From 2be111796d7f10da5d84a9d602b4bea20366ae32 Mon Sep 17 00:00:00 2001 From: Ananya Gupta <145869907+ananyag309@users.noreply.github.com> Date: Sat, 20 Jul 2024 11:32:42 +0530 Subject: [PATCH] Add files via upload --- .../Dataset/UniversalBank.csv | 5001 +++++++++++++++++ .../Images/Age Distribution.png | Bin 0 -> 19571 bytes .../Images/Age.png | Bin 0 -> 14081 bytes .../Images/Approved_Not_Approved.png | Bin 0 -> 36878 bytes .../Images/Average CC Spending.png | Bin 0 -> 20641 bytes .../Images/Box Plot of income.png | Bin 0 -> 14946 bytes .../CCAvg Distribution by Personal Loan.png | Bin 0 -> 34181 bytes .../Images/Distribution of Education.png | Bin 0 -> 17738 bytes .../Images/FNN_Accuracy.png | Bin 0 -> 60265 bytes .../Images/FNN_Loss.png | Bin 0 -> 50413 bytes .../Images/Heatmap.png | Bin 0 -> 113334 bytes ...Mortgage Distribution by Personal Loan.png | Bin 0 -> 19522 bytes .../Images/Personal loans.png | Bin 0 -> 29043 bytes .../Images/TabNet_Accuracy.png | Bin 0 -> 47201 bytes .../Images/TabNet_Loss.png | Bin 0 -> 42171 bytes .../Images/Updated_Correlation_Matrix.png | Bin 0 -> 131511 bytes .../Images/WDNN_Accuracy.png | Bin 0 -> 42723 bytes .../Images/WDNN_Loss.png | Bin 0 -> 35200 bytes .../Images/bar graph.png | Bin 0 -> 39556 bytes .../Images/conf_matrix.png | Bin 0 -> 4544 bytes .../Images/confusion matrix.png | Bin 0 -> 95211 bytes .../Images/histogram.png | Bin 0 -> 63808 bytes .../Images/income.png | Bin 0 -> 25899 bytes .../Images/input visualisation.png | Bin 0 -> 39844 bytes .../Images/modelloss.png | Bin 0 -> 33507 bytes .../Images/pie chart.png | Bin 0 -> 60503 bytes .../Images/training loss.png | Bin 0 -> 64588 bytes .../Model/FNN_TabNet_WDNN.ipynb | 1 + .../Model/README.md | 149 + .../Model/bank-loan-approval-using-AI.ipynb | 1864 ++++++ .../Bank Loan Approval Prediction/README.md | 16 + .../requirements.txt | 10 + 32 files changed, 7041 insertions(+) create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Dataset/UniversalBank.csv create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Age Distribution.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Age.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Approved_Not_Approved.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Average CC Spending.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Box Plot of income.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/CCAvg Distribution by Personal Loan.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Distribution of Education.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/FNN_Accuracy.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/FNN_Loss.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Heatmap.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Mortgage Distribution by Personal Loan.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Personal loans.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/TabNet_Accuracy.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/TabNet_Loss.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/Updated_Correlation_Matrix.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/WDNN_Accuracy.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/WDNN_Loss.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/bar graph.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/conf_matrix.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/confusion matrix.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/histogram.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/income.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/input visualisation.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/modelloss.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/pie chart.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Images/training loss.png create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Model/FNN_TabNet_WDNN.ipynb create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Model/README.md create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/Model/bank-loan-approval-using-AI.ipynb create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/README.md create mode 100644 Loan Status Prediction/Bank Loan Approval Prediction/requirements.txt diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Dataset/UniversalBank.csv b/Loan Status Prediction/Bank Loan Approval Prediction/Dataset/UniversalBank.csv new file mode 100644 index 00000000..1cb9db73 --- /dev/null +++ b/Loan Status Prediction/Bank Loan Approval Prediction/Dataset/UniversalBank.csv @@ -0,0 +1,5001 @@ +ID,Age,Experience,Income,ZIP Code,Family,CCAvg,Education,Mortgage,Personal Loan,Securities Account,CD Account,Online,CreditCard +1,25,1,49,91107,4,1.60,1,0,0,1,0,0,0 +2,45,19,34,90089,3,1.50,1,0,0,1,0,0,0 +3,39,15,11,94720,1,1.00,1,0,0,0,0,0,0 +4,35,9,100,94112,1,2.70,2,0,0,0,0,0,0 +5,35,8,45,91330,4,1.00,2,0,0,0,0,0,1 +6,37,13,29,92121,4,0.40,2,155,0,0,0,1,0 +7,53,27,72,91711,2,1.50,2,0,0,0,0,1,0 +8,50,24,22,93943,1,0.30,3,0,0,0,0,0,1 +9,35,10,81,90089,3,0.60,2,104,0,0,0,1,0 +10,34,9,180,93023,1,8.90,3,0,1,0,0,0,0 +11,65,39,105,94710,4,2.40,3,0,0,0,0,0,0 +12,29,5,45,90277,3,0.10,2,0,0,0,0,1,0 +13,48,23,114,93106,2,3.80,3,0,0,1,0,0,0 +14,59,32,40,94920,4,2.50,2,0,0,0,0,1,0 +15,67,41,112,91741,1,2.00,1,0,0,1,0,0,0 +16,60,30,22,95054,1,1.50,3,0,0,0,0,1,1 +17,38,14,130,95010,4,4.70,3,134,1,0,0,0,0 +18,42,18,81,94305,4,2.40,1,0,0,0,0,0,0 +19,46,21,193,91604,2,8.10,3,0,1,0,0,0,0 +20,55,28,21,94720,1,0.50,2,0,0,1,0,0,1 +21,56,31,25,94015,4,0.90,2,111,0,0,0,1,0 +22,57,27,63,90095,3,2.00,3,0,0,0,0,1,0 +23,29,5,62,90277,1,1.20,1,260,0,0,0,1,0 +24,44,18,43,91320,2,0.70,1,163,0,1,0,0,0 +25,36,11,152,95521,2,3.90,1,159,0,0,0,0,1 +26,43,19,29,94305,3,0.50,1,97,0,0,0,1,0 +27,40,16,83,95064,4,0.20,3,0,0,0,0,0,0 +28,46,20,158,90064,1,2.40,1,0,0,0,0,1,1 +29,56,30,48,94539,1,2.20,3,0,0,0,0,1,1 +30,38,13,119,94104,1,3.30,2,0,1,0,1,1,1 +31,59,35,35,93106,1,1.20,3,122,0,0,0,1,0 +32,40,16,29,94117,1,2.00,2,0,0,0,0,1,0 +33,53,28,41,94801,2,0.60,3,193,0,0,0,0,0 +34,30,6,18,91330,3,0.90,3,0,0,0,0,0,0 +35,31,5,50,94035,4,1.80,3,0,0,0,0,1,0 +36,48,24,81,92647,3,0.70,1,0,0,0,0,0,0 +37,59,35,121,94720,1,2.90,1,0,0,0,0,0,1 +38,51,25,71,95814,1,1.40,3,198,0,0,0,0,0 +39,42,18,141,94114,3,5.00,3,0,1,1,1,1,0 +40,38,13,80,94115,4,0.70,3,285,0,0,0,1,0 +41,57,32,84,92672,3,1.60,3,0,0,1,0,0,0 +42,34,9,60,94122,3,2.30,1,0,0,0,0,0,0 +43,32,7,132,90019,4,1.10,2,412,1,0,0,1,0 +44,39,15,45,95616,1,0.70,1,0,0,0,0,1,0 +45,46,20,104,94065,1,5.70,1,0,0,0,0,1,1 +46,57,31,52,94720,4,2.50,1,0,0,0,0,0,1 +47,39,14,43,95014,3,0.70,2,153,0,0,0,1,0 +48,37,12,194,91380,4,0.20,3,211,1,1,1,1,1 +49,56,26,81,95747,2,4.50,3,0,0,0,0,0,1 +50,40,16,49,92373,1,1.80,1,0,0,0,0,0,1 +51,32,8,8,92093,4,0.70,2,0,0,1,0,1,0 +52,61,37,131,94720,1,2.90,1,0,0,0,0,1,0 +53,30,6,72,94005,1,0.10,1,207,0,0,0,0,0 +54,50,26,190,90245,3,2.10,3,240,1,0,0,1,0 +55,29,5,44,95819,1,0.20,3,0,0,0,0,1,0 +56,41,17,139,94022,2,8.00,1,0,0,0,0,1,0 +57,55,30,29,94005,3,0.10,2,0,0,1,1,1,0 +58,56,31,131,95616,2,1.20,3,0,1,0,0,0,0 +59,28,2,93,94065,2,0.20,1,0,0,0,0,0,0 +60,31,5,188,91320,2,4.50,1,455,0,0,0,0,0 +61,49,24,39,90404,3,1.70,2,0,0,1,0,1,0 +62,47,21,125,93407,1,5.70,1,112,0,1,0,0,0 +63,42,18,22,90089,1,1.00,1,0,0,0,0,0,0 +64,42,17,32,94523,4,0.00,2,0,0,0,0,1,0 +65,47,23,105,90024,2,3.30,1,0,0,0,0,0,0 +66,59,35,131,91360,1,3.80,1,0,0,0,0,1,1 +67,62,36,105,95670,2,2.80,1,336,0,0,0,0,0 +68,53,23,45,95123,4,2.00,3,132,0,1,0,0,0 +69,47,21,60,93407,3,2.10,1,0,0,0,0,1,1 +70,53,29,20,90045,4,0.20,1,0,0,0,0,1,0 +71,42,18,115,91335,1,3.50,1,0,0,0,0,0,1 +72,53,29,69,93907,4,1.00,2,0,0,0,0,1,0 +73,44,20,130,92007,1,5.00,1,0,0,0,0,0,1 +74,41,16,85,94606,1,4.00,3,0,0,0,0,1,1 +75,28,3,135,94611,2,3.30,1,0,0,0,0,0,1 +76,31,7,135,94901,4,3.80,2,0,1,0,1,1,1 +77,58,32,12,91320,3,0.30,3,0,0,0,0,0,0 +78,46,20,29,92220,3,0.50,2,0,0,0,0,0,0 +79,54,30,133,93305,2,2.60,3,0,1,0,0,0,0 +80,50,26,19,94720,2,0.40,1,118,0,0,0,1,0 +81,60,36,41,95134,4,1.30,1,174,0,0,0,1,1 +82,47,22,40,94612,3,2.70,2,0,0,0,0,1,0 +83,41,16,82,92507,1,4.00,3,0,0,0,0,1,0 +84,33,9,50,94305,1,2.40,2,0,0,0,0,0,0 +85,46,22,18,91730,1,0.90,3,0,0,0,0,1,0 +86,27,2,109,94005,4,1.80,3,0,0,0,0,0,0 +87,40,16,42,94501,4,2.20,2,126,0,0,0,0,0 +88,48,22,78,94305,3,1.10,1,0,0,0,0,1,0 +89,65,41,51,94117,2,1.10,1,0,0,0,0,1,0 +90,25,-1,113,94303,4,2.30,3,0,0,0,0,0,1 +91,55,30,118,90277,4,5.60,2,0,1,0,0,1,0 +92,35,10,29,94105,4,1.10,3,0,0,0,0,1,0 +93,43,19,34,94305,3,0.60,2,0,0,0,0,0,0 +94,60,34,64,94550,2,1.70,3,236,0,1,0,1,0 +95,65,39,121,92612,1,2.00,1,0,0,0,0,0,0 +96,38,12,48,95617,4,0.20,3,0,0,0,0,1,0 +97,41,15,80,95014,1,5.20,1,0,0,0,0,0,0 +98,54,28,161,92121,1,2.90,1,0,0,0,0,1,0 +99,49,23,94,92374,1,0.30,1,0,0,0,0,1,0 +100,66,41,15,91711,3,0.10,3,0,0,0,0,1,0 +101,48,23,74,94080,1,1.20,1,0,0,0,0,1,0 +102,61,36,30,94608,3,1.30,2,0,0,0,0,0,0 +103,53,23,44,93555,3,1.00,3,198,0,0,0,1,1 +104,43,18,22,95670,2,0.30,2,0,0,0,0,1,0 +105,56,32,38,93311,4,1.30,1,166,0,0,0,1,1 +106,24,0,35,94704,3,0.10,2,0,0,1,0,1,0 +107,43,17,69,92717,4,2.90,1,0,0,0,0,1,1 +108,42,18,43,92037,1,0.70,1,136,0,0,0,0,0 +109,33,7,32,95136,1,0.60,3,166,0,0,0,1,0 +110,43,17,49,94542,1,2.80,1,0,0,0,0,1,0 +111,41,14,9,91330,3,1.00,2,0,0,0,0,0,0 +112,62,38,45,94143,4,1.30,2,0,0,0,0,1,0 +113,40,15,82,91775,3,1.00,1,309,0,0,0,0,0 +114,58,34,92,92703,2,2.80,1,103,0,0,0,0,0 +115,39,14,39,92354,3,0.50,3,0,0,0,0,1,0 +116,65,40,81,92024,3,1.80,2,0,0,0,0,1,0 +117,54,29,35,92831,1,1.50,2,0,0,0,0,1,0 +118,58,33,61,92833,2,2.30,3,193,0,0,0,1,0 +119,41,16,73,92647,3,3.00,1,0,0,0,0,1,0 +120,32,7,112,94304,1,4.60,1,366,0,0,0,0,0 +121,54,29,12,90057,2,0.20,3,0,0,0,0,1,0 +122,52,26,38,91711,3,0.90,3,0,0,0,0,1,0 +123,58,32,73,94523,2,0.70,2,0,0,0,0,1,1 +124,37,13,84,92130,1,3.60,2,0,0,1,0,0,0 +125,39,15,78,92121,4,2.40,1,118,0,0,0,1,0 +126,60,35,80,91301,3,0.50,1,0,0,0,0,1,0 +127,31,5,115,92096,2,1.30,1,101,0,0,0,1,1 +128,34,8,82,92646,1,2.70,2,251,0,0,0,1,0 +129,38,14,74,92182,2,0.00,1,0,0,1,0,1,0 +130,41,16,70,92131,3,0.50,3,0,0,0,0,0,1 +131,28,4,81,94801,3,1.50,1,276,0,0,0,1,0 +132,58,34,149,93720,4,7.20,2,0,1,0,1,1,1 +133,31,1,51,90840,2,1.75,3,0,0,0,0,0,0 +134,30,4,39,90245,3,1.10,2,0,0,0,0,1,0 +135,53,29,98,95035,3,1.80,2,0,0,0,0,0,0 +136,58,33,45,93010,4,2.10,1,0,0,0,0,1,1 +137,59,32,49,95035,4,2.50,2,0,0,0,0,1,0 +138,49,25,128,95054,2,0.40,1,0,0,0,0,0,0 +139,59,34,42,94928,3,1.50,1,0,0,1,1,0,1 +140,59,35,18,93305,1,1.20,3,0,0,0,0,1,0 +141,51,25,31,90245,2,0.40,3,161,0,0,0,1,1 +142,35,11,58,95831,3,2.00,1,149,0,0,0,1,1 +143,33,9,48,91770,1,2.10,3,0,0,0,0,0,1 +144,25,1,54,94117,4,1.60,1,0,0,0,0,1,1 +145,49,23,70,92093,2,1.50,2,0,0,0,0,0,0 +146,59,35,124,90007,1,7.40,1,0,0,0,0,0,1 +147,46,19,84,94102,1,2.67,2,0,0,0,0,1,1 +148,50,25,83,94542,4,3.60,3,188,0,0,0,1,0 +149,52,28,163,91423,2,0.40,1,116,0,0,0,1,0 +150,48,22,42,93955,3,2.20,2,0,0,0,0,0,0 +151,46,22,118,94107,2,7.50,1,0,0,0,1,1,1 +152,26,0,132,92834,3,6.50,3,0,1,0,0,0,1 +153,57,32,24,93117,1,1.30,1,0,0,0,0,1,1 +154,60,36,22,94551,2,1.00,1,0,0,1,1,1,1 +155,54,29,58,92612,4,1.30,3,0,0,0,0,0,0 +156,24,0,60,94596,4,1.60,1,0,0,0,0,1,0 +157,26,0,15,92131,4,0.40,1,0,0,0,0,0,1 +158,41,17,83,94025,4,2.67,1,0,0,0,0,1,1 +159,32,6,79,94720,2,1.50,3,0,0,0,0,1,1 +160,61,35,41,94545,4,1.70,2,0,0,1,0,1,0 +161,29,0,134,95819,4,6.50,3,0,1,0,0,0,0 +162,61,35,80,95053,2,2.80,1,0,0,0,0,1,0 +163,38,12,52,90036,1,2.00,1,0,0,0,0,0,0 +164,28,4,70,91125,4,2.60,1,0,0,0,0,1,0 +165,53,27,92,95120,2,1.10,1,0,0,1,0,0,0 +166,27,1,43,94706,1,1.50,1,0,0,0,0,1,0 +167,25,1,21,95827,3,1.00,2,0,0,0,0,0,0 +168,33,9,23,94305,3,0.90,3,0,0,0,0,1,1 +169,50,26,13,91320,4,1.00,1,0,0,0,0,1,0 +170,27,1,112,90503,4,2.10,3,0,0,0,0,0,1 +171,27,1,138,90250,2,2.00,1,0,0,0,0,1,0 +172,52,28,11,95817,3,0.40,1,0,0,1,0,0,0 +173,38,13,171,92717,2,7.80,1,0,0,0,0,1,0 +174,58,34,42,90095,4,1.50,1,0,0,0,0,1,1 +175,42,17,168,95503,2,7.90,2,0,1,0,0,1,0 +176,45,20,85,91711,4,1.10,2,0,0,1,0,1,0 +177,52,25,44,93111,3,1.00,2,135,0,0,0,1,0 +178,29,3,65,94132,4,1.80,2,244,0,0,0,0,0 +179,53,29,24,95818,4,0.20,1,0,0,0,0,1,1 +180,62,37,11,91942,1,0.10,1,0,0,0,0,1,0 +181,51,27,38,90401,2,1.00,3,164,0,0,0,1,0 +182,36,12,10,93524,4,0.70,2,81,0,0,0,0,0 +183,24,0,135,95133,1,1.50,1,0,0,0,0,1,0 +184,29,3,148,92173,3,4.10,1,0,1,0,0,1,0 +185,52,26,63,92717,2,1.50,2,0,0,1,0,1,0 +186,39,14,115,91320,1,1.00,3,0,0,0,0,1,0 +187,48,23,45,95616,1,0.30,1,0,0,0,0,1,1 +188,46,21,159,94305,3,1.90,3,315,1,0,0,1,0 +189,64,40,169,91320,2,2.10,1,122,0,0,0,1,0 +190,55,29,112,94043,2,1.40,1,0,0,0,0,1,0 +191,60,36,93,92521,1,4.30,1,0,0,0,0,1,0 +192,51,25,29,90404,1,0.30,3,140,0,0,0,0,0 +193,50,23,85,92122,1,2.67,2,0,0,0,0,1,0 +194,48,24,21,93118,4,0.60,1,0,0,0,0,1,1 +195,53,29,144,92697,2,6.80,1,0,0,0,0,1,0 +196,34,10,13,94577,4,1.00,1,95,0,1,0,1,0 +197,48,24,165,93407,1,5.00,1,0,0,0,0,0,1 +198,55,31,9,91345,4,0.70,1,89,0,0,0,1,0 +199,27,3,59,94123,4,0.00,1,90,0,1,0,1,0 +200,36,11,158,92152,1,5.10,3,0,1,0,1,1,1 +201,32,6,29,91355,1,1.90,3,0,0,0,0,1,1 +202,35,9,20,94609,2,1.40,3,0,0,0,0,1,1 +203,30,3,68,94306,4,2.00,2,0,0,0,0,1,0 +204,58,34,65,95747,4,2.20,1,0,0,0,0,1,0 +205,56,31,61,96150,2,1.90,2,105,0,0,0,0,0 +206,38,12,91,95616,4,1.40,2,100,0,0,0,0,1 +207,49,25,31,91355,1,1.00,1,0,0,1,0,1,0 +208,34,10,71,94115,4,0.10,2,0,0,0,0,0,0 +209,40,16,73,94110,4,2.67,1,0,0,0,0,1,1 +210,64,39,172,94707,4,3.10,1,282,1,0,1,1,1 +211,51,26,20,92131,2,0.00,1,0,0,0,0,0,0 +212,44,18,55,94720,1,0.20,1,0,0,0,0,0,0 +213,46,22,69,91604,2,1.70,1,209,0,0,0,0,0 +214,57,33,155,91326,1,7.40,1,0,0,0,0,1,0 +215,54,28,94,90291,1,1.90,2,0,0,0,0,0,0 +216,38,14,92,95818,2,0.00,1,249,0,0,0,1,1 +217,27,3,125,95521,2,0.60,1,0,0,0,0,0,0 +218,39,14,74,94305,3,3.00,1,0,0,0,0,0,0 +219,44,20,72,92807,3,0.30,3,0,0,0,0,1,0 +220,56,30,61,94707,1,2.20,3,0,0,0,0,1,1 +221,32,6,25,92130,2,0.30,1,0,0,0,0,0,1 +222,45,19,83,95051,2,1.70,2,0,0,0,0,1,0 +223,26,2,104,94306,3,2.50,1,0,0,0,0,0,0 +224,55,25,41,95014,3,1.00,3,0,0,0,0,1,0 +225,52,27,58,94305,4,1.80,3,91,0,0,0,0,0 +226,39,13,93,94720,1,1.50,3,0,0,0,0,0,1 +227,24,-1,39,94085,2,1.70,2,0,0,0,0,0,0 +228,47,23,148,94551,2,7.50,1,0,0,0,1,1,1 +229,47,22,53,92677,4,1.90,3,98,0,1,1,0,1 +230,48,24,71,93117,2,1.70,1,145,0,0,0,0,1 +231,47,22,92,94720,1,2.80,2,0,0,0,0,1,0 +232,35,10,61,94304,4,2.10,3,0,0,0,0,1,0 +233,46,19,38,94122,3,2.50,2,135,0,0,0,0,0 +234,62,37,58,91320,4,1.70,1,0,0,0,0,1,0 +235,26,1,80,95616,1,0.80,2,150,0,0,0,0,0 +236,38,8,71,94720,4,1.80,3,0,0,0,0,1,0 +237,43,18,89,93407,3,0.50,3,0,0,0,0,1,1 +238,62,38,83,92521,1,1.80,3,0,0,0,0,1,0 +239,57,32,28,95831,3,0.20,1,0,0,0,0,1,1 +240,28,3,52,94112,4,1.70,2,0,0,0,0,0,0 +241,51,26,70,90089,1,1.20,1,169,0,0,0,0,0 +242,48,22,71,91711,1,1.40,3,0,0,0,0,0,1 +243,41,16,75,94005,1,3.70,3,280,0,0,0,0,0 +244,65,39,170,90095,3,7.90,3,99,1,0,1,1,0 +245,41,17,78,94025,4,0.80,1,78,0,0,0,1,0 +246,35,11,25,92614,2,1.00,2,0,0,0,0,0,0 +247,38,14,60,94025,2,0.60,3,0,0,0,0,1,1 +248,53,29,120,92626,4,2.70,2,111,1,1,1,1,0 +249,55,29,99,92121,2,1.40,1,264,0,0,0,1,1 +250,26,1,55,90089,3,2.60,3,113,0,0,0,0,1 +251,30,6,29,94305,3,1.00,2,117,0,0,0,0,0 +252,54,28,170,92182,2,6.20,2,325,1,0,0,1,0 +253,65,40,53,91711,3,2.20,1,0,0,0,0,0,1 +254,47,21,138,94583,1,0.00,1,0,0,0,0,0,0 +255,65,41,134,91942,3,3.90,3,121,1,0,0,1,0 +256,66,40,42,92103,2,0.70,3,138,0,0,0,0,1 +257,26,0,99,92697,4,2.30,3,0,0,0,0,0,1 +258,66,41,18,92691,3,0.50,1,0,0,0,0,0,1 +259,35,9,24,95747,4,0.30,1,0,0,0,0,1,0 +260,56,30,55,94107,1,1.40,1,77,0,0,0,1,0 +261,51,27,58,92407,1,0.00,1,0,0,0,0,0,1 +262,42,16,111,93106,2,1.20,3,251,1,0,0,1,0 +263,49,23,33,90245,1,0.30,3,0,0,0,1,1,1 +264,27,1,74,92121,4,1.80,2,112,0,0,0,1,1 +265,45,19,38,90840,2,0.70,1,0,0,0,0,0,0 +266,49,23,23,94305,4,0.60,3,98,0,1,0,0,0 +267,63,38,61,94720,2,1.50,1,0,0,0,0,1,0 +268,47,22,81,90504,1,2.90,1,138,0,0,0,0,0 +269,64,39,129,94002,1,2.50,1,0,0,0,0,1,0 +270,43,13,33,95039,1,0.75,3,0,0,0,0,0,0 +271,60,36,63,94063,4,2.20,1,0,0,0,0,1,0 +272,40,14,70,94923,4,1.40,2,0,0,0,0,1,0 +273,29,3,45,95023,4,0.20,1,158,0,0,0,1,1 +274,41,16,65,90095,3,0.50,3,0,0,0,0,1,0 +275,30,5,74,95616,4,2.20,1,0,0,1,0,0,1 +276,49,24,50,94706,4,1.80,3,0,0,1,0,0,0 +277,30,5,22,90058,4,0.50,3,109,0,0,0,1,0 +278,29,2,30,92126,4,1.00,3,0,0,0,0,0,0 +279,50,26,21,91125,4,1.00,1,0,0,0,0,1,0 +280,39,14,155,94577,2,3.90,1,0,0,0,0,1,0 +281,33,8,64,92121,4,2.10,3,164,0,0,0,1,0 +282,57,31,65,94118,4,2.60,3,0,0,0,0,0,1 +283,34,9,71,91711,4,0.70,3,0,0,0,0,1,0 +284,61,36,40,90029,3,0.50,2,0,0,1,0,1,0 +285,44,19,69,92806,3,0.50,3,0,0,0,0,1,0 +286,40,13,69,94305,3,2.33,2,0,0,0,0,0,0 +287,51,25,45,94806,3,0.60,2,131,0,0,0,1,0 +288,37,12,62,92110,3,0.70,2,0,0,0,0,0,1 +289,44,19,172,94306,2,4.30,3,391,1,1,1,1,0 +290,42,15,24,92121,3,1.00,2,0,0,0,0,1,1 +291,51,25,80,92373,1,4.90,1,0,0,0,0,0,0 +292,43,16,8,90089,3,0.67,2,88,0,0,0,1,0 +293,30,5,38,94542,4,0.80,1,129,0,0,0,1,1 +294,45,19,93,90095,4,2.60,3,0,0,0,0,0,0 +295,35,9,55,94536,1,2.00,1,0,0,0,0,1,0 +296,60,34,64,94304,2,1.70,3,0,0,0,0,0,1 +297,34,9,122,90623,1,0.00,1,0,0,0,0,1,0 +298,55,25,70,93720,3,1.40,3,0,0,0,0,1,0 +299,43,19,81,92069,2,3.20,1,0,0,0,0,0,0 +300,41,15,159,90057,1,5.50,3,0,1,0,1,1,0 +301,34,9,70,92843,4,1.30,1,0,0,1,0,0,0 +302,65,39,150,92120,2,6.90,1,196,0,0,0,0,0 +303,45,21,152,94550,2,7.50,1,0,0,0,0,1,0 +304,49,25,195,95605,4,3.00,1,617,1,0,0,0,0 +305,48,23,22,90740,1,0.10,1,0,0,0,0,0,0 +306,60,35,22,91207,1,1.30,1,123,0,0,0,1,0 +307,55,29,79,92373,3,0.80,1,0,0,0,0,1,1 +308,42,18,33,90401,1,1.40,3,0,0,0,0,1,0 +309,32,8,128,94720,2,4.33,1,0,0,0,1,1,1 +310,62,38,91,95929,1,3.80,1,0,0,1,0,1,0 +311,57,32,39,90277,4,0.90,1,0,0,0,0,1,1 +312,52,26,121,94550,1,7.30,1,167,0,0,0,1,0 +313,36,6,21,91741,1,0.67,3,0,0,1,0,1,0 +314,34,9,41,93720,3,2.30,1,0,0,0,0,0,1 +315,63,37,45,93437,2,0.70,3,0,0,0,0,1,0 +316,24,-2,51,90630,3,0.30,3,0,0,0,0,1,0 +317,57,31,165,95054,1,1.60,2,0,1,0,0,1,0 +318,40,16,119,91335,2,4.20,2,0,1,0,0,1,0 +319,27,2,110,95670,4,1.80,3,190,0,0,0,1,0 +320,65,39,20,90034,3,0.70,2,0,0,0,0,0,1 +321,60,34,64,90266,1,0.80,2,248,0,0,0,0,0 +322,44,20,101,92717,3,4.40,2,82,1,0,0,0,0 +323,63,39,101,92007,1,3.90,1,0,1,1,1,1,0 +324,59,34,99,90034,1,4.40,1,0,1,0,0,0,0 +325,56,30,158,90089,4,6.10,1,0,1,0,0,0,0 +326,54,28,89,95039,1,1.90,2,0,0,0,0,1,1 +327,52,27,80,95616,1,1.30,3,0,0,0,1,1,1 +328,58,32,114,91330,2,2.00,1,402,0,0,0,1,0 +329,60,35,49,94110,3,0.50,2,0,0,0,0,1,1 +330,28,4,191,90064,1,6.33,1,0,0,0,0,1,0 +331,54,30,78,92374,4,1.00,2,0,0,0,0,1,0 +332,32,6,28,94115,3,1.00,1,0,0,0,0,0,0 +333,59,33,42,95630,1,0.80,2,0,0,0,0,1,0 +334,63,38,140,92407,1,2.50,1,0,0,0,0,0,0 +335,48,23,45,95053,1,1.30,2,0,0,0,0,1,0 +336,56,32,122,95827,2,0.30,1,360,0,0,1,1,1 +337,36,12,65,95051,3,2.60,2,0,0,0,0,1,0 +338,57,27,68,94117,1,1.40,3,0,0,0,0,1,0 +339,29,3,153,93657,2,2.00,1,392,0,0,0,0,0 +340,39,13,89,92110,4,1.40,2,0,0,0,0,0,0 +341,59,34,91,93524,1,2.60,1,0,0,0,0,1,1 +342,31,6,55,92038,4,2.00,2,185,0,0,0,1,0 +343,43,19,118,91304,2,3.30,1,0,0,0,0,0,1 +344,35,5,22,93407,1,0.67,3,103,0,0,0,0,0 +345,54,24,63,92606,3,1.40,3,138,0,0,0,1,1 +346,51,27,12,92192,4,0.50,2,78,0,1,0,1,0 +347,44,19,50,90745,3,2.70,2,0,0,0,0,1,0 +348,25,0,43,94305,2,1.60,3,0,0,1,1,1,1 +349,40,15,173,95060,4,6.60,1,0,1,0,1,1,1 +350,26,2,60,93407,2,3.00,1,132,1,0,0,0,0 +351,39,14,113,94301,1,1.00,3,0,0,1,0,1,0 +352,28,4,155,92182,4,5.30,2,0,1,0,0,1,0 +353,52,28,91,92692,4,1.00,2,0,0,0,0,0,1 +354,53,29,55,95818,4,1.10,2,0,0,0,0,1,0 +355,44,20,173,90277,2,1.40,1,419,0,0,0,1,0 +356,43,19,71,92101,3,0.30,3,0,0,0,0,0,1 +357,56,30,24,94704,2,0.40,3,88,0,0,0,0,0 +358,38,14,42,94610,1,2.00,2,81,0,0,0,1,0 +359,30,6,141,94539,2,4.33,1,0,0,0,0,1,0 +360,32,6,32,93106,1,1.90,3,0,0,0,0,1,0 +361,35,10,55,94539,4,1.30,1,0,0,0,0,0,0 +362,43,19,153,90254,2,7.50,1,0,0,0,0,1,0 +363,58,32,113,94590,2,1.40,1,270,0,0,0,0,1 +364,25,0,30,92691,2,1.70,2,0,0,0,0,0,0 +365,54,24,29,92028,3,1.00,3,148,0,0,0,0,1 +366,57,32,174,90089,1,6.80,2,466,1,0,0,1,0 +367,50,24,35,92717,1,0.30,3,0,0,0,0,1,0 +368,32,8,98,95054,2,2.00,2,175,0,0,0,1,0 +369,63,37,30,92054,2,1.00,3,159,0,0,0,1,0 +370,31,6,58,95051,2,2.50,1,0,0,0,0,0,1 +371,36,12,25,92101,4,1.00,1,147,0,0,0,0,0 +372,58,34,19,92029,4,0.70,1,0,0,0,0,0,0 +373,56,30,44,93105,4,0.70,2,174,0,0,0,1,0 +374,49,25,20,90291,4,1.00,1,111,0,0,0,1,1 +375,30,5,98,91941,2,3.10,1,220,0,0,0,1,0 +376,33,7,90,92346,3,1.60,1,0,0,0,0,1,0 +377,45,21,61,94304,3,0.70,1,0,0,0,0,0,0 +378,30,5,40,94402,4,2.00,2,0,0,0,0,1,0 +379,47,23,38,94618,2,2.10,3,0,0,0,0,0,0 +380,25,0,28,92093,2,1.70,2,0,0,0,0,0,0 +381,63,33,34,94305,1,1.50,3,0,0,0,0,1,1 +382,55,29,73,95616,2,2.30,3,0,0,0,0,1,1 +383,65,41,133,94904,4,2.00,1,0,1,0,0,0,1 +384,44,18,53,94608,1,0.20,1,0,0,0,0,1,0 +385,51,25,21,9307,4,0.60,3,0,0,0,0,1,1 +386,35,9,40,93943,3,0.90,1,0,0,0,0,1,0 +387,30,5,41,95051,4,1.70,2,0,0,0,0,1,0 +388,31,5,82,95482,4,1.80,2,0,0,0,0,1,0 +389,54,30,100,95814,4,3.40,3,0,1,0,0,0,0 +390,45,20,155,90024,1,7.00,1,0,0,0,0,1,1 +391,45,19,45,92521,1,0.20,1,0,0,0,0,1,0 +392,58,32,9,94080,3,0.30,3,0,0,0,0,0,1 +393,54,29,48,91709,4,1.80,3,0,0,0,0,1,0 +394,53,28,18,90095,4,0.10,3,109,0,1,1,1,1 +395,33,9,80,91311,4,3.40,1,0,0,0,0,1,1 +396,60,35,64,94509,2,2.80,1,0,0,0,0,0,0 +397,50,24,29,93023,4,0.10,1,0,0,0,0,0,0 +398,26,2,48,90503,3,0.70,2,0,0,0,0,1,0 +399,54,30,23,94608,2,0.40,1,0,0,0,0,0,0 +400,28,3,84,90024,4,0.20,1,0,0,0,0,1,1 +401,36,10,179,94542,3,6.60,1,0,1,0,0,1,0 +402,29,2,30,95747,4,1.50,2,112,0,0,0,0,1 +403,54,28,93,91604,1,4.90,1,133,0,0,1,1,1 +404,55,30,39,92647,2,1.90,2,0,0,0,0,0,0 +405,61,36,60,92866,3,0.50,2,182,0,0,0,0,0 +406,36,11,133,90245,1,3.80,1,290,0,1,1,1,1 +407,45,19,125,92354,1,2.40,1,0,0,0,0,0,0 +408,64,40,58,93437,1,1.80,3,0,0,0,0,1,0 +409,60,36,89,91745,2,2.80,1,0,0,0,0,1,0 +410,49,22,82,90019,1,2.67,2,125,0,0,0,1,0 +411,47,23,110,94111,2,3.30,1,0,0,0,0,1,1 +412,60,36,54,92182,4,2.30,3,0,0,1,0,0,0 +413,45,20,89,93311,4,1.90,3,0,0,0,0,1,0 +414,32,7,42,92407,3,2.30,1,0,0,0,0,1,0 +415,52,28,41,94309,3,1.90,2,0,0,0,0,0,1 +416,35,8,38,93106,4,1.00,2,124,0,0,0,1,0 +417,40,15,85,94304,2,0.40,1,0,0,0,0,1,0 +418,53,29,83,90073,4,1.00,2,0,0,0,0,1,0 +419,27,0,33,90089,4,1.00,3,0,0,0,0,0,0 +420,58,33,50,94501,4,2.10,1,0,0,0,0,0,1 +421,47,22,58,93105,4,3.60,3,0,0,0,0,1,1 +422,28,3,115,92333,4,3.10,2,0,1,0,0,0,0 +423,46,20,145,91380,2,6.30,1,0,0,1,1,1,0 +424,43,19,161,95616,2,7.50,1,0,0,0,0,0,0 +425,56,30,38,92029,1,0.20,1,0,0,0,0,0,0 +426,28,3,28,90505,4,0.80,1,0,0,0,0,1,0 +427,42,18,75,92182,3,2.33,1,0,0,0,0,0,1 +428,32,7,35,92521,3,1.30,1,116,0,0,0,0,1 +429,62,38,24,94720,2,1.00,1,116,0,0,0,0,1 +430,37,13,78,94998,4,0.10,2,0,0,0,0,1,0 +431,51,26,113,94086,1,1.30,3,161,0,0,0,1,0 +432,39,13,75,94305,3,2.10,1,224,0,0,0,1,0 +433,43,17,91,91311,1,5.70,1,0,0,0,0,1,0 +434,52,28,31,91330,4,0.20,1,141,0,0,0,1,1 +435,30,6,45,95819,1,1.80,2,0,0,0,0,1,0 +436,52,26,80,94709,3,0.80,1,0,0,0,0,0,0 +437,61,35,50,92122,3,1.40,3,112,0,0,0,1,0 +438,36,9,31,95825,4,1.00,2,0,0,1,0,1,0 +439,58,32,113,93943,2,3.80,2,119,1,0,1,1,1 +440,47,23,29,94304,4,0.60,1,0,0,0,0,1,0 +441,64,39,59,92626,2,1.50,1,139,0,0,0,1,0 +442,52,27,43,93555,1,1.30,2,0,0,1,0,1,0 +443,58,28,122,95136,1,3.00,3,115,1,0,0,1,0 +444,48,24,29,90509,1,1.00,1,0,0,0,0,0,0 +445,64,40,91,93106,2,0.00,3,0,0,0,0,1,1 +446,58,32,65,94590,3,2.20,3,0,0,0,0,1,0 +447,47,23,22,93108,1,1.00,1,0,0,0,0,0,1 +448,49,23,71,95134,1,1.40,3,0,0,0,0,0,0 +449,31,4,60,94588,4,2.00,2,0,0,0,0,1,1 +450,61,37,60,91706,3,2.00,3,0,0,0,0,1,0 +451,51,25,69,95747,1,0.30,1,0,0,0,0,1,1 +452,28,-2,48,94132,2,1.75,3,89,0,0,0,1,0 +453,39,13,21,94022,3,0.20,2,0,0,0,0,0,0 +454,54,28,53,92109,4,2.80,2,0,0,1,0,0,0 +455,50,24,29,94110,3,0.90,3,0,0,0,0,0,0 +456,30,4,60,91107,4,2.20,2,0,0,0,0,1,0 +457,64,39,42,92068,3,0.50,2,116,0,0,0,1,0 +458,29,3,69,94303,3,0.30,3,0,0,0,0,0,0 +459,48,24,20,95841,1,1.00,1,0,0,0,0,1,1 +460,35,10,200,91107,2,3.00,1,458,0,0,0,0,0 +461,60,36,141,90277,2,2.10,1,0,0,0,0,1,1 +462,55,30,81,92123,2,3.70,1,0,0,1,0,0,0 +463,29,4,183,91423,3,8.30,3,0,1,0,0,1,0 +464,48,22,149,94928,2,5.50,2,0,1,1,1,1,0 +465,43,19,83,94305,4,3.60,3,0,1,0,0,0,1 +466,66,42,35,94305,1,1.90,2,172,0,0,0,1,0 +467,25,0,13,91342,2,0.90,3,0,0,0,0,1,0 +468,45,20,39,90232,1,2.40,1,0,0,0,0,0,1 +469,34,10,21,92634,1,0.50,3,0,0,0,0,1,0 +470,48,23,10,94609,2,0.70,3,0,0,0,0,1,1 +471,32,6,84,91006,4,1.80,2,0,0,0,0,0,0 +472,50,24,30,91768,4,0.10,1,161,0,0,0,1,1 +473,43,19,31,90007,4,0.30,1,156,0,0,0,1,0 +474,64,39,182,93955,1,1.20,2,547,1,0,0,1,0 +475,60,34,114,90028,2,6.90,1,0,0,0,0,1,0 +476,43,19,152,92008,3,6.10,2,0,1,0,0,0,0 +477,60,34,53,92717,1,0.80,2,0,0,1,0,0,1 +478,64,39,24,95112,4,0.40,2,78,0,0,0,1,0 +479,44,20,150,95060,2,3.30,1,0,0,0,0,0,1 +480,60,36,132,92154,2,6.00,1,470,0,0,0,1,1 +481,54,29,68,94998,3,1.60,3,0,0,0,0,1,1 +482,33,9,53,94063,1,1.20,1,0,0,0,0,0,1 +483,56,32,173,94022,1,4.60,2,88,1,0,1,1,0 +484,29,5,30,90095,3,1.00,2,0,0,0,0,0,0 +485,25,1,113,95023,2,0.20,1,0,0,0,0,1,1 +486,60,34,15,95014,1,0.80,2,0,0,0,0,1,0 +487,55,30,84,92173,2,3.70,1,304,0,1,0,1,0 +488,39,13,88,94117,4,1.40,2,0,0,0,0,1,1 +489,37,13,43,94122,3,2.80,1,0,0,0,0,1,0 +490,53,28,43,91380,2,2.10,3,0,0,0,1,1,1 +491,34,10,90,94303,2,2.70,1,0,0,0,0,1,0 +492,42,18,34,92115,4,0.30,1,104,0,1,0,1,0 +493,60,36,38,94596,4,1.30,1,0,0,0,0,1,0 +494,50,24,173,94720,1,1.00,1,0,0,0,0,1,1 +495,41,17,160,92647,2,8.00,1,0,0,0,0,1,0 +496,25,0,44,94545,4,0.60,2,0,0,0,0,1,1 +497,50,24,83,94301,2,0.40,3,0,0,0,0,1,0 +498,48,22,94,90623,4,2.60,3,0,0,0,0,1,0 +499,32,8,43,95023,1,2.10,3,0,0,0,0,0,1 +500,50,25,42,93108,3,1.70,2,0,0,0,0,1,0 +501,59,33,34,92177,2,0.30,1,0,0,0,0,0,0 +502,50,26,39,90640,3,1.90,2,0,0,0,0,1,0 +503,44,19,70,92833,1,0.10,2,0,0,0,0,0,0 +504,31,5,39,94022,4,1.80,3,185,0,0,0,0,1 +505,40,10,44,94720,3,2.00,3,0,0,0,0,1,0 +506,36,12,69,94305,3,3.10,2,0,1,0,0,1,0 +507,51,25,44,94608,3,0.90,3,0,0,0,0,0,0 +508,64,40,32,91380,3,0.10,3,0,0,0,0,1,0 +509,47,22,15,95521,2,0.70,3,0,0,0,0,0,0 +510,52,28,118,90503,2,6.80,1,112,0,0,0,1,0 +511,51,26,62,95136,1,1.30,2,221,0,0,0,1,0 +512,31,5,82,94143,4,2.20,2,0,0,0,0,0,0 +513,39,14,54,95035,3,3.00,1,108,0,0,0,0,1 +514,30,6,48,94607,1,2.10,3,0,0,0,0,0,0 +515,27,1,74,91730,3,0.30,3,0,0,0,0,1,0 +516,41,16,113,92780,1,1.00,3,211,0,0,0,0,1 +517,53,27,81,90009,3,1.70,2,0,0,0,0,0,0 +518,54,27,43,92834,3,1.00,2,169,0,0,0,0,0 +519,28,4,34,92677,1,1.80,2,0,0,0,0,1,0 +520,34,9,48,95616,1,2.50,3,105,0,0,0,1,0 +521,61,37,54,90024,4,1.20,2,129,0,0,0,1,1 +522,48,24,75,92518,4,1.40,2,0,0,0,0,1,0 +523,36,11,72,91007,1,2.80,1,224,0,0,0,0,0 +524,56,31,39,93023,4,0.90,1,0,0,0,0,0,0 +525,24,-1,75,93014,4,0.20,1,0,0,0,0,1,0 +526,64,38,79,94024,2,2.80,1,179,0,0,0,0,0 +527,26,2,205,93106,1,6.33,1,271,0,0,0,0,1 +528,33,8,65,90027,2,0.10,1,89,0,0,0,1,0 +529,64,39,122,90089,4,0.20,1,378,1,0,0,1,0 +530,39,15,82,95207,1,0.80,2,0,0,0,0,1,0 +531,54,30,21,91706,2,0.20,1,0,0,0,0,0,1 +532,32,6,50,90401,4,2.10,3,0,0,1,1,1,1 +533,62,37,39,94305,2,2.80,1,113,0,0,1,1,1 +534,27,2,101,92807,1,1.90,1,0,0,0,0,0,0 +535,53,28,41,93117,2,0.60,3,0,0,1,0,0,0 +536,51,25,132,94143,1,0.30,1,0,0,0,0,1,0 +537,25,-1,43,92173,3,2.40,2,176,0,0,0,1,0 +538,44,20,131,90717,1,4.90,3,0,1,0,0,1,0 +539,31,5,11,94534,1,0.40,2,76,0,0,0,0,1 +540,57,32,21,94720,1,0.30,3,117,0,0,0,0,0 +541,25,-1,109,94010,4,2.30,3,314,0,0,0,1,0 +542,30,6,141,95014,2,4.33,1,0,0,0,0,0,0 +543,40,14,81,94709,3,0.10,1,0,0,0,0,1,0 +544,63,38,54,94704,3,2.40,1,90,0,0,0,0,1 +545,35,10,164,91614,2,7.80,1,0,0,0,0,1,0 +546,43,19,28,94303,4,0.30,1,87,0,0,0,0,0 +547,27,2,68,94025,3,2.60,3,203,0,1,0,0,0 +548,44,14,44,94132,3,2.00,3,180,0,1,1,1,1 +549,49,23,61,94117,1,1.40,3,0,0,0,0,1,1 +550,61,36,35,94110,3,1.30,2,0,0,0,0,0,1 +551,60,34,54,94301,3,0.30,2,0,0,0,0,1,1 +552,59,34,14,93118,1,0.10,1,0,0,0,0,1,1 +553,28,3,52,90024,4,2.20,1,230,0,0,0,1,0 +554,52,28,101,91330,2,0.30,1,0,0,0,0,0,0 +555,28,2,149,94720,2,7.20,1,0,0,0,0,1,0 +556,34,8,35,92037,4,0.80,1,137,0,0,1,1,1 +557,60,34,21,93105,3,0.30,3,129,0,0,0,1,0 +558,39,15,118,95039,2,1.90,1,0,0,0,0,0,1 +559,30,5,38,95064,4,2.00,2,0,0,1,0,0,0 +560,49,25,24,95818,4,0.20,1,138,0,0,0,1,0 +561,43,18,59,93943,1,3.70,3,0,0,0,0,1,0 +562,63,33,41,94234,4,1.67,3,0,0,0,0,1,0 +563,28,3,85,94035,1,0.80,2,0,0,0,0,1,1 +564,51,27,12,94608,4,1.00,1,0,0,0,0,1,0 +565,33,7,32,94904,1,0.60,3,152,0,0,0,0,0 +566,55,29,79,90210,3,0.80,1,0,0,0,0,1,0 +567,53,28,175,95060,3,3.60,3,0,1,0,1,1,1 +568,34,8,28,95112,3,0.90,1,0,0,0,0,0,0 +569,34,9,41,92101,2,0.10,1,161,0,0,0,1,1 +570,40,14,70,95136,3,2.10,1,185,0,0,0,0,0 +571,49,25,161,94928,3,6.50,2,485,1,1,1,0,0 +572,35,9,53,94143,4,2.20,2,0,0,0,0,1,0 +573,39,15,128,92333,1,3.40,1,0,0,0,0,0,0 +574,55,28,50,95020,3,1.00,2,0,0,0,0,1,1 +575,29,5,80,94709,2,2.00,2,0,0,0,0,1,1 +576,54,30,93,91107,1,2.70,2,0,0,0,0,1,0 +577,25,-1,48,92870,3,0.30,3,0,0,0,0,0,1 +578,52,28,149,94043,2,6.80,1,0,0,0,0,1,0 +579,46,19,49,92124,3,2.50,2,0,0,0,0,1,1 +580,57,33,88,93524,1,2.70,2,0,0,0,0,1,0 +581,52,22,22,90049,4,0.40,3,0,0,0,0,1,1 +582,28,3,55,94521,4,2.20,1,0,0,0,0,1,1 +583,44,18,72,95678,1,0.70,3,155,0,0,0,0,0 +584,24,-1,38,95045,2,1.70,2,0,0,0,0,1,0 +585,40,16,114,91604,1,3.40,1,300,0,0,0,1,0 +586,34,4,83,92653,4,4.00,3,0,0,0,0,1,0 +587,39,14,101,94305,2,0.40,1,0,0,0,0,1,1 +588,50,24,94,93305,1,4.90,1,272,0,0,0,1,0 +589,41,17,40,93117,2,2.50,1,0,0,0,1,1,1 +590,31,7,128,92821,1,6.00,1,0,0,0,0,0,0 +591,29,3,39,94612,4,2.10,3,0,0,0,0,1,0 +592,30,5,51,92037,1,1.00,1,0,0,0,0,1,0 +593,44,20,79,95051,4,2.00,3,0,0,1,1,1,1 +594,33,7,48,90025,4,2.20,2,0,0,0,0,1,0 +595,50,26,85,94143,1,0.00,1,144,0,0,0,0,0 +596,42,18,41,92121,1,1.80,1,94,0,0,0,1,0 +597,48,22,152,94022,1,3.50,3,0,1,0,0,1,0 +598,24,-2,125,92835,2,7.20,1,0,0,1,0,0,1 +599,56,31,11,92374,2,0.20,3,90,0,0,0,0,0 +600,28,4,103,94720,2,2.50,1,0,0,0,0,1,1 +601,56,30,141,94143,2,0.50,1,0,0,0,0,1,0 +602,58,32,38,91320,1,1.40,1,0,0,0,0,1,1 +603,29,5,135,95035,2,0.60,1,0,0,0,0,0,0 +604,63,38,28,94720,2,0.50,2,89,0,0,0,1,0 +605,28,3,70,90245,4,2.20,1,240,0,0,0,0,1 +606,57,31,41,91330,1,0.20,1,0,0,0,0,1,1 +607,34,8,81,91741,3,0.90,2,208,0,0,0,1,0 +608,28,3,170,95014,1,0.10,3,0,1,0,0,0,0 +609,27,2,55,91910,4,1.70,2,0,0,0,0,1,0 +610,37,11,24,91770,4,1.50,3,0,0,0,0,0,0 +611,52,28,81,94132,3,1.80,2,275,0,0,0,0,0 +612,49,23,32,94701,4,1.80,1,83,0,0,0,0,0 +613,65,40,129,90095,1,1.30,1,0,0,0,0,1,1 +614,60,35,108,94904,1,0.90,1,0,0,1,0,0,0 +615,37,12,180,90034,1,8.60,1,0,0,0,0,1,1 +616,63,37,139,93943,2,6.90,1,0,0,0,0,0,0 +617,40,14,33,94025,2,1.40,3,0,0,0,0,1,1 +618,46,20,74,94024,4,2.60,3,0,0,0,0,1,0 +619,63,37,42,91320,2,0.70,3,115,0,0,0,1,0 +620,57,27,73,93106,1,3.00,3,0,0,0,0,0,0 +621,33,8,115,91129,4,2.90,2,0,1,0,0,1,0 +622,41,17,114,91125,2,1.80,2,0,0,0,0,1,0 +623,41,17,92,93555,2,1.90,1,131,0,0,0,1,0 +624,44,19,34,95616,1,0.30,3,78,0,0,0,1,0 +625,33,6,54,92821,2,1.67,2,122,0,0,0,1,0 +626,52,28,64,95605,2,1.00,3,211,0,0,0,1,0 +627,30,6,42,94305,1,0.20,3,100,0,0,0,0,1 +628,45,19,70,92677,3,2.10,1,0,0,0,0,1,0 +629,49,24,51,90071,1,1.30,2,0,0,0,0,0,0 +630,45,19,71,91711,4,2.90,1,218,0,0,1,1,1 +631,32,7,35,96651,3,1.30,1,108,0,0,0,0,1 +632,45,18,40,94960,3,1.00,2,0,0,0,0,1,0 +633,57,32,165,94720,4,2.70,3,0,1,0,0,1,0 +634,61,31,18,94583,1,1.50,3,0,0,0,0,1,1 +635,57,31,32,90034,3,1.40,1,0,0,1,1,1,1 +636,60,35,35,90509,3,0.20,1,169,0,0,0,1,0 +637,40,16,120,92037,2,6.10,1,196,0,0,0,1,0 +638,53,28,31,90245,4,0.10,3,0,0,0,0,1,0 +639,42,16,35,92054,3,1.50,1,0,0,0,0,0,0 +640,62,36,32,92646,2,0.20,3,0,0,0,0,1,1 +641,43,18,85,94960,1,3.70,3,327,0,1,0,1,0 +642,35,10,139,95060,2,7.80,1,0,0,0,0,0,0 +643,50,24,103,94132,1,0.30,1,0,0,0,0,1,0 +644,45,21,152,91902,2,1.40,1,0,0,0,0,1,0 +645,52,27,33,92121,2,2.00,2,0,0,0,0,1,0 +646,35,9,84,95120,4,2.20,2,322,0,0,0,0,0 +647,58,33,61,90033,4,1.70,1,0,0,0,0,0,0 +648,62,38,64,95064,4,2.20,1,123,0,1,1,1,1 +649,50,25,34,95621,1,1.30,2,0,0,0,0,1,0 +650,25,-1,82,92677,4,2.10,3,0,0,0,0,1,0 +651,47,22,122,90037,1,5.10,3,163,1,1,0,0,0 +652,28,4,58,92121,3,1.50,1,131,0,0,0,0,0 +653,34,9,92,90005,1,2.80,1,0,0,0,0,1,0 +654,49,23,78,92691,2,2.40,2,205,0,0,0,0,1 +655,54,29,129,93940,4,4.20,3,0,1,0,0,0,0 +656,50,25,13,91109,2,0.70,3,0,0,0,0,0,0 +657,37,11,81,94539,1,2.80,3,145,0,0,0,0,0 +658,38,8,23,95207,1,0.67,3,0,0,0,0,0,0 +659,52,26,35,91711,3,0.90,3,0,0,0,0,0,0 +660,63,39,79,93009,4,1.70,2,0,0,0,0,1,1 +661,39,14,165,92126,2,3.30,1,0,0,0,0,1,0 +662,63,38,52,94720,2,2.80,1,0,0,0,0,1,0 +663,65,41,185,93561,3,2.00,2,0,1,0,0,0,0 +664,46,20,49,90503,3,2.20,2,0,0,0,0,0,0 +665,54,30,64,95126,1,1.80,3,227,0,0,0,0,1 +666,54,24,61,92866,4,2.00,3,0,0,1,0,1,0 +667,52,26,112,92120,1,2.40,1,0,0,1,1,1,1 +668,63,39,72,93106,3,2.00,3,190,0,1,0,1,0 +669,66,41,18,94010,3,0.50,1,0,0,0,0,0,0 +670,56,29,41,94109,4,2.50,2,0,0,0,0,0,0 +671,23,-1,61,92374,4,2.60,1,239,0,0,0,1,0 +672,65,41,105,92612,1,3.00,2,282,1,1,1,1,0 +673,51,27,23,96651,1,0.20,1,0,0,0,0,1,0 +674,34,10,22,95670,1,0.50,3,85,0,0,0,0,0 +675,49,23,59,95827,3,2.10,1,0,0,0,0,0,0 +676,29,2,33,91711,1,2.00,2,160,0,0,0,0,0 +677,47,23,11,94063,1,0.90,3,103,0,0,0,0,1 +678,46,21,204,92780,2,2.80,1,0,0,0,0,1,0 +679,52,27,61,92101,4,1.80,3,207,0,0,0,0,0 +680,55,31,103,92093,3,1.80,2,364,0,0,0,0,0 +681,61,36,51,94706,3,1.50,1,0,0,0,0,0,1 +682,34,9,164,94720,1,6.00,3,0,1,0,0,1,0 +683,58,34,12,90504,1,0.10,2,0,0,0,0,0,1 +684,40,16,82,91311,1,3.60,2,0,0,0,0,0,0 +685,43,17,164,90266,1,2.40,1,449,0,0,0,1,0 +686,35,8,48,93107,2,1.67,2,0,0,0,0,1,0 +687,24,-1,38,92612,4,0.60,2,0,0,0,0,1,0 +688,48,22,65,92120,2,1.50,2,0,0,0,0,1,0 +689,44,20,71,94304,4,1.90,1,207,0,0,0,1,0 +690,54,30,18,94591,1,0.30,1,0,0,1,1,1,0 +691,59,34,52,94115,2,1.60,3,75,0,0,0,1,0 +692,45,18,48,90025,3,2.50,2,113,0,0,0,1,1 +693,26,2,30,94720,1,1.00,3,111,0,0,0,0,0 +694,40,15,40,92096,2,2.20,3,107,0,0,0,1,0 +695,32,7,112,90740,1,3.80,1,81,0,0,0,1,0 +696,29,4,115,92717,1,1.90,1,0,0,0,0,0,0 +697,51,27,63,92251,2,1.00,3,82,0,0,0,1,0 +698,42,17,85,92648,1,3.70,3,0,0,0,0,1,0 +699,64,38,59,92028,1,2.50,3,220,0,0,0,0,0 +700,44,20,68,95060,1,0.80,3,91,0,0,0,0,0 +701,37,11,84,90089,2,1.80,1,0,0,0,0,1,1 +702,44,19,62,93106,3,0.80,3,0,0,0,0,0,1 +703,35,9,109,92709,3,4.00,1,0,1,0,0,0,0 +704,41,17,141,94022,2,7.60,1,92,0,0,0,0,0 +705,56,32,129,94065,1,7.40,1,0,0,0,0,0,0 +706,62,36,30,94720,3,0.70,2,0,0,0,0,1,0 +707,58,34,148,95819,1,4.70,1,0,0,0,0,1,0 +708,47,20,25,95064,3,0.67,2,0,0,0,0,1,1 +709,35,10,21,92182,3,1.30,1,115,0,0,0,0,0 +710,29,4,72,95841,4,2.20,1,0,0,0,0,1,0 +711,43,17,59,94085,3,0.90,3,87,0,0,0,1,1 +712,62,37,83,91754,3,1.80,2,187,0,1,0,0,0 +713,41,16,10,94123,2,0.30,2,0,0,0,0,1,0 +714,34,9,84,92009,3,0.60,2,0,0,0,0,1,0 +715,50,23,98,92068,3,2.00,2,0,0,0,0,0,0 +716,47,23,32,92130,1,1.00,1,0,0,1,1,1,1 +717,29,5,31,96064,4,0.40,2,161,0,0,0,1,1 +718,59,34,94,93940,3,0.50,1,0,0,0,0,0,1 +719,56,31,21,90024,2,0.20,3,137,0,0,1,1,1 +720,61,35,110,92521,3,4.40,1,0,0,1,0,1,0 +721,58,32,38,94025,1,2.20,3,0,0,0,0,0,0 +722,49,24,39,92717,1,1.40,3,0,0,0,0,1,0 +723,45,21,132,91103,3,1.20,2,0,1,0,1,1,1 +724,50,24,61,94301,4,2.60,1,0,0,0,0,1,0 +725,64,38,92,94086,1,2.00,1,0,0,0,0,1,0 +726,39,15,119,92037,2,6.10,1,0,0,0,0,0,0 +727,58,33,53,91030,4,2.10,1,0,0,0,0,1,0 +728,62,37,18,92037,3,1.30,2,0,0,0,0,1,0 +729,45,20,114,94720,2,4.40,2,0,1,0,0,0,0 +730,58,28,90,93106,1,3.00,3,0,0,0,0,0,1 +731,43,18,140,95616,1,7.00,1,205,0,0,0,1,0 +732,28,3,90,90066,2,3.30,1,0,0,0,0,1,1 +733,26,1,85,90064,1,1.90,1,0,0,0,0,1,0 +734,49,24,80,92009,1,1.20,1,0,0,0,0,1,0 +735,66,42,53,92182,2,1.10,1,0,0,0,0,1,1 +736,33,7,49,95403,4,2.20,2,0,0,0,0,1,0 +737,61,35,152,91016,3,3.30,3,0,1,0,0,1,0 +738,64,37,138,94709,2,2.80,2,0,1,0,0,1,0 +739,36,10,80,94596,4,2.20,2,0,0,0,0,1,0 +740,49,23,82,91902,2,2.40,2,0,0,0,0,0,0 +741,52,27,195,90266,1,8.10,1,0,0,0,0,0,0 +742,61,37,22,94590,1,1.20,3,0,0,0,0,1,0 +743,32,6,81,92626,1,2.50,1,0,0,0,0,1,0 +744,61,37,40,94539,4,2.20,1,0,0,1,1,1,1 +745,45,20,154,94720,2,2.80,1,0,0,1,0,1,0 +746,30,4,49,93955,3,1.10,2,0,0,0,0,0,1 +747,62,37,85,95051,4,3.40,2,0,0,0,0,1,0 +748,57,32,21,94112,3,0.10,2,0,0,1,1,1,0 +749,41,17,14,91330,1,1.00,1,0,0,0,0,0,0 +750,58,34,60,92008,4,1.60,2,0,0,0,0,0,1 +751,29,5,138,93106,2,4.33,1,0,0,0,0,1,0 +752,53,28,98,90210,1,1.30,3,355,0,0,0,1,0 +753,64,39,22,90071,4,0.60,2,0,0,0,0,0,0 +754,49,23,49,94720,1,1.20,2,0,0,0,0,1,1 +755,38,14,102,95020,2,1.90,1,0,0,0,1,1,1 +756,56,30,45,91103,4,0.70,2,0,0,0,0,0,1 +757,56,31,82,95348,4,1.30,3,0,0,0,0,1,0 +758,52,28,81,91745,3,1.80,2,0,0,1,0,0,0 +759,64,39,35,90266,1,1.50,2,0,0,1,0,0,0 +760,53,28,59,91950,2,1.90,2,0,0,0,0,1,0 +761,29,3,52,92122,3,1.10,2,0,0,0,0,1,0 +762,48,24,84,92152,3,0.70,1,166,0,0,0,1,0 +763,32,6,85,90504,1,2.70,2,100,0,0,0,1,0 +764,54,28,65,94122,1,0.20,1,0,0,0,0,0,1 +765,37,13,89,95051,2,1.70,2,314,0,0,0,0,1 +766,47,21,109,95822,4,1.80,1,0,1,0,0,0,0 +767,37,12,81,94538,1,2.80,1,0,0,0,0,0,0 +768,64,39,38,92024,1,1.10,3,108,0,0,0,0,0 +769,43,19,72,90024,2,1.70,1,0,0,0,0,1,0 +770,33,6,78,90250,4,2.00,2,119,0,1,0,1,0 +771,26,2,172,94551,2,6.90,2,0,1,0,0,1,0 +772,42,18,71,91614,3,2.33,1,106,0,1,0,1,0 +773,54,28,165,92093,1,4.10,3,0,1,0,1,1,1 +774,41,16,120,92612,2,3.90,1,0,0,0,0,1,1 +775,55,29,39,92154,1,0.20,1,0,0,0,0,0,1 +776,65,39,23,92835,3,0.70,2,0,0,0,0,0,1 +777,50,26,135,92121,2,4.60,3,91,1,0,0,1,0 +778,55,31,12,95060,2,0.20,1,76,0,0,0,1,1 +779,62,36,92,94801,2,0.70,2,0,0,0,0,1,0 +780,53,28,192,94304,2,6.40,3,0,1,0,0,0,0 +781,32,7,42,92634,4,0.80,1,0,0,0,0,1,1 +782,56,32,158,94588,3,3.70,3,0,1,0,0,1,0 +783,54,30,194,92056,3,6.00,3,587,1,1,1,1,1 +784,44,20,160,94606,2,7.60,1,0,0,1,0,0,0 +785,48,22,98,94115,2,6.30,1,0,0,0,0,0,0 +786,46,22,164,94122,2,7.60,1,0,0,0,1,1,1 +787,45,21,42,94305,2,2.50,1,0,0,1,0,1,0 +788,45,15,202,91380,3,10.00,3,0,1,0,0,0,0 +789,58,34,10,92521,4,0.70,1,0,0,0,0,0,0 +790,29,3,31,92126,4,0.30,2,0,0,0,0,1,0 +791,55,30,58,92028,4,0.90,1,0,0,0,0,1,1 +792,55,29,65,94501,4,2.80,2,0,0,0,0,1,0 +793,41,16,98,93117,1,4.00,3,0,0,0,0,0,1 +794,24,-2,150,94720,2,2.00,1,0,0,0,0,1,0 +795,54,29,44,91301,2,2.30,3,0,0,0,0,1,0 +796,57,32,15,92806,2,0.20,3,0,0,0,0,0,1 +797,30,6,82,93657,2,2.50,1,0,0,0,0,0,0 +798,42,17,61,94998,3,0.50,3,0,0,0,0,1,0 +799,29,2,38,93063,1,2.00,2,0,0,0,0,0,0 +800,29,3,39,95051,4,2.10,3,0,0,0,0,1,0 +801,31,7,173,91040,1,6.00,1,0,0,0,0,1,0 +802,47,23,8,92612,4,0.20,1,0,0,0,0,1,0 +803,36,12,51,92521,3,2.00,1,214,0,0,0,1,0 +804,52,27,62,92661,4,1.80,3,82,0,0,0,0,0 +805,54,28,34,94061,4,0.70,2,0,0,0,0,1,0 +806,55,29,132,95758,3,5.90,2,307,1,0,0,0,0 +807,53,27,44,94542,4,1.50,3,0,0,0,0,0,0 +808,52,27,162,92096,1,8.10,1,0,0,0,0,1,0 +809,64,39,64,92068,3,2.20,1,0,0,0,0,1,0 +810,54,29,111,94304,1,0.10,3,0,0,0,0,0,1 +811,32,6,41,92182,2,2.00,3,0,0,0,0,0,0 +812,63,33,52,94720,4,1.67,3,0,0,0,0,0,0 +813,36,10,65,90089,4,2.20,2,0,0,0,0,0,0 +814,50,25,130,94720,1,1.10,2,0,1,0,0,1,0 +815,33,8,45,93943,2,0.10,1,0,0,0,0,0,1 +816,62,38,35,94596,1,1.90,2,118,0,0,0,0,0 +817,49,23,65,94035,3,0.70,2,263,0,0,0,1,1 +818,41,15,38,90291,2,0.70,1,91,0,0,0,1,0 +819,51,27,42,95039,4,1.10,2,0,0,0,0,1,1 +820,56,30,45,90024,4,1.50,3,0,0,0,0,0,0 +821,51,25,145,90740,1,0.30,1,0,0,0,0,1,0 +822,39,13,33,92093,4,1.50,3,0,0,0,0,0,0 +823,61,35,60,96091,3,1.40,3,0,0,0,0,0,0 +824,35,9,45,90509,1,2.00,1,0,0,0,0,1,1 +825,39,15,72,94801,4,2.40,1,0,0,1,0,1,0 +826,37,11,34,95616,3,0.20,2,0,0,0,0,0,0 +827,48,21,23,93555,3,0.67,2,0,0,0,0,1,0 +828,63,37,45,94542,2,1.00,3,88,0,0,0,1,1 +829,35,9,28,94542,4,1.00,1,75,0,0,0,1,0 +830,55,30,81,90254,4,3.80,2,0,0,0,0,1,0 +831,29,5,72,92407,3,0.70,2,81,0,0,0,0,0 +832,61,31,49,94066,4,1.67,3,0,0,0,0,1,0 +833,36,10,31,90630,4,1.20,2,0,0,0,0,0,0 +834,61,35,63,94939,3,2.20,3,0,0,0,0,0,0 +835,36,12,150,95138,4,5.40,1,0,1,1,1,1,0 +836,58,33,142,92691,2,3.90,1,193,0,0,0,1,1 +837,42,17,74,92123,3,3.00,1,0,0,0,0,0,1 +838,30,4,24,92096,1,0.40,2,81,0,0,0,1,0 +839,45,20,29,92507,4,1.90,3,0,0,0,0,0,0 +840,39,15,79,92646,4,2.40,1,0,0,0,0,0,0 +841,27,3,94,92373,2,0.20,1,310,0,0,0,0,1 +842,57,33,121,94542,1,4.30,1,0,0,1,0,0,0 +843,34,10,54,92101,3,2.00,1,0,0,0,0,0,0 +844,64,39,73,94720,3,2.40,1,0,0,0,0,1,0 +845,47,23,71,95762,1,0.80,3,127,0,0,0,1,0 +846,44,17,29,94706,3,1.00,2,0,0,0,0,1,1 +847,51,27,93,92154,1,2.70,1,0,0,0,0,1,0 +848,40,14,73,94539,1,1.50,3,252,0,0,0,1,0 +849,57,32,19,94720,4,0.90,2,0,0,0,0,1,0 +850,33,8,58,94305,2,0.10,1,0,0,1,1,1,1 +851,46,20,39,95054,1,0.20,1,0,0,0,0,0,0 +852,41,16,23,94521,2,1.40,2,0,0,1,0,1,0 +853,33,7,29,92064,1,0.60,3,127,0,0,0,0,1 +854,27,2,155,95138,1,0.80,1,0,0,0,0,0,0 +855,52,28,90,95814,1,2.60,2,0,0,1,0,1,0 +856,59,33,113,92152,2,2.00,1,77,0,0,0,1,0 +857,62,38,42,94025,1,1.80,3,0,0,0,0,0,0 +858,49,25,30,95616,4,0.20,1,0,0,0,1,1,1 +859,45,19,19,94720,3,0.50,2,0,0,0,0,1,0 +860,63,37,124,92182,3,5.00,2,170,1,0,0,0,0 +861,57,31,30,95841,2,0.70,2,145,0,0,0,0,0 +862,60,30,28,92354,1,1.50,3,124,0,1,0,1,0 +863,50,23,15,94025,2,1.00,2,101,0,0,0,0,0 +864,54,30,70,90095,1,1.60,3,265,0,0,0,0,0 +865,28,2,10,94080,1,0.10,2,0,0,0,0,1,0 +866,60,34,22,92037,3,0.30,3,139,0,0,0,1,1 +867,44,20,70,94611,4,1.90,1,0,0,0,0,1,0 +868,61,35,61,94708,1,1.60,1,0,0,0,0,0,0 +869,40,15,161,94596,2,3.30,1,0,0,1,0,0,1 +870,54,30,29,93014,2,0.80,1,0,0,0,0,0,1 +871,43,19,35,92106,3,0.50,1,0,0,0,0,1,0 +872,54,28,48,96091,4,2.80,2,0,0,0,0,1,0 +873,32,7,44,90095,4,0.80,1,0,0,0,0,1,0 +874,24,0,88,90740,3,0.80,1,134,0,0,0,0,0 +875,30,4,40,92056,4,2.10,3,0,0,0,0,1,1 +876,61,36,21,95616,4,0.40,2,123,0,0,0,0,0 +877,40,14,58,94025,2,2.80,1,0,0,0,0,1,0 +878,35,11,59,95123,4,0.10,2,0,0,0,0,0,0 +879,33,3,74,95616,4,4.00,3,0,0,0,0,0,0 +880,63,37,84,91768,4,1.90,2,0,0,0,0,1,0 +881,57,31,58,91604,1,0.20,1,177,0,0,0,1,0 +882,44,19,154,92116,2,8.80,1,0,0,0,0,1,0 +883,51,25,185,94117,1,1.70,1,0,0,0,0,0,0 +884,51,26,78,92703,1,1.20,1,305,0,0,0,1,0 +885,38,13,55,91709,2,1.10,2,0,0,0,0,1,0 +886,31,5,30,94304,4,0.30,2,0,0,0,0,1,0 +887,54,29,74,93907,3,2.00,2,0,0,0,0,0,0 +888,41,16,118,94720,2,3.30,1,0,0,0,0,1,0 +889,57,33,182,94114,2,3.30,3,372,1,0,0,0,0 +890,24,-2,82,91103,2,1.60,3,0,0,0,0,1,1 +891,55,29,29,92780,4,1.50,3,79,0,0,0,1,0 +892,32,6,120,94102,4,5.40,1,301,1,0,1,1,1 +893,38,12,53,95616,2,2.40,2,0,0,0,0,1,0 +894,58,32,43,93943,3,1.40,1,0,0,0,0,0,1 +895,29,4,59,95064,4,2.20,1,232,0,0,0,1,1 +896,43,17,84,94608,4,2.60,3,289,0,1,1,1,1 +897,50,24,161,95133,3,3.40,1,212,1,0,0,1,0 +898,62,37,21,92691,4,0.40,2,137,0,0,0,1,1 +899,57,32,63,94111,4,0.70,1,0,0,0,0,1,0 +900,30,3,172,91302,3,3.40,2,0,1,0,0,0,1 +901,30,4,51,94709,4,0.20,1,172,0,0,0,0,1 +902,57,33,24,95616,4,0.70,1,0,0,0,0,1,0 +903,57,33,95,95054,2,1.60,1,0,0,0,0,0,0 +904,43,18,59,90048,1,2.40,1,250,0,0,0,1,0 +905,28,2,51,90503,4,1.80,2,0,0,1,0,0,0 +906,46,22,28,94720,1,1.00,1,84,0,0,0,1,1 +907,29,3,154,94720,2,2.00,1,130,0,0,0,0,0 +908,64,40,15,91711,2,0.30,3,115,0,0,0,1,1 +909,66,36,55,93023,4,1.67,3,0,0,0,0,0,1 +910,23,-1,149,91709,1,6.33,1,305,0,0,0,0,1 +911,60,36,79,92120,1,1.80,3,0,0,0,0,0,1 +912,47,21,68,94538,4,2.60,3,0,0,0,0,0,0 +913,35,10,78,94105,1,2.60,2,0,0,0,0,1,0 +914,57,32,34,92507,2,2.00,2,0,0,1,0,0,0 +915,65,41,195,91711,3,0.40,1,0,1,1,1,0,1 +916,53,28,184,94550,1,8.10,1,303,0,0,0,1,0 +917,44,20,85,92192,2,3.20,1,0,0,0,0,1,0 +918,45,20,200,90405,2,8.80,1,0,0,0,0,1,1 +919,41,16,64,92325,3,0.50,3,0,0,0,0,0,0 +920,51,27,88,91116,1,2.60,2,0,0,1,0,0,1 +921,27,1,42,94501,3,2.40,2,0,0,0,0,0,0 +922,31,5,91,92096,3,1.60,1,126,0,0,0,1,1 +923,32,6,38,92868,1,0.30,1,0,0,1,1,1,0 +924,55,30,28,95123,1,1.50,2,0,0,0,0,0,0 +925,55,30,32,91330,4,0.10,3,0,0,1,0,0,0 +926,42,18,31,94720,1,0.30,3,0,0,0,0,0,1 +927,33,9,22,93940,4,0.40,2,103,0,0,0,1,0 +928,65,40,95,95014,3,3.70,2,138,1,0,0,0,1 +929,35,10,74,90638,4,1.30,1,0,0,0,0,1,0 +930,55,30,22,92121,1,1.50,2,91,0,0,0,0,1 +931,28,4,43,92103,3,0.10,2,0,0,0,0,1,0 +932,27,3,43,91302,1,1.00,3,0,0,0,0,1,0 +933,51,27,112,94720,3,1.80,2,0,0,1,1,1,1 +934,50,23,9,92064,2,1.00,2,0,0,0,0,1,0 +935,58,33,81,91320,2,0.00,3,0,0,0,0,1,0 +936,46,20,131,95929,1,5.70,1,256,0,0,0,0,1 +937,62,32,19,92109,1,1.50,3,0,0,1,0,0,0 +938,38,13,62,92093,3,0.70,2,0,0,1,0,1,0 +939,62,37,19,95818,4,0.40,2,124,0,1,0,0,0 +940,56,32,8,93943,2,0.30,1,0,0,0,0,1,1 +941,61,36,193,94303,1,4.70,3,203,1,0,0,1,0 +942,38,13,129,92093,4,4.40,1,140,1,0,0,0,0 +943,55,29,30,91320,4,0.70,2,0,0,0,0,0,1 +944,30,4,80,94701,4,1.80,2,0,0,0,0,0,0 +945,41,15,22,90503,4,1.50,3,0,0,0,0,0,1 +946,57,32,33,91745,1,1.50,2,0,0,0,0,1,0 +947,36,11,64,91355,4,2.10,3,0,0,0,0,0,0 +948,55,29,60,94305,3,2.20,3,84,0,0,0,1,0 +949,30,4,81,92037,1,2.90,3,259,0,0,0,1,1 +950,40,16,45,94720,3,0.60,2,204,0,0,0,1,0 +951,32,6,112,95054,4,1.80,2,0,0,0,0,1,0 +952,59,34,83,94105,2,3.40,3,0,1,0,0,1,0 +953,44,20,180,93943,2,7.60,1,524,0,0,0,0,1 +954,51,26,28,92130,4,0.20,2,0,0,1,0,1,0 +955,37,12,169,91107,2,5.20,3,249,1,0,0,1,0 +956,59,35,14,90840,4,0.70,1,0,0,0,0,1,0 +957,37,11,43,90250,1,2.00,1,0,0,0,0,1,0 +958,56,32,88,94309,2,0.30,1,0,0,0,0,1,0 +959,55,29,78,90747,4,2.60,3,0,0,0,0,0,1 +960,49,24,68,94143,1,0.20,2,163,0,0,0,0,0 +961,46,22,144,93611,2,3.30,1,0,0,0,0,1,1 +962,35,9,30,94114,4,1.00,1,163,0,0,0,1,0 +963,47,21,120,95833,1,0.00,1,135,0,0,0,0,0 +964,39,14,24,94305,2,0.30,2,0,0,0,0,0,0 +965,27,1,78,92037,4,2.30,3,157,0,1,0,1,0 +966,62,36,135,94301,2,5.20,2,0,1,0,0,1,0 +967,57,32,44,91605,2,1.60,3,0,0,0,0,0,0 +968,55,30,73,92675,4,3.80,2,0,0,0,0,1,0 +969,55,31,90,92868,1,2.70,2,0,0,0,0,1,1 +970,41,15,58,94704,3,0.50,3,0,0,0,0,1,0 +971,57,32,75,94928,2,3.70,1,236,0,0,0,1,0 +972,43,19,174,92028,3,1.70,3,231,1,0,1,1,1 +973,40,16,50,92093,2,1.70,1,174,0,0,0,0,0 +974,43,18,85,92703,1,4.00,3,287,0,0,0,1,0 +975,63,38,54,90401,3,2.20,1,0,0,0,0,1,0 +976,63,38,83,92122,2,3.40,1,0,1,0,0,0,0 +977,54,30,24,94109,4,0.20,1,0,0,1,0,0,0 +978,54,30,45,95134,4,1.10,2,205,0,0,0,1,0 +979,52,26,68,92068,1,0.80,3,0,0,0,0,1,1 +980,50,26,48,94720,4,0.10,3,0,0,0,0,0,1 +981,38,13,114,92697,1,1.00,3,0,0,0,0,1,1 +982,36,12,142,90064,3,2.30,2,0,1,0,1,1,1 +983,58,33,52,94402,3,0.50,2,0,0,0,0,0,1 +984,46,22,142,92220,2,3.30,1,0,0,0,0,0,0 +985,50,25,15,92173,1,0.40,3,0,0,0,0,0,0 +986,46,22,118,92120,1,4.70,1,159,0,0,0,0,1 +987,53,27,101,90245,4,4.90,1,0,0,0,0,1,0 +988,62,36,84,94609,2,2.80,1,0,0,0,0,1,0 +989,63,39,32,94998,1,1.90,2,100,0,0,0,0,0 +990,42,16,64,94607,3,0.50,3,247,0,0,0,0,0 +991,34,10,81,94002,4,3.40,1,0,0,0,0,1,0 +992,40,14,28,94025,4,1.50,3,0,0,0,0,0,1 +993,34,9,93,94608,1,0.00,1,0,0,0,0,1,0 +994,41,15,185,91775,1,3.60,2,0,1,0,0,0,0 +995,32,8,42,90650,1,1.80,2,0,0,0,0,0,0 +996,28,3,45,94305,2,1.60,3,0,0,0,0,1,1 +997,33,6,49,92037,2,1.67,2,214,0,0,0,0,0 +998,46,20,69,92780,3,2.10,1,0,0,0,0,0,0 +999,52,27,94,93106,1,2.80,2,333,0,0,0,1,0 +1000,60,35,18,92120,1,1.50,2,0,0,0,0,1,1 +1001,59,35,8,92691,4,0.70,1,91,0,1,0,0,0 +1002,57,32,55,90717,4,2.10,1,108,0,0,0,1,0 +1003,46,20,85,95617,2,0.40,3,0,0,0,0,0,0 +1004,25,1,62,94720,4,0.00,1,229,0,0,0,1,0 +1005,53,23,65,95054,4,2.00,3,0,0,0,0,1,0 +1006,38,12,138,95112,2,0.00,1,0,0,1,0,1,0 +1007,63,38,103,91103,1,2.50,1,0,0,0,0,1,0 +1008,44,19,99,95064,3,3.50,3,357,1,0,0,0,0 +1009,50,24,152,92220,1,7.30,1,0,0,0,0,1,0 +1010,28,3,25,91330,2,0.90,3,140,0,0,0,1,0 +1011,27,3,98,95616,2,2.50,1,361,0,1,1,1,1 +1012,52,27,39,94304,2,0.70,2,166,0,0,0,1,0 +1013,50,25,40,95820,1,1.30,2,0,0,0,0,1,1 +1014,39,13,58,94551,3,2.10,1,169,0,0,0,1,0 +1015,50,26,192,90245,2,1.80,3,301,1,0,1,1,1 +1016,60,34,62,94303,1,0.80,2,0,0,0,0,0,0 +1017,30,5,69,94720,1,0.80,2,0,0,1,0,1,0 +1018,31,5,40,94305,4,1.30,3,170,0,0,0,0,0 +1019,39,15,61,90018,2,0.60,3,127,0,0,0,0,0 +1020,29,3,30,91745,4,0.30,2,157,0,0,0,0,0 +1021,54,29,29,90071,1,1.50,2,97,0,0,0,1,0 +1022,35,8,41,92612,2,1.00,2,0,0,0,0,1,1 +1023,27,3,118,95605,1,3.30,2,0,1,0,0,1,0 +1024,45,20,109,94117,1,7.00,1,366,0,0,0,1,0 +1025,58,33,122,93711,4,0.20,2,0,1,0,1,1,0 +1026,62,37,50,94545,3,1.50,1,169,0,0,0,1,0 +1027,28,4,43,95616,3,0.10,2,0,0,0,0,1,0 +1028,32,7,108,94550,1,4.60,1,0,0,1,0,0,0 +1029,29,4,110,92096,4,2.50,3,0,1,0,0,0,0 +1030,41,17,20,94720,1,1.40,3,0,0,0,0,1,0 +1031,61,35,112,90024,4,1.70,3,0,0,0,0,0,1 +1032,56,32,25,95403,1,0.10,2,136,0,0,0,1,0 +1033,37,12,42,94720,3,0.70,2,0,0,0,0,1,1 +1034,60,34,29,95973,2,0.30,1,0,0,0,0,1,0 +1035,49,23,84,90095,3,2.10,1,134,0,1,0,1,0 +1036,43,17,81,94720,4,2.60,3,0,0,1,0,1,0 +1037,53,28,55,94720,4,0.90,1,119,0,0,0,1,1 +1038,35,11,40,93106,1,2.40,2,0,0,1,0,1,0 +1039,56,30,145,95831,4,5.70,2,0,1,0,1,1,1 +1040,41,16,175,94304,2,1.10,3,0,1,0,0,1,0 +1041,36,6,78,91107,4,1.80,3,163,0,0,0,0,0 +1042,56,32,51,92780,4,1.50,1,0,0,0,0,0,0 +1043,64,34,50,95616,4,1.67,3,0,0,0,0,1,0 +1044,51,27,21,95630,3,0.40,1,0,0,0,0,1,0 +1045,49,24,79,95827,1,0.20,2,83,0,0,0,1,1 +1046,43,18,84,92096,1,4.00,3,0,0,0,0,0,0 +1047,51,26,34,94105,4,0.40,2,0,0,0,0,0,0 +1048,55,31,73,94143,4,1.60,2,0,0,0,0,0,0 +1049,62,37,90,95747,3,0.50,1,0,0,0,0,1,0 +1050,35,10,23,94501,4,0.20,3,0,0,0,0,1,0 +1051,53,27,145,90095,2,6.10,3,294,1,0,1,1,1 +1052,33,7,54,92886,4,0.20,1,141,0,1,0,0,0 +1053,43,17,49,95812,3,2.20,2,103,0,0,0,1,1 +1054,58,32,51,95819,1,2.80,2,0,0,0,0,1,0 +1055,63,38,8,95136,4,0.60,2,0,0,0,0,1,0 +1056,31,6,62,95630,1,1.00,1,0,0,1,0,1,0 +1057,36,6,25,95020,1,0.67,3,0,0,0,0,1,0 +1058,30,0,63,95503,2,1.75,3,0,0,0,0,1,0 +1059,59,34,24,94105,2,0.20,3,86,0,0,0,1,0 +1060,28,2,11,91203,1,0.10,2,0,0,0,0,1,1 +1061,59,34,23,93111,1,0.10,1,0,0,0,0,0,1 +1062,47,22,33,91105,1,1.40,3,0,0,0,0,1,0 +1063,47,21,83,92220,1,3.80,1,97,1,0,0,0,0 +1064,56,30,39,90024,3,1.40,1,131,0,0,0,0,1 +1065,41,17,138,95008,3,6.90,2,0,1,0,0,1,0 +1066,25,1,113,90401,3,2.50,1,0,0,0,0,0,1 +1067,30,5,125,90016,4,0.50,3,0,1,0,1,1,0 +1068,50,24,195,95035,1,1.70,1,0,0,0,0,0,0 +1069,34,9,105,90035,3,1.20,3,0,0,1,0,0,0 +1070,44,18,75,91203,2,3.50,1,0,1,0,0,1,0 +1071,36,9,40,90840,2,1.00,2,0,0,0,0,1,0 +1072,39,14,61,94005,3,0.50,3,137,0,0,0,1,0 +1073,54,24,75,90089,2,4.50,3,0,0,0,0,0,0 +1074,33,8,122,94583,1,0.00,1,0,0,0,0,1,1 +1075,39,14,75,95762,3,3.00,1,0,0,0,0,0,1 +1076,41,15,59,90024,4,0.20,3,0,0,0,0,0,0 +1077,40,13,24,94608,3,1.00,2,0,0,0,0,1,0 +1078,29,3,175,90095,3,3.30,3,329,1,0,0,1,0 +1079,51,27,39,92709,2,0.80,1,182,0,0,0,0,1 +1080,54,30,145,94591,2,6.80,1,0,0,1,0,0,0 +1081,47,22,24,90717,4,0.40,2,142,0,0,0,1,0 +1082,53,28,20,94080,3,0.10,2,0,0,0,0,0,0 +1083,30,5,85,94115,1,2.60,2,0,0,0,0,1,0 +1084,28,3,65,95014,3,2.60,3,0,0,1,0,0,0 +1085,60,35,191,93407,4,5.60,3,0,1,0,0,0,0 +1086,51,26,11,92612,2,0.00,1,0,0,1,0,0,0 +1087,63,37,40,94024,2,1.00,3,167,0,0,0,0,0 +1088,38,13,54,92028,3,0.70,2,196,0,0,0,0,0 +1089,59,35,95,95521,1,3.80,1,0,0,0,0,1,1 +1090,53,29,94,92103,4,1.00,2,0,0,0,0,1,0 +1091,31,5,79,94720,4,2.20,2,0,0,0,0,0,0 +1092,41,17,48,94720,3,0.30,3,0,0,0,0,1,1 +1093,25,1,70,92120,4,2.60,1,0,0,1,0,1,0 +1094,27,3,40,94550,3,0.10,2,111,0,0,0,1,0 +1095,50,24,44,94086,4,1.80,1,0,0,0,0,1,1 +1096,50,25,43,92129,1,1.40,3,137,0,0,0,1,0 +1097,43,18,29,90245,1,0.30,3,0,0,0,0,1,0 +1098,50,24,188,92007,3,1.30,1,184,1,0,0,0,1 +1099,46,20,114,90720,1,0.00,1,0,0,0,0,1,1 +1100,30,6,52,92717,3,0.70,2,0,0,0,0,1,0 +1101,42,16,13,91711,1,0.20,1,0,0,0,0,1,0 +1102,42,17,95,90095,3,0.50,3,0,0,0,0,0,0 +1103,29,3,84,95023,1,2.90,3,0,0,0,0,1,0 +1104,38,14,49,90037,1,1.80,1,0,0,0,0,0,0 +1105,51,25,181,93106,1,1.70,1,0,0,0,0,1,1 +1106,35,10,182,95051,1,0.30,2,229,1,0,1,1,1 +1107,37,13,70,92101,2,2.70,1,0,0,0,0,0,0 +1108,47,21,79,94110,3,1.10,1,185,0,0,0,1,1 +1109,55,29,61,95051,4,2.80,2,0,0,0,0,1,1 +1110,65,41,121,92126,2,2.10,1,0,0,0,0,1,0 +1111,58,33,34,92028,3,0.20,1,83,0,0,0,1,0 +1112,54,28,183,90071,1,1.00,1,442,0,0,0,0,0 +1113,52,28,51,94949,1,1.60,3,0,0,1,0,0,1 +1114,28,2,70,90630,3,0.30,3,0,0,0,0,0,1 +1115,32,8,39,95827,1,1.70,1,0,0,0,0,1,1 +1116,51,24,84,94117,3,2.00,2,0,0,0,0,0,0 +1117,43,18,122,92056,1,7.00,1,0,0,0,0,1,1 +1118,42,18,145,94709,1,1.70,1,132,0,0,0,1,1 +1119,42,17,98,95670,2,0.40,1,0,0,0,0,1,1 +1120,41,16,79,96064,1,1.00,3,233,0,0,0,1,0 +1121,34,8,38,94304,2,2.00,3,0,0,0,0,1,1 +1122,30,6,49,91330,3,0.70,2,196,0,0,0,0,1 +1123,32,7,38,90041,1,1.00,1,0,0,0,0,1,0 +1124,46,20,91,92521,4,2.60,3,0,0,0,0,0,0 +1125,38,12,29,94022,4,0.20,1,0,0,0,0,0,1 +1126,37,13,172,95003,2,6.50,1,0,0,0,0,0,0 +1127,32,8,104,95192,2,3.70,1,0,1,0,0,0,1 +1128,35,9,58,91101,1,2.50,1,0,0,0,0,1,1 +1129,30,5,171,94025,2,1.90,2,0,1,0,0,0,0 +1130,30,4,73,94305,3,3.30,1,0,1,0,1,1,1 +1131,58,32,191,94402,1,2.90,1,0,0,0,0,0,0 +1132,57,27,90,91709,2,4.50,3,0,0,0,0,1,0 +1133,34,9,55,94920,3,2.30,1,0,0,1,1,1,1 +1134,31,4,28,94126,1,2.00,2,0,0,0,0,0,0 +1135,39,14,42,95616,1,2.50,3,0,0,0,0,1,0 +1136,57,33,9,93106,1,0.10,2,91,0,1,0,1,0 +1137,47,21,65,94086,1,1.50,2,0,0,1,0,1,0 +1138,51,26,134,90230,4,4.50,3,0,1,1,1,1,0 +1139,30,6,83,93101,4,3.40,1,0,0,1,0,1,0 +1140,55,28,38,95616,3,1.00,2,0,0,0,0,1,0 +1141,32,6,13,94611,4,0.30,1,0,0,0,0,1,1 +1142,32,7,143,91365,3,2.90,3,0,1,0,0,1,0 +1143,44,20,75,91335,4,1.90,1,0,0,0,0,0,0 +1144,33,7,120,94022,1,3.20,3,0,1,0,0,1,0 +1145,49,24,91,95822,1,2.80,2,0,0,0,0,0,0 +1146,32,6,99,92101,2,1.50,3,0,0,0,0,0,1 +1147,31,7,71,90034,1,0.10,1,78,0,1,0,0,0 +1148,37,13,111,91367,1,0.80,2,0,0,0,0,0,0 +1149,41,15,108,90034,1,5.20,1,0,0,0,0,0,0 +1150,56,32,158,91763,1,7.40,1,0,0,0,0,0,0 +1151,55,31,81,95521,3,2.67,1,0,0,0,0,1,0 +1152,49,23,12,94720,2,0.10,3,0,0,1,1,1,0 +1153,63,37,21,95831,2,0.40,1,0,0,0,0,1,0 +1154,55,30,55,92821,4,0.90,1,215,0,0,0,1,1 +1155,59,35,42,93555,1,1.80,3,0,0,0,0,1,0 +1156,41,16,81,92653,2,0.40,1,0,0,0,0,0,1 +1157,49,25,13,94305,4,0.20,1,87,0,0,0,0,0 +1158,48,23,132,94998,1,0.60,1,157,0,0,0,0,0 +1159,41,16,99,92660,1,1.00,3,0,0,0,0,1,0 +1160,50,26,23,92028,4,0.20,1,0,0,0,0,0,1 +1161,28,1,40,95134,1,2.00,2,0,0,1,0,1,0 +1162,36,11,181,94309,3,1.40,1,0,1,0,0,0,0 +1163,38,14,112,94501,2,2.20,1,394,0,0,0,0,0 +1164,34,9,138,94720,2,7.80,1,227,0,0,0,1,0 +1165,41,17,94,90071,3,3.80,2,327,1,1,1,1,0 +1166,43,19,113,91203,1,1.70,1,0,0,0,0,0,0 +1167,30,5,112,91711,4,5.00,2,0,1,0,0,0,1 +1168,37,12,190,92354,2,3.00,1,475,0,0,0,1,0 +1169,62,37,38,91706,1,1.10,3,0,0,0,0,1,0 +1170,40,16,32,92110,1,1.40,3,158,0,0,0,1,0 +1171,35,10,104,91320,3,0.60,2,0,0,0,0,0,1 +1172,64,40,43,95014,1,1.90,2,0,0,0,0,1,0 +1173,49,24,45,92104,3,1.70,2,0,0,1,0,1,0 +1174,24,-1,35,94305,2,1.70,2,0,0,0,0,0,0 +1175,36,10,42,93106,4,1.20,2,0,0,0,0,1,1 +1176,29,4,58,91006,1,0.80,2,0,0,0,0,1,1 +1177,29,3,103,90049,4,3.40,1,0,1,0,0,1,0 +1178,28,3,71,90405,1,3.30,2,149,1,1,1,1,0 +1179,33,7,14,94025,1,0.40,2,98,0,0,0,1,0 +1180,36,11,98,90291,3,1.20,3,0,0,1,0,0,1 +1181,42,17,90,90504,1,0.10,2,0,0,0,0,0,1 +1182,25,0,65,90095,4,0.20,1,0,0,1,0,0,0 +1183,28,2,19,94720,4,0.40,1,0,0,0,0,1,1 +1184,50,25,35,94105,3,1.70,2,0,0,0,0,1,1 +1185,34,9,71,90041,4,1.30,1,0,0,0,0,1,0 +1186,43,19,31,94025,3,0.50,1,0,0,0,0,0,0 +1187,62,38,43,94928,4,1.20,2,0,0,0,0,1,0 +1188,61,36,24,94309,1,1.50,2,87,0,1,0,0,0 +1189,45,19,58,94305,2,0.40,3,0,0,1,0,0,1 +1190,42,17,115,92717,2,0.40,1,0,0,0,0,1,0 +1191,39,15,168,93117,2,8.00,1,152,0,1,0,0,0 +1192,29,5,128,94111,1,1.50,1,0,0,0,0,1,1 +1193,45,20,138,92870,1,7.00,1,0,0,0,0,0,1 +1194,58,32,81,92121,3,1.70,2,0,0,0,0,1,1 +1195,29,3,41,94305,4,1.30,3,0,0,0,0,1,0 +1196,32,7,123,92407,2,2.90,2,0,1,0,0,1,0 +1197,37,13,71,94609,2,2.70,1,94,0,0,0,1,0 +1198,48,23,8,92866,1,0.40,3,0,0,0,0,0,1 +1199,40,14,42,94801,2,0.70,1,101,0,0,0,1,0 +1200,29,4,62,92064,2,2.50,1,184,0,0,0,1,0 +1201,36,12,22,92507,4,1.00,1,91,0,1,0,1,0 +1202,35,8,38,95060,4,1.00,2,0,0,0,0,1,0 +1203,35,11,24,95521,4,0.40,2,0,0,0,0,0,0 +1204,62,37,50,91311,3,2.40,1,0,0,0,0,1,0 +1205,26,1,190,91604,4,1.30,2,197,1,0,0,1,0 +1206,32,7,94,91361,2,3.10,1,0,0,0,0,1,0 +1207,63,37,165,95035,4,5.10,3,0,1,0,0,0,0 +1208,38,12,43,94301,4,1.20,2,0,0,0,0,0,1 +1209,50,26,48,91711,1,1.60,2,0,0,0,0,0,1 +1210,46,21,52,91304,3,2.70,2,228,0,0,0,0,1 +1211,50,24,84,93943,4,4.90,1,0,0,0,0,1,0 +1212,61,36,131,92407,1,0.90,1,0,0,0,0,1,0 +1213,34,8,44,91101,4,0.20,1,0,0,0,0,0,0 +1214,27,2,78,93943,4,0.20,1,87,0,0,0,0,0 +1215,61,36,15,92521,4,0.40,2,0,0,0,0,0,0 +1216,45,20,38,94550,4,1.90,3,144,0,0,0,1,1 +1217,50,25,84,91107,1,1.30,3,0,0,1,0,1,0 +1218,44,20,122,94305,1,0.30,1,0,0,0,0,1,0 +1219,62,36,98,92122,2,2.80,1,0,0,0,0,0,0 +1220,45,18,80,92407,3,2.67,2,0,0,0,0,0,0 +1221,41,17,165,94143,2,8.00,1,0,0,0,0,1,0 +1222,30,5,121,94132,2,3.30,1,0,0,0,0,0,1 +1223,61,37,20,90011,3,0.40,2,94,0,0,0,0,0 +1224,45,19,11,96150,1,0.20,1,91,0,0,0,0,0 +1225,59,35,45,94920,1,1.80,3,0,0,0,0,1,0 +1226,30,6,118,94534,2,2.80,2,0,1,0,0,0,0 +1227,60,36,14,90089,2,0.30,1,109,0,0,0,1,1 +1228,39,13,30,92122,3,0.20,2,0,0,0,0,0,0 +1229,56,30,45,92870,1,0.20,1,98,0,0,0,0,0 +1230,56,32,80,94596,3,2.67,1,0,0,0,0,1,0 +1231,27,1,25,94920,4,0.30,2,0,0,0,0,1,1 +1232,66,41,144,94306,1,2.50,1,0,0,1,1,1,1 +1233,43,19,84,92646,4,0.20,3,297,0,0,0,1,0 +1234,53,29,22,93943,2,0.40,1,0,0,0,0,1,0 +1235,44,18,33,90405,3,1.50,1,0,0,0,0,1,1 +1236,54,28,60,94110,4,2.60,3,0,0,0,0,0,0 +1237,31,6,81,95762,4,2.20,2,116,0,0,0,1,0 +1238,38,13,169,92093,1,6.80,3,0,1,0,1,1,1 +1239,28,2,63,91116,2,1.60,3,0,0,0,0,1,0 +1240,51,26,12,90245,2,0.70,3,109,0,0,0,1,1 +1241,52,27,15,91320,4,0.80,1,101,0,0,0,0,0 +1242,64,38,39,92120,1,0.50,3,0,0,1,1,1,1 +1243,29,4,44,91380,4,2.00,2,0,0,0,0,1,0 +1244,34,10,110,92697,1,4.00,1,0,0,0,0,1,0 +1245,33,8,130,94720,3,6.30,2,99,1,0,0,0,1 +1246,46,21,41,94025,1,1.40,3,128,0,0,0,1,0 +1247,48,22,59,91775,1,1.40,3,241,0,0,0,1,0 +1248,52,28,39,94606,2,0.80,1,0,0,0,0,1,0 +1249,44,19,35,94305,4,0.00,2,0,0,0,0,1,0 +1250,51,27,80,90032,1,2.60,2,0,0,0,0,1,1 +1251,47,20,81,94301,1,2.67,2,0,0,0,0,1,0 +1252,39,13,31,95120,2,0.80,3,0,0,0,0,0,0 +1253,42,17,93,92182,4,1.90,3,0,0,0,0,0,0 +1254,57,33,45,92346,4,1.50,1,204,0,0,0,1,0 +1255,36,12,40,91101,2,0.60,3,0,0,0,0,1,1 +1256,27,1,80,95354,2,1.60,3,185,0,0,0,1,1 +1257,31,7,20,92115,1,0.40,3,0,0,0,0,1,0 +1258,63,37,41,93014,1,0.50,3,0,0,0,0,0,1 +1259,34,8,31,91203,1,0.30,1,104,0,0,0,1,1 +1260,52,27,35,95616,4,0.20,2,0,0,0,0,1,0 +1261,57,31,40,91107,3,1.40,3,137,0,0,0,1,1 +1262,63,39,84,94901,1,1.80,3,0,0,0,0,0,0 +1263,26,1,53,94720,2,1.60,3,0,0,0,0,1,0 +1264,35,5,85,92870,4,4.00,3,0,0,0,0,1,0 +1265,58,33,138,94546,2,3.90,1,0,0,0,0,1,0 +1266,32,2,71,95014,2,1.75,3,108,0,0,0,0,0 +1267,64,39,113,92121,1,0.80,3,0,0,0,0,0,1 +1268,50,23,23,94720,2,1.00,2,0,0,1,0,0,0 +1269,34,9,62,92677,3,2.30,1,0,0,0,0,0,0 +1270,36,11,14,92673,4,0.20,3,100,0,0,0,1,1 +1271,43,18,60,91311,2,2.20,3,0,0,0,0,0,1 +1272,28,4,94,92115,3,0.80,1,236,0,0,0,1,0 +1273,64,39,83,95616,3,1.80,2,0,0,0,0,1,0 +1274,60,35,130,95741,3,6.30,3,437,1,0,1,1,1 +1275,62,37,61,93117,4,1.70,1,0,0,0,0,0,0 +1276,27,2,92,95616,2,3.10,1,178,0,0,0,1,0 +1277,42,16,20,95351,2,0.80,3,117,0,0,0,1,1 +1278,45,20,194,92110,2,8.80,1,428,0,0,0,0,0 +1279,36,10,74,94305,1,2.50,1,0,0,0,0,0,1 +1280,48,22,84,90024,2,0.40,3,145,0,0,0,0,0 +1281,65,40,98,95064,3,1.80,2,333,0,0,0,0,0 +1282,39,15,52,92093,3,2.33,1,0,0,0,0,1,0 +1283,51,26,55,93955,1,1.30,2,236,0,0,0,0,1 +1284,30,6,64,94305,4,3.40,1,117,0,0,0,0,0 +1285,65,40,128,90740,1,2.50,1,162,0,0,0,1,0 +1286,38,13,113,94720,4,1.70,2,0,1,0,0,0,1 +1287,29,3,50,94010,3,1.10,2,0,0,0,0,0,1 +1288,42,18,54,94010,4,2.20,2,0,0,0,0,0,0 +1289,63,38,129,91326,1,0.90,1,366,0,0,0,1,0 +1290,46,21,82,94523,4,0.40,1,0,0,0,0,0,0 +1291,62,38,100,90277,4,1.70,2,0,0,0,0,1,0 +1292,58,34,44,94111,4,2.20,1,0,0,1,0,0,0 +1293,56,30,164,94610,4,0.50,2,234,1,0,1,1,1 +1294,56,31,81,92373,2,3.70,1,121,0,0,0,1,1 +1295,34,10,71,95003,1,0.10,1,257,0,0,0,1,1 +1296,42,17,28,92866,1,0.50,3,90,0,0,0,0,0 +1297,30,6,80,92399,3,1.50,1,219,0,0,0,1,0 +1298,61,35,90,95814,4,1.90,2,0,0,0,0,1,0 +1299,38,14,74,90274,1,3.60,2,0,0,0,0,1,1 +1300,50,25,14,95762,2,0.70,3,0,0,1,0,1,0 +1301,61,36,23,91754,2,0.50,2,103,0,0,0,1,0 +1302,41,17,153,92121,1,1.70,1,337,0,0,0,0,1 +1303,42,16,38,94087,3,0.90,3,0,0,0,0,0,0 +1304,29,5,112,94720,2,2.00,2,382,0,1,0,0,0 +1305,51,26,145,90025,1,8.10,1,397,0,0,0,0,1 +1306,32,6,28,94025,2,0.30,2,88,0,0,0,1,0 +1307,34,9,31,94115,4,1.10,3,0,0,0,0,1,1 +1308,26,2,195,94546,1,6.33,1,0,0,0,0,1,1 +1309,54,24,50,92037,3,2.00,3,0,0,0,0,1,1 +1310,38,14,71,95136,4,2.00,3,0,0,0,0,0,0 +1311,62,36,21,95616,3,0.30,3,0,0,0,0,0,0 +1312,37,11,35,90044,2,0.80,3,125,0,0,0,0,0 +1313,46,21,42,92691,1,2.40,1,0,0,0,0,1,1 +1314,52,27,78,92008,4,3.60,3,141,0,0,0,1,0 +1315,32,6,73,94305,4,2.20,2,0,0,0,0,0,0 +1316,49,25,53,95134,2,1.00,3,181,0,0,0,0,0 +1317,28,3,51,94086,2,1.60,3,123,0,0,0,0,0 +1318,55,30,40,95521,2,2.30,3,0,0,0,0,1,0 +1319,52,26,178,94234,1,1.00,1,0,0,0,0,0,0 +1320,32,6,35,94005,2,0.30,1,0,0,0,0,0,1 +1321,31,7,192,90250,1,0.00,2,0,1,0,0,1,0 +1322,27,3,123,95138,1,5.40,1,0,0,0,0,0,0 +1323,32,5,48,94022,2,1.67,2,0,0,1,1,1,1 +1324,52,26,45,91604,3,0.60,2,0,0,0,0,0,0 +1325,52,28,15,95064,1,0.20,1,0,0,0,0,1,0 +1326,50,24,79,94304,1,0.30,1,120,0,0,0,1,0 +1327,32,5,63,90024,4,2.00,2,0,0,1,0,1,0 +1328,61,35,30,94720,2,0.20,3,0,0,0,0,1,0 +1329,60,36,145,95616,4,6.90,1,380,1,0,0,0,1 +1330,28,4,32,90095,3,1.00,2,0,0,0,0,0,0 +1331,34,9,64,92346,2,0.10,1,224,0,0,0,1,1 +1332,31,7,84,92692,1,0.10,1,0,0,0,0,1,0 +1333,31,5,21,94309,1,0.40,2,0,0,0,0,1,0 +1334,62,38,99,95014,4,1.70,2,0,0,0,0,1,0 +1335,47,22,35,94304,2,1.30,1,0,0,0,0,1,0 +1336,50,24,180,94539,1,1.70,1,0,0,0,0,1,1 +1337,36,12,42,93555,1,1.33,1,0,0,0,0,1,0 +1338,26,0,179,92028,4,2.10,2,0,1,0,0,0,0 +1339,51,27,42,90245,4,0.10,3,0,0,0,0,0,0 +1340,52,25,180,94545,2,9.00,2,297,1,0,0,1,0 +1341,35,11,82,94131,4,3.40,1,0,0,0,0,0,0 +1342,42,16,55,91355,2,0.70,1,149,0,0,0,0,0 +1343,36,12,79,90041,2,2.20,1,0,0,0,0,1,0 +1344,41,17,48,92831,2,0.60,3,215,0,0,0,0,1 +1345,49,25,93,93117,1,2.70,1,0,0,1,0,1,0 +1346,57,32,23,92126,2,0.20,3,0,0,0,0,0,0 +1347,44,20,50,95670,3,2.33,1,200,0,0,0,0,0 +1348,60,34,85,91367,2,2.00,1,0,0,0,0,1,0 +1349,38,14,35,95051,1,1.50,2,97,0,0,0,1,0 +1350,26,2,171,93943,3,6.00,2,0,1,0,0,1,0 +1351,29,2,29,90266,4,1.50,2,0,0,0,0,0,1 +1352,59,35,84,94588,1,1.80,3,0,0,0,0,1,1 +1353,51,27,20,90401,4,0.50,2,0,0,0,0,1,0 +1354,50,25,14,94124,1,0.40,3,0,0,0,0,1,1 +1355,35,10,179,91942,1,8.60,1,357,0,0,0,0,0 +1356,61,37,48,91910,1,0.80,1,158,0,0,0,1,0 +1357,42,16,74,90066,1,2.80,1,0,0,0,0,1,0 +1358,55,29,53,95134,1,1.40,1,0,0,0,0,0,0 +1359,50,25,83,92007,1,2.80,2,0,0,0,0,1,1 +1360,64,40,171,90034,2,2.10,1,433,0,0,0,0,0 +1361,54,28,85,92028,4,4.90,1,0,0,0,0,1,0 +1362,50,26,38,95039,4,0.90,2,0,0,0,0,1,0 +1363,31,5,85,92130,3,1.60,1,157,0,0,0,1,1 +1364,32,8,79,92115,1,0.10,1,0,0,0,0,0,0 +1365,44,19,69,92129,4,0.40,1,0,0,0,0,0,0 +1366,60,35,43,94720,3,0.90,3,0,0,0,0,1,1 +1367,60,34,33,91107,2,0.30,1,101,0,0,0,1,0 +1368,62,38,42,95747,3,0.10,3,149,0,0,0,0,1 +1369,46,21,40,94025,4,1.90,3,122,0,0,0,1,0 +1370,57,33,43,91902,1,1.80,3,0,0,0,0,0,0 +1371,30,5,20,94545,4,0.50,3,117,0,0,0,0,0 +1372,58,32,65,95621,3,2.50,1,222,0,0,0,1,0 +1373,39,13,139,95616,3,3.40,1,483,1,0,0,1,0 +1374,60,35,135,92612,3,0.30,3,0,1,0,0,1,0 +1375,59,34,84,94043,3,1.60,3,0,0,0,0,1,0 +1376,50,26,179,92612,1,2.90,3,0,1,0,0,0,1 +1377,63,39,45,92870,4,1.30,2,86,0,0,0,0,0 +1378,27,3,109,93023,2,2.50,1,0,0,0,0,1,0 +1379,54,29,34,93305,4,0.10,3,0,0,0,0,1,0 +1380,62,37,162,95051,1,1.30,1,0,0,0,0,1,0 +1381,60,34,105,92103,2,1.40,1,0,0,0,0,1,0 +1382,38,12,22,91380,3,0.20,2,0,0,0,0,1,0 +1383,34,8,82,91775,2,1.80,1,178,0,0,0,1,1 +1384,65,41,105,95616,4,1.70,2,230,0,1,0,1,0 +1385,55,31,62,91711,1,1.80,3,0,0,0,0,1,0 +1386,57,31,82,95032,2,2.00,1,83,0,0,0,0,1 +1387,27,3,72,95616,4,0.00,1,0,0,0,0,1,0 +1388,35,10,38,95762,4,1.70,1,0,0,0,0,1,1 +1389,52,28,25,90212,4,1.00,1,0,0,0,0,0,0 +1390,45,15,20,94107,1,0.75,3,0,0,0,0,1,0 +1391,29,3,80,94305,4,1.80,2,0,0,0,0,1,1 +1392,44,18,84,91330,3,1.10,1,0,0,0,0,0,0 +1393,47,23,33,90095,1,1.00,1,0,0,0,0,1,1 +1394,62,37,55,95039,3,0.90,3,0,0,0,0,1,0 +1395,52,27,33,90095,2,0.70,2,0,0,0,0,0,1 +1396,47,23,190,92831,4,0.30,3,305,1,0,0,0,0 +1397,42,18,43,91107,1,0.30,3,158,0,0,0,0,0 +1398,65,41,45,95521,3,0.10,3,0,0,0,0,1,0 +1399,42,18,141,93407,1,3.50,1,0,0,0,0,0,0 +1400,40,16,69,92009,4,2.40,1,0,0,0,0,1,0 +1401,32,8,78,90401,4,0.10,2,0,0,0,0,1,0 +1402,40,15,84,94521,1,3.70,3,0,0,0,0,1,0 +1403,55,29,172,95064,1,5.20,2,0,1,0,0,0,0 +1404,32,6,51,93109,4,0.20,1,154,0,1,0,0,1 +1405,58,28,75,92121,1,1.40,3,0,0,0,0,1,0 +1406,46,22,183,91605,1,3.10,2,0,1,0,1,1,1 +1407,53,23,20,92123,4,0.40,3,0,0,0,0,1,1 +1408,63,39,101,94306,2,3.90,3,294,1,0,0,1,0 +1409,40,14,129,90089,1,5.90,3,0,1,0,0,1,0 +1410,41,17,63,90745,2,3.20,1,0,0,0,0,0,0 +1411,60,35,44,92126,4,2.10,1,0,0,0,0,0,0 +1412,65,39,184,91302,1,5.40,3,176,1,0,1,1,1 +1413,59,33,100,95064,2,2.00,1,127,0,0,0,0,0 +1414,48,24,12,90058,3,0.40,1,0,0,0,0,0,0 +1415,59,33,68,94105,2,2.30,3,128,0,1,0,1,0 +1416,33,8,48,94019,1,1.00,1,212,0,0,0,1,0 +1417,40,15,82,93101,2,0.40,1,0,0,0,0,0,0 +1418,42,18,52,94061,2,2.50,1,0,0,0,0,0,0 +1419,65,41,154,92008,2,4.60,2,0,1,1,1,1,1 +1420,30,4,39,91105,1,1.50,1,0,0,0,0,0,1 +1421,30,4,40,91605,1,0.30,1,0,0,0,1,1,1 +1422,42,17,54,94720,4,1.90,3,164,0,0,0,0,0 +1423,32,8,32,94143,2,1.00,2,103,0,0,1,1,1 +1424,55,30,64,90250,2,2.30,3,0,0,0,0,0,0 +1425,29,3,92,94539,2,1.30,1,287,0,0,0,1,0 +1426,64,38,40,91330,1,2.50,3,94,0,0,0,1,1 +1427,37,11,60,96651,3,0.50,3,0,0,0,0,1,0 +1428,31,5,85,95828,2,1.30,1,119,0,0,0,1,1 +1429,25,-1,21,94583,4,0.40,1,90,0,0,0,1,0 +1430,31,5,35,95064,1,0.60,3,171,0,0,0,0,0 +1431,32,7,52,92660,2,0.10,1,0,0,0,0,1,0 +1432,58,34,128,90058,1,7.40,1,0,0,0,0,0,0 +1433,26,2,195,90245,1,6.33,1,0,0,0,0,0,0 +1434,51,25,68,92647,2,1.50,2,117,0,0,0,0,1 +1435,65,41,55,93106,2,1.10,1,0,0,0,0,0,0 +1436,43,17,55,90266,1,0.20,1,0,0,0,0,1,0 +1437,46,21,80,95054,4,0.40,1,0,0,0,0,1,1 +1438,28,3,123,92007,1,0.80,1,146,0,0,0,0,0 +1439,63,37,90,94105,4,1.90,2,106,0,1,0,1,0 +1440,59,29,61,94025,1,1.40,3,0,0,0,0,0,0 +1441,42,15,41,94610,3,2.50,2,0,0,0,0,1,0 +1442,58,33,43,94720,2,1.60,3,0,0,0,0,1,0 +1443,39,13,71,95822,3,0.10,1,162,0,1,0,1,0 +1444,36,12,25,95051,4,1.00,1,0,0,0,0,1,0 +1445,60,33,154,90740,1,3.00,2,0,1,1,1,1,0 +1446,47,21,141,90095,1,2.40,1,0,0,0,0,0,0 +1447,29,4,22,92661,2,0.90,3,110,0,0,0,0,0 +1448,52,28,145,94131,2,6.80,1,0,0,0,0,1,0 +1449,41,16,49,92122,3,0.50,3,0,0,0,0,1,0 +1450,63,37,109,90740,1,2.00,1,0,0,0,0,1,0 +1451,59,34,80,90086,3,0.50,1,0,0,0,0,1,1 +1452,44,20,82,94555,4,1.40,2,201,0,0,0,1,1 +1453,54,28,52,94102,4,2.50,1,0,0,0,0,1,0 +1454,29,5,85,90232,3,2.50,1,0,0,0,0,1,1 +1455,51,25,148,90024,1,1.00,1,0,0,0,0,0,0 +1456,63,39,160,91330,2,2.10,1,0,0,0,0,0,1 +1457,36,11,39,90095,4,1.70,1,0,0,0,0,1,0 +1458,42,16,25,94304,2,0.80,3,0,0,0,0,0,1 +1459,51,25,33,93033,1,1.40,3,0,0,0,0,1,1 +1460,47,20,38,92115,3,2.50,2,0,0,0,0,0,0 +1461,40,16,85,92677,4,0.20,3,0,0,0,0,1,1 +1462,54,28,48,93022,1,0.20,1,0,0,0,0,1,0 +1463,47,21,15,95207,4,0.60,3,77,0,0,0,1,0 +1464,35,10,94,91343,1,0.00,1,174,0,0,0,1,0 +1465,28,4,120,92333,2,0.60,1,0,0,0,0,1,0 +1466,45,19,60,91911,1,0.70,3,159,0,0,0,1,0 +1467,33,9,145,94303,2,4.33,1,277,0,0,0,0,1 +1468,62,36,29,91107,2,0.70,3,0,0,0,0,0,0 +1469,45,18,78,92129,3,2.67,2,0,0,0,0,1,0 +1470,59,35,59,90005,4,1.20,2,0,0,0,0,1,0 +1471,58,28,80,91116,2,4.50,3,0,0,0,0,0,1 +1472,52,26,180,94305,1,1.00,1,0,0,0,0,1,1 +1473,34,8,8,94710,3,0.10,2,83,0,0,0,1,0 +1474,65,35,23,91711,1,1.50,3,0,0,0,0,1,0 +1475,48,23,79,92124,2,3.80,3,0,0,0,0,1,0 +1476,44,19,78,92064,2,3.80,3,268,0,0,0,0,0 +1477,61,37,64,92028,1,0.00,2,0,0,0,0,0,1 +1478,40,14,64,91320,4,0.20,3,0,0,0,0,1,1 +1479,65,39,160,94803,4,3.80,1,237,1,0,0,1,0 +1480,28,4,43,91304,1,1.00,3,102,0,0,0,0,0 +1481,67,42,32,93943,1,1.10,3,0,0,0,0,0,1 +1482,35,9,179,91125,2,0.00,1,76,0,1,0,1,0 +1483,60,35,8,94143,1,0.10,1,0,0,0,0,1,0 +1484,58,32,63,92717,1,1.60,1,0,0,1,0,1,0 +1485,55,30,40,94126,2,2.30,3,0,0,1,0,1,0 +1486,34,9,99,90245,4,2.20,2,155,0,0,0,1,0 +1487,35,9,141,93022,2,4.50,2,0,1,0,0,0,0 +1488,28,4,159,93907,1,1.50,1,0,0,0,0,1,1 +1489,38,12,39,95825,2,0.30,1,174,0,0,0,1,0 +1490,62,38,99,91604,4,1.70,2,0,0,0,0,0,0 +1491,30,4,18,95020,4,0.30,2,0,0,0,0,1,1 +1492,38,12,38,94553,2,0.30,1,0,0,0,0,1,1 +1493,33,8,133,90024,1,0.00,1,0,0,0,0,1,0 +1494,58,34,84,91380,2,2.80,1,0,0,0,0,1,1 +1495,59,35,60,90089,1,0.00,2,0,0,0,0,1,1 +1496,52,28,178,92647,3,5.40,3,147,1,0,0,1,0 +1497,36,12,18,91330,1,0.50,3,0,0,0,0,0,1 +1498,45,21,73,95020,1,0.80,3,0,0,0,0,1,0 +1499,49,23,125,94022,1,7.30,1,0,0,0,0,0,0 +1500,52,26,91,92173,1,4.30,2,0,1,0,1,1,1 +1501,54,28,74,95014,2,1.10,1,0,0,0,0,1,0 +1502,30,4,35,92130,2,0.30,2,0,0,1,0,0,1 +1503,65,39,113,90036,1,2.00,1,0,0,0,0,1,1 +1504,34,8,52,94720,4,2.20,2,0,0,0,0,0,0 +1505,30,6,191,92028,2,4.40,2,0,1,0,0,1,0 +1506,51,25,18,92109,1,0.30,3,93,0,0,0,0,1 +1507,52,27,25,95138,2,0.00,1,0,0,0,0,1,1 +1508,43,18,50,91006,4,1.90,3,0,0,0,0,0,0 +1509,35,10,75,93940,4,0.70,3,0,0,0,0,1,1 +1510,56,26,92,92647,2,4.50,3,0,0,1,0,0,1 +1511,57,32,33,95747,2,2.00,2,0,0,0,0,1,0 +1512,58,32,65,90266,3,2.20,3,0,0,0,0,0,0 +1513,53,28,44,91604,3,1.70,1,0,0,0,0,0,0 +1514,45,21,183,95211,2,1.40,1,354,0,0,0,0,0 +1515,44,20,175,96150,2,1.40,1,0,0,0,0,1,1 +1516,54,28,28,94305,4,1.50,3,0,0,0,0,1,1 +1517,41,17,49,92130,4,2.20,2,0,0,0,0,0,0 +1518,52,26,45,92697,4,1.80,1,0,0,0,0,1,0 +1519,43,17,64,95053,4,3.00,3,221,1,0,0,1,0 +1520,63,38,22,92115,3,0.10,3,90,0,0,0,1,0 +1521,54,30,120,95039,1,7.40,1,119,0,0,0,1,1 +1522,33,8,175,92354,2,6.70,1,102,0,0,0,1,0 +1523,25,-1,101,94720,4,2.30,3,256,0,0,0,0,1 +1524,41,16,104,92037,1,1.00,3,0,0,0,0,1,0 +1525,40,16,155,94002,4,0.10,3,0,1,0,1,1,1 +1526,43,18,58,95747,1,2.40,1,0,0,0,0,0,0 +1527,36,10,80,94608,4,2.20,2,0,0,0,0,1,0 +1528,57,33,45,94117,1,1.80,3,195,0,0,0,0,0 +1529,34,9,134,94550,1,4.60,1,164,0,1,0,1,0 +1530,38,14,58,91709,4,2.00,3,153,0,1,0,0,0 +1531,47,21,20,94066,1,0.20,1,0,0,0,0,1,1 +1532,39,13,25,90304,4,1.50,3,0,0,0,0,1,0 +1533,45,20,55,94588,1,0.30,1,0,0,0,0,1,1 +1534,62,37,155,93943,1,1.30,1,0,0,0,0,0,0 +1535,59,34,30,92084,1,1.30,1,0,0,0,0,1,1 +1536,61,37,39,92096,4,0.40,1,0,0,0,0,1,1 +1537,36,12,73,95617,4,2.00,3,188,0,0,0,1,0 +1538,58,34,41,94608,4,1.30,1,0,0,0,0,1,0 +1539,55,30,34,95820,4,0.10,3,157,0,0,0,1,0 +1540,29,5,21,90601,3,0.90,3,119,0,0,0,0,0 +1541,34,8,11,91320,4,0.30,1,0,0,1,1,1,1 +1542,61,35,154,92704,2,6.90,1,0,0,0,0,0,0 +1543,50,20,19,92612,4,0.40,3,0,0,0,0,0,0 +1544,52,26,101,93407,2,2.40,2,0,0,0,0,1,0 +1545,39,15,24,92123,1,1.00,1,116,0,0,0,1,1 +1546,55,29,131,92675,2,2.70,1,0,0,1,0,0,0 +1547,33,9,105,95136,1,4.00,1,0,0,0,0,1,0 +1548,47,21,52,94720,1,1.20,2,194,0,0,0,0,0 +1549,57,32,21,92037,4,0.90,2,113,0,1,0,0,0 +1550,57,31,45,94305,3,1.40,1,198,0,0,0,1,0 +1551,40,14,39,93117,1,2.00,1,0,0,0,0,1,0 +1552,50,25,192,94115,2,2.80,1,238,0,0,0,0,1 +1553,29,5,195,94301,1,4.30,1,0,0,0,0,0,0 +1554,46,22,83,95616,3,0.70,1,0,0,0,0,0,0 +1555,42,15,34,91302,3,1.00,2,0,0,1,0,1,0 +1556,59,33,49,93009,4,1.70,2,104,0,0,0,1,0 +1557,31,1,60,94143,4,4.00,3,244,0,0,0,0,0 +1558,51,25,41,94939,4,1.80,1,0,0,0,0,0,0 +1559,35,10,72,91320,3,2.30,1,285,0,0,0,0,0 +1560,59,35,102,92677,4,3.00,2,115,1,0,0,1,0 +1561,35,10,31,95605,3,1.30,1,0,0,0,0,0,0 +1562,46,20,73,93106,1,1.50,2,128,0,0,0,1,0 +1563,34,9,89,91763,1,0.00,1,0,0,0,0,1,0 +1564,55,29,19,92109,4,0.70,3,121,0,1,0,0,1 +1565,64,40,63,94706,4,1.20,2,0,0,0,0,1,0 +1566,34,9,104,95758,3,1.20,3,0,0,0,0,1,0 +1567,61,35,40,95064,1,0.80,2,128,0,0,0,1,0 +1568,63,39,92,94710,2,0.00,3,0,0,0,0,1,0 +1569,59,33,72,92350,2,0.70,2,226,0,0,0,0,0 +1570,51,27,44,94305,3,1.90,2,141,0,0,0,0,0 +1571,41,16,114,94705,4,3.50,1,0,1,0,0,0,1 +1572,37,13,73,95758,4,2.40,1,0,0,0,0,0,0 +1573,64,40,63,91711,4,1.20,2,0,0,1,0,0,1 +1574,44,20,69,92028,1,0.80,3,184,0,0,1,1,1 +1575,62,37,42,92106,3,1.50,1,0,0,0,0,1,0 +1576,50,26,88,90037,1,2.70,1,0,0,0,0,1,0 +1577,43,18,98,92131,2,0.40,1,0,0,0,0,1,0 +1578,34,8,65,92093,1,3.00,1,227,1,0,0,1,0 +1579,38,13,12,94143,2,0.30,2,104,0,1,0,1,0 +1580,29,5,122,94305,4,3.00,1,0,1,0,0,0,1 +1581,39,14,12,92093,2,0.00,3,0,0,0,0,0,0 +1582,53,29,24,94105,2,0.20,1,0,0,0,0,0,1 +1583,43,19,170,92037,4,4.25,1,318,1,0,1,1,1 +1584,61,36,184,92028,4,2.30,2,342,1,0,1,1,1 +1585,46,20,25,93401,4,0.60,3,125,0,0,0,0,0 +1586,57,31,131,90502,2,2.70,1,0,0,0,0,0,0 +1587,59,33,50,94122,2,2.30,3,0,0,0,0,0,1 +1588,52,28,21,94035,2,0.40,1,0,0,1,0,1,0 +1589,29,3,55,95616,3,1.10,2,0,0,0,0,1,0 +1590,57,32,124,90049,1,0.20,2,0,1,0,0,1,0 +1591,49,23,58,95819,4,2.60,1,188,0,0,0,0,0 +1592,39,13,72,95817,2,2.80,1,0,0,0,0,1,0 +1593,56,31,192,90089,1,7.00,3,0,1,0,1,1,0 +1594,63,38,83,91320,3,1.80,2,0,0,0,0,1,0 +1595,37,12,93,90025,1,2.80,1,0,0,1,0,1,0 +1596,56,26,38,94305,3,1.00,3,110,0,1,0,1,0 +1597,45,20,55,92606,4,1.90,3,164,0,1,0,0,0 +1598,66,41,11,92325,3,0.10,3,0,0,1,0,0,1 +1599,40,15,85,94550,2,0.40,1,0,0,1,0,0,0 +1600,50,24,124,93305,1,4.90,1,266,0,0,0,1,0 +1601,60,36,129,92028,2,6.00,1,0,0,0,0,1,0 +1602,31,7,180,93407,1,4.30,1,0,0,0,0,0,0 +1603,40,14,74,90245,4,1.40,2,0,0,0,0,1,0 +1604,36,6,138,92152,1,7.00,3,86,1,0,0,1,0 +1605,55,29,111,90502,2,3.60,3,0,1,0,0,0,1 +1606,54,28,83,93555,3,0.80,1,0,0,0,0,1,0 +1607,35,10,33,90266,4,1.70,1,87,0,0,0,1,0 +1608,55,29,21,92028,4,0.70,3,0,0,0,0,0,0 +1609,36,10,35,94608,2,0.30,1,98,0,0,0,1,0 +1610,66,41,105,93023,1,0.80,3,0,0,1,1,1,1 +1611,38,14,103,94305,1,0.80,2,0,0,0,0,0,1 +1612,58,32,75,92096,2,2.30,3,0,0,0,0,0,0 +1613,41,17,33,94550,1,0.70,1,104,0,0,0,0,0 +1614,60,34,52,94305,4,1.70,2,0,0,1,0,1,0 +1615,47,23,89,94920,1,2.60,2,0,0,1,1,1,1 +1616,62,36,63,93109,1,2.50,3,0,0,0,0,0,0 +1617,48,23,84,94402,4,3.10,2,0,1,1,1,1,0 +1618,61,36,44,91302,4,2.10,1,0,0,0,0,0,0 +1619,29,3,29,94720,3,1.00,1,0,0,0,0,1,1 +1620,45,21,29,90005,1,0.30,3,0,0,0,0,1,0 +1621,39,14,22,94035,2,0.30,2,0,0,0,0,1,0 +1622,31,6,53,92093,4,2.20,1,114,0,0,0,1,0 +1623,39,14,24,94611,2,0.30,2,0,0,0,0,1,0 +1624,63,38,153,90045,1,1.30,1,455,0,0,0,0,0 +1625,28,2,31,90024,2,0.30,2,0,0,1,0,1,0 +1626,56,30,21,94542,2,0.70,2,0,0,0,0,1,0 +1627,31,6,180,93108,2,6.70,1,0,0,0,0,0,0 +1628,46,20,82,91016,3,0.70,2,0,0,0,0,1,1 +1629,42,18,90,95064,4,0.80,1,245,0,1,0,0,0 +1630,53,29,154,93407,4,7.40,3,0,1,0,0,0,0 +1631,41,17,99,92096,2,1.80,2,0,0,0,0,1,1 +1632,61,36,153,91105,1,2.60,2,0,1,1,1,0,1 +1633,31,5,93,95032,2,3.10,2,0,1,0,0,1,0 +1634,62,38,53,92121,1,0.00,2,0,0,0,0,0,0 +1635,59,34,18,95814,3,1.30,2,104,0,0,1,1,1 +1636,49,24,70,91330,1,2.90,1,0,0,0,0,0,0 +1637,65,39,100,92122,4,1.70,3,0,0,0,0,0,1 +1638,30,6,193,94022,3,6.30,3,0,1,0,0,1,0 +1639,32,7,125,95133,1,0.00,1,0,0,0,0,1,1 +1640,56,31,68,94571,2,0.00,3,0,0,1,0,1,0 +1641,36,10,55,90009,1,2.00,1,95,0,0,0,1,0 +1642,58,34,152,92182,4,3.60,3,0,1,0,0,0,0 +1643,27,3,84,95814,3,1.50,1,0,0,0,0,1,1 +1644,41,16,13,91125,2,0.00,3,0,0,0,0,1,0 +1645,59,35,33,91355,4,0.40,1,131,0,0,0,0,1 +1646,56,32,89,92096,4,1.00,2,90,0,1,0,1,0 +1647,52,26,93,91745,1,2.40,1,0,0,0,0,1,0 +1648,35,5,68,90509,4,1.80,3,0,0,0,0,0,0 +1649,47,21,85,93106,2,1.70,2,0,0,0,0,0,1 +1650,29,4,73,95039,1,0.80,2,0,0,0,0,1,0 +1651,31,6,83,92131,4,2.20,2,106,0,0,0,1,0 +1652,62,36,158,94301,2,6.30,3,0,1,0,0,1,0 +1653,48,18,182,92626,4,6.00,3,0,1,0,0,1,0 +1654,26,1,24,96651,2,0.90,3,123,0,0,0,0,1 +1655,60,34,102,94305,2,2.00,1,0,0,0,0,1,1 +1656,35,11,53,91355,3,2.80,1,0,0,0,0,0,0 +1657,40,15,175,92646,2,3.30,1,0,0,0,0,1,0 +1658,31,5,28,94538,3,1.00,1,0,0,0,0,1,0 +1659,50,25,14,92037,4,0.80,1,0,0,0,0,1,0 +1660,33,7,139,95828,1,4.00,3,106,1,0,1,1,1 +1661,37,11,34,95747,3,0.90,1,0,0,0,0,1,0 +1662,38,14,64,92093,1,1.50,3,0,0,0,0,0,1 +1663,63,38,84,94607,4,0.10,2,0,0,0,0,0,0 +1664,57,32,42,95070,3,0.50,2,0,0,1,0,1,0 +1665,61,35,63,91605,1,1.60,1,0,0,0,0,1,0 +1666,37,12,100,92735,3,1.20,3,341,0,0,0,1,1 +1667,51,25,190,95138,2,4.20,2,0,1,0,0,1,0 +1668,44,20,22,90024,1,1.00,1,91,0,0,0,0,0 +1669,63,37,20,90066,1,0.80,2,0,0,1,0,0,1 +1670,43,18,21,95037,2,1.40,2,0,0,0,0,1,1 +1671,38,14,25,95135,4,0.40,2,101,0,0,0,1,0 +1672,34,9,20,92648,4,1.10,3,0,0,0,0,1,0 +1673,48,23,173,94546,3,0.20,1,0,1,0,1,1,1 +1674,29,5,81,94115,2,2.50,1,0,0,0,0,0,1 +1675,37,11,139,95814,2,0.80,2,421,1,0,0,1,0 +1676,60,35,119,90266,2,3.90,1,0,0,1,0,1,0 +1677,46,20,74,92821,4,2.60,3,104,0,0,0,1,0 +1678,34,10,42,92173,1,1.50,2,131,0,0,0,0,0 +1679,56,30,73,94035,2,1.10,1,0,0,0,0,0,0 +1680,57,31,114,94590,4,5.20,1,0,1,1,1,1,0 +1681,62,36,44,92093,2,1.00,3,0,0,0,0,0,0 +1682,32,8,141,90005,2,4.33,1,0,0,0,0,0,0 +1683,51,26,14,92182,2,0.00,1,103,0,0,0,1,0 +1684,55,29,33,92660,2,0.40,3,0,0,0,0,0,0 +1685,60,34,83,94028,2,2.00,1,249,0,0,0,0,0 +1686,40,16,89,90011,4,0.80,1,155,0,0,0,1,0 +1687,62,38,39,96003,4,2.20,1,0,0,1,0,1,0 +1688,63,39,83,90025,3,2.00,3,0,0,0,0,1,1 +1689,60,34,108,92152,2,2.00,1,359,0,0,0,1,0 +1690,59,34,21,92028,3,1.30,2,0,0,0,0,1,1 +1691,26,1,102,95521,1,1.90,1,0,0,0,0,0,0 +1692,56,32,48,94117,1,1.60,3,0,0,0,0,0,1 +1693,58,32,32,93014,3,1.40,1,0,0,0,0,1,0 +1694,57,31,43,95616,1,0.20,1,0,0,0,0,0,0 +1695,48,23,35,94025,4,0.40,2,118,0,0,0,0,0 +1696,30,6,184,91911,1,6.00,1,0,0,0,0,1,0 +1697,45,21,140,91024,2,7.60,1,132,0,0,0,0,0 +1698,64,38,32,90065,3,0.70,2,0,0,0,0,1,1 +1699,44,20,149,92121,1,1.70,1,0,0,0,0,1,0 +1700,51,25,15,94720,4,0.60,3,0,0,0,0,0,1 +1701,43,16,71,90089,3,2.33,2,0,0,0,0,0,0 +1702,29,3,108,94304,4,1.80,2,0,0,0,0,0,0 +1703,56,30,122,93555,2,0.50,1,0,0,0,0,0,1 +1704,65,41,40,94542,3,0.10,3,0,0,0,0,1,0 +1705,46,22,198,95521,2,6.67,1,0,0,0,0,0,1 +1706,48,24,79,90245,4,1.40,2,0,0,1,0,0,1 +1707,56,31,84,92672,1,0.10,3,0,0,0,0,1,0 +1708,61,37,31,92374,3,0.40,2,0,0,0,0,0,1 +1709,46,20,12,90250,4,0.60,3,0,0,0,0,0,1 +1710,58,34,88,93555,2,1.60,1,0,0,0,0,1,1 +1711,31,5,29,95405,2,0.30,2,131,0,0,0,1,1 +1712,27,3,201,95819,1,6.33,1,158,0,0,0,1,0 +1713,44,20,20,92780,1,1.40,3,0,0,0,0,0,0 +1714,44,20,15,90405,1,1.00,1,0,0,0,0,1,0 +1715,51,27,155,94720,2,0.40,1,107,0,0,0,0,1 +1716,39,13,25,95370,3,0.20,2,0,0,0,0,1,0 +1717,32,8,200,91330,2,6.50,1,565,0,0,0,1,0 +1718,33,7,101,93727,1,2.70,2,233,0,0,0,0,0 +1719,40,16,19,92028,4,0.40,2,0,0,0,0,1,1 +1720,36,12,188,91304,2,6.50,1,0,0,0,0,1,1 +1721,52,28,8,95060,1,0.30,1,0,0,0,0,1,0 +1722,54,29,59,92867,2,2.30,3,152,0,0,0,1,0 +1723,26,2,72,92647,4,2.60,1,0,0,1,1,1,0 +1724,39,15,55,95821,1,1.50,3,0,0,0,0,1,0 +1725,46,19,24,90025,3,0.67,2,0,0,0,0,1,0 +1726,57,32,19,95348,1,1.30,1,0,0,0,0,1,0 +1727,59,33,71,91335,2,2.30,3,150,0,0,0,1,1 +1728,52,26,54,90049,2,1.50,2,0,0,0,0,0,1 +1729,52,26,28,95405,1,0.30,3,0,0,0,0,1,0 +1730,50,20,25,91320,4,0.40,3,0,0,0,0,1,0 +1731,41,17,51,94402,2,0.60,3,0,0,0,0,0,1 +1732,43,19,125,92122,3,2.40,1,0,1,0,0,1,0 +1733,25,0,88,94566,2,1.80,2,319,0,0,0,1,1 +1734,40,16,125,95125,2,2.20,1,0,0,0,0,1,0 +1735,35,10,79,94720,4,2.10,3,182,0,0,0,1,0 +1736,60,36,31,95051,3,0.40,2,0,0,0,0,1,1 +1737,57,31,131,95133,2,2.70,1,394,0,0,0,0,1 +1738,44,19,70,92399,1,0.20,2,230,0,1,0,0,0 +1739,61,36,38,91129,3,0.90,3,82,0,0,0,1,1 +1740,33,7,83,95211,1,2.50,1,0,0,1,1,1,1 +1741,45,20,59,95008,1,2.40,1,0,0,1,1,1,0 +1742,45,21,121,94066,1,4.70,1,0,0,0,0,0,0 +1743,64,38,42,95929,2,0.70,3,137,0,0,0,1,0 +1744,50,24,32,94701,4,1.80,1,109,0,0,0,1,0 +1745,28,3,29,91105,4,0.80,1,135,0,0,0,1,0 +1746,37,12,40,90065,2,1.10,2,0,0,1,0,0,1 +1747,62,36,25,90740,3,0.30,3,0,0,0,0,1,1 +1748,29,5,21,90717,4,0.40,2,89,0,0,0,0,1 +1749,49,23,79,95819,3,0.70,2,151,0,0,0,1,0 +1750,46,22,52,95814,2,2.10,3,221,0,0,0,0,0 +1751,60,34,61,95521,4,1.70,2,229,0,0,0,0,0 +1752,55,31,25,94720,2,0.20,1,0,0,0,0,0,0 +1753,33,8,155,92717,1,7.40,3,0,1,0,0,0,0 +1754,53,29,25,92008,2,0.40,1,0,0,0,0,1,0 +1755,50,24,80,95616,4,4.90,1,0,0,0,0,1,0 +1756,28,3,55,92647,4,1.70,2,0,0,0,0,1,1 +1757,42,17,23,95053,2,0.00,3,0,0,0,0,0,0 +1758,33,9,60,90630,1,1.20,1,0,0,0,0,1,1 +1759,40,14,54,96003,2,0.70,1,0,0,0,0,0,0 +1760,31,6,44,94720,4,0.80,1,0,0,0,0,0,0 +1761,41,16,33,94309,4,0.00,2,0,0,0,0,1,0 +1762,52,27,45,94720,2,2.00,2,121,0,0,0,0,1 +1763,65,35,55,94526,4,1.67,3,89,0,0,0,1,1 +1764,48,24,134,94105,1,5.00,1,0,0,0,0,0,1 +1765,45,21,44,94596,3,0.60,2,0,0,0,0,1,0 +1766,26,0,149,95051,2,7.20,1,154,0,0,0,0,0 +1767,64,38,22,92697,2,0.20,3,0,0,1,0,0,0 +1768,41,14,74,92691,3,2.33,2,0,0,0,0,1,0 +1769,43,18,128,92093,4,5.30,1,84,1,0,0,0,0 +1770,60,36,62,94061,4,2.20,1,0,0,0,0,0,0 +1771,62,37,9,91320,1,0.10,1,94,0,0,0,0,0 +1772,46,21,9,95023,2,0.70,3,0,0,0,0,1,0 +1773,36,11,15,94720,2,0.30,2,119,0,0,0,0,0 +1774,31,5,28,92037,4,0.80,1,0,0,0,0,0,0 +1775,43,18,83,93109,3,0.50,3,0,0,0,0,0,1 +1776,46,22,73,91360,1,0.80,3,117,0,0,0,0,0 +1777,50,26,42,94080,4,1.10,2,151,0,0,0,1,0 +1778,52,27,34,93117,2,0.70,2,114,0,0,0,1,1 +1779,27,3,32,94710,3,1.00,2,0,0,0,0,0,0 +1780,34,9,68,94720,1,2.80,1,0,0,0,0,1,0 +1781,49,24,82,95051,1,2.90,1,267,0,0,0,1,0 +1782,52,26,19,90650,2,0.70,2,0,0,0,0,0,1 +1783,37,11,60,95825,2,2.80,1,181,0,0,0,0,1 +1784,53,27,192,94720,1,1.70,1,601,0,0,0,1,0 +1785,54,29,119,91355,3,2.00,1,0,1,1,1,0,0 +1786,29,3,190,94080,2,4.50,1,0,0,0,0,1,0 +1787,35,11,34,93117,1,1.50,2,0,0,0,0,0,0 +1788,32,6,44,94608,4,0.20,1,0,0,1,1,1,1 +1789,38,13,23,91116,4,0.20,3,0,0,0,0,1,0 +1790,44,20,171,91330,4,0.70,1,567,1,0,1,1,1 +1791,44,20,43,92124,1,0.30,3,0,0,1,0,0,1 +1792,48,22,139,94309,1,0.00,1,0,0,0,1,1,1 +1793,46,20,118,93009,1,5.70,1,0,0,0,1,1,1 +1794,35,9,113,94596,3,0.80,3,0,1,0,0,1,0 +1795,56,32,98,91355,3,3.90,3,0,1,0,0,0,0 +1796,49,24,70,90024,1,2.90,1,0,0,0,0,0,1 +1797,57,32,42,92831,2,2.10,3,0,0,0,0,1,0 +1798,35,10,143,91365,1,8.60,1,0,0,0,0,1,1 +1799,44,20,185,94086,3,2.70,1,0,1,0,0,1,0 +1800,38,14,28,95821,4,0.40,2,100,0,0,0,1,0 +1801,57,33,45,94080,3,1.50,1,181,0,1,1,1,1 +1802,35,10,78,92121,1,2.60,2,0,0,0,0,0,0 +1803,29,3,121,92806,2,1.30,1,0,0,0,0,0,0 +1804,58,32,59,94542,1,1.60,1,0,0,0,0,1,0 +1805,40,16,64,92661,4,2.67,1,0,0,1,0,1,0 +1806,51,26,15,92373,2,0.00,1,114,0,0,0,1,0 +1807,61,36,10,90740,1,0.10,1,0,0,0,0,0,0 +1808,46,20,61,90036,2,0.40,3,0,0,0,0,0,0 +1809,55,31,50,93010,4,1.50,1,0,0,0,0,1,0 +1810,35,10,79,95045,4,2.10,3,0,0,1,0,1,0 +1811,60,34,35,90025,1,0.20,1,0,0,0,0,1,0 +1812,28,3,11,94534,4,0.50,3,0,0,0,0,0,0 +1813,43,19,128,95054,1,4.70,1,0,0,0,0,1,0 +1814,61,36,55,90033,3,0.90,3,0,0,0,0,1,1 +1815,48,22,79,95747,3,0.70,2,0,0,0,0,1,0 +1816,65,39,18,94923,2,0.40,1,0,0,1,1,1,1 +1817,45,19,91,92373,2,1.70,2,0,0,1,0,1,0 +1818,36,11,9,94604,4,0.20,3,0,0,0,0,0,1 +1819,45,20,62,95818,2,2.20,3,0,0,0,0,1,0 +1820,60,34,59,94110,1,1.60,1,231,0,0,0,1,0 +1821,47,22,25,90404,1,0.10,1,148,0,0,0,1,0 +1822,32,7,54,96008,4,1.30,1,0,0,1,0,1,0 +1823,48,23,112,93014,1,5.10,2,86,1,1,1,1,0 +1824,33,8,125,91320,1,0.00,1,0,0,0,0,1,1 +1825,49,23,194,94022,4,8.30,2,0,1,0,0,0,1 +1826,56,32,161,94720,1,5.80,3,0,1,1,0,0,0 +1827,59,33,35,91105,1,0.20,1,171,0,0,0,0,0 +1828,56,30,113,92704,2,2.70,1,352,0,0,0,0,1 +1829,30,4,25,92123,2,0.30,2,0,0,0,0,0,0 +1830,59,29,45,95630,3,2.00,3,0,0,0,0,1,0 +1831,38,13,119,94571,2,7.80,1,221,0,0,0,0,0 +1832,47,22,30,94118,4,0.40,2,115,0,0,0,1,1 +1833,54,29,79,91330,4,3.80,2,0,0,1,0,1,0 +1834,34,9,178,94303,1,0.80,3,0,1,0,0,0,0 +1835,41,16,23,94143,2,0.30,2,118,0,0,0,0,0 +1836,47,23,171,94546,2,1.40,1,284,0,0,0,1,1 +1837,44,19,74,90041,4,1.90,3,0,0,0,0,0,0 +1838,43,18,103,90089,3,1.00,1,180,0,0,0,1,1 +1839,31,7,99,94720,1,4.00,1,0,0,0,0,1,0 +1840,28,2,43,95616,4,1.30,3,0,0,0,0,1,1 +1841,55,25,23,93106,4,0.40,3,88,0,0,0,0,0 +1842,42,17,91,94583,1,0.10,2,199,0,0,0,1,1 +1843,53,29,93,95051,1,2.70,2,256,0,0,0,1,0 +1844,30,6,154,90230,1,6.00,1,0,0,0,0,0,0 +1845,65,40,21,92717,3,0.10,3,0,0,0,0,0,1 +1846,43,18,65,93065,2,2.20,3,0,0,0,0,1,0 +1847,56,32,15,90089,1,0.10,2,0,0,0,0,1,0 +1848,25,0,52,95126,3,2.60,3,159,0,0,0,0,0 +1849,35,10,30,95032,3,1.30,1,0,0,1,1,1,1 +1850,50,26,42,90630,1,1.60,2,0,0,0,0,1,0 +1851,36,10,20,90033,4,0.30,1,97,0,0,0,1,0 +1852,34,8,60,94015,4,2.20,2,0,0,0,0,0,1 +1853,32,6,54,94596,4,1.80,3,167,0,0,0,0,0 +1854,51,25,60,90401,4,2.60,1,97,0,0,0,1,0 +1855,52,25,41,95403,3,1.00,2,0,0,0,0,1,0 +1856,65,39,30,94304,3,0.70,2,0,0,0,0,1,1 +1857,51,24,21,95014,2,1.00,2,0,0,0,0,1,0 +1858,37,13,105,94066,1,0.80,2,0,0,0,0,0,1 +1859,35,11,65,90747,3,2.80,1,240,0,0,0,1,0 +1860,67,41,20,91741,2,0.40,1,80,0,0,0,0,0 +1861,30,6,179,91103,3,4.90,1,142,1,0,0,1,0 +1862,62,38,161,90274,1,2.90,1,0,0,1,1,1,1 +1863,42,17,82,95616,1,3.70,3,0,0,0,0,1,0 +1864,48,22,43,94588,1,1.20,2,112,0,0,0,1,0 +1865,61,36,61,92103,2,2.80,1,0,0,0,0,0,0 +1866,36,6,90,91342,4,1.80,3,0,0,1,0,0,0 +1867,48,24,90,94523,1,2.60,2,334,0,0,0,1,0 +1868,65,39,21,94553,2,0.40,1,0,0,0,0,0,0 +1869,25,1,118,92833,1,5.40,1,0,0,0,0,1,1 +1870,55,30,44,94025,2,2.00,2,0,0,0,0,1,0 +1871,63,37,110,95032,1,4.10,3,0,1,0,0,0,0 +1872,31,5,99,94065,4,1.80,2,268,0,0,0,0,0 +1873,43,17,98,94402,3,1.10,1,0,0,0,0,0,0 +1874,28,4,69,94538,3,0.70,2,80,0,0,0,1,0 +1875,37,11,82,95819,3,0.90,2,218,0,0,0,1,1 +1876,27,3,112,90066,3,2.50,1,389,0,1,0,1,0 +1877,62,38,123,90210,1,2.90,1,0,0,0,0,0,0 +1878,51,24,78,90037,1,2.67,2,0,0,0,0,1,0 +1879,56,30,59,95833,3,0.80,1,159,0,1,0,1,0 +1880,56,30,78,90401,3,1.70,2,0,0,0,0,0,0 +1881,44,19,49,94720,4,1.90,3,89,0,0,0,1,0 +1882,46,19,82,91365,3,2.67,2,0,0,0,0,0,0 +1883,56,32,125,91330,3,0.60,1,342,1,0,1,1,1 +1884,56,30,185,91711,1,2.90,1,0,0,0,0,0,0 +1885,57,33,163,94132,1,7.40,1,0,0,0,0,1,0 +1886,31,6,19,96001,4,1.10,3,104,0,0,1,1,1 +1887,65,41,115,94105,4,1.70,2,0,0,0,0,0,0 +1888,31,7,81,95006,2,2.00,2,0,0,0,1,1,1 +1889,36,10,93,94305,1,2.80,3,0,0,0,0,1,0 +1890,56,30,111,93106,4,0.30,1,372,1,1,1,1,0 +1891,52,27,184,90630,1,8.10,1,0,0,0,0,0,0 +1892,42,18,50,95126,4,2.20,2,0,0,0,0,0,0 +1893,55,30,55,94110,3,1.70,1,0,0,0,0,0,1 +1894,49,24,13,94608,1,0.40,3,101,0,1,0,0,0 +1895,51,25,29,94303,4,0.10,1,0,0,0,0,1,1 +1896,26,2,72,95003,4,2.60,1,0,0,0,0,1,0 +1897,32,7,83,94304,1,2.60,2,0,0,1,0,0,1 +1898,54,29,98,93065,1,0.10,3,0,0,0,0,0,0 +1899,50,24,43,95630,4,0.10,1,0,0,0,0,1,0 +1900,59,33,34,94115,1,0.20,1,0,0,0,0,1,0 +1901,61,36,10,91365,4,0.40,2,0,0,0,0,1,0 +1902,43,19,201,94305,2,6.67,1,0,0,1,0,1,0 +1903,39,14,85,94005,3,1.20,3,107,0,0,0,1,1 +1904,56,26,50,90095,3,1.40,3,0,0,0,0,0,0 +1905,38,14,91,95060,2,0.00,1,0,0,0,0,1,0 +1906,25,-1,112,92507,2,2.00,1,241,0,0,0,1,0 +1907,42,17,98,92866,2,0.40,1,275,0,0,0,1,0 +1908,42,18,115,93711,1,0.30,1,0,0,0,0,0,0 +1909,50,26,22,92037,4,0.50,2,112,0,0,0,1,0 +1910,56,30,101,90048,3,1.70,2,0,0,0,0,0,1 +1911,43,18,83,95616,2,3.80,3,112,0,0,0,0,0 +1912,60,35,52,94709,3,0.50,2,0,0,0,0,0,0 +1913,42,16,191,94304,3,4.80,2,0,1,1,1,1,0 +1914,57,33,134,92110,4,0.90,1,198,1,0,0,1,0 +1915,48,24,54,95616,1,1.60,2,186,0,0,0,1,0 +1916,37,11,69,91911,3,2.10,1,0,0,1,0,0,0 +1917,57,32,64,95138,3,1.60,3,0,0,0,0,1,0 +1918,62,32,53,96001,4,1.67,3,142,0,0,0,0,0 +1919,39,9,118,93555,2,6.00,3,246,1,0,1,1,1 +1920,38,13,19,92069,2,1.40,2,120,0,0,0,0,1 +1921,54,28,31,92130,2,0.40,3,0,0,0,0,0,0 +1922,45,21,63,95621,1,0.80,3,245,0,0,0,1,1 +1923,39,15,25,93023,1,1.40,3,0,0,0,0,0,0 +1924,45,19,22,90639,1,0.20,1,0,0,0,0,1,0 +1925,62,38,78,92009,1,1.80,3,0,0,0,0,0,0 +1926,43,19,81,90245,1,0.30,1,218,0,0,0,1,0 +1927,30,6,41,90095,1,2.40,2,0,0,0,0,1,0 +1928,35,10,62,93106,3,2.30,1,0,0,0,0,0,0 +1929,58,34,35,94122,1,1.20,3,0,0,0,0,1,0 +1930,44,19,30,94501,1,0.60,3,0,0,0,0,1,0 +1931,56,29,51,94080,3,1.00,2,0,0,0,0,1,0 +1932,28,2,140,92122,2,2.00,1,0,0,0,0,1,0 +1933,64,39,73,90073,3,2.40,1,185,0,0,0,0,0 +1934,63,39,40,91311,4,1.20,2,0,0,0,0,1,0 +1935,44,20,69,95814,1,0.80,3,0,0,0,0,1,1 +1936,34,9,191,94086,1,4.80,3,0,1,0,1,1,1 +1937,50,24,82,90291,3,3.00,2,0,0,0,0,1,0 +1938,51,25,181,95051,1,3.30,3,589,1,1,1,1,0 +1939,30,4,38,90245,1,1.90,3,0,0,0,0,1,0 +1940,55,31,23,94122,2,0.20,1,0,0,0,0,1,0 +1941,57,33,55,92630,1,1.80,3,0,0,0,0,1,0 +1942,43,19,58,95307,2,3.20,1,0,0,0,0,1,0 +1943,61,36,29,90210,2,0.50,2,0,0,0,0,1,0 +1944,49,23,39,95521,4,2.60,1,0,0,0,0,0,0 +1945,52,28,39,90095,3,1.90,2,83,0,0,1,1,1 +1946,57,33,30,93106,3,1.50,1,151,0,1,0,1,0 +1947,53,23,58,94720,4,2.00,3,0,0,0,0,1,1 +1948,52,28,62,94111,1,1.80,3,231,0,0,0,1,0 +1949,39,15,62,93955,4,2.40,1,86,0,0,0,0,0 +1950,58,34,19,90504,1,1.20,3,0,0,0,0,0,0 +1951,36,12,38,94109,1,1.50,2,0,0,0,0,0,0 +1952,45,21,84,94550,4,2.00,3,0,0,0,0,1,1 +1953,30,5,78,92037,1,2.60,2,0,0,0,0,1,0 +1954,49,25,22,90058,4,0.20,1,83,0,0,0,1,0 +1955,44,20,81,90245,4,2.00,3,277,0,0,0,1,0 +1956,43,17,32,90401,3,0.50,2,0,0,0,0,1,0 +1957,42,18,89,94539,4,0.80,1,184,0,0,0,0,0 +1958,29,4,121,90028,2,3.30,1,0,0,0,0,1,0 +1959,28,2,42,95762,1,1.50,1,0,0,0,0,1,1 +1960,50,24,130,95833,1,1.00,1,0,0,0,0,0,0 +1961,44,19,30,95616,4,0.00,2,0,0,0,0,1,0 +1962,52,26,114,94304,1,4.90,1,0,0,0,0,0,0 +1963,28,4,155,90019,1,6.33,1,0,0,0,0,0,0 +1964,62,38,50,94539,2,1.10,1,0,0,0,0,0,1 +1965,34,10,34,95060,1,1.50,2,111,0,0,0,0,1 +1966,45,20,94,90095,3,0.50,3,0,0,0,0,1,0 +1967,52,26,114,91330,2,2.40,2,0,0,0,0,0,0 +1968,43,18,89,94303,3,0.50,3,108,0,0,0,0,1 +1969,54,24,49,91801,1,1.40,3,0,0,0,0,1,0 +1970,64,38,115,94105,1,2.00,1,0,0,0,0,1,1 +1971,27,3,148,92780,1,1.50,1,397,0,0,0,1,1 +1972,42,17,72,95616,4,1.10,2,203,0,0,0,0,1 +1973,28,2,114,94606,4,2.10,3,0,0,0,0,1,0 +1974,47,22,11,92192,2,0.00,1,78,0,0,0,0,0 +1975,39,13,63,90095,4,0.20,3,242,0,0,0,0,0 +1976,29,3,113,94132,2,0.20,1,0,0,0,0,1,1 +1977,39,13,80,95616,2,1.80,1,0,0,0,0,1,0 +1978,41,15,54,94303,3,0.50,3,0,0,0,0,1,1 +1979,37,11,32,94612,2,1.40,3,0,0,1,0,1,0 +1980,41,17,11,91330,1,1.00,1,0,0,0,0,0,0 +1981,45,19,141,94706,1,2.40,1,0,0,0,0,1,0 +1982,52,26,84,91768,3,3.00,2,0,0,0,0,1,0 +1983,58,33,18,94701,3,0.10,2,110,0,0,0,1,0 +1984,31,5,20,94720,2,0.30,1,0,0,0,0,0,0 +1985,26,1,55,92630,4,1.70,2,175,0,0,0,1,0 +1986,31,7,31,94920,4,0.40,2,79,0,0,0,0,0 +1987,42,17,114,90065,2,0.40,1,0,0,0,0,0,0 +1988,56,31,52,94118,3,2.00,2,0,0,1,1,1,1 +1989,52,28,18,91301,1,0.30,1,120,0,0,0,1,0 +1990,59,35,55,90274,1,1.80,3,0,0,1,0,0,0 +1991,32,8,29,92807,1,0.20,3,76,0,0,0,1,1 +1992,46,22,30,90747,3,0.50,1,0,0,0,0,0,0 +1993,52,28,38,94302,2,0.80,1,0,0,0,0,0,1 +1994,30,5,122,94545,2,3.10,1,0,0,0,0,0,0 +1995,32,8,183,94080,1,6.00,1,0,0,0,0,0,0 +1996,35,11,41,94720,1,2.40,2,0,0,0,0,0,0 +1997,49,24,38,94305,1,1.40,3,0,0,0,0,0,0 +1998,54,30,61,92093,1,1.80,3,0,0,0,0,1,0 +1999,56,32,103,94111,3,4.00,3,0,1,0,0,0,0 +2000,48,22,80,93940,2,2.40,2,0,0,0,0,1,0 +2001,28,2,22,95670,1,0.10,2,0,0,0,0,1,0 +2002,44,17,128,94928,2,3.25,2,0,1,0,0,0,1 +2003,30,4,142,92126,3,4.20,1,359,1,0,0,0,0 +2004,44,20,124,90277,1,4.70,1,0,0,0,0,1,1 +2005,30,4,44,92704,1,1.90,3,143,0,0,0,0,0 +2006,47,23,170,90254,2,6.50,2,0,1,0,1,1,1 +2007,64,39,75,94720,4,0.10,2,0,0,0,1,1,1 +2008,48,21,78,94010,3,2.00,2,0,0,0,0,1,1 +2009,63,38,31,92037,1,1.10,3,125,0,0,0,1,0 +2010,25,0,99,92735,1,1.90,1,323,0,0,0,0,0 +2011,61,36,41,96001,2,1.50,1,0,0,0,0,0,0 +2012,46,21,39,92507,4,0.00,2,0,0,0,0,1,0 +2013,57,31,51,93943,1,1.40,1,0,0,0,0,1,1 +2014,40,15,52,92691,3,0.80,3,113,0,0,0,1,0 +2015,49,19,169,95054,3,5.67,3,167,1,0,1,0,1 +2016,30,5,141,95747,1,0.80,1,0,0,0,0,1,0 +2017,41,17,93,92835,4,0.80,1,218,0,0,0,0,0 +2018,42,15,14,92064,3,1.00,2,0,0,1,0,0,0 +2019,63,39,160,90089,2,2.10,1,0,0,0,0,1,1 +2020,43,17,44,94611,1,0.20,1,0,0,1,1,1,0 +2021,59,34,33,94303,3,0.20,1,0,0,1,0,0,0 +2022,46,20,103,91380,4,4.80,3,0,1,0,0,1,0 +2023,33,3,71,93561,4,1.80,3,236,0,0,0,0,0 +2024,55,29,55,94720,1,0.20,1,151,0,0,0,1,0 +2025,36,12,113,94305,4,0.20,1,0,1,0,0,0,0 +2026,47,20,79,94720,3,2.00,2,185,0,1,0,0,0 +2027,59,33,80,93907,2,0.70,2,0,0,0,0,1,0 +2028,38,12,179,94596,2,0.00,1,380,0,0,0,0,0 +2029,42,17,9,91710,2,0.00,3,0,0,0,0,0,0 +2030,30,3,61,92152,4,2.00,2,0,0,0,0,1,0 +2031,63,38,111,95814,2,3.90,1,207,0,1,1,1,1 +2032,60,35,80,94608,3,0.50,1,0,0,0,0,1,0 +2033,62,37,32,90266,3,0.20,1,0,0,1,0,0,1 +2034,49,23,83,92126,1,0.30,1,0,0,0,0,1,1 +2035,59,33,91,92821,4,1.90,2,329,0,0,0,0,0 +2036,36,10,29,93065,4,1.00,1,0,0,0,0,1,1 +2037,46,19,19,94305,3,0.67,2,0,0,0,0,1,0 +2038,35,8,52,95616,2,1.00,2,0,0,0,0,0,1 +2039,50,24,150,94551,1,7.30,1,0,0,0,0,1,1 +2040,51,25,32,91605,2,0.40,3,0,0,0,0,1,0 +2041,41,16,91,94720,3,0.50,3,0,0,0,0,0,0 +2042,45,20,180,95403,3,8.50,2,535,1,0,0,0,0 +2043,41,17,121,94102,1,0.30,1,0,0,0,0,1,0 +2044,57,32,25,90049,2,0.20,3,0,0,0,0,1,1 +2045,51,25,102,92677,1,0.30,1,0,0,0,0,1,0 +2046,52,28,44,95051,4,0.90,2,107,0,0,0,1,0 +2047,43,16,161,95134,3,8.00,2,0,1,0,1,1,1 +2048,63,38,134,90640,3,4.00,2,0,1,0,0,0,1 +2049,28,4,43,94803,1,1.80,2,0,0,0,0,1,1 +2050,43,18,94,92717,4,1.10,2,0,0,0,0,1,0 +2051,41,15,29,94024,2,0.80,3,98,0,0,0,0,0 +2052,34,8,38,90018,4,0.20,1,0,0,0,0,0,0 +2053,28,3,120,94080,1,0.80,1,170,0,0,0,0,0 +2054,58,32,85,92110,2,2.00,1,161,0,1,1,1,1 +2055,39,15,89,92126,2,1.90,1,0,0,0,0,0,0 +2056,49,23,25,90274,1,1.40,3,0,0,0,0,1,0 +2057,33,8,20,92691,3,1.30,1,83,0,0,0,0,1 +2058,37,12,125,91754,2,3.90,1,0,0,0,0,1,1 +2059,33,7,18,92093,1,0.60,3,0,0,0,0,0,0 +2060,28,3,173,92121,2,6.70,1,222,0,0,0,1,0 +2061,54,29,34,92093,4,0.10,3,0,0,0,0,1,1 +2062,63,38,159,93950,4,4.90,2,111,1,0,0,0,0 +2063,57,31,55,92521,3,2.50,1,219,0,0,1,1,1 +2064,56,30,32,94080,2,0.40,3,0,0,0,0,1,0 +2065,54,29,65,94545,4,1.80,3,0,0,0,0,0,1 +2066,29,5,83,92354,3,1.50,1,0,0,0,0,1,1 +2067,41,16,30,95814,2,1.40,2,0,0,0,0,0,1 +2068,58,32,180,91770,1,2.90,1,0,0,0,0,0,1 +2069,61,37,13,90024,2,0.30,3,0,0,0,0,1,0 +2070,30,4,35,90059,4,0.80,1,0,0,0,0,1,1 +2071,62,37,95,91107,3,0.50,1,0,0,0,0,0,0 +2072,52,28,83,94705,1,0.00,1,0,0,0,0,1,0 +2073,29,3,39,95831,4,0.20,1,137,0,0,0,1,1 +2074,46,20,54,91107,1,0.70,3,154,0,0,0,1,1 +2075,52,27,81,91942,1,1.30,3,293,0,0,0,0,1 +2076,40,16,53,94123,4,2.00,3,0,0,0,0,0,0 +2077,49,23,119,91030,1,7.30,1,398,0,0,0,0,0 +2078,34,9,160,94108,4,8.00,3,0,1,0,0,0,1 +2079,35,11,21,95814,2,1.00,2,0,0,0,0,0,0 +2080,26,2,40,94132,1,1.00,3,0,0,0,0,1,0 +2081,65,40,69,91706,4,0.10,2,0,0,0,0,1,0 +2082,52,27,45,95006,1,1.30,2,0,0,0,0,0,0 +2083,32,7,55,91301,4,2.00,2,0,0,0,0,1,0 +2084,31,7,38,94025,1,0.20,3,0,0,0,0,1,0 +2085,36,9,44,93907,4,1.00,2,101,0,1,0,1,0 +2086,50,24,45,94105,3,0.60,2,117,0,0,0,1,0 +2087,36,12,84,90291,1,0.80,2,0,0,0,0,1,1 +2088,51,27,188,94305,2,6.90,2,343,1,0,0,1,0 +2089,39,9,29,94701,3,2.00,3,151,0,1,0,0,0 +2090,53,29,95,94304,1,2.70,2,0,0,0,0,1,0 +2091,50,25,79,95023,1,2.90,1,307,0,0,0,0,1 +2092,31,4,41,91360,1,2.00,2,0,0,1,0,1,0 +2093,53,23,19,92673,4,0.40,3,84,0,0,0,1,0 +2094,48,23,75,94111,4,3.60,3,0,0,0,0,1,1 +2095,57,31,64,90024,3,2.50,1,208,0,0,0,0,1 +2096,47,21,174,94025,4,3.20,3,0,1,0,0,0,0 +2097,55,29,54,95051,2,2.30,3,93,0,0,0,0,0 +2098,37,11,14,90740,3,0.10,2,113,0,0,0,1,0 +2099,59,35,94,90089,1,3.80,1,272,0,0,0,0,0 +2100,53,29,10,90095,2,0.40,1,0,0,0,0,0,0 +2101,31,6,145,93940,1,0.80,1,84,0,0,0,1,0 +2102,35,5,203,95032,1,10.00,3,0,1,0,0,0,0 +2103,25,-1,81,92647,2,1.60,3,0,0,0,0,1,1 +2104,37,13,153,90630,2,6.50,1,0,0,0,0,1,1 +2105,40,14,58,90245,4,0.20,3,0,0,0,0,1,0 +2106,31,5,49,94114,4,1.80,3,0,0,0,0,1,1 +2107,62,38,132,90210,1,2.90,1,0,0,0,0,0,0 +2108,41,17,85,90291,4,0.20,3,229,0,0,0,0,0 +2109,56,32,85,94132,3,2.67,1,0,0,1,0,1,0 +2110,47,23,178,93014,1,6.50,3,0,1,0,0,0,0 +2111,28,4,104,94301,3,2.50,1,0,0,0,0,0,0 +2112,60,34,40,94105,1,1.60,1,0,0,0,0,1,0 +2113,27,2,103,93117,1,1.90,1,120,0,0,0,1,0 +2114,57,33,25,92064,2,1.00,1,0,0,0,0,1,0 +2115,62,36,69,95039,2,1.70,3,0,0,0,0,1,0 +2116,57,31,30,95070,3,1.40,1,0,0,0,0,0,0 +2117,44,17,70,94920,3,2.67,2,0,0,0,0,0,0 +2118,31,7,15,91380,3,0.90,3,0,0,0,0,1,0 +2119,31,5,125,91320,2,1.30,1,0,0,0,0,1,1 +2120,39,13,50,94923,3,0.50,3,0,0,0,0,0,0 +2121,41,17,44,93106,1,0.30,3,0,0,0,0,1,0 +2122,41,17,38,92182,4,2.20,2,180,0,0,0,0,1 +2123,55,29,64,93437,3,0.80,1,119,0,0,0,0,1 +2124,28,2,9,95014,1,0.10,2,0,0,0,0,1,0 +2125,35,9,44,92054,3,0.90,1,89,0,0,0,0,0 +2126,44,20,93,91910,4,0.80,1,101,0,0,0,1,0 +2127,44,19,83,92121,4,0.40,1,141,0,0,0,0,0 +2128,40,14,179,94720,2,0.00,1,0,0,0,0,0,0 +2129,65,40,40,94104,1,1.10,3,0,0,0,0,0,0 +2130,35,10,58,91754,4,0.70,3,232,0,0,0,0,0 +2131,55,31,74,94607,3,2.67,1,0,0,0,0,0,1 +2132,55,31,15,95747,1,0.20,1,0,0,0,0,0,0 +2133,59,35,11,94949,2,1.00,1,0,0,0,0,0,1 +2134,39,15,41,95035,1,2.00,2,176,0,0,0,1,0 +2135,50,24,68,95821,1,1.50,2,120,0,0,0,1,1 +2136,45,15,28,95039,1,0.75,3,0,0,1,0,0,0 +2137,50,26,115,95008,1,1.20,3,0,1,0,0,0,1 +2138,65,40,83,92354,4,0.10,2,247,0,0,0,1,0 +2139,36,11,40,93611,2,1.10,2,166,0,1,0,0,0 +2140,57,32,113,91768,1,0.10,3,0,0,0,0,1,0 +2141,53,27,89,92130,1,0.80,3,0,0,1,0,1,0 +2142,28,4,38,92109,4,1.60,1,0,0,0,0,0,0 +2143,55,31,62,93943,4,1.50,1,0,0,0,0,1,0 +2144,56,31,65,92093,3,1.70,1,109,0,0,0,0,0 +2145,33,6,168,94720,3,5.67,2,0,1,1,1,1,0 +2146,57,32,40,94720,3,1.70,1,0,0,0,0,1,1 +2147,27,3,30,93108,1,1.00,3,80,0,0,0,0,0 +2148,27,3,20,92007,4,1.00,1,0,0,0,0,0,0 +2149,54,30,58,92007,2,3.20,3,0,0,0,0,0,0 +2150,48,22,150,95039,1,7.30,1,193,0,0,0,0,0 +2151,62,38,54,91320,1,0.80,1,0,0,1,0,0,1 +2152,41,16,19,91730,2,0.30,2,105,0,0,0,0,0 +2153,62,38,30,94304,3,0.10,3,128,0,0,0,1,0 +2154,40,14,123,90041,1,5.20,1,0,0,0,0,1,0 +2155,32,8,45,94558,1,2.40,2,0,0,0,0,0,0 +2156,62,38,154,94305,1,2.90,1,0,0,0,0,1,0 +2157,35,11,93,90747,2,2.70,1,0,0,0,0,1,1 +2158,25,0,71,93727,4,0.20,1,78,0,1,0,0,0 +2159,50,25,83,94720,4,3.10,1,0,1,0,0,0,1 +2160,61,35,99,94085,1,4.80,3,255,1,0,0,0,1 +2161,43,17,55,93933,3,2.20,2,0,0,0,0,0,0 +2162,52,28,38,94131,4,0.90,2,95,0,0,0,1,1 +2163,39,13,74,95008,3,0.90,2,155,0,0,0,1,0 +2164,33,3,69,92161,4,1.80,3,0,0,0,0,1,0 +2165,27,3,104,92007,2,2.50,1,184,0,1,0,1,0 +2166,27,0,38,95929,4,1.00,3,154,0,0,0,1,0 +2167,32,8,25,93524,3,0.90,3,0,0,0,0,1,1 +2168,65,40,162,94596,1,1.30,1,0,0,0,0,1,0 +2169,55,29,64,93063,4,2.60,3,0,0,0,0,1,0 +2170,52,27,30,94305,2,0.70,2,0,0,0,0,1,1 +2171,39,13,52,95039,3,0.50,3,0,0,1,0,0,1 +2172,35,11,42,93108,1,1.50,3,0,0,0,0,1,0 +2173,39,15,79,92028,2,1.80,2,219,0,0,0,0,0 +2174,34,10,34,93407,1,1.70,1,164,0,0,0,0,0 +2175,30,5,123,95605,2,3.10,1,0,0,0,0,1,0 +2176,37,12,160,94305,2,3.30,1,0,0,0,0,0,0 +2177,41,14,51,91320,3,2.33,2,0,0,0,0,1,0 +2178,31,7,108,94507,1,4.00,1,0,0,0,0,1,0 +2179,37,13,158,93943,2,2.30,2,0,1,0,1,1,1 +2180,49,23,68,90024,1,1.50,2,0,0,0,0,0,0 +2181,58,33,42,91380,2,1.60,3,0,0,0,0,1,0 +2182,45,15,32,94143,1,0.75,3,105,0,0,0,1,0 +2183,40,14,22,94566,2,1.40,3,0,0,0,0,0,0 +2184,34,8,29,90025,2,2.00,3,0,0,0,0,1,1 +2185,62,36,183,90095,2,3.40,3,0,1,0,0,0,0 +2186,54,30,69,92009,1,1.60,3,0,0,0,0,1,1 +2187,26,2,92,96001,2,0.20,1,0,0,0,0,1,0 +2188,54,30,40,90024,2,1.00,3,0,0,0,0,0,0 +2189,29,4,9,92037,4,0.50,3,86,0,0,0,1,1 +2190,48,23,128,94309,1,0.60,1,0,0,0,0,1,1 +2191,27,3,110,96150,2,0.20,1,294,0,1,0,0,1 +2192,42,18,171,90027,2,8.00,1,0,0,0,0,1,0 +2193,25,1,13,95814,4,1.00,1,95,0,0,0,0,1 +2194,45,19,25,94609,2,0.10,3,102,0,0,0,1,0 +2195,34,9,123,94553,1,1.60,2,0,1,0,0,1,0 +2196,51,27,33,92037,4,0.20,1,83,0,0,0,1,0 +2197,51,24,189,95211,4,4.75,2,0,1,0,0,1,0 +2198,60,35,34,94102,1,0.30,3,0,0,0,0,1,0 +2199,59,35,58,91355,1,0.00,2,0,0,0,0,1,0 +2200,49,24,51,91016,1,1.30,2,98,0,0,0,0,1 +2201,50,25,29,90095,2,1.30,1,0,0,0,0,0,0 +2202,41,16,111,92009,2,0.40,1,0,0,0,0,0,0 +2203,49,24,43,94709,4,1.90,3,0,0,0,0,1,0 +2204,50,25,130,91320,1,0.60,1,311,0,0,0,0,0 +2205,63,37,20,94704,2,0.40,1,76,0,0,0,0,0 +2206,63,37,101,95819,2,2.80,1,0,0,0,0,0,0 +2207,33,7,48,92831,4,2.20,2,207,0,0,0,0,0 +2208,38,12,180,90245,1,2.80,3,158,1,0,0,1,0 +2209,64,40,92,91109,2,0.00,3,185,0,1,0,1,0 +2210,36,10,33,94080,3,0.90,1,0,0,0,0,0,0 +2211,58,33,51,95006,2,1.90,2,0,0,0,0,0,0 +2212,39,14,31,92717,2,1.40,2,94,0,0,0,1,1 +2213,46,22,83,95060,1,2.70,1,0,0,0,0,1,0 +2214,61,37,45,94610,1,0.80,1,0,0,0,0,0,0 +2215,53,27,89,92735,1,0.80,3,146,0,0,0,1,1 +2216,28,3,193,94501,3,4.00,2,0,1,0,0,1,0 +2217,64,40,89,94707,1,3.80,1,0,0,0,0,0,0 +2218,48,24,162,91355,4,3.30,2,446,1,0,1,1,0 +2219,38,13,9,92634,2,0.30,2,0,0,0,0,0,0 +2220,52,22,58,93101,4,2.00,3,223,0,0,0,1,0 +2221,65,40,80,94105,1,0.80,3,0,0,0,0,1,0 +2222,59,33,73,92056,2,1.70,3,0,0,0,0,1,1 +2223,45,20,41,95008,1,0.30,1,0,0,0,0,1,0 +2224,53,28,74,91711,3,2.00,2,0,0,1,0,0,0 +2225,38,12,29,92084,2,1.40,3,0,0,0,0,1,0 +2226,54,24,25,90505,4,0.40,3,115,0,0,0,0,0 +2227,25,1,98,90717,1,5.40,1,0,0,0,0,1,0 +2228,61,35,59,90840,4,1.70,2,0,0,0,0,1,1 +2229,48,23,43,90254,4,1.90,3,0,0,0,0,1,0 +2230,46,22,72,91711,4,1.40,2,149,0,0,0,1,1 +2231,36,11,183,94704,1,3.00,3,0,1,0,1,1,1 +2232,46,20,134,94575,1,5.70,1,146,0,1,0,1,0 +2233,59,33,140,95035,2,0.50,1,262,0,0,0,1,0 +2234,59,35,39,92028,1,1.80,3,0,0,0,0,1,0 +2235,36,12,35,95812,4,0.40,2,0,0,0,0,1,0 +2236,63,37,141,92121,2,6.90,1,0,0,0,0,1,1 +2237,51,24,23,95616,1,0.50,2,0,0,0,0,1,0 +2238,30,5,134,92647,1,0.00,1,0,0,0,0,1,1 +2239,48,22,35,92709,1,1.40,3,0,0,0,0,1,0 +2240,55,29,42,95833,4,2.50,1,0,0,1,0,0,0 +2241,41,17,81,92868,4,0.20,3,167,0,1,0,0,0 +2242,26,0,14,94301,4,0.40,1,94,0,0,0,1,0 +2243,41,17,45,93437,1,1.80,1,172,0,1,0,1,0 +2244,54,28,79,91342,3,1.70,2,150,0,0,0,1,1 +2245,57,31,53,92806,1,0.80,2,120,0,0,0,0,0 +2246,54,28,33,94111,2,0.70,2,0,0,0,0,0,1 +2247,35,11,190,92093,3,3.10,2,266,1,0,0,0,0 +2248,60,34,60,95616,1,2.50,3,103,0,0,0,0,0 +2249,63,37,8,94618,1,0.80,2,97,0,0,0,1,0 +2250,41,14,38,95814,3,1.00,2,150,0,0,0,1,0 +2251,46,22,154,93109,1,5.00,1,0,0,0,0,1,0 +2252,31,5,54,92173,4,2.20,2,0,0,0,0,0,0 +2253,58,32,41,95819,3,1.40,1,0,0,0,0,1,0 +2254,59,35,25,95827,2,0.30,1,75,0,0,0,1,0 +2255,46,22,53,90025,2,1.70,1,109,0,0,0,0,0 +2256,33,9,79,94612,1,0.10,1,0,0,0,0,1,0 +2257,56,31,13,94305,4,0.90,2,76,0,0,1,1,1 +2258,47,23,130,91763,2,1.40,1,0,0,0,0,0,0 +2259,59,33,93,91320,2,0.70,2,0,0,0,0,0,0 +2260,24,0,82,90401,3,0.80,1,0,0,0,0,1,0 +2261,39,14,15,93561,2,0.30,2,92,0,0,0,0,0 +2262,30,3,150,94305,4,5.00,2,0,1,0,0,1,0 +2263,55,29,131,95070,2,0.70,2,0,1,0,0,0,1 +2264,47,21,28,92868,3,1.50,1,0,0,0,0,1,0 +2265,35,11,9,93106,4,0.70,2,0,0,0,0,1,0 +2266,47,23,88,94305,4,1.40,2,0,0,0,0,0,0 +2267,38,13,143,94550,1,4.10,1,0,0,0,0,0,0 +2268,38,13,168,92647,2,1.30,3,0,1,0,0,0,0 +2269,27,3,105,94304,1,3.00,2,0,1,1,0,0,0 +2270,42,18,62,94305,3,2.10,3,0,0,0,0,1,0 +2271,26,2,51,92103,4,2.60,1,0,0,0,0,1,0 +2272,60,34,101,94928,3,4.40,1,0,0,0,0,1,1 +2273,27,3,90,91365,3,0.80,1,0,0,0,0,1,0 +2274,27,1,83,91775,4,2.10,3,0,0,0,0,1,1 +2275,40,15,21,90034,2,0.00,3,0,0,0,0,1,0 +2276,40,16,115,94305,1,3.40,1,0,0,0,0,1,0 +2277,29,3,172,92093,4,4.40,1,0,1,0,0,0,0 +2278,30,6,32,91330,2,1.00,2,0,0,0,0,0,0 +2279,30,4,204,91107,2,4.50,1,0,0,0,0,1,0 +2280,47,23,34,91711,4,0.60,1,0,0,0,1,1,1 +2281,33,7,30,94920,2,2.00,3,132,0,0,0,0,0 +2282,57,32,31,95039,3,1.30,2,0,0,0,0,1,1 +2283,38,14,90,94110,2,2.70,1,0,0,0,0,1,1 +2284,54,28,79,92677,4,2.60,3,0,0,0,0,0,0 +2285,47,23,22,94901,4,0.60,1,0,0,0,0,1,1 +2286,48,22,114,92007,1,2.40,3,0,1,0,0,1,0 +2287,62,36,42,94122,1,0.50,3,128,0,0,0,1,0 +2288,30,6,29,92121,1,0.20,3,90,0,0,0,1,0 +2289,35,11,72,94706,3,2.60,2,0,0,0,0,1,0 +2290,59,35,68,93117,1,1.80,3,95,0,0,0,0,0 +2291,38,13,78,91942,4,0.70,3,0,0,0,0,1,0 +2292,47,23,90,95449,1,2.70,1,323,0,0,0,0,0 +2293,57,33,170,95051,2,2.10,2,0,1,0,0,0,0 +2294,42,17,14,91768,2,0.10,2,0,0,0,0,1,0 +2295,39,15,129,90035,2,1.90,1,0,0,0,0,0,0 +2296,53,23,39,92101,3,1.00,3,87,0,0,0,1,0 +2297,27,3,82,94305,2,0.20,1,0,0,0,0,0,1 +2298,59,35,31,94063,3,0.40,2,0,0,0,0,1,1 +2299,48,24,9,92630,4,0.50,2,0,0,0,0,0,1 +2300,62,37,15,94583,3,0.10,3,91,0,0,0,0,0 +2301,66,41,70,93711,3,2.20,1,0,0,0,0,0,0 +2302,38,13,84,93403,4,0.70,3,0,0,0,0,0,0 +2303,42,17,155,92806,1,7.00,1,0,0,0,0,0,1 +2304,47,21,89,94720,2,0.80,3,0,0,0,0,1,1 +2305,27,2,170,95818,3,4.70,1,0,1,0,0,1,0 +2306,32,7,185,92009,2,6.70,1,0,0,0,1,1,1 +2307,37,13,82,92373,2,2.20,1,0,0,0,0,0,0 +2308,56,31,60,92009,3,1.70,1,0,0,0,0,1,0 +2309,39,13,58,94590,2,2.40,2,0,0,0,0,1,0 +2310,36,12,29,94583,1,1.33,1,81,0,0,0,1,0 +2311,32,6,32,92806,2,0.30,1,0,0,0,0,0,0 +2312,62,37,115,90245,4,3.40,2,0,0,0,0,1,1 +2313,48,22,83,91345,2,2.40,2,0,0,0,0,1,0 +2314,58,32,54,94035,3,0.30,2,0,0,0,0,1,1 +2315,27,2,112,94501,4,1.80,3,0,0,1,0,1,0 +2316,52,26,182,95818,2,1.40,2,0,1,0,0,1,0 +2317,54,30,112,94920,2,6.80,1,0,0,0,0,1,0 +2318,31,5,129,95814,3,5.90,3,319,1,1,1,0,1 +2319,60,34,23,94803,1,0.80,2,112,0,0,0,1,0 +2320,34,9,198,95819,2,3.00,1,422,0,0,0,1,0 +2321,46,22,84,92692,4,2.00,3,0,0,0,0,1,0 +2322,41,15,39,91380,3,0.50,3,0,0,0,0,0,0 +2323,62,37,129,94143,1,1.30,1,0,0,0,0,1,0 +2324,31,7,113,94542,2,2.00,2,315,0,0,0,0,0 +2325,41,11,35,93107,1,0.75,3,114,0,0,0,1,0 +2326,55,30,85,94591,1,0.10,3,0,0,0,0,0,0 +2327,45,19,73,94086,4,2.90,1,0,0,0,0,0,0 +2328,51,25,70,90095,1,0.80,3,0,0,1,0,1,0 +2329,27,2,130,92182,3,4.40,1,192,1,0,0,1,0 +2330,30,4,39,94022,1,1.50,1,0,0,0,0,1,0 +2331,31,5,72,95133,4,1.80,2,242,0,0,0,1,1 +2332,61,37,68,90245,4,2.30,3,0,0,0,0,0,0 +2333,40,16,35,94022,1,1.40,3,0,0,0,0,1,1 +2334,45,21,61,95812,3,0.70,1,0,0,1,1,1,1 +2335,45,21,69,90025,4,1.90,1,0,0,0,0,0,0 +2336,37,13,59,93907,1,3.60,2,0,0,0,0,0,0 +2337,34,8,99,93460,2,4.50,3,217,0,0,0,0,0 +2338,43,16,201,95054,1,10.00,2,0,1,0,0,0,1 +2339,42,18,130,94611,2,7.50,1,0,0,0,0,0,1 +2340,56,31,72,90095,3,2.00,2,0,0,0,0,0,0 +2341,33,9,44,94112,1,1.20,1,0,0,0,0,0,0 +2342,36,10,91,92028,1,1.50,3,289,0,0,0,1,0 +2343,62,37,92,94608,3,0.50,1,310,0,0,0,1,0 +2344,58,34,55,90032,1,0.80,1,168,0,0,0,1,1 +2345,65,40,20,94608,3,0.50,1,102,0,0,0,1,1 +2346,65,40,89,90291,1,4.10,1,299,1,0,1,1,0 +2347,52,26,59,92660,2,1.50,2,239,0,0,0,0,1 +2348,64,39,8,92104,3,0.10,3,87,0,0,0,0,1 +2349,51,25,85,94015,4,4.90,1,0,0,0,0,1,1 +2350,59,35,94,94610,1,4.30,1,76,0,1,1,1,0 +2351,52,28,22,91711,2,0.40,1,0,0,0,0,1,1 +2352,55,31,74,94611,2,3.20,3,0,0,0,0,1,1 +2353,46,19,59,93555,3,2.67,2,0,0,0,0,0,0 +2354,61,36,12,93023,4,0.60,2,0,0,0,0,1,1 +2355,35,9,8,94043,1,0.40,2,0,0,0,0,1,0 +2356,56,31,74,94920,3,1.60,3,0,0,0,0,1,1 +2357,31,5,184,92064,4,3.40,2,0,1,0,1,1,1 +2358,44,19,34,95005,4,0.00,2,0,0,0,0,0,0 +2359,53,27,63,93109,2,0.80,3,0,0,1,0,1,0 +2360,36,12,123,95060,2,5.60,2,0,1,0,1,1,1 +2361,27,1,85,93302,2,1.60,3,0,0,0,0,0,0 +2362,36,12,109,94928,3,0.50,3,0,1,1,1,1,0 +2363,40,15,31,94720,1,0.60,3,0,0,0,0,1,0 +2364,39,13,61,90095,2,2.40,2,90,0,0,0,1,0 +2365,59,35,88,94923,2,1.60,1,0,0,0,0,0,1 +2366,43,18,22,91311,2,0.30,2,0,0,0,0,0,0 +2367,30,4,63,95008,4,2.20,2,0,0,1,0,1,0 +2368,26,1,80,95616,4,0.20,1,0,0,0,0,1,1 +2369,48,22,78,94588,3,2.10,1,0,0,0,0,1,1 +2370,50,24,45,94005,4,0.10,1,93,0,0,0,1,0 +2371,33,7,51,94040,4,2.10,3,0,0,0,0,0,1 +2372,32,6,111,95014,2,1.50,3,0,0,0,0,0,0 +2373,34,10,45,93943,3,2.80,1,153,0,0,0,1,1 +2374,33,9,184,94304,2,4.80,2,0,1,0,0,0,0 +2375,32,5,41,92008,2,1.00,2,112,0,1,0,1,0 +2376,55,30,69,91007,4,1.30,3,0,0,1,1,1,1 +2377,58,33,23,91768,3,0.20,1,0,0,0,0,0,0 +2378,47,23,160,92037,2,6.67,1,0,0,0,0,0,0 +2379,30,5,61,95605,1,0.80,2,251,0,1,1,1,0 +2380,42,18,110,94720,2,6.10,1,182,0,0,0,1,0 +2381,40,16,50,92606,2,0.60,3,0,0,0,0,0,0 +2382,33,9,49,94928,1,2.40,2,0,0,0,0,1,0 +2383,46,20,185,94131,4,7.50,2,428,1,0,0,0,1 +2384,63,39,52,90033,2,1.10,1,0,0,0,0,1,1 +2385,62,37,53,92028,2,2.80,1,0,0,0,0,1,0 +2386,43,17,125,94720,4,3.50,2,0,1,0,0,0,0 +2387,31,5,72,94542,3,1.60,1,0,0,0,0,1,0 +2388,28,2,51,94720,4,1.80,3,0,0,0,0,0,1 +2389,64,39,23,91768,3,0.50,1,0,0,1,0,0,0 +2390,27,1,41,90033,1,1.90,3,0,0,0,0,0,1 +2391,33,9,41,95814,3,2.00,1,108,0,0,0,1,0 +2392,39,12,138,92697,1,4.67,2,0,1,0,0,1,0 +2393,44,20,138,94143,2,3.30,1,0,0,0,0,0,1 +2394,53,28,14,94005,4,0.80,1,0,0,0,0,1,1 +2395,42,18,145,94065,2,8.00,1,505,0,0,0,0,0 +2396,44,17,25,95064,3,1.00,2,0,0,0,0,0,1 +2397,34,10,43,95014,1,1.70,1,142,0,0,0,0,1 +2398,47,22,93,90266,1,0.20,2,309,0,0,0,1,0 +2399,53,29,90,95053,2,0.30,1,217,0,1,0,0,1 +2400,62,36,41,90245,2,1.00,3,154,0,1,0,1,0 +2401,61,36,169,91380,2,6.10,3,106,1,0,1,1,1 +2402,42,17,63,95814,2,2.20,3,0,0,0,0,1,0 +2403,48,21,23,94720,3,0.67,2,95,0,0,0,0,0 +2404,38,13,140,90210,4,0.50,1,0,1,0,0,0,0 +2405,41,15,75,95010,1,1.50,3,0,0,0,0,1,0 +2406,57,32,13,94588,4,0.90,2,78,0,1,0,1,0 +2407,31,7,10,92354,1,0.50,3,81,0,0,0,1,0 +2408,39,15,100,94720,1,0.80,2,0,0,0,0,1,0 +2409,48,22,85,94105,3,1.10,1,203,0,0,0,1,0 +2410,55,31,73,95207,3,2.67,1,219,0,0,0,1,0 +2411,29,4,130,92630,2,6.70,1,0,0,0,0,0,1 +2412,47,22,65,91330,3,2.70,2,0,0,0,0,1,0 +2413,61,36,59,93118,4,1.70,1,148,0,0,0,0,0 +2414,60,34,31,91007,2,1.00,3,0,0,0,0,0,0 +2415,34,10,134,91775,1,4.00,1,0,0,0,0,0,0 +2416,45,21,11,94143,4,0.20,1,106,0,0,0,1,1 +2417,60,35,32,93611,1,0.30,3,80,0,0,0,1,0 +2418,25,0,53,90095,2,1.60,3,0,0,0,0,1,1 +2419,41,17,28,95616,1,0.70,1,0,0,0,0,0,1 +2420,63,37,44,94550,2,1.00,3,0,0,0,0,1,0 +2421,63,39,40,91304,1,0.80,1,118,0,0,0,0,1 +2422,43,19,40,94949,3,0.60,2,0,0,0,0,1,0 +2423,58,32,163,95014,2,0.50,1,400,0,0,0,0,0 +2424,50,25,82,91335,1,1.30,3,0,0,0,0,1,0 +2425,38,12,89,94583,4,1.40,2,0,0,0,0,0,0 +2426,54,30,78,92507,4,1.60,2,0,0,0,0,1,1 +2427,61,36,55,94132,3,0.90,3,197,0,0,0,0,0 +2428,29,5,34,92675,4,0.40,2,0,0,0,0,1,0 +2429,39,12,108,92717,4,3.67,2,301,1,0,0,0,1 +2430,33,7,58,95616,4,2.20,2,0,0,0,0,1,1 +2431,23,-1,73,92120,4,2.60,1,0,0,0,0,1,0 +2432,56,31,54,91380,4,2.10,1,0,0,0,0,1,0 +2433,54,30,45,92182,4,0.90,2,0,0,0,0,0,1 +2434,37,11,123,94720,1,2.30,2,0,1,1,1,1,0 +2435,38,12,93,95616,1,5.20,1,267,0,0,0,1,0 +2436,34,9,102,92115,4,2.20,2,0,0,0,0,1,0 +2437,53,29,39,92626,3,1.50,1,0,0,0,0,1,0 +2438,65,40,114,94608,4,3.40,2,0,0,0,0,0,1 +2439,62,37,29,91030,1,0.30,3,0,0,0,0,0,1 +2440,51,25,30,91116,3,0.60,2,144,0,0,0,0,1 +2441,31,5,22,91401,1,0.60,3,0,0,0,0,0,0 +2442,64,38,38,94305,2,0.30,1,186,0,0,0,1,1 +2443,39,15,41,90028,2,1.70,1,0,0,0,0,0,0 +2444,28,3,161,92646,4,1.70,3,422,1,0,1,1,1 +2445,60,35,38,94701,3,0.50,2,0,0,0,0,1,1 +2446,47,23,25,93106,1,0.90,3,0,0,0,0,1,0 +2447,25,1,70,93010,4,2.60,1,218,0,0,0,1,0 +2448,44,19,201,95819,2,8.80,1,0,0,0,0,1,1 +2449,51,26,42,92103,2,0.60,3,0,0,0,0,1,1 +2450,31,7,64,94720,1,1.20,1,0,0,0,0,1,0 +2451,32,7,28,90034,4,1.10,3,0,0,0,0,0,0 +2452,51,25,119,93940,1,4.90,1,208,0,0,0,1,1 +2453,25,1,28,94596,1,1.00,3,0,0,0,0,1,0 +2454,43,19,60,94104,3,2.10,3,0,0,0,0,1,0 +2455,54,29,23,93955,1,1.50,2,0,0,0,0,0,0 +2456,34,8,164,94720,4,7.40,3,0,1,0,0,1,0 +2457,54,30,39,95211,2,0.80,1,0,0,0,0,0,1 +2458,42,17,19,92115,2,0.00,3,85,0,0,0,1,1 +2459,46,20,72,93108,2,0.80,3,0,0,0,0,1,1 +2460,62,37,41,95060,3,0.90,3,0,0,0,0,1,1 +2461,31,5,32,92123,2,0.30,2,130,0,0,0,1,0 +2462,30,5,69,94302,1,0.80,2,0,0,0,0,1,0 +2463,52,28,23,95828,3,0.40,1,0,0,0,0,1,0 +2464,35,9,44,92009,4,0.20,1,0,0,0,0,1,0 +2465,60,36,32,92407,3,0.40,2,165,0,0,0,1,0 +2466,58,34,25,90059,2,0.30,1,123,0,0,0,1,0 +2467,24,-2,80,94105,2,1.60,3,0,0,0,0,1,0 +2468,40,16,83,92350,1,0.80,2,230,0,1,0,1,0 +2469,49,23,133,94304,1,7.30,1,0,0,0,0,1,1 +2470,43,18,89,92780,1,0.10,2,307,0,0,0,0,1 +2471,33,7,81,92122,2,4.50,3,187,0,0,1,1,1 +2472,36,11,44,91040,2,1.10,2,85,0,0,0,1,0 +2473,62,36,119,94720,2,2.00,1,0,0,0,0,0,0 +2474,57,32,39,92182,4,0.90,1,147,0,0,0,0,0 +2475,64,38,40,92122,2,1.00,3,0,0,0,0,0,0 +2476,52,26,79,95817,3,0.80,1,183,0,0,0,0,0 +2477,54,28,30,95616,4,0.70,2,0,0,0,0,1,0 +2478,40,14,179,90025,1,2.60,3,0,1,0,0,1,0 +2479,30,5,178,94063,2,6.70,1,0,0,0,0,0,0 +2480,55,30,82,94720,4,3.80,2,0,0,0,0,1,0 +2481,39,13,50,91768,2,2.40,2,0,0,0,0,0,0 +2482,55,30,64,94306,2,1.90,2,0,0,0,0,0,0 +2483,28,4,129,92115,1,1.50,1,0,0,0,0,0,1 +2484,44,18,68,93943,4,2.90,1,0,0,1,0,0,0 +2485,46,21,30,92697,1,1.40,3,112,0,1,0,0,0 +2486,61,36,48,94025,3,1.50,1,0,0,0,0,0,1 +2487,61,36,130,92717,1,1.30,1,257,0,0,0,0,0 +2488,45,20,40,92886,1,0.50,3,0,0,1,0,1,0 +2489,38,14,105,94708,2,1.90,1,0,0,0,0,1,0 +2490,29,3,41,92626,4,0.20,1,0,0,0,0,1,0 +2491,52,28,168,90404,3,6.50,3,118,1,0,0,1,0 +2492,38,14,80,92868,2,2.70,1,0,0,0,0,1,0 +2493,28,3,134,96091,2,3.10,1,0,0,0,0,1,0 +2494,34,9,49,94025,1,2.50,3,0,0,0,0,0,0 +2495,35,9,63,92697,2,1.80,1,0,0,0,0,1,0 +2496,46,22,70,94701,4,1.90,1,212,0,0,0,0,1 +2497,63,37,32,93117,3,0.70,2,141,0,0,0,0,0 +2498,33,9,14,95133,3,0.90,3,114,0,0,0,0,0 +2499,38,14,111,92028,2,6.10,1,326,0,0,0,0,0 +2500,53,27,38,94105,4,2.80,2,144,0,1,0,1,0 +2501,28,2,121,92096,2,2.00,1,341,0,0,0,1,0 +2502,44,18,90,95616,4,2.60,3,0,0,0,0,1,0 +2503,58,31,178,92009,2,6.00,2,0,1,0,0,1,0 +2504,38,14,20,94024,4,0.40,2,79,0,0,0,1,1 +2505,48,24,61,91380,2,1.70,1,229,0,0,0,0,1 +2506,33,7,43,96064,4,0.80,1,0,0,0,0,0,0 +2507,66,42,39,94590,1,1.90,2,0,0,0,0,1,1 +2508,59,34,60,90048,4,2.10,1,234,0,0,0,1,1 +2509,40,15,63,93407,3,3.00,1,0,0,1,0,1,0 +2510,36,11,8,93401,4,0.20,3,81,0,0,0,0,1 +2511,62,38,52,95616,4,1.30,2,0,0,0,0,1,1 +2512,51,27,92,92121,4,3.00,1,0,1,0,1,1,1 +2513,58,32,111,90212,2,1.40,1,298,0,0,0,1,0 +2514,52,26,71,92037,1,1.40,3,0,0,0,0,0,0 +2515,41,16,25,92182,2,0.10,2,91,0,1,0,0,0 +2516,31,5,34,94558,1,1.90,3,156,0,0,0,1,0 +2517,28,3,74,94720,3,2.60,3,0,0,0,0,0,0 +2518,57,31,120,95616,2,2.00,1,0,0,0,0,0,1 +2519,61,37,50,95125,4,1.30,2,0,0,0,0,0,1 +2520,60,36,10,92121,2,1.00,1,0,0,0,0,1,1 +2521,56,29,45,90095,4,2.50,2,113,0,0,0,1,0 +2522,49,23,29,94551,4,1.80,1,0,0,0,0,1,1 +2523,63,37,145,94025,2,6.90,1,0,0,0,0,1,0 +2524,49,23,100,95403,2,6.30,1,0,0,0,0,0,0 +2525,49,25,24,95678,3,0.40,1,0,0,0,0,1,0 +2526,32,8,60,95816,1,1.20,1,0,0,0,0,1,1 +2527,26,1,50,95616,4,0.60,2,0,0,0,0,0,0 +2528,27,1,43,95120,3,1.10,2,0,0,0,0,0,0 +2529,57,31,79,91335,3,4.40,1,0,0,0,0,0,1 +2530,29,5,44,95819,3,0.10,2,0,0,0,0,1,1 +2531,56,30,31,90024,4,1.50,3,0,0,0,0,1,0 +2532,59,35,14,94305,2,1.00,1,107,0,0,0,1,0 +2533,53,28,19,94608,4,0.80,1,106,0,0,0,0,1 +2534,54,29,111,93023,1,1.10,2,0,1,0,0,1,0 +2535,56,30,90,94402,1,1.90,2,0,0,0,0,1,0 +2536,50,25,21,90274,2,0.70,3,129,0,0,0,0,0 +2537,51,25,104,94949,1,4.20,2,0,1,0,0,1,0 +2538,53,27,75,94303,1,1.90,2,0,0,0,0,1,0 +2539,37,12,175,92037,2,7.80,1,297,0,0,0,1,1 +2540,32,7,98,95929,1,4.20,1,171,1,1,1,0,0 +2541,49,23,41,95521,4,0.10,1,153,0,0,0,1,0 +2542,34,8,171,90212,2,2.20,2,569,1,0,0,1,0 +2543,54,30,79,92630,4,1.60,2,0,0,0,0,1,0 +2544,64,39,24,94117,4,0.60,2,0,0,0,0,0,0 +2545,58,34,90,95039,1,3.60,2,0,1,0,0,0,0 +2546,25,-1,39,94720,3,2.40,2,0,0,0,0,1,0 +2547,50,25,9,91911,2,0.00,1,0,0,1,0,0,0 +2548,38,13,15,90245,2,0.10,2,90,0,0,0,1,0 +2549,48,24,80,91343,1,2.70,1,0,0,0,0,1,0 +2550,41,15,63,95060,1,0.70,3,79,0,0,0,0,1 +2551,32,8,20,93106,1,0.50,3,102,0,0,0,1,0 +2552,46,22,43,92120,2,2.10,3,0,0,1,1,1,1 +2553,39,15,65,95822,1,1.50,3,0,0,0,0,0,0 +2554,39,15,91,93907,2,1.70,2,151,0,0,0,0,0 +2555,63,39,53,93940,1,0.80,1,0,0,0,0,0,0 +2556,58,32,110,94143,3,1.70,2,0,0,0,0,0,0 +2557,28,4,82,92831,3,1.50,1,103,0,0,0,1,0 +2558,36,11,23,94553,4,0.20,3,0,0,0,0,1,0 +2559,43,19,172,95136,2,6.67,1,0,0,0,0,1,0 +2560,36,12,88,90212,2,2.70,1,0,0,0,0,1,0 +2561,44,18,71,93943,2,0.80,3,0,0,0,0,1,0 +2562,31,5,180,94720,1,2.90,3,144,1,1,0,0,0 +2563,45,21,39,92521,2,2.10,3,184,0,0,0,0,1 +2564,39,13,94,90401,1,1.50,3,0,0,0,0,0,1 +2565,43,16,25,94126,3,1.00,2,0,0,0,0,1,0 +2566,40,15,10,94708,2,0.00,3,102,0,0,0,1,0 +2567,30,5,42,94305,1,1.00,1,184,0,0,0,0,0 +2568,58,33,142,92333,2,3.90,1,0,0,0,0,0,1 +2569,46,21,34,92373,2,1.30,1,0,0,0,0,1,0 +2570,35,10,139,90024,1,4.60,1,0,0,0,0,0,0 +2571,30,4,154,95621,2,4.50,1,207,0,0,0,1,0 +2572,34,8,40,91768,2,2.00,3,89,0,0,0,0,0 +2573,62,32,33,93907,1,1.50,3,140,0,0,0,1,1 +2574,58,34,80,90095,2,1.60,1,0,0,0,0,1,1 +2575,45,18,10,92037,3,0.67,2,100,0,0,0,1,0 +2576,42,16,41,90401,3,0.50,3,0,0,0,0,1,0 +2577,60,36,30,93711,4,1.30,1,118,0,0,0,1,1 +2578,55,29,78,95521,1,0.80,3,190,0,0,0,1,0 +2579,45,21,164,90638,1,5.00,1,0,0,0,0,0,1 +2580,52,27,23,92780,1,0.40,3,0,0,0,0,0,0 +2581,31,7,149,92624,1,6.00,1,0,0,0,0,0,0 +2582,60,34,25,94132,4,0.70,3,0,0,0,0,1,0 +2583,33,9,42,95010,1,2.10,3,0,0,0,0,1,0 +2584,37,11,71,91302,1,2.50,1,185,0,0,0,1,1 +2585,59,34,114,94606,3,4.20,2,0,1,0,0,1,0 +2586,51,26,70,91320,1,2.80,2,0,0,0,0,1,1 +2587,47,23,149,92675,4,6.10,1,0,1,0,0,0,1 +2588,60,33,55,94998,4,2.50,2,0,0,0,0,1,0 +2589,61,36,29,93065,1,1.30,1,0,0,0,0,0,0 +2590,64,40,123,90840,1,3.80,1,0,0,0,0,1,1 +2591,46,20,152,95814,1,7.40,3,374,1,0,1,1,1 +2592,31,7,8,95131,4,0.70,2,0,0,0,0,0,0 +2593,57,32,69,94710,4,0.70,1,245,0,0,0,0,0 +2594,48,23,161,96003,4,7.90,3,310,1,0,0,0,0 +2595,48,23,79,94024,1,0.20,2,0,0,0,0,0,0 +2596,35,10,105,92780,1,4.60,1,0,0,0,0,0,0 +2597,33,8,39,95032,3,2.30,1,0,0,0,0,0,0 +2598,47,23,163,92653,1,5.00,1,0,0,0,0,0,0 +2599,46,20,9,94005,1,0.20,1,0,0,0,0,1,0 +2600,44,20,71,91006,4,2.00,3,0,0,0,0,0,1 +2601,42,18,51,92868,3,2.10,3,0,0,0,0,0,0 +2602,50,24,32,90277,1,1.40,3,167,0,0,0,0,0 +2603,52,26,161,93108,4,4.30,1,0,1,0,1,1,1 +2604,53,27,60,90049,1,0.20,1,0,0,0,0,1,0 +2605,37,10,35,92521,4,1.00,2,0,0,0,0,0,0 +2606,64,40,41,94305,4,1.20,2,0,0,0,0,1,0 +2607,46,22,73,92648,2,1.70,1,216,0,0,0,1,0 +2608,57,33,49,94305,4,1.50,1,214,0,1,1,1,1 +2609,61,35,79,94024,2,2.00,1,194,0,0,0,1,1 +2610,42,18,120,93407,2,7.50,1,0,0,1,0,0,0 +2611,40,16,60,94501,2,3.20,1,0,0,0,0,0,0 +2612,33,8,78,95051,3,0.60,2,0,0,0,0,1,0 +2613,50,26,40,95138,4,1.10,2,131,0,0,0,0,0 +2614,52,26,110,94501,2,5.40,3,204,1,1,1,1,0 +2615,35,11,160,92093,4,5.70,3,0,1,1,0,0,0 +2616,57,32,68,94542,4,0.70,1,191,0,0,0,1,1 +2617,56,31,49,92182,2,1.60,3,103,0,0,0,1,0 +2618,44,20,65,92037,2,2.50,1,0,0,0,0,1,0 +2619,23,-3,55,92704,3,2.40,2,145,0,0,0,1,0 +2620,33,8,62,92093,3,2.30,1,98,0,0,0,0,1 +2621,48,22,152,95616,1,0.00,1,0,0,0,0,0,0 +2622,45,18,42,95126,3,2.50,2,0,0,0,0,0,0 +2623,54,28,39,90245,4,0.70,2,0,0,0,0,1,0 +2624,42,17,111,94304,3,3.00,1,0,1,1,1,0,1 +2625,47,21,82,94109,3,2.10,1,0,0,0,0,0,0 +2626,61,36,108,93943,4,3.40,2,0,0,0,0,1,0 +2627,53,27,59,92038,2,0.80,3,0,0,0,0,1,0 +2628,56,30,61,93106,3,2.50,1,193,0,0,0,1,0 +2629,33,6,78,95819,4,2.00,2,0,0,1,0,1,0 +2630,44,18,18,93943,2,0.10,3,0,0,0,0,1,0 +2631,63,37,113,94611,4,1.70,3,0,0,0,0,1,1 +2632,47,20,62,92521,1,2.67,2,0,0,0,0,1,0 +2633,50,24,81,94720,1,4.90,1,248,0,0,0,1,0 +2634,49,25,13,95054,3,0.40,1,106,0,0,0,1,0 +2635,34,9,75,94303,1,2.80,1,194,0,0,0,0,0 +2636,40,14,33,95616,2,0.80,3,89,0,0,0,1,0 +2637,38,13,179,93943,1,4.10,1,0,0,0,0,1,0 +2638,51,26,69,94005,3,2.00,2,0,0,0,0,1,0 +2639,28,4,45,94025,1,1.00,3,0,0,0,0,1,0 +2640,52,26,59,95762,3,3.00,2,0,0,0,0,1,0 +2641,39,13,81,94309,2,2.80,1,0,0,0,0,1,0 +2642,29,5,133,90095,1,5.40,1,212,0,0,0,1,0 +2643,54,29,81,92096,2,0.00,3,0,0,0,0,1,0 +2644,63,38,14,92630,4,0.40,2,86,0,0,0,1,1 +2645,40,14,28,94061,2,0.80,3,0,0,0,0,0,0 +2646,36,12,93,95125,2,2.20,1,0,0,0,0,1,0 +2647,45,20,191,92007,3,2.60,3,123,1,0,0,0,0 +2648,61,37,155,91605,1,2.90,1,0,0,0,0,1,0 +2649,26,0,155,93105,2,7.20,1,0,0,0,0,0,0 +2650,33,8,68,92407,4,1.30,1,0,0,0,0,1,0 +2651,64,40,52,95060,2,1.10,1,226,0,0,0,0,0 +2652,43,17,51,94025,1,0.70,3,0,0,0,0,0,0 +2653,24,0,44,90089,4,1.60,1,180,0,0,0,1,0 +2654,30,5,121,94555,2,3.10,1,408,0,0,0,1,0 +2655,60,36,49,94965,4,2.20,1,204,0,1,0,1,0 +2656,50,26,42,91784,2,1.00,3,78,0,1,0,1,0 +2657,40,15,144,91040,1,4.10,1,0,0,0,0,0,0 +2658,31,6,72,94583,1,2.60,2,0,0,0,0,1,0 +2659,30,4,44,94304,1,1.50,1,109,0,0,0,0,0 +2660,60,35,43,91763,3,0.90,3,175,0,0,0,0,0 +2661,39,14,74,93063,1,0.10,2,144,0,1,0,1,0 +2662,66,41,145,90009,1,2.50,1,0,0,0,0,1,0 +2663,65,41,158,92346,2,2.10,1,0,0,0,0,0,0 +2664,54,28,78,91311,4,4.90,1,0,0,0,0,0,0 +2665,54,29,154,95014,1,2.40,2,352,1,0,0,1,0 +2666,35,9,105,90064,2,4.50,3,0,0,0,0,0,0 +2667,32,7,100,92126,3,0.60,2,0,0,0,0,1,0 +2668,63,39,58,94112,1,0.00,2,0,0,0,0,1,0 +2669,60,35,113,94507,1,0.90,1,406,0,0,0,1,0 +2670,43,18,10,91902,2,0.10,2,0,0,1,0,0,1 +2671,59,33,142,94080,2,2.70,1,0,0,0,0,0,0 +2672,62,37,128,92093,1,2.50,1,0,0,0,0,0,0 +2673,30,5,131,92068,3,0.50,3,0,1,0,0,0,0 +2674,54,30,88,92647,4,1.00,2,122,0,0,0,1,0 +2675,30,6,101,90245,2,0.60,1,0,0,0,0,1,0 +2676,31,1,70,92115,2,1.75,3,0,0,0,1,1,1 +2677,44,20,122,91765,1,0.30,1,0,0,1,0,1,0 +2678,32,8,70,91423,3,1.50,1,0,0,0,0,1,0 +2679,63,38,148,93023,2,4.30,3,0,1,0,0,1,0 +2680,57,32,43,92704,2,2.10,3,166,0,0,0,1,0 +2681,60,30,31,95060,1,1.50,3,0,0,0,0,1,0 +2682,37,11,35,94609,2,0.80,3,0,0,0,0,0,0 +2683,53,27,81,90032,4,2.60,3,0,0,0,0,1,0 +2684,51,25,19,95812,1,1.40,3,98,0,0,0,0,0 +2685,30,5,98,92028,4,1.80,3,129,0,1,1,1,1 +2686,28,2,101,90280,4,2.10,3,0,0,0,0,1,0 +2687,50,24,81,95053,2,0.40,3,0,0,0,0,0,0 +2688,52,27,135,93561,1,0.60,1,452,0,0,0,1,0 +2689,56,30,34,94542,2,0.70,2,0,0,0,0,1,0 +2690,40,16,104,91730,1,3.40,1,249,0,0,0,0,0 +2691,64,38,29,90245,3,0.70,2,0,0,0,0,1,0 +2692,61,36,119,95064,2,5.40,2,0,1,0,0,1,0 +2693,46,20,82,90230,2,1.70,2,0,0,0,0,1,1 +2694,55,29,62,90089,1,0.20,1,0,0,0,0,1,0 +2695,45,19,85,94720,3,2.10,1,0,0,0,0,1,1 +2696,40,15,8,94960,2,0.10,2,0,0,0,0,0,0 +2697,63,37,78,91711,4,1.70,3,0,0,0,0,1,0 +2698,57,32,44,93407,3,0.50,2,0,0,0,0,1,0 +2699,38,14,122,95819,2,8.00,1,0,0,0,0,1,1 +2700,37,11,22,90035,3,0.10,2,114,0,0,0,0,0 +2701,31,5,39,94590,4,2.20,2,0,0,0,0,1,1 +2702,50,26,55,94305,1,1.60,2,0,0,0,0,1,0 +2703,42,18,144,94063,2,6.10,1,158,0,0,0,0,0 +2704,51,27,71,92521,1,2.60,2,0,0,0,0,0,1 +2705,38,13,191,91710,2,3.00,1,0,0,0,0,1,0 +2706,53,26,22,92831,1,0.50,2,100,0,0,0,1,0 +2707,43,17,158,90740,1,2.40,1,0,0,0,0,1,0 +2708,35,9,131,90089,3,0.30,3,0,1,0,1,1,1 +2709,49,24,75,95670,1,2.80,2,160,0,0,0,0,1 +2710,28,4,69,94305,3,0.70,2,170,0,0,0,0,0 +2711,51,27,39,94304,2,0.80,1,0,0,0,0,0,0 +2712,39,14,34,94939,4,1.70,1,0,0,0,0,1,1 +2713,31,7,32,91320,1,1.70,1,0,0,0,0,1,0 +2714,44,18,129,92028,1,5.70,1,0,0,0,0,1,0 +2715,46,20,158,92870,3,5.40,1,432,1,0,0,0,1 +2716,42,18,54,90089,1,1.80,1,0,0,0,0,1,0 +2717,41,17,34,92182,1,2.00,2,0,0,0,0,0,0 +2718,23,-2,45,95422,4,0.60,2,0,0,0,0,1,1 +2719,59,33,68,95064,2,2.30,3,0,0,1,0,0,0 +2720,47,21,53,95929,1,1.50,2,0,0,0,0,1,0 +2721,48,23,32,93302,1,0.10,1,0,0,0,0,0,1 +2722,58,33,173,92121,2,7.20,3,0,1,0,0,1,0 +2723,58,34,31,92126,4,0.40,1,0,0,0,0,0,0 +2724,54,29,72,94558,2,3.70,1,144,0,0,0,1,0 +2725,49,24,30,90212,4,0.40,2,157,0,0,1,1,1 +2726,63,38,138,92675,1,2.50,1,0,0,0,0,1,0 +2727,62,37,18,92028,1,1.50,2,127,0,0,0,0,0 +2728,45,19,69,90840,1,2.80,1,220,0,0,0,1,1 +2729,39,13,58,94555,3,2.10,1,247,0,0,0,1,0 +2730,58,34,63,90007,4,1.50,1,0,0,0,0,1,0 +2731,56,30,43,90401,2,0.30,1,0,0,1,0,0,0 +2732,29,5,28,96651,1,0.20,3,0,0,0,0,1,0 +2733,33,9,38,93106,1,2.10,3,133,0,0,0,0,0 +2734,55,29,72,93107,3,0.30,2,147,0,0,0,0,0 +2735,56,31,64,94126,4,0.90,1,0,0,0,0,1,0 +2736,36,12,70,92131,3,2.60,2,165,0,0,0,1,0 +2737,53,29,12,95621,1,0.30,1,0,0,0,0,0,0 +2738,57,31,159,94577,2,0.50,1,0,0,0,0,0,0 +2739,35,9,103,95120,2,4.50,3,0,0,0,0,1,0 +2740,43,18,42,91330,1,0.30,3,0,0,0,0,1,0 +2741,54,29,48,92182,2,2.10,3,142,0,0,0,1,0 +2742,29,3,49,90266,1,1.50,1,0,0,0,0,0,0 +2743,39,14,89,95762,2,0.40,1,0,0,0,0,1,0 +2744,32,8,22,94583,4,0.70,2,0,0,0,0,1,1 +2745,51,27,10,92121,2,0.20,1,86,0,0,0,0,0 +2746,50,25,38,95616,1,1.30,2,120,0,0,0,0,1 +2747,54,29,49,92703,2,2.10,3,95,0,0,0,1,1 +2748,38,12,30,91765,2,1.40,3,0,0,0,0,0,1 +2749,32,7,82,94305,1,2.60,2,240,0,0,1,1,1 +2750,62,37,82,94086,1,0.80,3,312,0,0,0,1,0 +2751,57,33,24,94501,1,0.10,2,0,0,0,0,0,0 +2752,47,23,32,92251,4,0.60,1,156,0,0,0,1,1 +2753,51,25,34,95819,3,0.90,3,111,0,0,0,1,0 +2754,54,27,195,93117,2,4.75,2,477,1,0,0,0,0 +2755,26,1,61,93943,4,2.20,1,119,0,0,0,0,0 +2756,37,11,22,93711,3,0.10,2,0,0,0,0,1,1 +2757,27,0,40,91301,4,1.00,3,0,0,0,0,1,0 +2758,63,38,50,93943,2,2.80,1,205,0,0,0,0,0 +2759,62,36,35,94501,2,0.70,3,0,0,1,0,0,1 +2760,59,33,64,95617,3,0.30,2,0,0,0,0,0,0 +2761,32,7,49,94080,3,2.30,1,0,0,0,0,1,0 +2762,35,8,44,95045,4,1.00,2,192,0,0,0,0,1 +2763,56,31,65,93403,2,3.70,1,0,0,0,0,1,0 +2764,55,31,13,93943,4,0.70,1,0,0,0,0,1,0 +2765,31,5,84,91320,1,2.90,3,105,0,0,0,0,1 +2766,54,29,28,92093,4,0.20,2,101,0,0,0,1,0 +2767,58,32,108,95123,3,4.40,1,0,0,0,0,1,0 +2768,48,24,59,90401,1,0.00,1,144,0,0,0,1,0 +2769,48,22,163,95819,1,2.40,1,396,0,0,0,1,0 +2770,33,9,183,91320,2,8.80,3,582,1,0,0,1,0 +2771,36,6,69,90024,4,4.00,3,0,0,0,0,1,0 +2772,41,16,115,92333,1,7.00,1,0,0,0,0,0,0 +2773,55,31,130,92646,4,6.50,1,0,1,0,0,0,1 +2774,63,37,185,94309,2,7.90,2,358,1,0,0,1,0 +2775,53,29,118,94066,2,0.30,1,0,0,0,0,1,0 +2776,38,13,163,95039,1,4.10,1,0,0,0,0,0,0 +2777,46,20,140,93106,2,6.30,1,380,0,0,0,1,1 +2778,59,33,91,94122,2,0.70,2,0,0,0,0,1,1 +2779,56,31,61,92646,4,1.30,3,0,0,0,0,1,1 +2780,59,35,168,95521,4,4.10,2,0,1,0,0,1,0 +2781,39,13,69,90630,3,0.90,2,0,0,0,0,0,0 +2782,47,21,22,92037,1,0.20,1,104,0,0,0,0,0 +2783,47,22,53,92691,1,0.30,1,213,0,0,0,0,0 +2784,53,26,25,92123,2,1.00,2,0,0,0,1,1,1 +2785,36,9,115,91765,4,2.20,2,0,1,0,0,0,0 +2786,34,9,31,92521,4,1.10,3,85,0,1,1,1,1 +2787,36,10,83,94705,1,2.80,3,0,0,0,0,0,1 +2788,60,34,152,92807,2,6.90,1,0,0,0,0,0,0 +2789,45,20,30,96003,1,0.10,1,0,0,0,0,1,0 +2790,27,3,34,90065,1,0.20,3,0,0,0,0,1,1 +2791,47,22,44,95821,1,1.40,3,0,0,0,0,1,1 +2792,44,20,182,94710,2,7.60,1,0,0,0,0,0,0 +2793,54,30,44,95616,3,1.50,1,117,0,0,0,1,0 +2794,57,33,122,94301,2,6.00,1,153,0,1,1,1,1 +2795,52,26,35,94550,4,1.80,1,0,0,0,0,1,0 +2796,51,25,91,92407,1,0.80,3,0,0,0,0,0,0 +2797,57,32,30,94024,2,2.00,2,0,0,0,0,0,0 +2798,65,39,53,94608,1,2.50,3,0,0,0,0,1,0 +2799,58,33,28,94720,1,0.30,3,0,0,0,0,1,0 +2800,64,39,85,94720,4,3.40,2,200,0,0,0,1,0 +2801,52,26,28,93907,2,0.70,2,90,0,0,0,1,1 +2802,58,34,41,91016,4,0.40,1,177,0,0,0,1,0 +2803,52,22,154,90650,1,5.00,3,0,1,1,1,1,0 +2804,43,18,41,92831,1,0.30,3,0,0,0,0,1,0 +2805,56,32,33,95014,3,1.50,1,0,0,0,0,0,0 +2806,37,12,182,94523,3,5.80,3,0,1,0,0,1,0 +2807,53,27,59,90740,2,0.80,3,0,0,0,0,1,0 +2808,27,2,129,90009,2,3.30,1,0,0,1,0,0,0 +2809,53,27,35,94583,3,0.90,3,136,0,0,0,1,0 +2810,42,16,185,94705,3,2.20,2,0,1,1,1,1,1 +2811,58,34,45,93943,4,1.30,2,201,0,0,0,0,0 +2812,36,12,62,94065,4,0.10,2,145,0,0,0,0,0 +2813,53,28,183,96008,3,8.20,3,467,1,0,1,1,1 +2814,48,22,14,94303,2,0.10,3,0,0,0,0,1,0 +2815,54,28,53,94002,1,2.20,3,0,0,0,0,1,1 +2816,26,1,48,94019,3,2.60,3,169,0,0,0,0,0 +2817,50,26,128,92780,2,0.40,1,0,0,0,0,1,0 +2818,31,7,105,94025,1,4.00,1,331,0,0,0,1,0 +2819,35,9,40,93943,3,0.90,1,0,0,0,0,1,1 +2820,63,37,10,90095,2,0.40,1,0,0,0,0,1,0 +2821,29,4,102,90245,2,3.30,1,303,0,0,0,0,0 +2822,57,32,31,94143,3,0.10,2,0,0,0,0,1,0 +2823,30,5,30,90245,4,0.80,1,158,0,0,0,1,0 +2824,33,7,21,90095,1,0.60,3,0,0,1,0,0,0 +2825,62,36,44,92867,2,0.30,1,0,0,0,0,0,0 +2826,35,10,48,95060,1,2.50,3,164,0,0,0,1,0 +2827,37,11,21,94604,3,0.20,2,0,0,0,0,1,0 +2828,37,11,84,90266,4,2.20,2,0,0,0,0,1,1 +2829,35,10,64,94306,3,0.70,2,230,0,0,0,1,0 +2830,35,9,82,94720,1,2.50,1,138,0,0,0,0,0 +2831,59,35,39,95616,4,1.30,1,0,0,0,0,1,0 +2832,53,27,45,90405,2,0.80,3,0,0,0,0,1,1 +2833,45,21,133,92056,4,5.70,3,0,1,0,1,1,1 +2834,46,22,152,90009,2,1.40,1,0,0,0,0,1,0 +2835,40,16,12,90033,1,1.00,1,91,0,1,0,0,0 +2836,42,16,32,94112,3,1.50,1,149,0,0,0,1,0 +2837,25,1,74,94085,4,2.60,1,204,0,0,0,0,0 +2838,39,14,54,92037,2,1.10,2,159,0,0,0,0,1 +2839,30,6,181,94542,3,4.10,2,0,1,0,1,1,1 +2840,58,33,75,90034,2,0.00,3,0,0,0,0,1,0 +2841,41,15,95,91101,3,0.10,1,240,0,1,0,0,0 +2842,37,11,190,94305,4,7.30,2,565,1,0,1,1,0 +2843,36,11,90,94709,1,2.80,1,0,0,0,0,1,0 +2844,27,3,20,95616,4,1.00,1,134,0,0,0,1,1 +2845,60,34,64,95014,3,2.20,3,0,0,0,0,0,0 +2846,62,36,85,90019,2,1.70,3,98,0,0,0,0,0 +2847,67,43,105,93711,4,1.70,2,0,0,0,0,1,0 +2848,44,18,21,90840,1,0.20,1,0,0,0,0,1,0 +2849,24,-1,78,94720,2,1.80,2,0,0,0,0,0,0 +2850,45,21,158,94085,2,6.67,1,132,0,0,0,1,1 +2851,58,34,125,94720,1,4.30,1,219,0,0,0,0,0 +2852,61,36,81,95449,3,1.80,2,0,0,0,0,1,0 +2853,54,29,183,93105,1,8.10,1,0,0,0,0,1,1 +2854,28,3,54,94550,4,0.60,2,0,0,0,0,1,0 +2855,49,24,79,94025,4,3.60,3,212,0,0,0,1,0 +2856,35,11,38,91706,1,1.50,2,136,0,0,0,1,0 +2857,36,10,172,94704,4,1.00,2,295,1,0,0,1,0 +2858,34,8,184,93106,3,7.50,1,0,1,0,0,0,0 +2859,36,11,158,95054,2,7.80,1,114,0,0,0,1,1 +2860,35,11,188,94596,1,0.90,3,282,1,0,0,1,0 +2861,27,2,20,95064,4,0.50,3,0,0,0,0,1,0 +2862,42,18,60,92677,4,0.20,3,151,0,0,0,0,1 +2863,65,39,113,92096,4,2.40,3,0,0,0,0,1,0 +2864,29,5,70,93101,4,0.00,1,0,0,0,0,1,1 +2865,65,41,84,95762,2,0.00,3,0,0,0,0,1,1 +2866,59,33,23,94002,2,0.20,3,0,0,0,0,1,0 +2867,46,22,141,90089,2,3.30,1,0,0,1,1,1,1 +2868,59,33,110,90007,3,4.40,1,264,0,0,0,1,0 +2869,52,26,31,94923,4,1.80,1,0,0,0,0,1,1 +2870,60,35,22,92660,1,1.30,1,80,0,0,0,0,0 +2871,43,17,91,95134,1,5.20,1,0,0,1,0,0,0 +2872,65,39,82,94131,4,2.40,3,252,0,0,0,1,0 +2873,50,26,23,92630,1,0.30,1,0,0,0,0,0,0 +2874,48,23,35,93943,1,0.10,1,0,0,1,0,1,0 +2875,49,25,114,91380,1,2.50,3,0,1,0,0,1,0 +2876,58,33,18,94402,3,0.10,2,0,0,0,0,1,1 +2877,24,-2,80,91107,2,1.60,3,238,0,0,0,0,0 +2878,58,32,74,95817,2,2.30,3,0,0,0,0,0,1 +2879,45,19,122,94590,4,4.10,2,0,1,0,0,1,0 +2880,42,15,73,94545,3,2.33,2,0,0,0,0,0,0 +2881,64,40,40,96064,2,1.10,1,0,0,0,0,1,0 +2882,49,25,55,92103,4,0.10,3,0,0,0,0,1,0 +2883,55,31,69,90089,1,2.70,2,0,0,1,0,0,1 +2884,40,14,92,90024,4,1.40,2,0,0,0,0,1,0 +2885,28,2,48,93943,4,2.10,3,0,0,0,0,1,1 +2886,57,31,113,91711,4,0.60,3,327,1,0,0,1,0 +2887,50,25,58,93940,1,1.30,2,0,0,0,0,1,0 +2888,40,16,109,94025,2,2.20,1,0,0,0,0,1,0 +2889,55,28,39,94542,3,1.00,2,0,0,0,0,1,1 +2890,53,29,33,94591,3,1.90,2,144,0,0,0,0,0 +2891,48,24,18,94304,4,0.20,1,0,0,0,0,1,1 +2892,59,33,63,90044,1,1.60,1,0,0,0,0,1,1 +2893,58,32,43,92093,1,2.80,2,0,0,0,0,1,0 +2894,38,14,70,94022,4,2.00,3,0,0,0,0,1,0 +2895,49,25,19,94545,1,0.90,3,0,0,0,0,0,0 +2896,60,36,39,94501,4,1.30,2,140,0,0,0,1,0 +2897,54,28,81,94720,3,0.80,1,0,0,0,0,0,0 +2898,28,2,34,92161,4,1.30,3,0,0,0,0,0,0 +2899,27,1,140,91711,1,5.90,2,175,1,1,1,1,0 +2900,42,18,114,94305,1,0.30,1,0,0,0,0,0,0 +2901,52,28,55,91320,2,3.20,3,151,0,0,0,0,0 +2902,54,30,21,95351,1,0.10,2,76,0,0,0,1,0 +2903,56,30,50,94022,4,2.80,2,0,0,1,0,1,0 +2904,58,34,41,95833,3,1.50,1,0,0,0,0,1,1 +2905,56,32,190,90032,3,2.20,1,0,1,0,1,1,0 +2906,64,40,8,94110,2,0.30,3,0,0,0,0,1,0 +2907,35,8,55,92870,2,1.67,2,0,0,0,0,1,0 +2908,45,20,40,91763,2,1.30,1,0,0,0,0,0,1 +2909,57,32,22,95616,3,0.10,2,0,0,0,0,1,0 +2910,35,8,44,94590,2,1.67,2,0,0,1,0,0,1 +2911,46,22,102,95039,3,4.50,3,0,1,0,0,1,0 +2912,30,4,54,93033,4,1.80,3,235,0,0,0,1,0 +2913,44,20,130,90291,4,3.20,2,0,1,0,0,0,0 +2914,39,12,75,94501,3,2.33,2,0,0,0,0,1,1 +2915,42,18,42,95929,2,1.70,1,0,0,0,0,1,0 +2916,34,9,133,92110,1,3.80,1,0,0,0,0,1,0 +2917,46,20,40,92037,1,1.20,2,0,0,0,0,1,0 +2918,55,31,34,94305,3,1.50,1,101,0,0,0,1,0 +2919,28,3,142,93727,1,0.80,1,0,0,0,0,1,0 +2920,35,10,64,94542,3,2.30,1,0,0,0,1,1,1 +2921,60,35,44,94720,2,1.60,3,170,0,0,0,1,0 +2922,50,24,95,91401,1,0.30,1,262,0,0,0,1,0 +2923,52,26,49,90011,1,1.40,3,0,0,0,0,1,0 +2924,51,27,12,91007,2,0.20,1,0,0,0,0,0,0 +2925,51,26,98,90024,1,1.30,3,0,0,0,0,1,1 +2926,59,35,42,91711,4,0.40,1,0,0,0,0,1,0 +2927,53,28,44,92152,2,0.60,3,0,0,0,0,1,1 +2928,43,17,124,94117,1,5.20,1,0,0,0,0,0,0 +2929,31,6,175,95005,2,6.70,1,0,0,0,0,1,0 +2930,32,6,22,94061,4,0.30,1,0,0,0,0,0,0 +2931,41,17,78,95929,4,2.67,1,99,0,0,0,1,0 +2932,31,4,54,91741,2,1.00,2,109,0,0,0,0,1 +2933,41,16,154,92407,1,7.00,1,0,0,0,0,0,1 +2934,47,22,42,95820,3,2.70,2,0,0,0,0,1,0 +2935,37,13,195,91763,2,6.50,1,635,0,0,0,1,0 +2936,53,23,80,93023,1,3.00,3,0,0,0,0,1,1 +2937,49,22,81,94301,3,2.00,2,0,0,0,0,1,0 +2938,62,36,89,94022,2,2.00,1,0,0,0,0,1,1 +2939,33,9,61,93943,3,2.60,2,0,0,0,0,1,0 +2940,54,24,25,90016,4,0.40,3,0,0,0,0,0,1 +2941,27,3,43,90245,3,0.10,2,163,0,0,0,1,0 +2942,60,35,122,92606,1,2.60,1,352,0,0,0,0,0 +2943,29,5,160,90405,1,4.30,1,385,0,0,0,1,0 +2944,56,32,83,91320,4,1.60,2,0,0,0,0,0,0 +2945,55,30,79,92182,2,0.00,3,0,0,0,0,0,0 +2946,45,19,30,94305,3,0.50,2,0,0,0,0,1,1 +2947,33,9,145,94110,1,4.30,1,437,0,0,0,1,0 +2948,45,21,151,90024,2,3.30,1,328,0,0,0,0,0 +2949,44,18,14,94720,2,0.10,3,98,0,0,0,0,1 +2950,37,11,19,95054,3,0.20,2,0,0,0,0,1,0 +2951,42,16,55,95820,1,0.70,3,135,0,0,0,1,0 +2952,26,2,132,94720,2,2.40,3,0,1,0,0,0,1 +2953,33,8,182,94065,1,8.60,1,0,0,0,0,0,0 +2954,61,36,78,91330,3,0.50,1,0,0,0,0,1,1 +2955,31,7,42,95822,1,2.40,2,0,0,0,0,1,1 +2956,54,29,44,95518,2,2.30,3,187,0,0,0,1,0 +2957,62,38,195,91125,4,5.20,3,522,1,0,1,1,1 +2958,61,36,53,92717,3,0.50,2,0,0,0,0,1,0 +2959,66,41,65,92612,3,2.40,1,0,0,0,0,0,0 +2960,38,12,43,94305,4,0.20,1,0,0,0,0,0,0 +2961,55,29,38,90035,4,1.50,3,0,0,0,0,0,1 +2962,60,36,50,95741,1,1.80,3,0,0,0,0,1,0 +2963,23,-2,81,91711,2,1.80,2,0,0,0,0,0,0 +2964,29,3,41,94588,1,1.90,3,0,0,0,0,1,1 +2965,35,10,73,93943,3,2.30,1,0,0,0,0,1,0 +2966,53,27,31,91605,2,0.40,3,104,0,0,0,0,1 +2967,32,7,84,91320,3,0.60,2,0,0,0,0,1,1 +2968,38,14,95,94109,2,1.90,1,0,0,0,0,1,1 +2969,44,18,162,90840,4,1.30,1,301,1,0,0,0,0 +2970,43,18,60,95039,2,2.20,3,115,0,0,0,0,0 +2971,54,30,121,95039,2,1.10,3,0,1,1,0,0,0 +2972,52,25,43,91380,3,1.00,2,165,0,0,1,1,1 +2973,31,7,38,92182,1,1.80,2,182,0,0,1,1,1 +2974,47,22,82,92084,1,2.90,1,276,0,0,0,1,0 +2975,42,18,52,95008,4,1.90,1,0,0,0,0,1,0 +2976,57,33,43,91016,3,1.50,1,168,0,0,0,0,1 +2977,33,8,82,95747,1,2.60,2,0,0,1,1,1,1 +2978,35,10,161,94109,1,4.10,1,0,0,1,0,1,0 +2979,56,30,24,94550,2,0.70,2,0,0,0,0,1,0 +2980,57,32,102,90210,1,2.60,1,0,0,0,0,1,0 +2981,25,-1,53,94305,3,2.40,2,0,0,0,0,0,0 +2982,53,28,85,92037,1,1.20,1,0,0,0,0,0,0 +2983,59,33,111,95120,3,4.40,1,0,0,0,0,1,0 +2984,56,32,90,95054,2,0.30,1,0,0,0,0,1,1 +2985,54,28,94,92709,2,1.10,1,188,0,0,0,0,0 +2986,48,23,63,94606,4,3.60,3,0,0,0,0,0,0 +2987,55,30,153,94305,2,2.80,2,0,1,1,1,1,0 +2988,33,7,39,92037,2,2.00,3,0,0,0,0,0,0 +2989,46,21,205,95762,2,8.80,1,181,0,1,0,1,0 +2990,42,18,142,93106,1,3.40,1,496,0,0,0,1,0 +2991,49,25,163,94608,2,0.40,1,0,0,1,0,0,0 +2992,42,17,113,93014,3,1.00,1,0,0,1,0,1,0 +2993,46,21,64,92104,1,2.90,1,0,0,0,0,1,1 +2994,65,40,20,92647,3,0.10,3,0,0,0,0,0,1 +2995,50,24,179,94025,1,1.00,1,0,0,0,0,1,0 +2996,54,24,91,91101,2,4.50,3,90,0,0,0,1,0 +2997,42,18,103,91367,1,3.33,1,0,1,1,1,1,1 +2998,57,33,80,95053,4,1.60,2,0,0,0,0,0,0 +2999,61,35,38,93106,2,0.30,1,0,0,0,0,0,0 +3000,60,34,44,94143,1,0.20,1,0,0,0,0,0,1 +3001,40,14,164,94720,1,4.30,2,0,1,0,0,0,0 +3002,33,7,81,92647,3,1.60,1,0,0,0,0,1,1 +3003,37,13,95,90095,2,1.70,2,83,0,0,0,0,0 +3004,52,28,44,90747,3,1.90,2,0,0,0,0,0,1 +3005,33,7,88,94583,3,1.60,1,0,0,0,0,1,1 +3006,62,36,148,94111,3,7.00,2,0,1,0,0,1,0 +3007,62,37,169,95014,3,5.00,2,184,1,0,1,1,1 +3008,63,37,11,91711,1,0.80,2,102,0,0,0,0,1 +3009,55,25,92,94550,1,3.00,3,158,0,0,0,0,1 +3010,33,9,74,92120,3,2.60,2,0,0,0,0,1,0 +3011,25,1,72,94301,3,0.80,1,0,0,0,0,1,0 +3012,55,31,63,95616,3,2.67,1,0,0,0,0,1,0 +3013,29,3,172,92373,2,4.50,1,415,0,0,0,1,0 +3014,45,21,183,90029,2,1.40,1,0,0,0,0,1,1 +3015,60,34,40,91311,1,2.50,3,166,0,0,0,1,0 +3016,44,18,68,92673,4,2.90,1,0,0,1,0,0,1 +3017,48,23,78,91423,4,3.60,3,0,0,0,0,1,0 +3018,57,32,68,90041,2,3.70,1,184,0,0,0,0,0 +3019,58,32,49,94005,1,1.40,1,99,0,0,0,1,1 +3020,58,33,39,94132,2,2.30,3,0,0,0,0,1,0 +3021,44,20,151,95193,1,3.50,1,392,0,0,0,1,0 +3022,54,28,159,90245,2,0.50,1,461,0,0,0,1,0 +3023,59,33,89,94608,4,1.90,2,0,0,0,0,1,1 +3024,63,37,105,92694,4,1.70,3,244,0,0,0,0,1 +3025,61,35,78,90840,2,2.00,1,0,0,0,0,1,1 +3026,58,32,128,94609,2,2.70,1,344,0,0,0,0,0 +3027,44,20,81,90254,4,0.80,1,228,0,0,0,0,1 +3028,53,29,50,93305,4,0.10,3,152,0,0,0,1,0 +3029,63,39,38,92624,3,0.10,3,178,0,0,0,1,1 +3030,41,17,119,94960,2,6.10,1,263,0,1,0,1,0 +3031,50,26,110,94509,3,1.80,2,0,0,0,0,1,0 +3032,51,25,29,90212,1,1.40,3,102,0,0,0,0,1 +3033,47,22,19,94590,1,0.40,3,0,0,0,0,1,0 +3034,43,19,130,90630,2,4.70,3,221,1,0,0,0,1 +3035,46,21,38,90024,1,2.40,1,130,0,0,0,1,0 +3036,50,24,31,95054,1,0.30,3,0,0,0,0,0,0 +3037,33,9,14,91320,4,0.70,2,105,0,0,0,1,0 +3038,27,2,158,95060,3,0.40,2,0,1,0,1,1,0 +3039,34,8,39,92124,4,0.20,1,115,0,0,0,1,0 +3040,34,9,141,95616,2,4.90,3,0,1,0,0,0,1 +3041,28,2,33,95814,3,1.00,1,167,0,0,0,1,0 +3042,29,5,92,95006,2,0.60,1,0,0,0,0,1,0 +3043,52,26,78,94301,3,3.00,2,0,0,0,0,0,0 +3044,47,22,42,91754,3,2.70,2,0,0,0,0,1,1 +3045,41,16,15,94124,2,0.30,2,83,0,0,0,0,0 +3046,58,32,48,91768,1,2.80,2,0,0,0,0,1,0 +3047,37,12,63,95630,3,2.30,1,0,0,0,0,1,0 +3048,57,33,149,95060,1,4.70,1,0,0,1,0,0,0 +3049,63,39,49,90275,1,0.80,1,103,0,0,0,1,0 +3050,60,35,125,94720,2,3.90,1,0,0,0,0,0,0 +3051,50,25,58,92131,1,1.30,2,0,0,0,0,1,0 +3052,60,35,48,94538,3,1.50,1,0,0,0,0,1,0 +3053,54,30,75,94720,2,3.20,3,0,0,0,0,0,1 +3054,28,4,114,92521,2,0.20,1,0,0,0,0,1,0 +3055,45,21,134,92697,4,5.50,2,0,1,0,1,1,1 +3056,28,2,111,94305,4,2.30,3,0,0,0,0,1,0 +3057,54,29,62,94301,4,3.80,2,149,0,0,0,1,0 +3058,42,18,45,95616,1,0.70,1,0,0,1,0,1,0 +3059,30,4,113,90064,2,0.20,1,0,0,0,0,1,0 +3060,61,36,128,94550,1,2.60,1,0,0,0,0,1,0 +3061,64,38,168,94061,4,5.70,3,0,1,0,0,1,0 +3062,38,13,81,90095,1,4.00,3,206,0,1,0,1,0 +3063,39,14,75,92521,1,0.10,2,297,0,0,0,0,1 +3064,54,29,21,95841,4,0.10,3,0,0,0,0,0,0 +3065,59,33,83,94701,3,4.40,1,0,0,0,0,1,0 +3066,39,15,121,92354,1,3.50,1,368,0,1,0,1,0 +3067,63,33,40,91320,4,1.67,3,0,0,0,0,1,0 +3068,31,5,101,94501,1,2.90,3,170,0,1,0,0,0 +3069,56,26,90,92120,2,4.50,3,0,0,0,0,0,0 +3070,47,20,68,91320,1,2.67,2,0,0,0,0,1,1 +3071,28,3,74,91330,2,1.80,2,221,0,1,0,0,0 +3072,32,8,74,93023,4,0.10,2,257,0,0,0,0,1 +3073,54,30,51,92821,2,3.20,3,0,0,0,0,0,0 +3074,29,5,149,94611,1,1.50,1,0,0,0,0,1,0 +3075,39,15,31,95039,1,1.40,3,88,0,0,0,1,1 +3076,26,0,85,95616,2,1.60,3,0,0,0,0,0,0 +3077,29,-1,62,92672,2,1.75,3,0,0,0,0,0,1 +3078,46,21,44,95112,1,0.30,1,110,0,1,0,1,0 +3079,38,13,63,92325,3,0.50,3,190,0,1,1,1,1 +3080,55,31,23,95616,2,0.30,1,0,0,0,0,1,1 +3081,48,22,40,94063,3,2.20,2,87,0,0,0,1,0 +3082,36,10,78,95064,2,4.50,3,204,0,0,0,1,1 +3083,39,13,40,92122,3,0.90,3,129,0,0,0,1,0 +3084,40,16,78,90720,4,2.40,1,0,0,1,1,1,0 +3085,26,0,129,90028,3,0.70,2,0,1,0,0,0,0 +3086,55,29,71,91311,3,0.30,2,0,0,0,0,0,1 +3087,61,35,23,94720,3,0.30,3,0,0,0,0,1,0 +3088,57,33,15,94303,2,0.30,1,0,0,0,0,1,0 +3089,56,31,28,94720,1,1.30,1,138,0,0,0,0,1 +3090,31,5,23,94110,3,1.00,1,95,0,0,0,0,0 +3091,61,31,19,91109,1,1.50,3,0,0,0,0,1,0 +3092,58,32,42,95020,3,1.40,3,158,0,0,0,0,1 +3093,43,18,113,90036,2,0.40,1,325,0,1,0,0,0 +3094,29,5,34,90717,4,0.40,2,0,0,0,0,0,1 +3095,50,23,19,90272,1,0.50,2,104,0,0,0,0,1 +3096,49,25,43,94109,1,1.60,2,0,0,0,0,1,1 +3097,43,18,179,94108,3,1.20,1,0,1,1,1,1,0 +3098,58,32,44,92182,3,2.20,3,0,0,0,0,0,0 +3099,41,16,21,92024,2,0.10,2,0,0,0,0,0,0 +3100,65,40,115,92647,1,2.50,1,174,0,0,0,0,1 +3101,52,27,81,90024,4,3.80,2,0,0,0,0,0,1 +3102,55,31,91,93555,2,2.80,1,0,0,0,0,0,0 +3103,49,25,30,90095,4,0.90,2,0,0,0,0,0,1 +3104,52,22,55,92129,3,1.40,3,0,0,0,0,1,0 +3105,56,31,48,91775,2,2.10,3,0,0,0,0,0,1 +3106,30,4,23,94122,4,0.30,2,121,0,0,0,0,0 +3107,36,10,21,92084,3,0.10,2,0,0,0,0,0,0 +3108,41,17,55,92374,2,1.70,1,0,0,0,0,0,0 +3109,42,15,21,95678,3,1.00,2,0,0,0,0,1,0 +3110,60,34,40,93940,3,2.20,3,0,0,1,0,1,0 +3111,44,20,30,95020,4,0.30,1,0,0,0,0,0,1 +3112,34,9,78,90095,3,0.60,2,0,0,0,0,1,0 +3113,56,32,65,92677,2,3.20,3,0,0,0,0,1,0 +3114,31,5,50,91330,4,2.10,3,209,0,0,0,1,0 +3115,29,4,55,90024,4,2.00,2,0,0,1,0,1,0 +3116,31,5,111,94305,2,0.20,1,0,0,0,0,0,0 +3117,36,10,21,92008,3,0.10,2,0,0,0,0,0,1 +3118,42,16,65,92614,3,0.50,3,256,0,0,0,1,0 +3119,64,39,114,90095,1,0.80,3,0,0,0,0,1,0 +3120,61,36,54,91320,3,0.90,3,179,0,0,0,1,0 +3121,35,11,75,94542,2,1.70,2,0,0,0,0,1,0 +3122,28,2,13,91791,4,0.40,1,0,0,0,0,0,1 +3123,38,14,54,90095,2,0.60,3,218,0,0,0,0,0 +3124,44,17,22,94546,3,1.00,2,126,0,0,0,1,1 +3125,45,20,198,95053,2,2.80,1,0,0,0,0,1,1 +3126,46,20,18,92521,1,0.20,1,0,0,0,0,1,1 +3127,57,32,74,92780,4,0.70,1,0,0,0,0,0,1 +3128,40,14,61,94539,4,0.20,3,0,0,0,0,1,0 +3129,38,12,64,94115,2,1.80,1,0,0,0,0,0,0 +3130,39,14,10,92705,2,0.30,2,0,0,1,0,0,1 +3131,23,-2,82,92152,2,1.80,2,0,0,1,0,0,1 +3132,47,22,61,94025,3,2.70,2,168,0,0,0,1,1 +3133,32,7,83,94302,2,2.50,1,148,0,1,0,1,0 +3134,30,5,73,93711,3,2.60,3,0,0,0,0,1,0 +3135,54,30,22,95060,2,0.40,1,89,0,0,0,1,0 +3136,25,0,91,95039,2,1.80,2,321,0,0,0,0,0 +3137,60,34,65,95354,3,2.20,3,94,0,1,1,0,1 +3138,61,36,13,91711,3,0.50,1,0,0,0,0,1,0 +3139,36,11,103,93555,1,4.60,1,255,0,0,0,1,0 +3140,52,26,95,92130,1,0.30,1,0,0,0,0,1,0 +3141,33,7,31,94303,4,1.00,1,0,0,0,0,1,1 +3142,57,31,131,90405,3,0.60,1,0,1,0,0,1,0 +3143,34,8,175,95051,4,1.10,3,0,1,1,1,1,1 +3144,50,24,38,91105,4,0.10,1,0,0,0,0,1,0 +3145,43,18,104,91711,3,1.00,1,0,0,0,0,1,0 +3146,34,10,114,94305,3,3.30,3,0,1,0,0,0,0 +3147,26,1,38,91910,4,1.70,2,0,0,0,0,1,0 +3148,26,0,30,94024,4,1.30,3,0,0,0,0,1,1 +3149,48,22,19,95616,2,0.10,3,106,0,0,0,0,0 +3150,49,25,25,95192,4,1.00,1,0,0,0,0,1,1 +3151,47,22,124,90027,4,5.00,3,0,1,0,0,0,0 +3152,43,19,20,94110,3,0.50,1,0,0,0,0,0,0 +3153,40,15,83,90275,1,1.00,3,0,0,0,0,0,0 +3154,31,5,18,94111,4,0.30,2,0,0,0,0,0,1 +3155,27,1,99,94305,1,3.00,3,149,1,0,0,0,1 +3156,55,29,62,92626,3,0.30,2,0,0,0,0,1,0 +3157,54,30,24,92647,1,0.10,2,0,0,0,0,0,0 +3158,23,-1,13,94720,4,1.00,1,84,0,0,0,1,0 +3159,54,28,64,90095,2,0.80,3,0,0,1,0,1,0 +3160,57,33,62,92831,3,2.67,1,240,0,0,0,0,0 +3161,41,15,158,94304,1,4.70,2,0,1,1,1,0,1 +3162,28,4,88,94024,1,5.40,1,0,0,0,0,1,0 +3163,33,7,28,94109,4,0.80,1,0,0,0,0,1,0 +3164,51,27,52,94132,2,1.00,3,0,0,0,0,0,0 +3165,28,4,82,95136,4,0.00,1,0,0,0,0,1,1 +3166,63,37,140,91711,2,6.90,1,97,0,0,0,0,1 +3167,29,4,80,90028,1,0.80,2,0,0,0,0,1,1 +3168,62,38,58,94720,4,1.20,2,228,0,0,0,0,1 +3169,51,25,180,94701,1,1.70,1,0,0,0,0,1,0 +3170,52,28,55,94608,1,1.60,2,227,0,0,0,0,0 +3171,43,16,65,94110,3,2.67,2,100,0,0,0,0,0 +3172,39,12,62,91910,3,2.33,2,0,0,0,0,0,0 +3173,35,9,23,95670,4,0.30,1,0,0,0,0,0,0 +3174,34,10,35,94309,1,1.70,1,0,0,0,0,1,0 +3175,49,24,35,94701,4,0.20,2,0,0,0,0,0,1 +3176,43,18,74,92009,4,0.40,1,0,0,0,0,0,0 +3177,48,24,14,91330,3,0.40,1,0,0,0,0,1,0 +3178,30,4,83,91007,2,1.50,3,199,0,0,0,0,1 +3179,46,21,71,95814,4,1.90,3,0,0,0,0,0,0 +3180,43,17,53,90245,2,0.70,1,130,0,1,0,1,0 +3181,27,3,103,92121,2,0.60,1,84,0,0,0,0,0 +3182,39,15,109,95827,1,1.70,1,0,0,0,0,1,0 +3183,58,33,60,94304,2,1.90,2,94,0,1,0,1,0 +3184,44,17,12,94542,3,0.67,2,0,0,0,0,1,0 +3185,39,15,141,92354,2,8.00,1,0,0,0,0,1,0 +3186,35,10,128,92843,1,3.80,1,0,0,0,0,1,0 +3187,41,16,98,95192,3,1.00,1,296,0,0,0,0,0 +3188,43,18,41,94035,1,0.50,3,0,0,0,0,0,0 +3189,55,25,90,90717,2,4.50,3,0,0,0,0,0,1 +3190,32,6,31,92675,1,0.30,1,0,0,0,0,0,0 +3191,56,26,74,91335,1,3.00,3,0,0,0,0,0,0 +3192,30,5,83,93101,4,1.80,3,0,0,0,0,0,1 +3193,65,39,35,94005,1,0.50,3,0,0,0,0,0,0 +3194,31,7,140,95616,1,4.00,1,0,0,0,0,0,1 +3195,41,15,65,90019,3,0.50,3,0,0,0,0,0,0 +3196,55,29,35,90007,3,1.40,1,0,0,0,0,0,0 +3197,37,7,73,94043,4,1.80,3,0,0,0,0,1,1 +3198,34,10,29,93555,1,1.50,2,0,0,0,0,1,0 +3199,34,9,55,92122,4,2.00,2,147,0,0,0,0,1 +3200,33,9,20,95521,4,0.70,2,0,0,0,0,1,0 +3201,48,23,70,92122,1,2.80,2,0,0,0,0,0,0 +3202,28,3,81,92121,4,0.20,1,0,0,0,0,0,0 +3203,30,4,25,92173,2,0.30,1,0,0,1,0,1,0 +3204,44,20,119,92677,2,7.50,1,239,0,0,0,1,0 +3205,61,35,49,90095,4,1.70,2,185,0,0,0,0,0 +3206,59,33,38,92407,1,1.40,1,0,0,0,0,1,1 +3207,33,7,80,91103,2,1.50,3,0,0,0,0,1,1 +3208,56,32,84,93407,1,4.30,1,0,0,0,0,1,1 +3209,53,29,61,95032,4,1.60,2,0,0,0,0,1,0 +3210,42,16,173,91355,2,1.50,2,373,1,0,1,1,1 +3211,43,19,60,94301,2,2.50,1,0,0,1,0,0,0 +3212,35,9,83,90277,2,4.50,3,0,0,0,0,1,0 +3213,61,35,59,92697,1,2.80,2,0,0,0,0,0,0 +3214,39,9,32,90212,3,2.00,3,116,0,0,0,1,0 +3215,61,37,33,91775,3,0.10,3,0,0,0,0,1,0 +3216,40,15,19,90630,4,0.20,3,0,0,0,0,1,0 +3217,34,8,14,95014,4,0.30,1,0,0,0,0,0,0 +3218,65,39,94,93022,4,4.10,1,120,1,0,1,1,1 +3219,40,16,154,94122,2,6.10,1,325,0,0,0,1,0 +3220,39,15,33,92346,1,2.00,2,0,0,0,0,0,0 +3221,61,35,28,93302,2,0.20,3,135,0,0,0,1,0 +3222,40,16,44,93407,1,1.80,1,0,0,1,0,1,0 +3223,49,23,81,93107,2,0.80,3,0,0,0,0,0,0 +3224,43,18,29,95126,1,0.50,3,0,0,0,0,1,0 +3225,45,21,58,94025,3,0.30,3,0,0,1,0,1,0 +3226,52,28,38,95064,4,0.90,2,0,0,0,0,0,1 +3227,32,8,82,93943,3,1.50,1,0,0,0,0,1,1 +3228,31,7,18,94720,1,0.40,3,0,0,0,0,1,0 +3229,27,2,45,94305,2,1.70,2,0,0,0,0,0,1 +3230,33,9,64,92507,4,3.40,1,0,0,0,0,0,0 +3231,65,40,48,94708,3,2.40,1,0,0,0,0,0,1 +3232,62,37,24,90717,1,0.30,3,0,0,1,0,1,0 +3233,55,25,65,92093,4,2.00,3,0,0,0,0,1,0 +3234,46,20,111,95037,1,0.00,1,329,0,0,0,0,0 +3235,37,12,114,91107,3,0.60,2,0,0,0,0,1,0 +3236,60,35,39,91711,2,1.60,3,0,0,0,0,1,0 +3237,44,14,19,94112,1,0.75,3,0,0,0,0,0,1 +3238,35,9,22,94085,3,0.10,2,0,0,0,1,1,1 +3239,52,28,49,94928,4,1.10,2,0,0,0,0,1,0 +3240,30,4,40,90095,1,0.30,1,0,0,0,0,1,0 +3241,62,36,63,93407,1,1.60,1,118,0,0,0,1,0 +3242,41,15,55,94305,1,2.80,1,0,0,0,0,0,0 +3243,38,14,33,92096,1,2.00,2,0,0,0,0,1,0 +3244,52,26,31,92054,4,1.50,3,0,0,0,0,1,0 +3245,48,24,24,92624,4,0.20,1,0,0,0,0,1,0 +3246,47,22,81,90009,4,3.60,3,0,0,0,0,1,1 +3247,41,17,81,95422,1,0.80,2,223,0,0,0,1,0 +3248,44,20,113,95032,2,3.30,1,0,0,0,0,1,1 +3249,31,6,92,92037,2,3.30,1,0,0,0,0,0,0 +3250,50,25,81,92806,1,1.20,1,0,0,0,0,0,0 +3251,36,11,101,90212,3,1.20,3,0,0,1,0,0,1 +3252,52,26,78,90720,3,3.00,2,0,0,0,0,0,1 +3253,62,38,78,92521,2,0.00,3,0,0,0,0,1,0 +3254,55,30,35,94025,1,1.50,2,118,0,0,0,0,1 +3255,61,37,9,93907,2,0.30,3,0,0,0,0,1,0 +3256,34,7,82,95741,4,2.00,2,0,0,0,0,1,1 +3257,34,9,41,94305,1,2.50,3,0,0,0,0,0,0 +3258,59,35,84,92407,1,1.80,3,0,0,0,0,1,0 +3259,41,17,42,91910,4,2.20,2,185,0,1,0,1,0 +3260,33,8,54,92251,3,2.30,1,0,0,0,0,0,1 +3261,55,30,84,95821,2,0.00,3,0,0,0,0,0,0 +3262,64,40,131,91103,1,3.80,1,0,0,0,0,0,0 +3263,44,19,85,90024,2,3.80,3,0,0,0,0,1,0 +3264,32,8,84,92093,4,3.40,1,0,0,0,0,1,0 +3265,67,41,114,95616,4,2.40,3,0,0,0,0,1,0 +3266,40,14,61,94612,3,0.50,3,0,0,0,0,1,0 +3267,57,31,39,92821,1,2.20,3,0,0,0,0,1,1 +3268,59,35,21,95818,2,1.00,1,120,0,0,0,1,0 +3269,43,17,111,91423,4,5.40,3,0,1,0,0,1,0 +3270,58,34,68,94305,2,2.80,1,113,0,0,0,0,0 +3271,50,23,179,94609,4,3.60,2,0,1,0,0,1,0 +3272,52,27,93,90291,4,4.10,2,0,1,0,0,0,1 +3273,35,9,85,92121,2,1.80,1,0,0,0,0,0,0 +3274,40,15,180,90095,1,4.10,1,0,0,0,0,0,0 +3275,31,5,110,92123,2,1.50,3,0,0,0,0,1,0 +3276,32,8,65,95134,1,1.20,1,268,0,0,0,1,0 +3277,55,31,159,92123,1,3.90,3,0,1,0,0,0,0 +3278,43,19,81,92121,2,3.20,1,0,0,0,0,1,0 +3279,31,6,132,94571,1,3.80,1,0,0,0,0,1,0 +3280,26,-1,44,94901,1,2.00,2,0,0,0,0,0,0 +3281,58,33,98,90277,1,2.60,1,0,0,0,0,0,0 +3282,51,25,62,95014,2,1.50,2,0,0,0,0,1,1 +3283,45,21,91,95054,1,4.70,1,0,0,0,0,1,0 +3284,56,30,29,92152,4,0.70,2,87,0,0,0,1,0 +3285,25,-1,101,95819,4,2.10,3,0,0,0,0,0,1 +3286,38,13,65,91706,3,0.70,2,0,0,0,0,1,0 +3287,62,36,58,95020,1,2.80,2,0,0,0,0,0,1 +3288,39,13,32,90747,2,0.80,3,0,0,0,0,1,0 +3289,56,30,140,94122,4,0.50,1,292,1,0,0,0,0 +3290,50,25,44,94303,1,0.30,1,187,0,0,0,1,1 +3291,52,27,113,92038,1,0.10,3,0,0,0,0,0,0 +3292,53,28,38,94998,1,1.30,2,0,0,0,0,1,0 +3293,25,-1,13,95616,4,0.40,1,0,0,1,0,0,0 +3294,44,20,62,94939,2,2.50,1,0,0,1,0,1,0 +3295,42,12,29,93611,3,2.00,3,0,0,0,0,0,0 +3296,42,16,141,94960,3,4.00,2,0,1,0,0,0,0 +3297,63,37,132,94080,1,4.40,2,0,1,0,0,1,0 +3298,57,32,23,93407,1,0.30,3,0,0,0,0,1,1 +3299,56,32,11,94110,2,0.30,1,89,0,0,0,0,0 +3300,60,34,90,92192,4,1.90,2,0,0,0,0,1,0 +3301,62,38,43,92354,1,1.90,2,0,0,0,0,1,0 +3302,48,22,59,90086,4,2.60,1,0,0,0,0,1,1 +3303,37,11,28,94501,2,0.80,3,0,0,0,0,0,0 +3304,55,29,28,94539,2,0.70,2,82,0,0,0,1,1 +3305,42,17,108,95120,3,1.00,1,383,0,0,0,1,0 +3306,39,13,78,95616,1,2.80,3,0,0,0,0,0,0 +3307,47,22,65,90840,1,2.40,1,0,0,0,0,1,0 +3308,34,10,25,92038,4,1.00,1,0,0,0,0,1,0 +3309,48,23,108,92120,2,3.80,3,0,0,0,0,0,1 +3310,52,27,43,94611,4,0.20,2,0,0,0,0,1,0 +3311,53,29,95,94720,4,1.00,2,0,0,0,0,1,1 +3312,49,25,24,95819,1,0.30,1,0,0,0,0,0,0 +3313,47,22,190,94550,2,8.80,1,0,0,0,0,0,0 +3314,48,24,24,91950,1,0.90,3,0,0,0,0,0,0 +3315,38,13,41,90073,4,1.70,1,0,0,0,0,1,0 +3316,48,22,80,94720,3,1.10,1,0,0,0,0,0,0 +3317,56,26,63,94501,3,2.00,3,0,0,0,0,1,0 +3318,65,41,79,90035,3,2.00,3,0,0,0,0,0,0 +3319,46,20,105,90089,4,3.20,1,0,1,0,0,0,0 +3320,60,35,153,95136,3,2.00,3,0,1,0,0,0,1 +3321,50,25,114,92104,1,0.60,1,0,0,0,0,0,1 +3322,41,15,120,94521,1,5.20,1,0,0,0,0,1,0 +3323,41,16,104,92008,1,4.00,3,0,0,0,1,1,1 +3324,60,35,20,92110,1,1.30,1,0,0,0,0,1,0 +3325,57,31,41,91401,1,1.40,1,0,0,1,0,1,0 +3326,48,23,35,93302,2,1.30,1,0,0,0,0,0,0 +3327,53,27,174,91006,1,2.90,2,0,1,0,0,1,0 +3328,42,18,164,93407,1,1.30,3,0,1,1,1,1,1 +3329,45,20,22,90230,1,0.10,1,0,0,0,0,0,0 +3330,35,10,132,94123,1,3.80,1,82,0,0,0,0,1 +3331,34,9,32,95054,4,1.10,3,0,0,0,0,1,0 +3332,67,42,21,94607,3,0.10,3,0,0,0,0,0,1 +3333,36,9,49,94402,2,1.67,2,0,0,0,0,0,1 +3334,37,13,79,91711,4,0.10,2,280,0,0,0,1,0 +3335,40,14,30,94720,2,0.80,3,86,0,0,0,0,0 +3336,35,10,118,92069,2,7.80,1,358,0,0,0,0,0 +3337,60,34,11,94305,4,0.70,3,0,0,0,0,1,0 +3338,59,29,61,92008,3,2.00,3,0,0,0,0,1,0 +3339,35,9,43,92037,4,1.20,2,0,0,1,0,1,0 +3340,27,1,141,95135,4,5.10,3,354,1,0,0,0,0 +3341,29,3,54,94104,4,1.80,3,0,0,0,0,0,0 +3342,35,9,33,91125,2,0.30,1,0,0,1,0,1,0 +3343,38,13,84,91330,3,1.20,3,121,0,0,0,1,1 +3344,62,37,125,94801,1,1.00,3,0,1,0,0,1,0 +3345,43,19,110,90639,1,3.40,1,0,0,0,0,0,1 +3346,35,11,14,94720,4,1.00,1,0,0,0,1,1,1 +3347,41,15,65,92037,2,2.80,1,0,0,0,0,1,1 +3348,65,41,78,92109,3,2.00,3,0,0,0,1,1,1 +3349,61,35,18,94303,3,0.30,3,0,0,0,0,0,0 +3350,55,25,95,92407,2,4.50,3,275,0,0,0,0,0 +3351,28,3,95,90245,2,1.80,2,0,0,0,0,0,0 +3352,52,26,191,92121,1,1.70,1,0,0,0,0,1,0 +3353,34,4,19,92521,1,0.67,3,83,0,0,0,1,0 +3354,49,23,19,94521,4,0.60,3,0,0,0,0,1,1 +3355,42,18,39,92703,1,0.30,3,0,0,0,0,1,0 +3356,49,23,93,90036,1,2.40,1,0,0,0,0,1,1 +3357,49,23,115,95051,3,4.60,3,0,1,0,0,0,0 +3358,32,6,112,94111,1,2.70,2,408,0,1,1,1,1 +3359,59,35,40,94536,4,0.40,1,0,0,0,0,0,0 +3360,43,19,45,91773,3,0.60,2,0,0,0,0,0,0 +3361,48,24,133,90740,1,5.00,1,0,0,0,0,0,0 +3362,31,5,85,94117,3,1.60,1,87,0,0,0,1,1 +3363,30,4,18,90277,2,0.30,2,0,0,0,0,1,0 +3364,58,34,54,93003,4,1.30,2,0,0,0,0,1,0 +3365,41,15,41,94143,2,2.40,2,105,0,0,0,0,0 +3366,38,8,21,95060,1,0.67,3,0,0,0,0,1,0 +3367,33,9,152,90024,1,6.00,1,0,0,0,0,1,1 +3368,51,27,53,92122,1,1.60,2,0,0,0,0,1,0 +3369,45,18,163,94720,3,5.33,2,0,1,0,1,0,1 +3370,34,10,84,95616,4,0.10,2,0,0,0,0,1,0 +3371,39,13,59,90033,3,0.90,3,199,0,1,0,1,0 +3372,44,18,33,95351,3,0.50,2,0,0,0,0,0,0 +3373,55,29,81,94928,4,4.90,1,209,0,0,0,1,0 +3374,28,2,182,92660,3,7.20,2,442,1,0,1,1,1 +3375,57,31,61,91360,1,2.20,3,0,0,0,0,0,0 +3376,43,18,88,90089,4,1.10,2,0,0,0,0,1,0 +3377,46,21,170,95136,2,2.80,1,0,0,0,0,0,0 +3378,35,10,83,95370,4,0.70,3,315,0,0,0,1,0 +3379,25,0,44,94536,4,0.60,2,0,0,0,0,0,1 +3380,65,41,83,94305,3,2.00,3,0,0,0,0,1,0 +3381,64,38,21,95422,1,0.80,2,76,0,0,0,0,1 +3382,39,15,143,91711,1,3.50,1,0,0,0,0,1,1 +3383,62,36,103,92182,2,2.80,1,0,0,1,1,1,0 +3384,46,22,135,95135,3,4.10,1,213,1,0,0,1,0 +3385,36,11,162,94583,1,8.60,1,153,0,1,0,1,0 +3386,42,17,73,90089,4,0.40,1,0,0,1,0,0,0 +3387,35,10,142,94061,4,0.80,3,0,1,0,0,0,0 +3388,63,37,25,94035,2,0.20,3,0,0,0,0,1,0 +3389,45,21,115,91320,2,3.30,1,85,0,0,0,1,0 +3390,27,3,88,92182,3,0.80,1,238,0,0,0,0,0 +3391,29,3,73,94720,3,0.30,3,0,0,0,0,0,0 +3392,55,29,94,94109,1,0.80,3,221,0,0,0,0,0 +3393,32,7,58,92612,1,1.00,1,0,0,0,0,1,0 +3394,37,11,81,95123,3,0.90,2,0,0,0,0,1,1 +3395,25,-1,113,90089,4,2.10,3,0,0,0,0,1,0 +3396,41,16,35,94061,2,1.40,2,135,0,0,0,0,0 +3397,52,28,65,93106,1,0.00,1,0,0,0,0,1,1 +3398,31,6,170,94010,2,6.70,1,137,0,0,0,1,0 +3399,40,14,62,92028,2,2.40,2,0,0,0,0,1,1 +3400,54,29,54,94720,2,2.10,3,97,0,0,0,0,0 +3401,48,22,39,94065,1,1.20,2,0,0,0,0,0,0 +3402,39,15,28,95818,1,1.40,3,118,0,0,0,1,1 +3403,64,40,95,90095,2,0.00,3,0,0,0,0,1,1 +3404,54,29,82,94709,3,3.70,2,0,1,0,0,1,0 +3405,39,14,21,94303,1,0.60,3,101,0,0,0,0,0 +3406,55,30,50,94061,2,2.10,3,0,0,0,0,1,0 +3407,42,12,34,92177,3,2.00,3,0,0,0,0,0,1 +3408,58,32,19,90405,4,0.70,3,0,0,0,0,0,0 +3409,45,21,71,90029,4,1.90,1,0,0,0,0,1,0 +3410,29,5,113,95351,2,2.00,2,84,0,0,0,1,1 +3411,36,11,9,90230,4,0.20,3,0,0,0,0,1,0 +3412,63,37,118,94010,1,2.00,1,427,0,0,0,0,0 +3413,55,29,79,90029,4,4.90,1,0,0,0,0,0,0 +3414,54,24,72,95123,3,1.40,3,0,0,0,0,0,1 +3415,61,36,18,95010,1,1.30,1,0,0,0,0,0,0 +3416,36,12,93,90720,2,2.20,1,0,0,0,0,1,1 +3417,61,37,62,94111,1,0.00,2,244,0,0,0,1,0 +3418,39,12,23,90024,3,1.00,2,0,0,0,0,1,1 +3419,57,31,40,91775,3,1.40,3,0,0,0,1,1,1 +3420,35,10,34,95503,4,1.70,1,87,0,0,0,1,1 +3421,66,41,114,94305,1,0.80,3,0,0,0,0,1,1 +3422,49,23,125,90245,1,2.40,1,0,0,0,0,0,1 +3423,48,23,41,92677,1,1.40,3,0,0,0,0,0,1 +3424,61,35,38,93009,2,1.00,3,0,0,0,0,0,0 +3425,44,19,45,94539,4,0.00,2,0,0,0,0,1,1 +3426,23,-1,12,91605,4,1.00,1,90,0,0,0,1,0 +3427,31,5,115,90025,2,1.50,3,189,0,0,0,1,0 +3428,39,15,175,94080,2,8.00,1,0,0,0,0,1,0 +3429,45,21,24,93106,1,0.90,3,0,0,0,0,0,0 +3430,39,14,28,91320,2,1.40,2,108,0,0,0,0,1 +3431,64,38,32,90291,2,0.30,1,0,0,0,0,1,1 +3432,64,38,63,94305,2,1.70,3,184,0,1,0,1,0 +3433,47,23,32,95370,1,1.00,1,0,0,0,0,0,1 +3434,34,9,60,94306,4,1.30,1,0,0,1,0,0,0 +3435,56,31,53,95521,2,1.60,3,78,0,0,0,0,0 +3436,33,8,58,92037,4,1.30,1,0,0,1,0,0,0 +3437,56,29,42,92104,4,2.50,2,0,0,0,0,0,0 +3438,57,31,39,94304,4,0.70,2,0,0,1,0,1,0 +3439,43,17,72,94806,1,2.80,1,271,0,0,0,1,0 +3440,43,17,80,95020,3,0.10,1,0,0,0,1,1,1 +3441,26,1,39,95133,4,0.60,2,0,0,0,0,0,1 +3442,64,40,18,94309,2,0.30,3,0,0,1,1,1,1 +3443,43,18,30,93940,1,0.50,3,0,0,0,0,1,0 +3444,44,18,54,90639,1,2.80,1,202,0,0,0,0,0 +3445,60,35,128,93101,1,0.90,1,0,0,0,0,1,0 +3446,37,13,38,94701,1,1.50,2,116,0,0,0,0,1 +3447,56,32,120,90232,1,7.40,1,186,0,0,0,1,0 +3448,54,29,25,90747,4,0.10,3,109,0,0,0,0,0 +3449,43,18,85,92606,4,1.90,3,110,0,0,0,1,1 +3450,57,32,135,90095,3,4.80,2,0,1,1,1,1,0 +3451,29,4,14,94590,4,0.50,3,0,0,0,0,0,1 +3452,54,30,70,92182,1,1.60,3,251,0,0,0,1,1 +3453,61,37,23,94720,3,0.40,2,0,0,0,0,0,0 +3454,29,3,31,94709,4,0.30,2,0,0,0,0,1,0 +3455,47,21,132,92120,1,0.30,1,0,0,0,0,1,0 +3456,43,19,28,93010,3,0.50,1,0,0,0,0,1,1 +3457,46,22,125,94536,2,4.70,3,0,1,0,0,1,0 +3458,55,31,91,94110,2,2.80,1,0,0,0,0,1,0 +3459,48,23,191,95053,2,2.80,1,231,0,0,0,0,1 +3460,26,1,88,94025,2,1.80,2,0,0,0,0,0,0 +3461,63,37,84,92691,4,2.40,3,0,0,0,0,1,1 +3462,57,27,64,92007,3,2.00,3,142,0,0,0,1,0 +3463,58,33,28,94608,2,0.50,2,146,0,1,0,1,0 +3464,28,3,149,92121,1,0.80,1,0,0,0,0,1,0 +3465,61,37,172,92612,4,4.25,1,0,1,0,1,1,1 +3466,65,41,42,95616,1,1.90,2,0,0,0,0,0,0 +3467,33,6,53,94122,2,1.00,2,96,0,0,0,0,1 +3468,63,37,149,90840,2,0.20,3,364,1,0,0,1,0 +3469,43,19,113,93933,2,1.80,2,0,0,0,0,0,1 +3470,26,2,79,95630,2,2.50,1,0,0,0,0,1,0 +3471,57,31,175,90503,2,0.50,1,429,0,0,0,1,1 +3472,50,25,38,95503,1,1.40,3,0,0,0,0,1,0 +3473,54,27,120,92672,4,3.00,2,431,1,0,0,1,0 +3474,59,34,52,92173,4,0.70,1,0,0,1,0,0,0 +3475,49,24,42,92121,2,0.70,2,0,0,0,0,1,0 +3476,54,30,13,92037,1,0.30,1,0,0,0,0,0,0 +3477,65,39,141,90280,2,6.90,1,0,0,1,0,1,0 +3478,34,10,131,94024,2,4.33,1,156,0,0,0,1,1 +3479,31,6,133,95747,1,1.50,3,0,1,0,0,0,0 +3480,31,6,64,94720,2,2.50,1,0,0,0,0,1,0 +3481,64,39,49,94591,2,1.50,1,0,0,1,0,1,0 +3482,52,26,34,93023,1,0.30,3,0,0,0,0,1,0 +3483,57,33,91,95133,1,4.30,1,81,0,1,0,0,0 +3484,60,36,195,90066,1,4.70,1,0,0,0,0,1,0 +3485,45,18,53,92104,3,2.50,2,112,0,0,0,0,0 +3486,39,13,39,92103,2,0.80,3,0,0,0,0,0,0 +3487,25,1,20,92806,4,1.00,1,0,0,0,0,0,1 +3488,29,4,104,91711,4,1.80,3,0,0,0,0,0,1 +3489,40,15,51,94117,2,1.10,2,131,0,0,0,1,0 +3490,36,12,154,91320,3,6.40,1,0,1,1,0,0,0 +3491,33,9,38,95814,1,1.33,1,115,0,0,0,0,0 +3492,51,27,12,92697,2,0.40,1,0,0,0,0,0,1 +3493,35,9,28,94546,1,0.60,3,0,0,0,0,0,1 +3494,54,28,33,94710,2,0.40,3,0,0,0,0,1,0 +3495,29,2,31,91330,4,1.50,2,0,0,0,0,0,0 +3496,32,8,44,91401,1,1.80,2,192,0,0,0,1,0 +3497,37,13,49,91711,4,2.00,3,192,0,0,0,0,0 +3498,55,31,134,92130,2,0.30,1,0,0,0,0,0,0 +3499,30,6,182,93561,4,0.80,3,94,1,0,0,1,0 +3500,49,23,114,94550,1,0.30,1,286,0,0,0,1,0 +3501,51,26,90,94110,1,2.80,2,0,0,0,0,1,1 +3502,65,39,105,91380,4,1.70,3,0,0,1,0,1,0 +3503,32,8,58,95616,3,2.00,1,90,0,0,0,1,0 +3504,29,3,53,95814,4,2.10,3,0,0,0,0,1,0 +3505,46,20,15,95370,4,0.60,3,0,0,1,0,1,0 +3506,64,39,103,90304,1,0.80,3,0,0,0,0,1,1 +3507,27,1,58,95827,4,1.80,2,154,0,0,1,1,1 +3508,50,23,83,91791,1,2.67,2,0,0,0,1,1,1 +3509,33,9,125,92182,1,4.30,3,0,1,0,0,1,0 +3510,38,12,61,91330,3,0.90,3,0,0,0,0,0,0 +3511,38,11,69,92124,3,2.33,2,0,0,0,0,0,0 +3512,37,11,89,94609,1,1.50,3,0,0,0,0,1,0 +3513,46,20,70,90405,4,2.90,1,0,0,0,0,0,1 +3514,31,4,39,94501,2,1.00,2,0,0,0,0,0,0 +3515,35,9,41,90024,4,1.20,2,0,0,0,0,1,0 +3516,50,26,148,94143,2,0.40,1,508,0,0,0,0,0 +3517,45,21,38,93943,3,0.60,2,148,0,0,0,1,0 +3518,30,6,95,94234,1,3.90,3,146,1,0,0,0,1 +3519,60,36,129,95039,2,6.00,1,0,0,0,0,0,0 +3520,31,5,84,94720,4,1.80,2,0,0,1,0,1,0 +3521,60,35,29,92126,3,1.30,2,0,0,0,0,0,0 +3522,36,10,30,91711,2,0.80,3,0,0,0,0,1,0 +3523,64,40,90,94028,2,0.00,3,134,0,0,0,0,0 +3524,29,4,150,91302,1,0.80,1,0,0,0,0,0,1 +3525,58,33,15,94583,4,0.90,2,0,0,0,0,0,0 +3526,59,34,13,96651,4,0.90,2,0,0,0,0,0,0 +3527,58,33,9,95008,2,0.20,3,0,0,0,0,1,0 +3528,35,10,24,95054,4,1.10,3,0,0,0,0,0,0 +3529,43,17,41,90210,3,2.20,2,0,0,0,0,1,0 +3530,33,7,25,94132,4,1.00,1,0,0,0,0,1,1 +3531,54,28,49,90073,4,2.80,2,0,0,1,0,0,0 +3532,38,12,58,94542,3,0.90,3,128,0,0,0,0,1 +3533,38,12,141,94022,2,0.00,1,0,0,0,0,1,1 +3534,57,32,50,94545,4,2.10,1,211,0,0,0,0,0 +3535,34,10,61,95006,3,2.00,1,0,0,0,0,0,1 +3536,52,27,65,92104,1,1.20,1,0,0,0,0,1,1 +3537,50,24,112,94005,1,0.30,1,229,0,0,0,0,0 +3538,60,34,19,92093,3,0.30,3,0,0,0,0,1,0 +3539,26,0,23,93561,1,0.10,2,0,0,0,0,0,0 +3540,56,30,60,91380,1,2.20,3,0,0,0,0,0,0 +3541,39,15,30,94305,4,0.30,1,0,0,1,0,0,1 +3542,45,20,144,92106,4,5.40,1,210,1,0,0,1,0 +3543,30,5,118,92182,4,3.00,3,0,1,0,0,1,0 +3544,37,11,194,94303,2,0.00,1,0,0,0,0,0,0 +3545,45,19,109,92037,3,1.10,1,0,0,0,0,0,0 +3546,48,22,174,95827,1,2.40,1,0,0,0,0,1,0 +3547,65,40,34,94720,1,1.10,3,119,0,0,0,1,1 +3548,46,20,84,92354,3,0.70,2,0,0,0,0,1,0 +3549,40,16,41,91107,1,2.00,2,0,0,0,0,0,1 +3550,33,7,92,90840,3,1.60,1,0,0,0,0,0,0 +3551,40,10,19,94609,1,0.75,3,116,0,0,0,0,0 +3552,60,35,55,92807,3,0.50,2,172,0,0,0,0,0 +3553,51,27,22,93106,4,0.50,2,0,0,0,0,1,1 +3554,41,16,155,95070,1,7.00,1,0,0,0,0,0,0 +3555,37,13,72,92407,4,2.00,3,0,0,1,0,0,0 +3556,35,9,81,91107,1,2.70,2,0,0,0,0,1,0 +3557,35,11,30,94303,1,1.70,1,0,0,1,0,0,1 +3558,46,20,54,90755,4,2.90,1,189,0,0,0,1,1 +3559,60,34,60,94065,3,2.50,1,0,0,0,0,1,0 +3560,51,25,68,94065,1,1.50,2,0,0,0,0,0,0 +3561,31,5,65,94591,4,2.20,2,126,0,0,0,1,0 +3562,30,6,31,94720,3,1.00,2,142,0,0,0,0,0 +3563,32,8,169,94596,1,6.50,3,272,1,1,1,1,0 +3564,53,27,139,94998,1,0.90,3,0,1,0,0,0,0 +3565,33,7,29,94720,1,0.60,3,0,0,0,0,0,0 +3566,40,15,43,92120,2,1.10,2,0,0,0,0,0,1 +3567,57,33,80,92064,2,2.80,1,0,0,0,0,1,1 +3568,51,26,43,91040,1,1.30,2,123,0,0,0,1,0 +3569,30,4,194,93407,2,4.50,1,0,0,0,0,0,1 +3570,41,15,24,92130,2,0.80,3,0,0,1,0,1,0 +3571,54,29,32,91107,2,0.60,3,0,0,0,0,1,1 +3572,42,18,153,93955,3,5.60,1,416,1,0,0,0,0 +3573,30,6,30,90245,1,0.40,3,0,0,0,0,1,1 +3574,60,36,165,90095,3,5.60,1,0,1,0,0,0,1 +3575,56,30,64,95123,3,0.30,2,0,0,0,0,0,1 +3576,63,38,15,94305,4,0.60,2,83,0,0,0,0,0 +3577,56,30,70,90245,3,0.30,2,0,0,0,0,0,0 +3578,39,9,32,91016,3,2.00,3,0,0,0,0,1,0 +3579,29,5,128,91302,2,4.10,2,209,1,0,0,1,0 +3580,28,2,84,94305,1,2.90,3,102,0,1,1,0,1 +3581,41,16,62,94553,2,2.20,3,0,0,0,0,1,1 +3582,28,4,33,91330,3,1.00,2,0,0,0,0,0,1 +3583,49,25,65,92354,1,0.00,1,0,0,0,0,1,0 +3584,30,3,33,95112,4,1.50,2,85,0,0,0,0,0 +3585,63,37,15,92121,1,0.80,2,115,0,0,0,1,0 +3586,45,18,45,92037,3,1.00,2,0,0,0,0,1,0 +3587,40,15,132,94131,2,3.90,1,0,0,0,0,1,0 +3588,28,4,29,94080,3,0.10,2,0,0,0,0,1,0 +3589,62,38,65,91768,1,0.00,2,0,0,0,0,1,0 +3590,38,12,52,92807,2,2.40,2,147,0,0,0,0,0 +3591,32,7,64,92630,2,0.10,1,0,0,0,0,1,1 +3592,58,32,73,94109,2,2.30,3,224,0,0,0,1,1 +3593,33,3,20,94704,1,0.67,3,0,0,0,0,0,0 +3594,60,34,44,90018,2,0.30,1,192,0,0,0,1,0 +3595,34,8,79,95616,1,2.50,1,0,0,0,0,1,0 +3596,38,14,104,90025,2,1.80,2,79,0,0,0,0,0 +3597,44,20,88,94720,1,4.70,1,0,0,0,0,0,0 +3598,56,26,51,92028,3,2.00,3,0,0,0,0,1,0 +3599,37,11,61,95120,3,0.90,2,0,0,0,0,0,0 +3600,45,19,23,93101,2,0.10,3,91,0,0,1,1,1 +3601,44,20,38,90018,2,2.10,3,95,0,0,0,1,0 +3602,37,13,75,94305,3,2.60,2,0,0,1,0,0,0 +3603,47,21,42,95841,4,0.10,1,0,0,0,0,1,1 +3604,51,25,45,92407,4,0.10,1,0,0,0,0,1,1 +3605,63,38,59,92612,3,0.50,2,0,0,0,0,1,0 +3606,61,31,130,92333,2,2.60,3,0,1,0,0,0,0 +3607,43,18,9,96145,2,0.00,3,96,0,0,0,1,1 +3608,41,15,62,90401,3,0.90,3,0,0,0,0,0,0 +3609,59,35,202,94025,1,4.70,1,553,0,0,0,0,0 +3610,29,5,162,94022,1,4.30,1,0,0,0,0,0,1 +3611,32,6,93,90029,3,1.60,1,79,0,0,0,1,0 +3612,64,39,145,92705,1,0.90,1,0,0,0,0,0,0 +3613,50,25,99,90245,1,4.60,1,368,1,1,1,0,1 +3614,35,11,148,92672,1,5.80,3,0,1,0,0,1,0 +3615,34,10,154,94583,3,5.40,2,0,1,0,0,1,0 +3616,58,34,149,95616,2,6.00,1,0,0,0,0,1,1 +3617,41,15,69,92507,1,1.50,3,78,0,0,0,1,0 +3618,37,11,30,94304,2,0.30,1,146,0,0,0,0,0 +3619,35,8,48,92697,2,1.00,2,0,0,0,0,1,0 +3620,45,20,42,94703,1,0.30,3,0,0,0,0,1,0 +3621,53,29,132,95020,2,0.30,1,403,0,0,0,0,0 +3622,53,27,81,91730,3,1.70,2,193,0,0,0,1,0 +3623,54,29,60,94901,4,3.80,2,0,0,0,0,1,1 +3624,28,3,45,91105,4,1.70,2,95,0,0,0,0,0 +3625,58,28,70,92028,1,1.40,3,0,0,0,0,0,0 +3626,47,21,71,92037,4,2.90,1,0,0,0,0,1,0 +3627,24,-3,28,90089,4,1.00,3,0,0,0,0,0,0 +3628,27,1,83,90034,2,0.20,1,0,0,0,0,0,1 +3629,42,18,131,94949,1,3.40,1,0,0,0,0,0,1 +3630,50,26,82,95051,1,0.00,1,0,0,0,0,1,1 +3631,41,16,79,95020,1,4.00,3,225,0,0,0,1,0 +3632,46,21,51,90089,4,1.90,3,0,0,0,0,0,0 +3633,46,20,111,95307,2,6.30,1,0,0,0,0,0,1 +3634,51,25,93,90048,1,0.30,1,0,0,0,0,1,0 +3635,59,35,73,90009,4,2.30,3,0,0,0,0,0,0 +3636,58,33,24,95616,2,0.50,2,0,0,0,0,1,0 +3637,37,11,64,96094,3,0.90,2,0,0,0,0,1,0 +3638,39,14,104,94608,3,1.00,1,242,0,0,0,1,0 +3639,47,22,38,92866,4,1.90,3,0,0,0,0,1,0 +3640,51,26,191,94063,1,8.10,1,0,0,1,0,1,0 +3641,64,34,53,95821,4,1.67,3,0,0,0,0,0,1 +3642,59,35,74,94402,4,2.30,3,0,0,0,0,0,0 +3643,55,29,21,92704,4,0.70,3,0,0,1,0,1,0 +3644,57,32,80,92606,3,1.60,3,144,0,0,0,1,1 +3645,59,33,41,91711,4,2.50,1,174,0,0,0,0,0 +3646,42,17,79,92103,1,3.70,3,0,0,1,0,0,1 +3647,34,9,141,92056,3,6.90,2,260,1,0,0,1,0 +3648,41,14,32,91605,3,1.00,2,0,0,0,0,0,1 +3649,43,13,38,95616,3,2.00,3,0,0,0,0,1,0 +3650,53,29,85,92691,3,1.80,2,0,0,0,0,1,0 +3651,47,21,93,91604,2,0.80,3,107,0,0,0,0,0 +3652,49,23,140,90504,1,1.90,3,0,1,0,0,0,1 +3653,35,9,69,94704,4,2.20,2,0,0,0,0,0,1 +3654,52,27,32,92521,2,2.00,2,0,0,0,0,0,1 +3655,53,28,61,94061,4,0.90,1,177,0,0,0,0,0 +3656,48,22,125,90086,1,2.40,1,0,0,0,0,1,0 +3657,35,8,30,95014,4,1.00,2,0,0,1,0,0,0 +3658,52,26,104,94025,2,2.40,2,0,0,0,0,1,1 +3659,60,35,24,92612,1,0.10,1,0,0,0,0,0,0 +3660,33,7,22,94002,1,0.40,2,0,0,0,0,0,0 +3661,38,12,59,93401,2,2.40,2,0,0,0,0,0,0 +3662,29,4,120,94553,1,4.10,2,0,1,1,1,0,1 +3663,35,9,164,94305,2,0.00,1,500,0,0,0,0,0 +3664,26,2,60,94111,4,1.60,1,0,0,0,1,1,1 +3665,48,24,43,91791,3,1.90,2,0,0,0,0,1,0 +3666,43,19,70,91711,3,2.33,1,0,0,1,0,0,0 +3667,60,35,51,94143,2,2.80,1,0,0,0,0,1,0 +3668,27,3,59,94590,4,1.60,1,0,0,0,0,1,0 +3669,38,13,129,92037,4,0.30,3,75,1,0,0,1,0 +3670,40,15,22,95616,2,1.40,2,0,0,0,0,1,1 +3671,38,14,29,94402,4,0.40,2,0,0,0,0,1,0 +3672,50,25,18,93106,1,0.40,3,0,0,0,0,1,0 +3673,38,13,65,91320,3,0.50,3,0,0,0,0,1,0 +3674,34,9,65,95134,4,1.30,1,0,0,0,0,0,1 +3675,42,16,38,93437,1,0.20,1,0,0,1,0,0,0 +3676,60,34,110,92126,2,2.00,1,0,0,0,0,1,0 +3677,62,37,22,95818,1,1.50,2,111,0,0,0,1,0 +3678,59,33,43,94234,2,0.30,1,0,0,0,0,0,1 +3679,49,25,30,92093,4,0.60,1,0,0,0,0,0,0 +3680,49,23,134,90095,2,6.30,1,0,0,0,0,1,0 +3681,36,11,32,90064,3,1.30,1,0,0,0,0,0,0 +3682,33,9,139,95054,1,4.30,1,0,0,0,0,0,0 +3683,43,17,45,95051,2,0.70,1,0,0,0,0,0,0 +3684,53,27,62,95070,3,3.00,2,0,0,1,0,0,0 +3685,57,31,51,92093,4,1.70,2,103,0,0,0,1,0 +3686,53,27,93,94588,1,0.80,3,313,0,0,0,0,0 +3687,60,35,122,92521,1,1.30,1,0,0,0,0,0,0 +3688,34,10,45,93943,1,1.33,1,0,0,0,0,0,0 +3689,51,26,179,90245,1,8.10,1,0,0,1,0,1,0 +3690,36,12,64,94708,3,2.80,1,205,0,0,0,0,1 +3691,63,39,41,95449,2,1.10,1,0,0,0,0,0,0 +3692,37,13,58,95211,2,0.60,3,0,0,0,0,0,1 +3693,57,33,64,94132,4,2.20,1,0,0,0,0,1,0 +3694,52,27,28,93117,3,1.70,2,0,0,0,0,0,0 +3695,38,8,21,92037,1,0.67,3,0,0,0,0,1,0 +3696,61,35,60,90272,1,2.80,2,0,0,0,0,1,0 +3697,31,5,78,94309,2,0.20,1,0,0,0,0,0,1 +3698,39,13,59,95616,3,0.50,3,0,0,0,0,0,0 +3699,38,12,59,96001,3,0.50,3,0,0,1,1,1,1 +3700,46,22,83,94501,4,1.40,2,0,0,0,0,1,1 +3701,48,22,128,94608,1,5.70,1,0,0,1,0,0,0 +3702,58,33,95,90503,1,2.60,1,0,0,0,0,1,0 +3703,50,25,160,93108,4,4.30,3,410,1,0,0,0,0 +3704,67,41,78,94301,4,2.40,3,0,0,1,0,0,0 +3705,36,11,184,91304,2,5.10,2,0,1,0,0,0,0 +3706,30,4,30,91770,3,1.00,1,0,0,0,0,1,0 +3707,58,33,51,94305,2,1.60,3,123,0,0,0,1,0 +3708,43,18,35,92647,1,0.60,3,0,0,0,0,0,0 +3709,31,1,74,92116,4,4.00,3,0,0,0,0,0,0 +3710,37,11,43,92521,4,1.20,2,0,0,1,0,0,0 +3711,49,22,23,90032,2,1.00,2,0,0,0,0,1,1 +3712,27,1,20,94720,4,0.40,1,99,0,0,0,1,0 +3713,50,25,112,92154,1,0.60,1,0,0,0,0,0,0 +3714,46,20,74,90064,3,0.70,2,0,0,0,0,1,1 +3715,49,23,65,94720,2,0.40,3,232,0,0,0,0,1 +3716,29,5,124,92037,2,0.20,1,0,0,0,0,0,1 +3717,55,29,65,91773,3,2.50,1,0,0,0,0,0,0 +3718,61,37,73,94550,3,2.00,3,285,0,0,0,0,0 +3719,45,19,8,92833,2,0.10,3,0,0,0,0,0,1 +3720,33,8,53,92126,3,2.30,1,76,0,0,0,1,0 +3721,63,39,131,92521,3,2.60,3,229,1,0,0,1,0 +3722,32,6,13,91040,4,0.30,1,0,0,1,1,1,1 +3723,42,17,60,93118,1,2.40,1,98,0,0,0,1,0 +3724,51,27,45,94022,1,1.60,2,82,0,0,0,1,0 +3725,44,20,39,93108,2,2.10,3,119,0,0,0,0,0 +3726,33,6,78,94305,4,2.00,2,0,0,0,0,0,0 +3727,39,13,43,94304,3,0.50,3,0,0,0,0,1,0 +3728,56,30,31,94117,2,0.30,1,109,0,1,1,1,1 +3729,28,3,118,91902,3,2.40,2,161,1,0,0,0,0 +3730,43,17,82,94040,3,0.10,1,0,0,0,0,1,0 +3731,30,6,112,92093,3,2.50,1,0,0,0,0,1,0 +3732,34,8,10,92867,1,0.40,2,0,0,0,0,1,0 +3733,26,1,18,92521,2,0.90,3,95,0,0,0,0,0 +3734,58,32,72,94105,3,0.30,2,0,0,0,0,1,0 +3735,43,19,72,95193,4,0.20,3,0,0,0,0,1,0 +3736,40,14,78,91103,1,5.20,1,0,0,0,0,1,0 +3737,54,30,78,96001,3,1.80,2,0,0,0,0,0,0 +3738,44,19,30,91423,1,0.50,3,0,0,0,0,1,0 +3739,54,28,45,95008,3,1.40,1,0,0,0,0,0,1 +3740,39,14,80,90502,2,0.40,1,0,0,0,0,0,0 +3741,59,35,174,92660,1,4.70,1,0,0,0,0,1,1 +3742,53,29,51,92152,2,3.20,3,0,0,0,0,1,0 +3743,32,8,181,94596,1,6.00,1,0,0,0,1,1,1 +3744,40,14,78,94720,4,1.40,2,194,0,0,0,1,1 +3745,54,29,79,90025,3,1.60,3,0,0,0,0,0,0 +3746,27,3,119,90640,1,5.40,1,118,0,0,0,1,0 +3747,63,39,49,93943,4,1.20,2,109,0,1,1,1,1 +3748,26,0,83,91360,3,3.90,2,0,1,0,0,1,0 +3749,33,7,100,94025,1,2.70,2,126,0,0,0,1,0 +3750,43,19,70,90095,3,2.33,1,0,0,0,0,1,0 +3751,57,32,52,90266,3,0.50,2,0,0,0,0,1,0 +3752,26,2,12,94591,4,1.00,1,0,0,0,0,1,0 +3753,55,30,82,93003,4,1.30,3,219,0,0,0,0,1 +3754,30,4,34,95351,2,0.30,2,0,0,0,0,1,1 +3755,63,37,112,93106,4,2.40,3,0,0,0,0,1,1 +3756,55,25,42,94115,3,1.00,3,0,0,0,0,1,0 +3757,35,11,83,92122,2,2.20,1,0,0,0,0,0,0 +3758,45,21,142,91101,1,1.40,2,0,1,0,0,1,0 +3759,47,23,199,94720,2,6.67,1,0,0,0,0,1,0 +3760,31,4,29,92093,4,1.50,2,121,0,0,0,1,1 +3761,56,26,70,91107,3,1.40,3,273,0,0,0,1,1 +3762,49,24,25,95831,2,0.70,3,0,0,0,0,1,0 +3763,53,27,84,95616,2,1.10,1,0,0,0,0,1,0 +3764,62,36,81,95051,3,4.40,1,0,0,0,0,0,1 +3765,63,37,15,94720,2,0.40,1,0,0,0,0,0,0 +3766,26,0,54,94706,3,0.30,3,0,0,0,0,1,0 +3767,59,35,108,90245,4,3.80,2,304,1,0,0,1,0 +3768,40,16,83,95819,4,2.67,1,0,0,0,0,1,1 +3769,42,16,62,94309,1,0.70,3,170,0,0,1,1,1 +3770,29,4,134,90095,2,3.30,1,204,0,0,0,0,0 +3771,40,16,75,94306,3,2.33,1,79,0,0,0,0,0 +3772,31,7,109,91711,2,2.00,2,341,0,0,0,0,1 +3773,35,10,152,94112,2,3.00,1,0,0,0,0,1,0 +3774,62,36,83,93940,4,2.40,3,0,0,1,0,0,0 +3775,51,26,52,92521,4,1.80,3,0,0,0,0,1,0 +3776,32,6,31,90275,2,2.00,3,0,0,0,0,1,1 +3777,27,3,135,93108,3,2.70,3,449,1,0,0,0,1 +3778,62,37,98,94706,1,0.90,1,151,0,0,0,1,0 +3779,66,41,14,95814,4,0.60,2,0,0,0,0,0,0 +3780,53,27,64,93407,4,2.60,1,0,0,0,0,1,1 +3781,49,25,109,92780,2,6.80,1,0,0,0,0,0,0 +3782,65,40,118,94104,1,1.30,1,333,0,0,1,1,1 +3783,30,5,80,91311,4,2.20,2,0,0,1,0,1,0 +3784,60,34,51,90028,3,1.40,3,0,0,0,0,0,0 +3785,30,6,115,94611,4,3.80,2,0,1,0,0,1,0 +3786,54,28,83,95841,1,2.40,1,0,0,0,0,1,0 +3787,54,28,90,91301,1,0.30,1,0,0,0,0,1,0 +3788,37,12,28,95616,4,1.70,1,0,0,1,1,1,0 +3789,32,7,82,95616,2,2.50,1,221,0,0,0,1,1 +3790,51,27,24,94301,3,0.40,1,0,0,0,0,1,1 +3791,46,22,71,92029,2,1.70,1,0,0,0,0,1,1 +3792,41,17,80,91330,1,0.30,1,0,0,0,0,0,0 +3793,62,36,109,92709,4,1.70,3,0,0,0,0,1,0 +3794,54,28,140,91711,1,2.90,1,0,0,0,0,1,0 +3795,52,27,39,92612,4,0.20,2,0,0,1,0,1,0 +3796,51,25,39,94010,1,1.20,2,98,0,0,0,1,0 +3797,24,-2,50,94920,3,2.40,2,0,0,1,0,0,0 +3798,61,35,31,92521,2,0.30,1,0,0,0,0,1,0 +3799,55,25,35,93943,3,1.00,3,144,0,0,0,1,1 +3800,37,11,44,93109,4,0.20,1,0,0,0,0,0,1 +3801,64,38,35,93955,1,0.50,3,0,0,0,0,1,0 +3802,34,8,20,95616,2,0.30,1,106,0,0,0,1,1 +3803,31,7,10,95616,4,0.70,2,0,0,0,0,1,0 +3804,42,18,83,96001,4,2.00,3,0,0,0,0,1,0 +3805,47,22,203,95842,2,8.80,1,0,0,0,0,1,0 +3806,29,5,84,93109,3,0.80,1,0,0,0,0,0,0 +3807,34,8,41,92096,4,0.80,1,0,0,0,0,0,0 +3808,36,11,164,95051,2,7.80,1,0,0,0,0,1,1 +3809,34,10,152,90089,2,6.50,1,0,0,0,0,0,0 +3810,26,2,62,94080,4,1.60,1,0,0,1,0,0,0 +3811,48,24,12,94707,4,1.00,1,89,0,0,0,0,0 +3812,47,23,28,94061,4,0.60,1,0,0,0,0,1,0 +3813,39,13,52,94720,1,2.00,1,0,0,0,0,0,1 +3814,62,37,19,91343,3,1.30,2,97,0,0,0,1,0 +3815,34,9,35,94304,3,1.30,1,0,0,0,0,0,0 +3816,43,19,28,95053,4,0.30,1,96,0,0,0,1,0 +3817,55,30,70,94904,3,2.00,2,0,0,0,0,1,1 +3818,65,40,140,92093,1,0.90,1,0,0,0,0,0,0 +3819,26,0,102,94305,4,2.30,3,0,0,0,0,0,0 +3820,57,27,50,93950,4,2.00,3,0,0,0,0,1,0 +3821,32,7,61,94102,3,2.30,1,205,0,0,0,1,1 +3822,35,9,188,92220,2,3.70,2,259,1,0,0,1,0 +3823,63,33,178,91768,4,9.00,3,0,1,0,0,0,0 +3824,49,25,44,94708,4,0.90,2,194,0,0,0,1,0 +3825,23,-1,12,95064,4,1.00,1,0,0,1,0,0,1 +3826,30,6,69,94305,4,3.40,1,188,0,0,0,0,1 +3827,43,19,132,90089,1,5.00,1,0,0,0,0,0,0 +3828,39,14,128,93943,2,3.90,1,196,0,0,0,1,0 +3829,31,6,44,95616,4,0.80,1,122,0,0,0,1,0 +3830,65,39,44,92038,1,0.50,3,0,0,0,0,1,1 +3831,34,8,34,92130,2,2.00,3,0,0,1,0,1,0 +3832,37,12,132,90089,2,3.90,1,0,0,0,0,0,0 +3833,62,38,158,90230,2,2.10,1,0,0,0,0,0,1 +3834,33,9,83,93943,1,0.10,1,0,0,0,0,1,0 +3835,48,22,28,94720,1,1.40,3,75,0,0,0,1,0 +3836,33,9,131,90065,3,2.20,3,0,1,1,0,0,0 +3837,45,19,31,95616,3,0.50,2,0,0,0,0,1,1 +3838,44,19,40,92350,4,0.00,2,0,0,0,0,1,0 +3839,37,11,71,94501,2,1.80,1,127,0,1,0,0,0 +3840,31,5,42,93010,2,2.00,3,0,0,0,0,1,0 +3841,56,31,35,95211,3,0.10,2,114,0,0,0,0,0 +3842,30,4,81,94305,2,0.20,1,0,0,0,0,1,0 +3843,61,35,91,95136,2,2.00,1,0,0,0,0,1,0 +3844,32,7,129,94720,4,5.20,2,0,1,0,0,0,1 +3845,51,27,75,95828,1,2.70,1,0,0,0,0,0,0 +3846,26,1,54,94061,4,0.60,2,230,0,0,0,0,0 +3847,31,5,43,94720,1,1.50,1,0,0,0,0,0,0 +3848,43,18,94,94110,4,1.10,2,0,0,0,0,0,0 +3849,57,32,84,93106,4,1.30,3,0,0,0,0,0,1 +3850,42,18,34,92653,1,2.00,2,0,0,1,0,0,0 +3851,48,23,15,94061,4,0.80,1,0,0,0,0,1,0 +3852,46,21,99,90277,2,3.80,3,194,0,0,0,1,0 +3853,33,7,15,92152,1,0.40,2,82,0,1,1,1,1 +3854,45,21,83,94105,4,2.00,3,0,0,0,0,1,0 +3855,31,6,83,94720,4,1.80,3,0,0,0,0,1,0 +3856,42,18,143,95630,1,1.70,1,0,0,1,0,1,0 +3857,56,30,81,90401,4,2.60,3,0,0,0,0,1,0 +3858,63,39,39,91711,1,1.90,2,0,0,0,0,0,0 +3859,42,18,158,92124,2,0.40,2,277,1,0,0,0,1 +3860,50,24,62,90245,1,1.40,3,0,0,0,0,0,0 +3861,31,6,64,92121,2,0.10,1,0,0,0,0,1,1 +3862,65,40,29,90025,1,1.50,2,0,0,0,0,0,0 +3863,60,34,64,94104,3,2.50,1,0,0,0,0,1,0 +3864,34,10,21,91770,4,0.70,2,0,0,0,0,1,0 +3865,62,32,142,95112,2,2.80,3,0,1,0,0,0,1 +3866,56,30,64,93105,3,2.50,1,0,0,0,0,0,0 +3867,51,25,40,91401,4,1.80,1,0,0,1,0,0,1 +3868,44,19,61,94080,3,2.70,2,0,0,0,0,0,0 +3869,41,16,44,92037,1,0.30,3,0,0,0,0,0,0 +3870,43,16,78,95670,3,2.67,2,161,0,0,0,1,1 +3871,25,0,25,94596,2,0.90,3,0,0,0,0,0,0 +3872,40,16,125,91304,2,1.90,1,0,0,0,0,0,1 +3873,53,29,63,94720,2,1.00,3,0,0,0,0,1,0 +3874,54,30,54,94550,1,1.60,3,185,0,0,0,1,0 +3875,36,12,92,94709,2,0.00,1,184,0,0,0,0,0 +3876,26,2,119,95351,2,0.60,1,381,0,0,0,1,1 +3877,35,11,40,91784,1,2.40,2,0,0,0,0,1,0 +3878,29,4,41,93105,1,1.00,1,0,0,0,0,0,0 +3879,35,11,81,92064,2,0.00,1,0,0,0,0,1,1 +3880,28,4,101,95136,3,2.50,1,270,0,0,0,0,0 +3881,48,24,25,90024,4,0.50,2,0,0,0,0,0,0 +3882,46,20,55,91016,1,1.50,2,0,0,1,0,0,0 +3883,31,7,43,92646,1,2.10,3,166,0,0,0,0,1 +3884,40,16,98,94534,2,1.80,2,98,0,0,0,1,0 +3885,27,1,112,91330,4,2.30,3,402,0,0,0,1,1 +3886,32,2,69,93943,4,4.00,3,102,0,0,0,1,0 +3887,67,43,79,95616,4,1.70,2,215,0,0,1,1,1 +3888,24,-2,118,92634,2,7.20,1,0,0,1,0,1,0 +3889,45,18,81,95133,3,2.67,2,251,0,0,0,1,1 +3890,26,0,19,93014,1,0.10,2,121,0,0,0,1,0 +3891,42,17,139,91101,2,2.90,3,0,1,0,0,1,0 +3892,65,40,63,94701,3,0.50,2,0,0,0,0,1,0 +3893,59,33,102,91763,2,1.40,1,0,0,0,0,1,0 +3894,30,5,40,92521,4,1.70,2,0,0,0,0,1,0 +3895,32,6,44,92886,1,0.30,1,81,0,0,0,1,1 +3896,36,12,59,94104,3,2.00,1,216,0,0,0,0,0 +3897,48,24,224,93940,2,6.67,1,0,0,0,1,1,1 +3898,56,31,64,90245,2,2.30,3,0,0,0,0,0,0 +3899,44,20,129,96001,2,3.30,1,0,0,0,0,1,0 +3900,60,34,43,92697,1,1.40,1,0,0,0,0,1,1 +3901,51,27,12,92834,3,0.40,1,0,0,1,1,1,1 +3902,34,10,53,94107,3,2.60,2,0,0,0,0,1,0 +3903,45,21,39,93305,2,2.10,3,0,0,0,0,0,1 +3904,47,23,65,93943,1,0.00,1,0,0,0,0,0,0 +3905,29,5,18,94122,1,0.40,3,94,0,0,0,1,1 +3906,52,28,55,94596,1,1.60,3,0,0,0,0,0,0 +3907,61,35,60,90245,1,2.50,3,0,0,0,0,1,0 +3908,40,14,42,91330,2,0.30,1,187,0,0,0,1,0 +3909,24,0,44,90638,3,0.10,2,0,0,0,0,0,0 +3910,33,7,111,90245,2,1.30,1,0,0,0,0,1,0 +3911,33,8,62,94596,1,1.00,1,0,0,0,0,1,0 +3912,52,26,44,94025,2,0.80,3,148,0,0,0,0,1 +3913,40,14,69,95348,1,1.50,3,0,0,0,0,0,0 +3914,45,20,62,92064,3,0.80,3,172,0,0,0,1,0 +3915,27,3,35,94080,1,1.80,2,0,0,0,0,0,0 +3916,38,13,91,92037,1,2.80,1,0,0,0,0,1,1 +3917,50,26,12,92121,1,0.20,1,96,0,0,0,0,0 +3918,41,15,89,94608,3,0.10,1,292,0,0,0,1,0 +3919,60,34,65,90024,4,1.70,2,0,0,1,0,1,0 +3920,64,34,179,90024,2,4.50,3,400,1,0,0,0,0 +3921,34,8,82,93106,2,1.50,3,0,0,1,1,1,1 +3922,30,6,48,95812,1,1.20,1,0,0,0,0,1,0 +3923,31,4,20,95616,4,1.50,2,0,0,0,0,1,0 +3924,41,15,91,90502,1,2.80,3,330,0,1,0,1,0 +3925,61,37,122,94609,2,6.00,1,0,0,0,0,1,0 +3926,42,18,22,90717,1,1.40,3,0,0,0,0,1,0 +3927,48,23,43,94301,2,1.30,1,0,0,0,0,1,0 +3928,59,34,38,90291,4,1.70,1,0,0,0,0,0,1 +3929,57,33,61,92115,3,2.67,1,0,0,0,0,1,0 +3930,37,13,33,91773,4,0.40,2,0,0,0,0,0,0 +3931,53,27,145,95605,1,2.90,1,345,0,0,0,0,0 +3932,53,27,170,95003,1,1.00,1,0,0,0,0,1,0 +3933,26,2,55,94305,3,0.70,2,0,0,0,0,1,0 +3934,39,14,40,91302,1,2.50,3,0,0,0,0,1,0 +3935,35,11,68,94923,2,0.00,1,126,0,0,0,0,1 +3936,59,33,53,90034,3,2.50,1,0,0,0,0,1,0 +3937,43,18,63,95616,3,0.80,3,0,0,1,0,0,0 +3938,39,15,123,91604,2,2.20,1,92,0,0,0,0,1 +3939,49,24,13,95929,2,0.00,1,0,0,0,0,1,0 +3940,47,23,12,92110,4,0.20,1,102,0,0,0,0,1 +3941,41,17,53,93727,2,2.50,1,102,0,0,0,1,0 +3942,57,33,79,94588,1,2.70,2,294,0,0,0,1,1 +3943,42,17,89,90095,1,0.10,2,170,0,0,0,1,0 +3944,61,36,188,91360,1,9.30,2,0,1,0,0,0,0 +3945,56,26,62,91320,3,1.40,3,0,0,0,0,1,0 +3946,29,3,123,92821,3,5.60,3,428,1,0,0,1,0 +3947,25,-1,40,93117,3,2.40,2,0,0,0,0,1,0 +3948,32,8,119,94710,4,5.00,3,0,1,0,0,1,0 +3949,37,12,123,94304,4,3.10,2,253,1,0,1,1,1 +3950,31,5,23,93407,1,0.40,2,0,0,0,0,1,1 +3951,38,14,62,94143,1,1.50,3,255,0,0,0,1,0 +3952,40,14,69,92870,3,2.10,1,106,0,0,0,1,0 +3953,61,36,124,94611,2,3.90,1,0,0,1,0,0,1 +3954,50,26,52,93555,4,0.10,3,0,0,0,0,0,0 +3955,32,7,134,93108,2,3.10,1,0,0,0,0,0,0 +3956,62,36,58,94501,1,0.80,2,0,0,0,0,0,0 +3957,62,37,45,90033,3,0.50,2,200,0,0,0,1,1 +3958,40,15,75,95449,4,1.10,2,0,0,0,0,1,0 +3959,59,34,23,90009,4,0.40,2,78,0,0,0,0,0 +3960,43,19,123,91107,3,1.30,1,0,1,0,0,1,0 +3961,62,37,48,92028,3,2.20,1,0,0,0,0,0,0 +3962,48,22,145,95482,1,0.30,1,140,0,0,0,1,0 +3963,29,5,31,93014,1,1.00,3,0,0,0,0,0,0 +3964,58,32,38,93106,3,2.20,3,0,0,0,0,1,0 +3965,43,18,78,94025,4,1.90,3,0,0,0,0,0,0 +3966,39,15,94,91941,2,1.90,1,0,0,0,0,1,0 +3967,33,7,84,95051,1,2.90,3,0,0,0,0,1,0 +3968,40,15,22,94306,1,0.60,3,0,0,0,0,1,0 +3969,28,3,78,93108,4,0.20,1,0,0,0,0,1,1 +3970,38,11,75,94305,3,2.33,2,0,0,0,0,1,0 +3971,65,40,71,95060,3,2.20,1,0,0,0,0,0,1 +3972,35,11,24,95616,1,0.50,3,0,0,0,0,1,1 +3973,29,5,112,94998,2,4.33,1,0,0,0,0,1,1 +3974,61,35,53,90064,1,2.80,2,167,0,0,0,1,0 +3975,46,21,41,94305,1,0.50,3,0,0,0,0,0,0 +3976,50,23,25,91330,1,0.50,2,0,0,0,0,1,0 +3977,60,33,42,90277,4,2.50,2,194,0,0,0,1,0 +3978,54,27,51,94309,3,1.00,2,113,0,1,1,1,1 +3979,43,18,19,92325,2,0.30,2,0,0,0,0,1,0 +3980,38,14,90,93010,2,0.00,1,258,0,1,1,1,1 +3981,46,22,89,92866,4,1.40,2,0,0,0,0,1,0 +3982,64,39,22,92691,3,0.50,1,0,0,1,1,1,1 +3983,24,0,119,94566,1,1.50,1,0,0,0,0,1,0 +3984,39,13,93,93555,4,3.60,3,0,1,0,0,1,0 +3985,34,8,18,95741,4,0.30,1,0,0,0,0,0,0 +3986,65,40,32,90095,1,1.10,3,120,0,0,0,1,0 +3987,38,14,182,92152,3,2.60,3,0,1,0,1,1,1 +3988,62,36,19,95833,2,0.20,3,0,0,0,0,1,1 +3989,59,35,85,91330,1,3.40,3,0,1,0,1,0,1 +3990,49,25,90,92709,4,1.40,2,0,0,1,0,1,0 +3991,57,32,59,95014,2,3.70,1,134,0,0,0,1,0 +3992,64,38,84,94571,1,2.00,1,0,0,0,0,0,0 +3993,47,22,95,93311,2,3.90,2,0,1,0,0,0,0 +3994,30,6,13,93555,3,0.90,3,0,0,0,0,1,0 +3995,42,18,88,92675,4,0.80,1,0,0,0,0,1,1 +3996,53,28,34,92697,2,0.60,3,0,0,0,0,1,1 +3997,50,24,11,94501,4,0.60,3,0,0,0,0,0,1 +3998,62,38,80,94545,4,1.70,2,0,0,0,0,0,0 +3999,34,10,41,94102,1,1.33,1,0,0,0,0,0,1 +4000,47,21,90,90245,2,0.80,3,0,0,0,0,0,0 +4001,62,37,93,93003,3,3.00,3,0,1,0,1,1,1 +4002,61,35,81,94709,4,1.90,2,0,0,0,0,0,0 +4003,59,34,60,94015,2,2.80,1,0,0,0,0,1,0 +4004,47,21,39,92612,3,0.60,2,0,0,0,0,1,1 +4005,65,39,22,92507,3,0.70,2,0,0,0,0,0,0 +4006,56,32,32,95827,2,0.80,1,79,0,1,0,1,0 +4007,56,32,28,92130,1,1.20,3,0,0,0,0,1,0 +4008,31,7,35,91745,2,1.00,2,0,0,0,0,0,1 +4009,61,31,154,94555,3,7.50,3,351,1,0,1,1,1 +4010,42,18,189,91605,2,7.60,1,0,0,0,0,1,0 +4011,44,19,40,94618,4,1.90,3,84,0,0,0,0,0 +4012,47,21,88,94304,2,1.70,2,0,0,0,0,1,0 +4013,30,6,124,91320,2,0.60,1,0,0,0,0,1,0 +4014,62,38,23,91304,2,0.30,3,0,0,0,0,0,0 +4015,56,32,23,94720,4,0.70,1,0,0,0,0,1,1 +4016,25,-1,139,93106,2,2.00,1,0,0,0,0,0,1 +4017,53,28,173,91614,4,2.70,1,427,1,0,0,1,0 +4018,26,0,42,92009,4,1.30,3,153,0,0,0,1,0 +4019,59,35,161,94301,1,2.90,1,160,0,0,0,0,1 +4020,62,36,28,95020,3,0.70,2,0,0,0,0,1,0 +4021,58,32,191,93943,4,5.20,3,194,1,0,0,0,1 +4022,40,14,42,90638,2,0.30,1,106,0,0,0,0,1 +4023,35,5,81,94234,4,4.00,3,0,0,0,0,1,0 +4024,51,25,175,90089,3,0.70,1,312,1,0,0,0,0 +4025,41,15,82,94720,3,0.10,1,0,0,0,0,1,0 +4026,51,27,53,94114,1,1.80,3,0,0,0,0,0,1 +4027,27,1,142,92038,3,5.50,1,0,1,0,0,0,0 +4028,46,21,42,93727,4,1.90,3,0,0,0,0,1,0 +4029,46,20,64,94117,4,2.90,1,189,0,0,0,0,0 +4030,31,5,90,94301,2,1.30,1,0,0,1,0,1,0 +4031,58,32,44,92354,1,0.80,2,0,0,0,0,0,0 +4032,42,18,29,91320,1,0.30,3,0,0,0,0,1,0 +4033,59,35,93,94301,2,1.60,1,0,0,0,0,0,1 +4034,54,24,69,93117,3,1.40,3,132,0,0,0,1,0 +4035,35,11,82,94022,2,1.70,2,0,0,0,0,1,1 +4036,34,9,180,93955,2,6.50,3,0,1,0,1,1,0 +4037,46,21,13,93117,2,0.70,3,0,0,0,0,1,0 +4038,52,28,72,91335,1,0.00,1,178,0,0,0,0,0 +4039,55,30,54,91367,3,1.70,1,0,0,0,0,1,0 +4040,34,9,104,92152,1,4.60,1,0,0,0,0,1,1 +4041,57,32,44,90266,2,1.90,2,157,0,0,0,0,0 +4042,45,19,40,95060,1,0.20,1,0,0,1,1,1,1 +4043,29,3,190,92612,2,4.50,1,246,0,0,0,1,1 +4044,49,23,64,94588,4,2.60,1,0,0,0,0,1,1 +4045,36,11,9,90266,2,0.30,2,99,0,1,0,0,0 +4046,57,31,38,94720,4,0.70,2,0,0,0,0,1,0 +4047,25,0,72,94303,3,2.60,3,0,0,0,0,1,0 +4048,43,17,82,94114,1,5.20,1,79,0,0,0,1,0 +4049,27,2,48,90049,2,1.60,3,119,0,1,0,1,0 +4050,54,28,82,94122,4,2.60,3,294,0,0,0,0,0 +4051,53,26,14,94590,2,1.00,2,83,0,0,0,0,0 +4052,55,29,162,93105,1,2.90,1,0,0,0,0,1,1 +4053,43,19,54,94608,2,1.70,1,0,0,0,0,1,0 +4054,35,11,90,94720,2,0.00,1,0,0,0,0,0,0 +4055,59,34,64,94116,4,1.70,1,0,0,0,0,0,0 +4056,42,18,65,93460,3,2.10,3,0,0,0,0,1,1 +4057,51,25,113,91320,2,6.30,1,0,0,0,0,0,0 +4058,57,32,38,90740,2,2.10,3,0,0,0,0,0,0 +4059,39,15,65,92037,1,1.50,3,0,0,0,0,0,0 +4060,53,27,39,91330,4,1.50,3,0,0,0,0,1,0 +4061,31,6,174,93023,2,6.70,1,0,0,0,0,1,1 +4062,33,3,59,91040,2,1.75,3,0,0,0,0,1,0 +4063,38,14,43,95053,2,1.70,1,0,0,0,0,1,0 +4064,47,21,24,94108,2,0.10,3,0,0,0,0,0,1 +4065,63,39,50,94402,1,0.00,2,166,0,0,0,0,0 +4066,44,19,68,94305,1,3.70,3,0,0,0,0,1,0 +4067,61,37,61,94122,3,2.00,3,0,0,0,0,1,0 +4068,52,28,21,94025,4,0.50,2,0,0,0,0,1,0 +4069,59,34,21,95035,2,0.50,2,0,0,0,0,1,0 +4070,56,32,31,94596,4,1.30,1,0,0,0,0,0,0 +4071,58,33,70,94720,4,0.70,1,0,0,1,0,0,0 +4072,30,6,25,94304,3,1.00,2,135,0,0,0,0,1 +4073,42,17,78,92521,1,1.00,3,0,0,0,0,1,0 +4074,51,27,19,92120,1,0.20,1,0,0,0,0,0,0 +4075,60,35,23,94608,1,0.30,3,0,0,0,0,1,0 +4076,30,4,40,90601,4,0.80,1,0,0,0,0,1,0 +4077,49,23,22,92220,1,0.30,3,0,0,0,0,0,0 +4078,26,0,71,92093,4,1.80,2,0,0,1,0,1,0 +4079,36,12,58,91320,1,3.60,2,0,0,0,0,0,0 +4080,65,40,75,90036,3,2.20,1,0,0,0,0,1,0 +4081,27,0,40,90068,1,2.00,2,110,0,0,0,0,1 +4082,60,35,155,92521,1,1.50,3,0,1,0,0,0,1 +4083,32,6,83,90036,4,2.20,2,0,0,0,0,0,0 +4084,46,20,99,94302,3,1.10,1,0,0,0,0,0,0 +4085,60,36,59,94124,1,0.00,2,0,0,1,0,0,0 +4086,28,2,53,94609,3,2.40,2,0,0,0,0,1,0 +4087,50,26,11,93106,4,0.20,1,0,0,1,0,0,0 +4088,52,28,179,94583,4,4.20,3,0,1,0,0,0,0 +4089,29,-1,71,94801,2,1.75,3,0,0,0,0,0,0 +4090,30,4,85,94234,4,2.10,3,0,0,0,0,1,0 +4091,42,18,49,92717,3,2.10,3,0,0,1,0,1,0 +4092,32,6,122,94025,2,1.30,1,0,0,0,0,1,1 +4093,40,15,171,94539,2,3.30,1,0,0,0,0,1,0 +4094,49,24,138,93111,2,2.20,2,0,1,0,0,1,0 +4095,53,23,8,95616,4,0.40,3,0,0,1,0,1,0 +4096,42,17,59,94105,4,0.40,1,0,0,0,0,1,0 +4097,38,14,49,90740,3,2.80,1,0,0,0,0,0,0 +4098,60,34,92,95670,2,2.00,1,0,0,0,0,0,0 +4099,27,3,75,90032,4,0.00,1,0,0,0,0,0,0 +4100,61,35,60,92831,1,2.80,2,0,0,0,0,1,1 +4101,27,2,41,90254,2,1.70,2,0,0,0,0,1,0 +4102,45,21,40,93460,3,0.60,2,0,0,0,0,1,1 +4103,41,16,81,94305,2,0.40,1,146,0,0,0,1,1 +4104,44,20,52,94143,1,0.80,3,196,0,0,0,0,1 +4105,38,14,25,95616,4,1.00,1,0,0,0,0,0,0 +4106,39,15,139,91801,1,3.40,1,353,0,0,0,1,0 +4107,48,22,54,93106,1,1.20,2,0,0,0,0,0,0 +4108,47,22,81,94123,1,2.90,1,0,0,0,0,0,1 +4109,64,39,73,94025,3,2.20,1,0,0,1,0,0,1 +4110,27,0,30,93107,4,1.00,3,0,0,0,0,1,1 +4111,66,41,59,95617,3,2.40,1,0,0,0,0,0,0 +4112,43,17,21,95351,3,1.50,1,0,0,0,0,0,0 +4113,34,9,65,95014,3,0.70,2,104,0,0,0,1,0 +4114,28,2,41,93118,3,1.10,2,161,0,0,0,1,0 +4115,52,28,52,92126,4,0.10,3,121,0,0,0,0,0 +4116,45,20,84,94131,4,1.10,2,180,0,0,0,1,0 +4117,24,-2,135,90065,2,7.20,1,0,0,0,0,1,0 +4118,39,14,18,92037,4,0.20,3,0,0,1,0,0,0 +4119,40,16,34,93561,1,0.70,1,0,0,0,0,1,1 +4120,30,5,85,92624,4,1.80,3,0,0,0,0,1,0 +4121,49,23,23,94080,1,1.40,3,0,0,0,0,0,0 +4122,53,27,65,91711,4,2.80,2,0,0,0,0,0,1 +4123,56,30,195,90089,1,2.90,1,0,0,0,0,0,0 +4124,50,24,40,93460,4,2.60,1,89,0,0,0,1,0 +4125,53,29,141,90064,2,0.20,3,0,1,0,0,0,0 +4126,60,34,95,94104,2,0.70,2,322,0,0,0,1,1 +4127,58,33,23,90095,3,1.30,2,131,0,0,0,0,0 +4128,43,19,82,95758,2,1.80,2,0,0,0,0,1,1 +4129,46,21,53,93555,4,1.90,3,0,0,0,0,0,0 +4130,29,3,10,91320,4,0.40,1,87,0,0,0,1,1 +4131,56,30,75,91910,1,1.90,2,125,0,0,0,1,0 +4132,48,23,23,94534,4,0.40,2,122,0,0,0,0,0 +4133,61,36,133,90266,1,2.60,1,0,0,0,0,1,0 +4134,41,17,129,94720,1,3.40,1,0,0,0,0,0,1 +4135,35,11,85,92154,4,0.10,2,131,0,0,0,0,0 +4136,48,23,168,95929,2,2.80,1,308,0,0,0,1,0 +4137,43,19,83,92691,4,2.00,3,0,0,0,0,1,0 +4138,37,12,52,93943,2,1.10,2,0,0,0,0,1,0 +4139,47,22,114,95819,1,0.60,1,0,0,1,1,1,1 +4140,29,3,81,95827,1,2.90,3,0,0,0,0,0,0 +4141,63,38,32,94015,1,1.50,2,0,0,0,0,0,0 +4142,43,19,63,94118,3,2.10,3,0,0,0,0,0,0 +4143,57,32,70,90024,3,1.60,3,0,0,0,0,0,0 +4144,55,31,20,94720,2,0.30,1,0,0,0,0,1,0 +4145,47,23,138,91367,2,3.30,1,0,0,0,0,1,1 +4146,58,34,63,94305,4,1.60,2,0,0,0,0,0,0 +4147,53,28,85,95814,1,1.30,3,118,0,0,0,1,0 +4148,59,35,180,96008,2,6.50,2,0,1,1,1,1,1 +4149,46,22,80,95747,4,2.00,3,0,0,0,0,1,0 +4150,41,15,53,93106,1,0.70,3,0,0,0,0,1,0 +4151,46,20,72,92009,2,1.70,2,75,0,0,0,1,0 +4152,44,18,123,95841,3,5.90,1,0,1,0,1,1,1 +4153,44,18,91,91361,2,0.80,3,0,0,0,0,1,0 +4154,50,26,148,94608,2,6.80,1,0,0,0,0,1,0 +4155,51,25,163,94305,2,1.30,3,0,1,0,0,1,0 +4156,55,30,28,90291,4,0.10,3,149,0,0,0,1,1 +4157,37,12,193,92780,1,8.60,1,0,0,0,0,0,0 +4158,34,10,22,94545,3,0.90,3,0,0,0,0,1,0 +4159,59,34,74,92780,4,0.70,1,0,0,0,0,1,1 +4160,45,20,70,94305,4,1.90,3,0,0,0,0,1,1 +4161,30,4,11,95054,1,0.10,2,0,0,0,0,1,1 +4162,32,8,61,94703,3,2.60,2,0,0,0,0,0,0 +4163,61,37,41,94704,1,0.80,1,0,0,0,0,1,1 +4164,54,28,108,94110,4,1.90,2,0,1,0,0,1,0 +4165,35,10,23,90058,4,1.10,3,0,0,0,0,0,1 +4166,63,38,135,91768,2,3.80,3,183,1,0,0,0,0 +4167,66,40,30,95133,2,0.70,3,86,0,0,0,0,0 +4168,48,24,144,94025,4,3.50,2,0,1,0,0,0,0 +4169,60,34,139,95020,4,0.40,1,0,1,0,0,1,0 +4170,41,17,143,90059,2,2.70,3,209,1,0,0,1,0 +4171,31,7,44,93561,1,1.20,1,0,0,0,0,1,1 +4172,58,31,49,94521,4,2.50,2,0,0,0,0,1,0 +4173,67,42,75,90041,4,0.10,2,182,0,0,0,1,0 +4174,35,9,43,93943,2,0.30,1,0,0,0,0,1,0 +4175,40,14,59,91335,3,0.50,3,0,0,0,0,1,0 +4176,42,17,154,93955,3,4.90,1,0,1,0,1,1,1 +4177,44,18,75,95131,1,0.70,3,0,0,0,0,0,1 +4178,47,23,75,93106,1,2.60,2,0,0,0,0,0,1 +4179,59,35,88,91311,2,1.60,1,278,0,0,0,0,0 +4180,29,3,91,94122,1,3.40,3,0,1,0,0,0,0 +4181,36,6,11,92008,1,0.67,3,0,0,1,1,1,1 +4182,47,22,22,90024,1,0.40,3,0,0,0,0,1,0 +4183,55,29,49,92691,2,0.80,3,220,0,0,0,0,1 +4184,41,17,140,94542,1,3.50,1,342,0,0,0,0,0 +4185,51,25,99,90277,2,2.40,2,0,0,0,0,0,0 +4186,26,2,82,91950,2,2.50,1,199,0,0,0,0,0 +4187,33,9,10,90005,4,1.00,1,81,0,0,0,0,1 +4188,30,5,109,94305,4,2.20,2,103,0,0,0,0,1 +4189,30,4,45,90041,4,1.30,3,0,0,0,0,0,0 +4190,45,19,93,91116,2,1.70,2,0,0,0,0,0,0 +4191,40,16,89,95814,3,3.90,2,216,1,1,1,1,0 +4192,42,15,39,91711,3,1.00,2,132,0,0,0,0,0 +4193,50,26,21,91768,1,0.20,1,89,0,0,0,1,0 +4194,62,37,31,95008,3,0.20,1,0,0,0,0,1,0 +4195,63,37,31,95819,1,0.50,3,0,0,0,0,1,0 +4196,43,19,52,95054,4,2.20,2,0,0,0,0,0,0 +4197,49,25,13,95814,1,0.90,3,0,0,0,0,1,0 +4198,51,25,21,90840,2,0.40,3,76,0,1,0,1,0 +4199,61,36,50,96003,4,1.70,1,189,0,0,0,1,0 +4200,43,19,81,90630,4,0.20,3,0,0,0,0,0,1 +4201,43,19,74,94035,4,1.90,1,0,0,0,0,0,1 +4202,61,36,89,93109,3,0.50,1,0,0,0,0,1,0 +4203,35,9,82,95064,3,0.90,2,0,0,0,0,1,0 +4204,59,33,88,93106,4,1.90,2,0,0,0,0,0,0 +4205,40,16,61,91711,3,2.10,3,0,0,0,0,0,0 +4206,61,36,139,95133,2,3.90,1,0,0,0,0,0,0 +4207,48,23,29,93711,1,1.30,2,0,0,0,0,0,0 +4208,37,11,51,93305,3,2.10,1,0,0,0,0,1,1 +4209,56,32,58,95064,1,1.80,3,241,0,0,0,1,0 +4210,35,9,21,91125,2,1.40,3,125,0,0,0,1,0 +4211,35,8,43,95819,2,1.67,2,0,0,0,0,0,0 +4212,40,16,104,94301,2,1.80,2,0,0,0,0,0,0 +4213,50,23,9,94109,1,0.50,2,98,0,0,0,1,0 +4214,49,25,39,91125,3,1.90,2,0,0,0,0,0,0 +4215,46,22,89,94303,1,2.70,1,0,0,1,1,1,1 +4216,64,40,21,94028,2,0.30,3,0,0,0,0,0,0 +4217,60,35,173,90059,3,3.10,3,0,1,0,0,1,0 +4218,45,21,29,95051,1,0.30,3,105,0,0,0,1,1 +4219,52,27,43,94005,4,0.20,2,0,0,0,0,0,1 +4220,58,34,30,90066,3,0.40,2,0,0,0,0,0,0 +4221,54,30,39,94806,4,0.10,3,0,0,1,0,1,0 +4222,48,22,83,90028,2,0.40,3,248,0,0,0,1,0 +4223,51,25,58,93106,3,0.70,2,223,0,0,0,0,0 +4224,53,26,8,94709,1,0.50,2,0,0,0,0,0,1 +4225,57,27,39,95929,3,1.00,3,0,0,1,0,0,1 +4226,43,18,204,91902,2,8.80,1,0,0,0,0,1,0 +4227,37,13,45,94591,1,1.80,1,0,0,0,0,0,0 +4228,32,7,111,90277,1,3.80,1,0,0,1,0,0,0 +4229,34,10,83,95060,2,2.00,2,148,0,0,0,0,0 +4230,54,24,83,94596,1,3.00,3,0,0,0,0,0,0 +4231,62,36,115,92093,2,2.80,1,202,0,0,0,1,1 +4232,56,32,60,93106,1,1.80,3,227,0,0,0,1,0 +4233,39,15,53,94116,1,1.80,1,0,0,0,0,0,0 +4234,32,7,134,95929,2,3.30,1,0,0,0,0,1,0 +4235,50,24,91,93555,1,0.80,3,0,0,0,0,1,0 +4236,27,1,91,92173,2,0.20,1,0,0,0,0,1,0 +4237,37,12,128,91342,2,3.90,1,0,0,0,0,1,1 +4238,60,34,78,90401,3,4.40,1,0,0,1,0,0,0 +4239,43,19,161,92093,2,7.60,1,464,0,0,0,1,0 +4240,62,36,60,92182,3,2.20,3,0,0,0,0,1,0 +4241,39,14,161,95064,1,4.10,1,509,0,1,0,0,0 +4242,34,9,40,95054,4,2.00,2,0,0,0,0,1,1 +4243,46,21,68,94720,1,0.20,2,0,0,0,0,1,0 +4244,46,22,74,94550,3,0.70,1,0,0,0,0,1,0 +4245,51,26,55,92121,3,2.00,2,93,0,0,0,1,0 +4246,44,20,145,90630,1,3.50,1,0,0,0,0,0,1 +4247,60,35,24,94920,1,1.50,2,0,0,0,0,0,0 +4248,65,39,10,90210,1,0.80,2,0,0,0,0,1,0 +4249,58,33,138,90720,2,3.90,1,0,0,1,0,1,0 +4250,37,12,63,91942,4,2.10,3,0,0,0,0,1,0 +4251,52,28,54,90041,4,0.10,3,0,0,0,0,0,1 +4252,42,16,62,95064,3,0.90,3,0,0,0,0,1,0 +4253,54,29,81,91107,1,0.10,3,0,0,0,0,0,0 +4254,54,28,61,90601,3,3.00,2,0,0,0,0,1,1 +4255,51,27,68,91711,1,1.60,3,0,0,0,0,1,0 +4256,59,35,78,90095,2,2.80,1,0,0,0,0,1,0 +4257,41,17,165,91311,2,7.60,1,157,0,0,0,0,0 +4258,43,17,48,95762,3,2.20,2,0,0,0,0,0,1 +4259,52,26,155,92660,3,7.20,2,0,1,0,0,1,0 +4260,52,26,158,94920,2,3.70,3,251,1,0,0,0,1 +4261,57,31,52,94105,1,1.40,1,0,0,0,0,1,0 +4262,53,28,18,92507,4,0.80,1,0,0,0,0,0,0 +4263,58,33,42,92093,4,1.70,1,0,0,0,0,0,0 +4264,59,33,18,94542,2,0.20,3,0,0,0,0,0,0 +4265,57,31,40,94304,2,0.30,1,0,0,1,1,1,1 +4266,27,2,44,93943,4,0.60,2,0,0,1,1,1,0 +4267,42,16,11,94015,1,0.20,1,87,0,0,0,0,1 +4268,52,26,194,91902,2,5.70,2,0,1,0,0,1,0 +4269,49,23,108,95616,2,2.40,2,0,0,0,0,1,0 +4270,47,23,12,92518,4,0.50,2,0,0,0,0,0,0 +4271,45,19,19,93117,3,1.50,1,94,0,0,0,1,1 +4272,25,1,150,92507,1,6.33,1,0,0,0,0,0,0 +4273,47,22,89,92647,4,1.90,3,0,0,0,0,1,0 +4274,44,19,83,95812,2,3.80,3,0,0,1,0,0,1 +4275,30,3,79,91380,4,2.00,2,0,0,0,0,1,0 +4276,63,38,102,95616,4,3.40,2,0,0,0,0,0,0 +4277,50,24,155,92717,1,7.30,1,0,0,0,0,1,1 +4278,40,16,138,92612,1,3.50,1,0,0,0,0,1,0 +4279,56,31,51,92028,3,1.70,1,0,0,0,0,1,1 +4280,39,15,80,94608,2,1.80,2,86,0,0,0,1,1 +4281,42,18,135,95136,2,3.30,1,0,0,1,1,1,1 +4282,28,1,34,94949,4,1.50,2,162,0,0,0,0,1 +4283,26,0,195,92093,3,6.33,3,0,1,1,1,1,0 +4284,58,32,62,91320,3,2.20,3,217,0,0,1,1,1 +4285,38,13,173,94305,2,3.30,1,243,0,0,0,0,0 +4286,23,-3,149,93555,2,7.20,1,0,0,0,0,1,0 +4287,53,29,20,93955,1,0.20,1,131,0,0,0,1,1 +4288,54,28,42,95207,4,2.50,1,0,0,0,0,1,1 +4289,42,17,28,94010,1,0.60,3,0,0,0,0,0,1 +4290,54,28,95,90254,1,1.90,2,0,0,0,0,1,0 +4291,66,42,95,94596,2,0.00,3,0,0,0,0,1,0 +4292,46,21,34,90034,1,0.10,1,124,0,0,0,1,0 +4293,63,37,191,94131,2,4.30,3,205,1,0,0,0,0 +4294,63,38,41,90034,2,1.50,1,173,0,0,0,1,1 +4295,58,34,150,92110,1,7.40,1,481,0,0,0,1,0 +4296,65,41,91,91360,2,0.00,3,146,0,0,0,0,0 +4297,35,9,84,94709,4,2.20,2,0,0,0,0,1,0 +4298,33,9,73,92110,4,3.40,1,140,0,0,0,1,0 +4299,43,19,122,93106,1,0.30,1,0,0,0,0,1,0 +4300,30,5,73,90065,1,2.60,2,133,0,0,0,1,0 +4301,61,37,20,95973,2,0.30,3,0,0,0,0,1,0 +4302,49,24,130,92677,4,1.10,1,281,1,0,1,1,0 +4303,52,27,85,92037,3,3.40,3,0,1,0,0,0,0 +4304,45,21,134,94550,2,3.30,1,0,0,0,0,1,1 +4305,64,39,98,95678,3,1.80,2,80,0,0,0,1,0 +4306,26,1,54,91709,2,1.60,3,0,0,1,0,0,0 +4307,35,11,41,92123,3,2.00,1,0,0,0,0,1,0 +4308,45,19,128,94928,4,6.00,3,0,1,0,0,1,0 +4309,44,20,132,94115,3,2.60,1,308,1,0,0,0,0 +4310,34,8,188,94025,1,2.90,3,0,1,0,0,1,0 +4311,65,41,170,94143,4,6.10,2,0,1,0,1,1,1 +4312,32,8,14,90034,3,0.90,3,111,0,0,0,0,0 +4313,41,15,93,95616,1,2.80,3,0,0,0,0,1,0 +4314,52,28,79,94596,1,2.70,2,0,0,0,0,1,1 +4315,35,9,79,94305,4,2.20,2,0,0,0,0,0,0 +4316,51,26,62,90024,4,1.80,3,119,0,0,0,1,0 +4317,30,6,95,91950,2,0.20,1,0,0,1,0,1,0 +4318,58,33,60,92672,4,1.30,3,0,0,0,0,1,0 +4319,49,23,75,92374,1,1.50,2,0,0,0,0,0,1 +4320,63,38,85,91320,4,0.10,2,0,0,0,0,0,1 +4321,40,15,143,94801,1,4.10,1,0,0,0,0,1,0 +4322,27,0,34,92717,1,2.00,2,112,0,0,0,0,1 +4323,38,14,44,91320,2,1.70,1,0,0,0,0,0,0 +4324,52,28,31,92008,4,0.90,2,151,0,1,0,1,0 +4325,49,24,13,94538,4,0.80,1,111,0,0,0,1,0 +4326,59,35,52,95616,4,1.50,1,0,0,0,0,1,1 +4327,32,8,42,95136,1,0.20,3,102,0,0,0,1,0 +4328,30,4,102,91775,4,2.10,3,139,0,0,0,0,1 +4329,64,38,143,95039,2,6.40,3,0,1,1,1,1,0 +4330,59,33,10,94063,4,0.70,3,0,0,0,0,1,0 +4331,62,37,44,90401,1,1.10,3,0,0,0,0,0,0 +4332,61,37,158,94720,2,6.00,1,306,0,1,1,1,1 +4333,53,26,12,92672,2,1.00,2,0,0,0,0,0,1 +4334,51,26,59,90095,1,1.20,1,139,0,0,0,1,0 +4335,55,29,92,92130,1,1.90,2,0,0,0,0,0,0 +4336,36,10,82,94542,2,2.80,1,0,0,0,0,0,1 +4337,44,19,44,90509,4,0.00,2,0,0,0,0,0,0 +4338,26,2,182,93010,2,3.20,2,0,1,0,0,0,0 +4339,54,30,121,92121,2,0.40,1,0,0,0,0,1,0 +4340,35,11,38,95518,1,1.70,1,0,0,0,0,0,1 +4341,34,10,92,90024,2,2.70,1,0,0,1,1,0,1 +4342,28,3,53,94305,2,1.60,3,0,0,0,0,0,0 +4343,32,7,45,93611,3,2.30,1,83,0,1,0,1,0 +4344,38,14,63,95422,1,3.60,2,0,0,1,0,1,0 +4345,53,28,181,95051,1,8.10,1,0,0,0,0,1,0 +4346,26,1,184,94608,2,4.20,3,577,1,0,1,1,1 +4347,45,21,33,94970,3,0.50,1,136,0,0,1,1,1 +4348,58,33,22,90024,3,0.20,1,0,0,0,0,1,0 +4349,59,33,99,92093,2,2.70,1,0,0,0,0,0,0 +4350,45,18,44,90089,3,1.00,2,193,0,0,0,0,0 +4351,64,39,101,95134,4,3.40,2,0,0,0,0,0,1 +4352,30,3,32,94132,1,2.00,2,0,0,0,0,1,1 +4353,40,16,59,94305,4,2.67,1,0,0,0,0,1,0 +4354,61,36,25,94015,2,0.50,2,0,0,0,0,1,1 +4355,40,16,140,93940,3,5.60,1,0,1,0,0,0,0 +4356,40,10,29,94720,1,0.75,3,0,0,0,0,1,0 +4357,43,19,35,90630,1,0.70,1,0,0,0,0,0,0 +4358,39,14,141,93302,4,6.30,1,0,1,1,1,1,1 +4359,35,11,75,92672,4,2.00,3,79,0,0,0,0,0 +4360,38,12,58,95054,2,2.80,1,0,0,0,0,1,0 +4361,67,43,41,90024,2,1.10,1,0,0,0,0,0,0 +4362,55,30,42,93940,2,2.00,2,196,0,0,0,0,1 +4363,28,2,55,93940,3,1.10,2,0,0,0,0,0,0 +4364,30,4,18,93711,4,0.30,2,84,0,0,0,1,0 +4365,59,35,75,92121,4,2.30,3,0,0,1,0,0,0 +4366,26,2,85,95020,2,2.50,1,0,0,0,0,0,0 +4367,52,28,43,90089,4,1.10,2,0,0,0,0,0,0 +4368,40,15,149,90250,2,3.90,1,319,0,0,0,1,1 +4369,31,7,25,93943,2,1.00,2,0,0,1,1,1,1 +4370,50,25,19,94005,4,0.40,2,103,0,0,0,1,1 +4371,27,3,18,93524,1,0.40,3,0,0,0,0,0,0 +4372,64,39,13,90024,4,0.60,2,0,0,0,0,1,0 +4373,34,10,41,91765,1,2.40,2,0,0,0,0,0,0 +4374,30,6,139,94501,1,4.30,1,0,0,0,0,1,0 +4375,39,15,62,93955,3,2.33,1,131,0,0,1,1,1 +4376,34,10,51,90032,3,2.00,1,130,0,0,0,0,0 +4377,40,15,71,93950,3,3.00,1,272,0,0,0,1,0 +4378,33,8,145,92507,1,2.70,3,0,1,0,0,1,0 +4379,38,12,45,91768,4,1.20,2,138,0,0,0,1,0 +4380,42,17,53,93023,4,1.90,3,0,0,0,0,1,0 +4381,37,13,64,94105,1,1.50,3,0,0,0,0,1,0 +4382,33,8,39,94542,4,0.80,1,0,0,0,0,1,0 +4383,60,34,38,92182,3,2.20,3,0,0,1,0,0,0 +4384,28,4,85,94709,3,2.50,1,0,0,0,0,1,0 +4385,45,20,61,92717,3,2.70,2,0,0,0,0,0,1 +4386,56,32,23,94610,1,1.20,3,127,0,0,0,1,1 +4387,53,27,122,94305,1,2.40,1,330,0,0,0,0,0 +4388,37,12,72,91380,4,0.70,3,0,0,0,0,0,0 +4389,47,21,123,90840,1,7.30,1,0,0,0,0,0,0 +4390,58,32,40,90057,1,1.60,1,0,0,1,1,1,1 +4391,52,26,62,95134,4,2.80,2,0,0,0,0,1,0 +4392,46,22,113,94105,2,3.30,1,0,0,0,0,0,1 +4393,52,27,81,92634,4,3.80,2,0,0,0,0,0,0 +4394,24,0,59,95521,4,1.60,1,0,0,0,0,0,0 +4395,57,31,25,94523,2,0.70,2,103,0,0,0,0,0 +4396,66,41,25,94720,4,0.60,2,0,0,0,0,1,1 +4397,30,5,14,95014,4,0.50,3,0,0,0,0,1,0 +4398,48,23,19,90058,1,0.10,1,0,0,0,0,1,0 +4399,63,37,61,91942,1,2.50,3,0,0,0,0,0,0 +4400,48,23,21,94904,1,0.10,1,0,0,0,0,0,0 +4401,34,10,44,94143,1,1.33,1,0,0,0,0,1,0 +4402,60,35,42,91902,3,1.50,1,0,0,0,0,0,1 +4403,55,25,52,90095,1,1.40,3,207,0,1,0,0,0 +4404,50,24,112,92064,1,0.00,1,0,0,0,0,0,0 +4405,29,5,34,94301,1,0.40,3,0,0,0,0,0,0 +4406,61,35,83,91320,2,1.70,3,245,0,0,0,1,0 +4407,50,25,24,95133,4,0.40,2,137,0,0,0,1,0 +4408,37,13,71,90755,2,1.70,2,0,0,0,0,1,1 +4409,64,40,181,93403,2,2.30,2,0,1,0,1,1,1 +4410,43,19,75,91765,4,0.20,3,102,0,0,0,1,0 +4411,39,14,153,91614,2,3.00,1,0,0,0,0,0,0 +4412,23,-2,75,90291,2,1.80,2,0,0,0,0,1,1 +4413,34,10,19,91711,4,0.40,2,0,0,0,0,0,0 +4414,29,2,31,91775,4,1.50,2,0,0,0,0,0,1 +4415,33,8,178,94720,3,8.50,1,0,1,1,1,1,0 +4416,60,35,65,90245,2,1.50,1,220,0,0,0,0,1 +4417,49,25,8,94720,1,0.30,1,97,0,0,0,0,0 +4418,54,28,92,92374,2,1.10,1,0,0,0,0,1,0 +4419,59,34,145,95125,4,1.80,1,198,1,0,0,1,0 +4420,42,17,85,93065,1,3.70,3,272,0,0,0,0,0 +4421,62,38,149,92130,1,4.70,1,0,0,0,0,1,0 +4422,63,38,9,94707,4,0.60,2,100,0,0,0,1,1 +4423,57,31,164,94607,2,3.80,3,422,1,0,1,1,1 +4424,61,36,40,95816,3,0.50,2,100,0,1,0,0,0 +4425,35,10,54,93943,1,2.50,3,0,0,0,0,0,1 +4426,26,0,164,95973,2,4.00,3,301,1,0,0,1,0 +4427,33,8,140,95814,1,4.60,1,0,0,0,0,1,0 +4428,31,7,18,91711,1,0.40,3,0,0,0,0,0,0 +4429,51,27,12,95818,4,1.00,1,0,0,1,0,1,0 +4430,55,29,140,94720,2,2.70,1,0,0,0,0,1,0 +4431,38,12,24,94588,2,0.80,3,0,0,0,0,1,1 +4432,38,12,60,92806,2,1.80,1,0,0,0,0,1,0 +4433,53,27,50,92660,2,0.80,3,0,0,0,0,1,0 +4434,62,38,44,92612,1,1.90,2,0,0,0,0,0,1 +4435,35,9,51,94596,4,2.20,2,110,0,0,0,1,0 +4436,46,21,34,90840,2,1.30,1,116,0,0,0,0,0 +4437,60,35,33,90095,2,0.50,2,0,0,0,0,1,0 +4438,63,38,63,92507,2,1.50,1,0,0,0,0,1,0 +4439,43,18,22,90025,2,0.00,3,0,0,0,0,0,0 +4440,33,7,104,94542,2,3.60,3,0,1,0,0,0,1 +4441,43,19,75,90041,3,0.30,3,0,0,0,0,0,0 +4442,62,36,75,92709,2,1.70,3,0,0,0,0,0,0 +4443,48,23,62,91367,4,3.60,3,83,0,0,0,0,1 +4444,38,14,48,90034,1,1.80,1,169,0,0,0,0,0 +4445,36,10,73,95035,2,2.80,1,0,0,0,0,1,1 +4446,49,25,135,90064,2,1.40,1,82,0,0,0,1,1 +4447,61,35,61,92177,3,2.20,3,117,0,0,0,1,1 +4448,49,22,78,95616,3,2.00,2,0,0,0,0,1,0 +4449,59,34,40,94102,3,0.90,3,0,0,0,0,1,0 +4450,30,6,44,95211,1,0.20,3,0,0,0,0,0,1 +4451,44,20,45,94111,2,2.50,1,0,0,0,0,1,0 +4452,67,41,18,92130,2,0.40,1,0,0,0,0,1,0 +4453,59,35,53,90035,4,2.30,3,174,0,0,0,1,0 +4454,37,11,11,94112,3,0.10,2,0,0,0,0,0,0 +4455,50,24,38,94143,3,0.60,2,0,0,0,0,1,0 +4456,56,31,28,94040,1,1.50,2,0,0,1,1,1,1 +4457,29,3,35,94040,2,0.30,1,88,0,0,1,1,1 +4458,55,29,81,92843,3,1.70,2,171,0,0,0,1,0 +4459,48,22,90,94590,2,0.80,3,205,0,0,0,0,0 +4460,32,8,115,90064,1,4.00,1,0,0,0,0,0,0 +4461,47,22,78,92093,1,0.20,2,0,0,0,0,1,0 +4462,46,21,30,94301,4,1.90,3,0,0,0,0,1,0 +4463,33,7,39,95630,4,0.80,1,0,0,0,0,1,1 +4464,39,13,69,94123,3,0.10,1,0,0,0,0,0,0 +4465,60,35,29,93943,3,0.20,1,79,0,0,0,1,1 +4466,39,15,54,94108,4,2.20,2,0,0,0,0,0,1 +4467,34,10,60,90071,3,2.80,1,0,0,0,1,1,1 +4468,55,30,99,91768,1,0.10,3,0,0,0,0,0,0 +4469,67,42,51,94117,3,2.20,1,0,0,0,0,1,1 +4470,40,14,53,94025,3,0.50,3,0,0,1,1,1,1 +4471,44,20,111,91911,2,5.30,2,0,1,0,0,1,0 +4472,56,30,79,94588,3,0.80,1,302,0,0,0,0,0 +4473,50,25,90,95616,1,2.80,2,0,0,0,0,1,0 +4474,31,5,18,92115,2,0.30,1,124,0,0,0,1,1 +4475,66,41,73,95817,3,2.40,1,0,0,0,0,0,0 +4476,43,18,59,95039,3,0.80,3,91,0,0,0,1,0 +4477,58,32,40,95833,2,0.30,1,0,0,0,0,0,0 +4478,33,9,41,92028,1,1.50,2,0,0,0,1,1,1 +4479,33,9,53,91380,1,2.10,3,0,0,0,0,0,0 +4480,32,8,128,93117,2,4.33,1,0,0,0,0,1,0 +4481,55,30,145,92037,2,6.00,3,0,1,0,0,1,0 +4482,25,-2,35,95045,4,1.00,3,0,0,0,0,1,0 +4483,40,14,28,90404,2,0.80,3,0,0,0,0,0,0 +4484,54,28,155,90095,1,1.00,1,256,0,0,0,1,1 +4485,36,11,195,95747,2,3.00,1,0,0,0,0,1,1 +4486,35,9,50,92182,4,2.20,2,0,0,0,0,0,0 +4487,44,19,48,92735,3,0.80,3,0,0,0,0,0,1 +4488,38,14,81,94583,1,3.60,2,0,0,0,0,1,1 +4489,30,4,50,91030,1,1.50,1,0,0,0,0,0,0 +4490,39,13,21,95518,3,0.20,2,0,0,0,0,1,0 +4491,35,9,142,90250,2,0.00,1,0,0,1,0,1,0 +4492,41,16,64,91604,4,0.40,1,0,0,0,0,1,0 +4493,56,26,91,94939,1,3.00,3,0,0,0,0,1,1 +4494,52,28,74,96064,1,2.60,2,0,0,0,0,1,1 +4495,29,4,182,95354,1,3.70,3,0,1,0,0,1,0 +4496,38,14,82,95616,4,2.67,1,0,0,0,0,0,0 +4497,51,25,45,95616,4,2.60,1,0,0,0,0,0,0 +4498,45,21,85,95136,2,3.20,1,0,0,1,0,1,0 +4499,51,26,133,90291,1,0.60,1,328,0,0,0,0,0 +4500,53,26,22,91304,1,0.50,2,0,0,0,0,1,1 +4501,50,26,24,94305,4,0.50,2,0,0,0,0,0,1 +4502,59,33,38,94132,3,2.20,3,178,0,1,1,1,1 +4503,57,32,80,92647,2,0.00,3,0,0,0,0,0,0 +4504,45,21,33,92374,3,0.50,1,108,0,0,0,1,0 +4505,27,1,41,93023,4,1.80,3,147,0,0,0,0,0 +4506,40,15,90,94063,4,1.10,2,0,0,1,0,1,0 +4507,39,13,89,92037,1,2.80,3,153,0,0,0,1,1 +4508,26,1,8,94550,2,0.90,3,0,0,0,0,0,1 +4509,27,2,85,94117,1,1.90,1,0,0,0,0,1,1 +4510,55,30,53,94550,3,1.70,1,0,0,0,0,1,0 +4511,64,39,20,93109,3,0.10,3,0,0,0,0,0,0 +4512,41,17,9,91911,1,1.00,1,0,0,0,0,1,1 +4513,46,22,25,95747,4,0.60,1,0,0,0,0,1,1 +4514,43,19,114,92325,1,1.70,1,0,0,0,0,1,0 +4515,24,-3,41,91768,4,1.00,3,0,0,0,0,1,0 +4516,29,3,49,94305,4,2.10,3,0,0,0,0,0,0 +4517,58,32,12,95929,4,0.70,3,0,0,0,0,1,0 +4518,45,18,50,91902,3,2.50,2,0,0,0,0,1,0 +4519,53,28,30,94609,4,0.20,2,0,0,0,0,1,0 +4520,45,21,32,92399,4,0.60,1,77,0,0,0,0,1 +4521,32,7,41,94706,4,2.00,2,0,0,0,0,0,0 +4522,56,31,25,95123,3,0.10,2,0,0,0,0,0,0 +4523,31,5,29,90630,1,0.30,1,0,0,0,0,0,0 +4524,29,4,50,94040,4,1.70,2,0,0,0,0,1,0 +4525,48,24,79,94542,3,0.70,1,0,0,0,0,1,1 +4526,36,11,110,94110,1,3.80,1,0,0,0,0,1,1 +4527,36,9,40,92518,2,1.67,2,129,0,1,0,1,0 +4528,41,16,18,90024,1,0.60,3,0,0,0,0,0,1 +4529,48,23,48,94086,1,0.30,1,0,0,0,0,0,0 +4530,27,0,40,92103,4,1.00,3,0,0,0,0,0,0 +4531,33,9,19,95370,2,1.00,2,92,0,0,0,1,0 +4532,31,7,35,94025,1,1.33,1,131,0,0,0,0,1 +4533,48,22,133,90073,2,3.10,2,0,1,0,0,1,0 +4534,59,34,19,95762,2,0.50,2,0,0,0,0,1,0 +4535,41,17,83,94025,4,2.67,1,0,0,0,0,1,0 +4536,42,18,39,96091,3,2.10,3,0,0,0,0,0,0 +4537,62,37,38,92354,3,0.50,2,0,0,0,0,0,0 +4538,62,36,63,95929,1,2.50,3,0,0,0,0,1,1 +4539,51,24,85,94305,3,2.00,2,0,0,0,0,0,0 +4540,48,24,14,94305,4,1.00,1,0,0,0,0,1,0 +4541,56,32,64,90210,4,1.50,1,0,0,0,0,1,0 +4542,62,38,124,95023,1,3.80,1,405,0,0,0,1,0 +4543,53,29,20,94131,1,0.20,1,0,0,1,1,1,1 +4544,62,38,33,95134,3,0.10,3,0,0,0,0,1,0 +4545,28,4,80,95819,3,2.50,1,0,0,0,0,1,0 +4546,61,35,35,90025,2,0.20,3,0,0,0,0,1,0 +4547,48,24,74,91109,3,0.70,1,0,0,1,0,1,0 +4548,50,25,32,94304,2,0.70,2,0,0,0,0,1,0 +4549,58,33,73,93109,4,0.70,1,241,0,0,0,0,0 +4550,53,29,41,94080,2,0.80,1,0,0,0,0,1,0 +4551,65,40,18,95621,1,1.50,2,0,0,0,0,1,0 +4552,27,0,28,91330,4,1.50,2,0,0,0,0,1,0 +4553,50,23,64,92037,1,2.67,2,0,0,0,0,0,0 +4554,50,25,44,92093,2,0.70,2,192,0,0,0,1,0 +4555,41,16,109,94801,3,1.00,1,0,0,1,0,1,0 +4556,43,19,71,95054,3,0.30,3,179,0,0,0,0,0 +4557,55,29,79,94608,2,1.10,1,0,0,1,0,1,0 +4558,33,9,30,95054,2,1.00,2,0,0,0,0,1,0 +4559,44,19,82,95521,2,0.40,1,0,0,0,0,1,1 +4560,47,20,101,91950,3,2.00,2,270,0,0,0,1,0 +4561,43,18,13,94709,2,0.10,2,0,0,0,1,1,1 +4562,59,33,59,91365,3,1.40,3,0,0,0,0,0,0 +4563,65,40,64,94928,2,1.50,1,0,0,0,0,0,1 +4564,28,2,188,92350,2,4.50,1,0,0,1,0,1,0 +4565,58,32,28,90095,2,0.30,1,148,0,0,0,0,0 +4566,33,8,120,92614,2,4.20,3,76,1,0,0,0,1 +4567,24,0,131,92831,1,5.40,1,0,0,0,0,1,0 +4568,46,20,19,94105,3,0.50,2,97,0,1,0,1,0 +4569,26,0,44,94305,4,1.30,3,0,0,1,0,0,0 +4570,47,21,49,92152,3,2.20,2,0,0,1,0,0,0 +4571,32,6,99,91902,2,4.50,3,249,0,0,0,1,0 +4572,58,28,95,94304,1,3.00,3,0,0,0,0,0,0 +4573,32,7,81,95112,4,1.80,3,0,0,0,0,1,0 +4574,46,20,73,95616,2,0.80,3,264,0,0,1,1,1 +4575,35,11,193,91765,2,6.50,1,0,0,0,0,0,1 +4576,53,27,115,90095,2,0.50,3,0,1,0,0,0,0 +4577,55,30,41,93003,2,0.60,3,0,0,0,0,1,1 +4578,63,37,80,90401,2,1.70,3,0,0,0,0,1,1 +4579,45,20,90,94143,4,1.10,2,0,0,0,0,1,1 +4580,58,32,41,94305,1,0.20,1,81,0,0,0,1,0 +4581,50,24,102,91103,2,6.30,1,0,0,0,0,1,0 +4582,37,13,59,94234,1,1.50,3,0,0,0,0,0,1 +4583,25,-1,69,92691,3,0.30,3,0,0,0,0,1,0 +4584,52,26,83,92521,1,3.10,1,0,1,0,0,1,0 +4585,26,0,49,90089,3,2.40,2,0,0,0,0,0,0 +4586,35,11,180,94010,1,3.60,3,571,1,0,1,1,1 +4587,58,32,61,91910,3,2.20,3,0,0,0,0,1,1 +4588,37,11,59,94720,4,0.20,3,0,0,0,0,0,0 +4589,35,10,85,95351,4,2.10,3,0,0,0,0,0,1 +4590,31,7,13,93727,1,0.50,3,0,0,0,0,1,0 +4591,58,34,151,94022,3,0.60,2,0,1,0,0,0,0 +4592,43,16,44,94577,3,1.00,2,0,0,0,0,1,0 +4593,43,18,53,92115,3,0.80,3,154,0,0,0,0,0 +4594,54,30,133,95747,1,5.00,2,0,1,0,0,0,1 +4595,53,27,31,91320,3,0.90,3,78,0,0,0,1,0 +4596,32,7,101,90232,4,2.20,2,0,0,0,0,1,0 +4597,37,13,61,95131,3,2.80,1,0,0,0,0,0,0 +4598,34,10,68,90095,3,2.60,2,0,0,0,0,0,0 +4599,51,26,21,94143,4,0.80,1,0,0,0,0,1,0 +4600,49,25,149,90024,2,0.40,1,0,0,0,0,1,0 +4601,54,24,75,93555,1,1.40,3,0,0,0,0,0,0 +4602,37,12,55,95630,1,2.50,3,0,0,0,0,1,0 +4603,57,32,81,94305,2,3.70,1,226,0,0,0,1,1 +4604,37,12,179,91768,1,8.60,1,0,0,0,0,1,0 +4605,32,7,81,90601,2,3.40,2,0,1,0,0,0,1 +4606,48,22,42,94611,1,1.20,2,0,0,0,0,0,0 +4607,44,20,199,94607,2,6.67,1,0,0,0,0,1,0 +4608,50,23,18,93117,1,0.50,2,0,0,0,0,1,1 +4609,44,19,28,91604,1,0.30,3,0,0,0,0,1,0 +4610,54,28,80,95006,4,2.60,3,143,0,0,0,0,0 +4611,37,13,79,91330,1,3.60,2,104,0,0,0,1,0 +4612,34,7,52,93940,2,1.00,2,0,0,0,0,1,0 +4613,32,6,18,92007,2,0.30,2,0,0,0,0,1,0 +4614,63,38,52,91361,4,1.70,1,218,0,0,0,1,1 +4615,56,30,15,92093,4,0.70,3,102,0,0,0,0,0 +4616,37,12,84,93943,4,0.70,3,0,0,0,0,1,0 +4617,66,41,114,92521,1,0.80,3,0,0,0,0,1,1 +4618,38,13,41,95521,3,0.50,3,0,0,0,0,0,1 +4619,35,9,29,95354,3,0.90,1,126,0,0,0,1,0 +4620,61,36,23,95521,1,0.10,1,96,0,0,0,0,0 +4621,52,26,84,94132,1,2.40,1,0,0,0,0,1,0 +4622,57,32,60,93407,3,1.70,1,0,0,1,1,1,1 +4623,47,20,13,94545,3,0.67,2,0,0,0,0,1,0 +4624,50,25,45,90813,2,0.60,3,0,0,0,0,0,0 +4625,36,11,83,90638,1,2.80,1,0,0,0,0,0,0 +4626,45,21,102,92037,4,4.70,2,81,1,0,0,0,0 +4627,58,34,58,90034,4,2.30,3,169,0,0,0,1,0 +4628,27,1,134,93106,1,1.70,2,307,1,0,0,1,0 +4629,27,1,130,94801,3,2.90,2,0,1,0,0,0,0 +4630,48,24,148,91311,2,3.30,1,0,0,0,1,1,1 +4631,46,21,92,92886,1,0.20,2,0,0,0,0,0,0 +4632,32,8,142,90095,4,6.20,2,120,1,0,1,1,1 +4633,54,29,62,94720,4,0.70,1,0,0,0,0,0,1 +4634,31,5,50,93106,1,1.50,1,0,0,0,0,1,0 +4635,42,17,29,94928,1,0.60,3,0,0,0,0,1,0 +4636,30,5,85,91910,2,2.50,1,293,0,1,1,1,1 +4637,41,16,78,95616,4,0.40,1,0,0,0,0,1,0 +4638,44,19,85,92054,4,1.90,3,0,0,0,0,1,1 +4639,37,13,89,91711,2,1.70,2,0,0,0,0,1,0 +4640,51,25,33,92866,3,0.90,3,0,0,0,0,1,1 +4641,30,6,42,90034,1,2.10,3,0,0,0,0,1,0 +4642,36,11,31,94022,4,1.70,1,124,0,0,0,1,1 +4643,65,40,143,95616,4,6.60,2,0,1,0,0,1,0 +4644,33,7,35,95616,4,0.80,1,0,0,0,0,1,0 +4645,58,34,22,94608,1,0.10,2,0,0,0,0,1,0 +4646,34,10,45,92038,1,1.70,1,84,0,0,0,0,0 +4647,38,13,119,94545,2,3.30,1,0,0,0,0,0,0 +4648,59,35,43,95616,4,1.30,1,0,0,0,0,1,0 +4649,37,11,75,94704,3,0.90,2,0,0,0,0,1,0 +4650,59,35,121,91423,1,4.30,1,0,0,0,0,1,0 +4651,47,23,63,95521,1,0.80,3,0,0,0,0,1,0 +4652,48,24,58,94005,2,1.70,1,0,0,0,0,0,0 +4653,38,12,184,91311,3,8.00,1,0,1,0,0,1,0 +4654,34,10,155,92780,2,6.50,1,0,0,0,0,1,1 +4655,44,17,69,90095,3,2.67,2,0,0,0,0,0,0 +4656,33,7,188,95054,2,7.00,2,581,1,0,0,0,0 +4657,47,21,38,91101,3,0.60,2,0,0,1,0,0,0 +4658,41,16,9,90089,2,0.30,2,0,0,0,0,0,1 +4659,36,11,69,95929,4,2.10,3,0,0,0,0,1,1 +4660,28,4,199,92121,1,6.33,1,0,0,0,0,0,0 +4661,59,35,38,92122,1,0.80,1,0,0,0,0,1,0 +4662,43,19,129,95039,1,5.00,1,0,0,1,0,1,0 +4663,56,31,59,94303,2,1.90,2,0,0,0,0,1,0 +4664,28,3,115,92407,1,1.90,1,200,0,0,0,1,0 +4665,62,37,83,93657,4,0.10,2,0,0,0,0,0,0 +4666,40,16,65,90095,2,3.20,1,0,0,0,0,1,0 +4667,34,9,72,94555,3,2.30,1,124,0,0,0,0,0 +4668,52,28,72,94720,1,1.60,3,0,0,0,0,1,0 +4669,40,14,63,94025,3,0.50,3,221,0,0,0,1,0 +4670,27,1,64,94501,4,1.80,2,0,0,0,0,1,1 +4671,52,26,194,94305,1,1.70,1,0,0,0,0,1,0 +4672,39,14,104,95035,1,4.00,3,0,0,0,1,1,1 +4673,52,26,180,95831,1,1.70,1,550,0,0,0,1,0 +4674,50,23,18,95503,2,1.00,2,88,0,0,0,1,1 +4675,40,14,93,93933,1,2.80,3,328,0,1,1,1,1 +4676,35,11,32,91360,1,1.33,1,137,0,0,0,1,1 +4677,39,13,68,91950,3,2.10,1,0,0,1,0,1,0 +4678,25,0,38,93407,2,1.60,3,0,0,0,0,0,0 +4679,33,7,115,93305,1,2.70,2,283,0,0,0,1,0 +4680,26,0,161,94551,2,7.20,1,0,0,0,0,0,0 +4681,46,21,154,90245,2,2.80,1,94,0,0,0,0,0 +4682,27,3,68,95503,4,0.00,1,0,0,0,0,0,1 +4683,55,25,44,92093,3,1.00,3,0,0,0,0,1,0 +4684,52,28,149,92121,2,0.40,1,0,0,0,0,0,0 +4685,59,34,103,91360,1,2.60,1,0,0,0,0,1,0 +4686,63,39,41,91355,4,1.30,2,0,0,0,0,1,0 +4687,61,35,113,91741,2,2.80,1,0,0,0,0,0,0 +4688,58,34,48,93460,4,1.30,2,0,0,0,0,1,1 +4689,29,3,69,92093,4,1.80,2,0,0,0,0,1,1 +4690,51,27,43,95053,4,1.10,2,164,0,0,0,1,1 +4691,59,34,19,92192,1,0.30,3,0,0,0,0,1,0 +4692,41,17,65,90024,3,2.10,3,0,0,0,0,1,0 +4693,59,35,32,92064,3,0.40,2,0,0,0,0,0,1 +4694,52,28,20,95616,1,0.30,1,0,0,0,0,0,0 +4695,39,13,25,94132,2,0.80,3,0,0,0,0,0,0 +4696,45,19,70,95605,1,2.80,1,0,0,0,0,0,1 +4697,59,35,70,92103,4,2.30,3,0,0,0,0,0,0 +4698,49,22,103,91330,3,2.00,2,167,0,0,0,0,0 +4699,48,22,162,94143,3,1.40,1,400,1,0,0,0,0 +4700,61,36,61,91320,2,2.80,1,153,0,0,0,0,1 +4701,31,7,170,95006,1,6.00,1,0,0,0,0,1,0 +4702,42,16,49,90034,1,2.80,1,0,0,0,0,0,0 +4703,35,5,108,90630,2,2.75,3,0,1,1,0,0,0 +4704,57,27,62,94025,3,2.00,3,0,0,0,0,1,0 +4705,54,28,102,91360,3,1.70,2,0,0,0,0,1,0 +4706,61,37,141,92677,3,0.70,1,0,1,0,1,1,1 +4707,60,36,8,92626,2,1.00,1,0,0,0,0,0,0 +4708,59,35,91,95008,2,1.60,1,0,0,1,0,0,1 +4709,62,37,10,92606,3,0.50,1,0,0,0,0,1,0 +4710,26,1,35,90089,2,1.70,2,119,0,0,0,0,1 +4711,41,17,71,92182,3,0.30,3,0,0,0,0,0,1 +4712,65,40,59,94022,3,2.40,1,0,0,0,0,0,0 +4713,25,0,14,94309,2,0.90,3,0,0,0,0,0,1 +4714,25,1,122,93022,2,0.20,1,0,0,0,0,1,0 +4715,27,3,81,90291,3,1.50,1,307,0,1,1,1,1 +4716,65,39,35,92009,1,0.50,3,150,0,0,0,1,0 +4717,60,34,83,95616,2,1.40,1,75,0,1,0,1,0 +4718,29,5,121,95449,1,1.50,1,0,0,0,0,1,0 +4719,32,6,35,91107,3,1.00,1,0,0,1,0,1,0 +4720,32,8,140,94102,4,6.60,3,0,1,0,1,0,1 +4721,41,15,88,90740,1,2.80,3,0,0,1,0,0,0 +4722,52,26,70,94117,2,1.10,1,0,0,1,0,1,0 +4723,40,16,63,92807,1,1.50,3,0,0,0,0,0,0 +4724,39,15,125,90250,1,3.50,1,0,0,0,0,1,1 +4725,34,8,21,94107,4,1.00,1,0,0,0,0,0,0 +4726,34,8,75,95814,2,1.80,1,0,0,0,0,0,0 +4727,34,10,38,95039,1,1.33,1,0,0,1,0,1,0 +4728,41,17,58,92009,4,2.67,1,0,0,0,0,1,1 +4729,59,35,31,90630,3,0.40,2,0,0,0,0,1,0 +4730,40,14,18,90049,4,1.50,3,0,0,0,0,0,0 +4731,52,27,29,94720,1,1.50,2,159,0,0,0,0,1 +4732,37,11,29,91711,2,1.40,3,0,0,0,0,1,1 +4733,39,13,69,92096,3,0.10,1,247,0,0,0,0,0 +4734,49,23,121,90032,1,4.90,1,0,0,0,0,1,0 +4735,63,39,64,95814,1,1.80,3,147,0,0,0,1,1 +4736,34,9,84,94707,4,2.20,2,323,0,0,0,1,0 +4737,51,25,65,94143,3,0.70,2,0,0,0,0,0,0 +4738,61,36,85,94998,3,1.80,2,0,0,0,0,0,0 +4739,56,32,44,94575,3,1.50,1,153,0,0,0,1,0 +4740,62,38,174,94305,1,4.70,1,0,0,0,0,1,1 +4741,56,30,178,93940,1,2.90,1,0,0,0,0,1,0 +4742,58,32,55,93106,4,2.50,1,0,0,0,0,1,0 +4743,58,33,25,92121,4,0.90,2,90,0,0,0,1,1 +4744,50,26,21,94305,1,0.20,1,0,0,0,0,1,0 +4745,44,20,72,95616,3,0.30,3,0,0,0,0,1,0 +4746,49,23,129,94085,1,0.30,1,0,0,0,0,1,1 +4747,31,7,18,95616,1,0.40,3,0,0,0,0,1,0 +4748,49,25,91,94704,4,1.40,2,0,0,0,0,1,0 +4749,43,18,38,94309,1,0.50,3,144,0,0,0,1,0 +4750,31,5,21,94115,3,1.00,1,0,0,0,0,1,0 +4751,66,41,38,95134,1,1.10,3,0,0,0,0,0,1 +4752,41,17,154,92697,1,1.70,1,0,0,0,0,0,1 +4753,39,14,178,92123,1,4.10,1,207,0,0,0,1,0 +4754,46,21,85,92867,1,0.20,2,0,0,1,1,1,1 +4755,57,33,93,94025,2,1.60,1,161,0,0,0,0,0 +4756,59,35,151,93106,2,6.00,1,0,0,0,0,1,0 +4757,30,4,78,92677,4,2.20,2,236,0,1,0,0,0 +4758,26,2,135,94588,1,1.50,1,0,0,0,0,0,0 +4759,46,21,40,90045,1,0.30,1,116,0,0,0,0,0 +4760,66,41,80,92093,4,0.10,2,0,0,0,0,1,0 +4761,50,25,18,95819,2,0.00,1,0,0,0,0,0,1 +4762,61,35,74,91320,2,0.70,2,0,0,0,0,1,1 +4763,37,7,94,91016,4,1.80,3,232,0,0,0,1,0 +4764,51,25,173,95051,1,0.50,2,0,1,0,0,1,0 +4765,56,32,88,95051,4,1.00,2,0,0,0,0,1,1 +4766,58,34,82,94025,1,4.30,1,263,0,0,0,0,0 +4767,41,15,54,91775,3,2.10,1,0,0,0,0,1,0 +4768,35,9,45,90639,3,0.90,1,101,0,1,0,0,0 +4769,38,14,39,93118,1,2.00,2,0,0,0,0,1,0 +4770,26,2,20,95064,4,1.00,1,116,0,0,0,0,0 +4771,35,5,93,90095,4,1.80,3,0,0,0,0,0,1 +4772,36,11,85,90502,3,1.20,3,0,0,0,0,1,0 +4773,26,2,95,92130,3,0.80,1,0,0,0,0,1,0 +4774,53,28,48,92029,2,1.90,2,0,0,0,0,1,0 +4775,56,32,22,91768,1,1.20,3,0,0,0,0,1,1 +4776,44,14,33,94063,1,0.75,3,171,0,0,0,0,0 +4777,47,23,40,95123,2,2.10,3,156,0,0,0,1,0 +4778,32,8,30,94534,4,0.40,2,78,0,0,0,1,0 +4779,52,27,22,90755,4,0.80,1,0,0,0,0,1,1 +4780,39,14,20,90747,1,0.60,3,0,0,0,0,1,0 +4781,47,20,49,92104,3,2.50,2,0,0,0,0,1,0 +4782,35,9,25,94526,3,0.10,2,0,0,1,0,1,0 +4783,26,0,150,91311,2,7.20,1,0,0,0,0,0,1 +4784,43,19,32,94720,4,0.30,1,0,0,0,0,0,0 +4785,52,28,9,90405,2,0.20,1,0,0,0,0,0,0 +4786,30,5,23,94304,2,0.90,3,0,0,1,0,1,0 +4787,36,12,18,95521,4,1.00,1,0,0,0,0,1,1 +4788,48,22,42,95054,3,0.60,2,121,0,0,0,1,0 +4789,36,10,39,92009,1,2.00,1,153,0,0,0,0,0 +4790,58,34,84,95120,4,1.60,2,0,0,0,0,1,0 +4791,35,11,101,94143,3,3.80,3,150,1,0,0,1,0 +4792,59,35,43,91791,4,0.40,1,0,0,0,0,0,1 +4793,36,10,28,90840,4,1.00,1,130,0,0,0,1,0 +4794,45,21,59,94703,2,2.50,1,155,0,0,0,1,0 +4795,56,30,29,94110,4,1.50,3,146,0,0,0,0,0 +4796,46,21,39,91710,2,1.30,1,101,0,0,0,1,0 +4797,26,0,42,95032,4,1.30,3,0,0,1,0,0,0 +4798,37,11,24,94115,4,1.00,1,0,0,0,0,0,0 +4799,44,20,62,91604,3,0.30,3,0,0,0,0,0,1 +4800,44,20,33,94306,4,0.30,1,142,0,0,0,0,1 +4801,33,7,73,94028,1,2.50,1,135,0,0,0,0,0 +4802,34,10,88,94404,2,0.00,1,121,0,0,0,1,0 +4803,35,11,58,91330,3,2.80,1,0,0,0,0,1,0 +4804,48,24,48,92064,2,2.10,3,0,0,0,0,1,0 +4805,58,32,40,94124,1,2.80,2,0,0,0,0,0,0 +4806,30,6,160,90630,1,4.30,1,249,0,0,0,1,0 +4807,62,37,39,93117,3,1.50,1,0,0,0,0,1,0 +4808,40,14,53,90064,1,2.00,1,0,0,0,0,1,1 +4809,42,16,32,90033,3,0.50,2,0,0,0,0,0,1 +4810,43,19,32,94501,3,0.60,2,0,0,0,0,0,0 +4811,58,34,11,92037,2,0.30,1,96,0,0,0,1,0 +4812,36,12,123,90502,2,3.00,3,0,1,0,0,0,0 +4813,29,4,184,92126,4,2.20,3,612,1,0,0,1,0 +4814,49,23,60,95023,3,0.70,2,142,0,0,0,1,1 +4815,60,34,41,90064,3,2.20,3,0,0,0,0,0,1 +4816,58,32,99,92697,2,1.40,1,0,0,0,0,0,1 +4817,50,24,83,92333,3,3.00,2,0,0,0,0,0,1 +4818,46,22,134,93305,2,3.30,1,0,0,0,0,0,0 +4819,45,19,85,94112,2,1.70,2,0,0,0,0,1,0 +4820,32,6,41,95833,3,0.90,1,179,0,0,0,0,0 +4821,42,17,44,94124,1,0.30,3,0,0,1,1,1,1 +4822,30,6,62,95831,1,0.10,1,0,0,0,0,1,1 +4823,60,36,149,92007,1,4.70,1,0,0,0,0,1,0 +4824,46,21,115,95616,2,4.20,3,0,1,1,1,1,1 +4825,32,6,25,96001,3,1.00,1,0,0,0,0,1,0 +4826,56,32,84,95014,2,1.60,1,0,0,0,0,1,0 +4827,56,31,81,93943,2,0.00,3,225,0,0,0,0,0 +4828,30,6,181,91203,1,4.30,1,230,0,0,0,1,0 +4829,52,28,62,90089,1,1.80,3,0,0,0,0,1,0 +4830,31,7,11,94304,1,0.50,3,80,0,0,0,1,1 +4831,37,12,60,95616,4,2.10,3,217,0,0,0,1,0 +4832,30,6,42,91711,1,2.10,3,144,0,0,0,0,1 +4833,29,4,83,91950,4,2.20,2,0,0,0,0,1,1 +4834,49,24,109,92647,1,0.60,1,0,0,0,0,0,0 +4835,49,23,70,94305,1,0.30,1,217,0,0,0,0,0 +4836,65,39,25,95370,2,0.40,1,113,0,0,0,1,0 +4837,54,24,72,93943,3,1.40,3,218,0,0,0,0,1 +4838,36,10,183,95348,2,0.00,1,0,0,0,0,0,0 +4839,56,30,44,91330,4,2.50,1,0,0,0,0,0,1 +4840,34,8,52,95060,4,0.20,1,0,0,0,0,1,0 +4841,33,9,18,91768,4,0.40,2,0,0,0,0,1,0 +4842,59,35,40,92870,4,0.40,1,135,0,0,0,1,0 +4843,49,23,174,95449,3,4.60,2,590,1,0,0,0,0 +4844,61,34,41,94123,4,2.50,2,0,0,0,0,1,0 +4845,31,6,81,90840,2,2.50,1,313,0,0,0,0,0 +4846,45,21,128,94305,1,4.70,1,0,0,0,0,0,0 +4847,35,10,135,94596,3,4.80,2,0,1,0,0,1,0 +4848,37,11,65,94143,2,2.40,2,260,0,0,0,1,0 +4849,58,32,145,94920,2,0.50,1,119,0,0,0,1,0 +4850,49,25,65,90007,2,1.00,3,0,0,0,0,1,1 +4851,63,39,119,91330,1,2.90,1,0,0,1,0,1,0 +4852,55,31,124,93407,2,0.30,1,0,0,0,0,1,0 +4853,38,12,33,94708,4,1.50,3,0,0,1,0,0,1 +4854,45,19,41,91109,1,0.20,1,0,0,0,0,1,0 +4855,44,20,105,91730,1,4.70,1,0,0,0,0,0,1 +4856,58,32,130,94720,2,2.70,1,0,0,0,0,1,0 +4857,56,31,80,92069,4,1.30,3,0,0,0,0,1,0 +4858,37,13,115,90025,1,0.80,2,0,0,0,0,1,1 +4859,50,24,62,94550,2,0.80,3,0,0,0,0,1,0 +4860,34,8,165,91107,1,7.00,3,541,1,0,0,0,0 +4861,51,25,34,93106,3,0.60,2,128,0,0,0,1,0 +4862,49,24,18,95616,1,0.40,3,121,0,0,0,1,0 +4863,33,7,44,95605,1,0.30,1,0,0,0,0,0,0 +4864,61,35,25,91768,1,0.80,2,142,0,0,0,1,0 +4865,41,16,52,91311,2,2.20,3,0,0,0,0,1,0 +4866,50,24,133,90025,4,1.40,2,342,1,0,0,0,1 +4867,41,17,71,94801,2,3.20,1,0,0,0,0,1,1 +4868,38,12,61,94598,4,0.20,3,0,0,0,0,1,0 +4869,51,27,62,94063,2,3.20,3,118,0,0,0,0,1 +4870,63,39,33,92121,3,0.10,3,0,0,0,0,0,1 +4871,55,30,28,94040,2,2.00,2,0,0,0,0,1,1 +4872,46,22,53,95616,4,1.90,1,187,0,0,0,0,0 +4873,27,3,69,94305,3,0.70,2,0,0,0,0,1,1 +4874,59,35,165,94309,2,6.00,1,0,0,0,0,1,0 +4875,26,0,75,94061,3,0.30,3,0,0,0,0,0,0 +4876,61,36,54,94539,3,1.50,1,0,0,0,0,1,0 +4877,44,19,142,95054,1,1.50,3,0,1,0,0,0,0 +4878,53,29,53,92648,4,0.10,3,0,0,0,0,0,0 +4879,34,9,41,92093,1,1.00,1,0,0,0,0,1,0 +4880,40,15,43,90095,4,1.70,1,98,0,0,0,0,0 +4881,56,32,79,92037,3,2.67,1,0,0,0,0,1,0 +4882,57,32,24,92346,2,0.20,3,140,0,0,0,1,0 +4883,43,19,73,94301,3,2.33,1,0,0,1,1,1,1 +4884,38,13,129,92646,3,4.10,3,0,1,0,1,1,1 +4885,60,34,50,95670,3,2.20,3,0,0,0,0,1,1 +4886,54,30,28,92103,2,0.80,1,0,0,0,0,1,0 +4887,51,26,64,94005,4,1.80,3,0,0,0,0,0,0 +4888,41,15,49,90245,3,0.90,3,0,0,0,1,1,1 +4889,25,1,121,93106,1,5.40,1,158,0,0,0,1,0 +4890,58,28,58,90073,3,2.00,3,0,0,0,0,1,0 +4891,61,35,51,93555,3,1.40,3,0,0,0,0,1,0 +4892,56,31,61,90024,4,0.90,1,0,0,1,1,1,1 +4893,43,19,35,94112,1,0.30,3,120,0,1,0,1,0 +4894,42,12,39,94704,3,2.00,3,0,0,1,1,1,1 +4895,48,22,74,93950,1,1.40,3,0,0,1,0,0,0 +4896,45,20,201,92120,2,2.80,1,0,0,0,0,1,1 +4897,40,15,81,94304,2,0.40,1,0,0,0,0,1,0 +4898,43,18,44,91345,1,2.40,1,0,0,0,0,0,0 +4899,52,26,19,94143,1,1.40,3,96,0,0,0,1,0 +4900,54,29,85,94928,4,1.30,3,299,0,0,0,1,0 +4901,26,1,74,90028,4,2.20,1,0,0,0,0,1,0 +4902,26,0,54,96094,3,1.10,2,0,0,0,0,1,0 +4903,33,8,58,90505,2,2.50,1,0,0,0,0,1,0 +4904,40,15,18,94534,2,0.10,2,119,0,0,0,1,1 +4905,64,40,88,94305,1,3.80,1,243,0,0,0,1,1 +4906,62,37,19,93109,3,0.50,1,89,0,0,0,0,0 +4907,54,28,49,94608,1,2.20,3,128,0,0,0,0,0 +4908,34,9,101,94080,3,0.60,2,0,0,0,0,0,0 +4909,40,16,138,92121,2,6.10,1,0,0,0,0,1,0 +4910,41,16,25,95014,2,0.10,2,0,0,0,0,0,1 +4911,48,22,120,90291,1,0.00,1,0,0,0,0,1,0 +4912,46,22,153,94539,2,7.50,1,0,0,0,0,0,0 +4913,51,26,28,94061,1,1.30,2,94,0,1,0,1,0 +4914,30,4,110,93943,1,2.90,3,0,0,0,0,1,0 +4915,65,39,94,92374,1,2.00,1,0,0,0,0,0,1 +4916,49,24,48,93117,1,1.30,2,0,0,0,0,0,1 +4917,29,5,123,90291,2,0.60,1,0,0,0,0,1,0 +4918,36,10,33,95616,4,1.20,2,82,0,1,0,1,0 +4919,50,25,42,90232,2,0.70,2,110,0,0,0,0,1 +4920,41,16,68,92122,3,3.00,1,0,0,0,0,1,1 +4921,42,16,28,94002,4,1.50,3,91,0,0,0,1,1 +4922,37,11,42,95814,3,0.50,3,0,0,0,0,1,1 +4923,31,5,28,90717,1,0.30,1,0,0,0,0,1,1 +4924,40,15,73,92029,3,3.00,1,0,0,0,0,1,1 +4925,36,12,89,91304,2,2.70,1,0,0,0,0,0,0 +4926,64,39,82,94025,4,3.40,2,0,0,0,0,1,0 +4927,37,13,83,92220,2,1.70,2,0,0,0,0,0,1 +4928,43,19,121,94720,1,0.70,2,0,1,0,1,1,1 +4929,57,33,28,90245,1,1.20,3,98,0,0,0,1,0 +4930,62,36,39,92028,2,0.30,1,0,0,0,0,1,0 +4931,63,38,110,90095,3,1.80,2,109,0,0,0,1,0 +4932,57,27,55,95616,1,1.40,3,0,0,0,0,1,0 +4933,59,35,111,91107,1,4.30,1,0,0,0,0,1,0 +4934,47,23,94,92029,1,4.70,1,0,0,0,0,1,1 +4935,26,0,85,93950,2,1.60,3,0,0,0,0,1,1 +4936,59,33,81,94022,2,1.40,1,0,0,0,0,1,0 +4937,45,20,94,92009,3,0.50,3,0,0,0,0,0,0 +4938,33,8,162,94960,1,8.60,1,0,0,0,1,1,1 +4939,61,35,80,95973,4,1.70,3,0,0,0,0,1,0 +4940,54,29,70,92093,3,2.00,2,116,0,0,0,1,1 +4941,46,22,19,92870,3,0.50,1,0,0,0,0,1,0 +4942,28,4,112,90049,2,1.60,2,0,1,0,0,1,0 +4943,52,26,109,94710,1,2.40,1,308,0,0,1,1,1 +4944,26,0,12,96003,1,0.10,2,0,0,0,0,1,0 +4945,49,24,33,92093,3,1.70,2,0,0,0,0,1,0 +4946,42,18,49,95351,2,1.70,1,106,0,0,0,0,1 +4947,51,26,42,93118,1,1.30,2,0,0,0,0,1,0 +4948,39,13,41,95064,2,0.30,1,108,0,0,0,1,1 +4949,44,20,43,95032,1,0.70,1,0,0,0,0,0,1 +4950,29,5,64,94114,4,0.00,1,249,0,0,0,0,1 +4951,47,23,19,90089,1,1.00,1,0,0,0,0,0,1 +4952,53,27,65,92124,1,2.20,3,0,0,0,0,1,1 +4953,29,3,53,94005,4,1.80,3,0,0,0,0,1,0 +4954,47,21,32,95051,3,1.50,1,75,0,0,0,1,0 +4955,45,19,22,94904,3,1.50,1,0,0,0,0,1,1 +4956,63,37,39,91207,2,0.70,3,0,0,0,0,1,1 +4957,39,13,59,94109,4,0.20,3,0,0,1,0,0,1 +4958,29,-1,50,95842,2,1.75,3,0,0,0,0,0,1 +4959,50,26,19,90095,1,0.90,3,0,0,0,0,0,0 +4960,51,27,55,93014,1,1.60,2,197,0,1,0,1,0 +4961,58,28,81,91604,1,3.00,3,0,0,0,0,1,0 +4962,39,14,108,91401,3,1.20,3,0,0,0,0,1,1 +4963,46,20,122,90065,3,3.00,3,0,1,0,1,1,1 +4964,32,6,98,95054,2,4.50,3,306,0,0,0,0,0 +4965,53,27,110,90245,1,4.90,1,0,0,0,0,1,0 +4966,29,5,33,94709,1,1.80,2,78,0,0,0,1,0 +4967,41,17,34,91361,1,0.70,1,143,0,0,0,0,0 +4968,41,16,69,92697,1,0.10,2,0,0,0,0,1,0 +4969,58,32,41,93022,4,2.50,1,0,0,0,0,1,1 +4970,45,19,60,94143,2,0.40,3,250,0,0,0,1,0 +4971,37,13,95,95821,2,1.70,2,0,0,0,0,0,1 +4972,58,28,73,90024,1,1.40,3,0,0,1,0,0,0 +4973,58,32,41,93401,3,2.20,3,148,0,0,0,1,1 +4974,31,1,68,95045,4,4.00,3,0,0,0,0,1,0 +4975,59,33,64,92867,4,1.70,2,0,0,0,0,0,1 +4976,38,11,29,95207,4,1.00,2,0,0,0,0,1,0 +4977,29,5,31,95039,1,1.80,2,0,0,0,0,1,1 +4978,40,15,54,90266,3,0.80,3,0,0,0,0,1,0 +4979,57,27,63,90210,4,2.00,3,0,0,0,0,1,0 +4980,50,26,92,90740,1,2.60,2,213,0,0,0,0,1 +4981,29,5,135,95762,3,5.30,1,0,1,0,1,1,1 +4982,34,9,195,90266,2,3.00,1,122,0,0,0,1,0 +4983,36,10,45,95126,4,0.20,1,0,0,0,0,0,1 +4984,51,26,72,95370,1,2.90,1,0,0,0,0,0,0 +4985,27,1,98,94043,4,2.30,3,0,0,0,0,0,1 +4986,48,23,30,94720,3,1.70,2,162,0,0,0,1,0 +4987,32,6,78,95825,1,2.90,3,0,0,0,0,0,0 +4988,48,23,43,93943,3,1.70,2,159,0,0,0,1,0 +4989,34,8,85,95134,1,2.50,1,136,0,0,0,0,1 +4990,24,0,38,93555,1,1.00,3,0,0,0,0,1,0 +4991,55,25,58,95023,4,2.00,3,219,0,0,0,0,1 +4992,51,25,92,91330,1,1.90,2,100,0,0,0,0,1 +4993,30,5,13,90037,4,0.50,3,0,0,0,0,0,0 +4994,45,21,218,91801,2,6.67,1,0,0,0,0,1,0 +4995,64,40,75,94588,3,2.00,3,0,0,0,0,1,0 +4996,29,3,40,92697,1,1.90,3,0,0,0,0,1,0 +4997,30,4,15,92037,4,0.40,1,85,0,0,0,1,0 +4998,63,39,24,93023,2,0.30,3,0,0,0,0,0,0 +4999,65,40,49,90034,3,0.50,2,0,0,0,0,1,0 +5000,28,4,83,92612,3,0.80,1,0,0,0,0,1,1 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/Age Distribution.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/Age Distribution.png new file mode 100644 index 0000000000000000000000000000000000000000..5ea87572ac8b71af5a3ab94aed4b78a70a981fcf GIT binary patch literal 19571 zcmeIaXH-<{mNr^ysh}btY!M_QAd-Xv2~vQlL;(c_$tXD^IfICzf*_JXK(a`ZoRg@4 zflu2*;EBnVDXoI;^c1X7Z> z6i}$6Rq*uy?*#ltMEo)xd^=*TAR&gzXri2kAJ7IjWN)BQS^lSYA03CE@hv4)tWhY! zN66Qak0QxNDAXN1sarShJ7~@io^%L$u#H>3t{_H2M2tt3=%pEVbmodQ36W8T9zJb$ zW%g$UQy==vQ*kdJ65TkEzIWrT#tqR=JY*~innXufI4%U8dyS7h!fmk-h~e_0J%VAh zE{~ZNY!GU8d}l!0%0T2EI+gi}EUhYPd-fX>z{DZwk z_kL{o`c%BX^w!GwyppBhlV4uD>zVGs=NP5KCX=)(-11MNT%Hk~q3w_4e-ei;Hx$Aw zPtBr|oxo!;q(0=fVl9$Ay(|Tfb&KgCBJ2* zZy|?juH=spcGevI#&@cD#=V(D0`?2+$nJYsc-r zYbIR{zE;C-JM$}b%rQOGs6rue&m&&G=h;;yZESM!zaBezHt6{2^R>!au8dh(Syl&o zxcce#EsxW3oH#EnI1}1EmnpY8`3 z#JF~?O;4r!K&(6c}J$K7Rg*9&EzbX>d8nE zcQ=v_+`^!Vv*Ofc1M&DKql(G#1vPQrDvAp+4!`hO6q9`MYquXt_))SXmwUZ@ zu{WoNI)KadCPwG`8OP0^-s4p#X?XgzT$Z2Dm%a5XR8CcD94Hq)u~+OHO+v-)zS_vw zINGkWE{vP&Rdm~1S9V5w+!ez+L9|l3o_Ly!gC~?6mZZ-B+`D&g-)jH3qUpY8OCnvd zHF2?BE6?~rj@J5AYjsDuaeL*g?N}`_hC(A*j*28HckCywba$nmX%oBJfLYlb^^YVP zg3~=Mo`zw-;Mmy-inn`)97YL>a6`^|9Ut#8p+(j^6uGr4QO+F}xwn2Ux*wF_zh@Bl zeTy+@lJq`H)iAn;-R9@{IO{sylNDdO(PyIY@h%;S=&;i)yS49-{XC~??nlR=QrzB) zi{@ANLgU8Sow%chm|aO?3owo=y8SyBUEOG$rsyyf!Y-SZM#JT0_~YC9j97xwZAwF< z=R+c{H)DqtP3rR!(4sF}BeYSqO-y&fK2(QB=b3c(Vaa69YDE{@&i1kU8`Qp~n=mPT zcPzG7*kEVkFTT}$(z&Z z?*wlMY{7*$*WoTCw57-s| zvLF@CrL#KGIN{jUJx~cgoajed z^f61%7a6%vG1$FYb&(U@MaFsO?~CYni`p_iExeziplowgJyAM%E{~Mr*A=BShhC>1 z5$V}@TjQ*?X73QD%k%Ow2Hld2#j_bDrs-*JG_Jng>efGFB4h^T^x-Bn1~GS}t0~*f z_v!Vu#!Do+?QN3<-Eyd?5Kf*>94@e)lzZjxANu&)>u?3%Tv>O!+i^OYS(@r&@hyo_96Z|dF#DV z(WMg_uI+Jj{r$Oij-8(#gi^&ey)5r-MWxyHlJiXc|twKuVwG$&QUA@RE z={~KiV=bY`t~N)W2*}mHH$^-rds1=qtd%3G+7oeFSW~ym>GX;zZP{xwjvpKfqkomrFG4* z>)i>?^xIvkKXcbi)&*K)g4foB4LVKE(mFsF_Bw-&m6<%+we>{Hb^QTmB{kkbbu?Ac zcyH*}h3zK=9Hk$uPq{Buozy4SiZV~LnQqfx&`x}MU;YEK(_Ns(a@)?_$8bC5y(VRO zTwWlToaEy?g|Duf-CE{s@9Y&uG5+i%VMI#9nw{+_&Uty~xQOC+J6*-LCK%U#>t?J$ z(s5_ppnalQe?C*%#(Y06ZqYSwZL57-E9%@lY;K-dH7&v@yM@G1&Fw*od6`y^R0}y9 zw^84z4hzAy(nr-Na?&$Lq5MAb`RlYi)RqPt_3iZ`mO7i_?3vEg$k}P5m}{Jiq((7r+bPTf zyH2nFV4bLo z<7h)LYiP1UqI7h(rgLLpP>`;_WbAOV{o;__EZ_DXcSJFJ*%)eZx-Ty^*|0Tk!m*R3 zo;%{ZY{l?+lB626-Xf7Yi~DoYKJ(B7DdYVcS+@wDGIMjc3Axw(><-+0QQIDS^JESu zHp-a&%9S6b)OB=&1H*83eK{7x!bsyIPCB@B@CA?>xnM*ZMr2CL0yS_;0F9#6oxX3Z z+8!Cg(OC)?>P%?%iIKAaMo@Gzlj>c9V^dRx)^YE;GM<@Ui z!i#rXoIInWeeI`O=rBGnaIe6x{Py~fK$oqRELtU^wlF6^Wv|}6;l066Pyc0O_XW}1O#~K; z`Gknh^<-6}M`klCh8Avr7PK0BiT@>-Rk{2l&o5(Z3g+*Cu_ql&JZ#Yys+xBM_4MYi zA>f+d=iJM=DzZ$Hzaee@u~rG1;C!?GK6ZNmbtqI@>xYjtRVMXO*9-2aJ-qkgEY+3C zrl=eVuMDK`)lkhS)*SvHx8-6PF2bn8Zef5$UTE2?bm`0Kl|GZq-XYfboO_oT8GG5$ z#||&ui7(aFjYkQ_e*^~tl9UQ$lGW`>Q%T~aqq`C9vLeOu;8W08bBxwZccz8--7+S* z_l6UBoujD_QuWJ~@7(bfnCMco;MI!XD;Rbw*76aQp52mZ}rQD769BYj1cJVJ5a;o3Zf1~BT_dw8o zfvsD^KB|b2T{ZWr1!<{`V2%W}<5wZRJ}qeYTku9^7O%zMP}Gh3i*U$`?B$ZOD0~%a z-e#(fIV3FMA7Z(=xLVZ#fBL7X=1C{XMO_(o#YOFIHM?J9s4=Skz_GG4lbRXPQmj{h zo@68UJT9YTfmwH=Ll~Xw&IWIM)3EzN*&3kAV!Qb(GNBy2dzzf(n{h&$ zBhMzBb4_~{1nuT7OZZdsx(fEG7uy(x3%eGZ4i-N+K}gL8I4R9#qZgJet6@qlfUY~6 zT{RzM^&#vz&Kx%V zW(AJL_KW5P3YWZ1S-^qh0eiC)~pPbW7~B!Q!PX zy-NZ%k&9cf-21QoK97IW18lS@CVqsRF0qQ^d%;ndR}q$)*^Sy~hb!S9Yn zUtcJ!Hcu=Z4^b0p7FzWkEN)pW(}ewa0UuarZRL9b>jcrKN8bS(Tn#w5Nr=@I&K@px z%wf6S(pjH7+#kZJ#UZl48NX-D#Yg~U9PpU9r!8ro<-jJv6nEV-T5Y3fH=|sb`nOs3wf#ctOim>jtM+iy< zc~ybZG)^Te16OS{O!iYXcJE7KcF^#1+pBzfOb@oS0&ux-ZoSvN2*ufgyV79GIoL%q z%Pr&I?XiceI2au88%oZNZ+8zGl89oGn{_B#yHz;fUywW`Uq)!wmm2^bAw{Dkf52h% zO}0+W*>OsZTk9naHg)fF<#fr;Yw!h7cA9eB^u6lM-R_kh=65VF7vL@Hf@xAT! z9A||l(Ye8rf)t6?h`_T{g6eCxObDb?mC_q{sNgsl5nYZub_6Jt%guTU9`x*;v#Nxt zIl_iL9rs3MS}9km2}Q!v;%=xK$hMq`r@J?eYvJ|`V33erpXnSg!wq2y;@e;8g}7w` zvWeW*OYiTzr%LrlIfea@V=}qy#3g@)4~c(15>WQgQ$pPkS;*bWt#umTjLUvBT>Qd;B+%YoPC!wl>;yLyq= z=h=-PwX>A`+TvF2 zC$tk8%KMVn+O8j+8z0=D4vZcO5e^?pIs&bB^Tmk~dcD-m#4T1+hRx%)cta)jnJU7T zD`RzTuAxZ=<})Su7VSIGZ#`OwJLn!V$94&9=2AbLoNP}@%_`m7=$|O|o0|Dr|K!P& z4OWGzIiexQ?KSQ_Q{tg{nZ|K4YHITr?d{h9j(GWfI9sK<80qF$9BEPB+t4^!meKx% zO|!Je?Ri*TL|%(#^4wjglwpQ>ZWlrOs1yCH;Vu;Lx>$yfH(NP)$54D*&i9UG-hDVgi&2lJZ`AVd z-Eqj&f1S&rQC#c1SY|MBqKl;C8DH-8(`^QQT@7`2A{q6jSn6F_4Er!VLk$a z7Yc`_|B#Zpw<&ntiVMx^9@^_A=1B1ST8~hReO@f0@O(1<@ESSX@!F%lfR7ofVqfKy zAK9fA_jL6S(AGUaP6P)!i+#UNFk*#QRW5-iu21ZF%!`Q9skFjDVD@5VBH&_wBHxBM zrVF)?DLmH6GAklPj`5*Tg*=DX{NG8(ZVAi=CfMAHh#_hYapdYQkq{(2U`P!kIl9-m zwvoYu=f1bzjWlgU_Vs%HysjY}V)?UIj#6=k^k43m^kTH$GmjGawUE`K{Xd;Q|ZSD6kU*8P^|KtD8zC)I7Z z63G8g?vd+fm<<2Kc`Xuq;#Y-#6RJXaoW9!4i&Cfhk01I^8bZbodN+cycoLZtr`PYQ zI)Ky-JJUeWJ+op*w3tym(<`^#v2*>-Fl+aCpYw8^T3KVz4Pqj2?f`{(aey+W1lk*h5TK~ zV<~`}88zs^ zIrzD9zFkGnuBQ5kfYdJf>(?(+PS4;IBZ%(L$2qNGCdU9vkB)zBsfM7JN~F5H#(K{A z>Dj8GNgSwkRvU9F)>KszGPG_M=&*0xuvRlXPq1k`_dWlfomGamjs8FPA^x3tF@oXZ z;?h5L$^BZHEDFT|U8|Cr$5&ijiPzd=J7?PLoYxUlC`kvM1JE^vR3&!Ia#sEef{Q;u z%recCj2C~?@Pp2%e|Ud`uRl`k;6lD}r}WBrJu^ZAlcSxaK`=CMKC=1aXSMhE+O(p= zK^C1py^A|f8GD&*nHdV@CV$s^q%BdVo;9=dv68JyfqB#bs3dJkvKJ908Y`CIj9bWd zKiKcM_V_Dae_-}e-xDKWzuroVvq`4Xt5Jm`Fl(s%a_oz$RSiour^DLE9hbU&$nI1-Vdr!X4WL9g%r3y?;fhRHGdk^s!_ z3~TMLkYRq5fQC%s0gzqim7m`=*BL;lWN7X2!LD){a$%Q3(ku5b=LNGUe&2v&(UPKF z@eu9^Tjw6IQHC<7^>F=ck+YNnM1=m^-+^{!WMmAF81$Wbnf3bR%d4TP*VD#H!JyGs15#S+rD`FC zn0N!QgdWzPE8pKX0e!(AKc~3Nw3l0P`vW7PVEZ$PTf-c8q(w)J3BOl0J(w$$andRI! z__(^CNYf zkm4opnlVaAP^TJ}@px?jgB1|a-XiN{mCFpSd*($}!GE_E|7xlK_eCDoo`Pt9s_RO|ou3%N_2Wqgvx6J_ z%6?YleoO;_QHO@8@Imwla)&8}99lM#UcP!2pp>pERqnEt02pYcLs7o2$a>P06Rx>B zX$M^)h`B4E#nl4!)I*%hW-Lw;c$6;Gh@=XrG2G4@rid`Xrd6&E1cn(X9-r$BR9Yq! zGZWK~AHl48Z3$A`Pk!AZ7jpQFJqpL=I5k5w0A1OrH#_nEr~6V@lrz{ss>mi^)+lqz z`&v^|?@i-&8OkL0PyQ=cq`_j+{*tkg3clnIs7~X7^1=avwlk7G=h=08K0o5tZ@56> zd$_($6-mXAwf-pY&nsYG1TbT=M{5j z|GHWrN{M%4#ZuDmgmeE}tq8vIKzH=}n{53?is{bOP`IMsg7`PvpiapaJujFaEb0EM zG+v6qK4hHvSo;0~3qHj-qsGr|GVIAOK~(HFZjHOm)M5O)!oVH= zj}-=S4^uklyV4`iT(~M4!l7X-7c>i!GJZJ$1)?LPX3Z>)T00pp{KSinhN5sJ^}dIbOgw?Pvn z7}5NKf_*L(u{XW@7~oJNaY(@;{OotsWb4_9Uzz3GS9npWLXIn80`C6QSmPwQcGUaw zt^%-Rxa}9z1#D-6Cj;Dp&`jYkDD86A$>W?f44ak zm(}HN`jXW5vITCtYripdY)56Wo@(#AWXdO7;J|-Etop>s?mvEOW*%&DM;;!$-H9LP zq?Y^`Q3 zsN{%t`ML+Nw7FcqTfywsTdJT`x_WpX!sU~8kaNiQpP zq21hh&%55BJ*0F0D!L+CyNshh=H!g>n0pRc6W#ZIBJXxB!opp&lJi%T+xry_NX|7f zqG&haC|#=HxQkIWAs`Y~}1MYM}o<#Fusc>De2LC@6;^u_B2kWneVv=!yO)QR-<&&w61@uY zq2J{T_k^qcS6n+U1NTN_{#y4(D`QrBxV_m?C^GmrH`14mrUEwzVk`5=Y{-3L)q9 z8AecLg27jp1i!uk*90Cq_7@I-)SXj*T)713N#W3K=?&k1+V1g@+0tn5Q^nlx1<=}{ z<9zeEWJ!0yhJ_~MaI=%v!W5sl^n-L0+;%iBYkSr1*ptW~i8W5YwSv?%tqM&LISp{z zA@(mwuvHi$3hY)iY3BWQ^DXKFdlyzBk?N)N)JCHl*mG$=^T8TJpsPx*VZeK=vl1Xp zCT98QT#1CKp|X;>;R=zwHz0&>ynHX>t_e9E##gUiWrK$s&SUiM&U^lQAhnzNqjsC& z%2|0*WM9|kKQeL}pwDD;3@2d3kM}b*H9&kY`;zL1H&s%Qi@Vm(hnt2m>SX%W0a$eNj{qGw$J%s zxX!iE9>zOThK0G+Kvn2SQ&D_P#%Ydw3F)PQGf@`3+20n5?uvwZR(M@oo#M`PL1CRm_>EI0Mtj8J~QX%RnF zewG`*H#>{+=yy5i36U)Z*s2AP-jI}hi#S#0M_A6%2(u;2$GijKw{EGyQj6#JF;yr$ z4H_f#B2=MN&E)3;$*leSs5${$*(4gtOzm4+XPVF8ZjYKmta2bEk**MgpQPu{pG!f- zQz*#8LdDEBY^8Su#c943F0-h%t`V{$xzkO1vq9#FEKZk|p##;31Ck6eSVW4&I}_7^ z23DztDC-6A3y+asfkbKNIW-UMy~8wP4Yl)}Cjwy5@8rdnd^pQ5BP8#}!{*%sFwi*- zk$0lqx`g%zK@;KiCS7R(;TVI6aJn``C8m7~SAm3tWIVs$JO?N~O4M>$3a?9W1k!Xp z&$xHBpI6VU~@9kA)kbk(wTUty8ZDtxj-){`4t6)#2r(@RAQInJGjUmTtdkdTTG$XihG7}9E#*abs1=!=KH zdQ>h+;c?vm*m68wGJwAA<2{D(>-HIE$hp7%d3dNp_uwn#tIRvO~?_ck@Un83r0(ua9j zViFRDbk)3fu$;peSN|Q$8$G-s;7A9nVt2)7ZE<+GqX{Ou+AXVTml3uKJ}Muxpi<4%oEI zCO!Cgw`%Sp)+rY|vyz+k3yC8@UzeHh%ae8Jyr&UmEB39XCUUwP7N(wOL9|PtC<23?3trq0Av3kymAm~EjNvHLu%0VydkI#7j zLNn3F;xa+CpdcdL=cLm!FeJhT)qka*7|LtX6$HwAq*-UFqcutG`d6g66*9{lnoJG& zmK0a3LA3o|qb`UR7~?km zqThzv^%_w1LKzU9s%;~JfDIE83Z3uzww7?s0=pPI1z7~R^%B6EA$dw(#kQPG$3;O$r+fjd?P`7}sol{e;@T z20a4RFHGSywuplrODtz$0pc92NtTYau_Cyz5oTor(3VxcHOUx6w6q$t57tULI28Vc zM0n7lS04NbVpIPCnOJ6GVq&}5m0Yx#fo&Kx>u}bGCJuQ>z+lZJMXbPlP`A?Kh+d>4ie{-rrUT9N2!aA*eyq}@2BJO*E4haSu0r&g_fyi%bSlod1##DW~)l1)q zCaSq$ND*KrGutP)CV->@u z>-1oaW9EAeVt99y(jGo(wb4Vic!i!3p3>00ZUoo^Ol|mK=A?m36v;wFLp(1w!YWN9 zwxU8iio{~Np_F=P|I9%&e-xVaFN_br{jXy6Bg_z92m~j2GyU7wuRUtwPKTwM=ARmQ zUTy6s^iLV2iK8}qeuEFms0twl*_g=oY!I8|9{N6zaIwifKAcGa7YgL=9SJEiGBHKzz-(WTAN0)V~%%gZsN%E0CX;gqXy*-}QyJa3=Lo zm-U9rT{kYn^)0+~$=DOx9us120Ev{$)GPy_%aAXj3*A2n{R^Ta`Odc@c#P;FnD7R4 zx$g_e+Lp<7#p_ad2_I7u!9&RY1BG$GmpTUe%o+{MSfIypLDpos{hE}^l^lV0Z~-(B z&_W~#uXRI${m^7X5pMxjf^6d=T!6-@rB2AU|Fb9HbxYuuDgr1;*;Vf&apn9xael~v ztK%Ro_CB0TY=@g0vQ3aymj4^+p(FEj-`_G&B%vfGew2Uln(1XQ?X%tXoO04b*i`7H zq@*Tp75PrRvJ;F_?Slmaj{h3n!^zdb!YA=Y#*jgoaDtfIwDU|#vMxkHvJIN470Cv` z#7TLW6^GC~N+esO$Tt8P*)8yB$HC_h5O&=T<31JTjLgg|;BOO^nhy%5s1;-w8ABPJ z*dD2R#t3rS%Aoylc*F>ZuaUQ}!lECmIM~Z1Z(NTMa?HLZE-nqsJrTrE{fJz^bHf`* zVdcF+<9QM2J%p>`u7O&MBvT=UUfHqB1OqCq+5`pPe8>v4qQne5kupvx;x^E+=|>}? z2_qlczZcru-%=amhr!t)(>wp;?TlQu|Ei$Qr%N$GV^`mX||t8t}e<0JpkUHu>MHyE#in_K~QlF?vsUJ#p#0=TfcK-wWhSu+{{ z$tRgxx4a-Rsf=vL>-Gz|Wh{Qw*ei%3201n9pI@FQ0`jtgELuN;y}O}02?HAJ$k0$j zd_SDJ;n$bMNSvU)@X4qy5S4c@)MGSMS_GBlJ2f2>3S^7hFr0MBdZK}=su-e;hb~YC ztmA>W+ov62sv`l=x?Qt{4e4eh-*6BNJV}AboB-tgP=bKekb;D7fmuHjglh%TUexVLF=_B02yDzP{S@ zGE#5I1&|d6|Bu&&N<#z|jxwA6{^U?3)zw}0XMK^vGL?CGp#>l)eEheCr{=A#g?NkP z_cs2npip_r1YLf_fv6pS9tS+ViQ;agk@yl1>9k$sxBLM9Msj|cGp_GX*@eoJ_5Md~ z&$+|Q2Up^0)!BZ~J#x}R|GAnZ+3_RliN0W7?(eghy7{?jvIJ;Ydr zpb%qnBpM=kWv*Eau|-|Czh-?3E?C!LF+oscBFHu?AQAll?8)G|y%qpwOAqBqxSu$< zpPFDM!_Y=I53hD5%36c0_AU~EMM&Y*)%_tLIZQmWL57YiV_bX25NbkP6@=}Cu&YHF zwGFu+xc;>=%sV~?gcI_+BGY%%-K`@aaYTeu+dTD!S}qNikLh-)4bw~Dp|udIk$tnc zxjc$cmftI)uIsli*hz~%$&&6k^!d>GoVjq{fAzTXLg8z{x)~`e`e+S|3el+n(NQ!WS7|3<~+}nlN&kT27{OZ z7IX;YbdhdAOC@OY7V-ssny{t{FJBV(gn<=~9o(Y48LLv-XDt2R4lWc7?fSLpc0Cy0 z%!bhdWY+8ub@+(Uqaj14C>?Y;pbybSHfsLO4}6DA9zr|Qg^V$x(y9P4MK&;W!dFD4 zFi(W!e2_qCTb7OlD7joa-I-dP2F=mIOtKMSW{HXC{&WC)5oQOeG{P$IM?znbF#iC< zQV-G^+0Hogt@fDxO9)wq=}Ae%=ZBoi#uO>EKR(w`@Ca#PRITI#^fp=>-JQe2wY3^^ zzy^tgcZit?dOjluha3{aa{d~8@n4_~!5KA3SM=tYgr*S6-MPaP%g-J~CAPz%hY+;r zp1%<^F%EPL{}VB{-DQbakQHG50_j^Bz(l6bw?R!ZH+})g!w{#=CM2YO>O7mn4Jd%X z5;y2Jk--?n7-Z6;VY>y=@pSjncJ%-CFzNi`7J{yI#NhP|zP18yjl^;*RFJ&#j7z)>qxZkQ=L6#2-G@p@XH!(Kuf=@SqD8F#yCIXV*!X@?fa4JjeXU zkwQv0c~tD1gGZJWfBp1|=nUFJ#NK*h{<8|6FsF{C;=EX-Wq&K7Ps^hU&L- zsp6X_4sD?k32>ey_q!RMsfN^lKHox?zN4Y{&H{7CZF4vM%+2gf3Ra&ZC{J>_3wR#- zoqNhU4$8r^fflV5RcaTRaVYqUdlX7y6XRfFy*x(k-sLoFb|ltw^%4u@js5@yK z+jI6jxL!Wq>=^cdHhNUFETe(s49XAht4lV^I1@EXgw|}s(>WH)1N+OJM*%Zs`-)5k z>T#%eo!eieB?21i@>*4dc4ukwK-sJ#pW*FC{3dj_v1h8?6mxfIiY{(jbB=I0VmfzM zB`2Z61uXM){DU_EHQ(K1T-eu4_Kq&El78$Cj?f-H{neVXwol!?JOAXbtp^?Gou=RJ zW8pc^V>>c;FJ-%Gv8d)}53aCNxwaf<1vhfEOd~3SJ$ud8F4Mv_XZ5462F2*Dho{zN zXTH#^hQ!;M;ll0I#I*Z0SNyBI5F+t@ zw3*MU&jCZ`awszV&3DEVa5|qKoi>q~RB#eis|kM=6aQ7TT6gdw+~}oE{t0*9GHltP zi$Gw*9*86m+Vyx_r8122fHAORcmfbYMO7@@zv_t{6zNerYmOiQ4iA?J0d&w_@HL}C`C+(x?9b@G+dRrO#u!{3o& z=TzGV&qD~h@<3WCL!AXwqFm?O(QeyDD&;OkhvZx;08%m$$}k=f#IB|UIwI?#cIj#W zoYD#uDyc>hT;T3)nf|hJ`?XLSy_&SF74_N31eNuRbDG0yh2w8ag?1zycVb^Fl!)B} z+xO^`$k#P9YC=lGqgmV3%~=-94_z&Go(8t*{L&B1g7}~gZo3JTy#&bAoFgM+2A43~ znbV)>{f$E$GWLy3D;IG#@azO1LPMK4Nf?D!rFu4Yz2aaWSAooo+GQTv(j_lox(cSG z1Kck0v#>}Z%myZl%ODrrTUNVJx=6Xl`^A5x%4G4HrhCEiwm0>gYy<_sfI);+cY_r@ zniZx^L3|4ajU&>GAYb)Y3p{~fYf|LEXrqdK+vl#xwN@)KH{#;w-9u)j`{twT-l3SB zn^S9s2RQcwW|)6_2PY$i2q18e_4D!Iqzk`=6YaL#Bt%kidP^f!Fr_Ik439!6N5ViA;QQ2T+)!T{EPN;_=T)OLIZ5kaiNx{Gt2rN_6EPt5^@?CBXk?ZnT!lw zqEP>wr=v6bM;4VV;hF}QB}`%DE06tY7vvC0KRtRp0W1qE$Sn5z+(i;!Vc*Ol^JRcr z+Vl`(T$b9l95m?H)MQgm0}XOB3L&pFhHGC#&Vi%%J&|~y-5`??3WF2 ztp79_ktcDR&DJdfk=gD{zKY$2qDg9GoD3xQZ)>>4VJ-dUXm$wy^2r#^p6fr%j^R-O z9tj4b(p*X>?b9ui`v5%ljm6=ZJ`hVEIXleX9L%iPzk*B!BDT;O7i1(3dFDb9s8Vyp z^vDAd;E!sMJu=Yu{ShNlfoLhEH#`|^?C>fX>nhM#8keP~%-|XZ?w)Q7+?8nAa1a8C zsJ&M~2-2w8&Tj{)K;2MGQDAJ2yX_-{xMIl`!{z!SneK)cVR$$hBqF<6vC@s$MVO&l z9(Yni1rwj3_e4Vm*+J8Jp0|W~e3Bk+(keV5qYsN`>x-@?2Okn~)+2(C=CO%McsGNY zB7AhU&0oe=V17)*%Z@Pn`d)1bSXpGHO|QE})}|%;!4wa=Xi<6(nFB-;$0C`oQ<1zT zAqazAfpw<>SurM%26n~Z7gX%Y zB7t?pbgMuizBclp4~e9f2k1P)-k9>~ULaX#XoLqAwg}*ZwqM173Y5eBG5X?%*hzW! z?Ld%x-ggfjIoKIKXqeT6tAiv=Vc<-L+I{y45}26Al{ZZ*zZo~EWcSkcDh2cyrk9;J zA>&SL2a&f9Z@OH_x+!mO%(Fr~F9dR2J!O`lJF+)i{?PT*Bx>^S$QdoB0?$3^NL7~K zhljd^-y5OEI!S_NCcDQuavM*)ww*WzKD;#OEab##f97wIq?{CBY4;25ZJ4j{p(5SJ zs4iYK*(U;xqn!tPL|Wdfbyo0K_3YwVs&$y;&z|ec^Euc#+d@vWMpBXc396>*xlz}s z_GY{<%^qraRhE8!M3*jI3cH(TaF!EBYc^h*4wnz^zUzp1q-z1Z_gdoBZ5EFLqcdOt|5-`xjGUG^0^(|yVb49do4kG2(NERCoLd5eFw4=KwR6PjOZmukqg zTv}ab;w@Zquc?nVfxms{m2cCZoBCmb+7Woso`kU}>+)itTtG1S+KQ0lA8amBo z)dz%b}9e)s&Z@~1u*UNs33Jq$Pr5n@z1)1-!+so0@)9Y@pO(PCB(xF%&`;ce~8G34V z#7#p|{o~O5f+58ksc&>&3Xi-ukWJnPsw@fM0Xu^;lFbT{f*d|qp3&7I2#X`GFn9)d1PHsE;MsM9Cts|9 z`JqLs%}eUOJ)N8+=Ku+07>k1q-=!&Y4~8F+5d;`lUycg_!xhp9UMFCQ&_+hWBa2vE zA?_M1_WV?D8B4U|1i1=?69kOpo>{_!6c8Dc>5|CuSCSQophou6tuWsMYbu z>d!m_b8H)cHBB>+LTzQ`^ZzJkb!QbWQ1P= p;U2-E06VP^Jn>&ESiZFfC)@lLKM3UMD#Hs#^1}OTsA#IF@BG}8KnMuJs;c_^e1Z!8q=%}~=^;C~$tMA($AU1J)$7n} z1t#t4Mhr&Vf4|Y5BVkt={gGE`ZdY)8pA&cP7`5+?+4Je1U8hfZ*7)a7T|58nD$SO^ zY)HLhb+>D_D&(15@%EaOl#%IMo+nh?J-;sO+3Hntme84a%S>hcHnC6jl?phVvp9F^ zh{lVS7eSw9wULK4G-#8=m9}-!OZ=xt@{(ba7|er^sm_5_=+n#MJ?H-l@4Ll~KSO^X zTfZN@ojAOC1-$)W{PtkV#Ju5d^I8FqnPeEfT)v=&&I#FQp0e|tmQT0la#cPDGb)uM=kQs)wh$@!(^y2hRtSAQa z`Ppq?78uOKY}3EM+vjl#pTOIxow1wIw|BPx>Y#aWq&x-_##tUy9#qCMD_sp82yz$< ze)!yn&i>t7{h5PDsup0wPE`hTTP)XSgm#p1He{^YO?mw%e$}d9XcCJ)EsLzj+3b1( zAt{?Z;6KgbPh_+CAt!0s>{BQ8|A@65Rk~ndFxNTOUF@(%Qhiv}Fyy&gseZ2N9336qNu!z2N*wzp7SVFxBmItUUMq{$%nTp7Vt41n{+-9}Z1(o{9-^AaCrtO( zQ2z1Bx*^V>fS8*+^y4b|`2LVS<%roa>QR%GaP{YVi#F`vmKo*}HFH`%9zH0*r7j~+ zuWZ1Dau-?DD*WIWt<;&@faC6sTBsTHD|Qtw$bsT{gA49$nf=3*)SbuLXWC%j0=sN% zE4mM(L2bWwkmN0mKH(kTIY4=@Lmvk7wMo!yi@=dEkd$OlJ*JQG^vnDM?(*KoyBN`! zup0Y-7L&MEy{YoP*w&TUN*0d4j~ZSj&wHKC#$bBX!hh{}VLmX9-Fo-jTGO)GiC1R% zaMr-nb-x0zCWpRLRds?z{ww2AUc<0nTq~^2*!B;bG0WfrCd^^!VXftcj8IDBBs%$2 z;=kSzCLi)OF1;>)tTu34J$bBFCdrX~fEv!p>MkDB57T2A{SKD?89*!aXQHhXc(k`9 ztPu zd8MSC*iz0eUTiD9xb4^5{VraK4{kyb-TNSxbPQeG$~a7r8-71e`(jhuc-Y;?$6mQx)(mxls#6U=@~lM5V&|iJQRI0+zuNMIgYY*GlY!DMeNSbG!svXsO$L&eBM_XnBkyq~3kzHSJI59by<3lU)JL!&= zvbWka4M!qAy{xv$zizI($1T-S$|>v1Z@zjFMo(b%`jj>eHO0A7vyIil1-}7{RQL6R5^&(aW=8j0#$IWu>-)li*CBU>+|JKfOvck)DJz{CKU@ z`mU}n1Y}F+z%eiw*#m%&0LA<`TE0bwJ&Ubc{qj5bf3^LjE;?R*sD{_6jXn+7zavFn z6;+ihFb^uXK3(zxT(ZF40h9ci^Iyn`DlxnSRh3Wu&u2`K^8H>M|L#~@|3%G zg~Iq=`Q<}X^_*$^TOQ>0I5{Tfvbvku(+s_;S96apZZm=KE<<>>rwmZU?%qi^AKA6S zi#LRqFoZg{{auQ-a4?>Pq*#^M9j@a1n zx}0rcD8SLg#L6P(CfX^8HedTrJ6gf3&0xVd>`CwAOG*fS#l-$ehLqovq4-~uAqT-T zxEf<*BrUOj-PQv!$L_iVJOPt*8EQPYwv;5`3??O8=`X%KUDoGcqgDHn2%LQ?@p{)l zZ^+QOZO#3mgR(x|x6Y-drB#n*#|?4WZAl0b+*_|o)XdqY-=AU{+`gyFfH^C!^M9W82*S${t0I`KYCs>WUA*D4eeu3ppDMl zkG9UyT292J*LHW^4N>PJc>2XIL%~v8)uR=NDUWST+j*fCJ9$fY^48rUy}>1mtAWjue!*MOJ+Rld#^n~b z>eAz@1$>U{qYGQgz^u>EwpnJr@Lq*T-8I)oJ1!W`6e!ZTp7DnPvVjAH(rN4UdsJq@0rF9OPu58fTcIDSqwZ$55h2gfh>sj9jM*qU(0IN zW!AEXrtY>S;`pp2R{cVqDtO1S&5-+IPO0C?G_{AtS|g>oy*XZT9iko5PUN|6hx85i zVNPMMFWC;sGQ&)2xo@5TSR~oq{(290l*IQiGCFWYeTz!%%ul+I_M~e;UW_^Q=1y$x zYSr4?c3-z;8qlu>wVtb+?^PP$O@~sd1L-cEHx5&QJKQKC@^rPdw92BE-nd+W>oDcV zkDezy{Nn8T)yJ#+9iOJ_sEVsP$vEC8oTDe|sf@H`W%1?!aS#TIi51zFs)VS(RWBLe zbX74`u=q9&+;M`FNy?nTg^>PW+SrSGK?K;&fw_`U;{uC}?4Z%smcMhC+DLMd%(_ql zqgQKyl^EKnMv+;!&>!l2%b9Gb?bo{=@DDgxra`3k@?1y$!MNq+Wzam5N*rsnC)c21 za_3-v5>8=XWRmzxVf>|0`XyVZbLsf{U51b_YAXel*3HMRl8^cl*`TRnlVfQAhSMLf zjRpRu3Ax!iF|oVuEwSg;ZPWHKME5J+RAkzF6k&95=i$K7j8JW*nFlLHt)WX?l$f0$U zjx8c}2oba6R3aLDqB-*kXXPSpJl8TxZRTY=AwY}-NeKgFj`ph(k_vY;Mi`; zMVrkq@ZjQTk=}=~MfG+-u?-hm5P`*nMLGmGl>(BmZ>@}LjjVaHEVm!6Sx%B6_I~iB zc>n$2IM*Zt?G$B)?p_a}k*)+su-NrF`7$s+dMHE5))rojyTYvW+Y=l1 z!>%S;TkP6$v#2QN{(USG3he44f_<`t5laNzr5Elzvs(Yw!!t@pgt@gOwk3VyOvCx zf9~N5=29H89Ua7G-m0qP(Q$lNVQP--S3!X|nv5+{hY8N<7M@nv`|^fpal2iq`p!fLDFX!r#%n-V&D!(h?Gi=-?secngC#3q3}8 z*mz#5OV>>sguyW}V*_=Ox9lr!77OXw?sdJjroH7}*80n1IY>F9fTxHv!`mYHLw>#h zFOa!)jnQabT}|K;t{@^I;#R4vj%G#`F}4D-*V)t>gF9VJW)DXqM^P$|%c&WbZ!2B==Fo4#R4E*b0S_3)58a;V@uj3JOCIy<+#A z{Vff(}#Wt~64e*R3J^Z&_h8AmsRp1W&)kR;H3^KjE91sB#( zQy};yQj>@1@`5nmp4-=d7C4Gc?+?W)xx9Sv?OL+ohd9o2r?;Ak7{h8aN*tf%3gbv0Axw5FBOZCHw6v%w4xE&NJPl;y?=4X!X7`pZKiM#dB2C3r z15zjzsa>8Z5;9W+DwDL*q=V_&#z1j)zE6~dzLtM5U0h5IT;Bgl4l?lC;tEh@kOBpP zzUjgi^Py&Ge0+n5-cJAOS7&r*pY3&Ry}IjPy{){@(l7EZQmyKjTJS<~p3z&O7Cg~8 zZzxnV`#jlIm41^A^8A3P#RmDrn3(!#PBYS-GASqkUHe4#oi2&h{=Hh#f7!SGQ~3Xz zT>eko78Q|Zj+QMC^6SQGOR|;-Ld^hE-11?m@;|j!@3dmflxOC>lSFEGzaa@Ek(S?R zDt|`8f!L(%cwbY*VD{NYP0vGXQqech~QY%-9#6uy5QX9^8d7P{W1`FE7WxY`U_u-*@a>3LdiX!^+J+24= zns3?^Wt$|)fu;b&&aT4SCQ?oqNOTJQOJ7PjN2w(m%=c77l9B^tAHQe^Q4holtz~ej zf2Ixob3rJnpSd3ruHZ#)P6z}}*9_X|dWuZY0VAWSd!w0UCtp8~i9vA>T)LQAngQG! z6>gw@19?M5ODjqQW1?^u52&+{i&FhHh> zn=B<8o)M9iLiu1!Oq^=HZYxf})df1?3h4p0CX`t{o}b?P3o3A0)KJ&TEP*%$tL9Db zfZxXaP~`Z&MkD(l&Zz&>F$EPJx4X@C;kIK-C&#md^;XQaT#u6FKxD$9vmrRjf7fsR zA9Bn;gE83S=QT-uZV#T!%XTIch0e1Oh<1BX5PU`+4#YFBoRpUU1cwXcr~p9SUr742Q_9ilIW ze!{^98V4ffU5a)EjWlwX*z`1?5+J6?Sc!8*&P|ZxKA+k3vmYhl_+e`{e)+QWG0M-7 zQ@ps|7gisic&TjD@ze2%8qWJDk9)*Q_UxlvQO$96oBA8=^BnrqRBD-e$Ul63pazbR zGc;0m9{UU!p%?db;mUiUp>%*eAVrL3HAxhJTU2{C-#83{mCxjoI`(LDV!&E;Y-^OH ztdgrq^~aL39{=vg0%a$P{Z`2Y>=ss%K|zq#_KlIo*Q#wjaQWH0wNgO*tnX$?Nup9| zt-1(~JJVAe9&|NgqEIbt=HM|SlG_KWB5v9zZLa7YD zMn?C`dL9EWK|Vv~)R2921*;5azSW($krV6jBADi=c5?XPMl}~BnW&i`Sri-}e(}4H zR=W&8JdbLCND}w$EiZg7DJGV#gHJ>`RigfzhcVl$`VP7!zhIh4Zds_Y+V_Z8l3ZqU zj_2=7EbRB+kuyxReZ2kN;3ajl>Cn9Rc1}Mu!ED45JR1y5j2iE@8A?NVq>@Pjr20d8 zv>`)~BhTCZv8bF3By83YHLAwAm()L0e`Lj9SQx#eUb!QX$qTop9h%_R!VoxY z7!0#b$t}4SmlT6)l?T!^6+d3H@lzCNR>_538zbsylV^!KDTgD-(oeS64JNqx+IXXn zFw~Ok!{`Ws9LM8UiMWFejh{D>+pm~63o2*m zm;0bI#d<)(oZp8h8^AHYs{Ry_UBf>NNdk4X2px(ha}+!GYz5zNZ}ecV1`>F^Fj;*R2be3OYMiAe5jFFYV;LdV|Fo&YC&@}~xkvoT z(&^6LRq1bSsql+CRE`m}jh<->2ZPh7? z+>#G@@w;rDWk<6}#9BZq;6A`9H?;Na$Xl<|Pq4lUnn9BWTqwm~-5AtnAR)i_U{$P# zK2+gZ*F~eZL(=8rLmx@U`-dQ@yn*!5V0EA?;EEbt& z%M*(ewqz+i#_Y1-qw*8vs?fD4-yW7`{Eq5M4dzj!xnCMgt83-Tk0TbVp{hCt; zjX>3m%D$oU4vV-LnjkZ!mtiI;2JQ&{{0o=?fbmLr`;Eh;p11H*77ux*ct6wZXK6@X zkMEA09?-OO?5Pgy`0*pQWIj7w1Uq(39QF%#R3{I>BT_M(RBy0lx=l$D&;b76gLKn` zeC;xHA^@+2{syGGyKo%AF5X(*y8(&4p06p4|7=H#>b=3fnlqnq>KerN_x+N2!)78B zh8}}hY5(dk>H(T1+Aizhoo1(=Yn&04cRCT`Dk)Y~ZM&gU7>lOxjV4rhH0)CT*3Yq&x7eulg+ft`MP+=Qkp3WpwTNRexsTKl9^Fj0^V)}S-BM7q&`1C-`H&^eH72}IBaGu2@4gE z$V;N`P|VRsy04S1vq79(gQ9<3Cxq)d+0aUK6GdI~D4UMh}?}#iz9H zD1ncvHV7$^SSIYW0C}%-2klcawb1DoP@tWX_E#`-J08@crAFi~-Y6_Qhkg;U`D{t( zO*;qKyq3O&p-1agamIo~{ml2sx*EtYOC4(}$NY6tr~p~pE8d0{SA-PpTFJ;(zyk|$ zOe^Gq<2+(eGc$!mf%if2_6*swza})vrs(K~4Cmf?^%AJH zEIu?bY~O(*2*iVElG8ZWtUn9I3kWf!fxPLrUk})!K=bcp##lyZ-qM!WC&~$Az^ZqH zw5A<)Au9>Zgu_<3GuT2*8CM?qUc$+AlS$$Moxv!!bJWyOoT`O0Z^Aaty>_BtPnu8SG!+zBCOF3y3H3{F$>}kZCq)@Sz^HtqZ~rB$)Y#A)#bT zxz$uL52A9OC~2`_9C*b+&eUDYhDl+Zd->z(xE4V_lSrGfe^ga}Q!-uK z&kPmX??W{p&K*3-U>pzKCem^%R9M}qIv(8VP_ntw(OaetmA?A{D7@43!%xP^E0NgT zh1yYrwR)lK7M%h}+^U<{gICMC#7tzUw@>G3px&d|m#0PZldaOg7}CHsS@9eu87B** zW&G4i5mSld0ehqjqr&dG^M|+L_M<_-Je|2i65|lKJneyQQ~UjQx;ku`kBpRj_Yc4{ zWYQ9SOf%Y{lT|{uX7G+Bze5$PeTBRM@8@^i6!U0r*0#4Q9@V>-x4m+Q}6IoNr;bn9Tf{G}P z8!!RXu0gOh1G*T;LFYbM#w*bz6#P|34`&dqjcFNkxieGc72 z4g}eR7GUrV9l-Xai2a};&py>?Ti*g(pCGN14`C(`^(sX|G|m8Z!R`UbfVoiIst9YY z%!IH*c(7ts`F2+a2}iB*lL{!sjq8K_5`kCiN{Wr>I;QxEct2B_CDpqL_)@ z4|^suBd5J)IpO7-=|8PjJrFs4&!d58YhzP){cqdPvqmO8r<@1uu_Q8Y-dw;T3(~D3 zqE)e>)5lNnD}kMqgZy3&ytcsBDLk)-TPz8o(iBQ`eqjtWe<|I7uc`4mf@3eB-wd%L zpYB?A8xA)Ih&wmkug3uTHV(!cy4<+U@GzlD`Uz6er3{^1-a2ewP2$^C2jI->A&ws3 zYaS}3xBe4YGX}(YIweW<{@^Z>obq#KvoFs{3UO@vG8bdB@i_&=bCj{9A}eF7ym$!m zDzeZ(0-@c>yCS~W>_rxN7k$!M5W(WGbv$a9u=Ww80U!y;P;!sV|7WAlr#`M|JXl(>^Ovmv~9ZR-4OCB5~;()lZmGmrP`XkH9_1 zF)=jxoc`P2>_si_s%emUL9d@aqS%lZx1@pLiblO$83=x2)HsRD$lH>{w0Rr`P0i2< z3;+dw6154TlBOOKc-P{TU!f|nV7XKf`|ZkA&DYP$Nd=8Og$x>+S(+Npt&3~HKN8_; zNz#r79Yi~-7CAp9PG;nn2_yTff@SFN?RLQXQ7g1k)Vw=ygaJxQ&qt;@hImmeKf5^_ zS%LTp3Ow#iK<2*b1z;;3GX`Ioxf|8;kDlL@q_2)j-CB{vym&MM#Gxz=mrfWNHTdL} zx=s?w0A+!&h1!v1NMYn)5^-D1QyLR=1~#6R4Y5PbeN7=XR?VWsnbYoV93PbMxJuHT zNzqgu;0=^Ho91iUnbz;JBAvO=o1KtmsNn}{vw4KqSFUCg8yeW5{_NO$s6XVVeW3LBH@z z<_eV{18|xRmijCsn6&klRcob=_@aPR_%?475^2MBBbQyEut3|3KsUWrek;_J6#h}bWOt8Gfl{}&r})cL;I>Q9-x4g z2HA2$C|gxa5UW&T3eA_`4#8%irg~Bx{l=_NdD`cR(0kYdN2v!Z2>y)%eu)SW;Gw${9hcCvjofa_@ zX5YdINtEkNSLX;P^hCJ|wVLFj3GEfxwHclOux`>oRdda+ADk*@)^qYv2a9rjO7g(s zX0u=B&k#Wdn9b?~w>lkct1|wX0a@*+dY@Zg;P5)FE%VUL(F-bvdH5*0v|?T|q+=IF z^rmiig1~^feafNin9auDd!5n=sbV=OT?K&h6=Q|XW|C;VZWb1L^)OSojd}0#Xdw_m z3J;l4n)4feZQ)>n70SJVJVUA!PRg`0gBAiiDQK^eg4{k0YLpSc1LK4w=)Ec+%;0>B z8rSu}WZp(FPy~`6GeT|56f17UB31b%gw0FQ9#-?8KuBNL)l+Ml5JUfv$w+1ZjG_Mr#aG1_5S-g3j@PA3tJ5L90lgt?-$W z9x3Nk`s(ZdV~6vf1l_j36QxdJEEqy@6FotZ0x1D%@4jw0=fCe`N zTmfIuu@W;}1Y~XA@UNH$i4*V)N&Et|od_GZG~5rofCLd0E|9#q`|hF~>}m1X!%a!? zs0jfyzab^(rP$9t!GxK!-}RnGy>0jS&GSbeup}sdzY$=%^1gJNllsdDvcCPs7Dgps Ief{140KZy2+yDRo literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/Approved_Not_Approved.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/Approved_Not_Approved.png new file mode 100644 index 0000000000000000000000000000000000000000..b29f5dbc4943fd52a1a264e1545683629eebac1d GIT binary patch literal 36878 zcmeFZbySt>yEZx%5s((?6cmu|4w04;Q9>pH($d`_NVkAANC+z3-7#sTyK~arah|Db z@BRDE-e-?}zA?VP&S4D3TF&vl^Qk+o`?{}(z*maWm=8!EKp+rISs97f5C~E*1afB{ z^*;Cnqv31_{Db5|W4@kZ@O739&a$Nn10{PSGPx zH~YK#w3qdC`j62*LGEDS@E}h}K$rZyHGi6xz0=Hlds$xgZmwcwZ1N+%spL;}!dFG! zr1aD~X1e}`_heAfCQjYskBc`-sX}4v6kZcri`#OjA;>3hg^CH#b;#n-zCUAf~Om6I-8LQNm*MHOOcbutg zjS{ffUu=_4;)`qxCOllv2v6BRbg;A2DLSg#$c+5ErPidFn3!(oE3r(_%7~|OUm;<* zwYL4jvB9kMaiyhPJC#dVW;~>jJ9q9(yYALyW@mG{U)XhZci)NQFnG{#*2W5UZh6=9 zRxn4cz;L-E5`$7CDbcb%esok-H6PkJqNY7_K0QbN>LrPmIB0VyzonF6o*w+ACq zMyV^chkbh27sp&YJa_jlHVZh7`p6g<7|!NyueC*P&h&UJXXOnIX+1Be=8R2D7RskA zmS!C148X|I(a}d&l)s<-o6S`eIqiQ~?TJTfOyajyuXSRF=)uCCK7EQ@GSO2u_P#q- z+XKzZ-yfyKsQ>=FAF0K9E%|z_`|fPr6FNFh>y94!W08O8PZ37EZZ-d0o)(XH+Dbh9x+*EG zo_AmMkM&Q#e)|?b)$IUH&|#}lpF_9o9ecby)NQ{_OBG3YcH`Sz-OSwFElR3wUlM;$ zs%UCqAsYuLCos`giwaJ?_K?2xi@ZF|ij<3BjtHs09@Wasq*WbFYFQg8?vE9jn%ck6 z;xDVHxC(4Tr^OF*d1XbnWWwqCcr2dJni|5B82Vi<_U_)KX@ULhjh2at32?X)&sz`3 zdyjJiTBQ_>#^uhaiCSmQe$iXEwSd*L{iSnY3IgGlW@h?x_3juHLUC7DZs2GkzrV{@ zllW!qCb!>33c5r z3n60nM#G~mH0q~tb8}NK)VV{b?Zyu5m70N}tJ9O(s9nEeYFo;m?IkdhiHQj*7!D$^ zSfkfC?izMPJeGp3FAgb*uI$4o*XmAZH*K_^KYzaV^83z?x~C}Jh6KsK2dvV@(7$o5 z?3qdyn?YB!-t3r~6uy%GKl?6`i5|)nbo6wBHRYV2!&2bT_Rr(pLmlaV{wKgLt(gA* z7O1A!;^nUnVjH%uE)Wxll&0Wc(EG})DW#~`hZf%1(V+v*eFk>`o+TeY$gFv9BjF$a z58F{^U8qs~uzk<9xVkU)4}n7Bf*|6qS(BRcXD{(ch2q z4aC2nD%lTla2kQd&p5ley9*N&6DL!GZM<3}Y=G#1qmYo2a+p1BMrY+a{2uscx#-2} zOw%5h+d})Tcv?H%{ryIhr6!2ef)8b@yn59*rtR4)xLey&;Bm~z!NI`?JR}yz{Ju60 zVY!F>qNyw0v5vDM23?Ol!1|&hBby3!TgD4@ks#qh2dKQWPBeJ5@;dX4pM-9&4k2zA z@ND@6uE5+}CO<6lmvVCGyfb!qz<`WEbj#H!x$m{V1S>He%g;!m6BJAYTVYXuZrC11 z-rW&NBUr-4%ZrFBz%rZh)u3Xwwzj8N8V=nWVND;)Y{s-4i$0DpEG{h(a~jI8QFc`j zus~&ujp;8>ca1u~JQX^d_o=-eY(mvUeJ-{_F}A|axKMG zz1)mgLqh{<)A_U~fqOG<%@w$=M%hPv*ORRUcy{V)^=AHNZNblL z*fg@!D=>IQZf=Nd6fOVe(?8}T!}{paqtbaQFOgJVpvy{!$Gf}-zad&(IR%Y|Ke zAPzOj6|*kEzz&M-H&wx8i8%B-i0kU{;AJ^!EE>g`C2dGh7x;HXga=1v*b_Iv|KZ#n zoq&molQXKPM;;&qSBCt*Gx`QnO@7rX39$8X=P8hgd%rxDgE$?Js0kW9yMO=wYi;eh z6*7=MfGhft3pzxkrYd=Oh#(Fcz?Wng!Xv!&qS^TP;^yad8rg%30b=UvdMR>!q|zQj zJhXBZMXRs~kOndtCms5O2QqSUNMy0&*XRA7S>@&BwwYESRSR7o4UKO*K+4S~?(#`- zgVW`P0N?5at5!M<-=?;|Kw>YSF$qAe0Ita~{6StL?Ur45o0jIaY93j(}hQ<^%-? z-`U&W*9DD0|$D#}AvbZ)>7Nqtsa0 zC_A3pltAt)(?Wu2K3wR=vEh<@dwUxZGmnn!z-x1Ntk#kp2Y>%=jCd^Wbhh9hz9DPW zY=S-=Ld@wmJqC$k;oj}dX+wCmc~|r^;5FY5O(`iU z!6uGR1xrXv4-E`h51ZH5*9)Ca+iHa!A0Ka%v2QDaVNg0ZUfoHr|rXICZ-U{U;_TlfAUhLaMbk_T7mnkf5!uG{+S~7{5!iipm>nk zEp$D#=-so`gRR1pbc0n z10y4d1N`4%{N|rX5nuxst_hOIGbW~Ck5!hAKXu2Mic3h>UtC~^uB4;{s*BLD$1@T` zul`e2^gk?~{{P1ifcjsm$^Y{klJt&1EgvfT?i~rpcRh)`1>M(qd3ik`#}5y`X%8ip z2JsLAasbFYF1rPq?z{u=a?C%0 zKRrEN(TU}c;o=ToYspH;F}dM&chu4^*babC7(QbV&_3lNvWi)JYXGOq|S5?1w}gb+rQYeqliC`DeT{aA|gtFpr~(PKyELus!D*U%^-5IECv9P#>rA6H3F}`h#nWU$6kqY2Mjy)FRh_RU$|@D#EiH)X>UpYt zg1bT%HQPL1|8e@EowNS27`;6`PySLI!gQByoTAdJ3Pv7Sh~2P81La7a#Xlhh*IMMC zN(=XYO0WE%cZmOj)A|3-pa}K~H#YWqF+P>%FpE>vACWg?um}H}^6y`GD&K#y!M|3C zd}U1e(5f$h&;gbe&ujTU_EJ+*69M%=ya^%Y4Fh#I1Z10d0ec1n)#H9TlMLhK=C%fI z#R*{T;LwosdYZq$u4bt*Ze(PnzP^40sH4zXYv+4nY5$a>i=#=Z1bM2Ajx+XzjHXl?y;cgbeugI)wDzuTZn)MNRjaK%KtS^T@?R~Qx~7#S2Zd~ zOQVdvcVz}Z1shBl@?QYwia8HKP=@Fm8Q~EVPec{{P2Db-*)eUEm6aJ%r+`fi3=S6D zVJ9aiA08cjNI`J}g5~we6fvI_6$0@KSfXQN!=|Q4y)-TBViXd2>|1jF@DsT3M6h45 z5Mpr)3l?W*=hCvWBK^*XAYFtB&@wUx$G&$#^ZEqq~a4B$RYih@OL%~$7#h)4uz0R-m(H0AHCj2G7s_6V|$ijJ)r8d+Lece!!93u{xb`v<1NWU|2HM>%=CIP-e5|Zv)*P2*S^{J-GlU_{P z0Ach&md{?s;^}{A=zS0lr?oWk%v^BmQ?QSvspu*Edc7OfQA6$*Knkb6{d~9)lqP_U z<&NAoMWxGxQ4Mhu5B0!DEPSv9@va7(#p#gt$2j^mU2}xoV;i2~e)q-uE$dn5$Btm5IOWu~2wEw|9YQ)uO4hzf->k?7!mh ze>u;imw<({Mj1KZTSR`PxlW|8)t7#z#on@T;Q9Q9uy89|XNWrlG0e_OnqcZWt+y1l zPLE4@Tf%2QoelK4*W-@yy@YQ_Kjyu0&QiHL7r~ab#_1GCK4tTnwrNn4 zjIrpCkxU`xVQ$9bbV(O+TBTPMFSbS++eU|)|Nfo=e&H4tvlGG-7NvkaxFq(kHsx24 zqjx89!`8WQTnT!vXqG+hnWpjx{Glf8@M0t*XZ6RX_9kw9LP+PgTtgHOwe>7~(_))o z;mr$}QrU>Zj(`EOKahqZ~mawe}ay-(ZNCvBo04`ilUDY}g=I--0igxgK{lkbEV2@hvin2>ajpCfxyUs#bA<{c5jFFTtn*BV*{Q(4@gP zK&J!3Ax@Zkdk3uH@k7JXYWZZ-W@T-+}Q5U)|Rd0m3~fPCtKsd{}GY9eMIB}wlD61Czv ziA0HiV9BC55d~pSmiS2SxJJ*MXy?jR+JL-#=x_Rr02$WrjDwO;-`@M(J6hjDEw=`{n%WTmc~ zr?{9e=b@7G3lB#|OHndQDlqQcKL z+|hYMcKeT-24>zpYB1o4k4qqE!(6&l8Tj4h-H-ihWPEhHADDJuMlt<|(lAx0ORPO~ z|J>{*t%7ZK&G{ftfvkxgC#@l6NervXUx8~PqF%igYbUlSY)^PP;QjnhcmgzOX@>?a zmd;tRUJv}9v2A#Y02>fIi4G+;gZ+rav%tKJ8)gKqLh= z*R33)GBw>tShZsI>_=MFOi*fU{O}LR;tMx8;bL$@1u`~X9GmjQ@0YS#=>80eXKvd3 zsk@AH+zejmer-6U)3!9@)PvW+7efvvgy`px##pyqGfZ!A*_L0!x_+E%zc_dTf>Pyo z;D`k7G5)a=KH$J=T0dr5r`1D6St4UcR}T-W#i#8Y9ukz~2U+8n^=`XWSA=Ydj{us< zuML@#?8}@q8Vut8X&eIDWJ2DM2{$vUw zN;BqkJ9Z>;M#4zawIk6xN<}rO(LJ?6Rr>Ue4>6S(5Lbfh`?AYg+PBxTa6UE;4=oWB zk$2<{?AJzWbrk1GSAKj$M(e0Gof8W}sasitx6(g)_8$7eAK1H7L zVejW?E0J-HW~0ll3H!{ir0u7448LKraLHDUBc5;>r4on68c~$nANAbVN0;)nFuONO zqT@$j^xmrD!UDo}`~JWiE6&A%^vq$3gESE*uRssfEp3?$S?S z5niFWd50?MG3`Q#oN2hew&YiUEV9TmJLU1YHb^R;j2PzC0m)b*8!K&6#t6k+^dWCs z{yIWRp50$Gxs}`XOt)zb#iV4i(%Q|_A}L}xFL)?Z3K`)qXU_2&X9g5CVZ#nnRg$ge zh_wCM95?q|R7Mzkuz*b<)HHx-Jub-A$w$v#9haYm^x&6zs#;s-C)^Nu3~qrwH0L;Z zXfm;qT?Doq4_Vf)qTY2GcPRsL#(sAXFK*Xv;&`HF;i3Bi=5xJlo~%1@LSExKlmwRa zI+lU6L^yC}#DIfcC{3ex2!$=CAAHLeMbjo_z8|aQbM9+A*VZQ_a12QGw@K zYy=}*g2(3)nXdmE6{@tbA?VE`1P6d5+o@Wk*m4krfZk0{9J|jaBoq$4c8p&+ImzdP z5{fgkF@={}aaWMfPf3&8%benLhoOZ|P3?r=6voN|l73x$bpR`;YVD7jh!1o+O6SdN zzN(AkX84qzV5qt^NGjF$p+qn%xxRJ>N7v*1G$?5ntc4xOxZRzegpR_LNo>^92+=@>g; zQB_8C0~RIwyJh~yV=~17a)LjL&xTTOqCr6$3O4!Rw>Wl@aGLIuIf z%8KZ19ISMQ3mBdstn?%c5_)Nr7#6u4e*|X)n)N`Ff=ij25v$I^!jc8ZEznX0;+M05 zaF15dbFNM@1s%TRir~u61*v|McPq~d!Uj0`%M0~EdGcn<*6inFYPyvuVFNOH%O{(; z96oVvv@N%*oO$hO4j7DApt90%GQ26u0-U^ElKQw(Zgkh zHrY~NB%u?s?%901wTFmi6hfIGD=V7>wmr%HWTN(LF}Sp%g7T34|B4hjkg z4;NkKmy?r2v_Yt7Y5f2xtCynJcAVj3!=8Ws*K%0@Yr0 zl1agEP8Dww$QTN!ti3kC%$-na|Ivygb?Uf{Z0-@z*5bpjhsPfO`#5+evo!x-b3Fh* z&<{%8VgsL&gsGB1ke*Qcg={GS9g%Iwd!wPznJyXZwBSof1RA!Yx99zcwQ(9&&iXCV zM!_rRP%Rs-9RNYv+1E$Q!BOlVC7W7$>JCfi;k?nY`!cI1Lm-ja6vq2aKN~nYR8`Lu z#nOhExTGwK#|L0o1lW#{`89{K z-6%4Dv}F+LVY{G34f5{|CL4M!xl9j$^{v^n^q(_bN$hA&8q-Ff4gmlL*idI%Osm1E zy7(|h{m7mo4LCKw0R&`ADd~;op{*wFcr@TK8s*>D{VA!ag?BPNil-f>%mI^*kVjP8 z{xUK(WrP6A2IdCBjb2A@?^9ORa0Exor13&kbyOJ!IO6?5Io3OccJS9(3W*NQj*@zM zdT0+Ge3+@W2TAwlde_r-!XVb3e@u?GZrHgdKzGZb!x?npHQKm3G6stv0X~&;8hwz;EQt|-F@IvKg1T=z zW4fZ}4?t1j23iV2N594CPU)x?ncAklZBS)up^D^lA7_v4 z9r#;2dO6~lsYA+qMX!h=MZSSz>eP`;SLY4H2%GOFBx!c5W{kDIz6g@jYhm{!)~IB{ z`Dlhrb(cj?{{^aOLd5dXHC{~%KN3v<>fU1Ac3ZXL+txO9MLQ!|Sv26aK#Ngg(EYVf z7;_Ue_&$ETXo}Ld8<2#8U+I|>f6=ScYG%+=oOL_w1x?&3VZsJhK*J{s*1T_d1RCO? zli|r0B@gzNl|Os<(ZAW84%KQ``C*YQLh1ZKfGJqF{d% zwa~ELx0laSej%KMh`4_d6B%Ur6>nX3DQO!G5NAEg>`1#SD0Dx3yhn%;4ClV(VWOab z3ZzrAdL;M9UNXjg$&v$y-G89Xr|>UNz5er8Zrx>CBX{ZAbz9MYNi8jZcn1Xp2TO<3 zHuohiIN1b#ugkDx|IG6d)Sl=8(8_twyXoG!y35Q5X`~D!ViMBUggOKLC!Z^ihBYGV zmp>1^0)mh31a4DxKmnVM=EAR>KnuC@po`I!Awy>OgSr3oTbzV@%HkjkiCi@=B)L-k zpww?bB_$+DmdS+0j8zmfWJjkJiG>7U^9U%0S2;;ADSw)+E&3U8@m0@qVnl6(tIWCu zee;~UBFR||Ypw4Yl8ct|)o5FbUeT293QL|h<06A1U-218u2w*A0b~OG2xDeB^>i#% zmZ(?W<1QV3-fsU}&Qqs`sQ?0t9`0prx;*74sEfZrjZ-?ylW%1n-*T9pga%|!_;hnz z98bQm5)kU8fC}n4Q#% z>$EfaC}jF@7xCDG%m4W1mg`P)F`H9eJLD^B$eiv zXMRoHu`R#m#9f02eo9ow^ct>x`aV?{rvOdC9m~#2^+@g1UknQ2^L7)~s4eoE%&K?1 zUK|7dP@==^@!s(3taG_0ew$@-6v?N8?D%k7u4+(yMll3ax*y?+iHX&o&bmH%`m_l2 zHE)0nj!!UAX7|e}e<|;aNl8(+T)WgCO;%HM5!S+P$4{g(SCYS4bH3V0QBGLvNr4M)N_zZXX+q zHA;2=dT?Ol<~Dtq7~S!VzZPpUk?OcsZ!Q%ymPDnq@_nwvkg}ST8vMd3eeG|(l5al| zds@k>ZMUeLW;zy6ZC_cOD}vZ`wcoV>fC(Z1b3A@ZRzrSsu<%}r_A?vH)9G~?Mcs-i zM1e?gYfL$GUwXgCK4b6L=JwjPj@ghF1J&qwhofubU4YG@4b$Q;#gF>dv$f7{KxPD5 z9ZPU{U_*l_=-D_r@I=lw8QO<1_gqVJ_Ux@lg`)iGeolY$klSEGc@?s!C3?n%fANYH z<}tIoB|8nSn$_z$dqn$pr{UJ4{^~%E$6~qzbpHWNb8z6n9W$zE`J_Zebw3>tA5!)G zEl5)Du|=out=&90aYsFbH42_SH;){EON4C}P;O_`rp4UWxbb}zQN>XlX z-yJ8F)w>(UR&84WUUULqGgbn3P3p2+A zOSf`Zwow4uvUQy=dj(`m=ze&C2`F_glxUC6)6eo`f8uhLX-q(0ncF>z6j{rZB4A`- z08&_bAX{vknyNWG0hI#Gq)7t${`m2aX>4&;r0}QeXwqesg2Vq;w6<4D9tHLk%1 zGM+mnXzXPS^jxgHv+(3k?9M9;c-7yQGJS>-+{@uj*?Fbx9%=EW1V6( z_991`pNFDa({alw;fw`ghdwfw5!N9rqLK5gC zm%U`$N=0Pzj4PV|J%|F|xKKFqeIg{*jADllj&B|y==W45N*SBa9=IYZ){pCJ9j2V} zwF<*FQ?y}=Q|+9;+a4@|`FfN)aRTm7i2afYpi@f_(^t*eqatyd0eKD;5+V?_)Vg^* zh^M%*onw^Z>{n2K5%i4;_9hIJ`ma@0SBG_|S-K5<#Z5sA@ty=pvQ*Mz0P>*NLll0| zKf^ZfjEP{TUZY{o8_Hz7;PyIF|ZEakn3=j*9TQ9H;7pJCS#o>fMDXXz|8G8p4F1 z+Dl2_CG(t9%AJHIA)D^+a~-A%_A4t3$?8S5tQSs9xK*~V(^I>*%hoY3ZEuIh#;UE2 zf!v%xP2;ZCiDjJUn`s)NNZq$edRM$e=eIol>;{qYY#rH2?d9C&U6t(An*gm|UD*0u z-|h2Rqp*REj>lFvxBNlx9czhkx$n`6q6*I0L`x>(-`93qUE8L4uc3N~B*fNj7++kuTyJtM|CUdLdXUQDUMq&9+vg)krm!XW+S&AL^y9WL*eF5c zLTH$$H22)2$lv;LPN{moOpbo<^zXt^hvs^r9Utuc*fB~$Vy?09zo1CXn+^?hrslsj!(x`U-doNPS&A>R`p z@T(7W{GmMqD(e6+I$Z751F|y&QwL<|VZkib0YIcM0&pT!$-PLgCZs7=Ks7nKo{pZt zo8@}7y3q#4L+W2|Bd;*KzuKAH!b*0Lin+AwooP!(6W!zbjMnQ;Km3L>n0(7J7lynp1P~w zsD%mRpW}ZRamz z*1;Vn{JI*YQvjH(X8@fUWn%AruL-kNBhgD@Y|$&L@OzJ}iMN@9aOTW)zh7Q|H;VG^+^Y_D_HVsI@;G9f`*gL85?aQSy zJMQj`YPYt`B~mck-4L-Eo=G+6RL^1RT9K3Z9daJh3Wb*oJ0?FT1&c^SUt;L$dEkTA zAA5B}y=Nfb5Zc;+Fu2Kq(D|56S4RH&#qjIbFZBiwVQu$gd?lfM2_=I^)|iqLI_CCU zdGv#c8nwDdP|)R=`fBX^2FZ*ucjeVvJU}t+9S?TMD3OBRTu`dgBFu=c#H<@P>uN>i z=BUZy0YjqVrW-&pWhe~iE2L9=r~Rf*0PGWDh3k&gMV+Sx`~9GIC~0LAZN9D>|C8f! zD;%36+rZVW__sN#pt(KZtoicggM!+F2Z&1zpu8v;LJF!3Y1t%KK`m2Du0(3EBKm?X z2u#;`+p~Ni@FHXsi;>Zh01qT%`p_UE+TXA!e^&A?g|#R9t-suv&K9Zq-8~|TI(4C6 z2f}-9bOF(?bHaC0IuPWi3V5iA2(`ALJTvt;KJeZ+40%?M)LpgVA! zwkb07SqUs20fp3k_^i#wJAq0IGir)zk6tS@U5_hshx@1f@=M#yl1wviIsm#r^ZMJI zx?9V9&q)*TdeI{luT|$>m}oIV-VX$*MlQES&1>hN^&~Am?BSMHA;52)gOjzNjqcI(=6yN z^Hz^kd#6ALFgk$?07ggdu7eHKQc*dFN8bSiufD4;<`mXgg!Y64;31Ji6`bPaC6Jvt z`Di1eJ0R_}{v1p!M3%u1J}99dpHlNTr!pgt$SVX7H;Yj#+B6qe0_DE9clFLC5DkGV zY1Z%PabrJ}ywEMzb46k{quFU^CG#`nFTWl?O4r*bwN3zy@_AkF!y!F@ePOyB@iL(g zs6ZQzQQCx6LXC%kJsR-KHkH3*E$ajLI?)I#i{9md3nKRCKMD%QxZc18yBx$ceNHm* zPGg*SK4W?*-4MRp1g+b0&^s#5`0-U1i3aUt#G8)V=%acA6%z%b=TAZ|*=la0W*tds ziFM)uVb35)xnsOAZc?MqjJX^qh<9?G>*}7sxmg z<5Ip5H$`#A50#R}wU)aGd}>2IrHxX9`LG=Xx7PElYph99Ab227Zp{M{1h>kZ&mK)8 zps~abctlOvV64{e#U=*@Nqp-dJRq?e%%0dTJbsG`$G$Tll^wY|v{5+2%7F(+>#4&M{RjreqkWb;ZLDSOmhpD z!vAg=e}$vtt+WOv!8}}1dI+z#@oT>y`S9mRv}BU5gd1w_wkqIDz#ZJyZ6Jjp>ks>` zbK>nmEJcS4=YNdGcEU4$LK3~rE}&3wy1&CAkjukDl$FOJkz@cEMv)W>0J+%#k20kU z1|>+ucep{hpMss@0kkJ@4ZL03tD4)_V=O6wUnU8Fd&WgPRFv?l7_gR@{@S)B=F*^J z6SQeuF$wtXMODx%3wwGiXH5S|R}Ji6=GwV`%MZ$?zKU<<9qU|mqrk7voD$*%fQQgi zTL7M(EsvbXMvfc*ZKfdTrjm8{eV@mN_^_}E1O~9T&n&2;IbDl}Dh@Jkvzk&> zb-KHy=-_Y52}f;!%HYsnN{@XLmMfzqyGtl9R}<>9k`Tl&sCA?wzkKPyf;`7Y#5S`2 zgt|S56f@AMrP`=zQr9lweOk*$y|;>J*WT_#xRij{h!lCs%>ZF7L8%Ed=J_n+INAVu%gYFrClxX&5t7ZzvzZ?*sEW&#wbIEMh-xbGwJQV{Gd$P)Q-CYd%_I zcamjn6Jr2b0$f^0=gl|7Ze$*Lh;fxVSp6vOL>!Emf%0;V1B>rBJ{clQ#Ow15ckp(+ zX*9p-J|WDNV0=c^2yhE}u`Rf>vy*=#&KI5VAqh#>&Gls!NXE|KcFvuS&Q4t* z$KRSP3kG+|4?th?QO?LqaEk(5mNeKL%`=-UMH3Yj&97W+P`MA3$FqHxtkvt(Ms-}) z(p8k7%JBX45&LCtFpKdPh3eK8994+V3g#Abo>A8~`m5Sf(wKl8A~HM~Wd%Z zJjh9mXMaMXR8sF4Q2Ay3x#f#1p$V<@O#;b2iGn1~q0!NHa3QJ%aqX;cYNz&45pkgm zq{_3IT@M(m=egX?ae=43^OiRkR);mXN-63_Mt0H|{ayq@bWc^zXE?@;o;G^|oFa(Wm)wtVUjp z3neZPdpCoLP-UYou3qp0HN}sQW_pG$7!>aw$+bSk3`EPE`MCC6!v`3x3o{UAv+K1- zBqqwee@|gD;tFD^TI*Tg zXS(P>@Cw{BdS&MY9C?}V3(eJjv6J!JH<6t4rE_7-1n7rr{YIem4z7hDE+r#W``~UL z_!9|FfY4jhqRJO>BN~V$KqpnbSRV}nZpI;+ei-BekAmBpIs1itCd}@CD=LZv2zY ze<@)y7s|$TKS~N;5(;unx1MICb-5w8W z=6tocQG!p4!r|r(9l=TYJ&B4p-D{i1ET&_!1&{u~Rf~|oL1`0%ewT!Cop1cDzgkpqb4fH`BMalNbdb&T7 z977ZbGgNnw%c86%qW3o!GdU5lF!1!F|}h;=01GgVh9x=qJDsJje@>)SA1D$XH%M z#Y5{~xV8{HGuN5*CyKG!106eGTxhX_TIVzw>4J}F5#a!|L2O9Cn3fE4=p)V%4rz!n z3nK2xq}-b#5S;b0RsnS!K7arRMOG(Xs2NKE9nXTWj%Zn0V@Ikjl$WD_GQFHDJw<}8 zi2+rU(Q@u4nPu&xTuy<&p)G;eu!Rl7KGKJwv67-Zk}jm63UL-sKeO>fX5Ll>Uvl+$Jm+0}%ezkS113VPl5OZ<6`2;h0` z-#;&ax@c(zG3z($4DN8(le~Ld5e|`vY$u+mtFU8L3?E_#P)F9L|PXs#ro7g|ORjZ9L2PH89HMo2CEOsLu z(M75r$QY-KlxS(4g*zI1SRy5nmpzHqtYaqQny>p46R~WE_&YzJyAlJjaP=6F^}Yu+ zC}tk{J*Ukvok&WcU4;vp@r>Y{}tIAUryF)-nj&3op?fm@t z`Qsbq*6olT%9mahl8D(q0Y@%);=ZgNKyxgV5fxBLr=%S~j3v$EQ`WN1mEB`latOn( z2}IvF*qM-(g5l!Q?QywUDSqSwYDkzx1p=?GAPhG0GEEN`>(&bK6$NMPzi00m)PyM7 zbj{9qd`_0MpBA;n5lJxw78(#GPw_|+q;DWo0lT?)fN+%`te`0z$88yD5{7Ky zGLaGtO!}tQhE-h8r*bQo5AiOZ!TlC&7o3s{LlJxCzRYxQLwf6#(_Bwif3g?4j7gdojm^zybGG(K!bn! z^_n_**SGxs9-Cl20q&X{5t87XcQrNaM}4pWbfi^IoASfx4=2CY`^1RhWei`_gI24^ zlvI(*>=ZDe2r=P^{08{mUAjS8hoj~yB{~aWpj4h z6E7=~8MQ2gc|12zp4Nu5NGq2*fgW1s?%shTlm=RgW~Q1kL^kx*`{P$j;bvwa0mM83 zXgJ`gu+u~tsOeXABr_0m|Js#aS>eZF{L5=S4H1A{AGY&ldByJX2*?tGa3)$CE3W^I z*HKXx@iLK47Zr?vB-I2RGja*2?N3#|E}fBq+dhL!)c#&-5Hg24Uke03&Wy}`wQXQBptt$7@J;2IdJZ>>fte!&)$`Gt$iHN~`*~3cflp-hx)qAP~)s ztUDnL<5Lz!(1)3(mkCo)+v?hY0dP+4WjxPE?gWs0K)lYVo4b_IMxzN54g9mL%@h>03g?H0tOAe0e>S?8v|Hk1b=&i#Yv(K7>M(@~MeIfY?G}Uq6_)s_2)bY6y zGBNr*(*?>@ih1uNqV{a#_D?d}ye#|}luFnlQ<{ClrSxDrm1N+r#auE>VH&cclIkGF zXZBzkCP2tEWzV|(U4hW_>LR@foD(kL{E~^G+e^Mwc(r7t9%8ffD+E<_LWoceF~0>9 zF<5ZL34QxL?rQ-EgJL_C$Gi&ipj*?BrU5`Q5U$Gt^?*Nv*4pGpTs08Ac77INBrtFz zziq{LLJ`O(XX&|L(;I;rmdD|Mi#y*oqf++PFW_oy*%Ea3^8soFf2pfYIL5uCAd#Q~ z*BWzQFRhHA>y+f+h|%F|A$vo@rC}!S`jUyveOzk=*#(a$e&;3(zdG1Kf$GXIhk2ts z$sykQR^q!)cIsml<;1DntGUY>VluprEp{~Fn=9(YN$`h}qEI9cfU@_UV5zTPha>R8 z%c63z@8vx>*3S&lk4TZ93Vy4rl1{yt=*M~m9G6A|KFJ_15oU7mO$NXgv#tVAU61^M?aW5f?jlgW%O5ZeG*Z}bNw^v&b4Wr{BRbpxzDBk_gOC~&sS)PJfUJiUE zrp|xHcjs<;8u;@}!Yh=s-A$n5?8!2iC{1nSb~8)R{=^r|$t@fhc&ueb52_M!2|*E< z8!aA492-K$b~pc5XMq2}%(VCsbm5mat_FUyNYk;Do{FYBju0&s#H{tvEQYw}`#H^Z{?Kw`cjjz(JLG zi;$c`*vpQ5Dfk*Won?0B052yW7q1{aU+$5lR$m-+breZtaMxEe^VHt zC^@RCZs0(G`!xmTRhnJB!D}!1r-Zha^w`oA*o*FzBP7mgP|J07p1?&yl>^x7t%NFq zE9*nDab03&2Wz1mah*8~q0r^zAH)z~-i-kSTDIxkD&02~i9gDkyR5%%(g+WI706sU z^9fG)sVkxgQOO#t0&C=hV?2X_VTIGA1AA3##mKXQ#bIyK7>)16bcexL?B@2tNtR`T zs5)b~O{j-S{uvKiH+f9Gkq9784b3!O@dV&U)vZmu zE3W&M&&C@P3^cx0A&+W9I6S4darr7WiGBiA{@iIyp@xM@Fi*l#d;tS9@-F?a8Chi| z38*MIE0vR<(@{(qfttju-sSc)p76{otV?L4LJai)TbnH=ize9$1Dah?K|vw*Xp%c8 zb#@lq)er(>zy?^GT-H;JmjhwATXMjz?vuuEg$nC)!{L_a+pur|{_SXhU(J^gysr{H zNSAG4VK5TK57UdJE8Ea^vFmgC_wP|4-c;kd_j7V)e7p<9MP%gV4JRvYLH5OY`Y2Q6 zA_S5NK)W6TWKh5wi0b;sJ99{GaBS?Dt2^kCflwDxSP6;9URyIWuH&?Q@EMIl(+I|V zU$~AI$Nh@|vsrsKD?K}Gux9ZSC-a2OyE|---om)6(e#)Ozh0eM=)^Y4h`(Pf{b2%( zc~Ev!FV?@s$H(^w1fCKS64D}GgVxQrZ{Id%>XSjC?kgI#2aXR&rvMPMso+hudX?P+ zk&9KuVvVb6jcI_djsA3e2ylkPik^6$NFeh@$H#XAq&o7oLaV%^Rcw?Qa*|VaEopm2pA<##Pt0W2o%ImQ-e{g1KV${|CCtW`~NNn+)m!EUXBBqCg48X zcdg?Qzp9%ku1G~Ln#5-xX?St}3ZqqTrc=R@F%K{XJnFUX-b`!6mfvVS)sS)w&?kEftv(=c`yqSB09~)?W~Yz79lbg_Qt(K<$Om+RfE&!j zIx^&^U1;Bp!Sa=LAorjfWt*nsYy%B@3dkMad1JkV_vT~x)!msxgYDnTq0{!Yr)Fmj zWCA}MgoxXZ;cLP*RX z)c%Sm%H9R;%R`9@^zvwVc)r%u2#$}BBU5RR$dRIqhD;x@yf+&LzRSjPTav+egQf!# z5e#5qpk4!t|B2IvItXcH7Z#!+^Xy3B(_j#-`xgV;0t!=0z;Z80g|WG4Vnh&~CeM$$ z+cw*`3oRrkQ_*BrMqJf;kkESlRCq0(0Q;tNsJUhbi#Zz{S+ogG--258^)Am(ekJhX z=MH!E@XW}$x$#56jx9De7U0OXfakTD59j$97x!FUodo28uF(hyC7Ksh1p)*^zgXR6 zDb|=RzUR}IFLtejYA6v=9kARY?mn(W@d=`G3r4;Xif{w<-rmzL^O(r_LiqWt%rG!m zU>7UED@}J@KjxHt=dQroR_%iW!2_Ac(2YeRUs2z|-nlUObjIRaaYX`P)=@KYS6%7d zsj1X@L3h*a4AYh!wC;{C6Rm*_9dqKXaa*P3%@Cz;?-fQgwO@AqR!vp2*?gCAeMZsG zSe2tBSr;GY$QD;i&!>@sk-@wpj`MhmXT{4RyQE6K!Zmj5l~!{15&Q~6A#PLGdFW6^ zHzU>w@1f=}hE_(Wcztlf&AVbK{o_1+eopL)gx&P#?NdDrrK6jT3H?c17@ARzg-phQ z3bvX^*8MH}<;cU($~2iHF8k8ZvwC#OU89n*Ip z!?pEewd;Pp?q|My~k#cSHLi20i|-;~ShR4Qh&{lu))W0wA-v+*op;_{SvHs@Zr}EHv}vx-4_$67ZlO?iF0RH zdZPTexIw1=X<62*Gy?VGki7|kx`|t4sHg4-gpgYqJ*Xm@)B&A06(jPSH~Jmp-=kjL zJY@K7Bsw>7lZ%3r=6f)@90f^8<`{sqA@cF`he4-WtZqcy_}2N)ee7R3-7Kmdj}|fh zgS%}luw^TNHW@M89HiuaiKuK)5>F4h<)TTFjQ4x(-rCigQbX*#!cJWf~$ zxK`cy>r^jtc1l~eZMvS1Cq1}>eINVCSTwyJeg`;u0|Jnxr$8Hm8>X#;f2Pw}$+xDk zD{>XZ=P3uDs5J38V}xWx=*o6P#8s>uUOvN(nvWO0ALoen(9~oTxu+^afVXaL?YAbF z4|9>e?(yEj>Xg^7wV7Xp7n+Le6auKzGPTx%2F}8vW8(uox1o?|VWvT_sVbne^o1O{ zlGzaO9em!tQ7y0hLSj->rUdOM51al$Ul+CHpX5W=JR==$4ELCn46*m4M-Dvn1h^-9 zu`=Ioo~k47JPC4yy1x`V`~Dv;k}&#nHUYgY*`!e&Sd+TW0|`+A0ykbbI$@??13t}>de_%ee#I%9UR$W{je>v6L?DP>ftLC`M| z|K0HSx;4?}(fra7{bL#4+I51+R-;2ica--nUBnk1gr3l@b~se7455kgi;7-#@e{H| zYYKx=_Ic}iG@3Zfgs5pVo&4A!?py5iHJj;2%7TR9Ub}geyY&Ghi)?1S$<-I1@K2D#(C46VkE~)t~rHFB`ghp&DUFwl*O@ShNFiNu*ncL17E{#?)H_ zj$w!-7!SwKTYf%_=)uSmT0$yUtM<8TrU-F+h0S`y5|z7l?%3B}$=*zEn$I%v+Yf%2 z*+)XovoDWKxMZJV8alEdPYow{I&m6i-|Xt4owNE5Ybd_TSPVz(8UL}Y5hcBHudsKu zF^+i~h$POC&|Ciu%j&`uA{P}u{S@0=7aRIhQ(39?0^)J=@%r)N_Ebns3SUkbA<7H= zcK`Y;_ZGDF>dQr_Zrccx?g{oxE6Gh92W$dt+Y??{3hS ze5-&hCi8rq5&~ja!yMqy+9N zA=S)kZycUARcF?A)GbQ|$!cSo%|o<4zm20(N+3BxYcZa^Iy-lQT1hI$^QCYkG^4MiE%tHE#a*j)&Y9Z`VoAnjuQ%p1@ zW4?B>s8Sb-w9svV?I(Sr@;K6Q)&9AYXb&yPM?*+#POgPh(p#PI$7EpPU-4%Kq9+a>;6cC%?t(%8t5>!UH854Q zy0@Gu!^YF!+;pGj0BH@1pkXW#9qN`Ovb$Gt>arR(+wo4r8~CkDwAe-F4VD;P-k(dw z3Zq{9jHBOX#A?;{8Ey`fOjdXENRx(ci=Z6+z`WmBjGBabHQ_e3I^Y_3Aom^larQ=9 zko-DbxB_fzJ6BG}d$z?qkw!xt4>F*(V4Obu@Dru~7CpnF5u#f-&3hLOgMXjQ$Q{k{ z3(DGgbk?3?#&3}j)n1&>Qn-8tdKZ4L-BUh-LPf%793&Ef1LSuK(&&i0oSSc5AvY7x zfzz5CP)v7}V7rTT!ol$)u5sz*pJhkuh#RT~M2W>3=e$GP&#(@vaSF>dB)2X(8pF|U zoBg_%>coHomn8F;H`xzATe26)GqM)@8ydX6O1&kO68SDs%1ni*l?9&e`shW${N4xI z_dT?9?PVpuBi{w-^FGY-t-Adk*aLCgg}ThoII_@tP^u|s{@n2++uOB%OqWs>Ty$EC zGU{uz-H~?ZZM5R2!(hVIG~}S2-HJ-o$QB(W9h?Q{jNS1WUXV$%euP

