{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "collapsed": true, "id": "fv7OyVCrfC9v", "outputId": "20a64b13-1ed6-47e2-ca71-5868c51dd439", "tags": [ "hide-output" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: pandas in /Users/rt2549/miniconda3/envs/mast-book/lib/python3.11/site-packages (2.2.2)\n", "Requirement already satisfied: matplotlib in /Users/rt2549/miniconda3/envs/mast-book/lib/python3.11/site-packages (3.9.0)\n", "Requirement already satisfied: zarr in /Users/rt2549/miniconda3/envs/mast-book/lib/python3.11/site-packages (2.18.2)\n", "Requirement already satisfied: fsspec in /Users/rt2549/miniconda3/envs/mast-book/lib/python3.11/site-packages (2024.6.0)\n", "Requirement already satisfied: s3fs in /Users/rt2549/miniconda3/envs/mast-book/lib/python3.11/site-packages (2024.6.0)\n", "Requirement already satisfied: intake in 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partd>=1.2.0->dask>=2.2->intake_xarray) (1.0.0)\n" ] } ], "source": [ "!pip install pandas matplotlib zarr fsspec s3fs intake intake_xarray intake_parquet" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "id": "A88d8FK2fC9w" }, "outputs": [], "source": [ "import intake\n", "import matplotlib.pyplot as plt\n", "\n", "plt.rcParams[\"font.family\"] = \"sans\"\n", "plt.rcParams[\"font.size\"] = 8" ] }, { "cell_type": "markdown", "metadata": { "id": "t9cP5ZVovY7J" }, "source": [ "First let's take a look at the top level shots. In this table we can find all of the metadata we have about particular shots." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 669 }, "id": "LU6YGO6-sWfd", "outputId": "bcddcf93-7ef6-447c-acee-f223723784eb" }, "outputs": [ { "data": { "text/html": [ "
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urlpreshot_descriptionpostshot_descriptioncampaigncurrent_rangedivertor_configplasma_shapecomissionerfacilityshot_id...cpf_vol_ipmaxcpf_vol_maxcpf_vol_trubycpf_wmhd_ipmaxcpf_wmhd_maxcpf_wmhd_trubycpf_zeff_ipmaxcpf_zeff_maxcpf_zeff_trubycpf_zmag_efit
0s3://mast/level1/shots/11695.zarr\\n0.1T TF SHOT\\n\\nOK\\nM5NoneConventionalNoneNoneMAST11695...NaNNaNNaNNaNNaNNaNNoneNoneNoneNaN
1s3://mast/level1/shots/11696.zarr\\nSTANDARD 0.3T TF SHOT\\n\\nOK\\nM5NoneConventionalNoneNoneMAST11696...NaNNaNNaNNaNNaNNaNNoneNoneNoneNaN
2s3://mast/level1/shots/11697.zarr\\nRAISE TO 0.5T\\n\\nOK, ALARMS ARE LOWER\\nM5NoneConventionalNoneNoneMAST11697...NaNNaNNaNNaNNaNNaNNoneNoneNoneNaN
3s3://mast/level1/shots/11698.zarr\\nRAISE TO .56T\\n\\nSTILL ALARMS BUT LOWER AGAIN\\nM5NoneConventionalNoneNoneMAST11698...NaNNaNNaNNaNNaNNaNNoneNoneNoneNaN
4s3://mast/level1/shots/11699.zarr\\nRAISE TO .58T\\n\\nOK\\nM5NoneConventionalNoneNoneMAST11699...NaNNaNNaNNaNNaNNaNNoneNoneNoneNaN
..................................................................
15548s3://mast/level1/shots/30467.zarr\\nRepeat with new neutron camera position.\\ncH...\\nTwo times lower DD neutron rate than referen...M9700 kAConventionalConnected Double NullNoneMAST30467...9.0292029.0463940.049469.12246952653.4450.0NoneNoneNone0.013202
15549s3://mast/level1/shots/30468.zarr\\nRepeat with new neutron camera position.\\ncH...\\nGood beam.\\nGood repeat.\\nM9700 kAConventionalLower Single NullNoneMAST30468...9.1024119.1070170.048516.96267549382.1330.0NoneNoneNone0.012445
15550s3://mast/level1/shots/30469.zarr\\nRepeat with increased beam power (74 kV)\\ncH...\\nGood shot. Modes present.\\nM9700 kAConventionalConnected Double NullNoneMAST30469...8.9887309.0479230.047466.24961649115.8050.0NoneNoneNone0.015299
15551s3://mast/level1/shots/30470.zarr\\nRepeat last using hydrogen in outboard and c...\\nNo HF gas.\\nM9700 kAConventionalNoneNoneMAST30470...9.68704910.0555090.017290.43286522310.5160.0NoneNoneNone0.015164
15552s3://mast/level1/shots/30471.zarr\\nThe last plasma:\\nConvert to i/b Helios 1724...\\nGood shot.\\nM9700 kAConventionalLower Single NullNoneMAST30471...8.8175599.2837020.038063.58238040906.0900.0NoneNoneNone0.014340
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" ], "text/plain": [ " url \\\n", "0 s3://mast/level1/shots/11695.zarr \n", "1 s3://mast/level1/shots/11696.zarr \n", "2 s3://mast/level1/shots/11697.zarr \n", "3 s3://mast/level1/shots/11698.zarr \n", "4 s3://mast/level1/shots/11699.zarr \n", "... ... \n", "15548 s3://mast/level1/shots/30467.zarr \n", "15549 s3://mast/level1/shots/30468.zarr \n", "15550 s3://mast/level1/shots/30469.zarr \n", "15551 s3://mast/level1/shots/30470.zarr \n", "15552 s3://mast/level1/shots/30471.zarr \n", "\n", " preshot_description \\\n", "0 \\n0.1T TF SHOT\\n \n", "1 \\nSTANDARD 0.3T TF SHOT\\n \n", "2 \\nRAISE TO 0.5T\\n \n", "3 \\nRAISE TO .56T\\n \n", "4 \\nRAISE TO .58T\\n \n", "... ... \n", "15548 \\nRepeat with new neutron camera position.\\ncH... \n", "15549 \\nRepeat with new neutron camera position.\\ncH... \n", "15550 \\nRepeat with increased beam power (74 kV)\\ncH... \n", "15551 \\nRepeat last using hydrogen in outboard and c... \n", "15552 \\nThe last plasma:\\nConvert to i/b Helios 1724... \n", "\n", " postshot_description campaign \\\n", "0 \\nOK\\n M5 \n", "1 \\nOK\\n M5 \n", "2 \\nOK, ALARMS ARE LOWER\\n M5 \n", "3 \\nSTILL ALARMS BUT LOWER AGAIN\\n M5 \n", "4 \\nOK\\n M5 \n", "... ... ... \n", "15548 \\nTwo times lower DD neutron rate than referen... M9 \n", "15549 \\nGood beam.\\nGood repeat.\\n M9 \n", "15550 \\nGood shot. Modes present.\\n M9 \n", "15551 \\nNo HF gas.\\n M9 \n", "15552 \\nGood shot.\\n M9 \n", "\n", " current_range divertor_config plasma_shape comissioner \\\n", "0 None Conventional None None \n", "1 None Conventional None None \n", "2 None Conventional None None \n", "3 None Conventional None None \n", "4 None Conventional None None \n", "... ... ... ... ... \n", "15548 700 kA Conventional Connected Double Null None \n", "15549 700 kA Conventional Lower Single Null None \n", "15550 700 kA Conventional Connected Double Null None \n", "15551 700 kA Conventional None None \n", "15552 700 kA Conventional Lower Single Null None \n", "\n", " facility shot_id ... cpf_vol_ipmax cpf_vol_max cpf_vol_truby \\\n", "0 MAST 11695 ... NaN NaN NaN \n", "1 MAST 11696 ... NaN NaN NaN \n", "2 MAST 11697 ... NaN NaN NaN \n", "3 MAST 11698 ... NaN NaN NaN \n", "4 MAST 11699 ... NaN NaN NaN \n", "... ... ... ... ... ... ... \n", "15548 MAST 30467 ... 9.029202 9.046394 0.0 \n", "15549 MAST 30468 ... 9.102411 9.107017 0.0 \n", "15550 MAST 30469 ... 8.988730 9.047923 0.0 \n", "15551 MAST 30470 ... 9.687049 10.055509 0.0 \n", "15552 MAST 30471 ... 8.817559 9.283702 0.0 \n", "\n", " cpf_wmhd_ipmax cpf_wmhd_max cpf_wmhd_truby cpf_zeff_ipmax cpf_zeff_max \\\n", "0 NaN NaN NaN None None \n", "1 NaN NaN NaN None None \n", "2 NaN NaN NaN None None \n", "3 NaN NaN NaN None None \n", "4 NaN NaN NaN None None \n", "... ... ... ... ... ... \n", "15548 49469.122469 52653.445 0.0 None None \n", "15549 48516.962675 49382.133 0.0 None None \n", "15550 47466.249616 49115.805 0.0 None None \n", "15551 17290.432865 22310.516 0.0 None None \n", "15552 38063.582380 40906.090 0.0 None None \n", "\n", " cpf_zeff_truby cpf_zmag_efit \n", "0 None NaN \n", "1 None NaN \n", "2 None NaN \n", "3 None NaN \n", "4 None NaN \n", "... ... ... \n", "15548 None 0.013202 \n", "15549 None 0.012445 \n", "15550 None 0.015299 \n", "15551 None 0.015164 \n", "15552 None 0.014340 \n", "\n", "[15553 rows x 282 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "catalog = intake.open_catalog('https://mastapp.site/intake/catalog.yml')\n", "shots_df = catalog.index.level1.shots().read()\n", "shots_df" ] }, { "cell_type": "markdown", "metadata": { "id": "htFq_x13fC9w" }, "source": [ "# Thomson Scattering Data\n", "This notebook contains some examples of loading and plotting Thomson scattering data.\n", "\n", "First we can have a look at how many thompson scattering sources are in the database:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 424 }, "id": "28GBeNuzfC9x", "outputId": "5ee79fd8-78e6-4bd7-dfdf-a594b232b5e0" }, "outputs": [ { "data": { "text/html": [ "
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descriptionqualityuuidshot_idnameurl
36519Core Thomson scattering dataNot Checkeda61fdefa-e7e9-57df-a7f3-a341f737bcdd23001aycs3://mast/level1/shots/23001.zarr/ayc
36574Core Thomson scattering dataNot Checkeda654a084-97f5-52f5-99d6-4e726880b39a23018aycs3://mast/level1/shots/23018.zarr/ayc
36732Core Thomson scattering dataNot Checked3cca7bc2-9c91-5bd9-a1cd-939142a84cd223133aycs3://mast/level1/shots/23133.zarr/ayc
36742Core Thomson scattering dataNot Checked6fd9ab2f-ca5f-57a2-ba81-589cf6efe7d523135aycs3://mast/level1/shots/23135.zarr/ayc
36747Core Thomson scattering dataNot Checked5334374c-8f9a-5437-aa56-822448ea5d2723136aycs3://mast/level1/shots/23136.zarr/ayc
.....................
99004Core Thomson scattering dataNot Checked1d345219-99c7-5725-9d65-2c9d455b629c30467aycs3://mast/level1/shots/30467.zarr/ayc
