgYGCA7u7uNCFI308Q4/FInSH1fDOYYaIIHWU/mSHKfDPEymA/5SI8FmYwQ5T5UTKU20/pDqUkaYIwh1KSdB4h/tAnSedhP0mKarJ+6igwy9m8U8oMZgiRIfV8GDtFD8O/6Wv5NWkGM4wXqqPsp5bPkHq+GWJlsJ9yER4LM5ghyvwoGcrtp2SHUpdfDasOFT/34Tlw4mf5A5NivhnMEC1D6vkAD83OizOKVP0EMR6P1BlSzzeDGSaK1FH2kxlSzzdDrAz2Uy7CY2EGM0SZHyVDuf3kE51LkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcOlefa9Cxw/C/q0w0AenjsG0LuiZDwtWw/S5xWSYQS+LWc1VzOdSunidY7xMH7vZylH6iwkhneF6jMN+ks7meowldUe5HhSNazKO1P0ErgfF0orrMfyh1OEdsHcTHNyWv5whQDYEpfb8/Wfvg2uWw6J1MGtJYzLMZwlLWctClpMxDEAbbQyfeX8597GXR9nOJvrY1ZgQ0hmuxzjsJ+lsrsdYUneU60HRuCbjSN1P4HpQLK28HsP++l6WwfMbYdut0P84kOVFlQ2d+fjI+xkcfBwefX9ebFlW3xxLWcs6dnADy2ijjXY6aKeD0rj322hjIbezjp3cxj31DSCN43qMwX6SzuV6jCNCR7keFI1rMoYI/QSuB8XS6usx7KHUvs3w5L35+9npi3/uyMf3rMuvq5fbuIffYCMA7Uy76OeOfHwlm6bcIlEMrsc47CfpbK7HWFJ3lOtB0bgm40jdT+B6UCyux6CHUod35OVTjT3r4MjO2jPMZwkr2VTVtSvZxHzeV3sI6QzXYxz2k3Q212MsqTvK9aBoXJNxpO4ncD0oFtdjrqJDqQ0bNvDud7+brq4urrrqKn7t136N/fv31z3U3k1QqvLZrkod+fW1WspahjhV1bVDnJpSJ5dKz/U4OfupPK2yHlQc12N5WqWjXA+KxjU5uVbpJ3A9KBbXY66iQ6kdO3awZs0a9uzZwxNPPMGpU6f40Ic+xIkTJ+oW6PjB/AnvJrud80Ky0/Dio3C8hiemn0EvC1k+6e1zF9LONBbxEWYwp/oQ0hmux/LYT+VplfWgYrgey9cKHeV6UDSuyfK0Qj+B60GxuB7HVHQo9cMf/pDVq1dz/fXXc+ONN7J161YOHjzIs88+W7dA+7eOvQJDtUptsH9L9dcvZvXoM95XK2OYxdxV09eQwPVYLvupfK2wHlQM12P5WqGjXA+KxjVZnlboJ3A9KBbX45gqb6DMDQwMAPDmN7/5gp9z8uRJTp48OfrPg4ODF/+afbUkGjN4oPprr2J+HRJkzGReHb6OWp3rsTr208W03npQY7geqzdZR1XaT5C+o1wPisY1WZ2p2E/gelAsrscxVZ9XDw8P8wd/8Afccsst3HDDDRf8vA0bNtDT0zP61tvbe9Gve+rY2EuCVisbgjcm78YLupQu2mp8Dvg22rmM7pq+hgSux2rYTxfXautBjeN6rE45HVVpP0H6jnI9KBrXZOWmaj+B60GxuB7HVP1dWLNmDX/zN3/Dt771rYt+3vr16xkYGBh96++/+C8CT+uCUnu1qXKldrikhsfmdY4xXOOtdMMM8Ro1tKZ0huuxcvbTxbXaelDjuB6rU05HVdpPkL6jXA+KxjVZuanaT+B6UCyuxzFV/freJz/5SbZt28bOnTuZM+fiT6zV2dlJZ2dn2V+7px53sQHdNdzF9jL1uL+0xCvUcH+pdIbrsTL2UzlaZz2osVyPlSu3oyrtJ0jfUa4HReOarMxU7idwPSgW1+OYiu6UyrKMT37yk3zve9/jxz/+Mddee23dAy1YDVltB4Zkw7Cghuf72s1WSjXeSleijd3U8Ex80hmux/LYT+VrhfWgYrgey9cKHeV6UDSuyfK0Qj+B60GxuB7HVPRdWLNmDQ899BDf+MY36Orq4qWXXuKll17itddeq1ug6XNh7nIoVfkU7KUOuGYFTJ/8V5sv6Cj97GMbQ5yq6vohTrGXH3CUQ9WHkM5wPZbHfipPq6wHFcP1WL5W6CjXg6JxTZanFfoJXA+KxfU4pqJDqQceeICBgQFuvfVWZs2aNfr27W9/u66hblwH2enqrs2GYNHa2jM8wUbamVbVtW20s53NtYeQznA9Ts5+Kk+rrAcVx/VYnlbpKNeDonFNTq5V+glcD4rF9Zir+Nf3zve2evXquoaatQRu3ljdtTffn19fqz528QjVNd93uZc+dtUeQjrD9Tg5+6k8rbIeVBzXY3lapaNcD4rGNTm5VukncD0oFtdjrrZfYmyghfeMldZkt3mOfPzmjfl19bKdzaOLZLLb6kY+/ghrp8yJpWJxPcZhP0lncz3GkrqjXA+KxjUZR+p+AteDYnE9Bj6UKpXyWzRX7IC5twOl/GVAR15KdPT9Uv7xFTvyzy+V6ptjO5vZyBL28RjDDDPEaYY4TcYwQ5xiiNMMM8w+HmMjS6bU4lA8rscY7CfpXK7HOCJ0lOtB0bgmY4jQT+B6UCytvh6rfKq54sxakr8d74f9W2DwALwxCJd05y8JuuCu2p7wrhx97KKPXcxgDou5i5nM4zK6eY1BXuEAu9kyJZ5gTM3B9RiH/SSdzfUYS+qOcj0oGtdkHKn7CVwPiqWV12P4Q6kR03vhps+kzXCUQzzG59KGkM5wPcZhP0lncz3GkrqjXA+KxjUZR+p+AteDYmnF9Rj21/ckSZIkSZI0dXkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwpWyLMuKHDg4OEhPTw+U4IrZRU7OvXoEsmEotcHls4qfbwYzRMuQej7AicNABgMDA3R3d6cJQfp+ghiPR+oMqeebwQwTRego+8kMUeabIVYG+ykX4bEwgxmizI+Sodx+SncoJUkThDmUkqTzCPGHPkk6D/tJUlST9VNHgVnO5p1SZjBDiAyp58PYKXoY/k1fy69JM5hhvFAdZT+1fIbU880QK4P9lIvwWJjBDFHmR8lQbj8lO5S6/GpYdaj4uQ/PgRM/yx+YFPPNYIZoGVLPB3hodl6cUaTqJ4jxeKTOkHq+GcwwUaSOsp/MkHq+GWJlsJ9yER4LM5ghyvwoGcrtJ5/oXJIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmFS/bqe83o+EHYvxUG+uDUMZjWBT3zYcFqmD7XDEVmEMygl8Ws5irmcyldvM4xXqaP3WzlKP2p46lgEfalGTTCftJ4EfalGTSeHaXxUu/N1POjZFCuFfvJQ6kyHN4BezfBwW1QOnNvWTYEpfb8/Wfvg2uWw6J1MGuJGRqZQTCfJSxlLQtZTsYwAG20MXzm/eXcx14eZTub6GNXyqgqQIR9aQaNsJ80XoR9aQaNZ0dpvNR7M/X8KBmUa+V+8tf3LiLL4PmNsO1W6H8cyPJNmg2d+fjI+xkcfBwefX++qbPMDPXOoNxS1rKOHdzAMtpoo50O2umgNO79NtpYyO2sYye3cU/qyGqQCPvSDBrPftKICPvSDJrIjtKI1Hsz9fwoGTSm1fvJQ6mL2LcZnrw3fz87ffHPHfn4nnX5dWaobwbBbdzDb7ARgHamXfRzRz6+kk1TrrSUi7AvzaAR9pPGi7AvzaDx7CiNl3pvpp4fJYNy9lOFh1IPPPAAixYtoru7m+7ubt773vfy+OOPNypbUod35BuvGnvWwZGdZqhXBuW3c65kU1XXrmQT83lfnRPFYz+VZyp1Q4QMsp/K1SodFWFfmkHj2VGTa5V+gvR7M/X8KBmUs59yFR1KzZkzhy9+8Ys8++yzPPPMM/zqr/4qH/3oR/mf//N/NipfMns3QanKZ9wqdeTXm6E+GZTf0jnEqaquHeLUlDpJvxD7qTxTqRsiZJD9VK5W6agI+9IMGs+Omlyr9BOk35up50fJoJz9lKvoUGrFihXcfvvtzJ8/n7e//e18/vOfZ/r06ezZs6dR+ZI4fjB/srfJbmW8kOw0vPgoHK/hyfHNoBEz6GUhyye9nfNC2pnGIj7CDObUOVks9lN5pko3RMgg+6kSrdBREfalGTSeHVWeVugnSL83U8+PkkE5+2lM1c8pNTQ0xLe+9S1OnDjBe9/73npmSm7/1rFXH6hWqQ32bzFDrRkEi1k9+goM1coYZjF31SlRfPbTxU2FboiQQfZTtaZqR0XYl2bQeHZU5aZqP0H6vZl6fpQMytlPYyq+cW/fvn28973v5fXXX2f69Ol873vf45d/+Zcv+PknT57k5MmTo/88ODhYXdICDfTV5+sMHjBDrRkEVzG/Dl8lYybz6vB1YrOfytfs3RAhg+ynSlXSUfaTGeyn2tlR5Zvq/QTp92bq+VEyKGc/jan4nHTBggU899xzPPnkk/zu7/4ud955J3/7t397wc/fsGEDPT09o2+9vb01BS7CqWNjL4dZrWwI3qihn82gEZfSRVuNL5TZRjuX0V2nRHHZT+WZCt0QIYPsp0pV0lH2kxnsp9rZUeWb6v0E6fdm6vlRMihnP42p+LtwySWXMG/ePG666SY2bNjAjTfeyB//8R9f8PPXr1/PwMDA6Ft/f/xfQJ3WBaX22r5GqR0uqWF9mEEjXucYwzXe2jnMEK8x9f/rYT+VZyp0Q4QMsp8qVUlH2U9msJ9qZ0eVb6r3E6Tfm6nnR8mgnP00psrn3R8zPDx81u2bE3V2dtLZ2VnrmEL11ONOOqC7hjvpzKARL1OP+2xLvELr3WdrP11Ys3dDhAyyn2p1sY6yn8xgP9XOjqreVOsnSL83U8+PkkE5+2lMRXdKrV+/np07d/LCCy+wb98+1q9fz09+8hNWrVrVqHxJLFgNWW2HlmTDsKCG5xwzg0bsZiulGm/tLNHGbqb2MxLaT+WbCt0QIYPsp0q0QkdF2Jdm0Hh2VHlaoZ8g/d5MPT9KBuXspzEVfRdefvllfuu3fosFCxbwwQ9+kKeffpo//dM/ZenSpY3Kl8T0uTB3OZSqvI+s1AHXrIDpNfx6tRk04ij97GMbQ5yq6vohTrGXH3CUQ3VOFov9VJ6p0g0RMsh+qkQrdFSEfWkGjWdHlacV+gnS783U86NkUM5+GlPRcnzwwQcblSOcG9fBwUeruzYbgkVrzVCvDIIn2MiNfKSqa9toZzub65woHvupPFOpGyJkkP1UrlbpqAj70gwaz46aXKv0E6Tfm6nnR8mgnP2Uq+1+sSls1hK4eWN11958f369GeqTQdDHLh6huv8CfJd76WNXnRMppQj70gwaYT9pvAj70gwaz47SeKn3Zur5UTIoZz/lPJS6iIX3jG3YyW5xHPn4zRvz68xQ3wyC7WweLa3JbvMc+fgjrJ0yJ+g6W4R9aQaNsJ80XoR9aQaNZ0dpvNR7M/X8KBmUs588lLqoUim/PXHFDph7O1DKXwJz5GU0R98v5R9fsSP//FLJDPXOoNx2NrORJezjMYYZZojTDHGajGGGOMUQpxlmmH08xkaWTKmy0tki7EszaDz7SSMi7EszaCI7SiNS783U86Nk0JhW76cqn+Kstcxakr8d74f9W2DwALwxCJd05y+HueCuxj/Zmxk0oo9d9LGLGcxhMXcxk3lcRjevMcgrHGA3W6bEE96pPBH2pRk0wn7SeBH2pRk0nh2l8VLvzdTzo2RQrpX7yUOpCkzvhZs+Y4YIGQRHOcRjfC51DAURYV+aQSPsJ40XYV+aQePZURov9d5MPT9KBuVasZ/89T1JkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVrpRlWVbkwMHBQXp6eqAEV8wucnLu1SOQDUOpDS6fVfx8M5ghWobU8wFOHAYyGBgYoLu7O00I0vcTxHg8UmdIPd8MZpgoQkfZT2aIMt8MsTLYT7kIj4UZzBBlfpQM5fZTukMpSZogzKGUJJ1HiD/0SdJ52E+SopqsnzoKzHI275QygxlCZEg9H8ZO0cPwb/pafk2awQzjheoo+6nlM6Seb4ZYGeynXITHwgxmiDI/SoZy+ynZodTlV8OqQ8XPfXgOnPhZ/sCkmG8GM0TLkHo+wEOz8+KMIlU/QYzHI3WG1PPNYIaJInWU/WSG1PPNECuD/ZSL8FiYwQxR5kfJUG4/+UTnkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKly6V9+r0PGDsH8rDPTBqWMwrQt65sOC1TB9rhlaKcMMelnMaq5iPpfSxesc42X62M1WjtLf+ABm0ASp94QZYmVIvTdTz4+SQWNS74vU880wJsLeNIPGi7AvUmdIPT9Khgj70gxphD+UOrwD9m6Cg9vylzMEyIag1J6//+x9cM1yWLQOZi0xw1TOMJ8lLGUtC1lOxjAAbbQxfOb95dzHXh5lO5voY1f9A5hBE6TeE2aIlSH13kw9P0oGjUm9L1LPN8OYCHvTDBovwr5InSH1/CgZIuxLM6QV9tf3sgye3wjbboX+x4Es3yDZ0JmPj7yfwcHH4dH35xsqy8wwFTMsZS3r2MENLKONNtrpoJ0OSuPeb6ONhdzOOnZyG/fUb7gZNEGEPWGGOBkg/d5MPT9KBuVS74vU881wtgh70wwaEWFfpM6Qen6UDBBjX5ohvbCHUvs2w5P35u9npy/+uSMf37Muv84MUyvDbdzDb7ARgHamXfRzRz6+kk113axm0Hip94QZYmVIvTdTz4+SQWNS74vU880wJsLeNIPGi7AvUmdIPT9Khgj70gwxhDyUOrwjX/TV2LMOjuw0w1TJMJ8lrGRTVdeuZBPzeV9tAcygCVLvCTPEypB6b6aeHyWDxqTeF6nnm2FMhL1pBo0XYV+kzpB6fpQMEfalGeKo6VDqi1/8IqVSiT/4gz+oU5zc3k1QqvLZrkod+fVmmBoZlrKWIU5Vde0Qp+pygmyG5mQ/maGIDKn3Zur5UTI0m0b1E6TfF6nnm2FMhL1phubkz1CNy5B6fpQMEfalGeKo+lDq6aef5r/8l//CokWL6pmH4wfzJ1qb7DbCC8lOw4uPwvEanpjeDDEyzKCXhSyf9DbGC2lnGov4CDOYU10AMzQt+8kMRWRIvTdTz4+Sodk0qp8g/b5IPd8MYyLsTTM0J3+GalyG1POjZIiwL80QS1WHUsePH2fVqlV89atfZcaMGXUNtH/r2DP/V6vUBvu3mKHZMyxm9egrD1QrY5jF3FX19WZoPvaTGYrKkHpvpp4fJUMzaWQ/Qfp9kXq+GcZE2JtmaD7+DNXYDKnnR8kQYV+aIZaqluSaNWu44447uO222yb93JMnTzI4OHjW28UM9FWT6FyDB6q/1gwxMlzF/DpMz5jJvKqvNkPzsZ/MUFSG1Hsz9fwoGZpJI/sJ0u+L1PPNMCbC3jRD8ym3o5qxnyJkSD0/SoYI+9IMsVT826Tf+ta3+Ku/+iuefvrpsj5/w4YNfPazny376586NvZSlNXKhuCNybvRDMEzXEoXbTU+F38b7VxGd9XXm6G52E9mKDJD6r2Zen6UDM2i0f0E6fdF6vlmGBNhb5qhuVTSUc3YTxEypJ4fJUOEfWmGWCr6LvT39/OpT32Khx9+mEsvvbSsa9avX8/AwMDoW3//xX8BdVoXlNorSXWuUjtcUsNjY4YYGV7nGMM13tI4zBCvUX1rmqF52E9mKDpD6r2Zen6UDM2giH6C9Psi9XwzjImwN83QPCrtqGbspwgZUs+PkiHCvjRDLBXdKfXss8/y8ssv8853vnP03w0NDbFz506+/OUvc/LkSdrbz17lnZ2ddHZ2lj2jpx53sQHdNdzFZoYYGV6mHveXlniF6u8vNUPzsJ/MUHSG1Hsz9fwoGZpBEf0E6fdF6vlmGBNhb5qheVTaUc3YTxEypJ4fJUOEfWmGWCq6U+qDH/wg+/bt47nnnht9e9e73sWqVat47rnnzvmBqhoLVkNW24Eh2TAsqOH5vswQI8NutlKq8ZbGEm3spvpn4jND87CfzFB0htR7M/X8KBmaQRH9BOn3Rer5ZhgTYW+aoXn4M1QxGVLPj5Ihwr40QywVfRe6urq44YYbznq74ooruPLKK7nhhhvqEmj6XJi7HEoVP9tVrtQB16yA6b1maPYMR+lnH9sY4lRV1w9xir38gKMcqi6AGZqK/WSGojOk3pup50fJ0AyK6CdIvy9SzzfDmAh70wzNw5+hismQen6UDBH2pRliqfEFIRvjxnWQna7u2mwIFq01w1TJ8AQbaWdaVde20c52NtcWwAyaIPWeMEOsDKn3Zur5UTJoTOp9kXq+GcZE2Jtm0HgR9kXqDKnnR8kQYV+aIY6aD6V+8pOf8KUvfakOUcbMWgI3b6zu2pvvz683w9TI0McuHqG65vsu99LHrtoCmKGp2U9maHSG1Hsz9fwoGZpRI/oJ0u+L1PPNMCbC3jRD8/JnqMZkSD0/SoYI+9IMcYS8Uwpg4T1jm2Wy2wtHPn7zxvw6M0ytDNvZPLpZJ7u9ceTjj7C2rifHZtB4qfeEGWJlSL03U8+PkkFjUu+L1PPNMCbC3jSDxouwL1JnSD0/SoYI+9IMMYQ9lCqV8lsDV+yAubcDpfzlJ0dewnL0/VL+8RU78s8vlcwwFTNsZzMbWcI+HmOYYYY4zRCnyRhmiFMMcZphhtnHY2xkSUM2qRk0IsKeMEOcDJB+b6aeHyWDcqn3Rer5ZjhbhL1pBo2IsC9SZ0g9P0oGiLEvzZBelU9xVpxZS/K34/2wfwsMHoA3BuGS7vylKBfcVdsTrZmheTL0sYs+djGDOSzmLmYyj8vo5jUGeYUD7GZLw5/ozQwaL/WeMEOsDKn3Zur5UTJoTOp9kXq+GcZE2Jtm0HgR9kXqDKnnR8kQYV+aIa3wh1IjpvfCTZ8xgxngKId4jM+lC2AGTZB6T5ghVobUezP1/CgZNCb1vkg93wxjIuxNM2i8CPsidYbU86NkiLAvzZBG2F/fkyRJkiRJ0tTloZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgpXyrIsK3Lg4OAgPT09UIIrZhc5OffqEciGodQGl88qfr4ZzBAtQ+r5ACcOAxkMDAzQ3d2dJgTp+wliPB6pM6SebwYzTBSho+wnM0SZb4ZYGeynXITHwgxmiDI/SoZy+yndoZQkTRDmUEqSziPEH/ok6TzsJ0lRTdZPHQVmOZt3SpnBDCEypJ4PY6foYfg3fS2/Js1ghvFCdZT91PIZUs83Q6wM9lMuwmNhBjNEmR8lQ7n9lOxQ6vKrYdWh4uc+PAdO/Cx/YFLMN4MZomVIPR/godl5cUaRqp8gxuOROkPq+WYww0SROsp+MkPq+WaIlcF+ykV4LMxghijzo2Qot598onNJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFS7Zq+81o+MHYf9WGOiDU8dgWhf0zIcFq2H6XDMUlWEGvSxmNVcxn0vp4nWO8TJ97GYrR+lvfAApoNT70gxj7CjpbBH2pRly9pN0rtR7M/X8KBnsp9bloVQZDu+AvZvg4DYonbm3LBuCUnv+/rP3wTXLYdE6mLXEDI3KMJ8lLGUtC1lOxjAAbbQxfOb95dzHXh5lO5voY1f9A0gBpd6XZhhjR0lni7AvzZCzn6Rzpd6bqedHyWA/yV/fu4gsg+c3wrZbof9xIMs3aTZ05uMj72dw8HF49P35ps4yM9Q7w1LWso4d3MAy2mijnQ7a6aA07v022ljI7axjJ7dxT/2GSwFF2JdmGGNHSWMi7EszjLGfpLOl3pup50fJAPaTch5KXcS+zfDkvfn72emLf+7Ix/esy68zQ/0y3MY9/AYbAWhn2kU/d+TjK9lkaWlKS70vzTDGjpLOFmFfmiFnP0nnSr03U8+PksF+0oiKDqXuu+8+SqXSWW/XXXddo7IldXhHvvGqsWcdHNlphnpkmM8SVrKpqmtXson5vK+2AGoa9lN5pko3RMlgR6lcrdJREfalGXL2k8rVKv0E6fdm6vlRMthPGq/iO6Wuv/56jhw5Mvr2F3/xF43IldzeTVCq8hm3Sh359WaoPcNS1jLEqaquHeKUJ+ktxn6a3FTphigZ7ChVohU6KsK+NEPOflIlWqGfIP3eTD0/Sgb7SeNVvBw7Ojq4+uqrG5EljOMH8yd7o8rfmc1Ow4uPwvF+mN5rhmozzKCXhSynrcrfMm1nGov4CDOYw1EOVfU11Fzsp8lNhW6IksGOUqWmekdF2JdmyNlPqtRU7ydIvzdTz4+SwX7SRBWvhL6+PmbPns1b3/pWVq1axcGDBxuRK6n9W8defaBapTbYv8UMtWRYzOrRV2CoVsYwi7mrpq+h5mE/lafZuyFKBjtKlZrqHRVhX5ohZz+pUlO9nyD93kw9P0oG+0kTVXSn1K/8yq+wdetWFixYwJEjR/jsZz/L+973Pv7mb/6Grq6u815z8uRJTp48OfrPg4ODtSUuwEBffb7O4AEz1JLhKubXYXrGTObV4esoOvupMs3cDVEy2FGqRKUdZT+ZwX5SUVqhnyD93kw9P0oG+0kTVXQotWzZstH3Fy1axK/8yq9wzTXX8J3vfIff/u3fPu81GzZs4LOf/WxtKQt26tjYy2FWKxuCN2roZzPApXRVfVvniDbauYzumr6GmoP9VL5m74YoGewoVaLSjrKfzGA/qSit0E+Qfm+mnh8lg/2kiWpaDW9605t4+9vfzoEDFz4qXb9+PQMDA6Nv/f39tYwsxLQuKLXX9jVK7XBJDfvEDPA6xxiu8dbOYYZ4jeb42xvVl/10Yc3eDVEy2FGqxWQdZT+ZwX5SKlOxnyD93kw9P0oG+0kT1XQodfz4cf7X//pfzJo164Kf09nZSXd391lv0fXU445CoLuGOwrNAC9Tj/tLS7xCDfeXqmnZTxfXzN0QJYMdpVpM1lH2kxnsJ6UyFfsJ0u/N1POjZLCfNFFFh1Lr1q1jx44dvPDCC+zevZt/8k/+Ce3t7fzmb/5mo/IlsWA1ZLUd3pINw4IannvNDLCbrZRqvLWzRBu7qeGZ+NQ07KfyNXs3RMlgR6kSrdBREfalGXL2kyrRCv0E6fdm6vlRMthPmqii1XDo0CF+8zd/kwULFvBP/+k/5corr2TPnj3MnDmzUfmSmD4X5i6HUkXPuDWm1AHXrKj+ZTLNkDtKP/vYxhCnqrp+iFPs5Qe+VGiLsJ/KMxW6IUoGO0qVaIWOirAvzZCzn1SJVugnSL83U8+PksF+0kQVLcdvfetbjcoRzo3r4OCj1V2bDcGitWaoR4Yn2MiNfKSqa9toZzubawugpmE/lWeqdEOUDHaUytUqHRVhX5ohZz+pXK3ST5B+b6aeHyWD/aTxartvbgqbtQRu3ljdtTffn19vhtoz9LGLR6iu+b7LvfSxq7YAUkCp96UZxthR0tki7Esz5Own6Vyp92bq+VEy2E8az0Opi1h4z9iGnewWx5GP37wxv84M9cuwnc2jpTXZbZ4jH3+EtZ6ga0pLvS/NMMaOks4WYV+aIWc/SedKvTdTz4+SwX7SCA+lLqJUym9PXLED5t4OlPKXwBx5Gc3R90v5x1fsyD+/VDJDvTNsZzMbWcI+HmOYYYY4zRCnyRhmiFMMcZphhtnHY2xkiWWlKS/CvjTDGDtKGhNhX5phjP0knS313kw9P0oGsJ+Uq/IpzlrLrCX52/F+2L8FBg/AG4NwSXf+cpgL7qrtyd7MUJ4+dtHHLmYwh8XcxUzmcRndvMYgr3CA3WzxCe/UclLvSzOMsaOks0XYl2bI2U/SuVLvzdTzo2Swn+ShVAWm98JNnzFD6gxHOcRjfC5dACmg1PvSDGPsKOlsEfalGXL2k3Su1Hsz9fwoGeyn1uWv70mSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwpSzLsiIHDg4O0tPTAyW4YnaRk3OvHoFsGEptcPms4uebwQzRMqSeD3DiMJDBwMAA3d3daUKQvp8gxuOROkPq+WYww0QROsp+MkOU+WaIlcF+ykV4LMxghijzo2Qot5/SHUpJ0gRhDqUk6TxC/KFPks7DfpIU1WT91FFglrN5p5QZzBAiQ+r5MHaKHoZ/09fya9IMZhgvVEfZTy2fIfV8M8TKYD/lIjwWZjBDlPlRMpTbT8kOpS6/GlYdKn7uw3PgxM/yBybFfDOYIVqG1PMBHpqdF2cUqfoJYjweqTOknm8GM0wUqaPsJzOknm+GWBnsp1yEx8IMZogyP0qGcvvJJzqXJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4dK9+p6a1vGDsH8rDPTBqWMwrQt65sOC1TB97tSfbwYprhn0spjVXMV8LqWL1znGy/Sxm60cpb+QDKn3Zur5UTJI0dhPZpCisp/MkJKHUirb4R2wdxMc3Ja/tCRANgSl9vz9Z++Da5bDonUwa8nUm28GKa75LGEpa1nIcjKGAWijjeEz7y/nPvbyKNvZRB+7GpIh9d5MPT9KBika+8kMUlT2kxki8Nf3NKksg+c3wrZbof9xIMs3SDZ05uMj72dw8HF49P35hsqyqTHfDFJsS1nLOnZwA8too412Oming9K499toYyG3s46d3MY9dZ2fem+mnh8lgxRRq/eTGaS47CczROGhlCa1bzM8eW/+fnb64p878vE96/LrpsJ8M0hx3cY9/AYbAWhn2kU/d+TjK9lU1x+sUu/N1POjZJCisZ/MIEVlP5khEg+ldFGHd+SLvhp71sGRnc093wxSXPNZwko2VXXtSjYxn/fVnCH13kw9P0oGKRr7yQxSVPaTGaKp+FDqZz/7GR/72Me48sorueyyy1i4cCHPPPNMI7IpgL2boFTlM4+VOvLrm3m+GZqL/dRalrKWIU5Vde0Qp+ryt32p92bq+VEyNAs7qnXYT2ZoNvZT67CfzBBNRYdSR48e5ZZbbmHatGk8/vjj/O3f/i2bNm1ixowZjcqnhI4fzJ9obbLbCC8kOw0vPgrHq3zBhtTzzdBc7KfWMoNeFrJ80lvOL6SdaSziI8xgTtUZUu/N1POjZGgWdlTrsJ/M0Gzsp9ZhP5khoooOpf7oj/6I3t5etmzZwnve8x6uvfZaPvShD/G2t72tUfmU0P6tY8/8X61SG+zf0pzzzdBc7KfWspjVo68SU62MYRZzV9XXp96bqedHydAs7KjWYT+ZodnYT63DfjJDRBV9G37wgx/wrne9i5UrV3LVVVfxjne8g69+9asXvebkyZMMDg6e9abmMNBXn68zeKA555uhudhPreUq5tfhq2TMZF7VV6fem6nnR8nQLCrtKPupedlPZmg29lPrsJ/MEFFFh1L/8A//wAMPPMD8+fP50z/9U373d3+X3//93+frX//6Ba/ZsGEDPT09o2+9vb01h1YxTh0beynKamVD8EaV/51KPd8MzcV+ai2X0kVbja/V0UY7l9Fd9fWp92bq+VEyNItKO8p+al72kxmajf3UOuwnM0RU0YocHh7mne98J1/4whd4xzvewb/4F/+C3/md3+E//+f/fMFr1q9fz8DAwOhbf/8U+KXHFjGtC0rttX2NUjtcUmVnpZ5vhuZiP7WW1znGcI23nw8zxGtU/1/y1Hsz9fwoGZpFpR1lPzUv+8kMzcZ+ah32kxkiquhQatasWfzyL//yWf/uH/2jf8TBgwcveE1nZyfd3d1nvak59NTj7k6gu8q7O1PPN0NzsZ9ay8vU457nEq9Q/T3Pqfdm6vlRMjSLSjvKfmpe9pMZmo391DrsJzNEVNGh1C233ML+/fvP+nd///d/zzXXXFPXUIphwWrIajtIJxuGBVU+D17q+WZoLvZTa9nNVko13n5eoo3dVP/skKn3Zur5UTI0CzuqddhPZmg29lPrsJ/MEFFFK/Jf/+t/zZ49e/jCF77AgQMH+MY3vsF//a//lTVr1jQqnxKaPhfmLodSR3XXlzrgmhUwvcpfM0893wzNxX5qLUfpZx/bGOJUVdcPcYq9/ICjHKo6Q+q9mXp+lAzNwo5qHfaTGZqN/dQ67CczRFTRodS73/1uvve97/HNb36TG264gc997nN86UtfYtWqVY3Kp8RuXAfZ6equzYZg0drmnm+G5mE/tZ4n2Eg706q6to12trO55gyp92bq+VEyNAM7qrXYT2ZoJvZTa7GfzBBNxffuLV++nH379vH666/z05/+lN/5nd9pRC4FMWsJ3Lyxumtvvj+/vpnnm6G52E+tpY9dPEJ1/zX+LvfSx66aM6Tem6nnR8nQLOyo1mE/maHZ2E+tw34yQzS1/UKpWsLCe8Y2y2S3F458/OaN+XVTYb4ZpLi2s3n0B6vJbkUf+fgjrK3L3/KNSL03U8+PkkGKxn4ygxSV/WSGSDyU0qRKpfzWwBU7YO7tQCl/+cmRl7Acfb+Uf3zFjvzzS6WpMd8MUmzb2cxGlrCPxxhmmCFOM8RpMoYZ4hRDnGaYYfbxGBtZUtcfqCD93kw9P0oGKaJW7yczSHHZT2aIosqn1VIrmrUkfzveD/u3wOABeGMQLunOX4pywV2NfaK11PPNIMXVxy762MUM5rCYu5jJPC6jm9cY5BUOsJstNT0pZzlS783U86NkkKKxn8wgRWU/mSECD6VUsem9cNNnWne+GaS4jnKIx/hc0gyp92bq+VEySNHYT2aQorKfzJCSv74nSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMKVsizLihw4ODhIT08PlOCK2UVOzr16BLJhKLXB5bOKn28GM0TLkHo+wInDQAYDAwN0d3enCUH6foIYj0fqDKnnm8EME0XoKPvJDFHmmyFWBvspF+GxMIMZosyPkqHcfkp3KCVJE4Q5lJKk8wjxhz5JOg/7SVJUk/VTR4FZzuadUmYwQ4gMqefD2Cl6GP5NX8uvSTOYYbxQHWU/tXyG1PPNECuD/ZSL8FiYwQxR5kfJUG4/JTuUuvxqWHWo+LkPz4ETP8sfmBTzzWCGaBlSzwd4aHZenFGk6ieI8XikzpB6vhnMMFGkjrKfzJB6vhliZbCfchEeCzOYIcr8KBnK7Sef6FySJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmFS/fqe2paxw/C/q0w0AenjsG0LuiZDwtWw/S5jZ8/g14Ws5qrmM+ldPE6x3iZPnazlaP0Nz6ApPOKsDfNIOl8IuzLCBlS/wwn6VwRusEMSslDKZXt8A7YuwkObstfWhIgG4JSe/7+s/fBNcth0TqYtaT+8+ezhKWsZSHLyRgGoI02hs+8v5z72MujbGcTfeyqfwBJ5xVhb5pB0vlE2JcRMqT+GU7SuSJ0gxkUgb++p0llGTy/EbbdCv2PA1n+g0w2dObjI+9ncPBxePT9+Q8+WVa/DEtZyzp2cAPLaKONdjpop4PSuPfbaGMht7OOndzGPfUbLumCIuxNM0g6nwj7MnWGCD/DSTpX6m4wgyLxUEqT2rcZnrw3fz87ffHPHfn4nnX5dfVwG/fwG2wEoJ1pF/3ckY+vZJOlJTVYhL1pBknnE2FfRsiQ+mc4SeeK0A1mUCQVHUq95S1voVQqnfO2Zs2aRuVTYod35D+cVGPPOjiys7b581nCSjZVde1KNjGf99UWQE3FjipOhL1pBjUT+6k4EfZlhAypf4ZT87CfihOhG8ygaCo6lHr66ac5cuTI6NsTTzwBwMqVKxsSTunt3QSlKp95rNSRX1+LpaxliFNVXTvEKU/SW4wdVZwIe9MMaib2U3Ei7MsIGVL/DKfmYT8VJ0I3mEHRVHQoNXPmTK6++urRt23btvG2t72N97///Y3Kp4SOH8yfEHOy270vJDsNLz4Kx6t8sYQZ9LKQ5ZPeznkh7UxjER9hBnOqC6CmY0cVI8LeNIOajf1UjAj7MkKG1D/DqbnYT8WI0A1mUERVP6fUG2+8wUMPPcTdd99NqVSqZyYFsX/r2Cu0VKvUBvu3VHftYlaPvgJDtTKGWcxdNX0NNSc7qnEi7E0zqJnZT40TYV9GyJD6Zzg1L/upcSJ0gxkUUZU39cL3v/99fv7zn7N69eqLft7Jkyc5efLk6D8PDg5WO1IFG+irz9cZPFDddVcxvw7TM2Yyrw5fR82mnI6yn6oTYW+aQc3MfmqcCPsyQobUP8OpedlPjROhG8ygiKr+O5QHH3yQZcuWMXv27It+3oYNG+jp6Rl96+3trXakCnbq2NhLBlcrG4I3qvzv1KV00VbjC0S20c5ldNf0NdScyuko+6k6EfamGdTM7KfGibAvI2RI/TOcmpf91DgRusEMiqiq1fDiiy+yfft2Pv7xj0/6uevXr2dgYGD0rb/fX05vFtO6oNRe29cotcMlVfbF6xxjuMZbO4cZ4jX8iarVlNtR9lN1IuxNM6hZ2U+NFWFfRsiQ+mc4NSf7qbEidIMZFFFVv763ZcsWrrrqKu64445JP7ezs5POzs5qxiixnnrcWQl0V3ln5cvU497zEq/gveetptyOsp+qE2FvmkHNyn5qrAj7MkKG1D/DqTnZT40VoRvMoIgqvlNqeHiYLVu2cOedd9LRUfVTUqkJLFgNWW2H2GTDsKDK56DbzVZKNd7aWaKN3fgsna3Ejmq8CHvTDGpG9lPjRdiXETKk/hlOzcd+arwI3WAGRVTxati+fTsHDx7k7rvvbkQeBTJ9LsxdDqUq/7tU6oBrVsD0Kn/N/Cj97GMbQ5yq6vohTrGXH3CUQ9UFUFOyoxovwt40g5qR/dR4EfZlhAypf4ZT87GfGi9CN5hBEVV8KPWhD32ILMt4+9vf3og8CubGdZCdru7abAgWra1t/hNspJ1pVV3bRjvb2VxbADUdO6oYEfamGdRs7KdiRNiXETKk/hlOzcV+KkaEbjCDoqntvjlNebOWwM0bq7v25vvz62vRxy4eobqfir7LvfSxq7YAks4rwt40g6TzibAvI2RI/TOcpHNF6AYzKBoPpTSphfeM/VAz2W3gIx+/eWN+XT1sZ/NoaU12m+fIxx9hrSfoUoNF2JtmkHQ+EfZlhAypf4aTdK4I3WAGReKz2GlSpVJ+C/fMd8PeTfDio1A6c5yZDY295HA2DHNvzz+33n+7tp3NvMjT3MY9LOIjZGdeRrSNNoYZAkqUaGMfj7GdzZ6eSwWJsDfNIOl8IuzL1Bki/Awn6Vypu8EMisRDKZVt1pL87Xg/7N8CgwfgjUG4pDt/yeAFdzX2CTH72EUfu5jBHBZzFzOZx2V08xqDvMIBdrPFJ7yTEoiwN80g6Xwi7MsIGVL/DCfpXBG6wQyKwEMpVWx6L9z0mXTzj3KIx/hcugCSzivC3jSDpPOJsC8jZEj9M5ykc0XoBjMoJZ9TSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYUrZVmWFTlwcHCQnp4eKMEVs4ucnHv1SP6yt6U2uHxW8fPNYIZoGVLPBzhxGMhgYGCA7u7uNCFI308Q4/FInSH1fDOYYaIIHWU/mSHKfDPEymA/5SI8FmYwQ5T5UTKU20/pDqUkaYIwh1KSdB4h/tAnSedhP0mKarJ+6igwy9m8U8oMZgiRIfV8GDtFD8O/6Wv5NWkGM4wXqqPsp5bPkHq+GWJlsJ9yER4LM5ghyvwoGcrtp2SHUpdfDasOFT/34Tlw4mf5A5NivhnMEC1D6vkAD83OizOKVP0EMR6P1BlSzzeDGSaK1FH2kxlSzzdDrAz2Uy7CY2EGM0SZHyVDuf3kE51LkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcOlefU+SJElSYY4fhP1bYaAPTh2DaV3QMx8WrIbpc1Onk9TKIvTTDHpZzGquYj6X0sXrHONl+tjNVo7SX0yIFuShlCRJkjSFHd4BezfBwW35y4MDZENQas/ff/Y+uGY5LFoHs5YkiympBUXop/ksYSlrWchyMoYBaKON4TPvL+c+9vIo29lEH7saE6KF+et7kiRJ0hSUZfD8Rth2K/Q/DmT5H/ayoTMfH3k/g4OPw6Pvz/9wmGUJQ0tqCVH6aSlrWccObmAZbbTRTgftdFAa934bbSzkdtaxk9u4p74B5KGUJEmSNBXt2wxP3pu/n52++OeOfHzPuvw6SWqkCP10G/fwG2wEoJ1pF/3ckY+vZJMHU3XmoZQkSZI0xRzekf8Brhp71sGRnfXNI0kjIvTTfJawkk1VXbuSTcznfbWHEFDhodTQ0BB/+Id/yLXXXstll13G2972Nj73uc+ReY+vpMTsJ0mR2VEq2t5NUKry2WNLHfn1ag32k4oWoZ+WspYhTlV17RCnvFuqjipaCn/0R3/EAw88wNe//nWuv/56nnnmGe666y56enr4/d///UZllKRJ2U+SIrOjVKTjB/MnDabKM4XsNLz4KBzvh+m9dY2mgOwnFSlCP82gl4Usp63KXxxrZxqL+AgzmMNRDlUXQqMqOpTavXs3H/3oR7njjjsAeMtb3sI3v/lNnnrqqYaEk6Ry2U+SIrOjVKT9W/NXsRp5wuBqlNpg/xa46TN1i6Wg7CcVKUI/LWb1mVfZq/7ZjDKGWcxdPMbnqv4aylX0KCxevJgf/ehH/P3f/z0Azz//PH/xF3/BsmXLLnjNyZMnGRwcPOtNkurNfpIUWaUdZT+pFgN99fk6gwfq83UUm/2kIkXop6uYX4cEGTOZV4evo4rulPr0pz/N4OAg1113He3t7QwNDfH5z3+eVatWXfCaDRs28NnPfrbmoJJ0MfaTpMgq7Sj7SbU4day2uxAgv/4Nzxpagv2kIkXop0vpqvpX90a00c5ldNf0NZSr6JH4zne+w8MPP8w3vvEN/uqv/oqvf/3rbNy4ka9//esXvGb9+vUMDAyMvvX399ccWpImsp8kRVZpR9lPqsW0Lii11/Y1Su1wiX/eagn2k4oUoZ9e5xjDDNeUYZghXsOT+3qo6E6pe++9l09/+tP883/+zwFYuHAhL774Ihs2bODOO+887zWdnZ10dnbWnlSSLsJ+khRZpR1lP6kWPfX4zRSg299MaQn2k4oUoZ9eph6/Q1jiFfwd53qo6E6pV199lba2sy9pb29neLi2U0ZJqpX9JCkyO0pFWrAashqXVjYMC+6qSxwFZz+pSBH6aTdbKdX463sl2tjNlpq+hnIV3Sm1YsUKPv/5zzN37lyuv/56/vqv/5rNmzdz9913NyqfJJXFfpIUmR2lIk2fC3OXQ//j+cunV6rUAXNvr/7l1tVc7CcVKUI/HaWffWzjBpbRzrSKrx/iFPt4jKMcqj6ERlV0KPWf/tN/4g//8A/5xCc+wcsvv8zs2bP5l//yX/KZz/hasZLSsp8kRWZHqWg3roODj1Z3bTYEi9bWN4/isp9UtAj99AQbuZGPVHVtG+1sZ3PtIQRUeCjV1dXFl770Jb70pS81KI4kVcd+khSZHaWizVoCN2+EPesqv/bm+/Pr1RrsJxUtQj/1sYtHWMtKNlV87Xe5lz521R5CQIXPKSVJkiSpOSy8J/+DH+S/8nIxIx+/eWN+nSQ1UoR+2s5mHiG/7WqIUxf93JGPP8Ja75KqMw+lJEmSpCmoVMp/zWXFjvw5WCjlL6U+8nLso++X8o+v2JF/fqmUMrWkVhCln7azmY0sYR+PMcwwQ5xmiNNkDDPEKYY4zTDD7OMxNrLEA6kGqOjX9yRJkiQ1l1lL8rfj/bB/CwwegDcG4ZLu/GXVF9zlk5pLSiNCP/Wxiz52MYM5LOYuZjKPy+jmNQZ5hQPsZotPat5AHkpJkiRJLWB6L9zkc1dLCihCPx3lEI/xubQhWpC/vidJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwpWyLMuKHDgwMMCb3vQmAC6fVeTk3KsvARlQgsuvLn6+GcwQLUPq+QCvHsn/9+c//zk9PT1pQpC+nyDI4+GaNIMZzs4QoKPsJzNEmW+GYBnsJyDIY2EGMwSZHyZDmf1U+KHUoUOH6O3tLXKkpCbR39/PnDlzks23nyRdTMqOsp8kXYz9JCmqyfqp8EOp4eFhDh8+TFdXF6VSqeLrBwcH6e3tpb+/n+7u7gYkNEOzZEg93wz1y5BlGceOHWP27Nm0taX7rWL7yQxTKUPq+VMpQ4SOqrWfIP3jkXq+GcwQLYP9NCb1YxEhQ+r5ZjBDvTOU208dtYSsRltbW11O8bu7u5M9OGaIlSH1fDPUJ0PKX9sbYT+ZYSpmSD1/qmRI3VH16idI/3iknm8GM0TLYD+NSf1YRMiQer4ZzFDPDOX0k090LkmSJEmSpMJ5KCVJkiRJkqTCNd2hVGdnJ//+3/97Ojs7zdDiGVLPN0OsDBFE+D6YwQxR5pshntTfi9TzzWCGaBlSz48kwvcidYbU881ghlQZCn+ic0mSJEmSJKnp7pSSJEmSJElS8/NQSpIkSZIkSYXzUEqSJEmSJEmFa6pDqb/8y7+kvb2dO+64o/DZq1evplQqjb5deeWVfPjDH2bv3r2FZ3nppZf4vd/7Pd761rfS2dlJb28vK1as4Ec/+lHDZ4//PkybNo1f/MVfZOnSpXzta19jeHi44fMnZhj/9uEPf7iQ+ZPlOHDgQCHzX3rpJT71qU8xb948Lr30Un7xF3+RW265hQceeIBXX3214fNXr17Nr/3ar53z73/yk59QKpX4+c9/3vAM0dhR9tPEHKk6KnU/QdqOsp/OZT/ZTxNz2E/+DBWF/WQ/TcxhP7VWPzXVodSDDz7I7/3e77Fz504OHz5c+PwPf/jDHDlyhCNHjvCjH/2Ijo4Oli9fXmiGF154gZtuuokf//jH3H///ezbt48f/vCHfOADH2DNmjWFZBj5Przwwgs8/vjjfOADH+BTn/oUy5cv5/Tp04VmGP/2zW9+s5DZk+W49tprGz73H/7hH3jHO97Bn/3Zn/GFL3yBv/7rv+Yv//Iv+Tf/5t+wbds2tm/f3vAMOlerd5T9dG6OlB2Vqp/AjorIfrKfJuawn+ynKOwn+2liDvuptfqpI3WAch0/fpxvf/vbPPPMM7z00kts3bqVf/fv/l2hGTo7O7n66qsBuPrqq/n0pz/N+973Pl555RVmzpxZSIZPfOITlEolnnrqKa644orRf3/99ddz9913F5Jh/Pfhl37pl3jnO9/JzTffzAc/+EG2bt3Kxz/+8UIzpJQqxyc+8Qk6Ojp45plnzloHb33rW/noRz+KL6pZPDvKfrpQjlRSZrCjYrGf7KcL5UjFftII+8l+ulCOVOyn4jXNnVLf+c53uO6661iwYAEf+9jH+NrXvpb0QTl+/DgPPfQQ8+bN48orryxk5v/7f/+PH/7wh6xZs+asRTriTW96UyE5zudXf/VXufHGG/kf/+N/JMvQKv7v//2//Nmf/dkF1wFAqVQqOJVavaPsJ42wo+Kxn+wn5eyneOwn+0m5Vu6npjmUevDBB/nYxz4G5LfUDQwMsGPHjkIzbNu2jenTpzN9+nS6urr4wQ9+wLe//W3a2or5Nh44cIAsy7juuusKmVep6667jhdeeKGQWeMfi5G3L3zhC4XMvliOlStXNnzmyDpYsGDBWf/+F37hF0Zz/Nt/+28bngPO/zgsW7askNnRtHpH2U9ni9BRKfoJ4nSU/TTGfrKfxrOf0vcT2FEj7Cf7aTz7qTX7qSl+fW///v089dRTfO973wOgo6ODf/bP/hkPPvggt956a2E5PvCBD/DAAw8AcPToUf7kT/6EZcuW8dRTT3HNNdc0fH702/WyLCvs9Hb8YzHizW9+cyGzL5bjQqfaRXjqqacYHh5m1apVnDx5spCZ53scnnzyydEfLlqFHWU/TRShoyL1ExTfUfZTzn6ynyayn87lz1Bp2E/200T207laoZ+a4lDqwQcf5PTp08yePXv032VZRmdnJ1/+8pfp6ekpJMcVV1zBvHnzRv/5v/23/0ZPTw9f/epX+Y//8T82fP78+fMplUr83d/9XcNnVeOnP/1pYU8CN/GxSCVFjnnz5lEqldi/f/9Z//6tb30rAJdddllhWc73///QoUOFzY/CjrKfJorQUakyROko+ylnP9lPE9lP6fsJ7Ciwn8B+msh+as1+Cv/re6dPn+a///f/zqZNm3juuedG355//nlmz56d5BXXRpRKJdra2njttdcKmffmN7+Zf/yP/zFf+cpXOHHixDkfT/nysT/+8Y/Zt28fv/7rv54sQ6u48sorWbp0KV/+8pfPuw5ULDsqZz9phB0Vh/2Us580wn6Kw37K2U8a0cr9FP5OqW3btnH06FF++7d/+5zT8l//9V/nwQcf5F/9q39VSJaTJ0/y0ksvAfmtnV/+8pc5fvw4K1asKGQ+wFe+8hVuueUW3vOe9/Af/sN/YNGiRZw+fZonnniCBx54gJ/+9KcNzzDyfRgaGuL//J//ww9/+EM2bNjA8uXL+a3f+q2Gzx+fYbyOjg5+4Rd+oZD5qf3Jn/wJt9xyC+9617u47777WLRoEW1tbTz99NP83d/9HTfddFPqiC3DjhpjP52bYzw7yo4qmv00xn46N8d49pP9VDT7aYz9dG6O8eynFuinLLjly5dnt99++3k/9uSTT2ZA9vzzzzc8x5133pkBo29dXV3Zu9/97uy73/1uw2dPdPjw4WzNmjXZNddck11yySXZL/3SL2Uf+chHsj//8z9v+Ozx34eOjo5s5syZ2W233ZZ97Wtfy4aGhho+f2KG8W8LFiwoZP74HB/96EcLnTne4cOHs09+8pPZtddem02bNi2bPn169p73vCe7//77sxMnTjR8/oX+///5n/95BmRHjx5teIYI7KiztXo/TcyRqqNS91OWpe0o+ylnP53NfrKfRvgzVHr209nsJ/tpRCv2UynLgj+7miRJkiRJkqac8M8pJUmSJEmSpKnHQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBWuo+iBw8PDHD58mK6uLkqlUtHjJQWUZRnHjh1j9uzZtLWlOyu3nySdT4SOsp8knY/9JCmqcvup8EOpw4cP09vbW/RYSU2gv7+fOXPmJJtvP0m6mJQdZT9Juhj7SVJUk/VT4YdSXV1do+9fPqvo6fDqS0AGlODyq4ufbwYzRMuQej7Aq0fy/x3fDymk7icI8ni4Js1ghrMzBOgo+8kMUeabIVgG+wkI8liYwQxB5ofJUGY/FX4oNXJL5+Wz4GOHi54OD8+BEz+DK2bDqkPFzzeDGaJlSD0f4KHZeWmlvuU7dT9BjMcjdYbU881ghokidJT9ZIYo880QK4P9lIvwWJjBDFHmR8lQbj/5ROeSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSpcxYdSO3fuZMWKFcyePZtSqcT3v//9BsSSpMrZT5Kisp8kRWU/SUqp4kOpEydOcOONN/KVr3ylEXkkqWr2k6So7CdJUdlPklLqqPSCZcuWsWzZskZkkaSa2E+SorKfJEVlP0lKyeeUkiRJkiRJUuEqvlOqUidPnuTkyZOj/zw4ONjokZJUFvtJUlT2k6So7CdJ9dTwO6U2bNhAT0/P6Ftvb2+jR0pSWewnSVHZT5Kisp8k1VPDD6XWr1/PwMDA6Ft/f3+jR0pSWewnSVHZT5Kisp8k1VPDf32vs7OTzs7ORo+RpIrZT5Kisp8kRWU/Saqnig+ljh8/zoEDB0b/+X//7//Nc889x5vf/Gbmzp1b13CSVAn7SVJU9pOkqOwnSSlVfCj1zDPP8IEPfGD0n++55x4A7rzzTrZu3Vq3YJJUKftJUlT2k6So7CdJKVV8KHXrrbeSZVkjskhSTewnSVHZT5Kisp8kpdTwJzqXJEmSJEmSJvJQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmFK2VZlhU5cHBwkJ6eHijBFbOLnJx79Qhkw1Bqg8tnFT/fDGaIliH1fIATh4EMBgYG6O7uThOC9P0EMR6P1BlSzzeDGSaK0FH2kxmizDdDrAz2Uy7CY2EGM0SZHyVDuf2U7lBKkiYIcyglSecR4g99knQe9pOkqCbrp44Cs5zNO6XMYIYQGVLPh7FT9DD8m76WX5NmMMN4oTrKfmr5DKnnmyFWBvspF+GxMIMZosyPkqHcfkp2KHX51bDqUPFzH54DJ36WPzAp5pvBDNEypJ4P8NDsvDijSNVPEOPxSJ0h9XwzmGGiSB1lP5kh9XwzxMpgP+UiPBZmMEOU+VEylNtPPtG5JEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCpfu1fcqdPwg7N8KA31w6hhM64Ke+bBgNUyfW0yGGfSymNVcxXwupYvXOcbL9LGbrRylv5gQ0hmuxzjsJ+lsrsdYUneU60HRuCbjSN1P4HpQLK24HsMfSh3eAXs3wcFt+csZAmRDUGrP33/2PrhmOSxaB7OWNCbDfJawlLUsZDkZwwC00cbwmfeXcx97eZTtbKKPXY0JIZ3heozDfpLO5nqMJXVHuR4UjWsyjtT9BK4HxdLK6zHsr+9lGTy/EbbdCv2PA1leVNnQmY+PvJ/Bwcfh0ffnxZZl9c2xlLWsYwc3sIw22ming3Y6KI17v402FnI769jJbdxT3wDSOK7HGOwn6VyuxzgidJTrQdG4JmOI0E/gelAsrb4ewx5K7dsMT96bv5+dvvjnjnx8z7r8unq5jXv4DTYC0M60i37uyMdXsmnKLRLF4HqMw36SzuZ6jCV1R7keFI1rMo7U/QSuB8Xiegx6KHV4R14+1dizDo7srD3DfJawkk1VXbuSTcznfbWHkM5wPcZhP0lncz3GkrqjXA+KxjUZR+p+AteDYnE95io6lNqwYQPvfve76erq4qqrruLXfu3X2L9/f91D7d0EpSqf7arUkV9fq6WsZYhTVV07xKkpdXKp9FyPk7OfytMq60HFcT2Wp1U6yvWgaFyTk2uVfgLXg2JxPeYqOpTasWMHa9asYc+ePTzxxBOcOnWKD33oQ5w4caJugY4fzJ/wbrLbOS8kOw0vPgrHa3hi+hn0spDlk94+dyHtTGMRH2EGc6oPIZ3heiyP/VSeVlkPKobrsXyt0FGuB0XjmixPK/QTuB4Ui+txTEWHUj/84Q9ZvXo1119/PTfeeCNbt27l4MGDPPvss3ULtH/r2CswVKvUBvu3VH/9YlaPPuN9tTKGWcxdNX0NCVyP5bKfytcK60HFcD2WrxU6yvWgaFyT5WmFfgLXg2JxPY6p8gbK3MDAAABvfvObL/g5J0+e5OTJk6P/PDg4ePGv2VdLojGDB6q/9irm1yFBxkzm1eHrqNW5HqtjP11M660HNYbrsXqTdVSl/QTpO8r1oGhck9WZiv0ErgfF4nocU/V59fDwMH/wB3/ALbfcwg033HDBz9uwYQM9PT2jb729vRf9uqeOjb0kaLWyIXhj8m68oEvpoq3G54Bvo53L6K7pa0jgeqyG/XRxrbYe1Diux+qU01GV9hOk7yjXg6JxTVZuqvYTuB4Ui+txTNXfhTVr1vA3f/M3fOtb37ro561fv56BgYHRt/7+i/8i8LQuKLVXmypXaodLanhsXucYwzXeSjfMEK9RQ2tKZ7geK2c/XVyrrQc1juuxOuV0VKX9BOk7yvWgaFyTlZuq/QSuB8XiehxT1a/vffKTn2Tbtm3s3LmTOXMu/sRanZ2ddHZ2lv21e+pxFxvQXcNdbC9Tj/tLS7xCDfeXSme4HitjP5WjddaDGsv1WLlyO6rSfoL0HeV6UDSuycpM5X4C14NicT2OqehOqSzL+OQnP8n3vvc9fvzjH3PttdfWPdCC1ZDVdmBINgwLani+r91spVTjrXQl2thNDc/EJ53heiyP/VS+VlgPKobrsXyt0FGuB0XjmixPK/QTuB4Ui+txTEXfhTVr1vDQQw/xjW98g66uLl566SVeeuklXnvttboFmj4X5i6HUpVPwV7qgGtWwPTJf7X5go7Szz62McSpqq4f4hR7+QFHOVR9COkM12N57KfytMp6UDFcj+VrhY5yPSga12R5WqGfwPWgWFyPYyo6lHrggQcYGBjg1ltvZdasWaNv3/72t+sa6sZ1kJ2u7tpsCBatrT3DE2yknWlVXdtGO9vZXHsI6QzX4+Tsp/K0ynpQcVyP5WmVjnI9KBrX5ORapZ/A9aBYXI+5in9973xvq1evrmuoWUvg5o3VXXvz/fn1tepjF49QXfN9l3vpY1ftIaQzXI+Ts5/K0yrrQcVxPZanVTrK9aBoXJOTa5V+AteDYnE95mr7JcYGWnjPWGlNdpvnyMdv3phfVy/b2Ty6SCa7rW7k44+wdsqcWCoW12Mc9pN0NtdjLKk7yvWgaFyTcaTuJ3A9KBbXY+BDqVIpv0VzxQ6YeztQyl8GdOSlREffL+UfX7Ej//xSqb45trOZjSxhH48xzDBDnGaI02QMM8QphjjNMMPs4zE2smRKLQ7F43qMwX6SzuV6jCNCR7keFI1rMoYI/QSuB8XS6uuxyqeaK86sJfnb8X7YvwUGD8Abg3BJd/6SoAvuqu0J78rRxy762MUM5rCYu5jJPC6jm9cY5BUOsJstU+IJxtQcXI9x2E/S2VyPsaTuKNeDonFNxpG6n8D1oFhaeT2GP5QaMb0XbvpM2gxHOcRjfC5tCOkM12Mc9pN0NtdjLKk7yvWgaFyTcaTuJ3A9KJZWXI9hf31PkiRJkiRJU5eHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKlwpy7KsyIGDg4P09PRACa6YXeTk3KtHIBuGUhtcPqv4+WYwQ7QMqecDnDgMZDAwMEB3d3eaEKTvJ4jxeKTOkHq+GcwwUYSOsp/MEGW+GWJlsJ9yER4LM5ghyvwoGcrtp3SHUpI0QZhDKUk6jxB/6JOk87CfJEU1WT91FJjlbN4pZQYzhMiQej6MnaKH4d/0tfyaNIMZxgvVUfZTy2dIPd8MsTLYT7kIj4UZzBBlfpQM5fZTskOpy6+GVYeKn/vwHDjxs/yBSTHfDGaIliH1fICHZufFGUWqfoIYj0fqDKnnm8EME0XqKPvJDKnnmyFWBvspF+GxMIMZosyPkqHcfvKJziVJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuGSvvteMjh+E/VthoA9OHYNpXdAzHxashulzzVBkBsEMelnMaq5iPpfSxesc42X62M1WjtKfOp4KFmFfmkEj7CeNF2FfmkHj2VEaL/XeTD0/SgblWrGfPJQqw+EdsHcTHNwGpTP3lmVDUGrP33/2PrhmOSxaB7OWmKGRGQTzWcJS1rKQ5WQMA9BGG8Nn3l/OfezlUbaziT52pYyqAkTYl2bQCPtJ40XYl2bQeHaUxku9N1PPj5JBuVbuJ3997yKyDJ7fCNtuhf7HgSzfpNnQmY+PvJ/Bwcfh0ffnmzrLzFDvDMotZS3r2MENLKONNtrpoJ0OSuPeb6ONhdzOOnZyG/ekjqwGibAvzaDx7CeNiLAvzaCJ7CiNSL03U8+PkkFjWr2fPJS6iH2b4cl78/ez0xf/3JGP71mXX2eG+mYQ3MY9/AYbAWhn2kU/d+TjK9k05UpLuQj70gwaYT9pvAj70gwaz47SeKn3Zur5UTIoZz9VeCj1wAMPsGjRIrq7u+nu7ua9730vjz/+eKOyJXV4R77xqrFnHRzZaYZ6ZVB+O+dKNlV17Uo2MZ/31TlRPPZTeaZSN0TIIPupXK3SURH2pRk0nh01uVbpJ0i/N1PPj5JBOfspV9Gh1Jw5c/jiF7/Is88+yzPPPMOv/uqv8tGPfpT/+T//Z6PyJbN3E5SqfMatUkd+vRnqk0H5LZ1DnKrq2iFOTamT9Auxn8ozlbohQgbZT+VqlY6KsC/NoPHsqMm1Sj9B+r2Zen6UDMrZT7mKDqVWrFjB7bffzvz583n729/O5z//eaZPn86ePXsalS+J4wfzJ3ub7FbGC8lOw4uPwvEanhzfDBoxg14WsnzS2zkvpJ1pLOIjzGBOnZPFYj+VZ6p0Q4QMsp8q0QodFWFfmkHj2VHlaYV+gvR7M/X8KBmUs5/GVP2cUkNDQ3zrW9/ixIkTvPe9761npuT2bx179YFqldpg/xYz1JpBsJjVo6/AUK2MYRZzV50SxWc/XdxU6IYIGWQ/VWuqdlSEfWkGjWdHVW6q9hOk35up50fJoJz9NKbiG/f27dvHe9/7Xl5//XWmT5/O9773PX75l3/5gp9/8uRJTp48OfrPg4OD1SUt0EBffb7O4AEz1JpBcBXz6/BVMmYyrw5fJzb7qXzN3g0RMsh+qlQlHWU/mcF+qp0dVb6p3k+Qfm+mnh8lg3L205iKz0kXLFjAc889x5NPPsnv/u7vcuedd/K3f/u3F/z8DRs20NPTM/rW29tbU+AinDo29nKY1cqG4I0a+tkMGnEpXbTV+EKZbbRzGd11ShSX/VSeqdANETLIfqpUJR1lP5nBfqqdHVW+qd5PkH5vpp4fJYNy9tOYir8Ll1xyCfPmzeOmm25iw4YN3HjjjfzxH//xBT9//fr1DAwMjL7198f/BdRpXVBqr+1rlNrhkhrWhxk04nWOMVzjrZ3DDPEaU/+/HvZTeaZCN0TIIPupUpV0lP1kBvupdnZU+aZ6P0H6vZl6fpQMytlPY6p83v0xw8PDZ92+OVFnZyednZ21jilUTz3upAO6a7iTzgwa8TL1uM+2xCu03n229tOFNXs3RMgg+6lWF+so+8kM9lPt7KjqTbV+gvR7M/X8KBmUs5/GVHSn1Pr169m5cycvvPAC+/btY/369fzkJz9h1apVjcqXxILVkNV2aEk2DAtqeM4xM2jEbrZSqvHWzhJt7GZqPyOh/VS+qdANETLIfqpEK3RUhH1pBo1nR5WnFfoJ0u/N1POjZFDOfhpT0Xfh5Zdf5rd+67dYsGABH/zgB3n66af50z/9U5YuXdqofElMnwtzl0OpyvvISh1wzQqYXsOvV5tBI47Szz62McSpqq4f4hR7+QFHOVTnZLHYT+WZKt0QIYPsp0q0QkdF2Jdm0Hh2VHlaoZ8g/d5MPT9KBuXspzEVLccHH3ywUTnCuXEdHHy0umuzIVi01gz1yiB4go3cyEequraNdrazuc6J4rGfyjOVuiFCBtlP5WqVjoqwL82g8eyoybVKP0H6vZl6fpQMytlPudruF5vCZi2BmzdWd+3N9+fXm6E+GQR97OIRqvsvwHe5lz521TmRUoqwL82gEfaTxouwL82g8ewojZd6b6aeHyWDcvZTzkOpi1h4z9iGnewWx5GP37wxv84M9c0g2M7m0dKa7DbPkY8/wtopc4Kus0XYl2bQCPtJ40XYl2bQeHaUxku9N1PPj5JBOfvJQ6mLKpXy2xNX7IC5twOl/CUwR15Gc/T9Uv7xFTvyzy+VzFDvDMptZzMbWcI+HmOYYYY4zRCnyRhmiFMMcZphhtnHY2xkyZQqK50twr40g8aznzQiwr40gyayozQi9d5MPT9KBo1p9X6q8inOWsusJfnb8X7YvwUGD8Abg3BJd/5ymAvuavyTvZlBI/rYRR+7mMEcFnMXM5nHZXTzGoO8wgF2s2VKPOGdyhNhX5pBI+wnjRdhX5pB49lRGi/13kw9P0oG5Vq5nzyUqsD0XrjpM2aIkEFwlEM8xudSx1AQEfalGTTCftJ4EfalGTSeHaXxUu/N1POjZFCuFfvJX9+TJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4UpZlmVFDhwcHKSnpwdKcMXsIifnXj0C2TCU2uDyWcXPN4MZomVIPR/gxGEgg4GBAbq7u9OEIH0/QYzHI3WG1PPNYIaJInSU/WSGKPPNECuD/ZSL8FiYwQxR5kfJUG4/pTuUkqQJwhxKSdJ5hPhDnySdh/0kKarJ+qmjwCxn804pM5ghRIbU82HsFD0M/6av5dekGcwwXqiOsp9aPkPq+WaIlcF+ykV4LMxghijzo2Qot5+SHUpdfjWsOlT83IfnwImf5Q9MivlmMEO0DKnnAzw0Oy/OKFL1E8R4PFJnSD3fDGaYKFJH2U9mSD3fDLEy2E+5CI+FGcwQZX6UDOX2k090LkmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMKle/W9Ch0/CPu3wkAfnDoG07qgZz4sWA3T55qhlTKknm+GWBkiiPB9MIMZosw3Qzypvxep55vBDNEypJ4fSYTvReoMqeebwQypM4Q/lDq8A/ZugoPb8pczBMiGoNSev//sfXDNcli0DmYtMcNUzpB6vhliZYggwvfBDGaIMt8M8aT+XqSebwYzRMuQen4kEb4XqTOknm8GM0TJEPbX97IMnt8I226F/seBLP+GZENnPj7yfgYHH4dH359/A7PMDFMtQ+r5ZoiVIYII3wczmCHKfDPEk/p7kXq+GcwQLUPq+ZFE+F6kzpB6vhnMEC1D2EOpfZvhyXvz97PTF//ckY/vWZdfZ4aplSH1fDPEyhBBhO+DGcwQZb4Z4kn9vUg93wxmiJYh9fxIInwvUmdIPd8MZoiWIeSh1OEd+f/JauxZB0d2mmGqZEg93wyxMkQQ4ftgBjNEmW+GeFJ/L1LPN4MZomVIPT+SCN+L1BlSzzeDGSJmqOlQ6otf/CKlUok/+IM/qD3JOHs3QamjumtLHfn1ZpgaGVLPN0OsDJWwn8zQChlSzzdDdRrVT5D+e5F6vhnMEC1D6vnV8GeoxmVIPd8MZoiYoepDqaeffpr/8l/+C4sWLao9xTjHD+ZPrDXZbWMXkp2GFx+F4/1maPYMqeebIVaGSthPZmiFDKnnm6E6jeonSP+9SD3fDGaIliH1/Gr4M1TjMqSebwYzRMwAVR5KHT9+nFWrVvHVr36VGTNm1JZggv1bx57pvVqlNti/xQzNniH1fDPEylAu+8kMrZIh9XwzVK6R/QTpvxep55vBDNEypJ5fKX+GamyG1PPNYIaIGaDKQ6k1a9Zwxx13cNttt036uSdPnmRwcPCst4sZ6Ksm0bkGD1R/rRliZEg93wyxMpTLfjJDq2RIPd8MlWtkP0H670Xq+WYwQ7QMqedXqtyOasZ+ipAh9XwzmCFiBoCKf3vwW9/6Fn/1V3/F008/Xdbnb9iwgc9+9rNlf/1Txxh96cFqZUPwxuTdaIbgGVLPN0OsDOWwn8zQShlSzzdDZRrdT5D+e5F6vhnMEC1D6vmVqKSjmrGfImRIPd8MZoiYASq8U6q/v59PfepTPPzww1x66aVlXbN+/XoGBgZG3/r7L/4Lh9O6oNReSapzldrhku7qrzdDjAyp55shVobJ2E9maLUMqeeboXxF9BOk/16knm8GM0TLkHp+uSrtqGbspwgZUs83gxkiZoAK75R69tlnefnll3nnO985+u+GhobYuXMnX/7ylzl58iTt7Wf/v+rs7KSzs7PsGT3zK0l0Yd3zqr/WDDEypJ5vhlgZJmM/maHVMqSeb4byFdFPkP57kXq+GcwQLUPq+eWqtKOasZ8iZEg93wxmiJgBKrxT6oMf/CD79u3jueeeG31717vexapVq3juuefO+YGqGgtWQzZc29fIhmHBXWZo9gyp55shVobJ2E9maLUMqeeboXxF9BOk/16knm8GM0TLkHp+ufwZqpgMqeebwQwRM0CFh1JdXV3ccMMNZ71dccUVXHnlldxwww21JTlj+lyYuxxKFT/bVa7UAdesgOm9Zmj2DKnnmyFWhsnYT2ZotQyp55uhfEX0E6T/XqSebwYzRMuQen65/BmqmAyp55vBDBEzQJWvvtdoN66D7HR112ZDsGitGaZKhtTzzRArQwQRvg9mMEOU+WaIJ/X3IvV8M5ghWobU8yOJ8L1InSH1fDOYIWKGmg+lfvKTn/ClL32p9iTjzFoCN2+s7tqb78+vN8PUyJB6vhliZaiU/WSGqZ4h9XwzVK8R/QTpvxep55vBDNEypJ5fLX+GakyG1PPNYIaIGULeKQWw8J6xb85kt5ONfPzmjfl1ZphaGVLPN0OsDBFE+D6YwQxR5pshntTfi9TzzWCGaBlSz48kwvcidYbU881ghmgZwh5KlUr5rWArdsDc24ESlNoZfcnC0fdL+cdX7Mg/v1Qyw1TLkHq+GWJliCDC98EMZogy3wzxpP5epJ5vBjNEy5B6fiQRvhepM6SebwYzRMtQ5VNaFWfWkvzteD/s3wKDB+CNQbikO3/pwQV3Nf7J/8wQI0Pq+WaIlSGCCN8HM5ghynwzxJP6e5F6vhnMEC1D6vmRRPhepM6Qer4ZzBAlQ/hDqRHTe+Gmz5jBDOnnmyFWhggifB/MYIYo880QT+rvRer5ZjBDtAyp50cS4XuROkPq+WYwQ+oMYX99T5IkSZIkSVOXh1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXCnLsqzIgYODg/T09EAJrphd5OTcq0cgG4ZSG1w+q/j5ZjBDtAyp5wOcOAxkMDAwQHd3d5oQpO8niPF4pM6Qer4ZzDBRhI6yn8wQZb4ZYmWwn3IRHgszmCHK/CgZyu2ndIdSkjRBmEMpSTqPEH/ok6TzsJ8kRTVZP3UUmOVs3illBjOEyJB6Poydoofh3/S1/Jo0gxnGC9VR9lPLZ0g93wyxMthPuQiPhRnMEGV+lAzl9lOyQ6nLr4ZVh4qf+/AcOPGz/IFJMd8MZoiWIfV8gIdm58UZRap+ghiPR+oMqeebwQwTReoo+8kMqeebIVYG+ykX4bEwgxmizI+Sodx+8onOJUmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLh0r77XhI4fhP1bYaAPTh2DaV3QMx8WrIbpc81QVIYZ9LKY1VzFfC6li9c5xsv0sZutHKW/8QGkgFLvSzOMsaOks0XYl2bI2U/SuVLvzdTzo2Swn1qXh1JlOLwD9m6Cg9vyl1QEyIag1J6//+x9cM1yWLQOZi0xQ6MyzGcJS1nLQpaTMQxAG20Mn3l/Ofexl0fZzib62FX/AFJAqfelGcbYUdLZIuxLM+TsJ+lcqfdm6vlRMthP8tf3LiLL4PmNsO1W6H8cyPJNmg2d+fjI+xkcfBwefX++qbPMDPXOsJS1rGMHN7CMNtpop4N2OiiNe7+NNhZyO+vYyW3cU7/hUkAR9qUZxthR0pgI+9IMY+wn6Wyp92bq+VEygP2knIdSF7FvMzx5b/5+dvrinzvy8T3r8uvMUL8Mt3EPv8FGANqZdtHPHfn4SjZZWprSUu9LM4yxo6SzRdiXZsjZT9K5Uu/N1POjZLCfNKKiQ6n77ruPUql01tt1113XqGxJHd6Rb7xq7FkHR3aaoR4Z5rOElWyq6tqVbGI+76stgJqG/VSeqdINUTLYUSpXq3RUhH1phpz9pHK1Sj9B+r2Zen6UDPaTxqv4Tqnrr7+eI0eOjL79xV/8RSNyJbd3E5SqfMatUkd+vRlqz7CUtQxxqqprhzjlSXqLsZ8mN1W6IUoGO0qVaIWOirAvzZCzn1SJVugnSL83U8+PksF+0ngVL8eOjg6uvvrqRmQJ4/jB/MneqPJ3ZrPT8OKjcLwfpveaodoMM+hlIctpq/K3TNuZxiI+wgzmcJRDVX0NNRf7aXJToRuiZLCjVKmp3lER9qUZcvaTKjXV+wnS783U86NksJ80UcUroa+vj9mzZ/PWt76VVatWcfDgwUbkSmr/1rFXH6hWqQ32bzFDLRkWs3r0FRiqlTHMYu6q6WuoedhP5Wn2boiSwY5SpaZ6R0XYl2bI2U+q1FTvJ0i/N1PPj5LBftJEFd0p9Su/8its3bqVBQsWcOTIET772c/yvve9j7/5m7+hq6vrvNecPHmSkydPjv7z4OBgbYkLMNBXn68zeMAMtWS4ivl1mJ4xk3l1+DqKzn6qTDN3Q5QMdpQqUWlH2U9msJ9UlFboJ0i/N1PPj5LBftJEFR1KLVu2bPT9RYsW8Su/8itcc801fOc73+G3f/u3z3vNhg0b+OxnP1tbyoKdOjb2cpjVyobgjRr62QxwKV1V39Y5oo12LqO7pq+h5mA/la/ZuyFKBjtKlai0o+wnM9hPKkor9BOk35up50fJYD9poppWw5ve9Cbe/va3c+DAhY9K169fz8DAwOhbf39/LSMLMa0LSu21fY1SO1xSwz4xA7zOMYZrvLVzmCFeozn+9kb1ZT9dWLN3Q5QMdpRqMVlH2U9msJ+UylTsJ0i/N1PPj5LBftJENR1KHT9+nP/1v/4Xs2bNuuDndHZ20t3dfdZbdD31uKMQ6K7hjkIzwMvU4/7SEq9Qw/2lalr208U1czdEyWBHqRaTdZT9ZAb7SalMxX6C9Hsz9fwoGewnTVTRodS6devYsWMHL7zwArt37+af/JN/Qnt7O7/5m7/ZqHxJLFgNWW2Ht2TDsKCG514zA+xmK6Uab+0s0cZuangmPjUN+6l8zd4NUTLYUapEK3RUhH1phpz9pEq0Qj9B+r2Zen6UDPaTJqpoNRw6dIjf/M3fZMGCBfzTf/pPufLKK9mzZw8zZ85sVL4kps+FucuhVNEzbo0pdcA1K6p/mUwz5I7Szz62McSpqq4f4hR7+YEvFdoi7KfyTIVuiJLBjlIlWqGjIuxLM+TsJ1WiFfoJ0u/N1POjZLCfNFFFy/Fb3/pWo3KEc+M6OPhodddmQ7BorRnqkeEJNnIjH6nq2jba2c7m2gKoadhP5Zkq3RAlgx2lcrVKR0XYl2bI2U8qV6v0E6Tfm6nnR8lgP2m82u6bm8JmLYGbN1Z37c3359ebofYMfeziEaprvu9yL33sqi2AFFDqfWmGMXaUdLYI+9IMOftJOlfqvZl6fpQM9pPG81DqIhbeM7ZhJ7vFceTjN2/MrzND/TJsZ/NoaU12m+fIxx9hrSfomtJS70szjLGjpLNF2JdmyNlP0rlS783U86NksJ80wkOpiyiV8tsTV+yAubcDpfwlMEdeRnP0/VL+8RU78s8vlcxQ7wzb2cxGlrCPxxhmmCFOM8RpMoYZ4hRDnGaYYfbxGBtZYllpyouwL80wxo6SxkTYl2YYYz9JZ0u9N1PPj5IB7CflqnyKs9Yya0n+drwf9m+BwQPwxiBc0p2/HOaCu2p7sjczlKePXfSxixnMYTF3MZN5XEY3rzHIKxxgN1t8wju1nNT70gxj7CjpbBH2pRly9pN0rtR7M/X8KBnsJ3koVYHpvXDTZ8yQOsNRDvEYn0sXQAoo9b40wxg7SjpbhH1phpz9JJ0r9d5MPT9KBvupdfnre5IkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSpcKcuyrMiBg4OD9PT0QAmumF3k5NyrRyAbhlIbXD6r+PlmMEO0DKnnA5w4DGQwMDBAd3d3mhCk7yeI8XikzpB6vhnMMFGEjrKfzBBlvhliZbCfchEeCzOYIcr8KBnK7ad0h1KSNEGYQylJOo8Qf+iTpPOwnyRFNVk/dRSY5WzeKWUGM4TIkHo+jJ2ih+Hf9LX8mjSDGcYL1VH2U8tnSD3fDLEy2E+5CI+FGcwQZX6UDOX2U7JDqcuvhlWHip/78Bw48bP8gUkx3wxmiJYh9XyAh2bnxRlFqn6CGI9H6gyp55vBDBNF6ij7yQyp55shVgb7KRfhsTCDGaLMj5Kh3H7yic4lSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuHSvvqemNYNeFrOaq5jPpXTxOsd4mT52s5Wj9Dd8/vGDsH8rDPTBqWMwrQt65sOC1TB9bsPHm0EKLHU/RciQer4ZpPOLsCYj/OwQ4fuQOkPq+dJEEdak/dS6GTyUUtnms4SlrGUhy8kYBqCNNobPvL+c+9jLo2xnE33sqvv8wztg7yY4uC1/aUuAbAhK7fn7z94H1yyHRetg1pK6jzeDFFjqfoqQIfV8M0jnF2FNRvjZIcL3IXWG1POliSKsSfvJDP76nsqylLWsYwc3sIw22ming3Y6KI17v402FnI769jJbdxTt9lZBs9vhG23Qv/jQJYXVTZ05uMj72dw8HF49P15sWVZ3SKYQQosZT9FyZB6vhmk80u9JqP87JD6+xAhQ+r50kSp16T9ZIYRHkppUrdxD7/BRgDamXbRzx35+Eo21W2h7tsMT96bv5+dvvjnjnx8z7r8unoxgxRT6n6KkCH1fDNI5xdhTUb42SHC9yF1htTzpYkirEn7yQwjPJTSRc1nCSvZVNW1K9nEfN5X0/zDO/LyqcaedXBkZ03jzSAFlrqfImRIPd8M0vlFWJMRfnaI8H1InSH1fGmiCGvSfjLDeBUfSv3sZz/jYx/7GFdeeSWXXXYZCxcu5Jlnnqk5iGJaylqGOFXVtUOcqvn0dO8mKFX5zGeljvz6WpmhedhPrSV1P0XIkHq+GSpjR7WOCGsyws8OEb4PqTOknl8u+6l1RFiT9pMZxqvoUOro0aPccsstTJs2jccff5y//du/ZdOmTcyYMaPmIIpnBr0sZPmkt/BdSDvTWMRHmMGcqq4/fjB/wrvJbue8kOw0vPgoHK/hBQLM0Dzsp9aSup8iZEg93wyVsaNaR4Q1GeFnhwjfh9QZUs8vl/3UOiKsSfvJDBNVdCj1R3/0R/T29rJlyxbe8573cO211/KhD32It73tbTWFUEyLWT36rPvVyhhmMXdVde3+rWOvwFCtUhvs31L99WZoHvZTa0ndTxEypJ5vhsrYUa0jwpqM8LNDhO9D6gyp55fLfmodEdak/WSGiSpaDj/4wQ9417vexcqVK7nqqqt4xzvewVe/+tWLXnPy5EkGBwfPelNzuIr5dfgqGTOZV9WVA311GA8MHqj+WjM0D/uptaTupwgZUs83Q2Uq7Sj7qXlFWJMRfnaI8H1InSH1/HLZT60jwpq0n8wwUUWHUv/wD//AAw88wPz58/nTP/1Tfvd3f5ff//3f5+tf//oFr9mwYQM9PT2jb729vTUFVnEupYu2Gp8Lv412LqO7qmtPHRt7SdBqZUPwRg3/nTRD87CfWkvqfoqQIfV8M1Sm0o6yn5pXhDUZ4WeHCN+H1BlSzy+X/dQ6IqxJ+8kM536NCgwPD/POd76TL3zhC7zjHe/gX/yLf8Hv/M7v8J//83++4DXr169nYGBg9K2/f4o/sc0U8jrHGK7xdr5hhniN6hpjWheU2msaT6kdLqlhj5ihedhPrSV1P0XIkHq+GSqcUWFH2U/NK8KajPCzQ4TvQ+oMqeeXPcN+ahkR1qT9ZIaJKjqUmjVrFr/8y7981r/7R//oH3Hw4MELXtPZ2Ul3d/dZb2oOL1OPeytLvEJ191b21ONuQqC7hrsJzdA87KfWkrqfImRIPd8Mlam0o+yn5hVhTUb42SHC9yF1htTzy2U/tY4Ia9J+MsNEFR1K3XLLLezfv/+sf/f3f//3XHPNNTWFUEy72Uqpxtv5SrSxm+qehW7BashqO7glG4YFNTzvmhmah/3UWlL3U4QMqeeboTJ2VOuIsCYj/OwQ4fuQOkPq+eWyn1pHhDVpP5lhoooS/Ot//a/Zs2cPX/jCFzhw4ADf+MY3+K//9b+yZs2amkIopqP0s49tDHGqquuHOMVefsBRDlV1/fS5MHc5lDqqupxSB1yzAqbX8GvuZmge9lNrSd1PETKknm+GythRrSPCmozws0OE70PqDKnnl8t+ah0R1qT9ZIaJKjqUeve73833vvc9vvnNb3LDDTfwuc99ji996UusWrWqphCK6wk20s60qq5to53tbK5p/o3rIDtd3bXZECxaW9N4MzQR+6n1pO6nCBlSzzdD+eyo1hJhTUb42SHC9yF1htTzy2E/tZYIa9J+MsPZX6dCy5cvZ9++fbz++uv89Kc/5Xd+53dqDqG4+tjFI1S367/LvfSxq6b5s5bAzRuru/bm+/Pra2WG5mE/tZbU/RQhQ+r5ZqiMHdU6IqzJCD87RPg+pM6Qen657KfWEWFN2k9mGK+2XyBUS9jO5tGFOtmtfSMff4S1dfubnYX3jJXWZLd5jnz85o35dfViBimm1P0UIUPq+WaQzi/Cmozws0OE70PqDKnnSxNFWJP2kxlGeCilsmxnMxtZwj4eY5hhhjjNEKfJGGaIUwxxmmGG2cdjbGRJXTdJqZTforliB8y9HSjlLwM68lKio++X8o+v2JF/fqlUtwhmkAJL2U9RMqSebwbp/FKvySg/O6T+PkTIkHq+NFHqNWk/mWFElU8vplbUxy762MUM5rCYu5jJPC6jm9cY5BUOsJstDX0ixllL8rfj/bB/CwwegDcG4ZLu/CVBF9zV+CfzNoMUU+p+ipAh9XwzSOcXYU1G+NkhwvchdYbU86WJIqxJ+8kMHkqpYkc5xGN8Ltn86b1w02eSjTeDFFjqfoqQIfV8M0jnF2FNRvjZIcL3IXWG1POliSKsSfupdTP463uSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKlwpy7KsyIGDg4P09PRACa6YXeTk3KtHIBuGUhtcPqv4+WYwQ7QMqecDnDgMZDAwMEB3d3eaEKTvJ4jxeKTOkHq+GcwwUYSOsp/MEGW+GWJlsJ9yER4LM5ghyvwoGcrtp3SHUpI0QZhDKUk6jxB/6JOk87CfJEU1WT91FJjlbN4pZQYzhMiQej6MnaKH4d/0tfyaNIMZxgvVUfZTy2dIPd8MsTLYT7kIj4UZzBBlfpQM5fZTskOpy6+GVYeKn/vwHDjxs/yBSTHfDGaIliH1fICHZufFGUWqfoIYj0fqDKnnm8EME0XqKPvJDKnnmyFWBvspF+GxMIMZosyPkqHcfvKJziVJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4dK++p6rMoJfFrOYq5nMpXbzOMV6mj91s5Sj9LZEh9XxJ5xdhb5pB0vlE2JdmyB0/CPu3wkAfnDoG07qgZz4sWA3T5xYSQQolwr40gxlS8lCqScxnCUtZy0KWkzEMQBttDJ95fzn3sZdH2c4m+tg1JTOkni/p/CLsTTNIOp8I+9IMucM7YO8mOLgtf4lygGwISu35+8/eB9csh0XrYNaShkSQQomwL81ghgj89b0msJS1rGMHN7CMNtpop4N2OiiNe7+NNhZyO+vYyW3cM+UypJ4v6fwi7E0zSDqfCPvSDJBl8PxG2HYr9D8OZPlhVDZ05uMj72dw8HF49P354VWW1TWGFErqfWkGM0TioVRwt3EPv8FGANqZdtHPHfn4SjbVdaGmzpB6vqTzi7A3zSDpfCLsSzPk9m2GJ+/N389OX/xzRz6+Z11+nTQVRdiXZjBDJBUdSr3lLW+hVCqd87ZmzZpG5Wtp81nCSjZVde1KNjGf9zV9htTz1VzsqOJE2JtmUDOxn4oTYV+aIXd4R37AVI096+DIzpojqAz2U3Ei7EszmCGaig6lnn76aY4cOTL69sQTTwCwcuXKhoRrdUtZyxCnqrp2iFN1OT1NnSH1fDUXO6o4EfamGdRM7KfiRNiXZsjt3QSlKp/BttSRX6/Gs5+KE2FfmsEM0VR0KDVz5kyuvvrq0bdt27bxtre9jfe///2NyteyZtDLQpZPegvfhbQzjUV8hBnMadoMqeer+dhRxYiwN82gZmM/FSPCvjRD7vjB/EnNJ/uVvQvJTsOLj8LxqfliU6HYT8WIsC/NYIaIqn5OqTfeeIOHHnqIu+++m1KpVM9MAhazevRZ96uVMcxi7mraDKnnq7nZUY0TYW+aQc3MfmqcCPvSDLn9W8deZa9apTbYv6W2r6HK2E+NE2FfmsEMEVV5Qy18//vf5+c//zmrV6++6OedPHmSkydPjv7z4OBgtSNbylXMr8NXyZjJvKbNkHq+mls5HWU/VSfC3jSDmpn91DgR9qUZcgN9dYgADB6oz9dReeynxomwL81ghoiq/vuLBx98kGXLljF79uyLft6GDRvo6ekZfevt7a12ZEu5lC7aanxxxDbauYzups2Qer6aWzkdZT9VJ8LeNIOamf3UOBH2pRlyp45BNlRTBLIheMPzjkLZT40TYV+awQwRVfVdePHFF9m+fTsf//jHJ/3c9evXMzAwMPrW3+8vhpfjdY4xXOPtfMMM8RrV/5c8dYbU89W8yu0o+6k6EfamGdSs7KfGirAvzZCb1gWl9poiUGqHS5r/z1tNw35qrAj70gxmiKiqX9/bsmULV111FXfcccekn9vZ2UlnZ2c1Y1ray9TjnucSr1D9Pc+pM6Ser+ZVbkfZT9WJsDfNoGZlPzVWhH1phlxPPX4zBehu/t9MaRr2U2NF2JdmMENEFd8pNTw8zJYtW7jzzjvp6Kj6Kak0id1spVTj7Xwl2thN9c8OmTpD6vlqTnZU40XYm2ZQM7KfGi/CvjRDbsFqyGq7CYBsGBY0/3P4NgX7qfEi7EszmCGiir8L27dv5+DBg9x9992NyKMzjtLPPrYxxKmqrh/iFHv5AUc51LQZUs9Xc7KjGi/C3jSDmpH91HgR9qUZctPnwtzlUKryfKPUAdesgOk+XVEh7KfGi7AvzWCGiCo+lPrQhz5ElmW8/e1vb0QejfMEG2lnWlXXttHOdjY3fYbU89V87KhiRNibZlCzsZ+KEWFfmiF34zrITld3bTYEi9bWHEFlsp+KEWFfmsEM0dR2v5gaqo9dPEJ1/zX+LvfSx66mz5B6vqTzi7A3zSDpfCLsSzPkZi2BmzdWd+3N9+fXS1NJhH1pBjNE46FUcNvZPLpQJ7u1b+Tjj7C2rqemqTOkni/p/CLsTTNIOp8I+9IMuYX3jB1MTfarfCMfv3ljfp00FUXYl2YwQyQ+i10T2M5mXuRpbuMeFvERsjMvHdlGG8MMASVKtLGPx9jO5oacmKbOkHq+pPOLsDfNIOl8IuxLM0CplP8a3sx3w95N8OKjUDrz1+LZEJTaz7w/DHNvzz/XO6Q01aXel2YwQyQeSjWJPnbRxy5mMIfF3MVM5nEZ3bzGIK9wgN1safiTnKXOkHq+pPOLsDfNIOl8IuxLM+RmLcnfjvfD/i0weADeGIRLuqF7Xv4qez6puVpJhH1pBjNE4KFUkznKIR7jcy2dIfV8SecXYW+aQdL5RNiXZshN74WbPpM0ghRKhH1pBjOk5HNKSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXClLMuyIgcODg7S09MDJbhidpGTc68eyV9yttQGl88qfr4ZzBAtQ+r5ACcOAxkMDAzQ3d2dJgTp+wliPB6pM6SebwYzTBSho+wnM0SZb4ZYGeynXITHwgxmiDI/SoZy+yndoZQkTRDmUEqSziPEH/ok6TzsJ0lRTdZPHQVmOZt3SpnBDCEypJ4PY6foYfg3fS2/Js1ghvFCdZT91PIZUs83Q6wM9lMuwmNhBjNEmR8lQ7n9lOxQ6vKrYdWh4uc+PAdO/Cx/YFLMN4MZomVIPR/godl5cUaRqp8gxuOROkPq+WYww0SROsp+MkPq+WaIlcF+ykV4LMxghijzo2Qot598onNJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVLt2r70lVOn4Q9m+FgT44dQymdUHPfFiwGqbPLSbDDHpZzGquYj6X0sXrHONl+tjNVo7SX0wISSGl7ij7SdKFpO4nsKMknZ/91Lo8lFLTOLwD9m6Cg9vyl7YEyIag1J6//+x9cM1yWLQOZi1pTIb5LGEpa1nIcjKGAWijjeEz7y/nPvbyKNvZRB+7GhNCUkipO8p+knQhqfsJ7ChJ52c/yV/fU3hZBs9vhG23Qv/jQJYXVTZ05uMj72dw8HF49P15sWVZfXMsZS3r2MENLKONNtrpoJ2O/8/e3QdXed53/n+fI2H5AUkhLq6hYNcJBLcxeBwnqYMnxGlMNjjgtNOwux3ya3Da7m7jtGkB74ad2ayzbkI7ASadTerdpg5kx86TM3XHxuO0JmmADvVj14ZuUyratREBrz27RAJsY5Du3x+39YAs0Hm8r+/Reb9mNJUtHX0/va/r/gRfHJ1DadznZcos5hY2sJubWdfYAJJCitBR9pOkyUToJ7CjJL2R/aQRHkopvP1b4fE78s+zM+f/3pGvP7Yhf1yj3Mw6PspmADqYcd7vHfn6arZYWlIbSN1R9pOkc0ndT2BHSZqc/aQRHkoptCO78vKpxWMb4Oju+jMsZBmr2VLTY1ezhYW8t/4QkkJK3VH2k6RzSd1PYEdJmpz9pPGqOpQaGhriP/2n/8RVV13FRRddxFvf+lbuuususkY/h0563b4tUKrxlc9Knfnj67Wc9QxxuqbHDnHak/SC2E9KIXVH2U+tw45S0VL3E9hRrcJ+UtHsJ41X1Vb4wz/8Q+6++26+/vWv8/a3v52nnnqK2267jd7eXn7nd36nWRnVpk4cyl/wjhr/9zA7A88/BCf6Yeb82n7GLOazmJWUa3xSYQczWMKtzGIexzhcWwhVxH5S0VJ3lP3UWuwoFSl1P4Ed1UrsJxXJftJEVa3C3r17+chHPsKHP/xhfvZnf5aPfvSjfPCDH+SJJ55oVj61sQPbx96BoValMhzYVvvjl7J29B0YapUxzFJuq+tnaGr2k4qWuqPsp9ZiR6lIqfsJ7KhWYj+pSPaTJqpqOyxdupTvf//7/OM//iMAzz77LH/913/NihUrzvmYU6dOMTg4eNaHVImBvsb8nMGDtT/2MhY2IEHGbBY04OfofOwnFS11R9lPraXajrKfVI/U/QR2VCuxn1Qk+0kTVfXre5/5zGcYHBzk6quvpqOjg6GhIT7/+c+zZs2acz5m06ZNfO5zn6s7qNrP6eNjbwlaq2wIXqvjfycvpLvmp3WOKNPBRfTU9TM0NftJRUvdUfZTa6m2o+wn1SN1P4Ed1UrsJxXJftJEVa3Ed77zHe677z6+8Y1v8Ld/+7d8/etfZ/PmzXz9618/52M2btzIwMDA6Ed/f3/dodUeZnRDqaO+n1HqgAvq6IpXOc5wnU/tHGaIV/BvkJrNflLRUneU/dRaqu0o+0n1SN1PYEe1EvtJRbKfNFFVz5S64447+MxnPsO//tf/GoDFixfz/PPPs2nTJj7+8Y9P+piuri66urrqT6q209uIZ1UCPXU8q/JFGvH80hIvUcfzS1UR+0lFS91R9lNrqbaj7CfVI3U/gR3VSuwnFcl+0kRVPVPq5Zdfplw++yEdHR0MD9d3yihNZtFayOrcWtkwLKrj9ef2sp1SnU/tLFFmL3W8Ep8qYj+paKk7yn5qLXaUipS6n8COaiX2k4pkP2miqlZi1apVfP7zn+fhhx/mueee44EHHmDr1q388i//crPyqY3NvAKuWAmlqp7PN6bUCVeuqv2tQgGO0c9+djDE6ZoeP8Rp9vGgbxVaAPtJRUvdUfZTa7GjVKTU/QR2VCuxn1Qk+0kTVXUo9V//63/lox/9KJ/85Cf5uZ/7OTZs2MC//bf/lrvuuqtZ+dTmrt0A2ZnaHpsNwZL19Wd4lM10MKOmx5bpYCdb6w+hKdlPSiF1R9lPrcOOUtFS9xPYUa3CflLR7CeNV9WhVHd3N1/60pd4/vnneeWVV/inf/onfv/3f58LLrigWfnU5uYsgxs21/bYG76YP75efezhfmprvu9yB33sqT+EpmQ/KYXUHWU/tQ47SkVL3U9gR7UK+0lFs580Xn2/SCkVYPG6sdKa6mmeI1+/YXP+uEbZydbR0prqaZ4jX7+f9Z6gS20gdUfZT5LOJXU/gR0laXL2k0Z4KKXwSqX8KZqrdsEVtwCl/G1AR95KdPTzUv71Vbvy7y+VGptjJ1vZzDL28zDDDDPEGYY4Q8YwQ5xmiDMMM8x+HmYzyywrqU1E6Cj7SdJkIvQT2FGS3sh+0ogaX15MKt6cZfnHiX44sA0GD8Jrg3BBT/6WoItuq+8F7yrRxx762MMs5rGU25jNAi6ih1cY5CUOspdtvuCd1KZSd5T9JOlcUvcT2FGSJmc/yUMptZyZ8+H6z6bNcIzDPIwv/ijpjVJ3lP0k6VxS9xPYUZImZz+1L399T5IkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmFK2VZlhU5cGBggDe96U0AXDynyMm5l18AMqAEF19e/HwzmCFahtTzAV4+mv/fn/zkJ/T29qYJQfp+giDr4Z40gxnOzhCgo+wnM0SZb4ZgGewnIMhamMEMQeaHyVBhPxV+KHX48GHmz59f5EhJLaK/v5958+Ylm28/STqflB1lP0k6H/tJUlRT9VPhh1LDw8McOXKE7u5uSqVS1Y8fHBxk/vz59Pf309PT04SEZmiVDKnnm6FxGbIs4/jx48ydO5dyOd1vFdtPZphOGVLPn04ZInRUvf0E6dcj9XwzmCFaBvtpTOq1iJAh9XwzmKHRGSrtp856QtaiXC435BS/p6cn2eKYIVaG1PPN0JgMKX9tb4T9ZIbpmCH1/OmSIXVHNaqfIP16pJ5vBjNEy2A/jUm9FhEypJ5vBjM0MkMl/eQLnUuSJEmSJKlwHkpJkiRJkiSpcC13KNXV1cV//s//ma6uLjO0eYbU880QK0MEEa6DGcwQZb4Z4kl9LVLPN4MZomVIPT+SCNcidYbU881ghlQZCn+hc0mSJEmSJKnlniklSZIkSZKk1uehlCRJkiRJkgrnoZQkSZIkSZIK11KHUn/zN39DR0cHH/7whwufvXbtWkql0ujHpZdeyoc+9CH27dtXeJYXXniB3/7t3+Ytb3kLXV1dzJ8/n1WrVvH973+/6bPHX4cZM2bw0z/90yxfvpyvfe1rDA8PN33+xAzjPz70oQ8VMn+qHAcPHixk/gsvvMCnP/1pFixYwIUXXshP//RPc+ONN3L33Xfz8ssvN33+2rVr+aVf+qU3/Psf/vCHlEolfvKTnzQ9QzR2lP00MUeqjkrdT5C2o+ynN7Kf7KeJOewn/wwVhf1kP03MYT+1Vz+11KHUPffcw2//9m+ze/dujhw5Uvj8D33oQxw9epSjR4/y/e9/n87OTlauXFlohueee47rr7+eH/zgB3zxi19k//79fO973+P9738/t99+eyEZRq7Dc889xyOPPML73/9+Pv3pT7Ny5UrOnDlTaIbxH9/85jcLmT1Vjquuuqrpc//5n/+Z6667jr/8y7/kC1/4Av/zf/5P/uZv/oZ//+//PTt27GDnzp1Nz6A3aveOsp/emCNlR6XqJ7CjIrKf7KeJOewn+ykK+8l+mpjDfmqvfupMHaBSJ06c4Nvf/jZPPfUUL7zwAtu3b+c//sf/WGiGrq4uLr/8cgAuv/xyPvOZz/De976Xl156idmzZxeS4ZOf/CSlUoknnniCSy65ZPTfv/3tb+cTn/hEIRnGX4ef+Zmf4R3veAc33HADH/jAB9i+fTu/8Ru/UWiGlFLl+OQnP0lnZydPPfXUWfvgLW95Cx/5yEfwTTWLZ0fZT+fKkUrKDHZULPaT/XSuHKnYTxphP9lP58qRiv1UvJZ5ptR3vvMdrr76ahYtWsTHPvYxvva1ryVdlBMnTnDvvfeyYMECLr300kJm/r//9//43ve+x+23337WJh3xpje9qZAck/nFX/xFrr32Wv7sz/4sWYZ28X//7//lL//yL8+5DwBKpVLBqdTuHWU/aYQdFY/9ZD8pZz/FYz/ZT8q1cz+1zKHUPffcw8c+9jEgf0rdwMAAu3btKjTDjh07mDlzJjNnzqS7u5sHH3yQb3/725TLxVzGgwcPkmUZV199dSHzqnX11Vfz3HPPFTJr/FqMfHzhC18oZPb5cqxevbrpM0f2waJFi8769z/1Uz81muM//If/0PQcMPk6rFixopDZ0bR7R9lPZ4vQUSn6CeJ0lP00xn6yn8azn9L3E9hRI+wn+2k8+6k9+6klfn3vwIEDPPHEEzzwwAMAdHZ28q/+1b/innvu4aabbiosx/vf/37uvvtuAI4dO8Yf//Efs2LFCp544gmuvPLKps+P/nS9LMsKO70dvxYj3vzmNxcy+3w5znWqXYQnnniC4eFh1qxZw6lTpwqZOdk6PP7446N/uGgXdpT9NFGEjorUT1B8R9lPOfvJfprIfnoj/wyVhv1kP01kP71RO/RTSxxK3XPPPZw5c4a5c+eO/rssy+jq6uLLX/4yvb29heS45JJLWLBgweg//+mf/im9vb189atf5fd///ebPn/hwoWUSiX+4R/+oemzavGjH/2osBeBm7gWqaTIsWDBAkqlEgcOHDjr37/lLW8B4KKLLiosy2T//x8+fLiw+VHYUfbTRBE6KlWGKB1lP+XsJ/tpIvspfT+BHQX2E9hPE9lP7dlP4X9978yZM/yP//E/2LJlC88888zox7PPPsvcuXOTvOPaiFKpRLlc5pVXXilk3pvf/Gb+xb/4F3zlK1/h5MmTb/h6yreP/cEPfsD+/fv5lV/5lWQZ2sWll17K8uXL+fKXvzzpPlCx7Kic/aQRdlQc9lPOftII+ykO+ylnP2lEO/dT+GdK7dixg2PHjvHrv/7rbzgt/5Vf+RXuuece/t2/+3eFZDl16hQvvPACkD+188tf/jInTpxg1apVhcwH+MpXvsKNN97Iu9/9bv7Lf/kvLFmyhDNnzvDoo49y991386Mf/ajpGUauw9DQEP/n//wfvve977Fp0yZWrlzJr/3arzV9/vgM43V2dvJTP/VThcxP7Y//+I+58cYbeec738mdd97JkiVLKJfLPPnkk/zDP/wD119/feqIbcOOGmM/vTHHeHaUHVU0+2mM/fTGHOPZT/ZT0eynMfbTG3OMZz+1QT9lwa1cuTK75ZZbJv3a448/ngHZs88+2/QcH//4xzNg9KO7uzt717velX33u99t+uyJjhw5kt1+++3ZlVdemV1wwQXZz/zMz2S33npr9ld/9VdNnz3+OnR2dmazZ8/Obr755uxrX/taNjQ01PT5EzOM/1i0aFEh88fn+MhHPlLozPGOHDmSfepTn8quuuqqbMaMGdnMmTOzd7/73dkXv/jF7OTJk02ff67////qr/4qA7Jjx441PUMEdtTZ2r2fJuZI1VGp+ynL0naU/ZSzn85mP9lPI/wzVHr209nsJ/tpRDv2UynLgr+6miRJkiRJkqad8K8pJUmSJEmSpOnHQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBWus+iBw8PDHDlyhO7ubkqlUtHjJQWUZRnHjx9n7ty5lMvpzsrtJ0mTidBR9pOkydhPkqKqtJ8KP5Q6cuQI8+fPL3qspBbQ39/PvHnzks23nySdT8qOsp8knY/9JCmqqfqp8EOp7u7u0c8vnlP0dHj5BSADSnDx5cXPN4MZomVIPR/g5aP5/x3fDymk7icIsh7uSTOY4ewMATrKfjJDlPlmCJbBfgKCrIUZzBBkfpgMFfZT4YdSI0/pvHgOfOxI0dPhvnlw8sdwyVxYc7j4+WYwQ7QMqecD3Ds3L63UT/lO3U8QYz1SZ0g93wxmmChCR9lPZogy3wyxMthPuQhrYQYzRJkfJUOl/eQLnUuSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXBVH0rt3r2bVatWMXfuXEqlEn/+53/ehFiSVD37SVJU9pOkqOwnSSlVfSh18uRJrr32Wr7yla80I48k1cx+khSV/SQpKvtJUkqd1T5gxYoVrFixohlZJKku9pOkqOwnSVHZT5JS8jWlJEmSJEmSVLiqnylVrVOnTnHq1KnRfx4cHGz2SEmqiP0kKSr7SVJU9pOkRmr6M6U2bdpEb2/v6Mf8+fObPVKSKmI/SYrKfpIUlf0kqZGafii1ceNGBgYGRj/6+/ubPVKSKmI/SYrKfpIUlf0kqZGa/ut7XV1ddHV1NXuMJFXNfpIUlf0kKSr7SVIjVX0odeLECQ4ePDj6z//7f/9vnnnmGd785jdzxRVXNDScJFXDfpIUlf0kKSr7SVJKVR9KPfXUU7z//e8f/ed169YB8PGPf5zt27c3LJgkVct+khSV/SQpKvtJUkpVH0rddNNNZFnWjCySVBf7SVJU9pOkqOwnSSk1/YXOJUmSJEmSpIk8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4UpZlmVFDhwcHKS3txdKcMncIifnXj4K2TCUynDxnOLnm8EM0TKkng9w8giQwcDAAD09PWlCkL6fIMZ6pM6Qer4ZzDBRhI6yn8wQZb4ZYmWwn3IR1sIMZogyP0qGSvsp3aGUJE0Q5lBKkiYR4j/6JGkS9pOkqKbqp84Cs5zNZ0qZwQwhMqSeD2On6GH4N31tvyfNYIbxQnWU/dT2GVLPN0OsDPZTLsJamMEMUeZHyVBpPyU7lLr4clhzuPi5982Dkz/OFybFfDOYIVqG1PMB7p2bF2cUqfoJYqxH6gyp55vBDBNF6ij7yQyp55shVgb7KRdhLcxghijzo2SotJ98oXNJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVLt2771XpxCE4sB0G+uD0cZjRDb0LYdFamHlFMRlmMZ+lrOUyFnIh3bzKcV6kj71s5xj9xYRQCO5Hjed+UCTuR02Uek+knh8lg3IR1sKOiiPCfkidIfV8jYmwFu3YT+EPpY7sgn1b4NCO/O0MAbIhKHXknz99J1y5EpZsgDnLmpNhIctYznoWs5KMYQDKlBl+/fOV3Mk+HmInW+hjT3NCKAT3o8ZzPygS96MmSr0nUs+PkkG5CGthR8URYT+kzpB6vsZEWIt27qewv76XZfDsZthxE/Q/AmT5xsiGXv/6yOcZHHoEHnpfvpGyrLE5lrOeDeziGlZQpkwHnXTQSWnc52XKLOYWNrCbm1nX2AAKwf2o8dwPisT9qIlS74nU86NkUC7KWthRMUTYD6kzpJ6vMVHWot37Keyh1P6t8Pgd+efZmfN/78jXH9uQP65RbmYdH2UzAB3MOO/3jnx9NVum3SaR+1Fncz8oEvejJkq9J1LPj5JBuQhrYUfFEWE/pM6Qer7GRFgL+ynoodSRXfli1+KxDXB0d/0ZFrKM1Wyp6bGr2cJC3lt/CIXgftR47gdF4n7URKn3ROr5UTIoF2Et7Kg4IuyH1BlSz9eYCGthP+WqOpTatGkT73rXu+ju7uayyy7jl37plzhw4EDDQ+3bAqUaX+2q1Jk/vl7LWc8Qp2t67BCnp9XJZbtzP7YG+6ky7bIf2oX7sXW0S0elnh8lg3IR1sKOmlq79FOEDKnna0yEtbCfclUdSu3atYvbb7+dxx57jEcffZTTp0/zwQ9+kJMnTzYs0IlD+QuMTfX0uXPJzsDzD8GJOl6YfhbzWczKKZ8+dy4dzGAJtzKLebWHUAjux9ZhP1WmXfZDO3A/tpZ26KjU86NkUC7CWthRlWmHfoqQIfV8jYmwFvbTmKoOpb73ve+xdu1a3v72t3Pttdeyfft2Dh06xNNPP92wQAe2j73ifa1KZTiwrfbHL2Xt6Cve1ypjmKXcVtfPUHrux9ZhP1WuHfZDO3A/tpZ26KjU86NkUC7CWthRlWmHfoqQIfV8jYmwFvbTmBqfsJYbGBgA4M1vfvM5v+fUqVOcOnVq9J8HBwfP/zP76kk0ZvBg7Y+9jIUNSJAxmwUN+DlKyf3Yuuyn82m//TAduR9b21QdVW0/Qfo9kXp+lAzKRVgLO6o207GfImRIPV9jIqyF/TSm5vPB4eFhfvd3f5cbb7yRa6655pzft2nTJnp7e0c/5s+ff96fe/r42Fsw1iobgtem7sZzupBuynW+BnyZDi6ip66fofTcj63Jfjq/dtsP05X7sXVV0lHV9hOk3xOp50fJoFyEtbCjqjdd+ylChtTzNSbCWthPY2q+Crfffjt/93d/x7e+9a3zft/GjRsZGBgY/ejvP/8vXs7ohlJHralypQ64oI61eZXjDNf5VLphhngFG6PVuR9bk/10fu22H6Yr92PrqqSjqu0nSL8nUs+PkkG5CGthR1VvuvZThAyp52tMhLWwn8bU9Ot7n/rUp9ixYwe7d+9m3rzzv7BWV1cXXV1dFf/s3kY8iw3oqeNZbC/SiOfzlXgJn1vZ6tyPrcd+qkT77IfpzP3YmirtqGr7CdLvidTzo2RQLsJa2FHVmc79FCFD6vkaE2Et7KcxVT1TKssyPvWpT/HAAw/wgx/8gKuuuqrhgRathay+A0OyYVhUx+t97WU7pTqfSleizF58FbpW535sHfZT5dphP7QD92NraYeOSj0/SgblIqyFHVWZduinCBlSz9eYCGthP42p6ircfvvt3HvvvXzjG9+gu7ubF154gRdeeIFXXnmlYYFmXgFXrIRSjS/BXuqEK1fBzKl/tfmcjtHPfnYwxOmaHj/EafbxIMc4XHsIheB+bB32U2XaZT+0A/dja2mHjko9P0oG5SKshR1VmXbopwgZUs/XmAhrYT+NqepQ6u6772ZgYICbbrqJOXPmjH58+9vfbmioazdAdqa2x2ZDsGR9/RkeZTMdzKjpsWU62MnW+kMoBPdja7CfKtMu+6FduB9bR7t0VOr5UTIoF2Et7KiptUs/RciQer7GRFgL+ylX9a/vTfaxdu3ahoaaswxu2FzbY2/4Yv74evWxh/upbad9lzvoY0/9IRSC+7E12E+VaZf90C7cj62jXToq9fwoGZSLsBZ21NTapZ8iZEg9X2MirIX9lKvvlxibaPG6sU0y1dPqRr5+w+b8cY2yk62jm2Sqp9WNfP1+1k+bE0uNcT9qPPeDInE/aqLUeyL1/CgZlIuwFnZUHBH2Q+oMqedrTIS1sJ8CH0qVSvlT4lbtgituAUr52y6OvHXj6Oel/OurduXfXyo1NsdOtrKZZeznYYYZZogzDHGGjGGGOM0QZxhmmP08zGaWTavNoTHuR43nflAk7kdNlHpPpJ4fJYNyUdbCjoohwn5InSH1fI2Jshbt3k81vrRXceYsyz9O9MOBbTB4EF4bhAt68rdgXHRb81/srY899LGHWcxjKbcxmwVcRA+vMMhLHGQv26bFC4xpau5Hjed+UCTuR02Uek+knh8lg3IR1sKOiiPCfkidIfV8jYmwFu3cT+EPpUbMnA/XfzZthmMc5mHuShtCIbgfNZ77QZG4HzVR6j2Ren6UDMpFWAs7Ko4I+yF1htTzNSbCWrRjP4X99T1JkiRJkiRNXx5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXClLMuyIgcODg7S29sLJbhkbpGTcy8fhWwYSmW4eE7x881ghmgZUs8HOHkEyGBgYICenp40IUjfTxBjPVJnSD3fDGaYKEJH2U9miDLfDLEy2E+5CGthBjNEmR8lQ6X9lO5QSpImCHMoJUmTCPEffZI0CftJUlRT9VNngVnO5jOlzGCGEBlSz4exU/Qw/Ju+tt+TZjDDeKE6yn5q+wyp55shVgb7KRdhLcxghijzo2SotJ+SHUpdfDmsOVz83Pvmwckf5wuTYr4ZzBAtQ+r5APfOzYszilT9BDHWI3WG1PPNYIaJInWU/WSG1PPNECuD/ZSLsBZmMEOU+VEyVNpPvtC5JEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCpfu3fda0IlDcGA7DPTB6eMwoxt6F8KitTDzCjMUmUGuQySzmM9S1nIZC7mQbl7lOC/Sx162c4z+QjJE2A9m0AjXIZbUHRVhP5hB47kWcaTuJ0i/H1LPj5JBuXZcCw+lKnBkF+zbAod25G+pCJANQakj//zpO+HKlbBkA8xZZoZmZpDrEMlClrGc9SxmJRnDAJQpM/z65yu5k308xE620MeepmSIsB/MoBGuQyypOyrCfjCDxnMt4kjdT5B+P6SeHyWDcu28Fv763nlkGTy7GXbcBP2PAFm+MbKh178+8nkGhx6Bh96Xb6QsM0OjM8h1iGY569nALq5hBWXKdNBJB52Uxn1epsxibmEDu7mZdQ2dH2E/mEEjXId4UnZUhP1gBo3nWsTS7n+GSj0/SgblXAsPpc5r/1Z4/I788+zM+b935OuPbcgfZ4bGZpDrEMnNrOOjbAaggxnn/d6Rr69mS0P/UBVhP5hBI1yHWFJ3VIT9YAaN51rEkbqfIP1+SD0/SgblXIsqD6XuvvtulixZQk9PDz09PbznPe/hkUceaVa2pI7syhe7Fo9tgKO7zdCoDHIdKlFUPy1kGavZUtNjV7OFhby37gwR9oMZNMJ1qEy7dFSE/WAGjedaTK1d+gnS74fU86NkUM61yFV1KDVv3jz+4A/+gKeffpqnnnqKX/zFX+QjH/kI/+t//a9m5Utm3xYo1fiKW6XO/PFmaEwGuQ6VKKqflrOeIU7X9NghTjfkb/oi7AczaITrUJl26agI+8EMGs+1mFq79BOk3w+p50fJoJxrkavqUGrVqlXccsstLFy4kLe97W18/vOfZ+bMmTz22GPNypfEiUP5C4xN9fS5c8nOwPMPwYk63jDCDBrhOlSmiH6axXwWs3LKp5ufSwczWMKtzGJezRki7AczaITrULl26KgI+8EMGs+1qEw79BOk3w+p50fJoJxrMabm15QaGhriW9/6FidPnuQ973lPIzMld2D72Cve16pUhgPbzFBvBrkOtWhWPy1l7eg7xNQqY5il3Fbz4yPsBzNohOtQm+naURH2gxk0nmtRvenaT5B+P6SeHyWDcq7FmKqfLLZ//37e85738OqrrzJz5kweeOABfv7nf/6c33/q1ClOnTo1+s+Dg4O1JS3QQF9jfs7gQTPUm0GuQzWa3U+XsbABKTNms6DmR0fYD2bQCNehOtV0VC1/fkrdURH2gxk0nmtRueneT5B+P6SeHyWDcq7FmKrP5hYtWsQzzzzD448/zm/91m/x8Y9/nL//+78/5/dv2rSJ3t7e0Y/58+fXFbgIp4+PvQVjrbIheK2O8zczaITrULlm99OFdFOu801Ly3RwET01Pz7CfjCDRrgO1ammo2r581PqjoqwH8yg8VyLyk33foL0+yH1/CgZlHMtxlTdDBdccAELFizg+uuvZ9OmTVx77bX80R/90Tm/f+PGjQwMDIx+9PfH/6XHGd1Q6qjvZ5Q64ILaO9MMGuU6VK7Z/fQqxxmu86nnwwzxCrX/r0eE/WAGjXAdqlNNR9Xy56fUHRVhP5hB47kWlZvu/QTp90Pq+VEyKOdajKnxtd7HDA8Pn/X0zYm6urro6uqqd0yhehvx7FKgp/Znl5pBo1yH2jW6n16kEc+zLfEStT/PNsJ+MINGuA71OV9H1fLnp9QdFWE/mEHjuRa1m279BOn3Q+r5UTIo51qMqeqZUhs3bmT37t0899xz7N+/n40bN/LDH/6QNWvWNCtfEovWQlbfQT7ZMCyq/XX4zKBRrkNliuinvWynVOdTz0uU2Uvtr0gYYT+YQSNch8q1Q0dF2A9m0HiuRWXaoZ8g/X5IPT9KBuVcizFVNcOLL77Ir/3ar7Fo0SI+8IEP8OSTT/IXf/EXLF++vFn5kph5BVyxEko1Po+s1AlXroKZdbx8lhk0wnWoTBH9dIx+9rODIU7X9PghTrOPBznG4ZozRNgPZtAI16Fy7dBREfaDGTSea1GZdugnSL8fUs+PkkE512JMVZfgnnvuaVaOcK7dAIcequ2x2RAsWW+GRmWQ61CJovrpUTZzLbfW9NgyHexka90ZIuwHM2iE61CZdumoCPvBDBrPtZhau/QTpN8PqedHyaCca5Gr7zmU09icZXDD5toee8MX88eboTEZ5DpE0sce7qe2/wX4LnfQx566M0TYD2bQCNchltQdFWE/mEHjuRZxpO4nSL8fUs+PkkE51yLnodR5LF43tkmmelrdyNdv2Jw/zgyNzSDXIZKdbB39Q9VUT0Mf+fr9rG/I3/CNiLAfzKARrkMsqTsqwn4wg8ZzLeJI3U+Qfj+knh8lg3KuhYdS51Uq5U+JW7ULrrgFKOVvuzjy1o2jn5fyr6/alX9/qWSGRmeQ6xDNTraymWXs52GGGWaIMwxxhoxhhjjNEGcYZpj9PMxmljX0D1MQYz+YQSNch3hSdlSE/WAGjedaxNLuf4ZKPT9KBuVciypfU6pdzVmWf5zohwPbYPAgvDYIF/Tkb8G46Lbmv8CYGTTCdYijjz30sYdZzGMptzGbBVxED68wyEscZC/b6npBzkpE2A9m0AjXIZbUHRVhP5hB47kWcaTuJ0i/H1LPj5JBuXZeCw+lqjBzPlz/WTNEyCDXIZJjHOZh7kqaIcJ+MINGuA6xpO6oCPvBDBrPtYgjdT9B+v2Qen6UDMq141r463uSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXCnLsqzIgYODg/T29kIJLplb5OTcy0chG4ZSGS6eU/x8M5ghWobU8wFOHgEyGBgYoKenJ00I0vcTxFiP1BlSzzeDGSaK0FH2kxmizDdDrAz2Uy7CWpjBDFHmR8lQaT+lO5SSpAnCHEpJ0iRC/EefJE3CfpIU1VT91FlglrP5TCkzmCFEhtTzYewUPQz/pq/t96QZzDBeqI6yn9o+Q+r5ZoiVwX7KRVgLM5ghyvwoGSrtp2SHUhdfDmsOFz/3vnlw8sf5wqSYbwYzRMuQej7AvXPz4owiVT9BjPVInSH1fDOYYaJIHWU/mSH1fDPEymA/5SKshRnMEGV+lAyV9pMvdC5JkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTCpXv3vSqdOAQHtsNAH5w+DjO6oXchLFoLM68wQztlSD3fDLEyRBDhOsxiPktZy2Us5EK6eZXjvEgfe9nOMfoLyRDhOpgh/XwzxJP6WthPZjBDrPmRROiH1Bki7AczmCFlhvCHUkd2wb4tcGhH/naGANkQlDryz5++E65cCUs2wJxlZpjOGVLPN0OsDBFEuA4LWcZy1rOYlWQMA1CmzPDrn6/kTvbxEDvZQh97mpIhwnUwQ/r5Zogn9bWwn8xghljzI4nQD6kzRNgPZjBDhAxhf30vy+DZzbDjJuh/BMjyC5INvf71kc8zOPQIPPS+/AJmmRmmW4bU880QK0MEUa7DctazgV1cwwrKlOmgkw46KY37vEyZxdzCBnZzM+saOj/CdTBD+vlmiCfCtbCfzGCGOPOjSd0PqTNE2A9mMEOkDGEPpfZvhcfvyD/Pzpz/e0e+/tiG/HFmmF4ZUs83Q6wMEUS4Djezjo+yGYAOZpz3e0e+vpotDf1DVYTrYIb0880QT+prYT+ZwQyx5kcSoR9SZ4iwH8xghkgZQh5KHdmV/z9Zi8c2wNHdZpguGVLPN0OsDBFEuA4LWcZqttT02NVsYSHvrTtDhOtghvTzzRBP6mthP5nBDLHmRxKhH1JniLAfzGCGaBnqOpT6gz/4A0qlEr/7u79bf5Jx9m2BUmdtjy115o83w/TIkHq+GWJlqMZ07qflrGeI0zU9dojTDfmbvgjXwQzp55uhNs3qJ0h/LewnM5gh1vxaNKujIvRD6gwR9oMZzBAtQ82HUk8++ST//b//d5YsWVJ/inFOHMpfWGuqp42dS3YGnn8ITtTxRglmiJEh9XwzxMpQjencT7OYz2JWTvl083PpYAZLuJVZzKs5Q4TrYIb0881Qm2b1E6S/FvaTGcwQa34tmtVREfohdYYI+8EMZoiWAWo8lDpx4gRr1qzhq1/9KrNmzaovwQQHto+90nutSmU4sM0MrZ4h9XwzxMpQqeneT0tZO/oOMbXKGGYpt9X8+AjXwQzp55uhes3sJ0h/LewnM5gh1vxqNbOjIvRD6gwR9oMZzBAtA9R4KHX77bfz4Q9/mJtvvnnK7z116hSDg4NnfZzPQF8tid5o8GDtjzVDjAyp55shVoZKTfd+uoyFDUiQMZsFNT86wnUwQ/r5ZqheM/sJ0l8L+8kMZog1v1qVdlQt/RShH1JniLAfzGCGaBkAqv7twW9961v87d/+LU8++WRF379p0yY+97nPVfzzTx9n9K0Ha5UNwWtTd6MZgmdIPd8MsTJUoh366UK6Kdf5HhVlOriInpofH+E6mCH9fDNUp9n9BOmvhf1kBjPEml+Najqqln6K0A+pM0TYD2YwQ7QMUOUzpfr7+/n0pz/Nfffdx4UXXljRYzZu3MjAwMDoR3//+X/hcEY3lDqqSfVGpQ64oPa+MkOQDKnnmyFWhqm0Sz+9ynGG63zq+TBDvELt/+sR4TqYIf18M1SuiH6C9NfCfjKDGWLNr1S1HVVLP0Xoh9QZIuwHM5ghWgao8plSTz/9NC+++CLveMc7Rv/d0NAQu3fv5stf/jKnTp2io+Ps/6+6urro6uqqeEZvI55VCfTU/sxOMwTJkHq+GWJlmEq79NOLNOJ5tiVeovbn2Ua4DmZIP98MlSuinyD9tbCfzGCGWPMrVW1H1dJPEfohdYYI+8EMZoiWAap8ptQHPvAB9u/fzzPPPDP68c53vpM1a9bwzDPPvOEPVLVYtBay+g6wyYZhUe2vgWeGIBlSzzdDrAxTaZd+2st2SnU+9bxEmb3U/oqEEa6DGdLPN0PliugnSH8t7CczmCHW/EoV0VER+iF1hgj7wQxmiJYBqjyU6u7u5pprrjnr45JLLuHSSy/lmmuuqS/J62ZeAVeshFLVr3aVK3XClatg5nwztHqG1PPNECvDVNqln47Rz352MMTpmh4/xGn28SDHOFxzhgjXwQzp55uhckX0E6S/FvaTGcwQa36liuioCP2QOkOE/WAGM0TLADW++16zXbsBsjO1PTYbgiXrzTBdMqSeb4ZYGSKIcB0eZTMdzKjpsWU62MnWujNEuA5mSD/fDPGkvhb2kxnMEGt+JBH6IXWGCPvBDGaIlqHuQ6kf/vCHfOlLX6o/yThzlsENm2t77A1fzB9vhumRIfV8M8TKUK3p2k997OF+avtfgO9yB33sqTtDhOtghvTzzVC7ZvQTpL8W9pMZzBBrfq2a0VER+iF1hgj7wQxmiJYh5DOlABavG7s4Uz2dbOTrN2zOH2eG6ZUh9XwzxMoQQYTrsJOto3+omupp6CNfv5/1DflbxhERroMZ0s83Qzypr4X9ZAYzxJofSYR+SJ0hwn4wgxkiZQh7KFUq5U8FW7ULrrgFKOVvNzjyloWjn5fyr6/alX9/qWSG6ZYh9XwzxMoQQZTrsJOtbGYZ+3mYYYYZ4gxDnCFjmCFOM8QZhhlmPw+zmWUN/QMdxLgOZkg/3wzxRLgW9pMZzBBnfjSp+yF1hgj7wQxmiJShxpe0Ks6cZfnHiX44sA0GD8Jrg3BBT/7Wg4tua/6L/5khRobU880QK0MEEa5DH3voYw+zmMdSbmM2C7iIHl5hkJc4yF621fWioJWIcB3MkH6+GeJJfS3sJzOYIdb8SCL0Q+oMEfaDGcwQIUP4Q6kRM+fD9Z81gxnSzzdDrAwRRLgOxzjMw9yVNEOE62CG9PPNEE/qa2E/mcEMseZHEqEfUmeIsB/MYIaUGcL++p4kSZIkSZKmLw+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLhSlmVZkQMHBwfp7e2FElwyt8jJuZePQjYMpTJcPKf4+WYwQ7QMqecDnDwCZDAwMEBPT0+aEKTvJ4ixHqkzpJ5vBjNMFKGj7CczRJlvhlgZ7KdchLUwgxmizI+SodJ+SncoJUkThDmUkqRJhPiPPkmahP0kKaqp+qmzwCxn85lSZjBDiAyp58PYKXoY/k1f2+9JM5hhvFAdZT+1fYbU880QK4P9lIuwFmYwQ5T5UTJU2k/JDqUuvhzWHC5+7n3z4OSP84VJMd8MZoiWIfV8gHvn5sUZRap+ghjrkTpD6vlmMMNEkTrKfjJD6vlmiJXBfspFWAszmCHK/CgZKu0nX+hckiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhUv37nst6MQhOLAdBvrg9HGY0Q29C2HRWph5hRmKyjCL+SxlLZexkAvp5lWO8yJ97GU7x+hvfgApoNT3JcS4N70OUjzelzmvg/RGEfZk6gyp54P9pLQ8lKrAkV2wbwsc2pG/pSJANgSljvzzp++EK1fCkg0wZ5kZmpVhIctYznoWs5KMYQDKlBl+/fOV3Mk+HmInW+hjT+MDSAGlvi8hxr3pdZDi8b7MeR2kN4qwJ1NnSD0f7CfF4K/vnUeWwbObYcdN0P8IkOU3aTb0+tdHPs/g0CPw0PvymzrLzNDoDMtZzwZ2cQ0rKFOmg0466KQ07vMyZRZzCxvYzc2sa9xwKaAI9yWkvze9DlI83pc5r4M0uQh7MnWG1PPtJ0XiodR57N8Kj9+Rf56dOf/3jnz9sQ3548zQuAw3s46PshmADmac93tHvr6aLZaWprXU9yXEuDe9DlI83pc5r4P0RhH2ZOoMqeeD/aRYqjqUuvPOOymVSmd9XH311c3KltSRXfmNV4vHNsDR3WZoRIaFLGM1W2p67Gq2sJD31hdALcN+qkyjuiHCvel1UCtpl47yvsx5HdRKiuqnCHsydYbU88F+UjxVP1Pq7W9/O0ePHh39+Ou//utm5Epu3xYo1fiKW6XO/PFmqD/DctYzxOmaHjvEaU/S24z9NLVGdUOEe9ProFbTDh3lfZnzOqjVFNFPEfZk6gyp54P9pHiq3o6dnZ1cfvnlzcgSxolD+Yu9UePvzGZn4PmH4EQ/zJxvhlozzGI+i1lJucbfMu1gBku4lVnM4xiHa/oZai3209Qa0Q0R7k2vg1rRdO8o78uc10GtqNn9FGFPps6Qej7YT4qp6p3Q19fH3Llzectb3sKaNWs4dOhQM3IldWD72LsP1KpUhgPbzFBPhqWsHX0HhlplDLOU2+r6GWod9lNl6u2GCPem10GtaLp3lPdlzuugVtTsfoqwJ1NnSD0f7CfFVNUzpX7hF36B7du3s2jRIo4ePcrnPvc53vve9/J3f/d3dHd3T/qYU6dOcerUqdF/HhwcrC9xAQb6GvNzBg+aoZ4Ml7GwAdMzZrOgAT9H0dlP1amnGyLcm14HtZpqO8p+qk2E+9LroFZTRD9F2JOpM6SeD/aTYqrqUGrFihWjny9ZsoRf+IVf4Morr+Q73/kOv/7rvz7pYzZt2sTnPve5+lIW7PTxsbfDrFU2BK/V8edHM8CFdNf8tM4RZTq4iJ66foZag/1UuXq7IcK96XVQq6m2o+yn2kS4L70OajVF9FOEPZk6Q+r5YD8pprp2w5ve9Cbe9ra3cfDguY9KN27cyMDAwOhHf39/PSMLMaMbSh31/YxSB1xQx31iBniV4wzX+dTOYYZ4hfh/u6zGs5/Ord5uiHBveh3U6qbqKPupNhHuS6+DWl0z+inCnkydIfV8sJ8UU12HUidOnOCf/umfmDNnzjm/p6uri56enrM+outtxDMKgZ46nlFoBniRRjy/tMRL1PH8UrUs++n86umGCPem10GtbqqOsp9qE+G+9Dqo1TWjnyLsydQZUs8H+0kxVXUotWHDBnbt2sVzzz3H3r17+eVf/mU6Ojr41V/91WblS2LRWsjqO7wlG4ZFdbz2mhlgL9sp1fnUzhJl9lLHK/GpZdhPlau3GyLcm14HtZp26Cjvy5zXQa2miH6KsCdTZ0g9H+wnxVTVbjh8+DC/+qu/yqJFi/iX//Jfcumll/LYY48xe/bsZuVLYuYVcMVKKFX1iltjSp1w5ara3ybTDLlj9LOfHQxxuqbHD3GafTzoW4W2CfupMo3ohgj3ptdBraYdOsr7Mud1UKspop8i7MnUGVLPB/tJMVW1Hb/1rW81K0c4126AQw/V9thsCJasN0MjMjzKZq7l1poeW6aDnWytL4Bahv1UmUZ1Q4R70+ugVtIuHeV9mfM6qJUU1U8R9mTqDKnng/2keOp73tw0NmcZ3LC5tsfe8MX88WaoP0Mfe7if2prvu9xBH3vqCyAFlPq+hBj3ptdBisf7Mud1kN4owp5MnSH1fLCfFI+HUuexeN3YDTvVUxxHvn7D5vxxZmhchp1sHS2tqZ7mOfL1+1nvCbqmtdT3JcS4N70OUjzelzmvg/RGEfZk6gyp54P9pFg8lDqPUil/euKqXXDFLUApfwvMkbfRHP28lH991a78+0slMzQ6w062spll7OdhhhlmiDMMcYaMYYY4zRBnGGaY/TzMZpZZVpr2ItyXkP7e9DpI8Xhf5rwO0uQi7MnUGVLPt58USY0vcdZe5izLP070w4FtMHgQXhuEC3ryt8NcdFt9L/Zmhsr0sYc+9jCLeSzlNmazgIvo4RUGeYmD7GWbL3intpP6voQY96bXQYrH+zLndZDeKMKeTJ0h9XywnxSDh1JVmDkfrv+sGVJnOMZhHuaudAGkgFLflxDj3vQ6SPF4X+a8DtIbRdiTqTOkng/2k9Ly1/ckSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuFKWZVmRAwcHB+nt7YUSXDK3yMm5l49CNgylMlw8p/j5ZjBDtAyp5wOcPAJkMDAwQE9PT5oQpO8niLEeqTOknm8GM0wUoaPsJzNEmW+GWBnsp1yEtTCDGaLMj5Kh0n5KdyglSROEOZSSpEmE+I8+SZqE/SQpqqn6qbPALGfzmVJmMEOIDKnnw9gpehj+TV/b70kzmGG8UB1lP7V9htTzzRArg/2Ui7AWZjBDlPlRMlTaT8kOpS6+HNYcLn7uffPg5I/zhUkx3wxmiJYh9XyAe+fmxRlFqn6CGOuROkPq+WYww0SROsp+MkPq+WaIlcF+ykVYCzOYIcr8KBkq7Sdf6FySJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmFS/fue2pZs5jPUtZyGQu5kG5e5Tgv0sdetnOM/qbPP3EIDmyHgT44fRxmdEPvQli0FmZe0fTxQPprYAZpchH2ZOqOinANzCC9UYQ9mbqfIMZ1SJ0h9Xxpogh70n5q3wweSqliC1nGctazmJVkDANQpszw65+v5E728RA72UIfexo+/8gu2LcFDu3I39oSIBuCUkf++dN3wpUrYckGmLOs4eOB9NfADNLkIuzJ1B0V4RqYQXqjCHsydT9BjOuQOkPq+dJEEfak/WQGf31PFVnOejawi2tYQZkyHXTSQSelcZ+XKbOYW9jAbm5mXcNmZxk8uxl23AT9jwBZXlTZ0OtfH/k8g0OPwEPvy4styxoWAUh7DcwgnVvqPRmho1JfAzNIk0u9JyP0E6S/DhEypJ4vTZR6T9pPZhjhoZSmdDPr+CibAehgxnm/d+Trq9nSsI26fys8fkf+eXbm/N878vXHNuSPa5TU18AM0uQi7MnUHRXhGphBeqMIezJ1P0GM65A6Q+r50kQR9qT9ZIYRHkrpvBayjNVsqemxq9nCQt5b1/wju/LyqcVjG+Do7rrGA+mvgRmkyUXYk6k7KsI1MIP0RhH2ZOp+ghjXIXWG1POliSLsSfvJDONVfSj14x//mI997GNceumlXHTRRSxevJinnnqq7iCKaTnrGeJ0TY8d4nTdp6f7tkCpxlc+K3Xmj69X6mtghsrZT+0lwp5M3VERroEZKmdHtY8IezJ1P0GM65A6Q+r5lbKf2keEPWk/mWG8qg6ljh07xo033siMGTN45JFH+Pu//3u2bNnCrFmz6g6ieGYxn8WsnPIpfOfSwQyWcCuzmFfT408cyl/wbqqnc55LdgaefwhO1PEGAamvgRkqZz+1lwh7MnVHRbgGZqicHdU+IuzJ1P0EMa5D6gyp51fKfmofEfak/WSGiao6lPrDP/xD5s+fz7Zt23j3u9/NVVddxQc/+EHe+ta31hVCMS1l7eir7tcqY5il3FbTYw9sH3sHhlqVynBgW+2PT30NzFA5+6m9RNiTqTsqwjUwQ+XsqPYRYU+m7ieIcR1SZ0g9v1L2U/uIsCftJzNMVNV2ePDBB3nnO9/J6tWrueyyy7juuuv46le/et7HnDp1isHBwbM+1BouY2EDfkrGbBbU9MiBvgaMBwYP1v7Y1NfADJWzn9pLhD2ZuqMiXAMzVK7ajrKfWleEPZm6nyDGdUidIfX8StlP7SPCnrSfzDBRVYdS//zP/8zdd9/NwoUL+Yu/+At+67d+i9/5nd/h61//+jkfs2nTJnp7e0c/5s+fX1dgFedCuinX+Vr4ZTq4iJ6aHnv6+NhbgtYqG4LX6vjfydTXwAyVs5/aS4Q9mbqjIlwDM1Su2o6yn1pXhD2Zup8gxnVInSH1/ErZT+0jwp60n8zwxp9RheHhYd7xjnfwhS98geuuu45/82/+Db/5m7/Jf/tv/+2cj9m4cSMDAwOjH/39dfzypwr1KscZrvPpfMMM8Qq1NcaMbih11DWeUgdcUMc9kvoamKGKn28/tZUIezJ1R0W4BmaoYkaVHWU/ta4IezJ1P0GM65A6Q+r5Fc+wn9pGhD1pP5lhoqoOpebMmcPP//zPn/Xvfu7nfo5Dhw6d8zFdXV309PSc9aHW8CKNeG5liZeo7bmVvY14NiHQU8ezCVNfAzNUzn5qLxH2ZOqOinANzFC5ajvKfmpdEfZk6n6CGNchdYbU8ytlP7WPCHvSfjLDRFUdSt14440cOHDgrH/3j//4j1x55ZV1hVBMe9lOqc6n85Uos5faXoVu0VrI6ju4JRuGRXW87lrqa2CGytlP7SXCnkzdURGugRkqZ0e1jwh7MnU/QYzrkDpD6vmVsp/aR4Q9aT+ZYaKqEvze7/0ejz32GF/4whc4ePAg3/jGN/iTP/kTbr/99rpCKKZj9LOfHQxxuqbHD3GafTzIMQ7X9PiZV8AVK6HUWdPDKXXClatgZh2/5p76GpihcvZTe4mwJ1N3VIRrYIbK2VHtI8KeTN1PEOM6pM6Qen6l7Kf2EWFP2k9mmKiqQ6l3vetdPPDAA3zzm9/kmmuu4a677uJLX/oSa9asqSuE4nqUzXQwo6bHlulgJ1vrmn/tBsjO1PbYbAiWrK9rPJD+GpihMvZT+4mwJ1N3VIRrYIbK2FHtJcKeTN1PEOM6pM6Qen4l7Kf2EmFP2k9mOPvnVGnlypXs37+fV199lR/96Ef85m/+Zt0hFFcfe7if2u7673IHfeypa/6cZXDD5toee8MX88fXK/U1MEPl7Kf2EmFPpu6oCNfADJWzo9pHhD2Zup8gxnVInSH1/ErZT+0jwp60n8wwXn2/QKi2sJOtoxt1qqf2jXz9ftY37G92Fq8bK62pnuY58vUbNuePa5TU18AM0uQi7MnUHRXhGphBeqMIezJ1P0GM65A6Q+r50kQR9qT9ZIYRNf4mp9rNTrbyPE9yM+tYwq1kr791ZJkywwwBJUqU2c/D7GRrQ/9Wp1TKn6I5+12wbws8/xCUXj9OzYbG3lI0G4Yrbsm/txGn5xOlvAZmkM4t9Z6M0FGpr4EZpMml3pMR+gnSX4cIGVLPlyZKvSftJzOM8FBKFetjD33sYRbzWMptzGYBF9HDKwzyEgfZy7amvhDjnGX5x4l+OLANBg/Ca4NwQU/+lqCLbqvvBe8qkfoamEGaXIQ9mbqjIlwDM0hvFGFPpu4niHEdUmdIPV+aKMKetJ/M4KGUqnaMwzzMXcnmz5wP13822Xgg/TUwgzS5CHsydUdFuAZmkN4owp5M3U8Q4zqkzpB6vjRRhD1pP7VvBl9TSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmFK2VZlhU5cHBwkN7eXijBJXOLnJx7+Shkw1Aqw8Vzip9vBjNEy5B6PsDJI0AGAwMD9PT0pAlB+n6CGOuROkPq+WYww0QROsp+MkOU+WaIlcF+ykVYCzOYIcr8KBkq7ad0h1KSNEGYQylJmkSI/+iTpEnYT5KimqqfOgvMcjafKWUGM4TIkHo+jJ2ih+Hf9LX9njSDGcYL1VH2U9tnSD3fDLEy2E+5CGthBjNEmR8lQ6X9lOxQ6uLLYc3h4ufeNw9O/jhfmBTzzWCGaBlSzwe4d25enFGk6ieIsR6pM6SebwYzTBSpo+wnM6Seb4ZYGeynXIS1MIMZosyPkqHSfvKFziVJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4dO++p5rMYj5LWctlLORCunmV47xIH3vZzjH62yJD6vlmkCYXYU+aIf38KBmk8SLsSTOYQZpMhP1oBjOk5KFUi1jIMpaznsWsJGMYgDJlhl//fCV3so+H2MkW+tgzLTOknm8GaXIR9qQZ0s+PkkEaL8KeNIMZpMlE2I9mMEME/vpeC1jOejawi2tYQZkyHXTSQSelcZ+XKbOYW9jAbm5m3bTLkHq+GaTJRdiTZkg/P0oGabwIe9IMZpAmE2E/msEMUXgoFdzNrOOjbAaggxnn/d6Rr69mS0M3auoMqeebQZpchD1phvTzo2SQxouwJ81gBmkyEfajGcwQSVWHUj/7sz9LqVR6w8ftt9/erHxtbSHLWM2Wmh67mi0s5L0tnyH1fDO0FjuqOBH2pBnSz4+SoRXYT8WJsCfNYIZWYj8VJ8J+NIMZoqnqUOrJJ5/k6NGjox+PPvooAKtXr25KuHa3nPUMcbqmxw5xuiGnp6kzpJ5vhtZiRxUnwp40Q/r5UTK0AvupOBH2pBnM0Ersp+JE2I9mMEM0VR1KzZ49m8svv3z0Y8eOHbz1rW/lfe97X7Pyta1ZzGcxK6d8Ct+5dDCDJdzKLOa1bIbU883QeuyoYkTYk2ZIPz9KhlZhPxUjwp40gxlajf1UjAj70QxmiKjm15R67bXXuPfee/nEJz5BqVRqZCYBS1k7+qr7tcoYZim3tWyG1PPN0NrsqOaJsCfNkH5+lAytyH5qngh70gxmaGX2U/NE2I9mMENEnbU+8M///M/5yU9+wtq1a8/7fadOneLUqVOj/zw4OFjryLZyGQsb8FMyZrOgZTOknm+G1lZJR9lPtYmwJ82Qfn6UDK3IfmqeCHvSDGZoZfZT80TYj2YwQ0Q1P1PqnnvuYcWKFcydO/e837dp0yZ6e3tHP+bPn1/ryLZyId2U63xzxDIdXERPy2ZIPd8Mra2SjrKfahNhT5oh/fwoGVqR/dQ8EfakGczQyuyn5omwH81ghohqugrPP/88O3fu5Dd+4zem/N6NGzcyMDAw+tHf31/LyLbzKscZrvPpfMMM8Qq1/81F6gyp55uhdVXaUfZTbSLsSTOknx8lQ6uxn5orwp40gxlalf3UXBH2oxnMEFFNv763bds2LrvsMj784Q9P+b1dXV10dXXVMqatvUhfA35KiZc42LIZUs83Q+uqtKPsp9pE2JNmSD8/SoZWYz81V4Q9aQYztCr7qbki7EczmCGiqp8pNTw8zLZt2/j4xz9OZ2fNL0mlKexlO6U6n85XosxetrVshtTzzdCa7Kjmi7AnzZB+fpQMrcR+ar4Ie9IMZmhF9lPzRdiPZjBDRFVfhZ07d3Lo0CE+8YlPNCOPXneMfvazgyFO1/T4IU6zjwc5xuGWzZB6vhlakx3VfBH2pBnSz4+SoZXYT80XYU+awQytyH5qvgj70QxmiKjqQ6kPfvCDZFnG2972tmbk0TiPspkOZtT02DId7GRry2dIPd8MrceOKkaEPWmG9POjZGgV9lMxIuxJM5ih1dhPxYiwH81ghmjqe76YmqqPPdzP+poe+13uoI89LZ8h9XwzSJOLsCfNkH5+lAzSeBH2pBnMIE0mwn40gxmi8VAquJ1sHd2oUz21b+Tr97O+oaemqTOknm8GaXIR9qQZ0s+PkkEaL8KeNIMZpMlE2I9mMEMkvopdC9jJVp7nSW5mHUu4lez1t44sU2aYIaBEiTL7eZidbG3KiWnqDKnnm0GaXIQ9aYb086NkkMaLsCfNYAZpMhH2oxnMEIWHUi2ijz30sYdZzGMptzGbBVxED68wyEscZC/bmv4iZ6kzpJ5vBmlyEfakGdLPj5JBGi/CnjSDGaTJRNiPZjBDBB5KtZhjHOZh7mrrDKnnm0GaXIQ9aYb086NkkMaLsCfNYAZpMhH2oxnMkJKvKSVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTClbIsy4ocODg4SG9vL5TgkrlFTs69fBSyYSiV4eI5xc83gxmiZUg9H+DkESCDgYEBenp60oQgfT9BjPVInSH1fDOYYaIIHWU/mSHKfDPEymA/5SKshRnMEGV+lAyV9lO6QylJmiDMoZQkTSLEf/RJ0iTsJ0lRTdVPnQVmOZvPlDKDGUJkSD0fxk7Rw/Bv+tp+T5rBDOOF6ij7qe0zpJ5vhlgZ7KdchLUwgxmizI+SodJ+SnYodfHlsOZw8XPvmwcnf5wvTIr5ZjBDtAyp5wPcOzcvzihS9RPEWI/UGVLPN4MZJorUUfaTGVLPN0OsDPZTLsJamMEMUeZHyVBpP/lC55IkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXLJ335NqdeIQHNgOA31w+jjM6IbehbBoLcy8opgMs5jPUtZyGQu5kG5e5Tgv0sdetnOM/mJCSAopdUfZT5LOJXU/gR0laXL2U/vyUEot48gu2LcFDu2A0uvP8cuGoNSRf/70nXDlSliyAeYsa06GhSxjOetZzEoyhgEoU2b49c9Xcif7eIidbKGPPc0JISmk1B1lP0k6l9T9BHaUpMnZT/LX9xRelsGzm2HHTdD/CJDlRZUNvf71kc8zOPQIPPS+vNiyrLE5lrOeDeziGlZQpkwHnXTQSWnc52XKLOYWNrCbm1nX2ACSQorQUfaTpMlE6CewoyS9kf2kER5KKbz9W+HxO/LPszPn/96Rrz+2IX9co9zMOj7KZgA6mHHe7x35+mq2WFpSG0jdUfaTpHNJ3U9gR0manP2kEVUdSg0NDfGf/tN/4qqrruKiiy7irW99K3fddRdZo48rpdcd2ZWXTy0e2wBHd9efYSHLWM2Wmh67mi0s5L31h9CU7CelkLqj7KfWYUepaKn7CeyoVmE/qWj2k8ar6jWl/vAP/5C7776br3/967z97W/nqaee4rbbbqO3t5ff+Z3faVZGtbF9W6DUOfXp+WRKnfnj6/3d4+WsZ4jTU56eT2aI09zMOn/3uAD2k1JI3VH2U+uwo1S01P0EdlSrsJ9UNPtJ41V1KLV3714+8pGP8OEPfxiAn/3Zn+Wb3/wmTzzxRFPCqb2dOJS/4B01/iVNdgaefwhO9MPM+bX9jFnMZzErKdf4m64dzGAJtzKLeRzjcG0hVBH7SUVL3VH2U2uxo1Sk1P0EdlQrsZ9UJPtJE1W1CkuXLuX73/8+//iP/wjAs88+y1//9V+zYsWKpoRTezuwfewdGGpVKsOBbbU/filrR9+BoVYZwyzltrp+hqZmP6loqTvKfmotdpSKlLqfwI5qJfaTimQ/aaKqnin1mc98hsHBQa6++mo6OjoYGhri85//PGvWrDnnY06dOsWpU6dG/3lwcLD2tGorA32N+TmDB2t/7GUsbECCjNksaMDP0fnYTypa6o6yn1pLtR1lP6keqfsJ7KhWYj+pSPaTJqrqjPI73/kO9913H9/4xjf427/9W77+9a+zefNmvv71r5/zMZs2baK3t3f0Y/78Gp9jp7Zz+vjYW4LWKhuC1+r438kL6a75aZ0jynRwET11/QxNzX5S0VJ3lP3UWqrtKPtJ9UjdT2BHtRL7SUWynzRRVStxxx138JnPfIZ//a//NYsXL+b/+//+P37v936PTZs2nfMxGzduZGBgYPSjv7+/7tBqDzO6odRR388odcAFdXTFqxxnuM6ndg4zxCv4N0jNZj+paKk7yn5qLdV2lP2keqTuJ7CjWon9pCLZT5qoql/fe/nllymXzz7H6ujoYHj43Ava1dVFV1dXbenU1nob8axKoKeOZ1W+SCOeX1riJep4fqkqYj+paKk7yn5qLdV2lP2keqTuJ7CjWon9pCLZT5qoqmdKrVq1is9//vM8/PDDPPfcczzwwANs3bqVX/7lX25WPrWxRWshq+8Am2wYFtXx+nN72U6pzqd2liizlzpeiU8VsZ9UtNQdZT+1FjtKRUrdT2BHtRL7SUWynzRRVSvxX//rf+WjH/0on/zkJ/m5n/s5NmzYwL/9t/+Wu+66q1n51MZmXgFXrIRSVc/nG1PqhCtX1f5WoQDH6Gc/OxjidE2PH+I0+3jQtwotgP2koqXuKPuptdhRKlLqfgI7qpXYTyqS/aSJqtoK3d3dfOlLX+JLX/pSk+JIZ7t2Axx6qLbHZkOwZH39GR5lM9dya02PLdPBTrbWH0JTsp+UQuqOsp9ahx2loqXuJ7CjWoX9pKLZTxqvvuesSU02ZxncsLm2x97wxfzx9epjD/dTW/N9lzvoY0/9ISSFlLqj7CdJ55K6n8COkjQ5+0njeSil8BavGyutqZ7mOfL1Gzbnj2uUnWwdLa2pnuY58vX7We8JutQGUneU/STpXFL3E9hRkiZnP2mEh1IKr1TKn6K5ahdccQtQyt8GdOStREc/L+VfX7Ur//5SqbE5drKVzSxjPw8zzDBDnGGIM2QMM8RphjjDMMPs52E2s8yyktpEhI6ynyRNJkI/gR0l6Y3sJ42o8eXFpOLNWZZ/nOiHA9tg8CC8NggX9ORvCbrotvpe8K4Sfeyhjz3MYh5LuY3ZLOAieniFQV7iIHvZ5gveSW0qdUfZT5LOJXU/gR0laXL2kzyUUsuZOR+u/2zaDMc4zMP4jiSS3ih1R9lPks4ldT+BHSVpcvZT+/LX9yRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4UpZlWZEDBwYGeNOb3gTAxXOKnJx7+QUgA0pw8eXFzzeDGaJlSD0f4OWj+f/9yU9+Qm9vb5oQpO8nCLIe7kkzmOHsDAE6yn4yQ5T5ZgiWwX4CgqyFGcwQZH6YDBX2U+GHUocPH2b+/Ca/p6OkltTf38+8efOSzbefJJ1Pyo6ynySdj/0kKaqp+qnwQ6nh4WGOHDlCd3c3pVKp6scPDg4yf/58+vv76enpaUJCM7RKhtTzzdC4DFmWcfz4cebOnUu5nO63iu0nM0ynDKnnT6cMETqq3n6C9OuRer4ZzBAtg/00JvVaRMiQer4ZzNDoDJX2U2c9IWtRLpcbcorf09OTbHHMECtD6vlmaEyGlL+2N8J+MsN0zJB6/nTJkLqjGtVPkH49Us83gxmiZbCfxqReiwgZUs83gxkamaGSfvKFziVJkiRJklQ4D6UkSZIkSZJUuJY7lOrq6uI//+f/TFdXlxnaPEPq+WaIlSGCCNfBDGaIMt8M8aS+Fqnnm8EM0TKknh9JhGuROkPq+WYwQ6oMhb/QuSRJkiRJktRyz5SSJEmSJElS6/NQSpIkSZIkSYXzUEqSJEmSJEmFa6lDqb/5m7+ho6ODD3/4w4XPXrt2LaVSafTj0ksv5UMf+hD79u0rPMsLL7zAb//2b/OWt7yFrq4u5s+fz6pVq/j+97/f9Nnjr8OMGTP46Z/+aZYvX87XvvY1hoeHmz5/YobxHx/60IcKmT9VjoMHDxYy/4UXXuDTn/40CxYs4MILL+Snf/qnufHGG7n77rt5+eWXmz5/7dq1/NIv/dIb/v0Pf/hDSqUSP/nJT5qeIRo7yn6amCNVR6XuJ0jbUfbTG9lP9tPEHPaTf4aKwn6ynybmsJ/aq59a6lDqnnvu4bd/+7fZvXs3R44cKXz+hz70IY4ePcrRo0f5/ve/T2dnJytXriw0w3PPPcf111/PD37wA774xS+yf/9+vve97/H+97+f22+/vZAMI9fhueee45FHHuH9738/n/70p1m5ciVnzpwpNMP4j29+85uFzJ4qx1VXXdX0uf/8z//Mddddx1/+5V/yhS98gf/5P/8nf/M3f8O///f/nh07drBz586mZ9AbtXtH2U9vzJGyo1L1E9hREdlP9tPEHPaT/RSF/WQ/TcxhP7VXP3WmDlCpEydO8O1vf5unnnqKF154ge3bt/Mf/+N/LDRDV1cXl19+OQCXX345n/nMZ3jve9/LSy+9xOzZswvJ8MlPfpJSqcQTTzzBJZdcMvrv3/72t/OJT3yikAzjr8PP/MzP8I53vIMbbriBD3zgA2zfvp3f+I3fKDRDSqlyfPKTn6Szs5OnnnrqrH3wlre8hY985CP4pprFs6Psp3PlSCVlBjsqFvvJfjpXjlTsJ42wn+ync+VIxX4qXss8U+o73/kOV199NYsWLeJjH/sYX/va15IuyokTJ7j33ntZsGABl156aSEz/9//+39873vf4/bbbz9rk45405veVEiOyfziL/4i1157LX/2Z3+WLEO7+L//9//yl3/5l+fcBwClUqngVGr3jrKfNMKOisd+sp+Us5/isZ/sJ+XauZ9a5lDqnnvu4WMf+xiQP6VuYGCAXbt2FZphx44dzJw5k5kzZ9Ld3c2DDz7It7/9bcrlYi7jwYMHybKMq6++upB51br66qt57rnnCpk1fi1GPr7whS8UMvt8OVavXt30mSP7YNGiRWf9+5/6qZ8azfEf/sN/aHoOmHwdVqxYUcjsaNq9o+yns0XoqBT9BHE6yn4aYz/ZT+PZT+n7CeyoEfaT/TSe/dSe/dQSv7534MABnnjiCR544AEAOjs7+Vf/6l9xzz33cNNNNxWW4/3vfz933303AMeOHeOP//iPWbFiBU888QRXXnll0+dHf7pelmWFnd6OX4sRb37zmwuZfb4c5zrVLsITTzzB8PAwa9as4dSpU4XMnGwdHn/88dE/XLQLO8p+mihCR0XqJyi+o+ynnP1kP01kP72Rf4ZKw36ynyayn96oHfqpJQ6l7rnnHs6cOcPcuXNH/12WZXR1dfHlL3+Z3t7eQnJccsklLFiwYPSf//RP/5Te3l6++tWv8vu///tNn79w4UJKpRL/8A//0PRZtfjRj35U2IvATVyLVFLkWLBgAaVSiQMHDpz179/ylrcAcNFFFxWWZbL//w8fPlzY/CjsKPtpoggdlSpDlI6yn3L2k/00kf2Uvp/AjgL7Ceynieyn9uyn8L++d+bMGf7H//gfbNmyhWeeeWb049lnn2Xu3LlJ3nFtRKlUolwu88orrxQy781vfjP/4l/8C77yla9w8uTJN3w95dvH/uAHP2D//v38yq/8SrIM7eLSSy9l+fLlfPnLX550H6hYdlTOftIIOyoO+ylnP2mE/RSH/ZSznzSinfsp/DOlduzYwbFjx/j1X//1N5yW/8qv/Ar33HMP/+7f/btCspw6dYoXXngByJ/a+eUvf5kTJ06watWqQuYDfOUrX+HGG2/k3e9+N//lv/wXlixZwpkzZ3j00Ue5++67+dGPftT0DCPXYWhoiP/zf/4P3/ve99i0aRMrV67k137t15o+f3yG8To7O/mpn/qpQuan9sd//MfceOONvPOd7+TOO+9kyZIllMtlnnzySf7hH/6B66+/PnXEtmFHjbGf3phjPDvKjiqa/TTGfnpjjvHsJ/upaCw3/6cAAQAASURBVPbTGPvpjTnGs5/aoJ+y4FauXJndcsstk37t8ccfz4Ds2WefbXqOj3/84xkw+tHd3Z29613vyr773e82ffZER44cyW6//fbsyiuvzC644ILsZ37mZ7Jbb701+6u/+qumzx5/HTo7O7PZs2dnN998c/a1r30tGxoaavr8iRnGfyxatKiQ+eNzfOQjHyl05nhHjhzJPvWpT2VXXXVVNmPGjGzmzJnZu9/97uyLX/xidvLkyabPP9f//3/1V3+VAdmxY8eaniECO+ps7d5PE3Ok6qjU/ZRlaTvKfsrZT2ezn+ynEf4ZKj376Wz2k/00oh37qZRlwV9dTZIkSZIkSdNO+NeUkiRJkiRJ0vTjoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrXWfTA4eFhjhw5Qnd3N6VSqejxkgLKsozjx48zd+5cyuV0Z+X2k6TJROgo+0nSZOwnSVFV2k+FH0odOXKE+fPnFz1WUgvo7+9n3rx5yebbT5LOJ2VH2U+Szsd+khTVVP1U+KFUd3f36OcXzyl6Orz8ApABJbj48uLnm8EM0TKkng/w8tH8/47vhxRS9xMEWQ/3pBnMcHaGAB1lP5khynwzBMtgPwFB1sIMZggyP0yGCvup8EOpkad0XjwHPnak6Olw3zw4+WO4ZC6sOVz8fDOYIVqG1PMB7p2bl1bqp3yn7ieIsR6pM6SebwYzTBSho+wnM0SZb4ZYGeynXIS1MIMZosyPkqHSfvKFziVJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuMLffU+SpptZzGcpa7mMhVxIN69ynBfpYy/bOUZ/6niS2pwdJSkq+0mSh1KSVKOFLGM561nMSjKGAShTZvj1z1dyJ/t4iJ1soY89KaNKakN2lKSo7CdJI/z1PUmqwXLWs4FdXMMKypTpoJMOOimN+7xMmcXcwgZ2czPrUkeW1EbsKElR2U+SxvNQSpKqdDPr+CibAehgxnm/d+Trq9niH6okFcKOkhSV/SRpoqoPpXbv3s2qVauYO3cupVKJP//zP29CLEmqXhH9tJBlrGZLTY9dzRYW8t4GJ5LUCor685MdJala9pOklKo+lDp58iTXXnstX/nKV5qRR5JqVkQ/LWc9Q5yu6bFDnPZv+qQ2VdSfn+woSdWynySlVPULna9YsYIVK1Y0I4sk1aXZ/TSL+SxmJeUaf/O5gxks4VZmMY9jHG5wOkmRFfHnJztKUi3sJ0kp+ZpSklShpawdfYeYWmUMs5TbGpRIksbYUZKisp8knUvVz5Sq1qlTpzh16tToPw8ODjZ7pCRVpNp+uoyFDZiaMZsFDfg5kqazWv78ZEdJKoL9JKmRmv5MqU2bNtHb2zv6MX/+/GaPlKSKVNtPF9Jd89POR5Tp4CJ66voZkqa/Wv78ZEdJKoL9JKmRmn4otXHjRgYGBkY/+vv7mz1SkipSbT+9ynGG63zq+TBDvILPGJV0frX8+cmOklQE+0lSIzX91/e6urro6upq9hhJqlq1/fQifQ2YWuIlDjbg50iazmr585MdJakI9pOkRqr6mVInTpzgmWee4ZlnngHgf//v/80zzzzDoUOHGp1NkqrS7H7ay3ZKdT7BtESZvWxrSB5JraOIPz/ZUZJqYT9JSqnqZnjqqae47rrruO666wBYt24d1113HZ/97GcbHk6SqtHsfjpGP/vZwRCna3r8EKfZx4O+lbHUhor485MdJakW9pOklKr+9b2bbrqJLMuakUWS6lJEPz3KZq7l1poeW6aDnWxtcCJJraCoPz/ZUZKqZT9JSqnpL3QuSdNJH3u4n/U1Pfa73EEfexqcSJLG2FGSorKfJE3GQylJqtJOto7+oWqqp6GPfP1+1vs3fJIKYUdJisp+kjRR0999T5Kmo51s5Xme5GbWsYRbyV5/m+MyZYYZAkqUKLOfh9nJVv92T1Kh7ChJUdlPksbzUEqSatTHHvrYwyzmsZTbmM0CLqKHVxjkJQ6yl22+IKekZOwoSVHZT5JGeCglSXU6xmEe5q7UMSRpUnaUpKjsJ0m+ppQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKV8qyLCty4ODgIL29vVCCS+YWOTn38lHIhqFUhovnFD/fDGaIliH1fICTR4AMBgYG6OnpSROC9P0EMdYjdYbU881ghokidJT9ZIYo880QK4P9lIuwFmYwQ5T5UTJU2k/pDqUkaYIwh1KSNIkQ/9EnSZOwnyRFNVU/dRaY5Ww+U8oMZgiRIfV8GDtFD8O/6Wv7PWkGM4wXqqPsp7bPkHq+GWJlsJ9yEdbCDGaIMj9Khkr7Kdmh1MWXw5rDxc+9bx6c/HG+MCnmm8EM0TKkng9w79y8OKNI1U8QYz1SZ0g93wxmmChSR9lPZkg93wyxMthPuQhrYQYzRJkfJUOl/eQLnUuSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlw6d59r0onDsGB7TDQB6ePw4xu6F0Ii9bCzCvMUGQGxViHWcxnKWu5jIVcSDevcpwX6WMv2zlGfzEhBMRYiwgZItwXirEOEfajxqRej9TzIcZ9oVyEtUidIfX8SCL0Q+oM7oc4IqxFO2YIfyh1ZBfs2wKHduRvZwiQDUGpI//86TvhypWwZAPMWWaGZmZQjHVYyDKWs57FrCRjGIAyZYZf/3wld7KPh9jJFvrY05wQAmKsRYQMEe4LxViHCPtRY1KvR+r5EOO+UC7CWqTOkHp+JBH6IXUG90McEdainTOE/fW9LINnN8OOm6D/ESDLL0g29PrXRz7P4NAj8ND78guYZWZodAbFWYflrGcDu7iGFZQp00EnHXRSGvd5mTKLuYUN7OZm1jU2gEZFWIvUGaLcF+0uyjqk3o86W+r1SD0/yn2hGGuROkPq+dGk7ofUGdwPcURYCzMEPpTavxUevyP/PDtz/u8d+fpjG/LHmaGxGRRjHW5mHR9lMwAdzDjv9458fTVb/A+/JoiwFhEyRLgvFGMdIuxHjUm9HqnnQ4z7QrkIa5E6Q+r5kUToh9QZ3A9xRFgLMwQ9lDqyK/9/shaPbYCju83QqAyKsQ4LWcZqttT02NVsYSHvrT+EgBhrESFDhPtCMdYhwn7UmNTrkXo+xLgvlIuwFqkzpJ4fSYR+SJ3B/RBHhLUwQ66qQ6lNmzbxrne9i+7ubi677DJ+6Zd+iQMHDtSfYoJ9W6BU46tdlTrzx5uhMRkUYx2Ws54hTtf02CFOt8WzEYrqpwhrESFDhPtCMdYhwn5sBe3SUannQ4z7QrkIa5E6Q+r5lWiXfoqQoRX2Q7uIsBZmyFV1KLVr1y5uv/12HnvsMR599FFOnz7NBz/4QU6ePFl/ktedOJS/sNZUTxs7l+wMPP8QnKjjjRLMoBER1mEW81nMyimfXnwuHcxgCbcyi3m1h2gBRfRThLWIkCHCfaEY6xBhP7aKduio1PMhxn2hXIS1SJ0h9fxKtUM/RcjQKvuhHURYCzOMqepQ6nvf+x5r167l7W9/O9deey3bt2/n0KFDPP300/WlGOfA9rFXeq9VqQwHtpmh3gyKsQ5LWTv6jiC1yhhmKbfV9TOiK6KfIqxFhAwR7gvFWIcI+7FVtENHpZ4PMe4L5SKsReoMqedXqh36KUKGVtkP7SDCWphhTI1P1MoNDAwA8OY3v/mc33Pq1ClOnTo1+s+Dg4Pn/5l99SQaM3iw9seaQSMirMNlLGxAgozZLGjAz2kdzeinCGsRIUOE+0Ix1iHCfmxVU3VUtf0E6dcj9XyIcV8oF2EtUmdIPb9W07GfImRo1f0wHUVYCzOMqflcbHh4mN/93d/lxhtv5Jprrjnn923atIne3t7Rj/nz55/3554+PvbWg7XKhuC1qbvRDJpShHW4kG7Kdb4nQZkOLqKnrp/RSprVTxHWIkKGCPeFYqxDhP3YiirpqGr7CdKvR+r5EOO+UC7CWqTOkHp+LaZrP0XI0Ir7YbqKsBZmGFPzXXn77bfzd3/3d3zrW9867/dt3LiRgYGB0Y/+/vP/wuGMbih11JoqV+qAC+r4860ZNCLCOrzKcYbrfKrxMEO8Qvv8L1iz+inCWkTIEOG+UIx1iLAfW1ElHVVtP0H69Ug9H2LcF8pFWIvUGVLPr8V07acIGVpxP0xXEdbCDGNq+vW9T33qU+zYsYPdu3czb975X+itq6uLrq6uin92byOeVQn01PGbAGbQiAjr8CKNeF5liZdoj+f6NrOfIqxFhAwR7gvFWIcI+7HVVNpR1fYTpF+P1PMhxn2hXIS1SJ0h9fxqTed+ipCh1fbDdBZhLcwwpqpnSmVZxqc+9SkeeOABfvCDH3DVVVfVN30Si9ZCVt8BNtkwLKrjNVPNoBER1mEv2ynV+VTjEmX2Mr1fFbGIfoqwFhEyRLgvFGMdIuzHVtEOHZV6PsS4L5SLsBapM6SeX/GMNuinCBlaZT+0gwhrYYYxVd2Vt99+O/feey/f+MY36O7u5oUXXuCFF17glVdeqS/FODOvgCtWQqnGl2AvdcKVq2Dm1L/abAZNKcI6HKOf/exgiNM1PX6I0+zjQY5xuPYQLaCIfoqwFhEyRLgvFGMdIuzHVtEOHZV6PsS4L5SLsBapM6SeX6l26KcIGVplP7SDCGthhjFVHUrdfffdDAwMcNNNNzFnzpzRj29/+9v1pZjg2g2QnantsdkQLFlvhkZlUIx1eJTNdDCjpseW6WAnW+sPEVxR/RRhLSJkiHBfKMY6RNiPraBdOir1fIhxXygXYS1SZ0g9vxLt0k8RMrTCfmgXEdbCDLmqf31vso+1a9fWn2ScOcvghs21PfaGL+aPN0NjMijGOvSxh/up7Y7/LnfQx576QwRXVD9FWIsIGSLcF4qxDhH2Yytol45KPR9i3BfKRViL1BlSz69Eu/RThAytsB/aRYS1MEOuvl+qbaLF68YuzlRPJxv5+g2b88eZobEZFGMddrJ19H9Ep3ra8cjX72d92zwLoUgR1iJChgj3hWKsQ4T9qDGp1yP1fIhxXygXYS1SZ0g9P5II/ZA6g/shjghrYYbAh1KlUv5UsFW74IpbgFL+doMjb1k4+nkp//qqXfn3l0pmaHQGxVmHnWxlM8vYz8MMM8wQZxjiDBnDDHGaIc4wzDD7eZjNLPM/+JoowlqkzhDlvmh3UdYh9X7U2VKvR+r5Ue4LxViL1BlSz48mdT+kzuB+iCPCWpgBanxJq+LMWZZ/nOiHA9tg8CC8NggX9ORvPbjotua/2JsZNCLCOvSxhz72MIt5LOU2ZrOAi+jhFQZ5iYPsZVtbvGhwBBHWIkKGCPeFYqxDhP2oManXI/V8iHFfKBdhLVJnSD0/kgj9kDqD+yGOCGvRzhnCH0qNmDkfrv+sGSJkUIx1OMZhHuautCEExFiLCBki3BeKsQ4R9qPGpF6P1PMhxn2hXIS1SJ0h9fxIIvRD6gzuhzgirEU7Zgj763uSJEmSJEmavjyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuFKWZZlRQ4cHBykt7cXSnDJ3CIn514+CtkwlMpw8Zzi55vBDNEypJ4PcPIIkMHAwAA9PT1pQpC+nyDGeqTOkHq+GcwwUYSOsp/MEGW+GWJlsJ9yEdbCDGaIMj9Khkr7Kd2hlCRNEOZQSpImEeI/+iRpEvaTpKim6qfOArOczWdKmcEMITKkng9jp+hh+Dd9bb8nzWCG8UJ1lP3U9hlSzzdDrAz2Uy7CWpjBDFHmR8lQaT8lO5S6+HJYc7j4uffNg5M/zhcmxXwzmCFahtTzAe6dmxdnFKn6CWKsR+oMqeebwQwTReoo+8kMqeebIVYG+ykXYS3MYIYo86NkqLSffKFzSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFS7du+9VaRbzWcpaLmMhF9LNqxznRfrYy3aO0V9IhhOH4MB2GOiD08dhRjf0LoRFa2HmFYVEMINGuQ5x2E85r4NGuA6xpL43I+yH1NcAYlwH5VyLOLw3vQY6WzuuRfhDqYUsYznrWcxKMoYBKFNm+PXPV3In+3iInWyhjz1NyXBkF+zbAod25G+pCJANQakj//zpO+HKlbBkA8xZ1pQIZtAo1yEO+ynnddAI1yGW1PdmhP2Q+hpAjOugnGsRh/em10Bna+e1CP3re8tZzwZ2cQ0rKFOmg0466KQ07vMyZRZzCxvYzc2sa+j8LINnN8OOm6D/ESDLN0Y29PrXRz7P4NAj8ND78o2UZWZodAa5DtHYTzmvg8B1iCjlvRllP9hPGuFaxOK96TXQGNci8KHUzazjo2wGoIMZ5/3eka+vZktDb9j9W+HxO/LPszPn/96Rrz+2IX+cGRqbQa5DJPZTzuugEa5DLKnvzQj7IfU1gBjXQTnXIg7vTa+BzuZaVHkodffdd7NkyRJ6enro6enhPe95D4888kjDQy1kGavZUtNjV7OFhby37gxHduWLXYvHNsDR3XVHMINGuQ5Ts58q06j94HXQCNehMu3SURH2Q+prADGug3KuxdTapZ8g/X7wGmg81yJX1aHUvHnz+IM/+AOefvppnnrqKX7xF3+Rj3zkI/yv//W/GhpqOesZ4nRNjx3idENOkfdtgVKNr7hV6swfb4bGZJDrUAn7qTKN2g9eB41wHSrTLh0VYT+kvgYQ4zoo51pMrV36CdLvB6+BxnMtclUdSq1atYpbbrmFhQsX8ra3vY3Pf/7zzJw5k8cee6xhgWYxn8WsnPKpjOfSwQyWcCuzmFdzhhOH8hcYm+rpc+eSnYHnH4ITdbxZghk0wnWojP1UmUbsB6+DRrgOlWuHjoqwH1JfA4hxHZRzLSrTDv0E6feD10DjuRZjan5NqaGhIb71rW9x8uRJ3vOe9zQs0FLWjr77QK0yhlnKbTU//sD2sVe8r1WpDAe21f54M2iE61A9++n86t0PXgeNcB1qM107KsJ+SH0NIMZ1UM61qN507SdIvx+8BhrPtRhT9ZPF9u/fz3ve8x5effVVZs6cyQMPPMDP//zPn/P7T506xalTp0b/eXBw8Lw//zIWVhtpEhmzWVDzowf6GhABGDxY+2PNoBGuQ+Xsp8rVsx+8DhrhOlSnmo6qtp8g/b0ZYT+kvgYQ4zoo51pUbrr3E6TfD14DjedajKn6bG7RokU888wzPP744/zWb/0WH//4x/n7v//7c37/pk2b6O3tHf2YP3/+eX/+hXRTrvNNAct0cBE9NT/+9PGxt2CsVTYEr03dz2bQlFyHytlPlal3P3gdNMJ1qE41HVVtP0H6ezPCfkh9DSDGdVDOtajcdO8nSL8fvAYaz7UYU/VdccEFF7BgwQKuv/56Nm3axLXXXssf/dEfnfP7N27cyMDAwOhHf//5f+nxVY4zXOfTGocZ4hVqX50Z3VDqqCsCpQ64oPa+MINGuQ6Vs58qU+9+8DpohOtQnWo6qtp+gvT3ZoT9kPoaQIzroJxrUbnp3k+Qfj94DTSeazGmxtd6HzM8PHzW0zcn6urqoqurq+Kf9yKNeB5biZeo/XlsvY14ZiXQU/szK82gUa5D7eync6tnP3gdNMJ1qM/5OqrafoL092aE/ZD6GkCM66Cca1G76dZPkH4/eA00nmsxpqpnSm3cuJHdu3fz3HPPsX//fjZu3MgPf/hD1qxZ07BAe9lOqc6nNZYos5faX/Fr0VrI6jvEJhuGRbW/Bp0ZNMp1qIz9VLl694PXQSNch8q1Q0dF2A+prwHEuA7KuRaVaYd+gvT7wWug8VyLMVXdFS+++CK/9mu/xqJFi/jABz7Ak08+yV/8xV+wfPnyhgU6Rj/72cEQp2t6/BCn2ceDHONwzRlmXgFXrIRSjc8jK3XClatg5tS/Xm0GTcl1qIz9VJlG7Aevg0a4DpVrh46KsB9SXwOIcR2Ucy0q0w79BOn3g9dA47kWY6q6BPfcc0+zcpzlUTZzLbfW9NgyHexka90Zrt0Ahx6q7bHZECxZX3cEM2iU6zA1+6kyjdoPXgeNcB0q0y4dFWE/pL4GEOM6KOdaTK1d+gnS7wevgcZzLXL1PX+wSfrYw/3UdoW/yx30safuDHOWwQ2ba3vsDV/MH2+GxmSQ6xCJ/ZTzOmiE6xBL6nszwn5IfQ0gxnVQzrWIw3vTa6CzuRa5kIdSADvZOnrDTvUUx5Gv38/6hpwej1i8bmyTTPW0upGv37A5f5wZGptBrkMk9lPO66ARrkMsqe/NCPsh9TWAGNdBOdciDu9Nr4HO5loEPpSC/IbdzDL28zDDDDPEGYY4Q8YwQ5xmiDMMM8x+HmYzyxp6owKUSvlT4lbtgituAUr52y6OvHXj6Oel/OurduXfXyqZodEZ5DpEYz/lvA4C1yGilPdmlP1gP2mEaxGL96bXQGNciypfUyqFPvbQxx5mMY+l3MZsFnARPbzCIC9xkL1sq+vF3ioxZ1n+caIfDmyDwYPw2iBc0JO/BeOi25r/AmNm0AjXIQ77Ked10AjXIZbU92aE/ZD6GkCM66CcaxGH96bXQGdr57UIfyg14hiHeZi7kmaYOR+u/2zSCGbQKNchDvsp53XQCNchltT3ZoT9kPoaQIzroJxrEYf3ptdAZ2vHtQj963uSJEmSJEmanjyUkiRJkiRJUuE8lJIkSZIkSVLhPJSSJEmSJElS4UpZlmVFDhwcHKS3txdKcMncIifnXj4K2TCUynDxnOLnm8EM0TKkng9w8giQwcDAAD09PWlCkL6fIMZ6pM6Qer4ZzDBRhI6yn8wQZb4ZYmWwn3IR1sIMZogyP0qGSvsp3aGUJE0Q5lBKkiYR4j/6JGkS9pOkqKbqp84Cs5zNZ0qZwQwhMqSeD2On6GH4N31tvyfNYIbxQnWU/dT2GVLPN0OsDPZTLsJamMEMUeZHyVBpPyU7lLr4clhzuPi5982Dkz/OFybFfDOYIVqG1PMB7p2bF2cUqfoJYqxH6gyp55vBDBNF6ij7yQyp55shVgb7KRdhLcxghijzo2SotJ98oXNJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVLt2771VpFvNZylouYyEX0s2rHOdF+tjLdo7RX0iGE4fgwHYY6IPTx2FGN/QuhEVrYeYVhUQwQ4D5ZoiVIQL7KU4G1yL9fDPEk/q+iLAWETKkXgeIcR3MkH5+JN4X6eeD62CGtBnCH0otZBnLWc9iVpIxDECZMsOvf76SO9nHQ+xkC33saUqGI7tg3xY4tCN/S0WAbAhKHfnnT98JV66EJRtgzrKmRDBDgPlmiJUhAvspTgbXIv18M8ST+r6IsBYRMqReB4hxHcyQfn4k3hfp54PrYIYYGUL/+t5y1rOBXVzDCsqU6aCTDjopjfu8TJnF3MIGdnMz6xo6P8vg2c2w4ybofwTI8kXJhl7/+sjnGRx6BB56X76IWWaGRmZIPd8MsTJEYT/FyACuRer5Zogp5X0RYS0iZAD7yQwx5kfT7vdF6vkj2n0dzBAnQ9hDqZtZx0fZDEAHM877vSNfX82Wht4s+7fC43fkn2dnzv+9I19/bEP+ODM0LkPq+WaIlSEC+ylOBtci/XwzxJP6voiwFhEypF4HiHEdzJB+fiTeF+nng+tghlgZQh5KLWQZq9lS02NXs4WFvLfuDEd25Re6Fo9tgKO7645ghgDzzRArQwT2U5wMrkX6+WaIJ/V9EWEtImRIvQ4Q4zqYIf38SLwv0s8H18EM8TLUdSj1B3/wB5RKJX73d3+3/iTjLGc9Q5yu6bFDnG7ICe6+LVCq8RW3Sp35481Qf4bU880QK0M17KfJTaf94Fqkn2+G2jSrnyD9fRFhLSJkSL0OEOM6mCH9/Fr4Z6jJTZf94DqYIVqGmg+lnnzySf77f//vLFmypP4U48xiPotZOeXTCM+lgxks4VZmMa/mDCcO5S/uNdVT184lOwPPPwQn6nijAjOkn2+GWBmqYT+d23TZD65F+vlmqE2z+gnS3xcR1iJChtTrADGugxnSz6+Ff4Y6t+mwH1wHM0TLADUeSp04cYI1a9bw1a9+lVmzZtWXYIKlrB195f9aZQyzlNtqfvyB7WOvNl+rUhkObKv98WZIP98MsTJUyn6a2nTYD65F+vlmqF4z+wnS3xcR1iJChtTrADGugxnSz6+Wf4aaWqvvB9fBDNEyQI2HUrfffjsf/vCHufnmm6f83lOnTjE4OHjWx/lcxsJaIk2QMZsFNT96oK8BEYDBg7U/1gzp55shVoZK2U+VafX94Fqkn2+G6jWznyD9fRFhLSJkSL0OEOM6mCH9/GpV2lGt2E+Qfj1SzwfXwQzxMgBU/duD3/rWt/jbv/1bnnzyyYq+f9OmTXzuc5+r+OdfSDflOl9/vUwHF9FT8+NPHx97+8NaZUPw2tT9bIbA880QK0Ml7KfKTIf94Fqkn2+G6jS7nyD9fRFhLSJkSL0OEOM6mCH9/GpU01Gt2E+Qfj1SzwfXwQzxMkCVz5Tq7+/n05/+NPfddx8XXnhhRY/ZuHEjAwMDox/9/ef/hcNXOc5wnU8pHGaIV6j9yszohlJHXREodcAFtd+rZggw3wyxMkzFfqrcdNgPrkX6+WaoXBH9BOnviwhrESFD6nWAGNfBDOnnV6rajmrFfoL065F6PrgOZoiXAap8ptTTTz/Niy++yDve8Y7Rfzc0NMTu3bv58pe/zKlTp+joOPv/q66uLrq6uiqe8SKNeA5ZiZeo/TlkvY14ViPQU/uzGs0QYL4ZYmWYiv1UnVbfD65F+vlmqFwR/QTp74sIaxEhQ+p1gBjXwQzp51eq2o5qxX6C9OuRej64DmaIlwGqfKbUBz7wAfbv388zzzwz+vHOd76TNWvW8Mwzz7zhD1S12Mt2SnU+pbBEmb3U/mpbi9ZCVt8BMtkwLKr99d/MEGC+GWJlmIr9VLnpsB9ci/TzzVC5IvoJ0t8XEdYiQobU6wAxroMZ0s+vlH+Gqlyr7wfXwQzRMkCVh1Ld3d1cc801Z31ccsklXHrppVxzzTX1JXndMfrZzw6GOF3T44c4zT4e5BiHa84w8wq4YiWUqn7FrVypE65cBTPn1xzBDAHmmyFWhqnYT5WZLvvBtUg/3wyVK6KfIP19EWEtImRIvQ4Q4zqYIf38SvlnqMpMh/3gOpghWgao8d33mu1RNtPBjJoeW6aDnWytO8O1GyA7U9tjsyFYsr7uCGYIMN8MsTJEYD/FyeBapJ9vhnhS3xcR1iJChtTrADGugxnSz4/E+yL9fHAdzBAvQ92HUj/84Q/50pe+VH+ScfrYw/3U9v/dd7mDPvbUnWHOMrhhc22PveGL+ePNUH+G1PPNECtDteynN5pO+8G1SD/fDLVrRj9B+vsiwlpEyJB6HSDGdTBD+vm18s9QbzRd9oPrYIZoGUI+UwpgJ1tHb5apnl448vX7Wd+Qk9sRi9eNLdBUT2kb+foNm/PHmaFxGVLPN0OsDBHYT3EyuBbp55shntT3RYS1iJAh9TpAjOtghvTzI/G+SD8fXAczxMoQ9lAK8ptlM8vYz8MMM8wQZxjiDBnDDHGaIc4wzDD7eZjNLGvoTQJQKuVPR1u1C664BSjlb3k48raJo5+X8q+v2pV/f6lkhkZmSD3fDLEyRGE/xcgArkXq+WaIKeV9EWEtImQA+8kMMeZH0+73Rer5I9p9HcwQJ0ONL2lVnD720MceZjGPpdzGbBZwET28wiAvcZC9bKvrhdYqMWdZ/nGiHw5sg8GD8NogXNCTv/3hotua/wKEZkg/3wyxMkRgP8XJ4Fqkn2+GeFLfFxHWIkKG1OsAMa6DGdLPj8T7Iv18cB3MECND+EOpEcc4zMPclTTDzPlw/WeTRjBDgPlmiJUhAvspTgbXIv18M8ST+r6IsBYRMqReB4hxHcyQfn4k3hfp54PrYIa0GUL/+p4kSZIkSZKmJw+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLhSlmVZkQMHBwfp7e2FElwyt8jJuZePQjYMpTJcPKf4+WYwQ7QMqecDnDwCZDAwMEBPT0+aEKTvJ4ixHqkzpJ5vBjNMFKGj7CczRJlvhlgZ7KdchLUwgxmizI+SodJ+SncoJUkThDmUkqRJhPiPPkmahP0kKaqp+qmzwCxn85lSZjBDiAyp58PYKXoY/k1f2+9JM5hhvFAdZT+1fYbU880QK4P9lIuwFmYwQ5T5UTJU2k/JDqUuvhzWHC5+7n3z4OSP84VJMd8MZoiWIfV8gHvn5sUZRap+ghjrkTpD6vlmMMNEkTrKfjJD6vlmiJXBfspFWAszmCHK/CgZKu0nX+hckiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhUv37ntVmsV8lrKWy1jIhXTzKsd5kT72sp1j9BeS4cQhOLAdBvrg9HGY0Q29C2HRWph5RSERzECMvSCNF2FPpr4vzTAmwn6Qxku9JyPcl2bIpd4L0kQR9mTqezP1/CgZIuwFpRH+UGohy1jOehazkoxhAMqUGX7985XcyT4eYidb6GNPUzIc2QX7tsChHflbKgJkQ1DqyD9/+k64ciUs2QBzljUlghmIsRek8SLsydT3pRnGRNgP0nip92SE+9IMudR7QZoowp5MfW+mnh8lQ4S9oLRC//rectazgV1cwwrKlOmgkw46KY37vEyZxdzCBnZzM+saOj/L4NnNsOMm6H8EyPKbNBt6/esjn2dw6BF46H35TZ1lZmh0htR7QZoo9Z6McF+aYUzq/SBNlHJPRrgvzTDGflI0qfdk6nsz9fwoGSD9XlAMYQ+lbmYdH2UzAB3MOO/3jnx9NVsaulH3b4XH78g/z86c/3tHvv7YhvxxZmhchgh7QRovwp5MfV+aYUyE/SCNl3pPRrgvzZBLvRekiSLsydT3Zur5UTJE2AuKoapDqTvvvJNSqXTWx9VXX93wUAtZxmq21PTY1WxhIe+tO8ORXfmNV4vHNsDR3XVHMAMx9oJag/1UmenSDVEyRNgPag3t0lER7ksz5FLvBbWOduknSH9vpp4fJUOEvaA4qn6m1Nvf/naOHj06+vHXf/3XDQ+1nPUMcbqmxw5xuiGnp/u2QKnGV9wqdeaPN0P9GSLsBbUO+2lq06UbomSIsB/UOtqhoyLcl2bIpd4Lai3t0E+Q/t5MPT9Khgh7QXFUvR07Ozu5/PLLm5EFyF91fzErKdf4m4UdzGAJtzKLeRzjcE0/48Sh/MXeqPF3ZrMz8PxDcKIfZs6v7WeYIcZeUGuxn6Y2HbohSoYI+0GtZbp3VIT70gy51HtBrWe69xOkvzdTz4+SIcJeUCxV74S+vj7mzp3LW97yFtasWcOhQ4caGmgpa0dfdb9WGcMs5baaH39g+9i7D9SqVIYD22p/vBli7AW1FvupMq3eDVEyRNgPai3TvaMi3JdmyKXeC2o9072fIP29mXp+lAwR9oJiqeqZUr/wC7/A9u3bWbRoEUePHuVzn/sc733ve/m7v/s7uru7J33MqVOnOHXq1Og/Dw4OnnfGZSysJtI5ZMxmQc2PHuhrQARg8GDtjzVDjL2g1mE/VaeVuyFKhgj7Qa2j2o6qtp8g/Z6McF+aIZd6L6i1tEM/Qfp7M/X8KBki7AXFUtWh1IoVK0Y/X7JkCb/wC7/AlVdeyXe+8x1+/dd/fdLHbNq0ic997nMVz7iQ7pqfyjeiTAcX0VPz408fH3s7zFplQ/Da1P1shvOIsBfUOuynyrV6N0TJEGE/qHVU21HV9hOk35MR7ksz5FLvBbWWdugnSH9vpp4fJUOEvaBY6toNb3rTm3jb297GwYPnPirduHEjAwMDox/9/f3n/ZmvcpzhOp/ON8wQr1D7nTKjG0oddUWg1AEX1HGfmCHGXlDrsp/OrdW7IUqGCPtBrWuqjqq2nyD9noxwX5ohl3ovqLVNx36C9Pdm6vlRMkTYC4qlrkOpEydO8E//9E/MmTPnnN/T1dVFT0/PWR/n8yKNeE5hiZeo/TmFvY14RiHQU8czCs0QYy+oddlP59fK3RAlQ4T9oNY1VUdV20+Qfk9GuC/NkEu9F9TapmM/Qfp7M/X8KBki7AXFUtWh1IYNG9i1axfPPfcce/fu5Zd/+Zfp6OjgV3/1VxsWaC/bKdX5dL4SZfZS+6uvLVoLWX2Ht2TDsKiO114zQ4y9oNZhP1Wu1bshSoYI+0Gtox06KsJ9aYZc6r2g1tIO/QTp783U86NkiLAXFEtVu+Hw4cP86q/+KosWLeJf/st/yaWXXspjjz3G7NmzGxboGP3sZwdDnK7p8UOcZh8P1vX2kDOvgCtWQqmqV9waU+qEK1fV/jaZZshF2AtqHfZTZaZDN0TJEGE/qHW0Q0dFuC/NkEu9F9Ra2qGfIP29mXp+lAwR9oJiqWo7futb32pWjrM8ymau5daaHlumg51srTvDtRvg0EO1PTYbgiXr645gBmLsBbUG+6ky06UbomSIsB/UGtqloyLcl2bIpd4Lah3t0k+Q/t5MPT9Khgh7QXHU97y5JuljD/dT227/LnfQx566M8xZBjdsru2xN3wxf7wZ6s8QYS9I40XYk6nvSzOMibAfpPFS78kI96UZcqn3gjRRhD2Z+t5MPT9Khgh7QXGEPJQC2MnW0Y061VP7Rr5+P+sbemq6eN3YDTvVUxxHvn7D5vxxZmhchgh7QRovwp5MfV+aYUyE/SCNl3pPRrgvzZBLvRekiSLsydT3Zur5UTJE2AuKIeyhFOQbdTPL2M/DDDPMEGcY4gwZwwxxmiHOMMww+3mYzSxr+AYtlfKnJ67aBVfcApTyt8AceRvN0c9L+ddX7cq/v1QyQ6MzpN4L0kSp92SE+9IMY1LvB2milHsywn1phjH2k6JJvSdT35up50fJAOn3gmKo8SXOitPHHvrYwyzmsZTbmM0CLqKHVxjkJQ6yl21Nf5GzOcvyjxP9cGAbDB6E1wbhgp787TAX3Vbfi72ZoTIR9oI0XoQ9mfq+NMOYCPtBGi/1noxwX5ohl3ovSBNF2JOp783U86NkiLAXlFb4Q6kRxzjMw9yVNMPM+XD9Z5NGMAMx9oI0XoQ9mfq+NMOYCPtBGi/1noxwX5ohl3ovSBNF2JOp783U86NkiLAXlEboX9+TJEmSJEnS9OShlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSClfKsiwrcuDg4CC9vb1QgkvmFjk59/JRyIahVIaL5xQ/3wxmiJYh9XyAk0eADAYGBujp6UkTgvT9BDHWI3WG1PPNYIaJInSU/WSGKPPNECuD/ZSLsBZmMEOU+VEyVNpP6Q6lJGmCMIdSkjSJEP/RJ0mTsJ8kRTVVP3UWmOVsPlPKDGYIkSH1fBg7RQ/Dv+lr+z1pBjOMF6qj7Ke2z5B6vhliZbCfchHWwgxmiDI/SoZK+ynZodTFl8Oaw8XPvW8enPxxvjAp5pvBDNEypJ4PcO/cvDijSNVPEGM9UmdIPd8MZpgoUkfZT2ZIPd8MsTLYT7kIa2EGM0SZHyVDpf3kC51LkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcOnefa8FnTgEB7bDQB+cPg4zuqF3ISxaCzOvSJ2uOLOYz1LWchkLuZBuXuU4L9LHXrZzjP6mz4+wDqmvgRk0UYT7IoIIezL1WkS4BmbQeKnviSgi7MkIaxHhOqTOkHq+zhbhvkgtwp6MsA4RrkM7ZvBQqgJHdsG+LXBoR/6WigDZEJQ68s+fvhOuXAlLNsCcZcliNt1ClrGc9SxmJRnDAJQpM/z65yu5k308xE620Meehs+PsA6pr4EZNFGE+yKCCHsy9VpEuAZm0Hip74koIuzJCGsR4TqkzpB6vs4W4b5ILcKejLAOEa5DO2fw1/fOI8vg2c2w4ybofwTI8hskG3r96yOfZ3DoEXjoffkNlWUJQzfJctazgV1cwwrKlOmgkw46KY37vEyZxdzCBnZzM+saNjvKOqS8BmbQRFHuiwhS78kIa5H6GphB40W4J6JIvSejrEXq6xAhQ+r5GhPlvkgt9Z6Msg6pr4MZPJQ6r/1b4fE78s+zM+f/3pGvP7Yhf9x0cjPr+CibAehgxnm/d+Trq9nSsI0aYR1SXwMzaKII90UEEfZk6rWIcA3MoPFS3xNRRNiTEdYiwnVInSH1fJ0twn2RWoQ9GWEdIlwHM3godU5HduWbvhaPbYCjuxubJ5WFLGM1W2p67Gq2sJD31jU/wjqkvgZm0EQR7osIIuzJ1GsR4RqYQeOlvieiiLAnI6xFhOuQOkPq+TpbhPsitQh7MsI6RLgOZshVfSj14x//mI997GNceumlXHTRRSxevJinnnqq7iDR7NsCpRpfcavUmT9+OljOeoY4XdNjhzhd9+lphHVIfQ3MUDn7aWr2U65RezL1WkS4BmaoXDt0VOp7IooIezLCWkS4DqkzpJ5fqXboJ4hxX6QWYU9GWIcI18EMuaoOpY4dO8aNN97IjBkzeOSRR/j7v/97tmzZwqxZs+oOEsmJQ/kLrU31NMJzyc7A8w/BiRZ/84xZzGcxK6d8Ct+5dDCDJdzKLObV9PgI65D6GpihcvZTZeynXCP2ZOq1iHANzFC5duio1PdEFBH2ZIS1iHAdUmdIPb9S7dBPEOO+SC3CnoywDhGugxnGVHUo9Yd/+IfMnz+fbdu28e53v5urrrqKD37wg7z1rW+tK0Q0B7aPvfJ/rUplOLCtIXGSWcra0Vfdr1XGMEu5rabHRliH1NfADJWznypnP+Xq3ZOp1yLCNTBD5dqho1LfE1FE2JMR1iLCdUidIfX8SrVDP0GM+yK1CHsywjpEuA5mGFPVdnjwwQd55zvfyerVq7nsssu47rrr+OpXv3rex5w6dYrBwcGzPqIb6GvMzxk82Jifk8plLGzAT8mYzYKaHhlhHVJfAzNUzn6qjv0E9e7J1GsR4RqYoXLVdpT91Loi7MkIaxHhOqTOkHp+pdqhnyDGfZFahD0ZYR0iXAczjKnqUOqf//mfufvuu1m4cCF/8Rd/wW/91m/xO7/zO3z9618/52M2bdpEb2/v6Mf8+fPrClyE08fH3oqyVtkQvNYa/XxOF9JNuc7Xwi/TwUX01PTYCOuQ+hqYoXL2U+Xsp1y9ezL1WkS4BmaoXLUdZT+1rgh7MsJaRLgOqTOknl+pdugniHFfpBZhT0ZYhwjXwQzjf0YVhoeHecc73sEXvvAFrrvuOv7Nv/k3/OZv/ib/7b/9t3M+ZuPGjQwMDIx+9PfH/yXcGd1Q6qjvZ5Q64ILm/u9H073KcYbrfDrfMEO8Qm2NEWEdUl8DM1Tx8+2nitlPuXr3ZOq1iHANzFDFjCo7yn5qXRH2ZIS1iHAdUmdIPb/iGW3QTxDjvkgtwp6MsA4RroMZxlR1KDVnzhx+/ud//qx/93M/93McOnTonI/p6uqip6fnrI/oehvxLDagp7nPtG26F2nEcytLvERtz62MsA6pr4EZKmc/Vcd+gnr3ZOq1iHANzFC5ajvKfmpdEfZkhLWIcB1SZ0g9v1Lt0E8Q475ILcKejLAOEa6DGcZUdSh14403cuDAgbP+3T/+4z9y5ZVX1hUimkVrIavvwJBsGBY19zUJm24v2ynV+XS+EmX2Utur0EVYh9TXwAyVs58qZz/l6t2TqdciwjUwQ+XaoaNS3xNRRNiTEdYiwnVInSH1/Eq1Qz9BjPsitQh7MsI6RLgOZhhTVYLf+73f47HHHuMLX/gCBw8e5Bvf+AZ/8id/wu23315XiGhmXgFXrIRSZ22PL3XClatgZmv8evU5HaOf/exgiNM1PX6I0+zjQY5xuKbHR1iH1NfADJWznypjP+UasSdTr0WEa2CGyrVDR6W+J6KIsCcjrEWE65A6Q+r5lWqHfoIY90VqEfZkhHWIcB3MMKaqQ6l3vetdPPDAA3zzm9/kmmuu4a677uJLX/oSa9asqStERNdugOxMbY/NhmDJ+sbmSeVRNtPBjJoeW6aDnWyta36EdUh9DcxQGfupMvZTrlF7MvVaRLgGZqhMu3RU6nsiigh7MsJaRLgOqTOknl+JdukniHFfpBZhT0ZYhwjXwQwjP6dKK1euZP/+/bz66qv86Ec/4jd/8zfrDhHRnGVww+baHnvDF/PHTwd97OF+arvrv8sd9LGnrvkR1iH1NTBD5eynqdlPuUbtydRrEeEamKFy7dBRqe+JKCLsyQhrEeE6pM6Qen6l2qGfIMZ9kVqEPRlhHSJcBzPk6vsFwmlu8bqxm2WqpxeOfP2GzfnjppOdbB3dqFM9tW/k6/ezvmF/sxNhHVJfAzNoogj3RQQR9mTqtYhwDcyg8VLfE1FE2JMR1iLCdUidIfV8nS3CfZFahD0ZYR0iXAczeCh1XqVS/tTAVbvgiluAUv72kyNvYTn6eSn/+qpd+feXSilTN8dOtrKZZeznYYYZZogzDHGGjGGGOM0QZxhmmP08zGaWNfQmibIOKa+BGTRRlPsigtR7MsJapL4GZtB4Ee6JKFLvyShrkfo6RMiQer7GRLkvUku9J6OsQ+rrYAao8eXF2sucZfnHiX44sA0GD8Jrg3BBT/5WlItua+0XvKtUH3voYw+zmMdSbmM2C7iIHl5hkJc4yF62NfWFGCOsQ+prYAZNFOG+iCDCnky9FhGugRk0Xup7IooIezLCWkS4DqkzpJ6vs0W4L1KLsCcjrEOE69DOGTyUqsLM+XD9Z1OnSO8Yh3mYu5LNj7AOqa+BGTRRhPsiggh7MvVaRLgGZtB4qe+JKCLsyQhrEeE6pM6Qer7OFuG+SC3CnoywDhGuQztm8Nf3JEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4UpZlWZEDBwcH6e3thRJcMrfIybmXj0I2DKUyXDyn+PlmMEO0DKnnA5w8AmQwMDBAT09PmhCk7yeIsR6pM6SebwYzTBSho+wnM0SZb4ZYGeynXIS1MIMZosyPkqHSfkp3KCVJE4Q5lJKkSYT4jz5JmoT9JCmqqfqps8AsZ/OZUmYwQ4gMqefD2Cl6GP5NX9vvSTOYYbxQHWU/tX2G1PPNECuD/ZSLsBZmMEOU+VEyVNpPyQ6lLr4c1hwufu598+Dkj/OFSTHfDGaIliH1fIB75+bFGUWqfoIY65E6Q+r5ZjDDRJE6yn4yQ+r5ZoiVwX7KRVgLM5ghyvwoGSrtJ1/oXJIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYVL9+57qsks5rOUtVzGQi6km1c5zov0sZftHKO/LTKknm8GaXIR9qQZ0s+PkkEaL8KeNIMZpMlE2I9mMENKHkq1iIUsYznrWcxKMoYBKFNm+PXPV3In+3iInWyhjz3TMkPq+WaQJhdhT5oh/fwoGaTxIuxJM5hBmkyE/WgGM0Tgr++1gOWsZwO7uIYVlCnTQScddFIa93mZMou5hQ3s5mbWTbsMqeebQZpchD1phvTzo2SQxouwJ81gBmkyEfajGcwQhYdSwd3MOj7KZgA6mHHe7x35+mq2NHSjps6Qer4ZpMlF2JNmSD8/SgZpvAh70gxmkCYTYT+awQyReCgV2EKWsZotNT12NVtYyHtbPkPq+WaQJhdhT5oh/fwoGaTxIuxJM5hBmkyE/WgGM0RT1aHUz/7sz1Iqld7wcfvttzcrX1tbznqGOF3TY4c43ZDT09QZUs83Q2uxo4oTYU+aIf38KBlagf1UnAh70gxmaCX2U3Ei7EczmCGaqg6lnnzySY4ePTr68eijjwKwevXqpoRrZ7OYz2JWTvkUvnPpYAZLuJVZzGvZDKnnm6H12FHFiLAnzZB+fpQMrcJ+KkaEPWkGM7Qa+6kYEfajGcwQUVWHUrNnz+byyy8f/dixYwdvfetbed/73tesfG1rKWtHX3W/VhnDLOW2ls2Qer4ZWo8dVYwIe9IM6edHydAq7KdiRNiTZjBDq7GfihFhP5rBDBF11vrA1157jXvvvZd169ZRKpXO+X2nTp3i1KlTo/88ODhY68i2chkLG/BTMmazoGUzpJ5vhtZWSUfZT7WJsCfNkH5+lAytyH5qngh70gxmaGX2U/NE2I9mMENENb/Q+Z//+Z/zk5/8hLVr1573+zZt2kRvb+/ox/z582sd2VYupJtyna9DX6aDi+hp2Qyp55uhtVXSUfZTbSLsSTOknx8lQyuyn5onwp40gxlamf3UPBH2oxnMEFHNV+Gee+5hxYoVzJ0797zft3HjRgYGBkY/+vv7ax3ZVl7lOMN1Pp1vmCFeofa/uUidIfV8M7S2SjrKfqpNhD1phvTzo2RoRfZT80TYk2YwQyuzn5onwn40gxkiqunX955//nl27tzJn/3Zn035vV1dXXR1ddUypq29SF8DfkqJlzjYshlSzzdD66q0o+yn2kTYk2ZIPz9KhlZjPzVXhD1pBjO0KvupuSLsRzOYIaKanim1bds2LrvsMj784Q83Oo9et5ftlOp8Ol+JMnvZ1rIZUs83Q+uyo5orwp40Q/r5UTK0GvupuSLsSTOYoVXZT80VYT+awQwRVX0VhoeH2bZtGx//+Mfp7Kz5ddI1hWP0s58dDHG6pscPcZp9PMgxDrdshtTzzdCa7Kjmi7AnzZB+fpQMrcR+ar4Ie9IMZmhF9lPzRdiPZjBDRFUfSu3cuZNDhw7xiU98ohl5NM6jbKaDGTU9tkwHO9na8hlSzzdD67GjihFhT5oh/fwoGVqF/VSMCHvSDGZoNfZTMSLsRzOYIZqqD6U++MEPkmUZb3vb25qRR+P0sYf7WV/TY7/LHfSxp+UzpJ5vhtZjRxUjwp40Q/r5UTK0CvupGBH2pBnM0Grsp2JE2I9mMEM09f0So5puJ1tHN+pUT+0b+fr9rG/oqWnqDKnnm0GaXIQ9aYb086NkkMaLsCfNYAZpMhH2oxnMEIm/MNwCdrKV53mSm1nHEm4le/2tI8uUGWYIKFGizH4eZidbm3JimjpD6vlmkCYXYU+aIf38KBmk8SLsSTOYQZpMhP1oBjNE4aFUi+hjD33sYRbzWMptzGYBF9HDKwzyEgfZy7amv8hZ6gyp55tBmlyEPWmG9POjZJDGi7AnzWAGaTIR9qMZzBCBh1It5hiHeZi72jpD6vlmkCYXYU+aIf38KBmk8SLsSTOYQZpMhP1oBjOk5GtKSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXClLMuyIgcODg7S29sLJbhkbpGTcy8fhWwYSmW4eE7x881ghmgZUs8HOHkEyGBgYICenp40IUjfTxBjPVJnSD3fDGaYKEJH2U9miDLfDLEy2E+5CGthBjNEmR8lQ6X9lO5QSpImCHMoJUmTCPEffZI0CftJUlRT9VNngVnO5jOlzGCGEBlSz4exU/Qw/Ju+tt+TZjDDeKE6yn5q+wyp55shVgb7KRdhLcxghijzo2SotJ+SHUpdfDmsOVz83Pvmwckf5wuTYr4ZzBAtQ+r5APfOzYszilT9BDHWI3WG1PPNYIaJInWU/WSG1PPNECuD/ZSLsBZmMEOU+VEyVNpPvtC5JEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgqX7N33pFqdOAQHtsNAH5w+DjO6oXchLFoLM68oJsMs5rOUtVzGQi6km1c5zov0sZftHKO/mBCSQkrdUfbT/8/e3wfZWd/3/f/znF2x3Gh3LWMIUiQRbMkiMRJDsFMsBhnHKLGwhJOJ1TaDG4u0nTbGiRNJNFZn6pISW/EXSeP+Yoe2LpbcwTY2npABUUiQHUvKKNymIKVxlFUSrJUFhWnlXUmAkM65fn9c7I0WSXvu9vq8z57nY2bHC7vXvl9cn/fnbfHh2nMknU3q+QTOKCmiCPvSDJ3LQym1jcM7Ye9mOLgdSm8+45dVoNSVf/7snXD5SliyHmYvm5oMC1nGctaxmJVkVAEoU6b65ucruZO9PMwONjPA7qkJISmk1DPK+STpbFLPJ3BGSRFF2JdmkL++p/CyDJ7fBNtvhMFHgSz/g1RWefPrI59ncPBRePgD+R+8sqy1OZazjvXs5CpWUKZMF9100U1p3OdlyizmZtazi5tY29oAkkKKMKOcT5LOJMJ8AmeUFFGEfWkGgYdSagP7tsCTd+SfZ6fO/b0jX39ifX5dq9zEWj7GJgC6mHHO7x35+mo2O7SkDpB6RjmfJJ1N6vkEzigpogj70gwaUdehVKVS4T/8h//AFVdcwQUXXMC73vUu7rrrLrJW/+cU6U2Hd+Z/OGrEE+vhxV3NZ1jIMlazuaFrV7OZhdzQfAhNyvmkFFLPKOdT+3BGqWip5xM4o9qF86mzRNiXZtB4db2m1Be+8AXuuecevva1r/Ge97yHZ555httuu43+/n5+67d+a6oyqoPt3Qyl7sn/696ZlLrz65t9bYTlrKPCyUlPz8+kwkluYq2/e1wA55NSSD2jnE/twxmloqWeT+CMahfOp84SYV+aQePVdSi1Z88ePvrRj/KRj3wEgJ/6qZ/im9/8Jk899dSUhFNnO3Ywf0FOGvyPNNkp+OHDcGwQZs5r7GfMYh6LWUm5wd907WIGS7iFWczlCIcaC6GaOJ9UtNQzyvnUXpxRKlLq+QTOqHbifOocEfalGTRRXauwdOlSvvvd7/J3f/d3ADz//PP8xV/8BStWrJiScOps+7eNvUNMo0pl2L+18euXsmb0HRgalVFlKbc19TM0OeeTipZ6Rjmf2oszSkVKPZ/AGdVOnE+dI8K+NIMmqutJqc985jMMDw9z5ZVX0tXVRaVS4XOf+xy33nrrWa85ceIEJ06cGP3r4eHhxtOqowwNtObnDB9o/NpLWdiCBBmXsKAFP0fn4nxS0VLPKOdTe6l3Rjmf1IzU8wmcUe3E+dQ5IuxLM2iiuv4byre//W2+/vWv841vfIO/+qu/4mtf+xqbNm3ia1/72lmv2bhxI/39/aMf8+Y1+AywOs7Jo2NvWdyorAJvNPH/k+fT2/BjnSPKdHEBfU39DE3O+aSipZ5Rzqf2Uu+Mcj6pGannEzij2onzqXNE2Jdm0ER1rcQdd9zBZz7zGf75P//nLF68mH/xL/4Fv/M7v8PGjRvPes2GDRsYGhoa/RgcHGw6tDrDjF4odTX3M0pdcF4Ts+J1jlJt8tHOKhVew/+CNNWcTypa6hnlfGov9c4o55OakXo+gTOqnTifOkeEfWkGTVTXr++9+uqrlMunn2N1dXVRrZ59QXt6eujp6WksnTpafyueqgT6mniq8mVa8fx7iVdo4vl31cT5pKKlnlHOp/ZS74xyPqkZqecTOKPaifOpc0TYl2bQRHU9KbVq1So+97nP8cgjj/DCCy/w4IMPsmXLFn75l395qvKpgy1aA1lzB9hkVVjUxOvP7WEbpSYf7SxRZg9NvFKoauJ8UtFSzyjnU3txRqlIqecTOKPaifOpc0TYl2bQRHWtxB/+4R/ysY99jE9+8pP89E//NOvXr+ff/Jt/w1133TVV+dTBZs6H+SuhVNfzfGNK3XD5qsbfyhjgCIPsYzsVTjZ0fYWT7OUh3yq0AM4nFS31jHI+tRdnlIqUej6BM6qdOJ86R4R9aQZNVNf/VfX29vLFL36RL37xi1MURzrd1evh4MONXZtVYMm65jM8ziau5paGri3TxQ62NB9Ck3I+KYXUM8r51D6cUSpa6vkEzqh24XzqLBH2pRk0XnPPrElTbPYyuG5TY9ded3d+fbMG2M0DNPYns+9wBwPsbj6EpJBSzyjnk6SzST2fwBklRRRhX5pB43kopfAWrx37Q9Vkj6GPfP26Tfl1rbKDLaNDa7LHPEe+/gDrPEGXOkDqGeV8knQ2qecTOKOkiCLsSzNohIdSCq9Uyh8hX7UT5t8MlPK3KR55q+PRz0v511ftzL+/VGptjh1sYRPL2McjVKlS4RQVTpFRpcJJKpyiSpV9PMImljmspA4RYUY5nySdSYT5BM4oKaII+9IMgjpfU0pKafay/OPYIOzfCsMH4I1hOK8vf8viRbc194KctRhgNwPsZhZzWcptXMICLqCP1xjmFQ6wh62+4J3UoVLPKOeTpLNJPZ/AGSVFFGFfmkEeSqntzJwH1342bYYjHOIRfEcSSW+VekY5nySdTer5BM4oKaII+9IMnctf35MkSZIkSVLhPJSSJEmSJElS4TyUkiRJkiRJUuE8lJIkSZIkSVLhSlmWZUUWHBoa4m1vexsAF84usnLu1ZeADCjBhZcVX98MZoiWIXV9gFdfzP/3xz/+Mf39/WlCkH4+QZD1sCfNYIbTMwSYUc4nM0Spb4ZgGZxPQJC1MIMZgtQPk6HG+VT4odShQ4eYN2+K33NWUlsaHBxk7ty5yeo7nySdS8oZ5XySdC7OJ0lRTTafCj+UqlarHD58mN7eXkqlUt3XDw8PM2/ePAYHB+nr65uChGZolwyp65uhdRmyLOPo0aPMmTOHcjndbxU7n8wwnTKkrj+dMkSYUc3OJ0i/Hqnrm8EM0TI4n8akXosIGVLXN4MZWp2h1vnU3UzIRpTL5Zac4vf19SVbHDPEypC6vhlakyHlr+2NcD6ZYTpmSF1/umRIPaNaNZ8g/Xqkrm8GM0TL4Hwak3otImRIXd8MZmhlhlrmky90LkmSJEmSpMJ5KCVJkiRJkqTCtd2hVE9PD//xP/5Henp6zNDhGVLXN0OsDBFEuA9mMEOU+maIJ/W9SF3fDGaIliF1/Ugi3IvUGVLXN4MZUmUo/IXOJUmSJEmSpLZ7UkqSJEmSJEntz0MpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVrq0Opf7yL/+Srq4uPvKRjxRee82aNZRKpdGPiy++mA9/+MPs3bu38CwvvfQSv/mbv8k73/lOenp6mDdvHqtWreK73/3ulNcefx9mzJjBT/zET7B8+XK++tWvUq1Wp7z+xAzjPz784Q8XUn+yHAcOHCik/ksvvcSnP/1pFixYwPnnn89P/MRPcP3113PPPffw6quvTnn9NWvW8Eu/9Etv+fvf//73KZVK/PjHP57yDNE4o5xPE3OkmlGp5xOknVHOp7dyPjmfJuZwPvlnqCicT86niTmcT501n9rqUOree+/lN3/zN9m1axeHDx8uvP6HP/xhXnzxRV588UW++93v0t3dzcqVKwvN8MILL3Dttdfyve99j7vvvpt9+/bx2GOP8cEPfpDbb7+9kAwj9+GFF17g0Ucf5YMf/CCf/vSnWblyJadOnSo0w/iPb37zm4XUnizHFVdcMeV1/+Ef/oFrrrmGP/uzP+Pzn/88/+t//S/+8i//kn/37/4d27dvZ8eOHVOeQW/V6TPK+fTWHClnVKr5BM6oiJxPzqeJOZxPzqconE/Op4k5nE+dNZ+6Uweo1bFjx/jWt77FM888w0svvcS2bdv49//+3xeaoaenh8suuwyAyy67jM985jPccMMNvPLKK1xyySWFZPjkJz9JqVTiqaee4qKLLhr9++95z3v49V//9UIyjL8PP/mTP8nP/uzPct111/GhD32Ibdu28a/+1b8qNENKqXJ88pOfpLu7m2eeeea0PnjnO9/JRz/6UbIsKzxTp3NGOZ/OliOVlBmcUbE4n5xPZ8uRivNJI5xPzqez5UjF+VS8tnlS6tvf/jZXXnklixYt4uMf/zhf/epXky7KsWPHuO+++1iwYAEXX3xxITX/3//7fzz22GPcfvvtpzXpiLe97W2F5DiTn//5n+fqq6/mj//4j5Nl6BT/9//+X/7sz/7srH0AUCqVCk6lTp9RzieNcEbF43xyPinnfIrH+eR8Uq6T51PbHErde++9fPzjHwfyR+qGhobYuXNnoRm2b9/OzJkzmTlzJr29vTz00EN861vfolwu5jYeOHCALMu48sorC6lXryuvvJIXXnihkFrj12Lk4/Of/3whtc+VY/Xq1VNec6QPFi1adNrff8c73jGa43d/93enPAeceR1WrFhRSO1oOn1GOZ9OF2FGpZhPEGdGOZ/GOJ+cT+M5n9LPJ3BGjXA+OZ/Gcz515nxqi1/f279/P0899RQPPvggAN3d3fyzf/bPuPfee7nxxhsLy/HBD36Qe+65B4AjR47wR3/0R6xYsYKnnnqKyy+/fMrrR39cL8uywk5vx6/FiLe//e2F1D5XjrOdahfhqaeeolqtcuutt3LixIlCap5pHZ588snRP1x0CmeU82miCDMq0nyC4meU8ynnfHI+TeR8eiv/DJWG88n5NJHz6a06YT61xaHUvffey6lTp5gzZ87o38uyjJ6eHr70pS/R399fSI6LLrqIBQsWjP71f//v/53+/n6+8pWv8Pu///tTXn/hwoWUSiX+9m//dsprNeIHP/hBYS8CN3EtUkmRY8GCBZRKJfbv33/a33/nO98JwAUXXFBYljP98x86dKiw+lE4o5xPE0WYUakyRJlRzqec88n5NJHzKf18AmcUOJ/A+TSR86kz51P4X987deoU/+N//A82b97Mc889N/rx/PPPM2fOnCTvuDaiVCpRLpd57bXXCqn39re/nV/8xV/ky1/+MsePH3/L11O+fez3vvc99u3bx6/8yq8ky9ApLr74YpYvX86XvvSlM/aBiuWMyjmfNMIZFYfzKed80gjnUxzOp5zzSSM6eT6Ff1Jq+/btHDlyhH/5L//lW07Lf+VXfoV7772Xf/tv/20hWU6cOMFLL70E5I92fulLX+LYsWOsWrWqkPoAX/7yl7n++uv5uZ/7Of7Tf/pPLFmyhFOnTvH4449zzz338IMf/GDKM4zch0qlwv/5P/+Hxx57jI0bN7Jy5Up+7dd+bcrrj88wXnd3N+94xzsKqZ/aH/3RH3H99dfz3ve+lzvvvJMlS5ZQLpd5+umn+du//Vuuvfba1BE7hjNqjPPprTnGc0Y5o4rmfBrjfHprjvGcT86nojmfxjif3ppjPOdTB8ynLLiVK1dmN9988xm/9uSTT2ZA9vzzz095jk984hMZMPrR29ubve9978u+853vTHntiQ4fPpzdfvvt2eWXX56dd9552U/+5E9mt9xyS/bnf/7nU157/H3o7u7OLrnkkuymm27KvvrVr2aVSmXK60/MMP5j0aJFhdQfn+OjH/1ooTXHO3z4cPapT30qu+KKK7IZM2ZkM2fOzH7u534uu/vuu7Pjx49Pef2z/fP/+Z//eQZkR44cmfIMETijTtfp82lijlQzKvV8yrK0M8r5lHM+nc755Hwa4Z+h0nM+nc755Hwa0YnzqZRlwV9dTZIkSZIkSdNO+NeUkiRJkiRJ0vTjoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrXXXTBarXK4cOH6e3tpVQqFV1eUkBZlnH06FHmzJlDuZzurNz5JOlMIswo55OkM3E+SYqq1vlU+KHU4cOHmTdvXtFlJbWBwcFB5s6dm6y+80nSuaScUc4nSefifJIU1WTzqfBDqd7e3tHPL5xddHV49SUgA0pw4WXF1zeDGaJlSF0f4NUX8/8dPx9SSD2fIMh62JNmMMPpGQLMKOeTGaLUN0OwDM4nIMhamMEMQeqHyVDjfCr8UGrkkc4LZ8PHDxddHb4+F47/CC6aA7ceKr6+GcwQLUPq+gD3zcmHVupHvlPPJ4ixHqkzpK5vBjNMFGFGOZ/MEKW+GWJlcD7lIqyFGcwQpX6UDLXOJ1/oXJIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYUr/IXOGzWLeSxlDZeykPPp5XWO8jID7GEbRxhMHU9SB3M+SYrMGSUpKueTpPCHUgtZxnLWsZiVZFQBKFOm+ubnK7mTvTzMDjYzwO6UUSV1GOeTpMicUZKicj5JGhH61/eWs4717OQqVlCmTBfddNFNadznZcos5mbWs4ubWJs6sqQO4XySFJkzSlJUzidJ44U9lLqJtXyMTQB0MeOc3zvy9dVsdmhJmnLOJ0mROaMkReV8kjRR3YdSu3btYtWqVcyZM4dSqcSf/MmftDzUQpaxms0NXbuazSzkhhYnktQOnE+SoipiPoEzSlL9nE+SUqr7UOr48eNcffXVfPnLX56KPED+SGeFkw1dW+GkJ+lSh3I+SYqqiPkEzihJ9XM+SUqp7hc6X7FiBStWrJiKLED+DgyLWUm5wd8s7GIGS7iFWczlCIdanE5SZM4nSVFN9XwCZ5SkxjifJKUU7jWllrJm9B0YGpVRZSm3tSiRJOWcT5Iic0ZJisr5JOls6n5Sql4nTpzgxIkTo389PDx8zu+/lIUtqJpxCQta8HMkTWfOJ0lR1TufwBklqRjOJ0mtNOVPSm3cuJH+/v7Rj3nz5p3z+8+nt+HHOkeU6eIC+pr6GZKmP+eTpKjqnU/gjJJUDOeTpFaa8kOpDRs2MDQ0NPoxODh4zu9/naNUm3y0s0qF15j8xF5SZ3M+SYqq3vkEzihJxXA+SWqlKf/1vZ6eHnp6emr+/pcZaEHVEq9woAU/R9J05nySFFW98wmcUZKK4XyS1Ep1Pyl17NgxnnvuOZ577jkA/vEf/5HnnnuOgwcPtiTQHrZRavIBrhJl9rC1JXkktQ/nk6Sopno+gTNKUmOcT5JSqnsyPPPMM1xzzTVcc801AKxdu5ZrrrmGz372sy0JdIRB9rGdCicbur7CSfbykG8VKnUg55OkqKZ6PoEzSlJjnE+SUqr71/duvPFGsiybiiyjHmcTV3NLQ9eW6WIHW1qcSFI7cD5JiqqI+QTOKEn1cz5JSmnKX+i8EQPs5gHWNXTtd7iDAXa3OJEk5ZxPkiJzRkmKyvkk6UxCHkoB7GDL6NCa7DHPka8/wDpP0CVNOeeTpMicUZKicj5JmmjK332vGTvYwg95mptYyxJuIXvzbUTLlKlSAUqUKLOPR9jBFk/PJRXG+SQpMmeUpKicT5LGC30oBfljngPsZhZzWcptXMICLqCP1xjmFQ6wh62+4J2kJJxPkiJzRkmKyvkkaUT4Q6kRRzjEI9yVOoYkvYXzSVJkzihJUTmfJIV9TSlJkiRJkiRNXx5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcKUsy7IiCw4PD9Pf3w8luGhOkZVzr74IWRVKZbhwdvH1zWCGaBlS1wc4fhjIYGhoiL6+vjQhSD+fIMZ6pM6Qur4ZzDBRhBnlfDJDlPpmiJXB+ZSLsBZmMEOU+lEy1Dqf0h1KSdIEYQ6lJOkMQvxLnySdgfNJUlSTzafuArOczielzGCGEBlS14exU/Qw/C99Hd+TZjDDeKFmlPOp4zOkrm+GWBmcT7kIa2EGM0SpHyVDrfMp2aHUhZfBrYeKr/v1uXD8R/nCpKhvBjNEy5C6PsB9c/LBGUWq+QQx1iN1htT1zWCGiSLNKOeTGVLXN0OsDM6nXIS1MIMZotSPkqHW+eQLnUuSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlw6d59r06zmMdS1nApCzmfXl7nKC8zwB62cYTBjslw7CDs3wZDA3DyKMzohf6FsGgNzJxfSAQRYx3MEEeE2RAhg/0QQ4R1MEMsqedD6vpgP0QSYS1SZ0hdP5II8yF1htT1o2SIIMLe7MQM4Q+lFrKM5axjMSvJqAJQpkz1zc9Xcid7eZgdbGaA3dM2w+GdsHczHNyev60jQFaBUlf++bN3wuUrYcl6mL1sSiKIGOtghjgizIYIGeyHGCKsgxliST0fUtcH+yGSCGuROkPq+pFEmA+pM6SuHyVDBBH2ZidnCP3re8tZx3p2chUrKFOmi2666KY07vMyZRZzM+vZxU2snXYZsgye3wTbb4TBR4Esb4ys8ubXRz7P4OCj8PAH8kbKspbG6HgR1sEMsaSeDREy2A8xRFgHM8STej6krm8/xBFhLVJnSF0/mtTzIUKG1PWjZEgtwt40Q+BDqZtYy8fYBEAXM875vSNfX83mlm6WCBn2bYEn78g/z06d+3tHvv7E+vw6tU6EdTBDHBFmQ4QM9kMMEdbBDLGkng+p64P9EEmEtUidIXX9SCLMh9QZUtePkiGCCHvTDEEPpRayjNVsbuja1WxmITdMiwyHd+aL3Ygn1sOLu5qOIGKsgxniiDAbImSwH2KIsA5miCX1fEhdH+yHSCKsReoMqetHEmE+pM6Qun6UDBFE2JtmyNV1KLVx40be97730dvby6WXXsov/dIvsX///uZTTLCcdVQ42dC1FU625AQ3Qoa9m6HU4Kt+lbrz69W8COtghsk5n4rNEL0fOkWEdTBDbTplRqWuD+3RD50iwlqkzpC6fi06ZT5FyJC6fpQMEUTYm2bI1XUotXPnTm6//XaeeOIJHn/8cU6ePMkv/MIvcPz48eaTvGkW81jMykkfIzybLmawhFuYxdy2znDsYP4CY5M9Pnc22Sn44cNwrHPeLGFKRFgHM9TG+VRchnboh04QYR3MULtOmFGp60P79EMniLAWqTOkrl+rTphPETKkrh8lQwQR9qYZxtR1KPXYY4+xZs0a3vOe93D11Vezbds2Dh48yLPPPttcinGWsmb0lf8blVFlKbe1dYb928Ze8b5RpTLs39rcz+h0EdbBDLVxPhWXoR36oRNEWAcz1K4TZlTq+tA+/dAJIqxF6gyp69eqE+ZThAyp60fJEEGEvWmGMQ0+qJUbGhoC4O1vf/tZv+fEiROcOHFi9K+Hh4fP+TMvZWEzkd6UcQkLGr46QoahgRZEAIYPtObndKoI62CGxjifpi5DO/bDdBRhHczQuMlmVL3zCdLPh9T1oX37YTqKsBapM6Su36jpOJ8iZEhdP0qGCCLsTTOMafhcrFqt8tu//dtcf/31XHXVVWf9vo0bN9Lf3z/6MW/evHP+3PPppdzk66+X6eIC+hq+PkKGk0fH3oKxUVkF3pj8/yN0DhHWwQz1cz5NbYZ264fpKsI6mKExtcyoeucTpJ8PqetDe/bDdBVhLVJnSF2/EdN1PkXIkLp+lAwRRNibZhjTcEfefvvt/PVf/zX333//Ob9vw4YNDA0NjX4MDp77Fw5f5yjVJh8prFLhNRq/MxEyzOiFUldTESh1wXntPS+Si7AOZqif82lqM7RbP0xXEdbBDI2pZUbVO58g/XxIXR/asx+mqwhrkTpD6vqNmK7zKUKG1PWjZIggwt40w5iGfn3vU5/6FNu3b2fXrl3MnXvuFznr6emhp6en5p/9Mq14hqzEKzT+DFmEDP2teLIS6GvvJyuTi7AOZqiP82nqM7RTP0xnEdbBDPWrdUbVO58g/XxIXR/arx+mswhrkTpD6vr1ms7zKUKG1PWjZIggwt40w5i6npTKsoxPfepTPPjgg3zve9/jiiuuaK76GexhG6UmHyksUWYPjb/aVoQMi9ZA1twhNlkVFrX3a9AlF2EdzFDjz3c+FZahHfqhE0RYBzPUUaMDZlTq+tA+/dAJIqxF6gyp69dcowPmU4QMqetHyRBBhL1phjF1deTtt9/Offfdxze+8Q16e3t56aWXeOmll3jttdeaSzHOEQbZx3YqnGzo+gon2ctDHOFQW2eYOR/mr4RSgy9FX+qGy1fBzMl/xVvnEGEdzFAb51NxGdqhHzpBhHUwQ+06YUalrg/t0w+dIMJapM6Qun6tOmE+RciQun6UDBFE2JtmGFPXodQ999zD0NAQN954I7Nnzx79+Na3vtVcigkeZxNdzGjo2jJd7GDLtMhw9XrITjV2bVaBJeuajiBirIMZJud8KjZD9H7oFBHWwQy16ZQZlbo+tEc/dIoIa5E6Q+r6teiU+RQhQ+r6UTJEEGFvmiFX96/vneljzZo1zScZZ4DdPEBj/3Tf4Q4G2D0tMsxeBtdtauza6+7Or1fzIqyDGSbnfCo2Q/R+6BQR1sEMtemUGZW6PrRHP3SKCGuROkPq+rXolPkUIUPq+lEyRBBhb5oh19wvlE6hHWwZ3SyTPV448vUHWNfSk9sIGRavHWuSyR6rG/n6dZvy69Q6EdbBDHFEmA0RMtgPMURYBzPEkno+pK4P9kMkEdYidYbU9SOJMB9SZ0hdP0qGCCLsTTMEPpSCfLNsYhn7eIQqVSqcosIpMqpUOEmFU1Spso9H2MSyKdkkqTOUSvkjcat2wvybgVL+tosjb904+nkp//qqnfn3l0otjdHxIqyDGWJJPRsiZLAfYoiwDmaIJ/V8SF3ffogjwlqkzpC6fjSp50OEDKnrR8mQWoS9aQZo8CWtijPAbgbYzSzmspTbuIQFXEAfrzHMKxxgD1un/IXWImSYvSz/ODYI+7fC8AF4YxjO68vfgnHRbb4oZxEirIMZ4ogwGyJksB9iiLAOZogl9XxIXR/sh0girEXqDKnrRxJhPqTOkLp+lAwRRNibnZwh/KHUiCMc4hHu6vgMM+fBtZ9NGkHEWAczxBFhNkTIYD/EEGEdzBBL6vmQuj7YD5FEWIvUGVLXjyTCfEidIXX9KBkiiLA3OzFD6F/fkyRJkiRJ0vTkoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKV8qyLCuy4PDwMP39/VCCi+YUWTn36ouQVaFUhgtnF1/fDGaIliF1fYDjh4EMhoaG6OvrSxOC9PMJYqxH6gyp65vBDBNFmFHOJzNEqW+GWBmcT7kIa2EGM0SpHyVDrfMp3aGUJE0Q5lBKks4gxL/0SdIZOJ8kRTXZfOouMMvpfFLKDGYIkSF1fRg7RQ/D/9LX8T1pBjOMF2pGOZ86PkPq+maIlcH5lIuwFmYwQ5T6UTLUOp+SHUpdeBnceqj4ul+fC8d/lC9MivpmMEO0DKnrA9w3Jx+cUaSaTxBjPVJnSF3fDGaYKNKMcj6ZIXV9M8TK4HzKRVgLM5ghSv0oGWqdT77QuSRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgqX7t336jSLeSxlDZeykPPp5XWO8jID7GEbRxgsJMOxg7B/GwwNwMmjMKMX+hfCojUwc34hEbwPGuU6xOG+zHkfNMJ1iCX13ozQD6nvAcS4D8q5FnG4N2PcgwgZlEvdjymEP5RayDKWs47FrCSjCkCZMtU3P1/JnezlYXawmQF2T0mGwzth72Y4uD1/S0WArAKlrvzzZ++Ey1fCkvUwe9mURPA+aJTrEIf7Mud90AjXIZbUezNCP6S+BxDjPijnWsTh3oxxDyJkUC51P6YU+tf3lrOO9ezkKlZQpkwX3XTRTWnc52XKLOZm1rOLm1jb0vpZBs9vgu03wuCjQJY3RlZ58+sjn2dw8FF4+AN5I2VZS2N4HwS4DtG4L3PeB4HrEFHKvRmlH5xPGuFaxOLeTH8PomRQjH5MLeyh1E2s5WNsAqCLGef83pGvr2ZzSzfLvi3w5B3559mpc3/vyNefWJ9f1yreB41wHeJwX+a8DxrhOsSSem9G6IfU9wBi3AflXIs43Jsx7kGEDMql7scI6jqUuueee1iyZAl9fX309fXx/ve/n0cffbTloRayjNVsbuja1WxmITc0neHwznyxG/HEenhxV9MRvA8a5TpMzvlUG+dTrlP2RRFch9p0yoyK0A+p7wHEuA/KuRaT65T5BOn7IcI9iJBBudT9GEVdh1Jz587lD/7gD3j22Wd55pln+Pmf/3k++tGP8r//9/9uaajlrKPCyYaurXCyJSe4ezdDqcFX3Cp159c3y/ugEa7D5JxPtXE+5TplXxTBdahNp8yoCP2Q+h5AjPugnGsxuU6ZT5C+HyLcgwgZlEvdj1HUdSi1atUqbr75ZhYuXMi73/1uPve5zzFz5kyeeOKJlgWaxTwWs3LSxwjPposZLOEWZjG34QzHDuYvMDbZ43Nnk52CHz4Mx5p4owLvg0a4DrVxPtXG+ZTrlH0x1VyH2nXCjIrQD6nvAcS4D8q5FrXphPkE6fshwj2IkEG51P0YScOvKVWpVLj//vs5fvw473//+1sWaClrRl/5v1EZVZZyW8PX79829or3jSqVYf/Wxq/3PmiE61A/59O5OZ9ynbYvpoLr0JjpOqMi9EPqewAx7oNyrkX9put8gvT9EOEeRMigXOp+jKTuh8X27dvH+9//fl5//XVmzpzJgw8+yM/8zM+c9ftPnDjBiRMnRv96eHj4nD//UhbWG+kMMi5hQcNXDw20IAIwfKDxa70PGuE61M75VDvnU64T9sVUch3qU8+Mqnc+Qfq9GaEfUt8DiHEflHMtajfd5xOk74cI9yBCBuVS92MkdZ/NLVq0iOeee44nn3yS3/iN3+ATn/gEf/M3f3PW79+4cSP9/f2jH/PmzTvnzz+fXspNvilgmS4uoK/h608eHXsLxkZlFXhj8vl8Vt4HjXAdaud8qo3zKdcp+2IquQ71qWdG1TufIP3ejNAPqe8BxLgPyrkWtZvu8wnS90OEexAhg3Kp+zGSujvyvPPOY8GCBVx77bVs3LiRq6++mv/8n//zWb9/w4YNDA0NjX4MDp77lx5f5yjVJh8prFLhNRpfnRm9UOpqKgKlLjivib3qfdAI16F2zqfaOJ9ynbIvppLrUJ96ZlS98wnS780I/ZD6HkCM+6Cca1G76T6fIH0/RLgHETIol7ofI2nwtd7HVKvV0x7fnKinp4eenp6af97LtOI5thKv0PhzbP2teKoR6GviqUbvg0a4Do1zPp2d8ynXifuilVyH5pxrRtU7nyD93ozQD6nvAcS4D8q5Fo2bbvMJ0vdDhHsQIYNyqfsxkrqelNqwYQO7du3ihRdeYN++fWzYsIHvf//73HrrrS0LtIdtlJp8pLBEmT00/opfi9ZA1twBMlkVFjXx+m/eB41wHWrjfKqd8ynXCftiqrkOteuEGRWhH1LfA4hxH5RzLWrTCfMJ0vdDhHsQIYNyqfsxkro68uWXX+bXfu3XWLRoER/60Id4+umn+dM//VOWL1/eskBHGGQf26lwsqHrK5xkLw9xhEMNZ5g5H+avhFKDz5GVuuHyVTBz8l+vPivvg0a4DrVxPtXG+ZTrlH0x1VyH2nXCjIrQD6nvAcS4D8q5FrXphPkE6fshwj2IkEG51P0YSV234N57752qHKd5nE1czS0NXVumix1saTrD1evh4MONXZtVYMm6piN4HzTKdZic86k2zqdcp+yLIrgOtemUGRWhH1LfA4hxH5RzLSbXKfMJ0vdDhHsQIYNyqfsxiuae3ZsiA+zmARq7w9/hDgbY3XSG2cvguk2NXXvd3fn1zfI+aITrEIf7Mud90AjXIZbUezNCP6S+BxDjPijnWsTh3oxxDyJkUC51P0YR8lAKYAdbRjfLZI8Xjnz9Ada19OR28dqxJpnssbqRr1+3Kb+uVbwPGuE6xOG+zHkfNMJ1iCX13ozQD6nvAcS4D8q5FnG4N2PcgwgZlEvdjxGEPZSCfLNsYhn7eIQqVSqcosIpMqpUOEmFU1Spso9H2MSylm+SUil/JG7VTph/M1DK33Zx5K0bRz8v5V9ftTP//lKppTG8DwJch2jclznvg8B1iCjl3ozSD84njXAtYnFvpr8HUTIoRj+m1uDLahVngN0MsJtZzGUpt3EJC7iAPl5jmFc4wB62TvkLrc1eln8cG4T9W2H4ALwxDOf15W/BuOi2qX+BMe+DRrgOcbgvc94HjXAdYkm9NyP0Q+p7ADHug3KuRRzuzRj3IEIG5VL3Y0rhD6VGHOEQj3BX0gwz58G1n00awfugUa5DHO7LnPdBI1yHWFLvzQj9kPoeQIz7oJxrEYd7M8Y9iJBBudT9mELoX9+TJEmSJEnS9OShlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSClfKsiwrsuDw8DD9/f1QgovmFFk59+qLkFWhVIYLZxdf3wxmiJYhdX2A44eBDIaGhujr60sTgvTzCWKsR+oMqeubwQwTRZhRziczRKlvhlgZnE+5CGthBjNEqR8lQ63zKd2hlCRNEOZQSpLOIMS/9EnSGTifJEU12XzqLjDL6XxSygxmCJEhdX0YO0UPw//S1/E9aQYzjBdqRjmfOj5D6vpmiJXB+ZSLsBZmMEOU+lEy1Dqfkh1KXXgZ3Hqo+LpfnwvHf5QvTIr6ZjBDtAyp6wPcNycfnFGkmk8QYz1SZ0hd3wxmmCjSjHI+mSF1fTPEyuB8ykVYCzOYIUr9KBlqnU++0LkkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKl+7d9+o0i3ksZQ2XspDz6eV1jvIyA+xhG0cYLCTDsYOwfxsMDcDJozCjF/oXwqI1MHN+IRFCZEi9FhHugRniZIgg9Z6AGGsRIYNrkb6+GeJJvS8irEWEDKnXAWLcBzOkrx+J+yJ9fXAdzJA2Q/hDqYUsYznrWMxKMqoAlClTffPzldzJXh5mB5sZYPeUZDi8E/ZuhoPb87dUBMgqUOrKP3/2Trh8JSxZD7OXTUmEEBlSr0WEe2CGOBkiSL0nIMZaRMjgWqSvb4Z4Uu+LCGsRIUPqdYAY98EM6etH4r5IXx9cBzPEyBD61/eWs4717OQqVlCmTBfddNFNadznZcos5mbWs4ubWNvS+lkGz2+C7TfC4KNAli9KVnnz6yOfZ3DwUXj4A/kiZtn0ygBp1yLCPTBDnAxROJ9iZADXInV9M8Tk/2+nzwDOJzPEqB9Np++L1PVHdPo6mCFOhrCHUjexlo+xCYAuZpzze0e+vprNLd0s+7bAk3fkn2enzv29I19/Yn1+3XTKkHotItwDM8TJEEHqPQEx1iJCBtcifX0zxJN6X0RYiwgZUq8DxLgPZkhfPxL3Rfr64DqYIVaGkIdSC1nGajY3dO1qNrOQG5rOcHhnfqMb8cR6eHFX0xFCZEi9FhHugRniZIgg9Z6AGGsRIYNrkb6+GeJJvS8irEWEDKnXAWLcBzOkrx+J+yJ9fXAdzBAvQ1OHUn/wB39AqVTit3/7t5tPMs5y1lHhZEPXVjjZkhPcvZuh1OArbpW68+unQ4bUaxHhHpghToZ6OJ/ObDr1g2uRvr4ZGjNV8wnS74sIaxEhQ+p1gBj3wQzp6zfCP0Od2XTpB9fBDNEyNHwo9fTTT/Nf/+t/ZcmSJc2nGGcW81jMykkfIzybLmawhFuYxdyGMxw7mL+412SPrp1Ndgp++DAca+KNCiJkSL0WEe6BGeJkqIfz6eymSz+4Funrm6ExUzWfIP2+iLAWETKkXgeIcR/MkL5+I/wz1NlNh35wHcwQLQM0eCh17Ngxbr31Vr7yla8wa9as5hJMsJQ1o6/836iMKku5reHr928be7X5RpXKsH9r49dHyJB6LSLcAzPEyVAr59PkpkM/uBbp65uhflM5nyD9voiwFhEypF4HiHEfzJC+fr38M9Tk2r0fXAczRMsADR5K3X777XzkIx/hpptumvR7T5w4wfDw8Gkf53IpCxuJNEHGJSxo+OqhgRZEAIYPNH5thAyp1yLCPTBDnAy1cj7Vpt37wbVIX98M9ZvK+QTp90WEtYiQIfU6QIz7YIb09etV64xqx/kE6dcjdX1wHcwQLwNA3b89eP/99/NXf/VXPP300zV9/8aNG/m93/u9mn/++fRSbvL118t0cQF9DV9/8ujY2x82KqvAG5PP59AZUq9FhHtghjgZauF8qs106AfXIn19M9RnqucTpN8XEdYiQobU6wAx7oMZ0tevRz0zqh3nE6Rfj9T1wXUwQ7wMUOeTUoODg3z605/m61//Oueff35N12zYsIGhoaHRj8HBc//C4escpdrkI4VVKrxG43dmRi+UupqKQKkLzmt8r4bIkHotItwDM8TJMBnnU+2mQz+4Funrm6F2RcwnSL8vIqxFhAyp1wFi3AczpK9fq3pnVDvOJ0i/Hqnrg+tghngZoM4npZ599llefvllfvZnf3b071UqFXbt2sWXvvQlTpw4QVfX6f9UPT099PT01FzjZVrxDFmJV2j8GbL+VjzVCPQ1/lRjiAyp1yLCPTBDnAyTcT7Vp937wbVIX98MtStiPkH6fRFhLSJkSL0OEOM+mCF9/VrVO6PacT5B+vVIXR9cBzPEywB1Pin1oQ99iH379vHcc8+Nfrz3ve/l1ltv5bnnnnvLH6gasYdtlJp8pLBEmT00/mpbi9ZA1twBMlkVFjX++m8hMqReiwj3wAxxMkzG+VS76dAPrkX6+maoXRHzCdLviwhrESFD6nWAGPfBDOnr18o/Q9Wu3fvBdTBDtAxQ56FUb28vV1111WkfF110ERdffDFXXXVVc0nedIRB9rGdCicbur7CSfbyEEc41HCGmfNh/koo1f2KW7lSN1y+CmbOazhCiAyp1yLCPTBDnAyTcT7VZrr0g2uRvr4ZalfEfIL0+yLCWkTIkHodIMZ9MEP6+rXyz1C1mQ794DqYIVoGaPDd96ba42yiixkNXVumix1saTrD1eshO9XYtVkFlqxrOkKIDKnXIsI9MEOcDBGk3hMQYy0iZHAt0tc3Qzyp90WEtYiQIfU6QIz7YIb09SNxX6SvD66DGeJlaPpQ6vvf/z5f/OIXm08yzgC7eYDG/um+wx0MsLvpDLOXwXWbGrv2urvz66dDhtRrEeEemCFOhno5n95qOvWDa5G+vhkaNxXzCdLviwhrESFD6nWAGPfBDOnrN8o/Q73VdOkH18EM0TKEfFIKYAdbRjfLZI8Xjnz9Ada15OR2xOK1Yws02SNtI1+/blN+3XTKkHotItwDM8TJEEHqPQEx1iJCBtcifX0zxJN6X0RYiwgZUq8DxLgPZkhfPxL3Rfr64DqYIVaGsIdSkG+WTSxjH49QpUqFU1Q4RUaVCiepcIoqVfbxCJtY1tJNAlAq5Y+jrdoJ828GSvlbHo68beLo56X866t25t9fKk2vDJB2LSLcAzPEyRCF8ylGBnAtUtc3Q0z+/3b6DOB8MkOM+tF0+r5IXX9Ep6+DGeJkaPAlrYozwG4G2M0s5rKU27iEBVxAH68xzCscYA9bm3qhtVrMXpZ/HBuE/Vth+AC8MQzn9eVvf7jotql/AcIIGVKvRYR7YIY4GSJIvScgxlpEyOBapK9vhnhS74sIaxEhQ+p1gBj3wQzp60fivkhfH1wHM8TIEP5QasQRDvEIdyXNMHMeXPvZpBFCZEi9FhHugRniZIgg9Z6AGGsRIYNrkb6+GeJJvS8irEWEDKnXAWLcBzOkrx+J+yJ9fXAdzJA2Q+hf35MkSZIkSdL05KGUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSClfKsiwrsuDw8DD9/f1QgovmFFk59+qLkFWhVIYLZxdf3wxmiJYhdX2A44eBDIaGhujr60sTgvTzCWKsR+oMqeubwQwTRZhRziczRKlvhlgZnE+5CGthBjNEqR8lQ63zKd2hlCRNEOZQSpLOIMS/9EnSGTifJEU12XzqLjDL6XxSygxmCJEhdX0YO0UPw//S1/E9aQYzjBdqRjmfOj5D6vpmiJXB+ZSLsBZmMEOU+lEy1Dqfkh1KXXgZ3Hqo+LpfnwvHf5QvTIr6ZjBDtAyp6wPcNycfnFGkmk8QYz1SZ0hd3wxmmCjSjHI+mSF1fTPEyuB8ykVYCzOYIUr9KBlqnU++0LkkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKl+7d9+o0i3ksZQ2XspDz6eV1jvIyA+xhG0cYLCTDsYOwfxsMDcDJozCjF/oXwqI1MHN+IRHMQIxekMaL0JOp96UZxkToB2m81D0ZYV+aIZe6F6SJIvRk6r2Zun6UDBF6QWmEP5RayDKWs47FrCSjCkCZMtU3P1/JnezlYXawmQF2T0mGwzth72Y4uD1/S0WArAKlrvzzZ++Ey1fCkvUwe9mURDADMXpBGi9CT6bel2YYE6EfpPFS92SEfWmGXOpekCaK0JOp92bq+lEyROgFpRX61/eWs4717OQqVlCmTBfddNFNadznZcos5mbWs4ubWNvS+lkGz2+C7TfC4KNAlm/SrPLm10c+z+Dgo/DwB/JNnWVmaHWG1L0gTZS6JyPsSzOMSd0P0kQpezLCvjTDGOeTokndk6n3Zur6UTJA+l5QDGEPpW5iLR9jEwBdzDjn9458fTWbW9qo+7bAk3fkn2enzv29I19/Yn1+nRlalyFCL0jjRejJ1PvSDGMi9IM0XuqejLAvzZBL3QvSRBF6MvXeTF0/SoYIvaAYQh5KLWQZq9nc0LWr2cxCbmg6w+Gd+cZrxBPr4cVdTUcwAzF6QRovQk+m3pdmGBOhH6TxUvdkhH1phlzqXpAmitCTqfdm6vpRMkToBcVR16HUnXfeSalUOu3jyiuvbHmo5ayjwsmGrq1wsiWnp3s3Q6nBV9wqdefXm6H5DBF6Qe3B+VSb6TIbomSI0A9qD50yoyLsSzPkUveC2kenzCdIvzdT14+SIUIvKI66n5R6z3vew4svvjj68Rd/8RctDTSLeSxm5aSP8J1NFzNYwi3MYm7DGY4dzF/sbbJHGc8mOwU/fBiONfEmAWaI0QtqL86nyU2H2RAlQ4R+UHuZ7jMqwr40Qy51L6j9TPf5BOn3Zur6UTJE6AXFUvehVHd3N5dddtnoxzve8Y6WBlrKmtFX3W9URpWl3Nbw9fu3jb37QKNKZdi/tfHrzRCjF9RenE+1affZECVDhH5Qe5nuMyrCvjRDLnUvqP1M9/kE6fdm6vpRMkToBcVSd0sODAwwZ84c3vnOd3Lrrbdy8ODBc37/iRMnGB4ePu3jXC5lYb2RziDjEhY0fPXQQAsiAMMHGr/WDDF6Qe3F+VS7dp4NUTJE6Ae1l3pmVL3zCdL3ZIR9aYZc6l5Q+5nu8wnS783U9aNkiNALiqWuQ6l/8k/+Cdu2beOxxx7jnnvu4R//8R+54YYbOHr06Fmv2bhxI/39/aMf8+bNO2eN8+ml3OTrr5fp4gL6Gr7+5NGxt8NsVFaBNyafz2Y4hwi9oPbhfKpdu8+GKBki9IPaR70zqt75BOl7MsK+NEMudS+ovXTCfIL0ezN1/SgZIvSCYqmrG1asWMHq1atZsmQJv/iLv8j//J//kx//+Md8+9vfPus1GzZsYGhoaPRjcPDcv4D6OkepNvk4X5UKr9H4TpnRC6WupiJQ6oLzmtgnZojRC2ofzqfatftsiJIhQj+ofdQ7o+qdT5C+JyPsSzPkUveC2ksnzCdIvzdT14+SIUIvKJYGX3c/97a3vY13v/vdHDhw9uf3enp66Onpqflnvkwrniks8QqNP1PY34onCoG+Jp4oNEOMXlD7cj6dWzvPhigZIvSD2tdkM6re+QTpezLCvjRDLnUvqL1Nx/kE6fdm6vpRMkToBcXS1HNzx44d4+///u+ZPXt2q/Kwh22Umnycr0SZPTT+6muL1kDW3OEtWRUWNfHaa2aI0QtqX86ns2v32RAlQ4R+UPuajjMqwr40Qy51L6i9Tcf5BOn3Zur6UTJE6AXFUlc3rF+/np07d/LCCy+wZ88efvmXf5muri5+9Vd/tWWBjjDIPrZT4WRD11c4yV4e4giHGs4wcz7MXwmlBp8jK3XD5atg5uS/Xm2Gc4jQC2ofzqfaTIfZECVDhH5Q++iEGRVhX5ohl7oX1F46YT5B+r2Zun6UDBF6QbHUdSh16NAhfvVXf5VFixbxT//pP+Xiiy/miSee4JJLLmlpqMfZRBczGrq2TBc72NJ0hqvXQ3aqsWuzCixZ13QEMxCjF9QenE+1mS6zIUqGCP2g9tApMyrCvjRDLnUvqH10ynyC9Hszdf0oGSL0guKo61Dq/vvv5/Dhw5w4cYJDhw5x//338653vavloQbYzQM01u3f4Q4G2N10htnL4LpNjV173d359WZoPkOEXlB7cD7VZrrMhigZIvSD2kOnzKgI+9IMudS9oPbRKfMJ0u/N1PWjZIjQC4qjuV/mnEI72DLaqJM92jfy9QdY19JT08VrxzbsZI84jnz9uk35dWZoXYYIvSCNF6EnU+9LM4yJ0A/SeKl7MsK+NEMudS9IE0XoydR7M3X9KBki9IJiCHsoBXmjbmIZ+3iEKlUqnKLCKTKqVDhJhVNUqbKPR9jEspY3aKmUP564aifMvxko5W+BOfI2mqOfl/Kvr9qZf3+pZIZWZ0jdC9JEqXsywr40w5jU/SBNlLInI+xLM4xxPima1D2Zem+mrh8lA6TvBcXQ4EucFWeA3Qywm1nMZSm3cQkLuIA+XmOYVzjAHrZO+YuczV6WfxwbhP1bYfgAvDEM5/Xlb4e56LbmXuzNDLWJ0AvSeBF6MvW+NMOYCP0gjZe6JyPsSzPkUveCNFGEnky9N1PXj5IhQi8orfCHUiOOcIhHuCtphpnz4NrPJo1gBmL0gjRehJ5MvS/NMCZCP0jjpe7JCPvSDLnUvSBNFKEnU+/N1PWjZIjQC0oj9K/vSZIkSZIkaXryUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYUrZVmWFVlweHiY/v5+KMFFc4qsnHv1RciqUCrDhbOLr28GM0TLkLo+wPHDQAZDQ0P09fWlCUH6+QQx1iN1htT1zWCGiSLMKOeTGaLUN0OsDM6nXIS1MIMZotSPkqHW+ZTuUEqSJghzKCVJZxDiX/ok6QycT5Kimmw+dReY5XQ+KWUGM4TIkLo+jJ2ih+F/6ev4njSDGcYLNaOcTx2fIXV9M8TK4HzKRVgLM5ghSv0oGWqdT8kOpS68DG49VHzdr8+F4z/KFyZFfTOYIVqG1PUB7puTD84oUs0niLEeqTOkrm8GM0wUaUY5n8yQur4ZYmVwPuUirIUZzBClfpQMtc4nX+hckiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYVL9u577ejYQdi/DYYG4ORRmNEL/Qth0RqYOT91uuLMYh5LWcOlLOR8enmdo7zMAHvYxhEGp7x+hHVIfQ/MoIki7IsIIvRk6rWIcA/MoPFS7wkzxMoQYW+mzpC6vk6Xel+krm+GMRH2Zidm8FCqBod3wt7NcHA7lN58tiyrQKkr//zZO+HylbBkPcxelizmlFvIMpazjsWsJKMKQJky1Tc/X8md7OVhdrCZAXa3vH6EdUh9D8ygiSLsiwgi9GTqtYhwD8yg8VLvCTPEyhBhb6bOkLq+Tpd6X6Sub4YxEfZmJ2fw1/fOIcvg+U2w/UYYfBTI8g2SVd78+sjnGRx8FB7+QL6hsixh6CmynHWsZydXsYIyZbropotuSuM+L1NmMTeznl3cxNqW1Y6yDinvgRk0UZR9EUHqnoywFqnvgRk0XoQ9YYY4GSDG3kydIXV9jUm9L1LXN8PpIuzNTs/godQ57NsCT96Rf56dOvf3jnz9ifX5ddPJTazlY2wCoIsZ5/zeka+vZnPLGjXCOqS+B2bQRBH2RQQRejL1WkS4B2bQeKn3hBliZYiwN1NnSF1fp0u9L1LXN8OYCHvTDA0cSv3oRz/i4x//OBdffDEXXHABixcv5plnnmlJmEgO78ybvhFPrIcXd7U2TyoLWcZqNjd07Wo2s5AbmqofYR1S3wMz1M75NDnnU65VPZl6LSLcAzPUrhNmVOo9YYZYGSLszdQZUtevVSfMJ0i/L1LXN8OYCHvTDLm6DqWOHDnC9ddfz4wZM3j00Uf5m7/5GzZv3sysWbOaDhLN3s1QavAVt0rd+fXTwXLWUeFkQ9dWONn06WmEdUh9D8xQG+dTbZxPuVb1ZOq1iHAPzFCbTplRqfeEGWJliLA3U2dIXb8WnTKfIP2+SF3fDGMi7E0z5OpqhS984QvMmzePrVu3jv69K664oukQ0Rw7mL/QGg3+vmp2Cn74MBwbhJnzWhqtULOYx2JWUm7wtzy7mMESbmEWcznCobqvj7AOqe+BGWrnfKqN8ynXip5MvRYR7oEZatcJMyr1njBDrAwR9mbqDKnr16oT5hOk3xep65thTIS9aYYxdVV/6KGHeO9738vq1au59NJLueaaa/jKV77ScPGo9m8be+X/RpXKsH/r5N8X2VLWjL7qfqMyqizltoaujbAOqe+BGWrnfKqd8ynXbE+mXosI98AMteuEGZV6T5ghVoYIezN1htT1a9UJ8wnS74vU9c0wJsLeNMOYutrhH/7hH7jnnntYuHAhf/qnf8pv/MZv8Fu/9Vt87WtfO+s1J06cYHh4+LSP6IYGWvNzhg+05uekcikLW/BTMi5hQUNXRliH1PfADLVzPtXH+QTN9mTqtYhwD8xQu3pnlPPJDO2eIcLeTJ0hdf1adcJ8gvT7InV9M4yJsDfNMKauX9+rVqu8973v5fOf/zwA11xzDX/913/Nf/kv/4VPfOITZ7xm48aN/N7v/V5TIYt28ujYW1E2KqvAG+0xn8/qfHobfpRvRJkuLqCvoWsjrEPqe2CG2jmfaud8yjXbk6nXIsI9MEPt6p1RzicztHuGCHszdYbU9WvVCfMJ0u+L1PXNMCbC3jTD+J9Rh9mzZ/MzP/Mzp/29n/7pn+bgwYNnvWbDhg0MDQ2NfgwODjaWtEAzeqHU1dzPKHXBeVP7/x9T7nWOUm3ycb4qFV6jsYkRYR1S3wMz1M75VDvnU67Znky9FhHugRlqV++Mcj6Zod0zRNibqTOkrl+rTphPkH5fpK5vhjER9qYZxtT1pNT111/P/v37T/t7f/d3f8fll19+1mt6enro6elpLF0i/a14ig3om9onbafcy7Ti2coSr9DYs5UR1iH1PTBD7ZxP9XE+QbM9mXotItwDM9Su3hnlfDJDu2eIsDdTZ0hdv1adMJ8g/b5IXd8MYyLsTTOMqetJqd/5nd/hiSee4POf/zwHDhzgG9/4Bv/tv/03br/99qZCRLNoDWTNHRiSVWHR1L4m4ZTbwzZKTT7OV6LMHhp7FboI65D6Hpihds6n2jmfcs32ZOq1iHAPzFC7TphRqfeEGWJliLA3U2dIXb9WnTCfIP2+SF3fDGMi7E0zjKkrwfve9z4efPBBvvnNb3LVVVdx11138cUvfpFbb721qRDRzJwP81dCqa7nyMaUuuHyVe39dusARxhkH9upcLKh6yucZC8PNfz2kBHWIfU9MEPtnE+1cT7lWtGTqdciwj0wQ+06YUal3hNmiJUhwt5MnSF1/Vp1wnyC9PsidX0zjImwN80wpu5jsZUrV7Jv3z5ef/11fvCDH/Cv//W/bipAVFevh+xUY9dmFViyrrV5UnmcTXQxo6Fry3Sxgy1N1Y+wDqnvgRlq53yanPMp16qeTL0WEe6BGWrXCTMq9Z4wQ6wMEfZm6gyp69eqE+YTpN8XqeubYUyEvWmGkZ+jM5q9DK7b1Ni1192dXz8dDLCbB2hs13+HOxhgd1P1I6xD6ntgBk0UYV9EEKEnU69FhHtgBo2Xek+YIVaGCHszdYbU9XW61PsidX0zjImwN82Q81DqHBavHdsskz1eOPL16zbl100nO9gy2qiTPdo38vUHWNey/7ITYR1S3wMzaKII+yKCCD2Zei0i3AMzaLzUe8IMsTJE2JupM6Sur9Ol3hep65thTIS9aQYPpc6pVMofDVy1E+bfDJTyt58ceQvL0c9L+ddX7cy/v1RKmXpq7GALm1jGPh6hSpUKp6hwiowqFU5S4RRVquzjETaxrKWbJMo6pLwHZtBEUfZFBKl7MsJapL4HZtB4EfaEGeJkgBh7M3WG1PU1JvW+SF3fDKeLsDc7PUODLy/WWWYvyz+ODcL+rTB8AN4YhvP68reiXHRb+79ocC0G2M0Au5nFXJZyG5ewgAvo4zWGeYUD7GHrlL4QY4R1SH0PzKCJIuyLCCL0ZOq1iHAPzKDxUu8JM8TKEGFvps6Qur5Ol3pfpK5vhjER9mYnZ/BQqg4z58G1n02dIr0jHOIR7kpWP8I6pL4HZtBEEfZFBBF6MvVaRLgHZtB4qfeEGWJliLA3U2dIXV+nS70vUtc3w5gIe7MTM/jre5IkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSpcKcuyrMiCw8PD9Pf3QwkumlNk5dyrL0JWhVIZLpxdfH0zmCFahtT1AY4fBjIYGhqir68vTQjSzyeIsR6pM6SubwYzTBRhRjmfzBClvhliZXA+5SKshRnMEKV+lAy1zqd0h1KSNEGYQylJOoMQ/9InSWfgfJIU1WTzqbvALKfzSSkzmCFEhtT1YewUPQz/S1/H96QZzDBeqBnlfOr4DKnrmyFWBudTLsJamMEMUepHyVDrfEp2KHXhZXDroeLrfn0uHP9RvjAp6pvBDNEypK4PcN+cfHBGkWo+QYz1SJ0hdX0zmGGiSDPK+WSG1PXNECuD8ykXYS3MYIYo9aNkqHU++ULnkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKly6d99TQ2Yxj6Ws4VIWcj69vM5RXmaAPWzjCIMdkSF1fYBjB2H/NhgagJNHYUYv9C+ERWtg5vxCIoS4D9J4EXrSDM4n6Uwi9KQZcs4o6XQR+tEMOedTGh5KtYmFLGM561jMSjKqAJQpU33z85XcyV4eZgebGWD3tMyQuj7A4Z2wdzMc3J6/vSZAVoFSV/75s3fC5SthyXqYvWxKIoS4D9J4EXrSDM4n6Uwi9KQZcs4o6XQR+tEMOedTWv76XhtYzjrWs5OrWEGZMl1000U3pXGflymzmJtZzy5uYu20y5C6fpbB85tg+40w+CiQ5YMqq7z59ZHPMzj4KDz8gXywZVlLYyS/D9JEEXqy0zM4n6Qzi9CTZnBGSWcSoR/N4HyKwkOp4G5iLR9jEwBdzDjn9458fTWbW9qoqTOkrg+wbws8eUf+eXbq3N878vUn1ufXtUqE+yCNF6EnzeB8ks4kQk+aIeeMkk4XoR/NkHM+xeChVGALWcZqNjd07Wo2s5Ab2j5D6vqQP875xPrGrn1iPby4q+kIIe6DNF6EnjSD80k6kwg9aYacM0o6XYR+NEPO+RRHXYdSP/VTP0WpVHrLx+233z5V+TractZR4WRD11Y42ZLT09QZUteH/BHNUoOvvlbqzq9vVoT70A6cUcWJ0JNmcD61E+dTcSL0pBlyzqj24HwqToR+NEPO+RRHXYdSTz/9NC+++OLox+OPPw7A6tWrpyRcJ5vFPBazctJH+M6mixks4RZmMbdtM6SuD/k7MBzcPvnjnGeTnYIfPgzHmnijhAj3oV04o4oRoSfN4HxqN86nYkToSTPknFHtw/lUjAj9aIac8ymWug6lLrnkEi677LLRj+3bt/Oud72LD3zgA1OVr2MtZc3oq+43KqPKUm5r2wyp60P+lqClJn/JtVSG/Vsbvz7CfWgXzqhiROhJMzif2o3zqRgRetIMOWdU+3A+FSNCP5oh53yKpcEH1uCNN97gvvvuY+3atZRKpbN+34kTJzhx4sToXw8PDzdasqNcysIW/JSMS1jQthlS1wcYGmhBBGD4QOPXRrgP7aiWGeV8akyEnjSD86mdOZ+mToSeNEPOGdWenE9TJ0I/miHnfIql4fPBP/mTP+HHP/4xa9asOef3bdy4kf7+/tGPefPmNVqyo5xPL+UmX4e+TBcX0Ne2GVLXBzh5dOwtQRuVVeCNJv6/OsJ9aEe1zCjnU2Mi9KQZnE/tzPk0dSL0pBlyzqj25HyaOhH60Qw551MsDd+Fe++9lxUrVjBnzpxzft+GDRsYGhoa/RgcbOIXLzvI6xyl2uTjfFUqvEbjOyV1htT1AWb0QqmrqQiUuuC8JmZFhPvQjmqZUc6nxkToSTM4n9qZ82nqROhJM+ScUe3J+TR1IvSjGXLOp1ga+vW9H/7wh+zYsYM//uM/nvR7e3p66OnpaaRMR3uZVjxTWOIVGn+mMHWG1PUB+lvxVCXQ18RTlRHuQ7updUY5nxoToSfN4HxqV86nqRWhJ82Qc0a1H+fT1IrQj2bIOZ9iaehJqa1bt3LppZfykY98pNV59KY9bKPU5ON8JcrsofFXX0udIXV9gEVrIGvuAJusCouaeP25CPeh3TijplaEnjSD86ldOZ+mVoSeNEPOGdV+nE9TK0I/miHnfIql7rtQrVbZunUrn/jEJ+jubvh10jWJIwyyj+1UONnQ9RVOspeHOMKhts2Quj7AzPkwfyWUGmz1UjdcvgpmNvGr9hHuQztxRk29CD1pBudTO3I+Tb0IPWmGnDOqvTifpl6EfjRDzvkUS92HUjt27ODgwYP8+q//+lTk0TiPs4kuZjR0bZkudrCl7TOkrg9w9XrITjV2bVaBJeuajhDiPrQLZ1QxIvSkGZxP7cb5VIwIPWmGnDOqfTifihGhH82Qcz7FUfeh1C/8wi+QZRnvfve7pyKPxhlgNw/QWLd/hzsYYHfbZ0hdH2D2MrhuU2PXXnd3fn2zItyHduGMKkaEnjSD86ndOJ+KEaEnzZBzRrUP51MxIvSjGXLOpzia+yVGTbkdbBlt1Mke7Rv5+gOsa+mpaeoMqesDLF47NrQme8xz5OvXbcqva5UI90EaL0JPmsH5JJ1JhJ40Q84ZJZ0uQj+aIed8isFfGG4DO9jCD3mam1jLEm4he/OtI8uUqVIBSpQos49H2MGWKTkxTZ0hdf1SKX9E85L3wd7N8MOHofTmkW5WGXtL0awK82/Ov7cVp+cTpb4P0kQRerLTMzifpDOL0JNmcEZJZxKhH83gfIrCQ6k2McBuBtjNLOaylNu4hAVcQB+vMcwrHGAPW6f8Rc5SZ0hdH/IhNHsZHBuE/Vth+AC8MQzn9eVvCbrotuZe8K4WEe6DNF6EnjSD80k6kwg9aYacM0o6XYR+NEPO+ZSWh1Jt5giHeIS7OjpD6vqQD6VrP5s0Qoj7II0XoSfN4HySziRCT5oh54ySThehH82Qcz6l4WtKSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXClLMuyIgsODw/T398PJbhoTpGVc6++mL+lY6kMF84uvr4ZzBAtQ+r6AMcPAxkMDQ3R19eXJgTp5xPEWI/UGVLXN4MZJoowo5xPZohS3wyxMjifchHWwgxmiFI/SoZa51O6QylJmiDMoZQknUGIf+mTpDNwPkmKarL51F1gltP5pJQZzBAiQ+r6MHaKHob/pa/je9IMZhgv1IxyPnV8htT1zRArg/MpF2EtzGCGKPWjZKh1PiU7lLrwMrj1UPF1vz4Xjv8oX5gU9c1ghmgZUtcHuG9OPjijSDWfIMZ6pM6Qur4ZzDBRpBnlfDJD6vpmiJXB+ZSLsBZmMEOU+lEy1DqffKFzSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBUu2bvvqX3NYh5LWcOlLOR8enmdo7zMAHvYxhEGp339KBmOHYT922BoAE4ehRm90L8QFq2BmfMLiSCFE2Fvps6Qur4ZpDOL0JNmiJEhdX1pogg9aYbOzeChlGq2kGUsZx2LWUlGFYAyZapvfr6SO9nLw+xgMwPsnnb1o2Q4vBP2boaD26H05rOOWQVKXfnnz94Jl6+EJeth9rIpiSCFE2Fvps6Qur4ZpDOL0JNmiJEhdX1pogg9aQYz+Ot7qsly1rGenVzFCsqU6aKbLropjfu8TJnF3Mx6dnETa6dV/QgZsgye3wTbb4TBR4EsP4zKKm9+feTzDA4+Cg9/ID+8yrKWxpDCSb03I2RIXd8M0plF6EkzxMiQur40UYSeNIMZwEMp1eAm1vIxNgHQxYxzfu/I11ezuWWNmrp+lAz7tsCTd+SfZ6fO/b0jX39ifX6dNF1F2JupM6SubwbpzCL0pBliZEhdX5ooQk+awQwj6jqUqlQq/If/8B+44ooruOCCC3jXu97FXXfdReajGNPWQpaxms0NXbuazSzkhrauHyXD4Z35AVMjnlgPL+5qOkJ4zqfOE2Fvps6Qur4ZaueM6iwRetIMMTKkrl8L51NnidCTZjDDeHUdSn3hC1/gnnvu4Utf+hI/+MEP+MIXvsD/9//9f/zhH/5h00EU03LWUeFkQ9dWONn06Wnq+lEy7N0MpQZfAa7UnV8/3TmfOk+EvZk6Q+r6ZqidM6qzROhJM8TIkLp+LZxPnSVCT5rBDOPV9a+5e/bs4aMf/Sgf+chHAPipn/opvvnNb/LUU081HUTxzGIei1lJucHf8uxiBku4hVnM5QiH2q5+lAzHDuYvak6D/7EqOwU/fBiODcLMeY39jHbgfOosEfZm6gyp65uhPs6ozhGhJ80QI0Pq+rVyPnWOCD1pBjNMVFf1pUuX8t3vfpe/+7u/A+D555/nL/7iL1ixYkXDARTXUtaMvup+ozKqLOW2tqwfJcP+bWPvsteoUhn2b23uZ0TnfOosEfZm6gyp65uhPs6ozhGhJ80QI0Pq+rVyPnWOCD1pBjNMVNeTUp/5zGcYHh7myiuvpKuri0qlwuc+9zluvfXWs15z4sQJTpw4MfrXw8PDjadVoS5lYQt+SsYlLGjL+lEyDA20IAIwfKA1Pycq51NnibA3U2dIXd8M9al3Rjmf2leEnjRDjAyp69fK+dQ5IvSkGcwwUV3PX3z729/m61//Ot/4xjf4q7/6K772ta+xadMmvva1r531mo0bN9Lf3z/6MW/eNP79oWnmfHobfpRvRJkuLqCvLetHyXDyKGSVpiKQVeCNaf7nBedTZ4mwN1NnSF3fDPWpd0Y5n9pXhJ40Q4wMqevXyvnUOSL0pBnM8NafUYc77riDz3zmM/zzf/7PWbx4Mf/iX/wLfud3foeNGzee9ZoNGzYwNDQ0+jE4ONhUYBXndY5SbfJxvioVXqOx05DU9aNkmNELpa6mIlDqgvOm9s8zyTmfOkuEvZk6Q+r6ZqhPvTPK+dS+IvSkGWJkSF2/Vs6nzhGhJ81ghonq+vW9V199lXL59HOsrq4uqtWz/4P09PTQ09PTWDol9TKt+L2xEq/Q2O+Npa4fJUN/K56qBPqm9snv5JxPnSXC3kydIXV9M9Sn3hnlfGpfEXrSDDEypK5fK+dT54jQk2Yww0R1PSm1atUqPve5z/HII4/wwgsv8OCDD7JlyxZ++Zd/uakQimkP2yg1+ThfiTJ7aOwVtlPXj5Jh0RrImjvAJqvCoql9jczknE+dJcLeTJ0hdX0z1McZ1Tki9KQZYmRIXb9WzqfOEaEnzWCGiepK8Id/+Id87GMf45Of/CQ//dM/zfr16/k3/+bfcNdddzUVQjEdYZB9bKfCyYaur3CSvTzU8NtDpq4fJcPM+TB/JZTqeq5xTKkbLl8FM6f5r/s7nzpLhL2ZOkPq+maojzOqc0ToSTPEyJC6fq2cT50jQk+awQwT1XUo1dvbyxe/+EV++MMf8tprr/H3f//3/P7v/z7nnXdeUyEU1+NsoosZDV1bposdbGnr+lEyXL0eslONXZtVYMm6piOE53zqPBH2ZuoMqeuboXbOqM4SoSfNECND6vq1cD51lgg9aQYznP5zpHMYYDcP0NiJxne4gwF2t3X9KBlmL4PrNjV27XV359dL002EvZk6Q+r6ZpDOLEJPmiFGhtT1pYki9KQZzDCeh1Ka1A62jDbqZI/2jXz9Ada17L/spK4fJcPitWMHU5P9Kt/I16/blF8nTVcR9mbqDKnrm0E6swg9aYYYGVLXlyaK0JNmMMOIBl+lRp1mB1v4IU9zE2tZwi1kb751ZJkyVSpAiRJl9vEIO9jS8v+qk7p+hAylUv5reJe8D/Zuhh8+DKU3j5WzCpS63vy8CvNvzr/XJ6TUCVLvzQgZUtc3g3RmEXrSDDEypK4vTRShJ81gBvBQSnUYYDcD7GYWc1nKbVzCAi6gj9cY5hUOsIetU/pCjKnrR8kwe1n+cWwQ9m+F4QPwxjCc1wd9C/J32ZvuL2ouTRRhb6bOkLq+GaQzi9CTZoiRIXV9aaIIPWkGM3gopbod4RCPkO7dOFLXj5Jh5jy49rNJI0jhRNibqTOkrm8G6cwi9KQZYmRIXV+aKEJPmqFzM/iaUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSpcKcuyrMiCQ0NDvO1tbwPgwtlFVs69+hKQASW48LLi65vBDNEypK4P8OqL+f/++Mc/pr+/P00I0s8nCLIe9qQZzHB6hgAzyvlkhij1zRAsg/MJCLIWZjBDkPphMtQ4nwo/lDp06BDz5vl+9ZLeanBwkLlz5yar73ySdC4pZ5TzSdK5OJ8kRTXZfCr8UKparXL48GF6e3splUp1Xz88PMy8efMYHBykr69vChKaoV0ypK5vhtZlyLKMo0ePMmfOHMrldL9V7Hwyw3TKkLr+dMoQYUY1O58g/Xqkrm8GM0TL4Hwak3otImRIXd8MZmh1hlrnU3czIRtRLpdbcorf19eXbHHMECtD6vpmaE2GlL+2N8L5ZIbpmCF1/emSIfWMatV8gvTrkbq+GcwQLYPzaUzqtYiQIXV9M5ihlRlqmU++0LkkSZIkSZIK56GUJEmSJEmSCtd2h1I9PT38x//4H+np6TFDh2dIXd8MsTJEEOE+mMEMUeqbIZ7U9yJ1fTOYIVqG1PUjiXAvUmdIXd8MZkiVofAXOpckSZIkSZLa7kkpSZIkSZIktT8PpSRJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVLi2OpT6y7/8S7q6uvjIRz5SeO01a9ZQKpVGPy6++GI+/OEPs3fv3sKzvPTSS/zmb/4m73znO+np6WHevHmsWrWK7373u1Nee/x9mDFjBj/xEz/B8uXL+epXv0q1Wp3y+hMzjP/48Ic/XEj9yXIcOHCgkPovvfQSn/70p1mwYAHnn38+P/ETP8H111/PPffcw6uvvjrl9desWcMv/dIvveXvf//736dUKvHjH/94yjNE44xyPk3MkWpGpZ5PkHZGOZ/eyvnkfJqYw/nkn6GicD45nybmcD511nxqq0Ope++9l9/8zd9k165dHD58uPD6H/7wh3nxxRd58cUX+e53v0t3dzcrV64sNMMLL7zAtddey/e+9z3uvvtu9u3bx2OPPcYHP/hBbr/99kIyjNyHF154gUcffZQPfvCDfPrTn2blypWcOnWq0AzjP775zW8WUnuyHFdcccWU1/2Hf/gHrrnmGv7sz/6Mz3/+8/yv//W/+Mu//Ev+3b/7d2zfvp0dO3ZMeQa9VafPKOfTW3OknFGp5hM4oyJyPjmfJuZwPjmfonA+OZ8m5nA+ddZ86k4doFbHjh3jW9/6Fs888wwvvfQS27Zt49//+39faIaenh4uu+wyAC677DI+85nPcMMNN/DKK69wySWXFJLhk5/8JKVSiaeeeoqLLrpo9O+/5z3v4dd//dcLyTD+PvzkT/4kP/uzP8t1113Hhz70IbZt28a/+lf/qtAMKaXK8clPfpLu7m6eeeaZ0/rgne98Jx/96EfJsqzwTJ3OGeV8OluOVFJmcEbF4nxyPp0tRyrOJ41wPjmfzpYjFedT8drmSalvf/vbXHnllSxatIiPf/zjfPWrX026KMeOHeO+++5jwYIFXHzxxYXU/H//7//x2GOPcfvtt5/WpCPe9ra3FZLjTH7+53+eq6++mj/+4z9OlqFT/N//+3/5sz/7s7P2AUCpVCo4lTp9RjmfNMIZFY/zyfmknPMpHueT80m5Tp5PbXMode+99/Lxj38cyB+pGxoaYufOnYVm2L59OzNnzmTmzJn09vby0EMP8a1vfYtyuZjbeODAAbIs48orryykXr2uvPJKXnjhhUJqjV+LkY/Pf/7zhdQ+V47Vq1dPec2RPli0aNFpf/8d73jHaI7f/d3fnfIccOZ1WLFiRSG1o+n0GeV8Ol2EGZViPkGcGeV8GuN8cj6N53xKP5/AGTXC+eR8Gs/51JnzqS1+fW///v089dRTPPjggwB0d3fzz/7ZP+Pee+/lxhtvLCzHBz/4Qe655x4Ajhw5wh/90R+xYsUKnnrqKS6//PIprx/9cb0sywo7vR2/FiPe/va3F1L7XDnOdqpdhKeeeopqtcqtt97KiRMnCql5pnV48sknR/9w0SmcUc6niSLMqEjzCYqfUc6nnPPJ+TSR8+mt/DNUGs4n59NEzqe36oT51BaHUvfeey+nTp1izpw5o38vyzJ6enr40pe+RH9/fyE5LrroIhYsWDD61//9v/93+vv7+cpXvsLv//7vT3n9hQsXUiqV+Nu//dspr9WIH/zgB4W9CNzEtUglRY4FCxZQKpXYv3//aX//ne98JwAXXHBBYVnO9M9/6NChwupH4YxyPk0UYUalyhBlRjmfcs4n59NEzqf08wmcUeB8AufTRM6nzpxP4X9979SpU/yP//E/2Lx5M88999zox/PPP8+cOXOSvOPaiFKpRLlc5rXXXiuk3tvf/nZ+8Rd/kS9/+cscP378LV9P+fax3/ve99i3bx+/8iu/kixDp7j44otZvnw5X/rSl87YByqWMyrnfNIIZ1Qczqec80kjnE9xOJ9yzieN6OT5FP5Jqe3bt3PkyBH+5b/8l285Lf+VX/kV7r33Xv7tv/23hWQ5ceIEL730EpA/2vmlL32JY8eOsWrVqkLqA3z5y1/m+uuv5+d+7uf4T//pP7FkyRJOnTrF448/zj333MMPfvCDKc8wch8qlQr/5//8Hx577DE2btzIypUr+bVf+7Uprz8+w3jd3d284x3vKKR+an/0R3/E9ddfz3vf+17uvPNOlixZQrlc5umnn+Zv//Zvufbaa1NH7BjOqDHOp7fmGM8Z5YwqmvNpjPPprTnGcz45n4rmfBrjfHprjvGcTx0wn7LgVq5cmd18881n/NqTTz6ZAdnzzz8/5Tk+8YlPZMDoR29vb/a+970v+853vjPltSc6fPhwdvvtt2eXX355dt5552U/+ZM/md1yyy3Zn//5n0957fH3obu7O7vkkkuym266KfvqV7+aVSqVKa8/McP4j0WLFhVSf3yOj370o4XWHO/w4cPZpz71qeyKK67IZsyYkc2cOTP7uZ/7uezuu+/Ojh8/PuX1z/bP/+d//ucZkB05cmTKM0TgjDpdp8+niTlSzajU8ynL0s4o51PO+XQ655PzaYR/hkrP+XQ655PzaUQnzqdSlgV/dTVJkiRJkiRNO+FfU0qSJEmSJEnTj4dSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqnIdSkiRJkiRJKpyHUpIkSZIkSSqch1KSJEmSJEkqXHfRBavVKocPH6a3t5dSqVR0eUkBZVnG0aNHmTNnDuVyurNy55OkM4kwo5xPks7E+SQpqlrnU+GHUocPH2bevHlFl5XUBgYHB5k7d26y+s4nSeeSckY5nySdi/NJUlSTzafCD6V6e3tHP79wdtHV4dWXgAwowYWXFV/fDGaIliF1fYBXX8z/d/x8SCH1fIIg62FPmsEMp2cIMKOcT2aIUt8MwTI4n4Aga2EGMwSpHyZDjfOp8EOpkUc6L5wNHz9cdHX4+lw4/iO4aA7ceqj4+mYwQ7QMqesD3DcnH1qpH/lOPZ8gxnqkzpC6vhnMMFGEGeV8MkOU+maIlcH5lIuwFmYwQ5T6UTLUOp98oXNJkiRJkiQVzkMpSZIkSZIkFc5DKUmSJEmSJBXOQylJkiRJkiQVrvAXOm/ULOaxlDVcykLOp5fXOcrLDLCHbRxhMHU8SR3M+SQpstQz6thB2L8Nhgbg5FGY0Qv9C2HRGpg5f8rLSwos9XwCZ5SUWvhDqYUsYznrWMxKMqoAlClTffPzldzJXh5mB5sZYHfKqJI6jPNJUmSpZ9ThnbB3MxzcDqU3n83PKlDqyj9/9k64fCUsWQ+zl7W8vKTAUs8ncEZJUYT+9b3lrGM9O7mKFZQp00U3XXRTGvd5mTKLuZn17OIm1qaOLKlDOJ8kRZZyRmUZPL8Jtt8Ig48CWf4velnlza+PfJ7BwUfh4Q/k/2KYZS2LICmw1H+GckZJsYQ9lLqJtXyMTQB0MeOc3zvy9dVs9l/8JE0555OkyFLPqH1b4Mk78s+zU+f+3pGvP7E+v07S9JZ6PoEzSoqm7kOpXbt2sWrVKubMmUOpVOJP/uRPWh5qIctYzeaGrl3NZhZyQ4sTSWoHzidJURUxnyD9jDq8M/+Xt0Y8sR5e3NVUeUkN6JT5BM4oKaK6D6WOHz/O1VdfzZe//OWpyAPkj3RWONnQtRVO+jSC1KGcT5KiKmI+QfoZtXczlBp8xdJSd369pGJ1ynwCZ5QUUd1bcsWKFaxYsWIqsgD5OzAsZiXlBn+zsIsZLOEWZjGXIxxqcTpJkTmfJEU11fMJ0s+oYwfzFwymwdddyU7BDx+GY4Mwc15jP0NS/TphPoEzSooq3GtKLWXN6DswNCqjylJua1EiSco5nyRFlnpG7d829g5WjSqVYf/W5n6GpHhSzydwRklRNfjwYu1OnDjBiRMnRv96eHj4nN9/KQtbUDXjEha04OdIms6cT5Kiqnc+QfoZNTTQgvLA8IHW/BxJU6Md5xM4o6SopvxJqY0bN9Lf3z/6MW/euZ91PJ/ehh/rHFGmiwvoa+pnSJr+nE+Soqp3PkH6GXXy6Nhbqjcqq8Abk//7raSE2nE+gTNKimrKD6U2bNjA0NDQ6Mfg4OA5v/91jlJt8tHOKhVew2kh6dycT5Kiqnc+QfoZNaMXSl1NlafUBed5bi+F1o7zCZxRUlRT/ut7PT099PT01Pz9L9OK5ypLvILPVUo6N+eTpKjqnU+Qfkb1t+K3c4A+f8NZCq0d5xM4o6So6n5S6tixYzz33HM899xzAPzjP/4jzz33HAcPHmxJoD1so9TkA1wlyuzBV6CTOo3zSVJUUz2fIP2MWrQGsuYehCCrwiLfC0IqVCfMJ3BGSVHVPRmeeeYZrrnmGq655hoA1q5dyzXXXMNnP/vZlgQ6wiD72E6Fkw1dX+Eke3nIt1uXOpDzSVJUUz2fIP2Mmjkf5q+EUoPP4Ze64fJVvtW6VLROmE/gjJKiqntL3njjjWRZNhVZRj3OJq7mloauLdPFDra0OJGkduB8khRVEfMJ0s+oq9fDwYcbuzarwJJ1TZWX1IBOmU/gjJIimvIXOm/EALt5gMZ2/He4gwF2tziRJOWcT5IiSz2jZi+D6zY1du11d+fXS5qeUs8ncEZJEYU8lALYwZbRoTXZY54jX3+AdT6FIGnKOZ8kRZZ6Ri1eO/YvfZP9mszI16/blF8naXpLPZ/AGSVFE/ZQCvKhtYll7OMRqlSpcIoKp8ioUuEkFU5Rpco+HmETy/wXPkmFcT5JiizljCqV8l9xWbUT5t8MlPK3UR95K/bRz0v511ftzL+/VGpZBEmBpf4zlDNKiqXBl3krzgC7GWA3s5jLUm7jEhZwAX28xjCvcIA9bPVFgyUl4XySFFnqGTV7Wf5xbBD2b4XhA/DGMJzXl7+l+qLbfMFgqVOlnk/gjJKiCH8oNeIIh3iEu1LHkKS3cD5Jiiz1jJo5D65t3Zt4SZpGUs8ncEZJqYX+9T1JkiRJkiRNTx5KSZIkSZIkqXAeSkmSJEmSJKlwHkpJkiRJkiSpcKUsy7IiCw4PD9Pf3w8luGhOkZVzr74IWRVKZbhwdvH1zWCGaBlS1wc4fhjIYGhoiL6+vjQhSD+fIMZ6pM6Qur4ZzDBRhBnlfDJDlPpmiJXB+ZSLsBZmMEOU+lEy1Dqf0h1KSdIEYQ6lJOkMQvxLnySdgfNJUlSTzafuArOczielzGCGEBlS14exU/Qw/C99Hd+TZjDDeKFmlPOp4zOkrm+GWBmcT7kIa2EGM0SpHyVDrfMp2aHUhZfBrYeKr/v1uXD8R/nCpKhvBjNEy5C6PsB9c/LBGUWq+QQx1iN1htT1zWCGiSLNKOeTGVLXN0OsDM6nXIS1MIMZotSPkqHW+eQLnUuSJEmSJKlwHkpJkiRJkiSpcB5KSZIkSZIkqXAeSkmSJEmSJKlw6d59r06zmMdS1nApCzmfXl7nKC8zwB62cYRBM3RYhtSOHYT922BoAE4ehRm90L8QFq2BmfPNUGSGCCLsCTPEyZBahH1phlhS74sIa5H6HkTJEEGEfkidIXX9SCLsi9TrEeEeRMgQQepe6NQM4Q+lFrKM5axjMSvJqAJQpkz1zc9Xcid7eZgdbGaA3WaY5hlSO7wT9m6Gg9vzt9cEyCpQ6so/f/ZOuHwlLFkPs5eZYSozRBBhT5ghTobUIuxLM8SSel9EWIvU9yBKhggi9EPqDKnrRxJhX6Rejwj3IEKGCFL3QqdnCP3re8tZx3p2chUrKFOmi2666KY07vMyZRZzM+vZxU2sNcM0zpBSlsHzm2D7jTD4KJDlGzSrvPn1kc8zOPgoPPyBfENnmRlanSGKCHvCDHEypBRhX5ohnpT7IspaRJgNETKkFqEfUmdIXT+a1PsiwnqkvgdRMqQWoRfMEPhQ6ibW8jE2AdDFjHN+78jXV7O5pZvFDHEypLZvCzx5R/55durc3zvy9SfW59eZobUZIoiwJ8wQJ0NqEfalGWJJvS8irEXqexAlQwQR+iF1htT1I4mwL1KvR4R7ECFDBKl7wQy5kIdSC1nGajY3dO1qNrOQG8wwjTKkdnhnvuka8cR6eHGXGVqVIYIIe8IMcTKkFmFfmiGW1PsiwlqkvgdRMkQQoR9SZ0hdP5II+yL1ekS4BxEyRJC6F8wwpq5DqY0bN/K+972P3t5eLr30Un7pl36J/fv3N59iguWso8LJhq6tcLIlJ7hmiJMhtb2bodTgq6+VuvPrzdCaDOfifDJDigypRdiXZqhNp8yoCGuR+h5EyRBBhH5InSF1/Vp0ynyC9OsR4R5EyBBB6l4ww5i6DqV27tzJ7bffzhNPPMHjjz/OyZMn+YVf+AWOHz/efJI3zWIei1k56WOEZ9PFDJZwC7OYa4ZpkCG1YwfzF3qb7DHGs8lOwQ8fhmNNvGmFGWrjfDJD0RlSi7AvzVC7TphREdYi9T2IkiGCCP2QOkPq+rXqhPkE6dcjwj2IkCGC1L1ghtPVdSj12GOPsWbNGt7znvdw9dVXs23bNg4ePMizzz7bXIpxlrJm9JX/G5VRZSm3mWEaZEht/7axdx5oVKkM+7eaodkMk3E+maHoDKlF2JdmqF0nzKgIa5H6HkTJEEGEfkidIXX9WnXCfIL06xHhHkTIEEHqXjDD6Rp8UCs3NDQEwNvf/vazfs+JEyc4ceLE6F8PDw+f82deysJmIr0p4xIWNHy1GeJkSG1ooDU/Z/iAGZrNUC/nkxmmOkNqEfalGRo32Yyqdz5B+n0RYS1S34MoGSKI0A+pM6Su36jpOJ8g/XpEuAcRMkSQuhfMcLqGz8Wq1Sq//du/zfXXX89VV1111u/buHEj/f39ox/z5s075889n17KTb7+epkuLqCv4evNECdDaiePjr0VZqOyCrwx+f9Xm6GFnE9mKCJDahH2pRkaU8uMqnc+Qfp9EWEtUt+DKBkiiNAPqTOkrt+I6TqfIP16RLgHETJEkLoXzHC6hjvy9ttv56//+q+5//77z/l9GzZsYGhoaPRjcPDcv3D4OkepNvlIYZUKr9H4nTFDnAypzeiFUldzP6PUBec1MbfNUD/nkxmKyJBahH1phsbUMqPqnU+Qfl9EWIvU9yBKhggi9EPqDKnrN2K6zidIvx4R7kGEDBGk7gUznK6hX9/71Kc+xfbt29m1axdz5577Rc56enro6emp+We/TCueISvxCo0/Q2aGOBlS62/FE65AXxNPuJqhPs4nMxSVIbUI+9IM9at1RtU7nyD9voiwFqnvQZQMEUToh9QZUtev13SeT5B+PSLcgwgZIkjdC2Y4XV1PSmVZxqc+9SkefPBBvve973HFFVc0V/0M9rCNUpOPFJYos4fGX23LDHEypLZoDWTN/ccEsiosauK1AM1Q4893Ppmh4AypRdiXZqijRgfMqAhrkfoeRMkQQYR+SJ0hdf2aa3TAfIL06xHhHkTIEEHqXjDD6erqyNtvv5377ruPb3zjG/T29vLSSy/x0ksv8dprrzWXYpwjDLKP7VQ42dD1FU6yl4c4wiEzTIMMqc2cD/NXQqnBtwQodcPlq2Dm5L9qb4YmOZ/MUHSG1CLsSzPUrhNmVIS1SH0PomSIIEI/pM6Qun6tOmE+Qfr1iHAPImSIIHUvmOF0dR1K3XPPPQwNDXHjjTcye/bs0Y9vfetbzaWY4HE20cWMhq4t08UOtphhGmVI7er1kJ1q7NqsAkvWmaFVGc7F+WSGFBlSi7AvzVCbTplREdYi9T2IkiGCCP2QOkPq+rXolPkE6dcjwj2IkCGC1L1ghjF1//remT7WrFnTfJJxBtjNAzT2T/cd7mCA3WaYRhlSm70MrtvU2LXX3Z1fb4bWZDgX55MZUmRILcK+NENtOmVGRViL1PcgSoYIIvRD6gyp69eiU+YTpF+PCPcgQoYIUveCGcY09wulU2gHW0Y3y2SPF458/QHWtfTk1gxxMqS2eO3YZp3s8caRr1+3Kb/ODK3NEEGEPWGGOBlSi7AvzRBL6n0RYS1S34MoGSKI0A+pM6SuH0mEfZF6PSLcgwgZIkjdC2bIhT2UgnyzbGIZ+3iEKlUqnKLCKTKqVDhJhVNUqbKPR9jEsinZJGaIkyGlUil/NHHVTph/M1DK3/5y5C00Rz8v5V9ftTP//lLJDK3OEEWEPWGGOBlSirAvzRBPyn0RZS0izIYIGVKL0A+pM6SuH03qfRFhPVLfgygZUovQC2aABl/SqjgD7GaA3cxiLku5jUtYwAX08RrDvMIB9rB1yl9ozQxxMqQ2e1n+cWwQ9m+F4QPwxjCc15e/Feai26b+xSjNEEeEPWGGOBlSi7AvzRBL6n0RYS1S34MoGSKI0A+pM6SuH0mEfZF6PSLcgwgZIkjdC52eIfyh1IgjHOIR7jKDGUKYOQ+u/awZImSIIMKeMEOcDKlF2JdmiCX1voiwFqnvQZQMEUToh9QZUtePJMK+SL0eEe5BhAwRpO6FTs0Q+tf3JEmSJEmSND15KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMJ5KCVJkiRJkqTClbIsy4osODw8TH9/P5TgojlFVs69+iJkVSiV4cLZxdc3gxmiZUhdH+D4YSCDoaEh+vr60oQg/XyCGOuROkPq+mYww0QRZpTzyQxR6pshVgbnUy7CWpjBDFHqR8lQ63xKdyglSROEOZSSpDMI8S99knQGzidJUU02n7oLzHI6n5QygxlCZEhdH8ZO0cPwv/R1fE+awQzjhZpRzqeOz5C6vhliZXA+5SKshRnMEKV+lAy1zqdkh1IXXga3Hiq+7tfnwvEf5QuTor4ZzBAtQ+r6APfNyQdnFKnmE8RYj9QZUtc3gxkmijSjnE9mSF3fDLEyOJ9yEdbCDGaIUj9Khlrnky90LkmSJEmSpMJ5KCVJkiRJkqTCeSglSZIkSZKkwnkoJUmSJEmSpMKle/e9Os1iHktZw6Us5Hx6eZ2jvMwAe9jGEQYLyXDsIOzfBkMDcPIozOiF/oWwaA3MnF9IhBD3IUIGxehH5SLsiQj9EOE+RMigGP2oMan3RYR+SH0PomRQLkJPKhdhX6Tuhwj3IEIG5VL3YwrhD6UWsozlrGMxK8moAlCmTPXNz1dyJ3t5mB1sZoDdU5Lh8E7YuxkObs/fUhEgq0CpK//82Tvh8pWwZD3MXjYlEULchwgZFKMflYuwJyL0Q4T7ECGDYvSjxqTeFxH6IfU9iJJBuQg9qVyEfZG6HyLcgwgZlEvdjymF/vW95axjPTu5ihWUKdNFN110Uxr3eZkyi7mZ9eziJta2tH6WwfObYPuNMPgokOWNkVXe/PrI5xkcfBQe/kDeSFnW0hjJ70OUDJ0uSj8ql3pPROmH1PchSoZOF6UfNSblvojSDxFmQ4QMitOTyqXeFxH6IfU9iJJBMfoxtbCHUjexlo+xCYAuZpzze0e+vprNLd0s+7bAk3fkn2enzv29I19/Yn1+XatEuA8RMihGPyoXYU9E6IcI9yFCBsXoR41JvS8i9EPqexAlg3IRelK5CPsidT9EuAcRMiiXuh8jqOtQ6p577mHJkiX09fXR19fH+9//fh599NGWh1rIMlazuaFrV7OZhdzQdIbDO/PFbsQT6+HFXU1HCHEfImRQjH6MzvlUG+dTazMoRj+2g06ZURH6IfU9iJJBuQg9GV2nzCdI3w8R7kGEDMql7sco6jqUmjt3Ln/wB3/As88+yzPPPMPP//zP89GPfpT//b//d0tDLWcdFU42dG2Fky05wd27GUoNvuJWqTu/vlkR7kOEDIrRj9E5n2rjfGptBsXox3bQKTMqQj+kvgdRMigXoSej65T5BOn7IcI9iJBBudT9GEVdh1KrVq3i5ptvZuHChbz73e/mc5/7HDNnzuSJJ55oWaBZzGMxKyd9jPBsupjBEm5hFnMbznDsYP4CY5M9Pnc22Sn44cNwrIk3KohwHyJkUIx+bAfOp9o4n1qXQTH6sV10woyK0A+p70GUDMpF6Ml20AnzCdL3Q4R7ECGDcqn7MZKGX1OqUqlw//33c/z4cd7//ve3LNBS1oy+8n+jMqos5baGr9+/bewV7xtVKsP+rY1fH+E+RMigGP3YbpxP5+Z8ak0GxejHdjRdZ1SEfkh9D6JkUC5CT7ab6TqfIH0/RLgHETIol7ofI6n7YbF9+/bx/ve/n9dff52ZM2fy4IMP8jM/8zNn/f4TJ05w4sSJ0b8eHh4+58+/lIX1RjqDjEtY0PDVQwMtiAAMH2j82gj3IUIGxejHduF8qp3zqfkMitGP7aSeGVXvfIL0+yJCP6S+B1EyKBehJ9vFdJ9PkL4fItyDCBmUS92PkdR9Nrdo0SKee+45nnzySX7jN36DT3ziE/zN3/zNWb9/48aN9Pf3j37MmzfvnD//fHopN/mmgGW6uIC+hq8/eXTsLRgblVXgjcnn81lFuA8RMihGP7YL51NtnE+tyaAY/dhO6plR9c4nSL8vIvRD6nsQJYNyEXqyXUz3+QTp+yHCPYiQQbnU/RhJ3R153nnnsWDBAq699lo2btzI1VdfzX/+z//5rN+/YcMGhoaGRj8GB8/9S4+vc5Rqk48UVqnwGo2vzoxeKHU1FYFSF5zXxF6NcB8iZFCMfmwXzqfaOJ9ak0Ex+rGd1DOj6p1PkH5fROiH1PcgSgblIvRku5ju8wnS90OEexAhg3Kp+zGSBl/rfUy1Wj3t8c2Jenp66OnpqfnnvUwrnmMr8QqNP8fW34qnGoG+Jp5qjHAfImRQjH5sV86ns3M+NZ9BMfqxnZ1rRtU7nyD9vojQD6nvQZQMykXoyXY13eYTpO+HCPcgQgblUvdjJHU9KbVhwwZ27drFCy+8wL59+9iwYQPf//73ufXWW1sWaA/bKDX5SGGJMnto/BW/Fq2BrLkDZLIqLGri9d8i3IcIGRSjH9uB86l2zqfWZFCMfmwXnTCjIvRD6nsQJYNyEXqyHXTCfIL0/RDhHkTIoFzqfoykro58+eWX+bVf+zUWLVrEhz70IZ5++mn+9E//lOXLl7cs0BEG2cd2Kpxs6PoKJ9nLQxzhUMMZZs6H+Suh1OBzZKVuuHwVzJz816vPKsJ9iJBBMfqxHTifauN8al0GxejHdtEJMypCP6S+B1EyKBehJ9tBJ8wnSN8PEe5BhAzKpe7HSOq6Bffee+9U5TjN42ziam5p6NoyXexgS9MZrl4PBx9u7NqsAkvWNR0hxH2IkEEx+jE651NtnE+tzaAY/dgOOmVGReiH1PcgSgblIvRkdJ0ynyB9P0S4BxEyKJe6H6No7tm9KTLAbh6gsTv8He5ggN1NZ5i9DK7b1Ni1192dX9+sCPchQgbF6EflIuyJCP0Q4T5EyKAY/agxqfdFhH5IfQ+iZFAuQk8qF2FfpO6HCPcgQgblUvdjFCEPpQB2sGV0s0z2eOHI1x9gXUtPbhevHWuSyR6rG/n6dZvy61olwn2IkEEx+lG5CHsiQj9EuA8RMihGP2pM6n0RoR9S34MoGZSL0JPKRdgXqfshwj2IkEG51P0YQdhDKcg3yyaWsY9HqFKlwikqnCKjSoWTVDhFlSr7eIRNLGv5JimV8kfiVu2E+TcDpfxtF0feunH081L+9VU78+8vlVoaI/l9iJKh00XpR+VS74ko/ZD6PkTJ0Omi9KPGpNwXUfohwmyIkEFxelK51PsiQj+kvgdRMihGP6bW4MtqFWeA3Qywm1nMZSm3cQkLuIA+XmOYVzjAHrZO+QutzV6WfxwbhP1bYfgAvDEM5/Xlb8G46Lapf4GxCPchQgbF6EflIuyJCP0Q4T5EyKAY/agxqfdFhH5IfQ+iZFAuQk8qF2FfpO6HCPcgQgblUvdjSuEPpUYc4RCPcFfSDDPnwbWfTRohxH2IkEEx+lG5CHsiQj9EuA8RMihGP2pM6n0RoR9S34MoGZSL0JPKRdgXqfshwj2IkEG51P2YQuhf35MkSZIkSdL05KGUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKV8qyLCuy4PDwMP39/VCCi+YUWTn36ouQVaFUhgtnF1/fDGaIliF1fYDjh4EMhoaG6OvrSxOC9PMJYqxH6gyp65vBDBNFmFHOJzNEqW+GWBmcT7kIa2EGM0SpHyVDrfMp3aGUJE0Q5lBKks4gxL/0SdIZOJ8kRTXZfOouMMvpfFLKDGYIkSF1fRg7RQ/D/9LX8T1pBjOMF2pGOZ86PkPq+maIlcH5lIuwFmYwQ5T6UTLUOp+SHUpdeBnceqj4ul+fC8d/lC9MivpmMEO0DKnrA9w3Jx+cUaSaTxBjPVJnSF3fDGaYKNKMcj6ZIXV9M8TK4HzKRVgLM5ghSv0oGWqdT77QuSRJkiRJkgrnoZQkSZIkSZIK56GUJEmSJEmSCuehlCRJkiRJkgrnoZQkSZIkSZIKl+zd9+o1i3ksZQ2XspDz6eV1jvIyA+xhG0cYLCTDsYOwfxsMDcDJozCjF/oXwqI1MHN+IRFCZEi9FhHugRniZIgg9Z6AGGsRIUOEtUidIcI6mCEWezJGhtTrECVDhLVInSF1/UjsyfT1IcY6RMgQYS06MUP4Q6mFLGM561jMSjKqAJQpU33z85XcyV4eZgebGWD3lGQ4vBP2boaD26H05rNlWQVKXfnnz94Jl6+EJeth9rIpiRAiQ+q1iHAPzBAnQwSp9wTEWIsIGSKsReoMEdbBDLHYkzEypF6HKBkirEXqDKnrR2JPpq8PMdYhQoYIa9HJGUL/+t5y1rGenVzFCsqU6aKbLropjfu8TJnF3Mx6dnETa1taP8vg+U2w/UYYfBTI8kXJKm9+feTzDA4+Cg9/IF/ELJteGSDtWkS4B2aIkyEK51OMDJB+LVJniLAOZojHnkyfAZxPEGMtUmdIXT+aTu/J1PVHpF6HCBkirIUZAh9K3cRaPsYmALqYcc7vHfn6aja3tFH3bYEn78g/z06d+3tHvv7E+vy66ZQh9VpEuAdmiJMhgtR7AmKsRYQMEdYidYYI62CGWOzJGBlSr0OUDBHWInWG1PUjsSfT14cY6xAhQ4S1MEOTh1J/8Ad/QKlU4rd/+7dbk+ZNC1nGajY3dO1qNrOQG5rOcHhnfqMb8cR6eHFX0xFCZEi9FhHugRniZKiH8+nMplM/RFiL1BkirIMZ6jdV8wnsySgZUq9DlAwR1iJ1htT1G+Gfoc5suvRDhHWIkCHCWpgh1/Ch1NNPP81//a//lSVLljSfYoLlrKPCyYaurXCyJaenezdDqcFX3Cp159dPhwyp1yLCPTBDnAy1cj6d3XTqhwhrkTpDhHUwQ32mcj6BPRklQ+p1iJIhwlqkzpC6fr38M9TZTZd+iLAOETJEWAsz5Bo6lDp27Bi33norX/nKV5g1a1bzKcaZxTwWs3LSR/jOposZLOEWZjG34QzHDuYv7jXZo2tnk52CHz4Mx5p4k4AIGVKvRYR7YIY4GWrlfDq36dIPEdYidYYI62CG+kzlfAJ7MkqG1OsQJUOEtUidIXX9evlnqHObDv0QYR0iZIiwFmYY09Ch1O23385HPvIRbrrppuaqn8FS1oy+6n6jMqos5baGr9+/bezV5htVKsP+rY1fHyFD6rWIcA/MECdDrZxPk5sO/RBhLVJniLAOZqjPVM4nsCejZEi9DlEyRFiL1BlS16+Xf4aaXLv3Q4R1iJAhwlqYYUzdD2rdf//9/NVf/RVPP/10Td9/4sQJTpw4MfrXw8PD5/z+S1lYb6QzyLiEBQ1fPTTQggjA8IHGr42QIfVaRLgHZoiToRbOp9q1ez9EWIvUGSKsgxlqN9XzCezJKBlSr0OUDBHWInWG1PXrUc+Masf5BOnXI3V9iLEOETJEWAszjKnrXGxwcJBPf/rTfP3rX+f888+v6ZqNGzfS398/+jFv3rxzfv/59FJu8k0By3RxAX0NX3/y6NjbHzYqq8Abk8/n0BlSr0WEe2CGOBkm43yq3XTohwhrkTpDhHUwQ22KmE9gT0bJkHodomSIsBapM6SuX6t6Z1Q7zidIvx6p60OMdYiQIcJamGFMXd3w7LPP8vLLL/OzP/uzdHd3093dzc6dO/n//f/+f3R3d1OpvPWfaMOGDQwNDY1+DA6e+xcOX+co1SYf56tS4TUavzMzeqHU1VQESl1wXuP7JESG1GsR4R6YIU6GyTifajcd+iHCWqTOEGEdzFCbIuYT2JNRMqRehygZIqxF6gyp69eq3hnVjvMJ0q9H6voQYx0iZIiwFmYYU9ev733oQx9i3759p/292267jSuvvJLf/d3fpavrrf9EPT099PT01FzjZVrxDFmJV2j8GbL+VjxRCPQ1/kRhiAyp1yLCPTBDnAyTcT7Vp937IcJapM4QYR3MUJsi5hPYk1EypF6HKBkirEXqDKnr16reGdWO8wnSr0fq+hBjHSJkiLAWZhhT15NSvb29XHXVVad9XHTRRVx88cVcddVVzSV50x62UWrycb4SZfbQ+KttLVoDWXOHt2RVWNT4a6+FyJB6LSLcAzPEyTAZ51PtpkM/RFiL1BkirIMZalPEfAJ7MkqG1OsQJUOEtUidIXX9WvlnqNq1ez9EWIcIGSKshRnGNPla6613hEH2sZ0KJxu6vsJJ9vIQRzjUcIaZ82H+SijV/TLwuVI3XL4KZk7+69WhM6Reiwj3wAxxMkSQek9AjLWIkCHCWqTOEGEdzBCLPRkjQ+p1iJIhwlqkzpC6fiT2ZPr6EGMdImSIsBZmGNP0odT3v/99vvjFLzb7Y07zOJvoYkZD15bpYgdbms5w9XrITjV2bVaBJeuajhAiQ+q1iHAPzBAnQ72cT281nfohwlqkzhBhHczQmKmYT2BPRsmQeh2iZIiwFqkzpK7fKP8M9VbTpR8irEOEDBHWwgy5cE9KAQywmwdo7J/uO9zBALubzjB7GVy3qbFrr7s7v346ZEi9FhHugRniZIgg9Z6AGGsRIUOEtUidIcI6mCEWezJGhtTrECVDhLVInSF1/UjsyfT1IcY6RMgQYS3MkAt5KAWwgy2jjTrZo30jX3+AdS05NR2xeO3YAk32SNvI16/blF83nTKkXosI98AMcTJEkHpPQIy1iJAhwlqkzhBhHcwQiz0ZI0PqdYiSIcJapM6Qun4k9mT6+hBjHSJkiLAWZgh8KAV5o25iGft4hCpVKpyiwikyqlQ4SYVTVKmyj0fYxLKWNihAqZQ/jrZqJ8y/GSjlb3k48raJo5+X8q+v2pl/f6k0vTJA2rWIcA/MECdDFM6nGBkg/VqkzhBhHcwQjz2ZPgM4nyDGWqTOkLp+NJ3ek6nrj0i9DhEyRFgLM0CDL2lVnAF2M8BuZjGXpdzGJSzgAvp4jWFe4QB72NrUi5zVYvay/OPYIOzfCsMH4I1hOK8vf/vDRbdN/QsQRsiQei0i3AMzxMkQQeo9ATHWIkKGCGuROkOEdTBDLPZkjAyp1yFKhghrkTpD6vqR2JPp60OMdYiQIcJadHKG8IdSI45wiEe4K2mGmfPg2s8mjRAiQ+q1iHAPzBAnQwSp9wTEWIsIGSKsReoMEdbBDLHYkzEypF6HKBkirEXqDKnrR2JPpq8PMdYhQoYIa9GJGUL/+p4kSZIkSZKmJw+lJEmSJEmSVDgPpSRJkiRJklQ4D6UkSZIkSZJUuFKWZVmRBYeHh+nv74cSXDSnyMq5V1+ErAqlMlw4u/j6ZjBDtAyp6wMcPwxkMDQ0RF9fX5oQpJ9PEGM9UmdIXd8MZpgowoxyPpkhSn0zxMrgfMpFWAszmCFK/SgZap1P6Q6lJGmCMIdSknQGIf6lT5LOwPkkKarJ5lN3gVlO55NSZjBDiAyp68PYKXoY/pe+ju9JM5hhvFAzyvnU8RlS1zdDrAzOp1yEtTCDGaLUj5Kh1vmU7FDqwsvg1kPF1/36XDj+o3xhUtQ3gxmiZUhdH+C+OfngjCLVfIIY65E6Q+r6ZjDDRJFmlPPJDKnrmyFWBudTLsJamMEMUepHyVDrfPKFziVJkiRJklQ4D6UkSZIkSZJUOA+lJEmSJEmSVDgPpSRJkiRJklS4dO++V6dZzGMpa7iUhZxPL69zlJcZYA/bOMJgIRmOHYT922BoAE4ehRm90L8QFq2BmfMLiWAGYvSCNF6Enky9L80wJnU/pK6veFL3RIR9aYZc6l6IkkFxROiH1HvTe5CLcB8iZOhE4Q+lFrKM5axjMSvJqAJQpkz1zc9Xcid7eZgdbGaA3VOS4fBO2LsZDm7P31IRIKtAqSv//Nk74fKVsGQ9zF42JRHMQIxekMaL0JOp96UZxqTuh9T1FU/qnoiwL82QS90LUTIojgj9kHpveg9yEe5DhAydLPSv7y1nHevZyVWsoEyZLrrpopvSuM/LlFnMzaxnFzextqX1swye3wTbb4TBR4Es36RZ5c2vj3yewcFH4eEP5Js6y8zQ6gype0GaKHVPRtiXZhiTuh9S11c8KXsiwr40w5gI8yFCBsWRuh8i7E3vQS71fYiSodOFPZS6ibV8jE0AdDHjnN878vXVbG5pk+zbAk/ekX+enTr39458/Yn1+XVmaF2GCL0gjRehJ1PvSzOMSd0PqesrntQ9EWFfmiGXuheiZFAcEfoh9d70HuQi3IcIGRT0UGohy1jN5oauXc1mFnJD0xkO78w3XiOeWA8v7mo6ghmI0QvSeBF6MvW+NMOY1P2Qur7iSd0TEfalGXKpeyFKBsURoR9S703vQS7CfYiQQbm6DqXuvPNOSqXSaR9XXnlly0MtZx0VTjZ0bYWTLTm53LsZSg2+4lapO7/eDM1niNALag/Op9pMl9kQJUPqfkhdX7XrlBkVYV+aIZe6F6Jk0OQ6ZT5B+r3pPchFuA8RMihX95NS73nPe3jxxRdHP/7iL/6ipYFmMY/FrJz08bmz6WIGS7iFWcxtOMOxg/mLvU32KOPZZKfghw/DsSZeoN8MMXpB7cX5NLnpMBuiZEjdD6nrq37TfUZF2JdmyKXuhSgZVLvpPp8g/d70HuQi3IcIGTSm7kOp7u5uLrvsstGPd7zjHS0NtJQ1o69436iMKku5reHr928be/eBRpXKsH9r49ebIUYvqL04n2rT7rMhSobU/ZC6vuo33WdUhH1phlzqXoiSQbWb7vMJ0u9N70Euwn2IkEFj6m7JgYEB5syZwzvf+U5uvfVWDh48eM7vP3HiBMPDw6d9nMulLKw30hlkXMKChq8eGmhBBGD4QOPXmiFGL6i9OJ9q186zIUqG1P2Qur7qV8+Mqnc+QfqeiLAvzZBL3QtRMqh2030+Qfq96T3IRbgPETJoTF2HUv/kn/wTtm3bxmOPPcY999zDP/7jP3LDDTdw9OjRs16zceNG+vv7Rz/mzZt3zhrn00u5yddfL9PFBfQ1fP3Jo2Nvh9morAJvTD6fzXAOEXpB7cP5VLt2nw1RMqTuh9T1VZ96Z1S98wnS90SEfWmGXOpeiJJBtemE+QTp96b3IBfhPkTIoDF1rcSKFStYvXo1S5Ys4Rd/8Rf5n//zf/LjH/+Yb3/722e9ZsOGDQwNDY1+DA6e+xdQX+co1SYfpatS4TUa3ykzeqHU1VQESl1wXhM9aoYYvaD24XyqXbvPhigZUvdD6vqqT70zqt75BOl7IsK+NEMudS9EyaDadMJ8gvR703uQi3AfImTQmAZfdz/3tre9jXe/+90cOHD25/d6enro6emp+We+TCueKSzxCo0/U9jfiqf5gL4mnuYzQ4xeUPtyPp1bO8+GKBlS90Pq+mrOZDOq3vkE6Xsiwr40Qy51L0TJoMZMx/kE6fem9yAX4T5EyKAxTT2zduzYMf7+7/+e2bNntyoPe9hGqclH6UqU2UPjr762aA1kzR2cklVhUROve2aGGL2g9uV8Ort2nw1RMqTuh9T11ZzpOKMi7Esz5FL3QpQMasx0nE+Qfm96D3IR7kOEDBpT10qsX7+enTt38sILL7Bnzx5++Zd/ma6uLn71V3+1ZYGOMMg+tlPhZEPXVzjJXh7iCIcazjBzPsxfCaUGnyMrdcPlq2Dm5L9ebYZziNALah/Op9pMh9kQJUPqfkhdX/XphBkVYV+aIZe6F6JkUG06YT5B+r3pPchFuA8RMmhMXYdShw4d4ld/9VdZtGgR//Sf/lMuvvhinnjiCS655JKWhnqcTXQxo6Fry3Sxgy1NZ7h6PWSnGrs2q8CSdU1HMAMxekHtwflUm+kyG6JkSN0Pqeurdp0yoyLsSzPkUvdClAyaXKfMJ0i/N70HuQj3IUIG5eo6lLr//vs5fPgwJ06c4NChQ9x///28613vanmoAXbzAI11+3e4gwF2N51h9jK4blNj1153d369GZrPEKEX1B6cT7WZLrMhSobU/ZC6vmrXKTMqwr40Qy51L0TJoMl1ynyC9HvTe5CLcB8iZFCuuV+knEI72DLaJJM9Vjfy9QdY19ITy8VrxzbsZI84jnz9uk35dWZoXYYIvSCNF6EnU+9LM4xJ3Q+p6yue1D0RYV+aIZe6F6JkUBwR+iH13vQe5CLchwgZFPhQCvIm2cQy9vEIVapUOEWFU2RUqXCSCqeoUmUfj7CJZS1vjlIpfzxx1U6YfzNQyt8Cc+RtNEc/L+VfX7Uz//5SyQytzpC6F6SJUvdkhH1phjGp+yF1fcWTsici7EszjIkwHyJkUByp+yHC3vQe5FLfhygZOl2DL3FWnAF2M8BuZjGXpdzGJSzgAvp4jWFe4QB72DrlLzA2e1n+cWwQ9m+F4QPwxjCc15e/Heai25p7sTcz1CZCL0jjRejJ1PvSDGNS90Pq+oondU9E2JdmyKXuhSgZFEeEfki9N70HuQj3IUKGThb+UGrEEQ7xCHclzTBzHlz72aQRzECMXpDGi9CTqfelGcak7ofU9RVP6p6IsC/NkEvdC1EyKI4I/ZB6b3oPchHuQ4QMnSj0r+9JkiRJkiRpevJQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhStlWZYVWXB4eJj+/n4owUVziqyce/VFyKpQKsOFs4uvbwYzRMuQuj7A8cNABkNDQ/T19aUJQfr5BDHWI3WG1PXNYIaJIswo55MZotQ3Q6wMzqdchLUwgxmi1I+Sodb5lO5QSpImCHMoJUlnEOJf+iTpDJxPkqKabD51F5jldD4pZQYzhMiQuj6MnaKH4X/p6/ieNIMZxgs1o5xPHZ8hdX0zxMrgfMpFWAszmCFK/SgZap1PyQ6lLrwMbj1UfN2vz4XjP8oXJkV9M5ghWobU9QHum5MPzihSzSeIsR6pM6SubwYzTBRpRjmfzJC6vhliZXA+5SKshRnMEKV+lAy1zidf6FySJEmSJEmF81BKkiRJkiRJhfNQSpIkSZIkSYXzUEqSJEmSJEmF81BKkiRJkiRJhUv27nvt6NhB2L8Nhgbg5FGY0Qv9C2HRGpg53wxFZUhdH2AW81jKGi5lIefTy+sc5WUG2MM2jjBohgIzKBdhX5ghRoYI+9IMGi/1njBDrAwR9mbqDKnr63Sp1yPCvjRDLnUvdGoGD6VqcHgn7N0MB7dD6c1ny7IKlLryz5+9Ey5fCUvWw+xlZpiqDKnrAyxkGctZx2JWklEFoEyZ6pufr+RO9vIwO9jMALvNMIUZlIuwL8wQI0OEfWkGjZd6T5ghVoYIezN1htT1dbrU6xFhX5ohl7oXOj2Dv753DlkGz2+C7TfC4KNAlm+QrPLm10c+z+Dgo/DwB/INlWVmaGWG1PVHLGcd69nJVaygTJkuuumim9K4z8uUWczNrGcXN7G2tQHMoHEi7AszxMkQYV+aQSMi7AkzxMkAMfZm6gyp6+t0Kdcjwr40w5gIe7PTM3godQ77tsCTd+SfZ6fO/b0jX39ifX6dGVqXIXV9gJtYy8fYBEAXM875vSNfX83mlm5WM2i8CPvCDDEyRNiXZtB4qfeEGWJliLA3U2dIXV+nS70eEfalGXKpe8EMuboPpX70ox/x8Y9/nIsvvpgLLriAxYsX88wzz7QkTCSHd+ZN34gn1sOLu8zQigyp60P+GONqNjd07Wo2s5AbzNCiDJNxPk1uuswGM+Qi7Esz1K4TZlTqPWGGWBki7M3UGVLXr1UnzCdIvx4R9qUZcql7wQxj6jqUOnLkCNdffz0zZszg0Ucf5W/+5m/YvHkzs2bNajpINHs3Q6nBV9wqdefXm6H5DKnrQ/4oY4WTDV1b4WRLTpDNMDnnU22my2wwQy7CvjRDbTplRqXeE2aIlSHC3kydIXX9WnTKfIL06xFhX5ohl7oXzDCmrlb4whe+wLx589i6devo37viiiuaDhHNsYP5C63R4O+rZqfghw/DsUGYOc8MjWZIXR/ydx5YzErKDf6maxczWMItzGIuRzhkhiYyTMb5VJvpMBvMkIuwL81Qu06YUan3hBliZYiwN1NnSF2/Vp0wnyD9ekTYl2bIpe4FM5yuruoPPfQQ733ve1m9ejWXXnop11xzDV/5ylcaLh7V/m1jr/zfqFIZ9m+d/PvMELc+wFLWjL7zQKMyqizlNjM0mWEyzqfatftsMEMuwr40Q+06YUal3hNmiJUhwt5MnSF1/Vp1wnyC9OsRYV+aIZe6F8xwurra4R/+4R+45557WLhwIX/6p3/Kb/zGb/Bbv/VbfO1rXzvrNSdOnGB4ePi0j+iGBlrzc4YPmKGZDKnrA1zKwhYkyLiEBWZoMsNknE/1aefZYIZchH1phtrVO6OcT2Zo9wwR9mbqDKnr16oT5hOkX48I+9IMudS9YIbT1fXre9Vqlfe+9718/vOfB+Caa67hr//6r/kv/+W/8IlPfOKM12zcuJHf+73faypk0U4eHXsrykZlFXijiflshvT1Ac6nt+HHGUeU6eIC+szQZIbJOJ9q1+6zwQy5CPvSDLWrd0Y5n8zQ7hki7M3UGVLXr1UnzCdIvx4R9qUZcql7wQwTf0YdZs+ezc/8zM+c9vd++qd/moMHD571mg0bNjA0NDT6MTg42FjSAs3ohVJXcz+j1AXnNbE2ZkhfH+B1jlJt8pHGKhVeo/GpaYbaOJ9q1+6zwQy5CPvSDLWrd0Y5n8zQ7hki7M3UGVLXr1UnzCdIvx4R9qUZcql7wQynq+tJqeuvv579+/ef9vf+7u/+jssvv/ys1/T09NDT09NYukT6W/EUG9DXxFNsZkhfH+BlWvF8aYlXaPz5UjPUxvlUn3aeDWbIRdiXZqhdvTPK+WSGds8QYW+mzpC6fq06YT5B+vWIsC/NkEvdC2Y4XV1PSv3O7/wOTzzxBJ///Oc5cOAA3/jGN/hv/+2/cfvttzcVIppFayBr7sCQrAqLmni9LzOkrw+wh22UmnyksUSZPTT+SnxmqI3zqXbtPhvMkIuwL81Qu06YUan3hBliZYiwN1NnSF2/Vp0wnyD9ekTYl2bIpe4FM5yurgTve9/7ePDBB/nmN7/JVVddxV133cUXv/hFbr311qZCRDNzPsxfCaW6niMbU+qGy1c1/haVZohRH+AIg+xjOxVONnR9hZPs5aGm3iLTDLVxPtVmOswGM+Qi7Esz1K4TZlTqPWGGWBki7M3UGVLXr1UnzCdIvx4R9qUZcql7wQynq/tYbOXKlezbt4/XX3+dH/zgB/zrf/2vmwoQ1dXrITvV2LVZBZasM0MrMqSuD/A4m+hiRkPXluliB1vM0KIMk3E+TW66zAYz5CLsSzPUrhNmVOo9YYZYGSLszdQZUtevVSfMJ0i/HhH2pRlyqXvBDON/js5o9jK4blNj1153d369GZrPkLo+wAC7eYDGJt93uIMBdpuhRRmUi7AvzBAjQ4R9aQaNl3pPmCFWhgh7M3WG1PV1utTrEWFfmiGXuhfMMMZDqXNYvHZss0z2eOHI16/blF9nhtZlSF0fYAdbRjfrZI83jnz9Ada19L9umUHjRdgXZoiRIcK+NIPGS70nzBArQ4S9mTpD6vo6Xer1iLAvzZBL3QtmyHkodQ6lUv5o4KqdMP9moJS//eTIW1iOfl7Kv75qZ/79pZIZWpkhdf0RO9jCJpaxj0eoUqXCKSqcIqNKhZNUOEWVKvt4hE0sm5I/SJhBIyLsCzPEyRBhX5pBIyLsCTPEyQAx9mbqDKnr63Qp1yPCvjTDmAh7s9MzNPjyYp1l9rL849gg7N8KwwfgjWE4ry9/K8pFtzX3QmtmaI/6kD/eOMBuZjGXpdzGJSzgAvp4jWFe4QB72DrlL0ZpBo0XYV+YIUaGCPvSDBov9Z4wQ6wMEfZm6gyp6+t0qdcjwr40Qy51L3R6Bg+l6jBzHlz7WTOkzpC6PvD/Z+/vg+wqzzvf+7t3t2he1N2WMQQpahFsySIJkosQ5xBRlnGMHIMlO6mgMzOFJxaZOTWJiY8TSUysqRoPz2Bb8VhSeSZ2ODkeLHkKHNu4QsqIAwlybKGUwovJgJSJo7SSgFoWDNSM3C0JENLu9fyx6Be99t5r7173tXt/P1Vdbuheff183fd9IRar9+YwB3mYu80QIINyEc6FGWJkiHAuzaDJUp8JM8TKEOFsps6Qur5OlXo9IpxLM+RS74VOzeCv70mSJEmSJKl03pSSJEmSJElS6bwpJUmSJEmSpNJ5U0qSJEmSJEmlq2RZlpVZcGRkhP7+fqjAJfPKrJx79UXIRqFShYvnll/fDGaIliF1fYBjh4AMhoeH6evrSxOC9PMJYqxH6gyp65vBDKeLMKOcT2aIUt8MsTI4n3IR1sIMZohSP0qGeudTuptSknSaMDelJOksQvxLnySdhfNJUlRTzafuErOcyielzGCGEBlS14eJu+hh+F/6On5PmsEMk4WaUc6njs+Qur4ZYmVwPuUirIUZzBClfpQM9c6nZDelLr4CbjtYft3758OxH+ULk6K+GcwQLUPq+gD3zcsHZxSp5hPEWI/UGVLXN4MZThdpRjmfzJC6vhliZXA+5SKshRnMEKV+lAz1zidf6FySJEmSJEml86aUJEmSJEmSSudNKUmSJEmSJJXOm1KSJEmSJEkqXbp331MhRw/Avm0wPAgnjsCsXuhfBIvXwOwFnZFhDgMsYw2Xs4gL6eV1jvAyg+xmG4cZmv4ApO8BxOiDNFmEcxEhQ+qzaQ+kM0U4FxEyRDib9kGTuRYxzkSEDBH2gn1Iw5tSbeLQTtizGQ5sz9/WESCrQaUr//yZu+DKlbB0PcxdPjMzLGI5K1jHElaSMQpAlSqjb36+krvYw0PsYDOD7Gp9ANL3AGL0QZoswrmIkCH12bQH0pkinIsIGSKcTfugyVyLGGciQoYIe8E+pOWv7wWXZfDcJth+Iww9AmT5Aclqb3597PMMDjwCD703P1BZNrMyrGAd69nJNdxMlSpddNNFN5VJn1epsoRbWM/j3MTa1hUnRg8gfR+kySKciwgZIO3ZtAfSmSKciwgZIP3ZtA86XaevRYQzESEDpN8L9iEGb0oFt3cLPHln/nl28vzfO/b1J9bn182UDDexllvZBEAXs877vWNfX83mlh7W1D2AGH2QJotwLiJkSH027YF0pgjnIkKGCGfTPmgy1yLGmYiQIcJesA8xeFMqsEM7801fxBPr4cXH2z/DIpazms2Frl3NZhbxnuYCkL4HEKMP0mQRzkWEDKnPpj2QzhThXETIEOFs2gdN5lrEOBMRMkTYC/YhjoZuSv3UT/0UlUrljI877rhjuvJ1tD2boVLwVb8q3fn17Z5hBeuocaLQtTVOtOQOcuoeQIw+tANnVHkinIsIGVKfTXvQPpxP5YlwLiJkiHA27UN7KGs+uRYxzkSEDBH2gn2Io6GbUk8//TQvvvji+Mdjjz0GwOrVq6clXCc7eiB/obWpHiM8l+wkvPAQHG3iBfpTZ5jDAEtYOeVjjOfSxSyW8mHmML9YANL3AGL0oV04o8oR4VxEyJD6bNqD9uJ8KkeEcxEhQ4SzaR/aRxnzybWIcSYiZIiwF+xDLA3dlLrsssu44oorxj+2b9/OO97xDt773vdOV76OtW/bxCv/F1Wpwr6t7ZthGWvG33mgqIxRlnF74etT9wBi9KFdOKPKEeFcRMiQ+mzag/bifCpHhHMRIUOEs2kf2kcZ88m1iHEmImSIsBfsQywFH1iDN954g/vuu4+1a9dSqVTO+X3Hjx/n+PHj4389MjJStGRHGR5szc8Z2d++GS5nUQuqZ1zGwsJXp+4BxOhDO6pnRjmfiolwLiJkSH027UH7cj5NnwjnIkKGCGfTPrSn6ZpPrkWMMxEhQ4S9YB9iKXx/8E//9E/58Y9/zJo1a877fRs3bqS/v3/8Y2BgoGjJjnLiyMRbURaV1eCNJv4MmzrDhfRSbfK1+Kt0cRF9ha9P3QOI0Yd2VM+Mcj4VE+FcRMiQ+mzag/blfJo+Ec5FhAwRzqZ9aE/TNZ9cixhnIkKGCHvBPsRSuAv33nsvN998M/PmzTvv923YsIHh4eHxj6GhJn7xsoPM6oVKV3M/o9IFFzSxR1NneJ0jjDb5SOMoNV6j+LRI3QOI0Yd2VM+Mcj4VE+FcRMiQ+mzag/blfJo+Ec5FhAwRzqZ9aE/TNZ9cixhnIkKGCHvBPsRS6Nf3XnjhBXbs2MGf/MmfTPm9PT099PT0FCnT0fpb8TQf0NfE03ypM7xMK56rrPAKxZ+rTN0DiNGHdlPvjHI+FRPhXETIkPps2oP25HyaXhHORYQMEc6mfWg/0zmfXIsYZyJChgh7wT7EUuhJqa1bt3L55ZfzoQ99qNV59KbFayBr7sYp2SgsbuJ1z1Jn2M02Kk0+0lihym6KvwJd6h5AjD60G2fU9IpwLiJkSH027UF7cj5NrwjnIkKGCGfTPrSf6ZxPrkWMMxEhQ4S9YB9iabgLo6OjbN26lY997GN0dxd+nXRNYfYCWLASKgVbXOmGK1fB7CZegiJ1hsMMsZft1DhR6PoaJ9jDdzjMwWIBSN8DiNGHduKMmn4RzkWEDKnPpj1oP86n6RfhXETIEOFs2of2Mt3zybWIcSYiZIiwF+xDLA3flNqxYwcHDhzgN37jN6YjjyZ513rITha7NqvB0nXtn+ExNtHFrELXVuliB1uaC0D6HkCMPrQLZ1Q5IpyLCBlSn0170F6cT+WIcC4iZIhwNu1D+yhjPrkWMc5EhAwR9oJ9iKPhm1If+MAHyLKMd77zndORR5PMXQ7Xbyp27fVfyK9v9wyD7OIBip34b3Mng+xqLgDpewAx+tAunFHliHAuImRIfTbtQXtxPpUjwrmIkCHC2bQP7aOM+eRaxDgTETJE2Av2IY7mfolR027J2onDMtXjhWNfv35Tft1MybCDLeOHdarHG8e+/gDrWnrnOHUPIEYfpMkinIsIGVKfTXsgnSnCuYiQIcLZtA+azLWIcSYiZIiwF+xDDN6UCq5SyR8NXLUTFtwCVPK3nxx7C8vxzyv511ftzL+/UplZGXawhU0sZy8PM8ooNU5S4yQZo9Q4QY2TjDLKXh5mE8tbfkgj9ADS90GaLMK5iJAB0p5NeyCdKcK5iJAB0p9N+6DTdfpaRDgTETJA+r1gH2LwVTbbxNzl+cfRIdi3FUb2wxsjcEFf/laUi29v7oXW2iHDILsYZBdzmM8ybucyFnIRfbzGCK+wn91snfYXekvdA4jRB2myCOciQobUZ9MeSGeKcC4iZIhwNu2DJnMtYpyJCBki7AX7kJY3pdrM7AG47tOdneEwB3mYu9MFIH0PIEYfpMkinIsIGVKfTXsgnSnCuYiQIcLZtA+azLWIcSYiZIiwF+xDGv76niRJkiRJkkrnTSlJkiRJkiSVzptSkiRJkiRJKp03pSRJkiRJklS6SpZlWZkFR0ZG6O/vhwpcMq/MyrlXX4RsFCpVuHhu+fXNYIZoGVLXBzh2CMhgeHiYvr6+NCFIP58gxnqkzpC6vhnMcLoIM8r5ZIYo9c0QK4PzKRdhLcxghij1o2Sodz6luyklSacJc1NKks4ixL/0SdJZOJ8kRTXVfOouMcupfFLKDGYIkSF1fZi4ix6G/6Wv4/ekGcwwWagZ5Xzq+Ayp65shVgbnUy7CWpjBDFHqR8lQ73xKdlPq4ivgtoPl171/Phz7Ub4wKeqbwQzRMqSuD3DfvHxwRpFqPkGM9UidIXV9M5jhdJFmlPPJDKnrmyFWBudTLsJamMEMUepHyVDvfPKFziVJkiRJklQ6b0pJkiRJkiSpdN6UkiRJkiRJUum8KSVJkiRJkqTSeVNKkiRJkiRJpUv27nsq5ugB2LcNhgfhxBGY1Qv9i2DxGpi9oJwMcxhgGWu4nEVcSC+vc4SXGWQ32zjM0Iyvb4ZYGRSH8ylGhtT1zaCInE9miJQhdX3F4nwyQ6dn8KZUmzi0E/ZshgPbofLm821ZDSpd+efP3AVXroSl62Hu8unJsIjlrGAdS1hJxigAVaqMvvn5Su5iDw+xg80MsmvG1TdDrAyKw/kUI0Pq+mZQRM4nM0TKkLq+YnE+mcEMvFlDoWUZPLcJtt8IQ48AWT6sstqbXx/7PIMDj8BD782HW5a1NscK1rGenVzDzVSp0kU3XXRTmfR5lSpLuIX1PM5NrJ1R9c0QK4NicD7FyZC6vhkUjfPJDNEypK6vOJxPZjDDqbwpFdzeLfDknfnn2cnzf+/Y159Yn1/XKjexllvZBEAXs877vWNfX83mlm3U1PXNECuD4nA+xciQur4ZFJHzyQyRMqSur1icT2Yww6kauilVq9X49//+33PVVVdx0UUX8Y53vIO7776brNW3bQXkj3Q+sb7YtU+shxcfbz7DIpazms2Frl3NZhbxnraub4ZYGc7H+VQu51OMDKnrm6F+zqjyOJ/MEClD6vr1cD6Vx/lkBjOcqaGbUp///Oe55557+NKXvsQPf/hDPv/5z/Of/tN/4g/+4A+aDqIz7dkMlYKv+lXpzq9v1grWUeNEoWtrnGj67mnq+maIleF8nE/lcj7FyJC6vhnq54wqj/PJDJEypK5fD+dTeZxPZjDDmRq6KbV7924+8pGP8KEPfYif+qmf4tZbb+UDH/gATz31VNNBdKqjB/IXvZvqkc5zyU7CCw/B0SZeHH8OAyxh5ZSP8J1LF7NYyoeZw/y2rG+GWBmm4nwqj/MpRobU9c3QGGdUOZxPZoiUIXX9ejmfyuF8MoMZzq6hm1LLli3ju9/9Ln//938PwHPPPcdf/uVfcvPNNzcVQmfat23iXRiKqlRh39bi1y9jzfir7heVMcoybm/L+maIlWEqzqfyOJ9iZEhd3wyNcUaVw/lkhkgZUtevl/OpHM4nM5jh7Bp6ePBTn/oUIyMjXH311XR1dVGr1fjsZz/Lbbfdds5rjh8/zvHjx8f/emRkpHjaDjI82JqfM7K/+LWXs6gFCTIuY2Fb1jdDrAxTcT6Vx/kUI0Pq+mZoTKMzyvlUjPPJDJEypK5fL+dTOZxPZjDD2TV0r/Zb3/oW999/P1//+tf567/+a772ta+xadMmvva1r53zmo0bN9Lf3z/+MTAw0FTgTnHiyMTbghaV1eCNJv4ZcSG9VJt8g8YqXVxEX1vWN0OsDFNxPpXH+RQjQ+r6ZmhMozPK+VSM88kMkTKkrl8v51M5nE9mMMO5fkYD7rzzTj71qU/xz//5P2fJkiX8y3/5L/nd3/1dNm7ceM5rNmzYwPDw8PjH0FATvwTbQWb1QqWruZ9R6YILmtgfr3OE0SYf5xulxmsUm5yp65shVoapOJ/K43yKkSF1fTM0ptEZ5XwqxvlkhkgZUtevl/OpHM4nM5jh7Br69b1XX32VavXU+1hdXV2Mjp77/0hPTw89PT3F0nWw/lY8SQf0NfEk3cu04hnTCq9Q7BnT1PXNECvDVJxP5XE+xciQur4ZGtPojHI+FeN8MkOkDKnr18v5VA7nkxnMcHYNPSm1atUqPvvZz/Lwww/z/PPP8+CDD7JlyxZ+9Vd/takQOtPiNZA1d9OSbBQWN/GaY7vZRqXJx/kqVNlNsVfjS13fDLEyTMX5VB7nU4wMqeuboTHOqHI4n8wQKUPq+vVyPpXD+WQGM5xdQwn+4A/+gFtvvZWPf/zj/PRP/zTr16/n3/ybf8Pdd9/dVAidafYCWLASKg09yzah0g1XroLZTfyK92GG2Mt2apwodH2NE+zhOxzmYFvWN0OsDFNxPpXH+RQjQ+r6ZmiMM6ocziczRMqQun69nE/lcD6ZwQxn19BNqd7eXr74xS/ywgsv8Nprr/EP//APfOYzn+GCCy5oKoTO7l3rITtZ7NqsBkvXNZ/hMTbRxaxC11bpYgdb2rq+GWJlOB/nU7mcTzEypK5vhvo5o8rjfDJDpAyp69fD+VQe55MZzHC2n6Ow5i6H6zcVu/b6L+TXN2uQXTxAsen3be5kkF1tXd8MsTIoDudTjAyp65tBETmfzBApQ+r6isX5ZAYznMmbUsEtWTsxuKZ61HPs69dvyq9rlR1sGd+oUz3aN/b1B1jXsv+yk7q+GWJlUBzOpxgZUtc3gyJyPpkhUobU9RWL88kMZjhVwd9oVVkqlfwxzcveDXs2wwsPQeXNW4lZbeJtRbNRWHBL/r2tuIN+uh1s4QWe5ibWspQPk7351pFVqoxSAypUqLKXh9nBlpb/V53U9c0QK4NicD7FyZC6vhkUjfPJDNEypK6vOJxPZjDDqbwp1SbmLs8/jg7Bvq0wsh/eGIEL+vK3BV18e3MvelePQXYxyC7mMJ9l3M5lLOQi+niNEV5hP7vZOq0vxJi6vhliZVAczqcYGVLXN4Micj6ZIVKG1PUVi/PJDGbIeVOqzcwegOs+nTbDYQ7yMOnejSN1fTPEyqA4nE8xMqSubwZF5HwyQ6QMqesrFueTGTo9g68pJUmSJEmSpNJ5U0qSJEmSJEml86aUJEmSJEmSSudNKUmSJEmSJJWukmVZVmbB4eFh3vKWtwBw8dwyK+defQnIgApcfEX59c1ghmgZUtcHePXF/H9//OMf09/fnyYE6ecTBFkP96QZzHBqhgAzyvlkhij1zRAsg/MJCLIWZjBDkPphMtQ5n0q/KXXw4EEGBqb5vS0ltaWhoSHmz5+frL7zSdL5pJxRzidJ5+N8khTVVPOp9JtSo6OjHDp0iN7eXiqVSsPXj4yMMDAwwNDQEH19fdOQ0AztkiF1fTO0LkOWZRw5coR58+ZRrab7rWLnkxlmUobU9WdShggzqtn5BOnXI3V9M5ghWgbn04TUaxEhQ+r6ZjBDqzPUO5+6mwlZRLVabcld/L6+vmSLY4ZYGVLXN0NrMqT8tb0xziczzMQMqevPlAypZ1Sr5hOkX4/U9c1ghmgZnE8TUq9FhAyp65vBDK3MUM988oXOJUmSJEmSVDpvSkmSJEmSJKl0bXdTqqenh//wH/4DPT09ZujwDKnrmyFWhggi9MEMZohS3wzxpO5F6vpmMEO0DKnrRxKhF6kzpK5vBjOkylD6C51LkiRJkiRJbfeklCRJkiRJktqfN6UkSZIkSZJUOm9KSZIkSZIkqXTelJIkSZIkSVLp2uqm1F/91V/R1dXFhz70odJrr1mzhkqlMv5x6aWX8sEPfpA9e/aUnuWll17iE5/4BG9/+9vp6elhYGCAVatW8d3vfnfaa0/uw6xZs/iJn/gJVqxYwVe/+lVGR0envf7pGSZ/fPCDHyyl/lQ59u/fX0r9l156iU9+8pMsXLiQCy+8kJ/4iZ/ghhtu4J577uHVV1+d9vpr1qzhV37lV874+9///vepVCr8+Mc/nvYM0TijnE+n50g1o1LPJ0g7o5xPZ3I+OZ9Oz+F88s9QUTifnE+n53A+ddZ8aqubUvfeey+f+MQnePzxxzl06FDp9T/4wQ/y4osv8uKLL/Ld736X7u5uVq5cWWqG559/nuuuu46/+Iu/4Atf+AJ79+7l0Ucf5X3vex933HFHKRnG+vD888/zyCOP8L73vY9PfvKTrFy5kpMnT5aaYfLHH//xH5dSe6ocV1111bTX/cd//EeuvfZa/vzP/5zPfe5z/Pf//t/5q7/6K/7tv/23bN++nR07dkx7Bp2p02eU8+nMHClnVKr5BM6oiJxPzqfTczifnE9ROJ+cT6fncD511nzqTh2gXkePHuWb3/wmP/jBD3jppZfYtm0b/+7f/btSM/T09HDFFVcAcMUVV/CpT32K97znPbzyyitcdtllpWT4+Mc/TqVS4amnnuKSSy4Z//s/+7M/y2/8xm+UkmFyH37yJ3+Sn/u5n+P666/n/e9/P9u2beNf/+t/XWqGlFLl+PjHP053dzc/+MEPTtkHb3/72/nIRz5ClmWlZ+p0zijn07lypJIygzMqFueT8+lcOVJxPmmM88n5dK4cqTifytc2T0p961vf4uqrr2bx4sV89KMf5atf/WrSRTl69Cj33XcfCxcu5NJLLy2l5v/+3/+bRx99lDvuuOOUTTrmLW95Syk5zuaXfumXeNe73sWf/MmfJMvQKf7X//pf/Pmf//k59wFApVIpOZU6fUY5nzTGGRWP88n5pJzzKR7nk/NJuU6eT21zU+ree+/lox/9KJA/Ujc8PMzOnTtLzbB9+3Zmz57N7Nmz6e3t5Tvf+Q7f/OY3qVbLaeP+/fvJsoyrr766lHqNuvrqq3n++edLqTV5LcY+Pve5z5VS+3w5Vq9ePe01x/bB4sWLT/n7b3vb28Zz/N7v/d6054Czr8PNN99cSu1oOn1GOZ9OFWFGpZhPEGdGOZ8mOJ+cT5M5n9LPJ3BGjXE+OZ8mcz515nxqi1/f27dvH0899RQPPvggAN3d3fyzf/bPuPfee7nxxhtLy/G+972Pe+65B4DDhw/zh3/4h9x888089dRTXHnlldNeP/rjelmWlXb3dvJajHnrW99aSu3z5TjXXe0yPPXUU4yOjnLbbbdx/PjxUmqebR2efPLJ8T9cdApnlPPpdBFmVKT5BOXPKOdTzvnkfDqd8+lM/hkqDeeT8+l0zqczdcJ8aoubUvfeey8nT55k3rx5438vyzJ6enr40pe+RH9/fyk5LrnkEhYuXDj+1//1v/5X+vv7+cpXvsJnPvOZaa+/aNEiKpUKf/d3fzfttYr44Q9/WNqLwJ2+FqmkyLFw4UIqlQr79u075e+//e1vB+Ciiy4qLcvZ/v8fPHiwtPpROKOcT6eLMKNSZYgyo5xPOeeT8+l0zqf08wmcUeB8AufT6ZxPnTmfwv/63smTJ/lv/+2/sXnzZp599tnxj+eee4558+Ylece1MZVKhWq1ymuvvVZKvbe+9a388i//Ml/+8pc5duzYGV9P+faxf/EXf8HevXv5tV/7tWQZOsWll17KihUr+NKXvnTWfaByOaNyzieNcUbF4XzKOZ80xvkUh/Mp53zSmE6eT+GflNq+fTuHDx/mX/2rf3XG3fJf+7Vf49577+U3f/M3S8ly/PhxXnrpJSB/tPNLX/oSR48eZdWqVaXUB/jyl7/MDTfcwC/8wi/wH//jf2Tp0qWcPHmSxx57jHvuuYcf/vCH055hrA+1Wo3/+T//J48++igbN25k5cqV/Pqv//q015+cYbLu7m7e9ra3lVI/tT/8wz/khhtu4Od//ue56667WLp0KdVqlaeffpq/+7u/47rrrksdsWM4oyY4n87MMZkzyhlVNufTBOfTmTkmcz45n8rmfJrgfDozx2TOpw6YT1lwK1euzG655Zazfu3JJ5/MgOy5556b9hwf+9jHMmD8o7e3N3v3u9+dffvb35722qc7dOhQdscdd2RXXnlldsEFF2Q/+ZM/mX34wx/Ovve970177cl96O7uzi677LLspptuyr761a9mtVpt2uufnmHyx+LFi0upPznHRz7ykVJrTnbo0KHst3/7t7OrrroqmzVrVjZ79uzsF37hF7IvfOEL2bFjx6a9/rn+/3/ve9/LgOzw4cPTniECZ9SpOn0+nZ4j1YxKPZ+yLO2Mcj7lnE+ncj45n8b4Z6j0nE+ncj45n8Z04nyqZFnwV1eTJEmSJEnSjBP+NaUkSZIkSZI083hTSpIkSZIkSaXzppQkSZIkSZJK500pSZIkSZIklc6bUpIkSZIkSSqdN6UkSZIkSZJUOm9KSZIkSZIkqXTelJIkSZIkSVLpvCklSZIkSZKk0nlTSpIkSZIkSaXzppQkSZIkSZJK500pSZIkSZIklc6bUpIkSZIkSSqdN6UkSZIkSZJUOm9KSZIkSZIkqXTelJIkSZIkSVLpussuODo6yqFDh+jt7aVSqZRdXlJAWZZx5MgR5s2bR7Wa7l6580nS2USYUc4nSWfjfJIUVb3zqfSbUocOHWJgYKDsspLawNDQEPPnz09W3/kk6XxSzijnk6TzcT5Jimqq+VT6Tane3t7xzy+eW3Z1ePUlIAMqcPEV5dc3gxmiZUhdH+DVF/P/nTwfUkg9nyDIergnzWCGUzMEmFHOJzNEqW+GYBmcT0CQtTCDGYLUD5OhzvlU+k2psUc6L54LHz1UdnW4fz4c+xFcMg9uO1h+fTOYIVqG1PUB7puXD63Uj3ynnk8QYz1SZ0hd3wxmOF2EGeV8MkOU+maIlcH5lIuwFmYwQ5T6UTLUO598oXNJkiRJkiSVzptSkiRJkiRJKp03pSRJkiRJklQ6b0pJkiRJkiSpdKW/0HlRcxhgGWu4nEVcSC+vc4SXGWQ32zjMUCkZjh6AfdtgeBBOHIFZvdC/CBavgdkLSokQgn2QThVhPpkh53ySzpT6bKauHyWD80k6U4SzmTpD6vrgfFJa4W9KLWI5K1jHElaSMQpAlSqjb36+krvYw0PsYDOD7JqWDId2wp7NcGA7VN58tiyrQaUr//yZu+DKlbB0PcxdPi0RQrAP0qkizCcz5JxP0plSn83U9aNkcD5JZ4pwNlNnSF0fnE+KIfSv761gHevZyTXcTJUqXXTTRTeVSZ9XqbKEW1jP49zE2pbWzzJ4bhNsvxGGHgGy/JBmtTe/PvZ5BgcegYfemx/qLGtpjOTsg3Sm1PPJDDnnk3R2qc9m6voRMjifpLNLfTYjZEhd3/mkSMLelLqJtdzKJgC6mHXe7x37+mo2t/TA7t0CT96Zf56dPP/3jn39ifX5dTOJfZBOFWE+mSHnfJLOlPpspq4fJYPzSTpThLOZOkPq+uB8UiwN35R6/PHHWbVqFfPmzaNSqfCnf/qnLQ+1iOWsZnOha1ezmUW8p+kMh3bmB6+IJ9bDi483HSEE+6B20inzyQw555PaSRnzCdKfzdT1o2RwPqmddMp8ipAhdX1wPimehm9KHTt2jHe96118+ctfno48QP44Y40Tha6tcaIld5H3bIZKwVfcqnTn188E9kHtpFPmkxlyzie1kzLmE6Q/m6nrR8ngfFI76ZT5FCFD6vrgfFI8DW/Hm2++mZtvvnk6sgD5uw8sYSXVgr9Z2MUslvJh5jCfwxws9DOOHshf7I2CvzObnYQXHoKjQzB7oNjPiMA+qN10wnwyQ875pHYz3fMJ0p/N1PWjZHA+qd10wnyKkCF1fXA+KaZwrym1jDXj7z5QVMYoy7i98PX7tk28+0BRlSrs29rcz0jNPkinijCfzJBzPklnSn02U9ePksH5JJ0pwtlMnSF1fXA+KaaCD+7V7/jx4xw/fnz8r0dGRs77/ZezqAVVMy5jYeGrhwdbEAEY2d+an5OKfdBM147zyQw555NmukbnE6Q/m6nrR8ngfNJM147zKUKG1PXB+aSYpv1JqY0bN9Lf3z/+MTBw/uf8LqS38CONY6p0cRF9ha8/cWTi7TCLymrwxtTzOTT7oJmuHeeTGXLOJ810jc4nSH82U9ePksH5pJmuHedThAyp64PzSTFN+02pDRs2MDw8PP4xNDR03u9/nSOMNvlY4yg1XqP4SZnVC5WupiJQ6YILis+LEOyDZrp2nE9myDmfNNM1Op8g/dlMXT9KBueTZrp2nE8RMqSuD84nxTTtv77X09NDT09P3d//Mq14prDCKxR/prC/FU9WAn3Fn6wMwT5opmvH+WSGnPNJM12j8wnSn83U9aNkcD5ppmvH+RQhQ+r64HxSTA0/KXX06FGeffZZnn32WQD+6Z/+iWeffZYDBw60JNButlFp8gGuClV2U/zV1xavgay5m9hko7C4+GvQhWAf1G46YT6ZIed8UruZ7vkE6c9m6vpRMjif1G46YT5FyJC6PjifFFPDp+IHP/gB1157Lddeey0Aa9eu5dprr+XTn/50SwIdZoi9bKfGiULX1zjBHr5T+G0yAWYvgAUroVLwObJKN1y5qv3fJtM+qN10wnwyQ875pHYz3fMJ0p/N1PWjZHA+qd10wnyKkCF1fXA+KaaGb0rdeOONZFl2xse2bdtaFuoxNtHFrELXVuliB1uazvCu9ZCdLHZtVoOl65qOEIJ9UDvplPlkhpzzSe2kjPkE6c9m6vpRMjif1E46ZT5FyJC6PjifFM+0v9B5EYPs4gGK7fZvcyeD7Go6w9zlcP2mYtde/4X8+pnAPkinijCfzJBzPklnSn02U9ePksH5JJ0pwtlMnSF1fXA+KZ6QN6UAdrBl/MBO9Yjj2NcfYF1L7h6PWbJ24sBO9Yjj2Nev35RfN5PYB+lUEeaTGXLOJ+lMqc9m6vpRMjifpDNFOJupM6SuD84nxRL2phTkB3YTy9nLw4wySo2T1DhJxig1TlDjJKOMspeH2cTylh5UgEolfzxx1U5YcAtQyd8Cc+xtNMc/r+QV8y3CAAEAAElEQVRfX7Uz//5KpaUxkrMP0plSzycz5JxP0tmlPpup60fI4HySzi712YyQIXV955MiKfgSZ+UZZBeD7GIO81nG7VzGQi6ij9cY4RX2s5utTb3YWz3mLs8/jg7Bvq0wsh/eGIEL+vK3w1x8e2e82Jt9kE4VYT6ZIed8ks6U+mymrh8lg/NJOlOEs5k6Q+r64HxSDOFvSo05zEEe5u6kGWYPwHWtexOKtmUfpFNFmE9myDmfpDOlPpup60fJ4HySzhThbKbOkLo+OJ+UVuhf35MkSZIkSdLM5E0pSZIkSZIklc6bUpIkSZIkSSqdN6UkSZIkSZJUukqWZVmZBUdGRujv74cKXDKvzMq5V1+EbBQqVbh4bvn1zWCGaBlS1wc4dgjIYHh4mL6+vjQhSD+fIMZ6pM6Qur4ZzHC6CDPK+WSGKPXNECuD8ykXYS3MYIYo9aNkqHc+pbspJUmnCXNTSpLOIsS/9EnSWTifJEU11XzqLjHLqXxSygxmCJEhdX2YuIsehv+lr+P3pBnMMFmoGeV86vgMqeubIVYG51MuwlqYwQxR6kfJUO98SnZT6uIr4LaD5de9fz4c+1G+MCnqm8EM0TKkrg9w37x8cEaRaj5BjPVInSF1fTOY4XSRZpTzyQyp65shVgbnUy7CWpjBDFHqR8lQ73zyhc4lSZIkSZJUOm9KSZIkSZIkqXTelJIkSZIkSVLpvCklSZIkSZKk0nlTSpIkSZIkSaVL9u57jZrDAMtYw+Us4kJ6eZ0jvMwgu9nGYYZKyXD0AOzbBsODcOIIzOqF/kWweA3MXlBKBDMEEaEHZogjwnwyQ849GaMHZogl9dlMXT9KBvdkLkIfUmdIXT+SCGczdYbU9cE9OSZCHzoxQ/ibUotYzgrWsYSVZIwCUKXK6Jufr+Qu9vAQO9jMILumJcOhnbBnMxzYDpU3ny3LalDpyj9/5i64ciUsXQ9zl09LBDMEEaEHZogjwnwyQ849GaMHZogl9dlMXT9KBvdkLkIfUmdIXT+SCGczdYbU9cE9OSZCHzo5Q+hf31vBOtazk2u4mSpVuuimi24qkz6vUmUJt7Cex7mJtS2tn2Xw3CbYfiMMPQJk+aJktTe/PvZ5BgcegYfemy9ilpmh1RlSi9ADM8SSej6ZIeeejNEDM8ST+mymrh8hg3syF6EPqTOkrh9N6rMZIUPq+u7JXIQ+mCHwTambWMutbAKgi1nn/d6xr69mc0sP7N4t8OSd+efZyfN/79jXn1ifX2eG1mZILUIPzBBHhPlkhpx7MkYPzBBL6rOZun6UDO7JXIQ+pM6Qun4kEc5m6gyp64N7ckyEPpihwZtSGzdu5N3vfje9vb1cfvnl/Mqv/Ar79u1rTZJJFrGc1WwudO1qNrOI9zSd4dDOvNFFPLEeXny86QhmCCJCD8wwtU6aT2bIRd+TZYjQAzPUp1NmVOr6UTK0w54sQ4Q+pM6Qun49OmU+RciQuj60x54sQ4Q+mCHX0E2pnTt3cscdd/DEE0/w2GOPceLECT7wgQ9w7Nix5pNMsoJ11DhR6NoaJ1pyF3nPZqgUfMWtSnd+vRlakyG1CD0ww9Q6aT6ZIRd9T5YhQg/MUJ9OmVGp60fJ0A57sgwR+pA6Q+r69eiU+RQhQ+r60B57sgwR+mCGXEPlH3300VP+etu2bVx++eU888wzLF/emle6msMAS1hJteBvFnYxi6V8mDnM5zAHC/2MowfyF/ei4O9IZifhhYfg6BDMHij2M8wQQ4QemKE+nTKfzJBrhz053SL0wAz164QZlbp+lAztsienW4Q+pM6Qun69OmE+RciQuj60z56cbhH6YIYJTb2m1PDwMABvfetbm/kxp1jGmvF3HygqY5Rl3F74+n3bJl5tvqhKFfZtLX69GWKI0AMzFDNT55MZcu24J1stQg/MUNxMnFGp60fJ0K57stUi9CF1htT1i5qJ8ylChtT1oX33ZKtF6IMZJhR8UAtGR0f5nd/5HW644Qauueaac37f8ePHOX78+Phfj4yMnPfnXs6iopEmybiMhYWvHh5sQQRgZH/xa80QQ4QemKFxM3k+mSHXbntyOkTogRmKqWdGNTqfIP3ZTF0/SoZ23JPTIUIfUmdIXb+ImTqfImRIXR/ac09Ohwh9MMOEwvfF7rjjDv7mb/6Gb3zjG+f9vo0bN9Lf3z/+MTBw/ue6LqS38CONY6p0cRF9ha8/cWTi7Q+LymrwxtTz2QzBReiBGRo3k+eTGXLttienQ4QemKGYemZUo/MJ0p/N1PWjZGjHPTkdIvQhdYbU9YuYqfMpQobU9aE99+R0iNAHM0wodCp++7d/m+3bt/O9732P+fPnn/d7N2zYwPDw8PjH0NDQeb//dY4w2uRjjaPUeI3inZnVC5WupiJQ6YILis8LMwQRoQdmaMxMn09myLXTnpwuEXpghsbVO6ManU+Q/mymrh8lQ7vtyekSoQ+pM6Su36iZPJ8iZEhdH9pvT06XCH0ww4SGfn0vyzI+8YlP8OCDD/L973+fq666asprenp66OnpqbvGy7TiGbIKr1D8GbL+VjxZCfQVf7LSDEFE6IEZ6tMp88kMuXbYk9MtQg/MUL9GZ1Sj8wnSn83U9aNkaJc9Od0i9CF1htT169UJ8ylChtT1oX325HSL0AczTGjoSak77riD++67j69//ev09vby0ksv8dJLL/Haa681l2KS3Wyj0uRjjRWq7Kb4q20tXgNZczexyUZhcfHXoDNDEBF6YIb6dMp8MkOuHfbkdIvQAzPUrxNmVOr6UTK0y56cbhH6kDpD6vr16oT5FCFD6vrQPntyukXogxkmNHQq7rnnHoaHh7nxxhuZO3fu+Mc3v/nN5lJMcpgh9rKdGicKXV/jBHv4TuG3yQSYvQAWrIRKwZeBr3TDlauae1tEM