qs=~KcK98(t#O}M?U+si)0_HUWtp^)3U3Ouc%cK`50}Z zKW}ccxo?Npio4vmMrow$hHIM;{6V_M`97-+2~OzDwb%qN~6W|WJzXNRA) z&bHT)A|~z%{eaGc7`alncLQsL&kc9j+U2<)s?atEXH6-%^f>7=|A~54b6tR**+0mh z*NyB}F^B2?pv4_rXN2ApTU8HqorN!hedAAkD!it?Ov_%mwQ_BE5vK+|69?dg_<{ic z#!gG47XhdHo~Riu(`7zTL%BAnjB=g@DiJ=xIMqROBLC)C9rEzXukuGPN!7NDn!qmy6= z!AQ%F3g2$He?$b^^OAV;Nhm27xw?=gs*5Wq%N1ewKb^J^&_a%599+Y?_soYf(Bw`| z@I%)UUcX*uu^2+l#?oMowE4K8+U<6Azx?|}!sd-_x(qv(>|54P_Gh03F4Rgp&eFgfc)9&Gi%>vUG_Q0YSaCQ3{DS>&yCGo60pIe9~`B6$53lxkFY_jh2E3nv$k|KYFM#TE#|1+ z=p)#;(QQ)tgBY;dqE;rlYMG>pR-DP3IZs=Q9d|q}NF7+w&fZ)X?TR{rM|>Oaxo}(V z8)bh9tv8bT=!OUR6xpVLA?q-;HG8cEr6zzFre|b4v7WAZd{j|h{sb7#NNOyP6~)QP zN#YR{qP*!qJphFGgwJ=xP=N6KYbaZp6j&wDi$4b*-?rc-Xt&b>-TD1{3{W!%MR4qd zlY#W=4UfC}fnp0Z@O}4Pzvm~N*I(@3e4QuAxx-fH>A@iOn$!Oqur)jCAenbdPU_1%=4pQh~^Uk3}Iq(Cj~oY9Ip+QnN_;Unp6C z@cFpwucmi*Z)0K_g4!e!-2ip951_Q3_+OFD&X z^rywL8%Qqm0p>;)Ln0Ki>?UwJGBXC*`Cx0)3noS8ZqpGYbhNbJ_K+&?k6X8@+tnWt`T6^2=j91zw=aR9wqZ9BkiJG-{|9pCx6A8+ zM5nr2x94f@_ahH1)i6S<3+9;GGNLW=7cH|sMrrptnTld-nJ}r_%YB_oSm(&b1^ria zeuhS!CEYJR7OR=qFL}{oawGLR`r*ObL0Wl<&(oP|5$||7IccK0`N)1j^vHTM2NE2(P= ztB=Sw_-DsjaEKMm!Xo>%wLo2RZ&5Yp#$a&4c*pCiJyP`@)PBNsr0CLj>Es2yC+wg+ zGdX~|76)~Ndv?#Eo;r^}@Om8EERTT2N=s`ix7`{3$__iP;(wF23qsxq+K@)2I-RkVAXGD*%N~B z_~j7@*!C3Zjn7UQ0u;oa>Aqqhisj3P1A`k*$Mc6MU#R{rE{lmh`QEOmMJ#H@E-tJsJizx)ClcUY5aoN+*m?s^RbBkdVtDx(KiiTiX4nwZ1- z#cbY}9!9?tLO>^YDc+hMDuKW^kAWI3eAUXuFPfF0fenk}0jORhePKQ%CH>|a(Q5Ad zCI*7Nf_uL>VtR~_Bt@jV2WXEgfK>^K_xU_^)kdZl8R&oQ{+#X8BB)?$x%{t0z2Fiq9O&5 z)CJ1|0=|rL`q5&7Ky4>PDkK|Q!~Vj84@J|Gn>M^gsIC`}zdy1lJ+vfPr3Zkkh|fizFYP`y)bC1oUF1VgB4n+=<;dm+>rZV zn~$7=0g!M{mOYNq`$qXlFq25cv;FI!E|xNpjQj|UWkSvAGsxaj=^U71Eap5hl}eJe73FY>F`sxz@9sr+V8Fn((q2NaMD?A z&)?HNcX-3*@5k?As*mZLqDx-q#-xTJzBoHBYklK(hMbM|_ z@ZiD)V?xW`PoCXGp)}HgP+5s8&i8w*FKWFD)TjKL!${UoZ9{%ty%o7z-!adsmTU;K z9dH((l8P4zcQD^I5(C1cCBN2rG(OoH9g)|EMI@g?D}66?KrD|)B=jBw+~aMO9K6PYA#}_txS@&?S98yFM>eIgf;wEdnA2TK@2Kxq*?@Dvv8%14ksydxEvXTw z;}T|NPaxtT#W{(~(LHi!J8jqHI~d**pB#gP%}QW|`14c2XlfY^QI4bgL_ezg{#Y&( z@l7$6ab3HSb(_Q|C_mh1iSBwF7XGM1OwsroaTROS2IyCh3B*axsFQi>o9u^t?_?mW z4)T)6J#yUR>#PBlr>o0T9H7O3YDx$DYIPCsOojyTkv>V_+J^Qr`@3+9e4)K2FBqc{ z9QpcQC_=-6N_*&pL3ufOqq5Pey*i)l>Wlt)eAuov6Mf#}%o5RY_I?DRLNp{`(@LBt z;{6+x?>eo9y&@4rAL-5kY#Rp}Wr%|8>|?jpnKGo^neAh90Sk|7AA8>c0wxm}8V|dl zsXOq->G{f^Gne65V-rfO-jbu&sBMP%p2o~OWg9;gq2_LB?7MHt(q8}lQ_;_!Dv56|x60Q9Lmheh>FN^S9LBnxA`4kd6D1AL47(Cw~ak@>@TOR{u*o9dzaHX&CKH!1dIhzuUmEk7n&6y4X|z z+x8lqNbVV!3mFpRC%sG0j3Q+?`9F3j!R&I4u<&hO*Ih~$&7BN!i06(E$^3g-TulGr zp+0lWRN=Fd?Q})6y*n9#7MzQEX;b2jS1k%F^J^sO${*H(L-MIgibi-#Qe~HG0P?VaVQdIvi$mr!sS*&2ats5 z5Zq(}g2&yyE{B}Qf9C^UK7OCW&HpjjoITd$FeG)1Ar#SJf9YP5pP14n23NgTWkY(& z(i$+bMe~!N93{8&S+pVsB=DTat;*XY$xgi}Y1;4hX=frHPoHjEe6eIgto^zPf+Y@6 z5?%)F)kJGPRndd~1E|z~s~K)e#%@s_LiF^0jI>cuuZ2Cu4YN9kq0BdX2sJ~0)#Q9h zQb5>J<(P-M5vm5)Sfqk;ro}CW-B99co3i&5Q>W`i9K9|~k1#lQ2!jQnkRGaM`}CJi zN%BLf(8>yB41KR^d^A~~hZO(-Q9n^*^i-=%d#6;B7sa{9vE!6W5(}0Pej@l&Z&oe{TV~!O&n!lzOpmB zjW$23z1=IJq%w)4labFZuH`fJ7Rq69>M!EyT8v#syOT~eo6*EP?1 zK4f{TRa?|@mL~0#VM_~oHJ2kkw7k5gup=d2#=m@EE z{qjLtYELw>T%jSJ4>M=Mz0SQ>FaCkgxfiiA3D@Tjr=H?NTlX&-?qUe+2+B`Ky+X}Y zCgpq&4W%3SvevtO@BCv=7M2Ce_`gd17=S#$GodThfjXQyGy%7oQke1X;&3YCvqzNY zUN5ehUh9!;2h{hF-fkKlr+;W4#v{t`fZ;_P?ds@&ABr-JXP;1$y}0rQCrXwhrx1_(J(T95Ek* zZ+{Y(Ysf6~3y#}_5uzzGAyvgzgb!E7eUhMYMZk9O`{JM!Q~D_M&i>rj<;>lnBfDc= zsoTVneP-4A00Ud48oL^RD>0cBHB;IgKy>VwqGRBQTE+?yvZWRxu$p+E+{t{*U_* za@s8kpXium`^S1efs>~@*P4gjI!L6DYX4s2OqVq(5gT1rC)|@hvhcH(Li-90vvIOt zPW=rQZrKDp_W*eOS$neSa5a@iv7$K7@Q8;(D|rDpRunVI-h~24Vb6bRnDf zz~!2dVe*Ph|A-A&OXW9V8}>CVbw?$mRC8+pg^^?4%unt*GhJs#a!oUu^>wnn{q@{@ zp3tb?K>-n@p(~_jbvM7d^^&5%b#=#<_|g=tq{J8UlIlUoZbfUE+dDfbib~PZBWCOZ zAS`TJJNl?~eody8x^HCyyZ(<|gm{9ON(UQsPWq!-Z~J)&o~(0`Y8^H4Umjgdov(Jy zAy=xnp_0PPAo0gray<1Y#4r^d3dMzQAmbSSC< zH99Lj(R`N_c@=EzIpH(!vy7#KhgVGK5E=heaB6-0M(?6P{PG~jj3a6|{&xO^yxE+l zdR`C8C_6+Oy~THOb?Cx{**VX|2Up0&!kq70COw5E#6`E7TJwlX(9sh0^=ASj3mh z;73tG!=&e%7qMN|%sZ5r4b|)9*ti-MUmMyypb>y>At?T`2djpEEz&iDTQ(()*A2CQ zjZ`k)7-#c~DE}j`Qq6Nyo-^l5=b*7wJ&?48#^j0I9E(q z%hI_#w}n|I<6m}-esB}i&=d2j5DX9QFfEDyHFPWe1@VW0MPXT~dtNNxkIO#I4r+v` zxl?LyI=WPhAcnQidPd5S|2)>ea$J-&dFQuN!=b$G2HTm3@}rB0)ALPlZ-G=MhGjp! z;&TfPW<~EG$@`Unu&3=@kw&z^!(14%*g2%^`*X8|$WLNKNP1>SpKJHEA=|^QCPu3R zy8eoHXD>rZ@Lxs-P0tcWX{RhJ?^-IuSTUYdORgP@0p2@E-J7PYd zeip}FC6}XeP(NQSI;M8C7d2??Ol~r2)wgUKJe41_C~VJ7iy+$W_#O3oC(iP?bi~2c zBL2aS`-3Ne(65E`#Po0Y_kM;9#Yc$wIXy%tAF0;aIX^r_eAbyK5sQK0=4d>d0T)uIF$j2MbT5k*=hJj1&3SLLRyGeN{yqV{`J>|VCh1hl-V9CPvPpI zSf@zQaiPd0H#eHywX`~JO-)z^?SuE)#PFw3;f zq46!3JK|lx#daoe;nuZXPh^a~zq{}~zRm8y-n`1NUy^7>I7!d8QNde#RTG|Jkjh5T zNP%yPm(8m3Pu(}C0ra_OIx4qzVYE(qgpb|St7vlK?xyC1{Drz;QgHA@Nt~z2j$%rq z$XsQ+i~7WlB};34)lJB%5VERs7d>TP>MRLw@=!Ebh@85Y_q=r?knYvhsA)3Y#Y!7{ zm_Sr$qfz^;VaQ$86&rhJ>9b~=?SaV1-!yN_*%_Wl6}?YZfR1HQ)wy1%buDJLt)fv; znWDvWY}2NwGbr-mv*R4*VAXiE3s23;2gLy)dXC4jmXcB+dA<$RRg-<$l>S~NMxnfX zDQevcgYt5R$K!i5y)fO?@U^S=vdkGRUHYIO6{bc4?Y4;3d|`H|%T;Z}FM=?+>*62V z$(<&*rAO-Rdm>$LLC`reCM+3(bho*FzjKNdo#)^(u6&CIgm*)vpOOIAZw z>f7+I2nsI|Tjyo{5qQmurQr0;H#qnlC;E17>sR_PR{1*iH`^5x#p?09rnxPdWq8Tu z&pjq`c1-i{SMH)vIkm?JT-DcBV;AJq?eSg;A2Ib}-xqv$Q)Ynt`fb-)THLbA?_5oz zmLTk%{`{6=A*PXD~y_w4RlY(zK!Jv50ptieIOW+`QrYwRN4R% zbYH;_@ssYom$uIcqG_a?w2qrAe z>Ul0bemgMB_J_457iS~@l9)>Mc5O~JggYeSbew%jQZ3^)1d zqNo;k$v1Majn`Kh4-@Y;w=_^XX*=Ueh@;{)H>{(7@5g;^u+lp92DAPvjv|X53&TWm zykIB9oud~5*K&OasMR!J51$ zGUI2l=}qpcJIqAiOEQ#;${WarjM}VP?>_ zGbk4#)E%rV6b6>OM1xByd@W>#2Ya9CpXNITl)b|5*OC#pf3RDo$&P~WpE1iz_Dl+4 zi-{ZD(TbGR& zwRNG7dds=N7CAII*$G3TBJAZJgkBb$@80`F4$^SnLVcj&ZSQD2;IAV<-^>={ZcjIl zNIM?kIb>gs6o^T5zo9t89vG}UW%#K(Q(viJ-S^1r?u3p{%-fi~z+s<|{d+1s+?U(p zIPtk}JdR_-xCd$478wd_MQaRA9zJz4pP^jz4ObBtFVM;8Q7{YXuUQ;Yg&QKWp4J?+5PY!^Zlb>OdfyXd=JLdvvxNS^ zY|*-!@`)KU5!%nL#2t~yr<-~mahQY2{vTFEr5^nKOg4cboagvslY>~(T#LfID6V7y zoptYJT$QExLwx;-qTI0TVCj0BTBmF-ONHO>80;Sl#?Ci{-==-xjG;j3J7~DmFL{h! zg!cMgZ+kg$q?gEOL0!sSr*YTQh++?(dl5QUi#UqbybTX0x?SNLRb*nf7Z|fI;Jtc; z^=dgsZvv0;k~R2!5Z^lO1J*vJ5Qp5cyYA}=1j%-PFO44`CO9FuF#R^^qk~HAbOu~A z+RFZhqwAy~?T}WJIBo`h*Tfe!zn5@2%1oj7xzRW%@1R;$6v0EgnoP5*N+NigGkp-l z^(2mmsw$*H*8F%gqxq3mNl<#Do*?Igkm@!D9K_mKb)22&i(=lsglr#6)`n@W*`uew zJ&u2K;82jRbcplE&<~Z4j%qHyU1nmaR^a1P-)=A_BZ*0ua(8uc;7|@Md%|9xpXQzo zP9gR4cY<)o{@k>wqf+p;==oZYc6F>{F6HaOG8?9-HT+&EJ8* z;?-FhV4HQ-Tk>|;lVk7ozPA095YrGqj;gnEt9d}76(QQ^L={nkiFQSfRd0F_M16Im za`CoMJmWRvIGdU=Nz>YBe`5*?-uaZ$=}xA|;RE^(qmPt>ZB0W)^q5u#&n(EJ6gV1` z!h(bMKYlPV|IjFdt#Kutl-1TIs*v;>EJ5)p%qzUK+xX}JYdV#&W zyPJuTaTaI}AiN$029JbaAKI`=Vpf*4&qZVBp=F7Tn>gB{li!IZZju-A>%jGmc!3&2 zU)Z=yPu@;O;W4SZY~t@9**nJfM>liKm@v?(`Tm1}?jc_6`PACC7-j~OG^~$>{8{Pf zZba#c%6;ULPdIbkb+Hq9we7!lv9qhAH)Bp*rz@oGFel(YE@JR8|Ah76J_m;XWIBmm zv_6zm6Xnqq|Nj0Koj2o|peAyDGjodOA#EIav_XelF#SE@(8?^`DOUA!R-Gnn>|< zq|4g9ET*#1mXc(R3IDWw=LZqhgczR&ceTOlFAN ze8n}9ZC0){Y>`=afCyz39%|>ItMRzk6eKXvU1`Fat)%T&*oYk?(6tT#3GilmQ_0S> z^w+88qna^i!g-C0;6*W)&+k|}lbl+Y`VSV+0 zUitI$(L*7R7yS*sIVH#Es-0|%Lo#r_;-Ljak&w4#jlRG$XqF}+Xi9lO%#9f{xUH2# zzgE`ut+JA&VnW`|?g`4RTerY%`pqk(1zxd9KOG7*20Ou?FVHj&{$1(C3(*%Za6lZt za>@#6N&HiA3EG#g;ML~3$+fQb8T#u#O!`v`9}%6U2a=iOT~qXT7kdM zg<$VRCcg@ ze(S9=O9G>Bn}&(yibExh?(?&NsduD=PjiJn?PWw8B`0QZIFXrKa=KZTBGSpwl4ny0 z8MvizoQ!c4)Nmeuy_-20(mdBPXESTVZ_EEU&tA7gpqMWK1l~8W7@UG`xS!QI1>wi{ zgy=cznkVPE3OH4lQN=f}MVQ;Gdv9wWb6Wff=og;3yse{g`S+0ZkwIx8^=PYg;YF3I zib^ZeQvM4*9v+OgRK*!D1r|86@_L?fg3EuM61d(5EV`P1WSL4jh8U+ec*?uBb-`Qhe=GgjSu>9em%ZZI<4D$ zzsXd7PC+C}A$pG1>m{9MfWSG1T`UIHp{8=*a&nY{eM&_kOi*7(-HYYD#(o^)DOYNp zho#(QGg&4-rt3HNd@5Swj@;O4sQf@R?4(xwtakRuub!~JS1NZzHhv^%X1R68y>Va9 zdQac{K)*S%XMdja^hA0w@lIz1rp|a_ye09U$QTstx-r?OhY{C~CN9A}0x6$@5`;}{ z1hxU!BC;MbeJ$?oJj_o2YEV@=KCTgnL5kN$f|@#tl2G#9lYh9mT?I=<@dXv~r*n91 zj6&m&Sodm(kHtS+9!R0{}n_jf~76xY_bjyh&OIO%tLbAWtRL3|-s&>9VDK{W;%# zp{K6@{HV#o-@magDiwya$3#bqy?#v!+9##uz>nSrGK<0qZtg-c*xPMIfIvfi} zwjS|QU?ByIOHBuNPCURcI1=gWeUPieZaQ%P@7`W4sQM#4HLU=&5<>#!k=LXZ6^+3v z9yon-HoWTP7NkzqT+*^??KfR6PnMB~!`J%r2lMTb#y}vdb^H&j#gSTVcgH{s43KD6 ztI)1u?xJ12-E|N7Q>B6YyC+lRt4IHs&w+(k?cuL~ZK#9yb(o13&Bsbj@xfgbwhZY1 zSBVDQyO7q`rz0gL1?gw!nx9D958zL|eEG7YyL%q+IM*Uxp2oTEEwMYSyg=e#iVLc1 z*yW?CK?V~(1Bheb2dbFT^hG#5mqG(H=mD+-pA?;#*aPntC}+{GLGET?R)93Opn3L1 zIP1rckJ-wZAHRH&1RfM?-7#Itq4Z-NXTBlhiF?WmcU)_=Ir#X-1l{(tR(D-~0rH^) za9MqNG9v7N1S%;nKTLH*nrHNYR7-q@XueBWJz z3QRlQjnQJzw#^p$*!|}XmLo&oW>ly|l|F1k?<9=Sy0t`8jrFjct;FNFBK8x7_b&r{mi3w>K z`pW&jPB*bV`l*q7y1tTlLAK>Yd9iUX)wJ6>3(^4@9OGHXtw>M<^=>lquNHpd`Rn*d ztMWsdROAomZEXYsaXi-RMYQrEJ=w&@=&gaDvtLL>IcE48{tiTuG=bNCO~;Vrny zfn8@KHS&1zgVu9RO>*#un}a*62rM_266P% zUdOabN=lSd&Ej<{VZ9NSqeb5g(ucsm7gqVMiy&M635^r~FcHaxe0* z{@ckQ@Fy1@;P4x)gWD4ZM#i!UlEiE5=NojNN!Td(asDT+(2 zHjJQfhGMb;+yR73NI&uSWL%*D1r%zCdalC(aaFm+SQ9KXX=&-%G2`UL?98OKC)Qh) z^H`u?9z3y057xin3-F+!Usk721Goh~2?Yfjg4DGPnBANN>$rNQ#mbml8{+8h@iqauYRIRbjP|GWlRv&eJ) z*&l-)QeoEo^Ws-3hMXMvO3YFxKpIx!Mk)N)hQ&+-rkr(wVE!!{1TMe>x&Pz83YuWL z9sjAQYlYp3l*0%E`DmLSzIWc5>_n0)!T%eqnK(H)`vwM@V984Z0t$A}Woz#xs zO@0*kqL&5f=>Y=+FD2iTG_q7oHXUwGfbG*F>^sO%AA(++tx3LT&z`w}MKe2w{|z)O zo8uilB+oU1g711mqdyw#Am6@!zg02O1FT;~utY)fpkIUb7}7KXsmz6RFNZh5+V%(K z`%lQ(+i-PDTztU|x$wjnm=~9pK7ROsA`0sBgoK3R5)!z?#8NO1P@oW(POl(UOr|4Gw<9>q`$v^W2*Wn2Lah=6@{A- ze64h1K-j)~^QPx_qQEs16O)GZgC~Yv1aP?BXo$Keb-X{Q2(Y!?yw7a`@dk%b+V}78U>peQXB6Q{g2o&x zJj9xn2!tAVS79POtwBW#&RN)O-FBJ9#oy9!{JJYv9`f(BD;-P(r(oo3RUCO+$k+ed lRD_{R$N%TM!Pgt;gfz7GhEky2j42AdWF!>C3!drv{VzIpzSsZ& literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/Average CC Spending.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/Average CC Spending.png new file mode 100644 index 0000000000000000000000000000000000000000..3b4d03b95a8854a67c3a377b7a1a6d7650e2f4b1 GIT binary patch literal 20641 zcmd_SWmHvR)GmsFC?XiBD5Vk-Qqoc)B}htl2}pNH3kpgq2uP=NDBXw%Nav;-$xR9y zWK(x8{LVSwxaXdG&yRb~k9!@1u^q7XT5rsE&SyUJnd`m0ti&b!+xR#*IF}@!iay7| zIpczZb871RIrz=)&n`*$;B^pFb5OK4c5v3WGs2P4cd)UrcCautxZ`AGXK!k4#m>yZ z{P4k@mktg#_K#RtEdT2T%+_`$ER4Q0YH*VaHc!>a z#I24yyN_Y?k2iOB({~aEzDD{#AhmACZ_6c_xtuQYzr4KMKQZCizke@(>iYHTS%rnYD=;y*OTeqGdGam6 z^p~fR3&s8?pW)+!hkW~naQzwNGcalD6ny-@{&m8lGk5F+imcWz2rZ=JzSVz<4DzwT z*?$xD{ogZ)|G_fF=T zdu2R65$-x6a}i(8{wmzyyXy}wpEA!w*NBLSth6*y=BQ`SA|LbwTxSe%8QZNp_VC!P znpBpSmM%|0p7&Vkyk@<*g@ux^aQ!dL!GSv`7Z=6O=U`Iq?Alr#Rh?HxC(adh7A zZj}0PdmXtetE!ssu8sfMbJwVKuYe`sxAU^ID;yaeg}-D}Rz8Y%98lM&u=_IK5qmTL zDe`--GN<1R215e)Jk4V?Co0Bx?rAG#X~LYi^!D z_YQo6tB6&*_cUvuvN*BCuGMw~lZ3F>9LZxZeM ze15P}BTlR79M%85KmGsYLFZ{F#EA>4Pxf}=*fn#r4>i*eh)IabZA+h{8!+PLyA2DY zcN?GLo|J!cj`iUhRbHN{Dl3P3Y=iMHN&@*VXUi%sc>@oZ|YWk!y6Cb z%PDxcL|3L8DrG$mxg!d1`9+Ry2>#L9$BjRK#di8FMt;3gN>OEcLNo$@U*8R<|;)Rv$Sqg+{{E`y{7)+%quVf!sR zEnLsaEWg2;UsGD5uH*GssLC__`KvMswl1RjIg{on*OXa_A6=pctM}e~ z>*H^m(S;r~*VI&syHddZCtPk69l1ce)XHvGQd6Pom2V|vS%CP1pqs?}L44~fWi4o; zmz(Vu9umwJ*X|6{EM*#Xf{BIq`ygEUpXN*Z6)n<-x1bN ze=%lwPb$FCY|r0~bLwK;&MsVw)BdEsp}f#iw*c#Ysw4LEjndtBj>9D{bY55D`EAcg z1ml0BK*BsgjE3^(>VsLo)iP*}?!Uo!;P=fsn!YM6<#0kbR37Sku)tM%xv)W2E9<*i z>8R9-Yl=pE9p>vH^X%d5%8}7Y%849VMO`;{b`h}hBN%3G*pM*&vAE)Gmf;^yu7++- z`#&$(32MH6dz}in59jhGEagp~kl%s0P|%p#5%*69Bm2#&t`te65z%N|dslRutC{>Z248gXO&xk}1tKN&3jvihsA zyM&LClOhU#RuXxgWH!nl6BkcsNYGik&p~g?tgY}dHAW?rYi;!*A0Z6Z=E)C@4V40& zJbK0S%-mdQ2uf2|c8~u=)%6G6V&^a)co6SA@hUqz8{dR1NW^i~<2L>q4jR7t6*{WU z2eOI^u5l_Jy=e*ccZ+7>ZaAqBvu>V0>##fSjE+#%QBYQnh-A`q5`A5@lped?azAk~ zHB_+Ixps?u+`da-I>6V~OyXGq8J9@ot=WvJVFHoC_Rc7w%e~KHW7|WJ9SqVK!k@rm z(8?+*>0x14E3}xI)C)x!RdRV&*d!$-siO9=*rrBefuOv2rW%Hppr|&sTH}i*)RiS) z`873TUAH9-%Z6>?M&1gxZ_sZ^NlBIEQV&SLg#R2f#t$f6+|13oM{|QSx58H-q%}z;qQe@oGD?%iYc0bYm zp_VOc=Ze*OxDd(hvOadAxv!%Rt1JADL)7 zSgX&fNfY&V^M=MU<>_8HAt~4tD;(Vl0rJDJw3+j9^PdxMXS|&o#+D~*Qlgxr$&oyW zhX9wz&`Qpv&LED z;#mDfzY5&2G!yQA#>+3Vkyz7&2eGN&nlGZ?&GnBi}yp^gwc4Y0sko;vyA7OU~i{&OYU1To}D zI8q4m@n^es-mkx#_wpus{YWEjH2Dj6m*RSouI{nS7uR$C?IGZ!yy@mx`EXJs?7NcO zUnkL~iydLB>Qo>cBzoDF)^2W}^O)PjU^^^L80ec!opKfbv{%;LKZuLHLF{)Id5n1A z75<>;8gh@Y+;8=*Jz5W$H0%EMl37|V4|IeUsP5uWy@IPqG+|q!1>z4OFw*gI6-tzb zEEEQi9nL(nS4Q>c74X-Fgu&i;vo#XSAa^^2-C&`5Lc~Lv_bkH*9i^L)!lKPWAY{~dvC%mk8OsDJr3Dv3WsHNEAY>XU^8oa|Cf9?mDo$QL;l%iaoD;mT1ukCC;$$!m+l)e-vO9e|VreLF_Cjk^gd(uPs?X>;Z)NU1i7;XUzy1-lviW+_^I5Idr#6fOMwCVT@7ZKMR@rG>Z52}o zEX)<)uMjR+79>M1L(uuoPt5;D8xSBheW;JK5?5?;-0#nQ0Hp85ImPBD#uluImg(e} zDb#T%6~wVC5R%dWJh>Bw%vNUnOn~jkC)c3h$KtauoTPugXCn}~Dc$niAV{&x+M;`l z^tMAo_304c-f-UCfya#3=AW9QZ7$45bC3k4@R=B71AIYXPs(Vr7`xrx3S4;aXXd=F zwtWYuMu}O3PyJMe5DAay9g^PKHDMW6TkKugF%w#&#j#$8yu8)!#O%=yB*J?u+*Yoy zLg!a)x3hP>>`jxb+?{YMF>DU8S@01ncB}q_Ct~sSsy;zOw~5K`<)DKXc@rbKp`?}n z+>ZhYeEE0Sv+dEzBNb9^D<%577bYqooB z=0)Bh_h>MtqpG)bB91%j-;oYj`vo@v)4ol?!Krjpm`jjJ>d1?^i@JY(oK}XCW36k| zS!%Y!?CkAnB)KPCQjz?8!26wr%(!o>WXQ+yCR%bYrsq!QWZv5^RaWdFd4;Qyd6A%V z)7c^_h;CCP;>sJfN0j-!*o2iA-(iGB32`))o0M zGT42Jx|*}V&6VlqT~Y>LneDNa*ocXZMGXyQzJ7hma->)i9u?N#*Oz*9bi{Vy-7iek zB^91~_4s5v(-@ayjB$yIdw*tZSInmPo z`$IjqQ@{F)yg=5m<3nLMor}uHgsFiq5MXB`jXlPO@}i~daKYQFhG=eBRm|NOw`*f^ zoql`MVYOs1M447iRB_k4@T%eO;!xKj6;W^d)`#1+hGjYvV`-An7Xl!!rAN|(rth|1 z>~7el49pyhm%5{)qw8X_e@OXpw}QY_!7BQ;lDdk|Fq=&bxJ%v7@fpn%**)2EJ4@JC zxW*F5p*q#f#%LHQwXu{|0Sg+rNCs?FngID+_ z_d;A7(%xRY$-vI8C?|C2P+oM`htrWrD$Fi?Sg$dg49;;vd`AB3yEQdMsFOh7 zO?Pp^yr3pMEseV7;7=O^1H*F}nP5+BU!or$={+^YLGRvKZ8+NF8BZuSKe zBlSu$@KyHU>?wrab6v051!j*vqc7|4Uza?!Z}-NAFDGlb;av~=6#uk7@W#TYFN{?6 zU%cG1qy)XXPbR5g-hZFida_m_npv5Rm3b2>jK z-Ji(mJI))=v(}O~Lol3oCP%i9^Hv9UPHCwM;L)&g!D>@KeG+1RGUaDoNswxoUSKXt z)gzGUlL+TtYnwt>N% zbd({2?!7bFv#(U|>^RB9a>MkFW*qIW6WJ4}i9sl!rssQ)QSD(6sL$hLVL-{Ltasy8J#tWytQ`Ib z8<5hJnf_A8rXCk;q_?~K19SP*>5fDpUHkd=3(j1kN%IN5xS?07Upk>H8e=|?rBWW+ z#`@HM_-7_fnfMdON9)JSmFWCFa_6zTl4ceb{U}vk@=mRH@=O9c6=Ymrem?35Ieo2> zXBF$;ma#bNXH~Op8~)$EZx||&USdATKu<3j#$nn^T~b==$4PQe5w@Z5+W1O2zP13P z-1Tc=+uCuzx3pZWJ?h@l)y2+nz@+7Rocro#2M9w$! z$8xo*C)n6KlXaQXMF`sy%E8K-giytZQ48)?biIY+5Y&uTtz&sy-|!Bcg~Mk50|Bf` z@XqeuNp7k43U(Uu-K2-??3{*81czP62cbwdLU}NSH{I!XzOQ#S;^#R=o-rX$r)+Gs z=iy*1%2)y%^Vezx@^HPPVFwIK6}_BOpki!nT+V*?Ny)a2=;;t(fE2hpS^5>%*Lzeu znV%yW46+{&(B)Jv;7fNWz3Lu5e8^$cN-PuoP%Jt++I8wRUK0c5y{E7;Gg?kGD`)Y6u)`G#Ex) zxiT|#j?v<~Z(U>rNh)6_3yM)QrbJ&Z<78i847lrA8410GMr}%3TKsmJl9KNeJh7&S z^W1e8+;~Jo-H-nGgmbA|lfI>le?=PJ6pF z`1iL=#P{TOzkjGcx`TYlmf3%;!l4lOgNrcyvgm3vLcsSqNy^AFq)1&df!cW$W z*}?}NLE*U8waWb{>EGZM%5kl?<~yXMq#n&Mvau;7y8mfWGZH<^<0AS*)uqKj>%mnvB&YG7BXh25czlOdh4=EbhU>Wq;#v9JHY+FMAp4uLo&6O?OV|SL zY{!l`cbaA}SHOFEw^AQ1lKth#tI-i(XJr81gi=T|AAIcL?r4c|GqS(L_!P40bi~hN zn{(Plxzy?xrMsRD+%%qBIv!Y4F&y;%H(XyIf5idz#i%aIw5jPg2ZwWt)RM=W%Y@%EDjjU#a53~`$!#9VpZv83fooI7k4f&+Hkl4KDi&?)So%*)^cbIbm3I>L z4fN({3Z(l`8CPtrTcgsd z#pdGPrAsH%e)p1?KQ8Q)?&BIAA=pc){LcvpzlP~X^P$$aVv+Rsj)B64jnoK#18MG8 zUs~C>Kx}1*DWXQusN>qI(GxFqB@mXy&IV5g)(|!J-W0pCO?KE-RYE0U4a+k16Xqi| z;)-Wfc1tSQKAIf&#zs72dg}tw^7LTNiJ4#iNaw;s1H1F3x#~sPH+YOT9HCnG0nx*? zhMH`vB~E1DAOB3An*LObaUIsf%|J~u#ihAKi4fHmj-SM>EB-$I;qydiQNs&{hvc$3 z#V%26m6_7k7S^c!67qkurGwcPhX^JsUA!M_AINc+S6m1?%Z2OvkIoV$fH`O| z^1Zw#Z4l>l*f6Jv&`By*Rwvxq?mZd8*ZGfX7ZjVsl$Dh=N-d%x1QEKmuM8I< zb)it9Beg+o=lI&K`1Lo8gg=tnB zmc;_M;M+F^TwGkL!L6+=z=kgE%|b_iXR#|LLZtaTJRLsumnEq6q{sG$vz96G7e8|I z96-36>I(|2a0Fme4Am{nsNabs6Ej8-x zsCAt-61a17l@Nb?Z}x0|DMm7^kmueh!zs-uX_ef*&gliP!NhwOxYkDpd)fK<18d_| zb6b1G?t6AjI@N!_Hd_GRbsn?zSIO7P%FWHS5fdiqFD494`+APZ@Gcb+Xdj@^%1l_j zoBoM__{p9P;U_dqcLS@L-NsU<1vS6QX+Kg(Lz4H`s^l0|^FL90?2k@HHqZ8826YS6 zi;T$?aM(OirLTz5#f%eBe!)-q3GRTA8%$5D@nn3>Gv^lqSu~2D2Hs$Lv{H&k;iC8Z zPYkE|kG-Aq2zd)o)N;qsT(!mAtw zbTVjX=j?{rlT-S=9GuRD980vKq7z&4lv-6XX)_iT~j zomQGg9!D!vKS8U-|LSI&aN!XCnv#Ev+22==l&tsN>r9NxQp?Z=GMtMKL?YkI;apu9 z9-qjNe;PEUul3G$#Ifg-v~roNxRW#F69|P9_raI%R+!Qr4^4FC_o0P%Ka zX$6%OP4m(cx?gla=)5yPo-#@pcX{6s?r!V-WwW*A8Tg8QDkg%}!PVZH zwA7P;eBiPeR8JycbtGrrofQr0ZFjkz*0dZSZy6VeO#K{8{h^)cY4eTCcOln@0N0Na zN()`Sg$%3bH4H1ua*M9XR8dDNcUZw&Ar?5V3-oNRZg{E4(;-T-GH~WmM7*H>Wz60l zaylqRp9Gkf$VXUrpzGUCB9lHu$;|%JSIF>{kdhU3*~Cas`W@sB-)HDt{wkfR^@h43 zoy)tYP$+tA81WSbRh8)2kugB=y$w z6c6svbbg86qsM-=sypX?>Ldq>Q-K6aRR;Z<>MBXS@7p-d$h*3CGFt`6qG2Yv;74Y& zO)HVl#_fZpP-p&7T1d_&g#Yh#|o8-a8cuXC_`TCch^BFnfLF zg!TSz3U_8BAJcn#gY`i-Q6IQm$(B2B{E&lRNbNr0R zza=q(Nh!+YNZ2x0LGlk~^`--Aq4;mph@2chlY?)W`UH4Ly2KLj5Q(3@6Y(7jI9f4W zcO}6G0;V}RlT)9d0Pnq-Q;JH3y)|xrcOJl?xzpJ=ANyzQ#U)u1vCF&W!famir*Izs zhAOZGY5|jzK4!gKC^&?d#fd*QMt0NAlY zhZ48yY^%-Bh!dDfL#}|@AdO^r(XjBf9(`Ax!Y~7}lfAfi8<$8zd3^a}o4%sHMjY$~ z+w|9ABx!`orrFXh4g_3%mxM*l{8v@cA>{KCy)4lAKq|b!_@(8glk@g)bCfS6yRtF0 zWjMD^#NoX?A4e6dG89Q#W-%u~aq10>;Ve|$p&UOjd6xn9gxQNV4O7K;g7IvAfU!Nn zyuPGD%jV-x_bHw@RZ{(eMp=%?(H%Sptlqz%Vtgf=i0tEcVj0mK`?iPuXbd{s&k9Zf z6x%N2Q-sKm_cC$=Gz*Yvm6C`2+}wQh`pgsn-OIvo?;o8vLZ#TRy(qf{j!s&i#IKWH zMinWR=Z^l1Z3rBm~ld%OsSoG(05k0NQaf+UIAd9i<7iwKF zS9N{rU$hZ~K;l0r7jUFBnzV?B- zi1d5GjM%QcCm>YpMp?ve5U93gMrCY{*{<&gVoiQLDEqTFj5GsT2QrEq#${2 z4>;ho*J`2ZaO<=8sM&wt<%K}dUtCy^Z^J=YC8H~l@f7XkZ1(Iw3Z)_Mef+QRY5Ije z{rr zvC5r?i^(EhG@Bw1p3RVp(e{J1;>2DL0sAL(p z-IJq&RQIrL=NS8j^l*9ZKI?p-WS6U0=kBinl22Aa`HdvYeOD;fDSe`_1_zTuT~1y( zxAGnkOkgSZ?#Y4o_Q5mNv=2QI*(`*fu}QHKC{Vj#dYC{>OQWw7!0Fg3HW>afd#c>44XAK!Tx;j_wlj;K|k__?EsY*~%Yqaq)ur(9=LA=~*3GS+z8rdx%>pKrg6^d-#&KE>t_m=_jnB2{dx83@4e zB=>q}pl_}c930F*M@LeTkeFD|)YKI2dQ!TdsD2g0ZJjVOG9s%g`tq;0y=073{TbO7 z)h?#zQgMnzb+vs6e!UYQ_Op9jFYmgi%E%0B8{%&g5HY_F;>b#UZcmk;AL01?H!bK>% zm$>a(fyjVKw^j>Oe}sdh)6@iiPmhdGNWkdAUCKn9wUyF^28+>oQ?99w=&>3VzFse$02_9^S%q=XSD;5$EmM%FUAi$=vUSZ|s zk}@l`j3J)PRB^>#?t6p?Ceq38{f}hevJu&|`z93KO-~97JKxU`1!*O~Fp*U7)~V)t z!kF(%;PkfT0$VYdNu}j7%9S2izmuZEyL(q4$M|75T1(MbwZiZ;7~Fy$ebgtDC5S?Y z3#6#!<=vA5CVB;5hd9StKMUhv7i#P$^Nuj0F2}3_Hz|i&b=5aaMNaHv;-o3DEI{Q_A&zDS zk4STIrX9A_uW{DVDHBx}E9VLLo~-^2iTc3jv7~;3lef+x*SsjYh21sp`Y=e@FLbPb zQIQj(wVJ|4ihNyH0Vq0h>&`Si1-=&{zjO-BdfF)0*^x;4l@%6YWTZd!G3!q(pB@3? z#f<0gqmLpqQPZ0z_&|*qmj&N4e?5#kUg7(d3*Xgjhb*xzj_fFQp0xGajc-1}>1L+^ z|AhM7e9Oh{fE07p-?PC=rL=yE6FuBYvCA7C$UgSW7(kZlyAPd7Z+M{(G;1ADr}$0`0HS%YUEb8#=g4Z0mecXlXG8*^ zb{?0d)xG`Hg7?zQIN{-+`HDY#zLi^Lq;nX&lj7S0AD^2>T!YSStZBETd(KKju{tSH z$Jq~lwUjVvsp2i83d1pdTp#!_mb6j{v{`4%AZvZxzrPZsbuw)1i^Me}6G#qhZf|IM z5?^@xWJGK7OJKS&&_dr&0skmkqf>W;4mNA7BF9E`$%N~Z7&n7gy%OMaQw)H5f6s!U z?{&SnJ+CO~Fq7_rW6dhf_iTiRhenDgBfJMI8(@*Y9!cF{0M}_D=2w@k)!8x=EWZ5@@w-_sUk%XiHXdCRXIy}+2=u4pLLU<>6{v0AfK@e%nnuD$q|*0DE0R;ZdXkrFzH4Z8B|@k9lJ+5Cuk$ zpU+L)fz{=1a6AF_o3>|EWv3_uFaHgmoWXi{dW?1F6(s6{Yr@f20wJawb8HIo1AL9n_(<+xj>h(o zCMR|;meY>cB1Z9ZioKNo#Y7>JPYq2EEg(hm^D(g{-C2oB#5g}zqHmLuS67KfBnUOW zBG|9_it8wc#Y1g!SCKb5F2Do3`x6U%qU zjHZdlakJk72p7$;e$;v&)P^uW-5f{8*Lr}#3ZwS#kk{83vzcytrz)%w7e_1z6?{V6 zt{GU7{-Ej?H067lr=B8`K{f%2cn?9z=ZS*_l_7$wR+LAs_HH>(ZcltGy2H8ic={RK zC$6IY6wdd|4b8f@P{kS<>;9tI#R&9_w=KiOs(j;{7a-e;&Cq>JCO5&~Jtm2lrsvlNt;#_^4*=_> znXKVualCVVmMEQiK=8B;pKmoE!1JkGKyqHn2CNHd! zdqb9-+3liKFOM@=U!S*+iSYiud-hmgR$WbIJ9r&v>fjJyQSaLd!{j}q%>nI;wS_qf zZc=P<5yF z-r@_AAkP}<8_uwl5g3^m%i%69Yc+OHd3CMNL0znrIW{u&heLY&85|oB)&y>1&$yaM z#NOy?4ew~0$HlqlKW>}}B14*67l4Hr85GFO_7DKrCn2O(B7^(@?ng3z_CH|}@x=B+ zTg`udod@s6h@a5t{xwI@qt=@_zG*EQ=U$XPNz8|!TC=8=)UK(lnQXbV#jT@kc$3MU18!;?~uolKx6CM#bQ0-n>8 zrfz(M6bw4)JLI7Th{&{4vCM~~ZOYi`YzE-+U#bXar_a&0%<=q*6Bt-Mb>iplLUTY= zn||NibzX>M-fU51XsFZOdQ|p61ke{Ep93OcX}ERzm`mk1t*MHB0FueG%UWK`o+UrF zdGJXR=et_cl=@E~g}sLQGZ7IB*#bgbd}d&z7mrf@y%=UXJkr-w04bLFGsQA4lrueB zQ!-Fih&Btl?PiJF;1JGU!0oz+IOhc6I;%KcJuoy9Za9F5TQ&KKwr9Wp67&oRg9kMu zti4Q?&ge*r`TXyt<>6NnWK{qqsZ(GSMG+W=r-3L~L}WI$Ev99r;yQ)KziDzN(Syyw z<7PvX1(bD#+DNIhlc@~}O-PWL(K^7K$9X4xaLM=-CjL-EvoG0=Ilg^*9)}g**2=$= zL2^*$qOrNNTcXa`P|~EeS^x3=xN&1u=^`jQL9vhkS1i=!fSCMAeUbM91KNnB*U^3p zNjtA(@KEXOYH^7n`vhGA{eiK!OO|In00R5cQa3Md6>T}J#__}c#E@Ud@s<;-543r$ z_q5CMWj83a%z&B$pnS&wK>LkPY39I~ujy(fBN1#r_>u;8jTs61G2kYI@5-j_r;^@zp!AOW23pHrvAzUo$Mr^-LA#Ecoh zXdd^s$Ob4lJrBAe+wmMUuW%e*O4y$Sc-1m4M$XPGdc0O0D0K|mruMcF{|#?^N$b4{ zI5`>6YO%XV4T4{Mig|z{dEEbyK%}DO8 zexN@*w@=|TF+rV$o>wv^EIbV`vzhL$_e8;JHypN+a_8fx(?z$QD~MNvw2gy_TXL=f zve>8co@TjmPNScV3D1g9HRcZTIZRdQ0z_IS-wxHw>1pX(9_Wq&MUe0(b4PH1!ll$ zAX-p*o+|?7JkTcrf|adG)_eK~&j-YhxAD&+TLj(}vSz})HPx=E4?Da2aGaDK10|5D z@8S|ak~)HUUSK1nsU&Ze3sweE=GJ`^2KF9-KM@q`Dh5F!R{pD>N!#OAD$9HFZMXJ( zsi@v{sSHr6;Ox7f!t5WwP5Rf#k810>GMWw>q7Lg*4}XV^>XXvDZ~6yarofg|)yN@3 zEhkT%(DILecIwR;T$UdzON)J5q@>#sMfVx*^EN^H>8*GfU1)CSltOEAKV*!HhgcpY zEkMrCQA7GPQGh)>9O)TLE!8Oq=@FKd0vYWmo+v11N(DP-u`*ee|7_&>wCKdZHqT-- z|1wq0P@PLQonVeO)HCuK9dQ`TWu-cnjVStbUw>&%femQN$j(odJL9GNChEvEDsB4V z=Z{k=;whT9HuKL!5xL9RFbdRvX+IO?o7`QVz$|qN_ue%aG=E{b2COd>ayfy|yh8w$ zeP{<8{JH&?%2Ry@&u4jYD{Gv+dLYlayCC89-AmXrfAIVy(0-@y4qJvbaPh}1d>#En zGAnPlvhhwAm^#UC4RfpAyNhGJFk%s6mUVEcIk-zsZ;d;_$5Kyljt%_g5ed7ApPu52C^Hpy(X^o~>2NfwFu>FxmbXC+HIX z1P@4b&;$1c`{(_v1f2RTu9F)voCE%vvT5G|)$^Org})h!s=tZOfh0!Jtw7F_q5xDl zh;k>rW*;aWiG*t)NZ5Kj-6rM0$W0?24z>KdyeeGjZl}|erh-L$MNWCFwn!-tI4%oC zwGUkHvp*42rMzn}R#Y))zta2=`iP+hhZ^C_g!8T8R&BOQuCt(8aX(4O$~2Ng>p-e# zhLfIA!AQL!)!#_{0wl1`LwkWZvO+L;b{^vHK`+IuU1!Hdlfkb3ndoZ>gTvb5LV5kk zHXGsaqS14e8U0-hoF?@TNKy^es%)!O6ewE(Qq2A`jB^sf&9ZHk3se*~%f;`Vfi{>N zpMIX}X^r%powo+)6Yp=W6Z`+9>XqMU`Z&TBy0$ki0cmPpqLy2eEs+ecCM0seb0HZV zdte`7)%YwXXXo)!j_KA*XscP~!`rqM8Pt!he)=4|7BnwRZygZEEk#AU{2F}Ce$+do z72x=7^P&w0akcFoV*I5gM>kA^vNA$Ywy|{SYe2Wp*EeU&L=fR{(Ve+>`>uHY{a?Kv zLwv}d6iV_tJcQ*EoY&V>44qiTWDlZ+meG$^{bsZXfn*J^=Oc!AIx#07=l0j_KzIDc zLSdV}p(|Z(sEn3dalaDhk!C5g6TXbjQLQEpYB>fuMh`LN;Q7mVAp1 z%G)CX4d#a<0y?YfaLy((cFi93uW#jak;>Ou|Hb+1nW*b4Qg2urIjYZB{kLL;YVg`v z$n;W%t?ZYdmA~!e&s~Y8bDQ%~CcDb}^Kk4}B{Vo}@GQTaE%G0UQm^_&0zJC7fc1eMU473WY>+ibN z=y=RA>h}0uBK?$*kUx32<_wZod=qL#l=BWkrz1cSX-WnnZ~T>TR;{a5&y^}ASe~h$ zycS$EO+(<%$uRbyLxeL4EvfwiQ;Mp`-LKn3%vNs81MRj6AouS zD=RB2J1eW_&s-a3eBD#EZhw6J$8}Tby#wJ@v)z}#sasmE^gwS!N$MBXFr-=6OGhc6 z#^gp^x0gGxhD}A`<9n!;cm{34*j_T`FO5~y33jVixH=f6P`mRH=$R~ah8Ag7UN$h0zibJiXL(ghSJI|UWBjcs z;N+9s+KY_|&rDwv=5!{?{L-957%GQiqJWCFKlzR0K>`sep0AS9)ow19Np1S!eS!zT z+5RpZ1riLXw8BvW$);cS!6G^mVL>8me1H?2C`epBq;>0RpC`AITl_Gb6N|1Qe)L^<}-OJE06(1j8JbwYUb-dEC**&OXS{~lR0Bs|mK7PECucp7*8tH+w9YT-7 zr*JYTjlZvS&5N z;1XIB%wq5mybBxZTGL>DPGDkM<^|}kz(Tank0dcTvCKM)hVB|h)>n~2a$=a*qc z{ePUN@C02vRD=T}Cp}ABB;}+e>sDxDb@2Gy8DYS_F zY|#7CQZ6H7;~4TYw9{LmR_;eVfn9=?n|uC)BYoSCBt8|VzT@lkXf9l*ORT%w@@lFr zz>K;>)66M=3WY+EZ`FRiUR_Ptoj<)#Mm zIt;72!yOy3MoFZW2bIE(kW=9sdlKA&$BT_7l;eL7Qb`lNUYsATuHV~Q$f>N{{r9gH__PInzK<R~C-^}Ms8%-a6l+zxXAFu$dL|~BwkQ@NRj8gI;_t8d^_s;mKY~=;VaSq* zf8+bFxzC?T1a`;lr-Qs%4Mr>+X8-fbAcOv;_vT6R`Jq{e$T&C~rbAVf$bX=M;vZh< ziZMfU;6_G9t{e4u9U;DK&vkVR0+}nH_NB`x!Yex{Uj4pOL{)zld`po@*MPFBwh_pi zzvbsMYdeoS#yoP&Zf$GBKx05G`31wpX@5!;_)@xDVm^!KX5eiyG7i40KNbfxt)a>p z3BMM!(=;*3fUc(JGBF&IQ97`G(KA@akwT-u)30%2XVu4`#Y!1`Iri%)h5Lpu(o_P*p;2yg_c+`uE(OHY zdAfBvuprPn@Ud;KH;m?4u|Xq#k)b}p@A-MN&N$w%w4Xmk;jJb)-@f(yRw8)@LUg3* ztahiQ0Jv1c+^Q-~q`qxcwaO(K);9NCN-CftnKk{uv+mrvbH8`@QInGe7p~Dlp-bQ4 zXm5d$iD~ugDB|EWtt!OA9NL)5kY;P&3oRR_ASTiOPnG5_mOX{c{CwG1F3VmY+>4;K zX4}rQ_IM_=*CO|#Xme1ac(}%`3|a~>++JJUF#>L-$e^+c3c6O*NT^=DdWH4(`ipn{ z#tjB;Zq=5SmdcgFw)T*>Yy-W$DPv<=lFwyjLo_rrq-EcvPFugkx!*p!xj158fbu$8 z@Pg%NS>Yj}VyQbQgnt~)Yg(WoJL_4e3$1Vc(5RmUafV({Fkwku;l=UMp~g3Zw@&L5 zdFko2pq*V>%1GqmyCMC8#E+nXmG4{#Sl_kCsHhAq7W)wmD+pG^&UU2<=@rSZ+0pP= zdZydUIj999+@NIW<1m|RjX+vSU^lksW389lbdL&$zp;w{+1iRoOcZ)(<^^%Vbhas& zHsgmH2wj5%0s|wWqmjlR^ZW{NXah=s%bN;|ib|{}1toiHJ@!9EL>SrKBLijReT)Aq zLGBQ&*%?qJAcqk~hrDzL1P_KQpgsNuwQ41J|IJ)m6nZ9*W&U_d;$vJK*>z&#m(3yM zVQJ8CCj#e(o%ec^6i5@`wFYM}ySt14&4Rfn^upumivO#FfNu5YiN^;EGO*^hpUH7P zHvgxp`+xHe$RSXxa>`3^U8e8&%qD^~7f~NBN(l9)hy}J^I;SUnaIhdW7*)GX19g4~ zo{NKZM{{wHfoEM3|p(&)e+bkGNcNvJ3iXSP#$km!Z@KzsfxpK zSxMV<>5B&V<^->!JvQuxQ#d^V@Zzv{k2FgydSK=f9{a-Z2ByB7b$`V?rZ4JtXDjC* z9eAYH)e2pL`zyZ;6Fhd*$6aQFv4`tk1@LYqaDGcjzYG8$%E&}q9B&Z?crzObZemx4 z(9vdSC3ZOnb~+9B;*CXUjzYoKqDDrt;lNo=RI3Bn1A$66*p`X5*CD2G*rK(irAO?h z_KTfR&oga*j&y*b%sM zh+c7d&7DycB{`;ZUHPNUi%3M0&8*g~p-_qNwBD)+&(BOV~gZ_$7$P zZn<94Ae}hbybyg7*UiS8CB_}MBO)V__dXo|4L#0;(}#2QrzggT)zl7w&>m%Y_x6&aC{ z8IryC{=ME#ov-`;-uM0Z-oN#D{2sqQ&f{?D`pnn+^?I)N14Vh6L!|Vi7=|6XcJ((U z4BJhB|CA5xhfkPQDfF!{-r}6N6*uI?55sZX(KBav{#DdrbMV*{+5vOi+9HviVf|IzZT4G zc#4HAaW!-mEK&5V)D;XxCB9NTgJBZE_($ElF$t>!aQWYYsmL&i$$#a?Q;Iil9!7*sXxhRrXZzVYnQ0`@J2ij1qxs&FKM`mGt0d3uTCa=laOQR!fY z=h0z$UR!Iu%F7#VWt(9+p;hHc` zXKJ=m{#?CCiu}uP)8>Tu&c%t&L@n=otQETpsLM4X1uTgHoN3Q;R93z{Q6PR`i(zQh zaq4bNzLkic3GQ|FqJaJ?dA zJx);cm22T|>&{!XmloR%`?PvjRb4O5IJA3hZIr|F4PQ_do$Pk%6%8BMs9sxN%qxo? zU7$%6tVnkoOU-NAsGMp}(X!6G~#pPgeJOFhCoq^e~}qw6{nKhMy=VOcy=6__Y| z2_8nQ+tTESF|${0$fen#CIcRo684|2(BZ7Q3vpQuVj_%sr^Tv{ z@#(qGRPt@~;j`*VkFv?%V6hx;C&01hJ!b;-Ue6vkj(VIRTVXg?cTvI8;Xy3-{!zgu z`ag`^b>n10D2m22Yx~a}tY&hvC@f>|@hWbJXjn*Den;s^CAPUdaQ4poM=HVT3Q?Pi z%J}NTvx4WD_ITo}#eX$uPorfvcMmdj-l((oJW3%v{BnA&cS~%%VCaSErj;DC$NbH9 z;}{Pm^`LYY@>k;PeU#-H`sGcQQPQ(xdRxL9?`BJ;Ja|P*&6E@64~a}v0Y>X?oeFt65<05LzypWH>)2SN5E0FV+^0awp?X}6 zxN~MWM_6B8BP;=8VvJ`*4(4Kf5=t>8t&ro=`gHk-KeJACNUzswbBwRsRLMmVRv!{( z_p?E-R70#(1DnY>dZ)}LjHqPx4^)2)yUf21t5<iI(!xG`zG^@+JPPX)XOGu2J<=GH(W8HI3ejnmk+?GsC>KT%9phx|VQ{ zp&(tXf7pS+)T<9i*Hj>}d5|E%Q?U{*>b7`8rp$9gY5I#nAU7>Z4SQNu2(wyxZiiWt zZtCj5O1oa_-P&-|7kAeE#XT8327)f~Q0VYiHr~46FCA%-d96^VBY3xMja1Y{`tr6v z`wbt&TF-v_pdq_)OMElF+nU^bhILU%)4F6KQz>kek)mH_^JdpRmQv{%V*;P7Ti1*+ zm0o9r_|rGCPkHo~H7Zu}Z386b2;9k@Tr&sVFFyaG^5zy=!$mtD(tK`zuXl-FhOFvU#k+{OVYGVrN9;Ms>@S?O`Q`*s+cr z^N0v4aVuRVa_JUkHMO;B@y*9p7u#?DVPEuGaF$N3rEI3^ghuTU-1M$uR~16qr{4G^ z&vn_NUJ6Fx*NkKlO)%yb=IJXptezT~hKK~etbRNlujA8~5|Hl3fD36BN|u>;dZ{0G z-h1{JG-uSZt6dUjSVu-jcH6eNlAl%6b-A0Y7Fa}6k#Q`qD4@Ts$|c@*^s;sdlUi5x ztqHbhd!-GgDOAY<0 zCD(GQKB?QPXrgJ7l)u4iFifq<{BVqya^Re&A$y1yl}d<@Y6=reP~W-DD4w$QSxwe_ zujO*)CT0p)98RrGXW^|BF;%z_X81LfqO7n`O4Qf$**STJ17x~{Q)EJzOi3lW43dSZ zs`iQ623+ov=dij!vvewmh106eo_LV$_096(`(!*<$zJzIwF};(qm!=0U9;64|1&U7 zGtY`qI*2}u*1K{oP|LXzilH-2a5j%`#;ros!tnM+OS)%RZa{!rV}0aB-msKPMW{I( zo$fQ@2;AdB{G0%9>2iN|28Y;I{?^3GPz-bFTK81KN~|qGQ#r6xt+LH+dAiT^lUkP; zr|n-a!8ok8Jf9#KMJ7=XvOE*$^#eUCz@&nMXq*5)L=sB!PXv#gc=V|EvtXv@w zxUDEv+q4aSspi9 zce&~!^k3^4mx1aKUKQV3%}%2$F&>K=vF8=z)7OUMLX@<+49vrBsb1^6Q#lcz(DicZ%#wlPI5otT`G7Ezje{x+R-2vhWe=Vakn8mC3}Cuv;G z*~rPnc1JBVgY}>4IG)J{45N7bD_K}y$us~g(XmveWbRxuD^}WDTbEADM*)y|(0RvU zqJ!VkBX@N)B{4OV$#c06pLe}W$vmr0Kvw+evhdvVtJdZV~MGC z;nd8vP*+b|l5a!{^XH@%O%{&0IgEZz%7A%E&9TSQalax3N52diSZJ?Xlq|H8p;|Wi^y&)CiB>p6^=C?q?;#c0DOG^+@`8On_{DX*@N%OhR z58F(?BT3Z4UfTPpo1BD!eFzSI2(XV_9)SW2^`#;U`nK3jCd92Y! zl8f)YQ?JKGTQs~n{ zhq1FZU*9$o46ALLuCc`nV~X@NIHSVe2E0a=WRc?p@#FIgQULt3RH0~s|9gb& zzd_y_{Wqum#C@hbmx@McF?L24TKW$Uk6$28^XzImYuPyxkZ*uE7La=`Dt?m^=qSigdDpoDYx8A&Yb9M0hD~GYx zx=A5k&V@P?Nj#P81CPZo#<9i?FEl0snOwd-&gc)|G~)lo8tU-q>io!)784%eqQ^V3 zP2tBI@TG*K5)U>2rPp6~;B2MDsEtpyUgbJP>%=Vh)q77<8R1l=mpP#71DyD;Q!?*U zmd&$-N{Xwz;Zt=oe-)`MBv%!a=45(el&4N_`PsyRTVM`%Ie*gdEH8*y5^}lM8M*Q zOP5Nf;_dq1OaLNds(N_*sAGp|;ym3~v9<9hM9YQYasD>#qw?Y#^Y&icTDdnY^{TFN z1yvGxUNRhi5TC@A$4Zb5pggN-7{uQ+u{<*Xl(3F!n@E33Ic5;&T(r=t)fS;kmB>)R zwlSKLZp58o(RHtuTO-M;a&?z?f4HfC5ZP_{OEVQ2wLC>Wskt2-IVD@0Yo;f2Jk}PI zbh-Dpw$oL1M(h$uPE(7?dM%hI;M)~J!sqL`v3fVYkYC(XxL6nPZ&Rn=BLZ&=JB)_XTGRnkHcvVa z?fo;HNXsx=F;kLoQCWH>*5*d4kZMtU=HYct_+^F?8sIL>6a(5ot>i9vUr^HnU?o4 z-I_U5<;(%ICp%R3!f z@sYLpW`*Wl8;1vfk3ziH*5=Pz@lj_dxbE4?dn&G+Fbb3!w```qa*ool#EMd10+u)+HJ5_MfoWTd9@^_`Pn3Snx{ak?W?CNYXFu2THbMX>dXQT)`@LCCYJPvf z&(X)Vzde3ppBt=TZvL;ku?2)khP#WLpy9qZyJg_fAiDI?43m&T?*bME4Jl4iHRZ?{ zfe|x7&xnhsr*OGHFiX>t;9(kAig~Z1M=>rBSWW>R!Wc~R9XD<9?fv7OH)$Y3)gFue zHCu{?Uj=6FcwT?(KeY4tRLa(-Wj9^d*g0gXf*DWHa;ZPsd7F5xJgc3j0Fi=w=SxGH z%Z}d#Zol>ZIj0axh<~cP^CgNvi{1GWrF_Xh?09M2pik^P8LIvr2dCxbbOVLYD5qm} zX=*An3sc;U;0*J|uuSZ&6jhDX>v(4O>3153Fp~pl5*NG70dqbzhQ0NIhbL_V((9f0 zj__6r%$*-DPMyKl1BB8{c-GziTo~VW0k>)x?<_)X0vSdRs_ZENi}s8iH>TdDJ621L zT3-sgN=;2&%|9U$ll)jIKi{>BBo@*0y`zaWnwfs`npB@4&z=*#_XI*1yqVr;y zA0;yru(#-%(7a{4G*l*Xaiz!Q{Amo%5SFETi=3wLi&x^LgJ!=gXgs@MEI*8DU{B4b z_m5enKwHh!Y<^=ceIXjVJ|64G^z#+}HHeK)hJSzc{pxsFk>@eZ9Fy=e`G}xrwBLD? zIr6k)&r9%4uzloMTZKwaS5@s9=W)`aeSiU0{E z18E(2n}h#uHx^y_w%d4oXJr;TO_hH3nCLHc`Wv9*XjBjUK|)z?mJ&`3v zw}q@8tN4CLp&kOPvhyDUO5Jf=?LePncC;=Lm9u4a4&Q%b| zQ^>yaWX{uHcb+WWYh!HZ@2nx0{@ii$PS8wu_5ry0ohSQZ@T0&TXDaE8ceHLKC^!P? zfmSFlG7$<$0Rhp&Tod>A=eF(kZhG^d)IGh_I-9^>c=O?ji#$>Aax}Po>>5O!l323` zIf8}NR8;Qp*VIJ`*-6HTc_^(Eb|?C&aw{EvU*JL}CAj*5U)crPTC7~8KvI{=Xyhj! zb(Y*uE$dfg<}$f@)=h+A_E}j02hHaq zNZ!Jx@2dR|vu3{FkYTX>%`DwzezIExyES-HfT{0b#$%bsDe*Uo34lj_(!oYwDke9YbYErta^A&`M@@TIOX#~)XkSh zRh{J_qlkd{F6?C#w-bwi{HgrGa4lk7h!{Oj@iY+u;)G9~I5N6~&81#1@qJwps@k@d z8CCS=uS?^fU$oZkaKeAzg-M9PmlyrS*Y(@2%QlEGQW+@#_wx-cfMhQlmv!hIX#Lr? zRtp3`?M9-YU)0?bihh|8B+$VQWS*rMfN2ub(0lnv0q(FAL_JKa@3-gi!KAvb=J`hK zw8D$11q^$1vDU*M-i=dpRC|52NTO>9lPD2UFTlFWqOLFyh=7@zB-7&`1XcnZ3qD7;C)e^ur9V8Zb?xS_CkKfoKc9_ z>hM{suKekb7aDvJR+W?TcWZz*wFz%ZY-@ck*1Rok#2vA z*MZ0E$6C49!55QbO=>|B1%l!@Kv}Hg@N!HeQ^9r;7~6-v?7BtGad*(@)TBHW9q4t0 z1lq=9K(wAXw)+1hSv870W}7FS%Zw0FCy=T=!qzd-DSEr&&TUG{3BYX|1Kp7{u z%Xmjc|HnVt686xEynLMBzH4x@SwUP*P3~b@S4$l?5XU1#|XW~8O zBx~uT1~_&42UM~JNNkgY<&{OR80-t$He0pH4phNE}pUBvloIFPE9SFb5G{3Xlyn1F@4>K@FyN^Oct#Gu082Dpd+#TZ39k(@76}|Rvl;#+gEU6h$#Q;EX%(3 z)VvjOs}Lt?FR^QyZvZl?f&XigoQSJ01U4 zkY2%<9~7<8%Gm2K{-*kyuafW8()4E&lg|$t_YebY)|<^=&t@)f-0FR}7$!9iqH7bu z+tYjy+!bapS5gp%qE^oXC|W7gmZp=H z1r;^Z;&##zc-tYpt<|>jk;E7#Fj1FrmN~6@UK{vON@+Nrw80stnYQY#0=q2wL7q)K z2%eEO<$jdu4t=aOYU@H57gUo^#mHyCDR4m5to7kJ)oaem`NtE$@)4SOA+3C7#r{58 z%Q~p-hUdT=aK8D+39EdTC=d+#K;1IT2hYfi5yKi)Mn$8)g3WFxINvDMOf~gqzxD&@ zsYW^OXQREVzQ_d4m~zFb)M~mHFYce&fr_eg3S$2g+9Jtcin9^>oKD%sWA8 z3a0}Xr?0yDDnDZ^W^3J8wU&ge$i#y7GB#M@MlTotjjRaTWB%uVoH6wbMNg|8Mu%b7 zCpmHLT2=+8kQh3`>f>wy@1_she4Q)QwkfJ@Mq$4Bsa|o^+4?4nrsQR&dP>S0z>l*T ziGONj3^QT?ZlVNaBw~x29wVAA8K7jv54;NGAuR)g0WlkiC&^C!L29ENkUGff7&6cr zhjjthPE`aRQR11svh=W4zzisT+_L?mMJm97EzqC-`p%ST96_yM_23DlqoH@gR|@as z4+>#+G~v*cd3fyHuZ)CC(9s*gFdgTD)$0zc_hz0|HxcGFEff_TU=kcF80DB;To23Q zI}+w?CJ$n$Mc~tzA6K(htG9Wc3-Sml9z41QoQrUC%1KWC9xyh_k)8k|KkD>(J+7Q7 zKW^L-s&jcrdr+=0@MqM?Gv zJCty<{n#Dx<*$ECf0AKt5r!w91aDjyWb8gr{I8|LXrKrAh>UK>PQdl*EMQu5 z_E~$aX{GMLu!!qdVwF^_RE_E)!g#)(wfp|DG1syaPjejtBSI*Rl62|bxA%<+a*-sk?P@d@%I=_N+g!9O`ZUf7@eK+?k|*R8!-9x-5*k5p*Fim zB7B9+`2Qwel(nSOvA>zWK3iLk#6CpCQ7#BMSN4?|X6N35fRwVWO#&eEBCV=su)FaS zd7e-c(6xEDFBUXaWT>)_!*lDj`TpG47m%j-_L@bhALWD_8kY>#{!2V5Oo@5V=4sbG zh!(Upa0YbLOnu+XHV}7Awff=lC!;e0@+|E@WtBw(hN^4(svdX#g$6TY|3ZUmECT!6 z-#}%IpDUs+55)Qk#92|=dNzD%3D zMh%hu4e-q+OB>fNA1xf;2~aqp(~O|oO=q1b7a3mD0-|VEw&CRkAqP{Cu{-Ks{yeo~ z`Jsz9E`zzxT&J1LBT73|xH$ZYwPj%9pP^zGtf3mcCw}euF=IXlk2W2ytkfo4g6W-Y zJq}a)nIkW1;>23sG6s~t$W9#JMZ)l?zSn)OP6{YF@rZS za_PrGhhn_M?7B#ETsGO7vYKQW+K#kQ)xP~lt@c#Wm8*IwGuankwFt_nXA!m z7$Qp4b(;vw{Za^HK1&ylrE`VFs=kA~(v;Np>HYlowd?Biu-%K-%&DNk6 zUV1$B%XS-Gq521>`HvCc|E*7>10>_|UHFd?{G8e5Z9E^Ngf3)Tb_$qVYR|;KfF__C z*Hszg@RP5_f(wy!!zECBC?FsJzkks1pO&?+QVK$&k!LGf-S=QMPxK~3Ia$IJlzJZ; z3Gc$N0>hJz$Ac>BdnRRKGl&66H=YM^0X&rHK!%k*Md^rc!n5YgJ(ox_8HZx*Rcx45rem$UH!R zfY_)05CiX7YH=eJD*%kgzS&_B3|)Ti1&~&bJhPVMFCN)e;5QvM2!t$46(mQ%(B1wv zI9bonM`JJV__Y5Te#Jj0gRCYLr-PkRh8m0cU-q}di>TZ{ee{6>*Q_>*vQK$L-vCUFVA-_!Jld&q8?YVBhN}@}!6gl#4EP z9ev?G`{69;X*OSfCow7k+>*I&oBl13^~KAM)9QP}?K1ab#a28GxdD^(7LS$88a zkZt&n&;uw#0@1(~RO^`x zz#DzYHEPIqf3J(AgOPj-K*KLFaD$yCZc8@Jau>Jdij?$H;Tutc=iJA%dP$kR)@{)= zk*W>nmfD6VDfZ*-=N3Gkvq<^+I8JnMi=jj)o&@tQ)|iyE09j}|+PWR`(k*etp;Q?P zQ+5Gx_;P$J8pTdV4zyH%`|#w)5Q&mkRAzAKzVk$m2+Drg_v-o>adBKnME~So!c=Xx zSqld=pxoAN(PD|kadG@hA5bR>KqT^H1*)2+@zX$YjY?P`oO!~u-U1{B#Pe#p@6j13 z2n~j2JG3InAbU&#nwC@`EjKa5b3Tsm>B5`1VA4G#6y(Tx)cng9!it*ZMeZ&ECMwXH zlpHUbDvjJd29Sx~bNUbF*MamE6Il?-O8x8w5ZM=04>p}|w;@$3+k9XWQf{9~Fo`+E zn{PtHBE#}4RT;hn1r|q`d5)vbPs|w}ux6r{3=C5`{=NW5Ml|E?iU|0dcVVT4;Qb7G z%0t)Uy0)DO`QH)8_@9b-KyotkUeD_DFiARzht-NaY3L&c*$BLC0<$=|A}^*%gZ!4pSC2CJU-r9LzcBqaRe z^sqvp@2Z7+62Py>7Ivo@<8DCtDokST&L)tr;85=AZzv#sKJ2{}F|zjxS0I(_oRZzD zf5@|4FFpTXQzHKLp!t8MW&HP#pt7w|-TkLPN)XHD(MUAO&BgldCOh-2IVhRME@fMF z3x`EMS&ri5;K-!MsJCAl;5(}y6I~^Aj#&$rxa!4d%sait{{F8}$KHb>C<7JB{jZ5#JD|=72mg}MZn|tA%R3c#Ppp=OX=z@L_7h|y~n#hfXfPp^59KIZfGp2O;wj(bG^ig33NJZ!e za_1gs)3%dScNq)=)Y&E0JRbWGgS9SJHeEMv#OGnMu$kuVh6bo*B{dFon1QF@+n;B_c-UrW z2alfi0ZrONp8zVsAlefF(vYpL1qzULsVf7G4yUvwNy^8(KtnP;x7ozkNd-pOR0nvI zw}og(=!;M`qV&xd-}Zbe3rJMx=d`Gj0aexD3{_pwdm_F5`@OHg!l>d#s+qkQ&{VQN zmxA(Zv=Nf-EDazUR2GV%p)rT)?E6d)#0S6c{6R{UBV88?Y~z=K$5n@(*%Y6@#LA$?^ z;;iS~hs&7A?esMjj?alY%%VC_Eh&X4`mc*i0tCKFF0EW7N!qpdhz*|fxE#2 z@$@9*$EZA4YV{HXye|c?5`aBZk}%jvwC=9;eGDel%G{728o4lTjkv?M;!-mtlS7VQ zI1N%gy(Dtyzy3i%$&c}oSkzjuJRfW)U4xjnnzN3y+e z{?&a*r1yhaj0l9q%jGV1hqk;l{Y&}%r#Rz(t<%=MJuJg;7`Y4h{V2sOae99VU@7}- zh#y$M%tpIg$WS)aQF2gYCJ%)*irg+(W*l>yN#$2g{8PCE--k$bE4&Hn&VbHs}jgmOld}BZ7nI9`)wNlvm=W8AJpKKk*l~NIACtKxiXY!x_3sXx_Y`%iqfO++-G;Dn*hhmMJc^kj~MJS+up;5 zHn=4mfV`&hOm#2nCCE2}V7J0XiwwCf|4>ZT2uX|bzGSp3XM}Y*+Nno~{Dc74zCJ`! z#!_QYvWxT9gWfpTPwG)UR70axE(9-Vq)h_>%14qDFZ1E@m$^$RfGD{}kRE21BA=8M z^W}A8!t`)dWQtPccw6&S@Edu9#8lDl1bWMdalVAI?}zEwX^xh8q8U0r{7FA0HJ21+ ziOrDKQ+}c0(vzAN15qCGlyqlL^7oM7YiM425R&wL*hZ?d`dHraz&Z7lN}M)$Lsk9N z$C=Ba9Wzr1eS5S$8IaGp4*OWHdSF49p%3{9y3*4rSJJEkrL%qp3Y%s&A96^anVR;y zoGY$++@8;Rnc+-OT=BVM(nzrFX!&JQk*X6iu@RHv!T46SuGC+63ImvXtG_zKP{hFk z;u+g8>(71=!CD9LeS^ZSV~WVXoQ4orV(u~30r|ZI(CRAoX`Xvs{b?j$!V;iE66MQt zpldErC+@4DI^lH0f9~=?+MaVlZ_^9PjP2ljhZg!J(O z1jqoN*cYwYk+q76H=~?AZLl7neV?jwNwE#(3$EF`h&&j+2rZ8am)x7~HweWIVrxE3 zqOPyI4SAt_5jQkG=PPL!oZWZz|17-P@AFA){86~?YGwuWMi>{OCv?AsV? z_GOTrvHafS{yxv|c|Cu?bH85Q$$Xac-p;wsb*?k-v^AA!sadHZ5D4v4mB+de2q^;m zF+NWLeiP8Rrw9Hb@z7O%2r2Elwgmoh&hCN60|?|>9L>>la`11emny~{5D49K;vbSi zg#vpBB!czn;|Kb_7Wi>WU(>mRy?>@Z1EA|lx1Oq;zeM`FelPN($?elCx3#766;mUU zja5G}-k!5%YKOhj%~?Hn{^|LfubImKO!OO1^!a%y$j0ICqPcj{UU^%`W+``-m3e3zd~5@(UL#N^Q&VPd^UBR zq=)`ILXqb1gs?srMsp|L+#9P@UQv<%^{e*pSayMsldbIhFJC(41n$tk`@^7h|M^3G z!Y-aiK%nDXnn$;s5kfO_Ijgd=@nolL{^!e1xae8}+D;)Jue5Hrw>Cakm>Zi&dEHl0 z%6W7)tJ))3$P`M7-(Kn;=bD(Fn?zP(g;{nJ)6)eWy}6jg=JNf4l*`y+7I}xfh2zi{ zw>Sulx|tDn)3xqj9^PdWubyX+vedYZ)3-H8BK<8qsK0p3XPtD)D!e0qpKW7Qtx zxo!VyCyzC={N`D<0xaFzc;-juQY>ArhnF=RwwqN+pa$sXak$U6hEMhiqk52X)Q*z_vNAG8oSSepte|1G97 z&V+{fj>NR6u&|b_&zhi-nOg)^^5|?~5R=cqr#IL6r6+uI4-QWETNTD~Y4=2f_Qri| zPmlLf{{DT@*4>@b98Q_u{;hBF`SxNj)N=iUv(%8wIn`Q)3mo!h@~1~0G8;`~8Xo1x zRXYT@$*9-E?xoSnlIltSQ)Xd{)d|*uK^UIP#Bw~lx_%P*NgiQ}c1kEItx@&gS+;#x zGBF&mUhk8>{P`rq@_5;3bGf7}jZm<#%*=XB|Dg~+-kt8+fPK9%SYlMG?2s99axlNH zV_~s&{b|MtJ}LN>ZZAxKt?@K?i?Fg)rj~LCk=}8*vx31V%NvgR=X5vL?~bauySsO; zJd)hG_H8@5r#s}tV{2>YRNQ@5#c#Q&V9ay|#Zf4aK7^m*T|+*c923%84NqgUgLYE` z3^NP~JFc+WnZ=nxOV;61^OdY#S^51bGMTARvd&5M_4TK`ncR~>dzk@_84aa(Y8E-S z?k>&@e0oGFGZQ0@URrRd#RYD*@w(3?8KnuAA9`rX%zdOdT?B(?lJlJT# zYYD%P*F#P}EH678ENO)-Uw;}yp@USlm)uZRI85kF6)%{7WDp)1ya>xF`tn7hRZz}Q zN9Q?zjq0Ps$n!`S3;(73P2A+kkp7F1t@KGa&L_FvQbV%9(csz7wR9}3Y@n^ca21=oPc&c;6)Gi60+U`EFut`|(W(#pNz2==Wg z@pyOS;$^=-KtK$-IWG@IRZ-9&(;Q)iu0LK=-3nZsRBPOTsock-`spt|!PRCT?)5HA z(g@dCm6{&b^}fsxvL=6w)UJ<1$5lr923>Ttv^nN9NbwHpSwICF_j~NP z*3>V&?IYw_Ufuquu=1s1HY;E);qzxs2Em<$fxR)0?o^L$pW5SHoJLOnu>Sa@GDn%; z)_m%u5m=td>4Syr6ze!S^k5C&qN5H6GcERzM>CuGFm0f<)MasCxc2(+ud}ikNdyhD&)pxvEA`30@+~Zuhs0cEKdiO z{;Q%{SU<9lAJ!VnURC_szM{x5blXfVJ;HjrML$~*8E>CGlKdG{s`0*S7@^8ULxE`X zQHJS#F|4G|C+k?2pC4s^SZiK)FrU7bF!V{mvepi^Q+~&JG_Ia9o!Z~rWPAVtb^P`A zGSr(A`Im_#G zd_ygn4F)+?z8mXvs63e+|Mn!7kGT57gGF5pRm3J3#?!K zs3TxhDxu-0N_o{@{7Z1W<5of61HMBNLuvT(n?#E28jfeG3R5Ogkzt6isuTH9^@C{3 zqaWv7oYMmTwJ@hM=}MYO+r{@cy&@a0zgvImpKTg&T{WoAOBQ(;_r{w_d*@MD*I(`I z$fCm_akdYCjt5#T!|Nk;D#6M00~kZY!}oYW$r^ z!-63l%aG$rtV`U*sGj1eNWJ4r=oInp`~71sKO_3+Txsjj)CC-~ho}7{H=UIzeU{$X z=shq}*iblJ4=Ff*ZR0yG`L)9_-w_{Hz`t?HlNjut!6~N#_&-{N3w71K*}HMk}`qJ&5kaq zoS=OCR0TV7t%?yZUL5px$7f&|ed2QH>(Dq68C-?-y+b1O-ijIpIgTHO>SW%r3-D}; z4YnF!ubg0{r8~S?hRNL#9({e#E>Jdb!KwFa4hB7%QI>Rtw({_~MT(|+5-V+!d0f7P_)?wF zdAc3lx0}UvII?t%9x`+Zp7#U|+*XhRrcWU%SG=Tcu< zNG?h^)9{^la%3dVr4}O*d z)t9BS8&9Q0y{kPz>0%DXJte9P_fIxc8iAYh{MbM-R&#oq9RKH7-{1UEHwfIehcBcG zOlsszdix1qx+4y^Wm5mlB>(Yv%z zq`RJ?>1MF!)_dh@P+SiIwzO_^>eEjcO=b$p8Ena#g_wlKZeY5)yhke??VfbBhGlK_ zJff5N77Bf0k_|A|T52pyb>Oed%8R@)9vjV+_x2_N%C-PHO}|_RvIxmsH|ypBzmtOn zjEt9Z&oC1~(OuSSc{bza5304xt*IiXXM-vqovisZdc2q(Hf!AKx|hincfT)2Y&aX7eBfeR2RV|; z;^JaQ8>b`LI%l>Clcy6gw}w+GUT}2HUt>2nH#1wkaQ*(s0r$&>DM>FzNE*X$cw zHt6n3KW_U4ws-mPS<>^@ak# zOU3F=dJUUnR#u8jO2x#P7bl;dHp;%3EYICsuU@#mry?X*y4NNP@OI|dnAt*A<1un; zxbb9A=3w?iW&)S8i-(1W@|>m5xR<72p{o}N5)(mt=DgP~rl*Q-0|$`YP`Xq9OTO%5 zY|n6GlDw2G!;kLZUGXj7MJF<^Y>r)@5(SUQpxDJL8~kB>Jz>!9EPRH~gx{@P z_;UK;-WL{eA{lmGZlAVVRik9h!Q{bV#o_EeTaMkCaH$>qxa38 z%j+s3vIjL%T#j2I9?XG|&>=+;@<0_r>HGi-6*5TOYa@Espr1r^gA$+nC5Wvu8-bUm zfwVm)UPRfjc|npF|Ds$PZr92Nu7kF z4@zh}Jzj_Qc_9-ovda#13TlU(Q|SAk$(~=Kym*0DHsFz7^i7DODd&Hb2)vaMkRe&X z9tb3qH_t$?p%k90c4{9|lx)#;34C<#$qb@Ybr@{&3f1S_f<19vc@}qq}qHUl^Z#-9VlW5OIQG2_pk5*oBar-z~;v2vwg=!fX8Px`uu9LMr z1oPQcz?ty2R#_xM`s{K(e#8bVk$RFhsIue>QlBO#jx-Q3RAo28T1@GArLR*VHb~Dd zY4OzgpNp0Bq3(md|oyzt9?2(S4|6k@5yIjrZsletm^Oefsj*&3~kDj^e=<6dDH`6lb5>Jc4=u5oJ~q zQ7XSoT!EW7r|d@}5pT}s_mhw*8t&{pl8`Z?bXh&Y>Ay!rYJ+K~|DU^WGwJzK5v}F; z{DNATcmk##Nj9T2TLyOTk^eWbbb}IeZ(cMHAmL)o|1%mo>~f)@T4i?8=NC~nTxU0- zWlgGHsB-9Wvzu{Gk>)jq}y{J^)%h$2KpS9K;|qgJ@zs@!?W+H*o$B1{XiyTi!Has=^K(j znz~Bt+kHy%x5XoveLu%79UW}hwnQ-@4kq~d`4dI0fB(sQ`hn;Hz?<;aCO&F<@`-H> z&H9gumizLfu_pfG6GNBqdG&5Hzma#qRraz?PZb^|;Vs+E!1mTU*U#?N%I*ViFRtHS z9_*+Gjzd-0IVelvPBIw^J$K=iE4Kewz?H8 zpTu2v4qG*Kt>?jFvGd*#NROD)KFUCsc%E}GVN1=F98U8B$Phn3Dq-*@lE>rg!FErk zSMm;t!R7+1#Gf(1wwq{b=mn2Q6|w2EB*ocmKIQ-}qsQAJZIi9=Y~*K~{C8ycm@HGj z8HGYK+1bfb57#(YYl!^^`EO5mOX!Q*>dV)K63=G$z^>@~G-Nw%>)w)el+D>85Z5qJ zw{KS#J3CY?Z1O7<{dKY$2fZ+79wwOD**g%o;7})1(LtHt_Fc;5X9q4dk{`kH?QuLy zjAelg$A2!*j+GkGZov!Z{O^dr-Q^fZ*?+)xdno@k^<(+Bvg@6LJbTM!yh8D@ia~Iu zJfi(#=;(L1Tr8>cne&Jn=}BdG=Qa~2pRIn76vg-77~&*`V#+qht@YIt1kVhz`58$I zbu7vC!djox@V3)RkKF(itVbL~ak-ERk%}`^ z$A3#qq^}@9yXF>cKEo~bc;)MUzvM_EML#1ofydwkph?}Ec1bDvN~#bfFLBgr`E3`g z!R2?Bo{c?co9;g=eo^%Q=q%L#-C&o!_ngwBH^@}fyfL``zp<>|xc5L3-0Zb7lxC`NWGCO_Sh2L>{l1gGAErk}cJt2D)T1yEj zdNBDjtr)(HOOw+S`R}uyc_E03LAtbSa&a+##iX`~!R|gl`5HQIA(>07TM0xri8e2^2!6ywKFd2%|*&U9gC)7bB#IJ0Z$GAdD~Z ztrfLIxVdNx*ik`B?7}O}${n zYvM@8bvKwJ(R#3db(0JgoJH{P@qJI9>1SfMy^SKu7s#AJ+>;2W{j7Q8qz}X+6(-r1 zO!L!*AO?+t;(9hSD#U;HJ6(D|&zLS0q)w6-1u`kP^Mfb)<*cb@ljT9$_(qaZVnu|4 z?Qt&lpA{H|V)56T6?$E}M#z$-$t2Zh`=yD z;+9d-R#J+nE`)g}V284Y86kD;k)2&s`s#R@b9yMrFuwR3wNedSB=4Z}=|P6Ur1AVt zf1DgH>UBuX0sJRXbG-E`8Q=qYeTIjRQvbfL=)BWRG(_XzoxZwPR=;*r0st06oyzH8 z8mWql;E|GWXxcGxRZ2^x2#_g*LwVb9`;;-fk>aCoo>l@SfGn3Z%@G1-pL52Rw>V{L zKUqxz!)foLIS;YO?}&cFdAaSptfb?#s}^%rxvGc~5&cp1Ef>0nO^*ohJ`-F}YHA6`T^{K6yrC0CW1(mI^)wh9E(C@fsitoXsZ`AOpCBvPWeYEvBSF3j?Nu5Cv zjk^#OxSTSr0^1n%Wd6IVC7L*cI))@(sN@*cR5+$TKwB{dFB zoHiSQT&eh|+WZ&PO&zG(USgaG_TWdzsuY*p6U&|tL@|LC$Qg|)qD4r|k!{G|^W_u1 zmK1iOb(Oc+)Z#vTG)kanlsGhpF#DG)#GnJIbDI7U0maE(5hJ70WU}@05%{ue2SEaN z#9fFGb0ENLNRq6;>zoQ#rwtX-AN~Bo3I9yoCg-p^MX^FMfSHUZy(0L`3XML*UXy|^ zcfZV-_acLMpCfJ-TU*<}R)8n=sTBDOaUUnmWcT@Q#5zsX84n>%7p{|=(1EMsX%XHp zf@+b*m#HE5pETaZHEZ3YR~NUQ{CTfdKoQ$6(35s%v!O3_3t5qQ;zwXliDw!wKJp_& zl=OD{+5yZN zm_s5PGKpsD_f{p7Yn8C&D zqx159IgvD}If(}ozPz24^mu=C=wHjVkEH3XOo}NbsmE*T zl>^HLmrhyKSt5p>fPM4T8*frk`CMN~+`ZESzz&ez%y|nAj0xsHdLtUhPrL=Z- z`VB{Nopd|&5*(9IrqCAq)ksx)GNG@$t!&mkB3Z=ql@iJ zGK8AFso;{1$yickvv{*-GFtwIjSP$Q%p5i-~NsOT7xJbYLIaXHg-Dg?YzfL@gejezaYnkR(w0 z{m1L>-~StuMoS4pgfNks3=db{bAE011Ta)mEtynN4BJz9vpkEBD8I1391s8Q3>k5Zk*eZ`qaC;B|Uj=m}yhd~5 zBo$9N)EC|kO{H4-|DfXi1B#0Qelzc-JC7X8>Ncas!0H3$qJX$|I(ni=Y0gQJ53Btd zbWQi1MA-GmHk(nFf~%3FvBr28fa2G5a^`$*!IuN`Wt9e$n9aFs*J?_L9GQDFIWzp} zE?7g5W*YAlT|~r?PBF=9>!r}X53+UXeWhgxE%Y9}%@+D9c{bI`L|gj?aSsTZeb;Vp zZ&zQygSwfyn7H`3cLx(y(O+*z9T`M&X{5*;#8GTm+{=Sv^~R+=-Ie zDAn2Vsy^c>7C<`d&q1iW0I8kJWcmzsKYqf0=JCTY>CzoQn1DHn_eL6t3U#^XIlBCc zX)kbyN(PP~EoW=y3FkNIsgaZ2v`yzw@=%)|XyCEfI1eu;zQV-&#qpuHmq0oCAq|QV zJo|OpNq)^=y?Q@yA+~3daIrFuP@8Wz-BbjmW=zo~kY+|A_b%~ZVOj6Jfm+gs1Z%W` zfkC<3%##W_h%-J~xIqMmK94|`gnF~*Wb>H-*av&4aoX4EyYHke!rl8a8JjP|p(qBc z%EeaLr5``Xn<~H^j9#r(4D1_v+%V8%(wlod(>$039{u#^CvTqR zBqL`E-pYt+7f6<@S231U2n1w_W~n*l$~b!lCl7gmEW`qLv35}0l|kJO3ccfy{>JM< zL@4zM{bKa7UU1BZ%XFmxhB|9JnqJ5baoKf#=0r1^Vla#umfT9YW4?Ty+#5_k>>=QB zuxUC68UUy420~y0G*<-U0g7 zQ@l^+$Y72{H-f&pbGSpm^}|64t*jR49}`!b#4Uj=SeV{rZ-d zm(xg|HFW{Z@xDiTw7k50KS>)Jh&$g}pJ_#%BV<3RnW={I39j_~<1%im!d4OR#&>YQ z(B)O;0}*moq99?-exvi{9_#dk#oi=D(UAaz8lB#8+!8aUyQjx(yxDN3jnK1;pO@ro z-nc;zJIw!kZl)Q9_(2UpenFx15$dTgc9nfJEx`FR6H-dm!PfbCV9E=dV!>G77gD9N z%1UNPHB&`k3>9uea)e<0)rPk#!f31K2RKe#}QtWv`*)w`e z9d2a;tC@YA=lWnX?H^KGP-7(Y2*l@fp|4zEA-Eh!p`^{IwW-21RRIW!p6z58pLhff zbZjjBHy?<%Q?0tSdK;Xcw`o?a>QlD5yzst8YDGsAB4=u|OQ?C?Lql=JKn;X*W0EKt zjc>WcXQCQmW}M9uH)4NvT&X<02r-%X?lz-txf@JA2%Y08>j6o<_q(dA^}w-1X(X75 zX4AqoIl-YY)F^_J!Zg)PJ! z_^W3#A&D8dDHvxPzY^q<05aB^JhcR+xBN3?gO7ZG@CgtCWq z!gq$Yg1v<4XpP+(qRJI-=w~eV#WGy3A$szN^;E`Pr@Y{a(yKP*xlC z1GhWw^y)EywND1_JWZSGcnyN1$t(1a5$KVAVX_IOcgZDl|Je@V#*Yy+%r(ld5Fnp> z($mTq%B-F$)*>;t5RqGMRIs1(S-(gA9)GP*Oe2S`q|#^N(x$Pg;}?VY!SninCXS`!yapJ^g}NOgK2>A5%aPB$3>3<@+`ix^?p*7 zg|<>YSYkbG+9evf3ezL{H#I+eTOc&`*`4?AvQ=6bo4WdLtpkNdm&B`rzOnrG zOP0@sf@q2{p8hq@AU$UrMzKjFkBV7whL?hYy@d|)-gjrv2xFMuRLOULa0$0G?V?~@ z?T3M&2M@GZz_y~w;%7f)u0a3u3kdW{kO~TvUpxwLg zmztUirGa4bHO58I9CRYslB z*-VF(zr5|c>4Q6405)Odt%w_K;G8;dv%G~%3+h%6siHWne-}hYb-le$_99C9){&JZ zi7wTHw>~xiq7!iUu^<5bpy&@}yIb`piZ3)1`04=9FNv`-OZPa+Q)P?o@HcK>;dx+A zTy($@{>wZUUL;pGKS`n(hVtLQH*qMf2s z5#^_G0OlE!|4IL+ebv}o`(;fZndi#8(Ghwr13HDo`1cw8BJG(-B}p>aPBJJyTx7*h zPuYBlbk1T?Z=OObhFgD#$5tLt@~jD&na*gc9nnE~UE<6as`WKFw^HTwxFk0}@ppRR|Uvx7Y4ntnztQ)qfW9@j21vbmfi-{ zQ9C6Ykk)SgYvrg_o>nGKjqKaDi=outn=3?jckAlzSCEGyjsVCO-}1S5r#SJt-wE5c zzUA%YCl@^zUREaA>@$EV3ZqSXrP8mVw!3?D6bSD44ZAVucQ48L#}h%gcN|?R7g_6bA`HVJ?Z82$*fhUBIc412( z8?{{>`IZPyY=cG@T=dZiC@pS2h|4RcLKxtv5NmiPB_(ivY5jnPG{3l5)ql=N&61;Z z8zommKM-s_W1wfwL~}9&GLvC*pQmLO^|L?@7Y_ooDKXInlxp7g`sAb>87$zPp?dfl zo`@XZ(wfSW%3TtvEo_xq(8{>0bLJqAeu_8i5C0hl-1}^dcvpN^=DiM}9GU&rdfmg7 zJn^UDDw#n(6bDx{NX6<-Q})0QwiY^8u@yXwFKs68{M(3d-sy}}nGAF2Z`}^3lYbfa zLl`7o3z&3XI)$UJ7p~py@$_%l_(3z*rzV_KkmcVlXKl*F!~_+asA10G@md~eb0SLu zq)F?$@rIVw(Jhjk22d_^bX%YVAU%mF|FSTESl>!*QDzhZiTTpVx7+|mh=UU6 zWj`R!#hg5o_Wa~V@GKHZnlr9|wuOfmRTV!1$-BPt?22@54N6!uTRv#a5!W}z2`aY4EVL+yuuFe|Vunelio-srxg7)8 z^%C$jWOD41E+0$Q!R(F{E~6|i6J7j+_rFmBHlXB>;0pmrXA{Ue+a^zTrK|V< zMuQv>U9d8TYho!Ju|e;U^Z#wuFFAo|Tl)F=VaD<$W_Vp}-l$f{4lNIs%$1ZixW{ph z``v=aUY9em@S9^gSWr0S`}u}01?X=yh>~C#AR-+DdF3KdBV$L~VL=b1;iFrSoKm0} zd6=Iu7fDbcwgn^Mt}XVQbb?`g=F)d?)Ca}amCpT>K& zhs63{G2aI~feaA-v1!d(v{2hKB=*}h>$0=6g{!Npp&XC_q8j=rU$x-fk63Jej)|X|NTfN~M}LdU@3Jcv zu)iq>0>`<5b6V1GhhB#B11=yx_g~}Drdoxlc9LTlc#o(H1vw=YTn_tu(RJWHD}*V0eS2RAlJrnRd_Wh`gyYhb!&Xq z?*On}Uk4f#=06kU{I}zQKKogh!fBx2)GNwafId7=$>Xz}Hc$^x6kwaM*Em7B=|vr9 zd@%X2{yvnOgRu05V+vJX_O0+GJuNw&kfRxnInd(qfkE?bvzg~9*wabO7QPRH3Ao8L zfF^*b_LNjb3xI&gaC;0M5{N{wOwJ7UsR)Xf-Jxku+Z^4K7$3IwPfx+m?TR1Ie$et= z*LVab>Udt-Vc_9K9^XC+Y9HX1E6k(u77)=p-KvYf2*!+C9!>_?ZX zY-8=RQ-j#D>Kx3Kv`f&~~xzR#b_XQeqq_!|TK%G^pJs@5-G2jjp zZ4UjD<+70tG-+7QAh1N0Z6{hGhaY0D$>;|Ei?)P!tktgHA(B+~e~k|D8$^*Xma;FQ zbmB$$f>iTBed*Q}(v7Oo-u)zmFt`#e7k;q5Z5%t)g3BcicxsvxyZq9XJq*!AkdaOoPO?x{7E6l6i zc_v3mI0#2u-59Y{d^u-dS-i2ViRs;Bizi+&bb&9*kGK15MA${FLdV=YgwE2;^HU0E zg&^MACZ`p5F%Jx*u8EF0=wu0C44oV)ibk#H?!J1wQbBVS=F#9?{m>sK2Dbnb-c6t& z`ZLuWZVP%sHi73gHvIBzdV+fYXSr=hr&O8&3~l-@q7PkM3w~!T38Xyoq(QtYaQ1O0V;=Yi{FFBWPvMFISOGsR7620o89+ObZ9YS&QN8sV& zH`G*y^N7-SqV7SIWCy^Cm#!pzDN?;cX5V{OmECda&OthR`$VenN@&RA+}<>+<(XBi;#=22*zri0xW?@W{IaN??F&-=zwQMq2ka6!$_Po`swRNlIP zzpp4-4E9@#8kfsis$J7Imq_o$(RK z8`FakChVkrnY3xWN4LW4)w#a=AH?j_)&v1H~=(~n736{BDa;39qw)Z4mub8Az|gZGaOmy5HG~XCrW^T6`#Rfl0b-K_S?|P1->2)nz+`Cz9M9^ zl`ORLYFm4IB9Sbj+7+(f?n{$Lgj$|a&0OT;ooGJIC$W#qqcJB&mO-{?@F?%CZ#1X z6ef_Rrwan;W>0nIw14$4w20Y&qc}Er*}-$;L+QJaehukVg$*E8w@wrMG5wXO>2W7E z?-9vk@mJehKxvy!mkon9+%+a&>qTI1h2Uo%E9l(_viD)XS0tbNul|wp0?vhLz45dG z%ef=Ls=gxo_bu0K^+MJM+m7Tmo)ohe^P=o>{wQ$zf;}NQ#dlU+(C}KeN4Xa2Qf6Hm~)*1rG*kGgO-~zI0orlrsXyu@B@KlN6?q zC8dEreHSvapMH@ougI2~q;Bl9(EAiWlz`Ih#m4ml)Iof`|XB+3LBoZ+SC;#H| zzu%Q7Wl@nnyq0~>rxfc7`s41rHF~zROq$0l)b2EjdKx93E0$+o8Ng_fz#gl`o_~h! zlpMe#CqVNBBF_HNR?-zFrc~VawHxe9h5pW@eM{MB=@9!MSx9?AsGxbxfZ$`28}%b! zbHlU3V#s&7P1{bU!s+sA(uC=X5Y1M_7)HAcw@4s*w9E2C9E6iC{V}|kZYm`CBb6Sr zV&%PLN1exPPU`|%s-W4>!1X>7ZNKTlFP4p2LnVv@RwCvoSc2!;*gky>`#o<=Z2fyT~%cxotG4MP8=8r&$XV@u0mh}Q+)T~TzLgEQw z@|z%EUqbLti|;Q#Var@#Exhb=EJab4tStZR$%L5nzyRXK(T))!`Bha*lPWS~JS7Q)!QlzHQy< zFtzmAx3FM@Vp`8|xwFP6mPrDj0@PA6-hNC;8TM>cbbyJ#Er3P~TH4pIrC?5Ezn}1} z%z>Yi`Ze!izFf#(fGh$1(7cZ*j-9?e9_A8I;TUo~bN~^a<*7Y8^_PF?BLiSGN>HEc zvrQ!jJHrNgtwh)*9X=j`23)aY``vLLOZ&-&`s!8CUxyGpAy)gY2dqwK(dN;a_bMq- zdvn5nkA!H6kn3hs=(4#uF^JZ6pCD0<3P_`(T(D%Z3Man(!S>LEZ=5R50+z}@Wy3UMguG!n|u418VZoGdc`Mz1PwMCPUU7fh_YCzI&)28CS zPi<%61y`*V<>FrID#My2WZ+L6Fb8x9eT<2@us4bZ4(5wR{b)T!9;GQ3#kK5XD8YN; zfwGhe9k8L4TRQKWd_zM6-G@waMTVZ;N<_D=4F|vL(L(IiV@O;qGK$PMVOOr4VMVzj z8slxJkq7aZu)JP;hx|MV%+X-i9ROBrxf##oY(C7?>ePlk6P!%C9$*PX@#*elw_U76GJ)smqQ5JAI*nc;$x}RM{0F9Ox3zIOZ(2b`R zR|z6`_NFprq$Sl&Y2auPp&SDeb5$=}2E1u=h}SLk7o;~#S5FtNP9#8&Jaynpe_Yng zP=LEG#r_C5kJymQ293-;h)uYTm*PtKE+eI1Z%}?O`eOI35Ij6UuMf+Y8 zYO%`HE2gJp9E3-5 z>~f(k$Sj}v@Qq6@!n)0_O!J@cb@aoF>o>r)fS^G#s^hyWPdOkHc_pm;v_d3l|N2KQ zKq9VhR6XG5IL!`B9t9au=b}1On|&rZ_h%VAW|y$uC~XRv&@(r8HoU7J@O@AsuMAXA zI~N1Zdv#N?B7A(M;1ghDesldoQVmeXj!?CgaUmq%lH7g6dBc}LOaCpf7=^@M8aYzbMS_M*BCgrV zH2gyXmriCBKNN60P?{!Fr@PpCvfO{iKMa54L#2Jg7s8h2G3j$(D!LLut`t*w(7Ws; z@*e#{#6W7l&*q%(2j|}$gM1A(JbjaE?8Tj<2eKlA-b)WR{qCG4AMW6L2-<*}W$n7X z87Ol)jeU13q3O9M$<$vrM2qOHi-q0;UbupMie13)i^$dmM-`T#SgU1bKbF{S4?9b^ zlye%E^WZ*{I_Pck+ah+&-y7r7=--NpigLJ9@4w^jN`lrRe6VlSVsZ<&cKpVq7sfXw zC-o7g(neJQzAs`#m=oMtO?(E>=rP z5urYUrs&Ssi7%THNYokT?xlW%eVWz}A}TJTXE)VFgl^xCpZ@vA)vK+e;{)gpfd}Q} zV~f%`*Y4*cFuPZ^1jGUd&s!#|q0^)h12_FyYfv%eSS1|_$Q(^)ns z*q%7ueRVn_%mcI=AKF!ub2X%Z)|Tg9_#=thXWTtf9d!Vr{yi5q|6YsokVNGU`~Kq= z{aKK7r+{|nQ713HjYR4Yp`by&d;9=X=^GiPx9ujFfzzX_A%fu(!%1DH$?yHL-+5Wx znSwi8Q@pT*ws@@?*LC!lnF!Xl*T!*9l3&XB_J*yjks8~7qEC;#K9O^SN^*m~si-rK z@Av9y93YUgOZW3eZJ%Hkof`cCeAUPf7~k? zca}AMClQ|Qg$hf; z0YaJn0{#2Mcgh?MVnhVK1p#DM~jaW+u48u?=Y zKOJ{VqW?CF7#D;8`vPwjLrR{Q_f@1}ss$QWw2l?#J=Z_W1^*#U{5F*SB6FY+F{}e$ zo3glm3Dfz3*hRNfM1rc1Wxtn(U*3$z{%ABzYRM+cl=TubC6>P%at8Z=yrFy5$dkhs z{gmm#Q`@Qp=pIPLavi9-ADo^XW4wFkwO7?jun}5I9*Wq7bHvsoOJDH)7o7tl2;EfX zvP5oEgVtA)prCINfRUrlK@#aofZIMAQrbGpaJ&gd!#n~-1e+xee0ezW^`KrlQJiez zRg3`s3f>9Yc2~(@Y%DA+w=(!mMZ-@&8c>3M11dzDvWSvNx{L>6EMUDJ+W48UmQ|E& zVvtFZ`s!JY#9vTryv@VIvnB)?{Sit+*6H1h`2ULg?{F;tKYkduMKnl4qB6SdtV(7Q zaoIDHkv+5bNJUZh-o%B=%Fd=mHkU1{kWI4Z{XBbrzQ5yl+<)H3eH`~+{UMj@JkQtp zdOe?y=VQ#EnSy5YKBBJ3S9Ci#IFyXY!dnwj>3q$H(o5t`z3{X)!qp%SP^)a0qUz*` z20Bq&Vbuf&kRMmy;pvXOK7YMqyS)M?$R{O!UI&jQ9YNOXjttSh z+Se7ysxSl1L@X2>uc_OjH}HeLeoCv#zglDGx5q=8cvLmvsZdnEtqc5}vg$MGTjlnX zPXf;{T5UJ#q!?AMht28*l-3EFkTk!e6Zj^Eh$*fWBDj|0vb>W$4^a+eOPgkwr0j2HbZVtFFQX$~mmL$9J{H5TCx-DpL|}tDR5KBLb*XiMX^p zhYoQYuk-5YL(Z}e@y^`|DL$FDu}h~jp_#~m!Cw>peC}bSaL7V9bG;MD@tSdk{^7lf7~ud-Gr@-i=tw9_m@ha2uJIk18aCKqkquu3u2#+M zAMLg8*OEA+ug(&ld8f=y(-jGr#f0FB1hh74z}!kDN@u<7+#}Towk;znbkV5%dF#a0 z!5C80#l_vp5nt4Ekm5zCIX~*XHR+Ahc!+5C9gMG*XO79C7+oXppRW06o*glKl)u_z zARm;*p}FFAbLRvxBmp~%-~3>{u)~6PS3%Y^4KNn7lN8pGf|Rtm34=sdRd(j|s~qubIxvx!86!K#$R>As_L0CB!3BWBZ4|Hd<*-Q?I(tok=K6@?xQC@sGuMWGV&jTrsFw%GBm zaBNX+!mOwdDj7xNvn_37~el!qNl=#5OWeBr!&c+U0o{^_U_g5OK1;9|4~g?yrvq#ZuT|qve@DJXT=jW zcj{tc7Ddnvi2^*lfe5J4%*FUZkvOHceI~01W3s_s+1<%mwyc+;v0c(8?XPj!bvu{d z1Ui`jG+3D*z~XlUd@%hvGIumn~amw>}k{WGzBM(heM2Mt7hDKr!cnsG)Y{+@ve&CK*& z!s_TFFz5305?I8a3GPLWIQ!ywhs*}i-$MJ#Dn%{!W3dL{i(s}*><(p@ z?SrI9m(7pD+!C;(V0cXg^CjE%8E<5NR*qOaQ+rNMPxr<}mD*J^0xOv?v9DyNZJ9D5 zGqHMhH?OO8+K>`yq)WjJMTlEuF=50*O}Fzv9ot(~mGjiEHdszF@GKJ#GQROTT^DQ^ ztd)bKvwWq*=^`>Y2ecbBQ|m^*>4moQn1e`vD>M+g` z>dYj~Ea;_vr=F68Wt8w$tbf;ZWMh_I>!m!+5+}h%e}QOOaar`{(opyE=P@~A3mW=o zn_~<1zJD3i6PyB!)bns`v)H1~PrK_jpWN$Ta(;sgo_K1~Zdc+z>Y&oep(aALS5&)- z$kCv4xFlqy(b*Rh*4+`;sVTVNl_EU7G-;*a((|@yh{r^Z5~NHw7+W`yfekdlby;RP3Av9Q!Lw1~OQE1NGTsFu^jP_+sEbO*|(_{J4fdAG{G1 zqmFTQG-oD+d>_SnR|u;E-+uKTH(PUMzcqH;xdL;u zU~tC4j3y61s4Z4M?3PpOV!u8@<#-fiQ2P|mH%D=QbX?}(hSHN5)+p@_*0Fr87~1v5c)@5P*CV-%yeGuQlOHYKg+UKiD*1RKi|q$>;7 zj?IEmE3^gUH<6?MpTph7DP`$EiablI!G@5fw!KqZ^eJ*Dy>xqOSIFW$ENp2hvd%ow z95zBEcu)&z^VBZ$?;+Y1jr+6pJ2#yo9+218nqQrr=TJ)_`FfD%O2?zLyg&0js!63FgyG8#}3_!aDOrH)~!L7cX>e6S_n$;$pVf8d( z8--dQ2*GwEsP(+;<>`q44cHn#u_-39NF0oG&p=_vKh$Y)V3Z@56>gtx*)6=bM6NGW zpH+jEzv6f3P&Oy%l=dks^zQ0yy1T9g_l>3IBjAqHIoM08iQc-UtQGqz%jtKQ8EOPC z{}hHR09C0lRM`lUAw|EG3hNOE)9Ld}vw)yr8{H*VMRdU$=~znSRZ93_bGgV7$u;^dr^fS2Zw|xR-P51+LiNV#Vwna8YLzC%wc|U_S=ZTMA;<*H4u+e_ASPBDPRZq zD06zBg+`wd;eWzvI>7ejHeEHw6Dx3Y{vP@0fV6gKBCz|tNWzc5y`{U(p8PCeWJq;i zPt8O#S7jO3sIH^|jJZG+WXi6`(eogY-E6M?8#X;5Ut`iQeE$??_!}4`&IB^p@%@d| z($bQ5QB_7U`j*}|)-&XM?w{}`!+D;J>N}6HzL>NAA7E|0)O`mULahlsfctJVs6|Ro z-DzvjHdnkX_~kM9&itN5gwfdwafwTkBDgyOF61bE8mpgeTnROani;xDJa&eSMDzWx z2uaTf9?1C+sb3OV=|&7Q9|#mZDtiEhK89Rtz$HE}crTSYM)E6W*tE=xdHchc?XCEU zz<3oMj{Q}3)0&@gDO!tle`kP#=A?|*Hw6A~Gsww5GE}jtp8ZgQ#*+Fts-#6n+YNj0 z@w(VK^i>4f<}CVn50MO&ee*GGd5+nq>0FsgeJ(kB@%zal>-Upwnw{72K4O@v3@w*h zaWntNF21xVZtfURyo`7FtuQXYT29xPPFqVoAo_eb5S8@k>$Eh;U% zGF)^*;77$BL|1;hnF2L7%bYjw<}Y{SGqB^tVIyq|ynLNzT=va%e1V-6C^_x1xso+~ z;-RB0y6^NrggPXkQl4#FMBXnreKNx?5z*jt0Nk9j0eQ*`WE zjo2T$1Rbx^H7Su3WtX=KKc{pw|qrL?L?K{<~Bt`CkUn1Ha`<7(JfJ?gu$5z}C z?UD2e$f?&)cKl9$!|k{hkGZqbz5~3NL=_SH3DGx!W!cV6(`vnLek8ZAqB@##q1^K* z?lmj=0i)!0#EAzq%>(LLr)}*jHF0F^WhTvR4?@>+gJ1V|IHnV(j#k;*Z%2S{fhGDy zZo^G0zIXSpsSOkrN1u_9xwhh23oP4A&Ic~zit<4zED=A>nDM1T?E*j^cw$yqyAkH0 zIWa+uuJH@)#hpFgYoj;qx!Z2$Te&Rs$tX!2Iq%%)qiGhTw2VRcI5B^DKT3iD5Vz6| zg*MkaI&B9`pU9Qgqb-!~qQobwDZP6k%h+QW3y^<<80`BgEicSziQ;+ zb(4`~tCtKw3S&wpVy zO|ViGviUo~5X*G$y=+))KmftQkLt2yFy8!U6su(uw%v()*a5D;(7;iraW$?Ts|l|^ zbKqZaKf4w(=fcMss_D#Nlqe3Q8(V?G5onQS;c75Uhf}0xj7PmRA!iHV#OEW)i8+CR=3b5zrL>kS&mgKU>OoRrSDxC(SXIGtVHX^G}uJ-#~!K&bE z4wRY#A4`nbPOx%YS^_VEN^|3ZN@TLriy%DMb94SGDWh}vh+m3_BDJuCOl(0hMdBSJ zC|sVwGf6QI$kRF~w@+}rI20q`+|-4Xvp^wn>z0&;F2xKhPrqCd_5^C(&Y+qo%_;cm zsfiEw?o#kYZJdDbC!fLNglML`wj#C7g*Nmf{Rgx5Ue4+9`pHw!9tj>fPoGWoaj~FL z5fb7?L_`13^bi9J9K4@L_GLVO!O4atQs0CmLc^5_RdazQeB)k%T0{GDHOz}`;{%a! zhy;0r@7^Kc+ro2Cr)P7b2E!YgWTnL86XvN3}rLq8;4+_=&T)W9`im8wp zmqaFNz`piarmO$5+`+D zSw=O+Z?&{mOhHe&%DtfQ+r6Jv1`Go`hb#P}cSiNv4j7rKjOnSec%cM<9ZMZoUTn~| z*`DD0kWlR_6luJ`3oONQu{hn@NF9%Fd)=Co|8r?-Nr!qj1ZEk&bTXO|JDFT!Jg zjr5pC!ZWvWQT@h*lGTP%-(M1ig zbs&m5!F-js8qa#UWd**yl9ocV7C^hX~D9Atd&UXt1fw^Gl4&+Jh%k!%rj; zCDY%p7uRcGAcDECA@Bn)Q1`U4k$%!2p}MnRb|OYD@kc}5SDH3utiLwFRr;B;HaoJ3(1Q%nH(0DCw+Gqeu8y|+wR%s z{`bz&e?SpsvzJjo5jJPiZ2}?O3+nDNL*nmtb^X zV}Ii*%$4k=$$UBA-@^uPXm5NF>rHm0>TJE~gC6?lB~bUhYe12&&@{iLR`AD0ZFmyTPyQqhh{>Rv+1gOx*u9~(?J(by z@nYmtn!AvDKQx(EmDBIq$#NtK0!)`!bTrvO2L$fA6qjCBEwp+wG|6-9-56Yp)D_c$ z@9=A2N)_6zo4j3;#G(e&NRwn2p(7a{@v?iM3=PYUGI)a_)}E{w;*sZ;jK?>t%z9cQux{$@ni zVj@e-D!qWNoxs^}b4>coo%=9f><|Yll=g=nFAcGr;(1`=_rG6C`unfGPpjV0J0FC4 z=D$xslf+tQ*DxaSw?m-wq8u?1PIvoey5DVhmTvv3vI%pk>At&tLl=f0%wgA9m_wHV zIYdYbJ2$3$gkO$WWu%R?fb1wBuf^2dyd4A<7TW@YT|#;+L%=!X1t-e#k;Q1<=WS{` z7t8OoM0_}?xec0r_)9buH0ou4gkV7lw%h&f|vqncP$N zSss@T1K{lehvq*X!OS2WWcy<_6~>Du{K0~cJ}uEE6#Dq!<$Vd{yIWER7v2=;vP;`6 zC_{0HugQi`bJH9xTzls3QVDySkJ#`KX}ElD{2=IRLJSkHVX;5RwqJNB5m^yQo2mcZ z$5WG2{2DEe5u#DoXCXX(z^8aVCT2A~2ai{`$??aKbmtPG+*SA?y#dRoDfW-2Feqb~ zJ((?iq`8K7)9!Qt@;zP#TNZNc+)PI?5#cVVfU6hM6OM#kaD~x)$=S_Mc4h~kPV>fd zhs#^#gzz&MybnWh1z3{10|sdVn+6pOeXyZ~V2H<2`|bk!x$tiB12m#X08uEtRnkUY z{OJE4Ef@oR2k^{%o3nQ9%0WnP^jRGxSEJ6j3ied@fCQ>=HJBTBR7S?68HY)U#`m>c zAW}b@UsM!}sO|@g4S0JC2=W#sD=y>~myWH%2o(XV%QU#cIUJpSIWaFeCi|W!Y0d>Y z>3^k!JF%5(A;^JD1fa5FH=A+rm^^yw$9?=*(nm?FL1S}tY}tBX6LBs+@E;mEHzy~_ z;r&F2yEqg~L_VB3xwhaQE-X6%@7)H_>k^KgObO3KyuRB?*i?zFp@<2-;uU`sbj7o^ zppDo)MR=BUJm7_v;!%ed+R4%J=iPN~SjiUIo5g-d`E=`9aA31U{G5R4-Y;in4b!-3 zvw!S$M0~SM2Ex|`2pJ*$z*us2FZjv( z>{1*vZgCy@J*i{J5J=+n^4F%JrA=D-CV%34SvF<(s5qGPFVJEVxDP`N7te#dG){r1 z`aU9dCUK13x+{qlp>(w;4nIekaL17M!NdE@{;>V2Y}F%0ea1HZY@#k^v-SyedAMtYs>Sk#_@XWn<_VM zF2qTIs|X+WABV5bDGY5Do;JT-k^Lr0E{Opl?Y6~eKS41F+l0&6k^UR{{JjhPz_9B6 ztWx950`gtlreD#vAvWd{So6wJO6jk1Gvc5zjq%~IH zt=E|Nue{RO{GkB7!!;^nlyG|XLR>uzw;pN+9SfB`IRuZ__me2m47au20#1dhT{q3f zY`veIJK$n|QxEo@@^^}0mj=QH(FE`jx&Qf*n#jCd-m>r~ic!2C`FlpFHMjKWor#tX zN>O0_R?laKm;iHSl}yqRfje!qqhDpU_ELZf%RSd_T&G9b zv+W$r!q93n+oLS3L1F@!X@S3Ktx(hCDNJDjm?3q%--X59{ z1=U6wF?^rz?ZF$$UqtZA;k43mJr<1>0Awo&LP_l=miq87{#o4j-FA{Imb$`hO34;; zmoSf*Y_p;G$K09JI(H-~y-VeWy}{50B!Sa7vnJ4mRSCuPl}gFJiPE2+K%9#L->LuNuEdRg=^{9H6FQ^EoV@7ynfYp zoi$N?89rj^+SmH*y2)cR15z%;vDS>q!WO{TsuAA?Hg&9zTEU5p3kE46Ms4tA_-v(^ zyw{(50}U4TMx!PN`%dns-)Srt zVKyiN6EnmS``;&B718+#E)aqTaI@m%jBb^kW!}6e`U>&SQyA{_ zj~{g$ot!#-KUjr~ToIzO?$({Cyrf4*UtH#5U@ zOkRi`Vd%4e)3;$2;n4om$KqebM7;Qux`KGV>W8?`e*BT)h-Vpb`2IapR+zBaTeU}-36ew%x}~(=OLdQQFEocR(Uu=3$Xn*y2g5NaJD0e z-oO7s?l4#NWc}5QJ{Qa*7hqihmrOU!_k17OP6gB4(&=APJdEf^F(}UVdy!BJ%QE?t zdtDf&Z!Ujj!B>C0zr>mxag}a~R(`eP7OTo55a=>%65T2eebsj&pKFtnuzrYWl>lHJ zucxtKfJtlRh;O;5f>t!t%0nGW;Ku|61MfWCa;1)U4Q#>Qd)S%=Xo zjr{DjMD7eIM2h_uBTG1csG<5?n7S}_J@HQD-CvE7J1c%HPFrZQ`}tYg#ZMf2 zWoW;HyAyBqRKRJL3-aTO7y8C}_T|9`Hzy>gI5^gL8xL0f@J9R}A6zpEc zNIoS9EvkxRb0%h6nXHBg0~8mRbC{J1-;RuzwWTwXxq5u^KCujs{p@P6W~bk`yRTh%W(5f?su{!YF;{> zH_ocoua7-l^X8=`!9$UNJobgY47S&HuZeqyg?04jCa7}sEw_I-DGN9Sc0H6IAjz9U z{Fh3wOd^-vL7mE+T}L=*T_4+hoF>`1xC_uHae$>haK`w- z9tb)6J7?jSqb$lRPx5?!y`6J;O{!U#JLh(hY-4(K?i6N1MISY-*sgd=C~kvtmC|7} z%yyAZZ+X}EA}<7)oNJ~@)>blL9`x^61mSWTtF}B zRaj|4Bv#0_5LP+qSSbC$#@$3)!786+>buJm!55|YY<(i+$!s5~Q{Q))id1qpFn|~b z#j-jQRmM6E6_u$8f~;cTB^x~P+0tA{WQZ7(jgy;GBKbae3gdUeqb#nQ$_)-^Q3xXZ z$w)jXJhOQd5_$OAKOm7e{2;daOVA(jdephM+R1#U;9Is6U!lT@3F64Z+pzmdaBsgwuVrF>qYjv+aLM%-CLj(&=TZmE_Gq^{`O*?o-8&le$Q{IFF04Y zWeq0E{Lb?#bV61aq9#Abl?y3Kumd2%&c4GPqwY4ct)S;r?#!1`Ezae)o7uW-o$)3H zXP9lmH^3+2xoIJAr@l{INThKJlup-xG*@_M@IoUIE^yu_73gl&!ym9Mi%$0v?Bw3v zI+6W*H#n;K{!g;&@v9$)^%T>M)kR+>GSi>V$hLlJf3HOOo2Q_&)v1B@@T<}$J?T=I zVtTxrgl6{Dvlq!oFIW4lQ7xoa{rYQEWx`h&d_;c>jf$MjHWHv5gQ9-{Zm%KVfQPtC zHciUZK1>^2!@jZ4fQl^w85=`nkO)?vH+I63vecIXv$c?>St~spj*UZ%!&<5vEX-2x zJKjxf)`WRMNnzl??#tHPAj8BHeicxie-951tCAKz=HQQTO3&s~*q;sFZ7-DUL zJYC$!uW_|z2~qR&fBYz4#89CcaCi9JU}W=V%-)?6g`#rnAteNqs~IxnMA4$-xb@f& zT?gW>3t+|46`E?q`WRlpXn-U7#ncoUZ!Rv%Z=FXoXaRk_2CttoUnIv$TKT!fgQC2G z2T!F2>{8Gi`9wGpi&F#gxg^~>cmstbs&^xN^lN5vl*(Dn1mr?iic{5=tsQ7siB&Jp51tR*I;~tuY7Pl{IEji=& z6hj?EeiQ|u}9@;R^7=wEv7ta3N*4-{WI zjE0ma(+#l3PP!%O_2`44)Gwoflu{1gh1SdYsHTF{EOi0fL5w?NdO4=~9M(uZ>6eiA zs8z1g>Ce%8l4H1?p9o=Ru70=eJcH>@=vaf9p87)>$)clj9b{$`Iv~(>`*S_e@D(Hbbvx#u|le%CY@6s&s8$r*on)(NbqXEVCT{l zi}@H2?bdJd0k*y5%NR03wcZvcKQ1Jl?`6ji3`3UeL?yR2_ru>@M=R0Bk5uU+p>NRS zsow+)FWrbpJs{6~LA|T1#0t5F+`FFx`q(iEMcDKt4O-U_+ow`73kj9yb2*}VzRgmN zmZLwF*nTjM@>1YVQSQ-_a>=Jnu|6m1*|ReMnEw-mfl+%=`#YQ+l~#oP`G1{eX7{Si zx~36MeTOWC;44FUK1GyBjRvXuNbn*I)}ERX2n%*|B>mG`CU_}aFAzpdmz~A{%5NvIXWB)pF?*d z+H_9oKcar1h^zC8$|j6|EQ2mP0Ak|MS+ zYQ2WIgs-N9LW?{;6rzzf7vK<-4ZV!|`V|IEc!%ixY>{*Flf25SdK@{ceWipMW<_V) znHp~Ja|_V>yYx~pLoF3xsf)`g4BZ~`hbPDLMJ4V`D%P$sM5AJjlL`bSp4#c&?@bDl z*rzN0R$8V4J*t*0LpP&mghRynHSg6^cw6t7fB-s@LgzfQ>LZ`!vt9Xu$?av)x^sK~ zwMQRNTmS}UKK7W6S>QZR zxODbCL)?HM&KegV*n^a0+mn8N0+CnnTwiv%XL8=ln|#L;(Lj9nmXC(%a@vWfV@W~r zsf4tH&rHWX^~7=%ur|ntpb=M;^a0sgCA}mKrTIgb7Adt}+xtl!aahHzM+%LA0uYzb zK3NHR8Jaw#S{QWM@s#2wo^FS2)wtQj!S=EaD(>B|D}D8xySYQ<;Zvnl(A$nseCW%5 zgBbTwp;g1g2P%To@ip`Fpqve3I%_I#%9X6;N;k@ZQ?_*SnS(x}#1qpn)lu@K-t#-K znXV%3^XBph?lPf&Y?eWr%l-|YwXpNp63=Zce0KiY`rjEpK3;z5Tp-` z`yQ;!weNOmDCWgxvYvydEGG%(ANHg4DisFUJFz$=4$oEAh|JUy?bb6dTP!sA2RmXr zvJK=uh=^;3C^;f}(RlGJydEvrN-Oz_3*4-|Z)0CZF!{T^ym$4^V($By1oPCJjQcLe z`zj-z-&6h;nRFj9U*yjp7oeuj{c){Y;Q0E;X?9SS;zY**`P+bG3Tk=$@;fPihl@Hk zzkRw~W*e%kWs;zR9q4-+dgq%Mc{${WoQsNyF@2DLKrtIHm=2rJL(!_GDvoB2)`>IJ z884C?%^QpY3Vk{I7jzM-jX>@jGcUaFnQN9-i;HMfp4?%*+?e{L9(@|&emPF*JsFd2 zfFXH*M(1gShlEHDkepj6(plXG^~`+sF+>$@^ry3%gFDUi_ZyE^>>WV?k?0SpIfBoo zBu8K=u>2&NA-rY5W{ga(CoT&c`~ZD}&d!aV8t~d8bWZ3-NVw$2QbOgXE?mwHsOHZ6 z4w0=b-V92GpH zN5nF0-@1BLuxmaq)yi4HRS|Eu2_%oRkbIj*L>MZ1+qM3JiSY3sKb*NtsiAs2DznEJ zOpNgS>1%!_pLrQ9g1=|u^6UDtb}WhF4N8(1jy+PO)w0hk!B!HliQSpbWNV@AThd<% zeVRsFuvCsljK$6(zUmNO;{c&yNh=+Z&)z#F`quD2QLMQ7FL(f=Y%*aQj0~iX#Y;s*UjTfQSZ{b3uSxG}K2Tlgy^_;$ zaA`V1w&)S@-UY5j518)4ZRr39txm1qoE3BS1uF*FX&Slzl4Jxx@>`Z-z#h-zydxA( z@W1d1XW|^2uNxNUiE0xqGDFat6~{xMBcsYkO)4B4F0mbd>;)Qk&& zKQ`L2uR3J5=6gTe{4ZxmTKHvA@GG@?uuuIjP3P>$xtdbJ8=UPw9h$UM|Ihydh)-y& zR8A$<=FJXgMT`G`_d^=Y#ob#6fTO-{%u^@10eTk z$a6(JWcTJsAvkJALGV3Tiy{$H$RGRvF2xBi_1rV#A4kzu2sFdP6N{kMMn)OnxQ2)K zy&PPbkpQ#k=x8}r)d*m$KyDS-^ck-T!jJ1@LxRM-ww;S@IST_U1?gh|@P8;J^&H6s zztK~=TqVx&7q1V0&C=pD{jFQJqb%dKZgGYm{-kEXr#!DrxBodxk)bc^PE8uV=&t-C z4t53j)KnyK>ECU6ZU#Qtk%)_o4L5JVpQ-#?Jf^8X)IE-8Qn{va0Z z2)cm8?jSBwdU(tg-oW>D1S{}(vThgEMBq3Lz|jd?aCkcGmH(Nnc)E<1Tk=CNGP2>D z3}7`O87N$&(q_bXqGj{+ttpzfZKPCLG=07AWnpHuLF=R+*EC>y$WuK-RSov+oj391 zWOQ%(K-lrjzcv)_yVTbUa==T^_69DeBS4I`vc|lrhCPqd1T7=IAai}00`c+!g_|4; zRRpqU%KqHkhX{@z)_8b^=KsG{!Hf^K7tty=SYWv19QI{l3&MVCh9I0BF>EGl?dXUW z+xejmvqhgBIq&tTCzIfPF%DTn$VWUUf-)Zwsfj|`He!AM9f|wJ=-q)cXIub}*#*f| zz$mBL@mN8?t(hNSFLNT{6lhvv!52z2F0hlu<0}IYRQpeiOOL{n69Q9~I0UD!*IGg_ zK5*yit0yVvMs^-}Fkk_Uhxh*^icC)RALkjlb;bAyPnJN=ntp=dxqr2ZnOPf9LT20= z4^lwDT5F!gtM90`=7#WyiSX*cO_Or3PzmZ z0qR8w)`GCX^*zzjibZU3pj^F<9F&)Rcc(WXi7{aeu(yBb(G@X35TB&J1%;XheIa5$ z23+ONJ;b;|!Wy|l$-tEzJ7lQ$0Vl{(Bzn)_jVQ=Ykca~HY(`P{52CcFMBrrE+_=5VMwQpWOH}#0y4ZjG0KmOq!COTfP=2XGcA{$-jb~i zA~P){1lz-Aa~tukJl^Z}tEu|N=)K#~4ezCjOH2Ef zPZqTsBf;$NI{;n020mLc$qwJ>FrRd9rN_j^wjp_%0W*j=lOTS3MHHbIz(5Tl9VdOr zLktD0mrL8xF5B?#MV#jODA^^p^O)|IU2^q!4R~*q zfUjAYfJY(}RK;84EdLDK00@}dj!hrG43?W#1SJ!sEe;)Ps+yXncD%r_`nPg{=j0@@ zDSnKk1wj25KURpiO%iRw4yu8a1USu~uyVoo%irvE{ds)JQ4!z{Cr2rXd|z()luCUX ztptzM35LmcA?e-uUPgEssKlIVU51TUU=atyrhXT^8AKw8pS0z6^A)d*XC@crtt%t@JhGPd6! z#B%XvXZK@>E%M451WV0M+cfWuH(p;H0Pg(tkqYAFBuBk~sLLuLVNhCDrs%YF)_0u{_u~*TAY%I~^@1c}Y-JV! zi4fJ^(U5WCFWI-3rk_x&-yE>|g(R3E%yvuTA@PDicTB-A-Wfy+}0 z<_|lsTftAtgd-MF%r*`ohLgB=>8$f>RA+(|hlulGS!3G$kHof0ka!I=b;E@D5hECD zt=Reo)$B+^ab}x;fRBf`Y|D8;dJ^o8i-{Q!6tjoz18z97!_B#R^%`nbN#qD0 zjhT5aAtB$LlQ61Gs{@UA zSHVv6bNYKY2!WM@_(Ke8&Tm!2%;VOJdYuIepxeFZ^{jW17 z97E^W4k2%yO{sTRKYpgzwS1eJ17bFe2$cb6qVBta4>`U^O9n~3ha&t2VaSF&_uHCS zP*p_UfRxP=R~^`lB%6pIEDP)m&h_$~cH#VF;JcT-w?{A1jST#O$ae>WuOU0NM&`UkWLc~TY zX$rGxZb7{Z8x|*|e?`H_t^d%^*(&?~LbnJU35tF?E2P)~bYbf1Yr?alJsSEeG6#hm zM=8$8d^Zjz?n7_e{D4Gloj7L?qk<9el|lclKVH?9G0R5b6{6Cwr~mMQEuYyEsh07Y usF4~HZ=L9W$HD*Yfc}5!M`zFNom4ODDm|6!t$>fjdnluHzv!M}!2bny<}F14 literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/Distribution of Education.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/Distribution of Education.png new file mode 100644 index 0000000000000000000000000000000000000000..4f0b906b5fba80654bf9158bc685837f51d744a5 GIT binary patch literal 17738 zcmeHvbySq?y7yQJDuSXSD4mkhf(|Vm3QC7aH&W6l0*XpVH!39(Lw6_!-Q6JFNJp#`R9CVoj+V7BlFDj+;LsMy7jxGAc=p9^b`t(!k3m3S3;qVR>Plr zxH#|*1*`CLcsXLHBq@r@YQ8!PKO8p}krzRsasp59>79U|@oc2j?NBHJJ><`k4??M? zD3th!w7AGUC!NJ1JhyvYeKkKBSnzVay9irr-(NILZF~5UT17_uw(y)+#!JczNk_ff ziD_=L$eel^Y9=B=c%kzYlg1_W`(9Ees3YfsEm#Rs2hHi zXW)h5oc9qFYLwRNI{XkTP6!YCB;-FnB-~2EY4F0^+q<{hrz_u7InVhLtA;`4mg{nb zu`62!n|7(x#$1;r^9?cqdnt0~iF1ChUvsxKjRy)@Ngl;e-lB-|G)7&}f-fZQykcFh zR~=Fm#&}osqe>=IPEOA1Y6E)%d)3~D0ud zUF&14E3c8=bj+tQ?jW2$aM`sk8u2JYGyTfcENU({(k!wnK%-7266!LQ5ulEw9+`Xh zoILoQ*mD_wQl5#geni2su@*);(@il9s#=eH+YK-EN6vVD8_vIM}4!Um**{;vr zbxn$F4GSTRy&@TKm7|E%XqBt=0=v$w4`SKvJs-46YzsH$*~%6;*EEcWJy?$uU)aXp zJVt2)lep@SlbD*|p;2f#K(Cx4ms6qMgFCO(z>JchGOwk#wmig37lMnDqOe1qqvNt6BGk8 zl~V&6A7<`f5ep>J>s_JKlpgW-F7xPqMj~7>tTG^!EV(-UgATKp8dUP zp%@P`j9Sk7sO^n|sCB^t#aZ2xXVkIHd;NB4K-j6ZOm(ZcNm^hucP% z>Lw$Km`LQZaOLWp{B(1ixm8}S{|^kxlb-$#gu|*m501La3noP9)`UhI-x^uAaU( zaWzwlU$XWs*eid%PfH`?F$=}BJce^7$OF66m)P8Ddjj8);MU5M*Oxg&1ITXDTMiWR z2rX~Vw7k<(ppf0&T%;2e)Ts|=HTT+{X-jP4*y(jBS4x(da$X}Z^KD#fvkgq}*qO~} zIwt1nh3iG(U>S5(Bm>V27-9DmeU11pD3?DM=&DNu* z9I=a9w`?_XwM1fmCi#kX?EkEx zux#mD-`}{5^@tj>ZD2K8=u*`!KpW3QTE+XECXUu;hxI)2`PoTJOv_gD&E?4b&IkIg zZk1+TAGZY_FIi|B8&tNep?R?`6%;M7Wtwu*j?`@?ZFeN>Psrl?SIWom_K|a;7f$2j zH?C~Dz ztWiNSj*e?+O9W|#`~8pielCtwjcopMOB?IGI(^{ggn2%^GmvZeYIe(0LHSq)MlOo8 z5+vH)&fZkq!)(N!l0E+=rssAI~iyo9X#*YexF{*x1-ARIk4H zjM=TW+(5_0{=WEp7ej1isaF4wZ?7z^n`bjJn%^1^moFEX_ps%8Nz6S*aoNpnk5e2l z!aIeTvC`NeTG?=xH_s_NdSjo=DjLV3HO`K;k*LM-SIvD)Z(Q!J4`W`GYMxjxDL>fX zZNl@3hkD&NxZiJ%L%D*~pg7+X2dz<2IM1O0v}G8k^F;0#FFqc2W{`ZRrZ`$(ho?}r z-DJI>LyE6V8hP|Sg)5uJmyhYp1|EXtLJjl9RgLcyO>6s$tP?B^<(DNrzf<4l+~=~% zS`H!7ka>3my#_Umhihr*@zk`MDT$Po6P1#=e~V>Cpzy3DxG<-ec18+la3I56*hUX72)+l28Na@WRA&v`tD9X%QIFo!}7#ps4b-7B^q zv#X4RMMMd4f-vjHX_AS1Z&1WpmMsRdXBtCt|$D?76RrUiAQU-nBJ#TFjT^7-AH}-o{y2PC%iiqI zOUXZtWVwV|q7ufVdCa2+Fjf2ggYmDj2r}qMT&k19%VwTm)Apxb!%naBG+?IB3l9@| zADOskJc)jB4LaBH-WW7N0xwasT$Gk*fU-_Ob|xhAZ|3 z&+&-pYd04MEUifoqEsp{ja--=F5`H;=2`P_-4?nh1w}R0Fc3#=PV`G-y-oQ>_)(Wv{Gg>27Ls8l^w z?fde6j@QIY=iE({fU4ZEGOJ5P4(%{691|~`rkk34ZlC*uxk>lPef));=vj@=>Lo!i zHm6xOJV{YDpPd>~onzRxE|QSU?!rDc38!AuO=$>m-p=1%o8HwZFq=%*DEPSTQeoMX z6}LQKT~#2N)Mog>tS4)cStTQK+r`?HReO$!=Rp*TKOD44}ydTR*;vDq)s{ z@a^fn7SH{0S^S`>l8)&q?AA!j>UOK)T7RMCJhOUk5(dy#WhVh{<>9h7o~lX5TK4Dv zO!in=N%kmS?fQ7XA%Zk_@k2|I^+@G7SzM95)T#8AGm( z;M7t^m$&TWz$Tsyb}*)^9?gV7FS+WeKQ3VE&?{ofl;+ zz6+~c#jTHmpP_CS62n()FOGhGW>jr^u#cU}UEmiXY{qf-+VJZVmP2qlF1d4^X)Mc0 z_{G1Vcz+w-J2Yod!eb6|o!9su{qVM=>IKB81yIvW)3`xafd<$37*K*I)si%KY;AMZ zEm5E4RhM7Be%-k0a`yPx>DRywgvaurClGnjP*W!v)CFsCGvk`dp=~E#EcE5oc#kpN z|JeJ63%8p1^5KPUH&9h#H#Ld8U=^6Sp3Csq-!>-l#Z>Oh<<--!26x<0KMS0rCLOOk z>cMfLWrtJttb7P5x$(;Oh1Zy9g~Fdm$!HKlEC8`sHdrEWKat~RnM)XVfNma^o>eO2 zdzOp|zD=(vKlNsDZ6aP9}_r&i@J@ zFIQST->}n{4A=CUo-FNw!5*kjO&nFbL(7dlGr#=#h8YJ6E%S8gRsl%XhNeNL2(gEriJi%&oYql0#ar&~0MPLYq1Nf2~582$8A>7D3_ zwOjKi{a^VbY%U0<o!dsnG)}7#$Ur2>d2}x+*3dct=koQEJr}blH|Gce64yixi;kPGCH->E&z9H;rx)=35v5 z*r9(i-|{vhskLT|)zWdHm%}e0AUsfLzjyEI4j24N^_nKPLrl<=(0+3CBb4 zYv?FG>v*yXsdX>X8&$_no}IZZ*~p4QG5!i5N6*RPzntP_2G+OMN^jCcNh3 zJ-W-Tt91;P%!z9iIE5vuZ{MpU4#1%+ReG4wd=UQMkFg zR;3tsw<|qu_I}ST{h9zCuG|P6mo#TBz#UwMBv0Q4CadK4KP`NhqnME=%g4Z73a9KCmNmwNy6EI*~ zi;0Xh`CcLa?5!s{D_qIRkRaZVh#}h6Yvf>mi_?9_o+u@PRntf^FV*Si55PPg1k2*L zSi4&L4Ks=2Z$8d)*3!@!3$xcc<0AS_kU&vzJL%edYt7p+p*8&*BQ1||Cd>)R1>K4f zp01Q4M`D+0of*@Yt@n&fKGA``!exUqfp?wgHta-0SjxalJ*tag0m_RM4!1lxa;#Zn zSo~FoCjt!~I%prg{i+w9r1`cO#>kgBtGK$+%LR6$ff3qaQ>g~ahn}79ndu=Q<(3L( z(`Is*?+z;(c4=4#NKvo~Qyl3YSh!(Ow$MJ#V{owD;>kNANfC0u;-E9D-}yS(p@JOE zudo)gbz_4g->geUzqP{6L)1 zqDj!FR@)>gqTXAhJ%E4OwxG9q+wx~0tK;suu6sXg zCf`Vsb9Agj6X1WBSM1^yofW&Xzq=e0`;NhD_IN@(r6Ze5EY5?tbKPOo_TN>EV|cWf z;%Yn2Br;2y9DKN&*od7!W9>N0bl!zJ#^@@3f}#*MAECmI+{XFGzs4+fTS6b5+UJ>Y zobQ$wJlM1ANPViR`l8h%xyB@`Ln|e3!lhkzO1kl_p1IF6(K!ZY<%L*MCwW)sS(U&s zc9q1kP18FWI{>D~g% ze)*NZe?jKjxB)*3bt)n@mL(!AH1vY5mR2mrWn+#${a%{Vx1JRFDUqm;8SSMG=5`h)CLb^WbfyG>H5mr3Z0~PiJh#odGfbDbcx-m*72_==+fB%$pxRj` zw=E}*D1yAy*pnR0jbPL6Cq8#hPhm+G+Zr_HI#*}wx!s^^!R#L}uisGbBcRSEeh{+r zO+*h+=ajOy$I&*Si!5r{!d7LAym>ltSq0N=8+-ODs>ZJzrc@)ATNRnev0sxrR+v?@ zxIHhKv?uvpd*uWo$HF;N9sw7MG{xve{vxPNGIOsi1G>EIQK&oFrnAXYC$z0q6@A5Q zZjQ`{MZ{j>7EybZ2vyn2j$bIwOjUy`@x*YcNr8~|3yp@W_LhR$F$xFeqq`38YM(cgeVvx7)EieSqG;3wZhRloMe9`SrdfD)#f^H~Y{~ z37%7GWovz)yvm&}VUn56R+?dabBZtXXB$K30QYeyXK!urUQ%YL8n+ef*!$sEkiL{` zDenv!wGZ!2xTNK3Y&d5*b<_fbHLsaT^=-`iEMpw7q3lz%*qieu0G9LH?Ajj6jQb>{ zUK_z)8Uz^~L;Lm|CffQ|`+M7kl8viZOSLrQERnvQmvtIeM$*I>TowDQ1igw*7IAUS%XY`HSz>9Ldbd?Ri&2Rl7g zjXXsg1~=g=im&ND%gzc(O+E=+jwhmPjkluxom zxu+_+o@AK!&6awIJwIC@`69}++W~8TNsZW%oZmL7e6!ztiirWPYNLFIHQ`bQTj#22 z2I;xW8Kg&0wbxYq8P!f?V@m>d3X6G=nCk$c@3dMFx`?G8W#(gTv*kH0gj2?I1Omn}-lJU%;23-4~ z^TS<4C9=cfROoz3$5b+b8W;*Jt(WH1$wSS!Jvk{U@>L{{d3WPx5)QC)xtml}pEoa@ zJp^<~yR)eY6P;Z+;Z&U<4vUo+l<|z`w#9nv_Hvg?8OkXK1}>ucgj*r8rm1X1v}O^(3~w zg}H%hx;XbLd@Z5ypRnj(q4i$`a`^SX@BmpB<6{wOXRWjzk|1;7>^He6Hs4qAYW!s} zk0bkTIEy;<&!0boBO@6>{0t`HGD3jv;>@=ix^U=8Hg~TIx~U;zC`?%a+6Tl)_zDtG zc|?8juh0X%$@$xxfBD{jRP#A+*v|yf($Pi9&yrS_R=MvwcCfMhF|B~f+CSW-$x8#x zF$!B;d;|UoMuXSJuw?Xm*d#QQumsg`vF1mHP=HaCPYyr!Pi%xymhLl*m)Sb!57%My zHJ$R}5`-g^+_qWMVOVxJeIZ=20ViDXv=vJN4yx84fNveBF?7__qB7wu*Qltd9FKn% z)&J-_3iBdWVmp}xu-kFsb@>FhmklqW_p>W706|wsp9Y77$X}MQ=^(sHLJ~Fk{G!*& z2?@fpRxne-I`As+UzbY$X5E^MDG$ zuAVEdQD|}Pe!2?Je05VSe@8%4TV+Ne>>O8b#OP=t_1xc{1_%xsYC{v>2n(G|Xb=!N z1g?_7>^(_`t5E!T0!d~s>h2Z6eu;bw*hJG+JQ|z{qZ>;(HRO3Trm|+-*27vK@2AuI z`T5a{6OeFI{Il_2u)8MG>is^V) z3q{hnp*UX4Xcn#FJLK-`ceepVvjI%cPkfj~rGspDnehS#7Ur5j3O>4v`&Zy5PDLCg z@-E1K2bg)vo6i%wvk`)j8F)>W3?%2Yosfe4@ER|#gvafdja{0cbqCP`eC$r~g%^~2 zeZ~n)~5z_tV2e*>#6E4K7@|L=Oa< zgcq)Gfo+@A8^O0;=~iYS0U3FM{GO7TFSrG=YLhLmnxeNWbY=s9NQlrHb&+~!bCDS_ z!w5=Xrrz@3RZz^;EOX41OAyqS2qd?ZVS=lUX1U>415durjGjs1j-B%WSYyhJKG!_G zCJjZwqJ>1jE`7Xc(Ds!&=^|nxi1d2;Kgj$EY$pq^Pau5|945Pip|ZzC$Wwm0O$CI- zcCk?Eoa+j|!2<;2gi#l=4k&~EtF8PmcgO#I= zQYFq9G(ss@63O66oIih_n#;I3pT@M*e)i!Gwg^k*ymFJF?urfV-S zSLKJ2OeUY_vSC)TJr$EI?sxwD#fx+_60fsqU~+8k!*#zrCy;%HgKx0Vn^QP#LF)E+ zu|KS`0=qfjNbB!A3UWYwx$~L<5Jh^e$IHV*0WYuKa=H`EXUztSFy!l3algPoMEIx$ zZ)*X;2sU@&qTn&sX6t=P0&oHs)zi~E4`sA63>JLA3*d`7MlJEIh)}_8HK=A)I!ll2 zL%A4UdB>$e(|{-ehmT1~Nwwa1L`i?CEk;Pgv^upzItFZ8T3p<_^W%M4m(7K1LI-oBn5oht;yLTy>5B2p8zxd+kT8{`0KwC%k z9Csk>&V5lA!q5N~)T9rwPSCek#4+j<%Bc!bKY=$81!FHVtH?3k`|#j<=&(wbR^Nha zdEsL@qra;(Z_ie1e7AvpDhuo|2}oQD&M&|(oOxe~+gHZEBm;+e-WOx*1uT zy{-&(We~M!V|Xn&Ei*}m!GP`CioNCBo_>;MVAF<7HbgWK>$*{a$;wN2v6MH*W##k9CO_NK%51hgUZCD2XqWu;`JR^7Fub4S zp`xi~s8JzhKc?O0QZE`2fb$~u#v{>qw^ivhRZM&+)BXCZ9cju8eI<6OfGz;?H1+IQw+J1S z|2swNHH~CIE!cvSfc<%kKsu|m=*<>c0xIhIl>`V+7@)vp>p=8oB$>3PQlj(PloEJ& z(sFX4fV7an$?Ge8&E&A8P{fnwgjQ|uea>9rmFv$p)pu=f-58yMCTBdiM2=*+ppug>V>-0TohA zroKAA$6oQZw3QLKfkR-E!O(2#=dFXk1KM#;g(--73{a)R;8hkFrvW4m5Fd@m$jGuxX=Q1stf{ibd|pij z(LL+0ms=uvjpOh^pWAm%>aicU9xT3#1WlAr?wJP%2Pc6ja~@O-gkc#)@m8=0;+Ub2 zAP!3*Lt=LJb)sS{-{H6Z1rX_~`m~PjqzYlBRWj7{R6K4t%!Q`ScFC(gz2ibXD9c_! zo34@>3^GLX)t(}2-B}P*U25Hb7brvpNBS8k^M;^-rz9bhvQ!VOpGsBLrB&YaMi)X& zw#S}ROne~_3Wb%VL&|Hxh)~86kmk$+dZIMZcbCF7tvF;8(OZLd^tij2a~V99cGJx~ zR5yV-?rbevFI9oX`5Oc?eoZxgJ63Mrg^S;*!G5)t({JWT$RhbFHAiL0&@q&OkEiv~ zXP(wx$~v|hPt|yk`@!Wl^3HooGB*01!MkEYeh;W4t-yuiQgwROB1>1|>#H<>$uqoi}9Q~S!ycWSc(9}_sPLqtdAa3_t zm_bXKwH(^tsye7ctkMW=$0!o$k|;0r052P8)X88=0^oTlLz%y5+1A#^Y0-P#@71e3 zNu;iSW|kCj0#uaiyk_)s+b!2^+qPq~kiz5F=T2Oqy_GMUCV%@f)pQm4kE$3pXpZ5K zuW8P&$b{C3bRt(;_#MJQTZi1({^Cc8NHGW%J3}VG{RLVE>Uf#fi7^li8wz@K%;%nt zxGtkX$dlONwVRT2y?}hO9G=qQ(k}qcA%GU7Wn?&+C7cG3n8IE7XW^Cl`-I3Q9t2mU z5XtRbxCO&S>V@QeG?8EU9Fk7y)^%UCu0v6X6~ZBJ-q1+aLryJL4|zf_?H7u~Cz{`Z zVBA}gH~WpZa(C(G0Mk`__laD?hI+sSw6|^zZcb^hKdEyhaDH=nq;Bc+iE>z1TmG6( zBgb);4-0m9I*H!FX;XvYQ<_M?PpWL~bR!;XYyaWXE0+u;W^< z6Q?IY8jS#FYakK+^~q>hI^}{V9sdycn1*K0V0(C!jQL(!`2Cot)ckFL>?G+{d940; z#okX2AE9(Qv2IY(6vNj5<<0Umyo0L)-zTs(U$wC~pi1sEdPJG@9YWO(*UAAb0>fSv zjE?2b29q6o#d>hx@0F0{wE~_Hm&Mw2ON41hiZp2Mh?4;Esl%m|Ch@C=!ZQ^5#-K$h zbbi!@3-B$^2`G4pn?EQezl4(d)dE;{SeABKJ&f)jcU-?wXA5R=c%a};t(LGD!gW8b zZ!C|DkR#J{90L=70Ku+RgwcWVhm5nuo z1qWkMiZr2x0Wgly)ON5e+Z!0FI^fvA;Q=nm0Gn&lXH?CKjS3SyMCOSMYeQ~pO-k>@ z@%&!C3_eFAaR~5=nN&s88Yq}lvmkmTE-pUtfm>9T z4uL(}g45;d9Z6UY88XDnDyfe1HAkDa*sY9;m=2eh+=DG}o`?vEbNQYjp$1Ny_nXkc zU_lvPg~XHrZW1u#uqy1LwGm61y@WFauG&HOhJax+&b*QZK!k7zz(@myHe8*k%Z0+X z9yPu(-_rmt?IdiG5O~-I2>j9Ne}B!vtTyw=Y_2m6>OD0Py<89?w{HaOuFujy&*L12 zLAFuO^2)~Pgk+j1Th*Rz2@+dLp*z{n2Ud^ky0XSa3R}7C4&9={JGt zoAzeE>x=i?ckatK4T*BVKaT&I$qvuAu!5ta%l3?CX}}}MX>eW*>2haWj%-|?Zf{+* zBwYo3aHn{J3D^8i=jt=7q0*@Iy4lTIn!s8hU##rqD_-c2qcB53S8v!*x)0>&KSvZA zVZAr$lzYpb2bx(WQ=|g|V#d!lz7`64gBG2sV>epTN zzE#o1^V)$2w*}d`(Bx9W)n++LgCUd3Ag4KdiU^!b#O)nGc4jfXsz~om4mPgE4xXoZ zvOT-@?l+K23`Wk40E#gmZG;G-jLh+yX% zsRE{AWQe=`=+>{%XH(+*+PZ2H>M?@urTp&{*-s%Y?eQdx+Dd1T00dt93N2&$?45Hf z-FKsN4x_N#W}USbGGEe`=5KR%0`!~&t%_^@C>X*U^f%^hO|eOi(r(qb!!*zafD0=d?wUHa=zBgH;j@(-ZjDu8xT5`C^a_k=dt z52UIXHiXv!f^Ebz^WpgIGC)D!3z^Qpt`EOPt*n8rU3cf%JqE}ruPA00|+J;Wm{6(tZoVf=5xcQ_T?InM6lESUkdmIU?67E5w zNCpzz3m>FxZEbxCGs+7C3=ILTD-~Km#DIyZ{i@ zexTCbH41{FjgcH;yw<}OfwlbjohQ#;l^Xezk{L;fK>h9Y4n@TA%|WZ11Kuwgf{Izv z6+H%*ig6D_L{LbkM+xX3;KKm;$UeoZhBPj>Y{Kj*!s!r5*IR*e`p^orPlKjto?Iw% z9V(@(-o69yz`x5-itzEVj#R}MN?`cL*B}qJcu{%(EweB!J$*gMt&<22N3y7p)kp&G zU@8*WSj;CVuafEoW?|59C2D`Q+&-|Vrbyo*L{I=+ z&JH<>Fr?L!Qz57?Zz6hlZXr8fDpk*UruE(5@Oni3()d;TZEkI}sABACg9@8}4Xae% zs`$hAqK^9fqaX7BqZ06MpV)wB{}-E@_TQ@nCmaaLf1m#_=tcVFO(q1=AnCn(8ESWB zBG_1wIfS)0(8fJbWE}xf7iGlOId|?H=Yvluq=AwFbbFHSem9%feuZ@>0n(IeZ6%)`+|y$7BF;bj00r9{1;?Wn=p-38Q#wIiI7;0LU9T01}0P{8tC&Z<5{@-*!k= zIdAqE8-l({e-&v`+CZfFATfpjQfRFRD3nioCIfN=>>Vjcyvk{s_Ik!aV#a!7{3om@f`Ur0)Mya84M4ojHr zWPM*^hsjJAM{?0Vm725Va%9FC3PCN1_QzD-zJ0szx3nli=3Njv2KW|{1Y)8FAsZvU zxje$YT)q~7{!x7yAkMXlmBRnjB1Lpb#}th{A$wG z7Rf@wfYaj<5VT|;!kKGOnShxitSt@jIX{0Eq;xnv_uXzXAr_Fb*i|AT{eG7+NFpHz zQ%uuAvx#~D#)jpgWJ?SS#RKB6jkzWONqEvlKnIaPOx?x)0|1_1cez z4B3*}z_C(ZIt;yVB)@ZpelewT%oge~0+KlGXYTxNDi?pq8iGku>K5HBJnv`sG=uoh zafae2hj8Q3>1EK=+=*f#vUuv=p+io{_&>3O|E~=F9=&TYmms@O0(XnxG_02bt03QM zNQ2j+_km;ww`Ko5QBhG&3$)96cA{ya^#~gr5J(MWQEwka;#(6CM|VWHJ=>`{%5tZl z50MhYqFE@1NP%GC1;J|r7$;ydlse4QgNG(FBJujNo}@Sw9YawY8JU+X+NJmC<)dk> z%YXWQ{r0Vo2Cg>x9!!Ef;}(#TN~IurnFPW<{inGFtA`KYqpAIy*Cmh|174t`xWUq3 zNv_q90Qjvhx#5V9M!pFZlA(W1cC*`CAFc(Rt_zpqhRvrzl@E7554s@QBUGngxS#sB zBF{j@qj40cg-j*{mKfm3Q{kb%Y70zI9qhsX@K@oWQ2wp`U*on=@}fV@J0n7w#WHYh zd0daRCcb1)PaW^k^7HeH;i~9p*5umm{dzJ2bATGA~3IS0ws7-{T}-MaD{6FoKb4bScWoX<(k)B z{7B!f%(R2vE}iEK!j5*y5dpI;%8>QT-xVA(Z+F22yw3t(${u_^nsztQmyEv%vKDrl z$ubx1u7DY0-ktFVB#g+y_KS?`-lYiIh<{yOUENrGfY<=lbRV8&hl`nDmywf2-RHZb zb%r41Y4*KfPek=e>wVfnt05*3k>1(QbxI?~5fEIyni*SjQm31a3yg@u$Zt1Q3t{Od zck@xC<6%g%p&c|;eYu*R@ z!N1}$yy%ji_r--e&UX@Q`u^W*gfO9-Vib`K(WVMw&VO+=*q~N`6gXIY$XSl3mQUm# z%`-zlETPnYT{gacJlFT>XgDWS13Bh4Bje*-a( z+m6u>peMe)=KKjVnZxZt(lX-mKklCqcbVkd?-7-FJHq$3c9E-|tjzSkPJdakyHKCQ_CgU-;eVE!NCAvWFhIch@dMQKQ0kC zHTD(a;&NC_JZ0+SdB$F(F5OmIzx1cCk~>5Kqb+G9dhn@FVtwiqS;T$Ph-AIMZ{vQ|Jpb*fQFE-RBr3MyFHNxIdJhD<78p+ncwIl0G24+Ev+-_& zWf(ey41@q^d3jYf7y9%AQKO1I3O!qX9#4)3p%IM~7$kj6ra~lz|^k zm#C}abUMNb5?CXIH+CXwK%mjGD*q{wrdgD=cw0mQ8K_#E%!~Wb_YJ|pD?E9EOyu$j zIIbF&WYYFN*LBMZNdK=NT*J#Wsl% zpbcOgkvM-aFk#*TfaH0HsW==PUe@Q4(Amr3xVI6j9-82GQKDpEKh2$>95>Qa+}Z-H zf`Y?)ifKR}kTdHshFz#w%eMEoZ6ONZ-%SF!oN(lbNFnN1M>0+xa*iCB%PY%wZ~vfg zp%Tcd`8Uqp!>=RNOZdoJ)uL#AyA;bwii%(rX?PMJ_fD)8mte;SyI@@RQ~`&FaGB82uV10$m}7dxV~T9C8>;!y_E z$wu!601Erx4PkUS_2{@lQ)1o>xyLi!K7U!fc&3VE$oZQc-N&jAS!Re1RM(O zkXUXHFiOA~AFwKGIzH>|eSCXwttA;A5h0LV9=}%fW_vIR8EQGz-ksF9UrIr+qj5_W z(MXFB5D=B=0f`Oyn|Vk%_1s^hh=OcehE|DER_PoQQ88E==7Caco(Ef=NHA>;3)V0_ zfzVzy*^wu16UR_m_h8yLFS2TMLi{f6%mAE$o{r%%4q)eD+(FL$x#qWQfd$-?dQcV* zxXYAXtGG3PYjME1f6nt@H(?ezKx|qBhkG6)P!GHC3)zo781=mG`5PYjnOpOU6s`bl z8utN-xIqABOFmAZEB`(~SqvnOD#4kEEZkC4K2~6wj+~@fCquh*ZlZ+uA3*kZ^>b#? zu$hr1wg@@M4YZMtiAhH3OA=ZMWSs9yh6#K$ZfqJJZ%D(FVYflHfDM#BJ}gjpzM{T& z$rlhv-TBGVRb1&=&fe1FDlVbtRdAI7^cx7sL=GTGP7_tjez<~={|vzJ_`W7c^b0fF zrXTM*Q-&$9Azh>f} zyK43_4-p5W$Jdi?1>)GE)fLP`j!^aj@S&ubF*{vXS4UC^lPwLro*oujf&J2;I`}1Y z3GSOw{B4a1&E)3WU!l>-`F(-XWuYLx#%Iz>NhF2%Obr0lC*d&j8&w_WZ*BzIBBH7< zFY{T&TJ+~jL#*e4LhM>aW(I;g5V#Woo5PyQ>{MT#XKd4YZ_y`D% zZ(tYpCxZWWcxNUyof_%~@)6`6xz8bKRoj**DWADW6L^an4t&I7KXPjry){2;UfdNm zLagH?0u91Qvcn`2IVXeH;Uc7Ay!ZJeMdZaR>#j&f3oN8$@ITtYUWe>gk#3Ykpey1= z!RjkYQ?=^)7)Dk%vpt;<0bNc8QUH@hRoG0tZo8>QY28z2!Pk8e&tbfUv`pjcaBA=$ mP80s6+5J(QprDCR9}qOD(XwAX>s1KvqNHyth-ZmD@cMtI;>Pp< literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/FNN_Accuracy.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/FNN_Accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..575caf58a7502d104198879efdbc8eac021c3f26 GIT binary patch literal 60265 zcmcG$RX|qT7B-BcfJiDODV-9cAgv%N9fC+B4I&|((k%@V3P_2RG}0;EjdUnTO6Nb; z-sha};{R^H3%3F<@0x3_F`x0ocz2MZyd*XzDJBXE3bwS=Q)LtsRCN@TtF#zs@SQER z`Dply&t6=^Ud7tj-cjGy2t`ic{*9%zy``DKT?ZpuJ2UIo-0ZyU583XT+S|Xec2ZMcz?)O*ESQIB1I zrffwd{iOT+`diY~L-$lc0Rg+!8G(}MpL}+`#}u*YOqjQVp3+20(II~^6Ri!Vdj0Rq zNI^`gMVbHpFj7j^>p{UkulwiaE!X~^{!k{U*sy(Jef{NUcaz@aAeqej8@`mZ2OCoX zGMNUmb?*Le{mup7`S>X1s+c-EvNx0tq9?CB9y!7CIyB1^U`sNL104|mB?ox+_2En;W{-ckQ`h51k@TlDP z@D1C;TU%S{r^>tHIWnHdZ*up=vZ}+~cflr9I&6?Wv>0U@IYw6CEJmshOWMVwl??Ab zxcCuC`)8(Bp#3C3T2{8Dx3{2wQA1Oc$jk$Uh={25K3(VSKA}VMt(w0$dC&7ZM=CXI zT^NqR4*~Jx1!}s&=(~ntro?vY>O6dhUCeGxB8jMGNUOZIo(ghvR+ujUoj88p7Tesp}SZ)GLd6?c!%Z(3SfZvXwe7_aNWtV%hy)Ddm-=FMF$ zF0S_S`R0JdXw-kdU$x0zW({){d+tem*4bj!?`~B`S)JGevL&bm@qdtceTCa-s)PT4|*tt0FjA_ ziI$cY3AeFq0kykHUn){)!#PT*WMpJDH8mt69)e0rO8z|DCcR7f6*E^q!Ik~DmCvVb zyQ->f7SVjrakE7IFvlk*2D0SH%B`m2^23BZEjK31+)jRHtLAGG!W&h;U2iM17{e5N zEySu`&@wU-oBh$_!xJC0V%z0Tttla=Z7<##CsbWsUD%vl%`%n@$q0t~_XqnK`1leN zxlNS6J6ORM<*4S~LPf)xJK0~KSUG!RYW4cq5~;4nM(_2p!lCbu*5niv*#3JL=cjiB zoj6Cns5MVcl3H6^&p0h&M@2>1cApMrKEt|m{~9hXuBDY#u1Yq}R_!4r%H`Q#T$b2i zxg?(DaclUs990$^Dq*c(cFd7dl)97=?Ws_f259N&=}v38*(5xcBv7F(LqoT{=%2;G zhBm}7tGs#hW^Swg(zq@3PD@+c?sB{?(fHOEwYCJ06(aY^rp0B3Lt>A%<7YTE5MdrV(xbN^s;{ho)K0dzS@lv#tlM|==i9I}8 z3>+L|fQRehkz}+Ip?ZU#rT_0Odz?RdGlz0{I(wO;UPzh5V`b2tz{NMYIa8ZN#`~J{ z_4FgCm`9!$f;WlS=FX1)lJnVKiYC&k^qzm$}e^4}dc zq-156M$~m%dwRk$pT+NXbN3ZNA)g#>eat^M`RMMinQsi`+tSjqjclGl3r0AlkY>)J zc9ktXR6;{%XD}QPWToL$BJyzNu&ovr7k`fz(-L#&ygEDDd0;Ub`s0UGx#fhYh6c&z z=B8gg=9ya8JMb6_YY#|mY-|8#lI&J{=T}$N$0HgZySVTRxgLCmeRkU)QTOk& z`C0vzj)7r!A%tULWu*;pD}mRVQeR*H>&uGXqRWXA6Xc3uqdoc6n%*@PJt*ZO&&d92fqiHoY`pfwlT~s@sID+TLySrT+thk=q4x7_2uEc!w zyx@~OgcFI&aY<$rF31^4kaU!pEs=hY#6+!_4fn`{j|6BD!9W^#KHru^p zPW}}6T;gOS8XCwAg}Q@oGZH+WsCBJKXIii; z&@B71J84m9WWj6LhIL($=k;_#25yQxa$jtkrBYX7s_a%*CKxLI7BVGXqQ2Mr zt%3#@eqk%HWw+9;q{((s;jj>!6#@2xWuBqy;f0YQtomW#F2`nrumH|Nh-@dHhOt+x}}<{?1w|ak3!NydU5u*PfP4Lv=wj`>b%6LiwN!m zW&VX`i81y)&C*W}8^{cDNvNt4K>KZJZS_;hmcR3G1vp4?QPCWnwFh5^Odr(j zcCzwK8dLBB48tj!EHy*b+pB!h4j36bpM3Svqeq-(gLJ@Ds(>Yw9{|cUcXoDe&m^oH zLz@H=GFWDz{@AS-PLfg2hldkQFL*7-z3S^dakj!esNBgM9S^noRBSrYU!9Zhy%O5G zapT5Q35mf1Z2F^PAd7DWrC~RE_!UZl6T7j|=geqO(lFC-|4xo9@P8fD*q^!)TN zY(~Al-eWc}5CdrrYTm40?@#xqiAl@I7yy)bVGvH$xeLHX^Gtt*qnYT9ioOe2Jioaq z4^XI4%PSE|@lK|ul95}-WNWgpKA|E+23vtp~2F_My! zD&H5ceO;<~&tmjzn#EYbwd>byHYOhyXn&UgE_VYL*JNv^*1vqLP&XUM%khEZ`3byr zuAy=x;mw;jzdXeU{X<T^^6Gn7jxd`&-z4E^yUeSe<9nqABgVvd#l zG2Lvdsd9K#hH@@+gY2@JSC?tOV2P(;W zbGoYe!$S*=5@WgW4Im>+9gH6zbdc{aEjPMo?1@K|mA%DDbjg4IEP_%fFg)BCYJNEX zC9$ik>+7G@t>eXpA@(zp5tKa^g|!mUQJ?~l+o19|YW(FvcdKLZUvA#w`)8^mA}5Cl z!5ujsK_;dg0+U$j)?mWo;^Gc9@m><6DrzzR?Vpab_+(^VP{`qcZq!)ptgvfoz(Wx7 z^i{Jg7@t<6$he0z)$_tRWA(L_RnMm7#C+0loZ0E95%M&r<}OV0lZH9zs)kpozH_&UP2K@KGJ8t!k7D$AVqFnDK(}QOyn|R-E zBu_m$CdM~2)2KWE4N)O@_t_KyJY@rCT;GqpeE;D?r-I12s-{Y(zeGlw>*1#5Oikic zg*Dlz?stbUz)OPakMN|SpqhZuO;p)2iuq%8l%E6h;}c|%`|#k(4QAWXI7{7$+*LAh>k*!F4c>rlD{DIg6+1gSPcjC!XFV^Cre1enO21y! zRwAf7-TZF3At)&LYdH6I2+_TTm7b)kUdf2>-vtze_6b;@f7Js_1y0!YX^jb3gWnSu zM6tH`mRgMAsH>|(+iV625)5YxbQ}YA7b`o$*$eA0(m`a@94&+Z_3=2GMBPMR=?h}k&KLGfeo1brlI=%x< z*1C3|2n2%3_FN-~rc~J2+Y}T%ara&x9j|`eIXpChLIwH~%B+(0=Fd16zr!CXfOFS_ zKl7RKI_bLg9)L33PTP9$i=fb(pzuX5&!PhZ14a94VN*cyalKtrg@5@)N8cvnvHbC{ z{mNkA=WHoAO>D6R~bziEGYq0(1i21{p<(BgRxh8;MAdXUW);ZM&k&56L+#)3OOG+X;J=|Jt#uY&j ziA}pYCYX?QF#jd5&zvtb2;f8hiv8GRJaa265&<|Aro%arXgNv$&(-cG6Cw$7b+V`>Vp}G`}vzC;CLN*9o zDB<{7kJJ3pY}!bv&O7&45#NbY48ZGKZN1Ar3*cHdz-1;kbP)3~~MG_xc5P{AS zXTM;Bt62Zrz6JdeF$t(^cetsI7!XtC_exCq;{0Qmij6MLj=yRYzXRATdesp%m>Lc) zNVZfT()R!L&LR^~67A^!`-K!8!{dLb)_;C%aP?KM8aq7P*RyqD85y)Jv0whV)Bo6M zGB?DP07)`nBd!y@iEmS5pRRK!v$ozEO!fcY6_{y#{ryQXvsV2c6xcQn4B+E2_IGsT zs;)wNY18#QZ;e(E4uWox+bgbo@qR4g^P?Z@lFH;u`?SnByC;zZgmzj2P%%!fu4Ix|gw=S^wLZ}iiCVZ@NF{B9yiZQT-$`cK>h}bt z-~mA+`sbc*-wk8^&p+WWt}FkZ&j0<;t{^xto#}IScE*T#55K&oCMoz)P{m2^Y#kYr zN`+Km54bWs7! zo%QKDzho{5TzVx2zw&o1mr&g2v0oBfiae7p3J{XaKCzPl;?zoPj6d8RSd zHv5YaB4F)>goR-Pvs(eWzy zKnhVM0z0Zs!=S=K4mdDYX;WKM6}aFa00-~pVf^nS`TT%MZE@{z*3+ajhS}|CJ^&af zrl+T;%fTP%r%#_2Y(Qgm_c&fA2E1+u_u^>w@Oz zNUYEB4sPfBWBxpVRY;o=Jl`8SIyt#-+J86IZMVZs$RGmMadVpM451>>hK*kG0`iN! zboX9rg7&5#W1b!xO9+)j|GZ=!>?A~U!0*PfYirUNu1IQXYMLoL`R^%ZkdX@(diXFl zno(i5S73`|G9m3ZF>Gc7Hx)Ot2mJcLLoSD7AVaA?T+Zx8Q_IyXKzSvPJoya8A=FfbS| zHB+f;KVL7bzwdVR2CVHCGV7Ygm)5nhR<1zyt?SQuJkR%uf%FgOsYgI#8K{11fr4}{ z=z5}hdUru`*#GMH2Ctbk{4H2%f~S8<{4ZEka~hz25bf32*a&o?7=(?-#jyzj+0e0{ zf;Zy~9dx|jQ{-@KwjBrtAUiiKK}>`{B^)T+2PorPq@=;w*^JQ)atk0E{@E4hwJOIg zO7NE~r^>^Cf7}^eZ`R)*`^p7qOdw8u?;duTgyC>qlqBl;;YT;7yUdsfSfV?hO9cn> z6;K$SusmF3xqtsw{_~LRY?Jc+)YMe1YJ27}cQ{HNu;Smq(7>?z1N{hYDSgD4ln00y zBM(m;IJ)Trrv2vsxV#Vt(DYRS(+!9aK4EGl?42iG>ph=b0)ue5~At7S<&!K6{8W_+Z z=Ue1_?>0~#VjU-M5Sl5lpI5h`@q+;^gOFnLv4S2ruH66`;N=;X+fXsEvxfs+Epa`3 zjrHN1R$Tm!6?)&%s*|~jwIBN)!uGaO?6aoP#;rrp?;YdZp4WYr-ec-jm zX$YY5`0>rCD?!K=NNwpna09Jcmsq%zKQ2}8ly!X%ytt^m9Br;*)&uDwrKSTkV|KTQ ziA}ocuLh#um6n!11FZBrcqKzA=dd-SJ*o0O#_<1iP8A)2lhd&##e!fAPrxVH;kRjVjRz<0+%1VYE=6aM)144kv!FKS(LexQm- z>Mt(@z+1ek2VT`vadDfoBO5rnD39UDVVxqIgD`A9yA_gABO$80g4r)tKLM7lHiMah zF?Yjzbpgozo-AX9dOib(*9`(RK}Z@<{N0{sTd@QijGEd9R^B&H_dZ5m?-TJ>4=Ea*BO` z(TKN_kI8%B{-w$q4rO(8bc755*#5+5Kmd{)#jXp3)sDz#p!5)65^@9 z>uZ2amE(`dQ^@TI-acet<77SYp!BeU^rV~%&U_-D9Rmaui*QhYDS_C3YHDg)?r`!q zt$lWOc3a2#sknrMv4F{mQJE&t5{feOk^6sit89&EXlNAkM!^2YgMaRO3RW);iUK)eZ|v=t;M6~`nj}E%#6w&R484VxpyTk!{RB##Y~5Kn zJeF1qL|GC}qt`U6kYam0iz;J3}g3ElEDGshvq~HAL z?HU1G#SqEzCfCKTP+f##`e^1$WGXM8c;0occ|Yd$KO!1^)2!poI^9vJ&#g{4M`ZAo$r}yc>zsIg&6oY5mDPhYl!ng5aagF4)Yt4e@WPKLX4Bf zByrrHKdngYfhAp);umvol`L6(@Cy)G21gS~OQPPtZ>Y3cL?ID!vFB+F0lVm%&7uV4 zUyWeY{2s|8h8hCcn(EK8o~=VHFQkvn&FKNswIJ^ajXa87zTN$%}V#3t5>gLdBUpZ;TotYqD&+Y=(^N&1x@2^C?6TL@W%4aGAaJu?R3B7q+$(!bl%NY!$5U3dVC$Sy_+c zAJ}XptR-UC`T?33OF!XX?nkLK7&U*0j~AEb<-RRYEU%o!G?JVL_LMF7`GAm(u#aZo zM?&KJAW&<%#+f^bm<1elK;@4B6_6i32A>WgBkb(#{ye}$7kzMr=fHb_v+xdJ_Alht zoQ7?oQNlI03b2~-N*h{0N^yu38_}r}Mo<%o5nB{8i!|e&4`5fuL&ezu;}sNg1aig( z-d}{sMFKb_##0Ai<8eD~YW02;>4V%R5lRUWt;p{}^GFtU{{R;p0-pjxaxrKG{=m$E z$j}N2rEE-9a06zcq&h9!Kzb(Bame#LBXCIlY{|yHsD(hgwENXht);D^R>!iT(*tI zPRfPm`EGMlu7Xk%#tzY3mjVMgC)IAegU?|F1d1F{RdnF-l9xHVr} zR=MCNk>(1JfaqjsU*NuQD@6WdF%c5R<~1r6>Iea|YzIQ<4-6dPgureQK98U%>}U5~ zftk!_#E`YMgUy7P(F%e)Ps?4*K+8Ua7HR)yJaRSFH5?LXqAx3B;Pohg{P{Ie!U)p` zja^-=Ny!2Y=u~bEh!X@29?4t5P3lq7ay{Cf*U-@51aipyh#Jvl9T~y$=$y`w-w79`W+Y+*4ok0 zVfy5qBsdz9(ELd5zrui}ux$K}AwA*OYzJe0=-0j8eU-tn>d$`=BL(SdKfhPVGR6N- zP~Ty~wET$K?s+{H&A-5_x|aIkl{zyF=>bkt{0HP3lic^X6BZ{s`goj3oGaLw|N8p+ z7C~TCpjCx%W{$ce8ko^QGdpMxD=mEhX>u2`9}q9gv?d`==dGa6*TzqaIln4CxzzR5 zzfQwew13&MdtvR1&%k^eCUulol=4PkQpOkd8ZjHef(9c57xV+`Ms6%7IxgjBsBLl) zk7Q7LRsS_7TFA+d&~Um5yWCeq7aJ!kDn2mn7B->IYtGPUL`7w45#q-QrUKuz1KV&g zRU$DBJetdZ=4T%Gnsi~LaMtpaaMmywRn0*?$@@FhDaXyoqBZH}x& zK|z`Ge_jRiI^EBJlJ)zu=mh~SzXp>cTK1;L(bwDFrC-0C?_an3k&$J>Gg*(8GuMfO zQLncmErTigKU>Er#Y^pd>NP?#FB95g@}h60CiGl{Y3+LZcAw<@s@>-jsXi6at4>=y zIX7w9ZM5#;5tp8S-}WEJNcx3Db{7_^<-TBP^4++IONMgkPF_b;{pGt-&%8*r#ecGd zMSifOn87RbUZ3{}{JqM={NVpAyG!emY!ltPjQauU)v$oT<8Mv@QJ1mP#JZc$i%$Pnv|b&9C+46MnQ(8gMO? z=Lk4*%}UH@fw$gI=m(P&j!o=(IfN(>IX!Yc_&RV-2{i@wE}^5#L;?^V2p&3$FM#qO zJ~aacD+hRdIf`jl!H@g=`E$&Ve;dZqoCl}Y1by5~;g3~1^=|td0}{%0ft47~P9Iy6 zRF1rhOlla-baH>bbxrMqn9F_g6zeE6nNWx~BS5Lj>Vcl{_48XEF9+LKv()qn_~~Jr zW6jN|knXF<7C(meSX9pbF0Tf|a=geJ4VzREgtqcw9CNTJgr&K?|2P7fEkWX5G@^CW z7RCjRe^KihTgn&fV@LnciO-)IYmCd0w6Y6xx^O>oBBx7y8Du2NJ2a*XVkZ$Va=*S6yJ>MI*1A~JN0Ih)KT!*ERJ~VFu z%>27?IA7EN4R;Vyb!4VTw_X^Dh>H74&4zNczwgCK(ig zgsQSMCsX0v#KOW_3Svxc0ON|6mlyW^sheAk{wd-&9ZZ-UujLgYvqCWOR0GW0zj${M z7=Yo@kH}DRzNlG`uH%fi7iZ2e2jT;UJ*Wo+j-fe_m2+s82EvZ%!2lN+t_gz9_fbHx z!&MO~VMQhAB7~lG2)D;K3lyRyC z*kuBb6)C_z45X>RC{rAVZg@J=FvR(Vbtfz@PrbZQR9Of?WwCB2{{wfv($D-=x>{}X zg7_*bx-}eK_&(FePS?aqIsiq1I8Vy)Ao&o}BmLbtu1rkE@kbkau*5+*sk~ zeiCMJnvU4grwQ5^0(rje-Y+F+Bj1)ye%sjFgIi3mTA-EK z(D0Z+J~#6SZf=}~J4F*mqy z%_P8avp}A~W8^M0`{%KhKB~u$N^hJXGhe+msr#Mrk-ASp(wo1*!3-fX zA9Hbjs0+hbR|AvQVGLp6&!5ne61#G;EkxylJ6R0AgXkS~B(j1$6q)bpjP)z#gRjY* zl_6cO)1QDS9@qw=01#OKV+K&84gXj)g@WyxAnkz%KnRBA>Z-4IvE7V|q!#d)$YCY{ z1vU(kT96GP%-@1&b1dL6uB>@Aa?53Qha#=jZegbG;! zHu_cjdmK>cp;}kR$H}wf8u&zvH3K* zG+i(nXyq#M&hV!1oVb2)uke>?VeAmskoO&z6igcvuWWhoMnk>OsrB@4o_lyn_;mB? zWHfH~Sw{A~H7=`^priMHP$27_nX*ljcm>#zr53q-cz6yKJA;XtR)Go(g(1`t++Cy$ zwIG*<&hQsPFw{>Y<_NEbaz>`Dz-xy#p!_TO3slU)#)cK=R}@47W+3w`y&wYmfHwz4 zL@){oQ7|$xW`r-pHbU8vVX=Av*UA|BUFmlGt+CP^JR(xL65QftZc>2w1 ziU-Ca#9-VFOd`-FxACYwzz>D~wK}N_VY4%wju)k-_#in9K#4;O<8<1dGw4%8wwZz9 z58brzby8MS9)>N49*O2UzBi00uTy-#+}nM9$`rkaG8&FQ@YE62ue3_8_ecCK#y3J| zTrUXR9d_`Q*LA|W1+x4IOOvn!vYQ*XKK*7Ia{WQ)Ok)QdE<@k+w|n2jEdKO_Mlj_A zr~XyQRPTbn21jpkb=9Qu&L!9>$ZaFAip*|axpD<4dNj!T=#(!2XWTF-=yJH(gJh|2 z?wuh{mgSdtPRZj1I9u(8$-W6E1fo9#ZT=O=$Y26OOC1Yy=nX6^l2$K{tx&PhzD3dN zvKNvUef6hpfZd%aHM@=22q3MlfmjAD+FZqIYWa^?h9vzxOaj2OgUH!5=mrw#2DM=9 z?XF{^dDXhkZ2b9|HvhQztg`bPE9TkGw{5K7K{c8#f3NgsH5VK{Wzutr!lOzo?K|_2 zO*PJFEPt2d=dcqIbw}l@)Z$vP;g9#!;J^SJw}QBVsoWas%eDWTUX@8ZEda3qhBshv zd(kG?B@>e{|BOLJMFp@ggfIqpo)|Yebfl*{J2CU0zns%R{7Y);#-dGlN4N^i4XOO% z6X^ytZvz_y0|Vp70Ss<&`V@%+*_eQkv_K*f(7vv&4o&QjzM!Blsp63z82R+Jvd9j-#E$n-9y8;7#VeFH@x0 z^{SgM1VeSk7tSQ40w2uQbh1c#`ako0H>vCtfI@TA^U}cfR=S?J=c6+pr`dUIl48m~ zEHTsMU;m{2D+)qyJ&7j3HPaF@M#j_N0na$EQXo@5uq^B;2*+B%LPg?dm=Ilp!Q8uo zf;Ii_u%?vBG7Dse2BP3*a2k-J`Bnz;DiN>s%qwsNwdy@m;KZgP_N2uk%zr>G2Ze_W zb!eKHw*=xtfXs>feu_Xl%m*~H7S=T7C}m(#d$%D*0Fn~GjG-wMT6sN~O(hWYre|a% z0>^;l5{rx{6ehgi?60W-JLrW*bVVt99fF7z&_b)gn~*6h=f6+O>|efo35vTJrUKjG zJRHN8mMni-mi&(`01Hayv-1aS$(}^q3z!c>Xq?bPc&uk+VZ9)~yBs_ol48Rg;&O`P zOd1qamA@5?AOwAm;j6_eWme1$%6X}Zr+dd5pShCMT&wQu7BcCbF8#o?f=7ulX6yNjl}l)_(giCK&MpKR*&wYa zb~9!mmV?;@379HC#$qA2LgEp>P4)ceC1yhm0FnrpBh&ysq+nLg(1XX@FT{aA%W%sKS7REQo^_m2c9hui3ybvl|3$XE3(=z_i~BCZyl& zn;SbdrHh9kNj`WgH5VuA5X>?9eVB#QW%KrJCiGsUQ6lUH8M&}pf$$%$@ANw}KIdfx zJ4em-)u5oDiAmW6PH%vxwy@|M1>kfjuk@SEAJG&~n;XolpzO`$-3}3_ia?b<)c>i` zpZVn61H@gW$z_s-Agk5=29%KT4hoMjCs;8dn1n3HZ^bZ3nh~0q^$TZ z+3INaeN17u+{H+QNV&-la)XL&IelMA)jPV7RoBq2$;DnzX7Rb?R5Cqj;N717Fqk?( z8v!4wiE8(S2?=ifrfUcT{bm&LLbmSd?jyTpj`0)oozvetN;{|TmlTHIR@M}qKEdA?EKMF3fw2n}5JXl4E=#BsV@C{9* z;Fmv1v{CCRwfb{~dK-Gv7yJ~yS2tvxR7ygl3sL7ct{g?L^041~2GpGW)J5Efxp zyWgd&q9U~CAKw!R#P-4T=s)~EeO+YQ!h}?Pg<&DxDPN)ioLW@Y=)3yZNv0d`>akb*GrdE>6i>PgrWPQ)=%EEpFG#XLJ#y zCl*>?+@$H2@lu{IyCCgqNK6q^VZ6FSwDOePeO_)B1u=~?MjOe@=po(DlCCl)Y{FF~)tF7zL3~y}ccvD#4ps!w8 zd`xRiB`fnwN$J-}6WWJRCJ#?J$%fgFfo`9YBpb4mi9;0v-@RRIX?`c+lXg6QHf8d# zp!?4AtV2z;ZPYGX#cwSYsP^tu7spRYI7Y+!Emb@EX!#^ajzQ<9{1SG3(^aRy8PH&op}lf zC@eo*v#DszXV^Q=(lg8z#h#aw2_l@Km*hT=6W6*`Xe30(>9allN{4?o+%YdS{WyQQ z>ATg2-i2uUZ)Q9PEfQtkgU0;m1-p?9WfR|f4)~sGFJo~HAL4$tQM(2lF_uLw-Jmu2 zb7p4Z+pl0lKujnC;{bHcC3OD`%nS}HyL_dK+U*RlpngdCrQCOAQEn(ZmZJ3d7O8j7a;1MT{J2F%5^1){+37Q(2_-8s1KxMK$xg)?)Ret8wf`uAdP zXINuw#ZH9g*+yB%HU@YmuP*hVW2uRV>)91yYq5*&d?oi4&CFFIm=~YrR&irAYR!M1 z#kD+j#Zp^V#DkeSEYIN6fN8e}>X!jiXjbiQZ4zMSWkileJl##O*-@z6W6Zhd8})&? zx#Ok0FY0U%StslF;P`g>j-@5#{>&SOk1T4l7L+@5olu&>gSe_?xwU8MpZXnj<)E$v z^48X0EA;o9ov3xlvQevzc4jbD#AG{d8`-=$|3}c1*vp=R&Hh7o9`^0|X|yAEy3lEi zx(zvAJFK(P0(JzkecFMN+yFR?5Y9^6%ydRV{{67K77 zIYW&??izX%arzMo(k5+G>6Gd|ouc|S%R8KdsfoB{u1{RPDXx5f+xY;s&9`wu2e0U= zc;?D8BZ9)`$0^@`t_Ha^NRAg>HACj?q>mpbv9Ha+P~XlWBcAIsU$M6?Q-X%2?spzM z$8)(Rij!y(+8)$3)oNnAii4f{(EW1%)VmhF<)`7f@VnYQ;T~2NhLwkTFQ~PR#814$#aVqVU-!id)AiSuD-N?|T=Q=&T2jPADLHxA zGBFyZe=qM!(VsV*8k0@iBZ`@PbmGn5Jn$%9ojnewF`vJ;jvf>_Hxfwulc$KMngM5& z=t16!sOXnCJ^}WfVaH3GZOzX&BEDHt|Kn^kuWOy$F1Wmx%C=_xiT;+*r2Y5_=_ib| zpbxD~k6)5Z*0K!O7F=9+MC}n6&5&)O$C%;hHTr9_LYCe7h#;2q-J#w2nN4Z6t>WR@ zt^-PelMpK9+mO)!*LyppWN6Gg#}(IU45DuY-KXK7)0yb2kQrNZG8uYdkGZ#BC>zgD zc*UvU?ZaV~N4B&dSm$j->0Y(C;LnhFs*^|+SKJg)G^eq2x#A$-_r8nj>f+_XcNJz7 zEbHZ-lgqNjt|wtOB^3)NwbvxhTw>zYQx^_=BnvsKpnU_8X3LQ4iy1+CR8p^b6WA!t3YO0Hc*EDRI66`7rY`zui zNqp?CDe7b|7kr`1#KbN_PV;oMuL5s66{WA2TR-MAYX z%)QB1l?>mWMekA+-KG7xQ$eJlzBS$fP@-T++@rpR=hQe##!PK{LhK zc0WUTPA;wA8ktlnpfOP5O{~ECU@hqw?&gCKdS){fCzt8AV;amP&e zX8BNaZJ2o2TgIQWj*=4`YUaF_xaG8R?R(#p&E|6~?+SxT;`k_6*XuJABvRZ|>MZ<3 ziY6U*n{{|v*U;QK%D8pp@*k<1V?F#Hav~P664X?%oZ!`uUODk{Ub|7Y%G|}Czw!vZbN1sW znXpCg6pm-FRT);Aj>*wtE;#t|w-xq&QnYZXb{%oEeRmLlQAK(BgO$9*IgxXU|14HD zzBXw8g=Z-bYs5@T&rEPCwqM%Fq?8ydvs#y*Kr!0l@^n5)fkeyd?>i;m6iv9xzg-C7 zmj%f;+{?})j~ISW`erKU8!!L$*An!2POScQX*gIY7s5_nTSMF-W_fCgCF!VPUn=`^ zf^Ua?;a3@Ij?}*y@n%P!ZR<7GtNC99>=GCRFto=Wc!O9`t| z`8G*))0}tho!B4YkLRx>k8>TObL_JU6d(ANBX2M<#bHBx-+Le=d?3%8m})OyA(jp8 z#eY7ouKb+uAVl%lwtzuU%}jdxkZq^s!P0v(izum1Dq^1I5$#XqzIC%7%Cpq;e{qVF zsAsE-uKu3;_2S!NQeb`WtkK|Zv}#d>!Rk82%>xaB>*C&Imkp^AbMh!GcV%prV$u6- zOt;FeI;!V3bTAB|*fYuaoQBva`F`ujj6Wl{pr)1iE8bE{p3hgC4JsWt9K||+HU`V|mbcK~6yxII zqsW)1eyH7ETN$GzB$aaS5*3@RS}m4P6PvXlg>{&@H;j~20Zl_xB?$vqz05Ou0HpZcZy&UWeo~Ed}H-GWIQe1C-?&BA$nE!J(I49!z z+-0(&U1|3Ne+jkkq;LetNqrQjkb2wHTpfT=a5?8RmX}iyQvu+ zlwz)Dr9b2HZROu-b!8&yQ2+BgGhU1{x4-BTjrKcXBx}*Awt>rj6h)3Ia6h=o!3kAx zE#{2eZPJJ+S7`V4-ciods-moD#_h!FO)Qjw8@bnA*@8vKrN;$sgZJ^+LcgzONrz2# zOK!@g4$HB$cPM1h(jurNg+6?gsA}denV%!8(=kTN48C1eG4AU#AERlCNjxdCXVmhy ze1yq^y@$a90UsQjLZl*S+bm)x(ALUb(5Pp>N%Tz9drMFZ?S?>^&U#(Ih zoBHDVrg~x2ZR@?9o>c*kot@E}rGM=*zF4r&$hu2?lKdIvnWKbK++pTcxh#lsx&BA; zoSfx3f|9T5ahUr8hm%MzbMf9N zc}B$w35vd^BhIx4uX4*7;|b?8cYbi{kUqD`Qfm8{9sSl@A{RagG|+ZSlI+=+>XpH} zf3A_sT_qznmL>UdKp_D05qxoR;xYX7xPK%tG=G(TVjsVGKUW3&KnrX2)erZq0)gf) zt5Zu4EceSk1>d<^~Z?b}V&VhuIqEa$L%JosVH!P~}JUpz{kv|j8 z#eUg4y)tA)d?Q@u)mhZy*|{4BZG}>9nxbkGpKVc&8 z$?+U=H$EV{TIjEse{WilE%a-_R!kcfeWvs;u1CdEY=_5aY(02w&o#{V32vO@6VJ6+ zxAN?zFQ^=?i#|eW)^tf4_1VL-bI@9n{e_xrb?^AC?9KAjD#LA!(){`7duMs*Y1>;S zcttWx89BpqBIMPwCZqMm*Pi;#Ex&4(?0fKF;|k&RSQ%e0=VAZR=%?%h8$)P@&u$3G zsAwM+L~vLZZi`cQo^e-{umg41FP?LutfgCdgF!Q z{!fqa=|JO-G`%**oYdOLC*A44+D1;I_0bB=`p{C{gp0V?9iEGC;?52CoU)0~3||Uw z%rbe-zsHiO*f)ZG|5FF9ZUP+(pGeHQY6%(E8TM!xzQ0=R3g;`nN9r8|>cA{A1AMMH zrP+nioL_!XWjT46+jRRa>+bnX-si0K&RG5H%E8*;W;qsY5EfR*$88GAcGUGf6|7f4 zrzYLzba`7G{p@j4g=oSO{?nwm7eik9Ni=F;sf6#FBOVKQ2?EJaOG4*@%f={E@kCNOq^Y+j34^1~0W!z-=t@A~EdNmSv zeVNAhDZ4Fjvehw~zr3b$+QAb%y^T)0q49y*^}O{{+oP%2#-MpJk7(lH{U6>`nvzza6UBCf8?Hu&l4XOxG+*V z>AZy}UzGh40eqZzEv)@GA;WYPI+)Hx@N5%ilk9oRkQ|dE#mg?cI%qhdybX$DsW) zEwW53-f_kyALw-yIG7T_j8Ttb@;qpnl4`jCLu2bsQ6W>X(3)5{T?9H%pX`-#!cXmA z2UEj7%|CvVi+1DCS4jzjW+Cc@2c7Ty&G7!UA)%W3WAcCk$uyNu1@S-dUsQ?&I(rhc z9q6&~X54bNIDdhn^Gns|^}a7&z>J~3MJ|^U8>YAn`JYqry1&Gj<|pX1w+|YMVik)i z0ZwaT=QBwrvNVq)lghsZObRuAFLUy=syJ>N%(}DoGO@ez>YKuQI<$o(Wm7*!M}BE^ zrNr1%SQlX5)lN#AOh}D-!JCJ1|Iej%RXb~*LWYW-RLB?0#A!-hUV+!`bliLK&2AN| z=8*M#=`zqh(U$454fnK|-D^DIj zK3U$5N{553(>s2}3gklvhFEB3_1RYaq*s%qFsc;z>)X0LRJU#* zwxotnX|jkF-sWr~e@&9x?D)oDDJIB-mgFm8W?CbDBDxztyt35#nYVjVSp_S$F&qsr zx31%a$uCU_H95IeI0~_hlM(A2y+TzGO!*oVs-Q2aAHpQkk{U8U9Vpu{(DqJ0KUn?a z*P4H(x0F2w+E>?^x7yTx=vRIdQ?1(Kp}j1>*B0bJjox)>6Hf%Q0Om}|I_xn;_I`zo zuN(}l#Tv}VkFL6D6ML9r3uK2(N3NwbdTN;UaSF&u2GgYDz7B3`y3_KxX_uDwPL#f4 z&(Wfwq))mM!SP>r?hpSuI_kUmRS4fa z%FLsBg9elh)Xl4z?W`(cZK?@Pr#M?DHe174llLUdw$5nx-br5uE6%VfOgX01cloR6 z=csP)>s@NmH*^V>-4D(CbQw%=@`7n^c2#&oF0Wx#=UELYK2c6~RLQ-Plc4F!twS9| z160OS8_z5CzHa4wy<-zKWN)9l*vKoE^r-`{^G#8?-ex~TH^o9kO00jzlK}** z9ZZ&}RszzQYATM&JIweeN8cDK{{13Bm7OWkW0&u%(eW*`U(N8vd!+~eA7y71kX0A9 zX$%@fx>LH5ZX~2zx;v#i1?iA(N$F1MZjg}f?(U9R`290;Fh_I#9;|omz1Mo;zOTo{ z5SI||j0W}u>z`#0>~`Q=btAE%c#{u8^135|`t`H@$(G9`vHr12 zCv~TC=t*B-m~Y<=+R`E=>9EeuhA8|pTsK#M!Y_SKo5I(-;_p31c?_`5O1P4LFOvj7 z?(I%zf0SiKQ@Bu^f{OH_SaTr0NDFY#X-CtJCt!HQ3;-5IKFSvgVPgfAH3>t90Ir;epAgH~qZ zg~`4h-C^%Spg9YRV`0klsd)Z8DzcUVc1*EbdT%+sql|aue6QTNjuH>wRgE%7$&7yD zy2sMrjF{0Jwb~o8_`Fm@F*%zpMIhOqw=f94SnU#5^!w4TjE>gAs`iYz2RnCir@~K4 zm>S3m?5+3@r_qdd_%uSx$9iY5SQohY6D+|GF`G(H0(q28zqeTK=`rcbK5~5YF~b#3 zn+(-@fGbW}-?Z%PRpY_%(W`&(ChHBdgM}F8Y=#WUI$6pU$U;$g2`h1V;aqeT;^hl6 zl#wbtCJ{1y=2+@ng=tmTD{ONxtHnYvvOatU)|s1)*#J<0uqES3!^Qj&is=8R7A{=I zaHC8V6d!Wr(M`N?=U;0SH7Pw5HqKYAb~{P+$x&*8vdj}dKBy}FBraqMHuGpw!g7yk zoXQRe{2nEmATC0I>&ANVTDLxGsR;5p82bGPTZxp2JzQEW>c2AJ0L5Q+qN8`F#Tm0$ z6-P^(Jm9|>*vXubR`*gN!ObT3sx#i|)%EqYw_WZ99+%R72G zIvrvKy{M#Vv^@bSC8z4if2t#64ATH{4yn~Ca9K3yJq<1<@$l&$l_}rn4V%eh=tr-& z8A20WUWE^sX6pXWB^><~MC)ji(c{%k)n{m@*xKLO-6!ZLydIOkG`Uv`4=??#?dJUP&1f-;U<`{aaER3w$<{xw07_)t99#nsk9N&0s z?S%E#3j?PQ^^cqi~HJ8j3@0sqSFNwgxU8%ikI+5vQi9C?_u~(i}5a_eV8t4O9V5JDlF{ztlXX{Bnk|M`uWT z+$D8X_S`t5f94u2_IGS@KDiOWi1<+KDQCx<%w7~G{3j*ej43|7HD`4(_A`yG9c`;7 zy)pT%dc=WlsTDTA?48)h8QMS%=PhyeIq$nPgTMjZD%sxsSK}jvoSxAuvWg~8>TI+O z6cx0r($07UrRJ-$_K70K6BS~p)wQp8r+qF1Ab-yh0urx@B$kKZspJdH?Q^Lz#o z`Y%lUO>-AbAN$7-D;S`lCYg3+Yb7hdT=M&Hvuo@H%<-{PJg&w-Z-t z$Nc^XN@sx{`*^z2AJ(;)5CJ3-6WQiM3BrC{5;|1^%BYtx*1+REB)jeB07Sz@L~ z56^V>*5MHZ=EbnmP*hXdc{0jU;Ks|E4r%c2XUG@L*ln@NdV7DXWgdV(+zkU)eOF7dKBg8$-3(J2oaPhPYUgx#exa&uctpU4>J z!elkP8LVP_=D79ja*-#z2jz*~igKTJN&78&M^{llq;9{C7S3FJZaQp`O4%(=&b6a5 z52R6wyaN4(ld}Oup3_S{W&CDw^M)U}lbSb1U+k}%{w5LAHFuAnUzPbvgx}o}Btt*? zb&ni=M0=|=Y8up6;C4r2b3wb%hM$L%y`&R#`y+v8*p8nmJgOC+jD?G7WU+KPls!ni zX(5L^HB?oj(A`rOioGl(t1V^!b&za74DWEKea)IF40Nf8zCnTU(femX_kjV(fKdTd z9F^UIq+4ZU=F*E0pKj*T145XHMRYACu*4*bce)_|gO&VYPcD_OP?|WJY;NV$jid5Q z`P6PYx!5xk5#%xT*r{T2hOdv_DNA`5T21wRtJHR=VthXP>%$1*ZJApEUzj|u7T(R66oD1lTz3(6L(dZ`jV4vra z-e3y)@AXIv=Acjq5A|jWu9oyCGkyjhA8EGvOL|x4%#fDY z71nZDu%<6*>VT4N)kvv~6ILWOq69Xhsy6g++RRJPiTM#ierH41_+t*Lh3jk=iry)RHz;W<@uu(7My-MY?y@6EtGQg|w7%Eop4yT%QsQ{Zp= z)U-fC?OVG{SWP4fj91iH38-5~EgkvGKR}xc4W}mLNxG=~{PG7a!F0$J>%v(} z<{l4zcYCPVJy&+b9NdQ~UzJ~3vcfqix2EAxzs7RT#Ro7i99!ClXeBJwZcX=H=@-L0 zL50@!^M=}{Kd1ufyuACfp3lD4kicJ zdi(^(zN4f^|Lt1v{nZ+@X+;Pp@4q%`9__+gk2a;dRvEAde)9^ae>{>=~!XF6&=b$bF%{ zaWYkm5f`dGw>Qyr*MZ0_;SZJ3S*Px_zZ~>t=kPp#1*)_joHP85?8ow-az1*RX4IdT z2n6-caJ-Q?6^{5AMl&dZn8ckOObop@QdR3}tw`jZ*8Dx^bN9%vIeU|RAHMHi@K-Ud_p!Cv(o5UPMZrq0_N_s<#aCj}kI}_NEyXC7N0Os&=f9t;{1ks`Ip(8IO0+|7_D>l2Uc^ z1+6|8=a{}Kx6NR6hx|>evDLiG!qD_UUU}PK%8J@*}`*VID(jkQ-u z-URCca#EfKDQx&eyM&h@`4>Vv=sSXgFQ_P$?0ZTAAyZoPf1jNPvLoVJr$~!Z9L8*I zT*7EukmUPv1={PIK9&wB9C%`ycQ%%Kr}yq?FmvezT{jmhNg>hxnX{@VR&)rz4y`f2 zKH!i0x#cvA)(=#@j^eIl`LMip`(tuYna@855m?}q)HB3g+ssoqC#rs|f#UPXlS^dR z7rMiT1(%YP-O#H!Rr5sdY}mL7fXm2KREyT%AC9egm2HL&s_=%oRn+8!wNk6|+C0TU z%}Ni)bMtwB(yenu32|J?f_jv?$WHgZpj-M~JDs7{n99utUw{Z<1d3&Ax5vL&QMG4R zc_fCK{x|q$)<>$6x+l>^n9vXjK#OD9w=aU`ztR=Frzg#^GAASvLXQ%5g2D2AMc;10 zyeM8^fhixnZ8uq@9K2sIt6qqXKZzKlXZ_HrT&VN z$gaxp?G+xIq?Yha(!!c>==deO<8=sIL2BF`L5^}2ui}G|Eu9{In#UuFO;drKJg{&0}VI>%yz67x^?z z$|CJmUdHmnPyai52h%CTMx5<--(@J9u5mb*^&Zo9EZ zf4mESfj-qos)Zb}Yq<~&o?iVKBjFVQPZ8MWJD#SKXCS`U8>c+!S=%MulF}a^aK6U)30;1$;vFxCE+3ubPz`*b`4N0C1);Fxs!hwO9dlBG_$iJ z(_UxxcG-#JsK`%;T;1z3mWIJF&~Mjqs^WIwCE&l?GIzmqXAsFyXz%(_X=ttl&OtqD`Q$xwXxD{%Pu!?qd??Y2Z2uA6%Vl|&ts_zBqX?@cA zr}56ZyO8qTYT+mbV}y`sY~<6(?LB!>hQX)pS#FQ|{f`i`Q`gxI?o0&gylemSe=bgM z)%L;lXAqTyriCH&=FN2IbikV-m3^@sUuA3&|A=R0HeQ!45_&u~9wf?92eca`X6aTh zE#|#QDnVtflr;CoZ<97|{xG+A7bz!&vCO_7P-pC!@V=emhtXbXB-c&*zAFpejFy8R zqMXvIQq}?qre92W&TTKP1(x8O&_w4rR=7;kvk4ZAEE!BJLYzb!r0A?yO1aPnOqm6> z@Q6hmQOTw2W$<3-&u~8kfr6G1(s4nkbBs=ZCUQ0-YYN7|#Xr<_8N+jEh z?iG9ZQ#MQy^crx(E9bvcHp(FV1Pe+USc^T=CoT06G((=6lGcKo5dU3lpFZ6xyA2fT z>yEZYVv&&s7CEyWt14fOk_zD;+eR5ZU)!(FR##&>M$$@an)EHxI4wm}`?~rUhmWeK+w_d>5F!GonTdVWZr^+^yK8^|#mohkn)nnn&AvmX^-U%<# zJ&!PAEG6JY{w}CkLZ`|ZGUw(jgIjA2QV?dIpuU)_5Otn_TV*xZTyZ1K13zacg*>~P zMY)duA2!twCt#S=2X4W-`g%PJ3rS#wm~c||~mYiz<;T8dMf&Np$vG*~-kU{IjfU#INB zJCjbapU`Tv9i96nya>RtQUU1j1o*k^_9m!+=V}+Y6oHVm{x{%0U*7^i$_w2ZlU{Sh z`}v*_c$&5^cK=Y2zv%dZO&;J!Dh+zy(QDSV0SHWZQIUh51nDM@XG@&3MR}j-lM*2Y zmM16+47}c@N^*?GN#rDzi%227aeRXo<$g(NZ-#5C*sZwP^L>c@hXh#{9gA{@DQ~Oz zhH9!>T$0J=ie7Xknuy+GKcm~9$AsntlJc>9*CG@Ae>t%Al_oI@*I!Zta8)yhLdovP z^@KoSVpu>ElfK^a%y=I|9H6^T-Q)3-$qx!A$ysR(Jf#p^jGIIp6$t4jEv%U)^V