99019Core Thomson scattering dataNot Checked9ac2f540-8845-5c5a-8932-7634b7834d4030468aycs3://mast/level1/shots/30468.zarr/ayc
99034Core Thomson scattering dataNot Checkedd07dc339-1510-525c-9fa9-01590010165630469aycs3://mast/level1/shots/30469.zarr/ayc
99049Core Thomson scattering dataNot Checkedfa9b2d5d-348b-5e00-a4d5-fc5e39d7545230470aycs3://mast/level1/shots/30470.zarr/ayc
99064Core Thomson scattering dataNot Checked113ec983-6e14-5e41-8111-aadb0f74447130471aycs3://mast/level1/shots/30471.zarr/ayc
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4665 rows × 6 columns

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" ], "text/plain": [ " description quality \\\n", "36519 Core Thomson scattering data Not Checked \n", "36574 Core Thomson scattering data Not Checked \n", "36732 Core Thomson scattering data Not Checked \n", "36742 Core Thomson scattering data Not Checked \n", "36747 Core Thomson scattering data Not Checked \n", "... ... ... \n", "99004 Core Thomson scattering data Not Checked \n", "99019 Core Thomson scattering data Not Checked \n", "99034 Core Thomson scattering data Not Checked \n", "99049 Core Thomson scattering data Not Checked \n", "99064 Core Thomson scattering data Not Checked \n", "\n", " uuid shot_id name \\\n", "36519 a61fdefa-e7e9-57df-a7f3-a341f737bcdd 23001 ayc \n", "36574 a654a084-97f5-52f5-99d6-4e726880b39a 23018 ayc \n", "36732 3cca7bc2-9c91-5bd9-a1cd-939142a84cd2 23133 ayc \n", "36742 6fd9ab2f-ca5f-57a2-ba81-589cf6efe7d5 23135 ayc \n", "36747 5334374c-8f9a-5437-aa56-822448ea5d27 23136 ayc \n", "... ... ... ... \n", "99004 1d345219-99c7-5725-9d65-2c9d455b629c 30467 ayc \n", "99019 9ac2f540-8845-5c5a-8932-7634b7834d40 30468 ayc \n", "99034 d07dc339-1510-525c-9fa9-015900101656 30469 ayc \n", "99049 fa9b2d5d-348b-5e00-a4d5-fc5e39d75452 30470 ayc \n", "99064 113ec983-6e14-5e41-8111-aadb0f744471 30471 ayc \n", "\n", " url \n", "36519 s3://mast/level1/shots/23001.zarr/ayc \n", "36574 s3://mast/level1/shots/23018.zarr/ayc \n", "36732 s3://mast/level1/shots/23133.zarr/ayc \n", "36742 s3://mast/level1/shots/23135.zarr/ayc \n", "36747 s3://mast/level1/shots/23136.zarr/ayc \n", "... ... \n", "99004 s3://mast/level1/shots/30467.zarr/ayc \n", "99019 s3://mast/level1/shots/30468.zarr/ayc \n", "99034 s3://mast/level1/shots/30469.zarr/ayc \n", "99049 s3://mast/level1/shots/30470.zarr/ayc \n", "99064 s3://mast/level1/shots/30471.zarr/ayc \n", "\n", "[4665 rows x 6 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "catalog = intake.open_catalog('https://mastapp.site/intake/catalog.yml')\n", "sources_df = catalog.index.level1.sources().read()\n", "\n", "# Can also use name == 'aye' for thompson scattering edge data.\n", "sources_df = sources_df.loc[(sources_df.name == 'ayc')]\n", "sources_df" ] }, { "cell_type": "markdown", "metadata": { "id": "olNRh3zSfC9x" }, "source": [ "Let's look at the data for a particular shot. Here we are going to use shot 30420 as an example. Below we get the url for the `ayc` data." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 35 }, "id": "gAywePaZfn52", "outputId": "73f1537a-e736-4e34-eebf-49f0fcd623e5" }, "outputs": [ { "data": { "text/plain": [ "'s3://mast/level1/shots/30420.zarr/ayc'" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "shot_id = 30420\n", "url = sources_df.loc[sources_df.shot_id == shot_id].iloc[0].url\n", "url" ] }, { "cell_type": "markdown", "metadata": { "id": "ZducVCAtfC9x" }, "source": [ "### Thomson Scattering Data\n", "\n", "`ayc` source holds the Thomson Scattering data at the core. Thomson scattering diagnostics provide accurate measurements of electron temperature and density." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 270 }, "id": "A2zALb-3fC9y", "outputId": "4421dea3-deb6-4654-9ab4-972c61400a9c" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/rt2549/miniconda3/envs/mast-book/lib/python3.11/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n", " 'dims': dict(self._ds.dims),\n" ] }, { "data": { "text/html": [ "
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<xarray.Dataset> Size: 1MB\n",
              "Dimensions:              (acqiris_time: 73, radial_index: 130, arb: 130,\n",
              "                          time: 73, spectral_index: 4, instrument_time: 20,\n",
              "                          xyc_time: 73)\n",
              "Coordinates:\n",
              "  * acqiris_time         (acqiris_time) float32 292B 0.0 1.0 2.0 ... 71.0 72.0\n",
              "  * arb                  (arb) float32 520B 0.0 1.0 2.0 ... 127.0 128.0 129.0\n",
              "  * instrument_time      (instrument_time) float32 80B 1.0 2.0 3.0 ... 19.0 20.0\n",
              "  * radial_index         (radial_index) float32 520B 0.0 1.0 2.0 ... 128.0 129.0\n",
              "  * spectral_index       (spectral_index) float32 16B 1.0 2.0 3.0 4.0\n",
              "  * time                 (time) float32 292B 0.004166 0.008332 ... 0.3 0.3042\n",
              "  * xyc_time             (xyc_time) float32 292B 0.0 1.0 2.0 ... 70.0 71.0 72.0\n",
              "Data variables: (12/36)\n",
              "    acqiris_time_        (acqiris_time) float32 292B dask.array<chunksize=(73,), meta=np.ndarray>\n",
              "    angle                (radial_index) float32 520B dask.array<chunksize=(130,), meta=np.ndarray>\n",
              "    aspectra             (time, radial_index, spectral_index) float32 152kB dask.array<chunksize=(73, 130, 4), meta=np.ndarray>\n",
              "    chi2                 (time, radial_index) float32 38kB dask.array<chunksize=(73, 130), meta=np.ndarray>\n",
              "    covariance_ne_te     (time, radial_index) float32 38kB dask.array<chunksize=(73, 130), meta=np.ndarray>\n",
              "    instrument_dr        (instrument_time, radial_index) float32 10kB dask.array<chunksize=(20, 130), meta=np.ndarray>\n",
              "    ...                   ...\n",
              "    te_error             (time, radial_index) float32 38kB dask.array<chunksize=(73, 130), meta=np.ndarray>\n",
              "    version_fibre        float32 4B ...\n",
              "    version_poly         float32 4B ...\n",
              "    version_raman        float32 4B ...\n",
              "    xyc_time_            (xyc_time) float32 292B dask.array<chunksize=(73,), meta=np.ndarray>\n",
              "    yag_nelint           (time) float32 292B dask.array<chunksize=(73,), meta=np.ndarray>\n",
              "Attributes:\n",
              "    description:  Core Thomson scattering data\n",
              "    file_name:    ayc0304.20\n",
              "    format:       IDA3\n",
              "    mds_name:     None\n",
              "    name:         ayc\n",
              "    quality:      Not Checked\n",
              "    shot_id:      30420\n",
              "    signal_type:  Analysed\n",
              "    source:       ayc\n",
              "    uda_name:     AYC\n",
              "    uuid:         8d043ece-8bf8-5af8-87e4-d2a1b01716fa\n",
              "    version:      0
" ], "text/plain": [ " Size: 1MB\n", "Dimensions: (acqiris_time: 73, radial_index: 130, arb: 130,\n", " time: 73, spectral_index: 4, instrument_time: 20,\n", " xyc_time: 73)\n", "Coordinates:\n", " * acqiris_time (acqiris_time) float32 292B 0.0 1.0 2.0 ... 71.0 72.0\n", " * arb (arb) float32 520B 0.0 1.0 2.0 ... 127.0 128.0 129.0\n", " * instrument_time (instrument_time) float32 80B 1.0 2.0 3.0 ... 19.0 20.0\n", " * radial_index (radial_index) float32 520B 0.0 1.0 2.0 ... 128.0 129.0\n", " * spectral_index (spectral_index) float32 16B 1.0 2.0 3.0 4.0\n", " * time (time) float32 292B 0.004166 0.008332 ... 0.3 0.3042\n", " * xyc_time (xyc_time) float32 292B 0.0 1.0 2.0 ... 70.0 71.0 72.0\n", "Data variables: (12/36)\n", " acqiris_time_ (acqiris_time) float32 292B dask.array\n", " angle (radial_index) float32 520B dask.array\n", " aspectra (time, radial_index, spectral_index) float32 152kB dask.array\n", " chi2 (time, radial_index) float32 38kB dask.array\n", " covariance_ne_te (time, radial_index) float32 38kB dask.array\n", " instrument_dr (instrument_time, radial_index) float32 10kB dask.array\n", " ... ...\n", " te_error (time, radial_index) float32 38kB dask.array\n", " version_fibre float32 4B ...\n", " version_poly float32 4B ...\n", " version_raman float32 4B ...