8QQoQdmqE+nzCcz5NphT063CD0wQ/06YUalrh8lQ7vsyekWoQ+pM6SuX69OmE8RMqSuD+2zJ6dbhD6YYUJDN6WyLDvrx5o1a5pLcZrH2EQXswpdW6WLHWxpOsO71kN2sti1WQ2Wrms6ghmCiNADM9RRo4Pmkxly0fdkGSL0wAx11umQGZW6fpQM7bAnyxChD6kzpK5fV50OmU8RMqSuD+2xJ8sQoQ9myDX3/OA0GWQXD1Ds/923uZNBdjWdYe5yuH5TsWuv/0J+vRlakyG1CD0wQxwR5pMZcu7JGD0wQyypz2bq+lEyuCdzEfqQOkPq+pFEOJupM6SuD+7JMRH6YIZcyJtSADvYMn5gp3rEcezrD7CuJXePxyxZO7FAUz3SNvb16zfl15mhtRlSi9ADM8QRYT6ZIeeejNEDM8SS+mymrh8lg3syF6EPqTOkrh9JhLOZOkPq+uCeHBOhD2YIfFMK8gO7ieXs5WFGGaXGSWqcJGOUGieocZJRRtnLw2xieUsPKkClkj+OtmonLLgFqORveTj2tonjn1fyr6/amX9/pWKGVmdILUIPzBBL6vlkhpx7MkYPzBBP6rOZun6EDO7JXIQ+pM6Qun40qc9mhAyp67sncxH6YAYo+JJW5RlkF4PsYg7zWcbtXMZCLqKP1xjhFfazm61NvdhbPeYuzz+ODsG+rTCyH94YgQv68rc/XHz79L/YmxliiNADM8QRYT6ZIeeejNEDM8SS+mymrh8lg3syF6EPqTOkrh9JhLOZOkPq+uCeHBOhD52cIfxNqTGHOcjD3J00w+wBuO7TSSOYIYgIPTBDHBHmkxly7skYPTBDLKnPZur6UTK4J3MR+pA6Q+r6kUQ4m6kzpK4P7skxEfrQiRlC//qeJEmSJEmSZiZvSkmSJEmSJKl03pSSJEmSJElS6bwpJUmSJEmSpNJVsizLyiw4MjJCf38/VOCSeWVWzr36ImSjUKnCxXPLr28GM0TLkLo+wLFDQAbDw8P09fWlCUH6+QQx1iN1htT1zWCG00WYUc4nM0Spb4ZYGZxPuQhrYQYzRKkfJUO98yndTSlJOk2Ym1KSdBYh/qVPks7C+SQpqqnmU3eJWU7lk1JmMEOIDKnrw8Rd9DD8L30dvyfNYIbJQs0o51PHZ0hd3wyxMjifchHWwgxmiFI/SoZ651Oym1IXXwG3HSy/7v3z4diP8oVJUd8MZoiWIXV9gPvm5YMzilTzCWKsR+oMqeubwQynizSjnE9mSF3fDLEyOJ9yEdbCDGaIUj9Khnrnky90LkmSJEmSpNJ5U0qSJEmSJEml86aUJEmSJEmSSudNKUmSJEmSJJUu3bvvNWgOAyxjDZeziAvp5XWO8DKD7GYbhxkqJcPRA7BvGwwPwokjMKsX+hfB4jUwe0EpEeyDxrkOcXguc/ZBY1yHWFKfzQj7IXUPIEYflHMt4vBs2gOdKsJalL0nw9+UWsRyVrCOJawkYxSAKlVG3/x8JXexh4fYwWYG2TUtGQ7thD2b4cD2/C0VAbIaVLryz5+5C65cCUvXw9zl0xLBPmic6xCH5zJnHzTGdYgl9dmMsB9S9wBi9EE51yIOz6Y90KkirEWqPRn61/dWsI717OQabqZKlS666aKbyqTPq1RZwi2s53FuYm1L62cZPLcJtt8IQ48AWb4xstqbXx/7PIMDj8BD7803Upa1NIZ9EOA6ROO5zNkHgesQUcqzGWU/OJ80xrWIxbNpDzQhylqk3JNhb0rdxFpuZRMAXcw67/eOfX01m1vanL1b4Mk788+zk+f/3rGvP7E+v65V7IPGuA5xeC5z9kFjXIdYUp/NCPshdQ8gRh+Ucy3i8GzaA50qwlqk3pMhb0otYjmr2Vzo2tVsZhHvaTrDoZ35YhfxxHp48fGmI9gHjXMd4vBc5uyDxrgOsaQ+mxH2Q+oeQIw+KOdaxOHZtAc6VYS1iLAnG7opdc8997B06VL6+vro6+vjF3/xF3nkkUeaDnG6FayjxolC19Y40ZI7dns2Q6XgK25VuvPrm2UfNMZ1mJrzqT7Op1ynnIsyuA716ZQZFWE/pO4BxOiDcq7F1DplPkH6/WAPNFmEtYiwJxu6KTV//nx+//d/n2eeeYYf/OAH/NIv/RIf+chH+B//4380HWTMHAZYwsopHxs7ly5msZQPM4f5hTMcPZC/wNhUj8+dS3YSXngIjjbxwvT2QWNch/o4n+rjfMp1yrmYbq5D/TphRkXYD6l7ADH6oJxrUZ9OmE+Qfj/YA00WYS0i7Elo8KbUqlWruOWWW1i0aBHvfOc7+exnP8vs2bN54oknmgox2TLWjL/Se1EZoyzj9sLX79s28Yr3RVWqsG9r8evtg8a4DvVxPtXP+ZTrhHMx3VyH+nXCjIqwH1L3AGL0QTnXoj6dMJ8g/X6wB5oswlpE2JMABR8Wg1qtxgMPPMCxY8f4xV/8xXN+3/Hjxzl+/Pj4X4+MjJz3517OoqKRJsm4jIWFrx4ebEEEYGR/8Wvtg8a4Do1zPk3N+ZTrpHMxHVyHYuqZUY3OJ0h/NiPsh9Q9gBh9UM61aNxMnU+Qfj/YA00WYS0i7Eko8ELne/fuZfbs2fT09PCbv/mbPPjgg/zMz/zMOb9/48aN9Pf3j38MDAyc9+dfSC/VJl9/vUoXF9FX+PoTRybegrGorAZvTD2fz8k+aIzrUD/nU32cT7lOORfTyXVoTCMzqtH5BOnPZoT9kLoHEKMPyrkW9Zvp8wnS7wd7oMkirEWEPZn/jAYtXryYZ599lieffJLf+q3f4mMf+xh/+7d/e87v37BhA8PDw+MfQ0Pn/6XH1znCaJOPkI1S4zWKr86sXqh0NRWBShdc0MTa2AeNcR3q53yqj/Mp1ynnYjq5Do1pZEY1Op8g/dmMsB9S9wBi9EE516J+M30+Qfr9YA80WYS1iLAnocCv711wwQUsXJg/nnXdddfx9NNP85//83/mj/7oj876/T09PfT09NT981+mFc+xVXiF4s+x9bfiKTagr4mn2OyDxrgO9XM+1c/5lOuEczGdXIfGNDKjGp1PkP5sRtgPqXsAMfqgnGtRv5k+nyD9frAHmizCWkTYk1DgSanTjY6OnvI7xc3azTYqTcaqUGU3xV/xa/EayJq7YUg2CoubeL0v+6AxrkNxzqezcz7lOvVctJLr0JyZNqMi7IfUPYAYfVDOtShups0nSL8f7IEmi7AWEfYkNHhTasOGDTz++OM8//zz7N27lw0bNvD973+f2267rakQkx1miL1sp8aJQtfXOMEevsNhDhbOMHsBLFgJlYIvA1/phitXweypf736nOyDxrgO9XE+1cf5lOuUczHdXIf6dcKMirAfUvcAYvRBOdeiPp0wnyD9frAHmizCWkTYk9DgTamXX36ZX//1X2fx4sW8//3v5+mnn+bP/uzPWLFiRVMhTvcYm+hiVqFrq3Sxgy1NZ3jXeshOFrs2q8HSdU1HsA8a5zpMzflUH+dTrlPORRlch/p0yoyKsB9S9wBi9EE512JqnTKfIP1+sAeaLMJaRNiTDd2Uuvfee3n++ec5fvw4L7/8Mjt27Gj5sAIYZBcPUKzD3+ZOBtnVdIa5y+H6TcWuvf4L+fXNsg8a4zpMzflUH+dTrlPORRlch/p0yoyKsB9S9wBi9EE512JqnTKfIP1+sAeaLMJaRNiTTb+m1HTZwZbx5kz1ONnY1x9gXUvu1I1ZsnZik0z1WN3Y16/flF/XKvZBY1yHODyXOfugMa5DLKnPZoT9kLoHEKMPyrkWcXg27YFOFWEtUu/JsDelIG/OJpazl4cZZZQaJ6lxkoxRapygxklGGWUvD7OJ5S09qACVSv5I3KqdsOAWoJK/7eLYWzeOf17Jv75qZ/79lUpLY9gHAa5DNJ7LnH0QuA4RpTybUfaD80ljXItYPJv2QBOirEXKPVnwZbXKM8guBtnFHOazjNu5jIVcRB+vMcIr7Gc3W5t+Ya2pzF2efxwdgn1bYWQ/vDECF/Tlb8G4+Pbpf7E3+6AxrkMcnsucfdAY1yGW1Gczwn5I3QOI0QflXIs4PJv2QKeKsBap9mT4m1JjDnOQh7k7aYbZA3Ddp5NGsA8a5zrE4bnM2QeNcR1iSX02I+yH1D2AGH1QzrWIw7NpD3SqCGtR9p4M/et7kiRJkiRJmpm8KSVJkiRJkqTSeVNKkiRJkiRJpfOmlCRJkiRJkkpXybIsK7PgyMgI/f39UIFL5pVZOffqi5CNQqUKF88tv74ZzBAtQ+r6AMcOARkMDw/T19eXJgTp5xPEWI/UGVLXN4MZThdhRjmfzBClvhliZXA+5SKshRnMEKV+lAz1zqd0N6Uk6TRhbkpJ0lmE+Jc+SToL55OkqKaaT90lZjmVT0qZwQwhMqSuDxN30cPwv/R1/J40gxkmCzWjnE8dnyF1fTPEyuB8ykVYCzOYIUr9KBnqnU/JbkpdfAXcdrD8uvfPh2M/yhcmRX0zmCFahtT1Ae6blw/OKFLNJ4ixHqkzpK5vBjOcLtKMcj6ZIXV9M8TK4HzKRVgLM5ghSv0oGeqdT77QuSRJkiRJkkrnTSlJkiRJkiSVzptSkiRJkiRJKp03pSRJkiRJklQ6b0pJkiRJkiSpdMnefa9RcxhgGWu4nEVcSC+vc4SXGWQ32zjMUCkZjh6AfdtgeBBOHIFZvdC/CBavgdkLSolgBtwLZojHPWmGyVLvhwg9MEMs7kkzjEm9FyBGH1JnSF0/Evdk+vpRMrgXchH6UHaG8DelFrGcFaxjCSvJGAWgSpXRNz9fyV3s4SF2sJlBdk1LhkM7Yc9mOLAdKm8+W5bVoNKVf/7MXXDlSli6HuYun5YIZsC9YIZ43JNmmCz1fojQAzPE4p40w5jUewFi9CF1htT1I3FPpq8fJYN7IRehD6kyhP71vRWsYz07uYabqVKli2666KYy6fMqVZZwC+t5nJtY29L6WQbPbYLtN8LQI0CWb86s9ubXxz7P4MAj8NB7882cZWZodQb3ghmicU+aYbKU+yFCD8wQj3vSDGP851X6DKnrR9PpezJ1/SgZwL0wJnUfUmcIe1PqJtZyK5sA6GLWeb937Our2dzS5uzdAk/emX+enTz/9459/Yn1+XVmaF0G94IZonFPmmGy1PshQg/MEIt70gxjUu8FiNGH1BlS14/EPZm+fpQM7oVchD6kztDUTanf//3fp1Kp8Du/8zstCTNmEctZzeZC165mM4t4T9MZDu3MN1wRT6yHFx9vOoIZcC+YoTjn09nNpP0QIUPq/RChB2Zo3HTNJ3BPmmFC6r0AMfqQOkPq+kX4Z6izmyn7IUIG90IuQh8iZCh8U+rpp5/mj/7oj1i6dGnTIU63gnXUOFHo2honWnLHbs9mqBR8xa1Kd369GZrP4F4wQxHOp3ObSfshQobU+yFCD8zQmOmcT+CeNMOE1HsBYvQhdYbU9Rvln6HObabshwgZ3Au5CH2IkKHQTamjR49y22238ZWvfIU5c+Y0HWKyOQywhJVTPjZ2Ll3MYikfZg7zC2c4eiB/kbOpHuE7l+wkvPAQHG3ihenN4F4wQzHOp/ObKfshQobU+yFCD8zQmOmcT+CeNMOE1HsBYvQhdYbU9Rvln6HObybshwgZ3Au5CH2IkAEK3pS64447+NCHPsRNN93UVPGzWcaa8Vd6LypjlGXcXvj6fdsmXnW/qEoV9m0tfr0Z3AtmKMb5NLWZsB8iZEi9HyL0wAyNmc75BO5JM0xIvRcgRh9SZ0hdv1H+GWpq7b4fImRwL+Qi9CFCBoCGH1j7xje+wV//9V/z9NNP1/X9x48f5/jx4+N/PTIyct7vv5xFjUY6i4zLWFj46uHBFkQARvYXv9YM7gUzNM75VL923w8RMqTeDxF6YIb6Tfd8AvekGSak3gsQow+pM6Su34hGZlQ7zidIvx6p60fJ4F7IRehDhAzQ4JNSQ0NDfPKTn+T+++/nwgsvrOuajRs30t/fP/4xMDBw3u+/kF6qTb4pYJUuLqKv8PUnjky8DWRRWQ3emHo+m+E83AtmaITzqX4zYT9EyJB6P0TogRnqU8Z8AvekGSak3gsQow+pM6SuX69GZ1Q7zidIvx6p60fJ4F7IRehDhAz5z2jAM888w8svv8zP/dzP0d3dTXd3Nzt37uS//Jf/Qnd3N7XamSu7YcMGhoeHxz+Ghs7/i5evc4TRJh8hG6XGaxTfIbN6odLVVAQqXXBBE2tjBveCGRrjfKrfTNgPETKk3g8RemCG+pQxn8A9aYYJqfcCxOhD6gyp69er0RnVjvMJ0q9H6vpRMrgXchH6ECEDNPjre+9///vZu3fvKX/v9ttv5+qrr+b3fu/36Oo6c2V7enro6empu8bLtOJZugqvUPxZuv5WPMUG9DXxFJsZ3AtmaIzzqTHtvh8iZEi9HyL0wAz1KWM+gXvSDBNS7wWI0YfUGVLXr1ejM6od5xOkX4/U9aNkcC/kIvQhQgZo8Emp3t5errnmmlM+LrnkEi699FKuueaapoKM2c02Kk0+Qlahym6Kv+rY4jWQNXfDkGwUFjfxel9mcC+YoTHOp/rNhP0QIUPq/RChB2aoTxnzCdyTZpiQei9AjD6kzpC6fr38M1T92n0/RMjgXshF6EOEDFDw3fem02GG2Mt2apwodH2NE+zhOxzmYOEMsxfAgpVQafhl4HOVbrhyFcye+terzXAe7gUzROOeNMNkqfdDhB6YIRb3pBnGpN4LEKMPqTOkrh+JezJ9/SgZ3Au5CH2IkAFacFPq+9//Pl/84heb/TGneIxNdDGr0LVVutjBlqYzvGs9ZCeLXZvVYOm6piOYAfeCGZrjfDrTTNoPETKk3g8RemCGYqZjPoF70gwTUu8FiNGH1BlS1y/KP0OdaabshwgZ3Au5CH2IkCHck1IAg+ziAYqt8re5k0F2NZ1h7nK4flOxa6//Qn69GZrP4F4wQzTuSTNMlno/ROiBGWJxT5phTOq9ADH6kDpD6vqRuCfT14+Swb2Qi9CHCBlC3pQC2MGW8eZM9TjZ2NcfYF1L7tSNWbJ2YqNO9Wjf2Nev35RfZ4bWZXAvmCEa96QZJku9HyL0wAyxuCfNMCb1XoAYfUidIXX9SNyT6etHyeBeyEXoQ+oMYW9KQd6cTSxnLw8zyig1TlLjJBmj1DhBjZOMMspeHmYTy1u6MACVSv5Y3qqdsOAWoJK/9ePY20eOf17Jv75qZ/79lYoZWp3BvWCGaNyTZpgs5X6I0AMzxOOeNMMY/3mVPkPq+tF0+p5MXT9KBnAvjEndh9QZCr60V3kG2cUgu5jDfJZxO5exkIvo4zVGeIX97GZr0y+sNZW5y/OPo0OwbyuM7Ic3RuCCvvxtIBffPv0vQGgG94IZ4nFPmmGy1PshQg/MEIt70gxjUu8FiNGH1BlS14/EPZm+fpQM7oVchD6kyhD+ptSYwxzkYe5OmmH2AFz36aQRzIB7wQzxuCfNMFnq/RChB2aIxT1phjGp9wLE6EPqDKnrR+KeTF8/Sgb3Qi5CH8rOEPrX9yRJkiRJkjQzeVNKkiRJkiRJpfOmlCRJkiRJkkrnTSlJkiRJkiSVrpJlWVZmwZGREfr7+6ECl8wrs3Lu1RchG4VKFS6eW359M5ghWobU9QGOHQIyGB4epq+vL00I0s8niLEeqTOkrm8GM5wuwoxyPpkhSn0zxMrgfMpFWAszmCFK/SgZ6p1P6W5KSdJpwtyUkqSzCPEvfZJ0Fs4nSVFNNZ+6S8xyKp+UMoMZQmRIXR8m7qKH4X/p6/g9aQYzTBZqRjmfOj5D6vpmiJXB+ZSLsBZmMEOU+lEy1Dufkt2UuvgKuO1g+XXvnw/HfpQvTIr6ZjBDtAyp6wPcNy8fnFGkmk8QYz1SZ0hd3wxmOF2kGeV8MkPq+maIlcH5lIuwFmYwQ5T6UTLUO598oXNJkiRJkiSVzptSkiRJkiRJKp03pSRJkiRJklQ6b0pJkiRJkiSpdOnefa9BcxhgGWu4nEVcSC+vc4SXGWQ32zjMUCkZjh6AfdtgeBBOHIFZvdC/CBavgdkLSolgH4jRgwgZFEeE/ZD6XIJ9GJO6D6nrK57Ue8JzmbMPcTKkFmEvRBFhP6ReD3uQi9CHCBkiKLsP4W9KLWI5K1jHElaSMQpAlSqjb36+krvYw0PsYDOD7JqWDId2wp7NcGB7/paKAFkNKl3558/cBVeuhKXrYe7yaYlgH4jRgwgZFEeE/ZD6XIJ9GJO6D6nrK57Ue8JzmbMPcTKkFmEvRBFhP6ReD3uQi9CHCBkiSNWH0L++t4J1rGcn13AzVap00U0X3VQmfV6lyhJuYT2PcxNrW1o/y+C5TbD9Rhh6BMjyQ5rV3vz62OcZHHgEHnpvfqizrKUx7APpexAlg+JIvR8inEuwD2NS9yF1fcWTck94LnP2IVaGlKLshShS74cI62EPcqn7ECVDBCn7EPam1E2s5VY2AdDFrPN+79jXV7O5pc3ZuwWevDP/PDt5/u8d+/oT6/PrWsU+xOhBhAyKI8J+SH0uwT6MSd2H1PUVT+o94bnM2Yc4GVKLsBeiiLAfUq+HPchF6EOEDBGk7kPIm1KLWM5qNhe6djWbWcR7ms5waGd+8Ip4Yj28+HjTEewDMXoQIYPiiLAfUp9LsA9jUvchdX3Fk3pPeC5z9iFOhtQi7IUoIuyH1OthD3IR+hAhQwQR+tDQTam77rqLSqVyysfVV1/ddIjTrWAdNU4UurbGiZbcsduzGSoFX3Gr0p1f3yz7EKMHETJoas6n+jifcjOlD6nrq36dMqM8lzn7ECdDahH2wlQ6ZT5B+vWwB7kIfYiQIYIIfWj4Samf/dmf5cUXXxz/+Mu//MumQ0w2hwGWsHLKx8bOpYtZLOXDzGF+4QxHD+Qv9jbVo4znkp2EFx6Co028ML19iNGDCBlUP+fT1JxPuZnQh9T11biZPqM8lzn7ECdDahH2Qr1m+nyC9OthD3IR+hAhQwRR+tDwTanu7m6uuOKK8Y+3ve1tTQU43TLWjL/Se1EZoyzj9sLX79s28e4DRVWqsG9r8evtQ4weRMig+jmf6uN8yrV7H1LXV+Nm+ozyXObsQ5wMqUXYC/Wa6fMJ0q+HPchF6EOEDBFE6UPDW3JwcJB58+bx9re/ndtuu40DBw6c9/uPHz/OyMjIKR/nczmLGo10FhmXsbDw1cODLYgAjOwvfq19iNGDCBlUP+dT/ZxPuXbuQ+r6alwjM6rR+QTp94TnMmcf4mRILcJeqNdMn0+Qfj3sQS5CHyJkiCBKHxq6KfV//B//B9u2bePRRx/lnnvu4Z/+6Z94z3vew5EjR855zcaNG+nv7x//GBgYOG+NC+ml2uTrr1fp4iL6Cl9/4sjE22EWldXgjann8znZhxg9iJBB9XE+1c/5lGv3PqSur8Y0OqManU+Qfk94LnP2IU6G1CLshXp0wnyC9OthD3IR+hAhQwRR+tBQgptvvpnVq1ezdOlSfvmXf5n/7//7//jxj3/Mt771rXNes2HDBoaHh8c/hobO/wuor3OE0SYfIRulxmsUPymzeqHS1VQEKl1wQRNrYx9i9CBCBtXH+VQ/51Ou3fuQur4a0+iManQ+Qfo94bnM2Yc4GVKLsBfq0QnzCdKvhz3IRehDhAwRROlDwdfdz73lLW/hne98J/v3n/v5vZ6eHnp6eur+mS/TimcKK7xC8WcK+1vxFBvQ18RTbPYhRg8iZFAxzqfzcz7l2rkPqeurOVPNqEbnE6TfE57LnH2IkyG1CHuhiJk4nyD9etiDXIQ+RMgQQZQ+NPWs1tGjR/mHf/gH5s6d21SIyXazjUqTj5BVqLKb4q++tngNZM3dMCQbhcVNvN6XfYjRgwgZVIzz6dycT7l270Pq+mrOTJxRnsucfYiTIbUIe6GImTifIP162INchD5EyBBBlD40lGD9+vXs3LmT559/nt27d/Orv/qrdHV18S/+xb9oKsRkhxliL9upcaLQ9TVOsIfvcJiDhTPMXgALVkKl4HNklW64chXMnvrXq8/JPsToQYQMqo/zqT7Op9xM6EPq+mpMJ8woz2XOPsTJkFqEvVCPTphPkH497EEuQh8iZIggSh8auil18OBB/sW/+BcsXryY//P//D+59NJLeeKJJ7jsssuaCnG6x9hEF7MKXVulix1saTrDu9ZDdrLYtVkNlq5rOoJ9IEYPImTQ1JxP9XE+5WZKH1LXV/06ZUZ5LnP2IU6G1CLshal0ynyC9OthD3IR+hAhQwQR+tDQTalvfOMbHDp0iOPHj3Pw4EG+8Y1v8I53vKPpEKcbZBcPUGy3f5s7GWRX0xnmLofrNxW79vov5Nc3yz7E6EGEDJqa86k+zqfcTOlD6vqqX6fMKM9lzj7EyZBahL0wlU6ZT5B+PexBLkIfImSIIEIfmvsFwmm0gy3jzZnqcbKxrz/AupbesVyyduLATvWI49jXr9+UX9cq9iFGDyJkUBwR9kPqcwn2YUzqPqSur3hS7wnPZc4+xMmQWoS9EEWE/ZB6PexBLkIfImSIIHUfwt6Ugrw5m1jOXh5mlFFqnKTGSTJGqXGCGicZZZS9PMwmlrd8c1Qq+eOJq3bCgluASv4WmGNvozn+eSX/+qqd+fdXKi2NYR9I34MoGRRH6v0Q4VyCfRiTug+p6yuelHvCc5mzD7EypBRlL0SRej9EWA97kEvdhygZIkjZh4IvcVaeQXYxyC7mMJ9l3M5lLOQi+niNEV5hP7vZOu0vMDZ3ef5xdAj2bYWR/fDGCFzQl78d5uLbp/8FCO1DjB5EyKA4IuyH1OcS7MOY1H1IXV/xpN4TnsucfYiTIbUIeyGKCPsh9XrYg1yEPkTIEEGqPoS/KTXmMAd5mLuTZpg9ANd9OmkE+0CMHkTIoDgi7IfU5xLsw5jUfUhdX/Gk3hOey5x9iJMhtQh7IYoI+yH1etiDXIQ+RMgQQdl9CP3re5IkSZIkSZqZvCklSZIkSZKk0nlTSpIkSZIkSaXzppQkSZIkSZJKV8myLCuz4MjICP39/VCBS+aVWTn36ouQjUKlChfPLb++GcwQLUPq+gDHDgEZDA8P09fXlyYE6ecTxFiP1BlS1zeDGU4XYUY5n8wQpb4ZYmVwPuUirIUZzBClfpQM9c6ndDelJOk0YW5KSdJZhPiXPkk6C+eTpKimmk/dJWY5lU9KmcEMITKkrg8Td9HD8L/0dfyeNIMZJgs1o5xPHZ8hdX0zxMrgfMpFWAszmCFK/SgZ6p1PyW5KXXwF3Haw/Lr3z4djP8oXJkV9M5ghWobU9QHum5cPzihSzSeIsR6pM6SubwYznC7SjHI+mSF1fTPEyuB8ykVYCzOYIUr9KBnqnU++0LkkSZIkSZJK500pSZIkSZIklc6bUpIkSZIkSSqdN6UkSZIkSZJUOm9KSZIkSZIkqXTJ3n2vHc1hgGWs4XIWcSG9vM4RXmaQ3WzjMEOlZDh6APZtg+FBOHEEZvVC/yJYvAZmLyglQvIMqetDjL1gBk0WYS0inE0zxNgLZtBkEdYi9bk0wwT3Q4weaELq9Ui9H80wIfVegM7sgzel6rCI5axgHUtYScYoAFWqjL75+UruYg8PsYPNDLJrWjIc2gl7NsOB7VB58/m2rAaVrvzzZ+6CK1fC0vUwd/m0REieIXV9iLEXzKDJIqxFhLNphhh7wQyaLMJapD6XZpjgfojRA01IvR6p96MZJqTeC9DZffDX96awgnWsZyfXcDNVqnTRTRfdVCZ9XqXKEm5hPY9zE2tbWj/L4LlNsP1GGHoEyPLNmdXe/PrY5xkceAQeem++mbNs5mRIXX9M6r1gBp0u9VpEOJtmyKXeC2bQ6VKvRYRzaYYJ7of0PdCpUq5HhP1ohgmpz6Z98KbUed3EWm5lEwBdzDrv9459fTWbW7pAe7fAk3fmn2cnz/+9Y19/Yn1+3UzJkLo+xNgLZtBkEdYiwtk0Q4y9YAZNFmEtUp9LM0xwP8TogSakXo/U+9EME1LvBbAPUOCm1I9+9CM++tGPcumll3LRRRexZMkSfvCDH7QkTCSLWM5qNhe6djWbWcR7ms5waGe+4Yp4Yj28+HjTEZJnSF0fYuwFM9TH+TQ159PMyhBhL5ihfp0woyKsRepzaYYJ7ocYPahHJ8wnSL8eqfejGSak3gtgH8Y0dFPq8OHD3HDDDcyaNYtHHnmEv/3bv2Xz5s3MmTOn6SDRrGAdNU4UurbGiZbcNdyzGSoFX/Wr0p1f3+4ZUteHGHvBDFNzPtXH+TSzMkTYC2aoT6fMqAhrkfpcmmGC+yFGD6bSKfMJ0q9H6v1ohgmp9wLYhzENteDzn/88AwMDbN26dfzvXXXVVU2HiGYOAyxhJdWCv93YxSyW8mHmMJ/DHCz0M44eyF/kjIK/K5qdhBcegqNDMHug2M9InSF1fYixF8xQH+dTfZxPMydDhL1ghvp1woyKsBapz6UZJrgfYvSgHp0wnyD9eqTej2aYkHovgH2YrKHq3/nOd/j5n/95Vq9ezeWXX861117LV77ylcLFo1rGmvFXmy8qY5Rl3F74+n3bJl51v6hKFfZtnfr7omZIXR9i7AUz1Mf5VD/n08zIEGEvmKF+nTCjIqxF6nNphgnuhxg9qEcnzCdIvx6p96MZJqTeC2AfJmuoDf/4j//IPffcw6JFi/izP/szfuu3fov/+//+v/na1752zmuOHz/OyMjIKR/RXc6iFvyUjMtYWPjq4cEWRABG9he/NnWG1PUhxl4wQ32cT41wPs2EDBH2ghnq1+iMcj4Vk/pcmmGC+yFGD+rRCfMJ0q9H6v1ohgmp9wLYh8ka+vW90dFRfv7nf57Pfe5zAFx77bX8zd/8Df/P//P/8LGPfeys12zcuJH/3//v/9dUyLJdSG/hR9jGVOniIvoKX3/iyMTbQBaV1eCNJv4ZkTpD6voQYy+YoT7Op/o5n2ZGhgh7wQz1a3RGOZ+KSX0uzTDB/RCjB/XohPkE6dcj9X40w4TUewHsw6k/owFz587lZ37mZ075ez/90z/NgQMHznnNhg0bGB4eHv8YGhoqlrREr3OE0SYfYxulxmsU3yGzeqHS1VQEKl1wQRP7I3WG1PUhxl4wQ32cT/VzPs2MDBH2ghnq1+iMcj4Vk/pcmmGC+yFGD+rRCfMJ0q9H6v1ohgmp9wLYh8kaelLqhhtuYN++faf8vb//+7/nyiuvPOc1PT099PT0FEuXyMu04lm6Cq9Q/Fm6/lY8SQf0NfEkXeoMqetDjL1ghvo4nxrhfJoJGSLsBTPUr9EZ5XwqJvW5NMME90OMHtSjE+YTpF+P1PvRDBNS7wWwD5M19KTU7/7u7/LEE0/wuc99jv379/P1r3+d//f//X+54447mgoRzW62UWnyMbYKVXZT/FXHFq+BrLmblmSjsLiJ1xxLnSF1fYixF8xQH+dT/ZxPMyNDhL1ghvp1woyKsBapz6UZJrgfYvSgHp0wnyD9eqTej2aYkHovgH2YrKEE7373u3nwwQf54z/+Y6655hruvvtuvvjFL3Lbbbc1FSKawwyxl+3UOFHo+hon2MN3mnpbxNkLYMFKqDT0LNuESjdcuar420NGyJC6PsTYC2aoj/OpPs6nmZMhwl4wQ/06YUZFWIvU59IME9wPMXpQj06YT5B+PVLvRzNMSL0XwD5M1vBtsZUrV7J3715ef/11fvjDH/J//V//V1MBonqMTXQxq9C1VbrYwZamM7xrPWQni12b1WDpuqYjJM+Quj7E2AtmqI/zaWrOp5mVIcJeMEP9OmFGRViL1OfSDBPcDzF6UI9OmE+Qfj1S70czTEi9F8A+TPwcndUgu3iAYqv8be5kkF1NZ5i7HK7fVOza67+QX9/uGVLXhxh7wQyaLMJaRDibZoixF8ygySKsRepzaYYJ7ocYPdCE1OuRej+aYULqvQD2YYw3pc5jB1vGF2iqR9rGvv4A61r6XzSWrJ3YqFM92jf29es35dfNlAyp60OMvWAGTRZhLSKcTTPE2Atm0GQR1iL1uTTDBPdDjB5oQur1SL0fzTAh9V4A+wDelJrSDrawieXs5WFGGaXGSWqcJGOUGieocZJRRtnLw2xiecv/4VGp5I/lrdoJC24BKvlbP469feT455X866t25t9fqcycDKnrj0m9F8yg06Veiwhn0wy51HvBDDpd6rWIcC7NMMH9kL4HOlXK9YiwH80wIfXZtA9Q8GW1OssguxhkF3OYzzJu5zIWchF9vMYIr7Cf3Wyd9hcgnLs8/zg6BPu2wsh+eGMELujL3wZy8e3NvchZO2RIXR9i7AUzaLIIaxHhbJohxl4wgyaLsBapz6UZJrgfYvRAE1KvR+r9aIYJqfcCdHYfvCnVgMMc5GHuTpph9gBc9+mkEZJnSF0fYuwFM2iyCGsR4WyaIcZeMIMmi7AWqc+lGSa4H2L0QBNSr0fq/WiGCan3AnRmH/z1PUmSJEmSJJXOm1KSJEmSJEkqnTelJEmSJEmSVDpvSkmSJEmSJKl0lSzLsjILjoyM0N/fDxW4ZF6ZlXOvvgjZKFSqcPHc8uubwQzRMqSuD3DsEJDB8PAwfX19aUKQfj5BjPVInSF1fTOY4XQRZpTzyQxR6pshVgbnUy7CWpjBDFHqR8lQ73xKd1NKkk4T5qaUJJ1FiH/pk6SzcD5Jimqq+dRdYpZT+aSUGcwQIkPq+jBxFz0M/0tfx+9JM5hhslAzyvnU8RlS1zdDrAzOp1yEtTCDGaLUj5Kh3vmU7KbUxVfAbQfLr3v/fDj2o3xhUtQ3gxmiZUhdH+C+efngjCLVfIIY65E6Q+r6ZjDD6SLNKOeTGVLXN0OsDM6nXIS1MIMZotSPkqHe+eQLnUuSJEmSJKl03pSSJEmSJElS6bwpJUmSJEmSpNJ5U0qSJEmSJEmlS/fuew2awwDLWMPlLOJCenmdI7zMILvZxmGGUscrzdEDsG8bDA/CiSMwqxf6F8HiNTB7QWdkiLAXUvcAYvRBOdciF+FcRMiQej/YA53O9YhxLiJkiLAX7IMmcy1inIkIGSLsBfuQRvibUotYzgrWsYSVZIwCUKXK6Jufr+Qu9vAQO9jMILtSRp1Wh3bCns1wYHv+to4AWQ0qXfnnz9wFV66Epeth7vKZmSHCXkjdA4jRB+Vci1yEcxEhQ+r9YA90OtcjxrmIkCHCXrAPmsy1iHEmImSIsBfsQ1qhf31vBetYz06u4WaqVOmimy66qUz6vEqVJdzCeh7nJtamjtxyWQbPbYLtN8LQI0CWH5Cs9ubXxz7P4MAj8NB78wOVZTMrQ+q9EKEHkL4PmuBaxDgXETJA2v1gD3Q2nb4eEc5FhAyQfi/YB52u09ciwpmIkAHS7wX7EEPYm1I3sZZb2QRAF7PO+71jX1/N5hm3QHu3wJN35p9nJ8//vWNff2J9ft1MyRBhL6TuAcTog3KuRS7CuYiQIfV+sAc6nesR41xEyBBhL9gHTeZaxDgTETJE2Av2IYaQN6UWsZzVbC507Wo2s4j3tDhRGod25pu+iCfWw4uPt3+GCHshdQ8gRh+Ucy1yEc5FhAyp94M90OlcjxjnIkKGCHvBPmgy1yLGmYiQIcJesA9xNHRT6qd+6qeoVCpnfNxxxx0tDbWCddQ4UejaGidmzF3DPZuhUvBVvyrd+fXtniHCXkjdA4jRh3ZQxoxyLXIRzkWEDKn3gz1oH/4ZqjwRzkWEDBH2gn1oD86n8kQ4ExEyRNgL9iGOhm5KPf3007z44ovjH4899hgAq1evblmgOQywhJVTPrp2Ll3MYikfZg7zW5YphaMH8hdam+oxwnPJTsILD8HRJl6gP3WGCHshdQ8gRh/axXTPKNciF+FcRMiQej/Yg/bin6HKEeFcRMgQYS/Yh/bhfCpHhDMRIUOEvWAfYmnoptRll13GFVdcMf6xfft23vGOd/De9763ZYGWsWb81eaLyhhlGbe3KFEa+7ZNvPJ/UZUq7Nvavhki7IXUPYAYfWgX0z2jXItchHMRIUPq/WAP2ot/hipHhHMRIUOEvWAf2ofzqRwRzkSEDBH2gn2IpeADa/DGG29w3333sXbtWiqVyjm/7/jx4xw/fnz8r0dGRs77cy9nUdFIk2RcxsIW/Jx0hgdb83NG9rdvhgh7IXUPIEYf2lE9M8r5VEyEcxEhQ+r9YA/a13TMJ3A9IMa5iJAhwl6wD+3J+TR9IpyJCBki7AX7EEvh+4N/+qd/yo9//GPWrFlz3u/buHEj/f394x8DAwPn/f4L6aXa5OuvV+niIvqa+hmpnTgy8VaURWU1eGPqf0aEzRBhL6TuAcToQzuqZ0Y5n4qJcC4iZEi9H+xB+5qO+QSuB8Q4FxEyRNgL9qE9OZ+mT4QzESFDhL1gH2Ip3IV7772Xm2++mXnz5p33+zZs2MDw8PD4x9DQ+X/x8nWOMNrkY2yj1HiNJnZIALN6odLV3M+odMEFTezR1Bki7IXUPYAYfWhH9cwo51MxEc5FhAyp94M9aF/TMZ/A9YAY5yJChgh7wT60J+fT9IlwJiJkiLAX7EMshX5974UXXmDHjh38yZ/8yZTf29PTQ09PT90/+2Va8SxdhVdo4lm6APpb8TQf0NfE03ypM0TYC6l7ADH60G7qnVHOp2IinIsIGVLvB3vQnqZrPoHrATHORYQMEfaCfWg/zqfpFeFMRMgQYS/Yh1gKPSm1detWLr/8cj70oQ+1Og+72UalycfYKlTZTROvOhbA4jWQNXfjlGwUFjfxumepM0TYC6l7ADH60G6ma0a5FrkI5yJChtT7wR60J/8MNb0inIsIGSLsBfvQfpxP0yvCmYiQIcJesA+xNNyF0dFRtm7dysc+9jG6uwu/Tvo5HWaIvWynxolC19c4wR6+w2EOtjhZuWYvgAUroVKwxZVuuHIVzJ76V7zDZoiwF1L3AGL0oZ1M54xyLXIRzkWEDKn3gz1oP/4ZavpFOBcRMkTYC/ahvTifpl+EMxEhQ4S9YB9iafim1I4dOzhw4AC/8Ru/MR15AHiMTXQxq9C1VbrYwZYWJ0rjXeshO1ns2qwGS9e1f4YIeyF1DyBGH9rFdM8o1yIX4VxEyJB6P9iD9uKfocoR4VxEyBBhL9iH9uF8KkeEMxEhQ4S9YB/iaPim1Ac+8AGyLOOd73zndOQBYJBdPECxVf42dzLIrhYnSmPucrh+U7Frr/9Cfn27Z4iwF1L3AGL0oV1M94xyLXIRzkWEDKn3gz1oL/4ZqhwRzkWEDBH2gn1oH86nckQ4ExEyRNgL9iGO5n6JcRrtYMv4Ak31SNvY1x9g3Yy5WzhmydqJwzLV44VjX79+U37dTMkQYS+k7gHE6INyrkUuwrmIkCH1frAHOp3rEeNcRMgQYS/YB03mWsQ4ExEyRNgL9iGGsDelIF+gTSxnLw8zyig1TlLjJBmj1DhBjZOMMspeHmYTy2fUwoypVPJHA1fthAW3AJX87SfH3sJy/PNK/vVVO/Pvr1RmVobUeyFCDyB9HzTBtYhxLiJkgLT7wR7obDp9PSKciwgZIP1esA86XaevRYQzESEDpN8L9iGG1r+KXYsNsotBdjGH+Szjdi5jIRfRx2uM8Ar72c3WGfHiXlOZuzz/ODoE+7bCyH54YwQu6MvfinLx7c290Fo7ZIiwF1L3AGL0QTnXIhfhXETIkHo/2AOdzvWIcS4iZIiwF+yDJnMtYpyJCBki7AX7kFb4m1JjDnOQh7k7dYzkZg/AdZ/u7AwR9kLqHkCMPijnWuQinIsIGVLvB3ug07keMc5FhAwR9oJ90GSuRYwzESFDhL1gH9II/et7kiRJkiRJmpm8KSVJkiRJkqTSeVNKkiRJkiRJpfOmlCRJkiRJkkpXybIsK7PgyMgI/f39UIFL5pVZOffqi5CNQqUKF88tv74ZzBAtQ+r6AMcOARkMDw/T19eXJgTp5xPEWI/UGVLXN4MZThdhRjmfzBClvhliZXA+5SKshRnMEKV+lAz1zqd0N6Uk6TRhbkpJ0lmE+Jc+SToL55OkqKaaT90lZjmVT0qZwQwhMqSuDxN30cPwv/R1/J40gxkmCzWjnE8dnyF1fTPEyuB8ykVYCzOYIUr9KBnqnU/JbkpdfAXcdrD8uvfPh2M/yhcmRX0zmCFahtT1Ae6blw/OKFLNJ4ixHqkzpK5vBjOcLtKMcj6ZIXV9M8TK4HzKRVgLM5ghSv0oGeqdT77QuSRJkiRJkkrnTSlJkiRJkiSVzptSkiRJkiRJKp03pSRJkiRJklQ6b0pJkiRJkiSpdMnefU/FHD0A+7bB8CCcOAKzeqF/ESxeA7MXlJNhDgMsYw2Xs4gL6eV1jvAyg+xmG4cZmvH1zRArg+JwPsXIkLq+GRSR88kMkTKkrq9YnE9m6PQM3pRqE4d2wp7NcGA7VN58vi2rQaUr//yZu+DKlbB0PcxdPj0ZFrGcFaxjCSvJGAWgSpXRNz9fyV3s4SF2sJlBds24+maIlUFxOJ9iZEhd3wyKyPlkhkgZUtdXLM4nM5iBN2sotCyD5zbB9hth6BEgy4dVVnvz62OfZ3DgEXjovflwy7LW5ljBOtazk2u4mSpVuuimi24qkz6vUmUJt7Cex7mJtTOqvhliZVAMzqc4GVLXN4OicT6ZIVqG1PUVh/PJDGY4lTelgtu7BZ68M/88O3n+7x37+hPr8+ta5SbWciubAOhi1nm/d+zrq9ncso2aur4ZYmVQHM6nGBlS1zeDInI+mSFShtT1FYvzyQxmOFVDN6VqtRr//t//e6666iouuugi3vGOd3D33XeTtfq2rYD8kc4n1he79on18OLjzWdYxHJWs7nQtavZzCLe09b1zRArw/k4n8rlfIqRIXV9M9TPGVUe55MZImVIXb8ezqfyOJ/MYIYzNXRT6vOf/zz33HMPX/rSl/jhD3/I5z//ef7Tf/pP/MEf/EHTQXSmPZuhUvBVvyrd+fXNWsE6apwodG2NE03fPU1d3wyxMpyP86lczqcYGVLXN0P9nFHlcT6ZIVKG1PXr4Xwqj/PJDGY4U0M3pXbv3s1HPvIRPvShD/FTP/VT3HrrrXzgAx/gqaeeajqITnX0QP6id1M90nku2Ul44SE42sSL489hgCWsnPIRvnPpYhZL+TBzmN+W9c0QK8NUnE/lcT7FyJC6vhka44wqh/PJDJEypK5fL+dTOZxPZjDD2TV0U2rZsmV897vf5e///u8BeO655/jLv/xLbr755qZC6Ez7tk28C0NRlSrs21r8+mWsGX/V/aIyRlnG7W1Z3wyxMkzF+VQe51OMDKnrm6ExzqhyOJ/MEClD6vr1cj6Vw/lkBjOcXUMPD37qU59iZGSEq6++mq6uLmq1Gp/97Ge57bbbznnN8ePHOX78+Phfj4yMFE/bQYYHW/NzRvYXv/ZyFrUgQcZlLGzL+maIlWEqzqfyOJ9iZEhd3wyNaXRGOZ+KcT6ZIVKG1PXr5Xwqh/PJDGY4u4bu1X7rW9/i/vvv5+tf/zp//dd/zde+9jU2bdrE1772tXNes3HjRvr7+8c/BgYGmgrcKU4cmXhb0KKyGrzRxD8jLqSXapNv0Fili4voa8v6ZoiVYSrOp/I4n2JkSF3fDI1pdEY5n4pxPpkhUobU9evlfCqH88kMZjjXz2jAnXfeyac+9Sn++T//5yxZsoR/+S//Jb/7u7/Lxo0bz3nNhg0bGB4eHv8YGmril2A7yKxeqHQ19zMqXXBBE/vjdY4w2uTjfKPUeI1ikzN1fTPEyjAV51N5nE8xMqSub4bGNDqjnE/FOJ/MEClD6vr1cj6Vw/lkBjOcXUO/vvfqq69SrZ56H6urq4vR0XP/H+np6aGnp6dYug7W34on6YC+Jp6ke5lWPGNa4RWKPWOaur4ZYmWYivOpPM6nGBlS1zdDYxqdUc6nYpxPZoiUIXX9ejmfyuF8MoMZzq6hJ6VWrVrFZz/7WR5++GGef/55HnzwQbZs2cKv/uqvNhVCZ1q8BrLmblqSjcLiJl5zbDfbqDT5OF+FKrsp9mp8qeubIVaGqTifyuN8ipEhdX0zNMYZVQ7nkxkiZUhdv17Op3I4n8xghrNrKMEf/MEfcOutt/Lxj3+cn/7pn2b9+vX8m3/zb7j77rubCqEzzV4AC1ZCpaFn2SZUuuHKVTC7iV/xPswQe9lOjROFrq9xgj18h8McbMv6ZoiVYSrOp/I4n2JkSF3fDI1xRpXD+WSGSBlS16+X86kcziczmOHsGrop1dvbyxe/+EVeeOEFXnvtNf7hH/6Bz3zmM1xwwQVNhdDZvWs9ZCeLXZvVYOm65jM8xia6mFXo2ipd7GBLW9c3Q6wM5+N8KpfzKUaG1PXNUD9nVHmcT2aIlCF1/Xo4n8rjfDKDGc72cxTW3OVw/aZi117/hfz6Zg2yiwcoNv2+zZ0Msqut65shVgbF4XyKkSF1fTMoIueTGSJlSF1fsTifzGCGM3lTKrglaycG11SPeo59/fpN+XWtsoMt4xt1qkf7xr7+AOta9l92Utc3Q6wMisP5FCND6vpmUETOJzNEypC6vmJxPpnBDKcq+ButKkulkj+medm7Yc9meOEhqLx5KzGrTbytaDYKC27Jv7cVd9BPt4MtvMDT3MRalvJhsjffOrJKlVFqQIUKVfbyMDvY0vL/qpO6vhliZVAMzqc4GVLXN4OicT6ZIVqG1PUVh/PJDGY4lTel2sTc5fnH0SHYtxVG9sMbI3BBX/62oItvb+5F7+oxyC4G2cUc5rOM27mMhVxEH68xwivsZzdbp/WFGFPXN0OsDIrD+RQjQ+r6ZlBEziczRMqQur5icT6ZwQw5b0q1mdkDcN2n02Y4zEEeJt27caSub4ZYGRSH8ylGhtT1zaCInE9miJQhdX3F4nwyQ6dn8DWlJEmSJEmSVDpvSkmSJEmSJKl03pSSJEmSJElS6bwpJUmSJEmSpNJVsizLyiw4PDzMW97yFgAunltm5dyrLwEZUIGLryi/vhnMEC1D6voAr76Y/++Pf/xj+vv704Qg/XyCIOvhnjSDGU7NEGBGOZ/MEKW+GYJlcD4BQdbCDGYIUj9MhjrnU+k3pQ4ePMjAwDS/t6WktjQ0NMT8+fOT1Xc+STqflDPK+STpfJxPkqKaaj6VflNqdHSUQ4cO0dvbS6VSafj6kZERBgYGGBoaoq+vbxoSmqFdMqSub4bWZciyjCNHjjBv3jyq1XS/Vex8MsNMypC6/kzKEGFGNTufIP16pK5vBjNEy+B8mpB6LSJkSF3fDGZodYZ651N3MyGLqFarLbmL39fXl2xxzBArQ+r6ZmhNhpS/tjfG+WSGmZghdf2ZkiH1jGrVfIL065G6vhnMEC2D82lC6rWIkCF1fTOYoZUZ6plPvtC5JEmSJEmSSudNKUmSJEmSJJWu7W5K9fT08B/+w3+gp6fHDB2eIXV9M8TKEEGEPpjBDFHqmyGe1L1IXd8MZoiWIXX9SCL0InWG1PXNYIZUGUp/oXNJkiRJkiSp7Z6UkiRJkiRJUvvzppQkSZIkSZJK500pSZIkSZIklc6bUpIkSZIkSSpdW92U+qu/+iu6urr40Ic+VHrtNWvWUKlUxj8uvfRSPvjBD7Jnz57Ss7z00kt84hOf4O1vfzs9PT0MDAywatUqvvvd70577cl9mDVrFj/xEz/BihUr+OpXv8ro6Oi01z89w+SPD37wg6XUnyrH/v37S6n/0ksv8clPfpKFCxdy4YUX8hM/8RPccMMN3HPPPbz66qvTXn/NmjX8yq/8yhl///vf/z6VSoUf//jH054hGmeU8+n0HKlmVOr5BGlnlPPpTM4n59PpOZxP/hkqCueT8+n0HM6nzppPbXVT6t577+UTn/gEjz/+OIcOHSq9/gc/+EFefPFFXnzxRb773e/S3d3NypUrS83w/PPPc9111/EXf/EXfOELX2Dv3r08+uijvO997+OOO+4oJcNYH55//nkeeeQR3ve+9/HJT36SlStXcvLkyVIzTP744z/+41JqT5Xjqquumva6//iP/8i1117Ln//5n/O5z32O//7f/zt/9Vd/xb/9t/+W7du3s2PHjmnPoDN1+oxyPp2ZI+WMSjWfwBkVkfPJ+XR6DueT8ykK55Pz6fQczqfOmk/dqQPU6+jRo3zzm9/kBz/4AS+99BLbtm3j3/27f1dqhp6eHq644goArrjiCj71qU/xnve8h1deeYXLLruslAwf//jHqVQqPPXUU1xyySXjf/9nf/Zn+Y3f+I1SMkzuw0/+5E/ycz/3c1x//fW8//3vZ9u2bfzrf/2vS82QUqocH//4x+nu7uYHP/jBKfvg7W9/Ox/5yEfIsqz0TJ3OGeV8OleOVFJmcEbF4nxyPp0rRyrOJ41xPjmfzpUjFedT+drmSalvfetbXH311SxevJiPfvSjfPWrX026KEePHuW+++5j4cKFXHrppaXU/N//+3/z6KOPcscdd5yySce85S1vKSXH2fzSL/0S73rXu/iTP/mTZBk6xf/6X/+LP//zPz/nPgCoVColp1Knzyjnk8Y4o+JxPjmflHM+xeN8cj4p18nzqW1uSt1777189KMfBfJH6oaHh9m5c2epGbZv387s2bOZPXs2vb29fOc73+Gb3/wm1Wo5bdy/fz9ZlnH11VeXUq9RV199Nc8//3wptSavxdjH5z73uVJqny/H6tWrp73m2D5YvHjxKX//bW9723iO3/u935v2HHD2dbj55ptLqR1Np88o59OpIsyoFPMJ4swo59ME55PzaTLnU/r5BM6oMc4n59NkzqfOnE9t8et7+/bt46mnnuLBBx8EoLu7m3/2z/4Z9957LzfeeGNpOd73vvdxzz33AHD48GH+8A//kJtvvpmnnnqKK6+8ctrrR39cL8uy0u7eTl6LMW9961tLqX2+HOe6q12Gp556itHRUW677TaOHz9eSs2zrcOTTz45/oeLTuGMcj6dLsKMijSfoPwZ5XzKOZ+cT6dzPp3JP0Ol4XxyPp3O+XSmTphPbXFT6t577+XkyZPMmzdv/O9lWUZPTw9f+tKX6O/vLyXHJZdcwsKFC8f/+r/+1/9Kf38/X/nKV/jMZz4z7fUXLVpEpVLh7/7u76a9VhE//OEPS3sRuNPXIpUUORYuXEilUmHfvn2n/P23v/3tAFx00UWlZTnb//+DBw+WVj8KZ5Tz6XQRZlSqDFFmlPMp53xyPp3O+ZR+PoEzCpxP4Hw6nfOpM+dT+F/fO3nyJP/tv/03Nm/ezLPPPjv+8dxzzzFv3rwk77g2plKpUK1Wee2110qp99a3vpVf/uVf5stf/jLHjh074+sp3z72L/7iL9i7dy+/9mu/lixDp7j00ktZsWIFX/rSl866D1QuZ1TO+aQxzqg4nE8555PGOJ/icD7lnE8a08nzKfyTUtu3b+fw4cP8q3/1r864W/5rv/Zr3Hvvvfzmb/5mKVmOHz/OSy+9BOSPdn7pS1/i6NGjrFq1qpT6AF/+8pe54YYb+IVf+AX+43/8jyxdupSTJ0/y2GOPcc899/DDH/5w2jOM9aFWq/E//+f/5NFHH2Xjxo2sXLmSX//1X5/2+pMzTNbd3c3b3va2Uuqn9od/+IfccMMN/PzP/zx33XUXS5cupVqt8vTTT/N3f/d3XHfddakjdgxn1ATn05k5JnNGOaPK5nya4Hw6M8dkzifnU9mcTxOcT2fmmMz51AHzKQtu5cqV2S233HLWrz355JMZkD333HPTnuNjH/tYBox/9Pb2Zu9+97uzb3/729Ne+3SHDh3K7rjjjuzKK6/MLrjgguwnf/Insw9/+MPZ9773vWmvPbkP3d3d2WWXXZbddNNN2Ve/+tWsVqtNe/3TM0z+WLx4cSn1J+f4yEc+UmrNyQ4dOpT99m//dnbVVVdls2bNymbPnp39wi/8QvaFL3whO3bs2LTXP9f//+9973sZkB0+fHjaM0TgjDpVp8+n03OkmlGp51OWpZ1Rzqec8+lUzifn0xj/DJWe8+lUzifn05hOnE+VLAv+6mqSJEmSJEmaccK/ppQkSZIkSZJmHm9KSZIkSZIkqXTelJIkSZIkSVLpvCklSZIkSZKk0nlTSpIkSZIkSaXzppQkSZIkSZJK500pSZIkSZIklc6bUpIkSZIkSSqdN6UkSZIkSZJUOm9KSZIkSZIkqXTelJIkSZIkSVLpvCklSZIkSZKk0nlTSpIkSZIkSaXzppQkSZIkSZJK500pSZIkSZIklc6bUpIkSZIkSSpdd9kFR0dHOXToEL29vVQqlbLLSwooyzKOHDnCvHnzqFbT3St3Pkk6mwgzyvkk6WycT5Kiqnc+lX5T6tChQwwMDJRdVlIbGBoaYv78+cnqO58knU/KGeV8knQ+zidJUU01n0q/KdXb2zv++cVzy64Or74EZEAFLr6i/PpmMEO0DKnrA7z6Yv6/k+dDCqnnEwRZD/ekGcxwaoYAM8r5ZIYo9c0QLIPzCQiyFmYwQ5D6YTLUOZ9Kvyk19kjnxXPho4fKrg73z4djP4JL5sFtB8uvbwYzRMuQuj7AffPyoZX6ke/U8wlirEfqDKnrm8EMp4swo5xPZohS3wyxMjifchHWwgxmiFI/SoZ655MvdC5JkiRJkqTSeVNKkiRJkiRJpfOmlCRJkiRJkkrnTSlJkiRJkiSVrvQXOi9qDgMsYw2Xs4gL6eV1jvAyg+xmG4cZMkOJGY4egH3bYHgQThyBWb3QvwgWr4HZC0qJIIUS4VyaIed8ks6U+mymrh8lg/NJOlOEs5k6Q+r64HxSWuFvSi1iOStYxxJWkjEKQJUqo29+vpK72MND7GAzg+wywzRmOLQT9myGA9uh8uYzdlkNKl3558/cBVeuhKXrYe7yaYkghRLhXJoh53ySzpT6bKauHyWD80k6U4SzmTpD6vrgfFIMoX99bwXrWM9OruFmqlTpopsuuqlM+rxKlSXcwnoe5ybWmmEaMmQZPLcJtt8IQ48AWT6sstqbXx/7PIMDj8BD782HW5a1NIYUSupzaYac80k6u9RnM3X9CBmcT9LZpT6bETKkru98UiRhb0rdxFpuZRMAXcw67/eOfX01m1t6YM2Q27sFnrwz/zw7ef7vHfv6E+vz66SZKMK5NEPO+SSdKfXZTF0/Sgbnk3SmCGczdYbU9cH5pFhC3pRaxHJWs7nQtavZzCLeY4YWZTi0Mx9ARTyxHl58vOkIUigRzqUZcs4n6Uypz2bq+lEyOJ+kM0U4m6kzpK4PzifF0/BNqccff5xVq1Yxb948KpUKf/qnf9ryUCtYR40Tha6tcaIld5HNkNuzGSoFX3ms0p1fL5XF+dRZGZxPaidlzCdIfzZT14+SwfmkdtIp8ylChtT1wfmkeBq+KXXs2DHe9a538eUvf3k68jCHAZawcspHGc+li1ks5cPMYb4Zmsxw9ED+ondTPdJ5LtlJeOEhOFrOm0ZIzqcOyuB8UruZ7vkE6c9m6vpRMjif1G46YT5FyJC6PjifFFPDN6VuvvlmPvOZz/Crv/qr05GHZawZf/eBojJGWcbtZmgyw75tE+/CUFSlCvu2NvczpHo5nzong/NJ7Wa65xOkP5up60fJ4HxSu+mE+RQhQ+r64HxSTAUf3Kvf8ePHOX78+Phfj4yMnPf7L2dRC6pmXMbCwlebITc82IIIwMj+1vwcqdWcT+2bwfmkma7R+QTpz2bq+lEyOJ8007XjfIqQIXV9cD4ppml/ofONGzfS398//jEwMHDe77+QXqpNxqrSxUX0Fb7eDLkTRybeFrSorAZvTP3PKSkJ51P7ZnA+aaZrdD5B+rOZun6UDM4nzXTtOJ8iZEhdH5xPimnab0pt2LCB4eHh8Y+hofP/AurrHGG0yccaR6nxGsVPihlys3qh0tVUBCpdcEHxuSlNK+dT+2ZwPmmma3Q+Qfqzmbp+lAzOJ8107TifImRIXR+cT4pp2n99r6enh56enrq//2Va8UxhhVco/kyhGXL9rXjCFOgr/oSpNK2cT+2bwfmkma7R+QTpz2bq+lEyOJ8007XjfIqQIXV9cD4ppml/UqpRu9lGpclYFarspvirr5kht3gNZM3dzCcbhcXFX4tPCiXCuTRDzvkknSn12UxdP0oG55N0pghnM3WG1PXB+aSYGj4VR48e5dlnn+XZZ58F4J/+6Z949tlnOXDgQEsCHWaIvWynxolC19c4wR6+w2EOmqHJDLMXwIKVUCn4PF2lG65cBbOn/jVzqSWcT52TwfmkdjPd8wnSn83U9aNkcD6p3XTCfIqQIXV9cD4ppoZvSv3gBz/g2muv5dprrwVg7dq1XHvttXz6059uWajH2EQXswpdW6WLHWwxQ4syvGs9ZCeLXZvVYOm6piNIdXM+dVYG55PaSRnzCdKfzdT1o2RwPqmddMp8ipAhdX1wPimehm9K3XjjjWRZdsbHtm3bWhZqkF08QLHd/m3uZJBdZmhRhrnL4fpNxa69/gv59VJZnE+dlcH5pHZSxnyC9Gczdf0oGZxPaiedMp8iZEhdH5xPiifca0qN2cGW8QM71SOOY19/gHUtuXtshlMtWTsxuKZ61HPs69dvyq+TZqII59IMOeeTdKbUZzN1/SgZnE/SmSKczdQZUtcH55NiCXtTCvIDu4nl7OVhRhmlxklqnCRjlBonqHGSUUbZy8NsYnlLD6oZJlQq+WOaq3bCgluASv5WoGNvJzr+eSX/+qqd+fdXKi2NIYWS+lyaIed8ks4u9dlMXT9CBueTdHapz2aEDKnrO58UScGXOCvPILsYZBdzmM8ybucyFnIRfbzGCK+wn91sberF3sxQv7nL84+jQ7BvK4zshzdG4IK+/G1BF9/ui96ps0Q4l2bIOZ+kM6U+m6nrR8ngfJLOFOFsps6Quj44nxRD+JtSYw5zkIe52wwBMswegOta+7qHUluLcC7NkHM+SWdKfTZT14+SwfkknSnC2UydIXV9cD4prdC/vidJkiRJkqSZyZtSkiRJkiRJKp03pSRJkiRJklQ6b0pJkiRJkiSpdJUsy7IyC46MjNDf3w8VuGRemZVzr74I2ShUqnDx3PLrm8EM0TKkrg9w7BCQwfDwMH19fWlCkH4+QYz1SJ0hdX0zmOF0EWaU88kMUeqbIVYG51MuwlqYwQxR6kfJUO98SndTSpJOE+amlCSdRYh/6ZOks3A+SYpqqvnUXWKWU/mklBnMECJD6vowcRc9DP9LX8fvSTOYYbJQM8r51PEZUtc3Q6wMzqdchLUwgxmi1I+Sod75lOym1MVXwG0Hy697/3w49qN8YVLUN4MZomVIXR/gvnn54Iwi1XyCGOuROkPq+mYww+kizSjnkxlS1zdDrAzOp1yEtTCDGaLUj5Kh3vnkC51LkiRJkiSpdN6UkiRJkiRJUum8KSVJkiRJkqTSeVNKkiRJkiRJpfOmlCRJkiRJkkqX7N33GjWHAZaxhstZxIX08jpHeJlBdrONwwyZocQMRw/Avm0wPAgnjsCsXuhfBIvXwOwFpURILkIPzBBHhHNphpx7MkYPzBBL6rOZun6UDO7JXIQ+pM6Qun4kEc5m6gyp60fJEEGEs9mJGcLflFrEclawjiWsJGMUgCpVRt/8fCV3sYeH2MFmBtllhmnMcGgn7NkMB7ZD5c1n7LIaVLryz5+5C65cCUvXw9zl0xIhuQg9MEMcEc6lGXLuyRg9MEMsqc9m6vpRMrgncxH6kDpD6vqRRDibqTOkrh8lQwQRzmYnZwj963srWMd6dnINN1OlShfddNFNZdLnVaos4RbW8zg3sdYM05Ahy+C5TbD9Rhh6BMjyzZnV3vz62OcZHHgEHnpvvpmzrKUxkorQAzPEkvpcmiHnnozRAzPEk/pspq4fIYN7MhehD6kzpK4fTeqzGSFD6vpRMqQW4WyaIfBNqZtYy61sAqCLWef93rGvr2ZzSw+LGXJ7t8CTd+afZyfP/71jX39ifX7dTBGhB2aII8K5NEPOPRmjB2aIJfXZTF0/Sgb3ZC5CH1JnSF0/kghnM3WG1PWjZIggwtk0Q4M3pTZu3Mi73/1uent7ufzyy/mVX/kV9u3b15okkyxiOavZXOja1WxmEe8xQ4syHNqZb7ginlgPLz7edITkIvTADFNzPnVehuh7sgwRemCG+nTKjEpdP0qGdtiTZYjQh9QZUtevR6fMpwgZUtePkiGCCGfTDLmGbkrt3LmTO+64gyeeeILHHnuMEydO8IEPfIBjx441n2SSFayjxolC19Y40ZI7uGbI7dkMlYKvPFbpzq9vdxF6YIapOZ86L0P0PVmGCD0wQ306ZUalrh8lQzvsyTJE6EPqDKnr16NT5lOEDKnrR8kQQYSzaYZcQ+UfffTRU/5627ZtXH755TzzzDMsX96aV7qawwBLWEm14G8WdjGLpXyYOcznMAfN0ESGowfyFzmj4O+KZifhhYfg6BDMHij2M1KL0AMz1Mf51FkZ2mFPTrcIPTBD/TphRqWuHyVDu+zJ6RahD6kzpK5fr06YTxEypK4fJUMEEc6mGSY09ZpSw8PDALz1rW9t5secYhlrxl/5v6iMUZZxuxmazLBv28Sr7hdVqcK+rc39jJQi9MAMxTifZnaGdtyTrRahB2YobibOqNT1o2Ro1z3ZahH6kDpD6vpFzcT5FCFD6vpRMkQQ4WyaYULBB7VgdHSU3/md3+GGG27gmmuuOef3HT9+nOPHj4//9cjIyHl/7uUsKhppkozLWFj4ajPkhgdbEAEY2d+an5NChB6YoXHOp5mfod325HSI0AMzFFPPjGp0PkH6s5m6fpQM7bgnp0OEPqTOkLp+ETN1PkXIkLp+lAwRRDibZphQ+L7YHXfcwd/8zd/wjW9847zft3HjRvr7+8c/BgbO/1zXhfQWfpxwTJUuLqKv8PVmyJ04MvE2kEVlNXhj6n9OhRWhB2ZonPNp5mdotz05HSL0wAzF1DOjGp1PkP5spq4fJUM77snpEKEPqTOkrl/ETJ1PETKkrh8lQwQRzqYZJhTakb/927/N9u3b+d73vsf8+fPP+70bNmxgeHh4/GNoaOi83/86Rxht8pHCUWq8RvHOmCE3qxcqXU1FoNIFF7TxzIrQAzM0xvnUGRnaaU9Olwg9MEPj6p1Rjc4nSH82U9ePkqHd9uR0idCH1BlS12/UTJ5PETKkrh8lQwQRzqYZJjT063tZlvGJT3yCBx98kO9///tcddVVU17T09NDT09P3TVephXPkFV4heLPkJkh19+KpzuBvjZ+ujNCD8xQH+dTZ2Vohz053SL0wAz1a3RGNTqfIP3ZTF0/SoZ22ZPTLUIfUmdIXb9enTCfImRIXT9KhgginE0zTGjoSak77riD++67j69//ev09vby0ksv8dJLL/Haa681l2KS3Wyj0uQjhRWq7Kb4q22ZIbd4DWTN3UgnG4XFbfw6eBF6YIb6OJ86K0M77MnpFqEHZqhfJ8yo1PWjZGiXPTndIvQhdYbU9evVCfMpQobU9aNkiCDC2TTDhIZ25D333MPw8DA33ngjc+fOHf/45je/2VyKSQ4zxF62U+NEoetrnGAP32nqLSrNkJu9ABashErBl8OvdMOVq9r77Ywj9MAM9XE+dVaGdtiT0y1CD8xQv06YUanrR8nQLntyukXoQ+oMqevXqxPmU4QMqetHyRBBhLNphgkN3ZTKsuysH2vWrGkuxWkeYxNdzCp0bZUudrDFDC3K8K71kJ0sdm1Wg6Xrmo6QXIQemKGOGs6njssQfU+WIUIPzFBnnQ6ZUanrR8nQDnuyDBH6kDpD6vp11emQ+RQhQ+r6UTJEEOFsmiHX3LN702SQXTxAsf933+ZOBtllhhZlmLscrt9U7Nrrv5Bf3+4i9MAMcUQ4l2bIuSdj9MAMsaQ+m6nrR8ngnsxF6EPqDKnrRxLhbKbOkLp+lAwRRDibZsiFvCkFsIMt44dlqscLx77+AOtaeufWDLklayc26lSP9o19/fpN+XUzRYQemCGOCOfSDDn3ZIwemCGW1Gczdf0oGdyTuQh9SJ0hdf1IIpzN1BlS14+SIYIIZ9MMgW9KQX5YNrGcvTzMKKPUOEmNk2SMUuMENU4yyih7eZhNLJ+WQ2IGqFTyx/JW7YQFtwCV/K0fx94+cvzzSv71VTvz769UWhojqQg9MEMsqc+lGXLuyRg9MEM8qc9m6voRMrgncxH6kDpD6vrRpD6bETKkrh8lQ2oRzqYZoOBLWpVnkF0Msos5zGcZt3MZC7mIPl5jhFfYz262TvsLrZkhN3d5/nF0CPZthZH98MYIXNCXvw3k4tvb/0U5pxKhB2aII8K5NEPOPRmjB2aIJfXZTF0/Sgb3ZC5CH1JnSF0/kghnM3WG1PWjZIggwtns5Azhb0qNOcxBHuZuMwTIMHsArvt00gjJReiBGeKIcC7NkHNPxuiBGWJJfTZT14+SwT2Zi9CH1BlS148kwtlMnSF1/SgZIohwNjsxQ+hf35MkSZIkSdLM5E0pSZIkSZIklc6bUpIkSZIkSSqdN6UkSZIkSZJUukqWZVmZBUdGRujv74cKXDKvzMq5V1+EbBQqVbh4bvn1zWCGaBlS1wc4dgjIYHh4mL6+vjQhSD+fIMZ6pM6Qur4ZzHC6CDPK+WSGKPXNECuD8ykXYS3MYIYo9aNkqHc+pbspJUmnCXNTSpLOIsS/9EnSWTifJEU11XzqLjHLqXxSygxmCJEhdX2YuIsehv+lr+P3pBnMMFmoGeV86vgMqeubIVYG51MuwlqYwQxR6kfJUO98SnZT6uIr4LaD5de9fz4c+1G+MCnqm8EM0TKkrg9w37x8cEaRaj5BjPVInSF1fTOY4XSRZpTzyQyp65shVgbnUy7CWpjBDFHqR8lQ73zyhc4lSZIkSZJUOm9KSZIkSZIkqXTelJIkSZIkSVLpvCklSZIkSZKk0qV7970GzWGAZazhchZxIb28zhFeZpDdbOMwQ6VkOHoA9m2D4UE4cQRm9UL/Ili8BmYvKCWCfQgiQg8iZIiwHyOI0Af3Qy5CH1KL0IMIGSLsxyhS98L9kIvQhwgi9CF1htT1I/FsxuiBGXKp90KnZgh/U2oRy1nBOpawkoxRAKpUGX3z85XcxR4eYgebGWTXtGQ4tBP2bIYD2/O3VATIalDpyj9/5i64ciUsXQ9zl09LBPsQRIQeRMgQYT9GEKEP7odchD6kFqEHETJE2I9RpO6F+yEXoQ8RROhD6gyp60fi2YzRAzPkUu+FTs8Q+tf3VrCO9ezkGm6mSpUuuumim8qkz6tUWcItrOdxbmJtS+tnGTy3CbbfCEOPAFm+KFntza+PfZ7BgUfgoffmi5hlLY1hHwKI0IMIGSD9fowidR/cD7kofUgpQg8iZID0+zGSlL1wP+Si9CG1CH1InSF1/Wg8m+l7YIZchL1ghsA3pW5iLbeyCYAuZp33e8e+vprNLd2oe7fAk3fmn2cnz/+9Y19/Yn1+XavYhxgi9CBChgj7MYIIfXA/5CL0IbUIPYiQIcJ+jCJ1L9wPuQh9iCBCH1JnSF0/Es9mjB6YIZd6L5ghF/Km1CKWs5rNha5dzWYW8Z6mMxzamTe6iCfWw4uPNx3BPgQRoQcRMkTYjxFE6IP7IRehD6lF6EGEDBH2YxSpe+F+yEXoQwQR+pA6Q+r6kXg2Y/TADLnUe8EMExq6KXXPPfewdOlS+vr66Ovr4xd/8Rd55JFHmk9xmhWso8aJQtfWONGSu6d7NkOl4CtuVbrz65tlH2KI0IMIGSLsx/NxPtVnJu2HCH1ILUIPImSIsB+n0ikzyv2Qi9CHCCL0IXWG1PXr0SnzCdKvR4QemCGXei+YYUJDN6Xmz5/P7//+7/PMM8/wgx/8gF/6pV/iIx/5CP/jf/yP5pO8aQ4DLGHllI/wnUsXs1jKh5nD/MIZjh7IX9xrqkfXziU7CS88BEebeJMA+xBDhB5EyBBhP07F+VSfmbIfIvQhtQg9iJAhwn6sRyfMKPdDLkIfIojQh9QZUtevVyfMJ0i/HhF6YIZc6r1ghlM1dFNq1apV3HLLLSxatIh3vvOdfPazn2X27Nk88cQTzaWYZBlrxl91v6iMUZZxe+Hr922beLX5oipV2Le1+PX2IYYIPYiQIcJ+nIrzqX4zYT9E6ENqEXoQIUOE/ViPTphR7odchD5EEKEPqTOkrl+vTphPkH49IvTADLnUe8EMpyr4oBbUajUeeOABjh07xi/+4i+e8/uOHz/O8ePHx/96ZGTkvD/3chYVjTRJxmUsLHz18GALIgAj+4tfax9iiNCDCBki7MdGOJ+m1u77IUIfUovQgwgZIuzHRtUzoxqdT5C+F+6HXIQ+RBChD6kzpK5fxEydT5B+PSL0wAy51HvBDKdq+L7Y3r17mT17Nj09Pfzmb/4mDz74ID/zMz9zzu/fuHEj/f394x8DAwPn/fkX0ku1yddfr9LFRfQVvv7EkYm3Pywqq8EbU8/nc7IPMUToQYQMEfZjPZxP9ZkJ+yFCH1KL0IMIGSLsx3o1MqManU+Qvhfuh1yEPkQQoQ+pM6Su34iZPp8g/XpE6IEZcqn3ghlO1fBuWLx4Mc8++yxPPvkkv/Vbv8XHPvYx/vZv//ac379hwwaGh4fHP4aGzv8Lh69zhNEmH+cbpcZrFO/MrF6odDUVgUoXXNDEn2/tQwwRehAhQ4T9WA/nU31mwn6I0IfUIvQgQoYI+7FejcyoRucTpO+F+yEXoQ8RROhD6gyp6zdips8nSL8eEXpghlzqvWCGUzX863sXXHABCxfmj8pdd911PP300/zn//yf+aM/+qOzfn9PTw89PT11//yXacUzZBVeofgzZP2teKIQ6GviNwHsQwwRehAhQ4T9WA/nU/3afT9E6ENqEXoQIUOE/VivRmZUo/MJ0vfC/ZCL0IcIIvQhdYbU9Rsx0+cTpF+PCD0wQy71XjDDqZp8WSsYHR095XeKm7WbbVSajFWhym6Kv9rW4jWQNXfzlmwUFjfxmqn2IYYIPYiQIcJ+LML5dHYzYT9E6ENqEXoQIUOE/VjUTJtR7odchD5EEKEPqTOkrt+MmTafIP16ROiBGXKp94IZTtXQbtiwYQOPP/44zz//PHv37mXDhg18//vf57bbbmsuxSSHGWIv26lxotD1NU6wh+9wmIOFM8xeAAtWQqXgy8BXuuHKVTB76l+vPif7EEOEHkTIEGE/TsX5VJ+Zsh8i9CG1CD2IkCHCfqxHJ8wo90MuQh8iiNCH1BlS169XJ8wnSL8eEXpghlzqvWCGUzV0U+rll1/m13/911m8eDHvf//7efrpp/mzP/szVqxY0VyK0zzGJrqYVejaKl3sYEvTGd61HrKTxa7NarB0XdMR7EMQEXoQIUOE/Xg+zqf6zKT9EKEPqUXoQYQMEfbjVDplRrkfchH6EEGEPqTOkLp+PTplPkH69YjQAzPkUu8FM0xo6KbUvffey/PPP8/x48d5+eWX2bFjR8uHFcAgu3iAYv/vvs2dDLKr6Qxzl8P1m4pde/0X8uubZR9iiNCDCBki7MfzcT7VZybthwh9SC1CDyJkiLAfp9IpM8r9kIvQhwgi9CF1htT169Ep8wnSr0eEHpghl3ovmGFC068pNV12sGV8o071aN/Y1x9gXUv/a+eStRMLNNUjbWNfv35Tfl2r2IcYIvQgQoYI+zGCCH1wP+Qi9CG1CD2IkCHCfowidS/cD7kIfYggQh9SZ0hdPxLPZowemCGXei+YIRf2phTkG3UTy9nLw4wySo2T1DhJxig1TlDjJKOMspeH2cTylv/BslLJH0dbtRMW3AJU8rc8HHvbxPHPK/nXV+3Mv79SaWkM+xBAhB5EyADp92MUqfvgfshF6UNKEXoQIQOk34+RpOyF+yEXpQ+pRehD6gyp60fj2UzfAzPkIuwFM0DBl7QqzyC7GGQXc5jPMm7nMhZyEX28xgivsJ/dbJ32Fyeduzz/ODoE+7bCyH54YwQu6Mvf/nDx7dP/AoT2IYYIPYiQIcJ+jCBCH9wPuQh9SC1CDyJkiLAfo0jdC/dDLkIfIojQh9QZUtePxLMZowdmyKXeC52eIfxNqTGHOcjD3J00w+wBuO7TSSPYhyAi9CBChgj7MYIIfXA/5CL0IbUIPYiQIcJ+jCJ1L9wPuQh9iCBCH1JnSF0/Es9mjB6YIZd6L3RqhtC/vidJkiRJkqSZyZtSkiRJkiRJKp03pSRJkiRJklQ6b0pJkiRJkiSpdJUsy7IyC46MjNDf3w8VuGRemZVzr74I2ShUqnDx3PLrm8EM0TKkrg9w7BCQwfDwMH19fWlCkH4+QYz1SJ0hdX0zmOF0EWaU88kMUeqbIVYG51MuwlqYwQxR6kfJUO98SndTSpJOE+amlCSdRYh/6ZOks3A+SYpqqvnUXWKWU/mklBnMECJD6vowcRc9DP9LX8fvSTOYYbJQM8r51PEZUtc3Q6wMzqdchLUwgxmi1I+Sod75lOym1MVXwG0Hy697/3w49qN8YVLUN4MZomVIXR/gvnn54Iwi1XyCGOuROkPq+mYww+kizSjnkxlS1zdDrAzOp1yEtTCDGaLUj5Kh3vnkC51LkiRJkiSpdN6UkiRJkiRJUum8KSVJkiRJkqTSeVNKkiRJkiRJpfOmlCRJkiRJkkqX7N33GjWHAZaxhstZxIX08jpHeJlBdrONwwyVkuHoAdi3DYYH4cQRmNUL/Ytg8RqYvaCUCGYIUD9KhghnIkKGCCL0IcKeNEOMDKnrQ4wzESFDFKl7EWFPmsEMk3km4ki9FpB+PVLXhxjrECGDa5Eruw/hb0otYjkrWMcSVpIxCkCVKqNvfr6Su9jDQ+xgM4PsmpYMh3bCns1wYDtU3ny2LKtBpSv//Jm74MqVsHQ9zF0+LRHMEKB+lAwRzkSEDBFE6EOEPWmGGBlS14cYZyJChihS9yLCnjSDGSbzTMSRei0g/Xqkrg8x1iFCBtcil6oPoX99bwXrWM9OruFmqlTpopsuuqlM+rxKlSXcwnoe5ybWtrR+lsFzm2D7jTD0CJDli5LV3vz62OcZHHgEHnpvvohZZoZWZkhdP0oGSH8momSIIHUfIuxJM8TIkLr+mNRnIkqGKFL2IsKeNIMZTtfpZyKS1LM69Xqkrj8m9TpEyOBa5FL3IexNqZtYy61sAqCLWef93rGvr2ZzSxdo7xZ48s788+zk+b937OtPrM+vM0PrMqSuHyVDhDMRIUMEEfoQYU+aIUaG1PUhxpmIkCGK1L2IsCfNYIbJPBNxpF4LSL8eqetDjHWIkMG1yKXuQ1M3pX7/93+fSqXC7/zO77QmzZsWsZzVbC507Wo2s4j3NJ3h0M680UU8sR5efLzpCGYIUD9KhghnIkKGRjifzm4mnQszpK8PMc5EhAyNmK75BOl7EWFPmsEMk3kmGuefoc7Of27PrH9uuxa5CH0ofFPq6aef5o/+6I9YunRp8ylOs4J11DhR6NoaJ1py13DPZqgUfMWtSnd+vRmaz5C6fpQMEc5EhAz1cj6d20w6F2ZIXx9inIkIGeo1nfMJ0vciwp40gxkm80w0xj9DnZv/3J5Z/9x2LXIR+lDoptTRo0e57bbb+MpXvsKcOXOaTzHJHAZYwsopH107ly5msZQPM4f5hTMcPZC/uNdUj66dS3YSXngIjjbx4vhmSF8/SoYIZyJChno5n85vppwLM6SvDzHORIQM9ZrO+QTpexFhT5rBDJN5Jhrjn6HOz39uz5x/brsWuQh9gII3pe644w4+9KEPcdNNNzVX/SyWsWb81eaLyhhlGbcXvn7ftolXmy+qUoV9W4tfb4b09aNkiHAmImSol/NpajPhXJghfX2IcSYiZKjXdM4nSN+LCHvSDGaYzDPRGP8MNTX/uT0z/rntWuQi9AGg4Qe1vvGNb/DXf/3XPP3003V9//Hjxzl+/Pj4X4+MjJz3+y9nUaORziLjMhYWvnp4sAURgJH9xa81Q/r6UTJEOBMRMtTD+VS/dj8XZkhfH2KciQgZ6jHd8wnS9yLCnjSDGSbzTNSvkRnVjvMJ0q9H6voQYx0iZHAtchH6AA0+KTU0NMQnP/lJ7r//fi688MK6rtm4cSP9/f3jHwMDA+f9/gvppdrkmwJW6eIi+gpff+LIxNsfFpXV4I2p57MZAtePkiHCmYiQYSrOp/rNhHNhhvT1IcaZiJBhKmXMJ0jfiwh70gxmmMwzUZ9GZ1Q7zidIvx6p60OMdYiQwbXIRegDNHhT6plnnuHll1/m537u5+ju7qa7u5udO3fyX/7Lf6G7u5ta7cz/Rxs2bGB4eHj8Y2jo/L9w+DpHGG3yMbZRarxG8c7M6oVKV1MRqHTBBU38+dYM6etHyRDhTETIMBXnU/1mwrkwQ/r6EONMRMgwlTLmE6TvRYQ9aQYzTOaZqE+jM6od5xOkX4/U9SHGOkTI4FrkIvQBGvz1vfe///3s3bv3lL93++23c/XVV/N7v/d7dHWd+f+op6eHnp6eumu8TCueIavwCsWfIetvxZN0QF8TvwlghvT1o2SIcCYiZJiK86kx7X4uzJC+PsQ4ExEyTKWM+QTpexFhT5rBDJN5JurT6Ixqx/kE6dcjdX2IsQ4RMrgWuQh9gAaflOrt7eWaa6455eOSSy7h0ksv5ZprrmkuyZt2s41Kk4+xVaiym+KvtrV4DWTN3bQkG4XFTbxmqhnS14+SIcKZiJBhKs6n+s2Ec2GG9PUhxpmIkGEqZcwnSN+LCHvSDGaYzDNRH/8MVT//uT0z/rntWuQi9AEKvvvedDrMEHvZTo0Tha6vcYI9fIfDHCycYfYCWLASKg2/DHyu0g1XroLZU/96tRkC14+SIcKZiJAhggh9iLAnzRAjQ+r6EONMRMgQRepeRNiTZjDDZJ6JOFKvBaRfj9T1IcY6RMjgWuQi9AFacFPq+9//Pl/84heb/TGneIxNdDGr0LVVutjBlqYzvGs9ZCeLXZvVYOm6piOYIUD9KBkinIkIGRrlfDrTTDoXZkhfH2KciQgZGjUd8wnS9yLCnjSDGSbzTBTjn6HO5D+3Z9Y/t12LXIQ+hHtSCmCQXTxAsf933+ZOBtnVdIa5y+H6TcWuvf4L+fVmaD5D6vpRMkQ4ExEyRBChDxH2pBliZEhdH2KciQgZokjdiwh70gxmmMwzEUfqtYD065G6PsRYhwgZXItchD6EvCkFsIMt4ws01SNtY19/gHUt/a+dS9ZOLNBUj7SNff36Tfl1ZmhdhtT1o2SIcCYiZIggQh8i7EkzxMiQuj7EOBMRMkSRuhcR9qQZzDCZZyKO1GsB6dcjdX2IsQ4RMrgWudR9CHtTCvIF2sRy9vIwo4xS4yQ1TpIxSo0T1DjJKKPs5WE2sbzlf7CsVPLH0VbthAW3AJX8LQ/H3jZx/PNK/vVVO/Pvr1TM0MoMqetHyQDpz0SUDBGk7kOEPWmGGBlS1x+T+kxEyRBFyl5E2JNmMMPpOv1MRJJ6Vqdej9T1x6RehwgZXItc6j4UfEmr8gyyi0F2MYf5LON2LmMhF9HHa4zwCvvZzdZpf3HSucvzj6NDsG8rjOyHN0bggr787Q8X3z79L0BohvT1o2SIcCYiZIggQh8i7EkzxMiQuj7EOBMRMkSRuhcR9qQZzDCZZyKO1GsB6dcjdX2IsQ4RMrgWuVR9CH9TasxhDvIwdyfNMHsArvt00ghmCFA/SoYIZyJChggi9CHCnjRDjAyp60OMMxEhQxSpexFhT5rBDJN5JuJIvRaQfj1S14cY6xAhg2uRK7sPoX99T5IkSZIkSTOTN6UkSZIkSZJUOm9KSZIkSZIkqXTelJIkSZIkSVLpKlmWZWUWHBkZob+/HypwybwyK+defRGyUahU4eK55dc3gxmiZUhdH+DYISCD4eFh+vr60oQg/XyCGOuROkPq+mYww+kizCjnkxmi1DdDrAzOp1yEtTCDGaLUj5Kh3vmU7qaUJJ0mzE0pSTqLEP/SJ0ln4XySFNVU86m7xCyn8kkpM5ghRIbU9WHiLnoY/pe+jt+TZjDDZKFmlPOp4zOkrm+GWBmcT7kIa2EGM0SpHyVDvfMp2U2pi6+A2w6WX/f++XDsR/nCpKhvBjNEy5C6PsB98/LBGUWq+QQx1iN1htT1zWCG00WaUc4nM6Sub4ZYGZxPuQhrYQYzRKkfJUO988kXOpckSZIkSVLpvCklSZIkSZKk0nlTSpIkSZIkSaXzppQkSZIkSZJKl+7d9xo0hwGWsYbLWcSF9PI6R3iZQXazjcMMlZLh6AHYtw2GB+HEEZjVC/2LYPEamL2glAj2gRg9iJAhAvuQi9CH1OcS7MOY1H1IXT8K+zAhdS88lzn7ECdDahH2QhQR9kPq9bAHuQh9iJAhgrL3Q/ibUotYzgrWsYSVZIwCUKXK6Jufr+Qu9vAQO9jMILumJcOhnbBnMxzYnr+lIkBWg0pX/vkzd8GVK2Hpepi7fFoi2Adi9CBChgjsQy5CH1KfS7APY1L3IXX9KOzDhNS98Fzm7EOcDKlF2AtRRNgPqdfDHuQi9CFChghS7YfQv763gnWsZyfXcDNVqnTRTRfdVCZ9XqXKEm5hPY9zE2tbWj/L4LlNsP1GGHoEyPJFyWpvfn3s8wwOPAIPvTdfxCxraQz7QPoeRMkQgX3Ipe5DhHMJ9mFM6j6krh+FfZiQsheey5x9iJUhpSh7IYrU+yHCetiDXOo+RMmQWur9EPam1E2s5VY2AdDFrPN+79jXV7O5pZtk7xZ48s788+zk+b937OtPrM+vaxX7EKMHETJEYB9yEfqQ+lyCfRiTug+p60dhHyak7oXnMmcf4mRILcJeiCLCfki9HvYgF6EPETJEkHo/hLwptYjlrGZzoWtXs5lFvKfpDId25o3+/7N3/8Fx3Xe9/5+7kqP8sKS6qU1sLIe0Vh0gdiakheBM3BTiUqdyS4eYH5NCHbh3LtSUgq1cmjtDCaSt6Y3k6f3SkgsltcukpW06hEkcEohL65gxzi9uYgPFyEBiuXZI5l5Xsp3EkXbP94+TlWTZ1u6elc77Je3rMaOpEuno/ern8z7vOJ8c7WaxrxeOPd5wBK8DGmugkEGB1yGlsA7R9yV4HSqi1yG6vgqvw7jotfB9mfI66GSIptALKhT6IXo/vAYphXVQyKBAoR/qOpS68847KRQKZ3xceeWVjaeYZC1bKDGS6doSI9Nycrm/HwoZX3Gr0Jpe3yivg8YaKGRQoL4Onk+18XxKzZV1iK6vYjasQ7PMKN+XKa+DToZoCr1QTbPMJ4jfD69BSmEdFDIoUOiHup+U+uEf/mGOHTs29vF3f/d3jaeYYAFdrKSn6uNz59PCPFbxfhawNHOGk4fTF/eq9uja+SSj8MJDcLKBF+j3OmisgUIGBbNlHTyfqvN8Ss2FdYiur2I2rcNcn1G+L1NeB50M0RR6oVZzfT5B/H54DVIK66CQQYFCP0CGQ6nW1lYuu+yysY+3vOUtjSWYZDUbx17xPquEMqu5LfP1B3eMv9p8VoUiHNye/Xqvg8YaKGRQMFvWwfOpNp5Pqdm+DtH1VcymdZjrM8r3ZcrroJMhmkIv1GquzyeI3w+vQUphHRQyKFDoB8hwKDUwMMCSJUt461vfyq233srhw4en/P7Tp08zPDx8xsdUFtFdb6RzSFjI8sxXDw1MQwRg+FD2a70OGmugkEHBbFkHz6faeT6lZvM6RNdXMZvWoZ4ZVe98gvi18H2Z8jroZIim0Au1muvzCeL3w2uQUlgHhQwKFPoB6jyU+rEf+zF27NjBo48+yj333MN//Md/cMMNN3DixInzXrN161Y6OzvHPrq6uqascSHtFBt8/fUiLVxER+brR06Mv/1hVkkJXq8+n8/L66CxBgoZFMyGdfB8qp3nU2q2r0N0fRWzZR3qnVH1zieIXwvflymvg06GaAq9UItmmE8Qvx9eg5TCOihkUKDQD1DnodS6devYsGEDq1at4qd+6qf4q7/6K773ve/x9a9//bzX3HHHHQwNDY19DA5O/QuHr3GCcoOP0pUp8SrZV2ZeOxRaGopAoQUuaKBHvQ4aa6CQQcFsWAfPp9p5PqVm+zpE11cxW9ah3hlV73yC+LXwfZnyOuhkiKbQC7VohvkE8fvhNUgprINCBgUK/QCQ8XXWU29605t4+9vfzqFD539eq62tjba2tpp/5ktMxzNkBV4m+zNkndPxNB/Q0cDTfF4HjTVQyKBgNq6D59PUPJ9Ss3kdouurmK3rUG1G1TufIH4tfF+mvA46GaIp9EIWc3E+Qfx+eA1SCuugkEGBQj9AhteUmujkyZP827/9G4sXL24sxQR72UGhwUfpChTZS/ZX21qxEZLGDk5JyrCigdc98zporIFCBgWzcR08n87P8yk129chur6K2boOc3FG+b5MeR10MkRT6IUs5uJ8gvj98BqkFNZBIYMChX6AOg+lent72b17N88//zx79+7lgx/8IC0tLfzCL/xCYykmOM4gB9hJiZFM15cYYT8PcpwjmTPMXwbLeqCQ8TmyQitcvh7mV//16vPyOmisgUIGBbNhHTyfauP5lJoL6xBdX8VsWYdmmFG+L1NeB50M0RR6oRbNMJ8gfj+8BimFdVDIoEChH6DOQ6kjR47wC7/wC6xYsYKf/dmf5dJLL2Xfvn0sXLiwsRSTPEYfLczLdG2RFnaxreEMV/dCMprt2qQEq7Y0HMHrgMYaKGRQoL4Onk+18XxKzZV1iK6vYjasQ7PMKN+XKa+DToZoCr1QTbPMJ4jfD69BSmEdFDIoUOiHug6lvvrVr3L06FFOnz7NkSNH+OpXv8rb3va2xlNMMsAe7ifb/7tvcDsD7Gk4w+I1cF1ftmuvuzu9vlFeB401UMigQH0dPJ9q4/mUmivrEF1fxWxYh2aZUb4vU14HnQzRFHqhmmaZTxC/H16DlMI6KGRQoNAPjf0i5QzaxbaxJqn2WF3l6/ezZVpPLFduHt+gao+0Vb5+XV963XTxOmisgUIGBV6HlMI6RN+X4HWoiF6H6PoqvA7jotfC92XK66CTIZpCL6hQ6Ifo/fAapBTWQSGDguh+kD2UgrRJ+ljDAR6mTJkSo5QYJaFMiRFKjFKmzAEepo81094chUL6ONr63bDsZqCQvuVh5W0Txz4vpF9fvzv9/kJhWmN4HYhfA5UMCrwOqeh1ULgvwetQEb0O0fVVeB3GRa6F78uU10ErQySVXlAR3Q8K++E1SEWvg0qGaNH9kPElrfIzwB4G2MMClrKa21jIci6ig1cZ5mUOsZftM/4CY4vXpB8nB+Hgdhg+BK8PwwUd6dsfrrht5l+A0OugsQYKGRR4HVIK6xB9X4LXoSJ6HaLrq/A6jIteC9+XKa+DToZoCr2gQqEfovfDa5BSWAeFDAqi+kH+UKriOEd4mLtCM8zvgms/ERrB64DGGihkUOB1SCmsQ/R9CV6Hiuh1iK6vwuswLnotfF+mvA46GaIp9IIKhX6I3g+vQUphHRQyKMi7H6R/fc/MzMzMzMzMzOYmH0qZmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlrpAkSZJnweHhYTo7O6EAlyzJs3LqlWOQlKFQhIsX51/fGZxBLUN0fYBTR4EEhoaG6OjoiAlB/HwCjf2IzhBd3xmcYTKFGeX55Awq9Z1BK4PnU0phL5zBGVTqq2SodT7FHUqZmU0icyhlZnYOEv/SZ2Z2Dp5PZqaq2nxqzTHLmfyklDM4g0SG6Powfoouw/+lr+l70hmcYSKpGeX51PQZous7g1YGz6eUwl44gzOo1FfJUOt8CjuUuvgyuPVI/nW/vBROfTfdmIj6zuAMahmi6wPctyQdnCqi5hNo7Ed0huj6zuAMkynNKM8nZ4iu7wxaGTyfUgp74QzOoFJfJUOt88kvdG5mZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma5C3v3vdloAV2sZiOL6OZC2nmNE7zEAHvZwXEGc8lw8jAc3AFDAzByAua1Q2c3rNgI85flEiE8Q3R9cC9UKKyDpRT2QqEnncG9UKGwDpZS2AuFnnSGlPshvr6dKbonFfrBGVLRvQAa65B3Bh9K1aCbNaxlCyvpIaEMQJEi5Tc+7+FO9vMQu+hngD0zkuHobtjfD4d3QuGN59uSEhRa0s+fuRMu74FVvbB4zYxECM8QXR/cCxUK62Aphb1Q6ElncC9UKKyDpRT2QqEnnSHlfoivb2eK7kmFfnCGVHQvgMY6RGXwr+9VsZYt9LKbq1hHkSIttNJCK4UJnxcpspKb6eVxbmLztNZPEniuD3beCIOPAEnaGEnpja9XPk/g8CPw0LvSRkqSuZMhun6FeyEVvQ42LnovFHrSGVLuhVT0Oti46L1Q6ElnGNfs/RBd384W2ZMK/eAM45p9Pilk8KHUFG5iM7fQB0AL86b83srXN9A/rY16YBs8cXv6eTI69fdWvr6vN71urmSIrg/uhQqFdbCUwl4o9KQzuBcqFNbBUgp7odCTzpByP8TXtzNF96RCPzhDKroXQGMdojPUfSj13e9+lw996ENceumlXHTRRaxcuZKnn356etII6WYNG+jPdO0G+unmhoYzHN2dbnYW+3rh2OMNRwjPEF0f3AsVCutQjedTdXOpJ53BvVChsA61aIYZpbAXCj3pDCn3Q3z9WjXDfIL4nlToB2dIRfcCaKyDQoa6DqWOHz/O9ddfz7x583jkkUf453/+Z/r7+1mwYEHjScSsZQslRjJdW2JkWk5P9/dDIeOrfhVa0+tne4bo+uBeqFBYh6l4PtVmLvWkM7gXKhTWoZpmmVEKe6HQk86Qcj/E169Fs8wniO9JhX5whlR0L4DGOihkqKv8Zz7zGbq6uti+ffvY37viiisaTyFmAV2spIdixt9ubGEeq3g/C1jKcY5k+hknD6cvMEbG39NMRuGFh+DkIMzvyvYzojNE1wf3QoXCOlTj+VSbudKTzuBeqFBYh1o0w4xS2AuFnnSGlPshvn6tmmE+QXxPKvSDM6SiewE01kEhA9T5pNSDDz7IO97xDjZs2MCiRYu45ppr+MIXvpC9uqjVbBx71f2sEsqs5rbM1x/cMf6K91kVinBwe/XvU80QXR/cCxUK61CN51Pt5kJPOoN7oUJhHWrRDDNKYS8UetIZUu6H+Pq1aob5BPE9qdAPzpCK7gXQWAeFDFDnodS///u/c88999Dd3c1f//Vf82u/9mv8xm/8Bl/60pfOe83p06cZHh4+40PdIrqn4ackLGR55quHBqYhAjB8KPu10Rmi64N7oUJhHarxfKrH7O9JZ3AvVCisQy3qnVGeT9ko9KQzpNwP8fVr1QzzCeJ7UqEfnCEV3QugsQ4KGaDOX98rl8u84x3v4NOf/jQA11xzDf/4j//I//7f/5sPf/jD57xm69at/N7v/V5jKXN2Ie2ZH+WrKNLCRXRkvn7kxPhbMGaVlOD1Bv4ZEZ0huj64FyoU1qEaz6fazYWedAb3QoXCOtSi3hnl+ZSNQk86Q8r9EF+/Vs0wnyC+JxX6wRlS0b0AGuugkAHqfFJq8eLF/NAP/dAZf+8Hf/AHOXz48HmvueOOOxgaGhr7GBwczJY0R69xgnKDj/OVKfEq2XdnXjsUWhqKQKEFLmjgz9jRGaLrg3uhQmEdqvF8qt1c6ElncC9UKKxDLeqdUZ5P2Sj0pDOk3A/x9WvVDPMJ4ntSoR+cIRXdC6CxDgoZoM4npa6//noOHjx4xt/713/9Vy6//PLzXtPW1kZbW1u2dEFeYjqeYyvwMtmfY+ucjicKgY4GfhshOkN0fXAvVCisQzWeT/WY/T3pDO6FCoV1qEW9M8rzKRuFnnSGlPshvn6tmmE+QXxPKvSDM6SiewE01kEhA9T5pNRv/dZvsW/fPj796U9z6NAhvvKVr/Anf/InbNq0qbEUYvayg0KDj/MVKLKX7K/4tWIjJI0d3pKUYUUDr9sanSG6PrgXKhTWoRrPp9rNhZ50BvdChcI61KIZZpTCXij0pDOk3A/x9WvVDPMJ4ntSoR+cIRXdC6CxDgoZoM5DqXe+85088MAD/Pmf/zlXXXUVd911F5/97Ge59dZbG0sh5jiDHGAnJUYyXV9ihP082NBbS89fBst6oFDXs2zjCq1w+frG3poxOkN0fXAvVCisQzWeT7WZKz3pDO6FCoV1qEUzzCiFvVDoSWdIuR/i69eqGeYTxPekQj84Qyq6F0BjHRQyQJ2HUgA9PT0cOHCA1157je985zv81//6XxtLIOox+mhhXqZri7Swi20NZ7i6F5LRbNcmJVi1peEI4Rmi64N7oUJhHarxfKpuLvWkM7gXKhTWoRbNMKMU9kKhJ50h5X6Ir1+rZphPEN+TCv3gDKnoXgCNdVDI0Ngza3PYAHu4n2wr/A1uZ4A9DWdYvAau68t27XV3p9fP9gzR9cG9UKGwDpZS2AuFnnQG90KFwjpYSmEvFHrSGVLuh/j6dqbonlToB2dIRfcCaKyDQgYfSk1hF9vGGrXao32Vr9/Plmn9L64rN483SbXH6ipfv64vvW6uZIiuD+6FCoV1sJTCXij0pDO4FyoU1sFSCnuh0JPOkHI/xNe3M0X3pEI/OEMquhdAYx2iM/hQqopdbKOPNRzgYcqUKTFKiVESypQYocQoZcoc4GH6WDPtf7gtFNJH4tbvhmU3A4X0bRcrb9049nkh/fr63en3FwpzJ0N0/Qr3Qip6HWxc9F4o9KQzpNwLqeh1sHHRe6HQk84wrtn7Ibq+nS2yJxX6wRnGNft8UsiQ8SWtmssAexhgDwtYympuYyHLuYgOXmWYlznEXrbP+AukLl6TfpwchIPbYfgQvD4MF3Skb8G44raZfxHE6AzR9cG9UKGwDpZS2AuFnnQG90KFwjpYSmEvFHrSGVLuh/j6dqbonlToB2dIRfcCaKxDVAYfStXhOEd4mLtCM8zvgms/ERohPEN0fXAvVCisg6UU9kKhJ53BvVChsA6WUtgLhZ50hpT7Ib6+nSm6JxX6wRlS0b0AGuuQdwb/+p6ZmZmZmZmZmeXOh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma5KyRJkuRZcHh4mM7OTijAJUvyrJx65RgkZSgU4eLF+dd3BmdQyxBdH+DUUSCBoaEhOjo6YkIQP59AYz+iM0TXdwZnmExhRnk+OYNKfWfQyuD5lFLYC2dwBpX6KhlqnU9xh1JmZpPIHEqZmZ2DxL/0mZmdg+eTmamqNp9ac8xyJj8p5QzOIJEhuj6Mn6LL8H/pa/qedAZnmEhqRnk+NX2G6PrOoJXB8ymlsBfO4Awq9VUy1Dqfwg6lLr4Mbj2Sf90vL4VT3003JqK+MziDWobo+gD3LUkHp4qo+QQa+xGdIbq+MzjDZEozyvPJGaLrO4NWBs+nlMJeOIMzqNRXyVDrfPILnZuZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpa7uHffq9MCuljNRhbRzYW08xoneIkB9rKD4wxGx8vNycNwcAcMDcDICZjXDp3dsGIjzF/WHBkUeiF6DUBjHSylsBfO4AwVnk82WfR+RNd3Bq0MCjMqOkN0fSUKPRmdIbq+M4xTuDebMYP8oVQ3a1jLFlbSQ0IZgCJFym983sOd7OchdtHPAHsio86oo7thfz8c3pm+rSNAUoJCS/r5M3fC5T2wqhcWr5mbGRR6IXoNQGMdLKWwF87gDBWeTzZZ9H5E13cGrQwKMyo6Q3R9JQo9GZ0hur4zjFO4N5s5g/Sv761lC73s5irWUaRIC6200EphwudFiqzkZnp5nJvYHB152iUJPNcHO2+EwUeAJG2MpPTG1yufJ3D4EXjoXWkjJcncyhDdCwprAPHrYOMU9sIZnAE8n+zcovcjur4z6GRQmFHRGaLrq4nuSYUM0fWdIaVwbzqD8KHUTWzmFvoAaGHelN9b+foG+ufcH3IPbIMnbk8/T0an/t7K1/f1ptfNlQwKvRC9BqCxDpZS2AtncIYKzyebLHo/ous7g1YGhRkVnSG6vhKFnozOEF3fGcYp3JvOIHoo1c0aNtCf6doN9NPNDdOcKMbR3elmZ7GvF449PvszKPRC9BqAxjpYSmEvnMEZKjyfbLLo/Yiu7wxaGRRmVHSG6PpKFHoyOkN0fWcYp3BvOkOqrkOpH/iBH6BQKJz1sWnTpsaTTLCWLZQYyXRtiZE5819e9/dDIeOrfhVa0+tnewaFXoheA9BYh9kgjxmlsBfO4AwVnk+zR7P8GSq6vjNoZVCYUdEZouvXolnmk0KG6PrOME7h3nSGVF2HUk899RTHjh0b+3jssccA2LBhQ+NJ3rCALlbSU/URvvNpYR6reD8LWDptmSKcPJy+wFi1x+fOJxmFFx6Ckw28UUF0BoVeiF4D0FiH2WKmZ5TCXjiDM1R4Ps0uzfBnqOj6zqCVQWFGRWeIrl+rZphPChmi6zvDOIV70xnG1XUotXDhQi677LKxj507d/K2t72Nd73rXY2lmGA1G8dedT+rhDKruW2aEsU4uGP8Fe+zKhTh4PbZm0GhF6LXADTWYbaY6RmlsBfO4AwVnk+zSzP8GSq6vjNoZVCYUdEZouvXqhnmk0KG6PrOME7h3nSGcRkf1ILXX3+d++67j82bN1MoFM77fadPn+b06dNjfz08PDzlz11Ed9ZIEyQsZPk0/Jw4QwPT83OGD83eDAq9EL0GoLEOs1EtM2o2zidncIYKz6fZaybmE8TvR3R9Z9DKoDCjojNE189irs4nhQzR9Z1hnMK96QzjMp+L/eVf/iXf+9732Lhx45Tft3XrVjo7O8c+urq6pvz+C2mn2ODrrxdp4SI6GvoZ0UZOjL8FY1ZJCV6v/s8I2QwKvRC9BqCxDrNRLTNqNs4nZ3CGCs+n2Wsm5hPE70d0fWfQyqAwo6IzRNfPYq7OJ4UM0fWdYZzCvekM4zJ3w7333su6detYsmTJlN93xx13MDQ0NPYxODj1Lxy+xgnKDT7OV6bEq+Q4vWfAvHYotDT2MwotcEEDf86PzqDQC9FrABrrMBvVMqNm43xyBmeo8HyavWZiPkH8fkTXdwatDAozKjpDdP0s5up8UsgQXd8Zxincm84wLtOv773wwgvs2rWLv/iLv6j6vW1tbbS1tdX8s19iOp4hK/AyOT7nOgM6p+OpRqCjgd+IiM6g0AvRawAa6zDb1DqjZuN8cgZnqPB8mp1maj5B/H5E13cGrQwKMyo6Q3T9es3l+aSQIbq+M4xTuDedYVymJ6W2b9/OokWLeN/73tdY9XPYyw4KDT7OV6DIXmb4FQFn2IqNkDR2gExShhUNvHZsdAaFXoheA9BYh9lmpmaUwl44gzNUeD7NTnP5z1DR9Z1BK4PCjIrOEF2/XnN5PilkiK7vDOMU7k1nGFd3N5TLZbZv386HP/xhWlszv076eR1nkAPspMRIputLjLCfBznOkWlOlq/5y2BZDxQyLnGhFS5fD/Or/4q3bAaFXoheA9BYh9lkJmeUwl44gzNUeD7NPnP9z1DR9Z1BK4PCjIrOEF2/HnN9PilkiK7vDOMU7k1nGFf3odSuXbs4fPgwv/zLv9xY5Sk8Rh8tzMt0bZEWdrFtmhPFuLoXktFs1yYlWLVl9mdQ6IXoNQCNdZgtZnpGKeyFMzhDhefT7NIMf4aKru8MWhkUZlR0huj6tWqG+aSQIbq+M4xTuDedIVX3odR73vMekiTh7W9/e+PVz2OAPdxPtv933+B2BtgzzYliLF4D1/Vlu/a6u9PrZ3sGhV6IXgPQWIfZYqZnlMJeOIMzVHg+zS7N8Geo6PrOoJVBYUZFZ4iuX6tmmE8KGaLrO8M4hXvTGVKN/TLnDNrFtrFGrfZoX+Xr97Nlzv0X15Wbx5uk2mN1la9f15deN1cyKPRC9BqAxjpYSmEvnMEZKjyfbLLo/Yiu7wxaGRRmVHSG6PpKFHoyOkN0fWcYp3BvOoPwoRSkjdrHGg7wMGXKlBilxCgJZUqMUGKUMmUO8DB9rJmTf7gtFNJH4tbvhmU3A4X0bRcrb9049nkh/fr63en3FwpzK0N0LyisAcSvg41T2AtncAbwfLJzi96P6PrOoJNBYUZFZ4iurya6JxUyRNd3hpTCvekMMP2vYjfNBtjDAHtYwFJWcxsLWc5FdPAqw7zMIfayvSleIHXxmvTj5CAc3A7Dh+D1YbigI30LxhW3zfyLIEZnUOiF6DUAjXWwlMJeOIMzVHg+2WTR+xFd3xm0MijMqOgM0fWVKPRkdIbo+s4wTuHebOYM8odSFcc5wsPcFR0j3PwuuPYTzZ1BoRei1wA01sFSCnvhDM5Q4flkk0XvR3R9Z9DKoDCjojNE11ei0JPRGaLrO8M4hXuzGTNI//qemZmZmZmZmZnNTT6UMjMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy50PpczMzMzMzMzMLHeFJEmSPAsODw/T2dkJBbhkSZ6VU68cg6QMhSJcvDj/+s7gDGoZousDnDoKJDA0NERHR0dMCOLnE2jsR3SG6PrO4AyTKcwozydnUKnvDFoZPJ9SCnvhDM6gUl8lQ63zKe5QysxsEplDKTOzc5D4lz4zs3PwfDIzVdXmU2uOWc7kJ6WcwRkkMkTXh/FTdBn+L31N35PO4AwTSc0oz6emzxBd3xm0Mng+pRT2whmcQaW+SoZa51PYodTFl8GtR/Kv++WlcOq76cZE1HcGZ1DLEF0f4L4l6eBUETWfQGM/ojNE13cGZ5hMaUZ5PjlDdH1n0Mrg+ZRS2AtncAaV+ioZap1PfqFzMzMzMzMzMzPLnQ+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMchf37nuWycnDcHAHDA3AyAmY1w6d3bBiI8xflk+GBXSxmo0sopsLaec1TvASA+xlB8cZnPP1nUErg+nwfNLIEF3fGUyR55MzKGWIrm9aPJ+codkz+FBqlji6G/b3w+Gd6ds6AiQlKLSknz9zJ1zeA6t6YfGamcnQzRrWsoWV9JBQBqBIkfIbn/dwJ/t5iF30M8CeOVffGbQymA7PJ40M0fWdwRR5PjmDUobo+qbF88kZnIE3api0JIHn+mDnjTD4CJCkwyopvfH1yucJHH4EHnpXOtySZHpzrGULvezmKtZRpEgLrbTQSmHC50WKrORmenmcm9g8p+o7g1YG0+D5pJMhur4zmBrPJ2dQyxBd33R4PjmDM5zJh1LiDmyDJ25PP09Gp/7eytf39abXTZeb2Mwt9AHQwrwpv7fy9Q30T1ujRtd3Bq0MpsPzSSNDdH1nMEWeT86glCG6vmnxfHIGZzhTXYdSpVKJ3/md3+GKK67goosu4m1vext33XUXyXQf2xqQPtK5rzfbtft64djjjWfoZg0b6M907Qb66eaGWV3fGbQyTMXzKV+eTxoZous7Q+08o/Lj+eQMShmi69fC8yk/nk/O4Axnq+tQ6jOf+Qz33HMPn/vc5/jOd77DZz7zGf7n//yf/OEf/mHDQexs+/uhkPFVvwqt6fWNWssWSoxkurbESMOnp9H1nUErw1Q8n/Ll+aSRIbq+M9TOMyo/nk/OoJQhun4tPJ/y4/nkDM5wtroOpfbu3csHPvAB3ve+9/EDP/AD3HLLLbznPe/hySefbDiInenk4fRF76o90nk+ySi88BCcbODF8RfQxUp6qj7Cdz4tzGMV72cBS2dlfWfQylCN51N+PJ80MkTXd4b6eEblw/PJGZQyRNevledTPjyfnMEZzq2uQ6nVq1fzzW9+k3/9138F4LnnnuPv/u7vWLduXUMh7GwHd4y/C0NWhSIc3J79+tVsHHvV/awSyqzmtllZ3xm0MlTj+ZQfzyeNDNH1naE+nlH58HxyBqUM0fVr5fmUD88nZ3CGc6vr4cGPf/zjDA8Pc+WVV9LS0kKpVOJTn/oUt95663mvOX36NKdPnx776+Hh4expm8jQwPT8nOFD2a9dRPc0JEhYyPJZWd8ZtDJU4/mUH88njQzR9Z2hPvXOKM+nbDyfnEEpQ3T9Wnk+5cPzyRmc4dzqOqv9+te/zpe//GW+8pWv8A//8A986Utfoq+vjy996UvnvWbr1q10dnaOfXR1dTUUuFmMnBh/W9CskhK83sA/Iy6knWKDb9BYpIWL6JiV9Z1BK0M1nk/58XzSyBBd3xnqU++M8nzKxvPJGZQyRNevledTPjyfnMEZzvcz6nD77bfz8Y9/nJ//+Z9n5cqV/OIv/iK/9Vu/xdatW897zR133MHQ0NDYx+BgA78E20TmtUOhpbGfUWiBCxroj9c4QbnBx/nKlHiVbJMzur4zaGWoxvMpP55PGhmi6ztDfeqdUZ5P2Xg+OYNShuj6tfJ8yofnkzM4w7nV9et7r7zyCsXimedYLS0tlMvn/z/S1tZGW1tbtnRNrHM6nqQDOhp4ku4lpuMZ0wIvk+0Z0+j6zqCVoRrPp/x4PmlkiK7vDPWpd0Z5PmXj+eQMShmi69fK8ykfnk/O4AznVteTUuvXr+dTn/oUDz/8MM8//zwPPPAA27Zt44Mf/GBDIexsKzZC0tihJUkZVjTwmmN72UGhwcf5ChTZS7ZX44uu7wxaGarxfMqP55NGhuj6zlAfz6h8eD45g1KG6Pq18nzKh+eTMzjDudWV4A//8A+55ZZb+MhHPsIP/uAP0tvby3/7b/+Nu+66q6EQdrb5y2BZDxTqepZtXKEVLl8P8xv4Fe/jDHKAnZQYyXR9iRH28yDHOTIr6zuDVoZqPJ/y4/mkkSG6vjPUxzMqH55PzqCUIbp+rTyf8uH55AzOcG51HUq1t7fz2c9+lhdeeIFXX32Vf/u3f+OTn/wkF1xwQUMh7Nyu7oVkNNu1SQlWbWk8w2P00cK8TNcWaWEX22Z1fWfQyjAVz6d8eT5pZIiu7wy184zKj+eTMyhliK5fC8+n/Hg+OYMznOvnmKzFa+C6vmzXXnd3en2jBtjD/WSbft/gdgbYM6vrO4NWBtPh+aSRIbq+M5gizydnUMoQXd+0eD45gzOczYdS4lZuHh9c1R71rHz9ur70uumyi21jjVrt0b7K1+9ny7T9l53o+s6glcF0eD5pZIiu7wymyPPJGZQyRNc3LZ5PzuAMZ8r4G62Wl0IhfUxz4Tthfz+88BAU3jhKTErjbyualGHZzen3TscJ+mS72MYLPMVNbGYV7yd5460jixQpUwIKFChygIfZxbZp/6860fWdQSuDafB80skQXd8ZTI3nkzOoZYiubzo8n5zBGc7kQ6lZYvGa9OPkIBzcDsOH4PVhuKAjfVvQFbc19qJ3tRhgDwPsYQFLWc1tLGQ5F9HBqwzzMofYy/YZfSHG6PrOoJXBdHg+aWSIru8MpsjzyRmUMkTXNy2eT87gDCkfSs0y87vg2k/EZjjOER4m7t04ous7g1YG0+H5pJEhur4zmCLPJ2dQyhBd37R4PjlDs2fwa0qZmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlzodSZmZmZmZmZmaWu0KSJEmeBYeGhnjTm94EwMWL86yceuVFIAEKcPFl+dd3BmdQyxBdH+CVY+n/fu9736OzszMmBPHzCUT2wz3pDM5wZgaBGeX55Awq9Z1BLIPnEyCyF87gDCL1ZTLUOJ9yP5Q6cuQIXV0z/N6WZjYrDQ4OsnTp0rD6nk9mNpXIGeX5ZGZT8XwyM1XV5lPuh1LlcpmjR4/S3t5OoVCo+/rh4WG6uroYHByko6NjBhI6w2zJEF3fGaYvQ5IknDhxgiVLllAsxv1WseeTM8ylDNH151IGhRnV6HyC+P2Iru8MzqCWwfNpXPReKGSIru8MzjDdGWqdT62NhMyiWCxOyyl+R0dH2OY4g1aG6PrOMD0ZIn9tr8LzyRnmYobo+nMlQ/SMmq75BPH7EV3fGZxBLYPn07jovVDIEF3fGZxhOjPUMp/8QudmZmZmZmZmZpY7H0qZmZmZmZmZmVnuZt2hVFtbG7/7u79LW1ubMzR5huj6zqCVQYHCOjiDM6jUdwY90WsRXd8ZnEEtQ3R9JQprEZ0hur4zOENUhtxf6NzMzMzMzMzMzGzWPSllZmZmZmZmZmaznw+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMcjerDqX+/u//npaWFt73vvflXnvjxo0UCoWxj0svvZT3vve97N+/P/csL774Ih/96Ed561vfSltbG11dXaxfv55vfvObM1574jrMmzeP7/u+72Pt2rV88YtfpFwuz3j9yRkmfrz3ve/NpX61HIcOHcql/osvvsjHPvYxli9fzoUXXsj3fd/3cf3113PPPffwyiuvzHj9jRs38tM//dNn/f1vf/vbFAoFvve97814BjWeUZ5Pk3NEzajo+QSxM8rz6WyeT55Pk3N4PvnPUCo8nzyfJufwfGqu+TSrDqXuvfdePvrRj/L4449z9OjR3Ou/973v5dixYxw7doxvfvObtLa20tPTk2uG559/nmuvvZa//du/5e677+bAgQM8+uijvPvd72bTpk25ZKisw/PPP88jjzzCu9/9bj72sY/R09PD6Ohorhkmfvz5n/95LrWr5bjiiitmvO6///u/c8011/A3f/M3fPrTn+b//J//w9///d/z3//7f2fnzp3s2rVrxjPY2Zp9Rnk+nZ0jckZFzSfwjFLk+eT5NDmH55PnkwrPJ8+nyTk8n5prPrVGB6jVyZMn+drXvsbTTz/Niy++yI4dO/gf/+N/5Jqhra2Nyy67DIDLLruMj3/849xwww28/PLLLFy4MJcMH/nIRygUCjz55JNccsklY3//h3/4h/nlX/7lXDJMXIfv//7v50d+5Ee47rrr+Mmf/El27NjBf/kv/yXXDJGicnzkIx+htbWVp59++ow+eOtb38oHPvABkiTJPVOz84zyfDpfjiiRGTyjtHg+eT6dL0cUzyer8HzyfDpfjiieT/mbNU9Kff3rX+fKK69kxYoVfOhDH+KLX/xi6KacPHmS++67j+XLl3PppZfmUvP//b//x6OPPsqmTZvOaNKKN73pTbnkOJef+Imf4Oqrr+Yv/uIvwjI0i//7f/8vf/M3f3PePgAoFAo5p7Jmn1GeT1bhGaXH88nzyVKeT3o8nzyfLNXM82nWHErde++9fOhDHwLSR+qGhobYvXt3rhl27tzJ/PnzmT9/Pu3t7Tz44IN87Wtfo1jMZxkPHTpEkiRceeWVudSr15VXXsnzzz+fS62Je1H5+PSnP51L7alybNiwYcZrVvpgxYoVZ/z9t7zlLWM5fvu3f3vGc8C592HdunW51FbT7DPK8+lMCjMqYj6BzozyfBrn+eT5NJHnU/x8As+oCs8nz6eJPJ+acz7Nil/fO3jwIE8++SQPPPAAAK2trfzcz/0c9957LzfeeGNuOd797ndzzz33AHD8+HH+6I/+iHXr1vHkk09y+eWXz3h99cf1kiTJ7fR24l5UvPnNb86l9lQ5zneqnYcnn3yScrnMrbfeyunTp3Opea59eOKJJ8b+cNEsPKM8nyZTmFFK8wnyn1GeTynPJ8+nyTyfzuY/Q8XwfPJ8mszz6WzNMJ9mxaHUvffey+joKEuWLBn7e0mS0NbWxuc+9zk6OztzyXHJJZewfPnysb/+0z/9Uzo7O/nCF77AJz/5yRmv393dTaFQ4F/+5V9mvFYW3/nOd3J7EbjJexElIsfy5cspFAocPHjwjL//1re+FYCLLrootyzn+v9/5MiR3Oqr8IzyfJpMYUZFZVCZUZ5PKc8nz6fJPJ/i5xN4RoHnE3g+Teb51JzzSf7X90ZHR/mzP/sz+vv7efbZZ8c+nnvuOZYsWRLyjmsVhUKBYrHIq6++mku9N7/5zfzUT/0Un//85zl16tRZX498+9i//du/5cCBA/zMz/xMWIZmcemll7J27Vo+97nPnbMPLF+eUSnPJ6vwjNLh+ZTyfLIKzycdnk8pzyeraOb5JP+k1M6dOzl+/Di/8iu/ctZp+c/8zM9w77338qu/+qu5ZDl9+jQvvvgikD7a+bnPfY6TJ0+yfv36XOoDfP7zn+f666/nR3/0R/n93/99Vq1axejoKI899hj33HMP3/nOd2Y8Q2UdSqUS//mf/8mjjz7K1q1b6enp4Zd+6ZdmvP7EDBO1trbylre8JZf60f7oj/6I66+/nne84x3ceeedrFq1imKxyFNPPcW//Mu/cO2110ZHbBqeUeM8n87OMZFnlGdU3jyfxnk+nZ1jIs8nz6e8eT6N83w6O8dEnk9NMJ8ScT09PcnNN998zq898cQTCZA899xzM57jwx/+cAKMfbS3tyfvfOc7k2984xszXnuyo0ePJps2bUouv/zy5IILLki+//u/P3n/+9+ffOtb35rx2hPXobW1NVm4cGFy0003JV/84heTUqk04/UnZ5j4sWLFilzqT8zxgQ98INeaEx09ejT59V//9eSKK65I5s2bl8yfPz/50R/90eTuu+9OTp06NeP1z/f//1vf+lYCJMePH5/xDAo8o87U7PNpco6oGRU9n5IkdkZ5PqU8n87k+eT5VOE/Q8XzfDqT55PnU0UzzqdCkoi/upqZmZmZmZmZmc058q8pZWZmZmZmZmZmc48PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHLnQykzMzMzMzMzM8udD6XMzMzMzMzMzCx3PpQyMzMzMzMzM7Pc+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHLXmnfBcrnM0aNHaW9vp1Ao5F3ezAQlScKJEydYsmQJxWLcWbnnk5mdi8KM8nwys3PxfDIzVbXOp9wPpY4ePUpXV1feZc1sFhgcHGTp0qVh9T2fzGwqkTPK88nMpuL5ZGaqqs2n3A+l2tvbxz6/eHHe1eGVF4EEKMDFl+Vf3xmcQS1DdH2AV46l/ztxPkSInk8gsh/uSWdwhjMzCMwozydnUKnvDGIZPJ8Akb1wBmcQqS+Tocb5lPuhVOWRzosXw4eO5l0dvrwUTn0XLlkCtx7Jv74zOINahuj6APctSYdW9CPf0fMJNPYjOkN0fWdwhskUZpTnkzOo1HcGrQyeTymFvXAGZ1Cpr5Kh1vnkFzo3MzMzMzMzM7Pc+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsd7m/0HlWC+hiNRtZRDcX0s5rnOAlBtjLDo4z6Aw5Zjh5GA7ugKEBGDkB89qhsxtWbIT5y+Z+fbPJFO5LZ0gpzAeFDGYTRd+b0fVVMijMBmcwNQr3ZnSG6PqgcV86g468e1L+UKqbNaxlCyvpIaEMQJEi5Tc+7+FO9vMQu+hngD3OMIMZju6G/f1weCcU3njGLilBoSX9/Jk74fIeWNULi9fMvfpmkyncl86QUpgPChnMJoq+N6Prq2RQmA3OYGoU7s3oDNH1QeO+dAYdUT0p/et7a9lCL7u5inUUKdJCKy20UpjweZEiK7mZXh7nJjY7wwxkSBJ4rg923giDjwBJepMmpTe+Xvk8gcOPwEPvSm/qJJkb9c3OJfq+dIaUwnxQyGA2WfS9GV1fIYPCbHAGUxR9bypkiK6vcF86g5bInpQ9lLqJzdxCHwAtzJvyeytf30D/tC6OM6QObIMnbk8/T0an/t7K1/f1ptfNhfpmkyncl86QUpgPChnMJoq+N6Prq2RQmA3OYGoU7s3oDNH1QeO+dAYd0T0peSjVzRo20J/p2g30080NzjBNGY7uTm+8LPb1wrHHZ3d9s8kU7ktnSCnMB4UMZhNF35vR9VUyKMwGZzA1CvdmdIbo+qBxXzqDDoWerPtQ6vHHH2f9+vUsWbKEQqHAX/7lXzYcYrK1bKHESKZrS4xMy4mdM6T290Mh4yuPFVrT62dzfZtdPJ+aK4PCfFDIYLNDHvMJ4u/N6PoqGRRmgzNYrZplPilkiK4PGvelM+hQ6Mm6D6VOnTrF1Vdfzec///mGi5/LArpYSU/Vx8bOp4V5rOL9LGCpMzSY4eTh9MXeqj3KeD7JKLzwEJzM+AL90fVt9vF8ap4MCvNBIYPNHjM9nyD+3oyur5JBYTY4g9WjGeaTQobo+qBxXzqDDoWehAyHUuvWreOTn/wkH/zgBxsqfD6r2Tj2Su9ZJZRZzW3O0GCGgzvG330gq0IRDm6fnfVt9vF8ap4MCvNBIYPNHjM9nyD+3oyur5JBYTY4g9WjGeaTQobo+qBxXzqDDoWeBMj4wFrtTp8+zenTp8f+enh4eMrvX0T3NFRNWMjyzFc7Q2poYBoiAMOHZmd9m/s8n2ZvBoX5oJDB5q565xPE35vR9VUyKMwGZ7CZNBvnk0KG6PqgcV86gw6FnoQcXuh869atdHZ2jn10dXVN+f0X0k6xwVhFWriIjszXO0Nq5MT422FmlZTg9er/nJKsb3Of59PszaAwHxQy2NxV73yC+Hszur5KBoXZ4Aw2k2bjfFLIEF0fNO5LZ9Ch0JPpz5hhd9xxB0NDQ2Mfg4NT/+Lla5yg3OAjZGVKvEr2DnGG1Lx2KLQ0FIFCC1yQsUej69vc5/k0ezMozAeFDDZ31TufIP7ejK6vkkFhNjiDzaTZOJ8UMkTXB4370hl0KPQk5PDre21tbbS1tdX8/S8xHc/SFXiZ7M/SOUOqczqe5gM6Mj7NF13f5j7Pp9mbQWE+KGSwuave+QTx92Z0fZUMCrPBGWwmzcb5pJAhuj5o3JfOoEOhJyGHJ6XqtZcdFBqMVaDIXrK/6pgzpFZshKSxg1OSMqzI+Lpn0fXNJlO4L50hpTAfFDKYTRR9b0bXV8mgMBucwdQo3JvRGaLrg8Z96Qw6FHoSMhxKnTx5kmeffZZnn30WgP/4j//g2Wef5fDhww0FqTjOIAfYSYmRTNeXGGE/D3KcI87QYIb5y2BZDxQyPk9XaIXL18P86r9mLlnfZh/Pp+bJoDAfFDLY7DHT8wni783o+ioZFGaDM1g9mmE+KWSIrg8a96Uz6FDoSchwKPX0009zzTXXcM011wCwefNmrrnmGj7xiU80FGSix+ijhXmZri3Swi62OcM0Zbi6F5LRbNcmJVi1ZXbXt9nF86m5MijMB4UMNjvkMZ8g/t6Mrq+SQWE2OIPVqlnmk0KG6PqgcV86gw6Fnqz7UOrGG28kSZKzPnbs2NFwmIoB9nA/2Xb5G9zOAHucYZoyLF4D1/Vlu/a6u9PrZ3N9m108n5org8J8UMhgs0Me8wni783o+ioZFGaDM1itmmU+KWSIrg8a96Uz6FDoSbnXlKrYxbaxxan2OFnl6/ezZVpO6pzhTCs3j9+w1R5xrHz9ur70urlQ32wyhfvSGVIK80Ehg9lE0fdmdH2VDAqzwRlMjcK9GZ0huj5o3JfOoCO6J2UPpSBdnD7WcICHKVOmxCglRkkoU2KEEqOUKXOAh+ljzbTeqM4wrlBIH09cvxuW3QwU0rfArLyN5tjnhfTr63en318ozI36ZucSfV86Q0phPihkMJss+t6Mrq+QQWE2OIMpir43FTJE11e4L51BS2RPZnxpr/wMsIcB9rCApazmNhaynIvo4FWGeZlD7GV7wy+s5Qy1Wbwm/Tg5CAe3w/AheH0YLuhI3w5zxW0z+2Jv0fXNJlO4L50hpTAfFDKYTRR9b0bXV8mgMBucwdQo3JvRGaLrg8Z96Qw6onpS/lCq4jhHeJi7nEEgw/wuuHZ6X/dwVtU3m0zhvnSGlMJ8UMhgNlH0vRldXyWDwmxwBlOjcG9GZ4iuDxr3pTPoyLsnpX99z8zMzMzMzMzM5iYfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeWukCRJkmfB4eFhOjs7oQCXLMmzcuqVY5CUoVCEixfnX98ZnEEtQ3R9gFNHgQSGhobo6OiICUH8fAKN/YjOEF3fGZxhMoUZ5fnkDCr1nUErg+dTSmEvnMEZVOqrZKh1PsUdSpmZTSJzKGVmdg4S/9JnZnYOnk9mpqrafGrNMcuZ/KSUMziDRIbo+jB+ii7D/6Wv6XvSGZxhIqkZ5fnU9Bmi6zuDVgbPp5TCXjiDM6jUV8lQ63wKO5S6+DK49Uj+db+8FE59N92YiPrO4AxqGaLrA9y3JB2cKqLmE2jsR3SG6PrO4AyTKc0ozydniK7vDFoZPJ9SCnvhDM6gUl8lQ63zyS90bmZmZmZmZmZmufOhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrkLe/e9ei2gi9VsZBHdXEg7r3GClxhgLzs4zqAz5Jjh5GE4uAOGBmDkBMxrh85uWLER5i/LJUI4hTVwBh0K96UzOEOFwn3pDFqiezK6vjOMU7gvnCG+vhKF+yI6Q3R9lQwK94VCBoW9yDuD/KFUN2tYyxZW0kNCGYAiRcpvfN7DneznIXbRzwB7nGEGMxzdDfv74fBOKLzxjF1SgkJL+vkzd8LlPbCqFxavmZEI4RTWwBl0KNyXzuAMFQr3pTNoie7J6PrOME7hvnCG+PpKFO6L6AzR9VUyKNwXChkU9iIqg/Sv761lC73s5irWUaRIC6200EphwudFiqzkZnp5nJvY7AwzkCFJ4Lk+2HkjDD4CJOlNmpTe+Hrl8wQOPwIPvSu9qZNkWmOEUlgDZ9ASfV86gzNUKNyXzqAn+r6Iru8MKYX7whni66uJvi8UMkTXV8igcF8oZID4vYjOIHsodRObuYU+AFqYN+X3Vr6+gf5pXRxnSB3YBk/cnn6ejE79vZWv7+tNr5srFNbAGXQo3JfO4AwVCvelM2iJ7sno+s4wTuG+cIb4+koU7ovoDNH1VTIo3BcKGRT2IjpDXYdSW7du5Z3vfCft7e0sWrSIn/7pn+bgwYPTEmSibtawgf5M126gn25ucIZpynB0d3rjZbGvF4493nCEcApr4AzVeT45QzNmULgvnaE2zTKjous7wziF+8IZ4uvXolnmk0KG6PoqGRTuC4UMCnuhkKGuQ6ndu3ezadMm9u3bx2OPPcbIyAjvec97OHXqVMNBJlrLFkqMZLq2xMi0nNg5Q2p/PxQyvvJYoTW9frZTWANnqM7zyRmaMYPCfekMtWmWGRVd3xnGKdwXzhBfvxbNMp8UMkTXV8mgcF8oZFDYC4UMdW3Do48+esZf79ixg0WLFvHMM8+wZs30vOLXArpYSQ/FjL9Z2MI8VvF+FrCU4xxxhgYynDycvtgbGX9nNhmFFx6Ck4Mwvyvbz4imsAbOUBvPJ2dotgwK96Uz1K4ZZlR0fWcYp3BfOEN8/Vo1w3xSyBBdXyWDwn2hkEFhLxQyQIOvKTU0NATAm9/85kZ+zBlWs3Hsld6zSiizmtucocEMB3eMv/tAVoUiHNze2M+IpLAGzpCN55MzzPUMCvelM2Q3F2dUdH1nGKdwXzhDfP2s5uJ8UsgQXV8lg8J9oZBBYS8UMkCdT0pNVC6X+c3f/E2uv/56rrrqqvN+3+nTpzl9+vTYXw8PD0/5cxfRnTXSBAkLWZ75amdIDQ1MQwRg+ND0/JwICmvgDPXzfHKGZsigcF86Qza1zKh65xPE92R0fWcYp3BfOEN8/Szm6nxSyBBdXyWDwn2hkEFhLxQyQANPSm3atIl//Md/5Ktf/eqU37d161Y6OzvHPrq6pn6+7ULaMz8+VlGkhYvoyHy9M6RGToy/HWZWSQler/7PKVkKa+AM9fN8coZmyKBwXzpDNrXMqHrnE8T3ZHR9ZxincF84Q3z9LObqfFLIEF1fJYPCfaGQQWEvFDKkPyODX//1X2fnzp1861vfYunSpVN+7x133MHQ0NDYx+Dg4JTf/xonKDf4CFmZEq+SvUOcITWvHQotDUWg0AIXNNajoRTWwBnq4/nkDM2SQeG+dIb61Tqj6p1PEN+T0fWdYZzCfeEM8fXrNZfnk0KG6PoqGRTuC4UMCnuhkAHq/PW9JEn46Ec/ygMPPMC3v/1trrjiiqrXtLW10dbWVnONl5iOZ+kKvEz2Z+mcIdU5HU/zAR2NPc0XSmENnKE2nk/O0GwZFO5LZ6hdvTOq3vkE8T0ZXd8ZxincF84QX79WzTCfFDJE11fJoHBfKGRQ2AuFDFDnk1KbNm3ivvvu4ytf+Qrt7e28+OKLvPjii7z66qsNhZhoLzsoNPgIWYEie8n+qmPOkFqxEZLGDk5JyrCisdc9C6WwBs5QG88nZ2i2DAr3pTPUrhlmVHR9ZxincF84Q3z9WjXDfFLIEF1fJYPCfaGQQWEvFDJAnYdS99xzD0NDQ9x4440sXrx47ONrX/taQyEmOs4gB9hJiZFM15cYYT8PNvSWhM6Qmr8MlvVAIePL4Rda4fL1M/sWtjNNYQ2coTaeT87QbBkU7ktnqF0zzKjo+s4wTuG+cIb4+rVqhvmkkCG6vkoGhftCIYPCXihkgDoPpZIkOefHxo0bGwox2WP00cK8TNcWaWEX25xhmjJc3QvJaLZrkxKs2tJwhHAKa+AMNdTwfHKGJsygcF86Q411mmRGRdd3hnEK94UzxNevqU6TzCeFDNH1VTIo3BcKGRT2QiFDY89qzZAB9nA/2Xb5G9zOAHucYZoyLF4D1/Vlu/a6u9PrZzuFNXAGHQr3pTM4Q4XCfekMWqJ7Mrq+M4xTuC+cIb6+EoX7IjpDdH2VDAr3hUIGhb1QyCB5KAWwi21ji1PtcbLK1+9ny7Sc1DnDmVZuHr9hqz3iWPn6dX3pdXOFwho4gw6F+9IZnKFC4b50Bi3RPRld3xnGKdwXzhBfX4nCfRGdIbq+SgaF+0Ihg8JeRGeQPZSCdHH6WMMBHqZMmRKjlBgloUyJEUqMUqbMAR6mjzXTujHOMK5QSB9PXL8blt0MFNK3wKy8jebY54X06+t3p99fKExrjFAKa+AMWqLvS2dwhgqF+9IZ9ETfF9H1nSGlcF84Q3x9NdH3hUKG6PoKGRTuC4UMEL8X0RkyvrRXfgbYwwB7WMBSVnMbC1nORXTwKsO8zCH2sr3hF9ZyhtosXpN+nByEg9th+BC8PgwXdKRvh7nittn9oua1UFgDZ9ChcF86gzNUKNyXzqAluiej6zvDOIX7whni6ytRuC+iM0TXV8mgcF8oZFDYi6gM8odSFcc5wsPc5QwCGeZ3wbWfCI0QTmENnEGHwn3pDM5QoXBfOoOW6J6Mru8M4xTuC2eIr69E4b6IzhBdXyWDwn2hkEFhL/LOIP3re2ZmZmZmZmZmNjf5UMrMzMzMzMzMzHLnQykzMzMzMzMzM8udD6XMzMzMzMzMzCx3hSRJkjwLDg8P09nZCQW4ZEmelVOvHIOkDIUiXLw4//rO4AxqGaLrA5w6CiQwNDRER0dHTAji5xNo7Ed0huj6zuAMkynMKM8nZ1Cp7wxaGTyfUgp74QzOoFJfJUOt8ynuUMrMbBKZQykzs3OQ+Jc+M7Nz8HwyM1XV5lNrjlnO5CelnMEZJDJE14fxU3QZ/i99Td+TzuAME0nNKM+nps8QXd8ZtDJ4PqUU9sIZnEGlvkqGWudT2KHUxZfBrUfyr/vlpXDqu+nGRNR3BmdQyxBdH+C+JengVBE1n0BjP6IzRNd3BmeYTGlGeT45Q3R9Z9DK4PmUUtgLZ3AGlfoqGWqdT36hczMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHIX9+57dVpAF6vZyCK6uZB2XuMELzHAXnZwnMFcMpw8DAd3wNAAjJyAee3Q2Q0rNsL8ZblEkMgQvRfR9UFjH5xBh3tSJ4PCXkRniK4PGr2gkEFFdE8o7IUzpKJ7QSVD9F5E11fifoivr5JBoRcUMjTjXsgfSnWzhrVsYSU9JJQBKFKk/MbnPdzJfh5iF/0MsGdGMhzdDfv74fDO9C0VAZISFFrSz5+5Ey7vgVW9sHjNjESQyBC9F9H1QWMfnEGHe1Ing8JeRGeIrg8avaCQQUV0TyjshTOkontBJUP0XkTXV+J+iK+vkkGhFxQyNPNeSP/63lq20MturmIdRYq00EoLrRQmfF6kyEpuppfHuYnN01o/SeC5Pth5Iww+AiRpYySlN75e+TyBw4/AQ+9KGylJ5lYGiN+L6PoK++AMWtyTGhkgfi8UMkTXV+gFhQxKIntCYS+cYVz0fFDIEL0X0fXVuB/i+0EhA8T3gkIG74XwodRNbOYW+gBoYd6U31v5+gb6p3VxDmyDJ25PP09Gp/7eytf39abXzaUM0XsRXR809sEZdLgndTIo7EV0huj6oNELChlURPeEwl44Qyq6F1QyRO9FdH0l7of4+ioZFHpBIYP3QvRQqps1bKA/07Ub6KebGxrOcHR3utlZ7OuFY483HEEiQ/ReRNcHjX1wBh3uSZ0MCnsRnSG6Pmj0gkIGFdE9obAXzpCK7gWVDNF7EV1fifshvr5KBoVeUMjgvUjVdSh1zz33sGrVKjo6Oujo6ODHf/zHeeSRRxoOMdlatlBiJNO1JUam5cRufz8UMr7iVqE1vX4uZIjei+j6oLEPzlCd51Nt5lI/KOxFdIbo+qDRCwoZqmmWGaWwF86Qiu4FlQzRexFdvxbNMp8gfj+i66tkUOgFhQzei1Rdh1JLly7lD/7gD3jmmWd4+umn+Ymf+Ak+8IEP8E//9E8NB6lYQBcr6an62Nj5tDCPVbyfBSzNnOHk4fQFxqo9Pnc+ySi88BCcbOCF6RUyRO9FdH3Q2AdnqI3nU23mSj8o7EV0huj6oNELChlq0QwzSmEvnCEV3QsqGaL3Irp+rZphPkH8fkTXV8mg0AsKGbwX4+o6lFq/fj0333wz3d3dvP3tb+dTn/oU8+fPZ9++fQ2FmGg1G8de6T2rhDKruS3z9Qd3jL/ifVaFIhzcnv16hQzRexFdHzT2wRlq4/lUu7nQDwp7EZ0huj5o9IJChlo0w4xS2AtnSEX3gkqG6L2Irl+rZphPEL8f0fVVMij0gkIG78W4jA+LQalU4v777+fUqVP8+I//+Hm/7/Tp05w+fXrsr4eHh6f8uYvozhppgoSFLM989dDANEQAhg9lv1YhQ/ReRNcHjX1whvp5PlU32/tBYS+iM0TXB41eUMhQr1pmVL3zCeJ7QmEvnCEV3QsqGaL3Irp+FnN1PkH8fkTXV8mg0AsKGbwX4+o+mztw4ADz58+nra2NX/3VX+WBBx7gh37oh877/Vu3bqWzs3Pso6ura8qffyHtFBt8/fUiLVxER+brR06MvwVjVkkJXq8+n6UzRO9FdH3Q2AdnqJ3nU23mQj8o7EV0huj6oNELChlqVc+Mqnc+QXxPKOyFM6Sie0ElQ/ReRNevx1yfTxC/H9H1VTIo9IJCBu/FxJ9RpxUrVvDss8/yxBNP8Gu/9mt8+MMf5p//+Z/P+/133HEHQ0NDYx+Dg1P/0uNrnKDc4CNkZUq8SvbdmdcOhZaGIlBogQsa2BuFDNF7EV0fNPbBGWrn+VSbudAPCnsRnSG6Pmj0gkKGWtUzo+qdTxDfEwp74Qyp6F5QyRC9F9H16zHX5xPE70d0fZUMCr2gkMF7Ma7uX9+74IILWL48fTzr2muv5amnnuJ//a//xR//8R+f8/vb2tpoa2ur+ee/xHQ8x1bgZbI/x9Y5HU+xAR0NPMWmkCF6L6Lrg8Y+OEPtPJ9qN9v7QWEvojNE1weNXlDIUKt6ZlS98wnie0JhL5whFd0LKhmi9yK6fj3m+nyC+P2Irq+SQaEXFDJ4L8Y1+NJaUC6Xz/id4kbtZQeFBmMVKLKX7K/4tWIjJI0dGJKUYUUDr/elkCF6L6Lrg8Y+OEN2nk/nNhf6QWEvojNE1weNXlDIkNVcm1EKe+EMqeheUMkQvRfR9Rsx1+YTxO9HdH2VDAq9oJDBezGurgR33HEHjz/+OM8//zwHDhzgjjvu4Nvf/ja33nprQyEmOs4gB9hJiZFM15cYYT8PcpwjmTPMXwbLeqCQ8WXgC61w+XqYX/3Xq6UzRO9FdH3Q2AdnqI3nU23mSj8o7EV0huj6oNELChlq0QwzSmEvnCEV3QsqGaL3Irp+rZphPkH8fkTXV8mg0AsKGbwX4+o6lHrppZf4pV/6JVasWMFP/uRP8tRTT/HXf/3XrF27tqEQkz1GHy3My3RtkRZ2sa3hDFf3QjKa7dqkBKu2NBxBIkP0XkTXB419cIbqPJ9qM5f6QWEvojNE1weNXlDIUE2zzCiFvXCGVHQvqGSI3ovo+rVolvkE8fsRXV8lg0IvKGTwXlR+Th3uvfdenn/+eU6fPs1LL73Erl27pn1YAQywh/vJtsLf4HYG2NNwhsVr4Lq+bNded3d6/VzIEL0X0fVBYx+coTrPp9rMpX5Q2IvoDNH1QaMXFDJU0ywzSmEvnCEV3QsqGaL3Irp+LZplPkH8fkTXV8mg0AsKGbwXqYZfU2qm7GLb2OJUe5ys8vX72TItJ3UVKzePN0m1x+oqX7+uL71uLmWI3ovo+qCxD86gwz2pk0FhL6IzRNcHjV5QyKAiuicU9sIZUtG9oJIhei+i6ytxP8TXV8mg0AsKGbwXwodSkC5OH2s4wMOUKVNilBKjJJQpMUKJUcqUOcDD9LFmWpsDoFBIH4lbvxuW3QwU0rddrLx149jnhfTr63en318ozK0MEL8X0fUV9sEZtLgnNTJA/F4oZIiur9ALChmURPaEwl44w7jo+aCQIXovouurcT/E94NCBojvBYUM3gvI+LJa+RlgDwPsYQFLWc1tLGQ5F9HBqwzzMofYy/aGX1irmsVr0o+Tg3BwOwwfgteH4YKO9C0YV9w28y9AqJAhei+i64PGPjiDDvekTgaFvYjOEF0fNHpBIYOK6J5Q2AtnSEX3gkqG6L2Irq/E/RBfXyWDQi8oZGjmvZA/lKo4zhEe5q7QDPO74NpPhEaQyBC9F9H1QWMfnEGHe1Ing8JeRGeIrg8avaCQQUV0TyjshTOkontBJUP0XkTXV+J+iK+vkkGhFxQyNONeSP/6npmZmZmZmZmZzU0+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHLnQykzMzMzMzMzM8tdIUmSJM+Cw8PDdHZ2QgEuWZJn5dQrxyApQ6EIFy/Ov74zOINahuj6AKeOAgkMDQ3R0dERE4L4+QQa+xGdIbq+MzjDZAozyvPJGVTqO4NWBs+nlMJeOIMzqNRXyVDrfIo7lDIzm0TmUMrM7Bwk/qXPzOwcPJ/MTFW1+dSaY5Yz+UkpZ3AGiQzR9WH8FF2G/0tf0/ekMzjDRFIzyvOp6TNE13cGrQyeTymFvXAGZ1Cpr5Kh1vkUdih18WVw65H86355KZz6broxEfWdwRnUMkTXB7hvSTo4VUTNJ9DYj+gM0fWdwRkmU5pRnk/OEF3fGbQyeD6lFPbCGZxBpb5Khlrnk1/o3MzMzMzMzMzMcudDKTMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHIX9u579VpAF6vZyCK6uZB2XuMELzHAXnZwnMFcMpw8DAd3wNAAjJyAee3Q2Q0rNsL8ZblEkMgQvRfR9cH7UKGwDgq8FzoZFPYiOoP3IaWwDiqi90NhLxQyRO+DSgbvhcYaqIjeC4jfj+j6oLEPChm8FzEZ5A+lulnDWrawkh4SygAUKVJ+4/Me7mQ/D7GLfgbYMyMZju6G/f1weCcU3ni2LClBoSX9/Jk74fIeWNULi9fMSASJDNF7EV0fvA8VCuugwHuhk0FhL6IzeB9SCuugIno/FPZCIUP0Pqhk8F5orIGK6L2A+P2Irg8a+6CQwXsRm0H61/fWsoVednMV6yhSpIVWWmilMOHzIkVWcjO9PM5NbJ7W+kkCz/XBzhth8BEgSZszKb3x9crnCRx+BB56V9rMSTK3MkD8XkTX9z6kVNZBgfdCIwPE70V0Bu9DSmUdVDR7TypkgPj7QiGD90JnDVQ0e09G16+I3geFDN4LjQyyh1I3sZlb6AOghXlTfm/l6xvon9bFObANnrg9/TwZnfp7K1/f15teN5cyRO9FdH3wPlQorIMC74VOBoW9iM7gfUgprIOK6P1Q2AuFDNH7oJLBe6GxBiqi9wLi9yO6Pmjsg0IG74VGhoYOpf7gD/6AQqHAb/7mb05LmIpu1rCB/kzXbqCfbm5oOMPR3WnDZbGvF4493nAEiQzRexFdH7wPFQrrUA/Pp3PzfEpN115EZ/A+pBTWoR4zNZ8gfj8U9kIhQ/Q+qGTwXmisQb38Z6hzm479iK4PGvugkMF7oZMh86HUU089xR//8R+zatWqhkNMtpYtlBjJdG2JkWk5sdvfD4WMr7hVaE2vnwsZovciuj54HyoU1qFWnk/n5/mUmq69iM7gfUgprEOtZnI+Qfx+KOyFQobofVDJ4L3QWIN6+M9Q5zcd+xFdHzT2QSGD90InQ6ZDqZMnT3LrrbfyhS98gQULFjQcYqIFdLGSnqqPjZ1PC/NYxftZwNLMGU4eTl/krNojfOeTjMILD8HJBl6YXiFD9F5E1wfvQ4XCOtTK82lqnk+p6diL6Azeh5TCOtRqJucTxO+Hwl4oZIjeB5UM3guNNaiH/ww1tUb3I7o+aOyDQgbvhU4GyHgotWnTJt73vvdx0003NVT8XFazceyV3rNKKLOa2zJff3DH+KvuZ1UowsHt2a9XyBC9F9H1wftQobAOtfJ8qs7zKdXoXkRn8D6kFNahVjM5nyB+PxT2QiFD9D6oZPBeaKxBPfxnqOoa2Y/o+qCxDwoZvBc6GQDqfmDtq1/9Kv/wD//AU089VdP3nz59mtOnT4/99fDw8JTfv4jueiOdQ8JClme+emhgGiIAw4eyX6uQIXovouuD96FCYR1q4flUO88naHQvojN4H1IK61CLmZ5PEL8fCnuhkCF6H1QyeC801qBW9cyo2TifIH4/ouuDxj4oZPBe6GSAOp+UGhwc5GMf+xhf/vKXufDCC2u6ZuvWrXR2do59dHV1Tfn9F9JOscE3BSzSwkV0ZL5+5MT420BmlZTg9erzWTpD9F5E1wfvQ4XCOlTj+VQ7z6dUo3sRncH7kFJYh2rymE8Qvx8Ke6GQIXofVDJ4LzTWoBb1zqjZOJ8gfj+i64PGPihk8F7oZEh/Rh2eeeYZXnrpJX7kR36E1tZWWltb2b17N//f//f/0draSql09s7ecccdDA0NjX0MDk79i5evcYJyg4+QlSnxKtk7ZF47FFoaikChBS5oYG8UMkTvRXR98D5UKKxDNZ5PtfN8SjW6F9EZvA8phXWoJo/5BPH7obAXChmi90Elg/dCYw1qUe+Mmo3zCeL3I7o+aOyDQgbvhU4GqPPX937yJ3+SAwcOnPH3brvtNq688kp++7d/m5aWs3e2ra2Ntra2mmu8xHQ8S1fgZbI/S9c5HU+xAR0NPMWmkCF6L6Lrg/ehQmEdqvF8qo/nEzS6F9EZvA8phXWoJo/5BPH7obAXChmi90Elg/dCYw1qUe+Mmo3zCeL3I7o+aOyDQgbvhU4GqPNJqfb2dq666qozPi655BIuvfRSrrrqqoaCVOxlB4UGHyErUGQv2V91bMVGSBo7MCQpw4oGXu9LIUP0XkTXB+9DhcI6VOP5VDvPp1SjexGdwfuQUliHavKYTxC/Hwp7oZAheh9UMngvNNagFv4zVO0a2Y/o+qCxDwoZvBc6GSDju+/NpOMMcoCdlBjJdH2JEfbzIMc5kjnD/GWwrAcKdb8MfKrQCpevh/nVf71aOkP0XkTXB+9DhcI6KPBe6GRQ2IvoDN6HlMI6qIjeD4W9UMgQvQ8qGbwXGmugInovIH4/ouuDxj4oZPBe6GSAaTiU+va3v81nP/vZRn/MGR6jjxbmZbq2SAu72NZwhqt7IRnNdm1SglVbGo4gkSF6L6Lrg/ehQmEd6uX5dDbPp9R07UV0Bu9DSmEd6jUT8wni90NhLxQyRO+DSgbvhcYaZOE/Q51tOvYjuj5o7INCBu+FTga5J6UABtjD/WTb5W9wOwPsaTjD4jVwXV+2a6+7O71+LmSI3ovo+uB9qFBYBwXeC50MCnsRncH7kFJYBxXR+6GwFwoZovdBJYP3QmMNVETvBcTvR3R90NgHhQzeC50MkodSALvYNrY41R4nq3z9frZMy0ldxcrN441a7dG+ytev60uvm0sZovciuj54HyoU1kGB90Ing8JeRGfwPqQU1kFF9H4o7IVChuh9UMngvdBYAxXRewHx+xFdHzT2QSGD90Ijg+yhFKSL08caDvAwZcqUGKXEKAllSoxQYpQyZQ7wMH2smdaNASgU0sfy1u+GZTcDhfStHytvHzn2eSH9+vrd6fcXCnMrA8TvRXR970NKZR0UeC80MkD8XkRn8D6kVNZBRbP3pEIGiL8vFDJ4L3TWQEWz92R0/YrofVDI4L3QyJDxpb3yM8AeBtjDApaymttYyHIuooNXGeZlDrGX7Q2/sFY1i9ekHycH4eB2GD4Erw/DBR3p20CuuG3mX4BQIUP0XkTXB+9DhcI6KPBe6GRQ2IvoDN6HlMI6qIjeD4W9UMgQvQ8qGbwXGmugInovIH4/ouuDxj4oZPBexGaQP5SqOM4RHuau0Azzu+DaT4RGkMgQvRfR9cH7UKGwDgq8FzoZFPYiOoP3IaWwDiqi90NhLxQyRO+DSgbvhcYaqIjeC4jfj+j6oLEPChm8FzEZpH99z8zMzMzMzMzM5iYfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeWukCRJkmfB4eFhOjs7oQCXLMmzcuqVY5CUoVCEixfnX98ZnEEtQ3R9gFNHgQSGhobo6OiICUH8fAKN/YjOEF3fGZxhMoUZ5fnkDCr1nUErg+dTSmEvnMEZVOqrZKh1PsUdSpmZTSJzKGVmdg4S/9JnZnYOnk9mpqrafGrNMcuZ/KSUMziDRIbo+jB+ii7D/6Wv6XvSGZxhIqkZ5fnU9Bmi6zuDVgbPp5TCXjiDM6jUV8lQ63wKO5S6+DK49Uj+db+8FE59N92YiPrO4AxqGaLrA9y3JB2cKqLmE2jsR3SG6PrO4AyTKc0ozydniK7vDFoZPJ9SCnvhDM6gUl8lQ63zyS90bmZmZmZmZmZmufOhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe7i3n2vTgvoYjUbWUQ3F9LOa5zgJQbYyw6OM5hLhpOH4eAOGBqAkRMwrx06u2HFRpi/LJcIXgc01kAhg4LoXlCh0A8Ke+F1SEWvQ3R9FQq9oCK6JxT2InoNwOuglCGaQi+oUOiH6P3wGqQU1kEhg4K810H+UKqbNaxlCyvpIaEMQJEi5Tc+7+FO9vMQu+hngD0zkuHobtjfD4d3pm+pCJCUoNCSfv7MnXB5D6zqhcVrZiSC1wGNNVDIoCC6F1Qo9IPCXngdUtHrEF1fhUIvqIjuCYW9iF4D8DooZYim0AsqFPohej+8BimFdVDIoCBqHaR/fW8tW+hlN1exjiJFWmilhVYKEz4vUmQlN9PL49zE5mmtnyTwXB/svBEGHwGS9CZNSm98vfJ5AocfgYfeld7USTKtMbwOxK+BSoZoCr2gIrofVPbC65CKXofo+gpUekFFZE+o7EX0feF10MoQSaUXVET3g8J+eA1S0eugkkFB5DrIHkrdxGZuoQ+AFuZN+b2Vr2+gf1oX58A2eOL29PNkdOrvrXx9X2963XTxOmisgUIGBdG9oEKhHxT2wuuQil6H6PoqFHpBRXRPKOxF9BqA10EpQzSFXlCh0A/R++E1SCmsg0IGBdHrIHko1c0aNtCf6doN9NPNDQ1nOLo7vfGy2NcLxx5vOILXAY01UMigILoXVCj0g8JeeB1S0esQXV+FQi+oiO4Jhb2IXgPwOihliKbQCyoU+iF6P7wGKYV1UMigQGEd6jqUuvPOOykUCmd8XHnllQ2HmGwtWygxkunaEiPTcmK3vx8KGV9xq9CaXt8or4PGGihkUBDdC9V4PtXG8yk1V9Yhur4KhV6opllmlMJeRK8BeB2UMkRT6IVqmmU+Qfx+eA1SCuugkEGBwjrU/aTUD//wD3Ps2LGxj7/7u79rOMREC+hiJT1VHxs7nxbmsYr3s4ClmTOcPJy+2Fu1RxnPJxmFFx6Ckw28ML3XQWMNFDIoiO6FWnk+Vef5lJoL6xBdX4VCL9Rqrs8ohb2IXgPwOihliKbQC7Wa6/MJ4vfDa5BSWAeFDApU1qHuQ6nW1lYuu+yysY+3vOUtDQWYbDUbx17pPauEMqu5LfP1B3eMv/tAVoUiHNye/Xqvg8YaKGRQEN0LtfJ8qo3nU2q2r0N0fRUKvVCruT6jFPYieg3A66CUIZpCL9Rqrs8niN8Pr0FKYR0UMihQWYe6W3JgYIAlS5bw1re+lVtvvZXDhw9P+f2nT59meHj4jI+pLKK73kjnkLCQ5ZmvHhqYhgjA8KHs13odNNZAIYOC6F6oledT7TyfUrN5HaLrq1DohVrVM6PqnU8Q3xMKexG9BuB1UMoQTaEXajXX5xPE74fXIKWwDgoZFKisQ12HUj/2Yz/Gjh07ePTRR7nnnnv4j//4D2644QZOnDhx3mu2bt1KZ2fn2EdXV9eUNS6knWKDr79epIWL6Mh8/ciJ8bfDzCopwevV5/N5eR001kAhg4LoXqiF51PtPJ9Ss30douurUOiFWtQ7o+qdTxDfEwp7Eb0G4HVQyhBNoRdq0QzzCeL3w2uQUlgHhQwKVNahrgTr1q1jw4YNrFq1ip/6qZ/ir/7qr/je977H17/+9fNec8cddzA0NDT2MTg49S+gvsYJyg0+QlamxKtkv1PmtUOhpaEIFFrgggb2xuugsQYKGRRE90ItPJ9q5/mUmu3rEF1fhUIv1KLeGVXvfIL4nlDYi+g1AK+DUoZoCr1Qi2aYTxC/H16DlMI6KGRQoLIOGV93P/WmN72Jt7/97Rw6dP7n99ra2mhra6v5Z77EdDxTWOBlsj9T2DkdT7EBHQ08xeZ10FgDhQwKonshC8+nqXk+pWbzOkTXV6HQC1lUm1H1zieI7wmFvYheA/A6KGWIptALWczF+QTx++E1SCmsg0IGBSrr0NCzWidPnuTf/u3fWLx4cUMhJtrLDgoNPkJWoMhesr/62oqNkDR2YEhShhUNvN6X10FjDRQyKIjuhSw8n87P8yk129chur4KhV7IYi7OKIW9iF4D8DooZYim0AtZzMX5BPH74TVIKayDQgYFKutQV4Le3l52797N888/z969e/ngBz9IS0sLv/ALv9BQiImOM8gBdlJiJNP1JUbYz4Mc50jmDPOXwbIeKGR8jqzQCpevh/nVf736vLwOGmugkEFBdC/UwvOpNp5PqbmwDtH1VSj0Qi2aYUYp7EX0GoDXQSlDNIVeqEUzzCeI3w+vQUphHRQyKFBZh7oOpY4cOcIv/MIvsGLFCn72Z3+WSy+9lH379rFw4cKGQkz2GH20MC/TtUVa2MW2hjNc3QvJaLZrkxKs2tJwBK8DGmugkEFBdC9U4/lUG8+n1FxZh+j6KhR6oZpmmVEKexG9BuB1UMoQTaEXqmmW+QTx++E1SCmsg0IGBQrrUNeh1Fe/+lWOHj3K6dOnOXLkCF/96ld529ve1nCIyQbYw/1k6/ZvcDsD7Gk4w+I1cF1ftmuvuzu9vlFeB401UMigILoXqvF8qo3nU2qurEN0fRUKvVBNs8wohb2IXgPwOihliKbQC9U0y3yC+P3wGqQU1kEhgwKFdWjsFwhn0C62jS1OtcfJKl+/ny3TemK5cvP4DVvtEcfK16/rS6+bLl4HjTVQyKAguhdUKPSDwl54HVLR6xBdX4VCL6iI7gmFvYheA/A6KGWIptALKhT6IXo/vAYphXVQyKAgeh1kD6UgXZw+1nCAhylTpsQoJUZJKFNihBKjlClzgIfpY820N0ehkD6euH43LLsZKKRvgVl5G82xzwvp19fvTr+/UJjWGF4H4tdAJUM0hV5QEd0PKnvhdUhFr0N0fQUqvaAisidU9iL6vvA6aGWIpNILKqL7QWE/vAap6HVQyaAgch0yvsRZfgbYwwB7WMBSVnMbC1nORXTwKsO8zCH2sn3GX2Bs8Zr04+QgHNwOw4fg9WG4oCN9O8wVt838CxB6HTTWQCGDguheUKHQDwp74XVIRa9DdH0VCr2gIronFPYieg3A66CUIZpCL6hQ6Ifo/fAapBTWQSGDgqh1kD+UqjjOER7mrtAM87vg2k+ERvA6oLEGChkURPeCCoV+UNgLr0Mqeh2i66tQ6AUV0T2hsBfRawBeB6UM0RR6QYVCP0Tvh9cgpbAOChkU5L0O0r++Z2ZmZmZmZmZmc5MPpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHLnQykzMzMzMzMzM8tdIUmSJM+Cw8PDdHZ2QgEuWZJn5dQrxyApQ6EIFy/Ov74zOINahuj6AKeOAgkMDQ3R0dERE4L4+QQa+xGdIbq+MzjDZAozyvPJGVTqO4NWBs+nlMJeOIMzqNRXyVDrfIo7lDIzm0TmUMrM7Bwk/qXPzOwcPJ/MTFW1+dSaY5Yz+UkpZ3AGiQzR9WH8FF2G/0tf0/ekMzjDRFIzyvOp6TNE13cGrQyeTymFvXAGZ1Cpr5Kh1vkUdih18WVw65H86355KZz6broxEfWdwRnUMkTXB7hvSTo4VUTNJ9DYj+gM0fWdwRkmU5pRnk/OEF3fGbQyeD6lFPbCGZxBpb5Khlrnk1/o3MzMzMzMzMzMcudDKTMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9zFvfveLLSALlazkUV0cyHtvMYJXmKAvezgOIO5ZDh5GA7ugKEBGDkB89qhsxtWbIT5y3KJEJ4huj64F5QyWMo96QwV7gWdDJZyTzrDRO6H+Pp2puieVOgHZ0hF9wI05zr4UKoG3axhLVtYSQ8JZQCKFCm/8XkPd7Kfh9hFPwPsmZEMR3fD/n44vDN9W0eApASFlvTzZ+6Ey3tgVS8sXjMjEcIzRNcH94JSBku5J52hwr2gk8FS7klnmMj9EF/fzhTdkwr94Ayp6F6A5l4H//peFWvZQi+7uYp1FCnSQisttFKY8HmRIiu5mV4e5yY2T2v9JIHn+mDnjTD4CJCkzZmU3vh65fMEDj8CD70rbeYkmTsZoutXuBc0Mtg496QzVLgXNDLYOPekM0zU7P0QXd/OFtmTCv3gDOOafT5VRK6DD6WmcBObuYU+AFqYN+X3Vr6+gf5p3aAD2+CJ29PPk9Gpv7fy9X296XVzJUN0fXAvKGWwlHvSGSrcCzoZLOWedIaJ3A/x9e1M0T2p0A/OkIruBfA6QIZDqe9+97t86EMf4tJLL+Wiiy5i5cqVPP3009MSRkk3a9hAf6ZrN9BPNzc0nOHo7rThstjXC8cebzhCeIbo+uBeUMpQjedTde7JuZXBvaCToRbNMKPck84wkfshvn6tmmE+QXxPKvSDM6SiewG8DhV1HUodP36c66+/nnnz5vHII4/wz//8z/T397NgwYKGg6hZyxZKjGS6tsTItJwa7u+HQsZX/Sq0ptfP9gzR9cG9oJRhKp5PtXFPzq0M7gWdDNU0y4xyTzrDRO6H+Pq1aJb5BPE9qdAPzpCK7gXwOlTUtQSf+cxn6OrqYvv27WN/74orrmg4hJoFdLGSHooZf7uxhXms4v0sYCnHOZLpZ5w8nL7IGRl/VzQZhRcegpODML8r28+IzhBdH9wLShmq8XyqjXty7mRwL+hkqEUzzCj3pDNM5H6Ir1+rZphPEN+TCv3gDKnoXgCvw0R1VX/wwQd5xzvewYYNG1i0aBHXXHMNX/jCFzIXV7WajWOvNp9VQpnV3Jb5+oM7xl91P6tCEQ5ur/59qhmi64N7QSlDNZ5PtXNPzo0M7gWdDLVohhnlnnSGidwP8fVr1QzzCeJ7UqEfnCEV3QvgdZiormX493//d+655x66u7v567/+a37t136N3/iN3+BLX/rSea85ffo0w8PDZ3yoW0T3NPyUhIUsz3z10MA0RACGD2W/NjpDdH1wLyhlqMbzqR7uybmQwb2gk6EW9c4oz6dsFPrBGVLuh/j6tWqG+QTxPanQD86Qiu4F8DpMVNev75XLZd7xjnfw6U9/GoBrrrmGf/zHf+R//+//zYc//OFzXrN161Z+7/d+r6GQebuQ9syPsFUUaeEiOjJfP3Ji/G0gs0pK8HoD/4yIzhBdH9wLShmq8XyqnXtybmRwL+hkqEW9M8rzKRuFfnCGlPshvn6tmmE+QXxPKvSDM6SiewG8Dmf+jDosXryYH/qhHzrj7/3gD/4ghw8fPu81d9xxB0NDQ2Mfg4OD2ZLm6DVOUG7wMbYyJV4le4fMa4dCS0MRKLTABQ30R3SG6PrgXlDKUI3nU+3ck3Mjg3tBJ0Mt6p1Rnk/ZKPSDM6TcD/H1a9UM8wnie1KhH5whFd0L4HWYqK4npa6//noOHjx4xt/713/9Vy6//PLzXtPW1kZbW1u2dEFeYjqepSvwMtmfpeucjifpgI4GnqSLzhBdH9wLShmq8Xyqh3tyLmRwL+hkqEW9M8rzKRuFfnCGlPshvn6tmmE+QXxPKvSDM6SiewG8DhPV9aTUb/3Wb7Fv3z4+/elPc+jQIb7yla/wJ3/yJ2zatKmhEGr2soNCg4+xFSiyl+yvOrZiIySNHVqSlGFFA685Fp0huj64F5QyVOP5VDv35NzI4F7QyVCLZphR7klnmMj9EF+/Vs0wnyC+JxX6wRlS0b0AXoeJ6krwzne+kwceeIA///M/56qrruKuu+7is5/9LLfeemtDIdQcZ5AD7KTESKbrS4ywnwcbelvE+ctgWQ8U6nqWbVyhFS5f39jbx0ZniK4P7gWlDNV4PtXGPTl3MrgXdDLUohlmlHvSGSZyP8TXr1UzzCeI70mFfnCGVHQvgNdhorqPxXp6ejhw4ACvvfYa3/nOd/iv//W/NhRA1WP00cK8TNcWaWEX2xrOcHUvJKPZrk1KsGpLwxHCM0TXB/eCUoZqPJ+qc0/OrQzuBZ0MtWiGGeWedIaJ3A/x9WvVDPMJ4ntSoR+cIRXdC+B1GP85dk4D7OF+su3yN7idAfY0nGHxGriuL9u1192dXj/bM0TXB/eCUgZLuSedocK9oJPBUu5JZ5jI/RBf384U3ZMK/eAMqeheAK9DhQ+lprCLbWMbVO2RtsrX72fLtJwWVqzcPN6o1R7tq3z9ur70urmSIbo+uBeUMljKPekMFe4FnQyWck86w0Tuh/j6dqbonlToB2dIRfcCeB3Ah1JV7WIbfazhAA9TpkyJUUqMklCmxAglRilT5gAP08eaaW1QgEIhfSxv/W5YdjNQSN/6sfL2kWOfF9Kvr9+dfn+hMHcyRNevcC9oZLBx7klnqHAvaGSwce5JZ5io2fshur6dLbInFfrBGcY1+3yqiFyHjC+r1VwG2MMAe1jAUlZzGwtZzkV08CrDvMwh9rK94Rf3qmbxmvTj5CAc3A7Dh+D1YbigI30byBW3zfyLIEZniK4P7gWlDJZyTzpDhXtBJ4Ol3JPOMJH7Ib6+nSm6JxX6wRlS0b0Azb0OPpSqw3GO8DB3hWaY3wXXfiI0QniG6PrgXlDKYCn3pDNUuBd0MljKPekME7kf4uvbmaJ7UqEfnCEV3QvQnOvgX98zMzMzMzMzM7Pc+VDKzMzMzMzMzMxy50MpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsd4UkSZI8Cw4PD9PZ2QkFuGRJnpVTrxyDpAyFIly8OP/6zuAMahmi6wOcOgokMDQ0REdHR0wI4ucTaOxHdIbo+s7gDJMpzCjPJ2dQqe8MWhk8n1IKe+EMzqBSXyVDrfMp7lDKzGwSmUMpM7NzkPiXPjOzc/B8MjNV1eZTa45ZzuQnpZzBGSQyRNeH8VN0Gf4vfU3fk87gDBNJzSjPp6bPEF3fGbQyeD6lFPbCGZxBpb5KhlrnU9ih1MWXwa1H8q/75aVw6rvpxkTUdwZnUMsQXR/gviXp4FQRNZ9AYz+iM0TXdwZnmExpRnk+OUN0fWfQyuD5lFLYC2dwBpX6KhlqnU9+oXMzMzMzMzMzM8udD6XMzMzMzMzMzCx3PpQyMzMzMzMzM7Pc+VDKzMzMzMzMzMxyF/fue3VaQBer2cgiurmQdl7jBC8xwF52cJxBZ2iiDNH1AU4ehoM7YGgARk7AvHbo7IYVG2H+slwiOIMQhZ50BmeoULgvnUFLdE9G13cGrQwK92Z0huj6ShR6MjpDdH1nGKdwbypkyHsv5A+lulnDWrawkh4SygAUKVJ+4/Me7mQ/D7GLfgbY4wxzOEN0fYCju2F/Pxzemb69JkBSgkJL+vkzd8LlPbCqFxavmZEIziBEoSedwRkqFO5LZ9AS3ZPR9Z1BK4PCvRmdIbq+EoWejM4QXd8ZxincmwoZovZC+tf31rKFXnZzFesoUqSFVlpopTDh8yJFVnIzvTzOTWx2hjmaIbp+ksBzfbDzRhh8BEjSIZGU3vh65fMEDj8CD70rHSpJ4gzTnUFFdE86gzNUKNyXzqAn+r6Iru8MOhkU7s3oDNH11UT3pEKG6PrOkFK4NxUyQOxeyB5K3cRmbqEPgBbmTfm9la9voH9aF8cZNDJE1wc4sA2euD39PBmd+nsrX9/Xm17nDNObQYFCTzqDM1Qo3JfOoCW6J6PrO4NWBoV7MzpDdH0lCj0ZnSG6vjOMU7g3FTJE74XkoVQ3a9hAf6ZrN9BPNzc4wxzJEF0f0kcp9/Vmu3ZfLxx7vOEIziBEoSedwRkqFO5LZ9AS3ZPR9Z1BK4PCvRmdIbq+EoWejM4QXd8ZxincmwoZFPairkOpH/iBH6BQKJz1sWnTpoaDTLSWLZQYyXRtiZFpObFzBo0M0fUhfTyykPHV1wqt6fXOMD0ZqsljRin0pDM4Q4XCfekMtWmWP0NF13cGrQwK92Z0huj6tWiW+aSQIbq+M4xTuDcVMijsRV2HUk899RTHjh0b+3jssccA2LBhQ8NBKhbQxUp6qj42dj4tzGMV72cBS51hlmeIrg/pux8c3ln9UcrzSUbhhYfgZANvUuAMtZvpGaXQk87gDBUK96Uz1K4Z/gwVXd8ZtDIo3JvRGaLr16oZ5pNChuj6zjBO4d5UyKCwF1DnodTChQu57LLLxj527tzJ2972Nt71rnc1FGKi1Wwce6X3rBLKrOY2Z5jlGaLrQ/p2nIW67pKzFYpwcHv2652hdjM9oxR60hmcoULhvnSG2jXDn6Gi6zuDVgaFezM6Q3T9WjXDfFLIEF3fGcYp3JsKGRT2AiDjw2Lw+uuvc99997F582YKhcJ5v+/06dOcPn167K+Hh4en/LmL6M4aaYKEhSzPfLUzaGSIrg8wNDANEYDhQ9mvdYZsaplRnk/OMJszKNyXzpDNTMwniO/J6PrOoJVB4d6MzhBdP4u5Op8UMkTXd4ZxCvemQgaFvYAGXuj8L//yL/ne977Hxo0bp/y+rVu30tnZOfbR1dU15fdfSDvFBl9/vUgLF9GR+Xpn0MgQXR9g5MT423FmlZTg9er/rHaGaVbLjPJ8cobZnEHhvnSGbGZiPkF8T0bXdwatDAr3ZnSG6PpZzNX5pJAhur4zjFO4NxUyKOxF+jMyuvfee1m3bh1LliyZ8vvuuOMOhoaGxj4GB6f+pcfXOEG5wUfIypR4ley74wwaGaLrA8xrh0JLQxEotMAFDdynzpBNLTPK88kZZnMGhfvSGbKZifkE8T0ZXd8ZtDIo3JvRGaLrZzFX55NChuj6zjBO4d5UyKCwF5Dx1/deeOEFdu3axV/8xV9U/d62tjba2tpq/tkvMR3PsRV4mezPsTmDRobo+gCd0/FEI9DRwBONzlC/WmeU55MzzOYMCvelM9RvpuYTxPdkdH1n0MqgcG9GZ4iuX6+5PJ8UMkTXd4ZxCvemQgaFvYCMT0pt376dRYsW8b73va+h4ueylx0UGnyErECRvWR/xS9n0MgQXR9gxUZIGjs8JinDigZe+80Z6jdTM0qhJ53BGSoU7ktnqN9c/jNUdH1n0MqgcG9GZ4iuX6+5PJ8UMkTXd4ZxCvemQgaFvYAMh1Llcpnt27fz4Q9/mNbWzK+Tfl7HGeQAOykxkun6EiPs50GOc8QZZnmG6PoA85fBsh4oZGz1Qitcvh7mV/9Ve2eYJjM5oxR60hmcoULhvnSG+sz1P0NF13cGrQwK92Z0huj69Zjr80khQ3R9ZxincG8qZFDYC8hwKLVr1y4OHz7ML//yLzdUeCqP0UcL8zJdW6SFXWxzhjmSIbo+wNW9kIxmuzYpwaotDUdwhjrM9IxS6ElncIYKhfvSGWrXDH+Giq7vDFoZFO7N6AzR9WvVDPNJIUN0fWcYp3BvKmRQ2Iu6D6Xe8573kCQJb3/72xsufj4D7OF+sq3wN7idAfY4wxzJEF0fYPEauK4v27XX3Z1e7wzTk6EWMz2jFHrSGZyhQuG+dIbaNcOfoaLrO4NWBoV7MzpDdP1aNcN8UsgQXd8ZxincmwoZFPaisV8gnEG72Da2ONUeJ6t8/X62TMtJnTNoZYiuD7By8/jAqPaIZeXr1/Wl1znD9GZQoNCTzuAMFQr3pTNoie7J6PrOoJVB4d6MzhBdX4lCT0ZniK7vDOMU7k2FDNF7IXsoBeni9LGGAzxMmTIlRikxSkKZEiOUGKVMmQM8TB9rprVBnUErQ3T9QiF9PHL9blh2M1BI34Kz8jaeY58X0q+v351+f6HgDNOdQUV0TzqDM1Qo3JfOoCf6voiu7ww6GRTuzegM0fXVRPekQobo+s6QUrg3FTJA7F5M/6vYTbMB9jDAHhawlNXcxkKWcxEdvMowL3OIvWxv+IW1nGF2ZIiuD+kjkovXwMlBOLgdhg/B68NwQUf6dpwrbpv5F6N0Bh0KPekMzlChcF86g5bonoyu7wxaGRTuzegM0fWVKPRkdIbo+s4wTuHeVMgQtRfyh1IVxznCw9zlDM4QXh/SgXDtJ0IjOIMQhZ50BmeoULgvnUFLdE9G13cGrQwK92Z0huj6ShR6MjpDdH1nGKdwbypkyHsvpH99z8zMzMzMzMzM5iYfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpa7QpIkSZ4Fh4eH6ezshAJcsiTPyqlXjkFShkIRLl6cf31ncAa1DNH1AU4dBRIYGhqio6MjJgTx8wk09iM6Q3R9Z3CGyRRmlOeTM6jUdwatDJ5PKYW9cAZnUKmvkqHW+RR3KGVmNonMoZSZ2TlI/Eufmdk5eD6Zmapq86k1xyxn8pNSzuAMEhmi68P4KboM/5e+pu9JZ3CGiaRmlOdT02eIru8MWhk8n1IKe+EMzqBSXyVDrfMp7FDq4svg1iP51/3yUjj13XRjIuo7gzOoZYiuD3DfknRwqoiaT6CxH9EZous7gzNMpjSjPJ+cIbq+M2hl8HxKKeyFMziDSn2VDLXOJ7/QuZmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrmLe/c9y+TkYTi4A4YGYOQEzGuHzm5YsRHmL8snwwK6WM1GFtHNhbTzGid4iQH2soPjDM75+s6glcF0eD5pZIiu7wymyPPJGZQyRNc3LZ5PztDsGXwoNUsc3Q37++HwzvRtHQGSEhRa0s+fuRMu74FVvbB4zcxk6GYNa9nCSnpIKANQpEj5jc97uJP9PMQu+hlgz5yr7wxaGUyH55NGhuj6zmCKPJ+cQSlDdH3T4vnkDM7AGzVMWpLAc32w80YYfARI0mGVlN74euXzBA4/Ag+9Kx1uSTK9OdayhV52cxXrKFKkhVZaaKUw4fMiRVZyM708zk1snlP1nUErg2nwfNLJEF3fGUyN55MzqGWIrm86PJ+cwRnO5EMpcQe2wRO3p58no1N/b+Xr+3rT66bLTWzmFvoAaGHelN9b+foG+qetUaPrO4NWBtPh+aSRIbq+M5gizydnUMoQXd+0eD45gzOcqa5DqVKpxO/8zu9wxRVXcNFFF/G2t72Nu+66i2S6j20NSB/p3Neb7dp9vXDs8cYzdLOGDfRnunYD/XRzw6yu7wxaGabi+ZQvzyeNDNH1naF2nlH58XxyBqUM0fVr4fmUH88nZ3CGs9V1KPWZz3yGe+65h8997nN85zvf4TOf+Qz/83/+T/7wD/+w4SB2tv39UMj4ql+F1vT6Rq1lCyVGMl1bYqTh09Po+s6glWEqnk/58nzSyBBd3xlq5xmVH88nZ1DKEF2/Fp5P+fF8cgZnOFtdh1J79+7lAx/4AO973/v4gR/4AW655Rbe85738OSTTzYcxM508nD6onfVHuk8n2QUXngITjbw4vgL6GIlPVUf4TufFuaxivezgKWzsr4zaGWoxvMpP55PGhmi6ztDfTyj8uH55AxKGaLr18rzKR+eT87gDOdW16HU6tWr+eY3v8m//uu/AvDcc8/xd3/3d6xbt66hEHa2gzvG34Uhq0IRDm7Pfv1qNo696n5WCWVWc9usrO8MWhmq8XzKj+eTRobo+s5QH8+ofHg+OYNShuj6tfJ8yofnkzM4w7nV9fDgxz/+cYaHh7nyyitpaWmhVCrxqU99iltvvfW815w+fZrTp0+P/fXw8HD2tE1kaGB6fs7woezXLqJ7GhIkLGT5rKzvDFoZqvF8yo/nk0aG6PrOUJ96Z5TnUzaeT86glCG6fq08n/Lh+eQMznBudZ3Vfv3rX+fLX/4yX/nKV/iHf/gHvvSlL9HX18eXvvSl816zdetWOjs7xz66uroaCtwsRk6Mvy1oVkkJXm/gnxEX0k6xwTdoLNLCRXTMyvrOoJWhGs+n/Hg+aWSIru8M9al3Rnk+ZeP55AxKGaLr18rzKR+eT87gDOf7GXW4/fbb+fjHP87P//zPs3LlSn7xF3+R3/qt32Lr1q3nveaOO+5gaGho7GNwsIFfgm0i89qh0NLYzyi0wAUN9MdrnKDc4ON8ZUq8SrbJGV3fGbQyVOP5lB/PJ40M0fWdoT71zijPp2w8n5xBKUN0/Vp5PuXD88kZnOHc6vr1vVdeeYVi8cxzrJaWFsrl8/8faWtro62tLVu6JtY5HU/SAR0NPEn3EtPxjGmBl8n2jGl0fWfQylCN51N+PJ80MkTXd4b61DujPJ+y8XxyBqUM0fVr5fmUD88nZ3CGc6vrSan169fzqU99iocffpjnn3+eBx54gG3btvHBD36woRB2thUbIWns0JKkDCsaeM2xveyg0ODjfAWK7CXbq/FF13cGrQzVeD7lx/NJI0N0fWeoj2dUPjyfnEEpQ3T9Wnk+5cPzyRmc4dzqSvCHf/iH3HLLLXzkIx/hB3/wB+nt7eW//bf/xl133dVQCDvb/GWwrAcKdT3LNq7QCpevh/kN/Ir3cQY5wE5KjGS6vsQI+3mQ4xyZlfWdQStDNZ5P+fF80sgQXd8Z6uMZlQ/PJ2dQyhBdv1aeT/nwfHIGZzi3ug6l2tvb+exnP8sLL7zAq6++yr/927/xyU9+kgsuuKChEHZuV/dCMprt2qQEq7Y0nuEx+mhhXqZri7Swi22zur4zaGWYiudTvjyfNDJE13eG2nlG5cfzyRmUMkTXr4XnU348n5zBGc71c0zW4jVwXV+2a6+7O72+UQPs4X6yTb9vcDsD7JnV9Z1BK4Pp8HzSyBBd3xlMkeeTMyhliK5vWjyfnMEZzuZDKXErN48PrmqPela+fl1fet102cW2sUat9mhf5ev3s2Xa/stOdH1n0MpgOjyfNDJE13cGU+T55AxKGaLrmxbPJ2dwhjNl/I1Wy0uhkD6mufCdsL8fXngICm8cJSal8bcVTcqw7Ob0e6fjBH2yXWzjBZ7iJjaziveTvPHWkUWKlCkBBQoUOcDD7GLbtP9Xnej6zqCVwTR4PulkiK7vDKbG88kZ1DJE1zcdnk/O4Axn8qHULLF4TfpxchAObofhQ/D6MFzQkb4t6IrbGnvRu1oMsIcB9rCApazmNhaynIvo4FWGeZlD7GX7jL4QY3R9Z9DKYDo8nzQyRNd3BlPk+eQMShmi65sWzydncIaUD6VmmfldcO0nYjMc5wgPE/duHNH1nUErg+nwfNLIEF3fGUyR55MzKGWIrm9aPJ+codkz+DWlzMzMzMzMzMwsdz6UMjMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy10hSZIkz4JDQ0O86U1vAuDixXlWTr3yIpAABbj4svzrO4MzqGWIrg/wyrH0f7/3ve/R2dkZE4L4+QQi++GedAZnODODwIzyfHIGlfrOIJbB8wkQ2QtncAaR+jIZapxPuR9KHTlyhK6uGX5vSzOblQYHB1m6dGlYfc8nM5tK5IzyfDKzqXg+mZmqavMp90OpcrnM0aNHaW9vp1Ao1H398PAwXV1dDA4O0tHRMQMJnWG2ZIiu7wzTlyFJEk6cOMGSJUsoFuN+q9jzyRnmUobo+nMpg8KManQ+Qfx+RNd3BmdQy+D5NC56LxQyRNd3BmeY7gy1zqfWRkJmUSwWp+UUv6OjI2xznEErQ3R9Z5ieDJG/tlfh+eQMczFDdP25kiF6Rk3XfIL4/Yiu7wzOoJbB82lc9F4oZIiu7wzOMJ0ZaplPfqFzMzMzMzMzMzPLnQ+lzMzMzMzMzMwsd7PuUKqtrY3f/d3fpa2tzRmaPEN0fWfQyqBAYR2cwRlU6juDnui1iK7vDM6gliG6vhKFtYjOEF3fGZwhKkPuL3RuZmZmZmZmZmY2656UMjMzMzMzMzOz2c+HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrmbVYdSf//3f09LSwvve9/7cq+9ceNGCoXC2Mell17Ke9/7Xvbv3597lhdffJGPfvSjvPWtb6WtrY2uri7Wr1/PN7/5zRmvPXEd5s2bx/d93/exdu1avvjFL1Iul2e8/uQMEz/e+9735lK/Wo5Dhw7lUv/FF1/kYx/7GMuXL+fCCy/k+77v+7j++uu55557eOWVV2a8/saNG/npn/7ps/7+t7/9bQqFAt/73vdmPIMazyjPp8k5omZU9HyC2Bnl+XQ2zyfPp8k5PJ/8ZygVnk+eT5NzeD4113yaVYdS9957Lx/96Ed5/PHHOXr0aO713/ve93Ls2DGOHTvGN7/5TVpbW+np6ck1w/PPP8+1117L3/7t33L33Xdz4MABHn30Ud797nezadOmXDJU1uH555/nkUce4d3vfjcf+9jH6OnpYXR0NNcMEz/+/M//PJfa1XJcccUVM1733//937nmmmv4m7/5Gz796U/zf/7P/+Hv//7v+e///b+zc+dOdu3aNeMZ7GzNPqM8n87OETmjouYTeEYp8nzyfJqcw/PJ80mF55Pn0+Qcnk/NNZ9aowPU6uTJk3zta1/j6aef5sUXX2THjh38j//xP3LN0NbWxmWXXQbAZZddxsc//nFuuOEGXn75ZRYuXJhLho985CMUCgWefPJJLrnkkrG//8M//MP88i//ci4ZJq7D93//9/MjP/IjXHfddfzkT/4kO3bs4L/8l/+Sa4ZIUTk+8pGP0NraytNPP31GH7z1rW/lAx/4AEmS5J6p2XlGeT6dL0eUyAyeUVo8nzyfzpcjiueTVXg+eT6dL0cUz6f8zZonpb7+9a9z5ZVXsmLFCj70oQ/xxS9+MXRTTp48yX333cfy5cu59NJLc6n5//7f/+PRRx9l06ZNZzRpxZve9KZccpzLT/zET3D11VfzF3/xF2EZmsX//b//l7/5m785bx8AFAqFnFNZs88ozyer8IzS4/nk+WQpzyc9nk+eT5Zq5vk0aw6l7r33Xj70oQ8B6SN1Q0ND7N69O9cMO3fuZP78+cyfP5/29nYefPBBvva1r1Es5rOMhw4dIkkSrrzyylzq1evKK6/k+eefz6XWxL2ofHz605/OpfZUOTZs2DDjNSt9sGLFijP+/lve8paxHL/927894zng3Puwbt26XGqrafYZ5fl0JoUZFTGfQGdGeT6N83zyfJrI8yl+PoFnVIXnk+fTRJ5PzTmfZsWv7x08eJAnn3ySBx54AIDW1lZ+7ud+jnvvvZcbb7wxtxzvfve7ueeeewA4fvw4f/RHf8S6det48sknufzyy2e8vvrjekmS5HZ6O3EvKt785jfnUnuqHOc71c7Dk08+Sblc5tZbb+X06dO51DzXPjzxxBNjf7hoFp5Rnk+TKcwopfkE+c8oz6eU55Pn02SeT2fzn6FieD55Pk3m+XS2ZphPs+JQ6t5772V0dJQlS5aM/b0kSWhra+Nzn/scnZ2dueS45JJLWL58+dhf/+mf/imdnZ184Qtf4JOf/OSM1+/u7qZQKPAv//IvM14ri+985zu5vQjc5L2IEpFj+fLlFAoFDh48eMbff+tb3wrARRddlFuWc/3/P3LkSG71VXhGeT5NpjCjojKozCjPp5Tnk+fTZJ5P8fMJPKPA8wk8nybzfGrO+ST/63ujo6P82Z/9Gf39/Tz77LNjH8899xxLliwJece1ikKhQLFY5NVXX82l3pvf/GZ+6qd+is9//vOcOnXqrK9Hvn3s3/7t33LgwAF+5md+JixDs7j00ktZu3Ytn/vc/cvIqgAAmtVJREFU587ZB5Yvz6iU55NVeEbp8HxKeT5ZheeTDs+nlOeTVTTzfJJ/Umrnzp0cP36cX/mVXznrtPxnfuZnuPfee/nVX/3VXLKcPn2aF198EUgf7fzc5z7HyZMnWb9+fS71AT7/+c9z/fXX86M/+qP8/u//PqtWrWJ0dJTHHnuMe+65h+985zsznqGyDqVSif/8z//k0UcfZevWrfT09PBLv/RLM15/YoaJWltbectb3pJL/Wh/9Ed/xPXXX8873vEO7rzzTlatWkWxWOSpp57iX/7lX7j22mujIzYNz6hxnk9n55jIM8ozKm+eT+M8n87OMZHnk+dT3jyfxnk+nZ1jIs+nJphPibienp7k5ptvPufXnnjiiQRInnvuuRnP8eEPfzgBxj7a29uTd77znck3vvGNGa892dGjR5NNmzYll19+eXLBBRck3//935+8//3vT771rW/NeO2J69Da2posXLgwuemmm5IvfvGLSalUmvH6kzNM/FixYkUu9Sfm+MAHPpBrzYmOHj2a/Pqv/3pyxRVXJPPmzUvmz5+f/OiP/mhy9913J6dOnZrx+uf7//+tb30rAZLjx4/PeAYFnlFnavb5NDlH1IyKnk9JEjujPJ9Snk9n8nzyfKrwn6HieT6dyfPJ86miGedTIUnEX13NzMzMzMzMzMzmHPnXlDIzMzMzMzMzs7nHh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma586GUmZmZmZmZmZnlzodSZmZmZmZmZmaWOx9KmZmZmZmZmZlZ7nwoZWZmZmZmZmZmufOhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmljsfSpmZmZmZmZmZWe58KGVmZmZmZmZmZrnzoZSZmZmZmZmZmeXOh1JmZmZmZmZmZpY7H0qZmZmZmZmZmVnufChlZmZmZmZmZma5a827YLlc5ujRo7S3t1MoFPIub2aCkiThxIkTLFmyhGIx7qzc88nMzkVhRnk+mdm5eD6Zmapa51Puh1JHjx6lq6sr77JmNgsMDg6ydOnSsPqeT2Y2lcgZ5flkZlPxfDIzVdXmU+6HUu3t7WOfX7w47+rwyotAAhTg4svyr+8MzqCWIbo+wCvH0v+dOB8iRM8nENkP96QzOMOZGQRmlOeTM6jUdwaxDJ5PgMheOIMziNSXyVDjfMr9UKrySOfFi+FDR/OuDl9eCqe+C5csgVuP5F/fGZxBLUN0fYD7lqRDK/qR7+j5BBr7EZ0hur4zOMNkCjPK88kZVOo7g1YGz6eUwl44gzOo1FfJUOt88gudm5mZmZmZmZlZ7nwoZWZmZmZmZmZmufOhlJmZmZmZmZmZ5c6HUmZmZmZmZmZmlrvcX+g8qwV0sZqNLKKbC2nnNU7wEgPsZQfHGXSGHDOcPAwHd8DQAIycgHnt0NkNKzbC/GVzv75KBgUK/ahAYR2cIaVwb0ZniK6vQqEfVUSvRXR9lQwK96YzaFDoRxUKaxGdIbq+MzhDdAb5Q6lu1rCWLaykh4QyAEWKlN/4vIc72c9D7KKfAfY4wwxmOLob9vfD4Z1QeOMZu6QEhZb082fuhMt7YFUvLF4z9+qrZFCg0I8KFNbBGVIK92Z0huj6KhT6UUX0WkTXV8mgcG86gwaFflShsBbRGaLrO4MzqGSQ/vW9tWyhl91cxTqKFGmhlRZaKUz4vEiRldxML49zE5udYQYyJAk81wc7b4TBR4Ak/UNEUnrj65XPEzj8CDz0rvQPHUkyN+qrZFAR3Y8qFNbBGTTuzegM0fWVRPejkui1iK6vkEHh3nQGHdH9qERhLaIzRNd3BmdQyiB7KHUTm7mFPgBamDfl91a+voH+aV0cZ0gd2AZP3J5+noxO/b2Vr+/rTa+bC/VVMihQ6EcFCuvgDCmFezM6Q3R9FQr9qCJ6LaLrq2RQuDedQYNCP6pQWIvoDNH1ncEZ1DJIHkp1s4YN9Ge6dgP9dHODM0xThqO70z8YZLGvF449Prvrq2RQoNCPChTWwRlSCvdmdIbo+ioU+lFF9FpE11fJoHBvOoMGhX5UobAW0Rmi6zuDMyhmqPtQ6vHHH2f9+vUsWbKEQqHAX/7lXzYcYrK1bKHESKZrS4xMy4mdM6T290Mh4yuPFVrT62dzfZUMChT6sRrPp+bKoHBvRmeIrq9CoR+ryWM+QfxaRNdXyaBwbzqDBoV+rKZZ5pNChuj6zuAMihnqPpQ6deoUV199NZ///OcbLn4uC+hiJT1VHxs7nxbmsYr3s4ClztBghpOH0xejrPao9fkko/DCQ3Ay4wv0R9dXyaBAoR9r4fnUPBkU7s3oDNH1VSj0Yy1mej5B/FpE11fJoHBvOoMGhX6sRTPMJ4UM0fWdwRkUM0CGQ6l169bxyU9+kg9+8IMNFT6f1Wwce6X3rBLKrOY2Z2gww8Ed4++OklWhCAe3z876KhkUKPRjLTyfmieDwr0ZnSG6vgqFfqzFTM8niF+L6PoqGRTuTWfQoNCPtWiG+aSQIbq+MziDYgaAjA/U1u706dOcPn167K+Hh4en/P5FdE9D1YSFLM98tTOkhgamIQIwfGh21lfJoEChH2eC59PszaBwb0ZniK6vQqEfZ0K98wni1yK6vkoGhXvTGTQo9ONMmI3zSSFDdH1ncAbFDJDDC51v3bqVzs7OsY+urq4pv/9C2ik2GKtICxfRkfl6Z0iNnBh/u96skhK8Xv2fU5L1VTIoUOjHmeD5NHszKNyb0Rmi66tQ6MeZUO98gvi1iK6vkkHh3nQGDQr9OBNm43xSyBBd3xmcQTFD+jNm2B133MHQ0NDYx+Dg1L8Y/honKDf4CFmZEq+S/Z9gzpCa1w6FloYiUGiBCzL2aHR9lQwKFPpxJng+zd4MCvdmdIbo+ioU+nEm1DufIH4touurZFC4N51Bg0I/zoTZOJ8UMkTXdwZnUMwAOfz6XltbG21tbTV//0tMx7O+BV4m+7O+zpDqnI6n+YCOjE/zRddXyaBAoR9ngufT7M2gcG9GZ4iur0KhH2dCvfMJ4tciur5KBoV70xk0KPTjTJiN80khQ3R9Z3AGxQyQw5NS9drLDgoNxipQZC/ZXxXRGVIrNkLS2MEpSRlWZHzds+j6KhkUKPSjAoV1cIaUwr0ZnSG6vgqFflQRvRbR9VUyKNybzqBBoR9VKKxFdIbo+s7gDIoZIMOh1MmTJ3n22Wd59tlnAfiP//gPnn32WQ4fPtxQkIrjDHKAnZQYyXR9iRH28yDHOeIMDWaYvwyW9UAh4/N0hVa4fD3Mr/5r5pL1VTIoUOjHWng+NU8GhXszOkN0fRUK/ViLmZ5PEL8W0fVVMijcm86gQaEfa9EM80khQ3R9Z3AGxQyQ4VDq6aef5pprruGaa64BYPPmzVxzzTV84hOfaCjIRI/RRwvzMl1bpIVdbHOGacpwdS8ko9muTUqwasvsrq+SQYFCP1bj+dRcGRTuzegM0fVVKPRjNXnMJ4hfi+j6KhkU7k1n0KDQj9U0y3xSyBBd3xmcQTFD3YdSN954I0mSnPWxY8eOhsNUDLCH+8n2T6FvcDsD7HGGacqweA1c15ft2uvuTq+fzfVVMihQ6MdqPJ+aK4PCvRmdIbq+CoV+rCaP+QTxaxFdXyWDwr3pDBoU+rGaZplPChmi6zuDMyhmkHtNqYpdbBtbnGqPk1W+fj9bpvW/JjhDauXm8T9QVHsEu/L16/rS6+ZCfZUMChT6UYHCOjhDSuHejM4QXV+FQj+qiF6L6PoqGRTuTWfQoNCPKhTWIjpDdH1ncAa1DLKHUpAuTh9rOMDDlClTYpQSoySUKTFCiVHKlDnAw/SxZkYGtzNAoZA+Pr1+Nyy7GSikb9FbeZvfsc8L6dfX706/v1CYG/VVMqiI7kcVCuvgDBr3ZnSG6PpKovtRSfRaRNdXyKBwbzqDjuh+VKKwFtEZous7gzMoZcj40oP5GWAPA+xhAUtZzW0sZDkX0cGrDPMyh9jL9hl/8T9nSC1ek36cHISD22H4ELw+DBd0pG/Xu+K2mX0xyuj6KhkUKPSjAoV1cIaUwr0ZnSG6vgqFflQRvRbR9VUyKNybzqBBoR9VKKxFdIbo+s7gDCoZ5A+lKo5zhIe5yxkEMszvgmun93UPZ1V9lQwKFPpRgcI6OENK4d6MzhBdX4VCP6qIXovo+ioZFO5NZ9Cg0I8qFNYiOkN0fWdwhugM0r++Z2ZmZmZmZmZmc5MPpczMzMzMzMzMLHc+lDIzMzMzMzMzs9z5UMrMzMzMzMzMzHJXSJIkybPg8PAwnZ2dUIBLluRZOfXKMUjKUCjCxYvzr+8MzqCWIbo+wKmjQAJDQ0N0dHTEhCB+PoHGfkRniK7vDM4wmcKM8nxyBpX6zqCVwfMppbAXzuAMKvVVMtQ6n+IOpczMJpE5lDIzOweJf+kzMzsHzyczU1VtPrXmmOVMflLKGZxBIkN0fRg/RZfh/9LX9D3pDM4wkdSM8nxq+gzR9Z1BK4PnU0phL5zBGVTqq2SodT6FHUpdfBnceiT/ul9eCqe+m25MRH1ncAa1DNH1Ae5bkg5OFVHzCTT2IzpDdH1ncIbJlGaU55MzRNd3Bq0Mnk8phb1wBmdQqa+Sodb55Bc6NzMzMzMzMzOz3PlQyszMzMzMzMzMcudDKTMzMzMzMzMzy50PpczMzMzMzMzMLHc+lDIzMzMzMzMzs9yFvftevRbQxWo2sohuLqSd1zjBSwywlx0cZ9AZmijDycNwcAcMDcDICZjXDp3dsGIjzF824+VlMkTvg0oGBQrr4Aw6GaLnQ3R90NgHhQwqotciur4zjFOYDwoZovciur4ShbWIzhBdXyWDZ0PzZpA/lOpmDWvZwkp6SCgDUKRI+Y3Pe7iT/TzELvoZYI8zzOEMR3fD/n44vBMKbzzjl5Sg0JJ+/sydcHkPrOqFxWumvbxMhuh9UMmgQGEdnEEnQ/R8iK4PGvugkEFF9FpE13eGcQrzQSFD9F5E11eisBbRGaLrq2TwbHAG6V/fW8sWetnNVayjSJEWWmmhlcKEz4sUWcnN9PI4N7HZGeZghiSB5/pg540w+AiQpIMqKb3x9crnCRx+BB56VzrYkmTaIkhkAPeCEoV1cAaNDNHzIbp+RfQ+qGRQEb0W0fWdIaUwHxQyQPxeRNdXorAW0Rmi6ytk8GxwhgrZQ6mb2Mwt9AHQwrwpv7fy9Q30T+viOINGhgPb4Inb08+T0am/t/L1fb3pddNFIUP0PqhkUKCwDs6gkyF6PkTXB419UMigInotous7wziF+aCQIXovousrUViL6AzR9VUyeDY4Q0Vdh1Jbt27lne98J+3t7SxatIif/umf5uDBg9MSZKJu1rCB/kzXbqCfbm5whjmS4ejudPhksa8Xjj3eUHmZDNH7oJJhKp5PzhCRIXo+RNcHjX1QyFBNs8yo6PrOME5hPihkiN6L6Pq1aJb5pJAhur5KBs8GZ5iorkOp3bt3s2nTJvbt28djjz3GyMgI73nPezh16lTDQSZayxZKjGS6tsTItJzYOYNGhv39UMj4ymeF1vT6RilkiN4HlQxT8XxyhogM0fMhuj5o7INChmqaZUZF13eGcQrzQSFD9F5E169Fs8wnhQzR9VUyeDY4w0R1tcKjjz56xl/v2LGDRYsW8cwzz7BmzfS86tgCulhJD8WMv1nYwjxW8X4WsJTjHHGGWZzh5OH0Be/I+HvDySi88BCcHIT5Xdl+hkKG6H1QyVCN55Mz5J0hej5E1weNfVDIUItmmFHR9Z1hnMJ8UMgQvRfR9WvVDPNJIUN0fZUMng3OMFlDryk1NDQEwJvf/OZGfswZVrNx7JXes0oos5rbnGGWZzi4Y/wdGLIqFOHg9uzXK2SI3geVDPXyfHKGmc4QPR+i64PGPihkyGIuzqjo+s4wTmE+KGSI3ovo+lnNxfmkkCG6vkoGzwZnmCzjQ3NQLpf5zd/8Ta6//nquuuqq837f6dOnOX369NhfDw8PT/lzF9GdNdIECQtZnvlqZ9DIMDQwDeWB4UPZr1XIEL0PKhnq4fnkDHlkiJ4P0fVBYx8UMtSrlhlV73yC+LWIru8M4xTmg0KG6L2Irp/FXJ1PChmi66tk8Gxwhskyn1Fu2rSJf/zHf+SrX/3qlN+3detWOjs7xz66uqZ+xu5C2jM/PlZRpIWL6Mh8vTNoZBg5Mf6WoFklJXi9+j8npTNE74NKhnp4PjlDHhmi50N0fdDYB4UM9aplRtU7nyB+LaLrO8M4hfmgkCF6L6LrZzFX55NChuj6Khk8G5zh7J+Rwa//+q+zc+dOvvWtb7F06dIpv/eOO+5gaGho7GNwcHDK73+NE5QbfISsTIlXyd6lzqCRYV47FFoaKk+hBS5o4B5RyBC9DyoZauX55Ax5ZYieD9H1QWMfFDLUo9YZVe98gvi1iK7vDOMU5oNChui9iK5fr7k8nxQyRNdXyeDZ4AyT1fXre0mS8NGPfpQHHniAb3/721xxxRVVr2lra6Otra3mGi8xHc/zFXiZ7M/zOYNGhs7peJoQ6GjgaUKFDNH7oJKhGs8nZ8g7Q/R8iK4PGvugkKEW9c6oeucTxK9FdH1nGKcwHxQyRO9FdP1aNcN8UsgQXV8lg2eDM0xW15NSmzZt4r777uMrX/kK7e3tvPjii7z44ou8+uqrDYWYaC87KDT4CFmBInvJ/spnzqCRYcVGSBo7uCUpw4oGXndNIUP0PqhkqMbzyRnyzhA9H6Lrg8Y+KGSoRTPMqOj6zjBOYT4oZIjei+j6tWqG+aSQIbq+SgbPBmeYrK4E99xzD0NDQ9x4440sXrx47ONrX/taQyEmOs4gB9hJiZFM15cYYT8PNvSWhM6gkWH+MljWA4WML8dfaIXL12d/q1CVDNH7oJKhGs8nZ8g7Q/R8iK4PGvugkKEWzTCjous7wziF+aCQIXovouvXqhnmk0KG6PoqGTwbnGGyug6lkiQ558fGjRsbCjHZY/TRwrxM1xZpYRfbnGGOZLi6F5LRbNcmJVi1paHyMhmi90Elw1Q8n5whIkP0fIiuDxr7oJChmmaZUdH1nWGcwnxQyBC9F9H1a9Es80khQ3R9lQyeDc5w5s8RNMAe7idbp32D2xlgjzPMkQyL18B1fdmuve7u9PpGKWSI3geVDAoU1sEZdDJEz4fo+qCxDwoZVESvRXR9ZxinMB8UMkTvRXR9JQprEZ0hur5KBs8GZ5hI8lAKYBfbxhan2uNkla/fz5Zp/a8JzqCRYeXm8aFV7THPytev60uvmy4KGaL3QSWDAoV1cAadDNHzIbo+aOyDQgYV0WsRXd8ZxinMB4UM0XsRXV+JwlpEZ4iur5LBs8EZKjL+Jmc+drGNF3iKm9jMKt5P8sbbFRYpUqYEFChQ5AAPs4ttM/JfEpwhPkOhkD6iufCdsL8fXngICm8cpyal8bcUTcqw7Ob0e6fj9FwtA7gXlCisgzNoZIieD9H1K6L3QSWDiui1iK7vDCmF+aCQAeL3Irq+EoW1iM4QXV8hg2eDM1RIH0pB+jjZAHtYwFJWcxsLWc5FdPAqw7zMIfayfcZf/M8ZNDIsXpN+nByEg9th+BC8PgwXdKRvCbritsZe8G62ZIjeB5UMChTWwRl0MkTPh+j6oLEPChlURK9FdH1nGKcwHxQyRO9FdH0lCmsRnSG6vkoGzwZnkD+UqjjOER7mLmdwBuZ3wbWfCCsvkyF6H1QyKFBYB2fQyRA9H6Lrg8Y+KGRQEb0W0fWdYZzCfFDIEL0X0fWVKKxFdIbo+ioZPBuaN4Psa0qZmZmZmZmZmdnc5UMpMzMzMzMzMzPLnQ+lzMzMzMzMzMwsdz6UMjMzMzMzMzOz3BWSJEnyLDg8PExnZycU4JIleVZOvXIsfVvJQhEuXpx/fWdwBrUM0fUBTh0FEhgaGqKjoyMmBPHzCTT2IzpDdH1ncIbJFGaU55MzqNR3Bq0Mnk8phb1wBmdQqa+Sodb5FHcoZWY2icyhlJnZOUj8S5+Z2Tl4PpmZqmrzqTXHLGfyk1LO4AwSGaLrw/gpugz/l76m70lncIaJpGaU51PTZ4iu7wxaGTyfUgp74QzOoFJfJUOt8ynsUOriy+DWI/nX/fJSOPXddGMi6juDM6hliK4PcN+SdHCqiJpPoLEf0Rmi6zuDM0ymNKM8n5whur4zaGXwfEop7IUzOINKfZUMtc4nv9C5mZmZmZmZmZnlzodSZmZmZmZmZmaWOx9KmZmZmZmZmZlZ7nwoZWZmZmZmZmZmuYt79706LaCL1WxkEd1cSDuvcYKXGGAvOzjOYC4ZTh6GgztgaABGTsC8dujshhUbYf6yXCI4Axq9oJAheh9AYx0UKKyDQj84Qyq6H6Lrg/dBTfRaKPSDM6Sie0ElQ/ReKKyBCoW1iO6H6PoqGRR6QSFDM+6F/KFUN2tYyxZW0kNCGYAiRcpvfN7DneznIXbRzwB7ZiTD0d2wvx8O70zfUhEgKUGhJf38mTvh8h5Y1QuL18xIBGdAoxcUMkTvA2isgwKFdVDoB2dIRfdDdH3wPqiJXguFfnCGVHQvqGSI3guFNVChsBbR/RBdXyWDQi8oZGjmvZD+9b21bKGX3VzFOooUaaGVFlopTPi8SJGV3Ewvj3MTm6e1fpLAc32w80YYfARI0sZISm98vfJ5AocfgYfelTZSkjjDdGeI7gWFDAr7APHroCJ6HRT6wRnGRfdDdH3vg57ItVDoB2cYp3BfRGdQ2IvoNVASvRbR/RBdXyUDxPeCQgbvhfCh1E1s5hb6AGhh3pTfW/n6BvqndXEObIMnbk8/T0an/t7K1/f1ptc5w/RlUOgFhQzR+wAa66BAYR0U+sEZUtH9EF0fvA9qotdCoR+cIRXdCyoZovdCYQ1UKKxFdD9E11fJoNALChm8F6KHUt2sYQP9ma7dQD/d3NBwhqO7083OYl8vHHu84QjOgEYvKGSI3gfQWAcFCuug0A/OkIruh+j64H1QE70WCv3gDKnoXlDJEL0XCmugQmEtovshur5KBoVeUMjgvUjVdSh1zz33sGrVKjo6Oujo6ODHf/zHeeSRRxoOMdlatlBiJNO1JUam5cRufz8UMr7iVqE1vd4ZGs+g0AsKGaL3ATTWYSqeT7WZK7NBJUN0P0TXB+9DrZplRin0gzOkontBJUP0XiisQTXNMp8gvh+i66tkUOgFhQzei1Rdh1JLly7lD/7gD3jmmWd4+umn+Ymf+Ak+8IEP8E//9E8NB6lYQBcr6an62Nj5tDCPVbyfBSzNnOHk4fQFxqo9Pnc+ySi88BCcbOCF6Z1BoxcUMkTvA2isQzWeT7WZC7NBJUN0P0TXB+9DPZphRin0gzOkontBJUP0XiisQS2aYT5BfD9E11fJoNAL/397dx9kZ13f//95zm5YbrK7RgySNBsEswaVhEG0pWGIWIkKJFpH0taJXwm2narU2iahNZ2ppUVJLUnGVpRai4kd8A5HOhAKSrSGODHcWUn6E+NGC9mYUJg27CbchOSc6/fHxe4mgezuudnzee/Z52Nmpwu7V96vft7vfprz4TrXiZDBXgyp6FBq0aJFXHbZZXR3d/O6172OT3/600yePJmtW7fWFOJI81g6+KT3amWUmcdVVV+/Y/3QE++rVSjCjnXVX2+GGLMQIUPqPkCMdRiJ+9Pojfe9IUqG1POQuj7Yh0pMhD0qwjyYIZd6FqJkSN2LCGswGhNhf4L085C6fpQMEWYhQgZ7MaTKm8WgVCpx22238cwzz/Cbv/mbx/29gwcPcvDgwcF/7u/vH/bPPY3uaiMdIWMqs6q+uq+nDhGA/p3VX2uGGLMQIUPqPkCMdaiE+9PIxvPeECVD6nlIXR/sQ7VGs0dVuj9B+rWIMA9myKWehSgZUvciwhpUqln3J0g/D6nrR8kQYRYiZLAXQyo+m9u+fTuTJ0+mra2ND3/4w9x+++284Q1vOO7vr1q1is7OzsGvrq6uYf/8E2mnWOPz14u0cBIdVV9/aP/QRzBWKyvBCyPvz2YYRoRZiJAhdR8gxjqMhvvT6Iz3vSFKhtTzkLo+2IdKVbJHVbo/Qfq1iDAPZsilnoUoGVL3IsIajFaz70+Qfh5S14+SIcIsRMhgL478Myo0e/ZsfvKTn3D//ffzkY98hCuvvJKf/vSnx/39lStX0tfXN/jV2zv8mx6fZz/lGm8hK1PiOarvzqR2KLTUFIFCC5xQQ2/MEGMWImRI3QeIsQ6j4f40OuN9b4iSIfU8pK4P9qFSlexRle5PkH4tIsyDGXKpZyFKhtS9iLAGo9Xs+xOkn4fU9aNkiDALETLYiyEVv33vhBNOYNas/Pas888/nwcffJB/+Id/4Itf/OLL/n5bWxttbW2j/vOfpB73sRV4iurvY+usx11sQEcNd7GZIcYsRMiQug8QYx1Gw/1p9Mbz3hAlQ+p5SF0f7EOlKtmjKt2fIP1aRJgHM+RSz0KUDKl7EWENRqvZ9ydIPw+p60fJEGEWImSwF0NqfLQWlMvlo95TXKstrKdQY6wCRbZQ/RO/Zi+FrLYDQ7IyzK7heV9miDELETKk7gPEWIdquD+9vPG+N0TJkHoeUtcH+1CrZtujIsyDGXKpZyFKhtS9iLAG1Wq2/QnSz0Pq+lEyRJiFCBnsxZCKEqxcuZL77ruPxx57jO3bt7Ny5Up+8IMfsGTJkppCHGkfvWxnAyUOVXV9iUNs4w72sbvqDJNnwsyFUKjyMfCFVjhjEUwe+e3VZhhGhFmIkCF1HyDGOozE/Wl0mmFviJIh9Tykrg/2oRITYY+KMA9myKWehSgZUvciwhqMxkTYnyD9PKSuHyVDhFmIkMFeDKnoUOrJJ5/kgx/8ILNnz+btb387Dz74IN/5zndYsGBBTSGOdS+raWFSVdcWaWEja2vOcO4KyA5Xd21WgrnLa45gBmLMQoQMqfsAMdZhOO5Po9Mse0OUDKnnIXV9sA+jNVH2qAjzYIZc6lmIkiF1LyKswUgmyv4E6echdf0oGSLMQoQM9mLgz6nAzTffzGOPPcbBgwd58skn2bhxY903K4AeNnMb1a3wt7iGHjbXnGHafLhgdXXXXnBDfr0Zas8QYRYiZEjdB4ixDsNxfxqdZtkbomRIPQ+p64N9GK2JskdFmAcz5FLPQpQMqXsRYQ1GMlH2J0g/D6nrR8kQYRYiZLAXuZqfKTVWNrJ2cHFGup1s4Oe3sbyu/zVhzrKhIRnptrqBn1+wOr/ODPXLEGEWImRI3QeIsQ4RRFiHCPNghlzqeUhdH+xDNKnXIsI8mCGXehaiZEjdiwhrEEWEtUg9D6nrR8kQYRYiZLAXgQ+lIF+c1cxnO3dRpkyJw5Q4TEaZEococZgyZbZzF6uZX/eNu1DIb4lbtAlmXgYU8o9dHPjoxsHvC/nPF23Kf79QMEO9M6SehQgZIvQB0q9DFKnXIcI8mGFI6nlIXd8+xJNyLSLMgxmGRPi/i9QZIvQi9RpEknotUs9D6vpRMkD6WYiQwV5AlY/VapweNtPDZqYwg3lcxVRmcRIdPEc/T7GTLawb84f/TZuffx3ohR3roH8nvNAPJ3TkH8E4+6raHjBmhtGJMAsRMqTuA8RYhwgirEOEeTBDLvU8pK4P9iGa1GsRYR7MkEs9C1EypO5FhDWIIsJapJ6H1PWjZIgwCxEyTORehD+UGrCP3dzFdUkzTO6C8z+ZNIIZiDELETKk7gPEWIcIIqxDhHkwQy71PKSuD/YhmtRrEWEezJBLPQtRMqTuRYQ1iCLCWqSeh9T1o2SIMAsRMkzEXoR++54kSZIkSZKak4dSkiRJkiRJajgPpSRJkiRJktRwHkpJkiRJkiSp4TyUkiRJkiRJUsMVsizLGlmwv7+fzs5OKMAp0xtZOffsXsjKUCjCydMaX98MZoiWIXV9gGf2ABn09fXR0dGRJgTp9yeI0Y/UGVLXN4MZjhVhj3J/MkOU+maIlcH9KRehF2YwQ5T6UTKMdn9KdyglSccIcyglSS8jxIs+SXoZ7k+Sohppf2ptYJajeaeUGcwQIkPq+jB0ih6G/6Vvws+kGcxwpFB7lPvThM+Qur4ZYmVwf8pF6IUZzBClfpQMo92fkh1KnXw6LNnd+Lq3zoBnfpU3JkV9M5ghWobU9QFumZ5vnFGk2p8gRj9SZ0hd3wxmOFakPcr9yQyp65shVgb3p1yEXpjBDFHqR8kw2v3JB51LkiRJkiSp4TyUkiRJkiRJUsN5KCVJkiRJkqSG81BKkiRJkiRJDZfu0/cqNIUu5rGU0+jmRNp5nv08SQ9bWM8+ehuS4cAu2LEe+nrg0H6Y1A6d3TB7KUye2ZAIITKk7kXq+hCjDxEyROhFBBHWIcI8RMgQoRepM0ToQ4QMqfsQSeq1iDAPETKk7kOUDBF6kTpDhD5EEWEtUs9D6voQow8RMkToRYQMje5F+EOpbuazgOXMYSEZZQCKFCm/+P1CrmUbd7KRNfSweUwy7NkE29bArg35RyoCZCUotOTfP3wtnLEQ5q6AafPHJEKIDKl7kbo+xOhDhAwRehFBhHWIMA8RMkToReoMEfoQIUPqPkSSei0izEOEDKn7ECVDhF6kzhChD1FEWIvU85C6PsToQ4QMEXoRIUOqXoR++94ClrOCTZzDpRQp0kIrLbRSOOL7IkXmcBkruI9LWFbX+lkGj6yGDRdD791Alg9GVnrx5wPfZ7DrbrjzrfkgZVlzZYD0vUhdP0IfImSA9L2IIvU6RJiHCBkgfS9SZ4jQhwgZIMYsROFMps8AMWYydYYIvYiQIXUfIkm9FqnnIXX9Aan7ECFDhF5EyABpexH2UOoSlnEFqwFoYdKwvzvw88WsqevibF8L91+Tf58dHv53B36+dUV+XTNlSN2L1PUhRh8iZIjQiwgirEOEeYiQIUIvUmeI0IcIGVL3IZLUaxFhHiJkSN2HKBki9CJ1hgh9iCLCWqSeh9T1IUYfImSI0IsIGVL3oqZDqb/7u7+jUCjwp3/6p3UJM6Cb+SxmTVXXLmYN3VxUc4Y9m/JmV2PrCth7X80RQmRI3YvU9SFGHyJkiNCLSrg/vTxnMlevXqTOEKEPETKk7kOlxmp/gvRrEWEeImRI3YcoGSL0InWGCH2olH+Henn1mIfU9SFGHyJkiNCLCBki9KLqQ6kHH3yQL37xi8ydO7fmEMdawHJKHKrq2hKH6nJit20NFKp84lahNb++GTKk7kXq+hCjDxEyROjFaLk/HZ8zmatXL1JniNCHCBlS96ESY7k/Qfq1iDAPETKk7kOUDBF6kTpDhD5Uwr9DHV895iF1fYjRhwgZIvQiQoYIvajqUOrAgQMsWbKEL33pS0yZMqXmEEeaQhdzWDjibWPH08Ik5vJupjCj6gwHduUPGBvp9rnjyQ7D43fCgRoeTB8hQ+pepK4PMfoQIUOEXoyW+9PwnMlcPXqROkOEPkTIkLoPlRjL/QnSr0WEeYiQIXUfomSI0IvUGSL0oRL+HWp4tc5D6voQow8RMkToRYQMEXoBVR5KXX311Vx++eVccsklNRV/OfNYOvik92pllJnHVVVfv2P90BPvq1Uowo511V8fIUPqXqSuDzH6ECFDhF6MlvvTyJzJXK29SJ0hQh8iZEjdh0qM5f4E6dciwjxEyJC6D1EyROhF6gwR+lAJ/w41slrmIXV9iNGHCBki9CJChgi9AKj4ZrGvf/3r/PjHP+bBBx8c1e8fPHiQgwcPDv5zf3//sL9/Gt2VRnoZGVOZVfXVfT11iAD076z+2ggZUvcidX2I0YcIGSL0YjTcn0bPmYRae5E6Q4Q+RMiQug+jNdb7E6RfiwjzECFD6j5EyRChF6kzROjDaFWyR43H/QnSz0Pq+hCjDxEyROhFhAwRegEV3inV29vLxz/+cW699VZOPPHEUV2zatUqOjs7B7+6urqG/f0TaadY44cCFmnhJDqqvv7Q/qGPYKxWVoIXRt6fQ2dI3YvU9SFGHyJkiNCLkbg/jZ4zmau1F6kzROhDhAyp+zAajdifIP1aRJiHCBlS9yFKhgi9SJ0hQh9Go9I9ajzuT5B+HlLXhxh9iJAhQi8iZIjQi/zPqMDDDz/Mk08+yZve9CZaW1tpbW1l06ZN/OM//iOtra2USi9d1ZUrV9LX1zf41ds7/Jsen2c/5RpvIStT4jmq786kdii01BSBQgucUENvImRI3YvU9SFGHyJkiNCLkbg/jZ4zmau1F6kzROhDhAyp+zAajdifIP1aRJiHCBlS9yFKhgi9SJ0hQh9Go9I9ajzuT5B+HlLXhxh9iJAhQi8iZIjQC6jw7Xtvf/vb2b59+1H/7qqrruLss8/mL/7iL2hpeemqtrW10dbWNuoaT1KP+9gKPEX197F11uMuNqCjhrvYImRI3YvU9SFGHyJkiNCLkbg/VcaZhFp7kTpDhD5EyJC6D6PRiP0J0q9FhHmIkCF1H6JkiNCL1Bki9GE0Kt2jxuP+BOnnIXV9iNGHCBki9CJChgi9gArvlGpvb+ecc8456uuUU07h1FNP5ZxzzqkpyIAtrKdQ4y1kBYpsofonfs1eClltB4ZkZZhdw/O+ImRI3YvU9SFGHyJkiNCLkbg/jZ4zmau1F6kzROhDhAyp+zAajdifIP1aRJiHCBlS9yFKhgi9SJ0hQh9Gw79DjV4t85C6PsToQ4QMEXoRIUOEXkCVn743lvbRy3Y2UOJQVdeXOMQ27mAfu6vOMHkmzFwIhYofA58rtMIZi2DyyG+vDp0hdS9S14cYfYiQIUIvIoiwDhHmIUKGCL1InSFCHyJkSN2HSFKvRYR5iJAhdR+iZIjQi9QZIvQhighrkXoeUteHGH2IkCFCLyJkiNALqMOh1A9+8AM++9nP1vrHHOVeVtPCpKquLdLCRtbWnOHcFZAdru7arARzl9ccIUSG1L1IXR9i9CFChgi9qJT700s5k7l69SJ1hgh9iJAhdR+qMRb7E6RfiwjzECFD6j5EyRChF6kzROhDNfw71EvVYx5S14cYfYiQIUIvImSI0Itwd0oB9LCZ26huhb/FNfSwueYM0+bDBauru/aCG/LrmyFD6l6krg8x+hAhQ4ReRBBhHSLMQ4QMEXqROkOEPkTIkLoPkaReiwjzECFD6j5EyRChF6kzROhDFBHWIvU8pK4PMfoQIUOEXkTIEKEXIQ+lADaydnBxRrqdbODnt7G8rv81Yc6yoSEZ6ba6gZ9fsDq/rpkypO5F6voQow8RMkToRQQR1iHCPETIEKEXqTNE6EOEDKn7EEnqtYgwDxEypO5DlAwRepE6Q4Q+RBFhLVLPQ+r6EKMPETJE6EWEDKl7EfZQCvLFWc18tnMXZcqUOEyJw2SUKXGIEocpU2Y7d7Ga+XXfuAuF/Ja4RZtg5mVAIf/YxYGPbhz8vpD/fNGm/PcLhebKAOl7kbp+hD5EyADpexFF6nWIMA8RMkD6XqTOEKEPETJAjFmIwplMnwFizGTqDBF6ESFD6j5EknotUs9D6voDUvchQoYIvYiQAdL2osrHajVOD5vpYTNTmME8rmIqsziJDp6jn6fYyRbWjfnD/6bNz78O9MKOddC/E17ohxM68o9gnH1VbQ8YGy8ZUvcidX2I0YcIGSL0IoII6xBhHiJkiNCL1Bki9CFChtR9iCT1WkSYhwgZUvchSoYIvUidIUIfooiwFqnnIXV9iNGHCBki9CJChlS9CH8oNWAfu7mL65JmmNwF538yaYQQGVL3InV9iNGHCBki9CKCCOsQYR4iZIjQi9QZIvQhQobUfYgk9VpEmIcIGVL3IUqGCL1InSFCH6KIsBap5yF1fYjRhwgZIvQiQoZG9yL02/ckSZIkSZLUnDyUkiRJkiRJUsN5KCVJkiRJkqSG81BKkiRJkiRJDVfIsixrZMH+/n46OzuhAKdMb2Tl3LN7IStDoQgnT2t8fTOYIVqG1PUBntkDZNDX10dHR0eaEKTfnyBGP1JnSF3fDGY4VoQ9yv3JDFHqmyFWBvenXIRemMEMUepHyTDa/SndoZQkHSPMoZQkvYwQL/ok6WW4P0mKaqT9qbWBWY7mnVJmMEOIDKnrw9Apehj+l74JP5NmMMORQu1R7k8TPkPq+maIlcH9KRehF2YwQ5T6UTKMdn9Kdih18umwZHfj6946A575Vd6YFPXNYIZoGVLXB7hler5xRpFqf4IY/UidIXV9M5jhWJH2KPcnM6Sub4ZYGdyfchF6YQYzRKkfJcNo9ycfdC5JkiRJkqSG81BKkiRJkiRJDeehlCRJkiRJkhrOQylJkiRJkiQ1XLpP36vQFLqYx1JOo5sTaed59vMkPWxhPfvobUiGA7tgx3ro64FD+2FSO3R2w+ylMHlmQyK4DgHqm2FIhHmMIMI6OA+5COuQOkPq+lEyRJjHKFKvhfOQi7AOZoiRIcI8RhFhLZyH9GtghlgZGj2T4Q+lupnPApYzh4VklAEoUqT84vcLuZZt3MlG1tDD5jHJsGcTbFsDuzbkH6kIkJWg0JJ///C1cMZCmLsCps0fkwiuQ4D6ZhgSYR4jiLAOzkMuwjqkzpC6fpQMEeYxitRr4TzkIqyDGWJkiDCPUURYC+ch/RqYIVaGVDMZ+u17C1jOCjZxDpdSpEgLrbTQSuGI74sUmcNlrOA+LmFZXetnGTyyGjZcDL13A1k+GFnpxZ8PfJ/Brrvhzrfmg5RldY0x4dchdX0zHC31PEaReh2ch1yEdUidIXX9KBkg/TxGknItnIdchHUwQ5wMqecxktRr4TzEWAMzxMkAaWcy7KHUJSzjClYD0MKkYX934OeLWVPXxdm+Fu6/Jv8+Ozz87w78fOuK/Lp6cR3S1zfDkAjzGEGEdXAechHWIXWG1PWjZIgwj1GkXgvnIRdhHcwQI0OEeYwiwlo4D+nXwAyxMqSeyZCHUt3MZzFrqrp2MWvo5qKaM+zZlDe7GltXwN77ao7gOgSob4YhEeYxggjr4DzkIqxD6gyp60fJEGEeo0i9Fs5DLsI6mCFGhgjzGEWEtXAe0q+BGWJliDCTFR1KXXvttRQKhaO+zj777JpDHGsByylxqKprSxyqy4ndtjVQqPKJW4XW/PpauQ7p65thSIR5HI770+g00zxEWIfUGVLXj5IhwjyOZKLsUc5DLsI6mCFGhgjzOJKJsj+B8wDp18AMsTJEmMmK75R64xvfyN69ewe/fvjDH9Yc4khT6GIOC0e8bex4WpjEXN7NFGZUneHArvwBYyPdPnc82WF4/E44UMOD6V2H9PXNMCTCPI6G+9PImmUeIqxD6gyp60fJEGEeR6vZ9yjnIRdhHcwQI0OEeRytZt+fwHmA9GtghlgZIswkVHEo1drayumnnz749apXvaqmAMeax9LBJ71XK6PMPK6q+vod64eeeF+tQhF2rKv+etchfX0zDIkwj6Ph/jQ6zTAPEdYhdYbU9aNkiDCPo9Xse5TzkIuwDmaIkSHCPI5Ws+9P4DxA+jUwQ6wMEWYSqjiU6unpYfr06Zx11lksWbKEXbt2Dfv7Bw8epL+//6iv4ZxGd6WRXkbGVGZVfXVfTx0iAP07q7/WdUhf3wxDIszjaLg/jd54n4cI65A6Q+r6UTJEmMfRqmSPqnR/gvRr4TzkIqyDGWJkiDCPo9Xs+xM4D5B+DcwQK0OEmYQKD6V+4zd+g/Xr13PPPfdw00038d///d9cdNFF7N+//7jXrFq1is7OzsGvrq6uYWucSDvFGp+/XqSFk+io+vpD+4c+grFaWQleGHl/Pi7XIX19MwyJMI8jcX8avWaYhwjrkDpD6vpRMkSYx9GodI+qdH+C9GvhPOQirIMZYmSIMI+jMRH2J3AeIP0amCFWhggzmf8ZFbj00ktZvHgxc+fO5Z3vfCf//u//ztNPP803v/nN416zcuVK+vr6Br96e4d/0+Pz7Kdc4y1kZUo8R/XdmdQOhZaaIlBogRNq6I3rkL6+GYZEmMeRuD+NXjPMQ4R1SJ0hdf0oGSLM42hUukdVuj9B+rVwHnIR1sEMMTJEmMfRmAj7EzgPkH4NzBArQ4SZBKjyWe+5V7ziFbzuda9j587j3zPW1tZGW1vbqP/MJ6nHfWwFnqL6+9g663EXG9BRw11srkP6+mYYEmEeK+X+NLzxPg8R1iF1htT1o2SIMI/VGGmPqnR/gvRr4TzkIqyDGWJkiDCP1WjG/QmcB0i/BmaIlSHCTEIVz5Q60oEDB/jFL37BtGnTagpxpC2sp1DjLWQFimyh+id+zV4KWW0HhmRlmF3D875ch/T1zTAkwjxWyv3p+JphHiKsQ+oMqetHyRBhHqvRjHuU85CLsA5miJEhwjxWoxn3J3AeIP0amCFWhggzCRUeSq1YsYJNmzbx2GOPsWXLFt773vfS0tLC+9///ppCHGkfvWxnAyUOVXV9iUNs4w72sbvqDJNnwsyFUKjyPrJCK5yxCCaP/Pbq43Id0tc3w5AI8zgS96fRaZZ5iLAOqTOkrh8lQ4R5HI2JsEc5D7kI62CGGBkizONoTIT9CZwHSL8GZoiVIcJMQoWHUrt37+b9738/s2fP5nd+53c49dRT2bp1K1OnTq0pxLHuZTUtTKrq2iItbGRtzRnOXQHZ4equzUowd3nNEVyHAPXNMCTCPA7H/Wl0mmkeIqxD6gyp60fJEGEeRzJR9ijnIRdhHcwQI0OEeRzJRNmfwHmA9GtghlgZIsxkRYdSX//619mzZw8HDx5k9+7dfP3rX+e1r31tzSGO1cNmbqO6Ff4W19DD5pozTJsPF6yu7toLbsivr5XrkL6+GYZEmMfhuD+NTjPNQ4R1SJ0hdf0oGSLM40gmyh7lPOQirIMZYmSIMI8jmSj7EzgPkH4NzBArQ4SZrO0NhGNoI2sHF2ek28kGfn4by+v6XxPmLBsakpFuqxv4+QWr8+vqxXVIX98MQyLMYwQR1sF5yEVYh9QZUtePkiHCPEaRei2ch1yEdTBDjAwR5jGKCGvhPKRfAzPEypB6JsMeSkG+OKuZz3buokyZEocpcZiMMiUOUeIwZcps5y5WM7/uG3ehkN8St2gTzLwMKOQfuzjw0Y2D3xfyny/alP9+oVDXGBN+HVLXN8PRUs9jFKnXwXnIRViH1BlS14+SAdLPYyQp18J5yEVYBzPEyZB6HiNJvRbOQ4w1MEOcDJB2Jqt8rFbj9LCZHjYzhRnM4yqmMouT6OA5+nmKnWxh3Zg//G/a/PzrQC/sWAf9O+GFfjihI/8IxtlX1faAsdFwHdLXN8OQCPMYQYR1cB5yEdYhdYbU9aNkiDCPUaReC+chF2EdzBAjQ4R5jCLCWjgP6dfADLEypJrJ8IdSA/axm7u4LmmGyV1w/ieTRnAdAtQ3w5AI8xhBhHVwHnIR1iF1htT1o2SIMI9RpF4L5yEXYR3MECNDhHmMIsJaOA/p18AMsTI0eiZDv31PkiRJkiRJzclDKUmSJEmSJDWch1KSJEmSJElqOA+lJEmSJEmS1HAeSkmSJEmSJKnhClmWZY0s2N/fT2dnJxTglOmNrJx7di9kZSgU4eRpja9vBjNEy5C6PsAze4AM+vr66OjoSBOC9PsTxOhH6gyp65vBDMeKsEe5P5khSn0zxMrg/pSL0AszmCFK/SgZRrs/pTuUkqRjhDmUkqSXEeJFnyS9DPcnSVGNtD+1NjDL0bxTygxmCJEhdX0YOkUPw//SN+Fn0gxmOFKoPcr9acJnSF3fDLEyuD/lIvTCDGaIUj9KhtHuT8kOpU4+HZbsbnzdW2fAM7/KG5OivhnMEC1D6voAt0zPN84oUu1PEKMfqTOkrm8GMxwr0h7l/mSG1PXNECuD+1MuQi/MYIYo9aNkGO3+5IPOJUmSJEmS1HAeSkmSJEmSJKnhPJSSJEmSJElSw3koJUmSJEmSpIZL9+l749AUupjHUk6jmxNp53n28yQ9bGE9++htSIYDu2DHeujrgUP7YVI7dHbD7KUweWZDIiTPkLo+OAsDIqyDchF6EWEmzeAsDIiwDspF6EWEmTRDznmIsQYakrofqefRDENSzwJMzHXwUGoUupnPApYzh4VklAEoUqT84vcLuZZt3MlG1tDD5jHJsGcTbFsDuzbkH+sIkJWg0JJ///C1cMZCmLsCps0fkwjJM6SuD87CgAjroFyEXkSYSTM4CwMirINyEXoRYSbNkHMeYqyBhqTuR+p5NMOQ1LMAE3sdfPveCBawnBVs4hwupUiRFlppoZXCEd8XKTKHy1jBfVzCsrrWzzJ4ZDVsuBh67wayfDiz0os/H/g+g113w51vzYc5y5onQ+r6A5yFXOp10JDUvYgwk2bIOQu51OugIal7EWEmzTDEeUi/Bjpayn5EmEczDEn9f5uug4dSw7qEZVzBagBamDTs7w78fDFr6tqg7Wvh/mvy77PDw//uwM+3rsiva5YMqeuDszAgwjooF6EXEWbSDM7CgAjroFyEXkSYSTPknIcYa6AhqfuReh7NMCT1LIDrAFUcSv3qV7/iAx/4AKeeeionnXQSc+bM4aGHHqpLmEi6mc9i1lR17WLW0M1FNWfYsykfuGpsXQF776s5QvIMqeuDszAgwjqMxP1pZM00k2ZwFgZEWIfRmAh7VIReRJhJM+SchxhrMBoTYX+C9P1IPY9mGJJ6FsB1GFDRodS+ffu48MILmTRpEnfffTc//elPWbNmDVOmTKk5SDQLWE6JQ1VdW+JQXU4Nt62BQpVP/Sq05teP9wyp64OzMCDCOgzH/Wl0mmkmzeAsDIiwDiOZKHtUhF5EmEkz5JyHGGswkomyP0H6fqSeRzMMST0L4DoMqGgJPvOZz9DV1cW6desG/92ZZ55Zc4hoptDFHBZSrPLdjS1MYi7vZgoz2Mfuqv6MA7vyh5xR5XtFs8Pw+J1woBcmd1X3Z6TOkLo+OAsDIqzDSNyfRqdZZtIMzsKACOswGhNhj4rQiwgzaYac8xBjDUZjIuxPkL4fqefRDENSzwK4DkeqqPodd9zBm9/8ZhYvXsxpp53Geeedx5e+9KWqi0c1j6WDT5uvVkaZeVxV9fU71g89db9ahSLsWDfy70XNkLo+OAsDIqzDSNyfRq8ZZtIMzsKACOswGhNhj4rQiwgzaYac8xBjDUZjIuxPkL4fqefRDENSzwK4DkeqaBl++ctfctNNN9Hd3c13vvMdPvKRj/Anf/InfOUrXznuNQcPHqS/v/+or+hOo7sOf0rGVGZVfXVfTx0iAP07q782dYbU9cFZGBBhHUbi/lSJ8T+TZnAWBkRYh9GodI9yf6pOhJk0Q855iLEGozER9idI34/U82iGIalnAVyHI1X09r1yucyb3/xmrr/+egDOO+88/uu//ot/+qd/4sorr3zZa1atWsXf/M3f1BSy0U6kvepb2AYUaeEkOqq+/tD+oY+BrFZWghdq+P8RqTOkrg/OwoAI6zAS96fRa4aZNIOzMCDCOoxGpXuU+1N1IsykGXLOQ4w1GI2JsD9B+n6knkczDEk9C+A6HP1nVGDatGm84Q1vOOrfvf71r2fXrl3HvWblypX09fUNfvX29laXtIGeZz/lGm9jK1PiOaqfkEntUGipKQKFFjihhvlInSF1fXAWBkRYh5G4P41eM8ykGZyFARHWYTQq3aPcn6oTYSbNkHMeYqzBaEyE/QnS9yP1PJphSOpZANfhSBXdKXXhhReyY8eOo/7dz3/+c84444zjXtPW1kZbW1t16RJ5knrcS1fgKaq/l66zHnfSAR013EmXOkPq+uAsDIiwDiNxf6rE+J9JMzgLAyKsw2hUuke5P1UnwkyaIec8xFiD0ZgI+xOk70fqeTTDkNSzAK7DkSq6U+rP/uzP2Lp1K9dffz07d+7kq1/9Kv/8z//M1VdfXVOIaLawnkKNt7EVKLKF6p86NnspZLUdWpKVYXYNzxxLnSF1fXAWBkRYh5G4P41eM8ykGZyFARHWYTQmwh4VoRcRZtIMOechxhqMxkTYnyB9P1LPoxmGpJ4FcB2OVFGCt7zlLdx+++187Wtf45xzzuG6667js5/9LEuWLKkpRDT76GU7GyhxqKrrSxxiG3fU9LGIk2fCzIVQqOhetiGFVjhjUfUfDxkhQ+r64CwMiLAOI3F/Gp1mmUkzOAsDIqzDaEyEPSpCLyLMpBlyzkOMNRiNibA/Qfp+pJ5HMwxJPQvgOhyp4mOxhQsXsn37dp5//nkeffRR/vAP/7CmAFHdy2pamFTVtUVa2MjamjOcuwKyw9Vdm5Vg7vKaIyTPkLo+OAsDIqzDSNyfRtZMM2kGZ2FAhHUYjYmwR0XoRYSZNEPOeYixBqMxEfYnSN+P1PNohiGpZwFch6E/Ry+rh83cRnVd/hbX0MPmmjNMmw8XrK7u2gtuyK8f7xlS1wdnYUCEdVAuQi8izKQZnIUBEdZBuQi9iDCTZsg5DzHWQENS9yP1PJphSOpZANdhgIdSw9jI2sEGjXRL28DPb2N5Xf+LxpxlQ4M60q19Az+/YHV+XbNkSF0fnIUBEdZBuQi9iDCTZnAWBkRYB+Ui9CLCTJoh5zzEWAMNSd2P1PNohiGpZwFcB/BQakQbWctq5rOduyhTpsRhShwmo0yJQ5Q4TJky27mL1cyv+//zKBTy2/IWbYKZlwGF/KMfBz4+cvD7Qv7zRZvy3y8UmidD6voDnIVc6nXQkNS9iDCTZsg5C7nU66AhqXsRYSbNMMR5SL8GOlrKfkSYRzMMSf1/m64DVPlYrYmlh830sJkpzGAeVzGVWZxEB8/Rz1PsZAvrxvwBhNPm518HemHHOujfCS/0wwkd+cdAzr6qtoecjYcMqeuDszAgwjooF6EXEWbSDM7CgAjroFyEXkSYSTPknIcYa6AhqfuReh7NMCT1LMDEXgcPpSqwj93cxXVJM0zugvM/mTRC8gyp64OzMCDCOigXoRcRZtIMzsKACOugXIReRJhJM+SchxhroCGp+5F6Hs0wJPUswMRcB9++J0mSJEmSpIbzUEqSJEmSJEkN56GUJEmSJEmSGs5DKUmSJEmSJDVcIcuyrJEF+/v76ezshAKcMr2RlXPP7oWsDIUinDyt8fXNYIZoGVLXB3hmD5BBX18fHR0daUKQfn+CGP1InSF1fTOY4VgR9ij3JzNEqW+GWBncn3IRemEGM0SpHyXDaPendIdSknSMMIdSkvQyQrzok6SX4f4kKaqR9qfWBmY5mndKmcEMITKkrg9Dp+hh+F/6JvxMmsEMRwq1R7k/TfgMqeubIVYG96dchF6YwQxR6kfJMNr9Kdmh1Mmnw5Ldja976wx45ld5Y1LUN4MZomVIXR/glun5xhlFqv0JYvQjdYbU9c1ghmNF2qPcn8yQur4ZYmVwf8pF6IUZzBClfpQMo92ffNC5JEmSJEmSGs5DKUmSJEmSJDWch1KSJEmSJElqOA+lJEmSJEmS1HDpPn2vQlPoYh5LOY1uTqSd59nPk/SwhfXso9cMEyhD6voAB3bBjvXQ1wOH9sOkdujshtlLYfLMhkQIkSFCLyKIsA5mMMOACHtDhAyp+xBJ6rVwHsxwpAjzkDpDhD5EEWEtnAczDEg9C1EyNLoX4Q+lupnPApYzh4VklAEoUqT84vcLuZZt3MlG1tDDZjM0cYbU9QH2bIJta2DXhvzjNQGyEhRa8u8fvhbOWAhzV8C0+WMSIUSGCL2IIMI6mMEMAyLsDREypO5DJKnXwnkww5EizEPqDBH6EEWEtXAezDAg9SxEyZCqF6HfvreA5axgE+dwKUWKtNBKC60Ujvi+SJE5XMYK7uMSlpmhSTOkrp9l8Mhq2HAx9N4NZPkmkZVe/PnA9xnsuhvufGu+qWRZc2WA9L2IIsI6mMEMEGNviJABYsxCFBN9JiHGPJghxjxEyJC6D5GkXgvnwQwDIsxChAyQthdhD6UuYRlXsBqAFiYN+7sDP1/MmroujhliZEhdH2D7Wrj/mvz77PDwvzvw860r8uuaKUOEXkQQYR3MYIYBEfaGCBlS9yGS1GvhPJjhSBHmIXWGCH2IIsJaOA9mGJB6FqJkSN2LkIdS3cxnMWuqunYxa+jmIjM0SYbU9SG/lXLriuqu3boC9t5Xc4QQGSL0IoII62AGMwyIsDdEyJC6D5GkXgvnwQxHijAPqTNE6EMUEdbCeTDDgNSzECVDhF5UdCj1mte8hkKh8JKvq6++uuYgR1rAckocquraEofqcmJnhhgZUteH/PbIQpVPXyu05tc3Q4YIvRhJI/aoCOtgBjMMiLA3RMiQug+jMVH+DuU8mOFIEeYhdYYIfRjJRNmfwHkww5DUsxAlQ4ReVHQo9eCDD7J3797Br3vvvReAxYsX1xxkwBS6mMPCEW8bO54WJjGXdzOFGWYY5xlS14f80w92bRj5VsrjyQ7D43fCgRo+pCBChgi9GI2x3qMirIMZzDAgwt4QIUPqPozWRPg7lPNghiNFmIfUGSL0YTQmwv4EzoMZhqSehSgZIvQCKjyUmjp1Kqeffvrg14YNG3jta1/LW9/61ppCHGkeSwef9F6tjDLzuMoM4zxD6vqQfxxnoaL/K3mpQhF2rKv++ggZIvRiNMZ6j4qwDmYww4AIe0OEDKn7MFoT4e9QzoMZjhRhHlJniNCH0ZgI+xM4D2YYknoWomSI0AuAKm8WgxdeeIFbbrmFZcuWUSgUjvt7Bw8e5ODBg4P/3N/fP+yfexrd1UY6QsZUZlV9tRliZEhdH6Cvpw4RgP6d1V8bIUOEXlRqNHuU+5MZxnOGCHtDhAyp+1CNsdifIP1aOA9mOFKEeUidIUIfKtWs+xM4D2YYknoWomSI0Auo4UHn//Zv/8bTTz/N0qVLh/29VatW0dnZOfjV1dU17O+fSDvFGp+/XqSFk+io+nozxMiQuj7Aof1DH8dZrawEL4z8/6tDZ4jQi0qNZo9yfzLDeM4QYW+IkCF1H6oxFvsTpF8L58EMR4owD6kzROhDpZp1fwLnwQxDUs9ClAwRepH/GVW6+eabufTSS5k+ffqwv7dy5Ur6+voGv3p7h3/T4/Psp1zjLWRlSjxH9d0xQ4wMqesDTGqHQktNESi0wAk1/N9phAwRelGp0exR7k9mGM8ZIuwNETKk7kM1xmJ/gvRr4TyY4UgR5iF1hgh9qFSz7k/gPJhhSOpZiJIhQi+gyrfvPf7442zcuJFvf/vbI/5uW1sbbW1to/6zn6Qe97EVeIrq72MzQ4wMqesDdNbjjkago4Y7GiNkiNCLSox2j3J/MsN4zhBhb4iQIXUfKjVW+xOkXwvnwQxHijAPqTNE6EMlmnl/AufBDENSz0KUDBF6AVXeKbVu3TpOO+00Lr/88pqKv5wtrKdQ4y1kBYpsofonfpkhRobU9QFmL4WstsNjsjLMruHZbxEyROhFJcZqj4qwDmYww4AIe0OEDKn7UKlm/juU82CGI0WYh9QZIvShEs28P4HzYIYhqWchSoYIvYAqDqXK5TLr1q3jyiuvpLW16uekH9c+etnOBkocqur6EofYxh3sY7cZxnmG1PUBJs+EmQuhUOWoF1rhjEUweeS32ofOEKEXozWWe1SEdTCDGQZE2BsiZEjdh0o0+9+hnAczHCnCPKTOEKEPo9Xs+xM4D2YYknoWomSI0Auo4lBq48aN7Nq1iw996EM1FR7OvaymhUlVXVukhY2sNUOTZEhdH+DcFZAdru7arARzl9ccIUSGCL0YjbHeoyKsgxnMMCDC3hAhQ+o+jNZE+DuU82CGI0WYh9QZIvRhNCbC/gTOgxmGpJ6FKBki9KLiQ6l3vOMdZFnG6173upqLH08Pm7mN6lb4W1xDD5vN0CQZUtcHmDYfLlhd3bUX3JBf3wwZIvRiNMZ6j4qwDmYww4AIe0OEDKn7MFoT4e9QzoMZjhRhHlJniNCH0ZgI+xM4D2YYknoWomSI0Iva3kA4hjaydnBxRrqdbODnt7G8rv81wQwxMqSuDzBn2dCGMdItlgM/v2B1fl0zZYjQiwgirIMZzDAgwt4QIUPqPkSSei2cBzMcKcI8pM4QoQ9RRFgL58EMA1LPQpQMqXsR9lAK8sVZzXy2cxdlypQ4TInDZJQpcYgShylTZjt3sZr5Y7JxmyFGhtT1C4X89shFm2DmZUAh/wjOgY/xHPy+kP980ab89wuF5soA6XsRRYR1MIMZIMbeECEDxJiFKCb6TEKMeTBDjHmIkCF1HyJJvRbOgxkGRJiFCBkgbS/q/xS7OuthMz1sZgozmMdVTGUWJ9HBc/TzFDvZwroxf/ifGWJkSF0f8lskp82HA72wYx3074QX+uGEjvzjOGdfVdvD5sZLhgi9iCDCOpjBDAMi7A0RMqTuQySp18J5MMORIsxD6gwR+hBFhLVwHswwIPUsRMmQqhfhD6UG7GM3d3GdGcyQvD7kG8L5n0waIUSGCL2IIMI6mMEMAyLsDREypO5DJKnXwnkww5EizEPqDBH6EEWEtXAezDAg9SxEydDoXoR++54kSZIkSZKak4dSkiRJkiRJajgPpSRJkiRJktRwHkpJkiRJkiSp4TyUkiRJkiRJUsMVsizLGlmwv7+fzs5OKMAp0xtZOffsXsjKUCjCydMaX98MZoiWIXV9gGf2ABn09fXR0dGRJgTp9yeI0Y/UGVLXN4MZjhVhj3J/MkOU+maIlcH9KRehF2YwQ5T6UTKMdn9KdyglSccIcyglSS8jxIs+SXoZ7k+Sohppf2ptYJajeaeUGcwQIkPq+jB0ih6G/6Vvws+kGcxwpFB7lPvThM+Qur4ZYmVwf8pF6IUZzBClfpQMo92fkh1KnXw6LNnd+Lq3zoBnfpU3JkV9M5ghWobU9QFumZ5vnFGk2p8gRj9SZ0hd3wxmOFakPcr9yQyp65shVgb3p1yEXpjBDFHqR8kw2v3JB51LkiRJkiSp4TyUkiRJkiRJUsN5KCVJkiRJkqSG81BKkiRJkiRJDZfu0/dUlQO7YMd66OuBQ/thUjt0dsPspTB5ZmMyTKGLeSzlNLo5kXaeZz9P0sMW1rOP3qavb4ZYGZSL0AszxMiQur4Z4kn9d4cIvTCDGSJlSF0/ktT7E6TvR+r6ZjBD6gweSo0TezbBtjWwa0P+sY4AWQkKLfn3D18LZyyEuStg2vyxydDNfBawnDksJKMMQJEi5Re/X8i1bONONrKGHjY3XX0zxMqgXIRemCFGhtT1zRBP6r87ROiFGcwQKUPq+pGk3p8gfT9S1zeDGaJk8O17wWUZPLIaNlwMvXcDWb5hZ6UXfz7wfQa77oY735pv8FlW3xwLWM4KNnEOl1KkSAuttNBK4YjvixSZw2Ws4D4uYVlT1TdDrAzKReiFGWJkSF3fDLFE+LtDhF6YwQyRMqSuH0WE/QnS9yN1fTOYIVIGD6WC274W7r8m/z47PPzvDvx864r8unq5hGVcwWoAWpg07O8O/Hwxa+o2qKnrmyFWBuUi9MIMMTKkrm+GeFL/3SFCL8xghkgZUtePJPX+BOn7kbq+GcwQLUNFh1KlUom/+qu/4swzz+Skk07ita99Lddddx1ZvY+uBeS3tW5dUd21W1fA3vtqz9DNfBazpqprF7OGbi4a1/XNECvDcCbS/hShF2aIkSF1fTOMXqP2qNR/d4jQCzOYIVKG1PVHY6LsT5C+H6nrm8EMETNUdCj1mc98hptuuokbb7yRRx99lM985jP8/d//PZ/73OdqDqKX2rYGClU+9avQml9fqwUsp8Shqq4tcajm09PU9c0QK8NwJtL+FKEXZoiRIXV9M4xeo/ao1H93iNALM5ghUobU9UdjouxPkL4fqeubwQwRM1R0KLVlyxbe8573cPnll/Oa17yGK664gne84x088MADNQfR0Q7syh/8N9JtrceTHYbH74QDNTwcfwpdzGHhiLfwHU8Lk5jLu5nCjHFZ3wyxMoxkouxPEXphhhgZUtc3Q2UasUel/rtDhF6YwQyRMqSuP1oTYX+C9P1IXd8MZoiYASo8lJo3bx7f+973+PnPfw7AI488wg9/+EMuvfTSmkLopXasH/okimoVirBjXfXXz2Pp4FP3q5VRZh5Xjcv6ZoiVYSQTZX+K0AszxMiQur4ZKtOIPSr13x0i9MIMZoiUIXX90ZoI+xOk70fq+mYwQ8QMABXdQPmJT3yC/v5+zj77bFpaWiiVSnz6059myZIlx73m4MGDHDx4cPCf+/v7q087gfT11OfP6d9Z/bWn0V2HBBlTmTUu65shVoaRTJT9KUIvzBAjQ+r6ZqhMpXtUNftT6r87ROiFGcwQKUPq+qM1EfYnSN+P1PXNYIaIGaDCO6W++c1vcuutt/LVr36VH//4x3zlK19h9erVfOUrXznuNatWraKzs3Pwq6urq6bAE8Wh/UMfjVqtrAQv1PAa+0TaKdb4AY1FWjiJjnFZ3wyxMoxkouxPEXphhhgZUtc3Q2Uq3aOq2Z9S/90hQi/MYIZIGVLXH62JsD9B+n6krm8GM0TMkP8ZFbjmmmv4xCc+we/93u8xZ84c/t//+3/82Z/9GatWrTruNStXrqSvr2/wq7e3hjcCTyCT2qHQUtufUWiBE2qYj+fZT7nG2/nKlHiO6v6/R+r6ZoiVYSQTZX+K0AszxMiQur4ZKlPpHlXN/pT67w4RemEGM0TKkLr+aE2E/QnS9yN1fTOYIWIGqPDte88++yzF4tHnWC0tLZTLx/9fpK2tjba2turSTWCd9biTDuio4U66J6nHfbYFnqK6+2xT1zdDrAwjmSj7U4RemCFGhtT1zVCZSveoavan1H93iNALM5ghUobU9UdrIuxPkL4fqeubwQwRM0CFd0otWrSIT3/609x111089thj3H777axdu5b3vve9NYXQS81eCllth5ZkZZhdwzPHtrCeQo238xUosoXqnkiYur4ZYmUYyUTZnyL0wgwxMqSub4bKNGKPSv13hwi9MIMZImVIXX+0JsL+BOn7kbq+GcwQMQNUeCj1uc99jiuuuIKPfvSjvP71r2fFihX80R/9Edddd11NIfRSk2fCzIVQqOhetiGFVjhjEUyu4RE5++hlOxsocaiq60scYht3sI/d47K+GWJlGMlE2Z8i9MIMMTKkrm+GyjRij0r9d4cIvTCDGSJlSF1/tCbC/gTp+5G6vhnMEDEDVHgo1d7ezmc/+1kef/xxnnvuOX7xi1/wqU99ihNOOKGmEHp5566A7HB112YlmLu89gz3spoWJlV1bZEWNrJ2XNc3Q6wMw5lI+1OEXpghRobU9c0weo3ao1L/3SFCL8xghkgZUtcfjYmyP0H6fqSubwYzRMxQ271aGlPT5sMFq6u79oIb8utr1cNmbqO6/w/wLa6hh83jur4ZYmVQLkIvzBAjQ+r6Zogn9d8dIvTCDGaIlCF1/UhS70+Qvh+p65vBDBEzeCgV3JxlQ5v3SLe7Dvz8gtX5dfWykbWDgzrSrX0DP7+N5XX7Lzup65shVgblIvTCDDEypK5vhnhS/90hQi/MYIZIGVLXjyT1/gTp+5G6vhnMEC1Dle/qVaMUCvmtqlPfAtvWwON3QuHFo8SsNPTRqlkZZl6W/249/ivCsTaylsd5kEtYxlzeTfbiR0cWKVKmBBQoUGQ7d7GRtXX/rzqp65shVgblIvTCDDEypK5vhlgi/N0hQi/MYIZIGVLXjyLC/gTp+5G6vhnMECmDh1LjxLT5+deBXtixDvp3wgv9cEJH/tGos6+q7cF/o9HDZnrYzBRmMI+rmMosTqKD5+jnKXayhXVj+iDG1PXNECuDchF6YYYYGVLXN0M8qf/uEKEXZjBDpAyp60eSen+C9P1IXd8MZoiSwUOpcWZyF5z/ybQZ9rGbu0j3iWap65shVgblIvTCDDEypK5vhnhS/90hQi/MYIZIGVLXjyT1/gTp+5G6vhnMkDqDz5SSJEmSJElSw3koJUmSJEmSpIbzUEqSJEmSJEkN56GUJEmSJEmSGq6QZVnWyIJ9fX284hWvAODkaY2snHv2CSADCnDy6Y2vbwYzRMuQuj7As3vz//n000/T2dmZJgTp9ycI0g9n0gxmODpDgD3K/ckMUeqbIVgG9ycgSC/MYIYg9cNkGOX+1PBDqd27d9PVNcaf7ylpXOrt7WXGjBnJ6rs/SRpOyj3K/UnScNyfJEU10v7U8EOpcrnMnj17aG9vp1AoVHx9f38/XV1d9Pb20tHRMQYJzTBeMqSub4b6ZciyjP379zN9+nSKxXTvKnZ/MkMzZUhdv5kyRNijat2fIH0/Utc3gxmiZXB/GpK6FxEypK5vBjPUO8No96fWWkJWo1gs1uUUv6OjI1lzzBArQ+r6ZqhPhpRv2xvg/mSGZsyQun6zZEi9R9Vrf4L0/Uhd3wxmiJbB/WlI6l5EyJC6vhnMUM8Mo9mffNC5JEmSJEmSGs5DKUmSJEmSJDXcuDuUamtr46//+q9pa2szwwTPkLq+GWJliCDCOpjBDFHqmyGe1GuRur4ZzBAtQ+r6kURYi9QZUtc3gxlSZWj4g84lSZIkSZKkcXenlCRJkiRJksY/D6UkSZIkSZLUcB5KSZIkSZIkqeE8lJIkSZIkSVLDjatDqR/96Ee0tLRw+eWXN7z20qVLKRQKg1+nnnoq73rXu9i2bVvDszzxxBN87GMf46yzzqKtrY2uri4WLVrE9773vTGvfeQ6TJo0iVe/+tUsWLCAL3/5y5TL5TGvf2yGI7/e9a53NaT+SDl27tzZkPpPPPEEH//4x5k1axYnnngir371q7nwwgu56aabePbZZ8e8/tKlS/nt3/7tl/z7H/zgBxQKBZ5++ukxzxCNe5T707E5Uu1RqfcnSLtHuT+9lPuT+9OxOdyf/DtUFO5P7k/H5nB/mlj707g6lLr55pv52Mc+xn333ceePXsaXv9d73oXe/fuZe/evXzve9+jtbWVhQsXNjTDY489xvnnn8/3v/99brjhBrZv384999zD2972Nq6++uqGZBhYh8cee4y7776bt73tbXz84x9n4cKFHD58uKEZjvz62te+1pDaI+U488wzx7zuL3/5S8477zy++93vcv311/Of//mf/OhHP+LP//zP2bBhAxs3bhzzDHqpib5HuT+9NEfKPSrV/gTuURG5P7k/HZvD/cn9KQr3J/enY3O4P02s/ak1dYDROnDgAN/4xjd46KGHeOKJJ1i/fj1/+Zd/2dAMbW1tnH766QCcfvrpfOITn+Ciiy7iqaeeYurUqQ3J8NGPfpRCocADDzzAKaecMvjv3/jGN/KhD32oIRmOXIdf+7Vf401vehMXXHABb3/721m/fj1/8Ad/0NAMKaXK8dGPfpTW1lYeeuiho+bgrLPO4j3veQ9ZljU800TnHuX+dLwcqaTM4B4Vi/uT+9PxcqTi/qQB7k/uT8fLkYr7U+ONmzulvvnNb3L22Wcze/ZsPvCBD/DlL385aVMOHDjALbfcwqxZszj11FMbUvP//u//uOeee7j66quPGtIBr3jFKxqS4+X81m/9Fueeey7f/va3k2WYKP73f/+X7373u8edA4BCodDgVJroe5T7kwa4R8Xj/uT+pJz7UzzuT+5Pyk3k/WncHErdfPPNfOADHwDyW+r6+vrYtGlTQzNs2LCByZMnM3nyZNrb27njjjv4xje+QbHYmGXcuXMnWZZx9tlnN6Repc4++2wee+yxhtQ6shcDX9dff31Dag+XY/HixWNec2AOZs+efdS/f9WrXjWY4y/+4i/GPAe8fB8uvfTShtSOZqLvUe5PR4uwR6XYnyDOHuX+NMT9yf3pSO5P6fcncI8a4P7k/nQk96eJuT+Ni7fv7dixgwceeIDbb78dgNbWVn73d3+Xm2++mYsvvrhhOd72trdx0003AbBv3z6+8IUvcOmll/LAAw9wxhlnjHn96LfrZVnWsNPbI3sx4JWvfGVDag+X43in2o3wwAMPUC6XWbJkCQcPHmxIzZfrw/333z/4l4uJwj3K/elYEfaoSPsTNH6Pcn/KuT+5Px3L/eml/DtUGu5P7k/Hcn96qYmwP42LQ6mbb76Zw4cPM3369MF/l2UZbW1t3HjjjXR2djYkxymnnMKsWbMG//lf/uVf6Ozs5Etf+hKf+tSnxrx+d3c3hUKBn/3sZ2NeqxqPPvpowx4Cd2wvUkmRY9asWRQKBXbs2HHUvz/rrLMAOOmkkxqW5eX+99+9e3fD6kfhHuX+dKwIe1SqDFH2KPennPuT+9Ox3J/S70/gHgXuT+D+dCz3p4m5P4V/+97hw4f513/9V9asWcNPfvKTwa9HHnmE6dOnJ/nEtQGFQoFischzzz3XkHqvfOUreec738nnP/95nnnmmZf8POXHx37/+99n+/btvO9970uWYaI49dRTWbBgATfeeOPLzoEayz0q5/6kAe5Rcbg/5dyfNMD9KQ73p5z7kwZM5P0p/J1SGzZsYN++ffz+7//+S07L3/e+93HzzTfz4Q9/uCFZDh48yBNPPAHkt3beeOONHDhwgEWLFjWkPsDnP/95LrzwQn7913+dv/3bv2Xu3LkcPnyYe++9l5tuuolHH310zDMMrEOpVOJ//ud/uOeee1i1ahULFy7kgx/84JjXPzLDkVpbW3nVq17VkPqpfeELX+DCCy/kzW9+M9deey1z586lWCzy4IMP8rOf/Yzzzz8/dcQJwz1qiPvTS3McyT3KParR3J+GuD+9NMeR3J/cnxrN/WmI+9NLcxzJ/WkC7E9ZcAsXLswuu+yyl/3Z/fffnwHZI488MuY5rrzyygwY/Gpvb8/e8pa3ZN/61rfGvPax9uzZk1199dXZGWeckZ1wwgnZr/3ar2Xvfve7s//4j/8Y89pHrkNra2s2derU7JJLLsm+/OUvZ6VSaczrH5vhyK/Zs2c3pP6ROd7znvc0tOaR9uzZk/3xH/9xduaZZ2aTJk3KJk+enP36r/96dsMNN2TPPPPMmNc/3v/+//Ef/5EB2b59+8Y8QwTuUUeb6PvTsTlS7VGp96csS7tHuT/l3J+O5v7k/jTAv0Ol5/50NPcn96cBE3F/KmRZ8KerSZIkSZIkqemEf6aUJEmSJEmSmo+HUpIkSZIkSWo4D6UkSZIkSZLUcB5KSZIkSZIkqeE8lJIkSZIkSVLDeSglSZIkSZKkhvNQSpIkSZIkSQ3noZQkSZIkSZIazkMpSZIkSZIkNZyHUpIkSZIkSWo4D6UkSZIkSZLUcB5KSZIkSZIkqeE8lJIkSZIkSVLDeSglSZIkSZKkhvNQSpIkSZIkSQ3noZQkSZIkSZIarrXRBcvlMnv27KG9vZ1CodDo8pICyrKM/fv3M336dIpFz8olSZIkaSJo+KHUnj176OrqanRZSeNAb28vM2bMSB1DkiRJktQADT+Uam9vH/z+5GmNrg7PPgFkQAFOPr3x9c1ghmgZUtcHeHZv/j+P3B8kSZIkSc2t4YdSA2/ZO3kafGBPo6vDrTPgmV/BKdNhye7G1zeDGaJlSF0f4Jbp+cGUb+mVJEmSpInDh7dIkiRJkiSp4TyUkiRJkiRJUsN5KCVJkiRJkqSG81BKkiRJkiRJDdfwB51XawpdzGMpp9HNibTzPPt5kh62sJ599JphAmVIXd8MsTJIkiRJksan8IdS3cxnAcuZw0IyygAUKVJ+8fuFXMs27mQja+hhsxmaOEPq+maIlUGSJEmSNL6FfvveApazgk2cw6UUKdJCKy20Ujji+yJF5nAZK7iPS1hmhibNkLq+GWJlkCRJkiSNf2EPpS5hGVewGoAWJg37uwM/X8yaur4ANkOMDKnrmyFWBkmSJElScwh5KNXNfBazpqprF7OGbi4yQ5NkSF3fDLEySJIkSZKaR8WHUvfddx+LFi1i+vTpFAoF/u3f/q3uoRawnBKHqrq2xKG63JVhhhgZUtc3Q6wMkiRJkqTmUfGh1DPPPMO5557L5z//+bHIwxS6mMPCEd8adDwtTGIu72YKM8wwzjOkrm+GWBkkSZIkSc2l4kOpSy+9lE996lO8973vHYs8zGPp4Kd5VSujzDyuMsM4z5C6vhliZZAkSZIkNZfWsS5w8OBBDh48OPjP/f39w/7+aXTXoWrGVGZVfbUZYmRIXd8MsTJIkiRJkprLmD/ofNWqVXR2dg5+dXV1Dfv7J9JOscZYRVo4iY6qrzdDjAyp65shVgZJkiRJUnMZ80OplStX0tfXN/jV29s77O8/z37KNb5NqEyJ5xj+jiwzxM+Qur4ZYmWQJEmSJDWXMX/7XltbG21tbaP+/SfpqUPVAk+xs+qrzRAjQ+r6ZoiVQZIkSZLUXMb8TqlKbWE9hRpjFSiyhXVmGOcZUtc3Q6wMkiRJkqTmUvGrzAMHDvCTn/yEn/zkJwD893//Nz/5yU/YtWtXXQLto5ftbKDEoaquL3GIbdzBPnabYZxnSF3fDLEySJIkSZKaS8WHUg899BDnnXce5513HgDLli3jvPPO45Of/GTdQt3LalqYVNW1RVrYyFozNEmG1PXNECuDJEmSJKl5VHwodfHFF5Nl2Uu+1q9fX7dQPWzmNpZXde23uIYeNpuhSTKkrm+GWBkkSZIkSc0j3DOlBmxk7eAL4JHeMjTw89tYXte7McwQI0Pq+maIlUGSJEmS1BzG/NP3arGRtTzOg1zCMubybrIXP5K+SJEyJaBAgSLbuYuNrB2TOzHMECND6vpmiJVBkiRJkjT+hT6UgvwtQz1sZgozmMdVTGUWJ9HBc/TzFDvZwroxf3iyGWJkSF3fDLEySJIkSZLGt/CHUgP2sZu7uM4MZkhe3wyxMkiSJEmSxqewz5SSJEmSJElS8/JQSpIkSZIkSQ3noZQkSZIkSZIazkMpSZIkSZIkNVwhy7KskQX7+/vp7OyEApwyvZGVc8/uhawMhSKcPK3x9c1ghmgZUtcHeGYPkEFfXx8dHR1pQkiSJEmSGirdoZQkHcNDKUmSJEmaOFqTVfZOKTOYIUSG1PVh6E4pSZIkSdLEkexQ6uTTYcnuxte9dQY886v8xXeK+mYwQ7QMqesD3DI9PxyTJEmSJE0cPuhckiRJkiRJDeehlCRJkiRJkhrOQylJkiRJkiQ1nIdSkiRJkiRJajgPpSRJkiRJktRwyT59r1JT6GIeSzmNbk6knefZz5P0sIX17KPXDBMow4FdsGM99PXAof0wqR06u2H2Upg8c8zLA+nXwAySJEmSpPEu/KFUN/NZwHLmsJCMMgBFipRf/H4h17KNO9nIGnrYbIYmzrBnE2xbA7s2QOHFe/yyEhRa8u8fvhbOWAhzV8C0+XUvD6RfAzNIkiRJkppF6LfvLWA5K9jEOVxKkSIttNJCK4Ujvi9SZA6XsYL7uIRlZmjCDFkGj6yGDRdD791Alh9GZaUXfz7wfQa77oY735ofXmVZ3SIA9iFSBkmSJEnS+Bf2UOoSlnEFqwFoYdKwvzvw88WsqesLYDPEyLB9Ldx/Tf59dnj43x34+dYV+XX1knoNzCBJkiRJajYVHUqtWrWKt7zlLbS3t3Paaafx27/92+zYsaPuobqZz2LWVHXtYtbQzUVmaJIMezblB0zV2LoC9t5XU3kg/RqYQZIkSZLUjCo6lNq0aRNXX301W7du5d577+XQoUO84x3v4JlnnqlrqAUsp8Shqq4tcagud2WYIUaGbWugUOWTzwqt+fW1Sr0GZpAkSZIkNaOKXu7fc889R/3z+vXrOe2003j44YeZP78+T5aeQhdzWEixyncWtjCJubybKcxgH7vNMI4zHNiVP9ScKp8NlR2Gx++EA70wuau6PyP1GphBkiRJktSsanqmVF9fHwCvfOUr6xIGYB5LBz/Nq1oZZeZxlRnGeYYd64c+Za9ahSLsWFf99anXwAySJEmSpGZV5RujoFwu86d/+qdceOGFnHPOOcf9vYMHD3Lw4MHBf+7v7x/2zz2N7mojHSFjKrOqvtoMMTL09dShPNC/s/prU6+BGSRJkiRJzarq+1Cuvvpq/uu//ouvf/3rw/7eqlWr6OzsHPzq6hr+fVQn0l71W4QGFGnhJDqqvt4MMTIc2g9ZqabyZCV4Yfhz0GGlXgMzSJIkSZKaVVWvMv/4j/+YDRs28B//8R/MmDFj2N9duXIlfX19g1+9vb3D/v7z7Kdc49uEypR4jupPIswQI8Okdii01FSeQgucUMM5SOo1MIMkSZIkqVlV9Pa9LMv42Mc+xu23384PfvADzjzzzBGvaWtro62tbdQ1nqQe79kq8BTVv2fLDDEydNbjHWNARw3vGEu9BmaQJEmSJDWriu6Uuvrqq7nlllv46le/Snt7O0888QRPPPEEzz33XN0CbWE9hRrfJlSgyBaqf7q1GWJkmL0UstpuziErw+wanq2deg3MIEmSJElqVhW9yrzpppvo6+vj4osvZtq0aYNf3/jGN+oWaB+9bGcDJQ5VdX2JQ2zjjpo+dt4MMTJMngkzF0KhysfxF1rhjEUwefjHmA0r9RqYQZIkSZLUrCo6lMqy7GW/li5dWtdQ97KaFiZVdW2RFjay1gxNkuHcFZAdru7arARzl9dUHki/BmaQJEmSJDWj2t6PM0Z62MxtVHea8C2uoYfNZmiSDNPmwwWrq7v2ghvy62uVeg3MIEmSJElqRiEPpQA2snbwBfBIbxka+PltLK/r3RhmiJFhzrKhg6mR3so38PMLVufX1UvqNTCDJEmSJKnZVPm0nsbYyFoe50EuYRlzeTfZix9JX6RImRJQoECR7dzFRtaOyZ0YZkifoVDI34Y39S2wbQ08ficUXjxOzUpQaHnx+zLMvCz/3XrcIXWsid6HSBkkSZIkSeNf6EMpyN8y1MNmpjCDeVzFVGZxEh08Rz9PsZMtrBvzhyebIUaGafPzrwO9sGMd9O+EF/rhhA7omJV/yl4tDzUfjdRrYAZJkiRJUrMIfyg1YB+7uYvrzGAGJnfB+Z9MVh5IvwZmkCRJkiSNd2GfKSVJkiRJkqTm5aGUJEmSJEmSGs5DKUmSJEmSJDWch1KSJEmSJElquEKWZVkjC/b399PZ2QkFOGV6Iyvnnt0LWRkKRTh5WuPrm8EM0TKkrg/wzB4gg76+Pjo6OtKEkCRJkiQ1VLpDKUk6hodSkiRJkjRxtCar7J1SZjBDiAyp68PQnVKSJEmSpIkj2aHUyafDkt2Nr3vrDHjmV/mL7xT1zWCGaBlS1we4ZXp+OCZJkiRJmjh80LkkSZIkSZIazkMpSZIkSZIkNZyHUpIkSZIkSWo4D6UkSZIkSZLUcOk+fa9CU+hiHks5jW5OpJ3n2c+T9LCF9eyjtyEZDuyCHeuhrwcO7YdJ7dDZDbOXwuSZDYlgBmLMQoQMqfsAMdZBkiRJkjQ+hT+U6mY+C1jOHBaSUQagSJHyi98v5Fq2cScbWUMPm8ckw55NsG0N7NoAhRfvLctKUGjJv3/4WjhjIcxdAdPmj0kEMxBjFiJkSN0HiLEOkiRJkqTxLfTb9xawnBVs4hwupUiRFlppoZXCEd8XKTKHy1jBfVzCsrrWzzJ4ZDVsuBh67way/MV/Vnrx5wPfZ7DrbrjzrflhQZaZod4ZUs9ChAwR+gDp10GSJEmS1BzCHkpdwjKuYDUALUwa9ncHfr6YNXV9Abx9Ldx/Tf59dnj43x34+dYV+XVmqF+GCLMQIUPqPkCMdZAkSZIkNYeQh1LdzGcxa6q6djFr6OaimjPs2ZS/oK/G1hWw976aI5iBGLMQIUPqPkCMdZAkSZIkNY+KDqVuuukm5s6dS0dHBx0dHfzmb/4md999d91DLWA5JQ5VdW2JQ3W5K2PbGihU+cStQmt+vRlqzxBhFiJkSN0HiLEOkiRJkqTmUdGh1IwZM/i7v/s7Hn74YR566CF+67d+i/e85z38f//f/1e3QFPoYg4LR3xr0PG0MIm5vJspzKg6w4Fd+UOkR3qL1PFkh+HxO+FADR8+ZoYYsxAhQ+o+QIx1kCRJkiQ1l4oOpRYtWsRll11Gd3c3r3vd6/j0pz/N5MmT2bp1a90CzWPp4Kd5VSujzDyuqvr6HeuHPtWsWoUi7FhX/fVmiDELETKk7gPEWAdJkiRJUnOp8g1BUCqVuO2223jmmWf4zd/8zeP+3sGDBzl48ODgP/f39w/7555Gd7WRjpAxlVlVX93XU4cIQP/O6q81Q4xZiJAhdR8gxjpIkiRJkppLxfdfbN++ncmTJ9PW1saHP/xhbr/9dt7whjcc9/dXrVpFZ2fn4FdXV9ewf/6JtFOs8fnrRVo4iY6qrz+0H7JSTRHISvDC8OdvZhhBhFmIkCF1HyDGOkiSJEmSmkvFrzJnz57NT37yE+6//34+8pGPcOWVV/LTn/70uL+/cuVK+vr6Br96e4d/sM3z7Kdc49uEypR4jupfgU9qh0JLTREotMAJNbz+NkOMWYiQIXUfIMY6SJIkSZKaS8Vv3zvhhBOYNSt/C87555/Pgw8+yD/8wz/wxS9+8WV/v62tjba2tlH/+U9Sj/cqFXiK6t+r1FmPdyoBHTW8U8kMMWYhQobUfYAY6yBJkiRJai41Pj4ZyuXyUc+MqtUW1lOoMVaBIluo/qnOs5dCVttNIWRlmF3DM53NEGMWImRI3QeIsQ6SJEmSpOZS0avMlStXct999/HYY4+xfft2Vq5cyQ9+8AOWLFlSt0D76GU7GyhxqKrrSxxiG3ewj91VZ5g8E2YuhEKVj4EvtMIZi2Dy8I/PMsMIIsxChAyp+wAx1kGSJEmS1FwqOpR68skn+eAHP8js2bN5+9vfzoMPPsh3vvMdFixYUNdQ97KaFiZVdW2RFjaytuYM566A7HB112YlmLu85ghmIMYsRMiQug8QYx0kSZIkSc2jokOpm2++mccee4yDBw/y5JNPsnHjxrofSAH0sJnbqO5V9Le4hh4215xh2ny4YHV1115wQ369GWrPEGEWImRI3QeIsQ6SJEmSpOZR8zOlxspG1g6+AB7pLUMDP7+N5XW9G2POsqGDgJHeOjXw8wtW59eZoX4ZIsxChAyp+wAx1kGSJEmS1BzCHkpB/gJ4NfPZzl2UKVPiMCUOk1GmxCFKHKZMme3cxWrm1/2Fb6GQv+1p0SaYeRlQgEJL/gVHfF/If75oU/77hYIZ6p0h9SxEyBChD5B+HSRJkiRJzaHKRyc3Tg+b6WEzU5jBPK5iKrM4iQ6eo5+n2MkW1o35w5Onzc+/DvTCjnXQvxNe6IcTOqBjVv6pZrU8RNoMoxNhFiJkSN0HiLEOkiRJkqTxLfyh1IB97OYurkuaYXIXnP/JpBHMQIxZiJAhdR8gxjpIkiRJksan0G/fkyRJkiRJUnPyUEqSJEmSJEkN56GUJEmSJEmSGs5DKUmSJEmSJDWch1KSJEmSJElquEKWZVkjC/b399PZ2QkFOGV6Iyvnnt0LWRkKRTh5WuPrm8EM0TKkrg/wzB4gg76+Pjo6OtKEkCRJkiQ1VLpDKUk6hodSkiRJkjRxtCar7J1SZjBDiAyp68PQnVKSJEmSpIkj2aHUyafDkt2Nr3vrDHjmV/mL7xT1zWCGaBlS1we4ZXp+OCZJkiRJmjh80LkkSZIkSZIazkMpSZIkSZIkNZyHUpIkSZIkSWo4D6UkSZIkSZLUcOk+fa9CU+hiHks5jW5OpJ3n2c+T9LCF9eyjtyEZDuyCHeuhrwcO7YdJ7dDZDbOXwuSZDYkQIkPqXqSuDzH6ECFDhF5IkiRJksan8IdS3cxnAcuZw0IyygAUKVJ+8fuFXMs27mQja+hh85hk2LMJtq2BXRug8OK9ZVkJCi359w9fC2cshLkrYNr8MYkQIkPqXqSuDzH6ECFDhF5IkiRJksa30G/fW8ByVrCJc7iUIkVaaKWFVgpHfF+kyBwuYwX3cQnL6lo/y+CR1bDhYui9G8jyF/9Z6cWfD3yfwa674c635ocFWdZcGSB9L1LXj9CHCBkgfS8kSZIkSc0h7KHUJSzjClYD0MKkYX934OeLWVPXF8Db18L91+TfZ4eH/92Bn29dkV/XTBlS9yJ1fYjRhwgZIvRCkiRJktQcajqU+ru/+zsKhQJ/+qd/Wqc4uW7ms5g1VV27mDV0c1HNGfZsyl/QV2PrCth7X80RQmRI3YvU9SFGHyJkiNALSZIkSVLzqPpQ6sEHH+SLX/wic+fOrWceIH97UIlDVV1b4lBd7srYtgYKVT5xq9CaX98MGVL3InV9iNGHCBki9EKSJEmS1DyqOpQ6cOAAS5Ys4Utf+hJTpkypa6ApdDGHhSO+Neh4WpjEXN7NFGZUneHArvwh0iO9Rep4ssPw+J1woIYPH4uQIXUvUteHGH2IkCFCLyRJkiRJzaWqQ6mrr76ayy+/nEsuuaTeeZjH0sFP86pWRpl5XFX19TvWD32qWbUKRdixrvrrI2RI3YvU9SFGHyJkiNALSZIkSVJzqfgNQV//+tf58Y9/zIMPPjiq3z948CAHDx4c/Of+/v5hf/80uiuN9DIypjKr6qv7euoQAejfWf21ETKk7kXq+hCjDxEyROiFJEmSJKm5VHT/RW9vLx//+Me59dZbOfHEE0d1zapVq+js7Bz86urqGvb3T6SdYo0fClikhZPoqPr6Q/shK9UUgawELwx//hY+Q+pepK4PMfoQIUOEXkiSJEmSmktFrzIffvhhnnzySd70pjfR2tpKa2srmzZt4h//8R9pbW2lVHrpK+eVK1fS19c3+NXbO/yDbZ5nP+Ua3yZUpsRzVP8KfFI7FFpqikChBU6o4fV3hAype5G6PsToQ4QMEXohSZIkSWouFb197+1vfzvbt28/6t9dddVVnH322fzFX/wFLS0vfeXc1tZGW1vbqGs8ST3eq1TgKap/r1JnPd6pBHTU8E6lCBlS9yJ1fYjRhwgZIvRCkiRJktRcKrpTqr29nXPOOeeor1NOOYVTTz2Vc845py6BtrCeQo1vEypQZAvVP9V59lLIarsphKwMs2t4pnOEDKl7kbo+xOhDhAwReiFJkiRJai41fqZX/e2jl+1soMShqq4vcYht3ME+dledYfJMmLkQChU/Bj5XaIUzFsHk4R+fFT5D6l6krg8x+hAhQ4ReSJIkSZKaS82HUj/4wQ/47Gc/W4coQ+5lNS1MquraIi1sZG3NGc5dAdnh6q7NSjB3ec0RQmRI3YvU9SFGHyJkiNALSZIkSVLzCHenFEAPm7mN6l5Ff4tr6GFzzRmmzYcLVld37QU35Nc3Q4bUvUhdH2L0IUKGCL2QJEmSJDWPkIdSABtZO/gCeKS3DA38/DaW1/VujDnLhg4CRnrr1MDPL1idX9dMGVL3InV9iNGHCBki9EKSJEmS1BzCHkpB/gJ4NfPZzl2UKVPiMCUOk1GmxCFKHKZMme3cxWrm1/2Fb6GQv+1p0SaYeRlQgEJL/gVHfF/If75oU/77hUJzZYD0vUhdP0IfImSA9L2QJEmSJDWHKh+d3Dg9bKaHzUxhBvO4iqnM4iQ6eI5+nmInW1g35g9PnjY//zrQCzvWQf9OeKEfTuiAjln5p5rV8hDp8ZIhdS9S14cYfYiQIUIvJEmSJEnjW/hDqQH72M1dXJc0w+QuOP+TSSOEyJC6F6nrQ4w+RMgQoReSJEmSpPEp9Nv3JEmSJEmS1Jw8lJIkSZIkSVLDeSglSZIkSZKkhvNQSpIkSZIkSQ1XyLIsa2TB/v5+Ojs7oQCnTG9k5dyzeyErQ6EIJ09rfH0zmCFahtT1AZ7ZA2TQ19dHR0dHmhCSJEmSpIZKdyglScfwUEqSJEmSJo7WZJW9U8oMZgiRIXV9GLpTSpIkSZI0cSQ7lDr5dFiyu/F1b50Bz/wqf/Gdor4ZzBAtQ+r6ALdMzw/HJEmSJEkThw86lyRJkiRJUsN5KCVJkiRJkqSG81BKkiRJkiRJDeehlCRJkiRJkhou3afvVWgKXcxjKafRzYm08zz7eZIetrCeffQ2JMOBXbBjPfT1wKH9MKkdOrth9lKYPLMhEVyHAPXNMCTCPEqSJEmSxqfwh1LdzGcBy5nDQjLKABQpUn7x+4VcyzbuZCNr6GHzmGTYswm2rYFdG6Dw4r1lWQkKLfn3D18LZyyEuStg2vwxieA6BKhvhiER5lGSJEmSNL6FfvveApazgk2cw6UUKdJCKy20Ujji+yJF5nAZK7iPS1hW1/pZBo+shg0XQ+/dQJa/+M9KL/584PsMdt0Nd741PyzIsrrGmPDrkLq+GY6Weh4lSZIkSc0h7KHUJSzjClYD0MKkYX934OeLWVPXF8Db18L91+TfZ4eH/92Bn29dkV9XL65D+vpmGBJhHiVJkiRJzSHkoVQ381nMmqquXcwaurmo5gx7NuUv6KuxdQXsva/mCK5DgPpmGBJhHiVJkiRJzaOiQ6lrr72WQqFw1NfZZ59d91ALWE6JQ1VdW+JQXe7K2LYGClU+cavQml9fK9chfX0zDIkwj5IkSZKk5lHxnVJvfOMb2bt37+DXD3/4w7oGmkIXc1g44luDjqeFSczl3UxhRtUZDuzKHyI90lukjic7DI/fCQdq+PAx1yF9fTMMiTCPkiRJkqTmUvGhVGtrK6effvrg16te9aq6BprH0sFP86pWRpl5XFX19TvWD32qWbUKRdixrvrrXYf09c0wJMI8SpIkSZKaS8UvdXt6epg+fTpnnXUWS5YsYdeuXcP+/sGDB+nv7z/qazin0V1ppJeRMZVZVV/d11OHCED/zuqvdR3S1zfDkAjzKEmSJElqLhUdSv3Gb/wG69ev55577uGmm27iv//7v7nooovYv3//ca9ZtWoVnZ2dg19dXV3D1jiRdoo1Pn+9SAsn0VH19Yf2Q1aqKQJZCV4Y/vxtWK5D+vpmGBJhHiVJkiRJzaWiV5mXXnopixcvZu7cubzzne/k3//933n66af55je/edxrVq5cSV9f3+BXb+/wD7Z5nv2Ua3ybUJkSz1H9K/BJ7VBoqSkChRY4oYbX365D+vpmGBJhHiVJkiRJzaXKz/PKveIVr+B1r3sdO3ce/31BbW1ttLW1jfrPfJJ6vFepwFNU/16lznq8UwnoqOGdSq5D+vpmGBJhHiVJkiRJzaWm9+McOHCAX/ziF0ybNq1eedjCego1vk2oQJEtVP9U59lLIavtphCyMsyu4ZnOrkP6+mYYEmEeJUmSJEnNpaJXmStWrGDTpk089thjbNmyhfe+9720tLTw/ve/v26B9tHLdjZQ4lBV15c4xDbuYB+7q84weSbMXAiFKu8jK7TCGYtg8vCPzxqW65C+vhmGRJhHSZIkSVJzqehQavfu3bz//e9n9uzZ/M7v/A6nnnoqW7duZerUqXUNdS+raWFSVdcWaWEja2vOcO4KyA5Xd21WgrnLa47gOgSob4YhEeZRkiRJktQ8KjqU+vrXv86ePXs4ePAgu3fv5utf/zqvfe1r6x6qh83cRnWvor/FNfSwueYM0+bDBauru/aCG/Lra+U6pK9vhiER5lGSJEmS1Dxqe0jMGNrI2sEXwCO9ZWjg57exvK53Y8xZNnQQMNJbpwZ+fsHq/Lp6cR3S1zfDkAjzKEmSJElqDmEPpSB/Abya+WznLsqUKXGYEofJKFPiECUOU6bMdu5iNfPr/sK3UMjf9rRoE8y8DChAoSX/giO+L+Q/X7Qp//1Coa4xJvw6pK5vhqOlnkdJkiRJUnOo8tHJjdPDZnrYzBRmMI+rmMosTqKD5+jnKXayhXVj/vDkafPzrwO9sGMd9O+EF/rhhA7omJV/qlktD5EeDdchfX0zDIkwj5IkSZKk8S38odSAfezmLq5LmmFyF5z/yaQRXIcA9c0wJMI8SpIkSZLGp9Bv35MkSZIkSVJz8lBKkiRJkiRJDeehlCRJkiRJkhrOQylJkiRJkiQ1nIdSkiRJkiRJarhClmVZIwv29/fT2dkJBThleiMr557dC1kZCkU4eVrj65vBDNEypK4P8MweIIO+vj46OjrShJAkSZIkNVS6QylJOoaHUpIkSZI0cbQmq+ydUmYwQ4gMqevD0J1SkiRJkqSJI9mh1Mmnw5Ldja976wx45lf5i+8U9c1ghmgZUtcHuGV6fjgmSZIkSZo4fNC5JEmSJEmSGs5DKUmSJEmSJDWch1KSJEmSJElqOA+lJEmSJEmS1HDpPn2vQgd2wY710NcDh/bDpHbo7IbZS2HyTDNMpAyp6wNMoYt5LOU0ujmRdp5nP0/SwxbWs4/ehmRwHSRJkiRJ41n4Q6k9m2DbGti1If/IeoCsBIWW/PuHr4UzFsLcFTBtvhmaOUPq+gDdzGcBy5nDQjLKABQpUn7x+4VcyzbuZCNr6GHzmGRwHSRJkiRJzSDs2/eyDB5ZDRsuht67gSx/4Z2VXvz5wPcZ7Lob7nxr/kI9y8zQbBlS1x+wgOWsYBPncClFirTQSgutFI74vkiROVzGCu7jEpbVtb7rIEmSJElqJmEPpbavhfuvyb/PDg//uwM/37oiv84MzZUhdX2AS1jGFawGoIVJw/7uwM8Xs6auBzKugyRJkiSpmVR8KPWrX/2KD3zgA5x66qmcdNJJzJkzh4ceeqiuofZsyl9MV2PrCth7nxmaJUPq+pC/VW0xa6q6djFr6OaimjO4DpIkSZKkZlPRodS+ffu48MILmTRpEnfffTc//elPWbNmDVOmTKlrqG1roFDl064Krfn1ZmiODKnrQ/52tRKHqrq2xKG63CXkOkiSJEmSmk1FL3M/85nP0NXVxbp16wb/3ZlnnlnXQAd25Q9wpsrn4GSH4fE74UAvTO4yw3jOkLo+5J8uN4eFFKt8p2sLk5jLu5nCDPaxu6o/w3WQJEmSJDWjil5h3nHHHbz5zW9m8eLFnHbaaZx33nl86UtfqmugHeuHPlGsWoUi7Fg38u+ZIXaG1PUB5rF08NPlqpVRZh5XVX296yBJkiRJakYVvdT95S9/yU033UR3dzff+c53+MhHPsKf/Mmf8JWvfOW41xw8eJD+/v6jvobT11NJouPr31n9tWaIkSF1fYDT6K5DgoypzKr6atdBkiRJktSMKnr7Xrlc5s1vfjPXX389AOeddx7/9V//xT/90z9x5ZVXvuw1q1at4m/+5m9GXePQ/qGPuK9WVoIXhj/7MsM4yJC6PsCJtFf9lrUBRVo4iY6qr3cdJEmSJEnNqKJXmdOmTeMNb3jDUf/u9a9/Pbt27TruNStXrqSvr2/wq7e3d9gak9qh0FJJqpcqtMAJNbz2NUOMDKnrAzzPfso1vm2tTInnqP5EyHWQJEmSJDWjiu6UuvDCC9mxY8dR/+7nP/85Z5xxxnGvaWtro62tbdQ1OuvxLiGgo4Z3CZkhRobU9QGepB7vnSvwFNW/d851kCRJkiQ1o4rulPqzP/sztm7dyvXXX8/OnTv56le/yj//8z9z9dVX1y3Q7KWQ1XZDBlkZZtfwPGUzxMiQuj7AFtZTqPFtawWKbKH6p4y7DpIkSZKkZlTRq8y3vOUt3H777Xzta1/jnHPO4brrruOzn/0sS5YsqVugyTNh5kIoVHQP15BCK5yxCCZ3mWG8Z0hdH2AfvWxnAyUOVXV9iUNs4w72sbvqDK6DJEmSJKkZVXzrw8KFC9m+fTvPP/88jz76KH/4h39Y91DnroDscHXXZiWYu9wMzZIhdX2Ae1lNC5OqurZICxtZW3MG10GSJEmS1Gxqez/OGJk2Hy5YXd21F9yQX2+G5siQuj5AD5u5jepOdb7FNfSwueYMroMkSZIkqdmEPJQCmLNs6EX4SG9bGvj5Bavz68zQXBlS1wfYyNrBA5mR3sI28PPbWF7Xu4NcB0mSJElSMwl7KFUo5G85WrQJZl4GFPKPtS+0vPjzge8L+c8Xbcp/v1AwQ7NlSF1/wEbWspr5bOcuypQpcZgSh8koU+IQJQ5Tpsx27mI18+t+EOM6SJIkSZKaSZWPTm6cafPzrwO9sGMd9O+EF/rhhI78I+5nX1XbA5zNMH4ypK4P+VvYetjMFGYwj6uYyixOooPn6OcpdrKFdWP+MG/XQZIkSZLUDMIfSg2Y3AXnf9IMZkhfH2Afu7mL65JmcB0kSZIkSeNZ2LfvSZIkSZIkqXl5KCVJkiRJkqSG81BKkiRJkiRJDeehlCRJkiRJkhqukGVZ1siC/f39dHZ2QgFOmd7Iyrln90JWhkIRTp7W+PpmMEO0DKnrAzyzB8igr6+Pjo6ONCEkSZIkSQ2V7lBKko7hoZQkSZIkTRytySp7p5QZzBAiQ+r6MHSnlCRJkiRp4kh2KHXy6bBkd+Pr3joDnvlV/uI7RX0zmCFahtT1AW6Znh+OSZIkSZImDh90LkmSJEmSpIbzUEqSJEmSJEkN56GUJEmSJEmSGs5DKUmSJEmSJDVcuk/fq9CBXbBjPfT1wKH9MKkdOrth9lKYPHPiZJhCF/NYyml0cyLtPM9+nqSHLaxnH70TIkPq+hBjFiJkiNALSZIkSdL4FP5Qas8m2LYGdm3IP7IeICtBoSX//uFr4YyFMHcFTJvfvBm6mc8CljOHhWSUAShSpPzi9wu5lm3cyUbW0MPmpsyQuj7EmIUIGSL0QpIkSZI0voV9+16WwSOrYcPF0Hs3kOUvvLPSiz8f+D6DXXfDnW/NX6hnWXNlAFjAclawiXO4lCJFWmilhVYKR3xfpMgcLmMF93EJy+obIECG1PUjzEKEDJC+F5IkSZKk5hD2UGr7Wrj/mvz77PDwvzvw860r8uuaKcMlLOMKVgPQwqRhf3fg54tZU9eDgNQZUteHGLMQIUOEXkiSJEmSmkPIQ6k9m/IX09XYugL23tccGbqZz2LWVHXtYtbQzUXjPkPq+hBjFiJkiNALSZIkSVLzqOhQ6jWveQ2FQuElX1dffXVdQ21bA4Uqn3ZVaM2vb4YMC1hOiUNVXVviUF3uTkmdIXV9iDELETJE6IUkSZIkqXlUdCj14IMPsnfv3sGve++9F4DFixfXLdCBXfkDnEd6e9LxZIfh8TvhQA0f/BUhwxS6mMPCEd8idTwtTGIu72YKM8ZthtT1IcYsRMgQoReSJEmSpOZS0aHU1KlTOf300we/NmzYwGtf+1re+ta31i3QjvVDnyhWrUIRdqwb3xnmsXTwU82qlVFmHleN2wyp60OMWYiQIUIvJEmSJEnNpco3BMELL7zALbfcwrJlyygUCsf9vYMHD3Lw4MHBf+7v7x/2z+3rqTbR0fp3Vn9thAyn0V2HBBlTmTVuM6SuDzFmIUKGCL2QJEmSJDWXqu+/+Ld/+zeefvppli5dOuzvrVq1is7OzsGvrq6uYX//0P6hj7ivVlaCF4Y/+wqf4UTaKdb4HPoiLZxEx7jNkLo+xJiFCBki9EKSJEmS1FyqfpV58803c+mllzJ9+vRhf2/lypX09fUNfvX2Dv9gm0ntUGipNlWu0AIn1PDaN0KG59lPuca3S5Up8RzVn0SkzpC6PsSYhQgZIvRCkiRJktRcqnr73uOPP87GjRv59re/PeLvtrW10dbWNuo/u7Me7xICOmp4l1CEDE9Sj/dsFXiK6t+zlTpD6voQYxYiZIjQC0mSJElSc6nqTql169Zx2mmncfnll9c7D7OXQlbbDRlkZZhdw/OUI2TYwnoKNb5dqkCRLVT/dOvUGVLXhxizECFDhF5IkiRJkppLxa8yy+Uy69at48orr6S1ternpB/X5JkwcyEUqvyjC61wxiKYPPyjq8Jn2Ecv29lAiUNVXV/iENu4g33sHrcZUteHGLMQIUOEXkiSJEmSmkvFh1IbN25k165dfOhDHxqLPACcuwKyw9Vdm5Vg7vLmyHAvq2lhUlXXFmlhI2vHfYbU9SHGLETIEKEXkiRJkqTmUfGh1Dve8Q6yLON1r3vdWOQBYNp8uGB1dddecEN+fTNk6GEzt1HdacK3uIYeNo/7DKnrQ4xZiJAhQi8kSZIkSc2jtofEjKE5y4ZehI/0tqWBn1+wOr+umTJsZO3gQcBIb50a+PltLK/rXSmpM6SuDzFmIUKGCL2QJEmSJDWHsIdShUL+lqNFm2DmZUAh/1j7QsuLPx/4vpD/fNGm/PcLhebKAPlBwGrms527KFOmxGFKHCajTIlDlDhMmTLbuYvVzB+TA4DUGVLXjzALETJA+l5IkiRJkppD/Z9UXmfT5udfB3phxzro3wkv9MMJHflH3M++qrYHOI+XDD1spofNTGEG87iKqcziJDp4jn6eYidbWDfmD5FOnSF1fYgxCxEyROiFJEmSJGl8C38oNWByF5z/STPsYzd3cd2EzpC6PsSYhQgZIvRCkiRJkjQ+hX37niRJkiRJkpqXh1KSJEmSJElqOA+lJEmSJEmS1HAeSkmSJEmSJKnhPJSSJEmSJElSwxWyLMsaWbC/v5/Ozk4owCnTG1k59+xeyMpQKMLJ0xpf3wxmiJYhdX2AZ/YAGfT19dHR0ZEmhCRJkiSpodIdSknSMTyUkiRJkqSJozVZZe+UMoMZQmRIXR+G7pSSJEmSJE0cyQ6lTj4dluxufN1bZ8Azv8pffKeobwYzRMuQuj7ALdPzwzFJkiRJ0sThg84lSZIkSZLUcB5KSZIkSZIkqeE8lJIkSZIkSVLDeSglSZIkSZKkhkv36XsVOrALdqyHvh44tB8mtUNnN8xeCpNnNibDFLqYx1JOo5sTaed59vMkPWxhPfvoNUODMqSub4ZYGSRJkiRJ41P4Q6k9m2DbGti1If/IeoCsBIWW/PuHr4UzFsLcFTBt/thk6GY+C1jOHBaSUQagSJHyi98v5Fq2cScbWUMPm80wRhlS1zdDrAySJEmSpPEt7Nv3sgweWQ0bLobeu4EsP4zKSi/+fOD7DHbdDXe+NT+8yrL65ljAclawiXO4lCJFWmilhVYKR3xfpMgcLmMF93EJy+obwAwh6pshVgZJkiRJ0vgX9lBq+1q4/5r8++zw8L878POtK/Lr6uUSlnEFqwFoYdKwvzvw88WsqeuLcDOkr2+GWBkkSZIkSc0h5KHUnk35AVM1tq6AvffVnqGb+SxmTVXXLmYN3VxkhjpkSF3fDLEySJIkSZKaR0WHUqVSib/6q7/izDPP5KSTTuK1r30t1113HVmd3zO3bQ0UqnzaVaE1v75WC1hOiUNVXVviUF3uDDFD+vpmiJVBkiRJktQ8KjqU+sxnPsNNN93EjTfeyKOPPspnPvMZ/v7v/57Pfe5zdQt0YFf+UPOR3rJ3PNlhePxOOFDDB39NoYs5LBzx7UnH08Ik5vJupjDDDDVkSF3fDLEySJIkSZKaS0WHUlu2bOE973kPl19+Oa95zWu44ooreMc73sEDDzxQt0A71g99yl61CkXYsa766+exdPATxaqVUWYeV5mhhgyp65shVgZJkiRJUnOp6Phn3rx5fO973+PnP/85AI888gg//OEPufTSS497zcGDB+nv7z/qazh9PZUkOr7+ndVfexrddUiQMZVZZqghQ+r6ZoiVQZIkSZLUXCp6ctMnPvEJ+vv7Ofvss2lpaaFUKvHpT3+aJUuWHPeaVatW8Td/8zejrnFoP2SlSlK9VFaCF4Y/+xrWibRTrPEZ8EVaOIkOM9SQIXV9M8TKIEmSJElqLhW9yvzmN7/Jrbfeyle/+lV+/OMf85WvfIXVq1fzla985bjXrFy5kr6+vsGv3t7hH/Y0qR0KLZWkeqlCC5xQw2vf59lPuca3KpUp8RzVn4yZIX19M8TKIEmSJElqLhXdKXXNNdfwiU98gt/7vd8DYM6cOTz++OOsWrWKK6+88mWvaWtro62tbdQ1OuvxLiGgo4Z3CT1JPd5DWOApqn8PoRnS1zdDrAySJEmSpOZS0Z1Szz77LMXi0Ze0tLRQLtd2B8WRZi+FrMY/LivD7Bqep7yF9RRqfKtSgSJbqP5p62ZIX98MsTJIkiRJkppLRa8yFy1axKc//WnuuusuHnvsMW6//XbWrl3Le9/73roFmjwTZi6EQkX3cA0ptMIZi2ByV/UZ9tHLdjZQ4lBV15c4xDbuYB+7zVBDhtT1zRArgyRJkiSpuVR0KPW5z32OK664go9+9KO8/vWvZ8WKFfzRH/0R1113XV1DnbsCssPVXZuVYO7y2jPcy2pamFTVtUVa2MhaM9QhQ+r6ZoiVQZIkSZLUPCo6lGpvb+ezn/0sjz/+OM899xy/+MUv+NSnPsUJJ5xQ11DT5sMFq6u79oIb8utr1cNmbqO6061vcQ09bDZDHTKkrm+GWBkkSZIkSc2jtofEjKE5y4YOpkZ6K9/Azy9YnV9XLxtZO/gifKS3LQ38/DaW1/WOEDOkr2+GWBkkSZIkSc2hyic3jb1CIX8b3tS3wLY18PidUHjxCC0rQaHlxe/LMPOy/HfrcYfUsTaylsd5kEtYxlzeTUb+FPYiRcqUgAIFimznLjaydkzuBjFD+vpmiJVBkiRJkjT+hT2UGjBtfv51oBd2rIP+nfBCP5zQAR2z8k/Zq+Wh5qPRw2Z62MwUZjCPq5jKLE6ig+fo5yl2soV1Y/4AZzOkr2+GWBkkSZIkSeNb+EOpAZO74PxPps2wj93cRX0f6m6G8VffDLEySJIkSZLGp7D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\n", 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" ] @@ -1225,21 +1254,62 @@ "\n", "\n", "simulation_results = simulate_game(1, (RandomPolicy(1), RandomPolicy(1)))\n", - "plot_othello_boards(\n", - " drop_duplicate_boards(np.reshape(simulation_results[0], (-1, 8, 8)))\n", - ")" + "_unique_bords, _unique_actions = drop_duplicate_boards(\n", + " simulation_results[0].reshape(-1, 8, 8), simulation_results[1].reshape(-1, 2)\n", + ")\n", + "plot_othello_boards(_unique_bords, actions=_unique_actions)" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(70, 8, 8)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.reshape(simulation_results[0], (-1, 8, 8)).shape" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(70, 2)" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "simulation_results[1].reshape(-1, 2).shape" + ] + }, + { + "cell_type": "code", + "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "10.5 s ± 737 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "10.4 s ± 244 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] } ], @@ -1273,7 +1343,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -1308,7 +1378,7 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -1317,7 +1387,7 @@ "(70, 10000, 8, 8)" ] }, - "execution_count": 107, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -1343,43 +1413,23 @@ "Those possible turms then where counted for all games in the history stack." ] }, - { - "cell_type": "code", - "execution_count": 108, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(70, 10000)" - ] - }, - "execution_count": 108, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "count_poss_turns = np.sum(_poss_turns, axis=(2, 3))\n", - "count_poss_turns.shape" - ] - }, { "cell_type": "markdown", "metadata": {}, "source": [ - "And the po" + "The action space size can be drawn into a histogram by turn and a curve over the mean action space size.\n", + "This can be used to analyse in which area of the game that cant be solved abolutely." ] }, { "cell_type": "code", - "execution_count": 145, + "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b098bb4da154488b8b4c22722833e8c0", + "model_id": "ced6183663884763a686b1939c31603b", "version_major": 2, "version_minor": 0 }, @@ -1392,15 +1442,23 @@ } ], "source": [ + "count_poss_turns = np.sum(_poss_turns, axis=(2, 3))\n", "mean_possibilitie_count = np.mean(count_poss_turns, axis=1)\n", "std_possibilitie_count = np.std(count_poss_turns, axis=1)\n", + "cum_prod = count_poss_turns\n", "\n", "\n", "@interact(turn=(0, 69))\n", "def poss_turn_count(turn):\n", - " fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 7))\n", + " fig, axes = plt.subplots(2, 2, figsize=(15, 8))\n", + " ax1, ax2, ax3, ax4 = axes.flatten()\n", + " _mean_possibilitie_count = mean_possibilitie_count.copy()\n", + " _std_possibilitie_count = std_possibilitie_count.copy()\n", + " _mean_possibilitie_count[_mean_possibilitie_count <= 1] = 1\n", + " _std_possibilitie_count[_std_possibilitie_count <= 1] = 1\n", + " np.cumprod(_mean_possibilitie_count[::-1], axis=0)[::-1]\n", " fig.suptitle(\n", - " f\"Action space size analysis\\nThe total size is estimated to be around {np.prod(np.extract(mean_possibilitie_count, mean_possibilitie_count)):.4g}\"\n", + " f\"Action space size analysis\\nThe total size is estimated to be around {np.prod(_mean_possibilitie_count):.4g}\"\n", " )\n", " ax1.hist(count_poss_turns[turn], density=True)\n", " ax1.set_title(f\"Histogram of the action space size for turn {turn}\")\n", @@ -1418,6 +1476,22 @@ " )\n", " ax2.scatter(turn, mean_possibilitie_count[turn], marker=\"x\")\n", " ax2.legend()\n", + "\n", + " ax4.plot(\n", + " range(70),\n", + " np.cumprod((_mean_possibilitie_count)[::-1], axis=0)[::-1],\n", + " # yerr=np.cumprod(_std_possibilitie_count[::-1], axis=0)[::-1],\n", + " )\n", + " ax4.scatter(\n", + " turn,\n", + " np.cumprod(_mean_possibilitie_count[::-1], axis=0)[::-1][turn],\n", + " marker=\"x\",\n", + " )\n", + " ax4.set_yscale(\"log\", base=10)\n", + " ax4.set_xlabel(\"Turn\")\n", + " ax4.set_ylabel(\"Mean remaining total action space size\")\n", + " fig.delaxes(ax3)\n", + " fig.tight_layout()\n", " plt.show()" ] }, @@ -1430,7 +1504,7 @@ }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 35, "metadata": {}, "outputs": [ { @@ -1476,7 +1550,7 @@ "black 3.753117e+20" ] }, - "execution_count": 124, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -1499,13 +1573,13 @@ }, { "cell_type": "code", - "execution_count": 125, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7002a64f4eb740c7bcbb4810783e70fa", + "model_id": "a72e7227de764a69be1984db759e554f", "version_major": 2, "version_minor": 0 }, @@ -1536,7 +1610,7 @@ }, { "cell_type": "code", - "execution_count": 126, + "execution_count": 68, "metadata": {}, "outputs": [ { @@ -1545,28 +1619,6 @@ "text": [ "(70, 10000)\n" ] - }, - { - "data": { - "text/plain": [ - "array([[ 0.046875, 0.046875, 0.046875, ..., 0.046875, 0.046875,\n", - " 0.046875],\n", - " [-0.046875, -0.046875, -0.046875, ..., -0.046875, -0.046875,\n", - " -0.046875],\n", - " [ 0.046875, 0.046875, 0.046875, ..., 0.078125, 0.046875,\n", - " 0.046875],\n", - " ...,\n", - " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", - " 0. ],\n", - " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", - " 0. ],\n", - " [ 0. , 0. , 0. , ..., 0. , 0. ,\n", - " 0. ]])" - ] - }, - "execution_count": 126, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -1581,19 +1633,18 @@ "\n", "assert len(calculate_direct_score(_board_history).shape) == 2\n", "assert calculate_direct_score(_board_history).shape[0] == SIMULATE_TURNS\n", - "print(calculate_direct_score(_board_history).shape)\n", - "calculate_direct_score(_board_history)" + "print(calculate_direct_score(_board_history).shape)" ] }, { "cell_type": "code", - "execution_count": 146, + "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "75ffc8765b074cd0b4495ac6075bb6b8", + "model_id": "c0a2aea84ef34cfb840d16e53d72c691", "version_major": 2, "version_minor": 0 }, @@ -1641,7 +1692,7 @@ }, { "cell_type": "code", - "execution_count": 147, + "execution_count": 39, "metadata": {}, "outputs": [ { @@ -1670,12 +1721,12 @@ }, { "cell_type": "code", - "execution_count": 148, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { - "image/png": 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lypRSYzLGlJoXb5Q3X5XVvHlzDRgwQC+//LK+++67UvcfOXLkgtso+frl+eefV9euXRUUFORuz8zM1MaNGyv1Fc3FuPXWW3Xu3Dm99NJL7raioqJKPe+OHz9eqi0qKkqS3K+Ni32cz/f3v/9dJ0+edN9esmSJvvvuO/frqGSfZX0lWXIOR8l5OtKPY33llVcuuN/Kvo5Rt3FkBFZ16tRJAwYMUHR0tJo2baqNGzdqyZIlGjt2rLtPdHS0JOnRRx9VfHy8fH19NWTIEN1+++26/vrrNXHiRO3du1fdunXT6tWrtWzZMv3hD39wv0FGR0fr7rvvVnp6uo4dO+a+tPfrr7+WVLl/yQcGBqpfv36aPn26fvjhB4WHh2v16tXas2fPJXhUSuvWrZsSExP1yiuv6MSJE+rfv782bNigV199VYMHD9b111/v0f/WW29V48aNNX78ePn6+uruu+/2uL9NmzZ65plnlJKSor1792rw4MFq3Lix9uzZo7feeksPPvigxo8fX6Vay5svb2RkZKhPnz7q0qWLRo8erdatWys3N1dZWVk6ePCgPvvsswrXb9u2rcLCwrRjxw6PE0b79eunJ554QpIueRi5/fbbdd1112nChAnau3evOnXqpKVLl5b5YX6+qVOn6v3339fAgQPVqlUrHT58WH/961915ZVXun/3pk2bNgoODtbs2bPVuHFjNWzYULGxsWWe71QZTZs2VZ8+fZSUlKTc3Fylp6erbdu2Gj16tLtPdHS0Fi1apOTkZPXs2VONGjXS7bffrmuvvVa9evVSSkqKjh8/rqZNm2rhwoU6d+5cpR6nyryOUcdZuIIHdUTJ5Xyffvppmff379//gpf2PvPMMyYmJsYEBwebBg0amA4dOphnn33WnD171t3n3Llz5pFHHjHNmjUzDofD4xLIkydPmj/+8Y+mZcuWpn79+qZdu3ZmxowZpri42GO/BQUFZsyYMaZp06amUaNGZvDgwWbHjh1GkseltiWXWJZ1SeXBgwfNnXfeaYKDg01QUJC59957zaFDh8q9PPj8bSQmJpqGDRtW6nEqyw8//GCmTJlirr76alO/fn0TERFhUlJSPC5//bkHHnjASDIul6vcbf7rX/8yffr0MQ0bNjQNGzY0HTp0MGPGjDE7duzwur4S5c1XyaW9M2bMKLXO+Y+hMcbs3r3bDB8+3ISFhZn69eub8PBwc9ttt5klS5ZUqo57773XSDKLFi1yt509e9YEBAQYPz8/c+bMGY/+5V3aW9al5+dfHlueY8eOmWHDhpnAwEATFBRkhg0bZjZv3nzBS3szMzPNoEGDTMuWLY2fn59p2bKlGTp0qPn66689tr9s2TLTqVMnU69ePY9tVjRn5V3a+8Ybb5iUlBTTvHlz06BBAzNw4ED3peAlTp06Ze6//34THBxsJHlcort7927jcrmM0+k0oaGh5sknnzRr1qy54KW9xlT+dSzJjBkzptSYzn9fQe3jMIazfvDLtGXLFnXv3l2vvfaaHnjgAdvlAMAvFueM4BehrD9Clp6eLh8fnwv+8ikA4NLinBH8IkyfPl3Z2dm6/vrrVa9ePa1cuVIrV67Ugw8+qIiICNvlAcAvGl/T4BdhzZo1mjJlirZt26ZTp07pqquu0rBhwzRx4kTVq0cmBwCbCCMAAMAqzhkBAABWEUYAAIBVteLL8uLiYh06dEiNGzeu9p9ABgAAl4YxRidPnlTLli3l41P+8Y9aEUYOHTrEFQ8AANRSBw4c0JVXXlnu/bUijJT88aQDBw4oMDDQcjUAAKAy8vPzFRER4fFHEMtSK8JIyVczgYGBhBEAAGqZC51iwQmsAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAKsIIAACwqp7tAgAAlRc5YbntElAH7Z020Or+OTICAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAqiqFkYyMDEVGRsrf31+xsbHasGFDuX0HDBggh8NRahk4cGCViwYAAHWH12Fk0aJFSk5O1qRJk7Rp0yZ169ZN8fHxOnz4cJn9ly5dqu+++869fPnll/L19dW999570cUDAIDaz+swMmvWLI0ePVpJSUnq1KmTZs+erYCAAM2bN6/M/k2bNlVYWJh7WbNmjQICAggjAABAkpdh5OzZs8rOzpbL5fppAz4+crlcysrKqtQ25s6dqyFDhqhhw4bl9iksLFR+fr7HAgAA6iavwsjRo0dVVFSk0NBQj/bQ0FDl5ORccP0NGzboyy+/1KhRoyrsl5aWpqCgIPcSERHhTZkAAKAWqdGraebOnasuXbooJiamwn4pKSnKy8tzLwcOHKihCgEAQE2r503nkJAQ+fr6Kjc316M9NzdXYWFhFa5bUFCghQsXaurUqRfcj9PplNPp9KY0AABQS3l1ZMTPz0/R0dHKzMx0txUXFyszM1NxcXEVrvvmm2+qsLBQv/nNb6pWKQAAqJO8OjIiScnJyUpMTFSPHj0UExOj9PR0FRQUKCkpSZI0fPhwhYeHKy0tzWO9uXPnavDgwbriiiuqp3IAAFAneB1GEhISdOTIEaWmpionJ0dRUVFatWqV+6TW/fv3y8fH84DLjh07tH79eq1evbp6qgYAAHWGwxhjbBdxIfn5+QoKClJeXp4CAwNtlwMA1kROWG67BNRBe6ddml9Fr+znN3+bBgAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABY5fWlvXUNZ6bjUrlUZ6cDQF3DkREAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWFWlMJKRkaHIyEj5+/srNjZWGzZsqLD/iRMnNGbMGLVo0UJOp1PXXHONVqxYUaWCAQBA3VLP2xUWLVqk5ORkzZ49W7GxsUpPT1d8fLx27Nih5s2bl+p/9uxZ3XTTTWrevLmWLFmi8PBw7du3T8HBwdVRPwAAqOW8DiOzZs3S6NGjlZSUJEmaPXu2li9frnnz5mnChAml+s+bN0/Hjx/XRx99pPr160uSIiMjL65qAABQZ3j1Nc3Zs2eVnZ0tl8v10wZ8fORyuZSVlVXmOu+8847i4uI0ZswYhYaGqnPnznruuedUVFRU7n4KCwuVn5/vsQAAgLrJqzBy9OhRFRUVKTQ01KM9NDRUOTk5Za7zzTffaMmSJSoqKtKKFSv01FNP6c9//rOeeeaZcveTlpamoKAg9xIREeFNmQAAoBa55FfTFBcXq3nz5nrllVcUHR2thIQETZw4UbNnzy53nZSUFOXl5bmXAwcOXOoyAQCAJV6dMxISEiJfX1/l5uZ6tOfm5iosLKzMdVq0aKH69evL19fX3daxY0fl5OTo7Nmz8vPzK7WO0+mU0+n0pjQAAFBLeXVkxM/PT9HR0crMzHS3FRcXKzMzU3FxcWWuc91112nXrl0qLi52t3399ddq0aJFmUEEAAD8snj9NU1ycrLmzJmjV199Vdu3b9dDDz2kgoIC99U1w4cPV0pKirv/Qw89pOPHj+uxxx7T119/reXLl+u5557TmDFjqm8UAACg1vL60t6EhAQdOXJEqampysnJUVRUlFatWuU+qXX//v3y8fkp40REROjdd9/VH//4R3Xt2lXh4eF67LHH9MQTT1TfKAAAQK3ldRiRpLFjx2rs2LFl3rdu3bpSbXFxcfr444+rsisAAFDH8bdpAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWFWlMJKRkaHIyEj5+/srNjZWGzZsKLfvggUL5HA4PBZ/f/8qFwwAAOoWr8PIokWLlJycrEmTJmnTpk3q1q2b4uPjdfjw4XLXCQwM1Hfffede9u3bd1FFAwCAusPrMDJr1iyNHj1aSUlJ6tSpk2bPnq2AgADNmzev3HUcDofCwsLcS2ho6EUVDQAA6g6vwsjZs2eVnZ0tl8v10wZ8fORyuZSVlVXueqdOnVKrVq0UERGhQYMGaevWrRXup7CwUPn5+R4LAACom7wKI0ePHlVRUVGpIxuhoaHKyckpc5327dtr3rx5WrZsmV577TUVFxerd+/eOnjwYLn7SUtLU1BQkHuJiIjwpkwAAFCLXPKraeLi4jR8+HBFRUWpf//+Wrp0qZo1a6aXX3653HVSUlKUl5fnXg4cOHCpywQAAJbU86ZzSEiIfH19lZub69Gem5ursLCwSm2jfv366t69u3bt2lVuH6fTKafT6U1pAACglvLqyIifn5+io6OVmZnpbisuLlZmZqbi4uIqtY2ioiJ98cUXatGihXeVAgCAOsmrIyOSlJycrMTERPXo0UMxMTFKT09XQUGBkpKSJEnDhw9XeHi40tLSJElTp05Vr1691LZtW504cUIzZszQvn37NGrUqOodCQAAqJW8DiMJCQk6cuSIUlNTlZOTo6ioKK1atcp9Uuv+/fvl4/PTAZfvv/9eo0ePVk5Ojpo0aaLo6Gh99NFH6tSpU/WNAgAA1FoOY4yxXcSF5OfnKygoSHl5eQoMDKzWbUdOWF6t2wNK7J020HYJqIN4z8KlcKneryr7+c3fpgEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGBVlcJIRkaGIiMj5e/vr9jYWG3YsKFS6y1cuFAOh0ODBw+uym4BAEAd5HUYWbRokZKTkzVp0iRt2rRJ3bp1U3x8vA4fPlzhenv37tX48ePVt2/fKhcLAADqHq/DyKxZszR69GglJSWpU6dOmj17tgICAjRv3rxy1ykqKtIDDzygKVOmqHXr1hdVMAAAqFu8CiNnz55Vdna2XC7XTxvw8ZHL5VJWVla5602dOlXNmzfXyJEjK7WfwsJC5efneywAAKBu8iqMHD16VEVFRQoNDfVoDw0NVU5OTpnrrF+/XnPnztWcOXMqvZ+0tDQFBQW5l4iICG/KBAAAtcglvZrm5MmTGjZsmObMmaOQkJBKr5eSkqK8vDz3cuDAgUtYJQAAsKmeN51DQkLk6+ur3Nxcj/bc3FyFhYWV6r97927t3btXt99+u7utuLj4xx3Xq6cdO3aoTZs2pdZzOp1yOp3elAYAAGopr46M+Pn5KTo6WpmZme624uJiZWZmKi4urlT/Dh066IsvvtCWLVvcyx133KHrr79eW7Zs4esXAADg3ZERSUpOTlZiYqJ69OihmJgYpaenq6CgQElJSZKk4cOHKzw8XGlpafL391fnzp091g8ODpakUu0AAOCXyeswkpCQoCNHjig1NVU5OTmKiorSqlWr3Ce17t+/Xz4+/LArAACoHK/DiCSNHTtWY8eOLfO+devWVbjuggULqrJLAABQR3EIAwAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYFWVwkhGRoYiIyPl7++v2NhYbdiwody+S5cuVY8ePRQcHKyGDRsqKipK//jHP6pcMAAAqFu8DiOLFi1ScnKyJk2apE2bNqlbt26Kj4/X4cOHy+zftGlTTZw4UVlZWfr888+VlJSkpKQkvfvuuxddPAAAqP28DiOzZs3S6NGjlZSUpE6dOmn27NkKCAjQvHnzyuw/YMAA3XnnnerYsaPatGmjxx57TF27dtX69evL3UdhYaHy8/M9FgAAUDd5FUbOnj2r7OxsuVyunzbg4yOXy6WsrKwLrm+MUWZmpnbs2KF+/fqV2y8tLU1BQUHuJSIiwpsyAQBALeJVGDl69KiKiooUGhrq0R4aGqqcnJxy18vLy1OjRo3k5+engQMH6sUXX9RNN91Ubv+UlBTl5eW5lwMHDnhTJgAAqEXq1cROGjdurC1btujUqVPKzMxUcnKyWrdurQEDBpTZ3+l0yul01kRpAADAMq/CSEhIiHx9fZWbm+vRnpubq7CwsHLX8/HxUdu2bSVJUVFR2r59u9LS0soNIwAA4JfDq69p/Pz8FB0drczMTHdbcXGxMjMzFRcXV+ntFBcXq7Cw0JtdAwCAOsrrr2mSk5OVmJioHj16KCYmRunp6SooKFBSUpIkafjw4QoPD1daWpqkH09G7dGjh9q0aaPCwkKtWLFC//jHP/TSSy9V70gAAECt5HUYSUhI0JEjR5SamqqcnBxFRUVp1apV7pNa9+/fLx+fnw64FBQU6OGHH9bBgwfVoEEDdejQQa+99poSEhKqbxQAAKDWchhjjO0iLiQ/P19BQUHKy8tTYGBgtW47csLyat0eUGLvtIG2S0AdxHsWLoVL9X5V2c9v/jYNAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAq6oURjIyMhQZGSl/f3/FxsZqw4YN5fadM2eO+vbtqyZNmqhJkyZyuVwV9gcAAL8sXoeRRYsWKTk5WZMmTdKmTZvUrVs3xcfH6/Dhw2X2X7dunYYOHaq1a9cqKytLERER+vWvf61vv/32oosHAAC1n9dhZNasWRo9erSSkpLUqVMnzZ49WwEBAZo3b16Z/f/5z3/q4YcfVlRUlDp06KC//e1vKi4uVmZm5kUXDwAAaj+vwsjZs2eVnZ0tl8v10wZ8fORyuZSVlVWpbZw+fVo//PCDmjZtWm6fwsJC5efneywAAKBu8iqMHD16VEVFRQoNDfVoDw0NVU5OTqW28cQTT6hly5YegeZ8aWlpCgoKci8RERHelAkAAGqRGr2aZtq0aVq4cKHeeust+fv7l9svJSVFeXl57uXAgQM1WCUAAKhJ9bzpHBISIl9fX+Xm5nq05+bmKiwsrMJ1Z86cqWnTpum9995T165dK+zrdDrldDq9KQ0AANRSXh0Z8fPzU3R0tMfJpyUno8bFxZW73vTp0/X0009r1apV6tGjR9WrBQAAdY5XR0YkKTk5WYmJierRo4diYmKUnp6ugoICJSUlSZKGDx+u8PBwpaWlSZKef/55paam6vXXX1dkZKT73JJGjRqpUaNG1TgUAABQG3kdRhISEnTkyBGlpqYqJydHUVFRWrVqlfuk1v3798vH56cDLi+99JLOnj2re+65x2M7kyZN0uTJky+uegAAUOt5HUYkaezYsRo7dmyZ961bt87j9t69e6uyCwAA8AvB36YBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgVZXCSEZGhiIjI+Xv76/Y2Fht2LCh3L5bt27V3XffrcjISDkcDqWnp1e1VgAAUAd5HUYWLVqk5ORkTZo0SZs2bVK3bt0UHx+vw4cPl9n/9OnTat26taZNm6awsLCLLhgAANQtXoeRWbNmafTo0UpKSlKnTp00e/ZsBQQEaN68eWX279mzp2bMmKEhQ4bI6XRedMEAAKBu8SqMnD17VtnZ2XK5XD9twMdHLpdLWVlZ1VZUYWGh8vPzPRYAAFA3eRVGjh49qqKiIoWGhnq0h4aGKicnp9qKSktLU1BQkHuJiIiotm0DAIDLy2V5NU1KSory8vLcy4EDB2yXBAAALpF63nQOCQmRr6+vcnNzPdpzc3Or9eRUp9PJ+SUAAPxCeHVkxM/PT9HR0crMzHS3FRcXKzMzU3FxcdVeHAAAqPu8OjIiScnJyUpMTFSPHj0UExOj9PR0FRQUKCkpSZI0fPhwhYeHKy0tTdKPJ71u27bN/f/ffvuttmzZokaNGqlt27bVOBQAAFAbeR1GEhISdOTIEaWmpionJ0dRUVFatWqV+6TW/fv3y8fnpwMuhw4dUvfu3d23Z86cqZkzZ6p///5at27dxY8AAADUal6HEUkaO3asxo4dW+Z95weMyMhIGWOqshsAAPALcFleTQMAAH45CCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAq6r0C6wALixywnLbJQBArcCREQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYFWVwkhGRoYiIyPl7++v2NhYbdiwocL+b775pjp06CB/f3916dJFK1asqFKxAACg7vE6jCxatEjJycmaNGmSNm3apG7duik+Pl6HDx8us/9HH32koUOHauTIkdq8ebMGDx6swYMH68svv7zo4gEAQO3nMMYYb1aIjY1Vz5499Ze//EWSVFxcrIiICD3yyCOaMGFCqf4JCQkqKCjQ//7v/7rbevXqpaioKM2ePbtS+8zPz1dQUJDy8vIUGBjoTbkXFDlhebVuDwCA2mbvtIGXZLuV/fyu581Gz549q+zsbKWkpLjbfHx85HK5lJWVVeY6WVlZSk5O9miLj4/X22+/Xe5+CgsLVVhY6L6dl5cn6cdBVbfiwtPVvk0AAGqTS/H5+vPtXui4h1dh5OjRoyoqKlJoaKhHe2hoqL766qsy18nJySmzf05OTrn7SUtL05QpU0q1R0REeFMuAACohKD0S7v9kydPKigoqNz7vQojNSUlJcXjaEpxcbGOHz+uK664Qg6Ho9r2k5+fr4iICB04cKDav/65XNT1MTK+2q+uj5Hx1X51fYyXcnzGGJ08eVItW7assJ9XYSQkJES+vr7Kzc31aM/NzVVYWFiZ64SFhXnVX5KcTqecTqdHW3BwsDeleiUwMLBOPsF+rq6PkfHVfnV9jIyv9qvrY7xU46voiEgJr66m8fPzU3R0tDIzM91txcXFyszMVFxcXJnrxMXFefSXpDVr1pTbHwAA/LJ4/TVNcnKyEhMT1aNHD8XExCg9PV0FBQVKSkqSJA0fPlzh4eFKS0uTJD322GPq37+//vznP2vgwIFauHChNm7cqFdeeaV6RwIAAGolr8NIQkKCjhw5otTUVOXk5CgqKkqrVq1yn6S6f/9++fj8dMCld+/eev311/WnP/1JTz75pNq1a6e3335bnTt3rr5RVJHT6dSkSZNKfSVUl9T1MTK+2q+uj5Hx1X51fYyXw/i8/p0RAACA6sTfpgEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVtX5MPLss8+qd+/eCggIqPSvuBpjlJqaqhYtWqhBgwZyuVzauXOnR5/jx4/rgQceUGBgoIKDgzVy5EidOnXqEoygYt7WsXfvXjkcjjKXN998092vrPsXLlxYE0PyUJXHecCAAaVq//3vf+/RZ//+/Ro4cKACAgLUvHlzPf744zp37tylHEq5vB3j8ePH9cgjj6h9+/Zq0KCBrrrqKj366KPuPyhZwtYcZmRkKDIyUv7+/oqNjdWGDRsq7P/mm2+qQ4cO8vf3V5cuXbRixQqP+yvzeqxp3oxxzpw56tu3r5o0aaImTZrI5XKV6j9ixIhSc3XzzTdf6mGUy5vxLViwoFTt/v7+Hn0utzn0ZnxlvZ84HA4NHPjTX7m9nObv/fff1+23366WLVvK4XBU+EdpS6xbt06/+tWv5HQ61bZtWy1YsKBUH29f114zdVxqaqqZNWuWSU5ONkFBQZVaZ9q0aSYoKMi8/fbb5rPPPjN33HGHufrqq82ZM2fcfW6++WbTrVs38/HHH5sPPvjAtG3b1gwdOvQSjaJ83tZx7tw5891333ksU6ZMMY0aNTInT55095Nk5s+f79Hv5+OvKVV5nPv3729Gjx7tUXteXp77/nPnzpnOnTsbl8tlNm/ebFasWGFCQkJMSkrKpR5Ombwd4xdffGHuuusu884775hdu3aZzMxM065dO3P33Xd79LMxhwsXLjR+fn5m3rx5ZuvWrWb06NEmODjY5Obmltn/ww8/NL6+vmb69Olm27Zt5k9/+pOpX7+++eKLL9x9KvN6rEnejvH+++83GRkZZvPmzWb79u1mxIgRJigoyBw8eNDdJzEx0dx8880ec3X8+PGaGpIHb8c3f/58ExgY6FF7Tk6OR5/LaQ69Hd+xY8c8xvbll18aX19fM3/+fHefy2n+VqxYYSZOnGiWLl1qJJm33nqrwv7ffPONCQgIMMnJyWbbtm3mxRdfNL6+vmbVqlXuPt4+ZlVR58NIifnz51cqjBQXF5uwsDAzY8YMd9uJEyeM0+k0b7zxhjHGmG3bthlJ5tNPP3X3WblypXE4HObbb7+t9trLU111REVFmd/+9rcebZV5El9qVR1f//79zWOPPVbu/StWrDA+Pj4eb5gvvfSSCQwMNIWFhdVSe2VV1xwuXrzY+Pn5mR9++MHdZmMOY2JizJgxY9y3i4qKTMuWLU1aWlqZ/e+77z4zcOBAj7bY2Fjzu9/9zhhTuddjTfN2jOc7d+6cady4sXn11VfdbYmJiWbQoEHVXWqVeDu+C723Xm5zeLHz98ILL5jGjRubU6dOudsup/n7ucq8B/y///f/zLXXXuvRlpCQYOLj4923L/Yxq4w6/zWNt/bs2aOcnBy5XC53W1BQkGJjY5WVlSVJysrKUnBwsHr06OHu43K55OPjo08++aTGaq2OOrKzs7VlyxaNHDmy1H1jxoxRSEiIYmJiNG/ePJka/n28ixnfP//5T4WEhKhz585KSUnR6dOnPbbbpUsX968GS1J8fLzy8/O1devW6h9IBarruZSXl6fAwEDVq+f5o8o1OYdnz55Vdna2x2vHx8dHLpfL/do5X1ZWlkd/6ce5KOlfmddjTarKGM93+vRp/fDDD2ratKlH+7p169S8eXO1b99eDz30kI4dO1attVdGVcd36tQptWrVShERERo0aJDH6+hymsPqmL+5c+dqyJAhatiwoUf75TB/VXGh12B1PGaV4fXPwdd1OTk5kuTxQVVyu+S+nJwcNW/e3OP+evXqqWnTpu4+NaE66pg7d646duyo3r17e7RPnTpVN9xwgwICArR69Wo9/PDDOnXqlB599NFqq/9Cqjq++++/X61atVLLli31+eef64knntCOHTu0dOlS93bLmt+S+2pSdczh0aNH9fTTT+vBBx/0aK/pOTx69KiKiorKfGy/+uqrMtcpby5+/loraSuvT02qyhjP98QTT6hly5Yeb+4333yz7rrrLl199dXavXu3nnzySd1yyy3KysqSr69vtY6hIlUZX/v27TVv3jx17dpVeXl5mjlzpnr37q2tW7fqyiuvvKzm8GLnb8OGDfryyy81d+5cj/bLZf6qorzXYH5+vs6cOaPvv//+op/zlVErw8iECRP0/PPPV9hn+/bt6tChQw1VVL0qO76LdebMGb3++ut66qmnSt3387bu3buroKBAM2bMqJYPsks9vp9/KHfp0kUtWrTQjTfeqN27d6tNmzZV3q43amoO8/PzNXDgQHXq1EmTJ0/2uO9SziGqZtq0aVq4cKHWrVvncZLnkCFD3P/fpUsXde3aVW3atNG6det044032ii10uLi4jz+Cnvv3r3VsWNHvfzyy3r66actVlb95s6dqy5duigmJsajvTbP3+WiVoaRcePGacSIERX2ad26dZW2HRYWJknKzc1VixYt3O25ubmKiopy9zl8+LDHeufOndPx48fd61+Myo7vYutYsmSJTp8+reHDh1+wb2xsrJ5++mkVFhZe9B9TqqnxlYiNjZUk7dq1S23atFFYWFipM8Fzc3MlqVrmT6qZMZ48eVI333yzGjdurLfeekv169evsH91zmFZQkJC5Ovr634sS+Tm5pY7lrCwsAr7V+b1WJOqMsYSM2fO1LRp0/Tee++pa9euFfZt3bq1QkJCtGvXrhr9MLuY8ZWoX7++unfvrl27dkm6vObwYsZXUFCghQsXaurUqRfcj635q4ryXoOBgYFq0KCBfH19L/o5USnVdvbJZc7bE1hnzpzpbsvLyyvzBNaNGze6+7z77rvWTmCtah39+/cvdQVGeZ555hnTpEmTKtdaFdX1OK9fv95IMp999pkx5qcTWH9+JvjLL79sAgMDzX/+85/qG0AlVHWMeXl5plevXqZ///6moKCgUvuqiTmMiYkxY8eOdd8uKioy4eHhFZ7Aetttt3m0xcXFlTqBtaLXY03zdozGGPP888+bwMBAk5WVVal9HDhwwDgcDrNs2bKLrtdbVRnfz507d860b9/e/PGPfzTGXH5zWNXxzZ8/3zidTnP06NEL7sPm/P2cKnkCa+fOnT3ahg4dWuoE1ot5TlSq1mrb0mVq3759ZvPmze7LVzdv3mw2b97scRlr+/btzdKlS923p02bZoKDg82yZcvM559/bgYNGlTmpb3du3c3n3zyiVm/fr1p166dtUt7K6rj4MGDpn379uaTTz7xWG/nzp3G4XCYlStXltrmO++8Y+bMmWO++OILs3PnTvPXv/7VBAQEmNTU1Es+nvN5O75du3aZqVOnmo0bN5o9e/aYZcuWmdatW5t+/fq51ym5tPfXv/612bJli1m1apVp1qyZ1Ut7vRljXl6eiY2NNV26dDG7du3yuJzw3Llzxhh7c7hw4ULjdDrNggULzLZt28yDDz5ogoOD3VcuDRs2zEyYMMHd/8MPPzT16tUzM2fONNu3bzeTJk0q89LeC70ea5K3Y5w2bZrx8/MzS5Ys8ZirkvegkydPmvHjx5usrCyzZ88e895775lf/epXpl27djUejqsyvilTpph3333X7N6922RnZ5shQ4YYf39/s3XrVnefy2kOvR1fiT59+piEhIRS7Zfb/J08edL9OSfJzJo1y2zevNns27fPGGPMhAkTzLBhw9z9Sy7tffzxx8327dtNRkZGmZf2VvSYVYc6H0YSExONpFLL2rVr3X30//8eQ4ni4mLz1FNPmdDQUON0Os2NN95oduzY4bHdY8eOmaFDh5pGjRqZwMBAk5SU5BFwasqF6tizZ0+p8RpjTEpKiomIiDBFRUWltrly5UoTFRVlGjVqZBo2bGi6detmZs+eXWbfS83b8e3fv9/069fPNG3a1DidTtO2bVvz+OOPe/zOiDHG7N2719xyyy2mQYMGJiQkxIwbN87jstia5O0Y165dW+ZzWpLZs2ePMcbuHL744ovmqquuMn5+fiYmJsZ8/PHH7vv69+9vEhMTPfovXrzYXHPNNcbPz89ce+21Zvny5R73V+b1WNO8GWOrVq3KnKtJkyYZY4w5ffq0+fWvf22aNWtm6tevb1q1amVGjx5drW/03vJmfH/4wx/cfUNDQ82tt95qNm3a5LG9y20OvX2OfvXVV0aSWb16daltXW7zV977Q8mYEhMTTf/+/UutExUVZfz8/Ezr1q09Pg9LVPSYVQeHMTV8vSYAAMDP8DsjAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArPr/ABe1qcGpyxpNAAAAAElFTkSuQmCC\n", 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\n", "text/plain": [ "
