From 126e3d4c856f36f05f6bc3bcaaa236c85175e1eb Mon Sep 17 00:00:00 2001 From: Cai Wingfield Date: Thu, 16 Nov 2023 16:39:41 +0000 Subject: [PATCH 1/6] Simplify loading ExpressionSet from SampleDataset --- demos/demo_plotting.ipynb | 4 +--- kymata/entities/expression.py | 5 +++++ kymata/plot/plotting.py | 5 ++--- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/demos/demo_plotting.ipynb b/demos/demo_plotting.ipynb index 8d06c725..e7767223 100644 --- a/demos/demo_plotting.ipynb +++ b/demos/demo_plotting.ipynb @@ -82,9 +82,7 @@ "sample_data_dir = Path(Path(path.abspath(\"\")).parent, \"data\", \"sample-data\")\n", "\n", "# create new expression set object and add to it\n", - "# Download sample dataset\n", - "dataset_q3_2023 = get_dataset_kymata_mirror_q3_2023()\n", - "expression_data_kymata_mirror = ExpressionSet.load(from_path_or_file=Path(dataset_q3_2023.path, dataset_q3_2023.filenames[0]))\n", + "expression_data_kymata_mirror = ExpressionSet.from_sample_dataset(get_dataset_kymata_mirror_q3_2023())\n", "\n", "# print the names of all available functions in the expressionSet object\n", "print(\"\\n\".join(expression_data_kymata_mirror.functions))" diff --git a/kymata/entities/expression.py b/kymata/entities/expression.py index 0085404c..ee5a9964 100644 --- a/kymata/entities/expression.py +++ b/kymata/entities/expression.py @@ -16,6 +16,7 @@ from xarray import DataArray, Dataset, concat from pandas import DataFrame +from kymata.datasets.sample import SampleDataset from kymata.entities.sparse_data import expand_dims, minimise_pmatrix, densify_dataset from kymata.io.file import open_or_use, file_type, path_type @@ -286,6 +287,10 @@ def load(cls, from_path_or_file: path_type | file_type) -> ExpressionSet: data_rh=[right_sparse[:, :, i] for i in range(len(functions))], ) + @classmethod + def from_sample_dataset(cls, sample_dataset: SampleDataset) -> ExpressionSet: + return cls.load(from_path_or_file=Path(sample_dataset.path, sample_dataset.filenames[0])) + def best_functions(self) -> Tuple[DataFrame, DataFrame]: """ Return a pair of DataFrames (left, right), containing: diff --git a/kymata/plot/plotting.py b/kymata/plot/plotting.py index f11b5e61..e78e2c5a 100644 --- a/kymata/plot/plotting.py +++ b/kymata/plot/plotting.py @@ -190,7 +190,6 @@ def _get_yticks(ylim): sample_data_dir = Path(Path(path.abspath("")).parent.parent, "data", "sample-data") # create new expression set object and add to it - dataset_q3_2023 = get_dataset_kymata_mirror_q3_2023() - expression_data_kymata_mirror = ExpressionSet.load(from_path_or_file=Path(dataset_q3_2023.path, dataset_q3_2023.filenames[0])) + expression_data_kymata_mirror = ExpressionSet.from_sample_dataset(get_dataset_kymata_mirror_q3_2023()) - expression_plot(expression_data_kymata_mirror, save_to=Path("/Users/cai/Desktop/temp.png"), ylim=1e-172) + expression_plot(expression_data_kymata_mirror, show_only=expression_data_kymata_mirror.functions[1:], save_to=Path("/Users/cai/Desktop/temp.png")) From 12d9dd8d0ed0b4c702cd525a87de263b84ffe994 Mon Sep 17 00:00:00 2001 From: Cai Wingfield Date: Thu, 16 Nov 2023 17:48:27 +0000 Subject: [PATCH 2/6] Rewrite individual `SampleDataset`s as subclasses so they can decide themselves how to produce `ExpressionSets` --- demos/demo_ippm.ipynb | 47 ++++----- demos/demo_plotting.ipynb | 38 ++++---- demos/demo_save_load.ipynb | 51 ++++------ kymata/datasets/sample.py | 173 +++++++++++++++++++--------------- kymata/entities/expression.py | 5 - kymata/plot/plotting.py | 4 +- tests/test_datasets.py | 8 +- 7 files changed, 167 insertions(+), 159 deletions(-) diff --git a/demos/demo_ippm.ipynb b/demos/demo_ippm.ipynb index 86f2d412..ba91c6bb 100644 --- a/demos/demo_ippm.ipynb +++ b/demos/demo_ippm.ipynb @@ -26,15 +26,13 @@ "id": "9f56a8c5", "metadata": { "ExecuteTime": { - "end_time": "2023-11-03T16:22:14.402460Z", - "start_time": "2023-11-03T16:22:12.702099Z" + "end_time": "2023-11-16T17:43:28.916639Z", + "start_time": "2023-11-16T17:43:26.078088Z" } }, "outputs": [], "source": [ - "from os import path\n", - "from pathlib import Path\n", - "\n", + "from kymata.datasets.sample import KymataMirror2023Q3Dataset\n", "from kymata.entities.expression import ExpressionSet\n", "from kymata.ippm.builder import IPPMBuilder\n", "from kymata.ippm.data_tools import stem_plot, build_hexel_dict_from_expression_set\n", @@ -45,18 +43,25 @@ { "cell_type": "code", "execution_count": 2, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading dataset: kymata_mirror_Q3_2023\n", + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n" + ] + } + ], "source": [ - "sample_data_dir = Path(Path(path.abspath(\"\")).parent, \"data\", \"sample-data\")\n", - "\n", - "expression_set = ExpressionSet.load(from_path_or_file=Path(sample_data_dir, \"kymata_mirror_Q3_2023_expression_endtable.nkg\"))\n", + "expression_set: ExpressionSet = KymataMirror2023Q3Dataset().to_expressionset()\n", "hexels = build_hexel_dict_from_expression_set(expression_set)" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-03T16:22:22.473132Z", - "start_time": "2023-11-03T16:22:14.401830Z" + "end_time": "2023-11-16T17:43:36.201160Z", + "start_time": "2023-11-16T17:43:28.920003Z" } }, "id": "f1e6853801ccb49b" @@ -77,8 +82,8 @@ "id": "f6b85f98", "metadata": { "ExecuteTime": { - "end_time": "2023-11-03T16:22:26.255159Z", - "start_time": "2023-11-03T16:22:22.473671Z" + "end_time": "2023-11-16T17:43:39.814255Z", + "start_time": "2023-11-16T17:43:36.202129Z" } }, "outputs": [ @@ -112,8 +117,8 @@ "metadata": { "scrolled": false, "ExecuteTime": { - "end_time": "2023-11-03T16:22:30.281115Z", - "start_time": "2023-11-03T16:22:26.291633Z" + "end_time": "2023-11-16T17:43:43.852694Z", + "start_time": "2023-11-16T17:43:39.817178Z" } }, "outputs": [ @@ -193,15 +198,15 @@ "metadata": { "scrolled": false, "ExecuteTime": { - "end_time": "2023-11-03T16:22:30.506083Z", - "start_time": "2023-11-03T16:22:30.283619Z" + "end_time": "2023-11-16T17:43:44.063457Z", + "start_time": "2023-11-16T17:43:43.854749Z" } }, "outputs": [ { "data": { "text/plain": "
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cxyGrteTdq95P/gYOHIhKpWLt2rUPzivLREREMHTo0CpbayMsLIx169YRERHB8ePHcXd3JygoiJSUlArX8dtvvzFt2jRmzZrF0aNHcXJy4ocffihRLioqiri4OKKiooiIiCA8PJzw8HDd/rFjx3LgwAFWr17NqVOneP311+nevTsXL14EYMyYMahUKvbs2cPp06f58ssvdSvJT5kyhXPnzrF161ZiY2NZtGgRderUKbPNe/fupU2bNnrbKlLHJ598QmhoKCdOnMDDw4MBAwagVqsBOHbsGG+88QZvvvkmp0+fZtq0aUyZMkXvGgHmzZuHj48Pf/31F1OmTOHw4cMA7Nq1i6SkJNavX19qmxcsWECHDh0YMWKErvfP2dmZtLQ0XnzxRXx9fTl69Cjbtm3j1q1bvPHGG3rHR0REYGRkRExMDD/++KNu+7Rp01i4cCH79+/n6tWrvPHGG8yfP59Vq1axefNmduzYwffff69XV7t27Th8+DAqlarMeywI1UWjyufa5lNQldMlZZncW+ncOXylCisVBEF4+mhU+dzac/6JnOvm7vMFvUY1pNakl9ZW8U3W5lXvN83Ozo5XXnmFpUuXMnjwYKAgUIiPjyckJKRKzpGVlcWiRYsIDw+nR48eACxevJidO3eyZMkSJk6cWKF65s+fz/Dhw3XDwGbOnMmuXbtK9OrY2tqycOFClEolzZs3p1evXkRGRjJixAgSExNZtmwZiYmJ1K9fH4DQ0FC2bdvGsmXLmDVrFomJifTr1w9vb28A3NzcdHUnJibi6+uLn58fwEPn3SQkJOjOU5k6QkND6dWrFwDTp0/Hy8uLS5cu0bx5c7755hsCAwOZMmUKAB4eHpw7d46vvvqKoUOH6up48cUXmTBhgu7rwqDV3t4eR0fHMttsbW2NkZERZmZmeuUWLlyIr68vs2bN0m1bunQpzs7OXLhwAQ8PDwCaNm3K3LlzdWWSkpKAgu9XQEAAAMOHD2fy5MnExcXp7u9rr71GVFQUkyZN0h1bv3598vLyuHnzJo0aNSqzzYJQHe4eS0CdrXr04WrluL3vInatXFCaGFZ95YIgCE+BtDPXq+zD/4eR8zWknbuOvW/NPCvUmh4dRRWv2qowqv4YcdiwYezZs4e4uDig4OG1S5cuuLu7V0n9cXFx5Ofn6x5yAQwNDWnXrh2xsbEVric2NhZ/f3+9bR06dChRzsvLS68nysnJidu3bwNw+vRpNBoNHh4eWFhY6F67d+/WXf+4ceN0D+WfffYZp06d0tU1evRoVq9eTatWrQgLC2P//v3ltjknJ6dEGt+K1NGyZUu99gO6a4iNjdW7lwABAQFcvHgRjeZBpr/CQKo8e/fu1bsPK1euLLPsyZMniYqK0ivfvHlzAN29A0r0YJV2TfXq1cPMzEwviKxXr57uGguZmpoClBjSJgjVTdZqSTkeXy1BDoCs0ZJ65lr1VC4IglDDZFnm7rEnO5zs7tH4J3q+oiod6OzZs4fg4GDq16+PJEls3LjxocdER0fTunVrjI2NcXd3LzGU50kwsjZDMqiauE4yUGBkbVYldZUnMDAQFxcXwsPDSU9PZ/369U988rxCoSgxkazovJrKMDTU/4RUkiS098fDZ2ZmolQqOXbsGCdOnNC9YmNjWbBgAQDvvPMOly9fZtCgQZw+fRo/Pz/dkKoePXqQkJDABx98wI0bNwgMDCQ0NLTMttSpU4fUVP05WxWpo+g1FM5T0lZyTL+5uflDy/j5+endh5dffrnMspmZmQQHB+uVP3HiBBcvXqRz584PPW/xayrv+1SocGijg4NYg0R4sjIT7qLOqt4kHqknrlZr/YIgCDVFnZFLXmrWEz1nXkoW+Zk1M9S90t0SWVlZ+Pj4MGzYMF2K4/JcuXKFXr16MWrUKFauXElkZCTvvPMOTk5OBAUFPVKjH4WkkDBrYEtWwt3HrsusoR2SovrX0lEoFISEhLBkyRIaNGiAkZERr732WpXV36RJE92cjcLhR/n5+Rw5ckSXwtjBwYGMjAyysrJ0D8rF0yB7enpy6NAh3RA7oMzU2GXx9fVFo9Fw+/ZtOnXqVGY5Z2dnRo0axahRo5g8eTKLFy/mvffe07V1yJAhDBkyhE6dOjFx4kTmzZtX5vlKyxpWmTqK8/T0JCYmRm9bTEwMHh4e5c6pMjIyAtDr9TE1NS21587IyEivHEDr1q1Zt24drq6uGBg8mdGoZ86coWHDhuXOgxKE6pBzI01/1e5qoLqbSd69bBSGT8/q3oIgCFUhM/Hxn4MfRe6texha1H3i5630U1GPHj108zkq4scff6Rx48a67FOenp7s27ePb7/99okGOrJWi52vS5UEOnatXJA12sdKMV1RISEhzJgxg48//pgBAwbohgwVde/evRLBh729Pc7OzuXWbW5uzujRo5k4cSJ2dna4uLgwd+5csrOzdT1H/v7+mJmZ8fHHHzNu3DgOHTpUokfu/fffZ+jQofj5+REQEMDKlSs5e/as3vCnh/Hw8GDgwIEMHjyYr7/+Gl9fX5KTk4mMjKRly5b06tWL8ePH06NHDzw8PEhNTSUqKgpPT08Apk6dSps2bfDy8kKlUrFp0ybdvtIEBQUxefJkUlNTsbW1faQ6ipswYQJt27bl888/p3///hw4cICFCxeWmpihqLp162Jqasq2bdto2LAhJiYmWFtbl1rW1dWVQ4cOER8fj4WFBXZ2dowZM4bFixczYMAAwsLCsLOz49KlS6xevZr//Oc/VZa4oqi9e/fy0ksvVXm9gvAwOTfvUW3j1oq48GN0tZ9DEAShVpAkcm7ew7LJkw90qv1J/cCBA3Tr1k1vW1BQUIm0vNVNUiiw8nDE1LH0B8iKMnW0xsqj3hMJcgBcXFzo1q0bqampDBs2rNQy0dHR+Pr66r2mT59eofrnzJlDv379GDRoEK1bt+bSpUts375d9/BvZ2fHihUr2LJlC97e3vz6669MmzZNr47+/fszZcoUwsLCaNOmDQkJCYwePbrS17ps2TIGDx7MhAkTaNasGX379uXIkSO4uLgABT0eY8aMwdPTk+7du+Ph4aELIoyMjJg8eTItW7akc+fOKJXKctMfe3t707p1a3777TfdtsrWUVxhfatXr+a5555j6tSpzJgxQy8RQWkMDAz47rvv+Omnn6hfvz59+vQps2xoaChKpZIWLVrg4OCgS94QExODRqPhpZdewtvbm/Hjx2NjY4NCUfXv09zcXDZu3MiIESOqvG5BeJi8ezlPIs4RBEEQqooEmpxHm/bw2KeWH2MlH0mS2LBhA3379i2zjIeHByEhIUyePFm3bcuWLfTq1Yvs7OxSeygqIzc3lytXrtC4ceMSk8uLk7Va8lKzuRQRg5yvKbdsaSRDJe5DAjCyNUOqhgdI4cnavHkzEydO5MyZM9USEDyrFi1axIYNG9ixY0dNN+WZUZnfY7XdxSV7UN3JrOlmCIIgCBWlkLBr5UL9f3k9+VM/8TPWIEmhwMjWnEb92iBVcuy1ZKikUb82GNmaiyDnGdGrVy9GjhzJ9evXa7op/yiGhoYl1tURhCelqjNoCoIgCNVPYVAzcx6r/S+Go6Mjt27d0tt269YtrKysHrs351FICglzZ3vchwRwbdPJ++O9y2fqaE3D3j73g5zqT0IgPDmFSReEinvnnXdquglCLWZa16pgNW9t9Y5fq/dCMwxMCxKFPBj3IBcMm7v/dcH2gm2yVgZZLtglywVfa2XQapG1MrJWi6wpGFkgq7VoNZqCf9VaZLUGbZ4abb4aTa4GjSr/kUYdFDJraEu9F5pjbFP92UEFQfhnSTtznZtRfz/Zk2pljO0fnnG2OlR7oNOhQwe2bNmit23nzp2lrrPypEgKCSNbM9wGP0/6hVuk/JVA9vVUvcWTJAMFZg3tsGvlgpVHPZBlEeQIgiDUMFNHa/grsVrPoTA2oE5bN10K+Zoga7Soc/JQZ6lQZ6rIu5dNXloOqruZ5CZnoM7ILfPY7GupJKw5TIOeLbFu5vQEWy0IwtPO3MW+Rs5r8phz5B9VpQOdzMxMLl26pPv6ypUrnDhxQpe1a/LkyVy/fp1ffvkFgFGjRrFw4ULCwsIYNmwY//vf//jtt9/YvHlz1V3FIygcfmbVtC7WzRyRtTKaPHXBJ3AKCaWRAZJCKsiuJkkF6UwFQRCEGmXR2AEkqi8hgSRh1bRejQY5AJJSgaGFCYYWJlCv5P78zFyyr6aScfk26Rduoc1T6+3X5mm4uvEvNN3V2PmUn4FTEITaw9jBEkmpQNZUbg3AxyEZKDCxt3hi5yuq0pNNjh49qsvsBfDhhx/i6+vL1KlTAUhKSiIx8cGnbY0bN2bz5s3s3LkTHx8fvv76a/7zn/880dTS5ZELF0KUteTevEnm5cvk3rwJcsF2WX5ybwRBEAShfIaWJlg1rVd9Hz7JMvatG1VP3VXI0MIEa08nGvbyofnYQOoHPYeBRclEFje2nSb90q1SahAEoTZSKBVYe9WHJzVKSZKwea7BE8tWXOL0j5N17WnwqNmKtGoNkkIiaVsU8SvWk3L0JFrVg1VbFcbG2Pn54Pr2qzh1fwFZK9fYRCpBEJ5tIuta5WTfSOPy8v1VX7EkYdbABreBNTe0+nFoVGqSdp0l7Yx+ghWFsQHuQztiJObsCIJAwXpkcRExDy9YRZqEdMS0rtUTO19RtTJ9mKzRkJ1wjT0vD+Xo6I+4E3NYL8gB0KpU3Ik5zNHRH7G3TwjZCdeQNY8+OVQQBEGoGmb1bbBv41owhK0KSQqJBj1bVm2lT5DS2IAGPVtSp30Tve1alZrrW0/zD/9cUxCEKmLqaI15I/vqn5YhSVi41qmxIAdqYaAjazTcOXic3b3e5t7p2Aodk3bqHLt7vc2dg8dFsCMIgvAUqNelGca25lX6h9qpW4uCOv/BJEmiXmcPrFvU19uelXiXe+du1FCrBEF42jTo4Y2krN5AR1IqqN/Du1rP8TC1KtDRqjVkxV/j8PAP0eSUnbGmNJqcXA4P/5Cs+Gto1eqHHyAIgiBUG4WhEtc3/TG0Nq2SYKduJw/sWrlUQctqniRJ1H/pOQyt9IdB3ow+j/Yx0lYLgvDsMLI2wymwRbWew6lbC4ysnvxSMkXVqkBHUkgce39KpYOcQpqcXI6Pn/qPXjB06NCh9O3bt9rPM23aNFq1alXt53kcd+/epW7dusTHxwMQHR2NJEmkpaXVaLsEaN++PevWravpZghPOUNLE5q83QFzF7tHq0CSkAwU1O/uTd3n3au2cTVMaWyAU7FVyNWZudw9nlBDLRIE4Wlj6+OMfdvG1VJ3HX+3pyLj4z/3ib2StGo1SduiKjxcrSxpp86RtCP6sXp1JEkq9xUcHIwkSRw8eLDU4wMDA3n11VeBJxe4PIu++OIL+vTpg6urKwDPP/88SUlJWFtXTa736gz2nvXv+6effspHH32EViuyHgrlMzA3xrV/O+p390ZhfH/FhId18NzvATJ3tqPp8M5PxR/j6mDZpG7BOPwi7hy6XCIVtSAItZMkSTi+0Jw67d2qtF6HDk2o16VZldb5qGpNoKMwMCB+xfoqqSth+ToUBo++1mpSUpLuNX/+fKysrPS2/frrr/j4+LB06dISx8bHxxMVFcXw4cMf5xJqvezsbJYsWaJ3H42MjHB0dKzx9TME6NGjBxkZGWzdurWmmyL8A0iShJ2PM83HBNKgV0vM6tuWmcrUwNwYOx9n3EM60niA/zOdiaxgvo7+w4YmJ4+UU1drqEWCIDxtJEnCsUtzXF5pjdLU8NGTvEigNDXC5dU21Ovc7Kl5lqo1gY6s0ZBy9GSV1JVy9ORjJSVwdHTUvaytrQveZEW2WVhYMHz4cNasWUN2drbeseHh4Tg5OdG9e/fHvQwAVCoV48aNo27dupiYmNCxY0eOHDmidz4bGxu9YzZu3FjiDTxnzhzq1auHpaUlw4cPJzdXf3hgYQ/EvHnzcHJywt7enjFjxpCfn6/XltDQUBo0aIC5uTn+/v5ER0fr9ickJBAcHIytrS3m5uZ4eXmxZcsWAFJTUxk4cCAODg6YmprStGlTli1bVuZ1b9myBWNjY9q3b6/bVnzoWuG1b9++HU9PTywsLOjevTtJSUl6x7Rr1w5zc3NsbGwICAggISGB8PBwpk+fzsmTJ3U9deHh4QB88803eHt7Y25ujrOzM++++y6ZmZkl7nlZ5502bRoRERH8/vvvuroL79OkSZPw8PDAzMwMNzc3pkyZonePC3uZli9fjqurK9bW1rz55ptkZGToymi1WmbPnk3jxo0xNTXFx8eHtWvX6t2/3bt3065dO4yNjXFycuKjjz5CXaSX09XVlfnz5+sd06pVK6ZNmwaALMtMmzYNFxcXjI2NqV+/PuPGjdOVVSqV9OzZk9WrV5f5PRSE4hSGSmyfa4jb2x1o8eFLuA/rRKPX2+LSrw2ub/rT/L1A3ZozJjWYBehJMqtvg4Wbg962u0fjH6whJwiCAFh5ONJ0RBdsWzpXes0bSanA1seZpiM6F6xz9hSpNYFO1tUbJVJIPypNroqsq9WbvWbgwIGoVCq9B0xZlomIiGDo0KEolVWzpk9YWBjr1q0jIiKC48eP4+7uTlBQECkpKRWu47fffmPatGnMmjWLo0eP4uTkxA8//FCiXFRUFHFxcURFRREREUF4eLju4R9g7NixHDhwgNWrV3Pq1Clef/11unfvzsWLFwEYM2YMKpWKPXv2cPr0ab788kssLApW2p0yZQrnzp1j69atxMbGsmjRIurUqVNmm/fu3UubNm0eem3Z2dnMmzeP5cuXs2fPHhITEwkNDQVArVbTt29funTpwqlTpzhw4AAjR45EkiT69+/PhAkT8PLy0vXU9e/fHwCFQsF3333H2bNniYiI4H//+x9hYWEVPm9oaChvvPGGLvhJSkri+eefB8DS0pLw8HDOnTvHggULWLx4Md9++61e3XFxcWzcuJFNmzaxadMmdu/ezZw5c3T7Z8+ezS+//MKPP/7I2bNn+eCDD3j77bfZvXs3ANevX6dnz560bduWkydPsmjRIpYsWcLMmTMfej8LrVu3jm+//ZaffvqJixcvsnHjRry99TOztGvXjr1791a4TkEoSlIoMHGwxNLNASv3elg0ssfAzLimm1UjHIqlm86/l0P6xds11BpBEJ5WBqZGNOjuTfOxgTi+6IlpfZsygx5JqcC0vg2OgZ40HxtIgyBvDEyNnnCLH+7Rx1/9w6gzs6q0Pk1W9sMLPQY7OzteeeUVli5dyuDBg4GCQCE+Pp6QkJAqOUdWVhaLFi0iPDycHj16ALB48WJ27tzJkiVLmDhxYoXqmT9/PsOHD9cNA5s5cya7du0q0atja2vLwoULUSqVNG/enF69ehEZGcmIESNITExk2bJlJCYmUr9+QVrU0NBQtm3bxrJly5g1axaJiYn069dP90Ds5vZgTGliYiK+vr74+fkB6ObdlCUhIUF3nvLk5+fz448/0qRJwYPC2LFjmTFjBgDp6encu3eP3r176/Z7enrqjrWwsMDAwABHR0e9OsePH6/7v6urKzNnzmTUqFF6wWF557WwsMDU1BSVSlWi7k8//VSv7tDQUFavXq0XSGm1WsLDw7G0tARg0KBBREZG8sUXX6BSqZg1axa7du2iQ4eCRRPd3NzYt28fP/30E126dOGHH37A2dmZhQsXIkkSzZs358aNG0yaNImpU6eiqECyjsTERBwdHenWrRuGhoa4uLjQrl07vTL169fn6tWraLXaCtUpCELpzBraYupkTU7SPd22lOPxWDdzLOcoQRBqK6WJIXXaNqZO28bIWhnV3UzyM3KRNVokpQJDKxOM7SyQFE/H8LTy1JqnBwOLql0bQWle/eO6hw0bxp49e4iLiwNg6dKldOnSBXf3qskOFBcXR35+PgEBAbpthoaGtGvXjtjYiidtiI2Nxd/fX29b4UNyUV5eXno9UU5OTty+XfCp4unTp9FoNHh4eGBhYaF77d69W3f948aNY+bMmQQEBPDZZ59x6tQpXV2jR49m9erVtGrVirCwMPbvL3/V9JycnAqtQG9mZqYLNoq32c7OjqFDhxIUFERwcDALFizQG9ZWll27dhEYGEiDBg2wtLRk0KBB3L17V2+YYnnnLc+aNWsICAjQDYH89NNPSUxM1Cvj6uqqC3KK133p0iWys7P517/+pfd9+OWXX3Tfh9jYWDp06KA3fDEgIIDMzEyuXbv20DYCvP766+Tk5ODm5saIESPYsGGD3tA3AFNTU7RaLaoq6okVhNpKkqSCBVaLyEpMQXU3s/QDBEEQ7pMU0oPe8ab1sHRzwKSO5T8iyIFaFOiYO9dHYVw1wxaUJsaYOz+8N+BxBQYG4uLiQnh4OOnp6axfv/6JJyFQKBQlVtMuOuejMgwNDfW+liRJl1UrMzMTpVLJsWPHOHHihO4VGxvLggULAHjnnXe4fPkygwYN4vTp0/j5+fH9998DBZPXExIS+OCDD7hx4waBgYG6oV6lqVOnDqmpqY/U5qL3Y9myZRw4cIDnn3+eNWvW4OHhUWa2PChIJtG7d29atmzJunXrOHbsGP/3f/8HQF5eXoXPW5oDBw4wcOBAevbsyaZNm/jrr7/45JNP9Ootq+6i3weAzZs3630fzp07V2KeTnke9r5xdnbm/Pnz/PDDD5iamvLuu+/SuXNnvTIpKSmYm5tjalqzOfgF4Vlg1cwRpZn+sJKUE4lllBYEQXg21JpAR1IqsfPzqZK67Px8kKpojkx5FAoFISEhREREsGrVKoyMjHjttdeqrP4mTZpgZGRETEyMblt+fj5HjhyhRYuCRaQcHBzIyMggK+vB0L8TJ07o1ePp6cmhQ4f0tpX3sF8aX19fNBoNt2/fxt3dXe9VdHiWs7Mzo0aNYv369UyYMIHFixfr9jk4ODBkyBBWrFjB/Pnz+fnnn8s937lz5yrVxvLqmjx5Mvv37+e5555j1apVQEEWN02xpBXHjh1Dq9Xy9ddf0759ezw8PLhxo/LzvUqre//+/TRq1IhPPvkEPz8/mjZtSkJC5dbMaNGiBcbGxiQmJpb4Pjg7F6Tg9fT05MCBA3qBTExMDJaWljRs2BAo+F4U7d1KT0/nypUreucyNTUlODiY7777jujoaA4cOMDp06d1+8+cOYOvr2+l2i8IQukUBkpsvRvqbUs7cx2tWiwgKgjCs6vWBDpatRrXt1+tkroaDer3WOvoVEZISAjXr1/n448/ZsCAAaV+un3v3j29T99PnDjB1asPTx9qbm7O6NGjmThxItu2bePcuXOMGDGC7OxsXc+Rv78/ZmZmfPzxx8TFxbFq1Sq9BAIA77//PkuXLmXZsmVcuHCBzz77jLNnz1bqOj08PBg4cCCDBw9m/fr1XLlyhcOHDzN79mw2b94MFMxt2b59O1euXOH48eNERUXp5sRMnTqV33//nUuXLnH27Fk2bdqkN1+muKCgIM6ePVuhXp2yXLlyhcmTJ3PgwAESEhLYsWMHFy9e1J3X1dWVK1eucOLECe7cuYNKpcLd3Z38/Hy+//57Ll++zPLly/nxxx8rfW5XV1dOnTrF+fPnuXPnDvn5+TRt2pTExERWr15NXFwc3333HRs2bKhUvZaWloSGhvLBBx8QERFBXFwcx48f5/vvvyciIgKAd999l6tXr/Lee+/x999/8/vvv/PZZ5/x4Ycf6ubSvPjiiyxfvpy9e/dy+vRphgwZojdsMTw8nCVLlnDmzBkuX77MihUrMDU1pVGjRroye/fu5aWXXqr0vREEoXS2LfXXC9Lk5pMhkhIIgvAMqzWBjsLAAKfuL2DTssVj1WPTsgVOL3V9rHV0KsPFxYVu3bqRmprKsGHDSi0THR2Nr6+v3mv69OkVqn/OnDn069ePQYMG0bp1ay5dusT27duxtbUFCuahrFixgi1btuDt7c2vv/6qSxFcqH///kyZMoWwsDDatGlDQkICo0ePrvS1Llu2jMGDBzNhwgSaNWtG3759OXLkCC4uLgBoNBrGjBmDp6cn3bt3x8PDQzeB38jIiMmTJ9OyZUs6d+6MUqksNzWxt7c3rVu35rfffqt0OwuZmZnx999/069fPzw8PBg5ciRjxozh3//+NwD9+vWje/fuvPDCCzg4OOjWR/rmm2/48ssvee6551i5ciWzZ8+u9LlHjBhBs2bN8PPzw8HBgZiYGF5++WU++OADxo4dS6tWrdi/fz9TpkypdN2ff/45U6ZMYfbs2bp7vXnzZho3Llg9uUGDBmzZsoXDhw/j4+PDqFGjGD58uF4ihMmTJ9OlSxd69+5Nr1696Nu3r96cIxsbGxYvXkxAQAAtW7Zk165d/Pnnn9jbFyxueP36dfbv319liTcEQQBjO3PMXez0tqWerti8OkEQhH8iSX7YwP+nXG5uLleuXKFx48YPnVyuVWvITrjG7l5vo8nJLbdsaZSmJnTZvAKzRg2eWKAjVJ/NmzczceJEzpw5I7J6PWUmTZpEampqucMPnyWV+T0mCI8j9cw1rm9+kMgFCZqNfhFDS/G+EwTh2VOrnu4UBkrMXRvSbsk3KE0r90tdaWpCuyXfYO7aUAQ5z4hevXoxcuRIrl+/XtNNEYqpW7cun3/+eU03QxCeOdYejiiMiswxlSHtXPWuCycIglBTalWPTiFZoyEr/hrHx08l7dTDJ6TbtGxB6/kzMHdt+ESSEAiCULuIHh3hSbq2+SRpZx58wGPsYEnTYZ1qsEWCIAjVo1Z2TUhKJWaNGtDp92UkbY8mfvk6Uo6eRFtkvQ6liTF2fj40GtQPp5e6Imu1IsgRBEEQ/vFsnmuoF+iokjPIuZ2OaV2rGmyVIAhC1auVgQ6gG37m+K/O1O/xIrJWS35mFmg0oFRiaGGOpFCgVauRFAokMYdDEARBeAaYu9hhaGlCfsaDuar3zl4XgY4gCM8c8fQuF/TSyLJE7m1TMq6Yk3vbFFmW9PYLgiAIwrNAkiSsvfQXvU47dwNZ+48eyS4IglBCre3R0aplJAVc/UPFhR9zSI7JR1MkEZvSBBwCDPEYZYrLK8bIWlAYSDXXYEEQBEGoIjYtGnDn4GXd1+pMFVmJd7FwrVODrRIEQahatTLQ0WpkMuI07Hs7nZRjpS/8qcmFm5H53IzMx97PgIDlVlg2UYpgRxAEQfjHM3GwxKSuFbm303Xb0s5eF4GOIAjPlFo3dE2rkbm1O58tbVLKDHKKu3tUzZY2Kdzak49WLbr2BUEQhH8+m2LD19Iv3ESbr6mh1giCIFS9WhXoaNUyGZc0RL+chjq7cseqsyH65TQy4jQi2BEEQRD+8aw960ORQQraPA3pF2/VXIMEQRCqWK0KdCQF7Hs7vdJBTiF1NsQMSkf6B9+1oUOH0rdv32o/z7Rp02jVqlW1n6c6xMfHI0kSJ06cqOmmVMqgQYOYNWuW7mtXV1fmz59fcw0SAPjxxx8JDg6u6WYIQgmGliaYN9IfqlY07bQgCMI/3T/4kb1ytPkyiRtUFR6uVpa7R9Vc3ahCm//ovTqSJJX7Cg4ORpIkDh48WOrxgYGBvPrqq8CTC1yEJ+Ps2bP069cPV1dXJEmqcKBy8uRJtmzZwrhx43Tbjhw5wsiRI6ukXdUZ/EVHRyNJEmlpaVVe99Ng2LBhHD9+nL1799Z0UwShBNvnGuh9nRmfrJd2WhAE4Z+s1gQ6CkOJCz/mVEldF37MQWH46EkJkpKSdK/58+djZWWlt+3XX3/Fx8eHpUuXljg2Pj6eqKgohg8f/jiXIDylsrOzcXNzY86cOTg6Olb4uO+//57XX38dCwsL3TYHBwfMzMyqo5lCJRgZGfHWW2/x3Xff1XRTBKEEq6b1UBgVWUZBhrRzoldHEIRnQ60JdLQameSY/Cqp63ZMPrLm0Xt0HB0ddS9ra2skSdLbZmFhwfDhw1mzZg3Z2frj7MLDw3FycqJ79+6PexkAqFQqxo0bR926dTExMaFjx44cOXJE73w2NjZ6x2zcuBFJ0g/05syZQ7169bC0tGT48OHk5up/IljY8zRv3jycnJywt7dnzJgx5Oc/+J6oVCpCQ0Np0KAB5ubm+Pv7Ex0drdufkJBAcHAwtra2mJub4+XlxZYtWwBITU1l4MCBODg4YGpqStOmTVm2bFmZ163Vapk7dy7u7u4YGxvj4uLCF198oVfm8uXLvPDCC5iZmeHj48OBAwd0++7evcuAAQNo0KABZmZmeHt78+uvv+od37VrV8aNG0dYWBh2dnY4Ojoybdq0MtsE0LZtW7766ivefPNNjI2Nyy1bSKPRsHbt2hLDo4oPXZMkif/85z+88sormJmZ0bRpU/744w/d/vLuYePGjQHw9fVFkiS6du0KFPQa/etf/6JOnTpYW1vTpUsXjh8/rteO8s4bHx/PCy+8AICtrS2SJDF06FAAtm3bRseOHbGxscHe3p7evXsTFxenq7ewl2n9+vVlfp8A9u3bR6dOnTA1NcXZ2Zlx48aRlZWld92DBw/G1tYWMzMzevTowcWLF3X7SxuGOX/+fFxdXXVfR0dH065dO8zNzbGxsSEgIICEhATd/uDgYP744w9ycqrmwxZBqCoKIwOsmjnpbUs9dQ1ZFnNRBUH456s1gU7mFY3eOjmPQ5MDGVeqNzPNwIEDUalUrF27VrdNlmUiIiIYOnQoSmXVLGQaFhbGunXriIiI4Pjx47i7uxMUFERKSkqF6/jtt9+YNm0as2bN4ujRozg5OfHDDz+UKBcVFUVcXBxRUVFEREQQHh5OeHi4bv/YsWM5cOAAq1ev5tSpU7z++ut0795d99A5ZswYVCoVe/bs4fTp03z55Ze6HowpU6Zw7tw5tm7dSmxsLIsWLaJOnbLTpE6ePJk5c+bojlu1ahX16tXTK/PJJ58QGhrKiRMn8PDwYMCAAajVBUMfc3NzadOmDZs3b+bMmTOMHDmSQYMGcfjwYb06IiIiMDc359ChQ8ydO5cZM2awc+fOCt/bijh16hT37t3Dz8/voWWnT5/OG2+8walTp+jZsycDBw7Ufa/Lu4eF17Vr1y6SkpJYv349ABkZGQwZMoR9+/Zx8OBBmjZtSs+ePcnIyKjQeZ2dnVm3bh0A58+fJykpiQULFgCQlZXFhx9+yNGjR4mMjEShUPDKK6+g1Wr16i7v+xQXF0f37t3p168fp06dYs2aNezbt4+xY8fqjh86dChHjx7ljz/+4MCBA8iyTM+ePfWC8PKo1Wr69u1Lly5dOHXqFAcOHGDkyJF6Hwb4+fmhVqs5dOhQheoUhCfJ1ruh3td5KVlkX0+todYIgiBUIfkfLicnRz537pyck5NTbrk7x/LkX6RbVfa6ezyvStq/bNky2drautR9b775ptylSxfd15GRkTIgX7x4UbdtyJAhcp8+fSp8vqLlMzMzZUNDQ3nlypW6/Xl5eXL9+vXluXPnltm+DRs2yEXfOh06dJDfffddvTL+/v6yj4+P3nkbNWokq9Vq3bbXX39d7t+/vyzLspyQkCArlUr5+vXrevUEBgbKkydPlmVZlr29veVp06aVel3BwcFySEhIBe6ALKenp8vGxsby4sWLS91/5coVGZD/85//6LadPXtWBuTY2Ngy6+3Vq5c8YcIE3dddunSRO3bsqFembdu28qRJkyrUzkaNGsnffvvtQ8tt2LBBViqVslarLfd4QP700091X2dmZsqAvHXrVlmWy7+Hhffkr7/+KrctGo1GtrS0lP/8888KnzcqKkoG5NTU1HLrTk5OlgH59OnTem0q7/s0fPhweeTIkXr17N27V1YoFHJOTo584cIFGZBjYmJ0++/cuSObmprKv/32myzLsvzZZ5/pvZdlWZa//fZbuVGjRrIsy/Ldu3dlQI6Oji63/ba2tnJ4eHip+yr6e0wQqoNWq5XP/xwtn56zWfe6+ueJmm6WIAjCY6s1PTqGVlW70KeBZfUvHDps2DD27NmjG66zdOlSunTpgru7e5XUHxcXR35+PgEBAbpthoaGtGvXjtjY2ArXExsbi7+/v962Dh06lCjn5eWl1xPl5OTE7du3ATh9+jQajQYPDw8sLCx0r927d+uuf9y4ccycOZOAgAA+++wzTp06patr9OjRrF69mlatWhEWFsb+/fvLba9KpSIwMLDc62rZsqVeWwFdezUaDZ9//jne3t7Y2dlhYWHB9u3bSUxMLLOO4tdcVXJycjA2Ni4xnLA0Rdtjbm6OlZWVrj2VuYeFbt26xYgRI2jatCnW1tZYWVmRmZlZ7n0oft6yXLx4kQEDBuDm5oaVlZVuqFh5dRf/Pp08eZLw8HC991RQUBBarZYrV64QGxuLgYGB3vvX3t6eZs2aVfhnwM7OjqFDhxIUFERwcDALFiwgKSmpRDlTU9MSQ1EF4WkgSRK2LfV7de79nYQ6J6+GWiQIglA1DGq6AU+KRWMlShOqZPia0hQsG1fN0LHyBAYG4uLiQnh4OBMnTmT9+vX89NNP1X7eohQKRYmx2hUd0lOcoaGh3teSJOmGIWVmZqJUKjl27FiJYXmFw9PeeecdgoKC2Lx5Mzt27GD27Nl8/fXXvPfee/To0YOEhAS2bNnCzp07CQwMZMyYMcybN69EO0xNTSvd3sIgorC9X331FQsWLGD+/Pl4e3tjbm7O+PHjycvLK7OO4tdcVerUqUN2djZ5