\n", " xyc_time_ (xyc_time) float32 292B dask.array\n", " yag_nelint (time) float32 292B dask.array\n", "Attributes:\n", " description: Core Thomson scattering data\n", " file_name: ayc0304.20\n", " format: IDA3\n", " mds_name: None\n", " name: ayc\n", " quality: Not Checked\n", " shot_id: 30420\n", " signal_type: Analysed\n", " source: ayc\n", " uda_name: AYC\n", " uuid: 8d043ece-8bf8-5af8-87e4-d2a1b01716fa\n", " version: 0" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dataset = catalog.level1.sources(url=url)\n", "dataset = dataset.to_dask()\n", "\n", "dataset" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 493 }, "id": "HbYAmcmAfC9y", "outputId": "ea7f9449-96da-411b-c805-63c7bdeaf989" }, "outputs": [ { "data": { "image/png": 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QQggXs3nwV6PR8Mwzz6BWqxk4cCCDBg2SZM8OvjKkK4QQQoh2Ytcsw5EjR7J9+3ZntaVT87YmfNLDJ4QQQgjXsmsO365du1izZg29e/fGz8/P+vjevXsd3rDOxkcSPiGEEEK0E7sSvjfeeMNZ7ej0fKxz+GRIVwghhBCuZVfCN3nyZGe1o9OTHj4hhBBCtBe7Er6pU6daa/D93k8//eSwBnVWUpZFCCGEEO3FroTvgQcesP5fr9fz0Ucf0a9fP4c3qjOqK8tSIUO6QgghhHAxuxK+yy67rN7ns2bN4sILL3RogzorXxnSFUIIIUQ7adPmbyaTibNnzzqqLZ2aDOkKIYQQor3Y1cN31VVXWefwmUwmDh48yCWXXOKUhnU2stOGEEIIIdqLXQnf7Nmzzz1Rq+Vvf/sbY8eOdXSbOiXZaUMIIYQQ7cWuhC88PJyZM2fWe2zjxo0NHhMNyU4bQgghhGgvds3h+9vf/mbTY6KhusLLModPCCGEEK5mU8J34sQJvvrqK0pKSvjqq6+sHx988AGVlZUOacg333zDyJEjGT58OEOGDOG9994DIDc3l5kzZxIfH8+QIUPYunWr9TnNHXM3dYs2KqprUBSlnVsjhBBCiK7EpiHdnTt3smbNGnJzc3n55ZetjwcEBPDiiy+2uRGKojBnzhy2bNnCsGHDSE1NZcCAAVx99dUsXbqUcePGsXHjRhITE7nqqqtISUnBw8Oj2WPupi7hMytgqDHj5aFp5xYJIYQQoquwKeGbN28e8+bN45133uG2225zSkNUKhXFxcUAlJaWEhISgk6nY926dSQnJwMwevRooqKi+Pnnn7n44oubPeZu6oZ0wTKsKwmfEEIIIVzFrkUbt912G0ajkZSUFPR6vfXxYcOGtakRKpWK//73v1x99dX4+vpSVFTE+vXrKSsrw2g0EhERYT23Z8+epKWlUVBQ0OSxxhgMBgwGg/Xz0tJSAMxmM2azuU3tN5vNKIrS7HVUgKdWTXWNmXK9kUBvu0Lf5dgSU2EfialzSFwdT2LqeBJTx3OHmNpzb7uyjg0bNnD77bdTVFRkTczi4uJISUmxu5G/V1NTw9NPP8369euZNGkSiYmJXHnllezfv79N1/29FStWsHz58gaP5+Xl1UteW8NsNlNSUoKiKKjVTU+L9NaqqK6BjOxcPIzebbpnZ2drTIXtJKbOIXF1PImp40lMHc8dYlpWVmbzuXYlfI899hi7du1i9uzZ7Nu3j7Vr13LgwAG7G/hH+/fv5+zZs0yaNAmwDM9GR0dz8OBBtFot2dnZ1p681NRUYmNjCQkJafJYY5YtW8aSJUusn5eWlhITE0NoaCgBAQFtar/ZbEalUhEaGtrsF93Xy4MSvQkv/0DCwoLadM/OztaYCttJTJ1D4up4ElPHk5g6njvE1MvLy+Zz7Ur41Go1cXFx1NRYigfPmTOn3iKO1oqJiSErK4tjx44xcOBAkpOTOXXqFP379+e6665j5cqVPPHEEyQmJpKZmcnkyZMBmj32RzqdDp1O1+hrcsQXSqVStXitunl8eqP8hWULW2Iq7CMxdQ6Jq+NJTB1PYup47R1Te+5rV8JXt/o1Ojqazz//nJ49e1JUVGRf6xoRHh7Ov//9b66//nrUajVms5nXX3+d2NhYnnvuOebOnUt8fDyenp6sXbvW2o7mjrkj2W1DCCGEEO3BroTv3nvvpaioiKeffpobbriB4uJiXn31VYc05MYbb+TGG29s8Hh4eDjff/99o89p7pg7kt02hBBCCNEebE74TCYTnp6edOvWjVGjRnHy5ElntqtTkt02hBBCCNEebB781Wg0PPPMM85sS6fn/bvdNoQQQgghXMWuId2RI0eyfft2LrjgAme1p1PzlSFdIUQnozeayC83UFBeTX65ofajmrwyA6VVRob0CGTmkAiigqQUlRDtya6Eb9euXaxZs4bevXvj5+dnfXzv3r0Ob1hnJEO6QojOoLrGzI/Hclj3azpbT+ZjMje9P/j6fZk8ueEoCdGBzBwSySVDIujZ3bfV9y6urCan1ECN2YzZDDVmMyazQo1ZwWRW6BfuT6h/w4oMQnR1diV8b7zxhrPa0SXIkK4QoiNLyi5j3a/pfL4vk8KKauvjHhoV3f10tR+eln/9dXh7aNh+Mp/EM4UcyCjhQEYJz208zoAIf2YOiWBq/zAGRwWg1TQ/u6iyuobvj+Tw+b5Mtic3n2B6eahZe9tYzusZ7LDXLURnYFfCN3nyZIxGI2lpafTp08dZbeq06oZ0pYdPCNFRFJQb2Hgkm3WJ6RzIKLE+Huav49pR0VwzKpre3X1RqVSNPv+ei+LJLdPz/ZEcvjuSzY5TBRzPLuN4dhmvbDqJr6eGUT2DGdsrmHG9gxnaIwitGmrMCj+fyOPL/Wf5/mhOvakwwb6eaNUqtGoVGo0KrVqNWmWZLpNVoue2937ls8Xn0zfM3+nxEaKjsCvh27JlCzfddBNarZa0tDQSExN59dVXWbt2rbPa16l41w7pyhw+IYS7UhSFpJwyfjyWy4/HctiXXoxS26GmVau4eGA414+OZlJ8aIs9c3XC/L2YMy6OOePiKK6s5oejOXx/NIc9KYWUVBnZeiKPrSfyAEsPXUJ0ECdySimqPDcaEhfiw+zhPZg9oge9mhgSrqo2cdPbu9iXVsy8dxP5/M7xhAXYvhOBEJ2ZXQnf0qVL2bZtG9deey1g2QJt3759TmlYZ+QjizaEEG7GUGOioLyapJwyfjqWy0/Hc8ksrqp3zuCoAK4aYUm2uvu1bX5ckI8n150Xw3XnxWA2KxzPLmN3SgG7TxeyJ7WQwopqdqcUAhDs48EVCVHMGtGDETFBTfYi1vH21PDOvNFc868dpORXMH91Iv9dNA5/L/ctyC+Eq9iV8JlMpgZDuZ6eng5tUGfmIzttCCHaQWFFNVuScjmcWUpeuYG8Mr11JW1JlbHB+Tqtmgv6dueigeFMHRBKZKBzVtiq1SoGRQUwKCqAWyf0QlEUknPL+fVMITqTnsvO64POw65fUwT7evLerWO4+l87OJpVyuK1e3l3/mg8tbKdmOja7PpO8vLyory83PpX1qFDh/D2lqX2tvKRIV0hhAsoiqXn7KfjDYdlG+OhUREZ6M3E+O5cNDCM83t3ty4ycyWVSkV8uD99Qn3Jzc3Fw8Yh4z+KDfFh9fzR/OnfO9menM9Dnx7gpeuHo1Y330MoRGdmV8L32GOPMX36dDIyMpgzZw6bNm3io48+clbbOh0fWbQhhHCSyuoadp4q4KfjuWw+nsvZEn294wMjAxjfJ4TIQC9C/XWWDz/Lv4HeHi0Ol3Y0Q6MDefPmkSx871e+2H+WiEBvll4yoL2bJUS7sSvhmz59OvHx8WzcuBFFUVi+fLms1rWDlGURQjhSan4Fm5Ny2ZyUx67TBVTXmK3HvDzUTOjTnQsHhjG1f1iXLHw8pX8Y/7hmGA98coCVP59Co4YeQT4UlBsoqKimsPYjv9xAqL+Op2cPIS6k9TUChXBn9k2OAMLCwhg6dCgqlYqIiAhntKnT8pXCy0KIVqow1HCmoJK0wgp2pxSyJSmPlPyKeuf0CPJm6oBQLhoQzvl9QvDycP2wrLu5dlQ02SVVvPD9Cd7YfKrJ845nlzF/dSKfLR5PsK/MTRedj10J348//shNN91Ejx49UBSFrKwsPv74Y6ZOneqs9nUqskpXCFFdY6ZMb6TcUENltQm90USV0YTBaLb+X280k12qJ62ggrTCStIKK8kvr25wLa1axeiewUwdEMrU/mH0DfPrdEOzjnDX1L54aNT8cDSHIB8Pgn09CfHTEeLrSbCvJwFeHjz+1RFS8itY+F4iH90+TpJl0enYlfDdd999fPXVV4wdOxaAPXv2cNttt3Ho0CGnNK6zqRvSrTKaMJsVmUAsRCelKJaiwR/uTiOnVE+ZvoYyvZEyfQ2G3w272qubjwexIb4MCPdn6oBQJvTtLiVHbKBSqVg0uQ+LJjc9Balndx+u+ddO9qYVc+9/9vHmzaPQyM9o0YnYlfCp1WprsgcwZswYNBrH/BVkMBi4//77+e677/Dy8iIhIYG1a9dy8uRJ5s2bR35+PoGBgaxZs4bBgwcDNHvMHdUN6YIl6fPV2T2iLoRwY4qisOlYLq//dLLerhSN8fHU4OOpwcuj7kONl1aDt6cGnVZDqL8nscG+xIX4EBvsQ2yIDwGS3DlN3zB/3rrlPOa8vZvvjuTw1IajPH7FIOkxFZ2G3Ys21qxZw7x58wD44IMPmD59ukMasnTpUlQqFSdOnEClUpGdnQ3AokWLuOOOO5g/fz6ffvop8+fPJzExscVj7sjLQ41KBYpiGdaVhE+IzsGsKHx7OJs3Np/iaFYpYPl+v3lsHOP7hODv5YGfTou/l5YALw98dRqbd6kQrjOmVzAv/SmBuz/ax5odqfQI8ub2Sb3bu1lCOIRKUZqrzlRft27dKCkpwcPD8lem0WgkMDDQciGVisLCwlY1oqKigsjISDIyMggICLA+npubS9++fSksLESr1aIoCpGRkWzfvp2AgIAmj/Xt27fFe5aWlhIYGEhJSUm9e7aG2WwmNzeXsLAw1Ormf4gP+vtGKqtN/PzgFFkN1gx7YipsIzFtSFEU8surSS2oIKOokoLycys3CyqqKar9f6m+hiAfD7r7eRLq71X7r47ufjpMJjNvbU3mdIGlDIqvp4a55/dk4cRebd6Voqtq7/fq29tO8/TXxwB47cYRXJEQ5fI2OFp7x7QzcoeY2pPL2NXFtH///ra0q0mnTp0iODiYZ599lk2bNuHt7c0TTzxBUFAQkZGRaLWWZqpUKmJjY0lLSyMwMLDJY40lfAaDAYPBYP28tNTyV7jZbMZsbv2cmrprKIpi03W8PTRUVpso1xvbfN/OzJ6YCtt09ZjmlRn4+UQeqQWVpOZXcKawkjMFFZQbbFtElV9uIDm36eN+Oi3zx8dx64SedPOxrPLsqrFuq/Z+r946Po6MwkrW7DzD/ev2E+rnyZhewVRVm8gp05NToienzEBuqYEqo4lbzo8j0Nu9h9vbO6adkTvE1J5725XwxcXF2d0YW9TU1HDmzBkGDRrEP/7xD/bt28e0adP4+uuvHXaPFStWsHz58gaP5+XlodfrG3mG7cxmMyUlJSiK0mKW71Ub8bM5+YRo2nbfzsyemArbdNWYFlUa+eDXHD47kIvB1HBAQwVEBHjSI1BHsI+WIG8Pgry11o9u3lp8PTWUGmoorKihoNJIYaWRgooaCiuNlBtMjIjwZM7YaAK9PTGWF5Nb7vrX2Zm4w3v19tEhpOaVsCW5mHnv7sFDo6a8iQoLRzMKWD6zl4tbaB93iGln4w4xLSsrs/lcuxK+rVu38sADD5CcnExNTQ2KoqBSqay9Za0VGxuLWq3m5ptvBmDEiBH06tWLM2fOkJWVRU1NjXXYNi0tjdjYWAICApo81phly5axZMkS6+elpaXExMQQGhrqkCFdlUpFaGhoi190P28dlFSj8wsgLKx7m+7bmdkTU2GbrhbTkiojb29LYfWOVGsppCFRASTEBBEX4kOvEB/iQnyJCfZGp2394jOz2UxeXl6XiasruMt79c253Zn7zh5+SyvGYLK8h7w9NIQH6AgP8CLE15NvDmfz3fFC7r54AIOjAtutrS1xl5h2Ju4QUy8vL5vPtSvhu/3223nmmWccujoXoHv37lx00UV89913XHrppaSkpJCSksKECRMYOXIka9euZf78+Xz22WdER0dbh2ybO/ZHOp0Ona7hfBq1Wu2QL5RKpbLpWtbt1Yxm+aZrga0xFbZzl5hWVZs4mVtGTqmBkiojpVVGSmo/6v5fWW3CUGOi2mSmusaMoebcvz6eGvqH+9M/wvIxMDKAXt198dCoKdMbWf1LKm9tO02Z3rKrzdAegSyZ3o8p/UKdsurSXeLambhDTH10atYuHMfBjGJC/DwJC/DCX6et9x665+N9fHXgLM9/d4IPbhvbzNXanzvEtLNp75jac1+7Er6AgACuvfZauxtki5UrV3Lbbbfx8MMPo1arWbVqFT169GDVqlXMnz+fZ599loCAAFavXm19TnPH3JXstiG6EpNZ4UxBBcezyzieXUZSdilJ2WWcKazE9uViDRVWQEZRFT8ePzepzkOjok+oHzmleooqjQAMiPDnr9P6MX1QuJTXEK3i7alhbO+QJo8/OKM/3x7OYtvJfLaeyGNSv9A23a+g3MCaHamc3yeE8X1kFEg4jl0J3zXXXMMHH3zAn/70Jzw9Hbv1TO/evdm8eXODx/v378/OnTsbfU5zx9yVt+y2IToJQ42JD3aeYfUvqZRUGTErCiazgqJYypSYFKXZpK67n44e3bwJ8NIS6O1R7yPA2wOf2np0Og81Oo0anYcaT40GT62a4spqknLqkkjLR7mhhuPZlvksvUN9+evF/bhsaKQUOBdOFRPsw9xxPXn3lxT+8e1xLujbvdXvuZ+O5/DQp4fILzew+pdUfnpgMmH+tg/ZCdEcuxK+gQMHMmfOHObPnw9gncNnMknyYqtz26vVtHNLhGgds1nhfwfP8s/vksgoqmrxfC8PNf3C/RkQ4U//iIDaf/3bXLLk970uiqKQWVxFUnYZKhVMig+VOnfCZe6+sC+f/JrO0axSvjyQyVUjou16fmV1Dc98fYwPd6cBoFJBuaGGf25M4p/XJTijyaILsivh++tf/8qXX37Jeeed59A5fF2J7KcrOrIdyfk8++0xDmdaFmqFB+hYMq0fY3uFoFapUKtBrVKhUatQqUCjUhHk4+n0LapUKhXR3XyI7ubj1PsI0ZhgX0/+PKUP//wuiRe+O8ElQyJt3ot3f3oxf/3vflLyKwBYMKEX0waFc+Nbu/jktwzmjIsjISbIia0XXYVdCV9YWBgXXnihs9rSJfjUzuGThE90FIqikJRTxj++Pc6WpDzAUnNu8ZQ+LJjQyzpNQYiubMGEXnyw8wyZxVWs3XWGhROb36GjxmTm9c3JvPZTMiazQkSAFy9en8CEvpZ5e1eP6MH6fZk88b8jfPbn8TI1wUnqfr6pVSr6hfu3d3Ocyq6E78orr+T111/n+uuvr7cUuK1lTboSGdIV7qLcUMOZggrSCio5U1hJZlEVxX9YLVu3YrbGbJmMp1WruHlsLH+5KF52kRDid7w9NSyZ1o+HPjvIaz8lc92oGAJ9Gi/GfCyrlGXrD7E/vRiAKxKieHrWkHrnP3zJADYeyWZfWjGf78vkmlH2DROL5qXkV/DV/rN8dSCTU3mW3tUrE6J47PJBhPp3zp9tdiV8jz76KAD33HMPKpVK5vC1gizaEK5kMiukF1ZyIseyQvZIegE5FadIK6ykoKLa5uuoVDBzcAQPzRxAr+6yJaAQjblmVDRvbz/NiZxy3vw5mWWXDKx3vKTSyEs/JPHBrjOYFfD30vL07CHMGt6jwbXCA7y4+8K+PL8xiX9sPM6MIRH4NbP/enFlNX/7/BBqlYq/XzHI5sUepXojT284ysncch69bCCj4oLte9FupLK6huJKI14eGrw9NOi06no9o2eLq9hw8CxfHThrnZYC4KlVU2My89WBs/x8Io9HLh3IdedFd7qV/XYlfLIlS9tJWRbhaOWGGvLKDOSW6sktM5BRVMXJnDJO5JZxMqccQ03T37fBvp7EBvsQF+JDTDcfuvl6WlbJ1q2c9fEgwMuDIB8P63QEIUTjNGoVD88cwG3v/crqX1KZd35PooK8MZsV1v2azvPfJVFY+4fWpUMjePSyQUQFeTd5vdsu6MV/E9M5U1DJ6z8ls/SSAY2el1VSxS3v7OFk7RYvO08V8MJ1CUwdENZse/elFXHPf/aRXmhZfHXdyp3cMakPf50W36Zi5G1RUmXkra2nGdIjkBmDbSunZDIrvLcjlRe+T2rQmaLTqvHy0ODloSan9Nz2qhq1igl9u3NlQhTTB4dzJr+SpesPcuRsKQ99dpD1+zJ49qqh9A71c/hrbC92/wT/7bffOHr0KHPnzqW4uJiqqioiIyOd0bZOyVuGdEUrKYrC/vRi/ncgi8OZJeSWWRK8lnqLdVo1fcP8iA/zI9IHBseF0bO7H7EhPgR4uff+n0J0NBcOCGNsr2B2pxTy0g8nuHlsLI9/dYSDGSUAxIf58cSVg61z9Zqj02p47LJBLHz/V97dnsINo2Po+Yce9uTcMm55Zw9nS/SEB+jo5uPJ8ewybl2TyIIJvXj4kv4NkjezWWHl1lO89P0JaswK0d28GR4TxIaDWaz8+RSbj+fy0p8SWtw55GxxFcm55YyM69Zs76OtCsoNzH1nD0ezLL1vo3t249HLBjW7aOXI2RKWrT9kja9WrbJOQQEw1BZrL6ktKDCmZzBXJERy6dBIQn43LWVodCBf3jWB1b+k8tIPJ9h1upCZr27jL1P7smhyHzy1HX/Vv0pRbC9/+uabb7Jq1SrKy8s5deoUp06dYuHChY3Wz3N3paWlBAYGUlJS4pCt1XJzcwkLC2ux6vWGg2e5+6N9jOkVzLpF57fpvp2ZPTHt7JKyy/jqQCb/O5BFWmFlo+f4emoI9dcR5u9FRKAX/cL9iA/3p1+4P7HBPmjUKompk0hcHa+jx3R/ejGz3/gFlQprLUp/nZb7pvXjlvPj8LCjZJCiKMxbncjWE3lcPDCMt+eNth777UwhC9b8SkmVkd6hvry/YAzd/XT849vjrNmRCsDAyABeu3E4vbv7kpubC14BPPDpIbYn5wNw+bBInr16