" ] @@ -1690,21 +1741,24 @@ " return who_won\n", "\n", "\n", - "plt.title(\"Histogram over the win distribtuion\")\n", - "plt.hist(calculate_who_won(_board_history), density=True, bins=3)\n", + "plt.title(\"Win distribtuion\")\n", + "plt.bar(\n", + " [\"black\", \"draw\", \"white\"],\n", + " pd.Series(calculate_who_won(_board_history)).value_counts().sort_index() / 10000,\n", + ")\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 149, + "execution_count": 41, "metadata": { "scrolled": false }, "outputs": [ { "data": { - "image/png": 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Uo0cP2Ww2vf32200es3btWp1//vlyuVw688wz9dJLL7WgqAAAoD0KOIyUlJRoyJAhmjdvXrP237Vrl8aNG6eLL75YW7du1fTp03XbbbdpxYoVARcWAAC0PwFfKO/yyy/X5Zdf3uz9FyxYoL59++rJJ5+UJJ1zzjn66KOP9Pvf/17Z2dn1HlNRUaGKigr//aKiokCLCQDAacUYo2OllTp4vEIHiyt06HiFisqrVOXxqspj5D7xtcrrVaXHyBgjc+I4r5GMkaq3tMyU0X2V1qVD8E4oACG/am9eXp6ysrJqbMvOztb06dMbPCY3N1cPP/xwiEsGAIB1vF6jNz/5Tv/38R7tP1auwyUVqvS0PEy01lVDerTfMJKfn6+UlJQa21JSUlRUVKSysjLFxsbWOWbmzJnKycnx3y8qKlJaWlqoiwoAQFh8/l2hZr3zubbsPVbnscQO0eoW51JSnEvxsVGKctjldNgVZbcpymFXtMOmKLtddptkt9tkk2Sz2WSz6cT3LStTSnxMa06pVUIeRlrC5XLJ5XJZXQwAAILqSIlbv12xTYs27pUxUgenQ9MuOVNjzkxSt04ude3okjMq8ia6hjyMpKamqqCgoMa2goICxcfH19sqAgBAe+PxGr328R79buU3KiyrlCSNH9pDMy8/R6kJ1rVItBUhDyOZmZlatmxZjW2rVq1SZmZmqF8aAADLVXm8+snzH2vDriOSpAGpnfTI+EEa1beLxSVrOwIOI8ePH9eOHTv893ft2qWtW7eqS5cu6t27t2bOnKnvvvtOr7zyiiTpzjvv1DPPPKNf/OIXmjJlij744AP95S9/0dKlS4N3FgAAtFF/335IG3YdUQenQzMuH6CfjOqtKEfkdcU0JuDa2LRpk4YNG6Zhw4ZJknJycjRs2DDNmjVLkrR//37t3bvXv3/fvn21dOlSrVq1SkOGDNGTTz6p559/vsFpvQAAtCdLtvxbkvTjEWmamJlOEKmHzRhj3TyiZioqKlJCQoIKCwsVHx9vdXEAAGiWwrJKjXz0fbmrvHr3njEa1DPB6iKFVXM/v4lnAACEyLLP9std5VX/lDid24N/phtCGAEAIETe2FzdRXPd+b1ka+kCIBGAMAIAQAjsOVyiTXuOym6TrhnW0+ritGmEEQAAQuCNLd9Jksac1c3S1U1PB4QRAACCzOs1enOLr4uGVpGmEEYAAAiyjbuP6N9HyxTnitJlA1OtLk6bRxgBACDI3jzRRXPFeamKdTosLk3bRxgBACCIyis9WvrZfknVs2jQNMIIAABBtOKLfB2vqFKvzrEamc71Z5qDMAIAQBD5umh+dH4v2e2sLdIchBEAAIKkoKhcf99+UJL0I9YWaTbCCAAAQfLO1u/kNdKIPp2VntTR6uKcNggjAAAEgTFGb2w+2UWD5iOMAAAQBF98X6RtBcVyRtk1bnB3q4tzWiGMAAAQBH/71/eSpEsHpighNtri0pxeCCMAAATB3sOlkqRRTOcNGGEEAIAgOHzcLUlKinNZXJLTD2EEAIAgOFRSIUnq0tFpcUlOP4QRAACC4EiJr2WEMBIowggAAK1U6fHqWGmlJKkr3TQBI4wAANBKR0+0ithtUiIzaQJGGAEAoJUOnwgjXTo6uR5NCxBGAABoJd9Mmq4d6aJpCcIIAACtdJiZNK1CGAEAoJX8LSPMpGkRwggAAK3kaxlhwbOWIYwAANBKR04ZwIrAEUYAAGilQ3TTtAphBACAVjp8vLqbhtk0LUMYAQCglXzdNLSMtAxhBACAVjq5zghhpCUIIwAAtEJFlUfFFVWS6KZpKcIIAACt4OuiibLbFB8bZXFpTk+EEQAAWuHUBc9sNq5L0xKEEQAAWuHQcd9S8HTRtBRhBACAVvB10yQxk6bFCCMAALQCM2lajzACAEArHCqhm6a1CCMAALTCEZaCbzXCCAAArXCYMSOtRhgBAKAVDjObptUIIwAAtMJhrkvTaoQRAABawTebJomWkRYjjAAA0EKl7iqVVXokSV1oGWkxwggAAC3kaxVxRdnV0emwuDSnL8IIAAAtdHImjYvr0rQCYQQAgBY64l/wjC6a1iCMAADQQodY8CwoCCMAALTQyevSMJOmNQgjAAC0kK+bhpaR1iGMAADQQlyxNzgIIwAAtNAh/+qrdNO0BmEEAIAW8nfT0DLSKoQRAABa6DCzaYKCMAIAQAsYY/xhhHVGWocwAgBACxyvqJLb45XE1N7WalEYmTdvntLT0xUTE6OMjAxt2LCh0f3nzp2rs88+W7GxsUpLS9N9992n8vLyFhUYAIC2wNcq0tHpUCzXpWmVgMPI4sWLlZOTo9mzZ2vLli0aMmSIsrOzdeDAgXr3f+211zRjxgzNnj1bX331lV544QUtXrxYv/zlL1tdeAAArHLYtxQ840VaLeAwMmfOHN1+++2aPHmyBg4cqAULFqhDhw568cUX691//fr1Gj16tH7yk58oPT1dl112mW666aYmW1MAAGjLWH01eAIKI263W5s3b1ZWVtbJJ7DblZWVpby8vHqPueCCC7R582Z/+Ni5c6eWLVumK664osHXqaioUFFRUY0bAABtyckr9tIy0lpRgex86NAheTwepaSk1NiekpKir7/+ut5jfvKTn+jQoUMaM2aMjDGqqqrSnXfe2Wg3TW5urh5++OFAigYAQFgdPs4Ve4Ml5LNp1q5dq8cee0x//OMftWXLFr355ptaunSpfv3rXzd4zMyZM1VYWOi/7du3L9TFBAAgIIdZfTVoAmoZSUpKksPhUEFBQY3tBQUFSk1NrfeYBx98ULfccotuu+02SdJ5552nkpIS3XHHHXrggQdkt9fNQy6XSy4XP1wAQNvFdWmCJ6CWEafTqeHDh2v16tX+bV6vV6tXr1ZmZma9x5SWltYJHA5H9RQoY0yg5QUAoE04zBV7gyaglhFJysnJ0aRJkzRixAiNGjVKc+fOVUlJiSZPnixJmjhxonr27Knc3FxJ0lVXXaU5c+Zo2LBhysjI0I4dO/Tggw/qqquu8ocSAABON8ymCZ6Aw8iECRN08OBBzZo1S/n5+Ro6dKiWL1/uH9S6d+/eGi0hv/rVr2Sz2fSrX/1K3333nbp166arrrpKjz76aPDOAgCAMDs5ZoSWkdaymdOgr6SoqEgJCQkqLCxUfHy81cUBAEQ4r9eo/6/eU5XX6J8zxyo1IcbqIrVJzf385to0AAAEqKi8UlXe6v/lmdrbeoQRAAACdOjEeJH4mCg5o/gobS1qEACAAB1hjZGgIowAABAg3+qrrDESHIQRAAACdIiZNEFFGAEAIEBHTowZ6cIaI0FBGAEAIEC+1Ve5Ym9wEEYAAAgQ16UJLsIIAAAB8rWMdGE2TVAQRgAACJCvZSSJlpGgIIwAABAg33VpujBmJCgIIwAABMDjNTpayhV7g4kwAgBAAI6WumWMZLNJnTtEW12cdoEwAgBAAHzjRRJjoxXl4GM0GKhFAAAC4JtJw3VpgocwAgBAAFhjJPgIIwAABMB/kTxm0gQNYQQAgAAcKWEmTbARRgAACABX7A0+wggAAAHwd9MwZiRoCCMAAATA303DbJqgIYwAABAAZtMEH2EEAIAAHGbMSNARRgAAaCZ3lVeFZZWSmE0TTIQRAACayXeBPIfdpoRYrksTLIQRAACaqehEq0inmCjZ7TaLS9N+EEYAAGimskqPJKlDtMPikrQvhBEAAJqpzF0dRmKchJFgIowAANBM/pYRwkhQEUYAAGim8hNhJJZumqAijAAA0Ey+lpEYwkhQEUYAAGimMrdXEi0jwUYYAQCgmUrdVZKkWMaMBBVhBACAZmLMSGgQRgAAaCbGjIQGYQQAgGbyjRlham9wEUYAAGimMrppQoIwAgBAM/nHjNAyElSEEQAAmsk3m4YxI8FFGAEAoJnKKllnJBQIIwAANFO5m26aUCCMAADQTAxgDQ3CCAAAzVTGANaQIIwAANBMZW5aRkKBMAIAQDMxtTc0CCMAADRTKS0jIUEYAQCgGYwxXJsmRAgjAAA0Q0WV1/893TTBRRgBAKAZfINXJbppgo0wAgBAM/i6aJxRdjnsNotL074QRgAAaAYWPAsdwggAAM3AGiOhQxgBAKAZWH01dAgjAAA0g69lhGm9wUcYAQCgGU6OGeGjM9ioUQAAmsG3FHwHZ5TFJWl/WhRG5s2bp/T0dMXExCgjI0MbNmxodP9jx45p6tSp6t69u1wul/r3769ly5a1qMAAAFiBbprQCTjeLV68WDk5OVqwYIEyMjI0d+5cZWdna9u2bUpOTq6zv9vt1qWXXqrk5GQtWbJEPXv21J49e5SYmBiM8gMAEBYMYA2dgMPInDlzdPvtt2vy5MmSpAULFmjp0qV68cUXNWPGjDr7v/jiizpy5IjWr1+v6OhoSVJ6enrrSg0AQJgxZiR0AqpRt9utzZs3Kysr6+QT2O3KyspSXl5evcf89a9/VWZmpqZOnaqUlBQNGjRIjz32mDweT737S1JFRYWKiopq3AAAsBLrjIROQGHk0KFD8ng8SklJqbE9JSVF+fn59R6zc+dOLVmyRB6PR8uWLdODDz6oJ598Uv/zP//T4Ovk5uYqISHBf0tLSwukmAAABJ1/zAjdNEEX8rYmr9er5ORkPfvssxo+fLgmTJigBx54QAsWLGjwmJkzZ6qwsNB/27dvX6iLCQBAo1gOPnQCGjOSlJQkh8OhgoKCGtsLCgqUmppa7zHdu3dXdHS0HI6TP7xzzjlH+fn5crvdcjqddY5xuVxyuVyBFA0AgJAq80/tJYwEW0AtI06nU8OHD9fq1av927xer1avXq3MzMx6jxk9erR27Nghr9fr3/bNN9+oe/fu9QYRAADaonJaRkIm4G6anJwcPffcc3r55Zf11Vdf6a677lJJSYl/ds3EiRM1c+ZM//533XWXjhw5onvvvVfffPONli5dqscee0xTp04N3lkAABBirDMSOgFP7Z0wYYIOHjyoWbNmKT8/X0OHDtXy5cv9g1r37t0ru/1kxklLS9OKFSt03333afDgwerZs6fuvfde3X///cE7CwAAQox1RkLHZowxVheiKUVFRUpISFBhYaHi4+OtLg4AIAKNf+YjffrvQr0waYTGnpPS9AFo9uc3K7cAANAMzKYJHcIIAADN4AsjrDMSfIQRAACaocxdPSuUqb3BRxgBAKAZmNobOoQRAACaYIxhzEgIEUYAAGiC2+OVx1s9+ZQxI8FHGAEAoAnl7pOriNMyEnyEEQAAmuDroomy2xTt4KMz2KhRAACawHiR0CKMAADQBN91aVgKPjQIIwAANIHr0oQWYQQAgCawxkhoEUYAAGhC6YlumhjCSEgQRgAAaAIDWEOLMAIAQBPKGcAaUoQRAACaQMtIaBFGAABoArNpQoswAgBAE/zrjNAyEhKEEQAAmlBOy0hIEUYAAGgCU3tDizACAEATGMAaWoQRAACacDKM8LEZCtQqAABN8K0z0sEZZXFJ2ifCCAAATfC1jMQwgDUkCCMAADSBMSOhRRgBAKAJrDMSWoQRAACacHIFVj42Q4FaBQCgCWWsMxJShBEAAJrAmJHQIowAANAE33LwTO0NDcIIAACNqPR4VekxkmgZCRXCCAAAjfC1ikhSDANYQ4JaBQCgEb7xInab5HTwsRkK1CoAAI04dY0Rm81mcWnaJ8IIAACNOLnGCONFQoUwAgBAI1hjJPQIIwAANKLMP62XMBIqhBEAABpRzoJnIUcYAQCgEWVuryS6aUKJMAIAQCNK3VWSGMAaSoQRAAAaQTdN6BFGAABoBBfJCz3CCAAAjfCPGaGbJmQIIwAANMI/tZeWkZAhjAAA0IhyVmANOcIIAACNYAXW0COMAADQiFIGsIYcYQQAgEb4r9pLN03IEEYAAGgE64yEHmEEAIBG+GbTMGYkdAgjAAA0wtdNw1V7Q4cwAgBAI5jaG3qEEQAAGsFy8KFHGAEAoBGlrDMScoQRAAAaUUY3TcgRRgAAaIDHa+Suqr5QHt00odOiMDJv3jylp6crJiZGGRkZ2rBhQ7OOW7RokWw2m6655pqWvCwAAGHlG7wqEUZCKeAwsnjxYuXk5Gj27NnasmWLhgwZouzsbB04cKDR43bv3q2f//znuvDCC1tcWAAAwqnslDASE01nQqgEXLNz5szR7bffrsmTJ2vgwIFasGCBOnTooBdffLHBYzwej26++WY9/PDDOuOMM1pVYAAAwsW/FHy0QzabzeLStF8BhRG3263NmzcrKyvr5BPY7crKylJeXl6Dxz3yyCNKTk7WT3/602a9TkVFhYqKimrcAAAIN9YYCY+AwsihQ4fk8XiUkpJSY3tKSory8/PrPeajjz7SCy+8oOeee67Zr5Obm6uEhAT/LS0tLZBiAgAQFKVu1hgJh5B2gBUXF+uWW27Rc889p6SkpGYfN3PmTBUWFvpv+/btC2EpAQCo38nr0jBeJJSiAtk5KSlJDodDBQUFNbYXFBQoNTW1zv7ffvutdu/erauuusq/zeutniIVFRWlbdu2qV+/fnWOc7lccrlcgRQNAICgY42R8Ago6jmdTg0fPlyrV6/2b/N6vVq9erUyMzPr7D9gwAB99tln2rp1q/929dVX6+KLL9bWrVvpfgEAtGnlvovkRQf0vzsCFHDt5uTkaNKkSRoxYoRGjRqluXPnqqSkRJMnT5YkTZw4UT179lRubq5iYmI0aNCgGscnJiZKUp3tAAC0Nf5uGlpGQirgMDJhwgQdPHhQs2bNUn5+voYOHarly5f7B7Xu3btXdjt9awCA09/Ji+TxuRZKLWp3mjZtmqZNm1bvY2vXrm302JdeeqklLwkAQNiVMZsmLIh6AAA0wB9G6KYJKcIIAAANODm1lzASSoQRAAAacHLMCGEklAgjAAA0wLccfAe6aUKKMAIAQAN8Y0bopgktwggAAA1gBdbwIIwAANAALpQXHoQRAAAaUM4A1rAgjAAA0ACWgw8PwggAAA1gBdbwIIwAANCA8kqvJKb2hhphBACABrDoWXgQRgAAaADrjIQHYQQAgHp4vYZ1RsKEMAIAQD0qqrz+7+mmCS3CCAAA9fC1ikh004QaYQQAgHr4wogzyi6H3WZxado3wggAAPXwDV5lWm/oEUYAAKgHS8GHD2EEAIB6sMZI+BBGAACoRylrjIQNYQQAgHr4r0vDmJGQI4wAAFAPxoyED2EEAIB6+MaM0E0TeoQRAADqwdTe8CGMAABQD2bThA9hBACAepRzkbywIYwAAFAPpvaGD2EEAIB60E0TPoQRAADqUe5fZ4SPylCjhgEAqActI+FDGAEAoB7+MOKMsrgk7R9hBACAeviXg6dlJOQIIwAA1OPk1F4+KkONGgYAoB5M7Q0fwggAAPVgAGv4EEYAAKgHK7CGD2EEAIB6+C+UF81smlAjjAAAUIsxxt9NE8MA1pCjhgEAqMXt8cprqr9nzEjoEUYAAKjF10UjMZsmHAgjAADU4uuiiXbYFO3gozLUqGEAAGopY42RsCKMAABQC2uMhBdhBACAWnxrjHRgjZGwIIwAAFBLmdsriW6acCGMAABQSxmrr4YVYQQAgFpK3VWSGDMSLoQRAABqKWcAa1gRRgAAqMU/tZdumrAgjAAAUEtZZfUAVlpGwoMwAgBALWVM7Q0rwggAALUwZiS8CCMAANTCcvDhRRgBAKCWUjfrjIQTYQQAgFropgmvFoWRefPmKT09XTExMcrIyNCGDRsa3Pe5557ThRdeqM6dO6tz587KyspqdH8AAKy2v7BMktQ1zmlxSSJDwGFk8eLFysnJ0ezZs7VlyxYNGTJE2dnZOnDgQL37r127VjfddJPWrFmjvLw8paWl6bLLLtN3333X6sIDABAKuw6VSJLOSIqzuCSRwWaMMYEckJGRoZEjR+qZZ56RJHm9XqWlpemee+7RjBkzmjze4/Goc+fOeuaZZzRx4sRmvWZRUZESEhJUWFio+Pj4QIoLAEBAjpa4NezXqyRJXz3yn4wbaYXmfn4H1DLidru1efNmZWVlnXwCu11ZWVnKy8tr1nOUlpaqsrJSXbp0aXCfiooKFRUV1bgBABAOOw8dlyT1SIghiIRJQGHk0KFD8ng8SklJqbE9JSVF+fn5zXqO+++/Xz169KgRaGrLzc1VQkKC/5aWlhZIMQEAaLGdB0900XSjiyZcwjqb5vHHH9eiRYv01ltvKSYmpsH9Zs6cqcLCQv9t3759YSwlACCS7TwxXqRvUkeLSxI5ogLZOSkpSQ6HQwUFBTW2FxQUKDU1tdFjf/e73+nxxx/X+++/r8GDBze6r8vlksvlCqRoAAAExc6D1d00Z3QjjIRLQC0jTqdTw4cP1+rVq/3bvF6vVq9erczMzAaPe+KJJ/TrX/9ay5cv14gRI1peWgAAQsw/k4ZumrAJqGVEknJycjRp0iSNGDFCo0aN0ty5c1VSUqLJkydLkiZOnKiePXsqNzdXkvSb3/xGs2bN0muvvab09HT/2JK4uDjFxfGDBgC0HR6v0e7DpZKkM+imCZuAw8iECRN08OBBzZo1S/n5+Ro6dKiWL1/uH9S6d+9e2e0nG1zmz58vt9ut66+/vsbzzJ49Ww899FDrSg8AQBB9d7RM7iqvnFF29UiMtbo4ESPgdUaswDojAIBwWLvtgG5duFH9U+K08r6LrC7OaS8k64wAANCe+af1svJqWBFGAAA44eTgVcaLhBNhBACAE3yrr7LGSHgRRgAAOIHVV61BGAEAQFKpu0r7C8slMa033AgjAADo5HiRzh2i1bmj0+LSRBbCCAAAoovGSoQRAAB0smWEwavhRxgBAEBcIM9KhBEAACTtPMSCZ1YhjAAAIp4xRrsOsuCZVQgjAICId/B4hYorqmSzSX26drC6OBGHMAIAiHi+VpFenWPlinJYXJrIQxgBAEQ8xotYizACAIh4zKSxFmEEABDx/FfrZY0RSxBGAAARj9VXrUUYAQBEtEqPV3uPlEpi9VWrEEYAABFt35FSVXmNYqMdSo2Psbo4EYkwAgCIaL4umr5JHWW32ywuTWQijAAAItrOQ9Uzafoyk8YyhBEAQETzzaTpx3gRyxBGAAAR7VtfNw0tI5YhjAAAItouVl+1HGEEABCxissrdbC4QhItI1YijAAAIpZvJk1SnEvxMdEWlyZyEUYAABHL30VDq4ilCCMAgIjlv0AeM2ksRRgBAESsb2kZaRMIIwCAiLXrIDNp2gLCCAAgInm9xj9mhJk01iKMAAAiUkFxucoqPXLYberdpYPVxYlohBEAQET64OsDkqQzu8Up2sHHoZWofQBAxDHG6KV/7JYk/XhkmrWFAWEEABB5/rHjsLYfOK6OToduGNHL6uJEPMIIACDivLR+lyTp+uG9WHm1DSCMAAAiyp7DJVp9YrzIxAvSrS0MJBFGAAAR5uX1e2SMdFH/burXjfVF2gLCCAAgYhyvqNLrm/ZJkiaPTre2MPAjjAAAIsabW/6t4ooqnZHUUf9xVjeri4MTCCMAgIjg9Z6cznvr6HTZ7TZrCwQ/wggAICJ8uP2gdh4qUSdXlH50PtN52xLCCAAgIiw80Spyw4g0xbmirC0MaiCMAADavW8PHte6bw7KZpMmXdDH6uKgFsIIAKDde2X9bknS2AHJ6tOVK/S2NYQRAEC7VlReqSWb/y1Jmjy6r8WlQX0IIwCAdm3xhn0qcXt0VnKcLujX1erioB6EEQBAu7Xii3z9dsU2SdXTeW02pvO2RQwnBgC0S29/8p3++/VP5fEaXXFeqiaMSLO6SGgAYQQA0O689vFePfD2ZzJGuu78XvrNdecpykFnQFtFGAEAtCvP/32n/mfpV5KkW37QRw9ffS6rrbZxhBEAQLtgjNHTH+zQnFXfSJLuvKif7v/PsxknchogjAAATnvllR49uXKbnvv7LknSzy/rr6kXn0kQOU0QRgAAp61vDx7Xax/v1ZLN/1ZhWaUk6cErB+qnY1hP5HRCGAEAnFbcVV6t+rJA//fxHq3/9rB/e8/EWP1/2WfrmmE9LSwdWoIwAgA4LXx78Lhe3/RvLdn8bx06XiFJstukSwYk6+aMPvqP/t3kYKDqaYkwAgBos4rLK7X0X/v1+uZ/a/Oeo/7tyZ1cunFkmiaM6q2eibEWlhDB0KJJ1/PmzVN6erpiYmKUkZGhDRs2NLr/66+/rgEDBigmJkbnnXeeli1b1qLCAgDaF2OMyis9Olri1vfHyrTjwHF9/l2h1mw7oJy/bNWoR1drxpufafOeo3LYbRo7IFkL/ut8/WPGJcq57GyCSDsRcMvI4sWLlZOTowULFigjI0Nz585Vdna2tm3bpuTk5Dr7r1+/XjfddJNyc3N15ZVX6rXXXtM111yjLVu2aNCgQUE5CQBA8Blj5PZ4VV7pVUWlR2WVHlVUeeWu8qqiyqtKT/X37hPfl1V6VFxepeLyShVXVKm4vErHy6t0vKJKpe4qlbmrn6PU7VF5pcd/32saL0e/bh11w4g0/WhYTyXHx4Tn5BFWNmNME2+DmjIyMjRy5Eg988wzkiSv16u0tDTdc889mjFjRp39J0yYoJKSEr377rv+bT/4wQ80dOhQLViwoN7XqKioUEVFhf9+UVGR0tLSVFhYqPj4+ECK26gXPtqlfx8tDdrztQXGSGVuj0rcVSp1e1RSceKru0per1FMtEOuaIdiouyKdToUE+WQK9quKq9RZZVXbk/NPzBeI0U5bIp22BXtsCnKbvd/7zVGHq9RlffEV0/1VyOjKLvdf1yU3aboKLui7TbZG5hmZ1T9h89rTn5vTjzg8Rp5je928r4xks0mOU48r91mk8Mu//dWMqounzGqLqvvnAL6bWttGerWqSR/GXxVZLfZZLNJNkk2m0311dypPxNz6s+oGefjex2bzSZ7E6/TUl5j5DHVZfK/X7zV26Xqc5RNJ16/+nx95+0rm00nHrfZapyrt4F6q32Mx/d74PXW+b2o8npV6TGq9Hhr3Jd871+d8h4+8fNooILstpO/V86o6q9RJ+77f3c9Ru4qjyo9Ru4qr4yM//ntdslhs8lury6/16i6zJ5TyuytPq68yhPW96wzyq7YaIdiox3q4HIoo28X3TAiTcPSEpmie5oqKipSQkJCk5/fAbWMuN1ubd68WTNnzvRvs9vtysrKUl5eXr3H5OXlKScnp8a27Oxsvf322w2+Tm5urh5++OFAitYiS//1vbbsPRby1wGA053dJsVEOxQT7ZDTYZczqvqfEmeUQ84ou5wOm2KiHeoUE6VOrmjFxUSpU0yU4lzVXzs4o9TBWR00Yp3Vtw7RUYpx2tXBGaWYKDvLtUewgMLIoUOH5PF4lJKSUmN7SkqKvv7663qPyc/Pr3f//Pz8Bl9n5syZNQKMr2Uk2K4b3kuZ7exy0jbZqn/JnQ51dEapg6v6a6zTIYfdpvJKj8orvSe+Vt8qqrxynPgvK9phl+vEV6fDLrtdqvSc/O/OXeVVldeoyuOV3W5TlN0mh91+4mv1fUmqPLFPlae6mbfKU/2f4In2jnr5WjNq/6dut9uq/5OzSXb7yRYQm2z+1hKv18jjaz3xNvYq4WOTJH9rwKnnFMYy+P97P/nftq9Nwqi69eDUVo7Gas4mX+vCiee0nzyvhvies7qF4dTWleD+hGw68T6x12xh8E2s8L++zMlymIZbsPw/r1rnKtV/jIz8r1/798Fht8npqP6gjXL4vq9uZZTkb/XzeKt/Hr73cUO8XnOyleVEC4vv99MXEny/y9UhwS6bTf6WIs+J3xHvifJH2W2n/C5Xl8tX5phou2JOtKBGO2y0TiBk2uRsGpfLJZfLFfLXuTmjT8hfAwAANC6gNrGkpCQ5HA4VFBTU2F5QUKDU1NR6j0lNTQ1ofwAAEFkCCiNOp1PDhw/X6tWr/du8Xq9Wr16tzMzMeo/JzMyssb8krVq1qsH9AQBAZAm4myYnJ0eTJk3SiBEjNGrUKM2dO1clJSWaPHmyJGnixInq2bOncnNzJUn33nuvLrroIj355JMaN26cFi1apE2bNunZZ58N7pkAAIDTUsBhZMKECTp48KBmzZql/Px8DR06VMuXL/cPUt27d6/s9pMNLhdccIFee+01/epXv9Ivf/lLnXXWWXr77bdZYwQAAEhqwTojVmjuPGUAANB2NPfzm0ndAADAUoQRAABgKcIIAACwFGEEAABYijACAAAsRRgBAACWIowAAABLEUYAAICl2uRVe2vzrctWVFRkcUkAAEBz+T63m1pf9bQII8XFxZKktLQ0i0sCAAACVVxcrISEhAYfPy2Wg/d6vfr+++/VqVMn2Wy2oD1vUVGR0tLStG/fvoheZp56oA4k6sCHeqAOJOrAp7X1YIxRcXGxevToUeO6dbWdFi0jdrtdvXr1Ctnzx8fHR/SbzYd6oA4k6sCHeqAOJOrApzX10FiLiA8DWAEAgKUIIwAAwFIRHUZcLpdmz54tl8tldVEsRT1QBxJ14EM9UAcSdeATrno4LQawAgCA9iuiW0YAAID1CCMAAMBShBEAAGApwggAALAUYQQAAFgqosPIvHnzlJ6erpiYGGVkZGjDhg1WFylkPvzwQ1111VXq0aOHbDab3n777RqPG2M0a9Ysde/eXbGxscrKytL27dutKWyI5ObmauTIkerUqZOSk5N1zTXXaNu2bTX2KS8v19SpU9W1a1fFxcXpuuuuU0FBgUUlDo358+dr8ODB/hUVMzMz9d577/kfj4Q6qO3xxx+XzWbT9OnT/dvaez089NBDstlsNW4DBgzwP97ez/9U3333nf7rv/5LXbt2VWxsrM477zxt2rTJ/3h7//uYnp5e571gs9k0depUSeF5L0RsGFm8eLFycnI0e/ZsbdmyRUOGDFF2drYOHDhgddFCoqSkREOGDNG8efPqffyJJ57QU089pQULFujjjz9Wx44dlZ2drfLy8jCXNHTWrVunqVOn6p///KdWrVqlyspKXXbZZSopKfHvc9999+lvf/ubXn/9da1bt07ff/+9fvSjH1lY6uDr1auXHn/8cW3evFmbNm3SJZdcovHjx+uLL76QFBl1cKqNGzfqf//3fzV48OAa2yOhHs4991zt37/ff/voo4/8j0XC+UvS0aNHNXr0aEVHR+u9997Tl19+qSeffFKdO3f279Pe/z5u3Lixxvtg1apVkqQbbrhBUpjeCyZCjRo1ykydOtV/3+PxmB49epjc3FwLSxUeksxbb73lv+/1ek1qaqr57W9/69927Ngx43K5zJ///GcLShgeBw4cMJLMunXrjDHV5xwdHW1ef/11/z5fffWVkWTy8vKsKmZYdO7c2Tz//PMRVwfFxcXmrLPOMqtWrTIXXXSRuffee40xkfFemD17thkyZEi9j0XC+fvcf//9ZsyYMQ0+Hol/H++9917Tr18/4/V6w/ZeiMiWEbfbrc2bNysrK8u/zW63KysrS3l5eRaWzBq7du1Sfn5+jfpISEhQRkZGu66PwsJCSVKXLl0kSZs3b1ZlZWWNehgwYIB69+7dbuvB4/Fo0aJFKikpUWZmZsTVwdSpUzVu3Lga5ytFznth+/bt6tGjh8444wzdfPPN2rt3r6TIOX9J+utf/6oRI0bohhtuUHJysoYNG6bnnnvO/3ik/X10u93605/+pClTpshms4XtvRCRYeTQoUPyeDxKSUmpsT0lJUX5+fkWlco6vnOOpPrwer2aPn26Ro8erUGDBkmqrgen06nExMQa+7bHevjss88UFxcnl8ulO++8U2+99ZYGDhwYUXWwaNEibdmyRbm5uXUei4R6yMjI0EsvvaTly5dr/vz52rVrly688EIVFxdHxPn77Ny5U/Pnz9dZZ52lFStW6K677tLPfvYzvfzyy5Ii7+/j22+/rWPHjunWW2+VFL7fhaigPRNwGpk6dao+//zzGn3kkeTss8/W1q1bVVhYqCVLlmjSpElat26d1cUKm3379unee+/VqlWrFBMTY3VxLHH55Zf7vx88eLAyMjLUp08f/eUvf1FsbKyFJQsvr9erESNG6LHHHpMkDRs2TJ9//rkWLFigSZMmWVy68HvhhRd0+eWXq0ePHmF93YhsGUlKSpLD4agzGrigoECpqakWlco6vnOOlPqYNm2a3n33Xa1Zs0a9evXyb09NTZXb7daxY8dq7N8e68HpdOrMM8/U8OHDlZubqyFDhugPf/hDxNTB5s2bdeDAAZ1//vmKiopSVFSU1q1bp6eeekpRUVFKSUmJiHo4VWJiovr3768dO3ZEzPtAkrp3766BAwfW2HbOOef4u6wi6e/jnj179P777+u2227zbwvXeyEiw4jT6dTw4cO1evVq/zav16vVq1crMzPTwpJZo2/fvkpNTa1RH0VFRfr444/bVX0YYzRt2jS99dZb+uCDD9S3b98ajw8fPlzR0dE16mHbtm3au3dvu6qH+ni9XlVUVERMHYwdO1afffaZtm7d6r+NGDFCN998s//7SKiHUx0/flzffvutunfvHjHvA0kaPXp0nSn+33zzjfr06SMpcv4+StLChQuVnJyscePG+beF7b0QtKGwp5lFixYZl8tlXnrpJfPll1+aO+64wyQmJpr8/HyrixYSxcXF5pNPPjGffPKJkWTmzJljPvnkE7Nnzx5jjDGPP/64SUxMNO+8847517/+ZcaPH2/69u1rysrKLC558Nx1110mISHBrF271uzfv99/Ky0t9e9z5513mt69e5sPPvjAbNq0yWRmZprMzEwLSx18M2bMMOvWrTO7du0y//rXv8yMGTOMzWYzK1euNMZERh3U59TZNMa0/3r47//+b7N27Vqza9cu849//MNkZWWZpKQkc+DAAWNM+z9/nw0bNpioqCjz6KOPmu3bt5v/+7//Mx06dDB/+tOf/PtEwt9Hj8djevfube6///46j4XjvRCxYcQYY55++mnTu3dv43Q6zahRo8w///lPq4sUMmvWrDGS6twmTZpkjKmevvbggw+alJQU43K5zNixY822bdusLXSQ1Xf+kszChQv9+5SVlZm7777bdO7c2XTo0MFce+21Zv/+/dYVOgSmTJli+vTpY5xOp+nWrZsZO3asP4gYExl1UJ/aYaS918OECRNM9+7djdPpND179jQTJkwwO3bs8D/e3s//VH/729/MoEGDjMvlMgMGDDDPPvtsjccj4e/jihUrjKR6zysc7wWbMcYEr50FAAAgMBE5ZgQAALQdhBEAAGApwggAALAUYQQAAFiKMAIAACxFGAEAAJYijAAAAEsRRgAAgKUIIwAAwFKEEQAAYCnCCAAAsNT/D0AC278nYjwFAAAAAElFTkSuQmCC\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -1722,13 +1776,15 @@ "\n", "plt.title(\"Share of turns skipped\")\n", "plt.plot(1 - np.mean(history_changed(_board_history), axis=1))\n", - "# plt.yscale('log',base=10)\n", + "plt.xlabel(\"Turn\")\n", + "plt.ylabel(\"Factor of skipped turns\")\n", + "plt.yscale(\"log\", base=10)\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 150, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -1737,7 +1793,7 @@ "(70, 10000)" ] }, - "execution_count": 150, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -1755,29 +1811,105 @@ }, { "cell_type": "code", - "execution_count": 151, + "execution_count": 69, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "69\n", + "68\n", + "67\n", + "66\n", + "65\n", + "64\n", + "63\n", + "62\n", + "61\n", + "60\n", + "59\n", + "58\n", + "57\n", + "56\n", + "55\n", + "54\n", + "53\n", + "52\n", + "51\n", + "50\n", + "49\n", + "48\n", + "47\n", + "46\n", + "45\n", + "44\n", + "43\n", + "42\n", + "41\n", + "40\n", + "39\n", + "38\n", + "37\n", + "36\n", + "35\n", + "34\n", + "33\n", + "32\n", + "31\n", + "30\n", + "29\n", + "28\n", + "27\n", + "26\n", + "25\n", + "24\n", + "23\n", + "22\n", + "21\n", + "20\n", + "19\n", + "18\n", + "17\n", + "16\n", + "15\n", + "14\n", + "13\n", + "12\n", + "11\n", + "10\n", + "9\n", + "8\n", + "7\n", + "6\n", + "5\n", + "4\n", + "3\n", + "2\n", + "1\n", + "0\n" + ] + }, { "data": { "text/plain": [ - "array([0.06513542, 0.02282552, 0.08712565, 0.05031332, 0.1214854 ,\n", - " 0.06314092, 0.14037841, 0.0759323 , 0.16290323, 0.08841437,\n", - " 0.18861413, 0.10899313, 0.19318856, 0.10964757, 0.20731361,\n", - " 0.13148691, 0.22510605, 0.13292382, 0.23539045, 0.12585808,\n", - " 0.23848829, 0.15176572, 0.26641954, 0.17761089, 0.28060736,\n", - " 0.16112694, 0.31286326, 0.17623532, 0.28714693, 0.16549503,\n", - " 0.33439531, 0.19199073, 0.29858216, 0.20875418, 0.33700629,\n", - " 0.1993395 , 0.36539974, 0.24731134, 0.36773293, 0.24404735,\n", - " 0.42837075, 0.28564118, 0.41564522, 0.28406984, 0.41368105,\n", - " 0.2341238 , 0.39596409, 0.26595149, 0.39103311, 0.38067557,\n", - " 0.47846166, 0.30745852, 0.4819794 , 0.38419044, 0.5611122 ,\n", - " 0.524575 , 0.546425 , 0.466925 , 0.601625 , 0.570625 ,\n", - " 0.570625 , 0.35625 , 0.36875 , 0.36875 , 0.38125 ,\n", - " 0.38125 , 0.38125 , 0.38125 , 0.38125 , 0.39715854])" + "array([ 0.09677184, 0.0037773 , 0.12190913, 0.03519891, 0.16118614,\n", + " 0.00617017, 0.12490022, -0.03918723, 0.14632847, -0.01240192,\n", + " 0.1016851 , 0.00991888, 0.1295861 , -0.03332988, 0.07552515,\n", + " -0.10090606, 0.14730492, -0.08930635, 0.08367957, -0.09071304,\n", + " 0.1600462 , 0.08287025, 0.22077531, -0.07559336, 0.1789458 ,\n", + " 0.02836975, 0.23077469, 0.01503086, 0.13597608, -0.18159241,\n", + " -0.03167801, -0.23491001, 0.05792499, -0.04478127, 0.06121092,\n", + " -0.04067385, 0.37884519, 0.04386898, 0.17202373, -0.05840784,\n", + " 0.0441777 , -0.14009038, 0.02019953, -0.09193809, 0.15851489,\n", + " 0.08095611, 0.45275764, 0.13625955, 0.36563693, -0.05076633,\n", + " 0.28810459, -0.22580677, -0.16507096, -0.5579012 , -0.033314 ,\n", + " -0.15883 , 0.23115 , -0.45325 , -0.37125 , -0.58125 ,\n", + " -0.21875 , -0.21875 , -0.21875 , -0.21875 , -0.21875 ,\n", + " -0.21875 , -0.21875 , -0.21875 , -0.21875 , -0.14133253])" ] }, - "execution_count": 151, + "execution_count": 69, "metadata": {}, "output_type": "execute_result" } @@ -1809,26 +1941,117 @@ " return combined_score\n", "\n", "\n", - "np.max(calculate_q_reword(_board_history, gamma=0.8), axis=1)" + "calculate_q_reword(\n", + " _board_history, gamma=0.8, who_won_fraction=0, final_score_fraction=1\n", + ")[:, 0]" ] }, { "cell_type": "code", - "execution_count": 152, + "execution_count": 60, "metadata": {}, "outputs": [ { - "ename": "NameError", - "evalue": "name 'rewords' is not defined", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[1;32mIn[152], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mrewords\u001B[49m\n\u001B[0;32m 2\u001B[0m evaluate_boards(boards)\u001B[38;5;241m.\u001B[39mshape\n", - "\u001B[1;31mNameError\u001B[0m: name 'rewords' is not defined" - ] + "data": { + "text/plain": [ + "array([-1.53249554e-06, -1.91561943e-06, -2.39452428e-06, -2.99315535e-06,\n", + " -3.74144419e-06, -4.67680524e-06, -5.84600655e-06, -7.30750819e-06,\n", + " -9.13438523e-06, -1.14179815e-05, -1.42724769e-05, -1.78405962e-05,\n", + " -2.23007452e-05, -2.78759315e-05, -3.48449144e-05, -4.35561430e-05,\n", + " -5.44451787e-05, -6.80564734e-05, -8.50705917e-05, -1.06338240e-04,\n", + " -1.32922800e-04, -1.66153499e-04, -2.07691874e-04, -2.59614843e-04,\n", + " -3.24518554e-04, -4.05648192e-04, -5.07060240e-04, -6.33825300e-04,\n", + " 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final_score_fraction=0\n", + ")[:, 0]" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 3.09670969, 0.12088712, 3.9011089 , 1.12638612,\n", + " 5.15798265, 0.19747831, 3.99684789, -1.25394014,\n", + " 4.68257483, -0.39678147, 3.25402317, 0.31752896,\n", + " 4.1469112 , -1.066361 , 2.41704875, -3.22868907,\n", + " 4.71413867, -2.85732667, 2.67834167, -2.90207292,\n", + " 5.12240885, 2.65301107, 7.06626383, -2.41717021,\n", + " 5.72853724, 0.91067155, 7.38833944, 0.4854243 ,\n", + " 4.35678037, -5.80402453, -1.00503067, -7.50628834,\n", + " 1.86713958, -1.41607552, 1.9799056 , -1.27511801,\n", + " 12.15610249, 1.44512812, 5.55641015, -1.80448732,\n", + " 1.49439085, -4.38201144, 0.77248571, -2.78439287,\n", + " 5.26950892, 2.83688614, 14.79610768, 4.7451346 ,\n", + " 12.18141825, -1.02322719, 9.97096602, -6.28629248,\n", + " -4.1078656 , -16.384832 , 0.76896 , -2.7888 ,\n", + " 10.264 , -10.92 , 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sRYsWae3atdq3b5/mzZunX/7yl65mSEpKUufOnSVJnTt31vTp0/Xd735XX375pTp06OBKhttuu00+n08ffvihUlNTa+4//fTTdeONN7qSofb3oWvXrjrrrLN03nnn6ZJLLtG8efP0ox/9yNUMXvIqx2233aaEhAStXbu2zs9Bz549NW7cOBljXM8U6+go+qmhHF7xMgMdZRf6iX5qKIdX6CdUo5/op4ZyeIV+cl/UPFNq8eLF6tu3r/Ly8jRhwgTNmTPH04Ny+PBhPf300+rdu7cyMzNdmfn111/rtdde05QpU+r8kFZr27atKzn8ufjii3XmmWfqH//4h2cZYsWBAwf0xhtvNPhzIEk+n8/lVIj1jqKfUI2Osg/9RD/BQT/Zh36in+CI5X6KmkWp2bNna8KECZKcp9SVlJRo5cqVrmZYunSp2rRpozZt2igtLU0vvfSSFi1apLg4d76NO3bskDFGffv2dWVesPr27atdu3a5Mqv2sai+PfDAA67MbizH1VdfHfGZ1T8HeXl5de7PysqqyfGLX/wi4jkk/8dh9OjRrsy2Tax3FP1Ulw0d5UU/SfZ0FP30LfqJfqqNfvK+nyQ6qhr9RD/VRj/FZj9Fxcv3tm7dqg8//FBLliyRJCUkJOjaa6/V7NmzddFFF7mWY/jw4Zo1a5Yk6eDBg3riiSc0evRoffjhh+revXvE59v+dD1jjGurt7WPRbX27du7MruxHA2tarvhww8/VFVVlcaPH6/y8nJXZvo7DqtXr665uIgVdBT9VJ8NHWVTP0nudxT95KCf6Kf66KeTcQ3lDfqJfqqPfjpZLPRTVCxKzZ49W8ePH1d2dnbNfcYYJSUl6bHHHlNGRoYrOVJTU9W7d++aP//lL39RRkaGnnrqKf32t7+N+Pw+ffrI5/Npy5YtEZ8Vis2bN7v2JnD1j4VXvMjRu3dv+Xw+bd26tc79PXv2lCSlpKS4lsXf33/Pnj2uzbcFHUU/1WdDR3mVwZaOop8c9BP9VB/95H0/SXSURD9J9FN99FNs9pP1L987fvy4/vrXv+qPf/yj8vPza24bNmxQdna2J5+4Vs3n8ykuLk5Hjx51ZV779u31ve99T48//rjKyspO+rqXHx+7bNkyffzxx7rqqqs8yxArMjMzNWLECD322GN+fw7gLjrKQT+hGh1lD/rJQT+hGv1kD/rJQT+hWiz3k/XPlFq6dKkOHjyom2666aTV8quuukqzZ8/WLbfc4kqW8vJy7du3T5Lz1M7HHntMhw8f1tixY12ZL0mPP/64hg4dqnPPPVf33nuvBgwYoOPHj+vNN9/UrFmztHnz5ohnqP4+VFZW6osvvtBrr72mmTNnasyYMZo4cWLE59fOUFtCQoKysrJcme+1J554QkOHDtU555yju+++WwMGDFBcXJzWrFmjLVu26Oyzz/Y6Ysygo75FP52cozY6io5yG/30Lfrp5By10U/0k9vop2/RTyfnqI1+ioF+MpYbM2aMueyyy/x+bfXq1UaS2bBhQ8RzTJo0yUiquaWlpZnBgweb559/PuKz6yssLDRTpkwx3bt3N61atTJdu3Y1V1xxhVm+fHnEZ9f+PiQkJJgOHTqYSy+91MyZM8dUVlZGfH79DLVveXl5rsyvnWPcuHGuzqytsLDQ3H777aZHjx4mMTHRtGnTxpx77rnm97//vSkrK4v4/Ib+/suXLzeSzMGDByOewQZ0VF2x3k/1c3jVUV73kzHedhT95KCf6qKf6KdqXEN5j36qi36in6rFYj/5jLH83dUAAAAAAADQ4lj/nlIAAAAAAABoeViUAgAAAAAAgOtYlAIAAAAAAIDrWJQCAAAAAACA61iUAgAAAAAAgOtYlAIAAAAAAIDrWJQCAAAAAACA61iUAgAAAAAAgOtYlAIAAAAAAIDrWJRqgf785z8rLS1Nx48fr7nv8OHDSkxM1EUXXVRn2xUrVsjn82nnzp117jfGaPTo0fL5fHrhhRcCmjt8+HD95S9/8fu1yZMny+fz1bmNGjXqpO1efvllDRkyRCkpKWrXrp2+//3vN3v2RRddVGdup06ddPXVV+vzzz/3u/2BAweUk5Mjn8+n4uLigOYDCFyoHbVr166TeqT69txzzzU5t7kddcopp5y0zYMPPhjQ37lHjx566623/H6t9uPGx8crOztbN910kw4ePFjn+zBu3Dh16dJFqampGjhwoBYsWBDQbACBa+411KpVq3TxxRcrNTVV6enpuvDCC3X06NEm595www266667/H7t7rvvPql7+vbt63fbcF+/cQ0F2KM5/bRz505deeWV6tChg9LT03XNNdfoiy++CGhuc/vpJz/5iXr16qWUlBR16NBB48aN05YtWwKa3dx+2rBhg66//nrl5uYqJSVF/fr10yOPPBLQbLiHRakWaPjw4Tp8+LDWrl1bc9+//vUvde7cWatXr9axY8dq7l++fLm6deumXr161XmMhx9+WD6fL+CZX3/9td577z2NHTu2wW1GjRqloqKimtuzzz5b5+t///vf9cMf/lA33HCDNmzYoPfee08/+MEPwjL7xz/+sYqKilRYWKgXX3xRBQUFmjBhgt9tb7rpJg0YMKDJuQBCE2pH5ebm1umQoqIi3XPPPWrTpo1Gjx7d6MxwdJQk3XvvvXW2ueOOO5r8+27cuFEHDx7UsGHDGtym+nF3796tBQsW6J133tHUqVNrvv7+++9rwIAB+vvf/66NGzfqhhtu0MSJE7V06dIm5wMIXHOuoVatWqVRo0Zp5MiR+vDDD7VmzRrdfvvtiotr/HK7srJSS5cu1RVXXNHgNqeffnqd7nn33Xf9bheJ6zeuoQA7hNpPZWVlGjlypHw+n5YtW6b33ntP33zzjcaOHauqqqpGZ4ajn84++2zNnTtXmzdv1uuvvy5jjEaOHKnKyspGZ4ejn9atW6eOHTvq6aef1ieffKJf/epXmjFjhh577LFGZ8NdCV4HQPjl5eWpS5cuWrFihc477zxJ3/4r+7Jly/TBBx/UrKavWLFCw4cPr7N/fn6+/vjHP2rt2rXq0qVLQDNffvllnXXWWerUqVOD2yQlJalz585+v3b8+HFNmzZNv//973XTTTfV3H/aaaeFZXbr1q1rZnfp0kW33367fvKTn5y03axZs1RcXKz//u//1quvvtrkbADBC7Wj4uPjT+qQJUuW6JprrlGbNm0andncjqqWlpbW5Db1vfjiixo1apQSExMDetyuXbtq0qRJdRbFfvnLX9bZftq0aXrjjTf0j3/8Q2PGjAkqD4CGNeca6s4779TUqVM1ffr0Oo/XlPfff1+JiYkaPHhwg9skJCQ02T2Run7jGgqwQ6j99N5772nXrl1av3690tPTJUnz589Xu3bttGzZMl166aUNzgxHP9188801//+UU07Rb3/7W5155pnatWvXSU+MqC0c/XTjjTfW2b5nz55atWqV/vGPf+j2229v8HHhLp4p1UINHz5cy5cvr/nz8uXLddFFF2nYsGE19x89elSrV6+uc0F15MgR/eAHP9Djjz8e1C9eL730ksaNG9foNitWrFDHjh2Vl5enW2+9VQcOHKj52kcffaS9e/cqLi5OgwYNUpcuXTR69Ght2rQpLLNr+/rrr7V48WINGTKkzv2ffvqp7r33Xv31r39t8l81ATRPqB1V27p165Sfn19nIbshze2oag8++KAyMzM1aNAg/f73v6/zFPrmzK5t7969+uc//3lSR9VXUlKi9u3bB/y4AAITSj/t379fq1evVseOHXXBBReoU6dOGjZsWIPPaKrtpZde0tixYxt9htP27duVnZ2tnj17avz48dq9e3edr0fy+q02rqEAb4XST+Xl5fL5fEpKSqrZLzk5WXFxcU12VDj6qbaysjLNnTtXPXr0UG5ubpOzw9FP9XH9ZCGDFumpp54yqamppqKiwpSWlpqEhASzf/9+88wzz5gLL7zQGGPM22+/bSSZzz//vGa/m2++2dx00001f5ZklixZ0uisY8eOmTZt2phNmzY1uM2zzz5rXnzxRbNx40azZMkS069fPzN48GBz/Pjxmq9LMt26dTPPP/+8Wbt2rbn++utNZmamOXDgQLNmDxs2zCQmJprU1FTTunVrI8mceuqp5rPPPqvzOAMGDDB/+9vfjDHGLF++3EgyBw8ebPTvDiA0oXZUbbfeeqvp169fk7PC0VHGGPPHP/7RLF++3GzYsMHMmjXLtG3b1tx5552Nzt6zZ49p1apVo13SvXt306pVK5OammqSk5ONJDNkyJBG91m0aJFp1apVo38nAKEJpZ9WrVplJJn27dubOXPmmI8++sj89Kc/Na1atTLbtm1rdF6fPn3M0qVLG/z6K6+8YhYvXmw2bNhgXnvtNXP++eebbt26mdLS0pptInX9xjUUYJdQ+mn//v0mPT3dTJs2zZSVlZnDhw+b22+/3UgyN998c6PzwtFPxhjz+OOPm9TUVCPJ5OXlmR07djQ6N1z9VN97771nEhISzOuvv97ofLiLRakWavv27UaSef/9983LL79sTjvtNGOMMXv37jVJSUnm6NGj5te//rXp2bNnzT4vvvii6d27tzl06FDNfYFc1Lzyyit1HicQO3fuNJLMW2+9ZYwxZsGCBUaSefLJJ2u2OXbsmMnKyjJ//vOfmzV72LBhZvLkyWb79u1m+/bt5t133zWXXXaZ6dOnT01h3nnnnebaa6+t2YcLKiCyQumo2o4cOWIyMjLMH/7whyZnhaOj/Jk9e7ZJSEgwx44da3CbJ554wlx88cWNzurevbv51a9+ZbZv3262bdtm3n77bTNkyBBzwQUX1FkUq7Zs2TLTunVrM3/+/MD/QgACFko/vffee0aSmTFjRp3HOuOMM8z06dMbnPXpp5+a1NRUc/To0YDzHTx40KSnp5u//OUvxpjIXr9xDQXYJdTrp9dff9307NnT+Hw+Ex8fbyZMmGDOOussc8sttzQ4Kxz9VK24uNhs27bNrFy50ow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di1IAAAAAAADwHYtSAAAAAAAA8B2LUgAAAAAAAPAdi1IAAAAAAADwXcDzPM/PgSUlJcrMzJQCUodefk4OOrhT8iqlQILUvqf/88lABmsZXM+XpNIdkjypuLhYGRkZbkLIfT9JNo6H6wyu55OBDHVZ6Cj6iQxW5pPBVgb6KcjCsSADGazMt5Ih1H5ytygFAHWYWZQCgAaY+EsfADSAfgJgVXP9lORjltp4pRQZyGAig+v50vFVdDP4l764PyfJQIaaTHUU/RT3GVzPJ4OtDPRTkIVjQQYyWJlvJUOo/eRsUap9D2n8Nv/nPpctlW4PHhgX88lABmsZXM+XpGd7BYvTClf9JNk4Hq4zuJ5PBjLUZamj6CcyuJ5PBlsZ6KcgC8eCDGSwMt9KhlD7iQ86BwAAAAAAgO9YlAIAAAAAAIDvWJQCAAAAAACA79x90DmAVsvRUPXQQKUqXYe1X0Var0IVuI4FAPQTANPoKNS0e6W0b71Uvl9KTpc6DZS6DHOdCvEq3vqJRSkgxiQrVWfpeuVpsnqr/v9abtVK5WuGlmmuynXYQUIA8Yp+AmAZHYWajh6SNs2V1s6Q9hTU/33WUOm0yVLf66WkNL/TId7Ecz/x9j0ghnRTf03VOt2op5WtwQ1uk63BulFPa6rWqZv6+ZwQQLyinwBYRkehpn0fS/MHSW/fJO1Z3fA2e1YHfz9/kFT8ib/5EF/ivZ9YlAJiRDf11916X511ogIKKEGJDW6XoEQFFFBnnai7tbTNlRYAe+gnAJbRUahp38fSi2dLpduO3VDZyIbHbi/dJi0YzsIUooN+CnNRatq0aTrrrLOUnp6ubt266eqrr9aGDRuilQ3AMclK1e16XalKV6KSQ7pPopKVqnTdrkVKVmqUE7pHPwFu0E+hoaMAN+io5sVTPx09JL06WiovkbyK0O7jVQS3/9uo4P2BSKGfgsJalHr77bc1adIkvf/++1q0aJHKy8s1evRolZaWRisfAEln6XplqU/IZVUlUcnqopN0pq6LUjI76CfADfopNHQU4AYd1bx46qdNc6UDW0JfkKriVQTvt2ledHIhPtFPQWF90PnChQtr/XnOnDnq1q2bVqxYoQsuuCCiwQAcl6fJ8lSpQCMv52xKpSqUp9u0RM9EIZkd9BPgBv0UGjoKcIOOal489dPaGQq+LKOxt+w1JSF4/9yJkc2E+EU/BbXqM6WKi4slSSeccEJEwgCoL0dD1VvDGn1/cXMSlKg+OkM5GhrZYMbRT0D00U8tR0cB0UdHtUxb7afdK499y15LFqQUvN+elcHHAVqLfjourFdK1VRZWakf/OAHOu+883Taaac1ul1ZWZnKysqq/1xSUtLSkUBc6qGBEXmc7spVoQoi8ljW0U+AP+inlgmlo+gnoPXoqPC15X7atz5Cj7NB6jIsMo+F+EU/HdfiV0pNmjRJa9eu1dy5c5vcbtq0acrMzKz+ycnJaelIIC6lKj0ij5OmjIg8TiygnwB/0E8tE0pH0U9A69FR4WvL/VS+P0KPExtrcDCOfjquRYtS3//+9/XKK68oPz9f2dnZTW47ZcoUFRcXV/8UFha2KCgQrw4rMv8Lekjx8b+g9BPgH/opfKF2FP0EtB4dFZ623k/JkVkDUHLsrwHAAPrpuLDevud5nm677TYtWLBAixcv1sknn9zsfVJSUpSSktLigEC8K1JkXmscqcexin4C/Ec/hS7cjqKfgNajo0ITL/3UKTLvlorY4yC+0U/HhfVKqUmTJunZZ5/V888/r/T0dBUVFamoqEiHDh2KVj4g7hWqQFu1UpUK87trj6lUhbZohbZpVYST2UI/Af6jn0JHRwH+o6NCEy/91GWYlDVULf8AmwQpa5jUZWjkMiF+0U/HhXVJzpw5U8XFxRo5cqR69uxZ/TNv3rxo5QMgKV8zFGjh/4ImKFH5eizCieyhnwA36KfQ0FGAG3RU8+Kpn06brFZ9+95pkyOZBvGOfgoK++17APy3THM1Vj9TZ52oRCWHfL8KlWuvtmu52t6TirroJ8AN+ik0dBTgBh3VvHjqp77XSyvulUq3SV4YL1AJJEodsqW+10UvG+IP/RTU4m/fA+Cfch3Woxqtw9qvCpWHdJ8Kleuw9utRjVK5Dkc5IYB4RT8BsIyOQk1JadJlrwc/rDyQGNp9AonB7ccuCt4fiBT6KYhFKSBG7NInmq7h2qvtktTo+4+rbt+r7Zqu4dqljb5lBBCf6CcAltFRqKnTAOmapcFXPklq/G/Ex27vkB3cPrO/H+kQb+gnFqWAmLJLGzVVgzRHE1Wogga3KVSB5miipmpQmyorALbRTwAso6NQU2Z/adw6acRsKWtIw9tkDQn+ftw6FqQQXfHeT2F9phQA98p1WEv0jJboGeVoqLorV2nK0CGV6DNtaLTIACDa6CcAltFRqCkpTcqdGPzZvVLat0EqLwm+Va9TbvDb+gC/xHM/sSgFxLBCFbTpggIQu+gnAJbRUaipyzAWoWBHvPUTb98DAAAAAACA71iUAgAAAAAAgO9YlAIAAAAAAIDvAp7neX4OLCkpUWZmphSQOvTyc3LQwZ2SVykFEqT2Pf2fTwYyWMvger4kle6Q5EnFxcXKyMhwE0Lu+0mycTxcZ3A9nwxkqMtCR9FPZLAynwy2MtBPQRaOBRnIYGW+lQyh9pO7RSkAqMPMohQANMDEX/oAoAH0EwCrmusnd9++xyulyEAGExlcz5eOr6Kbwb/0xf05SQYy1GSqo+inuM/gej4ZbGWgn4IsHAsykMHKfCsZQu0nZ4tS7XtI47f5P/e5bKl0e/DAuJhPBjJYy+B6viQ92ytYnFa46ifJxvFwncH1fDKQoS5LHUU/kcH1fDLYykA/BVk4FmQgg5X5VjKE2k980DkAAAAAAAB8x6IUAAAAAAAAfMeiFAAAAAAAAHzn7oPOY1SOhqqHBipV6Tqs/SrSehWqwNcMu1dK+9ZL5ful5HSp00CpyzBfIzjP4Ho+GWAR/UQGK/OtZIAd9BMZyADLXJ8PrueTgQwusSgVgmSl6ixdrzxNVm/VPxu2aqXyNUPLNFflOhyVDEcPSZvmSmtnSHsK6v8+a6h02mSp7/VSUlpUIjjP4Ho+GWAR/UQGK/OtZIAd9BMZyADLXJ8PrueTgQxW8Pa9ZnRTf03VOt2op5WtwQ1uk63BulFPa6rWqZv6RTzDvo+l+YOkt2+S9qxueJs9q4O/nz9IKv4k4hGcZ3A9nwywiH4ig5X5VjLADvqJDGSAZa7PB9fzyUAGS1iUakI39dfdel+ddaICCihBiQ1ul6BEBRRQZ52ou7U0ok+s9n0svXi2VFr1NY6VjWx47PbSbdKC4ZE9UV1ncD2fDLCIfiKDlflWMsAO+okMZIBlrs8H1/PJQAZrwlqUmjlzpgYPHqyMjAxlZGTonHPO0WuvvRatbE4lK1W363WlKl2JSg7pPolKVqrSdbsWKVmprc5w9JD06mipvETyKkK7j1cR3P5vo4L3j/UMrueTIXbQT02jn9pmBtfzrWSIBfHSUfQTGcgQe+KlnyT354Pr+WQgg0VhLUplZ2dr+vTpWrFihZYvX64LL7xQV111lT766KNo5XPmLF2vLPUJ+QlVlUQlq4tO0pm6rtUZNs2VDmwJ/QSt4lUE77dpXqsjOM/gej4ZYgf91Dz6qe1lcD3fSoZYEC8dRT+RgQyxJ176SXJ/PrieTwYyWBTWotQVV1yhyy67TP3799eAAQP0wAMPqGPHjnr//fejlc+ZPE2W1+hr55pWqQrl6bZWZ1g7Qy1/g2XCsfvHeAbX88kQO+in0NBPbSuD6/lWMsSCeOko+okMZIg98dJPkvvzwfV8MpDBopbuAlVUVGju3LkqLS3VOeecE8lMzuVoqHprWKOfgdCcBCWqj85Qjoa2OMPulcc+db9lz+ukSmnPyuDjxGoG1/PJELvop8bRT20ng+v5VjLEorbaUfQTGcgQ+9pqP0nuzwfX88lABqvCXpRas2aNOnbsqJSUFN1yyy1asGCBTj311Ea3LysrU0lJSa0f63poYEQep7tyW3zffesjEkH7NrTivo4zuJ5PhthDP4WOfor9DK7nW8kQS8LpKPqpZSyck2QgQyxq6/0kuT8fXM8nAxmsCntRKjc3VwUFBVq6dKn+8z//UxMmTNC//vWvRrefNm2aMjMzq39ycnJaFdgPqUqPyOOkKaPF9y3fH5EIKm/F/0a4zuB6PhliD/0UOvop9jO4nm8lQywJp6Pop5axcE6SgQyxqK33k+T+fHA9nwxksCrsRal27dqpX79+OuOMMzRt2jQNGTJEjz76aKPbT5kyRcXFxdU/hYWFrQrsh8OKzBlySC0/Q5Ij87xOyS1/Xuc8g+v5ZIg99FPo6KfYz+B6vpUMsSScjqKfWsbCOUkGMsSitt5PkvvzwfV8MpDBqqTWPkBlZaXKysoa/X1KSopSUlJaO8ZXRYrMa+la8zidIvMK+FY9jusMrueTIfbRT9F5HAvnJBncz7eSIZY11VH0U8tYOCfJQIa2oK31k+T+fHA9nwxksCqsV0pNmTJF77zzjjZv3qw1a9ZoypQpWrx4scaPHx+tfE4UqkBbtVKVCvO7GY+pVIW2aIW2aVWLM3QZJmUNVas+jT9rmNRlaIsjOM/gej4ZYgv9FBr6qe1kcD3fSoZYEQ8dRT+RgQyxKR76SXJ/PrieTwYyWBXWLti1a5duvPFG5ebm6qKLLtKyZcv097//XaNGjYpWPmfyNUOBFp4hCUpUvh5rdYbTJqtVn8Z/2uRWR3CewfV8MsQO+ik09FPbyuB6vpUMsSBeOop+IgMZYk+89JPk/nxwPZ8MZLAorGcNs2bN0ubNm1VWVqZdu3bpjTfeaJNlJUnLNFd7tEUVKg/rfhUq125t1nLNa3WGvtdLHftIgTC/WTmQGLxf3+taHcF5BtfzyRA76Kfm0U9tL4Pr+VYyxIJ46Sj6iQxkiD3x0k+S+/PB9XwykMGilr5YrM0r12E9qtE6rP0hP7GqULkOa78e1SiV63CrMySlSZe9HvzwslBP1EBicPuxi4L3j/UMrueTARbRT2SwMt9KBthBP5GBDLDM9fngej4ZyGARi1JN2KVPNF3DtVfbJanRz0ioun2vtmu6hmuXNkYsQ6cB0jVLpQ7Zx25o7Igdu71DdnD7zP4Ri+A8g+v5ZIBF9BMZrMy3kgF20E9kIAMsc30+uJ5PBjJYw6JUM3Zpo6ZqkOZoogpV0OA2hSrQHE3UVA2K6BOqKpn9pXHrpBGzpawhDW+TNST4+3HronOCus7gej4ZYBH9RAYr861kgB30ExnIAMtcnw+u55OBDJYkuQ4QC8p1WEv0jJboGeVoqLorV2nK0CGV6DNtaPTJViQlpUm5E4M/u1dK+zZI5SXBl+51yg1+en9bz+B6PhlgEf1EBivzrWSAHfQTGcgAy1yfD67nk4EMVrAoFaZCFfjyJKopXYa5PyldZ3A9nwywiH4ig5X5VjLADvqJDGSAZa7PB9fzyUAGl3j7HgAAAAAAAHzHohQAAAAAAAB8x6IUAAAAAAAAfBfwPM/zc2BJSYkyMzOlgNShl5+Tgw7ulLxKKZAgte/p/3wykMFaBtfzJal0hyRPKi4uVkZGhpsQct9Pko3j4TqD6/lkIENdFjqKfiKDlflksJWBfgqycCzIQAYr861kCLWf3C1KAUAdZhalAKABJv7SBwANoJ8AWNVcP7n79j1eKUUGMpjI4Hq+dHwV3Qz+pS/uz0kykKEmUx1FP8V9BtfzyWArA/0UZOFYkIEMVuZbyRBqPzlblGrfQxq/zf+5z2VLpduDB8bFfDKQwVoG1/Ml6dleweK0wlU/STaOh+sMrueTgQx1Weoo+okMrueTwVYG+inIwrEgAxmszLeSIdR+4oPOAQAAAAAA4DsWpQAAAAAAAOA7FqUAAAAAAADgO3cfdN4CORqqHhqoVKXrsParSOtVqAIyOMiwe6W0b71Uvl9KTpc6DZS6DIuf+UBdFq5LMgRZ6AcLGYCaXF+brudbyWChGyxkAGri2mQfWMoA/5lflEpWqs7S9crTZPVW/TNyq1YqXzO0THNVrsNkiGKGo4ekTXOltTOkPQX1f581VDptstT3eikpre3NB+qycF2SIchCP1jIANTk+tp0Pd9KBgvdYCEDUBPXJvvAUga4Zfrte93UX1O1TjfqaWVrcIPbZGuwbtTTmqp16qZ+ZIhShn0fS/MHSW/fJO1Z3fA2e1YHfz9/kFT8SduaD9Rl4bokQ5CFfrCQAajJ9bXper6VDBa6wUIGoCauTfaBpQxwz+yiVDf11916X511ogIKKEGJDW6XoEQFFFBnnai7tTSiFywZgvZ9LL14tlRa9VWSlY1seOz20m3SguGRKw3X84G6LFyXZAiy0A8WMgA1ub42Xc+3ksFCN1jIANTEtck+sJQBNrRqUWr69OkKBAL6wQ9+EKE4QclK1e16XalKV6KSQ7pPopKVqnTdrkVKVioZIpTh6CHp1dFSeYnkVYR2H68iuP3fRgXvH8vzEbvop7afwUI/WMiA2BOtfpLcX5uu51vJYKEbLGRAbGrLz6FcXxfsAzsZYEeLF6WWLVum3/72txo8uOGXG7bGWbpeWeoT8oVaJVHJ6qKTdKauI0OEMmyaKx3YEnpZVPEqgvfbNC+25yM20U/xkcFCP1jIgNgSzX6S3F+brudbyWChGyxkQOxp68+hXF8X7AM7GWBHixalDhw4oPHjx+vJJ59U586dI51JeZosr9HX7zWtUhXK021kiFCGtTPU8qXLhGP3j+H5iD30U/xksNAPFjIgdkS7nyT316br+VYyWOgGCxkQW+LhOZTr64J9YCcD7GjRqTBp0iSNHTtWF198caTzKEdD1VvDGn1vbXMSlKg+OkM5GkqGVmbYvfLYNyC0rDelSmnPyuDjxOJ8xCb6KT4yWOgHCxkQW6LZT5L7a9P1fCsZLHSDhQyIPW39OZTr64J9YCcDbAl7UWru3Ln68MMPNW3atJC2LysrU0lJSa2fpvTQwHAjNai7clt8XzIE7VsfkQjatyE25yP20E/xk8FCP1jIgNgR7X6S3F+brudbyWChGyxkQGwJp6NisZ8k99cF+8BOBtgS1qJUYWGhbr/9dj333HNKTQ3tQ9amTZumzMzM6p+cnJwmt09VejiRGpWmjBbflwxB5fsjEkHlzf/vlMn5iC30U3xlsNAPFjIgNvjRT5L7a9P1fCsZLHSDhQyIHeF2VCz2k+T+umAf2MkAW8JalFqxYoV27dqlL3/5y0pKSlJSUpLefvttzZgxQ0lJSaqoqP9JZVOmTFFxcXH1T2FhYZMzDisyZ+khtfwsJUNQcmR6U8kt7E3X8xFb6Kf4ymChHyxkQGzwo58k99em6/lWMljoBgsZEDvC7ahY7CfJ/XXBPrCTAbYkhbPxRRddpDVr1tS67Vvf+pYGDhyou+66S4mJ9d8fm5KSopSUlJBnFCkyr+drzeOQIahTZF5h2uLHcT0fsYV+iq8MFvrBQgbEBj/6SXJ/bbqebyWDhW6wkAGxI9yOisV+ktxfF+wDOxlgS1iLUunp6TrttNNq3dahQwdlZWXVu72lClWgrVqpbA1u0YfAVapChSrQNq0iQyszdBkmZQ2V9qxWyz6ILkHKGiJ1GRqb8xFb6Kf4ymChHyxkQGzwo58k99em6/lWMljoBgsZEDvi5TmU6+uCfWAnA2xp6RcxRlW+ZijQwmgJSlS+HiNDhDKcNlmt+maE0ybH9nygLgvXJRmCLPSDhQxATa6vTdfzrWSw0A0WMgA1cW2yDyxlgB2tXpRavHixHnnkkQhEOW6Z5mqPtqhC5WHdr0Ll2q3NWq55ZIhQhr7XSx37SIEwF/MDicH79b0utucjttFPbTuDhX6wkAGxKRr9JLm/Nl3Pt5LBQjdYyIDY1VafQ7m+LtgHdjLADpOvlCrXYT2q0Tqs/SFfsBUq12Ht16MapXIdJkOEMiSlSZe9HvwguVBLI5AY3H7souD9Y3k+UJeF65IMQRb6wUIGoCbX16br+VYyWOgGCxmAmrg22QeWMsAOk4tSkrRLn2i6hmuvtksKvoe2IVW379V2Tddw7dJGMkQ4Q6cB0jVLpQ7Zx25o7Kw5dnuH7OD2mf3bxnygLgvXJRmCLPSDhQxATa6vTdfzrWSw0A0WMgA1cW2yDyxlgA1mF6UkaZc2aqoGaY4mqlAFDW5TqALN0URN1aCIXqhkqC2zvzRunTRidvCD5RqSNST4+3HrIl8WrucDdVm4LskQZKEfLGQAanJ9bbqebyWDhW6wkAGoiWuTfWApA9wL69v3XCjXYS3RM1qiZ5SjoequXKUpQ4dUos+0odGLmAyRl5Qm5U4M/uxeKe3bIJWXBF9G2Sk3+E0KbXk+UJeF65IMQRb6wUIGoCbX16br+VYyWOgGCxmAmrg22QeWMsAt84tSNRWqwJeLkwzN6zLMbUG4ng/UZeG6JMP/Z+/ew6Oq77X/vycHkhCSgAnIIQGRQ8BSCFVEaxWjBc+1/loVi1sp1G4rFdpetpUetnhEq20VrbS1ArZqkd1d1IdWKtqotUUUTVAUEKhAOBVBknAKhmT9/hhyPs0kM+v7mcz9uq5cz+NkzXzuru9a954s5hBkoR8sZBBpyPW56Xq+lQwWusFCBpGGdG5qH1jKIP4z/fY9ERERERERERHpmnRRSkREREREREREfKeLUiIiIiIiIiIi4ruA53menwMrKirIysqCAKT393Ny0OFd4NVAIAG69/N/vjIog7UMrucDHNoJeFBeXk5mZqabELjvJ7CxHq4zuJ6vDMrQlIWOUj8pg5X5ymArg/opyMJaKIMyWJlvJUOo/eTuopSISBNmLkqJiLTAxB99IiItUD+JiFXt9ZO7b9/TK6WUQRlMZHA9H+qvopuhf+mL+2NSGZShIVMdpX6K+wyu5yuDrQzqpyALa6EMymBlvpUMofaTs4tS3fvClO3+z30qFw7tCC6Mi/nKoAzWMrieD/Bk/2BxWuGqn8DGerjO4Hq+MihDU5Y6Sv2kDK7nK4OtDOqnIAtroQzKYGW+lQyh9pM+6FxERERERERERHyni1IiIiIiIiIiIuI7XZQSERERERERERHfufug8w7YWwxl66HqACRnQM8RkDM2/jLkUUBfRpBKBpUcYDfrKaUkrjJYWAdlkIYsrIWFDK67wUoG12vher6VDFLP9Xq4ng82usFCBgtroQzSkIW1cJ3BQjdYyOB6HZTBDfMXpY4dgc2LYe082FfS/PfZBTBqJgyZDElpXTdDMqmMYzKFzGQgzY/IbRRTxDzeYjFVVHbJDBbWQRmkIQtrYSGD626wksH1WriebyWD1HO9Hq7ng41usJDBwloogzRkYS1cZ7DQDRYyuF4HZXDP9Nv3yj6EJSPh1Wmw792Wt9n3bvD3S0ZC+caumaEPw5jDOq5jAbmMbnGbXEZzHQuYwzr6MLTLZbCwDsogDVlYCwsZXHeDlQyu18L1fCsZpJ7r9XA9H2x0g4UMFtZCGaQhC2vhOoOFbrCQwfU6KIMNZi9KlX0Iz54Bh2q/vrCmlQ2P335oOywdH9kFspChD8O4lTfoxQACBEggscXtEkgkQIBeDOBWVkW0NFxnsLAOyiANWVgLCxlcd4OVDK7XwvV8Kxmknuv1cD0fbHSDhQwW1kIZpCELa+E6g4VusJDB9Toogx1hXZSaM2cOgUCg0c+IESMiHurYEfjrJKiqAK86tPt41cHt/zIxeP+ukCGZVGbxIqlkkEhySPdJJJlUMpjFCpJJjfkMFtZBGWKD+snfDK67wUoG12vher6VDLEgXjrK9Xyw0Q0WMlhYC2WIDfHSTxYyWOgGCxlcr4My2BL2K6U+85nPsGvXrrqf119/PeKhNi+Gg1tDX5haXnXwfpuf6RoZxjGZbAaFXBa1Ekkmh5M4jatjPoOFdVCG2KF+8i+D626wksH1WriebyVDrIiHjnI9H2x0g4UMFtZCGWJHPPSThQwWusFCBtfroAy2hH1RKikpib59+9b95OTkRDzU2nkdSXZcwvH7d4EMhczEa/X1e22roZpCbo75DBbWQRlih/rJvwyuu8FKBtdr4Xq+lQyxIh46yvV8sNENFjJYWAtliB3x0E8WMljoBgsZXK+DMtgS9i7YuHEj/fv35+STT2bKlCls27YtooH2Fh//tPmOnSdQA/uKg48TyxnyKGAgY1t9f297EkhkEKeSR0HMZrCwDsoQW9RP/mRw3Q1WMrheC9fzrWSIJV29o1zPBxvdYCGDhbVQhtjS1fvJQgYL3WAhg+t1UAZ7wrooNX78eBYtWsTy5cuZP38+H330EWeffTYHDhxo9T5Hjx6loqKi0U9bytaHk6iNx9nQifsayNCXyLyP+0TyYzaDhXVQhtihfvIvg+tusJLB9Vq4nm8lQ6wIt6PC7Sdwvx6u54ONbrCQwcJaKEPsiId+spDBQjdYyOB6HZTBnqRwNr7ooovq/v+jR49m/PjxDBo0iCVLljB9+vQW7zN37lxuv/32kGdUtf73Y1iq2u9G0xlSyYhIhjQyYzaDhXVQhtihfvIvg+tusJLB9Vq4nm8lQ6wIt6PC7Sdwvx6u54ONbrCQwcJaKEPsiId+spDBQjdYyOB6HZTBno6+gxGAnj17Mnz4cDZt2tTqNrNnz6a8vLzup7S0tM3HTI7MeUJyx88TExkqicxReoSOH6WuM1hYB2WIXeqn6GVw3Q1WMrheC9fzrWSIVe11VLj9BO7Xw/V8sNENFjJYWAtliF1dsZ8sZLDQDRYyuF4HZbCnUxelDh48yObNm+nXr1+r26SkpJCZmdnopy09I/Tto515HAsZdhOZ1/N15nFcZ7CwDsoQu9RP0Xsc191gJYPrtXA930qGWNVeR4XbT+B+PVzPBxvdYCGDhbVQhtjVFfvJQgYL3WAhg+t1UAZ7wroodcstt/Dqq6+yZcsW/vWvf3HFFVeQmJjINddcE7FAOWMhuyDcZA0kQPZYyCmI7QyllLCNYmoI8/shj6uhmq28zXbWxGwGC+ugDLFD/eRfBtfdYCWD67VwPd9KhlgRDx3lej7Y6AYLGSyshTLEjnjoJwsZLHSDhQyu10EZ7AlrF2zfvp1rrrmG/Px8rrrqKrKzs3njjTfo3bt3REONmkmnPoV+1MyukaGIeQQ6eJQmkEgRD8d8BgvroAyxQf3kbwbX3WAlg+u1cD3fSoZYEC8d5Xo+2OgGCxksrIUyxIZ46ScLGSx0g4UMrtdBGWwJ62hcvHgxO3fu5OjRo2zfvp3FixczZMiQiIcaMhl6DIJAmN9UGUgM3m/I1V0jw1ssZh9bqaYqrPtVU8VetrCaZ2I+g4V1UIbYoH7yN4PrbrCSwfVauJ5vJUMsiJeOcj0fbHSDhQwW1kIZYkO89JOFDBa6wUIG1+ugDLZ06jOloiUpDS5+MfihXaEuUCAxuP0lK4L37woZqqjkISZRyYGQS6OaKio5wENMpIrKmM9gYR2UQRqysBYWMrjuBisZXK+F6/lWMkg91+vhej7Y6AYLGSyshTJIQxbWwnUGC91gIYPrdVAGW0xelALoORyuWAXpucdvaC3p8dvTc4PbZw3rWhn2sJF7Gc9+dgC0+v7f2tv3s4N7Gc8eWv/GsVjLYGEdlEEasrAWFjK47gYrGVyvhev5VjJIPdfr4Xo+2OgGCxksrIUySEMW1sJ1BgvdYCGD63VQBjvMXpSC4I6+ah1MWAjZY1reJntM8PdXrYvOwljIsIdNzGEki5hKKSUtblNKCYuYyhxGRrQsrGSwsA7KIA1ZWAsLGVx3g5UMrtfC9XwrGaSe6/VwPR9sdIOFDBbWQhmkIQtr4TqDhW6wkMH1OiiDDUmuA7QnKQ3ypwZ/9hZD2Qaoqgi+ZK1nfvBT6+MhQxWVrOQJVvIEeRRwIvmkkckRKvgPG1otkq6UwcI6KIM0ZGEtLGRw3Q1WMrheC9fzrWSQeq7Xw/V8sNENFjJYWAtlkIYsrIXrDBa6wUIG1+ugDO6ZvyjVUM5Y94thIUMpJb4UhOUMFtZBGaQhC2thIYPrbrCSwfVauJ5vJYPUc70erueDjW6wkMHCWiiDNGRhLVxnsNANFjK4XgdlcMP02/dERERERERERKRr0kUpERERERERERHxnS5KiYiIiIiIiIiI7wKe53l+DqyoqCArKwsCkN7fz8lBh3eBVwOBBOjez//5yqAM1jK4ng9waCfgQXl5OZmZmW5C4L6fwMZ6uM7ger4yKENTFjpK/aQMVuYrg60M6qcgC2uhDMpgZb6VDKH2k7uLUiIiTZi5KCUi0gITf/SJiLRA/SQiVrXXT+6+fU+vlFIGZTCRwfV8qL+Kbob+pS/uj0llUIaGTHWU+inuM7ierwy2MqifgiyshTIog5X5VjKE2k/OLkp17wtTtvs/96lcOLQjuDAu5iuDMljL4Ho+wJP9g8Vphat+Ahvr4TqD6/nKoAxNWeoo9ZMyuJ6vDLYyqJ+CLKyFMiiDlflWMoTaT/qgcxERERERERER8Z0uSomIiIiIiIiIiO90UUpERERERERERHzn7oPOO2BvMZSth6oDkJwBPUdAztj4y5BHAX0ZQSoZVHKA3aynlJK4yuB6vkhTFrpBGZTBynyxx/Ux4Xo+2HjuYGE/KINYY+F4cJ1B/aQM8cz8RaljR2DzYlg7D/aVNP99dgGMmglDJkNSWtfNkEwq45hMITMZSPOzYhvFFDGPt1hMFZVdMoPr+SJNWegGZVAGK/PFHtfHhOv5YOO5g4X9oAxijYXjwXUG9ZMySJDpt++VfQhLRsKr02Dfuy1vs+/d4O+XjITyjV0zQx+GMYd1XMcCchnd4ja5jOY6FjCHdfRhaJfL4Hq+SFMWukEZlMHKfLHH9THhej7YeO5gYT8og1hj4XhwnUH9pAxSz+xFqbIP4dkz4FDt1xfWtLLh8dsPbYel4yN7kFjI0Idh3Mob9GIAAQIkkNjidgkkEiBALwZwK6siWlyuM7ieL9KUhW5QBmWwMl/scX1MuJ4PNp47WNgPyiDWWDgeXGdQPymDNBb2RakdO3Zw7bXXkp2dTVpaGp/97GdZvXp1REMdOwJ/nQRVFeBVh3Yfrzq4/V8mBu/fFTIkk8osXiSVDBJJDuk+iSSTSgazWEEyqTGfwfV8iS3qJ2WItwyu50t44qGjXM8HG88dLOwHZZBwxEM/WcigflIGaS6si1L79+/nrLPOIjk5mRdeeIEPPviAn//85/Tq1SuioTYvhoNbQz84annVwfttfqZrZBjHZLIZFHJh1UokmRxO4jSujvkMrudL7FA/KUM8ZnA9X0IXLx3lej7YeO5gYT8og4QqXvrJQgb1kzJIc2FdlLrvvvvIy8tj4cKFnH766QwePJhJkyYxZMiQiIZaOy/cZA0kHL9/F8hQyEy8Vl9D2LYaqink5pjP4Hq+xA71kzLEYwbX8yV08dJRrueDjecOFvaDMkio4qWfLGRQPymDNBfWMjz//POcdtppXHnllfTp04exY8fy2GOPRTTQ3uLjn3jfsXMVamBfcfBxYjlDHgUMZGyr7zFuTwKJDOJU8iiI2Qyu50tsUT8pQ7xlcD1fwhMPHeV6Pth47mBhPyiDhCMe+slCBvWTMkjLwroo9e9//5v58+czbNgw/va3v/Gtb32LmTNn8sQTT7R6n6NHj1JRUdHopy1l68NJ1MbjbOjEfQ1k6MuIiGQ4kfyYzeB6vsQW9ZMyxFsG1/MlPOF2VLj9BO6PCdfzwcZzBwv7QRkkHPHQTxYyqJ+UQVqWFM7GNTU1nHbaadxzzz0AjB07lrVr1/LrX/+a66+/vsX7zJ07l9tvvz3kGVUHwknUxuO0342mM6SSEZEMaWTGbAbX8yW2qJ+UId4yuJ4v4Qm3o8LtJ3B/TLieDzaeO1jYD8og4YiHfrKQQf2kDNKysF4p1a9fP0455ZRGt40cOZJt27a1ep/Zs2dTXl5e91NaWtrmjOTInKskd+I6hIUMlUTmTDlCx88U1xlcz5fYon5ShnjL4Hq+hCfcjgq3n8D9MeF6Pth47mBhPyiDhCMe+slCBvWTMkjLwnql1FlnncWGDY1fo/bhhx8yaNCgVu+TkpJCSkpKyDN6RuZVjZ16HAsZdhOZ1xR25nFcZ3A9X2KL+kkZ4i2D6/kSnnA7Ktx+AvfHhOv5YOO5g4X9oAwSjnjoJwsZ1E/KIC0L65VS3/3ud3njjTe455572LRpE08//TS//e1vmTFjRsQC5YyF7IJwkzWQANljIacgtjOUUsI2iqkhzO+oPK6GarbyNttZE7MZXM+X2KJ+UoZ4y+B6voQnHjrK9Xyw8dzBwn5QBglHPPSThQzqJ2WQloW1DOPGjWPp0qX88Y9/ZNSoUdx55508+OCDTJkyJaKhRs2kU5+EP2pm18hQxDwCHTxTEkikiIdjPoPr+RI71E/KEI8ZXM+X0MVLR7meDzaeO1jYD8ogoYqXfrKQQf2kDNJc2GfEpZdeynvvvUdlZSXr1q3jhhtuiHioIZOhxyAIhPltmYHE4P2GXN01MrzFYvaxlWqqwrpfNVXsZQureSbmM7ieL7FF/aQM8ZbB9XwJTzx0lOv5YOO5g4X9oAwSjnjoJwsZ1E/KIM119AVrUZWUBhe/GPzgsFAPkkBicPtLVgTv3xUyVFHJQ0yikgMhF1c1VVRygIeYSBWVMZ/B9XyRpix0gzIog5X5Yo/rY8L1fLDx3MHCflAGscbC8eA6g/pJGaQ5kxelAHoOhytWQXru8RtaS3r89vTc4PZZw7pWhj1s5F7Gs58dAK2+B7n29v3s4F7Gs4dNXSaD6/kiTVnoBmVQBivzxR7Xx4Tr+WDjuYOF/aAMYo2F48F1BvWTMkhjZi9KQXCxr1oHExZC9piWt8keE/z9Veuic3BYyLCHTcxhJIuYSiklLW5TSgmLmMocRkblYozrDK7nizRloRuUQRmszBd7XB8TrueDjecOFvaDMog1Fo4H1xnUT8og9ZJcB2hPUhrkTw3+7C2Gsg1QVRF82VzP/OAn58dDhioqWckTrOQJ8ijgRPJJI5MjVPAfNrRaZl0pg+v5Ik1Z6AZlUAYr88Ue18eE6/lg47mDhf2gDGKNhePBdQb1kzJIkPmLUg3ljHV/QFjIUEqJ8wswrjO4ni/SlIVuUAZlsDJf7HF9TLieDzaeO1jYD8og1lg4HlxnUD8pQzwz/fY9ERERERERERHpmnRRSkREREREREREfKeLUiIiIiIiIiIi4ruA53menwMrKirIysqCAKT393Ny0OFd4NVAIAG69/N/vjIog7UMrucDHNoJeFBeXk5mZqabELjvJ7CxHq4zuJ6vDMrQlIWOUj8pg5X5ymArg/opyMJaKIMyWJlvJUOo/eTuopSISBNmLkqJiLTAxB99IiItUD+JiFXt9ZO7b9/TK6WUQRlMZHA9H+qvopuhf+mL+2NSGZShIVMdpX6K+wyu5yuDrQzqpyALa6EMymBlvpUMofaTs4tS3fvClO3+z30qFw7tCC6Mi/nKoAzWMrieD/Bk/2BxWuGqn8DGerjO4Hq+MihDU5Y6Sv2kDK7nK4OtDOqnIAtroQzKYGW+lQyh9pM+6FxERERERERERHyni1IiIiIiIiIiIuI7XZQSERERERERERHfufug8w7YWwxl66HqACRnQM8RkDNWGeIxQx4F9GUEqWRQyQF2s55SSvwLINKE63NCGZRBpC2uj0nX88HGcwcL+8FCBpGGLByTrjOon+xkEP+Zvyh17AhsXgxr58G+kua/zy6AUTNhyGRISlOGrpwhmVTGMZlCZjKQ5u20jWKKmMdbLKaKysgHEGnC9TmhDMog0hbXx6Tr+WDjuYOF/WAhg0hDFo5J1xnUT3YyiFum375X9iEsGQmvToN977a8zb53g79fMhLKNypDV83Qh2HMYR3XsYBcRre4TS6juY4FzGEdfRga2QAiTbg+J5RBGUTa4vqYdD0fbDx3sLAfLGQQacjCMek6g/rJTgZxz+xFqbIP4dkz4FDt1xfWtLLh8dsPbYel4yN7oCqDjQx9GMatvEEvBhAgQAKJLW6XQCIBAvRiALeyShemJGpcnxPKoAwibXF9TLqeDzaeO1jYDxYyiDRk4Zh0nUH9ZCeD2GDyotSxI/DXSVBVAV51aPfxqoPb/2Vi8P7K0DUyJJPKLF4klQwSSQ7pPokkk0oGs1hBMqmdCyDShOtzQhmUQaQtro9J1/PBxnMHC/vBQgaRhiwck64zqJ/sZBA7wrooddJJJxEIBJr9zJgxI6KhNi+Gg1tDP0BredXB+21+Rhm6SoZxTCabQSGXdq1EksnhJE7j6s4FkJjiR0e5PieUQRkkNsXLcyjX88HGcwcL+8FCBokN8dJPFjKon+xkEDvCuij11ltvsWvXrrqfFStWAHDllVdGNNTaeeEmayDh+P2VoUtkKGQmXquv5WxbDdUUcnPnAkhM8aOjXJ8TyqAMEpvi5TmU6/lg47mDhf1gIYPEhnjpJwsZ1E92MogdYR0KvXv3pm/fvnU/y5YtY8iQIUyYMCFigfYWH//U/Y6dq1AD+4qDj6MMsZ0hjwIGMrbV91m3J4FEBnEqeRR0LIDEnGh3lOtzQhmUQWJXPDyHcj0fbDx3sLAfLGSQ2BEP/WQhg/rJTgaxpcOfKfXpp5/y5JNPMm3aNAKBQKvbHT16lIqKikY/bSlb39FETR5nQyfuqwwmMvRlRETmn0h+RB5HYksoHaV+UoZYzyCxKRr9BO6PSdfzwcZzBwv7wUIGiU1dtZ8sZFA/2ckgtnT4otSzzz5LWVkZU6dObXO7uXPnkpWVVfeTl5fX5vZVBzqaqMnjtN+NymA8QyoZEZmfRmZEHkdiSygdpX5ShljPILEpGv0E7o9J1/PBxnMHC/vBQgaJTV21nyxkUD/ZySC2dPii1OOPP85FF11E//7929xu9uzZlJeX1/2Ulpa2uX1yZM5VkjtxHUIZbGSoJDKNdQQ1VjwKpaPUT8oQ6xkkNkWjn8D9Mel6Pth47mBhP1jIILGpq/aThQzqJzsZxJakjtxp69atvPTSS/z5z39ud9uUlBRSUlJCfuyekXlVY6ceRxlsZNhNZF7bGanHkdgRakepn5Qh1jNI7IlWP4H7Y9L1fLDx3MHCfrCQQWJPV+4nCxnUT3YyiC0deqXUwoUL6dOnD5dcckmk85AzFrIL6NSn8WePhZwCZYj1DKWUsI1iagjzu0KPq6GarbzNdtZ0LIDErGh1lOtzQhmUQWJfV34O5Xo+2HjuYGE/WMggsacr95OFDOonOxnElrAPhZqaGhYuXMj1119PUlKHXmjVrlEz6dSn8Y+aqQxdJUMR8wh0sLESSKSIhzsXQGJOtDvK9TmhDMogsSsenkO5ng82njtY2A8WMkjsiId+spBB/WQng9gR9hnx0ksvsW3bNqZNmxaNPAAMmQw9BkEgzG/LDCQG7zfkamXoKhneYjH72Eo1VWHdr5oq9rKF1TzTuQASc6LdUa7PCWVQBold8fAcyvV8sPHcwcJ+sJBBYkc89JOFDOonOxnEjrAvSk2aNAnP8xg+fHg08gCQlAYXvxj88LJQD9RAYnD7S1YE768MXSNDFZU8xCQqORByeVdTRSUHeIiJVFHZuQASc6LdUa7PCWVQBold8fAcyvV8sPHcwcJ+sJBBYkc89JOFDOonOxnEjg5/+1609RwOV6yC9NzjN7SW9Pjt6bnB7bOGKUNXy7CHjdzLePazA6DV92HX3r6fHdzLePawKTIBRJpwfU4ogzKItMX1Mel6Pth47mBhP1jIINKQhWPSdQb1k50MYoPZi1IQPOCuWgcTFkL2mJa3yR4T/P1V66JzgCqDjQx72MQcRrKIqZRS0uI2pZSwiKnMYaQuSEnUuT4nlEEZRNri+ph0PR9sPHewsB8sZBBpyMIx6TqD+slOBnEvOp9iF0FJaZA/NfiztxjKNkBVRfClez3zg5/erwzxkaGKSlbyBCt5gjwKOJF80sjkCBX8hw2tFrpItLg+J5RBGUTa4vqYdD0fbDx3sLAfLGQQacjCMek6g/rJTgZxy/xFqYZyxro/KJXBRoZSSnQRSkxxfU4ogzKItMX1Mel6Pth47mBhP1jIINKQhWPSdQb1k50M4j/Tb98TEREREREREZGuSRelRERERERERETEd7ooJSIiIiIiIiIivgt4nuf5ObCiooKsrCwIQHp/PycHHd4FXg0EEqB7P//nK4MyWMvgej7AoZ2AB+Xl5WRmZroJgft+Ahvr4TqD6/nKoAxNWego9ZMyWJmvDLYyqJ+CLKyFMiiDlflWMoTaT+4uSomINGHmopSISAtM/NEnItIC9ZOIWNVeP7n79j29UkoZlMFEBtfzof4quhn6l764PyaVQRkaMtVR6qe4z+B6vjLYyqB+CrKwFsqgDFbmW8kQaj85uyjVvS9M2e7/3Kdy4dCO4MK4mK8MymAtg+v5AE/2DxanFa76CWysh+sMrucrgzI0Zamj1E/K4Hq+MtjKoH4KsrAWyqAMVuZbyRBqP+mDzkVERERERERExHe6KCUiIiIiIiIiIr7TRSkREREREREREfGduw8674C9xVC2HqoOQHIG9BwBOWPjL4MF2g8ijVk4JyxksED7QaQ51+eF6/kAeRTQlxGkkkElB9jNekop8TWDhf0gYo2F88J1BvWTxDPzF6WOHYHNi2HtPNhX0vz32QUwaiYMmQxJaV03gwXaDyKNWTgnLGSwQPtBpDnX54Xr+QDJpDKOyRQyk4E0/+tqG8UUMY+3WEwVlVHJYGE/iFhj4bxwnUH9JBJk+u17ZR/CkpHw6jTY927L2+x7N/j7JSOhfGPXzGCB9oNIYxbOCQsZLNB+EGnO9Xnhej5AH4Yxh3VcxwJyGd3iNrmM5joWMId19GFoxDNY2A8i1lg4L1xnUD+J1DN7UarsQ3j2DDhU+/WFNa1sePz2Q9th6fjIniwWMlig/SDSmIVzwkIGC7QfRJpzfV64ng/BP/hu5Q16MYAAARJIbHG7BBIJEKAXA7iVVRH9w8/CfhCxxsJ54TqD+kmkMZMXpY4dgb9OgqoK8KpDu49XHdz+LxOD9+8KGSzQfhBpzMI5YSGDBdoPIs25Pi9cz4fgW2Jm8SKpZJBIckj3SSSZVDKYxQqSSe10Bgv7QcQaC+eF6wzqJ5HmwrooVV1dzU9/+lMGDx5MWloaQ4YM4c4778TzvIiG2rwYDm4N/SSp5VUH77f5ma6RwQLtB4kV6id/M1ig/SCxJF46yvV8gHFMJptBIf/BVyuRZHI4idO4utMZLOwHkVDFSz9ZyKB+EmkurItS9913H/Pnz+eRRx5h3bp13HffffzsZz/j4YcfjmiotfPCTdZAwvH7d4EMFmg/SKxQP/mbwQLtB4kl8dJRrucDFDITr9X3orSthmoKubnTGSzsB5FQxUs/WcigfhJpLqzD8V//+heXX345l1xyCSeddBJf/epXmTRpEm+++WbEAu0tPv7J/x07V6EG9hUHHyeWM1ig/SCxRP3kXwYLtB8k1sRDR7meD8GvVR/I2FY/o6U9CSQyiFPJo6DDGSzsB5FwxEM/WcigfhJpWVgXpT7/+c/z8ssv8+GHHwKwZs0aXn/9dS666KJW73P06FEqKioa/bSlbH04idp4nA2duK+BDBZoP0gsUT/5l8EC7QeJNeF2VLj9BO7PC9fzAfoyIiIZTiS/w/e1sB9EwhEP/WQhg/pJpGVJ4Wx86623UlFRwYgRI0hMTKS6upq7776bKVOmtHqfuXPncvvtt4c8o+pAOInaeJz2u9F0Bgu0HySWqJ/8y2CB9oPEmnA7Ktx+Avfnhev5AKlkRCRDGpkdvq+F/SASjnjoJwsZ1E8iLQvrlVJLlizhqaee4umnn+add97hiSee4IEHHuCJJ55o9T6zZ8+mvLy87qe0tLTNGcmROVdJ7vi5aiKDBdoPEkvUT/5lsED7QWJNuB0Vbj+B+/PC9XyASiLzF9cROv4Xl4X9IBKOeOgnCxnUTyItC+uVUt///ve59dZbmTx5MgCf/exn2bp1K3PnzuX6669v8T4pKSmkpKSEPKNnZF7V2KnHsZDBAu0HiSXqJzeP44r2g8SacDsq3H4C9+eF6/kAu4nMe1M68zgW9oNIOOKhnyxkUD+JtCysV0odPnyYhITGd0lMTKSmpqOflNZczljILgg3WQMJkD0WcgpiO4MF2g8SS9RP/mWwQPtBYk08dJTr+QCllLCNYmoI87vOj6uhmq28zXbWdDiDhf0gEo546CcLGdRPIi0L63C87LLLuPvuu/nLX/7Cli1bWLp0Kb/4xS+44oorIhpq1Ew69Y0Ao2Z2jQwWaD9IrFA/+ZvBAu0HiSXx0lGu5wMUMY9AB//iSiCRIh7udAYL+0EkVPHSTxYyqJ9EmgvrjHj44Yf56le/yk033cTIkSO55ZZb+O///m/uvPPOiIYaMhl6DIJAmN+WGUgM3m/I1V0jgwXaDxIr1E/+ZrBA+0FiSbx0lOv5AG+xmH1spZqqsO5XTRV72cJqnul0Bgv7QSRU8dJPFjKon0SaC+uiVEZGBg8++CBbt27lyJEjbN68mbvuuotu3bpFNFRSGlz8YvAD1EI9WQKJwe0vWRG8f1fIYIH2g8QK9ZO/GSzQfpBYEi8d5Xo+QBWVPMQkKjkQ8h9+1VRRyQEeYiJVVHY6g4X9IBKqeOknCxnUTyLNdfTdpFHXczhcsQrSc4/f0FrS47en5wa3zxrWtTJYoP0g0piFc8JCBgu0H0Sac31euJ4PsIeN3Mt49rMDoNXPcKm9fT87uJfx7GFTxDJY2A8i1lg4L1xnUD+JNGb2ohQED/qr1sGEhZA9puVtsscEf3/VuuicJBYyWKD9INKYhXPCQgYLtB9EmnN9XrieD7CHTcxhJIuYSiklLW5TSgmLmMocRkb0D75aFvaDiDUWzgvXGdRPIvWSXAdoT1Ia5E8N/uwthrINUFURfPlgz/zgNwjEQwYLtB9EGrNwTljIYIH2g0hzrs8L1/Mh+FaZlTzBSp4gjwJOJJ80MjlCBf9hQ6t/DEaShf0gYo2F88J1BvWTSJD5i1IN5Yx1f2JYyGCB9oNIYxbOCQsZLNB+EGnO9Xnhej4EX3Xgxx95bbGwH0SssXBeuM6gfpJ4ZvrteyIiIiIiIiIi0jXpopSIiIiIiIiIiPhOF6VERERERERERMR3Ac/zPD8HlpeX07NnTwC69/NzctDh3YAHBKB7X//nK4MyWMvgej7A4V3B/7esrIysrCw3IXDfT2BkPXRMKoMyNM5goKPUT8pgZb4yGMugfgKMrIUyKIOR+WYyhNhPvl+U2r59O3l5eX6OFJEYUVpaSm5urrP56icRaYvLjlI/iUhb1E8iYlV7/eT7Ramamhp27txJRkYGgUAg7PtXVFSQl5dHaWkpmZmZUUioDLGSwfV8ZYhcBs/zOHDgAP379ychwd27itVPytCVMrie35UyWOiozvYTuF8P1/OVQRmsZVA/1XO9FhYyuJ6vDMoQ6Qyh9lNSZ0J2REJCQkSu4mdmZjpbHGWwlcH1fGWITAaXb9urpX5Shq6YwfX8rpLBdUdFqp/A/Xq4nq8MymAtg/qpnuu1sJDB9XxlUIZIZgiln/RB5yIiIiIiIiIi4jtdlBIREREREREREd/F3EWplJQUbrvtNlJSUpQhzjO4nq8MtjJYYGE/KIMyWJmvDPa43heu5yuDMljL4Hq+JRb2hesMrucrgzK4yuD7B52LiIiIiIiIiIjE3CulREREREREREQk9umilIiIiIiIiIiI+E4XpURERERERERExHe6KCUiIiIiIiIiIr6LqYtSK1euJDExkUsuucT32VOnTiUQCNT9ZGdnc+GFF/Luu+/6nmX37t3cfPPNnHzyyaSkpJCXl8dll13Gyy+/HPXZDfdDcnIyJ554IhMnTmTBggXU1NREfX7TDA1/LrzwQl/mt5dj06ZNvszfvXs3s2bNYujQoaSmpnLiiSdy1llnMX/+fA4fPhz1+VOnTuXLX/5ys9tfeeUVAoEAZWVlUc9gjTpK/dQ0h6uOct1P4Laj1E/NqZ/UT01zqJ/0HMoK9ZP6qWkO9VN89VNMXZR6/PHHufnmm3nttdfYuXOn7/MvvPBCdu3axa5du3j55ZdJSkri0ksv9TXDli1bOPXUU/n73//O/fffz3vvvcfy5cspLCxkxowZvmSo3Q9btmzhhRdeoLCwkFmzZnHppZdy7NgxXzM0/PnjH//oy+z2cgwePDjqc//9738zduxYXnzxRe655x6Ki4tZuXIlP/jBD1i2bBkvvfRS1DNIc/HeUeqn5jlcdpSrfgJ1lEXqJ/VT0xzqJ/WTFeon9VPTHOqn+OqnJNcBQnXw4EGeeeYZVq9eze7du1m0aBE/+tGPfM2QkpJC3759Aejbty+33norZ599Nh9//DG9e/f2JcNNN91EIBDgzTffJD09ve72z3zmM0ybNs2XDA33w4ABA/jc5z7HGWecwfnnn8+iRYv4xje+4WsGl1zluOmmm0hKSmL16tWNjoOTTz6Zyy+/HM/zfM8U79RR6qfWcrjiMoM6yhb1k/qptRyuqJ+klvpJ/dRaDlfUT/6LmVdKLVmyhBEjRpCfn8+1117LggULnC7KwYMHefLJJxk6dCjZ2dm+zPzkk09Yvnw5M2bMaHSQ1urZs6cvOVpy3nnnMWbMGP785z87yxAv9u3bx4svvtjqcQAQCAR8TiXx3lHqJ6mljrJH/aR+kiD1kz3qJ/WTBMVzP8XMRanHH3+ca6+9Fgi+pK68vJxXX33V1wzLli2jR48e9OjRg4yMDJ5//nmeeeYZEhL82Y2bNm3C8zxGjBjhy7xwjRgxgi1btvgyq+Fa1P7cc889vsxuK8eVV14Z9Zm1x0F+fn6j23Nycupy/PCHP4x6Dmh5HS666CJfZlsT7x2lfmrMQke56Cew01Hqp3rqJ/VTQ+on9/0E6qha6if1U0Pqp/jsp5h4+96GDRt48803Wbp0KQBJSUlcffXVPP7445x77rm+5SgsLGT+/PkA7N+/n0cffZSLLrqIN998k0GDBkV9vvWX63me59vV24ZrUeuEE07wZXZbOVq7qu2HN998k5qaGqZMmcLRo0d9mdnSOqxataruyUW8UEepn5qy0FGW+gn87yj1U5D6Sf3UlPqpOT2HckP9pH5qSv3UXDz0U0xclHr88cc5duwY/fv3r7vN8zxSUlJ45JFHyMrK8iVHeno6Q4cOrfvv3/3ud2RlZfHYY49x1113RX3+sGHDCAQCrF+/PuqzOmLdunW+fQhc07VwxUWOoUOHEggE2LBhQ6PbTz75ZADS0tJ8y9LS//7t27f7Nt8KdZT6qSkLHeUqg5WOUj8FqZ/UT02pn9z3E6ijQP0E6qem1E/x2U/m37537Ngxfv/73/Pzn/+ckpKSup81a9bQv39/J9+4VisQCJCQkMCRI0d8mXfCCSdwwQUX8Ktf/YpDhw41+73Lr4/9+9//znvvvcdXvvIVZxniRXZ2NhMnTuSRRx5p8TgQf6mjgtRPUksdZYf6KUj9JLXUT3aon4LUT1IrnvvJ/Culli1bxv79+5k+fXqzq+Vf+cpXePzxx7nxxht9yXL06FF2794NBF/a+cgjj3Dw4EEuu+wyX+YD/OpXv+Kss87i9NNP54477mD06NEcO3aMFStWMH/+fNatWxf1DLX7obq6mv/85z8sX76cuXPncumll3LddddFfX7DDA0lJSWRk5Pjy3zXHn30Uc466yxOO+005syZw+jRo0lISOCtt95i/fr1nHrqqa4jxg11VD31U/McDamj1FF+Uz/VUz81z9GQ+kn95Df1Uz31U/McDamf4qCfPOMuvfRS7+KLL27xd6tWrfIAb82aNVHPcf3113tA3U9GRoY3btw4709/+lPUZze1c+dOb8aMGd6gQYO8bt26eQMGDPC+9KUveUVFRVGf3XA/JCUleb179/a++MUvegsWLPCqq6ujPr9phoY/+fn5vsxvmOPyyy/3dWZDO3fu9L797W97gwcP9pKTk70ePXp4p59+unf//fd7hw4divr81v73FxUVeYC3f//+qGewQB3VWLz3U9McrjrKdT95ntuOUj8FqZ8aUz+pn2rpOZR76qfG1E/qp1rx2E8BzzP+6WoiIiIiIiIiItLlmP9MKRERERERERER6Xp0UUpERERERERERHyni1IiIiIiIiIiIuI7XZQSERERERERERHf6aKUiIiIiIiIiIj4ThelRERERERERETEd7ooJSIiIiIiIiIivtNFKRERERERERER8Z0uSomIiIiIiIiIiO90USrG/PrXvyYjI4Njx47V3Xbw4EGSk5M599xzG237yiuvEAgE2Lx5M5988gk333wz+fn5pKWlMXDgQGbOnEl5eXmj+8ycOZNTTz2VlJQUCgoKwso2ePBgXnrppRZ/99///d8MGTKEtLQ0evfuzeWXX8769evrfr9mzRquueYa8vLySEtLY+TIkTz00EMhzT1y5Ajp6els2rSpxd8HAoG6n6SkJAYOHMj3vvc9jh49WrfNrl27+NrXvsbw4cNJSEjgO9/5TrPHef/99/nKV77CSSedRCAQ4MEHHwwpn0g8i3ZnASxatIjRo0eTmppKnz59mDFjRkjZOtNZEL2+rO2YQCBAYmIi/fv3Z/r06ezfv79umzlz5jTqttqf9PT0sHKIxBM/+ghg37595ObmEggEKCsrazdXe89jvvSlLzFw4EBSU1Pp168f//Vf/8XOnTsbbfPuu+9y9tlnk5qaSl5eHj/72c/anQuwdetW0tLSOHjwYLPfbdmypVG/dOvWjaFDh3LXXXfheV7ddqE+P/rVr37FSSedRGpqKuPHj+fNN98MKaNIvIpmZy1atKjF5xGBQIA9e/a0mautztqyZQvTp09n8ODBpKWlMWTIEG677TY+/fTTRtstWbKEgoICunfvzqBBg7j//vtD2ieR+LsP4KmnnmLMmDF0796dfv36MW3aNPbt2xdSBok8XZSKMYWFhRw8eJDVq1fX3faPf/yDvn37smrVKiorK+tuLyoqYuDAgQwZMoSdO3eyc+dOHnjgAdauXcuiRYtYvnw506dPbzZj2rRpXH311WHlevfdd9m/fz8TJkxo8fennnoqCxcuZN26dfztb3/D8zwmTZpEdXU1AG+//TZ9+vThySef5P333+fHP/4xs2fP5pFHHml39ooVKxg0aBBDhw5tdZuFCxeya9cuPvroIx599FH+8Ic/cNddd9X9/ujRo/Tu3Zuf/OQnjBkzpsXHOHz4MCeffDL33nsvffv2bTeXiES/s37xi1/w4x//mFtvvZX333+fl156iQsuuKDdXJ3trFrR6EuAO+64g127drFt2zaeeuopXnvtNWbOnFn3+1tuuYVdu3Y1+jnllFO48sorw8oiEk/8eA4FMH36dEaPHh1yrvaexxQWFrJkyRI2bNjA//3f/7F582a++tWv1v2+oqKCSZMmMWjQIN5++23uv/9+5syZw29/+9t2Zz/33HMUFhbSo0ePVrd56aWX2LVrFxs3buT222/n7rvvZsGCBXW/D+X50TPPPMP3vvc9brvtNt555x3GjBnDBRdc0O4fvyLxLJqddfXVVzd7HnHBBRcwYcIE+vTp02autjpr/fr11NTU8Jvf/Ib333+fX/7yl/z617/mRz/6Ud02L7zwAlOmTOHGG29k7dq1PProo/zyl7/07e++f/7zn1x33XVMnz6d999/n//93//lzTff5IYbbmh3vkSJJzGnX79+3ty5c+v++wc/+IE3Y8YMb+TIkV5RUVHd7eecc453/fXXt/o4S5Ys8bp16+ZVVVU1+91tt93mjRkzJuRMd9xxh3f11VeHvP2aNWs8wNu0aVOr29x0001eYWFhu481bdo074c//GGrvwe8pUuXNrpt+vTp3sUXX9zi9hMmTPBmzZrV5sxBgwZ5v/zlL9vNJiLR66xPPvnES0tL81566aWwM0WysyLdly31y5133umdcsoprd6npKTEA7zXXnst5Bwi8Sjaz6EeffRRb8KECd7LL7/sAd7+/fvbzdTe85imnnvuOS8QCHiffvpp3cxevXp5R48erdvmhz/8oZefn9/uY5133nne/PnzW/zdRx995AFecXFxo9vPP/9876abbmrxPq09Pzr99NO9GTNm1P13dXW1179//0ZrISLN+fF3n+d53p49e7zk5GTv97//fbuZwu2sn/3sZ97gwYPr/vuaa67xvvrVrzbaZt68eV5ubq5XU1PTqdmh/N13//33eyeffHKz+QMGDGjvf4pEiV4pFYMKCwspKiqq+++ioiLOPfdcJkyYUHf7kSNHWLVqFYWFha0+Tnl5OZmZmSQlJXU60/PPP8/ll18e0raHDh1i4cKFDB48mLy8vDbznXDCCW0+Vk1NDcuWLQt5NsCHH37I3//+d8aPHx/yfUSk46LVWStWrKCmpoYdO3YwcuRIcnNzueqqqygtLW03UzQ6K1ThzAbYsWMH/+///b82O+t3v/sdw4cP5+yzz+50PpGuLJrPoT744APuuOMOfv/735OQENpT7HCfx3zyySc89dRTfP7znyc5ORmAlStXcs4559CtW7e67S644AI2bNjQ6G2/TZWVlfH666/zpS99KaTZAKtXr+btt98O6znUp59+yttvv80Xv/jFutsSEhL44he/yMqVK0N+HJF45Nfffb///e/p3r17o1dhtqQjf3s1/Zvu6NGjpKamNtomLS2N7du3s3Xr1ojObunvvjPPPJPS0lL++te/4nke//nPf/jTn/7ExRdfHPLjSoS5viom4Xvssce89PR0r6qqyquoqPCSkpK8PXv2eE8//bR3zjnneJ7n1f0L3datW1t8jI8//tgbOHCg96Mf/ajF34fzL//bt2/3unXr1u6/Bv7qV7/y0tPTPcDLz89v81VS//znP72kpCTvb3/7W5uP+c9//tPr06ePV11d3eo2gJeamuqlp6d7KSkpHuBdeumldf/C2JReKSUSWdHqrLlz53rJyclefn6+t3z5cm/lypXe+eef7+Xn5zd6xUBTke6sSPfloEGDvG7dunnp6eleamqqB3jjx49v9T5HjhzxevXq5d13330hZRCJZ9Hqo8rKSm/06NHeH/7wB8/zPK+oqCikV0qF8jzG84KvjujevbsHeGeccYa3d+/eut9NnDjR++Y3v9lo+/fff98DvA8++KDVx3zqqae80047rdXf175SKi0tzUtPT/eSk5M9oNmshlp6frRjxw4P8P71r381uv373/++d/rpp7f6WCLiz999nud5I0eO9L71rW+1myfUzqq1ceNGLzMz0/vtb39bd9tvfvMbr3v37t5LL73kVVdXexs2bPBGjBjRYk+EOzvUv/uWLFni9ejRw0tKSvIA77LLLmv1b0OJPr1SKgade+65HDp0iLfeeot//OMfDB8+nN69ezNhwoS69xe/8sornHzyyQwcOLDZ/SsqKrjkkks45ZRTmDNnTqfzPP/883zhC1+gZ8+ebW43ZcoUiouLefXVVxk+fDhXXXVVo/dC11q7di2XX345t912G5MmTWrzMZ977jkuvfTSdv9F8pe//CUlJSWsWbOGZcuW8eGHH/Jf//Vf7f5vE5HOi1Zn1dTUUFVVxbx587jgggs444wz+OMf/8jGjRsb/atiU5HurHCEOvv73/8+JSUlvPvuu7z88ssAXHLJJc0+0wpg6dKlHDhwgOuvv75T2UTiQbT6aPbs2YwcOZJrr702rDyhPo/5/ve/T3FxMS+++CKJiYlcd911jT5svCOee+65kF4l9cwzz9Q9h1qyZAnPPfcct956a6dmi0ho/Pi7b+XKlaxbt67Vz8lrKNTOguArvS+88EKuvPLKRp/XdMMNN/Dtb3+bSy+9lG7dunHGGWcwefJkgDYfN1J/933wwQfMmjWL//mf/+Htt99m+fLlbNmyhRtvvLHd/00SHZ1/35b4bujQoeTm5lJUVNTow3L79+9PXl4e//rXvygqKuK8885rdt8DBw5w4YUXkpGRwdKlS+te+t0Zzz//fEhParKyssjKymLYsGGcccYZ9OrVi6VLl3LNNdfUbfPBBx9w/vnn881vfpOf/OQnIc2+9957292ub9++dR+Il5+fz4EDB7jmmmu466672vygPBHpvGh1Vr9+/QA45ZRT6m7r3bs3OTk5bNu2rdU8keyscIU6Oycnp66bhg0bxoMPPsiZZ55JUVFRo7fAQPCte5deeiknnnhih3OJxIto9dHf//533nvvPf70pz8B1F0wysnJ4cc//jG33357i3lCfR6Tk5NDTk4Ow4cPZ+TIkeTl5fHGG29w5pln0rdvX/7zn/802r72v1v74PFPP/2U5cuXN/rw4dbk5eXV9dHIkSPZvHkzP/3pT5kzZ06zt+C0lj0xMbHFjPriGJG2+fF33+9+9zsKCgo49dRT280Tamft3LmTwsJCPv/5zzf70oVAIMB9993HPffcw+7du+ndu3fdP8CdfPLJnZ7d3t99c+fO5ayzzuL73/8+AKNHjyY9PZ2zzz6bu+66q+75pfhHr5SKUYWFhbzyyiu88sorjb4S9JxzzuGFF17gzTffbPa+4tpvZ+nWrRvPP/98SE8k2nPw4EGKiorCem8vBJ+seZ7X6Os533//fQoLC7n++uu5++67232MjRs3snXrViZOnBh27sTERCD4HmwRib5odNZZZ50FwIYNG+pu++STT9i7dy+DBg1qMUckOytcHZ0NrXfWRx99RFFRUUj/uikiQdHoo//7v/9jzZo1lJSUUFJSwu9+9zsg+E1ZM2bMaDFHR5/H1NTUANT10Zlnnslrr71GVVVV3TYrVqwgPz+fXr16tfgYr7zyCr169Wr1G4fbkpiYyLFjx5p9xXtrunXrxqmnnlr3R2ft/4aXX36ZM888M+z5IvEmmn/3HTx4kCVLloT0PCLUztqxYwfnnntu3TcZt/bKpsTERAYMGEC3bt344x//yJlnnknv3r07Nbu1OVD/HOrw4cPNMtVu09lXoErH6JVSMaqwsJAZM2ZQVVXV6GvFJ0yYwLe//W0+/fTTRuVUW0yHDx/mySefpKKigoqKCiD4yoLaE3HTpk0cPHiQ3bt3c+TIEUpKSoDgKxEafoBmreXLlzN8+HBOOumkVrP++9//5plnnmHSpEn07t2b7du3c++995KWllb3gXJr167lvPPO44ILLuB73/seu3fvBoIF0Vo5Pffcc3zxi1+ke/fu7e6vsrIydu/eTU1NDRs3buSOO+6o+9fGWrX/Ww8ePMjHH39MSUkJ3bp1q3sVxqeffsoHH3xQ9//fsWMHJSUl9OjRQ6+2EmlHNDpr+PDhXH755cyaNYvf/va3ZGZmMnv2bEaMGNHqh31GqrMgOn1Z68CBA+zevRvP8ygtLeUHP/gBvXv35vOf/3yj7RYsWEC/fv246KKL2n1MEQmKRh8NGTKk0Yy9e/cCwVcWtfZ23VCex6xatYq33nqLL3zhC/Tq1avuVUpDhgypu6Dzta99jdtvv53p06fzwx/+kLVr1/LQQw/xy1/+stXHDfVVmwD79u1j9+7dHDt2jPfee4+HHnqIwsJCMjMzgdCeH33ve9/j+uuv57TTTuP000/nwQcf5NChQ3z9618PKYNIPIvW330QfHvusWPHQnrrcSidVXtBatCgQTzwwAN8/PHHdb+rfWXk3r17+dOf/sS5555LZWUlCxcu5H//93959dVXOzW7Vnt/91122WXccMMNzJ8/nwsuuIBdu3bxne98h9NPP53+/fu3+/gSBe4+zko6o/bDJ0eMGNHo9i1bttR9KG9DtR+42dLPRx99VLfdhAkT2t2moWuvvdb78Y9/3GbWHTt2eBdddJHXp08fLzk52cvNzfW+9rWveevXr6/b5rbbbmtx7qBBg1p93C984QveY4891uZsz/MaPV4gEPD69evnXX311d7mzZtb3a6l+bX7vOnPhAkT2s0gEu+i1Vnl5eXetGnTvJ49e3onnHCCd8UVV3jbtm1rNUekOsvzotOXnhf8oOCGj9e7d2/v4osvbva17NXV1V5ubm6bH1wqIs1Fq49auk9bH3QeyvOYd9991yssLPROOOEELyUlxTvppJO8G2+80du+fXuj7dasWeN94Qtf8FJSUrwBAwZ49957b5uPm5eX561YsaLNbZo+70lMTPRyc3O9G264wduzZ0+r27X2/Ojhhx/2Bg4c6HXr1s07/fTTvTfeeKPN+SISFM3OOvPMM72vfe1rIeUIpbMWLlzY6uxaH3/8sXfGGWd46enpXvfu3b3zzz+/3T6I9N998+bN80455RQvLS3N69evnzdlypRmvSr+CXieXqMmHXPs2DFOPPFEXnjhBU4//XRfZ+/du5d+/fqxfft2fY6KiITEZWe5nC0i9rh8HvPOO+9w3nnn8fHHH0fks0VFpOtz2Vn6u6/r02dKSYd98sknfPe732XcuHFOZv/iF79QMYlIyFx3lqvZImKPy+cxx44d4+GHH9YFKREJmcvO0t99XZ9eKSUiIiIiIiIiIr7TK6VERERERERERMR3uiglIiIiIiIiIiK+00UpERERERERERHxnS5KiYiIiIiIiIiI73RRSkREREREREREfKeLUiIiIiIiIiIi4jtdlBIREREREREREd/popSIiIiIiIiIiPhOF6VERERERERERMR3uiglIiIiIiIiIiK+00UpERERERERERHxnS5KiYiIiIiIiIiI73RRSkREREREREREfJfk98Camhp27txJRkYGgUDA7/EiYpDneRw4cID+/fuTkODuWrn6SURaYqGj1E8i0hL1k4hYFWo/+X5RaufOneTl5fk9VkRiQGlpKbm5uc7mq59EpC0uO0r9JCJtUT+JiFXt9ZPvF6UyMjLq/v/d+/k9HQ7vBjwgAN37+j9fGZTBWgbX8wEO7wr+vw37wQXX/QRG1kPHpDIoQ+MMBjpK/aQMVuYrg7EM6ifAyFoogzIYmW8mQ4j95PtFqdqXdHbvB9fu9Hs6PJULh3ZAen+Yst3/+cqgDNYyuJ4P8GT/YGm5fsm3634CG+vhOoPr+cqgDE1Z6Cj1kzJYma8MtjKon4IsrIUyKIOV+VYyhNpP+qBzERERERERERHxnS5KiYiIiIiIiIiI73RRSkREREREREREfKeLUiIiIiIiIiIi4jvfP+hcRERERERERERs2lsMZeuh6gAkZ0DPEZAzNjqzdFFKRERERERERCSOHTsCmxfD2nmwr6T577MLYNRMGDIZktIiN1dv3xMRERERERERiVNlH8KSkfDqNNj3bsvb7Hs3+PslI6F8Y+Rm66KUiIiIiIiIiEgcKvsQnj0DDm0/fkNNKxsev/3Qdlg6PnIXpsK+KPXaa69x2WWX0b9/fwKBAM8++2xkkoiIdJL6SUSsUj+JiFXqJ5H4dewI/HUSVFWAVx3afbzq4PZ/mRi8f2eFfVHq0KFDjBkzhl/96ledny4iEkHqJxGxSv0kIlapn0Ti1+bFcHBr6BekannVwfttfqbzGcL+oPOLLrqIiy66qPOTRUQiTP0kIlapn0TEKvWTSPxaO4/gS5Vae8teWxKC98+f2rkM+kwpEREREREREZE4srf4+LfsdeSCFMH77SsOPk5nhP1KqXAdPXqUo0eP1v13RUVFtEeKiIRE/SQiVqmfRMQq9ZNI11C2PkKPswFyxnb8/lF/pdTcuXPJysqq+8nLy4v2SBGRkKifRMQq9ZOIWKV+Eukaqg5E6HE6eV066helZs+eTXl5ed1PaWlptEeKiIRE/SQiVqmfRMQq9ZNI15CcEaHHyezc/aP+9r2UlBRSUlKiPUZEJGzqJxGxSv0kIlapn0S6hp4jbDxO2BelDh48yKZNm+r++6OPPqKkpIQTTjiBgQMHdi6NiEgnqJ9ExCr1k4hYpX4SiU85YyG7APa9S4e/fS97DOQUdC5H2BelVq9eTWFhYd1/f+973wPg+uuvZ9GiRZ1LIyLSCeonEbFK/SQiVqmfROLXqJnw6rQO3rkmeP/OCvui1LnnnovneZ2fLCISYeonEbFK/SQiVqmfROLXkMnw9u1waDt41aHfL5AI6bkw5OrOZ4j6B52LiIiIiIiIiIgtSWlw8YvBDysPJIZ2n0BicPtLVgTv31m6KCUiIiIiIiIiEod6DocrVgVf+QS0fpXo+O3pucHts4ZFZr4uSomIiIiIiIiIxKmsYXDVOpiwMPjh5S3JHhP8/VXrIndBCjrwmVIiIiIiIiIiItJ1JKVB/tTgz95iKNsAVRXBt+r1zA9+W19U5kbnYUVEREREREREJNbkjI3eRaim9PY9ERERERERERHxnS5KiYiIiIiIiIiI73RRSkREREREREREfBfwPM/zc2BFRQVZWVkQgPT+fk4OOrwLvBoIJED3fv7PVwZlsJbB9XyAQzsBD8rLy8nMzHQTAvf9BDbWw3UG1/OVQRmastBR6idlsDJfGWxlUD8FWVgLZVAGK/OtZAi1n9xdlBIRacLMRSkRkRaY+KNPRKQF6icRsaq9fnL37Xt6pZQyKIOJDK7nQ/1VdDP0L31xf0wqgzI0ZKqj1E9xn8H1fGWwlUH9FGRhLZRBGazMt5Ih1H5ydlGqe1+Yst3/uU/lwqEdwYVxMV8ZlMFaBtfzAZ7sHyxOK1z1E9hYD9cZXM9XBmVoylJHqZ+UwfV8ZbCVQf0UZGEtlEEZrMy3kiHUftIHnYuIiIiIiIiIiO90UUpERERERERERHyni1IiIiIiIiIiIuI7dx90HqP2FkPZeqg6AMkZ0HME5Ix1nUriVR4F9GUEqWRQyQF2s55SSlzHEkfUT2KJ+skW1+uhfhJrXJ8TUs/CWqijxJJ4Ox51USoEx47A5sWwdh7sK2n+++wCGDUThkyGpDS/00m8SSaVcUymkJkMpHk7baOYIubxFoupotJBQvGT+kksUT/Z4no91E9ijetzQupZWAt1lFgSz8ej3r7XjrIPYclIeHUa7Hu35W32vRv8/ZKRUL7R33wSX/owjDms4zoWkMvoFrfJZTTXsYA5rKMPQ31OKH5SP4kl6idbXK+H+kmscX1OSD0La6GOEkvi/XjURak2lH0Iz54Bh2q/QrGmlQ2P335oOywd3/UOErGhD8O4lTfoxQACBEggscXtEkgkQIBeDOBWVulJVRelfhJL1E+2uF4P9ZNY4/qckHoW1kIdJZboeAzzotTcuXMZN24cGRkZ9OnThy9/+cts2LAhWtmcOnYE/joJqirAqw7tPl51cPu/TAzeXyRSkkllFi+SSgaJJId0n0SSSSWDWawgmdQoJ3RP/dQ29ZNEi/opNH51lOv1UD+JNa7PiVgQL/0E6iixRcdjUFgXpV599VVmzJjBG2+8wYoVK6iqqmLSpEkcOnQoWvmc2bwYDm4N/eCo5VUH77f5mejkkvg0jslkMyjk/wNeK5FkcjiJ07g6SsnsUD+1T/0k0aB+Co1fHeV6PdRPYo3rcyIWxEs/gTpKbNHxGBTWB50vX7680X8vWrSIPn368Pbbb3POOedENJhra+cRvGTX2svn2pIQvH/+1MhmkvhVyEw8agi08hLnttRQTSE3s5InopDMDvVTiNRPEmHqp9D41VGu10P9JNa4PidiQbz0E6ijxBYdj0Gd+kyp8vJyAE444YSIhLFib/HxT7zvyMFB8H77ioOPI9JZeRQwkLGtvue+PQkkMohTyaMgssGMUz+1Qv0kEaR+6rhodJTr9VA/iTWuz4lY1RX7CdRRYouOx3odvihVU1PDd77zHc466yxGjRrV6nZHjx6loqKi0Y91Zesj9Dhd8+NsxGd9GRGRxzmR/Ig8TixQP4XwOOoniQD1U8eE0lEd6SfX66F+EmtcnxOxqKv2E6ijxBYdj/U6fFFqxowZrF27lsWLF7e53dy5c8nKyqr7ycvL6+hI31QdiNDj2P/7VmJAKhkReZw0MiPyOLFA/RTC46ifJALUTx0TSkd1pJ9cr4f6SaxxfU7Eoq7aT6COElt0PNbr0EWpb3/72yxbtoyioiJyc3Pb3Hb27NmUl5fX/ZSWlnYoqJ+SI9OZJMfP//2SKKokMo11hC7QWCFQP4X4OOoniQD1U/hC7aiO9JPr9VA/iTWuz4lY05X7CdRRYouOx3phfdC553ncfPPNLF26lFdeeYXBgwe3e5+UlBRSUlI6HNCFnpF5dWnEHkfi224i89rOSD2OVeonN48j8U39FLpwO6oj/eR6PdRPYo3rcyJWxEM/gTpKbNHxWC+sV0rNmDGDJ598kqeffpqMjAx2797N7t27OXLkSLTyOZEzFrIL6PibGxMgeyzkFEQuk8SvUkrYRjE1hPldocfVUM1W3mY7ayKczBb1U4jUTxJB6qfQ+dFRrtdD/STWuD4nYkU89BOoo8QWHY/1wtoF8+fPp7y8nHPPPZd+/frV/TzzzDPRyufMqJl06pPwR82MZBqJd0XMI9DBxkogkSIejnAie9RPIVI/SYSpn0LjV0e5Xg/1k1jj+pyIBfHST6COElt0PAaF1Qqe57X4M3Xq1CjFc2fIZOgxCAJhfmtpIDF4vyFXRyeXxKe3WMw+tlJNVVj3q6aKvWxhNV3vwkxT6qf2qZ8kGtRPofGro1yvh/pJrHF9TsSCeOknUEeJLToegzr87XtdXVIaXPxi8IPDQj1IAonB7S9ZEby/SKRUUclDTKKSAyH/H/JqqqjkAA8xkSoqo5xQ/KR+EkvUT7a4Xg/1k1jj+pyQehbWQh0lluh4DNJFqTb0HA5XrIL02i+faG1vHb89PTe4fdYwP9JJvNnDRu5lPPvZAdDqe/Jrb9/PDu5lPHvY5FtG8Y/6SSxRP9niej3UT2KN63NC6llYC3WUWKLjURel2pU1DK5aBxMWQvaYlrfJHhP8/VXrutbBIfbsYRNzGMkiplJKSYvblFLCIqYyh5F6MtXFqZ/EEvWTLa7XQ/0k1rg+J6SehbVQR4kl8X48JrkOEAuS0iB/avBnbzGUbYCqiuDL5nrmBz85X8QvVVSykidYyRPkUcCJ5JNGJkeo4D9saPX/uEvXpH4SS9RPtrheD/WTWOP6nJB6FtZCHSWWxPPxqItSYcoZ27UPCIktpZToCZTUUT+JJeonW1yvh/pJrHF9Tkg9C2uhjhJL4u141Nv3RERERERERETEd7ooJSIiIiIiIiIivtNFKRERERERERER8V3A8zzPz4EVFRVkZWVBANL7+zk56PAu8GogkADd+/k/XxmUwVoG1/MBDu0EPCgvLyczM9NNCNz3E9hYD9cZXM9XBmVoykJHqZ+Uwcp8ZbCVQf0UZGEtlEEZrMy3kiHUfnJ3UUpEpAkzF6VERFpg4o8+EZEWqJ9ExKr2+sndt+/plVLKoAwmMrieD/VX0c3Qv/TF/TGpDMrQkKmOUj/FfQbX85XBVgb1U5CFtVAGZbAy30qGUPvJ2UWp7n1hynb/5z6VC4d2BBfGxXxlUAZrGVzPB3iyf7A4rXDVT2BjPVxncD1fGZShKUsdpX5SBtfzlcFWBvVTkIW1UAZlsDLfSoZQ+0kfdC4iIiIiIiIiIr7TRSkREREREREREfGdLkqJiIiIiIiIiIjv3H3QeYzaWwxl66HqACRnQM8RkDNWGfzO4Hq+MkhTFtZCGZTBynwrGaSe6/XIo4C+jCCVDCo5wG7WU0qJfwFwvw+UQRmkZRbWwnVHWdgHyqAMruiiVAiOHYHNi2HtPNhX0vz32QUwaiYMmQxJacoQrQyu5yuDNGVhLZRBGazMt5JB6rlej2RSGcdkCpnJQJo/m95GMUXM4y0WU0Vl5APgfh8ogzJIyyysheuOsrAPlEEZLNDb99pR9iEsGQmvToN977a8zb53g79fMhLKNypDNDK4nq8M0pSFtVAGZbAy30oGqed6PfowjDms4zoWkMvoFrfJZTTXsYA5rKMPQyMbAPf7QBmUQVpmYS1cd5SFfaAMymCFLkq1oexDePYMOFT7FYo1rWx4/PZD22Hp+MgeJMrgfr4ySFMW1kIZlMHKfCsZpJ7r9ejDMG7lDXoxgAABEkhscbsEEgkQoBcDuJVVEf2jz/U+UAZlkJZZWAvXHWVhHyiDMlgS1kWp+fPnM3r0aDIzM8nMzOTMM8/khRdeiFY2p44dgb9OgqoK8KpDu49XHdz+LxOD91eGzmdwPV8ZYodf/WRhLZRBGazMt5IhFsRLRyWTyixeJJUMEkkO6T6JJJNKBrNYQTKpnQuA+32gDMoQa+Kln8B9R1nYB8qgDNaEdVEqNzeXe++9l7fffpvVq1dz3nnncfnll/P+++9HK58zmxfDwa2hHxy1vOrg/TY/owyRyOB6vjLEDr/6ycJaKIMyWJlvJUMsiJeOGsdkshkU8h97tRJJJoeTOI2rOxcA9/tAGZQh1sRLP4H7jrKwD5RBGawJ66LUZZddxsUXX8ywYcMYPnw4d999Nz169OCNN96IVj5n1s6j429uTDh+f2XodAbX85UhdvjVTxbWQhmUwcp8KxliQbx0VCEz8Vp970HbaqimkJs7FwD3+0AZlCHWxEs/gfuOsrAPlEEZrOnoLqC6uprFixdz6NAhzjzzzEhmcm5v8fFPvO9YX0EN7CsOPo4ydDyD6/nKELui1U8W1kIZlMHKfCsZYlFX7ag8ChjI2FY/n6U9CSQyiFPJo6BjAXC/D5RBGWJdV+0ncN9RFvaBMiiDRWFflHrvvffo0aMHKSkp3HjjjSxdupRTTjml1e2PHj1KRUVFox/rytZH6HE2KENnMrierwyxJ9r9ZGEtlEEZrMy3kiGWhNNRHXn+5Ho9+jIiIvNPJL/D93W9D5RBGWJVV+8ncN9RFvaBMiiDRWFflMrPz6ekpIRVq1bxrW99i+uvv54PPvig1e3nzp1LVlZW3U9eXl6nAvuh6kCEHqcT19+Uwf18ZYg90e4nC2uhDMpgZb6VDLEknI7qyPMn1+uRSkZE5qeR2eH7ut4HyqAMsaqr9xO47ygL+0AZlMGisC9KdevWjaFDh3Lqqacyd+5cxowZw0MPPdTq9rNnz6a8vLzup7S0tFOB/ZAcmb4iuePPqZTBwHxliD3R7icLa6EMymBlvpUMsSScjurI8yfX61FJZJ5hH6Hjz7Bd7wNlUIZY1dX7Cdx3lIV9oAzKYFFSZx+gpqaGo0ePtvr7lJQUUlJSOjvGVz0j88rOTj2OMrifrwyxL9L9ZGEtlEEZrMy3kiGWtdVRHXn+5Ho9dhOZ9yJ05nFc7wNlUIauoqv1E7jvKAv7QBmUwaKwXik1e/ZsXnvtNbZs2cJ7773H7NmzeeWVV5gyZUq08jmRMxayC+jUJ+Fnj4WcAmXoTAbX85UhtvjRTxbWQhmUwcp8KxliRTx0VCklbKOYGsL8buvjaqhmK2+znTUdC4D7faAMyhCL4qGfwH1HWdgHyqAMFoW1C/bs2cN1111Hfn4+559/Pm+99RZ/+9vfmDhxYrTyOTNqJp36JPxRM5UhEhlcz1eG2OFXP1lYC2VQBivzrWSIBfHSUUXMI9DBZ9gJJFLEw50LgPt9oAzKEGvipZ/AfUdZ2AfKoAzWhHVGPv7442zZsoWjR4+yZ88eXnrppS55QQpgyGToMQgCYX5jaCAxeL8hVytDJDK4nq8MscOvfrKwFsqgDFbmW8kQC+Klo95iMfvYSjVVYd2vmir2soXVPNO5ALjfB8qgDLEmXvoJ3HeUhX2gDMpgTUdfLNblJaXBxS8GPzgs1IMkkBjc/pIVwfsrQ+czuJ6vDNKUhbVQBmWwMt9KBqnnej2qqOQhJlHJgZD/6KumikoO8BATqaKycwFwvw+UQRmkZRbWwnVHWdgHyqAM1uiiVBt6DocrVkF67vEbWttbx29Pzw1unzVMGSKZwfV8ZZCmLKyFMiiDlflWMkg91+uxh43cy3j2swOg1c9vqb19Pzu4l/HsYVNkAuB+HyiDMkjLLKyF646ysA+UQRks0UWpdmQNg6vWwYSFkD2m5W2yxwR/f9W66BwcyuB+vjJIUxbWQhmUwcp8Kxmknuv12MMm5jCSRUyllJIWtymlhEVMZQ4jI3pBqpbrfaAMyiAts7AWrjvKwj5QBmWwIsl1gFiQlAb5U4M/e4uhbANUVQRfNtczP/jJ+coQ/Qyu5yuDNGVhLZRBGazMt5JB6rlejyoqWckTrOQJ8ijgRPJJI5MjVPAfNrT6h2Akud4HyqAM0jILa+G6oyzsA2VQBgt0USpMOWPdHxDK4H6+MkhTFtZCGZTBynwrGaSe6/UopcSXi1Btcb0PlEEZpGUW1sJ1R1nYB8qgDK7o7XsiIiIiIiIiIuI7XZQSERERERERERHf6aKUiIiIiIiIiIj4LuB5nufnwIqKCrKysiAA6f39nBx0eBd4NRBIgO79/J+vDMpgLYPr+QCHdgIelJeXk5mZ6SYE7vsJbKyH6wyu5yuDMjRloaPUT8pgZb4y2MqgfgqysBbKoAxW5lvJEGo/ubsoJSLShJmLUiIiLTDxR5+ISAvUTyJiVXv95O7b9/RKKWVQBhMZXM+H+qvoZuhf+uL+mFQGZWjIVEepn+I+g+v5ymArg/opyMJaKIMyWJlvJUOo/eTsolT3vjBlu/9zn8qFQzuCC+NivjIog7UMrucDPNk/WJxWuOonsLEerjO4nq8MytCUpY5SPymD6/nKYCuD+inIwloogzJYmW8lQ6j9pA86FxERERERERER3+milIiIiIiIiIiI+E4XpURERERERERExHfuPui8A/IooC8jSCWDSg6wm/WUUuJrhr3FULYeqg5Acgb0HAE5Y32NYGI/uM7ger6VDGKHhW6wkMHCeaEM7ueLPa77wfV8sHFeKIOdDGKHhX5wncHCOaEMdjLEG/MXpZJJZRyTKWQmA2neDNsopoh5vMViqqiMSoZjR2DzYlg7D/aVNP99dgGMmglDJkNSWlQimNgPrjO4nm8lg9hhoRssZLBwXiiD+/lij+t+cD0fbJwXymAng9hhoR9cZ7BwTiiDnQzxzPTb9/owjDms4zoWkMvoFrfJZTTXsYA5rKMPQyOeoexDWDISXp0G+95teZt97wZ/v2QklG+MeAQT+8F1BtfzrWQQOyx0g4UMFs4LZXA/X+xx3Q+u54ON80IZ7GQQOyz0g+sMFs4JZbCTId6ZvSjVh2Hcyhv0YgABAiSQ2OJ2CSQSIEAvBnArqyJ6kJR9CM+eAYdqv0KxppUNj99+aDssHR/Z0rKwH1xncD3fSgaxw0I3WMhg4bxQBvfzxR7X/eB6Ptg4L5TBTgaxw0I/uM5g4ZxQBjsZpJMXpe69914CgQDf+c53IhQnKJlUZvEiqWSQSHJI90kkmVQymMUKkkntdIZjR+Cvk6CqArzq0O7jVQe3/8vE4P07y8J+cJ3B9XwrGSR80eonC91gIYOF80IZ3M+XjolWP4H7fnA9H2ycF8pgJ4OET8+hopfBwjmhDHYySFCHL0q99dZb/OY3v2H06JZf4tYZ45hMNoNCPjhqJZJMDidxGld3OsPmxXBwa+hlVcurDt5v8zOdjmBiP7jO4Hq+lQwSnmj2k4VusJDBwnmhDO7nS/ii2U/gvh9czwcb54Uy2Mkg4dFzqOhmsHBOKIOdDBLUoYtSBw8eZMqUKTz22GP06tUr0pkoZCZeq6+jbFsN1RRyc6czrJ1Hxy/ZJRy/fydZ2A+uM7iebyWDhC7a/WShGyxksHBeKIP7+RKeaPcTuO8H1/PBxnmhDHYySOj0HCr6GSycE8pgJ4MEdeiUnDFjBpdccglf/OIXI52HPAoYyNhW38/ZngQSGcSp5FHQ4Qx7i49/A0PHjlGogX3FwcfpKAv7wXUG1/OtZJDwRLOfLHSDhQwWzgtlcD9fwhfNfgL3/eB6Ptg4L5TBTgYJj55DRTeDhXNCGexkkHphX5RavHgx77zzDnPnzg1p+6NHj1JRUdHopy19GRFupBadSH6H71u2PiIRKNvQ8fta2A+uM7iebyWDhC7a/WShGyxksHBeKIP7+RKeaPcTuO8H1/PBxnmhDHYySOjC6ahY7CcLGSycE8pgJ4PUC+uiVGlpKbNmzeKpp54iNTW0D/aaO3cuWVlZdT95eXltbp9KRjiRWpVGZofvW3UgIhGoar+fW2VhP7jO4Hq+lQwSGj/6yUI3WMhg4bxQBvfzJXR+9BO47wfX88HGeaEMdjJIaMLtqFjsJwsZLJwTymAng9QL66LU22+/zZ49e/jc5z5HUlISSUlJvPrqq8ybN4+kpCSqq5t/Ytzs2bMpLy+v+yktLW1zRiWRaYsjdLyxkiNzjJLciWPUwn5wncH1fCsZJDR+9JOFbrCQwcJ5oQzu50vo/OgncN8PrueDjfNCGexkkNCE21Gx2E8WMlg4J5TBTgaplxTOxueffz7vvfdeo9u+/vWvM2LECH74wx+SmNj8PZkpKSmkpKSEPGM3kXldZWcep2dkXs3XqcexsB9cZ3A930oGCY0f/WShGyxksHBeKIP7+RI6P/oJ3PeD6/lg47xQBjsZJDThdlQs9pOFDBbOCWWwk0HqhfVKqYyMDEaNGtXoJz09nezsbEaNGhWRQKWUsI1iagjzezqPq6GarbzNdtZ0OEPOWMguoFPfzJA9FnIKOhzBxH5wncH1fCsZJDR+9JOFbrCQwcJ5oQzu50vo/OgncN8PrueDjfNCGexkkNDoOZQ/GSycE8pgJ4PU6+gpGVVFzCPQwWgJJFLEw53OMGomnfpmhlEzOx3BxH5wncH1fCsZxA4L3WAhg4XzQhnczxd7XPeD6/lg47xQBjsZxA4L/eA6g4VzQhnsZJCgTl+UeuWVV3jwwQcjEKXeWyxmH1uppiqs+1VTxV62sJpnOp1hyGToMQgCYX5LZCAxeL8hV3c6gon94DqD6/lWMkjHRKOfLHSDhQwWzgtlcD9fOi4a/QTu+8H1fLBxXiiDnQzSMXoOFZ0MFs4JZbCTQYJMvlKqikoeYhKVHAj5IKmmikoO8BATqaKy0xmS0uDiF4MfZBdqaQUSg9tfsiJ4/86ysB9cZ3A930oGscNCN1jIYOG8UAb388Ue1/3gej7YOC+UwU4GscNCP7jOYOGcUAY7GSTI5EUpgD1s5F7Gs58dAK2+37P29v3s4F7Gs4dNEcvQczhcsQrSc4/f0NreOn57em5w+6xhEYtgYj+4zuB6vpUMYoeFbrCQwcJ5oQzu54s9rvvB9XywcV4og50MYoeFfnCdwcI5oQx2Mojhi1IAe9jEHEayiKmUUtLiNqWUsIipzGFkVA6OrGFw1TqYsBCyx7S8TfaY4O+vWhfZwqxlYT+4zuB6vpUMYoeFbrCQwcJ5oQzu54s9rvvB9XywcV4og50MYoeFfnCdwcI5oQx2MsS7JNcB2lNFJSt5gpU8QR4FnEg+aWRyhAr+w4ZWD5xISkqD/KnBn73FULYBqiqCL+PsmR/8Jodos7AfXGdwPd9KBrHDQjdYyGDhvFAG9/PFHtf94Ho+2DgvlMFOBrHDQj+4zmDhnFAGOxnimfmLUg2VUuL8gMgZ609JtsXCfnCdwfV8KxnEDgvdYCGDhfNCGdzPF3tc94Pr+WDjvFAGOxnEDgv94DqDhXNCGexkiDem374nIiIiIiIiIiJdky5KiYiIiIiIiIiI73RRSkREREREREREfBfwPM/zc2BFRQVZWVkQgPT+fk4OOrwLvBoIJED3fv7PVwZlsJbB9XyAQzsBD8rLy8nMzHQTAvf9BDbWw3UG1/OVQRmastBR6idlsDJfGWxlUD8FWVgLZVAGK/OtZAi1n9xdlBIRacLMRSkRkRaY+KNPRKQF6icRsaq9fnL37Xt6pZQyKIOJDK7nQ/1VdDP0L31xf0wqgzI0ZKqj1E9xn8H1fGWwlUH9FGRhLZRBGazMt5Ih1H5ydlGqe1+Yst3/uU/lwqEdwYVxMV8ZlMFaBtfzAZ7sHyxOK1z1E9hYD9cZXM9XBmVoylJHqZ+UwfV8ZbCVQf0UZGEtlEEZrMy3kiHUftIHnYuIiIiIiIiIiO90UUpERERERERERHyni1IiIiIiIiIiIuI7dx903gF7i6FsPVQdgOQM6DkCcsbGX4Y8CujLCFLJoJID7GY9pZTEVQbX88HGsWAhgwRZWAsLGSycm8pg41iwkEHquV4P1/PB/XmpDPUsHA8WMkiQhbVwncHCeakMQa6PBSsZ/GT+otSxI7B5MaydB/tKmv8+uwBGzYQhkyEpretmSCaVcUymkJkMpPkRuY1iipjHWyymisoumcH1fLBxLFjIIEEW1sJCBgvnpjLYOBYsZJB6rtfD9Xxwf14qQz0Lx4OFDBJkYS1cZ7BwXipDkOtjwUoGV0y/fa/sQ1gyEl6dBvvebXmbfe8Gf79kJJRv7JoZ+jCMOazjOhaQy+gWt8llNNexgDmsow9Du1wG1/PBxrFgIYMEWVgLCxksnJvKYONYsJBB6rleD9fzwf15qQz1LBwPFjJIkIW1cJ3BwnmpDEGujwUrGVwye1Gq7EN49gw4VPv1hTWtbHj89kPbYen4yC6QhQx9GMatvEEvBhAgQAKJLW6XQCIBAvRiALeyKqInrOsMrueDjWPBQgYJsrAWFjJYODeVwcaxYCGD1HO9Hq7ng/vzUhnqWTgeLGSQIAtr4TqDhfNSGYJcHwtWMrgW1kWpOXPmEAgEGv2MGDEi4qGOHYG/ToKqCvCqQ7uPVx3c/i8Tg/fvChmSSWUWL5JKBokkh3SfRJJJJYNZrCCZ1JjP4Ho+2DgWLGSwTv3kbwYL56Yy2DgWLGSIBfHSUa7ng/vzUhnqWTgeLGSwLl76yUIGC+elMgS5PhasZLAg7FdKfeYzn2HXrl11P6+//nrEQ21eDAe3hr4wtbzq4P02P9M1MoxjMtkMCvlErZVIMjmcxGlcHfMZXM8HG8eChQyxQP3kXwYL56Yy2DgWLGSIFfHQUa7ng/vzUhnqWTgeLGSIBfHQTxYyWDgvlSHI9bFgJYMFYV+USkpKom/fvnU/OTk5EQ+1dl5Hkh2XcPz+XSBDITPxWn39XttqqKaQm2M+g+v5YONYsJAhFqif/Mtg4dxUBhvHgoUMsSIeOsr1fHB/XipDPQvHg4UMsSAe+slCBgvnpTIEuT4WrGSwIOxdsHHjRvr378/JJ5/MlClT2LZtW0QD7S0+/mnzHTtGoQb2FQcfJ5Yz5FHAQMa2+t7a9iSQyCBOJY+CmM3gej7YOBYsZIgV6id/Mlg4N5XBxrFgIUMs6eod5Xo+uD8vlaGehePBQoZY0dX7yUIGC+elMgS5PhasZLAirItS48ePZ9GiRSxfvpz58+fz0UcfcfbZZ3PgwIFW73P06FEqKioa/bSlbH04idp4nA2duK+BDH2JzPu4TyQ/ZjO4ng82jgULGWKB+sm/DBbOTWWwcSxYyBArwu2ocPsJ3K+H6/ng/rxUhnoWjgcLGWJBPPSThQwWzktlCHJ9LFjJYEVSOBtfdNFFdf//0aNHM378eAYNGsSSJUuYPn16i/eZO3cut99+e8gzqlr/+zEsVe13o+kMqWREJEMamTGbwfV8sHEsWMgQC9RP/mWwcG4qg41jwUKGWBFuR4XbT+B+PVzPB/fnpTLUs3A8WMgQC+KhnyxksHBeKkOQ62PBSgYrOvoORgB69uzJ8OHD2bRpU6vbzJ49m/Ly8rqf0tLSNh8zOTLHKMkdP0ZNZKgkMkfpETp+lLrO4Ho+2DgWLGSIReqn6GWwcG4qg41jwUKGWNVeR4XbT+B+PVzPB/fnpTLUs3A8WMgQi7piP1nIYOG8VIYg18eClQxWdOqi1MGDB9m8eTP9+vVrdZuUlBQyMzMb/bSlZ4S+fbQzj2Mhw24i83q+zjyO6wyu54ONY8FChlikfore41g4N5XBxrFgIUOsaq+jwu0ncL8erueD+/NSGepZOB4sZIhFXbGfLGSwcF4qQ5DrY8FKBivCuih1yy238Oqrr7Jlyxb+9a9/ccUVV5CYmMg111wTsUA5YyG7INxkDSRA9ljIKYjtDKWUsI1iagjz+yGPq6GarbzNdtbEbAbX88HGsWAhQyxQP/mXwcK5qQw2jgULGWJFPHSU6/ng/rxUhnoWjgcLGWJBPPSThQwWzktlCHJ9LFjJYEVYu2D79u1cc8015Ofnc9VVV5Gdnc0bb7xB7969Ixpq1Ew69Sn0o2Z2jQxFzCPQwaM0gUSKeDjmM7ieDzaOBQsZrFM/+ZvBwrmpDDaOBQsZYkG8dJTr+eD+vFSGehaOBwsZrIuXfrKQwcJ5qQxBro8FKxksCOtIWLx4MTt37uTo0aNs376dxYsXM2TIkIiHGjIZegyCQJjfEhlIDN5vyNVdI8NbLGYfW6mmKqz7VVPFXrawmmdiPoPr+WDjWLCQwTr1k78ZLJybymDjWLCQIRbES0e5ng/uz0tlqGfheLCQwbp46ScLGSycl8oQ5PpYsJLBgk59plS0JKXBxS8GP7Qr1AUKJAa3v2RF8P5dIUMVlTzEJCo5EPIJW00VlRzgISZSRWXMZ3A9H2wcCxYySJCFtbCQwcK5qQw2jgULGaSe6/VwPR/cn5fKUM/C8WAhgwRZWAvXGSycl8oQ5PpYsJLBApMXpQB6DocrVkF67vEbWkt6/Pb03OD2WcO6VoY9bORexrOfHQCtvve29vb97OBexrOH1r9xLNYyuJ4PNo4FCxkkyMJaWMhg4dxUBhvHgoUMUs/1erieD+7PS2WoZ+F4sJBBgiyshesMFs5LZQhyfSxYyeCa2YtSENzRV62DCQshe0zL22SPCf7+qnXRWRgLGfawiTmMZBFTKaWkxW1KKWERU5nDyIieqFYyuJ4PNo4FCxkkyMJaWMhg4dxUBhvHgoUMUs/1erieD+7PS2WoZ+F4sJBBgiyshesMFs5LZQhyfSxYyeBSkusA7UlKg/ypwZ+9xVC2Aaoqgi9Z65kf/NT6eMhQRSUreYKVPEEeBZxIPmlkcoQK/sOGVk/irpTB9XywcSxYyCBBFtbCQgYL56Yy2DgWLGSQeq7Xw/V8cH9eKkM9C8eDhQwSZGEtXGewcF4qQ5DrY8FKBlfMX5RqKGes+8WwkKGUEl9OTssZXM8HG8eChQwSZGEtLGSwcG4qg41jwUIGqed6PVzPB/fnpTLUs3A8WMggQRbWwnUGC+elMgS5PhasZPCT6bfviYiIiIiIiIhI16SLUiIiIiIiIiIi4jtdlBIREREREREREd8FPM/z/BxYUVFBVlYWBCC9v5+Tgw7vAq8GAgnQvZ//85VBGaxlcD0f4NBOwIPy8nIyMzPdhMB9P4GN9XCdwfV8ZVCGpix0lPpJGazMVwZbGdRPQRbWQhmUwcp8KxlC7Sd3F6VERJowc1FKRKQFJv7oExFpgfpJRKxqr5/cffueXimlDMpgIoPr+VB/Fd0M/Utf3B+TyqAMDZnqKPVT3GdwPV8ZbGVQPwVZWAtlUAYr861kCLWfnF2U6t4Xpmz3f+5TuXBoR3BhXMxXBmWwlsH1fIAn+weL0wpX/QQ21sN1BtfzlUEZmrLUUeonZXA9XxlsZVA/BVlYC2VQBivzrWQItZ/0QeciIiIiIiIiIuI7XZQSERERERERERHf6aKUiIiIiIiIiIj4zt0HnXfA3mIoWw9VByA5A3qOgJyx8ZchjwL6MoJUMqjkALtZTyklcZXBwjpYyCB2WDgeLGRw3Q1WMrheC9fzxR7Xx4Tr+WCjGyxksLAWFjKIHRaOB9cZLHSDhQyu18FKhnhj/qLUsSOweTGsnQf7Spr/PrsARs2EIZMhKa3rZkgmlXFMppCZDKT5WbGNYoqYx1ssporKLpnBwjpYyCB2WDgeLGRw3Q1WMrheC9fzxR7Xx4Tr+WCjGyxksLAWFjKIHRaOB9cZLHSDhQyu18FKhnhm+u17ZR/CkpHw6jTY927L2+x7N/j7JSOhfGPXzNCHYcxhHdexgFxGt7hNLqO5jgXMYR19GNrlMlhYBwsZxA4Lx4OFDK67wUoG12vher7Y4/qYcD0fbHSDhQwW1sJCBrHDwvHgOoOFbrCQwfU6WMkQ78xelCr7EJ49Aw7Vfn1hTSsbHr/90HZYOj6yB4mFDH0Yxq28QS8GECBAAoktbpdAIgEC9GIAt7IqoqXhOoOFdbCQQeywcDxYyOC6G6xkcL0WrueLPa6PCdfzwUY3WMhgYS0sZBA7LBwPrjNY6AYLGVyvg5UMYvSi1LEj8NdJUFUBXnVo9/Gqg9v/ZWLw/l0hQzKpzOJFUskgkeSQ7pNIMqlkMIsVJJMa8xksrIOFDGKHhePBQgbX3WAlg+u1cD1f7HF9TLieDza6wUIGC2thIYPYYeF4cJ3BQjdYyOB6HaxkkKCwL0rt2LGDa6+9luzsbNLS0vjsZz/L6tWrIxpq82I4uDX0g6OWVx283+ZnukaGcUwmm0Ehl0WtRJLJ4SRO4+qYz2BhHSxkkNCon/zL4LobrGRwvRau50t44qGjXM8HG91gIYOFtbCQQUITD/1kIYOFbrCQwfU6WMkgQWFdlNq/fz9nnXUWycnJvPDCC3zwwQf8/Oc/p1evXhENtXZeuMkaSDh+/y6QoZCZeK2+hrBtNVRTyM0xn8HCOljIIO1TP/mbwXU3WMngei1cz5fQxUtHuZ4PNrrBQgYLa2Ehg7QvXvrJQgYL3WAhg+t1sJJBgsL69r377ruPvLw8Fi5cWHfb4MGDIxpob3HLn3gfshrYVxx8nI5+daOFDHkUtPgNCKFKIJFBnEoeBR3+Kk/XGSysg4UMEhr1k38ZXHeDlQyu18L1fAlPPHSU6/lgoxssZLCwFhYySGjioZ8sZLDQDRYyuF4HKxmkXljXBp9//nlOO+00rrzySvr06cPYsWN57LHH2rzP0aNHqaioaPTTlrL14SRq43E2dOK+BjL0ZUREMpxIfsxmsLAOFjJIaNRP/mVw3Q1WMrheC9fzJTzhdlS4/QTujwnX88FGN1jIYGEtLGSQ0MRDP1nIYKEbLGRwvQ5WMki9sC5K/fvf/2b+/PkMGzaMv/3tb3zrW99i5syZPPHEE63eZ+7cuWRlZdX95OXltTmj6kA4idp4nPa70XSGVDIikiGNzJjNYGEdLGSQ0Kif/MvguhusZHC9Fq7nS3jC7ahw+wncHxOu54ONbrCQwcJaWMggoYmHfrKQwUI3WMjgeh2sZJB6YV2Uqqmp4XOf+xz33HMPY8eO5Zvf/CY33HADv/71r1u9z+zZsykvL6/7KS0tbXNGcmTOE5I7fp6YyFBJZM6UI3T8THGdwcI6WMggoVE/+ZfBdTdYyeB6LVzPl/CE21Hh9hO4PyZczwcb3WAhg4W1sJBBQhMP/WQhg4VusJDB9TpYySD1wroo1a9fP0455ZRGt40cOZJt27a1ep+UlBQyMzMb/bSlZ2ReUdipx7GQYTeReU1hZx7HdQYL62Ahg4RG/eTf47juBisZXK+F6/kSnnA7Ktx+AvfHhOv5YKMbLGSwsBYWMkho4qGfLGSw0A0WMrheBysZpF5YF6XOOussNmxo/MbJDz/8kEGDBkUsUM5YyC4IN1kDCZA9FnIKYjtDKSVso5gawvyOyuNqqGYrb7OdNTGbwcI6WMggoVE/+ZfBdTdYyeB6LVzPl/DEQ0e5ng82usFCBgtrYSGDhCYe+slCBgvdYCGD63WwkkHqhbUM3/3ud3njjTe455572LRpE08//TS//e1vmTFjRkRDjZoJHfyWSqg5fv8ukKGIeQQ6eKYkkEgRD8d8BgvrYCGDtE/95G8G191gJYPrtXA9X0IXLx3lej7Y6AYLGSyshYUM0r546ScLGSx0g4UMrtfBSgYJCutoHDduHEuXLuWPf/wjo0aN4s477+TBBx9kypQpEQ01ZDL0GASBxPDuF0gM3m/I1V0jw1ssZh9bqaYqrPtVU8VetrCaZ2I+g4V1sJBB2qd+8jeD626wksH1WrieL6GLl45yPR9sdIOFDBbWwkIGaV+89JOFDBa6wUIG1+tgJYMEhX2J9NJLL+W9996jsrKSdevWccMNN0Q8VFIaXPxi8IPDQj1IAonB7S9ZEbx/V8hQRSUPMYlKDoRcGtVUUckBHmIiVVTGfAYL62Ahg4RG/eRfBtfdYCWD67VwPV/CEw8d5Xo+2OgGCxksrIWFDBKaeOgnCxksdIOFDK7XwUoGCerouyijrudwuGIVpOcev6G1pMdvT88Nbp81rGtl2MNG7mU8+9kB0Or7f2tv388O7mU8e9jUZTJYWAcLGcQOC8eDhQyuu8FKBtdr4Xq+2OP6mHA9H2x0g4UMFtbCQgaxw8Lx4DqDhW6wkMH1OljJIIYvSkFwsa9aBxMWQvaYlrfJHhP8/VXronNwWMiwh03MYSSLmEopJS1uU0oJi5jKHEZGtCysZLCwDhYyiB0WjgcLGVx3g5UMrtfC9Xyxx/Ux4Xo+2OgGCxksrIWFDGKHhePBdQYL3WAhg+t1sJIh3iW5DtCepDTInxr82VsMZRugqiL4srme+cFPzo+HDFVUspInWMkT5FHAieSTRiZHqOA/bGi1SLpSBgvrYCGD2GHheLCQwXU3WMngei1czxd7XB8TrueDjW6wkMHCWljIIHZYOB5cZ7DQDRYyuF4HKxnimfmLUg3ljHV/QFjIUEqJLwVhOYOFdbCQQeywcDxYyOC6G6xkcL0WrueLPa6PCdfzwUY3WMhgYS0sZBA7LBwPrjNY6AYLGVyvg5UM8cb02/dERERERERERKRr0kUpERERERERERHxnS5KiYiIiIiIiIiI7wKe53l+DqyoqCArKwsCkN7fz8lBh3eBVwOBBOjez//5yqAM1jK4ng9waCfgQXl5OZmZmW5C4L6fwMZ6uM7ger4yKENTFjpK/aQMVuYrg60M6qcgC2uhDMpgZb6VDKH2k7uLUiIiTZi5KCUi0gITf/SJiLRA/SQiVrXXT+6+fU+vlFIGZTCRwfV8qL+Kbob+pS/uj0llUIaGTHWU+inuM7ierwy2MqifgiyshTIog5X5VjKE2k/OLkp17wtTtvs/96lcOLQjuDAu5iuDMljL4Ho+wJP9g8Vphat+Ahvr4TqD6/nKoAxNWeoo9ZMyuJ6vDLYyqJ+CLKyFMiiDlflWMoTaT/qgcxERERERERER8Z0uSomIiIiIiIiIiO90UUpERERERERERHzn7oPOO2BvMZSth6oDkJwBPUdAztj4y5BHAX0ZQSoZVHKA3aynlBJfM7jeD67nizRl4Zi0kEH9ZCeDSEOuj0nX80H9ZCmDSEMWjknXGdRPdjKI/8xflDp2BDYvhrXzYF9J899nF8ComTBkMiSldd0MyaQyjskUMpOBND8zt1FMEfN4i8VUURmVDK73g+v5Ik1ZOCYtZFA/2ckg0pDrY9L1fFA/Wcog0pCFY9J1BvWTnQzilum375V9CEtGwqvTYN+7LW+z793g75eMhPKNXTNDH4Yxh3VcxwJyGd3iNrmM5joWMId19GFoxDO43g+u54s0ZeGYtJBB/WQng0hDro9J1/NB/WQpg0hDFo5J1xnUT3YyiHtmL0qVfQjPngGHar++sKaVDY/ffmg7LB0f2QPVQoY+DONW3qAXAwgQIIHEFrdLIJEAAXoxgFtZFdHicr0fXM8XacrCMWkhg/rJTgaRhlwfk67ng/rJUgaRhiwck64zqJ/sZBAbTF6UOnYE/joJqirAqw7tPl51cPu/TAzevytkSCaVWbxIKhkkkhzSfRJJJpUMZrGCZFI7ncH1fnA9X6QpC8ekhQzqJzsZRBpyfUy6ng/qJ0sZRBqycEy6zqB+spNB7AjrotRJJ51EIBBo9jNjxoyIhtq8GA5uDf0AreVVB++3+ZmukWEck8lmUMiFVSuRZHI4idO4utMZXO8H1/MltvjRURaOSQsZ1E92MkhsiJfnUK7ng/rJUgaJDfHSTxYyqJ/sZBA7wroo9dZbb7Fr1666nxUrVgBw5ZVXRjTU2nnhJmsg4fj9u0CGQmbitfo6xrbVUE0hN3c6g+v94Hq+xBY/OsrCMWkhg/rJTgaJDfHyHMr1fFA/WcogsSFe+slCBvWTnQxiR1iHQu/evenbt2/dz7JlyxgyZAgTJkyIWKC9xcc/db9j5yrUwL7i4OPEcoY8ChjI2FbfY9yeBBIZxKnkUdDhDK73g+v5Enui3VEWjkkLGdRPdjJI7IiH51Cu54P6yVIGiR3x0E8WMqif7GQQWzr8mVKffvopTz75JNOmTSMQCLS63dGjR6moqGj005ay9R1N1ORxNnTivgYy9GVERDKcSH6H7+t6P7ieL7EtlI5SP3WM+slOBolN0egncH9Mup4P6idLGSQ2ddV+spBB/WQng9jS4YtSzz77LGVlZUydOrXN7ebOnUtWVlbdT15eXpvbVx3oaKImj9N+N5rOkEpGRDKkkdnh+7reD67nS2wLpaPUTx2jfrKTQWJTNPoJ3B+TrueD+slSBolNXbWfLGRQP9nJILZ0+KLU448/zkUXXUT//v3b3G727NmUl5fX/ZSWlra5fXJkzlWSO36umshQSWTO1iN0/Gx1vR9cz5fYFkpHqZ86Rv1kJ4PEpmj0E7g/Jl3PB/WTpQwSm7pqP1nIoH6yk0FsSerInbZu3cpLL73En//853a3TUlJISUlJeTH7hmZVzV26nEsZNhNZF7X2JnHcb0fXM+X2BVqR6mfOkb9ZCeDxJ5o9RO4PyZdzwf1k6UMEnu6cj9ZyKB+spNBbOnQK6UWLlxInz59uOSSSyKdh5yxkF1Apz6NP3ss5BTEdoZSSthGMTWE+T2Zx9VQzVbeZjtrOpzB9X5wPV9iV7Q6ysIxaSGD+slOBok9Xfk5lOv5oH6ylEFiT1fuJwsZ1E92MogtYR8KNTU1LFy4kOuvv56kpA690Kpdo2bSqU/jHzWza2QoYh6BDp6tCSRSxMOdzuB6P7ieL7En2h1l4Zi0kEH9ZCeDxI54eA7lej6onyxlkNgRD/1kIYP6yU4GsSPsM+Kll15i27ZtTJs2LRp5ABgyGXoMgkCY35YZSAzeb8jVXSPDWyxmH1uppiqs+1VTxV62sJpnOp3B9X5wPV9iT7Q7ysIxaSGD+slOBokd8fAcyvV8UD9ZyiCxIx76yUIG9ZOdDGJH2BelJk2ahOd5DB8+PBp5AEhKg4tfDH54WagHaiAxuP0lK4L37woZqqjkISZRyYGQi6uaKio5wENMpIrKTmdwvR9cz5fYE+2OsnBMWsigfrKTQWJHPDyHcj0f1E+WMkjsiId+spBB/WQng9jR4W/fi7aew+GKVZCee/yG1pIevz09N7h91rCulWEPG7mX8exnB0Cr70GuvX0/O7iX8exhU8QyuN4PrueLNGXhmLSQQf1kJ4NIQ66PSdfzQf1kKYNIQxaOSdcZ1E92MogNZi9KQfCAu2odTFgI2WNa3iZ7TPD3V62LzgFqIcMeNjGHkSxiKqWUtLhNKSUsYipzGBnRwqrlej+4ni/SlIVj0kIG9ZOdDCINuT4mXc8H9ZOlDCINWTgmXWdQP9nJIO5F51PsIigpDfKnBn/2FkPZBqiqCL50r2d+8NP74yFDFZWs5AlW8gR5FHAi+aSRyREq+A8bWi2zSHK9H1zPF2nKwjFpIYP6yU4GkYZcH5Ou54P6yVIGkYYsHJOuM6if7GQQt8xflGooZ6z7g9JChlJKfCmptrjeD67nizRl4Zi0kEH9ZCeDSEOuj0nX80H9ZCmDSEMWjknXGdRPdjKI/0y/fU9ERERERERERLomXZQSERERERERERHf6aKUiIiIiIiIiIj4LuB5nufnwIqKCrKysiAA6f39nBx0eBd4NRBIgO79/J+vDMpgLYPr+QCHdgIelJeXk5mZ6SYE7vsJbKyH6wyu5yuDMjRloaPUT8pgZb4y2MqgfgqysBbKoAxW5lvJEGo/ubsoJSLShJmLUiIiLTDxR5+ISAvUTyJiVXv95O7b9/RKKWVQBhMZXM+H+qvoZuhf+uL+mFQGZWjIVEepn+I+g+v5ymArg/opyMJaKIMyWJlvJUOo/eTsolT3vjBlu/9zn8qFQzuCC+NivjIog7UMrucDPNk/WJxWuOonsLEerjO4nq8MytCUpY5SPymD6/nKYCuD+inIwloogzJYmW8lQ6j9pA86FxERERERERER3+milIiIiIiIiIiI+E4XpURERERERERExHfuPui8A/YWQ9l6qDoAyRnQcwTkjI2/DHkU0JcRpJJBJQfYzXpKKfE1g4X9IGKJhXPCQgb1k4hNrs8L1/NB/SRilYXzwnUG9ZPEM/MXpY4dgc2LYe082FfS/PfZBTBqJgyZDElpXTdDMqmMYzKFzGQgzdthG8UUMY+3WEwVlVHJYGE/iFhi4ZywkEH9JGKT6/PC9XxQP4lYZeG8cJ1B/SQSZPrte2UfwpKR8Oo02Pduy9vsezf4+yUjoXxj18zQh2HMYR3XsYBcRre4TS6juY4FzGEdfRga8QwW9oOIJRbOCQsZ1E8iNrk+L1zPB/WTiFUWzgvXGdRPIvXMXpQq+xCePQMO1X59YU0rGx6//dB2WDo+sieLhQx9GMatvEEvBhAgQAKJLW6XQCIBAvRiALeyKqLFZWE/iFhi4ZywkEH9JGKT6/PC9XxQP4lYZeG8cJ1B/STSmMmLUseOwF8nQVUFeNWh3cerDm7/l4nB+3eFDMmkMosXSSWDRJJDuk8iyaSSwSxWkExqpzNY2A8illg4JyxkUD+J2OT6vHA9H9RPIlZZOC9cZ1A/iTQX1kWp6upqfvrTnzJ48GDS0tIYMmQId955J57nRTTU5sVwcGvoJ0ktrzp4v83PdI0M45hMNoNCLqxaiSSTw0mcxtWdzmBhP4iEQv3kbwb1k0h44qWjXM8H9ZNIuOKlnyxkUD+JNBfWRan77ruP+fPn88gjj7Bu3Truu+8+fvazn/Hwww9HNNTaeeEmayDh+P27QIZCZuK1+lrKttVQTSE3dzqDhf0gEgr1k78Z1E8i4YmXjnI9H9RPIuGKl36ykEH9JNJcWIfjv/71Ly6//HIuueQSTjrpJL761a8yadIk3nzzzYgF2lt8/JP/O3auQg3sKw4+TixnyKOAgYxt9T3G7UkgkUGcSh4FHc5gYT+IhEr95F8G9ZNI+OKho1zPB/WTSEfEQz9ZyKB+EmlZWBelPv/5z/Pyyy/z4YcfArBmzRpef/11Lrroolbvc/ToUSoqKhr9tKVsfTiJ2nicDZ24r4EMfRkRkQwnkt/h+1rYDyKhUj/5l0H9JBK+cDsq3H4C9+eF6/mgfhLpiHjoJwsZ1E8iLUsKZ+Nbb72ViooKRowYQWJiItXV1dx9991MmTKl1fvMnTuX22+/PeQZVQfCSdTG47TfjaYzpJIRkQxpZHb4vhb2g0io1E/+ZVA/iYQv3I4Kt5/A/Xnhej6on0Q6Ih76yUIG9ZNIy8J6pdSSJUt46qmnePrpp3nnnXd44okneOCBB3jiiSdavc/s2bMpLy+v+yktLW1zRnJkzlWSO36umshQSWQa4wgdbwwL+0EkVOon/zKon0TCF25HhdtP4P68cD0f1E8iHREP/WQhg/pJpGVhvVLq+9//PrfeeiuTJ08G4LOf/Sxbt25l7ty5XH/99S3eJyUlhZSUlJBn9IzMqxo79TgWMuwmMq+t7MzjWNgPIqFSP/n3OOonkfCF21Hh9hO4Py9czwf1k0hHxEM/WcigfhJpWVivlDp8+DAJCY3vkpiYSE1NRz8prbmcsZBdEG6yBhIgeyzkFMR2hlJK2EYxNYT5XZ3H1VDNVt5mO2s6nMHCfhAJlfrJvwzqJ5HwxUNHuZ4P6ieRjoiHfrKQQf0k0rKwDsfLLruMu+++m7/85S9s2bKFpUuX8otf/IIrrrgioqFGzaRT3wgwambXyFDEPAIdbIwEEimi81/jamE/iIRC/eRvBvWTSHjipaNczwf1k0i44qWfLGRQP4k0F9YZ8fDDD/PVr36Vm266iZEjR3LLLbfw3//939x5550RDTVkMvQYBIEwvy0zkBi835Cru0aGt1jMPrZSTVVY96umir1sYTXPdDqDhf0gEgr1k78Z1E8i4YmXjnI9H9RPIuGKl36ykEH9JNJcWBelMjIyePDBB9m6dStHjhxh8+bN3HXXXXTr1i2ioZLS4OIXgx+gFurJEkgMbn/JiuD9u0KGKip5iElUciDk4qqmikoO8BATqaKy0xks7AeRUKif/M2gfhIJT7x0lOv5oH4SCVe89JOFDOonkeY6+m7SqOs5HK5YBem5x29oLenx29Nzg9tnDetaGfawkXsZz352ALT6HuTa2/ezg3sZzx42RSyDhf0gYomFc8JCBvWTiE2uzwvX80H9JGKVhfPCdQb1k0hjZi9KQfCgv2odTFgI2WNa3iZ7TPD3V62LzkliIcMeNjGHkSxiKqWUtLhNKSUsYipzGBnRwqplYT+IWGLhnLCQQf0kYpPr88L1fFA/iVhl4bxwnUH9JFIvyXWA9iSlQf7U4M/eYijbAFUVwZcP9swPfoNAPGSoopKVPMFKniCPAk4knzQyOUIF/2FDq2UWSRb2g4glFs4JCxnUTyI2uT4vXM8H9ZOIVRbOC9cZ1E8iQeYvSjWUM9b9iWEhQyklvpRUWyzsBxFLLJwTFjKon0Rscn1euJ4P6icRqyycF64zqJ8knpl++56IiIiIiIiIiHRNuiglIiIiIiIiIiK+00UpERERERERERHxXcDzPM/PgeXl5fTs2ROA7v38nBx0eDfgAQHo3tf/+cqgDNYyuJ4PcHhX8P8tKysjKyvLTQjc9xMYWQ8dk8qgDI0zGOgo9ZMyWJmvDMYyqJ8AI2uhDMpgZL6ZDCH2k+8XpbZv305eXp6fI0UkRpSWlpKbm+tsvvpJRNrisqPUTyLSFvWTiFjVXj/5flGqpqaGnTt3kpGRQSAQCPv+FRUV5OXlUVpaSmZmZhQSKkOsZHA9Xxkil8HzPA4cOED//v1JSHD3rmL1kzJ0pQyu53elDBY6qrP9BO7Xw/V8ZVAGaxnUT/Vcr4WFDK7nK4MyRDpDqP2U1JmQHZGQkBCRq/iZmZnOFkcZbGVwPV8ZIpPB5dv2aqmflKErZnA9v6tkcN1RkeoncL8erucrgzJYy6B+qud6LSxkcD1fGZQhkhlC6Sd90LmIiIiIiIiIiPhOF6VERERERERERMR3MXdRKiUlhdtuu42UlBRliPMMrucrg60MFljYD8qgDFbmK4M9rveF6/nKoAzWMrieb4mFfeE6g+v5yqAMrjL4/kHnIiIiIiIiIiIiMfdKKRERERERERERiX26KCUiIiIiIiIiIr7TRSkREREREREREfGdLkqJiIiIiIiIiIjvYuqi1MqVK0lMTOSSSy7xffbUqVMJBAJ1P9nZ2Vx44YW8++67vmfZvXs3N998MyeffDIpKSnk5eVx2WWX8fLLL0d9dsP9kJyczIknnsjEiRNZsGABNTU1UZ/fNEPDnwsvvNCX+e3l2LRpky/zd+/ezaxZsxg6dCipqamceOKJnHXWWcyfP5/Dhw9Hff7UqVP58pe/3Oz2V155hUAgQFlZWdQzWKOOUj81zeGqo1z3E7jtKPVTc+on9VPTHOonPYeyQv2kfmqaQ/0UX/0UUxelHn/8cW6++WZee+01du7c6fv8Cy+8kF27drFr1y5efvllkpKSuPTSS33NsGXLFk499VT+/ve/c//99/Pee++xfPlyCgsLmTFjhi8ZavfDli1beOGFFygsLGTWrFlceumlHDt2zNcMDX/++Mc/+jK7vRyDBw+O+tx///vfjB07lhdffJF77rmH4uJiVq5cyQ9+8AOWLVvGSy+9FPUM0ly8d5T6qXkOlx3lqp9AHWWR+kn91DSH+kn9ZIX6Sf3UNIf6Kb76Kcl1gFAdPHiQZ555htWrV7N7924WLVrEj370I18zpKSk0LdvXwD69u3Lrbfeytlnn83HH39M7969fclw0003EQgEePPNN0lPT6+7/TOf+QzTpk3zJUPD/TBgwAA+97nPccYZZ3D++eezaNEivvGNb/iawSVXOW666SaSkpJYvXp1o+Pg5JNP5vLLL8fzPN8zxTt1lPqptRyuuMygjrJF/aR+ai2HK+onqaV+Uj+1lsMV9ZP/YuaVUkuWLGHEiBHk5+dz7bXXsmDBAqeLcvDgQZ588kmGDh1Kdna2LzM/+eQTli9fzowZMxodpLV69uzpS46WnHfeeYwZM4Y///nPzjLEi3379vHiiy+2ehwABAIBn1NJvHeU+klqqaPsUT+pnyRI/WSP+kn9JEHx3E8xc1Hq8ccf59prrwWCL6krLy/n1Vdf9TXDsmXL6NGjBz169CAjI4Pnn3+eZ555hoQEf3bjpk2b8DyPESNG+DIvXCNGjGDLli2+zGq4FrU/99xzjy+z28px5ZVXRn1m7XGQn5/f6PacnJy6HD/84Q+jngNaXoeLLrrIl9nWxHtHqZ8as9BRLvoJ7HSU+qme+kn91JD6yX0/gTqqlvpJ/dSQ+ik++ykm3r63YcMG3nzzTZYuXQpAUlISV199NY8//jjnnnuubzkKCwuZP38+APv37+fRRx/loosu4s0332TQoEFRn2/95Xqe5/l29bbhWtQ64YQTfJndVo7Wrmr74c0336SmpoYpU6Zw9OhRX2a2tA6rVq2qe3IRL9RR6qemLHSUpX4C/ztK/RSkflI/NaV+ak7PodxQP6mfmlI/NRcP/RQTF6Uef/xxjh07Rv/+/etu8zyPlJQUHnnkEbKysnzJkZ6eztChQ+v++3e/+x1ZWVk89thj3HXXXVGfP2zYMAKBAOvXr4/6rI5Yt26dbx8C13QtXHGRY+jQoQQCATZs2NDo9pNPPhmAtLQ037K09L9/+/btvs23Qh2lfmrKQke5ymClo9RPQeon9VNT6if3/QTqKFA/gfqpKfVTfPaT+bfvHTt2jN///vf8/Oc/p6SkpO5nzZo19O/f38k3rtUKBAIkJCRw5MgRX+adcMIJXHDBBfzqV7/i0KFDzX7v8utj//73v/Pee+/xla98xVmGeJGdnc3EiRN55JFHWjwOxF/qqCD1k9RSR9mhfgpSP0kt9ZMd6qcg9ZPUiud+Mv9KqWXLlrF//36mT5/e7Gr5V77yFR5//HFuvPFGX7IcPXqU3bt3A8GXdj7yyCMcPHiQyy67zJf5AL/61a8466yzOP3007njjjsYPXo0x44dY8WKFcyfP59169ZFPUPtfqiuruY///kPy5cvZ+7cuVx66aVcd911UZ/fMENDSUlJ5OTk+DLftUcffZSzzjqL0047jTlz5jB69GgSEhJ46623WL9+PaeeeqrriHFDHVVP/dQ8R0PqKHWU39RP9dRPzXM0pH5SP/lN/VRP/dQ8R0PqpzjoJ8+4Sy+91Lv44otb/N2qVas8wFuzZk3Uc1x//fUeUPeTkZHhjRs3zvvTn/4U9dlN7dy505sxY4Y3aNAgr1u3bt6AAQO8L33pS15RUVHUZzfcD0lJSV7v3r29L37xi96CBQu86urqqM9vmqHhT35+vi/zG+a4/PLLfZ3Z0M6dO71vf/vb3uDBg73k5GSvR48e3umnn+7df//93qFDh6I+v7X//UVFRR7g7d+/P+oZLFBHNRbv/dQ0h6uOct1Pnue2o9RPQeqnxtRP6qdaeg7lnvqpMfWT+qlWPPZTwPOMf7qaiIiIiIiIiIh0OeY/U0pERERERERERLoeXZQSERERERERERHf6aKUiIiIiIiIiIj4ThelRERERERERETEd7ooJSIiIiIiIiIivtNFKRERERERERER8Z0uSomIiIiIiIiIiO90UUpERERERERERHyni1IiIiIiIiIiIuI7XZSKMb/+9a/JyMjg2LFjdbcdPHiQ5ORkzj333EbbvvLKKwQCATZv3swnn3zCzTffTH5+PmlpaQwcOJCZM2dSXl5et/2+ffu48MIL6d+/PykpKeTl5fHtb3+bioqKdnMdOXKE9PR0Nm3a1Ox3W7ZsYfr06QwePJi0tDSGDBnCbbfdxqefftpou7/97W+cccYZZGRk0Lt3b77yla+wZcuWTs0GCAQCdT9JSUkMHDiQ733vexw9erRum127dvG1r32N4cOHk5CQwHe+851mj/PnP/+Z0047jZ49e5Kenk5BQQF/+MMf2s0nEk+i2VHQ+Hyu/Vm8eHG7uTrbUXPmzGlxdnp6eruzt27dSlpaGgcPHmxxdsPH69atG0OHDuWuu+7C87y67d5//32+8pWvcNJJJxEIBHjwwQebPdbcuXMZN24cGRkZ9OnThy9/+cts2LCh3Xwi8SLa/VRr37595ObmEggEKCsrazdXJJ5DeZ7HAw88wPDhw0lJSWHAgAHcfffdnZoNkXsO1dDixYsJBAJ8+ctfbjefSLzwo58WLVrE6NGjSU1NpU+fPsyYMSOkbIMHD+all15qdrvL525NH1d/48W2JNcBJDyFhYUcPHiQ1atXc8YZZwDwj3/8g759+7Jq1SoqKytJTU0FoKioiIEDBzJkyBDWrl3Lzp07eeCBBzjllFPYunUrN954Izt37uRPf/oTAAkJCVx++eXcdddd9O7dm02bNjFjxgw++eQTnn766TZzrVixgkGDBjF06NBmv1u/fj01NTX85je/YejQoaxdu5YbbriBQ4cO8cADDwDw0Ucfcfnll/O9732Pp556ivLycr773e/y//1//x/vvPNOh2fXWrhwIRdeeCFVVVWsWbOGr3/966Snp3PnnXcCcPToUXr37s1PfvITfvnLX7b4GCeccAI//vGPGTFiBN26dWPZsmV8/etfp0+fPlxwwQVtZhSJF9HsqFq153Otnj17tpursx11yy23cOONNza63/nnn8+4cePanf3cc89RWFhIjx49Wt3mpZde4jOf+QxHjx7l9ddf5xvf+Ab9+vVj+vTpABw+fJiTTz6ZK6+8ku9+97stPsarr77KjBkzGDduHMeOHeNHP/oRkyZN4oMPPgjp4plIV+dHPwFMnz6d0aNHs2PHjpBydbafAGbNmsWLL77IAw88wGc/+1k++eQTPvnkk07NrhWJ51C1tmzZwi233MLZZ5/dbjaReBLtfvrFL37Bz3/+c+6//37Gjx/PoUOHQvrH/3fffZf9+/czYcKEZr/buXOns+duTR9Xf+PFOE9iTr9+/by5c+fW/fcPfvADb8aMGd7IkSO9oqKiutvPOecc7/rrr2/1cZYsWeJ169bNq6qqanWbhx56yMvNzW0307Rp07wf/vCHIeX3PM/72c9+5g0ePLjuv//3f//XS0pK8qqrq+tue/75571AIOB9+umnnZoNeEuXLm102/Tp072LL764xe0nTJjgzZo1q/3/EZ7njR071vvJT34S0rYi8SKaHdXS+RyKznZUUyUlJR7gvfbaa+0+1nnnnefNnz+/xd999NFHHuAVFxc3uv3888/3brrpphbvM2jQIO+Xv/xlu3P37NnjAd6rr77a7rYi8SLaz6EeffRRb8KECd7LL7/sAd7+/fvbzdTZfvrggw+8pKQkb/369SE/RqizI/kc6tixY97nP/9573e/+513/fXXe5dffnnYeUW6smj10yeffOKlpaV5L730UtiZ7rjjDu/qq68OeXs/n7vpb7yuQ2/fi0GFhYUUFRXV/XdRURHnnnsuEyZMqLv9yJEjrFq1isLCwlYfp7y8nMzMTJKSWn7B3M6dO/nzn//c4pXxhmpqali2bBmXX355yP8bysvLOeGEE+r++9RTTyUhIYGFCxdSXV1NeXk5f/jDH/jiF79IcnJyRGd/+OGH/P3vf2f8+PEh36cpz/N4+eWX2bBhA+ecc06HH0ekK4p2R82YMYOcnBxOP/10FixY0Ohtbi2JREc19bvf/Y7hw4e3+6/9ZWVlvP7663zpS18Kefbq1at5++23O9VRQN3L59v63yESb6LZTx988AF33HEHv//970lICO0pdiT66f/9v//HySefzLJlyxg8eDAnnXQS3/jGN9p9pZTfz6HuuOMO+vTpU/cKUBFpLFr9tGLFCmpqatixYwcjR44kNzeXq666itLS0nYzPf/882H3k6vnbvobL4a5vSYmHfHYY4956enpXlVVlVdRUeElJSV5e/bs8Z5++mnvnHPO8TzPq/sXuq1bt7b4GB9//LE3cOBA70c/+lGz302ePNlLS0vzAO+yyy7zjhw50maef/7zn16fPn0avcqpLRs3bvQyMzO93/72t41uf+WVV7w+ffp4iYmJHuCdeeaZ7f4LYyizAS81NdVLT0/3UlJSPMC79NJLW30FVltX0cvKyrz09HQvKSnJS0lJ8R5//PE284nEo2h21B133OG9/vrr3jvvvOPde++9XkpKivfQQw+1mSdSHVXryJEjXq9evbz77ruv3cd66qmnvNNOO63V39e+UiotLc1LT0/3kpOTPcD75je/2ep9QnmlVHV1tXfJJZd4Z511VrsZReJJtPqpsrLSGz16tPeHP/zB8zzPKyoqCumVUpHop//+7//2UlJSvPHjx3uvvfaaV1RU5BUUFHiFhYWdnh2p51D/+Mc/vAEDBngff/yx53meXikl0oJo9dPcuXO95ORkLz8/31u+fLm3cuVK7/zzz/fy8/O9o0ePtppn+/btXrdu3UJ6xWdrsz0ves/d9Dde16GLUjFo48aNHuD961//8v7yl794p5xyiud5nrdjxw4vJSXFO3LkiPfTn/7UO/nkk1u8f3l5uXf66ad7F154YYsn7a5du7x169Z5zz33nHfKKad43/rWt9rM84Mf/MCbNm1aSNm3b9/uDRkyxJs+fXqzmcOGDfO+//3ve++884736quvehMmTPDOP/98r6amplOzAW/+/Pnexo0bvfXr13vLli3zhg8f3upLUdsqrOrqam/jxo1ecXGx98ADD3hZWVmNXk4rItHvqIZ++tOftvsW40h0VENPP/20l5SU5O3evbvdx7vqqqu8O+64o9Xf116Uev75572NGzd6H3zwgbdkyRLvxBNPbPUl66FclLrxxhu9QYMGeaWlpe1mFIkn0eqn7373u42eV4R6USoS/XTDDTd4gLdhw4a6295++20PaPMtfX49h6qoqPBOOukk769//WvdbbooJdJctPrp7rvv9gDvb3/7W91te/bs8RISErzly5e3mufRRx/1zjvvvJCyu3jupr/xug5dlIpRubm53t133+3dcsstjS4aDR061Hv55Ze9L3zhC943vvGNZverqKjwzjzzTO/8889v9xVQnhf8ly3A27lzZ6vbjBgxwnv22WfbfawdO3Z4w4YN8/7rv/6r2VXvn/zkJ81eTVBaWuoB3sqVKzs1mxbeb/zHP/7RA7yNGzc22z6c9xtPnz7dmzRpUkjbisQTvzpq2bJlHuBVVla2uk0kOqqh8847z/vyl7/c7uMdPXrUy8zM9EpKSlrdprXPlJo7d66XlJTU4j5o76LUjBkzvNzcXO/f//53uxlF4lE0+mnMmDFeQkKCl5iY6CUmJnoJCQke4CUmJnr/8z//02qWSPTT//zP/3hJSUmNbjt8+LAHeC+++GKnZkfiOVRxcXHdvqj9CQQCXiAQ8BITE71Nmza1mUEknkSjnxYsWOABzf6hqk+fPq2+KtzzPO/CCy/0HnzwwXYzu3rupr/xug59plSMKiws5JVXXuGVV15p9DWh55xzDi+88AJvvvlms/caV1RUMGnSJLp168bzzz9f9w