sj8`Y0o4aw0{~) zj7c&u*{*f*Yy;lH^7B7MY;VNhHxp&sa z0kd)BA-*Cfuf7O0IOE2?{voPZ!MB$IGiIIs>C{s5qx~OiKA(O0H*;=}qh^k}0Uk-3 zr-vc_RqTa{a$_UKBB$QN`HO?y*Rq1780=3XklB;2P!js3U$xuU7TmtbPeY7Oy1f3H zq7uUUJB!ki!!u=;n;tdc=MNCJOsAa~cyJTavY2;npU9`XUEH3&f7Y(=CCuw|X^=nN zqY2Jx&tlxMFDcAYcF4{_f5xE;-xpn9`_6TMHP?r`^M|FBiwg@e!@k(}H|?`^?AzZ* zsxEAT=mcVSn_86Nff!A)ZXYr9db^)3C!JiMmJ>Jc{?6#Hs=_KQ;E#1OWNu*Umr{@; z3{G&M)j;kJ^O2q7f1twHs&fk4Et&``0)%bg#!X9`HDKrE<*j$1y3QK{9C|}wUUJx* zfaT}szdBkR1YX#`<~0Fq>{bi9|KoNA_?85KX+HRUbfF(=%Il8n`zcoQS$d~(~+`aEotVnh8094)wJ`iEc~4lKo}`}y7H5RjdrID@`E{oqFXcB!&WFlPnZJ?U_s z0kgSEld^w5PsR|((Py;kp7T5-SFI=C`JUhWP5bpYEbZ#^cBPnBp<^kq5bhN02TwzSD&0s165HW1=uiTn6rN>f%NNIQ5Kuk%k}2zFYPlnM6Z*hj?9yIHD8#h(Th^EBSwr&j>D&gr*xWhidR%sUc35*d!fm_N=Ir&8lBL;&aC>_C-HBt} zt9PvGV~w%ivZVfT&(7X1A@xHP=0q=_1yP@=>t624Ngn|>@O~{C-2h$_^c${kV+Oz@!QUw z{cWGfBxN(j3WOz-$ZjwYj+a03;qCF_M8;b0mP95nFvzS%4cEsAA@XtFwT%rF zZuFMT;Z4Nnqa5jBd($YE&cR6R-EV_(I5{1EdzEw{nhYGz)w=~Wy^ZA0-$!FFoDJjF z{C_UFMRr{vn#_8$qI@$31x@`(epVU`+Gt%fSbHcI{T<&A4_+i;pXi#*b~V~}I2Xbs z3`azWNiIDo_^UjI$?onq>6?`Hpo#tOODW-OYhR5556uIs3dX4!;_uS@=pzGHb_kET zt>vfOr~4+wOui2>I{fG&nXb|ommQv7@`4Y7hqI#|)3IH&|1X*02#D1&2TR6^uq1&;B*)31SDPnf?_&+1>8y0AtbR^7n*a*ZuUNbdm89O z#+kj%@A6p$qdAX$+-@nqr?Ry%N>HVzifaq3sP>U~(&s#I+5M9lNz04(r(UDNqv4SR z6!+nmRy&LZkl~`~H}jSvvnY$X++xy}A9|mPqEt2VU7vT|itlwA1+kUg)TeC>OyO-8 zfC`k9b@7I$pgYialxno#H;|J^P78fSx$wnc(#v2~vjl-`YSDeWrnry4y7%Q-j zLpMNwLuilf6nq+MuDSvywt$&82ruIh073V~_Xnl{y^Jt{_#8nX4g4R8%qH(30B`NZ z!p&kf=J#S326L1gxbT53_IKvU3ylD{?wQ=LECIo-i^{>rBiW zTDdUUO2ms!E789HS}=!-36AzK!>+31(7^12m%yM%uge0s9ZZpQIEMeahyb|$YpH9>3wZN~a9o{w>$UxyJe`}oBf9ZZ&%;^*p zo@a#|7pY#{qJC3%29!J#CzQ$A*WAtfmD~Cppl_oF`gP>|@+>6S1yzgBhHLV zztqTWFHmYu#$t%c(Wn#aRtnhg^}8LZCtp{|?Tf=`QtW9tJ~JLW)yjNhgT&)$AL8M( zh0H2*bmSMqTDhIXpD+^%7XcEo?9tdlw0kf&;RU+^?j9&WK_LccGJs^l5vI3VYU)qr zPLfRp3|?0dUlst~2Z$;2z+fAI%zyw+AfXh1?WqI?P~|dhX@Ht~0T=^_7abT@L%G`- z1L6m_vN%arVzV?9`1a?xC65bjn&YV+Y?lE2j%_LaypCukk|q`*)Mky4>5m8XTsUY$ zsfmVoUupB#^aqD_gpI97s5W$0yu^A=^M&<{nPYzDZbp35KzQ6_Tx@wt@W1~aVx&5& zW_FVy>*?j4`85iW1_G0thHvMC;A-phJ)kTQG-vv%i6Y zjFXRaPic11{XM)SaBWrqi+y!l8vOT22f|V#O3Ao#6EbKejo|4M`^aP%Wg{U-R+<#q zP~6HqT%|Sa=K-GUeR*Yq=KdJOrX5Z0gpQ_d_F$FecO4pfOOW~tcrk-XTn9V6D(L0{i!J)MV@{)Sa$j?ccN}`QHFi%e zDYYdB>l&&N9n9n^ymkX)I8@Lf!yI?l0$()JEW z?9#L|8Ma0%Gk&iDniG|$U$BI{_@u7upHJs~hzLk?8q<2T!Gs^b?r zzoijHhO^%{>>t@&5)lg-?yEI7Uud~2Z|kFpOpEr`u+Kn(rKKYdEzbX9#Km%QEQ#Ee zldTBWtc)GvJnlA`6VS-JT0!+^=1k7iWP`QN{&P_L1hbadO56#Du@$Fmk?i$Lj`;&p z^p||mOCz@1K%>%o4z+2j86)oJS82A~f)m@S?MW+=<-M4%n8EZ!hNshS)}B3taS3B^ z+>Bm-w>1hVZ^MfEMSfml_X#u=W)kk5t!7TcJZKnf&T0M@Y_<`ZM|p?SQ5h3c!Tqam z&i?JqP|1IVF(p?N=;FOQ5}h8pWT8|Ne(H-Oqtw=;=3)U?1ZPBzLbBS^s$XAiba1&N z^ky)_HU|mzV7eM^FKkZcw=zx(!CHhmr1#qeHkaSuq{`xSRFHpsK^Uv%no377Sa}fQ zxgGMRUgNXowp4KSCy1jlLy4H6q`NaUzF`fRb?xn|HaRLJ*m3r1W zdV4W7oIH=PUf7eq^o|293DgY9_jMn$99adhvir^EEay9qC@Md6!gFMh2+x&coWYQ69+uS$h8(ME=<)oANR4;_r82J-JW zM${~FgeWtuW=A!B#k3QD@W}45@<;yNQvB);z{#Dwf zDybojb4vMGY&80Z$ShivyhI4je`PJzQP=r>@2@MzmJ`;ZPcSEAx6&qv_W0t3dnH9-+Pwa&Q{XNr2R@e@_eQjWvdWOE z5;DRo^gZMAYpr#l|0n7on#M!r6hbA4%W8Mk`_WXik%%zDN0O%)jf!iMKc!5ovlvs~ zLJQ70D#~MOl2G7C#PWGD!ikeZt?y;xmT@(|ijzYKYu5T`PbJe5NAMV-|DZ+uQIEum zUrfKhod`u?%-)JtlG+DJvBr`L>Is>sNf~r%PV9!4EiOEIaS%#S{3G`0sZ@UzO^)xJ z(l7il8XXC&za)YMa@eWIGP)Wb`v4L?IG)9P6s>)i$Xq2CXGJ0)k(gW01V`oiwqCmX zVYw)*Jtfp$==xlPuj5~Me*UwGDalF`SVWcy@J12)xWOqP#DZ8R=wA`pFj^^qm*z)W z68jd}YV+9cN1^?Ya|6r6NLN~NI79>(&o*YzH{Y6q_h{VCq)59K`iOvu&f+pfx}F54 zU%Ffu_xVtYpouU|7`UnSk+8FvqaWV|rKB#-<HiK2n76Q~W~QFW7`?l_Bbha7orm92e0C?e`*o z&nATH90iMMhSu7V6f?FZ2FfKv0I}$0=aFc@%c2b%0QLFjNVN52wu@&HRf zzb%p1dE3x;J74&<6O)?(yJHbfe|Zz;^OI9--G&2*J1dP9QbZNWj)|LSW==mNojN>y z=O0GKN%aH0zc7V4%MWfTLAK^dOxbPr^(yE$H{J|cDsga;$_+fPqgMm1V_~@*9 z@KsEbO*;J}ZTZQ>K(w<`JWvjFmkQ>tqFqK_4@6okwOV5PMce)RqJssV{ic`R6rYQo zvFAf2%SSJwU6xd4v6micz5Yu78toPsl!n1Rs(O*Wje}eAZXh7Mw)p1%c_gjYJ?#ik=y|$i_5{iJKM!y4G61EKVkSg4gT55J*OC1p7&qYF&zZ*6`qfF=aBl_ zP|EMV={Gc3fw>zzliWT%>Ob#OM7tU)W36*2%0>l}tjVaLBDNXAg-QCwy}-wRA)--s z#FS1Xc*7~?MPwC5eT&)3KfR}GMzQu>HKj%M?cce7%lNF>5*VJ7eET8!6dX+XAJg=e z%WK!Lz2zlMZdX?-OHdNyB&3CzR&N@U^km5XY$3$8@rBc14zIv+lEQh;)d_@`Lh!8X zB!Q?Ln7tT{zJAM8EzP3*GwT(_;1n{)3e=t(F($b2^I2`VSvl5_$;$S0hi0*Og|z;o z(s9mY7Mkb;H21VUu_W31gcuUk@K|VX2vKTA-Aj4);txDXBfz8)z@75#z*31z2_fvS zep`21=DPKw#q;%`fdHTi;`+!;A55#>vx5ledK(H1;69&{GM6k1h_kC64^-8HT(En<<&62wBn9ImshoA)ls6P@F+^qn`~E+bt34}8T76?# z#w3;0^7}r9=U|K5=B3NTxvC%SMDaYviDPwRxhCFm$&S>j7_Y z)W72v<}6xoBt#<4j3<$XWfZ(q1U)d_ZQk^vj5pgt3*pka#v;&c%@b+lu4qYLH76lK zW|F3Wk3wVa1Uo02R;J$lwo%6*&B(~&IS zwskzRyI8Fvd+{TOs6*-?SpMmfF%nCXQaDRgm>_wgr&O2Ifa{hPZ{HE2%dniR9gwin z^XX?2+<2Xl^%5@u04FdrXOuxJMt&(>s%vNx+UQ6`Nu6Q=>&=Y}@uB(Qck(cX`l5W& z=nO~n&-Z6(aAdtJM0%4^vb;<>&dROC99E1po$=d^ho^L%0nK)8dC_c;=TI9n2Fa2%=iVBCjpXhJwr%M8sBSBCk~Y7s`^0+ zf$m7hOmUqCL)BAJNr^=lg%vDfCMy7pM#yle7%(g2+8ZsTp9Od1Ps~gjIQ`O5Wf4p8 zq+_gedYL~|e;{#Qm&jAR0RmSHL%$f%t&QV+gM&^@m@nH6Q#`p!N~Me^mpuNfjduWI z2|L8cc^Hn2bub#4Gbl`UwY5kvs!}IY=ryyS;2uAG@`88e(y?Mh4Er%ELCl|rsG(iC z!Ns>#ak1_Q{(jOc^=?E)GofAi(retg#UT$I?%(~x`}#fKlOPDbqz&X}r=h|m$ZKe} z*tc)%`^!y43}9>AgN+n1(T0_m2mD67E^N<{tl-w^;QP(gwY41wbXBEyes4F$C6PTC0Pw`b#;rn_&S)`Y)b_r-ft((n>xZhDW#sC+fcd$UZB+_B6}sv z9x?*!-jhepo8F~;dPEv=ay58ZOciWJhNm@f`}``eWM~XPhhfN0(Vigrz%m+XO%_fg z{`a3_t{)+#!j@hW%a4!cWKDT|z!f@)co|NZ7c~z-HuxzJbyXbu_X-U6@M1T3lJl9; zE;Sk@9q>du4mMuQ5Z-%pc0e6AO|o{roENm?0C&Bn5ELZIcE>=@MCWcotyJI#W%ceo zlt-pNZRw$ZEEaOw`Xc#qE?azZZ)reWHpI{7PdNb>q?v4Lc-aW|zXm%)K*&!C5IVJlsHhd*(W_x2&CPu=5oxw2d;{Sg z{AboYN5l{5NAPWO^+`9gy|@cJoTA>I#yQ8u~d8g0>h5 z2`~7}NtsvY6Gk65XP{y&UcCcFUT0*mswh>sZmnL^dq5Xu(^i6VB z`=R`ck+ZMi*zn}oLL(#wpw&d^LL}_MP6~yLk8(HuX8ICl_-5ZHA>HyAie+T){5$^9 zhUzMvznf!!JV>a;^gO60Rb`dx%br(e)PYIVkRDadln56^CH#!&?4El`{dp$vX{%LR zCu;r`g1I)jh9sg&$2untn$`hT88>pze>LM<4_$+ay)0bpI4w)HdqIsCm9LD?3xh-_ zt850#DQm`lD1!eZnDNJU(lK24Ub}xowXQ*fb}&*v+?G*mm!|S{UYcrbnQ#!rTAW+2!X8Tn^kel!krr1i%w_{+?7AyS7XQK1KU| zJu3#=$-=Q*eSxhfR(o?D+EaJ|Oxq65DNB(uO#f|D-6;d92*{&bz+^z2$sWvaTHD7c z1Sy)?N9ZD}&C=UJk}|!mh0Lg2SY{VnV4BN|pxChp53Z)Yo}pfuZO;tEiIaaG*1xBt&JW6^Y` zp{o#{n3IN8(Qw1Jrf0RKmxZR7){r4+y=plO$DM}(gMw4TO*mu7(|BqfgDBlh07T|F zPPKFy(7QiB4#-rW*pg}GmGA8gkswxF9^eB9cCW&(wa`ybs-{xUN{eH)uUnfwMq;EU>4=UYSGV!VqNgYz#b%3p>Sc|i~OMDV$F z3%nQPS6h}O{g<+A*oss4;BwOtD7Ib?q zoEV;^kSm+|p+ZByAy^c(HV3s5Ty49l)}%?v2tnX|1n>On!7bx95L28B~K-c(q+~L3Ya7~8y^ojQRQ5!9Y z^@H9u>a9yrpVr<&MUg7Dr`Cl0$9Nj=b|34mGv?)O*WomCRaj?e3z9X38ONtmd7&4A z03akxT-t4P(|h%d{1s!FRDZ=d$NgF|JS27dcE0)4F z&AQZKBfqz7EXR(-u3?m=AZjWl@T?4g901=U6M&5ipVcX%<+K&Mu)VJd8jJDwi6a!< z>f}!k*-W#~n9a`$R}*vK@~@prCF3JY-Qp_^+gn08SP;Sb#b;Yz-sKmJ$Mh|JWE;2A z*eKK3g(j1)<`0ZsD0r36fPxIv+gk88BH~0~Jw#N{d*Wo*AYYGU(E(w4c+_1E|#Tbk9Xh1Q_V;7&53z=yL0Rmk<+koKif}} zz63FJ9-6_D;@ke{d1}r=L+$(WqclvrwDpkL=ROnz=+a+6-}?FYFiEE6iDoK|rb&WxN9J+2T`OVO z*~zXy9b0;fh@~CZ2(2aXBve5B52ww$=Y zce0`u3geD1T?9}+IsbzMZN_H7&QQwHAM%0tttk119QH!2JV)JVO$iaR$;d#9GW7#}IRY~N+CKxV-sa-iKJ3a<{MKWbmTi!`TVeL>6VC#o<0 zi=|&~JoTz(p&7K{@1(bC7OmW zz#|2YY*+fI*tgSH9ea8AkCkB zbH_lL_DV%;crj$Pv03F+;$#^yXn0hypXAfng+*r((-V@lUVKqymvLFAX8%r56_yqX zW|Fy-#S_Bz*91&#bJN@Ie?nP8w*&$-D)9)FuTZW+_7|G;JwO_Obw}<(?Itk04vQ*geHwL{A3Vi zhKCK*)s#fELP}&P{|(R3x3VJeVg2BD4RSe`$8*P-GwSTT*rSCIa0|xaXtj-L`{AT% z!P7tm;o+oTF&bj4V%f%M2?O(_lp3x;gUo6{fcAxj0;kCbNnD%3KC=OaWAkHCn|(h@ z0WKHYsO{xeGobNiS*S~BYqyY}{f%Fb+aelorI4XkO8PKcAw>n1GQ-EPCyw|1!I}D zlg_Gy3lE48K&!2@X|ol6ps}Hvt_nk?H9bUI7u%+~!cc%2Ob9-(DcAE`7uvjNII36&#k4yLc_hcYTIu*@jvHO~i?ffPDbn&SvLRl~nOj-; zSzxFtsF1uYwST=o-1EefdFE34XwNBkWeHt%Nyo*yux9XNNmZzqU9Zb+6}jH=wbw2J zao`Yhpf96KsT8Su2@>MllYHn8?7rcOONY{Zrz@ry2beu;03Tp$-zWN4)>>0Uv#KT97WyVs$#kC^nDHL~&lZ1) zx|AXTa_r?QcWZOUK=Jzw{WoGk-*P-xW(1>(z9>*iY=s9<@u)!5xWm=!*Qx_g^-NqC zhmatEgOu`q&uUxQQreYog@_Q>t|>)uRc4aQfpkbWi@u$_a>)LQ$nF4F%!SiYkaB%{ z_>JSb>Ylx$zh{he9W68v?TsYlZhdrOXch)aJgD6MSJ63hv1Na+{LZ&pIDZVU7;klp zc$F89+bo%B?Fg=u`snw2*}g${#Y`xkR$Lqe2rVu!JIGrqpxSW!&o832&TdyZGb!hF z-F1XA=#J39wtkqnI{mZVt5AS_%MJ;pW4@bWaDjdSJlHwC3S1;?J5jX;W;7EaW*3(Fs5F{Y7vz+JF_7c#YF;HW8fF(CaM$^^#Jgd&B_AzWFx*49=A zehT$NNtHl+MbpJ|AuBl)%(pzyJzuSliZMk-qMd01{qqQUg7%U8GAaWFE^wIF;~+;ges^3&Xpiog`{bgKdC{a2P%Z#2 zFsZPmI*AaB)>rVn6uTW5&Ui*IgRvE0$&eq*9scc~;VqT+OuI^QW z4!<@gVL>BOqGVBY^|!E2&-0Gbw^~=p>FumD;@jwQlMns0+t;OhLgN41QiMB-4)C&sX3MO zJ3c6#x0Q(QiA{}9-=3B=aLL4-H5WuNH)<=X{JO_%%vLIzw~8}KwQOqZO;o-Cq}gS& zTM9P6+aXbnETR_7S9ICM$yd+&rE`AD2QV1!4fTKP4e95t5cf(Ts$Z?bRg^V#At>iS z|5494W{6doo90dbNxXOy;xJ1qj$w8fYK-_r(w!)E*mj_Jom!J3$1sUmxrHsbuk}xH z=bqhMF5I=voiyXCG0pHe?LlsPW{wkDd2!seQ^|o2-oyUTYw>zG z;R%vPd;r_hi$!y**ZR?)FpFy|MN%s z#t#^wEL#*?QX1x>1v`?vsf3VQbJ3hvl$sbfTgi`iMqkVC+HZL;cWUS?(LBg!O(Y9F z4@LN6?!u8~IDRQV4*6XN))n|yNqk(`GKhyH!SYxXOSFN^K!i~V;-wF~xI)VDOiyfm z_59T6DA}eym}X^l$L;ikG;~(vBu89f_tUv+XJkANWr_Rj!P#{QW_A_%+dG;lHyukT zUbR0tAwK3&o_j7@p?V|M_8%5fEUxwwj+5K>;+c3a`)a<=5fqc2KcC)+W}ka2Xjnsw zug)J2C|Z+M(7tb9wI4!v*L-z?4_^81!}upo>A6#H1z)X(Tf~C-liyl{`cW-RLdg%m zIq#L~riwf7?(BD4y(9U&2Y8P6D014D;bsy>#gx+?a zYq*&eQ^1_1e8Q8PI_8>_m0(@b zH*TCa=;RT>+GKkWvIcQ_1jJY3*x`vId{qfN$!ktS=a0f;xggRr#{8`mE&L*X&YhlY zJgU3=>gC^ZxpqKrIb>o^iQrU9M>cSrpAIiN-(>pMUGwwuP;~B&jpa`_9*VC0R4eEV zJ&JU%)4l5?*?@03Lkvbq_M%X3pqc_{CSZHk5hj0F??UplFk>mM!9@^maX1na#qg-7 zWUMRB5MssFOl{iMACgh#|IO?x+TUo^|Je*W5vy?0cf-23VwH{=?$q$uLVso|jV;M5 zMe0%jDRsi76sK2Po-2FUV0#UfbNfb~+&wY*4q*|I@>^)q$-2M=w-( zB$e?6cfLcf&fFYoW)?nkPug2y!n94FrMYxh5L_}stu0WSCFm~`s@5Zi_?L{Bb}5+B z+8g_K@WTE}+Ny_EEfg9^G2IuHKs47OM}*kVRm zs)`{Mv5|cBe5IXx%`6%32YpMAJt~+=U`cwYK~;<0cl^#ZI`o=;lwwtm{$NfM+`8_zXk+?spCMHdjf@8)qUIxb9$@P@^PO3kEOXghN~( zvJ5!XYHe3lJ$9Ur9CHgNvTE6MqSrsg3iuYTe371jrz47Owwz_^DoFGk{6V>4e zH~%~eYHzt+KW@^e4@(O+Xmky2>@$<%uzQ|Uaa_Vw*JkLOsZ)_zBlYFdth{^iuY|Wo zYT!;<&~mfsg6o;8fxHzzg!b{VvtEImlS$cs37lOpg_4F&I+pLWS(ojF%ZMhsqO%N` zXGxw!MRAs`-HW~*TXLlG0hRmB;s}xc8U2HSDIi;+Qf_Z27)4d~DdLLQ`!4@=WzviS zX(18O18t&~Xp~#~G+{i2bzjT?zP3~91G4p0=#op{vvcwGr0-OFe;WzK-m^iih1i@b z4H0jed}V-}(<=5F4n`H&h+w3{EupWJ2-~~Qi5f+MxSq0C)bPSxBhwtsi@qxp4A*gQ z=ueb8F03G^(}mZ;-Dsai#0Aa zD!0IL*@F%?eYXHUI0^)|TIyeREU*RVVENq{eNSaenH7aOYnoYR%+Z`4Y8ZOk0oQnV zl^aeQ{Nq`C*xu<+iPFQuV*;ns!7*8F33+p6=9kYH!hXV2VXmoYM$YfGLNM+Yxi7Aw zEk-aGk}ETW;C*XK@)GYAR($g^e7Ip~!Ari!2KV&)UT7J&f5q?Q&Ea*adaD{?Mo|vv z>KB`V(#{j0AV1V94yVh_wp2srs{Yns_~iJri&}2}vmh*p3u1?RBA?n+1NZmiU(%zc z5x>sT_X~E*O|~|M>t7i&ivDQ3z0sRh6RC*M_;zD2&0()^V|qD%Z(cMW`q?~5Fa1jw z{5qQIUXs_qH$qm+vM4KuBgt8k04A`(q_x>I5M!A4b2*x?e9s>!GD$J}?#F5wPMt*P z_zf9sh{4h9G+Vud@t;_skVn-8rBCVzZ$ZIigz&}Hj zFy1UJw_cyFE&vfiLpgUXlRTe;8KxRePQ^gQoe!pYh@oajsA03xQt#E81v&yYxLib8 zzJi$M8=$v6=v)wf?Dr~yX41JRsq*c^Ce9%&FKPNBi9nlyyQ{v$L9skyRyh7zS=fN_ z6yCP-h$WhaTQ`MP&|8UY09J7+LRj(uGK~Y!s0;Cc2YD%y#_nCh*-D zp|b5E1J~%h>wixzA?gp-r^Uboz$`FP-cU136$^^K_9vWsID~|>!GKoNZ%Yk39b8^B zfrLN{&$_=dpx{2~iUflf)7g_efG})fVIfY^v)IUE_Nwc0BjtO6w2Q^2$>%}t+_OV# za?Z&G{c<^GYq34)Ezk?wo^4`f!v;5&(KcHN(}_qAp_N?2c} zQcK9SlsrD!3l9Qn=YZs9ac6B!%{14wA!`tEOug1YX@gl*1D~k5;(SzGUCY2|4Enpu zP-q{RPB%6)0)|PtV6|bmneiw41^$zNL~~InZ9~J2^V-r`w7z3w`;KL+Q&rTAah3{}Qd85T$}JDQmaZ z{d2bEx*j_3-@v^x8TGJTv|g>-Yp#Uxa;$b~V0ZpgxNA3EU)MhT0$2|ydl~q7+c*yxHIHGn)>i!~8qSM6OaMg*@?Z+( zFc`C>FBDPbytE3+Jndb4{{H!?q!Ru)4gsb=26+=*|8d%Pxhe^5TbJ5fQD6%37Bv}0 zal+);7>v&|r6u|bMt8y7&D8aNKB4Ct)^Z9wr`s(SJ-)UD+E`VTR~G%Mqge?J&)D6g z!26tgT;l102#U?|9C9Wfs?tMin5*JzHZgAK34iF;`|Z$H|Azit3hM;c;jdCBGnW@V zHF;jYFM0+I`q2o@vF^G%*YEwkc;Z4dU#F?3H@fQFV&uGl0;N(KU}R?v*bvNNKXH3k zB~ct(^VtzhUaJPftxCb@$>)M_445{U2?hbq{(GxnM&K|QI~w)%>-DIDw6ePtA-J0W z)4@9}USBe=5i%)X)i`zjW!pajon=%#O1#4@wJWo#TV?Q#w?Ahwh zZ>DTJynd&!)7 zb#Cf!o{eodc+p^BIR^{Nlb=6-l1G4&2oxA7s8XNlywvRlrjTiAYiEFol$?BgYGB$| z!^xh2ts*E&$wDA*fDvAvQ^S>TUSBYk>SQ4KB7Jq$hK-f=ab@PDJ#uo&Ba$&5LnGk- zn!n`?RY!OS;zs#Lnt#R8;zGONcEP|26g6zQO?9CKgnT z==<0Kj}69oab^wVfICtcHuBDAwO$`78Y{K_Cj4e(<{UTCPbEoGk6!qV)vY|LXStoL zbRw;5i%lvkB2#CTYh(k{mR2qGHR#Uvi`|J_P%suVnuL^8 z2+Y2trlDE=5yFTV-x%^eoMeY8si_TvX?gUuU~X0%n6)^vESmaaR^0jWYuBd6bNfn# zn_?#_Ak@+yt7~1)9D$$C2$q^$&b3J_2&ccbT(Z(VJZPfjN>$!?&>WKzf*M-`K3R#u zOUd}W0?pu!h2~Vdtx(bv5m==ahM?l@tDzy3OhaHQZgy(wJy6m10+bx?2v)EF`zya1!|JOuz9H0LNsi!-uIN>_bL&s1F4%uKHaikeN+^$_T3l?Ulvz} zsiV6Us7=C9iaL6!x`i3&`7|=btVr?FL2eHHK2$R)7WK;E9$eGl;fqSSho1Gfy)5>n zN_05%Cc+?N-0QPSh)lI)G#IWZay$Vh64LqjwX-3u)`oP}R|cAes4@-!c=VW-JaYL6 z)wsy$FTWH*UK6H9cThmlbnP~_J0iuqG+R-uzRrqC-QDC4H*Y_U__E>rvsgB$Wrd#D z8+qlC?bVcx=K7EPy_~`74vU{0v5F1Ei*1Hs@jhctwQkT?Ax4NYlgZhWcXRsHbx(

>~?URN>piL{TBzP9oD zx6sHAN)f*c-CYd##daSBw4Z#*RXe$Ry6v1J|f7QFA}z@ASY6i85`1C^tzV)Y}($mgb05$oE z$LMh-WL~_`;I}N$r3rOZTwxx?Y+Q3ml@*_jt-1#X!(ahyYzf3JD#YnM?kRcfxTFxC zRP13xvWmeW(P=(m%lvwg+>mNlMe+lp>vnk`o%C(|W7Q{5$Zz>Ruapzj<+f;(ZGU3} zKvDn%5GLa5S(-Dnp3T^#3`FPX42SYfZ}_>l_s9B&qCd>ywFh{&=yTQYb%@?XU*ONUvVH^t(js zhU%=#hEbqJL@2wLADGWyT`yMXK)G(WawJMF01!wKo#f=j6rU^sENUl8-dvlaikzd# zM!jL(jc!6nbIAoWID@7Im?0-BJxH+OZK3YX^s}P=#R?2MP^wK4vEKcySd^1BOd9}B z#NO=UJv#}lT(^U#lb&z=j(&X(y&V_J)lA*oD(I|T*nj5!%jVnILXfK>B$a-aAkDtg;fINI{I z8sJb?L%Yz3=x0)pu?WWxzulP&;|VVf&$kpInGd9Yzt5%?z zvpUhu8}{?Ymx8Rovmyky#@`1ydnr-U#zOB9s?9jl}2kOlu2H^wqPq_9rdw!KEDYF6}Q~ zBD>7OnRF|B(kn}q;wc`J!P(5QW7-;ML$(F4!!Wt6s&-+Nmsv)xf=+JruwUM#XK{Xb zC+UEAoS+Zk5Qrp0UZCTvI#$!@vJ7@*gl+RTYgvs~+RMx9DF0j&f`wYgPO>S#GaDT0 z({Q-js0Qq_{Iz#RN1BElB1)pQK$-e({vf5XQJN+Nvc9k2o1b@!7+#`ON4ugUO1)63V7UCr6k%Y49LbgF*7Gk~T$!dkl(Wbmidr>{@eu;vicIbvXNpN;Wx6*`_7h zaxpiOCU3HUpiM2ux!O?k*B(hDEL>LsLv5-rmpWMQZ8*TxObw9%k=3YViB6S###8Tj zKIhU}eN7|%{QC<+bWzA3mJKrS@}QXlR8P0!(8y=AaH$$zN37_ixW}I;k_heG8C~Ej z{kTPSa^9sybE4dG)ARJfgVR6Vf4jAYxRGDIaF%q^Ztfe6)kxH8_}lOAcYnk1ffy=U z=XEz6Yqr;)JT=V*jq}r+-WHyg9n6leBGJG^uC6UV(o*V-;Z!mkZRh}m$~k_`CuJ12%=c5h#HVWf(g?vH z6Z~X6)1JDKd}BZILzILZ+EvecJ{3GZFRril zbfFx*xrUL`%U@i_2K)c6KIUPo?y|t!9U4+BUQQ}Hr%R$NWnLD7C9wq}%#_Kyy&*g~ z(}VAVX~2~pgCOWBJ|w?v!ViQB!P@vY6*g?`jIx9cF<$EZ?*%zKMz(Q^OA z=*jTp?UkJP9_@mN9B~b!w2%vT)Gz5GfH-8BVdv#L=MTOYjPFFS=5XhfQ0V9nW@*ON zyBZBU`Vfa|JSnK!2@*D-<0-t(sJCC8`N$cV@R@S(Z`Wx$p;|L!f;=c%@^N{Z>KeA-auS6Do-A?|nwD{w?XOKzd4_yM;gf ztdmvw9XFZ|+JCUBib(fvOU`Je8jNFcyHdCK$%2NcBI3L&a>J>T67MKHxtOZzO!vmo z<_W>cxx(V}D(8B!moTz!^7-G*-7&AQ^Lra6XmCGUf3KW&eK92X9u0DFpb_&hf713dj9v z!w}c$abqQfpU+#SNiUOi`>1$CR7wpmX4rqL2JUVcR{##AwR&kZeX{Wn5jBeKq{FhW zX_q2D8uEsi-@reAr#Xw`62E#6|8uorM}y=<8ia}fFc&X^)kT~avOq3qhR906bP)x&Ap8}5QaVzliinEj>Y zIa*})rC3^NTOt?Iq|f}eF- z(+Hm5VveQjWi#xVek6$=4?o-lE%qARlO{wOGDK=HLsc!oA>N9i8dGtoI49@lV!gGU z_+ZlnECT|_Y{vxpD!L_O{L(W2;4b>5y+yH6oVW&UdpR>Dzxdv&glx{JZ;KS!Q-Q29 zVK}XQyE^TW$o4;a0z!3;dtLz434&IiHRR`Sny%#^uU7VdyScwJsNR8jLEHohJenzf z&|Wxrp?UptHCOdje26I#c!^n=8k|#aq@`QBuv^k&XiAaW92`x#4QH={PTW6stGo*g zH7^>xn*3_e5ac8vRPx}9BncY;|D9uqqyguJPtSF!2A=}f6-p5b?Dw;XA9O5K#*)eh zx$g_V@^|9nK?GWt9066sC$;nYKIg-SM87;BE3$Q%_wg%^Fr9^7zNtrt#nql#l!k(j z`Lxmq{zS4LT`^z$WF80!7@2jhtUjFb-Ut19azW`d9TVT z!Y=bWKY8`}`rq^>5NC*#9C_FlO~JioX~OnGw#c;Oqy&NpuKf8T^<5B_6bBF|J|xvR z-WJ_0u_Y+Necgc(E~Who`M1EepGUe_Ir*#_R_lFO)uJLxD}n^;lJ>fIPI4>hwL(U{~X z!+1G-i->})kDe+p{#eM#tn>6H%ey+aG_6v-xccXS)!Xo{0LRODIN^R%<~=rjo;de8 zezx%&auUMKs#h!i=bOSkgiy&ak0-;u~RuG-oiUJ%7vZum+D7fY0g|Cntit ze=oHA8*SxIFQ!xj$>a5ICFb?7A9mFh_=%S%UvtNhZBzz$&S&2&*b?Zg0wymT+3coJJ!czVm71a(b6gN*qmJFz+P6fLweEzqE_+WFj^=sVhWUqbT=bW0@n|mo*`NM5@=5CHJ z<<_i!9%nDR1Z8KE751hGg{CRKw=n?=bzU47QqxHXTTeJk0`{BF1&1pLU&p|-^t8DT zA3nqh+v)#jxqjSoFAJt}!GZ-5TFWArmfe{+r?ncdVt9?p<_W6GNo!Cla}g{<;6nie zohPuKONqnFM}R{_D7D+B5kM!j4v zukl`j`L?)YPbWU=`>hdM0tnSL=@71(N%WsTf1bBdGKil_~q7GB#t;;j6ci6(gzkB)0ur!?UQ$({YpEj*k;t z`xDTUltxl7C&de!9#RQEA%&Hi5JFmMlC$D2wnJo=|Ag`BfH~o=n^j9n2*3cO0Q##A zFpzjm%yPd4ZLw7iQ4(4ws|`O;H9OqIU9@?0w#9zsGlJO42|9PT@_NBq1FK(<6zKCp zI(@Lwj~0j_%)&=^(ST&g9on4i+%WB_D+Z*gR9CORoV$iVjS~pnwZE7OMOr>+cEL57E^H`=B=k)H6X|YDf z#AHfrR^IP@{iM?KomMyVZlu{Y-j;2*Ez-C#)j;D6vccrrTQRIsZs%ehs%jLQr}(0R zJzdeeQKQmQEVBD$+@x0^t>1+&NvmAfbf|CL%FfKpZ2D`9CZ5eKA<8?M&2{!~M=)zA zMk$eIbTRW{oVB1K^--+nHY%Scf?Xy-(#TWQetYVs>>8F*Mrc7p>9i4!1UM()&YW}Q zSdDuDy5YjhZmbka6ZS0FL=oY>64SXrvQBiJE<&?k-T9ZI*!zs9HG?bME8D_39=47x z+I>jG_>WJm2Pf;g60YrvLoLH(6jP^o+bXG(Z(QcwsL&9IRbbB~{#MlzH)()))^K`2 zWuB?gK=?EYoFSgbt2e;1MNLbNWu`w#aAyK|Ki~3nP~Z=5_3}MTq6AFld`0cO!1Exv zw;R`b#on*3qH1S3D^++BPBD&UeTfBI$us~17 zeh-QC$gn@$!efTK)5kF>5ZO1|o^h}Kw0@jw1D*S@2OHzA>mvfL%e{dZqcm;Lk6NBu z#kv{Y1gjAS+>8B<1u}xjYl{@bM+RGGe{L=)aVpVg_rl072Rw#G;uH0*Zg+bZ+u{P8Nh2I&9@i4ukyP%{A| zf1EMcV&43vKv784GW3zhg9Y0x6cqa?Pl)bb)Cwz1qs#li*;!gyR zMvXGTPC4oDZJWZM@EcZJ0{57QuTVY3-LKc1ro5;Z`|M=-mV|vQm;$InI0}U~EQ>REmX{KUP5TVj-;gVNF zU>i%|AFMU+_Q)6m4w-y#fr=!$ExliE_wB(bCfTxVNNQ`Tzfoj(6Ul1$MdKACGaRpv zg`@El-p2uq>OKAqG+^8_vXZ=%3~SuTTNkJ}lPqX9ycOGHfr=%+#>QJSY?94f-`G*E zT?gsJ=@v(5ZGrcc5P0ix7BSR$Lz2jUR+8{Bq8a%iA99VHhpgqLo?fhmrsh6qgLKWs zk?7GDqOr+RS_HyCa63=HGXKFLFEXQWjLb#P_unJZlDVRdRQ~98iEirx_~Y8~UGxPw zm4u04Ah!jYCk=sYAr`D1Ktb_jC{8ty5j=o=J1-QVM*zo-WcHKDdde9U z#`fJPwnyE1$S}ioZ_5khjAhAo#Nd-&Yxz&^Tx(7h!f;DE*^Fl-bAQQIP4c9jwZ5pU z(^cTIiAuDG`6Df%%=N{Vb9XuaoB3%Xf?Xk*(G0(y4!ex?DU&9+0ACTW%9qBv7U-H~tTsatb7#_^g6mp!Al{%bo#vQYu zG3m(saY60QCq|DMJkWIu3XYvV@NhDq-yW=dWKY^oDzWOjhcf}X$5vl(PZDYDr+4-0 zRs9P4#Gbh@y`&7^{G5s%EBQ*N8uGfTg8(UTGLK&n* zN-F_G+6NgXt(BFP>Z3nlY_WpRz=cHCpH6O_xa7yh(E((t3h>|_V~Kt~orrycPM&Vx zye-JPMkgdp%;S36J12s@2WO z$&vO|X(|SJ%K#&X^?D&2cI$&V6=#d>kk4YE#lll%*1%iHR4f5G@e`UGOm91zJu$ z!F#KA-$DbMe|Z1?{Tbu;eE;{HYsuBcRH21pUz4HI@RP-S4gI-mY?va(lQgYbD3ZJ@ zrq5p^Y$+zmX}MmgldVc+TQJfs}symJ^~scm2jz`o?k{#q6| z@XPiW5b6JGiZwHy!DVwo4`f)Aa&vQC_LkLwiecsAbPJX&9WF7Yk}Pd_c{1F9gR?=C$D@4TYOGfW4^0~;iX_StijiAHcY&iRR+aa3(v(Cmi%1d5f{!>#%*Zn0{ zwc=zc-PWTZqIf;`oLsKWuQ=nh3Xj9*2K4YzYUJTX&g3+2llqS<{#)!J#|Dk9Q7=Av z3ugX3C%l-scw%t%U)mJ6^=5$KCEe)jAp)h+s-4bcQn0E3#_R z9;X9%{p+*!-?H}hc3cKCK{ad2bBV#w+isHbB-q62WN!t>A6x(jE;2gFkMo5ELo%C~k?kqcL8~vW(9{1Y{$#(s@KppTI%XQax}A)5cX9IG1tiXbn^8xKyzA{_u(cMG?O+q zeEXBysb;bo=oM<0Uc?Kl6x5&O8hLLBWn^Wcva=PRJ$okZx*7#s6Ew-*{~`#mRb&%h zgY8^4J`u3OHgeV!|4u0vH%v6a8{Hl+IS=17ffI=#2Suzga(y~6jXtC_|?JGxfD zG6?~%{U90iSJr#q!&fzb!)~&=?B^P7a9`%z)~hYs4vV>l0bKBdLiXsY3rLfKP(lizPC$pO8BCwV9ITI~f#U>@D0NxU z!0|&~pw%UTwCt6Ub^?ukXnWj4S8Jjeb9{k!}Aj)mtGoK6oWKMiD$2% zEr^JV*+jg^10GUk|A*xG$K(gx`2(Qw$tr3eIKGvlHpT%U9?Fl3x<$?)u5}5_B7QRc z_Vrc}t>-jEjd*xkqUOoaq%f6jZsN0pZF{9c{jT>@UR*I(@YT6q3c?~j{TjXkph9U5 z^{F<@Faw3IRzi#(o`d$q!#(~N&fs`Kk79hTvw-C4czKW}BFgY|3|w#ET=a=cMHLe3 z4wSiUIbSSjWCwSL;K#IR@c;aec9(3F5Xkl4OZI_`$v!(DGhf7}*49c&{cXKjeYVqC z=Csfu8$sUmQp2END8`G6(xI&pV?hp+a>$orZu!EyKCV7lViRvzY1rRHzWCY#9k8tJ zzu1vHrUS%;5P^=YSRfs^R|i%)83)Z*`};K}J?6r5(dZ%Xt-9ewz`YCji(mC}VPw|J z>(80f7-iwOuZEa+qWAKi#DnhB=_&TlGAuq~HqakmtAzw5XDuoP(|%dEgZC@Yy8)iX zX1@!Ig&F5xoS))g!Qk2PuIu*96De?#Hr=Ji$EdS0jG9XyST1(NaJ#NsN~0?tZ|_Pe zXo2j~Bg9Riw=a>^yHXhLo$ly7Vmp6h$gH`tkblv=W0ooLx*zXhRq4IQaQFpW<>H%C^?Pt zf%oGiu`TCvZw~uUemu@`dJ@PnnJw3 zr5TC{S~T6ZJ>!c?{M4k1&5p?MAUz!5P|v4;;RsHgo{T}w<@5xFQPF->_eR=ACvf<#5!U0QXj8M~^`}jY{gQciua}Veg+!VX% z&YfGHK>N$&YdSRib@Hsf&ATb(B&K(5s=$e4wTN4dZ~{&6qMW(hpsUjj4UGP0Z*in- z0bpBFeg(ZEp6}AO5NS{1s7mCNDAewBk5NRRX=8@BYfs_{Pit;n2OHN6gkRiWaC?`> z?*mt4P|y_|#`OaIQVHIQU6BW&`deMZvsIt+%i$8;S{A$A+sW;-j~=HeS9fsr0fmT_${PHb_?Lcz_S1zPQT38gZq)31MAX{gGAXF5@aEUOn!U0KyZhoA`Rp=A^xRUJytq zRS?QUy%u}6ys~qfsBD<-6-RGq62oAAi?z%{hR2qrgY{WaLjsOlq|83+Wu5p08vjK` zu)u$Y$-0s3{T8;ZaN=fnnQM&t)idm1fyXR7LQvQfoz{Q$8^>CF20uuE)D*9s^ts#U zSXR)LTQE6_NdK4^DJ1=)_a<8R22tzhblEPrI_{;afU9wIshH0dK+cqcxzC;T4YMib z^ir(Q*bE8!}!j#t(%+T>u}KA_kVH3Q`R;pop>AnkCsN-+Ob!$e84X>bBe^xJ9LmukQS; z5+Bm~uvuG@NUqY$f9?rXqfNSOUyE&=6$osuY+dLqU0avJdkO)1ScnzPEGMH!i}tIr z!kWq8sp(h2D1rMS@!nWbRQhZ0HC5BySIol42F~VpaQuNO`01fUao%V~ex~7a)x+Uc zkb2B6Ra$BPSnVQvJ7*WNORP2-J#JXhMmW+{rkHhm0k#-q za*B8x_jQC+D?m4PMTE;nA-Zgsabmkp62o0h_VvaaJWpfD_0$WE`f_gaz1m+fbcLH4 zAd^ONVIJlZY;s}E)uT}d`GC6I6wkXEP2s9qv34fSKyNg@YXtnhFy%E*#w4=4*0>m1_ce2L(3cSCwp#SFb&UpO=(>{V5VM&)H;S?Xhw5s)ja4 zJRw0*cXBl7boJ&2 z5&1t6t31R}>4V%HQawKKy^Lc8#11HSGDXNR5Ukt+zQ-g8rD##~+jD^aBzG?35jSyv zH)Vz;U)0ojk;@rMu;HQ=hDeiBDpb}x_M^0HA2LmJsvInNoeOdbZ;sL}4{QbuEJO z60RnCE@fqb*UDQXL(T)Tr~fRKa+Xtnzv}5ppTLzGP=>440uDKcv@HyC8|AcG2(AXy#ea)9kOsrjeUQ>?%Gll-dyy>rrNk)}tCV-F}7_fM9CpPybpco^5*?wWzko zO`Z;DCObbY{9hik23UV<40m|!gUJ&0>UktWN>hAk+|T$RnI6LyI6OE#p35O`k3fva zKcSReCsD*u<8qlrZI>4lp_1*i{pOU4$nM8TiW8HbStmPQZtYZTDymzoMWdnqb;fDK z!P+_GDc)9>HoXn{Zgkl&V5lIbl!CCLuAWzH*bO^Z^#)adCwET0Af^G6B_9iA@<;w1 zjZ#5ek30Fv>KgjUU>G;zD^&jYz`^1eqys8+Z=T8r_OdO-4+uM*aHbKqi55I6j_fLY zkO{&4S_!M;`ly(VWtJqREYFtozcV{Ux|uo-;E|JQK3n7!;ff0CfTQ`uD$|=L5XkC% z_zx)RfI<7Mbs0btu2BEWgLZtX*Q>)olIBprhP&oFvm`1f(__zRU=-caQUWYpX?RrX zz$)ys=JV{&*Wjw{dgjvq$Rw&+l5i~v!;@EdAXZy}fS%~RW!+k;ThLuXxjS&$_2$eSx%xXTFo`elL zeHW2+1$9Y(ognmy-RN3wX7NFpHQwm_T}Xf;C~+d7KpI?*8r_3dds*3kS0G?EEi*6R z8Y?7#nBJWwA%DXwne&Mb`AG8(-B`YFWe5SYMw#^@=oSP>WFUVc;5uad#u~nv$i}6N zkN3DO$;9uCG6pzX2vr)mf>%GM(h%vp)@FDqYzO6C|FN8LBG|T5<%Irev>5Je09nQI zLHIuaVi&~aVaF+%(?N$E%Nhg6w-@dU5x6hJo&C6v^G9Cu5(7hQr1i8!`{Y#RlA9(; z6@yb(0QVvIK-PBD*0N&!vGYG-4V-7p?V1j*@Ebts!}Sszh_d&CxD*lfl8zc68|bQ7 zmg7$WioLo6049LYvA~~bOd=Zl>LdU?H`6ty;k@t)cPy5JWpe!Lv~|8K;4^a`Y5&Kd zz~U)%mWFj8Yp-g;NFI5fJPAJP&nzNXD0RKm_-I^s? z2Ldg3TNC3kkNLoX2rh)VLO~;LPUkEN3@RLFu2C(V~CN-vp&12zTpb z_2H}AFF;m4;0|yF&bYc3&X9PJZ>%rMP>dP#m(wqK+{?d;1+^@|;d9(;#tQaGrWw_F zafpfO0g3d`Di#$lH9YIM{8fQb-OsNcR0RmREWZR@{(l$P{t{HH!yfwoaYfpk>5RfpG!gUu^*E16UL5oin`>iM#Mv7K2Quu;&F=L2W87#qsTdibk@uuM0?z|5Ne)`N%%z zgYnSbaIu~oE;}^9Hv zs)F0qFM@d~``ay)BI5NPe@!zopa0s421N>2&f=ID3Kf-JM$X&#f|vwkckU_hZ!)z; zE^a21Dxn7T`hQ`QR~qfpe%iWZkK~83X^V589KEN+mr;DmU4PlgG$CV!lAV%>j*iZk z7Rj5<{m ziRF^*?`z4o$qc6MAq9DoAq7Q6a?s(yP19L4dh%XnEf zGGlC||K#0GP{G;V5%Im?X47>XwWL;Zs8)R3nRR8DgDqj@!buy7;68Ah2zwj+-z3?W z!w9}%Vq5vJ^mJBoCTTdxqUsO||z&_4$eyH&6$Z|IIOY zwITLT9Z>jxkiw_qr0`gMktQ8bEde&FHPD3E45JfqB}yCXkZ*s)IL`Um|Z9jPrxrh)i##1?r~9L0((S#ZYb z$V6o;Ki$^`3R$4IM2v!D*qMg^$LZMB|M2_-K`7CkXMuVS(I6@0fV&PZ0jN@8d}NQ7 z`$A%s68YwL2!!ZpA#;|L*m{c*9VIHlb* zA$281k_+7T-E7uQ$ew%Qe;Q|;WqCy=Eyf2smLIp}1 z-_8K3D}C)hZ+Yd5`(o|~oO%!+^5+V8A$ffKYx&h?tSEMHEaG$I0HJEwzZy$fAMgeO zPk2UhD)6aZ=I8z=V3ejp|7ld(T5QrYVI&UtK9C!S0#yO@f=mDK!Kb&NxPXWg7ujv! zga52_HD*G#m_HN|)RQVc$`=TL*n*lnOFdA$3!wtAKp^5gA94k!E3Ov$FWgK&%lQk7 zH7H`GlBHrTOa1X7t@r@`?-hnSQnzs0CX9K^1hIl12+T#N#UJ_qd!a5(hiGJM-liVM zEF(pL?tD&_jkY}Lzw;NY80?9>g4;Z=a)27~j!LpTFfiE!aC?Q(-jPsKC^N_xcRi=& zZP&x@iQ(7_+-KPxbXmefn+`(3j#rs=SNZmB(VHCx{}sF62cPqisQz9N9t0}i>Jr@I zMfz+88=tkDU13wPT=loXp$@+KIlwm@P`aTyUk^fj=7YqX*UUIv{PvwAbz1pd?r2u> zu1=y|MM!I{;D+n7|Gutl9zskk>It}%rlEe2`Y!ANhHp=WHhpOxu6Y{qy@7)<3Q4=z z2MP7$*>GLRiy?F0@WfsC8*pJMb|D>RcQgQGOdQzw_c(^Z8X$~i9ksH;!@(-lozgNl zT!s@OmzojB)gxe#Yo9oyR3909YxOS}fwqkN<6wC$6(N1812@tg=b{ z4?MdM)|qpxDogu)h8F@->?|e)c2<4!pgLQV*=_`2f3WFZAKc}Ig?Hw=c&Apor+D0z zB`Vc*)|PO7CP)gAy$hc5cb*T6h{h6UL7=E=mZXEc4U7Z8jP*L&G$LyX2Rr35g(m+= zK5<)Bz`$m_P}AWmvl%Ed<`F8zu{Bhuz>r$`$?T+_X30WWhT`J>ZF$@Vls{mS$SCH_ zLfpt(MYcG6#0yeXp2TOsJ*YGA-Cy!Uy4V6OU9H&-@Gougfw%`qw|=@MYzc%?GXgtgcD!vvfsMJXn06GBDiU)3b#48loLvvmZ&@xmOKTslu z{$K)li{*LcCp-fZjHA#Ou%Cm%>OKb3?62i>$Mi-LLjtIPNe1wQEZ-tx?gDX;5D*?( zwNOAp`GQanmw@?{0Q13xyUo8eow0*m(L6$Xb9fMDG9s9|J?w3j4ctD1ojuoEM+p}j z7_kZUeM$s976L>;JnNK%c~7`#@mo%XAi&YO_&+DWksSB{_W-Wrt{YgvM)}>mja!Pq z;%4Xbf%Q^L;JgMqSifsSxO5{05QJcde~yc*a>5ZOe*sPO^MI*9ORr25=-&4+nVER9 zcgiYzsHc;`r-9&8K%}28rFX_OUMfLM=80dTZQ2+3!O&iyrLb(ixOx1)qHqIAe=wX7 zM~7-?Xbgg}lIQD|GMd`j(TAP@9)jcq%6)4}2@1u5bX*peHu(BFAKQF+G4O-w+k zuf8MY?d?vKa9zu<=rAp^0>B%QK7GFF?sYI~xqsMjY54vcdH-0MEe`*gTUe}S$(&nf zH?*egl$)@_@rWv}#7Dgn!EJ$zL2jH&{iCXDiT*zpNBdtKFI8_hlkV4T`Ko~m^nOr> z>avRw5&6Dx0)_#)Zj=qL=AzIV1x9syfNM6m`QU}<+-Kd#W6hvgOVP<|GFk-e3rk6` zFLXyN&^9(UrS_BJ0GJMVciEKLfGTGFBGYHz3aVz_k?sL~iOv2hmQKhf3Rm!l(}&3% zHBr(f?Bb+nV3gFLo@HW2IK9X!4()fp5y}7&z<)u0Oz$5@(RoMFvvZB}Kc1HZZEw?S zapfk(y6I;T941Wc_cWakDSPSar(`}tH_UP*IV~56X(>W(bD{V#~kSn-))atBbrVoqm8AdNY!X@GXBuasB$| z{|S0kL1F^cLvD+SE&w9MOrSz};eWB4EabIkg;R>*^b9y_#3V@p5#D0F!z$C|Q3x(U zNly1z5!9acf^GpQkUdg~eU#C@21acDZvqFRErbM6f`A~#>g?!m@#w0bD2Hx6Y^>hk z{^^2Ee>w{&Jh-R#-%pu1B>5}F`f#=hfjQat^wt8V7**(fzFMv4kpe7t1nv?4zoQ0& z|BtA_q9-Yz>1>AZq%YEs6^cvg5lf%^y;{+RCJ-BhULhhRr z7A?`ZO5y(*Qw+2f*R|%Ei)I;|hSJ`@2VSNVt*IDY|ysL z)jYAfA6Ib+-M=h(o%ohr-+zEn#W)=)&e#`wk_$e4A_0})+6b3Uo{DVSVKkWIiw5Zm zRKZZK=dKG-3wt52c7wMEIx3Wjm>B|b#|g&4FO5;k%c?i!$qDcdj~%8Y&w<34Yn-Cvg)bhF317bkX-x!0+5e}iTPuE2A=@EtP^W~;AOm^#>O@tE z$O}(Nke7>-@-Fw=`Iejw)Z{>Wc=9*WKaY^fhkxGKxbTgHS+_or((1Iig(C&=Wp!Dx z_N;JCUNIC~i?(+Hjs>DLaj+8bJ#hj0gSz%5V5UPeyREHHF|mRQ&Wl~v2VOvc6DQ+e z4;}|oqx$n004Nrly7civAMPJk?Er2S!SkpZjSu<1TD$V78uvB)DW^EnbPuPZNrPsJ z$DN1>l^?9*4q>wdWDj9gPh=K|8huB&lvkAsDO~^YQ6#k6j+s z;jqyNB;F3Jq}h6wvbC}O&C0|wMl50B1ovkt2s29JlDVliV`_(H#;Jh}j0k;=cLX6- zvC1y~y`MrIV!G7a>#-Bd`)p;GB6Pr=G7buR>$ zMoO}SIQYuSo2wEWj1yp7JGkxOmPwNCCWa1Ct20e}&AbU90hg?+X{_67kr>n>J-k^| zsp@I}H`hOG{au9u;fmp@rpNsLx_7-a@Zg;I$D4}8e$Ku(QF@|_Ia9LeHHFg@6L$f^ zm_5g3xzw%&afHgPG;G`LT9kkHSnoT0M~JbAk;+Z2>AK}Bua|Z1_8bu83U9j@i$;X~ zt0#>{!9Ws-lSZE+vx^P!=i_C7U@aEBzB=|H8UP?-F(S9LvqS=mEwT={i+#~-gP@iK z@DqP+ngddcm@Pw%)qi3iwL-9nN^<>;1a&mMNR%%cq67PMS|BS9ec`eEdypWe@ z)NgrljNlHT8voK&_tjX!fsH(Wb!MV|7J!_w%k8{@3twVSKRa(pbeIO??@bkmZe-h4 zXcd@{tW{uJa8&UBSa3I$`%zqGYGf&u_SZRA(xOe-S^$z9W{Qq&yFe}sY$e1@J{R&r z%aGf{FiJHLq4AM+53u>Oxr7#tckOpqD z{g>VsiVV{&Mkx=D!;rxUw+v=#dY!^h-G*T%!y8AhaFBmPuahkBWgHW(ZTgx8L$K`s z`1RN>1q)RJF-!KwO`GIioLLE7FK98uUudzX@%<&eI09;lv~d%{BQ&P)6tcDUnc9^( z6%mu2239P3pDJC{oTX5?8Z21gY;t#NzWU+YvPG>q5W;Jjn!4h7&-T#N)wSclZ7&EP zKj`J@8M#L%#;i>s%mPpNCu)$1O1X8*0D7HT-<`#o$C9$tvH3V!yXdx6`zWcX9NDGk zv*4{jtB33PL&8=b@^GO?FST&M-&c21tE%NqFfES3rKW9`OTX(De1WL839aATuxNN7 z@F&R-BmEz5uU%x=zbaBW(UDU~1J;KqWAEnn6Sza@UCKmwv!YV4tgkIDE(VZ�luh zM?iWfHdD$AJ9d-TsiCnk0a{lGqt>9^kB|Qv;NJ}B=-@QSgzmTmvMz9cvooYr*e0J} z=gAp(#)RZO)c3g4S1n;aXvQl$(oD((ZFE2(F-h3*&!W2f`clxQ!BK8h7BnXRlYhH8 z9>+pxsUgX;M0|Jz%^OkP)ME&Cj4lPaIX26eA0_c8x+7)OzEp%ff$V9a2$uQ2kG0a% z)3<}+h63)}_ba8gpPRQicY9;Tc5J7->6T|K1byl@f4hvZJMdTY&n>(`?1)+cL1|I` z{!hE*P4=$s9BD49TI_3e4BKMADykUEq0S@)JD&7^crfot!4tPEUFX7;-5pDR%XZ4M z=9!Oku~}}zv&DRghn@(?OM?1N^LY^0_8-vmjGR(H|Z z==haoX=gokTsZZgi(B6;0!_Mg6!Idzf^k51q859`bPs#A zo<44hLiPONjw1__Q322o>Z@13Gz~q1>g*yj{~*}0NATAKyZda})L+qPW8=n+P0!r! z*VQ#aw_TiAe-E}OHI|c;6FUtvySB@JAtzh}{ha_sfSo4+@=~*&88c?cVH;vxiWh!$ z36cc4wz<-sVf9O(NL!ED2G!mb94QO3<@I|9F4bIiliwNq{GL>?i(c>Z=L;AAboT5O zaGTNFH^x{)KF4l)UiN&S_-R!ln?emiL|*P5|HY#*;|HAg zI7YoG*VPzu|Fy!R;!Ut9azg4;zv?0+XL^^faG@4I=_3X-D}4M54H@9M`+=TWo%KkH zszb+VxnkFKD(&jv7FV9%^UP+1KX3z0O8Ox5CApcQ*ZuEwHbZ%p_U2=0$>S{;m=UDwg@L+DnUw!++*RxlN{B7AH}udj3LO zBi&$9#K9{xAi|RX;l3z2r*bUMGL>k3^zQ+(VVk98q~^SNPq1*8T^eXDvPJT;*53Xc zcAQV4c|oSs$2T^clWQw)8;{nt+|sut@21O1xnm-RB4Hhb=xzhBW=BC^Qc@D->fYWN z-z$#}4K~`&G7TM^ zj~RS?-4$zDZHHVj{%OfW$lS(d*m7e@242V9WxS1tz$?tcz(uwHXmsbK{0=k_QsEx4 zw({vOKjX2!oh-O^VX$;aE;Tm+wj&^Dm)2P0Vw?2wsa?&rH(Wum0o zhD9ji+&o3x-akdF|32;u)uHBFw$bA9s!6MdemXGZ&T!uc&jb9@&c}s2TUA+D@`$>@09-~2)t6J$ z(EwF*o05qsVjx_y=ihRA#L1>OP%&OU0@KI6k*uvbr}GE;Qp z+-0meqLUbl%Wa5Eq0sXS3WnoPGdDvA{=>;ia7oSCPN9R3R-nU54kGvn z3YXW%gd$|DDK&ZF65Qf7z3QwgAk#j@Q?d&(Dg&X&euPz3l?8=#Blbuyt6as_u}h5Y<{>j#5E2vd~W z4sme+BxJOQRD5BYhX`Y3CMd&P1wDk&G5w^Px;ibk>@bpt_|5Vrn~k`wX7h zXB()%LwqXMG8R^X%Gg5)vE!4ITc0_ipNxdJjt3;hU<+We0o@VqQ*j@R5k&Cy65I)d>eQ`ak~aD)5GQSY!yg?&#c z*HLFCt-dIzyKJ`5LR- IWm^va1BbxOm;e9( literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/FNN_Loss.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/FNN_Loss.png new file mode 100644 index 0000000000000000000000000000000000000000..a474b39de8fd5450501f2ff79336836966953356 GIT binary patch literal 50413 zcmbq*cQ}?&_`i`*kV!N+#tiH(hg^;J$z z)BpGYhq;v@=Tcmp8eHVKg|wPA78da%^auNccE-{QU!^@BuMbRp+Lbctw9uWV#2qO&Pkom?$7Rz>j*+Z6oYQ`ebuPYs zZ+9EsX^G^m|Ez2D;|nu<$9_hrtpCl$o9B4+yi;FYq*F9F5hEdC6)BgZ=sLNdpuwV$ zDj)k~u#lVR)%d6SKMN!AzkWTjva(9I(9S0NdkCnY~<5}vfF&@J^zw_6-LoEIPX3v1(#*w#A+2#9|MZ#%jIR3XFR*ZuB~C&lO}3%)#T*2Z~hPBoRo>YtO#12Qws zi|X((&VDRVlO#K zP-jPGp@c-!!-h8(W31bRK4}yLTz`J_QJ(r{yZat)rTvI&y%)K*^z);Hi|gyDl744J zHYbAnO!9H2Hl|`Irv@X*wH-VQhMoM*va4ej78Kg!MAb^{Og-1n^3^x$@o+!wWGLTV z(`XZ#qT1Qr{rxQgm*6bhAlB2n;FDZu*g)Ki~ZB`tyzDX3oa8HjY1A zOz|!^;6Z*3l?dPyQ9T^1@%i$!>m_^%;vr&N3jT<;?QDz(;ssc?^=|E~v^#G7PJP<_fdnpvMld^ER#MZh zrS87FN=~k6ft`?$a0DOUdT(=TWqYB5e6#GFhy$0Wr{@);Ztv7MC*S^DL-LJJhSp;> z$IW1J-X|s=KX&Y$^;BEw{@%7%!1ioz`>)|L;foh9zIgevGh6qTw%ewD?@WJxzsOPz z*%zZ8Uk?umQo3_o53wLrG8WgbOC;It{7{src`YA%wHA+Dvy!h@vwF2xN5RJC%EK0l z<3vOT%M*?8R4Xg(;wyc+fk7c5HSkZJF-P&u39`4r!JEAmdtQxtkGKB()^yvPoE<7D zsQJ`jUa?yTaoJkqLw5Z5@zGFK?NMLW3=HP$bI1r-b;OnQw*r#fcDK-j^_lRe+=-S_ zR#x`WJ4UJE@UxGWxk-_;GU>`wm1vgd8JB#g3KT{9q&OsiytCb#Xd+dhE6>*FZnNM4bw^ zq~v7F^&xvQ5|Xd5uI;ttIxXQkZjJikS}K?g_;^J`tHFH9f*6E$q?qeflotZU_b#s* zibb<)Ty@&fSka;YsioLCm)uR@IXzlPZ z4{ZKI~ng;587$s=r0+I`JbsG<5RUKtU$GpkN>D+zAUo zssLE~dJ;;?=?19WGY-P`^RtDERRn&!gLHJ0$%>*RK|IUr>xNY?j(e@)A3a)}9~>Mk zO-g=~1`ljp zEX~)%ZX2Vo=$dDm(jg=HQ}X#buKWy&iaK$QBB5Pu+n+|%>07a_@jJ}An6Pj(jJ_jB z|8`Y%wOWOnYh;Fy`<@HD3daM4HMiN$62M%kCg`r{2+-3%4`x#6OjV%u;L#D-Uv*xc zp4^JVLD_b|v>@Ak-!0#4NFB3roQx4OH8tg=9k!h!2qS>nW{E~n>S*1&x3xNBJ!IRv z1VI6Fd8G0g9s$fPr&h6zCADgS*^pwZc(k~?7&kY!rt@50hHH6w`Jn6iP*PITVl!t2 zR$Wicj$IJ796R#+_wO$z{W;$(CFfY1BDi&> z6%-7IOC7P`wp=hBs2cTBrG0&lZ(Vyvb+Lv_;S>c0T3*QOgNDrI8Awzsz@Atgn6=8WWx8#mI**EgvJEj(a0$f&3^ zAG$~Lo1UO{-um+tvJefbNheP-u(0?Vv_@ekZ}W-|tojv)A>SGT5X&e! zm;BV;H2Z#1r{lJn{PE645dE#f z-zm{hRGmHL?yG6qbV$DN@>*(SipQ$c6|t9@CIa94h| zj*t0q8uaJrYg&B8!}}RWNO{Fu)Ol@j*m=Pcu+n0i@WQvx8Un+PQ`E!(ni57Q_+FhN zv3w4w$r=DjIV1#}&$%eae!VxDrkY6uC_~atgY`Ck{>RMnD5yA*Nl6Sp+hT9SsI`)x zZm$0BdL`z%wfLt?VFiZ71yLZjJSayI9KivgZJ zUoxb9VMe)oYIS8r7m5JveoBZLhz`eCXq_{rRDiO;|r! z*Eq;)Zz3ZbQI&?>UAQ&_#t)*&sn>F`3(_`!Wy*2Y?uw+a~5t^rl}fNaiid|C z!t&-kpV4XK@1Gt4=+AIXOG_(V{jPDv^he0r+(7tRqOy1G<3}5dqb^V<@qYN!*VdxQ z<9b+$1#kfS9QWfRA5}9As$UXjjLXN1wbs+RYmV7Uy{4>P8n2HOw$Cuuk(Vce8#4$B zM!^2ZJ^f^f=pldf@9s3RH}>YcD-i&z)$>i%5)|)|kTB^36B>L6XayM6E6edZgjjTW zA~zPRiObS8jbKvQ)W3K`Zm_PWwttx0?*MTvG!(~GCq~qDdgx;{*wkbS01)ovKOd;$O+IPw`Y@Xcq>Gu+)&=`*#J!%D! zMeeZs-j4$jDF%SzFcrB@t43jLYGX#V+Gi7Q1*W*~?}_~Rb`v2#co*#{@~GU?l$1?? z`y&890p7i0()R{(_nAn2z}UiA#Ns<#y_(j9kdYyVew?{Gx&G}Y@e-`L)mJ=n3%IvZ zftl8@`@Sn&uwGTi_5Kr%yOL$=!_JZ!o3?&xpj9(_jF@W_0JlI`KTF7k25m7i;T&3;D+xae%-eyoB4BSj^L-MK*aTD) zz0M>Vv)wo!>A9pz6y$*Fp>EP{RP1ky(>P9$z;YoN-@Z8&-|kI9FCr>ZxiPv6@N}$v zdw#s*7VRZ|{xAR|*`@>einhDflz_Vx#CNYil}-XYjHi7bs0W1RC;&lv4vv7VEH0aEd-YRj6uycZy%YMM-va?jLr>FM~NEIxZV#Y#Qzli~q zqd@>eF0f${RxaOotnIQSS!_3_j_Fen+k8a`mM5DXeAc-jrN&YVan>AdUJlo9Qj31z?X656H4cctFDW&Z+@ajKm*Z!9JPH93-V15mdyeL@ zS8aVEqTgWS9=-g8G>Gy#1*ib(h)wy!py9^W5J1BY{p7f-LroLk8c>n>0 z_|DvqJhY@h%e3|Ef>`o-{d)Be*TDyBZc|;g@rIk8ahCf`5EJvUl@@;f z_U$fl;L)7iT(vJxNUC2E*Z21Jc2x%%NvsDbznG^@J2oV)NK)*cRLU|w3{y(S&;R`l z{pr;2c=Bz_rSRp<<1wF9Sb=J9)!%IT-(Ol8W^O%AgDNX}{a=dJ_0Q3Nhj>Oex4!{2 zhF<5~++0Wr7wPG7qg#Le43fE{GVBb`MebLtI6C7jiTU%xICBYbhV{;dH(IN+e3XK1M{8@oiObcs;0i)dSmes z!ej|8!S%SQ;o43-`GgNjZu~2+L)j2IF6B)8T?BnbEcz`DH)erI-w|>*$ffXEXEtwPBniP>idm9Zd`j7$YMiGp1x@WIUG0D@yZ<<|nA03;0W> zlMe|WtUR5~ez$g8W#g#D!-9ckTOvar9m%$fc}g&IQ=%Hm809ecdJ#&&SP@6k=vFBk z8ynBvj*bqKk@B*Jb)*eJ+7ATs5fl;802$?4h1+gljy?eZQ5KsW#EZ!kMD9J=hs_Nl z+x+GQvn(hK3dGmbng7fEfuV}Ql)QmKsHmuTwS@u!Ot~jxs`TBN2}bWx+u~*B?H-0HBG*X5{L}4%zBNPbED)hO>TNg@uJU+v8(nvZAjVdwauy zb>}#*&(rCwudmmSj8rtNJ9de$4fE5aiPnGA9ASqCf0COQ6n94O+KP!VY-x>XqtrAIkvX4Ftvdfyswz7nH6C^qbV_@toN- zS5ey|T=_LLJvDV}eSS!-*e1<5e#p%5cV{wQj%;mqzlq6@FFrs+RKFj@T~ZWJq+G4r zo!F~+np0XOcI*X1b{c7c3%!}N^#RoMY;2!2ds#mNS_V`jEiL__d!}28hO;MH#E}Pz zHDp4XKhr&aK%U=3MNLoV*aLLyglCF#T~otC`c%A_>y!SROOWgl-KPQyq+wQ68%%o> zC9BeJ*}C>51)!xtXiO&{}w#NungTy2YL2wR0A_V&<^*moFfX>tOu!+69 zWr|D0a`{xj zh?_2;S52$NOA@zk0ezE0(rk{NjOPkJz)l!@VO+EvBVrgFC9^z`CqJv_J%;j~(Yqgc zJc`$l2oyIYui4H0AfcjaX$Ybx*cprt4z5N;6L>A8Opy)Db3_hqbC!J>bT=?;iy5su zZ=M7j>cM9fjzSC$eD^*k0v;tA;6B_UT+5Dvv+R#z_M{hN3cw^CAMVj3UAQxu0CZuC zvbfODS}39)bSlIkjIV&c5_%dklw9o9P*CT_A#*|i7eXa!-rZyguIH7R zzRTt^PW%3P#r{&o{%+<8sY|FJ)ylNzckE?*(G;zHe@dUVRWx<0{}qjsHKV3P2aAaQpT+ z=;Ihbur((9*1M~{)+4U#OH1{%xQh_`=pVe!YbHPPjOzi(wZKd?7fr=!%(q{4+i`%| zsV#L}IYvl0`4yj5ulvJ2lcC}>IyyQk8JdlA1tV?N?V|NaL414ZwgW&JKhY_45kJoI z281C%RB(j6T(~jj2k3?XmTwHS*GI5~E+8vkF&m7y`HIN$*SCvUJgyR@QULx{c+_b;rX9V+JKLta?LvJO#~|}1NP-IA1=+^%c1pu zHvz>B4-;t^hg9B2txD@{84^ENo=_O2C(LkljYyw%I}bJp<$gX+{{pthn!>N}xSJ3j)!nDc4ai za)bbjenuH%(PKbQf#7Yy~>Ur zi^O&H6)_XnOB5J#=bq5rQWOpIyrkWaPh znHU*K$;nkOcxOFevsoA}8zjItAIK-9rKN?+J@q*C+>TO*31vX-2Mk3_7%1FgF+7l6#Nx& z&2308wE@(^ny;YTNRO~_)E@2w-6FVRPC!Vgk23G>+CU4Srp)p! zU)aUCrvT~0EWsnIJ}7q)LbMt*lF7Z8(AsUQhk4S4_dSDA)-8D2lYU0WeU}fa1=Oe| zpnPE^A{lgGtZ|?^0c=_ZWOPJJAn!5X&o_n3ym;~AAgdzahjcec>rH5@N=qL@9tLFo ziMO{oEVZmb-Yo@A01P!M-hD3;L9Pe5q1(_<@9Asl)b6M-D1w0my&=?Vp=d%2lO%Pfo$9e-;;0eaN60=5(o(i0SSr* z9r+d5EZ%_ajuKMV>};-R=|6|qH2nTa4cR&(%MJAY=eVD_?{ANkf|6ob_8nD;$B*gu z*WLH)eaM)ejFgLl?3H-`qY4(x5*P4gNPk|nj}r{r<67dyX>vn_tMzKLK+IhaTb(n&;j2274zX3Rc%KvfFj9?nQGLREtW4#QKib2_?Sdf z-xo$f>#byBVv=BHdw&!(m&|2j6?_)9)py@2OQo5ahqj%1{0=^J-7^?pt%dOhu78rw zjpFH5G!Ti>P#h*=>#!N-zl3M3?6ja`1h0kcT~MsyHI{eyv+{rW`9UGi-{PUI;2HeN z>nLUG#VhrQ9M(7!Qt-S$rpRh3RC(BjiGAy!2Y?kka6)H5Yij8W+WR24J2{=3OsQ^4@mhv;W(i4v}7zVmkv*q3bnj8-dk;C@9+%kk$2sNugm67hjs zv#dBKzJHIf{kg|Jkb=PD&U|a!*w1XSob}CPu#)-aK{8P0CBoNB4%=lF{_L{Qygz9X zV&qM(WkUkA2f%G=Vf1?D<+Y$rCWbN{ocrh>P_BsIUIpY< z<2V(23xGUqZDfD~n=90|534DIQ0variTCzCHeb3T-<#KjiX%dQV0@5)VAi9mb4OEC z(^EIjX_|Su=OegG#|j3m2o6{s#g){S7P)!QGSEBMu3_OGJ^2u{gN$ATPND1pkE7$_ zdIR@gMA+ud|Ac8T4C7t%2jerZxUj6wD!#X{?SXw8G|eJR829vUNtJ{uoaGxh(XDl8-k{tLmDr%J3o-mK6Qu*Ek>)ufrQ zZHvGU^$7_03BKtCZtm<#m&>U@b08Jogo@MmcRFEuP*7^-g0hV1c{yq!%1u2FA zfsnBDv@_{AR3XC}ZxT=|qe0MKhQg9#JEMXU1f=KwB5Njq6*!px6Urs;!0dzy6lNFx)?Qjl# zsF1S*1%bc?u*5bnxL0j{Rl)-N2JsJ}zn{_O24F>EA)W;K^M`AUY!%(z%1GUU#U0-g zD}(HT%oe0(fovZS^rgbtyJs0G9|IEp4nGb;9+U^fWZDTOluzkJc(!@BJ$gAurG1y5#NA- zSp*NH3mTI^468*pCe`@V)T>ql)+P1x0%i<+d_8&Q&^Q5290+?(bBBAatW3t=`~n-8 zl#~>K94u4lKl|2)eff__1?q{KnyLppsZj(c*-}R9DtodA>xo_yw{;+KU9k}k3bsH zUm)5bEd?eb1sVV(wOKD;_7W=gZ9LPY7x$I-(NY1~m)<69LdW0)brU+w%d4o&{Y-s{N5&(3SEP z1QMb3L2Ia#EIF5odyMoUyCSCtvVj$l4J*{@1?w6%7k%#q;DrNA#2ADI1dF!kg^`N` z>iD^AsyrQumCk)fLUfgBs)#udNto0{u&atET_(%yeM`)nNzX$}6C9b`V`lhp zsR$ub<(p5RK5dEO^CO{`dYJuS16*pPR0R=WtE!%eDZTbC5SJ@WSpfxo`laAT#6M7b zU1LMTJCGb*z@0oveYLymruBI|dF{&S7Qtjyd0|<^euA1#1K$JvL`2kIHn~cX6LT_# z^bmHBg#x6-{utO1fAgS{DpGgn3_n(EEt+w=kD0*xWJGikLZ-)~_A&Ma*4teKNm~}f znQhwzrB~`9rk(~Mny8Em;xAygvGMVx)m3&?VM`zqDk^8esWQ67p|2R{48j5#Ep1?r zQEh$dv{e4!W|x<1Su-3mfZ zVbyvxeDPESKw24VL_BJmH#avsz#6j(pV2ooTmkEc=gGGV?C;q06~T{aZ*OPszXOwT zAyXNkIo!@c90(R7KEuY@51<|B;)M&>JcC1gQWvPtggIdwrfI8(z5Ya1Vu(+VssNoA zBv~Bnvld~R>3`SAd;K0vN(@&?oC!qP$Y~}cgB(BfYnHU(+b@0u9Z(tvP8jQrzr@{p9h9C+n$|Jh_YWebW(I~rx>+*aKSx9y zD0Oh7WhMAXOtO<5ev;m#gTs}BA-|1BcgGlCtnA$wmsU0uMGr}m`M$Ez?*;xAwvh}6 z`q-E$jEKbcJK$Rwf;>EgbOc{Pu6FU&86TKuZwE4X6o$-8MTgXASi&=y{N4fj@bkF@zpIEg^gvl*_ck zMJ9*O=xee!o)P?eZS*!{OZriggBco@@(d2YciZaVatn!-jm?F!tDQL_A_q@(a0C6S z&rOHlMVnFTFGi&sz6IYrZXG&(*dM+G3Pq`0VeZGce+&|sR=6eqD`{oxV+WVdOn}S3 zNE3R2Ce^zahNQ1K*YMw-%e}7A%>Li%;lKq0;Cj{Ajgdk$G_Mc7=7GbMIliEK@mnv> zwfBFag0}-6JlEyH>6odcwgUi7Hw-(0+$wA)Ef--#SS3K%UNN3Z&twl{`WdWKh-!K& z*zfSFIS&DKW7N|Piy`H27V!2KKwnwToc!yD#-&y^68wA1e#y7;H!vI24|wFrk#8mT z=AfD=rLVgJ!bTo>*`LlP>W63k#lXVYQsq-f|8j96ksvz806y#j&;rQnE9fY`t|QQw zQ3SU0IYEnuXI_7q{y=?@L%r>n957JrIW1>C7oaW~L@^;N1Gy~)m&?#Ku+=~p02z{N zKuIV)aZ7`5IqK$NbN2g+Y=Icmr1{-_!VQdZ;{ zR+ZDvuYoOsIQ50<8 zNw%Kba_vit(&!;2AS;KTP*pw5@sMk73zbYir9PYsC=bb1-BdTw2WyOByDR=nYQ*T` zY~OyRhld2cZk=CTe1bkBVI%;*Z&FL2vbbjTGUw1yNrJ0xZboEpsbT#~x9CC6W*nwd zZ4lzf334e{Vo3j$#LI9QHnwm0cMl6jDwKf7qeZc+q+S2gY|xK8@HLpdB%#CmBtwM~ z(s*lpfJnT(4bgWV6;Uw#s}^i<(H5b4nZsNhhd%FB!Xy8$w7^W3Mpy>~AErBz+vxgy zul_y5Ep)vMyNQ2O5CUWP*&?Vv+1J>R?|4`|^H6O+JG=0_)&xg6<3QFNJGgG69^GKx zv5bG!(HB0JdN_WRCY!y~{>4ofR5&33BJU4N0u3rKUjNc)Jv@cgsEYWZ>OmI=v)lZy zJWTz4(=aXW@YIn4)Qia&ic|*FEDEoKYe7k7LAn&w?Q<|C9Bkj75G7>%tpRc9X8-MS zZHi?R{!}J*uU_3cfJBPI=q7FcWFM~otx2g67gptGd9S;jy~f^%Tnz~kNlzudQ)YaW z5)3SVPdzOi!;|m1rv3cbKg4hZe)h<{{^D?uaS4@alokdtrw=3bB~GeQWu#@N`r+E5 zw~rBA`Oids5`F)pkVJ9R&4Z2O@CB+0o#`?(vN;}JL}TI zcy01<+TOwCxgzB!|8D4(wq)12vKqvt?4oFg{poky6akhtM$Pz=rXDQ z0kHdbU_wX??jP=Thz#XBPY$=r6pV-wa3Da2iN4uG)F3_gzA`P!;;1~9422L4)d3Ka zo=b$^EoMg?Us}h$aPiI|+D(58H)psaFcb3b5KG*bg}afO-9H3L3U@KeuM2UQ4p%=- z5uTpJ@cFTSV^@ctgR-uPW07|C{DrGYEX)?^Qt(X2e;;l*RBm+UqF^Qo1-p?B0pk+mXvAnWA;?DcGCAqT7i{PWfL>vj_2f&FU zmoEue$O=#PTf&Y~<_^S{M`90BrpXxP-T`9FHer z(9NYUox{R(lFZG!WHFX6R;&w58<_y(xlNvwO(*>K5Y4gcAO)$X1+G59C~JevZ_=0L z33^HxhgK877j$|LW|P@wHiTIzLc}p=#!*p`G&?){B&}Es$Pz46wjD@{12YKVOf^W6 zHRGms`1_k(g=$-bLh;^UAJe>dNXvmIf%dpP?z!zV`4j_UYbT`$#fe>TSS&-vKL1%j z;s-5rW>cYkOwW_#(T+-H9v)J^+8fAW*#+O)fTw~E7d$3e%1kVz35_CL!jD~Zsm#imu5nK(8>6N~@HJp_QqpNug z(fun~W+=gk;Lxn;W0t=a~upJt}N4^&qsL1Yxw`JvRL)w)q zB6^x6?T+FJ6@0`pf_@}vdUo0NYSkmBnNVP`5(G;M=%NNG@4!HTvzG`jCX4lg>*5_4 zI0fBRu3DsC*lk znFnw^=`-j|fP_&tm=Dnc<|zPZu~1{o!7*28K0xPv;G9M{vjtAXm8Yc0{#nk0mN9aN zJ?H>mfg*~)q1f3Sd@-Vf^>=+g1r_z+a97oXrVQWWio0!BsO-=s4z>f zkrcH%V}X&-47#$f^T)#LpC(U=Z-};h6E|P~b5|mX-_jt4Zs1%XLas??nN=~}(2N5a z3XBHU2N03a+;Id0%?Xgp3T-_UADkcHz>({hNLqLvLKa68;N5+c=+-b*>aVpr-RZ_$ zT29DS)gi1FPH-9rwGUE&Z-I{a#R}UWeTX`_NX61bUgxY&iTVu8W?RDYzl}W7U*va0 z%ASiR6r=>`BnF-2?2#n^$Ag-4A63v zv8Q%Y-ki(&&X-Y545D_}2;CB1u?UWv4e|>z z-!Q9dEO5i0&Xau>OCU2?fn74>*>AGEh=Km@rg%%7#Oo4O*QLAY;LMt$FoYP6w~x<7 z=sAHA;eLajJ$5&Z{v5^87B}4zZD*&oHP6^@42GP3`E}gOG3Nq_6eNtYcC2F#utU;! zW+<^>dx3}mC#pJLR8?=*EV8 zn*@t+nDXf1{}=d?09y{a<#Mg31!&sdPy%4_Zo!ehN+!{}q<=Zo~CGpcU!hKpV6+ETKP; zvMqnMP@q__4^W8ljT$-fkpJeFd&L6f$sHUH!*z*NS7U#c8w+c^5hgDeNv@PhQeoy8 z4+%P!KbuYq>0J5@t38I{{%ri`hLvX1QymP>w743Qk8_0`W_ru!i!#{p15CN{+l#6k zMCMYg{iIj#c2lKRT2$(pq^2>yfpXviaNh4dsDK>)bY=UBwbu>eZFCNOlN|`-m~;dElf@SB?rgr_sP$HKr-%E60lYiI`aH z+ng)rGB@&KSE4EHyu4NF@}azS(?mAD34LrbrBi>rTMd+Mqfj2(o)YMd@N*Ttcrk%a zHz-%e=lLJrhdej+W~wr$+AQgQA4~beD@WD&RzrLvIM7YJlKQ6lsk6T{_Kbz61o&nj zh5X)7e|=K9>N?PsG{U#z{RPLK#jhiK4pK`ZZlCD z`iVLJU}M#T>zMiM)wP}c)hA@sH)IWnXfuX&vWY6d#R$h3Q+n;@XS> z!}T2^-I7Pddvve-?dEK0~8LEa-2dViA(v9%`v*C>o^xHSeVoH$|#4VxVw^%CxJOP3w+d zFeAVcJIlLIsb|yYyxm)-H`&+hHdNhKcS>}5P4e87a$1};dyq?uL(7Qo;NNZJ2ZDf| zop4N_nF)EcWfNhHya{dzp$BV;03AzBe4-D9OUbBof2J!#0k=e=i>H#7AtuQ`So-su zw*yq~KU6Yb?sPclu7W^dG7on+m80}^EL@dQHKe$;lIfIHr`Gj59+_SmN3Y;M{Lbl| z)lZ!aso|bYU8B%Zzo<L${M~uWKQ{9*#EXSOvFBptg=t+&N0Hp zN9Hap1O-%_yS8M+*QbwjZC~4!cifI;Z=|-97QFkC7(6e;-?kUURlLCEWKoDOTMjwldL_ga~15s zN_#*qGFOeNJ0;)dC|@r?-Y1&i&Wq#9ZX))!##bwuEsfd8EjXChLh-g$P!v1snVh$; z=f=KUHZ^huoPnzP6+|InRgAJ6L$XRz?4MIA|+b==KYc=V&uu9F=3R5hrdHyEo0VY`kpTEBM@mQd1s+#?~ z7n{fOO$775_Hl5GCn<^sMYY~fQI)tQ$|Y;xbFiz9K}CG}c^R^0dA1 zB`BM^Ag}T^VHIxCC*zw~+BzyXQZAeM-E$&471rw}B0ePs!PITSeCde%o6PGk4j@ZE zjD%NJ*E|0q$0Tj&M@@6TkZvCZ zH%I!;l#!&iCI-d?vq*h#@4B?pur1m;FH}7>p-r4vn5hVO6Q|F*Mb+l71iR?n!`oJ% zQ+8|WHwq>jk!ZsA&@<;Q>&3*dH;(5&8`AzYxyMfD^ZC5Al@yV<*;SQ|-QUL@37IMF z#J6qfx-Z;Fs$=b;VmjDJbI{?ap`SX1cL^@nWBTX|ew(}(@Aio@6aMJJl++;GEt}S_ zRSV+9!w#Riu4HPc1oc`Tl?TbA`$2M}ARh9Gf_{KNT5z?fE8^zq2lWw3%Iat1OHcNw zHLYe$4&JXfYBa<|U>b!+*luIvrt33C}Y1NZ*=%XGu+`#ULPIm56DTNGLG z$x5k^$q3Q(O>*|Iesn6LNafwWnET7ijNO2&_m4l`a_9_oW9-Q3E)o}9-wLU{zuV4H zHuoi&M_$I#udMT0LLd$qftWmenZEI|C$6`V#@af* zvGRlR4xN~W^W{u#2^q-1F|n(lVW**o2oC;kg}4Q{Y69ufuy0AP&IoCR4={|C*lt@; zZ4dOR{qPUYRaQU&9@lAb2oqHxz+bcQR5YfAcy_(}e(%aLf_K;JXyo$cbcZe*UQ;GD zG!#XG=g8u&nIzG^<&6R^xCgg)YSB~MUHNJ7k>bsdaPjXu|H;C`5R;tqPOcE+W zx35L)jl>~;zj~#f*`C87{a_~-!LEo7agcs3kl);Ouf1`M;GU`f9BI=kj|KRwGN?FeCK+B_XU^ z-*GLxw`LWHAC869$tEPy;uz3BFg-!dgP(NMlD&3IAhCT!54O*L$aw zi5u*P-)A`LQDcp=Z*wQvp2mv*%&z~v5v1#|2|B)8k-YLn$xdp_Z({EWAwspp1>wu^ z`SFy{Q<@-d)W5(MZO=s?L*2F8Nsj&^K z`!bTC3#^3jjqC9oxWU~HXb{5ZVXC{|irBl6y>`OF=yLO>7_wo-XE5s)#i7J=QvY8_ z@__+iJ_aB`ev?<8=+R*H(=_7^vYR8Iabc0d1m(^&V>u5e-^Bd%BLZfJt#^B(ynwLu@FTaF{^D<@%mtfRoNZ9 z^#hP-CO6+UwPV*Iadg|7=aOIYfb0{}QMMi>DBshZkjUJ3O75~9uqIS}FUc|GpFe-k zw9>?Kp;3#yaX-kC99fAQe|Z(x*ezG5xueg2`BG{N910a~Br; z1+!RzawaUs*N!^#=hSPZVN-2h=Je_}9>(UDul~@M`u=-GoH)poHAUvd!TL|CRUfZR zKPa`RWMb!v3UgvU`1=PphJ@QfXTcfX3g(K0x%WON*TyBR7{$%SE!S|N4M~wVM0h+T zQ#tbk-#B9JLSRc>xV$3B=uEWn>c*4mrlJOMT&7+q54cR?w7jZz0_wr;#Xm9q#5Va1 z;)uYgfBZ$oW;P;4&;XiFQlG90_pt`(85U6PZx&rYEF+`AP95u5A;U<9l8&lQ|h z9lJW~jTW^i38b$RQxH7ym0q1_5yYzxnR6}2ma@Ndw+I>`x}{+zu04?|uT0A+RDWyE zPbsL!aL!mti1%LY6G{q+{VOO}hz=*vIh)`At9rffJ{0b$vw4x|k!IloBy^ zBM~sHQUE}lr^Zgiuq1H5P|`ckrRGoTo8QX2*0XT(?1*BStH}Z*mdnOAwjz)93EDRm zmx^Fgl@%K6U*Ga`&%UGE*2LHTJ88QPQuo*;m|o9sf9UI^^dZJ^FXV(~m+j$>XG4^1 zzW#OU=E{c)q@6jN7OQGJvKehoQBw?x?33{$%5gc5kOvb)Dd!oSs-H|65<2iXgNIlC zjX-;2kz1GA*>ZN@T9dK1i|p7A&b8W|Ilc{7;W5BDQDhh5mDi62tZ;zCjzUyFN(mOm zvN$4n{jT1m_H6u0WYZfki{QWkdCkf3{h_#{6p4S$_+$<>0|O{w0$x@id8oOxi=t zX;`5Hf3jNyjyJTNt{}v^rF^N)+{!9!+B3+MrJm|#b20z>M-CU38Y8`gXAuTm{R!F| z^2w5pLSN6Ll=K!sFaCy^koy2^pnoi)$km(VLhF`3aiq{@j{Nm|7;+pzOv|3{>-!Sv zaRWaE4|?v5Xz=7|46Z)Xi}~OS0eytMP2k7d0!r=qF3p}Yl8%Hus@pA?X4_W;aTR8~ zx*AY=(&JAU{_Vap;=q%S3$deAnvZ$L(kO_nDMB{i|K!uCvOISA**(67hO1@SF2w!( z&clA-AR3*zs5qx=^Vf(@LK7`hr0?{!oCHIw$k+QP_lARsmx8rvW*y2s8**1ic5E3I zyo%MEVH-3xHW4`7m=0f{YO7?XCo$=trw9iG7!E~G24uH4r~4YJahXf5i4znM@-!`L z>*PmM8Gdie zgzu(yZj3JI*0mvRC_Q=S^~I(ROERq7OPs$H5B3cgtWR3~ojwi+&%{xE4e#$7M>e-D zny=AUUs;*b>YEKH1u9aF3Qa5`!>Y3)2WST6I|bi)kFo&=(r4-pP7ITFx+9D)j&5Wz ziG{}V(>{MEjR0o=%a42Qi1Prw0W@=lloZo^2iLzyK69`1d0f_-uIZg&Qj|ETNP2?!0>S;}Jv| zYk%%0Fc5X>X1U_=|G4_gsHnd8e;fuRB^Bug0qO2ik(7|`?jE`Z1_TKy=>`=6 z0qO1%kS^&Ox?8&boA>8?uk~B^BV8^W&e{9Sb*}4Gdqew<^>Nax`86+u(B{jTxe`sFAGvW0I#Ef{rWi`-fLi(1X+uNIx&6#qbCuBPy@v6 z8-S;Q(6efKHP`kp_6cwVfI=KZL1>nbl;7v-=C^n*hoZEC>X^Rz2@%m3Ph$LTQHn9#t8WT9`SMjM45qD9^hc)hF(IV$%RzA=#pU#?#8aS zegmxHl=gcc-kQmHz@2P=&XjqSeqMT=tmx?IJZ5zQB~#sb>YybE zOz7L0$lZMb5(cC_Jow#r3GcG~{-68=1Q5XxpP6Y8INAt!zeP?$&$PVp9rY#m!lpPj%4PQ)2PmX;b`muRQHK9t0m<@J5!9?&vi<@&|9o?XT)JdXNLaohtvyyGEcTC~yX`Xaz84G(PQn)a7x3DvMF^s!z zuLy**yOP?a0+<+sK1o1>2A{)|oIiUO$~}0>O^n~st^dDTvBIB^5si=57gnQ|jDUde z53X4tX%Rd?9%9P!@-BlBPqDF!3%_M)fHelOnwCJ{e0hEC<0I%eDnye>WpwpC;3qY{ zgLKr%QJ5{^X~Tsvnl|ahOCd3==MO(56F${ki@zsXd#LSsI9x5m?I5c*QI|TT3w_cv z*~qnS&S`3l3ox`S#0af|@W<;L1=j~ObJ3Ng#k?TKLP}cNv|KwZB7&t%0;Ia6q^$Hu z8+t9HJR;u}fPVtAZ@0 z30aU6H@{8#4Yeh*^vljAhx+-I|LA&RjAIASy7@zjC?|6?D3835%%`h(-TJ;T3viws zo{J(DLNPMwk|4BjwAuFpDT*Q^iW1O{zLOV<+2WbNf)NMkx)EUIC?qaS7=^bqBccxr z{_d8<$f8hCjGrU!82w7ti-;ZR$LJZ*x!nFnu6m;c3}ch?Lizuzgke36JBmR5_!t}j z2=;6cTm+0Qo*=BDFBk(K;n6*Y$s6PKNP7WW{NuOG8kjD6VyHF&T?ia;UORNM&rH)i z5Warfeo>iZe|}_b`(?m9YzZ+S$6reoX=k+!dE1IwV|PPVsNU{akFkibodDFJo>kWj zV8f7vLPcZ5&WXVX<^!z&t9Du21m_B{)1?f0A1?r!6IfgbffLgr@buBH3v3Y8%%SXE z7@vP{5PhU)NnH@BEnByi5#~id{r9u5HHQoVEx79~L~PGe0^JD-w;>V4(*mx zq8U$x0Ptd;LKG|v2uZSfdMK@hY5x!=WS*~w>3_t+=_^QFAHE4I)Ylu|%^BFB3(vxpPbT^RsF2)E{J+-^nw?~Onz z8yK&i)gav+uI5WJQ7)dnI2roKSfYkpab;{uv*OHpn}{6$q(Tu47ZSg#=bnxBP0Na- zl7v$dr>NT)5~qm>=3a6Y}UyD~oWj{%;~D;b&Q@dBMaSxyj58p-;C7`&_dIu?rm&=|qpNcZ?J zGPOVv4*~%>>s+b&rx}9PJ=G$tBgsPeKF;nj($f@2)1G=M=XaX!^DNPwDqnL9O?~*y z77aUh=U7=6J!qY>)NVb7qf`p%wYqzY1JxW|(aFDL!COv01M&G6aJTwkOdj{e+&e$z zI-MuT^fLZ&{N%xx<>I&$cPch1H`-T9xDt14IG_txuNi0lbjD~;A`!K16Gj>M>OY7@ zjzpuIoH2p}d5ztx_`d;~=J8@(EHji2nf}Fr{NI%?NliWmTDQ;v))~T{38xYUb~%cR zr_TH#VcUN&-(QqNWkm1AyN#9z8kJpU({B7UyXE?Rs%{9rX>k!_`^W+yn4rfC1r7SA zCyeY9Y?Fi*~@YO*}`y^NgCVQ34FCL7{JF6s=Rq@P5T5i%b}sd2lZ?G zAt}`&J1(|rAz6H9QX>MpcP7b#)c;y675K}< zegMb12|BTN>F`FEot#nJZO_eb)p?F*R72~0T1WXx_$$}pf;G*Nc+tM*UWc2 zo}QA@@@)Ms-N)I&GiP-%XUSo?i3qm*>66H`zi5Fbs)|rgt#O|mWAC%DVkJyV!*PO$ z8RXYraj~4N60{xqdoy#sC#|W2u3_NN_i(c6$_CW0$82QJvBldxeZNg(ruh9i z(6}EEk9~BH!CGCnYvBCl$LmkX)2RG|)2x?0q~#wAoz-n$k;I|tL+@YtdxWghiH6RX zhj&i`d>n2@g@u2NaQUT8#aUE?Z2i8hC$P7FOfBX8R6lg)cJvZ zZ#p1Cc!IH}q}oN|J;99Et3akD`xU*)a#YPz_Mp$ALjY6su9b#X?}e4G{-Z3jAhX*J zd(oNb{Imqj_y1kO;P=RQ^{5e4PDn+0^P2M?X5XY&ylu(-jeIN3$6{Bf%O(n~-|-)r zM6UE{=*#d;LVGLtKMVbnS@}hs^5j98=W@NjvM_hDWQX8JR3)7m@k(T;G-g&oj#gs# zpAVu0r43Zc5sinLs^Dd^DoBMdS094_-`S#q<=^?2iM%VpIZ3K}#hr1J?UD_Y&;1i( zX7vqLtof?kk0oEiUbLI)MydSx0}>f7eO+`E&RM>|IgJ?Cftzh>IZ?Uc;KMMWa3e5PC`wPMNy(FyD&q-(gRN8rmu?y2=P{tb!Wxt_fY1r&s=v|(+ zk-SBMdNt_@|3W79K#MP!zA%_+e%9FPBx`lP61Mc_SSCWgkB*1EO7V*v8?740oBV&TC{;n)_oNoJGs)@e zX7NZBEZ2a2VCVf*xBJ#?ol@YPM`KV<__jBq2K1?~a$bdicp@Ff_OE%r&xwu7$6KE1 zMXX`ht`9bOLvu)New}j=$2p%eNb|92=K+0-1bF<)rg0$1+|iCjRnGF*Cbi4i@z(ZQ z(%m4Ge?utuH_7RLl4DsuU}`Beyi*!+Apez)jY%0i=Z{#KD<2BNL#@?&Dr&Wq5|Vc%}Put;;)y2AS7iVCBwq~VB=}V-$%DVp~PW22}gCOcT50`n0yHt z=C`&z`eNiIZCJRZ?n$S?ldJW68d1&)>`h**E=$icmkXx*(?JFwvC4$0NsbgY;3hnHC1=!8mvx#M3ubMf#twp9pLu)c#k z>;;Q3u;i9OB|yQ(jnDU863Zm8WtsxV#U97r15Lt?nNpko-T~H+!WHH``gb5isatm0Z~Ca;O#T`!k9TKF$^0^^xC_8V}9{a z_TvEw5Wh8Aqi4Lc8;i3X$-7Y01YdpCAo@+qjJKxDhok@+(fCg^atG+O;quFlFstQN z7I=)#h@a@Ynv;J&<#T^h+fHP~1Mdl|CBC>NK4B$E1POFt1A24Pazf?m-)Mc!8}p|z zpfgshaO!9ebBU0?&IE1xPK-^kPXI=-eBRDBf7zRx2SiPUyhHVBj}qobE=x|dXySu4 zACd=K@F(2P>0vRk@7(=V@9Gs-Ok~AOs$8SDwQDXm*r9V{&|tJFiVdTnG&0w`cPFkx zpw51bjQ@{!K?IHrQK#SI(g9_5G<&)$+oN7+R;h-~=N3kSyaEtg3*n9f{9b#}jIE7! zImHk3B)}Q>|69rkdz5A;ff^zuM7lBVK!nhLr%xFOP8$oO4dj@ja5ij1^RCqrZ83uIYU zCl~}x(*NCSlccd=#>3C@=DnHOg-`vCK{@qyoQdUJ!S5aG4Lx@;fHYF4VLvz>m67jl z2aUpzkdjGxqG#r9V0@>F_tc}n8Biy`echVdt%JX$qW3p7@_FY9*JD zuMZseeuja-JQe@({vIpf67J#Mu4nP(F-Wem+U@+FS z?`WB<_ka00&={r;Fsftm&b&Znggqm~xeae0-mc2^wq$(x5$WpH;(FQr-RI0oT8gs_ z+Niehzxeu7T*v`n2fI}$kW>ov$s`clMmOHNuv*x=8&PV4ev`7w&Sdd?xjKt1H0&=r zxcZx5fsp$P;<*UQKzj~0E>}T#sIT!R65YtIOLIAFneNMnp(T4utG468ZVxFW#s@rf z2jsS}ly^wb!9C&FjwRjk0+0UQ;6Woq<3l&a34P#x{T=VYHZ&)Go4?sjL(2!4$z!Fv z!@w`7Um$q?8CV{T`7-L$!^#~-RDr!%T0Ncx+f4+Sye~I@j8Y%3^r5=as<^!8FY_uYC zZie_fEvS7!0mA4xQY(dw-GNkeh+<3!y)^4N`y4eXj2Q;$joIf9D0 zQ-75aA7tJgn@6(t9W$U%yjolEO-7z{pWog@oyCbRPfK6gvrbohy`zV;yGkXG>pfGcn&oBlI#C(Wne;c>S$~@z{NfE`?~% zW;@{XE-l%V!E3AZMyp#!-DX~^P2MyFCdKI&lDh>4yfIJn8o}0OuGF+0x3=$LZtAO4 zPibn29S0i#0G(|Jg-XIYq0urGRM7$iFm8yYC_viXw!ErU9RFQKmBB0~^hM|?#T&>~ zm0!Eb)NPm@VZXZa1CQ@@CJh~;|7~mB`}62Jle;`vpH>MP#KP06-jGdue0zjc`-Xjb z0xJl+dseZEGFD*oXJK6f@c70tuVH2AVhd1`c|1}00zpva9aekS2Z#@KDoY;yYvC$N z3?Y)EZ9a&bYi&PH0_Lp$gI&Yd_K9?oFJ&((CoYhdJC2Hauly^0(OZBKqAr4ED^9(5u zFvuC&rx-b5)Lxk=D$ZTclIiKw2-Xy5B;ut~CJ6^|C7+roKSs3~PwwhzwG;&~ip!|W zBB;>ZyV(+V7YC)`6K?IcI5)(1BDM~5*N|NV1r-_3jN`pP5o7T3u+M_qKXo2T?ADJd zw5%cC-TINq4X87K0&QeGne%zqei!8f3SY-FK$!f1f)U~D1s>`Y4Er!DSgkP%`zPRh56#u{%md+~x8-&(6`x}fP<~v;! zTa$IszC8xdU~87?4bh+4Ac7YrIqD8~Xh-Xckk#6eAK8rHR%)PT189-9m}iY%j^qGi z)mT5$T_r*dbbtEL!BWU}i6W`_IrdY`0X&uKvuw4-AOm~Yt)$nls1U5<}z+g?PukKBDIZB{AyH!iU;r!EbIb31#VUrn*Ffw>7x zSO5bxlTG*0-@IUnxVGPjRdK*LzgRx(4A;NEX1+f>jmnTc|5*J^X+JO%GjiYXftym1 zq3#GaV)qJ z-W~GSz%FY?Er4usHPkyBfsSt75qR(zJrf>4Ofjnu>*19$t_sI4I*0y5suRO`j%yAl zpx(WF?)llhuC)9YNQ}z4l4Yc6?JuXN4_tkhr!p0#zR!}tHmD38p$`jd)fSD9K#7IO z%GK?#q@##ay-=m%VCaiI)(s5iiTJ`VUdSu_Px300wHuKbfkGp;0)!hB2&Lf!6fK4h zmjtzLk{U@lqrT#zaBUTSAj zbwH>v?(Dwz!areO$eP;Mj!Y=o}WEl?xy?Dk%4*(cT8=mLv z=@to$fumBzUEU)Plyxfxb*|V7LP)i2L7>eutbMz>s6oVwc!|1}w3oVkIBdMm(tY3e zYCNcE$cNFBB=bjKUsAllVbSouG-QX$vg)6~F%p7hWq6Tq_sOZBWS#eG9?--@)OK_I zgS8&5e5d$fmAKkqVN$!!_i4+|_xRMigR}$Ni0sYZSc#}TGZet(fUT^s_duFJQFcWw7i#R)yxcp8jyeX=FBuLBu=eO((#4P@;D*`BWV z5&c*Gt12$`iM$UsJ<8Hw@wD^ZPQAa+wz+2qDStiI+wt}!TMt_=Gu09WOJKs4p5o)| zOW8c~sy3t9h3e+LHeJz}V5K4jJ7Ozy-z7m0$bFO}VJu)3O6^ufMktQJ$e=c=Uu=-4 zhzom^PW-TZ>a=%<>5z59`EJe5_=64!Vo%3xU7?>@=kt%uwfj56ibz z4R~4mRP9?!`M}!h&p69D>ApO>*9W|X_#?3JKgQSQt{zApteNp%@y(H3it8fy&a&ez@aZepRnyW7>VwH7DEeQP?6CKCpM58R*I+=CC-e3#DTTzHqv)NS-M=kNuJ~ zc&pfx+PW=>;9&Nac%I=iP4Vt%vmC`OwC}hv!wg1tTB<;})`MpIFW~1 zkn~!K^=wW8(8~bm{UGos#y7OaV;}bKyT>j6>PxVXYQRjZ=HJC4Gmg|I4j*1m!%26A&LXc{kdL`Jm6c(-I1bt8Z=2m&_D)S_a{l9X)0ih z8pvYQ%XvSzma+8L*1GpX>wd_mflBHJ7ML2mR9D51N(tap`t=XqGKs*{B;WK*0U_go z`0|nnD#kgVqI`aDt^FWgMX9m|O+zrkyufnk`f;jTaSTCf-3zn28uGdq&uIHU$T+=q zkN(f_+lQoBEJyqxWDm9`S&ElYhdp15s2s!|yKT54f-?fRE#*~LPCSl)Xg zLJa*xiuJ1DvZf57O8L&03Z#r`6|z7^d>Z?bpGuDTcN00nQC$jWw-D%CD@V8Rp2#8Qo$Kt1Ys57tu$N9`=_QI1feHHZuBJLyF$KBLPyd zES`qHd|OW`*g39KET2U2m1;I4ogQ$@8xN_{+Hj?V_5x>tbZU92Q`Z#;n+O_Lt}J9k zTlXS2)olrZ-K*T%jvRq)7lo(J{e|T0yU`*YgImAPe_Ve2?#$ze+!xOsenG$uU;6Ug z3fW|7-Z3GmTCjAwwyDmG5qRsXN~!u%vdTXhwt8B#v@Ae^DV%$uHRpI!7dEQ*$BCL_ zT+@vM(+5z+Z^_B~g6*A4j;QbwmnL-19)wi)JW?_F(wWkPKf3Sxx)Vep+Bu^}49_`&)kPqBA8OxlQsuJq1dEH#LZ= zm&7H(T4NPHCCUt~IRuX=Qo(GSkM+;S7{w7TsGk;M2l?H>20I7gl`xz{{lm!5)4cz2@UBekk6u9ZM@ zw;v64mD{1sUmgL7E@q}!)9b1*buy3?qDuDH!EpewPd?;F4n0-tKa8?XVhfHzR07zq z7zzF38kOq`U#?$%`2(Fi>56XlFS-pjYghV3u8*g3I=%NB9Q7A+o`HEHL#}_LIq`;= zYgLQg*N@(Hit;5N8{45SK`;M0cE>9*d-30Ys_wjuVl&S{uc8cXB?x`OzN4OPI5=cj z;$d*uUG2_J4}+4s|)ZapIG@1z62*{VA zoyY)c#93PI+Fd>8H&LA?$l?eF-EZA)#@3`nb&Cu z<*zgsN?e1Hqz$l+Cv*rr&(U~HH*6R09H{cu79fLPh;xdCh-->? zpgt#gHMAG!2$njCx$NO&-IqU~i+8#m@Ur)%K@LXz0>JvDiwARHLjpKZidYLH4I%*t z(Jvy>Huq-ICkf*5Nv(j_)k!5>@S}2ndJS#F} zy3&p{1weTLoBX(r(+w_U3)jqK+LelZ?rPAoZq427*{m7aa`FR^|68eWybPE_t2N%9 zKy>3iq?=poncDca7x{jr*^fEjuIdp$e?kU`pPpgUjbbvN z5#a_%W$5RhRD^#tfP|a#baR2e^-ZqNiX)DUp;=hPfRl?VTwP?(z>#$l=L-}oy5wRD z^1}xN&;auvfHH~huCFhml3FHZw>&+sO2?N~a|UqHpm!V~IP0PQa~uS(#?Q(Aq9wEJ zwUOi2IKcEs+i*Rx;oU8YU`>~gQr+@6rrRw_i%l=WT?W`lkDNGfK!g&`{ZQp;ZEUPV zzGr2F{&e}?n{~0x+V4QHX~3v@`LdQSdrmO@ty|MmR`I5rIq}Cw7-86GBD{r-cHXyH zAFwKcF*CoN8kH*!USlXy{i;{w1uuif-%g>wC8djQ@}BhH`%k^CgEe^SuNZi6FkM3D zM290KZ9$$7Fd>@TwVB_-)2?Hv40+;Byd7;8zJ$szja}GF-xGDDzg~HBx!wLbb2odk z$)RfAk)Qax$P2ISj1Uur#x?RuanXd$(!F;SMI3rD^vtP*=HFnEHhj*IjRoPx@zAz=yh9w$;$M zsO*l7QWk$DPGRd}*b*2RduBKe?UoBE%USC@@t){P12yxe1R&MVVLRV?jxv&PdrST>sDN#Y-+0TH)6X5s0x@lN+o_h#_MW2?8%>VXlI9H*|_ z3ICq&r+4pR=~qAx0y6#5!b+43hd$%(wN=4l`_l6I&`~e3_ARmfB{EJa&qvSLil4Hn zlmSK`7CDTfU+t>XWllc@0GM~9WIm~ZjPjw7@A@ZMjK_CAL&+z|>0N#-bRIneAw(R9 zP=IZ0whkBTR>JHi6xO&Y&_E`^C;za+%QKn6{Km~1folG5M5s)4=ai}Ga*`msmp4k0 zM{-4_US{5&11D(!>;~5VfXyN~RYH5YW~Y3=e26yf*MZ&s)-lx(8o^R`79`QzSIz^p z5HT?aA4&$ab@-yoTy(VPiq3Y1yO4vh8`dnvC?J*+d-@10Mj=jz0iHuaR%Gq(Dd3&` z#_cb(!2##LCL5Ght0LbC*3C{k^8LEqbWYs0$x@42V;#2>ZnOR{-jVWThxvk#iSF?c z4KJ!RY(ah2pZ#f%*ZME!d^KgaUa8&AdDGQcwS7i-B3ZsptU`JH#a zZa{g;B?fao3T7p=PkTPVTO}MAS@JKBU*=ixTuon1lQW=#Lj9w7oeEZhSWHVY%T5ZK z5H$h^Wq(sLa-GmlbCZq+2C$>!^!yoGCEK67^snB;k7sVy{I>r{Kc`f7^+#u;>MFD? z(+=KZz+_@L@~1X23}z--K9Vo-e@8w`&E`_RHuTvi?hB zPbAf6@?t={AwJ6H8S5#T{odvJRYgoAI=R&xlns{ z-ZRZbim4n0iii1cI_7vpo{k7@11l9u4EV@XL6%RxO%+3yF*)zi>YNxw%Wxfa(Q}MK z#690eoYMSFk&xQKxb$Ve<G4|LiL~*u`FNz_$E}mpNWI^s^^Tpor{PZYv{w9dCKnJwFPx|6NCEGHO=DRXJF5e zRlP^ zQ;!y9{E%IEFEVEB@A7?Z)fr{uV!QdEg`UnoR`8HglM})e7h>s6cHR1GzMLv`TY*Ng zrQ5ux3EP2Or99MFE@L!~@4I>!7R{EPn%!Gv=6w+GY_al~v&JU)_TUrkrAgy69E-8N2iF9?DB>t$P0KKZjyb&cTr*&Mf^bHXlGv?@f0%TwWJLkz};LyVlNKSVRq3N5ya{H^K^m$JO z3@=T@rpW!D8rk2PA9nU`By;;hIRGxFw#=pR*I<+6V)S;fXPRWQ1l$Z3CeFy3)}gMfW^Q{y!dX%%=1Dg<{F_6vfAs zgVKX7nQ?R$8GN3)jpB*Iu$0cTFLx%qr$SgTn zXWN0P*vs$AvAel8gngXQwbzct+w$Hc$x-4BFg>^5i#L&8VY3bN{Hc)U`4^~sd6Xoc zSkva9Qyq?BVjfCNj&os=DX!g|O}3=hxwcgN>wMdR7x~gVO>c;8A_1WNLIstEgRZu< z<=PEh!zpU1Mqa;0tI*N*QVwI6<<4?J-Kue}d5N|Ki{a8)!e?z6xgxDIBhbG<;Uz&h zC!fB=Xj+`p-rQ`n&GDA<(1mkBP}J$aP7ivCHp}cE_V?)##kmg!+Kmlsm+oeRB#8AjpxXn98%4=; z)U*IETHKx~4^Z)4^r<^`zf{&1>bxAb-$YvN&$t;@Kb%`wI^)O&!2^bMg*-vJGRLEb zXmz_yNys-3tJ!~2qPt;rb1=>drQ}wP<=u0;XT4pSWSmZ`Dm&VK+Y`Uoo71I68odo> zyMs5X36#Y!vKKAvFH%!#DZ`VuN2nu#F;Az0EqW?xetS0#G7@yJV8Wn~MRFvr;!m5~07#jhUxQQ8gPB1^jY|^rFVg;mi8r*+XdzC_;ute=w zq9_4pw51#%$7c$nwKNwlf9QgPIAk4GsZ4(*j{hjlmvQlkWs4%*xN!XVY`D$cwOycX zJck<)AjQ(e4)a<~TS;oy+5^0WW^BUNNICk>Ju%YF_XJM9!xt;8!hBCR=lNBDR>{!F z@VZ{fO0|;sX6O*4DIme9cq&T{55SQdP&UhhW+-~-TqGJiF5b!Yn5AFG^Yyw$^+z@| z4-USX1xmq*u^}Iud=pCnuL6pJdc2JVl-6csy;i+W$V`%d|x@YFp=jnz?(-?`kFGEpaUdy^v??CeN_SDDq z;Vsr%D`(^IC7z2Mwu$#nL9}^Ke3};}!*1VG=dZ}6VJejGH61Gf7<#1LH9j{8krupa z=ucaUUGHI{7I+8%3n*>C%*3XED;DNbN#gujOG_Fe!am*2y`#QYQPP6K=uz> zf0%1LJbG1F8o0VNvzJGtN}c#zck9~)ZFBhduRp({Gt+*h^?)&7&VJa#{=mdct*8>q zK#_|ti;nk}F%a*$>|180#?yOeIco6NJ_axG;mYBmgMp!Wn&br`*F&+XxZZ^IP%jUY zSKB&5x!$DTX@x4J#iq6~LR2Z|G>f^2DX355b}BB6zL27cSQW0DoT}%Ihr&JuQWXs3 zzq!*$u1QCEVPK>>jOHJRNdQWB*|B2%t?tL7)@y&U^76fYdPmIXf*3Tvi?_}zd~giD zjx8pAYL(FRoY|j;XOZN>%C)<*whK1gbxEHO&isf(ss(sI?Zx2q(AAp4j)v<-a=x(Y z(p>IQW-Y~&62!XA-=}KvA0knsBsxrqZ_hN95~$OSEOK^*mmd5+);@^7(~Rz#?PAia zPaTtQOs5QpI=1y_evtQUhKXyCyuZ^eq~6xN>Fc&GV@M}?8N)~;o!Cn+`lJnF@NXj5*5;QDcyeV%hl*uZEWo7 zWolA|tuN0s%GPH{?xr2ElFR`@1xISGzL(PH7B`^AYNO1{{7GTMwDTI2+0(B&aRO~9 zaic(8+sHw%TZDx+#gMMdK~m@UfY(IVVlh+w0(+ zr_<)L^%gH!G3$Zo-BSwRciUz0=F}s@a{d;t!iDvp?bcvZ&zwrvXpNVM6TgCcc>^>& zDSxwUC3UC@`yVwQPiXn+`N@4By30VV6U)Gg*eJB=dnQ|A`@eQ7Wi3CW6qRnYqb%!NQr#pTl``(V~qo~p^Vx>Ch5_lC;yBf|Oh%hkk z@^N|TaBb5-<@UKth{Q$D(Nw!Ozf^bm{w2y=B}Nzc9({C%^77wLyh8?ka8p|brsT@r z0j?aazrA9CQK73|XHyV_?gbUb!we(+=hAL(8~7qLeJXg2@8&pjc-|c%#N)g9=I%vr z!g9Nq4)DwuyBEapl?xOyKb%bF>DLRyb`Tcc=}9UvWXyk0+9h;$F(=E}u|*#EN<)k`Ryfc@W3bbcy)%hxG;Sb8rQ!k@NMQGZTdVL(&2xbjo->|M+L0 zw69j|`uI<-%{z&#_=e4k%wA%5xb{%oak$gvQk!(u&*hl5!ogBoga%w zLkii?)m_VT3L_{c^!G|dH(~qh_7S6bw+E6TQjA=V_l5(6nZA10r>0BPF08_h%Jk1k zGk*tXUzD%);!KmW95;`ylEH`Nm{-YO-`#T>>&|%SxSwg*)N)8k4v3@gse1HOt}%X}8ataAPm z@*FGy`rgxtxgwDjz19H#!-eY>)m8WfOX{hx!Ye4mm439Kgptiw-NZ=!dH;E))Hr;< zF`e_f-(cLK{`l7my(2&6#Gg5xUPq1t0eLNdFFZ^(HdbHeS;eNB(XjNqP0|tDY;M_T zo?nj+c>*=Q#SvjkCt%vYq${Aa``7Tgok%?ml`^_Uz4`eE6dxh3gXo6KxfBEsf2;kn%@RM$S+Y7n?*4(iKYu z-E%!WC(=@(gr?^oVMP^8*>!BP@Rz}O^xteo_N7t;kk1D~hK2)OCsqz+rY6?nw~7AN zWl}mN`0EtE8|Tg1*NKtY-0PmShDV^KjhBWyZBtNx<>PH2!@0xReNa|R!TMXgF;I2$ zF`^~=m)k#gwGofO0bjcWXY8CvJ6Y$W&95>}H6k92qI21o2?{H!?5;F?n3YnSrn-bg z;}wGB=^aZl9A%~tLgKKmD4Dy7i(VPv=O|N~BO+{cc+Wgn)0f$}493R@;0J$tE(A8i zsV+Eov*W8U|9w?neO?ogL=+(vMWBC^msTXl^Lma^0|~E@)?9~`4bcG(ubA`97|*-V zKyA9dD`n_>#a55us^qAN;d;Qjd8{N;n%Y_*sBm7mem&w;*qDW^w8HSeN2YLG?QS{? zTg9_K9S225d17#AR5BNz!~X5ymwJdf-}H3HmqW+KUgAUa!tUFix#fLZ?Bq;Fc0?q)FPz04au*)cms}n zatgz=>_YLEe-&2ZIC!jfnQ$`SZ!FJ{ipB^BmSPN+V@t};%`yrs~d?PPO;Gn z+P06fN9M=2NY{E>6daDQ24m0wOYg*w2lxql54j zOi!4*`^mu9d*=S-*a^HA^+EaX_w*a2_a{hO+9sU;3S zZ;ZRkpohz^RhkSQLzpcm+gK_F3A55#lkcq9mzT}^V{+zHCb|wn=33`V5q*^ypA&-0 zgL0#-uhJu8Vbzvo!(9HEUdBCn=eQv)r@vc1nXzTC&G=)LAfH6KFOwT%@hkoow5<{A zGU4Hh$GY=RV&_m8-dQ0u)Vgjte(F@*Vii$j=yc}U3PE0>oA}-OfYN|-v(a9dJaJhT zJ^VVmw%DNXX)%(2{8O5D^y;NCeU}>fp$%pSnosOYtA1@+PM{oiJmU)xa`|*!K6_o? z@W<%tV_Fz@8A}zF)xzn|fre%*2AK(6yz-`_{Z*Wzauq#sby!Z`MSI=8R#2XPjS@54 zZIDD~gv@dY$HdZ8?4iAn8XWCCZ;n=trv-3*U6~J;<|1PbF}oMdjr(K0Q2mbuX!7wR z{Nx)-PWw2P?S-Dl1oei@#MID?^l#^7m-CTc?z9uu&5~h6DVffuJr!&nFF!j{^d%_M zby2shJQn%ZDY%QGh` zs?K%_UGeXfOy#zs3YX6(6id};a?~jHw&DVdA2q5pwDzm_8MD;2zB{f=-U87;yu_!Yg(XHCqAj^n=|!n)`vRWL z*U~GA!mu|6A3`})cJ*)7YntZ6Wu0D6xr3K{u7^fGbhV-H-D|SMm+%3~iT!hrvSov_ z`G5BnPKr!}!9r3dLm~L-6DP%}N?&*2<<-n>d)IHb6N-wPIdJ)Zj=o29UV@c&Zr) zR!soM(Ihzqe!}}M80o=0SZ>F}Ac-e1d2BPygUL=A{k2Mg~Z5KfQ_PtVR?(zZW7K3-tZ$PW%42gioR znLmC07G1@E&*0l`VnnB++Ju4n2fwR}d*pGEg0H=6Kc3@Z8L0}tDVA~Ax~7esLo}-` z-21Fy`&yGZFX%l9(JARNyE4zjxo;d!vDHzsUYKAqv~!_Y9IrneMviQ(dU!p*v@yxP zVz|8&07npDw=m~1X*aAGOwyZG7MGbczO4{4h;E5+-li+NCD9f@sqw@3b~@oz#?z?5 z>FqFLZiFJb^V9h3_-q7b`|Zv6Ng44qwBggB%nIT(QQ~huo?86)1eKH1y4ZPp*YX>U z2xpZPS8Drb3Wo?0Aw>su{n;81sFO9z6le3Mf?ktM*=CamB}gL~SQB?etQ5^-ils_1 zan;izT0x}y6DP|A^c-4JuJ_c?sXN<|zZ=fPl{zSjU+?!(m9^Tfq>)&OQIk0mb(~oV zo8KyP`_pMUIA4Qv>>m%)CFZkzfdGz3e&7aanJ}*OR`{CP=BXt9rhZo1Z+(zv?9Rga#$Kk)BSLmhn;r z4)$$wk{kSgy`5!Lm0kC*$&Iuq(jg+C(%qn>NJ)2hcc+9%3rIIeOG&zEknYY+cX!8G zJn!><`kxQy!#T$x!?AIXz1O|gTyxGf=kLBRL|>{5()GGVd6=BN{ilb^v=2jjK0{~h zl?hKP{hRc;PKnRW?D%x2nh~psxzg1Gl}34=j+=4uLofQ{yYvUQMAFo1v9*HqiV+EB zbJpn}QrQ+qZ<6gVIC&qZ5vAyr>mQpt4FPs~dn%45fv?8h)NQL@tj6E7iObrazIXZD zEo+}{XDdD^?YsOL8RG%ETHDP{m1DxXHuyw2pop18`c{+BN8D=un$^$1u3+w_U)ea) zQncZB*U;u}moNm!CA!f3oG;h<(d z0cURvFD&m~tfrhQZ{=t5eRBMDIWK>t-7w;2ok`TFGar|hG?qfrf?!9s#jtNm^Zq8) zTzcj`oMl$ELGUG_Ls91^&1$p{HM&#m&)Yg`hWpeuWt5n)Z%G=o$*b;Xd|3ODgnj;U z)p5=Qegyj4c0S9Nvj-PR_19V(sj*Q%jn)p&wZcQj@2cs%>q06RrEBDC<6~n3v$H85 zA+v{zEp7*qB;3&e?(~TEO!jV6E>@RH;VK_0aR;c(CBU78?%#n&R4i_)wkTAhfm1To zJ?gBPmpczP#G?=L+?o4r0y|}pSCH*5b)RviUwm75_41TYKF)oyS+=&M-*PL`uQGqF zY}LsfiA6GwczNrKxn&$qy^kk`qE_}cFlpWT?e9DXqvVw_Zq|B$!9X~tPB>+KKE zYEo25^>aei5g-Jb#9o`zaaq6Q)@bvUNry`nxW}`^_@00|N@>ZJp1EY2&6=B;*vyi! zUa)s0dn7$CUi)AxqqyS%bI<1XSI6i0Ok>S{&b?jYnL8Y~qI6^T+gx_H;`tWY5f7x# zvh)POuEgj^`@XSb>VWt{3+vt+ntFE}?Yk&@LGMXQ1zTCcZkz+&;KRD6F>Jl~RFNjc zLAbKQZWY5sP032Zpgz}Y5_dAv@Nwxzx}*DF{Q|UK@Z=Wc=tZlvJE0sVI^mt@{ERiH zF^&Sq3}XDD;QMV~>WUP^S-{l7*W|WuOf@N4KUhy#xq-*SZ)66MEdyS6Ep+~Np~IYB z2A@H**^*;rFSTi~x~7IR2s>UIk^%U#vA`LwHOR=wutm`U2jp*VZ@J*%!j;4KECKy~E;qH^+$#{_GHMdvLB#%xZkv{)B+!fH&RA zVXHqHsTjEshHZEGmp)H#&VCo8*p^LD=JOfR?IF;vSz3Ks>q7KRc@cDFCypyAGkbEF zN_yx-d#$NAlW8<{dyYwDOeg(ydHz7*^o&@t>i(zEI+IgB4j!2R;(IGb@mx%^PZe-A zw;Lmzq0A@eI7D8-gi+O=%ybF+A8MGkPNfO%xiOM2hNtLLA&3x7ttfAtwtXAs-7B)a zPn^`SadOEURDvYzytM8pcNLEDNzs;ptx8!r4`F%qk_kG$1b2Agt@+5F?=*J0ZX zYl4426qz7OihX9Zqx^#H6&?SszOvD$@(z6oPSw+I%jp6!N8b2uS+nwF>9oX5%tpX> zYPGkPcSc_YN8x%Qz}c0XgLXlv_oE0WkM7nTM;g7@NKw8+3~32`Q&^VFt%L2oRaot>wqwFDOeyA2CJ<)2*R*^oL8wvT#8E5z@7czx7#zl#dr^~u znW-aw3buHtW_Mk=RYKh!?!6Mp<#uMA=zzJIQsP^4?cAZO?J66GN{R)86{Uk~o{(*h z3vpEpP^37NigZ_WXgF>dJ=OlmhebT!Vtm#+rC5wzRTrCYN=&)px>q9%7q+FI%naL} zKW_YVQd7irQ?7owyS5e>9*(&IARHI>S0@`(NB&Pi8REnSS=K5r&8Beo>x<7f5O!DR z18hE8Vl#Y~;nwRjZ0aoTt2%5TeAXAZ~x>FvrnpV{+7Mc#+d-3s5VxBaG3 z8X7yssokMv`XNJ0@ZLBgv7iXc;h}F&gzD$YhVh_Z=Pa|^=M@BSGKi=aYxMZZeo=kc zX*ulXEkUqg&8=;|)>=xHQ6ORKay<{2@k`we|po{Xj8vNw@xkWOM`ZX;M}k zr_X0^2cj=M+pY{!{Zx}?`d6eE3-&Z9C{x@DIXR5mhZOr6&&Cxh(j}V%JK*RQJ9+{O#2Q`UplTSh#vaeLy-2Z&!Hvy*);~)cu(R{?4 z{nW!CH|*j8=Mwq^0f)^ZI7byLS@E9-mhmcxJY0tHJ?Eo^&lep44A%T!la zKf;j#fpMe3q+C_C$(tX*O3IYW1Hcs9ukD!+`q9iVA7$3rrIaDhge%cH%cwj*?GXJj zQ*Q3c!(x?BWW(xkg33W6;Ik4gyxw}S0!OMY2yyY&E<6b%4Ut&iFRf-VII*MS!7w9i z-rj(Yl$WS1kwc_7AOcXv1ZFJ@#KZZXw)z^DEJp^*J*`Z2;i`Hc3f144#xw*+=zM>W ziLe>e;RtUt&=xD?mDXF1b(wWiYYOfZuA*5~MTg$!PpIZ#EO1wxo_jc#qW#^SYi@EX z*gdwdPIPhENvU)-ki_y&#bWkym4vXJQFLaV?Dsq&d$7YsHB-y6ua|eyXYC_|3(gxu z+RauLD(&XP*yR-M7`~{W|Hbn(bT|W4BI5C1?hD5J=y>orLeHoCvIr%qUoOeQhzgj^`ouuQgxaj1dp*l?C(}Dsyd|Bs>zyuMQ zxQ4@Pn}&A%^YpXKg$&y8nGbB2 zjVJ+k7{y{A!kwvTRrIhJ{4bx3FOTa9O_LS9!GN&)j73Mid*OVO*PM$R?LexLm$ow} zcPKL1Udj0`3O_Eu?v((htbs-cQ5@@^dsNHh>ygr6>=PHUqsK#1+Y%SV^PV$Za45yO zieJ)mP9DeOeSd>t_t)#YrTN6|10CNmI@W{Yu*E#mJotQ#{=~tr?47gYX>txOc8iuQ z*q(L%gp}&TRo+TW(`|_8i?jRY-u3O2gl7IRrD_p=`0HO*$oVk&vfmT$+ zjL!5$5E(#Eq7)EF14!+dsrby(FttSkBAz$zr(p&KeMFkOt5HsD-;+w1KO^N9OfN!Lg=|4e-LndZ7<+E0YY zXy+3QQ)GIv=0>-&Z7TM1)3?qpeVr+Y#0v_&r0L3Li?n`UT|SIM%a+bT0dV8* zY)b|I4r``3EP4LT8wZJDCZBxs;i75O{p2FQRD=Lgnxna_&oY`@5f`SN>h&WJ+p4XB z20TpXc~9@Toxcn_xSSl_wamfhbo%YihF&F%qk!__nd>4=;Cz?FpOpUW3Ks`zX8)wL zh(5w`h)G>fs&FHm9eguyQnQKI>6is{#+Ctm1RC?vj z1B7MPED06O(iZ2em3*&h)fl9fY#+4LuHIKIEj1rc&HK zJan8+ndRLjX?-!QU^6vMsorIIvEg-LyK+{RtC9{3v#m&Fv|`ggzy}W2UU~dUvC0$; zf7j<$iK#@=%bBe81=PoTmA99jhwz8Y4W~&=7Wgi`>XXEGrpttA2p~?(UVH+vmKA|? z6*3XiLe=1}TGR2bxC(o^RaH8}4NbR&tQB3Bp`uJqm|vm33EgV~3>~y4J_y#nVdO$@ z&zaA{^@Z$=Xo51zke)nJ?ez;Ea+QI*D=IybP)X#)dAxfmvM~Zq58}(86hAv!g(b(r z!{&rd)(_VYP_B$hd+w()t7*XQx;2*%JO-eUikkx8N^@a?1~ihn(pkDr%cY(0&MW;k zxjsBn8x`J1ug!2)GANc9Yp?{qgbq6te(~%JrdxgJHdgOaY}p~j`=EPrp*k8HRZwDO z&0gO%o;?b6<(@t6RUj?c+EQFrUw${ayqh4fk#wdt#j>W*7ztj zNX^V28d{*X%}pN)Z2wsaU&^i}!9oKA{CdY;{z$ z{CT_c9o~kyZD�x{~TcT+f_xGqQE?s$okm_L%*~1{!7(sDBEmIwc%Dyv=7X-^4rM z_781{@(%YRz}*$^Wm)?h{l&L41=DTC`NYaVi#*L~z zKM0d$b*neQBpl82OK&<@xeP-P^#iKjQR}D>8S8n{bR6Aoh0kGu!IsVqe)q*F> zFK*a&ytVpma!(@$dQeeDcRRiq9etThYW?>PhfpC6NiE9}S5g?x+ zVKmWLx8!dJ&B|}G{j0Iwm_tMuzVkLMGn{&7w2N{m+hIr|cn=#m9|rB$G=up>|=I;P+2 zFg3^k4JswA-R8Q(yx2&r9PB_=bU}i{nR|>-NyH9g~BPOai4Gir# zj`erHp|Qpo2e&c!4^_v*B7IpW7x6+5uFtTxsBN-{+L?vc)ctDN=6Uk5!2R3;b2<&P znF~tI5c%ThV)DAJT)Xc0#4=s-IvFasp~h+ynQAeRN=S(zQWImwwD@-C7hG7D)L)dY zZ3bW{2XxvBaK}(ln5aIphse@sTyvi3eP$J$89S~`LTc7U)Y1tsGGN-hg(O1{7OwxS zJCD*XW;HOO3}`Q3wd;wb$-*y|=nBq5i&@ryYNxhZ2GNUAS*opM!vFBFYEZVk5-C=KS1Rsk9P3Oue0kefk!Tv&j%TI*2F5>2{ zT+bGlK03L)P`v`hMy^U={oM>p;9SmG(r|9|d1 zFYft?n!#C204jJH_sn6{-Ah;4IsKFF)jfgo*G_w8`cOCCtb`g$G;$RW2*-)h=Q8pZ zcxzMXug&WPrl>Tg&g&>2_mKA6Q+#^${}_8J3?t_KB0&dD_nyh*2!rbUpRW(*M+3a2 zJ<;#q7Z2#_AdfJ|*$9HqLt1b(V!0(qu$YJC?zcJ-SWym3CChLUJs z0x2d-vP-t^8Xf_v7!~j7!Rt0V-)))8;k%Yg{OmO)(2;{?V`&dm*B@JOHSP0Df_qXH zFl>TXQq$kJqJEo!pzjBHG%0kyk&5VpJ@51@mh%mc+_#X~a91AKR_!qii;3;#LbNOT zx&JNt`?W$hRcHQHtcDdLP@vS32Wm}o^ej%Df?rOWiHs}U^r!itn)6=mu=aYp>0 zCX`RY!l*zHqEY{BA&r95O9bxVZC z*p`|iHB|JY=-!ICEWeEj(G_&0YcN){GTyMVzmRP6m<`}}caF$PAr+`qpZFCAX( z>L8WCANI{7JXha@4qW)88*Xp6CD8MHm}ls7t$p!DJ7+TRU8kiUaMZUrcx_3DM1SGKh8pdJOUifsE^`#`6|^{$HJh4#^iJ1TItmtHjGc88zg6|G;ckv$=+;#Q;<#j;y{UYsEux=joVU)?V5M6WscX)25*>+XUYXiGTZ}z3pZ$AEcQ4=$?+X!N@VtMI?&pan`&1qm^tIe}gJ7?7 zOcd%0p9@AZpqVFw&uR23r4R^j8(MNtgm4^<#% zd+$WmBNOzivS`q)ck8>?n$x^JRNaKBP=ZAxvif{lkx0f_jOem&iD6IAhmw4~x?IR(0F==^z9{Ze%_QT%y6GpinY#<1=<>`(_bc)aQ~y5rVnkp4|} z4fIA&SlS5L2xi{-;@@z5UO5OU^!9O5pfDzXof7aj<~trXA*wA0{J_`M**Wsd{?(85 zb&Qz>N?f>dG3gHOwrN>4`EwsV+9=Z4rI9h$S5Mc9pQkR0oI1^#5k1yDBpP<`)3(Y8 z)W;o7wqncuX_iL`SiFb@!>lF!}e{`_Pg(=|+%XGvZWFR!U{FX0e zm{n`S$>w@&BR`>d$6D&16Z2B&M?$WdE6?oGmZf+okqT>y8XXVlce{NVTdK(B#;*#5 z+e1K%#y>J^{S5rH_B2W*_NgIo&UeX|n(37)WE?yzkxeZe zXlJZ#vGtO)H0~LHxxFwLKagRRr$B$hHNAE6vi#hsY*Tmm%!2IQ zB8SFly%V%VJv9u1Nlc8{)EC3&eagDq$1UPM_d$OMmwJX^+}(evr^3Cma7){`n_yd6 z!2m^kV7@)-q+pKIfHww(9o)W&^Y6L-BB=VWE*qRu&rggA>Mt=*!Q_e%vJkMDyK&3) z_6EaCdwqGyb&5*o9gt`B@KZfrZdb~2Nmq(Rd_{iRd->I@tmbO}0`^c&8os~Z-6pJy zIQ~b>Roy!5=$)h25;V+4jT>)XgRo`JDi3Z`b24<0+*JEAA zLR8LMmuzE=*_#Hl45@)?ZOth_==1!vOUO@ZLbCK=XT3R^hWB_1yKdTn=keSQKSb9Y z4$jtk7IZ6Ne#-xyA2$nEd?e>~TYGeD>Vef3ly$_Xsow`e4jpcBh}tq8x-G-PObiV9 zE)uJctL^a4uZ6YQZz5DYEtZCC!tueZ!DW9Y+bB$fZ@hSR|?p%qdOO+mcEStxto->v1c6)9&wV zFqCd)$m*wR;ET=Ue0qt*G!B1dlfmtEG$-<#U;BO&T)cEYJ2XQhO_y`fn4U9Ckr8{= zM~>EQqEvRdIH=p6@ism=JJ>C<#-P>D>sKh3EWNC_vEU4Zrfyd7SMA;4=O_PU&BJV) z4-`@dNI?$)E5sQx*dU{20SRG;b5UD)t)lV)?}x>-8iIrdEXT{vxrB!tKH*TUlDSx? zv;n80b=ca1^DctyLwzKW=+sUTU!C5spPC!ypjL%^9A)E~ILk87V#G>m_}fQMqgqZb zrcDwoi0E3}qke647ucT&b4&lDS%Ff)L1xggzVcI3x%-JfC z_PGat^S~KqEvND@%pjd~Und1cm1dCA-Rl^5*|R7?I%`L6|x6Z8|ZF0s-B_oRk7=!i)hh*MeR%v*cIM1ywO93n<+>08+4aSLAk z6wSAT2kw?E7^H)SUqlJQ)V;>|RsH@IY$E1fvf`UWDALQW*+Bej$Z(NfRmcmbyJYc~ z7?)4?T}7pT)tzXJN1smalwAp%p1r9gF3NpTrn*>@w>Y+-yMxdc|2~#zLco8AzzV|= z`<=U3{p=Sc8L*23o=(_z(mriOVi0L9vB_+6J-cuEy>2Glm?ybsZ8_|8E=E<(NB8x` z(#AL0Zo{ShqUrIk)o6<#Z%0cDsEN*B+Uk0M!2(P?CRT#1@-Fpm%(SKdq<7Ex$K}SL zjvYI$0_!Cl>njy;z>Vb<#|B+%M^_>sIkWb}j{sr~-A>M-Qvr7D$uByJ6TNzZczkJ} zR0IDzvgOaBIROtVX5dswgrVs0V$G<32Xf&ZAI~m3s<>XM%nox~84%m$bBkKjW8USC z?b;mp!Z(!b-fr#o79wlHOMQmA+->coTFIM4UXzZXYgq%zuP=PNbDzwmLckt~C^fFpn}Fyo=7MGDxbfZsKj)MXe9t7qRo3EBthN1kzk*wf2}47 z1F|WIX?!OCVN{yB@ z>%WGV^~&@npi1&(KyC0RzCxMD1q7?u6ZG$t0r9{S)RcdI2M)1MA63l%ybz)IPecSS zz6t#!)B9)b|0Bcw=N)Ji|8eW!1+LJ)BcTX*6Y&4zgR`s9KhHaAp}gegp6;QN1Jrg2 zz?uf7te9@Yz2$G8M7AT|pcV*bz5aRsc)FmpR#F>FolAJhDOQ{Kpt<-XIvU|UzpFqkHRllk|Q6e;lj;E0Hh@$vDQcAVI6 zW2AD=#aB{AS*($mQyZT;fRcN^*{7!X8wc=!p14kt}5t+ig^ zxo3|Z%6~@%iffUzN;z6CXclHYRNem>%Kun}-z>bmywtL3VX3L9RiUrm5&n-)m?+_W z__O-Btd9#Lr#Z6xc(#3f^?$Tn%BN?OItoR~^t*d|W|JkPbb07o|f zTu)N&(X36=nnvjk&!f<%v9Xbhi|dgB4`}e_sjVSsYj+n5dD6)owY9aMi`Cg7*kn?M zhK7w+3_6W{0K9N?dir;II*~&7tL^=*8*Qwr;%mS-&I2eEx98H%n?qleij>!iywAAQy0b(>|KYOJ$QlC}4A3Ht z*4XGQFE9VnVv}q6nUjM(oQ zA;u@`{bA&SX{5Z)WzKu*z>Gj=85=Oa-DdeN<{TbDA5@ZYWo{?N`uh5{7xNy)s^)TX zNJvObPTPt?LPAp&CfNM$r;Gb_2kU?V;R|fSvCiedc)c%?&0>OX;YL2_Z$F#$T!O>K zz#2aQ%%|5oDHriV%R)eRV|%4Da?rzyBiTt%Q1A}SUyXi&h$zY?K+g1fSe2_fl9Q8r z0Wh}P0TmV17HFzo4+=h520jZ3p<`f>K{@SD=G=jnY=?9kj>OZcMb}7+hy-APtFx(5 zW)?+W-`_9s0TKtGONq+)`EwIk@91QSR*}ojgtQNUm^f+0ACTKQ0DQ@WzrR1arb$1P zl3qsndu*)e$B$1M+|PPE26dSpm$=$y!MZ&9 z`EtVBkzJjZ92K@pLL(z1n?srYU~UY-6`L$Jf4SO5 z>$-@1GdG+qespq@?YuXGK`xMzpZ}&A>eQ*4>w%99wOv9mt{}9rIq*F2@bGZBJk+C& z{iG-clxJ|r6FGBELU5{dc+@f}AM<2VO-FvBW^6|m7t<>hDt6ZtkC8{w^6{l$k@DDH z9UG;jrm9t25{478zhYxk1b$(xH4uHe&V>;yRHJpO=fk(;N23QTMD^y)H}KC9VD${= zNaACWaOsXiDIcBOEy|;nAfjNc?ocv_==u5iJ;B6W1G)t|E$ELZO7Y*oLM-ql6%hc! zhVN##;+Iw(9vHR-zPKXG-Oa_IhV{fR!o8WQY~%hUI_-J_6cm)ASV`!%+L!ovd=3td zNuviYpL;$50RiQAvH4;4JE3D#cC62-r53@G8?JPO1Cv{AI9OQ`26Pb#35l!f_-ji0 z>6sb%8fz`}D)aW6gC<#^5li>E{{!YZ|NHl+U^kdf|E3bl#>pP;TJKN3S`KAoA_{l) z@Q@^ZCaRqC>BaVB>0r4*=dbHKaE&jfW@bhTm1rkQbM}Eg@9TW2JR< zUxJ}sZOhx+v+%m?|A4+8a!N&gPF-d>&B9?h^+L%Ca|F$u<_jo)A-N2 zx<2mUsVhD~9w&aE&T1kv&p}8?cwK9^;^^Yy0vjHdYuZTjI0g2rRyvf`O2F@4sa;_# z4V#!yE>*88oUbsEy(?|H@6lj%633ma+Uj!B+WuZ!uGjW;3wU#AadGkf!9giDF^80( z^RDW=yTv%E^rTaRr7-KiVJUwOl)Q zn12oigC7sK1_=Apg9UQ1^UNnp`oY#c@e%+|f{fpNadFW%FOSBcBaDKboqd6$!elVl zZlz;tdU|PRrx!qlj*FXsI|A_lJ0c=ttVktN@cuH}QdS)V*zteL$jjBo0C~=2*!8rv zwUt1?lM9>g5Dq-68xC0RFo;ZG2-6K7oRV>LdN8Qd6+$+MGOXUWu8%w+S642d+anaG zor!*zu$p=IP_UKLfzM#oZHD`bO)dkX%%8M8kc1uQY(Yyj>K<1>M2_!zGrKPt$f`YV zJP(@AXDsT$4+xu6 zY~Kp6> zUlHnZkjBV_09<~T#{N*IaHA90FE82HaDBghd*bKsf8s~&3s7u&07VrR2JYGbadUIJ zVne!j=$BeWy%7x!4akFnLqqGv6&`h~sQ+Y^S@K|D(2^ZZGdo+`HzUr}F>e5SxF1M_FMch?k0*gm`mxX{I z0%8oWKXGbcqS|TxV-2x=eNy@c1}6Jl?mAYNWMUmXfg3? z31}R0K;p#3!@~j$NZ@KUrrs+YNECbH8BezI(vMrw85h^q+QD4+9v}sRGU3N)CD|un zNrXq);^;LxK;BWTg$rh>hLCXOf1CFiJf`<^96vAq05kgi>Yo|;CsF*roB02IK&;Hn V(H^MpYJvlQBt&IIN`!R%{ujBnt@Qu^ literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/Heatmap.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/Heatmap.png new file mode 100644 index 0000000000000000000000000000000000000000..22231ba0f1be2b2028052cbb9d7b5510b13fbf8b GIT binary patch literal 113334 zcmc$m1yoe+zwZZ8Q6$8mL#0INZd6KILAo2HyFo=kT0pua1nKS=x?u>3p#~U2YKE>E zX71+wzxBWCo_pSN*17A>TCkZt&)&m+Vn4s<`}uu$$SY-8LVQYm5C}vl_fkp~1iI=9 z{8Zn#4(#c#3(o^KLax$Uu4)bzt{%qD<{%|wS4Ue1S6ge72kz$1F4hkAJnX#e+^i3* zTwNVqggH3u{w%=m;B3k9G;mo9ILS@Nm)b5M(5<_dKRBS|RB{jw2qY)<{EcVo_PmF$ z(g|J9o@RU^7dL~2b@7bu=lk~y)#bPKf6{)}7=0vftsboLI%VV=_^pjY`P)J<9g$h4 z=iSICD$SD4;h~|`3tv%DTIb=Dbktd@3!;AAfB3{VN=Z*okNVN?FB3jnHkx;ze}9S6 z-FKDx{Z$l>FZ@R-4Vh~+B)`9&W`BtMqkP=!=d!;S@9h8ajsB05GNlQ-wGRzNm~@3Q z3Q4fDM~eHM?@sDEyv~xkdAu`wqBx-b*MW+{uD@Cf)C*}v0#^IuQia_@)$)|N>}Gfy zJdl`wFA0>Asj-F9ieOJ*0eSk3?$guLukuwHOY|FMUcDMoODO#7fBU4@;2JVl??Qzg zj(bX$z^?DTxwSn+@s*(zwS?6Xz8Y4bu`j6*{DAb%T{4@E+pJFl?I;z3jb7K9BDH}} zL+OXd9%?CCG`hwUwPo3N%~iYJAidwQ<+oki)(w2}HEn3iXC8XY2RpX5GeBni*y1QD zcfDb8RDj7%tG1;X&sE~V%valJHn{J+JwEYkmSFp%HaV8eZwU&ytgWuE1|MBjxES zSns@Q^7F^*IdA~oJNx;D*I<7?jUuf!U594r^TUlKKATA%HqAfVkPAFbt{`hfg27-^ zQXNc9JHE20rTf%3tjhnN8q@sE$RBNA&P^%#M}rS?uuqPWG^zglbI-qZf&cI*4bxu? z%twDa<&$53bSEu}|ET)~J_`H25VWhy`qj!x&R_NLA9l`B@;~az#J`+Ul36G}_&@Er z=Db0Flu0y9?H-X+-pu^7TmRcN{r%sL__NF!8I|eA4Fi^ca@5~1_PVt4Lkb>?mC0h= zR573UN7A9M>Ku);va))=vfLH(KKv#bOcYPFR~{6=6~Z=)VbYysMLS^LCno5AZIVzGUhSde%vC`*)D8T?zyrVTZn;kAX8 zg_X+s;yo+&uo*FbhPUweOG4yPqto`tP0;rC4moDx0seiC&uPsxPp@e3tOs9XNuC=2 zTKYQDAluu>(sIBM^K>txV%n@lk`gaSnO3Up&b2zHqwCoXQH(1lH!e9wLc~9p7IsK-b$UXFa|Cs6HI)tlLxy?MU^s^FUI3yixQ52W!goNc29xTSCnQZ zH`?>*^VFE~*Ex+8=?XkGA3fP;&pwZWcSTqewx)TO=076%uJcbARre%4Fh3)h8kHQb^r)Qw$V*!j| z{^*I{uHm{0=HrzvLKN6AisME-`HQ3i^IxJlcZsaG>jOBFtxfY>j8M-(!bF?Tc9@V~ zSX^Wlp3e1N(H6^y>N)HlZ@l9{pG`g<;2VPq$Xvcg!R2)$(wYWZZp<7jL*9bd1S?iv zKfM5}T_C8VU|71|^l?J0l1t*=ku9mReyUY{{IM_+wd+lb8gyE~eKk|ba3OQl4z%T# zX32QAwFD^HZ~9|UF{Kf3OW6MuP~q7QsI1i)H4qnPgQ6KGKTVoU+(tkWdKT8xw7Q8Y5z;?AtuU>AyQgKshDR=N{O7 zWIFe)boc13B*IrH|4ro;keyGBiOQmQvRAb^u$eiwz4mOJDB={kA~Z9BP=w@O{Nkw) zIVK9y*_i*~Q+2ZO!Y6~Blw&Q&6|LAWWT(Iulij+gSX%*4bdT>|pH%W2YbAtl{ce#q$vd7Ntm&(Dl5LpRNX~@_a-y?s z^u0#4@K}jG8D*^>ag-jy0AM0x_Her*a zx$c%TKM{kL&EUoTvu|$>0+}-V7vg$jImqbVSa*>HGI6hPoe@(=yerR8Tnv0teECTn z`~X&MPR#b!{o8~HjSvO1t^CBaG`C8;xo;Z(%-4#c8znhFJrCh?yeB$n&RFJPo?`d+HjmOwl zvp7rgK-hjb4C_}|Wij`S*_SvR38_B}hv#U~D8n zmjftD4_b&z*UKS#>tYmX+`D~b7vw*e)O372R>q^m@g4+Z3Rq1S;L!2^Qf{1~Q(dJ| zac+*Lmv&YP&GV3UULBBgDXmc?7Y%t2KWBv6FVq9LtgOJ(>52Ct5A1plsHsP-vNVG`tM2IJzk7=Bl&%OA@> zY!AJ>+shu);2N#Q@VzPBy7p{BI8K|SjPl)moWgvKT6~a`lT!{Pk(Tq#j)PvKoTBTd z54EBEI-Q?HGU^0@ySSKmol2MLfcY%EU}Ddt>y9LQ@Cgm0+FE#&Hra+y6Y??WX?ziX zNmykb#0fL_NopV>ER0_N+;tiXjpi?=A3e#c_uHyTs`PUIq;P+EA3AU~jhN}&pO?xX zCUrlfpUJM^^o@nvJ7WnbdWy8)Gw%9>C)}YOjZr}FZI&8ncG)5_`ju&hG$M9#vKU_J zO0t<{UK#&EY7+o63i@Sea3pMij(Z$1{-UrlrBV(Pz^1Kq)S!+tUF{{n#T5jfU22x? zMJy$M7zL-kh}y=c#5-h#M&-$+^oyq#X;+ZGV+*kR?i!~GN)>kw`uyc7C{@fUlGmEX z=_MT0T7J<}f5)3~^^VugiOn}$2rN*KjBwKvECID#8CH`AfnBF-#A+69b*#6#oe(mA8{U@;>hPA|Y+Cofvo1!w(w`8^%C3ECIVG{C@M4AK&4}E!{;w<@d+;7M zn(n8NiTSS6)myho??o0iDrE6zJ~!?LO9r-w+f~$?(LciEh&?*Qhw2d+hALQGbW>g1 z-|cB(95j@Obr46ruREoyvZfyAbm@ANi{<+C)~z6s51dyng|QdXOR9Ch4n`UbqFKUj z5QlKuL_+#^qTNWmg$M*ZretU8l1st{jO)ZIT4<{=5GARF5VNlL=B%)brw4iLYu(i; zeN<=#$34#Z7UQ<1I?u$lm1Tsj?Om$71Hh!~)W3Q7(_AG{A`(V)^)@g-h63!A7FuJY z>uda8R8viw9bqTIzGW7>znmWA&&|<_5$O>rxE6t|rYpo}1-5xHY4lNe2UCNK>)&Co z3trshk-|Fb&86LJPBp?3J+&-)KZTV!?hqdl6(&|nU9P!7!^!gJiDLp%&}D;hap66;a%+LRui&g%WIow%1b33UGLbR8p47De z#9TuM-hJKMq}0lhqO|DUErwxgY?Q(}yRP8=${y=kumMrF-Og~GnaA3IVRzY5>5v{F z`0Y~fP@dJsqt5P5Rq!F6p!slT71j>|(>-xK^ZoK&lBe;xUC{F4uhv~;uxf)m%d!2u z<;EA*EZ`6+>4jC;U97h7y~@q$JhstMt|C2)x&jJX$~K=>zk2_p>z~5NRtmKZN19|r z?0ZfYywz9O5);@v#LXPHjN^$I)i*@TaKm!(ZhJA0jb$dzZ#5t#hPE8HeH<5nP*yhc z&b5tsTTrC+IOjza3-yA>SC>2pPeA{p7Jb3!UXkcjVP|3WDCUzU+KXn@TxXUAJMAb$ z1d1}x&0#KKchRvz(9(E6DVYjRO6gQ(}rMJ?I0Jp(ILH9*Ls7oEidcAiYP`~zL;;e#m zIa@zcf(y%s;&z`3Hd2&K3O1U<-+s*G9R21cwsui=`(2nNhs)WE+YU`}!P$6`RE9oh zzPC~C)ZdKCYgMbhnQoxzfMK-=yKBj!UM@(5oiRx_%gC}0mf?MS!48roPUX}l14iLZ zLLwe(I!bDb26pGVJLkRU-fz;nk!7ZESf^BvBi}M5o(J99PRu7YrRU6|y{@Q+hQ`~p zX31)vj#uqzOFrU#GPSW(kjW#MtMi5@#Rp&!el^7l%5lPRYU7;jBqa_K3Dm?2#b#6gBY8RL59?Bw7TP9l;)+EFQywQeya}w|S~4 z5ynJAx#y2QmT+IJ>l5a*)g8Z(U=<{olA4884P}SMvw!di+&rXQhzM7v2#JVTU6}V_ zO*+!$w%A7-ocLkgM329BdZ}2wBA+Tl zR=}RBF-H70iT9^j0SC3J@XS_?(tKiF4XW$HxAZF0&Rg6-Kaje?#f7!FL3x^S2TyRx z8}inMGE#sM9SbZg;N-WGDurKX`Ep@IyoS+o%tn1^AgFd!Ou7C}F^NYt>qU9qLV$y^ zf&~^L=m=j^*Ug9h{Gw3K?clOizO_u$)!#(;>>}4~x}e|c%_J(+qR)o~ zoR`x@fS~>Or1B@rVqcXyt1;3tC-#)fxR877KA)68rBB&rgub89u-uq)w)?ggfh)t z{PO};G=)!H%?CE0ZFbW^LgQKXe~SYelx*&jXIL&K@B9pdfYTjlYPw4kwuRQ#wSN;x z2zF3Je34F1QA$Oe$dUBzP45G;ShBP`-W_fqiy=x`4ht$sizX*XBtB);gfadRY%Tz!V>V6*Dkn2^bO!5NPdu zod_vclc4ue7Wlvs#Mw0a*j}$OM8VxMD1e8YOu(|N+<4*Zry_%z$mP{gZeS_Y+1+Jq zW7@Gyp%9^I$I8ffz+qU;>L=sQOjOq9XmW=7AYu3zLCzz(up7&9zNDRf<#n_N#dtu| z-rG%dHIJ3r?5)&tN>!UPz8MLo6LLx!S0r%#yaa62b>4$Gjf{H??u|>0nQRf)E#X%SSIBX>EW* z>tTZ`@tzJ{bAI00>%6;REpI|$82<|}uei4_VuqqB42Hdx@c15fdY^ZD8t4r@NbJOx zH&<&ZhjuED%T_m=GOdsjSR+s|9_IB74>1?17~d1$^QEcB-)80n$M)qy@J+4Ra>(%7 zYN<#Hyb14{TkRUJl|jPvv>;{|J8=jq`6)L?`#8BYMC&i zwPF(o=Yts~w70LZC{nx3w4~1qvZx^`XRsW_N@qJ|ZjMW6WjMScB4aMqCjQ~D+OH~HSH z+2Pf_e~G)%UrA8jQBm=8|3uIIyY@*K%KH2FtdZqCkB*J?{s(%l>7QlJy1KQ5KWK*j zSC8t_`R^R{mLTmPNymTZ8dk5&e%HUbz=DLKsj2^@hW@UT|6|3w`%hK8GAt|%pb4e- zfX?x?F2M0hK9AsXN zN%<#@^Y;@xkCy(|89LD>e2<--Rf+#|d}KxNM;V}+BQj(E%hk-^{olb6{~TicN1eX# zztich|6xb`PZ$O>#RW0|+tJ+}1n-H`75>_@DbXN+^Zwv+@qI1q{>us_KqgKCBgn2? zSsxE@b%49(u_m2P20Q{^ABO8GWY+2eb^KE-7@ zd_-kr9E%9Mz4S!MFnNA;qm?@iD5 zXWawPQ;^(OdmrR#Sb(@AjDK*gb_YX1Jw7Ga4EapU3Kgcq9#tj@y0B8D5%l2r;Q7e- z^L&-2vZ!>NXYKcnmk)Vk&}#(7pzG=1F;cC)22@Qlme-%ZQ>`DYM}n@Sj#PNT`nB=Y z_zTbDZIdF#`__V?#a{p>;rOq|d(xjmZr339I3;z2}{kbpMA%(U_6^gTh5fr)>i?ba9qrNEK zW1ty60`GT+kg&!0fg!UN8zRkkTHSs;eF;wGErD{nTPJKQJ=OUhDa?m^i3?Y4bz9MH z;8#CR?+)WmLKuu@uZYtg?25Lc<~LdA1jBa71YXs3cKEIDsD4UnbieL0HEgsnLjmZ1 z=EtJxaYDmBIvzImqP0n2ep z=Zd%nwI%42Dtx%^zx`^7Skq>`kt$i3&URfzp2+)BlTMWn@AgSABj){F7vcsNahj7LL-4};p8 zM)F>a?22*j_bhd9gt-q|c5mjh#OAydz3&K*Th8oAH`Fv!0c-$(aOE4YBnR|B>YcY9 zxt8PphZIm6AH0rvUyp3W=tADD9lr+7AMo9;a=b}=1%@g4u|<{SN4#8IT&GIsAsH={ zUHe`V6(;i*!)T9%oFPp$|4id~9W?(sUW12K-%7?hsLTsxADJ%N5t9U~++CL&G&rQH zwTG2UQ9_D=v9mIikm4PeynoiZ7oN)bxX+!QnP9mR2mV7dpT+B7wR>Q8T+jgl3A0iy zWK()uZN7EB)4f49tk11XC-zIBa(%z)l8Sj?^mt3=VgSM4=+`NZTn&}5Kgb`Kd8E!+ z!Fe4b4Zugx_Dn^}8sE%#g$CYmM*Xv%1v`+{+_@M?$J67RP0f8q2t5kZ zltDIHr6H0$`L<{BNCZ^py-L|UL$ne|X?I!$vFg6q)ec=b5Vf_l+gO?kjNXwQE7lMw z5GYbcT&Y)@`DtwstUKi}TCZd2pRz}l7Ua&I1T!}yJGPxM<+jsr6_%-@GCn?y4O|j^ zK-QwJ!(%@JjKuB}%QoS|{|E00}%9 zNG@s&a(8zJSdR6e+d`$$rU|@$=;z)z6nyYNpk#gpoph^vgJ#QL>dlHie<^`txi8KW zFU<#p!G-s?bGSKqu_HSX@7 z0!7v#hv}QoF@I1gd2Vb2Kn2724QOs8wuDCoxm{mem`4q!3Z`UqGw7G)>p;SOh{Vsg zL~-{Vx9kGwXlg@dU3mVNPAML+ny+w+TdEXm2+nX?Si7$ajcL#DA_0bHU$JiO4FZCd z1Vex0(JW~YufQ%^40QwufWG(?U)Pvw1z)r|ZtJI6tk^nG*qeW7d{MM}y zbeoJ!_B?z8=Vih}8lZ6)n1s8x&vL#xe-Dj?vc!Jx;0z0hOk+?{CU#zT>}hLz?_FI` z{?HNN3p|z_uQC;Hf}VV3Y3n{cvm8#()9cHco}G;r*Vn;sIlB(brMaF&9PN$veDQci zR~JVXI?SB=KZXGmg9=z8bDIseW;O@oXwjC%=o}T~c^35*d+T#(TrIk?xZ9Eq6#aZa zUoX-q6#G!^IuTL?zcuuo`p+M__uuKKc-*~fdg_aw76ICLvMWJfI7 zYz8cLoP+sEd|9r(d%C1Kl-d`TuU$(yfU5y=v_irU1h!E@=mfl?)<%PBX7-cQrPz<3 z$i0zi;usF=apC1JOm6zc>{b9#T<1QKgwT`}v&>j9Z`^dL%FV zo-jrn0DEtW(+!@*=1L zL5WflYUc`%Im#A4;YsKB%7mN3bW(>GR{ZFekSF4~vlXF`jwS(Y^`{Dh@9;cL;|^p> zT>w(NjqF3c>oNBy1q$yxD0FryagsztM0YILg+Y|zk@;O8nLqGY7afY=Oq1VQtt*ea z@a~EslQ{NLtwf5qH#eT#VG{tvvr~8LcF|i7FxeydZ>0_IOOK$@o;6oBTz-_m0$^i9bh2WKT%+b2=RGp z`qpA1K94*FNqsbUm=d-W=G#{U^UQumiC}E` zFz}IeHr%GP_kN-JtJt?_*5udw3i|;fdsxWI%n{W+@27OYFd?D1 z-!)+~1#L#&Zp$>*!WAIajE&v?^6gcHPhE0VA7V-V$*-%Du$?d90N+{rPJTV{2{x^Pfz+0AO8=T5Bofg@=x{;(y( z2xZ7`H(n9zfNsI&_qAZ3?ReNYA7;ePfjwXZ6itGb9+vGK5>4j3qK~Q9w}*im??R%= zxytA2z3>2vl%tdppF5vY;ke&^FG8rkzM=6>@?s^8x6q#DEFe3VePgbblOG+E)~a(N zy~RJcJkS;!evMXvd&&!f3#5+ZzsVL&(O_se2Q= zyXL#hsF?LQwDl{JS5hY!x9%p`n3_tKM$ad5Gws?20Q4;-x%9iPgs z_8gWia_WgGN}x&*!`*Io?*0bt`cfxuY7(zA7;L=&=t5Wk(c+Z;E$s%Rru}@=P&!-w zK~{WN@P;@oDRpF6Pd4gfWx0~AFGg8AExm3|Im2~v%39%bXj2OMIryrJE%IX%fcYfv zNT=MnALhch{Uia?_%(IovuGT?a9<}3mO;u!aAH+sHF_l=Am9ov?%vT+*W@Irhlj`8 zNnY13QK#jr!NhdA?mIJIpQz(YNJy|7G$pP$=P9Mg0J(IJHA|=;)^g-&i9?p3kLH?0 z>;t$c`J|usd$Wq=_0uD+}WTYgiiY4#53onhu| z0)0rwi*~O(Makrr@yMGQeghvfWMUthUcV)4Lz{M9!^p%G6sJI_Sr?BgeZc!TyuL7( z$H>)zXh%pQF!3NK`MA+lECUY2GGj;jqcs^mf>Mj!ye5N|S1 z3elDkgSXJNF=wAA4hB@d5*Mc(jRnFn-N!EutmeUdSk!8O)O`6i@%Yc}UW{o~0W@0q zNIXj)IT@5LT$)%X>rLx*_GWD)y<^TZCpf-2P|QF)P8++v_LTr4nm#sL;Did=p4$~L ze!j#s4tsLWB(%R~v{hiY7CvkOWF))M)kX!;gTeZXw^Nljq!4wCo8i&QF z4SsYz3vKC7#M5o%mn-$R{2Y#kNy0`<2V&deo@!2)8RKHn2gE=)+1c3%q$)|myCY(4 z>44c82m~U;+|zRac;dPOd?|M`>L5{oC^c??F_Xe8?G@a`!C zak|bH8ob9^+idJ<3i_Y&r;<_%E9FX)zmz%7=_!_))YS_f>}W|6SBQ8#(ysLqQBEQV zWbpr4B1BisLr@}M^;2qpO}Y76V?0gDSk({;L@n-k?nUA6seqlJcY{IP#{ zN;X~;9DoXedk4TB5#W6xo>s2__{i|9esxJ+Yq#U*z`oMkvso<(F?3Fm*VWm{xlxIX z2*6gLWrwjTr;`KC=h;y*?>nk(Ju6JZV($5UP5!uSv)A6*Jot9ln)HzH_%JFK6kX{I| z8=ymnNn`=Bti_6dSEG^w>OvUYSoDwrVe)E>vm6RdJzZze zRQokK(7gj&Z=O8D5%gdD*vIdF}71bM`6z;7|rQIs4tfen>A#J&Jnk?QT7d3043=D`mCc#`P z@606s?;`s#C$7|9Idozyx-f<6qz2KZG)x$Fy=zkU(&(=R< z&H{V7W!)aAc;ck#LDn8fJJ0;c@xYN0m>FhI(GGged(-BmY`Py`Fyb$RO=$tVXy!EB zE`Vb=3iJ2|-S^a3n_eJ(Q>6Vq7Mr^K_LMJn6$*u_R;QEEO(5;lbEMLriMhtK#V{&Z z&DOB352wKa0;yN$_}=$yKblRKKb~D*-qx1&;lqcvGgUX=z4(MrLP~1kd}}hAUUu-# z?3fUihiIhM{D^;(?+E9cRnnum7N^>HgSIAI%v8 zf`X6;Fo)|o8bmo&N=WYCYS?IhS|QmOjAr9v z>?eg!4(WajPWFce2g^93Chg?EvR!{B3G=qqGXJHK;W!xWv8lQKb1wj=cQf^xu5O1h zpXLJf3cyjr^1r>K;6w@NOd+JUX40msoSz=~5vpW8)mXCwCN$|z`g+-qz$w@4LgT!s z-T^=sN-c4kVL60fwFM205+PW%|6o5Exj`+L!p;V|Ul>OZ+}g3q=}Pan)9v?)zVrIz zi484SLxR+GJxjIGH5_VRQv@8C>vtUH8~-BX2HfsWYT23YC(BU>3})YC^mkM4L85?_z&`wgoZ>Mm`l9hJadgFFC@VS@p(eT(#&FD9cAJTxDHhr9|8XqP+SHc@DmzNdR*yu&_1X%77hZScf;+DA{ zW34nBc>pEE;-KK!rU0LB6dBtAe{H%a?QQItgHDep?XDng{d`2=gU0ni<%Qb)+pb*G z1W-|Z`P7qlOE)vVKaEp#p8sjTl4h3KqvxM;Ad==Qo)rs`wbgHqXxI}1>*w~~t=Xel zh=kPJtI=J7A57O+h`9L?mX>a9NgDYM&raH^IM!pnM~J%9t2|jGp{)U zjKB#oWrCe@rF`)Q^alqSrr9dmgs3$nkhwRGgBejjU+z)XgSwyu=-+(K&~Y{KLCL~5 zN>mLEr}7EFw~4H&9U(i)CB8yJ{)<;L6C}MFT}i0Ng|7rTsSl^|(-=Oj7WCh}Ds*?% z!TYrrYKG>g+!rk76isJ&)+DjVHuWJs-EL#PPJ#^EocJVE$S8g1;#u*D4HNWMp6x_M zs)UR9YZboeuit2e`&xnUrY%s3PGv4f?rtQFh)juIy(em?wl7UYz`XzKLzlI|9J$ya zMuqs1JQcbUL$I=|EAPemQMT1+mPLdM>OAeuammZpnzOlxrZ89!aYic-p!v<9$Yne; z1Z}zhMsP)zfd#TiR|WuZ;mz?!H(SWtckQ!5iF{tPK&e4MetZ`}sMeC$eN-s$*r4Qb zU{8RetsZp^KR+;cW>n@Cm3}+uvxGyNvA3s6=D%rV^B@c)v<$+DH-_(?yOcU)q#(btTyGraVT4 zQ;hNWcRt(RDTc=vvTfD8F4i#DK|Eu&$?zbxOg-C!kz&Lb#Ll{ zJ5G5Eap-;2>a=i{mzV2&AAW|w9XMDt^Ld-EyDXh@Qw)0^ zrxSMyi zIS`O=^wB90%#`Ay;lGPbp03k+5!g-v6>$@%u-|Ifc~h*O1a`lE`@UBK$pvlq*;a$l z<$wp71}kUmu-KJYJ`QlUp>u^#MuLCu6RBEna z;q$LWuTtHcbx3GvB=u}r?*=RJAM2GdxTKwc-juF)m9Y8Ti6D*zG98}0c{-2~$o&0T zP{@uJI81)wzIK%z?d#~*;V926r-ea2iSfR5dJq#KD&81I&<^BYhzMYYh6w|3Ie|1V z85Nr6f$>K`4t{&Dy=i*G+)s8Urg#TgUr6UQ_`jIHda9ULWF+pa%krXJP3e4FsPt2c zU)@x%SY6}*m|=y9AuP}^f7yS zc$XXSS<$1~!5YB&6kVc&7uHnj{VNgLh-?|CwwbE)K+@97gnKTT{9&r;#eD*N9O&fo zJ7JWH3H#G#X5zmGzazKr+3YZU|99eA{^IY{?eB(}zgX!(*f_axpPbk~aISIvQRb3M z1}Xm|F8McGn>p{}ir;NWfH?@T?EII_L4{ndG5=*i{y)SD|1fU-Uu;_Uw101wL6yKq z%uoOB(gF-klk}H}RV%(Y?K^!Lxd_!nx}jyclT$p=b5;iKBK?vXRs( z`XzrGZ$3&rBlWHucj{f%`7vovHQ50b#e8h-03y-T(-VvYW7B7A9V!7EBJgE@jY@-& zD(i7TSV`T30e__XPyp^j*Iy&=!^k))OuF!AYU~uY)$on}GS2OP0IZYpQziOzA`+Iv zslZC4?ewH8jI1w-2N2Z_{m(wB7i!=vZfwZCd2?@RX{oNhUd+Azuj5UaRtFN+f99*9 z0kh~_qes+b6_goE#`1gZuNVXI5QtjDJ^aUy$9nqu8FhMp-CPDc0ZSB}|LJ>Sx6M~M zFG-U5Y-9jwfkMccVIYA6Z*i*>Yyr3`zp`q_#Ixyg`y2zcWt-kK_w|Os@59Hy1sE2Q zttOjOr7FM|Ddk4cip`v2YhnH=cC$5NQ`{4OGfirlKkpeHj#T|FPl1h~lUOK1*7}|~ zSAu2bH~uGJK062@RLSEr0T~3c^sZ4^jMnY=tf}l?yNZ|@Xe<`bG6-WIOr-l_g;`yE zCB7{Z-o4{9nt5{jgJeg<0n-I z{ugI1vLFTi!R(j6p?KA-+X@21>kt|og5#|WEB{7&Hlce>fviw&+>uOK8-IO)V8f{) zV`%Q#Hu&CWHB#ovwY^8zBR2*dW-s;(B~o5Q^))+&d|;j7Oo7#)cpMcC;fLb%-eqQ6 zz5wsHSRO1lbLFPS1J)lDXG5<@?GlID-6|h%X+L39^?LX_kY}A0%y`swixIlEbLW#* zjkWkw_v?RU7hJqwW!08Q02sY$bv!euOCD^OTI1Rw`gWo){ZV}rt4mSX&m!Ll=Rv4w z?AiNDYiOlc))^4qlb^x!28mOLq5^znkM*E99Vf6HL*|O*PUrK}BW|yugafcqcXIxq zjzk&;er{ru(x6gou=Xz=Kg}6tM>eSj@OaZ;H4SF}8;PCgu}^{6r)OJ8l-MQpqzW;a zDrA#;8HlfyX2>m`xe1#0nfay_7qhu&sK5(_3=;+FEk`_DRnWNW+&(*pJ!^(#o;Vhz zDUkt-dgqY{>(om#9@CkMk?|rmuz6tWivf84kjenq@&f$SdM~=Pyjhn>vxV?9*^A1O z+oOYn_hJ|Kfa&DJlb??vb3>I{w*`YW#B>>w9R!I8ET1n@`=jALa}hl_%q?d}Pc_m{ z16!h~@l-`zs8O`LDMHCfTj^M9ah6r-T7hQ((bonJuTQaj-Qq0-KV+igw*a6$P#5$Q zi1q#Rm-Ci1QPJ%B!bH@9MrZ-E-rJSUn!u_Aa5?jC`Q+SFL52ch>0QH8{%|@pUtl*Q z<~=^Am7YX5;W<9A6ZkAvp6@AWq{i~;@l`~2lBVwE#txzZ;@uhf3@n?o^>>C3ZD*py z=^IUvMk=0GSM@26vzk@Ngu%0E0F_^gnHTEX_aptEAnO+6Km6@-mG>)M$@_*2nf^!byio*Z+pe1^v(jLw>?z067Ad5d^J zCx`{hwN5CSmuW95{`EZi*Y4pV#I=U6gDMt~C9lM-Cd;;;UB8? z_4}(?-!(;;2+}*>Ir#yuN+Uf9CW2%sg;ICG0TmXycUHRrjcI<5vRa);zub&hGJ-A{ z`z(n>*)PlSFe9!}E=3ByxEel@y-}a$({CN9rq>Tjy<&Zpi6e0XXNj`?hKTo+_XS@? z0a*cKGlgObxg6iO%Gg13jXoS0!QD#67Xij=!pAsoir1xoroF6O-_0_x@L6a3f`>e@ z8EI?e37jGL4x1JS9Dp&UBUDYZ72@*?JJOaJC7vy6A*l{4Wm4Xc-o=r+#yDS`yW!t| z(iw7>8Ds^mU>wg=!FyoZ9e#*}Wn@W*sTOLmwYRr}1YOn$+_oma+d?be6zjwRDPX`o zRuZqlZA%7-5GZ)9ZdY1Day2<5)rDDE!wyhzC0mUVJm_i>b1kJq{V*$^$H2WzKz+Ai$6&(>+Mx=ssXE)(vH&qTn`P z>}@dx73oz30joIB51l-2z`>1M_Q;5DVp9X>0r1d=LyB?SFYJ=SK<5U$gaiQRtq0&I zh$zy!tX#=Y0)Y{7j}a9T>rLyR!NbGboG9oHYE5IZ8%}M0_KBMj^y5|TRVw&;hLBIX zGh>*EgM;k3t2N8%8Wk{er7R02s@1D@^=*IM*dQ!c{1?EE15wX-d{k7XaB|{d<8P=F zisdrBPP8L(rIij`l4CI++{}JG0x=+9nk#zDzvvxdQ@LMTy(YKF2qZ;yg@QWZw~3J= z@=ST*f)X)}l_@-z7YP7%P|*!7>4-m_gj|5n`x2)U&?DEMo?iE<*}=WE^Z}0Bu35%g zc`ubA*%tF}S&6l90BRovJEq{aSR66vs4=81yMpvq!9>&E_nN9RpdQb~d0Hnnr?>T} z`iWk_?MoW|>t8f{7sUiPA%DldxCF4+6zt3kiqbInA8Sa+jd%87<^0pt-47) z*3hDF!^?9bzrElT9fkOJ$OTQ@QOY zF=M7plBp@^b$SmJT}vIxn95C;F07i)BUVeKJOuz}d;P-*!s>{Ze&~=N6f3a+nxNB*>y)R>ROGr5k6xRlm&X$7devM?} zhLN%@Z%!1tZkYTiTWIl1abE3rTInSz&@3JP@j4sSQMnApVtfFqJ)mjmCmlsA7LIh< zTb8bIfDHqxnc_mD1FYq8oXt0SRJv}c3VR@IQ$5h9P8y{KL$Cns5O9*Z0IWC=6}Lek zQNRS|xV!kg<>GiYkG)3^;K?`Yso$bS08M{Nw#7;xcn`pF3=QQy3)|QsMk=80KphG0 z{A3++Z86&5J(>5S=yHdf2UC!h6o~%=cFe~~w&14+lf#QA^I=I6<|IoGNi2r;ygmg< zFCvb2Upqqefint3l#l41Y1NvGfVOJ37mw3kmgs|@XV&hM)Y;HQzkaRP?4CA{A|j!t z49f8bd|X!ziMTK{ckTtH1lwfsKYX5fbLJ!E?9U%+aU2_FOO60E&7+c%ugH{Ph&RRhcLZ0kV_{20dCZ5KF-f3a#mpr_w821+yf%1Tj^Z` z_f`W^$o6M*uZ3e)6inYUS97m7yo}HjRRqJ@KXf>GnZZ1qJosxuB0^RtBW4B7{m$)T z@2*9`YjJS^(qeXCs2eM=Yj#+%jx*T}^mAgsRGFh1v2Uxhw;R9ZpY6RD2!nL$?5<#N z0AljuF7-gihxR-7we;rnZz!DBzbuRV(`aew?{K0AWdW#OBtqhtn}tCH@T0Zg@vRNM z7QD1+tkdi6=D}YQn|KO;wq_|vl%oN3Ww-MjT(Gk4i#IFtE5yP{O@qe(EK**sW=DH0 zvob!p*TWJPyF|XIPf|;rkMxx_pwl?}T8LMxCsqKgn66&EI#Ow=LPRTSm1=Keqj0bm zgp!`EvhKj6^KAvPo2Fa*L|R&ikrzOU#u857)RaIUVt;G082)QCyBq8t$O#z zv&#R)vxB2DvXo9#dXpJ>e&gBvZZMOFz+;YtWg8CdAhJWThz6op^F3j>jl|y@W{YFg z@>=XdLPCsJRXfy+S20g}H5UojN|Kd#yNrIL*Ws%HBMh}&F7aG$V~T(}`%7$vUYueg znB=1SN)W9=L_zJNfcFCAsEZpl_S430n$8(Lv6Ed}7Ozq=0ecN68kPCAL^ZTo_e5Km zfh!OI)P}zU>h9U%f+n?)!lfy}J&2sVPkfcs=e48oW(bhM69zkkoFOXdBE+UwCid56 z9b)Jmi2SMfCIlCTx0cZx2dCJ&&mp&Z?z%CDj>`_;PU+`Z>@6I6a!WW0c&NxgxoOYK z3~@2dQUgZK5 z*MM{v(-a`(%F&%iuh`jrpnKwmq;c+VsM`1;hzw$|w*TqD!e?aU=`+ulSF!1W3i+X3 z&{NG#3eoAI322U{(n~Etd-mKo9|1DU78(=_$O9o&VSnJB%1wdqKv!)uEW1O{)&4x2 zDMp|ck*QRi>|y&Nc9IZB(0P#@Aw--0&g{gIuipDwP+=8R3`ntYq6d-?=Db{@d7|)e zsMaV98$E|?btX_>K67@&4K^V2N@k0FMR;>xqsawiiD`Spf~kn*7lP)LqHr^xFPTB2 zzpW<+KQ(S6o`N(EZ7v-tn>Pq-S*DWSz1xukX%WC&4D8bhVI7urc~~>0dzg6b4#Yvh z#MB*Pc^mG8US_kwS3e~kzUWJb8>isSk^>$_SQ0n3Pzrg1%&!C9dYS-=c{A${_FB(svHQplXn{SlW zucfVs5|>?PaauTdwiCpsWMBK_bqTq;-xD=x<0HWL{^g;Xw>Zk4Jo`LnZm~CF77Xzz zCXD)DyuAfjl-v6EkD{U=V$!jdl9p}|QIPKLZicQQRJI@>AT2E*-4a8i(mB!$-Q5kt zF#k24efHibe&@f>?|R>t>(a?*o@bs}Ydve--~0Qyn}vaHyj!V>rGfc$s>$UhN4cM4 zO;Lb>4-MKz!N*S!DtMmd*E=>nTxMow$YB~?_x;UxN4cHJt+g#_%@0=ajgpz`y283Q z@NnB$FZdi#B;nY(5&U63FS-cR6ocLXpIIP4=4d6A?Z|!AI5?)TtQ693?y}u3`SgxP z-$oO{L|ACt@~CNZJsHQHL!PMgN`Bqqnq$N15?SzlhVOtowK`f#eY{Q93IPsTvyMnw zEN0!R+iYxXNl8iVacoqVE(Khg1iet!>rf~xJe&Yr_;w__=5e19ctD}|Zr^_T{MXqT zM}X^E)|Lkm8bp}|0rY6Ya|;M&KXu@Vf6;+s{+$lodVJ#_%&PdXhi`Rp(~>kuzWxyA z1*yQg0`4SW9B$IQ`!uVYgh44yGxB&!N4fO-Rerx+4k9)jXY_>+2u(bbD-Nc!E7GsE z-w+V?@x=;VAGvl@)Ua5O*Bg<{hoYi~pGz+8nJM#J@-z>z0P?41ozW2Cl#M#UtGi~w zPWwxC-^Jw`XPU&Rt6bN4Xglv;ovAlJ9If)g%MMFTlPJA5$b|kWvA$F!21_GizX|j1 z=+{munTRTZ!~3k*=4c5Z0$b|U-b+-s&ul23m2v?N*`C5g*gFrJ<99!<+fUcY0rM=j z;xvpkQG-OjTi8bZlO9~%djfb?@41w@$u7Sfa|yWY+G4%%)N}GlSw`Z3 zxM#`^sZ#zCduKdpdUav{4$x+e*VpU@L*eL6ju%yjqvzW@Zr&HJiD$QoQwJ)!$8*Wh zo;es{_6<-$+efhZp=UxN*(_4M<&ixL!lB7ZC(0%3mLbVgtFh1E{ub1jMb@J#$G{v0&u(s`<+;XXrwO z(j@&Gv6Sme56HyZ7@;dd#Nx}Z!IG)J)I`#}`{Osz)a9~d<8#ytNqv2N-;;6&-z4GK z0U^Zs<>kP{L^2Ssyk_|A%~hA}DGHD`2C@(oz?Ac`)?SC6X(Mt=(CcVJD(EgP80E9H zE39Rc1rAF$!5ccWQ+=fm*M@)%IKySNzdJ=3SsfQeURgXX1@h;w*e1d!fmG&mp6NK1 z#64iOZ9?p9Iaktg6KxILNZ`Ih} zO|zE>gWVMeIh-M&{5&CRX-RbqBiopEtg=H1zrvzG@C^4hmh=qH|I zk@Fa?G zPwyr~ca2v1;(*o3oSz`!od+Z>IT!Qq_X!JR{V zx10Fl3Q}bTv^TMK$b{}RZcBUsY#N=B?I$ANtiHDE-)B_Enw#l=`-=oVIlug-&Hc#KQ`U^6Y5PY?B-bs~{Ph>pv8fJ6gVoUr9GCv2lfDaXmgMX~O# z)KU8=q_T$^&<-4_6u5d5tCuVUPQ9;u{cJSNv5_bSrp>0yt&NE4SqRpWf>!fNF16*4 zFO(07#EB7hH?a`9WgI?>3SfsRz7h+@kt!gkb}tje-Mt&iAkC{`_&cDV9ex zOMFL}M@dv3@tZzJ3;aB&(s%@!??aFe)6vw(sXs#@yvdpLMF0rGJqrqr%U~f8E32aK z%;Ok7b^9E*^CNqPV-lIoQhZq!kf3r{kWs#-b2jtbl&RUarNbEQvVT<5Y*QHVyk!dJ za^3i0(XCwQCo|`eVCZ?__}*HX9{_8K@(Lyn9=i-i8#k>d3O-HZ7Gmsw&!eYn0erfQ zPT#HrC6sVgJG`_V+3;uE3E!;tG)e@>d+4{|A**b0Q)#@KgLXuHrw? z7;XM4jWIOMVDI`YuNK4;1R38LIyPn(5*LNtFxpm}BjAzP@7jc|TxNujBuM%%W_6 zP6C8QOq1*_AZ->=ftdFYLQ-Uq`h`6yZ6TxrM<(i9y5GNq?lUOYDMs2&u_}F>=3y~h z?4`X)fh=|O3V)r9aF`*8ElO?cKitpJ&ga15cY>B2Zh>=(mEBk_D}4z-eVZL|b;ihINVcnU z(JdVXo*xHx*yxlB#qdZgR?SxxBV+hQkXVoh9dNcTKhwTe1hcMa2v?X@cY>tT$CDuo z@-vHjwQhx;=TSn~%r4Nwv_m!hP24LPg?eG-%(($_-hLYGeZ zo*r%L$*d~3MA~wi9~fQ;mL=L~$S26cqv+{v)LG1@rz#2z$e#8lQ8L_d`qE)ge`S(K z_A_#+cz5GMKmGK9z(~e=%?%fQ?l5({z`5vw7QW(^B(a-(T%qQiI9aCc=JT4lLI}TP ze`KVmsr3j)-}wRl+Dxf6iT!@oEDwZqm24RHG@31IdPSf4R#ID1#Q=jQ^Xj}0a8!S+ zwZ9gEz1#qN~Af>WabBZ)>z9RTnlQhy#4?8eUm0QG>VN4^H>-8u)}$=MEW( zvzL#(6C0RXNzkXsADhNS7L_>;h}8et0UOA5>;3tz$`VfRQk!T4HMD303+RWe_6b_^es>t^x3Pf?!C`X>X5(3s3?-EkeCEd0znYaJlP66k{O? z?+Vkka3mk#W48Hq6Q#<2mWmk$Y8)Os;lU-0aC6O-^4mo+j@($|zP=neIfbQKKK16B zTbkqeF(9Mb15Ha~NIRw@k&X9|k$Z9f^*jl`kz(YgggkMx1$L`av9ikE5>TOF*^W~a zz^wUMT_<7Cx@-7wJam99sn#?}#Op_#IehVj$Iu=PSP#~%uXcefe3A>Z{!;?9)9s9F z@8^N^wzmWijdQ1+uLDG!odW&WT}1xx2h7n`ugtg0vk`)ur*0dnM_Z$CFbV5U39sh* z>9jp(rjYo;F=80*mtx#a2pX*prDzv}eBMh<#5I*R{c!LfD>Cx(B}3A!+LZ zBueCx&hCg;o(5F3?|^sO+y8ay!A!EY++%~@Krw%bM8Smx6O)j69I89~cK6*IHiCTO ztw&Aac4N&g*n!#&6Q{mUBJO!PZu@ak_SX4@w-+PtoVtppn`A^ziY>tl)-l- z{==#llKrP1CaG+Ybn}RHo;zceOlfwtP8O%QcvsHOF_=^)19^bCH2Xdyb(4IAt-}qw z?QpqE%wS+5p9LsxpOxjr?*JJ#cH_o`0$#Bj<|Z*Ez-MOft)Un9rb4Z|04H=$=$g-I z$>=!fEN*raa`|f%mIk$W%ks&b&=h!6>u`WXh9E~-Q=Dv`@P|lzrun1T)ds&!C%(p8 zNu95!VeztP_co=5LeXf*I)RzCjOdo+)cjzqI0MNA9>~+nEH;1ylv79qCM4$`0-`8k zyGehRZ^&P;oJL>-MlIuMoSn_{OBM>ryf*fa!j;A7UxR3!QicS60*{^a?Dw};lQrCq zjse!=Ta&f9y44&Yt@bm>&6%k4i~_kM0&W{GcjsC#i8*Av_E!v#HV|CagYU*FZ1!8p zAUjP2qED>)X{6&=cSICH1-limAW71|VR>dadBUuS(J zJEHli|KvzL0GXusUp4ipja|scd0p8#l+t2v?bF4k{AR8I4$(%0+^t}7>;iB{d`Z5(d znZSsG?n6YeW<7a!c=GIEA19V>qnH2a=pgF8|F!M25{GXbSZ>=>3P7E4aCes*v_IZL zUBL;YO_(Y*!SlWFWF46ci8V61vxLt_f>>gBYU^>^QRCS!bO|dcol-XSzR#iJnF15j zM?}v_!)6^}MLLgE%RIO11wc=@@=DKdo7y?HyQ;R9)*80H?E^lTE7{gq*rfNQPx9NBXScg+Q>O{Y6 z6JzDa7GzpaGGeI~0_y6efbEbNKvN||3p;qg?*LKoLE}V5l_zmnB2W`QnYP?LpM^a3 zcrhKmG#onUdh28Dpw9Coyrs^!ipE=Q4m;r#L0$;mdSdyV-Tl^SEGY*4#z*u#6f?f( z7Bt*U|3)VKxHYfl%~&R2h>!IzDxqAG1&HMAZubA`InDaS?=GAn^VkQ3C5aeE@=Pbt zFO-9E1;R%g{Y0ba6_$Xka1PSJY{x4@p~qW&b)L>Z)Y1X+L^}wMyo_U|P|1@020$Zz z7pFMDQ#S^KD5yryURmCmZDQ7`d=KQZ{nhN$ND&_|z(fqs&Zc)>?!Ed6Sh2j(sN;>v z+PLC|vtUYLug{t(_FF(s^7VK_3SgixN#FLW>e{=c_m5tZ5v7=-QWM|R-RlU(?$T^P zYAh+}b%Q}Wiuc46cr&GUGH=gM1NqAI_(_jwZ6MP_F@g~#VD^l{cF&iW)2eh7F`*-9 zW7uz^Lh2NK3NN2B?5K+j7aDwTm1|V0tvtN%ZO0*a&z)uB#C@W|!ImSD(A7@Q*>F7} z%B8-MMsGT3^a1O>LzWL|{~>zp2`b{*hl=+2Ch)nG_GlR*|MpYzarBS03@&?Bf>#ou zYqJZ{K|toGgC;F~=ny93^`|8K1#(62VH9%Sgl(wqngtJq_lCEP`SQ{;+4d$AV_8c+ zx1u1t+Er`y7P||VFQLerg0SX&73!Zl80EJAcL$#ZO%QH2cB&(g`9YU2qyFd_KG8$! zXT=|eXm>^Seo{xP@LrL7PE->*CMz_OG#3nsa+=Oz^=HW>Zg|$e??#k4ZSFPspuH5Y z#FvSpmn#>bG5jUo$N{pf%dC{)w(~O%K*>ACCUUnhNyLCjC#ynLhUup{rdOkGoeS9A z0OYnP(UrL9ex%6LX(i#)zHN&+<Ng`|m&k#0QXE2>g=_YI*l9;3)2tFc|%lCm%os1S||Ie{ZR$t0O7^x?wY1AO!+=4z8}WzzI=zoHBcHFxL{| ze6*nj#@!ZBe*&06GgWhyy$|{%uUx%KOA-BmLA&NUFx3vSp)Q3oRszzP`9iyi-aM{Q z2vDSyV8-_nJYclUG)W2)hgW|Ax9*)>pH~GpKkgu4vL{wtK;kcPDDPnUP5p|#F+eq* zRTEBx<3{ymZM<;dbQCcTIJ1rt2YVSZ8T!DRAG4=#mU8io$s7V{ON13`I`NzK^^6n!fj1Oix`-x&qC~*ABF?^WC1+0LQ?-0WLoV#wbzpO(_0y8ME<@B zCu}Z-v({1Hjez&r8(Gllaj9$Dnp_uBntC)l!vED=2|d2V=e5E|)T_S`%IoaBVAwe+ zf6Uh-$de{z(=_8Jc?*b7lHbqepr)^8ttGynmqCg5;K{te0PJzQ#3*IAB4ngHORb(D zbUkwmIqX+Elutt|f&^4$4C8rS<0fno6cdO7^%=ehIv6-*Mljd-4#tL2;EO&v+7fvb-Is|D#=XhEjuOum{d$|sjYLO-z?dzGZmVXtjMAO<*N+2%r9JVfAKzIRxX1R_ z>p(@$e>~AdrwHS;#~^2q;PGAlGVoHA|C?t!cEeX+-6ZMX7n{GP+h|YmVk7aJM*G5U ziDYb)B#-?y1G&MiP{tRz{p&tU-22o^`fHT;)?c*z8ekHKnq}|n?Roq0$$*LRMrh#p z;n6lz`$WD?aLaL>h$UJCUx%#KTflARiv5l7V?dV`c48*LyXCh~84+j)#IY8TR|N7S zK#oys#XFl;Hwa+|{6i2n$q%>dyhWtL7-XxFm=XCTgl`#fFhV%?`OBN$!w>nU9lH+G z@QvB-!w=2Ki>PQ1*j-8WZ91MY0oZc@O8eLv34 z@IUBj6%$WaV<(PfqL~8X6wEO5U_dP(;mEXDa2F?;q+cyX=)14AMAr?9FO%G7RDJj9 z(=TA2ga5TBkv9m${jG=cm^BTnAO{N_QAwhHDbLINlj z%s}2YFj_8W2J>S9+G;ot;EVzWKTq+PG~laZJ^tw@tg_qCK6(0l=JjC-u}UWXTQ zhtm4YgieU-%{a_nCB0y_gC5^!y%Z>6SW&y?Q@IAoDsAYizW~Q7pr=yh>v}qW0Qrlo zDYdfJB_6}d^RHUS)a_>L&38}Z7&?0rVNu=a;llCg$0i8%ZIm|ns^27UWb?a%(?nSpr2f;6T<^1-|BhLA0kWetOTX|uy3%ik zB?z5&sr7#G4qr;BNZI;eV30qWXs+GZK5<#t6*r<~Nca09ylA zz|F0m4gQesyJh^kA}4H!z3M1_7*pjfw>p$Qt$fj>O+Ov9uWpd)_+g{(3Ag*Bf(*sO zM_UwvVLn?)qn=g%^}?&x(0kQpfl_2T%Yi14&xP9YNDGziWp4z~%Vq{*Zi(n2z6g8( zq*rXka@h!a%I%O?hRaVUvnp=r+Ev9ocIa_iJ0)#kTRR;#TDKO5fTAt`h<|mZ-CzX9 z!;bwdqgRJt^v(F79Ii>&A`ZJVBuUc_^fs&-8{`|0PgCgIC=ti0S*lH)re*7r^BQ=ABuuFDCsr{sY*TIU|@zx}R zejVS@(Gd{C#y?y14lrw$yaKB%AhflikjGYi=~uyGiwjKY>~tEVIx84UZIRE?A8m7F zp*`m7PHilHWK|luAa95_8Z9h5#Aq1ERz2HkL%!K!B^V?2`Pqjde!Qrq(B;91fdi|< z8<)y1+S(xjC6@EHC8e|Q7AAh5jp_R!3(i&x7HVC=SmrdMoc<_-c*^~~;}nRuVW3!8 zCf5`UH{7WmW!GQM{M}Lq;(fS)2Gj;n|K1`$N-jFp80Ct^^g`=Pe!2&9cPcXq*DF;j z)Xgr&NS*?Alf(h^geDtA-qJuY;u5i-=_B9iTf7TDO@8h|_7M_Ohxuhb`>c<)HPNr) zQ@wdoCXob=n`8La+}7gZ1mpb+^#ZZC)-yk@m-+3Vu@GLIGdZiD%K{)gpxGObpCuD^ z>}nP2S40T7TJOPUdjL&;A;UhEczJWQ`Z8QPK=K~)6hBRC|5z$jgo0jS6I@kVyxHA2 zY)0&})C==A5Vf(RABjaMc*2-8inJalF5f5XnluxQDq3GQwCO@Mj@%)0dd=mkbH{m> zi(T@9Zs|m112^^&>J!zwkdVbGsrITXryWG_-brN=6 z_i~;a<=J{J(O3_K-!1_z3h~)CR_v5psBS(||<1?ooE} zAnLF}9rym)@I#>nVOF}>A!>^Or!7NZPvk#YH~+4nmp;}ecU|CsDtmY{W4J_}@3VqT z6cs+~zCk0o{L^JAta5zf*ZYb5FQXo^)Vuq_4g9lqw`2X7X#rswx20ZMkv z5g8uy9PLh+T|`mkzCoj;1B)s>#rd4C9bfg4*cdV~v$isLdZkMeSPbz%mil>(od~cP zdhhODnXg0GWc7V(`!TSxZWMKT@V9bH7#Z!3UtKD1ODemH1d zc%9!hVhok&w3~|NtF&jUmR`u7gi}SaI$sMOWE9`LXpr4w_ZBtnS$t+rU~w_-+5J6U zs20q(8_0IC?-9Ol8Xk^~3DIx{(we|6TR2eG0rDEhk43wq1QPh<@Akv+Kn1pgY4&h{ zS(u-hc?HNv-u>3smz7VWl9)@kLo|csCZYly;#4!A-C8Gc7$CQA)AV~iV>XJYYoJ&= zqLlYhP<$z+ChbxV2&AqH+G{o66Z@al#FT)CQHz1gwN4j#B#TN-7+D1B-ZfohC)L9y zQs0x`-SrSG80yn6!hHAadW&nIj>C?EiPg5X<=^@rejM6#+yoJKEmLBFwny9fzZd-i z1-;f3B9ru|WiEb4nEp?Y+dm^T9ZO@wW@6HR|C~pEt#}wP^Zd1~{wHqisHTkMjI;_5W^PwN>DY1^%@!_D^cygAT()OdUN{+oWqhy!6x<`T(?6bFfmp4C6~3 zVjUX7yqMeq0}orG9X-1+ua12Ls}@70eAY1x&Gt)~3l?D|y})FF>WMFHVcn08=JYYTSY~ zT5feOp3@==EaLAoDE|tgwY1fBAc&<5>K@|WfBZC_!_0EHfCQjQ;N%LSq}-z*(e}&2 z5l839#-a1|zrug%MMh zZvH@fd)N?&a2s`15dZ=oU$<2F==9X=G@N;iFY)cVMMNumsMh|I?0g3FFbCLZ48&&zHi3Aik*J82XD(kT)i&AgQLchooyljx)Z(_nKay zn|!HmiezJ7y(T$dIKNG{N{MDa68dN5>!6986DUlk=o`$qNnPLupoIGtT;IwN8t+$E z3|cDo@NKT2&TF~4@ZVc{&#mx`?HhS23e?{-0&}8PKS4J8&rkbc-6>rIbt@OQe&kum zfFm^mfY|6_{addlPMz6J4prwH8^ciY10aa5WnNY!hj4ME06ds@-s-j-#S9_5%I;QC z2i8KWsQqP8{5Eh`6us*&)obTf(F`7dm$ROE_bO;F;ZRIrUe#eMvCsvRnnLf*c1jz4R!v7F4O#REn=zb@PPBfqcU3QCfn%^~t_ z8HqHDIyLKopMP1hh~3od9yO3iWGjtR1%jM8oUvTkIpl*qPI-!XPA9oI^5E& zv?lS@W`Dc7?z@!zK;^MowJNUU#hgBu1qQ`@Hge;>?b~AGrSI$Lz!SSfFldYBiFwcvD8}WX9%;{ zxXu7E!)0Ug+N;*WY3xsL-Eq8lwiQ4ct&xdI6o-^>;D|7~bLv4yG8>Ux9;V(~F|p9r zJk2;hC7Rv9no?1y4Dc#u zzts@L+{nRWTSqV@;N}O4Hl}R7(u`*ZTi&k<_S*8-KX&#x(m+>+{T2ZbSw~%sgX1`Y zjQz6ZeHym1#(!%ibDEtFaVZ)I?RBl`tI#Ldl9)1E&wDz*2hxWbGz!VT5v8J@X*hkU zs92mY^&uWLe{5&tHkT|hg)z5DC0=7$cLXa6ZLf;?kyV-1quhtfytoUQ!$@wcWz<7# z9fH|;wwpv*DdpXMZd7T0Aqv-PZrkor{%)LGeibbxbOVI+4yeWh6@b4@uSb5+dO>cg ztsq1_yZ{i&*3;{c1HB^+^@M(u@8cv1x=xvD)r+pQ1&UDZroko25zuHBCRl=K2azFg zL4YCmrX7+Y+1l+JVC@8n5FKg{E)D}*;r?2CKhS{Ac+l8My(+5z3Jw@6Y4 zs$lQ~CJEp-rx0}e?6Er+&8n9WO2&KnHVKIoCJR*g^L6kLEOh%%#<*>UG3In|E!sIe zTm*$(JCYpxF`UrFpPW$H-#MW%fP1=|+r9RR8_V{>2G6Wc8v8cLew>|@ta3lrPhXs> zcEtfP3qf!NdB}R`mYuIZ5(2=qSbU)39)L8>Z7kUWPhL+v0EjzyOeZAnMprJL7QsWNmUqsN|B#wW0 z{4)IjTV@EjIM2?18uzyYbzw+m#7!BwJqRRVbA{^gZmO(3?Iz( z|19n&?XZz=+@BS!V5UyXcN8P%uz|EVo_*fdP^;w5UoyEfF9NFn(G#S8A8O*h`o+^t z-<7eemXgw9l8ZK3QeA+Me0qfiIK5 z41vt}&bvReHZFquJ`)MGETQn*W%YkDQ2rXn+S`KY1{a(i%syY>O2UVWSH^U%}f?7dBt=pkoAzd$Fnj zsMPy(_B9{PV;}(zzfKIqdl=UwJ62Uge~~s^@&X&=_+I^*n~|Nnq;eG?%$ydEKD`Wj zV+vn2&tle}SWjt8ti^kHV~?PoJYbx#?XZUlYR;u7Y3EWGzbQsW#!j$8tsk?(_M@n7r??yT{@pGx(gwQszguU$X^3! z+h6G>rZFO!sezlT-vacZSYiRIR?v0s^LIhl>z}E|6<}3W)hZSi5dp2le(Qc@XtfCP z#*n>c)DT(+z4xu*a~xt?PdF*cqi|JV2Rw~`!?z0ba#>9WK8rAvO_)nckdXoJWVqf0 zm2jiyi6=<zd z{l0qO6LmC~_}}E1AcRbRdhQhJUKgCy|`QN!VF7_DN2UB1j%0zCbBTYcRA-6(UnE9x)B) zLUfFcjWw$W6&DS*8sB(doig0YTLtkH40yD;SrbAKn(aBc?-vccFqw?^vwcwE?}FdY zwY5w;od3AthSM;XihT*76(wX(qs=(|s8>Ku!Y1~79C{WX$-{+gwk)j!8oCOM_6L;6 z)8l48Ae0qg$aZt{9S6IdSWTMBg;3Z+l)5-GdHlzyWx<##Qr{RrPfU-t=%5)N^qNMN z*1PLJ@Wfln?D|1KGU%0)DK7QEny27fRl_}yUKH$cFdC;=cw9duD9Jom@puK06N55k z;^;{4Eh_d5@|HoDmjXaku*KF1pDRuj~k5(Jb- z*cI3n&~a{4-nSp4`xp08{jO|Rqu;T}xH=?TI=M49@6-Hv8hhwmn+Lzw4&N64gvS%y zXMjBXj7kgVr}=8vK^WuIWImaF5aymZ)U=-5=>j?OJK7R#$U=tCp9lushMKlNRe}yp z>D5js5eqA+$$`%q<2T_@kVm9X?U2Qh|F|3F-QigG-3qRph`<>l3fgLI17 zl>K`8RJicI@7A%m0>MD}%8I4j`5JU!J=Hfci^;E{4(j{Nb9^5%QTdv*{N!n*%h`&S z*^&3Kb9>K#+C%svofJ^|&5=Q+p{EuH=^wr-QXrtR?)Fm=G@Da38lHH|X`iBA{(3E- zV`v`X8R9R%?dLnyEA>7CPqNTL>7*_AHS-h^jJCNrQj&$`NToNCG zC}~6uTG@nkAvBPfR~Z| z7ShE|LtT&0q{`jwWOZTMG|dfY-c*8o8nYSy#mTG_L}tc=^F$;I{JQ@(vb!gQF06p#k9bY7vusF_z<))Svpd)CA| z$)mWIONge{mu8K}aP%v>n^#)Ab>~O7(W_LZh)( zp38Mo`_oJ+cqaSohhQAd%fd0)L7o*T$SfB$;Mp`sl4noFgu z@>dy}Q=K9prDp;ctJTH%sdVB|PwN}Ysk-XRmoJyQZE6pcgNw`>5Wn(Nb0Y~^v}ro{ z)ZqZ#8w~~uwIW?DQS^Bk%{+@vTR2r5O$>{Udae65Pv`*Vas@Wr3Y|m3ddUTuiplkz z;A=&uVI8Wdraau8ag$-XuaI!-v$L0xd4q)o)V1LaF7fiYNq_;scLi9Q7ni*mw#$xVkan z8p|XoFTKXabL+i+jt5v_L8o10I;Ovi+pqaH`&*py7Ud?B8HoG=1jkzd zcT=sKfCka|y|f5VR*ThaYrrbwx#W8(?{K1Ydxt5^C-T5*+D$r{wIa)xyXUS^W31Y~ zdVZmTWX0iXPBIxvEx&XZ=k=SG{YDoko2F1BO|H5L3{gvga(e&z2Q$VgKQi)>JK&}v|g)1&nPA zVVD!n%wOlSw4ybDwD#8Q*@#^;v6c;Pctt}DaMGNPRJI&DoeU*!#viU520ELlGzR2WWjFItzfPDB{w13E^Ss%Vs&RLBg;69M(y;|mm}M$d`W_P+jcM6 z^szONCDH{pGs3>mg?Sqxa}huMBmq5ZA5O?;^RNr4>{}`FD?bdz6Bo`Iftf9I|A^W~ zy4_@YT3VGcjftrE;{(4}zeX-VS7cK~^gwWEZ30neEZ{KnG=@QCNtA^Nz%$PP9)AcF zk^rk}ap0?FRQ~)9eb|cd?rTSsuIA*%>v{r#uvf&*CwjVz;K-n02)kw7w1{* z9sni9?Y^Z8rv9=7RHTi!!%4ZNJ@=YXCo3nW?|4>fAF6P>^;ynSPsG^|g5u~yMG9oe z!fx`He4*uT9bWhe98d93%WGSk*F!h!))jSe{Wb`$&34ygn^;E@z5r$c&x z9OdWx@(lM&T#MZxlT1=;$F2(ebnb%$GVkXplZCvcGmr|3bj$A(YCPWDWWVKX=jiM=1XnpLh@z`x_lHqAU_o-#b~1ZX=SZ8j?c~RCKD&U!LY4h= zLp~|Kc3xL@;b4yb2K|+>;1x^%tedC$^Ms+EUK``L*GFMntEG?#w9sTdMcN%W1u}L+ z>tv#|_{|yDb}`N|Wscf0VU7327jyfQRGQVe>ii0~T`!wVlCBgMq-v2D3CnoBB2aG5 zvPQ~^cAa^96m_Uf*nZsbr(5rmLdAS%cza|&UM#EtJH9H)Jlwu2ekfKphFe2e@Gw~) z#W!b_PsgNFWGfxRnCZ)3rJ4Z^AGjb&`PB?RcI=ooR}*o3-<$e5@7)d-cgUA|0|9rf z@sW)m6NRD-VAP1h@v|VEnPkX}l2&C+yMaxo!(IzAZ^^iu&oi84?TD&(W8qN&6JOlz9#-2*szuJ^HOP6syO=kuE|lJ z*SCs>LMI2RL{|sYEmD!p4d?cse2-F#-w}y~*x6LtTnxaC`<+u;x(0I$3 z-aj1sv>hlr1Pf_k*TXgtao4g#mJcI9c5xe|c$fw8>9xw4O#_Wu_WsINfjl9% z2{crjdLgJScqQM9eE;aZ_+fe*d*AS_Z+XfH`V0CMP2~d}-ymy?O{{|MzTR(R55G#M zA0DL~(^w%ZdcfP#x7>D0-L4Zx*e}uLpHIS&I(M-!f3NVv?Cqh;&Oda zXN-!UUgh?j?k{tD9awHo)$5ROnybEi+0GOv^Y>%JLp1s|g2h^962CJeK;K!9mFEJO ziQTX{$jeg@-A)2<(58Vy_^9u`F{%WDBa%ayc$pxh6=P)5_#;DUthkuFf;SXalW+!fjG_Vst5@R@;tmQ^74M3*>0uVb@c~# zD9ko*8`2)RK|s}x$+l%p&=&Vt&!)FT<*g~(>M}J%A}QOR>wssa&9*H!Zx=A0u{1uf zD09P7U$R^_#BAFKS?9gTt~408-Mr1bCZA6VTIQpEwo&7lMx>jc%;le7xkT)bwq^3$ z84L+wubYGowDNlW_QWVL?%&!f7Ei#NTR*pZ6`J;YQzpJo^7A=OO8-Y~O#g8sqnm$g z=7yfvY;Zo5{}BIAZT(Nj)2u1@E6rQV-;aV)fM=m$HljkjBu|oEp@8Cz8j11Ll=YFp z9WhKdtqXB02WN57-6a6?7Tao(67W!k)rS?+wMQtYLGM&wjA2g3yjmL&h}q_*7ql2^ zJT*6Q>74iPziSEm-|zkWg{AQR-iK^&Uj0w~^=9zRpJ#-bwe_~i=IzM)|2IyG(f{wT z@jmTug9URqyUW~z|N7Vi#3JVZ^Hxs+{?-~wgj#Pp`pkW`Ka*E`3W#-C>?W-*BLncsvUca&+Qg$FMaS*-+SSkqLc5g0 zy0^}42s(pVp)=1e^1_Mwm-UivoN~pxVrnc19t~)*oyx@{Pq_gb9&ZCYlzIHcW__hx zHQv$}57y!gbWX~d58SD6wC3q4-f~cx9C&Mm)A%z~gGKdO_!^0g@49@Ci;!hFhp99q zLH&z2JIlC`LcSYw|As-97V`x!_s+V$Hq5DZ-s}d(GJSv( zeP7n2(R8-5QH^yqFe#XOJ0pB;ZRVjU1z(kv^O9_-LpdbNWk@-p(IkxU6s`iwMVa)t z%WmbQ4P3JU6B#+3{rZVA(^#6!t`G82v7sYpWj2F8gUeY*3`xqC2X)2Ven{IM1cwZ$ zJFQTn%WSv9dru93?YS)x9b;*l-R%$@hMApfb_i4mZeyHiFAw%L_mOW=Ixe$gVr8pl zU2#9MD41NhH>%c#kEPx@Oly`hwj82{tFBbN+r zu6{NXT(;?3LXaW{9%o9$(WQO&WogN~KQd^C1}j0)wG7r!lOBawp?EL!4}}4@iyVkX zczDHD+c}543J>~IM`8nSA(GHX$7*Q`adsMRb|Y5O`>|TZ=cTO^seROPj@1ZV>5?Fr zsm@sWb4~k&Wfh&u$ET*?fLVPJx)3SG$&1dx+`i}{lACEaFv!iL<%YD`vK*x5o1;JM z|FAN!PDAU;L0OkwNcyekzBp>TAMv_EwApQV0$J)fkF*(%@ufK@|CrD zi>@YQWy-}#7=*3n+uNP3W-zi0W;ewV!WUgt^OWQfPNr(fUm8etgz{#l(-Fa{ThetW`Eu)X*gfQys}Y1#-z*6|URzziO-6W<223$eaIkEAq1> z0hQHJRrT3)JCzBG`)YXCV9gr+nqqzwZVYoy|By88OOe>&Phqeu1#+{^C(Kzj?q-YK zr(vB$#hDG0jr|{QfYf38fdIQa73w1*U^%%wRNwUr>Wgt^x^Ly$#K6m!vZn{Vo|4T&DK>_DoY+u&mI+=Senk)E8dMMF zEeDWv?x{Ibu3kCr$&@wseCYvjNe|*hQR25O#+^Sb&oYI6u5nS9S7}iGvV8}A4+@34 zk`GBykKa^*k?N_j_quLpAiVWyaBc*;E2PHj~&#ofe4xDU2AzVf*BrW$pxvjNMCiR$dw2jkYK-D+pH zA9iKVG62CV1v$q$s+y;#q(tzDB}Lr3bP)7`7FU9)Yxi9)-U1s?u0$v)qkdf#sH<2o zl&>KZ2^PYiK|PpUfHB6*#xEO57_i4 z4$i;=*}Ryg(5WX_8)lqAv$`-lAe|@@nl#A~UjgK%&x2MfnCButyE5_QNf!o3ewHC( zUGHqkXG4*R;9Ivt4%P9VqnGlA3JSQphGinds6;Z$SNq#rdJqMnA&F)EpQQ@t14D&5 zhM9GWtt(Ov`Br(;Yw1GI#n{>5Q!2~URCZdmdSWB~v{JlH_F8;VBPyU^1gg?InP&AQ z&97I~HDOS|xBVj;(lwInwb{w0XRo>-4wh(aE-HMqamM;%LP|Nv*WteU<&4SsCsES_j8NeXZF*I)j0(5w0cs~?d>gzSSh`-jje7LZC z&rYvi?}0bt$BNt;6@9W;NF>dsW~~Y>BViN`05+~RzmD=c*on|W1}YJ_a(&et_1QZK z>P;46(+D3;O=V%!Dlh5Jma)Nf0QKZG?S^I#5kc>rDu6L#f_1ZkLlN=NefZ6&G|QmY zN!%|wEv5?3l|`P6T3L+JKr`tVfC@ihv@ZI!74 zInPw5vGNIp$Xy}D^HtB8@3|qk1Pu&QH7-Yyk%F{wCQfa?%FS>uFePa4rgR}Zwm9L{ zAkt~)y)~h6UhO>Hft_ufjHKych=~Gg+Wt2TAE`5oow_AQxG^djPUa#Hy@cZ3B(S#Y(=vx;#=qGZ+8!O*fGLLCtes}$tQ(i-E0e~h$gjf@Iv$q z*^*s?&s@IRIHC2z0$U6#s*J7vZ3xj|v7qlT+c=Tc^J$12(RolzwuL!ZE;b#UwI2TB z=~07TKVI%kR;hMg{ISHsRBnf4+dGo4gT;er`Qw9XI{~i8szsDbZ-q46E#8XgZG#X2 z2xl6sa%Lelx)h>VD>@qucc#?i_1eeP9 zZ)s|=6$I5Pqe23KC46qnHg>ngEj3{ z%&c}=>Mbg6q)OM*IUXG>=0~f2F}>x*t8r^65232Bzcsc1lg*SF>IcE~LJI9SP7Wm_ zAE+7z^AL@Xccf?Xr?EzF2bvyr8sxn?8(Pl{j3D6l-hHemOqvHo#vv&rXutAZ{NgDWe63gv)6r_=agzZzE^Ec zt8XuON>W_&>isrY(3s-xKz=cF(&_WgtL-Hx%X%!y6HP$-I)b&&I4>{xU5sO~7U4 z1DJQ^b;oluF)~U=Mn8Iit0D+4r~@|OKVcBP$n3Hk%!wE-HYf(5Et9Tz-U@k?`M;R2#FzDd5cqaN)f{eteF0<@#)Y@zQqSIWLko$=o44Gki2kPB ztS1kA)}zKO7rJ=hDw+--CxlazUvWY|qH!6d9==ZN+?YMmCF2F*P{wsZt%aB#@h%wa zk2CE2XwV~Ncza^XZ0N2|Usw8i-Q-@6h(hdZCGPx4K}u*LL`Ayv08)c=5;}xXlYK|Wnc43<-!sp*kNt-p5J*T?R@Peg zbzbN1A{jV}F?D=CeDo-y8DnqgsaYAHv;!R-s8f`D_R*|jMXVeQ#Dan9G_#Z7&HGQj zN@JHI&p9a0YT?gwj=JBKI)W91RBx@bL}u^28AN*rI5UU%yx#kCrnYE55n-glOb{tL zn-o^&yX-h-p;>7pn`BC9Kg<-0T{M1Bu!A|wbhKw~kB`}jRLG?$hflF*ATRc~IR<^) zSNGY0$qCTDFGpscfElGd-WA|!5M6WJD05!#>+2NHTli&Mk!uiGF0uE0b?nH|t3#n6 zh4&Qt^4Fn7WHnR98$?KMZ2kE55Ngq` z3>Yn&t5t-OC{Q;#kdWb`N1UJx&4Pbcq!$Ufl;Rcl>~r-;1kR1ue!OW?nSAI_KRAU! z(<@hUl*sah1@`P7#NF7STzGb&P0aRPw2EK)*n3U!73(~(iw%}LWd%kdG#D8fot0y6 zDh9H4n$C#uy5>5;MJ+R|f14;Ed1Ti*azeDhU|Tnlag+Eh0?xx!QTfzb(UPIkki>i> zPw9%g4L&FJh$S_W$IE=}^0BA$Z|aSuoUv&n*a^Y`LNGULw$XsJ0IWQ;FMl9?S}53f zRwYUx6XS7yoI`LXX}8uQLI5ht7`-qbuT|wd)0u%Q)aO~0bldo1VBY+dmy*AzJpEP` zFsR(0aDU*iDO=wMT2a+eZl07bm@uWMb|Dg=9<@Dz75Uy{cU&xmqCGOgCXMIL7nouc zYt=&b`>~1`-2VOBU*yZFd^BGp>+IPgWNX3eqM8{<7MOdSv}J#jL1GDpzSGMKnIh_T zzWT{bBsfimk(A)Obg@duc|hh%-t|~8c7&P>x&Wdi(pI8%=*MM)w8+BvkR;n*R9<$F z9+yB>@}Mym#1Z#ot_!P%>g|niN|f9CjvCnd&p5x_zRDLoIlC?-YEye%OSB{=Tqff+ z_8InYv`~89jD1D_LadqP6nWSyc`yKaa;%~;zl{qgx4J@(ekjYt;pNSB7m&Z&SV`@x zO0;wx1`R&f*`kH|_>dX-wfOzJ8`;w?GqvZ7u2J^N$2_*8?Q$)q;B!GQ9J2 zjoSR5*j0=fc=U`YWA^WbV6>Z{Elsz`L=K#m^np#KTkE?u?lyqiT@CW}J-+d#2vac+ z-C{FG3yfJRD$3)V63xKkaJx-g#c^VmYQ~`6-Pyc963~%-_{)b}=!^HpaXr z;^vz-T5R2W22@a+fq@k(FC=X{tS5WvMN>1szq|c_nKuf$l#(Rqm@=##?7C-@{DN}D zL7`p+m!*NTD&W&dY`XWdEBogO*By&-#CU7Nu_4`33-N?&Rkz+Sog*7$)n+`UkijXr%n0{NnrcKR5g2>3wIB>kTg|_57Kku}^a1~|AhNBM z&T-6}C~Os0!Sf3XXvEw>V?civw#&Kz6#?(B5-B>rKbe1jSramGaWu5^rEo{$Hu_=5 z%?#x@Wk48n^-KSaU^#9h#P2YKa`Z0@c|g-{sJLyFMX~kfSueaBZ;Muwf!1M4HaG^7 zn;5i+1LOgntzGwma1UOy6qn`YQJXK7h1!|U-6=YT%yaOqx=P^$!qxRqx!m{%ptg-hNaN3m_yR&Yzg zt0>HGYEc}Ntj1?1cp#Le(SFBLJ==NID{a+aMthm`TZT*miY+JEs_#{Dg!4v#y+3q^ zyLY-iE%m6PPHx|m@tgT!NpC}LmNio?^vy4toa-&A~&g6rSA!8z!y z8IJeXG=y%y3k2{!C3a`pYAsw1E^S>buH(mhtLz4WDK^)U)o*QG_MKKthq2y}d;vHL zNiD1l<+-UySdB$eQA-L+zgL_W%MEf;Z8~VL5NYWyf+lup7kHON@{k?nH7n{I4X>oZ zuHI%}A9|AFT;QS2EuH zoOGaH?p1_1!*A+=^WcKcZcIuH(!aSf;WpFG8N#teTx`jZJF#>x@6g$n*RGBCwzIreJep?t(;SD3$xx?oC+$oL=cfM2$F8( z2idxF^qyg4F1j|^xqbF`i&!HDfB#N8vS>sG@`q}+uv5)c>fza zaoqCY8p9?3frJ3|__pmMD|WJ&zCEd**l+&>*8KCm3I%+E^*{27KS={{DQ%VhjU4^c zMmg%<$9NW!67awI)nEHu!yo%43+oBMD^_0p1)Tl~d;Nhh^#AYnn4?$zizo6IZ@cm4 z8w3VB|K*F$HL3sj^go@wc=0aCn(76^67!DpDrc)FNP}q;@pMoLCXZbNm!9;}n>=;X z>;MBp+-N^&OY!pZYQA?_|H?M9h)!0}JC=JjUZJZj?I$ebeErv~R-&uuH94nvPx!1whXbk?z`c#C6%`QiV8xjJCLAVMEBz>*b_W4{a60K(UGc_476*H zQNduXCRhkT=K^_;^TbG+zv}p?cWqLzPRWF4Ahf+V>Qp>qPfn?_iNJ*pk^d>ybe!=ma2_@tP)4AT@oUjCWD_z zs%gZXEw~`UmB&k66Zcxt2ctw9=KZ!tTk|+$_H@w><~?PHjx<`;%@M@hNBg587ZZbb z-CyrxbnJ{C!DTP|Y)#l*z4yq2Q?^QxwUARR&ZOM;ko{osO;}xMo`YY~^Is)z9HUyK z3iR9O9u$%>kU1H2TF(6?BiBg2u}@!ilh1*1yS1s#MCp}Ab>l;_Y%{ywWLu)eCog6p zy{4yc8gMtEfy6i=9Wn16N^Vcpjr=Vy<(YmMF0A+S5fx~vyFsa!+>BpNPUB3@j>i5I z7Y8?^at3__N_|RN7WdSbd{^%0ZzUFBq24>5QG=p-^+@&{yGC}Yj`{gT=G zo`1c79!52POWj(VNRp%VG}bB5NzzN+_C0357TZLEYTJm|Ero)eq`*jT_xaZOxlD*c zSa0frOWC6#yDEi|(EOB{mm+1u$P|{%HgCwHSJ|UA4frBXQ%=eEJ}Qy^1Px@>TX$Kl zTE?9$`sM0duvuPl7B*ddQmFC=B|Q8?7z1&~9@QRPnce40J$%4@w^BOr$qv(HjNo0+{ktVuTMLI~K)r`sl&E)mD)ffHU0Z zzucd?WK!TuE@_EAA0(gKX+&6O&-yvd2XKVsd)no?JLgZaw+WSDZT z(d9N&gpBdl8fp;H)xDlbiYdzTr(}UH!<>erZ(pC;+J!~gMCz1t7(l_`;}_)91pvH& z2WI<34mJ7y}kS&KW@h$vLTwR=mf zt(;d>pG|2xBzF=Fv0@Q!fr_MoWzL3T#*3laJVIQzx(C2 zA$ud7+7c{e=cB9|3csDN!p zL0o&bQLqt4rXEwEX2#0lRI(pU#9$LvL$`DrQOGpEDDRen`v-JBOgnza+ePDSxH+@C zG++q*g5kQMQ&~mp{ZH8TT$AsBF@3u}ipGb!usSgXZ|ad?!c@^>T5acJy=VAxxKHoq z-;mWwr%uoeg)#HU#BjWFWu=X6Kk zCSVg#!JE1|Lx{9D;02T*4phyEn$jd4pIhHZvX(y8SS|t~drNlt?;&|^S2}*uo}u2N z2J|*yo(*oh;w7<-*6%mvGtG}Bie6WsIp)B1?Xwu&Ftd7J>{YT(XVKe`Z5c(j^z3r3 z?D1t2W)q#tNs`q8cPQ*4gg~LF-b<8e=~<*cH_R^M8F<)STNj8n$~C8#630dC-%vqk zkE)v@Bviv)r^cb^mAPaIc}{#`pC!FK$w`_RMVzTWH6K2yV4IS>_7s%No4dNS5~SsJ z6j!m7(H_ul1lo9|01)aB!-B9I0o^A3C@^aYbC~5)HaLCRf<(md^q==1oDJYcTt;(C z*u8BC;}&`LAsOJKi>9@{s~a173DRz559$MdY3a;X23!d9|KdXNZG+b^Qi5)Sy3$^o zWjxjkfg!otdEq?PgwXwgp`jABv`&8WjYn$lX9-4VcocbP)h#?7jO6CGuNHImI*VkL zv;=K$@J6PDa2`75$?Y%Xur=tAaaoPO`K*oy!rH#e&zE)5S#{Cs$#ZWEP;*=2$|72O(hs8j87tHGD>+0r-@t@jZxa%(&Pkn^ zqb4@zhm;y#$WV_{&SGR2(U#0#*2#b~^FX3(^g6ev8Yb$ur`VxYdWtAjC{ecDCU!m$L5%mzwAg+lE*^Ju{|eZ zeA{}v48Psm_5k7sV|Nt$xZ*#c3^P(NWA&#~;M&u&c^H6(wK z6Ep8Vs;DSe_Aq-z*s{y$a1}>-XWrRB#P02#zIi>ZBy9`(k465(!Pr*OPoG9>X}?}e z$==aA#OzR`43mxF+GS49Zao|5#ZmCubpIs0RhBaA^CpuflkOZ24!}ZuE_H#2sp9X) zR~iC*71xLj8SIB^j(?*)B;rEu7@hVUNLn4N^o`)LZX8SyFe!e^!!IDJ%*Pbp4FKeE zSqGIS6S0_^A`JYyHZN1Tl}MeapRkmV<;XQq%u1>{cZ-80XPd&IObRza&Pzvws{{#^ zgq`!;vO|;vZ7KfgxtT~gij4E!>E!(w#@Io*vhLzy=eEOe+{a3}BO=G3$URk5LML=hC1E$od(%#Z^)g#6Hb z<%{CjjnC65{&5y_jUZ3WYVI7%OKKa~&7qxS%Pj_m7oP-_>EA88Y%vfnJNC?{IEHyWagKN^_#^Qb3PVeKOOc$Aen-(BAD8DxB&V73u!8M z`~!v~dBA_VcVdFWc>rmF7DBafpJ{E~{QA!^0dWpSOrluEn%^%mF_GMuls>L5f6gcM z?^i2wG-3)5n8BIS6h{Tm6kXz49jYAJ*JYsh;&ZI)T0^NBq2T=^^Uv{fyi0ebwJR;V z>)5|$_A@y?7xed;AI1*$>Q?y?=0?s6xh}R!6;E4I-^D*g4%m0;PXq-u9%-Z`U#{|e zo3!6(I6=)G6c9$})JindXR2gJV?HgGJu46N1+TD|`9Exmhg2jQ(kk}VMNv&1c0kG1 zMywL8=ZAf-{k2{Y>{YxuU}*ieSEEr#5+$T|PEI{MQrwaSJfH^QGe@BmJ5sm*LsIkT zsI;lL>2Bf)wo@A|!$~w>(W-}{t#T1TPVCLmSAzhK&Et;N=#D2VKh|) z4zDQjkC8WT@Nvm{uiphal@7p3K&g@jt>Ib5gVQXD_0*j{pkg6*Q@})VIGk z&C3)`>QXjvk;fQ|$C`;k*ZGTtaD3FSlCNEPK+okXH893yqGm4#jB}w~lW1=UVRzfv zu%}l_!`H_??9Wh*)#mnHe&XxrhXxa>4;(m<1Bv)zcDY6wl>B?axEP2we}^QdzP`f# zmblf*6P~$sphL{hS)gX7=W<`4Su;F*^XbRQ4I`1Gk{U37`Tpr=VYWHrJ5%_K=F%N) zZUygr84aKGcqu3Keqm!+dAtF+ai!Gpq>r!FVBs6K3Nc26$LcJ%GsQa^X~85}%5^dP zB*!V6z9YP)Go=z=Q##bA1z8IFn2t0mR9u3o#jX_`^pn2{6EUp-ooWIp@>%5@a71IHEVO2kTH2UoN3-Critn|Kd#Ur??armg-x_?9or6p%} z`3&ztZuFKWnCTkDv*)y)Kb%M)$bF`mH*W?ltnFY(F7^)oBjKfSEByk%lFD>CzRKL3 z_79R&4GvxbxRTJ|rgC^Fr~FxsB1^?<->6c0kgN8FbpVUaNS~*$yz^#dO^vMTnk;sh z*>i$WKohgp5kx*2hL<{|@H7jR=CKGR6tbvE&&|GxSmE}R#c=xS#L6ad?udF{Bk3&< zt?-iXcdBJ9`}Uo<>Yr80RXcgads*b?mK}QrIfVy-hR+U5^vEcMf81w!trmm1c&T%j z<2RO*!T`tnA9&F``W=gn7>I&M~nR$r()Y~0feq& zbuYU;sXCh-7OZf6X}HqxK+sG~bbi>9*aSXX?b(d8BrS1*_;vN$;l$y^h*<01(ooB- zeYf0Z`iwzq2>pzyMB#!h?pq=fllpleQ@K%H11Dx&1wZdfxW1k6c)zL0l)wtg{Kib& z^7!D>9S4yzh~3K7$>y}jkAEsK-mzP5{X@xu*LW6Nw4s26C`>;|ZG)!i$(flf1}3g- zNW=wr$-`HA`TA!~O($aL0jySF#1~+chZ!0BKyK;@o{A|KtM<+%=6_I>%j8sM)qcBnQIfDwnjtXP5Y7eLLWX#!XE4y%v z&8Q7swkntBM7yNnY{WOBd6+LH(&nfRh@aWHoOLMYxlW1H^7Puw3(-OvR?hB99>^{) zTJh8xs>sZ_H(^-l&lY1}2;?is`=_uZiZewRIGa24moO-l5b{$k)YwH)rF=RwD2 zL~cDOz-9|nASmhf^n32yr2{#z5R4J-8T~NosuB%M!6+YGFjd;6`S{nyyw*nH79mVP zd}(FNhprpE#HfBJ+_NG?T6&dSZU5L|W3lw{892FZ--03fsur_L`g19Yk2ysQtDuoG ztehxYwK!azrx2P5MXg&$g5i1)?N^8EUFVEG9%HL@9xcjz^2)H7@rPiWkH9_m|#d~y@N(w-d z6aYy`0U0NFA$*JpeQ$q0p_^}~K z-bGPS0BjIC-a-@%x{dyo>bDwwY`uh(5f_w*>FSdyLKG!V7EB-LE|SaBOM&l|o4y3z*!l zrp7OKwzF6$FgO@LlfdwHdg04nT(0ir!q)recXEmy4dSZX*J)mT2!&QRk8!%d-JS?m|bq`8d#EyPd^&KTM}dC#%v7FDTiW5!MI z^D5yAc;T+Ic7F0S6+qf;J4);i%Ocgd*LU?}G>q`C+5*=>w8yvVca_{nN!0$cc=5w9{0|RsOuUxhl zEJ?BlMDMklM1el-Ru2(y(g|SeB^mbAfU;t4hz0`$jJ=Bx_w4=&92gv;cXqj1NTfN_ z9D3^+u>C$HyZ}wErj@B6!qoP|bkf7ipRC%((c5eDypV7mWxl9Fqnm_{q_^*y#|tc3 z>&6)LoR&uAG9VFmzJC2GU|d}Wa)5IjZ*12xB=pF8>5L}~vFh0bZv!M+%o@Gw`^8ij+r&v%kG;4=e4qkNY?FjV{Pl+$DO&)#}bQ}Xtk zO7d7J=*kxZx{LEPG>QjbDfNx+oSE~&?38>LioTrri(UK)P5#t=oL-zds2Hm8-@>*3 zX^Q-BAMP(l=vA@%FaILw{0Wh+-3kWk&t2`=KLnY7=8k_oea(m8UgtfhD@Ox4ivIJx z{-TvYT6&uPH)-k5$NL*~{K1go&o;CVp5@{Hw=E;VgT19pf8Pt6yXj6?pqMP(7mK)0 zJWIc|-q_gy+$s=5U1(Qu2}RL~?o-+zT@cGv{n|%ob@AHXbgUQXz559eyk2e%2l_o; zgO)027Y*@lyRk zK6@T;@ZdNERy|3+pgxF|1WsYagWxo01;SzkbTU8V;KG0Kx_e;v!0>D>K|%L-5il9~ z!Gsg~xg5+-$pt0CMjOe8O}~+s2&SM5mquJm{{uIEcLjk>jiR=_y;5gKC6oH2#BKF@ zNML^Q>^7NXVb91dpPvUS$^{jD+V;}w7w2#9=i`1nSbMq6e_25j950{3=fOnU5@aX} z*sveqk7aynDg)dRWnzkPS2Hm&$?ONi^`yO4)4>uNq}`U3 zz{wPIBkIy!L2&>6Ms8$2kT`9?MEdQ83W5o;YUR}V?@-l5GfSPbH%F(@Zt&&r=f~|Z zemfgTwCazC`f}>WS3y@legD+{cwPVO@%`8tjgFele)`WM-`{rOANF7ThryqD{uJi^ zO#*xP?{NO_M~#1HzJDGGt~P!9BtdcmLVtK=l0YWaw=Z`j6f((go-v^nSW5W{X=Q)Uw4)3||TGikS@^Z5xzQsWtZfZY&+#y?njY zy}diVH)1lnzRj*SFDp-vTCC0Ow%a6D&{)Z}y|vtdnwD%EU%};QLse`>LkH;R$F^#T zSKpHiM`oRg!}7i!xNDU3_1{p4!MAKZlJ(M^;3dL0qP7dvq*Osv0xD zU_Y}gYCZmIg46tpf;qZOk;bygLy{e_AV026B~Ic}@7G(1!SME62urI0PR zc%!5t3ZXg1I1PC^uNk2uZav}QtorpLgsphemVUNa<6Z z$U92r95Bw?A8j=kUDX1+rV($y%G#WlVK`&$_Wn5d*@zg{1-AjOHZNq^Y3pKAxzNH} z3f^dd5;EtGNPgDt>Q)3Wx*wX{;cNk~-d-6yvW!ksp*lz}))eKG20r|l#wycT$n4%9jB zjy(`w)AdoP6zxknM`p9Gr6NZqlz#3n7a+LIAi^#!4kDb=rgz%9eQ^dv$;_DgHBU~* zweqm^4)XieJLq@z%VC3UtT+xUa3bC%v6COGVN zjmfw|@&IsE@J;L{1LfobsF6*f#GI*?yS3rDzzC!s+^G z=SHb@T#RGi>%Lo;xM*=8*nlp9SzQMbm|+1H#EGaa)x4vU#0oNA%24nn4-AEps+5zC z*@!@Z`BH2V7MDj03HJLcTGMk8O_@t~7ni>H%*7j|fH*&$T+6iS&n+CTa=vK#BoF{z z9OA7s5Yce7#VluLVgpKkV<-jw&dNV9X1OoBh>t|l+AqYp%Fb_!4W=(^?l8lxTyZNz z1?k10BC479TwE#Sa$(OckB>_{RwhLxza#-~%7}+<$?Ohs!2ab0Rkq(PF(IUi zxxL)tAk*;33u-ogeHkH)T-R(q+&y9POnMaf0FmgrmmbWyF;IHx@cvdNTdzm_!O*!A zmY64I-nP0)#oO!t$(LpjYaHN?>il5BG$I=m#UX{Eqa1N&7SkzU+!mzF3LIdQ9+A%+bJ1C9VKeVxKxd>iZSJ`cE%txGxESvw`A)VKkxs1r@6M~+s--t(#{lvP}trL#3} z6s=uc2D<3K+qxauJIx%&3!##B$tM1ma&KC;B6T{W&KOI1)X&TDQId2&E&STbxBOxi z`;J;sI7BG-EdK zn4md@Vn#dE-+^>D*JVXX__0Z0%tdV{=A$7wJ(={|cp)S`JKZQaGcP1Y*r*Rg)0=Kf z`m*6)6Nm+L;58|LGJF!VkJ(pTUxQ2G4Gm>1uwYLm`S34^4wiSH+DUZ7KsV=VP0O6G z7|XjrVyKlokZKQ^n+Knry)hBy=tit9;tfJZ@qktWUEowfr$5s@J@Czk4=GNPrUC{ zT^0`nCqhUDgCZc|iwbh>D%vf&>VaO~@nOD;N9@7ZueLXnuvWtUCXCvfy}v0cg!ZL~ z|Lon76=@I`*MHM(?=$o1@uu^C(M%RwlLvZL76%GU@5>hb2`d|^cxksU`uT9&gNV5= z$gPi2*TVKdaE&x#ES;;t$@sOtKC!y-@ABIx_FSXVr*p$d;<9zdR-+5jCc%4g*mS^k zG0bOg=xK%5P~*^92(v5j;o2Ok;MJ}?;Pe7o zD7Qi(2n4jhHrMPH{=_jbg+Rv(tmMNf|}=D%j|5N^My>wbC>&VsKybqiRvzzPicy0V%z>nKk5ZE7!sAM(7Cei7yW8 zD`-%qZkUB?2y+P^KIH4L$Kc;wU+24rsg#Kuq(8EUVb>lgnta%{GCrd*o{io*mwb(9rU z^&kE_>9 zMcLa?j=NGI>*C3O;liC;(@Z^^=m`8+Y1rpc%GRa>>YYQ0FQ$I6B}w1Q)1r?|dXm{M zS;){_cXbViK)#_IZW0U%*p+aoxbFJyx&99F-b*9XYoIP!`PTUS^Iu-PU7#5=xZPI= b>FPge8F3@#5w3$;4TOAI9ZIp7I zr%I&XA=3n40$}C4kC~Hmk0^OT>p;*H-C@}C+7Ph~I9|jNJ|Kw9*@qhTdwNiuSR{&W z$$fNS;@a5=jD}_hYGgfQ>H3ri^g2`lXc<;Q9qsMvX?K{q$8Nl$1j$^Q2)J@pH|rtr zRnQQ%Avr-i2Sc1rhyYr1N#kIy3yx7QxYJpnVzn#BUddJF;tJ)?3v;aDn6X#w1V8N< zrhqdL>hJ%YRHv&&=J1y}_+2 zQ}YBlBiE}JH)@yW=T?Vnli_ni#l!6Z#c9OXo81P# zcXt7fy;T)B-L(N7IxbvH8|z^d!dDj*vv$3yYiv8Xva#+A8w(jjqT~M~?!0C))M&4u zUB^P^fn$F_F8{Z~@*~>*Q^rU^5&*zrh359^^+_ zvqwncVokf-@7wCc>4%0_q{OGZtAdViWZ|F!%n>dHF4PaI!R1Zl{3f_!TG-go_Q^~@ zh@f5bZt%rzxPpky8ER*;W|enMOY zV#M>&T$O{d3$9}rK`p1{r-D#qdFLSgas*AR&3ms0QqN*O82<}^UTYf67JLY znQopzNigVRf(bo{(PygXi($AfFo!uu>}z1MZq@j0@6o$$Y;uP5e8J@}6LnQ)Gn27( zI*-t7HkIb3meD zf|R?SiB!#GVy|&CM?}tc0F;^TfT=wuaP_W>haS+$a4_c_@LSJlbyc29SJhZjDhGPw z0Gqk%)Xi~h|2DE`Cg&kPchse+Gy-BMTTh5hCA=k4xDey9*dV3XuHfX}eo;oo42rl; z6A|+mJs$LF_k!N%y?1=*NnbLRhoVk3HD?DPBXJLohEd`h+_1-$_Xxx zb+5mC#P|aVM;hB(&j(};Cob+Vlc3!|as#C~yU`+>kX-P`dvlUcXi)b4lSb#1&-|xG zhmC*tYL7vo%_v=fnV6^SzYX8nu@JZKyB@AvqN_E6J+TsIHdS+Rd{J(y-Q~*q->R0>LtKsr_5NVqDOAE8yHQE%_biw zw~#6cA7D7G?qM#1?IV9-HtiLcf^CZ@8wG>0RzXtXWq?H5O!VBa_m#GqX&3=W!qbEv z#JNbDD5ljOX6X=t&@qLK2$`_kWvuuX5j>hX~G4ZP@ZX8xJCTs&Hc}9eWgL z=ln2jm7D~~XOE7WT&dSZ6-JSfO6Q4;CCIOKJDzboIb71nu#~k5km^kjj6+>9dqM0g z$OCgwz?c-}%yE^pJ0W67sxLjk45V3VCCWA^bJDk~5_UgE$Yd=`636E%nJY z4`Z!j#>rqUbl^~5%1ql=WHw_$&mr4 zR}(O3@%;U=#d?g*V0sEYxlaYjg`byFu>I8ZDpxzBrj|=e^GaY>p|KBHu|lLEss&f# zLnl~TdU^X0df);iWL~O4%rS*<3B4{MKVUZh9>ON=^%yvmn(xc~4u7$^#n7Vh%ELrFPkMzCmhwW;d6D`}M zB3FL7AOqx(%-+Y}IySow{m4fV0lOGn+O=FhiIzd%lPw1%4kY3-nYAkGra%X}#}<$`^)wXliC{hx=#bnJbD z<%{ED^=D(G>j=GF2Yfq@oP815(kTynp6l-Te zG9ET_(wl_c9Q$A~?R<$J%XtgINH`oovu`(lu^Y%+6>qUpe1DGKIgp(QE{8yI&}MIa zSixcJ;jvgdBbtwiJ`L;u!0A{AI{^LhleyY<=+UJ36h|33uj2)$p4|Yo68y;RjmNLQ zEebyfU%2qQLf}spD0;D5gF%{X_Y|q)-jaO}kP_eP8~?@K*Y*ERE}Q4pmMl zD`-65m^Frzpz|mJok}!aGb`bjH66KlNM?1DKz^%|8$Tb8Uuvf{5Baw7HRIQ|?9nsc z<2Cj&wVUSU2@H34Sw}yp6s&qg>|A|rlE+zgTT>q4V$N_Q?MSifCf4tLQXyZyrsr#>x!~dQ9c5VNye*-gr zJ@UaTFV%hjSs44iss8@V{?g3!Wghdq`0qH;cj9x>)vgIU3o;ac)&p_Sbd%7cQVB|@ zk%+Dj^mn>Yt`>wK=I1_H^P%&|mXi+l;9DEQt1bFZy<<4&c(TRBammXxT$bY-)~w=K zb5EiiJsNjp*Y-yw=-(l&L)CZM%wp*o6!7NVFaPDnmW`B0{5^T_fAi!&cb>XGb;_fC zjAvf`m)@Y|yVCy)3jOTVZ9e(`{CxhTT0zC`KS7TEm%GWc1oZj4@c+!I|J;G^|4Fy$ znVg?^nz^Lu9nAwJ8FOSX32l-{%mvhJOhIS{R4m~Y4#vI#F;?qrTmI2YCg}iYXal!y z!Y-oX5tq=gs3B;S&@Oso`Zg0rOAbW*K_g7x)D(}#4792lb`-(Z)YUGrfRg@g>Vd%N z9&qqMElH{z*|o?4aa}AO6K-UV760fR5&S-!L5t2T@0KGK(z?f*JM-(>E~|Y)+6b)T zqUjsi%sEiJ>A_E(Ku--zgCK#naj8!M@zB8Ro<1jHjoH%{w?bB1#M}nD*J({3O}Gqi zLvm%inh0llsm+jemL{&QuguFII=zb2tG3~9BV17m+MUVq>d*Y157=q_3=K5<%z`bG zMFY{eY4N2&RqzYe)KDn_Xhu2@zis;^6xykJjxea8m$#C|9V@gp5gLNt8??yic-vmm zj7=FmkFlOwRD_p#Z76UttTMN!B~^UxY8eT_`%IQDYzLi9D6^aK6&jQ^{6nea(fzWL zsu`8KZP9u%WR!{}x;p%3i%9I=BKIztiLZUsj>g9EI~xs~VGfV|?82laB_u7}DDj6i6#>h@29mbu63 zuO)P+<6p}4;5|Jt&wr(ate;w`iryCKl*Pr0NcGS3?Y5Pc;gL_ggExo8^gtnti` z-t6d~tT&62z^~0qrl~gK+gB4?T&vOU1Qm2vz`z;ePM%Kr%z@2+` zNKHqq&oR)(Zuu{#PunU|w1Q z_?!rcifV_023S53ks?}IFvyDFnR}{UMKq5TS7O=Hvr6gOyYNG=%FMb$;S?bp7NY+w zDo+m{zWxnJ>}hh2_{g?X+-SLZ8+Id>#hZl4j8&ZHh6p;391HiUfQ7N_;gNQZQrE8O z%O=rU-r{0>1e30`ipggmaQ@KO91lkWlKJ zQ!+@uWE*j;*$!J|w#58kY)!5lmk}R^aBImZsBIR@5;9c~X#yP*f%81vbo|slY9gdm z)}LN(YWvPZBPz#KE3vBNE&34d_spd2-DJPKJu@t_E(~XF(Xn(~VAxY9#oK^Rw78=k zbG7^$t;gP01{LoI*CyHWW^@GB5`8tV1t!T-Hm$K^pk`ABy}IN+IK`SAiVZfMr7TH5 zM9J68SRIS)RQTXr^87D7@ptzP_f^i7SD6)@1&%d7Ik)!?J9n5PhH-A^RfD!wds2Ea z6GnFuM!88JsS3x>4NGc+NO=%llW~FB(Atjnig>kJDSlx)crnLuM@=&#upn}(%Ed3Q zu+6oT_7bIMSMZFggfAhLt`Um&`0#yMX>`jkzWK=K=$Rqvd1Gm0{R6K(nES?tjbuq$ zL;2~P+9eO2t!?J1sG(g?7`l0<8aY$z4V_CRD->vz{tO~e%!$!4W~&d`G)n_&^M?$@ zQT>rBEHLxt2(@06m+jrXS~ktRtib+@IiHs*4bNkd_1Z%>=?36V+#-?S{tm83yZuao zJyDY%i;pvzDJKpZG3+ssCISn*a+#Ql^C$Os z;DlqeBoxdxi;-NNtu@3H1r)49(ITS`kdox{5I_gIfEvXM31St|E4AoQzbWZBsta@% z-SoS^)2DqjhOy%!8QCRN3*cyN|HI7qT&UnNPHA1h+n`;kiuAZN5TMvHG-P<-2#YQl zM@4RzS-N=Xk}AD6zd!1t)=h9b=yJcRiX?$4RoaQNUb@w;)^4+%HbGp^PYez_X%sN^d&*jC_lFIh$Mq$jT?0AgKz zy+hCsSx*h(0MSF=uX6JFQtY0ktb1w0)%yTFViJVi>2>y=p;y+n0#TGEK_J}~n%1U_ zk&K>iAL(vF6 z_iSQBqaq$8I!u5lp0-TB4SO2&Z-%31);FG}_Xkh=D*m&;?sqxRA-*d0?X~i~e1GSQ z1u6#<2AC;K@K=y}p!ePPPvV)VqMA2W;yTDc)XdQqnvhD>rdxr-p20@A-2w5=)=KZn zY~PR)cq!=kKZDA%ayVdmShuP79{m-{+3rF=V#*BS!bdaEwo?*-e!BfEp!?xVD_Ahy z;n$X;8zapL+Oy3Qe1X9)BVmP?svoV#gP<~cf{wyQf_4tv+-z^*(?{*0ryg}|gTdy#rFHAr$|1BN9Io597DKM;% zXp;f*p@idTK0x5MpI-iM)1Cf`o~w634P^!3TrMb_g0zVYU_6mpqAYRppA+Q_0SWB> z@Qi^x;z8h-l{J!d814l5hIIT#pDO?m&J{Fho5Of-%;$i?qjWRG2Fw@z=zCeC3XB$- zypuiW)&$s4HKxJl1l#7SgotviKnC2+Iy33Q=ODu4iP((QnDnRht8vvvh#_R^+!50U zfR`>MtPlN$Q@@8U(!ez1Mg!t}iOYPhDD(A=}@8gt7i7VVgtoGVa)(UQw zm!0Dwc>zH;_a_{P~K^0p96IlWq&uygky!?AK=()nqOk5*A`p&{q+? zdomPP@-Xw1AoRL5VC2qOlLGL9=kXwTNIX2F+}}>BRKR{)Y#Xt4d#?;p4HTGiR{>fJ zI8j(QH$RMaya2X<+2O2{0*2_w@}i;BBu9*8bH1#<^Bn%oCqhsM{6YAvf-R)v**R8z z?c1Q^q8r2uK|$YRsTY+>g@dkBo*YngJj}$@59ZSHLO|~)3^bNb7-iycIJ%Mn(FP}n z$SV`2Cx$!-ewHW?G7*}ffHb*r;|3_01&W%Ba{U6lJh#PRDM=kBc^$Oqa< znjS~}syUF-Y1;H%pD7EH6kB^ad;cnmvu1C2&0fJ>YBjg|QTZpR@7FXLXOr-!Vp>Z< zcjJmo&qhC$=-^K)8mK)CA?m4m^!47d$Lv!e<1G`!yKRL-JD~s(xkm-|v4K_W8ze*oowwkWwa^og-j z=ZTPSLlTl`Wh;EQuh{?9vqTurZ3h;>`*~$}zA3tQeG{As*`97VZ=3DFMPYSf{Zt^3gF|P-z1_!?A1ihfaIO{I=1> z*0pR%Kjs_}WNi8t8T{M(WYh(Kr+PccVs2YqCE6i`bu;V_@^Xc`cK$T>%od+FqS1|LMpxI z^Sx#VL=#m;!3~xfik1Sh^udT@dg(u4KjsV~?3bFeS765F2y}~I0ncZD=RxeaU*jZE zw+J+!JN2%o2K7nysPe%@zVr>_3|m*O&G^*WFd1s1UAIG?H$HSdz2x{8s3V_d2&8?A z<^K9fc3B6M!|du&MnsO!5Q^01vDgMizmeKaYhdu8y?1H8IOV}SU)9Bg%Dhkq()Yb! z{VW*C)od^MUF7InMTEUv7Pzq*7y}emDAF_{ZlO4rY`)d-&1P*W*D6LQ@7rhYds+Y4COFTh9X1U#(|e3^BMj$}UB3elW|dmQ)Bc-D zK`luV4;cet#mpO?9kvdwy|-b8rMK5&)MbbDO#O2JUnNDg?606Y{V-=|XN?B8@{IOq zQTyjl9!nQB>E=Is00jOqx9z8@lxiL5J-4Mix9^&FhJorbZXi`68<=rEjV6|wAn;}t z&>DO|;!T0x=i9i$!_{LHRIFJRSkt6RxPeF?0~aq45(nw%W?Nmc$KBn`fp@{{psWAeP^!1m1qZU+}9m0ZCC&eeRx8QWmXtG&ol zP0;z-AZOL4Cr~37TB>g=y$2@Q%^!U)T^1l*qoKK0dVCeDQ|I+SiTG-jf6(rNv~2|B zT!C(Zfd+Wih^h_Z?Vim7Q?0w+E(%2OF%IB_$+N~u6@O?OJ2v7bE<%F{>&<9izp|Iq z4K`jKeES<>m#YKE1|I7GT_%X_OCjZg*AFAyE~^0QsHsob@v)ItoU?H8AAckhIP6zZSv#6$=qcjg$1TDQdmP>?I-zGQzdp3hrppK5$`13D z<@6tqN)5uh8eI-J*M}~5H9ktA%-77e0Xc>4JsaAs7nL**51vtTJD#va-Lky2%o(pB z#%q#rJI7UxPss)2rUA-R>Ti;mEwS;~E7RXg!Nu{_?WKhHB-eYbOVr%)rU?V4YWdgu z+gIF63ArR=-pP*4h~%m2U6{KT2%6L>-t;Xm4S}W(sVDFmjYre>^2D=UNw_`xhy&;) z*2j4;*)c@MrMfKcG2mEg0Nhd7(PU<^S-VJA72Gx&pve;fseAsQaJ3mPP9mCQfPAX% z*;!-j(Olr@R4oh${>y_IrXT`K2UgMfU>GDr3BMY;5yxx%9PqL<@eKVMNZein&5y#|tFEDKH$T*mq(a*n0I zV}aV7|JBTw?uMA(`PR?8FL?4aWl!NN2?o%DJEb=LFx6#~DRE1<44hO>dc^u_5qJP=ou1G*P3YH4e_B-IH>KX*uX+8R# zh}I`|$*C{*9<@x=Ju$Zcvmnq#u8!3A+Dzny53oq(kw9gh*IG1_s?vXXf=9byJ>JQ? z3CP-Dz$Q~IR>4SzQ>EeI;biGUDf;w?(7D(VC3en)p?7CuN)l&NV9kFV;3Azfa$KBy znerGW^W@qgaDZiHD8iVVO=#uStFPCr={cux3{+!TYm!Ks>N6lh*R|aA`pUQP#QI8np<>Xr(s7uL^iGYBaNbL`s--{}6PVt=hRK$teP|(^R8f z<69u;OiOQRa9L1KoAFbGeQGMg$YFGQ_6v0KSyQCH0pnkOU{DZP1>4(`U=09J|nO!?pVS+Xpv>n@WYc zwVxPjO3OHghkdReJTrAyno)lYd`X2pS5?Rp32{VF(;r4-EElK~?kh5y0YKgzwahzF2feTMwqo0Mb8N4pWSqMl3E!d+$94V(ecW8Gb|_cFQ<|Z^PiA z8Xo+$ZD4y#=E(o^X1`A!OcJ^Z!Z#h2eP4KiJhkG&XD-v;KDvHVNBqwFPF3;#97v-4 za^2YF3lYV96iGO>hbs+Bb&n8#Tz_(V_mnR2Gnp>4+4vF02!UCb7v0R`<|zT%OFtj` zOdY&K^mZl{qSUB9D^d=xPa5=~JBDKdnAe-)(gD}b8W1Qxefks~85zkS{OSen{vXKI z{b>0ID{??q$G*K;FdVC;!O&g6sYn?Do2YzL@#`wV1CNf10d*zW$f}>i?|K z`Y+&%?z+VP2U_+wbm~9Cy{gYCn*Hz5ssB<@3VcvI`9BO|4*Umxum2JZtXuB+@EE$x z{3{wJ0hE;bN{rb1L=2R%w0U;WbN^{P5T)ts^!}{H*3#z1rvDB3wE5olN4BI5?FRA6 zTF+J}0FvA>KS;HvW{uA*2XLRJ>qUinu zc^)uJjksa`Z-buyJ~T?{@*Q4=nNtzypcO z77wyDbiUj_Lk&g@A~wHG8GE zy#A@{fCNRX#X(Np7~njC`2#AhH|MW##GA)h6wt`l#|lBz*wxdGh}`$}u_BAY+HSRt=6NuUM2QOZ)tfFkIk9Hu^Oap&UJ8saO<6VC0M} z-oDht@D=FexfVbI)#|UuvaHQ~0Gxvirm4Dr64nM@q6|1_X6~|&C3>iD*R{%Ryyu;g zD8ub!u}* z0(X>Q3m0B~MPaC5znTfone&v%Yo2g5ce?;YBm74b*<~@ml z7mJM%I;+)Jlt!d*6-DUP(x*wHab{$s2PG5Ak*u=1p)Doa)fytiflWU;&@Q~nL^;<6 zbq|~G0sI;C=CXJiPMUFLkAd53+;U9vrx4M*M**<|`#25C0b@O+Jat^j+iN61rr$uT z^!S0cvcFcN@cD|h*5gxm)UP5GT21AWwzqoAqj1~>?%6C=g3zFx-r9+cbX9oMUUN3g zRAoHs;J6Pdm7`Q}Gl0t7ZuAV#v5m*W4=j9pdfw`+;k=4gc(U!et=6 z%u$3j)~p)}G&8*v&;2vJNQ@5VejPL@Sw;sgZcIZg3D*Z6&qi8J(T-l6YRQN#&=j;= ze<6*w=(=uhw$hN+N4H4V^`K@d=dMtbh?@L40=_O}5rKbs5P%nLx&C{;vRzons#MhG znp8{*2k+-<`HN2}96q#l&}(T6U-&>!oUCDs#9cow(k{9s!|Dei;NGEMKcpNuCmZU@ zGPDU)VD zcwh^y0+bL`md2N9xL;tmXYJrkxB|;9*@qkeZTs!~dFR!ko0?x0+kO=cVmj!Vne7*o zo2Q!m3O`Gks=-Uf-)fw83cT3wx){&MkECi@m5TQ)s=ndblIk^9O4e#>=rLOCLBg|M zwYVv_a&dLIr=kzU0lqS*J;$@*p{U!PS|}UW9mjV;wb@W0moTx zTA%%7gmZb8mhHPQ`HdV>lbPp){esKJfRV$j1niD08Ryna{N^So|2ra)JHFQ592bSGMf;7yQ!BX%{@1b3H3t-lblyJ_=);a1gX! zt?j-Qbq={T;%z}IUv(Om-ZH!6pdXZa-qj$k0Nuh`TZYK84W~Rb?{t|WBje|@6&|u3 z=~7|dXJ#E+>l`AG-@3y|`r3E{pKJO)QQ#A_5PN4sYD`h?2 zGW54S&l1_qy{#@7Dqd>`U4xtmq_9YEl=Hx078SAGkJFnsow}Jgf~ZiGsMgvu*>oDU zV$=+}KNiV14$F+lAORWoHcirA!wVT|zZ|qvX3o1B z#uXs?z%g_fuJMryNZ-AjM(R#7*BQ4#W-k|}=HAGUS#%~#+;@@<&ImY6!cQ<&h}#K zDVG>*9LY6)MD{{&us}QcBva;=*B#QJH*nMauZ~4;stRUV5S_A1-hJNpLlp+j?MaJM zzSLxoHDJoQk(+gv-(# zNV$%O4ra)ygED;~4#?t|P5pMy17j#DpuqN9_t{Dx3Mm30MyjOyComQtZSnU7kn>|$ zg(VL*9)!gOgT7>8aWSZ@jPK^no4@ikf`GpCS=Qr=H4d|vTC<*n-ZiMW4Kz$&fOIte zAWtx5$I-5GHem|F5(ld?JEh|3V(Yd$yE zFuU2CSD}r0jAMR9JI7ga_Sdw`o@x~TKD@$r#Z}<9tnB(mk8=gKUa-dJd|zL|ZW;aF za{njnN>+B30o0ETjvp`A#-h!}G+lis_gAcXd=t*KP9s7Odd04}%YFLnnn~P#xZ+8A z-9SvRx+!>Zk4Nf)?HSilk_wo4pwI; zLo%&rm#tkrLK0h`5ig_=bWxUpthL`(OdzSx6v2UEURhr*QleG7rD(cMzJ0>@bSbH~ zUB1H!SG!d=QS?gZ4szVMm%ups_3h-L7T(ggD@7SY;NXVy` zgRIl{wjj)eIP^;+aSs};v(77=QIT#A^x_TfftorJ8q4?4q%R@71`CMeE{~^ot`IuR zAtB-6fyp)za%^2SEQ*Dk90ivwpGM#Gm-N+R8@|q~l^EJadr^Y%shhTNN&w=q2((bw zvgxF-!V31Bq~@ePu41f*#0iK&Z}A$Rxp8<%ule<9i1H=c?I&<^0)^{wWW*=rQd>-& zRBQbUWX1V9YQKrr6yUL*);Ad5kivU6BOAcyUE@n99)B4!9w_g3HriRCtk=4&}T%gV}% z#~(Y2I?N~nWV+sedgkTkY-0kD8#Y>mW2>8?3ds-hrH!uPX3kPcAgFkMdW_Y|mM70u&!Bi+TPp@;{uW@b!nWgKKprdWd5YbH z{QzDvIN+c-S?|gLz%mGUoun^WBov5azxiSvT5w3lTeohd>t}qO+n(>t2~FS$G;N`i zAHTpn8d%{|=PYr%uQ2SG&60#c)Ug#qF2xfF8QkiADq|#S5Ty{-qtUPA$^cK5Ul)kFzV}XQs1aqWedF4Nk zu(>w5NKE0h4$2(w@>j8Qkaj^!?igkl8XbwuUuEhx=(J0!XW+mWf!+V4k;A_emyp+mzw8AJ+N_4ZYZ@0wl?x$&q*Ww5F^CWb0JxXP;jTo<9i8U1rlk-)4LuW*Fo zW^s5YbJzTnfb%iZegyK=Q76~uoTD1E^pjtwcZ(*BM;kS()u=J{(~#`nuc_Na_RTc! zeA_~h*FUt0JhX@2zi+(0MW^0-1JaiooV(>Ag(r<56`=-45$KX zhkm6MIheg?sw4>lzE$YYpNa$NB8UnNzzi0Ih-SFy6zfL;g&i6O$#4c~c0hX9RchRr zuTw+=oQK7wq(&<&m22z-2(2nnx6V5@AJCA1cAG<7oQ|K;a}SHn1C4JOqgVu(*vWY^ zy?OJd2|XZH*U&%&(TFLky&p3HH>FeX(h68sQ^E8uqZ}W_rmTf~fyF`Xu`T2iNuA%Lf?K8ZGRs~Vg=9*n-DQF%af&T;n%qhJ|mE)Y6=A2$MBG^ zmRPHJEW}SD^bU1OC1&EFX}Yxhl+)%BaB((k-ycjoS-akw|5e@|j+`EB$y4e;`W@r0 z9|g{K4OGW26+Z|fO%->33m!&7UOO*HK2WkcD9scb)+QsRuZ)cK}F3>_gCla)u^yz8G$hY=6FWY;3H;4j2MVR#;vJ<;5i6X|r<0I-2KCKpONFL1O{snP_X^8E@h~pX8}SBzFpPsTF{q7; z|A16ld2(>8CDr2fC{dC+^i%%tmaBn9ef&j@NM`9a+}!1*0Y@2yCz?KG_U6daq=6Zc z(Th+E=E}yr6dh@jmyw;DIDRD8ydHP$UCZv|q@t_iwfev8^`+XTOA5zJ`*wpk>KM}Z zYb_>)@S4<5pUn=2ntJe>wa31UEz^xxhbpzi-0Cu-=t|t0#|T)tv)$nakLjm|n1ctt{0!uExt_~MV~l@)cp6^} zZ{<1u!DVkCUD=*eC2&iPK4|!UvRmm)lTXmc&rT61{vT8H9G&F$SbRmdbMJ?oReDZn zcjMc?bgxp5DJ@pemu6dL{=!j?Y3-s3;wV0~IJ`(=X_e`69c_x(V55W^f-W^}W#c6Vj8 zwOg3w*Qckb@wqL0zrBu*(r@#bS0nck4v(cr0u|nUSj2w`YkSoS>OnD<)WLf1x?SA< zOFx(`(@jV*A8){kB_HpJ?;BGqyv^d>YhANLTwe!vzis7V`ub*vx@u2dp<6c;nlI@t z7Y(fUm!@mg`y=2pxF_m_|#p-aG@{6psav3MK6(W!STdg=t=MOas#_t z7t4Jga@+*0Bb9V%nBdtts9^#NG4Z*=vR5968-d$88=ws307V*Ts*`qhoPaD{zv|Uh z;PUUcuwo1im=(M^JX60LtRou=W`O8vN2oJMYI8ue^p`>LPY>3|>H|(C0V;V*HCdQR z$|DS1<+A>kq7`lfW%1pg#7d@mQdCdQ+|?+ht96*Uv#`e|XUD7Hbc|$v8p}o63SNUX zP0hT~DbWcTH#Xc+YQ4Wb+YB+dV~!+?4;gh?!raztNi`Dp6}b0Zd1%lzuu^5R(egla zU2ON<7q9xPnHJ}1m&?O}w|GtGG5yom`5B;>VDz+;41aM!ytzr--~-9~>W} zTnTqlU3m)Q%;B+IES#R?XnU-#`3-V{h)jBreTlF*%h^vqrukid%n?}wNh%l@)e?(TYd))MS=xrZ+*O+@~q1Y4zzU=92^xQ#XUI)CZSAM zD}r?e^5C|znr9fVd=GT1<4tvAM#~NUya|gB+8aI3P}?VhHnM@I74Mf#@vjycI7%yz z)fdwzg8C>I_^>s!7cvC!-pzN=2GtIJ+p|Fkd7e3xY0XYoLTGx+m&yL!)2{9)u?sAe zM=j6EZOi>j4sffWMc%d5qWyg{Py?&r z`kd2$^AK5O9YLaRsPeiZ5{fjaAL^n&3nywS+Dq^qzxSg*u%9i`Xe2Ll>O_`_sXFna zakuZj^Fst|ngurir&*EyVwH-1Z67H?S$EANu9x=5Pn{baB+Jdc*ZjUq-*Xx8qvY^7 zz+e|Pt&jcXrfzw>#+zd2`wA*gg!_-y62Xw_uGW||!bAd9kxIbsMrP6o#f%o=22G-u zRZJcQQ{(_YiC9jZOEKM#0Stc#B^*P&mPPHS+JR?>le6(BwUgDNaPt}8GYu=8SO%gfLqUi zF9osj1r9XkU=)6x=Xoq(>SzJd*~&DXXodZ$S|Lt%d15Q{W0P;>e6xZf+_28$4$nq% zhQrQs>#m=q^B3IJaYjN#U)(76GI|l$VkpSsb?CKMq0=*z76J>^@Cv=mG^{?n_l6sf_&|4X;Tbq#&1_;lVlb=?+V;0 z^%tS9b!=(xezAmM5Q2PgN#1a;Fg=Jxi) zM1Bj99CVn2i%L`0z2>(-#(eaflO4girewA)BUF!nDdi3KrPQu)TQOX55iW$cjbq^3 ze57h0LOe7vk*zISrVPFNc63cdjl16lL2tj8u~9D?+wnE}^8&%yq~YS6^D>u?DkeCfEAf0bKOK4T^NJ5b90Nm`7|~R5r?;oTMt7T{9(>_1;@| zOx=V`Ut2Q`ectr094*vSetsY*w`G05_l;3# zX0GxZdGe!!C#TMW48NN+B{6dFJ}XA~8qE^;ZrWlrzcjNN6eZjc<@|6A0$CgLBwp%( zA6cU%z5QkkZoSPD^XUQtwsriQlk|Xh>zpI$ zp81@#gRBe7w_R`%`8u)i-vmGZni)ec>3xNlm)A&|@%w6IKO%~iY*VrHZ2d=(j%z;i z*GwrBU*-L@r}FLo#GXIV9yzLje~C zzPTmy++5#=|7Kvb@BZlJ=I`qXsx6TnYL|?&m~9tM+xNrg$C4ry(-HBPG5()Fm5}#N zkAQuL%(q?M+N_2_ezyI<6+Y!1~@#hhqOwE0)X2kHfqxbiZ*Rb64Mtt4^#W@*QxffYh zf*pjygM`8{rLWUw`DZIVsW)xjDSvG)dLb62F^nmFYfNu~Mx7p6%2g3xT5dsY8J}-_ zZsL+p+(bTa;y4vsdannrbH$nN>FQtSxIbyr_>ErQMjD>_&r{%h|DUgl)3Lk#c`_a| zg(3gzETx1l9|TM)nT`I3XC|hZYvxfS~7+34@MW{cu%()@R>Lv__vzugYn>wG4uprqHx zRiVcpZSbY&zMA~@67<0ouS2Lfz(|C-*O#0@cn;{)LiQwpQ%a^mrBz5pX@WB_Aap1MyjTXl-v)xXKO=)OUR?a0u z6Kr4}#pUsVZzt2<0c__(p)b+;=}X!3v-;P?BPDF}wDKQ+cc$Sq_$;xJTY1-sg_Rs- zjO`B|Q_yxzo!kkHNwaVHik+Hm&Spup$TkkR7l<6XF?(){<&_kt2>#Zw#!hac=HYm{;8%ZC9So+_r;bBMCT2tgCe z=sF}{saeUTzFFze^KV>V;S&>sRq6ZQwo0gkP`Mt3t6 zt`+48`X6WuT6HI0&usbz|Ka;h*y#*@hax6Q$Fn_d3!!tU?nl`szn znI})FE1J?}wR~EPCDRW$ba%Rcre7=>aj+Xk#g#ly9#aT}3?y6k83=`YG(R^i8GOOd z?|VQQ7CtIAX-NFrnypD)YX@=-CI}tA1n8pw_Bc!h?;oABl~807aW62ScfVRIX>X-A zc9)aq6rymYAcpeU{U!q>uKPId*nGvT)DVd8)$vn&BqOBq z^n~t}daEc(51K}72lXxre zCH@H*JN=wgR8&89=6@7uV)#xaDJ&5Kr@G5} zgoX%Rcd3y=2L;(Jflr~3M?l;d+rQ|Y$|)NMdQ^`7=4t*Kf|o4)sm9x7S^C+~^3%>y zfD=ogm%qAfJte7HA5WEe<7+)X8&CY-SP4$3q}Ckav5D}$0blu*kLsVD_N0>NftVNB zJ1ARdW(Iz>U|kmZvR>R*;t++*!`S8YCLR9 zE?qX;mtDVfa24(cL)pTy4yprw68U>K@Z+<|l~PWu{Y}%~q?|I?@u4dZ*Wh2p?AP5a z2HJ7^$9q)04a9qz2zX{$k=So|EcA5?iAJI|{s*+wLaqtcBr67>>i3?E0m*nFV^Ytv zH`Lpt4@C=A4KpbA?Im7EDi~yZ6Inatg{Y-hKi7-&^c`+Pog)IL^D+vP6)r_vL4Iez zzQMgC^zGoq)Wr5X_3YfBFh?3<={(fg*W!ujV&Cd!N;ijA3Wh3GS; z7?!S9$0HcqyA>;by2Do%l%!QGkMD0qfZxu{ha~M^cSaxaJomov&FzTKk3XM{1dDni zU^~Oq!YTkj>cC-hvb2-Np>F8qiCd*G$yi!la0tQq{!-w{)wxed4#@W9&@V--nuKj* zsR1P+ic3w->1Yy4wkaI;Md1j09ED91^`JpS9Kw+T(v*e=z9h#4S;g0;kh3R}LcR-r zMF%2VhrDf(`{Wo4e!5kG3dW!*vdkcL4jZvT)orh?Mme#v*)015j}z&|`Q3oU9`_G5 ztnzsc#&pNK;-o4*UQLAkAA?n8vr)VUjhann&Ya^FYCckho#g9+?k9@AdOt+T)MA;b z@4x6RFD`{e8if}Yc1>+r1i~zKZSIw{k<2y|Tge zn{QtrNMQKRNp_;JXLwWV6;m3Rt+i^|%rAu1S~J~>M7O_FQ&jxj!NK9HO42nFF)^_U z$RI^)x{PnWLFFAV$nQcRGCqI4LIOmgPe3s1UE>B}fU7Nn&<3W7H2*BOJN24u^X!Jzo0xxG0KMV{~ z<%mcJCTUS}fdNDmjs$q6w*ulHK<>#v+=73+fBapWL*Gg>m<9IC zfAxQus(@iR|6;5{M7vCHt8LGu__>Wqz}QG#nOs2g`=>OwL67ZW4>LcI08{*h(*e~) zG3(6mEPp{m`%v4f6XG=l@nMZ&-HlHG)1wMjJL`nS7{66dZ|ncj?{P-hj%lT7CFJD*l&oE1@0SLMQ_A9N?G^(=uKSj zxPHs=K&oWQoTus1tRlsxWP7tkjlbO(N+twQ4oq5fxcyCCo*hQjK-aLU+UO!1ozC7e zPFohcBA!5p9J^}4*6gn1{|=6$pOkOa;8w_!~f0GEfrHBU;(LUtd>($>aH7y(@s0swL^A0OH3YX%h-FM$wNxAy+Q zCM*UZ)RoSQ@&FTmrGp1nKpMSkSxSR~GZ%-xJwm^WV=?FiW-r{)sgpwZ6@$ zwdlSElFj4+f879#!odR?u>!zG$jDcvO$0QrcLNd7{9IcQ2$4abV%4FXo|}^bx@9K)z*Mk*B_mKxTl+c@i3Is*;CBl+%+%$T zvXxsLI4zEJ^u|N^Ov%`af&nN#Q_pk_qnHFCJTR$!X|GGD!7pN z+>O5E0MOm{?L1Tw$3cQgGlEy0VScx0opG1Izh#`8fg06~b^JX_UL{;FA>wqZ{4hA@ zF+5zQi6kSaq^6^C=Vwy*Lw5Mw&z5XHs_)7IU95Ti!S4*rDmkgln#0pM@U_VzFIMEy z_60CkUniag$smq>bIdv`9sf3!W{z6isb^2 zNYDJd8&X~`e z^)iW#R+3r)>56Ml*{RA#ZVk?dTuiI79tCR?3%IsEG&V}1pafZ9J2`*2yT~Nz_7T*Q znxLbTk6`KsAv^Wn=sUE$MssPN@H01b3bnr~#UKmfya=a?ohMk1$K&Ms43ORZJR#cWZO+ZbN(>w-w?9= zhC-g^kxA*YTQ=1hpK_od~` z(N+o-I{t3BPI(cZPgw4ww1IuUS}}I6xOP;tB&IZa@@F7u4TCtm%QRiju6r!3z@P#? z@!qA}Wq$ze;fw04j7&P|550*cAQkCzR@8sPzislSl+2`LAUs8d0ex+JG+JNv%!{xi zv^@_1onms@G1s3nA#C4P&o#bJm@c&IbI1f6aZF2war)-C?WdNq!RX)d$pRpoI&I9QU?PbmKOs*Rtn{c>)G65 zD^a)$NC>ieIp*f(*3&gS*$R;nSU3Qs4M4B~@HPbz-~nbJ`au`P_q^((c~?Y~n4<{^ zcqFxfi$n#~F6l)SkyK*i3X3PGaS?vUiPhCS$N``N5$U*R@?)Ek%3~!;_sv0AFXG7K z_Nq9n0#e!Lsy&DZBD`-(#behw;Tp^+zupK7Je8`EA0m$xi?* z>q?6?&gF!=nuS;7wv0Xw!xVG5>2X$T6Z>{Y7i(g#PcJBi4am!@ z5yGmWrI6m9*2f=LaZO+WAUABe*gE`W(IR{rDKpChY>BvqXA1ipyY8W1oj9*ty!T94 z?p)`=e9ZW{I_Cq@7cJLV02mwfCm8!2b~BSI{l1~Uu!Cz-F+gg~g&CYwQ9TDmV%J`+ zIJ^t~pjG0aQ;74{=*SbirzhP11-vnaM){Nbcj6*?K>I6y!olz$msL_mjp{hr^;4R zQe&nbt08{IQR=Q(E^{NUO|xaa7{0kK5jPFtmGh`yYS;BA1ZHhNDF=Nyjz&F0QNh+vg&14Y-;Kt`zf zg$NE^x?6)wA#85I0cM~(hO(>ztgBHR>MWONc~$iF6WKGVsHr>Ve*}ZP4Q2qfE&aiA zgE#vEDo!w<;y5k+yb3Dlu4>x}eJCClu$l+z`nKCqfVc|ki^V-lR|TKt9%`U;f8^yQ zekUdb3-^tTVpFK_EOXB@6HGc>%gYe=+PTrz*7nM%x%lcfT$>zT&set(?oF-1jXV#^;(~cxP*-Lh`eZ>iXGdC--(~YuimHu0iIK zw|+U=$Xcz79Y8jMwxW4_b>&qFsq?Ji$Qij6o{fe-09(G8#@F7raC`9O-({orV{Wlt zmXrr$f}OtQH-Pfg5^hszAAZm>U1Jq&i5T~*yyMF{Bl^w0-vcn*JK5h~20%O!k5|Al zn@=Ss2^S27VT-Dk(4}m!MxLM1eP{At+vVz~V2h0_G%DCj;hc za#-^b?U6i1%n&zA&3)gbSyp(KW|hj-R5CRqs83LVxz&!^d#tr)&iM=v=C*YE#AXG@d#*Q8o_)DOA z0rm4J$TlRB{lE=^n+u|(6SboQ035e*LoBh5ff7z5udzS<%x5aw6VG$361Oo^F9i4~ zm3=wr46}|;0xnC6CnqQTNh)=9bvr;RPb}KO#2Z3?6TSL-I`D~#W>cW(Z66>3>bW`K z^#mY|Z=muAxyNmwCQ?e16ajsCHdqyjlrqqZ&o3-IBvNMJ%~F++!CXK&1fNl>-0Vq% zn}FQZ?x?z44j>4SF-!guytx+xR_FINV}%-k@xDG$mSKTjwKIfL@gX=*Dozz{q2T6^ zQ3CN;n&PwvMGZ*URu@HT>$i||ib99`ku0U=OF735FWG& z`z~GJ3Mee~Zo7iCgHwdUgNTDb;vy4T+t0D*a64Nrpw1ssf_sArU?t%X7`jcWx~c#s zs<8T9M-PWX#@FW&JXVLlGKmv1pdvEUPq?aX?C4@yWFG~Sp&Hc-h_sy&PE;uu-r8p= zv8~R#KYRin9bIc|1b*9aT+euwfDq4yvW?U@;fYR0&q1*2?52)y+GokEwX3D9P6BLbr**ZVm#w241oj^C$;TQU#5niH{aZkoyJ}HBNhKl)7 zFe#G5RE175Nu7i8JFFuKOfHLMg$jt+zc|4DPY>C_B#!zY;6D+l_4_CIf0**-gibsX zh&A>M^w6WKZ`D&@F0!U1);iM&2neXqNyBWamKP62i~GN$Xr{$05&#uezZH*y9x1F!0b~qltWX&JIRxOe!fV&Oy29rJ*!L?V~yNY>g=OG^nt%pW0F-x z#Ut}rPAgommRgU_rG9_UaL|Oy_cndIwPVp(2WA6f0hM=9Ro04bDr5kM-nE`sI(>W_ zy^CiyrwJoc0c^S%22#ZzO{-5iExg8gnbvzzpSy!G-_`}&JgFr_U_V$4rljdMKOZSf z@Q%no!*gL_bKzlcI*+*P9yg-wgyQwGYXD?Zj}|S2uQYiHiK!WV(MMqG8VIHj$2W8C`^r`5@;$KACc~B? ztUT3Szn6j^jUapF%i$=^Vr(OcoxSJ>->ZY7(H$n>$%Lr$3F5ON?_$rnOv=H5*_s?g zp$Xs2V0A5|!|G)4ryBpKT;k5&n zXO?a*6`s`XYE7w?Q;nBAs-+~q6EB%jTUl=tjTIGe&S#mzTWpB{Z4CLy~&A$|Jnz`?5a9Wk@8;}5VC9G z3dkb&xjp~V+q(-UI}Xc(QeYcwisYaLzKsct>3HMc1u6fNP+BauTbLirX9I^|h$fg2 z%hZbPSYa7n^Y}CB>RXWYyNYb_6-vF0_V41QL|PINexg*LEDm z$o`yP?AN{235UWC&soND25&=7((7$rys6D|!=)a?Pji&zx)(R_(1R`Jt9`NH!r@BX zl~U;%O3TUV=~|Q|mO;*7-)w^#DfRXd#RAq@HSpF!PtHe8A!8f`E@LnQKghC`X7%AY zei}Q$5X|&rAJAAk)3&(Q#ZzQ@y6c}&{rS#9h&xxx8{kJb%-C^s=qN79GYuHmd$ROH z8!nyZp%Qv75=gYO%_a;kMH&>oGOjKE+E%!rA8YcNa(;Z(D)AJS?D6E{q{ns z_{Zb)QZ~8o8-(aIc7+hT8I)7Y$(bB8!^HY?4fNq6IR=hly|^dJAC;e3AU%Dnj2_p$ zQD(S(Q~m2L&m+UWQO(b~KA=-_ttW%uJ_OdX@rZ8Qp7!}NJs-69{VomuNl zBHt~1b`U;u+)O(MfD^7l7hKS7DP!J`93uYHIw~Q4OX|B(J!nXSGngM-Thh)AKuRP; zyjJ$q$wFhflylk5C6=GU4o^+m@2_FFR8XR6REV=$naBhW-OhHy z9Xi|=X~ym5kb9%=3wE~0eHL!G;4v?tpS&dyrzXF+QE_-!-ns0(f`^TEqP@BI1{84Jqo z=$2%nIdQ}$A%B{$;zL;E#1Fc>l9WJ3ee3Zw7BPuf_7G3|GAeR)o|PRF9iA56AT2Tg{e zX1s)ZEG!|oU49sGYVzV5IqxPR@bnzM_^(wO4FiSOb!+KR-xFB5L!a}e2sWxXAxnj? z+^6}iCvQR(6b8_T?@BR1b$5I#q0rm&yi?IxM#kP}X~%VI8}0vYG_w(4aAgzK14;IU zluIXun{lP;pk8xjmgFPOnY*a&1%H>Scv_YB!? z6j!s&=s}(3|TYX2u0(yD$V8W{L1GZ6U8TpaE@YC3vAV)x? zv40@adw@tA3%ypbml$szoub~k0~g$?2G$gH@Db^SBnN3XGBecX7iSD*X6Zq-D;O#X z>Tjo>qPO4B=WQDw{Z!)OZg~MUobOEHR|jVpT_d_`UU})(x8*xt-aV^Msmt0$)NT6` zO8sSG+*S6am?m`m9@^;s1EG7RE9kMN$4Mi;ZGq;Z&&%yyCVM*K=nmUHiukbUan?e+ zqP0PwB*$i!fuEs+@ab1emx-|I7y@h=_5Li&4p`SY(nLjwXWlt%6qA_uM-gngD76(H z7+81eXDl@|{2ws4*T*63fObJHh}MhWPfYGO;-nYaA04p5eZ5nVzw4hbaj?I~_HqQX zr%}iet+qvaoYLRGx!@Ea>JzIDEhng(UlzMFxQ^z2Y=5xDHDufs`2`Mle_`3a0}86P-#@?<5*0ql$Nae|pMe5O6=QsK;ZF5OQ(!l7Qk zBq$gOEF7LbyJ_yEC!fZ2rcD&L0Z+=u&VO#An5b`fqJ&@xa5F>QMM(~aQ@N6Dte1T~uo=NGV#G12d-w{Y1nbUi3Oe$^0XP?*oot*w{va58Elj1Vbj^?fhXFi1(d?Rg1wZ!?YZ zGhC8f8N6B^$`5nxI3ADUX6To2kjYMFy>JXs)$jtKkHhew3KM)f_aIeXhqK|ZE0k-6tj4qLS|z2z5(Z7!+m z=ay>QT-lk44p0BewQN6zvwY3k_;&mxC$i+G`~!Yb?2%Nrk=rUyE`Q6c?L`V5Sncy) ze*IqM7`OHVxfo^&P&>#!+&>NS`beB()7mWsg~JKs9@FmfJj}sZ`)L2obS7uBc1GKQ z1H;G4YnO9%@Bq2Ru0jqvs_-(I`=X9bo5-Ep*b>q4!DPOhTE&EwK~r-)?`}Uk?{(w2 zgXi*;XY4QVyT+hpPCV)h&0J~Pd*mjz!a*XwLvIcMYMhmE)N5AmV&SRy>ccN`L)CTq z!qdO|RcC@;O{hKDJHRb}k7qyEjirde7?(U0a(ZLjjnk~1waY2ildZ14URQqM`FSrs zZ=$s^`_DTwJ=5Gr6QGK758#e8Dz_xi!T@SwuiD1fbU_bxo=b4t0SV2|pLdM1JJ(PV z5*(XAP#Gw3<0@i z8DNGt4OORo*qYf;K@hl6!l1b@DAkRSOO6yNrHY39?xJuIH97PZ!Rz5m7XNix03-k>4<#@FN=PX>51(oa}8KS{lt^F+SjOlq;7*>o5>xlY@0Weuay8Mmch!s84Cnoa?#A z81~2WrogzgxF=)JopB}NIk=I@A4dTXz+==HMs!7eT#tzJD*3(b@NEuni^N`xx|)$N ze05KXlcvmYvb=Z_l`^<}d_2v#8Q>PKH8yj`Gr3P@P2vkY1(=?b4Dd?o`1!=g$2(cd z(0c4vXM4w1te_>sr424zuLi*UsNcC<=}76X`sXL#6a})@*Cxa{%0#iA^~~z8DiaNr z9}ozzbdaBFH?FWo?{Tyx2+M`~*U7~3oCRY>lKk?zev?Jno$$DC^f5)Q6FNf`v^HMf z=-1Gg0|fRT3iZS;`tY+DH4ZzW=A3d*tCAAx6*HK3?=ctjiDUaT_sn9x(5Im)PT9=F zps~5GiZ(6{I)uxy)kzg;RyNH9)e72q%F5;!f~1)(v`ck&(F%aok{Na8qB8_a9HI<72cAK7`atOm_H6`nW=HkFS_)>HMVipWHW z1Iu;EcmCD{aT`0UH#S!9rF6=8lbiv+??Jem*R?KRyU&voBmE>Y?~F_qrMq!ohCtE!+%zCk z>^l}b;U07iFTJ#F)>m2O-|Y-wRj&<_7=M_ZlgdrcbjsRCrz#})7o+wDOCE(C>MAm< zO|jxs5bj@A@w=#)EM`a3|Lo{N=7EyS4)>DO2y*6{6vord6}k5P-**m%)X;8QbNu+) zO>6YB7#$;XIT-m^+Dsb)5uiRPR?}GtzID;?svBxZ>cWa zBFLJY&Q$9k?a7JRN2xH%E$q|nV-*oyGp)D0pNs5#xULxa8uiRDUspfl$MhzFK^)zzGq&#~1GU+UX=3p8-MiE}$% z4(+hYSl3CO(BE_u_GivWD|y=zvC0;yo|mKF+S22j@zj~TT|3UqM&?P25+AzY`=CEqT!d|<#_5O3mkzociqLj|7 zgFimu7i^zj`5uZqo>uB80!u<0SpVt1(d*CQeKk1~z;fp**Tj>8x{UF?w;B2^*wth9 zgzfAa6?U6Nz4yLnUZ&G3BUZAL*Hvwwt-evsfu?LhOYVna80ga!0SUr$!1XUMsNY4+ zmrR;<+IO9N?Qyd!plkZtGf>mh=ulV=3a>GzI_HG0rV9hn8{Pgmc*nQ?|-s<|t{I4Kp-9oF(Pc?;RX)G@!dY;Nd{T6pm9-M#tkfT4^am5fv(~^dwc8PX*vjSeITU%Sxfri63Z$>M+eA3`?bkWk%V%IYBpy>eY zki&L&x;3sZ%xMqa!BJ={j;}?0flQI-DCj^C17b-o#C_xxN#I^qOSWTzz`bC!*yqQQ zQTWip=d#wPOK|Hi7{0!V^leuC;=UnR*BleBvl+LO{Um?)s~)I={6^nNufBMPHPbXN zuhVb-ZvOhygVS(Pf^fmAQgEq?r5*7KL=XfFirblcJr6e)i|2yRXP+JOjE~>784qnf zXh>z~M$@BvVZ6b2(UIGbaX48tM0X^nSiQrXG_2-)e)b4ou6+1nMG5hvRf`6vuT3dyu|p;H zrJ&VSN-DUHZNJ{aqW5tr#$E>eS%b0ks2{WYl5-0qc_EqCW%v!Zkj$o9iaBCN=$Wyt z$;v@P*Xu*^TH$BzXR_TWE7@p%zq`NLOd099n-XNYzpk~7@pQq-imf|OCbF^JqB2Y` zUv5pzFZuX&>0x2OcT~*WM#gYuK+O>8fs@wf11GgE6376CX!)9>wyv8BA%nbl5b-dl z)C$g$(LQrO9;+| z?z`q53@3sg$=7}&lYNA$T`z{{5zz`9zXg}msO_?@@a|=*y2t#FtpvleZ0>Q2_H#&2 zz=kDY!?s0wRy<)9_bA#j2TYZjZP&z{f{feu9H#sNouWG`+#4LMatyS6 z=+3}n|GlQ+WN~rv|O?#W%y0L`NA4VDN9RSLsJt;qYlNl52{&-PdLx250rbbK*jB0 zu{pu^%BbFSgZ87*IIwq_V_FosXoQR|++Zd-_avQsX?RCSR4|%BSrkoW0&{xWW=sDvydVuagVcH->paem2iphq>XI42gD#aUs;E9f)}eW1fa_pDEdY(iDUoAR0W zLnW+Jn7sq9Skq|Fh~=)L6dIhn6gB<;Mw_FErD4cqh}ce&5V#M5w0G3u<4BW#T?V!A z2T1^8Y&Qn)+;TX3`0CWtTOd8X=q-EHS**&2*ej%N%qI$e!y*kEg23;{Y+`BkN%y=m z+-_1C*OB-d;DOJaN-G214aVH|8_NKK6Fs9-0QIWzno*9-9fxPY=c%-ym+@ll>Sefw zm=|dxUo1$SZ&M^~kh;r+S4D)C&p7999n>R7yW;Bi#{n!r)T#SPCH#?F<9%z4KU`cs4UKdwnJ$ayRue_lL zgFBsLz;$>K9h&cQ6#TbeJTZbLuCeX3#Ch9{=H+JOix|#2mkQ#_pMdLxaEgld_73tL zDow9HABE`qG*Ve;%~tGS)aq)99x8d{S5K}txvgVsBx#9&Oh^ESYiGi#-glQAr89lukdU#nf(_`LT1oZ)aNQT+7HmcJmU%lKWol${bzlX<>TA5)+(>#rMPt!uqLH zbbv2(+j%NT=)Fb}FF2JHHPe3SAG)^LS@RWXetv$*FoF1}Q3Sq-;Lk>#7a;jhSJ_~; zB}V`2Yd^RHc9u9=?ro!R-!?D*5`=UaJ#iQz{6~Q$l?4wN~5Sqt`6;r=F>G7w)_Z;NA-J{Pf!&@y;;TdbTGVJRLB-G2BIiM+CpVuHuCo zI@6Uav5S3K;m|yc<&$cmhTorPWxotKTt%GMnea0suz4Fok|4hs96|XS@8dC|j+_Xv zfYmfK5V5eN!5jaUL(OXc&ZPo+%V?}z9G3rvuUc_coJOro&~3-68J7l+GpNc*^j(Sgg_p*;YR+|JQ~WKz zO+Nlz;{A6j-*4h*Ku}L=qo3^GJ5Cq)>yQCt`tNjHqkopb7(u=yV1YsNDPC)1N88X- z+GhyV%gtg2bavKmL_FqRmL)pGPXMHA2YcqNV!UoSMs3j#-#)Q(Da$HZ`M_NZI%nKO z2?TE*bC^*t4#)q_@{%Tj^`)$BA+JBri0{F!U-WQxQJ?#?{eO!S7xk;PCWlA=C$#ME z2k?$R`=0|GG|un~EdQ;>2}hdl%Kw8S{rf5THCp}=y3dZi@t?`;zh5lB1N7t>AdH6p zw>PjiB6g?$=}o7tu=~z50wy=Bo*!lfp@qTy$0-;_o|C)~mUU4~j1B>fWmDhJ5-$jp zipm|B<8xfLI~H*%`f*J4MPgpd5t7J5ZE1b0E0KNOPvjeFrSu-s35Nik8^(F#5n}&e zaJiAo`=QQ@2Hb|N{05(PMhmLM@tPdB;|4qBp|)h_!tJRtR9Ll_juK(+Ija*&Sb%3m zatU5Z=v}GD@dr~hc&5!YuB=5Kq!uw1&h5REYmCv3ob+^`%2LZXU@O?JuQhHKE6%)i zUWt&0%Sv!e;xxKXGH3=D%$3&AXc4*oK~rg?<~xc5=OOa>^(UmgY>t!GEs#ND3Y`Us z56*SHQO|Wk#SK-Rgo)RauMFX9pUnb($nPw$snFwIgwS`N2%}a1ff@DCYS9!O>8glI zSF6sEFIajQvpS^)oN?>(pj`GLPLUm_o220XX?$+a$EvYzJ@n=zac{fsLV=f?*c+c2 zdt{->`c(aZnPkPY3qQ&0mW8T!-5D{34ul)MZAoL%A?EZA0Xb6Yh)e4E{NT&dtMY#6 zR$}(Nb;^k{!bDjg*krtGDl$Z*UJ~tb1dl6!XBc~w-yJy;w*fFSrCH34x>ySKtTga6 zuNotHJvYo|En}qsgGS7E2t6GzP2&TE*$p!lrQZ};w?!a9r0#}t|0k~Yh2H+hOAm6% z8M1Kx5^?o#uQ7r#IOimZ@4^wROonBZsn|azb|t$|}z=@#%ka zGASJhtk0yIa^1H!vtBw#O+sk!G4X43k+zx^?G@*9#04!nZF^^a;EG9a8Kx{BAd`Kn z_oGzy5=>5@VO|teP;J+zWfkIutH9?+E#|b!m!$_Ppy0=efD91#U>Uet?r2)S#h{4n zEIZBKXJ}_xzO*fXaxG+rY^Dbv%(1+tBbg$Qzn6t zlIP;Jyvz{-5kJZqVZ_$)sYDQBMzJ8PDZ{yBw#NH6+1qk*$Y}|oiEq!%zGqfGt(^F zLo_sr)Wh*6O>sYWp!Y4r2WsPqO!My!`b$sO1cRoe2GTiF;p$>Zk$B@-dGgV2o?#;q zl0{i2?jI`H8%38k%Us#B zPfoC80U-WrYoQ5~tQc1f=xsF<%h6}KBahmn?-wUiJsfM)QJx*Fvx?k|`HG$Co!cmC zreIR^x-OsIhxGHnG(Idw?5307`TBiGV~Wr|=86XdaID=ovtK&M{}*H2H>lm$oqh{J zP<|F~!m!LYdW=3NHF@{?+$mZ?Gd#ePXWDlHk6|GY$lF$GfQMou}UvJCH69OojEGDDN8AkOQAh1|FsNWe{Gq2gp#PnC2;-r%Xu{ zLiji^%+7AAllHp4{Ft~R7&7yOob~tQT~Nv1#3DD}r<*_qC1^KKTRkn3;~gI&E}(AN z81?C_j0H&QvMI+tz&lAdSUB?BPjX#bt0-Tig3SyCYKxX?q=iy4@eX%e)8z#uxm4cc~XywW_-Jr`Ec<=3cUp1dMjZl-mn5h7{{zEE0ouvR<20r1o6{Lb?kYVAL=m@x^3 zJv`+xHls5wS!ma6kKJ29s-3dod`(gMQrMA|71Ur)wW$qy5*DRH5@X57F)27>rB%7 z!m=@Tt?3!7;8w)GA=mABu}M&+UUONFWT$~(0P|)tz!4z(@=s6^k3`zeCA#TC{D1_r zLOjfwrFQ^S>@P5GX}$@P6ao+KFc-?NNlaxL9Pck$<7ytu&d!!s;}4EuOY8bP6X!?M9$>TK##9e{ ziCAXg3s8RK@BzB&LKfi?N_#Ay3f;#L9vU$tjx#I+{*i?ax zg4w`!-}|}Nkhr1E5|JaF+2=T;3qV z(PzmIPcbF)9&Jh-dQoKhj&Ekp4@#80YnKyz&3Y(p=GvtIp^hoF6XR1=c&im&TySFM z!?4)!$1Quc1KGuO1N1zkdnLfzNcJmOM;&iytvTL4Os^5}rLFQPCOX^YGN#`BIwYpC z&s^EEY|qgQc#jU|;%jKlHheG(sFm$Zf_n9o~!kH6!z8 zwYV~9!(pwe>%+8uvuTQ?`5DxN!_MCz1X)NbTenUa7Gh-0s_75>;zex1ZgL6WaacLh z0r!U&NFh1*>uc5;xLQO!v2M?s75~;Vu3NHXaRo_dNksgO=rx-%ly96`UUaWy$s}C0 zxT*&nSH!m-`O}B}DbBejE*<)G8+gc)FGyL48q2x-ic;Vp zb%zdh!kz^6z<0A$ySHI(qPmyQ(z?lP4JY#NAS=q!eWZ(8r{zpG4<4JFIlD;%6cRFUOVGisVdeTYRPvC9-VPjZFu)DHKm;eV*i?q zM`_1YYqD%6$D0}=cb&dTFX0vuL|6rE%Ile)H!s^5{VCY$LG=BoRbo9wXxN@u2P;a* zFn**ZL=yyHfuyzj(TI?sptnwIlK?aUv5W_lA*big^Jd4ttL|bNxsr}zr~>oac!BQd zTmza@5P~Y;s?zNG5TaO#j~8BMpro;|Z+`6>&kMWr$lJgWo&hE@_Rrqzp5gvPdT@|* zroM+Zvag1L-4){F)l~@Zf0Pf!m)E^~#7?L9&`zB19Xc<@Uwt31nh2Ipv0~w{X*3 zu?&F7gewXU$SPD{ueRQH>t~3Sexha>07_Kz7O#X6Q6ExAory@cXB%gT(};15Mkf-iwHR#&l1>Cj_lP&kG<%wHg{LT4@V{Nn&aeGGtyI>|aJGp#B4i5h>< zVhv6Bh})BHp~Jhj7j?l#DeOGDrZaj$oX-~16=C?OAlg%^ZCSJqx=(-coTG0LIviROkJ%HHjphi( zgi-h_K?1-gyf*|2GjfO~xpKVK*>FUPZMu*4$3 z%Qw&j?mBSi#$8NpJp~}wkWo_B2cH#105p%k^ZVtjNMm>%MF>0+j;=1YMD{$3)aj^e zrkDY_KQg%+hfh);5<=ZAjduy|X! zkxmiWZm$Ww1zwm7(3Z6sr<(ronP)K0G+Y?jkd2T3XLp1) z4<^mV3G^3o%=<0wyJK;kdDr=3Rn6~&IJ($kksCiO2Iu^m`vdUHF;D(25LfC0+#BGH z0s`A)?WfV6ZZv(mHS0lsnor_H@F3Jw{=vng+=Y0xM|k-$iq9fo`W)*Xmd=?$OaIb? zH|JRIr;bDPFx~Mh3ZPLpMT;Cn%w$Ad+^G$h&K>M(xAn-CS1EN?K6gAeT8~xhQ$JZj zow!s@|ELb%?Yw#Q(IW>L>=DE6#%@LKHBNCB#9@qb3Z2D0g>7P;{RY8-A!3Hj;@ zP7sj|@p!eqp)t0Ht@-)^sImvf_d|ED*|b0Azgt(xYp8e;8O<=akL~_4^N$kMwwU|1 zmhg*n85&TWep)pkQ~p(|$nCN--Q4;sxV((@47yUU^NnV8g|(Li>!S+JLCebHm2s`K zcR#2|NuUIIAGRh$#MeRA&_F=$h=fRt&7X1$2!?^wJO?1~^abH@Y5^1S07{PAuiIrH z2px)JDRAe~sPIUbpEm+OnH1E|$RO=HR}Z88VDm$Z;t=IY5T@@jgyfeB!I~W+Xb!G! zLY`=12fkNP&L4TAiDZUY#{g;`dumI8EXDaM$2@*$dn|@)YFREBrgJ zAi9%Upj)GUz(~K}6sCcst*;j|j!Ia2JGc+pfRq3iA3h@V zrxJ3gZ32{#!1=w^wU+@7Ei8A6`N0i0zKoI@qdYj->V%AE#ZNL|64G>|Vy4+Eg*_W7 zV(tA@!W^i(L!j{K*G(#u#D7CNKl>SB$ygGc!(L(4ASSoevtKqprkiwe3vz1o@5Y_q zI<{O?2k;WV9q$xnu=8gQl{!-*Hu}65Ue9ccte2TsNd?ji;ukWou|1uzen5x~Id#_4x|M6pK8;V9L_{0w4s2!Ke zo1#+mNRIMt3yrcWs$B1>u&%=|!pYDMOLN=1p8Y(KLFLc0hW;#)hZI79S~4POKDpjR z{B2?6B{30hV!pU+nmq!kBKd>ao>0|)FET{|#Vr40u_2kl^Im0!FheFbtiNAP!9t=k zd((CK?EN?2(F@cL%c7O}rb4Uc!~UPnKH3-^3bt?lm>G;|*wvTk0$+G7B+n5(ZuY-A zs}OIw$SuVluN!gOj=INY2VdumsQxKe^n3kLC)IUYZ~B(OdHESjW+|tx)>J=1phDL6 zRg)>my((KlSNLx%qVtj_O3tD?C%Bpm?S2+l3pCU$L7;dL`jG-qk2qn60f~cDS}4n7 zf1w@!AW(Gv7R1Tix)b*PKdE{CjSLEQy;S}GlS1Y1WmDPEKcxa7lKwy}{!3ov|3@uX{S%$c<+MIm$GXQq`JXqs+9-F_ zWa=<_amk)Oc4>MVpXu2H$;t$QrK4!v&rr_K8Q1S+p&XHx3krC7D|1Y8ROhqa5wW{|)g08LGd709)u=cw<#LfRe_D5ZRd(39)`<+{EJBI=Kz2IJN=XS*$X7E%7n_U9( z^y_C4P}t^Mi&~4Efi?tc+s!WT+yn)hbX{U^=U?u^YWm$D#i@7YmYXDbhz9-3MB*n#Q4@HUslw6C zcp(1_1R)IPxdtMpFdMrcMC&)w((ZQo?l zLG0FXPad6qeMFa`e1k8_XCkKg1$5~mSy&f=Fv0^#W<6a$_DV&;6sS>Qlkn+|OK8be zPT1*|oKd5|eN@lB4(!_7b>lcZwr@kMTKwG_hi^AuZS_)=_H0kShbyyAn zs`W6pgwLq!DbZRTzE>m1n7t)AS0#&{3*H+K_P}Uvqtntaf?1qf6xSg|6Q+IDWhJ43 z^Wxr9L=4@O%qN^y&wdGCyTMR^2}T~m_aYn=+Igi%)ROHy`{QxvY*9RBjt&7`*mPhX zvep|HKmA_W|7(rnWZYT2zk8PhGbe(8l+TD#u(Qov8OKrj{L(;6#*AF2m2!$Ba zEYILG6NYVkE4*6^rH`~TWe?#zp*Lc;iUKTKpA(R_nZjH{W}?f>4?2Gtb?}sbmwXmI zADv1p7)o+RAdzDT%WV5DaKGT(?!LEkPjm;!cumRD^Z1@HZK9~V87drLFKUIQI<>e9 ze-x)?&TDAA<&kXP9?kOtas~*vO}@RK+iOYd8PMk~yPI%2;Gc{4ls~Z^rHY5*fb~ex zq99ojLv`i&cSI#1Z!PpfQ6CuJJ&dSuMRPLjcpB|GF6=)k_%s};&m$gG^>{obRD6ES zAR3jpg(QMZPK|emdO$bG#ehW6OWH8D zi7>q8=f}L-HcMzk(`)iUx+ah8q_YZsAK0`{#JUvf%Hw{?4J&o? z9@?D%Xcc`N^dN>$o$(ya960+Ws(0iO0?HI@?$VoYv@0J!+RM{hB|;KdZT%4WGmB&J z&(53i@`F{)76IK2*e8$EbPg?xJyym7zVI$6p{|gzywI7Xy+#G?G4btUq`R1Xiygou z?O-bM^9!DcYp+O?T6VB=DPe;O#0984%TiiufD!AT8#ktMS_)>h)VHVB50y(3`22J@AY1oAcr9t-OZj-yA7^dHXoyb$Fx+;_VIp`;(P zW;>o(%`t`S%C?xF|5JKl$@AhVJ2SG)29cPupWH+~>?LvR+b(Gn+69hn{g#8Nm!mi< zd?x<=x|Div9!+yrK036*nu3=+PeR*In7jqG>625sa_%{9KhFO~%h>k6Vu%6;83WUD zq|i9U@L*_P7rGG(aY|{*L5KrxqIfiB)TFa=>)PPeU*gC4bq%^J$@u6!=$AC#H8asO z2HrWyz`X%ZY2*IS=fQWu$jt0r?vB0>2^zN}F4vJtMk_W#P}KtDYk>db9fWael)DY& z;Dao)!C#8cumr0qKEo0)BDW<&2-Qmf!^*_sqFj;948EOYa}*cRIk3M%5v2Rw9opNk zFI5%U&h1PFa9w)v{^aQBD4k?to~qTq2yL8u@<%#ioF?VdKVul*yKXa- zU}63Ls*{6}2zSM(6B52`>@;qq^WRV$UIzpQ! zcoxlEUzLInG|M-GmLeL$wxM!VoEz^4E&KE_>p_D4OS=Ow06iFmq@M>{|3NK1cUVbt zaYr$QEX)3sZ(4@mk)p(JLxuStLpryAW^U#`$TA!i?7?JY+bozMfP}geQs(Pv3l>^%7S;4B?VS3uNoxtXMYSnyi#M;cYZ~(YkMT1RJvmegSZLJ3nx2d zho|zMP5%L9@io{vq3(4VSh>p&Ip*hKAb0Za#x>fk6;z!+a7B0y%gIW9r%cJ`4qKtk z!W-u??VvA|s9ZLusHy6hfR|cM1p)L0TRB6M01!ZqDCejPBYf^-_+0Ucl1_TFd=xa} zX^hIRFh`ujcSt;vBwC0%?Y7RoLT^!UbcNMFlB3!SnpsY{!|`%Lt0Nbk)X$>+eOjkl zog>7Dg6^m1$0aBTZDouR__jYgZ+%mbZN_|q4xj!{X5F3P$aG0;iFQPQ3WoTsJ5Ylv z9&gBVm!487KnT6yvR*W!e)pal`>;HG7(0{s^`(X6ZTZw)wG%_O{``rv%jC4Q0X%Ps zy~*3C?|%W0tBuf-OIX7yyICi;%1ukDr;yiE!bU6Cwq`66CrM++KHyF&k?~8rxiMWN zY2J(KkDQ4vvq} zgaE9gq@;L*6I7F-ynhT}^9U!}nKNIUi=oey!LBGsCPMA(y-&o3zw9UB$(d!^Lda>s z@MTswq&za)b60xPBgFH?6@GnvmB>)dh`A8L zU3Z#ZgBu4VHRO~zn|eNHKvLLsUGI(ikl~IMrs?yV4X}NzAl^EPdgIF0o&-DhUtbf~LaEUQrV~6DS zx(o&7Ey5MK(%UQtV3TrPhtIJy?SC+rTv-bp;K)@TYF{$IT8E2zDs&mjG&st!aJ$Zs zezTmU`n!Ro_&ci2oT2K@ev>gA%aioi4?ZY|-eD`KMVp1h4_taMdHe)QG}dTMj8q7} z%kp0&3pw>hC3r~N?0NNXz<5YnO?r*`ztvL|1N1Utu zuB%=bw&0X=g2+DIl@O&5_b)`<0{V+?1=iYvBUKcjkM8v0!svU3AZ^$MCtbj6DB(XP#2RONPoM0 zPbyAn$g|OipZiBi)jsc{>h(77{*o(#o7zJlsNhi&dK~&C6dk!SAt>Rz?IUwo5z^=( zpF$*+(k;b8L;H)T#0OE%XlLuk+vhDbN{lyMzVm;e7IzmWlf(pz7OpTop$NZ;{}B&{ zkJARo0Qv~KI5X9GPqH>6(ryi`B#Ww&j` zB3A2SWCceq=Xbwqf3ETK@pq@_>?>jPOb#sdQj;*7b)C zbd)sDAjA=ZJ7Jj!!w=u@@1@sGrq58=A*{mnWWg*cq_Yo*Khv?iz5Kdzs67Byi?X4-hd(WJaWBO^BSDD_s!TA; zzzPpmRf-!;Q4F@&G2$iz-qr0v!Qk$#kWdbVA;)bySCgR-S2vBL6}mlJS+}4b&nWUq zyX+c7E5md0^dDH&XC}K}O%pwO-epVN(X}9!enpPPO4`%*77SZ#;^nP--9EW{efDNr zMFRKqT#AKlY3O~|LkVXnzp*;iFQZKf6)Fk+`%N@*)LGSKSY_D4~HNOnz z81&2sU)E@XkJQ6Yo(Nnp`{g6PG%LsU`Kk0zS;-L)NZCqXd~n~kDL7It#=sysAza-! zse$904MD9Yzm2Swp7o7ujMolVacB@oounQeW2j{!FiDto*B?dA6_;{4)z6@-x!Z;} z#I{EcYnF{(oij}AYk9cEirqkO#5zjQ`3>5e>a{s}I&+4lf0V2cxr&Rs>^}Xqrskj` zQle++F~QT?+M9HeT3bhNLiWjLlb*}ul#%;B;bCFVhle#F<@5qOJBdj?4VV~iJ$O)u zVy300Ho`7#U|W}#%+%D>Dl01y;AW6fRLojM+1lIJ0XP*J73BjlbojVv3ao^A(d$=% z^(sM~NyZ1~Y3FO)lW28M)J5)!XZz?*%yg3>#(VoH=H9edd>dQldGG4gz;#njLFQJt z;imz;$BwmhmtAW)XYZ1@pkI@>4(}CTz;2rci;y1-c{ZZ+*yt(Y9oi&6WjzfS0~@co ztJ}vMF9;V2pPw?RXS>($6j@MCnZMXeh*0CtdAb-kVzomdY>;hRLti>2K!9?(Qwhue z4p*Zl_rdz?pATI!|!cZyte zl6Sj)lz1=_w~)sAaHVl}l)gIrw1>E_dT4;^hG@uBT&m}k*$AD{Wy?Q>wj9XTDST(VoPDq}cIvKRu=y+X1$RkR+c8hu_f)|c4+cqVZbEmD z3e@)6g4a|9PM%KmZVZIQ$W(*{bBvjH4+@kA%FS^l!(rmz$IOk`CW*cwjl?*INKm6&+Dm9B zQ`#}*^atCYt#EVmU#%HqKzoQg9!0D+g+W`hiwD&!*wC}1m=<)bCUNk{;8Z=E)v#Ry zX^B9qf5?jDGl?5=0JkStZDtZK_Ai z`w(KgEv@=nI)RCR`|%!ExC-?zCvGJ8R2Akj%--1}g?%^m7jgI5zSgjEmK%k^t=3%$ zZAt%e;%vliFPP}*Kp_v`b`weo1afk6BsBc*TTrx;9%9gim{3|;S|;pepO))!$oTh$ zX54Te?<_D^2dh1aX0hFe)v*|EodZitOXKtNzT@NL$8fDrpCWd4cauGF*w6X-Ub(q^ z;6>M*7@M1)KccOz-9I!`Q(b-F?3G5*Q*YHY180yps(|NnDX`MoVO>IWDRr&2HKe?X zfAzfohP7{h4g-?V<9QHEc|*!a>7DjeNoM!M4Hhp${Z5gPkaXnt(eCKiro~!pTVRH{ zUBAVD#Tx5;`>uP)qnu8gh-)7cyFK;j_LX`!F`A~MtiB@T0lplPIu7IPhmieG<6(m~ zU8;zurmPFXIop>!d^L#j9|b)XY32|AYVz$P0gEaNdkn?hm9Zbx9cM#Jw96*(gGJk8 zj#SB3iJXGs{CMt+Q+znvI&ZU|xZ7z>u`4>JKMbblX7sSqo^-_f6XT9f4H^0@!(jsi zvDq`$_tH+%KI|eh?DoIA@487fFSLJW-+_?~iCdIIR7R6ZSAQEOXK3dVF?q{*UvHQ# zj}NX8$$c(uVnqMxl7}1peVMANZeo*UV$S=A7}NI7V{EQG--?nK9^9;<->2RSf8Wf` zGHXRQx;p>Tyfbc%9|d=~&I_&Pv?mC4@>HAj!?O&D9=8?d-YxUi0Y=*#Ac zcLZI%%s3WZ80 zrnC7P+o4nAfW48AkdMp6?Ji|AVKtj?7Ms=iu@#C6CiXlBX4xBr&IjDhd?ax5CFUiZ z7-;+|l4Zokg^0?_~P?Fc;Nh;@K0fy{#uerv263gk2trM?qwy3U_qXv!+={*lc zZjIUeTjnMli8ldC`DZRgKwWqz2C-Bo|}ncix$*n9&{{d zDB-J5dM|VQ!x!oRLkWlZMmhtdz>vJ9#*#BP$nEC-#z^ z>~`FQNdiri(6M1D%0)t`DHzLN3Q*)U4*69{HN=RcU#yu<^^ul667RlkJcY%HbyF$a zm<^Kuc#P|ettb2BA;CkX#f&3td^Miu6_9c_Ra8!h5tRkWPTkU#!D(?}U)((KfhqD{ zMxf{SMrGx<-u>1nCWYkGB~;n7^xKy2QgNM1vW4h-rg7Hb+q$lyHAla$lo{M@e`I$klUJa(b+NhW4#hf3W#R0VKUJRx0_3)mO_H|R z`T0-z8vFdO*F3+!UP`|4=i45!JQKIW$`1ef!GpTbNq_z4KfU%j@#lt(HM48!ui%(g zI?n$|NTlnk{Rgl6$z%S6I`R~Bm8Lz(9skY#{lDDT1g31CHc3BGyT5pnbZW|f^Lp#o z-;k+Cn&3(KpX}c6yK3ey|JPw{h-}2M|0l=iK^W5-HEr2zR5|(t8MFM!vp1-;WN9z-DJl~?&UeV6S4vPfrBC|zWeqQ?uIC>t z_4rrsRNdQD>ZyMI*SWh#QS*TZP-`gtMsw;^*_HkqKE7J>P2nuuyu7E+zR+KvZXyGV>7g@c&Kx;*tQyd; z(D?X3a5MV_-@3_rZ*mF?MLm2!4)B>Izke^2Tke5zdG=v?3Z7*((v8)2B~=HfW^*^6kDIf2N$Q zY*novS!hg*A7m6=;NdwnF)o>GI|0OtN=BJdn9_ zhvMuV%G(~p48m6DpiqkM%P_yN;1|po2k^2E^dN#?@k&TYFu-)CNJIKxMy38>6cQQ2 zqL?@i3Fb~atLJZz&9yZ(Rkg+m9Zn06I*r`M_gp9{^!(8&&3p0u9)rwHiXF%uXCfjZ zV&&z%|MlzFFnS5MOJ^nA)NJhRUPIo@r7MZ-F54>{US3|ZaInLeWbfqrTWlm1YvvQQ~dp|;3T3g?Og;DMW5osj!G-ibUEJ`MwZ@ezhv7EX0I%!c0W+T*b9ot=4{=gwWt z$;*39a{Ty3Ha51VuCDv|Z($mg3Kv;GFbms72~>ip<0pQ{6%FH^)rtFHTuKd**pu0t zPYFqdhAp=}JUre^ohl>W>PS8YhWcZm!#;<$8!as@cOja}$;s(4v|(1u*7cfq%K74m zq91ixZb)9pr>wJIhtNnf6_kG^=taab_TF+X#x}+x^Y-#0WZz;Wj0kIMl98W~|Au+Y| z9xTr=8g+%8Im7tAr|8B)j+kLk-^Ujvg7C|n8gz-ox8J7L| z=OyDbH7*YikNNS-UKdhRqsq&bvU75Tg@u<022O|I*~~{~?N6OLg;N9Q5w@4ZSFZ5ww6(ps`)+wT&BP?;M+k%5rcIB2e*da0yMJ_K z#L?YdLM5ph2Roy%!SXFZ(YQtA{|~Sd%7ec?yuOf*=3;Gf1_rkl02}!x6z{DRFf@{`9;E-w- z>eTSX4!*k3wOS1@ejMGCG<;&-ao%VdUQ?=)SSaJo{JH` zfd?i7ywNQ~V(n(n<+8G}jguX=rOu2JM#;e#G;j?b>E^9l4H(>^+Z3-0t!5aGucAT) zh`+vmYxfPC9ey&qR8>{4L9bo2*^`g^k3ISRPJ;y&>#JjbL03Wq5KND!Hr*Z)b~>_F3t~^z_BP z*Jxe$hs7$NM9p`MlwPdBc`R^S)eM`U=0l8ne14F(M98>mfvXu(e>kZ1mF8m9Hwp<~xg( zn}hAN`sj$OPc6*PJK|2FRBi2ea|E`O-M-z3)EKQv=-ci@o6x*VnPH)A=g3@F9Ir^_ zsnn0*3rR>=-PP4K-N@tMh~v+ptM@zLd~%8?_xSj@%CV^{6JrKZ%S#P1_)s5}0^$j81Z4?QwtqYuH}XpFf|8jop!w zu6EB8{%PNfV*Wdx{VY^(xyNd>t+jB9bKrUN_U$M#eQq&*yLRm&E(W3t6B85rI@5FL zisbWc&I9TrFaEK@@7*dAEz~X^g!&xr-j;eTBZFdOWXv3W{2sB5^h{GbI=M49nM*+6 z54oi3#K6hc&Q1=TVbMFglAoq8{H>)z=d84=v$Of|9Sd<~rb$%NAe`m<3nw6U!)}F@ zlsJovi}5^}Lt(G>dU?gd#_Rj~_^9cj`}7!5BsF5UTwlM5M?kyFYSX4o^KULW*jMP? z+Xy>#a&jV@DOJfM^y;a_U4CM_R8&+F4+PkCrWU_P2a(LIEM?h=sHiB?(H*Va>U(;) z;jgjYJ8*a2custO2vIWMzD7;(JLd@ck8%}PRaQ1%q49|eZaIK9T*Z4TL$U84K)js| z&}Uw8zu^7oO8)EYgE`~bJeV9Fq=r5_bZGK}tpt-8Eo;|Y4L^#9pyBuqbb6cd{(EXi z-ZL4Avu)Y3g&-QQx}TdUq(IjokQ4WcbWgIXuLQK=J;MpMcAAI3?&ap@-q(?_1Oen6 zU`hnA2G)NBh-U($)F>e}HCy=yRB(LOZJ?tbKKYimwnjwkjJ!OX@lsPBWsfcfyxBEM z``81%OfviW`s#kzdGy$^l4+kE%=%9gEh`F)5Jsn8d(}zJ^u7$CUq;gx`t}-p;d)rt z`Wj07ZEo6?D@yu4N2mHCF*b_DM4SyywKZ9u-XZ97(l~Q5+|>U4*N0qReMNf~m*>~5 zuvHjLyZF3uk9edkKlL(vhQvmI*H$6_+Xx3ZJUV(hBSWb1M<0DXx*w3{udaLd>coq6 z7g#LQ`Z0ZaV&|7qd&t?Aiys4z#>&EC3Q&h!weIA0*_<(#y*X!IV=WUsB1|l~ zrXO>ei7%?ZYlNX8U`O!|+8P#Fiz+IX8J(_%nKK)Su^l*Y;ELK2L!Z%me{ykh3aP5{ zB2vpI{E`0<6PZ|`(7<>oNq?uim?CTJvs=p0;c-f8DvOCo9h}-I9*Q!I5ysex?cO2_ zVq#+ZB>JK7*AEQXdyAA})8tpmN}drj=*5A+k&%&`-ox8EeO$9}p9IOmtUUYgF|x9< zX6NN)0W_<78d%W*)wlah^{Ix1g*m>ybBKhb3&J`WTPYY3BYqixibU#shdRx2r8=JfaqA{7Ls>@)nVe*`XVL?_EJv}`k2EdH;k}pdYof;U7 z($#l)EBNC)@77r#A0PRr=^E!y5P${TRB80A5_!Abz|zE}miOQW3lke3^@1_voWXkG#FT zgR81eq!cw7PFzz!K9*1YI6J^1o#~9CJUTZJh~%xX0JUxSuaY|J?nK3mG5%MWCJJtt z0V_j|wVthQstC*F%F0SgdP+DiTjH9bK!1&AzZwb7xC9lvLvw)vN}idKc2jdRvvd+m zyqLCwgP^swb(FvM_esvGkr8K{!di+~&Yrwo6SIUKpiuD13YuA$5GR(YyJ$BFutax3 z#KJHY2{rD{KN0vQc0l-B!NbEd`T8y!@FztDe*bVc)FQI8+{41y#VCgt8yQ_F#1Mml z|5Ke;Qq`CkE-53!nY{gENzIqFD7z3+3oj&&5XS3-O-Nv*qq8#|K({WZFEv#2b%35C zi;W$$(Ra6>UwOp#ZIb?ecf|}+-`P`2TP%`9Hf}WbV{k&A`^LgfJlMsH7h#;S^|TqO zLmM;3LL@PK=@Dkm4ZnZS0vHI&w2!5VR-y*#zUYc~*n7*3wXeUQG$2{NZj+JOj)`=) zLx;{o!_V>>taUqDAUQm7A0F1s)HE3AnliN%~`@80bi zuXPCE)Ztmduf_=r*4w#r4UALHduXff2O}wEbbfl+)KuqfZ1X(dOs7n780D4w`tRL# zj_Hf$Ra}bcu%QrODaWr<{Xk<^hAd~KWMm$~=lqWQ;tzxePJGnR{V_)-wGM z(wSlJ($RBT8$G5zeYiU)0{8s#8j{8P|fn<=g*&RCL&tmU*r70%}H4o?!4yzqS)_AQgN)z$sTyy^JHq(qepta zV}?2AP8bjyn&5Fs%s>TO6IG@JMk5hIpaQ6vHtd(UJOmz0r4<4Q6g)Y9&0S;t`epFl z+qP{Bt@oSx^ySN=uY;#zAtlrF^cvvJU?5Oc*g;v*E-tl66K2(2;@}`}e61-~Ft(v# zTeN`2TI#09GYODbCx9H>!XQ8nX{XiZsgAE>cV(g-4F3IUQc}`*e*e{X-~8G!5K9Q| zv9GulfiwfeV7~6xcP;Ja2zvpzCD~z=E|9~h4Gj(6^V3dnWnZBwH1btRz5(&ZPSgDy zS9#*=A3)u^J!zk1>weI|xmAC8bs#jpxdcQy>SdB?3U1HXWsH8=N@P`NI)`#w})qqvkro zV5TAII@?#_bNt7=yn=$lg$oygacbKUWIr>@16<#(GE$GL=v_S4!3q8R-y9X@*E-2} z!y3)uwnt>R&a6{(U+&(TY*t*6(~@q}p(rn}UFP1#Af8|o5TKR{gsT=V$HiXv-E9zHrNea84}S#Z30>LBQp6baOicVss!kXyUN87r0fjl81TaXK>!38zr^oM%wL< zA2TVsx7Op$nY$mnyDC?GiMZ_h5>P_G3j~zHLK&rf9Tb*TAGimtUupV@N%7yd2mSo~ z0{z*}-oC92WF8Q3&pDulctXJZM>zPlgu-r$x;(uAaY_i;K{O+JuC&aiz*5bwqxs2` z>vMOitJN1m*?+Q;*Yb8h$V5u})if%z1-#`9CTH$@lvq_!VL9(?b4lH+;Y?TV9-?UY zF}y6zuxS7x#W_6E0Tgv;=h5(2@_mI9=$pLXgz4P-=d6_X^pG}T@hI#jZRfmEhjX9# zmp|q=7vJ=@uxXmu#zH(xu@6zr-`9g%_#by+?l;$FHu^Ktc3_pN%5t6o$ zPA~2?0EA510&Fa+J^I16k*lQOy|eb&2FEhIk2DJy1N_5cJvr$a;O zQ1|qww_4^UqFP$*hhmVdc0}59pgI!N=m9VXI^RMZ;D!=7k0E)=2|+V6Ged9QoPpkO zzqy?JMa;KuL@i2-dTHeO^Npx4WXMaf!Qj5!9am$37VjhP1q}|Xv*P5!8y@IL;fyt_ za%!B{ZaNr&4uKr!*D41L?{u*1y6L1NV_VJyBtwrL%xB0C_usZv{ABzB9q!HV0d7{K zYgB4`TU#4YN_Ir(Qv@ImXbk8aNG~bnZhTeK?(O<@nk}$y?6T>(IT?#?ss4h(bI=-M zalSsXm41L!87dlDnW6NQHSqSDQ3rkD0U?)I*yRoxlgFI%J1J$}T z$BQSc`zzpZ-!wu|6kaDBXzS(8Y&hH(3h0f2g`~bG|M~ud{r9Z=)VoA(+ZMg!vHs?- ztsR1B2Pw9j(>FNYxd)Y%4;fcwz)zBiXt3A0&!5e3Jh?N@wG4)Q@Kt$1>nj`&Zz7er2=u(qNI4+rfj;^Yh15)YRxG0J$3x>o-GxXo7S@Yhr&2^$H+N z7a%X{+__esBBLK`MAkr4jxq+asc8zmS=?owB(gj2P%FN7U$cu9T;=3s8 zVDF9{e`xyCCv6CS3^^jIb5s56uxF2dtoce&2YL#%k@#oKi`U0BAc-=;*-+wbLs!%0 zvRgpx!-KwNoM;SXWQDRb+o0T~fv0Fda~smv5=p`f8Yh1ohd@h81c`j$ zt2Kxisrh|Uk^G~}qvh%Wb4(EZ5C@h}V`F1Oqp?~b>56F1FSIFxd*jZV)a=`KeS3QW zBV%J>gH=?0M+ZAeNnDAUc$1&qb>a_>PDS_(&4sbmffx^vnZ;xQT;~2t-@|J~mmTE% zeLaP|hkbp?JLlx#5&aw0OwZ0fdnbSAe@2kFHK4Gv$GS5!mF;FRD-XFOI_$?YP*Q&b z50Gb-BkvRI{a#tU^z1e_>`h{!fS7@V!rk@l-^o#;qN4Yk$Knzb!+`B6q6EIWb7+G~ zoH_z_WMX3CVJ&*pf1usZBiII`ctSgl%%ePV{7GpJo>nWW#GhA3BCDM<-2<9(2Dw zzxQcNOM+~KqoGDXXTF&zgdI_J_3G9Nd(=0leH6|f>(6gDACU_-2SvGAS_%#oNM&SS z@J9sjd*5x~t?GRxN`tFHtMw}_whEancv047bRVEdwfNXcL68Uc9mcf1CRBeHl9&WWJ2l20Wg zS;So`$IiI?#-DwXY?qw3&bUqxx(>}70=ENswF^Jd~xNNNWfT1$Vf zd4bZFI}!G7$dsAo%*@WBQAEGOuWJRC(z={}#LH)Ai=~}9_I?)>79bDx=;&x~2>RHY zyL}kb_SOv=ejA_{56Y^pso~(`+vEPkN?Usgv`=xBv_SYdMhuK>8y!HL;_{u_h8GHK zqmOSO3!vK+*AFeA6rBsj#KncRv>eKc6M2pp@-L+_TK#0HeCwiAk)z{F>d|>Y?)bDL zHg|2S%PD*N^ru>1mN7Ce2^Lv5lrZH;!s+L~;rqW*#x;Pk%&f;`WJanzbI$7YLd` zHYte ziV6pH^Y9zPox69lnuy0DFpffI0&D0tIzgm8bqx*1_0MXN`Oy4&RJ=OGz)JA4$ZE43 zb8~Y!^vZ>NJ%XqMKTbnbL~BA(wbY)ec>%g7%gc9b4PAC>gQxEG#Mp@U%bk*W%)$!uq(Y&>-Q^ zS)oaZNl4HgKUwB&H}}?wViQo`3Sz>T*HsI(#1ZX7aMxjmIiY!Z>md$uS#?-sb``{+ zyM?xqQS|tV==^-i>Q9f>0c2f$e4HkGhLK<7dLofl7rz~-#u(mIW?8U|XVoW4T4Dq= zY=`e%zI?gWV9esB@};gf2i9LV3Jg@YF5VLfgO7?4xdE0!zcnRY`d%@@W5l_0I;bR* zb9=&x&b~}glp7I!boCRgtgX2*OgjW|kyKMx9Qo_w#P(Y)EiDfar-~->wf#dV;It z01~2pC~kci)TI|PR*GHfJ(D8qQQ&c=6)PIA>74B-+P#_Ek8=dtpj%8YwuT`5G~H^B z8g;j71<}kp(oCu%;PdtI`TJi!ygpK!7abXCaHh>WsYB<@%Pa{lDUHyr*)7OsTwj2o zv<5V9Uw3{SXnHCNjPTDa(8j2GRH08J87=MXcLa$CibA3@YJa?%^Ft;yhv7r#aDp(@ z)zv#Pby@vB4%qoA?c&o2;Dj0s`nVM-H4c9M^KeSWJ5;-Z0Ocki+=jCWuFP=VPJ0~X=oT)S*eQ9dm8PuwgQUF zTP*(XA_uoG=QxJVlId(`Am}WSlsb6g#0gdt-MPcR`P{DEyGPM4Nzc>s4?q zxEDnvsrHO-Ld6+W5LQFI>>yMB!;8!Estk_}Lro+ZN;snj z2riDUt`GUuve)3GCuyPtZrv8Vgg*U5)vBYCDapw~$c7<7j2t9IrFn(#NP=(Cfi|Su zB*Y7RzziqRjlLw7mJE0eD^F)gqh<$K0Q-u_U?c}kiCYv)|5du}-YBxg`Uelnz>S~A zhIRp8%M|5kmcSJX3JOwddE z-<;z&4}*=kG=wqVymKd9%m65>2^j^y+TlIl)fT%W`yuy8w6$D>C4#t9qn&He4VIR4 z1{u|VGCabs3zZK_g1`LrA7O6Mn;6k5lHrAT2q1j6u1*VQUC(28@j~^u1E4T4FgODLAxd%+nvO#WqDaD{rSmHOSl1b3ZxPq( zpFLYmzjS%W50UFE$H$@~(lo=5;Gu01XN*H=)p1g0Oa;n`>#e~4mzJPq5`PQ+$As3{*Dp{Eg8@;T*$3Qc27kx z4&1nanuf+BZVOb3WEy_{I4DR86-rU1L?S63iAHjuO(G)Sn#9G#>btu+B_t$(>B6w> z$7i8AM#ShVAoUPlP#^^bKNtWN(+}4``5@D4K8tqhC?F2=edyf{{^6pQsFk4tyU|!Y=O-;?z*C*$Pm$hEi za&S}=5y?E24j_Qw2DSAxgli&RZP@(5>{1%CECk7*M|W^M^H~UJp%xx5O6nG+)##YV zezPK>YE;*`^+5b!1%=Wsh*(@p_}3LIv?F{gWtdx|zPsaP-6<_ZBwDtwk&)3&$NO{# z2da4iXLKMSu&}bCe&c*d$dc~;w{xYwz+sscrFtIQ3$2R=fK(YmsAtsstJ#*A;EHMr zJ#X)uxxokzyquhzj<|B@GmaX*{*#FknRRboCM2K2z%GkaTOmtl963~XZ9*i)dmHal*!-jb^*qMkTZB;h$V()%DWEBxH7tqkqAnza94mm}| z)hLY1p=TFRKTaXiE*I3?mjCC7rZgVNhQr}=RcXGhW zT){p!_P%PUMfD4s_qGKaUpP|kuf4$ z015dt1Lw~ixCafD1s;@vBEF0WbuhL|4@7OqZ?caAD>M=r6zV0as)n)SNoI$gh@Gj{ zq#OcRj1-T-h3BWZrz9kthAPKmvYrjjtfH#wT#Pnt?h<)ie4;j^Rt=e97MRa63Q6Dz zzhBAbM5;nJ5R$b8B51pZJ*_!EL?6-|5iy|)2uiAQ8x`f`BsULV2OkUVdb}4UM?^V= z3KoOQpNqj?KegoV$IL#CQU@kx<`9H1C?$kb5|Wka;$i3NDn?*C>RBfHD$Dvl;O%f< zh(fjH(tm%76V^>6p9`?&f^tU^see<*i#`1CO9BD{y-3kjzQ!&jzbKJ2sr+3s-1wxu zy$QeZdGmw|?~$ZGI$qfHoJdE~vbQ#93jsBqW_TP~!oKn0Y)VytqbcY|_#0-+BZUOjQ3KOX(yLy}PS9tgQYil#a^D%gcKiCt|P) z_6c;yU=W`HTT4g~RT1XkFl+qhHq0xqH?1o)_jgOCB(QUIwwO=Vn*V-&I*j8BvYqug zc~WzwpeAZg^xqZvnLvgO7-WS-Jurv`s{zcffr&qTMCy5@)3i2KqgYHEc;Js za9jgQDv7EAeQhZvBrD4Xw-2Ylxh^^)Lb?&D9`a#%i@J*a&lit-p!{PQ3Qr<4(dHSZj4evCDfIm^ojS^ z+fC5IuvTL0*P|q*eE)M6SRHWse|w+X(f}TaRva8(t4f-IqPb5v;OZ!f9}pPuUjJE- zY*VP$0#Lh_P>4JaVBu&#BAJ|$;sgNx&o}?B+>hH<@O(e1f1%j9xx+!D9Uos1MqwQj zQgRQ&vBYmj5Z1}(jQNe{@Nsk${M{Pt;ndfLFCrr*o`b~vZ3fDyb3nP&HLPU*t}+Q! zDpM3@bqx0&7Rj{X%lqer>_qOtbFh|Vt=FtuM^8a;nx6mU0)3ywM4v`WLOBB2bNJ*( p{c8oV2QW7F5-5{uRcZ;+% z3|;Se`#k@>`hC~2_F8*?ct3b>z>G6@T-SO2>bzgwR+A?tq#;D1P{fJ~vKlDV@mlzI zj{qP3B9^yJ2S1M4YslY3Wwp}H!7nFFZ>Zitp}qv1**821zn`{M(6&dRNDPsG$397= znxjz4eTuR-G@bPqM^3qE-W#l2WhEs@xI(~%CVqXAOol>RRyQ>FCTV!#g)o*&rJi>_ zzrNJ}B|b4i?&JyGGcUPc#^=j5W}PFW4EuHI4OAo*ARn)3CSn6HKeJnvOZg4Xvu zB*RN)hNC0J!r6~RwubFLit8VTV-fxoQGpy&j0_bVzGof*oC?bJf*}?BXuU*)heB0r zd&7aEgx~NGRg2uYb7yUPB49{k_L_cqzj)Z_?y&R3yP${&Gv$PhgRQaXx;TFGpiFk* zlRM%U?KgLnXfhH3bEprlCT#rR91Zch&ym ztZ}yIkkQy<+5h9(`0aX>F98)D%oXy zn%A_It_&X)Lt{uq@InwhSf6j+H96byv5>{jH_DfoRw?xAJuB5wdND_p&aN(Wn%VB6 z4VFW%%u(QOoTU3?L7#r`a^;@dV37@XcKO=txAbDYS&=f>x3co`LmG!&2bp_%I#)No z-~{RN&);UOa$fyam}2%>J1=FYs;^zjZQE8m=aH94V-REJl)OLP7kkv}t2I2N_#eca z!s0x38{EwIj7&@#h&@HcU$}a8kH&SSQ3h4|ycBXhOy4lu~m)o4Ea1~pl z!5rD;of&&SXl?3kJl1LRbanjP{X!4+S}cUK^~wrQs}J_s|9DHCLXzkxvyvL%vRKfk z^!@dDWNzZ>A_1baPyjWX5zTvUIt4Yt_G}C9UUwu)!loD?bCBoguk|I{&uW7 z*c@`4E9pRY_0|xczgo}NCT?HjK{)IihdtEZ-CDMZO_%gYRtiUOaYIL-#sQ$za4u&-KpJY+*x-> z>+q;LJife+8FKtASqmRtvJdwyoY%N9!kT$;upro`a_0wEOTwP~(Iy;cwhR5N>+0%i zXP&9LeaOWJsn25lNEii&R;uwx`lAfy$jFIT2RpHa`O$AHmkO;%EG%W=q8`=99pYHm zUEBM%d+r->#<{J%(u=AsYTF=C9jkP2ng99x3>QyRD~@KhV=J(d6}R(S&`hDPuSjYn z&bTQ|U}N`%>deN0i1W&$hSt_X%PE4*gRr>g2N{vVPZQ0(`rH%d=Vs)8lBg%|sg${! z_vMToEIFAR8Mv)}pH?_adYYhCnrb#&CYVKa@&$=xj=2jrbR zX_+yZIz?gO1|9=$H;Acuuk=}?XdLm0sF;ezJj%*VjI$;y;E6yol>ANZv|6VnPt^hF$ECHGfq*E*HC zBT2JvXku|EJDD=FDbdEg8$FTwmzB2OEnPNvxja% z?v8hZtCraBXT{9G4ZPk|ZeSY=H7wF) zneuHNEnQ3bE>!B4F^L0Q7u1}srtcKz&rhv-boA47VJ6tMG9v2sn4ehM?ZdlF240d~ zwra`#-JLeEihn*p2-i;&V7mJ2yNUbA1#IQwMniKm?g|TwYm|_UwWTkYT0xsH1iuD6cXRpo;aDSSKY<;%4b#QCvMCL<5h z+_FPqp+@DZTW`61Mt4>9IBZn9xdp6usY?yOk-~w${uMM$n5TJ;=8pqhH^-7KFk*$|5A{Vy^6zO z?rPQf)3573TP%oe;wo$I-7jsc81J#i&EC<8o>0jqbC=vL$5p%!3p25lh#kl?jo!oI zTk1@#LTjq+cEQWaY#1l5U|1$OrPD~(yr(*MR5iLBIXe-%nM}a!{2T=Nt~@c6PkFvqgM#s(kruc==Wx( z^@F8#L1?{!on7vSri7tG?9mq1u8FfK!o`M3QqnvwoTDy?xqmp> zdEpLr7n`Z)mQPzBd175$r_jp$mS?-Qgyei*wh-%AbIKQwR3do3V))u?H{Q_-g>hGI z*W^F8DDpkn+ls!-TzSEIY+gC;Mdc4cn^89nA$)WP@q(#)N?-kb19#)t@XF}|TF(Fm z;QVuiGI!jOvQ7+M95?A% zZ@8kkCg~TRvHYoi8XGxj47Zx!ZJz3>j(4{?(0ls*{Ipj1URP!0*R_L8M^%Cloe#c_ z5|bGQ+cckWF0JsMHY{iZ*FV`_*`TYVm+H*z&j=G^AuTrsgRO5tuobn?_$;VVYYzxiO#+t-^gl;AD{1M zThG|dj-!*mE~q?riQN_L$RcIL?ys&^*3-P**hn5Z_B_Eow&1A3@mNRo=QbIV@AK~S z<1WNc10**46|=vPUA`4jMdJ2uY7^@MS88rE(|5dj>yxC^2tKyd25-xfXSrxUX^48k z^xffXdmE3znEi<0B5%U+BJLH3B)eyo(!!(wl{&*7q0KvjUk3#RHB%~i5ES~XSshF; z9`PKU-gu+Er)t3w}hvEX2x_KWH_ z+?8f(zs^`amHMzhI^%ljzV-3FUf+k0&ZM=K>|^6zGlaG?a?-rq@Ypz&7;Br%x^Plv z?~)~(Wk;gV>CcD9hPPXDKl5u#yqyzU-psNW+BaPu0dwdwczph*LNKQZ$l?Y5D}+!{$$Yh{(kAcirV=s zH*7kmnb-08eB~D&*W03n+TI?c=9Xbn=zHs_TdAfq^Wl}*C;Q?YKMLQke4}a> zcZdGzxTe>gIOU%g^@x9#8sM5nBfv7`0^Fe3dcr4C4xw^KQ2E#x3+kNh$ zt-CmVsjB*@#^Kh^uzg$P`;@JZtm5YVU7`}#KIj}Z4bK)J|#qy(+4*DxIbn#MO|{|8?^S6)-mtX6wOcOT}xHsf^Dd{u)tHU58X+) zc~X5K*H~hdTeB@iHM-e#G{>^9@r!92L!R}`o6lXW?|s(1UTf&`;)~uyH^yMj{r4pC zKx}cbaDb44tLxSh+IOJw-I0CYc%?59^{=%1*|F5Wvs5B^O-5;tH`~S4`jI><_iDLY z>E^P&wOiaM)I9*qOl4p!%~z{yaUGvLKUpRjNNuFmwMlPxQ0*D_TwGxVkceY(Ovr7=D1~nj4gLj z({*w8!F=;4OF9OrUpqI{g)}1qmXzs5)eLlYY1Vyp)S(VYFuLOc;dGYU9vNJ2q@`&g zHQ&XiWFK(pl{z~v^c#jxw_j|>NgkitlqB3dNZAwYPv}t-aKTbVIshN&Xd|FMu6|@w z;Waiv{4ExW(a>=C(Y#C%=gPXuoTV%)({Lh=arq1-N-fc^d*gj!ELAXL{=M6Kz7}Ve zN_16@$whA_^ks>ZY#5yKyqyqz0@cviC_1-NroZF_&?=>Bs-#`A%qxG$JC?`!V54t{ zhRJVpribkG+Wa>W6u||~T2!;5$e@#kpKzB)tm|~~=ACYjq`~Y5>Sm%kt_}JXInOtx zy5DfmzLFIkv2T-LjnO<=H1~-}RDW@MbwZU;MvM{2E2?;JDRrOTgA+~QO6Ia`{Y>EZg=-}i~MY7~Ei?jtz^M%RS5clDg{ zQ8#^fh(NC}?J)i48U`kq;JLn*7Pop@_yVr#0lWcKqx>;LpH5yK)kpTG^@5==0U{E3 zd!Nt&T|_!*pwhie*Y@kl!gJy^wxl?fy|t;P=nr(1l%|%)P$*LCw6wI84h?SQY?wIg^Z52dCc}eHeVjd%X3ONcgUwHS=Yc)LZON`uqLSy;Q{wK0&&=MTaqEOx- zFuY{4?9B*tTpVl|EU-iqqfi9Q!1XWY%Q<&{x??w4PiC)t<~j?+vget=Q|3+aduULk}NwOhZHC3I|71n4Ou+LjRY- z6YzE~9wP67s>2O#?R>L9Ix)xQ-pTg08lN*Qc5rQIpe;2|w?wmoT2zR+l-W0hLNW0} zgN`V$=ur}92;lsnFt1Z&jaG)gS0PG`WqZ6Azs;!b>+@o(i=U=|6(}6+ZXhR8Zv!88 z9Je@hUnzvmP+25@I8~hyxkCxka4yw|o>1Ysk(*2hvQJSOT=E1EvM$NO`7vL-__cW+ z?RS>GS^V!axtRFzqcLb48YwE&)Z)%L?0C|Kb;(m?b8u`YI)bN6T4UHjD995)-FD8@ z&btK{lhv{>t3W_{5?TzI?*&7YoL3=10F8i>Kb^>9Yx9e@k`Rr|(@n^I7c=nXiC-k} z`Z6HBwas{ezQ{UU>#20#Gpg}ET^RCYe|t5B;UzyJr@hbq*B4dxEV4%Gg^qUns*E}k zTMG@YU3;&1X&xQQ&C9h1>=7xMGxjg?tDUG>h&lK=HzfZ>t{)IEVe?gA4S zA}6IrR6M3JezSJztM@(|DYJgoEy<-;r+<0n&v)D8tFMe!JVVdPKHFSKXydtb7LofV zX?KY}BCV9nH=X|&Tk|a6+Zs3pS<F!JR6fT?h zPtilv>(_9SN}vf?vHOMX;pUzwOHaPs=Gh0~M7`8;@#=XFt&sly2WfXx{oOWt?mL>d zUJM_v^;7Qoe6M9Kj8mr(77J9(y{%=?Y)Tb$bz?%f4fI_%elvr}QmE`zU+u7e?A-a8 zIBexk)`rv8h*PvHQ>QG3O49bHCqH_ydp|0M&(z;)xcH8~>m0Mla{2lK%_Z*gmFMM~ zgO+QEXayWE8G1lUm4>Tpsh*4q>1dAOi)#;Zq)pmlIe~RxHFT|qrGqP|-eMmPbe4l6F+OKg;tk zyfSZSvZ%j06>bpK!48*IlCM*i=dvQ|u^7ML5zOP%|e#fnyo5e}qKN1am=y|ueoG{!YBFi^-cBU{RT zH)Z8A;|^E02Z8)u`3o zYU3o}$TVHR$kIS}Fr1}17SFTy^99L*?ow+$9h=!-H3s*7V=l&Asc2 zqN6yE1w!wEy87-ciHj&O_wS! zXN$Z88Rt3p3IEhZP^6Kd^sk@u4n3?GB_UPICpzU7W_a!dnyhlYRSfCLLGRx)QLw5d z`A|uJ>$En z571+kdM3>ghSSHGI?YM_InVE71iw-f2p}CCt_&*$i%L#1-9%l0&;~RI4ASxx6cqzA zGOp<~CQN;KQa4BrZSo|%-Q?fxL2!%A5UHT+*sQuh#`|7AX#faFx2?$lQj<#OtpDHF z(`~ql$Foh_VpA9Z-#~YINva#oi1K`n;1^GQ-3eI4g~@aerxR)6bug=5qI5CPhF6$? z2u_#H-uk&>@lP)jyGkX8Sq zM!2K6|5xkoKMN~Sp1LmL42sIiO%7{SR&K7YzDXaxC(ZB89!xqOiOx;nC0v+tPgqqF zd(qvk`6?hF9D1H2G;C-~0Uoog%*+Ep^)Vv$SHSlPL&g6z7gtbI3)`6Q8;W`!9udLz zKEWQ@KaKYj$i>uO!+6Ma z8(25G>VOrS1~8I6T`TjUqJ_n0tNxs?y)oB7rq7swKAe;-g5ABWR(1@wRQu~$p5fxB zPr5Pr-ll6h* zjEq<}B?W~X;0LJNA%OFGt%;%MrgvxR^ySZbYz~;(t^B;P17K{CCgD0}_I4L>tq|0| z5iTHG(s#&LN3QIfbJ#+koIwMhO}oO2?q}=s+WwSA*pf&> z7F0GCl!1MV!1S_B=^P7%Ynj753lNP^a48yc3~QVFzYXr5fln<0Of(9#;&dfAJSD@9 zL+I&WG@@36e=OL2SZaX)lcL_Bb+HE{@t}zq)KL3`}du*!5-UB?II_jJZJp z__Uw7Y$PutV*}4-rf_z+^3ospkr4vQ;E|WyZ;9lSfBfVL`ZS7A>*2#FkwCqJu}^!+ znktHX2Be*QyvbcZ`i;Vk03ZH8$8`To+nTHzwor+|lon9J zHA=AH`G_k5#MfSO9#}w?J@FVg>|3bu+Q0_(XQYn4BpaZIi#x7C4f#VL6{=WoMW2Rs zK?HUFhEmAe>l7#y8`b~)6PAnk3#;VC0+d*kc$s8s-B3k^gV~`1RU<8hnYjwX@A#iC8*Z~=a1ULUo{9R zrICMcak~>18_FqBcTI5J&9@X_4pjPEG~UXgZ@G4Z@w^y!AWrgMUNz@G^X!8PtEj0N zf?FON>z&kfssK|_p{tOZp z;UFMX-}7N1%6?d&GztQCnobe8cGn+Oqapy(3P%sTVI zDK_)G2xj&@_+K~lJ$8)EN6Sn2t@>}XsKuDwTz-9?qgix)rY#&?u||Lm9MCYs;U>BK zPD{PQ%>4a?5tARm5N9h*!6rXF*QjJa0&7+i4xfWB4u#?dCX##n&ZibuRzN6v`XMA~IkHMTcRr zZiyWvoSbVkK{nz`$!WEu^aX_1Q0;|h3_?u`bICu|b4lxex1KAy(6}NxVAe}1uO$_I zm#OpSLxq_o{XaJP3~WjzAuce&b)H?nytp}5VrbYxVQH`+9jK&UtlOF*WQd@>+?%ag z`StzHpY+p}>2IR+e9lLQ2Z*#s;f=R<+`xIaLM$@m$A6IR`Y&(B|2Bp5CXMeAYqca&5v3g;<(rx#`C352Ly@Xo zJX8Cm&Oa2=S%{7@30NlR!w2;5rf_bXWF~Kzw(> zOM%=ACnR|;4-{C2=UWW~rFVQ~cjYyQPLD8BbY^`=Gf@L!M1HG$Ur$v>74*y<*2cXl znjo7#5DJw+6P@}}$B-u=66>*RZf|ZR@-T<=ss4hPuA4fQDqoEV)m zG4$@~%&e?UNNs5uP*zdlr_2X@ohyK{wb;EZ%Ff=>yYyQ}|Gv#CA z(HbK{PD^V!eFrlokm{3RybX&Wr1gW?P-iyg%4xk6%nsrRiQn!vpSRY3p3_;iWpf7> zxeG;Z*f>ahO<+H>jg&bR35blk%+OQw8ogW?$debe9%d67wta!9Eso|!iN;hrU#oml zrX*^UonHl+NKy@GN3LxZ#qzJ`WB%9~Zu+H6k9B-EY*!2p*C<_ndYzgCL@f~9x;57& zzf^VPk=I)8vYrGK!Gyu~75?~aUPLR4FmSq`KG%rmzYFFY zs0A!S_LrQhf<3iVmiTL9Xl(>=x4>M!#;{MMXbT?D-y87h(Cyv@z_a?J6z9ogCyr1$i> z>-=jjU%!3_f`^w8uK_>d+?V_DT{-DD9?U6XK-CqvAGbIAF@W$MDL#scJKrIQY2m`b z(WXtPywMr$CfhqeBiHaaYdxd)$M$Rv({jJbc0GKcX-v0KU%|L|ecerqG6wK2+y%t4 zZ2h1>LOpwLhN}Xnk#^^!Z{|BIZ^Ow`H9S9Aj0(u8&XXKU!^la=9E3HF!ba`?{Qk|;u}a{?FhN@Y!Bf6oVjrA{jGO2kvgisMd#cQ z*%kmy3dt&D8?S&^S%^ip|G5k}l2Z)M)w*6;a&InZWa*0V&Fv#gUdERw5H?05SVF4O zNWZ9oO5qHfzGQQ#y%efJYqNplfN`$Pm?Yx%pw1!Z1R2z*3qOJQcJ#iC#IAfjrMh*x zz-8S;5n{RP@FwXSu)>gqVl`6Qqx(utJ*-P{rV7|io(erMC12tu5gE{DP;6#!0tnbZ z&d z55Wp5q`gml97crz`lx$AuuvJ!d~p!oCA~fQjH);I7Z^FF4}A*)a$5IN#FmO>5Xk2O zHp1dyst~YK1pQG*KS%`z9%1Remz0{ST;*|)1VIvwLM!dL?zCX2B6VCXUtpD%>`X@| z1F+Lb(_rQsj^5Nkj(bglD1hpE4N!fL)C*&hhD%J3lSi8hxhPgw`L1JXdFm zDy@C8D82t;q-pGR&T0;=3?9}QRY+Xvu4&8U>QBnx75nPzWlgum+4wqjh0XpOfdI~A z_(CqlENtok14j`lGmhmD_PfByFQ=4w7hafeM;{&pI9N^mJE$^QPYB7{7IDq6{H+Ke zSPWXN$L?GzB5d(K+q8o6(I?{9lEb4UzYac5ug$A~ znvIzJGuzk1qZso9lm-J3xTq8}1tNV2A-|g&0 zTbDL?k3z69l8YAL1Yd3C-2ajgkd9Pbjiho;SA)X_JM%?~g8}xSKyMzGFINNtLCRQ; zev35}bC&kQaS|*~(?%u8T$WsgPr>Vt<nd<))Cct0}B2bD6%AS$btrd(XgpTBLzf zu+P~fHi`L&VG(B2 z{Hv1bXVk#?Qqb{bbe&C@fEvFKv1YR{L$mPjs&{a1%lT;f5G^aJpGf|Et-;Cq7 zHFPBEg5)hLRz}ElEg7Ve($5}4#n%&R3%%M~t{T&2dV+Z5kXMf?g+Ss>$c#MR-3F34 z*nJ)!6D-Yx%M1Yx79xyA0w>k8_k~TGsr~{oHLBQ8ovJm&5G@FJxyX`mu^8_Ew0FT9 zu2KbLK%fLf{V8?qZm{^#{<=T!y#a;sd-J>k zd9rf2;JVLg&RPOr?7aFx>x<+Em=)Igsh%$%BXg%;+%bvmC1A>J=Uq7a(6{z7m^Ndz zD|${N#xrWmh#+ns7{K%P(KdEmuV;~r-Q&VXxygHuS}AS^MW!v{jMdUc7m3PV@X#@k z^{GDYOj4Y_MCJPR9p0(4F?N3d0DPJ)3?8WPjv?UKvR4IU#z$&NXJX*;{;9SxK|z;5 z+2ox#-4-RF3>0n>$xz?-Kl60U2;TEE!#in01AIBm(y%tdry$B50_$00cXQG5R;V!W zVLe3CBFKKf^@|(g$JFbZIzD-Md1wRye2Hq;mjfSJTHHIM~aT zBIed#0K0LECu8K|XRXYuZ4z5C`RJiuT@M$?*C6GuOX&}8dhMp3YE!=IOFgj&(c&=B z8tWythM#1~QVRcBEMd!r54fu`WIl&-8;lZpx_t(v2Wc|~{v~Wb2{8ot_v7*2(`HG} zoXwJ^WFT`o38WqspYy*XG5_CIjz~cdQ+W7rP+NU&Zf=u7HaCy=jN4krVm*5Ac_gj` z5A`#MZ8@BA%;VoEMr^Nfi|_xj1FRKQR6?#l`Jn*POXjin_jhIZ5Gb!+`tfzh)f-}( zcS2(wRF-0Lhnm~|QWRUnZ*qWg46iSYsv-U>3aXPzzt3AK6qg&MDY4a9P?Ko?f;*EvH&8YEj%D%AuG8?3(lI86IqgMZIl=ELO zVi2vx?Isn>yFUejTd4+M`^w@_QMhWf;6Snn(4^%5Pl?H13ISpti zwHFaz_V_y?GL2(oY}}wKG;#$YoR%+%sCc9yug?s8mv4Rhf#Rnh%YmF~RC%~7Dk%k}#=0s&4n+lljGkqL_u>qRt3KcKAq4UGOW}ngtAWmt zdk`*30!o_ewqpmzIm~1zz@&~UWEy&upy3QgFRe1RMqfMQTio>2&{6?mrjBli}{ymu(|LCDV=Km93X3AZBE_9^&8H>8rFcNE5D-=SO}tXtY(4Zy0psM$cg?CZVb&=VYKZ5X#B#5$Co`ATAn@}i6A;N~+6YX{ z+VVSY;vJ%_=$?N`uH>iHb>|9LOe{z^WsY??Q%9%-Q42u2 z5txs86)T+@kfz6C#>_R?+1c6r^77RLJuLeLz0PJzhdO_g#?8o&E&E`v`BznW?xz@t zh)R|#<97ZSid8$QO5_xJpIY_mwCjakRhACeQdd=J*N`ORv|d7+5E#>8gh&I0Re5*u zHoc^(pYGk=i+pD7OgkW7G_#S4YJ4*Q>zATb8pd2mSopd1%O4;rf`lvXJq+QgL3(PD zCRLuw@swc%&)fEnY+7_q`??gEC!*C~!TTl@C#9U@p<^egU1B1l@Ff#HT;@i}-4(8s zA*em+$+G|nCqt@)iK9c;gVF=?yD`~}@oe?={y}?(k@my{HMV4O|M=)tEcRX5II9hn zU>=IF@-J*9_a6CpG&3#?FwBG!g`AeEIUFGuK#opxh-7Okk*OoiH8-hDtE-73FOGipiDn zT8OVAKH#e1HV`I_Y<&rcZ+sD8bshJi{4>odH0ms)m8HvW+!zvwc&Pt2h=xACiQp7O z{j0tQ)^Bi7(BxcdTo^1g7&0_ZUjcq^+@E9EnWZO&aMp4_n7Q^dtrMK}kivi041(p4 z07h>PSk z557E3VWx)jSi0J6_~1nj5*#eq=*YE+9M$@)+0eWP)2GTHLHTD>uwA|^106s;qDD@q zs;jdzCThQ|*f}>Zf-b@hcO+TVCwu1u?tmEZ9^10t(}W%VUW!@Br(A@dDm3-?AfBqz zDG9IE83aept9=l?hlJcB#a(g{#}$SzkL|o-jeRfaz6)nBakxEUq8*P!?1EPaUmx~e z`CDBi_DsBT{dxyxsI!fOa+UxWpe=w+YixmGgmpgWk@$@m& zx$>JMycyA1GFik7;t%kNX^ej3`n(Ev)uQ+nk@-sd<9gr>Po-y91|c$w18{C`M3{wX z--s%y;PS&?!uJm|+5G06E~tMo<0FZ;eIx3q*_gFc-R$@AJhLufp4Ti7ePvYY@bvRc z-bIGM;L?YQ)wr!Qy)ER1UM z&L+d{X3x`w$=_!h=~|rTFrNb{`5#2to4q4whKf)o#{y1dqGi`2T$o`X300 z|Myg5k@LQHH8ds@-*5$iAfgD$jZ;wpv);-59~Np)~hw=ft^dLI?rKYUCFLGEM;eeiFaU+SHNgy@YpuI>vZ*BHCb9$ zb93{ckdQ082AJZ}#b4|fAQHvaoaj#qEEGV!4g#(zO6|L&g7-Sb);(oPfJm%E^)cW)@R~S5TPPF|$uEb9tRFfoleG?OLu5Jkm`ytqaH1>Pu&M+D-@}EfGVvr z>p{3+gSc-XeB59ZU0^3~2Cixb^38?JPP6O17Y=OO>o$*$q-afdhpK0$IOfsNEX+mT z`1^-JhDZrWw#a1Cx@-FWjQzx3w0&q_RofdriK4_$U{$tCn7U`KM{4EZzMT2Zw`k?F z#`mr*?>S{w8-Jno4}m4J0+B=J;2{YVzak7b zafhypaYs7o3IA!P<7UdXA8);z1UDMsz=>l08vcK5&QmC#z(S(7i0d-&APO5x&w8*- zNKGJ+o9nt^VLp(XoVi+g{mps4si~&$ApoMJgb;RYM)IZ*nb3flDP)ELI%^>qtjKF{ ze#nzVya$lU4RB|};c)={QFITpG?HI~$LV<+iEwJ=8Y!Ch=OkRyEpG3fjFC>A0%gAc zAD@1FHpc?$&>wCL&lI=}MC-Z?#l~N2(x(mv3lIs|L<92J0)Kj@F;fsvJ`L$b%!2~R z?svrS-v|DSJfWiby(Q{)KRn6gL6m@{iE`ENj*osSFi#ZbSr5}CuwwIOS&(J^U*H?U z$b(PV0qYboqu5G8XR!6>=K(GdnFc`$JJ5R@gViP3Uo+4q$hrttJ z*c?nG4~wihL2C}5etP43razr$5 z@OL#NcP1(FAetwGPr`7m>R{0ZnSDT3PFLb@K8UWc8&sBSSHZl{bS09r@7)<$_AouX z6)uDxL>{GaYVZCf#Ain$viY}=hk>jWRUNc&H6(BrLV!3N@Tdal(NnoiTw;}~N-|D> zfRn(!Laf`R33${+f%1ACnDj}2N9@3ejYKN|_mQG<12ceiZnz|GK&Z4F@E#)e^(Tv1 zm#^L`IXc{%f?q@6p&t;F&zPYb^Cgf5_w{a5v(*`c$kXIWT5;cn9=-A>n|KH z?)*;ARw3w{`MK)c>BT%&qGZQVj$WVT-vpCF# ztvh4coXfq2dSe!*qir^wWhyyc#77xV!~(Zy4YT97=&oOHmmwJ-M@@p5hkAc1&$KNJ zdZ$vFMzYF%PsEa@Yczlu&Yb`4JQLNtVIfZKTv=p>`{<#{eLpb&27@BP4AJ+{J)c7n z11n|k`KIC~_-i&QMW?Y3dtI@ITWOr>kju#hXs&Y^NwGdO!LCP-{q+zH70P$}@k5BA zUFx%~nem_lQ@4UnU5W--s}U2>K9e!TV>4PFT=@0KJJ*!RZKVaZ@-P2b5H(_i0SrC5H2r}1#Wl!btoE5vLa z&25okG??3evaQzIWlcL6uDwUx7AG}k74BHD;;_s{;2M;$u=$NZ z`yJ4+o67^jHcpg3n%kwxhudSxAYar_RUn#;p>=Q;S)7^w$l8n^%%9tK{4EFzN(~vj zg5X9l_`?q>4>oncOC=}cKryBQGAk`IB!nS8)is< z@>M2VZ@9k(=|OSsz(z%=`O#?Ig$$d)I^-b?yq(F7KC)PVGDy zm!-_G+VspfWl{?-#l1euw;6Y|FAqwi(eVQR-1ck(DT)iBqkfLuRDd#cU8X|UV1-20 zbr{w^Pu}W*EOl3v_TGj?dS)Sc+#6_jqxoEWEQ@{_m}pETdZ-Yr4hp^~DoGsmmB!#VPGwG<*h1 NQBF-Z>*k~9{}1!7D!2du literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/Personal loans.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/Personal loans.png new file mode 100644 index 0000000000000000000000000000000000000000..05248596302b42f2bb9ce66e47dda7da45eb02d7 GIT binary patch literal 29043 zcmdqJbyQVt)GvxkNDD|wNlSOvOM|3EcXtb$R!SNXl?G|0Hb{4O2}swbySvY`;r+gG z@{W7|IcJ=^2YWciUTZxy=lspzjAe+bvMeUrGc*JQ1Wb83sn-Yyk01yL4`7dx!7rz+ z1M=V>0T*cvmpAriE^dZSrU*)gE)F*KE;g1%&s|NOoGtC`xLCPaIhmhZxVSht3$n4< z{^t#>_D<$(O#TZRU=UOXIZbB-1av(3_W?pe5)lG|1592@{4FGDd&V8|bvf;3e|Kx* z)SEgWfD92eJ(%io`p>^eV^+2!Mg_KI<&!5#qbHE+Gi%!dHBaV|+!02tGCvZvw>qj# zMZ1V{5+~ksbR}0eME@{^J>YaVr#oG(cB<=I>JxG!ZJc&bIdxamgN}s--+d58N(LWD z-F-|9e!@cTehhewFN_2KL_bOMqo;y@aH-zz-QOk=fR=K1mt1hsGcp*2mXS$&^mym+tkz7m-X{!=Ni%77*s(on3;t)R=K6$+zmw|_5XE3)h4{V zSx|8pA@@U4N+7BHZyL;yNAN?iKEBA{tuuPVd;{s-0{s7>{@=fn`7yr=uX87vh-cD1 zKBA{HZgYmIz6V|O^2*9)Lz(i53EUwa z##;hrjmGg}V{C!l+`Pht`A-xl>i05?rfjjNhFFj0Q;LbD*47GdxeBT4d-Ev7vL25O z-)jhlyAKoO+qZ8f=H?Vv{7g(?-QC?S{hsStv2py4ROp1PnYFc7!DCvr5RSmWz^4QR zul4nJp`G_K6Yu*Yt;Sk^X7o})VWQL$&v~_fIf%rLf5APBfF=Fs&*1cQsxL7yC<0mc zdgidF-PF_DD{LZFn4a#}+uJMIFR!TBI`4qsaM;IJ;<~Nn+jg&fsPJXI$x+U#tc?5e z1vg2VUg0~lVUr)yr=&N!y54)&raj*|%zBCbtNXR3hpoyE_FAyH>}Q3i?fCd+A=HcQ z5sN9FJ84BlpOMfB_Wnp>7u!s5=BqKGqM{0)FU8!1Qs3Sw3oj!8+s@eXG{u5lG zI#Gun{|AEo->`@O15o!r0?excxN)<`D?Y`?Kj(_PH%z%h?I!1capim^(PpYVVl~Ax z(srtx%vI0RQwUr1?D=rE(xLj(JM)aDY}$aLLp4i+uCBZe4h|41FE;Wtt6dn3J0eAv zYE!Sb%&*pD#TMKeE|VM5gNdMPA&Wu{dn7kqlyGyS>;tIu-(ikqzh;FU+4AzT4rD&? zCiLz;Do&F#Tg2TSh%ot1?V)mt*FhJXh}-@`8?#<5(T9r*4>9_Gy@;|82^?79SOx3A z$HzA@Gb6vMtgB0A(JpuB7g+tAnAnq(>eKCqgdSP>r#oFb>;)qu9H5q#OnjvY?p=}9 z{{nJQ#3)Ee6eJ}dWo2anpXhY4o>Kx)1PvYi8ejh2Wo4chz%&cg$bHTXSNak=;y8>e z54xF%`Rqtfr=78TzOx*T4Ts(xHHM~79g6+U)p>8K*zMXaI%<(IxP|A~Av zYdZHJgBUr_emFvKa=4@lFtxHkmEi}?}SeNb;e zvHkYs+sV1W^{XSP+X0rV_Wfl-_*|c}{OFx(LvOd4+)8}W%;(-OIg<`LY#;7zknP>v z`Wp@#Ug3ABANcj{e|@dWfe#+pe*~Xza0<(F?og>iSgT5?(a0YvjDdr?w=enR8(NDw z)=Ncj9}aOssghsk{)-zvh)%uq+lv+xKY`mvzZMOrUR%64u@}9&X9%3fMPA8+ZqcBm zVM@-bTYYohO9G=1MZfnd66!H?RB%P>{FCiRKcrtXix@+UwnBD0Hrf1R&us1?%Vx?E znKWFxkmJx&E)lNIojw55^xGGMHZVU6Vr}8jyRpQewzDCIk@2$b+s3iNt)259 zu;6+{V-9{HO5=k@9X4j>G zLAjZH)y3{b_Z7Ndkk0@g!RZTFLu8f}**F!YWu|YTz5_Xbx?zt3?D%3;0Dc-Koxs2Z zo~g6_wflJVrqO19z!yW`%Bt^~B=iK0aw zhtu=ZD)=BYnZMvSEV32}KBpXL7%=8+i3>~1X{$)9zB??`*I_L;IXupdyolX^bLz}+S&rQuf-PR=4j&izl5 ziYMwXuTKgCW>1-3{OY2DtrIK_+O0;^whJxIBQwR&;4=oT3lko!@sL z1z#&+hufLwtVIXXIH;eU1-CArRwsmaJ%=B%IDGYDWVN@fQs$^+Q)aJ`Y^3nR9oSETOwZ zkCE7z34)SQ@l(ak>jo|1Bhx$vBYVBFuCo8jOgFqnBTC(m6eFE+r@BLIaLxRy^d$^0K_9GAbu$ujVVA0~nAJkWzeVZ>D)E79R`+e}Gq_Qc8XYyVypDS&N# z7-!CiA??Q5CTYvlLD}Y!$$_6#Gy*U$r+=&icZn>Juuq~ECU`>cB-oL8_q%|B-x>yZ zuAdyKWgsXQ^N*UX%d@*9Rt3vKDOLODEu#jR486ebTIWWqPYcU3^!LNUvE?6YX#?c} z;YM=Q7ITSX8H+ql!3ekj5ubx#?n4Uinl0v*9}4>wX;DxUYs3Pa$9K+yb3&NJVlKip z(5AVf_YAPlHS5d1KE=56I$p|1Du|-`;#_pYywo$%oMymkqm6bf6t3*N5Sp@fTNOCBr;i2S_>*)TVVpfBH;kjp-Fl00%_q^1 zr@nve_>b*90o&_WUbDlx0+&0D08UGI;@jvL{kwbkW!rD{#_ZF+r_$>&l&mPT*R=dK z;mUV3{6QlW$^QIcIs6$MI6xjOnSC`8i+^W90FK39#sDT*hS)#X${EA(Qx9&sQrjEN*OUYS zn!CIE__k|d{e{(cR$Y%y0S*ohl)2rltyUAxbEe47!S{dvaY?Y3VkYXljDY^A_dtON z``=#av2n+Wk9f>=r;wxuCfolr(J`3^4|PpGpW7w|ba%h}T_UDmN(ExCkvw$@*IDW) z;bw}PJrof1?ABlI;6TeD`$hz8dKmwBd)N6s?D?~FEa8cnnQG+n1&{C>#_BchcW;!@ zTe55~Z-Hp%ctxX z;ok}K)aBTQD_Rwi zdf+rd?qaw+Ywu(rt*TWW*580FxIsxr)~lv}zG>^ffm!56n}3c@6TbINMYhzp1g@eO zhCYeu@$vEU?&qt+C5()WoxQ>rjDhfY6k2-_+OPnZX~Zs3vXxC_43Md`FQOY;tqWJB z?u~m&Asu921~P9A3-)754VoHlT(6MODThvfw5MScCOPLy-asBdew+r=@f4Z?M>`Q{8e-C zo#7~T)nxyMyFiTzTkMMcaHX$h+tqn7f{)W~nt!Kil^pOy%_4&b@QX}p`Hf~JI207V zt?ThrJ|nNt)ldT3o+X@kBJovRZpT{O~(Yn~6 ztb^5Ci6`ob5t_1xUtgINbMG@y;%oJwr#;HmTfciM*RvBVVSecBi4ij-bs*>k@wX(G z+!F?mh4IweB^(DK!}imt+sVK=qDoTwMKR~fq`kjw^?@pO5d7cD3-u#>z8EB_hchaC z3pzvsyN8x>^tlx?eD8*VQq}KOvfU;up4;DP&_d)$$i>KL{q?r};a17OYgN_8DBmk% z*PXvU+PGALR{pm)HMb^ZE#FkcO@2eywmmk_po2gaXHfHQ2i)q`D_YjjRqBEKqQCu` zLsVybDzYMU$6G$EsW&BZnPc6ab%<$zh@h&fsyCkN)B14EVJn`>pRuvk-EgX#`K^Np z#lYrkw_655Ogj&fFKDnTYlE4&%hUIIY+DdAauK}Hn-y)E<$MZ>tD=v6gfS0td@!|` z3=hRnPA1{bN>Zc2muzl)ypwA{xMf&HtZ%6+=6plFp<9;1yY-EVNL%+erfZ^Ctt!f{ zAMt&aYe*jt{@Obpn-3&0m~b<^%yT%={p>wCzv>}ew5ki)jjhM*!8@EMv6r~Ux?NTv zLqS><-`D;uiaOMOxqC+rf`WbUYZch)z9tK~Ib9!*9d6`7zoevKHNI2V&GKHSfxHjs zBtY$02oADNJuT2V@1ov2)0qqXZi(mhhQ9#og+69h-j5noBWD;>RAXyilhLt#)1w!0 z=sbyrhv=Wi4cs?N9g%+;kv}GfB4hAwDEv->@L>ZIk-xgd?~J4 z_-)u~GhWxs_m0anyx1LXn116N=z2;@m>>dladRv2x%R-?`uS&cR7PEW><8l0{lt@J zb9H8t-&m$k2_B=Zh#%99UvSb~pY`ym+!1hUL9-^$&4LODNR<8h`4iSJv@3iDadF{p zxH*PilPkB{>xldr#+^K!L&6KgZ1+JDy=2&SEb5G%aCb4?1aYT~PLNYIiJybqC)k>aS- zoECzc5AdXjY8!(|8CgjNpU#w)l?{%KbyTgUC^$KB4hSEHH+I_@J>8kP+Hq?*bmPUj zUAIwfLN}o{yWHuTx{e&Yi*n)5r1UI5gdLCRuZA)eKIi2fg{Dbebx)vr>oP(jcPjTq>|MpXe z19uNhRoHOjak4ehk|`fkq`{03r$~n{jH(Ql_3c^TBo!r0nnt4CMC0^nZ|#(u{av1k z^j(8bGYcc5(NwuDxZQUZXTPD}Lumkm&b{P^6AK77&AjIB1@oXl{}dKMA(oPm@XXg7 zXI~8JcKbMmKm+wzvF2wtEU$|fl^*}D<(> zW*URzJebHqCw0D7S!i4w5ds<-+RwbaLu+=NhCc+TO+8khhV6ptcEx90|CL&%55DlH zmX9-bVrRuY%R}E$agzi|xJ9_)l+KYgT42MsT!L`kAotJ4sR#sa+Uq+zE87)wD?s;P z3t?<0ZoJVS-y4J>;@86PqY?0+eo6z9=Km`ALuH`gz$|2eG2qcD!q|Mz(GOP#Rsqq; z0)~OXZ2rkUEa0(i^pn5J4I`(5h2G6;H1HF9kfYB>72jvZTD61=|9*+#xu6u!&1-V| zOAcvbF~wNw^BW-d=dwo$>$^Aa2a9pk5ItzD{?!5@4J|E))!!HJd_I`?bk=j%U>T2? zA0_+f7YwOkxB+u}q{#Nyy*)kb=0Kl)ge}~d`!4Sc_)rTgtMp&LLI4LWu^M3{hrm8I zb-&90Q!B4%9eP|3wOJK*x$I)M1&Roht3hd(I;)>v9 zD_iw5N~*!Nr<|(FRmh~plV|WW)Dn86=3af}>CC>DGR^Z}us{OYr;6v#Y_yRJ@b7~m z)W;pn5E4E+8ald_qKdUO3qY}jHHf8^Q>Kta3K$`2E2YvO2uH6*{ypLOxG9>-nVqI? z$_4!yr4Q;zY=2vq8{@(Zw`153?TTcdCCh<%TUDd?S%2bc~Ob%?lW{c2I zYOVj<8*oq!hA7TIbML$kei=A&Ywm&zKUK-~99`mPrP2}>C6k65e1@lJKj$p(A8h#v zlV3aZc()hi*KGfxZN7%^j>HGQZi)f41gVf5zgCqn9uW`v0dqiHJ?0*0F&uln_oO8J z)c#=jNUI#})~;bVyl<(_F=#)%PK3iM4T2@2iiEzp|L#ve!V4o#gR_aE6)0?n>&_TE zf4l*syBSocpw0eqxTr`gz%2*%4_|7uc#a=^8Z-}Q>y^QKqGTy#$tK}o3anJC9z<}J z*yHUU&5$R*O664I%~5XG_lK!j}ib zW&2e?3>cJ*5ZuY?GQXA2_^If| zZ2Q}3W5fT#lQ>B1r)|RsP*K}go){;&3-M1~HoSr-LgYTfH#ItgNXHe>1_JKz&m5=+ z{rfEC3mZK5k?!0tn7qZNRX~vjyLPxTm5jil>)OwcN^D@8aLw4gTMmzSWwtq%rF+S9 z+lO9PPawkg+PKdI--@o1mVxO{u6S6l&<{hxEiJoy88*O$wY(8HtHx49RX@VL=wvWL z0n`M17S!P-hBGCFDj*4Z0;Z&WUC1Hp_$k9ul23E2hwE|u0}NjF!sPG9F7N|Jeew(p zHS&5zD9AcA8zH7)qlUtH#Q#2~-X{TT&}F%l)#CP}M>vt=x5e4=dbHv8>@M}t$_Cc& zQug&@*TNK?I3ldn-j8RxB0U>^G>_p69Qlpiyy#7m9EKo8*R-^0uz2`K&GcS)4{}ny zXkB<>Ej_YH?JnFJH-l7eZSM8q0bC#QOjCIUVq4l)n=5;MtjVw0aqx$OaXTB~<1TIa z^$SM8x}uZe(nwo#yf-F{7httY1t=$t!vv^Ki0gQUtyO#L8Gpv^O)C09Mnpd?HxI@5 zBNb|h(^IaU4>_zs5d#wQ5!aUq>GVX!&|h;Z#q_J8cs+FBAf5ccrqk9N=~ffc8DwKT z2~3jEC~i@O?e1|O<8cE)?Q%~n7r@Db!^0{N;$mH1!Q))n?ZfdB@*d7IMHGTFTV+3Ot1EM!+lpNw@lfmW}fU`G9(X@H5ah>vqQz{MrvqGuJ zQj%tg84&n`#`T<3WohZahJ{YmVI5@0mT+atkNq|uxf)PLNPaAN-)}F8y8*xUE~YQR z_DTBoP1@9S`PG2$)qY162+XeVWrGsFdq0Uac0of$&e3`F%Ci0yyh0!SobbuvSc>}! zF(5vbn}s!zXXkBUgl|AK($J6+V6}gevY)cOkPDx9t;}8~MLrh)wc7Y4`CD7|d!Uft zpW;OY;q}+pScc~$jTRRF$9~z|=I0&GadxOfHmSLK@ zOBDM^#J1fmx>5ZIQDe&h(|>H|!y9|{JF?t~dN}oX_V2GZ46Ll#nVE<=!yt-Q&?qu! zqFl|_Z%EO$s|p0A*yt}`7N9RU|B{YBVq+cqLxd}3Gta)IIQLl3-2Yx&%5gwkBUa0x zI&C&v>kcwGK}^uvFOG}tjsqg6MK2pDGEE zw+x&VRBK&)y!V}8v}}uqpoEfoez;0;Fb=9Ho_p8$OloI`>!v@gSRZNANYOk?mhzL= zU^Y<<^3F3{LaKiya(B>+V}A5T!QVOO){?tSTyRl&-MP|!KR)qBqc$T>Ude>i>E&v9 z{f-w7jG7Bt1E)eTE243?4IoZ56Z<&h1rLgmV}X^C z(gQ;hnS7+8{MM%2e(`V!+v^Q)A3+A*v9?NTqRI*H@A~}s2>b$@T#K}-yxq^v%{FFR z1YEpf#CdH2Q;%$Cy!mHRB>PL^luX(_anZ2^bqP2s_J^2Dm@&_vz|MC;QH=8~92)mM zys05AAf5?9%&XN@JtF#RbD%VVVKAf2H)TC}W}q&zyPKO+GY~O>Nc|>5z~1H=-fyEW z`QYawyy2ze?CC8wpLAO`kB5d=)3T=I-&0(R8z6ko}*<0U9B|5x$SM>Q4hauw@0Ur9B&jWleN52jA(WOoMyfkzM zc4sHMz*qidsXuyqj^iK$v0_(9hmG03-=bXkR40ZaW~|J*iy+E-jR!?Y|%t>F`ni(`*j;bN%o-9zi z{DqKrw9GdKY=JEcRTrhCtVy2>Jx{R zlG^c8$A+SJs8i9}7LM0pzOY&>_kPbH(KX^DUY{NVH4`C@`aH!o{7?^W3&} zkb&kcM&g6blz?j6&l_`M>blB=Y|uOt?e`=T`|~=S0x?J9u#`z63d2=D)b(ES=3ZZzMD z%SMI470=A)b>p---xE?^bS_ysXAixH)-MyzepG&Jqu8NkWB4**{JK+tbA?roeufEqjOR4sE{TBdSg+ks$`#2{L zLQc0fydOD{Wk?I;>j-oBue*m_d1|xlZs!{-$y2XJ%9~o*N&K_>2)@=AF4!pnkt>|R z!$*qyk4lh!tN2$Jj9&;wUiQ>o623VfyLfrXx!ShTZD)|2eZL!j$eX*j~Dm<7wQV+%x;D<;ophW&Ku)lBtAe?_B0%++Iy ztA2ljYkJd}%eR^sgOa#-0meX~)ySo|ogTyXikmQKLXR6ksONAK*NG9!3sf zge=Ie<2feg)0Ei=u2?EZg;y z^TY0$ue>hL$do{+^Bj&Cf5;)6MEQo?9pRM4woG(Uo549p9*S44ZUiJ#R8=lcbUCZE zSWca3luV+2+Wq~D-OV>nLuGp1G(;O8ZDB&QMc zcgPn6L$NQDoPDdNhRB-=szwz1$P!56unEAaWp44;i<#4u$mSFk6gO-v=)+|QGea&zDbRNGoKO3LFi50}QaETErbsXOvZuy$83mS{ZP~q@e-SWe4Pu2eHP2nX-4Xeo$dwoa`6Hl~uy zzJH+p^W9#RTgsu>R|Ht7xdt*0_xhF{xuCJQX2v;eKBW#CSM4aeyV5^;h363 z|2304Y+Kjmgxvj+ColyApe0Svs;3K1f7nCMrpz&U$;T7L?WC~9h+fGnOcT|{$=S?U zxo`_S*pGJIse&*w?Id;OzhV$RQ|4HmZunxZzT2`qDzgsEKPg`Z<%xhL%OsWfmA!0U zAc=b07n9vZ`g8mMZQ;t`bQaFo*7Ab4nMoP?oQRd+L7|P+{$3R-Axb|!KJ`QW+sR%E z^{s^~N6YY+VeLyDW5<)00zNh6Kyj3Sq+w(EO8spO-9mj{+b#T5%z8I9Kaz;1R(rPi z+9TSZZBN=L*8`e!%O_h%{>M|eLm zh#XJ ztOTYzB?u+UbN~)_{u(&-=~BP!vsa#}AyD6^vhOPb8_?1cXHbDk8C_a&b4rISXnY~u*X}zF&1^X) z=1G(GlvUO3oX|N$#lKwb3BX~%7@G>R6f@j7e~^z8bcvnFIP`QX+mTP)j^HI4bu6q| z)Bdg*idv^pHE9iWZaLDi6A+48vOs~_=C1sU=@qiHfVqVOC)QM;3CL&Txwa!ewr$i> z?zEkcaN1#IeYt?gS9_kma$BF5^dBuWjA-}(E zaC`uE$p#(clYT=D;Y7H3w*s4u7)(l?Xn`u*itUK>@F+R2amFhyr06B<@_WN+vE$;jt*`EUyr81-X2=AN_oz4*T^fGs z!+J^sUl&Kmtrzkr+6Vs_FI2^|EOk_(99^K~SeEakX8-amSQ67>|Lb5fJSg&0=)}wLeNr3V+nFXHbsLoYKNN_&C8u$`t`64 z3_s-xDylbIm@2f;AR3M z%Kx7CLy0bu%0rjIA$ddhnntQ z4yVjMPE8iP?@ArIsPih=$yUE&(C^gUcZ=0~s`b##)b#vfxhAe1dYWii#)@tfM zVh7YvHKLBL&|NGtxuD)M-d_{GS-A~dw60$_71@^E@*w5mxH=u}b(Ep$b(w@yTayu4 zh3(ZyrZ8GkQQvYW4Fk9|EW;25f+p>_#%d`BW?h-0lv7O1wSdF;92(v>z}-5(v*TDh9{_StKe>3$}3zvF)okF+ht6+O0&P(?Z?p5Cm~ z!8L(n8S97ev5s&YkJ20Dw?<$6Q+3#buy<1008*`%DZT5xxxTzwYg78l_nw#xWa%;B zTg}Ns_0W2|x5Q48kk9PJmO@?;Ld&Hcx6@JZ>_vSN#`yQQFK;&W6Mxxl^9q7eAW^H83qthb=-UOMTv!)jetxm@CVeqYp!?Zn zI6;tXO++MOWBuQ%r1I_9R@bM)&qRjS_;LMS8#SM``8iH=az%+XRD7aM-CoQp!=L6i z=7)!e;|^1fy1Nr2msekpT6Kk3I@TV8+OZ@x1lOxn+VAR9&S`-2aIOXz9b&2G-1t@K zLul#sFn1m}gDWNx-lW?)6XD$(80m_N-0H2`j^WDg>|!zY>Ch%xQUe~yZ|eii_DVQ; zNEb|E=7P(ik&5C|%^I3o5M^eT8?$O&{uy_LLvWPRgH--6z2d&D2P@~}-*{9ISgw5S z$qcb#XZUg~)P8k(u3>;_lW8Bq{Z2!Q<}aMmSx%yJ#2cW4avjmnsS)j41!GHF+>sZi`+ukxu5<`>`toCWBG z7+XlUW)+b65EPf6Tkr5V9(EL8IlbX78TNEHR>q6L)0OGis5m$}4Bi}N9W_mE2ngWITR+G=Gods*Yob z?5?@LmpWiWd+k<&u3$`V2s4HZe>+r0y&<@&MlH5FnsI#>8`}G? z@KLW$tBGXVsv*vHcyr`4fjo#eWsE9`kAA!oMwK&*36Y=JpB8X?3Xk&Ysv}TlXWK%z z%Z{oZS^LW4;0OrL_|rFK84_kj@CgQh|R8BE)usmofx}IC!zelE?dxsjDZ7pdmb2GW4X7Wy@6#)5}}x z>XNS~ojMtytMQ#qKyqHrii4INN)NBv{!xx;_{)fu^pJHL8G$>8B8&4dCdH)Fg7E=V z=%@Ohr>V-ZA%rhmDwk#;h1bthl5GimIMe*!9ggA_WqW;&q`_dE9`SD zX`7olA-k{Fv#f|@cu-<*pVziNRH}p%{m;_>0mRB8W! z1`M7k!ckt0^ZiK+WlxsqnlK{^xA?Q=C0^0mAJN(}?{RDopOFpkR<{iQj7n@R+Tin+ zjH427G~(sRcpkqyK-^UsPBc5E*+DTk(N>|?%t zYXe0Gc;6iSl@f@uvND#6=sC^loNq&ek=zRb)jixx{k?~d166669hekj6Ye$LO`%po z$07vHEPAZnJM+2IVQfqz9@uit%f#L2O}q}{g_vWO%zb|H=S2}7-L9QjL{jkRkq z5yY6HsoNe`YQZW>>tFe}2A&Z>6eFnRu^#=LnyR9wM~?9CTXQ0ru;rDNhX%aX**}jY zB{^D6{HVLvXq=t`*U8H}ahBh7TK;PyXxNx)Xk$K!o8FmAke_cxfJSB`(p3LKINPQn zYC3leDE5nG+VgB%pW2*{_*2&Bi$ZO^WHH^u)VO8xAoPMaoH8;ob@lg)o;j+i5#*^u zMboTV^lIZkMd*>LzP{M=bDGCITSG^R{_b^ub~s;+m}aLBOPIz6{>DNVn#$j@DI5B; zd1)FkvSjL28wOo<;}FS;;`)+I>8(Gr?=-pi^QA!I^akHJ`^F`tPiyz3UsRjTLcX6# zyLszx7h_teeW4jh0K_Wy(@?Wc!(F?in(EctVv9j40v0XAe+&)Nnk-wN=t1of?T2_| z=usK<*gy{F2-160+2`Wf>r&Hq9S>z``=+=8}$PbPnEmc8069Ud~zDjSecNd3ke8)#P%PaZ|gb{)rBHsDs2SQnsK z8=ze)rGZ_GZ8=Zg-dZi^0s()W!F!*H=joV+l)khG(d=djX@2YCa@5M`D)4v*s98#v ziII^SDH6jVsGqdR){p>7+3hD!9IhP30VqS~=Yv>D8cZ&cNlleLD*zq@*gitV*t^rZZxVvU!2B zcZ;%jfpU6*((CpTh1@w#guhph)C_z0QwNUSe!6}+HhEN=vgU@ofeQ5IoB~3TzP3M?Kqi?(lR$QWjHtJtVh|J259PztF^{EH!e1viav&|UeR+3@ zl@(7&LMCg{xI`y?Fr#_yrK&T~oqW7iXl)LU-dE@>a6ke;>~K?;6Lj;KgV(4&3A^sr zosxU`f>z(RZ{MDA`2~aq85PNjyHpR#Uo~$BvTWmcjpFuAet(g0VH3Ca1#h-zE0dsI z>iwH16H2vxS?ixEGevzk$>!si-qoi2(NlIM%hvqYIOXj25iWspe~Y}1wcrI6 zI=q?^HuIsvPr*CP86r+`gCSDLIW@y2EAs1n`9>n)*W2tQNxe2E8^$v%^01jT zIVvBZGmF)h0yc#y0-c#?DF4qX=j1!)SMll|I6RZ zMuxd1CLQAK%){h1T2hu95tw5Zo&2MYQd&wGykL)5KUq+}9xwhUGKm}y`j_V5r4p5) z88)BUn1h`Y`e7(Xw)C~c1tZ{B_x;>`#O)|W8dP(Nn3Fa5oc>pL^oTKeuWYFB%HZ+iuP?& zz0mIDBNaCdwB=vUoov3Sd3nQY{8T|i@z46UR|(kPLmpCW+rdX1ZI zd8n8aJNH;YG6mw*HN=bdTF5IY`Q=fdvYVwkCmf1+iq+8hy zdC_APyO*+wTlOFNUOTXzGS5huL)AzKaMrN_Gqib7-}q89*8g^vBYbQVH!g9y*S_N` zJ4bfUng(uW!b1BSLSM#=?v$pbLF^LF(g?Z81UvBJ>Jl^tAc!%@o4^R6ZY1Z=`*mEYB>eVE zQ_S)&#qjlon_^nU$Pp1LPIksOW@m=nIg0`DDQZ9+8stsea$>&gGaDi^Be&i-kD&t!sKh#By|8LQYWnVp|dh zC27#Ngh~X?&@ELgA*&);{`FUXZIA-D9VpC5%NT=4L=V85Uk}yoQMhBzK%XZHyZwZ+nv>eJDoPg;1X5L#* zQ$IwVdX|a`p1J#7yr_YG21RUVHxT#M)fGjbJdXC3uY^=A_*`&byG9$x}#I zHjf9mDI#fNTd$iL;oilm+2_QkU1S6HuNI(b;`4BClBa39Cg`jigA&dj&IPfEo)@vjC>gVYWAHa{T~lahxe_aRk$ z8Ltk^pL7Grhg$>^Wqf@^{n~CxeP_KIJ_iS8^%vt-Cp=c!fgm#u@9-jhx2+~ehQ88t zD_Em$RTa!tl3zFCR0Av-J2SC#zZSEIoi$dd4>cP1e7O$mD4Z zFcrd=ChV0Lt9X{LE+V#jFBeg+9A;nCi;572*~Jk=Q%Zq&Jx=vf)#ALEGuy{o}&{x(n<(AS1IN6K>ds%{x*F4bYM|XjHp4Dm=sU8TS2>EbYpZ z;t?G|ftcHR2Mll}V=*KcgFgaTY_0}+d=6IkLni20`=N!VAfA!nIn>YTn-Hp;whVJR zixJVAiYqoVmDE8;DZl;+>KOOU$ddD&Eib*Pw{2AozNxFDTP=%&8=X|RAT30*$1jv- zmp7MV?oqclkSleg7u{W2$-6`TNxMkNhN<(H`xJmtafV*Ad6dNm@HuA^|0f=ULk3X;p`H?}y2q*kj3sb>r!%!`SSA8+1ve>Yy* zk&IYb-8wwZd$pO#OBnt4cNcs}CNbKCRl?-{T>@nj6>k)H4)E6fJyXHVGcv+x7^vla z%t`Nb>rGmS?eVPJ1CH-DSAJnSlc1g_A33aC?#uIH$EEF3X$9a`VU4i2W*d3)x#*Kt3;7t)I3{pckK(aprDmGVkaC zc8XZHA75PS&_gT?Ii`6wnau2Ugjauig={qini%M)oOHm5MWti^Xt#Y}D_YoZp6h<& zUc&nEoI%M;qy{UdI~lP!GT6q|Tvy!0jVGh~=A$O9%2Fn%^-^b-fb*LrRjSN^6!Ob}nQrXW2&1-SE`hw~A#)9NVa`4k|CaXD1gUVxO9!hEzlTz>Yg1l- zeNdIufgaW~1c7oyLNj@slw|6X1~9V2Iykz3RNO{ z$?$u(w zZHPKoL@y4OLx9&cBJ0Ut++t);I}F7-dDdR-rINTea6|^KAL~R9@*_NueyHwg!kQ@S z72|h6$nX;q9aQf4HK(u55(GC1o${Wp$D$e3q({f=Et(b3c(?K~r?!k#cED=qQnedF zVGxcI2td>17)L+kkpvA0|LUonCg1Tgqy~8oM^hP**qpp+(70_LX6U(tX~OL#C)2{X zAmsY$n+t&{G2y~*86q+j8XApWIuHanyi_AiRwj%poNfuk9^rJeVXOeNoGIdq;BbJK zlo2EAcKy2^R+*>l(O!T_G=6^^<5PD&Jb)2^_O**X3t-#(?B;d$D9z>^V<6k)DdtJ^e%363|YSFIs<0B_$yP6-il0$_w6L zq|dGSGDxe!QN6^lft&N2ZCkke%|O;zw1tae^bbN3yTwRQIC5-vNYQ%NZA|g42sZz& z_u04JZD$!y2BH47U@Fd5z=93dERSuY9Y(R0*LuLD6(Ti}6%``~C1LGO!{PIfNL4{u zM9QSZ@hDl!MV%x4%GAkfcA>Q3w#QQYHg;w0;l^T)YAkzT^%=ua0NL$EVn@kFw%YVp zRRTckYgP&Nj=7xAFX>H%Pv-Sl-A(Y#@o9=dofx$3SdJ*+5I+TyBzmd-am-obbndu% z+Uqj@eQilbbjj9Kt8ZDHUrHdE8Q$+dZJj_@C|2}Mp4PU(&{&ddpLoS#--Xelr-ug(c z{2^Ub*jYJQCO4Ee>sRpK_L0m|8-zyN@?o45adQaWHjZYgEJlkhDi?RXTv4!-M%8f= z&NS$!GbPD|TxHG~3b*D3a9{i;c8uAk*T-&Y=eMc-7k+V!K5aO1~aO;*vFdHsStu$wv}3~Md8 zuXBm~C1s}nt@DN2BAg+BZ(JJ)Z}{Sw*uMbw?P4VU_Qs954xBMvxD?Kc(Xpfcpri`v``5!*B@1$U=JKX&Z57)#2eH~N%l9m@j;(*8nQweP!zmN~()88c6T3;7 z6)|sGzMSldGNFS~&!)39Y|BKLB|vBHNZjZmP6V6+*12)6K6H~vQ$FlczommNTgmV3 zDI%`?`$jd;V8};RlA;tE zQ#^Xq`&O;y0x;RvyNqV>3F#3jU&oI_PM<>7-&bD}`DBcJ*Z)w*Nh;oXHBx(r#eaC! zce!&`;ft{SO=oiTAIc(O;XyoCq^O}-4B!gWc9!^7K0f<=#N&%6FASPe#(3wxxV{JU za5%AyWrtwAfg7rnk&%M9sKLJ6@IZjUS!#ei+^zY&O)+A=%sH*WZ@pEyyHQ1C;|&|l zgp&Ef<@6^hcl8J~WV zV*h5zOI_hiQmQO0Rx1cw@hdx90vJeLjiayf0Xc9wSRGL@gkpgbXaOMj%$PFWoK3E* zu6&=a3C1VpMo30ne|$zYv~c;#_*SdWLt-4O@3qrMM1)bnamdrjQh<%?_&{k>k%nUw0~*<1}p zlUPrZv99199s5HPh!0FexSV*IUDF6jw+N=V!F5^1gGZU51xw?UAz_PpP*3)mrYLUo zN?kF1wwoK|J(dVPI5X6l_y!ZUlm`;b^=n1xN)H{7RLdL9F>1Jfd7cNUi+sC`Hdioq` zp-N%qV4+-FuPT~7zIO}NyFoy`U^&V2!~DX;)+va?pucYaP79lunh9dCf*=YwCgX32 ziLGWiv*$=Mpfy%=??hk5A~&SIpB|q2XZ0Vl53oU=CwIkass!VIJ9Bh`xxT(aOPJAp zH#+!0?kLc-uc9OG=j==@#;@g?oN^aF%3N0g0+~`?G&f!$e7>VGIq}wEoQz6e1f5sD zc55pv+$G$Nr7Rl@4`(I-sZOO>-MW+Tr?`}lPtQxaZ*q|=^Z{?)dY8E`7bX5tksNd_ z0g7dnIa~u9G@%#@>&aiGD4&z#e)Es1%!fzm_Gjr*r6^v14$2``np;exay3P%GQdE|RO4Iw=<@Kkyk@}n=7nfd_ zJYx^uTc~~-%aSJ_7~2|w4W#}x*x|RlY=mJdrdVLNPx6eX-WHu#ND8JXm@_5XQBI$Y z%0N86?yu~q8*JPiR;W%oAs^It>ZosR?CFJ3X?<-RC>x{pPfYl89iQO{fncilz(NLv zvzI-aRBvqzV5V9c_IPnRF?T)Mew4aye>FUaa8!vQslasY4Ta$JKRMrL`Mu6EKQfl# z=mZ|&gu_ntLcNnko8jbRUhC{v)8d62dw^&`PwL1V)|yI{KC-afKeIJx3`YQA`5r7L zhspIl94aQNeX~&+?F}Y4zIfA@?;W%NVc#*6NQA~b=N(=8xgA{*ExzbxXTdBS52Ww4`)%EmRXXy&Z@LMTqImrYH@ybDB(J2~9uu}7m?Qg+T-XFeB+SL3Laz4d z4fW)x(9HAOW-|2{5y$D#ts&zZO{H;?gRwY9JwvBw)U|QSTmV3Be2+9F{H8@G**;p{Wl%!nN>CF4ZShK5G!stbwfD~~HC2W-43K|j z)sTf~Ek5oFwk}JA=6G8QC1^AfTL(_wzhgM6i70GEaVWHpM;^C;QG1n~^ z!e&@fDwYkhBFp)5@)s4~73ld&YZhOO8aWluE<$X39xX!Y=u_`61Gk zg%@)BOY&L3e@aU6{F6fGuK4;*p1z^%vj zizO@Pwsj7rbx!-k@TRuKd^h*}QV&mg4u04>WEfL-ZS40@sM8c+I{BgaC}yfE|I6LlnB4ecAn|An)dBE-eFpoD#I(U*P!wC@Tw9l=1!c%rQK~Z> zc)Jf2rGVi&+$df~6qUbIFPL_ln<8yEw7Sg^=4T1e1yzuWDz#QyYSM2^Uh=OiUN)7f zZ=uLVM8o)7Qgs-s63n7Zz5G}5Xj4-uZ|BlymS6BN5EpjkrgOcg;Yy|9x>H@!x=)q2 zQ*5+qwVgD-P&c=-)IU3F&SYD7s$?)9W2gCG@1q{>3r3lev z@G@oy1xQ)l_3UfB{+#k;GnOPj=5+fX?TREcpY3R@t@5Atyfn$?4%;bx;QG?6e7 znL<+!ixrHa*#nJhsoh`63$@Q43|}ID0sG!?VaQ{*7UR19Kur{9Bz$a9EkdL`#87#Y zwS8MFhSLfrW_6hvzv8-3_9{?(-W_w%m!(uYPy zbh-2inZ9={*o`WbD@_b8pekLKa$Kx)Tw3)zs4+b@sL2Aq?%9=U%aAXU0`wWY@KHEC z`@SF986d`Y?B$jZN_i$U=q{O1`{PjE}i z;!FG?889JafrV!>v6`=u&)6j6@P)ECs}S}dW|x;EY9XLWXJ-o}1X=5%I+F(r&}sM} zB(mgzTe}lvmEB|A^58_Tw2eL!cHNwtd!?_d^T%6qg>aV-EKG9l)}^Zq^j=RB@(jdz z=lw7m|5#^5tL261_2-<#92L_1O8dFjmEz(lfX%%dTOEiA%#ZzhOjJ((3iZ`XwvQR0 zi10MV{<>Py0fX8)-^NXY>zTHkwuMQb>IDB%O;QH;?#>)6hdp{q=SoE_DI`PaxrEbu zC}SsS)ZXy0`90S3OFtd5n@(A$?#{k7P9z&AVuRb#X0z9>^<>wcd;QCN{AJ7f*nD)) zFQY#(*|qVlrM#7DC=>FY#MlMaKLs>2K6i=>!&wT;W$bAzY`IqyIqj$ojwl0RuQwZL z6-3&>_GYfVmSV_7cFv*uk6MpSoERnvU)IN!W`MIj<0s@Q_68Ez0Yof#+gab6IdL_h6L~L zDn8>(k+qq+`^mUrN{DF}qn{hQHYPST>_Rh+N`lOqqsRv88XFTgRIF$rb}o`P?KV+O z8;!P46D50hw=`W>2;fZ1ptEDPZDKQs zEUHjNn?W3uBJ3U~vZ-6%8mkWgN9ys)NEj6`VQg8sdlRC|)S`DA!c!r)PBOA| z3doo&2p~9B|2isjvZS z9~h`$HHfrOf;{{_t);Ia%4rI{z%4uypoppaa0&3_M^gm1y}Z)o45{0*6-nCzJX}Cf zY%j5x6%-KKU*p@|Ix!qoha%HNROVUfyr7^6rF38ED!Ut{SLE&3e<-I!43&PGnY*a; z-N2uGJm_I8yMN4Y(joRh9Cfm+ybPCQxT*V+{npTwy-qDvO8We^p`)|msugGJ-~&@v z&Ir9|8Ru2+#h-tEEk7U9e`Z(C=f&5JA4-yefX{}yYr3d=Pqhc;u#ETZwG=6xyJ71Y zoebX1*O5B9dUZ}Qmxl9W2f{1roR+Rv+HemF-2xWhMjVfm_{ZNaX`Rao>9=^|ZRO8b zph`cmcnT#bamWlQ1{Dd49c^MO^!b)6ZZnD}-gVjP8ra)gPm!H<5*rQF<*u>4&fcy` zKw$3(P*$?4JPJJ(_`F-1a}9z){^cyo`PuC&JbDJQ$~sg{ILehc^{V2G*$*_1Q63B^ zUSIE%d!c0v=0{GiPlYH{o$sUJ|4^1-+|WfUNEcEb2!|h2!>-i*l_8}lJ&t>JA`9mu zSB`E8fBMBT{($u$WY~KlzaDorLQ%c-CE;7!7fyE$UR>(SkX9j=S1(Dpn^Kcdi{Mc-EwvctEZ7pQ%?Tw~h?l^{a zri6e|_b5E8K3~>8d)6*%V(MLHg~PzW{Pj zPSZ_HZxSCUVQaqw>6)sWYDMnhb|3Y)zS5(Xvm|n{N51+x6xnKfMY0z&1bKYh*PI}= z{!P*Gc{t))7lsx@kYz-(;LEh0buUq>B(U#jHuqbLqK+!-vgGX{4_)B#{$;h4R)KYH zJn|;fYU5&K)?j0%`+7}-ZMpA=RVTP;)q80o;Y_)#G+$E{`6#BW%Z^u11&Gjf+#ZZt z`4!>KF}6xvaf!^>4nCHa`V7+#w6h`v*?qLp;Ev(ug*(R%yUpx|;x(hQfch}yx_sN} zbk36j4yifOjE6dknm<9b2)CvXJ7dLUo@0bcTb zYHsxJb^)4$7xp4Ld2R>$M+ki-w^m_@NvgZ%#fR{PGBl&lRRG|i7jBBKMeIjDzv<>K7j7JhjN>=1@pv*D@Vu+I4G`>?OH1E=bT_S_DH+8*@ObeJ{YWEW!Qco= zn$#t-$3|Vp0&$ltxv$r#9MX>=DGQDJ&VPLv06gK1*_JZU+_wjrY{X{UA?VXd&1_aw zR3MhE3`~}Xib4Kn<8ZShG9h8HL*Ze7>&g44oMA~zKP@dRY{bi74G(Jc$~nfavYH3> zw%!=DAF*FiNT26+c%(6c%P=_Rwx9=z5Gk*7Ab~t2Q#wP<;Dutv+ydU+I#~&%xktnN z*CP8v2D<}$N5gtYXT{M3)*a~>wVglARaxnfmkY5lKVu!Nh3InfRhvJ**c=%7<3fUM zjt+U5OE^U=$Op5{mq4a*U-je-RdWC0w-$W*kM1{(r2JvbDxbupy)pT< zO*x-j7{!ye(BZo0c+D@bQwvYAOY!-w2hvt|NV`rj7?r$yj{9@A#An{6ylfdY>~^qR z($w5+3=k|3SbUprf@P7IU&pd?OGzbj5jPmxGk-o=z z9(<6S^`N%%a({#rG^h-@OJT^RYiz$jBEH#>PUPfdm|_J4gcxV`lHG}B za_I*ln_^f``DqI7Pxv zI9U&2b=@iRbS&E$ZyfIHmd75y83k1JU1u?*NT7I^?R8GB&?UcfTxM8)hz6kQAooo+ z@+!R-;^F3Yx#94wPTlj$oSk_W(2R(b3nBjGv9*4;j0WOwx)2pzjFq?&2_o?IB2}Jc zk2W`9E!mx|JX6Yh@dq1h*@19lfd%QR1-#^p)jm(e*1$Br7~5@y++?<~7qQ7N&7y`# znQH9bfJIo94LR1NV2XcuEza7lm2B+fkbj(1-n@$TL&;Z!{bbxR?E?}d_OS;tBt7Ry zc1`-dk(Dc}jihIh%MPw{($wxDH>hM3ZI_0>puhm}{jz1rC8Hf)uFZOrxHg~KS7RsU z)m{^x!`_HrCvC5UP4eUNJ}JYY;W&1V4}n;7oa0M0sj(IYcKV$J#7USE*LWWz7i=U< zA{SyFajZ2_(QpLoT2otF(S|1_*L|Ph$cl|~PD-@*w z_CxtwsMgwie53pzb}Wp%@FQd^QMHdAr1?g@B)h>+`Sfe8LO8+m8lIslw$T3Gubo># zDuKI`cQz1>pGdVc?l&{sv0`N)ZgT0|rU#mCjCzxnJ&p_1Dr+=z))Hr$3Ay;VA-h~@6_G9_%%N@L_aogOzNJ>&bxP1R4O|W z8F7sDratP9Q*ZEncsY5|+xPPuo2TkSw4wb6iMY$s=e)evPf{?ImB}+RGbYK?$VUrj zh6tF8)}BkbK1bO7BfHFZ(o7#`WVYvvBdgN-Z(ZsU*L3N)e171BE~xo!4HoGcPJLn<6BEO-?Fjqi{}QxePX=JPf6MIG z;^OGKy1Lq&;(tMsXL7$A{QQ^PX>GEBN}_)G#J7L$eL)}Yo1l*&zI8h@WHn!skO2aC zkL>OFq1%l}l1dDZb`79fDMc-yw}=E_-ARZ@_ts=d@$d8H|7a%%F*HH90*%b*Kvu7~ zH=A>lVDr`+nEs>f4>~$To0njV4qnW~B!g@*4GoP}foU)Z+Wzy$PXaUMd(ZnAG1rme z-DpD8gsa}Et*O}s)M*9j z=-606t3Dp0#8RpKwA)%WSy(s+wrSZ#@XdzlZS-$8ps3itva~b;xuj4Q$xr+y4Qox@ zDa5Pc-;uExj+EMmf|#LIPFX;5GD|9Z6aR?YbXZzi+8wXMU03ZLYq-u*MVtaI&2&;vnd09wSb%ZJb0!|a9OB4!?!j@sImFAI+$HkDB} z!wrrdl34g28qRrSSo~rSWb8WN?e12$>YJGec^IL1GFHR~crpg&hbmQ|1lYbepVAS| zEIv?bpQ?}jQ%zgD=^>S*jG7v?4$8WE*~MxSO|r9{>zxF0Qy>xqDp3FEW5VP^bBi1= zQRdI#aMc%@PpTIKK?<5Gv$uq$?cXX-)xk3@S^sTtkvF`o>$%;_qlfPKt<^<^$Kw;- z7k-e)$jb{t6B+>PUsT~ddakBc4Qrqs)TpeTXhl`Bv$GK}&?8RW$|N8gJvB8IdXe*J z&Y|r0%1Xnm1FpAMR!%Me27;ko>cAS74dokaeAl;;*R>Z(h%djOg~VBoNIpl{N1bS& z^JDh=!{f&dXXteeohbHb{*MM4k2$ZOi;jsY04ddUs8>rdI9kxu%GRg^ktxQwXQnTI z|NcF((ZV+mYQXFuk1dCd@FEI~Dkv%%HAmf$laIJO;ZQ~t_AME6zqQz(%Pk=ARK3ne z#?es_+7f+BOY{5r^QM@%_?x+S3s?!<)usYQ0`Z~Y*ReOApnVK>sxNSXin7SudSs5m_VNq;(s*nNX~Ykm+9*2 zYHV*epKnhhf!PrcWft$7c-F-#Dk_SAW+YC|&QL{uGoR#I^tZ~T7r>bTDQ{X5;)}sv zvnBp!&n-1y^`_W2FcziL;o`3$vW0Ou-0?ms!9}F8 zO6~ttS;Zllwy(X1oaI)VIid*9orVbJsIl4_pJL4TzxfQV5L@AksttaLZ>>BV+ zA7f*&msKV1BM`rE`Dv_P$D1je5ch%qjF)&LfRrRKPzKh5-U4mEuH(g9nmK7-zP#({ zd3HSSeH{4sc9|bh6wLF0z;8WpM;|)D)Y5HUnr6lqAGFzdU48<_gs8a)c2MT!d!k+* zC{hLeKXgX9`tjAPSHxa5SNV-ktEVd&0fAs?s5nHg+=U-3G?*_U-Kh-r-H+^S$z5mH z5qmONSI~dvR5!F)yB1Gu$3h_r2{cj2*|A+TP||~t2W_joHWS95=;*Zg)9W{8my8kp z%VJ;lG;CL4&~77v3xIy9cSKTB+rcWvZp{@$njA!kt=XPLsDs`y*kLzVY0xoC^>71(aDosK#Gz1- z1{XT!Hhqz(lnPS9al$r?b`{%nk=&~3IXU65lZ9j4! zI3cST+_(=s*&jquE__D;&xF|?Jp=A3+}&u;{Lye60kAEIn6h&KQ9-`Pz{g0+obCC;Kd8Z+zJAt_kMTEUw{2&xHOP|xYyy$ zB_{R>oRA|7F3T@DQ&SFb8xugEF$2F^R8j)4P(^olF_KsVFHvo6ZP?#2L>Rai^pPaB?X1i!?aYjIo;v8;*cw|}urhEku+u#?va_?Ya$laGfBH);12yLYxC%M(Od40jsWHrOOb9txs9^M-%E(&Mf^c=ezEKf8Zhv>5SC_(|*C z=e3Xj`x@*o%VPh1g~Y3H+JE2o%$w=f|MQDmC6KX5f}5K?qpOmbv~P1K4OHCXd*iS* z@kuI2w=0ymQ=j0<`7R1d#>jdshh?&;?!oD);of`;g-M9S5|ss2FI*DuFnlIkl#dC5eskRUtO>|Y$-czPrZ$xl>FI1LPXTpmcik7pR_|o)3sPzx$x$p<-aLnexJY%!$}gct5;h*82WY ze(>h{!m`R@Cf?xOv!kd zzbD&4)z#Je?j+oH{x8j^<`)(|H8%25h)3)F8A_9$_H+rvp?wGAuUx8gPgGRYSVObH ziTT#8Tfd4_V`!C%_ohrsWU9&V0Dg;;&5w1{bf$z_K77K@_sNlGG~ot?!X=8oLkvs&WDrj(eUah$uCs@EOfxsyd*n#HlY z@iR;OXlpW})dziPe*RUX%kjiF?Kk=MvYlb{noWs={1?ILZ-aCU4TXE7>1(YPTIJ>( z15;C<-p8R4x;WWhAI?C5*;p@jyt#It^|&y@m-YVQ+o?)Zzw+{O=C8Arrg(g= zCz($Bi-_SaRAxqe`r_i^&vy6KJ_48H4WFDGs*{tGNP5+1EdDd3j{-NB*hx}d8>0my zX4OvnI)dac>DQ{RGF*(Jz8)3c90IJ3#G z7m109XG>uMXMZxn{DXt_4wk#6XLeyP1_TB!Mk#5$&KcPsRni(qv5*Eo|u$$e)8LLeYTNDsYIh=W`_8q=gn2jT8bwLDJdzXRHDB|iQ&&oQ70D{ ze)cL@%ZFE|bLHA?$Sx;a#%d&lguQk4oA|s=OwrNN(@pLPV@0Y<>+9VUrMlL(w&a|g zu?hu>e8>3f>vPQljLnxUs#RubZ~Pu~u5^WwuC)hXyB!S+BN6dBeQ9(({h1?88i-3T zW@W|1YB-RoQf`pQZBHXd9|SwA*4EHrcecNvq)F`jU`3_Th20AoQ>=Uku2*Zf{`ieA zM$7Nt2@zD%2P4t~)(6X?*RX?OC}-;Im!@lN=~T+REt}4fv9Pc{c6scirKPbM4Sk%L zP@Z)=l$@TKi4*YTPvW-M=?KKJ+n!<{{j2G5PJxSy8%)9%@9&S=^ml{y@9FL!qVODf zczyniSPCy+zC7Cg9TUfDXtOu}+GM=gT#bsGJH9i7(Dv_|re-T7T@nIoOT-*7ypD)jbksr{y+R3hi=SFc{Z^St}6ySux>c*OTz z$P;G$o`04G_s2CoDPF#eUTE`M+SwWSbO$AtSr>V{L~{*(z;5BWHNpIZ!y*{!4Ptz+ zudme_oW4SJ-Jdi}87@>|MeNe|@88D{vcGuY|M4Tz#&}7}dX3M+!Kad_&)TsYum5gN zdEThO4wt`E0b`z}A^=a;U#6tt{MOdWYG`q3DWn(nXlB$4nbxz*gO%PVskQa>rjEO_ z>BlqQgb-^BZE0)&=;$%Hdd-D+~3mjy54%p z*Lw2&aE%?RDBHy)qgPAn`T4mqEJ*1}H<;KbsoT@FawBY#s*Ns{$VMnwByNk>EE_vB z_3=eTMPt>LbMn2=oCs*Fx6vL<~Rqhe+n4;pf z7cxOg7!jB3oeK4O2ZETlZ{He2&HDuff*p$PMq?zSriQqP2vaeS`(HcEp-@tR`bP({zwwD-%iH$Um1hI8*{1@CPC2WK0ykH#WenV_4ee|+O=fyQI_{vVmNAQYQeuZj$NwE zf4_@iP~ST~W-rFW#~1lsWu8*!nIt7Vn9Mg>V@*ChJlweg6}D|~Fbr1gE&L$%Ld|CW znPRs%h1~bgpe%O5-++LCTk^d>p=9SN6yWOjMBbA1Jb{)0RSg>--#;ON&<~4r;1@I8 zh<{WRPMaSV2Sa&9#c~M8tVsDzMpsB!*c#mZuL32krz2hNM`!jMznDF;k)))g8ZHld zp|99({K}Kx#3Eq1OGrq#bl8{30oC2f*?G9Z+4j{{qU-5SKU`hT-cY^Ph5|~GM0r;TA^}jYmM1tnLeN#0sDrmhk}{^LbI|TgM*Bt9cF=0i+)y`DygZfTU%SV zjEsypS>rx>wEyes`t&vv#c&;tPNq+s`FooE7crg|@HNlF$n=|zs@Pl7>|cbmsp;x^GZ*Yd~dnS?4M(oXa;q$!`1#;w{sRe2DN$U z!HAweH1xj8a?V2S6k3mbzWjQ?MZMELnSO6HyKxH+EiEmScED4k1xf_aE&zFTc6Xym zOH0SUG{4V#IV~67o716Qti}a}G|8k;<^B7I#~Y&&`2m9d7!k}$u(02T&9X~d!=i_G z1O^46!