KAFeHnx3JJu/rT9EQUU1WrWK+y6O58+T+9QrcZSaX8G3h7PZeCSbA7VzEHVaNRcPCmdWQhST+4e2qncwu0TPnHd2k5xbTjcfD6qMJvRGy+jE7OFRPDhzAD1+1xtaVW3ilR9P8Pa2FExmBX8vLcsuGcgNo2NQAL3RhN5oqr2OiapqM2G1W+K1JL2wkke+OMzWE5ZFaqH+OoJrqw3UfWjVKtQqCPCE568fSbBf+9RLtCeXsSvhGz58ODt37mT8+PHs27cPgCFDhnD48OG2tbgdtFfCt/l4LreuSWRoj0D+95cL2nTfzqyj/8Bvq5T8Cr4+eJb/HcgiKefc5tjeHhouHhTORQPCiAz0IizAizB/Hb42/HXd1WPqLBJXx+sMMb3rw718fSgLgGtHRfPwzAGtXgyQnFvOzFe2UmNWeG/BGCb3C2XT0Rzu/ngveqOZ4TFBvDt/NMG+5zZE+PFYDg9+epDCimq8PNT8/fJBeJn1PP3DGQorjXh7aFh+5eAGc9Xyyw088vkhvjuSA0BCTBAPTO/H3jPFfHs4y1rcHCxze8P8dfWGSgO8tFw6NJIrE6IY2zvEppJM6YWV3Pz2btIKK4kM9OLDhWPx9tTwz++SWL83E7AklQsn9mLxlL7sPVPEI18csg5FXzY0ksevGESYDcmcrRRF4asDZ3nyf0dbnO/8zOzB3Dyup8PubQ97chm7+mB1Oh3e3vXnG2i1Mq/HHjKkKxqjN5rYdbqALUl5bEnKJbXgXE+ep0bN5P6hXJEQxcUDw2QunRAdwNOzh9A3zI/J/UMZGdutTdfqG+bHvPE9eWd7Csv/d4SFF/TmsS8PYzIrTO0fyhs3j2zwc+GigeFsvHciS9YdYHtyPn/7/FzHjKXXbwR9wxrOT+vup2PlnFF8sT+Tv395hAPpxcx9Z4/1uEat4vzeIcwcEsH0weGE+uk4craUL/dn8tWBs+SUGvhPYjr/SUwnPEDH9efFcPPYOCICG0/GTuWVM+ft3WSV6IkN9uHDhWOJCbbU03zp+uHcOr4XT399lN0phbyx+RTv7zhDmcHy+zMy0IunZg3h4kHhbYpvY1QqFbOG9+CigeEcySzBZFaoMSv1/v3k13R+PJ7LmYLGR17cjU2/OSoqKvD19SU0NJQTJ05Y/xpYs2YNsbGxTm1gZyOFl7seRVEs80iMZgw1lmEKQ41lqOFAejGbk/LYcSrfOnwBln1hx/UO4YqEKGYMjiDQW+baCdGRdPP15K/T+jnsevdcFM8X+zI5nVfB3z4/BFh6DldcPbTJIeKwAC/eXzCGf287zQvfJVFjVpg/Po6llwxstjC0SqXiqhHRjOsdwiOfHyYxpZDRvYKZOSSCaQPD6eZbf2vVIT0CGdIjkKWXDGRPSiFfHcjk64NZ5JQaeO2nZN7ccoqZgyO45fw4xvQKtuYQx7JKmfvObvLLq+kb5seHC8c2GHIdGh3If+4Yxw9Hc1jx7XFS8itQqWDe+T15YEZ/h8wdbI6fTtvkXspniystCV8TU23cjU2RmjhxInv37uXll1/mpptu4vjx48TExBAQEMCGDRuc3cZORRK+zi+vzMC2k3lsScrjl+R8m8ufRAZ6MaV/KFP6hzGhb3en/yATQnQcgd4ePDijP0vXW5K9O6f04cEZ/VtcxapWq/jz5D5cPDCM9KxcJg/tZfMweWSgN+/OH93yibU0ahXn9wnh/D4hPHHlYH44msP7O8+wJ6WQrw9l8fWhLAZE+HPL+T3pHerLog9+o6TKyKDIAD64bUy9RRS/p1KpmD44gin9w/j2cBZ9Qv0Y0qP5BSWuEFvbE9nU3Gp3Y9NvlLppfvHx8ezevZukpCQURaF///6yxZqdfKQsi0vVmMzklhnIKqnibLGeCkMNY3oFO3SpvdFkZl9aMT+fyOXnE3n16jv9kVoFXrX1oXRaDbEhPkztH8bUAaH0D/fvdHWfhBCOc/15MVRUm4gI8OKyYfZVx+jd3Rc/s+tqaOq0Gi4fFsXlw6I4llXK+zvP8MW+TI5nl1l7KAFGxAax5tYxNo1ieGrVjdYsbC9xdQlfQaW1LrE7synh0+v1HDp0iD+u7zhy5AgAw4YNc3zLOqm6Hr5qkxmjyWzXaq2uTlEUfjtTxLpf0zlythStRo1Oo8ZDq8JTo8ZTq8ZTq8FsVsgqqSKrxFK2xGRuuC6pT6gv0wZFMG1QOCNighrdtkhRFHLLDCRll5GcW05BhYGiSiPFldUUVRgpqqy2fFQYqTbVr3U3pEcAk/uFMik+lL5hfuhqkzytWuX2PxSEEO5JrVZx2wW92rsZdhsYGcCKq4eydOYAPvktnQ92neFMQSXn9w7h7Xnn2bTozB1FB3ujAiqqTRRUVLv97kM2Rfn06dPMmjWrQcIHlq7W06dPO6xBq1evZsGCBXz++efMnj2b3NxcbrnlFk6dOoVOp+PNN99k0qRJAM0ec1e/33e0stpEoLckfC3JLzfw+d5M/pOYZt0Cxx5atYrwAC8iA73QqFX8dqaIU3kVnPr5FCt/PkV3Px0XDwxjYnwoBRWWBO9EThkncsopqTLadI9gX08mxndncr9QJsaHdtqteYQQorUCfTxYOLE3Cyb04mRuOX1CfeuVfOlodFoNYf4e5JQZOVNQ2TkSvkGDBlnLsDhTamoqb731FuPGjbM+tnTpUsaNG8fGjRtJTEzkqquuIiUlBQ8Pj2aPuStPjdpaGLKq2iST8ZtQYzKzM7WE737IYNOxXGshTW8PDZcPi2T64AhUWHpKq2ssHwaTGWPtrhIRgZYELyrIm+5+unqlAUr1RrYk5fHD0Ry2HM8lv/zcqrI/0qhVxIX40C/Mn/AAHUE+ngT7ehLk40E3H0+6+Vj+3yPIWzY3F0IIG6jVKvpH+Ld3MxwiKkBHTpmR9MJKRsW1bTW2s9mU8LliCMpsNrNw4UJee+017r//fuvj69atIzk5GYDRo0cTFRXFzz//zMUXX9zsMXelUqnw9tRQpq/p0qVZzGaFg5klnMgpI7dUT06pgexSPbmlerJL9eSVGfj9SGxCTBA3jI7h8mGR+Ldxd4gALw+uTIjiyoQoqmvM7E4p4IejOfx2pojIQC/6hfvTP8Kf+DB/eof6NruaTQghRNcVHaRjX2Z5hyjNYlPCN2rUKGe3g5deeokJEybUu1dBQQFGo5GIiAjrYz179iQtLa3ZY40xGAwYDOeKQ5aWWibWm83mNu8RbDabURTF5uv41CZ85Xpjl9qfuKraxI5T+Ww6lsuPx3PJL29+9WqAl4arRvTg+vNiGBh5rqCkI2OmVcOEPiFM6NP4sntH36892fs+FbaRuDqexNTxJKaOZzabiQqwDOOeKahol9jac0+bEr633nqr1Y2xxeHDh/nss8/YunWr0+6xYsUKli9f3uDxvLw89Hp9m65tNpspKSlBURSblrvrajuMzubmE+ZhaP7kDq6gwsgvKSVsO13MnrRSDDXnuu18PNUMifAlzM+TUD8Puvta/g318yDYW4vGWEFwtyDUaj25uW37Ggn736fCNhJXx5OYOp7E1PHMZjPdPCwjdck5xZat61ysrKys5ZNqucXSmG3btpGamkp8fDwA2dnZ3HHHHSxfvhytVkt2dra1Jy81NZXY2FhCQkKaPNaYZcuWsWTJEuvnpaWlxMTEEBoa6pCt1VQqFaGhoTZ9I/l766DIgM43gLCw0Dbd290YjCYSzxSx/WQ+25LzOZZV/83YI8ibiwaEcdFAywbjTW1IbTabycvLszmmomX2vk+FbSSujicxdTyJqeOZzWb6RVUCuWSV1RAWFubyNnh52b6dnFskfIsXL2bx4sXWz6dMmcJ9993H7Nmz2b17NytXruSJJ54gMTGRzMxMJk+eDMB1113X5LE/0ul06HQNV9Co1WqHvPlVKpXN16orzVJlNHeYbzy90USZvoYas5kak4LRZMZkVjCaFPQ1JvalFbP1RB67Uwrq7RgBkBAdyMUDw7l4UDgDImyvNWdPTIVtJKbOIXF1PImp40lMHS86yJJw5ZUZ0NeYXb71pT1fS7tbZjQaSUtLo0+fPvY+tVWee+455s6dS3x8PJ6enqxdu9a6Cre5Y+7Mu/YN0RF229AbTby5OZmVW09TXWPbXIHwAB0T40OZGN+dC/p2b7J6uhBCCNGRBXhpCfT2oKTKSFphJQMi2jZi6Ex2JXxbtmzhpptuQqvVkpaWRmJiIq+++ipr1651aKO2bNli/X94eDjff/99o+c1d8yd+db18Ln5Kt0dp/J55PPDpOSfq32nVavQalR4qNVoNSq0GjUeahV9wvyYFB/KpH6h9Av3k+LCQgghuoTYYB8OZZZwpqATJXxLly5l27ZtXHvttYClFIor6vN1NnXFlyvctIevsKKaZ74+xmd7MwAI89fxxJWDuWRIhCRyQgghxO/E1SZ8aW5emsWuhM9kMjUYyvX09HRog7qCujl87jakqygK6/dm8vTXRymqNKJSwZyxcTw4sz8Bbax9J4QQQnRGsSGWPXXPFNq/E5Qr2ZXweXl5UV5ebu3lOXToEN7e3k5pWGfmWzuHz12GdBVF4dczRbz8wwl2nCoAoH+4P89ePdTtK4cLIYQQ7Sk22JIHuXvxZbsSvscee4zp06eTmZnJnDlz2LRpEx999JGz2tZpebtJD5/eaOLL/Zm8t+MMR7Mshah1WjX3XhzP7RN749GB9zgUQgghXCEu2NLDl1bYSRI+RVEYOnQoH374IRs3bkRRFJYvX+6y1bqdSXsP6aYXVrJ21xn++2s6xZVGALw81MxK6MGdU/sQF+LbLu0SQgghOpq6Id3MoipqTGa0btpZYlcP37Rp0zh8+HC9mnnCfufKsrh2SDezuIonvjrCpmM5KLUbXkR38+aW8+O4/rwYgnxkPqYQQghhj3B/Lzy1aqprzJwt1lsTQHdjc8KnUqmIjo4mPz+f7t27O7NNnZ5vO/Xwrdxyih+O5gAwMb47887vydQBYWjUsvJWCCGEaA21WkVMN29O5VVwprCi4yd8AH5+fgwfPpxLL70UPz8/6+MvvfSSwxvWmbXXkO6BjGIAnr92GNefF+PSewshhBCdVVyIryXhK6hkYnx7t6ZxdiV8Q4cOZejQoc5qS5fRHjttGGpMHKtdmDGuV4jL7iuEEEJ0drEdYOGGXQnf448/7qx2dCntsdPGiexyjCaFQG8PYoKllI4QQgjhKHG1w7juXHzZrqUkZWVl3HXXXfTr149+/frxl7/8hbKyMme1rdNqj502DmYWAzAsOlB2yxBCCCEcKM5afLmTJHx33nknNTU1rFu3jk8++QSTycSdd97prLZ1Wj7WwsuuS/gOZZQAMLRHoMvuKYQQQnQFscGWcmZpBRUodWUw3IxdQ7oHDx7kwIED1s/ffPNNEhISHN6ozu7cKt0aFEVxSY/bwdqEb1i0JHxCCCGEI8UEe6NSWUbuCiqq6e6na+8mNWBXD5/JZKo3hFteXo7J5F77wXYEdUO6ZgUMNWan309vNHEix/J1Gxod5PT7CSGEEF2JTqshMsALcN8t1uxK+ObNm8e4ceN48sknefLJJxk3bhy33nprmxuh1+uZPXs2/fr1IyEhgWnTppGcnAxAbm4uM2fOJD4+niFDhrB161br85o75s7qhnTBNSt1j2WVUmNWCPH1JCrQy+n3E0IIIbqauvp7aYUV7dySxtmV8D344IO8+OKLlJaWUlpaygsvvMD999/vkIbccccdJCUlceDAAWbNmsXChQsBWLp0KePGjePkyZOsXr2am266CaPR2OIxd6ZRq/DUWkLvit02DmXWzt+TBRtCCCGEU8TVzuNz1x4+m+bwlZaWUlhYSM+ePZk5cyYzZ84EIDU1ldLSUgICAtrUCC8vLy699FLr5+PGjeOFF14AYN26ddbevtGjRxMVFcXPP//MxRdf3Owxd+frqaG6xuyShRvW+XuyYEMIIYRwilg3L81iU8L30EMPMW3aNHr27Fnv8b179/LDDz/wr3/9y6GNevXVV5k1axYFBQUYjUYiIiKsx3r27ElaWlqzxxpjMBgwGAzWz0tLLUWIzWYzZnPb5tGZzWYURbHrOt6eGooqjZTrjW2+f0sO1u6wMaRHgNPv5SitialonsTUOSSujicxdTyJqeP9Maax3Sw1bs8UVLgszvbcx6aEb8+ePaxcubLB41dffTWPPfaY7S2zwbPPPktycjI//vgjVVVVDrvuihUrWL58eYPH8/Ly0Ov1bbq22WympKQERVFQq20bJfesPe1sbgGRuuo23b85VUYTybnlAETqjOTm5jrtXo7UmpiK5klMnUPi6ngSU8eTmDreH2Pqr7LkEin55S77XWtPLWSbEr6amqbnmTnyjfPCCy+wfv16Nm3ahI+PDz4+Pmi1WrKzs609eampqcTGxhISEtLkscYsW7aMJUuWWD8vLS0lJiaG0NDQNg9Jm81mVCoVoaGhNscjwCcZCvV4+voTFhbWpvs359czRZgVCPPXMbh3tNPu42itialonsTUOSSujicxdTyJqeP9MaY6fyNwnMLKGnwDg/HV2VX5rlW8vGxfiGlTa4xGY6Nz9UpKShy2SOKll17i448/ZtOmTQQFBVkfv+6661i5ciVPPPEEiYmJZGZmMnny5BaP/ZFOp0Ona1gXR61WO+TNr1Kp7LqWT932akazU7/5Dmdahq6HRQd2uG9ye2MqWiYxdQ6Jq+NJTB1PYup4v49pN18dgd4elFQZySjWMzCybZ1JtrDna2nTmTfccANz586lqKjI+lhRURG33norN9xwg/0t/IOMjAzuv/9+iouLmTp1KsOHD2fs2LEAPPfcc+zYsYP4+Hjmz5/P2rVr8fDwaPGYuzu324ZzV+laV+j2CHLqfYQQQoiuzrrFmhsu3LCph+/RRx9lwYIFxMTEEB8fD8DJkye55pprHDKHLzo6usmtSMLDw/n+++/tPubuvK27bTh3lW7dgg3ZYUMIIYRwrthgHw5mlLhlLT6bEj6NRsN7773H3//+d/bu3QvAyJEj6dOnj1Mb15n5uiDhK9MbOZ1vedMNkZIsQgghhFN1+B6+On369JEkz0HqhnSdWXj5yNlSFAWiAr0I9Xe/ff2EEEKIzqSu+HJaofslfDJzs524Ykj3UMa5HTaEEEII4VyxbtzDJwlfO6kb0nXmThsHaxdsDIsOcto9hBBCCGFRN6SbWVyF0eReRa4l4Wsn3rVDuhVO7eErBmCozN8TQgghnC7c3wtPrRqTWSGruG2bOjiaJHztxFqHz0lz+EqqjKTWdilLwieEEEI4n1qtIja4dljXzVbqSsLXTnycPIfvSO1wbkywN918PZ1yDyGEEELUFxfsnvP4JOFrJz5OHtK1zt+TgstCCCGEy9Qt3HC3lbqS8LUTZw/pygpdIYQQwvXO9fDJkK6g5bIsaQWV/Jpa2OrrH8wsBmCYzN8TQgghXCYuxFKLz92GdO0qvCwcx9daeLl+wqc3mnhjczIrfz6F0aTw2OWDuO2CXnZdu6iimvTCKgAGS8InhBBCuExM8LkhXUVRUKlU7dwiC0n42sm5RRvnhnS3nczj0S8O1/ur4KkNRwn29eCqEdE2X/tQ7fy9Xt19CfT2cFCLhRBCCNGSmGBvVCpLh05+ebXb7HQlQ7rtpG5IV280k1uq597/7GPuO3s4U1BJeICOf908klsn9ATgwU8Osvl4rs3Xrkv4pByLEEII4Vo6rYbIAC8A0tyoNIskfO2kbkgX4KIXf+bL/WdRqWD++J5sWjKZS4ZG8thlg5g9PIoas8LiD3/jtzO2zek7WFtweZgs2BBCCCFczh23WOvwCd/JkycZP348/fr1Y/To0Rw5cqS9m2QTLw81dcP6ZYYahvQI4Mu7JvDElYPx97IMw6rVKv55XQJT+oeiN5q5dXUiSdllLV67boXuEOnhE0IIIVwuLtj9Fm50+IRv0aJF3HHHHZw4cYKHH36Y+fPnt3eTbKJSqUiIDsLXU8Njlw/iizsnNLrnrYdGzZs3j2RkbBCl+hpueXc3GUVNv4HyygycLdGjUsHgqAAnvgIhhBBCNGb2iB6suHoolw2LbO+mWHXohC83N5dff/2VOXPmAHDNNdeQnp5OcnJyO7fMNusWnc9vj03jtgt6odU0/aXw8dTy7vzR9Av3I6fUwC3v7KGg3NDouYdr5+/17u5r7SkUQgghhOuc3yeEG8fE0i/cv72bYtWhV+mmp6cTGRmJVmt5GSqVitjYWNLS0ujbt2+9cw0GAwbDuSSptLQUALPZjNlsblM7zGYziqLYfR2tGkBl0/MCvLSsmT+a61bt4nR+BTf8exfDY4IanHcy1zLkO7RHYJtfV3tqbUxF0ySmziFxdTyJqeNJTB3PHWJqz707dMJnjxUrVrB8+fIGj+fl5aHX69t0bbPZTElJCYqioFY7r9NUDbw8qzd3rEviZG45J3PLmzw3vpuW3FzbV/a6G1fFtCuRmDqHxNXxJKaOJzF1PHeIaVlZy/P666gURVGc2Banys3NpW/fvhQWFqLValEUhcjISLZv325TD19MTAxFRUUEBLRtrpvZbCYvL4/Q0FCXfNEziir59nA2NebGv3SBXh5cM6oHOq3G6W1xFlfHtCuQmDqHxNXxJKaOJzF1PHeIaWlpKd26daOkpKTFXKZD9/CFhYUxcuRI1q5dy/z58/nss8+Ijo5ukOwB6HQ6dLqGxQ/VarVDvlAqlcph12pJbIgfiyY3fI2djStj2lVITJ1D4up4ElPHk5g6XnvH1J77duiED2DVqlXMnz+fZ599loCAAFavXt3eTRJCCCGEcCsdPuHr378/O3fubO9mCCGEEEK4LenXFUIIIYTo5CThE0IIIYTo5CThE0IIIYTo5Dr8HL7WqqtGU1eAuS3MZjNlZWV4eXnJ6icHkZg6nsTUOSSujicxdTyJqeO5Q0zrchhbKux12YSvrlhhTExMO7dECCGEEKL1ysrKCAwMbPacDl14uS3MZjNnz57F398flUrVpmvVFXFOT09vcxFnYSExdTyJqXNIXB1PYup4ElPHc4eYKopCWVkZUVFRLfYydtkePrVaTXR0tEOvGRAQIN9IDiYxdTyJqXNIXB1PYup4ElPHa++YttSzV0cG8oUQQgghOjlJ+IQQQgghOjlJ+BxAp9Px+OOPN7pXr2gdianjSUydQ+LqeBJTx5OYOl5Hi2mXXbQhhBBCCNFVSA+fEEIIIUQnJwmfEEIIIUQnJwlfM06ePMn48ePp168fo0eP5siRI42e98477xAfH0+fPn24/fbbMRqNNh3rqtoa1y1btuDt7c3w4cOtH1VVVa58CW7HlpimpqYyZcoUAgMDGT58eIPj8l6tr60xlfdpQ7bE9KeffmLMmDEMGjSIwYMH89BDD2E2m63HN2zYwIABA4iPj+fqq692yG5JHVlbY5qamopGo6n3Pj116pSrX4bbsSWuO3futMZs8ODBLFq0CIPBYD3udj9TFdGkqVOnKqtXr1YURVE++eQT5bzzzmtwzunTp5XIyEglKytLMZvNyhVXXKG8/vrrLR7rytoa182bNysJCQkubLH7syWmBQUFyrZt25QNGzY0iJ+8Vxtqa0zlfdqQLTHdu3evcurUKUVRFKWqqkqZMGGC9TllZWVKWFiYcuzYMUVRFOWuu+5SHnjgAZe03V21NaYpKSlKYGCgi1rbcdgS14qKCqW6ulpRFEUxmUzK7NmzlZdeeklRFPf8mSoJXxNycnIUf39/xWg0KoqiKGazWQkPD1dOnjxZ77znn39eWbRokfXzr7/+WpkwYUKLx7oqR8RVfpHWZ2tM6zQWP3mv1ueImMr7tD57Y1rnrrvuUh5//HFFURRl3bp1yowZM6zHjhw5ovTo0cNpbXZ3joipJHwNtSauVVVVyowZM5SXX35ZURT3/JkqQ7pNSE9PJzIyEq3WshmJSqUiNjaWtLS0euelpaURFxdn/bxnz57Wc5o71lU5Iq4Ap06dYuTIkYwePZo333zTNY13U7bGtDnyXq3PETEFeZ/+Xmtimp2dzaeffsrll18ONP4+zcrKoqamxrmNd1OOiClARUUFo0ePZuTIkTz55JOYTCant92d2RPX1NRUEhIS6N69O4GBgdx5552Ae/5MlYRPdDgjR44kIyODvXv38vnnn7Ny5UrWrVvX3s0Soh55n7ZNaWkpV1xxBQ899BDnnXdeezenU2gsppGRkWRmZpKYmMimTZvYtm0bL774Yju3tOPo2bMnBw4cIDs7G4PBwPr169u7SU2ShK8JMTEx9f5yVBSFtLQ0YmNj650XGxvLmTNnrJ+npqZaz2nuWFfliLgGBARY9w6Mjo7mxhtvZNu2bS56Be7H1pg2R96r9TkipvI+rc+emJaVlTFz5kxmzZrFkiVLrI839j79fU9MV+OImOp0OsLCwgAIDg5mwYIFXfp9Cq37/vfz8+OGG27gww8/BNzzZ6okfE0ICwtj5MiRrF27FoDPPvuM6Oho+vbtW++8a665hq+++ors7GwURWHlypXccMMNLR7rqhwR16ysLOsKs7KyMjZs2MCIESNc+0LciK0xbY68V+tzREzlfVqfrTEtLy9n5syZzJw5k0cffbTesZkzZ7J3716OHz8OwJtvvinv0zbGNDc317p6tK6Hqiu/T8H2uCYnJ1tjV11dzeeff86wYcMAN/2Z2j5TBzuG48ePK+PGjVPi4+OVUaNGKQcPHlQURVFuu+025csvv7Se9+9//1vp3bu30rt3b2XBggXWVTstHeuq2hrX1157TRk0aJAybNgwZdCgQcrjjz+umM3mdnkt7sKWmFZUVCg9evRQunfvrnh4eCg9evRQli5dar2GvFfra2tM5X3akC0xffrppxWtVqskJCRYP55++mnrNb788kulf//+Sp8+fZRZs2YpxcXF7fJa3EVbY/rZZ58pgwcPtr5P7777bkWv17fb63EXtsR11apV9WL3l7/8RamqqrJew91+psrWakIIIYQQnZwM6QohhBBCdHKS8AkhhBBCdHKS8AkhhBBCdHKS8AkhhBBCdHKS8AkhhBBCdHKS8AkhhBBCdHKS8AkhhBBCdHJdcz8aIYT4neHDhwOWavlJSUkMHToUgP79+1s/br75Zqfdv7KykkmTJrF582b8/f0bPUev1zNhwgR++ukn65ZtQghhKym8LIQQtVJTUxk+fDjFxcUuve/zzz+PwWDgsccea/a8V155hcLCQp588kkXtUwI0VnIkK4QQjRj/vz5vPLKKwA88cQTXH/99VxxxRX069ePyy+/nMOHDzNjxgz69evHjTfeWG//3Ntvv50xY8YwbNgw7rjjDqqrqxu9x6pVq7jpppsAMJvN3H333QwcOJCEhARGjRqFXq8H4IYbbuCtt95C/k4XQthLEj4hhLDDr7/+yvvvv09SUhJlZWUsXLiQTz/9lKNHj3Ls2DG+/fZbAO6//34mTpzInj17OHDgAGazmVdffbXB9dLT0ykpKaFPnz4AHDhwgB9//JEjR45w4MABfvrpJzw9PQGIiIjA29ubI0eOuO4FCyE6BZnDJ4QQdpg+fTrdunUDYOTIkeh0Ouu8uxEjRnDy5EkAvvjiC3bu3MlLL70EQFVVFRqNpsH1MjIyCA8Pt37eu3dvampqWLBgAVOnTuWyyy5DrT73t3lERAQZGRkMGTLEaa9RCNH5SMInhBB28PLysv5fo9E0+LympgYARVH47LPP6NevX7PX8/HxsQ7ZAgQGBnL48GF+/vlnNm/ezLJly9i6dSt9+/YFLIs3vL29HfmShBBdgAzpCiGEE8yePZvnnnvOmgAWFRWRnJzc4Lz+/fuTm5tLVVUVAHl5eVRUVDB9+nSeffZZevbsydGjRwEwmUycOnXKuopYCCFsJQmfEEI4wcsvv4y3tzfDhw9n2LBhXHTRRaSmpjY4z8vLi+nTp/PTTz8Bljl906ZNY9iwYQwZMoQhQ4ZwySWXALB9+3ZGjx5NcHCwK1+KEKITkLIsQgjRzvbs2cOTTz7Jhg0bmj3vhhtu4LbbbmPatGkuapkQorOQHj4hhGhnY8aM4eqrr6asrKzJc/R6PZMnT5ZkTwjRKtLDJ4QQQgjRyUkPnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJnxBCCCFEJycJH3DPPffQs2dPVCoV+/fvt+k51157LVFRUahUKoqLi+sd++CDD0hISGDIkCFcdNFFpKWlOb7RQgghhBA2koQPS/K2fft24uLibH7On//850aTw+PHj/Pggw+yceNGDh8+zK233srixYsd2FohhBBCCPtIwgdMmjSJ6OjoBo8nJiZy4YUXct555zFixAg++eQT67GLL76YsLCwBs85fPgww4YNIzIyEoBLL72Ub7/9loKCAue9ACGEEEKIZmjbuwHuqri4mDvuuINvvvmGyMhI8vPzGTlyJOPHj6dHjx5NPi8hIYG9e/dy4sQJ+vXrx9q1a1EUhTNnzhASEuLCVyCEEEIIYSEJXxN27NjB6dOnueSSS+o9npSU1GzCFx8fz8qVK7nllluoqanhsssuIygoCK1WQi2EEEKI9iFZSBMURWHw4MHs2LHD7udee+21XHvttQBkZ2fz3HPP0bdvX0c3UQghhBDCJjKHrwnjx48nJSWFTZs2WR/bv38/1dXVLT43KysLAJPJxMMPP8xdd92Fj4+P09oqhBBCCNEclaIoSns3or0tWrSIr7/+muzsbEJCQvD39yc5OZm9e/fywAMPUFBQgNFoJDY2li+++AIvLy8uu+wyDhw4QGZmJlFRUcTHx7NlyxYALrnkEs6cOYPBYOCyyy7jn//8Jzqdrn1fpBBCCCG6LEn4hBBCCCE6OZfP4SsrK2Pbtm1kZGTg7e1NQkICw4YNc3UzhBBCCCG6DJf18J05c4a///3vfPvttwwdOpSIiAj0ej3Hjh3DbDbz0EMPsWDBAlc0RQghhBCiS3FZwjdp0iQeeOABLr300gYlSlJTU1m1ahU9evTg7rvvdkVzMJvNnD17Fn9/f1QqlUvuKYQQQgjhKIqiUFZWRlRUFGp18+twu+wcvoyMDGJiYtq7GUIIIYQQbZKent7ojmG/5/Q5fOXl5fj4+KBWqzly5AheXl706dPH2bdtkb+/P2AJUkBAQJuuZTabycvLIzQ0tMUMW9hGYup4ElPnkLg6nsTU8SSmjucOMS0tLSUmJsaa0zTHqQnf3//+d3bs2EGPHj0ICgoiMzMTf39/YmJiePLJJ5156xbVDeMGBAQ4JOHT6/UEBATIN5KDSEwdT2LqHBJXx5OYOp7E1PHcKaa2TE1zasL3008/sX37dkwmE4MGDSIpKQmAKVOmOPO2QgghhBDid1ySkmo0Gp544gnr57JIQgghhBDCdZya8L388suYTCYAbrzxRgCqq6u56667nHlbIYQQQgjxO04d0h09enSDxzw9Pbn88sudeVshhBBCCPE7Lp9leNdddxEUFERgYCAXXHAB9957L++9956rmyGEEEKITsJsVnh6w1FW/XzK7ufmluk5lVfuhFa5F5dvrfbtt9+Sn5+PVqvlwIED/Pbbb2zbto158+a5uilCCCGE6AR+PVPE29tTAAjw9uDGMbE2PS+toJLZb/5CuaGGzQ9MoUeQtzOb2a5cnvD179/fWpdv7NixjB071tVNEEIIIYQbKqyo5qUfkrh0SCTj+3a3+Xmbk3Kt/3/8yyMMiPBnRGy3Zp9Tpjdy23uJFFZUA/DDkWzmT+jVuoZ3AC4f0n3qqae46667yM/Pd/WthRBCCOGmjCYzi9f+xtpdaTz65WG7nrv5uCXhiwr0otpkZvHaveSVGZo832RWuOfjfZzMPTeU++Px3CbP7wxcnvD985//5D//+Q99+/ZlyJAhzJ8/n9dff93VzRBCCCFEG6QVVPLKphOcKahwyPWe/eYYu1MKATidV0Fyrm3z6rJL9BzPLkOlgv8uOp++YX5kl+q566O9GE3mRp/zj2+PsTkpDy8PNa/8aTgAu08XUm6occhrcUcuT/gSExPJysqiqKiITz/9lIsuuoiTJ0+6uhlCCCGEaIMHPj3AK5tOMv3lrbz240kMNaZWX2v93gxW/5IKYJ1H992RbJueu6V2OHd4TBAxwT6smjsKP52WPSmFPPvNsQbn/zcxjbe2Web7vXBdArOGR9EzxIdqk5ntJ/Na/RrcncsTvsGDB6NWq1GpVAwYMIC5c+fy6quvuroZQgghhGiltIJK9tT2xhlqzLz4wwkufXUbO08V2H2tw5klLFt/CIB7LuzLnVP7APD90Rybnl83f29q/zAA+oT68dL1CQCs/iWVz/dlWM/dfbqAR7+wDBffe1E8lw+LQqVSceGAcAB+PNZ5h3VdnvAFBARwww03kJKS4upbCyGEEMIBPttrSaImxnfn1RuG091Px6m8Cm58axdL1u2noLzp+XO/V1BuYNEHv2GoMXPhgDDuu7gf0waFo1LBgfRiskv0zT6/usbM9pOWNQFT+odaH58+OIK/XNgXgGXrD3HkbAlpBZX8ee1vGE0Klw2N5N6L4q3nXzTQkixuTsrFbFZsD0QH4vKEr1evXlRVVTFu3Diio6OZPXs2Tz/9tKubIYQQQohWMJsVa8J37ahoZg3vwY/3T2bOuFhUKli/N5MLX/yZ/+xJo6aJOXQANSYzd3+0j8ziKnp19+XlPw1HrVYR5u/FiJggAH442vyw7q9nCqmoNtHdz5MhUYH1jt13cT8m9wtFbzTz57W/sfD9RIoqjQztEcgL1yWgVp/b5nV0z2D8dVryy6s5mFnSysi4N5cnfE8//TTffvstOTk57Nq1i1tvvZXq6mpXN0MIIYQQrbA7pZCMoir8dVqmD4oAINDbg6dnD2X94vEMigygpMrI0vWHGPPsj/zt80PsSM7H9IeesxXfHmfn6QJ8PTX8e+4oAr09rMemD7Zct6Vh3S1Jljl3k/uF1UvgADRqFa/eMJzYYB/SC6s4kVNOmL+Ot245D29PTb1zPbVqJvWz9BD+eMy2oeSOxmUJ31133cUPP/xg3VsXIDo6mlmzZvHkk0+6qhlCCCGEaINPf7P07l2eENkgcRoR242v7p7Ao5cNJNjXk8KKaj7ancZNb+9m7LObeOyLw+w6XcBnv2XwTm2h5BevH058uH+968yoTfh2niqgpNLYZFvqyrFMHRDa6PEgH09WzhmFj6cGLw81b91yHhGBXo2ee+EAy7BuZ53H57LCyxdeeCHvvfceixYtYvz48Vx11VVccskl+Pj4uKoJQgghhGiDCkMN3x7OAizDuY3RatQsnNib+eN7svN0AV8fzGLjkWzyy6v5YNcZPth1xnruXy7sy8whEQ2u0au7L/FhfpzMLWdzUi6zR/RocE5GUSUnc8tRq2Bi38YTPoBBUQFsfmAKAOEBjSd7AFMHhKFSwdGsUrJKqogM7Fy7brish++aa65h7dq1nDhxgnnz5vHTTz8xbNgwrrzySt59910pxCyEEEK4uW8PZ1NZbaJXd19GtrCThVajZmJ8KP+4ZhiJj1zMmltHc+2oaPy9LH1NdYs0mlLXy9dUeZa64dxRcd0I9PFo9Jw64QFezSZ7AMG+ntbX1Bl7+Vy+tZpWq2XatGlMmzYNgD179vD5558zdepUDh065OrmCCGEEMJGn/6WDlh691QqVQtnn+OhUTOlfxhT+ofx7FVDOZZVyqCoADTqpq8xfXA4r29O5ucTeeiNJrw86g8f19Xfm1JbjsURLhwQxm9nivjpeC5zxsU57LruwOWLNv5ozJgxrFixQpI9IYQQwo2lF1ay63QhKhVc1cgQq608tWoSYoLw0DSfggztEUhkoBeV1SZr6ZU6eqOJX5ItNf+mOjDhqyvP8ktyPlXVrS8k7Y7aPeED6Nev6S5dIYQQQrS/ulIsE/p0JyrI+fPbVCoV0wdZCiJ//4fyLHtSCqkymggP0DEw0r+xp7dK/3B/egR5Y6gxs+NU55pq5rIh3YMHDzZ5rKyszFXNEEIIIYSd/lh7z1WmD47gvZ1n2HQslxqTGW1tr2Dd/L0p/cLsGlpuiUql4qKBYbxfe8+LBoY77NrtzWUJ3/Dhw+nZsyeK0rCCdUGB/Vux/NHq1atZsGABn3/+ObNnz27z9YQQQghhkZhaSHphFX46rXUxhSuM6RVMoLcHhRXV/HamiLG9Q4Bz8/eaKsfSFhcOsCR8Px3PQVGGODShbE8uS/ji4uLYvn07UVFRDY7FxMS06dqpqam89dZbjBs3rk3XEUIIIURD1tp7wxrW3nMmD42aiwaEsX5fJt8fzWFs7xBS8ys4nV+BVq1iQt/uDr/nuN4h+HhqyCk1cORsKUN6BLb8pA7AZXP4rrzySk6fPt3oscsuu6zV1zWbzSxcuJDXXnsNnU7X6usIIYQQoqEKQw1fH2q+9p4zTf9deRZFUay9e6N7BuPv1Xw5ltbw8tBwQW0i2ZnKs7ish+/VV19t8tjKlStbfd2XXnqJCRMmMGrUqGbPMxgMGAznNnMuLS0FLAmj2dz0Xn+2MJvNKIrS5uuIcySmjicxdQ6Jq+NJTB2vLTH99lAWldUm4kJ8GBET6PKvywV9g9Fp1WQUVXH0bAmbaxO+yf26O60tUweE8v3RHH48nsNfLuzT6Dnu8D61594uS/h2797N2LFjmzxeVVVFSkoKgwYNsvmahw8f5rPPPmPr1q0tnrtixQqWL1/e4PG8vDz0er3N92yM2WympKQERVFQq91i4XOHJzF1PImpc0hcHa+rx7TGpKBR49C5Y83FdNvpYvZnljMy2p+R0X54/6He3X92W7ZAm9EviLy8PIe1yR5jY/3ZerqEj3cks+uUZd7/sFANubnO6YEbGmKJ0cGMEo6lZBLi27An0R3ep/YsenVZwvfiiy9SVFTETTfdxNixYwkPD0ev15OUlMTGjRv5/vvvefnll+1K+LZt20Zqairx8fEAZGdnc8cdd5CVlcXixYvrnbts2TKWLFli/by0tJSYmBhCQ0MJCAho02szm82oVCpCQ0O75A8nZ5CYOp7E1Dkkro7XlWOaUVTJpf/6hbG9gnnz5hEt1qqzVVMx3XGqgKUbTmMyK3z4Ww6eGhWjewUzOT6UifHd8dVp+DW9DJUK5k7sR5gLyrE05vIR1Ww9fYh1B/KoNilEBXkxdkCs0xZUhAHDos9wMKOEQwVmru/VsNafO7xPvbya3z3k91yW8K1bt47ExERWrVrFM888Q0ZGBr6+vgwbNoxrrrmGX375BV9fX7uuuXjx4nqJ3ZQpU7jvvvsaXaWr0+kaneOnVqsd8oVSqVQOu5awkJg6nsTUOSSujtdVY/rDsTzKDTX8eDyXZ745zpOzhjjs2n+MaWp+BXd9tA+TWWFYdCAF5dVkFlfxS3KBpajxt1h7+8b3CSEm2L7f0Y508aAI1OsPUV1jGcKc2j8Mjca5i0cuGhDOwYwSfjqexw1jGt91o73fp/bc16Vbq40ePZrRo0e78pZCCCFEh7H79LkyZe/vPEN8uD9znbDFV6neyML3f6WkykhCTBD/vWMcOq2aU3kVbD2Rx88n8th1uoAqo2W3ievPa1s1jbYK9vVkTK9gdp0uBBy7nVpTLhoYxsubTrA9Ob/Rrd06GpfvpetMW7Zsae8mCCGEEK1iNivsSbUkNJcNjeTrQ1k88dUR+nT3ZXwL5UeSc8u4/5ODaFSw4uph9I9oevcJk1nhno/3kZxbTkSAF2/NHWVNZvqG+dE3zI8FF/RCbzSxO6WQ0iojlw+LdNwLbaXpgyLYdboQT42a8X1CnH6/wVEBRAR4kV2q5+uDWVzTDiuUHalr9ZULIYQQbiopp4ziSiM+nhpeuWE4V43ogcmssPjDvaTmVzT5vC/3Z3Ll679wIL2YvWnFXPH6dt7edhqzueFGBwDPbTzOlqQ8vDzUvHXLeYQFND4PzMtDw+R+oVyREOUWxYdnDY9iQIQ/8yf0xFfn/P4qlUrFvPE9AXjx+yT0xo69t64kfEIIIYQbqBvOHRXXDQ+NmhVXD2V4TBAlVUZuey+RkipjvfMNNSYe++Iw9/5nP5XVJib0DWFq/1Cqa8w8/fUxbn57N5nFVfWe8+lvGfx7q6Um7gvXJTA0uuMUFQ7x07Hxvkn87dKBLrvnrRN6EhXoxdkSPWt2pLrsvs4gCZ8QQgjhBurmp42r3T7My0PDv28ZRWSgF6fyKvjLx/uoMVkWLaQXVnLdyp18sOsMAPdc2Jf3F4zl3fmjeeaqIXh7aNh5uoCZr2zli32ZKIrCgbPlPPrFYev5lw9ruPOVqM/LQ8P90/sD8MbmZIoqqtu5Ra3n8oSvuLjY1bcUQggh3JqinJu/N653sPXxMH8v3rrlPLw9NGw9kcez3xznp+M5XP7adg5mlBDk48HqW0ezZHp/NGoVKpWKm8fG8c29ExkeE0SZvob7/rufuz7ax9INp6g2KcwcHMF9F/drr5fa4cwe0YOBkQGU6Wt4fXNyezen1Vye8MXHx3P77bdz4MABV99aCCGEcEsnc8sprKjGy0PN0B5B9Y4N6RHIS9cnAPDuLyksWHNude3X90xkaiMrVnt19+XTP5/Pkmn90KhVbDySQ1FlDQMj/XnpTwmo1e0/J6+j0KhVLLtkAADv70wlraCynVvUOi5P+JKTkxk8eDDXX389EydOZN26dZhMHXsipBBCCNEWu2rn750XF4yntuGv5kuGRrJk2rleuXnnx7Fu0Th6NFMIWatRc89F8Xx+53j6R/gTHajj33NG4ePZqQp0uMSkfpZC1EaTwj+/T2rv5rSKyxO+wMBA7rvvPpKSknjkkUd44IEHiI2N5ZlnnqGioulVSEIIIYQz/PO748x4eSuHM0varQ27a+fvje0V3OQ5f7mwL89fO4w1t45m+awh6LS21YUbFh3Et/dcwLr5g+nRrX12yugMll4yAJUK/nfgLAfSi9u7OXZrl0UbpaWlvPLKK9x7770MHjyY1157jezsbGbMmNEezRFCCNFFbTh4ljc2nyIpp4z5qxNJL3T9cJ2iKOxOsfTwje3ddH05lUrF9efFtLrosNoNSqt0ZIOjArlqRA8Anv3mGIrSeNkbd+XyhG/RokX069eP5ORkvvrqK7799luuvvpqXnvtNQoKClq+gBBCCOEAZ4ur+Nv6QwD46bTklxu45d09FJQbXNqOU3kV5JdXo9OqSYjpOGVSuqL7p/fHU6tmd0ohPyXltXdz7OLyhK9v374kJSXx+uuv07+/Zalzfn4+AD/99JOrmyOEEKILMpkVlqzbT6m+hoToQL776yR6BHmTkl/Bgvd+pbK6xmVtqZu/NzK2m83DtKJ99Ajy5tYJPQF4fmMSNU0Ut3ZHLk/4Pv74YwID6/8FM336dAAiI9t/6xYhhBCd31vbTrPrdGHtrhYj6BHkzfu3jaGbjwcH0ou568O9GGtr3tlDURQqq2vILdWTWVxl07Df7pTa+Xu9m56/J9zHnVP6EuTjwcnccjYcyW/v5tjMZUt1qqur0ev1mEwmysrKrN8EJSUlslhDCCGEyxzKKOHF2pWWT1wxmF7dfQHoE+rHO/NHc9Nbu9iclMey9Yf457XDGt1WLLdUz/p9mfyclEdxlZEyvZFyQw1l+hpMv+v1+evF/bj34vgm26IoinWHjXHNzN8T7iPQ24O/XBjPUxuO8tbOs8yZ2B8/L8/2blaLXNbDt2LFCoKCgjh8+DCBgYEEBQURFBTE0KFDmTNnjquaIYQQogurrK7h3v/uw1hbgPi686LrHR8Z2403bhqJRq3i098yePH7E9Zj1TVmNh7O4rY1iZz/j5/4x7fH2Xm6gGNZpWQUVVFcabQme3U54sqfT5FX1vScwJT8CnLLDHhq1QyPCXL46xXOMWdcLNHdvCmorGHTsdz2bo5NXNbD9/jjj/P444+zePFi/vWvf7nqtkIIIYTV018f43ReBeEBOlZcPbTR3ruLBobzzOwhLF1/iNc3J6PVqCitquGL/ZkU/m5rrVFx3Zg9ogexwT74e2nx12nx9/LAz0uLj4eGq/61gwPpxfxryyn+fsWgRttTN5w7PCYILw+Zv9dR6LQaRsV1I6OoipxSfXs3xyYuS/gqKirw9fXlueeeo7S0tMHxgIAAVzVFCCFEF/TD0Rw+2p0GwEvXD6ebb9PDcDeMiSW3zMBLP5zglU0nrY+H+eu4ZlQ0146Kpk+oX7P3e2B6P+a+s4e1u89w+6ReRAY2rIFnHc5tpv6ecE8hte+f/PKOsb+uy4Z0J06cCEBQUBDdunWzDunWfS6EEB1NemElC9//lV/TG/4RK5pWVW3itR9Pst+FxWtzS/U8/NlBAO6Y1JsJfbu3+Jy/XNiX2y7ohU6r5tKhEayeP5odSy/k4ZkDWkz2AC7o250xvYKprjHz+k8N92BVFIVdp+v2z5X5ex1Ndz9LwlcgCV99e/fuBcBsNmMymTCbzdYP2VpNCNERvbM9hZ+O5/HoNyn1hvpE8x7/6jAv/nCCv/53v0uK1xZVVHPnh3sprKhmUGQA90/v1/KTsBQ6fuzyQRx/aiZv3jyKqQPC0Gps/7WpUqm4v3Y7tP8mpjco6pxWWEl2qR4PjYoRsdLx0dGE+OkAKKhwbd3G1mqXnTbqlJSUcPjw4fZsghBCtIqiKPxwNAeA4qoanvr6WDu3qGP4Yl8m637NACwLFg45eTuzw5klXPH6dn49U4Svp4b/u3G43bXuGpvnZ6uxvUOYGN+dGrPCqz+erHesbju1hOggvD1l/l5HI0O6LZg5cybFxcWUl5eTkJDA5Zdfzt///ndXN0MIIdrkeHYZmcVVeGpUqFXw5f6z/HQ8p72b5dZS8it45HPLzhaB3h6AJW7O8sW+TK751w4yiqqIC/Fh/Z0T6Bvm77T7NeX+6ZZNBtbvzeBUXrn18V1SjqVD617Xw+finVlay+UJX05ODkFBQXzzzTfMmjWLkydP8vnnn7u6GUII0Sabanv3JsaH8qcRlr1NH/38MGV6Y3s2yyUMNSa+P5LNXz7ex/krfuSd7SktDs0aakzc/dFeKqpNjO0VzPPXDgMsG9GbHLxbgdFk5sn/HeW+/+7HUGNmSv9QvrrrAvpHuD7ZA8sK3IsHhmFWqLcARAoud2whdXP4Kqo7xL66LlulW8dotPww3Lp1KzNnzsTDwwOt1uXNEEKINtl0zJLwXTwwjHFRWn5JLSOtsIrnNybx1Owh7dw6xzOazOw4VcD/DpzluyPZlOnPbT321IajJOeWsfzKIXhqG+9HWPHNcY6cLSXY15NXbxhBsK8ngd4e5JYZ2H26gPE2LKKwRX65gbs+3GtNpu6e2pe/TuuHRt36YVlH+Ou0fmw6lsv/Dpzlzil98NNpySyuQqtWMSpO5u91RN1rh3SNJoXSqhoCfTzauUXNc3kP35AhQ7jkkkvYsGEDF154IZWVlS0/SQgh3EhOqZ4DGZa5ZxcOCMPbQ8OzVw0F4INdZ9hTm2x0BlklVTzy+SHGPvsj897dw6e/ZVCmryEiwIuFF/TivovjUang4z3p3PLubooaWbzy3ZFs1uxIBeDF6xKICPTCU6vm0qGW7TQdNay7L62IK17bzu6UQnw9NaycM4oHZvRv92QPYHBUIJfVvt6XfzhhTUiHRQfi4ymdHh2RzkODr6cljcrvAAs3XJ7wrVmzhkWLFrF582Z8fHwoKipixYoVrm6GEEK02k/HLZX1h8cEEepvmcczvk8IN4yOAWDpZwfRG11ffSC7RM+Rs45bBJFfbuCGf+/iw91pFFZUE+LrydxxcaxbdD47ll7Io5cP4r6L+/HOvPPw9dSw63Qhs9/8heTcc/PUMoureOhTSzmU2yf2YuqAMOuxKxOiAPjmcBaGmtbH63BmCYs++JWr3txBVome3t19+eKuCcwcEtHqazrDX6fFo1bB90dzeK82AR4r8/c6tG61vXr5zeym4i5cnvB5eXlx5ZVXotPpSEtLw2QyMWhQ4xXIhRDCHdXN35s2KLze48suHUiYv47T+RX83x9WZNqqpNLI7Dd+4e6P9mK2Y25bYUU1l/7fNi77v+2sS0xv1b1/r8JQw4I1iZwpqCS6mzfvLxjD7r9dxFOzhzCmVzDq3/WaXTggnPV3TiC6mzdnCiq56s1f2HoiD6PJzD0f76OkykhCTBAPzhhQ7x5jegUTEeBFmb6GLUl5drdxf3oxt61J5PLXtvPdEcvXZNbwKL64ewLx4e0zX685fcP8mT28B4B1dfJYKbjcoQX7WHpnCzpAWaZ26eGr20N31KhRjBo1ivPOO8/VzRBCiFaprK5he3I+ABcPrJ/wBXp7WOfvrdp6msOtKDnyzDdH2Z9ezIaDWaz71fbE7fmNx621AJeuP8h3R7Ltvncdo8nM4g/3cjCjhGBfT95fMIZJ/UKbrUHXP8KfL+6awHlx3SjT13DrmkTmvbuH384U4e+l5fUbRzSY36dRq7giwTLM+dUB24d1f00t5JZ39zD7jV/48XguapWlt/D7v07i1RtGEODlvnOp7r043jrErFGrOK+nJHwdWbfa1eYdYaWuyxO+p556isTERAoKCsjLyyMvL4/c3I6x8bAQQmw/mY+hxkxMsDf9whvutjBjcASXDY3EZFZ4+LOD1JjMNl/7l+R8a406gGe/OUaeDUNFe9OK+E9tr97E+O6YFfjLx/usZT/soSgKD396kK0n8vD20PDu/NH0tmFXCbCUqfjw9rFcPbIHJrPCjlOW+z93zTBign0afc6s2h6vTUdzKDfUNHpOneoaMwvf+5VrV+5k64k8NGoV14yMZtOSyfzfjSPo54a9en8UF+LL9edFAzCkRyB+Opm/15HV9fDldYBafC5P+Lp3707//v1dfVshhHCIutW5Fw0Ib7Ig7xNXDibQ24MjZ0t5Y/Mpm65bWV3D0vWWuW43jY1lcFQApfoanvn6aLPPM5kV/v6lpYD9taOiWT1/NNMHhVNdY+b29361u5fxuY1JrN+XiUat4s2bRzI8Jsiu5+u0Gl68LoGHZw5Ap1WzaFJv6+KMxgyOCqB3qC+GGjPft9Ar+X8/nmTTsRy0ahU3jI5h8/1TePH6BJsTUnfx4IwB3Dgmhr9dMqDlk4VbC/aRHr4mzZ49m1deeYXc3FxKS0utH601ffp0hg0bxvDhw5k4cSL79u1zYGsFQI3JzAc7U+sVDBWiKzKbFeuCjT/O3/u9UH8df7/cMjf55U0n+HxfRpPn1nnp+xOkF1YRFejF3y4dyIqrh6JWwRf7z7LtZNPz2z7afYbDmaX4e2lZeskAtBo1/3fjCMb2CqbMUMP81XtIza+w6fWt/iWFlT9bEtR/XD203gILe6hUKhZP6cPh5TNYdunAFs+dlWDp5Wtute6B9GL+Vdu2/7txBP+4ZhixIY33Grq7YF9PVlw9TBZsdALdanv48iXha+iRRx5hyZIlRERE0K1bN4KCgujWrfU1iNatW8fBgwfZv38/S5YsYf78+Y5rrAAsZSYe+/IIc97eTUll5y8qK0RT9mcUk19ejb+XljEtTLa/emQPFl7QC4AHPznIzyeaTtr2pRXx7i8pADxz9VD8dFqGRQdxy/k9AXj0i8ONrvrNLzfwz++SLPeY0d9a+d/LQ8Nb885jUGQA+eXVzH13N7ml+mbbu+HgWZ7ccNR6revOi2n2fFt42Ljv7JXDLat1tyfnN/qLU280cf8nBzCZFa5IiGq2x1AIVzrXwydDug2YzWbrh8lksv7bWkFBQdb/l5SUtGnPQ9FQjcnMO9stv4iySvQ89mXn2vs4u0TPeztSueHfO+n/6Le8ve10ezdJuLG61blT+oe1mMyoVCr+dulAZg+PosassHjtb+xPL25wXnWNmaWfHcKswFUjejC1/7letfun9yMiwIszBZW8/lNyg+f+49vjlOprGBwVwM1j4+odC/Dy4L0FY4gL8SG9sIpb3t1j/YNNURTyyw3sTSviy/2ZvPTDCZb89wCKAvPOj+POKX3sDU2b9OruS0J0ICazwjeHshocf/H7JJJzywn11/HklYNd2jYhmtPNu+Os0m2X2aJZWVkkJSUxZcoUampqMJvNeHp6tvp6t9xyC5s3bwbgm2++afQcg8GAwXDuL8e6YeS65LMtzGYziqK0+TruaOPhLDKKqvDTaakymvjqwFkuHBBqrZ/lLK2N6d60Ir7an0VYgI7obt5Ed/MmppsP3f08rX8MZBRVsvFwDhuPZLM3rbje85/++hjBPh7MHtHDUS/FbXTm96mr1CV8Fw0Itcaxpbj+4+qhFFRUs+1kPgtW72HdonH15py9ufkkSTllBPt48MilA+pdx9dTw+NXDGTxh/tYtfUUlw+LsC5M+PVMEZ/+ZhkqfvLKQahQGpRxCfH14L1bR3Pdql0czy7jyje24+WhIb2wksrqhn9oXzIkgkcvG4iiKC7fKuqKhEgOZJTw5b5MbhodbY1pYmohb9f+0fnsVUMI9NbKe7gV5Pvf8cxms3VIN6/M0C6xteeeLk/4Pv30U+6//35UKhWpqakcOXKEZcuWNZmo2eL9998H4L333uPhhx9u9ForVqxg+fLlDR7Py8tDr29+qKMlZrOZkpISFEVBrXZ5p6lTrdxsqSV2/fBQ1Cp4e1cWj31xmN5+ZsL8W5+kt6Q1MU0v1rPg4+OUGRr+ItNpVEQE6NBqVJzKr6p3bGikL1Pju3G2xMCnB/J48LODaGqqGBsX4JDX4i468/vUFTKKDZzILUejhkHdsFYXsCWuy6dFc3dpJUdzKpnz9m7e+lN/Qv08OV1Qxeu1izr+Ojmamopicv8w3W54dxUTewey7XQJD32yj5XX9ceswCOfHQPgisEh9PAyNlntwAt46creLP7kBGcKzu1spALC/D3oEaijR6CO+FAfZg/pTkG+/fXwHGFspAcq4Le0YvafTMcXPZXVNdz/3yQUBS4fFMLQYKSqQyvJ97/jmc1m1NWWb9hyQw3pZ7PRNbG1oLOUlZXZfK7LE74VK1awd+9eLr74YgASEhI4c+aMQ649b948/vznP1NQUEBISP3JsMuWLWPJkiXWz0tLS4mJiSE0NJSAgLb9YjebzahUKkJDQzvVN9JvZ4o4nF2Bp0bFogsHEuTjQWJGJQcySvjHlrO8f+voesVXHcnemFZW1/Dof3ZRZjAxKNKfAREBZBRVkl5URXapHoNJ4UyRJbFXq2BMz2BmDolg+qBwIgK9au+pYFAO8L+DWfzt69P8546xDI4KdMrraw+d9X1qq52nCvh0r6VHTKNWoVWrUauw/KuGYB9Pbh4XSzefxv+Q2XDS0ss0pmcIfWPP9XDbGtf3bgvmulW7SC2o5IENqXy0cAz//OwUNWaFCweEctMF/ZuckvLstQHMeGUbB89WsCWtGoPRxMn8KgK9Pfj7rARCaufuNSUsDD7rHkJiahE9unkTE+xDjyAvdFpNs89zpbAwGNf7LDtPF7DzrJFrBwXxxq48MkoMRAZ68fS17l1fz9119e9/Z6jrXfPQpGE0Kah9AgkL8nZpG7y8vGw+1+UJn0ajaZCMtXY4t7i4mMrKSqKiLD98v/jiC0JCQggObjiZWqfTodM1/KGoVqsd8uZXqVQOu5a7ePeXVABmj+hBeKDlTfzyn4Zz6f9tY8epAt7flcaC2knpzmBrTBVFYdnnR0jKLiPUX8fqW8cQHnDum6C6xkxWSRUZRVWUVBkZ0yvYOrn999RqeOH6BAoqqtlxqoBb1/zG53eOb7J+WEfUGd+ntsgrM3DnR5YdH5rz+f6zrJ4/mp7dfRsc+/GYpefr4kHhDeJnS1xDA7z54LaxXPOvHSRllzHz1e3klRnw02l55qqhaDRNJ18xwb7cP70/T204yj++PU7daOtDM/sTGmDbL5j+kYH0j3TvP2Bmj4hi5+kC/ncwi57+sHa3pbbgP69NIMin+aRWtKyrfv87k1qtJsTXk+xSA0WVRmKCG/7scPb9beXyhM/f35+cnBzrX7I//vhjowmaLUpKSrjuuuuoqqpCrVYTGhrKhg0bZOGGA6QVVFor9S+c2Nv6eO9QPx65bBCPfXGYf2w8zsT47u2+hdE721P434GzaGvrhv0+2QPw1KqJC/ElLqTlb0SdVsPKuaO4fuVOjmeXccu7e/hs8XiCfZ03fC2cb/n/jlBSZWRAhD9Xj+xBjdky363uX6NZ4av9Z0nJr+CqN3/h37ecx+jf7YBQUmlkT6pls/uLB7auVAlATLAP7y0Yw/Urd1oLKi+9ZACRgS0nbfPOj+PzfRkczrTMPx4WHcgNo2Nb3RZ3NHNwJI99cYQTOeU8+o1lAdWccbFcEN+9nVsmRNNC/HRklxrcfqWuyxO+f/zjH1xyySWcPn2aCy64gJSUFL7++utWXSsuLo49e/Y4uIUC4N1fUjArMLlfaIPq9XPGxvLjsRy2JOVx73/288VdExpsmeQqO07ls+Lb4wA8dvmger+kW6tudePVb+4gJb+CBWsS+fj2cXh7us/wl7Ddj8dy2HAwC41axQvXJTCkR+O9XLdO6Mnt7/3KgYwSbn5rN/+8bph1F4gtJ3IxmRX6hfvZ9IdDcwZGBvDWvPNYvPY3RvcM5qYxtiVtWo2aFVcNY9Yb21GAJ2cNsW7R1VkE+ngwpX8o3x/NoURvIjbYm2WXNF/HT4j21t3P0iGQ5+a1+Fz+W3r06NFs3ryZjz/+mL/97W8cOXKE4cOHu7oZXVJ1jZk9KYVU1zS/qqek0mjdw3PhxIZDtiqViuevGUY3Hw+OZpXyyqYTTmlvS84WV3H3R/swmRWuHtmDW86Pa/lJNgoP8OK9BaMJ9PZgf3oxd3+0164tsgRUGGp4esNRfjqeY/dz0woqySyuavnEFpQbanj0C0spoYUTezWZ7AGE+XvxnzvOZ8bgcKpNZu79z35e/+kkiqKw6ZhlocAf985trXG9Q9j9t4tZNXeUXfNgh0YH8v6Csbx36xi7d8DoKOqSbBXw/DXD8JWtx4SbC/G1TDdw9x4+lyZ8iYmJ/OlPf2LChAk8+OCDvP/++yQnN6wtJZzj3V9SuH7VTua9u6fZPSs/2pNGZbWJARH+XNC38aGUsAAvVlw9FICVP58isXa4y1X0RhN/XvsbhRXVDI4K4Nmrhjp8KL9vmD/vzDsPnVbNj8dzWfj+r+S0ULxWnPP4V0d4e3sK9/5nP6V62wt2ZxZXMfPVrUz552brHx6t9c+Nx8kq0RMb7MN9F/Vr8XxvTw1v3jyK22v/0Hnh+xM8+OlBtiTVJnzN7K5hL0+tulXv2QviuzOpX6jD2uFupg8OZ975cTx8UWyLxa2FcAchtT187r69mssSvp07dzJ9+nR69+7N008/zVNPPUXv3r2ZPn06u3fvdlUzurRTuZat0XaeLmDO27sprmz410h1jZk1OyyrERdO7N3sL6SZQyK5ZmQ0ZgXu+Xify5IhRbHsHXowo4QgHw9WzhmFl4dzhlvP6xnMazeOwEOjYktSHtNe+plPf8tweY2yjubL/ZnWGnFl+ho+2Gn7SvyVW05RWW3CaFJ46NODPL3hKCaz/fH+7UwR7++y3HfF1UNtHpLXqFU8ctkgnpo9BLUKPv0tgzJ9Dd39PBkeHWR3O4R9PDRqHr9iELOHdt6kVnQudUO67r69mssSvueff553332XFStWMHv2bK666iqeffZZVq9ezYoVK1zVjC6t6Hfbou1PL+aGf+8it6x+kvb1obPklBoI89fZVFz5iSsH0TvUl6wSPbe9l0hlddM9h47y8Z501v2agVoFr904wumraKcPjmDDXyYytEcgpfoaHvjkAAvWJJJdIr19jUkrqOTRzy3DqCNigwB4d3sKVY0U+v2j7BI9/0209OrVvf/e3p7CwvcS7eoltOxecRBFgWtHRTOhiZ7q5swdF8c780fjW5soXjggzGlliIQQHZd1SNfNd9twWcJ35MgRrrrqqgaPz5o1i6NHj7qqGV1aSZXlzXjfxfGE+us4nl3G9St3klFkKcaqKApvbbX07s0b39OmhRj+Xh6smT+GYF9PDmeWcs/H+1vVG2OrvDIDz3xteb88MKM/E+Nd0wvQP8Kfz+8cz0Mz++OpUbM5KY9pL//MJ7+mS2/f7xhNZu75zz7KDDWcF9eNj28fR0ywNwUV1Xy8J63F56/8+RTVJjNjegbz6g3Def2mEXh5WOJ99Zs7OFNQ0eI1AP615RQnc8vp7ufJI5e2ftL/1P5hfHbneOaP78k9F8W3+jpCiM7LumijTHr4APDxaboXxtfXtXVruqq6Hr4xvYL59M/nE93Nm9SCSq5fuZNTeeXsPF3A0axSvD003DzW9nIPsSE+vHXLKDy1ajYdy+HZb461+BxDjYk1v6Tw38SWk4Dfe2XTCSqqTQyLDuTPk1y736dWo+bOKX35+p4LSIgJokxfw4OfHuTWNYl2LzDIKqni718e5s4Pf+O5jcf5b2Iau04XkFVS1WB7rI7k5R9OsD+9mAAvLa/cMBwvDw1/nmz5Ov1762kMNU338uWW6q1J4T0XxaNSqbh8WBSfLBpPeICO5NxyZr3xCztPFTTbhuTcMt7YbJkb/PgVg+nWxpI6AyICeOLKwUR36zz1GIUQjmOdw+fmPXwuW/5kMBg4dOhQo70hbd3aTNimuDbhC/L2JC7El0/+fD5z3t7NqbwKrl+5k+jaodHrzosmqIndBpoyKi6YF69L4C8f7+Od7SnEhfhwy/k9Gz13b1oRD396kJO1cwqDfDyZMTiixXuczCmzJgSPXDqw3YbX4sP9+ezP5/P29hRe+uEEW5LymPrCFm4ZF8edU/s2W7NPbzTx9rbTvLH5FFXGxpMfnVZNXIgPUweE8dCMAR2m9MaO5Hz+9bNlm7B/XDPMmiBdOyqa//vxJNmletbvzeTGJsqQWBJCMyNjg5jQ91xx9qHRgXx19wXc8b6lZMrcd3Zz70XxDI8NIqabD1FB3tbeaLNZYelnh6g2mblwQBiXD4t08qsWQnR1dUO6hRXVmM2K2079cFnCV1VVxZVXXtnoMSmU7HyKolgXaXTztWxPFBnozbpF53PLu3s4craUgopqVCpYMKF1u2dckRBFWmEl//wuiSe+OkJMN0vSUqfCUMML3yexZkcqigIeGhVGk8Ijnx9mbK/gFpPMFd8ex6zA9EHhjO0d0uy5zqbVqPnz5D5cPDCcR784xK7Tlg3e/5OYzsKJvVg4sTd+vysnoSgK3x3J4ZlvjpJeaOkNHBXXjZmDI0gvqiS1oJK0ggrSi6ow1Jg5kVPOiZxyPDVq7p/ev71eps0KK6q577/7URS4cUwMlw49l2jptBpun9ibp78+xr+2nOK6UdFoNfUHF/LKDKzdbVlgUde793vhAV78d9H5PPjpQf534Cwv/nCuFJBKBREBXkR388bLQ8OvZ4rw9dTw1Owh8rNFCOF0dX/km8wKxVVGty3U77KELzU11VW3Eo2oqDZRUztUGOR97s0Y4qfjo9vHcduaRH49U8T0QeGNbitlqzun9CElv4JPf8vg7o/28smfxzMoKoBtJ/NYtv4QGUWWZOfqkT14eOYAbn57N8m55Tz5v6O89KfhTV73l+R8fjqei1atYuklA1rdPkfrG+bHx7ePY+vJfJ7feJwjZ0t5ZdNJ3t95hrum9uXmsbGkF1ay/H9H2Z6cD1iSk2WXDuDKhKgGCYnRZOZscRWbjuXy1IajvPZTMiNju9VLnN2Noig89OkBcssM9An15bHLBzU456axsby55RRphZVsOJjF7BE96h1/e9tp9EYzCdGBTG6i5IiXh4b/u2E4Y3p246fjuWQUVZFeVIneaCarRE/W7xbRPDRzAD1cvKelEKJr8tSqCfT2oKTKSEG5QRI+0b6KaucW6LTqBuUpAr09+OC2sXx3JLvJX7a2UqlUPHvVUDKLqth5uoAFaxIZ3yeE9fsyAegR5M0zVw1hSn9LAvP8tcO49l87WL8vk8uGRXJRI4VtTWaFp7+2zAucMy6O3qF+bWqjo6lUKib3C2Vi3+58cziLF78/QUp+BU9tOMrKn09RWFGNyazgqVVzx8TeLJ7Sp8lish4ayzZwt13Qi9T8Cj7YdYb7/rufDX+5wKbVyBWGGjKKqugX7uey3q33d55h07FcPDVqXrtxJD6eDV+bj6eWBRN68sL3J3hjczJXJkRZhz0Kyg28v7Pp3r3fU6lUzD2/J3NrpwsoikJBRTXphZXWBNDXU8vccY4rwi2EEC3p7udJSZWRvHJDu2832hTZQbmLqJu/162JYVNvTw2zR/Ro8wR3sPy1s3LOKPqE+lrmbe3LRKWC+eN78t1fJ1mTPYCRsd247QLLEPLfPj/U6Ob26/dmcCyrFH8vrVuvlFSrLYsMvv/rJFZcPZSIAC/yygyYzArTB4Wz6a+TeWBGf5t3Dnj08oEkxARRUmXkzg/3om9izl+do2dLmfHKVma8spVJ/9zMP787TlJ2mSNeWqOqa8x8sDOVZ2oX6fzt0gEMigpo8vy55/fEX6flZG453x89t/vGO9tTqDKaGBwVwIV29mSqVCq6++kYEduNKxKiuHNKX+aN7+m2c2iEEJ1TiJ/777YhCV8XUVxbkiXIx8Ml9wv08WD1/DHEBHszIMKfT/98Pk9cObjevLY690/vT6/uvuSUGnh6Q/0SPVXVJl74PgmAu1tYEOEuPDRqbhwTy5YHp/DcNUP5+PZx/PuW84gNsW+Vp06r4Y2bRhDk48GhzBKe3NB0+aINB89yzb92WIfM0wureGPzKWa8spWZr2zlzS3J1vI7bVVjMrPu13SmvrCFx748QnWNmWmDwpk3vmezzwv09uCW8Zaetzc2J1vnlb63IxVouXdPCCHcVfcOsNuGDOl2EXUlWVyV8IGlXMvPD0xtsbfFy0PD89cO4/pVO/nktwwuGxbJpHhLody3t6eQU2ogupt3iwmFu/Hy0PCn0baXt2lMdDcfXvnTcG5dk8hHu9M4L64bV4+Mth43mRVe+D6Jf22xrI6dGN+df16bwK9nCvly/1l+TsrjeHYZxzcm8fzGJAaF+zAsNpfeob706u5Hr+4+xAT7oNO2vAuF2ayw4VAWr/xwgtP5lnp4Yf46/nJhX/40OtamZG3BhF68uz2VQ5klbD2Zz2+phVTUbuM3zUH71AohhKt1r+3hy3fjHr52SfjMZjPZ2dnU1JzblSE2tm2/GEXzSmpX6P5+wYYr2Dq0NrpnMPPH92T1L6ksW3+IjfdeQEGFkVVbTwPw8MwBTts+zd1N6R/GXy6M5/9+PMnfPj/EoKgABkQEUFJl5N7/7GNLUh4Aiyb15qGZljIulw+L4vJhUZRUGtl4JIsv95+11FnMqeRoTv2ePrXKkljGhfgQ4utJkI8nQT4eBHl7EOTjSaCPB2X6Gt7cnMzx2iHiYF9PFk/uw5xxcTZvWQaWYY8bx8Ty7i8pvPR9EqfzLInjPRfFyzCsEKLDOrfbhvTwWa1Zs4Z77rkHDw8P1GrLiLJKpSI3N9fVTelS6nr46kqyuKMHZ/Tnx2O5pBVW8o9vk6isqqKy2sTwmKAuX0/t3ovi2ZdWxLaT+Sxeu5cXr0/g/nUHSMmvwMtDzXPXDGPW8B4Nnhfo48GfRsfyp9GxZBVXsnFfCoXVGlILq0jJLyclr4KKahNphZWkFbY85OvvpeWOib259YJejQ7P2+KOSb1Zu+sMBzJKAIgP82OmDXUYhRDCXXX3r9ttQ3r4rJ566ikSExPp39/9a4t1JkV1PXx2FlR2JR9PLc9dM4wb39rFx4np1PX3PHrZwC4/t0ujVvHqDSO4/P+2kZJfwdVv7gAsq55XzR3FkB6BLV4jPMCLSwaGEBYWZv1jS1EU8soMnM6vIK2wkpJKI8VV1RRXGi0ftf/XG03MGBzBHZN6t/k9FBHoxTWjoq1FtP8ivXtCiA5Oevga0b17d0n22kGJdZcN9+3hAzi/Twhzx8Xxwa4zKMDMweGc1zO4vZvlFoJ9PXnj5pFcv2onRpPCuN7BvHHTSOvqsNZQqVSEBXgRFuDFOBcWs75zSh82HDxLr+6+XDa0a/feCiE6vnOLNqSHz2r27Nm88sor3HTTTXh5eVkfDwhoupyDaLu6Hr6myrK4k6WXDGDbyTxyy/Q8NFP+OPi9EbHdeH/BWE7llfOn0TF4aDrmQvuYYB+2P3whOq26w2wdJ4QQTTm3aEN6+KweeeQRAJYsWWJ9TKVSYTI1X2NMtE1xbX27QBeu0m0tX52Wr+6eQGZWDj1DWr/rR2d1fp8Qzu/TvlvLOUKgm/c2CyGErUJqe/gqq01UVtc0WoC+vbm8e8BsNjf4kGTP+VoqvOxu/HRaunWA5FQIIYTw02nRaS0plbsO67bbeNDZs2c5e/Zse92+yym2DulKEiWEEEI4Ut2uP+C+w7ouT/iOHTvG4MGDrR9Dhw7l+PHjrm5Gl2I2K9YtyzrCkK4QQgjR0YS4+cINlyd8d955J4888ghFRUUUFRXxyCOPsHjxYlc3o0sp1RsxK5b/u7rwshBCCNEVSA/fHxQVFXHTTTdZP7/hhhsoKipydTO6lLr5e76eGjy1HXNVpxBCCOHOQmr3ei+okB4+ADQaDUePntsE/ujRo2g0XXPLLFfpCEWXhRBCiI6su7979/C5fN3wihUrmDRpEsOGDQPg0KFDfPjhh65uRpdSV5IlSObvCSGEEE5R18OX76Zz+Fya8JlMJn788UeOHTvG7t27ARg3bhzdu3d3ZTO6nOIOVHRZCCGE6Ijq5vAVuGkPn0uHdDUaDZs3byY0NJTLL7+cyy+/XJI9FyiqkB4+IYQQwplk0cYfXHrppTzzzDNkZWVRWlpq/WgNvV7P7Nmz6devHwkJCUybNo3k5GQHt7jjkyFdIYQQwrmkLMsfPPnkkzz22GP06NGDbt26ERQURLdu3Vp9vTvuuIOkpCQOHDjArFmzWLhwoQNb2znIkK4QQgjhXHU9fIWV1ZjqaqG5kXbdWs1kMrVpazUvLy8uvfRSVCrL5uvjxo0jNTXVga3tHOrKssjepUIIIYRzdPPxQKUCRYFCNyzN4vJVuvn5+Q3m7TX2WGu8+uqrzJo1q9FjBoMBg+HcuHrdMHJd8tkWZrMZRVHafB1nsZZl8fZw2zb+kbvHtCOSmDqHxNXxJKaOJzF1vD/GVK2Cbt4eFFYaySvTE+Lr/E4We76eLk/4pk+fzt69e1t8zF7PPvssycnJ/Pjjj40eX7FiBcuXL2/weF5eHnq9vk33NpvNlJSUoCgKarX7FTbOK6kEQGWsJDc3t51bYxt3j2lHJDF1Domr40lMHU9i6niNxTTIW0NhpZFTGTkEq6uc3oaysjKbz3VZwlddXY1er8dkMlFWVoaiWMa3S0pKqKioaNO1X3jhBdavX8+mTZvw8fFp9Jxly5axZMkS6+elpaX8f3v3HhTVle8L/LtppEHl/VAUkAiCDwREMUQdE29OBF/xNXcKM5Mqo0mcjE6mJs7V0Ylx9CQxes+YpGbKipOasmbKVM7JaIwpzZw7pRKj0YpxOCGKSlRoAUVBni02r97r/tH0hhbEptm9e9P9/VRR6cd27dU/NuTHWmv/Vnx8PKKjoxESEjKg88uyDEmSEB0drcsfpOZ2W6HrMbFRiIlxfb2klvQe08GIMXUPxlV9jKn6GFP19RbTEaFlKK1tQYf/UMTExLi9D4GBgU4fq1nC132ELTQ0VHk9JCQE69evd7nd3bt34+OPP8axY8cQFhb20OOMRiOMRmOP1/38/FS5+CVJUq0ttdnX8EUMM+qyfw+j55gOVoypezCu6mNM1ceYqu/BmEYF2xKwuvvtmsS5P+fQ7Lu+detWyLKMNWvWONy40dDQgC1btrjUZmVlJdavX4+GhgbMmTMHmZmZePzxx1Xu+eDWbpVhbu0AwK3ViIiI3Klrtw391eLTfA3f/Pnz0dDQoIzG1dfX48yZM1iwYEG/24qLi1Omhql3jZ01+CSJd+kSERG5U5RSi09/CZ/m47pbtmxxmHoNCwtzeYSPHs0+nRsSOAQGP8nDvSEiIvJeXdur6a8si8cn8iVJcrkOHz2avegyd9kgIiJyr0gdb6+mecIXHByMM2fOKM+//vprBAcHa90Nn1F/376tGtfvERERuZN9SveuDkf4NF/Dt2vXLixduhTjx48HAFy9ehWHDh3Suhs+o6Fb0WUiIiJyn6huI3xCCGUnMD3QPOF74okncPnyZZw9exYAMGPGjD7LqdDA2NfwhXNKl4iIyK0iO0f4WjtkNLdZMdyoeZr1UB5Zw9fS0oKhQ4di/vz5GD58ONra9Df06S0aLPY1fJzSJSIicqehAf4YGmAAoL87dTVP+A4cOICcnBysXLkSAFBcXIwlS5Zo3Q2f0bWGjyN8RERE7hY5XJ+1+DRP+Hbs2IHCwkKEh9u2+MrIyMCNGze07obPsK/hC+cIHxERkdt1rePT1+yl5gmfwWBAZGSkw2sBAUxG3KWBI3xERESaiRymz1p8HinLcufOHeXOlePHjyMiIkLrbvgMlmUhIiLSTpROp3Q1v31k586dmDdvHkpLSzFr1iyUlZXh6NGjWnfDZzSyLAsREZFmunbb8PGEb9q0aSgoKMCZM2cghGBZFjerV8qycISPiIjI3SJ1WnxZs4SvqalJeSxJEmbOnOnwXkhIiFZdGRT+/cglfH3tLv7z5RyXp2Nb2q2wtNu2rQsbxhE+IiIid9Pr9mqaJXxhYWGQJAlCCABQ1vDZK1FzP90uQgh88m0FzK0dKCipxtIpcS6102ixje4Z/CQE66j4IxERkbeyr+GrbdbXCJ9mN23Isgyr1QpZlpXH9udM9hzVNrfB3NoBADhXVudyO/Xd1u/paXsXIiIibxWl0xE+zRK+4uJi5XFrq2MQTp48qVU3BgXT3Wbl8UASPntJllCWZCEiItKEPeFruN+Odqvs4d500Szhe/7555XHTzzxhMN7v/71r7XqxqBgqr2vPL5e0+zyXwksukxERKStsKAh8OucVKvT0bSuZgmffe3eg497e+7ruo/wAcB5k2ujfA3KHboc4SMiItKCn5+EiGH6m9bVLOHrvobswfVkXF/mqKzWlvAF+Nu+PefK6l1qx16SJTSII3xERERaUW7c0FFpFs1u3bRYLLhw4QKEEA6P7e9RlxudCV/epJH4vOgWvnV5hM8+pcsRPiIiIq3Y1vGZdTXCp2nC9+yzzyrPuz/mCF8XIQRMd21r+H4yLR6fF91C8a1GmFvaERzYv8SN++gSERFpz6dH+Ewmk1anGtTu3mvDvdYOSBIwLTEc8RFBqKizoLC8AU+mRPerLaUsC2/aICIi0sy4EcGYkhCmqwEXVuPVGft07qjQIAQOMWB6YiQq6irxbVldvxO+BgtH+IiIiLS2dk4y1s5J9nQ3HGh20wY5p6zzDt3HooYBAKY/Fg7AtXp8LMtCREREABM+3TF1jvCNiRwKAMhOjAAAfFfZgNaO/u1IUs81fERERAQPJXxVVVX48ssvAQAdHR1oa9PPokZPsxddto/wPRY1DFHDjWjrkPF9ZaPT7Qgh0KgkfBzhIyIi8mWaJ3wHDhxATk4OVq5cCcC25dqSJUu07oZu2YsuJ0baEj5Jklya1r3fZkVb55YuLMtCRETk2zRP+Hbs2IHCwkKEh9uSmIyMDNy4ccPl9l599VUkJiZCkiR89913KvXSM2wlWToTvqihyuv2ad3+JHz2GzYCDH4IGmJQsZdEREQ02Gie