eXkYGRmVW7a89lTmHhYaMmQId+/eZcGCBTRq1AhjY2M6dOhQJfchODiYRo0asXjxYurXr49Wq+W5554rt+7i36fMzEz+/e9/62WjK+Ti4qI3F6csFfkZWLZsGePGjWPbtm2sWbOGTz/9lJ07d9K+fXtdmZSUFBwcHB56PkGoCbbPNeT2ngvI2oL3uqzRknrqGg7+bmUek3v7DncPHSftVCxpJ8+Rc+Mmmrw8FAaGGNexxaZlC2y8PbFr64OFW6MndSmCIAg6taZHR6GUcAgwfHjBCqgbYIikrP4eHYVCQUhICBEREaxatQojIyNee+21Kqu/SZMmGBkZERMTo9uWn5/PkSNHaNGiBVCQuSsjI0Nv8nbxFMOenp4l5h6UlRq7LL6+vmg0Gm7fvo27u7veq2j2MWdnZ0aNGsX69euZMGECixcv1u1zcHBgyJAhrFixgvnz5/Pzzz+Xeq6mTZtiampKZGRkpdpYVExMDH369OHtt9/Gx8cHNzc3Lly48Mj1PY7CifLnzp177LrKuoeFAZRGoz83LSYmhnHjxtGzZ0+8vLwwNjbmzp07lTpnaXXfvXuX8+fP8+mnnxIYGIinpyepqZWfM9C6dWvOnTtX4j3l7u6OkZERnp6eJebOFJ676M/AzZs39YKd0tJs+/r6MnnyZPbv389zzz3HqlWrdPvi4uLIzc3F19e30tcgCE+CgbkxVs31kxKkHI9HLvaBhCzL3DlwjCOjwtjh34tjYz/h8tLV3D10nOyrN1DdukPO9STSTp4j4deNnAj7nP+98Br7Xh/Bjc270OY/3hIPgiAIlVFrenS0+TIeo0y5Gfn4mdc8RpmizZcfK8V0RYWEhDBjxgw+/vhjBgwYUGpvxL1790o8eNnb2+Ps7Fxu3ebm5owePZqJEydiZ2eHi4sLc+fOJTs7W5e+2t/fHzMzMz7++GPGjRvHoUOH9BIIALz//vsMHToUPz8/AgICWLlyJWfPnsXNrexPAovz8PBg4MCBDB48mK+//hpfX1+Sk5OJjIykZcuW9OrVi/Hjx9OjRw88PDxITU0lKioKT09PAKZOnUqbNm3w8vJCpVKxadMm3b7iTExMmDRpEmFhYRgZGREQEEBycjJnz56tcNrupk2bsnbtWvbv34+trS3ffPMNt27d0j0cP6q8vDxdwJKXl8f169c5ceIEFhYWZQ5ZdHBwoHXr1uzbt++xFmkt7x7WrVsXU1NTtm3bRsOGDTExMcHa2pqmTZuyfPly/Pz8SE9PZ+LEiRXuMSvUqFEjJEli06ZN9OzZE1NTU2xtbbG3t+fnn3/GycmJxMREPvroo0pf06RJk2jfvj1jx47lnXfewdzcnHPnzrFz504WLlxI06ZN6dOnDyNGjOCnn37C0tKSjz76iAYNGtCnTx+gIHtecnIyc+fO5bXXXmPbtm1s3boVKysrAK5cucLPP//Myy+/TP369Tl//jwXL15k8ODBunbs3bsXNzc3mjRpUulrEIQnxb51I+6du6H7Oj89l3t/38SmRX0AMuOvcmLCdFKOnkRSKuF+ECSrSw9eim5POXaKlMMnMG3oROv5M7Bv26r6LkQQBOG+2tOjYyjh8oox9n6PF9vZ+xng3Nf4iQQ5UDC8plu3bqSmpjJs2LBSy0RHR+Pr66v3mj59eoXqnzNnDv369WPQoEG0bt2aS5cusX37dmxtbYGC+QcrVqxgy5YtuhTKxVMk9+/fnylTphAWFkabNm1ISEhg9OjRlb7WZcuWMXjwYCZMmECzZs3o27cvR44cwcXFBSj4xH/MmDF4enrSvXt3PDw8dNndjIyMmDx5Mi1btqRz584olUpWr15d5rmmTJnChAkTmDp1Kp6envTv379Sc2c+/fRTWrduTVBQEF27dsXR0bFKFm69ceOG7nuYlJTEvHnz8PX15Z133in3uHfeeYeVK1c+1rnLu4cGBgZ89913/PTTT9SvX18XBCxZsoTU1FRat27NoEGDdKnKK6NBgwZMnz6djz76iHr16jF27FgUCgWrV6/m2LFjPPfcc3zwwQd89dVXlb6mli1bsnv3bi5cuECnTp3w9fVl6tSp1K9fX1dm2bJltGnTht69e9OhQwdkWWbLli26IXGenp788MMP/N///R8+Pj4cPnyY0NBQ3fFmZmb8/fff9OvXDw8PD0aOHMmYMWP497//rSvz66+/MmLEiEq3XxCeJNP6NpjWt9HbdudQHFqtlsvLVhP9r/6k/nUGAFlTycyjmoKgKOfGLWJeH8GZ6V+jyRULkwqCUL0kufjg83+Y3Nxcrly5QuPGjTExMSm3rFYtkxGnYUubFNSPMCfYwAx6HrPDsokShcGTCXQEoSJycnJo1qwZa9asKTURhFBzzp49y4svvsiFCxewtrYutUxlfo8JQnW6dz6Jqxv/0n0ta7XkJhwgaeuOqj2RQoFda2/8w+djaGnx8PKCIAiPoNb06AAoDCQsmyjp+ocNBpVcMN7ADLr+YSOCHOGpZGpqyi+//FLp+TFC9UtKSuKXX34pM8gRhKeJlYcjxvYFgYcsyyTv/rPqgxwArZbUv05zcNB7qHNEz44gCNWjVvXoFCrs2YkZlM7dow+fGGnvZ0DAcisR5NRysiyjzsgk714Gcr4aWatFUipQGBpiZGuN0sy0QimeBaE40aMjPE3Szt3g2p8nSDsRQ8r+aghyilIoqN+7G37ff1G95xEEoVaqNckIiirs2elx0JbEjSouLMohOSZfL/W00rQgu5rHKFOc+xojaxFBTi2lVavJS0lDdTcVOT8fJAmKfj4gSeSlpKIwMcbY3g4jW2skRa3qLBUE4Rli7enE9c0HSDm4q/pPptVy448dJPXqhlP3F6r/fIIg1Cq1MtCBB0GLc7AxjV41QdbK5KXLyGqQDMDISkJSSGjzZSSFhCSeW2sldU4uWVcSkdUa4H5wU7wT9P7X2tw8cq4nobqbgkVjFxSGVZPOXBAE4YmSZZIjN+h+5VU7SeLEpC+w9/fFyNbmCZ1UEITaQDy+3yfLoLqjJStRg+qOtsSzrFD7qLNzyIyLv59dqCJviPsBjyqPjEvxaPMeP5W5IAjCk3Y7+gDpsedBrtrFjcsky+SnZxC/fN2TOZ8gCLVGre3R0aplJAVc/UPFhR9LGbpmAg73h665vCKGrtU2mrw8sq4kFkTAlY16ZRlZrSbzSiKW7q4F600IgiD8Q1wOX4OkVFY+hfTj0Gq58st/cX93CAqDWvtoIghCFauVPTpazf000/6p7Hk9nZuR+kEOgCYXbkbms+f1dLa2TyUjToNWLbp5agvV7TsFK4I/ateeLKNV5aFKSavSdgmCIFSnrMTrJO85+GSDnPtUyXe5tWvvEz+vIAjPrloX6Gg1Mrd257OlTQopxx6ecQ3g7lE1W9qkcGtPvgh2agGtWkNe6r1HD3J0ZPLupvAPT2woCEItcifmcBX87ns0koGS23sP1ci5BUF4NtWqQEerlsm4pCH65bRKLxiqzobol9NEz04tkJeaVmWTcLV5+agzs6qmMkEQhGqWdvpvpBoaOiarNaT+daZGzi0IwrOpVg2ElRSw7+30Sgc5hdTZEDMonR4Hbau2YU/Q0KFDSUtLY+PGjdV6nmnTprFx40ZOnDhRreepDhdPnaFlt67sWbMW7+aej11f1pXEgpTUpZJA0v+/BAXlpYLMf0iKB/8qFUiK+18rCv9f8AoM7s3IYcMY0L8/KBQYWVqw7rff6NOnb8H6PmKKWY2Y/PHHZGVl8d2CBWWW0arVyBotean3kIxynmDrBEFfytGTyOqKjXaoDhkX4tDm5aMwElkrBUF4fLUm0NHmy1z9Q1Xh4WpluXtUzdWNKhoGG6MwfLQnx4ctKtm7d282bdrEgQMHaN++fYn9gYGBWFtbs379+icWuNQm1fJHvsyhILJe71HEuv+y+s8/iL10CYBWLVow5b33aePdstzqt0T/j1tJSfRu256s+KsA/B0ZjY2VNRl/X3zs5u87cpjgd0KI33sAayurx66vqFW/b2DyV1+SsO9gldb7tBjZqw++vYJ4p9fLuDZ0LrVMnqwl5/Zt9o2chPr6rSfcQkF4esj5alR3UzB1qlfTTREE4RlQa4auKQwlLvxYNZ+UXvgx55GDHICkpCTda/78+VhZWelt+/XXX/Hx8WHp0qUljo2PjycqKorhw4c/ziUIZZBlGbRPKKVqKfYdPUK/Hj358z9L2bF8JQ3qOfLq6JHcuFX+w+/Pq1byVp++KIosVFqvjgPGRkbV3WThIextbXnx+QCW/LamppsiCP8IGlVeTTdBEIRnRK0JdLQameSYqlnX5HZMPrLm0SdxODo66l7W1tZIkqS3zcLCguHDh7NmzRqys/XH2YWHh+Pk5ET37t0f9zIAUKlUjBs3jrp162JiYkLHjh05cuSI3vlsbGz0jtm4cWOJXqk5c+ZQr149LC0tGT58OLm5+mnshg4dSt++fZk3bx5OTk7Y29szZswY8vMffE9UKhWhoaE0aNAAc3Nz/P39iY6O1u1PSEggODgYW1tbzM3N8fLyYsuWLQCkpqYycOBAHBwcMDU1pWnTpixbtqzM69ZqtcydOxd3d3eMjY1xcXHhiy++KNh5/9rir10jePhQ6vu3oePrr3D45And8SlpaQyfFEqLbi9Q378Nz/fry9qtm/XO0Xv4UCbNmcXUb+fRuFMHmr3YmTmL/q/MNgEsnj2Xd/oPwLu5Jx6N3fhu2gxkrZY9h8vu7biTksKew4fo3kV/VXFbHy82/y8SgMTr17H18eLPXTvLvKbEGzd48713ce3YgQb+fnR45WV27N1D4vXrBL8TAoBrpw7Y+njx7pSPAdgVs5fuQ96mUcf2uHV+nv5j3+XK1cQHdT7kvPuOHGbM1E9Jz8jA1scLWx8v3T1a/ecfvDDgDZw7tKXZi51556OJJN+9q6t735HD2Pp4sfvQQV4Y8Ab1/dvw0uCBXIy/oncftkT9jy79X8OxrS+tegbx5Y8/oC7Sa3c16QZvvT+Whu39cHm+HSETP+T23Tu6/e9O+ZiB49/Tq3Py3Nn0Hj5U9/XvO7fzfL++OLVrjVvn5+k7cjhZRX52u3fpyvptW8v8HgqC8IBILy0IQlWpNYFO5hVNiRTSj0qTAxlXqjf15sCBA1GpVKxdu1a3TZZlIiIiGDp0KMoqWpslLCyMdevWERERwfHjx3F3dycoKIiUlJQK1/Hbb78xbdo0Zs2axdGjR3FycuKHH34oUS4qKoq4uDiioqKIiIggPDyc8PBw3f6xY8dy4MABVq9ezalTp3j99dfp3r07Fy8WDL0aM2YMKpWKPXv2cPr0ab788kssLCwAmDJlCufOnWPr1q3ExsayaNEi6tSpU2abJ0+ezJw5c3THrVq1inr16hUEcMqCH4uZC79j7JAQ9qxZh3sjV975aKLuATlXpaJVCy/WLPyB/es2MrTf64z6ZDLHTp/SO8+vf/6OuakZu1asZvoHE5j70yKiDuyv8L3Nzs0lX63Gxsq6zDIH/zqOmYkJzdzcHlpfedc0cdZM8vLy2bwsgph1G/hs/IeYm5nRwNGRX76eD8CR3zfzd2Q0s8MmF7QvJ4cxg4YQtWoNv/+8BIVC4u0P3kdbrFesrPO2a9WK2WEfYWlhwd+R0fwdGc3YIUMBUKvVfDzmPfb+dz0r5n9P4o0bvDv1k5LX9P0CZk6YyP9WrcFAqWTsZ5/q9u0/foxRn05m1MC3ObjhD76d8hmrft/I1//5GSgIeAe+/x6p9+6xaWkE63/8D/HXrjEsLPSh97LQzeRk3vkojLf7vsKhDX/y55Jwegd2Qy4yJrH1c97cuHWTxOvXK1yvINRWhtaWNd0EQRCeEbXmY5P89KrNlKbOqN7Ma3Z2drzyyissXbqUwYMHAwWBQnx8PCEhIVVyjqysLBYtWkR4eDg9evQAYPHixezcuZMlS5YwceLECtUzf/58hg8frhtON3PmTHbt2lWiV8fW1paFCxeiVCpp3rw5vXr1IjIykhEjRpCYmMiyZctITEykfv36AISGhrJt2zaWLVvGrFmzSExMpF+/fnh7ewPgVuTBPjExEV9fX/z8/ABwdXUts70ZGRksWLCAhQsXMmTIEACaNGlCx44dATC0LPgjO3bwUII6dwHgo9Fj6PBqHy5fTcSjsRv169XjvSEPvg8j3xpI5P4YNu7YrjefxqupB59Nm4aRnQ2+Pf7F0o3rORh3gT5FegP0yCDLWtDKaDUaJo0bh5OjEy/16oWhUok2Px9ZrUar0RYMsZNlribdwMG+jt6wtbKUd03Xbibxcrd/4dXUo+AeFplPYmtdEGg52NnpzdF5udtLevUvnD4T964d+TsuDq9mzTG0tQEg9KNJvD5sGAAzXRvi7ePDbSMFzZu3oO6JYyiUSpp2DtCr690WH+l9be3eGP8OHVC41MfCwgKz5CQAZs37isAXXwTgYwOJ4JdfxsjNBRMTE7754D0++ugj/j0pDICWQIaJIR9NnswX381n565dnLt0kbiLF3F2Lrje5S1b4O3jw/mse7Rt2xZDaysMkLFq4aFri5GdLQZmpli18ODS8UzUajUDRo2kUaNGAHTo01uv7R4NHQG4a6zkuSL1FMrNzcVUKdFx3RIx3FCoUScmzeRW5L4aG8Jr2sARQ0uLGjm3IAjPnloT6BhaVW3KKQPL6k9hNWzYMIKCgoiLi6NJkyYsXbqULl264O7uXiX1x8XFkZ+fT0DAgwdMQ0ND2rVrR2xsbIXriY2NZdSoUXrbOnToQFRUlN42Ly8vvZ4oJycnTp8+DcDp06fRaDR4eOg/BKpUKuzt7QEYN24co0ePZseOHXTr1o1+/frRsmVBUDF69Gj69evH8ePHeemll+jbty/PP/98me1VqVQEBgaWut/ItuBB3qtIWxwdHABITknBo7EbGo2Gb/7zMxt2bCfp9i3y8/NR5edjZmqif80ezTCyt0Vx/7qd6tcn+c6dCg3N+GrOHP67YT3R0dHYuTUqtYys0aA1N8PU3BwjO1vUmVlo88oe317eNf37rYFM+OJz/ncghq7+HQju9i+e82hWshJJQlIokDUa4hISmPXD9xw7fZqUtFRdT861m0m0aNqU/NQ0AJo7NwIkFAZKGtwPKO6kpKAwMNDdm+L35NixY0ybNo2TJ0+Smlqk7hs3aNGihe64Vr6+umMbNGyoq9vFxYWTp04Rs38/s2bP1tWr0WjIzc0lNy+P8xcu4OzsTKPGjXX7n2vZEhsbG85fvIh/hw4FWe0kSa99kkIB97f5tmlDYGAgPr6+BAUF8dJLL/Haa69ha/sgO6P5/eA5V6Uq9XuvMDBAUiowsrXG2MSkxH5BeFLs/HwKAp2aoFRg6+tdM+cWBOGZVGuGrlk0VqKsoucHpSlYNq6aoWPlCQwMxMXFhfDwcNLT01m/fv0TT0KgUChKLHhZdF5NZRga6qcLlSRJ9/CamZmJUqnk2LFjnDhxQveKjY1lwf20vO+88w6XL19m0KBBnD59Gj8/P77//nsAevToQUJCAh988AE3btwgMDCQ0NDShx+ZmpqW206lsXFBew0etFe6n5tZvt/e78KX8uOqFbwfMpw//rOMPb+t48UOAeQVuzfGFua6B/Li11yeefPmMWfOHHbs2KEL5kojKZXUre9EWvo9zBo6YdXcHasWHpi5NCw8oV55w6IP68WuafCrr/HX5m307/Uy5y5e5MUBb/DzqpUlT3r//WDu1oi3JrzPvZxsvv9iFjtXrGbnitVAKe+RjEwyLl5GnZWtm99V3n3IysoiKCgIKysrVq5cyZEjR9iwYQMAecUCuaLvq+J1Z2ZmMn36dL331OnTp7l48SImFQwoHvYzoFQq2blzJ1u3bqVFixZ8//33NGvWjCtXHswVKhwK6nA/uBSEp5VdG5+aS8iilbHzKz/DpCAIQmXUmkBHoZRwCKiavPx1AwyRlNXfo6NQKAgJCSEiIoJVq1ZhZGTEa6+9VmX1N2nSBCMjI2JiYnTb8vPzOXLkCC1atAAKHswyMjLIynqw6GXxtXE8PT05dEh/NeuDByuXKtjX1xeNRsPt27dxd3fXezk6OurKOTs7M2rUKNavX8+ECRNYvHixbp+DgwNDhgxhxYoVzJ8/n59//rnUczVt2hRTU1MiIyMf0qqyhyceOvEXPbu+SP/ewXg3a45rQ2fiEuKLlCh4fxg8wqfzc+fO5fPPP2fbtm26oXjl8fX15ebNm6SmpgIFvQNGNgW9UqbO9TFtWB+pgsOhGjo6MeyN/iz/dgFjBg8lYn3BHLHCYEJz/wFI1mi4fiaWCxcv8tnnnxM8ZBBtewWRY1R2T5Wcn0/m5QRyk+/qbTcyMkKj0Z/z9vfff3P37l3mzJlDp06daN68Obdv367QNRTVunVrzp8/X+I95e7ujkKhwNPTk6tXr3L16lXdMefOnSMtLU3vZyApKUmv3uI/A5IkERAQwPTp0/nrr78wMjLSBWYAZ86cwdDQEC8vr0pfgyA8SXZ+LTFr1LCctb+qj6RU0rBv1STaEQRBgFo0dE2bL+MxypSbkY+fec1jlCnafPmxUkxXVEhICDNmzODjjz9mwIABpfZG3Lt3r8SDl729vW7OQVnMzc0ZPXo0EydOxM7ODhcXF+bOnUt2drau58jf3x8zMzM+/vhjxo0bx6FDh/QSCAC8//77DB06FD8/PwICAli5ciVnz57Vm0PzMB4eHgwcOJDBgwfz9ddf4+vrS3JyMpGRkbRs2ZJevXoxfvx4evTogYeHB6mpqURFReHpWbCg59SpU2nTpg1eXl6oVCo2bdqk21eciYkJkyZNIiwsDCMjIwICAkhOTubs2bN6PWZGdezLbG8Tl0b8vmsHh078hY2VFT8sj+B2yl2aNWlCYZCjNDFGMqhcz9+XX37J1KlTWbVqFa6urty8eRMACwsLXeKF4nx9falTpw4xMTH07q0/N0ShUGBsZ4OFmwsAkmHZwf7kubPpFtAJ90aupGWks+/IYZo1LvgeOjvVR5Iktu+J5l8dO2NiYoyViSn2trb8/PPPODk5kZiYyEczpgH3x9nb2sD1G/onkWVUt5L1Nrm6upKZmUlkZCQ+Pj6YmZnh4uKCkZER33//PaNGjeLMmTN8/vnnFbyLD0ydOpXevXvj4uLCa6+9hkKh4OTJk5w5c4aZM2fSrVs3vL29GThwIPPnz0etVvPuu+/SpUsXXZD54osv8tVXX/HLL7/QoUMHVqxYwZkzZ/D19QXg0KFDREZG8tJLL1G3bl0OHTpEcnKy3vtv7969dOrU6aG9iYJQ0yRJwi2kP2emf/Nkz6tU0qBPEEb35/UJgiBUhUfq0fm///s/XF1dMTExwd/fn8OHD5dZNj8/nxkzZtCkSRNMTEzw8fFh27Ztj9zgR6UwlHB5xRh7v8eL7ez9DHDu++iLhVaWi4sL3bp1IzU1lWH3J3MXFx0dja+vr95r+vTpFap/zpw59OvXj0GDBtG6dWsuXbrE9u3bdfML7OzsWLFiBVu2bMHb25tff/2VadOm6dXRv39/pkyZQlhYGG3atCEhIYHRo0dX+lqXLVvG4MGDmTBhAs2aNaNv374cOXIEF5eCh3SNRsOYMWPw9PSke/fueHh46LK7GRkZMXnyZFq2bEnnzp1RKpWsXr26zHNNmTKFCRMmMHXqVDw9Penfv3+JHgMjW2tMHOve/0r/+x068t/4eLbgtdEjCR4eQl37OvR64UVdUTOXBkiPkBlv0aJF5OXl8dprr+Hk5KR7zZs3r8xjlEolISEhrFxZyjCzwtbf/3TWvFFDjOvYl7geAI1Gy8TZM/F/JZjXRv+bJo1cmffJFADq16vH5NFjmL7gWzxe7EzY7C9QKBT8Z85XHD1yhOeee44PPviAr776CgCFoSHmzvUxdys72M5LzwTg+eefZ9SoUfTv3x8HBwfmzp2Lg4MD4eHh/Pe//6VFixbMmTOn3HtQlqCgIDZt2sSOHTto27Yt7du359tvv9UlDZAkid9//x1bW1s6d+5Mt27dcHNzY82aNXp1FL6/27ZtS0ZGhi5BCICVlRV79uyhZ8+eeHh48Omnn/L111/rEnwArF69mhEjRlS6/YJQE5z79cbA0vyJ9urIWi1Nhg94YucTBKF2kOTig88fYs2aNQwePJgff/wRf39/5s+fz3//+1/Onz9P3bp1S5SfNGkSK1asYPHixTRv3pzt27fz4Ycfsn//ft0noo8jNzeXK1eu0Lhx44eOudeqZTLiNGxpk4I6u9yipTIwg57H7LBsokRh8OS79YWakZ+eQe7NZDS5uQV/+Ev7kbm/3cDCHBPHuhiYPdlP7m/evImXlxfHjx/XPcSXJz8zi+yEa8iax0+TrjAxwbJp4xJrKxWSZRnV7Tvk3rqD3nBAScKiiesTv1dP2tatW5kwYQKnTp3CoIwkFJX5PSYIT8L1P3dwbGzJdO7VQpJw//cgWkx+7+FlBUEQKqHSgY6/vz9t27Zl4cKFQMGkX2dnZ957ryCNa3H169fnk08+YcyYMbpt/fr1w9TUlBUrVjxm8yv/gKBVy9zak0/0y2mVCnYMzKDrHzbU62wogpxaSJZlNDm55N1NJS8tHeQHk3UlpRIjWxuM7G10iQxqwsaNG7G3t6dTp04VKq/JySUz/iryIyaXKMq0YX2M7WzKLaO6m0LO9Zt625TmZli4NSozSHoWrF27FmdnZ/z9/cssIwId4WkjyzJH/j2JW7v2VMkHImWRlArMnBvQdfuvKE1q7venIAjPpkqN48rLy+PYsWNMnjxZt02hUNCtWzcOHDhQ6jEqlarEH25TU1P27auZ9JUKA4l6nQ3pecyOmEHp3D2qfugx9n4GBCy3Ej05tZgkSRiYmWJgZoppQyfQapG1WiSlsiDV8FOgb9++lSqvNDXBwq0RmZeuPMKDjETR3hnV7TsY2VgjKcr++TC2t0Obl4+qSDICTVY2+ekZGFlblXncP11VJhARhCdFkiRaffkxe/teIvvqjeoJdhQKlCYmtP1prghyBEGoFpV6Qrtz5w4ajYZ69erpba9Xr55u0nRxQUFBfPPNN1y8eBGtVsvOnTtZv359iSxGT5LCQMKyiZIeB23pvNYKx0DDEqmnlabg1M2QLmut6HHQVgQ5go4kSUhKJQpDw6cmyHlUSmMjzB8pw5J+R7A2L4+8tHsPPcqkngOKYhngVLfvllFaEISaZGRrw/OrF2HawPGR5hyWS6nAwNSE9isWYtW8ataGEwRBKK7as64tWLCAESNG0Lx5cyRJokmTJoSEhLB06dLqPnW5CoMW52BjGr1qgqyVyUuXkdUgGYCRlYSkkNDmy0gKCemf/TwrCGUysDDH1KkeOTdK/7CiTMXmK6mS72Jka13uMDRJocDE0YHsxOu6bZqcHDSqPJTGFUuBLQjCk2PqVI9OG5Zy5N9hpBw9WTWVKiRMnerRbvE8rFt4PLy8IAjCI6rU43udOnVQKpXcunVLb/utW7f01jopysHBgY0bN5KVlUVCQgJ///03FhYWlUo9/CTIMqjuaMlK1KC6oy11vrkgPKuM7G1RmptV7qBiPyRalQp1RlYZhR8wtLYq8elw/r30yp1bEIQnxriOHQH//ZnnpoWiMDZ65N4dSakECdxC3uSFXb+JIEcQhGpXqUDHyMiINm3a6C20qNVqiYyMpEOHDuUea2JiQoMGDVCr1axbt44+ffo8WouriFYtI2tlrv6hYue/UlltmczvHils8Uvld48UVlsms/NfqVz9Q4WsldGqReQjPLskScKsgVOlh7AVH7qnuptSoXMZFpuTk5+RWanzCoLwZEkKBW4h/Xlh1xoavfUKChPjgt8XDxu+e7+MpFDgGNSVThuW8dzUDzEwFUk3BEGofo+UXnrIkCH89NNPtGvXjvnz5/Pbb7/x999/U69ePQYPHkyDBg2YPXs2ULCY3vXr12nVqhXXr19n2rRpXLlyhePHj2NjY/PYF/Ao2Yq0GpmMSxr2vZ1OyjGRjEAQCmVfv0leBYIVnVLSbVs2c3/oMLT89Ayy4q8+qEapxKqFxzOdfa08Iuua8E+jzszi2sZtJO89ROqJM+TeTC5RxtDGChsfL+zb+eLyem9M6jnUQEsFQajNKj1Hp3///iQnJzN16lRu3rxJq1at2LZtmy5BQWJiIooin/Dk5uby6aefcvnyZSwsLOjZsyfLly+vkiDnUWg1Mrd2Vy699N2jara0SRHppYVnnomDPXkpqaWvFVQaWS74RFf7IN12Xkoqpk71yjmoYO0dvWo0GrT5apRGhpVusyAIT56BhTmub/fD9e1+AOSlppF76w4alQqFoSFGdjaY1HOotR9eCILwdKh0j87TRiwYKghVK/taUkGwU0EKYyO0qjzd15KBAVbNm5abalqWZdLPXdBLWWvu6oyhleWjNfofTvToCIIgCELVq1W5xCQF7Hs7/ZGCHAB1NsQMSv9HZ2AbOnRopddbeRTTpk2jVatW1X6e6hAfH48kSZw4caKmm1IpnTt3ZtWqVbqvJUli48aNla7H2MGuUuVltabY12ryMzLKPUaSpBJpprX5Dx9G+k/00Ucf8d57YsV3QRAEQXjS/sGP7JWjzZdJ3KCq0Jyc8tw9qubqRhXa/EfvCJMkqdxXcHAwkiRx8ODBUo8PDAzk1VdfBZ5c4CI8GevXr8fPzw8bGxvMzc1p1aoVy5cvf+hxf/zxB7du3eLNN9/UbUtKSqJHjx6VboPS2BilmX4Gtn1HDmPr48W99JLZ0WSNBmWxXoi81IevqVOYuWnV7xto1LE9skb7kCP+mUJDQ4mIiODy5cs13RRBEARBqFVqTaCjMJS48GNOldR14cccFIaPPnQtKSlJ95o/fz5WVlZ623799Vd8fHxKXWsoPj6eqKgohg8f/jiXIDyl7Ozs+OSTTzhw4ACnTp0iJCSEkJAQtm/fXu5x3333HSEhIXrz4xwdHTE2frTVxo1srStVXlFsbo06IxNtfn65x0hK/V8/srYaVl5/CtSpU4egoCAWLVpU000RBEEQhFql1gQ6Wo1Mckz5D14VdTsmH1nz6D06jo6Oupe1dcECi0W3WVhYMHz4cNasWUN2tv44u/DwcJycnOjevfvjXgYAKpWKcePGUbduXUxMTOjYsSNHjhzRO1/xxBEbN24sMcF0zpw51KtXD0tLS4YPH05ubq7e/sKep3nz5uHk5IS9vT1jxowhv8jDsEqlIjQ0lAYNGmBubo6/vz/R0dG6/QkJCQQHB2Nra4u5uTleXl5s2bIFgNTUVAYOHIiDgwOmpqY0bdqUZcuWlXndWq2WuXPn4u7ujrGxMS4uLnzxxRd6ZS5fvswLL7yAmZkZPj4+HDhwQLfv7t27DBgwgAYNGmBmZoa3tze//vqr3vFdu3Zl3LhxhIWFYWdnh6OjI9OmTSuzTYXHvPLKK3h6etKkSRPef/99WrZsyb59+8o8Jjk5mf/9738EBwfrbS86dK1wON769evLvKai99fOpSEdXn2ZHXv3kHj9OsHvhADg2qkDtj5evDvlYwB2xeyl+5C3adDSC7fOz9N/7LtcuZoIskxeWnq555WUSvYdOcyYqZ+SnpGBmVM9JEnS3aPly5fj5+eHpaUljo6OvPXWW9y+fVvX3ujoaCRJIjIyEj8/P8zMzHj++ec5f/683n34/fffad26NSYmJri5uTF9+nTU6gc9u4mJifTp0wcLCwusrKx444039NYKK63XdPz48XTt2lX39dq1a/H29sbU1BR7e3u6detGVtaDNYWCg4NZvXp1md9DQRAEQRCqXq0JdDKvaNDkPrxcRWhyIONK9X76PHDgQFQqFWvXrtVtk2WZiIgIhg4divIRF2wrLiwsjHXr1hEREcHx48dxd3cnKCiIlJSKpxj+7bffmDZtGrNmzeLo0aM4OTnxww8/lCgXFRVFXFwcUVFRREREEB4eTnh4uG7/2LFjOXDgAKtXr+bUqVO8/vrrdO/enYsXLwIwZswYVCoVe/bs4fTp03z55ZdYWFgAMGXKFM6dO8fWrVuJjY1l0aJF1KlTp8w2T548mTlz5uiOW7VqlS5zYKFPPvmE0NBQTpw4gYeHBwMGDNA9IOfm5tKmTRs2b97MmTNnGDlyJIMGDeLw4cN6dURERGBubs6hQ4eYO3cuM2bMYOfOnRW6r7IsExkZyfnz5+ncuXOZ5fbt24eZmRmenp4PrbO8ayp+f2dM/gRzMzMaODryy9fzATjy+2b+joxmdthkALJzchgzaAj/+/W/bP71NxQKibc/eB+tVkt+keFrpZ5Xo6Zdq1bMDvsISwsL4o6fICkpidDQUADy8/P5/PPPOXnyJBs3biQ+Pp6hQ4eWek1ff/01R48excDAgGHDhun27d27l8GDB/P+++9z7tw5fvrpJ8LDw3VBrVarpU+fPqSkpLB792527tzJ5cuX6d+//0PvZaGkpCQGDBjAsGHDiI2NJTo6mldffZWieV7atWvHtWvXiI+Pr3C9giAIgiA8JvkfLicnRz537pyck5NTbrk7x/LkX6RbVfa6ezyvStq/bNky2drautR9b775ptylSxfd15GRkTIgX7x4UbdtyJAhcp8+fSp8vqLlMzMzZUNDQ3nlypW6/Xl5eXL9+vXluXPnltm+DRs2yEXfOh06dJDfffddvTL+/v6yj4+P3nkbNWokq9Vq3bbXX39d7t+/vyzLspyQkCArlUr5+vXrevUEBgbKkydPlmVZlr29veVp06aVel3BwcFySEhIBe6ALKenp8vGxsby4sWLS91/5coVGZD/85//6LadPXtWBuTY2Ngy6+3Vq5c8YcIE3dddunSRO3bsqFembdu28qRJk8ptX1pammxubi4bGBjIxsbG8pIlS8ot/+2338pubm4ltgPyhg0bKnxNxe9v7p0UOfXkWTn15Fn5z/8skwE5fu8B3bbir5zbd+RL0ftkQI5Zu1FOPXlWvvT332We93jUbjn15Fn5/2bMlK0sLeWsa0nlXueRI0dkQM7IyJBlWZajoqJkQN61a5euzObNm2VA9/sgMDBQnjVrll49y5cvl52cnGRZluUdO3bISqVSTkxMLNG+w4cPy7Jc+s/Y+++/r/vZPHbsWMG9iY8vs+337t2TATk6OrrU/RX9PSYIgiAIQsXVmh4dQ6uqTQdtYFn96aWHDRvGnj17iIuLA2Dp0qV06dIFd3f3Kqk/Li6O/Px8AgICdNsMDQ1p164dsbGxFa4nNjYWf39/vW0dOnQoUc7Ly0uvJ8rJyUk3FOn06dNoNBo8PDywsLDQvXbv3q27/nHjxjFz5kwCAgL47LPPOHXqlK6u0aNHs3r1alq1akVYWBj79+8vt70qlYrAwMByr6tly5Z6bQV07dVoNHz++ed4e3tjZ2eHhYUF27dvJzExscw6il9zWSwtLTlx4gRHjhzhiy++4MMPP9QbwldcTk5OhVMSl3dNxe/vufiHT56PS0hg+KRQWvUMoq6bKz49XgLg2s0kAPLvpZd53uQ7d/UrK/YjdezYMYKDg3FxccHS0pIuXboAlHuPi1/TyZMnmTFjht57asSIESQlJZGdnU1sbCzOzs44Ozvr6mjRogU2NjYV/hnw8fEhMDAQb29vXn/9dRYvXkxqqn56blNTU4ASQ1EFQRAEQag+tSbQsWisRFlFy1MoTcGycdUMHStPYGAgLi4uhIeHk56ezvr16594EgKFQqE3BAfQm1dTGYaG+hPWJUlCe3+hyczMTJRKJceOHePEiRO6V2xsLAsWLADgnXfe4fLlywwaNIjTp0/j5+fH999/D0CPHj1ISEjggw8+4MaNGwQGBuqGQBVX+NBZmfYWzkkqbO9XX33FggULmDRpElFRUZw4cYKgoCDy8vLKrKP4NZdFoVDg7u5Oq1atmDBhAq+99hqzZ88us3ydOnVKPFg/yjUVv7/+HTqw+L9ryq1vwLgxpN27x4LPpvO/dRvZfX/OVOF7JC89s5zz6g//LBrnZGVlERQUhJWVFStXruTIkSNs2LChoM5y7nHxa8rMzGT69Ol676nTp09z8eLFCgeHD/sZUCqV7Ny5k61bt9KiRQu+//57mjVrxpUrV3RlCoeCOjiIleEFQRAE4UmpNYGOQinhEFA1q67XDTBEUlZ/j45CoSAkJISIiAhWrVqFkZERr732WpXV36RJE4yMjIiJidFty8/P58iRI7Ro0QIoeDDLyMjQm1hdfH0ZT09PDh06pLetrNTYZfH19UWj0XD79m3c3d31Xo6Ojrpyzs7OjBo1ivXr1zNhwgQWL16s2+fg4MCQIUNYsWIF8+fP5+effy71XE2bNsXU1JTIyMhKtbGomJgY+vTpw9tvv42Pjw9ubm5cuHDhkesrj1arRaVSlbnf19eXmzdvVjjYKU/x+xux7r/Ag2BCUyRIS0lL42L8FSaMHEUX//Y0bdCQDE2x9O3lrI0ja2Vd3VqNBopkjPv777+5e/cuc+bMoVOnTjRv3vyhPWGlad26NefPny/xnnJ3d0ehUODp6cnVq1e5evWq7phz586Rlpam9zOQlJSkV2/xnwFJkggICGD69On89ddfGBkZ6QIzgDNnzmBoaIiXl1elr0EQBEEQhEdjUNMNeFK0+TIeo0y5Gfn4mdc8RpmizZcfK8V0RYWEhDBjxgw+/vhjBgwYUGpvxL1790o8eNnb2+sNxymNubk5o0ePZuLEidjZ2eHi4sLcuXPJzs7W9Rz5+/tjZmbGxx9/zLhx4zh06JBeAgGA999/n6FDh+Ln50dAQAArV67k7NmzuLm5Vfg6PTw8GDhwIIMHD+brr7/G19eX5ORkIiMjadmyJb169WL8+PH06NEDDw8PUlNTiYqK0k3Anzp1Km3atMHLywuVSsWmTZvKnJxvYmLCpEmTCAsLw8jIiICAAJKTkzl79myFe8yaNm3K2rVr2b9/P7a2tnzzzTfcunVL93D8qGbPno2fnx9NmjRBpVKxZcsWli9fXm5qYl9fX+rUqUNMTAy9e/d+5HOXen+bNwfA2ak+kiSxfU80/+rYGRMTY2ysrLCzsSFi7X9xrFOHa0lJfP5TySQUZZILgiaX+g3IzM4met8+2nbtjJmZGS4uLhgZGfH9998zatQozpw5w+eff17pa5o6dSq9e/fGxcWF1157DYVCwcmTJzlz5gwzZ86kW7dueHt7M3DgQObPn49arebdd9+lS5cu+Pn5AfDiiy/y1Vdf8csvv9ChQwdWrFjBmTNn8PX1BeDQoUNERkby0ksvUbduXQ4dOkRycrLe+2/v3r106tSpwr2JgiAIgiA8vtrTo2Mo4fKKMfZ+jxfb2fsZ4NzX+IkEOQAuLi5069aN1NRUvWxSRUVHR+Pr66v3mj59eoXqnzNnDv369WPQoEG0bt2aS5cusX37dmxtbYGCdV1WrFjBli1bdCmUi6dI7t+/P1OmTCEsLIw2bdqQkJDA6NGjK32ty5YtY/DgwUyYMIFmzZrRt29fjhw5gouLC1AwL2bMmDF4enrSvXt3PDw8dNndjIyMmDx5Mi1btqRz584olcpy0/lOmTKFCRMmMHXqVDw9Penfv3+legw+/fRTWrduTVBQEF27dsXR0bFKFm7Nysri3XffxcvLi4CAANatW8eKFSt45513yjxGqVQSEhLCypUrH+vc5d3f+vXqMXn0GKYv+BaPFzsTNvsLFAoFS76cx8nYszzfry8fz/uSWVOnlVq3XMpwvcIeHf9WvoS83p9B/x6Bg4MDc+fOxcHBgfDwcP773//SokUL5syZw7x58yp9TUFBQWzatIkdO3bQtm1b2rdvz7fffkujRo2Agp6Y33//HVtbWzp37ky3bt1wc3NjzZo1enUUvr/btm1LRkYGgwcP1u23srJiz5499OzZEw8PDz799FO+/vprvcVaV69ezYgRIyrdfkEQBEEQHp0kFx98/g+Tm5vLlStXaNy48UPH3GvVMhlxGra0SUH9CHOCDcyg5zE7LJsoURg8mUBHECri5s2beHl5cfz4cd1DfFVJ//sS2mLzYspiZGeDSV0H0v++BDz41WLm0gAjG/1FSNPPx6EtMiSvtDLPgq1btzJhwgROnTqFgUHpH7RU5veYIAiCIAgVU2t6dAAUBhKWTZR0/cMGA7PKHWtgBl3/sBFBjvBUcnR0ZMmSJSUyklUFpVnFh1ups3NQGBliYKH/A5aXml6irKwploygitaGetpkZWWxbNmyMoMcQRAEQRCqR637y6swkKjX2ZCex+yIGZTO3aNlT5YuZO9nQMByKxHkCE+1qhg6VxqlqQn5afceXhDQ5uYhazQY2lijznyQwEKdmYk2X43CsOBXjizLtSbQqcoEIoIgCIIgVFyt6tEpVNiz0+OgLZ3XWuEYaFgi9bTSFJy6GdJlrRU9DtqKIEeotZQmxpUoLaPJVWFkbamXRQ1ZJq9IsCRrNFBs1KxC9HgIgiAIglCFau2TRWHQ4hxsTKNXTZC1MnnpMrIaJAMwspKQFBLafBlJISHVypBQEEBZyTkj6uwcDMzNMLS2Ij81Tbc9LzUN4zp2SJKErC7ZkyoZPJs9OoIgCIIg1Azx+H6fLIPqjpasRA2qO9riHzYLQq2lMDRAqkRviyYnFwAjW/3EAtpclW6fVl1y2JqkEL+OBEEQBEGoOrW2R0erlpEUcPUPFRd+zCE5Jh9N7oP9ShNwCDDEY5QpLq8YI2sRQ9eEWktpaoI6I7NCZQuDGQNzMxRGRnoZ2/JSUjEwMy3Ro1OZQEoQBEEQBKEiauXThVZTkGZ639vppBwrPRmBJhduRuZzMzJfJCMQaj2lsXGFAx2tqiAhgaRUYmRrTe6tZN2+vLR0TJzqoc3X/7kT83MEQRAEQahqtW6siFYjc2t3PlvapJQZ5BR396iaLW1SuLUnH61ajGkTah+FsVElShckJICCdXWQinw4oNWSn3oPuVigIxmKQEcQBEEQhKpVqwIdrVom45KG6JfTKr1gqDobol9OIyNOI4IdodapXKDzYPiawtAQQ0sLvX2qu6lo8/P16xeBjiAIgiAIVaxWBTqSAva9nV7pIKeQOhtiBqX/ozOwDR06tNrWWylq2rRptGrVqtrPUx3i4+ORJIkTJ07UdFMqpXPnzqxatUr3tSRJbNy4sUrqVho9WqADYGRvp7dPq1LpenwKKQwNH71xT7mPPvqI9957r6abIQiCIAi1zj/4kb1ytPkyiRtUFR6uVpa7R9Vc3ahCm//ovTqSJJX7Cg4ORpIkDh48WOrxgYGBvPrqq8CTC1yEJ2/16tVIklSh7+8ff/zBrVu3ePPNN3XbkpKS6NGjR5W0ZXfMPmx9vLiXnl6h8kUDHQMLMxTF1uLR5j3o0Vn1+wbqNXGrknY+jUJDQ4mIiODy5cs13RShFkk7q+bi4hwOjkpn579S2dYphZ3/SuXgqHQuLs4h9czj/S0UBEH4J6g140UUhhIXfsypkrou/JiDy6uVW1ukqKSkJN3/16xZw9SpUzl//rxum4WFBR07dmTp0qW0b99e79j4+HiioqL4888/H/n8wtMvPj6e0NBQOnXqVKHy3333HSEhISiKpGh2dHSssvZIUuWScGhUKmStFkmhQJIkjOvYk3PtxoMCsrbYCaqgkU+pOnXqEBQUxKJFi/jqq6+QtTJadcHUJUkJkuIZvnjhidLkycT/msvf3+eQcrwgkJEMQC4S09zak8/Fnws+iLDzNaD5e6a4vmWC0ki8DwVBePbUnh4djUxyTP7DC1bA7Zh8ZM2j9+g4OjrqXtbW1kiSpLfNwsKC4cOHs2bNGrKz9cfZhYeH4+TkRPfu3R/3MgBQqVSMGzeOunXrYmJiQseOHTly5Ije+WxsbPSO2bhxY4kH3zlz5lCvXj0sLS0ZPnw4ubm5evsLe57mzZuHk5MT9vb2jBkzhvwiczVUKhWhoaE0aNAAc3Nz/P39iY6O1u1PSEggODgYW1tbzM3N8fLyYsuWLQCkpqYycOBAHBwcMDU1pWnTpixbtqzM69ZqtcydOxd3d3eMjY1xcXHhiy++0Ctz+fJlXnjhBczMzPDx8eHAgQO6fXfv3mXAgAE0aNAAMzMzvL29+fXXX/WO79q1K+PGjSMsLAw7OzscHR2ZNm1amW0qpNFoGDhwINOnT8fN7eE9HcnJyfzvf/8jODhYb3vRoWuFw/HWr19f5jWVdX/j4+N54YUXAHDt1AFbHy/enfIxALti9tJ9yNs06tget87P03/su1y5mgiyjEaVpzvvpv/tInjEMOr7t6Hj669w+OQJAPYdOcyYqZ9y7949XY9m4T1avnw5fn5+WFpa4ujoyFtvvcXt27d17Y2OjkaSJCIjI/Hz88PMzIznn39e70MDgN9//53WrVtjYmKCm5sb06dPR10kvXViYiJ9+vTBwsICKysr3njjDW7duqXbX1qv6fjx4+natavu67Vr1+Lt7Y2pqSn29vZ069aNrKwsAGRZpke3Xvy6cjWpZ9SkHFeTdkpN6kk1KX+pSTurJvuGBm2emPsnPLq7x/PZ7JvC/pAMUk48eH/LxTpu5CJ/BlNOqtk/LINNrVK4e6xq/j4KgiA8TWpNoJN5RaO3Ts7j0ORAxhXNwws+hoEDB6JSqVi7dq1umyzLREREMHToUJTKqllFPiwsjHXr1hEREcHx48dxd3cnKCiIlJSUCtfx22+/MW3aNGbNmsXRo0dxcnLihx9+KFEuKiqKuLg4oqKiiIiIIDw8nPDwcN3+sWPHcuDAAVavXs2pU6d4/fXX6d69OxcvXgRgzJgxqFQq9uzZw+nTp/nyyy+xsCiY6D5lyhTOnTvH1q1