| \n", - " | Raman_shift (cm-1) | \n", - "Intensity | \n", - "Ne emission line in air | \n", - "
|---|---|---|---|
| 1 | \n", - "818.699523 | \n", - "5000.0 | \n", - "556.27662 | \n", - "
| 9 | \n", - "1117.086987 | \n", - "5000.0 | \n", - "565.66588 | \n", - "
| 16 | \n", - "1310.480205 | \n", - "5000.0 | \n", - "571.92248 | \n", - "
| 19 | \n", - "1398.915133 | \n", - "5000.0 | \n", - "574.82985 | \n", - "
| 23 | \n", - "1447.564622 | \n", - "7000.0 | \n", - "576.44188 | \n", - "
| \n", - " | Ne_Split | \n", - "Line_1 | \n", - "Line_2 | \n", - "Entered Pos Line 1 | \n", - "Entered Pos Line 2 | \n", - "
|---|---|---|---|---|---|
| 0 | \n", - "330.477634 | \n", - "1117.086987 | \n", - "1447.564622 | \n", - "1117 | \n", - "1447 | \n", - "
| \n", - " | Peak1_cent | \n", - "Peak1_height | \n", - "Peak2_cent | \n", - "Peak2_height | \n", - "Peak1_prom | \n", - "Peak2_prom | \n", - "
|---|---|---|---|---|---|---|
| 0 | \n", - "1116.16583 | \n", - "4342.0 | \n", - "1447.663174 | \n", - "44409.66797 | \n", - "3644.03335 | \n", - "43711.70132 | \n", - "
| \n", - " | filename | \n", - "1σ_Ne_Corr_test | \n", - "1σ_Ne_Corr | \n", - "pk2_peak_cent | \n", - "pk2_amplitude | \n", - "pk2_sigma | \n", - "pk2_gamma | \n", - "error_pk2 | \n", - "Peak2_Prop_Lor | \n", - "pk1_peak_cent | \n", - "... | \n", - "pk1_gamma | \n", - "error_pk1 | \n", - "Peak1_Prop_Lor | \n", - "deltaNe | \n", - "Ne_Corr | \n", - "Ne_Corr_min | \n", - "Ne_Corr_max | \n", - "residual_pk2 | \n", - "residual_pk1 | \n", - "residual_pk1+pk2 | \n", - "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", - "Ne3.txt | \n", - "0.000039 | \n", - "0.000039 | \n", - "1447.521963 | \n", - "46080.553118 | \n", - "0.389636 | \n", - "None | \n", - "0.00243 | \n", - "0.403724 | \n", - "1116.318852 | \n", - "... | \n", - "None | \n", - "0.012707 | \n", - "0.264314 | \n", - "331.20311 | \n", - "0.99781 | \n", - "0.997764 | \n", - "0.997855 | \n", - "109.333101 | \n", - "11.072854 | \n", - "120.405955 | \n", - "
1 rows × 22 columns
\n", - "| \n", - " | filename | \n", - "date | \n", - "Month | \n", - "Day | \n", - "power (mW) | \n", - "Int_time (s) | \n", - "accumulations | \n", - "Mag (X) | \n", - "duration | \n", - "24hr_time | \n", - "sec since midnight | \n", - "Spectral Center | \n", - "
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", - "Ne1.txt | \n", - "October 28, 2022\\n | \n", - "October | \n", - "28.0 | \n", - "11.978 | \n", - "45.0 | \n", - "3.0 | \n", - "50.0 | \n", - "['0h', '2m', '16s'] | \n", - "11:58:18 AM\\n | \n", - "43098.0 | \n", - "1325.004 | \n", - "
| 1 | \n", - "Ne2.txt | \n", - "October 28, 2022\\n | \n", - "October | \n", - "28.0 | \n", - "12.080 | \n", - "45.0 | \n", - "3.0 | \n", - "50.0 | \n", - "['0h', '2m', '16s'] | \n", - "12:25:51 PM\\n | \n", - "44751.0 | \n", - "1325.004 | \n", - "
| 2 | \n", - "Ne3.txt | \n", - "October 28, 2022\\n | \n", - "October | \n", - "28.0 | \n", - "19.977 | \n", - "45.0 | \n", - "3.0 | \n", - "50.0 | \n", - "['0h', '2m', '17s'] | \n", - "1:02:56 PM\\n | \n", - "46976.0 | \n", - "1325.004 | \n", - "
| 3 | \n", - "Ne4.txt | \n", - "October 28, 2022\\n | \n", - "October | \n", - "28.0 | \n", - "12.044 | \n", - "45.0 | \n", - "3.0 | \n", - "50.0 | \n", - "['0h', '2m', '16s'] | \n", - "1:34:44 PM\\n | \n", - "48884.0 | \n", - "1325.004 | \n", - "
| 4 | \n", - "Ne5.txt | \n", - "October 28, 2022\\n | \n", - "October | \n", - "28.0 | \n", - "19.988 | \n", - "45.0 | \n", - "3.0 | \n", - "50.0 | \n", - "['0h', '2m', '17s'] | \n", - "2:06:40 PM\\n | \n", - "50800.0 | \n", - "1325.004 | \n", - "
| \n", - " | filename | \n", - "approx_split | \n", - "Diad1_pos | \n", - "Diad2_pos | \n", - "HB1_pos | \n", - "HB2_pos | \n", - "C13_pos | \n", - "Diad1_abs_prom | \n", - "Diad2_abs_prom | \n", - "HB1_abs_prom | \n", - "... | \n", - "HB2_height | \n", - "C13_height | \n", - "Diad1_height | \n", - "HB1_height | \n", - "Diad1_Median_Bck | \n", - "Diad2_Median_Bck | \n", - "C13_HB2_abs_prom_ratio | \n", - "Diad2_HB2_Valley_prom | \n", - "HB1_prom/std_betweendiads | \n", - "HB2_prom/std_betweendiads | \n", - "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 17 | \n", - "K21-59-FI#1.txt | \n", - "102.996817 | \n", - "1286.096281 | \n", - "1389.093098 | \n", - "1265.593711 | \n", - "1410.338117 | \n", - "1370.619887 | \n", - "564.1425 | \n", - "970.145627 | \n", - "40.470333 | \n", - "... | \n", - "824.31078 | \n", - "751.73073 | \n", - "1308.442488 | \n", - "789.070308 | \n", - "744.299988 | \n", - "737.849991 | \n", - "7.244931 | \n", - "0.988121 | \n", - "14.80359 | \n", - "32.412829 | \n", - "
1 rows × 39 columns
\n", - "| \n", - " | filename | \n", - "approx_split | \n", - "Diad1_pos | \n", - "Diad2_pos | \n", - "HB1_pos | \n", - "HB2_pos | \n", - "C13_pos | \n", - "Diad1_abs_prom | \n", - "Diad2_abs_prom | \n", - "HB1_abs_prom | \n", - "... | \n", - "HB2_height | \n", - "C13_height | \n", - "Diad1_height | \n", - "HB1_height | \n", - "Diad1_Median_Bck | \n", - "Diad2_Median_Bck | \n", - "C13_HB2_abs_prom_ratio | \n", - "Diad2_HB2_Valley_prom | \n", - "HB1_prom/std_betweendiads | \n", - "HB2_prom/std_betweendiads | \n", - "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", - "K21-59-FI#1.txt | \n", - "102.996817 | \n", - "1286.096281 | \n", - "1389.093098 | \n", - "1265.593711 | \n", - "1410.338117 | \n", - "1370.619887 | \n", - "564.142500 | \n", - "970.145627 | \n", - "40.470333 | \n", - "... | \n", - "824.310780 | \n", - "751.730730 | \n", - "1308.442488 | \n", - "789.070308 | \n", - "744.299988 | \n", - "737.849991 | \n", - "7.244931 | \n", - "0.988121 | \n", - "14.803590 | \n", - "32.412829 | \n", - "