8BkMBkRGRjq8FhDg+pTjj3/8Y5w+fRpjxowZaNc87u69NjS3WeEnAfERXQnf9MdsCd+/btTDKju3DV19s70kyxDWOSQiIvJxmid8wcHBuHPnjpKEHD9+HBERES63N3v2bMTFxanVPY+y37AxKiwIRv+uUbnxI0MQbPTHvdYOXK5qcqqtrn10uX6PiIjI12leh++dd97BvHnzUFpailmzZqGsrAxHjx51+3lbW1vR2tq1xUlTky1xkmUZsiwPqG1ZliGEGHA7pTX3ANju0O3elgQga0w4Tv5Qg29KazExNviRbdU32z5raJD/gPvlCWrFlLowpu7BuKqPMVUfY6o+PcS0P+fWPOHLzs5GQUEBzpw5AyEEZsyYgbCwMLefd8eOHdi2bVuP12tqatDS0jKgtmVZRmNjI4QQ8PNzfdD0UnkNAGDEUD9UV1c7vDcpOgAnfwBOl1Rhwbihvf1zB+V3bOv9ggyiR1uDgVoxpS6MqXswrupjTNXHmKpPDzE1m81OH6tpwme1WrF582bs3LkT8+bN0/LU2LRpE1577TXleVNTE+Lj4xEdHY2QkJABtS3LMiRJQnR09IC+6TWWmwCACXGRiImJcXjvqbQh2PP1TXxfdR/R0dGPXJcn+9tGMEeED+/R1mCgVkypC2PqHoyr+hhT9TGm6tNDTAMDA50+VtOEz2AwoKCgQMtTKoxGI4xGY4/X/fz8VPlGSZI04La6avAN79FORnwYAvz9UNvcBlOdBUnRw/tsq8HSAQAIHxYwaH+41YgpOWJM3YNxVR9jqj7GVH2ejml/zqt5D+fPn4+33noLt27dQlNTk/LlqjVr1iAuLg6VlZXIzc1FcrK+9q5zlhBC2Uc3sbPocndGfwMy48MAAN86UZ6FN20QERGRneZr+LZv3w4A2LJli/KaJEmwWvu3bZjd3r17VemXp9Xca+1WkiWo12MefywC58rqcK6sDvnTE/psz76PblgQiy4TERH5Os0TPvsdJTdv2tarjR49Wusu6JLprm0698GSLN0pBZhNjx7hq7cnfBzhIyIi8nmaT+leuXIFaWlpmDx5svJVUlKidTd0x16D77FepnPtssaEw08CKustqGq09NmefaeNMG6rRkRE5PM0T/heeeUVbN68GXV1dairq8Pvfvc7/PznP9e6G7rz4B66vRlu9Efa6FAAj95mjWv4iIiIyE7zhK++vh7PPfec8jw/Px/19fVad0N37CN8YyL7rrHnzL66siy61vBxhI+IiMjneWQv3UuXLinPL126BIOh9zVrvsS+hq+vKV2gK+H7to91fObWDti33GXCR0RERJrftPH2229j9uzZSE9PBwBcuHABH330kdbd0BUhhDLC11tJlu6yE8MBAD/cuYf65jaED+s5ZWsf3RsaYHjoDSBERETkOzRP+HJzc3H58mV88803AICcnBxERUVp3Q1dqTG34r69JEt431O6kcONSI4ZjmvV93Dmei0WpMf2OMa+fo8lWYiIiAjQcEq3qakJJpMJABAdHY2FCxdi4cKFuHfv3oAKL3sD+w4bo8ODEOD/6G/J0xNsW6V9XnSz1/dZkoWIiIi60yzh27BhA/71r3/1eL2wsBAbN27Uqhu65Mwdut0tybTVLiy4UoPGztG87hpZkoWIiIi60SzhO3fuHJYvX97j9WXLluGrr77Sqhu6VFbbv4RvQmwIxo8MRptVxhcXq3q8X99sG+FjSRYiIiICNEz4Ojo6Ht4JH9/Iua89dB9mceco32f/03Nat/4+R/iIiIioi2aZVnt7e69r9RobG9He3nNa0peUKSVZ+r5ho7vFmaMAAN+U1eFmg+OuG5zSJSIiou40S/jy8/Px/PPPOxRZrq+vxwsvvID8/HytuqE7QghlhG+Mk1O6gG3P3Zyxtpp8h79zHOWz37TBKV0iIiICNEz4Xn/9dYSFhSE+Ph5TpkzBlClTEB8fj+DgYGzZskWrbuhOf0qyPGhJt2ldIYTyur0sSyjLshARERE0rMNnMBjw17/+FW+88QYKCwsBAFlZWUhKStKqC7pU1nmHblz4UKdKsnQ3b3Is3jhcjB/u3MPlKjMmjgoB0FV4mSN8REREBHig8HJSUpLPJ3ndObuHbm9Cg4bgf42PwX8X38bh7252JXyda/jCh3GEj4iIiDywly45shddftQeug+zZIptWvfwd7dg7dxA116WJTSII3xERETEhM/j+lt0+UFzxkcjJNAft5ta8E1ZLTqsMppabCVwwnmXLhEREcEDCV9LS0uP16qrq7Xuhm7Y1/Al9qMkS3dGf4Oyn+5n/3NTSfYA3rRBRERENponfPn5+Q53lNbV1SE3N1frbuiCrSSLbUrX1RE+oKsI8z8u3MbtRltCHRzoD38DB3CJiIjIAwlfamoqXn31VQCA2WzG/PnzsXbtWq27oQvV5lZY2q0w+EmI62dJlu6mJ0ZgVGggzK0d+LSwEgCLLhMREVEXzRO+nTt34u7du3jrrbewaNEirFixAi+++KLW3dAF+3Tu6LCgfpdk6c7PT8KznaN8/3W+AgBLshAREVEXzRK+pqYm5ev999/H4cOHkZOTgxdeeKHXLdd8gSt76D7M0s67dc2da/jCmPARERFRJ83q8IWFhUGSJAghlP+eP38eu3btgiRJsFqtWnVFN5Q9dF2owfeg1JHBmBAbgstVtuQ5jDdsEBERUSfNRvhkWYbVanX4r/3LF5M9oKskS3/20O3LksxRymOWZCEiIiI73sbpQfZdNlwtuvygZzNHQZJsj0M5pUtERESdNN9arbq6Glu3bkVRUZFDTT77/rq+4MrtJuz44gqu3DYDAJKih6vSbmxoEJ4YG4kz12sRGxqoSptEREQ0+Gk+wrd69WokJibi7t272LZtG0aNGoUFCxa43N7Vq1cxY8YMpKSkIDs7G8XFxSr2Vl23G1uw4UAR5r9/Cid/qMEQg4TXnklBggpr+Oz+7//OwP/JTVVu4iAiIiLSPOGrqKjAxo0bYTQasWjRInz66ac4duyYy+2tWbMGL7/8Mn744Qds3LgRK1euVK+zKjG3tOM//l8JnvqPAnxyvhKyABZMjsWx157Eq0+PU/Vco8OCsHZOMgKHGFRtl4iIiAYvzad0AwJsa8sCAwNRW1uL8PBw3L1716W2qqurcf78efzzn/8EACxfvhzr1q3DtWvXkJycrFqfXdVulfHxuXK8f+wqapvbAADZieHYPH8CpiSEe7h3RERE5Cs0T/hSUlJQW1uLn/3sZ3j88ccREhKCqVOnutRWRUUFYmNj4e9v+xiSJCEhIQHl5eU9Er7W1la0trYqz+21/+x3Cg+ELMsQQvRo52JlA944bJtiHhs1DBvzUvFvE2IgSdKAz+ntHhZTch1j6h6Mq/oYU/UxpurTQ0z7c27NE779+/cDAH71q19h2rRpqK+vR15entvPu2PHDmzbtq3H6zU1NQ43j7hClmU0NjZCCAE/v65Z8lgjsHRyFJKjhmJxWhT8DRJqamoGdC5f8bCYkusYU/dgXNXHmKqPMVWfHmJqNpudPlYSQgg39qVXVVVVKCkpwVNPPYWOjg7IsqxM9fZHdXU1kpOTUVdXB39/fwghEBsbi9OnTzs1whcfH4/6+nqEhIQM6PPIsoyamhpER0fzB0kljKn6GFP3YFzVx5iqjzFVnx5i2tTUhPDwcDQ2Nj4yl9F8hO/AgQNYv349JEmCyWRCcXExNm3ahC+++KLfbcXExCArKwv79+/HypUrcfDgQcTFxfW6fs9oNMJoNPZ43c/PT5VvlCRJqrVFNoyp+hhT92Bc1ceYqo8xVZ+nY9qf82rewx07dqCwsBDh4babFjIyMnDjxg2X29u7dy/27t2LlJQUvPPOO9i3b59aXSUiIiLyCpqP8BkMBkRGRjq85sp0rl1qairOnj070G4REREReS3NR/iCg4Nx584dSJ17gB0/fhwRERFad4OIiIjIZ2g+wrdz507MmzcPpaWlmDVrFsrKynD06FGtu0FERETkMzRN+C5evIjy8nJ8+OGHqK6uhhACM2bMQFhYmJbdAADYb0621+MbCFmWYTabERgYyMWwKmFM1ceYugfjqj7GVH2Mqfr0EFN7DuNMwRXNEr49e/Zg8+bNSE1NRUlJCfbt24elS5dqdfoe7LVr4uPjPdYHIiIiooEym80IDQ3t8xjN6vClpaXhiy++QEJCAi5cuIBXXnkFp0+f1uLUvZJlGbdu3UJwcLCyntBV9pp+FRUVA67pRzaMqfoYU/dgXNXHmKqPMVWfHmIqhIDZbMaoUaMeOcqo2QjfkCFDkJCQAACYPHkympubtTp1r/z8/BAXF6dqmyEhIfxBUhljqj7G1D0YV/UxpupjTNXn6Zg+amTPTrOEr6WlBRcuXFDmmR98np6erlVXiIiIiHyKZgmfxWLBs88+6/Ca/bkkSSgtLdWqK0REREQ+RbOEz2QyaXUqzRmNRmzdurXXrdvINYyp+hhT92Bc1ceYqo8xVd9gi6lmN20QERERkWewGA8RERGRl2PCR0REROTlmPD14erVq5gxYwZSUlKQnZ2N4uLiXo/7y1/+gnHjxiEpKQkvvfQS2tvbnXrPVw00rl9++SWCgoKQmZmpfFksFi0/gu44E1OTyYSnnnoKoaGhyMzM7PE+r1VHA40pr9OenInpiRMnMH36dEycOBGTJk3Chg0bIMuy8v6RI0cwfvx4jBs3DsuWLVNlt6TBbKAxNZlMMBgMDtfp9evXtf4YuuNMXM+ePavEbNKkSVizZg1aW1uV93X3O1XQQ82ZM0fs27dPCCHE3//+dzFt2rQex5SWlorY2FhRVVUlZFkWixYtEn/6058e+Z4vG2hcCwoKREZGhoY91j9nYlpbWytOnToljhw50iN+vFZ7GmhMeZ325ExMCwsLxfXr14UQQlgsFjFz5kzl35jNZhETEyMuX74shBBi7dq14je/+Y0mfdergca0rKxMhIaGatTbwcOZuDY3N4u2tjYhhBBWq1UsWbJE7N69Wwihz9+pTPge4s6dOyI4OFi0t7cLIYSQZVmMGDFCXL161eG4Xbt2iTVr1ijPjx49KmbOnPnI93yVGnHl/0gdORtTu97ix2vVkRox5XXqqL8xtVu7dq3YunWrEEKITz75ROTm5irvFRcXi9GjR7utz3qnRkyZ8PXkSlwtFovIzc0V7777rhBCn79TOaX7EBUVFYiNjYW/v61yjSRJSEhIQHl5ucNx5eXlGDNmjPI8MTFROaav93yVGnEFgOvXryMrKwvZ2dnYs2ePNp3XKWdj2hdeq47UiCnA67Q7V2J6+/ZtHDhwAAsXLgTQ+3VaVVWFjo4O93Zep9SIKQA0NzcjOzsbWVlZ2L59O6xWq9v7rmf9iavJZEJGRgaioqIQGhqKX/ziFwD0+TuVCR8NOllZWaisrERhYSEOHTqEDz74AJ988omnu0XkgNfpwDQ1NWHRokXYsGEDpk2b5unueIXeYhobG4ubN2/i22+/xbFjx3Dq1Cn84Q9/8HBPB4/ExEQUFRXh9u3baG1txaeffurpLj0UE76HiI+Pd/jLUQiB8vJyZT9gu4SEBNy4cUN5bjKZlGP6es9XqRHXkJAQZe/AuLg4rFixAqdOndLoE+iPszHtC69VR2rElNepo/7E1Gw2Iy8vD4sXL8Zrr72mvN7bddp9JMbXqBFTo9GImJgYAEBERARWrVrl09cp4NrP//Dhw5Gfn4+PPvoIgD5/pzLhe4iYmBhkZWVh//79AICDBw8iLi4OycnJDsctX74cn3/+OW7fvg0hBD744APk5+c/8j1fpUZcq6qqlDvMzGYzjhw5gilTpmj7QXTE2Zj2hdeqIzViyuvUkbMxvXfvHvLy8pCXl4fXX3/d4b28vDwUFhbiypUrAIA9e/bwOh1gTKurq5W7R+0jVL58nQLOx/XatWtK7Nra2nDo0CGkp6cD0OnvVM8sHRwcrly5InJycsS4cePE1KlTxffffy+EEGL16tXi8OHDynF//vOfxdixY8XYsWPFqlWrlLt2HvWerxpoXP/4xz+KiRMnivT0dDFx4kSxdetWIcuyRz6LXjgT0+bmZjF69GgRFRUlhgwZIkaPHi1++9vfKm3wWnU00JjyOu3JmZi++eabwt/fX2RkZChfb775ptLG4cOHRWpqqkhKShKLFy8WDQ0NHvksejHQmB48eFBMmjRJuU7XrVsnWlpaPPZ59MKZuO7du9chdr/85S+FxWJR2tDb71RurUZERETk5TilS0REROTlmPAREREReTkmfERERERejgkfERERkZdjwkdERETk5ZjwEREREXk5JnxEREREXo4JHxEREZGX880NCImIusnMzARg2x6ppKQEkydPBgCkpqYqXz/96U/ddv779+9j9uzZKCgoQHBwcK/HtLS0YObMmThx4oSyRy8RkbO40wYRUSeTyYTMzEw0NDRoet5du3ahtbUVW7Zs6fO49957D3V1ddi+fbtGPSMib8EpXSKiPqxcuRLvvfceAOD3v/89fvKTn2DRokVISUnBwoULcfHiReTm5iIlJQUrVqyALMsAALPZjJdeegnTp09Heno6Xn75ZbS1tfV6jr179+K5554DAMiyjHXr1mHChAnIyMjA1KlT0dLSAgDIz8/Hhx9+CP6dTkT9xYSPiKgfzp8/j7/97W8oKSmB2WzGiy++iAMHDuDSpUu4fPky/vGPfwAA1q9fjx/96Ec4d+4cioqKIMsy3n///R7tVVRUoLGxEUlJSQCAoqIiHD9+HMXFxSgqKsKJEycQEBAAABg5ciSCgoJQXFys3QcmIq/ANXxERP0wd+5chIeHAwCysrJgNBqVdXdTpkzB1atXAQCfffYZzp49i927dwMALBYLDAZDj/YqKysxYsQI5fnYsWPR0dGBVatWYc6cOViwYAH8/Lr+Nh85ciQqKyuRlpbmts9IRN6HCR8RUT8EBgYqjw0GQ4/nHR0dAAAhBA4ePIiUlJQ+2xs6dKgyZQsAoaGhuHjxIk6ePImCggJs2rQJX331FZKTkwHYbt4ICgpS8yMRkQ/glC4RkRssWbIEO3fuVBLA+vp6XLt2rcdxqampqK6uhsViAQDU1NSgubkZc+fOxdtvv43ExERcunQJAGC1WnH9+nXlLmIiImcx4SMicoN3330XQUFByMzMRHp6Op5++mmYTKYexwUGBmLu3Lk4ceIEANuavmeeeQbp6elIS0tDWloa5s2bBwA4ffo0srOzERERoeVHISIvwLIsREQedu7cOWzfvh1Hjhzp87j8/HysXr0azzzzjEY9IyJvwRE+IiIPmz59OpYtWwaz2fzQY1paWvDkk08y2SMil3CEj4iIiMjLcYSPiIiIyMsx4SMiIiLyckz4iIiIiLwcEz4iIiIiL8eEj4iIiMjLMeEjIiIi8nJM+IiIiIi8HBM+IiIiIi/3/wG42+/ehmNVMAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(2,1)\n", "ax1, ax2 = axes\n", "\n", "ax1.plot(dataset['time'], dataset['te_core'])\n", "ax1.set_xlabel('Time (s)')\n", "ax1.set_ylabel('Core Temperature (eV)')\n", "\n", "ax2.plot(dataset['time'], dataset['ne_core'])\n", "ax2.set_xlabel('Time (s)')\n", "ax2.set_ylabel('Peak Core Electron Density ($1 / m^3$)')\n", "\n", "for ax in axes:\n", " ax.grid(alpha=0.3)\n", "\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2D Thomson Profiles\n", "\n", "The dataset also includes 2D Thomson scattering profles as a function of time and angle/distance." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, (ax1, ax2) = plt.subplots(2, 1)\n", "dataset = catalog.level1.sources(url=url)\n", "dataset = dataset.to_dask()\n", "\n", "tmax = dataset['te_core'].dropna(dim='time').time.max()\n", "\n", "ds = dataset.copy()\n", "\n", "te = ds['te']\n", "te = te.sel(time=te.time <= tmax)\n", "te = te.fillna(0)\n", "te.plot.imshow(ax=ax1, vmax=1000)\n", "ax1.set_title('Temperature ($T_e$)')\n", "\n", "ne = ds['ne']\n", "ne = ne.sel(time=ne.time <= tmax)\n", "ne = ne.fillna(0)\n", "ne.plot.imshow(ax=ax2, vmax=1e20)\n", "ax2.set_title('Density ($n_e$)')\n", "\n", "ax1.grid(False)\n", "ax2.grid(False)\n", "plt.tight_layout()" ] } ], "metadata": { "colab": { "provenance": [] }, "kernelspec": { "display_name": "mast-book", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.9" } }, "nbformat": 4, "nbformat_minor": 0 }