biY2NZdGiRdSpU6fMNk+ePJk5c+bojlu1ahX16tXTK/PJJ58QGhrKiRMn8PDwYMCAAboH5NzcXNq0acPmzZs5c+YMI0eOZNCgQRw+fFivjoiICMzNzTl06BBz585lxowZ7Ny5s9z7OWPGDOrWrcvw4cPLLVdo3759mJmZ4enp+dCy5V1TWffX2dmZdevWAXDk9838HRnN7LDJAGTn5DBm0BCiVq3h95+XoFBIvP3B+2i1Wr3ha59OmcKE98ezZ8063Bu58s5HE1Gr1bRr1YrZYZOxsrIiKSmJpKQkQkNDAcjPz+fzzz/n5MmTbNy4kfj4eIYOHVrqNX399dccPXoUAwMDhg0bptu3d+9eBg8ezPvvv8+5c+f46aefCA8P1wW1Wq2WPn36kJKSwu7du9m5cyeXL1+mf//+Fbr3UNBDO2DAAIYNG0ZsbCzR0dG8+uqryLJMfoaWe2c1tLBvw/Wka8RfvqJ/sAyaHBlVqpbsJC173kwj5aR44BQqJ3Z+NlvapZJ+4f7fJW355XXul8u4qGGLfyrnvnnECayCIAhPqVozdC0/vWo/LVVnVO+nr3Z2drzyyissXbqUwYMHAwWBQnx8PCEhIVVyjqysLBYtWkR4eLhuLsfixYvZuXMnS5YsYeLEiRWqZ/78+QwfPlz3YD5z5kx27dpVolfH1taWhQsXolQqad68Ob169SIyMpIRI0aQmJjIsmXLSExMpH79+kDB3IZt27axbNkyZs2aRWJiIv369cPb2xtAr7cjMTERX19f/Pz8AHB1dS2zvRkZGSxYsICFCxcyZMgQAJo0aULHjh31yoWGhtKrVy8Apk+fjpeXF5cuXaJ58+Y0aNBA90AO8N5777F9+3Z+++032rVrp9vesmVLPvvsMwCaNm3KwoULiYyM5F//+lepbdu3bx9LliypVCKEhIQE6tWrpzdsrSzlXVN599fOriChgIOdHdZWVrrtL3d7Sa/+hdNn4t61I3/HxeFb90GgGRoaSp833yDjQhwfjR5Dh1f7cPlqIh6N3bCystL1ahZVNGBxc3Pju+++o23btmRmZuoCXIAvvviCLl26AAUT/3v16kVubi4mJiZMnz6djz76SPd9dnNz4/PPPycsLIzPPvuMyMhITp8+zZUrV3B2dgbgl19+wcvLiyNHjtC2bduH3tOkpCTUajWvvvoqjRo1AuA5r+fIvqYl/XbBg6djnYL39NWkRFzqu5as5P6vk7QzGrb4peIzzZznPjar9JBBofY5NTOLk1Pv9x4+Yh3y/fjoWGgm6kyZllPNq6ZxgiAINazW9OgYWlXtA4OBZfU/gAwbNow9e/YQFxcHwNKlS+nSpQvu7u5VUn9cXBz5+fkEBATothkaGtKuXTtiY2MrXE9sbCz+/v562zp06FCinJeXl15PlJOTk24o0unTp9FoNHh4eGBhYaF77d69W3f948aNY+bMmQQEBPDZZ59x6tQpXV2jR49m9erVtGrVirCwMPbv319ue1UqFYGBgeVeV8uWLfXaCujaq9Fo+Pzzz/H29sbOzg4LCwu2b99OYmJimXUUv+biMjIyGDRoEIsXLy63N6q4nJwcTEwqNmesvGsq7/6WJS4hgeGTQmnVMwiX59vh06MggLt2MwlNzoPMai1btkRSKDBxrIujgwMAybpew9Ifz44dO0ZwcDAuLi5YWlrqgpny7nHxazp58iQzZszQe0+NGDGCpKQksrOziY2NxdnZWRfkALRo0QIbG5sK/wz4+PgQGBiIt7c3r7/+Oj//9DOJx++Qe/vBx+omJqYA5OSW/4m5rCl4nZiSxaHRGciyGM4mlO3y8hxdkFNVTk7LIi6iauazCoIg1LRaE+hYNFaifPT8AXqUpmDZuGqGjpUnMDAQFxcXwsPDSU9PZ/369RUezlRVFApFiYet/PxHG1pjWCyFsCRJaLUFD4OZmZkolUqOHTvGiRMndK/Y2FgWLFgAwDvvvMPly5cZNGgQp0+fxs/Pj++//x6AHj16kJCQwAcffMCNGzcIDAzU63EpytTUtNLtLfxkvbC9X331FQsWLGDSpElERUVx4sQJgoKCyMvLq/A1FxcXF0d8fDzBwcEYGBhgYGDAL7/8wh9//IGBgYEu4CuuTp06pKamPvY1lXd/yzJg3BjS7t1jwWfT2bniV3auWA0UvEc0ubm6907heQ2trVAYFqSqlgvvg1YLWhltkUVEs7KyCAoKwsrKipUrV3LkyBE2bNgAUO49Ln5NmZmZTJ8+Xe89dfr0aS5evFjh4PBhPwNKpZKdO3eydetWWrRowXffLsTvJS8Srj8YppZ6ryCos7d1qNA5AS7+nMvpz8VQIqF02dc1HBqTWS2JPA6PzSDravUOzxYEQXgSak2go1BKOARUzVoddQMMkZTV36OjUCgICQkhIiKCVatWYWRkxGuvvVZl9Tdp0gQjIyNiYmJ02/Lz8zly5AgtWrQAwMHBgYyMDN3EaqDEsCpPT08OHTqkt62s1Nhl8fX1RaPRcPv2bdzd3fVeRYc0OTs7M2rUKNavX8+ECRNYvHixbp+DgwNDhgxhxYoVzJ8/n59//rnUczVt2hRTU1MiIyMr1caiYmJi6NOnD2+//TY+Pj64ublx4cKFR64PoHnz5pw+fVrvofzll1/mhRde4MSJE3q9DkX5+vpy8+bNCgc75Snr/hrdX0dHUyRIS0lL42L8FSaMHEUX//Y0c2tCWvo93X5Zo0FW68+EliQJpal+gGFoaIhGoybjQhw5SbfQqPL4+++/uXv3LnPmzKFTp040b968zJ6w8rRu3Zrz58+XeE+5u7ujUCjw9PTk6tWrXL16VXfMuXPnSEtL0/sZKJopEUr+DEiSREBAAJ988Bn/iziMoaERm6N/1+3/O+4shgaGNHdrUan2n5yRxd3jYs6OUNKhdzPQ5MqPPl6tHBoVHBqdUfUVC4IgPGG1Zo6ONl/GY5QpNyMf/6HBY5Qp2nwZhWH1BzshISHMmDGDjz/+mAEDBpTaG3Hv3r0SD1729vZlPhgXMjc3Z/To0UycOBE7OztcXFyYO3cu2dnZup4jf39/zMzM+Pjjjxk3bhyHDh3SSyAA8P777zN06FD8/PwICAhg5cqVnD17tkIZwwp5eHgwcOBABg8ezNdff42vry/JyclERkbSsmVLevXqxfjx4+nRowceHh6kpqYSFRWlm4A/depU2rRpg5eXFyqVik2bNpU5Od/ExIRJkyYRFhaGkZERAQEBJCcnc/bs2Qr3mDVt2pS1a9eyf/9+bG1t+eabb7h165bu4fhRmJiY8Nxzz+ltK8x4V3x7Ub6+vtSpU4eYmBh69+79yOcv7/42atQISZLYvncP/wroiImJMTZWVtjZ2BCx9r841qnDtaQkpi/4Vq9OTW5eifPIxXq0XOo3IDM7m+j9MTzn0QxTExNstRqMjIyY/9U8Rr07mnPnz/P5559X+pqmTp1K7969cXFx4bXXXkOhUHDy5EnOnDnDzJkz6datG97e3gwcOJD58+ejVqt599136dKli26+14svvshXX33FL7/8QocOHVixYgVnzpzB19cXgEOHDhXMu+r2L4xT7Dh64jB3U5PxcG2ua8eBE/to36ojpiYV600sJElwcEQGPY/aivk6gk76BTXX/iz5s1VVZDVc35LHvfNqrJvVmscEQRCeQbWnR8dQwuUVY+z9Hu+Xtr2fAc59jZ9IkAPg4uJCt27dSE1N1ZucXVR0dDS+vr56r+nTp1eo/jlz5tCvXz8GDRpE69atuXTpEtu3b8fW1hYomIS+YsUKtmzZokuhXDxFcv/+/ZkyZQphYWG0adOGhIQERo8eXelrXbZsGYMHD2bChAk0a9aMvn37cuTIEVxcXICCeTFjxozB09OT7t274+HhocvuZmRkxOTJk2nZsiWdO3dGqVSyevXqMs81ZcoUJkyYwNSpU/H09KR///6V6jH49NNPad26NUFBQXTt2hVHR8caW7hVqVQSEhLCypUrH6ue8u5vgwYNmD59OtMXfIPHi50Jm/0FCoWCJV/O42TsWZ7v15eP533JjA/1hwtqVaoS59EW6+Xxb+VLyOv9GRY2AfeuHfkufCl25hb834yZrF23Dm8fH2Z9No3PPyxIjqG6m4IqJQ11dsE8Aq1GU+ZclqCgIDZt2sSOHTto27Yt7du359tvv9UlDZAkid9//x1bW1s6d+5Mt27dcHNzY82aNXp1FL6/27ZtS0ZGhi5BCICVlRV79uyhV69etOvjxaxFnzFj/Fy6BTxIAb9hx28MeqX0n9/yyBpI+UvNnUNicUfhgQs/5iBV8+hpyQAuLBJzdQRB+GeT5H/4bNfc3FyuXLlC48aNHzrmXquWyYjTsKVNCupHGPpuYAY9j9lh2USJwkB8uio8PW7evImXlxfHjx/XPcRXh8y4BNRZFZ/8bGhjjblLA71t986eR9Y8GP9vYGGOOvMxJ1RLCiQDJQqlEslAiVT4r0KBpFAiKRVISgUoCrdJoFDo/19SPNbinffOq0vNxrgrZhtTF4SxZ9VxDAxK/6Alj1yu3Ung8mhb8hKKzesyALdBJjy/xKrUY4XaZ23DO+TcqGgO6Udn4qjg9RsVT4wiCILwtKlVfdIKAwnLJkq6/mFD9MtplQp2DMyg6x82IsgRnkqOjo4sWbKExMTEag10JMPK/crQFEsxLmu1ekEOgGn9gjlYqrup5N9LLzGvp0JkLXK+Fs0jJsrQkSS4v3BpQfBz/2uFVBBMSRIo7m8rUh5JQp1Zh9JmhmfnZvH91P+UGeQ8TMEwogyu/XkeSVIUtEupKGiPAiSF4kGbi7SxYDsPrgV0wd39xuuur+D4ItdfcDMKyhUp8+BeFJZ48H/duYoee/8ePRh1V+RYqcix6N86vWF6Zfy/tg7lU93VPpEgByD3ppbcZC0mDrVm8IcgCM+YWtWjU6iwZydmUDp3jz78ocrez4CA5VYiyBH+EWRZBi3IMshaCv6vLbJdC8hF/pUL/kWWdf9/sE3//+qsnPtpox/8HMgUebgt/Lfwt4okYWBmVlgQWSujyVXplVcYGyEhFRwiF5xQ1ha8KP7rSfdlaT+Hj/uzWXPHl9ejIwg1KXCrNfWDjGu6GYIgCI+kVvXoFCrs2elx0JbEjSouLMohOSYfTZEPn5WmBdnVPEaZ4tzXGFmLCHKEaiHLcsH6KWqQNff/ry1cU6X41wXBwv+zd+dxUVX9A8c/dzZ2ZBEFDVQEDDfEJVJMLe3BJVIzMzPNJU3THy2aprlXPmabtlqmYrk/amZl9piPZO5b7uSKUuaCLLIPM3PP74+RkWETFEzlvF+vecnc5dxz7wx4v/ec8z3Xf772vkBAUxlZmK5zuPYqIwHmzMIVst9fzb22oY1CpeTMlSSp3HKv3NXPQiVJquKqZKAD14MW/2gH6jzhiFAFeekCYbb2iTe4W7toqCaBolFQZMu9VA6qRaDmWbP9CZO1FVGYQTWDMItr/15fXrnBiSRJ0k1S5R8nSZLuXlU20ClMCDBeUTGlC/TuCno3rXymLBVLiGtBTJ71X0ue/XvVdC14kSRJusvp3eVTPkmS7l5VNtBRzQJFA3+uM3JibjFd1xzB51rXtYCesutaVSRUgcUIllxhfeUILLnW99yescAVS3NtLLd1HPu1weBcHx9uHctedFmB7VAt5KWmXetZlv+kt+AT36I/ax0NOFT3AsCUno4pI9O2TufsZF1XwtjzIk8bCo9dL2X9DRWz7c3+hgsB6X9U3kzyDj4Kjx/xvql9rWOzVNuYJ6Faro27yp9sUli3yR+nlT8wyzZmSxR9wfUxVdf+tQ2nKriNbYAX18Z7iSLbULAc7L9BN9zGbv0NrkFpSltf3mGs5d28nOXnXNTwW99q5TvILfBoWmVvEyRJugdUyb9gqsWajGDrs+mk7Cv+0bslFy5uMnFxk0kmI6gChBBYsgWmLIE5U2DJodJmHS+VAoo2/2XtMml7r1EK/Hxt/bWf84MY68+KLWBRNNeDl4rIUiUsCuaMK+XcSYejjzVFrZqbjUWTbluld9Xj4HVvPDHWOqlYcir+C6NooUZb/S1mvqrkSVek20YIwc7hVzBdrfw/Tno3Bde698bvpyRJVVOVC3RUi+DSr6ZypZdO3mtmfYsUOqzzoGY7vQx27gGqWWC+FtSYMq0/V0YrjaKzTlar6ECjA0WnXPvX2kJYcLmiK9DScoeyzkWjAbXsF0uYzagmMxq9DtVk/2BBucmUy3cih+oK2X9W/M2nsED9AU4VXq50d1IUhdpdDJxbZazULrKKDmp1NdzRf48kSZJu5N65yyiD/LTS5Z1DB8CcDXGPp8kJQ+9i5hxBXpqKKe1aYHOrNKA1KGgMoCnuXz1otPfe90Sj06Hm5ZW+kaLYdfmx5Oai0bsWmSPnngp0vDVkn1crNmBWwMlXQ+1uhgosVLrbNRjpxNnlxhtveAuEGRq8KANsSZLublWqTVrRwNZn08sd5OQzZ8O2/ul3dQa2gQMH0qNHj0o/ztSpU2nWrFmlH6c0QghMWSpZf1lIO2Lm6lEzOefVGwY5iX+fpXorA4ePHwBA0YPOTcHBR4NLgAa3EC0eTXV4hevwaKzDPUSHa10tzrW0OFbXYHDXoHNUbnuQ065dO5YuXWp7rygKa9eurfDjlCU4UQr9kuTPnaMWCnQ05ZyA9E6m0Sk41yr6x2H6xxN4/d2Xb65QAa0+cpUPViQ7Pm30eDTVolRSj0RFC9UaaanRVs7pJEnS3e0uvmUvH9UkSPzWWOKYnLJK3mvmz7VGVNPNtwgo12YxL+kVHR2Noijs3Lmz2P07duzIE088Ady+wOVuopoE2X9bSDtsJj3eQu5F1Trepgy0jgqGa2NGXOpp8WymwytMT7UGOlzraHGsocXgrkFrUCqlS0dsbGyR70NZJsJdt24dly5d4umnn7Ytu3DhAl26dKmQesXFxaEoCmlpaWh0Zbm7sr/eltxc63xBZvsB+4pOR2xsLB4eHhVSz3+aY00NOhfFLqvByP6vsvzHbzj715lylaVooU5vB+r0KttEyFLVoSgKree5lztPQlkJFdrMd5fd1iRJuutVmUBHo1c4MTenQso6MTcHjf7m/wO4cOGC7TV79mzc3d3tli1btoywsDAWLFhQZN+zZ8+yefNmhgwZciuncE8yZwsyz1pIPWQm528V9Qa9q9BYW2ocfTW4BWnxDLO20LjcZ72R1ztr/pEn6YW/D+fOnbvhPh999BGDBg1Co7n+K+3r64uDQ8XPaK6UoRVGFJp7Q80xXuu2Zr+8bEHT3UNRFNyCtGgM2IIdb4/qPPLgoyxc/WXZy9GCV3Mdree7VU5Fpbte9VZ6Go91rvi5dRVo9Joz1R+QrTmSJN39qkygo1oESdtMFVLW5W0mhOXmH6X5+vraXtWqVUNRFLtlrq6uDBkyhBUrVpCdbd/PLjY2Fj8/Pzp37nyrpwGA0WgkJiaGGjVq4OjoSNu2bdmzZ4/d8Qo/bV+7dm2RJ30zZ86kZs2auLm5MWTIEHJzc+3W57c8vffee/j5+eHt7c3IkSMxma5/JkajkTFjxlC7dm1cXFyIiIggLi7Otv7cuXNER0fj6emJi4sLjRo14scffyTvqsq5PUk8/cQz1A335b5Id1o90ZCl6xYVOV9Fj7ULWpDCVxs/oEW3+/Gq70xQ07r8e9YMu23PnDnDww8/jLOzM2FhYezYscO2Ljk5mb59+1K7dm2cnZ1p0qQJy5Yts9u/Q4cOxMTEMHbsWLy8vPD19WXq1Kmlfh5Ake9DzZo1S90+KSmJ//3vf0RHRxcpJ7/r2tmzZ1EUhTVr1pR4TsVd3/Xr13P27FkefvhhAOu6+2rx4qQJAPyy7Tc6P/csddo+SGC7NvQZ9SIJfyaSH9Aknj+PZ1gj1v74A4906kStiBa07d2T3QcPAAq/bt3KoEGDuHr1qq0FK/8affPNN7Rs2RI3Nzd8fX155plnuHz5sq2++a1MmzZtomXLljg7O9OmTRuOHz9udx2+++47mjdvjqOjI4GBgUybNg1zgS50iYmJdO/eHVdXV9zd3Xnqqae4dOmSbX1xraYvv/wyHTp0sL1ftWoVTZo0wcnJCR/f6vR+uQu54vrvbtRD3fj2vytL/RwL8nvUwKO/eKB3rTJ/oqWbEDbdhfuiDRX3P7kG7nvMQLM3XSqoQEmSpH9WlflfNDPBYjdPzq2w5EBGQuXNmQHQr18/jEYjq1atsi0TQrBo0SIGDhyIVlsxT8LHjh3L6tWrWbRoEfv37ycoKIioqChSUlLKXMbKlSuZOnUqM2bMYO/evfj5+fHZZ58V2W7z5s2cPn2azZs3s2jRImJjY4mNjbWtHzVqFDt27GD58uUcOnSI3r1707lzZ06ePAnAyJEjMRqNbNmyhcOHDzPjrZlorjqTcdLCm+9O4URCPMvnfM/2lYd4b9zHeHlY5x3ROlpbbdzv1+LZ1NoFbcq/3+Cdd95h0qRJHDt2jKVLlxYJKN544w3GjBnDgQMHCAkJoW/fvrYb5NzcXFq0aMGPP/7IkSNHGDZsGP3792f37t12ZSxatAgXFxd27drFrFmzmD59Ohs3biz1emZmZlKnTh38/f3p3r07R48eLXX7rVu34uzsTGhoaKnb3eicCl/fd955B1dXV/z9/Vm9ejUAx48f5+yRY/x77HgAsnNyGNn/OTYvXcF3X85Ho1F49pWXUAtlZXvr4zm8PPxFtqxYTVCdujz/+mtYEERGRhZp1RwzZgwAJpOJN998k4MHD7J27VrOnj3LwIEDiz2n999/n71796LT6Rg8eLBt3W+//caAAQN46aWXOHbsGF988QWxsbG8/fbbAKiqSvfu3UlJSeHXX39l48aNnDlzhj59+tzwWua7cOECffv2ZfDgwcTHxxMXF8cTvZ7AvYEG59oaUKB5o1b8ffkvEv8+W2pZWmeF1l+58ciP1dC7VZk/z9JN0ugU2q2sRsATFdNyG9DTgXb/qXZLPRYkSZLuJPfOSOAbMKVXbGdmc0blzmHg5eVFz549WbBgAQMGDACsgcLZs2cZNGhQhRwjKyuLzz//nNjYWNtYjnnz5rFx40bmz5/Pa6+9VqZyZs+ezZAhQ2zd6d566y1++eWXIq06np6efPLJJ2i1Wu6//366devGpk2bGDp0KImJiSxcuJDExERq1aoFwJgxY9iwYQMLFy5kxowZJCYm0qtXLxo3akzORZVqdfxtGa7+uphIkwbNCG/YAoCA2nVx8NLgWENB62w/niYjI4M5c+bwySef8NxzzwFQv3592rZta1ffMWPG0K1bNwCmTZtGo0aNOHXqFPfffz+1a9e23ZAD/N///R8///wzK1eu5IEHHrAtb9q0KVOmTAEgODiYTz75hE2bNvHoo48Wey0bNGjAggULaNq0KVevXuW9996jTZs2HD16lPvuu6/Yfc6dO0fNmjXtuq2VpLRzyr++TZo0ASAwMNC2n5eXdcLPGjVq4IyG7Gstmo93+pdd+Z9Me4ugDm354/RpGhUIvEYNGMi/HmpHXkoqr48YSesnupNw/i9aNm1o16pZUMGAJTAwkI8++ohWrVqRmZmJq6urbd3bb79N+/btAXj99dfp1q0bubm5ODo6Mm3aNF5//XXb5xwYGMibb77J2LFjmTJlCps2beLw4cMkJCTg7+8PwNdff02jRo3Ys2cPrVq1uuE1vXDhAmazmSeeeII6deoA2K4hbuBQXUM9d+tn9+eFRAJq1S1ShtZBwcFLIWqLB27eMtOVVHZag0K7Fe6c+iqXPa9koOZRrrTT1hT40PIDN4KHOcpxOZIk3VOqzCNDvXvF/vHWuVX+fwaDBw9my5YtnD59GoAFCxbQvn17goKCKqT806dPYzKZiIyMtC3T6/U88MADxMfHl7mc+Ph4IiIi7Ja1bt26yHaNGjWya4ny8/OzdUU6fPgwFouFkJAQXF1dba9ff/3Vdv4xMTG89dZbPNgikilTpnD0+CFbWYN6vcC3/11Jh34teWvBeOKzduNaT4vORVPkP+74+HiMRiMdO3Ys9byaNm1qV1fAVl+LxcKbb75JkyZN8PLywtXVlZ9//pnExMQSyyh8zsVp3bo1AwYMoFmzZrRv3541a9bg4+PDF198UeI+OTk5ZUpYcKNzyr++kZHW63vo0KFiy1AKjKs5fe4cQ8aNoVnXKALaPEBYF2sA99fFCygFPutGISGoRmvmNV8fHwCupKWVWtd9+/YRHR1NQEAAbm5utmCmtGtc+JwOHjzI9OnT7b5TQ4cO5cKFC2RnZxMfH4+/v78tyAFo2LAhHh4eZf4dCAsLo2PHjjRp0oTevXszb948UlNTbes1egWvutbATFvbiHsDLa71rS/3+7V4hutwD9ahd9Ogd6kyf5KlCqQoCsFDneh+zJugwY5oHbFOElzCo0xFZ12vdYSgQY48fsybkBecZJAjSdI9p8r8r+paT2v9418BtE7gVq/yB1F37NiRgIAAYmNjSU9PZ82aNbc9CYFGo0EUSu1TcFxNeej19oNbFUWxdXHKzMxEq9Wyb98+Dhw4YHvFx8czZ84chBD0e2wQ+749Tu/O/Yg/dYROA1ozb8WnADzaoTPHf09g9OuvkJR+kUejOtm1uBTk5FS2J+YF65t/A5Bf33fffZc5c+Ywbtw4Nm/ezIEDB4iKiiKv0PwypZ1zWesQHh7OqVOnStymevXqdjfWNyqvYF3g+jk9//zznDlzhv79+3P48GFatmzJxx9/XKQMTYEApm/MSNKuXmXOlGlsXLyMjYuXA9bviKK5ftOk1+mw5Fm/N8q10dOilJuqrKwsoqKicHd3Z8mSJezZs4dvv/0WoNRrXPicMjMzmTZtmt136vDhw5w8ebLMweGNfge0Wi0bN27kp59+omHDhnz88cc0aNCAhIQE2zb5XUFr+tZA76bBwdP60rtq7sm5lqR/hkuAlgfnuvPkxeo8+IUbgf0dqdZQi9bZOj5R6wTVGmoJ7O/Ig3PdePJCdR78wh3XOvdWUhBJkqR8VSbQ0WgVfCIrJotMjUg9ym24OdFoNAwaNIhFixaxdOlSDAYDTz75ZIWVX79+fQwGA9u2bbMtM5lM7Nmzh4YNGwLg4+NDRkYGWVlZtm0OHDhgV05oaCi7du2yW1ZSauyShIeHY7FYuHz5MkFBQXavmjVqknVOJfsvldq+/gzqNYxF7/6HF/u9zDdr5+NYQ4NHIx3+oTUZOGggixcvZvbs2Xz5ZfFZroKDg3FycmLTpk3lqmNB27Zto3v37jz77LOEhYURGBjIiRMnbrq8klgsFg4fPmxrqShOeHg4Fy9eLHOwUxp/f3+GDx/OmjVrGD16NPPmzQPAYDDY6pPfopOSlsbJswmMHjac9hEP0iCwPmnpV68XVqh3Z5HJQq8FTAaDAYvFfszbH3/8QXJyMjNnzuShhx7i/vvvL7UlrCTNmzfn+PHjRb5TQUFBaDQaQkND+fPPP/nzzz9t+xw7doy0tDS734ELFy7YlVv4d0BRFCIjI5k2bRq///47BoPBFpgBHDlyBL1eT6NGjcp9DpJUXgZ3DcHPO9FmvjuPH/HmmcwaPGuswTNZNXj8iDdt5rsTPNQJQ7UqcwsgSVIVVWXG6KgmQchwJy5uuvXMayHDnVBN4rYM2Bw0aBDTp09nwoQJ9O3bt9jWiKtXrxa58fL29rbrjlMcFxcXRowYwWuvvYaXlxcBAQHMmjWL7OxsW8tRREQEzs7OTJgwgZiYGHbt2mWXQADgpZdeYuDAgbRs2ZLIyEiWLFnC0aNH7cZ43EhISAj9+vVjwIABvP/++4SHh5OUlMQv//2FoOqN6diyC2+8P5qObaKoHxBMWkYa237/lUZhobgEaJk8eTItWrSgUaNGGI1GfvjhhxIH5zs6OjJu3DjGjh2LwWAgMjKSpKQkjh49WuYWs+DgYFatWsX27dvx9PTkgw8+4NKlS7ab45s1ffp0HnzwQYKCgkhLS+Pdd9/l3LlzPP/88yXuEx4eTvXq1dm2bRuPPfbYTR/75ZdfpkuXLoSEhJCamsrmzZtt17BOnTooisIPP/xAl85dyMvOwsPdHS8PDxat+g++1avz14ULTJvzoa08UbjlqlCriEZrvcmqW7cumZmZbNq0ibCwMJydnQkICMBgMPDxxx8zfPhwjhw5wptvvlnuc5o8eTKPPfYYAQEBPPnkk2g0Gg4ePMiRI0d466236NSpE02aNKFfv37Mnj0bs9nMiy++SPv27WnZsiUAjzzyCO+++y5ff/01rVu3ZvHixRw5coTw8HAAdu3axaZNm/jXv/5FjRo12LVrF0lJSXbfv99++42HHnqozK2JkiRJkiTduirzOEejVwjo6YB3y1uL7bxb6vDv4XDbstIEBATQqVMnUlNT7QZnFxQXF0d4eLjda9q0aWUqf+bMmfTq1Yv+/fvTvHlzTp06xc8//4ynpydgHYS+ePFi1q9fb0uhXDhFcp8+fZg0aRJjx46lRYsWnDt3jhEjRpT7XBcuXMiAAQMYPXo0DRo0oEePHuyI24Ofh3Ugt0W1MG7WS7R5qil9Xn6M0LAGfP7F54C1VWD8+PE0bdqUdu3aodVqWb58eYnHmjRpEqNHj2by5MmEhobSp0+fcrUYTJw4kebNmxMVFUWHDh3w9fWtkIlbU1NTGTp0KKGhoXTt2pX09HS2b99eagCl1WoZNGgQS5YsuaVjWywWRo4cSWhoKJ07dyYkJMSWPa927dq2gf2+fr6MnTkDjUbD/Hfe42D8Udr06sGE995h+qvXuwuqJjNoS/kTc61Fp02bNgwfPpw+ffrg4+PDrFmz8PHxITY2lv/85z80bNiQmTNn8t5775X7nKKiovjhhx/473//S6tWrXjwwQf58MMPbUkDFEXhu+++w9PTk3bt2tGpUycCAwNZsWKFXRn53+9WrVqRkZFhSxAC1nmPtmzZQteuXQkJCWHixIm8//77dpO1Ll++nKFDh5a7/pIkSZIk3TxFFO58fpfJzc0lISGBevXq3bDPvWoWZJy2sL5FCubsUjctls4Zuu7zwq2+9h+ZSLIqEaog/YQFc2ahr6fGOt7KwbPKxOhlcvHiRRo1asT+/fttN/GVKf34KVTjjWZkBZ2LM+as4n/ZnOvch6Gae0VX7Y7z008/MXr0aA4dOoROV/yDlvL8HZMkSZIkqWxu6m7x008/pW7dujg6OhIREVFk7pDCZs+eTYMGDXBycsLf359XXnmlSOrh20GjU3Crr6XDOg90zuXbV+cMHdZ5yCDnNhBCkHm2aJCjMUC1+2WQUxxfX1/mz59fJCNZZVG0ZWsZVQwlj4vTVNBcUHe6rKwsFi5cWGKQI0mSJElS5Sj3/7wrVqzg1VdfZe7cuURERDB79myioqI4fvw4NWrUKLL90qVLef3111mwYAFt2rThxIkTDBw4EEVR+OCDDyrkJMpDo1Oo2U5P131ebOufTvLeG0844N1SR+Q37jLIuU1y/lbJSyka5Ljfr0NrkNe/JBXRda6sCqaYLnW7UoIZpYrc+FdkAhFJkiRJksqu3I/GP/jgA4YOHcqgQYNo2LAhc+fOxdnZmQULFhS7/fbt24mMjOSZZ56hbt26/Otf/6Jv3743bAWqTPktO112etJulTu+HfVFUk9rncCvk572q9zpstNTBjm3SV6aSs4F+0HsihbcgmSQcycpa2tMafNylDVYkiRJkiRJuhnleqSal5fHvn37GD9+vG2ZRqOhU6dO7Nixo9h92rRpw+LFi9m9ezcPPPAAZ86cYf369fTv3//Wan6L8oMW/2gH6jzhiFAFeekCYbZOpmZwV1A0CqpJoGgUFNlbqtKpFkFWon2aYRRwDdSic5ZBzp2ktJaagoQqULRaRKH00aCUuQxJkiRJkqSbUa5A58qVK1gsFmrWrGm3vGbNmvzxxx/F7vPMM89w5coV2rZtixACs9nM8OHDmTBhws3XuhIIAcYrKqZ0gd5dQe+mRd5a3145f6uohca3u/hr5FwPd6CytsaoJhNaJyfMmZn2+2s1chZ2SZIkSZIqVaV3ko+Li2PGjBl89tlnREREcOrUKV566SXefPNNJk2aVNmHL5FqFiga+HOdkRNzc0jaZsJSID+C1hF8IvWEDHcioKcDQkV2XatE5mxB7mX7Lmt6dwUHHxnk3InK3KKTZ0Ln7lo00Kki43MkSZIkSfrnlOtuo3r16mi1Wi5dumS3/NKlS/j6+ha7z6RJk+jfv79twsMmTZqQlZXFsGHDeOONN9Bobv+NrGqxppne+mw6KfuKT0ZgyYWLm0xc3GSSyQgqmRDXuqwVzD+ggEuAVj71v0OVp0VH5+yEsfD+stuaJEmSJEmVrFxRhsFgoEWLFmzatMm2TFVVNm3aROvWrYvdJzs7u0gwo712k/NPTOGjWgSXfjWxvkVKiUFOYcl7zaxvkcKlLSZU81097dAdyZQhiqSSdvLVoHWUQc6dqswtOhYLGgeHovvLAFaSJEmSpEpW7uaUV199lXnz5rFo0SLi4+MZMWIEWVlZDBo0CIABAwbYJSuIjo7m888/Z/ny5SQkJLBx40YmTZpEdHS0LeC5XVSzIOOUhbjH08o9Yag5G+IeTyPjtEUGOxWscJc1jQM4+ckua3cyTXkypqkqisZ++7t8nmJJkiRJku4C5b6b7NOnD++99x6TJ0+mWbNmHDhwgA0bNtgSFCQmJnLhwgXb9hMnTmT06NFMnDiRhg0bMmTIEKKiovjiiy8q7izKSNHA1mfTyx3k5DNnw7b+6Xd1BraBAwfelvlWpk6dSrNmzW64nSVXYEor1JpTU4Oi+eee+J89exZFUThw4MA/Voeb0b9/f2bMmGF7X7duXWbPnl0pxypP1zPVZELR2f/SFM3Cdu+aO3cu0dHR/3Q1JEmSJKnKualb9lGjRnHu3DmMRiO7du0iIiLCti4uLo7Y2Fjbe51Ox5QpUzh16hQ5OTkkJiby6aef4uHhcat1LxfVJEj81ljm7molSd5r5s+1RlTTzT+RVhSl1Fd0dDSKorBz585i9+/YsSNPPPEEcPsCl8pSuDVH0YLB+y6OJCtAWloaI0eOxM/PDwcHB0JCQli/fn2p+xw8eJD169cTExNjW7Znzx6GDRtWIXUqHPyVK9DJM1H46YAwX/89jIuLQ1EU0tLSKqKqd5zBgwezf/9+fvvtt3+6KpIkSZJUpVSZ1EcavcKJuTkVUtaJuTkEPOF44w1LULDFa8WKFUyePJnjx4/blrm6utK2bVsWLFjAgw8+aLfv2bNn2bx5M99///1NH/9OoVoExmT7QMehugaNtuqO38jLy+PRRx+lRo0arFq1itq1a3Pu3LkbPhj4+OOP6d27N66urrZlPj4+lVZPRaMBjQZU9YbbqiZTkWXCYkHNM6Ex6CujencUg8HAM888w0cffcRDDz30T1dHkiRJkqqMKvPoXLUIkrYVveG6GZe3mRCWm2/R8fX1tb2qVauGoih2y1xdXRkyZAgrVqwgO9u+n11sbCx+fn507tz5Vk8DAKPRSExMDDVq1MDR0ZG2bduyZ88eu+MVvsleu3ZtkcHkM2fOpGbNmri5uTFkyBByc3Pt1ue3PL333nv4+fnh7e3Ni8NGkme8/pkY84xM+mAstWvXxsXFhYiICOLi4mzrz507R3R0NJ6enri4uNCoUSNbS0dqair9+vXDx8cHJycngoODWbhwYYnnraoqs2bNIigoCAcHBwICAnj77bfttjlz5gwPP/wwzs7OhIWF2U2Km5ycTN++falduzbOzs40adKEZcuW2e3foUMHYmJiGDt2LF5eXvj6+jJ16tQS6wSwYMECUlJSWLt2LZGRkdStW5f27dsTFhZW4j4Wi4VVq1YV6R5VuOuaoih89dVX9OzZE2dnZ4KDg1m3bp1tfWnXsF69egCEh4ejKAodOnRA0WrZf+QwPV94nvrtIwmIjKDb4Oc4GH/Mrh7OtXxZtHI5z74cQ62IFrSI7sL6uP9hzsrm7NmzPPzwwwB4enqiKAoDBw4EYMOGDbRt2xYPDw+8vb157LHHOH36tK3c/FamNWvWlPg5AWzdupWHHnoIJycn/P39iYmJISsry+68BwwYgKenJ87OznTp0oWTJ0/a1hfXDXP27NnUrVvX9j4uLo4HHngAFxcXPDw8iIyM5Ny5c7b10dHRrFu3jpycinnYIkmSJEnSjVWZQCczwWI3T86tsORARkLljjHo168fRqORVatW2ZYJIVi0aBEDBw6ssEQOY8eOZfXq1SxatIj9+/cTFBREVFQUKSkpZS5j5cqVTJ06lRkzZrB37178/Pz47LPPimy3efNmTp8+zebNm1m0aBHfLFvEsu+/tq0fP/sldu3eyfLlyzl06BC9e/emc+fOtpvOkSNHYjQa2bJlC4cPH+add96xtWBMmjSJY8eO8dNPPxEfH8/nn39O9erVS6zz+PHjmTlzpm2/pUuXFpkI94033mDMmDEcOHCAkJAQ+vbti/lal6vc3FxatGjBjz/+yJEjRxg2bBj9+/dn9+7ddmUsWrQIFxcXdu3axaxZs5g+fTobN24ssV7r1q2jdevWjBw5kpo1a9K4cWNmzJiBpZQxLYcOHeLq1au0bNmyxG3yTZs2jaeeeopDhw7RtWtX+vXrZ/usS7uG+ef1yy+/cOHCBdasWYOi1ZCZlcXT0d35KfYbNn6zlPoBdXhq5HAyCgQSAO98+gk9oqLY+p81PNq2HS+MH8flv/7C39+f1atXA3D8+HEuXLjAnDlzAMjKyuLVV19l7969bNq0CY1GQ8+ePVELtSKV9jmdPn2azp0706tXLw4dOsSKFSvYunUro0aNsu0/cOBA9u7dy7p169ixYwdCCLp27YqpmJao4pjNZnr06EH79u05dOgQO3bsYNiwYXYPA1q2bInZbGbXrl1lKlOSJEmSpAog7nI5OTni2LFjIicnp9TtruzLE18rlyrslbw/r0Lqv3DhQlGtWrVi1z399NOiffv2tvebNm0SgDh58qRt2XPPPSe6d+9e5uMV3D4zM1Po9XqxZMkS2/q8vDxRq1YtMWvWrBLr9+2334qCX53WrVuLF1980W6biIgIERYWZnfcOnXqCLPZLIQQQrWoovujvUSPR3uLK3vyxIHvTwmtVivOnz9vV07Hjh3F+PHjhRBCNGnSREydOrXY84qOjhaDBg0q0zVIT08XDg4OYt68ecWuT0hIEID46quvbMuOHj0qABEfH19iud26dROjR4+2vW/fvr1o27at3TatWrUS48aNK7GMBg0aCAcHBzF48GCxd+9esXz5cuHl5VXieQth/Ty0Wq1QVdVueZ06dcSHH35oew+IiRMn2t5nZmYKQPz0009CiNKvYf41+f33323LMk4liNSDR+1eyb8fFm4uLmLZR5/algFizNAXbO//2rFHAGL1l/OFEEJs3rxZACI1NbXEcxRCiKSkJAGIw4cP29WptM9pyJAhYtiwYXbl/Pbbb0Kj0YicnBxx4sQJAYht27bZ1l+5ckU4OTmJlStXCiGEmDJlit13WQghPvzwQ1GnTh0hhBDJyckCEHFxcaXW39PTU8TGxha7rqx/xyRJkiRJKrsq06Kjd6/YcR86t8ofRzJ48GC2bNli666zYMEC2rdvT1BQUIWUf/r0aUwmE5GRkbZler2eBx54gPj4+DKXEx8fb5eQAih2XqVGjRrZWqJMmYKaXn5cSU0C4NipI1gsFkJCQnB1dbW9fv31V9v5x8TE8NZbbxEZGcmUKVM4dOiQrewRI0awfPlymjVrxtixY9m+fXup9TUajXTs2LHU82ratKntZz8/PwAuX74MWLuLvfnmmzRp0gQvLy9cXV35+eefSUxMLLGM/HLyyyiOqqrUqFGDL7/8khYtWtCnTx/eeOMN5s6dW+I+OTk5ODg4lGlumoL1cXFxwd3d3Vaf8lxDsCYkuJx8hZemTaZFdBcCIiMIaPMAmdnZ/HXxgt22jUIaXD+uszNurq5cvnwJizGvxPJPnjxJ3759CQwMxN3d3dZVrLRrXPhzOnjwILGxsXbfqaioKFRVJSEhgfj4eHQ6nd3319vbmwYNGpT5d8DLy4uBAwcSFRVFdHQ0c+bMsRuHl8/JyalIV1RJkiRJkipPlQl0XOtp0d58/gA7Widwq1f5cwB17NiRgIAAYmNjSU9PZ82aNQwZMqTSj1uQRqMpMudJWbv0FKbXXx94bkoTKIpi64aUq2ah1WrZt28fBw4csL3i4+NtXZmef/55zpw5Q//+/Tl8+DAtW7bk448/BqBLly6cO3eOV155hb///puOHTsyZsyYYuvh5ORU7vrmBxH59X333XeZM2cO48aNY/PmzRw4cICoqCjy8vJKLCO/nMJdrwry8/MjJCTErmtiaGgoFy9eLFJ2vurVq5OdnV3i+rLWpzzXEKyBzosTJ3D4+B/8e+x4fl60hC0rV+Pl4VHkO6LX2ec9yT+uOSOzxPKjo6NJSUlh3rx57Nq1y9btq7RrXPhzyszM5IUXXrD7Th08eJCTJ09Sv379Eo9dUFl+BxYuXMiOHTto06YNK1asICQkpEjWxJSUlEpNECFJkiRJkr0qE+hotAo+kRWT4alGpB7lNmQG02g0DBo0iEWLFrF06VIMBgNPPvlkhZVfv359DAYD27Ztsy0zmUzs2bOHhg0bAtbMXRkZGXaDtwvPLxMaGlpk7EFJqbHz5V21v9lv/kA4FouFy5cvExQUZPfy9fW1befv78/w4cNZs2YNo0ePZt68ebZ1Pj4+PPfccyxevJjZs2fz5ZdfFnvs4OBgnJyc2LRpU6l1LM22bdvo3r07zz77LGFhYQQGBnLixImbLi9fZGQkp06dsguGTpw4gZ+fHwaDodh98gfKHzt2rNj15VHSNcw/dsGxQopWy64DvzOs77P866F2hAYFYTAYSE5NLfPxTJlZxZadnJzM8ePHmThxIh07diQ0NJTUcpSbr3nz5hw7dqzIdyroWl1DQ0OLjJ3JP3bB34GLFy/aBTvFzbEUHh7O+PHj2b59O40bN2bp0qW2dadPnyY3N5fw8PByn4MkSZIkSTenygQ6qkkQMrxsT/JvJGS40y3No1MegwYN4vz580yYMIG+ffsW2xpx9epVuyfWBw4c4M8//7xh2S4uLowYMYLXXnuNDRs2cOzYMYYOHUp2drat5SgiIgJnZ2cmTJjA6dOnWbp0qd08SQAvvfQSCxYsYOHChZw4cYIpU6Zw9OjREo+rmgSq0X5Zo+YN6NevHwMGDGDNmjUkJCSwe/du/v3vf/Pjjz8C8PLLL/Pzzz+TkJDA/v372bx5M6GhoQBMnjyZ7777jlOnTnH06FF++OEH27rCHB0dGTduHGPHjuXrr7/m9OnT7Ny5k/nz59/wmuULDg5m48aNbN++nfj4eF544QUuXbpU5v1LMmLECFJSUnjppZc4ceIEP/74IzNmzGDkyJEl7uPj40Pz5s3ZunXrLR27tGtYo0YNnJyc2LBhA5cuXeLq1asoWi2BAXVY+cP3HD9zmr2HDjFs/DicHMvedGrOyCLgPn8UReGHH34gKSmJzMxMPD098fb25ssvv+TUqVP873//49VXXy33OY0bN47t27czatQoDhw4wMmTJ/nuu+9syQiCg4Pp3r07Q4cOZevWrRw8eJBnn32W2rVr0717d8CaPS8pKYlZs2Zx+vRpPv30U3766SfbMRISEhg/fjw7duzg3Llz/Pe//+XkyZN237/ffvuNwMDAMrciSZIkSZJ066pMoKPRKwT0dMC75a1NHeTdUod/Dwc0+tsz10tAQACdOnUiNTWVwYMHF7tNXFwc4eHhdq9p06aVqfyZM2fSq1cv+vfvT/PmzTl16hQ///wznp6egHX8weLFi1m/fr0thXLhFMl9+vRh0qRJjB07lhYtWnDu3DlGjBhR4jHNWYWCRA1onRQWLlzIgAEDGD16NA0aNKBHjx7s2bOHgIAAwPrEf+TIkYSGhtK5c2dCQkJs2d0MBgPjx4+nadOmtGvXDq1Wy/Lly0usw6RJkxg9ejSTJ08mNDSUPn36lDp2prCJEyfSvHlzoqKi6NChA76+vhUycau/vz8///wze/bsoWnTpsTExPDSSy/x+uuvl7rf888/z5IlS27p2KVdQ51Ox0cffcQXX3xBrVq16N69O4pWw8dT3yQt4yodnu7N8Dde54Vn+lHdy6vsBxUqNapVY9q0abz++uvUrFmTUaNGodFoWL58Ofv27aNx48a88sorvPvuu+U+p6ZNm/Lrr79y4sQJHnroIcLDw5k8eTK1atWybbNw4UJatGjBY489RuvWrRFCsH79eluXuNDQUD777DM+/fRTwsLC2L17t61LnxACRwcn4uP/oFevXoSEhDBs2DBGjhzJCy+8YDvGsmXLGDp0aLnrL0mSJEnSzVNE4c7nd5nc3FwSEhKoV68ejjd4kqyaBRmnLaxvkYL5JsYE65yh6z4v3Opr0eiq7qSWtyr7vIWcC9e7ZuncFKo1qDJz11aKnJwcGjRowIoVK4pNBFEZ8tKukp14vtz7KVotokA3NX01d1zq3FeRVas0llxBXpqKOUtgzhKohYZFaR0VdK4KOmcweGrQ6BWOHj3KI488wokTJ6hWrVqx5Zbn75gkSZIkSWVTpe4uNToFt/paOqzzIO7xtHIFOzpn6LDOQwY5FaBwi47ORV7PW+Xk5MTXX3/NlStXbtsxFc3NJeTQGPRYcq4HOqb0TFSLBU0FzQ1V0YQQ5KUJci+rmDOufXcVoJhHRJZcgcUoMF6BrD9VDJ4Kf545z9dff11ikCNJkiRJUuWoUoEOWIOdmu30dN3nxbb+6STvNd9wH++WOiK/cZdBTgUQQshAp5J06NDhth5P0d5cz1etoyOWXCPkNyYLFVPaVRy8y9Hl7Tax5Aoyz1owZwprcJOvtHZwcf3fvFRBK7+HcaiuQTUL+fdDkiRJkm6jKjNGp6D8lp0uOz1pt8od3476IqmntU7g10lP+1XudNnpKYOcCmLJBWGxXyYDnbuTcpMtMIpeh97N1W6Z8UpqkRTO/7TcyxbSjpqvB+Y3U71r+xiTVdKOmslLLzm1uCRJkiRJFavKtejkyw9a/KMdqPOEI0IV5KULhBkUHRjcFRSNgmoSKBoFpUqGhBXPkmt/t6joQWuQgc7d6KYDHa0Wg7cnpvQM2zLVaMSUnomhmltFVe+mCSHIPq+Se7ECgxIBwgQZJy241gMHL/kHRZIkSZIqm/zf9hohwHhFJSvRgvGKyh32cPmeUTjQ0TpWbJAjVIFqEXdc68C96Ga7rilaLTpXFzQODnbLcy8l3RGfW87fFRzkFCQg84wFY6ps2ZEkSZKkylZlW3RUs0DRwJ/rjJyYm0PSNhOW3OvrtY7gE6knZLgTAT0dECqy61oFUHPt399qoCOEwHRVYExW7bNgKday9W4KDj4adE7ys6toikYDGg2o5btpV7RaFEXBsUZ1sv+8nrVNzc0lLzkFh+reFV3VMjOmqnYZAStL5hkLukZKhQf6kiRJkiRdVyUDHdViTTO99dl0UvYVn4zAkgsXN5m4uMkkkxFUoKItOjdfVt5VlaxzFmtwUzgLlgBLjsCSa82Wpa+m4FJHK7vJVTBFo0GUM9DRXGsJ0nu4o0lKRs29Hv3mXEhC6+KCzun2p1hWTYKsc5Ybb1hBMs9acG9gDfokSZIkSap4Va7rmmoRXPrVxPoWKSUGOYUl7zWzvkUKl7aYUM3/fNeau5UQokK6rgkhyPrTQsZJy/UWnJI+lmvLTemCtCNm8q7KLkMV6WbG6eTvoygKzrV97VcKleyzf6LmmSqieuWS9aelSKKMSiPAnCnITZLfR0mSJEmqLFUq0FHNgoxTlnLPoQNgzoa4x9PIOG2Rwc5NEuaiGdfKG+gIIchKVMm9VM4bRAGokHHKIjNfVaCbCnR01/fRuTjjUN0+rbRqMpF55pw1BfVtYjEK8lLEzWVWuwU5F9Q7YlySJEmSJN2LqlSgo2hg67Pp5Q5y8pmzYVv/9Ls6A9vAgQPp0aNHpR9n6tSpNGvWzG6ZxVjohk4BjaF85ealCIy38hRcQOZpC6qp5JvLs2fPoigKBw4cuPnj/APatWvH0qVLbe8VRWHt2rWVesybSUhQODhy9K2B1tnJbpmal0fGqQSMV1IQauUHArlJqv08ORVo+scTeP3dl4tdJ0yQlyYDHUmSJEmqDHfxLXv5qCZB4rfGMndXK0nyXjN/rjWWeqN8I4qilPqKjo5GURR27txZ7P4dO3bkiSeeAG5f4FIRbN3MrtE4KOUan6CaBVmJt963SKjWbkp3og4dOhT7nejWrVup+61bt45Lly7x9NNP25ZduHCBLl26VEi94uLiUBSFtLQ0u+XlbtFRFOurgEVff41/y/AiWdhQVXL+vkjGydMYk1MRlsppiRPqteC5kuKNkf1fZfmP33D2rzNFVyrcWuAuSZIkSVKJqkygo9ErnJibUyFlnZibg0Z/849/L1y4YHvNnj0bd3d3u2XLli0jLCyMBQsWFNn37NmzbN68mSFDhtzKKfwj1LxC43P05dvfeEWtmDEUwtoyZMm7856kr1mzxu67cOTIEbRaLb179y51v48++ohBgwah0Vz/lfb19cWhcPBQwcrbopOfca04roF1irTsAKjGPHLOX+Bq/Amyzv2FMSUNizGvwrp8WXJEpY7N8faoziMPPsrC1V8WXSnAlCHToUuSJElSZagygY5qESRtq5gBzpe3mRCWm78x8fX1tb2qVauGoih2y1xdXRkyZAgrVqwgO9u+n11sbCx+fn507tz5Vk8DAKPRSExMDDVq1MDR0ZG2bduyZ88eu+N5eHjY7bN27doiN6szZ86kZs2auLm5MWTIEHJz7fNIDxw4kKeee4JPvvmAhp0DCO7ky5i3YjCZrn8mRqORMWPGULt2bVxcXIiIiCAuLs62/uShszzzSg/qP1KDgIc8iHwqjI3bfgIgLT2VFyYOoMGjtbivrTutnmjI0nWLSjxvVaj8e/o7BAUF4eDgQEBAAG+//bbdNmfOnOHhhx/G2dmZsLAwduzYYVuXnJxM3759qV27Ns7OzjRp0oRly5bZ7d+hQwdiYmIYO3YsXl5e+Pr6MnXq1BLrBNi2y39t3LgRZ2fnUgOdpKQk/ve//xEdHW23vGDXtfzueGvWrCnxnM6dO0d0dDSenp64uLjQqFEj1q9fz9mzZ3n44YcB8PT0RFEUBg4cCMDGX3+l83PPUqftgwS2a0OfUS+S8GeirczE8+fxDGvE979sJHrIQPxahNkdNy4ujkGDBnH16lW0Bj3uwYG8G2sN8Jd/v46H+z6Ff+tWNHikHc+PHc3fZxLI+etvMo6f4sfYb1AUhR9XrKRFs2Y4OzvT+sEHOXb4MEK9Pvblu+++o3nz5jg6OhIYGMi0adMwm6+37J45kcizo5+gTjtP6nbwZsj4vlxOvmRbP2rqEPqP6WV3bd94fzSPv9DJ9n7dptU89HQ497V1J7iTL0+82JmsnCzb+qiHuvHtf1cW/wEK7FLbS5IkSZJUMapMoJOZYKmwmwlLDmQkVG7Xp379+mE0Glm1apVtmRCCRYsWMXDgQLQ3OSt9YWPHjmX16tUsWrSI/fv3ExQURFRUFCkpKWUuY+XKlUydOpUZM2awd+9e/Pz8+Oyzz4pst2V7HGfPn+G7uf/lkynzWbJ6EbGxsbb1o0aNYseOHSxfvpxDhw7Ru3dvOnfuzMmTJ1HNgjFvxpBnyuP7LzexZdl+Jv/fDFycXAH499ypnEiIZ/mc79m+8hDvjfsYL4+S52N585M3eP+TWbwxfiJHDh5l8ddL8KleA9UkbN0S35jwBq++PJr9e34nOCiEvn37kpdjQjUJsjNyaN6sOd+v/YFDvx9m6JCh9O/fn53bd10vQ8CiRYtwdnRmx9adzJzxDtOnT+fnn/5r2+ZGr/lfzafPU31wMjiXuM2WuN9wdnamQdD9dsvB2t2vrOf04osjyc01ErfpVw7uP8S/356Js6MLtX3v4z8rrN/D+CN/cD7xbz58b7b1OmTn8mL/QfxvySrWfhGLRqPh2VdewmJREEKLEJpr1/sjRg0Ywm9rfrA77oOtWvPh+x/i7u7O+cS/OZ/4N+MmTcG5Tl0sipbxL77ElpXf8c2Hn5J4/m9enDTxWrlaWyvMlLdnMO3/RrNp8X9QTBYG9X+OtMMnuXrkJD99vZwBzz7LsKf6sfvHX/hwylss/Go+U8a8TubZC2QknOfJZ7qTlp7Kd19sYvUnP3H2fALPT+hX5u//xSsXGPZGf555fCDbVx7iu7kbeezhHnatNM0bteLvy3+R+PfZYssonI1QkiRJkqRbV2Xm0TGlV+yNhDmjcm9MvLy86NmzJwsWLGDAgAEAbN68mbNnzzJo0KAKOUZWVhaff/45sbGxtrEc8+bNY+PGjcyfP5/XXnutTOXMnj2bIUOG2LrTvfXWW/zyyy9FWnWquXvyzmtz0Gq1BNe9n86PdmXTpk0MHTqUxMREFi5cSGJiIrVq1QJgzJgxbNiwgYULFzJt/Fucv5jIY4/0pGFQEwDq3hdoK/uvi4k0adCM8IYtAAioVbfE+mZkZfDl8k+Y+docHg/rB5ng5VqHRi0eJPWgmat/W5/2D+/9Cm1qR0EOvNpnIpFrmrH/xz8Irns/ztRkcMeXrxUI/dqO4IfWP/PNZysIfrk5AKZMQcPAJvzf429ANkQ3rUez0E9Yv3wjLX0evuF13X90D0eOHuGD174g9WDJY8v+2JGAj0dNrh5WAfvxHllnLWU+p7MnzvHYIz25Tw2FDIi8LwCA9CMCfWo1AAyXvXDI8UAFUjHzr2b2AcGciRE0eLQW8cdzCQ1qjGq2Bjoj+42jU2vr9/bVPtXtjqu76gaqgsOl6tbrdglMwNP/etlWbkBNmDG6Do8+15r0qzVwdXZFtfwJwBvD36F12CMAxAyw0Pfl7mRn1sLRwZGZn4wgZsA4eneKAaB2tQjGDc1j2scTePXZfxO36xeOnTzK/rUnqO3rD8BnUxcQ2acZ+4/upXmjljf8nC5duYjZYuaxh3vg71cHwPYdzedb3fqd/vNCYtHvpsItjfmTJEmSJKl4VSbQ0btXbEolnVvlT/I3ePBgoqKiOH36NPXr12fBggW0b9+eoKCgCin/9OnTmEwmIiMjbcv0ej0PPPAA8fHxZS4nPj6e4cOH2y1r3bo1mzdvtlt2f2BDu5YoPz8/jp04AsDhw4exWCyEhITY7WM0GvFw9SLjlIWhfUbx2sxRxO38hXYPPEL0Iz1pFNwUgEG9XmDQuD4c+uN3OjzYia7tu/NAWOti63vy7B8Y84y0a1V6sFHwZrVmdT8AklKSCK57PxaLhQ8XzuS7X1ZxIelvTKY8jHlGnB2dSizDWo4vV1KTSj1uvsXfLaRhUGOaN2pV6na5xhwcDGUbi1PaOZV2fUtyOvEkM7+Yxv4je0i+esU2eehfl/4kNKhxmY5bkgPx+5n15XSOnjxMWkaqrezzFxNpENjwetnBBcu2zstzJfUy9/kGcPTkIXYf2s6HC2fatrGoFnKNuWTnZnMi4Q9q1/S3BTkADQIbUs3Ng5Nn48sU6DQObkq7Vo/wUN/mPPLgo3SIeJTHOz6Bh7unbRvHa9+LnNwSUj7KOEeSJEmSKlyV6brmWk+LtoImW9c6gVu9iuk6VpqOHTsSEBBAbGws6enprFmz5rYnIdBoNEUGShccV1NmAnRa+7hao1NQr928ZmZmotVq2bdvHwcOHODAgQPs3/s7u9cfZvrw9xEW6N9jMPvWHqd3137EnzpCpwGtmbfiUwA6RXbm9+9PMfyZGC4mXeCJkVFMnj2u2Ko4OpTti6DXXa9v/pgkVVjr+8k37/Pl8k/4vwFjWPv5f9m8ZA8Pt/4Xeaa8QmXYZ1xQlOvnXJqsnCy+/e9K+j1+49Y7L4/qpGWk3XA7a31KPqfSrm9J+r3ak7T0VD5843P+u3ArPy/cCoCpyHUo+bjFycrJ4qn/64abiztz31zEL4u2s+jd/wCUeo2Vazmi869xVk4mY4dNZvOSPbbXlmX72b3mGI6Gsn0Piv0dMF//HdBqtaz+9CdWzPmekHqhfLXyUx58sjHnzifYtkm9au0K6u3pU/xBKv+5iSRJkiRVOVUm0NFoFXwiy5nmqwQ1IvUo2sq/M9FoNAwaNIhFixaxdOlSDAYDTz75ZIWVX79+fQwGA9u2bbMtM5lM7Nmzh4YNrU/MfXx8yMjIICvr+sDqwvPLhIaGsmvXLrtlhVNjF3dPW3A+ovDwcCwWC5cvXyYoKIjAOvWpYa5HgGd921N6gNq+/gzqNYxF7/6HF/u9zDdr59vWVff04enHBjD3zUW89er7fL32q2LPO9A/GCcHJ7bs2Vzs+rLYdXA7XdpH81TXfjQOCaNu7UBOJ5646fIKW/fLavJMRnp3eeaG2zZp0IzLyRdJS0+95eOWdH0NOuuERxbL9bFpKWnJnDp3glcHj6fdA48QUi+0zAFXQXq9HotqP+bt5NnjpFxNZvKot2kd3pbguveTlHK53GU3bRDO6XMnCPQPKvLSaDSE1Luf85f+5PzFP237HD9zjKsZaYTUs/4OeHtW59KVi3blHjlx0O69oihEhLXh9RemsHnxHvR6Az/GfWdb/8fpo+h1eu4v0BJlI6xBvyRJkiRJFavKdF1TTYKQ4U5c3HTrmddChjuhmsQtpZguq0GDBjF9+nQmTJhA3759cXIqmn736tWrRYIPb29v/P39i2xbkIuLCyNGjOC1117Dy8uLgIAAZs2aRXZ2tq3lKCIiAmdnZyZMmEBMTAy7du2ySyAA8NJLLzFw4EBatmxJZGQkS5Ys4ejRowQGXh9DUyR9roLdU+yQkBD69evHgAEDePfd9wh2b8rlC0ls2f0/GgY34V9tu/LG+6Pp2CaK+gHBpGWksXXfr7auT/+eO5Ww0ObcH9iQvDwj//3tR0JK6Bbl6ODI/z03humfjMcj0JHINpEkXUni6LGjDBk0hKvVrL8W7iE6PMOsPytp1n/d6mvxDNPRsEUIq9esJj57N54ennw45wOupF2msXsj2z56VwUHH8X2HkDvrsHgobFbVpwVL8fSvXsP6revWep2AO0bt6T6mOocTd/FYw89ZrfOpa61vmU5p1dGv0znqC6EBIeQmpbKzvgtNGrWEM8wHY2rB6IoClvPbaBrw644OTlRz9kHby9vvvluNn6+Jv66eIHpc963lq29hEZ/Bo3uLwA0uvNo9O4AVGtY3e64jbLrkzUpk/3JvxLWNAxnZ2ca16qHwWDgm82f88Kw4Rw5eoTZi/9tdw5uadZWVY/GOjw8rp2fsP5bLVSHZ10dU2dM5vEe0QSF1aHXE0+i0Wg4eOggR48e4c3pb9GjaRSNPm/CC5Of4+1X38diMfPaO/9Hm+btbOO9Hmr5MJ988wErfvyGlk0e5D8/LSX+9FGaNGgGwL4ju9my5390iHgUHy8f9h3ZTXJqkt33b8eBrTzYrC1OjkV/fwFra/PVG37UkiRJkiSVQ9Vp0dErBPR0wLvlrcV23i11+PdwuC1BDkBAQACdOnUiNTWVwYMHF7tNXFwc4eHhdq9p06aVqfyZM2fSq1cv+vfvT/PmzTl16hQ///wznp7W8QVeXl4sXryY9evX21IoF06R3KdPHyZNmsTYsWNp0aIF586dY8SIEfYHKtSio9FTJEX1woULGTBgAGNeGUOrbo3oP+ZJfj+2l/t8/VH0IAwWxs16iTZPNaVPzGPUDwjm3XEfA2DQG3jr04m079uC6Bc6otVqmff24hLPe8yQN3jllVeZOn0KjZo2pG+/p7mSnIRGr9g+2/yf7ZbprD9PmjyJ5s2b06VbZx559GH8avnRo0cPFM31/VBA0diXoWiw26a418kzJ9i6bSvPDx1S6nb5L72jjkGDBrFsxdIS61uWc1KFyv+9NIpGTRvS9bEuhDQI4fO5n6HRK/jXvY9p06YxYeJ4/O7zJeaV/0PnoGXpksUcjD9C5JPRvPHeDKa/OhoARVFRFAuKol57b7G9hGqyO27bdpEMHz6cvv2epmatGrz34bvUrFWD2NhYVq1ZReOwRsx67x3ee/89+3PQlXJO137u0q0zP/zwAxs3bSSizQO0eag1cz6eTd3Aumj0ClqDhjX/+RYPNw8eH/YIT4zsTN3a9fhqxhLbd+WR1v9i9JAJTPtoAo8+14bM7Ez6dHvWtt7NxY0d+7fS9+XHiejViBmfT2H6y7PoFHk9Bfy3/11J/57F//6igNZRtuhIkiRJUkVTxF0+U11ubi4JCQnUq1cPR8fS+9yrZkHGaQvrW6RgLmFMcGl0ztB1nxdu9bWyq0k55SapZJ273j1J56JQLbRo0GlMUck8Y9+NSeMA7g10KAqkHjYXCZrKTbEmp3APvncaNC9evEijRo3Yv38/derUuW3HFarK1SN/lGsf5zr+GKq5VVKNyk+ogpQDFfC9KsEv2zYwec5Ytizdj05X9Dunc1FwqGcu898xSZIkSZLKpsq06ID1CbJbfS0d1nmgcy7fvjpn6LDOQwY5N6lw+lylmBhDWATZf9kHOYoW3IN1aA3WJ/TOtSvgK6uAS0DlJ5O4nXx9fZk/fz6JiYk33rgiKYr1VQ5qXt6NN7qNFI2Cg7em0hICZOdm8fHkr4oNcgAca1SpP8OSJEmSdNvcO4+0y0ijU6jZTk/XfV5s659O8t6S5yfJ591SR+Q37jLIuQVqoaFRxXX9y72soha6B3YJ0Np163GsocGUITCl3XxDpGsdLVqHe+9z7NGjx20/pqIoKBoNwlL2CXTvtEAHrN8rY1LlNOk83rFXiesULRg8FYx33iWRJEmSpLtelXyUmN+y02WnJ+1WuePbUV8k9bTWCfw66Wm/yp0uOz1lkHOLhNk+MNEUSoAnVEHOZfsbTZ2bgsHL/porioJboBaDZzk/i2vJD1zqaq1P76UKo2jL1zqm3oF39TonxTrX1m3+FXesqUHRyL8rkiRJklQZqlyLTr78oMU/2oE6TzgiVEFeukCYrd2qDO4KikZBNQkUjWKXClkqv8ItOoW7rhmvCEShbVzu0xRJWADWrkaugVqMyYKsREvpYysUQFgHe7vW06JzljeVFU3RlO+X405s0QFwqaMl7aj59kzeeS0BgZOv/MMiSZIkSZWlygY6hQkBxisqpnSB3l1B76aVc/hVIFGoh2Dhrmu5V+yjFb27gs6l5JtARVFwrK5g8FTIS1YxJgvM2cLuJlXRgd5NwcFHg95NKTZokm5duVt08swIVS13gFTZtA4KLv5au6QZlcm1nmzNkSRJkqTKVGUDHdUsUDTw5zojJ+bmkLTNhCX3+nqtI/hE6gkZ7kRATweEKif1uxWqueRkBOYsFUu2/XrHmmW7CdZoFRxraHGsYZ2rR83j2mdlPYYMbiqfoi1vwCJQ80xoHR0qpT63wqG6gjlLg/FKJaVgu8YlQIvO+c4K9CRJkiTpXlMlAx3VYk0zvfXZdFL2FZ+MwJILFzeZuLjJJJMR3CIhRNEWnQLX0ZhSaPyOwdqiU16KoqC98+6d733lDnTAYsy7IwMdRVFwqaOxdmVNqZw+bM7+Ghx9ZJAjSZIkSZWtyv1vq1oEl341sb5FSolBTmHJe82sb5HCpS2mIi0T0o0VDnLgejICIQR5qfZPzx28ix+bI92ZFE35U3WrRmMl1KRiKIp1PJdt/ExFfBUVQIO13Jr3VmpzSZIkSbpTValARzULMk5ZiHs8rdwThpqzIe7xNDJOW2SwU05qMYGOcu1ez5ItiqSUNnhWqa/lXa/8XdfuzMxrBSmKgvN9Wtzv16Ix3EpB1n/0rgoejXQy458kSZIk3UZV6n9dRQNbn00vd5CTz5wN2/qn39UZ2AYOHHhb5luZOnUqzZo1A0AUnixUi20Qdl6h+XA0Dgpap0qvXqnOnj2LoigcOHDgn61IOfXv358ZM2bY3tetW5fZs2dX+nFvpkXHcocHOvn0rho8Gulw9tegyZ/PqSwtPNe20bkoLPt1Hv3G9Lwn526SJEmSpDvZXXzLXj6qSZD4rbHM3dVKkrzXzJ9rjaimm2/VURSl1Fd0dDSKorBz585i9+/YsSNPPPEEcPsCl1tRuEVHKZBxzZRhfx0NHjI72uzZs2nQoAFOTk74+/vzyiuvkJubW+o+Bw8eZP369cTExNiW7dmzh2HDhlVInUoL/m6uRceIENbPPi4uDkVRSEtLu8VaVg5Fo+BUU4tHIy1uIVocfTToXJRi/3oqWuv4MqeaGqo10lHtfh3D/u959u/fz2+//Xb7Ky9JkiRJVViVSUag0SucmJtTIWWdmJtDwBOON96wBBcuXLD9vGLFCiZPnszx48dty1xdXWnbti0LFizgwQcftNv37NmzbN68me+///6mj3+7FZks9Nq3TjULzJn26/TVqnaQs3TpUl5//XUWLFhAmzZtOHHiBAMHDkRRFD744IMS9/v444/p3bs3rq6utmU+Pj63o8o3FegIiwVhtqDo754/QYqiYHBXMLhb3xfM8odibTHW6Itm+jMYDDzzzDN89NFHPPTQQ7e/4pIkSZJURVWdFh2LIGmb6cYblsHlbSaE5eZbdHx9fW2vatWqoSiK3TJXV1eGDBnCihUryM6272cXGxuLn58fnTt3vtXTAMBoNBITE0ONGjVwdHSkbdu27Nmzx+54Hh4edvusXbu2yM3czJkzqVmzJm5ubgwZMsSuBUI1w6ipQ+g/pheffPMBDdr54+3tzYvDR2IyX/9MjCYj46e9Ru3atXFxcSEiIoK4uDjb+nPnzhEdHY2npycuLi40atSI9evXA5Camkq/fv3w8fHBycmJ4OBgFi5cWOJ5q6rKrFmzCAoKwsHBgYCAAN5++227bc6cOcPDDz+Ms7MzYWFh7Nixw7YuOTmZvn37Urt2bZydnWnSpAnLli2z279Dhw7ExMQwduxYvLy88PX1ZerUqSXWCWD79u1ERkbyzDPPULduXf71r3/Rt29fdu/eXeI+FouFVatWER0dbbe8cNc1RVH46quv6NmzJ87OzgQHB7Nu3Trb+tKuYb169QAIDw9HURQ6dOgAWFuNuvbsSf32kQRERtBt8HMcjD9mVw/PsEZ8vWYVz74SQ62IFrSI7sL6uP9hMRo5e/YsDz/8sHU7T08URWHgwIEAbNiwgbZt2+Lh4YG3tzePPfYYp0+ftpWb38q0Zs2aEj8ngK1bt/LQQw/ZWshiYmLIysqyO+8BAwbg6emJs7MzXbp04eTJk7b1Bbth5ps9ezb16tVD66Cgc1LYuvNXWreNwNXVFQ8PDyIjIzl37pxt++joaNatW0dOTsU8bJEkSZIk6caqTKCTmWCxmyfnVlhyICOhcicV7NevH0ajkVWrVtmWCSFYtGgRAwcORFvOSRpLMnbsWFavXs2iRYvYv38/QUFBREVFkZKSUuYyVq5cydSpU5kxYwZ79+7Fz8+Pzz777Hq9r3Vd27r3V86eP8OPy35h0aJFfLN0Ecu+/9q23fgPX2Lnzp0sX76cQ4cO0bt3bzp37my76Rw5ciRGo5EtW7Zw+PBh3nnnHVsLxqRJkzh27Bg//fQT8fHxfP7551SvXr3EOo8fP56ZM2fa9lu6dCk1a9a02+aNN95gzJgxHDhwgJCQEPr27YvZbD2Z3NxcWrRowY8//siRI0cYNmwY/fv3LxKQLFq0CBcXF3bt2sWsWbOYPn06GzduLLFebdq0Yd++fbZyzpw5w/r16+natWuJ+xw6dIirV6/SsmXLErfJN23aNJ566ikOHTpE165d6devn+2zLu0a5tfnl19+4cKFC6xZswaAjIwM+j/bj59iv2HjN0upH1CHp0YOJ6NAIAHwztzP6dmlG1v/s4ZH27bjhfHjuHLxIv7+/qxevRqA48ePc+HCBebMmQNAVlYWr776Knv37mXTpk1oNBp69uyJqtpn6Svtczp9+jSdO3emV69eHDp0iBUrVrB161ZGjRpl23/gwIHs3buXdevWsWPHDoQQdO3aFZOpbA9GzGYzPXr0oH379hw6dIgdO3YwbNgwu4cBLVu2xGw2s2vXrjKVKUmSJElSBRB3uZycHHHs2DGRk5NT6nZX9uWJr5VLFfZK3p9XIfVfuHChqFatWrHrnn76adG+fXvb+02bNglAnDx50rbsueeeE927dy/z8Qpun5mZKfR6vViyZIltfV5enqhVq5aYNWtWifX79ttvRcGvTuvWrcWLL75ot01ERIQICwsTQgiRftoknu7WX/j71RGXduaIzD/NQgghekQ9KXo82ltc2ZMnDnx/Smi1WnH+/Hm7cjp27CjGjx8vhBCiSZMmYurUqcWeV3R0tBg0aFCZrkF6erpwcHAQ8+bNK3Z9QkKCAMRXX31lW3b06FEBiPj4+BLL7datmxg9erTtffv27UXbtm3ttmnVqpUYN25cqfWbM2eO0Ov1QqfTCUAMHz681O2//fZbodVqhaqqdsvr1KkjPvzwQ9t7QEycONH2PjMzUwDip59+EkKUfg3zr8nvv/9eZJ05O0ekHjwqUg8eFcm/HxZuLi5i2Uef2pYBYszQF0T6iTMi9eBR8deOPQIQ335j/d5t3rxZACI1NbXU80xKShKAOHz4sF2dSvuchgwZIoYNG2ZXzm+//SY0Go3IyckRJ06cEIDYtm2bbf2VK1eEk5OTWLlypRBCiClTpti+y/k+/PBDUadOHSGEEMnJyQIQcXFxpdbf09NTxMbGFruurH/HJEmSJEkquyrTonMzE1CWRudW+WNJBg8ezJYtW2zddRYsWED79u0JCgqqkPJPnz6NyWQiMjLStkyv1/PAAw8QHx9f5nLi4+OJiIiwW9a6dWvbz/ktOg0CG6LVatFoQaiCGp6+XElNAuDYqSNYLBZCQkJwdXW1vX799Vfb+cfExPDWW28RGRnJlClTOHTokO0YI0aMYPny5TRr1oyxY8eyffv2UutrNBrp2LFjqefVtGlT289+fn4AXL58GbB2F3vzzTdp0qQJXl5euLq68vPPP5OYmFhiGfnl5JdRnLi4OGbMmMFnn33G/v37WbNmDT/++CNvvvlmifvk5OTg4OBQpiQOBevj4uKCu7u7rT7luYb5Ll26xAujRtIiugsBkREEtHmAzOxs/rp4wW67RiENbONxXJydcXN15XKhbQo7efIkffv2JTAwEHd3d+rWrQtQ6jUu/DkdPHiQ2NhYu+9UVFQUqqqSkJBAfHw8Op3O7vvr7e1NgwYNyvw74OXlxcCBA4mKiiI6Opo5c+bYjcPL5+TkVKQrqiRJkiRJlafKBDqu9bRobz5/gB2tE7jVq/xJ/zp27EhAQACxsbGkp6ezZs0ahgwZUunHLUij0diyY+Ura5eefOJaLz+9znqjq+gUzNkCBcXWDSkrOxOtVsu+ffs4cOCA7RUfH2/ryvT8889z5swZ+vfvz+HDh2nZsiUff/wxAF26dOHcuXO88sor/P3333Ts2JExY8YUWx8np7Llr9br9baf84OI/Pq+++67zJkzh3HjxrF582YOHDhAVFQUeXl5JZaRX07hrlcFTZo0if79+/P888/TpEkTevbsyYwZM/j3v/9d4n7Vq1cnOzu7yLFvdE6F61Oea5jvueee4+DBQ/x77Hh+XrSELStX4+XhUeQ7otfp0Oiu/84oioLZmFfku1VQdHQ0KSkpzJs3j127dtm6fZV2jQt/TpmZmbzwwgt236mDBw9y8uRJ6tevX+q55SvL78DChQvZsWMHbdq0YcWKFYSEhBTJmpiSknLbEkRIkiRJklSFAh2NVsEnUn/jDcugRqQeRVv5LToajYZBgwaxaNEili5disFg4Mknn6yw8uvXr4/BYGDbtm22ZSaTiT179tCwYUPAmrkrIyPDbvB24RTDoaGhRcYeFLzJKzzBqqIDc5b9smZh4VgsFi5fvkxQUJDdy9fX17adv78/w4cPZ82aNYwePZp58+bZ1vn4+PDcc8+xePFiZs+ezZdfflnseQcHB+Pk5MSmTZtKuzyl2rZtG927d+fZZ58lLCyMwMBATpw4cdPl5cvOzkajsf+1zB+PVVJQkD9Q/tixY8WuL4+SrqHBYJ0102KxH5u2bds2/i/m//jXQ+0IDQrCYDCQnJpabNlF5ttRVYTZXGzZycnJHD9+nIkTJ9KxY0dCQ0NJLaHc0jRv3pxjx44V+U4FXatraGhokbEz+ccu+Dtw8eJFu+tfXJrt8PBwxo8fz/bt22ncuDFLly61rTt9+jS5ubmEh4eX+xwkSZIkSbo5d09u11ukmgQhw524uOnWM6+FDHdCNQk0+soPdgYNGsT06dOZMGECffv2LbY14urVq0VuvLy9vfH39y+1bBcXF0aMGMFrr72Gl5cXAQEBzJo1i+zsbFvLUUREBM7OzkyYMIGYmBh27dpFbGysXTkvvfQSAwcOpGXLlkRGRrJkyRKOHj1KYGAgcL3rWj6NDkxp9svub9iAfv36MWDAAN5//33Cw8NJSkpi06ZNNG3alG7duvHyyy/TpUsXQkJCSE1NZfPmzYSGhgIwefJkWrRoQaNGjTAajfzwww+2dYU5Ojoybtw4xo4di8FgIDIykqSkJI4ePVrmFrPg4GBWrVrF9u3b8fT05IMPPuDSpUu2m+ObFR0dzQcffEB4eDgRERGcOnWKSZMmER0dXWICCh8fH5o3b87WrVuLZAcrj9KuYY0aNXBycmLDhg3cd999ODo6Uq1aNYKDg1m8eDENPLzJSM9g8ofv4eRYQtOpRgGNBgq0TFlyjNSpUwdFUfjhhx/o2rUrTk5OeHp64u3tzZdffomfnx+JiYm8/vrr5T6ncePG8eCDDzJq1Cief/55XFxcOHbsGBs3buSTTz4hODiY7t27M3ToUL744gvc3Nx4/fXXqV27Nt27dwes2fOSkpKYNWsWTz75JBs2bOCnn37C3d2aZzohIYEvv/ySxx9/nFq1anH8+HFOnjzJgAEDbPX47bffCAwMLHMrkiRJkiRJt67qtOjoFQJ6OuDd8tZiO++WOvx7ONyWIAcgICCATp06kZqayuDBg4vdJi4ujvDwcLvXtGnTylT+zJkz6dWrF/3796d58+acOnWKn3/+GU9PT8A6/mDx4sWsX7/elkK5cIrkPn36MGnSJMaOHUuLFi04d+4cI0aMAKxjcUShBHX5XdcK0jpbu/8MGDCA0aNH06BBA3r06MGePXsICAgArE/8R44cSWhoKJ07dyYkJMSW3c1gMDB+/HiaNm1Ku3bt0Gq1LF++vMTznjRpEqNHj2by5MmEhobSp0+fUsfOFDZx4kSaN29OVFQUHTp0wNfXt0Imbp04cSKjR49m4sSJNGzYkCFDhhAVFcUXX3xR6n7PP/88S5YsuaVjl3YNdTodH330EV988QW1atWyBQHz588nNTWVDk/1Yvgbr/PCM/2o7uVVbPnCoqItFARZcnOpXbs206ZN4/XXX6dmzZqMGjUKjUbD8uXL2bdvH40bN+aVV17h3XffLfc5NW3alF9//ZUTJ07w0EMPER4ezuTJk6lVq5Ztm4ULF9KiRQsee+wxWrdujRCC9evX27rEhYaG8tlnn/Hpp58SFhbG7t277br0OTs788cff9CrVy9CQkIYNmwYI0eO5IUXXrBts2zZMoYOHVru+kuSJEmSdPMUUVon+btAbm4uCQkJ1KtXD8eSniRfo5oFGactrG+RgvkmxgTrnKHrPi/c6mvR6Kr2xJZlpZoEqQftm3Q8muhIO2KGAt889/u16F2rTNxd4XJycmjQoAErVqywSwRxu6QfP41qNJa6jd6jGopWS17y9dTl+mruuNS5r7Kr9486evQojzzyCCdOnKBatWrFblOev2OSJEmSJJVNlbqz1OgU3Opr6bDOA51z+fbVOUOHdR4yyCkn1VzcMmEX5ABoneQ1vRVOTk58/fXXXLly5R85vqK98Z8SYTajdSrUopNTQZNb3cEuXLjA119/XWKQI0mSJElS5agyY3TyaXQKNdvp6brPi23900neW8ydeCHeLXVEfuMug5ybICyFIhoNqIXubTUO1mQR0q3p0KHDP3ZsRXPjQEctJtBR8/JQzWY0unv3T1GnTp3+6SpIkiRJUpV0Uy06n376KXXr1sXR0ZGIiIgis8EX1KFDBxRFKfLq1q3bTVf6VuW37HTZ6Um7Ve74dtQXST2tdQK/Tnrar3Kny05PGeTcpOISEZhzCo3Pka05dz2lhEQJBQmTGa2jgzUhQQGW7Hu/VUeSJEmSpNuv3I9RV6xYwauvvsrcuXOJiIhg9uzZREVFcfz4cWrUqFFk+zVr1tjNe5GcnExYWBi9e/e+tZrfovygxT/agTpPOCJUQV66QJit6Y8N7gqKRkE1CRSNglKlOvlVnMJd1xSdgqVQoKNzlIHO3a4sLTrCYgEh0Do5Ysm6PkjOnJOD3t21MqsnSZIkSVIVVO7b9w8++IChQ4cyaNAgGjZsyNy5c3F2dmbBggXFbu/l5YWvr6/ttXHjRpydnf/xQKcwIcB4RSUr0YLxisrdnaLhzlG465pGC5Zc2aJzzynDGB0A1WxBVyhFesGgR5IkSZIkqaKUq0UnLy+Pffv2MX78eNsyjUZDp06d2LFjR5nKmD9/Pk8//TQuLi7lq2kFU80CRQN/rjNyYm4OSdtMWAr0oNE6gk+knpDhTgT0dECoyK5rN6Fw1zVFC2qh5FyFuw1Kd5+ytOjAtYQELs5wJdm2zJydg1DVMpchSZIkSZJUFuUKdK5cuYLFYqFmzZp2y2vWrMkff/xxw/13797NkSNHmD9/fvlqWcFUizXN9NZn00nZV3wyAksuXNxk4uImk0xGcAsKz6FDMZdPI7uu3fUUzY3H6ACoJjM6l0KT3qoqlpxcdC7lTIUoSZIkSZJUitv6CHX+/Pk0adKEBx544HYe1o5qEVz61cT6FiklBjmFJe81s75FCpe2mKypkaUyK3K9Cr1V9DLj2r2gLOmlAYTZhEanQ+PoYLfclJFZGdWSJEmSJKkKK1egU716dbRaLZcuXbJbfunSJXx9fUvdNysri+XLlzNkyJDy17KCqGZBxikLcY+nlXvCUHM2xD2eRsZpiwx2yqFwi07hsU9a2ZpzTyhroKOarA8X9K72yQfMMtCRJEmSJKmClSvQMRgMtGjRgk2bNtmWqarKpk2bbjgb+3/+8x+MRiPPPvvszdW0Aiga2PpsermDnHzmbNjWP/2uzsA2cOBAevToUenHmTp1Ks2aNSsyRqdw4KN1uPMCnbNnz6IoCgcOHPinq1Iu/fv3Z8aMGbb3devWZfbs2bfl2OUZowOgK5RlzZKTi5pnqvB63Qnmzp1LdHT0P10NSZIkSapyyn3L/uqrrzJv3jwWLVpEfHw8I0aMICsri0GDBgEwYMAAu2QF+ebPn0+PHj3w9va+9VrfBNUkSPzWWObuaiVJ3mvmz7VGVNPNt+oUN69QwVd0dDSKorBz585i9+/YsSNPPPEEcPsCl5ulFm7RKRzoyEQEdkwmE9OnT6d+/fo4OjoSFhbGhg0bbrjfwYMHWb9+PTExMbZle/bsYdiwYRVSrxsFf2WZRwdANVm/ADpnZ9s+W/fsxjOsEZfPJVZIXe80gwcPZv/+/fz222//dFUkSZIkqUop9zw6ffr0ISkpicmTJ3Px4kWaNWvGhg0bbAkKEhMT0RR6unv8+HG2bt3Kf//734qp9U3Q6BVOzM2pkLJOzM0h4Imbv0O/cOGC7ecVK1YwefJkjh8/blvm6upK27ZtWbBgAQ8++KDdvmfPnmXz5s18//33N33820kU6uZXuNufxnDntej8kyZOnMjixYuZN28e999/Pz///DM9e/Zk+/bthIeHl7jfxx9/TO/evXEt0CXMx8fndlTZqswtOtZWG0WjoK/mRl5Kmm1d3tV0hBAoyr31nTAYDDzzzDN89NFHPPTQQ/90dSRJkiSpyripTlijRo3i3LlzGI1Gdu3aRUREhG1dXFwcsbGxdts3aNAAIQSPPvroLVX2VqgWQdK2iukac3mbqcj8MOVRcF6hatWqoSiK3TJXV1eGDBnCihUryM6272cXGxuLn58fnTt3vtXTAMBoNBITE0ONGjVwdHSkbdu27Nmzx+54Hh4edvusXbu2yM3ozJkzqVmzJm5ubgwZMoTcXGuu7vwWnFFTh9B/TC8+XvABDTsHENzJl7HvxKBqrn8mRqORMWPGULt2bVxcXIiIiCAuLs62/ty5c0RHR+Pp6YmLiwuNGjVi/fr1AKSmptKvXz98fHxwcnIiODiYhQsXlnjeqqoya9YsgoKCcHBwICAggLfffttumzNnzvDwww/j7OxMWFiYXQr15ORk+vbtS+3atXF2dqZJkyYsW7bMbv8OHToQExPD2LFjbfNJTZ06tcQ6AXzzzTdMmDCBrl27EhgYyIgRI+jatSvvv/9+iftYLBZWrVpVpHtU4a5riqLw1Vdf0bNnT5ydnQkODmbdunW29aVdw3r16gEQHh6Ooih06NABsLYaPfroo/j630dAZATdBj/HwfhjdvXwDGvE12tW8ezLMdRs2sh2XL1HNRLPnyf6eWtrcJ1WzdFoNAwcOBCADRs20LZtWzw8PPD29uaxxx7j9OnTtnLzW5nWrFlT4ucEsHXrVh566CGcnJzw9/cnJiaGrKwsu/MeMGAAnp6eODs706VLF06ePGlbn98Ns6DZs2dTt25d2/u4uDgeeOABXFxc8PDwIDIyknPnztnWR0dHs27dOnJyKuZhiyRJkiRJN3YXjzYpn8wEi908ObfCkgMZCYXzJlesfv36YTQaWbVqlW2ZEIJFixYxcOBAtGXsKnQjY8eOZfXq1SxatIj9+/cTFBREVFQUKSkpZS5j5cqVTJ06lRkzZrB37178/Pz47LPPrlX6+nZb9/7K2fNn+G7uf/lkynyW//A1Xy9fZFs/atQoduzYwfLlyzl06BC9e/emc+fOtpvOkSNHYjQa2bJlC4cPH+add96xtWBMmjSJY8eO8dNPPxEfH8/nn39O9erVS6zz+PHjmTlzpm2/pUuXFkmb/sYbbzBmzBgOHDhASEgIffv2xXxtjElubi4tWrTgxx9/5MiRIwwbNoz+/fuze/duuzIWLVqEi4sLu3btYtasWUyfPp2NGzeWWC+j0Yijo31roZOTE1u3bi1xn0OHDnH16lVatmxZ4jb5pk2bxlNPPcWhQ4fo2rUr/fr1s33WpV3D/PP65ZdfuHDhAmvWrAEgIyOD5557ji1xcWz8Zin1A+rw1MjhZBQIJADemfs5PaKi2Pqfb+nSpQv9+vUj3ZiLf0AAX78/G4A93/3IqV17mDNnDmBNYPLqq6+yd+9eNm3ahEajoWfPnqiqald2aZ/T6dOn6dy5M7169eLQoUOsWLGCrVu3MmrUKNv+AwcOZO/evaxbt44dO3YghKBr166YTGV7MGI2m+nRowft27fn0KFD7Nixg2HDhtk9DGjZsiVms5ldu3aVqUxJkiRJkiqAuMvl5OSIY8eOiZycnFK3u7IvT3ytXKqwV/L+vAqp/8KFC0W1atWKXff000+L9u3b295v2rRJAOLkyZO2Zc8995zo3r17mY9XcPvMzEyh1+vFkiVLbOvz8vJErVq1xKxZs0qs37fffisKfnVat24tXnzxRbttIiIiRFjTMHFlT564sidPPN2tv/D3qyMu7cyxLev+aC/Rp08fIYQQ586dE1qtVpw/f96unI4dO4rx48cLIYRo0qSJmDp1arHnFR0dLQYNGlSma5Ceni4cHBzEvHnzil2fkJAgAPHVV1/Zlh09elQAIj4+vsRyu3XrJkaPHm173759e9G2bVu7bVq1aiXGjRtXYhl9+/YVDRs2FCdOnBAWi0X897//FU5OTsJgMJS4z7fffiu0Wq1QVdVueZ06dcSHH35oew+IiRMn2t5nZmYKQPz0009CiNKvYf41+f3334tdr1osIvXgUZH8+2Hh5uIiln30qUg9eFSkHrRetzFDX7C9T09NtR03NylZfP/VQgGIs7/tEKkHjwpTZlaxx0hKShKAOHz4sF2dSvuchgwZIoYNG2ZXzm+//SY0Go3IyckRJ06cEIDYtm2bbf2VK1eEk5OTWLlypRBCiClTpoiwsDC7Mj788ENRp04dIYQQycnJAhBxcXHF1jufp6eniI2NLXZdWf+OSZIkSZJUdlWmRUfvXrH9/nVulT+OYPDgwWzZssXWXWfBggW0b9+eoKCgCin/9OnTmEwmIiMjbcv0ej0PPPAA8fHxZS4nPj7ervsiQOvWrYukkm4Q2NCuJcq3ph+XL18G4PDhw1gsFkJCQnB1dbW9fv31V9v5x8TE8NZbbxEZGcmUKVM4dOiQrawRI0awfPlymjVrxtixY9m+fXup9TUajXTs2LHU82ratKntZz8/PwBbfS0WC2+++SZNmjTBy8sLV1dXfv75ZxITE0ssI7+c/DKKM2fOHIKDg7n//vsxGAyMGjWKQYMGFRn3VlBOTg4ODg5lGttSsD4uLi64u7vb6lOea5jv0qVLDB06lJAGDQiIjCCgzQNkZmfz18ULdts1Cmlg+9nJ4GA7rsHTo8j4npzzFxFCcPLkSfr27UtgYCDu7u62rmKlXePCn9PBgweJjY21+05FRUWhqioJCQnEx8ej0+nsvr/e3t40aNCgzL8DXl5eDBw4kKioKKKjo5kzZ47dODzbeTs5FemKKkmSJElS5akygY5rPW2FZfjSOoFbvYrpOlaajh07EhAQQGxsLOnp6axZs+a2z0Ok0WgQhSKWsnbpKUyvs899odEqtm5ImZmZaLVa9u3bx4EDB2yv+Ph4W1em559/njNnztC/f38OHz5My5Yt+fjjjwHo0qUL586d45VXXuHvv/+mY8eOjBkzpth6ODk5la2+er3t5/wgIr++7777LnPmzGHcuHFs3ryZAwcOEBUVRV5eXoll5JdTuOtVQT4+Pqxdu5asrCzOnTvHH3/8gaurK4GBgSXuU716dbKzs4sc+0bnVLg+5bmG+Z577jkOHDjAnDlz+O/iZWxZuRovD48i35GCn71qMtuOq2g1GLw87La15OaSeymJ6OhoUlJSmDdvHrt27bJ1+yrtGhf+nDIzM3nhhRfsvlMHDx7k5MmT1K9f/0aXCyjb78DChQvZsWMHbdq0YcWKFYSEhBTJmpiSknJLCSJUs5BzeEmSJElSOVSZQEejVfCJ1N94wzKoEalH0VZ+i45Go2HQoEEsWrSIpUuXYjAYePLJJyus/Pr162MwGNi2bZttmclkYs+ePTRs2BCw3nhnZGTYDd4unGI4NDS0yNiDnTt32o3PKU7BaxgeHo7FYuHy5csEBQXZvQpORuvv78/w4cNZs2YNo0ePZt68ebZ1Pj4+PPfccyxevJjZs2fz5ZdfFnvc4OBgnJyc7OaDKq9t27bRvXt3nn32WcLCwggMDOTEiRM3XV5hjo6O1K5dG7PZzOrVq+nevXuJ2+YPlD927FiJ25RVSdfQYDAA1pasgrZt20ZMTAxdu3alYQNrK1RyamqpxxCFggSX6taU85YCAeCFE6c4fvw4EydOpGPHjoSGhpJ6g3KL07x5c44dO1bkOxUUFITBYCA0NLTI2Jnk5GSOHz9u9ztw8eJFu2CnuDTb4eHhjB8/nu3bt9O4cWOWLl1qW3f69Glyc3NLzZxXWO4VlaPvZrHxX6ks90xiicH6WuGdxC+dUzn2QTbGlJKDZkmSJEmq6sqdXvpupZoEIcOduLjp1jOvhQx3QjUJNPrKD3YGDRrE9OnTmTBhAn379i22NeLq1atFbry8vb3x9/cvtWwXFxdGjBjBa6+9hpeXFwEBAcyaNYvs7Gxby1FERATOzs5MmDCBmJgYdu3aVSSr3ksvvcTAgQNp2bIlkZGRLFmyhKNHj1IvoORWCMBu4tWQkBD69evHgAEDeP/99wkPDycpKYlNmzbRtGlTunXrxssvv0yXLl0ICQkhNTWVzZs3ExoaCsDkyZNp0aIFjRo1wmg08sMPP9jWFebo6Mi4ceMYO3YsBoOByMhIkpKSOHr0aJlbzIKDg1m1ahXbt2/H09OTDz74gEuXLtlujm/Wrl27OH/+PM2aNeP8+fNMnToVVVUZO3Zsifv4+PjQvHlztm7dWiQ7WHmUdg1r1KiBk5MTGzZs4L777sPR0ZFq1aoRHBzMN998Q8uWLblwJJ6JM2fg5Fh606lqtp/Lqm7duiiKws9bfuXRtg/h6OiAh7s7Xh4ezP3kU/z8/EhMTOT1118v9zmNGzeOBx98kFGjRvH888/j4uLCsWPH2LhxI5988gnBwcF0796doUOH8sUXX+Dm5sbrr79O7dq1bcFlhw4dSEpKYtasWTz55JNs2LCBn376CXd3dwASEhL48ssvefzxx6lVqxbHjx/n5MmTDBgwwFaP3377jcDAwDK1IpmzBQcmZnL80xzrPFQCu4cGeamCCxtNXPjFxO8TMrk/xpmwaS7onO6ttNySJEmSdKuqTouOXiGgpwPeLW8ttvNuqcO/h8NtCXIAAgIC6NSpE6mpqQwePLjYbeLi4ggPD7d7TZs2rUzlz5w5k169etG/f3+aN2/OqVOn+Pnnn/H09ASs4w8WL17M+vXrbSmUC6dI7tOnD5MmTWLs2LG0aNGCc+fOMWLEiBs16KAU6v23cOFCBgwYwOjRo2nQoAE9evRgz549BAQEANbWhJEjRxIaGkrnzp0JCQmxZXczGAyMHz+epk2b0q5dO7RaLcuXLy/x2JMmTWL06NFMnjyZ0NBQ+vTpU+rYmcImTpxI8+bNiYqKokOHDvj6+lbIxK25ublMnDiRhg0b0rNnT2rXrs3WrVuLpPgu7Pnnn2fJkiW3dOzSrqFOp+Ojjz7iiy++oFatWrYgYP78+aSmptK8eXOGjR3NC8/0o7qXV6nHESb7QKd27dpMmzaN6R/PJuSRdoz999toNBrmv/Me+/buoXHjxrzyyiu8++675T6npk2b8uuvv3LixAkeeughwsPDmTx5MrVq1bJts3DhQlq0aMFjjz12bWyZYP369bYucaGhoXz22Wd8+umnhIWFsXv3brsufc7Ozvzxxx/06tWLkJAQhg0bxsiRI3nhhRds2yxbtoyhQ4fesL5XT5hZ1ziZ+I9yUE2ASvEto8K6Ts2DYx9k833TZK4ev7XJkCVJkiTpXqOIwp3P7zK5ubkkJCRQr169Iml5C1PNgozTFta3SMF8E2OCdc7QdZ8XbvW1aHTy6emNZP9tIefvkrvWuN+vRe9aZWLtSpWTk0ODBg1YsWIFrVu3/kfqkJmQiDkj84bb6VxdcA2sU2S5EIKc8xfJSynaRU3n4oxjLV90ThU00O42Onr0KI888ggnTpygWrVqxW6Tm5vL6eNn+KO/BznxOtv8U2WlaK0JVzpv86Ta/VWmoV6SJEmSSlWl7jI1OgW3+lo6rPNA51y+fXXO0GGdhwxyyuFGN2sag7yOFcXJyYmvv/6aK1eu/GN1ULRl+3OimopveVAUBafavkWSEwCYs7LJPJlAVuJ5zNl316SbFy5c4Ouvvy4xyAHrhMa5SSqWbFHuIAesv2umdMH/otMw59zVz64kSZIkqcJUuUd/Gp1CzXZ6uu7zYlv/dJL33ri7h3dLHZHfuMsgp5xKvWFTQFMxuSGkazp06PCPHl8pJQV2QYW7rtmVoSg41fZDYzCQezEJ+35bAlPaVUxpV9E6OaGv5o6+mhtaB8OtVbySderU6Ybb5F5SUc03fjhQGmGBzASVQ1OzaP6O680XJEmSJEn3iCrVopMvv2Wny05P2q1yx7ejvkjqaa0T+HXS036VO112esog5yaIUlLhavSUad4X6e6haMqWcl2oFlRLyXf0iqLgWKM6LoEBaAzFR8OWnBxyL14i4/gp0o+fIvvPvzGmpGHJzUWod1eLhmoSGFMrKHuaCvEfZVdceZIkSZJ0F6tyLTr58oMW/2gH6jzhiFAFeekCYQZFBwZ3BUWjoJoEikaxyxAmlU1pT6dvVzIH6TYqY9c1uNaqoy09MNK7uqALqY8xKZncpGQoYf4h1ZhHnjEPUtOsCxQFjYMBrYMDGoPe+tIbUPQ6NDodik57RwXZxivqDVOxl4eaB2cW5RL6cjn750qSJEnSPabKBjr5hEYFtAgEmZZUjHlGHBQHPPFEQbGtl8pPLS3QubN7G0k3oaxd1wBUkwmto0OZynSs6YPB25O8lDSMyanX5uEpJVARoOaaUHNLSiWvoGi11oBHo7HWW6tF0Vp/VhQFCv977WX/s7UsFMAWOBVaXuCYJVU5L+2Gl6Hc/t6YJwMdSZIkqcqrsoGOqqooisIff/zB3r17SUxMxFxgfg+dTkdAQAAtW7akYcOGCCHQlONGTgJhKa3r2p3zRP1uJIRAqIAK4tqLa8vEtZTE+f8iQOT/q4qiy0Qx23N9u/wfC87nIgr8nF+GMLuimgr2AVWK/1lAxiktKCbbe1uZBbYp+nO1ay+pVAKSd9/6fGGSJEmSdLerkoGOqqqkpKSwevVq/v7772K3MZvNnDlzhjNnzlCrVi169eqFl5eXDHbKofSua7evHncCoQrrYHOzNQAUqvX6CIt13fWfr623/cy1YEZYA4ECgcydRwOUranuVgbdSzdmTBYIIe6oLnqSJEmSdLtVuUBHVVXOnj3L0qVLMZnK9tTz77//Zu7cuTzzzDPUrVtXBjtlIETpaXLv9tTSQhWoJutAcjXPOkeTuBbI5P9sDWysAQ5ybLgkSZIkSdJtVaXu2PNbcsoT5OQzmUwsXbqUlJQULKVkjCqrDh068PLLL99yOXeqG7U6KHqIi4tDURTS0tJK3G7q1Kk0a9asoqt3Q6pZYMpUMSarZF+wkJVoIf2UmbRjZlIOmkjZbybtsJn0PyxknrGQnaiS87dK7mWVvBSBKV1gybYGQTLIkW43B29FtuZIkiRJVV6VatFRFIXVq1eXO8jJZzKZWL16NcOGDbvluqxZswa9/vb235o6dSpr167lwIEDlX6sG04WegeM0RFCYMkF1Siw5Fp/tv5rbZG56yhYswNqro2NV65lC1Ty39v/rCj52ypF1tl+psD7Aj9ff399kL0wmci5dBml+AE2du81Bh3O/rXs6l7wX6XgMruFJZx3CcvLtKwMyh4ziAJjjUQxY42KRv+ZCYK8rJurV7EU8H6givUNlSRJkqRiVJlAx2Kx8Mcff5Q4Jqes/v77b+Lj42nQoAHaG6THLY2Xl9ct1eNOd8NA5zZ/84Swtq6Ys8T1V7YAFfJMeRj0ty8NnKK99tIoBX4GRavYfkYLGi1wLbW5LYDJ/1kpZvk//ATfYlQwJmWUaVuhatC53outDuU/H4OHheyKDHSAWo/KtIaSJEmSVGW6rmm1Wvbu3VshZe3Zs+eWghyw77pWt25dZsyYweDBg3FzcyMgIIAvv/zStu3Zs2dRFIXly5fTpk0bHB0dady4Mb/++qttm9jYWDw8POyOsXbtWtuNZGxsLNOmTePgwYMo19LkxsbG3rCeaWlpvPDCC9SsWdN23B9++MG2fvXq1TRq1AgHBwfq1q3L+++/D1zPuGbMMzLt4/E07RZIrTautOoZyuLvFqIUCHT27dtHy5YtcXZ2pk2bNhw/frzUOn311VeEhobi6OjI/fffz2effWa3fty4cYSEhODs7Ey9OoGMHfkGl/flkHbYTOYZC9PenErbx1vwzZoFNO8eQu1ItxtehxJpQOOooHNVMHgoOFTX4Oirwfk+DS51tbgFaXG/X0u1xjo8m+nwaqHDK1yPZ1M9Ho11VAvV4R6iwy1Ih2s9LS4BWpzv0+Lsp8WxhhbH6hocvDQYPDQY3DXoXTXonDXonBS0DgoavYJGe2cEDEo55tFBVRFmmZEAwKG65qZbmoqjMUDgc4433lCSJEmS7nFVpkVHVVUSExMrpKw///wTVVUrNCnB+++/z5tvvsmECRNYtWoVI0aMoH379jRo0MC2zWuvvcbs2bNp2LAhH3zwAdHR0SQkJODt7X3D8vv06cORI0fYsGEDv/zyCwDVqpWeqldVVbp06UJGRgaLFy+mfv36HDt2zBbk7du3j6eeeoqpU6fSp08ftm/fzosvvoi3tzfP9BwAwItTBrH38C7+PeYDGgU3JfHvs6RkXrG7MX/jjTd4//338fHxYfjw4QwePJht27YVW6clS5YwefJkPvnkE8LDw/n9998ZOnQoLi4uDOg/AFOGwMHiwkeTvqJmNT+OnTrCq2+PwEnrSsyAMbZyEv46zQ//+5bYWSvQakoIWhWswYTBmjxBo7/2r8Ha9U5juNYacwcEGXeCG8+jo1Cw65ZqMqHRV5k/QSXS6BUcPDWQVBGFQWiMs7U8SZIkSariqsxdRmpqqt08ObfCZDKRmppapgCjrLp27cqLL74IWFskPvzwQzZv3mwX6IwaNYpevXoB8Pnnn7Nhwwbmz5/P2LFjb1i+k5MTrq6u6HQ6fH19y1SnX375hd27dxMfH09ISAgAgYGBtvUffPABHTt2ZNKkSQCEhIRw7Ngx3n33Xfo+PoBT507w3S+rWP3JT7SP6AhA3fsC0bnYBwZvv/027du3B+D111+nW7du5Obm4uhY9Kn0lClTeP/993niiSes5dWty+Hfj/LZnLk81uQZUOGlp8fbtg+oVZdT507w7caVdoFOnimPT6ctoLqnD4reGtBoHRW0jlz791ogo5FBTJnlT6YpSshCUWidmmcCZ6fbVLk7m2NNDZoz1sD5ZilacK2nJWyaS8VVTJIkSZLuYlUm0DEajRVaXl5eXoWW17RpU9vPiqLg6+vL5cuX7bZp3bq17WedTkfLli2Jj4+v0HoUdODAAe677z5bkFNYfHw83bt3t1sWGRnJ7NmzMedZOHLiIFqtljYt2tltoxT61hU8dz8/PwAuX75MQECA3XZZWVmcPn2aIUOGMHToUNsElmaLGXfXarbsZt/+dyXzVnzK2b/OkJWTidlixs3F3XZsrYNCwH11qPeALzpn5Y5IjHAvUG4Y6GA3Fl+9yaQg9yKNVsHRR4PW2TpOq7zzDCla0LsrPLyuGlpH+X2WJEmSJKhCgY6Dg0OFlmcwVOxg38IZ2BRFQVXLnpdYo9EgCt1g3mx2uXxOTjf/tF1YBI4Oxe9fOLAoeO753cCKO/fMzEwAPv73FzSt29IubXN+97M9h3YyfPJzjBs2mYcf/Bcenu58F/cfPv7qQzwa69A4gIO3BtdqLhiqye49FU1RlDLPZarmyUCnII1Boe1id7b1KVYQPwAAboBJREFUyCUrUS17WnINuNTV8MgPHlRrUGX+pEuSJEnSDVWZOz1PT090uoq5CdDr9Xh6elZIWeWxc+dO289ms5l9+/YRGhoKgI+PDxkZGWRlXU/fVDiNtMFgKNccQE2bNuWvv/7ixIkTxa4PDQ0tMpZm27ZthISEoEFLw6DGqKrK9n1b7La5mYxrwiJws1TH16cWp+JPE1g7iED/6686tesBsPvQDvxr1eGNSW/Q4ckHaPFYKBeu/mkdb+N4Zwzav6eVdn0LBeJqBbeK3guqheh4/Ig3oTFOaPRY/0KXlCZbsSYeaPiqM9GHvGWQI0mSJEmFVJn/GTUaDQEBAZw5c+aWy/L396/QRARl9emnnxIcHExoaCgffvghqampDB48GICIiAicnZ2ZMGECMTEx7Nq1q0hWtbp165KQkGDrkubm5lZqS1f79u1p164dvXr14oMPPiAoKIg//vgDRVHo3Lkzo0ePplWrVrz55pv06dOHHTt28Mknn/DZZ58hLNbxMU9360/Mm8NsyQj+vJhIhnKFZ4c9XaZzFkIgLJB21IyaB+OGTWbCe6/g7lqNR1r/izyTkQPH9pOek8qrY16labsG/PVpIut+/Q+tWrXixx9/5Ntvv73pay6VU7kCHdmiUxyds0LLD9xoPMGF07G5XNho5MoeM6Y06/UzeCp4P6Cn1qMG6g90xMGryjyvkiRJkqRyqTL/Q1osFlq2bFkhZbVq1apcLSMVZebMmcycOZOwsDC2bt3KunXrqF69OmCdl2fx4sWsX7+eJk2asGzZMqZOnWq3f69evejcuTMPP/wwPj4+LFu27IbHXL16Na1ataJv3740bNiQsWPH2s69efPmrFy5kuXLl9O4cWMmT57M9OnTGThwIOq19NLvvv4J0R2f4LV3YmjduwmvvD2CbGPZJg1RLYK8NIFqtM6BA9C/x2A+nDiXZd8vol3f5jw+vBP/+d83hLauj1NNLT2e6M4rr7zCqFGjaNasGdu3b7clS5DuLKrJVKS7pXSdY3UNjcY40+lnT55O8aFfnvXVJ9mHTj950PBVZxnkSJIkSVIpFHGX32nk5uaSkJBAvXr1is3SVZAQgi+//PKWJg2tVasWw4YNu61doM6ePUu9evX4/fffadas2W077q1IP3X9CXRhbiFaDO6l36BZcgUZpy1Ycoovw6G6BqdaGrQG2RXtTnI1/iSiHGPD3EOD0RQan1YVlefvmCRJkiRJZVOlHgcKIejVq1eRgf9lpdfr6dWrV7mSBFRVpWWN0uhKD07yrqpcjTcXG+To3RSqNdTiWlcrg5y7QeEHAoXey+5rkiRJkiRVlioV6Gg0Gry8vHjmmWfKHezo9XqeeeYZvLy8bBNm3u2WLFmCq6trsa9GjRrdUtmlBjqlXHpTukrGKUuR/RUtuNbX4haiRedcpb62d5fCDcSFAhulUEIQi1EmJJAkSZIkqXJUmWQE+TQaDXXr1mX48OGsXr26TN3YatWqRa9evfDy8vpHkhDUrVu3UsYyPP7440RERBS77mZbvfIJS8n1LTyPTj5ztkrGaQuF8xNrnRTc6mvl/CB3g0LfUwX7dNOKVoMo0IgjM69JkiRJklRZqlygA9Zgx9PTk2HDhhEfH8+ePXtITEzEbDbbttHr9fj7+9OqVStCQ0NRVfUfCXIqk5ubG25ubpVSdkktOoqOYsc3WYyC9JNFW3IMngoudbVotDLIuRsUCcgL91wr9DukyhYdSZIkSZIqSZUMdABb97MGDRrQsGFDVFUlNTWVvLw8DAYDnp6eaDQaLBYLiqLcM93Vbof8lNDFKW58jhDWxAOi0HANg6eCa6BWzn1zN7lRy2ORMToy0JEkSZIkqXLcM4HOzXbtyg9gNBoN3t7eJa6XykFQpPtZvuK6reVeUrFk2++gc1NwrSeDnLuJUNUbBjpKoSYeizEPIUSV/5zv8uSXkiRJknRHuusDHb1ej6IoJCUl4ePjU+VvmO4EqkmQh7n4lYpCbu71r50lT5B+3n5brUHBqbYWY14JZUh3JNVsJk/YZyRUVAVRYJnFbMZScBuLSnZGBlqD4XZV844jhCApKQlFUW55bJwkSZIkSdfd9fPoAGRmZvLXX3/Jp6J3CNUkyP67+BTcelcFB+/r4zRyL6uYC6WRdvLVoHWQAevdRjWbyb2YZLdM0SgI9frnq9HrEBaL3TKH6l5oHR1uWz3vRIqicN999+Hq6vpPV0WSJEmS7hn3RKADYLFYMJVjokKp8qQeMbGld3qx64KHOdLwFRcAUn438dsz9tvVe8aRppNcKr2OUsVLP36KvSNet1umaLUIy/UBWwZPDxx9a5Aef8K2LGj4cwQ8FX3b6nkn0uv1spusJEmSJFWwu77rWj6tVitvFO4U6RryzhXfBcfR0ck28/vJD4122zn5aWg2zhOD472V3a6qyMjIwnz+UqnbWC5dwev+YFIKbJd1KB7HAb0ru3qSJEmSJFUx8o5SqnCmqyU3Ejr6WL9yGQkW/lxjtFsX+oozBnf5lbxbmdKzbriNMFtwredvtyzt0LHKqpIkSZIkSVWYvKuUKpwpvfjxOQAO3taxN398lE3BMek6V4XgoY6VXTWpEpnSM8q0nbN/bbv3GScTMGfnVEaVJEmSJEmqwmSgI1U4U3rJLToO1TWoFsHZZbl2y4OGOGKoJr+OdzNzRmaxyzWFEg0YqnuiFOxmqqpcPfJHZVZNkiRJkqQqSN5ZShWu1EDHW8OVnSZyL9tv0+BFp8qullTJSmrR0bnZZxKzZOXg1iDQblnKvkOVVi9JkiRJkqomGehIFa70Fh2FP7/Ls1vm0ViLe/A9kxejyjKlF9+io3d1tnufl5yKV/Omdssux22vtHpJkiRJklQ1yUBHqnAlBTqKDnSu8Oda+yQE/t2r9hwq9wpTCV3XtE72rXXG5FRqPNzGblnKnoOYrpZtjI8kSZIkSVJZyEBHqnB5GcUnI3Dw1pB5RiXjlMVuuQx07g3mErquaZ3sk0zkpaRSvU0rNA4G2zJhsXD5t52VWj9JkiRJkqoWGehIFa6kFh0Hb4UrO+wndXWsqcGrhey2di8oaYxOwYAGwHglBZ2zE94PNrdb/ueqHyutbpIkSZIkVT0y0JEqXImBTnUNSTvNdst8WutQFOV2VEuqZCWN0dHo7ANZY3IqALW6dLRbfjluO5ln/6ycykmSJEmSVOXIQEeqcOaMklp0NFzZZd+iUz1CfzuqJN0GJbXoKFr7PzN5KdZAp3b3KPTubtdXCMHZr1dVWv0kSZIkSapaZKAjVbiSWnT07pB6sFCLzoMy0LlXlDhhaKEWO+MVa6Cjc3bC/6lou3Xnlq4h+68LlVI/SZIkSZKqFjk4QqpweenFJyMQZhAF8hAoWvBqKQOde4GwWDBnZJWw0j7wzUtJRagqikZDved6c2b+Mts2lpxcDk95lwe+ev+O7NJoylRJPWAmeZ+ZlP1msv6yYMkRKApoXRTc6+vwaqHDu4WOao10aA133jlIkiRJUlUhAx2pwpXUomPJtV/uFqxF7yJvBO8F5szsEtcJs6XIe1N6BgaPargE3Eedfk9wbvFq2/pLv/zGhZ82U6vrI5VW3/JQzYK/fsjj+CfZXIwzgQpoQNFYg/eCLsWZEF9Yf9YYoE5vBxq86Ez1B+VYNEmSJEm63WTXNalCWYwC1Vj8OlOhsTvVQmWcfa8osdsaoOaZiiwzJqXYfg4d+yKG6l526w+8Np20w39UXAVvgsUoODIzi9UByfz6xFUu/XotyAFQiwY5YL9MzYOzK4xsiEzlh7AUEpbmIkTJk+lKkiRJklSxZKAjVajCwUxBxiuFAx1tZVdHuk1KC3QsOTno3F3tlhmvXA90DNXcaTz5Vbv15swsdg58iaxzf1VsRcsoea+JH5ql8PsbWeRetEY3wnKDnYqRH/ikHbOw9dl0/tftKtnnb6IgSZIkSZLKTQY6UoUqLdDJuWA/dke26Nw7TFdLDnTMWdk4FGqxMV5Jtntf+/F/USv6UbtleVdS2PHMSK4ePV5xFb0B1Sz4/Y1M1j+Yap3YtqIaYK599S/8ksd3oSmc/jqnggqWJEmSJKkkMtCRKpSphEQEADkXCwc6skXnXlFai44pIwuH6t52ywq26AAoikL4+1Op3rql3fLsv/7mt55DSPzP9xVX2RJYcgW/9rrKkZnZ1q5pldDwIsxgzhJsH5jBwWlZsiubJEmSJFWimwp0Pv30U+rWrYujoyMRERHs3r271O3T0tIYOXIkfn5+ODg4EBISwvr162+qwtKdraREBECRp+PuwTLQuVeUFugU26KTlFxkO62DgVZfvot7w2C75arRyIEx0/l99FRyi9mvIljyBJt7XOWvH/MqrhWnJNfKPzQtiwOTSshUJ0mSJEnSLSt3oLNixQpeffVVpkyZwv79+wkLCyMqKorLly8Xu31e3v+3d+fxUVV3/8A/997ZM0kme0II+75vgkDdCgouuPWxtLVCqUtVbK1onz7ax7X+StVqtRa1WhWrPu5LrSIuICAKyiqLENmRkH1PZr/3/P6YZJI72WaSmSQTPu/Xa14z99xz75wJl5n5zjnne7w499xzcfToUbz55pvIz8/HM888g9zc3C43nnqfthYLDWVOl2BMZIdiX+GrqWtzn9pqoFPRal1jkh2n/+txpEwe12Lf929+gDVnXob9f30a/vq2s7xFSgiBLxbVoPBTb1OygW6y509O7Hs0eq+FiIiImkT8TfORRx7BtddeiyVLlmDMmDF46qmnYLPZ8Nxzz7Va/7nnnkNFRQXeffddzJ49G4MGDcJZZ52FiRMndrnx1Pt42+jRkUKm49gHszenL2mvRwcAjMmJuu3QoWvNWTLSMPv1pzH4Fwtb7FOdLnz36DP49MzLcPDpl+Apr+xcg5s5/C83jr3u6fYgp9G2/65D5a5WUrgRERFRl0QU6Hi9Xmzbtg1z585tOoEsY+7cudi0aVOrx7z33nuYOXMmli5diqysLIwbNw5/+tOfoKrMPNQXtTV0TTHrtxno9C0dBjr2BN12R0PQZJMR4++9DVMf/39QbNYW+71lFfj2/z2Gj2dcgC3X/x7Fn30B0Yn3FGeBiq9/XQf05BI3AvhiUTU0H+frEBERRVNEgU5ZWRlUVUVWVpauPCsrC0VFRa0ec/jwYbz55ptQVRWrVq3CnXfeiYcffhj3339/51tNvVabQ9dCrjT7IAY6fUl7Q9cAQEnQByutzdFpTe7F5+GHa99A3hULgFYW3BQ+Pwo/XIuvfvFbfDL7Yuy++y8oXrMRfmfHWc2EENh0XS1Ul4j9vJz22qEClbtV7HmAQ9govgkh4KsXEBqDdiLqHWKe31fTNGRmZuLpp5+GoiiYOnUqCgoK8NBDD+Huu++O9dNTN2sz65qQ0PzbJHt0+hZfdY1uW1IUXQ+LwRoS6JSVQ2gaJLnj31qsOVmY/Je7MPTan2Hfn1egeO3GVuu5C0twZOVrOLLyNcgmI1KnTUTGWTORecYMJI4cCtmgf7sr+8qPkx96w32JsSWAPcvrMeo3VpiSOHeN4oe3SsOhlW7kP+VC3UEVQgMgAZYsGcOWWDDiV1YkDOD7PRH1jIgCnfT0dCiKguLiYl15cXExsrOzWz0mJycHRqMRitL0Rjd69GgUFRXB6/XCZDJ1otnUW7W1jo7m1ZcnDOCXub4ktEdHtpihNksYIFv0YxeFX4W3shrmtJSwnyNp5DDMeP6vKN+yE0dfeguFH66F5mk9UNG8PpR9uRVlX27FvuWPQ7GYkTRmBBzjRyN5/Cg4xo/G/r+nQzI0LerZ01Q3cOQlN0beaOvpphB1yO8U2Pa7Whx8zg2t8b+haLp3F2nY+6ATe/7sRP8FJsxYkQhbLgMeIupeEX3bNJlMmDp1KtasWRMs0zQNa9aswcyZM1s9Zvbs2Th48CA0remX/u+++w45OTkMcvqgtuboaCHfR215/MDrS0J7dJSQwEaS5RZDz9wlZZ16rrTTJmHqY3/EeVs+xPj7fofksSM7PEZ1e1C5fTeOvPA6dt52H9bO/RWO/p+z1wQ5jfY/7uLaOtTreco1fHRmJQ78ww3Ng0CA08plK9RAecEqLz44rRJV3/ay/3BE1OdF/LP6smXL8Mwzz+CFF17Avn37cMMNN6C+vh5LliwBACxatAi33357sP4NN9yAiooK3Hzzzfjuu+/wwQcf4E9/+hOWLl0avVdBvYavLrwvaQl57NHpS0KTERhCEgiobg9MqQ5dWbjzdNpiSk7C4MU/xlmrXsJZH76MUbfdgNTpkyEZOg6ifc4fotetlyyAmnwVZZv5ZZB6L79LYM1FVaj8xh8YphYG4Qc8pRo+mVOJ+hNMRERE3SfiOToLFy5EaWkp7rrrLhQVFWHSpElYvXp1MEHB8ePHITcbd5+Xl4ePPvoIt9xyCyZMmIDc3FzcfPPN+P3vfx+9V0G9RrsLhjYwJkowJfeyL5nUJb7qkEAnUZ9lzV9XD0tmOrzN0kF3tkenNcljRiB5zAiM+PUv4autQ9mXW1G6YTNKNmyG83hBi/p+zxj0aAaCNkgyULLRi4yZxp5uClGr9iyvR/kWf8Tp2IUKeMoFNl9bizkfOmLSNiKiUJ1KRnDTTTfhpptuanXfunXrWpTNnDkTmzdv7sxTUZwJJ9CxsTenT9F8fqghWc4Mdrtu219XD3NmGrDvQLDME8VApzljoh05885GzryzA89TXonqPftRtXs/qnfvQ9We/agpGAWg9w2fFELD8XeOwjGyAIYEGwx2GwwJCVBsFigWM2RL4F6xmMNK5EAUTapXIP8JV6fXnBJ+4OTHXtQe8iNxaMxzIRERxT7rGp1afLUdfwImcH5On9LaGjqmkAVC/XVOWDIzdGXu4tgEOqHMaSnIPGsmMs8KzCP0lGt4PaN7njtiQkb5FmDLjQ90WFU2GSGbTVBMZsgWExSzGbLZDCX42ATZYoZsMEA2GiEbDZCMBkhGY6DMZIBsCJTLBiNgUgL1GsuMBkgGA2SjAkgKJIMCSZEhKQpkxQAoMuSG7cA+A2RFBmQ5uN1YP3jfSopwih/H3/HAW9G1nlBJBr77hxtTH7R3XJmIqIsY6FBUtZV1rTlbLn+J7gwhBIQKaL5AFjvNB2g+Ac0buBe+wC+uwgfdPqEKaP7A0JHArfm2aCr3N+xTm+pCExACgbH4WsO9AIQmIBq2vZVOuKsWQwTnvMgo+2YYXJUj0bgS59G3RkA2GuGqzG0qe7M/nCW1gcn3ovE1IjixWTTL4NT636P5RuhO/d+tebmruJM/R3cToWag9uQrPd2MLmi4WODr6YZQLyRU4OA/XQx0iKhbMNChqApr6FofDXSEJuCtFvBWCfjrAjdfrRa4r2te1rStugVUN6C6mj12Nzx2hWy70RunlQAwAvixrqR8GwBMCG6XbWl8NCxY5t0HVO3reGFPIupbvFUCfpeAwcoePiKKLQY6FFX+MHp0rP3iY+ia3yXgKtTgKlThKtTgPKnBU6bBWyHgqdTgrRTwVDRsVwS2e2cgQkTUu/hqGegQUewx0KGoUT2B4VQd6Q09OkIIeMoFag+pqD2oou6QitrDKpwFgaDGdVKDt4pRCxFRLJiSGOQQUewx0KGoCWfYGtD9gY6rWEPFDh8qdvhRucuP2oOB4MZX3QcDGQmQTYBslCAbAdkISAYJsgGQFEBSpMC9AZAbHzfeDPptWZEAOTB5WJIReCwBkiwFH0MGnMe+R9WuvQh0Z2kwp6cgYXB/VGzdicYuLnN6CjLPmIET76wKlkESyLvioqY1d6SGc0rNHiPkcfB1hhRIbe9CyHZ9gYqjL3si/MN2Iwm4/FgaFHPv/yIoNA1C1SBUP4SqQVNVCFUD/P7APr/aUKYCmtYwz0xrmPulBepojduioV5gUpgQAlDVwFwwEXgeCK1hfpgamKTVMF8MQgTnYonAAc32ByaWBeeCaUK/H1rT8VrjOZpNGmt82PSgaYKYEM3mijUvC5lgJkLO2eIPGc5EtHaqtrnIbHTf4468NgM1BzMB0bX3cEu2DMXS+69vIop/DHQoasJJRAAA1tzYDV3zuwRKNvpQ8rkXFTv8qNjhh+tkz0w+N9glGO0SDIkN9w234OOEwE2xSFAsCNxbmz0O3TZLkM36IEY2NT6WIBkbgpNu9t3f38b+gieC21nn/AD9Lzsf2379t2BZ4tDBmPX8BXh/41OBL7MNxtx8OhwTxnRre73VWq8OdBKHKkjoHx/DO5sWXTX1aCuoe6RO9+Czi6u7dhIZGHm9teN6RERRwECHoiac1NKSAbCkR+/LuKYKVO7w4+QnXhSt8aLkCx+0KH+HVayArZ8Ca44MS6YMU6oEc6oMc6oEU7N7U0qg3OQIBDCSfGr8Yumr0n/xMTqSYLDrFwz11dVDUhRYstLhOlkcLHedLO72QMeULCNhkIz6o70v+5pkABcLpV6r3/kmWHNluAq69n9n2DWWKLWIiKh9DHQoasIZumbNlqMSAFTu8uPwv1w48n8euIo6/6ErGQD7IAWJw5TAL+kDZFj7KbD1k2HNCdyMSRLX/2iHr1q/jo4xOREGu01X5q93AgAsOVn6QKewGD0hfYYRzu89gRTavYjQgNQpfFum3klWJIy+2Ybtv6/r1Kg4SQEG/MgMW5wkpCGi+MdPVIqasDKuZXd+bLe3SsPB5904/C83Kr/xR3SsYgNSJxqQMskIx1gFicMNwcBGNjCI6QpvdY1u2+RIbtGj469zQggBW242KrftCpY3D3q6U/ZZJhx7vRcOX9OArLPYo0O91+hbrCje4MXJD70R/VAgGYDEIQpmPJnYcWUioihhoENRE84cHWtO5IGOt0bD/r+5sO8RZ1iZ0CQZSJtuQOYsI1KnGJE62YDEEUqPzF85FfhCAp3WenSgaVBdblhysnTFPdWjM+hnZmxdVhtYm6i3kIHUSQakTmKgQ72XrEg489VkbFhYjYJV3rB6diQFSBquYM5HDphTej7rJhGdOhjoUNSEO3QtXKpHYN+jTux9yAlvRfvnThqhIGeuCdlzTcg+2wiTgx+m3aXl0LUkGOwtVz3319XDGhroFBTFtG1tMSXJGLrYigPPuiAi6xyMHQ0Y9WtO0qbez2CTcPa7yfj2ISf2PeqEu0RAUqDv4Wn4XUmxAsOWWDHp/gSYkvm+TETdi4EORU1YPTphBjpVe/3YeGUNKne1/S3Ulitj8M8tGHKVBY4xvJR7SmiPjik5CYYEW4t6/rp6WPuFBDo9NHQNAEbcaMV3/3D12POHMiZLGPhjTtKm+CArEsb9TwLG3GrD9+958N1TLlTvUwMLgdqAhDwFw35pxeArzTAmMsAhop7Bb4cUNeENXWt/EqoQAvsfd2H77+vazJ424EdmjLjeiqyzjRyO1gt4q1oOXVPMJsgmIzRv0wqy/nonbP1zdHXdxaVQPV4o5u5PT5wy3oDBPzfj6Cu9IynB5D8lcKV4ijuyUcLAH1kw8EcM0omo9+HPLBQ1/jDSS1va6dHRVIEvl9Ri629bD3LyLjPjop2pOOuNZOTMMTHI6QU0nx+qU98rYkxOAoAWvTr+2nrY8nL1JxACroLCmLaxPac9lghTqtSj74SSAcg8y4gRv+KwNSIiomhioENR4+3CHB3NL/DFohoc/lfL2eGOcQou+DoFZ7+VjJQJ7ITsTUKHrQGBHh0ALTOv1dfDmGQPBkKNnN+fjF0DO2BOkTHr2SSgB5fUkQ3ArOeSTpl1l4iIiLoLAx2KGn9dx4GOJavlJSc0gY1X1eDoKy27cUb/1ooLvk5F2jRmouqNQoetAYH00kDLQMdXWw8AsOX105X3ZKADAP0vMmP0b3uoN0UCZj6bhMTBXFeEiIgo2hjoUNSENUenlUBn74NOHHtNH+TIZuDsd5Mx7ZFEKBb+0t1beSurddtKgg2yKRCUtuzRCSwa2tsCHQCY+hc7hiw2BzNFdZfpj9sx+Kec20BERBQLDHQoajoKdAx2CQab/ptk6WYfdt5ZrytTLMA57yYj72Jz1NtI0eWr1gc6JkfTsLQWc3TqAv/OCQP768rrjhyPUevCJ8kSZj2bhBG/in3QIckAJOD0ZxIx8saW2emIiIgoOhjoUNT4Owh0QntzfHUaNl5Zrct4JcnA2e8ko988BjnxIHToWuOwNQAwJIb06DQMXbMPG6Qrrz1wODaNi5AkS5i+IhEznkiEYg0kCYj+cwQScsz92IHhVzP5ABERUSwx0KGo6ahHJzTj2r5HXag7op8FPu4OG4OcOOILTS3drEfH2MbQtcThQ3Tl9UdPQPV4Y9TCyEiShBHXW3Hx3jRkzm6YFxaFd0mpYQrOsGssuGRfKnLmdH86bSIiolMNAx2Kmo4CneY9Op5KDd8+7NTtz5hlxIS7EkIPo17MVxU6dK1Zj05ooFNXBwCwDx2oP4mmob4XDF9rzj5IwblrHZj9YhJSJwe6djrTwyMpACSg3/kmnLfOgdOfSuLiiURERN2EuXopanw17efotWQ0fcH79mEnfNX6wGjGE4mQDUw8EE9CkxEYU9oeutaYdc2YaIclJxPuwpLgvtoDh5E0algMWxo5SZIw5EoLhlxpQfk2H/KfcOH7dzzwVgWu22DgoyGQxEACIBAcimnLlTFkkQXDr7PCPpBZ1YiIiLobAx2KCs0voLrar2PJDAQxqlsgf4W+8sCFZq6RE4e8IevomJqtkdOyR6cp6UTi8CG6QKd6Tz5yF5wXo1Z2XdpUI2Y9a4T4p0D9cQ0V23wo3+aHq1CD6haADBgsEuxDFKRNNSB1qhGWdPbcEBER9SR+s6SoCGsNnczAF78T//Hoe3MkYOLdHLIWj9qfo2PX7Wse6DgmjEHphs3B7Yrtu2PUwuiSJAn2gQrsAxUMuLynW0NERETt4U+OFBXhrKHTGOgcetGtK88624jkUYy541Ho0DVdeul2enRSp4zX7av65ltoPn8MWkhERESnKgY6FBXhBjruMg0nV+szbA29igsmxitvaDKCVEfwcVtzdAAgZco43T7N40H1t/nRbyARERGdshjoUFT4asILdAo/8UI0++FesQIDfsR00vHKW1Gl29ZlXWtjwVAAMKU4WmRfq/h6Z9TbR0RERKcuBjoUFeH26BSt0ffmZM8xMd1unFI9XqhOfVIJUztZ11SnC0JtWh02ddok3f6iTzdEv5FERER0yuI3TIoKf237qaUlGTA6gMKQQCfnh1w4MV6FrqEDAMYUR9Nje8sEE/66prWTss89Q7ev/Oud8JRVRK+BREREdEpjoENR0VGPjjldQv0xgfpj+oAoey4DnXjlCRm2BkmCKTkxuGkIyboGAP76puFrGWfMgGKzNu3UNBR9wl4dIiIiig4GOhQVHQY6GTLKvvaFlElwjOVCivHKF7pYaHISJKXp39OQYA09BL7auuBjxWJB1jmzdftPfvBplFtJREREpyoGOhQVHQU6lgwZFdv06YPTTzNCkqRYNotiqEVq6WbzcwBAUhQooQkJmmVeA4Cc+efotks//wo1+Qej2EoiIiI6VTHQoajoKOuaJUNG+XZ9j07qFK6dE89apJZ2JLeoY0xse9FQAMg698wWAdLBf7wUpRYSERHRqYyBDkWFv4MeHVOqhIrt+h6d1CnGWDaJYsxbXqnbNqW2DHRCFw1tPnQNAAxWCwYt/rGurODfq+E6WRSlVhIREdGpioEORYWvrv1ARzEDvmp9nTT26MQ1b2WVbtuUmtKijjEkxXRojw4ADF78YyiWprWUhF/FvoeejE4jiYiI6JTFQIeioqM5Opp+1BqMiRJsebz84pmnRY+Oo0UdQ8jQNV9ty0DHnOrAgIWX6MpOvL2K6+oQERFRl/CbJkWFr4N1dPz1+kAoaZTCRARxzhuSXtrcSo9O6NA1f8jQtUbDl/4ChiR9UPTN7cvhra7pWiOJiIjolMVAh6Kio2QEnnL9/uTRHLYW70IDHVOao0Wd0EVDWxu6BgCWrAyMu/MWXZmnpAw7b70Xmt/f6jFERERE7WGgQ1HRUTICV5G+xyd5FNfPiXeeiugMXWuUd8UCZJ49S1dW9MkG7LztPgit/R5DIiIiolAMdCgqOpqj4zyh6raTRrJHJ54JIcIbuhaajKCNoWsAIEkSJv75DhiTEnXlJ975ELvufBBCtH+NERERETXHQIeioqNAx12s3584nD068Ux1uqB5vLqycIau+doYutbImpOF6c8+rMvCBgDHXnoL25beAV9N24ESERERUXMMdKjLhBDtDl1TrC3LEocy0IlnoRnXAMCU4mhRFjp0rb0enUZp0yfjtKcfgmTU9/qd/OBTrL/oKlTt3hdZY4mIiOiUxECHukx1AaKdKRQGuz67mq2/DIOVGdfiWehiobLZ1CLDGtByHZ3QBUPbknnWTEx9/P8Bsv4tynnsBDZefjUOPvUi1JAeJSIiIqLmGOhQl/lq2p8orpj0QU3iMPbmxDtPeYVu25yW0mq68JY9Ou0PXWuu3/k/xPR//gXG5CRdueb14dvlf8NnP7wC37+9CkJV2zgDERERncoY6FCXdTQ/ByHffxOHMNCJd54yfY+OOT211XrGTgxday57zhk4a9VLSJk8vsU+54mT2HHL3Vh3wc9R+PF6BjxEIVS3QNkWHw6/6MKBZ1w4/KILZVt8UN1M7EFEpwamvqIu6yjQ0fz6/fbBDHTinTekR8eU1nqgE9qjo7o90Hx+yMbw33ps/XMw+42nse/BFTj09Est9tfuP4gt194GS04mBvzXRcj78QIkDOgf9vmJ+hJNFSj4wIv8FU4UrfVBtBL/SwqQdY4Ro5bakHuhCbKBQ4mJqG9ijw51WUdr6Kgu/badPTpxz1MWMnQtvWVqaaBljw4Q/jyd5mSjAWP/cDN+8NY/kXrapFbruAtL8N3jz2HNGZfhy5/cgO/fXgVvZVXEz0UUryp2+vD+pAqsu7S6zSAHAIQKFH/mw7rLqvH+xAqUb/d1b0OJiLoJe3Soyzrq0fHXsUenr2kxdK3NHp2WCQr8tXUwt7K4aDhSp03E7DeeRvHajdj3wArU5h9qtV7Zpq0o27QVkCQ4Jo5B5pmnI+PMmUiZPBaygW971Pfse8yJbbc1/YjQVpATur/mOxWrpldi6kN2jLnFFsMWEhF1P37iU5d1FOiEfuAy0Il/ockITGmt9+goVgskRdHNn+nqWjiSJCF7zhnIOnsWTvz7Ixx+9hVU79nfemUhULVzL6p27sV3f3sWhiQ7MmadhpSpE+AYPxrJY0fCmNSy14konuz5cz123BF+oo/mGt+ft91aB9UlMP6Olj9OEBHFKwY61GW+mvAntipWwJLJ8eDxruXQtdZ7dCRJgiHRDl9VdbAs0oQEbZEUBXmXX4C8yy9A9d58HH/9PzjxzofwVde0eYy/pg6Fqz9D4erPgmUJgwfAMX4UkseNgmP8aCSOGgZTSnKrWeSIepsT73s6HeSE2vm/9XCMMyDvYnPHlYmI4gADHeqyDrOuNZMwUOEXyD7AU1qu2zZnpLVZ15iYoAt0OjNHpyPJY0di/L0jMeb2X6Pok/U48faHKPtyC1S3p8Nj648cR/2R4yh47+OmNiclImFwHhIG6W/2wXmtLoxK1BM8lRq+vLomMNu2/Sz/4ZGBTdfUIHN/GsypnMJLRPGPgQ51mb82/E9Y+0AOW4t3ms8Pb0WVrsyS2Xag02Itnbro/PrcGsViRu6C85C74Dyobg8qtu5EyfrNKNmwGbX7D4Z9Hl9NLaq++RZV33zbYp8xKRGWnExYsjKa3dJ1j83paRFlliPqjL0POuGtENEJcgBAA7yVAnsfdGLKnzmkk4jiHz+Jqcu8EQxdSxjAXwnjnaesvEWZOSO9zfqhc2C6OkcnXIrFjIwfzEDGD2Zg7B9uhru4FCUbNqNy2y5U7d6PmvyDED5/xOf11dTCV1PbZiIEAIAkwZSWApMjGaaUZJgcSTA6kmBMToIpxRHcNjmSYXIkw+hIgiExAQabjQEShUX1CBz4h6vDpAOREipw4GkXJt6TAMXC3nciim+d+kRdsWIFHnroIRQVFWHixIl4/PHHMX369Fbrrly5EkuWLNGVmc1muN3uzjw19UIdpZduLoE9OnEvdNiaZDTA5Ehqs35oimlfTW1M2tURS1YGBlyxAAOuWAAAUD1e1H53CFW796F6174uBT8tCAFvWQW8IXOZwiGbTTAk2GCw2aDYbTDYrDDYEwJlCVYYEhKgNN5bzJDNJihmExSLJfA4WGaGbDE37DNDNgceyxYzM8/1ASc/8sJbFZuFP71VAgWrvRhwKefqEFF8i/jT7rXXXsOyZcvw1FNPYcaMGXj00Ucxb9485OfnIzMzs9VjkpKSkJ+fH9zmHI2+xVfXzoetBKDZ7oQBDHTinbukTLdtTk+FJLfdU2dIStRtRysZQVcpZhMc40fDMX408LNAmeb3w1VQFJi3c/QE6o4G7uuPfg/n9wUQ/q79fC4EEPhP0fwGQMjBx6pLgurywAMPgKqGI5vqNp2j+b2+TotyEbItSZCNRsBggGwwQjYokAwGSAYDZIMBksEISTFANiqQDEbIigLJaIBkUCAbjJAUBZAlSLICSZEhyQogK5B0ZYEbZAWSokBSJEiSAshy8BhJCrQFsgRIMiRJbmie3KxcggQ5UFeWmo6RZEBu+DyRZEhy4PVLQGB/8E8iBV9z4FzN/w6Nn0fNHjccKxrqSFKz8+n+1s23QvaH1m//8FbO37Gjr1kgyWYILfqfp5IBKN/iY6BDRHEv4kDnkUcewbXXXhvspXnqqafwwQcf4LnnnsP//M//tHqMJEnIzs7uWkup14ok6xqHrvVOQghoHkD1CggfoPkBzSeg+QDhD9xrvsC+0i898HvGAkKBgAKTNhjH3/VA+IT+OB+g+QUqvz0NnhoTABkCMk58NBx+fx2EimY3AU0FhL9pW6iA0ALbmipa7mvcrwFCC8xTaNxGs3L9duNj0U5dC4Q2AkIb0aKuULXATRNAsFwAIvA3hGgeVDQPZnjdU/wQKlC+PQo9m0REPSyiQMfr9WLbtm24/fbbg2WyLGPu3LnYtGlTm8fV1dVh4MCB0DQNU6ZMwZ/+9CeMHTu2862mXqXdrGshu2x57NFpi9AEVDfgdwqoLhG4dwbu/U4EH7e6zyWgegQ0b2DsvqZ7HHLvFVA9gOZputciWhh9YsMtwFkKrL+8uu3qOK3hFlDyBVDyhTPCv05vIQHgNUx9nAA8pdHKcEBE1HMiCnTKysqgqiqysrJ05VlZWdi/v/UF+0aOHInnnnsOEyZMQHV1Nf7yl79g1qxZ2Lt3L/r379/5llOvEfYcHQmw5fa9X7aFEPDXC3jKBDzlGrzVAr4aAV+NFrivbdwW8NVqTY9rmtWrFVBdPf1KiIgCpL73Vk1Ep6CYz0idOXMmZs6cGdyeNWsWRo8ejX/84x/44x//GOunp27grQnvlz9rlgzF1PvnZwkh4KsWcBZocJ5Q4S7R4G4IYjxlGjwVInBfrgWDG83b060m6gvaeS+RQn5Qaev3ldB6rR0T9ttQDCb7R+2UCvTzsqJHkgFbHiMdIop/EQU66enpUBQFxcXFuvLi4uKw5+AYjUZMnjwZBw+Gv6YF9W7h9uj0lg9OX71A7QE/6o5ocBaocJ7Q4DypwlmgwVWgof6ECjVeR1bFkKQAshHQfO7ABBz4AUmFKcUOkyMBsjEwiVk2Sg2PA/e+qkrU7M9H4EusBkOCGZlnz4BkaDinIkFSAl+uJAWBSesKgjfZoN/W7ZcbtmUEJqY3nkMOKWu4oaG8aTu8upCa3Qen3kgtyqSG6ThSs+k5gQnurR0fWl/Sn6vxv0vT/Hjd91rdJPmQOlKzeu0fj+BGi+PRbH/IY6mN8nbn5OuO7/0/ePR2u5fX45u76qOeXhoAIAFpU40xODERUfeKKNAxmUyYOnUq1qxZg0svvRQAoGka1qxZg5tuuimsc6iqit27d+OCCy6IuLHUO7U7R6eZhG6cn6P5BeqOqKj5LnCr/U5FzQE/avIDAU28kI2AYpNgsElQrAjcN2wHH1slKBZANktQzBJkM6CYJSjmQJlsQkN5U5nSUEc2NdWXzYBikiAZm4IV2SgFghcDGrJaAaunztOlTT79hceQefasNl9D6cbvsOnKu4LbprQUnPXGx7H7oxGdAjJ/YIxNkINAMoLM2Qx0iCj+RTx0bdmyZVi8eDGmTZuG6dOn49FHH0V9fX0wC9uiRYuQm5uL5cuXAwDuu+8+nH766Rg2bBiqqqrw0EMP4dixY7jmmmui+0qoRzROgA9HrObnCCFQe1BF2dd+lG/xoXyLDxU7/FB7YKkmyQCYUiSYkmQYkyT9zd5KWWO9RAmGhMbABcEARjb2rl++Na+vxdowluzW08o3MraSXloIwV/1ibog8wdG2IfKqDusRXeEnQTYB8nIPIOBDhHFv4gDnYULF6K0tBR33XUXioqKMGnSJKxevTqYoOD48eOQm62pUVlZiWuvvRZFRUVISUnB1KlT8eWXX2LMmDHRexXUY8LtzQGiF+gIIVD5jR8n3vei5HMvyrf64a2MzcJ55nQJ1hwZlgwZ5rTGmwRzesPjdKnhPlBuTJT69Bf40DV0AMCSndHuMYaQBUM1rw+axwPFYolq24hOJZIkYfTNNmy5OfrrUo262RbswSUiimeSECI23xDplFB7WMW7w8rDqvuDl5Iw+Ged+3LrdwkUrfWi4H0vTnzggfNEF4efSYCtv4yEPAW2XLnhpsCaKyOhvwxrrgJbPxmKmR/2zZVv+QZf/FdTb6xsNuPC/M/bDe485ZX4aMp5urLzvv4Qlqz0mLWT6FSg+QRWnVaBqr1qVIaxSQYgebSCC7em9rreZCKizoh51jXq23xhZlwDOtejU7nHj/zHnTj8srtTCQLM6RKSRhiQNEJB4nAFSSMUJI0wIHGYAoOVH+SRchUU6rat/bI67MEKHboGAL6aWgY6RF0kGyXMfjEZq6ZXBBa77crPlg0JMH7wYjKDHCLqMxjoUJdEMnTNGmago6kCBe97sf9xJ4rWhr+SpSVLRvp0A9JOMyJ9ugGpU4ywpPeOTG99RYtAJ7fjbIuy0QDFZoXqbFooyFdTG/W2EZ2KUsYbcPY7yVh3STU0Fe1m6G5TQ3bBs99ORsoEfi0gor6D72jUJb6aSObodJx1rfQrH776VS0qd/k7rGsfLCP3QjOyzjIifboRtv5yn54f0xs4C4p027bcnLCOMyYl6gOdagY6RNGSO9+MuZ84sOEnNfCUahENY5OUQM/3Ga8kI/tsU+waSUTUAxjoUJeE26NjSpHaHSrmrdGw84565D/panP4hSQDGbON6H+hCf0XmJE0SmFg081cJyLv0QEAY3Ii3EUlwW326BBFV9aZJlyyLxXbfleHQ8+7AYHAcLY2SAogBDD0FxZMfcgOk4O930TU9zDQoS4Jt0envfk5lbv8WHtRVZsJBiyZEkb8yorhv7LC1q/71uKhllr06PQPv0enOV91TdTaREQBpmQZM59OwsR7E3DwGTe+/48HVbv9uiUAZCPgmGBA/4vMGH6the+pRNSnMdChLvGH2aNjbePDtHSzD2svqIK3quV5HOMUjLnNhkELLcx+1gsIITo1RwcI9Og056uJfkpcIgqw5SiYcFcCJtyVAM0nUHdMheoGFAtgH6gw2QARnTIY6FCXhJt1zdavZY9O8Xov1l5UDX+9PshRrMDEexIw+rc2fiD3Ip6Scqgu/SqstrzcsI5ljw5Rz5CNEpKG8aOeiE5NfPejLvGGOXTNmqMPdJwnVay7vGWQkzHLiNn/SkLiEA6n6G3qjx7XbctmM6w5mWEdyx4dIiIi6m4MdKhLwh261rxHRwiBTVfXwlupP7bffBPOejMZBht7cXqjuiPf67YTBuZCksObwGxMTtJts0eHiIiIYo2BDnVJuFnXmvfoHPynGyc/8ur2514UCHIUE4Oc3qr+WEigM3hA2Mcak+y6bWZdIyIiolhjPknqknCzrjUmI1C9At/cW6/flyNj9sokBjm9XH1oj86gvLCPDe3R8VaxR4eIiIhii4EOdUm4yQgae3SOveaG66T+mJn/TIQ5lZdib1d3+Jhu2z44/EDH1GKODnt0iIiIKLb47ZK6JOyha9kyhBDY96hLV555phG555tj0TSKIs3rQ92ho7oy+7AhYR9vdCTrtjlHh4iIiGKNgQ51SThD10ypEhSzhJr9Kip2+HX7xtxii1XTKIrqjhyD8Ku6sqQR4Qc6ppCha/7aemg+fxu1iYiIiLqOgQ51STiBTuOwtRPve3TltlwZ/ReYYtIuiq7a/MO6bUtOZouU0e0JnaMDcPgaERERxRYDHeo0IUR4gU52Q6DzgT7TWv+LzJBkJiCIBzX7D+q2k0YOi+j41oIiDl8jIiKiWGKgQ53mdwIijFwE1hwZvnqB0i98uvLcC9mbEy9q9h3QbSeOHBrR8YrFDMWin4vFzGtEREQUSwx0qNPCzriWraBiqw+i2RQPSQGyzmGgEw+EEKjcuUdXljx2ZMTnYUICIiIi6k4MdKjTwl5DJ1tG6WZ9b07KRAOMCRy2Fg+c3xfAW1GlK0uZPDbi84QOX/OxR4eIiIhiiIEOdZo/3NTSOTLKvtIHOukzjLFoEsVA5Y69um1TqgO2vNyIz2NycNFQIiIi6j4MdKjTvBH06FRs16cSTp9uiEWTKAaqQoatpUweB0mKvDeOQ9eIiIioOzHQoU7zVYcX6CgWoP64fj5P6hT26MSL0i+36rZTJo3r1HlMIYGOt7K6020iIiIi6ggDHeq0cJMRuEr09WQzkDxKiUWTKMrcJWWoDUktnT5rWqfOZUoJDXSqOtssIiIiog4x0KFOCycZgWwGag+pujLHOANkIxMRxIPSjV/rtg2JCXBMijwRAQAYQwOdKvboEBERUeww0KFO84YxdM2aJaN6jz7QSZnA+TnxovTzr3Tb6TOnQTZ07t8vdOiaj0PXiIiIKIYY6FCnhdOjY8mWUbVHn4ggZTwDnXigeX0o/vRzXVnGD6Z3+nwth64x0CEiIqLYYaBDnRbOHB1LloSqvfpAxzGOgU48KPl8M3w1tbqy7HPP7PT5WgQ6HLpGREREMcRAhzotnB4dxSJBdenLHOzRiQsF732s2049bRKs/bI7fb7QoWv+2npoXl8btYmIiIi6hoEOdVo4gU7ocivmNAmWTCYi6O181bUo+ni9riz3onO7dM7QZAQAe3WIiIgodhjoUKeFE+iobv128mhDpxabpO517NV3oTqbdcXJMnIu+GGXzhnaowMw0CEiIqLYYaBDneat7niOTuiiosmjuX5Ob6f5/Tjywuu6sn7n/xCWzPQunVc2GmBMStSVecurunROIiIiorYw0KFOC6dHxx2yWGjyaM7P6e0K3vsYroIiXdmQq38alXOb0lJ0296Kyqicl4iIiCgUAx3qtNDemtbUn9AHOkmj2KPTm/mdLux7YIWuLGXyOKROnRCV85tSHbptT0VVVM5LREREFIqBDnWKECKsHh1/rb5O0kj26PRmh55+Ce6iEl3Z8JuWRO385pBAhz06REREFCsMdKhT/HUCooMpOrIpZNsMJAzgJddbVe3ehwMrnteVpf9gOrLmnBG15zClhgxd4xwdIiIiihF+66RO8YYxbM2YpM+uljhMgaww41pv5Kutw9ald+jXtZFljLvzlqhmyTOlOXTbHvboEBERUYxwHBF1SjjD1mSjfjtpRHxfbkITKPvKj7ItPtTsU6F6BAwJElImGJA+wwjHeCUuU2erHi+2Lb0DzmMndOXDrvs5kkYNi+pzmVv06DDQISIiotiI72+e1GPCSUQQWiNpeHwmIlA9Avl/d2Hf35xwfq8BEiAZEHiBEiAaOkEc4xWMWWbDkKsskOT4CHg0rw9bb/g9StZv0pWnTB6PUbfdEPXnC826xmQEREREFCscukadEs4aOppHv504LP4CnfJtPrw/sQLb/rsuEOQAgAgEN8LfFOQAQNVeFV8uqcXH51Sh7qjaMw2OgLukDJuuugnFazbqyo3JSZj69/8H2Rj930FaJCMor4j6cxAREREBDHSok8Lp0Qkd3hZvPTonP/Zg9exK1B5SW3ZPtaYhDird5MOq0ypQtdcf0/Z1RcnnX2H9BT9H+ebtunKDPQGnv/AYbP1zYvK85vQ03banvApC7f1BIREREcUfBjrUKeEkIxAh3/PjqUencpcfn11SDc0PiAi/hws/4K0S+PiHlXCXdtzz1Z3qjn6Pr6/7HTb//CZ4Sst1+xSbFTNWPoaUyeNi9vzmDH2gA03j8DUiIiKKCc7RoU7xhTF0rTnFClj7xUdcrfkENl5VHQjUOhmnCBXwVgh8dWMtznojOarti7gtQqDi6x048sIbKFz9Was9KNZ+WZj21ANImTg2pm0xpTkASQJEU6DsKauAJTQAIiIiIuoiBjrUKeH06DSXODR+MpIdfM6Nqj1hDldrh1CB4295ULzBi6wzTR0fEEVCVVGxfTeKPtmAok/Wo/7w8TbrZpx5OqY89scW82diQTYYYEp16LKteUrLgdHDY/7cREREdGphoEOdEs4cnebsQ+Jj2JoQAvv/5oza+SQDkL/CFdNAR/P54TxxErUHjqBq515UfrMXVbu+hb+mrt3jTGkpGHXb9Rj4k0shyd3X22bOSNMHOmVMSEBERETRx0CHOiWcdXSaS4yTQKcmX0X1vuhNjhd+4Pi7HqheAcUUXo+WEAKaxwNfbT38tXXw19XDV1MHX3UtPKXlcJeWw1NSBndxKeqPnYDz+5MRTehXrBYMuuq/MOLXV8OYZO/sS+s0c3oqaptte0rK26xLRERE1FkMdKhTvFUdTF6RoBv6lTg0doGO3yXgLtbgKtLgrdTgrRLwVmnw1wn46wX8TkB1CWheAdULaF4B4Ucg0YBfQGuYiyM0AefJ6CcPED7gs/P+F6bkAkDToPlVCFWFaLjX/H5oHi9UjweaxwvN4416GwAgYVAeBi36Lwz4rwUwJifG5DnCETofx11a1kMtISIior6MgQ51SodzdEICna4OXRNCoO6IhoptPlTu8qN6v4q6I4Gbt7KLk2m6QdUeD0wJe7v9eRNHDUP23DORPfcMOCaO6dYham0xZ6brtj0lDHSIiIgo+hjoUKf4qjoILkI6RjoT6PhqNRR86MX373lQ/JkPrsLelao5MrH/r2Z0JCNp1DCkTB4Lx8SxSJk8DtbszJg/b6SsOfo2uU4W91BLiIiIqC9joEOd0uHQtRD2geEHOlXf+rH/MScOv+yGGr28AD1Kkjr/QmSTEYZEO4yJdpjTU2HOSIMlMx3m9FRY++fAPngAEgbnweTo2TTW4bL2y9Ztu04W9VBLiIiIqC9joEOdEkl6aWs/GYql44n4riIVO+6ox6EX3J1K7SybAXOaDFOKBJNDhjFJgsEWuCkWQDZLUMwSZCMgmwBJkSAZAFkJPIYEVO/34+A/3ZE/eQfG3nkBbFlzAVmCbDBAMiiQZCVwr8iQzWYoFjMUswmy2QTZbIYhwQZjoh2KxRz19vQka78s3ba7uAxCVSEp8ZGwgoiIiOIDAx2KmNBERFnXwsm4dvwdDzZfVwNPefvnNWdISJ1sRMo4BYnDDbAPlpEwQIE1JxDYdHWtHnephoPPdi7Qaos5TcLIX8+Lm3WEYs2aow90hKrCXVLWopyIiIioKxjoUMR8tSKiQMA+uO1ARwiBPX92Yucf6lvdLylA9hwT8i4xIWeOCYnDY7vwqCVDRv8FJhSs8kL4u34+SQGGX2dlkNOMKS0Fstmkyy7nKihioENERERRxUCHIubtKBFBCPugtjN97f6jE9/c0zLIMdgljPqNFSNvsMKW271DmsbcasOJ96KT4llSgBG/skblXH2FJEmw5mSh/uj3wTJXIRMSEBERUXT1fK5ZijuRJiJIGNR6oHLoBVerQc6AH5lx6YE0TL7f3u1BDgBknWHCsGsskKLw1JOX25EwgHNPQoXO03F+f7KHWkJERER9VacCnRUrVmDQoEGwWCyYMWMGvv7667COe/XVVyFJEi699NLOPC31Er4IEhEArQ9dq97nx1c31uoLJWDqX+w48/UkWLN6Ngaf+hc7kkYpkDrb5ykD/S4wYdRv2JvTmoRBebrtusPHeqglRERE1FdF/G3ytddew7Jly3D33Xdj+/btmDhxIubNm4eSkpJ2jzt69Chuu+02nHHGGZ1uLPUOkS7QaQ/p0RGawKbraqG69PWmP27HmGW2XjGfxZQk47y1KXCMNQQWP41Q/wtMOPvNZMhKz7+W3sg+dJBuu+4QAx0iIiKKrogDnUceeQTXXnstlixZgjFjxuCpp56CzWbDc8891+YxqqriyiuvxL333oshQ4Z0qcHU8yIZuiYpgK2//jI78rIbpV/4dGUjrrdi5I22qLQvWiwZMs7fnIJxt9sAGR0PZZMBxQpMX2HH2e8mh5VS+1RlHzJQt1136BiEiGKqOyIiIjrlRRToeL1ebNu2DXPnzm06gSxj7ty52LRpU5vH3XfffcjMzMTVV1/d+ZZSrxFJj46tvwzZ0PSFX/MJfHOvfl5O4lAFUx+2R6190aSYJUy+345Lv0vDmGU2WNoYUmcfLGPy/Qm47Eg6Rt5ggyQzyGmPfag+0PFV18BbUdUzjSEiIqI+KaIZCGVlZVBVFVlZ+onEWVlZ2L9/f6vHbNy4Ec8++yx27tzZ6UZS7+KtDL9HJ3TY2tFX3ag7rD9+2l/tMFh7d2CQOETBlAfsmPKAHa4iFdX7VKhuAYNdgmOcAeYU5vWIhK1/DmSTEZq3qWev7vAxmNNSerBVRERE1JfENL10bW0trrrqKjzzzDNIT0+P5VNRN4okvXTCQH2gs//v+ok56TMMyL3QFJV2dRdrtgJrNjOpdYWkKEgYlIfa7w4Hy+oOHkHaaZN6rlFERETUp0QU6KSnp0NRFBQX69e8KC4uRnZ2dov6hw4dwtGjR7FgwYJgmaYFfs03GAzIz8/H0KFDO9Nu6kGRBDr2gU09HeXbfCjfol+Fc+x/J/SK5APU/RKHD9EFOlW79mHgTy/rwRYRERFRXxLReBuTyYSpU6dizZo1wTJN07BmzRrMnDmzRf1Ro0Zh9+7d2LlzZ/B28cUX45xzzsHOnTuRl5fX4hjq/SJJRtC8R+fwi27dPluejP4L4qs3h6LHMXGMbrty554eagkRERH1RREPXVu2bBkWL16MadOmYfr06Xj00UdRX1+PJUuWAAAWLVqE3NxcLF++HBaLBePGjdMd73A4AKBFOcWPSJIRNAY6mipw9FV9oDN0sUWXqIBOLSlTxuu2a/Yfgt/pgsHGtYeIiIio6yIOdBYuXIjS0lLcddddKCoqwqRJk7B69epggoLjx49Dljkxuy+LrEcncC2UfuGDu0QfIA2+0hLVdlF8SR43CpKiQKhqoEDTUL17H9JmTOnZhhEREVGfIAkuXkEReiuvDM6C8IKdn7kyoJglbLmlFvsfa0pEkDLBgIt2psaqiRQn1l/wc1TvzQ9uj7791xh+/aIebBERERH1Fex6oYi5K8ILcqz9ZCjmwNC0gg+8un15l3JuDgGOyfohrJVbv+mhlhAREVFfw0CHIqJ6BDRXx/WApoxrNQf9qD2o6vb1X2COdtMoDqVOnaDbLt34NVS3p4daQ0RERH0JAx2KSCSLhTYmIji5Wt+bY8mSkTo5pks4UZzIPGsm0GxOn+pyo+yLLT3YIiIiIuorGOhQRDwVEWRcywsEOkVr9YFOv3kmSDKzrRFgTktp0atT9OmGHmoNERER9SUMdCgi3jDn5wCBjGuaKlC8zqcrz5ljjHazKI5ln3umbrvokw0QWvjXGREREVFrGOhQRCLq0RmooPIbP7xV+mOyf8hEBNQkNNDxlJajcgcXDyUiIqKuYaBDEYlojs4ABSUb9L05icMV2HKVaDeL4ph9yEDYhw7SlR196a2eaQwRERH1GQx0KCKR9ejIKP5cH+hkncFha9RS/8sv0G0X/OdjuEvKeqg1RERE1Bcw0KGIhDtHx+SQYEyUUPqFPhFBJgMdasXAn10G2dyUclz4/OzVISIioi5hoEMRCbdHJ2GggrrDKtwl+vqZP2CgQy2ZUx3of+l8XdnRl9+G6vG2cQQRERFR+xjoUEQ8YfboJAyUUfqlftiaJVOCfQjn51DrhvzyJ7ptb1kFjr70Zg+1hoiIiOIdAx2KiKc8zEAnT0HpZr+uLH2mEZLE9XOodUmjhiF91jRdWf4jT8NdXNpDLSIiIqJ4xkCHIuItD3/oWtnX+h6djNM5bI3aN3LZr3Tb/rp67LnvkR5qDREREcUzBjoUEXeZGlY9W46Eym9CenSmM9Ch9qWdNgl5V1ykKzv5/qco2bC5h1pERERE8YqBDkXEE2aPjt8DiOZxjgSkTTPEplHUp4y5/TcwJifpyr75/f1MN01EREQRYaBDYVM9AqozvLruIn3PT/IYBcZEXm7UMXNaCsbcfpOuzHWyGF9fcyv8LncPtYqIiIjiDb95UtjCTUQgm4Ga7/SBTto0Dluj8A1YeAnSZkzWlVV98y2233wnhBbedUhERESnNgY6FLZwh60l5Cko36afn5M2lcPWKHySLGPaE3+GLa+frrzoo3XY+8e/QojwrkUiIiI6dTHQobCF26Nj6y+hZp++Ryd1Cnt0KDLm9FTMeP5RGJMSdeWHn3sV23/zv1DdHMZGREREbWOgQ2HzlIUX6BjsMkSzqpIMpE5ijw5FLnH4YJz2jwchGfQLzRa89zG+WHg93MVMUEBEREStY6BDYXOXhjk3IqRa0mgFBhsXCqXOSZ81DZMeuguQ9W9XVTv3YsMli1G169seahkRERH1Zgx0KGye0vDmRfjq9PVSJ7M3h7om7/ILMOO5R2CwJ+jK3YUl2HDJEuy++y/w1dT1UOuIiIioN2KgQ2ELt0fHXaSvlzqJ83Oo67LOmY0fvPNsiwQF0DQcWfka1v7wR/j+7VVMVEBEREQAGOhQBMJNRlB3NCQRAXt0KEqSRgzFGe+9gNTpk1vs85RWYMctd+OLH/8KpRu/ZsBDRER0ipMEvw1QmD45txJFa3ztV5LRYo7Oj8vTYU5hTE3Ro3l9OPDkCziwYiU0j6fVOokjh2LIL3+K/pfOg2KxdHMLidrndwnUHVGheQUMNgn2IQpkA+cyEhFFEwMdCtv7kypQucvfbh1TmgRvs/V2EgbIuPxoeqybRqeo+uMF2HPvwyj+9PM265hSHRh05eUY8NPLYMvN7sbWEenVHVNx4B8ufP9vD6rzVd2PQrIJSJlgwKCFFgxdYoE5lT8OERF1FQMdCtsbOaVwF7d/udj6y3CeaPr07n+xCee864hxy+hUV/TpBuy5+2E4T5xst55jwmhkzzsHOeedBfvwwZAk/oJOseep1LD1llocftEDSQaE2k5lGZANwNj/tmH8/yZAMfEaJSLqLAY6FBYhBF42l0K036EDa44MV2FToDP+f22YdJ89xq0jAlS3G8dfew+HV76G+sPHO6yfMGQAcuadjexzz4JjwhjIRs4lo+gr3uDF+iuq4a0Q7Qc4oSQgeZSCs/+djKRhvDaJiDqDgQ6FxVOh4fX0jhdnVGyA6mzaPvONJAz8EedHUPcRmoaS9Ztw+LlXUbphc1jHKBYzHBPHIHXaRKRMnYDUKeNhSnHEtqHU5xV+6sXai6qg+dFi7mI4JAUwpUiY/0UKkoYz2CEiihQDHQpL9T4/3htbEfFxl3yXyl8jqcfUfHcIR1a+jpPvfwpfdU1Ex9qHDkTKlAlwjBsF+/DBSBw2GObMNA53o7DUHlbxn/HlUD3oVJDTSFICQ4IX7EmDMYHXHhFRJBjoUFiK1nnxyQ+rIjrGYJfwk6p0SDI/nKlnaT4/yr/ajsKP1qHo4/VwF5V06jzGpETYhw1C4rDBweDHPmwQrP2yIBsY0FOA0AQ+OrsSZZv9HQ73DYsMjLzRiul/S4zCyYiITh0MdCgsR19z4/OfRvaLePrpBpz/ZWqMWkTUOUIIVO36FkUfrUPRJxtQ+93hrp9UlmHJTIc1JwvWflmw5GTClpsNS8O2NScL5vRUSDIzaZ0Kjr3lxoYrInu/DMfF+1KRPJIBNRFRuBjoUFj2PebE1lvq2q8kAWh2NQ2/zoLTn0qKabuIuspbWYXK7XtQsW0XKrbtQtXOPVDdra/N0xWS0QBTigOmVAfMDfemlOTAfaojuM+UEig3JiXCkGCFpChRbwvF1kfnVKJ0oy+y5AMdkAzAyKVWnPZX9uoQEYWLgQ6FZccdddjzZ2e7dSQjIJqtJzr973aMvNEW45YRRZfm86Nm/wFUbN2Fqm/2ovbAEdQdPBKT4Cccis0KQ4INhsQEGBISYLQnwGC3wWBP0JUb7DYoFjNksxmK2QzZYgrcm81QLOaGfabAY7MZssUM2WTknKMoc55U8Vb/8pic2+SQ8OPydP6bERGFiX3gFBZXccezaUPHoqdM4OUV74QQgACEFrjpHmsCQgDQELhvuImQewjRdGxb9RrP1bwMTduBtrS3TzT1JjZ/HrQ8Rnd883s03zcU9hFDYR9+WWBTFfCUlcN5ohDOE0VwnSiE80QhXAVF8Ne7Gg5q7ctnaJl+u+WvTC3P4XNJgO57swBQ33BrTThfgqXgnWw0QlJkSIoSuBkMgXtZgWRQIDfuMxj09Rr2S4ocGJInyZBkqeGxFNgvS4AkAXKgTtO+QF3IDfskOfDlXUKgviRBQtO21FAGoNnjhv1yU12peTkQPEb/0pudp419+qKmv1U4qvdbAWSEVzlC3iqBuqMaEgezl4+IKBz8JkphcYcR6IR+a3OMj8/LSwgBzQuoHgHN03gvoHoQct/w2Cug+QDhC9wHbqFl+n3CH1g0UPMH1tYI3AS0hnLh1z8O1G2qFwg0Gra1prLWtqGFlGnNyoLBS7Nziqb91JwBQF7DjahnVH7jZ6BDRBSm+PwmSt2uviCyweYJA2WYkrtn4rUQAn4n4C3X4CnX4KkQ8NUI+Go0+GobHzfc6jT46wL1VaeA3ymgugL3fqeA6gT8TtHaT+1ERD3OV8VfIIiIwsVAh8LiPBFZoBOtYWuqW6DmoIr6oyqcJzQ4C1Q4CwL37mIBd1kguNF6ZvoEEVG3kgycn0NEFC4GOtQh1SPgjXBurWNc5JeWq1hD6SYfyjb7ULnbj5p8P+qPahxCRa1rnDrRMC0j/G1Jvy/kfM3nYkitlLU4tr19LTZamQbS0XYnjmlrrnpgLlPTRKXgNhrmYjXc6yc1NZY3mywlAvsEoC/XP1vTsQ2b0D1upY5uX8i5Wt3XVN5+J2w7e0UYdSKg+a0QfjvCntQToYSBTFFORBQuBjrUIVdR5JFGysTwLq3KXX4cfd2N4295UJMfxVysMSIZAMUsQTaH3BsB2ShBargPbLdWJkFSAvskRYJsCKx8LhkaylvdliAZAFlpeKw01JED95Al3bbUYjtwHOTAOSA1HCdJgX1yQ5nucaC+JDd8aQ7ZF3zcuK9ZMCEFJ5Q33Mmh+/SPAxPWW98X+KPrt5lxinqz0k0+rJ5dGZuTS0DqZH5sExGFi++Y1CFnQScCnQ6GrhWv92Ln3fUo2eBrt16kJAUwpUowJcswJkmBW2LjvQxjogSDXYIhQYJiBQw2CQabBKXx3tp43xjISFDMCN5LMr9kE1HbUicbYEiU4K+N8kQ/OXBuo509OkRE4WKgQx1ynYysp0WxAInDW88KpLoFttxciwPPuCM6pzVbhi1Phi1Xhi1XgS1XhjVHhiVDhilNhiVdgjktENwwGCGinqJYJAy/2oL9j7uiumAoNGDUUmsUT0hE1Pcx0KEORdqjkzzWAFlpGWyoHoG1F1WhaG3bvTgGu4T06QakTzcieawByaMUJI1QYEzkr5hEFB9G3mRD/oooBjoyYMmUMXChJUonJCI6NTDQoQ7VH4tOxrWvl9a2GuTYcmUM+okFA/7LjLRprQdJRETxInGIgkn3J2D779ta1DVCGjD7+UQYrHxvJCKKBAMd6lD98ch6dFpLRFCwyoODz+mHqyk2YMqf7Rh+rRWKmR/gRNR3jF5mw8mPvShe5+tyz86o31rRb545Og0jIjqFcDwQdaj2iD+i+qE9OqpHYMvNdboyQ4KEeetSMOomG4McIupzZEXC2e86kPkDY5cyTQ+/zoJpf7FHr2FERKcQBjrUofqjEQ5dC+nR+e4pF2oP6c9x2mN2pE0zdrltRES9lTFBwpzVDoy73RZIwx7mGArJEOjxPv0fiZjxZCITrBARdRIDHWqXr06DN4IlIRIGyDCnNF1WfqfAnuX6ceoZMw0YuoSTaomo71PMEibfb8eFW1KQd6k5sIYVACnkd57GbcUKDL/aiku+TcPwa61cN4qIqAs4R4faVX8swvk5k/SX1IFnXHCX6NeTmPKgnR/eRHRKSZ1sxFmvJ8NZqKLwEy8qtvlRne+H6gaMiRIcYw1Im2pAzjwTTEn8DZKIKBoY6FC7ag93PuOa5hP49hGnbn+/+SZkzjZFpW1ERPHGlqNg6CIrhi7q6ZYQEfV9/NmI2lX7XWSBTurkpvEYx970wPm9vkdo/B9sUWkXEREREVF7GOhQu2q+izDjWrOha/sf1/fmZMwysjeHiIiIiLoFAx1qV82B8Ht0jMkS7IMCl1T5dh/KNuuDpNG/tUa1bUREREREbWGgQ+2qzg+/Ryd1iiGYZOC7p1y6fbb+MvIu5YJ3RERERNQ9GOhQm3x1GtyFouOKDdImB4at+Wo1HH3Fo9s3/ForZAMzrRERERFR9+hUoLNixQoMGjQIFosFM2bMwNdff91m3bfffhvTpk2Dw+FAQkICJk2ahBdffLHTDabuU70vwkQEUwKJCI6+7oG/vilAkmRg2C+5bg4RERERdZ+IA53XXnsNy5Ytw913343t27dj4sSJmDdvHkpKSlqtn5qaij/84Q/YtGkTdu3ahSVLlmDJkiX46KOPutx4iq3KnZElIkidEujROfS8W1eee6EJtlwlau0iIiIiIuqIJIQIf2wSgBkzZuC0007D3//+dwCApmnIy8vDr3/9a/zP//xPWOeYMmUKLrzwQvzxj3+MvMXUbb6+qRb5T7g6rojAgncLK9NRe1DFv0dV6Pad9XYyBnB+DhERERF1o4h6dLxeL7Zt24a5c+c2nUCWMXfuXGzatKnD44UQWLNmDfLz83HmmWdG3lrqVpW7IkhEMNUASZZw6F/63hxzhoT+FzKlNBERERF1L0PHVZqUlZVBVVVkZWXpyrOysrB///42j6uurkZubi48Hg8URcETTzyBc889t3Mtpm4hNIGKnb6w66dNNUJoAkde0gc6g39qgWxkEgIiIiIi6l4RBTqdlZiYiJ07d6Kurg5r1qzBsmXLMGTIEJx99tnd8fTUCbWHVfjrwq+fPsOAks99qD+u6cqHLmYSAiIiIiLqfhEFOunp6VAUBcXFxbry4uJiZGdnt3mcLMsYNmwYAGDSpEnYt28fli9fzkCnFyv9IvzeHABIn27ErvvqdWWOcQpSJnVLLE1EREREpBPRHB2TyYSpU6dizZo1wTJN07BmzRrMnDkz7PNomgaPx9NxReoxJREEOtZsGeYMCcfe1P+bDr7SElxAlIiIiIioO0X8c/uyZcuwePFiTJs2DdOnT8ejjz6K+vp6LFmyBACwaNEi5ObmYvny5QCA5cuXY9q0aRg6dCg8Hg9WrVqFF198EU8++WR0XwlFVemX4Qc6GbOMKPjAC19NswR+EjD4Zxy2RkREREQ9I+JAZ+HChSgtLcVdd92FoqIiTJo0CatXrw4mKDh+/DhkuamjqL6+HjfeeCNOnDgBq9WKUaNG4aWXXsLChQuj9yooqjwVGqq/DX+x0IyZRhx+WZ+EIOtsIxLyuHYOEREREfWMiNfRob7v2FtubLiiJuz653yQjPWXVkNr1gl0+jOJGH61NQatIyIiIiLqWERzdOjUUPCBN+y6igWoO6TqghzFAgz8Ly4QSkREREQ9h4EO6QhNoGBV+Iki0mcaceT/9MPW+i8ww5TMS4uIiIiIeg6/jZJO+TY/3CXhj2ZMHq2gbLNfVzbkKiYhICIiIqKexUCHdI6/HVnab12mNQDmDAn95pmi2SQiIiIioogx0KEgTRU4/KK744oNZAtQ9Jk+DfXgn1kgG7l2DhERERH1LAY6FFT4iReuk1rY9R1jDXAV6OsP/QWHrRERERFRz2OgQ0GHVobfmwMAmk8/bC11sgGpE43RbBIRERERUacw0CEAQO1hFcfejGx+TuiiosOuZm8OEREREfUODHQIALBneT0Q/qg1mDMkiGbJ1hRrYH4OEREREVFvwECHUH9cxaEXIhu2prr024N+YoHJwcuJiIiIiHoHfjMlbF1Wp+udCYe/Tj8/Z9RN1ii2iIiIiIioaxjonOKOv+uJeO0cJWSEWuYPjEidzCQERERERNR7MNA5hbnLNHy1tCbi49SQUW6jl9mi1CIiIiIiouhgoHOKUj0C6y+vhrtQdFy5uZArJmmUgv4LTNFrGBERERFRFDDQOQUJTWDz9bUo2eiL/OCQzGzjb7dBVqToNIyIiIiIKEoMPd0A6l6qV+DLX9bg6P9FNi8HACABaNYBlDxawSCmlCYiIiKiXoiBzinEXaZhw0+rULwmwhRrjUJGuU150M7eHCIiIiLqlRjohMnv9+Pw4cOora2FJElITk7GoEGDoChKTzctLMff8WDzddXwlEfnfLkXmJB7AefmEBEREVHvxECnA7W1tfjqq6+wZcsWuN36dGN2ux3Tp0/H9OnTYbX2znVkyrf6sPPuOpz8sBPzcdpgTJIwfUUiJIm9OURERETUO0lCiAjTbp06CgsL8a9//Qsulwtt/Zkae3cWL16M1NTUbm5h61SvwMmPvPj2YSdKNkQvwGl0xqtJGPRjzs0hIiIiot6LgU4bKioq8I9//AMej6fNIKeRLMtITEzEddddB7vd3k0t1PNWaSha78WRlzw48YEHmrvjYzpj4n0JmPC/CbE5ORERERFRlHDoWhtWr14dVpADAJqmoba2FuvXr8eFF14Y87Z5qzSUb/Oh6DMvSjf7UbHDB19lzJ8Wk+5PwLjbuTgoEREREfV+DHRaUV1djfz8/IiO0TQNO3bswNy5c2E2m8M6RvVq8FRpcBWpcBcDrkI/nN8L1B1VUXdChadEg69SwFMtoNYDwtuZV9N1lkwJpz+dhLyLw3tdREREREQ9jYFOK7Zv3w5JksLqzWnO5/XhmZmbkLxzTIxa1r0UGzDyeivG/SEB5hSuLUtERERE8YOBTivKyzuZg1mT4UvrhjFksSQBGacbMOgnFgz+mQXmNAY4RERERBR/GOi0QlXViHtzGglFi3JrYsuSJcMxTkHqRAMyZhmReYYJlgwGN0REREQU3xjotMJqtUKWZWhahEGLJKC4ejDtsgTIBkCxSDAkSjAmSjCnSbD2U2BJk2HJlGDNUWDNkZEwSIZ9kAJTMoMaIiIiIup7GOi0YvTo0di2bVvkB8oCjuLBMKUDEgDIACRAggTIgKwAUADZIAXujYDBJsGQIMFgl2BKlGBMkmDOkGF2SDAkyTDaZRgTAYNdDtSzAbJJgmKWIJskyKbAtsEKSDIX8CQiIiIiAhjotGro0KFITk5GdXV12MdIkoTc3Fws3t83EhEQEREREcUzjltqhSzLOOussyI6RggR8TFERERERBQbDHTaMGXKFMyaNSvs+vPmzcOIESNi2CIiIiIiIgqXJDqbXuwUIITA5s2b8dlnn8Hj8ejW1ml8bLPZMH/+fEycOLGHW0tERERERI0Y6ITB6/Vi79692LlzJ2pqaiBJEhwOB6ZMmYJRo0bBYOBUJyIiIiKi3oSBDhERERER9Tmco0NERERERH0OAx0iIiIiIupzGOgQEREREVGfw0CHiIiIiIj6HAY6RERERETU5zDQISIiIiKiPoeBDhERERER9TkMdIiIiIiIqM9hoENERERERH0OAx0iIiIiIupzGOgQEREREVGfw0CHiIiIiIj6HAY6RERERETU5zDQISIiIiKiPoeBDhERERER9TmGnm5AOIQQqK2t7elmEBERERFRL5GYmAhJktrcHxeBTm1tLZKTk3u6GURERERE1EtUV1cjKSmpzf2SEEJ0Y3s6pTf16NTU1CAvLw/ff/99u39Y6tt4HVAjXgsE8DqgJrwWCOB10F36RI+OJEm97iJJSkrqdW2i7sfrgBrxWiCA1wE14bVAAK+DnsZkBERERERE1Ocw0CEiIiIioj6HgU6EzGYz7r77bpjN5p5uCvUgXgfUiNcCAbwOqAmvBQJ4HfQWcZGMgIiIiIiIKBLs0SEiIiIioj6HgQ4REREREfU5DHSIiIiIiKjPYaBDRERERER9DgOdCKxYsQKDBg2CxWLBjBkz8PXXX/d0kyjG7rnnHkiSpLuNGjUquN/tdmPp0qVIS0uD3W7Hj370IxQXF/dgiykaNmzYgAULFqBfv36QJAnvvvuubr8QAnfddRdycnJgtVoxd+5cHDhwQFenoqICV155JZKSkuBwOHD11Vejrq6uG18FRUNH18IvfvGLFu8R8+fP19XhtRD/li9fjtNOOw2JiYnIzMzEpZdeivz8fF2dcD4Pjh8/jgsvvBA2mw2ZmZn43e9+B7/f350vhbognOvg7LPPbvGecP311+vq8DroPgx0wvTaa69h2bJluPvuu7F9+3ZMnDgR8+bNQ0lJSU83jWJs7NixKCwsDN42btwY3HfLLbfgP//5D9544w2sX78eJ0+exOWXX96DraVoqK+vx8SJE7FixYpW9z/44IP429/+hqeeegpfffUVEhISMG/ePLjd7mCdK6+8Env37sUnn3yC999/Hxs2bMB1113XXS+BoqSjawEA5s+fr3uPeOWVV3T7eS3Ev/Xr12Pp0qXYvHkzPvnkE/h8Ppx33nmor68P1uno80BVVVx44YXwer348ssv8cILL2DlypW46667euIlUSeEcx0AwLXXXqt7T3jwwQeD+3gddDNBYZk+fbpYunRpcFtVVdGvXz+xfPnyHmwVxdrdd98tJk6c2Oq+qqoqYTQaxRtvvBEs27dvnwAgNm3a1E0tpFgDIN55553gtqZpIjs7Wzz00EPBsqqqKmE2m8Urr7wihBDi22+/FQDEli1bgnU+/PBDIUmSKCgo6La2U3SFXgtCCLF48WJxySWXtHkMr4W+qaSkRAAQ69evF0KE93mwatUqIcuyKCoqCtZ58sknRVJSkvB4PN37AigqQq8DIYQ466yzxM0339zmMbwOuhd7dMLg9Xqxbds2zJ07N1gmyzLmzp2LTZs29WDLqDscOHAA/fr1w5AhQ3DllVfi+PHjAIBt27bB5/PprotRo0ZhwIABvC76sCNHjqCoqEj3756cnIwZM2YE/903bdoEh8OBadOmBevMnTsXsizjq6++6vY2U2ytW7cOmZmZGDlyJG644QaUl5cH9/Fa6Juqq6sBAKmpqQDC+zzYtGkTxo8fj6ysrGCdefPmoaamBnv37u3G1lO0hF4HjV5++WWkp6dj3LhxuP322+F0OoP7eB10L0NPNyAelJWVQVVV3UUJAFlZWdi/f38PtYq6w4wZM7By5UqMHDkShYWFuPfee3HGGWdgz549KCoqgslkgsPh0B2TlZWFoqKinmkwxVzjv21r7weN+4qKipCZmanbbzAYkJqaymujj5k/fz4uv/xyDB48GIcOHcIdd9yB888/H5s2bYKiKLwW+iBN0/Db3/4Ws2fPxrhx4wAgrM+DoqKiVt83GvdRfGntOgCAn/3sZxg4cCD69euHXbt24fe//z3y8/Px9ttvA+B10N0Y6BC14/zzzw8+njBhAmbMmIGBAwfi9ddfh9Vq7cGWEVFv8JOf/CT4ePz48ZgwYQKGDh2KdevWYc6cOT3YMoqVpUuXYs+ePbr5mnTqaes6aD7/bvz48cjJycGcOXNw6NAhDB06tLubecrj0LUwpKenQ1GUFtlTiouLkZ2d3UOtop7gcDgwYsQIHDx4ENnZ2fB6vaiqqtLV4XXRtzX+27b3fpCdnd0iUYnf70dFRQWvjT5uyJAhSE9Px8GDBwHwWuhrbrrpJrz//vv47LPP0L9//2B5OJ8H2dnZrb5vNO6j+NHWddCaGTNmAIDuPYHXQfdhoBMGk8mEqVOnYs2aNcEyTdOwZs0azJw5swdbRt2trq4Ohw4dQk5ODqZOnQqj0ai7LvLz83H8+HFeF33Y4MGDkZ2drft3r6mpwVdffRX8d585cyaqqqqwbdu2YJ21a9dC07Tghx71TSdOnEB5eTlycnIA8FroK4QQuOmmm/DOO+9g7dq1GDx4sG5/OJ8HM2fOxO7du3WB7yeffIKkpCSMGTOme14IdUlH10Frdu7cCQC69wReB92op7MhxItXX31VmM1msXLlSvHtt9+K6667TjgcDl3WDOp7br31VrFu3Tpx5MgR8cUXX4i5c+eK9PR0UVJSIoQQ4vrrrxcDBgwQa9euFVu3bhUzZ84UM2fO7OFWU1fV1taKHTt2iB07dggA4pFHHhE7duwQx44dE0II8ec//1k4HA7x73//W+zatUtccsklYvDgwcLlcgXPMX/+fDF58mTx1VdfiY0bN4rhw4eLn/70pz31kqiT2rsWamtrxW233SY2bdokjhw5Ij799FMxZcoUMXz4cOF2u4Pn4LUQ/2644QaRnJws1q1bJwoLC4M3p9MZrNPR54Hf7xfjxo0T5513nti5c6dYvXq1yMjIELfffntPvCTqhI6ug4MHD4r77rtPbN26VRw5ckT8+9//FkOGDBFnnnlm8By8DroXA50IPP7442LAgAHCZDKJ6dOni82bN/d0kyjGFi5cKHJycoTJZBK5ubli4cKF4uDBg8H9LpdL3HjjjSIlJUXYbDZx2WWXicLCwh5sMUXDZ599JgC0uC1evFgIEUgxfeedd4qsrCxhNpvFnDlzRH5+vu4c5eXl4qc//amw2+0iKSlJLFmyRNTW1vbAq6GuaO9acDqd4rzzzhMZGRnCaDSKgQMHimuvvbbFD2C8FuJfa9cAAPH8888H64TzeXD06FFx/vnnC6vVKtLT08Wtt94qfD5fN78a6qyOroPjx4+LM888U6Smpgqz2SyGDRsmfve734nq6mrdeXgddB9JCCG6r/+IiIiIiIgo9jhHh4iIiIiI+hwGOkRERERE1Ocw0CEiIiIioj6HgQ4REREREfU5DHSIiIiIiKjPYaBDRERERER9DgMdIiIiIiLqcxjoEBERERFRn8NAh4iITilXXXUV/vSnP8Xs/N9++y369++P+vr6mD0HERF1jIEOEdEp7Be/+AUuvfTSTh+/cuVKOByOqLUn1r755husWrUKv/nNb2L2HGPGjMHpp5+ORx55JGbPQUREHWOgQ0REp4zHH38cV1xxBex2e0yfZ8mSJXjyySfh9/tj+jxERNQ2BjpERNSmRx55BOPHj0dCQgLy8vJw4403oq6uDgCwbt06LFmyBNXV1ZAkCZIk4Z577gEAeDwe3HbbbcjNzUVCQgJmzJiBdevWBc/b2BP00UcfYfTo0bDb7Zg/fz4KCwt1z//cc89h7NixMJvNyMnJwU033QQA+OUvf4mLLrpIV9fn8yEzMxPPPvtsq69FVVW8+eabWLBgga580KBBuP/++7Fo0SLY7XYMHDgQ7733HkpLS3HJJZfAbrdjwoQJ2Lp1a/CYY8eOYcGCBUhJSUFCQgLGjh2LVatWBfefe+65qKiowPr16yP7gxMRUdQw0CEiojbJsoy//e1v2Lt3L1544QWsXbsW//3f/w0AmDVrFh599FEkJSWhsLAQhYWFuO222wAAN910EzZt2oRXX30Vu3btwhVXXIH58+fjwIEDwXM7nU785S9/wYsvvogNGzbg+PHjweMB4Mknn8TSpUtx3XXXYffu3XjvvfcwbNgwAMA111yD1atX6wKj999/H06nEwsXLmz1tezatQvV1dWYNm1ai31//etfMXv2bOzYsQMXXnghrrrqKixatAg///nPsX37dgwdOhSLFi2CEAIAsHTpUng8HmzYsAG7d+/GAw88oOslMplMmDRpEj7//PPO/umJiKirBBERnbIWL14sLrnkkrDrv/HGGyItLS24/fzzz4vk5GRdnWPHjglFUURBQYGufM6cOeL2228PHgdAHDx4MLh/xYoVIisrK7jdr18/8Yc//KHNtowZM0Y88MADwe0FCxaIX/ziF23Wf+edd4SiKELTNF35wIEDxc9//vPgdmFhoQAg7rzzzmDZpk2bBABRWFgohBBi/Pjx4p577mnzuYQQ4rLLLmu3PUREFFvs0SEiojZ9+umnmDNnDnJzc5GYmIirrroK5eXlcDqdbR6ze/duqKqKESNGwG63B2/r16/HoUOHgvVsNhuGDh0a3M7JyUFJSQkAoKSkBCdPnsScOXPafJ5rrrkGzz//PACguLgYH374IX75y1+2Wd/lcsFsNkOSpBb7JkyYEHyclZUFABg/fnyLssb2/eY3v8H999+P2bNn4+6778auXbtanNNqtbb7dyIiothioENERK06evQoLrroIkyYMAFvvfUWtm3bhhUrVgAAvF5vm8fV1dVBURRs27YNO3fuDN727duHxx57LFjPaDTqjpMkKTg0zGq1dti+RYsW4fDhw9i0aRNeeuklDB48GGeccUab9dPT0+F0Oltte/O2NAZCrZVpmgYgEGQdPnwYV111FXbv3o1p06bh8ccf152zoqICGRkZHb4OIiKKDQY6RETUqm3btkHTNDz88MM4/fTTMWLECJw8eVJXx2QyQVVVXdnkyZOhqipKSkowbNgw3S07Ozus505MTMSgQYOwZs2aNuukpaXh0ksvxfPPP4+VK1diyZIl7Z5z0qRJAALr3ERDXl4err/+erz99tu49dZb8cwzz+j279mzB5MnT47KcxERUeQMPd0AIiLqWdXV1di5c6euLC0tDcOGDYPP58Pjjz+OBQsW4IsvvsBTTz2lqzdo0CDU1dVhzZo1mDhxImw2G0aMGIErr7wSixYtwsMPP4zJkyejtLQUa9aswYQJE3DhhReG1a577rkH119/PTIzM3H++eejtrYWX3zxBX79618H61xzzTW46KKLoKoqFi9e3O75MjIyMGXKFGzcuDEY9HTWb3/7W5x//vkYMWIEKisr8dlnn2H06NHB/UePHkVBQQHmzp3bpechIqLOY48OEdEpbt26dZg8ebLudu+992LixIl45JFH8MADD2DcuHF4+eWXsXz5ct2xs2bNwvXXX4+FCxciIyMDDz74IADg+eefx6JFi3Drrbdi5MiRuPTSS7FlyxYMGDAg7HYtXrwYjz76KJ544gmMHTsWF110kS5rGwDMnTsXOTk5mDdvHvr169fhOa+55hq8/PLLYbehLaqqYunSpRg9ejTmz5+PESNG4Iknngjuf+WVV3Deeedh4MCBXX4uIiLqHEk0DogmIiKKM3V1dcjNzcXzzz+Pyy+/vMP6LpcLI0eOxGuvvYaZM2fGpE1erxfDhw/H//3f/2H27NkxeQ4iIuoYh64REVHc0TQNZWVlePjhh+FwOHDxxReHdZzVasW//vUvlJWVxaxtx48fxx133MEgh4ioh7FHh4iI4s7Ro0cxePBg9O/fHytXrmw3DTUREZ2aGOgQEREREVGfw2QERERERETU5zDQISIiIiKiPoeBDhERERER9TkMdIiIiIiIqM9hoENERERERH0OAx0iIiIiIupzGOgQEREREVGfw0CHiIiIiIj6nP8PYBqNS9yLLCsAAAAASUVORK5CYII=" 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" }, "metadata": {}, "output_type": "display_data" @@ -261,15 +266,15 @@ "metadata": { "scrolled": false, "ExecuteTime": { - "end_time": "2023-11-03T16:22:30.687841Z", - "start_time": "2023-11-03T16:22:30.511022Z" + "end_time": "2023-11-16T17:43:44.228872Z", + "start_time": "2023-11-16T17:43:44.061343Z" } }, "outputs": [ { "data": { "text/plain": "