| 1 | \n", - "K21-59-FI#2.txt | \n", - "102.958320 | \n", - "1286.162277 | \n", - "1389.120596 | \n", - "1265.940187 | \n", - "1410.431610 | \n", - "1372.429260 | \n", - "227.209893 | \n", - "364.861100 | \n", - "13.978213 | \n", - "... | \n", - "862.498117 | \n", - "823.866439 | \n", - "1048.409905 | \n", - "840.978213 | \n", - "821.200012 | \n", - "813.000000 | \n", - "4.410694 | \n", - "0.997159 | \n", - "3.877687 | \n", - "14.397028 | \n", - "
| 2 | \n", - "K21-59-FI#3.txt | \n", - "102.980318 | \n", - "1286.123779 | \n", - "1389.104097 | \n", - "1265.654207 | \n", - "1410.426110 | \n", - "1370.608887 | \n", - "556.510975 | \n", - "886.185692 | \n", - "48.552072 | \n", - "... | \n", - "809.430077 | \n", - "736.981367 | \n", - "1281.710987 | \n", - "773.552072 | \n", - "725.200012 | \n", - "726.550003 | \n", - "6.548169 | \n", - "0.992287 | \n", - "21.914986 | \n", - "36.890576 | \n", - "
| 3 | \n", - "K21-61-FI#1-rep1.txt | \n", - "103.282797 | \n", - "1285.397830 | \n", - "1388.680627 | \n", - "1265.593711 | \n", - "1410.228124 | \n", - "NaN | \n", - "62.207973 | \n", - "119.120630 | \n", - "-2.297127 | \n", - "... | \n", - "746.493404 | \n", - "NaN | \n", - "807.307979 | \n", - "750.902885 | \n", - "745.100006 | \n", - "734.800003 | \n", - "NaN | \n", - "0.995087 | \n", - "-0.988985 | \n", - "5.981546 | \n", - "
| 4 | \n", - "K21-61-FI#1-rep2.txt | \n", - "103.205802 | \n", - "1285.485824 | \n", - "1388.691626 | \n", - "1265.390225 | \n", - "1410.134631 | \n", - "1370.498895 | \n", - "582.752855 | \n", - "1066.388011 | \n", - "41.550324 | \n", - "... | \n", - "783.061222 | \n", - "717.015013 | \n", - "1287.752855 | \n", - "747.750336 | \n", - "705.000000 | \n", - "699.550003 | \n", - "5.806225 | \n", - "0.996421 | \n", - "19.469849 | \n", - "41.123563 | \n", - "
5 rows × 39 columns
\n", - "" - ], - "text/plain": [ - " filename approx_split Diad1_pos Diad2_pos HB1_pos \\\n", - "0 K21-59-FI#1.txt 102.996817 1286.096281 1389.093098 1265.593711 \n", - "1 K21-59-FI#2.txt 102.958320 1286.162277 1389.120596 1265.940187 \n", - "2 K21-59-FI#3.txt 102.980318 1286.123779 1389.104097 1265.654207 \n", - "3 K21-61-FI#1-rep1.txt 103.282797 1285.397830 1388.680627 1265.593711 \n", - "4 K21-61-FI#1-rep2.txt 103.205802 1285.485824 1388.691626 1265.390225 \n", - "\n", - " HB2_pos C13_pos Diad1_abs_prom Diad2_abs_prom HB1_abs_prom \\\n", - "0 1410.338117 1370.619887 564.142500 970.145627 40.470333 \n", - "1 1410.431610 1372.429260 227.209893 364.861100 13.978213 \n", - "2 1410.426110 1370.608887 556.510975 886.185692 48.552072 \n", - "3 1410.228124 NaN 62.207973 119.120630 -2.297127 \n", - "4 1410.134631 1370.498895 582.752855 1066.388011 41.550324 \n", - "\n", - " ... HB2_height C13_height Diad1_height HB1_height Diad1_Median_Bck \\\n", - "0 ... 824.310780 751.730730 1308.442488 789.070308 744.299988 \n", - "1 ... 862.498117 823.866439 1048.409905 840.978213 821.200012 \n", - "2 ... 809.430077 736.981367 1281.710987 773.552072 725.200012 \n", - "3 ... 746.493404 NaN 807.307979 750.902885 745.100006 \n", - "4 ... 783.061222 717.015013 1287.752855 747.750336 705.000000 \n", - "\n", - " Diad2_Median_Bck C13_HB2_abs_prom_ratio Diad2_HB2_Valley_prom \\\n", - "0 737.849991 7.244931 0.988121 \n", - "1 813.000000 4.410694 0.997159 \n", - "2 726.550003 6.548169 0.992287 \n", - "3 734.800003 NaN 0.995087 \n", - "4 699.550003 5.806225 0.996421 \n", - "\n", - " HB1_prom/std_betweendiads HB2_prom/std_betweendiads \n", - "0 14.803590 32.412829 \n", - "1 3.877687 14.397028 \n", - "2 21.914986 36.890576 \n", - "3 -0.988985 5.981546 \n", - "4 19.469849 41.123563 \n", - "\n", - "[5 rows x 39 columns]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "fit_params, data_y_all=pf.loop_approx_diad_fits(spectra_path=spectra_path, config=diad_id_config, \n", - " Diad_Files=Diad_Files, filetype=filetype, plot_figure=False)\n", - "fit_params.head()" - ] - }, - { - "cell_type": "markdown", - "id": "f09618b7-f567-4789-8f4f-9446eced48d1", - "metadata": {}, - "source": [ - "## Filter out spectra with Cosmic rays" - ] - }, - { - "cell_type": "markdown", - "id": "76576d6a-3b75-4a37-a612-77cf5b012c16", - "metadata": {}, - "source": [ - "### Pick a spectra to tweak first" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "d43d4bea-0ddb-4851-9125-30dec44f7b4d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "K21-61-FI#2.txt\n" - ] - }, - { - "data": { - "image/png": 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p8qZAQuqcgoICJCUlaXz5YYB/Nqq3ZW8AwJNHTzTeUlQ3xhi4rVv5N8bGQFKSdgtEqqxhw4aws7Or1b9FCiSkTmGMITU1FQYGBnB0dIRIpNlnbpVMiX9y/wEAWJtZQ8TpxOQR1caUDFxuLr9tZg6u1EPDRHcxxpCbm4v09HQAgH0tDtenQKLH8vPzhTVVfv75Z5iYmGgub4UCQffu8Xm3bQsTHbnZLpfLkZubCwcHB43PiAzwgcRQzv9bmZiY1I1AUrwtEoHT4N8YqTlTU1MA/JRRNjY2tdbNpd9/5fWcQqHA77//jt9//10rU6T8/vw5fn/+XKemSCn+OWj6SX9CdFXxF6rCwsJay4NaJHrMyMhIeDpfG1OkbG7VStjWNfp+b4IQddHE/wIFEj0mFosxdepU7eQtEmFq06ZayZsQoluoa4sQUmtcXFywadMmbReD1DIKJHpMqVQKS+1qeqirkjEk5uYiMTcXSpquTS0mTJgAjuMwZcqUMsc++eQTcByntUk6qysmJgaTJ08W3nMch0OHDmmvQKRWUCDRY3l5eWjdujVat26NvLw8zeatVKL1lStofeUK8rTwvEZd5ejoiNDQUJXfZ35+Pn755Rc4OTlpsWQAUPUvDE2aNNHK6DmiWRRI9FzxmvJaydvAABIdGfb7Ojk5OcjJyUHJya4LCgqQk5MDmUxWbtqSrbzCwkLk5OSUWYmyorTV5eHhAScnJxw4cEDYd+DAATg6OgrzqgFAWFgY3nzzTTRs2BCNGzeGv78/Hjx4oHKuS5cuoXPnzjAxMUG3bt1w6NAhcByHuLg4AMC5c+fAcRzOnDmDbt26wczMDL169UJCQoLKeY7++Se6BgXB1N0dzZs3x4oVKyCXy4Xjy5cvh5OTE4yNjeHg4IAZM2YIx0p2bbm4uAAA3nnnHXAcJ7wHgKNHj6Jr164wMTEpNw+i2yiQ6DFzc3NkZmYiMzNToxM2AoC5gQEyvbyQqScTNlpYWMDCwgL//POPsO+rr76ChYUFpk2bppLWxsYGFhYWSE5OFvZt2bIFFhYWmDRpkkpaFxcXWFhYID4+Xti3P2R/jcr6wQcfCAuWAcDOnTsxceJElTQ5OTn49NNPERMTgzNnzkAkEuGdd94RAtrLly8xZMgQdOzYEdeuXcPKlSsxf/78cvNbvHgxNmzYgKtXr8LQ0FAlrz/++APjli7FjNGjcefYMWzbtg27d+/Gl19+CQD4/fffsXHjRmzbtg2JiYk4dOgQOnbsWG4+MTExAPj1hlJTU4X3f/zxB8aNG4cZM2bg7t27ZfIguo9GbRGiY4KCgrBw4UI8fPgQHMfh4sWLCA0Nxblz54Q0I0aMUPnMjh07YGNjg7t378LNzQ0hISHgOA7bt2+HiYkJ2rdvj5SUFAQHB5fJ78svv0SfPn0AAAsWLMDgwYORn58PExMTrF6zGgvGj8d4f38wCwu0aNsWK1euxGeffYZly5YhOTkZdnZ26N+/P8RiMZycnPDGG2+UW68mTZoA+N+UHSXzX7BgAcaPHw8AaN68uUoeRPdRICH1QnbR2ikl++vnzZuHWbNmwdBQ9d+geEqJ4qeCAX5Z6ODg4DJPBj98+LBM2lGBo2pUVmtrawwePBg//fQTGGMYPHgwrK2tVdI8ePAAS5YsQXR0NP755x+hJZKcnAw3NzckJCSgU6dOKrMdVHSB79Spk7BdPI1Geno6nJycEBsbi5grV/Dlrl0AxwEcB4VCgfz8fOTm5mLkyJHYtGkTmjdvDj8/PwwaNAhDhgwp8zN9ldjYWMTExKi0QErmQfdYdB8FEj0mk8nw0UcfAQC2bdsGY2NjzeWtVOKjor70bW3awFjDc1pVVXldf0ZGRuU+yFleWrFYDLFYXOm0NTVx4kShy23Lli1ljg8ZMgSOjo7Yvn07HBwcoFQq4ebmJsx4zBgr8yBaRYuhlixv8WeKA5NSqcSKyZMxvG9fMDMzcC1aCGlNTEzg6OiIhIQEhIeH4/Tp0/jkk0/w1Vdf4fz585X+OSiVSqxYsQLDhw8vc0yT0/6Q6qNAosfkcjl++uknAPzFRpOBRM4Yfnr2jM+7dWtoLuf6wc/PTwgKvr6+KsdevHiB+Ph4bNu2DV5eXgCACxcuqKRp27YtQkJCIJPJhL+Lq1evVrkcHh4eSHj0CC0dHcEsLMC1bFkmjampKQICAhAQEICpU6eibdu2uHXrFjw8PMqkFYvFZabz8fDwQEJCAlqWc26iHyiQ6DGxWIx169YJ2xrNm+OwrnlzYZuol4GBgXADv3R3mpWVFRo3bowffvgB9vb2SE5OxoIFC1TSjB07FosXL8bkyZOxYMECJCcnY/369QCqNmXGks+XYMgQfzja2uLdIUNgwBhu3ryJW7duYdWqVdi9ezcUCgV69OgBMzMz/PzzzzA1NYVz0Rompbm4uODMmTPo3bs3jI2NYWVlhaVLl8Lf3x+Ojo4YOXIkRCKRSh5E9+l2fwR5JSMjI8ybNw/z5s3T/FxbIhHmOTlhnpMTjHS8W0tfNWjQAA0aNCizXyQSITQ0FLGxsXBzc8Ps2bPx1Vdflfns0aNHERcXh86dO2Px4sVYunQpgKp1F/n6+uLYxo0Iv3wZb4wahZ49e+Lrr78WAkXDhg2xfft29O7dG506dcKZM2dw9OhRNG7cuNzzbdiwAeHh4SrDmX19fXHs2DGEh4eje/fuZfIgeoBp0fnz55m/vz+zt7dnANjBgwdVjoN/AqrMa926dUKaPn36lDk+evRolfP8+++/bNy4caxBgwasQYMGbNy4cSwjI6NKZZVKpQwAk0ql1a2uXpDL5SwiIoJFREQwuVyu7eJUWV5eHrt79y7Ly8vTSv4KpYKlZKWwlKwUplAqtFKGiuzdu5eJxWKWm5tb6c8oFUrGYmIYi4lhyvj4WiwdqS2v+p9Q13VNq11bOTk5cHd3xwcffFBmOCMApKamqrw/efIkJk2aVCZtcHAwvvjiC+F9yRE0AN/Mf/LkCcLCwgAAkydPRlBQEI4ePaquqmiFUqkUfkb29vYaXcRJyRhSi/rw7Y2MIKLuLZ2zZ88eNG/eHE2bNsWNGzcwf/58jBo1qsz/ByE1pdVAMnDgQAwcOLDC4yXHmgPA4cOH0bdvXzQv6psvZmZmViZtsfj4eISFhSE6Oho9evQAAGzfvh2enp5ISEhAmzZtalgL7cnLy0OzZs0A8MNbNflQYp5SiWZRUXzeevJQYn2TlpaGpUuXIi0tDfb29hg5ciQ95Edqhd50bj979gzHjx8v82QxAISEhMDa2hodOnTA3Llz8fLlS+FYVFQUJBKJEEQAoGfPnpBIJLh06VKF+clkMmRlZam8dJGhoWGVxuyrNW+OgyG1RHTWZ599hocPHyI/Px9JSUnYuHEjPZNBaoXejNr66aefYGlpWWaseWBgIFxdXWFnZ4fbt29j4cKFuHHjBsLDwwHw38psbGzKnM/GxgZpaWkV5rdmzRqsWLFCvZVQM3Nz81pd9eyVeRsYoLDoaWhCSP2mN4Fk586dCAwMLDPipOSUD25ubmjVqhW6deuGa9euCePYyxvuyMp5YKukhQsX4tNPPxXeZ2VlwdHRsabVIISQOkcvAklkZCQSEhLw66+/vjath4cHxGIxEhMT4eHhATs7OzwrenCupOfPn8PW1rbC8xgbG2v0AT9CCNFXenGPZMeOHejatSvc3d1fm/bOnTsoLCwU5gzy9PSEVCrFlStXhDSXL1+GVCpFr169aq3MmiCTyTB16lRMnTq1zFTotZ63Uomp9+9j6v37kNF6JITUa1ptkWRnZ+Ovv/4S3iclJSEuLg6NGjUSFvHJysrCb7/9hg0bNpT5/IMHDxASEoJBgwbB2toad+/exZw5c9ClSxf07t0bANCuXTv4+fkhODgY27ZtA8AP//X399frEVsAP0XK999/DwBYt26dxqdI+f7pUz7vFi1oihRC6jGtBpKrV6+ib9++wvviexLjx4/H7t27AQChoaFgjOG9994r83kjIyOcOXMG33zzDbKzs+Ho6IjBgwdj2bJlKtNKhISEYMaMGfDx8QEABAQEYPPmzbVYM80Qi8XCNNvamCJlWdGTxzRFCiH1XI0eZ6xH6Ml2/VCfn2xftmwZc3d3V+s5lQolWxYczNxbtXrtk+3Ozs5s48aNas1f3yQlJTEA7Pr168K+CxcuMDc3N2ZoaMiGDh2q8TJp4sn2at0jmTBhAv7880+1BjRCCL88roGBAfz8/LRdlCqLiYnB5MmThfccx+HQoUPVPp+rqyvCwsKEJYGtrKzKLHV85coVcBxXpYkoK5KTk4P58+ejefPmMDExQZMmTeDt7Y1jx47V6LyffvopOnfujKSkJKGn5XUmTJiAYcOG1ShfTapWIHn58iV8fHzQqlUrrF69GikpKeouF6kExpiw1C6rYK2JWs27sBCZhYUaz7su27lzJ6ZPn44LFy6oLPWry4qnu2/SpInaHni8efMmXrx4odL1bWlpiYMHD6qk27lzp3A/taamTJmCQ4cOYfPmzbh37x7CwsIwYsQIvHjxokbnffDgAfr164dmzZqhYcOGaimrrqlWIPnvf/+LlJQUTJs2Db/99htcXFwwcOBA/P7771p7QK4+ys3NhZWVFaysrJCbm6vZvJVKWF28CKuLF5Grw6O2GGNQKBRaeVU1wObk5GD//v34+OOP4e/vr/Lttfhb+ZkzZ9CtWzeYmZmhV69eSChaXKykn3/+GS4uLpBIJBgzZoww08OePXvQuHHjMiP8RowYgffff194v3btWtja2sLS0hKTPpyE/FLpi78tr1mzBg4ODmjdujUAfor4TZs2CdsA8M4774DjOOE9ABw9ehRdu3aFiYkJmjdvjhUrVkAul6vkcfjwYfj6+qoMIBk/fjx27twpvM/Ly0NoaKiwRG9J27dvh6OjI8zMzPDOO+/g66+/fu1F/OjRo1i0aBEGDRoEFxcXdO3aFdOnT1c5f3mtrIYNG5bb0iheKvnFixeYOHEiOI4Tpt2fNGkSXF1dYWpqijZt2uCbb74RPrd8+XL89NNPOHz4sNDaKl5mOSUlBaNHjxaWEhg6dKiwSqc2Vftme+PGjTFz5kzMnDkT169fx86dOxEUFAQLCwuMGzcOn3zyCVq1aqXOshJSZUqlEpGRkRrLjzGG7AJ+WV+7t+1gIKr8HGS//vor2rRpgzZt2mDcuHGYPn06lixZotJts3jxYmzYsAFNmjTBlClTMHHiRFy8eFE4/uDBAxw6dAjHjh1DRkYGRo0ahbVr1+LLL7/EyJEjMWPGDBw5cgQjR44EAPzzzz84duyYMKHp/v37sWzZMmzZsgVeXl7Ys2cPvvvmGzR3cFAp65kzZ9CgQQOEh4eXGzBjYmJgY2ODXbt2wc/PTxj88scff2DcuHH49ttv4eXlhQcPHgjdYSXXZz9y5Ahmzpypcs6goCB89dVXSE5OhpOTE/773//CxcWlzAJaFy9exJQpU/Cf//wHAQEBOH36NJYsWfLan7+dnR1OnDiB4cOHw9LS8rXpX8fR0RGpqalo06YNvvjiC4wePRoSiQRKpRLNmjXD/v37YW1tjUuXLmHy5Mmwt7fHqFGjMHfuXMTHxyMrKwu7du0CADRq1Ai5ubno27cvvLy88Oeff8LQ0BCrVq2Cn58fbt68qfGlJEqq8XMkqampOHXqFE6dOgUDAwMMGjQId+7cQfv27bFx40Z1lJFUwMzMDAUFBSgoKND4HEpmIhEK3noLBW+9BTNaj0QtduzYgXHjxgHgV0jMzs7GmTNnVNJ8+eWX6NOnD9q3b48FCxbg0qVLKvcNlEoldu/eDTc3N3h5eSEoKEg4h6mpKcaOHStcnAB+RGOzZs3g7e0NANi0aRMmTpyIDz/8EG3atMGqlavQ3tW1TFnNzc3x448/okOHDnBzcytzvEmTJgD4b+t2dnbC+y+//BILFizA+PHj0bx5cwwYMAArV64UhuYD/LfuGzduYNCgQSrntLGxwcCBA4Vv/zt37sTEiRPL5P3dd99h4MCBmDt3Llq3bo1PPvnklZPDFvvhhx9w6dIlNG7cGN27d8fs2bNVgnRVGRgYwM7ODhzHQSKRwM7ODqamphCLxVixYgW6d+8OV1dXBAYGYsKECdi/fz8AwMLCAqampjA2NoadnR3s7OxgZGSE0NBQiEQi/Pjjj+jYsSPatWuHXbt2ITk5WWixaEu1WiSFhYU4cuQIdu3ahVOnTqFTp06YPXs2AgMDhUgeGhqKjz/+GLNnz1Zrgcn/cByn8WG/KnnrwbBfkUgkLEerCUqmRFp2mpB3ZSUkJODKlSs4cOAAAH4yztGjR2Pnzp3o37+/kK5Tp07CdvFDt+np6cJ9AhcXF5Vv0/b29khPTxfeBwcHo3v37khJSUHTpk2xa9cuTJgwQWj1xMfHY8qUKSpl8+zYERGllunt2LFjtb4Bx8bGIiYmRmUWYoVCgfz8fOTm5sLMzAxHjhxB79690ahRozKfnzhxImbOnIlx48YhKioKv/32W5kWZ0JCAt555x2VfW+88YZw0zw5ORnt27cXji1atAiLFi3CW2+9hb///hvR0dG4ePEizp49i2+++QYrVqyoVIumKrZu3Yoff/wRjx49Ql5eHgoKCtC5c+dXfiY2NhZ//fVXmdZSfn4+Hjx4oNbyVVW1Aom9vT2USiXee+89XLlypdwfgK+vb529sUT0B8dxZZaqrdX8snJg+/hfSG0lVRpJtGPHDsjlcjRt2lTYxxiDWCxGRkaGsK/kF4fi8ytL3KMq/cWC4ziV4126dIG7uzv27NkDX19f3Lp1q1rr8lR3yQKlUokVK1aUmXwV+N/KjUeOHMHQoUPL/fygQYPw0UcfYdKkSRgyZEi5KzGycubRK9n95uDggLi4OOF9yYAlFovh5eUFLy8vLFiwAKtWrcIXX3yB+fPnw8jICBzHlenKq+p94f3792P27NnYsGEDPD09YWlpia+++gqXL19+5eeUSiW6du2KkJCQMseKW3zaUq1AsnHjRowcOfKVS3ZaWVkhKSmp2gUjr1dQUIDFixcD4LsMNNlHWqBUYnHR7/dLV1dabreI6P59GAFo/PgF0KRyo4nkcjn27NmDDRs2CA/NFhsxYgRCQkLK7T6qrg8//BAbN25ESkoK+vfvrzIZabt27RAdHa1y8z369u1q5SMWi6FQKFT2eXh4ICEhAS1btiz3M9nZ2YiIiMCWLVvKPW5gYICgoCCsW7cOJ0+eLDdN27ZtVaZEAviHn4sZGhpWmH9p7du3h1wuR35+PoyMjNCkSROVBfcSExOrPNAlMjISvXr1wieffCLsK92iMDIyKvdn9+uvv8LGxqbcJZi1qVr//REREeVG4ZycnHL7LEntKCwsxPr167F+/XqNj5YrZAzrHz/G+sePUUjDf8sQVeFnUnxjfNKkSXBzc1N5vfvuu9ixY4dayxYYGIiUlBRs3769zP/rzJkzsXPnTuzcuRP379/HsuXLcOfvv6uVj4uLC86cOYO0tDShVbV06VLs2bMHy5cvx507dxAfH49ff/0Vn3/+OQAgLCwMrVq1KrN4XUkrV67E8+fP4evrW+7x6dOn48SJE/j666+RmJiIbdu24eTJk69tIXp7e2Pbtm2IjY3Fw4cPceLECSxatAh9+/YVLtz9+vXD5s2bce3aNVy9ehVTpkypcvdyy5YtcfXqVfzxxx+4f/8+lixZgpiYGJU0Li4uuHnzJhISEvDPP/+gsLAQgYGBsLa2xtChQxEZGYmkpCScP38eM2fOxJMnT6pUBnWrViD56aefkJeXV2Z/Xl4e9uzZU+NCkcoRi8WYO3cu5s6dq5UpUuY6OmKuo6Ne3CvRZTt27ED//v0hkUjKHBsxYgTi4uJw7do1teXXoEEDjBgxAhYWFmUeehs9ejSWLl2K+fPno2vXrkh+lIyPy1kGuzI2bNiA8PBwODo6okuXLgD4Lu9jx44hPDwc3bt3R8+ePfH111/DuWi6ncOHD1fYrVXMyMgI1tbWFQaG3r17Y+vWrfj666/h7u6OsLAwzJ49+5U9KMVl++mnn+Dj44N27dph+vTp8PX1FW6CF9fJ0dERb731FsaOHYu5c+dWeaDLlClTMHz4cIwePRo9evTAixcvVFonAH8vq02bNujWrRuaNGmCixcvwszMDH/++SecnJwwfPhwtGvXDhMnTkReXp7WWygcq8Jg96ysLDDGYGVlhcTERJV+OYVCgaNHj2LBggV4WjSZX12SlZUFiUQCqVSq9V9abVIoFMLNSy8vL43eX1CH4tUAXV1dX3vhqBUlulCUXT0g4nSzy2/AgAFo164dvv3221emY0oG7losv21hAa5t21ork0KhgI2NDU6ePIk33nhDrecODg7GvXv3NDoUXFe86n9CXde1Kt0jadiwofCATPFDSCVxHKfzqwoSUp/9+++/OHXqFM6ePatzE5e+ePECs2fPRvfu3Wt8rvXr12PAgAEwNzfHyZMn8dNPPwkzZRP1q1IgiYiIAGMM/fr1w3//+1+V0Q5GRkZwdnaGQ6kHl0jtYYwJTwQbGhqqZb6hKuVd1Jg1VNNcR6T2eXh4ICMjA//5z390bhkFGxsb4V5JTV25cgXr1q3Dy5cv0bx5c3z77bf48MMP1XJuUlaVAkmfojW6k5KS4OTkRBcPLcvNzYWFhQUAfrRLdYdkVitvpRIWRd0E2V5eMNezLrD6Shem09CEkvc1SO2rdCC5efMm3NzcIBKJIJVKcevWrQrTlnxoihBCSN1W6UDSuXNnpKWlwcbGBp07dy73wRyAv09SevwzqR1mZmbCsEptTJGSUbQKJU2RQkj9VulAkpSUJIzSogcNdQPHcVqbPYDjODTU0vQs+oCerCH1SaUDSfE479LbhBBC6rdqP5B4/Phx4f1nn32Ghg0bolevXnj06JHaCkderaCgAMuXL8fy5cuFxYU0lrdSieVJSVielIQCHV6PhBBS+6oVSFavXg1TU1MAQFRUFDZv3ox169bB2tqaZvvVoMLCQqxYsQIrVqzQyhQpKx49wopHj2iKFELquWpN2vj48WNh0rNDhw7h3XffxeTJk9G7d29hXQNS+wwNDYWpFQwNq71GWfXy5jh8UvTMkCENAy+LfiSkHqlWi8TCwkJYx/jUqVPCegkmJiblzsFVkT///BNDhgyBg4NDuUtYFq+TUPLVs2dPlTQymQzTp0+HtbU1zM3NERAQUGYCs4yMDAQFBUEikUAikSAoKAiZmZlVr7iOMTY2xpYtW7BlyxaVJUk1krdIhC2tW2NL69YwplFbapGeno6PPvoITk5OwqJGvr6+iIqKEtJcunQJgwYNgpWVFUxMTNCxY0ds2LBBZaTkw4cPVZZybdGiBZYtW6bx7k9Sf1TrCjBgwAB8+OGH+PDDD3H//n0MHjwYAHDnzh2VtZlfJycnB+7u7q+cqsHPzw+pqanC68SJEyrHZ82ahYMHDyI0NBQXLlxAdnY2/P39Vf6xxo4di7i4OISFhSEsLAxxcXEICgqqWqUJqQJWjSbJiBEjcOPGDfz000+4f/8+jhw5Am9vb/z7778AgIMHD6JPnz5o1qwZIiIicO/ePcycORNffvklxowZIwzHv3fvHpRKJbZt24Y7d+5g48aN2Lp1KxYtWqTWOhIiYNWQkZHBpk6dygICAtjJkyeF/UuXLmWrVq2qzikZAHbw4EGVfePHj2dDhw6t8DOZmZlMLBaz0NBQYV9KSgoTiUQsLCyMMcbY3bt3GQAWHR0tpImKimIA2L179ypdPqlUygAwqVRa6c/oI7lcziIiIlhERASTy+XaLk6V5eXlsbt377K8vDyV/dlyOcuWy5lSqRT2yRQKli2Xs3yFoty0ihJpC4rS5pX6mZRJGxPDCq5cYYqrV5lCqXreV8nIyGAA2Llz58o9np2dzRo3bsyGDx9e5tiRI0cYAJX/g9LWrVvHXF1dK12eYkqFkrGYGMZiYpgyPr7KnyfaV9H/BGPqu65Vq0XSsGFDbN68GYcPH4afn5+wf8WKFcJCS+py7tw52NjYoHXr1ggODlZZNjQ2NhaFhYUqiwE5ODjAzc0Nly5dAsAPBpBIJOjRo4eQpmfPnpBIJEIafZWTkwOxWAyxWIycnBzN5q1QQHz+PMTnzyNHDx5AtYiMhEVkJP4pMSjhq8ePYREZiWmJiSppbS5ehEVkJJJLrIW+JSUFFpGRmJSQoJLWJToaFpGRiC+xuNHuovnPqlQ+CwtYWFjg0KFDkMlkZY6fOnUKL168wNy5c8scGzJkCFq3bo1ffvmlwvNLpdJyl64lRB2qfYc2MzMTV65cQXp6uspSnhzHqa3baODAgRg5ciScnZ2RlJSEJUuWoF+/foiNjYWxsTHS0tJgZGQEKysrlc/Z2toiLY1fN7v4afzSbGxshDTlkclkKv/QWVlZaqmTusmrcdFSW940WqtiVezZMjQ0xO7duxEcHIytW7fCw8MDffr0wZgxY9CpUyfcv38fAL+CYXnatm0rpCntwYMH+O6777Bhw4aqFYqQSqpWIDl69CgCAwORk5MDS0tLlckb1RlIRo8eLWy7ubmhW7ducHZ2xvHjx8td87kYK7Vmc3mTS5ZOU9qaNWt0fkp8U1NTYWBB8XBsjeUtEuGJp6ewreuyvbwAqE7nMs/REbOaNSsz6iy9aOqXkvWa2rQpgh0cUHpqyodFgz9Kpp1QzRF0I0aMwODBgxEZGYmoqCiEhYVh3bp1+PHHH4U0rILgXdHf89OnT+Hn54eRI0fS7Lek1lTrCjBnzhxMnDgRL1++RGZmJjIyMoRX8Y3B2mBvbw9nZ2ckFnVF2NnZoaCgQJhvqlh6ejpsbW2FNM+ePStzrufPnwtpyrNw4UJIpVLh9fjxYzXWRD1EIhGaNm2Kpk2bQqThi7mI49DU2BhNjY0h0oPhv+YGBjA3MFC52BqJRDA3MCgz6qw4bcl6iYvSmpSa5bjctDX4eZiYmGDAgAFYunQpLl26hAkTJmDZsmXC+j/x8fHlfu7evXto1aqVyr6nT5+ib9++8PT0xA8//FDtMhHyOtW6+qSkpGDGjBkanyjwxYsXePz4Mezt7QEAXbt2hVgsRnh4uJAmNTUVt2/fRq9evQAAnp6ekEqluHLlipDm8uXLkEqlQpryGBsbo0GDBiovQjStffv2yMnJgY+PDxo1alRu99SRI0eQmJiI9957T9iXkpICb29veHh4YNeuXTX4okHdl+T1qtUG9/X1xdWrV9G8efMaZZ6dnY2//vpLeJ+UlIS4uDg0atQIjRo1wvLlyzFixAjY29vj4cOHWLRoEaytrfHOO+8AACQSCSZNmoQ5c+agcePGaNSoEebOnYuOHTsKz7a0a9cOfn5+CA4OxrZt2wAAkydPhr+/v84t7FNVBQUF+OabbwAAM2fOhJGRkebyVirxTVG32sxmzWCkB91buuzFixcYOXIkJk6ciE6dOsHS0hJXr17FunXrMHToUJibm2Pbtm0YM2YMJk+ejGnTpqFBgwY4c+YM5s2bh3fffRejRo0CwLdEvL294eTkhPXr1+P58+dCPnZ2dtqqIqnLqjPU68cff2ROTk5s2bJl7Pfff2eHDx9WeVVWREQEA/+VR+U1fvx4lpuby3x8fFiTJk2YWCxmTk5ObPz48Sw5OVnlHHl5eWzatGmsUaNGzNTUlPn7+5dJ8+LFCxYYGMgsLS2ZpaUlCwwMZBkZGVWqsy4O/83OzhZ+ZtnZ2Wo5Z2WH/2bL5QwREQwRESxbh4YJv2qoo0YUDZVVxFZt+G9+fj5bsGAB8/DwYBKJhJmZmbE2bdqwzz//nOXm5grp/vzzT+bn58ckEgkzMjJi7du3Z+vXr1f5Xe3atavc/6vq/Lsr5Qoa/qvnNDH8l2Os6kNvXtVMrqvrkWRlZUEikUAqlepMN5dMJsNHH30EANi2bZtanm5XKBSILFr50MvLCwYVrHwoUyrxUdFQ2G1t2ujM0+35+flISkqCq6srTExMNF+Aq1cBAAoDEbjOnSHidOPnUl1MoQR3/Rq/bWEBrm1bLZeIVNWr/ifUdV2rVteWkmZ71QnGxsbYvXu3dvIWibC7gqGohJD6pcZfl/JLPLRFCCGk/qlWIFEoFFi5ciWaNm0KCwsL/P333wCAJUuWYMeOHWotICGEEN1WrUDy5ZdfYvfu3Vi3bp3KSKGOHTuqPDxFaldOTg4aNmyIhg0bamWKlIaRkWgYGakXU6QQQmpPtQLJnj178MMPPyAwMFDlZmynTp1w7949tRWOvF7xA5NayVuhgJSCSPl0/xlNQtSmWjfbU1JShIWtSlIqlRpfqa8+MzU1FeZX0sYUKfffeEPYJoTUX9UKJB06dEBkZCScnZ1V9v/222/o0qWLWgpGXk8kEpWZFkNjeXMcWml4ZgOiDfRkO3m9agWSZcuWISgoCCkpKVAqlThw4AASEhKwZ88eHDt2TN1lJETvMHDUu0XqjWr1SQwZMgS//vorTpw4AY7jsHTpUsTHx+Po0aMYMGCAustIKlBYWCgstavpLsVCpRJbUlKwJSUFhfRckUaVtyx1VS1fvhydO3dWS3kIqXbntq+vL86fP4/s7Gzk5ubiwoULKgtMkdpXUFCAadOmYdq0aRpfj7uAMUxLTMS0xEQU0LokZVWjOTJhwgRwHAeO4yAWi2Fra4sBAwZg586dKg8Bp6amYuDAgWosLL9M9ogRI+Di4gKO47Bp0yb+AP1qSSVUK5A0b94cL168KLM/MzOzxhM5ksozMDDAu+++i3fffbfCqUxqLW8A7zZpgnebNCmzRgepPj8/P6SmpuLhw4c4efIk+vbti5kzZ8Lf319YxMzOzk4t0+GUlJubi+bNm2Pt2rU0sSOpsmoFkocPH5Y7n5ZMJkNKSkqNC0Uqx8TEBL/99ht+++03jc8rZWJggN86dMBvHTqUWaODVJ+xsTHs7OzQtGlTeHh4YNGiRTh8+DBOnjwpTIdTumtr/vz5aN26NczMzNC8eXMsWbKkTFfn2rVrYWtrC0tLS0yaNKnMjBTdu3fHV199hTFjxqg9SJG6r0o3248cOSJs//HHH5BIJMJ7hUKBM2fOwMXFRW2FI6SmGGMoVGrw/lFRXnKlEsaMqeV5kn79+sHd3R0HDhwod5VDS0tL7N69Gw4ODrh16xaCg4NhaWmJzz77DACwf/9+LFu2DFu2bIGXlxd+/vlnfPvtt9R7QNSmSoFk2LBhAPhvROPHj1c5JhaL4eLiQutCE51SqCzE6sjVmsvw6VMAgFLEYVHHTjAQqae11rZtW9y8ebPcY59//rmw7eLigjlz5uDXX38VAsmmTZswceJEIQitWrUKp0+fpnnyiNpUKZAU3/BzdXVFTEwMrK2ta6VQpHJyc3OF50gSExM1umJlrkKBVpcv83n36AEz6t6qVayCNdkB4Pfff8emTZvw119/ITs7G3K5XGVK8Pj4eEyZMkXlM56enoiIiKjVMpP6o1rPkSQlJam7HKQaGGN4WvQNuBrLytQsbwBPi0aK6fLAHrFIjEVeizSXYWwsAEAuNoBYJFbbaePj4+Hq6lpmf3R0NMaMGYMVK1bA19cXEokEoaGh1DNANKpagQQAzpw5gzNnziA9Pb3M+iQ7d+6sccHI65mYmOD69evCtkbzFolwvWtXYVtXcRwHIwPNLUGMouAhEhlU2IKoqrNnz+LWrVuYPXt2mWMXL16Es7MzFi9eLOx79OiRSpp27dohOjoa77//vrAvOjpaLWUjBKhmIFmxYgW++OILdOvWDfb29mr7hyFVY2BgoLWHygw4Dp0tLbWSd10mk8mQlpYGhUKBZ8+eISwsDGvWrIG/v79KICjWsmVLJCcnIzQ0FN27d8fx48dx8OBBlTQzZ87E+PHj0a1bN7z55psICQnBnTt3VG62FxQU4O7du8J2SkoK4uLiYG5iAu1MwkP0SbUCydatW7F7924EBQWpuzyE1GthYWGwt7eHoaEhrKys4O7ujm+//Rbjx48vd4nroUOHYvbs2Zg2bRpkMhkGDx6MJUuWYPny5UKa0aNH48GDB5g/fz7y8/MxYsQIfPzxx/jjjz+ENE+fPlWZJ2/9+vVYv349+rz1Fs5RNxl5jWqt2d64cWNcuXIFLVq0qI0y6SRdXLO9sLAQISEhAIDAwECIxTXvk6/smu2FSiVCnj3j87a1hVhHurd0Zc12udgAok7u+r9me6Ec3I04fpvWbNdLmlizvVp/5R9++CH27dtX7UyJehQUFOCDDz7ABx98oJUpUj5ISMAHCQk0RQoh9Vy1urby8/Pxww8/4PTp0+jUqVOZb8Jff/21WgpHXs3AwACDBg0StjWaN4BBjRoJ24SQ+qtaLZKbN2+ic+fOEIlEuH37Nq5fv67yqqw///wTQ4YMgYODQ5lpHwoLCzF//nx07NgR5ubmcHBwwPvvvy8Mdy3m7e0tTHRX/BozZoxKmoyMDAQFBUEikUAikSAoKAiZmZnVqbpOMTExwfHjx3H8+HGtTJFyvFMnHO/UiaZIIaSeq1aLRF0PMuXk5MDd3R0ffPABRowYoXIsNzcX165dw5IlS+Du7o6MjAzMmjULAQEBuFrUD10sODgYX3zxhfC+9GqBY8eOxZMnTxAWFgYAmDx5MoKCgnD06FG11IMQQuqzKgWS4cOHvzYNx3H473//W6nzDRw4sMLpsCUSCcLDw1X2fffdd3jjjTeQnJwMJycnYb+ZmVmFM5bGx8cjLCwM0dHR6NGjBwBg+/bt8PT0REJCAtq0aVOpshJCCClflbq2iruGXvWqzRFNUqkUHMehYcOGKvtDQkJgbW2NDh06YO7cuXj58qVwLCoqChKJRAgiANCzZ09IJBJcunSpwrxkMhmysrJUXrqmeIqUVq1aITc3V7N5F02R0uryZeSWMxM0IaT+qFKLZNeuXbVVjtfKz8/HggULMHbsWJVgFRgYCFdXV9jZ2eH27dtYuHAhbty4IbRm0tLSYGNjU+Z8NjY2SEtLqzC/NWvWYMWKFeqviBoxxvDXX38J2xrNG8BfeXnCNiGk/qr2FCmaVFhYiDFjxkCpVOL7779XORYcHCxsu7m5oVWrVujWrRuuXbsGDw8PACj3yftXTYIHAAsXLsSnn34qvM/KyoKjo2NNq6JWJiYmuHDhgrCt0bxFIlwoeoBNl6dIIYTUPp0PJIWFhRg1ahSSkpJw9uzZ13adeXh4QCwWIzExER4eHrCzs8OzogfnSnr+/DlsbW0rPI+xsbHOL/BjYGCA3r17aydvjkPvEuvRkLqK2pvk9XT6q2RxEElMTMTp06fRuHHj137mzp07KCwshL29PQB+umypVIorV64IaS5fvgypVIpevXrVWtkJqS2lh8pXx/Lly7U2Txupe7QaSLKzsxEXF4e4uDgA/PT0cXFxSE5Ohlwux7vvvourV68iJCQECoUCaWlpSEtLE57ifvDgAb744gtcvXoVDx8+xIkTJzBy5Eh06dJF+Kberl07+Pn5ITg4GNHR0YiOjkZwcDD8/f31fsSWXC4XltotXs9bY3krlfgtPR2/padDXmr2Z1I9EyZMEJ6FEovFsLW1xYABA7Bz506VGbZTU1MrHO1YXdu3b4eXlxesrKxgZWWF/v3781++qEFCKkGrgeTq1avo0qWLMFncp59+ii5dumDp0qV48uQJjhw5gidPnqBz586wt7cXXsWjrYyMjHDmzBn4+vqiTZs2mDFjBnx8fHD69GmVJ71DQkLQsWNH+Pj4wMfHB506dcLPP/+slTqrk0wmw6hRozBq1CjIZDLN5s0YRt29i1F370JGU6SojZ+fH1JTU/Hw4UOcPHkSffv2xcyZM+Hv7y98WbCzs1N7t+u5c+fw3nvvISIiAlFRUXBycoKPjw9SUlLUmg+pm7R6j8Tb2/uVo41eNxLJ0dER58+ff20+jRo1wt69e6tcPl0nEonQp08fYVujeQPoU3SPRKf7R/WMsbGx8ExU06ZN4eHhgZ49e+Ltt9/G7t278eGHH4LjOBw8eFBY+nr+/Pk4ePAgnjx5Ajs7OwQGBmLp0qUqUxetXbsWGzduRG5uLkaNGoUmTZqo5Fs8+Wex7du34/fff8eZiLMY36lT7Vaa6D2dv9lOKmZqaopz585pJ28DA5wrMe24rmKMgRVqsMVUlJcSDBxjgBqW6unXrx/c3d1x4MABYd31kiwtLbF79244ODjg1q1bCA4OhqWlpbBm+/79+7Fs2TJs2bIFXl5e+Pnnn/Htt9+qrEdSWm5uLgoLC9HIqlHNK0DqPAokpE5jhQyPVj96fUJ1ecrfv1OKRHD+hgFq6oFq27Ytbt68We6xzz//XNh2cXHBnDlz8OuvvwqBZNOmTZg4caIQhFatWoXTp08jPz+/wvwWLFiApk2bov/bbwP3E9RTCVJnUa8EIXrgVc89/f7773jzzTdhZ2cHCwsLLFmyBMnJycLx+Ph4eHp6qnym9PuS1q1bh19++QUHDhzQzpouRO9Qi0SP5eXlCReEqKioMpNV1mreCgU8r13j8/bwgKmOzgDMiTk4L3LWXIax/wAA5GJDcGL1LUEdHx8PV1fXMvujo6MxZswYrFixAr6+vpBIJAgNDcWGaq5quH79eqxevVpYIoIVFP7vII2pIBWgQKLHlEolbty4IWxrNG8AN3JyhG1dxXEcOCP1XdBfqyh4iMTcK2dOqIqzZ8/i1q1bmD17dpljFy9ehLOzMxYvXizse/RItSuvXbt2iI6OVlnzPTo6usy5vvrqK6xatQp//PEHunXrppayk/qBAokeMzExwalTp4RtjeYtEuFU0WgemiJFfWQyGdLS0qBQKPDs2TOEhYVhzZo18Pf3VwkExVq2bInk5GSEhoaie/fuOH78OA4ePKiSZubMmRg/fjy6deuGN998EyEhIbhz547KzfZ169ZhyZIl2LdvH1xcXIR56MyNjGEppKImCSkfBRI9ZmBggAEDBmgnb47DgEY0okfdwsLCYG9vD0NDQ1hZWcHd3R3ffvstxo8fX+4Q76FDh2L27NmYNm0aZDIZBg8ejCVLlmD58uVCmtGjR+PBgweYP38+8vPzMWLECHz88cf4448/hDTff/89CgoK8O6776qcf+nnn2PF0KG1Vl9SN3BM09PG6qmsrCxIJBJIpdJanSpf2xQKBSIjIwEAXl5eGl/Ct6by8/ORlJQEV1dX7dwoLlp0TS42hKhTJ4g4/W6tMVkBuFv8aDFmbg6uXTstl4hU1av+J9R1XaMWiR6Ty+XCt0pfX18YGmru1ylXKvFHRgaft5UVDKl7S5UGb8sQom0USPSYTCaDv78/AH7eMk0GEhlj8L91i8/by4v+kOos6rAgr0f//3pMJBIJo2u0MUVKN0tLYZsAqIu9xHWwSkT9KJDoMVNTU8TExGgnbwMDxHTtqpW89QFdf0l9Ql8mCSGvQCGRvB4FElInaWUwYl3v2qqD1asPNPG/QIFEj+Xl5aF3797o3bs38vLyNJu3QoHe166h97VryFMoNJr3qxQPVy5e/IyQ+i43NxcAVJYVUDe6R6LHlEqlsMiXNqZIuZSVJWzrCkNDQ5iZmeH58+cQi8WaHYRQ4ndQyBgM8vPrwHMk+cJIZqZUgHvFjMFEtzDGkJubi/T0dDRs2LBWnwmjQKLHjI2Nhekw1L1i3mvz5jgc7NBB2NYVHMfB3t4eSUlJZeacqnWMAf/wkzYqDEQQiY3VNt+WtrCCQnBFdYKREaBnD6gSoGHDhsJiabWFAokeMzQ0FFbJ03jeIhGGlVplT1cYGRmhVatWmu/eys8HBg0CAGTYW8H89HkYGRhptgxqprx3H6IpUwAArEMHcP/9r5ZLRKpCLBZrZHYKCiSkThKJRJqfIkWpBIpaQWJlNkxMTPQ/kICDqKhOrLE1OFqfhJSDAoke0+a8WArGEJmZyefdsCEM9LwLRy1K3CPh6soIrpL33upKnYjaUSDRY/n5+ejbty8AfooUc3NzzeWtVKJv0Voo2V5eMKe+c9ULbV255mp4EAfRT1odUvLnn39iyJAhcHBwAMdxOHTokMpxxhiWL18OBwcHmJqawtvbG3fu3FFJI5PJMH36dFhbW8Pc3BwBAQF48uSJSpqMjAwEBQVBIpFAIpEgKCgImUXfpvUZx3Fo37492rdvr/GbuhyA9mZmaG9mRvMTFisRSOpMi0QlONaROhG102ogycnJgbu7OzZv3lzu8XXr1uHrr7/G5s2bERMTAzs7OwwYMAAvX74U0syaNQsHDx5EaGgoLly4gOzsbPj7+0NR4tmGsWPHIi4uDmFhYQgLC0NcXByCgoJqvX61zczMDHfu3MGdO3dgZmam2bwNDHDnjTdw5403YEatEV5dvNBSi4RUBtMRANjBgweF90qlktnZ2bG1a9cK+/Lz85lEImFbt25ljDGWmZnJxGIxCw0NFdKkpKQwkUjEwsLCGGOM3b17lwFg0dHRQpqoqCgGgN27d6/S5ZNKpQwAk0ql1a2iXpDL5SwiIoJFREQwuVyu7eLol4wMxvhwwv61b8hkcpm2S1RjiqgrQp2U7p21XRyiZuq6runs01JJSUlIS0uDj4+PsM/Y2Bh9+vQRHsKLjY1FYWGhShoHBwe4ubkJaaKioiCRSNCjRw8hTc+ePSGRSIQ0hKgF3SMh9ZTO3mwvXjPa1tZWZb+tra3woFlaWhqMjIxgZWVVJk3x59PS0mBjY1Pm/DY2NkKa8shkMshkMuF9VtFT3LokLy8PAQEBAIAjR47A1NRUc3krFAi4fZvP280NptS9VfdHbVFQIRXQ2UBSrPRNZMbYa28sl05TXvrXnWfNmjVYsWJFFUurWUqlEqdPnxa2NZo3gNNFKyTS5aVIXQkeJdHNdlIJOtu1VfxIf+lWQ3p6utBKsbOzQ0FBATKKLmgVpXn27FmZ8z9//rxMa6ekhQsXQiqVCq/Hjx/XqD61wdjYGHv37sXevXu1MkXK3nbtsLddO52aIkWr6uKorZJfUHRock6iW3Q2kLi6usLOzg7h4eHCvoKCApw/fx69evUCAHTt2hVisVglTWpqKm7fvi2k8fT0hFQqxZUrV4Q0ly9fhlQqFdKUx9jYGA0aNFB56RpDQ0MEBgYiMDBQo8vsAvwUKYG2tgi0taX12ovV9Xsk1LVFKqDVrq3s7Gz89ddfwvukpCTExcWhUaNGcHJywqxZs7B69Wq0atUKrVq1wurVq2FmZoaxY8cCACQSCSZNmoQ5c+agcePGaNSoEebOnYuOHTuif//+AIB27drBz88PwcHB2LZtGwBg8uTJ8Pf3R5s2bTRfaVJ31cUWScl6UIuEVECrgeTq1avCk9kA8OmnnwIAxo8fj927d+Ozzz5DXl4ePvnkE2RkZKBHjx44deoULIvWCgeAjRs3wtDQEKNGjUJeXh7efvtt7N69W2W6kJCQEMyYMUMY3RUQEFDhsyv6RKFQ4Nq1awAADw8PjU+Rcq3oeR4PS0uaIgVQDSTKOhJIqEVCKoFjrK58dapdWVlZkEgkkEqlOtPNlZOTAwsLCwDqmyKlsvN35SgUsChKR1OkFHn6FGjaFACQbWUOo+f/6v+kjafOQOTLt+6Zswu4h0laLhFRJ3Vd13R+1BapGMdxcHZ2FrY1mjcA56Ib/NQWKVIXWyQq932oRULKR4FEj5mZmeHhw4faydvAAA89PbWSt84qcdEV1ZVuIBq1RSqBhtsQoi51sUVC90hIJVAgIURdaNQWqacokOix/Px8DBs2DMOGDUN+fr5m81YoMOzWLQy7dQv5dIHhlZwihVokpB6heyR6TKFQ4PDhw8K2RvMGcPjFC2GbAJDLhU2OsbrxTCK1SEglUCDRY0ZGRvjhhx+EbY3mzXH4oXVrYZtANZAo60ggoRYJqQQKJHpMLBYjODhYO3mLRAh2cNBK3jqrVIukTqBRW6QS6B4JIepSqkVSJ5QMiNQiIRWgFokeUyqViI+PB8DPKSbS4OSJSsYQn5vL521mBhF1b9XNFgmjFgl5PQokeiwvLw9ubm4A1DdFSqXzVirhFhPD501TpPBUAgnqxvoddI+EVAIFEj1nbW2tvbzFYq3lrZNKBBIAdePCS6O2SCVQINFj5ubmeP78uXbyNjDA8969tZK3zqqLgUTl2Zg6UB9SK+hmOyHqUscDSbnvCQEFEkLUpy4GktL3eSpTp7pwb4hUCQUSPZafny8stauNKVIC795F4N27NEVKsboYSErX4XW/62+/Baytgbi4WisS0T0USPSYQqHAvn37sG/fPq1MkbIvPR370tNpipRi9SGQvK5OM2cC//4LzJpVa0UiuodutusxIyMjbNy4UdjWaN4ch40tWgjbBHUzkJRu6Vb2CwsNB69XKJDoMbFYjFla+uYnFokwy9FRK3nrrDoZSGSq7ytbJzMz9ZeF6Czq2iJEXUoHkoIC7ZRDnfLyVN9XtkWiwYdjifZRi0SPKZVKJCcnAwCcnJw0PkVKclG3h5OJCU2RApQNJKUvwvpIVqpr61UtkpKjtTTc1Uq0iwKJHsvLy4OrqysA7UyR4nr5Mp83TZHCKyxUfV8HAglXug6l61hSyRaYBr/UEO3T+d+2i4sLOI4r85o6dSoAYMKECWWO9ezZU+UcMpkM06dPh7W1NczNzREQEIAnT55oozpqZ2ZmBjMt9UebiUQwqy8XjIgI4Pr1V6fJzlZ5y+XqfyApc7M9J6fitEWTeAKgQFLP6HyLJCYmRmVo6+3btzFgwACMHDlS2Ofn54ddu3YJ70uPYJo1axaOHj2K0NBQNG7cGHPmzIG/vz9iY2NhoMffpM3NzZHzqn/s2szbwAA5b72llbw17ulToF8/fjsvDzAxKT+dVKr6vg60SMoEkqysitOWDCT0bFG9ovOBpEmTJirv165dixYtWqBPnz7CPmNjY9jZ2ZX7ealUih07duDnn39G//79AQB79+6Fo6MjTp8+DV9f39orPKkbSrZeY2OBiuYYK32RrROBpFQdXr6sOG3JQFIX6k4qTa/anwUFBdi7dy8mTpwIrsTN3XPnzsHGxgatW7dGcHAw0tPThWOxsbEoLCyEj4+PsM/BwQFubm64dOlShXnJZDJkZWWpvEg9VbQ2PQDVoFJa6RZJ6YuwPnr2TPV9ZVskrwo4pM7Rq0By6NAhZGZmYsKECcK+gQMHIiQkBGfPnsWGDRsQExODfv36QSbjx7+npaXByMgIVlZWKueytbVFWlpahXmtWbMGEolEeDnq4DMTMpkMwcHBCA4OFuqrsbyVSgQnJCA4IQGyuvC8xKv888//tlNTK06XkaHylsvJrSChHnn6VPV96WBZUsl7RJmZtVIcopv0KpDs2LEDAwcOhEOJtcJHjx6NwYMHw83NDUOGDMHJkydx//59HD9+/JXnYoyptGpKW7hwIaRSqfB6/Phx9Qr977/Aw4fV++xryOVy/Pjjj/jxxx8hLz30tJbJGcOPqan4MTUV8ro+SV/J4FH6wlpS0e+50Liox7j0t3ldo1QCQ4YAQUHlH2cMePQQACCzbcfve8WXL5WWGwWSekVvAsmjR49w+vRpfPjhh69MZ29vD2dnZyQmJgIA7OzsUFBQgIxS3xbT09Nha2tb4XmMjY3RoEEDlVeVnT7NT2Dn6gpw3P9eEglw/jz/j/rPP/w/dGGh6jj8lBQgKemVpxeLxVi1ahVWrVoFsYYXmRJzHFa5umKVqyvE6n6G5M8/+cn/tB2glErgwQOg5JeIilokSiXw118AgIedXQAAhnPm1XIBa+jvv4Fjx4C9e8sPEE+egHv5EkxkiHyXHvy+oueWylWiS5kCSf2i8zfbi+3atQs2NjYYPHjwK9O9ePECjx8/hr29PQCga9euEIvFCA8Px6hRowAAqampuH37NtatW1e7he7atfyLYVYW4O1d8eeGDQMOHQIMDYEpU4B9+4Bp0/iLlYEBsG0bYGsLo6+/xuIRI4DWrfnhqXI5cO4cP55/4ECgUSPAxYV///QpH7Q4DnBz498bGfEBLD4eaNcOMDUFSg5ukMuBa9f48nbowF9QTU0BGxsYvfceFpuaAu++y4/QcXUFLCz4ssbE8CObVq/mR/04O/OvkgGHMf68eXn8BbhXL37IqFIJFA+kcHICevTgu4xateLr/u+/fBmSk4Hvvwc8PQE7O77816/zdf38c+CLL/hzOToCbdrwdc/N5ctgZcW3HhwcgDt3+J9Tjx78hbCwkC8rwP/st29X/d3s3Qv4+QGBgar79+wBXr4EMzfH/Z6t0eoyH1Rw+TLwxhuqddcVKSn/246L4+tVUnAwAKCwsSsK7PklnfHtt0DfvvzfaGklg+zz58CNG4BMxtef1GkcY9r+2vd6SqUSrq6ueO+997B27Vphf3Z2NpYvX44RI0bA3t4eDx8+xKJFi5CcnIz4+HhYWloCAD7++GMcO3YMu3fvRqNGjTB37ly8ePGiSsN/s7KyIJFIIJVKq9Y6SUkBmjWrUn2J/lJ8MAErg5ywvN8XqgeGDgUOHy77gQ8/5IPYrVt8YG/ShL/4du4stHDQqhW/XywGmjfng/OcOfzx58/5LwYrV/JB2dqav9H9xRf85wwNgYMH+W6n/v35qUuMjfnWSEoKcPPm/8qyaBFw4QLfIiwhu2MAng9bD5ftb4Er2XLp2BGYPx/YupX/XEV27OCD+nvv8V8K8vKAli3/F1zlcr6cFWFMNwNxHVDt61opehFITp06BV9fXyQkJKB169bC/ry8PAwbNgzXr19HZmYm7O3t0bdvX6xcuVLl5nh+fj7mzZuHffv2IS8vD2+//Ta+//77Kt1Ar9EPvOQ/Qm4ucPs28OOP/DdoiQQ4c6Zq5yO6qVkzFPyVgNVR6+B4KxmTZux6/Wf0wOOZf0LesBmcu8ZDFPDqHgEAfCuwOvcUjY35IArwLT6O41uAxbp0+V8L+MED4NIlvjXZtSt/r+err/hW66pVfKuzcWPg+HEgMRHo2ZP/v5PL+ZbugAF8t17jxnzL+PRp4M03gUmT+IcuX77kg/vs2XxrNzQUiIriu6T79gUSEoCmTfl6jhrFB1JbWz5A7toFjB/Pn7tYQQEfTPPzgQYN/vfApkKh1ZmS61Ug0QXq+oFXyfPnwL17/D9QZib/h3r2LH+sTRvkMIbA5s3xLoDRkyZB3KcPYGnJf3Nt3Bj49Vf+Dzozk/+2+/w5cPQoMGgQ34XTpQvf9dK4Mb/f3BzKwkKwrVsBAKLOncFt3sz/4X/3HbBlC/8PGRiI3IAA2Ny5g0HR0fipd2+YtmzJB0wjI/4C8PIl/w8cFwesX8//w0ycCPzf//HbLVrwQfTaNdU6i8XATz/x36CNjYH//IfvcnrvPb7uvXvz721t+YuIWMx3oeTn811ap04B9vb8DeS8PODuXX7IbnY2YGMDhIXxF5MHD/hzDB8OrFnD34/q1InvlitmYvK/B/IeP+bLs2ULsGKFaplbt+Z/Rvv2oaC5M1ZHrgYALGoyHEZu7ur+q1AfY2Pgo4/4n8n9+2WPN20KZcx1PNrGj8ZyXuQM0akT/EW7ImfP8t2c/fvzP2PCd8WWfq6mZNBs3Fh1oEKxRo2At9/mW4+dO/Mj5n7/XTVN69Z8gGIMOHmSb4VWAQUSDdNKIHmNnJwcWFhYAFDfXFsKhQKRkZEAAC8vrwq7/nIUClgUpVPbXFu61IWRmcmXp2FD/n0ly1WgKPhfIPFaBCMDI/6CYWTEn+/AAf5+UPHIQ8b4wCYW8wF282a+1frPP3ygd3bmW65ubvy32pUr+WA6axYfCEUi/pt548b8BadBA/6btKsr36XUpg0fEN9+m9+WyYDISL7V8MYb/Lfh4sEesbH8PacSdVUWKPFo9SMARYHEqOibdGoqn39ODh+kMzP5LwfFs0r88w9fjkaN+Htw//d/fH3S0v731PuBA3zePj58C+LXX6v/+yL87/Svv6o0YSYFEg3TxUBSGyobSEj5yg0keqzCQFJbir9MFBTwQU8m47uRXF35YCcSAVeu8IEzP58PkOnpfBAaO5a/RxQezgdICwu+hf70KR/0Ll7kz2NtzbcwL13ig/iOHfw9pZQU4Ouv+Vba/v18l1a7dvw9rMJCPmC2aMEPKGnShO/GunuX78rq25cPzBcu8K3a0ksImJvzLeKkJP6eaWoqH1DnzOHTl7ovJWjY8H8j4AwMXj31zI8/8l1zVUCBRMPqSyBhjEFZ9IChSCR65bM2pCzGGAqV/Ay5YpFY739+jDGwQv4SwYk5va+PxuXk8F2rbdq8Pl3xg71Fg4RUKJVlJ8JkjN+fmsq3aF/xOENF1HVd05vhv0QzOI6jVkgNcByn962QkjiOA2dEwaPazM1fH0SK071KebMpcxzfStGBUaF680AiIYQQ3USBhBBCSI1QICGEEFIjFEgIIYTUCAUSQgghNUKBhBBCSI1QICGEEFIj9BxJJRU/t0lL7hJC6ori61lNn0unQFJJL4vWoNbFJXcJIaQmXr58CYlEUu3P0xQplaRUKvH06VNYWlrq/DQRWVlZcHR0xOPHj+vEdC51qT5UF91Ul+oCVL4+jDG8fPkSDg4OEJX39HwlUYukkkQiEZrpwFQEVVHtJYJ1VF2qD9VFN9WlugCVq09NWiLF6GY7IYSQGqFAQgghpEYokNRBxsbGWLZsGYyNjbVdFLWoS/WhuuimulQXQPP1oZvthBBCaoRaJIQQQmqEAgkhhJAaoUBCCCGkRiiQEEIIqREKJDrqzz//xJAhQ+Dg4ACO43Do0CGV4wcOHICvry+sra3BcRzi4uLKnEMmk2H69OmwtraGubk5AgIC8OTJE5U0GRkZCAoKgkQigUQiQVBQEDIzMzVWl8LCQsyfPx8dO3aEubk5HBwc8P777+Pp06c6WZfX1QcAli9fjrZt28Lc3BxWVlbo378/Ll++rJP1eV1dSvroo4/AcRw2bdqkl3WZMGECvwZ9iVfPnj31si4AEB8fj4CAAEgkElhaWqJnz55ITk7WSl0okOionJwcuLu7Y/PmzRUe7927N9auXVvhOWbNmoWDBw8iNDQUFy5cQHZ2Nvz9/aFQKIQ0Y8eORVxcHMLCwhAWFoa4uDgEBQVprC65ubm4du0alixZgmvXruHAgQO4f/8+AgICdLIur6sPALRu3RqbN2/GrVu3cOHCBbi4uMDHxwfPnz/Xufq8ri7FDh06hMuXL8PBwaHMMX2qi5+fH1JTU4XXiRMn9LIuDx48wJtvvom2bdvi3LlzuHHjBpYsWQITExPt1IURnQeAHTx4sNxjSUlJDAC7fv26yv7MzEwmFotZaGiosC8lJYWJRCIWFhbGGGPs7t27DACLjo4W0kRFRTEA7N69e2qvB2OvrkuxK1euMADs0aNHjDHdrQtjlauPVCplANjp06cZY7pbn4rq8uTJE9a0aVN2+/Zt5uzszDZu3Cgc06e6jB8/ng0dOrTCz+hTXUaPHs3GjRtX4Wc0XRdqkdRRsbGxKCwshI+Pj7DPwcEBbm5uuHTpEgAgKioKEokEPXr0ENL07NkTEolESKMNUqkUHMehYcOGAPS7LgUFBfjhhx8gkUjg7u4OQL/qo1QqERQUhHnz5qFDhw5ljutTXQDg3LlzsLGxQevWrREcHIz09HThmL7URalU4vjx42jdujV8fX1hY2ODHj16qHR/abouFEjqqLS0NBgZGcHKykplv62tLdLS0oQ0NjY2ZT5rY2MjpNG0/Px8LFiwAGPHjhUmm9PHuhw7dgwWFhYwMTHBxo0bER4eDmtrawD6VZ///Oc/MDQ0xIwZM8o9rk91GThwIEJCQnD27Fls2LABMTEx6NevH2QymVBOfahLeno6srOzsXbtWvj5+eHUqVN45513MHz4cJw/f14opybrQrP/1jOMMZVp8MubEr90Gk0pLCzEmDFjoFQq8f333782vS7XpW/fvoiLi8M///yD7du3Y9SoUbh8+XK5/7jFdK0+sbGx+Oabb3Dt2rUq56lrdQGA0aNHC9tubm7o1q0bnJ2dcfz4cQwfPrzCz+laXZRKJQBg6NChmD17NgCgc+fOuHTpErZu3Yo+ffpU+Nnaqgu1SOooOzs7FBQUICMjQ2V/eno6bG1thTTPnj0r89nnz58LaTSlsLAQo0aNQlJSEsLDw1Wmvta3ugCAubk5WrZsiZ49e2LHjh0wNDTEjh07AOhPfSIjI5Geng4nJycYGhrC0NAQjx49wpw5c+Di4iKUUx/qUh57e3s4OzsjMTERgP7UxdraGoaGhmjfvr3K/nbt2gmjtjRdFwokdVTXrl0hFosRHh4u7EtNTcXt27fRq1cvAICnpyekUimuXLkipLl8+TKkUqmQRhOKg0hiYiJOnz6Nxo0bqxzXp7pUhDEmdKHoS32CgoJw8+ZNxMXFCS8HBwfMmzcPf/zxh17VpTwvXrzA48ePYW9vD0B/6mJkZITu3bsjISFBZf/9+/fh7OwMQAt1qdKteaIxL1++ZNevX2fXr19nANjXX3/Nrl+/LoxkevHiBbt+/To7fvw4A8BCQ0PZ9evXWWpqqnCOKVOmsGbNmrHTp0+za9eusX79+jF3d3cml8uFNH5+fqxTp04sKiqKRUVFsY4dOzJ/f3+N1aWwsJAFBASwZs2asbi4OJaamiq8ZDKZztXldfXJzs5mCxcuZFFRUezhw4csNjaWTZo0iRkbG7Pbt2/rXH1e93dWWulRW/pSl5cvX7I5c+awS5cusaSkJBYREcE8PT1Z06ZNWVZWll7VhTHGDhw4wMRiMfvhhx9YYmIi++6775iBgQGLjIzUSl0okOioiIgIBqDMa/z48Ywxxnbt2lXu8WXLlgnnyMvLY9OmTWONGjVipqamzN/fnyUnJ6vk8+LFCxYYGMgsLS2ZpaUlCwwMZBkZGRqrS/Hw5fJeEREROleX19UnLy+PvfPOO8zBwYEZGRkxe3t7FhAQwK5cuaJyDl2pz+v+zkorL5DoQ11yc3OZj48Pa9KkCROLxczJyYmNHz++TDn1oS7FduzYwVq2bMlMTEyYu7s7O3TokNbqQtPIE0IIqRG6R0IIIaRGKJAQQgipEQokhBBCaoQCCSGEkBqhQEIIIaRGKJAQQgipEQokhBBCaoQCCSGEkBqhQEKIjlm+fDk6d+6s0TzPnj2Ltm3bCjPL6pK5c+dWOI090Q0USIjWbN26FZaWlpDL5cK+7OxsiMVieHl5qaSNjIwEx3G4f/++potZL3z22WdYvHgxRCLNXhJSU1MxduxYtGnTBiKRCLNmzSq3bLt27UJSUpJGy0YqjwIJ0Zq+ffsiOzsbV69eFfZFRkbCzs4OMTExyM3NFfafO3cODg4OaN26tTaKWicUFhaWu//SpUtITEzEyJEjNVwiQCaToUmTJli8eLGwgmRpNjY28PHxwdatWzVcOlJZFEiI1rRp0wYODg44d+6csO/cuXMYOnQoWrRoobLc57lz59C3b18AwN69e9GtWzdYWlrCzs4OY8eOFZZMVSqVaNasWZmLTvHiTH///TcAfjnfyZMnw8bGBg0aNEC/fv1w48YNIX1x99LPP/8MFxcXSCQSjBkzBi9fvhTSuLi4YNOmTSr5dO7cGcuXLxfecxyHbdu2wd/fH2ZmZmjXrh2ioqLw119/wdvbG+bm5vD09MSDBw/K/Hy2bdsGR0dHmJmZYeTIkcjMzFQ5vmvXLrRr1w4mJiZo27atymJgDx8+BMdx2L9/P7y9vWFiYoK9e/eW+3sIDQ2Fj48PTExMVPYfOXIE3bp1g4mJCaytrVUWf3JxccGqVavw/vvvw8LCAs7Ozjh8+DCeP3+OoUOHwsLCAh07dlT5klAeFxcXfPPNN3j//fchkUgqTBcQEIBffvnlleci2kOBhGiVt7c3IiIihPcRERHw9vZGnz59hP0FBQWIiooSAklBQQFWrlyJGzdu4NChQ0hKSsKECRMAACKRCGPGjEFISIhKPvv27YOnpyeaN28OxhgGDx6MtLQ0nDhxArGxsfDw8MDbb7+Nf//9V/jMgwcPcOjQIRw7dgzHjh3D+fPnsXbt2irXceXKlXj//fcRFxeHtm3bYuzYsfjoo4+wcOFC4UI7bdo0lc/89ddf2L9/P44ePYqwsDDExcVh6tSpwvHt27dj8eLF+PLLLxEfH4/Vq1djyZIl+Omnn1TOM3/+fMyYMQPx8fHw9fUtt3x//vknunXrprKveNXAwYMH4/r16zhz5kyZNBs3bkTv3r1x/fp1DB48GEFBQXj//fcxbtw4XLt2DS1btsT7778PdcwL+8Ybb+Dx48d49OhRjc9FakGV5wsmRI1++OEHZm5uzgoLC1lWVhYzNDRkz549Y6GhoaxXr16MMcbOnz/PALAHDx6Ue44rV64wAOzly5eMMcauXbvGOI5jDx8+ZIwxplAoWNOmTdmWLVsYY4ydOXOGNWjQgOXn56ucp0WLFmzbtm2MMcaWLVvGzMzMVNaqmDdvHuvRo4fwvrwp1d3d3VWm8gfAPv/8c+F9VFQUA8B27Ngh7Pvll1+YiYmJ8H7ZsmXMwMCAPX78WNh38uRJJhKJhPVmHB0d2b59+1TyXrlyJfP09GSMMWF6/k2bNpX7MytJIpGwPXv2qOzz9PRkgYGBFX7G2dmZjRs3TnifmprKALAlS5aUqWvJNXJepU+fPmzmzJnlHpNKpQwAO3fuXKXORTSLWiREq/r27YucnBzExMQgMjISrVu3ho2NDfr06YOYmBjk5OTg3LlzcHJyQvPmzQEA169fx9ChQ+Hs7AxLS0t4e3sDgLDMaJcuXdC2bVuhK+T8+fNIT0/HqFGjAPBrkWdnZ6Nx48awsLAQXklJSSpdTC4uLrC0tBTe29vbC11oVdGpUydhu3gJ044dO6rsy8/PR1ZWlrDPyckJzZo1E957enpCqVQiISEBz58/x+PHjzFp0iSV8q9atapMF1npVkR58vLyynRrxcXF4e23365xvQAIP7OSZZ0yZcpry1WSqakpAKjcNyO6w1DbBSD1W8uWLdGsWTNEREQgIyMDffr0AcCvJ+3q6oqLFy8iIiIC/fr1AwDk5OTAx8cHPj4+2Lt3L5o0aYLk5GT4+vqioKBAOG9gYCD27duHBQsWYN++ffD19YW1tTUA/j6Kvb29yr2ZYg0bNhS2xWKxyjGO41SGx4pEojLdNuXd0C55Ho7jKtz3qqG3xWlKlmH79u3o0aOHSjoDAwOV9+bm5hWes5i1tXWZtb2LL9yvUtV6xcXFCccaNGjw2vOXVNzl2KRJkyp9jmgGBRKidX379sW5c+eQkZGBefPmCfv79OmDP/74A9HR0fjggw8AAPfu3cM///yDtWvXwtHREQDKvaE7duxYfP7554iNjcXvv/+O//u//xOOeXh4IC0tDYaGhnBxcal2uZs0aYLU1FThfVZWltqGqCYnJ+Pp06dwcHAAAERFRUEkEqF169awtbVF06ZN8ffffyMwMLDGeXXp0gV3795V2depUyecOXNG+LmrQ8uWLav92du3b0MsFqNDhw5qKw9RHwokROv69u2LqVOnorCwUGiRAHwg+fjjj5Gfny/caHdycoKRkRG+++47TJkyBbdv38bKlSvLnNPV1RW9evXCpEmTIJfLMXToUOFY//794enpiWHDhuE///kP2rRpg6dPn+LEiRMYNmxYpbqDAKBfv37YvXs3hgwZAisrKyxZsqRMi6C6TExMMH78eKxfvx5ZWVmYMWMGRo0aBTs7OwD8qLIZM2agQYMGGDhwIGQyGa5evYqMjAx8+umnVcrL19e3zE36ZcuW4e2330aLFi0wZswYyOVynDx5Ep999pla6ldScUslOzsbz58/R1xcHIyMjNC+fXshTWRkJLy8vCrVUiKaR/dIiNb17dsXeXl5aNmypdCvDvCB5OXLl2jRooXQ+mjSpAl2796N3377De3bt8fatWuxfv36cs8bGBiIGzduYPjw4SoXII7jcOLECbz11luYOHEiWrdujTFjxuDhw4cq+b/OwoUL8dZbb8Hf3x+DBg3CsGHD0KJFi2r+FFS1bNkSw4cPx6BBg+Dj4wM3NzeV4b0ffvghfvzxR+zevRsdO3ZEnz59sHv3bri6ulY5r3HjxuHu3btISEgQ9nl7e+O3337DkSNH0LlzZ/Tr1w+XL19WS91K69KlC7p06YLY2Fjs27cPXbp0waBBg1TS/PLLLwgODq6V/EnN0ZrthBB89tlnkEql2LZtm7aLUsbx48cxb9483Lx5E4aG1Imii6hFQgjB4sWL4ezsDIVCoe2ilJGTk4Ndu3ZRENFh1CIhhBBSI9QiIYQQUiMUSAghhNQIBRJCCCE1QoGEEEJIjVAgIYQQUiMUSAghhNQIBRJCCCE1QoGEEEJIjVAgIYQQUiP/D8GM8RfIzC/lAAAAAElFTkSuQmCC", - "text/plain": [ - "| \n", - " | filename | \n", - "rays_present | \n", - "approx_split | \n", - "Diad1_pos | \n", - "Diad2_pos | \n", - "HB1_pos | \n", - "HB2_pos | \n", - "C13_pos | \n", - "Diad1_abs_prom | \n", - "Diad2_abs_prom | \n", - "... | \n", - "HB2_height | \n", - "C13_height | \n", - "Diad1_height | \n", - "HB1_height | \n", - "Diad1_Median_Bck | \n", - "Diad2_Median_Bck | \n", - "C13_HB2_abs_prom_ratio | \n", - "Diad2_HB2_Valley_prom | \n", - "HB1_prom/std_betweendiads | \n", - "HB2_prom/std_betweendiads | \n", - "
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| 1 | \n", - "K21-59-FI#2 | \n", - "103.011311 | \n", - "0.011688 | \n", - "0.016082 | \n", - "1286.157455 | \n", - "0.009950 | \n", - "227.655256 | \n", - "1286.157505 | \n", - "198.574397 | \n", - "0.409721 | \n", - "... | \n", - "October | \n", - "28.0 | \n", - "12.068 | \n", - "45.0 | \n", - "5.0 | \n", - "50.0 | \n", - "['0h', '3m', '47s'] | \n", - "12:19:53 PM\\n | \n", - "44393.0 | \n", - "1325.004 | \n", - "
| 2 | \n", - "K21-59-FI#3 | \n", - "103.046227 | \n", - "0.003908 | \n", - "0.005329 | \n", - "1286.074215 | \n", - "0.003398 | \n", - "570.233153 | \n", - "1286.074265 | \n", - "580.899302 | \n", - "0.422487 | \n", - "... | \n", - "October | \n", - "28.0 | \n", - "12.064 | \n", - "45.0 | \n", - "5.0 | \n", - "50.0 | \n", - "['0h', '3m', '47s'] | \n", - "12:32:26 PM\\n | \n", - "45146.0 | \n", - "1325.004 | \n", - "
| 3 | \n", - "K21-61-FI#1-rep1_CRR_DiadFit | \n", - "103.312261 | \n", - "0.031987 | \n", - "0.042104 | \n", - "1285.431180 | \n", - "0.029323 | \n", - "66.226323 | \n", - "1285.431180 | \n", - "80.426681 | \n", - "0.570436 | \n", - "... | \n", - "October | \n", - "28.0 | \n", - "12.046 | \n", - "45.0 | \n", - "5.0 | \n", - "50.0 | \n", - "['0h', '3m', '47s'] | \n", - "12:45:44 PM\\n | \n", - "45944.0 | \n", - "1325.004 | \n", - "
| 4 | \n", - "K21-61-FI#1-rep2_CRR_DiadFit | \n", - "103.305046 | \n", - "0.003063 | \n", - "0.004135 | \n", - "1285.435753 | \n", - "0.002712 | \n", - "607.647353 | \n", - "1285.435803 | \n", - "895.504629 | \n", - "0.568594 | \n", - "... | \n", - "October | \n", - "28.0 | \n", - "12.030 | \n", - "45.0 | \n", - "5.0 | \n", - "50.0 | \n", - "['0h', '3m', '46s'] | \n", - "12:50:47 PM\\n | \n", - "46247.0 | \n", - "1325.004 | \n", - "
5 rows × 54 columns
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| 2 | \n", - "K21-59-FI#3 | \n", - "103.046227 | \n", - "0.003908 | \n", - "0.005329 | \n", - "1286.074215 | \n", - "0.003398 | \n", - "570.233153 | \n", - "1286.074265 | \n", - "580.899302 | \n", - "0.422487 | \n", - "... | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "
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| 4 | \n", - "K21-61-FI#1-rep2_CRR_DiadFit | \n", - "103.305046 | \n", - "0.003063 | \n", - "0.004135 | \n", - "1285.435753 | \n", - "0.002712 | \n", - "607.647353 | \n", - "1285.435803 | \n", - "895.504629 | \n", - "0.568594 | \n", - "... | \n", - "K21-61-FI#1-rep2.txt | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "1090.919723 | \n", - "900.825267 | \n", - "43.734455 | \n", - "0.38602 | \n", - "NaN | \n", - "
5 rows × 64 columns
\n", - "| \n", - " | filename | \n", - "filename | \n", - "Density g/cm3 | \n", - "σ Density g/cm3 | \n", - "σ Density g/cm3 (from Ne+peakfit) | \n", - "σ Density g/cm3 (from densimeter) | \n", - "Corrected_Splitting | \n", - "Corrected_Splitting_σ | \n", - "Corrected_Splitting_σ_Ne | \n", - "Corrected_Splitting_σ_peak_fit | \n", - "... | \n", - "Model_name | \n", - "Peak_Cent_Carb | \n", - "Peak_Area_Carb | \n", - "Peak_Height_Carb | \n", - "Carb_Diad_Ratio | \n", - "SO2_Diad_Ratio | \n", - "time | \n", - "preferred_values | \n", - "lower_values | \n", - "upper_values | \n", - "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", - "K21-59-FI#1_CRR_DiadFit | \n", - "K21-59-FI#1.txt | \n", - "0.033914 | \n", - "0.004195 | \n", - "0.001609 | \n", - "0.003875 | \n", - "102.835846 | \n", - "0.004061 | \n", - "0.000571 | \n", - "0.004029 | \n", - "... | \n", - "Spline | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "0.032879 | \n", - "43795 | \n", - "0.997845 | \n", - "0.997840 | \n", - "0.997851 | \n", - "
| 1 | \n", - "K21-59-FI#2 | \n", - "NaN | \n", - "0.015169 | \n", - "0.006073 | \n", - "0.004627 | \n", - "0.003934 | \n", - "102.788537 | \n", - "0.011676 | \n", - "0.000565 | \n", - "0.011688 | \n", - "... | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "44393 | \n", - "0.997837 | \n", - "0.997832 | \n", - "0.997843 | \n", - "
| 2 | \n", - "K21-59-FI#3 | \n", - "NaN | \n", - "0.028598 | \n", - "0.004191 | \n", - "0.001561 | \n", - "0.003890 | \n", - "102.822428 | \n", - "0.003940 | \n", - "0.000558 | \n", - "0.003908 | \n", - "... | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "45146 | \n", - "0.997828 | \n", - "0.997823 | \n", - "0.997834 | \n", - "
| 3 | \n", - "K21-61-FI#1-rep1_CRR_DiadFit | \n", - "NaN | \n", - "0.133407 | \n", - "0.013223 | \n", - "0.012649 | \n", - "0.003855 | \n", - "103.086937 | \n", - "0.031922 | \n", - "0.000554 | \n", - "0.031987 | \n", - "... | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "NaN | \n", - "45944 | \n", - "0.997819 | \n", - "0.997814 | \n", - "0.997824 | \n", - "
| 4 | \n", - "K21-61-FI#1-rep2_CRR_DiadFit | \n", - "K21-61-FI#1-rep2.txt | \n", - "0.130418 | \n", - "0.004040 | \n", - "0.001230 | \n", - "0.003848 | \n", - "103.079394 | \n", - "0.003105 | \n", - "0.000551 | \n", - "0.003063 | \n", - "... | \n", - "NaN | \n", - "1090.919723 | \n", - "900.825267 | \n", - "43.734455 | \n", - "0.38602 | \n", - "NaN | \n", - "46247 | \n", - "0.997816 | \n", - "0.997810 | \n", - "0.997821 | \n", - "
5 rows × 89 columns
\n", - "| \n", - " | P_kbar | \n", - "P_MPa | \n", - "T_K | \n", - "CO2_dens_gcm3 | \n", - "
|---|---|---|---|---|
| 0 | \n", - "0.093190 | \n", - "9.319002 | \n", - "1423.15 | \n", - "0.033914 | \n", - "
| 1 | \n", - "0.041177 | \n", - "4.117742 | \n", - "1423.15 | \n", - "0.015169 | \n", - "
| 2 | \n", - "0.078309 | \n", - "7.830926 | \n", - "1423.15 | \n", - "0.028598 | \n", - "
| 3 | \n", - "0.392829 | \n", - "39.282919 | \n", - "1423.15 | \n", - "0.133407 | \n", - "
| 4 | \n", - "0.383182 | \n", - "38.318188 | \n", - "1423.15 | \n", - "0.130418 | \n", - "