>%BE`VUN_gEKt zL3>BXaJ{4D5;u2JC=RXS-szlYxy1}O3_&YQ@cG}(lJkq*=8@-g1jA`>P+;y<0Mj7e zyT90>{NV$lLoIPzHtZwYt_|of|M>c=M3YoWNeLQ_``@GPVU|q*B09UXjSUw&_3{OZ zm{e3$7|3@91#a9zV;rTwj;36ZdS1R35kVD?VbEXynPsejb^m@kRBOrr=8mNg->y}U zD13^F%;Q;(T^f@Wi#}MN?x=SL6TGRlSpmGb49x|DgqKr1<>LFNJI+vHYCNvEVKrVt zS9Uv{ag3V{d$>6HFF21K3MJ-2#lkWi%~#0l@zrc{n+%rWlg|`+1eot<5m`)Jj}78( z0aFOQdsk*Q$pS+aGBZzt7&Sm6U4|*{oiLS%&JB0F0u`yxZmX)Q>gdm~*FALHhfkjL zlr&$91>w@~ot(TZF4yU}4{f3yx{|pXE-7hBmZ+L zW^@7Hz&ajQR=zWTd46bo5*KG-O(7O3VoUdZqOw9L;4#7Mc*Na%_hjH^n*fTll@xub z41|@#YC1*-%M%R{D_{rdY0X!!kS*fOYbSmei*&JusydlosJ+9@JNIyV)ndt zLw-PHq}BvOEWZip`u=>L^_`>j5kHxXccpsWj{%u|tE!T+9|7K#{I2fa{b$~2SrsI_ zQy;#>#{R$(xYR2CB3lZz2x_Ble?0qigY!tuC9HU}sS4`0i*?woF#LTf0xA6o93urv zCGsV6^^S~^L86r=qe!y$m<>+*>7~4m?~ZooQZh52YdEjqw6?bX>@(LlHjZ1ZVKwM; zG7I_k=bj5# zn*eU7MXNig^phS_h-n!ccSC8FYfO%ti#XzUlpKlWcX!D@=H=rv{+WqpyV|z^Yhk@J zqP4Bf3%Ws>(Jlu;Iyw|OTiqd1*eB}$Y1opQ0v5VgWVz}(H z;^JcY-1nc{FHTC$f4|fv_}lkqqLdty@TDH~SLhaUX@d7)Z$%kkL_r;qjAvT_TuDYv zjV2%<;Bj+xYNtvIlnL!S3aQ(x6n=MDAlbl9)}{P;fOSUGsR%+FbUy6opjNA4I$RrE z158w?R?8yEQCp~7??5jjBV)Jmi+W~!bF{z@&_1-HBj~k`bM7%vbB4+dr4ir|7E`V3 zDFc8*{jow7dAJ>z+A^({+t5cl;J-%GHO%nG>~~ejxQ1&8Ow!WEh8Q#hSR2Stz5vRN zm1qub|E^{wa)t5$G)@a<9>BpJJUl$bVzsy({BjtbX!tx>?3fxJ=lWvNbfSQ+316Ct z*bZO;(IMe;LE7u4O3}M)`$rJ!{ScngmcoFs#LB2t3I>17=lS#w7$jGu8??U8D*v+RR@1Q*R zX16XY_~wnZy?vHc5;yE^0(3q-A0MB4FiHBrSnReY9w8u33E*O4adB~2WBy@bIofT$ zFaY%8DUI+_#85%arTb8U3J4@eD(MXBb)H6}OTInOvOYq~h8C#jVcEtNz}yl2GXDqa z`+5g+{_|yQgZ}uA)&2x#d<-?{1~bb&y}dy|Iamz(@ByK|c5~xZ$d}iKRa9X)$3L=5 z#Rro%F*!M$uTaqCfeeF81?U;rC~$>Ipm!o+P zN<&e!N{c%?QZN9yYPDt7bFj;wQd0*2y4D7UUZT+$%jad@!6syvBYL7rF;@%oON{ zYL996`{LoFpnar&s5I$I;24}}U5LK_uf(N&J6sLzzhW2KkJth`d<2e|6Kad#(NEo%wp{2yAyzG?0MzT&_iRuKV}geQ?` z@y~^=EsR{Op^lD@!qVpy6#IzQ586{BkQdfKkCKJL3+yuO?%7#ecVl-)d3oJoU|=}tdaDw=){ z(0`xi+5ew(r`M-|YaIX1#)ieEkzY70A~Mn&@bLcrK9>ib%%0xyC3K?po*uDmvVWDq zA9qEI%bqebfBo|1p^mPu?WJ;j_QLjdf2Ha8vY?XQ2ZsSt6ciLtF20qPcBlRMcZlxe ziWakUYcW}!AL!H3)9)W2gTO^896{pM@(KhgfYj1S6%zh8Jw4|c#!mpbd;9oU!)wK2 z80goM5tkK07O{yEg`dD2Akd|k*PBq%K`ka|nEpvgNow8e)#CN`O*&ILr_eb6jDW4()#eXL$_TzIUGF1R0aWBn3_>Rw& z>Y_logEqgWEb-r0cs*Adgc@+#UV?^Asb|~_JaKs?Msr~AFXj`rr_Z0?RZ<$KBW9%S ziK6ub@LO#$(^IJntsNG%VHmvE9|mk`9B8(cwY6xa8I;XVdpSyx0aR(}K?w!PiqcY0 z6L`i~x276h5ojC%d4RR9^)RPAr>5?ne)jK;`V*0LN1++TzcbUZ33czF*ceeSHvZtN zdjxREqqeRNnqctYU?P_ntWqeQ=}?0}6Do5(wP4U_5CKNBe{j&+-5mgJz1;kFmHfq( zW%VnNf`G>hju)$2TUn*rt^WijFn0FWv;N*d0tXhzWq?%$fhk+t*esr}rBFS8-d-aK z3kK8;N(&2%n)-SuHuwO4|7`-@O%kL^rv)FpSXM)+cn}VnrRJL45xpxkH1t=# zLJ$bEgqoVw7R0b_ItKfViHOO}?G zlmDk8B6Px(6w(I|9>_z_0jiui71p9PkLajOOb=C6RRi%D2LMYVzk;m}YNSy9aa(IE ztVnHufznqJ|1JQbfiKR*5>FXKrG3Jxmj7ByOPY9jg{*scL*E6yNF7O|5D1OP8nhV% z2!fA8kQ!k9sqlhCKG$dfssauI*i=%>aA6&2C_o6jK(4V}>A|^=$B?-5x3siWB96re zh=-20b_=Lz_cRg4!)#R0vVi=jxHEf-6z=1 z0OyuYQru4nfD~yjwg+_Thk1|?u-hz)fLIu9GMO>MH0QL0iC|p-o$}zJ0WwLX@F(py zU4#OHy!G(m!&lHekq|N)`Mcox>N$@LkS9Ny+ybf4s@T37zzRIFv8avy?US+S#Q0y7 z!YAfT`2K;xt&<&G{h7t^T}nQ{c$KnzVWFW0pyMLu1-5;7L_|PP&=O39^t3b(g5WS> zVq)0h3&2yt)aPK4$12}CJ3GT45A*kb%EtC{vi%UhVBd0CIzM z$E8yEB?Sd<)2miVIC?rbICNTs0vTJ}TWCw}|P?GKQ*SM2*0s`KzMPr=?BP(&uS2CT?>LQFw=&kpW+k0 ze+yWXO1ttka*og{@6Qd|!^T3)6Oa;_S{r>LVqyX=o6LP%_bKbw_Lzl=MNgo-7=nOO zVKn?1*afdW58^qNJw;vaj76Vk*a_;nJ+3BSs>Mzcak3+GOvgqIlbRp!dM-w<)GaSB zxbfK}^ksCoTEJ&r0J^|*Cnks)K~tTdpH~ZM0lNU?i3cRSA^d=@kq_X?3+BRH}xv#h~?_44ai6M9Bn? zCaxn055Z*kj%yH$@yFaw$8(nJYV1po1Kc-HqL-7#^uJZIm`hX2)#Bs!|0-IWaN_mu zn`W)9`n9lQ6y#Tqxf5D-PV*Idcsn*Asd$j3hCwFpANCojgPv(GS# z(8{`Ct<}Jz=yu^zP*9XwEeKLd#tUVMMaedvECw;M*l);7CG(0xaX-I29E4j(*L2&z z2RaV|tDXJ*E8Fbh&VPNTi-7V#oMCf5D|Hu{BxU;?pv4tpO2FBaHj^1J#_J2<(y zv-5R8h!phyY}hsVyPQo`)$i`^xi)juS49*oiJzX!?>_UtjR z!fEh$Xn7OO_N~e~X1d?Gb4@KSm<9P|VD3m&IdSIgGB_xnyI|BlS6VF1mP+aY&Bk~r z^%jU*aL2wse*91i(}kisU1uKz%UK7wZ7*Z91oYl-6%sd6{m?qlu&|^#7G7vJ@q)i- zc(OGqk;EMZ%Rk9+*4YmVX>jr-a8)GWYzoe z5FxpjlrWCuNJFWmD7QE?pw&16%qOuQCu=U}p zB;YZp<54BK?HtRwreNT}U|oVy6_Yk7izsU6;%e#1gB-~Q3v)_HsC#yLTJD}rGakvT z)#-mOXGms^)qU{@V_JWAdF zM*H+atRzrH@beJv%oBE#%z7z@fs|?f@wc;pOWQ$-G6s<1`$6BwDe^yvS0+@gelS;G zxWE7&MzC z0N3;p$EyHze?&quaJIjcr&Kbli~X-FzAWACa%b+w`K#p(XV`4&!irAsGKqq*Z0AT# zXiho309Ii~nb&x1#q~cZ40BoAN9qz=@?S03FKrr3)$IgXY#lUL*OFp_eO~0_IWEnN z=^H=%^EIPupcgo@b25-o&_8tn76ST%4LDI{P6*@5;b>$~YB)#|&tWMQ$D$9$s1Jg2 z!K|XG-w#^dUJ>SU+2%(g&Oh5TjuETjn#fd9${88Xk+R-EsX06;BPVKdNpbYx>!}(^ za~rE<@gW|uh)~}bb-}%I_aSvqTeb+!w^JMV9q0HvGV5(E*||$YBsJL92Mu6cAuep| z_tlUMG_v1W8^8tq8{UnuN%;wtp8S!Nnyv{edEIsBn|R}imk`^B<*A`J?!!|vr7G~^ z+ZS2A*Em{xR&L7v&vNn)fq@KN7r0d|uvv?`ByJa;Rftn?D;>ISR8dS5t6Yn@drUhA zSXL$Ljs&O@)!BrVxX7nDPm)mvFp64gou`@hO?Z4#{ko47d1R$0U%*mPvgPGN(B-;9 z@jo1{9IXkvZ7PF9#r231&q7$>Adte)V|LI`J^y`eZb5fgf$@{(l>7QW>*S_uNMjbZ z6G`QpY#l3@DK#nhh^RNWB~&a8d6UdoXIyM~Sdvc_Np!m=nUJ2`tzpeFRB)R~=0DZH zPb-eDVM!t~!jc@U=HQK9ok75I`t)iOcg^c$g_V!0pe5CM$%AN3FoV;UHc%g>#QL~6 z-llVWH1z9WRGKQLK;eN*+|l&^u#z7N)ntn*o)Q%DUBv>0(WbikuMf+TBTwv>W7P4u z9QeWq=5`HUH9l?_siP}C$)us?2sND!#d!w-qp13gt}Y8KhQYw z+^moeAGVY)+uop!_&o{ zhOl@DIMN2j3b})(muQAR%=@LuK4@+7ys}U7zwwc;OVGK>_JvSQ!={&C?Wr%dmqp`p z!)T7=m}lD zr)&2fhhr+MZaCG7Qomzk3~B6-h`1*?;_olMC}oF0F&nNDx2wsqYpi(U%hP1;`gK_` zz6@w)oLSiwca$^VT{Dn|sqJy%l7mGqn;hEro3JmxjRPrneyO#BfAq!DN@CXO$qOD+ zasD0UuhAqo+jA3JJa`GaoYx_tMu-mFlXc-+B^tqSgC@((UXw+89Y=clGbV!|f9Q=&B9h+Q{iGHVQKR$j5$eGs^u> zFo+U6B@@~#(-?7M_X%rSXKmQ4$^pClRdGKW{(tBrOV4AU+;#bOUPO7>u=$wvnse|P zg`!K-Of8T@6`8-1VntDiH^q#z!&mp&M;h&GZNK|=g^RieJq{-?qvaVk;thf)t|o*A z_>HJtDms32jV4RiE2dX@YDaYLzfeLkZQ52%ie3rYTghg9zRup`!Xq;#Zm&YOxh=R( zCdD}=_Cf3Z0X2etlWC5yg?P1`PPp?2zhX3mHJ0=HF`122+3fcw@r6r=WlB}4Suz^_ z$+HilSi;0gih2`5qG-m3U_oM!C+YlNe{XPQ|Fu%sVo#ja!Q#np9je7du!W@`c}?;XE}+Bt6FbnWOshiuOt_Axy!Gaco5|Cz9H$#Z9}Ki^moZXI?SbUp z#0G-6jY^x@fnQiwIocml?8R|B%$RR|wU5uXKHK0MBdP87U3!++x$RUxF`O2Nm6U%j zJ2^P2M=#WIpJ%T(^@AA?PLH=eRjmhOs1n}Q8z?8xfdUqH^4YiE@2Pi|aJ9s#%6yEU zJ{e(%%Kc;dH{VN;S1i21Pzc04Q86(cXh6mqzd?&c=+_{|LI8_G?t;&0?)BS=1S);a6I-74}pSzCgiZtGNpBV1uA|?4Ka@N(3}$5lxGyr zFdEXt2bG~Rw@0wGR_y$r6nd^I{$qQ3SJyZ#qb!9M^NvE9LWa<@t-^B6bvjYY@2SRv z@}m{PYv~^xj|}o3ulf)b8mmtFNh!GJEopKJukpDQf5yYS!*_N)h<;gfNamT0sk_VJ z$=slV#If5|dO2i|G)+`UFkVH(XNnu)94l1(WqE^u*=&LdT+)H#&2eggr}^XH-HQXG zV@XoJ1zu)6O?%G4$;m*aZjoATIH1&Y<0puq69D8|hpn5RY?zH2VNp?+b@!hon^Rc` zF&Pf(!`wZSDe2sYIoTJydJJ1Su{HE1(sYQZ-du;(iCRP3EV?7=gRqq!l@~;{4k^1g z4gMif_bSEyN!LzA!Mr`4x3v}+m31#Z`%%)D#Ox>2Nx6PmHM>Goxw13N0n=fUty8kX z5kHe*=k?mIG~VB;iR$WqyJDm(x*0fYm%kyN@sp(X!{ztc&hTOLo}ZPzq@-64pZV}w zx+wS|wNQCp@YSsr5 zV&Z;K6na2C0Fw^^CC|>!7a$4+J}tnzZtT;|-CfHqGE}SUOXqkt$MFYjm{mzZfTKVXIVBJ)dEViww)0QvItZotf{@l%% zKU7&q`Zm#ARO02gQytET>cp%~EZ01KV_M9n38_ge4ms!6UAB}mFOu?;{f%_bGp%E^ zrb&m;dl$vu7MxHo80S`Wlrc_qM{mNPH+G(|Ry&)nKQeKz3wacTb$HRO3VoLJH2NS! z_0j%i+2-SZ(z)#Z%_U78c?| z)B(!Ok{1>~(~0{vP#@rih|JTUKSm~Fh27w}gMbPi4Q9h$D>~#4--9WWL(-0}fj~=aucGx&L7(ikTSg6hAnYD(?It3)poOc^f|A2!^C6%ZJ*Xe9;8D%%W z`2!h@sS4vaKt&=5hii!Vikj$x6`QK15c)o2y9>-a zxnx-~C*K2FS{F--ooH{Ln!Iy>R8EGR!W>Z^(hDI25u0NS0&cq(!1Y(5`lQ2veypq6 z0aF<~*P6Pz?7BUVr4WvZGJW*k7{`DS!LUxw;A3V+KqJLaS}-?M43xV(>nQ zFWR8Yf%j=N*Te@Y8c!V?cF^Zw9!-hnMzbXe5hD-wGtwDwN3b3di3?@b0#630easd& z>p3Y013bHXW2%+}F{8!m7kMdjo-jWFpc@jTK(Zwk+`lI&o(J7jg&K|VP-0kg+EJnA zbb)F)S!Yi>$ahMV%0Kr*g#CvrWI+*GMj}qDj}Yzp0t^`n+(?B1+Ovbu+_UGiSI77X z(zCZyt&OoBs5SK#A37Sbnp36N7YX^%aM{`p5*;CjL~xKRd;EDqdsF*b4JsA&meHGL z?hfZP53~lgvY7W9cHFmvII)%6<6dK44ih4%U3ex3K6Xx@MEHk^VPBb|-UEjM7NUBR z76iHS+@ehTibf}3m$c$nytJT)z=C##8{#307S2110z9@dE9}nORqQw#|Q?Dz@ zR*=91(v$y(VPHU6`7)<=hFkaWP38-wVj{3rv|t*6TLz=!F(5Q>ke=>-{QnX+t*m}b zSR>@kQk{xnDKqOA_541&uHVMGl4?+Eu9@~+>$eVYfg2D!G0SY^Hq z*n$wyh=9druyK`{1M`@dEG#U{s@;0`rP;(Q06}nNP;#t~Hxypk??c8c6Qs=box$<( z7w0-lb3g#*#_p9S^N}kS)>jb2AJ8lf* zHr+8_P^qoJm0-I^cjSWDXE`8MBD7(L3#vwBeC%c6E^%H9j0w*IrclVs7O7UVKyvl= zojV|%<^Y)JOc@*r#oPml@}L!+aj&0aj>&OH4U#}f3(G2~UtPyY>$_cPLmwsNc6E)0 zlKve}b+I0eCsA$>h-xEb(!FqQx;VUT8al0avr_LiQ%-|oHEi8-0~`Adauv&A0%XzzeK5A`K~__% zcL)LZ0kl7)Gf-pYipnAXCkF8-$e2J>77?!7oS2wM9T#wZ3fAmO95`-}{^)$J2ST{A zvhsT{OE5YTk`YQbWQXPVZy{0^eaUx=@;Y5K(NQ?h+S7%RfU%PW*Hl;lDAB6=tCkB z@n+2v)?xGD|2G6qmFE2vTSY1>yJDz+qnm+Hkz-s0pJALXjHsddkYHbwxOVk z>oO(JfbS!Ml)jdES0aq27!yK9Jk=hT`uAhK>n)CkVy;|#C#+I=Hu%@6b=ni;qnL8} zB(nih^R3%Pt-7*ftdZ3=^mueq%0F$W)D~6(}g%a0+hglCud;^Z}CDQ)TC9f zW203p)B?DH2swdc_4vt?_=V*SNQGs9&4TfS&A&T>3Y&l+j#88wUJT0v(QJMdt0#au z{taUP@|$ND5KcSL2R+F^8uhqa!qbJPoIo2@0li zh+-&%FAI@{EWqh`8iWAIAQrU(dFWt#=Fb4*haiy%QmkJ=0WG9eIUpFD2BB1mSf)=( zn(k3#Zv%(m*Z@Q#Cdv)55S0M{Jj7_jz+w)EOoj~@8}hnC$(abB86tL&7zES$3}QWU zm96I&7pz7@Pa&&hLT7}C005e5O?~Z!^sS;o587QYAx9`Q?wsG|a;VxQ+A?Ut%5Je& zF}t_-Oh%C2RWls63uV097c_G!XHGHa?O(i7ifg=JsUPs$m)tdpOQur*adI|TUe`Bt zcG*D4ExXFGtkOk!uVomSN>%(MrE*Sa9XWCbI(7#O(nOBtPEq=Q-FF-9ZV zm|$-sqQ)>zKK}mx7~A8(pAmsX;Hc0syqcQ@<~%OwA=uJjodk~BKAfpw1+V~S9|D_z zp_5jseD@X57Q|T~hzhQOH{F-S!=dmP70j*g(6O8#&6%rS{}Qfbw>z5zYs}!>R+KvQ z>#S2A{8-1*au80mI6>^}91eRpLDZM zZ8arawyR8Vn*i8FA+CJBQBYzuQ+F)41QB!^NDF3x;R;6+m>@NvTN?Ne^uT3E>#bFe zYmoEuCIX1b$(!JW_w(Oe+WKM;g!@Q~qJG7`uC<97|NH>^N!-VXA{;pv#f5V*euAm7 z;jzHMdd1b+gSSqW9o7Rr??zTG_<~IoqGJ*wT}-0tg0zPV`O+!98;?W^!pn(!Np`d8ny=s_>hg=f5V3Qp-90KZ3k6;5ch*Ya^-yxSa;I7nu)R*%luk zH#Gm{EVyaB_3EOB-)%JGerT1-&G^=iUT+xVFTDSRb-n`x5Bj4-^DlFZ30?prf}7HdPJP z4iSsbOa;$714z#=+LeLa6=6<%x3E)1qBl8hoX-lSP%5v`M{464&1uiyPYhH3?!p1% z1wuuG!BE0;2$V#?%c0w00hmg;=3b&V(r+vA!3(Rh%>lgvu$W1qgWC(oQ zC~Z%T`t)bz&7YF{{dVJVp z$vWMi3Xm%3l)UpA^A|Rr(zghr%6t*EiMq#~^Z*D!;6K!YfOJAhXdzOW#N!C3)3Dc* zDOl(W)*#+cS)rVz+uQx#ArZ5!^XKQdJ0@RpIrcVMJwevX0-M0?XDwNyDISMoY-^vz zY?$s@x+kX#-|eIa@A#B_#}iO`@cEv38$YM|9@6%{Avs>@^)iGl^u4mO^g}g2e)#Yq zJTWmCQf?4Y8(F?&PMT=fqb%Y<``#-lCet&5_Oa5EP3Koxh8YiWPi$1z`RRr`rCq*% zQswiU!E`>noxRR*&sxF=|AI#Lkqh|@l}WPI2jcK_g#-_%6a^Co)2=sHL*HHcVJtp^ za}TlmUH2^BwJ)t13~u({3F%eeDm-8JiEsFwO~*}4$LAE1Tz+DGmHbbmbF@)>Cl(LG zUhCEsh?$w`CFq-TM$cg>v{rm}ENH*4b;>3Z$ZE<-Mqf^)gkT47P7K1PGSwF9a1M5F z!agEAJeJM)G1$F`Z$oSdaZ1#LxKU%!kJLk?JDdWrJk@{Bo(lDdp+76z0u1FbX^-|X zj7RbNETw%xq>oQ1j30}q2r)QWwwLej5*uzAjGr^vdehpd$h$o*VfgD;@-n3(_4Q!< zTNSQ`TOIes&uzgQB{=%#yw$eGT)i;&b~Q*iv$t^Ob_~60XRb^}EW0T#MECVU4?-M@ zgRGHkrpQ#i`%+h!A%Lh$$T>vPDuqHt9)jE~oM;jU$^O>a+|6}YUmPpqR3A{uWrzu2 zz|kN$r~$|Q`lmgD1pVElM%eiOZr_Ey4yMsi{^xPsadX+u2zyJm#mdw+1c(04g@Qj* zN7t5syj;KkGCsTX?_5G*vsp_Trs21~4wEboi<8KGhwQ{^R*?J-?U+++(_|Xz_DC6K z0$O0@p(WA$td=U}B`$wRmh#u}(KPpis^a%I>=XOpBZkl8U>1K2D#Q;&487iA8wsD^jT5w!rOlFNgJH6$+Fdx|3~Izk zle;St;+P9U^;K>6ez<5oMvSh#+hJu^L>D_$x+upOAB1b8bxwO6_wD4lIF^R)L3BAn z-Y#)f=;&a8=vP9+3Z1}K4XX0@q5^}Uw$a)6ve|*iV;jY}#w6;cmEZ#RF#+-a_3<3Z zGen!56MqQeu<|iof_0>6&LwV^PNJ#A*OcZRcBXCU2hI_?mGj)Sm1wq_d>059>sjD~OkB40H~PELMn z6q7lp;1<7R&wf9#-;b2#%kJddGd+HF&-)*h;v?I;I=J7YWKryi<{ZeM*c&YRvYPSX zh;>;y9=>VLkKDHzSja8k^&^fUd9FB=>i?-nUra|kj)z{!#jA6)-Z~LIgbbuJ|C;9r zH3wL`T+!OLj<^aVf^^7?^#=TWoA_c`tA8f;d8_W@8bsbng3M9(F=VTw+z7m8R{AKA6Ovc`emB_JaLmTQmi9dnF$=0i)(9LaM~+Rv$@Io91=WTK>IoXjgFX&lxPY7f$xFzBjPXt za09!YX@W)#ONmfWW_Fuz_~9@m4j@iA0>*!_RW2_&?I{UZ0#4ayt2DvUWg?=?!G?!} z`J*kkTd1Yq+Z1)p*!jj(elQllYfCJTo)-V5t(!JX_5GD(SOX98(O?4in3~K@Do@PN zNb9&;DJ8*Ewg-Yb_S3@9HfO%HU@5$9_?uKt2l{VAw7g6i|2Qq}~p>;ZAcMj?5f-J*> zZy-5nfsWI%dze!xkn{KAj-J=Q8K{>vJW~K}kU_tlCN{S!E$=zD{s8G8-TtN#q=red zk4l6%gAr@edTNi?z;0$ZY8l@)0ucTvB9+4<6i%7?5Ra~HF6epHXVC9Fz&*1d{4`oi zZlri(lohXQZ9$$g(MNvXkv6}myHlcX!6gZX4o=_p&@XG`78wN|BEOIbbJg0J_~Q)Bthv44(*u6~+ptQl9{?x(kj z_&-U_{}OzR z%vb1vGf;#gPH5+jmq9y>Y9Qdpu>4|dQ_~O6!%K~BUS?>e@=$o0(SXadb)a=0Cx7{T zCI~C$cb(vQ==)k8?i)(w580RW7N{{df{td?ip`jQN{*iz6O46g&rlNQFu29(raV4% zcnSplZPUKN`eTvuo%>As#YiVx7d?`M^NyZ@fPr{1{K|%0NNXd+IXJBMapPyT`-KC< zh4Z;|8 zP#lReX>oMo-70F~7!!}gW@1SvyPlfVyE{U8y9>hs(*aUXS@`4hygIjY?^*~`WKIqC zcowr(In++!+d6!ohZ1RVPtn-2^Ujb3i`oU@&b@+WR=!oeW*pHJjD$I* zu+4_M$@(M3OYfC&swXb!w-Rq>sjd}`(Ryj%T<+!F9y?hLrBsToRGkOJfe%Uy9NkL? z5)YAp5b&aOk0Bt9f+(AKnr^qgL#eC2YDOWgwL4C<)iv?17(=Ue52FEkoB z5wHVrmOh9B@OvzN(e28her*Q1_B@pI>R+1Q za~o25Rh^QmR_|Bh8tGeg<5g*y8>mK+kh`I|8l8xQSCxm}WSj7e8rLrReSTiu1nu0d zEwz5)ES;e@dki?6>y^qK!b870vB?O%T&-<|sccmHh|lr}g#21RMm?PPIsJ%lcHREl ziDVS&=eqO9Lyu`rKbD!dyu9P%zoqs|GJdjXVVNe%Utu$*vF17sT|1|xiHS{I_3iK6 zYt)Gway5Ze4;1m2-Luw`Z&NU6eZQ|)&XeR`@BAHQbCl;ADC|}MSq%*xeJLZ1e-VD4 z147RLg=A?ZYxQfb%dttmVlFV2|7tN-Ha6*?fYGVdJcP3lOWbhSVZIGZU>W2Jgq98d z;z18>$sR;4S5AIo3ogHr^AHe+){EHOW4W0sI^QbG+Pg+cNXLH#sDrsea03w=2+dTO zubm&7;m;lAi&0DG&=DJ+p7UU6+QmXfYt5v|ZMMj!DItuu?fUHQ$)J1~k0(}CU5sWO=aB|DQ7g|&;V_tp!$|ClFrSQlCh!LE%D<||3%sNy`lbQG?x+@|=Em&Dv>*4-_rz(9xRIYU--$lY-+GfBTl7Io1DAjx zprF9im*(?w1)Nev96JZZnK@YZgN@6RW$o-3mD|0UP|~Y|aWw1otFa*E<;=Oz>G?Kx zD*s^V&Vi}VSW`+`uVxnGOsu)B&KbN`i4bQwHt&NS-TW?I@!M_N>#al#Pq%!M>YFDf z&1Yx!OFJ!n?;bi6=VN|km|K$yjz=EH%2!N@D0sGd(l(yxo~pxa zj@8;$+p$?{vgP8!Vsk^|rb>*_y|+mE{#P))5Y)6;S-yL8 zg{dQsR@aWB=_vWf`J2-7k7CLF1_NxVSZhB8Pk;>ZU26y*))^Znx59CMIe20aKr$nl z^!EL<(@sTjX4Q}8+sE@``^OoEx##kfyYB#xh+24Zwmxs%aEVJ*J>IIyg@;qDa^>|= zcK}XqecO!3ZMzMNlYl5LLd`#-6EAOND}9hGUY`Uwehi>p)xd~3Jm1s4^Ge9gSqDD?zNZ?lifSCfv0_$J)6h7Phehy6Ar@lZ79 zA5^9dQ?<_hsmeFYPI1`97IjporL>98x0Y`aQB`cUM0!?Q8h^JIscQe9>6cs(vG>k` zoaWJ#d!ktp{#;W-ZJRTVCWkBTgQDJs#um5Qa}00;h7G2q_;)|VRYj3%&g|KV{2#L3 zJCN%4jsI6d2qmM;h=x^UMJ3X(=drhp?7c?_MUow|l68)m>`f?po$Qr;?Ckx!j^3Z| zZ~f69N3U_e?s;AJeO-?y3$`ypjGtQ?(Z&=p1dp^_zbt1)qcxhrMXnWW?Cl*mTN_Pa z6ddo3Lo)Vr!0DJI<(FyHi)?q=px-Lov66k9yUt8>x>-$1U-O-mIpw0wD; zA%^AgO#^!$N32<%UKU6^?#{0C&ZN zj$Shq%LpnRNLwMbopj>G^%|5D*COW&s#tGL9vV=e3;V%_iDtWDd+fYb>4NJxsgpu1 zXq-a1KCh^DqIX;$a6RQ$MeK0(!j;nRPaM&jd*m0!J|1zOjY}`@v2-CIXLz6b?YjbX zN|a)FB!{e4Ua#nSIR@2EeX&xB)jFeJv`=PWM|<0VAnH?;#ozpoO%YA6A0S`2y66{S z*c=@hIhHdt%Ccp4-Kp%PwRr;*0+=b$qjsy3>BBWYKaGnhi{LghckKlRYU3 zGk^@wi#cfXBe(_5Xzig0 z6xu!siOKaUBTbJdyXl`6#m3Fpbyi5)e?t>(dp+00(wm>utWvr$*KEQ=Wmm=T47;8v zb=3D`q4RE>Z9{62&tW&mMCfqu{*~~)Z^Jhy=VrSMDv@7|!=77Rqi`@0sH-E;9xU&W z)~*!G@Z-9NaPGvh~y*J%+Hq)0c5sIC+&b@AamT2>@Pc?fO)Y-;hv#^YsY-%O2WoWYE$ z?H?Zs+!5eaMJ1}cKtHM9{=!7akMS!#KmL#b6u}jO|V?;;ZANgIgKW@qrQy? z-Wxhsn`ZZTni7Td5R8Umx#PZbb*H65)G@Cg@_6SkMm=dG%|;^XbG94d@xG$t;%%Kf z8wX|i^j_}tU&NHJZW)7boH>#eZDfSfh;4EHxo7xLra%apEGkciQ1L=bnO%6MA`%EQ zHD$TEH)?K1DD#cku()6eVX@cOjzF$^De}h^ufp@h12QqMlgWo_=X!Fdrn9`LL`M`<}2u1tU|G9=aP;eHwG=h5VHwtj}~-7T`?Y$WEs zn{jo~Lw`BSsK<%pXDezHv{&qgQnmBrtH?;k+XkGTwlo9}qsRM4$1_jx>M9U+E91B3 z{{QRP_77=Z9g~HC5ltka+JOvRePeimkwo z>1FezY{HJBlt=y+{!8jCtH_ zjlNRM?yhJ2MDW|!$E2S-FJHh{+d!JRZs%U$OuD-zvoM!Dwuo7e>sMBczHG2spXaB) z)yh`DrlCpcoyEtpb8}!T3#rj5S|mC8DB{?S+gY#qq;HCf(b$?!ZOXZCCsnF&%pgG_ zt6Z-p?YP<~ASy)2B*4N~?D(QB<*cK8PW&&z8<6x1IUa9Zj5+rYh%&^OZ3_wwEQal7 zNt<87LWm9I^I}jVc79HKfo8XC@badCc93Aa>jQN=-~EjHc~$#2F)C;At>4T&lC25; z^gJ2!VQ2pg;zQ}A=7h!t^3;iWa!2aJ#cxO>(^n! z8ArM^CBpQ&a8N(qNfQ#aG^e!Kcemy|5SS5-S3fp@34a`X)$J$t^L3$DkgovZKQ3DHAB zkrMe6-frcRs!8``@uLiDRBzS_SI&((&1SuMs;GQHm&X=@hZX0;4G_*>8SJHnnIKkO7hdtV0-@GMgr}8g4zw3 z15wF2g*0USChzvM6`SP7?pw!wvVV8Ff(1bsBZQ+i_#HDb4c6Mv1b5|qAZ)dm<7SX8 zzF?(BZmoK+SncWs%*ujXd!N6*AHk-2cGKAbArmieDk=<@$-(Wl4)rVfl1KJ=_thLp zTHo=EG@3oxATT5X-)1fNRX<_PdHbY55fOy;Wp;;v{_U)2nlP0a28%Bnf8tdI-9=*<`=*ZWO^*1rWX9pgHzVy+#Hep|*YY;Aqorkp66rG7 zSmSycMG#W?OzM=hm|e^53Ox~|mhe_dp|qx>m1`vbXtll1X*C9nC3D-3-hMP{LnGsN z>==B{{ILuNr(GG@apCkaLaj@pNP7M4oNI}c5za1gZMBfE` zq)08_X1R%+iNg<^MRGp|hsu{u+uJvBqmJn$bgET>Pv>=U1bQk#H|uYAXt~p4&)mQ{ zTpim%#rmR66v?m`oO;CT}C4$NJ>qw)V z7kFC-wobU&SCCB?-6DDA`|7Tic6OfU6U6LUzK)buX&ZLq zF}00|@;j(Ej>G5p$ij;JkeS>4C(48#?KoUd5qJgRGT*%D%-zwBIZ$Nj$(5&{Ml}#d z<~&2+wIvuGt%wi#&l*^vR^D?ydW~=WsPdX6kA|mzqGH5jM%^sWs z$|u39R3ewPm#3&vM_Z}CkBl}NLjE|~zAd;`h+&SU7dZAwPQ2fbcTnRX)Y}mlBZal$ zDO^fY|G3&7Gkwqwtp)4G+6|HFNtrZ4CZ3dyjBgxkAKLbpGCuxLbzgi$-pEz%C_Rxn z2Y1v<*--DVaQ_z!*HNAyoEh$#F#H%*(yr9-%Er%)|K{FS_@#UJBSi)|vfWUb>0<>M zmk?@GVM<<_k5TQhy^CcYX3W*VpAFaZ*m-_4=aqL2`4>d+vWPv}zVk2JrS+`v<9!{< z+QsYWaK|aesFw*^Y2`c&iFwtZD^nB&93#HGaP4i3ySkHCUmk|Bol-!aeW`MvLdBbQ z*4fva8mTfLq@7e5lAhJ+&`N+|9{)`_0hh_J*4xez^Z!6T`rW@<0 zH0k8frI+LX_LhkX>bOY2ie)-I)QoG2r}X5omD{yuz= zud))YC2(b8|BPdbgINg8y>R-@6EaMdS$LN;+jg#-ce5(;Z@($>?c+k*E}O4=1d;KI zja)Xi*XVST$=UN-Fkc2yzGc^2$Kyhj3`4d(GsxKw#JVQqGjuIX{5_cv$|)9_d}SN$ z4akEORo2WtZBL^N%E=*71peU)>sICQ`6ynaX|76Hf~V$La9En<>MffsFTnoAIxBeE zuO{<;!&!}&51X>@&Lhkf#NHr11}(IuN~+RdZYS~-&@$?13}aM&p} z%gSx~rVeHDR)!fVmweigWrE$T8fAH=CAGJ_0(FjR!%IdcwKA=rhfGgqZ#-*e@G_wIyZj5wo`IDmU^7Qg`uft zb+(Za%}}ELyzSrTueY&25#GSr7UiC~E(a5-*_)J`ef`_-kc~xlWKkpcDSr(dZ%VB7 ztLB@x_^rJ6!u+XG?#*sA(a$R8L@Ub>+UQqE=7RI^hx$%7kM@~2?+3Q{v_=W|WxI~3 zdmRbQkE_|1Y&Y^H$MEyyDmt=?*!F@dP)#=<3Y@`I$9Zc8nb(|GC{cFZZmF_c5sX%0 zbJgBSXX8*lXuNq+6;zfgnVqDT<@NivLo~8WJcEOZ*)0HTMcn$Ra^ju$e(LoTx;uC7q87)w%dN)YUs-4A?BRc ztk8cvj$TVvO7bhrIqiK2T}`~=M5duVqqS zI3x+0tv`IFy3_FC4ti=^H@-MNFRe)Ox0l5iw%aRlL?q9U{eQ0OAGz>N3TD>a8};JX zEqMX6aq>)HnSD0W6A?4~lh%giycvnik(69hd#PFVL1pGyN0TCHTF1Exhs7n; z0;w`o5(R1&Pva;EW1w7ZxV;^JDd1&ksZ>>S?;;{5nZh5p&po^Ex}p8Z`7l+O6eyR> zNCSR;Bye6;g$@(rl$l48dM%$)c_lXpZ$L1UmXW|KAcqmDa$Z-gqqovwFtLQy zyrR(>CbMdku-lyVLpQ5?%?sh=@!oFyG}o%Hk5OFYo;365eivn9bZ1TPuTnx94To-4 zARC|6oWal(#-VG)9PQ@dzuV#3j4PmVPR|t!3e?=Aior$lqBl5Bo$W z5AVL!dfR5RuHbjFSd-o)14FXuazKL0Oi!nkJmuZiBBjwxuA{7CcC=Qz(e$7A!gcjw z)cBGAsPf{FFW23dsc|ALeY_<6m8nGPrIe~UD)+a9b&EpH!h{RXw$2=xUU6omrzwqk zohxE&QEwYoP2;CGM}c@}r%zq#Do&a4Vp3sNw9{{8;*x3ZEn+}f0KXt6y)JrZa+R^G z%eJnVN2R;yb~dVEI03UR=IPx_&(1{DVd2tc`KR;yR4`kHL;Tv^QSM$t{gf8!o6T9m zi>>&NPjm}azwFn9UxtW*f+1l)#oO;vVS@RY(&NX?w&(cS?_w;Xw9n6Oc~xv)VoPA+ z2T_y--3cPc(1;-Ck;0U^-J)~DZ}p>woh^9`SWN$a|9NQP2ITi`92Gcv z!_Hmyx)eL#?6unr9hSb0o)i9P`AVzp9nZx#H1b{tEJ70jnwFJAm41lWIXkCEmznU=3d$j@*`x;>YjYUkv(G_D$(bPSAQofy0hh>ayJ!xiQVa!WF#ml zKjqTa1TmF z;n9-(8IuZv9QH(`zRKI}O<6=<&8nGu>0hjnJl~)D)^;m}gnhGpAxs_RSK*dpM|Ml) zj7RmIw3f8=Y9&AQ zUlI#NomqLpFPcIgIzHR&gTZOUi1n+d(_gsr=BKv5RDCT0;qM$nq}Bm33gMjJTxPFR zq%!&-J5d#LW;rAC*JuBWu{R)`vYsV(G{oq5Owa3RP6&`q7cx~pS33qxt!%!Dow&zz zIFUy&beE2vW+Ot=_U;5{@n&XFhCTj{wf>o7613`YUf*ZFo2sbwr!&HF#$0Un-|l?n z`Z8OjboojKi`qieo8#5TTeGWA8p8C#p4j_9!dX31Y5LpnYG!OA_eWAAa$j90F* zVff;@cZ;iuWyejpu*8+S=)?<`IKc<4p=2Q>I~gOy+GXT;7?D;KN6VHm8^}X_vop{+ zXI0zl?utRG2C1uIa`{E(IagI*YLzUEPhCY{B#9>#itz23FIHK!9B^bi#~Lpd6U(EY z{f~{u-1{eDGh5g#;=a4@efq!oaXM2y3>T~>^C`ld4Q`g_g?5{*+?)?plyl4GhjN&fLa|-hQ z2@Pgeni@aGM7;;_G1ZYX+VmA(NoDT7*!(yNH}p;?Fh8g<2fZb-+#_@rJr*E%k~yRM zN#oeR%vR)sKcwbP*CKMqLS`biGCu7esJs1UYf6T1+qB`eqK?U&3zo^)+gTMM{I++2 zK>MtMm&`4`>Ha`%jUT;b1P?wPq|?KOO)J~Z8>a{(X!6eR*Rx&jOmH+o&YpnBOM@rV z{2DP-Gb;9W3G9ZqzVj=rYF&h*etU5o{8hwG9r8tT0nTCB0{KvNvnzzNN$flCTg{_x z{eVQ!S4!Q)?5*z|udmw|n!t`=T^vRgsN}?Xu$Oq%GF}>MU;`FD3%okp%k>3<% zf5s{7>$v+WddTBlFc;~Qb$mfGwHxmcDipW#H1eHf;aoXI(b@hv%bUA_JeJ9wt1QKM=R*9^2JK(H$*bYYg7k zx8*&rQhi=!TYh`5dF4;&y_CxG`MVIi42iGvswL-eF;p3EgA;z$_boW^axF_h>^Y?I z@kiU-`AktS*?i}ABwb3l?-};G-+K$fr&PJ0xG+I}Nq$SHnpU!^bFQBNkA$xBv58Oh zvNFdeq1oBd8QhfdZw|yXSOkiu)CrK6x{8(bmHdA3)KzCWQDsGF5UUX)pa`eydoj6RUC^7F2%+pkZDO5fecm8r; z?JWC&;-MbK@3MhrW6z>o^x$O5}tfwloY55iUlWlGz-qv+rcmBW$LD;YW zKnsP9vx+~Fmpgx-h?K#Me6XIiH`nA9$-~*l6ZRh|P{n2IWH_P+d21bc&$&&zDpa_u z7qm$hFHoU=77tV)8#xcpmQpFL3%k#C6aYU6w((!UK>u6#RZy*mAeRwGSOEQJN_}>H zQFBl%&wpb43VEuYzJQA5NE-o44(D#EkBF`V>hq+8S0U%4vs6z0!x^=|G>b~hC|eUC zfeZ@y=@YEp)2hD+^DS`Bt)8VdanYxAQFYsQ;wSBLCe-L2y6BzMbfC-p*x7Hg{p@b3 zAs&YvdjU^zDg7A&=cp@GTv5XR>hR|o?8h=LMCdolm*$gX(HLLAWpBDFQNtyqA+T)T%Mzqk@F#bn;+35% z4^$EQ?=rhS2kSymOkmyKINC$=DEdja#(n1p*t&YF#R4njo_~7XY{A;97=-xj=q3tY zUGrvLAi*MyAgR|d#SaV9@*X8e@{HFOnOSA85$ERzBPUGE-~@A<=CclQG=G;f_pSi% zkuA25FtuT4?!UM)ewLRZTma)b$Czx;f5AHOqs0V7J;U;HnVpz^dtZhXZPCe?A>B%pwE#uWm~#g$jG%qW6tm zdc_}B(rn(*l=C+*G^&%sHSfv&CO1T>bYsT06Y6Q8QO_C~h)VbCQqATH(hg51?mUk~Cstgw>%ymV$X5o6o=B7MCPvWm!pt0Z9nnksnNc7R# zeCtsY{7QvBA~rcJtwv9xwJ$nReaL%#nSEk~Rj^FMbMU`#z+Hhetq#YLO9!Gw8fO4b zW>)iQed=`VOh3VvK4$szmul5z+}x*0m0UJJuu6?#G#Y2+Q$f0_lW7Q!ehE*K`u$;5 zol3(4r+qvSA}+wmG@uk8eRDmyFD5mEEmt9nfC7apL{Aq-tl5<1$?MKYQyEtD-#e~j z-=XSHr=s45WYlgfAVo#czAx~6b4VdZ3ZK5Kw+L>{R*2(6(~sx>^% zs_r1Ea+GRBrLWNKN_du05u7};adRyMeS?a=ENU>omk<$Q;$VA->WR)-yist1c&S5}YRB8L?S)zs&&>}kEyv7~t& zWyFO>7JLtY1x3{$+w7Ha5!DE8%AlY`_UU7=PW#(R(;b1=_(sD%s*SvNnprV>2EDJS zmMYFZew}f>*G)CUPN83mbn_BFDKd)las=&Zt5C3<_NkE?qUPwV=7sMX^i@ttB{B4q zJqcHE@CDXP+BRnLOA6ZBZ=Fu4KfF(?pm0u;uSWS-y8QQOTU$u0#Rj7ei*%$4n7Wh= z@RU7A#6_<28s?vNE@pr1U|>~9v2pQnJN#Lx60`ba4a;QlB0{F&o`9U?V=UIvz+~bfl18!{C$U$s`zKJk9oO!>4)udaZ;B-v9eee`JBLodp z*qDBB8`-7rTKH5l$8)(qNvt+%%PJsbm)I zbBl7^?mI>}`@e5D0s1PxBZqwPU%7j+GwYofZ+&Y_&VE$$X0hgY)D|6)f>XKUp&lSW z^3m$`>2>Q;@mW z;Of~)3zI&7Hfd(v-id3jknvLg9s#6V!F4>6@I7tIEv*wZ?~apyrv`0i~+VS_{qZSL!$>wTW+k(7UM^vfTC zm_8j2^vD}5%!xQ;1l50skW{}Jh)8*2PVw5}qS#6-o6wPF7Vh*vlb>uvUd%*L*F%K~ zy=(vSw3_RcvF%1}@!*o!H_=qcB=TzZmM2D$;h0!&;GYgUCh2ET$98qr&#lhh&7OW( zx_NV+BV|(4_yeS`L190IV_P);<6A*ed{Av$uDVu~FL~#da{YUSf5lXafYC-*d~A9? z4uABBIlt!n)h^Lg1#BwR>HVixLVnS6>pw5(3?mrd7a_X{AGCfFxOG|;`gS~>Q5Ww+ z3=!{~^@wp|JH>=(5J5YdpbxG_4K?M*h!tO2hBhL9HzGZDNjjT*M*BE@TPM!?$Qw9T3OvD1xiZ4NX1jXLS15KZDqsxO&M+#S!;G0r`rKax0rdK*zYBzZuSl_i}$a3-xgv zqW@P0VEeyu`3wdYkD~|c8wT&vkroEzwokFH&rE}E3g=C$uum4r4wr7WxC+NJ>HX_e zvc`<|TafrXwYnM#s4Pf2!*a1hwFMw<9+29XE?#^Me+KY{5f;4m8&q-89i@^qil2@Mu!LpGNFNWvnM#r-M>o1`Y19V44mm6fYX#l6Ii3blNE99e+Eo3!=_P<4-GkHz zLlE2omAWXfL74VfDMNmHutPdT1s-}F_oonPwp9}kG9jq^Lo7?dLMHq``f>iIbwEzPLSw&n> zfzih*ll|5OaTP|7wKG77z}4Gbo5YHfV6o;;gQ?D})tnrK0*90v*d9|(kV4(&?|l7l z!adr_7Z*Q|6YakVZ1psMJi{OlOaDs_g&~&*=lt-2d@{K@`RU1-)5Y{{Wt+t>gnHqrHCLttbrfnZWQKVWaBATYlm3Gi$b)~eG?LNao#N>EEznu^3o$|lg!FDeY0>@cyE3}g|< zMPh+XKjPf9EEB6k{w;2dAO*3|pT`Knd3y!(X)V%8Ntv&ePVmoHfW(3T40LGB30UIRd&p!Syr z;{fDPvrn95f7jM(dwRmVy1JBGpFDZ8zP&B$ObfDLfSr2+nEc7fNr>sk zCjLl9xebK00woRvkG>A&0#hYhtL$$<0Z1wsn48BNmjT*5anHX)s$kk2A9v}13P<~> zKi|oweVePFu?FvP4Cd*^Qs;~Rim>!?T$}WUi{4o{G}$4 zNdYm6vlD>DS5tdnp%o0;r-!@iTICLeAYq1;TmXt5D0<$@RRTdBl{}qx=pfjHVHoEx zAvqV+twc)36Mvd>Sp|N)uD6V{rPI2-0*8Pl*V)R#%W_Uvyf=fy8dz)zVE(=y3;}CI z@u4*!EPxs3hIu6HF#j0jo1`x#-g@CAgBUj_g&*{`Tu^N`}T;E0V~fD0hiUFK%rk2*zG z`BS?FD-cLwQIUR@CUOzyX-oXe7_h-EU5XLEWTJ_QZu3Hmo<2w6E-c1Gx$bo~hpJnp z>%upNEhS@WNf91^jEc4R=OHtDg9$~U<(}@B9{8GSLbZXV;=PPCcB2|cNcDef@gF9M zT=6=Jt7lKR6k$>4AG9h-Bw~fU3_@oDB!wg2px3`%d3+N}{%PBjU|;-}4&xzhoJGmv zhew}>B{TltPrB?*P1=qKl@a`n0dlu@0x|B(KmS(GuxQAKw}#;KOZ_s1c{L_tiWhd3 z{cGo>3+40x5{-qz9+b)twGO^Kz)~6BT*L#brT&oFx;|7!?-@2i`^p9Naa9i%x?KhE z;z&Q`FOCgeC#yJjy0LP8T^Ees4dOA}0G1aY0^1Gs6ja}qh820z$C0dGnoz)RapYBh zn-aEu=y{(G%U_T#*8NwLHc*potNWr`qZLGIgAHl)cMBiU>4udZu{73IucD`(rPkIv zWbEu4GMUo!aVWg~;!pSgz4y#k)uiSchHEV+MI%Xt)Q_^^+KNuow!I6}k2gM$y)e@7 zl_~e(7mc2;Qpu$CReEEbdv4!H9E z+7Nym^*(KGfah%`sqC11PL0G9>DXZ;;F1zMif@dToR;L4AQ-u`Q9Z2rrpw=>j)HzG zj-E3oQR>|3e8U)ze6ys0|8VITyym-SvzMi*5+RDuNg4UC%HL){|N5jV$sPQqsMmY6 z=@JBhAG0ej{!S=dlad;^kGJ{DEJ4Y9V&!Q*B%B0(;;rmuQqU@;4*^;#AYI}e#!s91 ziyrvZpF-2?iU@uo3WVfzN*vg)RFkzhE03N(**!N~|T z4HCIt-YFN9Ec*Yn1P`>t-d6|0P2@TLtDl7>GyKdv^>-O=b<4{ zJBE6u|LuWY#0$n2Gf}1O&npg&lrdC#@Z2Tv3~4_E;`IDC{9nEYo$uK&3NohW=&9@* zs`pJHMSn&7rXryG0(=-|NuQt264SWYmOpi~F|3uVoQOZFK)x0e7%%Z+rB5Karr~+=`%keCC^%So|lV z{yXLQf8)LmocX(u3ae~2)-zidA^*7^l~MplK47+b+$Yne?rZG`#gGJu z!?4^qzA_w-VLO=kGnf+XbR}aR=LP9anU1L)8^Qzx1n|he4uGHt{*QfsaSvQ6<{fR3 zuhnyPTs}1qKM9s9A#@#Fv%3OL`{~bNC~MiO#u$e&mRr6;?2HrjpW0X0)mYhFtP~V1 zHL%#VzjF~6jroiNaV}F2qO~j^*b-NXrUH^U4eQ*0`1dpuo&>EBAl!kCqJUJs4f)oM zfT@xIsnmA^;-U_Vg7cT_>gb7Lc$|5&vfcmJSuVy#rA=cXnH#&H0^f0?iPm~zYN`Qb z6a|6qCi~+SQTX$UbF(SjG6E~jw%2yKgy@TC z0Hf|;5n!+?aRXYASLUA4=P${n$9i6<2ftZuj{M4UFuT-E&FHbV?$fq^d-#(LMSBAh z#Ubwz3$KK9NYFH30PB7VY|Ki~H^G|Rz&VZQQBk-!-961_^k?G#?(sk4q;IN%maZ{K zuz=+CIbvdBkiYyXFz$gB5PiRh^%{nXHhwo2{={W|a_tYzJV$L_dRZ!WIRM##K3VXs zt2;ORKhNZ%dc?vs5~xPs&Co#rgM&(>25Ge3Y^856CBU9E499tTCcMWC@s)XCHo?r} zc8&_92g(2JZu&o8!`Ax?4FIiM3SWL)?zeStcnRfFCzYg-?^g;^@8hwi3k8*3N3w8K z2m0{;^xRG!?XEwN%Xw-?{{?X>d(c*nILAtqX-=k*8-(VD+XQW|hXW)ozpywNVz%uA zub(!;-vao2@JEDzy((3B2nJLos9WD4l%#n4>z%9J-wD`K!0Gx{NezIb+*Rg(4L2Ks zQp%8pg#8fSR*>}T0FZ<Q-Fa;P9QSoya>0t}`D>R6{y8d3tqyiZ zAmsv1zoOiXI(zY@IHuk&X*Y)+6*QJRi;V70WADL#Q@^g|=kN@51i5)+Ohk{N^ zS3v8E?x7n6xU1mXiGfGeo3J5y{)^b;G2(HI$qlmOsWwX>XH5br6mW_Et5c%a936 zP$rdIg&i@G%gN$rBEq$1!nk~hceEz~a}0!w3)WP6{~JGN!WO16(8aJ_6zDE+3fsj? zf-~wzWaCyf_We@O;T*D*Ve zM_-EX`=Wo#){UrzXm$XQ1MC_HNNgjOS+hiJ3SZ7)`KFc*%qLO{x@^(OShD70cjKf&~*pPE%AI*|BRozMnYvYph^Q6NgR;!dI$LJE>I!^1xxi}i`ZYd z6nk0>w~WI+X3rIdWSns+P>=|sbh@j_@o(jxXn{2b5V})SK+eVzd_klAwsPjj0)ym> zIO2hIRjrtUt2fCKOKyH*pDb_@8vd)X@wl+@^wms6#nL3c0I9EUX$b;NwyzpGr8fG2 zo7NB@&00;IsU2&FZMdhbcc(&$ao)RD)5#XACk~xDC}MAKwkX>fSz5|~;<6DJdl>ia zshqX}R-2aSLh+j{N)Wp@iadzrB>ne|YewZB!@$R>1*T>vl+d1;LE+;k*Glv|+DjZK zb2K=Nj@hsMBXv#>s$kFXWO>xpAreu&vYx@C@{A|!%^Plgd_u8L8hD!WEDSXAnwxf- z(*v6de$VBiTdD344di}kwog-tSFvL3*4b1rRkl$JYPuyJ`RnmTqi_j>YlQklge+Og zRXd@~bq@6(`?R)>vKx`elCdFoYKy|ZyDLZT!&T2Po!-ZVpplvP{X6g0eD@PjJL4Q1 zFSd;D#V24iw%nX=_akZOy2rQ_uK%K@MY4B|fzXN(7Y7IDtW-q<8itbg-3z-3E!yE} zDny}C;rnG(2cb^U=B<+vJc0NN?<9^!$3(DK%fZzksI1LRx*Inh? zwy;IeWW>hFRiASN&%JiHY^Ox$+=q0V86Q?3Z%(1iZ@qI-zkg+W)5b4sAD_X&x%g?w zbB68Kt@&?8{aGyMB^Xc?YF_EG-s;Ye!#58kjwmltE&V>duylw%7yQA|KShlO-7xsJ zN@|W|U`}!vs-0-)NQjgj!u?QgTv4<**T2&38jKix_-6~1&0Dfff`jwA_VC$#UJXBW%Pa}D!?JcUUM8Sd_Dcu#t{(sKnRzTl#_FQX20gh zQ0ltoF5IH5=%%5dU+3oWyYFq@ef;Tqbi+HVz7P z9zUjW$(nNi8bEWK9=c(VIE;{ws6 z?Auz7v#}}J#?8Q+?JxfB6SF$;+_`?Yti4g6R&bB8td;#eNF~He%$u+4Ha@$ zL=KsFuLQ6I@JT4Aa4RGz_yW3UbZ`}J!|610E|r8A01AB=vkP8+nhYmI4lSF=gGG-(RZ!;!t?hO(J!cb)l8okBw8lpJ4^S`feI5JNEg2kaM{ECm=R2p>vht}9!kbAadr3JT zU_*Cfe=E;>8S00CUc=hkp#j0(a98E7;{OJ1T$dxQqoxTWM1f3WyO9|?lWj@8JQ5^$7;}%k&qx99gCFk@fejf zSrJR$MON?so*9MaXj=(O{+UmjXMyd&pOMgk;j6nrYfF<}7qqLubi_7XGhMk&BaiDx zisgMHH<_K1@{~LOO7?K*sOBii4Rd?c>tI>PX5zI~`N9neMScAgz^uts9c>TGGG6nj zW!m8+{H|s>=_P z=<;mjC}zB$GlY*KPp#+8m&$HEz>d;fl|cUN5vO6x^5x=T76~*O?FQ)7%>l#EtkP07 z6%;xP_f3qjr?`;g3m&|Rnb|s-gPh#eh_A`lBL4S)iXAP!+iYw-z=(^Aj!p;MuBgDM zLj;^@Pq!7+QS)jSNiuT9YJ0P0Wt}@9;UI)MeI4^kwUq77oqiybWdIU#zQ5+U2zFW# zy1IFw{5XA zt(x8gfc$6a8xahio86=#B&rilM=BX+w40WLS0zRsT!C*Ln?p9Br+-DD0nO!kuw0^1 z=~4hT0WwC{YjE-mY=A1dy1K@RcvpiodwO;@hsZh-jO)(#Eq@qio2`kW%qCq6NxzlOie(bL0 zSh^2@Vn>igH=nHc$JRLo9oAV@N(DK9;gk+q8X9FSt!xl( z-)Ka`iJMKY1O#zW6z)EK zR;haI>2lpVQDn`ljZx5d5BK?9?=FShPr}Qu7NMnJ!=KM>)09)EQVlzuKwU(}#N3Q; zPxtjb3p?mCV2Ul%m?98S*(xYNSZdJ8Nl0|V>BZ1t+mCmbi%h$jL+FK7Vq;@rLh8eQ z;}^+EP`3FFA_|tk>_s+(B_-v7f^D(TF%a{`UHuWfD80EQEVbE@9GjX8vd26Ac10+vPI)uQtCCR#oa#eh00ZMXgI zID>@q1SArvXpwEQng-3FEH9r7(zoh>1Y@9=A})UB&w*iA@+_h;q5S!x;&ymV z+jeTz{!?S$V<+8Wse`{ab%ebqE`JiSIk!RZLGL&@Rg2phi9$t1Mt%jJu@*P2!~7#v z8StPpKz~AKZ*OmZ!jFurOb(+6>mhXKY?xrFn%UXdBIDwQW=({gSF&MDXXfV0f;5S| zhDKbX%O66cmoHz02L%Ts)YY><^Mud4$*c&Onfb!|cq0jBfpN1MH5ZrC`i2J0ElL_1 z4Bv^Ud#@Ucgor0QT2*RRmS}-ri^#5np;8Loep{j^tl?A&DsN!OkLgRKYsQ_>V){`n&5G=3Y z0F;fLy%(sO2o;rdz~BEgE?fXvl^B-BA3sci49>a#HYi9DPBl8G@uu7ULIy%dCl^jp&EQn8{V5l?w_lQzgQ*8F z7z{7WX7mqS8Mt_v@@xKU`aLS z*_LGF{m6I`SP^S0F6G*6nX#pThajz(SHQKJJ74dGqW!nnGCnS?N1KF(N|y zSE}wUok(Q5PMCfj&F||SX`a|7=@2iikAl`hC=qUVUwubJM)+@ydtC@OyQ&0lPN{Cs ztqlCv9=o^dDY^12;``*UKV^AwyT9~1YJ)_@^1g>6c_RlrZNeSCzcQW8r^@Q1ua>ZO zG2NrAfM@YNLa|YU_gnsZ}TlCXNZS)?^P&heTTZa_2oO z2Uq9zgPi?u<3#Y}>OdQRDfUqob=t234!4;a(zKyBys~aokCpCmjD3T(mv#yv0+l{k1t4Kp<`cel>7}#4{T`QVetogD8nG_&%6q64ve+8_82-A;RZppbdc=lUj*u2r z>|E3yMkG9Kd@d`&eA;9smvXy?QkV}6V>oUzkELmQR@F$V#HYOPPyokhp{E+2fTIe< z<`Y;c(WnV!^?~1OWN+BNJGuBBbvGX5TxgK*t|s0o`S-YHc%0%g;X>P`gN;p#7$?UG zmyj0OBvrK+AD`_=I=s?_+h3!w7wwTA7>WhF`~c%`kxQA74$UrlNxzP3nHa9H;e#>@ zZRZ?uJHBnLFgP8zhlGxRkgKfb2|joiuSrBu+#T>Rcwhop+tQiGiHpqG01b)U)d^>M znjzW!i)%UP-xv~rF*Kciq>^^Cb75j#1CJnfGkEO(D($-Csczr@`SzrGT2w|9Cr|b% zLdZOk;wampI9AzvCo(Fd5^_p54J+fwKDMZYjLd8*GczPIe%DRE=eJ+4@9*{XpU?Sx z?tS0ab-l0mbzg+v-!Q>95^m4-mIUEwMD_Do`lSuBN7N#Ipd*R8XJ|K*h+&bFtzggy z=Pj*G)fLN5dfjLh#&^9Zp~T^e(YY7OM`&XozVY5%N>JKl$V^zqK623``p#<8J{w6V zC6UEor3brPEBUkezagW}K@8rCp0O8^cQUqI2;%%CiQ~C@a1spw)(`ioC_VD6fzm5< z7U2(2j79^5Cd1oZyInJMxgNQk!*2ajK}R{(WuvjI^2?dYponkfnG)GW*@K(&LSRV- z7D}o-v`goq3M-k#Dv>Vtaa*TpAN|xd!ZG+|l?ghvq{m77`1Uzci+{V>SUr}XF&BQp ztnM4yZP#U=pF817P&M0I@uXN!jy7A`pu&`9`-9V5}?%%>!_Doi$M zW;qg=lsP}um~hk`Wtk+)psMW8Qg@pSOHPG4_9fkQk8n|6sP^Z)wbhS=<0Kj(rU5Bx zLAkmfZ5&yCQ@;GfR}qgn&o$f;W0iWgBVD=g;9qSx-a1Y%R9ydU2Zr|~Se`{nMgxs# zb&exTYnIV3{j90D0C6f8e_cJPGH8gei*pM7((mWMkjm#q2q50SM7~;lrfj*In7=aj zM%;f#%xNy+kK~==Vpp+8otzbg!iOi;w3(*u&xfCd zC);;d5uZ94CsnRoNH3RhkUO}9=H=`l48~v9FSO>$){6F2wTlI+j+eeoYZM$}Y36+Q zyP~@e40qFh5Q1GbEyat2QlfxXotqB5s${JX{4(Bf-{@p_D7s}A|`n-0=p@{vqYuNy-nufMDuK(*0bhGmd!SwZ}c;eAt7|HEz7MYr8G zc!K^wS_Z{Y#r6oiGwTMWe5qQ~PMCT5n4_DO@2YmK(G$Q!SQkWq57e#~^98xkgla@5@% z!;+JsDh3CscJ@h)v4uRGqNEqX2jjX$;rBrtbnk1VwH;e&@|$uFhq`8$wCyl$$BYh8 zw%yxv|4OX5{YUeXDb7zR`%O1@^ERd-KD9RDMQ+;e1j+2Zzq)5aUOxMn?9D5PCe(5Y z9h>E_a(MX4bMfzzFRC~8FtuxOI!xq`3q@T%xC^>g3Hyhh|C2q@ZKYI{Rf?AoEp)o! z_m?o`JS5O$*2pi&i65E&L^zFZ36$w8@cq6+zDe!D#mO#Bv)n7-@o9m?D*QJnfLsbU zNxcB8C91*9)YQ}xG|-ccwM|W(VA0bbI`rb}R};9Uo#?qV?Yh`GYo}7~WO_J2+kS&^ zaH#+_mqTEe4j6n|1_tqvhbhapr+^o1d_canptP9LrWi3*xRtjZ(#U6k>N$RECtEY{ z*7Cf5{TOlX$TG|V>lCtY5ol;=axR}J9)6;yrKk6ek~OT)@-690$y8IE%dk~vw$)U6 zsyfIsJJ#N}ytbRe^x?~p72Ja#E$vxg))1Wp_tZ|b>lhMEOcJ4I9V5$-gs&44*uRX8 zJqqT_7-XB$Qc(#pa3AuAiYfZ(zotu6;XZW@ZS5!h?qBvHxDWE&Pp|0qCpi@YhV{Ww zBgIa|(y75;j`7eAj&x1=RLyRLFx|Xzms`@_!a~i_F&i9}JvUGA@F+qCqh@fr^{ig< z@+$ja<{Wel++5v|p_KC%DB%w{c-h&9$hIAwonjS`F7Szo;cbiT%arMQs-osb$b)LF z0)2L}&CAaB-Jiy0BQr$L&FFu!7g>(h3f%xceXO7l9reGOc-^f}6sn2;yg7|aZ|@#i z7L8F3m03xpluS$PW0RsbIDem?&xdrN+BNvK1k`6ujBLDFZ4Grzr2fVI#;q>5buzU>WzfDY7A&{W3 z*C_~qrMPw0?&_=AsZXDtMP|6%Imv=m{-41SoCN8bOX{Jo#rKC=_LU3}B+__0-CDEO zO`ldzy>|UyMk!i5Uw>a{KsrQKfI*oK$)MiO-M_y(DLJ`dISS#_KzajXxfQN)e+*z4 zcf7kCGc$8$W1O&gh|KEjIR*xXmjG8q998&j-XcVCF&ge|mtu?|rmY%~>04YQzYZ>m z4;Zzl4D@W2O&{)WuwM6exY2()V#xD9%~`DY_3qXXg+01JKeGh>D8L*xGG@75T9+@U z3SN6h`jHF!a(sN;%EqQma;EeJuV(V;3iHDOaP9gF$hPziIB&oLC?ow~E$zSe2YEP_ zo`sk5ha0u%b{|8U?W;8Fn|=XHcdu7r(8;wiIA?kb!DHgi$vL^XB2Hfw5ikQOLg0e? zCmiGbo-;%bk7Ag8P6FJEuYKi86y&-}%gGTsdHK~@v`X;n?#?kqMMWNvbZHS@=jGzM zFg!d=PK3*$dH?#W($1~NWq$CntcKdF>IT45W8G|vVV0|>Q1$Cour~n_mhfJs#(S?= zhDStLk2OEj1^%3KSP*2P1@Fpdnu6kD3ApT7btf&GmWxZClamv|USJQ3B+SD_#)@RS z(z$nxUS;6NE}kj>MOq6ltFfzHp1z|+fv*{d&rVayE}`4vqeiGy&$dV5|1ZJS+R^5u1>yx%Q;^F{1Hz#irR zmq|IQQ&o6+JJXZxD#K|AA!yz`RF^=EAdIRiB^&W}Ws}DP)2xV~9le(2Qf^doZrK`g zS?YIlWt~ikr3kr({UYsJ??12f6DE$f7TZWeA#`KAbk;u*km}wXO%5U=EeVr%0lrb` zw$CqH$n%zRQ~{f<*i`NQp&dKm$Di1$aJ)5N_4HtPdNSv&LpziBgg)SQUqXkUL7>BM z7I>J_d~)!rWy#eImor4YUVTaBu;km+zkDzLMOsep!+yek@l+a7VYN%P7;ub}Fjv=b zp;GEExio%)LNIuF>URb1{fY@vmOe5z$>)?s`g$gGu2}B=)2tZ%9#Lgqzy8iDtbaKZ zOuw@e+N7sy;~|}iuXqAuNM&)JdT8XQV76RqmXxeVyAxC+ z1(No;QfsA$+q=Cobd6uj7EeXrj&A0VvR zxhmyuEIlgg_W1eudG)!4x(znUE4t)O`y~J8R9ELGo0jOn#O^N|-_MSZn8&tEat}mU zZ#mD_7U>q1oJv0*Lj@~B!DjUumOi)WuNFk;(*`?GYq6?r6WKnK4>{I;tQZu#o?<|Y z)At7~A@cV)jn}O|Mhm5INqb$WwGu%@+I6p(#ttzn_fYpWZw;To9wZXC9T=+9x!l-Q zPtiM)SpF#SKn1jSe&CluNeB@q$am@Ddgm$s9m1UOs&B}km?ieWLRYIsy8*8RF*-+H zDC(%)JPef8uvn5%RAR(*k@m~D4=RUwQG+Apq@*#VD-+{aX|NvE>sPzeHME{r+fGa9 zW~Ox9l8%O*jr~w8v?6LW8JW<}}co zd?DtUp=r{%*bC1y#wJiTCK?o0UoZf}7<#~J$^t)JUBwzpRIFMZ()TOR`=w)MKb!wr zXkR~cfA5|SoNxdyUu^qR_{}#LHbXCyCvLH2^cN>#xzO;146h&?+X47(FkzRD_hgFZ z=mHjZk%Lgd+;>hhAlcLHEcy<6oV1Lf9cT}wb@W8tL^ol6-PAWF5Ka0|k*e?nkF3N? zl1i#bJ3<|weQ2agi*`HO%=pEQC&$T&K1U*+QRc$f*ud?L8Qg&CEbN!B*h)I-vdeNI zhjmIII>EPZuL{Rn6Vx@Cp0u?r2-Vb#z|17zd zMzPj{NwOPj?P{$?JA2!Xp}MBh{30##X)k#(Ko6v(Sm5z72Rh2?`}H~&1Y^l^jZrsAoMjLm0rdQ|Kg5-~jsz=m3rtj(jc5?~W=qqo|g z%ZrX)k~nGps_GY;Ej~02p1uPxQ|F3T4JV;h!DW8d0+piZhf7!p%}mN+Zi### zZ|V}V)oRRLhhgUo(JxoogTgjFT$oZC=y%3|&dY1&6ZBZ-w0n0nq@|CdBEU4e`5`7| zN+;6}+d&*@Hlhth67lSzs&HCfyk?5P4{as#v@zirJRBtM(vdM~7fZ_N-Wxo|4BJ95 zo(+i;-voBj@~)VM=KGm|P%k~0oZjmDPjl$ZT>Gsguo< zp74BY$}{2rr^T{-z0RcH)=nwIP~A=&aXXC{4bAy|U)t~@9b4Zv@2Coo$nDx|oAGKx zxKH@@*4hAo?nY5VplVuLe`4ya(b`2ue*~an>|q9-aD`6@WN(qgpuei+wiYQSLJpn- zn9d{fp?P7F63>P}QQ!JOjk^)Q3bV@|d%G3xNZMMXvu1F3{X>>ZH53(C8BT``ZcOE$ zo6sC)aQh}$igDOhg;W^KnSTtSqA;<(n;;BEsx`L zgR-I{JM;6KdubUNHuI}D=0_|cU#!RSa0GnBFFjlNN3^JIG=vTH4~e42RjRYm>I5;K zY?;GY~-8uK)%`}N0!?B6TJNifYy-m00;I2)hM^>Te>U3VpNiZ|I%!5!muLf*Di)jML|D za|#rBG)fg~Q}%I!o5Dk88b%KsYOSVCa~4!3B_$09hgW=je7Z-oQd8BetgK=Z#(Rr$ z!KM8I)bhA9j&hckmL8w)aX$_V`#2<8U0uz<#@4?oAt9lgl$3P;-o3C|6Q{2@iHzc6 z-M(U1O-sv{V7N(3F#crw+aN?PN!H=}Mb{1oK*&&fUS1w9{@X_f@ZTYacKWMVYQR1X z=h$-TS%IG_VlAV~MjH&16O2LqH%3|eTs!sm7j|)geGS;b)a;Uz|EEuvy{S*D|2C|U z@6hFO?r38;<+8}!&z#EAQmKYmam}u-E*5d8L`DIFjP7n-7@vz|7YHKala|&8A1FBy z43G4Tj7yLN7JQmfj3+K116Oqo)@Lu_N)Ky1>JJ1$Hz-@eX+9Iy}3#GabtBUs5lJ8@BiGsrM>@S zU(PK&9E9AO_fG@g1SYN4M92~b;$*+r-gBz>wY*}N@#jDiK;CNn>g*l!9ec9K;A4jn zB_1&LAX|L2glih)73}#O3rk{nWQ0#pP#xTmh{U6%u0HhaKy^$hq?}<9GEtmwkf?dU z`~u8I>ay3!eo6;WMYv&YDqy|xmJiSGjL0>5y)EieGNTVH+JV*blo8sYx}ePei^LJn z#!`C8);2RICnwLOmMl8p0~zubTP_NW1H{t~6mu}llVE$LQ7DZK$NdYhRCt#;IXmZD zwsL{1{r%PKu_tbADF^WqzG*o|j!B%Dpx&TIiUxa-20IwI|`9Th1(4`k`ZUgsu6 zo*B3~AB;#m%27h+A$w672lS#5rYzrOTw@=zP~uz15n74~1g}XzK;C=;WJ^9>F`B)6 ztBAGq`4cHtwF41==b<@^RSVGT{q;Ek264J#S9l?6*k zF5HV!9!s5)bI+}-Q#wb^_FnU-J~ipgdHQtQWynA|FJ5weMwEjY0^koXf>(}QWT(w-e-z_?OZQ!|1*)Q#?6!xZ*b51P|bY}QwoFKBCP$IRStT6Y+(yC`z{ zbSiWWuqg`}MquXsd5FsbVoTYMGT&?fZ!=(a{a5)RZ#DtN*jy&ro|KEq?VWbRWPr zi+2y0C7izAwrCHT?Flk?obOoOd-ve9(?X)S;?s9In=@xl=VWc3aRQ3gMMRqt!l%*)ww zkQ}lVW=pTEriqPI3(2e&Ac!H=u)-UrE0U3)lzPODDm&n{6sIss3!?B??Yhsy3V;9^ ztvhbvAY?QF+U7Fyff-S^5NZO@w4fwO@t}1smsdV`e2p|nkp7}=!qkvz#sYu zwX^{@aP13rLrq@Zujbv`oU;OmcmZjxwTa4bx&o(S;+gtuCXoiFk%Ro^aKx=Zg7L+- zOopidOf=MJYHGGOH$R26_JwB>mhW%@(_x~oq%eRM3(WPKASTD*Rg>w#od4in@N#g- z1M6NFRy>MT_V@GS;pFsRzT0F58PH*~ z#@LrYg@N6o0TI61u)6`a9Ug!7y1uQg%>ve0Ll!NoL?UnyIXO5|p+dAA79potnrea! z1ZPIX1KkdeF-wqQ@kdUV%E9v6B-?@91bJj>5Y+!tlN=J(+8+lW5$3aGNYheAbr~31QJQZ zjPUhlHoU-FyTc!_r2d8R)?k=|!_b}!AX5dsR$Q*3VV?1{T94dYeTsBs0LhffjqK5X zT{q+wj=H3qYZjam_z#SOFesgsS-qg`0JxL6-U}o}IMFecP5$m4P~(}N%)TBX@hqF;6Zhw!OTj6NJQ&$j$1~?fb3P~maWOWLP8o|D+?ci zD?igMun#kP2AX(mP-?MF6N$6DYc=~3F%Mc?=r+@Tl8}~}*$%WcAn9dg>J>r|6LAGr zqOMMD?sQ(+&^YvvoT;V+O5T7FiS$r z0mkkg03e*H2cB~ZTo*6{9LbX*_~oyU5LwVvC~Bed58APC9Ro{md&phSB5D)4{ym~% zEX!vt-FxHL0BBDjbJfX-fZr=V;#TcIq%_bpfdPe-n?{}?v+#mYtjV=)82r0<9L9HGd04=w>n|yShMb(-{5-(UdG7WfA_e()dBZrSpclYG zZFsFjM*acN%BK2CbhsW7(0T`&l7M6Yr0G444+VacjZFs7pd?qqF&G(SQOrt0+cKYw zi(izNe?yF8Vqxk2oL_4~ZZLCx`w-yD+tNBv4oghf!mPKKbUx;ZJ zv25XpllIhx=#p?Y@1Mp?-s%`%9dX!D9WI^Xp``muS8vAd49 zoQIH`C%_TrAt2r-cf!r*3T!vzk6(D82JWY6>X-c|b@Nh-GGWJqhN9xL(wcxcy0GU7 z*ZXgz{3<_&sl=(Dq{Gmu0cH*%1ep+d<>A2tkZd)~6a4*$-R21c@DKm?Szv?=)%{Dh b-0clo*L}N;nqh z6SSvs;Wx{;W1;XL0f&1U4$9W14o(m4Oi*$U9c(PE9W2cauRb-gvp2W4;%4Jx<6*h_ z$iczJUXY#r$-f_9v$iv1UyYB~gh9^ONNL)mP=pVWAFOn-G;FQhs6E8X->#D&mA{QbSXIA2SI6`oj|Pbr-sMq@s8_r7;+80J$_ zXB0~=U_Qo(g$y>?p8N3Y8-IV6j-rY00bh-|!Yps8{>W6#;)s&X)+%hQ%>Hmlm6w+n zDNAqK60Q1?=bnTFmt|k>g&{MSo(eaoGN(M1m7h_Od2vK^bbfKM zx9G`!+hSV2AQ&g;NOS%A%k1oIuI%iU9<**#iS2}xtgM3rVwSsavyH* z>`b~^Z!HZ)w)}NVe<84&C0R4wKlPO(*l@8u;G<7{zEFdn(prI#CkHKkmo-W zYVO{>uK`yw|Mi(MhR-_naW5K%Tp2k$AoE_XI*g~VDtWfDVxyz0o1vUWz+SO_p})Vs zbkla0JRvquIFvzQ%Ik2K+HtN61`R8EGLUaO@m*(Nif^jXn2Xcyw^Zfsl2A176W^>X zX1VB_4_C+QT;}u(El8gH`drh}5+LX}w{oz%O!kPf_eTir>YqO}JUl#YZZA#|(%-z< zxOE&Dh=e*9=-Z%=#k=KI~H@*udoU%i+3tSA-4_HUvJANLmN>qRSTdm5n+ zcBZMVs`j6rIB{ZSWo0z_G5Xc=a!P{``m*<@3HBLxZ>gUA?b|14 zCH${mzkZUBk5B9Kqnd^Og0<|eIx_wCGRMbXDk@;0M9l)zFB?7Dn_Jx6+?T{Wg*WE9 zzrwm!SBnceEj8zxH2Lm(oF~e-?DdP7h|!2aAwJo9q;k+@I&RQoYv|?6m#FXLr0neM zaOqbO5oBVAd)!9#fpm$fq@wF&Q#m^PsMgCqqk0AV`EL+u}cv3IE{~Qw70!#Y-Yy&u=eEh z7cX+O20q++;XEDZq)}pX4TdQ9aIvsp65CtB{`&gdSHryE;9&6_y^7NW1XHEc@n758 zg8KS2DtD%0vZ!dq?z}!bR&$ElxZxe$pz}n)=Hx)J^>j|vf#E`59?EjCBm^Fl9gMA% zByrBr$jD{6Vryo&LdffI-zm|R^a(Eo--tVR)&3^M;lWmwc~?5oi03XV5(EWHuvpvE z30~x)?)-^~i7?)a!~JD1CMW)(f)L0Y0-GjoTT6uk0s@o$(<#|%S)W`t=8CkfD|mYU?5s@>pa$S^TNLzL7Fk#A z_u%&NS`9ka?UQstezHWP(M2^cPEBha4BEH#qXw3S%AfFRAB^le&iBCojTNw8Xi`J# zm}6TqtD`@&m#>dZlrL8nU=>M+()UN0n3(jJIm{YjTXLJVer9i5E`dkwf?kFiQBbk^ zor1TT^y0-(vwf{Xi~iRHS1i2tzg<-5Lk-MzXDv3h#)~}8(k(Ay<>KlHkBf_&*SXAN zVJxGdP@J>dqiqdW-&`D6qntN{vA@h!b+Z-^8rs|1<}Hp?jZ`kcW97BBw$_I7u-HW9 zvHl>Y!8m_^wVry@1orG_oRcSi3oKg=mGwi}F!d5~oKvAN*j?{bSZw0r;af8S!tA1%2*WdCKH#Gm2tUmuLw5{ z4Gk@}wZ)4xK{U*Cq~OEDUHDZvpSgSG=A-im2M3$Ix@8Vn{xaXtsggldu*mfXWiD$| z+uPfH#VxI^raONo2kn|zU;6kA^k!)nvq894%pJ(lUxbY<KF4)Pa6}e*2COf3<``S}JguRkA9bB!%3+ z(Db#owgjr@_G0mf)cyM>44_^)%(Oq7nR&G9iiL%RbD6OC(NCJ&ckWygcFy&Pg1s6f zvPs_1&;WUx-TP;el9CeI`E3Fe7NMsL2Ft@0uS9f-Lb8+q(=g(6XQ{VsJmjqpydp%- zVSuWvtb}DePf2N+aCQRHg8GnkOEiytMe7-@G=&7V^&)|RY0DT$hOo;aep?FkJe&S- zKWe|)(b1uiYk-A<%d%*FeluWQH6&^Zi*GgPI{(R^S}gvk2c^ZFot;%aX;_n*{JTIGyehkpj_+W1b1s5btPD$Z}<=Yjc z4}F_c`L|K@-ro>f$r3;mk08X*R5`UJu*+9BHYN+&M6vzz%t`%T2`zu=tZYpR5^ZG8 z`BHnuX|QH*XHB!rff1sSmV+Z#B~7zxB2Z|1^abJeR@Gq(l$Wm^DKd-H+cIvhTa+fN z*7{T`S!w~Fw2Si%YED>{&C){xl7@_JAMk4aS0VH6*7Ed3kXR}dPj>( zpN08JnIxWJy?eJ2LA(4ef3Aa zOh)K94LQDi{rXq$&RkXwxuC-h>&l%}kN#5oXT4)%AA3bkBdAzYv|UE((NuZUo|dewXEs}HyPwhdf+ z7S;@y0JGA-MWWJ3SKtqgQu50+brm?5E?xQpuq}{@k<72|b`X`wHpCUb>w3D!4#e5^ zY+3@|mxNm{a6{tbTLDUGesSh>8nl%}Zz&{*#--I?H=}H=i@;qPsY=-2-6GpA0jP0} zn>*ACN*yI2t2PZPzq)tRC7o#sZQSQPZ>`Vw24!cn47)9h?B*{lSVA3(pNjNC5?@*2T<^_&14Y!)fpzL=jge^&6cJr z1qB67L+B;hPq#v5K(&`US@(R>u7{t+d7vo1@F4Uy_#rvcvatn17RHn;PLID1U%q^q z>G?zZDNI$DvTV^xuiNc$GM!=gy zcYcT3IhywX<w0Ju~i#J3Vp7_q1aT;|yZoNw#oWHws;taP{v zHX2-3VP#_@1sFrNc5&cjQ^Y`8BD+6?Kxc+B145Vpz?l!0a3X;p;RD(bNKD-23? zNK}+G0A1LI=9Lv;u(fbUccv4jTZNXt_4h}?00Vb=>yQCN5BKchuas<>Xf*~!QM(62W=#NAk>|2zN<&MF>>rH+({qqC z>jnlWymyzY65#K)Lyo-a^86x3z`cL*RZ4O0BclP7b5XCkCVB9Kz^ z;|MoVMl?c^8>I{ku8JLO(;n`$c{z{0B3s$onuh3}`a7SK2K*?HjgUih^bi1n@J5%i z|0QnV=BMdpBdej};@^yU7zkm%3K>kX*h&|+aoBtXJj%R>UvZIwJ3cW1IWI-G{AqKX zP_O9EI}c!=;u2CdQ&@kwb$GD9NL^x&a10F=(y7+CCJ4fru8fOK5$x<8Tf>&T1(4R_ zoyX6J?yoD$(qBY?FQg56R_&tZ!X>i=kMBtGgf#l1#WV>*eGevCYHED)(LfO^LMORR zn~^H3@k!0l(D2VW^=sFzW$TuQ!xzJ6JJal!1_h$|tXtukRG;G;RGe8WjrMb!VS_Ej z5q;CV7NFN9V7eC>oi#h!PeMV8LC`-E-`DBsFI>Ld2&9Fa z&ni~LMijOUi$<<@icG}2_;`8P7|xJ87x`>Si5Lk&KMC(QsK66T(Y7kR*QqX(;XMA9 z!5Q|qw7h)f!Z!*U8j@GvK@yQ-GdDLc)mt7aj{t!76QqiI;_G4GQ=ZKKZU}Y%)4<@c zG^kl~|1J~G2IkWbA3i)w!Rw!%eglafx8({+S64x=z135&5$qjYl%Cy_lpz*~;kGh!4zKD_| zHECMVk5I?4u`%@u>GE1t(LgE@n8M4Xrt=sX$Zj04L09^N3E%nmel{Dhdsn_wSf3{& zlLXutDe55zbic`I2!iRgy1qvkAWLN51BTdc^E&t{vNdR=kBBAB@ghRKPb=KEOd*VL zGV5W#aa2BoWN}Y8>m7Wf0m|`gcNQ6FBm|%CF;Nv#GZGyCFcn^54D5I$CM_)udO{y} zZ5Y3>4kXVY*rc3B-_Igq0zlr`p>n=*r{z@GIW9efr%xlvCJi=wNlD2HFq%D9VYt!Whr0vN8GWdabKT#kg1;23XF8NJ@JLd4iMX~>{WZUe>djWhL!;A zB6MJV-GPM^AK(|;){s-e{yux<_6fLOi(YgK^Eo75u}ktiiK)vj09$#$waDvRKf-F9Tw$Cb@ZQ~2g}28IH_EFf>(Q&Ay? z+dVZ3arQZ9AX}3g@(Pl`H9(C5mBu4}KY&Uk8kVFyhVSZJ=35$^uwF{#)gmSf(#FNzpzOR=7D*zsY=~Ogpp%^J$-= zKET-UI{;gy;q~?P7cXCS?O%j)4VfS3s-R$WoRAZj?f6}{k}?&T?5$h376yvhM{FkN z=AxHhBJn#pMRwaI^S{P$LM8((?F*1>LZYL!k{3bW0O^8K=&9@$Mc8d-i`~_g6$HnV zkwpkElT4XK-uW8l=Z6m!6M=0Aar3st9wA{?XMVtHuLz`I%m4mu49ElR`c*AN25z~}k{8%0zvmu5CnslD zmU@oHV(Xa4rzD90LqHp!%{yN|UHruf+!b&TqOzd2hTYg-T#*A(iweJBGk`4}^lbUYW9|`SBDN(Yi z%%bpn_2hjkP`?0*K4JpW z@1}{Kp5ErP0G|}wk8>6;UcA6p_3`s-B3a&GnoK}2BdGXY@NAX1^YJ#MntrgY^X`aP z@@hY`ID76~p_sde2WOP*W^eh^#aa*n0VTZ!z&bHE*9iK|ci70KAl;oga|Y2o5rNo! z=a0^A#d^Lts98SLo?ut7uppjY7vMYa0iAVuUpBDsU?M<)~Bp8kLq0k;6U(HxOs zVReAyUIV*+_UxJP?n1%YD}r5~g#91+J^tQAf(Zl*P_NsIt@SsThGHJa5sGeCi%uTE zC6LtW>FF6Ul-6xwQv31@)E#Vfb@kn|V*(H?h!PJ4wxqQ5L6#cp?x#pgUJ4)?NzhV& zDtUp5suixQ_Ir(4ZmtyRPJ}3hhDXUw@1(DShZn{3My|C*`fr=n4XCV57H>X z6~Vhzp8L*|Vd^%HjwaA2K==)0AZ56_rX@4bL=hbjWY!l@lewWqfG}kEQ#qfOn#$$! z#~5(=MaT}I`tvD>Y!Cw}z!}}>)i+xjECq=;6mr@s2urI&P9wI9g}tOZIzHzpz7JQp zX@WKYdm*wqhcYbXL?!&$Ze zfI4H}DaV&*R8Ii#svh<&qBg8ex23^yPzpM{0l5@w1!l751v04nY8}~4^NyD#CHx0_ zYi%?M`sRq*0e?z;fuFY*m?`YedwZimz<%hp-yy@k3fc-#;pa`mhNt~Uxj>#oArJ(3 z#`o9fD3B*zId5ia$_4coh!i$?F-J7V!{?wB!790~Kf*mrj;e;L*8)P2uY0^eq6LU1 zpuZA%12Bc_*1&qz!zEe)V9!GSM3xQ(l7bnai9G=P5kt!Wuv|9#%}Uo=g|KLe(K@B? zKs)>cb-@OdYq(`e(2^jeyE0XqDi=XcJag_`3ScRIAt88na!}LMf7`Rj;i*r?&i%`x>uf83Awd>Mo2_oHvTX+F4#lz7{W>s&wnxK;pnyOW zl=nQFvD;8HB-GSM0SZzIJFocenh$>|-7if`V}J*E{rYvCryfuc-EvQWie8Z8HPw6x zz`8xoImp9M-14+Oy%MaV6mnYn*3j@443@$I}Tk!ZDuwtJd(hSlepKzKBJNEn+$0D+qZ8k5F;TV zO(BxTlj0#<@w<0V0{WVQIIjc94k;rNty}&sDr$B#b4{s)X__}-6?e4nnFqm9FVQYr zv*0z{8>c}v3bbyCM~`kmf6zqhMNSSokPGM${H$aFa?7gidmy<3yC?+G3gD8(CeRui zV9^lDi8^=r<_|~Nt8MdsJD|})0)V0HSoI4`13VH0=HXx8KyL8{4!#N-!5*}36y){U zkt(syR5>F6QwXD794IE+5tfnJnU@LGQ5vkhio>O#U+SlctXiWy0%WIRtY_dmphp4R zB;HZ_GVZ+oQ!#=_zcd*6^ZW(R~!2>3e4zaYYe#Kp2j3l2wf9?z$O#1$PrZvHM=t7Q{D4n3?@xI)7k$+D`=Vy$cDs1wuGrfROzQb%43e4}%>vqPlnDF*brfhO&Ei*! z!gufAzYGde$Yc1N?whT~3|h!|pwQB2N`xL$!G!2aH8v>je%)DDc3le77pLz(Ddy-G z7lG{Z_=9c2$>nwaQ%6np$rfn6Aqov3A6gNSI7FR^j3i$wn@1~&EJ0G6?Jr<}ZHF*y zAVo2d2#ZyMG>LBLgxL>Y3qhSUPVin}$(>1%MFQ}wX+ad+{A!o7!o!08N6`KSMxO@o zH^p`E90e~2$R5zrkO3eH5j_Fg4STnd+R4AkdaXFGC4#N&YrEgSVx2urfB1*bMgbX+ zk{0kx8;iTiL(p4IJez&R$@0VPuT@e}7F>F<@owCZQYQe(kZ*JXYgGlN=ZxuxiT^PN zyf?#BC#jY$AVPP@e-kXi@I#_fmRDJLR~r~nDD96{*I5v>q@>5Fql#i|m1qm=?5926 z@ORlH$1+byIq}ecUXc}=8^s{8yT9#-(M+hU@}KsT2~jBCm={?X(z)lbJRHXm?_7Hz z$i;=^eLY(W03xtf>I+5@U7nOrfKnpBIFK#r2Qor|BuXvjjC#kljpU>zWQYtE$cG>q zdi?RQ2JQ_wA5e|j%)jufWO9}>{v>Lkx@F&1U}Tc>^#*cMu3)pQIgMF^8S!w9HiwgT!B=4W7NhMRGg5}Q3I&m zVUJzx?6~wjcj%z6JPHAG7Vs|AI~e;GfRb$}-#H~CGVJ(+Wq-c# z00JjKvZsc61f3FcZqu_-QBmGM?QeSSIYZ%B0O^N5v_WqzB?8B4q%sbgC|4;I;%`yMqYLP$F>8UFL9F z(n0+XU`H<>s{tVHbehso`TNtMXXJ%^#C!DKT{JxX)ZrEqUpQe=csZ}hoE^DitMt-N z?rq&Dan^I>VPIfbs@T$lC9H#V8q{EXVifek>rg}h9fZcl%0e+l5Ct$h#0LP1k_f`l zf$ivSkOK^WeS6`;1%&(x*iXr#S2YEodmqK~m=v@TOIWN^RL&^q{>8gYU4prP)A!o1 z8?W=ztaKMZnnW&}A@APZhP($<8k>U8>iV^7&k#WodKXi8!O+OO4#_)=Sv?<`s_^x@ z4h}a#M5tD6W2jndI-^##_Xi&ss_>s5w7_BBK#|2lRtM<`40~+pf^z!}=?Op|Um741 zd-;f2ybB_cMnkV#8PG7jT=ZSIcz>}qHFUrbZ4nS92Id2u1qt|TL+E#oXlP&Lfe<*= zmY@K5Ou%90ybr+@ru9;i*R`rRA>*XD4Z)80x5^M;$Y>69pW6D%DlRfLgp>QroUpFg zPy;4`G+&@go}Y6F+Ec!9!vz>n|AS4T`;Hx~X5BkFnbU-PwNqI+mC z;3>S&>H+j=_w^iKu3?=o&8sXR#kn54Pl0(s%0d|cen(I)$o3sYPqabnZ+$~Viy^TH zi<<37DRu2)3kT*1%3M7lkcE*n1R$6+g|C8Myb3AV9>Aqmk)t0L$7GHEY126(&J_r&!hy>_T03iS)w!A!Z5e3z43iLb^$i|3&z~BEY@M?VFR0}}2 zkSY3Jkch)0`jgFPJuHlXZ&(!Aru59r_^<&_BuKXAA&{L=4F#C7)}k=qZOh87#G)hl z45?pTrM!j)IXExayYkpXO+nKW(ZITCHApTdCI-+`dZ6e@e}x+#h_*Iph^fc*;1`Kq z7TsDNQ7|>7hw<{+?VmnPg%qj4vYVsQMjeye3tFo06cN}H9D-h6^e1bE|UuF$&&1Un)9+1;k{b6-QB*#Gu zVhUP42wj3WZ~vsthXPy6xnb9NRs@znC$0gwDx&W}^N4QqlUA|S6=?e;>Q{LpTmc*u z)JVgF&eh*fKuBoX^$Ay0uGXg%yX=k*;FyRIi@3mkCP^Zt*XX-H)`$NU!>VO&+|W@y zZ*@z8FI7Pz_60^m&4^tpnIHgyhsas>Q_W*wl`06T(t@@Dk`NKv$Ex-DD!_1PIuJXL zAg}=hQxJEWD;I#PwG|@rT83&CDXgwA5Q{{h(3Jc(S9=9Ppn=A={)UFv!43l>BjcvY zfcZNI zVe2zLUqH^}h6^K44JeE=7_aOQQIvxhq0Xjlt0X&FO&j^mO;2$=TV4JA@+N03pjkmxG$voS7 z4CsAxz*<^HCJDCIAlMzg{Apw^?J1p2jd2FddV0bnl9$cWL zj9qqE0a2AjGyf&9zn_rgtjZU85$Djb=k8*y2lt;4D0I;Ewif~X12u3QYEV5qFd$pJRSS(2TaUJ3O7~A!0$NV-yUm+9^Oe^mI!f0CcX~o3MNF4j zgk(L~4H;M5&4`BHn53-iSul)Mj-Q%h1~z>iVE@E~awhfj6!#g}(V(Rwofx|Os*gnp z%!Na>#@M=~8n;RWwfU_waEq{G1N>^rqmnSOO~hCN4lvW^$Xie>f#|qHsIur+3XjAv zs;dCH{h?XRA@#zZ!SIUiQGX;6kR#mFH^f%}(go6dg2K-u;<|3*U`{6ikXCx@tk2Ed zSv?H=SE?x~FE4;PC>ik})8X1<9K$uvCCABk?%!&TnlnFA0Ir^osE$TC#|b?R~r1EdgGR&~k9y9Q&XE>R#ekT;>a$}8u|BpxZi zVEmAllB#ZNBlN3N%AR1>QN22Lutb@M^Pt|r-(UHZ%>zUo3b6x!Cvi1ZE?$#q0kHko z<>hXPFQTL#3vJXNHS$RDZGK3*l6#v8pJk0@V5vn^MlJJo%RC*R>mQ0up zB_I0tgM)*_=;U_FAx~scL#K#v#d|Vd{7WrTZB%QFU3yW~vkMQ8c^D0ua!IBE3)c4v z^q_K(;IUn~G!ia1L1o!|ekO*9P%Z0-ZxDr0!n2nZf5e*qgg&<6<@6v! z3HLX&2){Yn=tPX{@C+k4^!WmR`AhdH2i5bJT!tAF5j7;jJW2$#`5$KBR`)v}IjKVs zB7WljQ~Xm`Cw^o7Gdlqo;=|dtIaK5YLV@GSAzvrjxrZ8!w)16;(hoMOSg&?V z?Z1(p6rW;jA-{oyloHi(FYo-NOK$<9g9c&-IUquJ3jk&!>}KFVW3#i;08&BUmqt5+ z(h3NQ4w@7|7hKn8YCyr1*}d5)`yma#{xt4Y%_GoA#7IU-g+}TO5O-(L9Q*T4@S#3_ zfbKU4WxvZkA@d@I5R$(U6os?EqCmhe00_A&2#LfHY-P|-djU$|1Y92Wr~rUq%{a9T zt{Ayk+jBTq7oD?>{4k46^nvna7SthN=7b#3+(T3az`cmm7qJRB?E}){26YK(wE~!N z2AF^(FT_=9u&yN+Cm4ogXt>`fm@lXkl+gHWL>T64Gqti-7jnJ}MHbD+i#YoG#|yLn zw=Ny_`HL6tK*ItuL~hRX{JadLP)z_VPQxx{@%vy^2#t@o@``)^{-ijdEMRB%M62Ef z+waND|JXzmm{q@X=o{m?zvEcCNvm|;LQIJgepD=klqgevdg2wZ`@GJAHhM4!K2lOr z=t+>u5F=pzK%9X6Yaod*cwn937^rY5U=c-qtE=nZvYi#RA1?0#+Z|Ysp)n^D!B+S6 zYm(x$iWZ1T;qx0mjW43C7=1KA$)Uaf4)1pdT$=p9UYf4o6A}jg7xbO4st;V;+zLRE z0+Wwso*@pjjc5S;z*>`;djViDg_@4(Lqc9dU?TWT?x)XvY-nyahFDl%=)VXm_wJu; zN3WW;QEQ<)ReHV8LSwMA-v61iTa-+``rlfvN&CNby4B7ToKuH38yFi9S(O#+Hw-s# zuICR#wV2NJe8LxpAO&&N7}`^y8VptHLSG%a1f`pou3U**J^)X=t)pX0!5|po2lvt{ zKZggmUrzp|v&xY&5gUzq=18d#_ugqTgH@(3X_K}tag+95N)c_{gLjK*9J{tNFG&HW zeYP5k2By&$0oYzGTjLfWa=b6pS=|=Y+^XeIpMcTOevuoH5`-<8MZ%A$E-Tn)N zg2#EmcH89H|5Ja>n^QCsb{|4ZfkPv8hatfoAuFf6p_IR6h#!USR4O1y5UyfCZ$l(c zu&9owce2=yc`of);eVu(loIkp5jq~7=iq<;^=miaNu=F}Y+!ICflHE`L45GTHX`!)wS@o!r81%n9r9{O+ny)IKxW>V79h?)C3IP#$w7dWpP4h}N4 zm0agD!)J)ie0EOhg5eG7PAg2lQqeu`sTu$N5wcTR4B~)J4rm!B(5s$gUTTBm2H-CT z&x@iGUARn!)x%)is5AopGGb&)hcLB`@ezf8Y+6SXc<=Zht4ZUJAU8)gRMDf*8Io6y zkEuWgG+4S7g4#~5f59`5S9f%ATjZ10QgU2RNLh^U*zI-m9eEg(l5A9;z1npnGQ;Q4 zyKZrm8sE@@N@XzSX+=qQ-aET9no|)%_U^Y3NX)rc71RTX&Whi6|0lO*{DNO|6!d?) z)T@YUjr+%Hfec|YO9eH?^6jbPxk+^+)u`W{7G)zXI)1EkW%5EEZxv`S3CW!NDw8rjmcDWQ6Fpf2VPY+3!bAQ5Z^Qp zz_iDRkn!$c9TSE3`Bl>YvZL5*zbP{+mZGmX7%&aY*eLHw(QGoXvgl#Sztz1>OnrqF@n!`LDY$> z=bwnXg{L0&G7VC4+-($p+VN7q7l3uW-tx7iH*915)^WvGLdYdezbM=liy2QMro2mO z0=&2zi|ubS8S?b3CGRQqqctc*K1x+nh_We4y)!5M-+rBlRrzgT&!6n=WhYFhSScJP z7GhI{-d2S<>{gp7m~4 zK5Cj0VZJOIuI`AEy?oS+R!W6STq;O_kSKotZ%9}?D9JR|c|n6^(`O9ktiTSSjN&+|sp?4>lc7S|f9Bbr4BL94$Q^GV0g?)#fE^ zfg~Ah1fJh*MB-UxsO{f%GlDS{x9q1wLm^|Hxm~gdU|v*1;C-v*d@oKheHph zB3C%*0tV-ApwmM4uK?(D6M7dCYI}+d8F=f#=9vb4OP3yMUQ2TNP{!UQ&`DD~E>FI$ zvmEy?=e**!`4+lnN2_aL<6Hu2GZj>manRC?f$4pI^z%8Ou~0aWv-}rq42CPCHQCTD zh29jb{Vh17!*6$eE8E%Q@A?=R$v5la^o$;9nzB{$b{9_dMi*6X|FPyTH95Uv!(-A& zOyxX^^_q}c9#q>XP9t0(obG_0cF{lSMq;ye2S6A1GocVSeRh^uQ&CB}kt2pogYg<}cD)$frl$do-_9bw- zr9pQMj#2u8P$t^u2|lqFfY%E-V1ZdMDn$_1)^#)uFl*2;kzR3ZTpa!v-Ga^xmgr5A ziayy2)T6!}eMU9LNmXEOr_=YPR^jJC#-fz%dx_nK(#%g+DKDd8&*o~de5f?A7DL1P+lB}ur9H4bgb*{=4rEo9CPKJlBov**4@I>=pHy_5y_s&x6Re#VOhR-&(wuum=rSwTZqGCUST_Iw~ z3KW?y>m4$P)dy@wIvf0O4rB`25iei83X>WlxmPIo6IGJXY&|j$yiu_LkONwr;h*0P{#S&; z0Z|oM4K+eDU@=q&90I|BwEBC!z!ml5$B)sX0V`S-mga*!u>C%xB`yo8Q; zW=NwPl+vsRRV1iq=7+(-4y`ran2M~T2YD@4p(Pd7#dpQD8-4Ph!s7xp`RTKbT*L3Z z?;EGC2wl;|^a!O=QfyTF1+)wgMRpzeH>Fa@_axKxx`hrx5)$EIJiGFOC08*utMT4g zW+p#1TC1cE>mN3K2I@6a>&QHlFfD0ro`us1uoxyDuQff)>Yjlvho()VY-+eYO?_*u zk@}#fr20`MFh?#Vk3O$)$~)$3fMUvVZMhF^R@DoGC~x$^cVkj!k|TG-eShS)mj2}y z#sVj*!(XHc#JwB);fpCWOy^!@W&Yl)Knu4mq&!ULQ=`}`Q|BW_S`b8xXJ8TyJMqkc z%c*Yr2I3RP!vXeFwe$Qg-Vr*Z+lg1r?iLvOr2G8>W_9Y|QHAlB_L-fvT(Tq9cQU)6 z%-!!g^Z5n-MP$f~ZCKW51EayP$!}I=bH@e!0u=Oam8MHhg`xA8r(QDugOYUM`Ymw% z3r~L*>T%FtTo4Zbmd9-#_(=wtd-8KwKZ{J=NKTIS&Q~+1#ZYRCYRg9)+ZNV`2g|W~ z;p8Q=YqO_&dD3zJS#?_oKOT8DiRu$leRYNB0&EIRN6vH<o zZTaYzyXVIz?psLk&L0X)_LUti83!!cjqSaXte3i==b^h(j`9cQi~Vlsr&#U#?j>5K zLRc{^Q|XyU-?@o=$4qc@qP)g5$-d%hEGs=htSsHsU0zl=laIEm^!c_VPo z&NVzK6A`_LGIC+eOp9q4w35R6*RA-wxURubPbP{h>i@l4z}%`hd>oZjBj)*#kFI*^=>j94vb@btC6F~9w3@27>>D>iw-HoS3HBtt26 zjwW395eC(aWp5^rG-xKDnKMqbAG#{8oR6Un#NiM=YOK?ywdD(bc5LTVj_-sL?u3Qk zx@2y+`n0+imAtX_o~ESAQMg}&$(Te8&f{I}>J1Q;yPel>@TX&lfC=MjNFE2|*T`1c z8`f>1zo)YNH&QOwSW;MQ0K2M^o;QK{L>VSsN|- zKL$_Wi9^;X;J>3NGO@Ed7=aS~nIy_4Z`xBIJKkHtK&cpe6dZ78-ABt6_1Lx~LFkT9 z*9re&<}B5UqvWHG`9K1-Q&=u@n>L|Sj$d)sMK5ZZ@%qL3#u5(Xsf73&({(-IqE&)9$)-D+4w9p!#!_RF@6g(*>9l3 zb@!W{m2KfMG9XY;XP_#tWJ7hTEzt4MW@R&DKzhb`cvOOZo%gtLr>;2R*q9AOcb#1s z-R^fVMZaY&|8*3X=U*{D8(o_~U-%PPe!|9z*L!NTu;erW{8Ni+L39$n?^ zE9TO6dq+csN|?;d@YP5N8>zPZKRtgcOjM3n7G4lBs!zefhD57#e>Zpw+BVHm)q8S2 zeG$PrY9tsk_}*=jMyCQye0L=z#;2wvKo0ANmqnQL?!#d`^f=8^* zkG=8-V6aC&KjMI+h#u6jkqz}vT6LgwXqMX1L9GRp{~Yua+uuKk{_l!oo$?~&i-`z` zi-{=Fa~x5lX;tIfYl?=mJx39K3r-=(L4ycv0m#9(&JtTA=qo()@i_%=5U{PBZ;KO( zKx}Y;4leUr{(!%}0aGg&y1jos<^g-Pp7R(Ea{d!JI0HwX5#Jvevve=TYvNpV_Z;k2 zbw#7*e4M#+P0pd{Sxf)^#l)HFvrt;X_>hnq5G~j?l6QoM zW8{gs@sk=CpT5)eHVRnKi^1`tde~AKnmu?)a=PqUidF)#oMs_)M(lqmb;PFnpwltP z$6f`)1#l6araQN9_Z4Oth|si&?jq+)HaSSh$jnCSQ+AtOmX$!oGzNFAOE|l388IPY z(24E`zYzGGxw|Du*0w=DX7RI@y2fEcz9q26)blMj_hy!yzeRXJze*>FQ(BA`v5-#?}w|^{J!OF5Pm!(u{5P-*;2qZ}_g1MdA_j zI$X~~>AFdeXR?wKra=|*QE4D#{6@fLsJ*K8E&iK2I5;>D^EBQB1+^6li;Bj#w=;Vw zCj568y*Vi`PzNUqNJ+yVCqS!jXQ`>Xn?zl`SGWm|q&KyA&2{9|U3xxuXHTC$Vfa+{ zoUWsvqL>-g%;mbSNw=LUlHJ*XFM_S4K7v2uvURhfa@*bE(F{u$! z+YPPCd*CcaMT&Weg05@=4;xMoMu4L*%-BOIyqVPKySVqu=R;;JJ|H$U#D6a;=%pHU zxGy2Cjydpb9PuSaBj^91Eu&H4$^&8rqHUm{H}bx^y7~gEVq>I-l3%S4GYG2_ zy%byZ(S^KfM`c+lg_u#N;^6N*a=;UD1A>RE^W!~y6e){_L6wdoQ+lj4E1qpmmS4u! zedPIMX415f_QBCQ`B?s2aKIXQE5ao5l#w$?YO(y{g==GT->7~xq8K7>KZ);j+gMiM z<9_^vWy>ieAVG3$^BS^jN<<_X(@d`1`tp^~hdethYV5E)1#3EWGl;K)cRsBtd9BTFa4wVi+$ zuCcAFb92*TDq7=$GS4Pv_DoeU1mdg#O$ddYEWLgEHa}b)948N?omfMggT9$qs7E{i96Zi_r{*pCqT!JLTzn;D$ZxL+n=`>p7 zf92pU1Ae;i-`|l(+wA*&U*oa9Wp_K#De?I8&G32f4Sqv(5s>;WaT=Zk3(E)OOk*^U zUqdKEghPOm-pxy=$5^k?UQ(-2n`!Ajx}`A9kXluEA5tH@Xa|lvUWL{Wc$7db`vFHK zw&BD$ECwTcv+2x6{;K;L3x8!=d%5Bf(Nj^oSJ|ctsXph+A3VfLf&9RsLoRqr!4w=q zW@`AG{N?S!*^S-jtQ6rv%tdqt-R>R4C3<_Lta? z@he=G>B(GkM75HRZ;lfD0xQoc#IxK2re*X|F`pD;rspdDvPvAsFyjp!>7NeN=UU@! zjJX%KQ`=**j&?H>MOtk(ye6ZXxiTR#QX^I?nP!#XnS4-9=G$C%;hSH6Mxrac?Ob!H zqRU@JRn>8PRDR+v5-XEufI;3Js_F5}`uZcxqR{%PgA$~zRe0Z}^Wk;pSK{MXecKNc z`P7dWg8tQ9X|#a7sd@J`l8`Jion8IyG3XRtxI2QgbbvFgb3Di)+@(k(xjX7Ml(x$$Lf7_okZ z-uZr<{LY7UGOvceIE5IZ0^RSCGYPothph5NebIzG+$t<2cOfy797*AcvE_P_F zD5`x&dSZh;=MtPas1T1KTqJ*6Q1|V1pYoo|jlA`_qlN|!d^#T@jFaH60(K})QOgT~ zV)40*EUU}o6B37{V<`9S7}p%6G9(*5D0$cM)Ah#SK1s>n>YBophlKp4hnX=$BLaBd z_XdJ&uXBF-oOLuTCk*R4r*mqH6>H=)f8oe!jZ;0kwxQq0L>)3Iq>8$~vka+dAfqw? z4`bB57BF@|^4;>ed7441T<(4rv(-DOEOoE%#EL{{lB!}D5OGXx*n83C^W;URFAtyY zzqGP(dV4aUsr7o_Cr=K?=OO|z@pWGUd>TtMFcI_-W}81Yj^)(+jDR+vms$VyGWD}; zf8ng?7W$=S!*#tDor^MRMTIQPB*^C(FTgy6O!3z}ajYT@o3EERvbhVM?~tF?bQEuz z1Mp^Zoim_LXq-|p8^edkAZYp@3!PYsCS)5vUw&D14kyh{L2qoza%}0b1=dQ<9JwXV zmrHrbhul_>xXBTe+c& zB^@%(Rllp6;0KkD=!iEGzkze!@#WNA^CrTF^Yc2^-Gr;D+WQ8Uyhc+;O{G8g$L=@! zq+$o;2vs)NA7-6uRcI3R>b%yPJeOLFDdwV#I?_9eIeh$Xx5sbs=hO9S$Ian(aCF6V z`CEz(*tFlm!8{zz@`AUbmqGbJNEd470j=c8&=Ycm;!$ONi4_mnJ z&r{@15h(KA^SQXNc;8(~5Wkq(QT#}_P=~vllpLZOox?T@s!iM|9kz4K=lJ}>R(Xuj zQ5n-;Wb}b8v1eoV>NOvE8++-^^9EA8S|tK8{kAvXIv&QdOdR1&v@G0S1ie53uIH(q z1s&@hw=x^;`O7Hx*=+f|Klx^#wQXR_F*BgyB=b|cT=r|F3-cJP zTnbE{Q9oAa!vn7g7tsh@2^=?DkFV!ZqI$=fl2HtqPDAO@L?@dgQm86MCfomxkldYV7{#kjYjooF~N?*u3wc7*H1ZI~{Q7RtkNT47q9Y9KI zVEw-4&UWr*l&o+&9iF$qyrDouRGirrOoZo8tzcdx@So-*Cphzpyc`LX0&s*y3OZWE zI|63+X)tcwcmxMN7~`M4_l=dob~-q%IqNdK)XU-zCM@~uX1NAgR!o?qCxO%L|5q_U zSy}n5ukUzauO7TUa6Nzb2{@%OCvD;Va?9EFO0C@ssNsjfp17NbvC~h?{GuLSp~c!> zDfY_MI(~Y#EDVxV?v3vm!Mu+R{v}Fpc>hf<91?^V02smBOiG34i@^#Br%g`$-t{D4 zU`S(roguH+bQ=xYy*<6~pZUmuCbiYX(>7Stv&8%NAwwlU#qh92SK? zl-16Q5Ls>T-?0*6AMQIJ+VI=^ep627peJUs zSwD84fCd34SU!TY1pLwdaQRMvyMXc8;h@FZkSPd0z$zOL1i?xJZ$<$?`U(zYg*;|F z12!pmf2V)Eh}-zW!a}=NV{FUo#keT`IDxw(Wu%tpb|*DcsN0>_hz@p#2s{J0l^HU5 zlXkn*342^r%l4)6GWMlx|3}NqRnx$HW}rA{A39qth(1zi(QODme1CFInvo~};TvL8 zD14tmk8QAcGxn(`VGHh5d82Oc-RBL>UR6V_&4s6IZ1Y!i^mYFab8i_HSJQQi;;z9x zKyY`5phbMv(_LMA z@2XWx=9-hnqmp^vFHZ)1+5h@NlUt@iKXU$TSwKYy3P7NPMrQy5fuQs0?N|XPv{1iI z97GH(mA>*MR$k)o_dmjI|4Gu_2a%}fcH$41=Eq%$=1LO*{xtdqD4r#u3R2;)zP1K! zE(H**P~VjQXqc(_mc zJ=o7?ax?x1^RhBpH1i6i&p=;#J8)D1l@tTE*clEKlRgU%0+=NoJUtTte*>^DQ0S7E zlS6tHM-ByWH+bbk5ySx7Lj+iWJ_2r3;0?ALRdRY9t#C_7Fu~G~hkEPXf4dCpOd_4* z`phN3k7O`6a_eDzz4W(433`rp4`&;fLHlXIav%|LV+GYYnOCo%D5KjKM9A2b-8QYC z9-*8hAbQ*{2Q+(w&>lKKqXYsnxD^lqK-;50LpK0ND}tVhYtV-Tcx2eeoxePraCu&m ziE*3Q(ZI8^;oUR&%B3uJ(hBlTR^+;E-Mb>$@Sp2>f8o=qTlAA${C_L6tt0#(2i^S| z6t7M}mHn%lrHY=KHHIYSO1Iri4NlHs;|@KxODxTR73939DY@ANo3J_snkoo3g8Ex| zKb^Kr18D%PRX2Gi2PO$=!=uofBJ*GoCSaQAaLvE%fFpJXdhIfRY`2KfsaN;D`kBf* z0*~rfWu*gO#CG71c5-xm&a@Set^dd)56L`vQb`T~MMi`8OovJ;Rr1blrU6C^o8{<7 z{AJ;*+R6T3S(nFu$mdYPr@B@#aoXUm+yV^IWA*r;1{fC@ zd>Tt(Xwu$Swa@|a$YkWk7gCb&sWU ztdc-H@8|WBW5Z8gB{Kz>y ztfBJxX-ry+(68w7@}n%-b?~)tCz-fUhKm zsK0VFcL(ViU+Y8lGj0|1y3(g1Wmq#@J`@@=r6x<*fd|kg$V%IC6EBYY@e4nq@CA_AcGI*X_PI*3QOl!-ayI?n#I)qW^UpT47n?D;kd!bBkM!1w#MlbC|WI_VdFl*4x* zPe_F}?rq9V(qdo`A^=@$MJHgj8TF^kto>Dh{}R`co@ThtVo)u0Dzd8I_R_uJ=@; zEr4#MYhgZy>@JL#$E!F8naDz8$!_>R9-m%vr3RsS;q-t zysZzys8cPrqV|{17uv{!b_lFAx`budARFDSAtr>j66!~o&Ssbk_o~@(PwBI7@txn) zbYkrgs;iF|hOm(`+DIy@wX@yVAsd6f7fZ!0n&@-hAL_!DyCTILjP$ePS)jhww{YmE z4jx9GgT{i-50_&qK45f-O!m$XMFNk2bqQCaB6h)tV^F8?;}bsVCoh=ZjIbz1-3UTk zgwbLD^kT|tM$A&NB@5b^_v8^0r1)unz5WJ#Q>O&n3@ga~PIp;-HS2v-K#RutEwMg! zY4}&Xe2u5N&R1)|T0(Su?qH@_@ET@GtFqjnMZ*slXKtasd@7SJU;D|^`>GAzl|($& zz^_-P1g-K`WgH{U|MrtM{7*Sv^$e6RsR*d`fmgH}bbe*TW&j_Bc~;K0l?+n7i+^Zk`abTps;V3_bh_;YvvBH~s{KPXU}b7_|5 zYyaocM4*$#-CFN&p@^x}uxI0FpDF%5yt0P*=h(qTfkf@e(5^>TCV`e%c0gE^iDKHAvaBR z49yNsNk`r_UUq-eD4WJpBou7LQ@U5>|L;|S`k50!$5I)FWfsrH4l@sOW+!oK!=Rqy!*GMVh}gz{|6}W6F-zC0j_WZ(!1h@Nbdd3 zxvd!9n)+OgMD0H}C9w0`Ygn;~7A#N~<);uFn!9J)5+p@1UuG!#uU@oEa2$hoK z?k-`!m3lfW2f;eQS4r~fP$VOdokh^M6CWHvci+fZ>9h$$@{QSSa+QWgO$k2%SA8DJ z4KF6-TssZ^=s1=5N9jzGdp;7;+dqE!vxrZFsQ_AfrkweC8P1E|UYNV(6EUAVZN&ou zD|bZmcY@ydakgx?a8K`4gnn%oDAk^t#Dhk!t7H4t1(&VPv|+pVm%@;1_W!QpS?Jrw zji;wgWj5zvL~qae2_IeeI@2(RM@Z{$8IaZJq0hT}gIm9o&t^mP&R!B7)cM-~NZ{RPKIJPGTPW~Hs&Ztg~ z+&qwjsb8^Yn|lqc2lpOg$iYn{_LQ3NmXTPcPu>6Wz#zRwb#@2MTNSmusF$lUPDt*4 zuIYmTUIs%!z5^7xnNX|$7335WR91kM+Pj^@CD{8j#BKF*<h z6Z&6+d-in_>%`>Zp5m%wf+CEdJzGV&e1(PBemy-+eg5@7-HQpI^S~$Nz{8-h_y4Rrg(6yN9{Fh4 zoU8CO?lb6L!&2oCsv3tGVS?O-J4o9GI-Yu#UcZ4ZT;n4+0B4UK=%faXkbuAjN+C6Ki|>e_!GPW&(A@qeO+eDJGX3G)_f^spMycoD|A(0N zm&^sz8soI=G(_al5Js?kYT^myLy#feHTjiE)dMs~Li?dXhqM`h#6d*_K=+9lW$e4_-TK)3TaMedAkZ2LfJH`m)CD2ta$wvf@^5rqt*V~17dqe4k3>G-IR6*{3Qa5ABT*%WLmG{N}iIx6W zyd($WrB-snGH4|S@V9{~enTSQ4XLo!7(2LEo$v*(gV^=-f|T_?rDK{&mA{~Lys`Bx z?`yp$;%Rja!E{Pph5d!}p50y6Gl{VOR!9He$jb_c51IdaX&5|CC}0*!Ct_eKr=nMD zLju}*0bS`VAQRcXo*Pe#S+>tLyvb54-w)Bw)uXG@{~y@(gfwahLb^IX{GZ_-hsZ}+ z%l&Zxm|W)4d7_Dva0N7R@=NWRi`RAou?q>;V%yOV(e7WC444`oGymIw^Z)e!fF>NY zYO3(J7OVer=(n(^n#T&Va;OcC7zH+Z2pQ4q|H^sD|I-$T|5@4`ot)1KA1ZwT2v*HN zs3dweDxH^?2ko7L0mKPQI$u=(#~=^z+m*N9;xm;u@|O<;!Q^H%mia+@73yi8%o#>_ zTmxVy!s&~rG6y9209uJlK`{gcL*l6bFeFa(wbX+M05^c@)~~iqPzeXY+7Cd34FIh_ zUqXkCDVlxk%DimN7Y`S@x%cQiOyAk6g6{IXfd45do3W`i+E>jJEhgF++4FkLet2Lg zs5Vf`GaV_s{N+K=|D?8Qc7DZmbT_fr)>2mVgi`7kf__`c`1gVth4VBDXU=kHShh&@@vDjroTz$;^{) zfUM6&Y2_ZuPy2lp)4-9v<`n7=6m5Z#nIp(j!^gy#11gsvdvf+2@7#k!g|gX_eQsNL zF)sthx#WHepEVtyUnwaTJY|>6q-h+Szb^Xu!_P4DcPG-q3)o5}=hH zgidv}*Llrm)I*ONL;z({2?WmA$-$>7)&;j1F7PG5zg@T+CZ*ig3s0Dy?4lD!%Rwe% zDafE_aij2mXpJJ=Z(RAe?XUbvnCeHmPMJ@8w{(SPB3GoG6ZxGm;Nw8Wypc+~eZHf` zX|4CPZboeaX$bye4s~f>m}uBpP|AT~0EoIB$LHHB?~hW@SsHGQi|4;|!DduU9>OPN zP?sPgOdyT47bCO4w4v1dVTd-s+oho<=(Z5g1Lu0A6m_UG+r`Kpd zPQa^@a_`w2U27(ai5@&HY(Dx1!737dKLnB1z@B3Q7P<0!X{M>yB8(u!9%`U z9`q^Ag44A~=7t|V*H`U1$TM_c`%|vB=o=Mom~{|3#%OCzwf|8;%b29co3Jnz^=gCj z_r*jNS#@E3LCNV=R>c!Di}9}SUmLcDKCQ#GT!03rhdTU-!4U>rdHQC@%0>YyFVti# z0LP@r1Wr^pS-hT3fEOJSdRY7AQ+kK0zU}7zw_DG8Z(XEcKjWM&Ls((rVJt3R9+*zq z2zp~EQE|d)C~ft7W|CuXo1YvWH-4Q(6%86ju85{w%6{L*fiTIIaSC-Im_X7dLH_5v z@%M9+C#HkxrX^zAa(jQ&GOxYJ>`P|`fQ#(lokm(O{87FQr@E*9#b_Opj9dS$pWM%} zCRbs?&sfs^sIP_WL_f#td-$>AmVE5}di2N9^RoI3v2Y%KP7KA>`)4>5FWa9EybijJ z{SBFNQhq&>xloQea>%{@-?~WtK&}+{;HLuZl z+q$-f&@5GctOK9*^Yw$Jh_o%-gvqbU^a2&z6o5-^7~)W!{v{IX9V7F zgp;~?Wdc#&&#^gIPD3W%xtMj2;I=j0xgl=lXmr=p% zW`(u2fk?j#WW6>wD{RGGNDy_ixO!bbAkBURWGOEwgLuN9(~^*0ARpqq(f}ccN)d=l zA~I%ea_p-)K}=-oJIK^J=aUSInYiBE-~K3E9&J>Kxs;K0+m>37HoalA8^%gEtzb-F z{N9t%3pp~ovPIjw!S(ZncjE|yJ(RTId8Og$N>b#o!I>`PLH#mA$Y<5_uX2Uy=91Yq zvBjhP)>*RIdtl9(=)kl13@S2fsf91gBGF7hI{9k5To43L5$9Y5nk|vVFXi~Nlur1~8B+U8zz2f^D(dlv<%_NP)rd|Ivo zdpbS*cXfuV<2SiP*6RZm-qZ`+ke$mV=E9lfm85Cvjp@&`Q~}XRxaoH^?AKc3^%#Fy z&N^ei+Vaobf8m;9UA4cuHofvia`8pe!WQs41IFj1+AR2wO^iaK3OJEy5Y>4`gBiT1 zHjj6AkG%)qw9dIC%lcCoKOW=j={H9UB<|%{-y1YeV*jw??;i5`ZF`)3%&k8-BnTyttqaInT*sv43+h1Po&4~MQu8*E zYj|eO=#F~0Jn?w4P5ofgt~IW#R%+Z{1(%7pdRC@SSkk2gulp)3?P&Z0JY=7U*vf*B zHMfGrZd7&UyX!kL83ylm(y_H&gJaA2;6)v(zUHDTyrqYPbtUMog!dU7s%Y{Px;>!O zH6u&9qSsQTVP3Eac>Tn(=S}>m^L<@x^coeCl$4u1G`h!c>~&M>Y&f~wyB8@Tie$YM zWc`T#7D;dG_!$6T?;n|Ip8EG5R;4QpR`bLZ6F++x_9qi)I}P0RfjN!m&GZfrsxELG zz$3zjG(0dSg}2husIY>x-ohAvkjR`IjyFx{VI8Gu-x$xHNai2_XTK;gKi*vBx%0eI zEZf&%HKPd@9lmt%RIN)TdfVk2f#!B3_&kfV-dgBhlL-zRtzUOD(@sD7_(+;{~~&u!CzkI)>VXE1aa@|LP==Z}MxgpU}U->pRb0b*_v zu<6W{X_yZmE$>9zuAI)01c=+>Md7HAVbaAN#-@XNPba=Ou;a$jbyiB0`>{svURSJ} zBCr#^gD^)&>o;9XSvVIik;3IL-_u2cZKz@drtI1LO6+zwhLr`tE%5Y9abg43>ncm)2ZvZqMblLijIL#Nx4`5tNS?uUH^|@8o4b zYE3>i`b&xz_0k0T@o>$8RSke`#QOGqne`X<*nj(aV?;XgLa!{z?=B5EKExCBK>)E% z&SN*g0e5f>;CcuOeVu{JD=kW+yL1+O6ZPg(l#G3e>@6-~Ts#m&gZo>Ta-7b? z?B0vv@HV08aV;e_W=^_LZP_^Js!qU&M+GK z^&88*zImc>{k5&1|KY-j^^$B>-n_L*Gh0h^MS3>;QVO=#{h}GCQ_+m}WxkH7G!aKG z!)RNrV?%^FPInoX7y1`0vJSWLSG}#fI@UU6nr(HEhrgcu!}U5YeF8*@wprL^;-lZQ zaDVOS>|T90ttJuZU%JlaLf?oK>veJm>=T@MDaU-jQjR;ynipQqTZIPiJ{MXloTMGK zNIHPM4tHlFN!g6SZVjIzOOm3RGq@wu*=r}&yyTzQGYBc^71&+Qs2{cXbiFtfg= zUTcj%;r#UVsPZ(vPT3}9R(d-SN&bP z5&u|=AE*1T*pBnImylD&&uwG5SW+qHz0EC10yqOzA1i0Z;eVLKU^r zrV@$2uc8nZ6T^x4h*H~K+yZ0^FM3ew}9(VeOLh>@W8UXH-q zUVVYx%RnUG=XsXfk83q%WK>4#iUDUYAW8mB$Q>qJ;y5oT8Y;?)%eh31zrf- z?Xg1OkIJYFr#lz;QZiuEjx|mcQZix(LZ#BkmIp@7aOQr^2&A!3jAVhJ>zrrirpOUh z#V>s!ruHAMgSZDG@#;V;YkNILofnyd^WNcs6UX*UD2}T|3vNjjk5jp^8^0G0%^Vrk z#U(2jrBG6E!;RGGd@OdW;gG_wW`M3BWYc-wMrK#|zOCs*FbUx{k>ru;k~K7@nrO-S zJkYBprq;)(jw?;yX<_|xeaBmQ>nCw`;Q+L)yhxqIp=>pvrI9((VuR#9^qP@XpvoMl=093jxUP%T+3e7ZS2bV8OC z(6{iQc>d%0Ih_wLQnyzHZ3f zuEMg&;AkA#;l z%Eg}^FZN!}nGHR9NMgpMSfnkf`+0qjX4y_YKE3#D23fAzRSlifS^Y__QvbO>r>Z8) z7xj-%!#0k-z0hFfKlHYWxrvj_*5R7%@fY~j4Qo2W@0Y&KUwm=FxL^-ljE==#|7c0H zbXtl!7EFD^PP;(x>gJ>7HFHUpp-+Y5dEjmz$Q7{rAMzAWZlPY?ihzReL7NOXvAZ7R z;??)rd-3mOuSb&-Ef$y!HsNOKI*B2lx@bp z!oQ>)XE(WNKya5%qO#Yk_BUs;dTr9@H^?9yPBLy>4?9aoy$eZcvo^h&aiI1+DldXq zM1)xWOO@778J8G5eD5T+cs~}>Ft$b0Q^pN)L zh4~1&*t(F|mJs&g(b_#%Z>nt!lQ5b2oul!z6m7GfXd-V#+1L-VB@2Z69CD6R^7IAw z?C{-gI|z4IqPz5cYol*39e!CqHK91H+%e> zYh0KSC6AU;ulx`Jx@)di4rJxN3%M(ED4GyKx?bg`p$YJJoAI!h-fqvLClvsgvM)X9 zr6&_(F#*=SU+b&g+h$`;P7*Om!X$L;g7nQYIfn+9k6xd-=(pDfZo&G;wu`k3iLjR6 zXyvht#A)k7(FF&Cu`D|U?b@1YOk2_7BuaGlkaOs;&OXB_tIZ?Y!_~h|Rx<;|3S6;n zlrEx?&X45aFduF4&&P#fKNuPiGE=)mj~|F#uAYst9iim$viTgB>F?K#awRlU&CMQz zd5XbJFLaE8Fw%ZH5IoEw@i;eh*iRK^yUDRUC@m!6eQ&9k2KhK$`S!)j@tgoPfgU9(e3;;5|f5_ec zCb9K`GDP+rS<>^M0TY#J93G8)Hcs=y=m0pFnCj;MSU=W zZn(R0=-G#?ZVjir7{i(7a^~Y8{K(g)m$kNU^`kwqLySjE&sUGIyWFW)eE3!2~{`Ew*Y%&2K&~smS}iKmD8!@3L+fE@=zG zdD^%lWDVWIv?yXZC%b)sIFd7*BMM~Z9!`8(Y50r^_rLUiUjGjEvt|&ei+n0Clgac64S~2t}`Vjc^C1s?)NAY8k7@K>ZoZ1`(|T zg(mVxOA}4e3Yq1|{PXt^X;;r%m{h0E!s~V|+V{8V*zcAMi8|HZgzc7`p=YzO9p@-W z=sF`aMxTb7(mAG>BdRj_T|{&V3hR7md8`Bp7|#abV^Au_*w>66nWFml-?W@@>vG3D z%jI!-nJe)^8T|n}+Q$z;vo?xmII|=-Z@JkuZj8&g2(1pEK@z&e+Uq4<&OV(G!S#zo zgQTaeXk$!Ji3>Nxz1pP9?&hokQNi;*V2{LP&|&&)s!AyH%kDJ{kve}LUIMp<(oMXq zjC^8vG=T3!8lCe@b3go`54mo{&H6eVLiPA#ATR5Bx%~Fc8;lrJ_ocY%&U7iHTA<=G0VsdIrKVK_*amGwwJw6bt@vOQ z%cV1jwKRzK*IGW@l6dNhg}KK};2(T=`(6y-@5_8Uh#_jpvk0It!7eQZq6#{Y{3QO{ zN?4qEFq}7^s>(7NJYJO2dOUKR$=r_0GyT32~yF3Yz*LJ z9v8<`$9&0*xYDjJ;%OI7hDkx#BhvWG2y{;v?YH7VUG9+TO>*5hklM^Im<8Yg7(hhd z);LKm+!>#c_1KYlWn$-bE1=g@BP39R;_l*!=yYczoQ9olWV~kym@n4KbKihNO@UlD zV-UlNtOI;ByHOu?3I78~Mec!Xmtp@a&ipAf-gTpLJtl3?xit{6qrG{cUzB>vYTX(>CLGfw?49p9%ot4|| zmH_hoPpi))2=o*FipBW;Hc!Hq2EOoMGj7Ptc=6#&bBhy|^<~z-fuZnguK`1VUVtQ6 z@BU>R?4#ZUwQ7}FP{N4#*Y(F}1GG$A>JDTnpFaKrf%$^qy}%Ews2|?JR{36gU(Z4zQ#$LFQi*@P0`aF~7kT|%vP)*z@oDvy#RE=Du&Ub(8>ONd80c4f>8bK0@tQ)Xk zcy4a`mdt!>kDre_hSVCLS*XQ=(?($+^&#I&51NF{01y8+fzC2x2o=@-AZ?bd;ruEO zMpjM2tMbwTh}e!XS6Wodqbd{0o}kx;&nJ1Kz674`bVcg6*_C^-bW1#vm-DBFKP~Gy z*p))lk_tb(^%p0dN(69=mqoXtvrEBuJE3~L2-!yCXxA}0hAooptV67 z4P4xnj-P+7e6N#<@v@@xPvl>bnwAhKUr3hMKo0QH3j!=)e6HbTk2eIJ*XGG4v< zulEarZ| zopP9Qy8X58(z|V0p!H>-Y&cwgK=&7lyNJs9npAA_xo*JG>VR~stczD z!Pd?-J#U6~ov-!$#!>q&wx4;E$un558gj317{^vZXPceVo(ffZk&3y5ALZDd@tqiA z8s{)}ZXeSsF&S^s(&TW4fl}fQgK}}Z|8ioi@-XvYnmdcABrKo0$WJZuLaWN~1FM>u z)e|I#lAbtYwu^|%ffsOh9k6oi^#KU6f)Tal;(3cH z;ZF@_@sZwEf99`D$y>*$Lkt-`f1D{h0VVhI?+pX78)bUwLi5oZ2YTt-JF?Ci91E?_ z>GQUa|LHOapY>bQvyg8C29j^m4%&bY3R&T0Voy7y<>I`=CwxrDhTU>joX3 z@FyoHNAt@MgaDe4PUR2SDUX3>j$Cs=eLa-Xo~qXRIZb0?50hzfs%86xqO^xTC*#`L zte)D({p|M1wU;%Mabam2Qtb^X^f+pnVM8#YraKpJ{Nr@p}!4l}o z-X5IQ`z0g>A2)Ml`)YXRxLyAu$D^5qWg|{D@r_752O!xfL*>HOIBY(}0wP{?YKIkmMA|e&`lG?qXD!ad&ZW#xj^#lo?%x&vf2`+&5kGgPVqCIDO);PDV| z2Vy;8%Xb?B_rv~x_E%X&B}o6_Bnc(}@OI~vlwkPZL8yR|ZP<~geEu`S==|l|$OsD$ z%WvEk-zsn0h`#AWahXx{CcECpdEUYDx?Y4yYe+YtXRvb&dJ(ALsl9$DN|ZCfY1P(r zyTX$%u)-kw@k)Y9E&I-cOz*y#^6_xgk~NJ7NrHWl_^$z#jEu{9q-FhyR|{0P1Q533 zE-@s$<^&YKK(P_yDl;ky4a)g#r0?j+1^O9CEA4@f(Q73oIUs8enB_x(v<8wKq}_K- zj1pUv@}0-L9rpdSV%7+9)`&o|LUgKg7S*oX=w#%%w6r7JR6HQ^&3Tp*DZh|tUBA`f z*Y^1N!K_v?RD&utW<=?i@nS9ML~TRG&3&$i^E-GyRc@qZD&t0Wk3dGkOq*bot>Qu zr*(PI%TGi=K=4Wa)?FFOF$_A1$L$|qQTZao%JG1iHda+tX$l0E8I@3xqD_tDd;9Rd z$7NXQqDNJ#Z93Z0)~AsWkN7+IT%~-xuToQjSF?nIG|FP?-Me=qbXjDlc7a{1fyk67 zZLOK+M?$#JLf|!o`r2{YFZEU z)}JR;V@v2#PGMsr?wUIsz*cnbcV+eO9-H+rO}Ho=Ef}IcSX&7v4pI8{&_~4af%g$w zhld#n?riFm*DBzSJD75(JpU#?HaACF*;Z3?9yFrxku`BZm7!E1pv+zwJv-=;ejw%QaeH=-t$ZOY* z=U+hz1kABLE8+*nHjZA>C3Ty0TK#tdG^yv#LjDXtR^_wb8vu2?8PE?Sub==6(_w%E zm2m^uCS;#?%F4JvMI#b)yoX+X`}Qrnuy89V%lYQa(#6H)IgqAG9Re8K#zL@B{k1p= zkV%CrFP8g`&bRIE?7T4_F0#B9Qq4QrJm1vQO}qS|rPgDPmk5AAH&^ys2-D@W6*P2~ zqJe>^oF`|RcAwe6+YQQx91Ax@%gMOpcQfk_%5pcFe| zkN~;Azke(27KLHjfv7GQ(6YIExNPgwbzckx91yF3Bc~ngO(K|p@$GJ)AHnJW-~+go zCnhIXHQH_noSdDN0eyA#?hBfn-RanmNH)HAX3dwAB+zMVH7?F*&Bl~|8-fXF{wKJQ zZrxexNsqrlj4Kc^Mo2cN%P6rFb^@_2EZlur&VeINkMi<8#?XN4zZi=0{W4^jfAoEZ zUbV2Hvq%fcrZ266goTNGQiRhpj}Rt5sEhnUBRL>8mm9O7eWmjvr&xZlYZ7$x#MjpH zL-n%3X>ql5*%}VG%EOUMEo^K;WKM>#ci##uh5$6<+8>6jZlEQdkdzb-^y|Vl>p#oq zUjg|T=(&+oT#Q~+R0IV#R=VwL4ZDI!g^M-;rQY31cw_NXP;kNU+9}@tRdX#x_=pQ6 zWGE7kpJ8cc941Ak{a*~i!soOQ?Gwf1uawxcFtE9OyM0SvC}uw3p{W%J(@@nbO)+sf zD?T&Z2tSBx@Ri)N-|Bw2!P+Z7>^@d!u(HiIg|y1Sy!6Turm-XBPOFF*Q!;17c_IF=ymWyRBW9i5-Rw`=#^oufgN67mgC$I+WOwPU zhLzqpN*}%XxDo65il$ol#TN0e6xOn{l~aC)Zx!A{Zm-`!uSzyIHi^$bHb*^Bq)*#n z^J+BUy;3|?xKc(BxJ2-%WK30w<}xV3VMo?E`6nPZLAAJWUFDy)3vm)DnhHe4<#*lI zZD_u^Jj2RLQT2>l9->H`=Gel1FLJo{QO7DFqsg;{RBNeY1oQ)9Yq=bCt`L4b%JBK{ zcRy`s94Df{PTo2WYt&~pdDdOL{`&nu!uJGPz0#LK8+W!sYkW~hZb4dsCM`~yhrOQn zlIh!MZ&Md1X5qv8;urD+W8RL@vPoh_h8TWgoFgs+(XHGkU`{0X%~twCNl*}E$!!mM z{gr+}z}hXebOnyCPhrz?@{1UyD80HC!F-Im*f*WF#-CwA4*Gq38_8<;8N8bP&OG3K zqa~W%JmI#^kyeE5_2U_SQQ!x9ghu@N_=Y%(aG5CY>^H9!bxVlL`k% zJLtqf(ttA%J^fu$2m5AZi8t8roVNa5mwUHeq0=bT24!cywE49ABJ~=<~YBg?t6Ez=l%A zcaLU7JQc_o1pRw)U-W?*!KjjdTMFa!RHavy5Q5gf*;c@u-jfS<9;%o@Y!XLrQD88(1lppD(wl9 zHj21iDY|!WE`1`5UpqGYs#x({;3JVEs}hrRx=Pqtw?Z41GQQ#Ad2Y{AbfTR=$)epa zm!`45ljz0wY18cXFu+xItApn&je~tmWKs&m2&Vr%fW{`bPNOZWK*ZpbLk z4RDSbDedLFa_E2V6C%JKlY-smgs;hd7tq|bkB(gKY+WN2gb`fJp=inO?SS2&_6(~q z`77y?z5A`h!p;`DZgzgZRe0C_tDZktYUz9JJD2fm-nq}-1B3PXn9wBUSMUQ?4jT@> zB^b5D^oj@a zw3evZKVmLg1{X0}Y8%908e#9|)lUmn?zCOsJJ=fNvDlq3BYpG1-Nwbllf*HYDh5BC z)%F!wFh|Hi7F#H;vBlL5pG^O*Tm+eHaTs^^>;^tZ`OR&4d^+!R1b#=Y+#$Kfr8AD* zQBhwg3J;pb&)0_WfcbdOy%e;DO6bEOM$H_U-PA{f_O3MB!DnGd=4~;s)$kJ5^hsz( zh}{k_3-9&ZWjhlka6*PwQI`#W%`H~AU4}_dG}Lg6`iCU2<|1Jen69?{$j7$6|De5p zl{bf!p%OOs#}Ne1(keQScDcN~PnN)CG2sn}rl-!m{i4{1OEgxqNm4v42n z!}ed5TM_y=pR^zfys`Qi6Ybxy{d z;^}byaOC~r(Z3r<--os(o4Uv<%NMsBR({89;)RUfIWiqHgTqvCbTl$7j;$85VV|?+a93^!(1xZptHU zVHT}2wh;8?V?CDFT$_A7#YBtb?dW+obFxm-+)x0^V54;Bd&mU+UHEL>*_l?wS^WI^ z^AC2xtN}>h1+BVGsc7(G&Hm~rLlPSFM9x8(s1=fS&T6=ak0UMmBo9`XOi0-T0v|Aa zzysvtXw@YYZ6cp-9{!}7=PW;~MtNPb*`RgH;HvF53--c1D zo%jVZpV@!$Z{x4-=Lyn*C^JT@#}pZ}R3+?@j}{Ldjpx1cbfCZm?+WDSRBL4SJXins zUTGd~$H!k7-PY`PVps5zdu6-riP8m?5DOMB-@v0v%almQjP$T3h95G6#v2!iqob=* z8AG93X?U)-N)vPGg0lx9^F&am5LkHRn|c)BK9PoEXqhf+QHRRS)~Wx-DfsGls+&;< zR!A5BPYc%nJZj|$MpKmqy-zVvPwCt*Ya|?7B;G(?uJhC8YqH-j4Xy2Uk!`TBV;rL# z47huk3}aMv5@4RAz}fZlt^Ux#OBMD$np#qwarut=HlyV#3%mH(XV!5+Lk z&|Uc%=F%zaMYB=6boC^51(h56GwDC5vDFtqayjfA;6b*_y!V3xxd$)Gu#zeZU?MjMcIp+g9ZQyGuD%ZL_ z$B|!H{i`=uVU}koFgz&?k;GP`PCy|x9W?+FC5M~X%G*nMTMKjQ@48X^CE z%u$&SYdX0>Q4xWE_rn<=LVsYoQhf9w7M7DBwTi zMlhm1c>v(0od2J_WKwC@{u&&8Fzt4Aef4w!Bb(Ci-eK>#iTrc&EJ>5rAbCm&gog#4 zO9%JNWoHw|-3TS24x5HV8`hHsbgja`03s0PUN&lw^QFm2XkT@BE-wC%vx%~nFH^Cr z$Vn{Y?9AgLOo1R7VW|y<1>CQpKYq|}o!=zahL(vxr8}TWhj66m8fj@R@^jiK8geXT zAYw$FpmSHmywpG%AVVYR<>gh920Ff`Pm#lrVnI5m<0)}4YEbEB!I+~fvFzHnLyl!3 z3AIBq_=x{~EHcXN4t$+V-{gT-I;ng<_te|$Vw~Nli-8W%VYEN`zPr&+@H-;ZP~$4& z9}PdPeei!zjtzKC7WO~e;s1PT66La=rTjSy3p(>Rw9wGdnKpm_k~A6GQ6NhY2AE}# zK@5w701JAjVg=cwXrRm+pnvOSsk$*BkQD^^85>ds+J2y>-~c-LqzcBVg@j1*^YaUf ziXsL3_T7xfa%4G4V*x8{*WL9gG^vtHIR3iI@7_x>U64!kqdCZE0NNTt@!`2_g>%4c zDTRXoSXWq^LZXt3PsJ8D$}ee3*wYbRTN!jI-=a;WY% zkg-r!S4RRCPUNr|k3EUSXPCq982xTn|FIMB-74$p#cgbuEdY@&E*rjBe9&wN6)=Yq ze)@oWa^ob%XCsWh0&>Bjm#(g^ zk@EQ}K0wyocvOn?j}3ns%1c%b4kB4DH5R7^orPvk=d1LeKbdg@G{N00Hv5Z`n4HWA z2px+{C>md2g-Z_(4B!p)_jd#3=qMn>MIf8dCg$P@)HMki-lp=dRBBFR9qPos*DHVG zJ^{SIowqNZp>7PO1V=?h5!c3)@t>ccgH#A^4L%iBd}pWB)U)&P#YIdQPGSt00Klo( zxp^u(@lH|_7U(K#O5juDpcnvYaEAsRMrLNPGUJIAIMk$)?isB zB`mP26ICXsUQ7UkRFd!97XkB} z7{dstdevWVq(Nn!V6tzN8S#NGS%hHHx%4KvxDTIdz>--7e3kcc$93WCKR|LEDmHv_dJ3LU5K!k_nbNlJ0qV&{dLqz`hw%JN|5H4< z(6cf7jIE}Bo13{+RnHa|7d?PXF*FnQH7TjD@gr|1A0MCL_TPL)7M5W7{3uuFEoL6~ zgN38rNIZrd@Ew3j=xS5q5w%8(qAStyWi;-93AZHkw+ph_yqX#U!e~0V(wyS41}{Ul zu^ym8LHr0(XU9Myf<{bCta;g}vVHd)WRqCde5SB7a^Ew4N=u6da;io^e)MUv1D4q- zEZqq}RtkDYIDwQ30EU7eFgXYik`Gd(51zF#yC0=f0OE^)GZG{)$xfFk!-{eLSE|t* z)G~;>fzp;TP<8K09Gj#U5g`K;%Si-=4hV1bY0*UFL;%uSW59?5)}yFkA(Lrw9xzBQZuNRiP!Ox_n~CLc<5~|fVoPS zs?&;#Q%c;=eqReGNn=zm% zYuWeoZ}9v9J@=k_&vTwWPwwYaE?<~Y6;;LDM!sY`bwpi!>u?4`;2zHfL)z( zBSt=7a2E$lhpLHr;98ekU=L_j=Hoxhm8=VZ15@0s*;SPMqVf?FL*# zTH}r~$fMt)R&G#>?BORhx^HSH|7#o*S0bGLxa3$U2VY5>*yua*{COWNt@~SATNylc z?zE>iT-nPryUzNuw!|*d)`SWY5jU3%CXl$+QK91bn6mVnb=jDdwcY{MiKl3aa-=kN= zPCc!s>#|fDO+feJ%mbz+4o*3=RA{;^#`WPcbS7A-H>2Kaz~^R64ye!Xyp;qNGjwzT zM}YuaweVUV5zS?g-k)>P;$so7V5U7GN$_ydAv_d9F(z!>^}E|CxYMcT=4Of#*3u0I zL$XBD2Y-9}iP?ihRm3#Q9QHW~4VkM?{hLMtkww2GLTQ^X%7OUYHmp{ZLY~e=cd@sG zMt?RwenNbw3U{_XfhFGXyDBg!NLd47I|ssZcKVkYeNLF$v)>!5ar~-d=Q#jn^F$kS z`n_NXrk%ErG+0e~r=Q+AcV~EXbXjXAow8v)j}FByT49&+*bWHMy4rl6ml5cTb*wXsU*zXnm32X!;v5$XyO#!ViAZ-;hUr zUy*rx+O#bqYczi@q&}>6kl#T|h>zq1RD@!QJs%z-Z$j5SxH=Utp|GJ*klV0{^m(uF zTbm7v$2FD77aAIT>Qm1{$qFg>tg_=Wijtz&ovvRWm^}L;Uo{q1^%%VwimLm%u>Zbn z5bT^dHR~2^IeVy(AB*VpE<4QNyxlynWMz5BC z+z=cVmNWB5C)xh+lmireEH~m3=3|j2ch^+GM9(U0A?6~^jI@3G7=h6jC!k2TLJ7_f z384{RJOYmg^(-$MylM~Nk(K_1-At~^efH0xf!U!ro^uaO&!sP?`*}{Q$0i`jBQHyA zW}nl=?}ZmIPjCf08PCKo!M8nkkbSA9roU?~7E@)8B85i`B!aI0sK^anyR>cHM+P_> jz2|-+#afI{k(WE;QsP%!-Ibl>O<`;irzW)}N=yC+JG{NQ literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/Updated_Correlation_Matrix.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/Updated_Correlation_Matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..a836d4663fbbb8f0cd63f8e9b33c774ff3203e01 GIT binary patch literal 131511 zcmb@ubzGEP+cv5<0xGFUmw@Aup9x4+-s`;QT?Ypz+d;#}u>uH!h534Sjpg>#?m{;gZLaHQY7R=jl!4FX;i zcQL@7ZujJ9@JGN&LfuITV(R2-;9zn~*1*Zm8scPaVffg^#KF-5V#~$G$Hv3**xbp< z&QXw^-R7SM*dPvO?C_Kn4baFvyEht+w{GDXpkB9g#d0ie-M)28`t?g?x1^mpS2yL( zix&9)X#&P=@%=^wn@-(*mt)0Z4>(ggZODeoPVSE-355ot7Khf4ILetJ$7CKGG5QO}BLj3N7JOBUPrp;y1thgKVR>IoaI$)QJmzOB!ZD+bfD3f(+ zYq2l#=6HX;`DZ)mn}VMc40Ofra7CJ4K1C)&GWi?6mvggMBSpBj|BU8Z!Qse zgJ_O*hM~GC89~wOI`54T3+^;6H{eYi**-x=FW;m2^h_k4m+=$6uK}d#oPK6z#tV$` zHf6P!Yy$VX?L-bgPuof2=XT6RFDFhszJRZbiZ}5AYwFD+eCW$}l;J^-iPaL31$@Z~UazP+Ev#BAF77ss0wHc+C1iMQtF&)S3V%;uZCo4Cn& zt$$ce72lFc;O<4#9*LPDZ>}xIvT^EN_tyf+ZCk8)j|RAg&tS}M!_ZIn2!Jiddf%kI z3VQh9LF@U^`nzk50DSRp;b9H;Xgc(!hsBU6i`|$gP|F*g_eEZ_=r+VbZR^7sQrteG zrpEKsI)Xx=4KeRa{pECHBxBYaF(;EE9FIxm=C?MOcnR}7UyTLJCX*^k8Pxtkx5R9& z&Ka9pG-)VVh|6k{W!#b{)%%nb4HI_-d{?GcwQXltrTGYLp(^uOwrsm)~v>ldHZa&emO$Oe7cmT+-%r%I7P(k3f`?;qMOVIbIVXR5pvm4r}8>@`JG*FXdZdv z+9I?ynJ$4P=)C2maiNqW2XDs{v%B1_9xF9?_4Vsl^%^^x>x+}+gT?moe3j7etXhYo z@7Up2N5e;vzE}QD-j{#fx$?}(%Hr@kv)ilNX4`8-=vt2FDj0k1H(j!APZk-qeY$5o zS4S8w+1?g_b$*SQKL?-A0|uEVnu9O?+2K9#7gtYBjE$f9IUEi0#WHz2IaU1i3{0|b z%jxD=4znL>R_3d~Mq~CnghHCpGj*DM8vl9*CP2}eHxW|by{wSHYm<*nDX0v06K>k& zO_a5mE=}V!?!lk00#hh+``cKKJZ2`d_2Eiy$c(k>j!QiR+7m?=1KQO4etNt)cK?Uh z>5N&E4W*#d`+T*M;>@h9^D409@(KkLeZUaCp{9cgS-1MYlp*}QBS^U<^E4~BOuCt@ z!SF&l4HX_qDA?BT@|yhm@iHX+SqOAjH9bB38?m0(2=RQ9fTPzr_|7GldiF~S4F8wz zn_015P?x<~_ZhSPsS-Ug^!K7y2ko@;+u)+53d{|o-(eqf$+H}}WW_?&0*8LqYHc{z zeVR|XB%C&icWG|Y4|A9TKYjYfbPaamUoF7@{Z%Cf?;yApJ4ZeRmM##NQgfw=UM3FT z4ygs^6XKz-sY#ZXmzSBH{WUte{l`oH=^A@Fs>qz_>HB-k%*>(VxK>n75fpISlX6(9p1GRfTPA znAf@NzKy1r4e`oO?p|J;bDcM7{fM3<>Mgi%)0D4L@O{heR;ATcQ+}uP+E8+Tq}a_H zCns(_?-N4cMcAEnL9kw>OXmC6Sh7@$G%1AL4)PE4l=Bs{m@Q3umtg(WDv4ZXa%KH9 z#IC-Y9v*^V!_jebe~Z=i2<{3eH{vFnDL2F8G97qk-%(6!!JR-`%^ae*Fq$b{VL1_^+vovbON4Nm4v@@;dCF*EZ7WfDIQylAlLwxAto&? z9oy&&(hpR&(IS+Erw?mzzik2YxwN?j0<6Xwzo6?LDp1A?xw3&+8rzuq^{b*a?CL?u zM>=h}oM?0`BJJ;!hGpL@$xH?lcs75fp@kB&HrzHc?*a_Y@W)% z<$bn#B?(fcCH6x5OG`^pF=*gk!)7hoB5qI+}h2w2n)`-x90mBMrjn zU!y#>vvDBG1K0LSTwJ_VoyBP%*4W|sFcjs`iCENI3N^~TBH7M%%7-`Ro5hAj5ELN8 zSyS1S2OfY_dCxEwwaA#=5tK?)ZVR`wKrR!aTcQTq`UY$CWClqZp1S4ysskf?(^>i` z@OlzCV~im8P%#}!BK;z%&=7f_M8ILiq`TKwxrJ}uOUanR6S1cPHcf$Yk){ermEMA_ z79+G*^Gc)MrHEZtA@crogM0aCh7?|>F(+fC<%A;2wB~=F0>_NV>K__X1va1aDJY29 zZ@=uegb33Mg-0kWc?$+c7~Pu*vREcCb*i}3q7+}~kqWmN85wUwLqp1+p;HsSPg#Q%Hs3aV9NqhGVYK#22 z`uKNl{=eQXZUbW?74hH(!xaZ60TKXhj$yE!H^%b_F#JCNpId4^l3pNM{3o?XeSC>& zWo6}8leZ@fBuR={V%`_rbW#zn{myHQfn%|h?Nj{<_$ z(`2mdd7OhA7a4bsP4z4Dy#=O(K9rJI+8Rs%cqLUg3ttlc^dGf14#nWDEDC8`|uVj zAB1`Ci=b>B6*y4mnWmcyE3iE7D%~+rAbS02wB~-j%WgUd)lNIp5ByNhqRdDNm9E}; z`0(N9(9okS5RPe>)ryTzwkA*xs~YAJ3L;`0h{d`S_9iR;w!~s_kf$?l+Rua%u`+QE zgU#IUti1`6@IT*EjK!2JgUu5BE#mK?h~K&Wk40z`e>7?R+DA+G?^*cor`&8=kRzc! z^{0(QmS9w7|L4YQ{4f6=M~CxEA{NH@|MpgO^N(NxhOa3pLwI6Ws3WOHgB!;!&7$v2 zD*3;Pb%gesE^X=Ml0Iwdz^^Zvyz72#1Yh3W9>*{$+S;i*q50~gspXJDUN>U7H>R$| z)9J(efuLOMu}?4Jw#63Gks>^ME{G#vtEt7v0TBn^Oud#&CO9o`ME7J84SX)b+a$q?{B`s zBle6k^fG31ANg_B#e}0Hy zO0)dwNSGceaK1ULy)$&!EtFp!CAxdHdO5ML#y0Omd4gT5+yw8n{Z7ai|WRsU; zivu~AyL9c0VZWnC8o6hc4*B5LtQq6j>2~SL`8=~es`MS4O(&TEe_z&H_QuVIDm}9P z3=W!KWm(rPsyyER@wB6mmS(UWk*J*{%O*PM63&giolQskTEa50tQ$A@n@)_&VW>jSSS;x}l-rzF10^A-y9~0awnuOnFllXY1EVPC%y3^iVb% zpQFc(;cqstfF2reFAGbUXwr8_Q-`Y<#LT!2w#KE=M$;j|@kG9|`s}MZ(vA6%meC2` zHLv)9F?1!{@*fkAQgf6XDUB`@&rAxEr^JS7!K!|PvZxQ<1WK2v*q>E|sz7%MiL9P? zc^bK*p$U?oS;mC(i4M1ID!Q%US_Q*hY}1yjKG3ULR~`LMmsyIQ6LtuS`SK1PsHO5r zW5TOiG&WXr&=}rFp~*MO;qxi$3hu)7{73YM5>=?%Q9lcXT%3nz?<%ymHbUz%QN6Zv z$m-qC&+_(MCoZAvy0;qTI@8A3e4wgjt5~gSU9alNNvCI8VhbGHyrt=JW821sUcC*g zeupJejl*5;pu|?<^Zlil1C`P~HY0w?g<=D*?$r~2iDvB(SGV&en|bwi*+%C=*s39{ z+GQw*QTTbE--NQ$#Rbp!EZ6Jdh&W-`dDl?um@Pdn7rsg-d5$htCEY~f%$zo5HSnc?wSlVj^?{q5&91t~t1*ep7U{j()M?du*!orguCsrcQCvPNwbC1G%?~@-j4bcyzFWro+IduL`3l2>5*gp4; z4RvkmUG>Tj@(tr8g357!R&?CQM}tPLz)$&VDTI@|GZ#PXzD~9zQ{8ts9OA2Gxfpy| zX~*MBZSYJjY3YJKneRiZ{$nPlkl&S7V|hvpDeh~eK38xlpX(DfB34c1#qM_+l~G3J zYf;C`35r=I$jJI05z67H9N1%_wMS+|UeZgh1?FcPuk{iFBW0I%81x95-2`T&Ob}`nl-vvZM;;Hk{*ewh=^uo8%Ogu(xQgO(kYKkY!^;x#gfcO%6-~%<_&{ zRCnzoyim3nNKp3E*!{I@xhh>IaHRHeKQD&vE+8mz<<#uXJtC>KO@wm`qV%e!XIvZX z8aiF|Fd4KaT>NQ;dwwm$b zk4%=Dd!nO!wui^S7ArnQBq49N36<*~;m0FSKYAmlrd~PLS*wiK2z48SCLfI4$GnuQ zla^Nd{O<7JI+blpbqe3MsHR}FRW;H-PwvHm_xi_OS2X<>QfLKLPysu}wWrN9cgyqN zhPmsTiD=;p&bahQETQAQn_5{KQ1ap+KY^XaBBT1t%58_}JEZ&!Y(p@B+ z{iWMo)$YC%)_YV<;C_Ej^AV-hyo+E&SM3b`F70`G8$?Ju=^gx6eGy;d+&wJcDq>59 zBtn?n=j~7@*y|_^T#7fBr@Iz(jihPqfcdzW8E!iZ~#fnTuU>y&4$D^K%TO9W8+)VWH z68Eay=-4|wpYT41jje}@RY~HUq;pd+KH85`Cl0qHrY`ASNY-3p><;^SBIpwhu8-$*y-7#wq%6`>=caeFL1x(ORzo{qWg~0m5aKSZ3XDGD|fjM;4gaiS+G= z)T8&!k|Sc}Csw%vK5PfCPd7C1POKjJ8k&#$ODQl}*J+eaEbHeJe1Kzg|LyVf1Kp)) zjF#?qCT*})MaNJdjfitli$qJczjNQ3`1NBVmtRxAS(;cxyXW|9RGT%NY)e_mQ5c47 zRP!@}+ipn_&dX7Rvd_xZSiG01{|j6xV^pfDSd{2LPUcf61X~WDoLph@>1e)3_~2(rKBW1ilYNU?p2%CB>$g906Q$z)~?yp`fRa z@f$M8f~!CM>|>vA zL(<1Ty-HNh{K0HgP}k$e=F7% z97F1>FG|59+Ir)bB)%E9W9~OyXLwPb_hpaX>AtIO0-*Y5lTmb101Y)L+Xq-^BC#H} zwv+K>p@vh@0zZXx9*O0hh##buub29I+KgNmWEwv+u;aZt$qyJ+?u;VgH&oNSl&|?L zdyx8UW&Vu9QZ+h$IkgSn@U-}j>bD(j^lB-Zj&zLsD`mO819{V%*sVnSO$2gssR((g z5nan*an^uk6+-HgL2`)sqT67sUM26wVw8}0sSu&4c1n28ibM~alJz-J#FWG8;fXHe zX%75`T;=NcyFT->H$zg=O@)5L4f6u}GEQZ#fMmX+5Y(CnLrei{|O{4z(yfD`}u#TskkPw#smA?j~JWcN2C&VO3JZE0iw zB4$Z_7MVP6A9_~--Ws`T#n5pgpDi0g3owTWfNI-q7j?3qaX7BYaB_0~r3(aI=ftgU1gRTr-l?R2jGwnu` zk|F# zTL+~1x@%{qoRr7%(QM{G005ENPMX`L#gjyEgNGtp{N5m=T!Y^l^t( zT9raZv2P7|ReZa^n|l>HBk$lc;`$nQuK z4|Y6VeUP|ds&9sdL1`_tk$UmSQuTqQf)eYj=aL$;VtD&K;-A9PJ0{Hzq}K4_ITJHC zcDi0-k<9G++PsqBV{5#T?kl*cOHRzjG8^v>{6?^7#=>mr4VKx%xeodjj?&Nvjkr}5 z2VGXu)`vsJTEJ${IdE5antj@DbK3~rsYbZUEs@~oPVqi zgPeA5vzK)5-#6Ij$Pt54y3j}b#83PpWi3wSUq>>sZP4!%#150%$CfDZm-iXUD|JIo z$9C(Wopj{5flT99butl1pNB~H@9lt_#w*XR>gKd2efNf!(-Luxtx8r8Nckue&GVFG z2djPE#1avoWaN`AEk(~eKWL)U#F~cAP{0UUL-4Kt+wo{}-}!lAebl#5s!>jnupN^p zbXxa5pGQF(I3QuCT@|*~(aktq4}ih(jtu(Ad0-0?LUG;atA!d*+^xk31YF2ng4%Y` zWRnC_)rtwZ`1Ty_r(U3$DG7Hxt*=c>#%)yXj39v&y5b#H5j0!(Lm0G$oywzpb}K0a zma|_eL4@Fg7!VzW0)w{qXwLb0=WbbOm2XvkB)?}WOg__7>aXa1D7`Lw0C*gQa#Ps~ zP1Xkw9-y!SU*zSyOx*Lu1mR4fLPv6s;_F$2YeDVsEjyQ9htqjJf>(o+-}Cgr)RHmWp0S`3i!@PpLiWHUs$S`^IGL2Xyz^>N{z;^`LS3H6{!kb z`G0LIht-elcusF!&ad9lhKFHK>2sX(?Fekqb|m%Z!sx{ZV3;48kT!BHkAg)hvBA_G zUyJPS;olNPPOM$hoHKV^Ubx|#Z*_N_o77cDz`Hv--zR2Mmd zcn&?+GrL?WQhT+n1>cG3HMrgFdFqcn%GrO@f9mOTj>}`zq}+7WjKeZ-xky%s-sg%? zAf9};nuxSpJ`d=thIpc7cwF`)g6(04I#=(``-nf5gsIt7XG|5;xW;u7?>EPyM})kV z%q=6TaradVBPf`;{Iz=JhHPZ%r-po+thSslzzf8r*pJ5>mF|D0)c{i4vIK4HU60Mh z`aCL8-Nnb3qc%zpR8?A}PvW28=@r{^7S=~B&N*kAK0_TiVSn0&8uSsvJLKN2reuTjH9b z`ceuDHzTI|uj-5%@iy5aHwbK5BpF`SZ{FqE7Kq(i6l30La-p5gmsGey`jiDzHK{M_ zyYY$8d2E1${A_0`9U8ppicv*?<mm*hW&uJ6 z;I&jLDkr$;Syw0ON;K&~tJr#`nhS~Asy~B&Nf<-3PZ|o43y@bcxWKGJVR{4CIRd#` za7_6?Or7MrRr}h{uWkJh)kb|#(ilp~yhc9OFb1MK!+$YBM3irW>hzcsg=b&8WY_n%v{`h2V`%s+`T=^`@`mx`# zF)ll!U!(XG7XLt}G}M-^vW8QLnKAk@2B*vqN!a(AA;wdw8WaX$zT zjiKyPIk%I%L!kF2A9Z^Kizn{D%g`i9!7@}YWGP;r0`-LZt|%HZDf$m6i&~%wNH@S{ z-HmlkQ4bzbW385*&!8TRM|_Uyp2tdwn~yid$>&T#e6IZY>e+YU%zEShX@M-F{~qq= z?T;+#ik$yBOaI0e!CR;n{$pbPv!LcbpvIs2(*M&cT7uew|F(+%0nk21G{ngKj|+U| zYYYH>Kurf3vqB7GZws>E(a0aCBGvkZD*j1EIRMaP`{SC;3yBg$#A0$2 zF)~V2V+OpX_^(z9jCVxUY2a(*LciW3*-Qr{dAgUASS}d-GqLs_9${~pn!cvSGEl`a zBhc|`;*3^W*S>9$Fg{@qUBD-s8d-$5#J?tXB+_e%QM-wg0`O)|<83fAy^iiz2v_o6 z;&;W}*Meju3VvWLsU|e_m{#`Wm%VE@na4KvFrHIIgJ~) zZtT)uCDFZFU1rHF8d1)xoO_mrZV=E19{XT-FSr$b&hR5YncQXI% zquzhPd@Ypd0;o3jGA($C*qO)+8kRb;-O$$Rv$ob+@pHuTbYoNGlVxV#IM>;A!pAwI}7l;v^e;>~9E^~$}1jKtADYG|;+oQEkQ zsdst%#O0^;YG|#z7A2a{=3R~g{?x6-`f%K(uOX3@-UK*w9wfOB(`ld1wGV40fymE3 zfuPV>$A52PVj;q4bqj7jct(TBcjhC~U6i?y1 z>dos+{%Z1uq^{)Zj&~)~YDD!~QM(2FVl2sR*P9nX_HOM%hSMc{*$^>jJ()3Hzb}U? z2ER`(6#ir{I?GA-f+}rS>teJ*=YTT`&GUixJoe3w2SJ_{-)9v-rjq$ zt1T|v!(?ZXF`8^sp0ut`Q*Lpe37^Bk-mqRMP~nB031j8F1EB!JAT5HGcC7Zli8xm5A}h8 z2kn8@rmQl{)?Y(65t8_Z_Zk=s+HJ`rhh*W6-;0LWd>g!3us3Z@M~34YjupsobJ~vK z51w{IyL#r@#n0?t@s^9qtXdmVjde@i8NcU;Q*SNf%{7D2JoP*mOt2x(Cmqr0|J~@` zfXoQ}gmphUaI=&oR8Fs?E<^~^e8zd8-BYZF->a*=(Z6#1bIp}*r0U7Ucu_GeU5=q3 z0s7qZV2hs|Mw6z^@*sP;9lycW?$hed>^kXIszxbaR$| zSr9kd6x39aeB7=^)3+lQxfa~gsG1zodgo|Y^N5Pfh)n=ys@XNGzcOWm3%g)a+Ny7pZor5`4Q6P=>^2Zn-W z7aq^g-7lfF?`$aeSJ#@NB-8WHnyoyFs@pG)h@@%_ncoJ{YuavRm`%trKv>J|MF-ng zK;l`QCRs)8!r>Yp?w>Pz<^5W}0py`d_onD|?>2D~O)+dXT#H2|ClCHK=|5W+L-vB= zCXEVng_cXP>th1hL|#x_!>QkLi-=t}>}?jP;Fyaw1w{tOyHLP`z6M2V@q*4w0s;b4 zPhhu`v9GEIhi;d;sRL{Iy(lZaNolDX(VTF+8X=Br#d7sQtmj* z;%xfKkk26xJTx}id*ulxRYCyNG-t0vtDh3mo<|^XIm6fC+my5u7fs=1OthyhH1NHEQ!57p0f1Q%(@1S?tAc8EzP``ZF_cyDGC`_I1#6I~~L zXwL#60Qtmp_TarLq~D-3RUqlz5FN+FV1&QRA=8f#>@CBUsUnxtWIKDd&OtL~hr8AJ zo4*RrJcL0E9=xQm7Fl=#xGuE<>l*D}1x3|Vsq!ZWBX|N7{F}5qbL}HF!alQc@1R|R zeV%xTaFKzl3XY&gDasCpRe0(?SMc4DUwHv()55PjHP4LX*%H%tljQBo-2$qkJzjOU z5J=>_qoIQ?d(JTHj~klHbBRF)O!u<{;UkCGkYsZO#pLHl-FsJpi>R#!a}z@E+Rj~Y zyQ~-~J<1Id=@xmC!+cdEfM-VKWUG3t;ZZV47SZi_cI21%4Lg9xb2dp{X=8-*xpyw9 zBx3yVBv4p*YQgZLWeCG(&eRMUEIgFurtXx-y7#MMrONHdhe3OvdS9zC5AbnYlj-?S0U zEJYllD$)JB#6KdA%NCq?qns2Lr*`F*l!T9M){)iI&fJkILOK*eT4k%6h7GKt5s1K3 zK|nLY>0|Nt_otr09vU^t_1FB&9nXL3iH?TaKJb$%y)jSLb5eam94yQi zK?*kO0=1b1MR+^V>d4+`h9gk0g0Ujze)t3w(k@SGK}-OhjjEpk8;!%H@7w*zO3S!} z=LHEFW>;gyJ93|8?Z!$~M{wdKah$EpKQn%jx^1|0Xs#@i()SRSfd*iD4C{9qjlrL( zC~v*rbo%6MDZBNX_2y29_*Nb3C&Y$&u~C7Optw*Ky^Z&xH{@x$XAtdC?up0jX$!Lp z*c=ZU1w9dY6X}zd@JBJ(X6p`}i6xq!0uS(Ug5)kDqqg7k6Ygh9>v%`GbCa3Bf7hL+ zbR!({SCG6Qz=K&VK}HoFzq?qAna}Af>6~)zNtiIfeDk`bf|h+^nXc@^$=UJw(st&* zxB%tI$c{R5<@z%ZYtCGNV+yZs=&i)U7nN>mV{35(qTy_0Q;d0GmABm=q2neyjMm8M zlb)Je8Qv&OxUHt;&+_(!G$l#wlmK);MQ}Y`dM@3yc;tnDLY*I~OLBr1iqBvvyD|-Y z8G886U1?tRg?Whs}0cZDfJMIEP$J`0oYPQ{#k zlB0H&tK~x(!8lHo+9a-}&7S|c>TIAA66(KOone_9@;nqQ3RY+0Mz+CVx{wAL&v+44 zoYd`zuGNtRQ0p_nW6qQB$Ne{z@Th*Cc_cSY&e{0|=8M}A$snDRlpy!pHCrumq0b!BB-lC*9Y)3sC+xSDnkmB#N8c2hLtq1d1&pQWMNo4KFLbQ!g^`L{Ub8$ zMbX648#(50^f<4SjcX%zp{|N)-V8a0xeCWkN>kS9i*y7We8qT7gs9BK`3N6dVd9pZ z*}9!QR5wBR8b2^$;$>0xq)tZg2COwUyP>TRmi>%Q=wP0YuKQI@<%TI!N1DIm>mAj0l zg5M@ORyTLwwv4xv|F$@IrhF!1d+uceSE(pCx3OP56)OL9TAzLg3X!^T6)gDWG{x*a z-?*yfm4Y97UoA!4HjSR9KU_c)Xzi3QNhpNfNd1Gn7C34B|)ur=f?%btj@C{9Xpqvt%ry6SaeK7 ziwt^MgO}`M>=(q3BwAgzSm3GbcyXq+`%O9Kmy1@|g0&Cib*bV5;wHT6)?ni1lY7Tci8Xx@4Gz(=D@yKg}n4T5ysFy~^v35dzLuS!T2EeMNkb zP%FL2a1W4b#{kY(4AN8=`b-2$7XMtZ1A!3I%T}{<^6}jnI=S`*)c)p-t*K0|c;#nn zMYiw7%OmB-s02^|wbkoj;3BlYCMf z#v<&3IW!*Xc6j()xkU4stO`Z&2RawE{_1_QfK#38!;zMc?x(W?=#?)ci!J#hj(WL$ z&+l313}1{+%cYuJ{%TI+Ncw5z>q2O_hzNU-%_cx7u&Ab%->_k8NNhhG>&@& zYTlnRQh}dLuN8Ht1#Fj{ACB<*Q&H8@-KkevY+s#G^KKr4W#GyYsT*)0J=JQ$Ua`Um zpM-ujIa)Y<78~vqpgC@AOg!H!K)Nqt8_txV=n89aZWA*s9DAh0AYMea^iVr?716n^ zdY73y|AFbqmnapl+iTrgjg~Wl5MH4gk-jVm%&Xm~38(X(7fn0bY+9KumdAP~5d5qz z!;d+8$MO~vxhi2B*=ep;IF3zC7jimfVCM;1*E(oXSmGA8!%iCvp-cLgyZm-ck<+hz zF_k>?aD&wUk{SijEFpX7*JbAUmO6#f@SZ+}UluBH*muI30^(F+!w+LrZ|q-%2-Ya!lTXxHLbCY#~11QLGc2P^q{i*b_q~r=zbqs{P@i&azEzF zn$F`N?%v2sv;Kg5tR zY8hO&D*08lxSk~(`aP761Kq~$*#riH#-el8;%)n$@|&iG)5f8v>rpAI*(!9%o}!T- z=?au03`0cTU$z|wUoqg8BeFJ%*@uCldfym$fe5h z*tQQ9KdCV&0?{6dhN8%XnSMy1QRdudX@rcoXSjY^aA9USW2=`5EqKJXe8gxAAthF) zoi~3!QWFso4SyPAuls@uLb~lunUX#pdI)>*Jw@k&YTd+{_Gz=+oi1o@RRn=qsAv@w zr|e#_pD=()p3%TAcp8yZPn{3mE}gcVD+kb{@4ZsE9d4Bu{EqG72{YTwt7Xj(3?{Oc zmt*@Pi>5aSHrQn=vad%0m9!445`sg3qP3QG$$Lr=?kQq7aLt=lUL0Kz&J$rmAwliv zd88rxF>bA|BqM^>oUuB|vlv}yh^sL{S%$eP-*cF$b7fPf^3vD2mD(6T?g_eaQ2rI` z{(+<#b17PcyJ#80+}J&VpQwH;YD6%{T|_=z#amK9!@KyKT`83sQeO7~&Rdjm&+X3Z zmu11W2^06isx@?Q%pM~7`nNE(NY&^yN;8c)4~bS(3)Nde!8UNrmv^zS8oF0N*0_qw z54KC1*Fe>)DX0{m1?BiC%T&!!)=5y~1@*BW#~ZER7?o;}Hi2nEpfWd;_W5T1CUA^p}d+F@jH`lTu)`7?YfIEP-cbiLG{N9b_- z(;zjZAv8^dmE@S|ra_q@U&?%AWT@xH2p3d^ZcYB;v~{}+S{wRK2b0B|n|1O3ex}R= zXT0ACHUDL0FwC(pJ!8XX-dn+V)zp89`2Nb4iX<;Xo*YMN*u#A4jqL6lLNV*pt}ojQ zKi9+Dg}=mX?><)k=3Gx1wqfyjH9c`08!zM14Z5_kd?R?ZK}nPziCNW2AQ>0@u3?Ue_KsWt^nzT# zS+rzY?nRzqxC@7E>4)-Os->^9$J;-oN>s|OOZg@}14(*%RMpESv}}D}*Si@P2H#LR zQ$!4AC@E1o7Zhkz4b7*-;ov_=Kb_N47irUKis#Lm9nNGX*^ht1cl}#01o4>GMxn}5R090~~i?qmMv)Fas)oJU$hrNBP6E3lDnZ>f0A-%ac#tQ@U zY-Q&!Ys=s}4Hle5umov;sV<{P`IVLxUv%MP!No+q5w!yGat$Rw_`zI1QD*FQYnVTX z{`ux?Z?q}Z^Nx48rSYy-w!w!w^OH9_uLE@>&5m1~H zX=^QJ&d~9-7wmvGHrbrS@)hxxM;$6!HX9X8T{w81mWmHzZlo)g0X-o4L6ReTBu7a5-b-8r@N*Z2}bsEunXG8_oP<$I4?d(Vtzjj_a3jF|=G%wS<-{JX7E>~l4 z`U6euk~0Uw(YL|fHefOw2Yc7zWr>nK&Dh{jyNk~Ss4Ju5-)%Jm>cu2hqk!DsZ%Py}x))b_TzLqwt zwtwXdKp5v@ZD&>SBWdQ2uqr#fq2weJ(0L*;jv*)!`%Tu44ac1+2xd!yj@+>(p(`Gz zu19W7BKkb^erG|K;bFCvXT+)j&kX6z*g`npMEgf->)UWPWP3z9NiF0XBHo_E>`=X` z*ef)2S0p8wr0k7fD7M}mPQ=(z7+~4 zzOwkuJhs6BE8VDbL`bPw^vYH@#)>Wy+vaEUbzvDAMZr`pc znKN5RbsS|D3RAp9NkuMp-F!XxBM15mQ55KnQJOF>@Cry_1C9&;kwBi>YEAAVpS&?$2%E?IiUo`XKzkZpZhOOu0)2Gq@ z)?j=B4D^4z)$^ys{{N|MD#G{whix-SD17U~{d*jDX@*3dtia6eecWf-oz8kXMlTWI z>1OMJsvQ6Y14HaARXd(ZOEv7&S+2{ z1%gW;#r_6#aEgr{C;g+oK-?&NeLUuMv6*wcH4zE~L>%@@ua%hyL1=TyizKJ`r#NEj zOZ(zuE-tQxRXhF=nafisbq$X4d6Os_)=%A4Yi=t zv*znlt*5V75PS9e>CfI~b=eh#|9_J8Jo6QpOcjm@jGPMsV1ovxA^&j)v+<7Ldt=QQ z)pyGb$d|jGwt%_E5a^a8IGWW~RD&F5ji|G7d-^ab@Zm`66*0wMM%bP8s`XBLm(G@{ zZjJ>=%Fjxv=kStPshCX_;YA&f{r-A1`zu`4F}3S=KI3Wmy`;G7+wgZycr5;TEV>k7( z&fX}lo8if-s6d#F(|BHStD!Q7Szh>2-qWd~pLesX_(_&2N7`SMR0#sW~i* zK2?oz_=$imBgUY%wlexl5fY!v*wA z7oA#xvdEmLbA5AMyLTcj!*xWZE-b;>lM_L`x-d@sE(SLK16Rja z^Ud$TUF$6euAFuD?A=Ig8~kg0g3J%*EiE4oE;en`f+wtW)K^m2cf^z?e}5#UFVNm+WqyqpVj-g@b~6Q zkqPfmj(eO}^u2<-ji)8#uk+5K@96-O7FR#e)v9EBBii;xnb0@s4>4@(15-TymK=gF zV`KlkOQg)EM#xsqj;am+U#z`#Sd?4C_H6+cpduixAfQM{HwXxb zba!|6(2PiTNta4@cL_*$H%NDvz%cWzamTaweeeA~-*LR}AO54`FwC{Cb*;6|^ZcEb zoQXZ^n>*LI9KAWX+_S>Xebsu@O_sjBWIYSMpVxvEvYlx*tzNsYeasI+1l&ix`Q^)( z>xExAEcJ`ETTnFsp8%Qs1{)cr23K~F6Mt_)sn-~+YC^Ep!5i3S9RcYB@Iq$yZ z0{sn(GghE38bhm&1mJ+D0Cv}&b%^{~L zJxd@9*4nuIz(9Vu!M|XF3%GwLY`%3?cuG7P<^ndYz+n{b>7Rw43x5k(Sw2oB1+sN` zX^NWwY^}R9guSy#*kGZrT-FelFPKrty=x%Rr~D3x+skcjSZ68eNX5G)JMx+o0s7ln z8!~!Ce0OVaZBbId($CyIZBA_AE3{o&hq{-!EH-9iToLYSvN^{m2y5Kx%q8~25dyvT z#KoSEbRsYdY;=;Obvn;>3hUFzLVwM=#BDN4_Wc3s85T}^N*r}meQRAzMqcwC?LBF< z0}&_K+NBsNKa-t_v}-DRS*ADd>2k@-slM~atbvM-oKmcI_qqH*mJay!8)E7|7Gz;= z{=bsOFV_>kaQDLM=o9McG5RQ0kotDB0Qe-@)GYl)8V2wQ^QHd!YNRv{?k!6^hr86e z?aVKhv;rzY%2O4ydcyj7Xj-Y>D(dPiBiX#@vNx9*B_Q@MP$$wPL|kykTHG*(cswyjmu;|a*rjd{`n zD@M3uQ%gxXB+=ef&9)FhBMLPow09XNwcjEx`2^B3;FFUC>yRmCPU zZN%Wv>2ut&lDT8=ILe&U()2UwUIjw|bridKNf{{_*`N_q0}o#V80UZ;6VP)6hW0^a z<5lqGUSmpy`7{!IfxLeJ)F-%I_F{0T(RD4K4d_N|#qGpPme5NAa74X5TN|^M>=FWE z*KAsTc3`1mRIUQqo@lDwYv=~1>s}y2Zo5FcKD`71`lxi#m=Y+$-2$w`K;XX(peNjn z%~%L5L4=3|3ZwVMAfmGIjtBUWQjilzavU&-IKBh^z%PLuyy9Wl?xbPLN`B>>4%ml) zpM;E$U(Tsk+mP$F1tAwr$j<{Z>O&wQk{eJ?Du*tMWgu^R90WB<_#=u|bA34Liv>D5 zJu)yRrbZkb&?);+j)Uk6k!oaxdmuFRYgmoNtB13kkK=^%$CoP5G_KpOP5G~nPS#51 z(MCk<%`$b93up~Et-9Jaz zam6=r)Sn{XKKtIUw@-_t@b0QI5uRx#CwV|4U7rQ}^Jt~v25 z9f=Hrx5l)blN|VK8SW#9T|@TRsm0Ghta5^}g1v*K-izXP!$k&zC;TABH+u8v#W!Fq z!B^{&Ev!M!7s3vs*!b#uFD_Z<%!RylbV1i}wiR+aFsFsy+5&&1?$n;`NuzC(Lfcn8 z=lW!zd6Yu(5fzU^+gm^)bpu@Pa3?SdHu+x}n=s8mFLSHqH|gB^3BCnjzbaD6zdnr& ztRnwtIIUnS6l(PH!VfT!kTn1|soKa$xG^-AuNni6q0j&^?r61_9iV3R>W(llx%RJF zTU#SZOMr?ZovT1|4NTg7$i#|aid&m$VLj@H?iC%t*8zcmhK?sh7-)s{r}(C0c?a@- zLc#dO#={giv}*4f-LG7Y0b)mfeqNII3W=WhZczy^IZj}sQN2}A>v$lDu&aUTMzf3s zJa9ICubM%#PbCoDyW~>%I#r0J6F{?M=Fq91Cmk;RVlIe~l{xpk+i@DMCc`+BX6T$nkiHV~>={Vh z$2Brt(LF3AZ*=QIhaL2myp+SFqg4Q*LQ4HfF0Xim18+B&0|j2UfgpJ+)ta zzl1n%gh!!2dHn(Krk-l4Mp4aOIvzW7Yr3D4gXerIVENSnDq76S-e4*kRa9d!*wRs2 z)}P>5R3?Bd+7C#rG06G7A@*(I8_kh-gKnKTgVC*M7DOqL_|2e{UauqU!wvxcgb>{n z=DE9@33TCW&nYQo3pKa__sZ#q2U-A^kg+ZeOk-h1HZUG{raV2Q);HD-N~feje@38Q zh{1bKWj+Uub02K{{Niqftf4=`)#)2kx7!)F;54SD?m%ZS5Q#g2czVtY6(5Zi+mj2y z8;48t!|$XDxI!C`^e>n>$4F{z-4G-xiNekm33ymJQZ%Fqp90fU42JTflC1@esGH{gME zp7nJybAa_}l**QaZD}GFXR2-GautFHQ-zTyWPss;I80&_h@yBRi$ae=WFogJw~uy z>Xd`^_M``we+DxSTF~P4o_OYad7&s~)6ix?vyV{v4={pqkosY;g;BnLX0X@gBG?v_ zi`1%dh+c%Xf2Cl|B(&`;_!j4kG&%U-dk`rJoOBE4-d&xvU3)x&%3YJQ0OZqQ*a~G) z63>>XE~i`cjsU`^&5WPGq%}O2-xvRvf_1yst91vOQbHk&~#4%vG1EgD*S(w&YQt57D(sN8}1BqE;IP@Op2pU(+8-o~$KhhAH-zT- zdvdyk&fj+{`UZ0B+ROPKp>#VGd|#}pux`URZ#fPE)mjsfbM$hX|8 z1iU~Qt7nnTm)T%u$UYke3+oTn)hJQqV?bSx2oHa_AJ1;Ps=q<_M<8?#*0`7AIK#chV`l6gb#8fi#&XX_lw-D+JSwcUG`b4vFbs+|6H^8>Nk46(Y7 zMre!wk}CsMesq?q#dG78n(m=0^J=z7vI9Q8GUiq!5ejO_t16=ZA<=_{1H&mHsg2eG z!@9^tMZG>p#%y+&YtxQPlB9JcQf2p8nGQz94&GX4!_z#z_-VoVJ-Ht|;AQy0+5UW| zqx7br6P;C>p{BZJ#{#unsBHa7mEafW8IV)8AKLM#dh758L|MOjgvg>0TWbA9Tu-QD zxQ~iWyJY*)X^z3-u~J*G$rhV+#rmO5?K74p>@dp4AjwZsZ6~JAyqY3J8Cs#NKdOlR zBu@wO3J}dPca2npv5E-YepjRGq{i|Jd>H-5E&TViOandX=SJ?gp1rU8@eEkFj%vIY zgNLkYV!fr2@!IV#%Cp}b6GlfbaAf^OA(3keH-_XwrDVzF)VJLWpEqK#=3^=Of`5OY z%1>mW!disE`iBxuLOoyo5p4HbPqyfI4_AMsQSVP=jGFlS`TYO}IDLR?0)$R~u-_W2 zFjt*(-l9o%JrvQLs;XiG$kw*y&PXr=U;=~x8dyo*_zbvBVCl;pM8f-vAOt*AfPd5s zCJ==T%|2{sGA7ESA zj;lL_141ewB{m1)F?K!91(8^T^N|_S3KW%pj;~4m?Zl5IA70#|`!K@gq zMV!7?PgqCZi{(ZBOgl`e`u`!H+vfdaj(1Eq zl{jM#@1w@Ol!78{2FJo8&oe4BCt^g^f6ClLr8C?92a=txCOWrVFgTS;TR2y?Drs1t zco+y55 zMbRnVc>YrXC)u)Qu1PJ>Qk}7X^LI3bxQXc-d_FS zTeXM;zjiODad{-pE1~(3v^Z za$0=ri{}`>zY(fv4iL5f8ES+Z8pJ%O?3Q!r44P7mqGcy=uI+~h$#N_YB8 z3HJiqLhWzr^BOUqW-7k&WoXe-G@6x$%D0wZO7r!9RhpsytTdl4WMAz^4s>`7+oRlj#~#H<2El)vj$Dt$!$L|F>=fO zQP03m{ll@}J&aGqV6w0Z{-@&XhFPC{dEWYsA!Io<5aYlTMNiXFuu1tx zUIZZKX;}ta)*7er23x*$Bs*EK7P#*-~TXcJ_57qgvKw6XU?N?)f>KlRzG~cDSY1^#=vAN4A&Pueb=! z&Mi49iBb7D&`J41sib`KW5yTA!N-_v`IZH4l*lL#`zmn(nkApd(!Q0P=lO|$?1!TS zv7g_Imcxm%VK$WwxCYKvGQsi~>|P2>1gZWqOFTjSQ?Z#jgPTGIvGB9Qm-VWy(dd-bQ(r$z!I!;eHZeitAA7ck!MiD97Z zrbiT~N4)#XfBQon2BG6$d~&4RTE&Buc|j)lpA_J%wYv@9#k2J2$vg(2zl(}LOFL4K1oPSq5DNf-a+BK?MW{FPN^ zTrVI(zBpff3jNXnDSf9K)SXyg1i=Bfv5G3eeYc%;nhW`g**O7m=VKq_C2!_DHvCIE zT#$f@Ga#3-n3oH#0YT=Hk=IN;=|PjoA0&Q|Bc1`O_%BxNFX8=fAkP00&rkShbVbR- z|MLC(C5ikVDH;Foaq$1swM~yk5qgAJ-;kgf;pBI;_x!{+z!OMZkkB*MFjDEE3qJo7GK+939>XNZEp?{dn z(y=2Uqaj$&dXz)Ksrc+7HZld?)4H1%8{3XiHq;o1S1R3mz(yJ9-t~0jW9@fvVjhP# z*v=m--!l0YH>I#=d4yf@O+1CY{R|76SDU?^BNy=2wI;UWTCGIU&C%baKHkzhY;zgw zjKEe_45`fZU#O=6G`sKQs|T%xafv)@n9Ki}(j_#E;!!s`{_Y0yHJ-%^_K?|&2O_-r zH0=H8vqsEk#(DYiI=l(r{3l5sG%jC$U^+pthX@Vtwmgsz?zy5Tbl%oyfDpg1P4xb6 zh4(mOYagBH`2McR^O3KMY5@s_{Z*xdd7+-kb^USEL?n=8YJ{$y|xCw-|_iN7K@%mg@zG~{kaa=XV+@%|uDP{^q zi$SJ=<88^{O~Luqlj}dVdL?+&DmkA@dUja3CqfkCbg8!+T<~9Cw7uY`R>2_b)Z6{I z^qq1UC!xV@>vdajzUWb#0%UYKjYVXdBYz=2|uWyt5`3YhoYtNmTfse z@>JW-Cj^#P_4fBgyR(%W^{aKLw-e;I&JWi{)6xwG%G`;PW9@MB6PTzOb^_2<9nU>m zuTLLy&_LY}8uly&rGKs`q?}vtr0A_J4;47+Cf7g-PfTz$`wPZ8G*F$(2Xz^8fH2%! zQl4%^IrR$>X-e6kY>8<^3DVC0#fYppEXS@LhjyNhri3Mh^Ph0gR2>woWsMfCbA;Q# z*`V-a%STHX;o*=FzRLcz=^y^rjd8db!-C3eV^(%XEC~hLd#M!juKknbY&Ok0_PWm3 zgX$TT3dww-2xHaVh2xkYKKn8zF$WaH80E&+osy@Fz`L0^!Jt~QoaSeG|$ajAT0LPal=Qr!;pnnZ!tEOL}iao7s?VD zBbN&6`ZFwaJElkk&Z1I27b>Ky6|WNfcM3fHJI73Rbx84*IILu}Z!5*{AxOq|nd9Uc zK+iYJsW4I?#U{1&{EO7<1qmh$21@9wZiL;RphV5P`}-F?tLt{H^Mn=*IqXhtZH>H~ zvS#t|%=haqbzb!)R~~&ArRRFR^i-3YH*{G3G%|VqG(~HdPBoS*>z*h{L)0pB?qPqw zLPWH>oo{Q@+G>-eq7@H!VD*yE{!&?OEOQ3QsKCueL~yQf5oFbI-gIy|p_@=w`)o!f zW?E>}0Nish-3twy9g8{lY?_Nl-HI*#!;^Ja3kN#GJ?<6gS$TT|=-h?nW>=}>FRx9;84G6c5|u_mxP`3dhXZ3_GtfJ^ zGLeF|dz44~5p==B;i6XtNl%>HvGhZ7pXXL?FVB+C+sx;aDZ?&GnX)x~g*7i(aTyo_ zdv)pY&h-}(8pbjAdNCXkM=1&iCxu(F)(CFb!_DC*!KlP;JM(Ob1v;mW_NWe{!-bw6 z>87@Em+~xNu(s$H4oEN!(`TfFYgSG=Ed`o^^r)j_9!hSfW~jxEWtun{QA%DB{oa;Y zGd0yNi8-xep05MEdCJmo*l@W8b~U+|EuD$d4R<49ZymW4!x*#Q!EsD-bSrwmL@*?0Q|fe7IA!+bmJ?==C{;>>GCMk*Du_=Y8-e z-6vXS^jR>HZH~?!{t8|T|0$NkQ1TD&W^hOwkK}Z@pa7Q3Rp`mydgToB40SX#5Nms9h{FXZb#~|y|m2?!5{s8;UV81D6V`Ebw!v4=$ zV=+au;CW<#g%}&3wu_b(JZ{8cag9)<6>BSRVEzZiw*j|c@Eqh8t`_~jk5PQF{XE+~1 z;s-X(+4Fuf`r39nJuSq=)9??X!p-TvG$7tMtCu0jQAkHw^k|FHBT2ed`W%z zG-)_JEPUsnetU%w@BRNZ+!Q$h{3G2oa&c=Puq`SGtx9%2M}B9*6jfYXwBze%frt0} z5mSGmm{#0ky5D-XHd(@%Bx_w=cL0A$N_Kp_@krV%nP?Et_4I_DWv@=jEdFvgujO>z zj^|>Nno`I7`E&M(8qTESo)SzVXoE4YZf(VKbRUh8TIyXy%{gk2GY#){$V-N+vs&Gb z4*UJSdVvk4Mv8JW{*9q5oL*BQ)U;ufk+(jvZiTl4vpcS$T6b7S4LZjSC(5{kBa7MV z4khl(=RR4VCM%iXnucip;MM$IVy!wz*U9Tt2b?gRr2Z}-4J#E){j0l;xD$`W*g@UU0^dE=% zM*3D>4B2hFG2XOvifzkxiDEB^fH|z-TM&=<4&HPg&XS->Za@$RIdk(C&dZn)0}*d@ zzvxDx)Vxc;*P`Q?axr|)kM8Q6$S1UhqvNA&+~IRwLpxyf`kd+kV8nz~BNEi-y+X0_ z@;aRKMWx9!Xh~+A%cKV%ebY^CtXE$)K$^48D)71y9V-*cztY~tR55Mkaolv?PAFlr(&I4X#3ikIFIi{N56DDQoX%N(fJA5?r{X;er?(bs!XPa8o; z1!!v`t^vLcJ1_)JZOH1ur37w!pMvXU0$uDT*vN>i~kk%uveBb@oPnwLhzm5n9M!>fFk@sED-(Lf$V;{|tG*)G&WTEa)MSnaEUt^+YnX zf?}0dK3I`Br_04>dlJu-{kmfS#})1>G2+s9D>j6XK|Wc?5NKU zay4>Vg!^xeElk{EMHkI#`4y6v^VMApC_KZ?Hn6`bPj8zb$i+52LOhfFZLpCs8}EK{z1KtA2EEl1=I3cKZZ(#C;JNFc zr=w+9))<+fYis*ciNajPD>|%Hk0a^KaBATgiXnJCvs<86L0f;yP$N0=sMyzNrY6%e zK_x%KdMi1R`=NS{TNNQ>W|vEBtfbYdT+PYpdtyMUsw#p>tXxHWyn=?!3MN;4ZnJ}7 z;qFM0O5z;9VT)t6x$QLXvKA>TBHDj{B6HO2t9_&o`EF?$z~CBse*cbbLiuR6HCbw{ z5=;1AIhJt$^58zmt}`)PNHGtL=RXV<#Ltl7lW+e1tKItx+ zY*LmORaDK8M$=QauP|r^cy0l)E)YDm7{CCovD*Nr^K+Lj;LN=RoYo_qU7#xH3n-I8 z^3lPqa&sRjjEqJDPm$d;puegOY%Sw}hYJ*p++l0;dq@@wdVs)_bOrR0P%<(`0!hdQ zSwfYk3~Fy;n*hS~-TTAj+er7W%Wk!AJF!a;_}N3Ca0Gs}2Su7wwoe0+8n8`HSf=9G zJt*aW)5_(COcVf~w}2`Xv&k(a1o?5mXv5{D8pz}Brwl|((o(Br zvrtRuC|Oif`>-cn^X()U7ZoW=nnz5G^hwO?PwwVe~mMxLeiJ88yjee#-wI-NA zR4M!=huKOlFK6_vNpyY(*8y&clI{Lui_qpvEaCl7k0j;8H6D1WdnldwbPcoPdBt_= zShfg5%LWfy+|t`SmD7ECEnpOJ9lXH@l$EtZKxN*mX?Qb$!*qaMY-WBcdY1=uF zBBw5rkiTr>T*cus@NKWU=)nRQSNL3Q^7a?)?#@Xn2Ux?efJAPoYrO z z6+8OVK+N2246L=F^(aHXyW5h(fsK%j(1XSszuF z5p1S7T)`_>YI$>*g8mYvzvwgUhX_&3F7Jiaod_Ptwsnyq7ME(0=CY&y9>}*#z40q^ zKLwRJ>WkUHCd%n2sl7TQY^4Ob-yMTCFDkjf4vLk<@&pr^xSC&dW+;(H5o~IF;ShhM zmMWBY;M>_5qa|T2MZ2^n2i*i%{p`6PXx!&;Y7^QrP!Pf_=!27CGnUws6AOL`X#IYq zYw;#kVK@iE9KmR-1Y6@FCLBTezyrd~L#(;VQ5E*NjIdrhW&0n`b!*jToACuMEvhl*-)xy@Afx9{4z6H*2dH8J8fTW1EkKREdq4ms^vkTB)$&x>$)d6@Vi^I|h_65B51~H-r=p=V+uLTK zlCozcTb6EG5d;%xr%~qyYmh)_Egdj%X*n}#P5%aO##}L_8?6D*IB>gng6Tof)n~8`7hC<3e0{lbr{~6$a z&wE&LmgO0VqEOV+cu;Ls_XTI~ZbWO_mNYFv+&ut#?x1auh5YU*K$P|&!Q=wL-ySjv z1iw?mQ+C|ONX*7PSYFZ2(kPdT&tZF12&X!PW6|nh!IHvYhv>|>1udJ4TUG^?7`~4S zT5y=-*s&Y&C!%L@*=?HVJ9|>xaUW(Z@p}w@@q0}~+5eb3ULGGW&S`nYi4BXSD(v0N zx!M#H-E@bl*QB3NevO%RMA^0)sX#!(^+pvxynLZxp`F6U;2goQc>R{BH6g|CCfB}D z+&m#`VM|beeZ*~@EF%kUX@{MmZyj~BstHdCBHn4dtxCqq>>8isb!JEq3Egee8T&k( zBhqhoFgO$PJ@JKV`vl>m5S9FAoMcvd9Gqn6rb?Y;!wK%^pLiAFz9N!t@8#-O^*P+Z ztf(@WHLBKe8`cB%s@ab;YQmxU3Ie65_WqJ$*Y{@;kY{9(9k&rYw0e3&Wqh-_AqU?? zaErYa5T3C4mk0;0?=k_9uLDL>Mjmc@tB$|(1j-zzQ%h*dbSi{C%a|7Fqm20{_PiSR zAL@9=DZCv{6Xa&)UVVlV7O5%WjYD~dKDUF~z`m7wdSwM)M*%mXf%KMbQkEQFiPby( z@ZymzG0>Oe7aF=YQT(+qq7vXdK$r&2Y`V^g5p+f!1=mCgf_Mp=>(AGq$+LPpeH@pY z*>JTd4zOZw)qymZlQM@d77$Gu6!~);!UJ(muEsHfoQ;&gaoLfe1N98CpQs($vh;Nt z{B<^YEj*XM@~-tYj{h4BAa9V$Cz#6NERjg#+!Y04_-pEAv|+;O9~FY{H*jTdSkUU# zWaHuew8X{ECTFfcZo&;Ya}5AwYym`L5?~5g6A@7^i3YIJJq=~ms4w(X_~a}-7kFc1 zQh%L1M*5<{CW&FpzYY($i?dXA7RP7Gjp+h79Njlpibw(^ z2Ufi|t&n{0d)O$|+*T}|;z!OvmvO3J+;VeTp5jiFwE3xFxM(XsqhX1NK|4&<&!N5c{e}&vk1<$cWj=J8;-lYSp&3%?l zmJKPh23|$?o{JP7t!69|>00ds2BO+LI~5ul{88OC53&Yxuysg6(>0ndlg>U}ICW%m zIwcH$IJfsEe=}ST9aDepI)apKvO*0biA{ae4QJVk?-wz=$C7drEc?DPwbH(mQ{x=W zOO76nIs8su4QAEr#yP@S*^hEg)2mhR^OLij^ZmIO8)K9}Yado=)KqX6G-V%7(@pOy zmo735Uzx*o?0(5JDNtGi->dk|FXHO{yI;iYUi|2&6~)2S6$HgL>A^T1o>OffvIdsG zqRK0KOhEQO`u!(=Jc1{JKQiu4QF+{iy3IIAq!bSYM z{?i9;J@X=t+Y+w^+ttk`mgyaK zAeDw|;*oBbY}|W{Q_u_4jatlzVq0GH42d_U^wtpT!Q2h?d~ob>e@px6`PYOp5WaU# z=;$~t+Vg6}ko=Pmk)LYn!2X1HModkH7?gvcLRhp0nkqcu5+Hdjm?bD)Znallt`crS zC{Y!*(qurVNv;7meRLL-E$I3+>AN0Uf(%=HjC|9YMRUm>zD8``11D2{OVX8Q>igOm5~4LFD*Ph1@x-{@cD^9f zKFOpkTQ-S~Wsh=vV=-D{ZZO%fQCavz>Ru?u4#qd4S=CazX}&q7;<#Fu@@KTno}sMU z`f7Ag%B6hGilIV5HxnTxki2MNdw)HUruw*o!X|&r}u`l_V?^a8}Fl+2Q#H9&LmS zA(M&L!XR4w{@SS=WS7Q;V9;gaR>Nh#mRYFj$9;B%L|8jgF6Ir4Yb7Ody`_YW#x84Z^` zv`@_mkBaQZ=_1a@79>WC zBj6-LXu2zmuyyt3dWVLxx=?#@;93fK!eVtAMA2bX5XQ7 zL!=}nza5$+Tfc9RBUiXLUATBq1nst&I;}$~&sdb;WPMxvgmvQEq#mXrAT*d3{vtH^ zomCpmXx+qPzx%4vx!Zh+2UoT&c72|&ePM!&gJoE{vL?Q8{1S@whb2d&WOD)TGD5ZK zWDE+Sr~=>rQd#?^?bkshLKg(*kWLq5pJAE^mIn07{u?L%DL?@pAv=zdCKf=c*Kpn- z2kmcw!&hNC9>NR%=?VPm(V+bJ>x;X=1gxtdHl6oD(ysbnQ38%Wox4wPpRKBa7PdcN z0-h>`K1f*mtH_&~gIt$?j8@y)5^gu_J|i zwODf4an_de>4xsL=8}KkMl?-Wckua<2h!inYw)#eJZTlwtosL-iBf|T>@Ut2H`EV* zb-q+)>|M=FI6~%_;uI`<)0)VZirXn|v<@5Jsn>VLQ2Y}EB2KMhFrZms&kDFmo;ajV zo_#()YwW(0)$*swr{3NXAZ&ow*Hd90kSTtoeU?PKN#=6SDLTA+D!~ndDJJas*5pOQ zKYbYdY%p~by(qq%kS)HoXFPPl<~&q0*C)K_0pju2YA{XRRUN{;$hXZ!vPM9udbsmRJZzaRYfdLDW!DH)@fm9iI7X>^kKdBPP`R;d*4T9PLbY{!8(KI_b7tX zHq)g`z8~j(h+~#sP~eGWieP_LX?5Ay_{BNP+r_z3e+Zq()i{Eo#L0OQf5;p{N=?Br z7P@!@4fzsKu9J}qJ)cz$5<-_0H%4l`-xlsC$J$>r^f=5X(kJB_(QKfJ_j(Pj;BCu3 zbK#6=%oATOcM`syrPBKC(mH5j{&#)j zF5P#a+uG3JXmFf2JUUqftd?V0ZF4LybY-ScMo_2(6+(h1N!%n?EsFEvGNwd)TkE z=%>e3C=Cd&4}wEGlEBxS@KA0*7tPFY9GU)k}!( z#$M1zOIap$)P+4L!q-%AW=LtU3EbP;$>r6*+?327&m%bFTCnVwY&Uy$)a*2MQV`o- zwj9V4?mL>Mqr`fZj;07W61KFHF*x-8x202Gz~`qX-eRU8EDQk$o6O}GNn(Qz@`&!| zaG6Dx{)`s%l2beO3;~^9&>Iaoq%*tKBo8`mMABcZ5QRP<9q_bNOK9aTh{7~{`x;*D zg|vS}*QrJN(><%nAfZ-hmeQ9~rkj9(16Pqe176JUT>yVK)cgs)U%Yqy&Ozi) z9|&k5_!p!A(tYx8Z-J*u_0L_MBqN7eA0qxF-v38M!e0pd??E4D_&?Tt{_?YA|E+$Y zh|Z;SD8#((C>!a50@VjuR=-LDK>Yw_^8K~nU=8V~3qgLsSG7>Rfwb?`^KvIf)vO}B z0`N9Cx{fi;kbm0?x*ygz_m}qce^o>vX&aYw+zfQ3NW#N;s5h#5os4f`J}5O{T-gai zUi`TP9EHheet#ij{2#yE|3o?b;Rr%@EKH^SX3bi>_#FKo#;QNuQ{PYc0Lp>%A8{Hy zSu4`l$;1D6Dd1`RY48H$V3@-Dw|5^$1E1lo3QFLj6 z)a(5xuRl+mU4m>akSP6wgVTXi8yVaKX}_QFK1CpYg3|0B5DVl3Sct&cl;I6M0C{jd zUx^{)btf#H6a&udY5*y#KAUp^Oa<(VbGV|=3CmDs((hFTt|u@hX_PT{D_LLeUmYEboW63O$A>a9_|C9ypmPN|+qg4QD&)IeK8qXf0O+X{!Z z02;R^-KamZB7s(p(z$YYI6XbNX0+a3=K^*(?*IRy)U`nA=)@!+^o-Jgo>8POJHNbW zW^ z?E;RO+WZg?B73h`c_fD0HPy4~QCF24py#{%2HtOJ380Yxa!*^fLW|$7GiWoAVwMY@ z&9>UkOTbo5(p!}?!$a#n!}x5;Nd)4^x0!R38G6L+dXwLUZ1eu)&i!Q|6t@1U-ZtzHZ>`*8PTz{k5^hXP55OxN!)hj~3uJKH$A)YbC2BXV1Wsb}}n zDcLD`xv%=H0mu^7XEV0D)tnBydLSxW2gWv_@BMW6>DAas;Jo={M!sEf>;2FEW`1gg zSeCiBA8HouYg&z~%)>meReS4Bou0jn!^j9`eW-T~?TjSN*M=b(tZ2>UPvBip>f4?iEjIZSF+H_!n5?x1lo>*(Ah`H@acSm zA`hR#VOD>ID#NPiq&twg^Rb>U!x$7HBM)W!lM1J<89n(@ z#%0N|&buuoEZ6V_sq&`vm-1W5T`PvfN~xh2v-alL-|}w)VuHm2uO@b6 z{Kk(#RdMW9>(UDoiV%jPouXh?930ypX-T}H%u>8FE}M*bwb35xWz=(8tNDVhN@ldg z^`lA~YY5BW%8KsSA0$#2<>Eb4DpX8}wNPN$_ix_c`l7F8NEFEOiQy=hG>-*rKh&Si zDd1ZWWf_h_7%g3u-aEFmU#ABocW?J%$iB&ckL8!mTi&8Euy0omZS ze%E6#BO|BXI1sYrglzw)*($jCO{e&^`4kf{stjzM90T_Xkm=6NOjo+1exo0J`_ben z^8S5|85Gc>R)P1vUF$VyzU&5B%@?$^1sX!~I`3GCaw`(pt(qmk?{NMq@Xj5%byxM) zdOv~MEpXb>RUx1-RGQ>kU-38>{i5tF`8B+*y?H7LM1l!ft9a^hXD z-TvgE4*yMTj>;UiRc-ELvq?+sX}(v+lM)RovLAa<-8idsd16+Um-Jf+xs1tP^@}Vj zbMl%|r3>5>4>s&NsdPkh7%g_Ljk`&?lh|!j@`FEaeWc`&q4?x;)DCXf_pkObG5(sT zDoT~ZiyKba=y9ej*4wQPojODwFHT1tJg3ScCmdG6MUAJ5G*7@0AN zg&DzhMj(SjoxZ*Q~{dLo`jb zdHN6EOC?y^rrA^0bb4tCvXvz+${jLURTq|4a6pzLEN*Sl%qJ3vkq-&dDVT~*3t}&1 z@rXy1TPj*uAjIX7;aiK-n$$`=w9e%(c|+0chQh4In&>Xg68r6oO?;z1iBXO_*g;uJ zu?-ML6mYMk9xhx%hD7Q~z3daN)6DtV9|as0L?y*be!<6tl!2_V#Z&6X#)|HFo;617 z@p^_W#INwGB^1m`!(8W@K1isfFquM>*c`jA&Ks3v-}{LOw&O69#4cMNj6v{FCz6Z| zcW4RPBTNyouHn2<+8>(K?eZqISATc|+<`j(yU#g8j=pxoB`0A~JHE5}#)B6!4$3tT z3N^Mu+%^i+2}L2`$8^S+zBe9x{UPJT^ou@S!OJ1XToflKry19yUS#qLS?H!%UeNTT z;n=)9npeXROz`&!Sn_7Hqws@KBRk#7e*$)ZerE(ZwNlXs;E5P2(H9j8dcr3mfpM*~ zvoi>gZHjf+5$6x0wpHlBVqFS5rmwb$ApH;B;-S zWnw+Tk!DPmO4dE7Nq0*}y-QKah+s5x`}YngqF-W(D89fd9$fk4UkVkAtHS?M&l!1g z#FC;Px5a`rR?B#eD%dBiV5eiMXf)y53hCBbzSn7i<2!r#ENr7E*;dr8oX^`)2qo=@ zp4Y$x-b5OCFJ(7SQu}vG#J^Q^ee`+!^#fT{rtp~RG zFZQ*tpHa-4$LEKA+7&-)e7r{@?PHn%uCYViZZg8FGzRL69TgY|em8&CgP_@?de#sH ztj`MJj-3!jo22E(Y^G`~n_gc>X1g(e3V#}ZojKeIV*R&o-_}AtpbK;oEdX#E0Wc4D z?%z){><3v$c6S&XIQK2E<7{nhMcM*b=UpR#_K(c^@tiMX0R{|62cc*Ik*&;V@FQ@> z1%luo5_S*HRMtzA@E8rOK<<10JC>x?to`_4rKKh~LgwZ{z-)U~rwCXcnAxmJ^A+#? z+-=s$T&pj+flf6N5b*KQy#3wxR2rEqC};`~Z2beZWY2k1-z<5@7U~dzW#oE;GfVrp znVd<_iw77@Nu+7l7(P4WD;V4(oPL!U$_4)?~w^?I+zH36j&MJnM?NE7cOqqp}#vSu|ntxWE^D zxx=j`N-bQp)Yb~IJa5ohPe)7kV(U*2CqmsFDEjF?Cvp}1s6}VVenGufs!rXGJN}Bg z;DQA)y>!Lhy}#F#()IdH(Lu9=63cv!6$Ji-yOR|uBz zu@z(9V5meuiKn0nmWU?tJ{>ns6v_x?-UQ&(_JtaQhkp#9VBDe7g?N3hSj%aJ@H%GXZrf zSkgJL^<(Rzs_eR5P50u~piqk!LETaTuZoOaYrovMbHylwwioLvX5;0R?wBcP+3`rz z=R7y=9%YWcqM0K$XPV)LMKBZ}Ptjq0bp>1h*&oC;rFya_hOqrg2AHtSV@IttV(k5$ zwoO)s6$eUKQe)J@Za(u2caMwhL7sj&l%NYr9#@nm111&^!9W~juPopwFI1o9QGp^G zvFQr)JD8Z1OiX1%W%(-Qq|csx@d;NDmzI8r$qRc8>TPPb>p}cev%(DM5Ov29dtT^t z4L?a^llPS&KfHp|%J};cxRzb$EH58FcJWoar5=k{Ff;L99T-~gDdyK1e++(~-(QDX zgz$_Lzd{p4Dg)lC*28B3VwB0;$ZLYi- zWKDKb1npx`%-LNvIVA}?RV{YKNoZe86vGC#Bzr@ZMp);W%Uy;V!=p>h zptG|VE#;l_UHeUuED>Ejw>Ls0S4sSI)pH=P>EQk`N5Wqe_{P zheED?cQg&p9w0UZ0*1|vfedj1$nMNWDIC1g4Za7c>%t*~U%-oE>dU6O4Z{<7+&Iq9 z&v^>LDAbJZ)A8)#%3O+0p~|6HZ|9>wA(JsAx-YM zmV)|U#p=Whr6?j833*oDp?qhCyLG)4Up5b=bbV);qW@6fGNP87_*zV_5PYuX?fvRB zR<(3eS1Xdk3QhQQBR&RYngK_3L3m}2;&mDVDr^a5cZ!xydvv$GNTbnr3t~QJ-3=2~ zf%oNOk0RqD@FghLEcL6l-DUeYjj^|S8L_R@$;$iX=3?HzcNoZ#j^hfEx22f9Oj0we z671b;!zo?S3O>vvq^@0^^Y-dh;KKg zxLhoMz1E6D+_xQvOqtEy6*L%Gm#LV70#4r*~?B^2D(IEvK7i^IHKARi|k?(c@jzLyYfq@2277_tb@=Nm_Q9BNz zrluyI!b2bN=(RO&9HFzp!D7K{=%kN{pO}+^aRIa5!~WX7_Zn0HR}NNbS9-&V%8xBF zpJgOB&$2!lFxHxWwkMUZ6&WBTZSs|WRyz#_+W8&aRcE=Wl