", - "image/png": 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" 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" }, "metadata": {}, "output_type": "display_data" diff --git a/demos/demo_plotting.ipynb b/demos/demo_plotting.ipynb index e7767223..3afca4d3 100644 --- a/demos/demo_plotting.ipynb +++ b/demos/demo_plotting.ipynb @@ -7,18 +7,15 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2023-11-16T15:07:16.397964Z", - "start_time": "2023-11-16T15:07:14.938429Z" + "end_time": "2023-11-16T17:42:05.719071Z", + "start_time": "2023-11-16T17:42:04.158167Z" } }, "outputs": [], "source": [ - "from os import path\n", - "from pathlib import Path\n", - "\n", - "from kymata.plot.plotting import expression_plot\n", "from kymata.entities.expression import ExpressionSet\n", - "from kymata.datasets.sample import get_dataset_kymata_mirror_q3_2023" + "from kymata.plot.plotting import expression_plot\n", + "from kymata.datasets.sample import KymataMirror2023Q3Dataset" ] }, { @@ -78,11 +75,8 @@ } ], "source": [ - "# set location of tutorial data\n", - "sample_data_dir = Path(Path(path.abspath(\"\")).parent, \"data\", \"sample-data\")\n", - "\n", - "# create new expression set object and add to it\n", - "expression_data_kymata_mirror = ExpressionSet.from_sample_dataset(get_dataset_kymata_mirror_q3_2023())\n", + "# We'll create new expression set object and add to it\n", + "expression_data_kymata_mirror: ExpressionSet = KymataMirror2023Q3Dataset().to_expressionset()\n", "\n", "# print the names of all available functions in the expressionSet object\n", "print(\"\\n\".join(expression_data_kymata_mirror.functions))" @@ -90,8 +84,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T15:07:19.664622Z", - "start_time": "2023-11-16T15:07:16.404646Z" + "end_time": "2023-11-16T17:42:09.477738Z", + "start_time": "2023-11-16T17:42:05.721193Z" } }, "id": "4023a711ee8a1675" @@ -116,8 +110,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T15:07:24.985700Z", - "start_time": "2023-11-16T15:07:19.664759Z" + "end_time": "2023-11-16T17:42:15.053885Z", + "start_time": "2023-11-16T17:42:09.478074Z" } }, "id": "d466d1d098417e8" @@ -148,8 +142,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T15:07:26.736174Z", - "start_time": "2023-11-16T15:07:24.984193Z" + "end_time": "2023-11-16T17:42:17.761039Z", + "start_time": "2023-11-16T17:42:15.052261Z" } }, "id": "d77e82f5aaaa4e74" @@ -181,8 +175,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T15:07:27.980010Z", - "start_time": "2023-11-16T15:07:26.737767Z" + "end_time": "2023-11-16T17:42:18.291306Z", + "start_time": "2023-11-16T17:42:16.899062Z" } }, "id": "2c27c48ebb92d21a" @@ -249,8 +243,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T15:07:30.950826Z", - "start_time": "2023-11-16T15:07:27.982844Z" + "end_time": "2023-11-16T17:42:21.477482Z", + "start_time": "2023-11-16T17:42:18.298132Z" } }, "id": "736f99a2ddc28751" diff --git a/demos/demo_save_load.ipynb b/demos/demo_save_load.ipynb index b760a62f..0d71cd9d 100644 --- a/demos/demo_save_load.ipynb +++ b/demos/demo_save_load.ipynb @@ -7,8 +7,8 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2023-11-10T20:02:56.737736Z", - "start_time": "2023-11-10T20:02:56.215552Z" + "end_time": "2023-11-16T17:43:47.830263Z", + "start_time": "2023-11-16T17:43:46.709113Z" } }, "outputs": [], @@ -17,10 +17,8 @@ "from pathlib import Path\n", "from tempfile import NamedTemporaryFile\n", "\n", - "from kymata.datasets.sample import get_dataset_kymata_mirror_q3_2023, get_dataset_gm_loudness, \\\n", - " get_dataset_d_ins_loudness_tonop_chan1\n", - "from kymata.entities.expression import ExpressionSet\n", - "from kymata.io.matlab import load_matab_expression_files" + "from kymata.datasets.sample import KymataMirror2023Q3Dataset, GMLoudnessDataset, GMDeltaInstantaneousLoudnessTonotopicChannel1Dataset\n", + "from kymata.entities.expression import ExpressionSet" ] }, { @@ -32,7 +30,7 @@ "output_type": "stream", "text": [ "Downloading dataset: kymata_mirror_Q3_2023\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//kymata_mirror_Q3_2023_expression_endtable.nkg to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n" + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n" ] } ], @@ -41,14 +39,13 @@ "sample_data_dir = Path(Path(path.abspath(\"\")).parent, \"data\", \"sample-data\")\n", "\n", "# Start with sample dataset\n", - "dataset_q3_2023 = get_dataset_kymata_mirror_q3_2023()\n", - "expression_data_kymata_mirror = ExpressionSet.load(from_path_or_file=Path(dataset_q3_2023.path, dataset_q3_2023.filenames[0]))\n" + "expression_data_kymata_mirror: ExpressionSet = KymataMirror2023Q3Dataset().to_expressionset()\n" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-10T20:03:00.508482Z", - "start_time": "2023-11-10T20:02:56.738612Z" + "end_time": "2023-11-16T17:43:51.004805Z", + "start_time": "2023-11-16T17:43:47.836303Z" } }, "id": "4df17a3a727b7c02" @@ -62,11 +59,11 @@ "output_type": "stream", "text": [ "Downloading dataset: GMLoudness\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Downloading dataset: GMLoudness\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n" + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", + "Downloading dataset: GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1\n", + "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", + "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n" ] } ], @@ -74,24 +71,14 @@ "# Get a second sample dataset\n", "\n", "# Create new expression set object for the new results (or you can just add to an existing expressionSet directly using '+=' ).\n", - "dataset_gm_loudness = get_dataset_gm_loudness()\n", - "expression_data_new_results = load_matab_expression_files(\n", - " function_name=\"ins_loudness_2020\",\n", - " lh_file=Path(dataset_gm_loudness.path, dataset_gm_loudness.filenames[0]),\n", - " rh_file=Path(dataset_gm_loudness.path, dataset_gm_loudness.filenames[1]),\n", - ")\n", - "dataset_d_ins_loudness_tonop_chan1 = get_dataset_d_ins_loudness_tonop_chan1()\n", - "expression_data_new_results += load_matab_expression_files(\n", - " function_name=\"delta_ins_loudness_tonotop_chan1_2020\",\n", - " lh_file=Path(dataset_d_ins_loudness_tonop_chan1.path, dataset_d_ins_loudness_tonop_chan1.filenames[0]),\n", - " rh_file=Path(dataset_d_ins_loudness_tonop_chan1.path, dataset_d_ins_loudness_tonop_chan1.filenames[1]),\n", - ")" + "expression_data_new_results = GMLoudnessDataset().to_expressionset()\n", + "expression_data_new_results += GMDeltaInstantaneousLoudnessTonotopicChannel1Dataset().to_expressionset()" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-10T20:03:11.535225Z", - "start_time": "2023-11-10T20:03:00.507022Z" + "end_time": "2023-11-16T17:44:00.396583Z", + "start_time": "2023-11-16T17:43:51.006473Z" } }, "id": "681594ea282bf0f" @@ -120,8 +107,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-10T20:03:18.279668Z", - "start_time": "2023-11-10T20:03:11.536073Z" + "end_time": "2023-11-16T17:44:11.663681Z", + "start_time": "2023-11-16T17:44:00.398815Z" } }, "id": "77c6c3617357edbb" diff --git a/kymata/datasets/sample.py b/kymata/datasets/sample.py index 615a38e5..bb225354 100644 --- a/kymata/datasets/sample.py +++ b/kymata/datasets/sample.py @@ -1,11 +1,12 @@ -from dataclasses import dataclass +from abc import ABC, abstractmethod from os import getenv, getcwd, remove, rmdir from pathlib import Path from typing import Optional from urllib import request +from kymata.entities.expression import ExpressionSet from kymata.io.file import path_type - +from kymata.io.matlab import load_matab_expression_files _DATA_PATH_ENVIRONMENT_VAR_NAME = "KYMATA_DATA_ROOT" _DATA_DIR_NAME = "kymata_data" @@ -19,21 +20,110 @@ ] -@dataclass -class SampleDataset: +class SampleDataset(ABC): """ Info required to retrieve a dataset stored locally. Names in `.filenames` refer to local files, which (if `remote_root` is specified) are paired with identically named remote files. """ - name: str - path: Path - filenames: list[str] - remote_root: Optional[str] = None + + def __init__(self, + name: str, + filenames: list[str], + data_root: Optional[path_type], + remote_root: Optional[str], + download: bool): + self.name: str = name + self.filenames: list[str] = filenames + self.data_root: Path = data_root_path(data_root) + self.remote_root: str = remote_root + + if download: + self.download() + + @property + def path(self) -> Path: + return Path(self.data_root, self.name) def download(self): - _download_dataset(self) + print(f"Downloading dataset: {self.name}") + if self.remote_root is None: + raise ValueError("No remote root provided") + self.path.mkdir(exist_ok=True) + for filename in self.filenames: + remote = self.remote_root + "/" + filename + local = Path(self.path, filename) + if local.exists(): + print(f"Local file already exists: {local}") + else: + print(f"Downloading {remote} to {local}") + request.urlretrieve(remote, local) + + @abstractmethod + def to_expressionset(self) -> ExpressionSet: + raise NotImplementedError() + + +class KymataMirror2023Q3Dataset(SampleDataset): + def __init__(self, data_root: Optional[path_type] = None, download: bool = True): + name = "kymata_mirror_Q3_2023" + super().__init__( + name=name, + filenames=[ + "kymata_mirror_Q3_2023_expression_endtable.nkg", + ], + data_root=data_root, + remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", + download=download, + ) + + def to_expressionset(self) -> ExpressionSet: + return ExpressionSet.load(from_path_or_file=Path(self.path, self.filenames[0])) + + +class GMLoudnessDataset(SampleDataset): + def __init__(self, data_root: Optional[path_type] = None, download: bool = True): + name = "GMLoudness" + super().__init__( + name=name, + filenames=[ + "GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", + "GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", + ], + data_root=data_root, + remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", + download=download, + ) + + def to_expressionset(self) -> ExpressionSet: + return load_matab_expression_files( + function_name="ins_loudness_2020", + lh_file=Path(self.path, self.filenames[0]), + rh_file=Path(self.path, self.filenames[1]), + ) + + +class GMDeltaInstantaneousLoudnessTonotopicChannel1Dataset(SampleDataset): + def __init__(self, data_root: Optional[path_type] = None, download: bool = True): + name = "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1" + super().__init__( + name=name, + filenames=[ + "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", + "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", + ], + data_root=data_root, + remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", + download=download, + ) + + def to_expressionset(self) -> ExpressionSet: + return load_matab_expression_files( + function_name="delta_ins_loudness_tonotop_chan1_2020", + lh_file=Path(self.path, self.filenames[0]), + rh_file=Path(self.path, self.filenames[1]), + ) def data_root_path(data_root: Optional[path_type] = None) -> Path: @@ -92,71 +182,6 @@ def data_root_path(data_root: Optional[path_type] = None) -> Path: return data_root -def _download_dataset(local_dataset): - print(f"Downloading dataset: {local_dataset.name}") - if local_dataset.remote_root is None: - raise ValueError("No remote root provided") - local_dataset.path.mkdir(exist_ok=True) - for filename in local_dataset.filenames: - remote = local_dataset.remote_root + "/" + filename - local = Path(local_dataset.path, filename) - if local.exists(): - print(f"Local file already exists: {local}") - else: - print(f"Downloading {remote} to {local}") - request.urlretrieve(remote, local) - - -def get_dataset_kymata_mirror_q3_2023(download: bool = True, data_root: Optional[path_type] = None) -> SampleDataset: - name = "kymata_mirror_Q3_2023" - - local_dataset = SampleDataset( - name=name, - path=Path(data_root_path(data_root=data_root), name), - filenames=[ - "kymata_mirror_Q3_2023_expression_endtable.nkg", - ], - remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", - ) - if download: - local_dataset.download() - return local_dataset - - -def get_dataset_gm_loudness(download: bool = True, data_root: Optional[path_type] = None) -> SampleDataset: - name = "GMLoudness" - - local_dataset = SampleDataset( - name=name, - path=Path(data_root_path(data_root=data_root), name), - filenames=[ - "GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", - "GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", - ], - remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", - ) - if download: - local_dataset.download() - return local_dataset - - -def get_dataset_d_ins_loudness_tonop_chan1(download: bool = True, data_root: Optional[path_type] = None) -> SampleDataset: - name = "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1" - - local_dataset = SampleDataset( - name=name, - path=Path(data_root_path(data_root=data_root), name), - filenames=[ - "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", - "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", - ], - remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", - ) - if download: - local_dataset.download() - return local_dataset - - def delete_dataset(local_dataset: SampleDataset): # Make sure it's not silent print(f"Deleting dataset {local_dataset.name}") diff --git a/kymata/entities/expression.py b/kymata/entities/expression.py index ee5a9964..0085404c 100644 --- a/kymata/entities/expression.py +++ b/kymata/entities/expression.py @@ -16,7 +16,6 @@ from xarray import DataArray, Dataset, concat from pandas import DataFrame -from kymata.datasets.sample import SampleDataset from kymata.entities.sparse_data import expand_dims, minimise_pmatrix, densify_dataset from kymata.io.file import open_or_use, file_type, path_type @@ -287,10 +286,6 @@ def load(cls, from_path_or_file: path_type | file_type) -> ExpressionSet: data_rh=[right_sparse[:, :, i] for i in range(len(functions))], ) - @classmethod - def from_sample_dataset(cls, sample_dataset: SampleDataset) -> ExpressionSet: - return cls.load(from_path_or_file=Path(sample_dataset.path, sample_dataset.filenames[0])) - def best_functions(self) -> Tuple[DataFrame, DataFrame]: """ Return a pair of DataFrames (left, right), containing: diff --git a/kymata/plot/plotting.py b/kymata/plot/plotting.py index e78e2c5a..0656bab7 100644 --- a/kymata/plot/plotting.py +++ b/kymata/plot/plotting.py @@ -184,12 +184,12 @@ def _get_yticks(ylim): if __name__ == '__main__': - from kymata.datasets.sample import get_dataset_kymata_mirror_q3_2023 + from kymata.datasets.sample import KymataMirror2023Q3Dataset # set location of tutorial data sample_data_dir = Path(Path(path.abspath("")).parent.parent, "data", "sample-data") # create new expression set object and add to it - expression_data_kymata_mirror = ExpressionSet.from_sample_dataset(get_dataset_kymata_mirror_q3_2023()) + expression_data_kymata_mirror = KymataMirror2023Q3Dataset().to_expressionset() expression_plot(expression_data_kymata_mirror, show_only=expression_data_kymata_mirror.functions[1:], save_to=Path("/Users/cai/Desktop/temp.png")) diff --git a/tests/test_datasets.py b/tests/test_datasets.py index f636d562..97ea4246 100644 --- a/tests/test_datasets.py +++ b/tests/test_datasets.py @@ -1,10 +1,11 @@ from pathlib import Path -from kymata.datasets.sample import get_dataset_kymata_mirror_q3_2023, delete_dataset, get_dataset_gm_loudness +from kymata.datasets.sample import delete_dataset def test_download_and_delete_q3_2023_data_files(): - dataset = get_dataset_kymata_mirror_q3_2023(download=False) + from kymata.datasets.sample import KymataMirror2023Q3Dataset + dataset = KymataMirror2023Q3Dataset(download=False) try: dataset.download() for filename in dataset.filenames: @@ -16,7 +17,8 @@ def test_download_and_delete_q3_2023_data_files(): def test_download_and_delete_gm_loudness3_data_files(): - dataset = get_dataset_gm_loudness(download=False) + from kymata.datasets.sample import GMLoudnessDataset + dataset = GMLoudnessDataset(download=False) try: dataset.download() for filename in dataset.filenames: From ac79c903f50110fd563a7e19f1e5a819d801b80d Mon Sep 17 00:00:00 2001 From: Cai Wingfield Date: Thu, 16 Nov 2023 19:09:54 +0000 Subject: [PATCH 3/6] Make notebooks more explicit about how to load data --- demos/demo_plotting.ipynb | 2 ++ demos/demo_save_load.ipynb | 33 ++++++++++++++++++++------------- 2 files changed, 22 insertions(+), 13 deletions(-) diff --git a/demos/demo_plotting.ipynb b/demos/demo_plotting.ipynb index 3afca4d3..64721cd2 100644 --- a/demos/demo_plotting.ipynb +++ b/demos/demo_plotting.ipynb @@ -76,6 +76,8 @@ ], "source": [ "# We'll create new expression set object and add to it\n", + "\n", + "# For more explanation of saving and loading ExpressionSets, see the demo_save_load.ipynb\n", "expression_data_kymata_mirror: ExpressionSet = KymataMirror2023Q3Dataset().to_expressionset()\n", "\n", "# print the names of all available functions in the expressionSet object\n", diff --git a/demos/demo_save_load.ipynb b/demos/demo_save_load.ipynb index 0d71cd9d..4e312301 100644 --- a/demos/demo_save_load.ipynb +++ b/demos/demo_save_load.ipynb @@ -7,8 +7,8 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2023-11-16T17:43:47.830263Z", - "start_time": "2023-11-16T17:43:46.709113Z" + "end_time": "2023-11-16T18:38:00.217236Z", + "start_time": "2023-11-16T18:37:59.180817Z" } }, "outputs": [], @@ -30,7 +30,8 @@ "output_type": "stream", "text": [ "Downloading dataset: kymata_mirror_Q3_2023\n", - "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n" + "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//kymata_mirror_Q3_2023_expression_endtable.nkg to /Users/cai/Dox/Work/Kymata lab/Code/kymata-toolbox/data/sample-data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n", + "kymata_mirror_Q3_2023_expression_endtable.nkg\n" ] } ], @@ -38,14 +39,20 @@ "# set location of tutorial data\n", "sample_data_dir = Path(Path(path.abspath(\"\")).parent, \"data\", \"sample-data\")\n", "\n", - "# Start with sample dataset\n", - "expression_data_kymata_mirror: ExpressionSet = KymataMirror2023Q3Dataset().to_expressionset()\n" + "# First we'll download some sample data provided by the Kymata Atlas\n", + "sample_dataset = KymataMirror2023Q3Dataset(data_root=sample_data_dir, download=True)\n", + "# This downloads a .nkg file, containing both lefthand and righthand data for a set of functions\n", + "nkg_path = Path(sample_dataset.path, sample_dataset.filenames[0])\n", + "print(nkg_path.name)\n", + "\n", + "# We load this file into an ExpressionSet object\n", + "expression_data_kymata_mirror = ExpressionSet.load(from_path_or_file=nkg_path)" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T17:43:51.004805Z", - "start_time": "2023-11-16T17:43:47.836303Z" + "end_time": "2023-11-16T18:38:04.306612Z", + "start_time": "2023-11-16T18:38:00.218669Z" } }, "id": "4df17a3a727b7c02" @@ -62,8 +69,8 @@ "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", "Downloading dataset: GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat to /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n" + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n" ] } ], @@ -77,8 +84,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T17:44:00.396583Z", - "start_time": "2023-11-16T17:43:51.006473Z" + "end_time": "2023-11-16T18:38:10.580466Z", + "start_time": "2023-11-16T18:38:04.306977Z" } }, "id": "681594ea282bf0f" @@ -107,8 +114,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T17:44:11.663681Z", - "start_time": "2023-11-16T17:44:00.398815Z" + "end_time": "2023-11-16T18:38:21.746972Z", + "start_time": "2023-11-16T18:38:10.581418Z" } }, "id": "77c6c3617357edbb" From 1b071a462129fb0d7fcb29a0960c26a48b09f7ac Mon Sep 17 00:00:00 2001 From: neukym Date: Fri, 17 Nov 2023 17:24:40 +0000 Subject: [PATCH 4/6] Update demo_save_load.ipynb --- demos/demo_save_load.ipynb | 57 ++++++++++++++++++-------------------- 1 file changed, 27 insertions(+), 30 deletions(-) diff --git a/demos/demo_save_load.ipynb b/demos/demo_save_load.ipynb index 4e312301..afbb7f3f 100644 --- a/demos/demo_save_load.ipynb +++ b/demos/demo_save_load.ipynb @@ -2,13 +2,13 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, "id": "initial_id", "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2023-11-16T18:38:00.217236Z", - "start_time": "2023-11-16T18:37:59.180817Z" + "end_time": "2023-11-17T14:54:55.548333Z", + "start_time": "2023-11-17T14:54:53.847330Z" } }, "outputs": [], @@ -23,14 +23,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 8, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading dataset: kymata_mirror_Q3_2023\n", - "Downloading https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data//kymata_mirror_Q3_2023_expression_endtable.nkg to /Users/cai/Dox/Work/Kymata lab/Code/kymata-toolbox/data/sample-data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n", + "Local file already exists: /Users/administration/Github/kymata-toolbox/data/sample-data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n", "kymata_mirror_Q3_2023_expression_endtable.nkg\n" ] } @@ -51,29 +51,16 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T18:38:04.306612Z", - "start_time": "2023-11-16T18:38:00.218669Z" + "end_time": "2023-11-17T16:16:48.039300Z", + "start_time": "2023-11-17T16:16:48.036796Z" } }, "id": "4df17a3a727b7c02" }, { "cell_type": "code", - "execution_count": 3, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Downloading dataset: GMLoudness\n", - "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMLoudness/GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Downloading dataset: GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1\n", - "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Data/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n" - ] - } - ], + "execution_count": 10, + "outputs": [], "source": [ "# Get a second sample dataset\n", "\n", @@ -84,22 +71,32 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T18:38:10.580466Z", - "start_time": "2023-11-16T18:38:04.306977Z" + "end_time": "2023-11-17T16:19:35.681567Z", + "start_time": "2023-11-17T16:19:34.481894Z" } }, "id": "681594ea282bf0f" }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 7, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "/Users/cai/Dox/Work/Kymata lab/Code/kymata-toolbox/kymata/entities/expression.py:215: UserWarning: Experimental function. The on-disk data format for ExpressionSet is not yet fixed. Files saved using .save should not (yet) be treated as stable or future-proof.\n", - " warn(\"Experimental function. \"\n" + "Data root set at /Users/administration/Github/kymata-toolbox/kymata_data.\n", + "Consider setting this as environmental variable KYMATA_DATA_ROOT to ensure it's reused next time.\n", + "Hint: $> KYMATA_DATA_ROOT=\"/Users/administration/Github/kymata-toolbox/kymata_data\"\n", + "Downloading dataset: GMLoudness\n", + "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMLoudness/GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", + "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMLoudness/GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", + "Data root set at /Users/administration/Github/kymata-toolbox/kymata_data.\n", + "Consider setting this as environmental variable KYMATA_DATA_ROOT to ensure it's reused next time.\n", + "Hint: $> KYMATA_DATA_ROOT=\"/Users/administration/Github/kymata-toolbox/kymata_data\"\n", + "Downloading dataset: GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1\n", + "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", + "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n" ] } ], @@ -114,8 +111,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-16T18:38:21.746972Z", - "start_time": "2023-11-16T18:38:10.581418Z" + "end_time": "2023-11-17T14:55:17.432084Z", + "start_time": "2023-11-17T14:55:14.771992Z" } }, "id": "77c6c3617357edbb" From ee5083189e3f4fc3ec777101d60e5f8897db429b Mon Sep 17 00:00:00 2001 From: neukym Date: Sun, 19 Nov 2023 17:53:48 +0000 Subject: [PATCH 5/6] Updates code to use only .nkg files --- demos/demo_save_load.ipynb | 92 +++++++++++++++++++++++--------------- kymata/datasets/sample.py | 27 ++++------- 2 files changed, 64 insertions(+), 55 deletions(-) diff --git a/demos/demo_save_load.ipynb b/demos/demo_save_load.ipynb index afbb7f3f..170e7e71 100644 --- a/demos/demo_save_load.ipynb +++ b/demos/demo_save_load.ipynb @@ -2,13 +2,13 @@ "cells": [ { "cell_type": "code", - "execution_count": 4, + "execution_count": 1, "id": "initial_id", "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2023-11-17T14:54:55.548333Z", - "start_time": "2023-11-17T14:54:53.847330Z" + "end_time": "2023-11-19T17:38:45.841572Z", + "start_time": "2023-11-19T17:38:45.202251Z" } }, "outputs": [], @@ -17,13 +17,13 @@ "from pathlib import Path\n", "from tempfile import NamedTemporaryFile\n", "\n", - "from kymata.datasets.sample import KymataMirror2023Q3Dataset, GMLoudnessDataset, GMDeltaInstantaneousLoudnessTonotopicChannel1Dataset\n", + "from kymata.datasets.sample import KymataMirror2023Q3Dataset, TVLInsLoudnessOnlyDataset, TVLDeltaInsTC1LoudnessOnlyDataset\n", "from kymata.entities.expression import ExpressionSet" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "outputs": [ { "name": "stdout", @@ -31,77 +31,97 @@ "text": [ "Downloading dataset: kymata_mirror_Q3_2023\n", "Local file already exists: /Users/administration/Github/kymata-toolbox/data/sample-data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n", - "kymata_mirror_Q3_2023_expression_endtable.nkg\n" + "kymata_mirror_Q3_2023_expression_endtable.nkg\n", + "Downloading dataset: TVL_2020_ins_loudness_only\n", + "Local file already exists: /Users/administration/Github/kymata-toolbox/data/sample-data/TVL_2020_ins_loudness_only/TVL_2020_ins_loudness_only.nkg\n", + "Downloading dataset: TVL_2020_delta_ins_tontop_chan1_loudness_only\n", + "Local file already exists: /Users/administration/Github/kymata-toolbox/data/sample-data/TVL_2020_delta_ins_tontop_chan1_loudness_only/TVL_2020_delta_ins_tontop_chan1_loudness_only.nkg\n" ] } ], "source": [ + "## Download sample data. This cell can be ignored if you wish to load your own\n", + "## data from a gridsearch.\n", + "\n", "# set location of tutorial data\n", "sample_data_dir = Path(Path(path.abspath(\"\")).parent, \"data\", \"sample-data\")\n", "\n", - "# First we'll download some sample data provided by the Kymata Atlas\n", + "# First we'll download a sample .nkg file which loads a range of functions,\n", + "# from the Kymata Research Group. nkg files contain both lefthand and\n", + "# righthand data for a set of functions\n", + "\n", "sample_dataset = KymataMirror2023Q3Dataset(data_root=sample_data_dir, download=True)\n", - "# This downloads a .nkg file, containing both lefthand and righthand data for a set of functions\n", "nkg_path = Path(sample_dataset.path, sample_dataset.filenames[0])\n", "print(nkg_path.name)\n", "\n", - "# We load this file into an ExpressionSet object\n", + "# Second we will download two .nkg files which only contain one\n", + "# function each - 'ins_loudness' and 'd_ins_tc1_loudness':\n", + "ins_loudness_only_dataset = TVLInsLoudnessOnlyDataset(data_root=sample_data_dir, download=True)\n", + "ins_loudness_path = Path(ins_loudness_only_dataset.path, ins_loudness_only_dataset.filenames[0])\n", + "\n", + "d_ins_tc1_loudness_only_dataset = TVLDeltaInsTC1LoudnessOnlyDataset(data_root=sample_data_dir, download=True)\n", + "d_ins_tc1_loudness_path = Path(d_ins_tc1_loudness_only_dataset.path, d_ins_tc1_loudness_only_dataset.filenames[0])" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-11-19T17:46:34.078784Z", + "start_time": "2023-11-19T17:46:34.069744Z" + } + }, + "id": "1f36e2e91b52522f" + }, + { + "cell_type": "code", + "execution_count": 4, + "outputs": [], + "source": [ + "# Let's load the KymataMirror2023Q3 .nkg file. This contains around 30 functions.\n", "expression_data_kymata_mirror = ExpressionSet.load(from_path_or_file=nkg_path)" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-17T16:16:48.039300Z", - "start_time": "2023-11-17T16:16:48.036796Z" + "end_time": "2023-11-19T17:46:29.809860Z", + "start_time": "2023-11-19T17:46:28.647459Z" } }, "id": "4df17a3a727b7c02" }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "outputs": [], "source": [ - "# Get a second sample dataset\n", - "\n", - "# Create new expression set object for the new results (or you can just add to an existing expressionSet directly using '+=' ).\n", - "expression_data_new_results = GMLoudnessDataset().to_expressionset()\n", - "expression_data_new_results += GMDeltaInstantaneousLoudnessTonotopicChannel1Dataset().to_expressionset()" + "# Let's seperately load the 'ins_loudness' .nkg file, and then load and add the\n", + "# d_ins_tc1_loudness to it using '+='. 'expression_data_new_results' now contains two functions.\n", + "expression_data_new_results = ExpressionSet.load(from_path_or_file=ins_loudness_path)\n", + "expression_data_new_results += ExpressionSet.load(from_path_or_file=d_ins_tc1_loudness_path)" ], "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-17T16:19:35.681567Z", - "start_time": "2023-11-17T16:19:34.481894Z" + "end_time": "2023-11-19T17:46:40.422043Z", + "start_time": "2023-11-19T17:46:39.774911Z" } }, "id": "681594ea282bf0f" }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Data root set at /Users/administration/Github/kymata-toolbox/kymata_data.\n", - "Consider setting this as environmental variable KYMATA_DATA_ROOT to ensure it's reused next time.\n", - "Hint: $> KYMATA_DATA_ROOT=\"/Users/administration/Github/kymata-toolbox/kymata_data\"\n", - "Downloading dataset: GMLoudness\n", - "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMLoudness/GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMLoudness/GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Data root set at /Users/administration/Github/kymata-toolbox/kymata_data.\n", - "Consider setting this as environmental variable KYMATA_DATA_ROOT to ensure it's reused next time.\n", - "Hint: $> KYMATA_DATA_ROOT=\"/Users/administration/Github/kymata-toolbox/kymata_data\"\n", - "Downloading dataset: GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1\n", - "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n", - "Local file already exists: /Users/administration/Github/kymata-toolbox/kymata_data/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1/GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat\n" + "/Users/administration/Github/kymata-toolbox/kymata/entities/expression.py:215: UserWarning: Experimental function. The on-disk data format for ExpressionSet is not yet fixed. Files saved using .save should not (yet) be treated as stable or future-proof.\n", + " warn(\"Experimental function. \"\n" ] } ], "source": [ - "# You can add two ExpressionSets together\n", + "# We can add these two ExpressionSets together with '+' or \"=+\"\n", "expression_data_extended = expression_data_kymata_mirror + expression_data_new_results\n", "\n", "# Save new expressionSet for use again in the future.\n", @@ -111,8 +131,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-17T14:55:17.432084Z", - "start_time": "2023-11-17T14:55:14.771992Z" + "end_time": "2023-11-19T17:46:52.217736Z", + "start_time": "2023-11-19T17:46:45.070575Z" } }, "id": "77c6c3617357edbb" diff --git a/kymata/datasets/sample.py b/kymata/datasets/sample.py index bb225354..6d580fc4 100644 --- a/kymata/datasets/sample.py +++ b/kymata/datasets/sample.py @@ -82,14 +82,13 @@ def to_expressionset(self) -> ExpressionSet: return ExpressionSet.load(from_path_or_file=Path(self.path, self.filenames[0])) -class GMLoudnessDataset(SampleDataset): +class TVLInsLoudnessOnlyDataset(SampleDataset): def __init__(self, data_root: Optional[path_type] = None, download: bool = True): - name = "GMLoudness" + name = "TVL_2020_ins_loudness_only" super().__init__( name=name, filenames=[ - "GMLoudness_lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", - "GMLoudness_rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", + "TVL_2020_ins_loudness_only.nkg", ], data_root=data_root, remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", @@ -97,33 +96,23 @@ def __init__(self, data_root: Optional[path_type] = None, download: bool = True) ) def to_expressionset(self) -> ExpressionSet: - return load_matab_expression_files( - function_name="ins_loudness_2020", - lh_file=Path(self.path, self.filenames[0]), - rh_file=Path(self.path, self.filenames[1]), - ) + return ExpressionSet.load(from_path_or_file=Path(self.path, self.filenames[0])) -class GMDeltaInstantaneousLoudnessTonotopicChannel1Dataset(SampleDataset): +class TVLDeltaInsTC1LoudnessOnlyDataset(SampleDataset): def __init__(self, data_root: Optional[path_type] = None, download: bool = True): - name = "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1" + name = "TVL_2020_delta_ins_tontop_chan1_loudness_only" super().__init__( name=name, filenames=[ - "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__lh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", - "GMloudness_tonotop_82dB_d_ins_loudness_tonop_chan1__rh_10242verts_-200-800ms_cuttoff1000_5perms_ttestpval.mat", - ], + "TVL_2020_delta_ins_tontop_chan1_loudness_only.nkg", ], data_root=data_root, remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", download=download, ) def to_expressionset(self) -> ExpressionSet: - return load_matab_expression_files( - function_name="delta_ins_loudness_tonotop_chan1_2020", - lh_file=Path(self.path, self.filenames[0]), - rh_file=Path(self.path, self.filenames[1]), - ) + return ExpressionSet.load(from_path_or_file=Path(self.path, self.filenames[0])) def data_root_path(data_root: Optional[path_type] = None) -> Path: From f2779e26b02b08a2ebc5d655432393c0c9071ea1 Mon Sep 17 00:00:00 2001 From: Cai Wingfield Date: Fri, 24 Nov 2023 14:59:33 +0000 Subject: [PATCH 6/6] Fix test and remove unused code --- demos/demo_save_load.ipynb | 36 ++++++++++++++++++------------------ kymata/datasets/sample.py | 4 ++-- tests/test_datasets.py | 4 ++-- 3 files changed, 22 insertions(+), 22 deletions(-) diff --git a/demos/demo_save_load.ipynb b/demos/demo_save_load.ipynb index 170e7e71..900e186c 100644 --- a/demos/demo_save_load.ipynb +++ b/demos/demo_save_load.ipynb @@ -7,8 +7,8 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2023-11-19T17:38:45.841572Z", - "start_time": "2023-11-19T17:38:45.202251Z" + "end_time": "2023-11-24T14:58:41.997983Z", + "start_time": "2023-11-24T14:58:41.316625Z" } }, "outputs": [], @@ -23,19 +23,19 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading dataset: kymata_mirror_Q3_2023\n", - "Local file already exists: /Users/administration/Github/kymata-toolbox/data/sample-data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n", + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Code/kymata-toolbox/data/sample-data/kymata_mirror_Q3_2023/kymata_mirror_Q3_2023_expression_endtable.nkg\n", "kymata_mirror_Q3_2023_expression_endtable.nkg\n", "Downloading dataset: TVL_2020_ins_loudness_only\n", - "Local file already exists: /Users/administration/Github/kymata-toolbox/data/sample-data/TVL_2020_ins_loudness_only/TVL_2020_ins_loudness_only.nkg\n", + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Code/kymata-toolbox/data/sample-data/TVL_2020_ins_loudness_only/TVL_2020_ins_loudness_only.nkg\n", "Downloading dataset: TVL_2020_delta_ins_tontop_chan1_loudness_only\n", - "Local file already exists: /Users/administration/Github/kymata-toolbox/data/sample-data/TVL_2020_delta_ins_tontop_chan1_loudness_only/TVL_2020_delta_ins_tontop_chan1_loudness_only.nkg\n" + "Local file already exists: /Users/cai/Dox/Work/Kymata lab/Code/kymata-toolbox/data/sample-data/TVL_2020_delta_ins_tontop_chan1_loudness_only/TVL_2020_delta_ins_tontop_chan1_loudness_only.nkg\n" ] } ], @@ -65,15 +65,15 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-19T17:46:34.078784Z", - "start_time": "2023-11-19T17:46:34.069744Z" + "end_time": "2023-11-24T14:58:42.005080Z", + "start_time": "2023-11-24T14:58:42.000338Z" } }, "id": "1f36e2e91b52522f" }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "outputs": [], "source": [ "# Let's load the KymataMirror2023Q3 .nkg file. This contains around 30 functions.\n", @@ -82,15 +82,15 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-19T17:46:29.809860Z", - "start_time": "2023-11-19T17:46:28.647459Z" + "end_time": "2023-11-24T14:58:45.622635Z", + "start_time": "2023-11-24T14:58:42.003480Z" } }, "id": "4df17a3a727b7c02" }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "outputs": [], "source": [ "# Let's seperately load the 'ins_loudness' .nkg file, and then load and add the\n", @@ -101,21 +101,21 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-19T17:46:40.422043Z", - "start_time": "2023-11-19T17:46:39.774911Z" + "end_time": "2023-11-24T14:58:46.679846Z", + "start_time": "2023-11-24T14:58:45.624221Z" } }, "id": "681594ea282bf0f" }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/Users/administration/Github/kymata-toolbox/kymata/entities/expression.py:215: UserWarning: Experimental function. The on-disk data format for ExpressionSet is not yet fixed. Files saved using .save should not (yet) be treated as stable or future-proof.\n", + "/Users/cai/Dox/Work/Kymata lab/Code/kymata-toolbox/kymata/entities/expression.py:215: UserWarning: Experimental function. The on-disk data format for ExpressionSet is not yet fixed. Files saved using .save should not (yet) be treated as stable or future-proof.\n", " warn(\"Experimental function. \"\n" ] } @@ -131,8 +131,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2023-11-19T17:46:52.217736Z", - "start_time": "2023-11-19T17:46:45.070575Z" + "end_time": "2023-11-24T14:59:02.740098Z", + "start_time": "2023-11-24T14:58:46.681865Z" } }, "id": "77c6c3617357edbb" diff --git a/kymata/datasets/sample.py b/kymata/datasets/sample.py index 6d580fc4..adcaf87e 100644 --- a/kymata/datasets/sample.py +++ b/kymata/datasets/sample.py @@ -6,7 +6,6 @@ from kymata.entities.expression import ExpressionSet from kymata.io.file import path_type -from kymata.io.matlab import load_matab_expression_files _DATA_PATH_ENVIRONMENT_VAR_NAME = "KYMATA_DATA_ROOT" _DATA_DIR_NAME = "kymata_data" @@ -105,7 +104,8 @@ def __init__(self, data_root: Optional[path_type] = None, download: bool = True) super().__init__( name=name, filenames=[ - "TVL_2020_delta_ins_tontop_chan1_loudness_only.nkg", ], + "TVL_2020_delta_ins_tontop_chan1_loudness_only.nkg" + ], data_root=data_root, remote_root="https://kymata.org/assets_kymata_toolbox_tutorial_data/gridsearch-result-data/", download=download, diff --git a/tests/test_datasets.py b/tests/test_datasets.py index 97ea4246..82e6688e 100644 --- a/tests/test_datasets.py +++ b/tests/test_datasets.py @@ -17,8 +17,8 @@ def test_download_and_delete_q3_2023_data_files(): def test_download_and_delete_gm_loudness3_data_files(): - from kymata.datasets.sample import GMLoudnessDataset - dataset = GMLoudnessDataset(download=False) + from kymata.datasets.sample import TVLInsLoudnessOnlyDataset + dataset = TVLInsLoudnessOnlyDataset(download=False) try: dataset.download() for filename in dataset.filenames: