diff --git "a/notebooks/benchmarking_process_discovery.ipynb" "b/notebooks/benchmarking_process_discovery.ipynb"
new file mode 100644--- /dev/null
+++ "b/notebooks/benchmarking_process_discovery.ipynb"
@@ -0,0 +1,1430 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "b7408494",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from scipy import spatial\n",
+    "from sklearn.metrics.pairwise import cosine_similarity\n",
+    "TEST='kendalltau'\n",
+    "DATA_SOURCE = 'Generated'\n",
+    "EXP_BASELINE = False\n",
+    "IMPUTE = False #If False Nan lines are dropped"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "ee0f1487",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Generated\n",
+      "kendalltau_GenED_nanDropped\n"
+     ]
+    }
+   ],
+   "source": [
+    "def get_output_file_name(test, data_source, exp_baseline, impute):    \n",
+    "    print(data_source)\n",
+    "    if data_source=='Real':\n",
+    "        data_source = 'BaselineED'\n",
+    "    else:\n",
+    "        if EXP_BASELINE:\n",
+    "            data_source = 'GenBaselineED'\n",
+    "        else:\n",
+    "            data_source = 'GenED'\n",
+    "    impute = 'imputed' if impute else 'nanDropped'\n",
+    "    return (\"_\".join([test, data_source, impute]))\n",
+    "print(get_output_file_name(TEST, DATA_SOURCE, EXP_BASELINE, IMPUTE))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4ff27cb8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(467, 8) (26, 8)\n",
+      "(493, 9)\n",
+      "['BPIC12' 'BPIC13cp' 'BPIC13inc' 'BPIC13op' 'BPIC14dc_p' 'BPIC14di_p'\n",
+      " 'BPIC14dia_p' 'BPIC15f1' 'BPIC15f2' 'BPIC15f3' 'BPIC15f4' 'BPIC15f5'\n",
+      " 'BPIC16c_p' 'BPIC16wm_p' 'BPIC17' 'BPIC17ol' 'BPIC19' 'BPIC20a' 'BPIC20b'\n",
+      " 'BPIC20c' 'BPIC20d' 'BPIC20e' 'HD' 'RTFMP' 'RWABOCSL' 'SEPSIS'\n",
+      " '2_rmcv_rt10v_genELtask_40_03_06' '2_enself_rutpt_genELtask_25_02_02'\n",
+      " '2_rt10v_rutpt_genELtask_39_03_05' '2_ense_rt10v_genELtask_32_02_09'\n",
+      " '2_enseef_rt10v_genELtask_41_03_07' '2_enseef_rt10v_genELtask_18_01_06'\n",
+      " '2_ense_rt10v_genELtask_40_03_06' '2_enve_rt10v_genELtask_45_04_00'\n",
+      " '2_ense_rt10v_genELtask_21_01_09' '2_enself_rt10v_genELtask_10_00_09'\n",
+      " '2_enseef_rt10v_genELtask_20_01_08' '2_enself_enve_genELtask_42_03_08'\n",
+      " '2_enself_rmcv_genELtask_36_03_02' '2_ense_enseef_genELtask_60_05_04'\n",
+      " '2_enseef_rmcv_genELtask_6_00_05' '2_enself_rutpt_genELtask_5_00_04'\n",
+      " '2_enve_rt10v_genELtask_69_06_02' '2_enve_rutpt_genELtask_53_04_08'\n",
+      " '2_enself_rt10v_genELtask_22_01_10' '2_enseef_enve_genELtask_63_05_07'\n",
+      " '2_enseef_rutpt_genELtask_26_02_03' '2_enself_rutpt_genELtask_20_01_08'\n",
+      " '2_enseef_rt10v_genELtask_30_02_07' '2_enseef_enself_genELtask_60_05_04'\n",
+      " '2_enve_rmcv_genELtask_48_04_03' '2_enve_rutpt_genELtask_74_06_07'\n",
+      " '2_ense_rt10v_genELtask_45_04_00' '2_rmcv_rutpt_genELtask_56_05_00'\n",
+      " '2_enself_rt10v_genELtask_20_01_08' '2_ense_enself_genELtask_82_07_04'\n",
+      " '2_ense_enself_genELtask_70_06_03' '2_ense_enseef_genELtask_24_02_01'\n",
+      " '2_enself_enve_genELtask_17_01_05' '2_enve_rmcv_genELtask_69_06_02'\n",
+      " '2_ense_rutpt_genELtask_72_06_05' '2_ense_enve_genELtask_65_05_09'\n",
+      " '2_ense_enseef_genELtask_82_07_04' '2_rmcv_rt10v_genELtask_14_01_02'\n",
+      " '2_ense_rt10v_genELtask_53_04_08' '2_enseef_rutpt_genELtask_25_02_02'\n",
+      " '2_enseef_rt10v_genELtask_57_05_01' '2_rt10v_rutpt_genELtask_82_07_04'\n",
+      " '2_rt10v_rutpt_genELtask_27_02_04' '2_enve_rt10v_genELtask_47_04_02'\n",
+      " '2_enself_rutpt_genELtask_22_01_10' '2_ense_enve_genELtask_2_00_01'\n",
+      " '2_enseef_rutpt_genELtask_14_01_02' '2_enve_rutpt_genELtask_64_05_08'\n",
+      " '2_enve_rt10v_genELtask_77_06_10' '2_enve_rmcv_genELtask_49_04_04'\n",
+      " '2_enseef_enve_genELtask_3_00_02' '2_enseef_enself_genELtask_13_01_01'\n",
+      " '2_enve_rmcv_genELtask_6_00_05' '2_enve_rt10v_genELtask_96_08_07'\n",
+      " '2_ense_enseef_genELtask_58_05_02' '2_enself_rutpt_genELtask_19_01_07'\n",
+      " '2_enseef_enself_genELtask_2_00_01' '2_enself_rt10v_genELtask_31_02_08'\n",
+      " '2_ense_enve_genELtask_75_06_08' '2_enve_rmcv_genELtask_47_04_02'\n",
+      " '2_enseef_rt10v_genELtask_42_03_08' '2_enseef_rmcv_genELtask_56_05_00'\n",
+      " '2_enve_rutpt_genELtask_79_07_01' '2_enseef_enve_genELtask_28_02_05'\n",
+      " '2_ense_enself_genELtask_2_00_01' '2_ense_enself_genELtask_46_04_01'\n",
+      " '2_ense_rmcv_genELtask_59_05_03' '2_enseef_rutpt_genELtask_38_03_04'\n",
+      " '2_ense_enseef_genELtask_71_06_04' '2_enseef_rutpt_genELtask_16_01_04'\n",
+      " '2_enve_rt10v_genELtask_17_01_05' '2_enve_rmcv_genELtask_68_06_01'\n",
+      " '2_enseef_rmcv_genELtask_15_01_03' '2_enseef_rutpt_genELtask_40_03_06'\n",
+      " '2_ense_rt10v_genELtask_71_06_04' '2_rt10v_rutpt_genELtask_51_04_06'\n",
+      " '2_enseef_rmcv_genELtask_7_00_06' '2_ense_enve_genELtask_27_02_04'\n",
+      " '2_enseef_rmcv_genELtask_26_02_03' '2_enseef_enve_genELtask_42_03_08'\n",
+      " '2_enseef_rt10v_genELtask_22_01_10' '2_enve_rutpt_genELtask_3_00_02'\n",
+      " '2_ense_rutpt_genELtask_48_04_03' '2_enseef_rmcv_genELtask_24_02_01'\n",
+      " '2_rmcv_rt10v_genELtask_43_03_09' '2_ense_enve_genELtask_17_01_05'\n",
+      " '2_enve_rmcv_genELtask_57_05_01' '2_ense_enve_genELtask_41_03_07'\n",
+      " '2_ense_enve_genELtask_31_02_08' '2_enve_rutpt_genELtask_88_07_10'\n",
+      " '2_enseef_rt10v_genELtask_19_01_07' '2_rmcv_rutpt_genELtask_27_02_04'\n",
+      " '2_rmcv_rutpt_genELtask_38_03_04' '2_ense_enself_genELtask_58_05_02'\n",
+      " '2_ense_enve_genELtask_74_06_07' '2_enself_enve_genELtask_19_01_07'\n",
+      " '2_ense_rutpt_genELtask_49_04_04' '2_ense_rt10v_genELtask_55_04_10'\n",
+      " '2_enve_rmcv_genELtask_35_03_01' '2_enve_rutpt_genELtask_77_06_10'\n",
+      " '2_ense_rt10v_genELtask_49_04_04' '2_ense_enve_genELtask_37_03_03'\n",
+      " '2_enve_rutpt_genELtask_92_08_03' '2_rt10v_rutpt_genELtask_72_06_05'\n",
+      " '2_ense_rt10v_genELtask_22_01_10' '2_enseef_rt10v_genELtask_12_01_00'\n",
+      " '2_ense_enve_genELtask_14_01_02' '2_enseef_enve_genELtask_30_02_07'\n",
+      " '2_enself_rt10v_genELtask_4_00_03' '2_ense_rt10v_genELtask_60_05_04'\n",
+      " '2_enve_rt10v_genELtask_6_00_05' '2_rt10v_rutpt_genELtask_1_00_00'\n",
+      " '2_ense_rmcv_genELtask_67_06_00' '2_enve_rmcv_genELtask_80_07_02'\n",
+      " '2_enself_rmcv_genELtask_2_00_01' '2_ense_rt10v_genELtask_72_06_05'\n",
+      " '2_enve_rt10v_genELtask_73_06_06' '2_rt10v_rutpt_genELtask_32_02_09'\n",
+      " '2_ense_rt10v_genELtask_62_05_06' '2_enseef_rt10v_genELtask_17_01_05'\n",
+      " '2_ense_rt10v_genELtask_70_06_03' '2_enself_rt10v_genELtask_18_01_06'\n",
+      " '2_ense_rutpt_genELtask_1_00_00' '2_rt10v_rutpt_genELtask_71_06_04'\n",
+      " '2_rmcv_rutpt_genELtask_13_01_01' '2_enve_rutpt_genELtask_61_05_05'\n",
+      " '2_rt10v_rutpt_genELtask_22_01_10' '2_enseef_enself_genELtask_1_00_00'\n",
+      " '2_ense_enve_genELtask_76_06_09' '2_enseef_enve_genELtask_52_04_07'\n",
+      " '2_rmcv_rt10v_genELtask_19_01_07' '2_enve_rt10v_genELtask_108_09_08'\n",
+      " '2_enself_rutpt_genELtask_44_03_10' '2_enself_rt10v_genELtask_40_03_06'\n",
+      " '2_ense_rt10v_genELtask_31_02_08' '2_rt10v_rutpt_genELtask_30_02_07'\n",
+      " '2_enself_enve_genELtask_7_00_06' '2_rmcv_rutpt_genELtask_20_01_08'\n",
+      " '2_enve_rt10v_genELtask_90_08_01' '2_enself_enve_genELtask_2_00_01'\n",
+      " '2_enve_rt10v_genELtask_57_05_01' '2_ense_rmcv_genELtask_48_04_03'\n",
+      " '2_enve_rutpt_genELtask_62_05_06' '2_ense_rt10v_genELtask_52_04_07'\n",
+      " '2_ense_rt10v_genELtask_69_06_02' '2_enseef_enve_genELtask_43_03_09'\n",
+      " '2_enself_rt10v_genELtask_36_03_02' '2_ense_rutpt_genELtask_13_01_01'\n",
+      " '2_rmcv_rt10v_genELtask_17_01_05' '2_ense_rmcv_genELtask_25_02_02'\n",
+      " '2_enseef_rmcv_genELtask_13_01_01' '2_rt10v_rutpt_genELtask_21_01_09'\n",
+      " '2_ense_rutpt_genELtask_46_04_01' '2_ense_enseef_genELtask_59_05_03'\n",
+      " '2_enve_rt10v_genELtask_74_06_07' '2_enseef_rutpt_genELtask_54_04_09'\n",
+      " '2_enve_rt10v_genELtask_76_06_09' '2_enve_rutpt_genELtask_68_06_01'\n",
+      " '2_ense_rutpt_genELtask_73_06_06' '2_rmcv_rt10v_genELtask_48_04_03'\n",
+      " '2_enseef_enself_genELtask_37_03_03' '2_ense_rutpt_genELtask_75_06_08'\n",
+      " '2_enve_rutpt_genELtask_83_07_05' '2_ense_rt10v_genELtask_64_05_08'\n",
+      " '2_ense_rmcv_genELtask_16_01_04' '2_enself_rutpt_genELtask_13_01_01'\n",
+      " '2_enself_rutpt_genELtask_3_00_02' '2_enself_rmcv_genELtask_15_01_03'\n",
+      " '2_ense_rutpt_genELtask_74_06_07' '2_enve_rutpt_genELtask_93_08_04'\n",
+      " '2_ense_rt10v_genELtask_42_03_08' '2_enseef_enve_genELtask_64_05_08'\n",
+      " '2_ense_enve_genELtask_63_05_07' '2_ense_rt10v_genELtask_47_04_02'\n",
+      " '2_enve_rutpt_genELtask_102_09_02' '2_enself_rt10v_genELtask_46_04_01'\n",
+      " '2_enseef_rutpt_genELtask_55_04_10' '2_enve_rmcv_genELtask_70_06_03'\n",
+      " '2_enself_rmcv_genELtask_7_00_06' '2_enself_enve_genELtask_54_04_09'\n",
+      " '2_enve_rutpt_genELtask_65_05_09' '2_enseef_rt10v_genELtask_27_02_04'\n",
+      " '2_enself_rt10v_genELtask_21_01_09' '2_ense_rutpt_genELtask_33_02_10'\n",
+      " '2_ense_rt10v_genELtask_68_06_01' '2_enself_rt10v_genELtask_14_01_02'\n",
+      " '2_enseef_rutpt_genELtask_12_01_00' '2_ense_rmcv_genELtask_6_00_05'\n",
+      " '2_ense_rutpt_genELtask_12_01_00' '2_enve_rmcv_genELtask_7_00_06'\n",
+      " '2_ense_rt10v_genELtask_63_05_07' '2_enseef_rutpt_genELtask_53_04_08'\n",
+      " '2_ense_rutpt_genELtask_65_05_09' '2_enself_rmcv_genELtask_6_00_05'\n",
+      " '2_ense_rutpt_genELtask_58_05_02' '2_ense_enve_genELtask_50_04_05'\n",
+      " '2_enve_rmcv_genELtask_89_08_00' '2_ense_enself_genELtask_67_06_00'\n",
+      " '2_ense_rt10v_genELtask_12_01_00' '2_ense_rt10v_genELtask_74_06_07'\n",
+      " '2_enself_enve_genELtask_43_03_09' '2_ense_rutpt_genELtask_62_05_06'\n",
+      " '2_ense_enseef_genELtask_47_04_02' '2_enself_enve_genELtask_53_04_08'\n",
+      " '2_enseef_rt10v_genELtask_35_03_01' '2_rt10v_rutpt_genELtask_41_03_07'\n",
+      " '2_ense_rt10v_genELtask_43_03_09' '2_enseef_rutpt_genELtask_1_00_00'\n",
+      " '2_ense_rmcv_genELtask_7_00_06' '2_rt10v_rutpt_genELtask_62_05_06'\n",
+      " '2_ense_enve_genELtask_61_05_05' '2_enself_rt10v_genELtask_35_03_01'\n",
+      " '2_rt10v_rutpt_genELtask_91_08_02' '2_enself_rmcv_genELtask_17_01_05'\n",
+      " '2_enve_rutpt_genELtask_46_04_01' '2_enseef_enve_genELtask_54_04_09'\n",
+      " '2_ense_rutpt_genELtask_54_04_09' '2_enseef_enve_genELtask_32_02_09'\n",
+      " '2_enve_rutpt_genELtask_44_03_10' '2_enself_rmcv_genELtask_14_01_02'\n",
+      " '2_rmcv_rt10v_genELtask_27_02_04' '2_rmcv_rutpt_genELtask_25_02_02'\n",
+      " '2_enself_enve_genELtask_9_00_08' '2_rmcv_rt10v_genELtask_37_03_03'\n",
+      " '2_rmcv_rt10v_genELtask_34_03_00' '2_rmcv_rutpt_genELtask_39_03_05'\n",
+      " '2_ense_enself_genELtask_24_02_01' '2_enseef_rutpt_genELtask_66_05_10'\n",
+      " '2_ense_rt10v_genELtask_33_02_10' '2_enve_rutpt_genELtask_70_06_03'\n",
+      " '2_ense_rmcv_genELtask_37_03_03' '2_ense_rutpt_genELtask_25_02_02'\n",
+      " '2_ense_rutpt_genELtask_26_02_03' '2_enseef_enve_genELtask_29_02_06'\n",
+      " '2_enseef_rt10v_genELtask_6_00_05' '2_ense_rt10v_genELtask_36_03_02'\n",
+      " '2_ense_rt10v_genELtask_23_02_00' '2_rmcv_rt10v_genELtask_12_01_00'\n",
+      " '2_enve_rt10v_genELtask_109_09_09' '2_enve_rt10v_genELtask_80_07_02'\n",
+      " '2_enve_rutpt_genELtask_48_04_03' '2_enve_rt10v_genELtask_64_05_08'\n",
+      " '2_rt10v_rutpt_genELtask_49_04_04' '2_enself_rmcv_genELtask_24_02_01'\n",
+      " '2_ense_enself_genELtask_47_04_02' '2_enseef_rutpt_genELtask_2_00_01'\n",
+      " '2_enseef_rt10v_genELtask_21_01_09' '2_enve_rutpt_genELtask_40_03_06'\n",
+      " '2_ense_rt10v_genELtask_57_05_01' '2_ense_enseef_genELtask_1_00_00'\n",
+      " '2_ense_rutpt_genELtask_35_03_01' '2_ense_rutpt_genELtask_53_04_08'\n",
+      " '2_enve_rmcv_genELtask_90_08_01' '2_rmcv_rt10v_genELtask_29_02_06'\n",
+      " '2_enseef_enve_genELtask_31_02_08' '2_ense_enve_genELtask_42_03_08'\n",
+      " '2_ense_enve_genELtask_73_06_06' '2_ense_enve_genELtask_43_03_09'\n",
+      " '2_rt10v_rutpt_genELtask_42_03_08' '2_rmcv_rutpt_genELtask_40_03_06'\n",
+      " '2_ense_rutpt_genELtask_60_05_04' '2_rmcv_rt10v_genELtask_54_04_09'\n",
+      " '2_ense_enve_genELtask_52_04_07' '2_rmcv_rt10v_genELtask_39_03_05'\n",
+      " '2_rt10v_rutpt_genELtask_81_07_03' '2_enve_rmcv_genELtask_100_09_00'\n",
+      " '2_rmcv_rutpt_genELtask_45_04_00' '2_ense_rutpt_genELtask_64_05_08'\n",
+      " '2_ense_enve_genELtask_38_03_04' '2_rmcv_rt10v_genELtask_55_04_10'\n",
+      " '2_enve_rutpt_genELtask_55_04_10' '2_enve_rt10v_genELtask_86_07_08'\n",
+      " '2_ense_enseef_genELtask_36_03_02' '2_ense_enve_genELtask_29_02_06'\n",
+      " '2_ense_enve_genELtask_86_07_08' '2_ense_rutpt_genELtask_88_07_10'\n",
+      " '2_ense_enseef_genELtask_83_07_05' '2_ense_enseef_genELtask_25_02_02'\n",
+      " '2_rmcv_rt10v_genELtask_38_03_04' '2_ense_rutpt_genELtask_59_05_03'\n",
+      " '2_enve_rutpt_genELtask_81_07_03' '2_enve_rutpt_genELtask_60_05_04'\n",
+      " '2_enve_rt10v_genELtask_60_05_04' '2_rmcv_rutpt_genELtask_11_00_10'\n",
+      " '2_rmcv_rutpt_genELtask_26_02_03' '2_enseef_rmcv_genELtask_25_02_02'\n",
+      " '2_enself_rt10v_genELtask_7_00_06' '2_rmcv_rt10v_genELtask_2_00_01'\n",
+      " '2_enseef_rmcv_genELtask_37_03_03' '2_ense_rt10v_genELtask_6_00_05'\n",
+      " '2_enve_rutpt_genELtask_71_06_04' '2_rmcv_rutpt_genELtask_14_01_02'\n",
+      " '2_ense_enself_genELtask_78_07_00' '2_enve_rmcv_genELtask_40_03_06'\n",
+      " '2_rmcv_rt10v_genELtask_20_01_08' '2_ense_rmcv_genELtask_46_04_01'\n",
+      " '2_ense_rmcv_genELtask_18_01_06' '2_enseef_rutpt_genELtask_33_02_10'\n",
+      " '2_ense_enseef_genELtask_70_06_03' '2_enve_rmcv_genELtask_37_03_03'\n",
+      " '2_enseef_enself_genELtask_48_04_03' '2_rt10v_rutpt_genELtask_102_09_02'\n",
+      " '2_ense_rutpt_genELtask_77_06_10' '2_enself_rutpt_genELtask_4_00_03'\n",
+      " '2_ense_rutpt_genELtask_39_03_05' '2_enseef_enve_genELtask_21_01_09'\n",
+      " '2_rt10v_rutpt_genELtask_38_03_04' '2_ense_enve_genELtask_30_02_07'\n",
+      " '2_enve_rutpt_genELtask_99_08_10' '2_ense_enve_genELtask_40_03_06'\n",
+      " '2_enself_enve_genELtask_6_00_05' '2_enself_rutpt_genELtask_2_00_01'\n",
+      " '2_enself_enve_genELtask_1_00_00' '2_enve_rmcv_genELtask_104_09_04'\n",
+      " '2_enve_rutpt_genELtask_86_07_08' '2_rt10v_rutpt_genELtask_101_09_01'\n",
+      " '2_enve_rt10v_genELtask_91_08_02' '2_ense_enself_genELtask_81_07_03'\n",
+      " '2_ense_rutpt_genELtask_51_04_06' '2_enve_rt10v_genELtask_75_06_08'\n",
+      " '2_enself_rmcv_genELtask_34_03_00' '2_enseef_rt10v_genELtask_23_02_00'\n",
+      " '2_enseef_enve_genELtask_17_01_05' '2_ense_rutpt_genELtask_43_03_09'\n",
+      " '2_ense_enseef_genELtask_48_04_03' '2_enve_rt10v_genELtask_46_04_01'\n",
+      " '2_enve_rmcv_genELtask_92_08_03' '2_ense_enve_genELtask_1_00_00'\n",
+      " '2_ense_rutpt_genELtask_66_05_10' '2_enseef_enve_genELtask_16_01_04'\n",
+      " '2_enve_rmcv_genELtask_58_05_02' '2_rt10v_rutpt_genELtask_90_08_01'\n",
+      " '2_enself_enve_genELtask_29_02_06' '2_enve_rmcv_genELtask_79_07_01'\n",
+      " '2_ense_rutpt_genELtask_52_04_07' '2_rt10v_rutpt_genELtask_79_07_01'\n",
+      " '2_ense_rutpt_genELtask_87_07_09' '2_ense_rutpt_genELtask_55_04_10'\n",
+      " '2_enve_rutpt_genELtask_38_03_04' '2_enself_enve_genELtask_31_02_08'\n",
+      " '2_enself_rutpt_genELtask_55_04_10' '2_rmcv_rutpt_genELtask_35_03_01'\n",
+      " '2_enseef_rt10v_genELtask_46_04_01' '2_enve_rutpt_genELtask_57_05_01'\n",
+      " '2_rmcv_rutpt_genELtask_57_05_01' '2_enve_rt10v_genELtask_71_06_04'\n",
+      " '2_ense_enself_genELtask_68_06_01' '2_ense_rt10v_genELtask_58_05_02'\n",
+      " '2_enve_rt10v_genELtask_95_08_06' '2_enseef_rt10v_genELtask_47_04_02'\n",
+      " '2_ense_rt10v_genELtask_79_07_01' '2_ense_rt10v_genELtask_50_04_05'\n",
+      " '2_ense_rutpt_genELtask_71_06_04' '2_ense_enself_genELtask_36_03_02'\n",
+      " '2_enseef_enself_genELtask_59_05_03' '2_enseef_enve_genELtask_2_00_01'\n",
+      " '2_ense_rmcv_genELtask_57_05_01' '2_enself_rutpt_genELtask_21_01_09'\n",
+      " '2_enself_rutpt_genELtask_1_00_00' '2_enseef_rutpt_genELtask_44_03_10'\n",
+      " '2_enseef_enself_genELtask_36_03_02' '2_enve_rt10v_genELtask_97_08_08'\n",
+      " '2_ense_rmcv_genELtask_78_07_00' '2_ense_enseef_genELtask_69_06_02'\n",