0ObampqQFo9NWaDW3cuJGtW7cyceLENh9nx44dnHvuuZx66qksXLiw2WctHD58uNltiYmJjTJ0dHZLah/7yJEjYd+3oZqamlb3jUg886ujSkpK6NWrFykpKS3+PlIdVeujjz6iqKgopM9EeeWVV+jV6/9n7+7jq67v+/8/Ti5MAiQBg1yZiMpFwFJIVIrOrogWWrWtdVsFh1NqZ9cWhbbrVmm7b1kvxG29krajrVWx1TZ6W4f1Z9WKLdp1VQqWqFSuJxBARNAkEAmG5PP740NCgFycc3Lyeb3OOc/77ZbbtuScvJ57v9+fp/HjyckQpkyZ0utjT5abm8vRo0dP+bPvPQmCgFtuuYUVK1bw29/+lnPOOSfhuSLZoD/66Re/+AUvvPACtbW11NbW8uMf/xgI/3pWd392PVX9dMkll3D06FG2bdvW8bnNmzcDMHr06D7N7kqiP0NNmDCBl156qWNtamtr+dCHPsSMGTOora2loqIi4Qwimao/+umSSy4BYNOmTR2fe+ONN9i/f3+3HXHo0CFWrVrV63s6Wf7s1hX9O1566vodrsW9GTNmMH/+fFpaWk54I/Lp06dzyy238Pbbb59QWO2F8dZbb3H//ffT2NhIY2MjAGeccQa5ubk89thjvPbaa0ydOpVBgwbx5z//mX/6p3/ikksu4eyzz+4yxy9/+Uve+973MmDAgG6ztv8wNXr0aL7xjW/w+uuvd3xtxIgRAFx11VV8+9vf5itf+QrXXXcdBw8e5Atf+AKjR4+muro66dnt6uvr2bt3L21tbWzZsoWvfOUrjB8/nokTJ3Y8pra2FghL+PXXX6e2tpbTTjuN8847D4AlS5Zw4YUXMmbMGI4cOcJjjz3GT3/6U5YtW9brfJFs0x8d9f/9f/8fr732GhdddBGFhYWsXLmS22+/nc997nPd5khVR7W75557GDlyJFdccUWva/DII4/E/QbnBw4cYO/evRw9epSXXnqJO++8kxkzZlBSUgLA22+/zcsvv9zxv+/evZva2loGDRrU8aeS58+fz89+9jN++ctfUlxczN69ewEoLS2lqKgorhwi2aA/+mnMmDEnzNi/fz8AEydO7PZPn6eqn9773vdy/vnnc9NNN/Gd73yHtrY25s+fz8yZMxk/fnzSs9v19WeowsJCJk2adML3bF+Tkz8vku36o5/Gjx/P1VdfzcKFC/nRj35ESUkJixYtYsKECd2+YfoTTzzB+PHju/13wHhn99fPbu3073gZwvqlWpKc9l/5mDBhwgmf3759ewAElZWVJ3y+/b0Nuvp45ZVXgiAIgt/+9rfBxRdfHJSWlgaFhYXBuHHjgs9//vM9vh/Cu9/97uCuu+7qMeu9997b7ezOfv7znwfV1dXBwIEDgzPOOCP40Ic+FGzYsKFPs4MgOGFeLBYLRo4cGcyePTvYtm1bt49r/xg9enTH17/4xS8GY8eODQoLC4MhQ4YEF198cVBTU9PrfJFs1B8d9fjjjwdVVVXBoEGDgoEDBwZTpkwJfvCDH/T4q3ap7KjW1tagvLy8yz8Q0ZWKiopg5cqVPT6mfZ3aP3Jzc4Py8vLg5ptvDvbt29ft49o/pk+f3vGY7v5/uPfee+PKK5It+qOfThbPe0qlsp92794d/NVf/VUwaNCgYPjw4cG8efOCAwcO9Gl2EKTuZ6iT6T2lRLrWX/3U0NAQ3HTTTcHgwYOD008/PbjmmmuCnTt3dpvj+uuvD774xS/2mNXyZ7cg0L/jZZJYEPTy9xhFurF//35GjhzJrl27GD58eNbMFpH0YNkTf/rTn7jssst4/fXXyc/Pj3S2iPinn6FExKujR48yfPhwHn/8cd71rndFOlv9lJ30nlKStDfeeINvfetbJoVhOVtE0oNlTxw9epTvfve7uiElIl3Sz1Ai4tUbb7zBZz7zGaZOnWoyW/2UffRKKRERERERERERiZxeKSUiIiIiIiIiIpHTTSkREREREREREYmcbkqJiIiIiIiIiEjkdFNKREREREREREQip5tSIiIiIiIiIiISOd2UEhERERERERGRyOmmlIiIiIiIiIiIRE43pUREREREREREJHK6KSUiIiIiIiIiIpHTTSkREREREREREYmcbkqJiIiIiIiIiEjkdFNKREREREREREQip5tSIiIiIiIiIiISOd2UEhERERERERGRyOVFPbCtrY09e/ZQXFxMLBaLeryIOBQEAQcPHmTUqFHk5NjdK1c/iUhXPHSU+klEuqJ+EhGv4u2nyG9K7dmzh4qKiqjHikgaqKuro7y83Gy++klEemLZUeonEemJ+klEvOqtnyK/KVVcXNzxvw8YGfV0eGsvEAAxGDAi+vnKoAzeMljPB3jr1fB/du4HC9b9BE72Q2dSGZThxAwOOkr9pAxe5iuDswzqJ8DJXiiDMjiZ7yZDnP0U+U2p9pd0DhgJ1++Jejo8UA5Nu2HgKJi7K/r5yqAM3jJYzwe4f1RYWtYv+bbuJ/CxH9YZrOcrgzKczENHqZ+Uwct8ZfCVQf0U8rAXyqAMXuZ7yRBvP+mNzkVEREREREREJHK6KSUiIiIiIiIiIpHTTSkREREREREREYlc5O8pJSKZZf86qN8ILQchvxgGT4Ch1dapRETUTyLil/pJRDyLsqN0U0pEEnb0MGyrgfVL4UDtqV8vq4JJC2DMHMgrijqdiGQz9ZOIeKV+EhHPrDpKv74nIgmp3wwPTYRnboIDL3b9mAMvhl9/aCI0bIk2n4hkL/WTiHilfhIRzyw7SjelRCRu9Zvh4Yugqf3PirZ188Bjn2/aBSum6QcrEel/6icR8Ur9JCKeWXdUwjelfve73/HBD36QUaNGEYvFePjhh1OTRERcO3oYHpsFLY0QtMb3nKA1fPyvZobP72/qJ5HspH4SEa/UTyLimYeOSvimVFNTE1OmTOH73/9+36eLSNrYVgOHdsRfVu2C1vB52x7sn1ydqZ9EspP6SUS8Uj+JiGceOirhNzq/4ooruOKKK/o+WUTSyvqlhLexu3s5Z09ywudXzkttppOpn0Syk/pJRLxSP4mIZx46Su8pJSK92r/u2F9gSKasCJ93YF34fUREUkn9JCJeqZ9ExDMvHZXwK6USdeTIEY4cOdLxfzc2Nvb3SBFJsfqNKfo+m2BodWq+Vyqon0TSn/pJRLxSP4mIZ146qt9fKbVkyRJKS0s7PioqKvp7pIikWMvBFH0fZz+zqJ9E0p/6SUS8Uj+JiGdeOqrfb0otWrSIhoaGjo+6urr+HikiKZZfnKLvU5Ka75Mq6ieR9Kd+EhGv1E8i4pmXjur3X98rKCigoKCgv8eISD8aPMHX90kV9ZNI+lM/iYhX6icR8cxLRyV8U+rQoUNs3bq14/9+5ZVXqK2t5fTTT+ess87qWxoRcWloNZRVwYEXSfovM5RNgaFVqc11MvWTSPZRP4mIV+onEfHMS0cl/Ot7a9eupbq6murq8J2sPvvZz1JdXc3/+3//r29JRMS1SQvo019mmLQglWm6pn4SyU7qJxHxSv0kIp556KiEXyl16aWXEgRB3yeLSFoZMwee/1do2gVBa/zPi+XCwHIYM7v/srVTP4lkJ/WTiHilfhIRzzx0VL+/0bmIZIa8IrjyyfCN7GK58T0nlhs+/qqV4fNFRPqD+klEvFI/iYhnHjpKN6VEJG6Dx8M1q8O74kD3DXLs8wPLw8eXjosinYhkM/WTiHilfhIRz6w7SjelRCQhpePg2g0w/d7wje26UjYl/Pq1G/QDlYhER/0kIl6pn0TEM8uOSvg9pURE8oqgcl74sX8d1G+ClsbwZZyDK8O/5CAiYkH9JCJeqZ9ExDOrjtJNKRHpk6HV+iFKRHxSP4mIV+onEfEsyo7Sr++JiIiIiIiIiEjkdFNKREREREREREQip5tSIiIiIiIiIiISuVgQBEGUAxsbGyktLYUYDBwV5eTQW69C0AaxHBgwMvr5yqAM3jJYzwdo2gME0NDQQElJiU0I7PsJfOyHdQbr+cqgDCfz0FHqJ2XwMl8ZfGVQP4U87IUyKIOX+V4yxNtPdjelRERO4uamlIhIF1z8S5+ISBfUTyLiVW/9ZPfX9/RKKWVQBhcZrOfD8bvobui/9GX9mVQGZejMVUepn7I+g/V8ZfCVQf0U8rAXyqAMXuZ7yRBvP5ndlBowAubuin7uA+XQtDvcGIv5yqAM3jJYzwe4f1RYnF5Y9RP42A/rDNbzlUEZTuapo9RPymA9Xxl8ZVA/hTzshTIog5f5XjLE2096o3MREREREREREYmcbkqJiIiIiIiIiEjkdFNKREREREREREQiZ/dG50mooIoRTKCQYpo5yF42UkdtpBn2r4P6jdByEPKLYfAEGFodaQSRDjqPfqifpDPthdbAG+uO0nnww8NeWJ9H8LEOEtJ58MHDGnjIoPMYPfc3pfIpZCpzmMECzuLUndjJOlaxlDXU0EJzv2Q4ehi21cD6pXCg9tSvl1XBpAUwZg7kFfVLBJEOOo9+qJ+kM+2F1sAb647SefDDw15Yn0fwsQ4S0nnwwcMaeMig82jL9a/vDWMci9nADdxDOZO7fEw5k7mBe1jMBoYxNuUZ6jfDQxPhmZvgwItdP+bAi+HXH5oIDVtSHkGkg86jH+on6Ux7oTXwxrqjdB788LAX1ucRfKyDhHQefPCwBh4y6Dzac3tTahjjuI3nGMKZxIiRQ26Xj8shlxgxhnAmt7E6pYekfjM8fBE0tf8JxbZuHnjs8027YMW0zDsk4oPOox/qJ+lMe6E18Ma6o3Qe/PCwF9bnEXysg4R0HnzwsAYeMug8+pDQTaklS5YwdepUiouLGTZsGB/+8IfZtGlTykPlU8hCnqSQYnLJj+s5ueRTSDELWUk+hX3OcPQwPDYLWhohaI3vOUFr+PhfzQyfL5IqOo+9Uz/1LNvOQ1S0F1qDeGVLR+k8+OFhL6zPI/hYB++ypZ9A5wF8rIGHDDqPfiR0U+qZZ55h/vz5PPfcc6xcuZKWlhZmzZpFU1NTSkNNZQ5ljI77cLTLJZ+hnM2FzO5zhm01cGhH/IejXdAaPm/bg32OINJB57F36qfeZdN5iIr2QmsQr2zpKJ0HPzzshfV5BB/r4F229BPoPICPNfCQQefRj4RuSj3xxBPMmzePd7zjHUyZMoXly5ezc+dOnn/++ZSGmsECgm5ft9azNlqZwa19zrB+Kcn/cmPOseeLpIjOY+/UT3HKkvMQFe2F1iBe2dJROg9+eNgL6/MIPtbBu2zpJ9B5AB9r4CGDzqMffXpPqYaGBgBOP/30lISB8E8wnkV1t7/P2ZscchnNBVRQlXSG/euOveN9cmcU2uDAuvD7iPSVzmNy1E/dyNLz0B+0F1qDvsjEjtJ58MPDXlifR/CxDukoE/sJdB7Axxp4yKDz6EvSN6Xa2tr49Kc/zSWXXMKkSZO6fdyRI0dobGw84aMnI5iQbKQTDKcy6efWb0xJBOpT/6vYkoV0HhOnforj+2TReegv2gutQbLi6ahE+wnsO0rnwQ8Pe2F9HsHHOqSbTO0n0HkAH2vgIYPOoy9J35SaP38+69evp6ampsfHLVmyhNLS0o6PioqKHh9fSHGykU5QREnSz205mJIItPTezyK90nlMnPopju+TReehv2gvtAbJiqejEu0nsO8onQc/POyF9XkEH+uQbjK1n0DnAXysgYcMOo++JHVT6pZbbuHRRx9l1apVlJeX9/jYRYsW0dDQ0PFRV1fX4+ObSc3uHCb53clPzRklP/kzKtJB5zEx6qc4v0+WnIf+pL3QGiQj3o5KtJ/AvqN0HvzwsBfW5xF8rEM6yeR+Ap0H8LEGHjLoPPqSl8iDgyDg1ltvZcWKFTz99NOcc845vT6noKCAgoKCuGfsJTWvY+vL9xmcmlfzpez7SHbTeYyP+snm+2Qz7YXWIBGJdlSi/QT2HaXz4IeHvbA+j+BjHdJBNvQT6DyAjzXwkEHn0ZeEXik1f/587r//fn72s59RXFzM3r172bt3L4cPH05ZoDpq2ck62kjw7yIe00YrO3ieXbyQdIah1VBWRZ/eCb+sGoZWJR1BpIPOY3zUT3HKkvMQBe2F1iAR2dBROg9+eNgL6/MIPtYhHWRDP4HOA/hYAw8ZdB59SWgJli1bRkNDA5deeikjR47s+HjwwQdTGmoVS4kluTs55LKK7/Y5w6QF9Omd8Cct6HMEkQ46j71TP8UpS85DVLQXWoN4ZUtH6Tz44WEvrM8j+FgH77Kln0DnAXysgYcMOo9+JLQLQRB0+TFv3ryUhlpDDQfYQSstCT2vlRb2s5219L1Ax8yBQaMhluBfiYzlhs8bM7vPEUQ66Dz2Tv3Uu2w6D1HRXmgN4pUtHaXz4IeHvbA+j+BjHbzLln4CnQfwsQYeMug8+pH0X9/rTy00cyezaOZg3IeklRaaOcidzKSF5j5nyCuCK58M3zgs3kMSyw0ff9XK8PkiqaLz6If6STrTXmgNvLHuKJ0HPzzshfV5BB/rICGdBx88rIGHDDqPfri8KQWwjy3cwTTeZDdAt7/v2f75N9nNHUxjH1tTlmHweLhmNQxs/+MT3a3Wsc8PLA8fXzouZRFEOug8+qF+ks60F1oDb6w7SufBDw97YX0ewcc6SEjnwQcPa+Ahg86jD25vSgHsYyuLmchy5lFHbZePqaOW5cxjMRNTejjalY6DazfA9HuhbErXjymbEn792g2ZdTjEH51HP9RP0pn2QmvgjXVH6Tz44WEvrM8j+FgHCek8+OBhDTxk0Hm0l2cdoDctNPMs9/Es91FBFcOppIgSDtPIa2zq9uCkUl4RVM4LP/avg/pN0NIYvmxucGX4zvkiUdF59EP9JJ1pL7QG3lh3lM6DHx72wvo8go91kJDOgw8e1sBDBp1HW+5vSnVWR20kB6InQ6sz+0BIetF59EP9JJ1pL7QG3lh3lM6DHx72wvo8go91kJDOgw8e1sBDBp3H6Ln+9T0REREREREREclMuiklIiIiIiIiIiKR000pERERERERERGJXCwIgiDKgY2NjZSWlkIMBo6KcnLorVchaINYDgwYGf18ZVAGbxms5wM07QECaGhooKSkxCYE9v0EPvbDOoP1fGVQhpN56Cj1kzJ4ma8MvjKon0Ie9kIZlMHLfC8Z4u0nu5tSIiIncXNTSkSkCy7+pU9EpAvqJxHxqrd+svvre3qllDIog4sM1vPh+F10N/Rf+rL+TCqDMnTmqqPUT1mfwXq+MvjKoH4KedgLZVAGL/O9ZIi3n8xuSg0YAXN3RT/3gXJo2h1ujMV8ZVAGbxms5wPcPyosTi+s+gl87Id1Buv5yqAMJ/PUUeonZbCerwy+MqifQh72QhmUwct8Lxni7Se90bmIiIiIiIiIiERON6VERERERERERCRyuiklIiIiIiIiIiKRs3uj8yTsXwf1G6HlIOQXw+AJMLQ62gwVVDGCCRRSTDMH2ctG6qhVhogzWM9XBl8ZPFA/+cngYS+sM3jYB2XwRWfSRwbrfQAf66AM9vM90XXhYw2UIWR9FrIxg/ubUkcPw7YaWL8UDtSe+vWyKpi0AMbMgbyi/smQTyFTmcMMFnAWp14VO1nHKpayhhpaaFaGfspgPV8ZfGXwQP3kJ4OHvbDO4GEflMEXnUkfGaz3AXysgzLYz/dE14WPNVCGkPVZyPYMsSAIIv0joo2NjZSWljJgJFy/p+fH1m+Gx2bBoR2Ev2jY1sWDjn1+0Gi4aiWUjuv5e7a/C/3AM+N7F/phjGMhT1LGaALayCH3lMe00UqMHA6wgzuZyT62KkOKM/THfGVIfH5/ZWj/ywwNDQ2UlJT0HqKfWPcT2J8HDxkSPZMe/llhnSFTz4KXDB46KpF+Ap1JLxms9wF89LQyqJ8603Xh4+dIZQhZn4VMzhBvP7l9T6n6zfDwRdDUvoBdHdBOn2/aBSumQcOW1GUYxjhu4zmGcCYxYl1uDEAOucSIMYQzuY3VDGOsMqQwg/V8ZfCVwQP1k58MHvbCOoOHfVAGX3QmfWSw3gfwsQ7KYD/fE10XPtZAGULWZ0EZ2r9vApYtW8bkyZMpKSmhpKSEiy++mMcffzwlQTo7eji8Y9rSCEFrfM8JWsPH/2pm+Py+yqeQhTxJIcXkkh/Xc3LJp5BiFrKSfAqVIQUZrOcrg68MPVE/9SwTz4OHvbDO4GEflCE+2dJRHvbCQwbrfQAf66AM9vPjkS39BPb74WENlCFkfRaU4biEbkqVl5dzxx138Pzzz7N27Vouu+wyrr76av785z/3OUhn22rCl/DFe0DbBa3h87Y92PcMU5lDGaPj3ph2ueQzlLO5kNnKkIIM1vOVwVeGnqifepdp58HDXlhn8LAPyhCfbOkoD3vhIYP1PoCPdVAG+/nxyJZ+Avv98LAGyhCyPgvKcFxCN6U++MEPcuWVVzJu3DjGjx/P17/+dQYNGsRzzz3X5yCdrV+aaLJOco49v49msICg29cQ9qyNVmZwqzKkIIP1fGXwlaEn6qf4ZNJ58LAX1hk87IMyxCdbOsrDXnjIYL0P4GMdlMF+fjyypZ/Afj88rIEyhKzPgjIcl/R7SrW2tlJTU0NTUxMXX3xxn4O027/u2LvuJ7cu0AYH1oXfJ1kVVHEW1d3+LmVvcshlNBdQQZUy9CGD9Xxl8JUhEeqn7mXKefCwF9YZPOyDMiQnUzvKw154yGC9D+BjHZTBfn4yMrWfwH4/PKyBMoSsz4IynPx9EvTSSy8xaNAgCgoK+MQnPsGKFSs477zzun38kSNHaGxsPOGjJ/UbE03UzffZlPxzRzAhJRmGU6kMfchgPV8ZfGWIh/opful+HjzshXUGD/ugDIlJpKMS7SfQmfSSwXofwMc6KIP9/ERkej+B/X54WANlCFmfBWU4UcI3pSorK6mtrWX16tV88pOf5MYbb+Tll1/u9vFLliyhtLS046OioqLH799yMNFE3Xyf3ruxW4UUpyRDEcn/WVZlsJ+vDL4yxEP9FL90Pw8e9sI6g4d9UIbEJNJRifYT6Ex6yWC9D+BjHZTBfn4iMr2fwH4/PKyBMoSsz4IynCjhm1KnnXYaY8eO5YILLmDJkiVMmTKFO++8s9vHL1q0iIaGho6Purq6Hr9/fmrWhfw+rEszqblSDpP8laIM9vOVwVeGeKif4pfu58HDXlhn8LAPypCYRDoq0X4CnUkvGaz3AXysgzLYz09EpvcT2O+HhzVQhpD1WVCGE+X1NUBbWxtHjhzp9usFBQUUFBTE/f0Gp+YVZH36PntJzWsK+/J9lMF+vjL4ypAM9VP/fB8PGTzshXUGD/ugDH3TU0cl2k+gM+klg/U+gI91UAb7+X2Raf0E9vvhYQ2UIWR9FpThRAm9UmrRokX87ne/Y/v27bz00kssWrSIp59+mrlz5/YpRGdDq6GsKtFkneRAWTUMrUo+Qx217GQdbST4NyqPaaOVHTzPLl5Qhj5ksJ6vDL4y9Eb9FJ9MOQ8e9sI6g4d9UIb4ZUNHedgLDxms9wF8rIMy2M+PVzb0E9jvh4c1UIaQ9VlQhhMldBT27dvHDTfcQGVlJZdffjlr1qzh17/+NTNnzuxTiJNNWkCf3o1/0oK+Z1jFUmJJXik55LKK7ypDCjJYz1cGXxl6on6KTyadBw97YZ3Bwz4oQ3yypaM87IWHDNb7AD7WQRns58cjW/oJ7PfDwxooQ8j6LChD5++TgLvvvpvt27dz5MgR9u3bx1NPPZXysgIYMwcGjYZYgn+ZMJYbPm/M7L5nWEMNB9hBKy0JPa+VFvaznbU8qAwpyGA9Xxl8ZeiJ+ql3mXYePOyFdQYP+6AM8cmWjvKwFx4yWO8D+FgHZbCfH49s6Sew3w8Pa6AMIeuzoAzHJfuiuX6VVwRXPhm+eVm8BzWWGz7+qpXh8/uqhWbuZBbNHIx7g1ppoZmD3MlMWmhWhhRksJ6vDL4yeKB+8pPBw15YZ/CwD8rgi86kjwzW+wA+1kEZ7Od7ouvCxxooQ8j6LCjDcS5vSgEMHg/XrIaB5cc+0V3SY58fWB4+vnRc6jLsYwt3MI032Q3Q7e9atn/+TXZzB9PYx1ZlSGEG6/nK4CuDB+onPxk87IV1Bg/7oAy+6Ez6yGC9D+BjHZTBfr4nui58rIEyhKzPgjKE3N6UgvDAXbsBpt8LZVO6fkzZlPDr125I7QFtt4+tLGYiy5lHHbVdPqaOWpYzj8VM7Jd/eCiD/Xxl8JXBA/WTnwwe9sI6g4d9UAZfdCZ9ZLDeB/CxDspgP98TXRc+1kAZQtZnQRkgL2XfqZ/kFUHlvPBj/zqo3wQtjeFL9wZXhu/e399aaOZZ7uNZ7qOCKoZTSRElHKaR19jU7aYpQ2bNVwZfGTxQP/nJ4GEvrDN42Adl8EVn0kcG630AH+ugDPbzPdF14WMNlCFkfRayPYP7m1KdDa2O5lD2pI5a839gKIP9fGXwlcED9ZOfDB72wjqDh31QBl90Jn1ksN4H8LEOymA/3xNdFz7WQBlC1mchGzO4/vU9ERERERERERHJTLopJSIiIiIiIiIikdNNKRERERERERERiVwsCIIgyoGNjY2UlpZCDAaOinJy6K1XIWiDWA4MGBn9fGVQBm8ZrOcDNO0BAmhoaKCkpMQmBPb9BD72wzqD9XxlUIaTeego9ZMyeJmvDL4yqJ9CHvZCGZTBy3wvGeLtJ7ubUiIiJ3FzU0pEpAsu/qVPRKQL6icR8aq3frL763t6pZQyKIOLDNbz4fhddDf0X/qy/kwqgzJ05qqj1E9Zn8F6vjL4yqB+CnnYC2VQBi/zvWSIt5/MbkoNGAFzd0U/94FQuaxCAAEAAElEQVRyaNodbozFfGVQBm8ZrOcD3D8qLE4vrPoJfOyHdQbr+cqgDCfz1FHqJ2Wwnq8MvjKon0Ie9kIZlMHLfC8Z4u0nvdG5iIiIiIiIiIhETjelREREREREREQkcropJSIiIiIiIiIikbN7o/Mk7F8H9Ruh5SDkF8PgCTC0OvsyVFDFCCZQSDHNHGQvG6mjNqsyWM/3kkH88NANyhDycG1ar4OHNRBfrM+k9XwvGTxcm1oH8cbDmbTOYD0ffFyXHtbBQ4Zs4/6m1NHDsK0G1i+FA7Wnfr2sCiYtgDFzIK8oczPkU8hU5jCDBZzFqVfFTtaxiqWsoYYWmjMyg/V8LxnEDw/doAwhD9em9Tp4WAPxxfpMWs/3ksHDtal1EG88nEnrDNbzwcd16WEdPGTIZq5/fa9+Mzw0EZ65CQ682PVjDrwYfv2hidCwJTMzDGMci9nADdxDOZO7fEw5k7mBe1jMBoYxNuMyWM/3kkH88NANyhDycG1ar4OHNRBfrM+k9XwvGTxcm1oH8cbDmbTOYD0ffFyXHtbBQ4Zs5/amVP1mePgiaGr/84Vt3Tzw2OebdsGKaak9JB4yDGMct/EcQziTGDFyyO3ycTnkEiPGEM7kNlantDSsM1jP95JB/PDQDcoQ8nBtWq+DhzUQX6zPpPV8Lxk8XJtaB/HGw5m0zmA9H3xclx7WwUMG6eNNqTvuuINYLManP/3pFMUJHT0Mj82ClkYIWuN7TtAaPv5XM8PnZ0KGfApZyJMUUkwu+XE9J5d8CilmISvJpzDtM1jP95JBEqd+yvwMHq5N63XwsAaSuP7qJ7A/k9bzvWTwcG1qHSRZ+hmq/zJYzwcf16WHdfCQQUJJ35Ras2YNP/zhD5k8ueuX+vXFtho4tCP+w9EuaA2ft+3BzMgwlTmUMTrusmiXSz5DOZsLmZ32Gazne8kgiVE/ZUcGD9em9Tp4WANJTH/2E9ifSev5XjJ4uDa1DpIM/QzVvxms54OP69LDOnjIIKGkbkodOnSIuXPnctdddzFkyJBUZ2L9UpK/XZZz7PkZkGEGCwi6fQ1hz9poZQa3pn0G6/leMkj81E/Zk8HDtWm9Dh7WQOLX3/0E9mfSer6XDB6uTa2DJEo/Q/V/Buv54OO69LAOHjJIKKltmD9/PldddRXvfe97U52H/euOveN9ctcJtMGBdeH3SecMFVRxFtXd/n5vb3LIZTQXUEFV2mawnu8lgyRG/ZQdGTxcm9br4GENJDH92U9gfyat53vJ4OHa1DpIMvQzVP9msJ4PPq5LD+vgIYMcl/BNqZqaGv70pz+xZMmSuB5/5MgRGhsbT/joSf3GRBN183029eG5DjKMYEJKMgynMm0zWM/3kkHip37Kngwerk3rdfCwBhK//u4nsD+T1vO9ZPBwbWodJFGJdFQ69pOHDNbzwcd16WEdPGSQ4xK6KVVXV8fChQt54IEHKCyM7w3OlixZQmlpacdHRUVFj49vOZhIoh6+T+/d6DpDIcUpyVBESdpmsJ7vJYPER/2UXRk8XJvW6+BhDSQ+UfQT2J9J6/leMni4NrUOkohEOyod+8lDBuv54OO69LAOHjLIcQndlHr++efZt28f559/Pnl5eeTl5fHMM8+wdOlS8vLyaG099V3CFi1aRENDQ8dHXV1djzPyU3OdkN+Hf355yNBMaq6UwyR/pVhnsJ7vJYPER/2UXRk8XJvW6+BhDSQ+UfQT2J9J6/leMni4NrUOkohEOyod+8lDBuv54OO69LAOHjLIcXmJPPjyyy/npZdeOuFzH/3oR5kwYQKf//znyc099XdTCwoKKCgoiHvG4NS8orBP38dDhr2k5jWFffk+1hms53vJIPFRP2VXBg/XpvU6eFgDiU8U/QT2Z9J6vpcMHq5NrYMkItGOSsd+8pDBej74uC49rIOHDHJcQjeliouLmTRp0gmfGzhwIGVlZad8PllDq6GsCg68SHJvPJYDZVNgaFV6Z6ijlp2so5zJSb0RXRut1FHLLl5I2wzW871kkPion7Irg4dr03odPKyBxCeKfgL7M2k930sGD9em1kESoZ+hoslgPR98XJce1sFDBjku2T+C2K8mLaBP74Q/aUFmZFjFUmJJblEOuaziu2mfwXq+lwzih4duUIaQh2vTeh08rIH4Yn0mred7yeDh2tQ6iDcezqR1Buv54OO69LAOHjJIqM83pZ5++mm+853vpCDKcWPmwKDREEvw5m0sN3zemNmZkWENNRxgB620JPS8VlrYz3bW8mDaZ7Ce7yWDJEf9lNkZPFyb1uvgYQ0kOf3RT2B/Jq3ne8ng4drUOkhf6Geo/slgPR98XJce1sFDBgm5fKVUXhFc+WT4xmHxHpJYbvj4q1aGz8+EDC00cyezaOZg3KXRSgvNHOROZtJCc9pnsJ7vJYP44aEblCHk4dq0XgcPayC+WJ9J6/leMni4NrUO4o2HM2mdwXo++LguPayDhwwScnlTCmDweLhmNQwsP/aJ7pIe+/zA8vDxpeMyK8M+tnAH03iT3UD4e7xdaf/8m+zmDqaxj60Zk8F6vpcM4oeHblCGkIdr03odPKyB+GJ9Jq3ne8ng4drUOog3Hs6kdQbr+eDjuvSwDh4yiOObUhBu9rUbYPq94RuJdaVsSvj1azf0z+HwkGEfW1nMRJYzjzpqu3xMHbUsZx6Lmdgv/xC3zmA930sG8cNDNyhDyMO1ab0OHtZAfLE+k9bzvWTwcG1qHcQbD2fSOoP1fPBxXXpYBw8Zsl1Cf33PQl4RVM4LP/avg/pN0NIYvmxucGX4zvnZkKGFZp7lPp7lPiqoYjiVFFHCYRp5jU3dFkkmZbCe7yWD+OGhG5Qh5OHatF4HD2sgvlifSev5XjJ4uDa1DuKNhzNpncF6Pvi4Lj2sg4cM2cz9TanOhlbbHwgPGeqoNf8Ht3UG6/leMogfHrpBGUIerk3rdfCwBuKL9Zm0nu8lg4drU+sg3ng4k9YZrOeDj+vSwzp4yJBtXP/6noiIiIiIiIiIZCbdlBIRERERERERkcjpppSIiIiIiIiIiEQuFgRBEOXAxsZGSktLIQYDR0U5OfTWqxC0QSwHBoyMfr4yKIO3DNbzAZr2AAE0NDRQUlJiEwL7fgIf+2GdwXq+MijDyTx0lPpJGbzMVwZfGdRPIQ97oQzK4GW+lwzx9pPdTSkRkZO4uSklItIFF//SJyLSBfWTiHjVWz/Z/fU9vVJKGZTBRQbr+XD8Lrob+i99WX8mlUEZOnPVUeqnrM9gPV8ZfGVQP4U87IUyKIOX+V4yxNtPZjelBoyAubuin/tAOTTtDjfGYr4yKIO3DNbzAe4fFRanF1b9BD72wzqD9XxlUIaTeeoo9ZMyWM9XBl8Z1E8hD3uhDMrgZb6XDPH2k97oXEREREREREREIqebUiIiIiIiIiIiEjndlBIRERERERERkcjZvdF5Evavg/qN0HIQ8oth8AQYWp19GSqoYgQTKKSYZg6yl43UUZtVGazng4+z4CGDhDzshYcMHq5NDxms98J6vpcMcpz1fljPBx/d4CGDh71QBunMw15YZ/DQDR4yWO+DMthwf1Pq6GHYVgPrl8KB2lO/XlYFkxbAmDmQV5S5GfIpZCpzmMECzuLUE7mTdaxiKWuooYXmjMxgPR98nAUPGSTkYS88ZPBwbXrIYL0X1vO9ZJDjrPfDej746AYPGTzshTJIZx72wjqDh27wkMF6H5TBnutf36vfDA9NhGduggMvdv2YAy+GX39oIjRsycwMwxjHYjZwA/dQzuQuH1POZG7gHhazgWGMzbgM1vPBx1nwkEFCHvbCQwYP16aHDNZ7YT3fSwY5zno/rOeDj27wkMHDXiiDdOZhL6wzeOgGDxms90EZfHB7U6p+Mzx8ETS1//nCtm4eeOzzTbtgxbTUbpCHDMMYx208xxDOJEaMHHK7fFwOucSIMYQzuY3VKS0N6wzW88HHWfCQQUIe9sJDBg/XpocM1nthPd9LBjnOej+s54OPbvCQwcNeKIN05mEvrDN46AYPGaz3QRn8cHlT6uhheGwWtDRC0Brfc4LW8PG/mhk+PxMy5FPIQp6kkGJyyY/rObnkU0gxC1lJPoVpn8F6Pvg4Cx4ySMjDXnjI4OHa9JDBei+s53vJIMdZ74f1fPDRDR4yeNgLZZDOPOyFdQYP3eAhg/U+KIMvCd2UWrx4MbFY7ISPCRMmpDzUtho4tCP+jWkXtIbP2/ZgZmSYyhzKGB13WbTLJZ+hnM2FzE77DNbzwcdZ8JDBO/VTtBk8XJseMljvhfV8LxnSQbZ0lPV88NENHjJ42AtlSA/Z0k8eMnjoBg8ZrPdBGXxJ+JVS73jHO3j11Vc7Pn7/+9+nPNT6pckkOybn2PMzIMMMFhB0+/q9nrXRygxuTfsM1vPBx1nwkCEdqJ+iy+Dh2vSQwXovrOd7yZAusqGjrOeDj27wkMHDXihD+siGfvKQwUM3eMhgvQ/K4EvCS5CXl8eIESM6PoYOHZrSQPvXHXu3+eSuE2iDA+vC75POGSqo4iyqu/393t7kkMtoLqCCqrTNYD0ffJwFDxnShfopmgwerk0PGaz3wnq+lwzpJNM7yno++OgGDxk87IUypJdM7ycPGTx0g4cM1vugDP4kfFNqy5YtjBo1inPPPZe5c+eyc+fOHh9/5MgRGhsbT/joSf3GRBN183029eG5DjKMIDUvmR1OZdpmsJ4PPs6ChwzpQv0UTQYP16aHDNZ7YT3fS4Z0kkhHJdpPYL8f1vPBRzd4yOBhL5QhvWR6P3nI4KEbPGSw3gdl8Cehm1LTpk1j+fLlPPHEEyxbtoxXXnmFv/zLv+TgwYPdPmfJkiWUlpZ2fFRUVPQ4o6X7b5WQlt670XWGQopTkqGIkrTNYD0ffJwFDxnSgfopugwerk0PGaz3wnq+lwzpItGOSrSfwH4/rOeDj27wkMHDXihD+siGfvKQwUM3eMhgvQ/K4E9CN6WuuOIKPvKRjzB58mTe97738dhjj1FfX89DDz3U7XMWLVpEQ0NDx0ddXV2PM/JTc52Qn/x14iJDM6k5pYdJ/pRaZ7CeDz7OgocM6UD9FF0GD9emhwzWe2E930uGdJFoRyXaT2C/H9bzwUc3eMjgYS+UIX1kQz95yOChGzxksN4HZfAnry9PHjx4MOPHj2fr1q3dPqagoICCgoL4v2eK/tBDX76Phwx7Sc3r+fryfawzWM8HH2fBQ4Z0pH7qv+/j4dr0kMF6L6zne8mQrnrrqET7Cez3w3o++OgGDxk87IUypK9M7CcPGTx0g4cM1vugDP4k+17vABw6dIht27YxcuTIVOVhaDWUVdGnd6Evq4ahVemdoY5adrKONhL8+5DHtNHKDp5nFy+kbQbr+eDjLHjIkI7UT/2XwcO16SGD9V5Yz/eSIV1lYkdZzwcf3eAhg4e9UIb0lYn95CGDh27wkMF6H5TBn4SW4HOf+xzPPPMM27dv5w9/+APXXHMNubm5XHfddSkNNWkBfXoX+kkLMiPDKpYSS/KU5pDLKr6b9hms54OPs+Ahg3fqp2gzeLg2PWSw3gvr+V4ypINs6Sjr+eCjGzxk8LAXypAesqWfPGTw0A0eMljvgzL4ktBp3LVrF9dddx2VlZVce+21lJWV8dxzz3HGGWekNNSYOTBoNMQS/EuVsdzweWNmZ0aGNdRwgB200pLQ81ppYT/bWcuDaZ/Bej74OAseMninfoo2g4dr00MG672wnu8lQzrIlo6yng8+usFDBg97oQzpIVv6yUMGD93gIYP1PiiDLwndlKqpqWHPnj0cOXKEXbt2UVNTw5gxY1IeKq8IrnwyfNOueDcolhs+/qqV4fMzIUMLzdzJLJo5GHdptNJCMwe5k5m00Jz2Gazng4+z4CGDd+qnaDN4uDY9ZLDeC+v5XjKkg2zpKOv54KMbPGTwsBfKkB6ypZ88ZPDQDR4yWO+DMvjSp/eU6k+Dx8M1q2Fg+bFPdJf02OcHloePLx2XWRn2sYU7mMab7Abo9vd/2z//Jru5g2nso/s3d063DNbzwcdZ8JBBQh72wkMGD9emhwzWe2E930sGOc56P6zng49u8JDBw14og3TmYS+sM3joBg8ZrPdBGfxwe1MKwoW+dgNMvxfKpnT9mLIp4dev3dA/G+Mhwz62spiJLGceddR2+Zg6alnOPBYzMaVl4SWD9XzwcRY8ZJCQh73wkMHDtekhg/VeWM/3kkGOs94P6/ngoxs8ZPCwF8ognXnYC+sMHrrBQwbrfVAGH/KsA/Qmrwgq54Uf+9dB/SZoaQxfsja4MnzX+mzI0EIzz3Ifz3IfFVQxnEqKKOEwjbzGpm6LJJMyWM8HH2fBQwYJedgLDxk8XJseMljvhfV8LxnkOOv9sJ4PPrrBQwYPe6EM0pmHvbDO4KEbPGSw3gdlsOf+plRnQ6vtN8NDhjpqIykIzxms54OPs+Ahg4Q87IWHDB6uTQ8ZrPfCer6XDHKc9X5Yzwcf3eAhg4e9UAbpzMNeWGfw0A0eMljvgzLYcP3reyIiIiIiIiIikpl0U0pERERERERERCKnm1IiIiIiIiIiIhK5WBAEQZQDGxsbKS0thRgMHBXl5NBbr0LQBrEcGDAy+vnKoAzeMljPB2jaAwTQ0NBASUmJTQjs+wl87Id1Buv5yqAMJ/PQUeonZfAyXxl8ZVA/hTzshTIog5f5XjLE2092N6VERE7i5qaUiEgXXPxLn4hIF9RPIuJVb/1k99f39EopZVAGFxms58Pxu+hu6L/0Zf2ZVAZl6MxVR6mfsj6D9Xxl8JVB/RTysBfKoAxe5nvJEG8/md2UGjAC5u6Kfu4D5dC0O9wYi/nKoAzeMljPB7h/VFicXlj1E/jYD+sM1vOVQRlO5qmj1E/KYD1fGXxlUD+FPOyFMiiDl/leMsTbT3qjcxERERERERERiZxuSomIiIiIiIiISOR0U0pERERERERERCJn90bnSdi/Duo3QstByC+GwRNgaHX2ZaigihFMoJBimjnIXjZSR21WZfCwDx4yiB8ezoOHDNbd4CWD9V5Yzxd/rM+E9Xzw0Q0eMnjYCw8ZxA8P58E6g4du8JDBeh+8ZMg27m9KHT0M22pg/VI4UHvq18uqYNICGDMH8ooyN0M+hUxlDjNYwFmcelXsZB2rWMoaamihOSMzeNgHDxnEDw/nwUMG627wksF6L6zniz/WZ8J6PvjoBg8ZPOyFhwzih4fzYJ3BQzd4yGC9D14yZDPXv75XvxkemgjP3AQHXuz6MQdeDL/+0ERo2JKZGYYxjsVs4AbuoZzJXT6mnMncwD0sZgPDGJtxGTzsg4cM4oeH8+Ahg3U3eMlgvRfW88Uf6zNhPR98dIOHDB72wkMG8cPDebDO4KEbPGSw3gcvGbKd25tS9Zvh4Yugqf3PF7Z188Bjn2/aBSumpfaQeMgwjHHcxnMM4UxixMght8vH5ZBLjBhDOJPbWJ3S0rDO4GEfPGQQPzycBw8ZrLvBSwbrvbCeL/5Ynwnr+eCjGzxk8LAXHjKIHx7Og3UGD93gIYP1PnjJIE5vSh09DI/NgpZGCFrje07QGj7+VzPD52dChnwKWciTFFJMLvlxPSeXfAopZiEryacw7TN42AcPGcQPD+fBQwbrbvCSwXovrOeLP9Znwno++OgGDxk87IWHDOKHh/NgncFDN3jIYL0PXjJIKOGbUrt37+b666+nrKyMoqIi3vnOd7J27dqUhtpWA4d2xH842gWt4fO2PZgZGaYyhzJGx10W7XLJZyhncyGz0z6Dh33wkEHio36KLoN1N3jJYL0X1vMlMdnQUdbzwUc3eMjgYS88ZJD4ZEM/ecjgoRs8ZLDeBy8ZJJTQTak333yTSy65hPz8fB5//HFefvllvvnNbzJkyJCUhlq/NNFkneQce34GZJjBAoJuX0PYszZamcGtaZ/Bwz54yCC9Uz9Fm8G6G7xksN4L6/kSv2zpKOv54KMbPGTwsBceMkjvsqWfPGTw0A0eMljvg5cMEkror+/927/9GxUVFdx7770dnzvnnHNSGmj/uq7f8T5ubXBgXfh9kv3TjR4yVFDV5V9AiFcOuYzmAiqoSvpPeVpn8LAPHjJIfNRP0WWw7gYvGaz3wnq+JCYbOsp6PvjoBg8ZPOyFhwwSn2zoJw8ZPHSDhwzW++AlgxyX0L3BRx55hAsvvJCPfOQjDBs2jOrqau66664en3PkyBEaGxtP+OhJ/cZEEvXwfTb14bkOMoxgQkoyDKcybTN42AcPGSQ+6qfoMlh3g5cM1nthPV8Sk2hHJdpPYH8mrOeDj27wkMHDXnjIIPHJhn7ykMFDN3jIYL0PXjLIcQndlPq///s/li1bxrhx4/j1r3/NJz/5SRYsWMB9993X7XOWLFlCaWlpx0dFRUWPM1oOJpKoh+/Teze6zlBIcUoyFFGSthk87IOHDBIf9VN0Gay7wUsG672wni+JSbSjEu0nsD8T1vPBRzd4yOBhLzxkkPhkQz95yOChGzxksN4HLxnkuIRuSrW1tXH++edz++23U11dzcc//nFuvvlmfvCDH3T7nEWLFtHQ0NDxUVdX1+OM/NRcJ+Qnf524yNBMaq6UwyR/pVhn8LAPHjJIfNRP0WWw7gYvGaz3wnq+JCbRjkq0n8D+TFjPBx/d4CGDh73wkEHikw395CGDh27wkMF6H7xkkOMSuik1cuRIzjvvvBM+N3HiRHbu3NntcwoKCigpKTnhoyeDU/OKwj59Hw8Z9pKa1xT25ftYZ/CwDx4ySHzUT9F9H+tu8JLBei+s50tiEu2oRPsJ7M+E9Xzw0Q0eMnjYCw8ZJD7Z0E8eMnjoBg8ZrPfBSwY5LqGbUpdccgmbNp34i5ObN29m9OjRKQs0tBrKqhJN1kkOlFXD0Kr0zlBHLTtZRxsJ/o3KY9poZQfPs4sX0jaDh33wkEHio36KLoN1N3jJYL0X1vMlMdnQUdbzwUc3eMjgYS88ZJD4ZEM/ecjgoRs8ZLDeBy8Z5LiEtuEzn/kMzz33HLfffjtbt27lZz/7GT/60Y+YP39+SkNNWgBJ/pVKaDv2/AzIsIqlxJK8UnLIZRXfTfsMHvbBQwbpnfop2gzW3eAlg/VeWM+X+GVLR1nPBx/d4CGDh73wkEF6ly395CGDh27wkMF6H7xkkFBCp3Hq1KmsWLGCn//850yaNImvfvWrfOc732Hu3LkpDTVmDgwaDbHcxJ4Xyw2fN2Z2ZmRYQw0H2EErLQk9r5UW9rOdtTyY9hk87IOHDNI79VO0Gay7wUsG672wni/xy5aOsp4PPrrBQwYPe+Ehg/QuW/rJQwYP3eAhg/U+eMkgoYRvkX7gAx/gpZdeorm5mQ0bNnDzzTenPFReEVz5ZPjGYfEeklhu+PirVobPz4QMLTRzJ7No5mDcpdFKC80c5E5m0kJz2mfwsA8eMkh81E/RZbDuBi8ZrPfCer4kJhs6yno++OgGDxk87IWHDBKfbOgnDxk8dIOHDNb74CWDhJL9Lcp+N3g8XLMaBpYf+0R3SY99fmB5+PjScZmVYR9buINpvMlugG5//7f982+ymzuYxj62ZkwGD/vgIYP44eE8eMhg3Q1eMljvhfV88cf6TFjPBx/d4CGDh73wkEH88HAerDN46AYPGaz3wUsGcXxTCsLNvnYDTL8XyqZ0/ZiyKeHXr93QP4fDQ4Z9bGUxE1nOPOqo7fIxddSynHksZmJKy8JLBg/74CGD+OHhPHjIYN0NXjJY74X1fPHH+kxYzwcf3eAhg4e98JBB/PBwHqwzeOgGDxms98FLhmyXZx2gN3lFUDkv/Ni/Duo3QUtj+LK5wZXhO+dnQ4YWmnmW+3iW+6igiuFUUkQJh2nkNTZ1WySZlMHDPnjIIH54OA8eMlh3g5cM1nthPV/8sT4T1vPBRzd4yOBhLzxkED88nAfrDB66wUMG633wkiGbub8p1dnQavsD4SFDHbWRFITnDB72wUMG8cPDefCQwbobvGSw3gvr+eKP9Zmwng8+usFDBg974SGD+OHhPFhn8NANHjJY74OXDNnG9a/viYiIiIiIiIhIZtJNKRERERERERERiZxuSomIiIiIiIiISORiQRAEUQ5sbGyktLQUYjBwVJSTQ2+9CkEbxHJgwMjo5yuDMnjLYD0foGkPEEBDQwMlJSU2IbDvJ/CxH9YZrOcrgzKczENHqZ+Uwct8ZfCVQf0U8rAXyqAMXuZ7yRBvP9ndlBIROYmbm1IiIl1w8S99IiJdUD+JiFe99ZPdX9/TK6WUQRlcZLCeD8fvoruh/9KX9WdSGZShM1cdpX7K+gzW85XBVwb1U8jDXiiDMniZ7yVDvP1kdlNqwAiYuyv6uQ+UQ9PucGMs5iuDMnjLYD0f4P5RYXF6YdVP4GM/rDNYz1cGZTiZp45SPymD9Xxl8JVB/RTysBfKoAxe5nvJEG8/6Y3ORUREREREREQkcropJSIiIiIiIiIikdNNKRERERERERERiZzdG50nYf86qN8ILQchvxgGT4Ch1dmXoYIqRjCBQopp5iB72UgdtZFmsF4H6/kiJ/NwJj1kUD/5ySDSmfWZtJ4P6idPGUQ683AmrTOon/xkkOi5vyl19DBsq4H1S+FA7alfL6uCSQtgzBzIK8rcDPkUMpU5zGABZ3HqlbmTdaxiKWuooYXmfslgvQ7W80VO5uFMesigfvKTQaQz6zNpPR/UT54yiHTm4UxaZ1A/+ckgtlz/+l79ZnhoIjxzExx4sevHHHgx/PpDE6FhS2ZmGMY4FrOBG7iHciZ3+ZhyJnMD97CYDQxjbMozWK+D9XyRk3k4kx4yqJ/8ZBDpzPpMWs8H9ZOnDCKdeTiT1hnUT34yiD23N6XqN8PDF0FT+58vbOvmgcc+37QLVkxL7UH1kGEY47iN5xjCmcSIkUNul4/LIZcYMYZwJrexOqXFZb0O1vNFTubhTHrIoH7yk0GkM+szaT0f1E+eMoh05uFMWmdQP/nJID64vCl19DA8NgtaGiFoje85QWv4+F/NDJ+fCRnyKWQhT1JIMbnkx/WcXPIppJiFrCSfwj5nsF4H6/kiJ/NwJj1kUD/5ySDSmfWZtJ4P6idPGUQ683AmrTOon/xkED8Suil19tlnE4vFTvmYP39+SkNtq4FDO+I/oO2C1vB52x7MjAxTmUMZo+MurHa55DOUs7mQ2X3OYL0O1vMlvUTRUR7OpIcM6ic/GSQ9ZMvPUNbzQf3kKYOkh2zpJw8Z1E9+MogfCd2UWrNmDa+++mrHx8qVKwH4yEc+ktJQ65cmmqyTnGPPz4AMM1hA0O3rGHvWRiszuLXPGazXwXq+pJcoOsrDmfSQQf3kJ4Okh2z5Gcp6PqifPGWQ9JAt/eQhg/rJTwbxI6GjcMYZZzBixIiOj0cffZQxY8Ywffr0lAXav+7Yu+4nd61CGxxYF36fdM5QQRVnUd3t7xj3JodcRnMBFVQlncF6HaznS/rp747ycCY9ZFA/+ckg6SMbfoayng/qJ08ZJH1kQz95yKB+8pNBfEn6PaXefvtt7r//fm666SZisVi3jzty5AiNjY0nfPSkfmOyiU76Ppv68FwHGUYwISUZhlOZ9HOt18F6vqS3eDpK/ZQc9ZOfDJKe+qOfwP5MWs8H9ZOnDJKeMrWfPGRQP/nJIL4kfVPq4Ycfpr6+nnnz5vX4uCVLllBaWtrxUVFR0ePjWw4mm+ik79N7N7rOUEhxSjIUUZL0c63XwXq+pLd4Okr9lBz1k58Mkp76o5/A/kxazwf1k6cMkp4ytZ88ZFA/+ckgviR9U+ruu+/miiuuYNSoUT0+btGiRTQ0NHR81NXV9fj4/NRcq+Qnf626yNBMaq7WwyR/tVqvg/V8SW/xdJT6KTnqJz8ZJD31Rz+B/Zm0ng/qJ08ZJD1laj95yKB+8pNBfMlL5kk7duzgqaee4r//+797fWxBQQEFBQVxf+/BqXlVY5++j4cMe0nN6xr78n2s18F6vqSveDtK/ZQc9ZOfDJJ++qufwP5MWs8H9ZOnDJJ+MrmfPGRQP/nJIL4k9Uqpe++9l2HDhnHVVVelOg9Dq6Gsij69G39ZNQytSu8MddSyk3W0keDfyTymjVZ28Dy7eCHpDNbrYD1f0ld/dZSHM+khg/rJTwZJP5n8M5T1fFA/ecog6SeT+8lDBvWTnwziS8JHoa2tjXvvvZcbb7yRvLykXmjVq0kL6NO78U9akBkZVrGUWJJXaw65rOK7fc5gvQ7W8yX99HdHeTiTHjKon/xkkPSRDT9DWc8H9ZOnDJI+sqGfPGRQP/nJIH4kfEU89dRT7Ny5k5tuuqk/8gAwZg4MGg2xBP9aZiw3fN6Y2ZmRYQ01HGAHrbQk9LxWWtjPdtbyYJ8zWK+D9XxJP/3dUR7OpIcM6ic/GSR9ZMPPUNbzQf3kKYOkj2zoJw8Z1E9+MogfCd+UmjVrFkEQMH78+P7IA0BeEVz5ZPjmZfEe1Fhu+PirVobPz4QMLTRzJ7No5mDcxdVKC80c5E5m0kJznzNYr4P1fEk//d1RHs6khwzqJz8ZJH1kw89Q1vNB/eQpg6SPbOgnDxnUT34yiB9J//W9/jZ4PFyzGgaWH/tEd0mPfX5gefj40nGZlWEfW7iDabzJboBufwe5/fNvsps7mMY+tqYsg/U6WM8XOZmHM+khg/rJTwaRzqzPpPV8UD95yiDSmYczaZ1B/eQng/jg9qYUhAfu2g0w/V4om9L1Y8qmhF+/dkP/HFAPGfaxlcVMZDnzqKO2y8fUUcty5rGYiSktrHbW62A9X+RkHs6khwzqJz8ZRDqzPpPW80H95CmDSGcezqR1BvWTnwxir3/exS6F8oqgcl74sX8d1G+ClsbwpXuDK8N378+GDC008yz38Sz3UUEVw6mkiBIO08hrbOq2zFLJeh2s54uczMOZ9JBB/eQng0hn1mfSej6onzxlEOnMw5m0zqB+8pNBbLm/KdXZ0Gr7Q+khQx21kZRUT6zXwXq+yMk8nEkPGdRPfjKIdGZ9Jq3ng/rJUwaRzjycSesM6ic/GSR6rn99T0REREREREREMpNuSomIiIiIiIiISOR0U0pERERERERERCIXC4IgiHJgY2MjpaWlEIOBo6KcHHrrVQjaIJYDA0ZGP18ZlMFbBuv5AE17gAAaGhooKSmxCYF9P4GP/bDOYD1fGZThZB46Sv2kDF7mK4OvDOqnkIe9UAZl8DLfS4Z4+8nuppSIyEnc3JQSEemCi3/pExHpgvpJRLzqrZ/s/vqeXimlDMrgIoP1fDh+F90N/Ze+rD+TyqAMnbnqKPVT1mewnq8MvjKon0Ie9kIZlMHLfC8Z4u0ns5tSA0bA3F3Rz32gHJp2hxtjMV8ZlMFbBuv5APePCovTC6t+Ah/7YZ3Ber4yKMPJPHWU+kkZrOcrg68M6qeQh71QBmXwMt9Lhnj7SW90LiIiIiIiIiIikdNNKRERERERERERiZxuSomIiIiIiIiISOTs3ug8CfvXQf1GaDkI+cUweAIMrc6+DBVUMYIJFFJMMwfZy0bqqI00g4d1EPHEwzXhIYP6ScQn6+vCej6on0S88nBdWGdQP0k2c39T6uhh2FYD65fCgdpTv15WBZMWwJg5kFeUuRnyKWQqc5jBAs7i1HbYyTpWsZQ11NBCc79k8LAOIp54uCY8ZFA/ifhkfV1Yzwf1k4hXHq4L6wzqJ5GQ61/fq98MD02EZ26CAy92/ZgDL4Zff2giNGzJzAzDGMdiNnAD91DO5C4fU85kbuAeFrOBYYxNeQYP6yDiiYdrwkMG9ZOIT9bXhfV8UD+JeOXhurDOoH4SOc7tTan6zfDwRdDU/ucL27p54LHPN+2CFdNSe7F4yDCMcdzGcwzhTGLEyCG3y8flkEuMGEM4k9tYndLi8rAOIp54uCY8ZFA/ifhkfV1Yzwf1k4hXHq4L6wzqJ5ETubwpdfQwPDYLWhohaI3vOUFr+PhfzQyfnwkZ8ilkIU9SSDG55Mf1nFzyKaSYhawkn8I+Z/CwDiKeeLgmPGRQP4n4ZH1dWM8H9ZOIVx6uC+sM6ieRUyV0U6q1tZV/+Zd/4ZxzzqGoqIgxY8bw1a9+lSAIUhpqWw0c2hH/RdIuaA2ft+3BzMgwlTmUMTruwmqXSz5DOZsLmd3nDB7WQSQe6qdoM6ifRBKTLR1lPR/UTyKJypZ+8pBB/SRyqoRuSv3bv/0by5Yt43vf+x4bNmzg3/7t3/j3f/93vvvd76Y01PqliSbrJOfY8zMgwwwWEHT7WsqetdHKDG7tcwYP6yASD/VTtBnUTyKJyZaOsp4P6ieRRGVLP3nIoH4SOVVCx/EPf/gDV199NVdddRVnn302f/M3f8OsWbP44x//mLJA+9cde+f/5K5VaIMD68Lvk84ZKqjiLKq7/R3j3uSQy2guoIKqpDN4WAeReKmfosugfhJJXDZ0lPV8UD+JJCMb+slDBvWTSNcSuin1F3/xF/zmN79h8+bNALzwwgv8/ve/54orruj2OUeOHKGxsfGEj57Ub0wkUQ/fZ1MfnusgwwgmpCTDcCqTfq6HdRCJl/opugzqJ5HEJdpRifYT2F8X1vNB/SSSjGzoJw8Z1E8iXctL5MG33XYbjY2NTJgwgdzcXFpbW/n617/O3Llzu33OkiVL+Nd//de4Z7QcTCRRD9+n9250naGQ4pRkKKIk6ed6WAeReKmfosugfhJJXKIdlWg/gf11YT0f1E8iyciGfvKQQf0k0rWEXin10EMP8cADD/Czn/2MP/3pT9x333184xvf4L777uv2OYsWLaKhoaHjo66urscZ+am5VslP/lp1kaGZ1DTGYZJvDA/rIBIv9VN0GdRPIolLtKMS7Sewvy6s54P6SSQZ2dBPHjKon0S6ltArpf7pn/6J2267jTlz5gDwzne+kx07drBkyRJuvPHGLp9TUFBAQUFB3DMGp+ZVjX36Ph4y7CU1r63sy/fxsA4i8VI/Rfd91E8iiUu0oxLtJ7C/Lqzng/pJJBnZ0E8eMqifRLqW0Cul3nrrLXJyTnxKbm4ubW3JvlPaqYZWQ1lVosk6yYGyahhald4Z6qhlJ+toI8G/1XlMG63s4Hl28ULSGTysg0i81E/RZVA/iSQuGzrKej6on0SSkQ395CGD+kmkawkdxw9+8IN8/etf51e/+hXbt29nxYoVfOtb3+Kaa65JaahJC+jTXwSYtCAzMqxiKbEkGyOHXFbR9z/j6mEdROKhfoo2g/pJJDHZ0lHW80H9JJKobOknDxnUTyKnSuiK+O53v8vf/M3f8KlPfYqJEyfyuc99jn/4h3/gq1/9akpDjZkDg0ZDLMG/lhnLDZ83ZnZmZFhDDQfYQSstCT2vlRb2s521PNjnDB7WQSQe6qdoM6ifRBKTLR1lPR/UTyKJypZ+8pBB/SRyqoRuShUXF/Od73yHHTt2cPjwYbZt28bXvvY1TjvttJSGyiuCK58M30At3osllhs+/qqV4fMzIUMLzdzJLJo5GHdxtdJCMwe5k5m00NznDB7WQSQe6qdoM6ifRBKTLR1lPR/UTyKJypZ+8pBB/SRyqmR/m7TfDR4P16yGgeXHPtFd0mOfH1gePr50XGZl2McW7mAab7IboNvfQW7//Jvs5g6msY+tKcvgYR1EPPFwTXjIoH4S8cn6urCeD+onEa88XBfWGdRPIidye1MKwkN/7QaYfi+UTen6MWVTwq9fu6F/LhIPGfaxlcVMZDnzqKO2y8fUUcty5rGYiSktrHYe1kHEEw/XhIcM6icRn6yvC+v5oH4S8crDdWGdQf0kclyedYDe5BVB5bzwY/86qN8ELY3hywcHV4Z/QSAbMrTQzLPcx7PcRwVVDKeSIko4TCOvsanbMkslD+sg4omHa8JDBvWTiE/W14X1fFA/iXjl4bqwzqB+Egm5vynV2dBq+wvDQ4Y6aiMpqZ54WAcRTzxcEx4yqJ9EfLK+Lqzng/pJxCsP14V1BvWTZDPXv74nIiIiIiIiIiKZSTelREREREREREQkcropJSIiIiIiIiIikYsFQRBEObChoYHBgwcDMGBklJNDb+0FAiAGA0ZEP18ZlMFbBuv5AG+9Gv7P+vp6SktLbUJg30/gZD90JpVBGU7M4KCj1E/K4GW+MjjLoH4CnOyFMiiDk/luMsTZT5HflNq1axcVFRVRjhSRNFFXV0d5ebnZfPWTiPTEsqPUTyLSE/WTiHjVWz9FflOqra2NPXv2UFxcTCwWS/j5jY2NVFRUUFdXR0lJST8kVIZ0yWA9XxlSlyEIAg4ePMioUaPIybH7rWL1kzJkUgbr+ZmUwUNH9bWfwH4/rOcrgzJ4y6B+Os56LzxksJ6vDMqQ6gzx9lNeX0ImIycnJyV38UtKSsw2Rxl8ZbCerwypyWD5a3vt1E/KkIkZrOdnSgbrjkpVP4H9fljPVwZl8JZB/XSc9V54yGA9XxmUIZUZ4uknvdG5iIiIiIiIiIhETjelREREREREREQkcml3U6qgoIAvf/nLFBQUKEOWZ7Cerwy+MnjgYR2UQRm8zFcGf6zXwnq+MiiDtwzW8z3xsBbWGaznK4MyWGWI/I3ORURERERERERE0u6VUiIiIiIiIiIikv50U0pERERERERERCKnm1IiIiIiIiIiIhI53ZQSEREREREREZHIpdVNqWeffZbc3FyuuuqqyGfPmzePWCzW8VFWVsb73/9+Xnzxxciz7N27l1tvvZVzzz2XgoICKioq+OAHP8hvfvObfp/deR3y8/MZPnw4M2fO5J577qGtra3f55+cofPH+9///kjm95Zj69atkczfu3cvCxcuZOzYsRQWFjJ8+HAuueQSli1bxltvvdXv8+fNm8eHP/zhUz7/9NNPE4vFqK+v7/cM3qij1E8n57DqKOt+AtuOUj+dSv2kfjo5h/pJP0N5oX5SP52cQ/2UXf2UVjel7r77bm699VZ+97vfsWfPnsjnv//97+fVV1/l1Vdf5Te/+Q15eXl84AMfiDTD9u3bueCCC/jtb3/Lf/zHf/DSSy/xxBNPMGPGDObPnx9JhvZ12L59O48//jgzZsxg4cKFfOADH+Do0aORZuj88fOf/zyS2b3lOOecc/p97v/93/9RXV3Nk08+ye233866det49tln+ed//mceffRRnnrqqX7PIKfK9o5SP52aw7KjrPoJ1FEeqZ/UTyfnUD+pn7xQP6mfTs6hfsqufsqzDhCvQ4cO8eCDD7J27Vr27t3L8uXL+cIXvhBphoKCAkaMGAHAiBEjuO222/jLv/xLXn/9dc4444xIMnzqU58iFovxxz/+kYEDB3Z8/h3veAc33XRTJBk6r8OZZ57J+eefz0UXXcTll1/O8uXL+fu///tIM1iyyvGpT32KvLw81q5de8I5OPfcc7n66qsJgiDyTNlOHaV+6i6HFcsM6ihf1E/qp+5yWFE/STv1k/qpuxxW1E/RS5tXSj300ENMmDCByspKrr/+eu655x7TTTl06BD3338/Y8eOpaysLJKZb7zxBk888QTz588/4ZC2Gzx4cCQ5unLZZZcxZcoU/vu//9ssQ7Y4cOAATz75ZLfnACAWi0WcSrK9o9RP0k4d5Y/6Sf0kIfWTP+on9ZOEsrmf0uam1N133831118PhC+pa2ho4Jlnnok0w6OPPsqgQYMYNGgQxcXFPPLIIzz44IPk5ESzjFu3biUIAiZMmBDJvERNmDCB7du3RzKr8160f9x+++2RzO4px0c+8pF+n9l+DiorK0/4/NChQztyfP7zn+/3HND1PlxxxRWRzPYm2ztK/XQiDx1l0U/gp6PUT8epn9RPnamf7PsJ1FHt1E/qp87UT9nZT2nx63ubNm3ij3/8IytWrAAgLy+P2bNnc/fdd3PppZdGlmPGjBksW7YMgDfffJP//M//5IorruCPf/wjo0eP7vf53l+uFwRBZHdvO+9Fu9NPPz2S2T3l6O6udhT++Mc/0tbWxty5czly5EgkM7vah9WrV3f8cJEt1FHqp5N56ChP/QTRd5T6KaR+Uj+dTP10Kv0MZUP9pH46mfrpVNnQT2lxU+ruu+/m6NGjjBo1quNzQRBQUFDA9773PUpLSyPJMXDgQMaOHdvxf//4xz+mtLSUu+66i6997Wv9Pn/cuHHEYjE2btzY77OSsWHDhsjeBO7kvbBikWPs2LHEYjE2bdp0wufPPfdcAIqKiiLL0tX//7t27YpsvhfqKPXTyTx0lFUGLx2lfgqpn9RPJ1M/2fcTqKNA/QTqp5Opn7Kzn9z/+t7Ro0f5yU9+wje/+U1qa2s7Pl544QVGjRpl8hfX2sViMXJycjh8+HAk804//XTe97738f3vf5+mpqZTvm7552N/+9vf8tJLL/HXf/3XZhmyRVlZGTNnzuR73/tel+dAoqWOCqmfpJ06yg/1U0j9JO3UT36on0LqJ2mXzf3k/pVSjz76KG+++SYf+9jHTrlb/td//dfcfffdfOITn4gky5EjR9i7dy8QvrTze9/7HocOHeKDH/xgJPMBvv/973PJJZfwrne9i6985StMnjyZo0ePsnLlSpYtW8aGDRv6PUP7OrS2tvLaa6/xxBNPsGTJEj7wgQ9www039Pv8zhk6y8vLY+jQoZHMt/af//mfXHLJJVx44YUsXryYyZMnk5OTw5o1a9i4cSMXXHCBdcSsoY46Tv10ao7O1FHqqKipn45TP52aozP1k/opauqn49RPp+boTP2UBf0UOPeBD3wguPLKK7v82urVqwMgeOGFF/o9x4033hgAHR/FxcXB1KlTg//6r//q99kn27NnTzB//vxg9OjRwWmnnRaceeaZwYc+9KFg1apV/T678zrk5eUFZ5xxRvDe9743uOeee4LW1tZ+n39yhs4flZWVkczvnOPqq6+OdGZne/bsCW655ZbgnHPOCfLz84NBgwYF73rXu4L/+I//CJqamvp9fnf//69atSoAgjfffLPfM3igjjpRtvfTyTmsOsq6n4LAtqPUTyH104nUT+qndvoZyp766UTqJ/VTu2zsp1gQOH93NRERERERERERyTju31NKREREREREREQyj25KiYiIiIiIiIhI5HRTSkREREREREREIqebUiIiIiIiIiIiEjndlBIRERERERERkcjpppSIiIiIiIiIiERON6VERERERERERCRyuiklIiIiIiIiIiKR000pERERERERERGJnG5KpZkf/OAHFBcXc/To0Y7PHTp0iPz8fC699NITHvv0008Ti8XYtm0bb7zxBrfeeiuVlZUUFRVx1llnsWDBAhoaGk54zoIFC7jgggsoKCigqqoqoWznnHMOTz311Cmfj3d2uwMHDlBeXk4sFqO+vr7XuYcPH2bgwIFs3bq1y6/HYrGOj7y8PM466yw++9nPcuTIkY7HvPrqq/zt3/4t48ePJycnh09/+tOnfJ+Wlha+8pWvMGbMGAoLC5kyZQpPPPFEr/lEskl/dtTy5ctPuJ47f+zbt6/HXD31xPbt2/nYxz7GOeecQ1FREWPGjOHLX/4yb7/9dsdjNm3axIwZMxg+fDiFhYWce+65fOlLX6KlpaXXNdmxYwdFRUUcOnSoy9md//847bTTGDt2LF/72tcIgqDjcX/+85/567/+a84++2xisRjf+c53epx5xx13EIvFuuwykWzV3z9DQdhTkydPprCwkGHDhjF//vy4svXlZ6gXXniB6667joqKCoqKipg4cSJ33nlnXHOj+hkKoL6+nvnz5zNy5EgKCgoYP348jz32WFw5RTJdsv0E8A//8A+MGTOGoqIizjjjDK6++mo2btx4wnN27tzJVVddxYABAxg2bBj/9E//dMKs7vT156fm5mbmzZvHO9/5TvLy8vjwhz8c95pE1U///d//zYUXXsjgwYMZOHAgVVVV/PSnP407p/RdnnUAScyMGTM4dOgQa9eu5aKLLgLgf/7nfxgxYgSrV6+mubmZwsJCAFatWsVZZ53FmDFjWL9+PXv27OEb3/gG5513Hjt27OATn/gEe/bs4b/+679OmHHTTTexevVqXnzxxbhzvfjii7z55ptMnz79lK/t2bMn7tkAH/vYx5g8eTK7d++Oa/bKlSsZPXo0Y8eO7fYx9957L+9///tpaWnhhRde4KMf/SgDBw7kq1/9KgBHjhzhjDPO4Etf+hLf/va3u/weX/rSl7j//vu56667mDBhAr/+9a+55ppr+MMf/kB1dXVcWUUyXX921OzZs3n/+99/wrx58+bR3NzMsGHDeszVU09s3LiRtrY2fvjDHzJ27FjWr1/PzTffTFNTE9/4xjcAyM/P54YbbuD8889n8ODBvPDCC9x88820tbVx++239zj7l7/8JTNmzGDQoEHdPuapp57iHe94B0eOHOH3v/89f//3f8/IkSP52Mc+BsBbb73Fueeey0c+8hE+85nP9DhvzZo1/PCHP2Ty5Mk9Pk4k2/T3z1Df+ta3+OY3v8l//Md/MG3aNJqamti+fXuvufr6M9Tzzz/PsGHDuP/++6moqOAPf/gDH//4x8nNzeWWW27pcXZUP0O9/fbbzJw5k2HDhvFf//VfnHnmmezYsYPBgwf3uj4i2SDZfgK44IILmDt3LmeddRZvvPEGixcvZtasWbzyyivk5ubS2trKVVddxYgRI/jDH/7Aq6++yg033EB+fn6vP8P09een1tZWioqKWLBgAb/4xS8SWpOo+un000/ni1/8IhMmTOC0007j0Ucf5aMf/SjDhg3jfe97X0KZJUmBpJ2RI0cGS5Ys6fi///mf/zmYP39+MHHixGDVqlUdn3/Pe94T3Hjjjd1+n4ceeig47bTTgpaWllO+9uUvfzmYMmVK3Jm+8pWvBLNnz4778d3N/s///M9g+vTpwW9+85sACN58881ev9dNN90UfP7zn+/260CwYsWKEz73sY99LLjyyiu7fPz06dODhQsXnvL5kSNHBt/73vdO+Nxf/dVfBXPnzu01o0g2iaKjgiAI9u3bF+Tn5wc/+clPes3UW0+c7N///d+Dc845p8fHfOYznwne/e539/q9LrvssmDZsmVdfu2VV14JgGDdunUnfP7yyy8PPvWpT3X5nNGjRwff/va3u/zawYMHg3HjxgUrV67ststEsll/9dMbb7wRFBUVBU899VTCmVL1M1Rnn/rUp4IZM2b0+r2i+hlq2bJlwbnnnhu8/fbbvWYSyVap6qcXXnghAIKtW7cGQRAEjz32WJCTkxPs3bu34zHLli0LSkpKgiNHjvSYKZU/P914443B1VdfHff3iqqfulJdXR186Utfijeq9JF+fS8NzZgxg1WrVnX836tWreLSSy9l+vTpHZ8/fPgwq1evZsaMGd1+n4aGBkpKSsjL6/sL5h555BGuvvrquB/f1eyXX36Zr3zlK/zkJz8hJye+o9nW1sajjz6a0OzNmzfz29/+lmnTpsX9HAjvtLf/F4p2RUVF/P73v0/o+4hkuqg66ic/+QkDBgzgb/7mb3rMk0xPNDQ0cPrpp3f79a1bt/LEE090+cqGzurr6/n973/Phz70obhnr127lueffz7hjgKYP38+V111Fe9973sTfq5INuivflq5ciVtbW3s3r2biRMnUl5ezrXXXktdXV2vmVLxM1RXj+mpwyDan6EeeeQRLr74YubPn8/w4cOZNGkSt99+O62trQl9H5FMlop+ampq4t577+Wcc86hoqICgGeffZZ3vvOdDB8+vONx73vf+2hsbOTPf/5zt3n64+eneEXZT50FQcBvfvMbNm3axHve856kv48kyPqumCTurrvuCgYOHBi0tLQEjY2NQV5eXrBv377gZz/7WfCe97wnCIKg45VGO3bs6PJ7vP7668FZZ50VfOELX+jy64m8UmrXrl3BaaedFtermrqb3dzcHEyePDn46U9/GgRBEKxatSquV0r97//+bzBs2LCgtbW128cAQWFhYTBw4MCgoKAgAIIPfOAD3f7Xuu7uol933XXBeeedF2zevDlobW0NnnzyyaCoqCg47bTTev9/WiSLRNFRQRAEEydODD75yU/2mieenuhsy5YtQUlJSfCjH/3olK9dfPHFHT3y8Y9/vNfv+cADDwQXXnhht19vf6VUUVFRMHDgwCA/P7/je3enu1dK/fznPw8mTZoUHD58OAiCxP6LoEi26K9+WrJkSZCfnx9UVlYGTzzxRPDss88Gl19+eVBZWdnjKxFS8TPUyf73f/83yMvLC37961/3+L2i/BmqsrIyKCgoCG666aZg7dq1QU1NTXD66acHixcv7jGjSDbpSz99//vfDwYOHBgAQWVlZcerpIIgCG6++eZg1qxZJzy+qakpAILHHnus2zyp/PkpCBJ7pVSU/RQEQVBfXx8MHDgwyMvLCwoKCoK77747rpySGnqlVBq69NJLaWpqYs2aNfzP//wP48eP54wzzmD69Okdv3P89NNPc+6553LWWWed8vzGxkauuuoqzjvvPBYvXtznPI888gjvfve743pfgO5mL1q0iIkTJ3L99dcnNPuXv/wlH/jAB3p9ZdW3v/1tamtreeGFF3j00UfZvHkzf/d3f5fQrDvvvJNx48Z1/L7xLbfcwkc/+tG4X9Ulki2i6Khnn32WDRs2dLznUk/i7QmA3bt38/73v5+PfOQj3Hzzzad8/cEHH+RPf/oTP/vZz/jVr37V8Z4JPc2O51VSDz74YEdHPfTQQ/zyl7/ktttu6/V57erq6li4cCEPPPDAKa/oFJHj+quf2traaGlpYenSpbzvfe/joosu4uc//zlbtmw54ZUPJ0vFz1CdrV+/nquvvpovf/nLzJo1q8fvF+XPUG1tbQwbNowf/ehHXHDBBcyePZsvfvGL/OAHP0jo+4hksr7009y5c1m3bh3PPPMM48eP59prr6W5ublPeVL581N/zU5FPwEUFxdTW1vLmjVr+PrXv85nP/tZnn766STTS6L0RudpaOzYsZSXl7Nq1aoT3hhz1KhRHW9wuWrVKi677LJTnnvw4EHe//73U1xczIoVK8jPz+9znkceeSSuf+nqafZvf/tbXnrppY437QyO/dWpoUOH8sUvfpF//dd/7Xb2HXfc0evsESNGdLxJXmVlJQcPHuS6667ja1/7Wo9vntfZGWecwcMPP0xzczMHDhxg1KhR3HbbbZx77rlxPV8kW0TRUT/+8Y+pqqriggsu6DVPvD2xZ88eZsyYwV/8xV/wox/9qMvHtL8U/rzzzqO1tZWPf/zj/OM//iO5ubmnPPbtt9/miSee4Atf+EKvsysqKjq6aOLEiWzbto1/+Zd/YfHixXHdZHr++efZt28f559/fsfnWltb+d3vfsf3vvc9jhw50mVGkWzTX/00cuRIIOyGdmeccQZDhw5l586d3eZJxc9Q7V5++WUuv/xyPv7xj/OlL32p1+8Z5c9QI0eOJD8//4QemjhxInv37uXtt9/mtNNOi+v7iGSyvvRTaWkppaWljBs3josuuoghQ4awYsUKrrvuOkaMGMEf//jHEx7/2muvAeH13Z1U/vyUqCj7CSAnJ6fj8VVVVWzYsIElS5ac8pcPpX/oJR5pasaMGTz99NM8/fTTJ1ws73nPe3j88cf54x//eMrvGjc2NjJr1ixOO+00HnnkkZT81/RDhw6xatWqXn/ft7fZv/jFL3jhhReora2ltraWH//4x0D4Vye6+3PKW7ZsYceOHcycOTPh3O0/FB0+fDjh5xYWFnLmmWdy9OhRfvGLXyT0u84i2aI/O+rQoUM89NBDcb1KKt6e2L17N5deeikXXHAB9957b1z/VbD9lRFtbW1dfv3pp59myJAhTJkypdfvdbLc3FyOHj16wp9V7snll1/OSy+91NGhtbW1XHjhhcydO5fa2lrdkBLppD/66ZJLLgFg06ZNHZ9744032L9/P6NHj+4yR6p+hgL485//zIwZM7jxxhv5+te/3uP3g+h/hrrkkkvYunXrCX25efNmRo4cqRtSIp0k008nC4KAIAg4cuQIABdffDEvvfQS+/bt63jMypUrKSkpOeFGemf9+fNTb6z+Ha+ztra2jvWT/qdXSqWpGTNmMH/+fFpaWk54o93p06dzyy238Pbbb59QWO0/0Lz11lvcf//9NDY20tjYCIT/Ja/9At66dSuHDh1i7969HD58mNraWiD8L39d/dDwxBNPMH78eM4+++xus8Yzu/1Pmrbbv38/EP5XtO5e0v7LX/6S9773vQwYMKDnxSJ8s+G9e/fS1tbGli1b+MpXvsL48eOZOHFix2Pa/389dOgQr7/+OrW1tZx22mkdZb169Wp2795NVVUVu3fvZvHixbS1tfHP//zPvc4XyTb91VEQ/qrb0aNH4/p133h6ov0HqtGjR/ONb3yD119/veNr7f8F8YEHHiA/P593vvOdFBQUsHbtWhYtWsTs2bO7fTVXvK+AADhw4AB79+7l6NGjvPTSS9x5553MmDGDkpISIHzV1csvv9zxv+/evZva2loGDRrE2LFjKS4uZtKkSSd8z4EDB1JWVnbK50WyXX/00/jx47n66qtZuHAhP/rRjygpKWHRokVMmDCh23+BTNXPUOvXr+eyyy7jfe97H5/97GfZu3cvEP7L2RlnnNHl9436Z6hPfvKTfO9732PhwoXceuutbNmyhdtvv50FCxb0Ol8kmyTaT//3f//Hgw8+yKxZszjjjDPYtWsXd9xxB0VFRVx55ZUAzJo1i/POO4+/+7u/49///d/Zu3cvX/rSl5g/fz4FBQVd5kjVz08Qvorz7bff5o033uDgwYMdfVFVVZX07Hap6KclS5Zw4YUXMmbMGI4cOcJjjz3GT3/6U5YtW9brfEkR4/e0kiS1vznuhAkTTvj89u3bO97grrP2Nw7v6uOVV17peNz06dN7fUxn119/ffDFL36xx6zxzu7qOT298ee73/3u4K677upxdhAEJ8yLxWLByJEjg9mzZwfbtm3r9nHtH6NHj+74+tNPPx1MnDgxKCgoCMrKyoK/+7u/C3bv3t3rfJFs1F8dFQThm43/7d/+bVw54umJe++9t9vZ7WpqaoLzzz8/GDRoUDBw4MDgvPPOC26//faONxXvSkVFRbBy5coeZ7evU/tHbm5uUF5eHtx8883Bvn37un1c+8f06dO7/d56o3ORrvVXPzU0NAQ33XRTMHjw4OD0008PrrnmmmDnzp3d5kjVz1Bf/vKXe/0Z5mRR/wwVBEHwhz/8IZg2bVpQUFAQnHvuucHXv/714OjRo71mEMkmifbT7t27gyuuuCIYNmxYkJ+fH5SXlwd/+7d/G2zcuPGU519xxRVBUVFRMHTo0OAf//Efg5aWlm5zpOrnpyAI/0BLb49JdHYQpK6fvvjFLwZjx44NCgsLgyFDhgQXX3xxUFNT0+t8SZ1YEBx78x6RBB09epThw4fz+OOP8653vSvS2fv372fkyJHs2rXrhD9vKiLSzrIn/vSnP3HZZZfx+uuvp+S9+0Qks+hnKBHxyrIj1E/ZSe8pJUl74403+MxnPsPUqVNNZn/rW99SWYlItyx74ujRo3z3u9/VDSkR6ZJ+hhIRryw7Qv2UnfRKKRERERERERERiZxeKSUiIiIiIiIiIpHTTSkREREREREREYmcbkqJiIiIiIiIiEjkdFNKREREREREREQip5tSIiIiIiIiIiISOd2UEhERERERERGRyOmmlIiIiIiIiIiIRE43pUREREREREREJHK6KSUiIiIiIiIiIpHTTSkREREREREREYmcbkqJiIiIiIiIiEjkdFNKREREREREREQip5tSIiIiIiIiIiISOd2UEhERERERERGRyOVFPbCtrY09e/ZQXFxMLBaLeryIOBQEAQcPHmTUqFHk5NjdK1c/iUhXPHSU+klEuqJ+EhGv4u2nyG9K7dmzh4qKiqjHikgaqKuro7y83Gy++klEemLZUeonEemJ+klEvOqtnyK/KVVcXNzxvw8YGfV0eGsvEAAxGDAi+vnKoAzeMljPB3jr1fB/du4HC9b9BE72Q2dSGZThxAwOOkr9pAxe5iuDswzqJ8DJXiiDMjiZ7yZDnP0U+U2p9pd0DhgJ1++Jejo8UA5Nu2HgKJi7K/r5yqAM3jJYzwe4f1RYWtYv+bbuJ/CxH9YZrOcrgzKczENHqZ+Uwct8ZfCVQf0U8rAXyqAMXuZ7yRBvP+mNzkVEREREREREJHK6KSUiIiIiIiIiIpHTTSkREREREREREYlc5O8ple4qqGIEEyikmGYOspeN1FFrHUvEzP51UL8RWg5CfjEMngBDq61TZSf1k7TTdRnSOvihfgppHUK6NrUG3uja1Bq007UZinIddFMqDvkUMpU5zGABZ3HqTuxkHatYyhpqaKHZIKFItI4ehm01sH4pHKg99etlVTBpAYyZA3lFUafLLuonaafrMqR18EP9FNI6hHRtag280bWpNWinazNktQ769b1eDGMci9nADdxDOZO7fEw5k7mBe1jMBoYxNuKEItGq3wwPTYRnboIDL3b9mAMvhl9/aCI0bIk2XzZRP0k7XZchrYMf6qeQ1iGka1Nr4I2uTa1BO12bIct10E2pHgxjHLfxHEM4kxgxcsjt8nE55BIjxhDO5DZWZ+wFK1K/GR6+CJra/6xoWzcPPPb5pl2wYlrmlrcl9ZO003UZ0jr4oX4KaR1Cuja1Bt7o2tQatNO1GbJeh4RvSv3ud7/jgx/8IKNGjSIWi/Hwww+nJokz+RSykCcppJhc8uN6Ti75FFLMQlaST2E/JxSJ1tHD8NgsaGmEoDW+5wSt4eN/NTN8fn9TP3VP/ZSZ0uG6jEI6rIP6qXuZ2E9ah1A6XJv9LR3WIFv6CXRtgtagXTpcm1HwsA4J35RqampiypQpfP/73+/7dMemMocyRsd9obbLJZ+hnM2FzO6nZCI2ttXAoR3xl1W7oDV83rYH+ydXZ+qnnqmfMk86XJdRSId1UD/1LNP6SesQSodrs7+lwxpkSz+Brk3QGrRLh2szCh7WIeGbUldccQVf+9rXuOaaa/o+3bEZLCDo9nVrPWujlRncmuJEIrbWLyX5X/jNOfb8fqZ+6p36KbOkw3UZhXRYB/VT7zKpn7QOoXS4NvtbOqxBtvQT6NoErUG7dLg2o+BhHfSeUl2ooIqzqO72d2t7k0Muo7mACqpSG0zEyP51x/4CQ3L//II2OLAu/D7SN+onaafrMqR18EP9FNI6hHRtag280bWpNWinazPkZR36/abUkSNHaGxsPOHDuxFMSMn3GU5lSr6PiLX6jSn6PptS831SRf0k6SxTr8tEZeo6qJ/Sl9YhlKnXZiIydQ3SsZ9A1yZoDdpl6rWZKC/r0O83pZYsWUJpaWnHR0VFRX+P7LNCilPyfYooScn3EbHWcjBF38fZzyzqJ0lnmXpdJipT10H9lL60DqFMvTYTkalrkI79BLo2QWvQLlOvzUR5WYd+vym1aNEiGhoaOj7q6ur6e2SfNZOa3TlMmp9SkWPyU/PPL/Kd/fNL/STpLFOvy0Rl6jqon9KX1iGUqddmIjJ1DdKxn0DXJmgN2mXqtZkoL+uQl5oY3SsoKKCgoKC/x6TUXlLzOrZUfR8Ra4NT80rflH2fVFE/STrL1OsyUZm6Duqn9KV1CGXqtZmITF2DdOwn0LUJWoN2mXptJsrLOiT8SqlDhw5RW1tLbW0tAK+88gq1tbXs3Lmzb0kcqaOWnayjjQT/LuIxbbSyg+fZxQspTiZiY2g1lFXRp7/MUFYNQ6tSl6kr6qfeqZ8yR7pcl/0tXdZB/dS7TOknrUMoXa7N/pQua5AN/QS6NkFr0C5drs3+5mUdEh6/du1aqqurqa6uBuCzn/0s1dXV/L//9//6lsSZVSwlluTu5JDLKr6b4kQitiYtoE9/mWHSglSm6Zr6qXfqp8ySDtdlFNJhHdRPvcukftI6hNLh2uxv6bAG2dJPoGsTtAbt0uHajIKHdUj4NF566aUEQXDKx/Lly/uexpE11HCAHbTSktDzWmlhP9tZy4P9lEzExpg5MGg0xBL8C7Kx3PB5Y2b3T67O1E89Uz9lnnS4LqOQDuugfupZpvWT1iGUDtdmf0uHNciWfgJdm6A1aJcO12YUPKxDv7/RebpqoZk7mUUzB+O+YFtpoZmD3MlMWmju54Qi0corgiufDN/ILt7SiuWGj79qZfh8SQ31k7TTdRnSOvihfgppHUK6NrUG3uja1Bq007UZ8rAOuinVg31s4Q6m8Sa7Abr93dv2z7/Jbu5gGvvYGllGkSgNHg/XrIaB5cc+0V2DHPv8wPLw8aXjokiXXdRP0k7XZUjr4If6KaR1COna1Bp4o2tTa9BO12bIeh10U6oX+9jKYiaynHnUUdvlY+qoZTnzWMzEjLtQRU5WOg6u3QDT74WyKV0/pmxK+PVrN2ReaXuifpJ2ui5DWgc/1E8hrUNI16bWwBtdm1qDdro2Q5brkJe6b5W5WmjmWe7jWe6jgiqGU0kRJRymkdfY1O1FLJKp8oqgcl74sX8d1G+ClsbwZZyDK8O/5CDRUD9JO12XIa2DH+qnkNYhpGtTa+CNrk2tQTtdmyGrddBNqQTVUZs1F6dIPIZWZ09Re6d+kna6LkNaBz/UTyGtQ0jXptbAG12bWoN2ujZDUa6Dfn1PREREREREREQip5tSIiIiIiIiIiISOd2UEhERERERERGRyMWCIAiiHNjY2EhpaSnEYOCoKCeH3noVgjaI5cCAkdHPVwZl8JbBej5A0x4ggIaGBkpKSmxCYN9P4GM/rDNYz1cGZTiZh45SPymDl/nK4CuD+inkYS+UQRm8zPeSId5+srspJSJyEjc3pUREuuDiX/pERLqgfhIRr3rrJ7u/vqdXSimDMrjIYD0fjt9Fd0P/pS/rz6QyKENnrjpK/ZT1GaznK4OvDOqnkIe9UAZl8DLfS4Z4+8nsptSAETB3V/RzHyiHpt3hxljMVwZl8JbBej7A/aPC4vTCqp/Ax35YZ7CerwzKcDJPHaV+Ugbr+crgK4P6KeRhL5RBGbzM95Ih3n7SG52LiIiIiIiIiEjkdFNKREREREREREQip5tSIiIiIiIiIiISObs3Ok9CBVWMYAKFFNPMQfaykTpqsy6DB/vXQf1GaDkI+cUweAIMrc6e+eDjLHhYBwl5OA8eMnjg4bqwzmA930sGOc66H6zne+FhHTxcm8ognXm4LjxksOZhDTxcl8oQfQb3N6XyKWQqc5jBAs7i1FXYyTpWsZQ11NBCc8Zm8ODoYdhWA+uXwoHaU79eVgWTFsCYOZBXlHnzwcdZ8LAOEvJwHjxk8MDDdWGdwXq+lwxynHU/WM/3wsM6eLg2lUE683BdeMhgzcMaeLgulcE2g+tf3xvGOBazgRu4h3Imd/mYciZzA/ewmA0MY2xGZvCgfjM8NBGeuQkOvNj1Yw68GH79oYnQsCWz5oOPs+BhHSTk4Tx4yOCBh+vCOoP1fC8Z5DjrfrCe74WHdfBwbSqDdObhuvCQwZqHNfBwXSqDfQa3N6WGMY7beI4hnEmMGDnkdvm4HHKJEWMIZ3Ibq1N6sXjI4EH9Znj4Imhq/1OSbd088Njnm3bBimmpO6jW88HHWfCwDhLycB48ZPDAw3VhncF6vpcMcpx1P1jP98LDOni4NpVBOvNwXXjIYM3DGni4LpXBR4aEbkotWbKEqVOnUlxczLBhw/jwhz/Mpk2bUpOkk3wKWciTFFJMLvlxPSeXfAopZiEryacwIzJ4cPQwPDYLWhohaI3vOUFr+PhfzQyfn87zwcdZ8LAO3qmfos3ggYfrwjqD9XwvGdJBtnSU9XwvPKyDh2tTGdJDtvSTlwzWPKyBh+tSGfxkSOim1DPPPMP8+fN57rnnWLlyJS0tLcyaNYumpqa+J+lkKnMoY3TcF0m7XPIZytlcyOyMyODBtho4tCP+A9ouaA2ft+3B9J4PPs6Ch3XwTv0UbQYPPFwX1hms53vJkA6ypaOs53vhYR08XJvKkB6ypZ+8ZLDmYQ08XJfK4CdDQjelnnjiCebNm8c73vEOpkyZwvLly9m5cyfPP/9835N0MoMFBN2+ZqxnbbQyg1szIoMH65eS/C955hx7fhrPBx9nwcM6eKd+ijaDBx6uC+sM1vO9ZEgH2dJR1vO98LAOHq5NZUgP2dJPXjJY87AGHq5LZfCToU/vKdXQ0ADA6aef3vckx1RQxVlUd/t7rb3JIZfRXEAFVWmdwYP96469635ynQVtcGBd+H3ScT74OAse1iEdqZ/6L4MHHq4L6wzW871kSFeZ2FHW873wsA4erk1lSF+Z2E9eMljzsAYerktl8JMB+nBTqq2tjU9/+tNccsklTJo0qdvHHTlyhMbGxhM+ejKCCclGOsFwKpN+rocMHtRvTNH3SfJX0q3ng4+z4GEd0o36qX8zeODhurDOYD3fS4Z0FE9HJdpPYN8P1vO98LAOHq5NZUhPmdpPXjJY87AGHq5LZfCTAfpwU2r+/PmsX7+empqaHh+3ZMkSSktLOz4qKip6fHwhxclGOkERJUk/10MGD1oOpuj79P7PKZfzwcdZ8LAO6Ub91L8ZPPBwXVhnsJ7vJUM6iqejEu0nsO8H6/leeFgHD9emMqSnTO0nLxmseVgDD9elMvjJAEnelLrlllt49NFHWbVqFeXl5T0+dtGiRTQ0NHR81NXV9fj4ZlKzModJfmU8ZPAgPzWdRX6SnWU9H3ycBQ/rkE7UT/2fwQMP14V1Buv5XjKkm3g7KtF+Avt+sJ7vhYd18HBtKkP6yeR+8pLBmoc18HBdKoOfDAB5iTw4CAJuvfVWVqxYwdNPP80555zT63MKCgooKCiIe8ZeUvMasr58Hw8ZPBicmld3Jv19rOeDj7PgYR3SgfrJ5vtY8XBdWGewnu8lQ7pItKMS7Sew7wfr+V54WAcP16YypI9s6CcvGax5WAMP16Uy+MkACb5Sav78+dx///387Gc/o7i4mL1797J3714OHz7ctxSd1FHLTtbRRoJ/k/CYNlrZwfPs4oW0zuDB0Gooq6JP78ZfVg1Dq9JzPvg4Cx7WIR2on6LL4IGH68I6g/V8LxnSRTZ0lPV8Lzysg4drUxnSRzb0k5cM1jysgYfrUhn8ZCDR8cuWLaOhoYFLL72UkSNHdnw8+OCDfUtxklUsJZbkyuSQyyq+mxEZPJi0gD69G/+kBek9H3ycBQ/r4J36KdoMHni4LqwzWM/3kiEdZEtHWc/3wsM6eLg2lSE9ZEs/eclgzcMaeLgulcFPhoROYxAEXX7Mmzev70k6WUMNB9hBKy0JPa+VFvaznbX0vUA9ZPBgzBwYNBpiCf7V0Fhu+Lwxs9N7Pvg4Cx7WwTv1U7QZPPBwXVhnsJ7vJUM6yJaOsp7vhYd18HBtKkN6yJZ+8pLBmoc18HBdKoOfDEn/9b3+1EIzdzKLZg7GfbG00kIzB7mTmbTQnBEZPMgrgiufDN+8LN6DGssNH3/VyvD56TwffJwFD+sgIQ/nwUMGDzxcF9YZrOd7ySDHWfeD9XwvPKyDh2tTGaQzD9eFhwzWPKyBh+tSGfxkcHlTCmAfW7iDabzJboBuf++1/fNvsps7mMY+tmZUBg8Gj4drVsPA9j/C0d2pOfb5geXh40vHZcZ88HEWPKyDhDycBw8ZPPBwXVhnsJ7vJYMcZ90P1vO98LAOHq5NZZDOPFwXHjJY87AGHq5LZfCRwe1NKYB9bGUxE1nOPOqo7fIxddSynHksZmK/FIWHDB6UjoNrN8D0e6FsStePKZsSfv3aDan/h7j1fPBxFjysg4Q8nAcPGTzwcF1YZ7Ce7yWDHGfdD9bzvfCwDh6uTWWQzjxcFx4yWPOwBh6uS2Wwz5CXum/VP1po5lnu41nuo4IqhlNJESUcppHX2NTtBZRpGTzIK4LKeeHH/nVQvwlaGsOX7g2uDN+9P5Png4+z4GEdJOThPHjI4IGH68I6g/V8LxnkOOt+sJ7vhYd18HBtKoN05uG68JDBmoc18HBdKoNtBvc3pTqro9a8HDxk8GBote0/uK3ng4+z4GEdJOThPHjI4IGH68I6g/V8LxnkOOt+sJ7vhYd18HBtKoN05uG68JDBmoc18HBdKkP0GVz/+p6IiIiIiIiIiGQm3ZQSEREREREREZHI6aaUiIiIiIiIiIhELhYEQRDlwMbGRkpLSyEGA0dFOTn01qsQtEEsBwaMjH6+MiiDtwzW8wGa9gABNDQ0UFJSYhMC+34CH/thncF6vjIow8k8dJT6SRm8zFcGXxnUTyEPe6EMyuBlvpcM8faT3U0pEZGTuLkpJSLSBRf/0ici0gX1k4h41Vs/2f31Pb1SShmUwUUG6/lw/C66G/ovfVl/JpVBGTpz1VHqp6zPYD1fGXxlUD+FPOyFMiiDl/leMsTbT2Y3pQaMgLm7op/7QDk07Q43xmK+MiiDtwzW8wHuHxUWpxdW/QQ+9sM6g/V8ZVCGk3nqKPWTMljPVwZfGdRPIQ97oQzK4GW+lwzx9pPe6FxERERERERERCKnm1IiIiIiIiIiIhI53ZQSEREREREREZHI2b3ReRL2r4P6jdByEPKLYfAEGFodbYYKqhjBBAopppmD7GUjddRGmsHDOlhnsJ4PPs6CMvihMxnysA7KYD8ffJxHDxm8sD4THvbCeg1A6+Apg/VeWM/3ROdBa9DOwzooQyjK8+D+ptTRw7CtBtYvhQO1p369rAomLYAxcyCvqH8y5FPIVOYwgwWcxamnYSfrWMVS1lBDC839ksHDOlhnsJ4PPs6CMvihMxnysA7KYD8ffJxHDxm8sD4THvbCeg1A6+Apg/VeWM/3ROdBa9DOwzooQ8jqPMSCIIj0j4g2NjZSWlrKgJFw/Z6eH1u/GR6bBYd2EP6iYVsXDzr2+UGj4aqVUDqu5+/Z/i70A8+M713ohzGOhTxJGaMJaCOH3FMe00YrMXI4wA7uZCb72JrSDB7WwTpDf8xPNEN/nAUPGTxcE+1/maGhoYGSkpLeQ/QT634C+/OQaAbrblCG/pufaAYP57G/MnjoqET6CezPpIfzkKnXRbr1k5cM1nuhfjpO5yFz+ynRDB7WwcN59JDB8t/x3L6nVP1mePgiaGpfwK42ptPnm3bBimnQsCV1GYYxjtt4jiGcSYxYlxsDkEMuMWIM4UxuYzXDGJuyDB7WwTqD9XzwcRaUwQ+dyZCHdVAG+/ng4zx6yOCF9ZnwsBfWawBaB08ZrPfCer4nOg9ag3Ye1kEZQtbnIaGbUsuWLWPy5MmUlJRQUlLCxRdfzOOPP56SIJ0dPRzeKWxphKA1vucEreHjfzUzfH5f5VPIQp6kkGJyyY/rObnkU0gxC1lJPoV9zuBhHawzWM8HH2dBGXqnfuqZ+ikzM1jPBx/n0UOG3mRLR3nYC+s1AK2DpwzWe2E9Px7Z0k9gvx9ag5CHdVCGkIfzkNBNqfLycu644w6ef/551q5dy2WXXcbVV1/Nn//85z4H6WxbTfjStXg3pl3QGj5v24N9zzCVOZQxOu6NaZdLPkM5mwuZ3ecMHtbBOoP1fPBxFpShd+qn3qmfMi+D9XzwcR49ZOhNtnSUh72wXgPQOnjKYL0X1vPjkS39BPb7oTUIeVgHZQh5OA8J3ZT64Ac/yJVXXsm4ceMYP348X//61xk0aBDPPfdcn4N0tn5posk6yTn2/D6awQKCbl8717M2WpnBrX3O4GEdrDNYzwcfZ0EZeqd+io/6KbMyWM8HH+fRQ4beZEtHedgL6zUArYOnDNZ7YT0/HtnST2C/H1qDkId1UIaQh/OQ9HtKtba2UlNTQ1NTExdffHGfg7Tbv+7Yu80nty7QBgfWhd8nWRVUcRbV3f4uZW9yyGU0F1BBVdIZPKyDdQbr+eDjLChD4tRP3VM/ZU4G6/ng4zx6yJCoTO0oD3thvQagdfCUwXovrOcnI1P7Cez3Q2sQ8rAOyhDycB7C75Ogl156iUGDBlFQUMAnPvEJVqxYwXnnndft448cOUJjY+MJHz2p35hoom6+z6bknzuCCSnJMJzKpJ/rYR2sM1jPBx9nQRnip36Kn/op/TNYzwcf59FDhngl0lGJ9hPYnwkPe2G9BqB18JTBei+s5yci0/sJ7PdDaxDysA7KEPJwHiCJm1KVlZXU1tayevVqPvnJT3LjjTfy8ssvd/v4JUuWUFpa2vFRUVHR4/dvOZhoom6+T+/d2K1CilOSoYjk/yyrh3WwzmA9H3ycBWWIn/opfuqn9M9gPR98nEcPGeKVSEcl2k9gfyY87IX1GoDWwVMG672wnp+ITO8nsN8PrUHIwzooQ8jDeYAkbkqddtppjB07lgsuuIAlS5YwZcoU7rzzzm4fv2jRIhoaGjo+6urqevz++alZF/L7sC7NpOaEHCb5E+JhHawzWM8HH2dBGeKnfoqf+in9M1jPBx/n0UOGeCXSUYn2E9ifCQ97Yb0GoHXwlMF6L6znJyLT+wns90NrEPKwDsoQ8nAeAPL6GqCtrY0jR450+/WCggIKCgri/n6DU/MKsj59n72k5rV0ffk+HtbBOoP1fPBxFpQheeqn/vk+HtZBGezng4/z6CFDsnrqqET7CezPhIe9sF4D0Dp4ymC9F9bz+yLT+gns90NrEPKwDsoQ8nAeIMFXSi1atIjf/e53bN++nZdeeolFixbx9NNPM3fu3D6F6GxoNZRVJZqskxwoq4ahVclnqKOWnayjjQT/NuMxbbSyg+fZxQtJZ/CwDtYZrOeDj7OgDPFRP8VH/ZQ5Gazng4/z6CFDPLKhozzshfUagNbBUwbrvbCeH69s6Cew3w+tQcjDOihDyMN5gASXYN++fdxwww1UVlZy+eWXs2bNGn79618zc+bMPoU42aQF9Old6Cct6HuGVSwlluQJySGXVXy3zxk8rIN1Buv54OMsKEPv1E/xUT9lVgbr+eDjPHrI0Jts6SgPe2G9BqB18JTBei+s58cjW/oJ7PdDaxDysA7KEPJwHhKafvfdd7N9+3aOHDnCvn37eOqpp1JeVgBj5sCg0RBL8C8TxnLD542Z3fcMa6jhADtopSWh57XSwn62s5YH+5zBwzpYZ7CeDz7OgjL0Tv3UO/VT5mWwng8+zqOHDL3Jlo7ysBfWawBaB08ZrPfCen48sqWfwH4/tAYhD+ugDCEP5yHZF4v1q7wiuPLJ8E274t2gWG74+KtWhs/vqxaauZNZNHMw7g1qpYVmDnInM2mhuc8ZPKyDdQbr+eDjLCiDHzqTIQ/roAz288HHefSQwQvrM+FhL6zXALQOnjJY74X1fE90HrQG7TysgzKEPJwHlzelAAaPh2tWw8DyY5/oLumxzw8sDx9fOi51GfaxhTuYxpvsBuj2dy3bP/8mu7mDaexja8oyeFgH6wzW88HHWVAGP3QmQx7WQRns54OP8+ghgxfWZ8LDXlivAWgdPGWw3gvr+Z7oPGgN2nlYB2UIWZ8HtzelIFzoazfA9HuhbErXjymbEn792g2p3Zh2+9jKYiaynHnUUdvlY+qoZTnzWMzEfvmHh4d1sM5gPR98nAVl8ENnMuRhHZTBfj74OI8eMnhhfSY87IX1GoDWwVMG672wnu+JzoPWoJ2HdVCGkOV5yEvZd+oneUVQOS/82L8O6jdBS2P4krXBleG71ve3Fpp5lvt4lvuooIrhVFJECYdp5DU2dbtpqeRhHawzWM8HH2dBGfzQmQx5WAdlsJ8PPs6jhwxeWJ8JD3thvQagdfCUwXovrOd7ovOgNWjnYR2UIWR1HtzflOpsaHU0m9GTOmrN/4HhYR2sM1jPBx9nQRn80JkMeVgHZbCfDz7Oo4cMXlifCQ97Yb0GoHXwlMF6L6zne6LzoDVo52EdlCEU5Xlw/et7IiIiIiIiIiKSmXRTSkREREREREREIqebUiIiIiIiIiIiErlYEARBlAMbGxspLS2FGAwcFeXk0FuvQtAGsRwYMDL6+cqgDN4yWM8HaNoDBNDQ0EBJSYlNCOz7CXzsh3UG6/nKoAwn89BR6idl8DJfGXxlUD+FPOyFMiiDl/leMsTbT3Y3pURETuLmppSISBdc/EufiEgX1E8i4lVv/WT31/f0SillUAYXGaznw/G76G7ov/Rl/ZlUBmXozFVHqZ+yPoP1fGXwlUH9FPKwF8qgDF7me8kQbz+Z3ZQaMALm7op+7gPl0LQ73BiL+cqgDN4yWM8HuH9UWJxeWPUT+NgP6wzW85VBGU7mqaPUT8pgPV8ZfGVQP4U87IUyKIOX+V4yxNtPeqNzERERERERERGJnG5KiYiIiIiIiIhI5HRTSkREREREREREImf3RudJ2L8O6jdCy0HIL4bBE2BotTJYZKigihFMoJBimjnIXjZSR21k8z2sgYcM4oeH86AMIet+Avt1sJ4v/lifCev5XjKon/xkED88nAfrDNbzQf3kKUO2cX9T6uhh2FYD65fCgdpTv15WBZMWwJg5kFekDP2ZIZ9CpjKHGSzgLE69MneyjlUsZQ01tNCc8vke1sBDBvHDw3lQhpB1P4H9OljPF3+sz4T1fC8Z1E9+MogfHs6DdQbr+aB+8pQhm7n+9b36zfDQRHjmJjjwYtePOfBi+PWHJkLDFmXorwzDGMdiNnAD91DO5C4fU85kbuAeFrOBYYxN6XwPa+Ahg/jh4TwoQ8i6n8B+Hazniz/WZ8J6vpcM6ic/GcQPD+fBOoP1fFA/ecqQ7dzelKrfDA9fBE3tf76wrZsHHvt80y5YMS21h0QZQsMYx208xxDOJEaMHHK7fFwOucSIMYQzuY3VKSsuD2vgIYP44eE8KEPIup/Afh2s54s/1mfCer6XDOonPxnEDw/nwTqD9XxQP3nKIH28KXXHHXcQi8X49Kc/naI4oaOH4bFZ0NIIQWt8zwlaw8f/amb4fGVITYZ8ClnIkxRSTC75cT0nl3wKKWYhK8mnsE/zPayBhwySOPVT5mew7iewXwfr+ZKc/uonsD8T1vO9ZFA/+ckgidPPUP2XwXo+qJ88ZZBQ0jel1qxZww9/+EMmT+76pX59sa0GDu2I/3C0C1rD5217UBlSlWEqcyhjdNyF1S6XfIZyNhcyu0/zPayBhwySGPVTdmSw7iewXwfr+ZK4/uwnsD8T1vO9ZFA/+ckgidHPUP2bwXo+qJ88ZZBQUjelDh06xNy5c7nrrrsYMmRIqjOxfinJ3y7LOfZ8ZUhJhhksIOj2dYw9a6OVGdzap/ke1sBDBomf+il7Mlj3E9ivg/V8SUx/9xPYnwnr+V4yqJ/8ZJD46Weo/s9gPR/UT54ySCipbZg/fz5XXXUV733ve1Odh/3rjr3jfXLXCbTBgXXh91GGvmWooIqzqO72d4x7k0Muo7mACqqSer6HNfCQQRKjfsqODNb9BPbrYD1fEtef/QT2Z8J6vpcM6ic/GSQx+hmqfzNYzwf1k6cMclzCN6Vqamr405/+xJIlS+J6/JEjR2hsbDzhoyf1GxNN1M332dSH5yoDACOYkJIMw6lM6nke1sBDBomf+il7Mlj3E9ivg/V8SUx/9xPYnwnr+V4yqJ/8ZJD4JdJR6dhPHjJYzwf1k6cMclxCN6Xq6upYuHAhDzzwAIWF8b3B2ZIlSygtLe34qKio6PHxLQcTSdTD9+m9G5WhF4UUpyRDESVJPc/DGnjIIPFRP2VXBut+Avt1sJ4v8Yuin8D+TFjP95JB/eQng8Qn0Y5Kx37ykMF6PqifPGWQ4xK6KfX888+zb98+zj//fPLy8sjLy+OZZ55h6dKl5OXl0dp66ruELVq0iIaGho6Purq6Hmfkp+Y6IT/560QZjmkmNVfrYZK7Wj2sgYcMEh/1U3ZlsO4nsF8H6/kSvyj6CezPhPV8LxnUT34ySHwS7ah07CcPGazng/rJUwY5Li+RB19++eW89NJLJ3zuox/9KBMmTODzn/88ubmn/m5qQUEBBQUFcc8YnJpXFPbp+yhDaC+peV1jst/Hwxp4yCDxUT9lVwbrfgL7dbCeL/GLop/A/kxYz/eSQf3kJ4PEJ9GOSsd+8pDBej6onzxlkOMSuilVXFzMpEmTTvjcwIEDKSsrO+XzyRpaDWVVcOBFknvjsRwomwJDq5ShrxnqqGUn6yhnclJvhtdGK3XUsosXkprvYQ08ZJD4qJ+yK4N1P4H9OljPl/hF0U9gfyas53vJoH7yk0Hio5+hoslgPR/UT54yyHHJ/hHEfjVpAX16J/xJC5QhVRlWsZRYksckh1xW8d0+zfewBh4yiB8ezoMyhKz7CezXwXq++GN9Jqzne8mgfvKTQfzwcB6sM1jPB/WTpwwS6vNNqaeffprvfOc7KYhy3Jg5MGg0xBK8eRvLDZ83ZrYypCrDGmo4wA5aaUnoea20sJ/trOXBPs33sAYeMkhy1E+ZncG6n8B+HaznS/L6o5/A/kxYz/eSQf3kJ4MkRz9D9U8G6/mgfvKUQUIuXymVVwRXPhm+cVi8hySWGz7+qpXh85UhNRlaaOZOZtHMwbiLq5UWmjnIncykheY+zfewBh4yiB8ezoMyhKz7CezXwXq++GN9Jqzne8mgfvKTQfzwcB6sM1jPB/WTpwwScnlTCmDweLhmNQwsP/aJ7pIe+/zA8vDxpeOUIdUZ9rGFO5jGm+wGwt8l7kr7599kN3cwjX1sTcl8D2vgIYP44eE8KEPIup/Afh2s54s/1mfCer6XDOonPxnEDw/nwTqD9XxQP3nKII5vSkG42ddugOn3hm8k1pWyKeHXr93QP4dDGUL72MpiJrKcedRR2+Vj6qhlOfNYzMSUFhb4WAMPGcQPD+dBGULW/QT262A9X/yxPhPW871kUD/5ySB+eDgP1hms54P6yVOGbJfQX9+zkFcElfPCj/3roH4TtDSGL5sbXBm+c74yRJOhhWae5T6e5T4qqGI4lRRRwmEaeY1N3ZZZqnhYAw8ZxA8P50EZQtb9BPbrYD1f/LE+E9bzvWRQP/nJIH54OA/WGazng/rJU4Zs5v6mVGdDq+0PhDKE6qiNpKS642ENPGQQPzycB2UIWfcT2K+D9Xzxx/pMWM/3kkH95CeD+OHhPFhnsJ4P6idPGbKN61/fExERERERERGRzKSbUiIiIiIiIiIiEjndlBIRERERERERkcjFgiAIohzY2NhIaWkpxGDgqCgnh956FYI2iOXAgJHRz1cGZfCWwXo+QNMeIICGhgZKSkpsQmDfT+BjP6wzWM9XBmU4mYeOUj8pg5f5yuArg/op5GEvlEEZvMz3kiHefrK7KSUichI3N6VERLrg4l/6RES6oH4SEa966ye7v76nV0opgzK4yGA9H47fRXdD/6Uv68+kMihDZ646Sv2U9Rms5yuDrwzqp5CHvVAGZfAy30uGePvJ7KbUgBEwd1f0cx8oh6bd4cZYzFcGZfCWwXo+wP2jwuL0wqqfwMd+WGewnq8MynAyTx2lflIG6/nK4CuD+inkYS+UQRm8zPeSId5+0hudi4iIiIiIiIhI5HRTSkREREREREREIqebUiIiIiIiIiIiEjm7NzpPwv51UL8RWg5CfjEMngBDq7MvQwVVjGAChRTTzEH2spE6arMqg4d9UAbpzMNeeMhg3Q1eMljvhfV8LxnkOOv9sJ4PPrrBQwYPe6EM0pmHvbDO4KEbPGSw3gdlsOH+ptTRw7CtBtYvhQO1p369rAomLYAxcyCvKHMz5FPIVOYwgwWcxakncifrWMVS1lBDC80ZmcHDPiiDdOZhLzxksO4GLxms98J6vpcMcpz1fljPBx/d4CGDh71QBunMw15YZ/DQDR4yWO+DMthz/et79ZvhoYnwzE1w4MWuH3PgxfDrD02Ehi2ZmWEY41jMBm7gHsqZ3OVjypnMDdzDYjYwjLEZl8HDPiiDdOZhLzxksO4GLxms98J6vpcMcpz1fljPBx/d4CGDh71QBunMw15YZ/DQDR4yWO+DMvjg9qZU/WZ4+CJoav/zhW3dPPDY55t2wYppqd0gDxmGMY7beI4hnEmMGDnkdvm4HHKJEWMIZ3Ibq1NaGtYZPOyDMkhnHvbCQwbrbvCSwXovrOd7ySDHWe+H9Xzw0Q0eMnjYC2WQzjzshXUGD93gIYP1PiiDHy5vSh09DI/NgpZGCFrje07QGj7+VzPD52dChnwKWciTFFJMLvlxPSeXfAopZiEryacw7TN42AdlkM487IWHDNbd4CWD9V5Yz/eSQY6z3g/r+eCjGzxk8LAXyiCdedgL6wweusFDBut9UAZfEroptXjxYmKx2AkfEyZMSHmobTVwaEf8G9MuaA2ft+3BzMgwlTmUMTrusmiXSz5DOZsLmZ32GTzsgzKkB/VTtBmsu8FLBuu9sJ7vJUM6yJaOsp4PPrrBQwYPe6EM6SFb+slDBg/d4CGD9T4ogy8Jv1LqHe94B6+++mrHx+9///uUh1q/NJlkx+Qce34GZJjBAoJuX7/XszZamcGtaZ/Bwz4oQ/pQP0WXwbobvGSw3gvr+V4ypIts6Cjr+eCjGzxk8LAXypA+sqGfPGTw0A0eMljvgzL4kvAS5OXlMWLEiI6PoUOHpjTQ/nXH3m0+uesE2uDAuvD7pHOGCqo4i+puf7+3NznkMpoLqKAqbTN42AdlSC/qp2gyWHeDlwzWe2E930uGdJLpHWU9H3x0g4cMHvZCGdJLpveThwweusFDBut9UAZ/Er4ptWXLFkaNGsW5557L3Llz2blzZ4+PP3LkCI2NjSd89KR+Y6KJuvk+m/rwXAcZRpCal8wOpzJtM3jYB2VIL+qnaDJYd4OXDNZ7YT3fS4Z0kkhHJdpPYL8f1vPBRzd4yOBhL5QhvWR6P3nI4KEbPGSw3gdl8Cehm1LTpk1j+fLlPPHEEyxbtoxXXnmFv/zLv+TgwYPdPmfJkiWUlpZ2fFRUVPQ4o6X7b5WQlt670XWGQopTkqGIkrTN4GEflCF9qJ+iy2DdDV4yWO+F9XwvGdJFoh2VaD+B/X5Yzwcf3eAhg4e9UIb0kQ395CGDh27wkMF6H5TBn4RuSl1xxRV85CMfYfLkybzvfe/jscceo76+noceeqjb5yxatIiGhoaOj7q6uh5n5KfmOiE/+evERYZmUnNKD5P8KbXO4GEflCF9qJ+iy2DdDV4yWO+F9XwvGdJFoh2VaD+B/X5Yzwcf3eAhg4e9UIb0kQ395CGDh27wkMF6H5TBn7y+PHnw4MGMHz+erVu3dvuYgoICCgoK4v+eKfpDD335Ph4y7CU1r+fry/exzuBhH5Qhfamf+u/7WHeDlwzWe2E930uGdNVbRyXaT2C/H9bzwUc3eMjgYS+UIX1lYj95yOChGzxksN4HZfAn2fd6B+DQoUNs27aNkSNHpioPQ6uhrIo+vQt9WTUMrUrvDHXUspN1tJHg34c8po1WdvA8u3ghbTN42AdlSF/qp/7LYN0NXjJY74X1fC8Z0lUmdpT1fPDRDR4yeNgLZUhfmdhPHjJ46AYPGaz3QRn8SWgJPve5z/HMM8+wfft2/vCHP3DNNdeQm5vLddddl9JQkxbQp3ehn7QgMzKsYimxJE9pDrms4rtpn8HDPihDelA/RZvBuhu8ZLDeC+v5XjKkg2zpKOv54KMbPGTwsBfKkB6ypZ88ZPDQDR4yWO+DMviS0GnctWsX1113HZWVlVx77bWUlZXx3HPPccYZZ6Q01Jg5MGg0xBL8S5Wx3PB5Y2ZnRoY11HCAHbTSktDzWmlhP9tZy4Npn8HDPihDelA/RZvBuhu8ZLDeC+v5XjKkg2zpKOv54KMbPGTwsBfKkB6ypZ88ZPDQDR4yWO+DMviS0E2pmpoa9uzZw5EjR9i1axc1NTWMGTMm5aHyiuDKJ8M37Yp3g2K54eOvWhk+PxMytNDMncyimYNxl0YrLTRzkDuZSQvNaZ/Bwz4oQ3pQP0WbwbobvGSw3gvr+V4ypINs6Sjr+eCjGzxk8LAXypAesqWfPGTw0A0eMljvgzL40qf3lOpPg8fDNathYPmxT3SX9NjnB5aHjy8dl1kZ9rGFO5jGm+wG6Pb3f9s//ya7uYNp7KP7N3dOtwwe9kEZpDMPe+Ehg3U3eMlgvRfW871kkOOs98N6PvjoBg8ZPOyFMkhnHvbCOoOHbvCQwXoflMEPtzelIFzoazfA9HuhbErXjymbEn792g39szEeMuxjK4uZyHLmUUdtl4+po5blzGMxE1NaFl4yeNgHZZDOPOyFhwzW3eAlg/VeWM/3kkGOs94P6/ngoxs8ZPCwF8ognXnYC+sMHrrBQwbrfVAGH/KsA/Qmrwgq54Uf+9dB/SZoaQxfsja4MnzX+mzI0EIzz3Ifz3IfFVQxnEqKKOEwjbzGpm6LJJMyeNgHZZDOPOyFhwzW3eAlg/VeWM/3kkGOs94P6/ngoxs8ZPCwF8ognXnYC+sMHrrBQwbrfVAGe+5vSnU2tNp+MzxkqKM2koLwnMHDPiiDdOZhLzxksO4GLxms98J6vpcMcpz1fljPBx/d4CGDh71QBunMw15YZ/DQDR4yWO+DMthw/et7IiIiIiIiIiKSmXRTSkREREREREREIqebUiIiIiIiIiIiErlYEARBlAMbGxspLS2FGAwcFeXk0FuvQtAGsRwYMDL6+cqgDN4yWM8HaNoDBNDQ0EBJSYlNCOz7CXzsh3UG6/nKoAwn89BR6idl8DJfGXxlUD+FPOyFMiiDl/leMsTbT3Y3pURETuLmppSISBdc/EufiEgX1E8i4lVv/WT31/f0SillUAYXGaznw/G76G7ov/Rl/ZlUBmXozFVHqZ+yPoP1fGXwlUH9FPKwF8qgDF7me8kQbz+Z3ZQaMALm7op+7gPl0LQ73BiL+cqgDN4yWM8HuH9UWJxeWPUT+NgP6wzW85VBGU7mqaPUT8pgPV8ZfGVQP4U87IUyKIOX+V4yxNtPeqNzERERERERERGJnG5KiYiIiIiIiIhI5HRTSkREREREREREImf3RudJ2L8O6jdCy0HIL4bBE2BodfZlqKCKEUygkGKaOcheNlJHbVZl8LAPHjKIHx7Og4cM1t3gJYP1XljPF3+sz4T1fPDRDR4yeNgLDxnEDw/nwTqDh27wkMF6H7xkyDbub0odPQzbamD9UjhQe+rXy6pg0gIYMwfyijI3Qz6FTGUOM1jAWZx6VexkHatYyhpqaKE5IzN42AcPGcQPD+fBQwbrbvCSwXovrOeLP9Znwno++OgGDxk87IWHDOKHh/NgncFDN3jIYL0PXjJkM9e/vle/GR6aCM/cBAde7PoxB14Mv/7QRGjYkpkZhjGOxWzgBu6hnMldPqacydzAPSxmA8MYm3EZPOyDhwzih4fz4CGDdTd4yWC9F9bzxR/rM2E9H3x0g4cMHvbCQwbxw8N5sM7goRs8ZLDeBy8Zsp3bm1L1m+Hhi6Cp/c8XtnXzwGOfb9oFK6al9pB4yDCMcdzGcwzhTGLEyCG3y8flkEuMGEM4k9tYndLSsM7gYR88ZBA/PJwHDxmsu8FLBuu9sJ4v/lifCev54KMbPGTwsBceMogfHs6DdQYP3eAhg/U+eMkgTm9KHT0Mj82ClkYIWuN7TtAaPv5XM8PnZ0KGfApZyJMUUkwu+XE9J5d8CilmISvJpzDtM3jYBw8ZxA8P58FDButu8JLBei+s54s/1mfCej746AYPGTzshYcM4oeH82CdwUM3eMhgvQ9eMkgo4ZtSu3fv5vrrr6esrIyioiLe+c53snbt2pSG2lYDh3bEfzjaBa3h87Y9mBkZpjKHMkbHXRbtcslnKGdzIbPTPoOHffCQQeKjfooug3U3eMlgvRfW8yUx2dBR1vPBRzd4yOBhLzxkkPhkQz95yOChGzxksN4HLxkklNBNqTfffJNLLrmE/Px8Hn/8cV5++WW++c1vMmTIkJSGWr800WSd5Bx7fgZkmMECgm5fQ9izNlqZwa1pn8HDPnjIIL1TP0WbwbobvGSw3gvr+RK/bOko6/ngoxs8ZPCwFx4ySO+ypZ88ZPj/2bvz+Kjqe//jr8lCEiAJGnYIUVkC1kKoCy5tMSoooJf6aFUqVrlaW1sUq78u0va2VKvQ2kVxobcWAesC3F5tue6oqG1FRJugVhahAmGTgpCwBUNyfn8cErJnJpk538/MvJ+PRx73djgzn7ff8z1vw3EysdANFjK4Pg9WMogvot++94tf/IL8/HzmzZtX99iJJ54Y1UC7Spr/xPuw1cDuEv912vurGy1kyKeo2d+AEK4UUingVPIpavev8nSdwcJ5sJBBwqN+Ci6D626wksH1uXA9XyKTDB3lej7Y6AYLGSycCwsZJDzJ0E8WMljoBgsZXJ8HKxnkmIjuDS5ZsoTTTjuNyy67jJ49ezJy5EgeeuihVp9z+PBhKioqGny1Zu+aSBK18jprO/BcAxl6MzQqGXpRGLcZLJwHCxkkPOqn4DK47gYrGVyfC9fzJTKRdlSk/QTu94Tr+WCjGyxksHAuLGSQ8CRDP1nIYKEbLGRwfR6sZJBjIrop9a9//Ys5c+YwePBgXnjhBb71rW8xbdo0FixY0OJzZs6cSW5ubt1Xfn5+qzOq9kWSqJXXabsbTWfIJDsqGbLIidsMFs6DhQwSHvVTcBlcd4OVDK7Phev5EplIOyrSfgL3e8L1fLDRDRYyWDgXFjJIeJKhnyxksNANFjK4Pg9WMsgxEd2Uqqmp4XOf+xx33XUXI0eO5Bvf+AbXX389v/vd71p8zvTp0ykvL6/7Kisra3VGenSuE9Lbf52YyFBJdK6UQ7T/SnGdwcJ5sJBBwqN+Ci6D626wksH1uXA9XyITaUdF2k/gfk+4ng82usFCBgvnwkIGCU8y9JOFDBa6wUIG1+fBSgY5JqKbUn369OHkk09u8NiwYcPYvHlzi8/JyMggJyenwVdrukXnHYUdeh0LGXYQnfcUduR1XGewcB4sZJDwqJ+Cex3X3WAlg+tz4Xq+RCbSjoq0n8D9nnA9H2x0g4UMFs6FhQwSnmToJwsZLHSDhQyuz4OVDHJMRDelzjnnHNaubfiDk+vWraOgoCBqgbqPhLyiSJPVkwJ5I6F7UXxnKKOUzZRQQ4S/o/KoGqrZxDtsYVXcZrBwHixkkPCon4LL4LobrGRwfS5cz5fIJENHuZ4PNrrBQgYL58JCBglPMvSThQwWusFCBtfnwUoGOSai03DLLbfw5ptvctddd7F+/Xoef/xxfv/73zN16tSohjplGrTzt1RCzdHnJ0CGZcwm1M4rJYVUlnFf3GewcB4sZJC2qZ+CzeC6G6xkcH0uXM+X8CVLR7meDza6wUIGC+fCQgZpW7L0k4UMFrrBQgbX58FKBvFFtBtPP/10nnrqKZ544glOOeUU7rjjDu655x4mT54c1VADJ0HXAgilRva8UKr/vIFXJEaGlSxkN5uopiqi51VTxS428jaL4j6DhfNgIYO0Tf0UbAbX3WAlg+tz4Xq+hC9ZOsr1fLDRDRYyWDgXFjJI25KlnyxksNANFjK4Pg9WMogv4lukF198Me+99x6VlZWsXr2a66+/Puqh0rJg/Iv+B4eFu0lCqf7xE5b6z0+EDFVUci9jqWRf2KVRTRWV7ONexlBFZdxnsHAeLGSQ8KifgsvguhusZHB9LlzPl8gkQ0e5ng82usFCBgvnwkIGCU8y9JOFDBa6wUIG1+fBSgbxtfenKGOu2xC4dAV06X/0gZaSHn28S3//+NzBiZVhJx8yi1HsYStAiz//W/v4HrYyi1HsZH3CZLBwHixkEDss7AcLGVx3g5UMrs+F6/lij+s94Xo+2OgGCxksnAsLGcQOC/vBdQYL3WAhg+vzYCWDGL4pBf7Jvnw1jJ4HeSOaPyZvhP/nl6+OzeawkGEn65nBMOYzhTJKmz2mjFLmM4UZDItqWVjJYOE8WMggdljYDxYyuO4GKxlcnwvX88Ue13vC9Xyw0Q0WMlg4FxYyiB0W9oPrDBa6wUIG1+fBSoZkl+Y6QFvSsqBwiv+1qwT2roWqCv9tc90K/U/OT4YMVVSynAUsZwH5FNGLQrLI4RAVfMzaFoskkTJYOA8WMogdFvaDhQyuu8FKBtfnwvV8scf1nnA9H2x0g4UMFs6FhQxih4X94DqDhW6wkMH1ebCSIZmZvylVX/eR7jeEhQxllAZSEJYzWDgPFjKIHRb2g4UMrrvBSgbX58L1fLHH9Z5wPR9sdIOFDBbOhYUMYoeF/eA6g4VusJDB9XmwkiHZmP7xPRERERERERERSUy6KSUiIiIiIiIiIoHTTSkREREREREREQlcyPM8L8iBFRUV5ObmQgi69A1ysu/gdvBqIJQCnfsEP18ZlMFaBtfzAQ5sAzwoLy8nJyfHTQjc9xPYOB+uM7ierwzK0JiFjlI/KYOV+cpgK4P6yWfhXCiDMliZbyVDuP3k7qaUiEgjZm5KiYg0w8Rf+kREmqF+EhGr2uond799T++UUgZlMJHB9Xw4dhfdDP2XvqTfk8qgDPWZ6ij1U9JncD1fGWxlUD/5LJwLZVAGK/OtZAi3n5zdlOrcGyZvCX7uY/3hwFb/xLiYrwzKYC2D6/kAj/b1i9MKV/0ENs6H6wyu5yuDMjRmqaPUT8rger4y2MqgfvJZOBfKoAxW5lvJEG4/6YPORUREREREREQkcLopJSIiIiIiIiIigdNNKRERERERERERCZy7Dzpvh10lsHcNVO2D9GzoNhS6j0y+DPkU0ZuhZJJNJfvYwRrKKA00g+t1cD1fpDELe9JCBvWTnQwi9bnek67ng/rJUgaR+izsSdcZ1E92MkjwzN+UOnIINiyE92fD7tKmf55XBKdMg4GTIC0rcTOkk8npTKKYaQyg6ZW5mRKWMZuVLKSKyphkcL0OrueLNGZhT1rIoH6yk0GkPtd70vV8UD9ZyiBSn4U96TqD+slOBnHL9I/v7V0Hi4fBa9fC7nebP2b3u/6fLx4G5R8mZoaeDGYGq7mah+nP8GaP6c9wruZhZrCangyKegbX6+B6vkhjFvakhQzqJzsZROpzvSddzwf1k6UMIvVZ2JOuM6if7GQQ98zelNq7Dv58Jhyo/fWFNS0cePTxA1vgqVHR3agWMvRkMLfxJsfRjxAhUkht9rgUUgkR4jj6cRsrolpcrtfB9XyRxizsSQsZ1E92MojU53pPup4P6idLGUTqs7AnXWdQP9nJIDaYvCl15BA8OxaqKsCrDu85XrV//DNj/OcnQoZ0MrmZF8kkm1TSw3pOKulkks3NLCWdzA5ncL0OrueLNGZhT1rIoH6yk0GkPtd70vV8UD9ZyiBSn4U96TqD+slOBrEjoptSJ5xwAqFQqMnX1KlToxpqw0LYvyn8DVrLq/aft2FRYmQ4nUnkURB2YdVKJZ3unMBpXNHhDK7XwfV8iS9BdJSFPWkhg/rJTgaJD8nyPZTr+aB+spRB4kOy9JOFDOonOxnEjohuSq1cuZLt27fXfS1duhSAyy67LKqh3p8dabJ6Uo4+PwEyFDMNr8X3MbauhmqKuanDGVyvg+v5El+C6CgLe9JCBvWTnQwSH5LleyjX80H9ZCmDxIdk6ScLGdRPdjKIHRFthR49etC7d++6r6effpqBAwcyevToqAXaVXL0U/fbd61CDewu8V8nnjPkU8QARrb4M8ZtSSGVAk4ln6J2Z3C9Dq7nS/yJdUdZ2JMWMqif7GSQ+JEM30O5ng/qJ0sZJH4kQz9ZyKB+spNBbGn3Z0p9+umnPProo1x77bWEQqEWjzt8+DAVFRUNvlqzd017EzV6nbUdeK6BDL0ZGpUMvShs93Ndr4Pr+RLfwuko9VP7qJ/sZJD4FIt+Avd70vV8UD9ZyiDxKVH7yUIG9ZOdDGJLu29K/fnPf2bv3r1MmTKl1eNmzpxJbm5u3Vd+fn6rx1fta2+iRq/TdjeazpBJdlQyZJHT7ue6XgfX8yW+hdNR6qf2UT/ZySDxKRb9BO73pOv5oH6ylEHiU6L2k4UM6ic7GcSWdt+Umjt3LuPGjaNv376tHjd9+nTKy8vrvsrKylo9Pj061yrp7b9WTWSoJDpX6yHaf7W6XgfX8yW+hdNR6qf2UT/ZySDxKRb9BO73pOv5oH6ylEHiU6L2k4UM6ic7GcSWtPY8adOmTbz00ks8+eSTbR6bkZFBRkZG2K/dLTrvauzQ61jIsIPovK+xI6/jeh1cz5f4FW5HqZ/aR/1kJ4PEn1j1E7jfk67ng/rJUgaJP4ncTxYyqJ/sZBBb2vVOqXnz5tGzZ08mTJgQ7Tx0Hwl5RXTo0/jzRkL3ovjOUEYpmymhhgh/T+ZRNVSziXfYwqp2Z3C9Dq7nS/yKVUdZ2JMWMqif7GSQ+JPI30O5ng/qJ0sZJP4kcj9ZyKB+spNBbIl4K9TU1DBv3jyuueYa0tLa9UarNp0yjQ59Gv8p0xIjwzJmE2rn1ZpCKsu4r8MZXK+D6/kSf2LdURb2pIUM6ic7GSR+JMP3UK7ng/rJUgaJH8nQTxYyqJ/sZBA7Ir4iXnrpJTZv3sy1114bizwADJwEXQsgFOFvywyl+s8beEViZFjJQnaziWqqInpeNVXsYiNvs6jDGVyvg+v5En9i3VEW9qSFDOonOxkkfiTD91Cu54P6yVIGiR/J0E8WMqif7GQQOyK+KTV27Fg8z2PIkCGxyANAWhaMf9H/8LJwN2oo1T9+wlL/+YmQoYpK7mUslewLu7iqqaKSfdzLGKqo7HAG1+vger7En1h3lIU9aSGD+slOBokfyfA9lOv5oH6ylEHiRzL0k4UM6ic7GcSOdv/2vVjrNgQuXQFd+h99oKWkRx/v0t8/PndwYmXYyYfMYhR72ArQ4s8g1z6+h63MYhQ7WR+1DK7XwfV8kcYs7EkLGdRPdjKI1Od6T7qeD+onSxlE6rOwJ11nUD/ZySA2mL0pBf6Gu3w1jJ4HeSOaPyZvhP/nl6+OzQa1kGEn65nBMOYzhTJKmz2mjFLmM4UZDItqYdVyvQ6u54s0ZmFPWsigfrKTQaQ+13vS9XxQP1nKIFKfhT3pOoP6yU4GcS82n2IXRWlZUDjF/9pVAnvXQlWF/9a9boX+p/cnQ4YqKlnOApazgHyK6EUhWeRwiAo+Zm2LZRZNrtfB9XyRxizsSQsZ1E92MojU53pPup4P6idLGUTqs7AnXWdQP9nJIG6ZvylVX/eR7jelhQxllAZSUq1xvQ6u54s0ZmFPWsigfrKTQaQ+13vS9XxQP1nKIFKfhT3pOoP6yU4GCZ7pH98TEREREREREZHEpJtSIiIiIiIiIiISON2UEhERERERERGRwIU8z/OCHFhRUUFubi6EoEvfICf7Dm4HrwZCKdC5T/DzlUEZrGVwPR/gwDbAg/LycnJyctyEwH0/gY3z4TqD6/nKoAyNWego9ZMyWJmvDLYyqJ98Fs6FMiiDlflWMoTbT+5uSomINGLmppSISDNM/KVPRKQZ6icRsaqtfnL32/f0TillUAYTGVzPh2N30c3Qf+lL+j2pDMpQn6mOUj8lfQbX85XBVgb1k8/CuVAGZbAy30qGcPvJ2U2pzr1h8pbg5z7WHw5s9U+Mi/nKoAzWMrieD/BoX784rXDVT2DjfLjO4Hq+MihDY5Y6Sv2kDK7nK4OtDOonn4VzoQzKYGW+lQzh9pM+6FxERERERERERAKnm1IiIiIiIiIiIhI43ZQSEREREREREZHAufug83bYVQJ710DVPkjPhm5DofvI5MuQTxG9GUom2VSyjx2soYzSQDNYWAcRSyxcExYyqJ9EbHJ9XbieD+onEassXBeuM6ifJJmZvyl15BBsWAjvz4bdpU3/PK8ITpkGAydBWlbiZkgnk9OZRDHTGEDTdthMCcuYzUoWUkVlTDJYWAcRSyxcExYyqJ9EbHJ9XbieD+onEassXBeuM6ifRHymf3xv7zpYPAxeuxZ2v9v8Mbvf9f988TAo/zAxM/RkMDNYzdU8TH+GN3tMf4ZzNQ8zg9X0ZFDUM1hYBxFLLFwTFjKon0Rscn1duJ4P6icRqyxcF64zqJ9EjjF7U2rvOvjzmXCg9tcX1rRw4NHHD2yBp0ZF92KxkKEng7mNNzmOfoQIkUJqs8elkEqIEMfRj9tYEdXisrAOIpZYuCYsZFA/idjk+rpwPR/UTyJWWbguXGdQP4k0ZPKm1JFD8OxYqKoArzq853jV/vHPjPGfnwgZ0snkZl4kk2xSSQ/rOamkk0k2N7OUdDI7nMHCOohYYuGasJBB/SRik+vrwvV8UD+JWGXhunCdQf0k0lREN6Wqq6v5r//6L0488USysrIYOHAgd9xxB57nRTXUhoWwf1P4F0ktr9p/3oZFiZHhdCaRR0HYhVUrlXS6cwKncUWHM1hYB5FwqJ+CzaB+EolMsnSU6/mgfhKJVLL0k4UM6ieRpiK6KfWLX/yCOXPmcP/997N69Wp+8Ytf8Mtf/pL77rsvqqHenx1psnpSjj4/ATIUMw2vxfdStq6Gaoq5qcMZLKyDSDjUT8FmUD+JRCZZOsr1fFA/iUQqWfrJQgb1k0hTEW3HN954g4kTJzJhwgROOOEEvvKVrzB27FjeeuutqAXaVXL0k//bd61CDewu8V8nnjPkU8QARrb4M8ZtSSGVAk4ln6J2Z7CwDiLhUj8Fl0H9JBK5ZOgo1/NB/STSHsnQTxYyqJ9EmhfRTamzzz6bl19+mXXr1gGwatUq/va3vzFu3LgWn3P48GEqKioafLVm75pIErXyOms78FwDGXozNCoZelHY7udaWAeRcKmfgsugfhKJXKQdFWk/gfvrwvV8UD+JtEcy9JOFDOonkealRXLwbbfdRkVFBUOHDiU1NZXq6mruvPNOJk+e3OJzZs6cyc9+9rOwZ1TtiyRRK6/TdjeazpBJdlQyZJHT7udaWAeRcKmfgsugfhKJXKQdFWk/gfvrwvV8UD+JtEcy9JOFDOonkeZF9E6pxYsX89hjj/H444/zj3/8gwULFvCrX/2KBQsWtPic6dOnU15eXvdVVlbW6oz06FyrpLf/WjWRoZLoNMYh2t8YFtZBJFzqp+AyqJ9EIhdpR0XaT+D+unA9H9RPIu2RDP1kIYP6SaR5Eb1T6nvf+x633XYbkyZNAuCzn/0smzZtYubMmVxzzTXNPicjI4OMjIywZ3SLzrsaO/Q6FjLsIDrvrezI61hYB5FwqZ+Cex31k0jkIu2oSPsJ3F8XrueD+kmkPZKhnyxkUD+JNC+id0odPHiQlJSGT0lNTaWmpr2flNZU95GQVxRpsnpSIG8kdC+K7wxllLKZEmqI8Hd1HlVDNZt4hy2sancGC+sgEi71U3AZ1E8ikUuGjnI9H9RPIu2RDP1kIYP6SaR5EW3HSy65hDvvvJNnnnmGjRs38tRTT/Gb3/yGSy+9NKqhTplGh34jwCnTEiPDMmYTamdjpJDKMjr+a1wtrINIONRPwWZQP4lEJlk6yvV8UD+JRCpZ+slCBvWTSFMRXRH33XcfX/nKV/j2t7/NsGHD+O53v8s3v/lN7rjjjqiGGjgJuhZAKMLflhlK9Z838IrEyLCShexmE9VURfS8aqrYxUbeZlGHM1hYB5FwqJ+CzaB+EolMsnSU6/mgfhKJVLL0k4UM6ieRpiK6KZWdnc0999zDpk2bOHToEBs2bODnP/85nTp1imqotCwY/6L/AWrhXiyhVP/4CUv95ydChioquZexVLIv7OKqpopK9nEvY6iissMZLKyDSDjUT8FmUD+JRCZZOsr1fFA/iUQqWfrJQgb1k0hT7f1p0pjrNgQuXQFd+h99oKWkRx/v0t8/PndwYmXYyYfMYhR72ArQ4s8g1z6+h63MYhQ7WR+1DBbWQcQSC9eEhQzqJxGbXF8XrueD+knEKgvXhesM6ieRhszelAJ/01++GkbPg7wRzR+TN8L/88tXx+YisZBhJ+uZwTDmM4UySps9poxS5jOFGQyLamHVsrAOIpZYuCYsZFA/idjk+rpwPR/UTyJWWbguXGdQP4kck+Y6QFvSsqBwiv+1qwT2roWqCv/tg90K/d8gkAwZqqhkOQtYzgLyKaIXhWSRwyEq+Ji1LZZZNFlYBxFLLFwTFjKon0Rscn1duJ4P6icRqyxcF64zqJ9EfOZvStXXfaT7C8NChjJKAymp1lhYBxFLLFwTFjKon0Rscn1duJ4P6icRqyxcF64zqJ8kmZn+8T0REREREREREUlMuiklIiIiIiIiIiKB000pEREREREREREJXMjzPC/IgeXl5XTr1g2Azn2CnOw7uAPwgBB07h38fGVQBmsZXM8HOLjd/7979+4lNzfXTQjc9xMYOR/ak8qgDA0zGOgo9ZMyWJmvDMYyqJ8AI+dCGZTByHwzGcLsp8BvSm3ZsoX8/PwgR4pInCgrK6N///7O5qufRKQ1LjtK/SQirVE/iYhVbfVT4Delampq2LZtG9nZ2YRCoYifX1FRQX5+PmVlZeTk5MQgoTLESwbX85Uhehk8z2Pfvn307duXlBR3P1WsflKGRMrgen4iZbDQUR3tJ3B/PlzPVwZlsJZB/XSM63NhIYPr+cqgDNHOEG4/pXUkZHukpKRE5S5+Tk6Os5OjDLYyuJ6vDNHJ4PLH9mqpn5QhETO4np8oGVx3VLT6CdyfD9fzlUEZrGVQPx3j+lxYyOB6vjIoQzQzhNNP+qBzEREREREREREJnG5KiYiIiIiIiIhI4OLuplRGRgY//elPycjIUIYkz+B6vjLYymCBhXVQBmWwMl8Z7HG9Fq7nK4MyWMvger4lFtbCdQbX85VBGVxlCPyDzkVEREREREREROLunVIiIiIiIiIiIhL/dFNKREREREREREQCp5tSIiIiIiIiIiISON2UEhERERERERGRwMXVTanly5eTmprKhAkTAp89ZcoUQqFQ3VdeXh4XXXQR7777buBZduzYwU033cRJJ51ERkYG+fn5XHLJJbz88ssxn11/HdLT0+nVqxdjxozh4YcfpqamJubzG2eo/3XRRRcFMr+tHOvXrw9k/o4dO7j55psZNGgQmZmZ9OrVi3POOYc5c+Zw8ODBmM+fMmUKX/rSl5o8/uqrrxIKhdi7d2/MM1ijjlI/Nc7hqqNc9xO47Sj1U1PqJ/VT4xzqJ30PZYX6Sf3UOIf6Kbn6Ka5uSs2dO5ebbrqJ119/nW3btgU+/6KLLmL79u1s376dl19+mbS0NC6++OJAM2zcuJFTTz2VV155hbvvvpv33nuP559/nuLiYqZOnRpIhtp12LhxI8899xzFxcXcfPPNXHzxxRw5ciTQDPW/nnjiiUBmt5XjxBNPjPncf/3rX4wcOZIXX3yRu+66i5KSEpYvX873v/99nn76aV566aWYZ5Cmkr2j1E9Nc7jsKFf9BOooi9RP6qfGOdRP6icr1E/qp8Y51E/J1U9prgOEa//+/SxatIi3336bHTt2MH/+fH74wx8GmiEjI4PevXsD0Lt3b2677Ta+8IUv8O9//5sePXoEkuHb3/42oVCIt956iy5dutQ9/pnPfIZrr702kAz116Ffv3587nOf48wzz+T8889n/vz5fP3rXw80g0uucnz7298mLS2Nt99+u8E+OOmkk5g4cSKe5wWeKdmpo9RPLeVwxWUGdZQt6if1U0s5XFE/SS31k/qppRyuqJ+CFzfvlFq8eDFDhw6lsLCQq666iocfftjpSdm/fz+PPvoogwYNIi8vL5CZn3zyCc8//zxTp05tsElrdevWLZAczTnvvPMYMWIETz75pLMMyWL37t28+OKLLe4DgFAoFHAqSfaOUj9JLXWUPeon9ZP41E/2qJ/UT+JL5n6Km5tSc+fO5aqrrgL8t9SVl5fz2muvBZrh6aefpmvXrnTt2pXs7GyWLFnCokWLSEkJZhnXr1+P53kMHTo0kHmRGjp0KBs3bgxkVv1zUft11113BTK7tRyXXXZZzGfW7oPCwsIGj3fv3r0uxw9+8IOY54Dmz8O4ceMCmW1NsneU+qkhCx3lop/ATkepn45RP6mf6lM/ue8nUEfVUj+pn+pTPyVnP8XFj++tXbuWt956i6eeegqAtLQ0rrjiCubOncu5554bWI7i4mLmzJkDwJ49e3jwwQcZN24cb731FgUFBTGfb/3tep7nBXb3tv65qHX88ccHMru1HC3d1Q7CW2+9RU1NDZMnT+bw4cOBzGzuPKxYsaLum4tkoY5SPzVmoaMs9RME31HqJ5/6Sf3UmPqpKX0P5Yb6Sf3UmPqpqWTop7i4KTV37lyOHDlC37596x7zPI+MjAzuv/9+cnNzA8nRpUsXBg0aVPe///CHP5Cbm8tDDz3Ez3/+85jPHzx4MKFQiDVr1sR8VnusXr06sA+Ba3wuXHGRY9CgQYRCIdauXdvg8ZNOOgmArKyswLI098+/ZcuWwOZboY5SPzVmoaNcZbDSUeonn/pJ/dSY+sl9P4E6CtRPoH5qTP2UnP1k/sf3jhw5wiOPPMKvf/1rSktL675WrVpF3759nfzGtVqhUIiUlBQOHToUyLzjjz+eCy+8kAceeIADBw40+XOXvz72lVde4b333uPLX/6yswzJIi8vjzFjxnD//fc3uw8kWOoon/pJaqmj7FA/+dRPUkv9ZIf6yad+klrJ3E/m3yn19NNPs2fPHq677romd8u//OUvM3fuXG644YZAshw+fJgdO3YA/ls777//fvbv388ll1wSyHyABx54gHPOOYczzjiD22+/neHDh3PkyBGWLl3KnDlzWL16dcwz1K5DdXU1H3/8Mc8//zwzZ87k4osv5uqrr475/PoZ6ktLS6N79+6BzHftwQcf5JxzzuG0005jxowZDB8+nJSUFFauXMmaNWs49dRTXUdMGuqoY9RPTXPUp45SRwVN/XSM+qlpjvrUT+qnoKmfjlE/Nc1Rn/opCfrJM+7iiy/2xo8f3+yfrVixwgO8VatWxTzHNddc4wF1X9nZ2d7pp5/u/elPf4r57Ma2bdvmTZ061SsoKPA6derk9evXz/uP//gPb9myZTGfXX8d0tLSvB49engXXHCB9/DDD3vV1dUxn984Q/2vwsLCQObXzzFx4sRAZ9a3bds278Ybb/ROPPFELz093evatat3xhlneHfffbd34MCBmM9v6Z9/2bJlHuDt2bMn5hksUEc1lOz91DiHq45y3U+e57aj1E8+9VND6if1Uy19D+We+qkh9ZP6qVYy9lPI84x/upqIiIiIiIiIiCQc858pJSIiIiIiIiIiiUc3pUREREREREREJHC6KSUiIiIiIiIiIoHTTSkREREREREREQmcbkqJiIiIiIiIiEjgdFNKREREREREREQCp5tSIiIiIiIiIiISON2UEhERERERERGRwOmmlIiIiIiIiIiIBE43peLM7373O7Kzszly5EjdY/v37yc9PZ1zzz23wbGvvvoqoVCIDRs28Mknn3DTTTdRWFhIVlYWAwYMYNq0aZSXlzd4zssvv8zZZ59NdnY2vXv35gc/+EGDWa058cQTeemll5o8Hu7szZs3M2HCBDp37kzPnj353ve+F9bsQ4cO0aVLF9avX9/sn4dCobqvtLQ0BgwYwK233srhw4frjtm+fTtXXnklQ4YMISUlhe985ztNXmf+/PkNXisUCpGZmdlmPpFk0t6OAvjmN7/JwIEDycrKokePHkycOJE1a9bUHb9q1Sq++tWvkp+fT1ZWFsOGDePee+8NK1dbPXHnnXdy9tln07lzZ7p169bsMbHoR4ATTjihrlNSU1Pp27cv1113HXv27Kk7prKykilTpvDZz36WtLQ0vvSlLzV5nb/97W+cc8455OXlkZWVxdChQ/ntb38bVj6RZBDLfoLYfR8TTj+tXLmS888/n27dunHcccdx4YUXsmrVqjZnQzD9BHD48GF+9KMfUVBQQEZGBieccAIPP/xwWBlFEl2ifv/U3N+far927tzZodn6O17i0E2pOFNcXMz+/ft5++236x7761//Su/evVmxYgWVlZV1jy9btowBAwYwcOBAtm3bxrZt2/jVr37F+++/z/z583n++ee57rrr6o5ftWoV48eP56KLLqKkpIRFixaxZMkSbrvttjZzvfvuu+zZs4fRo0c3+bNwZldXVzNhwgQ+/fRT3njjDRYsWMD8+fP5yU9+0ubspUuXUlBQwKBBg1o8Zt68eWzfvp2PPvqIBx98kD/+8Y/8/Oc/r/vzw4cP06NHD3784x8zYsSIFl8nJyeH7du3131t2rSpzXwiyaS9HQVw6qmnMm/ePFavXs0LL7yA53mMHTuW6upqAN555x169uzJo48+yj//+U9+9KMfMX36dO6///42c7XVE59++imXXXYZ3/rWt5r981j1Y63bb7+d7du3s3nzZh577DFef/11pk2bVvfn1dXVZGVlMW3aNC644IJmX6NLly7ceOONvP7666xevZof//jH/PjHP+b3v/99mxlFkkEs+ymW38e01U/79+/noosuYsCAAaxYsYK//e1vZGdnc+GFF1JVVdXq7KD6CeDyyy/n5ZdfZu7cuaxdu5YnnniCwsLCVvOJJItE/f7piiuuaPB3p+3bt3PhhRcyevRoevbs2aHZoL/jJQxP4k6fPn28mTNn1v3v73//+97UqVO9YcOGecuWLat7/Itf/KJ3zTXXtPg6ixcv9jp16uRVVVV5nud506dP90477bQGxyxZssTLzMz0KioqWs10++23e1dccUXY/wyNZz/77LNeSkqKt2PHjrpj5syZ4+Xk5HiHDx9u9bWuvfZa7wc/+EGLfw54Tz31VIPHrrvuOm/8+PHNHj969Gjv5ptvbvL4vHnzvNzc3FaziEj0OmrVqlUe4K1fv77FY7797W97xcXFbWZqqydqtXSdx7IfCwoKvN/+9rcNHrvjjju8k08+udnjr7nmGm/ixImtzqx16aWXeldddVVYx4okg1j1Uyy/j6nVUj+tXLnSA7zNmzfXPfbuu+96gPfhhx+2+ppB9dNzzz3n5ebmert37241j0gyS8TvnxrbuXOnl56e7j3yyCMdnq2/4yUOvVMqDhUXF7Ns2bK6/71s2TLOPfdcRo8eXff4oUOHWLFiBcXFxS2+Tnl5OTk5OaSlpQH+neTGb1XMysqisrKSd955p9VMS5YsYeLEiWH/MzSevXz5cj772c/Sq1evumMuvPBCKioq+Oc//9ni69TU1PD0009HNHvdunW88sorjBo1Kuzn1Nq/fz8FBQXk5+czceLEVrOJJKtodNSBAweYN28eJ554Ivn5+S3OKi8v5/jjj281T3t6orEg+3Hr1q383//9X7s6qr6SkhLeeOONVt8BIZJsYtVPQX4f01hhYSF5eXnMnTuXTz/9lEOHDjF37lyGDRvGCSec0Opzg+qnJUuWcNppp/HLX/6Sfv36MWTIEL773e9y6NChiF5HJJEl4vdPjT3yyCN07tyZr3zlK1Gfrb/jxTHXd8Ukcg899JDXpUsXr6qqyquoqPDS0tK8nTt3eo8//rj3xS9+0fM8z3v55Zc9wNu0aVOzr/Hvf//bGzBggPfDH/6w7rEXXnjBS0lJ8R5//HHvyJEj3pYtW7wvfOELHuA9/vjjLebZsmWL16lTJ2/Pnj1h5W9u9vXXX++NHTu2wXEHDhzwAO/ZZ59t8bX+/ve/ez179vSqq6tbPAbwMjMzvS5dungZGRke4F188cXep59+2uzxLd1Ff+ONN7wFCxZ4JSUl3quvvupdfPHFXk5OjldWVtbGP7FIculIRz3wwANely5dPMArLCxs9b/y/f3vf/fS0tK8F154odU84fRErZb+a1ks+7GgoMDr1KmT16VLFy8zM9MDvFGjRrX4nLbeKdWvXz+vU6dOXkpKinf77be3eJxIMopVP8Xy+5harf3X/Pfee88bOHCgl5KS4qWkpHiFhYXexo0bW329IPvpwgsv9DIyMrwJEyZ4K1as8J555hmvoKDAmzJlSqsZRZJJIn7/1NiwYcO8b33rW20ep7/jJRe9UyoOnXvuuRw4cICVK1fy17/+lSFDhtCjRw9Gjx5d9zPHr776KieddBIDBgxo8vyKigomTJjAySefzIwZM+oeHzt2LHfffTc33HADGRkZDBkyhPHjxwOQktLyVlmyZAmf//znW/zwzXBmt9df/vIXLr744lbzAfz2t7+ltLSUVatW8fTTT7Nu3Tq+9rWvRTTrrLPO4uqrr6aoqIjRo0fz5JNP0qNHD/77v/+7I/8IIgmnIx01efJkSkpKeO211xgyZAiXX355g89RqPX+++8zceJEfvrTnzJ27NhW84TbE62JdT9+73vfo7S0lHfffZeXX34ZgAkTJtR9HkQk/vrXv/L222/zu9/9jnvuuYcnnngi4tcQSVRB9FMkotFPhw4d4rrrruOcc87hzTff5O9//zunnHIKEyZMaPWdSEH2U01NDaFQiMcee4wzzjiD8ePH85vf/IYFCxbo3VIiRyXi90/1LV++nNWrVzf4XOGOztbf8RKDbkrFoUGDBtG/f3+WLVvGsmXL6n40o2/fvuTn5/PGG2+wbNkyzjvvvCbP3bdvHxdddBHZ2dk89dRTpKenN/jzW2+9lb1797J582Z27dpV95bJk046qcU8S5Ys4T/+4z/azN3a7N69e/Pxxx83OL72f/fu3bvDs3v37s2gQYMoLCxkwoQJ/OxnP2PRokUt/jaHcKSnpzNy5MgOvYZIIupIR+Xm5jJ48GC++MUv8qc//Yk1a9bw1FNPNTjmgw8+4Pzzz+cb3/gGP/7xj9vME25PtCWW/di9e3cGDRrE4MGDOe+887jnnnvq1ilSJ554Ip/97Ge5/vrrueWWW6LyHwBEEkWs+inW38e05vHHH2fjxo3MmzeP008/nTPPPJPHH3+cjz76iL/85S8dnh2NfurTpw/9+vUjNze37rFhw4bheR5btmwJ+3VEElmifv9U6w9/+ANFRUWceuqpUZutv+MlBt2UilPFxcW8+uqrvPrqqw1+TegXv/hFnnvuOd56660mP2tcUVHB2LFj6dSpE0uWLGnxV12GQiH69u1LVlYWTzzxBPn5+Xzuc59r9tj9+/ezbNmyNn/et63ZZ511Fu+9916DXw26dOlScnJyOPnkk5t9zQ8//JBNmzYxZsyYVmc3JzU1FaBD/3Wuurqa9957jz59+rT7NUQSVXs6qjHP8/A8r8Gv9v3nP/9JcXEx11xzDXfeeWebOTrSE82JRT82JxodBf67E+qvn4jEpp+C/j6mvoMHD5KSkkIoFKp7rPZ/19TUNPucoPvpnHPOYdu2bezfv7/usXXr1pGSkkL//v0jziCSqBL1+6f9+/ezePHisN4lpb/jJZ801wGkfYqLi5k6dSpVVVUNPsR29OjR3HjjjXz66acNCqv2ptDBgwd59NFHqaiooKKiAoAePXrUXcB33303F110ESkpKTz55JPMmjWLxYsX1/15Y88//zxDhgxp9YM0w5k9duxYTj75ZL72ta/xy1/+kh07dvDjH/+YqVOnkpGR0ezr/uUvf+GCCy6gc+fOba7X3r172bFjBzU1NXz44YfcfvvtDBkyhGHDhtUdU1paCvil+e9//5vS0lI6depU983k7bffzplnnsmgQYPYu3cvd999N5s2beLrX/96m/NFkk2kHfWvf/2LRYsWMXbsWHr06MGWLVuYNWsWWVlZdT8m9/7773Peeedx4YUXcuutt7Jjxw7A/wakR48ezeYItyc2b97MJ598wubNm6murq7rg0GDBtG1a1cgNv1Ya9++fezYsQPP8ygrK+P73/8+PXr04Oyzz6475oMPPuDTTz/lk08+Yd++fXUZi4qKAHjggQcYMGAAQ4cOBeD111/nV7/6VYNf3S4isemnWH4f01Y/jRkzhu9973tMnTqVm266iZqaGmbNmkVaWlqLf3kNup+uvPJK7rjjDv7zP/+Tn/3sZ+zatYvvfe97XHvttWRlZbWZQSRZJOL3TwCLFi3iyJEjXHXVVW2ugf6Ol4ScfZqVdMhHH33kAd7QoUMbPL5x48a6D7irb9myZR7Q7NdHH31Ud1xxcbGXm5vrZWZmeqNGjWr1wzk9z/Ouuuoq70c/+lGrx4Q7e+PGjd64ceO8rKwsr3v37t7/+3//z6uqqmrxdT//+c97Dz30UKuzPc9rMC8UCnl9+vTxrrjiCm/Dhg0tHlf7VVBQUPfn3/nOd7wBAwZ4nTp18nr16uWNHz/e+8c//tHmfJFkFGlHbd261Rs3bpzXs2dPLz093evfv7935ZVXemvWrKk75qc//Wmb12lj4fbENddc0+xr1/8VzLHoR8/zP0i4/swePXp448eP90pKSlo9rvar1uzZs73PfOYzXufOnb2cnBxv5MiR3oMPPhjWB5SKJJNY9FPt82PxfUw4/fTiiy9655xzjpebm+sdd9xx3nnnnectX768xdcMup88z/NWr17tXXDBBV5WVpbXv39/79Zbb/UOHjzYZgaRZJKI3z95nuedddZZ3pVXXtn2AkQwW3/HSxwhz/O8dt3NkqR35MgRevXqxXPPPccZZ5wR6Oxdu3bRp08ftmzZ0uDXL4uI1HLZEy77UUTsUz+JiFUu+0l/x0tO+kwpabdPPvmEW265hdNPP93J7N/85jcqKxFpkcuecNmPImKf+klErHLdT/o7XvLRO6VERERERERERCRweqeUiIiIiIiIiIgETjelREREREREREQkcLopJSIiIiIiIiIigdNNKRERERERERERCZxuSomIiIiIiIiISOB0U0pERERERERERAKnm1IiIiIiIiIiIhI43ZQSEREREREREZHA6aaUiIiIiIiIiIgETjelREREREREREQkcLopJSIiIiIiIiIigdNNKRERERERERERCZxuSomIiIiIiIiISOB0U0pERERERERERAKXFvTAmpoatm3bRnZ2NqFQKOjxImKQ53ns27ePvn37kpLi7l65+klEmmOho9RPItIc9ZOIWBVuPwV+U2rbtm3k5+cHPVZE4kBZWRn9+/d3Nl/9JCKtcdlR6icRaY36SUSsaqufAr8plZ2dXff/d+4T9HQ4uAPwgBB07h38fGVQBmsZXM8HOLjd/7/1+8EF1/0ERs6H9qQyKEPDDAY6Sv2kDFbmK4OxDOonwMi5UAZlMDLfTIYw+ynwm1K1b+ns3Aeu2hb0dHisPxzYCl36wuQtwc9XBmWwlsH1fIBH+/ql5fot3677CWycD9cZXM9XBmVozEJHqZ+Uwcp8ZbCVQf3ks3AulEEZrMy3kiHcftIHnYuIiIiIiIiISOB0U0pERERERERERAKnm1IiIiIiIiIiIhK4wD9TKt7lU0RvhpJJNpXsYwdrKKPUdazAaR1gVwnsXQNV+yA9G7oNhe4jXacKntbBDl2XPq2DrstaWgc7dF36tA4+XZtaA2t0bWoNauna9AW5DropFYZ0MjmdSRQzjQE0PRObKWEZs1nJQqqodJAwGFoHOHIINiyE92fD7tKmf55XBKdMg4GTIC0r6HTB0TrYoevSp3XQdVlL62CHrkuf1sGna1NrYI2uTa1BLV2bPlfroB/fa0NPBjOD1VzNw/RneLPH9Gc4V/MwM1hNTwYFnDAYWgfYuw4WD4PXroXd7zZ/zO53/T9fPAzKPww2X1C0DnbouvRpHXRd1tI62KHr0qd18Ona1BpYo2tTa1BL16bP5TroplQrejKY23iT4+hHiBAppDZ7XAqphAhxHP24jRUJd8FqHfyL9M9nwoHaX6dZ08KBRx8/sAWeGpV4paV1sEPXpU/roOuyltbBDl2XPq2DT9em1sAaXZtag1q6Nn2u1yHim1Kvv/46l1xyCX379iUUCvHnP/85OkmMSSeTm3mRTLJJJT2s56SSTibZ3MxS0smMccJgaB38tzE+OxaqKsCrDu85XrV//DNj/OcngnhYB/VTyxLtugStA8THdRmEeFgH9VPLEu26BK1DrXi4NmMtHtYgWfoJdG2C1qBWPFybQbCwDhHflDpw4AAjRozggQce6Ph0w05nEnkUhH2h1kolne6cwGlcEaNkwdI6+D9Xu39T+BdpLa/af96GRbHJFbR4WAf1U+sS6boErQPEx3UZhHhYB/VT6xLpugStQ614uDZjLR7WIFn6CXRtgtagVjxcm0GwsA4R35QaN24cP//5z7n00ks7Pt2wYqbhtfi+tdbVUE0xN0U5kRtaB/+D3tr9g64pR5+fAOJhHdRPbUuU6xK0DhAf12UQ4mEd1E9tS5TrErQOteLh2oy1eFiDZOkn0LUJWoNa8XBtBsHCOugzpZqRTxEDGNniz9a2JYVUCjiVfIqiGyxgWgf/V2HuLqXln6ttSw3sLvFfJ55pHezQdenTOui6rKV1sEPXpU/r4NO1qTWwRtem1qCWrk2flXWI+U2pw4cPU1FR0eDLut4Mjcrr9KIwKq/jitYB9q6J0uusjc7ruJKo66B+il9ah8S9LiOVqOugfopfWgdfol6bkUjUNYjHfgJdm6A1qJWo12akrKxDzG9KzZw5k9zc3Lqv/Pz8WI/ssEyyo/I6WeRE5XVc0TpA1b4ovU58/Lu6RYm6Duqn+KV1SNzrMlKJug7qp/ildfAl6rUZiURdg3jsJ9C1CVqDWol6bUbKyjrE/KbU9OnTKS8vr/sqKyuL9cgOqyQ6Z+cQ8b1LtQ6QHp3eJj2+ezth10H9FL+0Dol7XUYqUddB/RS/tA6+RL02I5GoaxCP/QS6NkFrUCtRr81IWVmHtOjEaFlGRgYZGRmxHhNVO4jO+9ii9TquaB2gW3Te4Rq113ElUddB/RS/tA6Je11GKlHXQf0Uv7QOvkS9NiORqGsQj/0EujZBa1ArUa/NSFlZh4jfKbV//35KS0spLS0F4KOPPqK0tJTNmzd3LIkhZZSymRJqiPD3Ih5VQzWbeIctrIpysmBpHaD7SMgrokO/kSBvJHQvil4mF+JlHdRPbUuE6xK0DhA/12Wsxcs6qJ/algjXJWgdasXLtRlL8bIGydBPoGsTtAa14uXajDUr6xDx+LfffpuRI0cycuRIAG699VZGjhzJT37yk44lMWYZswm18+ykkMoy7otyIje0DnDKNDr0GwlOmRbNNO7Ewzqon9qWKNclaB0gPq7LIMTDOqif2pYo1yVoHWrFw7UZa/GwBsnST6BrE7QGteLh2gyChXWIeDeee+65eJ7X5Gv+/PkdT2PIShaym01UUxXR86qpYhcbeZtFMUoWLK0DDJwEXQsgFOFvTg2l+s8beEVscgUtHtZB/dS6RLouQesA8XFdBiEe1kH91LpEui5B61ArHq7NWIuHNUiWfgJdm6A1qBUP12YQLKxDzD/oPF5VUcm9jKWSfWFfsNVUUck+7mUMVVTGOGEwtA6QlgXjX/Q/wC3cizWU6h8/Yan//ESgdbBD16VP66DrspbWwQ5dlz6tg0/XptbAGl2bWoNaujZ9FtZBN6VasZMPmcUo9rAVoMWfva19fA9bmcUodrI+sIxB0DpAtyFw6Qro0v/oAy1dOUcf79LfPz53cBDpgqN1sEPXpU/roOuyltbBDl2XPq2DT9em1sAaXZtag1q6Nn2u10E3pdqwk/XMYBjzmUIZpc0eU0Yp85nCDIYl3IVaS+vgX3SXr4bR8yBvRPPH5I3w//zy1YlXVrW0DnbouvRpHXRd1tI62KHr0qd18Ona1BpYo2tTa1BL16bP5TqkRe+lElcVlSxnActZQD5F9KKQLHI4RAUfs7bFizjRaB38tycWTvG/dpXA3rVQVeG/fbFbof8bDJKB1sEOXZc+rYOuy1paBzt0Xfq0Dj5dm1oDa3Rtag1q6dr0uVoH3ZSKUBmlSXNxtkbr4F+UyVJQrdE62KHr0qd10HVZS+tgh65Ln9bBp2tTa2CNrk2tQS1dm74g10E/viciIiIiIiIiIoHTTSkREREREREREQmcbkqJiIiIiIiIiEjgQp7neUEOrKioIDc3F0LQpW+Qk30Ht4NXA6EU6Nwn+PnKoAzWMrieD3BgG+BBeXk5OTk5bkLgvp/AxvlwncH1fGVQhsYsdJT6SRmszFcGWxnUTz4L50IZlMHKfCsZwu0ndzelREQaMXNTSkSkGSb+0ici0gz1k4hY1VY/ufvte3qnlDIog4kMrufDsbvoZui/9CX9nlQGZajPVEepn5I+g+v5ymArg/rJZ+FcKIMyWJlvJUO4/eTsplTn3jB5S/BzH+sPB7b6J8bFfGVQBmsZXM8HeLSvX5xWuOonsHE+XGdwPV8ZlKExSx2lflIG1/OVwVYG9ZPPwrlQBmWwMt9KhnD7SR90LiIiIiIiIiIigdNNKRERERERERERCZxuSomIiIiIiIiISODcfdB5O+RTRG+Gkkk2lexjB2soozTpMljgeh12lcDeNVC1D9KzodtQ6D4ysPHKYCyDBa6vCSsZLLCwDq6vC9fzlcEe19eF6/lWWFgHC9eFMrifb4mF68JCBtcsrIGF60IZgs9g/qZUOpmcziSKmcYAmq7CZkpYxmxWspAqKhM2gwWu1+HIIdiwEN6fDbtLm/55XhGcMg0GToK0rKiPVwZjGSxwfU1YyWCBhXVwfV24nq8M9ri+LlzPt8LCOli4LpTB/XxLLFwXFjK4ZmENLFwXyuA2g+kf3+vJYGawmqt5mP4Mb/aY/gznah5mBqvpyaCEzGCB63XYuw4WD4PXroXd7zZ/zO53/T9fPAzKP4zqeGUwlsEC19eElQwWWFgH19eF6/nKYI/r68L1fCssrIOF60IZ3M+3xMJ1YSGDaxbWwMJ1oQzuM5i9KdWTwdzGmxxHP0KESCG12eNSSCVEiOPox22siOrFYiGDBa7XYe86+POZcKD2V1nWtHDg0ccPbIGnRkX3QlEGOxkscH1NWMlggYV1cH1duJ6vDPa4vi5cz7fCwjpYuC6Uwf18SyxcFxYyuGZhDSxcF8pgI0NEN6VmzpzJ6aefTnZ2Nj179uRLX/oSa9eujU6SetLJ5GZeJJNsUkkP6zmppJNJNjezlHQyEyKDBa7X4cgheHYsVFWAVx3ec7xq//hnxvjP7yhlsJOhNeqnYDNYYGEdXF8XrucrQ/iSpaNcz7fCwjpYuC6Uwf38cCRLP1nJ4JqFNbBwXSiDnQwR3ZR67bXXmDp1Km+++SZLly6lqqqKsWPHcuDAgY4nqed0JpFHQdgXSa1U0unOCZzGFQmRwQLX67BhIezfFP4FUsur9p+3YVGHxiuDsQytUT8Fm8ECC+vg+rpwPV8ZwpcsHeV6vhUW1sHCdaEM7ueHI1n6yUoG1yysgYXrQhnsZIjoptTzzz/PlClT+MxnPsOIESOYP38+mzdv5p133ul4knqKmYbX4nvGWldDNcXclBAZLHC9Du/Ppv0/ZJpy9PkdpAx2MrRG/RRsBgssrIPr68L1fGUIX7J0lOv5VlhYBwvXhTK4nx+OZOknKxlcs7AGFq4LZbCToUOfKVVeXg7A8ccf3/EkR+VTxABGtvhzrW1JIZUCTiWforjOYIHrddhVcvRT/9vXmVADu0v812kvZbCTIVLqp9hlsMDCOri+LlzPV4aOScSOcj3fCgvrYOG6UAb389srEfvJSgbXLKyBhetCGexkgA7clKqpqeE73/kO55xzDqecckqLxx0+fJiKiooGX63pzdD2RmqgF4Xtfq6FDBa4Xoe9a6Iynr0d+JF4ZbCTIRLqp9hmsMDCOri+LlzPV4b2C6ejIu0ncH9duJ5vhYV1sHBdKIP7+e2RqP1kJYNrFtbAwnWhDHYyQAduSk2dOpX333+fhQsXtnrczJkzyc3NrfvKz89v9fhMstsbqYEsctr9XAsZLHC9DlX7ojKeqrb/PakMcZAhEuqn2GawwMI6uL4uXM9XhvYLp6Mi7Sdwf124nm+FhXWwcF0og/v57ZGo/WQlg2sW1sDCdaEMdjJAO29K3XjjjTz99NMsW7aM/v37t3rs9OnTKS8vr/sqKytr9fhKorMyh2j/yljIYIHrdUiPTmeS3oF/byiDnQzhUj/FPoMFFtbB9XXher4ytE+4HRVpP4H768L1fCssrIOF60IZ3M+PVCL3k5UMrllYAwvXhTLYyQCQFsnBnudx00038dRTT/Hqq69y4okntvmcjIwMMjIywp6xg+i8h6wjr2MhgwWu16FbdN5d2qHXUQY7GdqifnLzOq5YWAfX14Xr+coQmUg7KtJ+AvfXhev5VlhYBwvXhTK4nx+uZOgnKxlcs7AGFq4LZbCTASJ8p9TUqVN59NFHefzxx8nOzmbHjh3s2LGDQ4cOdSxFPWWUspkSaojwdxIeVUM1m3iHLayK6wwWuF6H7iMhr4gO/TaAvJHQvaidz1cGUxnaon4KLoMFFtbB9XXher4yRCYZOsr1fCssrIOF60IZ3M8PVzL0k5UMrllYAwvXhTLYyUCk4+fMmUN5eTnnnnsuffr0qftatGhRx1I0sozZhNq5Mimksoz7EiKDBa7X4ZRpdOi3AZwyrUPjlcFYhtaon4LNYIGFdXB9XbierwzhS5aOcj3fCgvrYOG6UAb388ORLP1kJYNrFtbAwnWhDHYyRLQbPc9r9mvKlCkdT1LPShaym01UUxXR86qpYhcbeZuOF6iFDBa4XoeBk6BrAYQi/K2loVT/eQOv6NB4ZTCWoTXqp2AzWGBhHVxfF67nK0P4kqWjXM+3wsI6WLgulMH9/HAkSz9ZyeCahTWwcF0og50M7f7te7FURSX3MpZK9oV9sVRTRSX7uJcxVFGZEBkscL0OaVkw/kX/w9PCvVBCqf7xE5b6z+8oZbCTwQLX14SVDBZYWAfX14Xr+cpgj+vrwvV8Kyysg4XrQhncz7fEwnVhIYNrFtbAwnWhDHYymLwpBbCTD5nFKPawFaDFn3utfXwPW5nFKHayPqEyWOB6HboNgUtXQJfaXwLS0q49+niX/v7xuYOjMl4ZjGWwwPU1YSWDBRbWwfV14Xq+Mtjj+rpwPd8KC+tg4bpQBvfzLbFwXVjI4JqFNbBwXSiDjQxmb0oB7GQ9MxjGfKZQRmmzx5RRynymMINhMSkKCxkscL0OuYPh8tUweh7kjWj+mLwR/p9fvjo2/xJXBjsZLHB9TVjJYIGFdXB9Xbierwz2uL4uXM+3wsI6WLgulMH9fEssXBcWMrhmYQ0sXBfK4D5DWvReKjaqqGQ5C1jOAvIpoheFZJHDISr4mLUtXkCJlsEC1+uQlgWFU/yvXSWwdy1UVfhvHexW6P/2gFhTBjsZLHB9TVjJYIGFdXB9Xbierwz2uL4uXM+3wsI6WLgulMH9fEssXBcWMrhmYQ0sXBfK4DaD+ZtS9ZVR6rwcLGSwwPU6dB/p/l/cymAngwWurwkrGSywsA6urwvX85XBHtfXhev5VlhYBwvXhTK4n2+JhevCQgbXLKyBhetCGYLPYPrH90REREREREREJDHpppSIiIiIiIiIiARON6VERERERERERCRwIc/zvCAHVlRUkJubCyHo0jfIyb6D28GrgVAKdO4T/HxlUAZrGVzPBziwDfCgvLycnJwcNyFw309g43y4zuB6vjIoQ2MWOkr9pAxW5iuDrQzqJ5+Fc6EMymBlvpUM4faTu5tSIiKNmLkpJSLSDBN/6RMRaYb6SUSsaquf3P32Pb1TShmUwUQG1/Ph2F10M/Rf+pJ+TyqDMtRnqqPUT0mfwfV8ZbCVQf3ks3AulEEZrMy3kiHcfnJ2U6pzb5i8Jfi5j/WHA1v9E+NivjIog7UMrucDPNrXL04rXPUT2DgfrjO4nq8MytCYpY5SPymD6/nKYCuD+sln4VwogzJYmW8lQ7j9pA86FxERERERERGRwOmmlIiIiIiIiIiIBE43pUREREREREREJHDuPui8HXaVwN41ULUP0rOh21DoPjLYDPkU0ZuhZJJNJfvYwRrKKA00g9bBxhoog8/1XrBC58KndfC5XgfX861ksLAXrHB9PiycC9drAFoHZTjGwl6wwvW5APfnQ2vgs7AOyuALcj+Yvyl15BBsWAjvz4bdpU3/PK8ITpkGAydBWlZsMqSTyelMophpDKDpbthMCcuYzUoWUkVlTDJoHWysgTL4XO8FK3QufFoHn+t1cD3fSgYLe8EK1+fDwrlwvQagdVCGYyzsBStcnwtwfz60Bj4L66AMPlf7IeR5XqC/RLSiooLc3Fw694GrtrV+7N518OxY2L8J/wcNa5o56OjjXQtgwlLIHdz6a9Z+Cn2XfuF9Cn1PBnMzL5JHAR41pJDa5JgaqgmRwm42cS9j2Mn6qGbQOsRmDZQh8vkQm71Q+5sZysvLycnJaTtEjLjuJ4jsfMTiXESaIVH3ZLz1tIX9aCFDrK4JCx0VST+B+z2ZqP0UaQb1kzLUUj8d4/pcgPtrM1H7KdIMFtbBwn60kMHl3/HMfqbU3nXw5zPhQO0CNndi6j1+YAs8NQrKP4xehp4M5jbe5Dj6ESLU7IkBSCGVECGOox+3sYKeDIpaBq2DjTVQBp/rvWCFzoVP6+BzvQ6u51vJYGEvWOH6fFg4F67XALQOynCMhb1ghetzAe7Ph9bAZ2EdlMHnej9EdFNqzpw5DB8+nJycHHJycjjrrLN47rnnohKkviOH/DuFVRXgVYf3HK/aP/6ZMf7zOyqdTG7mRTLJJpX0sJ6TSjqZZHMzS0kns8MZtA421kAZfK73QlvUT61TP/kSbR1cz7eSwcJeaEuydJSFc+F6DUDroAzHWNgLbUmWfgL350Nr4LOwDsrgs7AfIrop1b9/f2bNmsU777zD22+/zXnnncfEiRP55z//2eEg9W1Y6L91LdwTU8ur9p+3YVHHM5zOJPIoCPvE1Eolne6cwGlc0eEMWgcba6AMPtd7oS3qp7apn3yJtA6u51vJYGEvtCVZOsrCuXC9BqB1UIZjLOyFtiRLP4H786E18FlYB2XwWdgPEd2UuuSSSxg/fjyDBw9myJAh3HnnnXTt2pU333yzw0Hqe392pMnqSTn6/A4qZhpei++da10N1RRzU4czaB1srIEy+Fzvhbaon8KjfvIlyjq4nm8lg4W90JZk6SgL58L1GoDWQRmOsbAX2pIs/QTuz4fWwGdhHZTBZ2E/tPszpaqrq1m4cCEHDhzgrLPO6nCQWrtKjn7afPvWBWpgd4n/Ou2VTxEDGNniz1K2JYVUCjiVfIranUHrYGMNlMHnei9ESv3UMvWTLxHWwfV8Kxks7IVIJWpHWTgXrtcAtA7KcIyFvRCpRO0ncH8+tAY+C+ugDD4L+8F/nQi99957dO3alYyMDG644QaeeuopTj755BaPP3z4MBUVFQ2+WrN3TaSJWnidte1/bm+GRiVDLwrb/Vytg401UAaf670QLvVT+NRPvnheB9fzrWSwsBfCFUlHRdpP4P58WDgXrtcAtA7KcIyFvRCuRO8ncH8+tAY+C+ugDD4L+wHacVOqsLCQ0tJSVqxYwbe+9S2uueYaPvjggxaPnzlzJrm5uXVf+fn5rb5+1b5IE7XwOm13Y4syyY5Khiza/2tZtQ421kAZfK73QrjUT+FTP/nieR1cz7eSwcJeCFckHRVpP4H782HhXLheA9A6KMMxFvZCuBK9n8D9+dAa+CysgzL4LOwHaMdNqU6dOjFo0CBOPfVUZs6cyYgRI7j33ntbPH769OmUl5fXfZWVlbX6+unRWRfSO7AulURnhxyi/TtE62BjDZTB53ovhEv9FD71ky+e18H1fCsZLOyFcEXSUZH2E7g/HxbOhes1AK2DMhxjYS+EK9H7CdyfD62Bz8I6KIPPwn4ASOtogJqaGg4fPtzin2dkZJCRkRH263WLzjvIOvQ6O4jOe+k68jpaBxtroAw+13uhvdRPsXkdrYPP9Tq4nm8lg4W90F6tdVSk/QTuz4eFc+F6DUDroAzHWNgL7ZVo/QTuz4fWwGdhHZTBZ2E/QITvlJo+fTqvv/46Gzdu5L333mP69Om8+uqrTJ48uUMh6us+EvKKIk1WTwrkjYTuRe3PUEYpmymhhgh/N+NRNVSziXfYwqp2Z9A62FgDZfC53gvhUD+FR/3kS4R1cD3fSgYLeyEcydBRFs6F6zUArYMyHGNhL4QjGfoJ3J8PrYHPwjoog8/CfoAIl2Dnzp1cffXVFBYWcv7557Ny5UpeeOEFxowZ06EQjZ0yjQ59Cv0p0zqeYRmzCbVzh6SQyjLu63AGrYONNVAGn+u90Bb1U3jUT75EWQfX861ksLAX2pIsHWXhXLheA9A6KMMxFvZCW5Kln8D9+dAa+CysgzL4LOyHiKbPnTuXjRs3cvjwYXbu3MlLL70U9bICGDgJuhZAKMLfTBhK9Z838IqOZ1jJQnaziWqqInpeNVXsYiNvs6jDGbQONtZAGXyu90Jb1E9tUz/5EmkdXM+3ksHCXmhLsnSUhXPheg1A66AMx1jYC21Jln4C9+dDa+CzsA7K4LOwH9r7ZrGYSsuC8S/6H9oV7gkKpfrHT1jqP7+jqqjkXsZSyb6wT1A1VVSyj3sZQxWVHc6gdbCxBsrgc70XrNC58GkdfK7XwfV8Kxks7AUrXJ8PC+fC9RqA1kEZjrGwF6xwfS7A/fnQGvgsrIMy+CzsB5M3pQC6DYFLV0CX/kcfaCnp0ce79PePzx0cvQw7+ZBZjGIPWwFa/FnL2sf3sJVZjGIn66OWQetgYw2Uwed6L1ihc+HTOvhcr4Pr+VYyWNgLVrg+HxbOhes1AK2DMhxjYS9Y4fpcgPvzoTXwWVgHZfC53g9mb0qBv9CXr4bR8yBvRPPH5I3w//zy1dE9MbV2sp4ZDGM+UyijtNljyihlPlOYwbCY/MtD62BjDZTB53ovWKFz4dM6+Fyvg+v5VjJY2AtWuD4fFs6F6zUArYMyHGNhL1jh+lyA+/OhNfBZWAdl8LncD2lRe6UYScuCwin+164S2LsWqir8t6x1K/Q/tT7WqqhkOQtYzgLyKaIXhWSRwyEq+Ji1LZ60aNI62FgDZfC53gtW6Fz4tA4+1+vger6VDBb2ghWuz4eFc+F6DUDroAzHWNgLVrg+F+D+fGgNfBbWQRl8rvaD+ZtS9XUfGczJaE0Zpc7/haF1sLEGyuBzvRes0LnwaR18rtfB9XwrGSzsBStcnw8L58L1GoDWQRmOsbAXrHB9LsD9+dAa+CysgzL4gtwPpn98T0REREREREREEpNuSomIiIiIiIiISOB0U0pERERERERERAIX8jzPC3JgRUUFubm5EIIufYOc7Du4HbwaCKVA5z7Bz1cGZbCWwfV8gAPbAA/Ky8vJyclxEwL3/QQ2zofrDK7nK4MyNGaho9RPymBlvjLYyqB+8lk4F8qgDFbmW8kQbj+5uyklItKImZtSIiLNMPGXPhGRZqifRMSqtvrJ3W/f0zullEEZTGRwPR+O3UU3Q/+lL+n3pDIoQ32mOkr9lPQZXM9XBlsZ1E8+C+dCGZTBynwrGcLtJ2c3pTr3hslbgp/7WH84sNU/MS7mK4MyWMvgej7Ao3394rTCVT+BjfPhOoPr+cqgDI1Z6ij1kzK4nq8MtjKon3wWzoUyKIOV+VYyhNtP+qBzEREREREREREJnG5KiYiIiIiIiIhI4HRTSkREREREREREAufug87bYVcJ7F0DVfsgPRu6DYXuI5XBRYZ8iujNUDLJppJ97GANZZQGNt/CGljIIHZY2A/K4HPdT+B+HVzPt5JBjnF9PlzPt5LBQj9ZyGDhXFjIID4L58J1BtfzrWRQP9nJECTzN6WOHIINC+H92bC7tOmf5xXBKdNg4CRIy1KGWGZIJ5PTmUQx0xhA06tiMyUsYzYrWUgVlVGfb2ENLGQQOyzsB2Xwue4ncL8OrudbySDHuD4frudbyWChnyxksHAuLGQQn4Vz4TqD6/lWMqif7GRwxfSP7+1dB4uHwWvXwu53mz9m97v+ny8eBuUfKkOsMvRkMDNYzdU8TH+GN3tMf4ZzNQ8zg9X0ZFBU51tYAwsZxA4L+0EZfK77Cdyvg+v5VjLIMa7Ph+v5VjJY6CcLGSycCwsZxGfhXLjO4Hq+lQzqJzsZXDJ7U2rvOvjzmXCg9tcX1rRw4NHHD2yBp0ZF9wQpg68ng7mNNzmOfoQIkUJqs8elkEqIEMfRj9tYEbXSsLAGFjKIHRb2gzL4XPcTuF8H1/OtZJBjXJ8P1/OtZLDQTxYyWDgXFjKIz8K5cJ3B9XwrGdRPdjK4ZvKm1JFD8OxYqKoArzq853jV/vHPjPGfrwzRyZBOJjfzIplkk0p6WM9JJZ1MsrmZpaST2aH5FtbAQgaxw8J+UAaf634C9+vger6VDHKM6/Pher6VDBb6yUIGC+fCQgbxWTgXrjO4nm8lg/rJTgYLOnRTatasWYRCIb7zne9EKY5vw0LYvyn8E1PLq/aft2GRMkQrw+lMIo+CsMuiVirpdOcETuOKDs23sAYWMkjk1E+Jn8F1P4H7dXA930qGeBOrfgL358P1fCsZLPSThQwWzoWFDPFG30PFLoPr+VYyqJ/sZLCg3TelVq5cyX//938zfHjzP/vZEe/Ppv3JUo4+XxmikqGYaXgtvoewdTVUU8xNHZpvYQ0sZJDIqJ+SI4PrfgL36+B6vpUM8SSW/QTuz4fr+VYyWOgnCxksnAsLGeKJvoeKbQbX861kUD/ZyWBBu5Zg//79TJ48mYceeojjjjsuqoF2lRz9tPn27VGogd0l/usoQ8cy5FPEAEa2+PO9bUkhlQJOJZ+idj3fwhpYyCCRUT8lRwbX/QTu18H1fCsZ4kks+wncnw/X861ksNBPFjJYOBcWMsQTfQ8V2wyu51vJoH6yk8GKdt2Umjp1KhMmTOCCCy5o89jDhw9TUVHR4Ks1e9e0J1Ezr7O2A89VBgB6MzQqGXpR2K7nWVgDCxkkMuqn5Mjgup/A/Tq4nm8lQzyJZT+B+/Pher6VDBb6yUIGC+fCQoZ4Em5HxWM/Wcjger6VDOonOxmsSIv0CQsXLuQf//gHK1euDOv4mTNn8rOf/Szs16/aF2miFl6n7W5UhjZkkh2VDFnktOt5FtbAQgYJn/opeTK47idwvw6u51vJEC9i3U/g/ny4nm8lg4V+spDBwrmwkCFeRNJR8dhPFjK4nm8lg/rJTgYrInqnVFlZGTfffDOPPfYYmZnhfeL99OnTKS8vr/sqKytr9fj06OxR0tu/R5XhqEqic6Ucon1XioU1sJBBwqN+Sq4MrvsJ3K+D6/lWMsSDIPoJ3J8P1/OtZLDQTxYyWDgXFjLEg0g7Kh77yUIG1/OtZFA/2clgRUTvlHrnnXfYuXMnn/vc5+oeq66u5vXXX+f+++/n8OHDpKY2/NnQjIwMMjIywp7RLTrv5uvQ6yiDbwfReU9he1/HwhpYyCDhUT8lVwbX/QTu18H1fCsZ4kEQ/QTuz4fr+VYyWOgnCxksnAsLGeJBpB0Vj/1kIYPr+VYyqJ/sZLAiondKnX/++bz33nuUlpbWfZ122mlMnjyZ0tLSJt9QtUf3kZBXFGmyelIgbyR0L1KGjmYoo5TNlFBDhL+j8qgaqtnEO2xhVbueb2ENLGSQ8KifkiuD634C9+vger6VDPEgiH4C9+fD9XwrGSz0k4UMFs6FhQzxQN9DBZPB9XwrGdRPdjJYEdESZGdnc8oppzT46tKlC3l5eZxyyilRC3XKNDr0KfSnTFOGaGVYxmxC7bxSUkhlGfd1aL6FNbCQQdqmfkq+DK77Cdyvg+v5VjJYF1Q/gfvz4Xq+lQwW+slCBgvnwkIG6/Q9VHAZXM+3kkH9ZCeDBe29LxdTAydB1wIIRXhTPpTqP2/gFcoQrQwrWchuNlFNVUTPq6aKXWzkbRZ1aL6FNbCQQeywsB+Uwee6n8D9OriebyWDHOP6fLiebyWDhX6ykMHCubCQQXwWzoXrDK7nW8mgfrKTwYIO35R69dVXueeee6IQ5Zi0LBj/ov+hXeGeoFCqf/yEpf7zlSE6Gaqo5F7GUsm+sEujmioq2ce9jKGKyg7Nt7AGFjJI+6ifEjuD634C9+vger6VDPEoFv0E7s+H6/lWMljoJwsZLJwLCxnikb6Hik0G1/OtZFA/2clggcl3SgF0GwKXroAu/Y8+0FLSo4936e8fnztYGaKdYScfMotR7GErQIs//1v7+B62MotR7GR9VOZbWAMLGcQOC/tBGXyu+wncr4Pr+VYyyDGuz4fr+VYyWOgnCxksnAsLGcRn4Vy4zuB6vpUM6ic7GVwze1MK/IW+fDWMngd5I5o/Jm+E/+eXr47NiVEG307WM4NhzGcKZZQ2e0wZpcxnCjMYFtWyABtrYCGD2GFhPyiDz3U/gft1cD3fSgY5xvX5cD3fSgYL/WQhg4VzYSGD+CycC9cZXM+3kkH9ZCeDS2muA7QlLQsKp/hfu0pg71qoqvDfstat0P/UemUIJkMVlSxnActZQD5F9KKQLHI4RAUfs7bFIokWC2tgIYPYYWE/KIPPdT+B+3VwPd9KBjnG9flwPd9KBgv9ZCGDhXNhIYP4LJwL1xlcz7eSQf1kJ4Mr5m9K1dd9pPuToQy+MkoDKYiWWFgDCxnEDgv7QRl8rvsJ3K+D6/lWMsgxrs+H6/lWMljoJwsZLJwLCxnEZ+FcuM7ger6VDOonOxmCZPrH90REREREREREJDHpppSIiIiIiIiIiARON6VERERERERERCRwIc/zvCAHVlRUkJubCyHo0jfIyb6D28GrgVAKdO4T/HxlUAZrGVzPBziwDfCgvLycnJwcNyFw309g43y4zuB6vjIoQ2MWOkr9pAxW5iuDrQzqJ5+Fc6EMymBlvpUM4faTu5tSIiKNmLkpJSLSDBN/6RMRaYb6SUSsaquf3P32Pb1TShmUwUQG1/Ph2F10M/Rf+pJ+TyqDMtRnqqPUT0mfwfV8ZbCVQf3ks3AulEEZrMy3kiHcfnJ2U6pzb5i8Jfi5j/WHA1v9E+NivjIog7UMrucDPNrXL04rXPUT2DgfrjO4nq8MytCYpY5SPymD6/nKYCuD+sln4VwogzJYmW8lQ7j9pA86FxERERERERGRwOmmlIiIiIiIiIiIBE43pUREREREREREJHDuPui8HXaVwN41ULUP0rOh21DoPjL5MuRTRG+Gkkk2lexjB2soozSpMrierwy2MlhgoRssZLCwH5RBe8FSBitc7wnX88HGflAGZbAy3xIL/eA6g4X9YCGD6/MAWodaQa6D+ZtSRw7BhoXw/mzYXdr0z/OK4JRpMHASpGUlboZ0MjmdSRQzjQE03ZGbKWEZs1nJQqqoTMgMrucrg60MFljoBgsZLOwHZdBesJTBCtd7wvV8sLEflEEZrMy3xEI/uM5gYT9YyOD6PIDWoZardQh5nhfoLxGtqKggNzeXzn3gqm2tH7t3HTw7FvZvwv9Bw5pmDjr6eNcCmLAUcge3/pq1n0LfpV94n0JvIUNPBnMzL5JHAR41pJDa5JgaqgmRwm42cS9j2Mn6hMoQi/nKEPn8WGWo/c0M5eXl5OTktB0iRlz3E0R2PixkSNQ9GW8ZEnUvWMlgoaMi6Sdw//2L9mTsMsRbPylD7OaD+qlWvP0dL1H7KdIMifrvinjbj+D273hmP1Nq7zr485lwoHYBmzsx9R4/sAWeGgXlHyZWhp4M5jbe5Dj6ESLU7OYASCGVECGOox+3sYKeDEqYDK7nK4OtDBZY6AYLGSzsB2XQXrCUwQrXe8L1fLCxH5RBGazMt8RCP7jOYGE/WMjg+jyA1qGW63UweVPqyCH/TmFVBXjV4T3Hq/aPf2aM//xEyJBOJjfzIplkk0p6WM9JJZ1MsrmZpaSTGfcZXM9XBlsZLLDQDRYyWNgPyqC9YCmDFa73hOv5YGM/KIMyWJlviYV+cJ3Bwn6wkMH1eQCtQy0L6xDRTakZM2YQCoUafA0dOrTDIRrbsNB/61q4J6aWV+0/b8OixMhwOpPIoyDszVErlXS6cwKncUXcZ3A9XxlsZWiN+inYDBb2gzJoL1jK0JZk6SjX88HGflAGZbAyPxzJ0k8WMljYDxYyuD4PoHWoZWEdIn6n1Gc+8xm2b99e9/W3v/2twyEae392e5IdlXL0+QmQoZhpeC2+f691NVRTzE1xn8H1fGWwlaEt6qfgMljYD8qgvWApQziSoaNczwcb+0EZlMHK/HAlQz9ZyGBhP1jI4Po8gNahloV1iHgJ0tLS6N27d91X9+7dOxyivl0lRz9tvn3rAjWwu8R/nXjOkE8RAxjZ4s9ztiWFVAo4lXyK4jaD6/nKYCtDONRPwWSwsB+UQXvBUoZwJXpHuZ4PNvaDMiiDlfmRSPR+spDBwn6wkMH1eQCtQy0L6+C/ToQ+/PBD+vbty0knncTkyZPZvHlzq8cfPnyYioqKBl+t2bsm0kQtvM7aDjzXQIbeROcts70ojNsMrucrg60M4VA/BZPBwn5QBu0FSxnCFUlHRdpP4H5PuJ4PNvaDMiiDlfmRSPR+spDBwn6wkMH1eQCtQy0L6wAR3pQaNWoU8+fP5/nnn2fOnDl89NFHfOELX2Dfvn0tPmfmzJnk5ubWfeXn57c6o6rll4pIVdvdaDpDJtlRyZBF+381rOsMrucrg60MbVE/BZfBwn5QBu0FSxnCEWlHRdpP4H5PuJ4PNvaDMiiDlfnhSoZ+spDBwn6wkMH1eQCtQy0L6wAR3pQaN24cl112GcOHD+fCCy/k2WefZe/evSxevLjF50yfPp3y8vK6r7KyslZnpEdnXUjvwLpYyFBJdHbpIdq/S11ncD1fGWxlaIv6KbgMFvaDMmgvWMoQjkg7KtJ+Avd7wvV8sLEflEEZrMwPVzL0k4UMFvaDhQyuzwNoHWpZWAeAtI48uVu3bgwZMoT169e3eExGRgYZGRnhv2aUftFDR17HQoYdROf9fB15HdcZXM9XBlsZIqV+it3rWNgPyqC9YClDe7TVUZH2E7jfE67ng439oAzKYGV+eyViP1nIYGE/WMjg+jyA1qGWhXWA9n/WOwD79+9nw4YN9OnTp0Mh6us+EvKK6NCn0OeNhO5F8Z2hjFI2U0INEf5+yKNqqGYT77CFVXGbwfV8ZbCVIVLqp9hlsLAflEF7wVKG9kjEjnI9H2zsB2VQBivz2ysR+8lCBgv7wUIG1+cBtA61LKwDRLgE3/3ud3nttdfYuHEjb7zxBpdeeimpqal89atf7VCIxk6ZRoc+hf6UaYmRYRmzCbVzl6aQyjLui/sMrucrg60MrVE/BZvBwn5QBu0FSxnakiwd5Xo+2NgPyqAMVuaHI1n6yUIGC/vBQgbX5wG0DrUsrENE07ds2cJXv/pVCgsLufzyy8nLy+PNN9+kR48eHQ5S38BJ0LUAQhH+ZsJQqv+8gVckRoaVLGQ3m6imKqLnVVPFLjbyNoviPoPr+cpgK0Nr1E/BZrCwH5RBe8FShrYkS0e5ng829oMyKIOV+eFIln6ykMHCfrCQwfV5AK1DLQvrENFNqYULF7Jt2zYOHz7Mli1bWLhwIQMHDuxwiMbSsmD8i/6HdoV7gkKp/vETlvrPT4QMVVRyL2OpZF/Ym6SaKirZx72MoYrKuM/ger4y2MrQGvVTsBks7Adl0F6wlKEtydJRrueDjf2gDMpgZX44kqWfLGSwsB8sZHB9HkDrUMvCOnToM6ViqdsQuHQFdOl/9IGWkh59vEt///jcwYmVYScfMotR7GErQIs/71n7+B62MotR7KTlD3eOtwyu5yuDrQwWWOgGCxks7Adl0F6wlMEK13vC9XywsR+UQRmszLfEQj+4zmBhP1jI4Po8gNahlut1MHtTCvyFvnw1jJ4HeSOaPyZvhP/nl6+O7omxlGEn65nBMOYzhTJKmz2mjFLmM4UZDIvJv8BcZ3A9XxlsZbDAQjdYyGBhPyiD9oKlDFa43hOu54ON/aAMymBlviUW+sF1Bgv7wUIG1+cBtA61XK5DWtReKUbSsqBwiv+1qwT2roWqCv8ta90K/U+tT4YMVVSynAUsZwH5FNGLQrLI4RAVfMzaFjdOImVwPV8ZbGWwwEI3WMhgYT8og/aCpQxWuN4TrueDjf2gDMpgZb4lFvrBdQYL+8FCBtfnAbQOtVytg/mbUvV1HxnMybCeoYxS5//Scp3B9XxlsJXBAgvdYCGDhf2gDNoLljJY4XpPuJ4PNvaDMiiDlfmWWOgH1xks7AcLGVyfB9A61ApyHUz/+J6IiIiIiIiIiCQm3ZQSEREREREREZHA6aaUiIiIiIiIiIgELuR5nhfkwIqKCnJzcyEEXfoGOdl3cDt4NRBKgc59gp+vDMpgLYPr+QAHtgEelJeXk5OT4yYE7vsJbJwP1xlcz1cGZWjMQkepn5TBynxlsJVB/eSzcC6UQRmszLeSIdx+cndTSkSkETM3pUREmmHiL30iIs1QP4mIVW31k7vfvqd3SimDMpjI4Ho+HLuLbob+S1/S70llUIb6THWU+inpM7ierwy2MqiffBbOhTIog5X5VjKE20/Obkp17g2TtwQ/97H+cGCrf2JczFcGZbCWwfV8gEf7+sVphat+Ahvnw3UG1/OVQRkas9RR6idlcD1fGWxlUD/5LJwLZVAGK/OtZAi3n/RB5yIiIiIiIiIiEjjdlBIRERERERERkcDpppSIiIiIiIiIiATO3Qedt8OuEti7Bqr2QXo2dBsK3UcmX4Z8iujNUDLJppJ97GANZZQmVQYL58FCBrHDwn6wkMF1N1jJ4PpcuJ4v9rjeE67ng41uUAZlkKYs9IPrDBb2ozL4XO8FKxmCZP6m1JFDsGEhvD8bdpc2/fO8IjhlGgycBGlZiZshnUxOZxLFTGMATXfkZkpYxmxWspAqKhMyg4XzYCGD2GFhP1jI4LobrGRwfS5czxd7XO8J1/PBRjcogzJIUxb6wXUGC/tRGXyu94KVDK6Y/vG9vetg8TB47VrY/W7zx+x+1//zxcOg/MPEzNCTwcxgNVfzMP0Z3uwx/RnO1TzMDFbTk0EJl8HCebCQQeywsB8sZHDdDVYyuD4XrueLPa73hOv5YKMblEEZpCkL/eA6g4X9qAw+13vBSgaXzN6U2rsO/nwmHKj99YU1LRx49PEDW+CpUdE9QRYy9GQwt/Emx9GPECFSSG32uBRSCRHiOPpxGyuiesG6zmDhPFjIIHZY2A8WMrjuBisZXJ8L1/PFHtd7wvV8sNENyqAM0pSFfnCdwcJ+VAaf671gJYNrJm9KHTkEz46FqgrwqsN7jlftH//MGP/5iZAhnUxu5kUyySaV9LCek0o6mWRzM0tJJzPuM1g4DxYyiB0W9oOFDK67wUoG1+fC9Xyxx/WecD0fbHSDMiiDNGWhH1xnsLAflcHnei9YyWBBxDeltm7dylVXXUVeXh5ZWVl89rOf5e23345qqA0LYf+m8E9MLa/af96GRYmR4XQmkUdB2BdqrVTS6c4JnMYVcZ/BwnmwkEHCo34KLoPrbrCSwfW5cD1fIpMMHeV6PtjoBmVQhniTDP1kIYOF/agMPtd7wUoGCyK6KbVnzx7OOecc0tPTee655/jggw/49a9/zXHHHRfVUO/PjjRZPSlHn58AGYqZhtfi+/daV0M1xdwU9xksnAcLGaRt6qdgM7juBisZXJ8L1/MlfMnSUa7ng41uUAZliCfJ0k8WMljYj8rgc70XrGSwIKLfvveLX/yC/Px85s2bV/fYiSeeGNVAu0qa/7T5sNXA7hL/ddr7axMtZMinqNnfPhCuFFIp4FTyKWr3r9F0ncHCebCQQcKjfgoug+tusJLB9blwPV8ikwwd5Xo+2OgGZVCGeJMM/WQhg4X9qAw+13vBSgYrIrovt2TJEk477TQuu+wyevbsyciRI3nooYdafc7hw4epqKho8NWavWsiSdTK66ztwHMNZOjN0Khk6EVh3GawcB4sZJDwqJ+Cy+C6G6xkcH0uXM+XyETaUZH2E7jfE67ng41uUAZliDfJ0E8WMljYj8rgc70XrGSwIqKbUv/617+YM2cOgwcP5oUXXuBb3/oW06ZNY8GCBS0+Z+bMmeTm5tZ95efntzqjal8kiVp5nba70XSGTLKjkiGLnLjNYOE8WMgg4VE/BZfBdTdYyeD6XLieL5GJtKMi7Sdwvydczwcb3aAMyhBvkqGfLGSwsB+Vwed6L1jJYEVEN6Vqamr43Oc+x1133cXIkSP5xje+wfXXX8/vfve7Fp8zffp0ysvL677KyspanZEenT1Kegf+3WEhQyXR2aWHaP8udZ3BwnmwkEHCo34KLoPrbrCSwfW5cD1fIhNpR0XaT+B+T7ieDza6QRmUId4kQz9ZyGBhPyqDz/VesJLBiohuSvXp04eTTz65wWPDhg1j8+bNLT4nIyODnJycBl+t6Radd/N16HUsZNhBdN7P15HXcZ3BwnmwkEHCo34K7nVcd4OVDK7Phev5EplIOyrSfgL3e8L1fLDRDcqgDPEmGfrJQgYL+1EZfK73gpUMVkR0U+qcc85h7dqGP7S4bt06CgoKohao+0jIK4o0WT0pkDcSuhfFd4YyStlMCTVE+Pshj6qhmk28wxZWxW0GC+fBQgYJj/opuAyuu8FKBtfnwvV8iUwydJTr+WCjG5RBGeJNMvSThQwW9qMy+FzvBSsZrIhoCW655RbefPNN7rrrLtavX8/jjz/O73//e6ZOnRrVUKdMg3b+hkioOfr8BMiwjNmE2rlLU0hlGffFfQYL58FCBmmb+inYDK67wUoG1+fC9XwJX7J0lOv5YKMblEEZ4kmy9JOFDBb2ozL4XO8FKxksiGgnnH766Tz11FM88cQTnHLKKdxxxx3cc889TJ48OaqhBk6CrgUQSo3seaFU/3kDr0iMDCtZyG42UU1VRM+rpopdbORtFsV9BgvnwUIGaZv6KdgMrrvBSgbX58L1fAlfsnSU6/lgoxuUQRniSbL0k4UMFvajMvhc7wUrGSyI+PbkxRdfzHvvvUdlZSWrV6/m+uuvj3qotCwY/6L/oV3hnqBQqn/8hKX+8xMhQxWV3MtYKtkX9gVbTRWV7ONexlBFZdxnsHAeLGSQ8KifgsvguhusZHB9LlzPl8gkQ0e5ng82ukEZlCHeJEM/WchgYT8qg8/1XrCSwYL2/gRjzHUbApeugC79jz7QUtKjj3fp7x+fOzixMuzkQ2Yxij1sBWjxZ29rH9/DVmYxip2sT5gMFs6DhQxih4X9YCGD626wksH1uXA9X+xxvSdczwcb3aAMyiBNWegH1xks7Edl8LneC1YyuGb2phT4C335ahg9D/JGNH9M3gj/zy9fHZsTYyHDTtYzg2HMZwpllDZ7TBmlzGcKMxgWk3+Bus5g4TxYyCB2WNgPFjK47gYrGVyfC9fzxR7Xe8L1fLDRDcqgDNKUhX5wncHCflQGn+u9YCWDS2muA7QlLQsKp/hfu0pg71qoqvDfstat0P/U+mTIUEUly1nAchaQTxG9KCSLHA5RwcesbfEiTqQMFs6DhQxih4X9YCGD626wksH1uXA9X+xxvSdczwcb3aAMyiBNWegH1xks7Edl8LneC1YyuGL+plR93Ue6PxkWMpRR6vxfmq4zWDgPFjKIHRb2g4UMrrvBSgbX58L1fLHH9Z5wPR9sdIMyKIM0ZaEfXGewsB+Vwed6L1jJECTTP74nIiIiIiIiIiKJSTelREREREREREQkcLopJSIiIiIiIiIigQt5nucFObCiooLc3FwIQZe+QU72HdwOXg2EUqBzn+DnK4MyWMvgej7AgW2AB+Xl5eTk5LgJgft+Ahvnw3UG1/OVQRkas9BR6idlsDJfGWxlUD/5LJwLZVAGK/OtZAi3n9zdlBIRacTMTSkRkWaY+EufiEgz1E8iYlVb/eTut+/pnVLKoAwmMrieD8fuopuh/9KX9HtSGZShPlMdpX5K+gyu5yuDrQzqJ5+Fc6EMymBlvpUM4faTs5tSnXvD5C3Bz32sPxzY6p8YF/OVQRmsZXA9H+DRvn5xWuGqn8DG+XCdwfV8ZVCGxix1lPpJGVzPVwZbGdRPPgvnQhmUwcp8KxnC7Sd90LmIiIiIiIiIiARON6VERERERERERCRwuiklIiIiIiIiIiKBc/dB5+2wqwT2roGqfZCeDd2GQveRyZchnyJ6M5RMsqlkHztYQxmlgWZwvQ6u54s0ZmFPWsigfrKTQaQ+13vS9XxQP1nKIFKfhT3pOoP6yU4GC5JtHczflDpyCDYshPdnw+7Spn+eVwSnTIOBkyAtK3EzpJPJ6UyimGkMoOmO3EwJy5jNShZSRWVMMrheB9fzRRqzsCctZFA/2ckgUp/rPel6PqifLGUQqc/CnnSdQf1kJ4MFybwOpn98b+86WDwMXrsWdr/b/DG73/X/fPEwKP8wMTP0ZDAzWM3VPEx/hjd7TH+GczUPM4PV9GRQ1DO4XgfX80Uas7AnLWRQP9nJIFKf6z3pej6onyxlEKnPwp50nUH9ZCeDBcm+DmZvSu1dB38+Ew7U/vrCmhYOPPr4gS3w1KjoniALGXoymNt4k+PoR4gQKaQ2e1wKqYQIcRz9uI0VUS0u1+vger5IYxb2pIUM6ic7GUTqc70nXc8H9ZOlDCL1WdiTrjOon+xksEDrYPSm1JFD8OxYqKoArzq853jV/vHPjPGfnwgZ0snkZl4kk2xSSQ/rOamkk0k2N7OUdDI7nMH1OrieL9KYhT1pIYP6yU4Gkfpc70nX80H9ZCmDSH0W9qTrDOonOxks0Dr4IropdcIJJxAKhZp8TZ06NaqhNiyE/ZvCPzG1vGr/eRsWJUaG05lEHgVhF1atVNLpzgmcxhUdzuB6HVzPl/gSREdZ2JMWMqif7GSQ+JAs30O5ng/qJ0sZJD4kSz9ZyKB+spPBAq2DL6KbUitXrmT79u11X0uXLgXgsssui2qo92dHmqyelKPPT4AMxUzDa/H9e62roZpibupwBtfr4Hq+xJcgOsrCnrSQQf1kJ4PEh2T5Hsr1fFA/Wcog8SFZ+slCBvWTnQwWaB18ES1Bjx496N27d93X008/zcCBAxk9enTUAu0qOfpp8+27VqEGdpf4rxPPGfIpYgAjW/wZ47akkEoBp5JPUbszuF4H1/Ml/sS6oyzsSQsZ1E92Mkj8SIbvoVzPB/WTpQwSP5KhnyxkUD/ZyWCB1uGYdn+m1Keffsqjjz7KtddeSygUavG4w4cPU1FR0eCrNXvXtDdRo9dZ24HnGsjQm6FRydCLwnY/1/U6uJ4v8S2cjlI/tY/6yU4GiU+x6Cdwvyddzwf1k6UMEp8StZ8sZFA/2clggdbhmHbflPrzn//M3r17mTJlSqvHzZw5k9zc3Lqv/Pz8Vo+v2tfeRI1ep+1uNJ0hk+yoZMgip93Pdb0OrudLfAuno9RP7aN+spNB4lMs+gnc70nX80H9ZCmDxKdE7ScLGdRPdjJYoHU4pt03pebOncu4cePo27dvq8dNnz6d8vLyuq+ysrJWj0+PzrVKevuvVRMZKonOLj1E+3ep63VwPV/iWzgdpX5qH/WTnQwSn2LRT+B+T7qeD+onSxkkPiVqP1nIoH6yk8ECrcMxae150qZNm3jppZd48skn2zw2IyODjIyMsF+7W3Te1dih17GQYQfReT9fR17H9Tq4ni/xK9yOUj+1j/rJTgaJP7HqJ3C/J13PB/WTpQwSfxK5nyxkUD/ZyWCB1uGYdr1Tat68efTs2ZMJEyZEOw/dR0JeER36FPq8kdC9KL4zlFHKZkqoIcLfD3lUDdVs4h22sKrdGVyvg+v5Er9i1VEW9qSFDOonOxkk/iTy91Cu54P6yVIGiT+J3E8WMqif7GSwQOtwTMRLUFNTw7x587jmmmtIS2vXG63adMo0OvQp9KdMS4wMy5hNqJ27NIVUlnFfhzO4XgfX8yX+xLqjLOxJCxnUT3YySPxIhu+hXM8H9ZOlDBI/kqGfLGRQP9nJYIHWwRfxFfHSSy+xefNmrr322ljkAWDgJOhaAKEIf1tmKNV/3sArEiPDShaym01UUxXR86qpYhcbeZtFHc7geh1cz5f4E+uOsrAnLWRQP9nJIPEjGb6Hcj0f1E+WMkj8SIZ+spBB/WQngwVaB1/EN6XGjh2L53kMGTIkFnkASMuC8S/6H9oV7gkKpfrHT1jqPz8RMlRRyb2MpZJ9YRdXNVVUso97GUMVlR3O4HodXM+X+BPrjrKwJy1kUD/ZySDxIxm+h3I9H9RPljJI/EiGfrKQQf1kJ4MFWgdfu3/7Xqx1GwKXroAu/Y8+0FLSo4936e8fnzs4sTLs5ENmMYo9bAVo8WeQax/fw1ZmMYqdrI9aBtfr4Hq+SGMW9qSFDOonOxlE6nO9J13PB/WTpQwi9VnYk64zqJ/sZLBA62D4phT4C335ahg9D/JGNH9M3gj/zy9fHZsTYyHDTtYzg2HMZwpllDZ7TBmlzGcKMxgW1cKq5XodXM8XaczCnrSQQf1kJ4NIfa73pOv5oH6ylEGkPgt70nUG9ZOdDBYk+zrE5lPsoigtCwqn+F+7SmDvWqiq8N+y1q3Q/9T6ZMhQRSXLWcByFpBPEb0oJIscDlHBx6xtscyiyfU6uJ4v0piFPWkhg/rJTgaR+lzvSdfzQf1kKYNIfRb2pOsM6ic7GSxI5nUwf1Oqvu4j3Z8MCxnKKA2kpFrjeh1czxdpzMKetJBB/WQng0h9rvek6/mgfrKUQaQ+C3vSdQb1k50MFiTbOpj+8T0REREREREREUlMuiklIiIiIiIiIiKB000pEREREREREREJXMjzPC/IgRUVFeTm5kIIuvQNcrLv4HbwaiCUAp37BD9fGZTBWgbX8wEObAM8KC8vJycnx00I3PcT2DgfrjO4nq8MytCYhY5SPymDlfnKYCuD+sln4VwogzJYmW8lQ7j95O6mlIhII2ZuSomINMPEX/pERJqhfhIRq9rqJ3e/fU/vlFIGZTCRwfV8OHYX3Qz9l76k35PKoAz1meoo9VPSZ3A9XxlsZVA/+SycC2VQBivzrWQIt5+c3ZTq3Bsmbwl+7mP94cBW/8S4mK8MymAtg+v5AI/29YvTClf9BDbOh+sMrucrgzI0Zqmj1E/K4Hq+MtjKoH7yWTgXyqAMVuZbyRBuP+mDzkVEREREREREJHC6KSUiIiIiIiIiIoHTTSkREREREREREQmcuw86b4ddJbB3DVTtg/Rs6DYUuo9Mvgz5FNGboWSSTSX72MEayigNNIOFdRCxxMI1YSGD+knEJtfXhev5oH4SscrCdeE6g/pJkpn5m1JHDsGGhfD+bNhd2vTP84rglGkwcBKkZSVuhnQyOZ1JFDONATRth82UsIzZrGQhVVTGJIOFdRCxxMI1YSGD+knEJtfXhev5oH4SscrCdeE6g/pJxGf6x/f2roPFw+C1a2H3u80fs/td/88XD4PyDxMzQ08GM4PVXM3D9Gd4s8f0ZzhX8zAzWE1PBkU9g4V1ELHEwjVhIYP6ScQm19eF6/mgfhKxysJ14TqD+knkGLM3pfaugz+fCQdqf31hTQsHHn38wBZ4alR0LxYLGXoymNt4k+PoR4gQKaQ2e1wKqYQIcRz9uI0VUS0uC+sgYomFa8JCBvWTiE2urwvX80H9JGKVhevCdQb1k0hDJm9KHTkEz46FqgrwqsN7jlftH//MGP/5iZAhnUxu5kUyySaV9LCek0o6mWRzM0tJJ7PDGSysg4glFq4JCxnUTyI2ub4uXM8H9ZOIVRauC9cZ1E8iTUV0U6q6upr/+q//4sQTTyQrK4uBAwdyxx134HleVENtWAj7N4V/kdTyqv3nbViUGBlOZxJ5FIRdWLVSSac7J3AaV3Q4g4V1EAmH+inYDOonkcgkS0e5ng/qJ5FIJUs/WcigfhJpKqKbUr/4xS+YM2cO999/P6tXr+YXv/gFv/zlL7nvvvuiGur92ZEmqyfl6PMTIEMx0/BafC9l62qoppibOpzBwjqIhEP9FGwG9ZNIZJKlo1zPB/WTSKSSpZ8sZFA/iTQV0XZ84403mDhxIhMmTOCEE07gK1/5CmPHjuWtt96KWqBdJUc/+b991yrUwO4S/3XiOUM+RQxgZIs/Y9yWFFIp4FTyKWp3BgvrIBIu9VNwGdRPIpFLho5yPR/UTyLtkQz9ZCGD+kmkeRHdlDr77LN5+eWXWbduHQCrVq3ib3/7G+PGjWvxOYcPH6aioqLBV2v2rokkUSuvs7YDzzWQoTdDo5KhF4Xtfq6FdRAJl/opuAzqJ5HIRdpRkfYTuL8uXM8H9ZNIeyRDP1nIoH4SaV5aJAffdtttVFRUMHToUFJTU6murubOO+9k8uTJLT5n5syZ/OxnPwt7RtW+SBK18jptd6PpDJlkRyVDFjntfq6FdRAJl/opuAzqJ5HIRdpRkfYTuL8uXM8H9ZNIeyRDP1nIoH4SaV5E75RavHgxjz32GI8//jj/+Mc/WLBgAb/61a9YsGBBi8+ZPn065eXldV9lZWWtzkiPzrVKevuvVRMZKolOYxyi/Y1hYR1EwqV+Ci6D+kkkcpF2VKT9BO6vC9fzQf0k0h7J0E8WMqifRJoX0Tulvve973HbbbcxadIkAD772c+yadMmZs6cyTXXXNPsczIyMsjIyAh7RrfovKuxQ69jIcMOovPeyo68joV1EAmX+im411E/iUQu0o6KtJ/A/XXhej6on0TaIxn6yUIG9ZNI8yJ6p9TBgwdJSWn4lNTUVGpq2vtJaU11Hwl5RZEmqycF8kZC96L4zlBGKZspoYYIf1fnUTVUs4l32MKqdmewsA4i4VI/BZdB/SQSuWToKNfzQf0k0h7J0E8WMqifRJoX0Xa85JJLuPPOO3nmmWfYuHEjTz31FL/5zW+49NJLoxrqlGl06DcCnDItMTIsYzahdjZGCqkso+O/xtXCOoiEQ/0UbAb1k0hkkqWjXM8H9ZNIpJKlnyxkUD+JNBXRFXHffffxla98hW9/+9sMGzaM7373u3zzm9/kjjvuiGqogZOgawGEIvxtmaFU/3kDr0iMDCtZyG42UU1VRM+rpopdbORtFnU4g4V1EAmH+inYDOonkcgkS0e5ng/qJ5FIJUs/WcigfhJpKqKbUtnZ2dxzzz1s2rSJQ4cOsWHDBn7+85/TqVOnqIZKy4LxL/ofoBbuxRJK9Y+fsNR/fiJkqKKSexlLJfvCLq5qqqhkH/cyhioqO5zBwjqIhEP9FGwG9ZNIZJKlo1zPB/WTSKSSpZ8sZFA/iTTV3p8mjbluQ+DSFdCl/9EHWkp69PEu/f3jcwcnVoadfMgsRrGHrQAt/gxy7eN72MosRrGT9VHLYGEdRCyxcE1YyKB+ErHJ9XXhej6on0SssnBduM6gfhJpyOxNKfA3/eWrYfQ8yBvR/DF5I/w/v3x1bC4SCxl2sp4ZDGM+UyijtNljyihlPlOYwbCoFlYtC+sgYomFa8JCBvWTiE2urwvX80H9JGKVhevCdQb1k8gxaa4DtCUtCwqn+F+7SmDvWqiq8N8+2K3Q/w0CyZChikqWs4DlLCCfInpRSBY5HKKCj1nbYplFk4V1ELHEwjVhIYP6ScQm19eF6/mgfhKxysJ14TqD+knEZ/6mVH3dR7q/MCxkKKM0kJJqjYV1ELHEwjVhIYP6ScQm19eF6/mgfhKxysJ14TqD+kmSmekf3xMRERERERERkcSkm1IiIiIiIiIiIhI43ZQSEREREREREZHAhTzP84IcWF5eTrdu3QDo3CfIyb6DOwAPCEHn3sHPVwZlsJbB9XyAg9v9/7t3715yc3PdhMB9P4GR86E9qQzK0DCDgY5SPymDlfnKYCyD+gkwci6UQRmMzDeTIcx+Cvym1JYtW8jPzw9ypIjEPw44vAABAABJREFUibKyMvr37+9svvpJRFrjsqPUTyLSGvWTiFjVVj8FflOqpqaGbdu2kZ2dTSgUivj5FRUV5OfnU1ZWRk5OTgwSKkO8ZHA9Xxmil8HzPPbt20ffvn1JSXH3U8XqJ2VIpAyu5ydSBgsd1dF+Avfnw/V8ZVAGaxnUT8e4PhcWMrierwzKEO0M4fZTWkdCtkdKSkpU7uLn5OQ4OznKYCuD6/nKEJ0MLn9sr5b6SRkSMYPr+YmSwXVHRaufwP35cD1fGZTBWgb10zGuz4WFDK7nK4MyRDNDOP2kDzoXEREREREREZHA6aaUiIiIiIiIiIgELu5uSmVkZPDTn/6UjIwMZUjyDK7nK4OtDBZYWAdlUAYr85XBHtdr4Xq+MiiDtQyu51tiYS1cZ3A9XxmUwVWGwD/oXEREREREREREJO7eKSUiIiIiIiIiIvFPN6VERERERERERCRwuiklIiIiIiIiIiKB000pEREREREREREJXFzdlFq+fDmpqalMmDAh8NlTpkwhFArVfeXl5XHRRRfx7rvvBp5lx44d3HTTTZx00klkZGSQn5/PJZdcwssvvxzz2fXXIT09nV69ejFmzBgefvhhampqYj6/cYb6XxdddFEg89vKsX79+kDm79ixg5tvvplBgwaRmZlJr169OOecc5gzZw4HDx6M+fwpU6bwpS99qcnjr776KqFQiL1798Y8gzXqKPVT4xyuOsp1P4HbjlI/NaV+Uj81zqF+0vdQVqif1E+Nc6ifkquf4uqm1Ny5c7npppt4/fXX2bZtW+DzL7roIrZv38727dt5+eWXSUtL4+KLLw40w8aNGzn11FN55ZVXuPvuu3nvvfd4/vnnKS4uZurUqYFkqF2HjRs38txzz1FcXMzNN9/MxRdfzJEjRwLNUP/riSeeCGR2WzlOPPHEmM/917/+xciRI3nxxRe56667KCkpYfny5Xz/+9/n6aef5qWXXop5Bmkq2TtK/dQ0h8uOctVPoI6ySP2kfmqcQ/2kfrJC/aR+apxD/ZRc/ZTmOkC49u/fz6JFi3j77bfZsWMH8+fP54c//GGgGTIyMujduzcAvXv35rbbbuMLX/gC//73v+nRo0cgGb797W8TCoV466236NKlS93jn/nMZ7j22msDyVB/Hfr168fnPvc5zjzzTM4//3zmz5/P17/+9UAzuOQqx7e//W3S0tJ4++23G+yDk046iYkTJ+J5XuCZkp06Sv3UUg5XXGZQR9miflI/tZTDFfWT1FI/qZ9ayuGK+il4cfNOqcWLFzN06FAKCwu56qqrePjhh52elP379/Poo48yaNAg8vLyApn5ySef8PzzzzN16tQGm7RWt27dAsnRnPPOO48RI0bw5JNPOsuQLHbv3s2LL77Y4j4ACIVCAaeSZO8o9ZPUUkfZo35SP4lP/WSP+kn9JL5k7qe4uSk1d+5crrrqKsB/S115eTmvvfZaoBmefvppunbtSteuXcnOzmbJkiUsWrSIlJRglnH9+vV4nsfQoUMDmRepoUOHsnHjxkBm1T8XtV933XVXILNby3HZZZfFfGbtPigsLGzwePfu3ety/OAHP4h5Dmj+PIwbNy6Q2dYke0epnxqy0FEu+gnsdJT66Rj1k/qpPvWT+34CdVQt9ZP6qT71U3L2U1z8+N7atWt56623eOqppwBIS0vjiiuuYO7cuZx77rmB5SguLmbOnDkA7NmzhwcffJBx48bx1ltvUVBQEPP51t+u53leYHdv65+LWscff3wgs1vL0dJd7SC89dZb1NTUMHnyZA4fPhzIzObOw4oVK+q+uUgW6ij1U2MWOspSP0HwHaV+8qmf1E+NqZ+a0vdQbqif1E+NqZ+aSoZ+ioubUnPnzuXIkSP07du37jHP88jIyOD+++8nNzc3kBxdunRh0KBBdf/7D3/4A7m5uTz00EP8/Oc/j/n8wYMHEwqFWLNmTcxntcfq1asD+xC4xufCFRc5Bg0aRCgUYu3atQ0eP+mkkwDIysoKLEtz//xbtmwJbL4V6ij1U2MWOspVBisdpX7yqZ/UT42pn9z3E6ijQP0E6qfG1E/J2U/mf3zvyJEjPPLII/z617+mtLS07mvVqlX07dvXyW9cqxUKhUhJSeHQoUOBzDv++OO58MILeeCBBzhw4ECTP3f562NfeeUV3nvvPb785S87y5As8vLyGDNmDPfff3+z+0CCpY7yqZ+kljrKDvWTT/0ktdRPdqiffOonqZXM/WT+nVJPP/00e/bs4brrrmtyt/zLX/4yc+fO5YYbbggky+HDh9mxYwfgv7Xz/vvvZ//+/VxyySWBzAd44IEHOOecczjjjDO4/fbbGT58OEeOHGHp0qXMmTOH1atXxzxD7TpUV1fz8ccf8/zzzzNz5kwuvvhirr766pjPr5+hvrS0NLp37x7IfNcefPBBzjnnHE477TRmzJjB8OHDSUlJYeXKlaxZs4ZTTz3VdcSkoY46Rv3UNEd96ih1VNDUT8eon5rmqE/9pH4KmvrpGPVT0xz1qZ+SoJ884y6++GJv/Pjxzf7ZihUrPMBbtWpVzHNcc801HlD3lZ2d7Z1++unen/70p5jPbmzbtm3e1KlTvYKCAq9Tp05ev379vP/4j//wli1bFvPZ9dchLS3N69Gjh3fBBRd4Dz/8sFddXR3z+Y0z1P8qLCwMZH79HBMnTgx0Zn3btm3zbrzxRu/EE0/00tPTva5du3pnnHGGd/fdd3sHDhyI+fyW/vmXLVvmAd6ePXtinsECdVRDyd5PjXO46ijX/eR5bjtK/eRTPzWkflI/1dL3UO6pnxpSP6mfaiVjP4U8z/inq4mIiIiIiIiISMIx/5lSIiIiIiIiIiKSeHRTSkREREREREREAqebUiIiIiIiIiIiEjjdlBIRERERERERkcDpppSIiIiIiIiIiARON6VERERERERERCRwuiklIiIiIiIiIiKB000pEREREREREREJnG5KiYiIiIiIiIhI4HRTKs787ne/Izs7myNHjtQ9tn//ftLT0zn33HMbHPvqq68SCoXYsGEDn3zyCTfddBOFhYVkZWUxYMAApk2bRnl5eYPnvPzyy5x99tlkZ2fTu3dvfvCDHzSY1ZoTTzyRl156qdk/+/3vf8+5555LTk4OoVCIvXv3NnvcM888w6hRo8jKyuK4447jS1/6Ulizi4uL+cMf/tDsn5177rmEQqG6r169enHZZZexadOmBsdNmzaNU089lYyMDIqKipp9rcWLF1NUVETnzp0pKCjg7rvvDiufSLJob0cBfPOb32TgwIFkZWXRo0cPJk6cyJo1axo8J5zrtCUd7agTTjihQZeEQiFmzZrV4dn1Xzc1NZW+ffty3XXXsWfPnrpjKisrmTJlCp/97GdJS0trsRsfe+wxRowYQefOnenTpw/XXnstu3fvDiujSKKL5fdQ8+fPb9IPtV87d+5sNdehQ4fo0qUL69evb/bP77zzTs4++2w6d+5Mt27dWn2t3bt3079//1a/14pkdv1/jrS0NAYMGMCtt97K4cOH64558sknGTNmDD169CAnJ4ezzjqLF154ocHrzJkzh+HDh5OTk1N3zHPPPddmPpFkEcvvn3bv3s1FF11E3759ycjIID8/nxtvvJGKioo2c3W0n2I5O5x+2r59O1deeSVDhgwhJSWF73znO82+1j333FPX8fn5+dxyyy1UVla2mVGiQzel4kxxcTH79+/n7bffrnvsr3/9K71792bFihUNLp5ly5YxYMAABg4cyLZt29i2bRu/+tWveP/995k/fz7PP/881113Xd3xq1atYvz48Vx00UWUlJSwaNEilixZwm233dZmrnfffZc9e/YwevToZv/84MGDXHTRRfzwhz9s8TX+93//l6997Wv853/+J6tWreLvf/87V155ZZuzP/nkE/7+979zySWXtHjM9ddfz/bt29m2bRt/+ctfKCsr46qrrmpy3LXXXssVV1zR7Gs899xzTJ48mRtuuIH333+fBx98kN/+9rfcf//9bWYUSRbt7SiAU089lXnz5rF69WpeeOEFPM9j7NixVFdXN5jR2nXakmh0FMDtt9/O9u3b675uuummDs+u/7qbN2/mscce4/XXX2fatGl1f15dXU1WVhbTpk3jggsuaPY1/v73v3P11Vdz3XXX8c9//pP/+Z//4a233uL6669vM6NIMojl91BXXHFFg27Yvn07F154IaNHj6Znz56t5lq6dCkFBQUMGjSo2T//9NNPueyyy/jWt77V5j/jddddx/Dhw9s8LtzZAPPmzWP79u189NFHPPjgg/zxj3/k5z//ed2fv/7664wZM4Znn32Wd955h+LiYi655BJKSkrqjunfvz+zZs3inXfe4e233+a8885j4sSJ/POf/ww7q0gii+X3TykpKUycOJElS5awbt065s+fz0svvcQNN9zQZq6O9lMsZ0Pb/XT48GF69OjBj3/8Y0aMGNHsazz++OPcdttt/PSnP2X16tXMnTuXRYsWtfk9oUSRJ3GnT58+3syZM+v+9/e//31v6tSp3rBhw7xly5bVPf7FL37Ru+aaa1p8ncWLF3udOnXyqqqqPM/zvOnTp3unnXZag2OWLFniZWZmehUVFa1muv32270rrriizezLli3zAG/Pnj0NHq+qqvL69evn/eEPf2jzNRp75JFHvFGjRrX456NHj/ZuvvnmBo/98Y9/9Dp37tzs8T/96U+9ESNGNHn8q1/9qveVr3ylwWOzZ8/2+vfv79XU1EScWyRRRaujVq1a5QHe+vXrm/xZS9dpSzraUZ7neQUFBd5vf/vbsGeGO7u5173jjju8k08+udnjr7nmGm/ixIlNHr/77ru9k046qcFjs2fP9vr16xdxZpFEFavvoRrbuXOnl56e7j3yyCNtZrr22mu9H/zgB20eN2/ePC83N7fFP3/wwQe90aNHey+//HKLPRbpbMB76qmnGjx23XXXeePHj2/1dU8++WTvZz/7WavHHHfcce36vk8kUQXx/VOte++91+vfv3+bmaLVT7GYHWk/Nfd3Qs/zvKlTp3rnnXdeg8duvfVW75xzzmkzo0SH3ikVh4qLi1m2bFnd/162bBnnnnsuo0ePrnv80KFDrFixguLi4hZfp7y8nJycHNLS0gD/TnJmZmaDY7KysqisrOSdd95pNdOSJUuYOHFie/+R+Mc//sHWrVtJSUlh5MiR9OnTh3HjxvH++++3+dxIZ3/yyScsXryYUaNGRZSxpfXZsmVLkx8FFElm0eioAwcOMG/ePE488UTy8/M7nKmjHVVr1qxZ5OXlMXLkSO6+++6wfrw50tlbt27l//7v/yLuqLPOOouysjKeffZZPM/j448/5k9/+hPjx4+P6HVEElmsvodq7JFHHqFz58585StfaTVPTU0NTz/9dIf76YMPPuD222/nkUceISUlvG/v2zN73bp1vPLKK632U01NDfv27eP4449v9s+rq6tZuHAhBw4c4Kyzzgp7tkiiC+r7p23btvHkk0+2+g5uiF4/BTU7nH5qztlnn80777zDW2+9BcC//vUvnn32WX3/FCTXd8Ukcg899JDXpUsXr6qqyquoqPDS0tK8nTt3eo8//rj3xS9+0fM8r+6/km3atKnZ1/j3v//tDRgwwPvhD39Y99gLL7zgpaSkeI8//rh35MgRb8uWLd4XvvAFD/Aef/zxFvNs2bLF69SpU1j/Ra6ldyE88cQTHuANGDDA+9Of/uS9/fbb3le/+lUvLy/P2717d4uvV1lZ6XXt2tV7//33Wzxm9OjRXnp6utelSxevc+fOHuANGTLE++ijj5o9vqV3YPz3f/+317lzZ++ll17yqqurvbVr13pDhw71AO+NN95o859dJFl0pKMeeOABr0uXLh7gFRYWtvhf+SJ5p1Q0OsrzPO/Xv/61t2zZMm/VqlXenDlzvG7dunm33HJLh2cXFBR4nTp18rp06eJlZmZ6gDdq1KgWn9PSO6U8z3/3RteuXb20tDQP8C655BLv008/bTWjSDKJ1fdQjQ0bNsz71re+1Waev//9717Pnj296urqNo9t6Z0IlZWV3vDhw70//vGPnue13mORzga8zMxMr0uXLl5GRoYHeBdffHGrvfKLX/zCO+6447yPP/64wePvvvuu16VLFy81NdXLzc31nnnmmVbziSSbWH//NGnSJC8rK6vu+4NDhw61mica/RTL2ZH2U0vvlPI8/91b6enpdd8/3XDDDa3mk+jSO6Xi0LnnnsuBAwdYuXIlf/3rXxkyZAg9evRg9OjRdT9z/Oqrr3LSSScxYMCAJs+vqKhgwoQJnHzyycyYMaPu8bFjx3L33Xdzww03kJGRwZAhQ+ruELf2X92WLFnC5z//+TY/fLM1NTU1APzoRz/iy1/+ct3PRodCIf7nf/6nxee98sor9OzZk8985jOtvv7kyZMpLS1l1apV/O1vf2PQoEGMHTuWffv2hZ3x+uuv58Ybb+Tiiy+mU6dOnHnmmUyaNAlofX1Ekk1HOmry5MmUlJTw2muvMWTIEC6//PIOf9BkNDoK4NZbb+Xcc89l+PDh3HDDDfz617/mvvvua/CBmu2d/b3vfY/S0lLeffddXn75ZQAmTJjQ5PO0WvPBBx9w880385Of/IR33nmH559/no0bN4b1uQ0iySJW30PVt3z5clavXt3gM6da8pe//IWLL764Q99HTJ8+nWHDhjX7WZnRmP3b3/627nuop59+mnXr1vG1r32t2WMff/xxfvazn7F48eImn6VVWFhIaWkpK1as4Fvf+hbXXHMNH3zwQUSZRRJZrL9/+u1vf8s//vEP/vKXv7BhwwZuvfXWVvNEo59iPTuSfmrJq6++yl133cWDDz7IP/7xD5588kmeeeYZ7rjjjoheRzrA9V0xaZ/+/ft7d955p/fd7363wX+JGzRokPfyyy97n//8572vf/3rTZ5XUVHhnXXWWd7555/f4h3qmpoab+vWrd7Bgwe9Dz74wAO8t956q8UsF110kXfPPfeElbul/3r3yiuveID317/+tcHjZ5xxRqv/JfKGG27wvvOd77Q6s7m74tu3b/cA76GHHmpyfFvvwKh9F9nhw4e9Z5991gO8nTt3tppBJNm0t6PqO3z4sNe5c+dm36kZyTulotFRzXn//fc9wFuzZk2HZjf3mVLLly/3AG/p0qVNjm/pnVJXXXVVk8+9++tf/+oB3rZt21rNIJJMYvk9lOf5n4NSVFQUVpahQ4d6f/7zn8M6tqV3IowYMcJLSUnxUlNTvdTUVC8lJcUDvNTUVO8nP/lJh2bTzGe21L67/cMPP2zyeFZWlvf000+H9c9z/vnne9/4xjfCOlYkWcT6+6da4Xx/EI1+iuXsSPrJ81p+p9TnP/9577vf/W6Dx/74xz96WVlZYb1LTDpOb++IU8XFxbz66qu8+uqrDX5N6Be/+EWee+453nrrrSY/a1xRUcHYsWPp1KkTS5YsafL5SLVCoRB9+/YlKyuLJ554gvz8fD73uc81e+z+/ftZtmxZh3/WuPZXvK9du7busaqqKjZu3EhBQUGzz/E8j//7v/9r1+zU1FTA/7ns9jy3X79+dOrUiSeeeIKzzjqLHj16RPw6IomsPR3VmOd5eJ7X6juR2hKtjmpOaWkpKSkpLf5mrY7Mbk9HHTx4sMl/Uax9Hc/zIs4gkqhi+T3U/v37Wbx4cVjvkvrwww/ZtGkTY8aM6dA/z//+7/+yatUqSktLKS0t5Q9/+APg/+auqVOnRn12c/30xBNP8J//+Z888cQTTJgwIazXqamp6VC/iySioL5/qv0plZaOiVY/BT1b3z/Fp+Y/nVHMKy4uZurUqVRVVTX4oLjRo0dz44038umnnzYorNpvpg4ePMijjz5KRUUFFRUVAPTo0aPuwrv77ru56KKLSElJ4cknn2TWrFksXry47s8be/755xkyZAgnnHBCq3l37NjBjh07WL9+PQDvvfce2dnZDBgwgOOPP56cnBxuuOEGfvrTn5Kfn09BQQF33303AJdddlmzr/nOO+9w8OBBPv/5z7e5XgcPHmTHjh0AfPzxx9xxxx1kZmYyduzYumPWr1/P/v372bFjB4cOHaK0tBSAk08+mU6dOrFr1y7+9Kc/ce6551JZWcm8efP4n//5H1577bU254skm0g76l//+heLFi1i7Nix9OjRgy1btjBr1iyysrIafNBkW9dpY9HqqOXLl9d9sGh2djbLly/nlltu4aqrruK4445r9jXDnQ2wb98+duzYged5lJWV8f3vf58ePXpw9tln1x3zwQcf8Omnn/LJJ5+wb9++un/2oqIiAC655BKuv/565syZw4UXXsj27dv5zne+wxlnnEHfvn3bzCCSLGL1PRTAokWLOHLkSFg/SveXv/yFCy64gM6dO7d63ObNm/nkk0/YvHkz1dXVddf+oEGD6Nq1a92vha+1a9cuAIYNG9bijw6HOxtg79697Nixg5qaGj788ENuv/12hgwZwrBhwwD/R/auueYa7r33XkaNGlX3/VZWVha5ubmA/yOG48aNY8CAAezbt4/HH3+cV199lRdeeKHN+SLJJBbfPz377LN8/PHHnH766XTt2pV//vOffO973+Occ85p8XuUaPVTLGdD2/0E1GXav38///73vyktLaVTp06cfPLJgP/9029+8xtGjhzJqFGjWL9+Pf/1X//FJZdc0uLfgSXK3L1JSzrio48+8gBv6NChDR7fuHFj3Qfc1Vf7IynNfdX/wO/i4mIvNzfXy8zM9EaNGuU9++yzrea46qqrvB/96Edt5v3pT3/a7Ox58+bVHfPpp596/+///T+vZ8+eXnZ2tnfBBRe0+gHmP/7xj73Jkye3OXv06NENZh533HHe6NGjvVdeeaXV4xqvz7///W/vzDPPrPvA9PPPP997880325wvkowi7aitW7d648aN83r27Omlp6d7/fv396688somPxrX1nXaWLQ66p133vFGjRpV14/Dhg3z7rrrLq+ysrLF1wx3dkFBQYOZPXr08MaPH++VlJS0elztV32zZ8/2Tj75ZC8rK8vr06ePN3nyZG/Lli1tZhBJJrH6HsrzPO+ss87yrrzyyrByfP7zn2/2YwQau+aaa5qdXf9XxDeXt7UfQw53dv15oVDI69Onj3fFFVd4GzZsqDumpV6u/yvrr7322rpf6tCjRw/v/PPP91588cU254skm1h8//TKK694Z511Vt33MIMHD/Z+8IMfRKUj2uqnWM4Op58aH1f7VVBQUPfnVVVV3owZM7yBAwd6mZmZXn5+vvftb387rI9ykOgIeZ7ekybtc+TIEXr16sVzzz3HGWecEfj84cOH8+Mf/5jLL7888NkiYp/LjnLdjyJi265du+jTpw9btmyhV69eSTNbROxTP0nQ9JlS0m6ffPIJt9xyC6effnrgsz/99FO+/OUvM27cuMBni0h8cNlRLmeLiH2ffPIJv/nNb5z8pcvlbBGxT/0kQdM7pUREREREREREJHB6p5SIiIiIiIiIiARON6VERERERERERCRwuiklIiIiIiIiIiKB000pEREREREREREJnG5KiYiIiIiIiIhI4HRTSkREREREREREAqebUiIiIiIiIiIiEjjdlBIRERERERERkcDpppSIiIiIiIiIiARON6VERERERERERCRwuiklIiIiIiIiIiKB000pEREREREREREJnG5KiYiIiIiIiIhI4HRTSkREREREREREApcW9MCamhq2bdtGdnY2oVAo6PEiYpDneezbt4++ffuSkuLuXrn6SUSaY6Gj1E8i0hz1k4hYFW4/BX5Tatu2beTn5wc9VkTiQFlZGf3793c2X/0kIq1x2VHqJxFpjfpJRKxqq58CvymVnZ1d9/937hP0dDi4A/CAEHTuHfx8ZVAGaxlczwc4uN3/v/X7wQXX/QRGzof2pDIoQ8MMBjpK/aQMVuYrg7EM6ifAyLlQBmUwMt9MhjD7KfCbUrVv6ezcB67aFvR0eKw/HNgKXfrC5C3Bz1cGZbCWwfV8gEf7+qXl+i3frvsJbJwP1xlcz1cGZWjMQkepn5TBynxlsJVB/eSzcC6UQRmszLeSIdx+0gedi4iIiIiIiIhI4HRTSkREREREREREAqebUiIiIiIiIiIiErjAP1Mq3uVTRG+Gkkk2lexjB2soo9R1rMC5XgfX8wF2lcDeNVC1D9KzodtQ6D4y0AgmaB3ssHBdWGBhHVxn0HXp0zrY4fqaUAZbGXRtag3qs7AWrjO4nq8MtjJYEOQ66KZUGNLJ5HQmUcw0BtD0TGymhGXMZiULqfr/7L19nJT1ee//nl3WXYTdxSwiICsqImCIQnwgiUmVJJCosdZXjorFKkmatCkVm5ymldP8GvMIaZpWzYNNc1TsUQP2nJp6jBpJgto0atCwPiSAQgMsKOFAYBeQJevu/P64WXaBfZjZmZ3rMzOf9+s1rza79z3X2+v6fj8MNzP30BZgWBii+xBdH+DNA7BxObx8O+xqOvb3DTNg+iKYNA+GDR8SBQncBx0U9oUCCn2IdvC+THAfdIjeE3bQcvDedA96otCLaIfo+nbQclAgqg/++N4AjGEyt7CW67mLCZzd6zETOJvruYtbWMsYziiwYWGI7kN0fYA9r8AD0+DJj8KuF3s/ZteLye8fmAYtr+ZdQQL3QQeFfaGAQh+iHbwvE9wHHaL3hB20HLw33YOeKPQi2iG6vh20HBSI7IMvSvXDGCZzM89wAieTIkUFlb0eV0ElKVKcwMnczLMl9xe/6D5E14dkk37/HbC/6+s0O/s48NDP92+FB2eVXmi5Dzoo7AsFFPoQ7eB9meA+6BC9J+yg5eC96R70RKEX0Q7R9e2g5aBAdB+yvij11FNPcfnllzN+/HhSqRTf//7382MiRhU13MTj1FBLJVUZnVNJFTXUchMrqaJmiA0LQ3QfoutD8jbGR+ZCeyukOzI7J92RHP+DOcn5pUAx9MH51DfOp4R89yHaoRj2ZSEohj44n/qm1PalHbophr051BRDDwqVTwq9iHaIrm8HLQcFFPqQ9UWp/fv3c8455/Ctb30r9+rCnM88GpiY8R/iXVRSxWhO5TyuGSKzwhLdh+j6kHyudt/mzDdpF+mO5LyNK3JWkKAY+uB86h/nU0I++xDtUAz7shAUQx+cT/1TSvvSDt0Uw94caoqhB4XKJ4VeRDtE17eDloMCCn3I+qLUJZdcwpe+9CWuvPLK3KsLM5tFpPt831r/dNLBbG7Ms1EM0X2Irg/Jjd4G/UHXikPnlwDF0Afn08A4nxLy1Ydoh2LYl4WgGPrgfBqYUtmXduimGPbmUFMMPShUPin0Itohur4dtBwUUOiD7ynVC43M4BRm9vm5+4GooJKJnEsjM/IrVmCi+xBdH5KvwtzVRN+fqx2ITti1JnmeYsZ90EFhXyig0IdoB+/LBPdBh+g9YQctB+9N96AnCr2IdoiubwctBwVU+jDkF6UOHjxIa2vrEQ91xjI1L89zElPy8jxRRPchuj7AnnV5UWDP+vw8TxSl2gfnU/Gi0Idoh1Ldl9lSqn1wPtmh2B1KdW9mQ6n2YDD5pNCLaIfo+nbQclBApQ9DflFqyZIl1NfXH340NjYOdcmcqaE2L88znLq8PE8U0X2Irg/QvjcvCrTr/12iX0q1D86n4kWhD9EOpbovs6VU++B8skOxO5Tq3syGUu3BYPJJoRfRDtH17aDloIBKH4b8otTixYtpaWk5/Ghubh7qkjnTRn6mc4DiXqXRfYiuD1CVn9d0VBX33/9Ltg/Op+JFoQ/RDqW6L7OlVPvgfLJDsTuU6t7MhlLtwWDySaEX0Q7R9e2g5aCASh+G5Uejb6qrq6murh7qMnllO/l5H1u+nieK6D5E1wcYlZ93v+fteaIo1T44n4oXhT5EO5TqvsyWUu2D88kOxe5QqnszG0q1B4PJJ4VeRDtE17eDloMCKn3I+p1S+/bto6mpiaamJgB+/etf09TUxJYtW3IzEaKZJrawhk6y/F7EQ3TSwWaeZysv5NmssET3Ibo+wOiZ0DCDnL6RoGEmjJ4xaAUJiqUPzqeBcT4l5KMP0Q7Fsi+HmmLpg/NpYEphX9qhm2LZm0NJsfSgEPmk0Itoh+j6dtByUEClD1mXf+6555g5cyYzZ84E4NOf/jQzZ87kb//2b3MzEWMVt5Ma5HQqqGQV38izUQzRfYiuDzB9ETl9I8H0RTkrSFAMfXA+DYzzKSFffYh2KIZ9WQiKoQ/Op4EplX1ph26KYW8ONcXQg0Llk0Ivoh2i69tBy0EBhT5k/SfVxRdfTDqdPuaxbNmy3G2EWM1ydrGZDtqzOq+DdnayiedYMURmhSW6D9H1ASbNg5ETIZXltyqnKpPzJl2Ts4IExdAH51P/OJ8S8tmHaIdi2JeFoBj64Hzqn1Lal3bophj25lBTDD0oVD4p9CLaIbq+HbQcFFDow5Df6LxYaaeN25hLG3sz/sO8g3ba2MttzKGdtiE2LAzRfYiuDzBsOFz6eHIDt0w3a6oyOf6ylcn5pYD7oIPCvlBAoQ/RDt6XCe6DDtF7wg5aDt6b7kFPFHoR7RBd3w5aDgoo9MEXpfphB6+ylFnsZhtAn5/L7/r5braxlFnsYEPBHAtBdB+i6wOMOhOufBZGTDj0g752zqGfj5iQHF8/OW8KErgPOijsCwUU+hDt4H2Z4D7oEL0n7KDl4L3pHvREoRfRDtH17aDloEB0H3xRagB2sIFbmMYyFtBMU6/HNNPEMhZwC9NK7i98XUT3Ibo+JJvu6rVw0d3QcE7vxzSck/z+6rWlF1ZduA86KOwLBRT6EO3gfZngPugQvSfsoOXgveke9EShF9EO0fXtoOWgQGQfhuXvqUqXdtp4mnt4mntoZAYnMYXh1HGAVn7D+j7/gC81ovsQXR+StydOWZA8dq6BPeuhvTV5++KoKck3GJQD7oMOCvtCAYU+RDt4Xya4DzpE7wk7aDl4b7oHPVHoRbRDdH07aDkoENUHX5TKkmaayuYvef0R3Yfo+pBsynIJqP5wH3RQ2BcKKPQh2sH7MsF90CF6T9hBy8F70z3oiUIvoh2i69tBy0GBQvbBH98zxhhjjDHGGGOMMQXHF6WMMcYYY4wxxhhjTMHxRSljjDHGGGOMMcYYU3BS6XQ6XciCra2t1NfXQwpGjC9k5YQ3Xod0J6Qq4Phxha9vBzuoOUTXB9j/GpCGlpYW6urqYiSIzyfQmEe0Q3R9O9jhaBQyyvlkB5X6dtBycD4lKMzCDnZQqa/ikGk+xV2UMsaYo5C5KGWMMb0g8Zc+Y4zpBeeTMUaVgfIp7tv3/E4pO9hBwiG6PnRfRZfB/9JX9mvSDnboiVRGOZ/K3iG6vh20HJxPCQqzsIMdVOqrOGSaT2EXpY4fC/O3Fr7ufRNg/7ZkMBH17WAHNYfo+gD3jk+CU4WofAKNeUQ7RNe3gx2ORimjnE92iK5vBy0H51OCwizsYAeV+ioOmeaTb3RujDHGGGOMMcYYYwqOL0oZY4wxxhhjjDHGmILji1LGGGOMMcYYY4wxpuDE3eh8EDQyg7FMpYZa2tjLdtbRTFPZOSgQ3Yfo+gA718CeddC+F6pqYdRUGD2zoAp2EEJhTSo4KKwHO8TXt4Me0fkQXd8O3SjsCzvE11dCoRfRDgrZoOAQPQc7xDjIX5SqoobzmcdsFnEKx3ZhC2tYxe2sZjnttJWsgwLRfYiuD/DmAdi4HF6+HXY1Hfv7hhkwfRFMmgfDhg+Jgh2EUFiTCg4K68EO8fXtoEd0PkTXt0M3CvvCDvH1lVDoRbSDQjYoOETPwQ7xDql0Ol3QLxFtbW2lvr6e48fBda/1f+wYJnMTj9PARNJ0UkHlMcd00kGKCnaxmduYww429PucXXehH3FyZnehV3AYCoqtD0NRP1uHPa/AI3Nh32aSD7529nLQoZ+PnAiXrYT6yQMqhDtkuxaGwqHrmxlaWlqoq6sbWGKIiM4n8L7Itr4dhq6+HbpRyKhs8gn853YpOxRbPtlh6OpDceZT9CwUHEo1n7J1KNXXDsW2HofKIdN8kr2n1BgmczPPcAInkyLV6yYBqKCSFClO4GRu5lnGcEZJOSgQ3Yfo+pBs0u+/A/Z3bejeNmmPn+/fCg/OgpZX86ZgByEU1qSCg8J6sEN8fTvoEZ0P0fXt0I3CvrBDfH0lFHoR7aCQDQoO0XOwg45DVhellixZwvnnn09tbS1jxozhD/7gD1i/fn1+THpQRQ038Tg11FJJVUbnVFJFDbXcxEqqqCkJBwWi+xBdH5K3MT4yF9pbId2R2TnpjuT4H8xJzrdDfhz6w/lUWAeF9WCH+Pp2yJxyyajo+nboRmFf2CG+fiYUKp8UehHtoJANCg7Rc7CDlkNWF6WefPJJFi5cyDPPPMPKlStpb29n7ty57N+/P3eTHpzPPBqYmPEm6aKSKkZzKudxTUk4KBDdh+j6kHyudt/mzDdpF+mO5LyNK3JWsEMGOJ8K66CwHuwQX98OmVMuGRVd3w7dKOwLO8TXz4RC5ZNCL6IdFLJBwSF6DnbQcsjqotRjjz3GggULeOtb38o555zDsmXL2LJlC88//3zuJj2YzSLSfb5nrH866WA2N5aEgwLRfYiuD8mN3gb9QdeKQ+fbIS8O/eF8KqyDwnqwQ3x9O2ROuWRUdH07dKOwL+wQXz8TCpVPCr2IdlDIBgWH6DnYQcshp3tKtbS0APCWt7wld5NDNDKDU5jZ5+daB6KCSiZyLo3MKGoHBaL7EF0fkq/C3NVE35+rHYhO2LUmeR475OaQLc6noXNQWA92iK9vh9woxYyKrm+HbhT2hR3i6w+WocgnhV5EOyhkg4JD9BzsoOUAOVyU6uzs5C/+4i+48MILmT59ep/HHTx4kNbW1iMe/TGWqYNVOoKTmDLocxUcFIjuQ3R9gD3r8qLAnhw+lm+H7HE+Da2DwnqwQ3x9OwyeTDIq23yC+HyIrm+HbhT2hR3i6w+GoconhV5EOyhkg4JD9BzsoOUAOVyUWrhwIS+//DLLly/v97glS5ZQX19/+NHY2Njv8TXUDlbpCIYz+K9EVXBQILoP0fUB2vfmRYH2gf+stkMecT4NrYPCerBDfH07DJ5MMirbfIL4fIiub4duFPaFHeLrD4ahyieFXkQ7KGSDgkP0HOyg5QCDvCj153/+5zz88MOsWrWKCRMm9Hvs4sWLaWlpOfxobm7u9/g28tOZAwy+MwoOCkT3Ibo+QFV+cpuqHK5P2iE7nE9D76CwHuwQX98OgyPTjMo2nyA+H6Lr26EbhX1hh/j62TKU+aTQi2gHhWxQcIiegx20HACGZXNwOp3mxhtv5MEHH+SJJ57gtNNOG/Cc6upqqqurM66xnfy8hyyX51FwUCC6D9H1AUbl5x2uOT2PHTLD+VS451FYD3aIr2+H7Mg2o7LNJ4jPh+j6duhGYV/YIb5+phQinxR6Ee2gkA0KDtFzsIOWA2T5TqmFCxdy7733cv/991NbW8v27dvZvn07Bw4cyM2iB800sYU1dJLldxIeopMONvM8W3mhqB0UiO5DdH2A0TOhYQY5fSNBw0wYPWPQCnbIEOdT4RwU1oMd4uvbITvKIaOi69uhG4V9YYf4+plSiHxS6EW0g0I2KDhEz8EOWg5kW/6OO+6gpaWFiy++mHHjxh1+rFixIjeLo1jF7aQG2ZkKKlnFN0rCQYHoPkTXB5i+iJy+kWD6opwV7JABzqfCOiisBzvE17dD5pRLRkXXt0M3CvvCDvH1M6FQ+aTQi2gHhWxQcIiegx20HLJajel0utfHggULcjfpwWqWs4vNdNCe1XkdtLOTTTxH7gGq4KBAdB+i6wNMmgcjJ0Iqy29OTVUm5026JmcFO2SA86mwDgrrwQ7x9e2QOeWSUdH17dCNwr6wQ3z9TChUPin0ItpBIRsUHKLnYActh0F/+95Q0k4btzGXNvZmvFk6aKeNvdzGHNppKwkHBaL7EF0fYNhwuPTx5AZumW7WVGVy/GUrk/PtkB8HBRTWpIKDwnqwQ3x9O+gRnQ/R9e3QjcK+sEN8fSUUehHtoJANCg7Rc7CDloPkRSmAHbzKUmaxm20AfX7utevnu9nGUmaxgw0l5aBAdB+i6wOMOhOufBZGdH0RSV8759DPR0xIjq+fnDcFOwihsCYVHBTWgx3i69tBj+h8iK5vh24U9oUd4usrodCLaAeFbFBwiJ6DHXQcZC9KAexgA7cwjWUsoJmmXo9ppollLOAWpg3JxSAFBwWi+xBdH5JNd/VauOhuaDin92Mazkl+f/XaoXkhYQcdFNakgoPCerBDfH076BGdD9H17dCNwr6wQ3x9JRR6Ee2gkA0KDtFzsIOGw7D8PdXQ0E4bT3MPT3MPjczgJKYwnDoO0MpvWN/nBio1BwWi+xBdH5K3J05ZkDx2roE966G9NXn74qgpyTcY2KEwDgoorEkFB4X1YIf4+nbQIzofouvboRuFfWGH+PpKKPQi2kEhGxQcoudgh3gH+YtSPWmmKfwCkIKDAtF9iK4PyaaMfvFgBx0U1qSCg8J6sEN8fTvoEZ0P0fXt0I3CvrBDfH0lFHoR7aCQDQoO0XOwQ4yD9Mf3jDHGGGOMMcYYY0xp4otSxhhjjDHGGGOMMabg+KKUMcYYY4wxxhhjjCk4qXQ6nS5kwdbWVurr6yEFI8YXsnLCG69DuhNSFXD8uMLXt4Md1Byi6wPsfw1IQ0tLC3V1dTESxOcTaMwj2iG6vh3scDQKGeV8soNKfTtoOTifEhRmYQc7qNRXccg0n+IuShljzFHIXJQyxphekPhLnzHG9ILzyRijykD5FPfte36nlB3sIOEQXR+6r6LL4H/pK/s1aQc79EQqo5xPZe8QXd8OWg7OpwSFWdjBDir1VRwyzaewi1LHj4X5Wwtf974JsH9bMpiI+nawg5pDdH2Ae8cnwalCVD6BxjyiHaLr28EOR6OUUc4nO0TXt4OWg/MpQWEWdrCDSn0Vh0zzyTc6N8YYY4wxxhhjjDEFxxeljDHGGGOMMcYYY0zB8UUpY4wxxhhjjDHGGFNw4m50Pgh2roE966B9L1TVwqipMHpmYR0amcFYplJDLW3sZTvraKapoA7uQ3x90JiDgoPCLBRQmIUddByi94VCDxQcouegRPQ8ouuDxnpwHxIU+hDtoDAHFaJnoeAQXV/FQWFfKPRBwaGQs5C/KPXmAdi4HF6+HXY1Hfv7hhkwfRFMmgfDhg+NQxU1nM88ZrOIUzh2NWxhDau4ndUsp522IXFwH+Lrg8YcFBwUZqGAwizsoOMQvS8UeqDgED0HJaLnEV0fNNaD+5Cg0IdoB4U5qBA9CwWH6PoqDgr7QqEPCg5Rs0il0+mCfoloa2sr9fX1HD8Ornut/2P3vAKPzIV9m0k+aNjZy0GHfj5yIly2Euon9/+cXXehH3FyZnehH8NkbuJxGphImk4qqDzmmE46SFHBLjZzG3PYwYa8OrgPQ1M/W4ehmIOCg8Ja6PpmhpaWFurq6gaWGCKi8wni14OCgzMye4dSXQvZOgzVnxUKGZVNPkH8vijl9RDdh2LLJ9DoQ7SD86mb6FkoOChkpIKDc1rHIfLveLL3lNrzCnz/HbC/q4G9DabHz/dvhQdnQcur+XMYw2Ru5hlO4GRSpHodDEAFlaRIcQInczPPMoYz8ubgPsTXB405KDgozEIBhVnYQcchel8o9EDBIXoOSkTPI7o+aKwH9yFBoQ/RDgpzUCF6FgoO0fVVHBT2hUIfFByiZ5HVRak77riDs88+m7q6Ourq6njnO9/Jo48+mheRnrx5ILlS2N4K6Y7Mzkl3JMf/YE5yfq5UUcNNPE4NtVRSldE5lVRRQy03sZIqanJ2cB/i64PGHBQcFGbRH+WUT3bQcYjeFwo9UHCInkMmlEtGRdcHjfXgPiQo9CHaQWEOA1Eu+aTgEF1fxUFhXyj0QcFBYRZZXZSaMGECS5cu5fnnn+e5557jve99L1dccQW//OUvcxbpycblyVvXMh1MF+mO5LyNK3J3OJ95NDAx48F0UUkVozmV87gmZwf3Ib4+aMxBwUFhFv1RTvlkBx2H6H2h0AMFh+g5ZEK5ZFR0fdBYD+5DgkIfoh0U5jAQ5ZJPCg7R9VUcFPaFQh8UHBRmkdVFqcsvv5xLL72UyZMnc+aZZ/LlL3+ZkSNH8swzz+Qs0pOXb8/WrAcVh87PkdksIt3ne+f6p5MOZnNjzg7uQ3x90JiDgoPCLPqjnPLJDjoO0ftCoQcKDtFzyIRyyajo+qCxHtyHBIU+RDsozGEgyiWfFByi66s4KOwLhT4oOCjMYrAtoKOjg+XLl7N//37e+c535izSxc41h+42P7i+QCfsWpM8z2BpZAanMLPPz1IORAWVTORcGpkxaAf3Ib4+aMxBwUFhFtlQyvlkBx2H6H2h0AMFh+g5DIZSzajo+qCxHtyHBIU+RDsozCFbSjWfFByi66s4KOwLhT4oOCjMInmeLHnppZcYOXIk1dXV/Omf/ikPPvggZ511Vp/HHzx4kNbW1iMe/bFnXbZGfTzP+sGfO5apeXE4iSmDPtd9iK8PGnNQcFCYRSaUQz7ZQcchel8o9EDBIXoO2ZBNRmWbTxA/j+j6oLEe3IcEhT5EOyjMIVNKPZ8UHKLrqzgo7AuFPig4KMwCBnFRasqUKTQ1NfHss8/yyU9+khtuuIFf/epXfR6/ZMkS6uvrDz8aGxv7ff72vdka9fE8A2djn9RQmxeH4Qz+a1ndh/j6oDEHBQeFWWRCOeSTHXQcoveFQg8UHKLnkA3ZZFS2+QTx84iuDxrrwX1IUOhDtIPCHDKl1PNJwSG6voqDwr5Q6IOCg8IsYBAXpY477jjOOOMMzj33XJYsWcI555zDbbfd1ufxixcvpqWl5fCjubm53+evyk9fqMqhL23kZ4UcYPArxH2Irw8ac1BwUJhFJpRDPtlBxyF6Xyj0QMEheg7ZkE1GZZtPED+P6PqgsR7chwSFPkQ7KMwhU0o9nxQcouurOCjsC4U+KDgozAJgWK4CnZ2dHDx4sM/fV1dXU11dnfHzjcrPO8hyep7t5Oe9dLk8j/sQXx805qDgoDCLwVCK+WQHHYfofaHQAwWH6DnkQn8ZlW0+Qfw8ouuDxnpwHxIU+hDtoDCHwVJq+aTgEF1fxUFhXyj0QcFBYRaQ5TulFi9ezFNPPcWmTZt46aWXWLx4MU888QTz58/PSaIno2dCw4xszXpQAQ0zYfSMwTs008QW1tBJlt/NeIhOOtjM82zlhUE7uA/x9UFjDgoOCrMYiHLJJzvoOETvC4UeKDhEzyFTyiGjouuDxnpwHxIU+hDtoDCHTCiHfFJwiK6v4qCwLxT6oOCgMAvIsgU7duzg+uuvZ8qUKbzvfe9j9erV/PCHP2TOnDk5SRzN9EXkdBf66Ytyd1jF7aQGuUIqqGQV38jZwX2Irw8ac1BwUJhFf5RTPtlBxyF6Xyj0QMEheg6ZUC4ZFV0fNNaD+5Cg0IdoB4U5DES55JOCQ3R9FQeFfaHQBwUHhVlkVf3OO+9k06ZNHDx4kB07dvCjH/0o72EFMGkejJwIqSy/mTBVmZw36ZrcHVaznF1spoP2rM7roJ2dbOI5VuTs4D7E1weNOSg4KMyiP8opn+yg4xC9LxR6oOAQPYdMKJeMiq4PGuvBfUhQ6EO0g8IcBqJc8knBIbq+ioPCvlDog4KDwiwG+2axIWXYcLj08eSmXZkOKFWZHH/ZyuT8XGmnjduYSxt7Mx5QB+20sZfbmEM7bTk7uA/x9UFjDgoOCrNQQGEWdtBxiN4XCj1QcIiegxLR84iuDxrrwX1IUOhDtIPCHFSInoWCQ3R9FQeFfaHQBwUHhVlIXpQCGHUmXPksjJhw6Ad9mR76+YgJyfH1k/PnsINXWcosdrMNoM/PWnb9fDfbWMosdrAhbw7uQ3x90JiDgoPCLBRQmIUddByi94VCDxQcouegRPQ8ouuDxnpwHxIU+hDtoDAHFaJnoeAQXV/FQWFfKPRBwSF6FrIXpSBp9NVr4aK7oeGc3o9pOCf5/dVr8zuYLnawgVuYxjIW0ExTr8c008QyFnAL04bkDw/3Ib4+aMxBwUFhFgoozMIOOg7R+0KhBwoO0XNQInoe0fVBYz24DwkKfYh2UJiDCtGzUHCIrq/ioLAvFPqg4BA5i2F5e6YhYthwmLIgeexcA3vWQ3tr8pa1UVOSu9YPNe208TT38DT30MgMTmIKw6njAK38hvV9Di2fuA/x9UFjDgoOCrNQQGEWdtBxiN4XCj1QcIiegxLR84iuDxrrwX1IUOhDtIPCHFSInoWCQ3R9FQeFfaHQBwWHqFnIX5TqyeiZhRlGfzTTFP4HhvsQXx805qDgoDALBRRmYQcdh+h9odADBYfoOSgRPY/o+qCxHtyHBIU+RDsozEGF6FkoOETXV3FQ2BcKfVBwKOQspD++Z4wxxhhjjDHGGGNKE1+UMsYYY4wxxhhjjDEFxxeljDHGGGOMMcYYY0zBSaXT6XQhC7a2tlJfXw8pGDG+kJUT3ngd0p2QqoDjxxW+vh3soOYQXR9g/2tAGlpaWqirq4uRID6fQGMe0Q7R9e1gh6NRyCjnkx1U6ttBy8H5lKAwCzvYQaW+ikOm+RR3UcoYY45C5qKUMcb0gsRf+owxphecT8YYVQbKp7hv3/M7pexgBwmH6PrQfRVdBv9LX9mvSTvYoSdSGeV8KnuH6Pp20HJwPiUozMIOdlCpr+KQaT6FXZQ6fizM31r4uvdNgP3bksFE1LeDHdQcousD3Ds+CU4VovIJNOYR7RBd3w52OBqljHI+2SG6vh20HJxPCQqzsIMdVOqrOGSaT77RuTHGGGOMMcYYY4wpOL4oZYwxxhhjjDHGGGMKji9KGWOMMcYYY4wxxpiCE3ej80Gwcw3sWQfte6GqFkZNhdEz7VCODo3MYCxTqaGWNvaynXU001Q4AeJ7oOJgEhRmYQc7qNRXcTDdRM8juj74tYMd9BxMgsIsoh2cT3ZQcygk8hel3jwAG5fDy7fDrqZjf98wA6YvgknzYNhwO5SyQxU1nM88ZrOIUzh2V25hDau4ndUsp522/AsQ3wMVB5OgMAs72EGlvoqD6SZ6HtH1wa8d7KDnYBIUZhHt4Hyyg5pDFNIf39vzCjwwDZ78KOx6sfdjdr2Y/P6BadDyqh1K1WEMk7mFtVzPXUzg7F6PmcDZXM9d3MJaxnBGfgWI74GKg0lQmIUd7KBSX8XBdBM9j+j64NcOdtBzMAkKs4h2cD7ZQc0hEtmLUntege+/A/Z3fX1hZx8HHvr5/q3w4Kz8DsgOGg5jmMzNPMMJnEyKFBVU9npcBZWkSHECJ3Mzz+Y1vKN7oOJgEhRmYQc7qNRXcTDdRM8juj74tYMd9BxMgsIsoh2cT3ZQc4hG8qLUmwfgkbnQ3grpjszOSXckx/9gTnK+HUrDoYoabuJxaqilkqqMzqmkihpquYmVVFGTmwDxPVBxMAkKs7CDHVTqqziYbqLnEV0f/NrBDnoOJkFhFtEOzic7qDkokNNFqaVLl5JKpfiLv/iLPOkkbFwO+zZnPpgu0h3JeRtX2KFUHM5nHg1MzDi0u6ikitGcynlck5sA8T1QcSg2nE92KAeH6PoqDsXGUOUTxM8juj74tYMd9ByKDb+GGjoH55Md1BwUGPRFqdWrV/Od73yHs8/u/TOwufDy7QzerOLQ+XYoCYfZLCLd53sY+6eTDmZzY24CxPdAxaGYcD7ZoVwcouurOBQTQ5lPED+P6Prg1w520HMoJvwaamgdnE92UHNQYFAt2LdvH/Pnz+e73/0uJ5xwQl6Fdq45dLf5we1V6IRda5LnsUNxOzQyg1OY2efnrAeigkomci6NzBicAPE9UHEoJpxPdigXh+j6Kg7FxFDmE8TPI7o++LWDHfQcigm/hhpaB+eTHdQcVBjURamFCxdy2WWX8f73v3/AYw8ePEhra+sRj/7Ys24wRr08z/oczrWDhMNYpual/klMGfS50T1QcSgmnE92KBeH6PoqDsXEUOYTxM8juj74tYMd9ByKiUwzqhjzScHB+WQHNQcVhmV7wvLly/nFL37B6tWrMzp+yZIlfP7zn8/4+dv3ZmvUx/MMnI12EHeooTYv9YdTN+hzo3ug4lAsOJ/sUE4O0fVVHIqFoc4niJ9HdH3wawc76DkUC9lkVDHmk4KD88kOag4qZPVOqebmZm666Sbuu+8+amoyu/P/4sWLaWlpOfxobm7u9/iq/OxVqga/V+0g4tBGfnbqAQa/U6N7oOJQDDif7FBuDtH1VRyKgULkE8TPI7o++LWDHfQcioFsM6oY80nBwflkBzUHFbJ6p9Tzzz/Pjh07ePvb3374Zx0dHTz11FN885vf5ODBg1RWHvkZ2erqaqqrqzOuMSo/72rM6XnsoOGwnfy8pzGX54nugYpDMeB8skO5OUTXV3EoBgqRTxA/j+j64NcOdtBzKAayzahizCcFB+eTHdQcVMjqnVLve9/7eOmll2hqajr8OO+885g/fz5NTU3HvKAaDKNnQsOMbM16UAENM2H0DDsUu0MzTWxhDZ1k+R2Zh+ikg808z1ZeGJwA8T1QcSgGnE92KDeH6PoqDsVAIfIJ4ucRXR/82sEOeg7FgF9DFcbB+WQHNQcVsmpBbW0t06dPP+IxYsQIGhoamD59et6kpi8ip7vQT19kh1JxWMXtpAa5UyuoZBXfyE2A+B6oOKjjfLJDOTpE11dxUKdQ+QTx84iuD37tYAc9B3X8GqpwDs4nO6g5KDDY63JDyqR5MHIipLK8KJ+qTM6bdI0dSsVhNcvZxWY6aM/qvA7a2ckmnmNFbgLE90DFwSQozMIOdlCpr+JguomeR3R98GsHO+g5mASFWUQ7OJ/soOagQM4XpZ544gluvfXWPKh0M2w4XPp4ctOuTAeUqkyOv2xlcr4dSsOhnTZuYy5t7M04vDtop4293MYc2mnLTYD4Hqg4FCPOJzuUukN0fRWHYmQo8gni5xFdH/zawQ56DsWIX0MNjYPzyQ5qDgpIvlMKYNSZcOWzMGLCoR/0ZXro5yMmJMfXT7ZDqTns4FWWMovdbAPo83PYXT/fzTaWMosdbMiPAPE9UHEwCQqzsIMdVOqrOJhuoucRXR/82sEOeg4mQWEW0Q7OJzuoOUQje1EKkkZfvRYuuhsazun9mIZzkt9fvXZoBmMHDYcdbOAWprGMBTTT1OsxzTSxjAXcwrS8hnYX0T1QcTAJCrOwgx1U6qs4mG6i5xFdH/zawQ56DiZBYRbRDs4nO6g5RDIsWmAghg2HKQuSx841sGc9tLcmb1kbNSW5a70dysOhnTae5h6e5h4amcFJTGE4dRygld+wvs9AzyfRPVBxMAkKs7CDHVTqqziYbqLnEV0f/NrBDnoOJkFhFtEOzic7qDlEIX9RqiejZ8YPww4aDs00FSSo+yO6ByoOJkFhFnawg0p9FQfTTfQ8ouuDXzvYQc/BJCjMItrB+WQHNYdCIv3xPWOMMcYYY4wxxhhTmviilDHGGGOMMcYYY4wpOL4oZYwxxhhjjDHGGGMKTiqdTqcLWbC1tZX6+npIwYjxhayc8MbrkO6EVAUcP67w9e1gBzWH6PoA+18D0tDS0kJdXV2MBPH5BBrziHaIrm8HOxyNQkY5n+ygUt8OWg7OpwSFWdjBDir1VRwyzae4i1LGGHMUMheljDGmFyT+0meMMb3gfDLGqDJQPsV9+57fKWUHO0g4RNeH7qvoMvhf+sp+TdrBDj2RyijnU9k7RNe3g5aD8ylBYRZ2sINKfRWHTPMp7KLU8WNh/tbC171vAuzflgwmor4d7KDmEF0f4N7xSXCqEJVPoDGPaIfo+naww9EoZZTzyQ7R9e2g5eB8SlCYhR3soFJfxSHTfPKNzo0xxhhjjDHGGGNMwfFFKWOMMcYYY4wxxhhTcHxRyhhjjDHGGGOMMcYUnLgbnQ+CnWtgzzpo3wtVtTBqKoyeWX4OjcxgLFOpoZY29rKddTTTVFYOnkOC+6CDwiwUHBTWg4JD9Cyi66s4KKwFFaLnEV0fNNaDgoPCLOygsRZUiJ6FgoPCelBwiJ6DHbop5HqQvyj15gHYuBxevh12NR37+4YZMH0RTJoHw4aXrkMVNZzPPGaziFM4dkVuYQ2ruJ3VLKedtpJ08BwS3AcdFGah4KCwHhQcomcRXV/FQWEtqBA9j+j6oLEeFBwUZmEHjbWgQvQsFBwU1oOCQ/Qc7NBN1HpIpdPpgn6JaGtrK/X19Rw/Dq57rf9j97wCj8yFfZtJPmjY2ctBh34+ciJcthLqJ/f/nF13oR9xcmZ3oVdwGMNkbuJxGphImk4qqDzmmE46SFHBLjZzG3PYwYaSchiKOWTrMBQ9yNahVNdj1zcztLS0UFdXN7DEEBGdTxC/HrJ1iM4GFYfovamwFhQchiqnFTIqm3wCr0nQ+HPb+WSHLpxP3UTPQsGhVPMpWweFPyui14KKQ+Tf8WTvKbXnFfj+O2B/VwN7G0yPn+/fCg/OgpZXS8thDJO5mWc4gZNJkep1cQBUUEmKFCdwMjfzLGM4o2QcPIcE90EHhVkoOCisBwWH6FlE11dxUFgLKkTPI7o+aKwHBQeFWdhBYy2oED0LBQeF9aDgED0HO3QTvR4kL0q9eSC5UtjeCumOzM5JdyTH/2BOcn4pOFRRw008Tg21VFKV0TmVVFFDLTexkipqit7Bc0hwH3RQmIWCg8J6UHCInkV0fRUHhbWgQvQ8ouuDxnpQcFCYhR001oIK0bNQcFBYDwoO0XOwQzcK6yGri1K33HILqVTqiMfUqVNzljiajcuTt65lOpgu0h3JeRtXlIbD+cyjgYkZL44uKqliNKdyHtcUvYPnkOA+DIzzqbAOCutBwSF6FtH1VRwU1sJAlEtGRdcHjfWg4KAwCztorIWBKJd8UnBQWA8KDtFzsEM3Cush63dKvfWtb+X1118//PjpT3+as8TRvHz7YMwOUXHo/BJwmM0i0n2+f69/OulgNjcWvYPnkOA+ZIbzqXAOCutBwSF6FtH1VRwU1kImlENGRdcHjfWg4KAwCztorIVMKId8UnBQWA8KDtFzsEM3Cush6xYMGzaMsWPHHn6MHj06Z4me7Fxz6G7zg+sLdMKuNcnzFLNDIzM4hZl9fp5zICqoZCLn0siMonXwHBLch8xxPhXGQWE9KDhEzyK6voqDwlrIlFLPqOj6oLEeFBwUZmEHjbWQKaWeTwoOCutBwSF6DnboRmE9JM+TJa+++irjx4/n9NNPZ/78+WzZsqXf4w8ePEhra+sRj/7Ysy5boz6eZ30O5wo4jCU/b5k9iSlF6+A5JLgPmeN8KoyDwnpQcIieRXR9FQeFtZAp2WRUtvkE8fOIrg8a60HBQWEWdtBYC5lS6vmk4KCwHhQcoudgh24U1gNkeVFq1qxZLFu2jMcee4w77riDX//617znPe9h7969fZ6zZMkS6uvrDz8aGxv7rdHe91NlRfvA2SjtUENtXhyGM/ivho128BwS3IfMcD4VzkFhPSg4RM8iur6Kg8JayIRsMyrbfIL4eUTXB431oOCgMAs7aKyFTCiHfFJwUFgPCg7Rc7BDNwrrAbK8KHXJJZdw1VVXcfbZZ/OBD3yARx55hD179vDAAw/0ec7ixYtpaWk5/Ghubu63RlV++kJVDn1RcGgjP6v0AINfpdEOnkOC+5AZzqfCOSisBwWH6FlE11dxUFgLmZBtRmWbTxA/j+j6oLEeFBwUZmEHjbWQCeWQTwoOCutBwSF6DnboRmE9AAzL5eRRo0Zx5plnsmHDhj6Pqa6uprq6OvPnzNMXPeTyPAoO28nP+/lyeZ5oB88hwX0YHM6noXsehfWg4BA9i+j6Kg4Ka2EwDJRR2eYTxM8juj5orAcFB4VZ2EFjLQyGUswnBQeF9aDgED0HO3SjsB5g8Pd6B2Dfvn1s3LiRcePG5STRk9EzoWEGOd2FvmEmjJ5R3A7NNLGFNXSS5fdDHqKTDjbzPFt5oWgdPIcE92FwOJ+GzkFhPSg4RM8iur6Kg8JaGAylmFHR9UFjPSg4KMzCDhprYTCUYj4pOCisBwWH6DnYoRuF9QBZtuAv//IvefLJJ9m0aRM/+9nPuPLKK6msrOTaa6/NSeJopi8ip7vQT19UGg6ruJ3UIFdpBZWs4htF7+A5JLgPA+N8KqyDwnpQcIieRXR9FQeFtTAQ5ZJR0fVBYz0oOCjMwg4aa2EgyiWfFBwU1oOCQ/Qc7NCNwnrIqvrWrVu59tprmTJlCldffTUNDQ0888wznHjiiTmL9GTSPBg5EVJZfjNhqjI5b9I1peGwmuXsYjMdtGd1Xgft7GQTz7Gi6B08hwT3YWCcT4V1UFgPCg7Rs4iur+KgsBYGolwyKro+aKwHBQeFWdhBYy0MRLnkk4KDwnpQcIiegx26UVgPWV2UWr58Oa+99hoHDx5k69atLF++nEmTJuUscTTDhsOljyc37cp0QKnK5PjLVibnl4JDO23cxlza2JvxIumgnTb2chtzaKet6B08hwT3YWCcT4V1UFgPCg7Rs4iur+KgsBYGolwyKro+aKwHBQeFWdhBYy0MRLnkk4KDwnpQcIiegx26UVgPOd1TaigZdSZc+SyMmHDoB32ZHvr5iAnJ8fWTS8thB6+ylFnsZhtAn5/37Pr5braxlFnsoO+bOxebg+eQ4D7ooDALBQeF9aDgED2L6PoqDgprQYXoeUTXB431oOCgMAs7aKwFFaJnoeCgsB4UHKLnYIduoteD7EUpSBp99Vq46G5oOKf3YxrOSX5/9dr8DkbJYQcbuIVpLGMBzTT1ekwzTSxjAbcwbUj+AIt28BwS3AcdFGah4KCwHhQcomcRXV/FQWEtqBA9j+j6oLEeFBwUZmEHjbWgQvQsFBwU1oOCQ/Qc7NBN5HoYlrdnGiKGDYcpC5LHzjWwZz20tyZvWRs1JblrfTk4tNPG09zD09xDIzM4iSkMp44DtPIb1ve5cErJwXNIcB90UJiFgoPCelBwiJ5FdH0VB4W1oEL0PKLrg8Z6UHBQmIUdNNaCCtGzUHBQWA8KDtFzsEM3UetB/qJUT0bPLMww1B2aaQr/QyvawXNIcB90UJiFgoPCelBwiJ5FdH0VB4W1oEL0PKLrg8Z6UHBQmIUdNNaCCtGzUHBQWA8KDtFzsEM3hVwP0h/fM8YYY4wxxhhjjDGliS9KGWOMMcYYY4wxxpiC44tSxhhjjDHGGGOMMabgpNLpdLqQBVtbW6mvr4cUjBhfyMoJb7wO6U5IVcDx4wpf3w52UHOIrg+w/zUgDS0tLdTV1cVIEJ9PoDGPaIfo+naww9EoZJTzyQ4q9e2g5eB8SlCYhR3soFJfxSHTfIq7KGWMMUchc1HKGGN6QeIvfcYY0wvOJ2OMKgPlU9y37/mdUnawg4RDdH3ovooug/+lr+zXpB3s0BOpjHI+lb1DdH07aDk4nxIUZmEHO6jUV3HINJ/CLkodPxbmby183fsmwP5tyWAi6tvBDmoO0fUB7h2fBKcKUfkEGvOIdoiubwc7HI1SRjmf7BBd3w5aDs6nBIVZ2MEOKvVVHDLNJ9/o3BhjjDHGGGOMMcYUHF+UMsYYY4wxxhhjjDEFxxeljDHGGGOMMcYYY0zBibvR+SDYuQb2rIP2vVBVC6OmwuiZ5efQyAzGMpUaamljL9tZRzNNZeUQXR801oKCg0lQmIWCg8LetIPGWlBwMN1EzyO6PsTvSzt0o7AeFBxMgsIsoh0U9qUdEqLXgopDIZG/KPXmAdi4HF6+HXY1Hfv7hhkwfRFMmgfDhpeuQxU1nM88ZrOIUzh2RW5hDau4ndUsp522knSIrg8aa0HBwSQozELBQWFv2kFjLSg4mG6i5xFdH+L3pR26UVgPCg4mQWEW0Q4K+9IOCdFrQcUhCumP7+15BR6YBk9+FHa92Psxu15Mfv/ANGh5tTQdxjCZW1jL9dzFBM7u9ZgJnM313MUtrGUMZ5ScQ3R90FgLCg4mQWEWCg4Ke9MOGmtBwcF0Ez2P6PoQvy/t0I3CelBwMAkKs4h2UNiXdkiIXgsqDpHIXpTa8wp8/x2wv+vrCzv7OPDQz/dvhQdn5XdACg5jmMzNPMMJnEyKFBVU9npcBZWkSHECJ3Mzz+Z1w0Y7RNcHjbWg4GASFGah4KCwN+2gsRYUHEw30fOIrg/x+9IO3SisBwUHk6Awi2gHhX1ph4TotaDiEI3kRak3D8Ajc6G9FdIdmZ2T7kiO/8Gc5PxScKiihpt4nBpqqaQqo3MqqaKGWm5iJVXUFL1DdH3QWAsKDiZBYRYKDgp70w4aa0HBwXQTPY/o+hC/L+3QjcJ6UHAwCQqziHZQ2Jd2SIheCyoOCmR9UWrbtm1cd911NDQ0MHz4cN72trfx3HPP5VVq43LYtznzwXSR7kjO27iiNBzOZx4NTMx4o3ZRSRWjOZXzuKboHaLrg8ZaUHAoBpxPhXNQ2Jt20FgLCg7FQjlkVHR9iN+XduhGYT0oOBQD5ZBPCg4K+9IOCdFrQcVBgawuSu3evZsLL7yQqqoqHn30UX71q1/x9a9/nRNOOCGvUi/fnq1ZDyoOnV8CDrNZRLrP9+/1TycdzObGoneIrg8aa0HBQR3nU2EdFPamHTTWgoJDMVAuGRVdH+L3pR26UVgPCg7qlEs+KTgo7Es7JESvBRUHBbJqwVe/+lUaGxu5++67ueCCCzjttNOYO3cukyZNypvQzjWH7jY/uDUKnbBrTfI8xezQyAxOYWafn60diAoqmci5NDKjaB2i64PGWlBwKAacT4VzUNibdtBYCwoOxUI5ZFR0fYjfl3boRmE9KDgUA+WQTwoOCvvSDgnRa0HFQYWsLko99NBDnHfeeVx11VWMGTOGmTNn8t3vfrffcw4ePEhra+sRj/7Ysy4bo36eZ30O5wo4jGVqXhxOYkrROkTXB421oOBQDDifCuegsDftoLEWFByKhWwzKtt8gvh5RNeH+H1ph24U1oOCQzFQDvmk4KCwL+2QEL0WVBxUyOqi1H/9139xxx13MHnyZH74wx/yyU9+kkWLFnHPPff0ec6SJUuor68//GhsbOy3RvvebIz6eZ6Bs1HaoYbavDgMp65oHaLrg8ZaUHAoBpxPhXNQ2Jt20FgLCg7FQrYZlW0+Qfw8outD/L60QzcK60HBoRgoh3xScFDYl3ZIiF4LKg4qZHVRqrOzk7e//e185StfYebMmXziE5/g4x//OP/0T//U5zmLFy+mpaXl8KO5ubnfGlX5WaNUDX6NSji0kZ9VeoDBr9Joh+j6oLEWFByKAedT4RwU9qYdNNaCgkOxkG1GZZtPED+P6PoQvy/t0I3CelBwKAbKIZ8UHBT2pR0SoteCioMKWV2UGjduHGedddYRP5s2bRpbtmzp85zq6mrq6uqOePTHqPy8my+n51Fw2E5+3s+Xy/NEO0TXB421oOBQDDifCvc8CnvTDhprQcGhWMg2o7LNJ4ifR3R9iN+XduhGYT0oOBQD5ZBPCg4K+9IOCdFrQcVBhawuSl144YWsX3/khxZfeeUVJk6cmDeh0TOhYUa2Zj2ogIaZMHpGcTs008QW1tBJlt8PeYhOOtjM82zlhaJ1iK4PGmtBwaEYcD4VzkFhb9pBYy0oOBQL5ZBR0fUhfl/aoRuF9aDgUAyUQz4pOCjsSzskRK8FFQcVsmrBpz71KZ555hm+8pWvsGHDBu6//37++Z//mYULF+ZVavoicroL/fRFpeGwittJDXKVVlDJKr5R9A7R9UFjLSg4qON8KqyDwt60g8ZaUHAoBsolo6LrQ/y+tEM3CutBwUGdcsknBQeFfWmHhOi1oOKgQFYr4fzzz+fBBx/ke9/7HtOnT+eLX/wit956K/Pnz8+r1KR5MHIipLL8lshUZXLepGtKw2E1y9nFZjpoz+q8DtrZySaeY0XRO0TXB421oOCgjvOpsA4Ke9MOGmtBwaEYKJeMiq4P8fvSDt0orAcFB3XKJZ8UHBT2pR0SoteCioMCWV+e/NCHPsRLL71EW1sba9eu5eMf/3jepYYNh0sfT27alemAUpXJ8ZetTM4vBYd22riNubSxN+MN20E7bezlNubQTlvRO0TXB421oOBQDDifCuegsDftoLEWFByKhXLIqOj6EL8v7dCNwnpQcCgGyiGfFBwU9qUdEqLXgoqDAoP9BOOQM+pMuPJZGDHh0A/6Mj308xETkuPrJ5eWww5eZSmz2M02gD4/e9v1891sYymz2MGGknGIrg8aa0HBwSQozELBQWFv2kFjLSg4mG6i5xFdH+L3pR26UVgPCg4mQWEW0Q4K+9IOCdFrQcUhGtmLUpA0+uq1cNHd0HBO78c0nJP8/uq1QzMYBYcdbOAWprGMBTTT1OsxzTSxjAXcwrS8blQVh+j6oLEWFBxMgsIsFBwU9qYdNNaCgoPpJnoe0fUhfl/aoRuF9aDgYBIUZhHtoLAv7ZAQvRZUHCIZFi0wEMOGw5QFyWPnGtizHtpbk7esjZqS3LW+HBzaaeNp7uFp7qGRGZzEFIZTxwFa+Q3r+9zEpeQQXR801oKCg0lQmIWCg8LetIPGWlBwMN1EzyO6PsTvSzt0o7AeFBxMgsIsoh0U9qUdEqLXgopDFPIXpXoyemb8MBQcmmkqyOZUdoiuDxprQcHBJCjMQsFBYW/aQWMtKDiYbqLnEV0f4velHbpRWA8KDiZBYRbRDgr70g4J0WtBxaGQSH98zxhjjDHGGGOMMcaUJr4oZYwxxhhjjDHGGGMKji9KGWOMMcYYY4wxxpiCk0qn0+lCFmxtbaW+vh5SMGJ8ISsnvPE6pDshVQHHjyt8fTvYQc0huj7A/teANLS0tFBXVxcjQXw+gcY8oh2i69vBDkejkFHOJzuo1LeDloPzKUFhFnawg0p9FYdM8ynuopQxxhyFzEUpY4zpBYm/9BljTC84n4wxqgyUT3Hfvud3StnBDhIO0fWh+yq6DP6XvrJfk3awQ0+kMsr5VPYO0fXtoOXgfEpQmIUd7KBSX8Uh03wKuyh1/FiYv7Xwde+bAPu3JYOJqG8HO6g5RNcHuHd8EpwqROUTaMwj2iG6vh3scDRKGeV8skN0fTtoOTifEhRmYQc7qNRXccg0n3yjc2OMMcYYY4wxxhhTcHxRyhhjjDHGGGOMMcYUHF+UMsYYY4wxxhhjjDEFJ+5G54Ng5xrYsw7a90JVLYyaCqNnlp9DIzMYy1RqqKWNvWxnHc00FdQhug/R9VVwH3RQmIWCg/NJxyEa90CL6HlE1wfnk5KDAu6DDgqziHZwPuk4KFBufZC/KPXmAdi4HF6+HXY1Hfv7hhkwfRFMmgfDhpeuQxU1nM88ZrOIUzh2RW5hDau4ndUsp522IXGI7kN0fRXcBx0UZqHg4HzScYjGPdAieh7R9cH5pOSggPugg8Isoh2cTzoOCpRzH6Q/vrfnFXhgGjz5Udj1Yu/H7Hox+f0D06Dl1dJ0GMNkbmEt13MXEzi712MmcDbXcxe3sJYxnJF3h+g+RNdXwX3QQWEWCg7OJx2HaNwDLaLnEV0fnE9KDgq4DzoozCLawfmk46BAufdB9qLUnlfg+++A/V1fX9jZx4GHfr5/Kzw4K78DUnAYw2Ru5hlO4GRSpKigstfjKqgkRYoTOJmbeTavwRXdh+j6KrgPOijMQsHB+aTjEI17oEX0PKLrg/NJyUEB90EHhVlEOzifdBwUcB9EL0q9eQAemQvtrZDuyOycdEdy/A/mJOeXgkMVNdzE49RQSyVVGZ1TSRU11HITK6miJmeH6D5E11fBfdBBYRYKDs4nHYdo3AMtoucRXR+cT0oOCrgPOijMItrB+aTjoID7kJDVRalTTz2VVCp1zGPhwoV5ldq4HPZtznwwXaQ7kvM2rigNh/OZRwMTMw6sLiqpYjSnch7X5OwQ3Yfo+iq4D5lRiIxSmIWCg/NJxyEa9yAzyuU1VHR9cD4pOSjgPgxMueSTgoPzScdBAfchIauLUqtXr+b1118//Fi5ciUAV111VV6lXr49W7MeVBw6vwQcZrOIdJ/v3+ufTjqYzY05O0T3Ibq+Cu5DZhQioxRmoeDgfNJxiMY9yIxyeQ0VXR+cT0oOCrgPA1Mu+aTg4HzScVDAfUjIqgUnnngiY8eOPfx4+OGHmTRpEhdddFHehHauOXS3+cHtVeiEXWuS5ylmh0ZmcAoz+/yM8UBUUMlEzqWRGYN2iO5DdH0V3IfMGeqMUpiFgoPzScchGvcgc8rhNVR0fXA+KTko4D5kRjnkk4KD80nHQQH3oZtB31Pqd7/7Hffeey8f/ehHSaVSfR538OBBWltbj3j0x551gzU66nnW53CugMNYpubF4SSmDPrc6D5E11fBfRgcmWSU82lwOJ90HKJxDwbHUOQTxM8juj44n5QcFHAfsqdU80nBwfmk46CA+9DNoC9Kff/732fPnj0sWLCg3+OWLFlCfX394UdjY2O/x7fvHazRUc8zcDZKO9RQmxeH4dQN+tzoPkTXV8F9GByZZJTzaXA4n3QconEPBsdQ5BPEzyO6PjiflBwUcB+yp1TzScHB+aTjoID70M2gL0rdeeedXHLJJYwfP77f4xYvXkxLS8vhR3Nzc7/HV+Vnr1I1+L0q4dBGflbpAQa/SqP7EF1fBfdhcGSSUc6nweF80nGIxj0YHEORTxA/j+j64HxSclDAfcieUs0nBQfnk46DAu5DN8MGc9LmzZv50Y9+xL/9278NeGx1dTXV1dUZP/eo/LyrMafnUXDYTn7ez5fL80T3Ibq+Cu5D9mSaUc6nweF80nGIxj3InqHKJ4ifR3R9cD4pOSjgPmRHKeeTgoPzScdBAfehm0G9U+ruu+9mzJgxXHbZZfn2YfRMaJhBTnehb5gJo2cUt0MzTWxhDZ1k+f2Qh+ikg808z1ZeGLRDdB+i66vgPmTPUGWUwiwUHJxPOg7RuAfZU8qvoaLrg/NJyUEB9yE7SjmfFBycTzoOCrgP3WTdgs7OTu6++25uuOEGhg0b1ButBmT6InK6C/30RaXhsIrbSQ1ylVZQySq+kbNDdB+i66vgPmTOUGeUwiwUHJxPOg7RuAeZUw6voaLrg/NJyUEB9yEzyiGfFBycTzoOCrgPCVnviB/96Eds2bKFj370o0PhA8CkeTByIqSy/LbMVGVy3qRrSsNhNcvZxWY6aM/qvA7a2ckmnmNFzg7RfYiur4L7kDlDnVEKs1BwcD7pOETjHmROObyGiq4PziclBwXch8woh3xScHA+6Tgo4D4kZH1Rau7cuaTTac4888yh8AFg2HC49PHkpl2ZDihVmRx/2crk/FJwaKeN25hLG3szDq4O2mljL7cxh3bacnaI7kN0fRXch8wZ6oxSmIWCg/NJxyEa9yBzyuE1VHR9cD4pOSjgPmRGOeSTgoPzScdBAfchYdDfvjfUjDoTrnwWRkw49IO+TA/9fMSE5Pj6yaXlsINXWcosdrMNoM/PIHf9fDfbWMosdrAhbw7RfYiur4L7oIPCLBQcnE86DtG4B1pEzyO6PjiflBwUcB90UJhFtIPzScdBAfdB+KIUJI2+ei1cdDc0nNP7MQ3nJL+/eu3QDEbBYQcbuIVpLGMBzTT1ekwzTSxjAbcwLa+B1UV0H6Lrq+A+6KAwCwUH55OOQzTugRbR84iuD84nJQcF3AcdFGYR7eB80nFQoNz7MDR3scsjw4bDlAXJY+ca2LMe2luTt6yNmpLctb4cHNpp42nu4WnuoZEZnMQUhlPHAVr5Dev7DLN8Et2H6PoquA86KMxCwcH5pOMQjXugRfQ8ouuD80nJQQH3QQeFWUQ7OJ90HBQo5z7IX5TqyeiZ8cNQcGimqSAh1R/RfYiur4L7oIPCLBQcnE86DtG4B1pEzyO6PjiflBwUcB90UJhFtIPzScdBgXLrg/TH94wxxhhjjDHGGGNMaeKLUsYYY4wxxhhjjDGm4PiilDHGGGOMMcYYY4wpOKl0Op0uZMHW1lbq6+shBSPGF7JywhuvQ7oTUhVw/LjC17eDHdQcousD7H8NSENLSwt1dXUxEsTnE2jMI9ohur4d7HA0ChnlfLKDSn07aDk4nxIUZmEHO6jUV3HINJ/iLkoZY8xRyFyUMsaYXpD4S58xxvSC88kYo8pA+RT37Xt+p5Qd7CDhEF0fuq+iy+B/6Sv7NWkHO/REKqOcT2XvEF3fDloOzqcEhVnYwQ4q9VUcMs2nsItSx4+F+VsLX/e+CbB/WzKYiPp2sIOaQ3R9gHvHJ8GpQlQ+gcY8oh2i69vBDkejlFHOJztE17eDloPzKUFhFnawg0p9FYdM88k3OjfGGGOMMcYYY4wxBccXpYwxxhhjjDHGGGNMwfFFKWOMMcYYY4wxxhhTcOJudD4Idq6BPeugfS9U1cKoqTB6Zvk5NDKDsUylhlra2Mt21tFMU0EdFPpgjBIKe0LBwflkjCbR+yK6PjifjFFFYV9EOzifTDkjf1HqzQOwcTm8fDvsajr29w0zYPoimDQPhg0vXYcqajifecxmEadwbDpsYQ2ruJ3VLKedtiFxUOiDMUoo7AkFB+eTMZpE74vo+uB8MkYVhX0R7eB8MiZB+uN7e16BB6bBkx+FXS/2fsyuF5PfPzANWl4tTYcxTOYW1nI9dzGBs3s9ZgJncz13cQtrGcMZeXdQ6IMxSijsCQUH55MxmkTvi+j64HwyRhWFfRHt4HwyphvZi1J7XoHvvwP2d319YWcfBx76+f6t8OCs/G4WBYcxTOZmnuEETiZFigoqez2ugkpSpDiBk7mZZ/MaXAp9MEYJhT2h4OB8MkaT6H0RXR+cT8aoorAvoh2cT8YcieRFqTcPwCNzob0V0h2ZnZPuSI7/wZzk/FJwqKKGm3icGmqppCqjcyqpooZabmIlVdTk7KDQB2OUUNgTCg7OJ2M0id4X0fXB+WSMKgr7ItrB+WTMsWR1Uaqjo4P/7//7/zjttNMYPnw4kyZN4otf/CLpdDqvUhuXw77NmW+SLtIdyXkbV5SGw/nMo4GJGQdWF5VUMZpTOY9rcnZQ6IMxmeB8KqyD88mY7CiXjIquD84nY7KlXPJJwcH5ZMyxZHVR6qtf/Sp33HEH3/zmN1m7di1f/epX+bu/+zu+8Y1v5FXq5duzNetBxaHzS8BhNotI9/leyv7ppIPZ3Jizg0IfjMkE51NhHZxPxmRHuWRUdH1wPhmTLeWSTwoOzidjjiWr5fizn/2MK664gssuu4xTTz2V//bf/htz587l5z//ed6Edq45dOf/we1V6IRda5LnKWaHRmZwCjP7/IzxQFRQyUTOpZEZg3ZQ6IMxmeJ8KpyD88mY7CmHjIquD84nYwZDOeSTgoPzyZjeyeqi1Lve9S5+/OMf88orrwDwwgsv8NOf/pRLLrmkz3MOHjxIa2vrEY/+2LMuG6N+nmd9DucKOIxlal4cTmLKoM9V6IMxmeJ8KpyD88mY7Mk2o7LNJ4jfF9H1wflkzGAoh3xScHA+GdM7w7I5+Oabb6a1tZWpU6dSWVlJR0cHX/7yl5k/f36f5yxZsoTPf/7zGddo35uNUT/PM3A2SjvUUJsXh+HUDfpchT4YkynOp8I5OJ+MyZ5sMyrbfIL4fRFdH5xPxgyGcsgnBQfnkzG9k9U7pR544AHuu+8+7r//fn7xi19wzz338Pd///fcc889fZ6zePFiWlpaDj+am5v7rVGVn71K1eD3qoRDG/lJjAMMPjEU+mBMpjifCufgfDIme7LNqGzzCeL3RXR9cD4ZMxjKIZ8UHJxPxvROVu+U+sxnPsPNN9/MvHnzAHjb297G5s2bWbJkCTfccEOv51RXV1NdXZ1xjVH5eVdjTs+j4LCd/Ly3MpfnUeiDMZnifCrc8zifjMmebDMq23yC+H0RXR+cT8YMhnLIJwUH55MxvZPVO6XeeOMNKiqOPKWyspLOzsHeKe1YRs+EhhnZmvWgAhpmwugZxe3QTBNbWEMnWX5X5yE66WAzz7OVFwbtoNAHYzLF+VQ4B+eTMdlTDhkVXR+cT8YMhnLIJwUH55MxvZPVcrz88sv58pe/zA9+8AM2bdrEgw8+yD/8wz9w5ZVX5lVq+iJy+kaA6YtKw2EVt5MaZGJUUMkqcv8aV4U+GJMJzqfCOjifjMmOcsmo6PrgfDImW8olnxQcnE/GHEtWO+Ib3/gG/+2//Tf+7M/+jGnTpvGXf/mX/Mmf/Alf/OIX8yo1aR6MnAipLL8tM1WZnDfpmtJwWM1ydrGZDtqzOq+DdnayiedYkbODQh+MyQTnU2EdnE/GZEe5ZFR0fXA+GZMt5ZJPCg7OJ2OOJauLUrW1tdx6661s3ryZAwcOsHHjRr70pS9x3HHH5VVq2HC49PHkBmqZbpZUZXL8ZSuT80vBoZ02bmMubezNOLg6aKeNvdzGHNppy9lBoQ/GZILzqbAOzidjsqNcMiq6PjifjMmWcsknBQfnkzHHMthPkw45o86EK5+FERMO/aAv00M/HzEhOb5+cmk57OBVljKL3WwD6PMzyF0/3802ljKLHWzIm4NCH4xRQmFPKDg4n4zRJHpfRNcH55Mxqijsi2gH55MxRyJ7UQqSRX/1Wrjobmg4p/djGs5Jfn/12qHZJAoOO9jALUxjGQtopqnXY5ppYhkLuIVpeQ2sLhT6YIwSCntCwcH5ZIwm0fsiuj44n4xRRWFfRDs4n4zpZli0wEAMGw5TFiSPnWtgz3pob03ePjhqSvINAuXg0E4bT3MPT3MPjczgJKYwnDoO0MpvWN9nmOUThT4Yo4TCnlBwcD4Zo0n0voiuD84nY1RR2BfRDs4nYxLkL0r1ZPTM+I2h4NBMU0FCqj8U+mCMEgp7QsHB+WSMJtH7Iro+OJ+MUUVhX0Q7OJ9MOSP98T1jjDHGGGOMMcYYU5r4opQxxhhjjDHGGGOMKTi+KGWMMcYYY4wxxhhjCo4vShljjDHGGGOMMcaYgpNKp9PpQhZsaWlh1KhRABw/rpCVE97YDqSBFBw/tvD17WAHNYfo+gBvvJ783z179lBfXx8jQXw+gcg8vCbtYIcjHQQyyvlkB5X6dhBzcD4BIrOwgx1E6ss4ZJhPBb8otXXrVhobGwtZ0hhTJDQ3NzNhwoSw+s4nY0x/RGaU88kY0x/OJ2OMKgPlU8EvSnV2dvLaa69RW1tLKpXK+vzW1lYaGxtpbm6mrq5uCAztUCwO0fXtkD+HdDrN3r17GT9+PBUVcZ8qdj7ZoZQcouuXkoNCRuWaTxA/j+j6drCDmoPzqZvoWSg4RNe3gx3y7ZBpPg3LRXIwVFRU5OUqfl1dXdhw7KDlEF3fDvlxiPzYXhfOJzuUokN0/VJxiM6ofOUTxM8jur4d7KDm4HzqJnoWCg7R9e1gh3w6ZJJPvtG5McYYY4wxxhhjjCk4vihljDHGGGOMMcYYYwpO0V2Uqq6u5nOf+xzV1dV2KHOH6Pp20HJQQKEPdrCDSn076BHdi+j6drCDmkN0fSUUehHtEF3fDnaIcij4jc6NMcYYY4wxxhhjjCm6d0oZY4wxxhhjjDHGmOLHF6WMMcYYY4wxxhhjTMHxRSljjDHGGGOMMcYYU3CK6qLU008/TWVlJZdddlnBay9YsIBUKnX40dDQwAc/+EFefPHFgrts376dG2+8kdNPP53q6moaGxu5/PLL+fGPfzzktXv2oaqqipNOOok5c+Zw11130dnZOeT1j3bo+fjgBz9YkPoDeWzYsKEg9bdv385NN93EGWecQU1NDSeddBIXXnghd9xxB2+88caQ11+wYAF/8Ad/cMzPn3jiCVKpFHv27BlyBzWcUc6noz2iMio6nyA2o5xPx+J8cj4d7eF88msoFZxPzqejPZxP5ZVPRXVR6s477+TGG2/kqaee4rXXXit4/Q9+8IO8/vrrvP766/z4xz9m2LBhfOhDHyqow6ZNmzj33HP5yU9+wte+9jVeeuklHnvsMWbPns3ChQsL4tDVh02bNvHoo48ye/ZsbrrpJj70oQ/x5ptvFtSh5+N73/teQWoP5HHaaacNed3/+q//YubMmTz++ON85StfYc2aNTz99NP81V/9FQ8//DA/+tGPhtzBHEu5Z5Tz6ViPyIyKyidwRinifHI+He3hfHI+qeB8cj4d7eF8Kq98GhYtkCn79u1jxYoVPPfcc2zfvp1ly5bxP/7H/yioQ3V1NWPHjgVg7Nix3HzzzbznPe/h//2//8eJJ55YEIc/+7M/I5VK8fOf/5wRI0Yc/vlb3/pWPvrRjxbEoWcfTj75ZN7+9rfzjne8g/e9730sW7aMP/7jPy6oQyRRHn/2Z3/GsGHDeO65545YB6effjpXXHEF/lLNwuOMcj715RFFpIMzSgvnk/OpL48onE+mC+eT86kvjyicT4WnaN4p9cADDzB16lSmTJnCddddx1133RU6lH379nHvvfdyxhln0NDQUJCav/3tb3nsscdYuHDhEYu0i1GjRhXEozfe+973cs455/Bv//ZvYQ7lwq5du3j88cf7XAcAqVSqwFam3DPK+WS6cEbp4XxyPpkE55Mezifnk0ko53wqmotSd955J9dddx2QvKWupaWFJ598sqAODz/8MCNHjmTkyJHU1tby0EMPsWLFCioqCtPGDRs2kE6nmTp1akHqZcvUqVPZtGlTQWr1nEXX4ytf+UpBavfncdVVVw15za51MGXKlCN+Pnr06MMef/3Xfz3kHtD7HC655JKC1Faj3DPK+XQkChkVkU+gk1HOp26cT86nnjif4vMJnFFdOJ+cTz1xPpVnPhXFx/fWr1/Pz3/+cx588EEAhg0bxjXXXMOdd97JxRdfXDCP2bNnc8cddwCwe/duvv3tb3PJJZfw85//nIkTJw55ffW366XT6YJdve05iy7e8pa3FKR2fx59XdUuBD//+c/p7Oxk/vz5HDx4sCA1e5vDs88+e/jFRbngjHI+HY1CRinlExQ+o5xPCc4n59PROJ+Oxa+hYnA+OZ+Oxvl0LOWQT0VxUerOO+/kzTffZPz48Yd/lk6nqa6u5pvf/Cb19fUF8RgxYgRnnHHG4f/9P//n/6S+vp7vfve7fOlLXxry+pMnTyaVSrFu3bohrzUY1q5dW7CbwB09iygiPM444wxSqRTr168/4uenn346AMOHDy+YS2///Vu3bi1YfRWcUc6no1HIqCgHlYxyPiU4n5xPR+N8is8ncEaB8wmcT0fjfCrPfJL/+N6bb77Jv/zLv/D1r3+dpqamw48XXniB8ePHh3zjWhepVIqKigoOHDhQkHpvectb+MAHPsC3vvUt9u/ff8zvI78+9ic/+QkvvfQSH/7wh8McyoWGhgbmzJnDN7/5zV7XgSkszqgE55Ppwhmlg/MpwflkunA+6eB8SnA+mS7KOZ/k3yn18MMPs3v3bj72sY8dc7X8wx/+MHfeeSd/+qd/WhCXgwcPsn37diB5a+c3v/lN9u3bx+WXX16Q+gDf+ta3uPDCC7ngggv4whe+wNlnn82bb77JypUrueOOO1i7du2QO3T1oaOjg9/85jc89thjLFmyhA996ENcf/31Q16/p0NPhg0bxujRowtSP5pvf/vbXHjhhZx33nnccsstnH322VRUVLB69WrWrVvHueeeG61YNjijunE+HevRE2eUM6rQOJ+6cT4d69ET55PzqdA4n7pxPh3r0RPnUxnkU1qcD33oQ+lLL7201989++yzaSD9wgsvDLnHDTfckAYOP2pra9Pnn39++n//7/895LWP5rXXXksvXLgwPXHixPRxxx2XPvnkk9O///u/n161atWQ1+7Zh2HDhqVPPPHE9Pvf//70XXfdle7o6Bjy+kc79HxMmTKlIPV7elxxxRUFrdmT1157Lf3nf/7n6dNOOy1dVVWVHjlyZPqCCy5If+1rX0vv379/yOv39d+/atWqNJDevXv3kDso4Iw6knLPp6M9ojIqOp/S6diMcj4lOJ+OxPnkfOrCr6HicT4difPJ+dRFOeZTKp0Wv7uaMcYYY4wxxhhjjCk55O8pZYwxxhhjjDHGGGNKD1+UMsYYY4wxxhhjjDEFxxeljDHGGGOMMcYYY0zB8UUpY4wxxhhjjDHGGFNwfFHKGGOMMcYYY4wxxhQcX5QyxhhjjDHGGGOMMQXHF6WMMcYYY4wxxhhjTMHxRSljjDHGGGOMMcYYU3B8UcoYY4wxxhhjjDHGFBxflCoy/umf/ona2lrefPPNwz/bt28fVVVVXHzxxUcc+8QTT5BKpdi4cSMAf/Inf8KkSZMYPnw4J554IldccQXr1q074pxFixZx7rnnUl1dzYwZM7JyO+200/jRj37U6+/++Z//mYsvvpi6ujpSqRR79uw54vebNm3iYx/7GKeddhrDhw9n0qRJfO5zn+N3v/tdzrVPPfVUUqkUqVSKyspKxo8fz8c+9jF27959+JgnnniCK664gnHjxjFixAhmzJjBfffdd8Tz/PKXv+TDH/7w4ee79dZbM3IzppwY6oxavXo173vf+xg1ahQnnHACH/jAB3jhhRcycsslowC+/OUv8653vYvjjz+eUaNGZVSzi9mzZ/M//+f/7PV3F1988eGMSqVSnHTSSVx11VVs3rz5iOMGyudNmzYd8Txdj2eeeSYrV2NKlaHOpy527drFhAkT+sySozlw4AAjRoxgw4YNvf4+k+zZsmULl112GccffzxjxozhM5/5zBH/nYOt3TNLhg0bximnnMKnP/1pDh48ePiYf/u3f2POnDmceOKJ1NXV8c53vpMf/vCHxzzXt771LU499VRqamqYNWsWP//5zwf0M6acySWzukin01xyySWkUim+//3vH/75Cy+8wLXXXktjYyPDhw9n2rRp3HbbbRl5DZQbv/jFL5gzZw6jRo2ioaGBT3ziE+zbty+j5y7E66X169cze/ZsTjrpJGpqajj99NP57Gc/S3t7e0aOJv/4olSRMXv2bPbt28dzzz13+Gf/8R//wdixY3n22Wdpa2s7/PNVq1ZxyimnMGnSJADOPfdc7r77btauXcsPf/hD0uk0c+fOpaOj44gaH/3oR7nmmmuy8nrxxRfZvXs3F110Ua+/f+ONN/jgBz/I//gf/6PX369bt47Ozk6+853v8Mtf/pJ//Md/5J/+6Z/6PD6b2gBf+MIXeP3119myZQv33XcfTz31FIsWLTr8+5/97GecffbZ/J//83948cUX+chHPsL111/Pww8/fMR/w+mnn87SpUsZO3bsgF7GlCNDmVH79u3jgx/8IKeccgrPPvssP/3pT6mtreUDH/jAgC8kcs0ogN/97ndcddVVfPKTn8y4HwC//e1v+c///E8uv/zyPo/5+Mc/zuuvv85rr73Gv//7v9Pc3Mx11113zHGZ5POPfvQjXn/99cOPc889NytfY0qVQryGAvjYxz7G2WefnbHXypUrmThxImeccUavvx8oezo6Orjsssv43e9+x89+9jPuueceli1bxt/+7d/mXBvg7rvv5vXXX+fXv/413/72t/lf/+t/8aUvfenw75966inmzJnDI488wvPPP8/s2bO5/PLLWbNmzeFjVqxYwac//Wk+97nP8Ytf/IJzzjmHD3zgA+zYsWNAR2PKlVwyq4tbb72VVCp1zHM///zzjBkzhnvvvZdf/vKX/M3f/A2LFy/mm9/85oBe/eXGa6+9xvvf/37OOOMMnn32WR577DF++ctfsmDBggGft1Cvl6qqqrj++ut5/PHHWb9+Pbfeeivf/e53+dznPjegoxki0qboGDduXHrJkiWH//df/dVfpRcuXJieNm1aetWqVYd//nu/93vpG264oc/neeGFF9JAesOGDcf87nOf+1z6nHPOydjpC1/4Qvqaa64Z8LhVq1algfTu3bsHPPbv/u7v0qeddlrOtSdOnJj+x3/8xyN+9sUvfjF91lln9fu8l156afojH/lIxs9pjEkYqoxavXp1Gkhv2bLl8DEvvvhiGki/+uqr/TrlM6PuvvvudH19/YDP1cW//Mu/pGfNmtXn7y+66KL0TTfddMTP/tf/+l/p448/vtfj+8rnX//612kgvWbNmozdjCk3hvo11Le//e30RRddlP7xj3+c8eudj370o+m//uu/HvC4vrLnkUceSVdUVKS3b99++Gd33HFHuq6uLn3w4MGcagPpBx988IiffexjH0tfeuml/T7vWWedlf785z9/+H9fcMEF6YULFx7+3x0dHenx48cfMQtjzLHkkllr1qxJn3zyyenXX3+91718NH/2Z3+Wnj179oBO/eXGd77znfSYMWPSHR0dh3+W6Wu1Qr1e6o1PfepT6Xe/+90ZHWvyj98pVYTMnj2bVatWHf7fq1at4uKLL+aiiy46/PMDBw7w7LPPMnv27F6fY//+/dx9992cdtppNDY25uz00EMPccUVV+T8PD1paWnhLW95S95rb9u2jf/7f/8vs2bNykt9Y8yRDFVGTZkyhYaGBu68805+97vfceDAAe68806mTZvGqaee2q/TUGRUpmRb+7e//S0PPPDAgBnVF7//+7/PmDFjePe7381DDz00qOcwplQZytdQv/rVr/jCF77Av/zLv1BRkdlL7M7OTh5++OGc8unpp5/mbW97GyeddNLhn33gAx+gtbWVX/7yl3mt/corr/CTn/yk33zq7Oxk7969h19D/e53v+P555/n/e9//+FjKioqeP/738/TTz+dcW1jypHBZtYbb7zBH/7hH/Ktb30r4094ZPJ3n4Fy4+DBgxx33HFHZODw4cMB+OlPf9rvcxf69VIXGzZs4LHHHuv3UzdmaPFFqSJk9uzZ/Od//idvvvkme/fuZc2aNVx00UX83u/9Hk888QSQvEA5ePDgMS+ovv3tbzNy5EhGjhzJo48+ysqVKznuuONy8tm2bRsvvvgil1xySU7P05MNGzbwjW98gz/5kz/JS+2//uu/ZuTIkQwfPvzwfR7+4R/+oc/jH3jgAVavXs1HPvKRQfkbU84MVUbV1tbyxBNPcO+99zJ8+HBGjhzJY489xqOPPsqwYcP69BmKjMqUgwcP8thjj/H7v//7/R7X9d89YsQIGhoaWL9+PXfddVdWtUaOHMnXv/51/vVf/5Uf/OAHvPvd7+YP/uAPfGHKmB4MVT4dPHiQa6+9lq997WuccsopGft03fMtl79Ubd++/YgLUsDh/719+/aca1977bWMHDmSmpoapkyZwlvf+lYWL17c5/F///d/z759+7j66qsB2LlzJx0dHb069udnjBl8Zn3qU5/iXe96V8YXeX72s5+xYsUKPvGJT/R73EC58d73vpft27fzta99jd/97nfs3r2bm2++GYDXX3+9z+ct5OulLt71rndRU1PD5MmTec973sMXvvCFQT2PyR1flCpCLr74Yvbv38/q1av5j//4D84880xOPPFELrroosOfL37iiSc4/fTTj3lhNH/+fNasWcOTTz7JmWeeydVXX33E55EHw0MPPcS73/3urG/82xfbtm3jgx/8IFdddRUf//jH81L7M5/5DE1NTbz44ov8+Mc/BuCyyy7r9V4Qq1at4iMf+Qjf/e53eetb3zro/w5jypWhyqgDBw7wsY99jAsvvJBnnnmG//zP/2T69OlcdtllHDhwoE+ffGdUNvzkJz9hzJgxA2bJ/PnzaWpq4oUXXuCnP/0pZ5xxBnPnzmXv3r0Z1xo9ejSf/vSnmTVrFueffz5Lly7luuuu42tf+1qu/xnGlAxDlU+LFy9m2rRpvd7bpD/+/d//nQ996EMZv7Mqn2Ra+x//8R8P59PDDz/MK6+8wh/90R/1euz999/P5z//eR544AHGjBkzFNrGlBWDyayHHnqIn/zkJxl/KdPLL7/MFVdcwec+9znmzp3b77ED5cZb3/pW7rnnHr7+9a9z/PHHM3bsWE477TROOumkfrOmkK+XulixYgW/+MUvuP/++/nBD37A3//932f9HCY/9P1Py0aWM844gwkTJrBq1aojbtw7fvx4Ghsb+dnPfsaqVat473vfe8y59fX11NfXM3nyZN7xjndwwgkn8OCDD3LttdcO2uehhx4a8Kp2prz22mvMnj2bd73rXfzzP/9z3mqPHj368M34Jk+ezK233so73/lOVq1adcTbyZ988kkuv/xy/vEf/5Hrr79+8P8hxpQxQ5VR999/P5s2beLpp58+/MLm/vvv54QTTuDf//3fmTdvXq8++cyobMm0dn19/eGMOuOMM7jzzjsZN24cK1as4I//+I8HXX/WrFmsXLly0OcbU2oMVT795Cc/4aWXXuJ//+//DSTfeAXJ64+/+Zu/4fOf/3yvPg899BBLly7N6b9p7Nixx3yT3W9+85vDv+uLTGuPHTv2cD5NmTKFvXv3cu211/KlL33piBsdL1++nD/+4z/mX//1X494bTV69GgqKysPO/V09BfHGNM/g8msn/zkJ2zcuPGYf4z78Ic/zHve857D77CC5GPH73vf+/jEJz7BZz/72QF9MsmNP/zDP+QP//AP+c1vfsOIESMOf0Ll9NNP7/d5C/16qevj12eddRYdHR184hOf4L//9/9OZWVlVs9jcsfvlCpSZs+ezRNPPMETTzxxxFeC/t7v/R6PPvooP//5z/u8F0IX6XSadDp9xNf6Zsu+fftYtWpVXu7Vsm3bNi6++OLD33Az0L/c5VK7K2x6vrviiSee4LLLLuOrX/3qgG9dNcb0z1Bk1BtvvEFFRcUR3yLT9b87Ozt7fY58ZlS2pNNp/u///b95y6jB0NTUxLhx43J6DmNKjaHIp//zf/4PL7zwAk1NTTQ1NR3+SvP/+I//YOHChb0+x6uvvsrmzZuZM2dOTv8973znO3nppZeO+Ca7lStXUldXx1lnnZX32r3l0/e+9z0+8pGP8L3vfY/LLrvsiOOPO+44zj333MPvVIfkvjQ//vGPeec735l1fWPKjWwz6+abb+bFF188nEdNTU1A8q7Hu++++/Bxv/zlL5k9ezY33HADX/7ylwf0yDY3TjrpJEaOHMmKFSuoqanp8zyF10udnZ20t7f3+XrSDC1+p1SRMnv2bBYuXEh7e/sRN2W76KKL+PM//3N+97vfHRFO//Vf/8WKFSuYO3cuJ554Ilu3bmXp0qUMHz6cSy+99PBxGzZsYN++fWzfvp0DBw4cDrGzzjqr13tPPfbYY5x55pkD3mR4+/btbN++nQ0bNgDw0ksvUVtbyymnnMJb3vKWwxekJk6cyN///d/z//7f/zt8bl//ipZpbYC9e/eyfft20uk0zc3N/NVf/RUnnngi73rXu4DkI3sf+tCHuOmmm/jwhz98+B4Hxx133BE36vzVr351+P/ftm0bTU1NjBw5st+vUjamHBmKjJozZw6f+cxnWLhwITfeeCOdnZ0sXbqUYcOG9fkXyHxlFMCWLVv47W9/y5YtW+jo6Dicj2eccQYjR4485jmff/553njjDd797ncP2K833njjcO785je/4Ytf/CI1NTVHvI1+oHy+5557OO6445g5cyYA//Zv/8Zdd911+C/HxpiEocino7+GfefOnQBMmzatz48O//u//zvvf//7Of744/v1HSh75s6dy1lnncUf/dEf8Xd/93ds376dz372syxcuJDq6uqcagPs2bOH7du309nZyauvvsoXvvAFzjzzTKZNmwYk71i94YYbuO2225g1a9bhLBs+fDj19fUAfPrTn+aGG27gvPPO44ILLuDWW29l//79vnenMRmQbWaNHTu2178/nXLKKZx22mlA8pG99773vXzgAx/g05/+9OF9W1lZyYknntirR6a58c1vfpN3vetdjBw5kpUrV/KZz3yGpUuX9pmFhX69dN9991FVVcXb3vY2qquree6551i8eDHXXHMNVVVVAzqYISDqa/9MbnR99ffUqVOP+PmmTZvSQHrKlClH/Hzbtm3pSy65JD1mzJh0VVVVesKECek//MM/TK9bt+6I4y666KI0cMzj17/+da8e1113Xfpv/uZvBvT93Oc+1+vz3n333el0Ovma495+398SzbT2xIkTj3i+E088MX3ppZce8bXpN9xwQ6+1L7roosPHdPW8v2OMMQlDlVGPP/54+sILL0zX19enTzjhhPR73/ve9NNPP92nR74yKp3uOyd6fiVzTz772c+m58+fP2Dto3P3hBNOSF900UXpn/zkJ/0ed3Q+L1u2LD1t2rT08ccfn66rq0tfcMEF6X/9138dsL4x5cZQ5VNPVq1alQbSu3fv7vOYd7/73envfve7A/pmkj2bNm1KX3LJJenhw4enR48enf7v//2/p9vb23Ou3bNeKpVKjxs3Ln3NNdekN27cePiYvrLp6K+n/8Y3vpE+5ZRT0scdd1z6ggsuSD/zzDMD1jfGZJ9ZvQGkH3zwwcP/u6/XPRMnTuzzOTLNjT/6oz9Kv+Utb0kfd9xx6bPPPjv9L//yL/0eX+jXS8uXL0+//e1vT48cOTI9YsSI9FlnnZX+yle+kj5w4MCADmZoSKXThz70bkyWvPnmm5x00kk8+uijXHDBBWVT2xhTHETnxNlnn81nP/vZw99AZYwxXezcuZNx48axdevWY76VrpRrG2OKk6HMDb9eMr6nlBk0v/3tb/nUpz7F+eefX1a1jTHFQWRO/O53v+PDH/4wl1xyScFrG2P0+e1vf8s//MM/hFwUiqxtjClOhio3/HrJAPidUsYYY4wxxhhjjDGm4PidUsYYY4wxxhhjjDGm4PiilDHGGGOMMcYYY4wpOL4oZYwxxhhjjDHGGGMKji9KGWOMMcYYY4wxxpiC44tSxhhjjDHGGGOMMabg+KKUMcYYY4wxxhhjjCk4vihljDHGGGOMMcYYYwqOL0oZY4wxxhhjjDHGmILji1LGGGOMMcYYY4wxpuD4opQxxhhjjDHGGGOMKTi+KGWMMcYYY4wxxhhjCo4vShljjDHGGGOMMcaYguOLUsYYY4wxxhhjjDGm4PiilDHGGGOMMcYYY4wpOMMKXbCzs5PXXnuN2tpaUqlUocsbYwRJp9Ps3buX8ePHU1ERd63c+WSM6Q2FjHI+GWN6w/lkjFEl03wq+EWp1157jcbGxkKXNcYUAc3NzUyYMCGsvvPJGNMfkRnlfDLG9IfzyRijykD5VPCLUrW1tYf//+PHFbo6vLEdSAMpOH5s4evbwQ5qDtH1Ad54Pfm/PfMhguh8ApF5eE3awQ5HOghklPPJDir17SDm4HwCRGZhBzuI1JdxyDCfCn5RqustncePg+teK3R1uG8C7N8GI8bD/K2Fr28HO6g5RNcHuHd8ElrRb/mOzifQmEe0Q3R9O9jhaBQyyvlkB5X6dtBycD4lKMzCDnZQqa/ikGk++UbnxhhjjDHGGGOMMabg+KKUMcYYY4wxxhhjjCk4vihljDHGGGOMMcYYYwpOwe8plQs718CeddC+F6pqYdRUGD3TDuXoEF1fxUEB9yFBoQ92sINKfRXch26iexFd3w52UMM96EahF9EO0fXtoOWgQCH7IH9R6s0DsHE5vHw77Go69vcNM2D6Ipg0D4YNt0MpO0TXV3FQwH1IUOiDHeygUl8F96Gb6F5E17eDHdRwD7pR6EW0Q3R9O2g5KBDVB+mP7+15BR6YBk9+FHa92Psxu15Mfv/ANGh51Q6l6hBdX8VBAfchQaEPdrCDSn0V3IduonsRXd8OdlDDPehGoRfRDtH17aDloEBkH2QvSu15Bb7/Dtjf9fWFnX0ceOjn+7fCg7Py2xw7aDhE11dxUMB9SFDogx3soFJfBfehm+heRNe3gx3UcA+6UehFtEN0fTtoOSgQ3YesL0o99dRTXH755YwfP55UKsX3v//9/Jj04M0D8MhcaG+FdEdm56Q7kuN/MCc53w6l4RBdX8VBgWLog/PJDuXmEF1fhWLoQyHyCeJ7EV3fDnZQoxh6UC75pOAQXd8OWg4KKPQh64tS+/fv55xzzuFb3/pW7tX7YONy2Lc586Z0ke5Iztu4wg6l4hBdX8VBgWLog/PJDuXmEF1fhWLoQyHyCeJ7EV3fDnZQoxh6UC75pOAQXd8OWg4KKPQh64tSl1xyCV/60pe48sorc6/eBy/fzuA/WFhx6Hw7lIRDdH0VBwWKoQ/OJzuUm0N0fRWKoQ+FyCeI70V0fTvYQY1i6EG55JOCQ3R9O2g5KKDQh8GWHzJ2rjl0p/e+Psc4EJ2wa03yPHYobofo+ioOCrgPCQp9sIMdVOqr4D50E92L6Pp2sIMa7kE3Cr2IdoiubwctBwVU+jDkF6UOHjxIa2vrEY/+2LMuP3X3rM/hXDtIOETXV3FQoFT74HyyQzE7RNdXoVT7kG0+QXwvouvbwQ5qlGoPijGfFByi69tBy0EBlT4M+UWpJUuWUF9ff/jR2NjY7/Hte/NTt33gbLSDuEN0fRUHBUq1D84nOxSzQ3R9FUq1D9nmE8T3Irq+HeygRqn2oBjzScEhur4dtBwUUOnDkF+UWrx4MS0tLYcfzc3N/R5fVZufulV1OZxrBwmH6PoqDgqUah+cT3YoZofo+iqUah+yzSeI70V0fTvYQY1S7UEx5pOCQ3R9O2g5KKDSh2H50eib6upqqqurMz5+1NT81M3leeyg4RBdX8VBgVLtg/PJDsXsEF1fhVLtQ7b5BPG9iK5vBzuoUao9KMZ8UnCIrm8HLQcFVPqQ9Tul9u3bR1NTE01NTQD8+te/pqmpiS1btuRmcojRM6FhxmDMDlEBDTNh9Aw7FLtDdH0VBwWKpQ/OJzuUk0N0fRWKpQ9DnU8Q34vo+nawgxrF0oNyyCcFh+j6dtByUEClD1mXf+6555g5cyYzZ84E4NOf/jQzZ87kb//2b3Mz6cH0ReR0B/jpi+xQKg7R9VUcFCiGPjif7FBuDtH1VSiGPhQinyC+F9H17WAHNYqhB+WSTwoO0fXtoOWggEIfsr4odfHFF5NOp495LFu2LHebQ0yaByMnQqoyu/NSlcl5k66xQ6k4RNdXcVCgGPrgfLJDuTlE11ehGPpQiHyC+F5E17eDHdQohh6USz4pOETXt4OWgwIKfRjyG50PhmHD4dLHkxtmZdqcVGVy/GUrk/PtUBoO0fVVHBRwHxIU+mAHO6jUV8F96Ca6F9H17WAHNdyDbhR6Ee0QXd8OWg4KKPRB8qIUwKgz4cpnYcSEQz/oy/TQz0dMSI6vn2yHUnOIrq/ioID7kKDQBzvYQaW+Cu5DN9G9iK5vBzuo4R50o9CLaIfo+nbQclAgug+yF6Ug+Y+8ei1cdDc0nNP7MQ3nJL+/eu3QLA47aDhE11dxUMB9SFDogx3soFJfBfehm+heRNe3gx3UcA+6UehFtEN0fTtoOSgQ2Ydh+XuqoWHYcJiyIHnsXAN71kN7a/J2sVFTkjvG26E8HKLrqzgo4D4kKPTBDnZQqa+C+9BNdC+i69vBDmq4B90o9CLaIbq+HbQcFIjqg/xFqZ6Mnhm/IOyg4RBdX8VBAfchQaEPdrCDSn0V3IduonsRXd8OdlDDPehGoRfRDtH17aDloEAh+yD98T1jjDHGGGOMMcYYU5r4opQxxhhjjDHGGGOMKTi+KGWMMcYYY4wxxhhjCk4qnU6nC1mwtbWV+vp6SMGI8YWsnPDG65DuhFQFHD+u8PXtYAc1h+j6APtfA9LQ0tJCXV1djATx+QQa84h2iK5vBzscjUJGOZ/soFLfDloOzqcEhVnYwQ4q9VUcMs2nuItSxhhzFDIXpYwxphck/tJnjDG94HwyxqgyUD7Fffue3yllBztIOETXh+6r6DL4X/rKfk3awQ49kcoo51PZO0TXt4OWg/MpQWEWdrCDSn0Vh0zzKeyi1PFjYf7Wwte9bwLs35YMJqK+Heyg5hBdH+De8UlwqhCVT6Axj2iH6Pp2sMPRKGWU88kO0fXtoOXgfEpQmIUd7KBSX8Uh03zyjc6NMcYYY4wxxhhjTMHxRSljjDHGGGOMMcYYU3B8UcoYY4wxxhhjjDHGFJy4G50Pgp1rYM86aN8LVbUwaiqMnll+Do3MYCxTqaGWNvaynXU001RWDgpzsIOOgwIKfVBwiM4GFYfoWUTXt4Me0b2Irg8a2aDgoDALO8TXV0KhF9EOCtmg4BA9BzvEOMhflHrzAGxcDi/fDruajv19wwyYvggmzYNhw0vXoYoazmces1nEKRy7GrawhlXczmqW005bSToozMEOOg4KKPRBwSE6G1QcomcRXd8OekT3Iro+aGSDgoPCLOwQX18JhV5EOyhkg4JD9BzsEO+QSqfTBf0S0dbWVurr6zl+HFz3Wv/H7nkFHpkL+zaTfNCws5eDDv185ES4bCXUT+7/ObvuQj/i5MzuQq/gMIbJ3MTjNDCRNJ1UUHnMMZ10kKKCXWzmNuawgw0l5TAUc7BD9vWHyqHrmxlaWlqoq6sbWGKIiM4niF8P2TpEZ4OKQ/TeVFgLpeygkFHZ5BN4TcLQZIOCQ7Hlkx2Grj44n7ootvVQqvmUrYPCnxXRa6GUHTLNJ9l7Su15Bb7/Dtjf1cDemtLj5/u3woOzoOXV0nIYw2Ru5hlO4GRSpHoNC4AKKkmR4gRO5maeZQxnlIyDwhzsoOOggEIfFByis0HFIXoW0fXtoEd0L6Lrg0Y2KDgozMIO8fWVUOhFtINCNig4RM/BDjoOWV2UWrJkCeeffz61tbWMGTOGP/iDP2D9+vX5MenBmweSq3TtrZDuyOycdEdy/A/mJOeXgkMVNdzE49RQSyVVGZ1TSRU11HITK6mipugdFOZgBx2H/nA+FdYhOhtUHKJnEV3fDplTLhkVXR80skHBQWEWdoivnwnlkk8KDgrZoOAQPQc7aDlkdVHqySefZOHChTzzzDOsXLmS9vZ25s6dy/79+3M36cHG5cnbxjJtShfpjuS8jStKw+F85tHAxIzDootKqhjNqZzHNUXvoDAHO+g49IfzqbAO0dmg4hA9i+j6dsiccsmo6PqgkQ0KDgqzsEN8/Uwol3xScFDIBgWH6DnYQcshq4tSjz32GAsWLOCtb30r55xzDsuWLWPLli08//zzuZv04OXbszXrQcWh80vAYTaLSPf53rn+6aSD2dxY9A4Kc7CDjkN/OJ8K6xCdDSoO0bOIrm+HzCmXjIquDxrZoOCgMAs7xNfPhHLJJwUHhWxQcIiegx20HAZbHkhuWAXwlre8JXeTQ+xcc+hO74PbJ9AJu9Ykz1PMDo3M4BRm9vn53oGooJKJnEsjM4rWQWEOdtBxyBbn09A5RGeDikP0LKLr2yE3SjGjouuDRjYoOCjMwg7x9QdLKeaTgoNCNig4RM/BDloOkMNFqc7OTv7iL/6CCy+8kOnTp/d53MGDB2ltbT3i0R971g3W6KjnyeFj0AoOY5maF4eTmFK0DgpzsIOOQzY4n4bWITobVByiZxFd3w6DJ5OMyjafIL4X0fVBIxsUHBRmYYf4+oOhVPNJwUEhGxQcoudgBy0HyOGi1MKFC3n55ZdZvnx5v8ctWbKE+vr6w4/GxsZ+j2/fO1ijo55n4GyUdqihNi8Owxn8V8NGOyjMwQ46DtngfBpah+hsUHGInkV0fTsMnkwyKtt8gvheRNcHjWxQcFCYhR3i6w+GUs0nBQeFbFBwiJ6DHbQcYJAXpf78z/+chx9+mFWrVjFhwoR+j128eDEtLS2HH83Nzf0eX5WffULV4PeJhEMb+VkhBxj8Col2UJiDHXQcMsX5NPQO0dmg4hA9i+j6dhgcmWZUtvkE8b2Irg8a2aDgoDALO8TXz5ZSzicFB4VsUHCInoMdtBwAhmVzcDqd5sYbb+TBBx/kiSee4LTTThvwnOrqaqqrqzOuMSo/7yjM6XkUHLaTn/fS5fI80Q4Kc7CDjsNAOJ8K9zzR2aDiED2L6Pp2yI5sMyrbfIL4XkTXB41sUHBQmIUd4utnSjnkk4KDQjYoOETPwQ5aDpDlO6UWLlzIvffey/33309tbS3bt29n+/btHDhwIDeLHoyeCQ0zsjXrQQU0zITRM4rboZkmtrCGTrL8bsZDdNLBZp5nKy8UrYPCHOyg4zAQzqfCOURng4pD9Cyi69shO8oho6Lrg0Y2KDgozMIO8fUzpRzyScFBIRsUHKLnYActB7Itf8cdd9DS0sLFF1/MuHHjDj9WrFiRm8VRTF9ETneAn76oNBxWcTupQa6QCipZxTeK3kFhDnbQcegP51NhHaKzQcUhehbR9e2QOeWSUdH1QSMbFBwUZmGH+PqZUC75pOCgkA0KDtFzsIOWQ1arMZ1O9/pYsGBB7iY9mDQPRk6EVJbfVJmqTM6bdE1pOKxmObvYTAftWZ3XQTs72cRz5P4HSbSDwhzsoOPQH86nwjpEZ4OKQ/QsouvbIXPKJaOi64NGNig4KMzCDvH1M6Fc8knBQSEbFByi52AHLYdBf/veUDJsOFz6eHLDrEybk6pMjr9sZXJ+KTi008ZtzKWNvRmHRgfttLGX25hDO21F76AwBzvoOCig0AcFh+hsUHGInkV0fTvoEd2L6PqgkQ0KDgqzsEN8fSUUehHtoJANCg7Rc7CDloPkRSmAUWfClc/CiK4vfujL9NDPR0xIjq+fXFoOO3iVpcxiN9sA+vz8b9fPd7ONpcxiBxtKxkFhDnbQcVBAoQ8KDtHZoOIQPYvo+nbQI7oX0fVBIxsUHBRmYYf4+koo9CLaQSEbFByi52AHHQfZi1KQ/EdevRYuuhsazun9mIZzkt9fvXZoglvBYQcbuIVpLGMBzTT1ekwzTSxjAbcwLa9hoeKgMAc76DgooNAHBYfobFBxiJ5FdH076BHdi+j6oJENCg4Ks7BDfH0lFHoR7aCQDQoO0XOwg4bDsPw91dAwbDhMWZA8dq6BPeuhvTV5u9ioKckd48vBoZ02nuYenuYeGpnBSUxhOHUcoJXfsL7PICklB4U52EHHQQGFPig4RGeDikP0LKLr20GP6F5E1weNbFBwUJiFHeLrK6HQi2gHhWxQcIiegx3iHeQvSvVk9Mz4sFZwaKapIAGh7KAwBzvoOCig0AcFh+hsUHGInkV0fTvoEd2L6PqgkQ0KDgqzsEN8fSUUehHtoJANCg7Rc7BDjIP0x/eMMcYYY4wxxhhjTGnii1LGGGOMMcYYY4wxpuD4opQxxhhjjDHGGGOMKTipdDqdLmTB1tZW6uvrIQUjxheycsIbr0O6E1IVcPy4wte3gx3UHKLrA+x/DUhDS0sLdXV1MRLE5xNozCPaIbq+HexwNAoZ5Xyyg0p9O2g5OJ8SFGZhBzuo1FdxyDSf4i5KGWPMUchclDLGmF6Q+EufMcb0gvPJGKPKQPkU9+17fqeUHewg4RBdH7qvosvgf+kr+zVpBzv0RCqjnE9l7xBd3w5aDs6nBIVZ2MEOKvVVHDLNp7CLUsePhflbC1/3vgmwf1symIj6drCDmkN0fYB7xyfBqUJUPoHGPKIdouvbwQ5Ho5RRzic7RNe3g5aD8ylBYRZ2sINKfRWHTPPJNzo3xhhjjDHGGGOMMQXHF6WMMcYYY4wxxhhjTMHxRSljjDHGGGOMMcYYU3DibnQ+CHaugT3roH0vVNXCqKkweqYdytGhkRmMZSo11NLGXrazjmaaCidAfA9UHBRmoYDCLOyg4xC9LxR6oOAQPQcloucRXd8O3SjsC4U+RDsozEGF6FkoOETXV3FQ2BcKfVBwKOQs5C9KvXkANi6Hl2+HXU3H/r5hBkxfBJPmwbDhdihlhypqOJ95zGYRp3DsrtzCGlZxO6tZTjtt+RcgvgcqDgqzUEBhFnbQcYjeFwo9UHCInoMS0fOIrm+HbhT2hUIfoh0U5qBC9CwUHKLrqzgo7AuFPig4RM0ilU6nC/oloq2trdTX13P8OLjutf6P3fMKPDIX9m0m+aBhZy8HHfr5yIlw2Uqon9z/c3bdhX7EyZndhd4OGg5jmMxNPE4DE0nTSQWVxxzTSQcpKtjFZm5jDjvYMOB/VzYOQ9EDBYds18JQzKLrmxlaWlqoq6sbWGKIiM4niF8PCg7Flk8wNPsieg7F6DBUf1YoZFQ2+QTx+0JhPZSqQ7HlE2j0IdrB+dRN9CwUHEo1n7J1KNW/4xXbeoTYv+PJ3lNqzyvw/XfA/q4G9jaYHj/fvxUenAUtr9qh1BzGMJmbeYYTOJkUqV43CEAFlaRIcQInczPPMoYz8iNAfA9UHBRmoYDCLOyg4xC9LxR6oOAQPQcloucRXd8O3SjsC4U+RDsozEGF6FkoOETXV3FQ2BcKfVBwiJ6F5EWpNw8kVwrbWyHdkdk56Y7k+B/MSc63Q2k4VFHDTTxODbVUUpXROZVUUUMtN7GSKmpyEyC+ByoOCrNQQGEWdtBxiN4XCj1QcIiegxLR84iub4duFPaFQh+iHRTmoEL0LBQcouurOCjsC4U+KDgozCKri1J33HEHZ599NnV1ddTV1fHOd76TRx99NGeJo9m4PHnrWqaD6SLdkZy3cYUdSsXhfObRwMSMN0gXlVQxmlM5j2tyEyC+ByoOCrPoD+eTHSIcoveFQg8UHKLnkAnlklHR9e3QjcK+UOhDtIPCHAaiXPJJwSG6voqDwr5Q6IOCg8IssrooNWHCBJYuXcrzzz/Pc889x3vf+16uuOIKfvnLX+Ys0pOXb8/WrAcVh863Q0k4zGYR6T7fw9g/nXQwmxtzEyC+ByoOCrPoD+eTHSIcoveFQg8UHKLnkAnlklHR9e3QjcK+UOhDtIPCHAaiXPJJwSG6voqDwr5Q6IOCg8IssmrB5ZdfzqWXXsrkyZM588wz+fKXv8zIkSN55plnchbpYueaQ3ebH1xfoBN2rUmexw7F7dDIDE5hZp+faR2ICiqZyLk0MmNwAsT3QMVBYRYD4XyyQ6EdoveFQg8UHKLnkCnlkFHR9e3QjcK+UOhDtIPCHDKhHPJJwSG6voqDwr5Q6IOCg8IskucZJB0dHSxfvpz9+/fzzne+s8/jDh48SGtr6xGP/tizbrBGRz3P+hzOtYOEw1im5qX+SUwZ9LnRPVBxUJhFNjif7FAIh+h9odADBYfoOQyGTDIq23yC+HlE17dDNwr7QqEP0Q4Kc8iWUs0nBYfo+ioOCvtCoQ8KDgqzgEFclHrppZcYOXIk1dXV/Omf/ikPPvggZ511Vp/HL1myhPr6+sOPxsbGfp+/fW+2Rn08z8DZaAdxhxpq81J/OIP/etzoHqg4KMwiE5xPdiikQ/S+UOiBgkP0HLIhm4zKNp8gfh7R9e3QjcK+UOhDtIPCHDKl1PNJwSG6voqDwr5Q6IOCg8IsYBAXpaZMmUJTUxPPPvssn/zkJ7nhhhv41a9+1efxixcvpqWl5fCjubm53+evyk9fqMqhL3bQcGgjPzv1AIPfqdE9UHFQmEUmOJ/sUEiH6H2h0AMFh+g5ZEM2GZVtPkH8PKLr26EbhX2h0IdoB4U5ZEqp55OCQ3R9FQeFfaHQBwUHhVkADMv2hOOOO44zzjgDgHPPPZfVq1dz22238Z3vfKfX46urq6murs74+Ufl5x1kOT2PHTQctpOf9zTm8jzRPVBxUJhFJjif7FDI54neFwo9UHCInkM2ZJNR2eYTxM8jur4dulHYFwp9iHZQmEOmlHo+KThE11dxUNgXCn1QcFCYBeRwT6kuOjs7OXjwYK5Pc5jRM6FhBjndhb5hJoyeYYdid2imiS2soZMsvyPzEJ10sJnn2coLgxMgvgcqDgqzGFRd55MdhtAhel8o9EDBIXoOuVBqGRVd3w7dKOwLhT5EOyjMYbCUWj4pOETXV3FQ2BcKfVBwUJgFZNmCxYsX89RTT7Fp0yZeeuklFi9ezBNPPMH8+fNzkjia6YvI6S700xfZoVQcVnE7qUHu1AoqWcU3chMgvgcqDgqz6A/nkx0iHKL3hUIPFByi55AJ5ZJR0fXt0I3CvlDoQ7SDwhwGolzyScEhur6Kg8K+UOiDgoPCLLKqvmPHDq6//nqmTJnC+973PlavXs0Pf/hD5syZk7NITybNg5ETIZXlNxOmKpPzJl1jh1JxWM1ydrGZDtqzOq+DdnayiedYkZsA8T1QcVCYRX84n+wQ4RC9LxR6oOAQPYdMKJeMiq5vh24U9oVCH6IdFOYwEOWSTwoO0fVVHBT2hUIfFBwUZpHVRak777yTTZs2cfDgQXbs2MGPfvSjvIcVwLDhcOnjyU27Mh1QqjI5/rKVyfl2KA2Hdtq4jbm0sTfjjdJBO23s5Tbm0E5bbgLE90DFQWEW/eF8skOEQ/S+UOiBgkP0HDKhXDIqur4dulHYFwp9iHZQmMNAlEs+KThE11dxUNgXCn1QcFCYRc73lBoqRp0JVz4LIyYc+kFfpod+PmJCcnz9ZDuUmsMOXmUps9jNNoA+P/Pa9fPdbGMps9jBhvwIEN8DFQeFWSigMAs76DhE7wuFHig4RM9Bieh5RNe3QzcK+0KhD9EOCnNQIXoWCg7R9VUcFPaFQh8UHKJnIXtRCpJGX70WLrobGs7p/ZiGc5LfX702v4Oxg5bDDjZwC9NYxgKaaer1mGaaWMYCbmHakPwhHt0DFQeFWSigMAs76DhE7wuFHig4RM9Bieh5RNe3QzcK+0KhD9EOCnNQIXoWCg7R9VUcFPaFQh8UHCJnMSxvzzREDBsOUxYkj51rYM96aG9N3rI2akpy13o7lIdDO208zT08zT00MoOTmMJw6jhAK79hfZ+bJ59E90DFQWEWCijMwg46DtH7QqEHCg7Rc1Aieh7R9e3QjcK+UOhDtIPCHFSInoWCQ3R9FQeFfaHQBwWHqFnIX5TqyeiZhRmGHfQdmmkK/4M7ugcqDgqzUEBhFnbQcYjeFwo9UHCInoMS0fOIrm+HbhT2hUIfoh0U5qBC9CwUHKLrqzgo7AuFPig4FHIW0h/fM8YYY4wxxhhjjDGliS9KGWOMMcYYY4wxxpiC44tSxhhjjDHGGGOMMabgpNLpdLqQBVtbW6mvr4cUjBhfyMoJb7wO6U5IVcDx4wpf3w52UHOIrg+w/zUgDS0tLdTV1cVIEJ9PoDGPaIfo+naww9EoZJTzyQ4q9e2g5eB8SlCYhR3soFJfxSHTfIq7KGWMMUchc1HKGGN6QeIvfcYY0wvOJ2OMKgPlU9y37/mdUnawg4RDdH3ovooug/+lr+zXpB3s0BOpjHI+lb1DdH07aDk4nxIUZmEHO6jUV3HINJ/CLkodPxbmby183fsmwP5tyWAi6tvBDmoO0fUB7h2fBKcKUfkEGvOIdoiubwc7HI1SRjmf7BBd3w5aDs6nBIVZ2MEOKvVVHDLNJ9/o3BhjjDHGGGOMMcYUHF+UMsYYY4wxxhhjjDEFxxeljDHGGGOMMcYYY0zBibvR+SDYuQb2rIP2vVBVC6OmwuiZ5efQyAzGMpUaamljL9tZRzNNBXWI7kN0fTuYo1GYhR3soFJfxcF0Ez2P6Pp26MavI3UcTILCLKIdouurODifdBwKifxFqTcPwMbl8PLtsKvp2N83zIDpi2DSPBg2vHQdqqjhfOYxm0WcwrErcgtrWMXtrGY57bQNiUN0H6Lr28EcjcIs7GAHlfoqDqab6HlE17dDN34dqeNgEhRmEe0QXV/Fwfmk4xCF9Mf39rwCD0yDJz8Ku17s/ZhdLya/f2AatLxamg5jmMwtrOV67mICZ/d6zATO5nru4hbWMoYz8u4Q3Yfo+nYwR6MwCzvYQaW+ioPpJnoe0fXt0I1fR+o4mASFWUQ7RNdXcXA+6ThEIntRas8r8P13wP6ury/s7OPAQz/fvxUenJXfASk4jGEyN/MMJ3AyKVJUUNnrcRVUkiLFCZzMzTyb1w0b3Yfo+nYwR6MwCzvYQaW+ioPpJnoe0fXt0I1fR+o4mASFWUQ7RNdXcXA+6ThEI3lR6s0D8MhcaG+FdEdm56Q7kuN/MCc5vxQcqqjhJh6nhloqqcronEqqqKGWm1hJFTU5O0T3Ibq+HczRKMzCDnZQqa/iYLqJnkd0fTt049eROg4mQWEW0Q7R9VUcnE86DgrkdFFq6dKlpFIp/uIv/iJPOgkbl8O+zZkPpot0R3LexhWl4XA+82hgYsYbtYtKqhjNqZzHNTk7RPchur4dihfnkx3KwSG6vopDsTFU+QTx84iub4du/DpSx6HY8GuooXOIrq/i4HzScVBg0BelVq9ezXe+8x3OPrv3z37mwsu3M3izikPnl4DDbBaR7vP9e/3TSQezuTFnh+g+RNe3Q3HifLJDuThE11dxKCaGMp8gfh7R9e3QjV9H6jgUE34NNbQO0fVVHJxPOg4KDKoF+/btY/78+Xz3u9/lhBNOyKvQzjWH7jY/uDUKnbBrTfI8xezQyAxOYWafn60diAoqmci5NDJj0A7RfYiub4fixPlkh3JxiK6v4lBMDGU+Qfw8ouvboRu/jtRxKCb8GmpoHaLrqzg4n3QcVBjURamFCxdy2WWX8f73v3/AYw8ePEhra+sRj/7Ys24wRr08z/oczhVwGMvUvDicxJRBnxvdh+j6dihOnE92KBeH6PoqDsXEUOYTxM8jur4duvHrSB2HYiLTjCrGfFJwiK6v4uB80nFQYVi2Jyxfvpxf/OIXrF69OqPjlyxZwuc///mMn799b7ZGfTzPwNko7VBDbV4chlM36HOj+xBd3w7Fh/PJDuXkEF1fxaFYGOp8gvh5RNe3Qzd+HanjUCxkk1HFmE8KDtH1VRycTzoOKmT1Tqnm5mZuuukm7rvvPmpqMrvj/eLFi2lpaTn8aG5u7vf4qvysUaoGv0YlHNrIzyo9wOBXaXQfouvbobhwPtmh3Byi66s4FAOFyCeIn0d0fTt049eROg7FQLYZVYz5pOAQXV/Fwfmk46BCVu+Uev7559mxYwdvf/vbD/+so6ODp556im9+85scPHiQysojPxtaXV1NdXV1xjVG5efdfDk9j4LDdvLzfr5cnie6D9H17VBcOJ/sUG4O0fVVHIqBQuQTxM8jur4duvHrSB2HYiDbjCrGfFJwiK6v4uB80nFQIat3Sr3vfe/jpZdeoqmp6fDjvPPOY/78+TQ1NR3zgmowjJ4JDTOyNetBBTTMhNEzituhmSa2sIZOsvx+yEN00sFmnmcrLwzaIboP0fXtUFw4n+xQbg7R9VUcioFC5BPEzyO6vh268etIHYdiwK+hCuMQXV/Fwfmk46BCVi2ora1l+vTpRzxGjBhBQ0MD06dPz5vU9EXkdBf66YtKw2EVt5Ma5CqtoJJVfCNnh+g+RNe3Q/HgfLJDOTpE11dxUKdQ+QTx84iub4du/DpSx0Edv4YqnEN0fRUH55OOgwKDvS43pEyaByMnQirLi/KpyuS8SdeUhsNqlrOLzXTQntV5HbSzk008x4qcHaL7EF3fDuZoFGZhBzuo1FdxMN1EzyO6vh268etIHQeToDCLaIfo+ioOzicdBwVyvij1xBNPcOutt+ZBpZthw+HSx5ObdmU6oFRlcvxlK5PzS8GhnTZuYy5t7M14w3bQTht7uY05tNOWs0N0H6Lr26G4cT7ZodQdouurOBQjQ5FPED+P6Pp26MavI3UcihG/hhoah+j6Kg7OJx0HBSTfKQUw6ky48lkYMeHQD/oyPfTzEROS4+snl5bDDl5lKbPYzTaAPj972/Xz3WxjKbPYwYa8OUT3Ibq+HczRKMzCDnZQqa/iYLqJnkd0fTt049eROg4mQWEW0Q7R9VUcnE86DtHIXpSCpNFXr4WL7oaGc3o/puGc5PdXrx2awSg47GADtzCNZSygmaZej2mmiWUs4Bam5XWjdhHdh+j6djBHozALO9hBpb6Kg+kmeh7R9e3QjV9H6jiYBIVZRDtE11dxcD7pOEQyLFpgIIYNhykLksfONbBnPbS3Jm9ZGzUluWt9OTi008bT3MPT3EMjMziJKQynjgO08hvW97mJ80l0H6Lr28EcjcIs7GAHlfoqDqab6HlE17dDN34dqeNgEhRmEe0QXV/Fwfmk4xCF/EWpnoyeGT8MBYdmmgqyOfsjug/R9e1gjkZhFnawg0p9FQfTTfQ8ouvboRu/jtRxMAkKs4h2iK6v4uB80nEoJNIf3zPGGGOMMcYYY4wxpYkvShljjDHGGGOMMcaYguOLUsYYY4wxxhhjjDGm4KTS6XS6kAVbW1upr6+HFIwYX8jKCW+8DulOSFXA8eMKX98OdlBziK4PsP81IA0tLS3U1dXFSBCfT6Axj2iH6Pp2sMPRKGSU88kOKvXtoOXgfEpQmIUd7KBSX8Uh03yKuyhljDFHIXNRyhhjekHiL33GGNMLzidjjCoD5VPct+/5nVJ2sIOEQ3R96L6KLoP/pa/s16Qd7NATqYxyPpW9Q3R9O2g5OJ8SFGZhBzuo1FdxyDSfwi5KHT8W5m8tfN37JsD+bclgIurbwQ5qDtH1Ae4dnwSnClH5BBrziHaIrm8HOxyNUkY5n+wQXd8OWg7OpwSFWdjBDir1VRwyzSff6NwYY4wxxhhjjDHGFBxflDLGGGOMMcYYY4wxBccXpYwxxhhjjDHGGGNMwYm70fkg2LkG9qyD9r1QVQujpsLomeXn0MgMxjKVGmppYy/bWUczTWXloDAHOyRErwUVFGah4KCwHhT6EO0QXV/FQWE9qhA9j+j6oLEe3IcEhT5EOyjMQYXoWSg4KKyH6B6A+6DkUMhZyF+UevMAbFwOL98Ou5qO/X3DDJi+CCbNg2HDS9ehihrOZx6zWcQpHLsit7CGVdzOapbTTltJOijMwQ4J0WtBBYVZKDgorAeFPkQ7RNdXcVBYjypEzyO6PmisB/chQaEP0Q4Kc1AhehYKDgrrIboH4D4oOUTNIpVOpwv6JaKtra3U19dz/Di47rX+j93zCjwyF/ZtJvmgYWcvBx36+ciJcNlKqJ/c/3N23YV+xMmZ3YVewWEMk7mJx2lgImk6qaDymGM66SBFBbvYzG3MYQcbSsphKOZgh+zrw9Csha5vZmhpaaGurm5giSEiOp8gfj1k6xCdDaCxL6IdFNaCgsNQrEfQyKhs8gm8JmHo1kN0HxT+3C62jFRwcD51Ez0LBYdSzadsHUq1D8W2HiH273iy95Ta8wp8/x2wv6uBvQ2mx8/3b4UHZ0HLq6XlMIbJ3MwznMDJpEj1ujgAKqgkRYoTOJmbeZYxnFEyDgpzsENC9FpQQWEWCg4K60GhD9EO0fVVHBTWowrR84iuDxrrwX1IUOhDtIPCHFSInoWCg8J6iO4BuA9KDtGzkLwo9eaB5EpheyukOzI7J92RHP+DOcn5peBQRQ038Tg11FJJVUbnVFJFDbXcxEqqqCl6B4U52CEhei2ooDALBQeF9aDQh2iH6PoqDgrrUYXoeUTXB4314D4kKPQh2kFhDipEz0LBQWE9RPcA3AclB4VZZHVR6pZbbiGVSh3xmDp1as4SR7NxefLWtUwH00W6Izlv44rScDifeTQwMePF0UUlVYzmVM7jmqJ3UJiDHRKi18JAOJ8K66CwHhT6EO0QXV/FQWE9DkS5ZFR0fdBYD+5DgkIfoh0U5jAQ5ZJPCg4K6yG6B+A+KDkozCLrd0q99a1v5fXXXz/8+OlPf5qzxNG8fPtgzA5Rcej8EnCYzSLSfb5/r3866WA2Nxa9g8Ic7JAQvRYywflUOAeF9aDQh2iH6PoqDgrrMRPKIaOi64PGenAfEhT6EO2gMIdMKId8UnBQWA/RPQD3QclBYRZZt2DYsGGMHTv28GP06NE5S/Rk55pDd5sfXF+gE3atSZ6nmB0amcEpzOzz85wDUUElEzmXRmYUrYPCHOyQEL0WMsX5VBgHhfWg0Idoh+j6Kg4K6zFTSj2jouuDxnpwHxIU+hDtoDCHTCn1fFJwUFgP0T0A90HJQWEWyfNkyauvvsr48eM5/fTTmT9/Plu2bOn3+IMHD9La2nrEoz/2rMvWqI/nWZ/DuQIOY8nPW2ZPYkrROijMwQ4J0WshU5xPhXFQWA8KfYh2iK6v4qCwHjMlm4zKNp8gfh7R9UFjPbgPCQp9iHZQmEOmlHo+KTgorIfoHoD7oOSgMAvI8qLUrFmzWLZsGY899hh33HEHv/71r3nPe97D3r17+zxnyZIl1NfXH340Njb2W6O976fKivaBs1HaoYbavDgMZ/BfDRvtoDAHOyREr4VMcD4VzkFhPSj0Idohur6Kg8J6zIRsMyrbfIL4eUTXB4314D4kKPQh2kFhDplQDvmk4KCwHqJ7AO6DkoPCLCDLi1KXXHIJV111FWeffTYf+MAHeOSRR9izZw8PPPBAn+csXryYlpaWw4/m5uZ+a1Tlpy9U5dAXBYc28rNKDzD4VRrtoDAHOyREr4VMcD4VzkFhPSj0Idohur6Kg8J6zIRsMyrbfIL4eUTXB4314D4kKPQh2kFhDplQDvmk4KCwHqJ7AO6DkoPCLACG5XLyqFGjOPPMM9mwYUOfx1RXV1NdXZ35c+bpix5yeR4Fh+3k5/18uTxPtIPCHOyQEL0WBoPzaeieR2E9KPQh2iG6voqDwnocDANlVLb5BPHziK4PGuvBfUhQ6EO0g8IcBkMp5pOCg8J6iO4BuA9KDgqzgMHf6x2Affv2sXHjRsaNG5eTRE9Gz4SGGeR0F/qGmTB6RnE7NNPEFtbQSZbfD3mITjrYzPNs5YWidVCYgx0SotfCYHA+DZ2DwnpQ6EO0Q3R9FQeF9TgYSjGjouuDxnpwHxIU+hDtoDCHwVCK+aTgoLAeonsA7oOSg8IsIMsW/OVf/iVPPvkkmzZt4mc/+xlXXnkllZWVXHvttTlJHM30ReR0F/rpi0rDYRW3kxrkKq2gklV8o+gdFOZgh4TotTAQzqfCOiisB4U+RDtE11dxUFiPA1EuGRVdHzTWg/uQoNCHaAeFOQxEueSTgoPCeojuAbgPSg4Ks8iq+tatW7n22muZMmUKV199NQ0NDTzzzDOceOKJOYv0ZNI8GDkRUll+M2GqMjlv0jWl4bCa5exiMx20Z3VeB+3sZBPPsaLoHRTmYIeE6LUwEM6nwjoorAeFPkQ7RNdXcVBYjwNRLhkVXR801oP7kKDQh2gHhTkMRLnkk4KDwnqI7gG4D0oOCrPI6qLU8uXLee211zh48CBbt25l+fLlTJo0KWeJoxk2HC59PLlpV6YDSlUmx1+2Mjm/FBzaaeM25tLG3owXSQfttLGX25hDO21F76AwBzskRK+FgXA+FdZBYT0o9CHaIbq+ioPCehyIcsmo6PqgsR7chwSFPkQ7KMxhIMolnxQcFNZDdA/AfVByUJhFTveUGkpGnQlXPgsjJhz6QV+mh34+YkJyfP3k0nLYwassZRa72QbQ5+c9u36+m20sZRY76PvmzsXmoDAHOyRErwUVFGah4KCwHhT6EO0QXV/FQWE9qhA9j+j6oLEe3IcEhT5EOyjMQYXoWSg4KKyH6B6A+6DkED0L2YtSkDT66rVw0d3QcE7vxzSck/z+6rX5HYySww42cAvTWMYCmmnq9ZhmmljGAm5h2pD8ARbtoDAHOyRErwUVFGah4KCwHhT6EO0QXV/FQWE9qhA9j+j6oLEe3IcEhT5EOyjMQYXoWSg4KKyH6B6A+6DkEDmLYXl7piFi2HCYsiB57FwDe9ZDe2vylrVRU5K71peDQzttPM09PM09NDKDk5jCcOo4QCu/YX2fC6eUHBTmYIeE6LWggsIsFBwU1oNCH6IdouurOCisRxWi5xFdHzTWg/uQoNCHaAeFOagQPQsFB4X1EN0DcB+UHKJmIX9RqiejZxZmGOoOzTSF/6EV7aAwBzskRK8FFRRmoeCgsB4U+hDtEF1fxUFhPaoQPY/o+qCxHtyHBIU+RDsozEGF6FkoOCish+gegPug5FDIWUh/fM8YY4wxxhhjjDHGlCa+KGWMMcYYY4wxxhhjCo4vShljjDHGGGOMMcaYgpNKp9PpQhZsbW2lvr4eUjBifCErJ7zxOqQ7IVUBx48rfH072EHNIbo+wP7XgDS0tLRQV1cXI0F8PoHGPKIdouvbwQ5Ho5BRzic7qNS3g5aD8ylBYRZ2sINKfRWHTPMp7qKUMcYchcxFKWOM6QWJv/QZY0wvOJ+MMaoMlE9x377nd0rZwQ4SDtH1ofsqugz+l76yX5N2sENPpDLK+VT2DtH17aDl4HxKUJiFHeygUl/FIdN8CrsodfxYmL+18HXvmwD7tyWDiahvBzuoOUTXB7h3fBKcKkTlE2jMI9ohur4d7HA0ShnlfLJDdH07aDk4nxIUZmEHO6jUV3HINJ98o3NjjDHGGGOMMcYYU3B8UcoYY4wxxhhjjDHGFBxflDLGGGOMMcYYY4wxBSfuRueDYOca2LMO2vdCVS2MmgqjZ5afQyMzGMtUaqiljb1sZx3NNJWVQ3R90FgLCg4mQWEWCg4Ke1PBIXoW0fVVHEw30fOIrg8a2WCHBK8H0xOF9RDtoLAe7ZAQvRZUHAqJ/EWpNw/AxuXw8u2wq+nY3zfMgOmLYNI8GDa8dB2qqOF85jGbRZzCsStyC2tYxe2sZjnttJWkQ3R90FgLCg4mQWEWCg4Ke1PBIXoW0fVVHEw30fOIrg8a2WCHBK8H0xOF9RDtoLAe7ZAQvRZUHKKQ/vjenlfggWnw5Edh14u9H7PrxeT3D0yDlldL02EMk7mFtVzPXUzg7F6PmcDZXM9d3MJaxnBGyTlE1weNtaDgYBIUZqHgoLA3FRyiZxFdX8XBdBM9j+j6oJENdkjwejA9UVgP0Q4K69EOCdFrQcUhEtmLUntege+/A/Z3fX1hZx8HHvr5/q3w4Kz8DkjBYQyTuZlnOIGTSZGigspej6ugkhQpTuBkbubZvG7YaIfo+qCxFhQcTILCLBQcFPamgkP0LKLrqziYbqLnEV0fNLLBDgleD6YnCush2kFhPdohIXotqDhEI3lR6s0D8MhcaG+FdEdm56Q7kuN/MCc5vxQcqqjhJh6nhloqqcronEqqqKGWm1hJFTVF7xBdHzTWgoKDSVCYhYKDwt5UcIieRXR9FQfTTfQ8ouuDRjbYIcHrwfREYT1EOyisRzskRK8FFQcFsr4otW3bNq677joaGhoYPnw4b3vb23juuefyKrVxOezbnPlgukh3JOdtXFEaDuczjwYmZrxRu6ikitGcynlcU/QO0fVBYy0oOBQDzqfCOSjsTQWH6FlE11dxKBbKIaOi64NGNtghweuheCiHfFJwUFiPdkiIXgsqDgpkdVFq9+7dXHjhhVRVVfHoo4/yq1/9iq9//euccMIJeZV6+fZszXpQcej8EnCYzSLSfb5/r3866WA2Nxa9Q3R90FgLCg7qOJ8K66CwNxUcomcRXV/FoRgol4yKrg8a2WCHBK+H4qBc8knBQWE92iEhei2oOCiQVQu++tWv0tjYyN13380FF1zAaaedxty5c5k0aVLehHauOXS3+cGtUeiEXWuS5ylmh0ZmcAoz+/xs7UBUUMlEzqWRGUXrEF0fNNaCgkMx4HwqnIPC3lRwiJ5FdH0Vh2KhHDIquj5oZIMdErweiodyyCcFB4X1aIeE6LWg4qBCVhelHnroIc477zyuuuoqxowZw8yZM/nud7/b7zkHDx6ktbX1iEd/7FmXjVE/z7M+h3MFHMYyNS8OJzGlaB2i64PGWlBwKAacT4VzUNibCg7Rs4iur+JQLGSbUdnmE8TPI7o+aGSDHRK8HoqHcsgnBQeF9WiHhOi1oOKgQlYXpf7rv/6LO+64g8mTJ/PDH/6QT37ykyxatIh77rmnz3OWLFlCfX394UdjY2O/Ndr3ZmPUz/MMnI3SDjXU5sVhOHVF6xBdHzTWgoJDMeB8KpyDwt5UcIieRXR9FYdiIduMyjafIH4e0fVBIxvskOD1UDyUQz4pOCisRzskRK8FFQcVsroo1dnZydvf/na+8pWvMHPmTD7xiU/w8Y9/nH/6p3/q85zFixfT0tJy+NHc3Nxvjar8rFGqcvizQ8Ghjfys0gMMfpVGO0TXB421oOBQDDifCuegsDcVHKJnEV1fxaFYyDajss0niJ9HdH3QyAY7JHg9FA/lkE8KDgrr0Q4J0WtBxUGFrC5KjRs3jrPOOuuIn02bNo0tW7b0eU51dTV1dXVHPPpjVH7ezZfT8yg4bCc/7+fL5XmiHaLrg8ZaUHAoBpxPhXsehb2p4BA9i+j6Kg7FQrYZlW0+Qfw8ouuDRjbYIcHroXgoh3xScFBYj3ZIiF4LKg4qZHVR6sILL2T9+iM/tPjKK68wceLEvAmNngkNM7I160EFNMyE0TOK26GZJrawhk6y/H7IQ3TSwWaeZysvFK1DdH3QWAsKDsWA86lwDgp7U8EhehbR9VUcioVyyKjo+qCRDXZI8HooHsohnxQcFNajHRKi14KKgwpZteBTn/oUzzzzDF/5ylfYsGED999/P//8z//MwoUL8yo1fRE53YV++qLScFjF7aQGuUorqGQV3yh6h+j6oLEWFBzUcT4V1kFhbyo4RM8iur6KQzFQLhkVXR80ssEOCV4PxUG55JOCg8J6tENC9FpQcVAgq5Vw/vnn8+CDD/K9732P6dOn88UvfpFbb72V+fPn51Vq0jwYORFSWX5LZKoyOW/SNaXhsJrl7GIzHbRndV4H7exkE8+xougdouuDxlpQcFDH+VRYB4W9qeAQPYvo+ioOxUC5ZFR0fdDIBjskeD0UB+WSTwoOCuvRDgnRa0HFQYGsL09+6EMf4qWXXqKtrY21a9fy8Y9/PO9Sw4bDpY8nN+3KdECpyuT4y1Ym55eCQztt3MZc2tib8YbtoJ029nIbc2inregdouuDxlpQcCgGnE+Fc1DYmwoO0bOIrq/iUCyUQ0ZF1weNbLBDgtdD8VAO+aTgoLAe7ZAQvRZUHBQY7CcYh5xRZ8KVz8KICYd+0JfpoZ+PmJAcXz+5tBx28CpLmcVutgH0+dnbrp/vZhtLmcUONpSMQ3R90FgLCg4mQWEWCg4Ke1PBIXoW0fVVHEw30fOIrg8a2WCHBK8H0xOF9RDtoLAe7ZAQvRZUHKKRvSgFSaOvXgsX3Q0N5/R+TMM5ye+vXjs0g1Fw2MEGbmEay1hAM029HtNME8tYwC1MG5I/QKMdouuDxlpQcDAJCrNQcFDYmwoO0bOIrq/iYLqJnkd0fdDIBjskeD2Yniish2gHhfVoh4TotaDiEMmwaIGBGDYcpixIHjvXwJ710N6avGVt1JTkrvXl4NBOG09zD09zD43M4CSmMJw6DtDKb1jf5yYuJYfo+qCxFhQcTILCLBQcFPamgkP0LKLrqziYbqLnEV0fNLLBDgleD6YnCush2kFhPdohIXotqDhEIX9RqiejZ8YPQ8GhmabwPzSjHaLrg8ZaUHAwCQqzUHBQ2JsKDtGziK6v4mC6iZ5HdH3QyAY7JHg9mJ4orIdoB4X1aIeE6LWg4lBIpD++Z4wxxhhjjDHGGGNKE1+UMsYYY4wxxhhjjDEFxxeljDHGGGOMMf8/e28eH2V97u9fk8UkQBIw7BAjAgLWSqgLKh4xKiiiUo91OdUq1dPThQqn/dWty7dWW7HLqXttaxHo0RY8PcelVq2ooG1FQEtELXsLhE3KlrAbkuf3x0NWssxkmfuemff1es2rdfLMc1+578/zZvgwixBCCBF3IkEQBPEsWFFRQX5+PkSga/94Vg7ZvwWCaoikQZd+8a8vBzl4c7CuD7BvMxBAeXk5eXl5NhLY5xP4mIe1g3V9OcihMR4ySvkkBy/15eDLQfkU4mEWcpCDl/peHKLNJ7tNKSGEaISbTSkhhGgCF3/pE0KIJlA+CSG80lo+2X37nl4pJQc5uHCwrg91u+hu0L/0pfyalIMc6uMqo5RPKe9gXV8OvhyUTyEeZiEHOXip78Uh2nwy25Tq0heu2xj/uk8NhH2bwsFY1JeDHLw5WNcHeLJ/GJxesMon8DEPawfr+nKQQ2M8ZZTySQ7W9eXgy0H5FOJhFnKQg5f6XhyizSd90LkQQgghhBBCCCGEiDvalBJCCCGEEEIIIYQQcUebUkIIIYQQQgghhBAi7th90Hkb2L4Udq+Ayj2QmQvdh0PPUannUEgxfRlONrkcZA9bWUEZpXF1sO6Dhx54wHoOog4Ps/Dg4OHa9NAHawfr+l4cRB3W87CuDz7ySQ5+HDysSRHiYRbWDh6uCTn4cbBej/F2cL8pdfgArJ0DHzwEO0qP/nlBMZw8FQZfCxk5yeuQSTancy0lTOU4jl4NG1jKfB5iCXOo5GCnOFj3wUMPPGA9B1GHh1l4cPBwbXrog7WDdX0vDqIO63lY1wcf+SQHPw4e1qQI8TALawcP14Qc/DhYr0dLB9dv39u9Cp4eAW/cBDuWNX3MjmXhz58eAeWrk9OhN0O5i+XcwBMM5JQmjxnIKdzAE9zFcnozpMMdrPvgoQcesJ6DqMPDLDw4eLg2PfTB2sG6vhcHUYf1PKzrg498koMfBw9rUoR4mIW1g4drQg5+HKzXo7WD202p3avg2TNhX83XF1Y3c+CR+/dthGdGd2xzPDj0Zih38DY9GECECGmkN3lcGulEiNCDAdzBog69WKz74KEHHrCeg6jDwyw8OHi4Nj30wdrBur4XB1GH9Tys64OPfJKDHwcPa1KEeJiFtYOHa0IOfhys16MHB5ebUocPwIvjobICgqroHhNUhcf/YVz4+GRwyCSbabxCNrmkkxnVY9LJJJtcpjGPTLLb7WDdBw898ID1HEQdHmbhwcHDtemhD9YO1vW9OIg6rOdhXR985JMc/Dh4WJMixMMsrB08XBNy8ONgvR69OMS0KXX88ccTiUSOuk2ZMqX9JvVYOwf2ro++KTUEVeHj1s5NDofTuZYCiqK+SGpIJ5OeHM9pXNNuB+s+eOiBB6znkCjEI6M8zMKDg4dr00MfrB2s63txSARS5TmUdX3wkU9y8OPgYU16J1XyyYODh2tCDn4crNejF4eYNqWWLFnCli1bam/z5s0D4Kqrrmq/ST0+eChWs3qkHXl8EjiUMJWg2dfOtUw1VZRwS7sdrPvgoQcesJ5DohCPjPIwCw8OHq5ND32wdrCu78UhEUiV51DW9cFHPsnBj4OHNemdVMknDw4ergk5+HGwXo9eHGIq36tXL/r27Vt7e+GFFxg8eDBjx45tv8kRti898knvbVsfUA07lobnSWSHQoo5jlHNvq+1NdJIp4hTKaS4zQ7WffDQAw9YzyGR6OyM8jALDw4erk0PfbB2sK7vxSFRSIXnUNb1wUc+ycGPg4c1mQikQj55cPBwTcjBj4P1evTiAO34TKmPP/6YJ598kptuuolIJNLscYcOHaKioqLBrSV2r2irUaPzrGzHYx049GV4hzj0YVibH2vdBw898ID1HBKVaDJK+dQ2PFybHvpg7WBd34tDItIZ+QT287CuDz7ySQ5+HDysyUQjWfPJg4OHa0IOfhys16MXB2jHptSzzz7L7t27mTx5covHTZ8+nfz8/NpbYWFhi8dX7mmrUaPztJ6Nrh2yye0Qhxzy2vxY6z546IEHrOeQqESTUcqntuHh2vTQB2sH6/peHBKRzsgnsJ+HdX3wkU9y8OPgYU0mGsmaTx4cPFwTcvDjYL0evThAOzalZsyYwYQJE+jfv3+Lx915552Ul5fX3srKylo8PrNj1geZ7diH8OBwkI5ZIQdo+wqx7oOHHnjAeg6JSjQZpXxqGx6uTQ99sHawru/FIRHpjHwC+3lY1wcf+SQHPw4e1mSikaz55MHBwzUhBz8O1uvRiwNARlsetH79el599VX+7//+r9Vjs7KyyMrKivrc3TvmlXTtOo8Hh610zGvp2nMe6z546IEHrOeQiESbUcqntuHh2vTQB2sH6/peHBKNzsonsJ+HdX3wkU9y8OPgYU0mEsmcTx4cPFwTcvDjYL0evThAG18pNXPmTHr37s3EiRPbV70Jeo6CgmLa9QnwBaOgZ3FiO5RRygaWUk2M3814hGqqWM+7bOS9NjtY98FDDzxgPYdEpLMyysMsPDh4uDY99MHawbq+F4dEI5mfQ1nXBx/5JAc/Dh7WZCKRzPnkwcHDNSEHPw7W69GLA20pX11dzcyZM7nxxhvJyGjTC61a5eSptOsT4E+emhwO83mISBtXSBrpzOfhdjtY98FDDzxgPYdEorMzysMsPDh4uDY99MHawbq+F4dEIRWeQ1nXBx/5JAc/Dh7WZCKQCvnkwcHDNSEHPw7W69GLQ8xTePXVV9mwYQM33XRT+6s3w+BroVsRRGL8hsZIevi4wdckh8MS5rCD9VRRGdPjqqhkO+t4h7ntdrDug4ceeMB6DolEZ2eUh1l4cPBwbXrog7WDdX0vDolCKjyHsq4PPvJJDn4cPKzJRCAV8smDg4drQg5+HKzXoxeHmDelxo8fTxAEnHjiie2v3gwZOXDJK+EHZkXbnEh6ePzEeeHjk8GhkoM8yHgOsifqi6WKSg6yhwcZRyUH2+1g3QcPPfCA9RwSic7OKA+z8ODg4dr00AdrB+v6XhwShVR4DmVdH3zkkxz8OHhYk4lAKuSTBwcP14Qc/DhYr0cvDm3+9r3OpvuJcMUi6DrwyB3NmR65v+vA8Pj8ocnlsI3V3MdodrEJoNn3vdbcv4tN3MdotrGmwxys++ChBx6wnoOow8MsPDh4uDY99MHawbq+FwdRh/U8rOuDj3ySgx8HD2tShHiYhbWDh2tCDn4crNejBwe3m1IQ/pJXL4exM6FgZNPHFIwMf3718s75g8ODwzbWcBcjmMVkyiht8pgySpnFZO5iRKdsxlj3wUMPPGA9B1GHh1l4cPBwbXrog7WDdX0vDqIO63lY1wcf+SQHPw4e1qQI8TALawcP14Qc/DhYr0drh875FLsOJCMHhk0Ob9uXwu6VUFkRvlys+7DwE+NTwaGSgyxkNguZTSHF9GEYOeRxgAo+YmWzF1BHYt0HDz3wgPUcRB0eZuHBwcO16aEP1g7W9b04iDqs52FdH3zkkxz8OHhYkyLEwyysHTxcE3Lw42C9Hi0d3G9K1afnKPs/LDw4lFFqvgFj3QcPPfCA9RxEHR5m4cHBw7XpoQ/WDtb1vTiIOqznYV0ffOSTHPw4eFiTIsTDLKwdPFwTcvDjYL0e4+3g+u17QgghhBBCCCGEECI50aaUEEIIIYQQQgghhIg72pQSQgghhBBCCCGEEHEnEgRBEM+CFRUV5OfnQwS69o9n5ZD9WyCohkgadOkX//pykIM3B+v6APs2AwGUl5eTl5dnI4F9PoGPeVg7WNeXgxwa4yGjlE9y8FJfDr4clE8hHmYhBzl4qe/FIdp8stuUEkKIRrjZlBJCiCZw8Zc+IYRoAuWTEMIrreWT3bfv6ZVScpCDCwfr+lC3i+4G/Utfyq9JOcihPq4ySvmU8g7W9eXgy0H5FOJhFnKQg5f6XhyizSezTakufeG6jfGv+9RA2LcpHIxFfTnIwZuDdX2AJ/uHwekFq3wCH/OwdrCuLwc5NMZTRimf5GBdXw6+HJRPIR5mIQc5eKnvxSHafNIHnQshhBBCCCGEEEKIuKNNKSGEEEIIIYQQQggRd7QpJYQQQgghhBBCCCHijjalhBBCCCGEEEIIIUTcsfv2vTawfSnsXgGVeyAzF7oPh56jUs+hkGL6MpxscjnIHraygjJK4+rgoQ/WeJiD8IOHa8KDg4frwkMfrPEwB+EL6+vCuj74uC7k4MdB+MFDPlg7eLgm5ODHIdVwvyl1+ACsnQMfPAQ7So/+eUExnDwVBl8LGTnJ65BJNqdzLSVM5TiOTsgNLGU+D7GEOVRysFMcPPTBGg9zEH7wcE14cPBwXXjogzUe5iB8YX1dWNcHH9eFHPw4CD94yAdrBw/XhBz8OKQyrt++t3sVPD0C3rgJdixr+pgdy8KfPz0Cylcnp0NvhnIXy7mBJxjIKU0eM5BTuIEnuIvl9GZIhzt46IM1HuYg/ODhmvDg4OG68NAHazzMQfjC+rqwrg8+rgs5+HEQfvCQD9YOHq4JOfhxSHXcbkrtXgXPngn7Nh65o7qZA4/cv28jPDO6YwPDg0NvhnIHb9ODAUSIkEZ6k8elkU6ECD0YwB0s6tCLxUMfrPEwB+EHD9eEBwcP14WHPljjYQ7CF9bXhXV98HFdyMGPg/CDh3ywdvBwTcjBj4OIcVOqqqqK73znOwwaNIicnBwGDx7MPffcQxAEHSp1+AC8OB4qKyCoiu4xQVV4/B/GhY9PBodMspnGK2STSzqZUT0mnUyyyWUa88gku90OHvpgjYc5iNZRPsXXwcN14aEP1niYg4iOVMko6/rg47qQgx8H0Tqpkk8eHDxcE3Lw4yBCYtqU+uEPf8hjjz3GI488wvLly/nhD3/Ij370Ix5++OEOlVo7B/aujz4oagiqwsetnZscDqdzLQUURX2R1JBOJj05ntO4pt0OHvpgjYc5iNZRPsXXwcN14aEP1niYg4iOVMko6/rg47qQgx8H0Tqpkk8eHDxcE3Lw4yBCYtqUeuutt5g0aRITJ07k+OOP5zOf+Qzjx49n8eLFHSr1wUOxmtUj7cjjk8ChhKkEzb6etGWqqaKEW9rt4KEP1niYg2gd5VN8HTxcFx76YI2HOYjoSJWMsq4PPq4LOfhxEK2TKvnkwcHDNSEHPw4iJKZL8uyzz+a1115j1apVALz33nv8+c9/ZsKECR0mtH3pkW8/aNv6gGrYsTQ8TyI7FFLMcYxq9n2trZFGOkWcSiHFbXbw0AdrPMxBRIfyKX4OHq4LD32wxsMcRPSkQkZZ1wcf14Uc/DiI6EiFfPLg4OGakIMfB1FHRiwH33HHHVRUVDB8+HDS09OpqqriBz/4Adddd12zjzl06BCHDh2q/e+KiooWa+xeEYtRC+dZCT2P/jbH6B7rwKEvwzvEoQ/DKKO0TY/10AdrPMxBRIfyKX4OHq4LD32wxsMcRPTEmlGx5hPYXxfW9cHHdSEHPw4iOlIhnzw4eLgm5ODHQdQR0yulnn76aZ566il+85vf8Ne//pXZs2fzk5/8hNmzZzf7mOnTp5Ofn197KywsbLFG5Z5YjFo4T+vZ6Nohm9wOccghr82P9dAHazzMQUSH8il+Dh6uCw99sMbDHET0xJpRseYT2F8X1vXBx3UhBz8OIjpSIZ88OHi4JuTgx0HUEdOm1K233sodd9zBtddeyyc/+Uk+97nP8bWvfY3p06c3+5g777yT8vLy2ltZWVmLNTI7Zn2Q2Y714cHhIB2Tmgdoe3J76IM1HuYgokP5FD8HD9eFhz5Y42EOInpizahY8wnsrwvr+uDjupCDHwcRHamQTx4cPFwTcvDjIOqI6e17+/fvJy2t4T5Weno61dXNvzE3KyuLrKysqGt075hX0rXrPB4cttIxry9tz3k89MEaD3MQ0aF8it95PFwXHvpgjYc5iOiJNaNizSewvy6s64OP60IOfhxEdKRCPnlw8HBNyMGPg6gjpldKXXbZZfzgBz/gD3/4A+vWreOZZ57hpz/9KVdccUWHCfUcBQXFsZrVIw0KRkHP4sR2KKOUDSylmhi/r/QI1VSxnnfZyHttdvDQB2s8zEFEh/Ipfg4ergsPfbDGwxxE9KRCRlnXBx/XhRz8OIjoSIV88uDg4ZqQgx8HUUdMl+TDDz/MZz7zGb7yla8wYsQIvvGNb/DFL36Re+65p0OlTp5Ku74V4eSpyeEwn4eItDE100hnPg+328FDH6zxMAfROsqn+Dp4uC489MEaD3MQ0ZEqGWVdH3xcF3Lw4yBaJ1XyyYODh2tCDn4cREhMU8jNzeWBBx5g/fr1HDhwgLVr1/L973+fY445pkOlBl8L3YogEuM3NEbSw8cNviY5HJYwhx2sp4rKmB5XRSXbWcc7zG23g4c+WONhDqJ1lE/xdfBwXXjogzUe5iCiI1Uyyro++Lgu5ODHQbROquSTBwcP14Qc/DiIkLa+eLFTyciBS14JP0Qu2sCIpIfHT5wXPj4ZHCo5yIOM5yB7or5YqqjkIHt4kHFUcrDdDh76YI2HOQg/eLgmPDh4uC489MEaD3MQvrC+Lqzrg4/rQg5+HIQfPOSDtYOHa0IOfhxEiMtNKYDuJ8IVi6DrwCN3NGd65P6uA8Pj84cml8M2VnMfo9nFJoBm3/dac/8uNnEfo9nGmg5z8NAHazzMQfjBwzXhwcHDdeGhD9Z4mIPwhfV1YV0ffFwXcvDjIPzgIR+sHTxcE3Lw4yAcb0pBeOFfvRzGzoSCkU0fUzAy/PnVyzvnLxkeHLaxhrsYwSwmU0Zpk8eUUcosJnMXIzrlIvHQB2s8zEH4wcM14cHBw3XhoQ/WeJiD8IX1dWFdH3xcF3Lw4yD84CEfrB08XBNy8OOQ6mRYC7RGRg4Mmxzeti+F3SuhsiJ8CWX3YeG3KKSCQyUHWchsFjKbQorpwzByyOMAFXzEymYvoI7EQx+s8TAH4QcP14QHBw/XhYc+WONhDsIX1teFdX3wcV3IwY+D8IOHfLB28HBNyMGPQyrjflOqPj1H2f/FwoNDGaXmF4aHPljjYQ7CDx6uCQ8OHq4LD32wxsMchC+srwvr+uDjupCDHwfhBw/5YO3g4ZqQgx+HVMP12/eEEEIIIYQQQgghRHKiTSkhhBBCCCGEEEIIEXe0KSWEEEIIIYQQQggh4k4kCIIgngXLy8vp3r07AF36xbNyyP6tQABEoEvf+NeXgxy8OVjXB9i/Jfzf3bt3k5+fbyOBfT6Bk3loTcpBDg0dHGSU8kkOXurLwZmD8glwMgs5yMFJfTcOUeZT3DelNm7cSGFhYTxLCiEShLKyMgYOHGhWX/kkhGgJy4xSPgkhWkL5JITwSmv5FPdNqerqajZv3kxubi6RSCTmx1dUVFBYWEhZWRl5eXmdYCiHRHGwri+HjnMIgoA9e/bQv39/0tLs3lWsfJJDMjlY108mBw8Z1d58Avt5WNeXgxy8OSif6rCehQcH6/pykENHO0SbTxntkWwLaWlpHbKLn5eXZzYcOfhysK4vh45xsHzbXg3KJzkko4N1/WRxsM6ojsonsJ+HdX05yMGbg/KpDutZeHCwri8HOXSkQzT5pA86F0IIIYQQQgghhBBxR5tSQgghhBBCCCGEECLuJNymVFZWFt/97nfJysqSQ4o7WNeXgy8HD3jogxzk4KW+HPxh3Qvr+nKQgzcH6/qe8NALawfr+nKQg5VD3D/oXAghhBBCCCGEEEKIhHullBBCCCGEEEIIIYRIfLQpJYQQQgghhBBCCCHijjalhBBCCCGEEEIIIUTcSahNqYULF5Kens7EiRPjXnvy5MlEIpHaW0FBARdffDHLli2Lu8vWrVu55ZZbOOGEE8jKyqKwsJDLLruM1157rdNr1+9DZmYmffr0Ydy4cTzxxBNUV1d3ev3GDvVvF198cVzqt+axZs2auNTfunUr06ZNY8iQIWRnZ9OnTx/GjBnDY489xv79+zu9/uTJk/n0pz991P0LFiwgEomwe/fuTnfwhjJK+dTYwyqjrPMJbDNK+XQ0yiflU2MP5ZOeQ3lB+aR8auyhfEqtfEqoTakZM2Zwyy238Oabb7J58+a417/44ovZsmULW7Zs4bXXXiMjI4NLL700rg7r1q3j1FNP5fXXX+fHP/4x77//Pi+//DIlJSVMmTIlLg41fVi3bh0vvfQSJSUlTJs2jUsvvZTDhw/H1aH+7be//W1carfmMWjQoE6v+/e//51Ro0bxyiuvcO+997J06VIWLlzIbbfdxgsvvMCrr77a6Q7iaFI9o5RPR3tYZpRVPoEyyiPKJ+VTYw/lk/LJC8on5VNjD+VTauVThrVAtOzdu5e5c+fyzjvvsHXrVmbNmsU3v/nNuDpkZWXRt29fAPr27csdd9zBv/zLv/DPf/6TXr16xcXhK1/5CpFIhMWLF9O1a9fa+z/xiU9w0003xcWhfh8GDBjApz71Kc4880wuuOACZs2axb//+7/H1cESK4+vfOUrZGRk8M477zRYByeccAKTJk1CX6oZf5RRyqfmPKywdFBG+UL5pHxqzsMK5ZOoQfmkfGrOwwrlU/xJmFdKPf300wwfPpxhw4Zx/fXX88QTT5gOZe/evTz55JMMGTKEgoKCuNTcuXMnL7/8MlOmTGmwSGvo3r17XDya4vzzz2fkyJH83//9n5lDqrBjxw5eeeWVZtcBQCQSibOVSPWMUj6JGpRR/lA+KZ9EiPLJH8on5ZMISeV8SphNqRkzZnD99dcD4UvqysvLeeONN+Lq8MILL9CtWze6detGbm4uzz//PHPnziUtLT5tXLNmDUEQMHz48LjUi5Xhw4ezbt26uNSqP4ua27333huX2i15XHXVVZ1es2YdDBs2rMH9PXv2rPW4/fbbO90Dmp7DhAkT4lLbG6meUcqnhnjIKIt8Aj8ZpXyqQ/mkfKqP8sk+n0AZVYPySflUH+VTauZTQrx9b+XKlSxevJhnnnkGgIyMDK655hpmzJjBeeedFzePkpISHnvsMQB27drFz372MyZMmMDixYspKirq9PreX64XBEHcdm/rz6KGY489Ni61W/Joblc7HixevJjq6mquu+46Dh06FJeaTc1h0aJFtU8uUgVllPKpMR4yylM+QfwzSvkUonxSPjVG+XQ0eg5lg/JJ+dQY5dPRpEI+JcSm1IwZMzh8+DD9+/evvS8IArKysnjkkUfIz8+Pi0fXrl0ZMmRI7X//6le/Ij8/n8cff5zvf//7nV5/6NChRCIRVqxY0em12sLy5cvj9iFwjWdhhYXHkCFDiEQirFy5ssH9J5xwAgA5OTlxc2nq99+4cWPc6ntBGaV8aoyHjLJy8JJRyqcQ5ZPyqTHKJ/t8AmUUKJ9A+dQY5VNq5pP7t+8dPnyYX//61/zXf/0XpaWltbf33nuP/v37m3zjWg2RSIS0tDQOHDgQl3rHHnssF110EY8++ij79u076ueWXx/7+uuv8/7773PllVeaOaQKBQUFjBs3jkceeaTJdSDiizIqRPkkalBG+UH5FKJ8EjUon/ygfApRPokaUjmf3L9S6oUXXmDXrl3cfPPNR+2WX3nllcyYMYMvfelLcXE5dOgQW7duBcKXdj7yyCPs3buXyy67LC71AR599FHGjBnDGWecwd13380pp5zC4cOHmTdvHo899hjLly/vdIeaPlRVVfHRRx/x8ssvM336dC699FJuuOGGTq9f36E+GRkZ9OzZMy71rfnZz37GmDFjOO2007jrrrs45ZRTSEtLY8mSJaxYsYJTTz3VWjFlUEbVoXw62qM+yihlVLxRPtWhfDraoz7KJ+VTvFE+1aF8OtqjPsqnFMinwDmXXnppcMkllzT5s0WLFgVA8N5773W6x4033hgAtbfc3Nzg9NNPD373u991eu3GbN68OZgyZUpQVFQUHHPMMcGAAQOCyy+/PJg/f36n167fh4yMjKBXr17BhRdeGDzxxBNBVVVVp9dv7FD/NmzYsLjUr+8xadKkuNasz+bNm4OvfvWrwaBBg4LMzMygW7duwRlnnBH8+Mc/Dvbt29fp9Zv7/efPnx8Awa5duzrdwQPKqIakej419rDKKOt8CgLbjFI+hSifGqJ8Uj7VoOdQ9iifGqJ8Uj7VkIr5FAkC55+uJoQQQgghhBBCCCGSDvefKSWEEEIIIYQQQgghkg9tSgkhhBBCCCGEEEKIuKNNKSGEEEIIIYQQQggRd7QpJYQQQgghhBBCCCHijjalhBBCCCGEEEIIIUTc0aaUEEIIIYQQQgghhIg72pQSQgghhBBCCCGEEHFHm1JCCCGEEEIIIYQQIu5oU0oIIYQQQgghhBBCxB1tSiUBP//5z8nNzeXw4cO19+3du5fMzEzOO++8BscuWLCASCTC2rVrG9wfBAETJkwgEonw7LPPNvjZ1KlTOfXUU8nKyqK4uDgmt0GDBvHqq682+bOtW7fyuc99jr59+9K1a1c+9alP8b//+79Rnffzn/883/72t5v82eTJk4lEIrW3goICLr74YpYtW9bguB/84AecffbZdOnShe7duzd5rvrnqbnNmTMnKkchROfnE8CsWbM45ZRTyM7Opnfv3kyZMiUqt+byad26dU1e+5FIhP/5n/9p9bwlJSX86le/avJn5513XoPz9enTh6uuuor169c3OK613D148CCTJ0/mk5/8JBkZGXz605+O6ncWQtTRnnz64he/yODBg8nJyaFXr15MmjSJFStWNHjMkiVLuOCCC+jevTs9evTgoosu4r333ovKraXnTwALFy7k/PPPp2vXruTl5XHuuedy4MCBVs/b3udP69at4+abb2bQoEHk5OQwePBgvvvd7/Lxxx83ONeyZcv4l3/5F7KzsyksLORHP/pRVL+3EKKOzn4OtWHDBiZOnEiXLl3o3bs3t956a4NazXHgwAG6du3KmjVrmvz58ccff9Tzp/vuuy+q37ml7Kt/3vT0dPr378/NN9/Mrl27ao+J9vnRo48+yogRI8jJyWHYsGH8+te/jspPdA7alEoCSkpK2Lt3L++8807tfX/605/o27cvixYt4uDBg7X3z58/n+OOO47Bgwc3OMcDDzxAJBJptsZNN93ENddcE5PXsmXL2LVrF2PHjm3y5zfccAMrV67k+eef5/333+df//Vfufrqq1m6dGmL562qquKFF17g8ssvb/aYiy++mC1btrBlyxZee+01MjIyuPTSSxsc8/HHH3PVVVfx5S9/ucV6M2fOrD3Xli1b9Jc/IWKgs/Pppz/9Kd/61re44447+PDDD3n11Ve56KKLWvVqKZ8KCwsbXPNbtmzhe9/7Ht26dWPChAktnnfnzp385S9/4bLLLmv2mC984Qts2bKFzZs389xzz1FWVsb1119/1HEt5W5VVRU5OTlMnTqVCy+8sJXfVgjRFO3Jp1NPPZWZM2eyfPly/vjHPxIEAePHj6eqqgoI/+J48cUXc9xxx7Fo0SL+/Oc/k5uby0UXXURlZWWLXq09f1q4cCEXX3wx48ePZ/HixSxZsoSvfvWrpKW1/LS+I54/rVixgurqan7xi1/w4Ycfcv/99/Pzn/+cb37zm7XHVFRUMH78eIqKinj33Xf58Y9/zF133cUvf/nLFv2EEA3pzOdQVVVVTJw4kY8//pi33nqL2bNnM2vWLP7f//t/rXrNmzePoqIihgwZ0uwxd999d4PnUbfcckur520t++qfd8OGDTz11FO8+eabTJ06tcHv1drzo8cee4w777yTu+66iw8//JDvfe97TJkyhd///vetOopOIhBJQb9+/YLp06fX/vdtt90WTJkyJRgxYkQwf/782vvPPffc4MYbb2zw2KVLlwYDBgwItmzZEgDBM88802SN7373u8HIkSOjdrr77ruDa665ptmfd+3aNfj1r3/d4L5jjz02ePzxx1s875tvvhn069cvqK6ubvLnN954YzBp0qQG9/3pT38KgGDbtm1HHT9z5swgPz+/yXO11A8hRHR0Vj7t3LkzyMnJCV599dWYnVrLp8YUFxcHN910U6vH/frXvw5Gjx7d7M/Hjh0bTJs2rcF9//3f/x106dKlyeOjyd2mMk8IER3tyaf6vPfeewEQrFmzJgiCIFiyZEkABBs2bKg9ZtmyZQEQrF69ukWn1vJp9OjRwbe//e1WfrOj6ejnTzX86Ec/CgYNGlT73z/72c+CHj16BIcOHaq97/bbbw+GDRsWs7MQqU5nPYd68cUXg7S0tGDr1q219z322GNBXl5eg2u3KW666abg9ttvb/bnRUVFwf333x/V71ef1rKvqfPec889wUknndTk8c09PzrrrLOCb3zjGw3u+/rXvx6MGTMmZmfRMeiVUklCSUkJ8+fPr/3v+fPnc9555zF27Nja+w8cOMCiRYsoKSmpPW7//v189rOf5dFHH6Vv374d6vT8888zadKkZn9+9tlnM3fuXHbu3El1dTVz5szh4MGDR70ctanzXnbZZS2+sqs+e/fu5cknn2TIkCEUFBTE8isAMGXKFHr27MkZZ5zBE088QRAEMZ9DiFSms/Jp3rx5VFdXs2nTJkaMGMHAgQO5+uqrKSsra9WptXyqz7vvvktpaSk333xzh54XwldWPf3004wePTrqxwghOo625lN99u3bx8yZMxk0aBCFhYUADBs2jIKCAmbMmMHHH3/MgQMHmDFjBiNGjOD4449v0amlHNm2bRuLFi2id+/enH322fTp04exY8fy5z//udXftbOeP5WXl3PsscfW/vfChQs599xzOeaYY2rvu+iii1i5cmWDt9kIIVqns55DLVy4kE9+8pP06dOn9r6LLrqIiooKPvzww2Z9qqureeGFF1p9rnPfffdRUFDAqFGj+PGPfxzV2wJjfQ61adMmfv/738f8HOrQoUNkZ2c3uC8nJ4fFixe3+kpW0TloUypJKCkp4S9/+QuHDx9mz549LF26lLFjx3LuueeyYMECIAyfQ4cONQisr33ta5x99tkxBUA0bNq0iWXLlrX4Vpenn36ayspKCgoKyMrK4otf/CLPPPNMiy8FBXjuuedafOk5wAsvvEC3bt3o1q0bubm5PP/888ydO7fVl7Y35u677+bpp59m3rx5XHnllXzlK1/h4YcfjukcQqQ6nZVPf//736murubee+/lgQce4He/+x07d+5k3LhxR32+SX2iyaf61PxF8uyzz27xuEOHDvHyyy+3mk8/+9nP6NatG127dqWgoICVK1fyxBNPROUihOhY2ppPUHctd+vWjZdeeol58+bVbsTk5uayYMECnnzySXJycujWrRsvv/wyL730EhkZGc36tJZPf//73wG46667+MIXvsDLL7/Mpz71KS644AJWr17d4u/aGc+f1qxZw8MPP8wXv/jF2vu2bt3a4C+6QO1/b926tcX6QoiGdNZzqLZep2+//TZAixtBU6dOZc6cOcyfP58vfvGL3Hvvvdx2220t/p7RPje7/fbb6datGzk5OQwcOJBIJMJPf/rTFh/TmIsuuohf/epXvPvuuwRBwDvvvMOvfvUrKisr2b59e0znEh2DNqWShPPOO499+/axZMkS/vSnP3HiiSfSq1cvxo4dW/ue4wULFnDCCSdw3HHHAeFu9Ouvv84DDzzQ4T7PP/8855xzTrMfIA7wne98h927d/Pqq6/yzjvv8PWvf52rr76a999/v9nHLF++nM2bN3PBBRe0WL+kpITS0lJKS0tZvHgxF110ERMmTDjqw4Rb4zvf+Q5jxoxh1KhR3H777dx22238+Mc/jukcQqQ6nZVP1dXVVFZW8tBDD3HRRRdx5pln8tvf/pbVq1c3+FfFxkSTTzUcOHCA3/zmN1G9Sur111+nd+/efOITn2jxuOuuu47S0lLee+89/vznPzNkyBDGjx/Pnj17Wq0hhOhY2pJPNVx33XUsXbqUN954gxNPPJGrr7669jNeDhw4wM0338yYMWN4++23+ctf/sLJJ5/MxIkTW/xA8tbyqbq6Ggg/aP3zn/88o0aN4v7772fYsGEtbm53xvOnTZs2cfHFF3PVVVfxhS98ocXzCiHahre/4z333HNceumlLf5D/9e//nXOO+88TjnlFL70pS/xX//1Xzz88MMcOnSo2cdE+9zs1ltvpbS0lGXLlvHaa68BMHHixNrP84uG73znO0yYMIEzzzyTzMxMJk2axI033ggQ8wsYRMegricJQ4YMYeDAgcyfP5/58+fXfkBc//79KSws5K233mL+/Pmcf/75tY95/fXXWbt2Ld27dycjI6P2X+6uvPLKVt9C1xrPP/98i/8at3btWh555BGeeOIJLrjgAkaOHMl3v/tdTjvtNB599NEWzztu3LijXnLZmK5duzJkyBCGDBnC6aefzq9+9Sv27dvH448/3ubfCcJ/Fdi4cWOLoSqEaEhn5VO/fv0AOOmkk2of16tXL3r27MmGDRua9Wktn+rzu9/9jv3793PDDTe0emy0583Pz6/NpzFjxjBjxgxWr17N3Llzo3ISQnQcbcmnGvLz8xk6dCjnnnsuv/vd71ixYgXPPPMMAL/5zW9Yt24dM2fO5PTTT+fMM8/kN7/5Df/4xz947rnnmvVpLUeayj2AESNGtJp7Hfn8afPmzZSUlHD22Wcf9QHmffv25aOPPmpwX81/d/RHRQiR7HTWc6i2XqexPIeqYfTo0Rw+fJh169a1+7w9e/ZkyJAhDB06lPPPP58HHnigtgfRkpOTwxNPPMH+/ftZt24dGzZs4Pjjjyc3N5devXpFfR7RcWhTKokoKSlhwYIFLFiwoMGm0rnnnstLL73E4sWLG7ys84477mDZsmW1/yJWWloKwP3338/MmTPb7LF3717mz5/f4lsC9+/fDxy9G52enl77r4BN8dxzz7XprYaRSIS0tLSovi65JUpLS+nRowdZWVntOo8QqUZn5NOYMWMAWLlyZe3jdu7cyfbt2ykqKmrSI5p8qs+MGTO4/PLLW32SEgQBv//979uUT+np6QDtzichRNuINZ+aIggCgiCo/Uer/fv3k5aW1uDzm2r+u7nnOdHk0/HHH0///v0b5B7AqlWrms096NjnT5s2beK8886r/QbCxs/lzjrrLN58880Gn80yb948hg0bRo8ePWJ2ECLV6YznUGeddRbvv/8+27Ztq33cvHnzyMvLO2rTu4bVq1ezfv16xo0bF5N/aWkpaWlp9O7du8mfx/rcrD7teQ6VmZnJwIEDSU9PZ86cOa2+Akx0Hs2/qV0kHCUlJUyZMoXKysoGX6U5duxYvvrVr/Lxxx83CKy+ffs2uRN+3HHHMWjQoNr/XrNmDXv37mXr1q0cOHCgNthOOumkBh9iWcPLL7/MiSee2OIHeQ4fPpwhQ4bwxS9+kZ/85CcUFBTw7LPPMm/ePF544YUmH7Nt2zbeeecdnn/++dZawaFDh2rfD71r1y4eeeQR9u7d2+Br2jds2MDOnTvZsGEDVVVVtb/XkCFD6NatG7///e/56KOPOPPMM8nOzmbevHnce++9fOMb32i1vhCiIZ2RTyeeeCKTJk1i2rRp/PKXvyQvL48777yT4cOHN/sXyGjyqYY1a9bw5ptv8uKLL7Z67Lvvvsv+/fs555xzWj12//79tfn00Ucfcc8995Cdnc348eMb1G4td//2t7/x8ccfs3PnTvbs2VN7THFxcasOQog6Ys2nv//978ydO5fx48fTq1cvNm7cyH333UdOTg6XXHIJAOPGjePWW29lypQp3HLLLVRXV3PfffeRkZHRrnyKRCLceuutfPe732XkyJEUFxcze/ZsVqxYwe9+97smH9ORz59qNqSKior4yU9+wj//+c/ax9Zk9mc/+1m+973vcfPNN3P77bfzwQcf8OCDD3L//fe3Wl8IcTSd8Rxq/PjxnHTSSXzuc5/jRz/6EVu3buXb3/42U6ZMafYf35977jkuvPBCunTp0qzrwoULaz90PTc3l4ULF/K1r32N66+/vtlN6Viem+3Zs4etW7cSBAFlZWXcdttt9OrVq8Hnfrb2/GjVqlUsXryY0aNHs2vXLn7605/ywQcfMHv27Fbri07C8qv/RMfyj3/8IwCC4cOHN7h/3bp1ARDVV/HS6OtCgyD8CnPgqNs//vGPJs9x/fXXB9/61rdarbVq1argX//1X4PevXsHXbp0CU455ZTg17/+dbPH/+pXv4rqqzpvvPHGBp65ubnB6aefHvzud79r8biaW83Xq7700ktBcXFx0K1bt6Br167ByJEjg5///OdBVVVVqw5CiIZ0Vj6Vl5cHN910U9C9e/fg2GOPDa644ooGX8HemGjzKQiC4M477wwKCwujuua//e1vB9ddd12rxzXO0x49egRjx44NXn/99RaPayp3i4qKmjxGCBEbsebTpk2bggkTJgS9e/cOMjMzg4EDBwaf/exngxUrVjQ47pVXXgnGjBkT5OfnBz169AjOP//8YOHChc16xJJP06dPDwYOHBh06dIlOOuss4I//elPzR7bkc+fZs6c2WTuNM6e9957LzjnnHOCrKysYMCAAcF9990X1e8lhDiaznoOtW7dumDChAlBTk5O0LNnz+D/+//+v6CysrLZc5xzzjnB448/3mKdd999Nxg9enSQn58fZGdnByNGjAjuvffe4ODBg80+Jtrsa/y8p1evXsEll1wSLF26tMXjGmfU3/72t6C4uDjIyckJ8vLygkmTJh2V3yK+RIJA328vOo7Dhw/Tp08fXnrpJc4444wOPffll1/OOeec0+q3NwghRFN0Zj6dcsopfPvb3+bqq6/u0PMKIVIDPX8SQnhm+/bt9OvXj40bNx71rX3toTOzTyQOetOk6FB27tzJ1772NU4//fQOP/c555zDv/3bv3X4eYUQqUFn5dPHH3/MlVde2erXGAshRHPo+ZMQwjM7d+7kpz/9aYduSNWct7OyTyQOeqWUEEIIIYQQQgghhIg7eqWUEEIIIYQQQgghhIg72pQSQgghhBBCCCGEEHFHm1JCCCGEEEIIIYQQIu5oU0oIIYQQQgghhBBCxB1tSgkhhBBCCCGEEEKIuKNNKSGEEEIIIYQQQggRd7QpJYQQQgghhBBCCCHijjalhBBCCCGEEEIIIUTc0aaUEEIIIYQQQgghhIg72pQSQgghhBBCCCGEEHFHm1JCCCGEEEIIIYQQIu5oU0oIIYQQQgghhBBCxB1tSgkhhBBCCCGEEEKIuKNNKSGEEEIIIYQQQggRdzLiXbC6uprNmzeTm5tLJBKJd3khhEOCIGDPnj3079+ftDS7vXLlkxCiKTxklPJJCNEUyichhFeizae4b0pt3ryZwsLCeJcVQiQAZWVlDBw40Ky+8kkI0RKWGaV8EkK0hPJJCOGV1vIp7ptSubm5tf+/S794V4f9W4EAiECXvvGvLwc5eHOwrg+wf0v4v/XzwQLrfAIn89CalIMcGjo4yCjlkxy81JeDMwflE+BkFnKQg5P6bhyizKe4b0rVvKSzSz+4fnO8q8NTA2HfJujaH67bGP/6cpCDNwfr+gBP9g9Dy/ol39b5BD7mYe1gXV8OcmiMh4xSPsnBS305+HJQPoV4mIUc5OClvheHaPNJH3QuhBBCCCGEEEIIIeKONqWEEEIIIYQQQgghRNzRppQQQgghhBBCCCGEiDtx/0yp9rB9KexeAZV7IDMXug+HnqPkkIoO1vW9OHhAfQjx0Ac5yMFLfS+oD3VY98K6vhzk4A31oA4PvbB2sK4vB18OHohnH9xvSh0+AGvnwAcPwY7So39eUAwnT4XB10JGjhyS2cG6vhcHD6gPIR76IAc5eKnvBfWhDuteWNeXgxy8oR7U4aEX1g7W9eXgy8EDVn1w/fa93avg6RHwxk2wY1nTx+xYFv786RFQvloOyepgXd+LgwfUhxAPfZCDHLzU94L6UId1L6zry0EO3lAP6vDQC2sH6/py8OXgAcs+uN2U2r0Knj0T9tV8fWF1MwceuX/fRnhmdMc2Rw4+HKzre3HwgPoQ4qEPcpCDl/peUB/qsO6FdX05yMEb6kEdHnph7WBdXw6+HDxg3YeYN6XefPNNLrvsMvr3708kEuHZZ5/tGJN6HD4AL46HygoIqqJ7TFAVHv+HceHj5ZAcDtb1vTh4IBH6oHySQ6o5WNf3QiL0IR75BPa9sK4vBzl4IxF6kCr55MHBur4cfDl4wEMfYt6U2rdvHyNHjuTRRx9tf/VmWDsH9q6Pvik1BFXh49bOlUOyOFjX9+LggUTog/JJDqnmYF3fC4nQh3jkE9j3wrq+HOTgjUToQarkkwcH6/py8OXgAQ99iHlTasKECXz/+9/niiuuaH/1ZvjgIdr+xsK0I4+XQ1I4WNf34uCBROiD8kkOqeZgXd8LidCHeOQT2PfCur4c5OCNROhBquSTBwfr+nLw5eABD31oa/lOY/vSI5/03tz7GFujGnYsDc8jh8R2sK7vxcED6kOIhz7IQQ5e6ntBfajDuhfW9eUgB2+oB3V46IW1g3V9Ofhy8ICXPnT6ptShQ4eoqKhocGuJ3Ss6pu7ule14rBxcOFjX9+LggWTtg/JJDonsYF3fC8nah1jzCex7YV1fDnLwRrL2IBHzyYODdX05+HLwgJc+dPqm1PTp08nPz6+9FRYWtnh85Z6OqVvZejbKwbmDdX0vDh5I1j4on+SQyA7W9b2QrH2INZ/AvhfW9eUgB28kaw8SMZ88OFjXl4MvBw946UOnb0rdeeedlJeX197KyspaPD4zt2PqZua147FycOFgXd+LgweStQ/KJzkksoN1fS8kax9izSew74V1fTnIwRvJ2oNEzCcPDtb15eDLwQNe+pDRMRrNk5WVRVZWVtTHdx/eMXXbcx45+HCwru/FwQPJ2gflkxwS2cG6vheStQ+x5hPY98K6vhzk4I1k7UEi5pMHB+v6cvDl4AEvfYj5lVJ79+6ltLSU0tJSAP7xj39QWlrKhg0b2mdyhJ6joKC4LWZHSIOCUdCzWA6J7mBd34uDBxKlD8onOaSSg3V9LyRKHzo7n8C+F9b15SAHbyRKD1Ihnzw4WNeXgy8HD3jpQ8zl33nnHUaNGsWoUaMA+PrXv86oUaP4f//v/7XPpB4nT6VdnwB/8lQ5JIuDdX0vDh5IhD4on+SQag7W9b2QCH2IRz6BfS+s68tBDt5IhB6kSj55cLCuLwdfDh7w0IeYN6XOO+88giA46jZr1qz22xxh8LXQrQgi6bE9LpIePm7wNXJIFgfr+l4cPJAIfVA+ySHVHKzreyER+hCPfAL7XljXl4McvJEIPUiVfPLgYF1fDr4cPOChD53+QedtISMHLnkl/MCsaJsTSQ+PnzgvfLwcksPBur4XBw+oDyEe+iAHOXip7wX1oQ7rXljXl4McvKEe1OGhF9YO1vXl4MvBAx764HJTCqD7iXDFIug68MgdzZkeub/rwPD4/KFySDYH6/peHDygPoR46IMc5OClvhfUhzqse2FdXw5y8IZ6UIeHXlg7WNeXgy8HD1j3we2mFIS/5NXLYexMKBjZ9DEFI8OfX728cxaHHHw4WNf34uAB9SHEQx/kIAcv9b2gPtRh3Qvr+nKQgzfUgzo89MLawbq+HHw5eMCyDxkdd6rOISMHhk0Ob9uXwu6VUFkRvlys+7DwE+PlkBoO1vW9OHhAfQjx0Ac5yMFLfS+oD3VY98K6vhzk4A31oA4PvbB2sK4vB18OHrDqg/tNqfr0HGW/IOTgw8G6vhcHD6gPIR76IAc5eKnvBfWhDuteWNeXgxy8oR7U4aEX1g7W9eXgy8ED8eyD67fvCSGEEEIIIYQQQojkRJtSQgghhBBCCCGEECLuaFNKCCGEEEIIIYQQQsSdSBAEQTwLVlRUkJ+fDxHo2j+elUP2b4GgGiJp0KVf/OvLQQ7eHKzrA+zbDARQXl5OXl6ejQT2+QQ+5mHtYF1fDnJojIeMUj7JwUt9OfhyUD6FeJiFHOTgpb4Xh2jzyW5TSgghGuFmU0oIIZrAxV/6hBCiCZRPQgivtJZPdt++p1dKyUEOLhys60PdLrob9C99Kb8m5SCH+rjKKOVTyjtY15eDLwflU4iHWchBDl7qe3GINp/MNqW69IXrNsa/7lMDYd+mcDAW9eUgB28O1vUBnuwfBqcXrPIJfMzD2sG6vhzk0BhPGaV8koN1fTn4clA+hXiYhRzk4KW+F4do80kfdC6EEEIIIYQQQggh4o42pYQQQgghhBBCCCFE3NGmlBBCCCGEEEIIIYSIO8qzJcUAAKbnSURBVHYfdN4Gti+F3Sugcg9k5kL34dBzVOo5FFJMX4aTTS4H2cNWVlBGaUo5eJiDHPw4eMBDHzw4WGeDFwfrWVjXl4M/rHthXR98ZIMHBw+zkIN9fU946IW1g4ds8OBgPQc52Di435Q6fADWzoEPHoIdpUf/vKAYTp4Kg6+FjJzkdcgkm9O5lhKmchxHr4YNLGU+D7GEOVRyMCkdPMxBDn4cPOChDx4crLPBi4P1LKzry8Ef1r2wrg8+ssGDg4dZyMG+vic89MLawUM2eHCwnoMc7B0iQRDE9UtEKyoqyM/Pp0s/uH5zy8fuXgUvjoe96wnfaFjdxEFH7u9WBBPnQf7Qls9Z8yn0XQdE9yn0Hhx6M5RpvEIBRQRUk0b6UcdUU0WENHawngcZxzbWJJVDZ8xBDrHX7yyHmm9mKC8vJy8vr3WJTsI6n8B+PcTqYJ0NXhysr00PayGZHTxkVCz5BFqT0DnZ4MEh0fJJDp1XH5RPNSTaekjWfIrVwcOfFdZrIZkdos0nt58ptXsVPHsm7KtpYFNNqXf/vo3wzGgoX51cDr0Zyh28TQ8GECHSZFgApJFOhAg9GMAdLKI3Q5LGwcMc5ODHwQMe+uDBwTobvDhYz8K6vhz8Yd0L6/rgIxs8OHiYhRzs63vCQy+sHTxkgwcH6znIwY+Dy02pwwfCXbrKCgiqontMUBUe/4dx4eOTwSGTbKbxCtnkkk5mVI9JJ5NscpnGPDLJTngHD3OQgx8HD3jogwcH62zw4mA9C+v6cvCHdS+s64OPbPDg4GEWcrCv7wkPvbB28JANHhys5yAHXw4xbUpNnz6d008/ndzcXHr37s2nP/1pVq5c2X6LRqydE75sLNqm1BBUhY9bOzc5HE7nWgooijosakgnk54cz2lck/AOHuYgBz8OLaF8iq+DdTZ4cbCehXV9OURPqmSUdX3wkQ0eHDzMQg729aMhVfLJg4OHbPDgYD0HOfhyiGlT6o033mDKlCm8/fbbzJs3j8rKSsaPH8++ffvab1KPDx6K1aweaUcenwQOJUwlaPa1cy1TTRUl3JLwDh7mIAc/Di2hfIqvg3U2eHGwnoV1fTlET6pklHV98JENHhw8zEIO9vWjIVXyyYODh2zw4GA9Bzn4coip/Msvv8zkyZP5xCc+wciRI5k1axYbNmzg3Xffbb/JEbYvPfJJ7227TqAadiwNz5PIDoUUcxyjmn1/b2ukkU4Rp1JIccI6eJiDHPw4tIbyKX4O1tngxcF6Ftb15RAbqZBR1vXBRzZ4cPAwCznY14+WVMgnDw4essGDg/Uc5ODLAdr5mVLl5eUAHHvssc0ec+jQISoqKhrcWmL3ivYY1TtPO15x6sGhL8M7xKEPwxLWwcMc5ODHIVaUT53nYJ0NXhysZ2FdXw7to7WMijWfwL4X1vXBRzZ4cPAwCznY128ryZhPHhw8ZIMHB+s5yMGXA7RjU6q6upr//M//ZMyYMZx88snNHjd9+nTy8/Nrb4WFhS2et3JPW40anaf1bHTtkE1uhzjk0PavhrV28DAHOfhxiAXlU+c6WGeDFwfrWVjXl0PbiSajYs0nsO+FdX3wkQ0eHDzMQg729dtCsuaTBwcP2eDBwXoOcvDlAO3YlJoyZQoffPABc+bMafG4O++8k/Ly8tpbWVlZi8dndsx1QmbbrxMXDgfpmBVygLavEGsHD3OQgx+HWFA+da6DdTZ4cbCehXV9ObSdaDIq1nwC+15Y1wcf2eDBwcMs5GBfvy0kaz55cPCQDR4crOcgB18OABltedBXv/pVXnjhBd58800GDhzY4rFZWVlkZWVFfe7uHfOKwnadx4PDVjrmtXTtOY+1g4c5yMGPQ7Qonzr/PNbZ4MXBehbW9eXQNqLNqFjzCex7YV0ffGSDBwcPs5CDff1YSeZ88uDgIRs8OFjPQQ6+HCDGV0oFQcBXv/pVnnnmGV5//XUGDRrUvupN0HMUFBTHalaPNCgYBT2LE9uhjFI2sJRqYvxuxiNUU8V63mUj7yWsg4c5yMGPQ2son+LnYJ0NXhysZ2FdXw6xkQoZZV0ffGSDBwcPs5CDff1oSYV88uDgIRs8OFjPQQ6+HIi1/JQpU3jyySf5zW9+Q25uLlu3bmXr1q0cOHCgfRaNOHkq7foE+JOnJofDfB4i0sYVkkY683k44R08zEEOfhxaQvkUXwfrbPDiYD0L6/pyiJ5UySjr+uAjGzw4eJiFHOzrR0Oq5JMHBw/Z4MHBeg5y8OUQ02p87LHHKC8v57zzzqNfv361t7lz57bfpB6Dr4VuRRCJ8ZsqI+nh4wZfkxwOS5jDDtZTRWVMj6uiku2s4x3aPxdrBw9zkIMfh5ZQPsXXwTobvDhYz8K6vhyiJ1Uyyro++MgGDw4eZiEH+/rRkCr55MHBQzZ4cLCegxx8OcT89r2mbpMnT26/ST0ycuCSV8IPzIq2OZH08PiJ88LHJ4NDJQd5kPEcZE/UoVFFJQfZw4OMo5KDCe/gYQ5y8OPQEsqn+DpYZ4MXB+tZWNeXQ/SkSkZZ1wcf2eDBwcMs5GBfPxpSJZ88OHjIBg8O1nOQgy+HNn/7XmfT/US4YhF0rfmMveZMj9zfdWB4fP7Q5HLYxmruYzS72ATQ7Pt/a+7fxSbuYzTbWJM0Dh7mIAc/Dh7w0AcPDtbZ4MXBehbW9eXgD+teWNcHH9ngwcHDLORgX98THnph7eAhGzw4WM9BDn4c3G5KQfhLXr0cxs6EgpFNH1MwMvz51cs7J7g9OGxjDXcxgllMpozSJo8po5RZTOYuRnRoWHhx8DAHOfhx8ICHPnhwsM4GLw7Ws7CuLwd/WPfCuj74yAYPDh5mIQf7+p7w0AtrBw/Z4MHBeg5y8OGQ0XGn6hwycmDY5PC2fSnsXgmVFeHLxboPCz8xPhUcKjnIQmazkNkUUkwfhpFDHgeo4CNWNhskyeTgYQ5y8OPgAQ998OBgnQ1eHKxnYV1fDv6w7oV1ffCRDR4cPMxCDvb1PeGhF9YOHrLBg4P1HORg7+B+U6o+PUfZh7UHhzJK4xIQnh08zEEOfhw84KEPHhyss8GLg/UsrOvLwR/WvbCuDz6ywYODh1nIwb6+Jzz0wtrBQzZ4cLCegxxsHFy/fU8IIYQQQgghhBBCJCfalBJCCCGEEEIIIYQQcUebUkIIIYQQQgghhBAi7kSCIAjiWbCiooL8/HyIQNf+8awcsn8LBNUQSYMu/eJfXw5y8OZgXR9g32YggPLycvLy8mwksM8n8DEPawfr+nKQQ2M8ZJTySQ5e6svBl4PyKcTDLOQgBy/1vThEm092m1JCCNEIN5tSQgjRBC7+0ieEEE2gfBJCeKW1fLL79j29UkoOcnDhYF0f6nbR3aB/6Uv5NSkHOdTHVUYpn1Lewbq+HHw5KJ9CPMxCDnLwUt+LQ7T5ZLYp1aUvXLcx/nWfGgj7NoWDsagvBzl4c7CuD/Bk/zA4vWCVT+BjHtYO1vXlIIfGeMoo5ZMcrOvLwZeD8inEwyzkIAcv9b04RJtP+qBzIYQQQgghhBBCCBF3tCklhBBCCCGEEEIIIeKONqWEEEIIIYQQQgghRNyx+6DzNrB9KexeAZV7IDMXug+HnqPkkIoOhRTTl+Fkk8tB9rCVFZRRGj8B7HvgxcHDLDzgYRZy8ONgfV146IEHB+s5eMJ6Htb15VCHh+vCQx+sHTzMwQvWs/DgYF3fi4OH68JDH1LNwf2m1OEDsHYOfPAQ7Cg9+ucFxXDyVBh8LWTkyCGZHTLJ5nSupYSpHMfRV8QGljKfh1jCHCo52PEC2PfAi4OHWXjAwyzk4MfB+rrw0AMPDtZz8IT1PKzry6EOD9eFhz5YO3iYgxesZ+HBwbq+FwcP14WHPqSyQyQIgrh+iWhFRQX5+fl06QfXb2752N2r4MXxsHc94RsNq5s46Mj93Ypg4jzIH9ryOWs+hb7rgOg+hV4OPhx6M5RpvEIBRQRUk0b6UcdUU0WENHawngcZxzbWtPp7xeLQGT3w4BDrWuiMWdR8M0N5eTl5eXmtS3QS1vkE9uvBg0Oi5RN0znVhPYdEdOisPys8ZFQs+QT214WH9ZCsDomWT+CjD9YOyqc6rGfhwSFZ8ylWh2T9O16ircfOcog2n9x+ptTuVfDsmbCvpoFNNaXe/fs2wjOjoXy1HJLNoTdDuYO36cEAIkSaDCuANNKJEKEHA7iDRfRmSMcIYN8DLw4eZuEBD7OQgx8H6+vCQw88OFjPwRPW87CuL4c6PFwXHvpg7eBhDl6wnoUHB+v6Xhw8XBce+iAHp5tShw+Eu3SVFRBURfeYoCo8/g/jwsfLITkcMslmGq+QTS7pZEb1mHQyySaXacwjk+z2CWDfAy8OHmbhAQ+zkIMfB+vrwkMPPDhYz8ET1vOwri+HOjxcFx76YO3gYQ5esJ6FBwfr+l4cPFwXHvogh5CYNqUee+wxTjnlFPLy8sjLy+Oss87ipZdear9FI9bOCV82Fm1TagiqwsetnSuHZHE4nWspoCjqsKohnUx6cjyncU37BLDvgRcHD7NoCeWTHCwcrK8LDz3w4GA9h2hIlYyyri+HOjxcFx76YO3gYQ6tkSr55MHBur4XBw/XhYc+yCEkpk2pgQMHct999/Huu+/yzjvvcP755zNp0iQ+/PDD9pvU44OHYjWrR9qRx8shKRxKmErQ7OsHW6aaKkq4pX0C2PfAi4OHWbSE8kkOFg7W14WHHnhwsJ5DNKRKRlnXl0MdHq4LD32wdvAwh9ZIlXzy4GBd34uDh+vCQx/kUHua6Lnsssu45JJLGDp0KCeeeCI/+MEP6NatG2+//Xb7TY6wfemRT3pv2xqFatixNDyPHBLboZBijmNUs+8vbo000iniVAopbpsA9j3w4uBhFq2hfJJDvB2srwsPPfDgYD2HaEmFjLKuL4c6PFwXHvpg7eBhDtGQCvnkwcG6vhcHD9eFhz7IoY627olRVVXFnDlz2LdvH2eddVazxx06dIiKiooGt5bYvaKtRo3Os7Idj5WDC4e+DO+Q+n0Y1ubHWvfAi4OHWcSC8kkO8XCwvi489MCDg/Uc2kI0GRVrPoH9PKzry6EOD9eFhz5YO3iYQ6wkaz55cLCu78XBw3XhoQ9yqCPmTan333+fbt26kZWVxZe+9CWeeeYZTjrppGaPnz59Ovn5+bW3wsLCFs9fuSdWo2bO03o2ysG5Qza5HVI/h7Z/Pa51D7w4eJhFNCif5BBPB+vrwkMPPDhYzyEWYsmoWPMJ7OdhXV8OdXi4Ljz0wdrBwxyiJdnzyYODdX0vDh6uCw99kEMdMW9KDRs2jNLSUhYtWsSXv/xlbrzxRv72t781e/ydd95JeXl57a2srKzF82d2zBolsx3ZLQcfDgfpmKvkAG2/Sqx74MXBwyyiQfkkh3g6WF8XHnrgwcF6DrEQS0bFmk9gPw/r+nKow8N14aEP1g4e5hAtyZ5PHhys63tx8HBdeOiDHOrIiPUBxxxzDEOGDAHg1FNPZcmSJTz44IP84he/aPL4rKwssrKyoj5/9455NV+7ziMHHw5b6ZjXE7bnPNY98OLgYRbRoHySQzzPY31deOiBBwfrOcRCLBkVaz6B/Tys68uhDg/XhYc+WDt4mEO0JHs+eXCwru/FwcN14aEPcqijzZ8pVUN1dTWHDh1q72lq6TkKCopp1yfAF4yCnsVySHSHMkrZwFKqifH7KY9QTRXreZeNvNc2Aex74MXBwyzaVFf5JIdOdLC+Ljz0wIOD9RzaQ7JllHV9OdTh4brw0AdrBw9zaCvJlk8eHKzre3HwcF146IMcGpwmeu68807efPNN1q1bx/vvv8+dd97JggULuO6669pn0YiTp9KuT4A/eaocksVhPg8RaeNVkkY683m4fQLY98CLg4dZtITySQ4WDtbXhYceeHCwnkM0pEpGWdeXQx0ergsPfbB28DCH1kiVfPLgYF3fi4OH68JDH+QQEtNK2LZtGzfccAPDhg3jggsuYMmSJfzxj39k3Lhx7Tepx+BroVsRRGL8lshIevi4wdfIIVkcljCHHaynisqYHldFJdtZxzvMbZ8A9j3w4uBhFi2hfJKDhYP1deGhBx4crOcQDamSUdb15VCHh+vCQx+sHTzMoTVSJZ88OFjX9+Lg4brw0Ac5hMS0KTVjxgzWrVvHoUOH2LZtG6+++mqHhxVARg5c8kr4gVnRNieSHh4/cV74eDkkh0MlB3mQ8RxkT9ShVUUlB9nDg4yjkoPtE8C+B14cPMyiJZRPcrBwsL4uPPTAg4P1HKIhVTLKur4c6vBwXXjog7WDhzm0RqrkkwcH6/peHDxcFx76IIeQdn+mVGfR/US4YhF0HXjkjuZMj9zfdWB4fP5QOSSbwzZWcx+j2cUmgGbff1xz/y42cR+j2caajhHAvgdeHDzMwgMeZiEHPw7W14WHHnhwsJ6DJ6znYV1fDnV4uC489MHawcMcvGA9Cw8O1vW9OHi4Ljz0QQ6ON6Ug/CWvXg5jZ0LByKaPKRgZ/vzq5R07GDn4ctjGGu5iBLOYTBmlTR5TRimzmMxdjOiUP8Ste+DFwcMsPOBhFnLw42B9XXjogQcH6zl4wnoe1vXlUIeH68JDH6wdPMzBC9az8OBgXd+Lg4frwkMfUt0ho+NO1Tlk5MCwyeFt+1LYvRIqK8KXi3UfFn5ivBxSw6GSgyxkNguZTSHF9GEYOeRxgAo+YmWzQdaRWPfAi4OHWXjAwyzk4MfB+rrw0AMPDtZz8IT1PKzry6EOD9eFhz5YO3iYgxesZ+HBwbq+FwcP14WHPqSyg/tNqfr0HBWfYcjBv0MZpeZ/cFv3wIuDh1l4wMMs5ODHwfq68NADDw7Wc/CE9Tys68uhDg/XhYc+WDt4mIMXrGfhwcG6vhcHD9eFhz6kmoPrt+8JIYQQQgghhBBCiOREm1JCCCGEEEIIIYQQIu5oU0oIIYQQQgghhBBCxJ1IEARBPAtWVFSQn58PEejaP56VQ/ZvgaAaImnQpV/868tBDt4crOsD7NsMBFBeXk5eXp6NBPb5BD7mYe1gXV8OcmiMh4xSPsnBS305+HJQPoV4mIUc5OClvheHaPPJblNKCCEa4WZTSgghmsDFX/qEEKIJlE9CCK+0lk92376nV0rJQQ4uHKzrQ90uuhv0L30pvyblIIf6uMoo5VPKO1jXl4MvB+VTiIdZyEEOXup7cYg2n8w2pbr0hes2xr/uUwNh36ZwMBb15SAHbw7W9QGe7B8Gpxes8gl8zMPawbq+HOTQGE8ZpXySg3V9OfhyUD6FeJiFHOTgpb4Xh2jzSR90LoQQQgghhBBCCCHijjalhBBCCCGEEEIIIUTc0aaUEEIIIYQQQgghhIg7dh903ga2L4XdK6ByD2TmQvfh0HOUHFLRoZBi+jKcbHI5yB62soIySuMn4MTBeg6iDg+zkIMfB+t8sK4PPuYg6rCeh3V9OdThIR88OHiYhQjxMAtrB+v6Xhw8ZIMHBw+ziKeD+02pwwdg7Rz44CHYUXr0zwuK4eSpMPhayMiRQzI7ZJLN6VxLCVM5jqOviA0sZT4PsYQ5VHKw4wWcOFjPQdThYRZy8ONgnQ/W9cHHHEQd1vOwri+HOjzkgwcHD7MQIR5mYe1gXd+Lg4ds8ODgYRZWDq7fvrd7FTw9At64CXYsa/qYHcvCnz89AspXyyFZHXozlLtYzg08wUBOafKYgZzCDTzBXSynN0M6VsCJg/UcRB0eZiEHPw7W+WBdH3zMQdRhPQ/r+nKow0M+eHDwMAsR4mEW1g7W9b04eMgGDw4eZmHp4HZTavcqePZM2Ffz9YXVzRx45P59G+GZ0R3bHDn4cOjNUO7gbXowgAgR0khv8rg00okQoQcDuINFHRoYHhys5yDq8DALOfhxsM4H6/rgYw6iDut5WNeXQx0e8sGDg4dZiBAPs7B2sK7vxcFDNnhw8DALaweXm1KHD8CL46GyAoKq6B4TVIXH/2Fc+Hg5JIdDJtlM4xWyySWdzKgek04m2eQyjXlkkt0+AScO1nMQdXiYhRz8OFjng3V98DEHUYf1PKzry6EOD/ngwcHDLESIh1lYO1jX9+LgIRs8OHiYhQeHdm1K3XfffUQiEf7zP/+z/Sb1WDsH9q6Pvik1BFXh49bOlUOyOJzOtRRQFHVQ1JBOJj05ntO4pn0CThys55CIKJ/kEA8H63ywrg8+5pBodFY+gf08rOvLoQ4P+eDBwcMsEg09h+o8B+v6Xhw8ZIMHBw+z8ODQ5k2pJUuW8Itf/IJTTmn6fZft4YOHaLtZ2pHHyyEpHEqYStDs6wdbppoqSrilfQJOHKznkGgon+QQLwfrfLCuDz7mkEh0Zj6B/Tys68uhDg/54MHBwywSCT2H6lwH6/peHDxkgwcHD7Pw4NCm8nv37uW6667j8ccfp0ePHu23qMf2pUc+6b1t6wOqYcfS8DxySGyHQoo5jlHNvre3NdJIp4hTKaS4bQJOHKznkGgon+QQLwfrfLCuDz7mkEh0Zj6B/Tys68uhDg/54MHBwywSCT2H6lwH6/peHDxkgwcHD7Pw4ABt3JSaMmUKEydO5MILL2z12EOHDlFRUdHg1hK7V7TFqInzrGzHY+XgwqEvwzukfh+GtfmxHhys55BoKJ/kEC8H63ywrg8+5pBIdGY+gf08rOvLoQ4P+eDBwcMsEoloMyoR88mDg3V9Lw4essGDg4dZeHAAyIj1AXPmzOGvf/0rS5Ysier46dOn873vfS/q81fuidWomfO0no1ycO6QTW6H1M8hr82P9eBgPYdEQvkkh3g6WOeDdX3wMYdEobPzCeznYV1fDnV4yAcPDh5mkSjEklGJmE8eHKzre3HwkA0eHDzMwoMDxPhKqbKyMqZNm8ZTTz1FdnZ0nzZ/5513Ul5eXnsrKytr8fjMjlkfZLZ9fcjBicNBOuYqOUDbrxIPDtZzSBSUT3KIt4N1PljXBx9zSATikU9gPw/r+nKow0M+eHDwMItEINaMSsR88uBgXd+Lg4ds8ODgYRYeHCDGV0q9++67bNu2jU996lO191VVVfHmm2/yyCOPcOjQIdLTG74vMysri6ysrKhrdO+YV9K16zxy8OGwlY55PWF7zuPBwXoOiYLySQ7xPo91PljXBx9zSATikU9gPw/r+nKow0M+eHDwMItEINaMSsR88uBgXd+Lg4ds8ODgYRYeHCDGV0pdcMEFvP/++5SWltbeTjvtNK677jpKS0uPekLVFnqOgoLiWM3qkQYFo6BnsRwS3aGMUjawlGpi/H7KI1RTxXreZSPvtU3AiYP1HBIF5ZMc4u1gnQ/W9cHHHBKBeOQT2M/Dur4c6vCQDx4cPMwiEdBzqPg4WNf34uAhGzw4eJiFBwdiLZ+bm8vJJ5/c4Na1a1cKCgo4+eST22dSj5On0q5PgD95qhySxWE+DxFp41WSRjrzebh9Ak4crOeQCCif5GDhYJ0P1vXBxxy8E698Avt5WNeXQx0e8sGDg4dZeEfPoeLnYF3fi4OHbPDg4GEWHhzauifWqQy+FroVQSTGTflIevi4wdfIIVkcljCHHaynisqYHldFJdtZxzvMbZ+AEwfrOYg6PMxCDn4crPPBuj74mIOow3oe1vXlUIeHfPDg4GEWIsTDLKwdrOt7cfCQDR4cPMzCg0O7N6UWLFjAAw880H6TemTkwCWvhB+YFW1zIunh8RPnhY+XQ3I4VHKQBxnPQfZEHRhVVHKQPTzIOCo52D4BJw7Wc0hUlE9y6GwH63ywrg8+5pCIdEY+gf08rOvLoQ4P+eDBwcMsEhE9h+ocB+v6Xhw8ZIMHBw+z8ODg8pVSAN1PhCsWQdeBR+5ozvTI/V0HhsfnD5VDsjlsYzX3MZpdbAJo9r2/NffvYhP3MZptrOkYAScO1nMQdXiYhRz8OFjng3V98DEHUYf1PKzry6EOD/ngwcHDLESIh1lYO1jX9+LgIRs8OHiYhbWD200pCH/Jq5fD2JlQMLLpYwpGhj+/ennn/MEhBx8O21jDXYxgFpMpo7TJY8ooZRaTuYsRHRoUnhys5yDq8DALOfhxsM4H6/rgYw6iDut5WNeXQx0e8sGDg4dZiBAPs7B2sK7vxcFDNnhw8DALS4eMjjtV55CRA8Mmh7ftS2H3SqisCF8u1n1Y+InxckgNh0oOspDZLGQ2hRTTh2HkkMcBKviIlc2GSLI5WM9B1OFhFnLw42CdD9b1wcccRB3W87CuL4c6POSDBwcPsxAhHmZh7WBd34uDh2zw4OBhFlYO7jel6tNzlP0fFnLw4VBGaVzCwbuD9RxEHR5mIQc/Dtb5YF0ffMxB1GE9D+v6cqjDQz54cPAwCxHiYRbWDtb1vTh4yAYPDh5mEU8H12/fE0IIIYQQQgghhBDJiTalhBBCCCGEEEIIIUTc0aaUEEIIIYQQQgghhIg7kSAIgngWrKioID8/HyLQtX88K4fs3wJBNUTSoEu/+NeXgxy8OVjXB9i3GQigvLycvLw8Gwns8wl8zMPawbq+HOTQGA8ZpXySg5f6cvDloHwK8TALOcjBS30vDtHmk92mlBBCNMLNppQQQjSBi7/0CSFEEyifhBBeaS2f7L59T6+UkoMcXDhY14e6XXQ36F/6Un5NykEO9XGVUcqnlHewri8HXw7KpxAPs5CDHLzU9+IQbT6ZbUp16QvXbYx/3acGwr5N4WAs6stBDt4crOsDPNk/DE4vWOUT+JiHtYN1fTnIoTGeMkr5JAfr+nLw5aB8CvEwCznIwUt9Lw7R5pM+6FwIIYQQQgghhBBCxB1tSgkhhBBCCCGEEEKIuKNNKSGEEEIIIYQQQggRd+w+6LwNbF8Ku1dA5R7IzIXuw6HnqNRzKKSYvgwnm1wOsoetrKCM0rg6WPdBPQjx0AcPDh7wsB48OHhYD+qDjx54cLCegyes52FdH3ysB/UhxEMfrB08zMEL1rPw4OBhPVj3ANQHTw7xnIX7TanDB2DtHPjgIdhRevTPC4rh5Kkw+FrIyEleh0yyOZ1rKWEqx3H0itzAUubzEEuYQyUHO8XBug/qQYiHPnhw8ICH9eDBwcN6UB989MCDg/UcPGE9D+v64GM9qA8hHvpg7eBhDl6wnoUHBw/rwboHoD54crCaRSQIgrh+iWhFRQX5+fl06QfXb2752N2r4MXxsHc94RsNq5s46Mj93Ypg4jzIH9ryOWs+hb7rgOg+hd6DQ2+GMo1XKKCIgGrSSD/qmGqqiJDGDtbzIOPYxpoOdbDuQ2f0IFaHzuhBrA4e1kJnONR8M0N5eTl5eXmtS3QS1vkEWpOx1gf7fAL7PnhYCx4cOuvPCg8ZFUs+gf11kczrwboPiZZP4KMP1g7KpzqsZ+HBIVnzKVaHZO1Doq1HsP07ntvPlNq9Cp49E/bVNLCpwdS7f99GeGY0lK9OLofeDOUO3qYHA4gQaXJxAKSRToQIPRjAHSyiN0M6zMG6D+pBiIc+eHDwgIf14MHBw3pQH3z0wIOD9Rw8YT0P6/rgYz2oDyEe+mDt4GEOXrCehQcHD+vBugegPnhysJ6Fy02pwwfCncLKCgiqontMUBUe/4dx4eOTwSGTbKbxCtnkkk5mVI9JJ5NscpnGPDLJbreDdR/UgxAPffDg4AEP68GDg4f1oD746IEHB+s5eMJ6Htb1wcd6UB9CPPTB2sHDHLxgPQsPDh7Wg3UPQH3w5OBhFjFtSt11111EIpEGt+HDh7dbojFr54QvXYt2MDUEVeHj1s5NDofTuZYCiqJeHDWkk0lPjuc0rmm3g3Uf1IMQD33w4NASyqf4OnhYD+qDjx54cLCeQzSkSkZZ1wcf60F9CPHQB2sHD3NojVTJJw8OHtaDdQ9AffDk4GEWMb9S6hOf+ARbtmypvf35z39ut0RjPnioLWZHSDvy+CRwKGEqQbOv32uZaqoo4ZZ2O1j3QT0I8dAHDw6toXyKn4OH9aA++OiBBwfrOURLKmSUdX3wsR7UhxAPfbB28DCHaEiFfPLg4GE9WPcA1AdPDh5mEXMLMjIy6Nu3b+2tZ8+e7Zaoz/alRz5tvm19gWrYsTQ8TyI7FFLMcYxq9v2crZFGOkWcSiHFbXaw7oN6EOKhDx4cokH5FB8HD+tBffDRAw8O1nOIhWTPKOv64GM9qA8hHvpg7eBhDtGS7PnkwcHDerDuAagPnhw8zCI8T4ysXr2a/v37c8IJJ3DdddexYcOGFo8/dOgQFRUVDW4tsXtFrEbNnGdlOx7rwKEvHfOS2T4Ma/NjrfugHoR46IMHh2hQPsXHwcN6UB989MCDg/UcYiGWjIo1n8B+Htb1wcd6UB9CPPTB2sHDHKIl2fPJg4OH9WDdA1AfPDl4mAXEuCk1evRoZs2axcsvv8xjjz3GP/7xD/7lX/6FPXv2NPuY6dOnk5+fX3srLCxssUZl86eKicrWs9G1Qza5HeKQQ9u/Gta6D+pBiIc+eHBoDeVT/Bw8rAf1wUcPPDhYzyFaYs2oWPMJ7OdhXR98rAf1IcRDH6wdPMwhGlIhnzw4eFgP1j0A9cGTg4dZQIybUhMmTOCqq67ilFNO4aKLLuLFF19k9+7dPP30080+5s4776S8vLz2VlZW1mKNzI7pC5nt6IsHh4N0zCo9QNtXqXUf1IMQD33w4NAayqf4OXhYD+qDjx54cLCeQ7TEmlGx5hPYz8O6PvhYD+pDiIc+WDt4mEM0pEI+eXDwsB6sewDqgycHD7MAyGjPg7t3786JJ57ImjVrmj0mKyuLrKys6M/ZQV/00J7zeHDYSse8nq8957Hug3oQ4qEPHhxiRfnUeefxsB7UBx898OBgPYe20lpGxZpPYD8P6/rgYz2oDyEe+mDt4GEObSEZ88mDg4f1YN0DUB88OXiYBbT9s94B2Lt3L2vXrqVfv37tkqhPz1FQUEy7PoW+YBT0LE5shzJK2cBSqonx+yGPUE0V63mXjbzXZgfrPqgHIR764MEhVpRPnefgYT2oDz564MHBeg5tJRkzyro++FgP6kOIhz5YO3iYQ1tIxnzy4OBhPVj3ANQHTw4eZgExtuAb3/gGb7zxBuvWreOtt97iiiuuID09nX/7t39rl0RjTp5Kuz6F/uSpyeEwn4eItHGVppHOfB5ut4N1H9SDEA998ODQEsqn+Dp4WA/qg48eeHCwnkM0pEpGWdcHH+tBfQjx0AdrBw9zaI1UyScPDh7Wg3UPQH3w5OBhFjFV37hxI//2b//GsGHDuPrqqykoKODtt9+mV69e7Rapz+BroVsRRGL8ZsJIevi4wdckh8MS5rCD9VRRGdPjqqhkO+t4h7ntdrDug3oQ4qEPHhxaQvkUXwcP60F98NEDDw7Wc4iGVMko6/rgYz2oDyEe+mDt4GEOrZEq+eTBwcN6sO4BqA+eHDzMIqZNqTlz5rB582YOHTrExo0bmTNnDoMHD263RGMycuCSV8IP7Yp2QJH08PiJ88LHJ4NDJQd5kPEcZE/Ui6SKSg6yhwcZRyUH2+1g3Qf1IMRDHzw4tITyKb4OHtaD+uCjBx4crOcQDamSUdb1wcd6UB9CPPTB2sHDHFojVfLJg4OH9WDdA1AfPDl4mEW7PlOqM+l+IlyxCLoOPHJHc6ZH7u86MDw+f2hyOWxjNfcxml1sAmj2/Z419+9iE/cxmm00/+HOsWLdB/UgxEMfPDh4wMN68ODgYT2oDz564MHBeg6esJ6HdX3wsR7UhxAPfbB28DAHL1jPwoODh/Vg3QNQHzw5WM/C7aYUhI2+ejmMnQkFI5s+pmBk+POrl3fsYDw5bGMNdzGCWUymjNImjymjlFlM5i5GdMofYNZ9UA9CPPTBg4MHPKwHDw4e1oP64KMHHhys5+AJ63lY1wcf60F9CPHQB2sHD3PwgvUsPDh4WA/WPQD1wZOD5SwyOuxMnURGDgybHN62L4XdK6GyInzJWvdh4afWp4JDJQdZyGwWMptCiunDMHLI4wAVfMTKZhdOR2LdB/UgxEMfPDh4wMN68ODgYT2oDz564MHBeg6esJ6HdX3wsR7UhxAPfbB28DAHL1jPwoODh/Vg3QNQHzw5WM3C/aZUfXqOis8wvDuUUWr+h5Z1H9SDEA998ODgAQ/rwYODh/WgPvjogQcH6zl4wnoe1vXBx3pQH0I89MHawcMcvGA9Cw8OHtaDdQ9AffDkEM9ZuH77nhBCCCGEEEIIIYRITrQpJYQQQgghhBBCCCHijjalhBBCCCGEEEIIIUTciQRBEMSzYEVFBfn5+RCBrv3jWTlk/xYIqiGSBl36xb++HOTgzcG6PsC+zUAA5eXl5OXl2Uhgn0/gYx7WDtb15SCHxnjIKOWTHLzUl4MvB+VTiIdZyEEOXup7cYg2n+w2pYQQohFuNqWEEKIJXPylTwghmkD5JITwSmv5ZPfte3qllBzk4MLBuj7U7aK7Qf/Sl/JrUg5yqI+rjFI+pbyDdX05+HJQPoV4mIUc5OClvheHaPPJbFOqS1+4bmP86z41EPZtCgdjUV8OcvDmYF0f4Mn+YXB6wSqfwMc8rB2s68tBDo3xlFHKJzlY15eDLwflU4iHWchBDl7qe3GINp/0QedCCCGEEEIIIYQQIu5oU0oIIYQQQgghhBBCxB1tSgkhhBBCCCGEEEKIuGP3QedtYPtS2L0CKvdAZi50Hw49R6WeQyHF9GU42eRykD1sZQVllKaUg3V9Ofhy8ICHbPDg4GE9eHCwnoV6EOKhD16wnod1ffCxHjw4aBYh1n3w0AMvWM/Cg4OH9eDBwXoOoD7UEM8+uN+UOnwA1s6BDx6CHaVH/7ygGE6eCoOvhYyc5HXIJJvTuZYSpnIcR6/IDSxlPg+xhDlUcjApHazry8GXgwc8ZIMHBw/rwYOD9SzUgxAPffCC9Tys64OP9eDBQbMIse6Dhx54wXoWHhw8rAcPDtZzAPWhBqs+RIIgiOuXiFZUVJCfn0+XfnD95paP3b0KXhwPe9cTvtGwuomDjtzfrQgmzoP8oS2fs+ZT6LsOiO5T6D049GYo03iFAooIqCaN9KOOqaaKCGnsYD0PMo5trEkqh86oL4fY63eWQ803M5SXl5OXl9e6RCdhnU8Q2zw8OCTrmky0Pys85FOyrkfwkVGx5BPYr8lkXg/WDomWT6A+gPKpPtaz8OCQrPkUq0Oy/lmRaOsRbP+O5/YzpXavgmfPhH01DWxqMPXu37cRnhkN5auTy6E3Q7mDt+nBACJEmlwcAGmkEyFCDwZwB4vozZCkcbCuLwdfDh7wkA0eHDysBw8O1rNQD0I89MEL1vOwrg8+1oMHB80ixLoPHnrgBetZeHDwsB48OFjPAdSHGqz74HJT6vCBcKewsgKCqugeE1SFx/9hXPj4ZHDIJJtpvEI2uaSTGdVj0skkm1ymMY9MshPewbq+HHw5eMBDNnhw8LAePDhYz0I9CPHQBy9Yz8O6PvhYDx4cNIsQ6z546IEXrGfhwcHDevDgYD0HUB9q8NCHmDelNm3axPXXX09BQQE5OTl88pOf5J133mm3SH3WzglfuhbtYGoIqsLHrZ2bHA6ncy0FFEW9OGpIJ5OeHM9pXJPwDtb15eDLoTWUT/Fz8LAePDhYz0I9CPHQh2hIhYyyrg8+1oMHB80ixLoPHnoQDamQTx4cPKwHDw7WcwD1oQYPfYhpU2rXrl2MGTOGzMxMXnrpJf72t7/xX//1X/To0aPdIvX54KFYzeqRduTxSeBQwlSCZl+/1zLVVFHCLQnvYF1fDr4cWkL5FF8HD+vBg4P1LNSDEA99aI1UySjr+uBjPXhw0CxCrPvgoQetkSr55MHBw3rw4GA9B1AfavDQh5ha8MMf/pDCwkJmzpzJGWecwaBBgxg/fjyDBw9ut0gN25ce+bT5tvUFqmHH0vA8iexQSDHHMarZ93O2RhrpFHEqhRQnrIN1fTn4cmgN5VP8HDysBw8O1rNQD0I89CEaUiGjrOuDj/XgwUGzCLHug4ceREMq5JMHBw/rwYOD9RxAfajBQx/C88TA888/z2mnncZVV11F7969GTVqFI8//niLjzl06BAVFRUNbi2xe0UsRi2cZ2U7HuvAoS/DO8ShD8MS1sG6vhx8ObSG8il+Dh7WgwcH61moByEe+hANsWZUrPkE9vOwrg8+1oMHB80ixLoPHnoQDamQTx4cPKwHDw7WcwD1oQYPfYAYN6X+/ve/89hjjzF06FD++Mc/8uUvf5mpU6cye/bsZh8zffp08vPza2+FhYUt1qjcE4tRC+dpPRtdO2ST2yEOObT9q2GtHazry8GXQ2son+Ln4GE9eHCwnoV6EOKhD9EQa0bFmk9gPw/r+uBjPXhw0CxCrPvgoQfRkAr55MHBw3rw4GA9B1AfavDQB4hxU6q6uppPfepT3HvvvYwaNYr/+I//4Atf+AI///nPm33MnXfeSXl5ee2trKysxRqZHdMXMtvRFw8OB+mYVXqAtq9Sawfr+nLw5dAayqf4OXhYDx4crGehHoR46EM0xJpRseYT2M/Duj74WA8eHDSLEOs+eOhBNKRCPnlw8LAePDhYzwHUhxo89AFi3JTq168fJ510UoP7RowYwYYNG5p9TFZWFnl5eQ1uLdG9Y15B1q7zeHDYSse8nq8957F2sK4vB18OraF8it95PKwHDw7Ws1APQjz0IRpizahY8wns52FdH3ysBw8OmkWIdR889CAaUiGfPDh4WA8eHKznAOpDDR76ADFuSo0ZM4aVKxu+aXHVqlUUFRW1S6I+PUdBQXGsZvVIg4JR0LM4sR3KKGUDS6kmxu+HPEI1VaznXTbyXsI6WNeXgy+H1lA+xc/Bw3rw4GA9C/UgxEMfoiEVMsq6PvhYDx4cNIsQ6z546EE0pEI+eXDwsB48OFjPAdSHGjz0AWJswde+9jXefvtt7r33XtasWcNvfvMbfvnLXzJlypR2STTm5Km061PoT56aHA7zeYhIG1dpGunM5+GEd7CuLwdfDi2hfIqvg4f14MHBehbqQYiHPrRGqmSUdX3wsR48OGgWIdZ98NCD1kiVfPLg4GE9eHCwngOoDzV46ENM1U8//XSeeeYZfvvb33LyySdzzz338MADD3Dddde1W6Q+g6+FbkUQifGbCSPp4eMGX5McDkuYww7WU0VlTI+ropLtrOMd5ia8g3V9OfhyaAnlU3wdPKwHDw7Ws1APQjz0oTVSJaOs64OP9eDBQbMIse6Dhx60RqrkkwcHD+vBg4P1HEB9qMFDH2LeErv00kt5//33OXjwIMuXL+cLX/hCuyUak5EDl7wSfmhXtAOKpIfHT5wXPj4ZHCo5yIOM5yB7ol4kVVRykD08yDgqOZjwDtb15eDLoTWUT/Fz8LAePDhYz0I9CPHQh2hIhYyyrg8+1oMHB80ixLoPHnoQDamQTx4cPKwHDw7WcwD1oQYPfWjrOxg7ne4nwhWLoOvAI3c0Z3rk/q4Dw+PzhyaXwzZWcx+j2cUmgGbf71lz/y42cR+j2caapHGwri8HXw4e8JANHhw8rAcPDtazUA9CPPTBC9bzsK4PPtaDBwfNIsS6Dx564AXrWXhw8LAePDhYzwHUhxqs++B2UwrCRl+9HMbOhIKRTR9TMDL8+dXLO3Ywnhy2sYa7GMEsJlNGaZPHlFHKLCZzFyM65Q8wawfr+nLw5eABD9ngwcHDevDgYD0L9SDEQx+8YD0P6/rgYz14cNAsQqz74KEHXrCehQcHD+vBg4P1HEB9qMGyDxkddqZOIiMHhk0Ob9uXwu6VUFkRvmSt+7DwU+tTwaGSgyxkNguZTSHF9GEYOeRxgAo+YmWzCyeZHKzry8GXgwc8ZIMHBw/rwYOD9SzUgxAPffCC9Tys64OP9eDBQbMIse6Dhx54wXoWHhw8rAcPDtZzAPWhBqs+uN+Uqk/PUfEZhneHMkrN/9CydrCuLwdfDh7wkA0eHDysBw8O1rNQD0I89MEL1vOwrg8+1oMHB80ixLoPHnrgBetZeHDwsB48OFjPAdSHGuLZB9dv3xNCCCGEEEIIIYQQyYk2pYQQQgghhBBCCCFE3NGmlBBCCCGEEEIIIYSIO5EgCIJ4FqyoqCA/Px8i0LV/PCuH7N8CQTVE0qBLv/jXl4McvDlY1wfYtxkIoLy8nLy8PBsJ7PMJfMzD2sG6vhzk0BgPGaV8koOX+nLw5aB8CvEwCznIwUt9Lw7R5pPdppQQQjTCzaaUEEI0gYu/9AkhRBMon4QQXmktn+y+fU+vlJKDHFw4WNeHul10N+hf+lJ+TcpBDvVxlVHKp5R3sK4vB18OyqcQD7OQgxy81PfiEG0+mW1KdekL122Mf92nBsK+TeFgLOrLQQ7eHKzrAzzZPwxOL1jlE/iYh7WDdX05yKExnjJK+SQH6/py8OWgfArxMAs5yMFLfS8O0eaTPuhcCCGEEEIIIYQQQsQdbUoJIYQQQgghhBBCiLijTSkhhBBCCCGEEEIIEXe0KSWEEEIIIYQQQggh4o7dt++1ge1LYfcKqNwDmbnQfTj0HJV6DoUU05fhZJPLQfawlRWUUZpSDtb15VCHh2vCAx764MHBw5qUg4+1IAdfWPfCuj7YX5dyqEPrwb6+JzysB2sHD+tBDiHWawF89CGeDu43pQ4fgLVz4IOHYEfp0T8vKIaTp8LgayEjJ3kdMsnmdK6lhKkcx9FXxQaWMp+HWMIcKjmYlA7W9eVQh4drwgMe+uDBwcOalIOPtSAHX1j3wro+2F+XcqhD68G+vic8rAdrBw/rQQ4h1msBfPTByiESBEHQYWeLgoqKCvLz8+nSD67f3PKxu1fBi+Nh73rCNxpWN3HQkfu7FcHEeZA/tOVz1nw1YtcB0X01ogeH3gxlGq9QQBEB1aSRftQx1VQRIY0drOdBxrGNNUnl0Bn15RB7feica6Lm60LLy8vJy8trXaKTsM4niG0eHhw8rEk5+FgLyezgIaNiySewf/7iYT3oz20/DtbrEez70FnrUfkUkmhrMlnzKREdrNcC2OdTZzlEm09uP1Nq9yp49kzYV9PAphZHvfv3bYRnRkP56uRy6M1Q7uBtejCACJEmFwdAGulEiNCDAdzBInozJGkcrOvLoQ4P14QHPPTBg4OHNSkHH2tBDr6w7oV1fbC/LuVQh9aDfX1PeFgP1g4e1oMcQqzXAvjog7VDTJtSxx9/PJFI5KjblClTOkSmhsMHwt3KygoIqqJ7TFAVHv+HceHjk8Ehk2ym8QrZ5JJOZlSPSSeTbHKZxjwyyU54B+v6cqjDwzXRGvHIKA998ODgYU3KwcdakEN0pMpzKOv6YH9dyqEOrQf7+tGQKvnkwcHDepBDiPVaAB998OAQ06bUkiVL2LJlS+1t3rx5AFx11VXtFqnP2jnhy+eiXRw1BFXh49bOTQ6H07mWAoqiXhw1pJNJT47nNK5JeAfr+nKow8M10RrxyCgPffDg4GFNysHHWpBDdKTKcyjr+mB/XcqhDq0H+/rRkCr55MHBw3qQQ4j1WgAfffDgENOmVK9evejbt2/t7YUXXmDw4MGMHTu23SL1+eChWM3qkXbk8UngUMJUgmZfQ9gy1VRRwi0J72BdXw51eLgmWiMeGeWhDx4cPKxJOfhYC3KIjlR5DmVdH+yvSznUofVgXz8aUiWfPDh4WA9yCLFeC+CjDx4c2vyZUh9//DFPPvkkN910E5FIpN0iNWxfeuQT79vWF6iGHUvD8ySyQyHFHMeoZt/P2RpppFPEqRRSnLAO1vXlUIeHayJWOiOjPPTBg4OHNSkHH2tBDm0jWZ9DWdcH++tSDnVoPdjXbwvJmk8eHDysBzmEWK8F8NEHDw7hedrIs88+y+7du5k8eXKLxx06dIiKiooGt5bYvaKtRo3Os7Idj3Xg0JfhHeLQh2EJ62BdXw51eLgmYiWajFI+tQ0Pa1IOPtaCHNpGZ+QT2PfCuj7YX5dyqEPrwb5+W0jWfPLg4GE9yCHEei2Ajz54cIB2bErNmDGDCRMm0L9//xaPmz59Ovn5+bW3wsLCFo+v3NNWo0bnaT0bXTtkk9shDjm0/athrR2s68uhDg/XRKxEk1HKp7bhYU3KwcdakEPb6Ix8AvteWNcH++tSDnVoPdjXbwvJmk8eHDysBzmEWK8F8NEHDw7Qxk2p9evX8+qrr/Lv//7vrR575513Ul5eXnsrKytr8fjMjukLme3oiweHg3TMlXKAtl8p1g7W9eVQh4drIhaizSjlU9vwsCbl4GMtyCF2OiufwL4X1vXB/rqUQx1aD/b1YyWZ88mDg4f1IIcQ67UAPvrgwQEgoy0PmjlzJr1792bixImtHpuVlUVWVlbU5+7eMa8ga9d5PDhspWNeU9ie81g7WNeXQx0erolYiDajlE9tw8OalIOPtSCH2OmsfAL7XljXB/vrUg51aD3Y14+VZM4nDw4e1oMcQqzXAvjogwcHaMMrpaqrq5k5cyY33ngjGRlt2tNqkZ6joKC4LWZHSIOCUdCzOLEdyihlA0upJsbvqDxCNVWs51028l7COljXl0MdHq6JaOnMjPLQBw8OHtakHHysBTnERrI/h7KuD/bXpRzq0Hqwrx9TrSTPJw8OHtaDHEKs1wL46IMHB2jDGF599VU2bNjATTfd1K7CLXHyVNr1SfgnT00Oh/k8RKSNV0oa6czn4YR3sK4vhzo8XBPR0NkZ5aEPHhw8rEk5+FgLcoieVHgOZV0f7K9LOdSh9WBfP1pSIZ88OHhYD3IIsV4L4KMPHhxirj5+/HiCIODEE09sd/HmGHwtdCuCSIzfTBhJDx83+JrkcFjCHHawnioqY3pcFZVsZx3vMDfhHazry6EOD9dENHR2RnnogwcHD2tSDj7WghyiJxWeQ1nXB/vrUg51aD3Y14+WVMgnDw4e1oMcQqzXAvjogweHNn/7XmeSkQOXvBJ+cFi0iySSHh4/cV74+GRwqOQgDzKeg+yJepFUUclB9vAg46jkYMI7WNeXQx0ergkPeOiDBwcPa1IOPtaCHHxh3Qvr+mB/XcqhDq0H+/qe8LAerB08rAc5hFivBfDRBw8OLjelALqfCFcsgq4Dj9zRnOmR+7sODI/PH5pcDttYzX2MZhebAJp9v2fN/bvYxH2MZhtrksbBur4c6vBwTXjAQx88OHhYk3LwsRbk4AvrXljXB/vrUg51aD3Y1/eEh/Vg7eBhPcghxHotgI8+WDu43ZSCcNhXL4exM6FgZNPHFIwMf3718s55YunBYRtruIsRzGIyZZQ2eUwZpcxiMncxolP+ALN2sK4vhzo8XBMe8NAHDw4e1qQcfKwFOfjCuhfW9cH+upRDHVoP9vU94WE9WDt4WA9yCLFeC+CjD5YOHf/VCh1MRg4Mmxzeti+F3SuhsiJ82Vz3YeEn56eCQyUHWchsFjKbQorpwzByyOMAFXzEymYXTjI5WNeXQx0ergkPeOiDBwcPa1IOPtaCHHxh3Qvr+mB/XcqhDq0H+/qe8LAerB08rAc5hFivBfDRBysH95tS9ek5yv7JpAeHMkrN/9CydrCuL4c6PFwTHvDQBw8OHtakHHysBTn4wroX1vXB/rqUQx1aD/b1PeFhPVg7eFgPcgixXgvgow/xdHD99j0hhBBCCCGEEEIIkZxoU0oIIYQQQgghhBBCxB1tSgkhhBBCCCGEEEKIuBMJgiCIZ8GKigry8/MhAl37x7NyyP4tEFRDJA269It/fTnIwZuDdX2AfZuBAMrLy8nLy7ORwD6fwMc8rB2s68tBDo3xkFHKJzl4qS8HXw7KpxAPs5CDHLzU9+IQbT7ZbUoJIUQj3GxKCSFEE7j4S58QQjSB8kkI4ZXW8snu2/f0Sik5yMGFg3V9qNtFd4P+pS/l16Qc5FAfVxmlfEp5B+v6cvDloHwK8TALOcjBS30vDtHmk9mmVJe+cN3G+Nd9aiDs2xQOxqK+HOTgzcG6PsCT/cPg9IJVPoGPeVg7WNeXgxwa4ymjlE9ysK4vB18OyqcQD7OQgxy81PfiEG0+6YPOhRBCCCGEEEIIIUTc0aaUEEIIIYQQQgghhIg72pQSQgghhBBCCCGEEHHH7oPO28D2pbB7BVTugcxc6D4ceo5KPYdCiunLcLLJ5SB72MoKyihNKQfr+l4chB88ZIMc5OClvhcHUYf1PKzry0EO3hz0PLIO61l4cLCuLwc5NCaeGeV+U+rwAVg7Bz54CHaUHv3zgmI4eSoMvhYycpLXIZNsTudaSpjKcRy9IjewlPk8xBLmUMnBpHSwru/FQfjBQzbIQQ5e6ntxEHVYz8O6vhzk4M1BzyPrsJ6FBwfr+nKQQ2OsMsr12/d2r4KnR8AbN8GOZU0fs2NZ+POnR0D56uR06M1Q7mI5N/AEAzmlyWMGcgo38AR3sZzeDEk6B+v6XhyEHzxkgxzk4KW+FwdRh/U8rOvLQQ7eHPQ8sg7rWXhwsK4vBzk0xjKj3G5K7V4Fz54J+2q+vrC6mQOP3L9vIzwzumMH5MGhN0O5g7fpwQAiREgjvcnj0kgnQoQeDOAOFnXoIrF2sK7vxUH4wUM2yEEOXup7cRB1WM/Dur4c5ODNQc8j67CehQcH6/pykENjrDMqpk2pqqoqvvOd7zBo0CBycnIYPHgw99xzD0EQdIhMDYcPwIvjobICgqroHhNUhcf/YVz4+GRwyCSbabxCNrmkkxnVY9LJJJtcpjGPTLIT3sG6vhcH0TrKJzmkooN1fS8OiUCqZJR1fTnIwZtDIjyPTJV88uBgXV8OcmiMh4yKaVPqhz/8IY899hiPPPIIy5cv54c//CE/+tGPePjhh9stUp+1c2Dv+ugHU0NQFT5u7dzkcDidaymgKOrFUUM6mfTkeE7jmoR3sK7vxUG0jvJJDqnoYF3fi0MikCoZZV1fDnLw5pAIzyNTJZ88OFjXl4McGuMho2LalHrrrbeYNGkSEydO5Pjjj+czn/kM48ePZ/Hixe0Wqc8HD8VqVo+0I49PAocSphI0+/q9lqmmihJuSXgH6/peHETrKJ/kkIoO1vW9OCQCqZJR1vXlIAdvDonwPDJV8smDg3V9OcihMR4yKqYWnH322bz22musWrUKgPfee48///nPTJgwod0iNWxfeuTT5tvWF6iGHUvD8ySyQyHFHMeoZt/P2RpppFPEqRRSnLAO1vW9OIjoUD7JIdUcrOt7cUgUUiGjrOvLQQ7eHBLleWQq5JMHB+v6cpBDY7xkVEybUnfccQfXXnstw4cPJzMzk1GjRvGf//mfXHfddc0+5tChQ1RUVDS4tcTuFbEYtXCele14rAOHvgzvEIc+DEtYB+v6XhxEdCif5JBqDtb1vTgkCrFmVKz5BPbzsK4vBzl4c0iU55GpkE8eHKzry0EOjfGSUTFtSj399NM89dRT/OY3v+Gvf/0rs2fP5ic/+QmzZ89u9jHTp08nPz+/9lZYWNhijco9sRi1cJ7Ws9G1Qza5HeKQQ17COljX9+IgokP5JIdUc7Cu78UhUYg1o2LNJ7Cfh3V9OcjBm0OiPI9MhXzy4GBdXw5yaIyXjIppU+rWW2+t3Un/5Cc/yec+9zm+9rWvMX369GYfc+edd1JeXl57Kysra7FGZsf0hcx29MWDw0E6ZpUeoO2r1NrBur4XBxEdyic5pJqDdX0vDolCrBkVaz6B/Tys68tBDt4cEuV5ZCrkkwcH6/pykENjvGRURiwH79+/n7S0hvtY6enpVFc3/0bIrKwssrKyoq7RvWNeQdau83hw2ErHvJ6vPeexdrCu78VBRIfySQ6p5mBd34tDohBrRsWaT2A/D+v6cpCDN4dEeR6ZCvnkwcG6vhzk0BgvGRXTK6Uuu+wyfvCDH/CHP/yBdevW8cwzz/DTn/6UK664ol0S9ek5CgqKYzWrRxoUjIKexYntUEYpG1hKNTF+P+QRqqliPe+ykfcS1sG6vhcHER3KJzmkmoN1fS8OiUIqZJR1fTnIwZtDojyPTIV88uBgXV8OcmiMl4yKqQUPP/wwn/nMZ/jKV77CiBEj+MY3vsEXv/hF7rnnnnZJNObkqbTrU+hPnpocDvN5iEgbV2ka6czn4YR3sK7vxUG0jvJJDqnoYF3fi0MikCoZZV1fDnLw5pAIzyNTJZ88OFjXl4McGuMho2KqnpubywMPPMD69es5cOAAa9eu5fvf/z7HHHNMu0XqM/ha6FYEkRi/mTCSHj5u8DXJ4bCEOexgPVVUxvS4KirZzjreYW7CO1jX9+IgWkf5JIdUdLCu78UhEUiVjLKuLwc5eHNIhOeRqZJPHhys68tBDo3xkFFtfbFYp5KRA5e8En5oV7QDiqSHx0+cFz4+GRwqOciDjOcge6JeJFVUcpA9PMg4KjmY8A7W9b04CD94yAY5yMFLfS8Oog7reVjXl4McvDnoeWQd1rPw4GBdXw5yaIyHjHK5KQXQ/US4YhF0HXjkjuZMj9zfdWB4fP7Q5HLYxmruYzS72ATQ7Ps9a+7fxSbuYzTbWJM0Dtb1vTgIP3jIBjnIwUt9Lw6iDut5WNeXgxy8Oeh5ZB3Ws/DgYF1fDnJojHVGud2UgrDRVy+HsTOhYGTTxxSMDH9+9fLOeXLrwWEba7iLEcxiMmWUNnlMGaXMYjJ3MaJT/gCzdrCu78VB+MFDNshBDl7qe3EQdVjPw7q+HOTgzUHPI+uwnoUHB+v6cpBDYywzKqPDztRJZOTAsMnhbftS2L0SKivCl6x1HxZ+an0qOFRykIXMZiGzKaSYPgwjhzwOUMFHrGx24SSTg3V9Lw7CDx6yQQ5y8FLfi4Oow3oe1vXlIAdvDnoeWYf1LDw4WNeXgxwaY5VR7jel6tNzlP0TWg8OZZSa/6Fl7WBd34uD8IOHbJCDHLzU9+Ig6rCeh3V9OcjBm4OeR9ZhPQsPDtb15SCHxsQzo1y/fU8IIYQQQgghhBBCJCfalBJCCCGEEEIIIYQQcUebUkIIIYQQQgghhBAi7kSCIAjiWbC8vJzu3bsD0KVfPCuH7N8KBEAEuvSNf305yMGbg3V9gP1bwv/dvXs3+fn5NhLY5xM4mYfWpBzk0NDBQUYpn+Tgpb4cnDkonwAns5CDHJzUd+MQZT7FfVNq48aNFBYWxrOkECJBKCsrY+DAgWb1lU9CiJawzCjlkxCiJZRPQgivtJZPcd+Uqq6uZvPmzeTm5hKJRGJ+fEVFBYWFhZSVlZGXl9cJhnJIFAfr+nLoOIcgCNizZw/9+/cnLc3uXcXKJzkkk4N1/WRy8JBR7c0nsJ+HdX05yMGbg/KpDutZeHCwri8HOXS0Q7T5lNEeybaQlpbWIbv4eXl5ZsORgy8H6/py6BgHy7ft1aB8kkMyOljXTxYH64zqqHwC+3lY15eDHLw5KJ/qsJ6FBwfr+nKQQ0c6RJNP+qBzIYQQQgghhBBCCBF3tCklhBBCCCGEEEIIIeJOwm1KZWVl8d3vfpesrCw5pLiDdX05+HLwgIc+yEEOXurLwR/WvbCuLwc5eHOwru8JD72wdrCuLwc5WDnE/YPOhRBCCCGEEEIIIYRIuFdKCSGEEEIIIYQQQojER5tSQgghhBBCCCGEECLuaFNKCCGEEEIIIYQQQsSdhNqUWrhwIenp6UycODHutSdPnkwkEqm9FRQUcPHFF7Ns2bK4u2zdupVbbrmFE044gaysLAoLC7nssst47bXXOr12/T5kZmbSp08fxo0bxxNPPEF1dXWn12/sUP928cUXx6V+ax5r1qyJS/2tW7cybdo0hgwZQnZ2Nn369GHMmDE89thj7N+/v9PrT548mU9/+tNH3b9gwQIikQi7d+/udAdvKKOUT409rDLKOp/ANqOUT0ejfFI+NfZQPuk5lBeUT8qnxh7Kp9TKp4TalJoxYwa33HILb775Jps3b457/YsvvpgtW7awZcsWXnvtNTIyMrj00kvj6rBu3TpOPfVUXn/9dX784x/z/vvv8/LLL1NSUsKUKVPi4lDTh3Xr1vHSSy9RUlLCtGnTuPTSSzl8+HBcHerffvvb38aldmsegwYN6vS6f//73xk1ahSvvPIK9957L0uXLmXhwoXcdtttvPDCC7z66qud7iCOJtUzSvl0tIdlRlnlEyijPKJ8Uj419lA+KZ+8oHxSPjX2UD6lVj5lWAtEy969e5k7dy7vvPMOW7duZdasWXzzm9+Mq0NWVhZ9+/YFoG/fvtxxxx38y7/8C//85z/p1atXXBy+8pWvEIlEWLx4MV27dq29/xOf+AQ33XRTXBzq92HAgAF86lOf4swzz+SCCy5g1qxZ/Pu//3tcHSyx8vjKV75CRkYG77zzToN1cMIJJzBp0iT0pZrxRxmlfGrOwwpLB2WUL5RPyqfmPKxQPokalE/Kp+Y8rFA+xZ+EeaXU008/zfDhwxk2bBjXX389TzzxhOlQ9u7dy5NPPsmQIUMoKCiIS82dO3fy8ssvM2XKlAaLtIbu3bvHxaMpzj//fEaOHMn//d//mTmkCjt27OCVV15pdh0ARCKROFuJVM8o5ZOoQRnlD+WT8kmEKJ/8oXxSPomQVM6nhNmUmjFjBtdffz0QvqSuvLycN954I64OL7zwAt26daNbt27k5uby/PPPM3fuXNLS4tPGNWvWEAQBw4cPj0u9WBk+fDjr1q2LS636s6i53XvvvXGp3ZLHVVdd1ek1a9bBsGHDGtzfs2fPWo/bb7+90z2g6TlMmDAhLrW9keoZpXxqiIeMssgn8JNRyqc6lE/Kp/oon+zzCZRRNSiflE/1UT6lZj4lxNv3Vq5cyeLFi3nmmWcAyMjI4JprrmHGjBmcd955cfMoKSnhscceA2DXrl387Gc/Y8KECSxevJiioqJOr+/95XpBEMRt97b+LGo49thj41K7JY/mdrXjweLFi6murua6667j0KFDcanZ1BwWLVpU++QiVVBGKZ8a4yGjPOUTxD+jlE8hyiflU2OUT0ej51A2KJ+UT41RPh1NKuRTQmxKzZgxg8OHD9O/f//a+4IgICsri0ceeYT8/Py4eHTt2pUhQ4bU/vevfvUr8vPzefzxx/n+97/f6fWHDh1KJBJhxYoVnV6rLSxfvjxuHwLXeBZWWHgMGTKESCTCypUrG9x/wgknAJCTkxM3l6Z+/40bN8atvheUUcqnxnjIKCsHLxmlfApRPimfGqN8ss8nUEaB8gmUT41RPqVmPrl/+97hw4f59a9/zX/9139RWlpae3vvvffo37+/yTeu1RCJREhLS+PAgQNxqXfsscdy0UUX8eijj7Jv376jfm759bGvv/4677//PldeeaWZQ6pQUFDAuHHjeOSRR5pcByK+KKNClE+iBmWUH5RPIconUYPyyQ/KpxDlk6ghlfPJ/SulXnjhBXbt2sXNN9981G75lVdeyYwZM/jSl74UF5dDhw6xdetWIHxp5yOPPMLevXu57LLL4lIf4NFHH2XMmDGcccYZ3H333ZxyyikcPnyYefPm8dhjj7F8+fJOd6jpQ1VVFR999BEvv/wy06dP59JLL+WGG27o9Pr1HeqTkZFBz54941Lfmp/97GeMGTOG0047jbvuuotTTjmFtLQ0lixZwooVKzj11FOtFVMGZVQdyqejPeqjjFJGxRvlUx3Kp6M96qN8Uj7FG+VTHcqnoz3qo3xKgXwKnHPppZcGl1xySZM/W7RoUQAE7733Xqd73HjjjQFQe8vNzQ1OP/304He/+12n127M5s2bgylTpgRFRUXBMcccEwwYMCC4/PLLg/nz53d67fp9yMjICHr16hVceOGFwRNPPBFUVVV1ev3GDvVvw4YNi0v9+h6TJk2Ka836bN68OfjqV78aDBo0KMjMzAy6desWnHHGGcGPf/zjYN++fZ1ev7nff/78+QEQ7Nq1q9MdPKCMakiq51NjD6uMss6nILDNKOVTiPKpIcon5VMNeg5lj/KpIcon5VMNqZhPkSBw/ulqQgghhBBCCCGEECLpcP+ZUkIIIYQQQgghhBAi+dCmlBBCCCGEEEIIIYSIO9qUEkIIIYQQQgghhBBxR5tSQgghhBBCCCGEECLuaFNKCCGEEEIIIYQQQsQdbUoJIYQQQgghhBBCiLijTSkhhBBCCCGEEEIIEXe0KSWEEEIIIYQQQggh4o42pYQQQgghhBBCCCFE3NGmVBLw85//nNzcXA4fPlx73969e8nMzOS8885rcOyCBQuIRCKsXbsWgC9+8YsMHjyYnJwcevXqxaRJk1ixYkWDx0QikaNuc+bMadXrwIEDdO3alTVr1rR43KFDhyguLiYSiVBaWhrV7zxo0CBeffXVJn92/PHH13qmp6fTv39/br75Znbt2lV7zIIFC5g0aRL9+vWja9euFBcX89RTTzU4z6xZs476vbOzs6PyE0KEtCefagiCgAkTJhCJRHj22Wcb/Kyz8unyyy/nuOOOIzs7m379+vG5z32OzZs3R/U7tzefDh48yOTJk/nkJz9JRkYGn/70p5s816FDh/jWt75FUVERWVlZHH/88TzxxBNROQohOjefduzYwcUXX0z//v3JysqisLCQr371q1RUVLTq1VI+rVu3jptvvplBgwaRk5PD4MGD+e53v8vHH38c1e8cr3x69NFHGTFiBDk5OQwbNoxf//rXUfkJIepI1OdQP/jBDzj77LPp0qUL3bt3j+p3raGkpIRf/epXTf7svPPOa+Dap08frrrqKtavX9/guKlTp3LqqaeSlZVFcXFxk+f64x//yJlnnklubi69evXiyiuvZN26dTG5io5Dm1JJQElJCXv37uWdd96pve9Pf/oTffv2ZdGiRRw8eLD2/vnz53PccccxePBgAE499VRmzpzJ8uXL+eMf/0gQBIwfP56qqqoGNWbOnMmWLVtqb809CanPvHnzKCoqYsiQIS0ed9ttt9G/f/+of99ly5axa9cuxo4d2+wxd999N1u2bGHDhg089dRTvPnmm0ydOrX252+99RannHIK//u//8uyZcv4/Oc/zw033MALL7zQ4Dx5eXkNfu/GoSeEaJn25FMNDzzwAJFIpNkanZFPJSUlPP3006xcuZL//d//Ze3atXzmM59p9bwdkU9VVVXk5OQwdepULrzwwmbPc/XVV/Paa68xY8YMVq5cyW9/+1uGDRvWqqMQIqQz8yktLY1Jkybx/PPPs2rVKmbNmsWrr77Kl770pVa9WsqnFStWUF1dzS9+8Qs+/PBD7r//fn7+85/zzW9+s9XzxiufHnvsMe68807uuusuPvzwQ773ve8xZcoUfv/737fqKISoI1GfQ3388cdcddVVfPnLX271XPXZuXMnf/nLX7jsssuaPeYLX/gCW7ZsYfPmzTz33HOUlZVx/fXXH3XcTTfdxDXXXNPkOf7xj38wadIkzj//fEpLS/njH//I9u3b+dd//deYfEUHEoikoF+/fsH06dNr//u2224LpkyZEowYMSKYP39+7f3nnntucOONNzZ7nvfeey8AgjVr1tTeBwTPPPNMzE433XRTcPvtt7d4zIsvvhgMHz48+PDDDwMgWLp0aavnvfvuu4Nrrrmm2Z8XFRUF999/f4P77rnnnuCkk05q8byXXHJJ8PnPf772v2fOnBnk5+e36iOEaJn25NPSpUuDAQMGBFu2bGkyizozn+rz3HPPBZFIJPj4449bPK6j8+nGG28MJk2adNT9L730UpCfnx/s2LGjVXchRPN0Zj415sEHHwwGDhzYqlOs+fSjH/0oGDRoUKvHxSufzjrrrOAb3/hGg/u+/vWvB2PGjGnVUQjRkER+DhXr36V+/etfB6NHj27252PHjg2mTZvW4L7//u//Drp06dLk8d/97neDkSNHHnX///zP/wQZGRlBVVVV7X3PP/98VM/zROegV0olCSUlJcyfP7/2v+fPn895553H2LFja+8/cOAAixYtoqSkpMlz7Nu3j5kzZzJo0CAKCwsb/GzKlCn07NmTM844gyeeeIIgCFr0qa6u5oUXXmDSpEnNHvPRRx/xhS98gf/+7/+mS5cu0f6qPP/88y2etzGbNm3i97//PaNHj27xuPLyco499tgG9+3du5eioiIKCwuZNGkSH374YdR1hRAhbc2n/fv389nPfpZHH32Uvn37Nnv+zsin+uzcuZOnnnqKs88+m8zMzBaP7ax8aqrOaaedxo9+9CMGDBjAiSeeyDe+8Q0OHDgQ03mESHU6O59q2Lx5M//3f//X4quUIPZ8gqafvzRFvPLp0KFDR33cQU5ODosXL6aysjKmcwmR6iT6c6hYiDWjdu7cydNPPx1zRp166qmkpaUxc+ZMqqqqKC8v57//+7+58MILW32eJzoJ400x0UE8/vjjQdeuXYPKysqgoqIiyMjICLZt2xb85je/Cc4999wgCILgtddeC4Bg/fr1DR776KOPBl27dg2AYNiwYQ1eJRUE4b+s/fnPfw7++te/Bvfdd1+QlZUVPPjggy36/OUvfwl69+7dYAe6PtXV1cHFF18c3HPPPUEQBME//vGPqF4ptXHjxuCYY44Jdu3a1ewxRUVFwTHHHBN07do1yM7ODoBg9OjRLT5m7ty5wTHHHBN88MEHtfe99dZbwezZs4OlS5cGCxYsCC699NIgLy8vKCsra9FRCNGQtubTf/zHfwQ333xz7X/TxL/odUY+1XDbbbcFXbp0CYDgzDPPDLZv397i8Z2RT829EuGiiy4KsrKygokTJwaLFi0K/vCHPwRFRUXB5MmTW3QUQjSkM/MpCILg2muvDXJycgIguOyyy4IDBw606BNtPtWwevXqIC8vL/jlL3/Z4nHxzKc777wz6Nu3b/DOO+8E1dXVwZIlS4I+ffoEQLB58+aofi8hREiiPocKgtheKXXw4MGgW7duDf4u1pixY8cGmZmZQdeuXWufn5144onBP/7xjyaPb+6VUkEQBAsWLAh69+4dpKenB0Bw1llntZiPonPRplSSsHr16gAI3nrrreAPf/hD7UutN23aFGRlZQUHDhwIvvOd7wQnnHDCUY/dvXt3sGrVquCNN94ILrvssuBTn/pUi0+avvOd77T68vPbbrstuOmmm5r9+YMPPhiMGTMmOHz4cBAE0W9K/exnPwvOP//8Fo8pKioKvvWtbwWrV68OVq1aFbz22mvB6NGjg7PPPru2Xn1ef/31oEuXLsHs2bNbPO/HH38cDB48OPj2t7/d4nFCiIa0JZ+ee+65YMiQIcGePXtq72vuL3316Yh8quGf//xnsHLlyuCVV14JxowZE1xyySVBdXV1s8d3Rj4195e+cePGBdnZ2cHu3btr7/vf//3fIBKJBPv372/1dxNChHR2Pm3ZsiVYvnx58NxzzwUnnXRS8OUvf7lFn2jzKQjCjabBgwc3+Itnc8Qzn/bv3x98/vOfDzIyMoL09PSgf//+wW233RYAwdatW6P63YQQIYn6HCoIYtuUevHFF5v8e2p9xo4dG0yePDlYvXp1sHr16uDPf/5zcMkllwRDhw4NKioqjjq+uU2pLVu2BEOHDg1uvfXW4K9//WvwxhtvBGPHjg0uuOCCFp/nic5Db99LEoYMGcLAgQOZP38+8+fPr315eP/+/SksLOStt95i/vz5nH/++Uc9Nj8/n6FDh3Luuefyu9/9jhUrVvDMM880W2v06NFs3LiRQ4cONXvM888/z+WXX97sz19//XUWLlxIVlYWGRkZtR+Ud9ppp3HjjTe2+bw19OzZkyFDhjB06FDOP/98Hnjggdoe1OeNN97gsssu4/777+eGG25o8ZyZmZmMGjWq1W8TFEI0pC359Prrr7N27Vq6d+9ORkYGGRkZAFx55ZVHfeNMfToin2ro2bMnJ554IuPGjWPOnDm8+OKLvP322x1y3mjyqSX69evHgAEDyM/Pr71vxIgRBEHAxo0boz6PEKlOZ+dT3759GT58OJdffjm/+MUveOyxx9iyZUuzPtHmyObNmykpKeHss8/ml7/8ZavHxzOfcnJyeOKJJ9i/fz/r1q1jw4YNHH/88bXfciWEiJ5EfQ4VK9GeNz8/nyFDhjBkyBDGjBnDjBkzWL16NXPnzo261qOPPkp+fj4/+tGPGDVqFOeeey5PPvkkr732GosWLWrPryHaiDalkoiSkhIWLFjAggULGgTOueeey0svvcTixYub/TypGoLw1XMthlFpaSk9evQgKyuryZ+vXr2a9evXM27cuGbP8dBDD/Hee+9RWlpKaWkpL774IgBz587lBz/4QZOP2bt3L/Pnz2/Te5jT09MBGnzeyoIFC5g4cSI//OEP+Y//+I9Wz1FVVcX7779Pv379Yq4vRKoTaz7dcccdLFu2rDYjSktLAbj//vuZOXNms3U6Ip+aorq6GqDZbOzofGqNMWPGsHnzZvbu3Vt736pVq0hLS2PgwIExOwiRysQrn1rLkWjzadOmTZx33nm136Ccltby0/l451MNmZmZDBw4kPT0dObMmcOll17aqqsQ4mgS/TlUawRBwO9///u4ZdT+/fuPyqKa89TktIgvGdYCouMoKSlhypQpVFZWNvggzbFjx/LVr36Vjz/+uEFg/f3vf2fu3LmMHz+eXr16sXHjRu677z5ycnK45JJLAPj973/PRx99xJlnnkl2djbz5s3j3nvv5Rvf+EazHs899xwXXnhhix9eftxxxzX4727dugEwePDgZv9C9fLLL3PiiSdy/PHHt9qLPXv2sHXrVoIgoKysjNtuu41evXpx9tlnA+GHBF566aVMmzaNK6+8kq1btwJwzDHH1H5Y6N13382ZZ57JkCFD2L17Nz/+8Y9Zv349//7v/95qfSFEQ2LNp759+zb5wZzHHXccgwYNAjovnxYtWsSSJUs455xz6NGjB2vXruU73/kOgwcP5qyzzmryMR2ZTwB/+9vf+Pjjj9m5cyd79uypfUJZXFwMwGc/+1nuuecePv/5z/O9732P7du3c+utt3LTTTeRk5PTqoMQoo7OyKcXX3yRjz76iNNPP51u3brx4YcfcuuttzJmzJhmcyKafKrZkCoqKuInP/kJ//znPxt4NUW882nVqlUsXryY0aNHs2vXLn7605/ywQcfMHv27FbrCyGOJpGeQwFs2LCBnTt3smHDBqqqqmozYsiQIbV/56vPu+++y/79+znnnHNaPC+EG0o1f2/76KOPuOeee8jOzmb8+PG1x6xZs4a9e/eydetWDhw4UFv/pJNO4phjjmHixIncf//93H333fzbv/0be/bs4Zvf/CZFRUWMGjWqVQfRCRi+dVB0MDWfyzR8+PAG969bt672Q8zrs2nTpmDChAlB7969g8zMzGDgwIHBZz/72WDFihW1x7z00ktBcXFx0K1bt6Br167ByJEjg5///OctfrjdOeecEzz++ONtcm/pM6Wuv/764Fvf+lar5yoqKgqA2luvXr2CSy65pMG5b7zxxgbH1NzGjh1be8x//ud/Bscdd1xwzDHHBH369AkuueSS4K9//WtMv5cQIiTWfGoKGn0eQmfl07Jly4KSkpLg2GOPDbKysoLjjz8++NKXvhRs3Lix2cd0ZD41dVzNrT7Lly8PLrzwwiAnJycYOHBg8PWvf12fJyVEG+iMfHr99deDs846K8jPzw+ys7ODoUOHBrfffnuLH6QbTT7NnDmzyWxo6Sl9vPPpb3/7W1BcXBzk5OQEeXl5waRJkxo8txRCxEYiPYcKgub/njV//vwmj//2t78dXHfdda2ed+zYsQ3O16NHj2Ds2LHB66+/3uJxNbf6H4j+29/+Nhg1alTQtWvXoFevXsHll18eLF++vFUH0TlEgqCV730UIga2b99Ov3792LhxI3369Omw8x4+fJg+ffrw0ksvccYZZ3TYeYUQqYPySQjhFeWTEMIznZVRAKeccgrf/va3ufrqqzv0vCJx0Bu7RYeyc+dOfvrTn3Z4WO3cuZOvfe1rnH766R16XiFE6qB8EkJ4RfkkhPBMZ2XUxx9/zJVXXsmECRM69LwisdArpYQQQgghhBBCCCFE3NErpYQQQgghhBBCCCFE3NGmlBBCCCGEEEIIIYSIO9qUEkIIIYQQQgghhBBxR5tSQgghhBBCCCGEECLuaFNKCCGEEEIIIYQQQsQdbUoJIYQQQgghhBBCiLijTSkhhBBCCCGEEEIIEXe0KSWEEEIIIYQQQggh4o42pYQQQgghhBBCCCFE3NGmlBBCCCGEEEIIIYSIO9qUEkIIIYQQQgghhBBxR5tSQgghhBBCCCGEECLuaFNKCCGEEEIIIYQQQsQdbUoJIYQQQgghhBBCiLiTEe+C1dXVbN68mdzcXCKRSLzLCyEcEgQBe/bsoX///qSlaa9cCCGEEEIIIVKBuG9Kbd68mcLCwniXFUIkAGVlZQwcONBaQwghhBBCCCFEHIj7plRubm7t/+/SL97VYf9WIAAi0KVv/OvLQQ7eHKzrA+zfEv5v/XwQQgghhBBCCJHcxH1TquYte136wfWb410dnhoI+zZB1/5w3cb415eDHLw5WNcHeLJ/uDGlt/QKIYQQQgghROqgD28RQgghhBBCCCGEEHFHm1JCCCGEEEIIIYQQIu5oU0oIIYQQQgghhBBCxJ24f6ZUe9i+FHavgMo9kJkL3YdDz1FySEUH6/peHAoppi/DySaXg+xhKysoozSuDh76IIQQQgghhBAi8XC/KXX4AKydAx88BDtKj/55QTGcPBUGXwsZOXJIZgfr+l4cMsnmdK6lhKkcx9G7PxtYynweYglzqORgpzh46IMQQgghhBBCiMTG9dv3dq+Cp0fAGzfBjmVNH7NjWfjzp0dA+Wo5JKuDdX0vDr0Zyl0s5waeYCCnNHnMQE7hBp7gLpbTmyEd7uChD0IIIYQQQgghEh+3m1K7V8GzZ8K+mq+or27mwCP379sIz4zu2L8Ay8GHg3V9Lw69GcodvE0PBhAhQhrpTR6XRjoRIvRgAHewqEM3pjz0QQghhBBCCCFEchDzptSbb77JZZddRv/+/YlEIjz77LMdLnX4ALw4HiorIKiK7jFBVXj8H8aFj5dDcjhY1/fikEk203iFbHJJJzOqx6STSTa5TGMemWS328FDH4QQQgghhBBCJA8xb0rt27ePkSNH8uijj3aGDxB+Vs3e9dH/xbeGoCp83Nq5ckgWB+v6XhxO51oKKIp6Q6qGdDLpyfGcxjXtdvDQByGEEEIIIYQQyUPMm1ITJkzg+9//PldccUVn+ADhhye3+Y2FaUceL4ekcLCu78WhhKkEzb5XrmWqqaKEW9rt4KEPQgghhBBCCCGSB3efKbV96ZFv82rb37+hGnYsDc8jh8R2sK7vxaGQYo5jVLOfIdUaaaRTxKkUUtxmBw99EEIIIYQQQgiRXHT6ptShQ4eoqKhocGuJ3Ss6pu7ule14rBxcOFjX9+LQl+Ed4tCHYW1+rIc+CCGEEEIIIYRILjp9U2r69Onk5+fX3goLC1s8vnJPx9StbHnvSw4J4GBd34tDNrkd4pBDXpsf+/+3d+/hVdV3vsffO5cmEZKA4S4RlUugMpAULbbOFNIWvFCP47EiffC0PJ3pZUqFttNzKnPmnHHGUej0zBlBq51jUZjBFpwLrbVqQUV7ERFo4qUFFDpAuMlAyQUkMST7/LFJAElCdrLZa+3F+/U86/Fh7d9v/T75reUfv++zLmGYB0mSJElStJz3otSCBQuoq6tr32pqarpsn5ua9Te5PV9/myEkGYIePywZGklNReg4Pa8IhWEeJEmSJEnRknO+B8jLyyMvL6/b7ful5kmlXh3HDOHIEPT4YclwgNQ8O9eb44RhHiRJkiRJ0ZL0nVJHjx6lurqa6upqAP7jP/6D6upqdu/enZJAAyqgpLwnyU7KgpIKGFBuhkzPEPT4YclQQzW7qaKVlh71b6WFXWxmD6/1OEMY5kGSJEmSFC1JLzE3bdpERUUFFRUVAHzjG9+goqKC//2//3fKQo2fR6++8jV+nhmikiHo8cOSYR1LiPWwIpRFNut4oNcZwjAPkiRJkqToSHqVO3XqVOLx+FnbsmXLUhZq5CzoOwJi2cn1i2Un+o283QxRyRD0+GHJsJGVHGYXLTQn1a+FZg6xk02s6nWGMMyDJEmSJCk6zvuLznsipwBuXJN4KXJ3F8Cx7ET7GWsT/c0QjQxBjx+WDM00spjpNNLQ7cJUC8000sBiptFMY68zhGEeJEmSJEnREcqiFEC/MXDLBugz/OSOzpKe3N9neKJ98WgzRC1D0OOHJcNB3mYRkznCXoBO3zHVtv8Ie1nEZA6yPWUZwjAPkiRJkqRoCG1RChIL2ZlbYMpjUDKx4zYlExO/z9xyfha+ZghHhqDHD0uGg2znbsaxjDnUUN1hmxqqWcYc7mZcSgtSbcIwD5IkSZKkzJcTdIBzySmAsjmJ7VAV1G6D5vrEI0H9yhJfBTPDhZEh6PHDkqGZRtaznPUsp5RyBlNGAUUcp5532NZpsSqVwjAPkiRJkqTMFvqi1OkGVAS/2DVDODIEPX5YMtRQnZYiVFfCMA+SJEmSpMwT6sf3JEmSJEmSFE0WpSRJkiRJkpR2FqUkSZIkSZKUdrF4PB5P54D19fUUFxdDDPoMS+fICe/uh3grxLLgoqHpH98MZghbhqDHBzi2D4hDXV0dRUVFwYSQJEmSJKVVcEUpSXofi1KSJEmSdOEI7ut73illBjOEIkPQ48OpO6UkSZIkSReOwIpSFw2B2XvSP+7jw+HY3sTiO4jxzWCGsGUIenyAFcMSxTFJkiRJ0oXDF51LkiRJkiQp7SxKSZIkSZIkKe0sSkmSJEmSJCntgnvReQ8cqoLardDcALmF0G8sDKi48DKUUs4QxpJPIY00cICt1FB9QWXwPIQnQxjOhSRJkiQp84S+KHXiOOxYCW8ugcPVZ/9eUg7j58HIWZBTEN0MueRzNbOoZB6XcvaKfzdVrGMJG1lJM42RzOB5CE+GMJwLSZIkSVJmi8Xj8bR+iL2+vp7i4mIuGgp37Ou6be1b8PR0OLqLxIOGrR00Orm/7wiYsRaKR3d9zLYvjfW5pHtfGgtDhkGMZj5rKGEEcVrJIvusNq20ECOLw+xiMdM4yPZIZTgf5yHZDOdjDsKQIQz/T7R9fa+uro6ioqJzh5AkSZIkZbzQvlOq9i340TVwrG2R3NHC97T9x/bA6slQ93a0MgxiNHfxCv25hBixDosQAFlkEyNGfy7hLjYwiFGRyeB5CE+GMJwLSZIkSVI0hLIodeJ44k6M5nqIt3SvT7wl0f6n0xL9o5Ahl3zms4Z8Cskmt1t9sskln0Lms5Zc8jM+g+chPBnCcC4kSZIkSdGRVFFq4cKFXH311RQWFjJo0CD++I//mG3btqU81I6ViUeDurvwbRNvSfTbsSoaGa5mFiWM6HYRok02uQzgMq7i9ozP4HkIT4YwnAtJkiRJUnQkVZR66aWXmDt3Lq+88gpr166lubmZ6dOnc+zYsZSGenNJsslOk3WyfwQyVDKPeKfPR3WtlRYquTPjM3gewpMhDOdCkiRJkhQdSS0xn332WebMmcOVV17JxIkTWbZsGbt372bz5s0pC3So6uTXvHq2/oZWOFyVOE4mZyilnEup6PS9QeeSRTYjmEQp5RmbwfMQngxhOBeSJEmSpGjp1Tul6urqALj44os7bdPU1ER9ff0ZW1dqt/Ym0WnH6cVThWHIMISxKckwmLKMzeB5CE+GMJwLSZIkSVK09Lgo1drayte+9jWuvfZaxo8f32m7hQsXUlxc3L6VlpZ2edzmhp4met9xuq59hT5DPoUpyVBAUcZm8DyEJ0MYzoUkSZIkKVp6XJSaO3cub775JitXruyy3YIFC6irq2vfampqumyfm5r1N7k9X3+HIkMjqakCHKfnVYCgM3gewpMhDOdCkiRJkhQtOT3p9NWvfpWnnnqKn//85wwfPrzLtnl5eeTl5XX72P1S86RSr44ThgwHSM3zUr05TtAZPA/hyRCGcyFJkiRJipak7pSKx+N89atfZfXq1bzwwgtcfvnlKQ80oAJKypNNdposKKmAAeWZnaGGanZTRSstPerfSgu72MweXsvYDJ6H8GQIw7mQJEmSJEVLUkvMuXPnsmLFCn7wgx9QWFjIgQMHOHDgAMePH09pqPHz6NVXvsbPi0aGdSwh1sMqQBbZrOOBjM/geQhPhjCcC0mSJElSdCS1yn344Yepq6tj6tSpDB06tH1btWpVSkONnAV9R0AsO7l+sexEv5G3RyPDRlZymF200JxUvxaaOcRONtH78xJ0Bs9DeDKE4VxIkiRJkqIj6cf3OtrmzJmT0lA5BXDjmsRLkbu7AI5lJ9rPWJvoH4UMzTSymOk00tDtYkQLzTTSwGKm0UxjxmfwPIQnQxjOhSRJkiQpOnr89b3zrd8YuGUD9Gl7j3pnSU/u7zM80b54dLQyHORtFjGZI+wF6PS9Qm37j7CXRUzmINsjk8HzEJ4MYTgXkiRJkqRoCG1RChIL2ZlbYMpjUDKx4zYlExO/z9xyfha+YchwkO3czTiWMYcaqjtsU0M1y5jD3YxLaREiLBk8D+HJEIZzIUmSJEnKfDlBBziXnAIom5PYDlVB7TZork88EtSvLPFVsAshQzONrGc561lOKeUMpowCijhOPe+wrdMCRZQyeB7CkyEM50KSJEmSlNlCX5Q63YCK4Be7YchQQ3VaCg9hzuB5CE+GMJwLSZIkSVLmCfXje5IkSZIkSYomi1KSJEmSJElKO4tSkiRJkiRJSrtYPB6Pp3PA+vp6iouLIQZ9hqVz5IR390O8FWJZcNHQ9I9vBjOELUPQ4wMc2wfEoa6ujqKiomBCSJIkSZLSKriilCS9j0UpSZIkSbpwBPf1Pe+UMoMZQpEh6PHh1J1SkiRJkqQLR2BFqYuGwOw96R/38eFwbG9i8R3E+GYwQ9gyBD0+wIphieKYJEmSJOnC4YvOJUmSJEmSlHYWpSRJkiRJkpR2FqUkSZIkSZKUdsG96LwHDlVB7VZoboDcQug3FgZUmOFCzFBKOUMYSz6FNNLAAbZSQ3X6AhD8HIDzIEmSJEnKXKEvSp04DjtWwptL4HD12b+XlMP4eTByFuQUmCHKGXLJ52pmUck8LuXsqsduqljHEjaykmYaUx+A4OcAnAdJkiRJUjTE4vF4Wj/EXl9fT3FxMRcNhTv2dd229i14ejoc3UXiQcPWDhqd3N93BMxYC8Wjuz5m25fG+lzSvS+NmSEcGQYxmvmsoYQRxGkli+yz2rTSQowsDrOLxUzjINvP+Xclk+F8zEGyGc7HPIThWmj7+l5dXR1FRUXnDiFJkiRJynihfadU7Vvwo2vgWNsiuaOF72n7j+2B1ZOh7m0zRC3DIEZzF6/Qn0uIEeuwEAOQRTYxYvTnEu5iA4MYlZoABD8H4DxIkiRJkqIllEWpE8cTd2I010O8pXt94i2J9j+dluhvhmhkyCWf+awhn0Kyye1Wn2xyyaeQ+awll/zeBSD4OQDnQZIkSZIUPUkVpR5++GEmTJhAUVERRUVFfOQjH+GZZ55JeagdKxOPBnV34dsm3pLot2OVGaKS4WpmUcKIbhdi2mSTywAu4ypu710Agp8DcB4kSZIkSdGTVFFq+PDhLFq0iM2bN7Np0yY+/vGPc/PNN/Ob3/wmpaHeXJJsstNknexvhkhkqGQe8U6fEetaKy1UcmfvAhD8HIDzIEmSJEmKnqSWmDfddBM33ngjo0ePZsyYMdx777307duXV155JWWBDlWd/JpXz9bf0AqHqxLHMUNmZyilnEup6PTdSeeSRTYjmEQp5T0LQPBzAM6DJEmSJCmaevxOqZaWFlauXMmxY8f4yEc+0mm7pqYm6uvrz9i6Uru1p4ned5xtvehrhlBkGMLYlIw/mLIe9w16DsB5kCRJkiRFU9JFqTfeeIO+ffuSl5fHl7/8ZVavXs0HP/jBTtsvXLiQ4uLi9q20tLTL4zc3JJuok+N0XfsyQwZkyKcwJeMXUNTjvkHPATgPkiRJkqRoSrooVVZWRnV1NRs2bODP/uzP+NznPsdvf/vbTtsvWLCAurq69q2mpqbL4+emZv1Nbs/X32YISYZGUlMJOU7PKyFBzwE4D5IkSZKkaMpJtsMHPvABRo0aBcCkSZPYuHEjixcv5h//8R87bJ+Xl0deXl63j98vNU8q9eo4ZghHhgOk5pmx3hwn6DkA50GSJEmSFE09fqdUm9bWVpqamlKRBYABFVBSTq++8lVSAQPKzZDpGWqoZjdVtNLSo/6ttLCLzezhtZ4FIPg5AOdBkiRJkhRNSS0xFyxYwM9//nN27tzJG2+8wYIFC3jxxReZPXt2SkONn0evvvI1fp4ZopJhHUuI9bASkkU263igdwEIfg7AeZAkSZIkRU9Sq9yDBw/y2c9+lrKyMj7xiU+wceNGfvaznzFt2rSUhho5C/qOgFh2cv1i2Yl+I283Q1QybGQlh9lFC81J9WuhmUPsZBOreheA4OcAnAdJkiRJUvQkVZRaunQpO3fupKmpiYMHD/Lcc8+lvCAFkFMAN65JvBS5uwvgWHai/Yy1if5miEaGZhpZzHQaaeh2QaaFZhppYDHTaKaxdwEIfg7AeZAkSZIkRU+v3yl1vvQbA7dsgD7DT+7oLOnJ/X2GJ9oXjzZD1DIc5G0WMZkj7AXo9N1KbfuPsJdFTOYg21MTgODnAJwHSZIkSVK0hLYoBYmF7MwtMOUxKJnYcZuSiYnfZ245PwtfM4Qjw0G2czfjWMYcaqjusE0N1SxjDnczLqWFmDZBzwE4D5IkSZKk6MgJOsC55BRA2ZzEdqgKardBc33ikaB+ZYmvgpnhwsjQTCPrWc56llNKOYMpo4AijlPPO2zrtEiTSkHPATgPkiRJkqRoCH1R6nQDKoJf7JohHBlqqE5L8aUrQc8BOA+SJEmSpMwV6sf3JEmSJEmSFE0WpSRJkiRJkpR2FqUkSZIkSZKUdrF4PB5P54D19fUUFxdDDPoMS+fICe/uh3grxLLgoqHpH98MZghbhqDHBzi2D4hDXV0dRUVFwYSQJEmSJKVVcEUpSXofi1KSJEmSdOEI7ut73illBjOEIkPQ48OpO6UkSZIkSReOwIpSFw2B2XvSP+7jw+HY3sTiO4jxzWCGsGUIenyAFcMSxTFJkiRJ0oXDF51LkiRJkiQp7SxKSZIkSZIkKe0sSkmSJEmSJCntgnvReQ8cqoLardDcALmF0G8sDKgww4WYoZRyhjCWfApppIEDbKWG6vQFMEO7oK8FSZIkSVJmCn1R6sRx2LES3lwCh6vP/r2kHMbPg5GzIKfADFHOkEs+VzOLSuZxKWdXPXZTxTqWsJGVNNOY+gBmaBf0tSBJkiRJynyxeDye1g+x19fXU1xczEVD4Y59XbetfQueng5Hd5F40LC1g0Yn9/cdATPWQvHoro/Z9qWxPpd070tjZghHhkGMZj5rKGEEcVrJIvusNq20ECOLw+xiMdM4yPZz/l1mCMe10Pb1vbq6OoqKis4dQpIkSZKU8UL7Tqnat+BH18CxtkVyRwvf0/Yf2wOrJ0Pd22aIWoZBjOYuXqE/lxAj1mEhBiCLbGLE6M8l3MUGBjEqNQHM0C7oa0GSJEmSFB2hLEqdOJ64E6O5HuIt3esTb0m0/+m0RH8zRCNDLvnMZw35FJJNbrf6ZJNLPoXMZy255PcugBnaBX0tSJIkSZKipVdFqUWLFhGLxfja176WojgJO1YmHg3q7sK3Tbwl0W/HKjNEJcPVzKKEEd0uxLTJJpcBXMZV3N67AGZoF/S1IEmSJEmKlh4XpTZu3Mg//uM/MmHChFTmARIvT+5xsqyT/c0QiQyVzCPe6TNiXWulhUru7F0AM7QL+lqQJEmSJEVLj5aYR48eZfbs2TzyyCP0798/pYEOVZ38mlfP1t/QCoerEscxQ2ZnKKWcS6no9N1J55JFNiOYRCnlPQtghnZBXwuSJEmSpOjpUVFq7ty5zJgxg09+8pPnbNvU1ER9ff0ZW1dqt/YkUQfH2daLvmYIRYYhjE3J+IMp63FfMyQEfS1IkiRJkqInJ9kOK1eu5Ne//jUbN27sVvuFCxfy13/9190+fnNDsok6OU7XtS8zZECGfApTMn4BRT3ua4aEoK8FSZIkSVL0JHWnVE1NDfPnz+fxxx8nP797X/NasGABdXV17VtNTU2X7XNTs/4mt+frbzOEJEMjqamEHKfnlRAzJAR9LUiSJEmSoiepO6U2b97MwYMH+dCHPtS+r6WlhZ///Oc8+OCDNDU1kZ195ntv8vLyyMvL6/YY/VLzpFKvjmOGcGQ4QGqeGevNccyQEPS1IEmSJEmKnqTulPrEJz7BG2+8QXV1dft21VVXMXv2bKqrq88qSPXEgAooKU822WmyoKQCBpSbIdMz1FDNbqpopaVH/VtpYReb2cNrPQtghnZBXwuSJEmSpOhJaolZWFjI+PHjz9j69OlDSUkJ48ePT1mo8fPo1Ve+xs8zQ1QyrGMJsR5WQrLIZh0P9C6AGdoFfS1IkiRJkqKlp/c9nFcjZ0HfERBL8sarWHai38jbzRCVDBtZyWF20UJzUv1aaOYQO9nEqt4FMEO7oK8FSZIkSVK09Loo9eKLL3L//fenIMopOQVw45rES5G7uwCOZSfaz1ib6G+GaGRoppHFTKeRhm4XZFpoppEGFjONZhp7F8AM7YK+FiRJkiRJ0RLKO6UA+o2BWzZAn+End3SW9OT+PsMT7YtHmyFqGQ7yNouYzBH2AnT6bqW2/UfYyyImc5DtqQlghnZBXwuSJEmSpOgIbVEKEgvZmVtgymNQMrHjNiUTE7/P3HJ+Fr5mCEeGg2znbsaxjDnUUN1hmxqqWcYc7mZcSgsxZjhT0NeCJEmSJCkacoIOcC45BVA2J7EdqoLabdBcn3gkqF9Z4qtgZrgwMjTTyHqWs57llFLOYMoooIjj1PMO2zot0pgh9YK+FiRJkiRJmS/0RanTDagIfrFrhnBkqKE6LcUXM5xb0NeCJEmSJCkzhfrxPUmSJEmSJEWTRSlJkiRJkiSlnUUpSZIkSZIkpV0sHo/H0zlgfX09xcXFEIM+w9I5csK7+yHeCrEsuGho+sc3gxnCliHo8QGO7QPiUFdXR1FRUTAhJEmSJElpFVxRSpLex6KUJEmSJF04gvv6nndKmcEMocgQ9Phw6k4pSZIkSdKFI7Ci1EVDYPae9I/7+HA4tjex+A5ifDOYIWwZgh4fYMWwRHFMkiRJknTh8EXnkiRJkiRJSjuLUpIkSZIkSUo7i1KSJEmSJElKu+BedN4Dh6qgdis0N0BuIfQbCwMqLrwMpZQzhLHkU0gjDRxgKzVUpzVD0PPgHCSEYR7CkEGSJEmSlHlCX5Q6cRx2rIQ3l8Dh6rN/LymH8fNg5CzIKYhuhlzyuZpZVDKPSzm78rGbKtaxhI2spJnG85Ih6HlwDhLCMA9hyCBJkiRJymyxeDye1g+x19fXU1xczEVD4Y59XbetfQueng5Hd5F40LC1g0Yn9/cdATPWQvHoro/Z9qWxPpd070tjYcgwiNHMZw0ljCBOK1lkn9WmlRZiZHGYXSxmGgfZntIMQc/D+ZiDZDOcjzlINkMYroXzkaHt63t1dXUUFRWdO4QkSZIkKeOF9p1StW/Bj66BY22L5I4KAKftP7YHVk+GurejlWEQo7mLV+jPJcSIdVgAAMgimxgx+nMJd7GBQYxKWYag58E5SAjDPIQhgyRJkiQpGkJZlDpxPHFHSnM9xFu61yfekmj/02mJ/lHIkEs+81lDPoVkk9utPtnkkk8h81lLLvm9zhD0PDgHCWGYhzBkkCRJkiRFR1JFqbvvvptYLHbGNnbs2JSH2rEy8YhUdwsAbeItiX47VkUjw9XMooQR3S4AtMkmlwFcxlXc3usMQc+Dc5AQhnkIQwZJkiRJUnQkfafUlVdeyf79+9u3X/7ylykP9eaSniQ7Ketk/whkqGQe8U6fE+taKy1UcmevMwQ9D85BQhjmIQwZJEmSJEnRkfRSOycnhyFDhrRvAwYMSGmgQ1Unv2rWs7UvtMLhqsRxMjlDKeVcSkWn7+w5lyyyGcEkSinvcYag58E5SAjDPIQhgyRJkiQpWpIuSr399tsMGzaMK664gtmzZ7N79+4u2zc1NVFfX3/G1pXarckm6uQ423rRNwQZhpCaxyIHU9bjvkHPg3OQEIZ5CEMGSZIkSVK0JFWUmjx5MsuWLePZZ5/l4Ycf5j/+4z/4oz/6IxoaGjrts3DhQoqLi9u30tLSLsdo7vxQSWnuuvYV+gz5FKYkQwFFPe4b9Dw4BwlhmIcwZJAkSZIkRUtSRakbbriB2267jQkTJnDdddfx9NNPU1tbyxNPPNFpnwULFlBXV9e+1dTUdDlGbmrWvuT2Yu0bhgyNpKYacpyeV0OCngfnICEM8xCGDJIkSZKkaMnpTed+/foxZswYtm/f3mmbvLw88vLyun/MFH3MrzfHCUOGA6TmubHeHCfoeXAOEsIwD2HIIEmSJEmKlp5+UwyAo0ePsmPHDoYOHZqqPAyogJJyevW1s5IKGFCe2RlqqGY3VbTS0qP+rbSwi83s4bUeZwh6HpyDhDDMQxgySJIkSZKiJaml9je/+U1eeukldu7cycsvv8wtt9xCdnY2n/nMZ1Iaavw8evW1s/HzopFhHUuI9bAakkU263ig1xmCngfnICEM8xCGDJIkSZKk6Ehqhblnzx4+85nPUFZWxsyZMykpKeGVV15h4MCBKQ01chb0HQGxJL8+H8tO9Bt5ezQybGQlh9lFC81J9WuhmUPsZBOrep0h6HlwDhLCMA9hyCBJkiRJio6kilIrV65k3759NDU1sWfPHlauXMnIkSNTHiqnAG5ck3g5dHcLAbHsRPsZaxP9o5ChmUYWM51GGrpdCGihmUYaWMw0mmnsdYag58E5SAjDPIQhgyRJkiQpOnr1Tqnzqd8YuGUD9Bl+ckdnSU/u7zM80b54dLQyHORtFjGZI+wF6PSdPm37j7CXRUzmIJ2/fD5ZQc+Dc5AQhnkIQwZJkiRJUjSEtigFiQX9zC0w5TEomdhxm5KJid9nbkltASBMGQ6ynbsZxzLmUEN1h21qqGYZc7ibceelABD0PDgHCWGYhzBkkCRJkiRlvpygA5xLTgGUzUlsh6qgdhs01ycejepXlvg62oWQoZlG1rOc9SynlHIGU0YBRRynnnfY1mlxIJWCngfnICEM8xCGDJIkSZKkzBb6otTpBlSkZ9Ef9gw1VAe+6A96HpyDhDDMQxgySJIkSZIyT6gf35MkSZIkSVI0WZSSJEmSJElS2lmUkiRJkiRJUtrF4vF4PJ0D1tfXU1xcDDHoMyydIye8ux/irRDLgouGpn98M5ghbBmCHh/g2D4gDnV1dRQVFQUTQpIkSZKUVsEVpSTpfSxKSZIkSdKFI7iv73mnlBnMEIoMQY8Pp+6UkiRJkiRdOAIrSl00BGbvSf+4jw+HY3sTi+8gxjeDGcKWIejxAVYMSxTHJEmSJEkXDl90LkmSJEmSpLSzKCVJkiRJkqS0syglSZIkSZKktAvuRec9cKgKardCcwPkFkK/sTCg4sLLUEo5QxhLPoU00sABtlJD9QWVwfNgBkmSJElSZgt9UerEcdixEt5cAoerz/69pBzGz4ORsyCnILoZcsnnamZRyTwu5ezqy26qWMcSNrKSZhojmcHzYAZJkiRJUnTE4vF4Wj/EXl9fT3FxMRcNhTv2dd229i14ejoc3UXiQcPWDhqd3N93BMxYC8Wjuz5m25fG+lzSvS+NhSHDIEYznzWUMII4rWSRfVabVlqIkcVhdrGYaRxke6QynI/zkGyG8zEHYcgQhmuh7et7dXV1FBUVnTuEJEmSJCnjhfadUrVvwY+ugWNti+SOihCn7T+2B1ZPhrq3o5VhEKO5i1fozyXEiHVYAADIIpsYMfpzCXexgUGMikwGz4MZJEmSJEnRE8qi1Injibtimush3tK9PvGWRPufTkv0j0KGXPKZzxryKSSb3G71ySaXfAqZz1pyyc/4DJ4HM0iSJEmSoinpotTevXu54447KCkpoaCggD/4gz9g06ZNKQ21Y2XiMa3uFiHaxFsS/XasikaGq5lFCSO6XQBok00uA7iMq7g94zN4HswgSZIkSYqmpIpSR44c4dprryU3N5dnnnmG3/72t/z93/89/fv3T2moN5ckm+w0WSf7RyBDJfOId/qsWtdaaaGSOzM+g+fBDJIkSZKkaEpquf/tb3+b0tJSHnvsMT784Q9z+eWXM336dEaOHJmyQIeqTn5ZrWdrX2iFw1WJ42RyhlLKuZSKTt/Zcy5ZZDOCSZRSnrEZPA9mkCRJkiRFV1JFqSeffJKrrrqK2267jUGDBlFRUcEjjzzSZZ+mpibq6+vP2LpSuzWZRF0cZ1sv+oYgwxDGpiTDYMoyNoPnwQySJEmSpOhKqij1u9/9jocffpjRo0fzs5/9jD/7sz9j3rx5LF++vNM+CxcupLi4uH0rLS3tcozmhmQSdXGcrmtfoc+QT2FKMhRQlLEZPA9mkCRJkiRFV1JFqdbWVj70oQ9x3333UVFRwRe/+EW+8IUv8L3vfa/TPgsWLKCurq59q6mp6XKM3NSsfcntxdo3DBkaSU1F5jg9r8gEncHzYAZJkiRJUnQlVZQaOnQoH/zgB8/YN27cOHbv3t1pn7y8PIqKis7YutIvNU8J9eo4YchwgNQ8u9ab4wSdwfNgBkmSJElSdCVVlLr22mvZtu3MF/S89dZbjBgxImWBBlRASXmyyU6TBSUVMKA8szPUUM1uqmilpUf9W2lhF5vZw2sZm8HzYAZJkiRJUnQltdz/+te/ziuvvMJ9993H9u3b+cEPfsD/+3//j7lz56Y01Ph59OqLa+PnRSPDOpYQ62FFJots1vFAxmfwPJhBkiRJkhRNSa0wr776alavXs0Pf/hDxo8fzz333MP999/P7NmzUxpq5CzoOwJiSX59Ppad6Dfy9mhk2MhKDrOLFpqT6tdCM4fYySZWZXwGz4MZJEmSJEnRlPRtD5/61Kd44403aGxsZMuWLXzhC19IeaicArhxTeIF1d0tRsSyE+1nrE30j0KGZhpZzHQaaeh2IaCFZhppYDHTaKYx4zN4HswgSZIkSYqmnr6t57zrNwZu2QB9hp/c0VnSk/v7DE+0Lx4drQwHeZtFTOYIewE6fadP2/4j7GURkznI9shk8DyYQZIkSZIUPaEtSkGiqDBzC0x5DEomdtymZGLi95lbUluECFOGg2znbsaxjDnUUN1hmxqqWcYc7mbceSkABJ3B82AGSZIkSVK05AQd4FxyCqBsTmI7VAW126C5PvF4Vr+yxBfaLoQMzTSynuWsZzmllDOYMgoo4jj1vMO2TosDUcrgeTCDJEmSJCk6Ql+UOt2AivQUHsKeoYbqwBf9QWfwPJhBkiRJkpTZQv34niRJkiRJkqLJopQkSZIkSZLSzqKUJEmSJEmS0s6ilCRJkiRJktIuFo/H4+kcsL6+nuLiYohBn2HpHDnh3f0Qb4VYFlw0NP3jm8EMYcsQ9PgAx/YBcairq6OoqCiYEJIkSZKktAquKCVJ72NRSpIkSZIuHDmBjeydUmYwQygyBD0+nLpTSpIkSZJ04QisKHXREJi9J/3jPj4cju1NLL6DGN8MZghbhqDHB1gxLFEckyRJkiRdOHzRuSRJkiRJktLOopQkSZIkSZLSzqKUJEmSJEmS0i64F533wKEqqN0KzQ2QWwj9xsKAigsvQynlDGEs+RTSSAMH2EoN1RdUhqDHB6+FMGWQJEmSJGWe0BelThyHHSvhzSVwuPrs30vKYfw8GDkLcgqimyGXfK5mFpXM41LOrnzspop1LGEjK2mmMZIZgh4fvBbClEGSJEmSlNli8Xg8rR9ir6+vp7i4mIuGwh37um5b+xY8PR2O7iLxoGFrB41O7u87AmasheLRXR+z7UtjfS7p3pfGwpBhEKOZzxpKGEGcVrLIPqtNKy3EyOIwu1jMNA6yPVIZzsf4yWY4H9dCshmCPg/nK0Pb1/fq6uooKio6dwhJkiRJUsYL7Tulat+CH10Dx9oWyR0VAE7bf2wPrJ4MdW9HK8MgRnMXr9CfS4gR67AAAJBFNjFi9OcS7mIDgxgVmQxBjw9eC2HKIEmSJEmKhqSKUpdddhmxWOysbe7cuSkNdeJ44o6U5nqIt3SvT7wl0f6n0xL9o5Ahl3zms4Z8Cskmt1t9sskln0Lms5Zc8jM+Q9Djg9dCmDJIkiRJkqIjqaLUxo0b2b9/f/u2du1aAG677baUhtqxMvGIVHcLAG3iLYl+O1ZFI8PVzKKEEd0uALTJJpcBXMZV3J7xGYIeH7wWwpRBkiRJkhQdSRWlBg4cyJAhQ9q3p556ipEjRzJlypSUhnpzSbLJTpN1sn8EMlQyj3inz4l1rZUWKrkz4zMEPT54LYQpgyRJkiQpOnr8Tqn33nuPFStW8PnPf55YLJayQIeqTn7VrGdrX2iFw1WJ42RyhlLKuZSKTt/Zcy5ZZDOCSZRSnrEZgh4fvBbClEGSJEmSFC09Lkr96Ec/ora2ljlz5nTZrqmpifr6+jO2rtRu7Wmi9x1nWy/6hiDDEMamJMNgyjI2Q9Djg9dCmDJIkiRJkqKlx0WppUuXcsMNNzBs2LAu2y1cuJDi4uL2rbS0tMv2zQ09TfS+43Rd+wp9hnwKU5KhgKKMzRD0+OC1EKYMkiRJkqRo6VFRateuXTz33HP86Z/+6TnbLliwgLq6uvatpqamy/a5qVn7ktuLtW8YMjSSmmrIcXpeDQk6Q9Djg9dCmDJIkiRJkqIlpyedHnvsMQYNGsSMGTPO2TYvL4+8vLxuH7tfap4S6tVxwpDhAKl5bqw3xwk6Q9Djg9dCmDJIkiRJkqIl6TulWltbeeyxx/jc5z5HTk6PalpdGlABJeU9SXZSFpRUwIDyzM5QQzW7qaKVlh71b6WFXWxmD69lbIagxwevhTBlkCRJkiRFS9JL7eeee47du3fz+c9//nzkAWD8PHr1tbPx86KRYR1LiPWwGpJFNut4IOMzBD0+eC2EKYMkSZIkKTqSXmFOnz6deDzOmDFjzkceAEbOgr4jIJbk1+dj2Yl+I2+PRoaNrOQwu2ihOal+LTRziJ1sYlXGZwh6fPBaCFMGSZIkSVJ09Pjre+dTTgHcuCbxcujuFgJi2Yn2M9Ym+kchQzONLGY6jTR0uxDQQjONNLCYaTTTmPEZgh4fvBbClEGSJEmSFB2hLEoB9BsDt2yAPsNP7ugs6cn9fYYn2hePjlaGg7zNIiZzhL0Anb7Tp23/EfayiMkcZHtkMgQ9PngthCmDJEmSJCkaQluUgsSCfuYWmPIYlEzsuE3JxMTvM7ektgAQpgwH2c7djGMZc6ihusM2NVSzjDnczbjzUgAIOkPQ44PXQpgySJIkSZIyX+o/n5diOQVQNiexHaqC2m3QXJ94NKpfWeLraBdChmYaWc9y1rOcUsoZTBkFFHGcet5hW6fFgShlCHp88FoIUwZJkiRJUmYLfVHqdAMq0rPoD3uGGqoDX/QHnSHo8cFrIUwZJEmSJEmZJ9SP70mSJEmSJCmaLEpJkiRJkiQp7SxKSZIkSZIkKe1i8Xg8ns4B6+vrKS4uhhj0GZbOkRPe3Q/xVohlwUVD0z++GcwQtgxBjw9wbB8Qh7q6OoqKioIJIUmSJElKq+CKUpL0PhalJEmSJOnCEdzX97xTygxmCEWGoMeHU3dKSZIkSZIuHIEVpS4aArP3pH/cx4fDsb2JxXcQ45vBDGHLEPT4ACuGJYpjkiRJkqQLhy86lyRJkiRJUtpZlJIkSZIkSVLaWZSSJEmSJElS2gX3ovMeOFQFtVuhuQFyC6HfWBhQYYYLMUPQ45vhlFLKGcJY8imkkQYOsJUaqtMbQpIkSZKUcUJflDpxHHashDeXwOHqs38vKYfx82DkLMgpMEOUMwQ9vhlOySWfq5lFJfO4lLOrYLupYh1L2MhKmmk8PyEkSZIkSRkt1I/v1b4FT4yDlz4Ph1/vuM3h1xO/PzEO6t42Q1QzBD2+GU4ZxGjuZguf5VGGM6HDNsOZwGd5lLvZwiBGpT6EJEmSJCnjhbYoVfsW/OgaONb2ifrWThqe3H9sD6yenNpFuBnCkSHo8c1wyiBGcxev0J9LiBEji+wO22WRTYwY/bmEu9hgYUqSJEmSdJakilItLS38r//1v7j88sspKChg5MiR3HPPPcTj8ZSGOnEcnp4OzfUQb+len3hLov1PpyX6myEaGYIe3wyn5JLPfNaQTyHZ5HarTza55FPIfNaSS37vQ0iSJEmSIiOpotS3v/1tHn74YR588EG2bNnCt7/9bf7u7/6OBx54IKWhdqyEo7u6v/huE29J9NuxygxRyRD0+GY45WpmUcKIbhek2mSTywAu4ypu730ISZIkSVJkJFWUevnll7n55puZMWMGl112GZ/+9KeZPn06r776akpDvbkk2WSnyTrZ3wyRyBD0+GY4pZJ5xDt9ZrBrrbRQyZ29DyFJkiRJioyklrkf/ehHef7553nrrbcAeO211/jlL3/JDTfckLJAh6pOflGsZ2tfaIXDVYnjmCGzMwQ9vhlOKaWcS6no9B1S55JFNiOYRCnlPQ8hSZIkSYqUpIpSd911F7NmzWLs2LHk5uZSUVHB1772NWbPnt1pn6amJurr68/YulK7NZlEXRxnWy/6miEUGYIe3wynDGFsSjIMpiwlx5EkSZIkZb6kilJPPPEEjz/+OD/4wQ/49a9/zfLly/k//+f/sHz58k77LFy4kOLi4vattLS0yzGaG5JJ1MVxuq59mSEDMgQ9vhlOyacwJRkKKErJcSRJkiRJmS+potR//+//vf1uqT/4gz/gv/23/8bXv/51Fi5c2GmfBQsWUFdX177V1NR0OUZuata+5PZi7WuGcGQIenwznNJIaipjx+lFZUySJEmSFCk5yTR+9913yco6s46VnZ1Na2vnL7vJy8sjLy+v22P0S81TQr06jhnCkSHo8c1wygFS8wxhqo4jSZIkScp8Sd0pddNNN3Hvvffy05/+lJ07d7J69Wr+7//9v9xyyy0pCzSgAkrKk012miwoqYAB5WbI9AxBj2+GU2qoZjdVtNLSo/6ttLCLzezhtZ6HkCRJkiRFSlLL3AceeIBPf/rTfOUrX2HcuHF885vf5Etf+hL33HNPSkONn0evvjQ2fp4ZopIh6PHNcMo6lhDrYWUsi2zW8UDvQ0iSJEmSIiOpFWZhYSH3338/u3bt4vjx4+zYsYO//du/5QMf+EBKQ42cBX1HQCzJr8/HshP9Rt5uhqhkCHp8M5yykZUcZhctNCfVr4VmDrGTTazqfQhJkiRJUmT09IGg8yqnAG5ck3gxc3cX4bHsRPsZaxP9zRCNDEGPb4ZTmmlkMdNppKHbhakWmmmkgcVMo5nG3oeQJEmSJEVGKItSAP3GwC0boM/wkzs6S3pyf5/hifbFo80QtQxBj2+GUw7yNouYzBH2AnT6jqm2/UfYyyImc5DtqQshSZIkSYqE0BalILGYnrkFpjwGJRM7blMyMfH7zC2pXXybIVwZgh7fDKccZDt3M45lzKGG6g7b1FDNMuZwN+MsSEmSJEmSOpQTdIBzySmAsjmJ7VAV1G6D5vrEY0n9yhJfJjPDhZEh6PHNcEozjaxnOetZTinlDKaMAoo4Tj3vsK3TYpUkSZIkSW1CX5Q63YCK9Cy4zRD+DEGPb4ZTaqi2CCVJkiRJSlqoH9+TJEmSJElSNFmUkiRJkiRJUtpZlJIkSZIkSVLaxeLxeDydA9bV1dGvXz8ALhqazpET3j0AxIEYXDQk/eObwQxhyxD0+ADv7k/8t7a2luLi4mBCSJIkSZLSKu1FqT179lBaWprOISVliJqaGoYPHx50DEmSJElSGqS9KNXa2sq+ffsoLCwkFosl3b++vp7S0lJqamooKio6DwnNkCkZgh7fDKnLEI/HaWhoYNiwYWRl+VSxJEmSJF0IctI9YFZWVkruhCgqKgpsAW6GcGUIenwzpCaDj+1JkiRJ0oXFWxIkSZIkSZKUdhalJEmSJEmSlHYZV5TKy8vjr/7qr8jLyzPDBZ4h6PHNEK4MkiRJkqTMkvYXnUuSJEmSJEkZd6eUJEmSJEmSMp9FKUmSJEmSJKWdRSlJkiRJkiSlXUYVpdavX092djYzZsxI+9hz5swhFou1byUlJVx//fW8/vrrac9y4MAB7rzzTq644gry8vIoLS3lpptu4vnnnz/vY58+D7m5uQwePJhp06bx6KOP0traet7Hf3+G07frr78+LeOfK8f27dvTMv6BAweYP38+o0aNIj8/n8GDB3Pttdfy8MMP8+6775738efMmcMf//Efn7X/xRdfJBaLUVtbe94zSJIkSZIyV0YVpZYuXcqdd97Jz3/+c/bt25f28a+//nr279/P/v37ef7558nJyeFTn/pUWjPs3LmTSZMm8cILL/Cd73yHN954g2effZbKykrmzp2blgxt87Bz506eeeYZKisrmT9/Pp/61Kc4ceJEWjOcvv3whz9My9jnynH55Zef93F/97vfUVFRwZo1a7jvvvuoqqpi/fr1/I//8T946qmneO655857BkmSJEmSeiMn6ADddfToUVatWsWmTZs4cOAAy5Yt4y/+4i/SmiEvL48hQ4YAMGTIEO666y7+6I/+iP/8z/9k4MCBacnwla98hVgsxquvvkqfPn3a91955ZV8/vOfT0uG0+fhkksu4UMf+hDXXHMNn/jEJ1i2bBl/+qd/mtYMQQoqx1e+8hVycnLYtGnTGdfBFVdcwc0334wf1ZQkSZIkhV3G3Cn1xBNPMHbsWMrKyrjjjjt49NFHA114Hz16lBUrVjBq1ChKSkrSMubvf/97nn32WebOnXtGIaJNv3790pKjIx//+MeZOHEi//7v/x5YhgvF4cOHWbNmTafXAUAsFktzKkmSJEmSkpMxRamlS5dyxx13AIlHpurq6njppZfSmuGpp56ib9++9O3bl8LCQp588klWrVpFVlZ6pnH79u3E43HGjh2blvGSNXbsWHbu3JmWsU4/F23bfffdl5axu8px2223nfcx266DsrKyM/YPGDCgPce3vvWt854DOj4PN9xwQ1rGliRJkiRltox4fG/btm28+uqrrF69GoCcnBxuv/12li5dytSpU9OWo7KykocffhiAI0eO8NBDD3HDDTfw6quvMmLEiPM+ftgfyYrH42m7Q+f0c9Hm4osvTsvYXeXo7M6ldHj11VdpbW1l9uzZNDU1pWXMjs7Dhg0b2gvIkiRJkiR1JiOKUkuXLuXEiRMMGzasfV88HicvL48HH3yQ4uLitOTo06cPo0aNav/397//fYqLi3nkkUf427/92/M+/ujRo4nFYmzduvW8j9UTW7ZsSctLvuHscxGUIHKMGjWKWCzGtm3bzth/xRVXAFBQUJC2LB39/Xv27Enb+JIkSZKkzBX6x/dOnDjBP/3TP/H3f//3VFdXt2+vvfYaw4YNC+SLa21isRhZWVkcP348LeNdfPHFXHfddXz3u9/l2LFjZ/1eW1ublhwdeeGFF3jjjTe49dZbA8twoSgpKWHatGk8+OCDHV4HkiRJkiRlgtDfKfXUU09x5MgR/uRP/uSsO6JuvfVWli5dype//OW0ZGlqauLAgQNA4vG9Bx98kKNHj3LTTTelZXyA7373u1x77bV8+MMf5m/+5m+YMGECJ06cYO3atTz88MNs2bLlvGdom4eWlhbeeecdnn32WRYuXMinPvUpPvvZz5738U/PcLqcnBwGDBiQlvGD9tBDD3Httddy1VVXcffddzNhwgSysrLYuHEjW7duZdKkSUFHlCRJkiSpS6EvSi1dupRPfvKTHT6id+utt/J3f/d3vP7660yYMOG8Z3n22WcZOnQoAIWFhYwdO5Z/+Zd/Set7ra644gp+/etfc++99/Lnf/7n7N+/n4EDBzJp0qSz3u1zvrTNQ05ODv3792fixIksWbKEz33uc2l76fvp56JNWVlZaB9tTLWRI0dSVVXFfffdx4IFC9izZw95eXl88IMf5Jvf/CZf+cpXgo4oSZIkSVKXYvGwvz1bkiRJkiRJkRP6d0pJkiRJkiQpeixKSZIkSZIkKe0sSkmSJEmSJCntLEpJkiRJkiQp7SxKSZIkSZIkKe0sSkmSJEmSJCntLEpJkiRJkiQp7SxKSZIkSZIkKe0sSkmSJEmSJCntLEpJkiRJkiQp7SxKRcD3vvc9CgsLOXHiRPu+o0ePkpuby9SpU89o++KLLxKLxdixYwcAX/rSlxg5ciQFBQUMHDiQm2++ma1bt57R5/nnn+ejH/0ohYWFDBkyhG9961tnjNWVyy+/nOeee67D3xobG5k7dy4lJSX07duXW2+9lXfeeadbx62srOT73/9+h79NnTqVWCzWvg0ePJjbbruNXbt2tbd57bXX+MxnPkNpaSkFBQWMGzeOxYsXn3Gctrl6/3bgwIFuZZQkSZIkSZ2zKBUBlZWVHD16lE2bNrXv+8UvfsGQIUPYsGEDjY2N7fvXrVvHpZdeysiRIwGYNGkSjz32GFu2bOFnP/sZ8Xic6dOn09LSAiSKNzfeeCPXX389VVVVrFq1iieffJK77rrrnLlef/11jhw5wpQpUzr8/etf/zo/+clP+Jd/+Rdeeukl9u3bx3/9r//1nMf9/e9/z69+9StuuummTtt84QtfYP/+/ezbt48f//jH1NTUcMcdd7T/vnnzZgYNGsSKFSv4zW9+w//8n/+TBQsW8OCDD551rG3btrF///72bdCgQefMKEmSJEmSuhaLx+PxoEOo94YNG8a8efPai0Xf+ta3OHbsGC+88AIPPfRQ+x1TU6ZM4fLLL2fZsmUdHuf1119n4sSJbN++nZEjR/IXf/EXrF27lo0bN7a3+clPfsLMmTM5ePAghYWFnWa65557+M1vfsPKlSvP+q2uro6BAwfygx/8gE9/+tMAbN26lXHjxrF+/XquueaaTo/7z//8z3z3u9/llVde6fD3qVOnUl5ezv3339++b8WKFXzpS1/i2LFjnR537ty5bNmyhRdeeAFI3ClVWVnJkSNH6NevX6f9JEmSJElS8rxTKiIqKytZt25d+7/XrVvH1KlTmTJlSvv+48ePs2HDBiorKzs8xrFjx3jssce4/PLLKS0tBaCpqYn8/Pwz2hUUFNDY2MjmzZu7zPTkk09y8803d/jb5s2baW5u5pOf/GT7vrFjx3LppZeyfv36Hh+3I7///e954oknmDx5cpft6urquPjii8/aX15eztChQ5k2bRq/+tWvuj2uJEmSJEnqnEWpiKisrORXv/oVJ06coKGhgaqqKqZMmcLHPvYxXnzxRQDWr19PU1PTWUWphx56iL59+9K3b1+eeeYZ1q5dywc+8AEArrvuOl5++WV++MMf0tLSwt69e/mbv/kbAPbv399pnr179/L6669zww03dPj7gQMH+MAHPnDWHUiDBw/u8p1NTU1NPPvss/yX//JfupyPtr+pT58+lJSUsG3bNh599NFO27/88susWrWKL37xi+37hg4dyve+9z3+7d/+jX/7t3+jtLSUqVOn8utf/7rLsSVJkiRJ0rlZlIqIqVOncuzYMTZu3MgvfvELxowZw8CBA5kyZUr7e6VefPFFrrjiCi699NIz+s6ePZuqqipeeuklxowZw8yZM9vfQzV9+nS+853v8OUvf5m8vDzGjBnDjTfeCEBWVueXz5NPPskf/uEfpvyxtxdeeIFBgwZx5ZVXdtlu9uzZVFdX89prr/HLX/6SUaNGMX36dBoaGs5q++abb3LzzTfzV3/1V0yfPr19f1lZGV/60peYNGkSH/3oR3n00Uf56Ec/yj/8wz+k9G+SJEmSJOlCZFEqIkaNGsXw4cNZt24d69ata3+5+LBhwygtLeXll19m3bp1fPzjHz+rb3FxMaNHj+ZjH/sY//qv/8rWrVtZvXp1++/f+MY3qK2tZffu3Rw6dKj90bkrrrii0zxPPvlkl3czDRkyhPfee4/a2toz9r/zzjsMGTKkx8c9/W8aNWoUo0aN4tprr2Xp0qW8/fbbrFq16ox2v/3tb/nEJz7BF7/4Rf7yL//ynMf98Ic/zPbt28/ZTpIkSZIkdc2iVIRUVlby4osv8uKLL7a/2BzgYx/7GM888wyvvvpqp++TahOPx4nH4zQ1NZ2xPxaLMWzYMAoKCvjhD39IaWkpH/rQhzo8xtGjR1m3bl2X732aNGkSubm5PP/88+37tm3bxu7du/nIRz7Sabaf/OQnSb1Pqk12djaQeK9Wm9/85jdUVlbyuc99jnvvvbdbx6murmbo0KFJjy9JkiRJks6UE3QApU5lZSVz586lubm5/U4pSHxx76tf/SrvvffeGUWp3/3ud6xatYrp06czcOBA9uzZw6JFiygoKGh/RA/gO9/5Dtdffz1ZWVn8+7//O4sWLeKJJ55oL/S837PPPsuYMWO47LLLOs1aXFzMn/zJn/CNb3yDiy++mKKiIu68804+8pGPdPrlvc2bN/Puu+/yh3/4h+eci3fffbf93VTvvPMO99xzD/n5+e2P57355pt8/OMf57rrruMb3/hGe9vs7GwGDhwIwP3338/ll1/OlVdeSWNjI9///vd54YUXWLNmzTnHlyRJkiRJXbMoFSGVlZUcP36csWPHMnjw4Pb9U6ZMoaGhgbKysjPu8snPz+cXv/gF999/P0eOHGHw4MF87GMf4+WXX2bQoEHt7Z555hnuvfdempqamDhxIj/+8Y87fYE5wI9//ONuPWL3D//wD2RlZXHrrbfS1NTEddddx0MPPdTlcW+88UZycs592T7yyCM88sgjAPTv358JEybw9NNPU1ZWBsC//uu/8p//+Z+sWLGCFStWtPcbMWIEO3fuBOC9997jz//8z9m7dy8XXXQREyZM4Lnnnjvn3WaSJEmSJOncYvF4PB50CEXHiRMnGDx4MM888wwf/vCHU3rsCRMm8Jd/+ZfMnDkzpceVJEmSJEnp5zullFK///3v+frXv87VV1+d0uO+99573HrrrV3eoSVJkiRJkjKHd0pJkiRJkiQp7bxTSpIkSZIkSWlnUUqSJEmSJElpZ1FKkiRJkiRJaWdRSpIkSZIkSWlnUUqSJEmSJElpZ1FKkiRJkiRJaWdRSpIkSZIkSWlnUUqSJEmSJElpZ1FKkiRJkiRJaff/Ac/UPj3W4U1uAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_unique_bords = drop_duplicate_boards(_board_history[:, 0].reshape(-1, 8, 8), None)\n", + "plot_othello_boards(_unique_bords[0], None)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "rewords\n", "evaluate_boards(boards).shape" -- 2.49.0