+      " '2_rt10v_rutpt_genELtask_68_06_01' '2_ense_enve_genELtask_62_05_06'\n",
+      " '2_ense_enseef_genELtask_13_01_01' '2_ense_enseef_genELtask_35_03_01'\n",
+      " '2_enself_enve_genELtask_3_00_02' '2_ense_rmcv_genELtask_58_05_02'\n",
+      " '2_enve_rmcv_genELtask_78_07_00' '2_ense_enve_genELtask_13_01_01'\n",
+      " '2_enve_rt10v_genELtask_82_07_04' '2_ense_enve_genELtask_48_04_03'\n",
+      " '2_enself_rmcv_genELtask_3_00_02' '2_rt10v_rutpt_genELtask_52_04_07'\n",
+      " '2_rt10v_rutpt_genELtask_61_05_05' '2_enseef_enself_genELtask_49_04_04'\n",
+      " '2_enseef_enve_genELtask_1_00_00' '2_enve_rt10v_genELtask_87_07_09'\n",
+      " '2_enself_rt10v_genELtask_5_00_04' '2_enself_rutpt_genELtask_15_01_03'\n",
+      " '2_ense_rt10v_genELtask_61_05_05' '2_ense_rutpt_genELtask_47_04_02'\n",
+      " '2_enve_rt10v_genELtask_84_07_06' '2_enve_rutpt_genELtask_91_08_02'\n",
+      " '2_enve_rt10v_genELtask_85_07_07' '2_enseef_enself_genELtask_24_02_01'\n",
+      " '2_enve_rutpt_genELtask_66_05_10' '2_enve_rt10v_genELtask_56_05_00'\n",
+      " '2_enseef_rutpt_genELtask_13_01_01' '2_enseef_rt10v_genELtask_29_02_06'\n",
+      " '2_enve_rt10v_genELtask_26_02_03' '2_ense_rutpt_genELtask_24_02_01'\n",
+      " '2_enve_rutpt_genELtask_1_00_00' '2_enve_rutpt_genELtask_82_07_04'\n",
+      " '2_enve_rt10v_genELtask_102_09_02' '2_enself_rutpt_genELtask_42_03_08'\n",
+      " '2_ense_rmcv_genELtask_15_01_03' '2_ense_enve_genELtask_18_01_06'\n",
+      " '2_enve_rmcv_genELtask_81_07_03' '2_enve_rt10v_genELtask_83_07_05'\n",
+      " '2_ense_enve_genELtask_53_04_08' '2_enseef_rmcv_genELtask_45_04_00'\n",
+      " '2_enseef_rutpt_genELtask_27_02_04' '2_enve_rt10v_genELtask_48_04_03'\n",
+      " '2_enve_rutpt_genELtask_76_06_09' '2_ense_rutpt_genELtask_63_05_07'\n",
+      " '2_ense_rmcv_genELtask_17_01_05' '2_rt10v_rutpt_genELtask_34_03_00'\n",
+      " '2_ense_enve_genELtask_16_01_04' '2_ense_enve_genELtask_51_04_06'\n",
+      " '2_enve_rutpt_genELtask_104_09_04' '2_enseef_rmcv_genELtask_14_01_02'\n",
+      " '2_enseef_rutpt_genELtask_36_03_02' '2_enself_rmcv_genELtask_45_04_00'\n",
+      " '2_rmcv_rt10v_genELtask_15_01_03' '2_ense_rmcv_genELtask_35_03_01'\n",
+      " '2_enseef_enve_genELtask_27_02_04' '2_ense_enve_genELtask_3_00_02'\n",
+      " '2_ense_rmcv_genELtask_47_04_02' '2_enseef_rutpt_genELtask_15_01_03'\n",
+      " '2_ense_enself_genELtask_25_02_02' '2_enseef_rt10v_genELtask_43_03_09'\n",
+      " '2_enseef_enve_genELtask_18_01_06' '2_enve_rutpt_genELtask_90_08_01'\n",
+      " '2_ense_rt10v_genELtask_41_03_07' '2_ense_enve_genELtask_85_07_07'\n",
+      " '2_enve_rutpt_genELtask_63_05_07' '2_enself_rutpt_genELtask_6_00_05'\n",
+      " '2_enseef_rutpt_genELtask_30_02_07' '2_enseef_rmcv_genELtask_36_03_02'\n",
+      " '2_rmcv_rutpt_genELtask_15_01_03' '2_ense_enself_genELtask_1_00_00'\n",
+      " '2_rt10v_rutpt_genELtask_36_03_02' '2_enself_rutpt_genELtask_16_01_04'\n",
+      " '2_enself_rt10v_genELtask_13_01_01' '2_ense_rmcv_genELtask_36_03_02'\n",
+      " '2_enself_rmcv_genELtask_13_01_01' '2_rt10v_rutpt_genELtask_46_04_01'\n",
+      " '2_enseef_enve_genELtask_53_04_08' '2_ense_enve_genELtask_64_05_08'\n",
+      " '2_enself_rt10v_genELtask_6_00_05' '2_ense_rutpt_genELtask_76_06_09'\n",
+      " '2_enve_rt10v_genELtask_88_07_10' '2_ense_rutpt_genELtask_61_05_05'\n",
+      " '2_enve_rmcv_genELtask_91_08_02' '2_enseef_rutpt_genELtask_37_03_03'\n",
+      " '2_ense_rmcv_genELtask_26_02_03' '2_enself_enve_genELtask_32_02_09'\n",
+      " '2_rmcv_rutpt_genELtask_22_01_10' '2_enseef_enve_genELtask_15_01_03'\n",
+      " '2_enve_rutpt_genELtask_98_08_09' '2_ense_enself_genELtask_35_03_01'\n",
+      " '2_ense_rt10v_genELtask_25_02_02' '2_rt10v_rutpt_genELtask_80_07_02'\n",
+      " '2_rt10v_rutpt_genELtask_92_08_03' '2_enve_rt10v_genELtask_23_02_00'\n",
+      " '2_enself_rt10v_genELtask_8_00_07' '2_enseef_enve_genELtask_19_01_07'\n",
+      " '2_ense_rt10v_genELtask_51_04_06' '2_enseef_rt10v_genELtask_11_00_10'\n",
+      " '2_rmcv_rt10v_genELtask_67_06_00' '2_ense_rutpt_genELtask_36_03_02'\n",
+      " '2_enve_rt10v_genELtask_79_07_01' '2_enve_rt10v_genELtask_72_06_05'\n",
+      " '2_enself_rmcv_genELtask_25_02_02']\n"
+     ]
+    }
+   ],
+   "source": [
+    "## LOAD FEATURE FILES\n",
+    "#bpi_ft = pd.read_csv(\"../data/34_bpic_features.csv\").sort_values('log')\n",
+    "bpi_ft = pd.read_csv(\"../data/baseline_ED_feat.csv\").sort_values('log')\n",
+    "\n",
+    "#gen_ft =pd.read_csv(\"../output/generated/instance_selection_feat.csv\")\n",
+    "gen_ft = pd.read_csv(\"../data/GenED_feat.csv\")\n",
+    "if EXP_BASELINE:\n",
+    "    gen_ft = pd.read_csv(\"../data/GenBaseline_ED_feat.csv\")\n",
+    "    gen_ft['log']=gen_ft.apply(lambda x: \"Gen\"+x['log'], axis=1)\n",
+    "\n",
+    "#print(gen_ft['log'].unique())\n",
+    "\n",
+    "paper_cols = [\"log\",\"ratio_unique_traces_per_trace\", \"ratio_most_common_variant\", 'ratio_top_10_variants', 'epa_normalized_variant_entropy', 'epa_normalized_sequence_entropy', 'epa_normalized_sequence_entropy_linear_forgetting', 'epa_normalized_sequence_entropy_exponential_forgetting'] \n",
+    "bpi_ft= bpi_ft[paper_cols]\n",
+    "print(gen_ft.shape, bpi_ft.shape)\n",
+    "#print(gen_ft.columns == df.columns)\n",
+    "bpi_ft['source']='Real'\n",
+    "gen_ft['source']='Generated'\n",
+    "\n",
+    "\n",
+    "#if EXP_BASELINE:\n",
+    "#    gen_ft['log']=gen_ft.apply(lambda x: \"Gen\"+x['log'], axis=1)\n",
+    "both_df = pd.concat([bpi_ft, gen_ft])\n",
+    "#both_df['log']=both_df.apply(lambda x: x['log'].replace(\".xes\",\"\"), axis=1)\n",
+    "#both_df['log']=both_df.apply(lambda x: x['log'].replace(\"_processed\",\"\"), axis=1)\n",
+    "print(both_df.shape)\n",
+    "print(both_df['log'].unique())\n",
+    "feature_logs = both_df['log'].unique()\n",
+    "#print(feature_logs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d3d0e83b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(432, 19) (17, 19)\n",
+      "(449, 17)\n",
+      "['BPIC13cp' 'BPIC13inc' 'BPIC13op' 'BPIC14dc_p' 'BPIC14di_p' 'BPIC16c_p'\n",
+      " 'BPIC16wm_p' 'BPIC17ol' 'BPIC20a' 'BPIC20b' 'BPIC20c' 'BPIC20d' 'BPIC20e'\n",
+      " 'HD' 'RTFMP' 'RWABOCSL' 'SEPSIS' '2_ense_rmcv_genELtask_67_06_00'\n",
+      " '2_enself_rmcv_genELtask_13_01_01' '2_rt10v_rutpt_genELtask_1_00_00'\n",
+      " '2_ense_enve_genELtask_2_00_01' '2_rmcv_rutpt_genELtask_35_03_01'\n",
+      " '2_enseef_rutpt_genELtask_30_02_07' '2_enve_rutpt_genELtask_98_08_09'\n",
+      " '2_ense_enve_genELtask_27_02_04' '2_rmcv_rutpt_genELtask_40_03_06'\n",
+      " '2_enve_rmcv_genELtask_57_05_01' '2_ense_rutpt_genELtask_13_01_01'\n",
+      " '2_enself_rutpt_genELtask_6_00_05' '2_enself_enve_genELtask_1_00_00'\n",
+      " '2_ense_enve_genELtask_75_06_08' '2_ense_rutpt_genELtask_63_05_07'\n",
+      " '2_ense_enseef_genELtask_13_01_01' '2_enve_rt10v_genELtask_87_07_09'\n",
+      " '2_enseef_rmcv_genELtask_26_02_03' '2_enseef_rmcv_genELtask_7_00_06'\n",
+      " '2_enseef_rutpt_genELtask_66_05_10' '2_ense_enve_genELtask_38_03_04'\n",
+      " '2_ense_enself_genELtask_46_04_01' '2_ense_rmcv_genELtask_57_05_01'\n",
+      " '2_enseef_rt10v_genELtask_57_05_01' '2_enve_rt10v_genELtask_95_08_06'\n",
+      " '2_ense_rmcv_genELtask_16_01_04' '2_ense_enve_genELtask_16_01_04'\n",
+      " '2_enseef_enve_genELtask_16_01_04' '2_enve_rt10v_genELtask_26_02_03'\n",
+      " '2_ense_enve_genELtask_86_07_08' '2_ense_rt10v_genELtask_36_03_02'\n",
+      " '2_ense_rutpt_genELtask_74_06_07' '2_ense_enve_genELtask_63_05_07'\n",
+      " '2_enseef_rutpt_genELtask_36_03_02' '2_enve_rutpt_genELtask_104_09_04'\n",
+      " '2_enseef_rmcv_genELtask_25_02_02' '2_enself_rt10v_genELtask_46_04_01'\n",
+      " '2_enve_rutpt_genELtask_92_08_03' '2_rt10v_rutpt_genELtask_39_03_05'\n",
+      " '2_enve_rutpt_genELtask_90_08_01' '2_enseef_rt10v_genELtask_30_02_07'\n",
+      " '2_ense_rt10v_genELtask_6_00_05' '2_enve_rt10v_genELtask_83_07_05'\n",
+      " '2_ense_rutpt_genELtask_60_05_04' '2_rmcv_rutpt_genELtask_27_02_04'\n",
+      " '2_ense_enself_genELtask_68_06_01' '2_ense_rutpt_genELtask_64_05_08'\n",
+      " '2_ense_rt10v_genELtask_52_04_07' '2_enself_rt10v_genELtask_4_00_03'\n",
+      " '2_enve_rutpt_genELtask_40_03_06' '2_enve_rmcv_genELtask_6_00_05'\n",
+      " '2_enself_rt10v_genELtask_5_00_04' '2_rt10v_rutpt_genELtask_46_04_01'\n",
+      " '2_enself_rutpt_genELtask_16_01_04' '2_ense_rutpt_genELtask_51_04_06'\n",
+      " '2_ense_rmcv_genELtask_15_01_03' '2_ense_enve_genELtask_50_04_05'\n",
+      " '2_rt10v_rutpt_genELtask_36_03_02' '2_enseef_enve_genELtask_43_03_09'\n",
+      " '2_enseef_rt10v_genELtask_35_03_01' '2_rmcv_rt10v_genELtask_29_02_06'\n",
+      " '2_enseef_enself_genELtask_59_05_03' '2_rt10v_rutpt_genELtask_34_03_00'\n",
+      " '2_enve_rmcv_genELtask_70_06_03' '2_enve_rmcv_genELtask_81_07_03'\n",
+      " '2_enseef_rutpt_genELtask_33_02_10' '2_enseef_rutpt_genELtask_44_03_10'\n",
+      " '2_rmcv_rutpt_genELtask_20_01_08' '2_ense_rutpt_genELtask_73_06_06'\n",
+      " '2_ense_rutpt_genELtask_43_03_09' '2_ense_rt10v_genELtask_60_05_04'\n",
+      " '2_ense_rt10v_genELtask_58_05_02' '2_ense_rutpt_genELtask_24_02_01'\n",
+      " '2_enself_enve_genELtask_9_00_08' '2_enve_rmcv_genELtask_58_05_02'\n",
+      " '2_enseef_rmcv_genELtask_24_02_01' '2_ense_rmcv_genELtask_36_03_02'\n",
+      " '2_rt10v_rutpt_genELtask_79_07_01' '2_ense_enseef_genELtask_48_04_03'\n",
+      " '2_enve_rutpt_genELtask_68_06_01' '2_enself_rutpt_genELtask_19_01_07'\n",
+      " '2_enself_rutpt_genELtask_15_01_03' '2_ense_rt10v_genELtask_49_04_04'\n",
+      " '2_ense_rutpt_genELtask_36_03_02' '2_ense_enself_genELtask_2_00_01'\n",
+      " '2_ense_rt10v_genELtask_53_04_08' '2_enve_rutpt_genELtask_79_07_01'\n",
+      " '2_ense_enve_genELtask_51_04_06' '2_rmcv_rt10v_genELtask_37_03_03'\n",
+      " '2_ense_enve_genELtask_31_02_08' '2_enve_rt10v_genELtask_85_07_07'\n",
+      " '2_ense_rutpt_genELtask_48_04_03' '2_enseef_rmcv_genELtask_37_03_03'\n",
+      " '2_enself_rt10v_genELtask_18_01_06' '2_ense_enve_genELtask_13_01_01'\n",
+      " '2_enseef_enve_genELtask_32_02_09' '2_enve_rutpt_genELtask_38_03_04'\n",
+      " '2_ense_rutpt_genELtask_55_04_10' '2_enve_rmcv_genELtask_48_04_03'\n",
+      " '2_ense_enve_genELtask_85_07_07' '2_rmcv_rt10v_genELtask_38_03_04'\n",
+      " '2_rt10v_rutpt_genELtask_92_08_03' '2_ense_enve_genELtask_14_01_02'\n",
+      " '2_ense_rt10v_genELtask_21_01_09' '2_enseef_rt10v_genELtask_20_01_08'\n",
+      " '2_enve_rutpt_genELtask_57_05_01' '2_enve_rt10v_genELtask_90_08_01'\n",
+      " '2_enve_rt10v_genELtask_88_07_10' '2_rt10v_rutpt_genELtask_91_08_02'\n",
+      " '2_ense_enself_genELtask_81_07_03' '2_enve_rutpt_genELtask_65_05_09'\n",
+      " '2_enve_rt10v_genELtask_56_05_00' '2_ense_rmcv_genELtask_47_04_02'\n",
+      " '2_rmcv_rt10v_genELtask_12_01_00' '2_enve_rt10v_genELtask_109_09_09'\n",
+      " '2_enself_rmcv_genELtask_6_00_05' '2_enself_rt10v_genELtask_13_01_01'\n",
+      " '2_enseef_rmcv_genELtask_14_01_02' '2_enself_enve_genELtask_32_02_09'\n",
+      " '2_ense_enve_genELtask_52_04_07' '2_enseef_rt10v_genELtask_46_04_01'\n",
+      " '2_ense_enve_genELtask_3_00_02' '2_enseef_enve_genELtask_64_05_08'\n",
+      " '2_enve_rutpt_genELtask_74_06_07' '2_rt10v_rutpt_genELtask_52_04_07'\n",
+      " '2_rt10v_rutpt_genELtask_71_06_04' '2_enve_rt10v_genELtask_74_06_07'\n",
+      " '2_enve_rt10v_genELtask_47_04_02' '2_ense_enseef_genELtask_59_05_03'\n",
+      " '2_ense_enseef_genELtask_1_00_00' '2_rmcv_rt10v_genELtask_39_03_05'\n",
+      " '2_enself_enve_genELtask_3_00_02' '2_enseef_rmcv_genELtask_56_05_00'\n",
+      " '2_enve_rt10v_genELtask_48_04_03' '2_ense_enve_genELtask_1_00_00'\n",
+      " '2_ense_enve_genELtask_74_06_07' '2_ense_rutpt_genELtask_88_07_10'\n",
+      " '2_enself_rmcv_genELtask_15_01_03' '2_rmcv_rt10v_genELtask_54_04_09'\n",
+      " '2_ense_enseef_genELtask_47_04_02' '2_rt10v_rutpt_genELtask_62_05_06'\n",
+      " '2_rt10v_rutpt_genELtask_90_08_01' '2_enve_rt10v_genELtask_60_05_04'\n",
+      " '2_rt10v_rutpt_genELtask_27_02_04' '2_rmcv_rt10v_genELtask_27_02_04'\n",
+      " '2_ense_rmcv_genELtask_37_03_03' '2_enseef_enve_genELtask_31_02_08'\n",
+      " '2_rt10v_rutpt_genELtask_61_05_05' '2_ense_rt10v_genELtask_25_02_02'\n",
+      " '2_enseef_enve_genELtask_30_02_07' '2_enself_rt10v_genELtask_10_00_09'\n",
+      " '2_rmcv_rutpt_genELtask_38_03_04' '2_enself_enve_genELtask_6_00_05'\n",
+      " '2_enve_rutpt_genELtask_46_04_01' '2_ense_rutpt_genELtask_49_04_04'\n",
+      " '2_ense_rutpt_genELtask_53_04_08' '2_enseef_enself_genELtask_36_03_02'\n",
+      " '2_ense_rt10v_genELtask_51_04_06' '2_ense_enve_genELtask_64_05_08'\n",
+      " '2_ense_enseef_genELtask_35_03_01' '2_enve_rutpt_genELtask_77_06_10'\n",
+      " '2_enseef_rmcv_genELtask_13_01_01' '2_ense_enseef_genELtask_58_05_02'\n",
+      " '2_enve_rt10v_genELtask_96_08_07' '2_enseef_rutpt_genELtask_27_02_04'\n",
+      " '2_ense_rt10v_genELtask_43_03_09' '2_enve_rt10v_genELtask_75_06_08'\n",
+      " '2_rt10v_rutpt_genELtask_51_04_06' '2_enve_rmcv_genELtask_47_04_02'\n",
+      " '2_enve_rutpt_genELtask_70_06_03' '2_enseef_enself_genELtask_13_01_01'\n",
+      " '2_enself_rt10v_genELtask_6_00_05' '2_enve_rmcv_genELtask_89_08_00'\n",
+      " '2_ense_rt10v_genELtask_50_04_05' '2_enve_rt10v_genELtask_86_07_08'\n",
+      " '2_ense_rt10v_genELtask_33_02_10' '2_enself_rt10v_genELtask_21_01_09'\n",
+      " '2_rt10v_rutpt_genELtask_102_09_02' '2_enseef_rutpt_genELtask_53_04_08'\n",
+      " '2_rt10v_rutpt_genELtask_80_07_02' '2_enself_rmcv_genELtask_3_00_02'\n",
+      " '2_enseef_rt10v_genELtask_21_01_09' '2_ense_rt10v_genELtask_31_02_08'\n",
+      " '2_rmcv_rutpt_genELtask_22_01_10' '2_ense_enself_genELtask_36_03_02'\n",
+      " '2_ense_enseef_genELtask_70_06_03' '2_ense_rutpt_genELtask_59_05_03'\n",
+      " '2_enve_rutpt_genELtask_83_07_05' '2_enve_rutpt_genELtask_93_08_04'\n",
+      " '2_ense_enseef_genELtask_36_03_02' '2_enve_rutpt_genELtask_81_07_03'\n",
+      " '2_ense_rutpt_genELtask_46_04_01' '2_enself_enve_genELtask_43_03_09'\n",
+      " '2_enve_rutpt_genELtask_91_08_02' '2_ense_enve_genELtask_30_02_07'\n",
+      " '2_enself_enve_genELtask_31_02_08' '2_ense_enseef_genELtask_82_07_04'\n",
+      " '2_ense_enseef_genELtask_71_06_04' '2_rmcv_rt10v_genELtask_17_01_05'\n",
+      " '2_ense_rt10v_genELtask_63_05_07' '2_enve_rutpt_genELtask_48_04_03'\n",
+      " '2_rmcv_rutpt_genELtask_39_03_05' '2_ense_rmcv_genELtask_6_00_05'\n",
+      " '2_enself_enve_genELtask_42_03_08' '2_enve_rutpt_genELtask_55_04_10'\n",
+      " '2_enself_enve_genELtask_7_00_06' '2_enself_enve_genELtask_54_04_09'\n",
+      " '2_enseef_enve_genELtask_53_04_08' '2_ense_rutpt_genELtask_58_05_02'\n",
+      " '2_enseef_rmcv_genELtask_6_00_05' '2_enve_rmcv_genELtask_69_06_02'\n",
+      " '2_enseef_enve_genELtask_19_01_07' '2_enve_rt10v_genELtask_73_06_06'\n",
+      " '2_rt10v_rutpt_genELtask_38_03_04' '2_enseef_rutpt_genELtask_15_01_03'\n",
+      " '2_enve_rutpt_genELtask_53_04_08' '2_enve_rt10v_genELtask_102_09_02'\n",
+      " '2_ense_rt10v_genELtask_45_04_00' '2_enseef_rt10v_genELtask_18_01_06'\n",
+      " '2_enself_rt10v_genELtask_35_03_01' '2_ense_enseef_genELtask_60_05_04'\n",
+      " '2_rmcv_rt10v_genELtask_40_03_06' '2_enseef_rutpt_genELtask_26_02_03'\n",
+      " '2_enseef_enself_genELtask_37_03_03' '2_enseef_enve_genELtask_63_05_07'\n",
+      " '2_enve_rt10v_genELtask_82_07_04' '2_enve_rt10v_genELtask_79_07_01'\n",
+      " '2_enseef_rt10v_genELtask_29_02_06' '2_ense_rutpt_genELtask_61_05_05'\n",
+      " '2_ense_rt10v_genELtask_71_06_04' '2_enseef_enve_genELtask_17_01_05'\n",
+      " '2_enve_rmcv_genELtask_80_07_02' '2_enve_rutpt_genELtask_3_00_02'\n",
+      " '2_enve_rmcv_genELtask_68_06_01' '2_enve_rmcv_genELtask_90_08_01'\n",
+      " '2_ense_rmcv_genELtask_26_02_03' '2_enself_rutpt_genELtask_1_00_00'\n",
+      " '2_enself_enve_genELtask_19_01_07' '2_rt10v_rutpt_genELtask_41_03_07'\n",
+      " '2_enself_rutpt_genELtask_13_01_01' '2_enve_rt10v_genELtask_23_02_00'\n",
+      " '2_enseef_rmcv_genELtask_45_04_00' '2_rmcv_rutpt_genELtask_13_01_01'\n",
+      " '2_ense_enself_genELtask_35_03_01' '2_ense_rmcv_genELtask_78_07_00'\n",
+      " '2_ense_rt10v_genELtask_64_05_08' '2_ense_enve_genELtask_43_03_09'\n",
+      " '2_enself_rutpt_genELtask_4_00_03' '2_enseef_enself_genELtask_24_02_01'\n",
+      " '2_enve_rmcv_genELtask_78_07_00' '2_ense_rutpt_genELtask_35_03_01'\n",
+      " '2_enself_rmcv_genELtask_24_02_01' '2_ense_rmcv_genELtask_35_03_01'\n",
+      " '2_ense_rutpt_genELtask_25_02_02' '2_enseef_rt10v_genELtask_23_02_00'\n",
+      " '2_ense_rutpt_genELtask_54_04_09' '2_enseef_enve_genELtask_29_02_06'\n",
+      " '2_enseef_enself_genELtask_1_00_00' '2_enseef_rt10v_genELtask_22_01_10'\n",
+      " '2_enself_rmcv_genELtask_36_03_02' '2_enseef_rutpt_genELtask_25_02_02'\n",
+      " '2_enve_rutpt_genELtask_82_07_04' '2_ense_rutpt_genELtask_12_01_00'\n",
+      " '2_enseef_rt10v_genELtask_6_00_05' '2_ense_enve_genELtask_48_04_03'\n",
+      " '2_ense_rmcv_genELtask_48_04_03' '2_enve_rmcv_genELtask_100_09_00'\n",
+      " '2_rmcv_rt10v_genELtask_15_01_03' '2_enve_rt10v_genELtask_45_04_00'\n",
+      " '2_enself_rt10v_genELtask_20_01_08' '2_enve_rutpt_genELtask_44_03_10'\n",
+      " '2_enseef_rutpt_genELtask_13_01_01' '2_enseef_rt10v_genELtask_12_01_00'\n",
+      " '2_ense_enself_genELtask_1_00_00' '2_enseef_enve_genELtask_18_01_06'\n",
+      " '2_rmcv_rutpt_genELtask_25_02_02' '2_ense_enseef_genELtask_24_02_01'\n",
+      " '2_enseef_enve_genELtask_54_04_09' '2_ense_rt10v_genELtask_55_04_10'\n",
+      " '2_ense_rmcv_genELtask_59_05_03' '2_rmcv_rutpt_genELtask_57_05_01'\n",
+      " '2_enseef_rt10v_genELtask_11_00_10' '2_enself_rt10v_genELtask_31_02_08'\n",
+      " '2_enve_rmcv_genELtask_35_03_01' '2_enve_rt10v_genELtask_77_06_10'\n",
+      " '2_ense_enve_genELtask_40_03_06' '2_enseef_enve_genELtask_2_00_01'\n",
+      " '2_enseef_rmcv_genELtask_36_03_02' '2_ense_rutpt_genELtask_33_02_10'\n",
+      " '2_rmcv_rt10v_genELtask_48_04_03' '2_enself_enve_genELtask_53_04_08'\n",
+      " '2_enseef_enve_genELtask_42_03_08' '2_ense_rt10v_genELtask_47_04_02'\n",
+      " '2_ense_enve_genELtask_42_03_08' '2_ense_rutpt_genELtask_77_06_10'\n",
+      " '2_enve_rutpt_genELtask_99_08_10' '2_enve_rt10v_genELtask_76_06_09'\n",
+      " '2_rmcv_rt10v_genELtask_67_06_00' '2_rt10v_rutpt_genELtask_81_07_03'\n",
+      " '2_enseef_enself_genELtask_60_05_04' '2_rmcv_rt10v_genELtask_20_01_08'\n",
+      " '2_rmcv_rt10v_genELtask_34_03_00' '2_rt10v_rutpt_genELtask_49_04_04'\n",
+      " '2_rt10v_rutpt_genELtask_22_01_10' '2_rt10v_rutpt_genELtask_101_09_01'\n",
+      " '2_enve_rmcv_genELtask_49_04_04' '2_ense_rt10v_genELtask_41_03_07'\n",
+      " '2_ense_rt10v_genELtask_22_01_10' '2_enseef_rt10v_genELtask_27_02_04'\n",
+      " '2_enve_rt10v_genELtask_17_01_05' '2_enself_rutpt_genELtask_2_00_01'\n",
+      " '2_enself_rutpt_genELtask_20_01_08' '2_ense_enve_genELtask_37_03_03'\n",
+      " '2_enself_rutpt_genELtask_44_03_10' '2_ense_rt10v_genELtask_68_06_01'\n",
+      " '2_enve_rt10v_genELtask_64_05_08' '2_enself_enve_genELtask_29_02_06'\n",
+      " '2_enseef_enself_genELtask_2_00_01' '2_ense_enve_genELtask_18_01_06'\n",
+      " '2_ense_rmcv_genELtask_46_04_01' '2_enseef_rt10v_genELtask_47_04_02'\n",
+      " '2_enseef_enve_genELtask_52_04_07' '2_enself_rutpt_genELtask_55_04_10'\n",
+      " '2_enseef_enve_genELtask_3_00_02' '2_ense_rt10v_genELtask_40_03_06'\n",
+      " '2_ense_rmcv_genELtask_17_01_05' '2_enself_rmcv_genELtask_17_01_05'\n",
+      " '2_rmcv_rutpt_genELtask_11_00_10' '2_enseef_rt10v_genELtask_19_01_07'\n",
+      " '2_rt10v_rutpt_genELtask_68_06_01' '2_enve_rmcv_genELtask_104_09_04'\n",
+      " '2_enself_rutpt_genELtask_21_01_09' '2_enseef_rutpt_genELtask_12_01_00'\n",
+      " '2_enve_rmcv_genELtask_7_00_06' '2_ense_rutpt_genELtask_62_05_06'\n",
+      " '2_rmcv_rt10v_genELtask_19_01_07' '2_rmcv_rt10v_genELtask_43_03_09'\n",
+      " '2_ense_rt10v_genELtask_70_06_03' '2_ense_rt10v_genELtask_23_02_00'\n",
+      " '2_ense_enve_genELtask_41_03_07' '2_ense_rt10v_genELtask_32_02_09'\n",
+      " '2_rmcv_rt10v_genELtask_55_04_10' '2_enseef_rutpt_genELtask_37_03_03'\n",
+      " '2_ense_rt10v_genELtask_62_05_06' '2_ense_enself_genELtask_47_04_02'\n",
+      " '2_enself_rmcv_genELtask_7_00_06' '2_enseef_rmcv_genELtask_15_01_03'\n",
+      " '2_enself_rmcv_genELtask_45_04_00' '2_enself_rt10v_genELtask_22_01_10'\n",
+      " '2_enve_rt10v_genELtask_6_00_05' '2_ense_rutpt_genELtask_26_02_03'\n",
+      " '2_enseef_enve_genELtask_1_00_00' '2_enseef_enve_genELtask_15_01_03'\n",
+      " '2_enself_enve_genELtask_2_00_01' '2_enself_rutpt_genELtask_3_00_02'\n",
+      " '2_rt10v_rutpt_genELtask_42_03_08' '2_enve_rmcv_genELtask_92_08_03'\n",
+      " '2_ense_enve_genELtask_62_05_06' '2_ense_rutpt_genELtask_39_03_05'\n",
+      " '2_enseef_enve_genELtask_27_02_04' '2_ense_enseef_genELtask_83_07_05'\n",
+      " '2_ense_enve_genELtask_76_06_09' '2_ense_rt10v_genELtask_79_07_01'\n",
+      " '2_enve_rt10v_genELtask_57_05_01' '2_ense_enve_genELtask_53_04_08'\n",
+      " '2_enseef_rutpt_genELtask_38_03_04' '2_ense_rutpt_genELtask_1_00_00'\n",
+      " '2_enve_rt10v_genELtask_84_07_06' '2_enself_rmcv_genELtask_25_02_02'\n",
+      " '2_enve_rt10v_genELtask_46_04_01' '2_enve_rt10v_genELtask_108_09_08'\n",
+      " '2_enself_rt10v_genELtask_36_03_02' '2_ense_enseef_genELtask_25_02_02'\n",
+      " '2_enself_rutpt_genELtask_22_01_10' '2_ense_rutpt_genELtask_52_04_07'\n",
+      " '2_enself_rutpt_genELtask_42_03_08' '2_ense_enself_genELtask_24_02_01'\n",
+      " '2_ense_rmcv_genELtask_58_05_02' '2_ense_rutpt_genELtask_66_05_10'\n",
+      " '2_rmcv_rutpt_genELtask_45_04_00' '2_enseef_rt10v_genELtask_17_01_05'\n",
+      " '2_enseef_rutpt_genELtask_54_04_09' '2_enve_rutpt_genELtask_63_05_07'\n",
+      " '2_ense_rt10v_genELtask_61_05_05' '2_enve_rutpt_genELtask_102_09_02'\n",
+      " '2_enseef_rt10v_genELtask_41_03_07' '2_ense_enseef_genELtask_69_06_02'\n",
+      " '2_enve_rmcv_genELtask_40_03_06' '2_enself_rt10v_genELtask_14_01_02'\n",
+      " '2_rmcv_rutpt_genELtask_26_02_03' '2_enve_rutpt_genELtask_64_05_08'\n",
+      " '2_ense_rt10v_genELtask_42_03_08' '2_enseef_rutpt_genELtask_2_00_01'\n",
+      " '2_enve_rt10v_genELtask_97_08_08' '2_enseef_rutpt_genELtask_14_01_02'\n",
+      " '2_enself_rmcv_genELtask_14_01_02' '2_enve_rt10v_genELtask_91_08_02'\n",
+      " '2_ense_enve_genELtask_29_02_06' '2_ense_enself_genELtask_58_05_02'\n",
+      " '2_enve_rutpt_genELtask_66_05_10' '2_enself_rmcv_genELtask_2_00_01'\n",
+      " '2_rmcv_rutpt_genELtask_56_05_00' '2_rt10v_rutpt_genELtask_30_02_07'\n",
+      " '2_ense_rmcv_genELtask_7_00_06' '2_enself_enve_genELtask_17_01_05'\n",
+      " '2_enve_rutpt_genELtask_1_00_00' '2_enself_rt10v_genELtask_40_03_06'\n",
+      " '2_ense_enself_genELtask_25_02_02' '2_ense_rt10v_genELtask_57_05_01'\n",
+      " '2_rmcv_rutpt_genELtask_14_01_02' '2_enseef_rutpt_genELtask_1_00_00'\n",
+      " '2_enseef_enve_genELtask_21_01_09' '2_enseef_enself_genELtask_48_04_03'\n",
+      " '2_ense_rt10v_genELtask_74_06_07' '2_rt10v_rutpt_genELtask_82_07_04'\n",
+      " '2_ense_rutpt_genELtask_71_06_04' '2_ense_enve_genELtask_61_05_05'\n",
+      " '2_enself_rt10v_genELtask_7_00_06' '2_enve_rutpt_genELtask_60_05_04'\n",
+      " '2_ense_rmcv_genELtask_18_01_06' '2_enself_rmcv_genELtask_34_03_00'\n",
+      " '2_enve_rutpt_genELtask_61_05_05' '2_enve_rt10v_genELtask_80_07_02'\n",
+      " '2_enseef_rutpt_genELtask_40_03_06' '2_ense_enself_genELtask_70_06_03'\n",
+      " '2_enseef_rt10v_genELtask_43_03_09' '2_enself_rutpt_genELtask_5_00_04'\n",
+      " '2_ense_rt10v_genELtask_12_01_00' '2_enseef_enself_genELtask_49_04_04'\n",
+      " '2_ense_rutpt_genELtask_75_06_08' '2_rmcv_rt10v_genELtask_2_00_01'\n",
+      " '2_enself_rt10v_genELtask_8_00_07']\n"
+     ]
+    }
+   ],
+   "source": [
+    "## LOAD DISCOVERY METRICS FILES\n",
+    "bpi_pd = pd.read_csv(\"../output/benchmark/bpics_PDbenchmark.csv\").sort_values('log')\n",
+    "bpi_pd = pd.read_csv(\"../data/baseline_ED_bench.csv\").sort_values('log')\n",
+    "\n",
+    "gen_pd = pd.read_csv(\"../output/benchmark/instance_selection_3_2_bench.csv\")\n",
+    "gen_pd = pd.read_csv(\"../data/GenED_bench.csv\")\n",
+    "if EXP_BASELINE:\n",
+    "    gen_pd = pd.read_csv(\"../data/GenBaseline_ED_bench.csv\")\n",
+    "    gen_pd['log']=gen_pd.apply(lambda x: \"Gen\"+x['log'].replace(\"genEL\",\"\").rsplit(\"_\",7)[0], axis=1)\n",
+    "\n",
+    "#gen_pd = gen_pd.sample(30)\n",
+    "\n",
+    "paper_metrics = ['log', 'fitness_heuristics', 'precision_heuristics',\n",
+    "       'fscore_heuristics', 'size_heuristics', 'cfc_heuristics', 'fitness_ilp', 'precision_ilp', 'fscore_ilp',\n",
+    "       'size_ilp','cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf', 'source']\n",
+    "\n",
+    "print(gen_pd.shape, bpi_pd.shape)\n",
+    "bpi_pd['source']='Real'\n",
+    "gen_pd['source']='Generated'\n",
+    "#gen_pd['log']=gen_pd.apply(lambda x: \"Gen\"+x['log'].replace(\"genEL\",\"\").rsplit(\"_\",7)[0], axis=1)\n",
+    "#if EXP_BASELINE:\n",
+    "#    gen_pd['log']=gen_pd.apply(lambda x: \"Gen\"+x['log'], axis=1)\n",
+    "both_pd = pd.concat([bpi_pd, gen_pd])\n",
+    "both_pd= both_pd[paper_metrics]\n",
+    "#both_pd['log']=both_pd.apply(lambda x: x['log'].replace(\".xes\",\"\"), axis=1)\n",
+    "#both_pd['log']=both_pd.apply(lambda x: x['log'].replace(\"_processed\",\"\"), axis=1)\n",
+    "print(both_pd.shape)\n",
+    "print(both_pd['log'].unique())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "ca100d3e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(449, 24)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array(['BPIC13cp', 'BPIC13inc', 'BPIC13op', 'BPIC14dc_p', 'BPIC14di_p',\n",
+       "       'BPIC16c_p', 'BPIC16wm_p', 'BPIC17ol', 'BPIC20a', 'BPIC20b',\n",
+       "       'BPIC20c', 'BPIC20d', 'BPIC20e', 'HD', 'RTFMP', 'RWABOCSL',\n",
+       "       'SEPSIS', '2_rmcv_rt10v_genELtask_40_03_06',\n",
+       "       '2_rt10v_rutpt_genELtask_39_03_05',\n",
+       "       '2_ense_rt10v_genELtask_32_02_09',\n",
+       "       '2_enseef_rt10v_genELtask_41_03_07',\n",
+       "       '2_enseef_rt10v_genELtask_18_01_06',\n",
+       "       '2_ense_rt10v_genELtask_40_03_06',\n",
+       "       '2_enve_rt10v_genELtask_45_04_00',\n",
+       "       '2_ense_rt10v_genELtask_21_01_09',\n",
+       "       '2_enself_rt10v_genELtask_10_00_09',\n",
+       "       '2_enseef_rt10v_genELtask_20_01_08',\n",
+       "       '2_enself_enve_genELtask_42_03_08',\n",
+       "       '2_enself_rmcv_genELtask_36_03_02',\n",
+       "       '2_ense_enseef_genELtask_60_05_04',\n",
+       "       '2_enseef_rmcv_genELtask_6_00_05',\n",
+       "       '2_enself_rutpt_genELtask_5_00_04',\n",
+       "       '2_enve_rutpt_genELtask_53_04_08',\n",
+       "       '2_enself_rt10v_genELtask_22_01_10',\n",
+       "       '2_enseef_enve_genELtask_63_05_07',\n",
+       "       '2_enseef_rutpt_genELtask_26_02_03',\n",
+       "       '2_enself_rutpt_genELtask_20_01_08',\n",
+       "       '2_enseef_rt10v_genELtask_30_02_07',\n",
+       "       '2_enseef_enself_genELtask_60_05_04',\n",
+       "       '2_enve_rmcv_genELtask_48_04_03',\n",
+       "       '2_enve_rutpt_genELtask_74_06_07',\n",
+       "       '2_ense_rt10v_genELtask_45_04_00',\n",
+       "       '2_rmcv_rutpt_genELtask_56_05_00',\n",
+       "       '2_enself_rt10v_genELtask_20_01_08',\n",
+       "       '2_ense_enself_genELtask_70_06_03',\n",
+       "       '2_ense_enseef_genELtask_24_02_01',\n",
+       "       '2_enself_enve_genELtask_17_01_05',\n",
+       "       '2_enve_rmcv_genELtask_69_06_02',\n",
+       "       '2_ense_enseef_genELtask_82_07_04',\n",
+       "       '2_ense_rt10v_genELtask_53_04_08',\n",
+       "       '2_enseef_rutpt_genELtask_25_02_02',\n",
+       "       '2_enseef_rt10v_genELtask_57_05_01',\n",
+       "       '2_rt10v_rutpt_genELtask_82_07_04',\n",
+       "       '2_rt10v_rutpt_genELtask_27_02_04',\n",
+       "       '2_enve_rt10v_genELtask_47_04_02',\n",
+       "       '2_enself_rutpt_genELtask_22_01_10',\n",
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+       "       '2_enseef_rutpt_genELtask_14_01_02',\n",
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+       "       '2_enve_rt10v_genELtask_77_06_10',\n",
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+       "       '2_enseef_enve_genELtask_3_00_02',\n",
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+       "       '2_ense_enseef_genELtask_58_05_02',\n",
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+       "       '2_enseef_rmcv_genELtask_15_01_03',\n",
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+       "       '2_enseef_rmcv_genELtask_7_00_06',\n",
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+       "       '2_enseef_rmcv_genELtask_26_02_03',\n",
+       "       '2_enseef_enve_genELtask_42_03_08',\n",
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+       "       '2_enve_rutpt_genELtask_3_00_02',\n",
+       "       '2_ense_rutpt_genELtask_48_04_03',\n",
+       "       '2_enseef_rmcv_genELtask_24_02_01',\n",
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+       "       '2_ense_enve_genELtask_31_02_08',\n",
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+       "       '2_ense_enself_genELtask_58_05_02',\n",
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+       "       '2_ense_rt10v_genELtask_55_04_10',\n",
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+       "       '2_enve_rutpt_genELtask_77_06_10',\n",
+       "       '2_ense_rt10v_genELtask_49_04_04',\n",
+       "       '2_ense_enve_genELtask_37_03_03',\n",
+       "       '2_enve_rutpt_genELtask_92_08_03',\n",
+       "       '2_ense_rt10v_genELtask_22_01_10',\n",
+       "       '2_enseef_rt10v_genELtask_12_01_00',\n",
+       "       '2_ense_enve_genELtask_14_01_02',\n",
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+       "       '2_enself_rmcv_genELtask_2_00_01',\n",
+       "       '2_enve_rt10v_genELtask_73_06_06',\n",
+       "       '2_ense_rt10v_genELtask_62_05_06',\n",
+       "       '2_enseef_rt10v_genELtask_17_01_05',\n",
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+       "       '2_rmcv_rutpt_genELtask_13_01_01',\n",
+       "       '2_enve_rutpt_genELtask_61_05_05',\n",
+       "       '2_rt10v_rutpt_genELtask_22_01_10',\n",
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+       "       '2_ense_rmcv_genELtask_48_04_03',\n",
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+       "       '2_ense_rutpt_genELtask_13_01_01',\n",
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+       "       '2_ense_rutpt_genELtask_46_04_01',\n",
+       "       '2_ense_enseef_genELtask_59_05_03',\n",
+       "       '2_enve_rt10v_genELtask_74_06_07',\n",
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+       "       '2_enve_rutpt_genELtask_68_06_01',\n",
+       "       '2_ense_rutpt_genELtask_73_06_06',\n",
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+       "       '2_ense_rutpt_genELtask_75_06_08',\n",
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+       "       '2_enself_rutpt_genELtask_13_01_01',\n",
+       "       '2_enself_rutpt_genELtask_3_00_02',\n",
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+       "       '2_ense_rutpt_genELtask_74_06_07',\n",
+       "       '2_enve_rutpt_genELtask_93_08_04',\n",
+       "       '2_ense_rt10v_genELtask_42_03_08',\n",
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+       "       '2_ense_enve_genELtask_63_05_07',\n",
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+       "       '2_enve_rutpt_genELtask_102_09_02',\n",
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+       "       '2_enve_rmcv_genELtask_70_06_03',\n",
+       "       '2_enself_rmcv_genELtask_7_00_06',\n",
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+       "       '2_enve_rutpt_genELtask_65_05_09',\n",
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+       "       '2_enself_rt10v_genELtask_21_01_09',\n",
+       "       '2_ense_rutpt_genELtask_33_02_10',\n",
+       "       '2_ense_rt10v_genELtask_68_06_01',\n",
+       "       '2_enself_rt10v_genELtask_14_01_02',\n",
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+       "       '2_enseef_rutpt_genELtask_53_04_08',\n",
+       "       '2_enself_rmcv_genELtask_6_00_05',\n",
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+       "       '2_ense_rt10v_genELtask_12_01_00',\n",
+       "       '2_ense_rt10v_genELtask_74_06_07',\n",
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+       "       '2_ense_rutpt_genELtask_62_05_06',\n",
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+       "       '2_enself_enve_genELtask_53_04_08',\n",
+       "       '2_enseef_rt10v_genELtask_35_03_01',\n",
+       "       '2_rt10v_rutpt_genELtask_41_03_07',\n",
+       "       '2_ense_rt10v_genELtask_43_03_09',\n",
+       "       '2_enseef_rutpt_genELtask_1_00_00',\n",
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+       "       '2_ense_enve_genELtask_61_05_05',\n",
+       "       '2_enself_rt10v_genELtask_35_03_01',\n",
+       "       '2_rt10v_rutpt_genELtask_91_08_02',\n",
+       "       '2_enself_rmcv_genELtask_17_01_05',\n",
+       "       '2_enve_rutpt_genELtask_46_04_01',\n",
+       "       '2_enseef_enve_genELtask_54_04_09',\n",
+       "       '2_ense_rutpt_genELtask_54_04_09',\n",
+       "       '2_enseef_enve_genELtask_32_02_09',\n",
+       "       '2_enve_rutpt_genELtask_44_03_10',\n",
+       "       '2_enself_rmcv_genELtask_14_01_02',\n",
+       "       '2_rmcv_rt10v_genELtask_27_02_04',\n",
+       "       '2_rmcv_rutpt_genELtask_25_02_02',\n",
+       "       '2_enself_enve_genELtask_9_00_08',\n",
+       "       '2_rmcv_rt10v_genELtask_37_03_03',\n",
+       "       '2_rmcv_rt10v_genELtask_34_03_00',\n",
+       "       '2_rmcv_rutpt_genELtask_39_03_05',\n",
+       "       '2_ense_enself_genELtask_24_02_01',\n",
+       "       '2_enseef_rutpt_genELtask_66_05_10',\n",
+       "       '2_ense_rt10v_genELtask_33_02_10',\n",
+       "       '2_enve_rutpt_genELtask_70_06_03',\n",
+       "       '2_ense_rmcv_genELtask_37_03_03',\n",
+       "       '2_ense_rutpt_genELtask_25_02_02',\n",
+       "       '2_ense_rutpt_genELtask_26_02_03',\n",
+       "       '2_enseef_enve_genELtask_29_02_06',\n",
+       "       '2_enseef_rt10v_genELtask_6_00_05',\n",
+       "       '2_ense_rt10v_genELtask_36_03_02',\n",
+       "       '2_ense_rt10v_genELtask_23_02_00',\n",
+       "       '2_rmcv_rt10v_genELtask_12_01_00',\n",
+       "       '2_enve_rt10v_genELtask_109_09_09',\n",
+       "       '2_enve_rt10v_genELtask_80_07_02',\n",
+       "       '2_enve_rutpt_genELtask_48_04_03',\n",
+       "       '2_enve_rt10v_genELtask_64_05_08',\n",
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+       "       '2_ense_enself_genELtask_47_04_02',\n",
+       "       '2_enseef_rutpt_genELtask_2_00_01',\n",
+       "       '2_enseef_rt10v_genELtask_21_01_09',\n",
+       "       '2_enve_rutpt_genELtask_40_03_06',\n",
+       "       '2_ense_rt10v_genELtask_57_05_01',\n",
+       "       '2_ense_enseef_genELtask_1_00_00',\n",
+       "       '2_ense_rutpt_genELtask_35_03_01',\n",
+       "       '2_ense_rutpt_genELtask_53_04_08',\n",
+       "       '2_enve_rmcv_genELtask_90_08_01',\n",
+       "       '2_rmcv_rt10v_genELtask_29_02_06',\n",
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+       "       '2_ense_enve_genELtask_42_03_08', '2_ense_enve_genELtask_43_03_09',\n",
+       "       '2_rt10v_rutpt_genELtask_42_03_08',\n",
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+       "       '2_ense_rutpt_genELtask_60_05_04',\n",
+       "       '2_rmcv_rt10v_genELtask_54_04_09',\n",
+       "       '2_ense_enve_genELtask_52_04_07',\n",
+       "       '2_rmcv_rt10v_genELtask_39_03_05',\n",
+       "       '2_rt10v_rutpt_genELtask_81_07_03',\n",
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+       "       '2_ense_rutpt_genELtask_64_05_08',\n",
+       "       '2_ense_enve_genELtask_38_03_04',\n",
+       "       '2_rmcv_rt10v_genELtask_55_04_10',\n",
+       "       '2_enve_rutpt_genELtask_55_04_10',\n",
+       "       '2_enve_rt10v_genELtask_86_07_08',\n",
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+       "       '2_ense_rutpt_genELtask_88_07_10',\n",
+       "       '2_ense_enseef_genELtask_83_07_05',\n",
+       "       '2_ense_enseef_genELtask_25_02_02',\n",
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+       "       '2_ense_rutpt_genELtask_59_05_03',\n",
+       "       '2_enve_rutpt_genELtask_81_07_03',\n",
+       "       '2_enve_rutpt_genELtask_60_05_04',\n",
+       "       '2_enve_rt10v_genELtask_60_05_04',\n",
+       "       '2_rmcv_rutpt_genELtask_11_00_10',\n",
+       "       '2_rmcv_rutpt_genELtask_26_02_03',\n",
+       "       '2_enseef_rmcv_genELtask_25_02_02',\n",
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+       "       '2_rmcv_rt10v_genELtask_2_00_01',\n",
+       "       '2_enseef_rmcv_genELtask_37_03_03',\n",
+       "       '2_ense_rt10v_genELtask_6_00_05',\n",
+       "       '2_rmcv_rutpt_genELtask_14_01_02',\n",
+       "       '2_enve_rmcv_genELtask_40_03_06',\n",
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+       "       '2_enseef_rutpt_genELtask_33_02_10',\n",
+       "       '2_ense_enseef_genELtask_70_06_03',\n",
+       "       '2_enseef_enself_genELtask_48_04_03',\n",
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+       "       '2_enseef_enve_genELtask_21_01_09',\n",
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+       "       '2_enve_rutpt_genELtask_99_08_10',\n",
+       "       '2_ense_enve_genELtask_40_03_06',\n",
+       "       '2_enself_enve_genELtask_6_00_05',\n",
+       "       '2_enself_rutpt_genELtask_2_00_01',\n",
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+       "       '2_enve_rt10v_genELtask_91_08_02',\n",
+       "       '2_ense_enself_genELtask_81_07_03',\n",
+       "       '2_ense_rutpt_genELtask_51_04_06',\n",
+       "       '2_enve_rt10v_genELtask_75_06_08',\n",
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+       "       '2_enseef_rt10v_genELtask_23_02_00',\n",
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+       "       '2_ense_rutpt_genELtask_66_05_10',\n",
+       "       '2_enseef_enve_genELtask_16_01_04',\n",
+       "       '2_enve_rmcv_genELtask_58_05_02',\n",
+       "       '2_rt10v_rutpt_genELtask_90_08_01',\n",
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+       "       '2_enve_rutpt_genELtask_38_03_04',\n",
+       "       '2_enself_enve_genELtask_31_02_08',\n",
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+       "       '2_rmcv_rutpt_genELtask_35_03_01',\n",
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+       "       '2_rmcv_rutpt_genELtask_57_05_01',\n",
+       "       '2_ense_enself_genELtask_68_06_01',\n",
+       "       '2_ense_rt10v_genELtask_58_05_02',\n",
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+       "       '2_ense_rt10v_genELtask_79_07_01',\n",
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+       "       '2_ense_rutpt_genELtask_71_06_04',\n",
+       "       '2_ense_enself_genELtask_36_03_02',\n",
+       "       '2_enseef_enself_genELtask_59_05_03',\n",
+       "       '2_enseef_enve_genELtask_2_00_01',\n",
+       "       '2_ense_rmcv_genELtask_57_05_01',\n",
+       "       '2_enself_rutpt_genELtask_21_01_09',\n",
+       "       '2_enself_rutpt_genELtask_1_00_00',\n",
+       "       '2_enseef_rutpt_genELtask_44_03_10',\n",
+       "       '2_enseef_enself_genELtask_36_03_02',\n",
+       "       '2_enve_rt10v_genELtask_97_08_08',\n",
+       "       '2_ense_rmcv_genELtask_78_07_00',\n",
+       "       '2_ense_enseef_genELtask_69_06_02',\n",
+       "       '2_rt10v_rutpt_genELtask_68_06_01',\n",
+       "       '2_ense_enve_genELtask_62_05_06',\n",
+       "       '2_ense_enseef_genELtask_13_01_01',\n",
+       "       '2_ense_enseef_genELtask_35_03_01',\n",
+       "       '2_enself_enve_genELtask_3_00_02',\n",
+       "       '2_ense_rmcv_genELtask_58_05_02', '2_enve_rmcv_genELtask_78_07_00',\n",
+       "       '2_ense_enve_genELtask_13_01_01',\n",
+       "       '2_enve_rt10v_genELtask_82_07_04',\n",
+       "       '2_ense_enve_genELtask_48_04_03',\n",
+       "       '2_enself_rmcv_genELtask_3_00_02',\n",
+       "       '2_rt10v_rutpt_genELtask_52_04_07',\n",
+       "       '2_rt10v_rutpt_genELtask_61_05_05',\n",
+       "       '2_enseef_enself_genELtask_49_04_04',\n",
+       "       '2_enseef_enve_genELtask_1_00_00',\n",
+       "       '2_enve_rt10v_genELtask_87_07_09',\n",
+       "       '2_enself_rt10v_genELtask_5_00_04',\n",
+       "       '2_enself_rutpt_genELtask_15_01_03',\n",
+       "       '2_ense_rt10v_genELtask_61_05_05',\n",
+       "       '2_enve_rt10v_genELtask_84_07_06',\n",
+       "       '2_enve_rutpt_genELtask_91_08_02',\n",
+       "       '2_enve_rt10v_genELtask_85_07_07',\n",
+       "       '2_enseef_enself_genELtask_24_02_01',\n",
+       "       '2_enve_rutpt_genELtask_66_05_10',\n",
+       "       '2_enve_rt10v_genELtask_56_05_00',\n",
+       "       '2_enseef_rutpt_genELtask_13_01_01',\n",
+       "       '2_enseef_rt10v_genELtask_29_02_06',\n",
+       "       '2_enve_rt10v_genELtask_26_02_03',\n",
+       "       '2_ense_rutpt_genELtask_24_02_01',\n",
+       "       '2_enve_rutpt_genELtask_1_00_00',\n",
+       "       '2_enve_rutpt_genELtask_82_07_04',\n",
+       "       '2_enve_rt10v_genELtask_102_09_02',\n",
+       "       '2_enself_rutpt_genELtask_42_03_08',\n",
+       "       '2_ense_rmcv_genELtask_15_01_03', '2_ense_enve_genELtask_18_01_06',\n",
+       "       '2_enve_rmcv_genELtask_81_07_03',\n",
+       "       '2_enve_rt10v_genELtask_83_07_05',\n",
+       "       '2_ense_enve_genELtask_53_04_08',\n",
+       "       '2_enseef_rmcv_genELtask_45_04_00',\n",
+       "       '2_enseef_rutpt_genELtask_27_02_04',\n",
+       "       '2_enve_rt10v_genELtask_48_04_03',\n",
+       "       '2_ense_rutpt_genELtask_63_05_07',\n",
+       "       '2_ense_rmcv_genELtask_17_01_05',\n",
+       "       '2_rt10v_rutpt_genELtask_34_03_00',\n",
+       "       '2_ense_enve_genELtask_16_01_04', '2_ense_enve_genELtask_51_04_06',\n",
+       "       '2_enve_rutpt_genELtask_104_09_04',\n",
+       "       '2_enseef_rmcv_genELtask_14_01_02',\n",
+       "       '2_enseef_rutpt_genELtask_36_03_02',\n",
+       "       '2_enself_rmcv_genELtask_45_04_00',\n",
+       "       '2_rmcv_rt10v_genELtask_15_01_03',\n",
+       "       '2_ense_rmcv_genELtask_35_03_01',\n",
+       "       '2_enseef_enve_genELtask_27_02_04',\n",
+       "       '2_ense_enve_genELtask_3_00_02', '2_ense_rmcv_genELtask_47_04_02',\n",
+       "       '2_enseef_rutpt_genELtask_15_01_03',\n",
+       "       '2_ense_enself_genELtask_25_02_02',\n",
+       "       '2_enseef_rt10v_genELtask_43_03_09',\n",
+       "       '2_enseef_enve_genELtask_18_01_06',\n",
+       "       '2_enve_rutpt_genELtask_90_08_01',\n",
+       "       '2_ense_rt10v_genELtask_41_03_07',\n",
+       "       '2_ense_enve_genELtask_85_07_07',\n",
+       "       '2_enve_rutpt_genELtask_63_05_07',\n",
+       "       '2_enself_rutpt_genELtask_6_00_05',\n",
+       "       '2_enseef_rutpt_genELtask_30_02_07',\n",
+       "       '2_enseef_rmcv_genELtask_36_03_02',\n",
+       "       '2_ense_enself_genELtask_1_00_00',\n",
+       "       '2_rt10v_rutpt_genELtask_36_03_02',\n",
+       "       '2_enself_rutpt_genELtask_16_01_04',\n",
+       "       '2_enself_rt10v_genELtask_13_01_01',\n",
+       "       '2_ense_rmcv_genELtask_36_03_02',\n",
+       "       '2_enself_rmcv_genELtask_13_01_01',\n",
+       "       '2_rt10v_rutpt_genELtask_46_04_01',\n",
+       "       '2_enseef_enve_genELtask_53_04_08',\n",
+       "       '2_ense_enve_genELtask_64_05_08',\n",
+       "       '2_enself_rt10v_genELtask_6_00_05',\n",
+       "       '2_enve_rt10v_genELtask_88_07_10',\n",
+       "       '2_ense_rutpt_genELtask_61_05_05',\n",
+       "       '2_enseef_rutpt_genELtask_37_03_03',\n",
+       "       '2_ense_rmcv_genELtask_26_02_03',\n",
+       "       '2_enself_enve_genELtask_32_02_09',\n",
+       "       '2_rmcv_rutpt_genELtask_22_01_10',\n",
+       "       '2_enseef_enve_genELtask_15_01_03',\n",
+       "       '2_enve_rutpt_genELtask_98_08_09',\n",
+       "       '2_ense_enself_genELtask_35_03_01',\n",
+       "       '2_ense_rt10v_genELtask_25_02_02',\n",
+       "       '2_rt10v_rutpt_genELtask_80_07_02',\n",
+       "       '2_rt10v_rutpt_genELtask_92_08_03',\n",
+       "       '2_enve_rt10v_genELtask_23_02_00',\n",
+       "       '2_enself_rt10v_genELtask_8_00_07',\n",
+       "       '2_enseef_enve_genELtask_19_01_07',\n",
+       "       '2_ense_rt10v_genELtask_51_04_06',\n",
+       "       '2_enseef_rt10v_genELtask_11_00_10',\n",
+       "       '2_rmcv_rt10v_genELtask_67_06_00',\n",
+       "       '2_ense_rutpt_genELtask_36_03_02',\n",
+       "       '2_enve_rt10v_genELtask_79_07_01',\n",
+       "       '2_enself_rmcv_genELtask_25_02_02'], dtype=object)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "## MERGE FEATURES AND METRICS\n",
+    "fd_pdm = pd.merge(both_df, both_pd, on=['log', 'source'], how='inner').reset_index(drop=True)#.reindex(both_df.index)\n",
+    "\n",
+    "## DROP DUPLICATES\n",
+    "fd_pdm = fd_pdm.reset_index(drop=True)\n",
+    "fd_pdm = fd_pdm.T.drop_duplicates().T\n",
+    "print(fd_pdm.shape)\n",
+    "fd_pdm['log'].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "0d5d55a1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Imputed dataset: (449, 24)\n",
+      "432\n",
+      "No nan's dataset: (295, 24)\n",
+      "281\n"
+     ]
+    }
+   ],
+   "source": [
+    "### INSTANCE SELECTION: NULLS OR IMPUTATION?\n",
+    "import numpy as np\n",
+    "from sklearn.impute import SimpleImputer\n",
+    "\n",
+    "num_cols = fd_pdm.convert_dtypes().select_dtypes(exclude=['string']).columns\n",
+    "str_cols = fd_pdm.convert_dtypes().select_dtypes(include=['string']).columns\n",
+    "\n",
+    "imputer = SimpleImputer(missing_values=np.nan, strategy='mean')\n",
+    "imputer.fit(fd_pdm.drop(str_cols, axis=1))\n",
+    "imp_df = imputer.transform(fd_pdm.drop(str_cols, axis=1))\n",
+    "imp_df = pd.DataFrame(imp_df, columns=num_cols)\n",
+    "imp_df['source'] = fd_pdm['source']\n",
+    "imp_df['log'] = fd_pdm['log']\n",
+    "print(\"Imputed dataset:\" ,imp_df.shape)\n",
+    "print(len(imp_df[imp_df['source']==DATA_SOURCE]['log']))\n",
+    "\n",
+    "ft_pdm_no_nans = fd_pdm.copy()\n",
+    "ft_pdm_no_nans = ft_pdm_no_nans.dropna()\n",
+    "ft_pdm_no_nans['source'] = fd_pdm['source']\n",
+    "ft_pdm_no_nans['log'] = fd_pdm['log']\n",
+    "print(\"No nan's dataset:\" ,ft_pdm_no_nans.shape)\n",
+    "print(len(ft_pdm_no_nans[ft_pdm_no_nans['source']==DATA_SOURCE]['log']))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "eb40e909",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "if IMPUTE:\n",
+    "    benchmarked_ft = imp_df[both_df.columns]\n",
+    "    benchmarked_pd = imp_df[both_pd.columns]\n",
+    "else:\n",
+    "    benchmarked_ft = ft_pdm_no_nans[both_df.columns]\n",
+    "    benchmarked_pd = ft_pdm_no_nans[both_pd.columns]\n",
+    "\n",
+    "real_log_names = benchmarked_ft[benchmarked_ft['source']=='Real']['log'].unique()\n",
+    "gen_log_names = benchmarked_ft[benchmarked_ft['source']=='Generated']['log'].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "83549f71",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Feature similarity: (13, 282)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "ft_similarity = cosine_similarity(benchmarked_ft.drop(str_cols, axis=1))\n",
+    "ft_similarity = pd.DataFrame(ft_similarity, columns=benchmarked_ft['log'], index=benchmarked_ft['log'])#.sort_values(by='BPI_Challenge_2013_closed_problems')\n",
+    "ft_similarity = ft_similarity.loc[ft_similarity.columns[len(real_log_names)-1:],ft_similarity.columns[:len(real_log_names)-1]].copy()\n",
+    "ft_similarity = ft_similarity.sort_values(by=ft_similarity.columns[0], ascending=False).transpose()\n",
+    "\n",
+    "#with_pcs.loc[:,~with_pcs.columns.duplicated()].copy()\n",
+    "print(\"Feature similarity:\", ft_similarity.shape)\n",
+    "#plt.imshow(ft_similarity, cmap='viridis', interpolation='nearest')\n",
+    "sns.heatmap(ft_similarity.astype(np.float16), cmap=\"viridis\")\n",
+    "ax = plt.gca()\n",
+    "ax.set_title(\"Feature similarity between BPICs and GenED\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "296941ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Metrics similarity: (13, 282)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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v+jLeWVjN5mQT9+yZBcDZxUt4rG4mn61YRpMmadUUDaqMjCbYkWpiWUsFZ09cFvTD36y0bZkSeB0nNmLlPqfXm7gOyuFwOAYxSQ3+jXqudQi5lh+Hw+Fw9CKpnltf63dcB+VwOByDmFSfW/nqO3JeSUJEkiKyUEReE5H5InKiDZ8gxsXzQhFZJiI3WPtTE0Rkief8Y0XkeRFZISILROQvIlJo7XDNEZFmEfmaRz4hIq/Y9JaKyPf7o9wOh8PRGyRVA2+5xkAYQTWq6iwAETkb+AnGkR8Yy8qzxLjQfhq4EGMbDys/HOPN9hJVnWPDLsYaecTYvbvQl14zxldRnf2S/78i8oiqvtQ3xXM4HI6+w03x7T9KMUYQO6CqbSIyG+NsbL7n0Gcx3jPneGTv8RzfJiLn++JSjEFEMP5V4lhXCCJyDMaoZxGmIzsDeC/G7HwZxj/KX1XVjbocDkdO0DqAp/gGQgdVICILMU7sRmLcDHdARAoxncV3fYdmYqxBh8Kasn8V0+H9XlVfFpE8jPuCD6jqXBEpZa+zwWNtWg3AXBH5j6rOC5uuw+Fw9Da5OHUXlJxfg8JO8anqNOAc4HYRSevqT7ad14vAf1T1kd5IUFWTdlpxDHCsiMwEDgY2q+pcK7PH49n2CVXdaf313IfxKNsBEblKROaJyLyF96zujWw6HA5Ht6RCbLnGQOig2rFTdUOBKhu0ynZeR6jqNRlOWQoctQ/p1QDPYDrGLkW7+Y+q3qiqR6vq0bMuDuy/z+FwOPaJJBp4yzUGVAclItOAKMG9aP4OuFxEjvPE8R6rPJEtjSoRKbf7BcCZGOdmK4CRdh0KESmxyhkAZ4pIpZW/EDOiczgcjn4nqcG3XGMgrUEBCHC5qib3zvJlR1W3isglwM9FZBhmFPs88KiIjMB4xi0FUiLyJWAGZp3rNrsOFQHuVtWHAETkA8BvbUfUiPHMCcYj572YKcG/uvUnh8ORK+Ti1F1Qcr6DUrUGszqHr8UoJnQZbqcFT8kQRQOmQ/GzCDgiS5pzgeO9Ybaj3KCqF2Y6x+FwOPqTVs0p83qhyPkOyuFwOBw9J4nroA5YVPVW4NZ+zobD4XBkxHVQDofD4chJUm6KzxGGuCSJS5JmjROXJHkixCVJBEiI9VVDlMpoA3lWGSSOOack0kSJQFza2mXzREhEWkmiVEZgu7TRIjFK8pqJS5KySJQh0XoKoq0kIq3t6TRIGwmJ0ZSKk5AoQyL1pFDKog0kJEpZtAGA0khT+36eCKWRJvJESKq0569EmnxlVEqkiZT1S5QiRUI6LtcmRCiKtJBKRdrjLpEmmiROnhifS23JCHGS7X6QoiJE1MyrR0SJ2LfDfInTSrJTXSeJmDxLCw3kUSTQGmkhX5R8iZLMcE7cxlkWbSQuUUoijeRLgY1PKRFoBaqidSSJkNQIJWLqNE+SlERaKIyovT7mukQFEtJKwtZXQypOoTQTEYggxCXSfm6rRoAIJZE48VSSOEJUjO+qqAgoJCImngjGl1RVbE+7Sm4rSonsXbotijTbvEQYmqgnKhGaUilKIlEiSPt5RWLqYki0niZN0aQxRkRraVElIcKIvBoiCCPzdpMC4hIladtLmpKIyVNVdA8box19hA2J1hG39TQ6f5eJM1bDzlQRcWkjLkIUJWnLE5cIcUnRpFASiTLS+rSqT+Xb9pMiIRHKI43WH5Sp/67I5A8qIW0sYQxJlBQpRuftolWjtn1FiEuSIfF620bbKI+b8pbEmiiPNFIeN/dpfl4bpfEmyqONJCRJXPIoiUSIEKGhPc9CcdTcK00aozjaRKumSGHaS3XK3CNRhPJIoz/7PcKNoBwOh8ORk7Rm1jMbELgOyuFwOAYxbgTlcDgcjpwkqQPKHkMHcjLnueQDyp47Y//WgMPhcPQOKSKBt1wjV0dQOeMDSlU/3jdFdDgcjr5nIE/x5V6X2ZmsPqCAtA8oLxl9QKnqVlXdZq1BtPriUlXN5gPqWRE52u7XiciP7EjrpbRNPxEZLiL/suGvpUd8DofD0d8kNRJ4yzVyL0eGAjuNtxz4C/ADv4DHB9Ri36GZGF9OoRCRqLX5tw3jPuPlDGJFwEuqejjGpt8nbPhvgOds+JEYK+oOh8PR77QSDbwFQUTOscsnK0Xk6gzHx4vIUyKyyL7gj/EcSy/fLBSRB7pLayBM8Z2A8QGVtq+X9gGlwL9V9RERmbCvCapqEphlLZn/S0RmquoSn1gL8JDdfxVj6RyME8WPeOLZva/5cTgcjt6gN0dG1oj27zHPvg0YB60PqOoyj9jPgdtV9TYROR2zRHOZPdb+bA9Cro6g2skxH1Ct1iU8QJIQHbzXYeH8e9b2NHsOh8MRil5WkjgWWKmqq1W1BbgLuMAnMwOjHwDmWeo/Hpic76D62QdUUJ4CPm3Pj4pImV/A67DwyIsnhIja4XA4ek5SJfAWgNHAes//DTbMy2vAe+z+RUCJiAyx/xP2Rf0lEbmwu8RydYovZ3xABeSLwI0iciVmZPVpYE7XpzgcDkffkwwxDhGRq4CrPEE3quqNIZP8GvA7EbkC8+zdCO02xcar6kYRmQQ8LSKLVXVVtohysoPKMR9Qp3n2iz379wD32P2t7MMw1uFwOPqKVg3+mLedUVcd0kZgrOf/GBvmjWMTdgQlIsXAe+3SCaq60f6uFpFnMc/drB1Uzk/xORwOh6Pn9PIU31xgqohMFJE84BKggzaeiAwVkXTf8k3gZhteISL5aRngJMCrXNEJ10E5HA7HIKY3lSTs96efAx4DXscshywVkWtF5N1W7DRghYi8AQwHfmTDpwPzROQ1jPLEdT7tv07k5BSfw+FwOHqH3v4AV1UfBh72hX3Xs9++/OGTmQ0cGiYt10E5HA7HICY1gE0duQ6qH3hm61Qq8htZvGw8T445iOrJL/JizRRKRzzLnlSCn79hvv/99+E3sbSlnNGxPcxpmMEdK4/l70fcxPyWSp7YPZPTS5fxSvV43la8nDm7JlEYaeb0ohX8btMZbKov5eih67hu1bncMO1vjIq2sb6+gu1NJawoLmZPKtGenyd3HUJ5tIGGVD6zGyqYt2c84/N2MGf3ZACGx3czZ/dk3mwczjvLF1KTKqRFo/x8xZmMOOQeEtJKk8Y7lHFnKp8mjVOTKgTg6cYER+Xv6CDToEp9Ko9bt5/E3OJNHJ5YB8AvVp/FiKJaimPN1M2p4uaKUzij8nUm5W2jKlpPdbKYv+04gQ8NnUNc2nhg97GcW7qIncmSTnV9y6oTmDFjIycnmvjC6vN438hXubRkHX/dM4Hzit/g4bqDOp1zWuGb7ftzmmBqXFnU0sLGtnJu3nwKV495mIVN4/hw6VomxXZz+eoLKB3zOJPitdy49VR+MeY/JCTG6rYkd9ccx/D4bhpS+SzYM5YLhy6gKraHb71xEYdWbqYyr54pia0cV7CGe6qP4dIhc/jnrmN5V/kC4iS5s/oUji5ey9j4Tp6qPYSh8VpaNcpHyxYCsDYZpyGVx4mJapa0GB2eO3acyBeHP9lehuXNYymPrCFKkmU7h3NvZQWv1h/BhypeokmVJqv7Myley7WLzufLhzzFgrpxzN02jmcOv4MnG0dQHm1gad0onk2sZ2n9KNY1V3JZ5Wx+vP5dnDZkRXta9Qo7Uylmxtt4uaFjm5gUa2J3SoAWFteO4b5IC60a5U/LT2Zk2R7+PPVOfvzWeazfVc57J7/GiNge/rztVNY3lHP7lHtYXDuaR7bMYN32Sn581P0cmr+J+lSK5S1jaNWocbwZ6WDFrBOZHBZeXLyRK185iuGH7WZsXjUrGobz3LopvDpiPF8c9Ti3rDieyuIGphds4vdrTqOpLcYVlbNZXD2K5WUjeXbzVM4sXULNziKWRYazdsgQFjWM491lCxgdVZ5ojPHz18+kfOa/iZCiOWXq5esrL+aiUa/xx5pD2dlawueGPM931l/EFSP+S21qGK0a5biuChOQXDRhFBTXQTkcDscgxjksdDgcDkdOEuY7qFzDdVAOh8MxiEkN4Cm+nM55LjkudDgcjoFIEgm85Rq5PoLKGceFfVM8h8Ph6FvcCGr/0N+OC8+wo7DFInKz54votSLyMxv+ioj48+FwOBz9xkAeQeV6B5UTjgtFJAHcCnxAVQ/FjDw/7Tlttw3/HXB92DQdDoejr2hNxQJvuUaud1CN1vfTNIx/pttlr0nztOPCF4H/qOojvZGgqibttOIY4FjrKPFgYI2qvmHFbgPe5jntTs/vCZni9fqD2vKf13ojqw6Hw9EtKSTwlmvkegfVTo45LuwknmXfG1+7P6gR5x/e02w5HA5HKJIaCbzlGrmXoyz0s+PCFcAEz/rSZcBznlM/4Pl1fqAcDkfOkFIJvOUauTfp2JGccVwoIh8F/mm1BucCN3iSqxCRRRgtwEv3scwOh8PRa7gPdfuIHHNc+FS2Y8D/qeo3shxzOByOfqPNmTpyOBwORy4S0BFhTuI6qH1EVSf0dx4cDocjG7m4thQU10E5HA7HIGYgW5JwHZTD4XAMYnLRQkRQRDXjZzuOPmT8X/5P46XN3Hn8X5jfOJ7Hdx7C1oZixhbXkBdJcmTpW5xS+AYXPf55Tpz5Jk3JOEs2jeRrhz3Bzxaczcwxm9jZVMjxVW+xsbEMgIgoM0s2cvuK4zhl7GqmF23mz387l0986BH+se4otqyrpHL0bqqK6qjMb2B0wW7WN1QwtnAXpdFG9iQLuHfJLD546Fzm7RrHoeWbWVwzEoAVK0Zz8MEbOWnIal6vG8GcRVM54bA3+dLIJ7h+85mUxJp5/OXDOpTx4JnrWbFkLMRTAFxx4n+5fXFH92tFRc3UVhdy6OQNvHPYIp7ddTBzXj2YX57zV/629QSmFm9jesEmHtg+i0S0lermQhLRNhLRVg4u3sqKuuGUxRt5W9kbPFszjYmF2zvV9czEBv6+7XjmLDyIy056kWW1I3l18SQOP2Qta3ZVMn3otk7nLN46AoDGunzOmLaCp1YczGkHvUF5vJFheXu4c9XRTB2ygwWvTCHaJPzy/bfwgzfeSXNblBlDt/LSqoloSpg+fjPDEnVMK97MluYyNjRWUNOcYFhBHT8Z8yBXvnkpY4p2c2jJBp7ZfjC7WxK0tMWYXrmVllSUPS0JxhbtYldLERFJkYi2UpVXR3MqxmNrpgMweegOUggrZ0/g6NNeB+B9VXO5c+vx7eVpSUXZ0VhEPJLkrS1D+PisFzmicC3XvvEuJpbt/WpjzorJ/PLku/j9urfz3lELKIo0c82j7+XCU+aypamUOW9M4pxDlvLo0kO47IiXWd0wlMNLNnDT8r3fpufFkkyq3MniuZOIjmnoUK8tu/MZPmYXSRV2bi/h/Ye/yj8XH8n9b/sDq1qH8qM3zuOagx+kNNLE/755ES1tUT435Vkmxbdx1YLLaKzN5+a33cKE2B5urD6JR9ZNp6klTkF+K6qgKoh0/TwTAdW9vwCNCyu5+v33srWtlLq2BH978US+efqD7GgrYVndSN5W/gbXzT2HTx/5PE2pODfPPZkjDnqLpc9MofCIamo2lHHC4W+w8k/TqB0nNE1pZvr4zRTGWpm/ZizvmzmfuCRpSOWxqbGcV9cb/azvHfEQ31/wTq6cOZtJedv5+Ztn8vFJL/Jq7QRK4008sf4gXnvnD/a5d/nUq5cFfsjfcNQd3aYnIucAv8Z89vMXVb3Od3w8cDPmm9Vq4MOqusEeuxz4thX9oare1lVabgTlcDgcg5je1OKzn+D8HvON6AZgrog8oKrLPGI/B25X1dtE5HSMke/LRKQS+B5wNMagwav23E42VtMM3MlJh8PhcHRLUiXwFoBjgZWqulpVW4C7gAt8MjMwHibAWONJHz8bY9+02nZKT9CNpR7XQTkcDscgJqWRwFsARgPrPf832DAvrwHvsfsXASUiMiTguR3ImQ5qfzsntOeUi8g9IrJcRF4XkYyGXh0Oh2OgEsbUkdeotd2u6kGSXwNOFZEFGP99G4FkT/KeS2tQ+9s5IZiFvkdV9WIRyQMKe79YDofD0X+EsVKuqjcCN3YhshEY6/k/xoZ549iEHUGJSDHwXlWtEZGNwGm+c5/tKj85M4Ly0efOCUWkDOMy4yYr32ItmCMiU0TkSc9obnKmTIrIaXbU9h87crtBRHK1Th0OxwFILxuLnQtMFZGJ9qX+EuABr4CIDPU8B7+J0egDeAw4S0QqRKQCOMuGZSWXRlBpw7AJjNHW0/0CHueE3/Udmonx0RSGicB24BYRORzj3PCLqloP/A24TlX/ZZ0VdtXpHItZFHwLeBTz5nBPyLw4HA5Hn9CW6j0tPlVtE5HPYTqWKHCzqi4VkWuBear6AGaU9BMxOv/PYwYQqGq1iPwA08kBXKuq1V2ll0tv+/vbOWEMOBL4o6oeAdQDV4tICTBaVf8FoKpNqtrQRTyvWI2WJMZh4cmZhLxzu3XPv9QL2Xc4HI7u6W2Hhar6sKoepKqTVfVHNuy7tnNKz15NtTIfV9Vmz7k3q+oUu93SXVq51EG1s5+cE24ANqjqy/b/PZgOK3R2u/lvAj0OC4vfdnwmEYfD4eh1BrI/qJzsoPaHc0JV3QKsF5GDbdAZwDJVrQU2iMiFNp58O7WYjWPtfGwE47DwvwHz7HA4HH3OQO6gcnENCvaDc0JV3QN8HvibXexbDXzURnkZ8Cc7r9oKvM8ez8RcTAc5BfNR2r9CldrhcDj6kFzseIKSMx1UPzgnRFUXYsxu+MPfJIOSRhb2qOo7A8o6HA7HfqXNWTN3OBwORy7iRlCDHBE5FLjDF9ysqsfRzYdmDofD0Z+4DmqQo6qLgVn9nQ+Hw+EIi+ugHA6Hw5GTDOQOyjks7AcufekqLYk18+QLhzP9qLWcO2wJ65qHMDRex5i8au7cfCx1rXm8d9QCalMJxuftZFNrOY9tncHpw1YwI7GJefUTObpoDdeuOJ+Lxy/gkc2HMKN8C+8f8gqP7j6M9Y0VvLRyIsdPWcOXRj7B4uYx/GzxWZQXNXLxuAUcnNjMK3WTOLZ4Nd9ecgE/nPlvRkR389CeWWxoKufCIQu4f+cRALxv6Fz+ueMYRuXvpjjWxOEF63itcRx3rjqaSyfPIy5JDs7f3KGMCxomcEThWqJiHBY+XzuNwwrXd5Bp1SiFkWYWNYwjEWklIilmJjZww4bTmF62FYDHbzuecy6fzeTENmpTCapitWxqLWdTUwWjEruIS5KNzRVMLdhKXTLRqa7/MO80Pnn0cxycv5kHq2dxfOlqEpFW6lP5FEWaqU/ldzqnKGK+K5yzZzInlK6iKRVvP/Zq7QQuGfoSrzWOZ0ZiA/MaJvH8jil8bPSLlEQbeXbPdCYntjE2bye1yQJWt1TxVuOQdkeDBxVsoSZZyAObDuP04W8QQUkhHFH4FiuaRjIlfwtLGseSiLRyeMFbzKmfysh4DdXJIhqS+e31dHTBGgC2tJUxJFbHgoYJxMXY41zZMIwzyve655ldO4XTy16nJNLIn7ecysySTSyrG8lZlUupSRbSkMoDYHzeTn715hl8bsqzPFtzMJsayvjc2Kd5sPoIDiraQnMqTlm0gYZUPttaSxmdt4tFdaMZk6hpT2tkXg27kwWMitewtKGjoeqRebupbitifP4ONrVUUBJtYlR8Fz9942wmlldzQsUq5tZMpLq5gNOq3mRc3g6WNo5hfWMF5w9ZxOuNo5i/ayyb60o5fsRaKmINHFSwhWMSb9GkUepTeRRFWrLddgAkJEmTRtt/AXNvLDuLU8asojjWwui8Xfx17TGcPGI1w/JquX/dYcwcupnSWBObGsuJiPLOoQt5tPpQvjXqYX606Txmlmzkn2uPZGJ5Ne+uWsiGlkrKog1Myt/GsqbRPLDpMN49ahG72wpptem+VjOaw8s3klKhORXjyOK3eHjHYRxV9hav14/g88Of4shx6/a5dzntqa8Ffsg/e8bPc6o3cyMoh8PhGMQ4LT6Hw+Fw5CQ6gKf4XAflcDgcg5iBvAbVZ2M/54DQ4XA4+h9VCbzlGn05gnIOCB0Oh6OfcSOo7uk3B4QiMkxEXrUyh4uIisg4+3+VHZXdKiJ/FJGXRGS1dUR4sx2F3dpVwUSkTkR+JSJLReQpEanqSt7hcDj2J6rBt1yjLzuoAjuNtxz4C/ADv4DHAeFi36GZGAeCYfA6IExPCRap6jYgISKlGFt984BTRGQ8sM3j66kCOAH4MsZD5K+AQ4BDRWRWF+kWYRx1HQI8B3wvZL4dDoejz0hqJPCWa/RljnLCAaE9Nhs4CTPC+rH9PQV4wXP+g2o+ClsMbFXVxaqawviamtBFuingH3b/rwRwWLjy/td7UDyHw+EIz0B2t7FfuswccED4PKZDGg/8Gzgc05F4O6i018eUZz/9P8xaXbcOC6dcOD1EdA6Hw9Fz3BRfN/SnA0K7/wLwYeBNOyqqBs6jd5wLRoCL7f4HeylOh8Ph6BWcFl9mcsYBoaqutdOLz9sk/guMUdVOihs9oB7jVffbwDaMV12Hw+HICXq74xGRczAa01HgL6p6ne/4OOA2oNzKXK2qD4vIBOB1YIUVfUlVP9VVWn3WQeWSA0J7bKxn/8eYtaj0/yu6yEf7sWyo6le6k3E4HI7+IJnqvQ5KRKLA74EzMcsqc0XkAVVd5hH7NnC3qv5RRGYAD7N3HX9V+vOjIOSe2obD4XA4eo1enuI7FlipqqtVtQW4C7jAnyRmhgugDNjU07w7U0cBEZGXAb/p68tUtbg/8uNwOBxBCDPFJyJXAVd5gm5U1Rs9/0cDXrcEG4Dj6Mg1wOMi8nnMZzjv8BybKCILgD3At1X1BbrAdVABsd5zHQ6HY0ARRjnPdkY3divYNZcCt6rqL6y5uTtEZCawGRinqjtF5CjgfhE5xOoPZMR1UP3AiMQeRubtpvKM2ZxfupD1bUOoitVy3/ajoAy+NvYxDs9rZNZTn+WoyetYk1dFVV4t35/4b66Y91Eun/YyE/O3s6W1jJbWGPNqJtDYEqc01sRNW9/Gp4Y/Q6Kijc/+8Qt85W2Pc/uOk3jo9ZloXZxdKeHV3eMpizawsGYM4/J3MqpsN1tay3iwehYfGPIyP9j2TraUlrFqz1AA/txyKjubCvn81Kf40YZ38squiURE+db0R7h72zFU5DXwyJZDOpQxpcJzMoXSPKOxf2zFGm58q+OSYkWikbZUhKtGP8eQaB3/t+FcnmyZxv9MeJQIyrBoHS+dN54zSpeyra2U+7YcwfiiXexuLeB/R/+HH288nylF2/hg5Us8Uzedylhdp7o+a8Yy5tVM4OaNJ/LwCX9gduMEfrToXL512CPct/VIPjBibqdz/rXNfJ3wyrJJjD1hFzcvPpFLZsxjXP5Ovj7iCX63/VQOLdrAp168DGryuObse3m1fgIbm8q5cvjzfOKly6mqqOXgim18oOpldrUWcWzRKvKkjeXNo5hbM5G7pv2NpxrGMSy2h+XNo7h/5xGcXv46v33rdK6e+Agv109hfuME3la8nPWtQ5i3cwJXjXyWuCRJaoQ/bDodgIgoR5ev5ebHTufoE94A4Kdj/82vtp/WXp55O8a177+6cSznHLaEI4at5c5txzMysZu3GoYA8EDtYXzzoEd4bs80vjT8ScbElONf/BRnTl7O3JqJ1LQkeNfwRTy1/WB+MvE+btj2dv535GOcO/sz7fGPGrKb0UW7uWHJ25H8ZMeKTQkjRtQwpKCellSUj4/5Lw9XH8azs27nuaZyfrPuDL454WES0soft5zOtrwS3lG2lGFltXx7zYUAfHTMbI5PrOPn287gwbdmMr58NPOKJgKQRIiGehwbHnzlCC463vg1K4y28Oi2GZw5egUfqZjDn3a8jTNGv8HW5hKG5dXywcqXuGn723hh98FUNxfyx+2nURRtYV7NBOoa89mZX8jTu6ZzduUS5tdP4F+bZ/HeUQv480F/48XGSby6ezxz3pwEwEun/4bjn/4CN59yCyOidXxr3YX8Yvx9PFw3nagot+w4hSPHdZP5APSyksRGYKzn/xgb5uVKzLevqOocEUkAQ63RhGYb/qqIrAIOwii9ZcStQTkcDsdgRkNs3TMXmCoiE6229CUYyzte1mE+80FEpgMJYLuIVFklC0RkEjAVo22dFTeCcjgcjkFMqhe1+FS1TUQ+BzyGUSG/WVWXisi1GJNvDwBfBf4sIl/GdHtXqKqKyNuAa0WkFfPp0KdUtbqr9FwH5XA4HIOY3v4OSlUfxqiOe8O+69lfhjEt5z/vXuDeMGkNmCm+/e1fSkQOtnGmtz32o+Cu8nirdQvicDgcuYFK8C3HGEgjqP3qX0pVVwDp9KKYhcB/9UnJHA6Ho4/IRRt7QRkwIygffe5fyscZmE7wLQARmWV9Ry0SkX+JSMW+FsjhcDj6hN5VktivDKQOan/7l/JyCXCn5//twDdU9TCblvMB5XA4chJNSeAt1xioU3wnYPxLpW3mpf1LKfBvVX3EGibcZ6wq5buBb9r/ZUC5qj5nRW7DTB86HA5HzpGLVsqDMpBGUO3sJ/9Sac4F5qvq1h6eD3R0WLj43lX7EpXD4XAEx03x7V/2h38pD5fimd5T1d3ALhFJm0W4DOPqvUu8DgsPfe/kgNl2OByOfUVCbLnFQJri2+/+pUSkCGNW/pO+KC8HbrBrXu1+pxwOhyPnyMGRUVAGTAfVT/6l6oEhGcIXAsdnCL8iUzwOh8PRb7gOyuFwOBy5SC5q5wXFdVAOh8MxmHEjKIfD4XDkJANYzdx1UA6HwzGIETeCcoThuU1TqCqq4yvjHmdLsow1zVVsbC5nfOFOmlJxNrZVMDVeR35RC5OLthMRZWHNGGYVvUVZYSM7WotZ31TBYcUbmFG1lfGFO0lEWzmkcCOLd49iXuMkRsV3sXuysLqliurWQvIKWikob2B4cS3jC3eSJMJBpdtIEuGMqhUkibBk50jOriikLK+JJBHK8poAWLlzKBMqqlnfVsnkou088tYMzh2/jAnxHUwu2k5FvJ7/rpvUoYwnjF3DnPUT2RYzTuveN3weqQxqrFvqSnipbgpnlS5havE2Hlh1KMkJEebUT2Zy/lbePvxN5tRPJT/SytiiGirz6imPN7C2bQjjC3dSEa+nVSNEJEVhpKVT/KeVL2dh/TiWRkewsHkka5qriIjyRuMIYpEUa5qrOp3TkjL6OPnlTRRGWigpaaQw2kJUUixvGcqGxgpKY00gkCpMMiq2i6ebp9OSjPFyw2RKShoBKI01saxpNIcUbmRTawWbW8vZ3VbA+MKdFEuMV2onM6lgO6PiuyiNVfHinqmU5jWzuGks8UgbO1tLWNw0lrpkgslF21nbUkVJtImmVJyWpMnj+OJqtrWUkixOMr7QfHVRq1EKonstd00q3Ul9Mp8ISrI1SmGkmbGxGlIIxdHm9vPW7K4kEWmluqWIPal8VrYmSSUjzCjcxLroEBZtmQnDYV11BWvHDGF4/h7ebK2ktLipPa2SeDOjC3YjeUlKyho71GtzS4zxpbuISIoFm8ZQM7KQZTuH0zomRVRSDE3UAxBF2dOaIBYxbScuSXOtdgxh9IRdFIows2gja8qG0KYR1jVUkFIhpUKkm6dxRLRdLpUeWUSVqQVbKYk0kiLCHVuO5YIRr7G8ZRjD8mopizbw6PrpnHPwEt5oGc6cTRM4f8JSHl98CHlTk6zYNox3T17M0iVTWTuigNZJUUYmxlIQaaGpLU5CWlnUMpKopBhdsLu9XtYn8ygpa6Q+lU9TpJHCWAtbkgVERDmkaBNP7zi4y7IExnVQDofD4chJ3BSfw+FwOHKSVH9noOe4DsrhcDgGM4N9ik9E3pMheDewWFW39W6WAuUnibEiLkAS+JyqzrYGYl8HVgB5GGsRnwHGAQ+p6kx7/rHAz4HhmA91X8X4hLoI+IaNtxb4tKq+Zs85B/g1xsTSX1T1uv1SWIfD4dgXBvAUX1BbfFdiXFx8yG5/xjzIXxSRy/oob13RaI3DHo6xMv4Tz7FV1ur5YcAMfI4IPc4Lv6GqB6vqEcCjGOeFa4BTVfVQjDuPG+05UeD3GMOxM4BLRWRG3xXP4XA4egfR4Fug+ETOsZ7JV4rI1RmOjxORZ6zn8kUicp7n2DfteSus49kuCTrFFwOmpy1624f87cBxmFHKHQHj6QuyOi8UkbTzwvmeQxmdF9pdr8Xyl9hrAulYYKWqrgYQkbuAC4BlIvJd4F1AAcZZ4idVB7IPS4fDMajoxaeR52X9TGADMFdEHlDVZR6xbwN3q+of7Yv8w8AEu38JcAgwCnhSRA5S1WS29IKOoMb63E1ss2HVdO2Jtq/YH84LrwQesfujgfWeYxtsGMDvVPUYO31YALwzcCkcDoejj+nlEVT7y7qqtgDpl3Uvihk4AJQBm+z+BcBdqtqsqmuAlTa+rATtoJ4VkYdE5HIRuRx4wIYVATUB4+hN0lN804BzMM4L0xOtaeeFLwL/UdVHskWSDRF5O6aD+kYA8beLyMsishg4HfN2kCnOdn9QOx6Zn0nE4XA4eh+VwJv3OWW3q3yxdfWynuYa4MMisgEzevp8iHM7EHSK77PAe4CT7f/bgHvtVNbbA8bRJ6jqHBHp5Lywi1PSzgv/nemgiByGGZWdq6ppf1MbgbEesTHARhFJAH8AjlbV9SJyDZDIks8bsWtaRz78bYW6AKVzOByOfSTEFJ/3ObUPXArcqqq/sN7P7/B4Pw9FoBGU7Yj+CzwNPAU8nyvrLL3pvFBExgH3AZep6huec+YCU0VkonUBfwlmFJnujHaISDFw8T4Wx+FwOHqX3vWom/Fl3SdzJXA3tLs5SmA8oAc5twOBOigReT/wCuYB/H7gZRHpz4dxeg1qIfAPrPPCICfatbS088IVIvI6cDZGrfy7GP9Pf7Dxz7PntAGfAx7DqLHfrapLVbUGo9G4xB6b24tldDgcjn2ml9egsr2se1mHWf9HRKZjOqjtVu4SEckXkYnAVEy/kpWgU3zfAo5Jf/MkIlXAk8A9XZ7VR/Sh88KP2y1T3A9j5lP94d/GaK04HA5H7tGLc11WOzr9sh4FblbVpSJyLTBPVR8Avgr8WUS+bFO/ws64LRWRu4FlQBvw2e4GFkE7qIjvg9ydBFewcDgcDkc/Ib1s6ijTy7qqftezvww4Kcu5PwJ+FDStoB3UoyLyGHCn/f8BfwYdDofDkYMMYEsSgTooVf26iLyXvb3ijar6r77LlsPhcDh6hZxQZ+sZgY3Fquq9wL19mBeHw+Fw9DKD1mGhiNSSuf8VjPZ5aYZjjm44a8xyhsf38EztDI4qWsNhBes4KLGZ2bVTKYs1ABAXIS+WpDGZx9hENW+vWgFANKKMzt/F2Hg1SSKsqK5iWH4tq2qGUl1azMTincxIbKBFY+TvgsJIMxMKdrI4PpKa7cU0NceZUbaF8mgDtW0JyqMNLKkfzcmlbzJzyGYOim9ja30J5dEGttaXADBr+EZW7BrGpPgOnkwewqzhG2lM5vFGy3Aak3kMjddx+MhNHcqY0giHj9xEXqQNgIS0MK2so13hqrxahif2cHzxSiqjDTQm8zh85CZqkkUcW7SK0dHd/GHNaXxn6kM0peIsqR1NZayezS1lHJ63lWd1GlWxWsojzYyK11AUae5U10/vnk5KI4ws381heZsBGF0xmVlFb5EkwvREZy3XhtI8AF5bPZayaAPxSJKhsVoqo3VMy9vBkWXrOKxgHfcVH05bQYTtyVIOKd5EbTLB0QVruC8yi8nlOyiItnB4Yh1LmsZyYuGbjIrvojZVwNy6iTST5Ijit5iQt52NrRUUR5s5ungN9zQezeGJddSkCimLNjIhbztNqTjP7J7BkQVvkUeSeo1zUKmxwtWYjDM5sQ3yUrRa3aERUaUyVt9enteaR3NW1evUJhO0NcQoj5g2Niy/lqHxWna1FQIwtcI4RSyKNTM13kBColSW1ZGItNKcilGYaGFUfBeFiRYOzd/KiuaRzIjvpL4prz2t4ooWKmL1xAvaaGjI71Cv+YkWEtFWyuMNFBU0UxXbw5SKHVRECtnZVsyw/FpqkoXUUEgskmJWyXqaNE5tKsH4omq21RezqmUYJZEmmlNxYpJiSsl26tvySSEkVYh257AQJYW0/wIsK2llfu14Di3ewIjYbqrK61hUN4bjq1axva2UV2snMLJkD0kilEcbmFS5k8pYPVMnbmZ4opbYiBSNyTxSh9QxsrSeI4ds4KiiNWxvK2VK2Q6qYns4Kn8HS1vKmJec2F4vk2KmjibHd1IoKUYnapgab6Y2tZWX66cwvKC2y7IEZrB2UKpasr8y4nA4HI7eZ9COoBwOh8MxwHEOCx0Oh8ORiwzkEdSA/JZJRJLW0sNrIjJfRE604RNEpNEeWyYiN4hIxIYv8Zx/rIg8by1JLBCRv4hIoYh8yPovWSwis0XkcM85GX2giMhaawvQ4XA4HL3IQB1BNaYNwlqnVz8BTrXHVqnqLBGJYWwHXojHH5THYeElaZ9Q1myT12HhLhE5F2M08biAPlAcDocj93AjqH4lq8NCjAPBKb5DGR0WqupWVZ2tqum4MjoszOID5X/sqOsVEfGn53A4HP1Gb3vU3Z8M1A4qlxwWAuy2buJ/B1wfpAAOh8OxX0iF2HKMgdpB5ZLDQthrAupO4IQscbY7Alt4z+qwWXI4HI4eMZBHUAN1Daqd/nRY6M1Gln1vPtsdgV296GKFPV1k0eFwOHqJHOx4gjJQR1Dt9LPDwjQf8PzOweFwOHIEN4La/xTYaTwwZpcuV9Xk3lm+7KjqVhFJOywchpl5fR54FGMGPu2wEKBNVY/O5gPFE22FiCwCmjHujh0OhyM3yMGOJygDsoPKMYeFE+xu0PUqh8Ph2H+4DsrhcDgcuUhvOyzcn7gOyuFwOAYzA3gENeCVJBwOh8ORnd5Wkshm9s1z/Ff2O9WFIvKGiNR4jiU9xx7wn+vHjaD6gUSklfxIK3FJAlAaaSKVijA0Xkd5tIGo/WKuONHMkLw6KmN1JNW8S5QlGimPNlBofR8VxFsZkldHItZKWbSBilgDcUmSJEJbEUQlxdB4HaUFTdTlJUjktzI0XkdJpJHyeCMlkUZKY02URBopiTVREmkjEW+lJNJIIt4KQGVePYl4KwlJMSSvjoikqIg3kCdJhuTVMTRWy5D8ug5lzI+00ZyKtZdxSLSe4fkdVeuHxmuJiJKQVopsXEmEuLQRJ0lcUkQjKbMfSVIZb6AyVkerRskTYWi8jqrYHpOvaC0JaetU18XRZuKRJMMK6okIlEYaGVZQR1GkmeHxPZREmjqdMyzP5DOa38aQWB2VhQ1UxfbYa6NUxOopjzRQWtBEMhUhIS2URRvIj7SSJ0kqCxusryWTTlm0gZJICzWpNkoijVTEGojYciakldJoExXxehKRVkrjTeRJkmHRWlIaoUhaiEZMvRdJK3FRSO3NY11bgspYPfEic10B8olSGdt7PcrzGhka20N+pBWJpSiNNJGw7WJItI5d8SIA2lJRoqQojTWRkCgRhPKCRiqjdQyJ15OItVEebSARayMhSmW0njwREnmt7WlV5NUzNFZLUWEzTc3xDvVaWtBMVX4dFTETV1GkmZKYacd5kmRIvJ64JEkRoTDaQmW0joS0Epc2qvLqTLoR2yZjdQxN1DEsbw87pYSkCm2pKLFIstP19BIVbfcblbSu0AsLm4lJkvJoA+XRehKxVuKSIi4pKmN15EfaiEmK8mg9SY0Qi6QYGqslEW2jNN7E7tYCc19ElPxom/F3FWkmFa2jKr+u3f9WebSR8ngD8TzTTuNEiOe1USgpErY9x4lQHmmkMlbHrlhhl2UJTC+OoIKYfVPVL3vkPw8c4YmisZvPgDrgRlAOh8MxiOnlEVR3Zt/8XMpeQwahcR2Uw+FwDGY0+Oa1eGO3q3yxdWf2rR0RGQ9MxBjtTpOw8b4kIhd2l3U3xedwOByDmDAf4Hot3vQClwD3qKp33nW8qm4UkUnA0yKyWFVXZYtgQI6gcskflC9fp4nIQ31fAw6HwxGQECOoAHRn9s3LJfim91R1o/1dDTxLx/WpTgzIDoq9xmIPB76J8QeVJm2L7zBgBsYfVDsef1DfUNWDVfUIjBUJrz+oQzEW0m+056QXBs+1cV4qIjP6rngOh8PRO/TyGlR3Zt9MmsYEXQUe028iUiEi+XZ/KHAS0KVPvcEwxZfVH5SIpP1BzfccyugPyu5u9chl9AcFICLphcFlInIOxsVGA/Df3iiQw+Fw9Bq9qMWXzeybiFwLzFPVdGd1CXCXqnpTnw78SURSmMHRdd05fR2oHVTaFl8CGAmc7hfw+IP6ru/QTOC2AGl05w/qOBFJAH+26a8E/hG8CA6Hw7Ef6OUPdTOZfVPV7/r+X5PhvNnAoWHSGqgdlNfl+wkYf1BpW3tpf1AK/FtVHxGRCWEi9/iDOrkb0WnAGlV90573V8Cv9eJwOBz9xkA2dTRQ16DasVN1nfxBqeoRmXpx9vqDyojHH9QFIfxBdYtXffPVf64Nc6rD4XD0mIHsbmPAd1D97A9qOTBBRCZbuayuNlT1Ruu64+ij3jchaPEcDodj3+hdLb79ykCd4ssZf1D2Q7b/iEgD8AJGG9DhcDhyglwcGQVlQHZQOeYP6lHMWpTD4XDkHq6DcjgcDkdO4jooh8PhcOQiA1mLz3VQDofDMYgRHbhDKNdBORwOx2Bm4PZProPqD57YPI0RRbV8dtRT1KYKWNo8mnXNQxiZV0NTKk5hrJmkKhExzvFaNMacmslcXDWPvEiS6rZiVjYN56iiNRxauZmKWD2HVmxmdLyaF3ZP5c3mEYyI76apSmnVGOuaK1EVxg2vZnhhHWXRBpo0zrD4Hpo0zvSCTTRpnGW7R7C2vJSxxTU0aZyxxTUAzNsxjgml1axvK6EiVs8Tm6fx/rGvMi1vC1vayohLG/O2jetQxrNHv86LWyYRjxpDxhdUzOeNuuEdZGryC3mjtorCaDPDooupiNXz8IZDuLhyLvMaJtGQ2Mw7RqzgtaZxxplcvIEWjVEWbWB5awll0QZqkkU0xXaxra2U0fFOFq84tng1a1uGsrmhhDdbK1ndPIyN9WWsaBrF2qYh7Y4fvaxoGAFAeWkDTak4EVFqUwXEJcnatlIW1Y2hVaPUN+fR0hpjdKyGl+qm0JyKESVFRJS19UMYlreH5c2jGB2vZmnLCN5qGUqrRimLNVAseSxvHEWrxpiQt52URni1fiIF0VbebBlOXJJsbS2jPpVPq0apiNWzuHkU5dF66lP5rGkwn/2NL9jJWy1DUIWyqHGMtyPVSlNqr7PAsQW7eKNpJAB5Ra20aJQigV1tRdTH89vPm9c4nndXzGdZwyjWJ5VWFXY2GGeGZbEGGlvj1CQLaWyN82ZrKQBvthYztKi+Pa2URmjSOK1tUYaV1Xao15Y287jZ3VZAfUse9al83twzlLpUE1Ux4dXkBIZE64jbOanljaM4q3QJ5ZFmtjaXUt+Sx9S8rYyKtrE+2kBcUqxqGEZrKkpKhRRCpJuncUSUlEr7L0BjU5yjS9YyIlZDBGXrnhI+PPZlNrWV0pDK5/DidczdPo4iaWFbqoS1uytoGhJnybpRVE5t4PUdwzixYiXJFSWsHZlPSV4zJdEmyqINrKkfQm1pglebC8mTNipj9e318lYyxbCyWjYlC6iKNlHdVsRbbbCxrZyqWC0vN0/qsixBcVp8DofD4chNXAflcDgcjlzEKUk4HA6HIycZyFN8A9LUUa46LHQ4HI6cw5k62u94rZmfjXFYeKo9tkpVZ4lIDHga47Cw3R+Ux2HhJWmfUCJyMR0dFu4SkXMxDguP8zgsPBPjamOuiDzQnS8Th8Ph6G/cCKp/yeqwEEg7LPSS0WGhqm5V1dmqmo4ro8NCVW0B0g4LEZGjROQ5EXlVRB4TkZG9WjqHw+HYF1SDbznGQO2gCuw03nKMa4wf+AU8DgsX+w7NBF4NkEZ3DgtHi0gc+C1wsaoeBdyMMTjrcDgcOcFAdrcxGKb4+tNh4cGYDu8Ja/08CmwOk5bD4XD0JZLs7xz0nIE6gmqnnx0WCrDUpjdLVQ9V1bOyxNvusHDLfxaGKKHD4XDsA72sJNGdwpiI/MrOcC0UkTdEpMZz7HIRedNul3eX1oDvoPrZYeEKoMqO4hCRuIgckilRr8PCEefPCllKh8Ph6Bm9OcXnURg7F5gBXCoiM7wyqvrl9Es7ZgnkPntuJfA94DjMuv73RKSiq/QG6hRfLjksvBj4jYiUYerzeswozeFwOPqf3lV+aFcYAxCRtMJYNo3mSzGdEsDZwBOqWm3PfQI4B7gzW2IDsoPKMYeFC4G3dZ9rh8Ph2P/0svJDJoWx4zIJish4YCLmc59s547uKrEBP8XncDgcji4IsQblXSu321X7kPIlwD2q2mM1jQE5gnI4HA5HMCQVfAilqjdiDBRkI5vCWCYuwXx36j33NN+5z3aVHzeCcjgcjkFML38HlU1hrGOaRnmtApjjCX4MOEtEKqxyxFk2LCtuBOVwOByDmV5cg8qmMCYi1wLzVDXdWV0C3KW6V0NDVatF5AeYTg7g2rTCRDZEc9C8xWDniTXTdUi0nu+svZCPjJrDO4u2sT3ZwrLWIUyI7WJh8xgOzd/Ik3UzGJ+3nUPzt5IQ5YXGcVS3FXFm0XJKIlCvcMXrl/HVSY/zpw2n8sVxTzI6upvCSJK1rWV84rEr+fPZNzEutptH62fwx2VvY0hJPd+a8h+mxquZ3TiBEwvW8uedJ/GJIS+yqa2YkxIp3rfqbH42/l/8z1sXAfCV0Y/xy41n89dJD/FYQyVV0Vq2J0tY2TyCKflbGB2rocWnt7IlWcaI6O72/xPi9VQnO74PlUTaqE3FqIomKYvE2+N+s2UEpxeuoiQS5agnPs+zZ1xPSSTKQ/XjOD6xllVtlZyRaOCppkJmxHdSEonSrClaMrTlb218J+8dOo9EpJVj8ncRJ8LLzSUcnb+H6lSKqkhnfZuaVBsAn1h5CbdN/Qf31U7jgpLXKZQoUYRabaNQovyrbiL1qXwqo3WcUbiOFlXyRLivdhrHFa4GYGosyezmMk7O30N1qpXKSJznmsqZEK8mijIqGmF1m9E+rYy08nTDZM4rWk2hxGjQNppUKY/EeK5pCOcX1gHQqkk2JI2jxTdbK5mVV81Pt53K2eXGaMqpiVo2tLW2l+evNcfx2cqXaVDl/Lmf4r/H/ZnaVJJajTIkkmJhSyUAo6O7ebjuUKbkb+XdhbvYlWrihaaRTI5vZ2NbOU/uPoQfDH+R72w9iZ+NeJnlra2Mj8Gn153bntbHhr/AiFgtj9Qeygs7O1oZO3HIKg4vWMfYWA1/2XEKX656lsUtVRyat52nGyYzK7GOVa1VbG8rpSGVx0fLljKvuZQkkfZzJiR2Mjy+m9GxXWxsq+CYxHrebK0kqRFaNUq8m69So5IiqZH2X4AVzSN5sXoKnxj1HNPiO/lrzTG8XjeCn419EID/Wf8uphdv4YLSBdSkCpjbOJELShbzRP3BTMjbzurmYYzNq+bB6llMLNjBRaULqIpCqypbkjHGx1I0a4qKSD5PNpZw40ZjNvTmyffxsVXv4Z4p/6FZ29icbGNcLJ8IwlNNhSQ1wrsmLepeNbkbTn3X/wV+yD/34Nf3Ob3exI2gHA6HYzATYg0q13AdlMPhcAxinMNCh8PhcOQmA3gZx2nxdYGI1Pn+XyEiv7P714jIRmtv6k0Ruc9v8sPhcDj6m4Fszdx1UPvGr6zNqanAP4CnRaSqu5McDodjvzGAPeq6DqqXUNV/AI8DH+zvvDgcDkcaUQ285RpuDaprvEZpASrJ8FGah/nAtD7NkcPhcIRhACtJuBFU1zR6fD3NAr7bjXzWbwi8Nq7+c2dNb+bR4XA4siIpDbzlGm4E1bscAczLdMBr4+qJNdMV6vdnvhwOx4FKDk7dBcWNoHoJEXkvxrZUVt8mDofDsb8ZyFp8bgS1b3xZRD4MFAFLgNNVdXs/58nhcDj2MoBHUK6D6gJVLfb9vxW41e5fA1yzv/PkcDgcYXCWJBwOh8ORm7gRlMPhcDhykVzUzguK66AcDodjMONGUA6Hw+HISdwalCMMUbtquXZXJeurKoFttCIUSQuFkmJTazkAMxPrSSEUCeRLlA0tlcwsWE9ZxLS5KEoyFaEo0kxKhfpUPhPzhZVtMba0lRGrbGJLWxnH5dczK7GOaDRFNJKiSFqIohRGmomiVLcWEUUZH6ulIRUnEW0lipKIGqd3U+MNJKKtVKdaKIo0MzXeQIPmsbJhGIcXvEVElGnxxg5lbGqOMy2vkaR9e2tQmBjr+B1zVPIYGlF2pBRSrSQirUzLa+T5+nJqNUoqlSS6M06DRqgkQnm0gZIIFEkL21KNFEmMPBF2JFMMj0Zp0bZOdb2tsZiiSDMz8naxqS3GlHiEQ/NqSEicUdFoe/68DI8mABhWUEdchIPzN1MoxrHhpmSKybECmrWN4wrWUJNM8N+GgxgS2UZUIqxpa+Dg/M0cHEuxI9VKKxHqU/k0k6RBI4yJ5FEUaWZu4wSOL1hDKymaNJ8RUVN/o+PVtKJERSiTfGqTzcQlQkJaqEs1E0FIoYyzedyebKAsEufEkpUUSQsAG9paKfN8QFISbWJYtJhGbaY40UyrpnirrYQZefVEiLSfNzEmrGmo4sTClWxONrK6rZTjE5vY1JagKNLM2EQ1URHGJqrZlWqiMAKbksLQvL3f9I2L7SZflOMKV/F6/YgO9Xp4wTqqonWMiCqj82sAmBCvZnbTOLa2lTIi2sYLDRWsbRrKrKJ1VEQKqUkWsTNZzMn5exidX8O65krWNVcyoryG0bFdjInmU5OqI6VCEiHajUG5iCgplfZfgBFFe7h3/RHUp/JpVWFKYisv7JhMdTLG8GiSHU1FlJQ10aTmviqJNFEkUBXbQ1W0jp3RYhLSwtC8OkbGaxgTjdJMkkKJcnBcaFJY2lLGiYkGiiLNDE0YG9RvtuYzNFHHHm2mJqUMj0ZZ09bCxFieaX/R2i7LEpRcNGEUFNdBORwOx2BmAHdQ7kNdh8PhGMwkNfgWABE5R0RWiMhKEbk6i8z7RWSZiCwVkb97wpPWRdFCEenKringRlAOh8MxqOnNKT4RiQK/B84ENgBzReQBVV3mkZkKfBM4SVV3icgwTxSN1q5pIAbtCMrTUy8RkQdFpFxEXrZh60Rku6cnnyAia0VksSfsRBuuIvJDT7xDRaQ1i+PCJSLy7v4rtcPhcPhQDb51z7HASlVdraotwF3ABT6ZTwC/V9VdJnnd1tOsD9oOir2WyGcC1cBnVfU4j1Xyf3gsla+157zdEzbbhq0BzvfE+z5gqS+tX9l43wfcLCKDuV4dDsdAonc7qNHAes//DTbMy0HAQSLyooi8JCLneI4lrFeHl0Tkwu4SO1AepHPoXIlBaQBeF5Gj7f8PAHdnElTV14E2YGgP03I4HI7eJUQH5XULZLerepBiDJgKnAZcCvxZRMrtsfGqejTGsev1IjK5u4gGNXbO9AzgpgDiz4hIEmhW1eM84XcBl4jIViAJbAJGZUjrOIwGuDMY63A4coMQ30F53QJlYSMw1vN/jA3zsgF4WVVbgTUi8gamw5qrqhttOqtF5FmMi6JV2RIbzCOotDfcLcBw4IkA56Sn+I7zhT+KWRS8BPhHhvO+bNP6OfAB1c5jZe+byUN/rwleCofD4dgHJJUKvAVgLjBVRCaKSB7mmejXxrsfM3pCRIZipvxWi0iFiOR7wk8CltEFg7mDSmuLjMd4uv1sTyOyi4GvAl8F7skg8ivbsZ2iqi9kieNGVT1aVY9+5wfLe5oVh8PhCEdKg2/doKptwOeAx4DXgbtVdamIXOtREHsM2Ckiy4BngK+r6k5gOjBPRF6z4dd5tf8yMein+FS1QUS+ANwvIn+wFdwTfgE8p6rVIlk9uzscDkdu0csf6qrqw8DDvrDvevYV+IrdvDKzgUPDpDWYR1DtqOoCYBFmwa6ncSxV1dt6L1cOh8OxH+hdLb79yqAdQWVwNvguz/6tWMeDnrAJGeJYC8zMEN5+vnVc6HA4HLlJDnY8QRm0HZTD4XA4CLS2lKu4DsrhcDgGM6lkf+egx7gOyuFwOAYzbgTlCMO/qo9mbKKar05/ktHxapa1CmtbR1IeaWBTsoAZiY0cl1/DD7edzDlli9iYzOO1prHMLFjPK/WTiZOkNpVgat52jqwyVkdmlm/moPg2/lU/lrHxnYyO76KtKc7o+C6ebBzCC7UHM65iFyMK9tCiUeo1SpQU9RrlvIrXqNco9+4+ik9VzKUs3ki9RimzPp6u33kiZfHGdmPH1+88kbeXLOOKqheoTSWIkuL/tp/YoYzHF6/k/7bPJCLmpC8Mmc09deM6yAyJ1bGiaSQzC9ZzYv7u9njOL3uN9W3ljI3VcPxJr7O+rYwmraM+lc/GZB4tanwztWiU2hQMj0bZlExRkkHl56NjjMWqW3Ydw0Vl81nSEuGx2qN5e/EyalKFjIjt6XTOeuuPq641n+1JeLH+IEbEXqVIksRFeKChgnGxam7ZcSrNqRifH/4UTzWVktQIpZEIL9YfxJste5iat4XyaCMHxbdRnVTWt5WzM9lCq0a5tGQjD9SPYmreVqqiTaxtK2VnspitrcbfUEOkiW3JQqCQ2pTx17Q1maQkAvUKC5uN/c08STKvuYG7th7LZ0Y9DcCYWJwlLXsrozDSzLNNQlILaW4zt/yx+a083ljFpPiO9vq8s3Yi76pcwPLmkRyR1wSxPfxy+6l8asjz1LQV8GL1FN5TsogXq6fwwdLF1KTyGBJpZk9boj2tFxsncUj+Rm7dfhJNyXiHen2s5lBOLn2DLW2tzNk1iXNLFnNH9Ql8f9g8Xont4tXmoZxYuJJZiXU8UzedZ+M7mZq3lVmykUcaRjNn1yS+MvoxhkUbaCHCy40T2ZZsYEPLEJIIKY0Qka6/5Ymi7X6jkhht3Fd3j+e9YxdwUHwbhRHlzs3H8s4Ri4mIsj0V4bzhS3mpZhIXlSxmT6qOe7YdzZEFb3HDulN554gl/HfXFK4a+Sz/WHwUw4fuYfe4Vzm84C3KI4281DiJdxUvZ1i0jt2pJE1aQlMyTkojTIg1tdfR8EiMOc3FHJm/mx2pJoZE4IWGg/B/kNkj3BqUw+FwOHIS10E5HA6HIydxHZTD4XA4cpLkwFWS6NcPdbP4bCoXkZ1izTWIyAnWJ9MY+79MRKrTLi1E5Esi0iQiZZ54TxOR3TbuRSLypNdplrWLt9xur4jIyZ5jcRG5TkTeFJH5IjJHRM61xz5mfUYtsnm+wIbfKiIX759aczgcjhAM4A91+9uSRCafTTXAZozdJoATgQX2F+B44BVVTa+GXooxYPgeX9wv2LgPs8c/CyAi7wQ+CZysqtOATwF/F5ER9rwfACOBmap6JHAhUGI7yG/Z8w6z+VjUO9XgcDgcfUQv2uLb3/R3B+XF67NpNns7pBOBX/n+vwhgfYkUA98mixkjOxIrAXbZoG9gjBfuAFDV+cBtwGdFpBDjDfLzqtpsj29V1buBYUAtUGfD61R1zb4X2+FwOPoO1VTgLdfIiQ7K47Mpbbb9RfZ2SJOAfwJph4EnYjowMKbe7wJeAA4WkeGeaE+xLjDWAe8Abrbhh2Ask3uZZ8OnAOtUtbPuMbwGbMX4N7lFRN6VQcbhcDhyCzeC6jHZfDbNBk4UkYnAWlVtwgyGioGjgJet3KXAXXa6716My/U06Sm+scAtwM/2JaOqmgTOAS4G3gB+JSLX7EucDofD0ee4Nagek9Fnk6q+CZQD78JM/YEZ9XwU02HVicihGC+NT4jIWsxoKpu18geAt9n9ZZhOzstRwFJgJTBOREozRaKGV1T1Jza99wYtqNdh4ZL7VgY9zeFwOPaNZDL4lmP0dwcFGJ9NwBeAr4pIWvX9JeCL7O2g5gBfwq4/YTqja1R1gt1GAaNEZHyGJE5mr1vhnwE/FZEhACIyC7gC+IPNx03Ar623SESkSkTeJyKjRORIT5yzgLdClLHdYeHM90wJeprD4XDsE5pKBd5yjZz5DkpVF4hI2mfTHZiO6DzM+hCYDmoSHdefzvNF8y8b/jJ716AE2A183KbzgIiMBmaLiGIUHz6sqpttHN8GfggsE5EmoB74LhAHfi4io4AmYDtGAzDNn0Tkeru/XlVP6HltOBwORy+Rg1N3QenXDqobn03/B/yf5/9aQDz/J2WIz+vBscx/3CP3R+CPWY61AP9jNz+nZznnimxpORwOR7+Sg8oPQcmZEZTD4XA4+oAcVB8PSk6sQTkcDoejb9CUBt6CICLniMgKEVkpIldnkXm/iCwTkaUi8ndP+OXWSs+bInJ5d2m5EZTD4XAMYrQXtfPsN6u/B84ENgBzReQBVV3mkZkKfBM4SVV3pc3MiUgl8D3MN60KvGrP3eVPJ40bQTkcDsdgRlPBt+45Flipqqvtev1dwAU+mU8Av093PKq6zYafDTyhqtX22BOYb0u7yLuq2/bzBlzVm3IuztyPc7CVZ6DEOdjK09cbcBVGczq9XeU7fjHwF8//y4Df+WTux3zO8yLmc6FzbPjXgG975L4DfK2r/LgRVP9wVS/LuThzP87BVp6BEudgK0+fop7vNe12Yw+iiWGMKJyG+WzozyJS3pP8uA7K4XA4HEHZCIz1/B9jw7xsAB5Q1VY1BrXfwHRYQc7tgOugHA6HwxGUucBUEZlore1cwl4j32nux4yeEJGhwEHAauAx4CwRqRCRCuAsG5YVp8XXPwQdNocZXrs4czvOwVaegRLnYCtPv6KqbSLyOUzHEgVuVtWlInItME9VH2BvR7QMSGLcG+0EEJEfYDo5gGtVtbqr9MQuVjkcDofDkVO4KT6Hw+Fw5CSug3I4HA5HTuI6KIfD4XDkJK6DcuxXrFaPw+FwdIvroPoYESkVkZ+IyB0i8kHfsT+EiKe4e6nMciIyLv2hnIhMEJGLRWRmiLTP9P0XETlORN5jt+NERDKcd66IrBGR/4rIESKyFHhZRDaIyBnePIvItdaw5G4R2S4iL4nIFVnyE/Ode7S189VdOT4TtMxdxDFCREbY/Spb/kMyyE0TkUdE5D8iMllEbhWRGhF5RUSm+2RLRWRyhjgO8/0/x7NfJiI3icgiEfm7iAz3xReozQVNuytCtM2P+v4Xisj/iMjXRSQhIleIyAMi8jN/nLY+vyEiv7HbN/z1GCD97/r+ny0if7RpPmD3O5neCfuRqW0XR4jIYVnuxzIRuU5ElotItYjsFJHXbViotAY9/W1aY7BvwL3AdcCFmO8F7gXy7bH5IeJZ1xM54GpgDbAc47RxOcZr8FLgK2HjxHy7sBJ4BPiL3R61YWf5zlsITAdOAHYCx9vw6d6yA//GeDUeA3wFYwJlKnAb8GNfnFfYuN4AzsV8X/EUsB641CP3Fd/2VWBH+n+Iel/s2f+krcu1wKcxjjFvAlYAV/rOex54F+ZL+rcw34uIDXvKI/d+YJOtq6XAMZ5j831xeuvsLxjHmuOBLwP3h21zYdLuo7Z5N/AL4A/2Gv4OOAXjB+4Oj9w3bB6vBj5st6vTYT3JJ3A98LC9Lifb7RIb9mvfeW3Ak8CVQHkX8c+wciuBFts+1gC3AmUeucdsmUZ4wkbYsMeDludA2JyaeR8jIgtVdZbn/7cwnoDfjTGceKTn2Fc6x2AOAd9S1cowclZ2KcZ6cCHmwTpJVbeLSBHwsqrOtHL+j+28cZ6uqkVW7nXgXDUOJL3lnAg8rKrTPWHz0+UTkfWqOtZzrL1eROQ1VT3cc2yuqh4jIhFgmapO8xxbDLwdKAFeA45Q1VV2BPGEqh5m5WoxD5ul7HV0+SXMgwlV/b4nzvd0UfYbVLXKk/ZxQAGm05miqlvEfHT4jO86L1DVI+z+SlWdkqVeFtr63CwixwK3A99U1X9548h0ni89b30GanMh0w7aNhd1IXeQqub782xH35uBkaqq9v9rnmv5BnCIqrZ2iNB8KLpUVad6wvZ0kX6BqsbScarqQZ2ETNpv+OJcjLHOfSnGuOl/gTuBf6tqo0fuJeByVV1h6/Ozqnq5iHwCOFtVL7ZyK1T14IyZ7OLYgYj7ULfvyReRiKoxFayqPxKRjZg3bP/w/8eYt8e2DPFEeiAHkFTVRhFpARoxow9UtV46zsqdgnkzrfOdLxgLxmliGFMmfjYCcV9YjYh8EigFdonIlzFvze/wpVMvIier6n9F5N1Atc1jSqTT1GFSVXcAO0SkTlVXWdmtPtFDMG/nRcD3VbVBRC73dkwe/gH8DeMCwE/Cs9+qqg1Ag4isUtUtNu1dIuI/N+rZ/6XvWJ5XTlU323heEZG3Aw+JyNgM+RlmOwoBSkVEdO8bpve6B21zYdIO2uaGY6xW+10oCDA7w7nYTunhdFnsf2/6KWAU5qXAy0h7zEsNZiS41Z+OiKz3/G0SkWNUda5P7BigyRfWqqoPYeqmADMKvgT4vYg8pqrpadQCVV1hy/CKiNxg9//s6+DfEpH/AW5L59O+YF2BmQlwWFwH1fc8iHEV/2Q6QFVvFZEtwG99svMxUzWv+iMRkY/3QA5gvhiHYUWYaZTbRORRm6dlHrmXgAZVfS5DnCs8f2/G+IC5i70301jMDXuT79TLgW9jHnZnYd5AH8M8aD7hkfsU8BcROQhYgplKQUSqML5nvKwTkZ9gRlDLReQXwH2YTm9zWkhV1wHvE5ELgCdE5Ff+cnlYBPxcVZdkKPs7PH9VROL2Tf58j0yCzi8GvxeRYlWtU9U/eGSn4GkLQK2ITPZ0tJtF5DSMuRj/2tafbbnBTH8OBbaLWRNb6JEL2ubCpB20zT0EFKvqwgxyz/qC5nnq6GMeuclArUfuS8BTIvIme9vcOGAK8DlfnLdjpj07dVDA3z37VwB/FJES9r5wjQV222Mdsp7esSOmu4G7RaQMM42aZpWIfAd4GngP9pqISJyO7eMDmCnK52Tv2uEWzHTs+zPk+4DFTfHlECJyMFCtqtszHBvuedsKJGf/x4D3YTqJezCjoQ8C6zA+W+p7kM/pGB8wo23QRoxxyGXZz+odRKQU+CymPL/DTLlcgSnPD9IjAt85RcA1wHGq+rYMx08B3rKdmv/Y0ao6z+6PAzZnmGoaDUxX1Sf95wcoz+GYF4M3feFx4P2q+rewcfZF2mHaXC/lzTs6RMx077F0bHNzVXWfvPHZzr09zvSo2CfzNVX9eYC4yoH/xaxFvQZcp6q1tiObrqov7UteD0RcB7UfEJGzMW9a3pvr36r66H7ORyWAdmH/yr7ReW/YHj94bOd4JZ3Lfj/GhlerR7bP6ihIuUPG120decp+EWZ6CmyZgJsydHKB6j1oPYWpz9685ja+9LSwN+1XNMPDRkSmkfll5/V9iLMM8+LilX1MVWt6ItcX5MozIddxHVQfIyLXY6z53s7eqYQxwEeAN1X1ix7ZMsxi7IXAMMwoYRvmoXZd+sYJKmdlx2Gch52Omb4QzJrQ0xgNqLVW7gjgj0AZe03gj8HM6X9GVecHKOsjqnqu5/+d9vzbfGW/HKhU1Q/0YR2ly32GzUPGclvZQJ2JiMwCbshSR59W1QU9KHuYOAPVUwi5MGkHrfezMFp5b/rinIJpR4974vwGZtr3Ll8+LwHuUtXrehDnRzBuxR/3yZ6JWYu8PYxcyLKn5S7ArMVlk7uegO39gEdzQJVwMG8YjaBM4YJpjN6wQOqnQeVs+BzMnHfUExbFPARe8oQtxEyB+fN5PEajKv3/yCzbUZjpr27L7j/WS3V0ta+OApXbht+J6ZyPxzwoxtj9PwL/CFtHIcu+z3H66ymEXJi0g7bN14EJGeKcCLzuLw8QzyCb58tnmDhXkEEVHKjw1XsguZBlDyoXuL0f6Fu/Z2Cwb5gF+GMyhB+L5xsbG7aii3hWhJWz/7M2eN9DoCu5lZ79JGYU8kyGrdF33kuY9a+IJyyC6The7uM6ClRu+z9oZxKojkKWPUycgeophFyYtAPXOxDLIJOXIc7lwPgMsuP3Ic438Hxz5Akv87X3QHIhyx5ULnB7P9A3p8XX91xBcG2hoOqnYdRUXxVjPeA2OmrdXQ4s8Mg9IiL/wUw7eOU+gvkQN83rwCfVt7Bu8+BP+xLgp8AfRGSXDSvHdGaXeOSuoPfrKGi5AapF5H3AvWpVs+2i/PvoqC4dtI7ClD1MnFcQrJ6CyoVJO2i9h9Hy/BLBtPPCxPkjjObq4744zwR+0AO5MGUPKncFwdv7AY1bg9pPdKctJMZczibMVNUFmLluMOqyDwA/VbvIL+bD0G7lrGweZn3lAk/6GzCqyDeparNH9lwyL1g/7JG5GPOW51U9Tx+7UFXvz1L+IQBqHZf5jp2pqk/0ch2FKfcETGdyOns7pHJMZ3K1GrfVgesobNkxn3sEjjNIPalxIhekPscFSTtkmwus5RlEO8+mPSJEnBWYb7H8yg+79kGuV+9LKx/oOvrLd0DR30M4t5mNcKZlLu9NOSv7zYByv+2DtAOVvY/q6Ju+/0OAIVlkz+zNOgpZ9r6Isy/SDlrv9/ZBecLEOac35UKWPahc4PY+WDdnLDZ36GRstQu+2MtyYKazgnBSH6QdtOx9UUcdyq2qOzXDSMfy04BxBq0jCF6mvoizL9IOWu+TQsQZNJ9h4kx0LxJKDnr/vgzT3gclroPKHcLMtfbFA723b4Yw8QUt+2CrIwhXpt6Osy/SDlpHYdLui/IMhDZ3wK+/uA5qYNKfN2x/xddX6fdnHQ1GDuQ66s8Xg0GJ66Byh5YQsv05OuiLtNcGlOvvOurttCF42cPEGbSegsr1Zzs6kOMM094HJa6D2g9IACd3qnp8iChf7GU5gH8GlPt10LRF5N1iDKl2iaq+B0jbgOuAeDzw9lEdBS03BO9Mfi0ieSLyEbHGZkXkgyLyOxH5rLec6bIHjDOQE0FVPV6MU7wPiMhX7PYB8TnDC1GfQa85eOpdRColuyPJb2QKlMxOJc/IENZlnCIyXESOtNvwDLKXhZELSI/vSxH5sT8sZHsflDg18z5GjLuJqzFvTT/FfOewBOMg7WeqepNHVuho2PV0jMrqcoxfIr9rgUzpfVRVb+lGppMvHNuBfg/jvuC7wOeB92K+e/qiWiOsInIc5uv9PWJcD1yNsSSxDONccLcnzkagHuPc8E6MCm8n455i3DzcgVmQng9cpXtNMLX7QOpB+m+3ZRiL+cD4DeAvqrqym/qZCByB8UW1PGwdWdm/YdTHCzGmg4oxVtfPwNx3l3eVBxvHjap6led/EuOg8S7gTs1inFeCm/uJYNrje+3xdB3doKrPBsjf06p6ui8sjIkpv48pwZgK+jGAqvrdlGTKg9+81iyym29qN9kVVC5LmidjVOOXqMfMUlA5EfmNXxTTEd4OoKpf6KLIBxb9rUY42DdgMeYhNQTjA2mEDa8AFvpk/4DpmB4A/op5u78M80D6dcD0/F5La4E9dqu1WzId7pF7FPPAvRrzpfs3MA/2z2OMWKbllmK/6gduxDgAPBnzQLzPl/YCW85PYFx9bMU8FE71yc3FOKQDuBhjOSDtfXeBTzZQ+sBPgFswPq7uwfgy+oTN0/t8cd7v2b8A4wX1Fow5nCvC1pGVXWR/Y7bcUftf0sfs/8os2xBgQ4b6nIn5yHQlxmL21fjMABHc3M8tGCvvJ9t6vBbTiT0JfN5fHt+2GGhO//fIhTExVYvxxfVde/2+h/kO7XvA9zxyYcxrLSSYya5AcjbsFc/+J+y538OMhK7ugdx6zP39EcyH45cD29P7+/P5lOtbv2dgsG90dLHtb/gLfP8X2984xrFgnv0f8z0E/A+LDg8NX5y/wbyZDfeErcmQzwWefX8nt9Cz/7pmKJtfLsvxEcAX7ENsfRf1cgjmIXthhjgCpU9Hkz4x4EW7X4F5o81W9tnARLs/1PdQC1RH9v8SjCmeCsyDuNKGJ3xlSI+K1ni29P+WburzWIwzxA3AbE94UHM/i3zHX7K/+XS2cZd+aZqGMUU0AfOgHY/HXBHhTEyNw7yE/RQotGGrM5wXxrxWUJNdYcw8ea/7XKDK7hf52llQuRLMC8HfgVHZyu02Z+pofxDGyV0bgKq2inF73mL/t4mId3ovsNdSVf2CiBwF3Cki92N8KGmGfHrzcnsXx5Z4phFfE+svSYyzwVbfeR0Wg9V8Kf8b4DciMt5zqFVERuheD7VLReQMjPO7yb44g6afEpFKNV/vj8J6uFXj/da/SO2tj5hayxGqusNX70HrCIwJnuU23W8B/xSR1Zg39Ls8cquBMzSzLyq/6Sh/fb4CvCIiXwW8fq6CmvFpFeuwUESOxC7Kq2qz+DwEq+q7ReQizKj156r6gIi0qqrfy21gE1Ma3KlkGPNaQc03hTHzFLFWIiKY6dntNv/1ItIWVk5Va4Ev2fvybzYfTh8gE/3dQw72DfNgyGSxeTTwDl/YIxhvpH7ZEXScPrgJODlLen/PEh7BjF5eADZlOH5tlrSnAPd4/pcBtwKrgJcxncJq4DngcN+5pwWso3f4z7Xh5cC3fGGB0sdMM70FPIFxZni+Da/y1xHmDT09BdoCjLTheXQcuQaqI0/4KPa+IZdjpi+P9cl8NlPZ7TH/NNsHQ7S7Csy02lftdglQ4ZM53dbNSsyI7ThPHf0sS7xFmFHbv/FNQXrq7NOYh/xiuz0KfAbI7yK/RZhp2OczHLsYODjLeRdmCDsXM5X8oN1uAM7bB7m17B3Vrva0j2I6jtoDyfniFtsG/hr02h5Im1OS2E/IPjiFE+MRtkhVt/VCPkYCR2gXtuMCxlOKcXcQwzyospYnTNkloHPBIOnbuCZhpmxquixQ5jTKMZ5Q54Q9154f2MleD+LuFeeTNo9DVHVHyPQPB05Q1RvCnNdFfL3qVHJ/ICKFmKnzNT2R25dnwoGCm+LrY7JpC4lIDT6ncFa+jMxePrf55PbJa6mIrNHOXkuDemsVYLpHLiYi2/xpd1N2r0ZVJ80v2wF10vwKkz5mZDQZeJud1evSY2qWB8Ycn0zQOsrqZE9E/E72gnqVDVRPvnrfgHlL71TvloOBC8S4rc+ato23U9sUkXLt6CAzmxflTp6Ew1z3EPVeRjCngYHkPPFmu9/8nU63ckHvC4dTM+9zRGQhZv78ZV/48cCfVPVwT1hQ9eC+8Fp6PcG8sIZJO1DZRWQOZtH4HrVq6CISxajcf0k934METT9oXVrZrrwJt79EBK0jK/s6cG6GznUi8LCqTrf/A12fMPUUot7DpB20bQbyJByyPGHq/TFMB3eb2jVNMZ8HXAGcrqpnhZGz4UHbXFC5hQR8Jhzw9Pcc42DfCOkUjmDqwX3htTSoF9YwafeGRpVf8ytQ+kHr0oYtJJhqchjPv4Gc7AW9PmHqKUS9h0k7aNsM5PwxZHnC1HtfOP0M2uaCygV+Jhzom5vi63vCaAsJmTXsUnTU4Iqx903Sy0aMirr/3FEYhQEvI+2xNE0icoyqzvXJHQM09TDtoGUP41wwaPpB6xLM+t7LfkFVfcmu/6UJWkcQ3Mle0OsDve98MkzaQeszqPPHMOUJU+9vSe87/Qza5oLKhXkmHNC4DqqPUaPmncnJ3e+1s6JCUPXgvvBaegXBvHwGTjtE2T+CWbf4vkeu3bmgrzxB0w/jMTXoA+MKAnpCVdWfiFHrvwA4wVP2D2lHCxBfItj1gYD1FKLew6QdtD6DehIOXB7CeaD9AObj5edExO808P09kIPgbS6QXMhnwgGNW4PKEUTkt6r6eQnu5bPXvZaq+UYoiBfWVNC0g5AuewC5b9oHf6CyB61LKxvYU26QOtKAnlBF5F7M6CLQ9QkY5zdV9ScB5H6L8U0UtG0Erk97XrdelMOUp5fr/XJVvS2oXIg2F/i+DJB2oPtiUNPfc4xuMxvhvMUG9QbaF15L+8K7aV941A2UftC6tLJBvQmHyeeCPoizt69lX7TNfitPH8YZtM0FlXMedXu3u3PsJ4J6+ewLr6V94d00KGFcHwRNP4zH1KCeZfvCWeNAcT4ZtD4Hm2sMCN7m+uLeGJS4DmpgEvShFmb+trfj7Iu54/4sTxj6O87eTr+/6/1AjvOAxnVQuUNfOM4bKPSnc8H+pj8dJg6U+jxQ62igXJ8+w3VQuUMYp3D9OeXRF15Yg5Y9jHPBgVBHkMVx3z6kDb3vfLIv6mhtiDiDlidMvfeF08/ebnNhngmDk/5eBBvsG0Zdd6jdnwI8j/nS/mXg0B7GOTOg3Fn2NwJE7H4expdOpU/W/7/YypX3MI9nhSk7RjvsSjr7NvpYT9PPEPbuntallf12CNlSjE+qO/AZeQX+0M25n8kQVonxK/Y/wNcxaz1XYNSif4bHiC3GuPAfgd9j/EpdgzHaejfWgGnIuqzMUr6j6GyAdqY9NjnDOYf5/k/CqGb/0La3P2PclPzT3w6sfKaPiodmCJuGMZ9U7As/J2B5P9pbbS6L3Ce9ZQK+ba/jj7FuR9xm66e/MzDYN2CpZ/8/wEV2/zSsjyLP8Y959sdgnPzVYFxoHOQ5Ng1j+fw/GFtzt1q5VzDGTb1xXoj5vmMzRv31ZRvvBuBdHrk/ePZPxli5fgbzPcd5nmPz7Q3V6QHU07LbG/N5jNmbVXiseNPZB9I5nv0yzPclizC+dbw+r97j294LbEn/98V5H8axYSdL5T65JMZCxA+AGd3I3gtcZ+v/Afs/318m4Cu+7avAjvR/X5x3A7/AmNN5CuM65RSMFfA7PHJBnU8eCrxkr/GNeDobPNbz7f+/svdl42zbPp7EfOT7Po/c+4FNGOscS4FjuriWz2Msn1+N6Zi+avN5JfC0R+7tmPa6A2NqaUIXcX4BY/Xifswo7YJssl1cO7+vr0D3G8Hbpvf6/8LGdyrwK+D23njuDJat3zMw2Dc6mleZ6zvmdxjnbbh3A1dhRj8XAU95jj0PvAtjR+0tzIeAYsOe8sW5APNGPRHjUuJgGz4emJcl7WeAI+3+JJ/cGuDn9gH1CvBlrEuJnpYd83af9pJbDjwM/Cqd/y7q6C+Yt+/xNh/3e461YvxJ3YzxHHsLxp3GLcDNvjg3YrzuVtt6vwjrLDJDXXbr0dbKLvT9/xZmumiIrwyBvMp647TXegt7v2P0e+ld4NnvyvnkfzHGX8uBr2E6lMlZ6t3rcG92usx0duq4kL1uJo7F+MS6KEucXeXTeyyMx+XF2BcNjFPFecAXM8QZxulnoPuN4G3Tm4+F2JGh/zq6zXVQfV/B5mF2K+ZB/7+Yr/fHAx8FHvLJehv4Qt+xBVn2/fb8/G+UXlm/J9n5WfZfDSh3CuZtfgumU7uqJ2Wnsw2/KObt8594RmEB6mihZ/8YzCjj056wNVmu0QL7Wwpchukgt2M6s7MypW3/Z/Romy4TdlrVE3YFphN4yxMWyKtshvL5O9nXsuz/0Ce3KJOc/f927MM/Q1mXAqV2/7/estFxpLzYd95I4FXMyMYf56sYI7DHYEZHR9vwKd3ksyuPy/72UowZUf7SV39bgVm2PXq3Cfj8pRHwfgvRNldjXoLeS+e236GsB/rW7xk4EDb7YHrZ3oS1wDLMtFaZT24bxuPsb7H2uzzHlnj2vTfvZ3xxdHJnzt71p2M94VFfnA3sfYOsxU73YEZwXrlO0yQ2rnOAWzIc+2h3ZceMdE7NcO4PgZQvbAN7p8JWY0cR/nrx5P2LmM7zWLI/+DOVaQjwKTpONS3Icr74849ZF3pHBtlzyGAsFDP9+iJmhJAtn38hs8PEycB/Pf+DOp98LUMbPAzTSe30hb8f06F8DNOZ3ouxmXcr8AuP3Gx8078YF+dP0Xlkcgamo3kdM618L2Zkuo2OU3PzgBG+c8dgRh+1vvCngVm+sBjGjFXSExbY6ScB77egbZO9I/r0NtyGj8A3A3Kgb/2eAbd5Loa54b1bupMYAfzYI/fJLh5A1/vCjgESGWQnAB/2/Pe/SebZ8KF41mwwbhh6u9wFQEGWY6N9/7/n26o8dZRx/h5jduZusj/4O3lxzSIX2KNtD+shq1fZAOdKD875I3aqzBc+Dvhzlvb1U+BfGHt5fwTO9skcDkzJcG4cY4ewuzwNBaK+sGwel8vo7HF5DL7OzHPsJM9+RXd5ScsFvd960jbd1vXmbPHtB0TkWEBVda6IzMC8RS/XQW4YUkTyMPP1G1X1KRH5IHAi5o35Ru3ovG4EgKpuEZEqzPThCg1oWy0XEZFJGKWMsRgFizcwb+d7ehhfuj43qeqTXdVnwPjmq+qRPcnLviIic1T1hAzht6vqR/ZD+oHKvr/qaH+Ve6DhvoPqY0Tke5hpuz+KyE8wmldFwNUi8i2fbKGI/I+IfF1EEiJyhYg8ICI/E5HigOl91/f/HM9+uYjcJCKLROTv1r1A+tg0EXlERP4jIpNF5FYRqRGRV6wBzLTcF0RkbMDi3wKcD3xJRO7AGEV9GTOq+4snzk9iPNe+JCKfxkz5nQ/cJyJX+srzBREZE6AeykTkOhFZLiLVIrJTRF63YeXdnDtRRN4jxtOtNzxQHVnZLwJ/wqiDHwPkYzqql0TktO7yb+N4xBeUrs8vdlWfIYj2tI5s/t7oQZppErZte7cHgfek/weJJEMdBSXwN0sicpFYl/QiUiUit4vIYhH5h7ctishxYjwCIyIFIvJ9EXlQRH4qxoNvWm6fy33A0N9DuMG+YdZ0ophvWPawd6G5gM5rJoHUiLtJz68NFVSzKKim0m6MGvELwGew0xhZ8rLI/sYwi9JR+9+vdbbY1s8QoA47RYOZXlnoizNQ+sBjGPXqEZ6wETbscZ+stx4uwGgq3oJZH7kibB15r7vdLwSetfvj6LjofmSW7Shgc0/qM0Tb3BOijmqtfK1nS6bDe5D2fLv9FfPZwan2d7PdP7UndRQm/RD5XOb5/w/MvTMGs7b8hOfYUvZqo96I+WziZMx0332+OLstt9vcGlTfV3AW7Tv7f2Gm/3SvRrwny1YLtPniDKpZ5M1nV5pKCzAj77MwC83bMVpSlwMlvvOWYD4MrrB5q7ThCTp6GPXG79fY8tdZoPQJ5zHVW/bZwES771ehDlRH9v9i9n73VEFHVX3vwnoSs7D/TIatsSf1GaJtNoWoo99gFA283/Os2Yf7Yr69jl8GnsAqNpBhnTBMHYVJP0Q+vZ9L+DVcvfdQxjadQS5Qud3mPOruD1pEpFBVGzBvfICZgqKz11LALFaJyMNqW679710srMF8ALnVf66I+L2BDhORr2A6uVIRkXS8dJzijXr2f+mLI8+XvRTmg8nHRSQOnIsZVfwcqPLI3oT5DiaK+Q7onyKyGqPGfJc3ThGJq1lDOd9TlgSdp6GDpv+WBPeY6q3bmKqusQntEBHvNQpaR2BGq3NF5GXMKPinNg9VmO+t0ryOsSzwpu/8TNcyaH2mz89X1WZfWKWqptPfFrSO1DjZOwq4U4wjxt+xb0ZPxV7HX4nIP+3vVjI7UQ1TR4HTDyH3rIhci7EM8qyIXKSq/xKRt2NG9GmWiMhHVfUW4DUROVpV54nIQZjv8gAIUW5Hf/eQg33DvkVnCB+Kx9wP5q04qBrxD/GojPtkf+r7/z0CaBYRXFNpQRdl7WSmBeNSfJTdL8eoUR/rkzkUOzXiCx+NT1U7aPq2Pn+KeaBX2+11G+Y365Rk7wi0hb0fmubRceQaWHvShh9iyzutizxfjv14OsOxC3tYn2ntz//Q8VOFkXhGAGHqyHNOBPNN0wv4vhfyyZ2bIexTnv1OJqYwLyc/zhAeqo5s+JUZwq7z7FcGlcNoIF6D+Th9HebFshZjIWKcR7YMo3a/CrM22IpRN3+ODFqIAcodSNNwMG/9ngG32QvRzZQDHb+pODNgnIeESP/ygHK/CCgX+ObqruweuTl4TD71VvpdxFEOnNCD877ZB2UPdH28cQKfwKiERzGfFSwioL24AGmMxGMCyxN+pv2dDZzuCf8f4JEephW6jjAfW3/I8//3wE0Zzgkk5zleBgzJcixt7aIUo25/FJ4pUY9cUBX3A95hYb9nwG32QgT0rGplc97DaMi0A5W9t+qInhsD7QtvsUHL3qM4gc9ivllaDJwYIo6e1lG6cxyKsfN3CsaiyL1kMB/VV3WEUUJ6AjP1exvw6yznBJLrzWsUQi5QuQfz5tTMc4cw8/kDwcNoX3iV7a06+n6IeLz0hbfYoGUKE2eViHzFrj0mMJqDC4HjbVgQelpHAmb9Dng3ZkQyCrhYVcO4w/ASuI5EpNKqhBcAH8eM3GqB76dVxa1gILmQ9Pa9sS9rfIMCtzA3MOmLB3pvx9nfN9c0EVmUIVyA4RnCg9CfZQ8TZwRjXijNffbXG0aW+oF9q6PDRGSPjUMx63iTgIutfk5pD+MNgmLMMaknfcGs8Zxv/6fdrQeVC5t+b8od8LgOKnfob++Z/elhtC/SjgEfwVgG98cxO0Q8PaE/R64AW1W1wwhIRCIYBQ+vFYvhGNcZvVlHr2nvW14IXEeqOjGIYFC5fqa/nwn9jpvi20/4LSLYsOs8f8/whHdqmCKS7/m7NmCy7VMqvvPTYd6pjBczhKXlvDdzUO+m7WUIWnYROTeD3Kc8fy8LmDYYrbxiVX3Lt60Fng0RT4fs2DwFrqMQZQ90fULG+XcRKRWRIsw3VMtE5OseuYcIWUdB26aInGTTRUQ+LCK/FJFxWeLsizp6n4iU2P1vi8h9InJEhvMDyQUklLfpMM+EA5b+XgQ7UDZCaAvR2ZVCMRmsHAPX+v5Hgb9libNLlWNP+ItYaxf2/wx8FtJteCA13jBlJ4TmV5j0u7kuXid9gVSjg9ZRyLIHuj4h41xofz+EsVASp2cWJ7x1FLRtLsI8iA/HfFz9WeC5/VhHaasbJ2M62/OBl3sqZ2UC3W9B22bQch/ImxtB7T/eC1whIpeKyG0Yiw+d3qAsG0TkDwAiUoH5KPWvGeTGisg3rVw+Zq2h08eMlvuBu0UkKiITMKaAvplB7sfAgyJSbD/M/CfG22yn8ojIh9J/ROT3eD7S1b0fg0Lwsr8b+LGInCIiPwKOw5geykSY9LviKc/+d0TkdE+c/+NNX1WX2N2gdQTBy34/wa5PmDjj9kPmC4EH1HwI3ZP1D28dBW2bbWqeuhcAv1PV3+NbA+tBee4neB0l7e/5GEO6/6Hzx9Rh5CD4/Ra0bYZ5JhyY9HcPOdg3zId+6W085m3yd+mwLs77GXADxpvoe7PICOZjwW9iHhRf6iYvgVSOMQ+02VYu43dHBFDP7UnZgWGYt+9bILsLiSDpB7w+Czz7gVWju6ujHpa9y+sTNk7MB7UbMW/qYs95YV/qKETbfM62yzcwH4VH6OzMsNfryCP3EMZY72rM92z5ZHAGGFQuzP3WXdvsSbkP1M252+hjRGQNnbWF0qiqTvLIvsd7KvAdjFv1R63wfVbOuwgdx9xgL2JM4aCq8z1xetWKBaM4sAhzU6Cqv7Ryv6Xj2/UZmC/i11q5L1g575x/Ceat9kWMy3LUM3IJWnYRqfXJ5QFtdl/Vo/kVJv0giM+dgogMA57EOudTzw0StI5Clj3Q9QkTZzfljalqW3dyvnPmY6yXePOZsW16zhkBfBCYq6ov2PWn01T19rDlCVNHnrgLMW5tFqvqmyIyEmO55fGwckHvt6Btszeu44GC66ByCBG5pYvDqqofs3LPdCPnnab6XldpqtX2EpHLu5G7zcr1683V2+nbh+9UX5wZO8igdRQy/UDXp6eIyPkYk0vt33Cp6rUh45iP8b6bjfa22RfsSx3ZFw5v2deFlQt6v/X3vTEo6e8h3IGyYXz3lNj9b2Pmr4/op7xE8CzydyFXARy2v8oOnAQU2f0PYwyyjtvX9LvJ24J9PL/LOurJde/u+oSozxswFsjXY+wwLqYHi/A9qSOMAdu5GPcpLZi1nt37sY7ejVkfqse4T0kCS3sq10dtL2eeCbm69XsGDpSNcNpCP8PY84pjFqi343HP7pH7opUTjKHZ+WSxtYaZOy/FOEtcBmwAvp5B7lkrV2lv2JeBX2aQC3xzBS074TS/gj6kw2gbBuogg9ZRyLIHuj5h69P3W0yGNaiQdRS0bc7DGNFdgNF2+yjwk/1YR69h/IstsP/fTmbNwEByYe63EG0z8DPhQN2cFt/+I4y20FlqPqh8J2Z9Ywrw9QxyH7NyZ2FussuA6zLIAcywshcCjwATyfxdUZmVew/G2vlxwDsyyH1HVWtF5GR7/CbMG3smgpY9jOZX0PTDaPv9EWgQkcOBr2LWl+7IEGfQOoLgZQ96fcLE2Wh/G0RkFMa69sgMcmHqKGjbRFVXYpwqJtW4oDgnk1yI8oSpo1ZV3QlERCSiqs8AR++DHAS/34K2zTDPhAMS10HtPzaKyJ+ADwAPWzXVbPWftvBxPvBPVd2dRS49x30e5kG5lI7z3l6CqhzH7ELx+zEaTtkIc3MFLXutVeP9MPAfMdYP4vuYfhhV3qAdZNA6guBlD6MSHjTOh8S4bv8/zNv+WuDODHJh6iho22wQkTxgoYj8TES+nCWPYcoTpo5qRKQY4wX5byLya8w0Xk/lIPj9FrRthnkmHJj09xDuQNkwbr/fA0y1/0eSfTruOoyPngWYB3QVmac8bsGou75p4y8h+4eLgVSOMdMTi4A/2P+TgHszyIVRzw1Udow68leAU+z/ccBHssTZZfr0TIW5W9XoMHUUsuyBVcJDxJnv3ce4ivCG9aSOgrbN8Rilg1LM+tcvgcn7sY6K7PWLYfxJfSFTmYLKhbnfumubPXkmHKib0+Lbz4TQKqrELConrSpsqapu8clEgFkYd9E1IjIEGK2qiwLmJbTKsefcQGq8vnMClb030u+JRlUQ1eh9yG/osnd3fbqL069C7w/rqdZZwLb5RVX9dXdhYcqT5ZyMdSQiP1XVb/RWmA0PdL+FvTd6874YbLgOaj8hIu/GmJsZBWzDjA6Wq+ohWeRnYkzoeBtupwelmK/5p/rkns8SZ7cqx2LcrF+ZQS6jGnGQmyto2UXkeOC3wHTMlEgUqFPVskxpB02/twlTR2Gue1CV8O7itB3taIyFhw+yt+MpBW5Q1WmhC90x/W7bZpbOcYGqZrKH1xd1lCn9Rap6WE/kPMfC3G/dvUCEeiYckPT3EO5A2QinLfQ94BlgK2ZaYQtwTwa5j2NUh3dZ+Ubg6SxxBlI5xpjt+QFGQeByzJRGJisRgdVzg5adcJpfQdWIw2gbBlKNDlpHIcseWCW8uzhtnp7B+Dd62u4/A/wbuGgf66jLtomxnvCgbZMPeLZnyGCzr7frCPi0Da/HTMOmtzV47OYFlevJ/RaibQZ+JhyoW79n4EDZgHn29zUgkt7PIrsYMy/+mv0/HHgii1yCvUZBpwH3ZYkzqMrxAp9cHHgpg1yYDjdQ2T1yi/z56Wn6hFPvD9RBBq2jkGUPdH1CxtnJDFGWsDB11GXbxKwLnQbMAU71bEdiNPr6tI4w62wTMMog4z1bZU/kenK/hWibgZ8JB+rm/EHtP/zaQtvIri3UqKopEWkTkVLM8H9sBrkmVW0SEUQkX1WXi8jB2eK0v2mV451kVjlu9eR3JuYNeVgmOVXdKSLt6rkicn2WtIOWvYPmF7CZ7FpNQdPvpFElIj/MIAcY1WgRiapqErhFRBbQ2SBp0DpKywQpe9DrEzhOVb03w7m/wtgY9BKmjrpsm6r6FvAWcIL/RBF5EfOtWY/KQ4A6UqNVuBszkvOnv05Vx4WR8xH0fgvaNsM8Ew5IXAe1/7gAc4N9GeP+oIzsbrXnWfXgP2NswtVh3kj9bLBy9wNPiMguzMMhE36VY8V8bOjnRjvP/m3M1Ewxxu6anzA3V9CyX4bpkD5nZcditJwyETT9tCrvmcBPu1HlDdpBBq0jCF72oNcnTJyZyKQWHaaOgrbNTGT0B0Xf1FEmsn2CEVQu6P0WtG3uy3U8MOjvIdyBsgE/DRKWQWYCAcwNYaZR3o3HX47veJcqx55jEwOGhVHPDVR24ItBwsKkTzj1/vEEUI0OWkchyx7o+uxLW7Jy6/aljnrSNrtKu6/qKEz6PZHr6n4L0TZ7fB0PlK3fM3CgbMD8DGEZnceR2QFcprA7goR1kX7QsEzfegS+uYKWPYvcgixxhrq5MVNw49JbFpkvBgwLVEe9UPZOYUHixKyVLMqwLQaa97GOumybtqPLtL0X2N7XdYT5ji7T9lWgOqycL+5A91vQthnmmXCgbm6Kr48RkU8DnwEmiYj3e4kSjD8hr2wC8zY71E4hedWDR2eI3q+mHQWO8oWlVY4LxLiy9sZZ6JGbZuMrk45uP0rxqMp6OBPwfytyrjcsaNlF5FKMOvREEXnAJ5fNfUa36du4M6ry4qs7y+WA/zudK9JhYeooRNkDXZ8wcWLMEAUmSB2FaJvv6iKpDlY3+qKOyG4aCzpe26ByXrq93yxdts0wz4QDHddB9T1/x9gN+wlwtSe8Vjv7Lvok8CXMg+JV9t6IezDfBwEgxhzQ/2Ju2D3pYIxq9I2+OM/GPGTHYB5C3ji9i/8HYx5s5XR8yNRi1GvTaYe5uYKWfTZmvWeozaM37Q5uHnpwc/8Aoz7+pKoeISJvx+f9NkQHGaiOLEHLHvT6hImzQFWX27Llq2qzp6zH03ndpNs6ImDbVNWPEpxeryMN6J4kqBwEv99CtM0wz4QDm/4ewh3IG9nn5D+fIey4DGGZVKBHZYkzqMrxCRnCvuTZLyOkem6YsmeQe9H3P1T6BFDlJaRqdHd11JOyB70+QeLEM3VE5ymwTNNKYT6B6LJtAtd79r/ok7u1r+sIuNuz/1PfscfDyvnCu7zfeuPeCHpfHChbv2fgQN6A9SFke22Bt6/iDJl2oLLvax1hvOMWY97y78RM38wOEeeLPU27F8reozjp6MZ+gU9uQYZz97WOetw59nYd+cruTz9jvXQl11vXKIRc4PZ+IGzZVEkd+wcNIbuvKrL7I84waQct+77W0QVAA0aV91GM9YcwazTZVKODpJ2NoGXqaZzZ9rOlva91JAH2w9LTOurqvK7qpSdpZ0p/X+XCpD3ocWtQfYyIfCXbIcxba1D64oHe23F2kAtadp/CgV+uIGDandK3fFeN4c8UcJtN76d0XsQOE2e3cr103Xsa5xgR+Y0NT++n5TIp2/RmHUWsEkXEs59+OEd7WJ6gaQMUWkWKCB2VKvxtKahc2PS7levFZ8Kgx3VQfU9gbSEReZDMDV4wplPScr/tQq7cF+fiLmSHe+Rqu5Ar8MiFubmClj2M5lfYmzuItmGgDjJoHVkClT3o9QkTJx0dCM7zyfn/Q7A6CtQ2MeswXiWK+Z5j/vP7oo42Y75fA2Ph45eeY1t6IBf4fgvRNnuiQXhA4qyZ5xAicmpXx1X1OSt3eTdyt3niHN+NbDbLE9ny+L1u4uvTL+GDpu/VqMJMWaUpwayveD3I3tJNnGE000LR29cnZNph6ihQ2+wL+rOObPqB7rf+vjcGJf29CDbYN0JoC2H86mSLJ+OHkxnkYr7/0zz7+b5jx3v2T/fsT/TJvacvy04vaX75zttnjaoMcQauoxBlD3R9wrYlG3YQRg36cYxV86fxWN8OU0c9aZuY6cQTgbelt76uI9+xEzGfD3wkve2LXJZzY0Fle3odD+St3zMw2DdCaAvRUQPqqS6O/dezf0c2uQznBTrWjVyYDjdQ2YOmHTb9Lq6JX/Pres/+F33Hbu1hPvui7IHbkg17DeNW4ljMB6VHAUf1sI4CtU3vtcG4mH8Y437jQYyb9j6tI0/4HZhvj/6A0U78LfCbnsgFvd+Cts2w1/FA3twaVN+jIY55NX0quzhW5Nn3W0Twawt1pVUVVPvK+3+qZ9+/dlHlOy9o2cNofoVJPxv+NN7m2b+cjusAXsd1QesIeqfsPY0zTZuq/rGLc7qiq7x01TbTXAgcrJ6PhDPQF3WU5mhghtqnfhcEkQt6vwVtm2Gv4wGL66D6njDaQpplv7tj2eR6GmdvpR207IE1v0KmH1QuaAcZtI4geNn7Is40D4rIZ4B/Ae0dhQazVtDTdpRmNcZPVlcdVF/UUZolwAiMMkRXBJEL2uaCyvWWBuGgx3VQfU9gbSFgmNUEEs8+9r/3DaxcRC7CNPByjxaaYNYVvARVOZ5kzfyIZz8tN9EjF+bmClr2MoJrfgVKP6S2X9AOMmgdQfCyh1EJD9OWwIwGoaNWn2KUIsLWUdC2maYB47bkKTp2jl/oQXnCqs2DMZu1TERe8aX/7h7IBb3fgt4bYa/jAYvT4sshQmio3dKNXLvWWQgNpFO7kUtrED7Tjdzbuzq+rwRNP4xGlYisxXwDlGn0pKqafqAHqqMwhNHI7G1C1lFgWSufsVw9KU9P6ijbtfJfoyByQe+3/r43BiOug9qPiMiJGK2p9pGrqt7ebxnajwQtu4iMxmiSeeWe3w9Z7DP64roHiVNECjEuJMap6lUiMhWzLtTh27K+QkQKbNorAsj2RR2Nx/i4etLWRVRVa3sq1xccyM+EILgpvv2EiNwBTAYWstfFtgKZHtJVwCfo3HA/5pPLx/jZ8ctdmyHOg4CvZZA93Sd3EnANezsJwTOK8MkG7XQCld1aL/gAsMwnl7GD6ip9EblbVd+fjleNpYT0eY+r6llZ4uy2gwxZR0HLHuj6hIkTuAUzdXqi/b8R+Cf24+ee1FGItvku4OdAHsZK/Czg2gxTbH1VR58ArsIodEzGTAXeAJzREzkrG+Z+C/ICEfiZcKDiOqj9R1CtIoB/Ay9gjHgmu5HbjXkIdbUYDebBdAPGRXZXcd6Escn2aldyIW+uoGW/kO41v4KmH1rbL0QHGaiOLEHLHvT6hIlzsqp+QIw7EVS1QUR6qpGZJmjbvAaj3v6sTXuhiHTqwC19UUeftem/bNN/U0SG7YMcBLzfQtwbYZ4JBySug9p/BNUqAij0vs12wRhVPSdg+kFVjner6iMB5MLcXEHLHkTzK2j6PdH2u5BgHWTQOoLgZQ+jEh40zhY7zaYAIjKZjnXbkzoK2jZbVXV3x/6QVBbZvqijZlVtSacvIjEylymoHAS/34LeG2GeCQckroPafwTVKgJ4SETOU9WHu4lztogcqqqLA6QfVOX4GRH5P+A+n9x8n1yYmyto2YNofgVNvyeqvEE7yKB1BMHLHkYlPGic38NYJx8rIn8DTsI4/kvTkzoK2jaXisgHgahd+/oC2b3F9kUdPSciaSeDZ2JMOj24D3IQ/H4Lem+EeSYckDglif1EUK0iK1uL+TiwxW7pNY5Sn9wyYAqwBtPA03KH4UNE1mROvuO6SRZNJM2wVvUMMAvo9ub6//bOPNyyojr7v0U3Ag22IiIYgWYwCojMoAgGIjYRo9EA0hgNxCBxFodPUSIxHygGksCHOBtAUcOMEtHGEVpoZrqbpgEBhRYhgjM0ODC4vj9W7b777rv32Wudu889l3vqfZ56ztn7rLNq2KuqdlW9tSrAqHIzv9ri74dRJSIXADsAPTtIbxklWW/eXc8nojPJboCdlivA1ar6y9Jv/ZSR1zbnAP8M7JdkvgUcp6p/6Dc/wTJaAzi8Ev9/VUc1Xrkk66pv3roReY6jitxBTSG6ZgtJgxNNHbDzzBR3qHIFGFUu5tcgKnekgwzq7Zwl5tEpIjvX/PUB4Ceq+thk4u8aw2TSeeGtb8EXiGmf76FCp4G/pVEIGPPpOuDH6frPqfg0K8kK8HrgmHS9KbB7g+xewBvS9w2pODEtyc0BPgR8rhT/K2rkNsJIAAvT9bbA4Q065wEvLel/8mTyjh27cRtwV7rekYr/tj7jdzsDxaa2ntvyLCNl5M276/kEdV6NjXKuZ2xhfwnmuXy/fsrIa5sk33uV8CXgSGDtKSijm4DllXA5cDKwQVSuj/rWapvefI9yyCfqTh3ehq0BPAjGFgKa2EKfAvbAGgyAh4BPVoXENk8eBXww3VoT+HKDzjOwxqpMOf5IjdwXsGmOP0vXtwPvqon7COB84LPp1rOArzXE7c37v2KMqt8muWUkrwf9xp8YVf+BNSy7pbBrg85XYsyrS9L1jjLmLaKML+AoowRv3r3PJ6Lzf4GdVHVXVd0F2AlbZ5sPnFgIRcoIp22meB4CPp/Cg8AqzMP65/vMT6SMFgLfAF6Xwtexjvo+7PlF5dz1LVA3Im3CaGLYPeSoBOCa9Lk0fc4GljfILinLpu831sgtw95oy3JNOq936ryuRm5ZQ9xPqsjdNJm8Y2sk1bib8uOKH7iVNJXteEY3YK5ryjpX9FtGwby7nk9QZ13aV1TTGywjr21e16Pcbp6CMqrzsF6k/aaoXMnmWutbwDbdbcKohjyCmjpU2ULn0cwWelREZjFGD96QeoruI2qWXcitWyOzWraFclzg4bSwXsi9EFu3qOKPqvpIcdFCz/XmfRzzS+wk0ybmlzf+glHlwaOqWs1rXbl7ywj8efc+n4jOm0Xk0yKydwqfwlhjawGPluRCZeS0zfVEZLPiIn0v/Ps9UpEdRBnNEpHdS/Hvxphfxcf6kAN/ffPaZqRNGE0Mu4cclYBReY/AjPD89L32rRWbavgf4B7go9i6zGtq5P4PNo1wZ9J3FfCOBp3zgUXAL4CvYGf17FMjtzOwGGtwF2PTV9vXyJ0IHA38MOn+KvDRyeQdm6v/KDYvf336vnaDTlf8wKXAb7ApudXrIQ06T8OmrpZj6wGnAp/pt4yCeXc9n6DOdYD3prL5arKXOen/6/VZRl7bfDlwd9J9GfAT4K8xBuC7pqCMdsPWl+5KYXm6ty5wcFQuUt8CtuluE0Y1ZBbfNIWIbI25WxFs4fTWBrn5lCiyqvqdHjobKccVudnAc5Pcbar6aI2Mm547CARoxHvX/V/rGVURanRrGUXhfT5dQUQuUNUD+2Bkem1zLWDrdHlbuRxFZH4vW+2R5lAZichTUl4eqNw/TEvszIBca30bdt2YScgd1BRBRG5i4jD/AWyk8BFV/VVJtnogHMCqyTSCXsqxjB0lUJW7SVV/3mfcrryLyNd7yH22rqNwxj+Pbun97jIK5N1NCY/YUks+lqrqTum7q4y6sk0RWaKqO6fvnZdRJP4u5PpBV89xJiN7kpg6LMT8cv13uj4Em24p2EKvLMkuwei7v8HewJ4K3Cci9wNHqOoNsHrTZJOBv1dV7yzd/xQ2NbU86dwOuBl4ioi8RVW/neQOx1hal6brfTDywBYicqyqfinFHalc3rzfiVF3z0rXCxjP/Pr7QmGgUYs4A/V2kK4yCubd+3wiOttQrKW4ywinbTpQ9oE0iDKKxO+S89a3QN3o6jnOXAx7jnFUAjG20OeBvypd74fNfb+QxPxJ948D3gQ8GZiLNTKFw9PLKjovBJ5Xut4Wm/fekvGMrm8BG5WuN0r3nkaJFYbNs38MeH4KH8X2jhwFfL2fvBNjfrniJ8Y2PAVrLF6ZwpexRvGTwJeiZRTMu+v5RG3JY5PBMnLZZqQ+DKKM+qmPjnS66lvANjt5jjM5DD0BoxKAGyltaMQWYm9M35dWZOsoqcvT57Kyzhq5ZXW/VRvO8r2KzlsqMlLcqzRgkQ7XlXeM7rxZ6Xoz4NaGMvI2ahF6v6uD9JZRMO+u5xO1pRabLMokUkYu23TEXW74Oy8jb94jct76FrDNTp7jTA55im/q8EbgdBEpqLargMMTVfVjFdmfichRwNnpegFwf6L3lim9vxORg7G3SICDgGIaqjrFcLOIfLqis45yfJmIXIwxi8DOv7kspfO3JblZIrK7ql4LrfRcb97fC1whIj+G1ceovzXJVd0NeeOvUnl7OQNdT0Q2U9W7k84marS3jCJ59z6fiM4211GFV/JIGXltsw0r+8hPaxmJyJGqeoqI7Kmqi3vEvzjJb6Gqd5V/qNwr6/DWN69tRtqE0cSwe8hRC9hG0KfU3D+s9P3pGMV5KTbnfyq2NvMk4NkluS2xhuSXGPX265gzy3WAvSr6vZRjwRrck1M4iHrKr5ueG8z7WpjD1h2Y6BJnfjR+YvR+FzXaW0aRvHufT1Cny3VUsIy8tjkHOAb4fLpudEvUZRkxNqIJT+GV7t3QIOuqb17bjNSLUQ1DT0AO6UE4K1SSPdUp98GAzguccldVridduSbZmHRauXF2kJEy6ijvrudT1km9Z4yBrm0UtgmcA7yfsSm4OQSn4fopI4xgcwfwMOP9691EadoSo78fiPklPKAU/oHKemcgnR+sXE/KNiNtwkwNeYpv+sDLKgLz3+XBa/BPFTSddlrF2uULneh5ocCRTJyWa0KYUeWNP0rlVTus8MYGnScAnr07a7eLrIY3797nU9ZZd2hgtSy6pjsXttl2mm8E7jJS1Z1EZGOMtNLrXKXnAq/AWIhlttwqbATZD8bVtw7qRr/lNWOQO6jpgwkNRweIGLg3fq/cMOMux98lldebp0g6B5H3QtZ7aOAg6M4Rt0RtCJWRqt6HjYCbBVUvAi4SkT1U9ao+01VF3y9aDRhEm/CEQu6gpg8G8bY0TAPvpzMZRPwv1fEbLW8qNl+KyOv71NklBpH3Quc7MM8Yf8Q6n29R7/27yzIq8K/0Ps03AncZNYwGCx2qEw/zvD/tf3th+t9VwLt1/B5CL4b5kjcjkTuoASPKKvKq7VgOcDsO7meD4yxVfbyHrDfvK51y5fgjbMOuUM57hCXWtc6tVfWfsU6qF7osIwFQ1W+LyA2MuSU6Uptda3VlH4JN20Xw39g+t79N14dg61gvCOop4nfLdZjvmYthL4LN9ECAVUTaDIpV5l5y/5A+96z5bc/S96NL3w8A1uqh845yGnrIbZc+Z7XIfaL0/W7gcyT/bT3+42Z+eeOnD7ZhD50Xps/3AM9qK6Om504zS6zxsERKBwx6dWJsxFuxDabb9Uhvaxn1YZtfB14LrOsoV699TIi7fI+JhzDOY+zQwHWoPzSw7riM2iM8HPk4On1OOMSwfK9km658j3IYegJmesDJKkqyt2CH4N0IrI95JlgdanQ3bgisuX8GRpv+EvaWObvy+wrMk3eV1XQAcECNPnflwjqegzFPACuBT1ChwSc5N/MrWrnxUdyXY16ot2rR9WHMxc7lwNspeZUoyYRYYjgo4VGd6T8bY2tPi5PNfaifMurDNvfGvHD8BKOuH0SzZ3qvfdTZ+9IGna7TajHiyweAzbEO7f0Y0WFCvjCXW98r2ef2deXZkM66FwhXvkc5ZGexU4BerCJV/UlJ7p3AWzDG1r2MnzJQVd0yye2BnSr6LmwfToG5wN+qau0CsYisCeyPbXDcC/iOqr4x/bYXdpTCwdhxCpVk6j9WdM3BOrpDMP9oFwNnq+oVTeWQ/rc+5lLodao6q/Lb9aq6a8WJ6Y11+ek3/ho9Zael87CyWYBtOj0HOFfTxt2a/26fZA8E7lHVl5Z+exXwauyZl8tzVUrnOLJCmg57CeYyp8j7Tar6/H51VvQ/H2t8F6jqk5rkGv67BCNLtNpmzX9npXwdAbxMVee2xDXBPhIT8O8wm728JP5k4E+qWudXcRl2OvM1TeWZ7t1V/W9TvkRkEfA+zC9joXOFqm6Xvm8NPA9zdfS+kp65wPtU9XmRfGfkNagpgTpYRUnu48DHReTTqvqWHqJPwjwczMYqaYEHsTfVJv2PishCbJF2Hayxe2P67QrMi8P1qnqaI62/A84Fzi1VrkWMrV2Mg9iRDguAl2H05YNrxNzMr2j8PbC6oU0vCycCJybW2zHYG3aTzp9jTLdfUTmqW+MssVZKeFSniGzDWAf6K6zDfa8jLRNUBWyzHP862MhwAfYS0UitbrGPK4GfYZuE/7N0fxU26q3DH1X1kaI8pfnQwG204iVfRNau3kuYo6rXVp5ReY0uTF131ovRxbCHcDM9kKbyakLdFN/TeoUa3fPS51xq5tcrsvtjb8Er0+fLqUzzJbl1gQ8Bn0vXvdaBimmcO7HO4sAGuZXYzv+eaxKY49FFOA6ki8TfUi5LKtfFNM8NwLWYl+rqf96KeZq4GWOrbdtDf+F94BdYh3YRtl+nKuc6LDGo8ypsz82fTdKGl/Rhm+em5/cZ4C+BNXrod9lHkt0YG0G+Eti4h5z30MDINPlCzNt7sRH6IGBhjdweznJ153tUQ57iGzDStFEjdPwU312MveVVGUGqlWkUEdkVW1sqRlEPAP+oNUceiMhZmA+zS9Q2ozal9xyscT5UVbdLU2lXquqOFbmVmLubc7G1kod76Jyrqg82/V6R9R6q6I6/Jb6lOjZdcw2wZtJ5rjZQjUXkY8A5qrrMof9qjCVWHCFyCHYK6wsqcuXDEiFRwrX+sESXzq4gIkuxUUHENv8K+K72ZqkVsi77EJHDsfW/76c07A0cq6qn18j2PDQwTbs/C/NY/3elPM3FXgy2rtG5Jbbu+SLsuJG7sCm5n9TInUILdT1SL0YWw+4hRyngYBUF9S0HXly63otmL9QbYdMsO1OzqF+Suz59Li3dq/PiPNeRvtnY8QQLGRs5LgTeDKxZIx9hfrXGn+RcjKr0vZZBV/mvYA1PQVB4Ab2ZZy6WGLBz5Lk7de6Jeb64HRtl3gXcWSPnZmQG7fNFWON/aBEmaR+3ARuUrjfATuptS8fTgO0r9w7DWI6r0mcR/ocaUlC5nLBZhsa6C1yNnV02O4XXM/6YnFC+RznkEdQUQUqHwqnqVmmN4zNav8ArGGFhC1U9Tsyr9saa9qmU5JZqevsv3Rt3AqiI7IhNszwFW9wG2ATzuv1WVV1S+f+VGDNusdpGza2As1R19/T7bOzN9NXYGyhJ70XAaVo6WTWN2n6LrT3cU4r7sFQOCypxF/Pxf40xsM4GLtbxR4W7468rj3TvBlXdhQpE5HjgRFX9bbpeH5vi+1C63g+bUryjUpbPTmU54cA8ETkBe9s+G3ubXoCx4P4dQFV/neQuxaavzsdGZyuquvrQ+UPg3diIePVIRiuui0TkbmxT7TnA97VHoxCwzS9h02HLSnGrqr6zJBO1jyuxKd9H0vWTMFLJi2rSeRk2FTg75f/n2EzAuytyB6rqBU35rci6yklElmtlQ3CZ7BPN9ygjd1BTBC+rKN3/NMYie4mqbpMaym+r6m4Vuf+HjcTOYqyh+gM2bYGqLknxvklVr6n894UYG2mHyv352BrUtsC3SR4AVPWy9Lu7conI7ar6nIby6PVbI/PLG38/jKq2Dl9EbgX2V9WVFZktgG+q6jY1OiMssY2xRfIFKZ3nqOoEzw9enSJyjTqm/SKMyIBt3oqtzfXq7EL2ISJnYgcAXoTZ+6sYG4GgqieVZJeq+eV7I7Cpqn64oeP4MDXkCVU9tiZNrnJqe4HApq7D9WIUkVl8UwcvqwjgBWn0shRAVX+T3harKDqXD1fu75R0vwSbLrum8juqerXYuTPV+98RoxU3eQDYpaYC3QNcLSK3V+7/WkReg3ni/hOsXht4DVaBJ8DB/PLG348z0FkispamNbqUlrVKv89mrFMs415s7aoObpaYGtvz42k09X7gX6h3TeTVeamI/Du2z2b1umN11KwxRqTXNldgI8Kf1fxWIGofP06hwEXp88k1srNF5JlYh9/Lk8ZDpe9rYzZza51goJwKJt6bKvcPwerlz6P1YlSRO6ipwyLxHwr3aBpFFAu6G1J/GNzhOnHhdcvKvYUi8g3gTOCn6d6m2JrAJVWFaQpnf4wVdqyIbCYlNzjEGpVDMJr2p0Sk+O2p2Fz/ITVxn4uNMi/BNi0uKuIowRW/9ucM9CvA90TkjHT9BsZ3kKcD14nI2Ywvy0MwFl4drsQ62p73JEYJd+lkzF3PrqV7xYvLOIif7uy1zadjhwley/jOsbwXMGQf2KnF55VviMhrqvcSjsWIEVeo6nVixIU7qkKqWqatIyL/kf5XC2c59XyBEJHNieV7ZJGn+KYI0sIqqsi+jvEjiIOwHevVyulaXxGR/bHpkPKazf+o6jdr4u45hVOqXC9hrEN4Kla5PqAVH3ElvRvAxPWPikwr8ysavzgZVSX5/bE1OLCNzN+q/L4N9WV5S0UuxBITkauwKaHzVPV/G9IWZp55IDFGptc29677v6ouatDrsY86e59wbzJI9n6dqj675reVOMopkk5PvkcZuYMaAkTkacAmqtq0ybBYQ9kXa4S+p6q3Vn7ra8e6I22FF+vV6zHS7M2h78olIvNVdcLZSiLyIsztzOrRvaqe2aDD06iFKdkiMrcS/6975aVBx2GYC6JdsTftAquAL6jqhYPWKSIbAcdj+6D2F5FtsT06p1XkQnTnXrZZkZsH/Lmqfjet38xS1VXOOFbbR3ppeDk2WjmnJDYXW+faveb/G2JTuZsz/llWPaKUvZ/Pwk4HPlZVP1Gjs2c5dfEC0VQvRhW5g5oiiJNVlGS3wlzn/FFE9sF8fp2pY+yyV9Gny5tKPJ9T1X+q3LsGowdflzqqDbER1E61Ssb/1125RORuVd2scq+V+RWNX1oYVZX7bwL+L0Y0+ROsPqKh1o1P5b8LVXX/mvsulpiI7Ilt+p2H2Uhj3AGdC7F9cv+sqjuIrXsu1UTMkSAjMv2np22W5Nys1Ya0r7YPEdkB8014LLYuV2AVcKmqTli3EWP8Xc5EBuMFFbl5pcvHgPtVtdaDe1un18VLSV29GGXkDmqKIE5WUZJdhhn55sA3sE7oear68opc6/pKGq3V/oTtndmkIu+awmmIa1zlEpGqT79y3C9R1XEkDXEwvyLxp3suSnaSvQMbYTRtDm6aShKMDv/Mmv+4WGLipIQHdV6nqrtVRsPLNG26lj7ozgHbXEYLa7UP+5jd1HnUpVMrm8trZGZhTnZdU6OBTq/nC0Q036OMTJKYOnhZRWAOMB8TkQOwTZKnSmJNVfBP6U11HCrTGL/APEqPc+6Zrsf5j0v//YqY49JiCufVlenFXpVrg8q9F2ObFB+qkZ0wLYOD+RWMH9oZVeURyo+B3zXFje3NWgQTPCmArYPVwcsSe0BVF/aIux+dD6dp0ILQ8ELM20iBCCOzgNc2PazVqH3cISJ1HXPdCPdiEXm51qyzlv73uIjcJiKbaYND4ArmqOpRDrntRGTCNHvpBSKa75FF7qCmDi5WUcKjYh6cD2WMIl1HY7649H1t7NC16gL7ncC+dRVQRH5ac28r7MiHT6YpnPki8rPSFE6kcl0N/E5rFsZF5Laa/HiYX9HKHXEG+kHgyjTNWY6/mGK8FdtTNuG51ZVl+q+XJeaihAd1vgcb4WwlIoux9ZWyM+HwNgD8trlI2lmrUfsosxHXTulsmiE4EjhaRB4BHmFsyrTqTX194OZkc6tJDxWbK9Da6SW0vUBE8z2yyFN80xBpMfvNwFWqepbYRtCDVfWElv+tgXWALyrde1u6d2ON/DtU9dTKvWX0mMJJ6xonquqlNfp+oKp/Ecrs+P+3Mr+i8UuMUXUtcAXmyHc1dVpVv5h+Pwi4SVUnNCIi8mpV/VrvHNLIEhPb+1SFquoESrhXZ/ptNrYnTDC3QGVPH6/HOhk3I9NrmxJgrU4G0uAVJPB/N9tQRFZhbo7aOr3q/9YCvqWq+/SbzpGFTgN/S6MQsLfXozFnk6cXoeM4ngv8qOG3CafpNtwrPDW/H2O7QcOhcIF0neC5l+7PY8xf4Rz69FeITRXugr257sSYH8J9gB82/MeVT1r8+1Xul73Z34yRY94+yfLsRCclr93Y9OgGk0lXMO4LovZReoY7Yy9Rb6bh9Fus83g9cEy63hTYvY90XtVBXtevq5eRejGqYegJGJWAbaQ8AVsTObAIDbJeJ5+rsDOginB7D52uYwWAazCHrSuKRpd0gmhFLtLp1MVT5/DUdQqqJ376cwZ6PMY8eybxk4ybjnGfVwrPouaIkyS3EbbZd2G63hbbiN23TodNLu3x2/zJ2GYk7oB9lJ/jd7CXvVoHv8Cnse0Ft6brYpQ5mXS6Oj2cLxDefI9yGHoCRiXQcHR5g+wPMW8OzyC92VJ5u02VZTOHrtBIIjWMHwdem663AI6qkWutXNgJrDdhxIPlpXAX8OW6MsIOY1xaundTQ768jZr7jKiUrmq4s/R79Bj3WXVl3BD3Quzl5cZ0Pbsu7xGdjjhrzz1Kv93dr216447YB7AGdhpwKG+0eOWPlBHOTo+WF4hovRjlkEkSUwfvAis4GF2qqmIujCY4m63gr7AGdBPsNNKCgfYgNuVY1XsL8M7S9V3YyA8AEXkLtuC9lYiUNxo/GVhcUfffWMP7MeADpfurtH7zayvzKxg/tDOqCr1rYOsu51RlSwj599MYS+zpqnquiHww/fcxEZngUSOosw1bNrAimxiREGMbtsFtH6r6JxF5H+M36vaC1yVTBK1+CFOc39Le1PVovRhZ5A5q6nAkPlYR+BldS0RkN1W9rilSVf2i2AbY16rqV9oSKe0bRiONygMi8hCwk1YOdWuAh/kVrdwuSranAVTVi0TkYmxEebwjP+BnibVRwvvR2YY5wGeJ0Z3dbMMWSB/28V0R+T/YMyrnu+65fxw7rfYZIvJR0n6+YBph/JaC1k7P8wLRR75HFpnFNw3hZXSJbe58NrbP6WHGOpO6zb/Xq+qu1fs1cq0bRiW+wfEijHDR843fy/yKxl/5byOjSkT+DfglLQ2giFyrNe51GuLbu+6+VlhiYpuATwW2w9b/NgQO0hp3WAGdczCHs5up6hFi3hyeq6oXp9/DjMw22xSR76nqviJygvbYMyQi+2k6PytgH3c1xF3r6UN6uwtbP42A3oMda3Jvg47tNJ3NJX4/hD/AptN7vkB48z3KyB3UFEFkwkFvmwLP1MpBb0Gd8+ruF29lRSVM372Nr/cMIXfl8lZYh54LVPXAaPwVHb0o2a4GUEROxvb+VMsyOopARK5S1T3S916U8IgbqatUdQ8ROQd70ThUVbdLHdaV2uJhYTIQkVuAN2KEj7I/OqC+jDq0j0gZFT4nP4yt/f0ae57nqer9Pf7n6fS8LxCd5HsmI3dQUwRxHvSWZF1OPh1xlg/b8za+/4YtxPecwolUrshek16Q8S57vG+pbmegjvjnq52X5RrhOnWuzlOLnNtrt4y51bpeVXeVFse/daOdphFQm22K7RU7HNiL8f7ooKGMOrSPcBmVrrdn7LiTe1T1pZG4I/GXXiA6yfdMRl6Dmjp4D3oD+ALJyWe6vh17uwt1UJTeXlV1i56CY2+f3jOEjvEmoq3ClUcRbar6iP8Vpe89nYE6cAJ2BMdf9hISkcM0be51wPuGWOdeqU3nI2KHLhZrJltReukoYT5Q7Yz2r7kHLbapqucD54vIMap6nCux3dlHP2VU4OfAfdhZXBNcgDnhjX9t6DTfMxa5g5o6RFhFLkaXA5HhsavxXa2428q1tlMuFD/2Ft/GqIrA2wAdycSTgCeLfqY6Powd/ripiHwF28P0D8WPEmdEQottyphD3W9IjXPdfqZB8dtHuIxE5K3YFN+GwHnAEVo52ysAb/xeuXC9mGnIHdTUIcIqijC6uoKkuDqZXiRWuQYxilhbu6Vkw2DSGZEN6UzTkUuwwxoFOFLHe2rvh+7cZpv/WfsvQ91I3AN3xyMiW2jDoZlV0fS5KfAuVV3WR7oGjZFff8kd1BRB272EryY00OLks49K6Epi+vwC3UwvRirXs6F53aMEjyfpavxdUbIjqLIO5zF2cN862MbN4uC+v3fqXBnVKbZlYJmqfkPM797RInJKQaLR/ujOPW3TOwIfEFYC5wO7FGzCHrL7JuLSRdh+sC2xs7CuVZ3AGu26vg3ipWRmQqfBbuEcJu7qx14enofRjtes/HZ7+qx1A1SSm+Cmpy1+0s54xu/AXzbZ/LTI/h47JLHq7WJnYOfJlCewd13oU+eFTrly2bncN2F7ko4BPl+Se0WDfq/O5VhjuAPmueFtwKIauYtweCVx2ub8Un4+BHyuLT/e8vSUEXYk+9HAT7HOdFwoye0H/AgbQf5XCpeke/tVdN6QPt31jfE+Jdeh5FMS2C5qR6Ma8ghq+qBKx30M8+NVh03ENrQ+J+3jGAdVPSl9Rnalr0yfXU0vjstPyxv/0VjDswlwUkVPv9NCxTSXe61MWvYNqeoBSW6WqvZaEyyv37yNdHBf0nGHiNQtwp+BUcKLdbt7sTWRi2tkvTofU1UVO4H5k6p6mogcXiMXGmW22OYJmJ+8Ij+FZ/1e+fGOMj1ldAh2QvBsbC2tCadgHcjKSjq2AL4JbFO6vUakvknpNGHshOhNgM9gsydo2lcVyPfIIndQ0weRKbGV2Cbatkq4Gt7Gl/YzhMo6XZXLUWFPBk6OML8i8begvFbm7STuEpFLsKnP72t63S2gqm8vXXoO7gPYSlUXiJ21hKr+Too/TYRX56pEZng98BdiG6Hrzm5yMzIdKNLszk+gQW/VqXYUyglip1X3csk0m7FThMu4l4ll5O30CrheICId2agid1BPTPxBVT2VsAxX46uqS9L+jJ4bRoOVq2eF7Yf51WHlLjfs3kZ1a4y+/jbgNDH3R2er6hU1souk3X0T+CnhEZ0LsM2yh6vqfSKyGemo+zIio0wHohR38I8IIzqXiMhpNJN9TgeuE5GzselAMMLEIVTWWwOdXgHvC4Q336OLYc8xzvRAwzlBNXJLAzqL9ZXIEQ3XV+NhEt6diXkev6YcN/ZitLz0+6U9wvcbdLrj9+Qnfb8SWy8o8rgVtmje6//rA2cCjzf8vga2ZnQetoB/BGmDfEVuPnac/C+Ar2Cj5H0mo7NDG+7HNiP56WkffZZRq3d4bBrvA5iLqVPT92175M1V34ATsWnrH6Y0fxX4aL/5HuUw9ATM9EAfC6wOnRemT9cRDem3cOPboGdp+nRXLm+FDaajk8rN+A4u0gDuDXwKOxPpXJrP4TqAmoMhG2Q3AP4aG509vYecS2eSuwNbQ3yQdH5YH2UUIbxcWPruzY/bPgI6OyH7VHR6j0TxvpR0Xi9mWhh6AmZ6wMkqqvzHxeiKVMJI49uSn6KDizQq3grrZn4F45+Hk1HlaQBT2X0VO9hx3ZbyOgNz5vulpLPpwMI9C13YmtFJwLxJ6vwRsE0HNlweZXptM5Ifr31EdF6WnmVhry+khsHY8N+FDfdd9Q3/C8SUjoSfiGHoCZjpAVvLOQr4Gbazf1xo+M852JHrK9L1nIaKEKqEnsbXkZ8iLnflClRYV74j8RM7pdfVAAJzg2W2JvA32IvBTzAP7VUZFyU8qHNxRza8tA/bdOcnYB8RnTtjbMoH0uftwPaV3+vCLsDPGnS66hv+Fwj36HpUw9ATMCoB2D8g61ovaquEFVn322dL2orpxcjUlbfCutfJAo3aMvxrZd59Q18Enlq6Xh84vSUda2KHHF4I/LLm96LR+xfSugYtU2sOnadgHcprKZ0A3KDLNcoM2KY7PwH7CJURvfdrPQ58n/p1z9836IvUN88LhCvfoxyGnoBRCcQIDe71ol6VsCLnbXy9UzihyuWssJF8exu1yFqZqwGkhjRQdy/d3x/zzrEyfb68Lq3Y9OsHU6O3MTZCbOpIvTrPqAkTOlJio0zXM4rkJ2AfkTIqpotr7Rg7c+vPG/770x7pdNW3Up4aXyC8+R7lMPQEjEogRmhwrRe1VcKKrLfxjUyzhSpXW4X15jsSP7G1KlcDCNwIrF+6flqPZ3kWtoem52gvxfce4MXpejPsHKe+dQZscxn+UabXNt35CdhHpIx62jG2t++5Df99dcN9V33D+QLhzfcoh6EnYFQCQVYRvsX6SGfibXxDdHRP5YpUWE++I/ETWytzNYDAoViHdxzwkfT974dtYzXpfA7wvZJ9bI+dAFuVCzEio8/Ikc5Qg+7U6Z2KnLANpO5euu9df/O+lHSe75kWhp6AUQkECA34F+sjazbextc7hRPpdLwVNsLS8k5zDWQhGpuifXsKvfbOuKjeXrmgzkXYRtCyfayokYuMMr22GcmP1z4iOr12XDeLcEODzk72EkbzPcph6AkYlUBsgdW7XtTJ3qaKTu8UTueVy5vvSPwE1sqCDeD62Iikp1NbnFRvr1xQp5cWHRllem2zE4r7JMqopx1j3kAOBH5MiUCCnZd1c4NOb6fXyf6zHHIHNbWF7Sc0eNeLIhtLI41v11M43jf+MJPNGb9rrSzQ8B+H7Wu7jHaPFy6qt1cuqHNhakSLcj2Imj0+xBiZXtuM5MdrHyHafC87Bl6Fvbz8ivEkko8DL2rQ531589pR7shagqSCyhgwkrPW92DTIROctVZkF2Gu/98A/AV2HPWNqvr8GtkNGDuQ7modfyBdWe5HwCu1dAZVg1xxhtDD6QyhnYHVZwiV5A7APFc/I8UtgKrq3EnEHcm3O/4kvybwskK3qj69Rmaxqu7ZK41J7jbg+ar6iEP2FGx69WuU/Map6oX9yAV1bgl8DvMo/hvgLuB1Nc/yDMxj/A+wdZZL1DyW1+XH9YyC+fHaR0Rnqx2LnXB9lKoe3yveit7W+hawI1e+Rxm5g5oiiMg5mLPWQ1V1u9RhXamqO9bIbow5+bxOVS9PTj73UdUzK3KuziTJeivNcmz6ZnvsjfI04GBV3bsi565cgbhd+Y7ELyL7Y05T98FGPOcC365rgAMN/wXAW1T15448nVFzW1X1H/uRi8om+XWBNXTM03tx/zBV/WL6via2rrcA2Av4jqq+sUaX1zYj+fHaR0Sn146vVdXd2+JOst6XN68dufI9ysgd1BRBRK5X1V1FZKmq7pTu3aiqO0xCp6sSJllvpVmiqjuLyL8A96qdIbREVXeuyLkrV+TN14tAo3YWNipYqKpNnq8LWW9nsit2yN8KxudnkKf0do7qc/WMMgeUjkHYh9eOT8amgM9h/FlYdR70vZ2e1446z/dMQz5uY+rgPiogMH3lPZAOYC7wO+wk0QKK0bPL8J4hdH0aFX6N9srlijs4beeKX1VfW/PfWqjqG5yiX0zpvAn4Uy9BEXkO8GlgozRy3h74G1X9SD9yUdkWSNJXHWX+F7Znry4/rmcUTKPXPiI6vXa8Y/o8thL3S2pkXfUtYEfeOjm60GmwEDYKgRihwbvIGtqt70ynl45+Rk3o6e7HEXeEpeWKnxg5xLtv6LpAnrxUb5dcVLYlbQXhwc3IDNrmpNM4iTIKbxRu0HNYJX7PXkKXHeXgKP9hJ2CUAv6jArwsrcjO+qFVmkDD34lz04rOSKfn7UxOAj6GHf7YRjP3Ur0jnuk7OUqCBvdMLf/x2mYkP6EXg8nmO5jfsid378ub145yR9YS1iBjSpAWWP+gqt8AngocLXZkeR2uF5FzROS1InJAEapCqnqfqp6kqpen67u1hlCQ8Hns7e/RJLscOz20ms4DROQOEXlARB4UkVUi8mCN3HNE5HsisiJdby8iH5pM3N58B+O/X/0sqTmqem3lXh2bbSeMyXU88J8p/EeDzl+m6dxiavcgzLN9v3IuWRHZWkT2FZH1KvdfVrpcnO65nnmC9xlF8uO1D7fOYJ56YfWJyoH65rUjb75HF8PuIUclENuEOojpK++bfOdTOIG43dOG3viJefRu3TcEzALeHXjuWwLfxdYa7gWuoN7zgkvOIwu8E7gNW59bCbyq9FvdnqVBTK1G8uO1j4jOQZyF5d2v5d1/NuUjwidaGHoCRiUwgE2owYbFW2kGMYXjijuY90F0et7OpJ+TiNeldIRF6f5h/ci1yP4UWC993xy4HjiyWl7RZ97nc2rNT9Q+nDoHcRaW9+XNa0ed14uZFoaegFEJxI4K6HzNJlBpXCOOSOUKxO2ekx9k5W5rAIGTgU8AL6ZlDcoRl+slxSuXZH9fuV4P21x7EvWdeGSU2cm6CeNHJu6RUUBna54wd0f7kjrz0v2Xlb5/ovQ96smizY46yfdMDnkf1BTBu8ExyS4C3gd8Vsf2TK1Q1e0qcuF9FNKyaTOwh8PlpSAYtyvfkfg7pGSX99ZcWvOzqmodNblN59Iir13IJdlV2EL+stK92cDpWBnNqsi7nnmSdT+jljROyE+bfUR0tuVJRN6JTbPfilHNj1TVi9JvE/ZLpfud7Fuq6p9svmc0ht1D5jAxMIDpK0ecfU03EpiSaovbm+9I/HRId8bJeusn710+H2x/1sYNv+3ZT95L/++KQRjJz6DKyD0Nmu53Ut8CdjRpP5RP9JA36k4RgptQXWwl9W8IdCUxxRUacajqw3X3gSOxDa3uuIkxv7zxz1HVa0Wk/FutnzkHvNMN/eS9KzmwDaX31f2gqosnKI498/AzakAkP+EycuRpDVV9CEBVV4rIPsD5iVlbG1+H9c1rR5EympHINPOpw4lYBXmKqs5V1Sc3dE5gUw+fBbYWkXuBdwFvrgoFqd5tKCpNV9TXSOUq4nblOxh/Vw1qWadLzkv1DlLC3bIBRJ556zMaQBq1D51tebpfRHZcHYF1Vq8Ang5McE6c4uqqvnntKK+/DHsINyqBPlhFDGH6iuFM4SytXHc5beglaIQWzNvixkn19spFZYPPqsup1S93nUbgnqjOtjwBmxCcBvXUt47taKlHbiaHoSdgVAIBppRDV2jNJlJp6Igdx1iH12nDH42/dN3Y6XXd8ANLca5xeOWissH0dsaIBH4fSaPTPn4VzXeXeSrpbOv0Ii8bndWLmRyGnoBRCXRLaFiaPj0bS6ObNltHHN7KFY07kO+uRzuRTsKb95srv9dSvb1yUdlguXZGdyZAcffaRz/57jJPJZ0965vXjrquFzM5DD0BOfTx0ALTV5HGt/K/SU/h9Bt3r3x3Xbmx0Y63M4m8IX8f2LFybzZwJvB4VC4q26dddTG1uiqQH2+D3ne+u8hT6T9tHjy8djSQkfBMDENPwKgEOnQMWTXiXpXQW2kCcbuncAYQ99KuKzfW6Xk7k8hIy7XG4ZWLynYZiE2trgjkx9ugd57vSJ5q/ttU325x2tFARsIzMWQW39TB66w1zIBS1Ye1sskv4Uj6YCu1QUv0XOwMof1F5CQmspPccQfyvUYgfg8EOBQYR8tW1cdU9VDsWPMC7rhV9R51UL29clHZjhFhJV4WSKPLPgaU774p3D3q2+P47KjzOjljMeweclQCDkIDg5m+6vTtk9gUjncU0fnUWbrf6UJ0JO6ZFBjA1GrEPgaVpwHoXDrd8/1EC0NPwKgEfISGzqevBpAP9xROQOcgps5mVIM6zMAAplaHHQaR5kHUt1EP2ZPE1OFtmO+4YoPjXcDrKjLh3e0tCP1HRLYGngVcU6Qj3X+Zql6SLi/T7qdb3PlW1XualFTiPwLYRVUfEpHNk77NVfWUqk4vAnE/YeB85ouBv+zYNgeGQJ46j3oAOkcaeQ1qiqCqd6rqS4ENga1VdS8tOTYVkcMYzJqNC8l55kXAO4AVIvKq0s/Hl9L0dq/OAAYxJ9/1WtWMQ/CZPyHWTQZlxwPy4JHRhmEP4XKwgM3zD3P6amhTON58B3WO5HrRoJ75IJ7RsPMU0Jn3LQ0p5Cm+6QPRIU5f0f30ohuBfEdwKBWnsKr6GHCoiHy2T50zDYOYWh02BmHHg6hvGQ7kKb7pAw3IDmL66gkxheOFDo+S/UTCjHrmCXm6eAYhd1DTBxFDH0Ql9O4Fypg5mInPfBB5mokd+RMC+UTdKYCHVSQin1Dnwq2IbELDmT8ismceIWRkdIdc34aH3EENGNLH0dIZGRkZGWSSxBQgL7BmZGRk9IHcQQ0eQ2PHZWRkZDyRkUkSg0deYM3IyMjoA3kNasDIC6wZGRkZ/SF3UBkZGRkZ0xJ5ii8jIyMjY1oid1AZGRkZGdMSuYPKyJhCiMhD7VIZGRmQO6iMjIyMjGmK3EFlZAwBYvh3EVkhIjeJyIJ0fw0R+ZSI/FBEviMi3xSRg4ad3oyMYSBv1M3IGA4OwFxf7YDtibtORH4A7ImdY7Qt8AzMRdbpw0liRsZwkUdQGRnDwV7AWar6uKreDywCdkv3z1PVP6W9c5cOM5EZGcNE7qAyMjIyMqYlcgeVkTEcXA4sEJFZIrIhdlbRtcBi4MC0FrURdjheRsZIIq9BZWQMB18F9gBuxE5Tfr+q3iciFwD7ArcAPwWWAA8MLZUZGUNEdnWUkTHNICLrpeNZNsBGVXs2HV+fkTGTkUdQGRnTDxeLyFOBJwHH5c4pY1SRR1AZGRkZGdMSmSSRkZGRkTEtkTuojIyMjIxpidxBZWRkZGRMS+QOKiMjIyNjWiJ3UBkZGRkZ0xK5g8rIyMjImJb4/4CMp2Gb7oNmAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pdm_similarity = cosine_similarity(benchmarked_pd.drop(str_cols, axis=1))\n",
+    "pdm_similarity = pd.DataFrame(pdm_similarity, columns=benchmarked_pd['log'], index=benchmarked_pd['log'])#.sort_values(by='BPI_Challenge_2013_closed_problems')\n",
+    "pdm_similarity = pdm_similarity.loc[pdm_similarity.columns[len(real_log_names)-1:],pdm_similarity.columns[:len(real_log_names)-1]].copy()\n",
+    "pdm_similarity = pdm_similarity.transpose()[ft_similarity.columns]#.sort_values(by=ft_similarity.columns[0], ascending=False)\n",
+    "\n",
+    "print(\"Metrics similarity:\", pdm_similarity.shape)\n",
+    "#plt.imshow(pdm_similarity, cmap='viridis', interpolation='nearest')\n",
+    "sns.heatmap(pdm_similarity.astype(np.float16), cmap=\"viridis\", vmin=0.6)\n",
+    "ax = plt.gca()\n",
+    "ax.set_title(\"Performance metrics similarity between BPICs and GenED\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "15811602",
+   "metadata": {},
+   "source": [
+    "## Statistical test: Is there a statistical significant relation between feature similarity and performance metrics?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "b949efcd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "kendalltau: stat=0.061, p=0.000\n",
+      "Probably dependent\n"
+     ]
+    }
+   ],
+   "source": [
+    "## STATISTICAL TEST ON COSINE SIMILARITIES\n",
+    "from scipy.stats import pearsonr\n",
+    "from scipy.stats import kendalltau\n",
+    "\n",
+    "data1 = ft_similarity.to_numpy().flatten()\n",
+    "data2 = pdm_similarity.to_numpy().flatten()\n",
+    "\n",
+    "stat, p = eval(f\"{TEST}(data1, data2)\")\n",
+    "print(f\"{TEST}:\",'stat=%.3f, p=%.3f' % (stat, p))\n",
+    "if p > 0.05:\n",
+    " print('Probably independent')\n",
+    "else:\n",
+    " print('Probably dependent')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "d702b321",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(295, 9) (295, 17)\n",
+      "Generated (281, 9) (281, 17)\n",
+      "['rutpt', 'rmcv', 'rt10v', 'enve', 'ense', 'enself', 'enseef']\n",
+      "Direct kendalltau Generated\n",
+      "Generated\n",
+      "../output/plots/pdm_kendalltau_GenED_nanDropped\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### DIRECT STATISTICAL TEST\n",
+    "from scipy.stats import spearmanr\n",
+    "from scipy.stats import kendalltau\n",
+    "from scipy.stats import pearsonr\n",
+    "from numpy import isnan\n",
+    "\n",
+    "import sys\n",
+    "import os\n",
+    "sys.path.append(os.path.dirname(\"../tag/utils/io_helpers.py\"))\n",
+    "from io_helpers import get_keys_abbreviation\n",
+    "\n",
+    "print(benchmarked_ft.shape, benchmarked_pd.shape)\n",
+    "\n",
+    "benchmarked_ft_plot = benchmarked_ft.copy()[benchmarked_ft['source']==DATA_SOURCE]\n",
+    "benchmarked_pdm_plot = benchmarked_pd.copy()[benchmarked_pd['source']==DATA_SOURCE]\n",
+    "\n",
+    "#benchmarked_ft = benchmarked_ft.head(10)\n",
+    "#benchmarked_pdm = benchmarked_pdm.head(10)\n",
+    "print(DATA_SOURCE, benchmarked_ft_plot.shape, benchmarked_pdm_plot.shape)\n",
+    "\n",
+    "tmp = list(benchmarked_ft_plot.columns[1:-1])\n",
+    "df_tmp = pd.DataFrame(index=benchmarked_pdm_plot.columns[1:-1], columns=tmp)\n",
+    "#print(\"Benchmark_pdm:\", benchmarked_pdm.columns[1:-1])\n",
+    "#print (\"Benchmark_ft:\", tmp)\n",
+    "\n",
+    "for feature in benchmarked_ft_plot.columns:\n",
+    "    if feature != 'log' and feature != 'source':\n",
+    "        for metric in benchmarked_pdm_plot.columns:\n",
+    "            if metric != 'log' and metric != 'source':\n",
+    "                #print(feature, benchmarked_pdm.columns[1])\n",
+    "                stat, p = eval(f\"{TEST}(benchmarked_ft_plot[feature], benchmarked_pdm_plot[metric])\")   \n",
+    "                #print(feature, metric, p, p <= 0.05)\n",
+    "                df_tmp.loc[metric, feature] = stat*(1.0 if (p <= 0.05) else 0.0)\n",
+    "\n",
+    "feature_keys = get_keys_abbreviation(df_tmp.columns).split(\"_\")\n",
+    "print(feature_keys)\n",
+    "df_tmp.columns=feature_keys\n",
+    "print(\"Direct\", TEST, DATA_SOURCE)\n",
+    "# df_tmp[pd.isnan()]\n",
+    "\n",
+    "sns.heatmap(df_tmp.fillna(0), annot=True, cmap=\"viridis\", annot_kws={\"size\": 9})\n",
+    "ax = plt.gca()\n",
+    "sns.heatmap(df_tmp.fillna(0), mask=df_tmp.fillna(0)!=0, cmap=\"Greys\", annot=False, cbar=False, ax=ax)\n",
+    "#ax.set_title(\"P-values of features leading to process discovery metrics\", fontsize=15)\n",
+    "plt.tight_layout()\n",
+    "output_path = f\"../output/plots/pdm_{get_output_file_name(TEST, DATA_SOURCE, EXP_BASELINE, IMPUTE)}\"\n",
+    "print(output_path)\n",
+    "plt.savefig(output_path, dpi=300)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b367b003",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(295, 9) (295, 17)\n",
+      "Generated (281, 9) (281, 17)\n",
+      "['rutpt', 'rmcv', 'rt10v', 'enve', 'ense', 'enself', 'enseef']\n",
+      "Similarity kendalltau Generated\n",
+      "Generated\n",
+      "../output/plots/pdmSim_kendalltau_GenED_nanDropped\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### SIMILARITY STATISTICAL TEST\n",
+    "from scipy.stats import spearmanr\n",
+    "from scipy.stats import kendalltau\n",
+    "from numpy import isnan\n",
+    "\n",
+    "print(benchmarked_ft.shape, benchmarked_pd.shape)\n",
+    "\n",
+    "benchmarked_ft_plot = benchmarked_ft.copy()[benchmarked_ft['source']==DATA_SOURCE]\n",
+    "benchmarked_pdm_plot = benchmarked_pd.copy()[benchmarked_pd['source']==DATA_SOURCE]\n",
+    "\n",
+    "print(DATA_SOURCE, benchmarked_ft_plot.shape, benchmarked_pdm_plot.shape)\n",
+    "\n",
+    "tmp = list(benchmarked_ft_plot.columns[1:-1])\n",
+    "df_tmp = pd.DataFrame(index=benchmarked_pdm_plot.columns[1:-1], columns=tmp)\n",
+    "#print(\"Benchmark_pdm:\", benchmarked_pdm.columns[1:-1])\n",
+    "#print (\"Benchmark_ft:\", tmp)\n",
+    "\n",
+    "\n",
+    "for feature in benchmarked_ft_plot.columns:\n",
+    "    if feature != 'log' and feature != 'source':\n",
+    "        for metric in benchmarked_pd.columns:\n",
+    "            if metric != 'log' and metric != 'source':\n",
+    "                #print(feature, benchmarked_pdm.columns[1])\n",
+    "                X = benchmarked_ft_plot[feature].to_numpy()\n",
+    "                ft_sim = (1-np.abs(np.subtract.outer(X,X)/max(X))).flatten()\n",
+    "                #ft_sim = np.nan_to_num(ft_sim)\n",
+    "                \n",
+    "                Y = benchmarked_pdm_plot[metric].to_numpy()\n",
+    "                Y = [y if y!=0 else 1.e-100 for y in Y]\n",
+    "                pdm_sim = (1-np.abs(np.subtract.outer(Y,Y))/Y).flatten()\n",
+    "                #pdm_sim = np.nan_to_num(pdm_sim)\n",
+    "                #print(ft_sim, pdm_sim)\n",
+    "                #print(f\"{TEST}(ft_sim, pdm_sim)\")\n",
+    "                stat, p = eval(f\"{TEST}(ft_sim, pdm_sim)\")\n",
+    "                #print(feature, metric, p, p <= 0.05)\n",
+    "                df_tmp.loc[metric, feature] = stat*(1.0 if (p <= 0.05) else 0)\n",
+    "\n",
+    "# df_tmp[pd.isnan()]\n",
+    "\n",
+    "feature_keys = get_keys_abbreviation(df_tmp.columns).split(\"_\")\n",
+    "print(feature_keys)\n",
+    "df_tmp.columns=feature_keys\n",
+    "sns.heatmap(df_tmp.fillna(0), annot=True, cmap=\"viridis\", annot_kws={\"size\": 9})\n",
+    "ax = plt.gca()\n",
+    "sns.heatmap(df_tmp.fillna(0), mask=df_tmp.fillna(0)!=0, cmap=\"Greys\", annot=True, annot_kws={\"color\":\"white\", \"size\": 9},  cbar=False, ax=ax)\n",
+    "print(\"Similarity\", TEST, DATA_SOURCE)\n",
+    "\n",
+    "#ax.set_title(\"P-values of feature similarity leading to process discovery metrics similarity\", fontsize=15)\n",
+    "output_path = f\"../output/plots/pdmSim_{get_output_file_name(TEST, DATA_SOURCE, EXP_BASELINE, IMPUTE)}\"\n",
+    "print(output_path)\n",
+    "plt.tight_layout()\n",
+    "plt.savefig(output_path, dpi=300)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}