TPyAOrR@F$!Hh)Ol?4e#FP&-Lh6 zjM5s&zRgmt$xOuj!}0)LGTz)V$HAfY0_!Z)CdU7YvhF~F0O}OCJ}xa<2*Lll^>T)J zMxCNUQ-vak3SThCzfOt*|LqH=fIQ_msf3_g4gktZd3Kf6W)OUPcLd+f%wM(uac#;&&J7IwIfr{5`3b}D7U)AQ zhOjy<KZm@NX?O1^J^mA3&-x=j4KuuRt3haQXlXm$((DBjw)~N_Gi3!ZJm}p@xq&K zTt(_JHlNU0F3ZtGin~MOcKJYMy-%_^)7$@#wYQFos$2htQAAWkR79jz1O%kJK}wL2 zZjkPdp-};m?k*|mZWuu6?v9~5h8~({&3)_ro^zh_{NDHde4f9=i9IuG@4eQ#u5bBJ zPBX{{OQq?YKZ4{TX1*Jm@mZ>jSM`Zck>9w#o}Qs(2LhLb^Q*%-3Ea1CXn~z z2>eeO@B=}$^%X3y1NCk$D9C0;f)oW}214TP?Tz%UV=*0l`1I-RDjyzNl@hOptD{0> z^Wku7B798KC6MoOT{_9lerr5b%i}TlfC1%Q z(tu}l+^&dAxSw0WC(*AtcbOe=x5UaG8NFF?qN0dc5zPFg=sJ z3NEN#RMIThp}@65^wbU?2N6K8Gn~sFs63Nxj*1{;sWROOGM!{T#>%yiq``G)Xvi&6^7$;#Y*kir#QeRfcr@q7A(@|5Eer*7)?N@pbb z>NI|NqD~912p>#zEgtP&gY951baPW2D8`BPS!dp5$X){%+A0&|oHuvf6aJnfR+WoF z@9MC2%B5TC`>*a8UQUF2X@YB6UUTVe(ML2~7&mX?%Ezk>S&OZ-#nyUG#)AaceK|_w z2^jMxL~Y=9R+UTERU>K=k?WzGSfGpUB?D}dwh3iB4vk(rrjn4Ge((~pk*GMjl{dj~ z`qG1{31t(aGGGianrW*Sn&>1nG}xBkEbA%|F@gMPehh9$FvsY#)>^$Zyl4z!d{aBV zbgque5R1K8(dC@ZfM;*jy*n&dM(pn>>5np{aPNy)X!ywJmnLHz)H-H%cjs=>=WI1) z3aX^|f1d1;)ut;V;X!Z`&|=qM8VttYM$N4g9Hrm%3~ z*brcnbge|crlz9{1{9MI4eoAWr2soY9nkSmDwoD%rTkmZTE%+Ok#-Yo8M{H^MhCEo zS|7>91xXyVq#^;&85lx=>15ZSTE5~}ED|Ys`6sh(2qMsAS?Z2uQi%Jx3$~xwzZJ{5 zNE-72$XAR-CvkoF3F(Wc({gX6C%z3-ryeS2AVwxMJiH0q^8-fH;a)7}lZQD7>ZU)< z`0Il=PchKY(0J+mm-h|lmGcz=?Z2r=yNSE&iLf?c)0jF0{yh=}nD!?Lm7sKb`1tX{K^%i_tNsfEef@bW_HRK!$123& zjn2-_)g+sM@8}BV7k0u2iUsN&NT)WW{|az!i_GmL{%43zlG)tO?2xW3$@&UzU-u%} z6Qw{O=>&WgncNY(&Cx($G7ED(kkoYDYoW3f#kc%DB&LEyQp%}A>p8>9{@=dw=PQPX zhR&CAlahMI#KhQ)WotF?f@;59bz5Z=?ED6YhKg15jmjr&#;D(amHeYt$1yHf1-hqJ z;6cdU1?EG5ReYCD=3Oor0+owY0{iEob+?d9&biZw4eT8My_u5UfSp_m4%hXYxziwJ91p_|Z)@Bd=Vf$watk+rt+`D~;H4oA{pF#+4>`l%9s&j2cLOM6&zixGZgvmt? zZPKOsGdlMjKBtSpOZ=p>tSaPeg` zIQ-*P;6)Ph=l3_43+y=MMl1#Wb}cx$@z3=RUZwpfvfI>CLRpq_-Rbvjd57;g&p(%= z=S#Quk)hMSJqEy2e=ZfTT~tOh*}su5Ye}mPFS5w6Kc5Sp`ya>sm@gfy*ig`bO}Yl` zVo=cJmOB2PTO!_P3{P~Cv=?=7G6Pq0a0OaT>@T(j4*}7R>g+5~GSJ6Ll-JK};7@5u zUrTWUatDRnHt3*w9aQ&I{65ZxEn4kg`;BpJT(3d|W@wvTMmxVG-zy-rluo07E!`*3DtNsl zpVLDC_dGHh>Slu_Ln4djGQZ%raap?xieUM^>VNVxrTOiZrN!gy^{9J85F?`IL|xsg zf>_^g&Z<`&2hY?TRyCputWkM9k{-Tqs}RV-!7-G5@3g*+ozPd{{%dWD_LD#&>K(?M zcU=zqmj(nKtJJg&MDe+J6LNyeA%1zTxYQMDV(gnzg|F#zGQW-nj(DNxzAmp}Pg>Ah zb|63_D==wul&QO#F}@mp^|q!$boRO5OeK$aYcK(omLb3NWUp(|&x$c^DXGQg0F`vt zt2*g8@^Fg&iw-f+(4k}x`8iK;-zO-H+#HC2WQZ)Y8LxO>~Ji)}K)hdcMHeEnV|&NwB=p==&=vL~sM2Md05RAP}# zQ+Q1UA*Q<;5pcKe(Lq}q;{~J1atlu(0XdqMqn(?+PfbLQhMhNjm#6YxCD^ZSwm7Fs zhNEnt<8NcFW20Ph8a*3aehXERin1uNst7}(IZQc~LCykHj0cHtW=)pY z@ZbzT1Z`O^Cryo>WVEI$0Y1^=UVR14iUN`A2l!v@j=(-4+`AMnvUy6jXU%_ah2u0^ z0!pNowLYaOXqJu-T5s`M(IKk-duOKI3zG{ZlHJ!jz_jZX4NcGLNS;dRtiD!gXy~)R z)>-{2rOmIJoVOuEdn0j=VJE2%b9-7qJLU2B0>?xP& z`5KrB$0TiE;tC&Z+4-fqd_mMS)b|+=aV2{Agr8O0&P1eQz$tYq*jfjeT-p>vLkW&XHHKK{Czx z{}W!joG81|Pybf?l9&MQYH08apIRn`ikL8i#=}!d%$!ly>UpT(kY0F|*z;G!E>)C9h6?$myLfk74^%Up_%3*XmG@GMTO`uUvVGMaEi? z&07nLJ*IR}N`!WrODIrA$^A^^5tYSep~0*eg{|Van1r>>7(Yws3mCKZ=iRw)C?)$E zZx>(3Y7f4H5PN{|Zc)C8(W_rd-mz>ts5z}p$%0DYAzsdI<^axTaE$M>~dQ)pew* z2rpx_4XypP-;T3T=i!yK?PK1pF5mb|?g4q=UZ4`e_l3jiSqe>$KoxbD^gYEku%BgM zVBjshK5w{A0}U5oSFWS0>jdn%D5>_7y8Dv(lKcBVMA2zUsjCx;q=f>5=ftqE$6yiS z2mQ~x7#O;fWyb7;FjBxT3XjHT)Vl+qk|UL<*jT_{*KhjTS=g`C*1zMdXwFo6?G-pI zfu2l5N6!2q#g*9&1#;yLi1)_*E`&Z42FZfiCZ-j-dO0o|LYeA!rb2q#vY=j2*E zINgeuuh{C$r|(JUA}A*14GwM)UlEeMYmE1_V!MO1@TcZHrxIh4911|1CnDFLla957 zY2}Zb(K?sWHt4&$wV^!jTm!w6 z8mvKNV+%Mw)GbpL7mnx-qajwUM3y3Cdj+S73rAxyn_l7y5IV5`t27NseGLW7B*5T^ zLBn{u3u-lFg7;ZEB_-uNP$K9KqzdP0*2MuPugzwDWr@wQII>j2)pGp>x;7^u+9ju~ z&xhFgTVeg#J^vOL#a$3tFj%AwB(8X}xyf`dgu7xTs@HR2_PqAf5kvB0?S+p(#b2 z;akRP`udpzKm7{fQSGG(H66j!*`;1_2on-kt+C zO(=cDQ$$YAW&Bvf8u3*VLn_*TP}S&}R(?M$vE$4szOSU)KK}0J3?53Ph~T?12R-xg z4aqs1(4zyzw=R(E$Y-gf%)=OWKYDzDxPJ7V=qMgCScp^Tx0expf`&gV2c}EFw2xd# zl@U6nKm}90RL1!azF6@8^ve4hV;_X2Qv6-MW;vZ5qmT#6V~=GWOVM6r(<)K}8V6gj zM%4j3Ysm$-@e`+0h|PY2|2T$I-c3~&*-(wSg?eq1Bs`Lz$)efDL}~}ziq!qDW#=9J z5D@sypbT~ZuUhk1zsWG;ng4E#c64u8lP5*-yG+Ew5Q^1}HaS9OU&@9g6a2LLyk8-X z6$^bz@l<{YyN{=iXRnR3juNg8Mub!1wv368ywIOHYj~~CUvH)dtlH`4&R=@6Ea%1ok-tfCN;L0~zmeZ{L6R69jB(fB)+x{LK9KCYTdZDg(p(rsc z<$T3Ro4&PTLIHazy1bX8uoT^~c%g&-LI7r8LGoI^H;h~J`i;+W1I|!o_-7wWjC>iW zcFNAEmPI|hPNMphwa;bb5q{n;qYt)Yl1CHee8H=l@AVFP)vu10?Cs33<@3$s4tGkF z}#F#V6=+)EKNeIjI%kuu@L?|O-*JMgY7c)-&7$4Rr(~_A zB7BLP1!?feep%|m@ktC$Y%^Mz*w|r9TR;Ah;>AQuBI*pHVdOTL=K?utFLqp`aU*NE zog7s1oN3P!pT_RFQs5p`dAN9EXVcazTdo?F_;aCWgR8!jyIxsZ{kWDc{{%v!Cody! z<5c%p?+u?8D){mcu)!v8@^&;;F2spqrhRe@dh3IO-o1^aGThw{G7) zd&A{%jVFVp968Txk^({&~|En&BWL0$V8$1?d!$RE*NN84z)DU7##mQ_C<$@#1?2s- zztjOe+sH*`-~kaP69A&}fP!!D$H2+4NS1t#O*BWMLUP1>iVtxrASXxklpUyuD9da~gE(Q(>v;tE?)D)~T@2dnDC#uv$ZXe}^L-4GdJaWslo z;EE>f^;dFm8>4hVQ_l2m+qu(dX3yYa{75MjjrjaAO#)Q!Yl}Y{+~*b*Z=K37a>V_x zWy&|!3syC>o9p*jDVJ~+TxG2oTk2-loHwZ0V8>+2?6C{mXagV!pp77F#Z2`y+6d!) z0y`n?+fH>JEQah3x;%Dlx>f=l&7;<-QJ!i-o_QYYVWa8u`xpZu;j4jkZ-kmUm`0Kn z=^B0p&Fm~m_`#RYN>{~=NtEi6Ds@V0-$d2@;%?8%v1+Ysv~ixe*;SpI^V(|GibnhM zy;2Y6F|k5|DwhenfqEXJnzcJ-r{3&6PxDl&*|#0+Wajk;y>!J8+r_y#iRgasB*gbG zJgjBI`sYw=Frdp+%&)&I8hp)@BztPbsSz!ipgpJsle3cvow%%bnTt^S4y(IZU?q|Q zJB@n%SJVv)+Fz6wg6;Q&aSzhWqz%3cEO(T4>9E+&LqI+J-mNk=7UD$AR-g@EX>ndC znXQ}OpS=_YG>w~q(PPx!Wc7HE;`ygf({)C%%H^b=L~DMl{CcDsB9mPnOGmxvTbXcC z^K=pIIzUA|{vyp|*P|Uo5m|92B4fdk-YkG}YP~aE&8Ig@#A)~41+nA0-$CIDf+a52 zr9E<(FF|9rqpuI)B$>>6Sz`B;T5pAer?Bh|;uSEeb1WoUEAP(}K*{WloPGEgJl$kS zgwtP>{Z%enqPB3XaS?KB-m2=vNKB^O@II58Mna#pqvk3j(Gm`)kxR#uQ|Cm#r-94~ z5|j;)=J`+Qwhqbm@>E7s>YK*95t-HjwU3gNT>IHI-ppuOo4VTq<0rY@H7l!5R4KlGoA1}QW^ ze(qR>I_AWT->x?t3Dh~%(^Du^>YDc&23$0jeZ^#|@A`t?OgIt<*S{fcpR;n4B^Ui` zohBMadF@{571hLu1(W6f6I8ywDEVFX5pNZi(-cC%G#PAk)?-=ws5yGXrRo!dtYJwn zJvCDln0S0Msf`|uJj%rGU9K`BUUUf?;T91VS3IRq>4>F`i{~j{GabsN^=v*kxCWBZXI5?YclZU8*h=(Xj{^ zQBEugU9Iz85fZbrb@!?YLgSd$BZsjAJBP80O~Poim1tR~U%s8jbu`IMvSNR+3=LN- zUT#slijI!h`L4jRr+9d3GSuQo*F!hreMzD47;ax&zt`H5BPM>X`(p&r7PA?E>_{3z zHFQ-g%zS$c7B3OAtH{p#UJGt_63;o-)HRaBhI9$)T3!Iz-}%h>QkkUe?BlBnu%eEA zvvG3+c`Y6yH4~$UDfHF>zR;Hxdu`A_FN&S}dLNYF$D?q@p@#4v*mild7xgqx<2OZA zHLM!x#v|1j2g8S|n6C9Xw>+hUi#jfI0%sQ|x5)yCKBn3x1c}JpxL6+jXoEqtCAmw? zlU&Cak-}3K{dLTY+TbG_>LurTHc86L6@$PUGnM<)YP~!m-j9_ZH^}3Lv7Wz_PXR}0 zn8ufQ8x|Q6u+jH*4F0Q)Xy!EjO zA~-7B?X;ns6Z67zJq{{~9!XS5=6n)^-N6z7ST=ATGtaD`s_Tszc6;DvSsF2gu*ya;eW`@C3-*cvBp>?By=6CW{l{acmGVN|3 zWw))p2xa~@YJKqS^_d;UVp}Zn4Zh*ls%C!QRV&9vx$zMLY@X9^?J?TN}Y7E$i3ua53AnnZ9p{cIcS! zTJN8uJ;vAb4R`4A-f0$Z?H@5D+*K5PTN#27fk>LNbk?p8YAWO(JzaATQdcL%sSO%|`Ns2&w5ZYbEIzC%uKdD^a-3+j+LnJge1FrXi8;->d4h*~M)ZU8a({f%Z`EP%(!KOYIIL zj?LyAKN8SCV;p0Gw$ED)R8&V1I1>yQE9k9qjk^su2FIK5dY^Xow1C79a@dnCr+0{M zIvck|OpNFKc4APU?pp*nt(bQK!#6Ni%W<)sOTElAMOTOf8xRQ+Zlc!)#hmVq#kJM0 zwK0RPAI0@_1ivl{IyOe^)fs~sD_r5|_JH%-FHj0DYZ?jYWglzOHA&qpPdB8eF!sW5 z)EEWyUzTU2!>i6$Zc8MNdo9^!TxSL>_1IOaV4dxn_##JxA(3#MD-#URY!G@uj3Pz-x0~;;IJ3e-BzRq3(l15d7$Ki3xHLU0$?lKKqhaPXH&%kB<@`;&)x!>woSi&&0)a3(Akl)24il{cy~bthQK z*4o1yc*8Q=VB{N5)YoE|+gV7FR6kUibYi4p9JuLwg6(h<6Bs@h zi3tOZ00&>BGr8Mcj2dnj-Dn)%%+yR)SGO&rWk&2Fp=F#y&&?S6ZWr3UpYIT}xe!&A z(ozG&;SQHY8?Zyp86(@faukCuFTqz$dji(CEuQPIaKzR&f(*Aj(D9>T9KhWmAEgIXk5m9Cxyb-f(@3rF=ax z`!n}m{dM!jj_wsMygbJWu>oic9}uDT74RH@GTx{n;R#7h?3um3f;b~~G`7F~4%Qx7 z-Vb-_+wcQmC`yId#M{d=P&}KCkvIn@{tbbqnxwBvqR<29G`(B-za@RN|A3+Z{M8oA zcm?^5`!-^|>-&?~9XI!u{7rVi;UB&Lz)xF$Klk?J#y@~}6?v6jW0<(u&TmQJzk{*P zFee0rkK+xlRs8Hr%K$KbTxlT=5ZVO=xdfH=qR1;D{QcLlPvO>(h1xfRZq%kKIz zA9=1FXf_Z2My9D;3{9Ss6y$8aF6fPrp+DNbKpu+MkQ?D{x5{-mA%D~L>972;#3B;x!B>IbLhA8NqGr+<#7jtxe?^ZzjVWY|&i z|8|6bIk{o=8UJ?D{-<-hm>-mpnTZVWDgkU2SvfgiU4|@jk=`vJsQbw$xAWt@Nz+1P zyx#u70nmTy_kS1QKImowvY}2x7r>JF2rf*s+4@9c9_Qf}(VUXvF@mc4@CTk!EgkY) zTKSYKt_7uo_P6av7@*Nf55wOAxXynRCp=;WCcbjm4N&48;(z;~hO zH?fct8DmNGxc$2Ya8C7JG|YcNCfmEi z6dD0~eU-VOQMUaM!`+`EH!DJsVV;|>f`mvX4K!Xpn9O^Yb4^$+F`tqdZ1~*X+X{56 z<}J93QaTFPIqq|D9W};()QKexQ%Ga)`U{qS-?=wt`o2Ip2;E`8T9A(D7jEa?!Vwwo zvZI+tT_s_3%{M-S<+fRI1~pS+xEDba9*plvxWJ2fc}jqbJ*OE`)IO`A!JOuV64MZD zX5-@jG%b~zC~jz{kc9Vs4uJATJPka$g`VTIF!D+&Q#pr7_x}QtJrY#PjhMmjY5#mg zj|W(`n%(HhnKra(3v>l;)Yz55LFxL~sPo$Rn(lPI<}TD%G?H%LU+CWUVOq_#eWMny zkfw}fuF-y_wJNI`BkXuNdRTi37h>5_wwO#fT-?$;Cyvebq3q-lO)efm0;SxooBBW{YKr+63DMj>$wT61U&5*@xi7(l# ztC*@P)q`5kGfaG&p(-vs=B3-xan`!GBWrgqJ)FJNEOMPR1`0jDzR+O)3(>YIu><(> zDs=$~z(W5MoQBMNe@$N#9mOgM2m;hG`Lsb~z;3cfT)=vpaPj!MBBYM5FC(2k{M+q( zJjW@%Z^p9jvF%b^y~hf0Yu;0O@9J!Ik1o5K`*F(i6_CQ~nEbBU)Pqmwc=S8os=kO+ z1~>ad^TL+zO4d{(zZNhv^i~u!v9Q+C^^G7zzsPa2V;|ICwsgnZ!S@*WF&A%dtUt|s z!JogdhR5a479p!FdjKUKl9q0GpbA(XnY|M#Wd-;497Y-Qd|=pcHUe?Cg>66rMzE^t zqzyl_qe^n;OCD6^L_8XMipQ$r146FWM)L{yt}mDXnVK9Oi&ziPr|%PU#{ec6N|EcS z4Olw@TXeL65QmV*IRe-YhJkEvq!{+Z3=Zf?$V69QSj}h&gVvn9Q(#SvPI@t8_eNc= zdovmLV{tXIRJ^g_H?|H_?b;R$$QxJh%uQYnw}JJRae3ZhtSRjGx=rPEi|Wm3hFA2; z3X_LE!*-l$l}ALjq7L!QZ1b+B2*BNbc99tB7S}kQUC}c~ssr;c&Au5@&l7FkM|8ct zFF9seZ1xJ`RQh5mVoCNqU$16hk!R zRV|$3XMT|$MA_07hQwljJ!lGt>@DP@`rbRfEKn2jF4jJ~Od7lJu`G~D(4Xml-!^B# z2_%G#1X@pY%Bvl>f_{p3SyztYgUHN}r%#y*d+446@hfP$LDLCyX(JY8HItNne!&5^ z^jci>qBYyFZucC$fm`G+rfUxWiG?MtA^eoPStnGPnwcRHCfdEJ0e(Y9I6+BomJjq} zS%Mz%|KEVoPX=}-In{k@#6M#!E0g}Va8z=usyOoY zZ8%D12`c1{XS?h+Om=N1!X{@tsFOCD%tNEQUc}qqx9O53dG@5)90F_GWa3*$#9C$4 zJ9*9PxN3jAJ+UsvgzzWhEu@s@_7TrWh0NYy397X1La|sc)bF9Cwxpq*SFZ^7v1EK` z^tyqY`M-nSkjq@mPa>iBHXSA$O|9=H=QCsD;Znl`V(b2m*Y{FhK^4!d$%8QOZh+&2-{~+N_ zaYtM27m5TDb(i<{T8*Evwg2oiH_*IJ4FRHSkofkpf9)?2zTKF>)FH-{P*=k?JA%{Y z6!rSse#3BDFs~nQJzMQfoOYNp2Wz9B!}jFfQn+-9+qr|dxVYo)FLXQ}XJ+6JL<&q5 z(g47NOb`dma7M#k!sKl?kb8?v)RIWzjxB7siW`(g_`(6H5rl2NdiClg-D5Qo0(_#q zSFb^`awy2LeNd;_2PC^HMIUcaMfyRZP}S=#L6XGiNMOIlRBG(FNOh3POZ+;n0 z0aIRPQqMV!8IKVe%~VI@2$`~Ze`VT(Pqr!#R$R53KV!3&>?gcRDlXj`d(2re{C)T> z*2Ono5%)>?=K5P09RRD>jFUDBi7Uvb=Cum?Pq6*d$chfXlBYDMe~++x=+Hq>0U7wg2D{C866f zrr%>J>yDW-OAIl zb(W-29t+YpHDsu*bwZy+q#Fy!mVX5MZSyA+BxmTaGQ0*cpYYav^nTkVY-UqFXzO0& zY9_ov|D>JaJ`u0qc&nt7<3{+}p|iVYZOQcEHkU&RWOmbdxauy$5rNHOPvua$3Pup| z-f_j(5e$UW_GEqRF;VS9xdws2MWX+%NWQ)|`AG`@aWChIesbVJHLcKuvJGyPHK_fU!@+nxpyl#(PJg>A|G%SPLqMN(Sh&W2T{~F-oi;|y2%GF7SJrKw> zc)hY}G-7|>#J;7?A~z$3MT@&BgiA}n@J_aMfs&3B%CUogZ4j=+Q7$Nhzl>_wM z3(k)3*l5(SR6tmRh;vZ5@aFr!l+N%gLT8#o<3j!aB0r`!)>j~d6>utAvf0kPg<>c^ z#eSS6j}PzP0XFbuC6^(Qhh`N1qmer0^S-!q(REKpx62$wtiN4r0%aj72L}fd{ReC8 zM@9{IVIF4Y2q3};iHvM1?c-J3VSOto$m3C~PRo0~#e}qKSFN;=1PstqzzaYz8p**y z>h!^i%)3daUKIjVa41%1hsMZ6b&G1C38H3k&i&flwH-%=v|TDs9VOnke$i%$91Ul7nvZI@087wyv@tkoy& zV-%Jds1+uCkU-N=xjL36W@kp&6F|bobTWb#-~wStwwU&BTIbqYl2GJrGH~r(1L+@b zd(MOVCa^T8&`QE7o~~}i>E)_lIGuZVa8BB}HJq;EoYrM_&bNYfAt=Wb5sp!jF^Pm+ z=Hvw`+pH$nM*m+_(mS%$49!9&*|<5{vyUuEE7OO?7CIiQR%WRbW{aaqUuQ7P=65b_ zRc~O4*0pO_hQ&I^e5E;eMx?xEt|`F6Gh8r*Ue0=gUi*@-5U0b=ipr1I_lUS4qzv=z zIAf4%b;576P1O;4lNE4zi#X^s;qlgFZ$E*^7`tZq&A`+rL1Zq{>3_7=e5aQ9X~$w% zA&#R0;W2*FBllHtq@r_Mn-&Qjs8{74U{7^cN;Fq&yjLBp$2WIbgwPF@ZS&)|9o5+^ zA^?H4e;yZEM z{=Be75wo&5FUCFcg!~g_(yQ8zN=;ED?Y(O`)qZmn=P!jde}*xwD!_}$$jAboG2Hy* z0#-j zj3{a4U-{(mTYW$0m;bQklB)4x>s7P-)kqV6+P(5r0LfQfebJ#{m|w0Wl(>zfd$xW` zQ@=vN^#WI?myQbCHnizClR#D2J+?1aYwNpvI>Kb)7&Sw0nX8@J>M;TKPogHzZ@zct zE`^=0vG-P@VyxLUywJ~BpEsgnCiK4Xh^OT6PT;Z+8b~ZyZ1PRxh)?V@<-7PgGrts? zGIL|?Awf@rC5gn)w-1aM?_&-QEQl{o(4)BB(aAMhlzelkP8uV3N|vjNnuUw9F90GR z)TKs24!yv>`CIipRz&E7R$G~@^bw(wq-2DEt`^!2JW^(Kg80Gg`*vWn-^=^^ zty>>Ck~PRBS$|ZmAlU@p&aL9&;qeXCXbynRz~XKPYBhh7(MUemZIf7kTWb!YXI~oK zq6lu1wsU#ZC?3m9-NV?o=1lbZdiKB;6BCn^<OKH5aixAh5xe?e-aUFHL1V>|{w7XI%3iU%XyVYg=Q^l=URjCKQ z{LL(w7+W|v70cRAh;D>lCfkvhud_&<|<(73CU|@ng(;-J( z&_U9_;%czxo3qh4rBYECRA;t?aU(OrZ{D2NTAzW;_AvEvH+6(l7!RbPL1yf6rTH$I zrz$NoA#m6mFy#S;yEFb*Utiy7Nvpw9!#;6@aj|ldva2a;q7*QVNHQ;0K}GlhV1$%cNGd>#EkI!~6}Op%<)vGS@2Y zah?=-V|5pIA5ek7^{Bg~Pz0CjiAGD)9aDcz3^_}zS747MtyZwZ`}H%=ml*CBtq0c) zeB#;LyH}Z*JJ_ANSj>kP*9%-?4PEZ4tPEBMn2)%R7xrfL&#$-d-zK%JyQW+jlzp%@ z+hv&S{?1OqZ4v^7wjHh7Q&+q9(*qrIuYbX+&N{4Z zSzN;~iFfaisu-LfT^$|s=kNw_i7|jU?miozre9E}14jT-gR`LB9`XW-S0lk}Kv?qw zCvI$wsXK_>|A_yL5og5mVq33YK zD_)WHfeZP8kADcG()wEolYI>82OD~RE-o_j3YPaz)u7S$m^NgnbGpbWI%uiLUS?gy zH<5Y<+{(fk_G24e3DwraiTYT|)gNKI3Mmp04gdBqtTdO6dgU*=MQs_O*0@Ei4WXWV zsExPHR=v$;t<(gJJ@F}V?S~*kr8Gh~_Xi;z*|61X|L`!c+vp)`b2AX55Bz}!U!hNx z8B6+w&tY&-3H&z|{^3T?c$J&hjk^?ef*E)?_z` zj7@k2=uzLlOx(kGub$-V4_%M!8l=9*P5)LJ$R&cKB1fynFn?O5NJJziq^Hvp=vp0h zHlHpvMLg9%IO?`e(x=Vz9G0scZ*Y1cXFx0@Q&2E=JtsyWrf=ZoFPZDB@nP#6#8~iDa>AFIMFF<1&q}tzW+UOG^GzuzDXOy z_lRXrFL<{z9O`_u!JyN8hxcMv(9fT)!6pJEZG${tej%Y-$Xxi&nbsCxAz&@>E=?qG zyupJHNV}89fR}X3#p!`H`!wG%GSH*NAGZ_)#!Dq~wrD_{G6jPC{dEyLGrUu?<)%s* z$=blBb!m0=915gd?kb%AI6x4Yq@)_Wx&o|V!daWwOIQ;tws>*d+>`dWn#DxMv)i**s?{F3pvL$}!H6V3b9?TQ!msE7!n zud_b&O6t7p?QL`Fko;&^vj6QqW7L!t>g(e1cfFKZMFNgw(b2jHJsKoO-~O38#ZrxWnam+ z6t|8UVysVH2BaQv?U!HGZ5~PdHYQMlyC=z(hL;^E_HAx)U~o9Ga#kKmUFi%{H<#0g zS(TjCp%PRq?XU3#F)Sy;loSgB$#NN;v<;5Fvge?d39*`qZUCXe7h0f6!JhK97_6Qw z1}Xu3Od8cz>*wx;hOtBIOZ*qa3#yg*`wr@~xU5sl!4~614rny06{#u*QRR;do9j^_l~~cNXO;0ZrV;)J+q8m z6d5`*N%r?t@MSBoZfV2co0W8iZS;e%({~N-munNH6krF%NW|sPY*ATiF~e!l6W0Qy zg{Ox@(#Vu1wi!EY!0Jo`#ua+{`gxTfH8xlXBo7nYQ4p? z;S5@xG}IV+s&7bM2Odjq#3d!{{0y>0GJE;9RwT5{@<~gy+Jg@!<<{?&5M_gOuIEfL zzsQM61~5KxIhX4W91B8=T`?dC^S+5ZSKgVb;Ja>h4WBC&Ep$I_k`H5Hyej?fr9$A4 zqL}?`q}V~K7lrk2*M@^?sgixd=_SfGSnCcpW#^GS1-*&MH#_(Q!X`D50dJ@gf&S!NV=GMI zO96)Q#rD!S_{_nkVa@&?W-49B>>ZjOf=$XdHX*UP$ZxA%Y)Q;XNNaPjo&H0qp{=ax z2z%nB=RkB(c^LK*35gmGn<%hf9ssoKDWi~A+L zM8at-j~~ywSETmHO1M`bu1Xsdo**AKyz}C9-byK3P@O$Dyn)9vYOKXtBbW8!unD5v zZSeIz3EI!=x+DDg`A5@SdvqvoP7Pkr6!?>p|G420AIMW%d9c}MdfFAyaAsDSo*t7Q z@1egS$U+b(JKE|qG4Nh#u+bI#ew7W^lWMB&*o5PU=Qe8GaZncRpm&N)4bIvQ@3eItZ|#Cy{0gU zl(T{dG$$TkZ{FM*m7P2W79HhUy#AE0;@oxX^j}h3zKyj~rtIx|&b0g*KQXkwo!sc? zv)35H?PQ=^&do;HGaD-@H zL)$vtNHG(7tbh^MM=K>7&Okrlr3R1BFWL@?v_{2z691lFO+A1_XKt9oCD73JLch>E zw9X#*!G$Ekmw-jXzJCHQunvI-A;y6Ifpx3G>iRXQA=C6Z$)Kc<6zUX~Q(x?tKq^2! z4aMEbHhY-zvG}c2O8DbakE8w$!5V4`K!P2HI@uoY%yi`z)_2ND^9ZY|;sfy=&~x`N zUF@yITN;4GO61-U^esMo_`q*w_6DdL<|CCfwSiX@GTTTR$f`@WeZ0Krf%oQ0Z(>&r zgYKPs_jI<#i-FG@TQm=P0qAog73SPW!*Un1*Ow$f=?ro*H9rE%Ee>;HsOI~* zh{n-xC?vcqK7i@WCY5}n_vTNlv~`4hiR4c^7nsH+vABROyzP^03)H>I&2(IM_AaaM z>WY;*cb_;cc;^YCo{Va|ndg#ockWYf5;NYZFn5C^j}w_e zqr~kRX5V@Lj!Id&qGJO^_1dN{z$`N9k%%;h`!xahjqUU;s}lk)kIio3y~mrXA^ zJ>-^X+6HbU;WcYIjYCwoaSfKkH9lP0K<&&QIOqF`QZ#>LtV!-U9z3TU--4mKNTf&2 z@xyWU{vw;CSH55|c71~K?_85%M7q<;3xx04SXZfX*}?|J#GUogBwm90-HTa=m06T` zSFV)kjgt;ewBv_s(xido-LsQF9;;tY-I_F`aGLTrhOY*qfsc?wc{yYl6JUCEZ*zrW;2H9{SHxhNMa;Vx20*PwQ^q_VjPmtHyhT* zdtBn-(w<=vsxCgG!|`a8`YzDYo-~PprRc!8nknl?E1~oFX*yu!c=U;_OVulz8rWF^ z8yh3g^Zc930*M3moez3u^jBkR-9#U{?z&M@$eE62fd(gYMhl0T))8?FS}fQ*HT7V5 zY*1o*R~u*1;`J&fcqA1X!WK?F;B*J$=Uv?R6>A;l!EQ1R2MzH@wRwPcxkGI6^Shii zsYxJeIXI9xw~CR7F+3s?*&>5p6l zK`%Y831P`lm6myIW8_QAO;wT`+~@ehrJ+nLAy`Ty_D_@yJ733~Ik+R)8zkI#jS;a< z$XB|Z*coZ~d`KDAMK4TPgA5ia_#k;AVtw(uCu?cJYXfQM^Yim&6D8hA$3cL6j@m2# z<(9DE;l)k$-3AzU5Vrw~TQHryprG&pUT_B>%QuqihVO6gN-#wr+x#AIeAw;fx?+O< z&04vDg#HI<Q-q4gLWF@0)G@hTkiW8f0SAGa~jZ65E2$vsM3^` zeGH5OGl9nmQbYmvy&4Ju;KR#z)>X*ti5eARIVRd?S5%R-85i@gpa%C3@<=)rFnw9) zJ03$4Ygn(D`wRDRr-4sIbOrJOz^`h`@MB#|{6>1!I zH@CL#kLw2Sfh3RU+MuTSk3T=%K+^aZK#UP79UVM}!17-$A*$u=k4u!_JbCiu1o|eb zi*6TK!u%J5md3tgAk4zX!D&es3(ra9`{x8)^!+c^-a0PIwO`{!U4VdqigbyTv~+`l zfV6ajbc1w*fQYoxIUwELDcvm+14Bu7H*@Y;>wR7CI(zSP_KAP|_;F-(o_XTFf7f+= zuOwDO6bcFop%M@m(T-(iV894$f92>{IefUjZU)#V{d1@Pig~31U`d!kv;^|MtWd>h z#eCaZiD0V$9=MsqY$BfH73oN>lBsuH&(??c0Ufn z{Q+Te0DX=2^Uzv5!>p~LRN)rQt7wn^TeH=*`IM2)Z`#N|s2?XeMtBSSN?4m&Z4TKP*$ayNBG&=wl{hYfd^~SOdC^$WcKrVYeNh#K+5~;BJx}rB z<-N?c+H>=yl<30Xnz`n@wtX7_n@};ruT^jAZ!L>H6rLaSx(9IVgNHlL)nv{;q#FN1 zK8T5aQRoEGcWG`79xX{S7mIHufS`8br);#!uhBfwH_8rk<>OErFKPM&5P350xVFsn zi`uH4(1LKuGY;czOx8aV?((=+en=oErKK*aT#APVywKNXv}3v(bbpfdWNq}>M2#IN_Z^x5)x?Hl8g_`u~#?iyQley%)ZqcuFu19Wbq_bX?5#`9S>} zHV8+dFW;nz*ndhXnZyG87|f!t%27BY~Q#s zQwJox<}e%l4!wOP6BWLaJ@~&fFcEdS<+0uzA8(~~g7w5^atiP}^bQmV_@Fu>EJzT* zKLi2)d8_9uGWFbhmrg&%n!;kIo^zt41n0~T=loDSs&6BYAV%Uo9UpJW;Erg~^jHxf zn-c5a$8bxwhqW$AA5H-`pP{gzbrQ-$yv(=Cn+9;;=Cfh$)V4cOGQL%&+4SoNxS^P@ zkQxR8UVAEYb912*V0EZ3Zm&-VR;A%6XbESEW^P?x>L;fL>&B~;1czznThEN}m!cON zAYnYquH8TM2mhX@{X5)TMynFt7yaW`&pG*BuU4?k zIC0gMP?{2Pazb1^P7lz>2VB1iVy2%6z&G{DJUy{D5=>xTS(NTNCj~7tLweRo9Kp)! zHT_)xe}8V3l>p)jfnCaPdx{ksXy|R$v-h{|pgO3|^!5aJ1m?1C_Q}sb7wNRVnb_vv zFd9PV52BOXCCa5?>qw$ud`L#}=%s3N2=dnUfUb?{_$%7enTFf%|Go7nCK|0tZt=gG zk7g`L3TBKl7hXOK%x+T7I{uU$wtlcoQqH~m&fzSH_vZF4-+)`d=fxXAbC7fqOXALP zxQ@Y|o;^}U$EF&w?9{IOdSXGcCq{WiKrkaZ99IzRYVA#imlV{fjy2$*7gwp@9Ms-`XZ zp@Rn3Q2*SCKHjAU>7HBSnC0sE9$aLid)4?QS_XBzD@nkZhvTgn0Mk$tOJAH_iwNnd zh(Jy5%yN$b_t8zB%xB9e4p{Naobg9EILk-q7#Q~!&JUJB?Fv$pt~}rvYt-1J4A&EL z+q?!9Epc&c8hGU75mH&t=;(SYtbo}7@YL^TjJ{D zuYrW?uV1}U5T_(gOO%&!%sRkRg!q|Spc7z7Xyu!j3KxwSFhA`Ci7>luFnZrMna zhfAn9C2;>zv$B?Pm5+9V9L_e6fvH-$f2cOTw0D(3Mcw*n{dM@l7C#D*#(TS5`PYuL z3#W}KIr}ABPIr$@7(5$i+dzVY?MNF;Isl7^%OGP`P>*w>r72M-NbZ!(#a?K*6I*Lr zeP^Ud<$}|C-q|8Nhv#A^&40iXf9s47G(M!e5YHdCiW5L-KiG23*!?^V=mB&iD}F1( zH3fdcI%Z(G^qbgCS4%oPa(zjQiDpU)<}Y0r+V};|py$ug-b*5kc5wGKzopAGPpo!` z=~^6tkCLbmeDy(+i;)9cUc4Gi@@XR^e9J>ZxpwGOkk|9j_;FHooX;U1^!v-JpRJ9Y zTRdpp7?N^K#^6#OHOKvg8Jh20Se4RZ!Z2_hM5+{Upt3Rhk8Lr$)eGuK3H z9+61fDJX`lnbpibY)vO;pK31okokn2U09MvKt^=FxD~g!;_4kmD$C$IOX?9cGP;~Jg|rnHTk&Zj+Jd}1o3`Q|c`lf%O^ zomRGjmW;}6mphYDU21eRip29+jD*_6fEK2@?8-v)bNu_^U{(itMI^YdHUb8xuIm;Mh3A_iEq)k}8`?llRy&JqI%~ zCw?ZXtO;GO?TBv755V6Fnm$&)qw(h@$gP4%%+RC?q+1J1ecG8KqD6Nrse7$F+4EWy z4fu?D`y3)&e-1^oBy5a`_$#*4Pp9^MtmTqiE=mN6-ETdYSgG=qmtqQsYh$H}M;ZW-MFQkR=aAH?3 z3x6#Q#A$?TH6rgB(d(_C+#EwS&tg*zyC8qcZgjKx`X!tb1^}}>&?=1c^kFWYNp`f- zYKp29ruV_rR4Izq7xP6qQBIaRnj6aFzz=)Y$I|`}a0fSRizvT`&e3l8A*cL2+4sz^ z7E44Eu(xsXZp%rPxTU1)dphIq@4V$%MdZ!&)^depw19Aw> z)|$0YKii}=O`(e^k}?q{g%0#lipZvor0C4&SiK0{0ERYQ{CaAQ_!!h3Q zSmwAPZ~Z{=5wJmet=+TykP<{mJ5<~%g8_5;GKSB5W4;5=T*dbv9yV)9Wq8>6@P8O%E z?Llphn%ek)W8)bmB`;{M-+|W9vW*Eop%M^CMi4m96tuMm0Cg>1*r%Dc8Eh^;0!I<6 z%dR%WZIw`dMorHv#`hlT-F>h}2HP}(0TXt2ubl_;Y#X4!0v9wORO#slh2)MLGF(5+ z2ySCLE5?nf_58H1P5%-TjK_k6cfTvPkG>TbT$I#=8!Yprl8s_p+f>RE^ z$~^)qM&r*Pfngcn9Y8JT7v>{_tH3hgb@GCH_za_eu)-Zy5YA3Votesg)N^mp^~irY zT9ahf&4DtV^5mnMLxa!jTa?_zu4c_s(u&E(2U{-{l%K>AN-9}7KYFBiYy14|o;O@k z%;d}-DGDY?lCQ@fptqD#IKP%=d@q0>HD9B2s5Rk;v*qa{yrrR}SFZV)R6xntl`Zp&Ex&giD zl@&l4E~1R&$fp*-yn(I=sFWr9H{jQ!VV~P5AZ-GZ+u%I|J_T?|mJNNdBXId;okan_RtW$(()b*p}E(ANg7Vy6RE z1mpsb29M8UeFCk9On!j6Nh4 zuRCAtrj%cMJ80M#x@)D(S$DDOlKFi9`x`;}1!$PlID;cKeg!k@bm!?GE-BGpx2U)j z#cBZcV@U5tEU48>#BJO669lg3Nt?$d(j?PQgJRQ6;n%HOcrMfnS8bZvsI{#;Gx+5Z za^y34v%_Pw*h9wvo-vf}#I8o#FWB*ZO>BC7MD`eTlp!m_9!jyqO3rI7+7=8 zU^pkEW9d?gA)D)ec3&{}E>pMokZo1HFis9SwnFW%(Ve?7Ql!c6)^q>984MP9-;LNt z0ru0PsNnf-flA!arCG&=t~fUVeSFrkA8>k)fr?oKrk04q?8Ep*CRll?7qturwTOeZ z2={|uKQ&r0HNaK4kQL`?JLCh{0Th?h=rwv)&WnHy(r||l!RIjP`4^vKDd#`=9JSqd z(>eyI58Ti2&1$dFSH#4!v`;VY0b*Yo%X``aln2zgbyfulS?JLb6^B_(>*bY|@e zVCCzRp%TVuCKXi_4)Ry<+FRAE`RoKNhUtGJDtBl~6=qcK4^rafpQ45^F12=_y<^KC z{p0yB+^KU{6a2?=PgE^ET1;>0|I?WwM_3I$UA>hbX_T&*0y2&bUc%hoRkT}^$3>?# zUotb>k=OEYpUWd+jVAxyQ!iwynYjwI6^K)X&mkUj1&cuhYCHBLtl#iiSkm{lug*RM=+a zI0yEv_l|`N8EVp#!;nU%{C80vD7}YIVt9Zn@sA`=4?`fJT^PHgNHOi|x2!p&Bug>< zYRYNbAj&ab`&v-4{2=>g#jo&4e1RPNii+k^8@Geo42@p*!of3naZ*BX&VDO$1* z$99v46Tg)tOX~Yow$bNCVs$)dcy{)SxIyk7@ThedIIwzX9H`8v?hYG^Xg7e-v4zEW zHYS+VXJ%!&#ahod&(RKcQiR22gN4eO116w!XOdI#N`}ERFVhjV zh$yCaS)J2#%+g27^uw4UKropMZyirRF1KfN+al4yBJ5MT?OaP*CZl#yUi| z;>fpsT5SBVWhWQ*rEZ?VhXs&5L{$bfRiz}EWC>Os+v-U02Ms;@jgAOZ0wNmT3^|S# zT3ue!E3&1)tW6s3W1q?@vAhxUwmVs31XaNNwkM54kcux+rWp=ew(?&UN*+$Oy=m*U z*!^RwlsZlVZWl@iKW;9!w`SCc>BV4|SMz94W3crQSQK@?VhkaeiJRRyK&rLkIy@tz zG3cSD<0|Ly$WvtYe(_-MQnw06)1t~K|#@s!wMLgH1d!EU|JOgDu~%^Ei1x@_MDDRAKZQ? zhKRvvz4b+JANk?&mN&l(<|u+H2%6i#7B_7ocPeI~_#@ziPy?euKIv{$;5^op+p!5L zD299gE7YHv=^kK(?9Y|#7S#O7oXS$jY@3ZiG-K$jk2sz^RKB9TTYB-uABy_Nm&mLy zksIlH9-K2sQyv34QS(AiKlnYyw{&TM&$~~xrgodH&+Ez>lt+aR;u4AHs#ka3Tu3o# zbD;%{qXlH`LPBOrSz%ot_4y))`FW!j-@T({`m1BZF#d&%gm+m8E_Bwd*1RPwuZD;K z#5%rG@#|=se-2YTU&Xg&n9B7Zc^dEqWBHH;hN_^xR9}c+$=7_t8iTrPC39G(IL0<0 z;ApEyfZiIoOaBrunn7k;*m>nlT%$bdCt_*t@|CMfY zSf~ufU{a#%^)S4on7IwG)D4!#S`sUY}m60r$1Y7dz19IqM*yz6_7~) zg~WlmTg)Oh1ZMq&%Y1;mDx-kiz{CHb#j$-mo)gwqrcAq&M9-0%vy`&~ ztB5O-NS=l14Nf1?%jGnfO~0fl{u+F-Wnn8bTVACx%gGh|!;yhdLv@!JU)H&J(3GZ^ zaG1+*3v$Gj&QEoR zLsr_HM`wLe>%`&}@Ka zQ@DwpwLlW|YXzZmIUt{4MbbB40`;LkaWrHpI?ydj~?A8Iwh)d{U zn0TitLonzQCtyzAeG*%n+iU0u253KUK|+=n0G3+8;#Tm?TjvQrzJ!R#-FY9lU=)pP zIw+#!u%3wql+TE-loIY^<{U)Lx0jaSMj!(!i#LE$4A_go!-6)5dI-=(g=pK%06#?V z00oGKoxtTDmj0Ykv-0!5npu{XmR$Fm&IBUvA-RYi0!ZjGV1BNq!mnvT`IR6T)HQB9 zG~Qlrftm!60}=ugy$x6szva)u1A)_ph|0hFM(%>XkxurH42*AAlvp9X@5|pe#e8kz z2;I!0V3_Z`p1>P(m<;&+e^*r zkl~+G0-`-4{T&{sjUk;aQ-m{|Rr=*n2VW%d0hQ}7cxP-I`B+89pFmugyywVcy`$v6PnG1HPBfQByCx(;X zQYh4AG1BPRopV^uS}cw3gTKU~+h(V~x;4zxlECmO$CO8Bi&OtoSnBBX5xg>RRy0}7 z=FM7_%Und={gNER%}l%>7!!auW_&VCIH2d5EnfE1`Sw%1vZL89bNle@&K1cw>}Hk~ zBa1gWD|?fjm?K*?lk`bC8IMv5UvbXB2;8HH8acy;Oqm}M zV~mfv4D#A*zKMsUps(X6`qB>Bc7?ySb%yBOwMbqnm?ypVO3s^8jAt2?!_d zbpc`y-nWw9dvcG0`Rur`&jVJ>$xcgr0iCsUF!+4f$R*jWC%m7U1es4DdIK+O`LmDW zBFEP|re$GhIj*@dfcV$#Qx;f({*R7(2!}{f;`~=&JMnTo+Or0>lR(`fSd*R8;yC`Z z^YCrXyIH4)KI3u@SLj3!WnyuYGjx4W)TeTmV8mk-rZhbOu)K9yB7=Cg^7E5 zdJg)XQ2wR6;sK~io`Z9yc-wyD4G-4@I@)96qOLTh zgI^vO(V7+|@VR+|zwi?@5Maxd0BDVZh>b+_4iw+tdaPqifueC+ot1}{tREu@t zyBt0ikHLsJ!}ek4E|iRVxf?U4gguSc+EhsX9dzpjZH}Em7o(yO97Zb})r(_x`-{qv z_3IOoHw*hXa2lVNzdV713s5+a@(=r8tIpU}7kNe;^#;=QNE$B` zjc@R|8U#RLb-RYu*T;A|D6ru)sBUgmeE0FhXiXEIziwxq@)_$w@X2dhCeXnxaMDrJ z67RJYghfn;56^;;vZ<89!>{SzX@1z|4N%pjUMl!PXe*~Cc&&qx7wD}`EZ*EqiQ@C>@`B(t?x9i zwf^FZt2Nko>PA7AfR!D_{mAI}wx@~+H&7m`-ZXbDOn$Tv;X`p6Ei=9+dY_=>?MX#lGAt`5nU0V8cP?+KE zfUuJC7ag0+akPf@DG!b)Na}Dq{5ZE5e2$En}B&?tYTv2X5VLiNPZO$%ZmJk z$0+FBd9a(kT);`)cpyfhniK+fA%%?(YJR@IdU&tDCf?23`wrb2serRYTF!$&l>GZ> z%Ib&GbS%RR?^=TmW;iF`!_Ab!3Q_+ZjpKrR_2ZH0*pBC^5(PXys-HjPP~nbG z6F-3p=8)|V8cJl;$GjXnS@c=l9M-Ra+3`!09cog;{J_Q;{)qk%!|Mlody+~%*Ux7f zc~h24JbP9lHHxlJeRUaD)58kYZeFr{t#zSJYEFH%2gn?234f9~vdCotnZu7wpXpC= zy&H(@;BvH6xJegwux*`e%@%=Wz(6OnL%RljgfL%IkpO|~%jTZ*!k(6#}LkCxDld6y*Z-H({m zW__O7SuK6IIsVa4K3?x3;B$EL%&*DZW-sRk5b6=-`_}sejx$JI7 zt&YnJXMx(f^%Hl%4;Yjn_fqyCRPXv?!>4KupamaO0CV?94Z$rKx!^-oZ|oEs_TOQE zVrfVYJ0G6RC>C<9kLzwp9vzWkSh{HPq^RC7jKP^$v3K(gPn_9NF zD?%-@YI(Sq?iAO3)vt@O<*X?n$Wo=>zlrQf&I7Tz*Y#+kl$u-i8lR{LBA65#n{*p4 z0n3~mLHl7l_NfPDu+C|$#f~>6S)hC{DqFfGiO|0PiDu=NmZhC;U+UpxgAV|&Bux9X ziCbj*569x;5ao{4sdTbp|F?Z1q({JbM$W>p3i5{*@|;6G zXO4;Fx5#Q9;mt+fS=N2_GJ{rsGSYrrqSHBTIBa;V{D>g>!=bSJ^3QwgyoYFjIi-8^ zou0KY$9E-3I!M@r8o++sgz+8`WsXqGX)W@#dk~&8!3JXQ;fMOWEix{b}yt@f}UU!0I?X8iPbfqwh?^k0z}j z+_{76gQ_acS|H@}N#CW#4@RKKP^QaK8xqdRKS0v>R^GF@{^OUIDp@BTUu-n1$;!)b zO2dvx0KFp4psK-hGbrq;un=lYL05Fje0yq@WdNtcM~%`p!vDT0$h_^mK2>;4Zhy7~ z6xl%1Am(xm{c#HX4Y!dUK9@^(U(gfOnJ6eXWvqzfau1(k<^Upr5^xweyrSBT0E5Cm0b8< zt^Zo84+LzCQ!*qX*gVhQL)7Yo!%fL=#9d|SMIo3 zfQ(`B=7Zx{|H(W#s*Cm;5fQ&dZ*SdUhlq0ShO4^X?d_qV?d>F>heo$Up-C4w6-HgQiyZcE*_CxpfVuUt;U zzABzUCxn|`uW_{IGdES*2Uo*gt45kAUxrcI+=FVs?w;qg(`!933id6fd5G~;D#qXpwba~ zRW%d-sYWD^s#eb9F*8|RQy5JD)?4bjF*-TeITUwrLW|dD`gM^7vR-sv^jpfFuqb>I zZfN26JPdIQ6#V2CB2GuEB{{|XgaSe_>5oWef*C8o}%?4EljRbu}HBMzjA_} z?(n&hwN6-p>8#l_Za*(4s9T@vA&V;pdc&H|WU#QDM936Su%qhKNpOjdPZvXsDM z_Y8QkDtzF8p~32YY$hH?BE7Yd;oCGt`ko#;U0TYVeW$+2f=;Ul?)hf+kg2m1S9a-r z;(if16C%72LY8@{p@VbPXAFXM>d>iDDP&c~`rixen@Vu4gTlFc~`NZ{|+{@1awuKX^aOIxi zIGKJ>@?mTc)5}1rnS;*kp0rOE#G^=N{V)bC#f92lN`WRFtC)iIlqzMH>1uI8hz~md zg1x)WS1I{O{ML!hzR;x-GGhKRPx(vKUg_Y_J(e@S$piZuFFp0k=m&3xtH+9hcHFqL z9?wiDEo3P1V9GOMf^*^hphIBo)tjiMKj_tp2R_`n2V4z8ss%BC#JsS#$3q9q*I3|z z3?_a%{XZ-~{c7bRfUwI!!IwV4bcPQM4R7Au2jBatF?gwtZVoIGE`XPx7kv2|8X7=2 z06VedYJ?9W#|e1m5Jj$cv@(uBqBoRGFfk|9dj`^F#J0Gl zrnqGFtB2#Mk55HoXsUAaJ#D7dpC=Onvsa&7)n?}oVzXLquYvGC$$A-voXZ&?kgOn8 z9N%J1WagR~LAk2YGItR_$N6IS70Z$$Vay|(RCIX8mp|Rf*2PrtOvtmd(mQyB9hwl5RDbLwQQ&Stw!5MaKiiI(&Vpq# zRH*BBGGp9m(Yd*mJ`U-Wa=e=y(r_cmq0JPbb1-YiU0S~?zyK!#*VhQ59=FzR87UqB zkgRRH$15DMkMwGQ#|fdyfEIW`ki+*cDPfV0Wkf{sJ7MCgu|;ebAa-H~nrp{h=v5X) z?`O*-w0Z3D3U3R6nDf48uenBt2IZ(-!l{p*&-2M{B}wt><-Yc-85w8fu6WB%t1{h& z{?#|j8A_2~bxtMf3OcpT8tXj|Hf=~tYH}PJVGtLZh>~%)t8dErJyI^shN&?Szc|}b zmuiY<8K( zEEWRvVZR6qJsX~3NYl9o%nCB3z0L0#3*zmvvt=Zq;Q89Gei{36(%DFdRgBxt`gqEaC)%#m}8og%4AUr2vXVU1S6AY0| z{SwOcop-P5&Mm<>d)coIR;nBW)`St&yl56#>f?i~J*JadRhmP2xyYylzg@2W*CN|! z_H0V($J6&tja5Suq}NUze(i~c!mkOWj1K}wN%>8wEIplaHjG7t2Z*MrvM$&qAEI5b; zOxEtz*v!>~JWb@6h4@!{UA^*12-P@@h|?8>K+S>72jUouOQ6%lnilTPeajErZ22k$ z_P5t=7L&z0$DoOhfn!xNismZ>vU{AsVLm3iaV-8us$xpmjt+0Eg7HVuZmr8gv2W?q znDNflumQZ!LEK6;pA1Qn-`0F0Uc=DH0q5(g$a2vliS0VmQkd)u{u^=d+GR@b^49Du zhcc#h&qb8Sc0XuXUX$OY$aJm{nY{8CjIh$;Orq7jfLQ2NNZasZgA9BT#N(zWrdE9vwNRzJ}IX zegh(TPb=a6ee*Zl=4)(^h^vy)N}(Rv#qO^BWIl$R5lz)&w`jSr&+bfnD`k_avAK&V z)$Y%D2MypI`1UYhgu~^_d#!)++SRFspY7446JAKsH(a6x?Q9EWh4;K!3n*Fr^EAQCENfNv%LTPuRu6YL`F`IR(w^5uFnod3JXXw8KBf3_;gKaEDCl;3vE~MJ z+dTEMXFz#f0~;G^5UvAg1pK-=P)5kCUHctKF!!;rx}Z?#t;{Tryg)0sbxN6-&>*~y zNWqp4uP5`A0^{QeVi`3=K-vfdh%sB>yVtN3M58_UyNRHM1@YjGW!8}b91(Cgs?2c% zatr|gFElqdAMZf%0U8nb*51g<8n=B!L+&b^u)rXpL90V%bf`W_gWT>^QDr4c%GCf< z2{t&rNO+fPd)(~eX(fgTF1AW{h7M!zxkJ`VC~07?9g`EtiYm<}O0Q~{hbkg+?vl$> zt6W>1QRiPU^s={2JOBWVtOn5)3szhH%p6;Orl33%#WAJ_+h!qW>lzY`%Yp9p$Au1! zl$RTyC2R3)rL`J8Y(mvcLuwAITnjE4Mu`_JR(HCgWqUY`aQ(+B?L?2XD_9%2u0Os? zmF^$%zjMCRFnN&o@Vj8Um9brSBKcJL62m7!ZcJggg;6&3oiw}2Z%#EQ7HdXXUm=er z#5JEG^&a3O?H`_WLrd1p+e6x84$tbDP!HEZsa}UNMz6Wa?$-7za8^?0kg~RL%!W{! zhFS?55kGEn^C6=|b+u=O$v7qlkrmC3=IT$fY7OiX5eUx`hY=6lu%luZ-HouE5HSfq zsSa%6*cFJ}>4&A+zo*Rq$gwyjjPZiVJ`dXWQ@Y%#cgyus^_#UYv_i@x%J)Zy1CqLo zc=;mPAT^S%0B^=^=?hlAUpkS%jpLhbv`*CkxLW)tYn;#19M zXG&xBzOhkjm`1DWc?(6EdZ^f;;tbtGFz=G2KBYiY>uyUMNB!1wj-tRt3qH3pyB|02 z@9s|A<>A|OLSpuA`AB3)mIaGe3rcArf$#3zCz^@4ITN&;?+PG1GUIchH%E<#Y8Lhz zIgnpi-FUU_=Vuzml!rGbQMR}?nfG|?^LHXyp2j&<8lvi|n4l93z4m_Y4{~R`eXpgi zd9UE6S+rkVH=Ym`VYT#ej?{WA>T%ARlUsygVavB9#m*O72c8^TZ-JF}K=cEQdwjJ~ z5M!r&T3y!>Re4~(zw)pVG+Q`mChMSz4+`fVZwf#u(rks`gtyex$oYb^)5k;b+q2PnVISdL7TN*mH^5m;t3JL0kdfj8;)8z z1K~sPd_nZ4_YMqXsuZYNO_lnhA5ZRBF(PUhlFe2X=a33}X1J=WC&MU1Sc# zJs7N=lqyVQ|4mJtowGK?MM$N(-WSFoi5sX}VhZAzfA(pBUhPwB;mh@mWMLmj5Dsl5 zKnMZ%2qHlQ8q+Is+&1%aMm8J~`%y%Pm#e$`7|8wUx^HADuBhm9?T%+CFo1;=)?8H_ zvd@WD^*HHOpErG@00{<`IN`zA3R`JL;7!1!-c9Vz@rd18wkC?RW9YK$$|GAOyuv}d z{Af4^t8G2mo*>^9MuI7mOZeoxe83v!0a-BHk{6S%ZOV>VTE$@}G%q3c4k^ijoa+?c zUYk=5x$ScGP4Cbf{CShtl+nxt&l9Qcm%d(FaqqYYHLg!WtCCJ=S+3|&xxB^X zOdj8=Y>oRIW1mvkYnZETbC)66vpv=jGAzBBf5gA~xXh6G6{nWNyaUFaH}#Im6Z5>f zvrV8a9O=F-@8{ii;kqIo+e&X2X3Z+UM>kC)bqqW>mPTEX$DS7jZP0dw*t1l&g_VTC z8y%-pidgnoqp3hqLRsLB&UUfHb|kA_%+E0lmC^X(J^m4cdJ$UwXs3p;65i0t0WEuc zHIDvFTwa7&nK0tZ)2p+((YPs}`3jDBp`a0b@h>iP5X0eSvBPYiZSy6N2G6z^Yom>* zY0A7>r#r>;L>FzAl(A8p!@KDntnb^c(u<7x`g&#I@`3lQgn*Zo@iTT#tbn$!H5wa1 zjF*mIZst*IhE^7S*8MSQ(>`*5ab$ZNKGit?0UYN=7}?||8vA@1Q~`75#7d&`YQ`O#(8rJ-u5zC7Hnj}B)a_{GoO^mTFh2bql}?n z-v4!xT|>2v`)&`@OEp)@UaFNltjX~?ZFWponC7VzfYmo*!wUANUQ@=ytj70-A zZnT5m6T?{skehsR!RW*f4;R>A_N`6|6A&<*1eDQYT72wi@m((rJi|5W4)_*eJ01v#9@YrGI0hV3IUg^Uo~q=g25l zU$LkzsE$p?=SLtoqi7wptZ>wBVaR>WZcR#P7`|3{m} z-M`x`ir;-jlMbf(TL!-STj~XGqG{X~nf|+DL!=hzxBfSa`-^%`?C)Iu`#Zk_&iC>E zR%cz1F@Sum@cTU}wEvcmchSL1qyPC*n?=m&ze+#SuZx7t=xe;@p@+NV(XM9_&$Wjt zQni`(9!mXc;HGDD*3@(hRIsX`xvbM}G?%E31Lwx-WFaxjK+p5N7gE0p;ymN8qskiF zpI4uW=knTd6(fH8smedTsu-LA31v46P|Oulu>-+L)StOqv4~UaJ3(j1H17(jc$ut+ zZa1Xo_z)}O^~}W4N@qd>;!g)XN1-cAObG1DK5vY{ zKR)l@oCV~+ISV?i!Hx83&;M4mng3R_U69>WUj8rM;uY*jmE-q!1-_85nud;^uatxw zW^dgB|Dqwht}D~*-&0ZqIqqj198X+aTxP1R`@tp&UG@qPd`IdWOzD+#Uk0G#u7hRo z*A0wi#daEraFSji@*=%0m{2a!O?gBqzTX1B!RF?UyQHJ8_PTOLJR2=6=)Jwc6(pBX zTT_9Wl4Nl(LeJwe-N8a!4z`a^>f~zhG~H{Qx+j%-vtF}Ha~b21nxed1D_&?GBKv`@ zqBJTYsTv*t7ID`HF3fJ1K(b<*sZO_~kM%Xtg- zkqO3H_H_id)jsoOL7!AlI6o>YEPhjYaZuoB5BEQ~t=A_GQMG+W&6L8&=?7A=q8x>! zs_$lmYxb7>r!kUa&41Wj-yAVswG^o`%){#wg{!Y+Rh^k-H-9cw<&b@IfBQ1e5P5y} zwd}B}rl%u1Gp*LSwH7lz4*D?E#A%jbN>^HpoLbTx@Ah0`xYsO7De-ov($TE2OSE92 z4VPWIW_9jxPet2$lYV35ZBQI4m3CFRb80|8T>yNJ=*QcUj0ALHmfFNSNmvQI4%56% zEiA`2-=1;2^i{kgxuF_+YfK~9AR}Tjm)cTcfAM%svE(t4YElk_SU#ox1Vg65bPX$( zN{DCpD^W6fr$!05ZpXJGhn`-UwiXM) zdMvjju(m^&NqX$^NpP!~iuLr5guJ*70kg-04PlIqP*g6T;bP&O@xuQ5^#c1Q;27|f z8$JS0847;NpuUOC(VNz`W!Z54_T8##SN3Av?5zdK%5`1W#w#wb;h~9fbC}Z~bDyGx zV8JPx3P&-c=hbE(JtpW$2-rS-RM867&5w-o7~6Dd*sXi)+&j1L*?qP^kWZ>$U!yB(tv=`X7llv=f3 z+1JN#dOUdDH8sW%Gg1uXsZlhVD1*1V0}v?&*s73S(ngP%cc z=CQ*bmu5ZZWVw+NRw`3p$GeYq*zS0Q4k7gxWb3P~Gjnd9{Y zCHY0+hgwY~snOWg8#E?4@0hO2x3IeRAmMo)(o|XgakSK}XU{2^F#@K#vl>@(Ij6&Y zB{@7^E$=5#VvC@CTk?W^$q}&cb2|MYLcZ^PrOl@-nvz;kUfaP~7%@r3l5K6cm z6erQjf`^Hr$XcF?+8|GmQ2#vXvjYvJdD1^kDxAJnjR8|9$x^+ZI$}e*e3ZB-l(3Ki zahYO@;vSo48C@x`&)=9o6T&6i%W4~MS~#YN!4;SSSf2{K=9}@?Muh=^^?A8VYj2cV zF~rZDD0%1l8pCLsHLRCP?qkq6v_cv4e4MR}Vc7F8w!eOrxjIA@X}37Ig_cCd#%jKE zXR)>Y^uQ-sKHIAuzhZSH!$r9Hb_oZI+;Mgyx#E4@xaqcZNygjfW|QBf^Ogm@%$R&i zl0~4+hHhp{d*^Be-Q@G(G_>ql-;ZewnVVz$HeB}@);)upzsP2noqzJEq!rIL$Do7Qhtb;dz)ia010%VTcUD0a~m+~Amux-3dm0cPLtT@jZe8)!l%)G$_E3pr^pK3L` zN_lotVKDoixXE>Fcgzz8dF&rcD+=!~iS9^|?G)+jWd^Z$4=$f0vr}GKpcR@GsBzf5 z9n|Yx^%rkGXNo{3exQ7y^ddhsTV`qQ>Wl_&IHmQbJ$0#R*ykBlA=WsIR9<{$;_kSI z`^Edc5rsxUCoJ-z>wqD_y_Iej;f1Mhb4UcoZrTF)onGybUpK?}hi#d89eUyVT@oeH zl8u8~wXC%jv6vnwp4B{o43Z`g@=S(GGAv9*w)9kf4>^L1?KqO~6n0kkGzY;#h4u>u z6V;s`agw2M@c}_Ci}f*?_VOb4X7xn>Ry38p*f{5e7#ab$2 z4OpmIg$|PO!yQ35d8$Q35C{Zu@q>&SbTS1@{K3-{{Ec7~Oro?23k32Q>=G-@$5G_v z<*%==*Qd%T0n4begxllP3fu+)#52Bu;Uz#-kI>Nsh_r%#z6T&}MmHRRHqcFmGer~x zWJ?-G#s}Eg*od{}KmvO|haTw3A_RmNTzX{?+aE2_6CO(DHG~UMQwIQPDIUD+gp}Ya9Jpd97G|Ly zY{L*nJF!>>`pn5TpUG3^&bIUuUV_k(Z$Wq;7|V$=85(RwZvu|ja!ejceber^f>s@M%}3W%NS4%-$qr@GA#$kIA|5noto ztNtG5Y+1ahTp7fKib<8Jsa~NaZ z5|+m27W6!ghfcjx&V*GPYVcczrYo#8(>?Ex%GfK@b~q#T4HZtyGk3?iEyj|aN%?TJ zn^1gTO%S-k{eRpq=*)`>*NsNU1tX8sy^BC`*+d)y<*FYCWH6x!@twfYw4I0a$Un2Y zN6y}l*E-nm9o`*BRkjt$xzeL;>_k$|Z`%^|7fQm!(97!H#~yV*kL4TM!m>`1$iQkh zo3gnd<7Y8$8P5b;_COEkE)~bAf8d@1Mso|Rs*a6Y-tIBF*gl^dino_!XG;CYqfEc- zcdr^`l^hI+{?e`O$eYZL#C3y&%ridozCdZyB{7%BIURd$u*SGN=7(#P!q;8K8pXQy z>k*s%n}m+psyt#3`NS!5V;YKyzQdLW1YxS0lMLtayR#i(xda%{i1;@$73KOZU;BIU z__)fmhS|TL`E2sK56LJd#>D@D(E_)o$_z#qE*VSx^%H)8p|eN$I!^aYvB+IkTnLUr zRK(BERl@wj>!ypze4?3OMYQeyee_j`2l+FqO0FDvQskFw8=aPWKC)1`CN%WoS3C7# zZr9UlK|=VFQi`5=%R4_s+KX|-Pazy%-%qrG8^!|~h8^_0zy_}Ihi;<-KSjkKD>4<% z87?TM2Mo!QZeYJooGKmuzCobm3#}zK+?~-L?DBFC*W-7&Ze+#QlSdBgUzkuEy4P3*dSNRXhF7GI`2l1!^qLdoZ2C`Glw_|539{gU-mg7xr~s zTHa)2WWeu_1g1~_2WxK`R`t5}YhwUPh%}NGAl+RG3P=k`hqUCNI~1k6bI>8(J?N6| z?(Xj1_i(Of?YY)|*0J~TzR&zJj|r2J|G4k#IzWjUO$Gq-!uiVrh}z+ z2T+%SU-rNZot5trm=(|&FVuSf{(V32bHE#C`5I+2c|a`o5E=OhBtTmNAYs;FjpX*M z{;mkf>zKQ|K)u{@zTqCIdbfh-DN@Nh-kT#!9T@Ejj*1ciEoXRv94@kpF-TYdLs0dG zxjSIjv44E5yEj|w46eE`VA?X7EY0d(e7JvBb`lKrwLSi}ypg9?shy%<=1xNtft8J% z9Y0!hKV+ayaO~cGKXnI-lK4$iyV#g^VDXv`A>4KGR9j zf3X#gtLQuSl^N54-;+InqqJf08@I#uF*q+t(~LSt)}5Du*)TytOZM z4@aX3I+H!vl;KF&%}mh{eKt*g4*(`>y}|=&%Hmhd>9QZg^yz$jc^$e=z&-|3_NlN$JpZ~1{iR? zHZW$KTE7wrTn0U6q(9tH7el@7T%8NN2UMog0~*bqjz2v-ia?VZyqGpnHWq{88}!C& zffu?xT^06(#DuaNkUf}KSWTS~G|#xL-+AOd?w0~p!<3T9+o9Ka+| zG_M0Q0=%3B-mE@2^+1e5&9H^W+LB&Q8gnt!D_37vb^nC+e6deF^KH6(aExiKA+$jZ zajxj_ScWkvmB)>Y>SiA~(bz(7nX^4UMhBb`a^0k3I=vNAbcBlPT>Gng+#f+-7 z^2aB(DjEZ0UVe%w`3T1H=<|7N!ZJ0&jLKY9v?{eBnX?Iv-zuP|Z@ z#!EBiTQB`WuW{zIR_>B_ySbKk=3S0Le^y9no(Qc8_ty+tHuC10tmyiI?$)1!>Z1Dk zX*xwp`$txFL>p_0-@A&Kz{w7Uwhp}_ZTZTYB2Vq0-`&M(Je%E6I#q7c&@3cU^8_l6 zOY_$34{8DskjxeCJ+U;3>DwOnA+OP3>y6jVl-CNAPodLU_NjlNAwd$fQ{c3LlO=-1 zL(DFM%to4!@LiQ*T<1^KRmsv49Z?jBebsE@wQkaOtz}EQt2))bnvLzH6;ki?>m12x z+Kmb*53S@Hznv0-rhO{I%GdpFe^y#Nmb!~TF3o!17WHbS-zvdj&{lEjCk?u+N%GkQ z2h+x^Mx*5orAR*#(gj>3YkJS-lWEkKcECwvRcn+k_Tt3+-GyP1-C_~cpDN7ML9znkxTl#bI2CDC%l*5e7<3p3`nOKj zt*Zsykl)J41P|?1hG-PjXVFw8-Ji|)?kRG`oxpQ-Io2I|(=Y`(^Z1^Q*ik0>CjwO! z8ZQ$6&@EFT9H4?u-L>BtpVO+U63}cszzK`InUicXW^!)Qb)AF#So56I3=Fy9P$PC@r@TTxw^~Q*&tj7MYHFmU+!<~suN~Kv5HnVqwQeKH;8~&pWbY2FQcuHr{Nx-~*tce+1fTa1cY$ESuk+%#&EL9M!HxupJ2n)u6{&7! zG$3S}U@2mFK_Mn8F5X%oxX_36CPK_T8|lGQg`6i*+6={uW1410Feoo+z4S{GqmJ>4&GDA8?-) zob9y6J#}&ie}U(+O1zhDb;Wgf_Oi{*_3B{u3Ak)cBCO4&pzpUwC-{&{2fg6J_3QXq zE|%_WNSz#Hw_8+0GT|_4+^&A_Ugr zEP2Uhz2uu?ib}A>okNL0QSP$sMtnH2IZVjbT!rQIUBE4FZ`i(sZJHt^6sMht%vo+z zgTs8dx!iH&)1Kp&87ZHoI{eyIaR)U^;K4jP86dpqirAT6sK!35Y7(zz0}&po<+|Xm zcB<&2p6IMQU1{Nwf3}gCcnFx+BCTd5l`?93-QRhY(<~5hl^M=gj|2B=o?6l*VEv8m z(FanAEcKf5p*01%`K>MKSXLkP8ruOdd+&O&g5SXY(-J6$r3}HI|056=`H~!+EcolR z`6t7b!Qi1l8dhx7FUY|rxU=IjW#dIx~M*l0Aj1GoUh z%jW(K7()6B80yf614F1btT;1lPZdT2j-pUqMaNCPN87WUK$Jx84d*1=s z)cvkpuQz+zZRe;{7cEDdW}y5_wfWQPG}}|cw8f@~CY?Y@M!AaWKb%oDoHJUptx|z; z$ktSSD$ut%CF9Z4)GtyRcjFChv+?C{?l37br$1%B#We{i&;ER!wY=7Rs}pj{3U1i( zoKDH(Q?$;SPvgG6;BDbbY!aGAfwquy&q~;PA9)zhY*N#!i6@3?k@HOn&ICKV6}%OR z9c&?r(oWY8Ub_GG-cLkoZ%OKNGzY2X1`X!mXIIAd5YK7V@74#th3WJMS4qwMk7xsbMSB5H7XW$s7VO!Q z(2EZlHgj(>W0>7s*s;G37~wsg6uY8Ka(uN}28(LfpizfayfW>>q&_jPySFu0@*vA8 z5aA0O;YR`M`*)-}B#&`WsBIw9lL>=-XUJoLA+J$w+)1L8QIc%g^pXp3s-nLnOR=pv zqhQ$XcGS(9=WJ&#*NiwUhYzHAn;Eesmu*@wYuCHPv}!Ntw%jusGgaH(QOZ-0pb#-W zbZn-3K_59bo9Gc0q#4t)^~;OoLNCYb^ZRxHHUl(U>V*C6%u|k(r8{WIeY=;dTWf(t z6@kg@>Mo5zdwP$gqowE)+Em~Xex zgjjcX>jY;WvK8{gfU5$&ECuaK1USTiM#Sz9?kYoIx2jN}(E}C$OAs`Z^=_Ghb0O{^73Z$^dt@R=H$%xsG#gPo3qw!{wcQD|U=j8Eg20a_{tqZMr=f zX}{lDeT?*tN;2y&+|JN4)!#!z1miuYXlpf^eW{io1lstS3BHlJU4;qT7-3;4#dL40 zxoXsgoTueXk2SNSR|+Q2C*ShLoL#91x@XIj`3lU@-8{HMaRt?_?Q(6{K)H}3X-)f& z=!Y!$OFh=c$zW+*xRyo-A**kPmYUGy6i9N^-V}bvCmS9}_3*^Tmni*}li~Qymt2)t zU2_V9XnjanTsyY)^lUQ;oZMn9Rf8PycFY_{xN#eQf;~6U=PIu#U)dY16utD6C00Tt8;s(g2+kFmc z3~l_}H#RT?Hxjl384UEOP}-K)O6$`t=m9E?x1v)_H{gdG6AGg{Wg|pxBGCj^^^y6K zGn@_s5=WC}4;2*-r!>ni6|;U~o_&3kpR3!e!Y77kuetT9;>0tGezxvRpb3Lz?p3a> zi_xgzZ_g3&{|J?3rfDOro$7S-K3`ct+vm|^nPTglRMJtyWcLcJIpY#L zg)H-(XE(%Kl6*;a;@xf}?3U6*bf7sa%ba@*fzT+ncg|10@MQ;cJK!2-4`l4#K|z_I zxUt#xZ|pe2OoS5r|@Jw!xgvfWlna2Zu-!~lggcrLc-B&&w=!H1@% zrf3cb=}ff^jjdWA{}rtl2ATf({sO3Iz~iyN(zm(VW=rgvsK(mDl`KRoy-Amu3C#Gw z{}$;9v3KK_B+w|#Rj(Q4M?1``m|XBfKSZS&W|q+_jGJe9SqTw? zPEOu~{`xjKwkEyJF4a*%Qp=WSvOe-lbo&hxhQ-sW)6iXpDE&#A;mz-6r!kZQj=g<` zZg+7|VKK*zUX!@fje%ddyp}<|x7r8FT_sSRQ@MqW1ts%0o!%AnQQt}UwuR>P0c~cD zwLUD-_3cTZ*Jnyz6XSRWwW#I1MQvR9AzjOzkNV#V<6QWS$zRUmE!}sy1SU%c;eX6yq@ll zO9Mt?c8v(;>!ptwf_RZi$0iS{CYm^CthO)Y8%2ChJhhm>eX(0Jv8&+};BSRcT{k7D zxSH>)p4A6PtY#>ryBn@M>6`j>7krr#vvIaBCw((V1%vbfMfdzRJHkV?`_%Bpg|E@b zW*K4<8ZmdvK2#Fpo6r-HrrQv@qmMO2Jmv3ScDSa&0wu~?A0rH9`Ldy@uZ`8E4-?O% z=ld-xt#i$x;7qMDmW8a;3rgYYii%Q^bLNwd@ZO+ z@NPEUK9KJUuOsfZDAVW4h6MEg9w+k7f&(ZubDU$J3hjb|sY+d>FXrHoaWJ!t5CV0l z>A-WnmV=PFsx^u)Sj!z~yL)_yLq9gn$?Zr?_?_w0f74 z4DLeOt7y`B+RJvPQ6|N8YHnOPXF;EQ_mt)Q^Cp;xJB&E!&pN_1p91c|^TC$O2 zf{#&yB*9zsR%SU_8&0Q^VnpLQxuBDr0 zPTuD#yN}AZr!ZIhDWqs@DN~`h(!JcMEV=%lz*K4?eO_OA9UgGNLjGK ztS`mifAt?8-K6;I|33nXf|e@wpRegBs*F)wCupGhg`aSl@xw^#K%GF}^1NF9)}1a$^MaxV{(}u2UWbdV zT!4s;*Ac9>jvE>RM9iljT$rjs1V%)ef`2rTp*go`0eLXd@2;=XX!Gs2FS^dE6MZ^X$r9mK`N7NK^tT0OCBU`Z~MEQlD(ZraJS2NME| z`#pL8R`~qv<=GzO?yP37t_zf`fz{VruDY_46X0j&?Mv`((*UQcS5u4s%w zf&4Wc-A*98_1@01RAz<>Zz)QzI(w15&J&-k4|8T4lWJXjre$D-T^0USe`A$6WvLrs zeHwRqssnnNY(#zerlYgWa=G;TXScObgEw)}R~18p$wh=<h$<8b# z!+?g4pBphMjPAOeF3Rt5pv|;AW2GMtUGt2&92KX{KufWygYIg$Ykx&fD^Jpo$R`1; z_LVf8ZWG;ubX67p724N+Y^fT?r);FcPs*Rjr;uXu0+_S1Ha;`m_ zl}v@Tk-q$5;G%PV5R?!$K#|E>adbwV9~dybJ}MDVA=Max18-qIXD`|}<;Y4;(Ii60 zh2g%=RK2jO`2L$fwT}7^@^r~I{cAn-dEb|nZgLi5TcVCPKP$+1af2-37g3l!}^{N<6IAsj4g-FdGyw`FDLARJ3lXCih{E-N=bcqon<< zu0P$)iKSXWwXYaIiY2;2uUc`Tt@K3r(*FoR#?Y|JR$pwk(wCN*@f1tNt34q`G;iM% zF@vwri73YnDx!T&4wk6jKMSop-KAP@o7Ld4#7NL;vc`G;s1fzA_m^7x@FOGd8M`(y zSnJY<*>@EOB76m}zg^hKJ?GcHwc`FnC~^MlC>M_YhQM8Gqs3p8t`qiKI{C&{=(PnS z*il%f?HeaLQfv8NzKGZn{;dAgIAwcdb?hJV`7V6sB&gCU{MVW(2(%{VcaBCx#WTM= zHUv%54}i81{rIs;?f}nfI@pfv+?s)26QX4wAdM25}D zk?j0dy6#1}+H7K6qdVIKYi^eQd$&GjpQ`_klww}RTQEc0UF@yqbL77vkL&uV--dSD z($&m_yYoPO#t>(Dw8i2}Y#FzkHb58>)O~u7?}r5dG+DxX)`ueB11lTZe=?p#UUHptsQhUNzjwWK08aI z)ZlL48?L0{bZGqTS?i#Ow`F6uSt(aT#re!sd#R53Ymxd8IBT!CvnQ+@e*4cIR)%V? zY3$(X} zEYaQGqLcYCKQb&^W!r1c_9WpQhAS_DR;R?f_o7N98MQnK{-rsH8E40b3$w|o_D-9` z{P7p4P^a0hAWheXBB7dljO$00_Vm72o_rlwi44mgALV@NiJSd{G^lKHWln7#!sis6 z<6}l@I`gMj?ZB38M)m839-s>8JKsaT9SHgHud0lGW=R8|o9)WMfpmFRl~sc{rgA<~TtE z6dkm-7VEBdt;EhiOx~v|OFb|S4G-B92_m(b90iqN!pd{QnGXn)ZS1$B8Fww&g2KPw8LwrbwkxF(J~jf-kc}`V|D`(1lAZx!s8tfU~{QaFm`mgRe+6! z<*tyE4mv6T+G@YO0mDOJ=lPtUpC8o2h5)h+YRkyqKnW2T04O;*2>@vZ_->_o*IGFk ziidk?DeF}+xOu`~SN)cwhA9|rx;)uhT3Pu3TFgFveh*A)BT?~a=K(WTxHfmXGv#;P zLq1Xx!Lwz%W^tSw0#5SPo0x#as8IcdO~J8^kx3{NAYJ@_kS+!yOGd(EA)P6oQ?X)? zJw<)1?f8&oR@6^S6u09c;!7$<;d=X%fo45yCgVA4;|_n2uIXSuaC%deq3kv6&I)$z zF2MmBEVq%SK{^Kl357|H(i1KC( z$^cE;USw5n@1~OYqaeyXqYRY+n@`1P+-ABV0lVBj%A~ifbxL%}yCTFB*KNg;dlYZ4 zkH|9Xb5B5j(p1oy!bP}d#VVoHhq!Ue{i<^V;JqckH zry{YUqGiR`3=f3EBG^w*0xPVr**-DpmynR+s%tx+-7 zkp3DK8po-9Yx|j0q&F6{0W6ssn+{1XnFFevQ0cbLmN6~z&=~&UaK*owr%NIt)!Wgw zxy+vPw>E`JRuTA*cQH1AG9UZS(3Hrt@N^!F>3b#uCSQhJ`35X91S{lZ)#Iv*&eD8t zKIw~av8x!W7tAvcRQV8nV!{J&CL~&4uh|v689Hkd-9K;UZg`ERy^Wa$`y-L9x#J-k z*6p}j?lD_}gZDIQ6z9pLeDTXZtAn@?EevyS$NgUI7&d7Te%OxJQ&TB)&y`!_WY=e2 zjpr2MQ_sE>Cq_0@?TSBc7oE{c;tl*cd;kW(Z~rXkDL zCKF`FV<%s;^kx!xU-rgU#_MX`mN}*e)7VZDNt=+AIc0GvTOFjfCqCXYc+eew6QewvfMk=?*e5jzCj9Ne0K| zH8}CT+DV6KFcz+(u5Ls^wBIYS{f!RcO z!XZe*cuf(u^AND%5*gBoy?`P0_V!K!Pd^Rl&3G=WjQ1B&U@ZZDu2gCM0+?%_Q&4z< zYs`IkHlQaukv^oqwY3#YDtlp>*1x%}6LYQ&kFVDHt(0(&UXAHfiBV%j{vSb1eD%6g zJ4(DSyKITd0)7Rl%2Y7DIMrSTpz-IovR+ei0vuJs+-j^49l(h&8#P#-Nnjm^I zlJg6!tK$a&P+1wPMP*%c$FOu#b`mSxHcbrC3ZRX^61*?}euW166TalBQZ}-hA4kUa zBApcf3O?blm(+8uZCYLNSIR2GM_L=j(A+|Oi)$--0utfla`(4naKr2t{VlyOAU^DnEX9Ej=nNQ8|5wlft2t=Osm?4 zO0BJq1Dx23k12e)Sr&|d8*yv0z zE@skl_saFkxM0AyrX|`gOEua5C-IC%w#$DHLcNIj7Z8e6+{_ja#p6CSQ!#7tref2( z*!Jd&%k%+Xw4J$nH6eMLP zfp8Vx<9;C^DtP$K?e@Y8L^Xr};DRic6O=3!^3^&Z^*3$s+9EJ{wFqJGwZK6nOrRhx zZTVh*JSYx#zaYA(KxIbZI zV*`ztGZ!3%uY0BGlla#JE;H~9imLO!(F zzDgbV4U$le@6Sq$2ZvYKP-c$@3U4 z1sEUX&Nim2HAil;VySe-1eM>zWNb?Xb}`oRy9mqNl)yhIv$(;Y#gf)zwK)%mGV$=} z0KipY_1h}jLK5=3LWxIP&{`^pU914%U7sDgX- zaE$I57v6o8EK0b*$9N9_;w#@P?t;YRwY|`uH38$z`PE)Mz)vuMHem^<7gpNI+;qXz zH8G!KH~>+=K4`gA!^|w-Wqb}mrS<>~6(_OJ0qw`y006ne165(Qwb015l@*KKX|CO> zHB#X~;*W{^F6%Qj9PrR!fb)SuJ#KYRmDSoH7_|XZ%)NDx8VCLwo)v$*JrM?9Fv(`E z1Hsq#Eix|4pJ0tOMP$a&`TO@gC|7VuJ^?`#?QxzNv%XT9B^=WT?(XiQ5)!ln?8lBb zlC_11eA44^zUY#(O}+1uF6aGK6$vm9oF(CdAtr@A+6$|fd7IS-GScloaOQ49|Eg!&`*f>CD|EzkN78vPSHx_VZ0TU^0(#k-YnM#GTl zK`JPiZ5qwIdyo@Bnc!9%pK^0n_Q&mG_KPy|j%Q3jhiv~fe`|MQP3J9_@~2xd=bA>a z)}5_&8mh5_z-?i0^%*>V08AHlbauXc^X6B>T57&P(CWgc;}#@vWiqa#L<(q&gM4>z zjC95F1z#EnMCeHQ;AeK3Z>cvW0oMuYT%R9+?n?r=UK|1kRgvKk1^Be>hPd@hV!$@| zDF_FQi;EjNgnvgR27Rixx2i5~G-ByHfkOcfN;0=A5MsRWy$WW%PMl0q`EMOzlt0@2 zq`CqV*vuDvQ)})VM?op5ar9 zu~FSa<+25m3|MNYjoiepw}TV+S*87!2}>UCYo0Te?u*^SSpqBla@?}G`xtamwL-Jp zt&+8jcLj@l2Cup2{DT8sW}fbqDSto>wV|86wi|FU8y6NXPj9eyu?AETWN*~b;*hG| ze>=`84`w5Fr4GQ7h-LWceuUCX$q*E`C#V?}qhk}xxa3HC;e=7ZF->hx6MZA15p$xT z)~5prx_?;d9es2s41peI9E*|j4zxp2W>M;tW1Oa#MB>@7NTLky&Q6$3XjC~yKefJT zzSv@u){E)=<}g$LkCXnkZdM-`OFrg4pb)u zUSQlM7;0MMG?wxK)u|c2=aEX>;`;;#4!RFu3@l|l;UyBB0`L!?Iyl0Bf(Hvu2YgBu28J>QL^BAG;_K?`TY^PfATgKr9jyi| z8cebTM@9;RyF-x@?e)o+CZbs?Kyt3Ztpbs~5^N3u0Y?oAEY>P@V4ViGXb7ByP>xlt z+c9z+5sO0z$lCy%FOLg_WURFuckMk;%sZ7@AE1!{XciRU>$7eqIVZV|}ED%0vA zNP)?y`kZ}0(B9jsd*OxIsSmO?R!?-dLMH2H>Ni>IskC6t1X+{>qM-w-a^_DJmpun~ z>>qzj+%I~ppJ@X)avKgOTCgLrhe%lQ9L$!^sV>X84jkw=3B`NKkLK;3tETBHiC>>l ze}sYN@o?7ac>Vof*tv_^&W#4Aevk1sAM&&lk*2)7^i+JI2C2Nbnxwb4>MR`UG5Id; zgO|x`)uQ&E6#wZ_K>dMZb6#RMit8pUb14 z0;?!Pr$Cu3ucH91y95%^8LNi~IRm1X$=K&-U-v|lWMs0OoPc+Texz<@*htWLWC>jM z;Pg;ahxdcw{He=BRl-<`eSODah@a_jvk;Rg5N^0svnK3>*9|rjeF@gyn3mB);KV0sJ=eF?$ zz$+6dP+Ymf9}hf8&qA{om-#$GAK#hUccDiRa#q%GRD62#<=>d0VPUB8x+{QUYn_`* z1h>e<`n%gW@XJClgWVQH)(5VnmF5fg;qdO+?u;7DJ_NL-ELXc@1QVU&SPY&#Kth8P zHLOO%zi+Gf<5s}+_z^n#iVtPNJP@Ghf;#@G3%zPNS|OiPWJpLOe8mU!L-3(e@FcIP zsZqYclk~uDqu6>w7L2FbF9mRLf;c{gy02S1+3GdyAQm15JSXro5$KE8KyidHjc73#| zsJ7?oXnj~-yhfPtJ`I&aWzdrVLR*p&bPJ2IhVzBlufzL8)x@9&;LK~9sM^gWNBa** zB{kOU;b+-Hdotie%6lJgC7-ZF+7GtcsW3C3HWGTpX1ba4_*asylC)i^5u%gSq^m)~ zJ=;Xa!?*Z$n-6myWu+_+%TTO4fDJ?#isp_H145H6B5xldCB94&}sRkr^ ziyp{)8-v|UsWYQLkhob#`^&$_e)ARcJgdgrd;H_o>=F{``sO?6Q&m{d$w6VOsxNAf z>dMg4S)~<3L}X&db^PrQLbKzq$uE-JL*Zq444I-O&oxZnqqAytom^iUkOjL$qZE|(5)iZ7!FiYjXQNlk_8Kove=i^n z7)2>P`)e8LYIeJp+Ldn!fs(AHreA5AF-}h3=6Le8ljt>zWInGf_U#-?SOMSj>&jvj zsM7{bIVeti&qGdA(IdY-js6T~MQA?*YJ+W{ypAYuGyB(K=KObhBUU5Ct5>Fai^-&f zmu0m@#BslfQqqj&IH<3vDlK`^E=X*+)cGm`X>Bak8?f1{@* zNX$4f$0*`+{B+j*m=(HKd0TaUgJrGtVmR)QI>E+RcBx7P?nOdnS(_SCi)IQ69%%k` zdj1@?Ig&PzYiDtE{M@$D7YqZQ-HMzWFOglBoJfN^-IvA+xq-hSFkP;eysGt=6&J(; z#ZfKiU1~nH4b>5TZ~$hf<`fa!5eqWw-W^ZK@p3G<0C3+h3q+ey=upqcrlfUN2O{(v znzoOfj3I;avFwPZ^14-Mh0fMHzMCmyL(9Ab`;_{;1WwB~%yz$KvwTW!wt@cqecknr&LptAr>(l4GrNB9OtNe{rD>aY=+Y#&@2=9iX) zK;H896jR?y74b5#TusOBfi2 z87MK32KUw9Jw4>i%%NbZ7YrC#8JVZxQn&*2yS0XHj~_n@x`E3&G$5yb2$~1vmOqvzb_c_7t`-ptyn0W+$v%S5L3Vbc!9o zI0`AIIC@JOe83STa9T^>oC zAaGoDi<9whZI#w@7-WWpeyXl9j>916ucWfC%)BbYH;%nnJtNMHzPSmvcjWB7^pc9( zKm4up)+x{Q5m+}s6jnLWr<4yANfmN4|X|{KGWD&R zIA8BaViZ=+2&T9-%p;LwYhz4U=+2ffbTGGDHIwo-d*|%Jk@_o+KF=t{6Fbt)o1RX! zUUjM)==LiENqdJk>r=v3J0JS->Qte|iG?ZdXFW^|)6pV#w&kehX{@MLW2=~MBicb# z7Luyn1^nCByQu|keJj%|g9gVLE{@>H4w_D_QSg-PR!Jy8yUN->HmBvp(aRY_vOP8r zUzm&UGSAdkL9#Z71(`K9m#>xL=XY5cG0p^n?XHbkcCwq3NH+sU1$u;PCBIiKC1kJZ zW}S;ggH-sk)D{*Fq~<55mT*Xgb$avvgj5(RiR+oWtBCtCncYg*zmyHmg1!Jf8SefJEB`|MQ zCnr35Y+ll*aM3u#FLmW~RD+fud3Y%@t&TGq%D?`)g^rhltqdmgCIq5c(16Oq498Bc zHp$7N{OqRJHsHb>z)y{(AL5%hTz7Khvs|W-OW}qceaU01 zswK01s^ z9y%oD{3oi!&rf1PQ{(R(#D6d6dG~KzNpJ$kU$jGu`a8#eLtEDViF6c-j;V(H-ygiu zh-&ZAuGxP8UvfZL#cPkxmZE>5ITrZ#dj>jHJ5Gl>o0d~{7684r(&^2x+Z4UA0{VX)-agXqqV1N0L>WXgEN+cwd_38H* zeN6`$ah+Zcb%F2GSg~(xWl=pfUv*Y1{5OIQj=;_5*-tog-uZ<)N@j3OW`@Wq{NDhU zLJ-{ZA@s5MU!2L)Cd7Xlq!#m^4_V+y{_pge{{*+tG8+|({-@8ux)%52-yh(5VSr1U#KNu8efZwAK z;7V*@;6?!5z=sbX_Gd^EB{=PJfra{~+#C4T5me;;*Akop0Y*AgG-s9BohXnPrQzsP zT3X6e9`tVjMJKq_$}V%O#~QAWOp<_UMu3OVPK9>0+Lzp1!Iw?h1uwv)I-pT}G}FU! z7;Z@7r2z+NM1ZyTVXv)hjo}?SAYqrT4d^vIBdL zw;8JEESk6M`B^DCuh<#^15!c&QTlSL=rjae7z9qIUdFl6x`Y$XTi?Goh@uAMYe_LoD>`ZrsHRa?#n`>M=pDA;ej((4?y2V zsqQN~CbC@!f!i}^uOE`6DvL=AV3D$~6a6Z*GZluN^;m%?enF!Q1=-X8h1N)9%Gk!B zC(_VtL(V&rL+vF_9zFIb*UK3y$$&MoYR4_43rD z6v}bmeaoV+86ubGeblDu#@S0$>owy%Td35%t#pIiewO=^=M|8lQ?qU`MoT?t16|wB z*Q+~Qk%bl`_n8M}ALV2A?hh1TD`Z-HH@urIjjwgP>4+FFL69$)_;yA1Y%QFhfx~MK zzh`;9&Q#YRT`o(E&GFbNn%>1T@*`}ek(wnEXG37*2#5d3Ko{QpyW3n^x|5-xVaLJZ_>Jc~E{RuM zn`EO0(6#IhMk&YV6CZWl7*8Bd;c%l9bcI1~rQVwJMY?juZu^JdA0k4pI=?_3GTo=K zzr=AKV745D!1gx;PWyxydLATcbk(H?Rw$c-rynfTs{g(rZUq2~g$dQ=y?>`YdM|Q5 z({Pg6861v{EFyCL2Q^R0JhK+_>Y^%Dbl_Q?dwwvpg}R``!*)Bm#(JX}X1}qK!%A0g z_XJ7YYpbTtX-Pb+!CbVxl=qo*oGxWz=59RXA`D6~H3LmCGzy;9@{4;*qDNmu$Xzv1 zBJXsxb}3LdxD-ftv)`+~uhqbEx|?lTtYWEjJC}o>C zByw;%%;n5^gwK5jiz2JP{-)z)``}Cen#F+{&KbH>=$U}#Z`801EH^ICXJoa9iT?is zn23|*oeKLMw@2@TcIL~xxhyQ%AaWKzeu(@pVu`bty+k!*cMZuqej7*oJiJ%4DvoF| zzZ1{}EWd0u{W(R}kX%(6q2GlPSKJcmDL7f<3;2nJgdH387LR=%lx_}3Ma|uOALGCE zLAkx>e9?H6mhpOg=(_w1A!X3E_V9U7G_MXKA2M%KC|9Dn_1!76kMgw3tz19_la7g< z6lg-V2fq+{gn^L>`myj<6Q9#5XZp$MDFsm30P*xT!{rsAY~efI=Yfhp z4lm!p4v;{%hUsQA8@xID`eBgMM0!d$V~zc05C`Z$0T=W%CTF( zYlYi3K*J1-2jHL}0;AV%UU9|y>WcniS7}nrH3@(@6@D>g2d@0sQ3d>JDIlr)KixQl zPO+w5$0n1Rl-#{)>$YOqsw`|kiZx-^`Cc$PLbGCn321FhWz5@c#`KL|GQ>{Uj*Eg{ z*f^o9i52%(`7BkCcrzCPy~{n%~+QW>YY?Mb`U# zSl(;n39rw`V`x~|Ir=*6N`OB3Bw6;0sUsS&4u?6R(qrEniR<6E9eWI6LWszoX9l^w z1|?bxImZOIFH|t*{yL{5E8SDq@`(M)LqqRvVW=?0Bz;tB4Cqm?!HEy@s{N!O%dFLI zL33c(UmQs1@`2&kYQdN0cc>Ow-C4o@2j~eWj-FKIOfA+O&Yzv1jfd_g9hTO6oBD|O$ef{` zrYHgsHEz4;eSN;Hp)?}b+s0wYL{uRXv=WQt)297B_5uyjb`6aF#!1?Wkaa@%DTv=;crkaAm+_ zE4H?};Hf5{E*M{z$mhfk-|53OFXKfz@J%^r`#b>pWq7IyJnaPJ?5u*25$D4W%3t#3 zs!?F-To-ig;H_$69$SAvEkuEi?$j(JjSswf0Z;`?P#tY*Zgv1MgiJ9K*6aP>fkO{o zv`|wcwy>~}i03S7nPQM2*CYq0OA3ALcGuxQOfZf3+|=Yh|4jyi7=h)U^9D+vklV1K z#FG3SaZc(9y8MiF5$-b`3fA>Gu4y$oeK6exR!>cv|M01dZZ)hNd3BkPQJ&_f7<#=( zC%u$ax=pCk%@BTk$U)sE5zxSs2tUxrZ#BS3*i)=sH44Edo~QWg)yzfz>R_o-A*G3U zs&tS3H7ACo?_cpT?ILAjC@DwjAn;1mZ3oALN|R^Ec8A6cUk|XahcgEr8OK9kpDV{hTx$R0P*vD z4VhRG{qhfu3(B2js}}n+Z<=`+rb7LLC^3uKNBJZ1>%aNZUaKKIf59FqZh#@1^C?QU z6}6lh)9M!IB(AiKL5?~CbQvR$KD8PX6QaSBf2=hEiKN-K*vS_gY-Q!JOwenVu0B>; zh9F5!MS*s(c3JpbJMOhXf&-7!DJ>u!z*1x8l$}~3S2Tk9vv*)1J!=3^sR01b`D8>9 z0e&374m)YoD$Tza7BV96U+)WPIIQ5p=cKM2^His(&%tq50-56nJ_vYp4ZybOmhzxrSA9P zC~o+yd(iHmBW5)|S3Vby1sFr5y7*kEL$KWHBu*_Zf9oGwvKUTlnP*k#_03Jk9aZ?w z%|yYE6yOa^Ci@!PZ-j+O`%srS-lTfNsbQa_cHBWAD>9Mj%x7*E>NA!Dd-5DMkv?d|j8ymG4G75A|Vl8Xl3 zT-^{xx}Zm^QN~nKl;QAc9XM)&BVv5Pi)kO@(udTG0e2t$D7(Tn?*rfk0REk3k^06I z$eh7oiHl73v*Z}%Vy;R{1sf;i0s(5|eJ zLeyE;dn+WqZzw@X&2`!0E2JQJNKG(uO^fM&7fVAk=Yu@WXYI_mWN>I{#r3QxvDL~z zhAWBigosCTJXV52-{n%EP{m>KVyufwWz6sFE-nmt)WUhs2q_>zY9+huqc>k`hMwGh z9lOOx2bH@kwI|!t4L|MN-sf2iYfX*PuQtW#_&exO;NJY;wAy^?=N9h{Y3&55clpGx z>Rj+Zbgt-KOq(i{+eYRM&U<0u*;95|Sy@prvEs8NTwP!QRI7Ew1&GX_$$QY=0%&W( z(4qVE=G7wj0}eKY0O2LcjbWqq65KJOG(7QxEC0-Y#Nmwd!sBop{~m{v7~Ue1`TErq zQybXGF3V~+_Sx#Ls4%JK+B;EyCmKDF4-IiydvdtFbv44pFS=!{<#gi|qa(-Hmf~$_5oh2@s@|WlG|BJM@fU2rp+eQ~4p@4uWAte}eOQ(Q{(%mf}jdX(&ijpc_ zBHbWT(%mJ}NH-!SUFTkJ?Qeho-sk*doIS?7htyhY&iTas+*id^b-YxwCX0*BeMRfe z5G2ifX1lY$EuO6sk!1Th?Dv=4L$xfGcC9i)bCd_vi0@gXy^*8Xr$-Z>nXTdZ)c1ov zr14H2&ct)9w%C`#Vk=BdYVEtbo%R2MuV=3>hn&8D|I{pFM)S>XYt&-$x0FrJ`&Pze zkt%m9SXR{wi!6V*q}x=xxv4{-R7AutatBkbE5hCn+p4$2(5()=SXgUzDH>8j<4-WW zD1DgD-z@8$CA2bIiwpRPH&tGzXvt6&skEAxy}lu`+pP_RD=0|ukUr1?0w)=pZ#nOt z1IbX4ArkE1vg*MiS_yV=5e?Aaz^p0uxk@E00~XJa3EvEfb6^%wW<~FM`~yI5yVY-Z z<&uSUXAbt(N6e7k7+ucbjp6EAQ8SWnzt{=9$FVvQz!3TP_{vYcc)mTmAJg+t zw>!|EPZS2Y@+*Df6c&hePiR?M#N49-zH*TtT>ZMuty5B}+(C8&jr(A(yMTAps z)$`hLr%ohve2p0i9e=0y-NL^yu#LVf?^qqnPu)xW!bx03qU}t;FI$({6uchl*KmV` z7hRnjEsE{f?RkbQqJC9k`M%a=>~~ZD z4sE2%_-)H@{}o(28^PhMPc!yU8gTQw=+!J1q^WKy*typX4BO?-n0S=^>R$ZDGd1}) zW_?cP{VL!+0cMtN`HcB6woxh6v*bLSg*^V(=8W7n&NN+*4kP*1)PoP4(>D0T(kXjG z(Ec|bUNJky81VARkBRqXnT~x0Ig|GwLc_Z&-1v5kReDfP~%u*ER*;T{HpOs&^=V~5IhHs3Z&apH)J(6r=oNr%7KtS4Wg z3PW+!jOpo*R*O<3-gIi_K81kh*+b|g0LF|9_JP8{+Gu#nfh6`o_Fxa-#y`zDIXS^& zqV3szdvK2MK0h)8v!+L2@MDy$bEghYT1weUcY$;2JlHS|#)1G{ivvg94XhvBfW`%O z$XB3AaT{PHa8uc7#AfXW#OJHyY9k!$4q<=K1`IkPA_9&~$NL*y;9Q6d-Z`4_!y^&) z`+{+gN3PTMJ6mdW`uFDD})p?X4quAGW}M~aoXIEcvTTDPNh z#)J6`gU!d7lF8obe+Py52Yh=fzP4V_ThDU#XEVEDitBD<#G4AEly=!~go^ws9-TT{m;dA8WKT~BC>D%3S zziOp6i7z9a6J{;ksyDwxzOcUDtRKLrp8w^l`bTHK*VttnSFKWSaT1^No1PrJ;8dgB zDEJ6R!jk7|H&xW}RZxa0?3xu>N$h`zN1#P|rKmgH%`B`B@JAJ=EB?PQH^7?6^-;Uv zPA(eX%f3bu-0^H?r9t=Scx@Cx-&i0i?ANtP#~8$Y4|jGZl8uXF9!r<*VY#^-&8ao+ zX5_Zz{(rbVyj`9(qw|G}iZevkg zT(U``Y-Xu&Bl`8uV#4Ek?oy4MLWraau4Q9w&qyyBg|$<2PG#AyZ>pi1K!p@zpyJ?maD>&XCN<@E^8m z9_D(>w&Jkb|6`xGyP9>nu~6v-h6q2UFK%6*@!mIE*PV2Fl^mVO-v$8O|8e+Pwn`;KraYxVpT5t|457*HmCJBol;@g4S{?z5{BR{T%oR}C*KgmZ z!v65ZYU~|wJq6Oez?1=L%+UYrJ`jn&73c~eiS^gn4rSQ2F>(4(@nnb|nlR6L{bfxuRm1x>(xCLgd@k73&}Ib!z2 zICIke2KF*Dz$Y^|0iQJNyZq>O;hn3=?6a#WAN93+N~8U>4{cOgG)L~yX3eBGyEk2b zIIvCRJs#8M>#T)QHWL29)UY>BaITR5+x;sJ^AS^_yvZw;Cl`AjxOvkq9?!qpcjIau z(9*6m_!J($`x$&E=hBGT=pog1HMa!IyhXxbVoUcIi6w7da1W@7U;6AasFU-me0D&c zd~?1Mzw&KxuKF`2N!qFP&;+j8#gvb>@nkzLdr(?=Ih?cnf!1na=yXk2S|;w6|A8(t z-10df9aZQ&bt-j5Y1IBr%X7luF+A2Ov1qYZc`-&c;5N}IVVdI*+b$>nbog9qm#kEv(b;lj6ko zitO&mB?T2GTWd@WEnNEWBaQ? zp7q%4eQol#Cw}G^Xt(w=Z%70u`EzG+P*OkG-*iZ2ExxEVGiURRR-Dx}To0Zbm?WVzljzI2Tg6NNsUBkmbdd-!=Of`=O~NzRRmPE6 z36oZAJ#Y^=-9YB1g#5%{_1WM*!rp4(WsQDw1b||4NJM ztgVrKoN0Hrliim7LQ$!8#(XSB)Beo5nfrCu81?OcGZMII`zPf4y6WYS5p%ixW1xY& zg+g`m#}D&~GG>t7F>;(0)}23rV?DA%`+U9?yj04XPd@x3l>bl0?;`) zI1+^2YijFxA6P`pP(K+@_|TV# zS!)aUGSPHC|Clfw_Qn63Z*8vun;l4!piN?;pP|Blbkc<4hQ)3I{@?it9)w3EiwzP> z>fN~Yx9Wegw*-tJfT{{z?*?;Flhn}b+S_vg)7sY;k+}%ww{Q+5s@MR_P1M1*wzggdnz-$Zi1!MFC0+)C{-s}#_gpcf3*dU<62Mu5J9;l7vQzk+o>Af0ht=YnXT zfnWrrCP-r(SjIUmzSAL)QQV~#Lq7?V{s>{(7>|TQ45vXo0x}jGfvR{2>`Un{`u}|N zUso1+^&bb}PzfibrQJcc^ugoId^nF3%qq*}pMcY!pVBJH!YHILBF+7#+}D|rhSiFh zaugtcc??XaC;#KsBrXG;G8D$mjl&<%pSRWGc3e>iyh@>!y-KHMe^4K0Y)A0Q z70d5VNK~K9AlSZ=!?XOIclxJ}|NL=_+Bt0>zWbZp;QwFaouGs8-zXJsk6r%FpyIy} zDgtGR{*4guFErmELLL43zajne8y7(e?#;ZD`QXIhGo74<*WCPs5T@-@4<6Juzx5q%4w(~`+CCHXGW`0Ivfs9 zTtuC%@-iMda6vo`gcanCrqJFi-qMH%l)Nx8>dh1w$}pc+cGYLU4do>pQ5h(Xh?`+x z5d3k&v+T|*#*T*<`xl$+Ra(^uH2$xH#l;u^|L>~HFpa4Mb4<#J7Y_g0=cu-lE>I@@ zH7X&Vdwf$YCkt%NV-8jME04b=EAVpxI3IA^CwddWc?AIH)dnsAoY&MyWc7*vt~8Jm z5f|Rc05Th721b`jLfwqk-lh6KZ3^fJ>#VAssv!+!#VcP%=gF6|*7fbR$s0I7SLFN@ zctC)F^vn3ereFd5GMp;vA%^xJa|b?eCpF|}XdC}C3g>X;x{h2~k*9}V#9{>?s>kIc z3ImVK8QTQ*5`t@s$*Ts6i{ru>%Ir^9KmFujZYxkLq!=xGEkw2)9+@NoknJzGLu=6B z(z98Ai{w1rYm07fO8_ncN6jnQPqKv(a^}FC6j1YN*%r!e@0DupD!(GjkCQRz%T9Ow zjZ%wNu`;7YEyvAiq7b`6tpGIf*6<<=>49}eb8$a&+nJ${SKW%ACnR#jON*TS`jFAO z8>ZmU`0UGz$d1>q7n-H1!fP)yvW;pKHKPrEy*KWEu}%9k#%W?Z=EKrWTmnV=Z@X%} zy~!f-pff@;qLBHmpPp9m)Gd!+V@-VHl=ZnpXO_F&YK-D!0!?MW4(#=!Fm^PwxfZLyj) zxi|%;=Tyx2l#Y?iy_T5){^qK?ZZpQ~qw2 zUOr6x8=mJW>^8F2YXeUNuDoe8gYj$Hx7RBH9{=CCyu-Q0q!saH7Y3h((zVOJ9^=ne zLD_=@L^E}z_q zo-tN)j(OEuUncq0^z7Kd@HgXjiG8cX2sCZtDE|N7kvY;7tdp^z+fEN;>ABA|k+b|Z zoevB#lE~5+cSwi|WN+FoT0yQLY?$0OlTsrEy4iX){IHN2gOo+5)-x8sE<#_ZXoSxX zjgvfg9)rjY`5V(d7hWk7Jt9{2f12_jEpFFF3d4Z?3mffS7M5P~8Y-XD2&Cr!*DpCJ ze-5Ds@~eIG*OX2dm`;!jn9TvdD0z4poIpOBTRWw!|9+NjIPx3~LUMxYEDSrAbdaeQ zWabFF5z!OLn`)<#U4V;0!@_$iTsq&v#vkK{H}i0QY}^mp;GY5}G!WHMIPseVg#5#- z74u)EmAN87E>FRYl*|9nLj#G4qs`o*_20_vyvlm(4^g=-$WiKOn__YX0&a*iN4G55 z-cusd4D=}b_IW+#g-{!AbEbyIXL@2k0uNG*QD><>IEsCm?_~KUwp;$7;b@{XHm?0G zgt*bs`0z|NoT889&{~}gf3^X<+)P$S?laqkR_rsi%oUDe&c^y*mL^8qlFJ;=?~XMd z_>8iQBZFvKVl?(#C_^l>6{8wzDg`3i5FjcT{h}}Ln2`PZf!<(#K%g#MqmVhxY)*iQ zw)J9#ZqrNSjd2Hlc%+Y|N{gJskfIoVo|+W$M}LNW#C(1`NLl!H$nt-~xC4I# zusAM50E;@VwOAjfex_kON<}sodPb$=FSgkpccsk7Jg29A+0&m{4RQIO-{t@GefysE zXv1m;r_`abL-Dr}*ClFuR-L);mdYJ(1p8WSi3sXE(F|EbzhqwaFuz{x5cS-=;mT*Z z#QD*fju?j>EKV=T)(wfvLt%^CwTz{bv}S zWD=&|;C1K#ko9Fb>CLRKtIaoW7-vY%)HzgCYIP&Av_G-m%$*oB-xXd?Lse{HLp|1} zKg8U@L2&_j%0ySXrU#2n#iYaQV6=+)o!2M_G7b?U&PO^Wp4M`JwA$p8y8(*HoY8p7tR+Os**`5f%GBDE8{hj9J}=B9wfNfwV`5uPqmoq`b~;Gam@|^Y zSF7{$iWSSgljn`ek|^RiF@gJ^;ncSOsTaSn+^n6CGs%A{8L z4a}Ki`eFXHBq!}$)%ALzwJa^nvQMv7zkkht_){&>CoJDRtY0cdl zuRTdq*$ZhnwNW_dFZSE|DrTG<-aPFwHLy-O^N71?zU28n-#1oq_4MmDGw1XUs>0A< zx7D8872D6!3a_S#j^fI%s4yKY+LNsx{&0KWQ{Vb7ei3_X-AnAqYkKH1^M#Mdhw^7a zo!x5nl8+MExUbh&#a@aQ7x8MGh-R2)O(~)zK1(z<(3Lxp&DnSFUO62Trmd|hG%>5e zNDXfqmGMfdDK>Yje&T+bTxaW07}4I<^KzQp77N{7fz94?;*9qDdB#Mh;^m~)=^yPucnMtZWgjmR zdE0VdAFfUQzB8w2UFhaeke7a~oRmbp29@!hx_9%_xl|&w?`%zE4mW2v<|};WvA*JI zU(S8fEA=?IK3hoI;MivNnpk^VYAe~>gv3N@d@Otdf)|uR_otg_XlM+~%`Y=DE=m}n zq3y8`puRv{dDx*I`)z*@9k(ryX)&Zt-{&ju1uvN3g1ZNG4+2;-|4It^L(wu#w1Ha(u!s@99@BgEOi zC*{PGUXD28)?Yt33ol16)CRC3I|32Qua@EQK0kKwyHwWhabJjS>`^$+PetLm_fuKI ztXWN+UsW~CWJ8`Pyb1|GOr6{`P8r{9Sl(A_+q@dxNjx)s;@`_}sFNo5;a1^i%)G6e zCPaImiO3N1wVV(1gwg8!Y_|z)&lu8GTlK{Zg@{n;PG@C9?t7GAKPzn0=QcwTt}d+U zYj3`Wnv&EycgJ?R`em_Oz{ROo-_H}=o*KzdYVUgyh;@d7b}5h0+%}#__jzU*FwNX+ zB5y}CP3# zM%??$ArBY3q8~xHB*e;KEG#T!B}&W5wSosxKeQ8+G}*tkwqgJeqjA11Z1(5Ry#3jg zm8?BW)9#oT!NEACVZgL`rV|~FS1qHSCHzjGK0G4bH`i;n1T9F4Z%TiJ2G<@vJcdU7 zVy`)p+V|{KilIy|{)pJw@v{97N+rA)-Kg?HzP0 zr4aR{Iqr$!uYE61$BVLHa{u(f9`n)3{q&{tP&%B^SAuzyu+u%SMz8g5hvE;pGt$!B z#M)l>3%>1HuMIEvW17+N5i!rFvk7dHDWaauTq@6xH+O5Ee$xr@AbFt>78yYOt?<>y z>PO0@#*moQw!Th{K-?3dB6Xqq`0`OnBlacK54ICHt0NaD)pe-Iht&Brd|U0z)=D zaDnbyI5zvgdSwhCm`15Z7p#dN0hNif`l_O~CP) z#9x@fb4Tc0!1zmndd173F#)CfF2u9(aTrDPv=W>9*IwgZsyG+rJGiZWMW>22K%Pvz zVsy2kSL^k8QlRUp&i-S@gG9WJM}u(~&veA8hNDnD5AsQ9yijZ;=xhs)ONmn*N*WW0 z#dj5(^zf#KIekk55J|EUMI}UYN*c3$rgt#lqvS;SmX+auQbJE@B`o{=F4oo!WicmQ zPqxLbFe9%CttKQQB3&W3iO`)iRraiL(#&Q#sBHG# z56fy%@|e-LzA4s5GGeLjCgd>(WSx?B5zmaA`0teN_GibEI86-&JxKiEL~|#DZL@ik zYh9v?pXPqPiSL_5|CI?vP1=H*T*7MvY$?%~B`{E}L?Up-ixH-+ond|3I-AlT*gtyi z=#M>leI>^|?^UN-qkL|gOZqdl2}H<`--gEY60CUa@Mn{*S>4Ctk1l_`?^8!9J*%dQ zXT45VKdyvTXbX3YU`{E^RH#7Xe0Rhcb{nrjL#$uA<9wI($p7Vv2U9e2%V1 z9LUWsW#`-FPoKZvT_YuH$g{zX8OldNu-WIKmVD*9Ra}COs9;G5{;D0FUEs5`%tFF9 zp3?d*o6XrtY>4Wlp)8tbZunAGL6COM4d-Ji@#*T7=wRYU|q6svwHAk2-Uqa+~LhyhO{k8G;# zcYnwe>_}k{iZ9~k*^6tTb5nFY7_JIhiOLXTlbKa6Iedy0nCh_GIQjl04i!;G)u&d)cTRF(^t3a8rPi&` z6R%Fa_Fmi~nJWizVmt$x6MTR}Dpl6$@zCRykq6R8Q{gm+oF7>03lAA>M`RYs3 zk6P{+ZWlfd;lI~v+<&HpQSlS?qLEKNKH8ig*~RxvwE}}otI5l@ z(`mDfv!$-_u~*_5Y*si8Ic2&(h~sj8dv^=}demn8Z{jWee%-yJz4zL7XA4B5>b5UY zls}wQIQ90ImPNXM~HBsuT4Xy7BC|Bs~^xUXJMO;HW zxNS9x^V&M!;IM!i6T!DF|2%hs?z;{j+SPeXnger=#z#GkUCPm_BX`am$Z2xzvwjIY zsC?}5?2?T$=~eTHhcf56tctJtCL_e2B7WP@zDUvVZR=ay5{NlV_E@R(WtHA9d04M- zIik;MG6$#Zw&w?@_dVN#{O3%f+b6t)ohRsL!o8P_)zeBS=2P>Mjb1$V*~$!75965~ zI%)peu|!fMn7BbgWiqdVJr%j#%w;R=N&P4<_E~4uL1{gP~3+^7CBa89T{jlL1vi66Hs`PX*@MMHT0lElrT+~j`z z=eK7sq02}8G{fGjCiv@zcnW=Fe>wRQKBGRJQ~c-4EdBZ!8?Sy+~_bG zx~(|=l?>(!IhUOYysA@gn2`YLQP{t3#1`V8yU6>()bU2xKTpFSGiy2IPYA2=@)dOJ zZ@T1bZnyus2+EJGf8X#e1aADDKfi5Jkq_m_&TuJE~m^LF2yguiG<7L)wM+)_u8XI2{l8TfQmF{g@ z3!%l_yu5W9iHgbcIO0(3U`@;^XSJa!2rDWBwYuA2YmHhN3L#tIAL>R{APOXZ;bc^7fw3S}%5ly_rxHpQuD!$(x(L;42 zY371-HkQrxCJ@eQ?r=&oa8uw;syVIBW!z?WSY9%^U&#D2MFM8*!l>6h%cI?45~ zG+!+51jZI4`ji$AmvvZ@?hr2xkDz&uOZE2;A&%WqB?Kc34`Ruyk7S(uSYwYgs1P3= zurF&>yfvUBn%Qa5PMq;$<9^<9U$Kp~yH*|9-j6XACqc8Ysky5aFL{*R=&=genNN-c9je_>{JG~FtA7SLTJ zB^dJsL0aA@!pAzxvgYPND=bV20YJ?_{wVf5vWG(THkg-!VL=PX0!qDQy}i%P+^mI! zgjDi02#$|i%F{2TTi=CuEh^AGvDF-Q?{!}p7W02!zPo)Q!smLf^dds{4jcP-?;7!k z)WS-e z7E@*&hg?r>rZxPz_nJqY?qM=In?8u^Gsp{L|GnqvBkQ+@u`(d}a(=|2_~#~*ptLId zq&}?lIdk zc1bnzIS(5s4kEE8dtJP%!tFh=jp3$bAXYfnRi2WI;_hwvI#u1Fn0E^|DWj7;C7NAk zIbqqi<${F@cmRg+$+DO@;ob4gedfZ zsbt*ndMeeVWNMV&q4_WULzCyXm>5S5HeL?6o-sUh>Y1`;++tf`2$a#dG(B`OP~af) zb4UM8zxJ{SJ!5^{@kcW&|L!8X$z--di4ih>l?U@p@mp)BxH>k!MVilwaeu`VeG+>W zm1Ak;;nrk*gwxEV6V@f`J|nAfrItNtios}vYNPj%|NDSYj-z#fWhAYYq@gp3S%%tH7AkeC8Js&J`0cJ}s-kb!vX zeTT}lz`c7IU`7!rLGu9U2hZ2O)0d8T`;0z?Sr4Kq!S1b;PQ>` z;^G3Y+0@&66`H6I)YPKZJViwjOiWC6U{VF9hlEDOBw&Z(x;=;f)p_HJxVShkKfe)> zEcMg!v`4t=_g-;KzWG4C$mQonoYo%A{!FP!bbT*>jpP=?gV0^-BiHS?2U|U!F!nwM zRP7w=&=;*rv4|NjO39jqhkyFnQBpGO7Z9}1vmJ(9sdYTU!{P}#t1l9|{8Uosh^%*UFF@=-1xI=ex8%AbmC9qP(6AX z)}Ie*jhB>V(~2z+^7T&jJnFPW57mvHTg67#8e*=lmGwePsE&Pg5*8_PF-_}WXv5^| zQQF7J){&Y*(pI=k^D_dcPw57ht9tF8&KuTgMnfeX5B1syv_oA7N7Cr$f@xNs&rE-xB2y#g2lT#~}&mXvLS*`zXJ=pA|ip-pW_E9pxJq zZRrdp*-B+434EY(C_BUzmMS*zMOM9H*e3YOaO6NvlS|f|0>yUNuZx3^n_Kz9X-O5Y zpG^-*@i~5#7*VGf!{mD|Pq5v^@${i^>w8>*@aoM=`2Pz}cGv zVhqxA`kq|EYltl}g4ALxEGz}CpMc6k=l0gMAiMciTxjkhJOBJ8qhn)+z}rRmW@XXc zxqBCx13?w3NO#=`{MTH!W>CtkCj!CJZw}0B6{~~=1js;%+yp^!+cOPl8rs^%;3)&G zjb?EED{|S?vl=ZzVb!ZXjQMnWONd&b<;m-q%mAN$QpAA#VwRSohf|)#ZHeE?dt|;@ z5`5%Vj_UeBSPE?2w0MI9gs7@{0Tw)2IKD8v$Qdl^BAm0bGM|f+#ol`5XN~L#vpcvs zpmfXnzm}o%T!~;rpL@T^PsZdfR^Ka$rzn4=E)WHOPXeROMc>#q71K)y<dyn=;EB=XM}?DEpiBy&D`-hTVR_UTI;IsV#=ye0I*NKJXH zQB7=uM1?d;+V>}6Gv7#y;Z2G?BkETCNFPK*ZU|LaieKHrS7W9za&{)gvDzehT zLqHs?ubZEitJ{*rEIN)~v{_-}C-XBUnI})kdfd>qRt9df;rQL;vhds*_dYu|gvf%N zKIj|10TPaJ|HlUi1T8HslSUDu?sNy+)645Q1Q`IW2&kBZz`nSKFo2fy*8cwR@!8(* z-wFi@pQ|Ru$F+v&s@!%>gE-~l?mynM#l*w};0PZXPYyJ4WMUpU#&Fd5w4H3orFI7Uvv@0v49W4r zkr6b0o*UG6Btxs^$;T|LvV=C_C)_OyL)CgHoT=ZAoaT*9OI$8kxj3p->$^2hQlAo1 zh?tpjqs6;4opc8Wz{=WA&+(b{50F9L^7YnTPO5b@ges}2X)d0z+k4%YJ6_rgmQxH0 z#goxJz2()2Iu7FD`A?dp8qtH^#`!groH@xozkm3Y>KfdNze#(u>oc`IsfiR=0mzV7a>Tne62y08Va?Yqa6Cl`9S4$_RJ7zUe$ zgT+m@!luDH{tEI`VlNP9J_%^iakv)_YQD*Pv&KQz47XSp)5nXeKSZ;!@dPN)1inb; z^FKar_t?&9=PES#xuz1QC?ZhHMBYebQH^2{^G^L85Y)20C~w|;!>C@6y}) zsRP`r+cY$&&d$y`fn~X1PahoKg6o@=Dq3 zpo+I2d!!BYdau|x#eI&7#utX(DuS4p80!)$T#@(I_$P6qlFy&nAbt%fanE!ZBcz@P z8N)6PVuP0hsgIB~0G)aPIg5U6FzCP^Fhu6uv<(al#K#iec>E1wIoNEIj+?c?uDjkn zr?=28zDu;gK!vanJBGwUn1FHXUc6#F7T$Hi2g*KkYW;R4_iq@?r%cNKazgVh=NsRR zyLs8M;A!^H8%*vsTP69PN7SC}_MxyCzurUNm`UZt zM}=s2hs)tbqdU_jg~KUZi?lIp4N(svmQ!7i-CuPNeTZd3F1bb>Z(|d$FzL_JENZ_z zz%uFcp5^Mic(k_2$c#Y=w@bSA$TbYSUfyDckbPzp{IYm$F<4I@+m|rE#U)G zG;!_o==<{^DgnC-KH& z4XD{jTWUjfPy}UF>(lLLi!e|S(G2dc@AA%~_a47NWl{b9>VZo6p!lgr7YgzHNro8g zSr=a7vE=MQ*#bmTt%8r&gNAil%ZqukWTsbd6W#UH1%#SuBYWcss5q7v(O3s>= zyVQ+d*s*tvpzGq{(oH#*VxXJOdDuCkhWEVBM62#q!H!euNSiT*zOvfR4p+(edac68 zuZd;<8|KKF`d?_o;C7WFdE%n>f>7f&+G2b-llqAd4Pr)1wZ`)1o>${x0==`5wS$e;U7`D&|KhXH{rm# zv{oJ`ma_HUw)aSZN?7%H5C6k~g6)jjvk~&b!dD1H%qfI9d--0W+zeT|hNVzz&6%cO zr~c;gWAoJ32?2QSuXI=*ftsucq`%G0&9`9H0*7;E=a_jAo`Z(>HPVb6nEhaXUtgeG z#RjqR2vMLDDuRz3sNS$Z{8Qn$dJXvhnpROcs<~pf@Moa!{LsQ8$0EJ`-BU+rXGw2w zVBgH+33{KBKxg_@a`H5$kGHzIx~rR;Aq4AIJfFw-HCgEgCZ0|G3T?+{3RffUb8;%5 z&~+4byiGYe%*YVFS-I9UuH>6!ErGv^ZO5rJmfK&Rh?N*eRB-M{&qT%b^LKwnfp8x4 zrIpc9gle9D#kGQJJ-SO6Zf^|Dn43cf-SDqmV&hWrUhxXN=`DPRs>g!#<8xfEQH?A8 zxqpH!f-2|KXDNOpx^XuOK0E(AtYJX|tqJ_-#w#AO!OfzJSHy+{X)UFx8PxGD1aB}& z$M*f`@*Cl~Rw1yO3a|-=D=GEuw+~iQ8*%3AI3?HJ11kHbB0g1CVNHL(?<>nk?Oq-& zYIUoA53{q93Tl^eFM7{$lExM}Jm+Dt-v{@b=a)bCeZE4e&w(tII&Wat#J!o-lhv&K z3&vrbzFZSLkl}5(&so0P|0xt+Rw>Fh`D!3O8DeCUxEGUy^V-KZk(7B%AI2C}@jt;o zgYP6qCEB_jMID{$(#H*PiyHGFuYI6P94F!hf`^i!nAVVhEg>X7)vF-B3@ z^~QBFf}d9Y71y;6OLQxu!$M`7vo^9YCw9bsZ_+(z)y9}DPR^uu-UE%W;8{x4A|3{ixiY#*5%=|RQ+pWq#NQiZ|Vb%c&^4b@05mE^a< zHmqYyf;2b2XH)w=2;Y25v)TI4(wud9^3gZ9tGEqjVk+ruRWFkk>eI~cNiQrtMML0( z$jm5}Q19DbP$(YQ&YE;`>Ik`Djj*1+b)R-U{j=_0`5Ti_EzmVs&_FkJvJ^Ek!$#QY z@{&50vncCcEcEHJ*?$oaxvOmWbIm_TWZ%!4)wVhRvVtyQxjW;}K(DY)w69HRfrJ)? z$=F`T;&*H&E;`)CB;p;3!vbY%=NA_I0sJ+BUG5NgJzx%biII^JQjzdM0Q&vN3H%-o z52k(Cea=0Zz%Ld910zc@6(bOj>Z<6G|7!gUG!kwrlDPZks8G%U$({&eHTdhyz+V=b zXDX8{Od%eK(*VClfRC^6DHswqT41^rS&eaku_GFspIebTsNGCGUQ`1Bp6n172k8_T z+}zyAgbL6So<-a}GNcY$V2hHP9cxCIO40~=WY_CoEYUDNa+_+Dz*?%Q;huYc6St1_cZ4`c<=xVZY8dw=@hXQAQ z2_$0&BAY)-Hm($flUv6QGt#EQ!a_Pith7;q&!qw?9P!v zEXmEzgRq*lMN5+u%=ZVK2XcT|O-0%^-235EtzPTQeVjAIKpf1b>`@aN&k+%IG=09r zWicDX6I=NF>4@ahj5>)MnCijFl_;h}orZ4atnY8R+OodHrach7*VUHHn33g`+*>1= zV!1hh@SPQ5ZfZ!hEH>FFZ13%qfST=4fBN~eAKQaGt4rEmY_=L?J-t@yUV08Kg$Uo~ z`ZFvtZZsopMv_{~b`(*$Q{~Au?kimCy}nI{FWSB0g0~b)wsyXo3~@caAb-`KL!NUY zr(pAq;^vEZ-9T}zrv!vMP6TXJCD$;h?{4j4crz~)*$1=VJ8MV|I>~K|-(uOUP$ji$ zqbmkP$1Rdr!E{MGk)(pCE9wm_FdPEcD{f8hFKOMEWlPVfHNImIPtX|3C?n{)TU8|6=_7 z4JnAZ`riB-acM-mZ}skPq#^lh(8);Xe?}p2m^GA`{wGZEub1z?_oF5CpD$-oEdGTJ z^%p(<3nrrNe|h)ce(RstvO@)Y!acOzkn5hkzD^H$O16da!`xW;qkE;6Hy68dh=ma?2fmaXP1my z9aHTh`eF3nUv`Z65;6USbKz5d{LeQ1AO9-2 z34R(rK#!FP1p4^r@Rg>ezT`0Qtq7S1aXd1e1v?0f-s4&6V=>{|*(z@!4pSvp4fpu? z*s6`1sk67Y^>BM0X-$g|b#%O+kdVLz9=9q5I;4Y{@@9P07bd2r7D6oeShtAYQeO*t z!be~@0nWL0OWmZ^uG^?r0>m~ZL58F8Bt0=Hi4tP44Xmy6oll|8Eh;Mu)L}8BkG1ja zmT4ae{Kazl2{YRDf_q5w6M&{A(=R|h{bd*h4sL=;RCQ$s_P7os0`J%LBW2BB)mdr!A8EJ~QI zl2iJ^(AKt3iRL^W!m*L}1CF5$!^35xUmMVInx6F>t_?9lhqMIlmZQm4T-=A1_KO-) zDja{7UsQ8*b9Ni!T;N801K6s8sj0V-3Z7yLJY?y&T}pUQ=J4fXELJvuyKuNd2>OTx znI|WRh>R>o3VIwtLWInVfmFBA&`iTd|I0Fv*%k{q+hAAGDuax0W5aO(#4JOv#+@m1 z@E2TWa7qd_QoJO2=UO%gtLA5aq^nHV>K6}S*KvX(NK#%tY+!Iu*@TkEhP(vM$WepY zCFSL2P;$1i;WWj>#AJPLZEj}E$jGpg9DID|8oQjFT=z?K>==LlOJ(z({m>nYfgl4m zFlR7AO3jeDkg;5rM8;-jZB}4(q6wRzv7uoD6EJEwvKR&i24tXrMw+6KwGWg!k`#q@ zXTf|_G_+XgsBr@EPX^Ada2dPc7|)6HQsRsK3W;cx5FYVsV;ZSy`Fn=FObmAPE}e8S}PeumNL|8jM_wCN>g&M>=?9na89E6H}<1 z?pqEAxA=cO1E%yL7!>r^c(?%bTE(dv%;jQ05csy^3IuaypVvSx1+qtqY==2Hp(7+7 zJ~V88O+W(vaoPlzql+e-???>7#3z9_M`~7XE`!HQQ%qbO2iyr`>R6jiksgn_=(~6B z__K3z8gs_U!PxHxx*utvVjnqVmVqe*cj{_$=2RXa7VI#wOh_bSOF!ndg^;yXX0DBc zI{OtV40h#OPqz%uqn&P8reedx@ym>}Bc$%gI68i5-G<&>Ykz;ZAxWUy>0$BOw2r~k zr_B-)5=c}Y8BK+Td6f+(^<03MlCt*$tA0|;(>SCg&lEVq$c-0T!5o^JnlNDLmiv;; z(v;{Y*oEIn&?xSa)ak!UO-&^Yl4vx&pAU;-3{*)MdV+x&S{#=p1~_TTbq9SZDeScAdk<+eD%~Jm_6`mWY&bSk)j=OW-eS`H zdftoX8v)M1{lhRmm{Q5Dv1Hj@7`}70>7l?mIVYnd^s=!{74V18@lJ>AqjfJ*b!ZdvZepMua4Un6~1}CNO z1-jZBabS<2lB4o?K1e_tcE~NT)I-)Gh?%vuH?Vp%G&H>UVZeVq&t3BidqcH$OPD23 z9b9B9%;aKdf8mgEN_yPpTDexaG zrb)xyn|%TE??CWj0R4{~z7-^67*J8<3LEv_{E4h=3kWgs$;tEFD{jB95a1y-Kwfv}{zlv)URhFC#1a z9Gr?&ZKoDJfqS233J_p9}9OC3AI{{OE6CLj1CKH*e&;7&## zjsv#h)o_Q(7Cz2sr2{Rp1_KM8PjDT`nFcm|fL$7;XJ$4{PwVfg)W9Bq+^Ni7CEQ@+ z;CKn#%L#Tzuy7>CxJr&CFE0kaNI;1S%SwOhBfPSCbB!8zE)Wcb%Eog)caE`D zgkjqT={dnLPV*hO$Gq`|1LYkc_K#XeM`sHvJ~(wG0&6O~4=^cwP{}s~WImAgm=IA9 z-hRjuxI2yuJ3BjDqu2;NLoTs1_ADbWFV7C5-$G^sVZ=OxGL%-m^efCzh?Me&r`anX z#Y*yWwA@y|bRJwLn~{qsw0BDg^IpFbmYLBys%7QpzX@p-qA;Cc&OjNa{d;pd*#XZD zVbT|#nMsR-i>tbM17f+w4ssu820-!F1O$J?CTe}-PF*jaYFflVnBqrj<%3#33CL~ZnOY5d|hvVSBH}cA&tWNxVj2c3(u_taXHEzjxp2$oTb{ZJ2nZnKziv+GSxr@ImSU0~c_O!f|EI7s z56gM&+W(!gR78eKN!kcWnJS5dBz8z8ga(n224WkVQ)o^8dSzeqGU>$ zMJaQ5KUcf`Jo|SX@A3Zj@%&-$2i^DgdtGat>pai37NUUIrgZuG^$DlvpD&L%S_XzJ zQ*oCZI(?cg*I(NbB%Jj2`XEDH5+@ovQGiy#vU0c8_U*FFi1;+RN65g26 z)qQ^zvQ`0M%zC`b!v_!Qm}Tdc_~J%MN#~3ekIlY*cqY178bkc;zqKLvwM@1k|6M3UX3?l2OCn>%Y-cREHs2qMZ>vyH5PnSk|_MAcYB3|77FdTq&9 z7Lr-lHUQ@y{I$9h{hxXGLoJ5?+9yjtpf1BvrtTlrt+{M0$;rqHf(|HvyG>qvvsd=o zj~3OVf9%(U8mW;L_lZEuh$mt3_x^UncHmC8c|HfXjQ3GhRlUU|?&}AP_w_ihy?$Po z1KWtl$qZ#<3q$V_Bf4<`i!T29dCffV>9w5Hc(ytQ>#$+Lij z`syNqqa?mDF{)*+cP!g+?U})vxghG^XG`1r6CHJ4m&YQ}SiDVKq0q{LB(Xf#K9Qe(|f_9Oxpx%CK|nh=5o~L3RRj z$$&*(R;0zh4jr)@70Th|t;3mXKPKMy)EV-1nVVaffZ=@HS}pZU8GWmyp8fiMe%)vB zqvrH%w6Cl&7&4?2v%rHcUL1?KESF^;!Gb~us)ylcj?1xnqBB{2D+68V4~cX+D(y3@%S8IxG^bm7OR zxqJ5Rt$O$HFApD|LcVwBu3ZC}%ABGWmAnGMj=+5+AzEb@4ahJTG~;0~6J8FD$>{o$xH zt|k6))_;n0OD(r_=~6p8JJ$_Es$U0OWn#O5p`q0Dk=nA)YtolhbP?-chpALa13o^; z;I<3nPKZ@k0=#5rXLDrYS5-<*VaLnmI}EoyU!6+E5gKsj`maODU?ch+@Ln=v!UgfI zIn_lF7$tBjXODD!!_>iC%3@E7j_?f~vMv)9RyDXTT2xqJmNL>SOO^9%Bw{QaP1=qT$kWTqlu6icYiq&&@-P7H#bibXA3H$o_>9hz6319k)LZ0*95TJ( z_oLRksaBuT87N9_YJuR;P#GQjOkXwu9^bDh-6qB@yMFoPH6|68wbnen=7O<{f_Ciu z>@|LjQO+qX-BBtZ`#EE*jI^}FkjtBdk%FwM%q*l~qSylo^uhiM8+E5#bNh1kMW^4a z{GOVcijxd-FFQ8816Ui)i4&4!+*q|ec6>tC>mS{AWSv`^s)Kqo&ec^5lplZ%;@QMtl%QAP=waC@-i%$*8+)(p0U`KLta+d{j<1P0O*;7+${KtnjtKU8FOG_K} zB5nKaarAPG2_TUPU{apyA`4EDAyU{R**X$#VrpGFcL4nW>keJ|e;nS83!UxD1$GFY+`Q{3&`|a#~tGS2*dj|hl)`Lcsiti{^3qXhB>a~ywt zYHGjn1chWas#$h4+!7vMz`e0aa^?jnD)zUmY0Q33rqVwP{1fyXL?Usfj844Ha)?3@hhQ+98cU~vo!5S- znH+i=@A2y%Q?0x>O9fa8L>LH<8ltSM?D{C%kQ{z1(Pq%DE?tTpq%{@L+wb`$JH znrlg)U`M4z#G2hLIyBKp8G(r72 z)EtHA@6~H?J2&%mv8N~Tw`}=gbav4Vm1Cs9xILRax*>^K1+$e&*)YkZLXhoY^mZK8Ld zC~4YYvdhiCalJErYE`IM#TeSN)zRhzB`!iv!T~!8#&8ym+_QT-kXmZh>pSBRyaWz2 z|4ndGW-As=ohnDhFx;y={dsBnroOYfKT2THFb8l|aYgvntrM_#GhS`_)hp8Xq$@g_ zNIMo?*znzYpZVkS>v}*xNTT&GawiuV?)RBId2(XG*hlwZnnmptX}*I<%uL{9qpFc=KV zRuo*uhwdLR9X#huPF|2K6#v}Z@O;MhCHlln(eF58#thf{XA+7V2%5GximLu3!)h8C z%^jhC`ek^VS)UruLBRg}`F+Ly7bMhm(0ix5DsISzoppPtPmpuh?t9zv-uiidCX&zz zt+=t6>34Z0p3VpP>U!0fmPyz(V3rpeB`wEz~MPPSJ@|X zI#6GvIZMt)7Ae$oC(>u7nZPcD~d-~23m z2~R+@iHjB;D{g>i9!J49px;149rp!?ey1HP#aOZ1Kx-4QH2*bAL{vgH2Wi$^`O^-b zN~h#&-#j}1*Ik?M9U^4fv|@H@7jkG|TwLEl%3Ho~XnknadwrcfY}kPA5=5TxQ%I&W zQ<-styJxPmy>Ob4B1}qRFo(_Qo%{Cn6g4g}D6OYu2*FVlVL}xmDL4X0ko5c^*^PGZ z*wGp@CL@A8b{---qrDih`c#V*bb}6sSQ1W**C77xK=n-Me=$a96gvb-6}` znyz_e)sMya8<5 z|Afov)$df7p8hd_Qi&4p$$aCzQgn6SD6Z{5y+pro_AxY2movSoIblMVdN2kFRY zEVI(;dYxOU3>+x)de$X0P{@>(B`ZgP2o&LZJx3cD>@nmg%Z3i09B1_$w$cUZOnJzV zA&VGBdHv|*9ZLM#Y{7zqVrIDJPK%0&1RGo1?!$cE+7({CYLR~8$9Hvm&(H7XnKAy2 z7_*Q-o=e&v261v7M5Ro%!2jj#p5)t#Gw`=+<)}o!7D|^~zV3C7ni5?zBabZU8)d$y zuFfO88uYexLLa0kN5(-K?%n@pPKNspY7PPzX@yI@?{+8aR?t`1`Tj!k-WUVD(NQ*Z z%=O&daW9aYG%M@RSWKDX%;mX4CJ&g*uZ=oZDT!-e`0Uv;y-vMGJBW`;Rtl~)D0q4; zJivOO3-7g%B5k+c(4kJSiF;8zhk`7enPQCmTuKv?5(d>p#7rSFr%~}P%JpwMmD*?z z;f#ak#@hPW^r$5+E(IdDbMmNLwu^n?2)v~*f`!+vZONh-8Ad8R2G)2RTuOc3eJjJj z8UQS1DLsbF*F}$*O6AV?-@_y(J&w@gL48*2MGzzpsuVdpIVpL2H;8AzD`g8@sX;H2 zsgknt&W(q*MgIBcRYG^FT6I9MoO0emJO`>buU>T$|02Y;GooWypKk|=b677%3z!en zm`6EOA@gbH|Gxm8@w=sEN77*Z-|YqaoKa~VdyU>qlyRWu)Q*4FgWMN0 zcGG<43-2iB>S{9{dwCt+iTdP3-K0W~!mCoTl8Bln*J@}jy9z{1c>Cyl&(jMowv!-; z$HFlQvi16n8?!BsPo6fd6X{K5%h2=dzjmQ&7szaYa#aU7d~;<^S^$a%Rd;StQGEH* z&+i{Eut=~de(*qboBG(huGz@$(&(;l1HXkGjf+d@o`e=VbGiI25YEy@K{&Z?(HiEX5)HS}EdB&|Q%sVNL0g&nd zz?75}71<49fg3`{B|IU5Bco!Nmz$VCe&B=NGZ>;EEvnw`+dH2+j43I49F!bt78p`@ z`0#~BmZ2^S7v@~MCQBK2H`7z(p?DRg^;Wm`Wr2TRzIr9hC zZgttDwi01?LBvb!|7zkyhy@{-oGh3e01Yr~1;P9%P}q9097qKmLto?f!RH+(95 zKF=RqSh>ET>8rPpU%~x+mX!d&5uC$7v@1WF9)V>)j4$e`7xjYVd#k6wC$uzGUbiz?Nasz2fbbBrStXdj0 zM8D&DtHyTcDLU=`@)=A*6!it={hJ3F5%TCKT!@e~x)B@bI`fCE=QLOtR)kQ_bcA&+ zaa}`EBSP7lkFUF-^1|1ePoC_DV0gctIs>DT?T9nG2CJ+5{4s{kg8mC4?6jNp%W(^4 za7}|Ko%xwl3}@HF%eTV9WZCgZzXvAy{bU9NP}{V~PLD=BqAeb4z-A07scIABIl{#E z)>a8!p-f6L>!1A@d$UfMRr*fZ1t&H6g<1KsMD`1%gl8ahl;6J(n%sWn+O^ViPfYNN z$E)lkNzIb4!fd40_)&I64-P9C`cCkS)Szwo7iE_{JlCyXzkV;vl6K#(-}Liqdw5{M zWm78bBl|NYYs4oraH|?Noj~4Tn&Q+g9l8zdJ!Z`O#npp#bRvcs$B@pBv-pBO=0=L#Fo8)|L~6<$%5C{Ifp8jCIY?i4k6cGwHo?6M8HHOc93h_jA;!YJ^*!O zzyX#`57+!Mw$tj0o!@n|b?fL(LzWyLdRV}^XmB$%u*Qxn&`!gjUq~@lwb)0KfEY~Y zdgpj&!2F2dod^KFaSMY+8ylk&2NBmz`b06buq~*35=9(vhtx3M%PTc8r0Tz9JN8u8z za4ZBLLbxz7xZOD}73?SmtkFN$8&;V>W4qih_t@tUi!pzEI9k3m%Rt3HTBo^E;ZdI~ zZ?IQQbzZu3%j1pT!%M$UwmCjss>R14(fX`Rk)z5NHO$!VAO%WA2gep9xjKI~l3jRh zkIdnVU-GGis$dyoaCoihUJ)5kbLNmVJZn84oY%G@7K@E){>R zVFT5E0q(5G$Vdr}K%aNKSnasm#n4MoZ>4qvK9j%2cZy$|(m|Xm(H@8>8t>DzZS2n+ zepO#rH68~H;!22~bKw)V2fDpiWPL*p2y11>^Zf#^(IKSa(zQp=#p-?jF=cffGaM);ZrV$_|%p4!y9WWd%&&wqFB3?#KECD5XfJm zq>*L!js9aOUm@hq9qTf)ha!KH%?w98KIse21bjwNmL-{uB~*GZIyKj?S+k#Wzk7(7 z)Z${ti9hT9Fs!`X?!@f0b}$nL8=DLS)0<>F7-mF}G*hQe)m`^#+1Vp6f9u-86Nx;1 zUjRNcXLLfh@KJxRoIi4d>vuxpcPk64p=1?cXuIy(cD|@*ZjFUrulyz;ak9g43j{>s zjmj8^64HM%#>8DflRXS#SOQbc+BFXvOYZ?_hD2Rpjn{zKVz`q-6KbIz~%b?n2B2lgk5NE)>J zn83z5E?*u_YCDX&wK+6&94Ox~Lw>v;a#@+e9Q;F%t_zn+5Gm13Zy(Y?@kiJC66j?; zG;)@GE78N;S|UVc%FjH6?h=N^?^5h?R_K>kkMkRy$%=b;mqbaMBID7c4L%2+6O;fa zrrC%z<}b&U>^yNcYE_lYflt^VdRzI0BOgwn$SDac5m;3#J6oJ^DhM;5GG)B@)GJnO zgTy!@J~cr6n{Ln`Qk8Xs8Y*oHkN3;>@72gR+SrS7TTSA+UgFIPy3tZ6HBTSq#sA{CUjCxKu#A+a7Dac&=n5MlL33T;1717%VSu?9Mare%@u>Oi^Y$uBN-xeJBQ_+W7 zWmdJFpn{+fpl6$ojNGpyFNX3PnTGzcX3dkjs{G>%E{*~F`-_@e++(7d;jB{=LDU_E z*^A5M=29E5FKU5w)dIU;aXmod$1{P!fX{Jg#tE(?~{fG2t z><*Dbujb{o5~y0Xv(Ots1B(Xi^y!;b-{n6Ji1{cwp{I@*uBh3-n9X6+Cor)YKSGX3Y+A$SHr0-<=_eh&rg)A|Mqby zPeqaFyCG%#(h6cm3eJUQW5BZlymy}O9~n10+ukRYWO_Oa|0#9JtmUh*Rr^yc#sZtQ zskMF;x5I+DbuDE zp*9OT-DZfr)Tz@xKDs4@S2-^eJn)mhg6gsBFSDb#N+QBCH6E zpI(hOWdesha{vAt;D|{Ps=1xUHu;`7p-r`x@bG1aHmxWtQuds}wRnW9>n@6}*6rj> zs4g6rEV=S3czTPHjm&cxy-);1hI4B~nH%i;x)dQ_HpOmg_{dnZFI7`u?1zCq*Q{G7 zsJ1&E-{oL`LU<`}M*sToYzoEdPDs(d+_4$o#Rd%0cLigu@vJRXyA9i z>UA7{Dqgc*W7c2x$vz#1qZ13dka&ba-By=$JQ9^=Ecp!p{-mmfe-^$qaEt(NN_tLh-aWq93HT@Kb#8hgzo|UJ+|H~y<_Th& z;ELZj`@Y#BFh>5gu|EQFYo^6S9t1~=M=7Yq{QTBP-1?vcn->Z7wx6;uZf++DZ@c`F zdY6LqwHiAugz1B+7vuWv@N-l``Jhr)p_mM^(_Um08-`Pd)lvcIO$TbVeueUg;ghP6 zzB&DxLxyatHSfC}g9y@>__kc`WkprS)bIlQ3PBYNj(Ai>Gv4LP=D5M-ARZPO^>I|D zg=N4I{BFtM4xq)X+BF@1I7;X#A)#nyDpJsokmq&L{VDbp?{ zN7FpQ#IU?paBIR_hH~H*p21rYk&kofBtEBp`wB(V3z?WjhP&M{uU>;^6|ik*-nhz> ziP10*x1g+syFXAuQ!~ScRS_}KZY1K2m=aBap6Cqg2=kM7IZD%JT|&xoj(p#9?l5Kx z3?^R*SJG=GITNAsr1F#M9gjhO;phtG*)KU^p3Tq@p)efdLMoLS97OONyn(GtXR^CKt=(i#U#@IKs%ohZBiyASIMI*2y}1vSMGGA-EAgRvqu zt@Cf(kOykKSQa2H5l%a}HMCmOemg{mx2~R^qtUKE;Y@qt74YL80xYFWvQFmm&=eFD za9_cufe9Zne#8wDcl0?_L!yFSy@?*HJ78lyox_~C*t&+^bW#exww140P$x; zSQk0R%WJ6pym}=MHMN6k&T3>$RzJLU64Vk9Z(?g5~Pv{q&^5dhn_S>_pIng1?YE zU!NBaXhBj4QGxQQckkZ54?QNv01^e97A`ZAAAm=L$VHJP9LvHk%+F6%Ye;$mt0fTj z)#w3uh4Py1J<^BE;BJoen|5F;xyp%QG|V{eMqwgUV1~&#^G>;bHAz-0BW3TkKhG6! z2P6@WDRwr6@g1y>Pxq^}D!e=n(9L zfCaDbBm_`g2ydpetn7HQVMW9wX~!r~Iz^iZ^%RFM?b~|)`uQU+W@-kSk1~a$33m}; zsiTSEi@_Wjlq*NW{l^%jpL_FWC!n^lUnV=`wvyx!t_8HC=ZvvB{m!m|&H&e5 z?-!fSogdk$nfTZP9uw6os6a}x_Vc^n<@HT3Na)Z@=`FLnhn6yvp5hyph*f7|_8#M4 zF7b#Z%o468oBo0pwzG_1QjzKc4c%T0-ldm8)KwB+pq;n-%e5937Adl>XsaZmtj1Ow zg8oHa>q2WA?T(7_qfp7ed2^esW#2OnG8!&rV0-Iz`ajsoC@dh-+FrS5d1pFG-kM9V3>redjI=!+TBQBXWaGkc0E07A{8C} zm&MM3Gk*MN^YGlN@x;0j-5(4PnNys;_8nEBO#_!Uzo@?5x73$T8|w(UlPI4BcrIZF zE#pF-a`v?Q|5o!xZ{g+0F7q;Y)k9)x-V_wYeRdhD3@5ye@>{f$VD?_~vx%`i*A3FO za7|ny^sQR7w&A(F*kl`?F-=J7kX;0?-`{*Csjqxn-WfYtT+CJv`R1f9ELNZoSJhcs zT}4qS7U!A{G?o6kB24G}0*Eo_k9}!V-jBr*gp330Yr^>c*ds^8(Fs-T-v^=xJz&`+ zYfldktrFciI;UP=>G3zcde6=yJ_k8W_;l%$va&SG3_jbT_tCAdSlIw|Xf2;X`%WKY z<9VxoLV9r1oCc_A1UBhU-2I3k@#5|6?-HSclFOw*BEg~>Swl(?4W`|9ECKFJvbTTG ze(dE zc(Uv)CYIkO6APV}c&PFM8dy*d{MO{imWSm0#G{C??2ycyy06{-i7vWw`)-WMPwg3Y#3ITg$oZM8=RT^xj*K%?qZ%aPqc|vMFUJS z9o0q!0y=~Y%sjL`hTi=u^<>(&wD)GSKzKroZ+^bEaIN ztu+>k;ceSeC+t6f(7?hjpCk^HztD13cqnn$+{c>_$V4f;yS3OzqH%PkyvlI% z+6F+!QhQ{_oZDgJN#Rqqy5>=BfG?2YHiC*-0anm z72*|?XL@Q9lWzE^o}{Bk+4d>4X8*dWeE&SbyYf3~k`(^$9&0y} zI9-TGQ~KtB9t7x45H0TS4*h;k>}SkdCzvzj62xXdAeiQ$L9!B>I6Cmeca<)2Qfk-A z&!qYbj0G%Av1uPuY4uySQsTo^o&R4rD?#dY-;t06r^9#Re;mp78-C=?)x%y$J33=- zQuahDc+k5ayMhamr2*8;cOM`bv(MPiQg&6ZgWb-V1e#f5jk?KP?&mm5`GVC{m11(j)w zJBckGg1AE>2t?Gp{}pmIIeP1VU+@Zi76OwA>zlLaWs;RGEpG^)5@>oOcN$WsT)s(f z1)gzQWEgMu%w&Der0JS1j!L5E2V3tdZGHV70{zZeahC{Du{nMwPUOnY(i)>D{5{;d z>ZHc_;OLjl5gq)-tqvfXhVv zSKa^Z!z05R zJ(TUi$)WPAg2Y=g2G8v-l32;qh;*Al?B~&@;!U@EPL^{NR#op0ewePPcJGw zB>ZxML?R_OdBQkr*FZ+3{QX7D2M|lfanB_ry{CjE;n{rMM4|2A;E-cG+ElveKc9Xj zl``3>2;|8cIXNX|<-_9ByC-YH<>>0FT8h z@a0ieF4WTyApp9%IRxyAijqQL#!Hc)Hf_q304n}D0TBwO9sWJC<@tZd+x+`K|LexK ugdN_{Ki`kP{r}m9&`es0Q?D_)Zj;tcz1v0++HEBKGkK!rgj1#t{{I6(pQzyg literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/WDNN_Accuracy.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/WDNN_Accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..8ccd361e0e1f392dbf064061b23dd3c925fed617 GIT binary patch literal 42723 zcmb@ugjR<5zOKMuB3%1)#=k`3LL@apBp>e$XP%ETExkH)yB+&P$j-m}<11qV zM$gDM>4DhU^$IapH+P7~$j#Fg{+*(H8jl#=k5=6GvRwNdSL^n-1vHA(*cktNeaZA|M7r_k|-Pg=Yw%a$RkQ3Jheg%1BBXa zTGwJ*F!+hrQ4e$WOin@qWe_oqT7K6O#Q$!z-lgsGorQ&F-Iap2<8Z5Q{$jZtRs%Me*KwqDMYqocE2-mYPGOk9{SI|6W z{6s(So4=rWc}M~kmMs@gJ~RJUInz>PNS49-TZdt7{$vD=U<8j*r_Sg_U#RDPV?6l& z0B+kfQlwq|W{5$;E1}AAlGkGF#q3!mtXF;1rcXjjOXK~!Yj;3 zWilO`1XK9TNO*X7tfor8UZc)bs%><0p|Vn0V*h)lz50C^cI0G{cGtgbIYMi6eSg2a zm$!GQH$5q7WPt^PUwu7_AD4QyXQ3s4O4Nnjaea`3_x$n-IaH=qGz-=?>68lY{|k?c ziz_!3J)HiwP_rTkmyrD6ppBHzY>@W3e8R$*fbItw89dee&-N~SQc?uNrEkfic>iU} zlKvL3?#)q1+L$P!fx%#6=qn_a*V&xw@%Cio_wRQa8XCTbhp(>2LprSlD1y)cQ z&n}02Z`yp(D2Snv(c#fihHkx!)oe{!vt{USqzN}ACBMZ(gb#{CAxWU4uP^ku!tYYI z!=*R7kTOGDYdEw64o{kz(vY}1XfqsOq5&WF@$oS>H6{138UFM7TW~NOvCiOo^*T+$ z`wj_7XIEG7OqC_F8HZHo^j!K!NJxfuwT;)wxO#$o&YPj36w!Eav8AOYA%~Sa=&NKUt)OEE#KUic-&HXD3VPRn*0x8(s{3>6qs26NgC@pV|^R^nuF_{z* z=Y!MJ=VD^X`1Edmqq$1(vqT|##vw5z5f%tEloT>xtF7z^BcT`T)^(keKG_;SJUPjJ z8%)BkQ&ZY3aeFT`ed$Ylnk6+izMz4GMx7h0b-h zCjy{Fk&N@%(j^(Qof<(y3$Z*@r z%kA#%WgXj_t9Nw-A$@TFzJFvSDKYiSg+K~Dtc6L4Z-+kj!GIv*p~u{8ts|(CLfv}k zR9g1;&x*0jY|3P0%);K6F9qkE9-PfOl7dSx7#J8}VaoIT;)2KH*c`0l9OQ=EVF$%~ z1%=gc!TFjc`}M&TIV~+}QpqcBynwIZE-9jWH30$mqiZj@M&+`gA44nnuX(@o0{M(PC>L z<~dJy6B83b29bi85(x?lDyE9P-=A;1d-twEe*(|vBCXiAVA2Zx7Js(X%ok_#o?N8j z$M+=BSA2p9uL^Gz)EYho^A_cToik$52-+9}G?;Z95+5tni~+xgY{6$32DRa`H>;V^ zpEYi=I-zZA0)j4f)XntLV(hyu>>?=rZ7}(a>*l{~S~0hu0Jt8|(+@__iJtHKqWi#C zjcOY@@c5WVZ}dDnx>!#`f{T#R(h}MA42iR_{7_60iAqfDS&o!c{P^)+n$IOm^{fLS z#QWq?HNwa9>ovr4mp@E~NlEhhCD_sBlS#<>yyw2j_2o&2N0Z}P|6+vbUi0W^%kcvl1+laLT)#dJT2dH>OB zU+sFTr`ysG=67;(M&LoL5U`Y~si~!#J3B{5M;oKLq`GxZiy%~y*Xx)tM}y^NMoN4D z%cT*pT9|W1tWK2~d0ni=pHAA&)y0ClE-fy$yd@Qvl9wmKC!t*kX7E{vRo6?Gjii^7 zmgX@VOn#HLoh|=_4m)bYGh=!rcAOCl{eQ)7H4~NMSjkg$D4ttL;d~i zmAi|<4A9HVORb8Eid}dR37tiFLPlf}B0xP@unr-|P1lBOFA+`^`t%K~pW!j~T4VbP;f*v;kkskOVi z`vll4ty|muiF~{8P?3F*_j(I_0M91`=iS-}G)U=0KAWRAHq5sHPVGjfc^$oH)4$%W zM(n`<{rgvlfuzp%c8vj3$FFDq{wgzBDk?^JBS7B32{fv$;c6Q?zGqzwz8bf-0jGdx z*j?ADFjd%opd_ZO-$ViN8X?f2VAuG#K}jCkVNs=3#An(M9+*WXN5>&8L&CS956Aki@F!oa|Qx~{Bz866X|Ia9?3N_l6# z5f#!!2a0?=U$sJV54@{S57H#@@t{I5Q9fD1`!~4krz#6o0o!?<3`b6_$~&&EuJqo= z$|wNIait{Z`z8SXBmhHoT<4tqcGt!17G8n-tLxY70GLz=CFdY82|j|vG%4BH*+r#| zR=xoJ$-%kOI}K3WW&i^fb1VpQE4t13L-$HYOYV=cZrCeK7Q=?^XENO2fWsC zz1VHG3G#Ri-_UF*mE+J72}wiG#4syG$HuA}KdN6+gJJ+!Q&ZCm=qW$z7c&{sp*7pZ z^*a<5fL_d+{cg$se)(fzLEonFM9p+C`Msi|V%ebbFN}5y3nPM|_C%Z2gb%=0;1XCH zo0uFfg>v10^e7OJUrS5Nw{PEmMn``t9J(=-ji61J38w}G^Jr@R&+C9Us8nIcAm&sz z|I$)!FE6h5jsNmp~B-1Eyd*y8u0O0d$^f@|6S> z%*@Fdk(Ko{jtgRgIBWij^U`|exV%dgkSAcm7vuiidwY8T_bY}^&(Ga3VgN(#NF>wK zr{4f`;!sGOT`eF#?AlC~KG_9X$vtU3m@MqHG5lJUK{`w0<+_|y7Lo2%ktgieuZMN6 z`--n#VR1Dc-!CgGbMy49a7UV^dhXR4#`3y4I^`* zJJ9zzU&JpjFQ*i;`{T_J(9*09@$LXgcn;9-98ib*!dHAZtNzt|xvrtCC}~vJXSq zOcZLi@ePT+?Th08kJ)BeW(OEI&i&%jOC42#1~4yVzjPb9HefX0;2xNo1`-zV7iX-% zTK#9doqg#qM*zMav9{R?ByEltPyk3@1T>Oq&=&ML?^EEnZ@0k~x~Qh1em;4Np%x*R z9ZF$g;X>`|2*AQ6?OkM1z3(y2LO_v5nLkik7>>p^83Bm5(ypd^kD5B9y4p2L_29!N zs(k?2YXJ0~^Yh1EAlDx}cwod}>RLuZCjx*8A0xKb22=VP&*u9Y+>z&9k~hjrP)~Pv zdmt)~rp?l#e*J2XhxqgW_*ZgstMN`NfnA1xyf|7*vYn|mF*AdVXLOE?jIcvs$;ZdX z*ey$`;+_OMuBSViAXx^p-pA|&N@AVv!qqnto>93_(9!8`==gbWSU5R3l|?!W0}g)j z^5w5DqdAW}Y+C$ry+DBE(a#b zS%MVs8;C|@nN^2Nut+^UdIqn9uii;OnSu8?oD^Rq8~he=wn#TxD^XBQ)-Sb1z(Ajq z{^|!3RQ(MKfxiFX!Q17|@KBT*Ckq=}DCkSj%D5OiX?`b_}4K#g>UQSp6` zjN~d8zwi$TsNKv-N)Y!HzzC#H8rw?s?1yBv_f0^bN?WLstN6J{CY zmTGw&e zhqJ`>u?nc0cCg2~=9Kf}=QpVR_i}Q}aoRR4M;G8H_wL_s1;Pvf&|^&3gOQ3NJT}(t_=X zIsBGXx!%Q^gh8UeHIR_-43L26 z%56^+5sFPVdb$c&O*I2VdH3N1BRBU?005XS+Ve?Bfx$~^s+Z>XY#R>oz*cu55KYZU z+oo#)8yg$2LBT)|h`8?cmz(qzZ&e6Vhhuh3>|!ORKUJItU@%AZY%7TU`vSEhf*qg? zbbyfH0j+n?xJ9<>{`}SPs1h#g2kc7A$p`>jiJPOj6>f)y?Bs;OBy_C2=LCd=Mxad* z1FcvCYOmhd%xtv5-4R0^0ASRY&QyK@L|WM0RVdMGQ4#Q&aPG2EirbyUDEXY#f$Hpx^=^antZ4-g!h@Q{PPC@ zqq{&C4_t~QAWoM<0(p+y-P}OuC3ygniw}sxhQ`KPpeU$7C(of(`J&Vo2pLTKv)mQA z9zZJbSX4A=V`JkDm3Ara98hI*NMd4K{k{flsCQ9-A_>Iit8E#;9Wp>uG5F=@_t10D`eG34D<2M339Laj0g30 zjs0UZ@BjI9#?6c3H{NACI$uPh32gr7;r)NK`Y=23|C?|4|6Z&nBP-=+%GQn=#-L>R z1pL4y3xOejQju2tlm#9C3T@1;W=moAolW=@pPkma-goasKMaR=NT^x?{Ol7e#>=b; zseGE?E1BT<SMZlR)D^2gN;|EasDL+Zbs)-+yWjXYvYas2+hh8ttZ4mw$l24d4pijxxC zus0}O&)dOK2Lo-Td)|NVW9!O_LQ^`N-T1E#o+i(md0GutH8wS^y+-HVn`logis|c7 z47~2Mx-|)V_S13X6Fxm`L1lL<(z@!++86Hi<{mmI9DyrEPSWeY4PTR}JBlY}WPFBk ze?JT*zNHi#e7xl(pkeFaVyOesy5HY4ME>Vx167@b_olb@tWmw&^@Y2JL{Ho;OTICC z>&EDQzEWc`t3+#0oo5eilC5Yw&ineH?v@NL0g92YtIb+QCu?_|O~?t8LxWemp^HAb zXK??tP@D&dKmYE&`xkAMSTsktIQ&5y(y#vPA@yn1$-vB9^W65#pa~D0)orb*WTlZ} z&n(%0>^6LNA;iA~d0fBIxQ>Qn4bQw$@?ye)V)v;;x2Y()b(8=A$-Y?VPt1)6#4o^)n@A zPg`QSBt#-Ab=wPl2z|W%x!juHFb#fr7G0>Ot!CLn2wk}MXBWq=?e;;Qh3D*F$*W`b zotu$~(_O+ph=+eCN52fX+^tQ7Hg7FGekwWD+XuU{^v=KLpcM8kpeD9aKQ9q?Z`w60 z^L#=JzoWq=rY=4)kxM;K6lE=U=0CN8H*RQE?a@de5%0d1F|?F1wA}xsTOoMacgBW- zFIiGAeJGv&T#c*IMbw{#W{~#9EJgHLz$QVgVk36w9mQ?9zltDfS0#fL?$<$j&MQ9o zdBW*+PP7&&0@dp}4ua zhk{Dlj~{wTi0b#&**!_RPpWCQxZwfcHIyNR<8C7Y$U;}&1hKg*wM;lkPuDTJ=`hNh*lJh)#yW8>?qJFXQNP`>5N>N8PM zm?-bIl06MOKd1?MJSRHrF70#_%%@$nK(Ul8po1GQZqe9oTW=(vBmmr3w}AF`DXmKL z7QohWsMFoh*-2ww9zf9;{dfQVeRJTAqtATNUEzXy2~5CzZi`})C1^ZNLtiliwTtry zaB87WZFw^ilZ{HTGj*jm!HXO;2KHh~>L|R_p-e(~R#XY^Y zBCI>&x+0P>_o8ufzpr9vB+!p0O^HC0zBMi1B}LLPyuOxDw1&z}ixI*Ya4GeN8#312 zbt8mHVU*aODXgLx(0hj+5*9bLAIBh(*%8{=Zs2&p~Zk7a?AA3xk8 zL=`9Vuo3z)&|8wm8Md_5Z%igAKo=@Lc3KU^@|iAqMZCx`8m#ah(cfpHIEg8&7`}MF z!Jp?e=u8|!LnFkGMjan-j{XP@HQE}>1K$M$GYd4hTIOh=RCzp4tt2itn5YG; zx`!mu{Xn1%f>yzNJpU2Kk#4sVfJ1;$?c#B=)d5BhstX!SGGPnA4lkEHJsBT<5!J_= zq>q|}E(YehOhaqk-}HG}Bi;NBt>N;|qpxXV&K9`bypVsaHAZLa(@~C4Z4)j&-DGSU z^`$iuS0ADZ{N^ZxHCp1l!iYC4*teS4U4GuulhzaG*mG2%Jx{3N%G$BzH-cDF>=yHl zKSP>7N7`F-^^-#TME*t%Ud6T`QiJQ@$<)JMGwvDxyo{i`YIj*L4#m8mG$ii2@Pu}d zyIqO5#WhUE35Pb$$IazWZnyp%KI+xSLfgTMT&n$tRUUY(Cq~-fr=rL+1Wm!CPmvUKzhXP%@80lpD$_p8Sb=2JxKEWww>W== z;UeD3IE=JWsw~wS=X|8yE|+$)AQyi+A=$72OHHvzn$*~EJ;T!AtQyQ-Z2fuW(3+Q6 zQd1)Yyz(y43NMt=%Dx38cuW~zxPxv@YyZ#tB!yCR$l zTv(s0Ls`%e1TS8Z)`427w3?0vKAfI2JoX~`1C!u`n`B(e`6`7t{Db3Q7t%Muvev#* zT%Z0(QWrw8$!H|Y#WkyQISAF}*NlF}RX#npC53k=wIwa?X->xN_DJCKps4)SaA{#xv@@~G;-oP@u%&$K_%QLwajhFQQ|U= z%~ls0ZrFC4`()Si(>E_#Nx3|*axT->?Qq25oA=3CW0t{%B& zMP-bCD*Zm#@l~ZWPp)Zj6#a&KO>?z%o3lDAuzu*`apU*G{Lp?5*Nc928yn6f0c*pZ zsj^dRnan8QHcgG5(@6a<;{5{2_ZDogi(mO3ANbA3@Qj%U!ZUmgrkaShgXel^xF1+l+O5>vOE_}c zK!{orTxcyniXYkdQ1qL^cP(l!TE&re=t_p5ir~^g`d9Pbh}gZ1PBpfmUC0vDs-ck~ zL7TY4;W`v5@zXU=n7(6djp5_|^I0GIQ2TvGjcf9WU4%aD(7CW|65@y~IX^obvzeWM zg&K5CQVtHOmwl^l{&(@d@C2pTJ*L+;l=o7P>ybap&;)7kHF|PuXf>5(hzKw98d0zY z8FeY})@|9gQ#@Os^>cz%jI25SI2mD0PQFFnr zPql#&r3v#AuAcW`Gp(q7rT=Rm%r^877Fyc7x*m|(8_1(DW893)OrU=CK{tfyE-P&j zslcYuDR0EsBLA{lm*0Z{RKb(bPw8&!sZUN<3=I|0A@v=np0SHmtvAE4c6{d!!-hJd zSFcRPc1auG#?Hnh5YtTm9H%(wNFtIhb>KsDe;mgnS)DkId|(-G(W zro%x|*>cF+iB1Xcamn0J)gHyHjuE9h?-6%j<-00CrHI!HA&r(2F3PPc0wY&b>|XL_ zSVC$=IB+KXm}TXvu_09sBZiY`pRCSW!biu77yPD>se$Ap+ohT8db%BXl0pUEf0cEC z=0ySQK((9mC_h_&>Lbj2&?oV={#lY!iQT_OrgumJ=Ap)riX^vjUOql5F}H(9e2`Vv zbI?3K#DFfCVm0e?-=m?C8%h;V%I@=t@S5i^}4R~-L6xgOdi$OFt`skbM z_Rdc7S|#PglD~gnfcb!~;nX6S!T_^0K8UV&T(pt2x@zBG>J&E!X;e^@uE6c;L2H?* z9jZ&WU4G5OhFiUl{$bx#B$81(eviG8S^Yd;HK=KA>1KHuYh{j~#`3x#Vcq%J4{iH2 zZ?>T1m+U7fLwfGa^G5?mRxzi<|7DcxB28~hJ-3Fu#$02WlQ*8+tYja|$yt%QQ?hRK1!{(U-Q+7IrHtLZ& zD}=T%7;#+~s$j=Z>_1`Z3acM!-q3S)FI6Fu$@CvBP@YFOK{X1m++PNIr2E`H|J8J= z{!pzTHih|LH@~*I4igsFS+rSkuP4MwIxjB|G~D%jrEOqb06a$Ev#^$8CZY!i2aFIf zrEUd-EIAh!fn24u=KzfXEPu>ZTztOQ z;L#Xx+q}zj1XtXu-o=M(uUipee6Qi+~S2p6HdEpWu(Y>4qDm zgaEDL;y}IDy%qJcrk5;otB2_AqOMN~=hq|xUAgzR_B-Hbl^I4mst?0haMcQ`hMl5A zI0c7VFW=^BmNWgx7L9o)UsZ&=v1yZKGLT;xo+neEuvJ;C8vY8gbXIgUMWL%|FDaXg z3juS|$}giqt9|i~aO>(@P=A`fcrLTCzsm96Mc^PqR8$nO8-PV;xd(Bv;_D1n*g8T-NbTn$Zj!|^*e;<>poDL}OXHrSgcIaiJV4<~YqE4Es!_K7 z&>L|P?z;CyT8D03$18OCY3}+#TG|;mIx_Rr;~Dd)L(Q4*w%b*ZhnS1E_$=+Oy9#{* zhg%tQ>{DK0TdHC|h!2?rvIxr3eb)C;WaJB~2G|wH$zp1I!X42mKd#DAPrpo4tW8~d z)GaPAc5a602+&Hj1+|&^;ZPC{Kki4+hgF5=DH^MCeBS+#tYzVIyfH#VC-Ms%Q}_q- z_RLXC!JOU!Clm1X!L&e1Murz?daQ{Oh|-%k*ucks3XIer517Fa+wFAPjF5KHu#DSr zO&*NPL+U+Ss@)cvZ-G&X90KNjmw>=8I$QyVC5CC1#v;z(1O=7h#ho;+RexMctw}onoK~5u7O*m{Tdg(c5#f1P zM&x=-tfx(mb09-)!5E;H{lU#VJxTpAmvz&wXvg|?j5I1b^t@RGi~3aZS63UbgY-yh_-$2V2+B zG_M5npo!y>jzGZ~GsRR%NG@EuMdJ~?Dcwg3|Dx`AJ!Sv17D=D$vqNNrln=u9w+=F} zH=@NS_1J<|X1{aMDU7(aZ>~Fih3H1eD=s{E=%6dAg7(9pzN;a1{e#hj#zE*$PpLnG z)<*fGoH^9si;84FLeo~s?yGbh!gF67#n=bpx{~5LUq*_vGm?o94v=9E-e7_DEE>!x zeu25)()zkA2&wyS)g-~gQ7nye;~(CQrJyn?-1dO}nsr5ZV~%uyK@2z!gqitL3EJrV zShL9+Yxu?HE_^U425+q~BbkEMqFyDXLy2CEYh}CS-#?R85n#WZ47|TaY#RihZ~CZE z)}VD>Srk^Mjum#^LB1jMZ%xzAT(zZxE5NWN)87~8cZ`d~;|g4pIKJR1pTS_60KJyX z52|L>gU>YCp;nVC(on1T>fk6d)JtRY+yq9Pl>S*Uy(=4hh;=!K>1?gdJzHX{_kVpi zAzn!wYUH*`D*>^n>C~SgNh26Mj8gUf{&!13N|k{z|1#Ov3cj|#tA!@bF-=NnFsDef z71GkL2UjO?_TSLr`et+DpGUK`&P$bqIAi8JMA7YtCX&30`HuB`?%y{k4+X47qx6Du z88)YATAcWYHMN1i^x522@GlSTPZbIcN6VaRXam%hh3eVrD*X4-`s(0Ul}#wThlnKg z!+Lk3e1BX9mt{B}+!7f8&buX7tSy@U$uD6Z_ZH7n>xkJ>wK}_QoRbq{KC*MblXH1q zZY+C0X=#XDgY3!k?sy4>*3G%6VR6di#pkPSd6l#Rbi!?&ZDtqC2UJi7C6437bIGwo?bh1ea`VHbblHAVD9pS{u^j@**1h5avdJ)zsY3I(+KrOBt0hmY1k#g9R z)xXx^e~f4d%*g$>W+uw)fG{{W$|wO~+5 zncTNhls||?n|e3)xE!XK@IKfvt3Th=aXIsBCI9)nVsu5t0KX9y3(cD4P&YGBTqQTU7FIm!1+uYHvVCIieaUmEMz|7GO5Bu)Ncwvs%sqbQHFkS1lE!*9 z_fZng-LbJ%8Jef~*_k1}r@xLB7h)pcqRt|8z~*&=Wt>u`%3SZ0%<-{wXmJW(I4|C( z(RLWY*-G=Oh$Oqdc_*88&OAx5%4{*vnnyQ%+#9Mo#|7h-Y~r?#YQQGIGkJYd%)wo* zr9WhN?ig3(B{UT=z53qVMX)CRT2OOxmcjAg!mus$4Z$fkp(p3nffXmGJ4IzRPR(WWHk|z4^x78uadyV+jd#Plt4;ZTjz@nVe9HbDgx8Ta zxH4UWHk^A6_pq?9vYsy9_*2j~Y?jpDaJ;OzR$Q&?RUKNU>lMF(eFV5Htx&k#%rbIn zonrjXv8mLg$n2=ZR&-)SQ(t$_a(itkcKI*%`-A9uv@u@KCe)9!9TDn#`rYIsN-JAp zc570cnF@6xa9^c@htg{Lx7p=XIe+|Ce#?)+n$ z`!bPu>62naK>Bog5gH4T+0CM zpgrttd~y+vXYR!3@j*Xv))$O{peKh0(wvDmegN~4rgbFjNlP%uNs0Q)fup@rhj(lOPuE0 zl%=cgoCREqm7Etmo zrEYsrXlgKyHMx!7oIcIr0YqFVZjSQjF3%_BI<{4Dyc$D5G4 zqY?O^))xN*_iJ>V^@9Ipq0qPErgRuas|ow;r4Vyg3zTM-o%J zfUZy#n=_}=4WAEhtI2d8_;kVhr$OaFwez8uZuXAj!9XSjuT0TiFbrK5+s650mPn|v zX+iq@ki+hDSXz|okEy8k!N`FrTpBsfz1}itYi()p%(}vw&*K&HE0o~tlM}A9ExEqF zuYCCEINfR6f@oI`Y)jznrMn2`elBrz^L=SDUH*vz-^7f>|Kg}EvbbAx__U%?sGH#L zWz86=4#$_>dUzhn)BJ2oD(nj2X3vZY=pB24B zCO0HwU{d$p5wIMWAl+&s~zkWDy~=4j-ug?zxC7XHGS@8oD@r> z(>`8ckbs_oZ>2^dVA17j@7!~12yeY&mV?OhKeW=hdo9JC&ZB)$$!d<| zhip5J>q93G5{429DJ>WJ$m8$M-CDxrp|Mm=3`-{+p1_j0bBbI!5lwRRZsP{fky^6j zlK!(9NIhCm8P5nB78gw)i~J?HYgW3bl=m~ zoU*r6v1(IC@bA9?vj3G(>@c)s0oB#~>kFHN{h8Ul={l>SL=W0i_HtaqV6{i=-xncm z0_X(z8)tLs z%~_LY2#gXgRkMMUKTQdT@+?RqpX8$oRMZcaZPkAqf9uQE>nJ(u?Z+uD`Y2-{R zV%ctr1S!3QM78FH5u#J&nXfbCrLVaqpC8-4S+8r!o(~FrmSuc6H9KGxp>%5jMp8vN zS;8|XC{bCp(>OK?DBBbrH$~`@~;DO@)OIr<(fX9>J?0I&l4#-+F{~;sNjd3OZ<9y^BBz zY>PL!U4Krl2iYhfgEdZIV{@NgAL``%Ko?1Lhm8mCsP_GyBx>(!3qM&8-c~(1(I0bm zu5B`M%Hy26T%K4KYtpC5n|42UtKqp>>m;&Za8^LjY8R;i{uZ|5#R+I3_ljM$gJsZ) zCiN_*p}#bppE?OTs3-jv8!L+FBUS>+jn8wAET=?FpJ75B5V_Lq$H=54*(tfAT;sK) zf25+C2WCAL{DYS$H~Xq4+L%Dj6aPcIk7c)kru>!dd7&R@9o{3ukNuZnt;rh#~5sI&vjhz17=2f+saBXYuS1pS3A5O^Uc^$@B^Hyw2vBD#B%b6Bw;gM;} z(733pOv@BYiPNf2|J%*CTX)YLC~0-gJZDe7)aQ0E$78jW;gahEIso zkuk$Nigu3aLzT34(>E_-KiOXzSwMdz7LX#F#_@M!PpK#G=sT5M&JMqLSgKl@)L>ri zJu>}!+{+DEN0)+;H93CI`Qh#D`z}*lE81g3D@9*9@*aG0>3c2oyT@wLw~3Ci&v*@1 zqxB8%*NtI+HVYGT z7-;{$U4}Pput6JD19HNrSN2bs)>P<3BEDS;=9jjrI`rJUAc_AO-BDu;U0mMmDPeT6h&h+(2={Cn=qGYrms_P7j{3=A^Il>XTUMq(3or^4< ziI|$8Q3=0(4x=Y-8MKvKD1lN+8 z3Es>xUMp{-H=i!o3RX1x`1#lUo%Q#l-LHPj-2V5H*Uyx{K*U&aFZQ9Jz+c(`?hgAx zHH|X~b}CXezHb6SUn`!xn3(2Z`#o|;dDpsHk4w0opYc)amUoZX>4hmO>jqe>Zl!W` zGP)27Ns1S;$%&p46=g?$jo}y_m2c*4V?piHBOh0v6!mr2Vx&p>HlG@U;bm`tm7Gx5 zLga*_Zos|H*|G0a>*H&9QdkKYf~Qzhk8q)%E?(aZZo)SGCdZW<##rh5Tf6)1S|@!kY)zFQyK| zckL_c|DfT&*`9rRufeV+q2cZaV%TCBm=ksDw(6lFaL42!?tZvQkvve_w>Fkko4?RP z6%GUan!evi)pTCwGS?6&9kUDNu7B_npQCd27T@~<33ZL%HyXTj^OXHDRdMu}H0P?=RF;z~*U2CKh4&7k{+-D+bPT z37C#nah!Xu-SgtP9ew6ELU-9fu*=}kE26@<^Z=u58lpgG~V)54CCc3rHT89PGy6;QVC}M1^drJqa z+?Utq*k|IpfuFpLYKlPW$Ipn(ipTjOU&oGHn4Dg^>1o!)Sj7asVjz8v7%BX?X>G3y zLQD`XU99{k5+A*x6}*^YS>dq%9l#S~i`(}%w1s_|9(vuix?*7Wm=KUZ(7Fh0 zn@f9BL^A2aPR2q3Wc6Y9jskEMn@0z_v$T`A|9W$vkm5AKBiVY~K>M_NHtm>=MpYd9 z+VY=O7Icg@ZpTjxCYkX%T(}^W=jV4ig-7WZT16DAt0UN}YE`QO3Jz`>t*4w;*kdSm zmm-K~pNg(Wgb(NIJ?LS`(L%E1HC8L9?<>vHn9MwbROuM9{SVgLlZ|}1);X<%| z2iQ`Y3tU`lmYEJplAGiiV@F)I?^7aA1j^-28L=BL7GMIE-}AN1C2dIsW%ShJMYUv) zfS9_l>9dzW+#6~w>cW^fXU^YYTSQ|W5ve`KJ%dlKZFbI5P8cymeF6m0K zwpiNK6Tsz|ky2molNBj9HoK2L8?_;MZpM8WoFWh6r&dtZf0;l-!&|5l)+PrF{r=q& z(Cu`h!q1uk7xbd)$D-45x-R|OB_S%*no^uY#?XVU4Bh^#Yi|9%wFbVwkH!n!^iG}m zvAx|;scOIu`F$6$tH1u^^Yfe17%)sooNBt8@}Xv<00bDk3l?bz*6Nb-j^n^lK6W-5}4m061OPbb=fmL`CquS5cs+9j9)C4arVP0hkSkJ z+vc;J@X)s6-bsN-FNDlkq04565VD^ffNdWbKCn+mNxkU}WYx5h!Py0NbNzctahgD~ zz5N#OS9lIsGp#1G-D;?6OWwY$t_m@h^CH-_P-h#LPL!6)@&c4PO^2{T31(ztbCK0% z5C;!(JM5V%X0I;nuMQ@;R{wF0IVcc`OB!izv>!RPR12t%+r#vtm|{56Wp)QD7<33# z@yNkm{t62O3uc=x_MW1asDFtqN->v--)2F{s|!TyKu& z*QEi@_(R;z(-N?&WlE4rrjA#dK5*9%aPBdraNJ9LWBNtdJTPKE2~NR2=7PhdY(VEu zPxCUrppnSmR&{6ST$89w`2CrgG$Uc zZz%r#mBC7j+-T0Q#`qV^cUd&A5KD8X>y~QBbfp+O4?&Vl1*fV{EW=O0Dc^SlFjhVl z@~69%bLwkyta-CygxjPkraci)v zRR_~Z(A%85&D@;az^|kGE9$5*GO4>z0odCSU>IBD6HYn9lG9KAUVxJ5*itWGnJnHVasV8xBeUH?+plvvU=kpvRrw;!jxb@9g?ae$*1A)yk>aAksP;QadfWaVGYs($jo0pNJTVJhs?iS0+a?~@1EX{Byoy4_PA5AM#N zm->8ChB#sfzVxIJzS^^M2x_Fg$T_djD56LWB{`}ZVz5vx&`O`Iry>Tei@(o+#lbb? zZbPFLL$H$B5g0{YxsE@f-zDp7w6EG3KmX8cRaS1Len0KXC!q>o30^H&OxAob$a8E< zX5V9^&93Hf#D1#J&NeB3Dt%^s>vv**C=^25V6v(eGK=1iB&MYN$MbvL#^QVMnmRZf zqQeJjF)_sY&H-4z{G|ai@Xm0c8F=sWrfG#@TkzRP4q8HRzFm5b6qFT}>wpf;O>g=4 zdow-;Y;rxDTUe00N3ZkdQX z2aa>cM){ZYvWh;6KAYZSL#ndS0TTeY&nxS6@BOS3;1%A~cIxmKybegrpcwNkhC?ih zIjh`e-eQguUCRIpor&LKCOe>BLUg|`Z6wNriUxcj1u!^t+TjWDBhB$(06H6ULdh;X zxCK+$CP_l}oJrq)u}8pdDd?F~`<@ROK6~=4U|5XBHS;T&W$h5|$$UPk1(IiOpj+2E zv!+P(Da2N!v%YDE`N^};yNG@L%ZtZ5dr;+gBKfmt(?R5%Q^~L5dWfd52VU=5+CzfP z8B5ZwO{Bkq1M%-R0g`K`Okrz0DJB0rg8e7a+Z>4_dTf}IaYe?6j6W_l)n|qBk!J`%S=3j+h zgZVn}q%_Oh$nAE8^tdg@|H?F9uz#iux4f;x3t!&f{n}KGf6{gp>NRgw=D^C4`^wIR zl_NMO>Z{J=T>yN!mV`4)5Lz#vDa{s;65M zy1Z_+IwsnI$8#9>Jf6r3t6_F-W90EKdg3=1XGIFr4(uJ|A9vra=sV!CohBQ0q^dL= za8!on_nw>tOgl|=)7Tb4NeghessHH8JEO$P|8Bvuk6>VA(TdY}m-ILX1MICAqMxtwL5E~));6B%NLUN%{c{vIB00dyuT*)|sbMj*M(^#yG3ve zRK{;7-!(TnBWrkM%|ez3wCXkC2Yc14SS(J;j`%AiGbhxVi#W=(n}`WftAURDc1q?B zVL$^ES%6)heVDM=3YZ1HL02c8yXy^laTq5gY__^CKgC8_pVQE^J0T{4`WS5PHh*A` zQ#?tE+k(z@3G08;GKk)FtAI{x;NWy!puqC0(I7ttgft@CS*bph{zG@3xwz z!$HrF=^2)t(x~BP(=IC-JpZoY?E`>zgA)_nI7Z&m97?b>IvHf_#eb^H-& z&ob@2I9E@I1)S7mgvbECO#p=(lWLSH2qC+s8&9IexMGYwBQ0&gGJv+Rzus=d$lZh| zf<}pemI&dvvQeej2Sa>F7WL;=*d}+1%UnLbnV)MpPsvf>Ys*m*16 zY~kP6Mf`dt?^I;#A%=H?|Io=XKwG;;n_C?}*(NNI$xaE@UwAdaCFqO3d?7HYv$F;F zSh%s$BUzhOERE|kywS!|knramYqN<&DTtAVng`UOS_MyG?M*KhFUAhI`#Cf*kaWdp zc))0Fz4>0(@a&IDAK9orYk4M_Nqzd1A=mR1z?aV4A z5a|0S&krO1Rc#r6CrS-dwopv$(fU{6kDjWNcAAaBNAc2{cdb9?zd%fI@x`{jYGob+ zSC5jx^ZiscZWYWf1}Kx+nZ`;iPJ|iD_FNUeS|##CxA9`lpH99}wccSmY?2=I6(LvdVxqAF3D%4UhrCgC2Ec$< za&SaC^6Lq%_jO0fdbpYI!IOLJx!_)d$*78Pdw7t(ul2NV|KyJvGYa6nZc!8e;_}}b z@iD^n%F~NUE8tL(7JhZqQuMsoQSv~GHsF#S@IddfG1VYd zQD!&AEc0EC`sLMjA+79q36&etbL+4z8p}pIp6lsivZlCeEM98o=yru8ENj_(+d|ZjMn+yka)M7QBPC}y z%4PF)gw~{p;#)bp>+0(6vq?O8`Eor3A&AJ$;lqdZho=1m#1J!*RkQn#D(QqZ7A}h~B7ecFj^0k6)zVk}xd$8G))>YHieFh)Ba=o^nrR$fu zSk0$p-AaQNa{3%7$P}SPmdF`+OJ7gAAp>oVytl5)M4;kTh%Vue=rl=1{W6soR1DA| zuGf@i1-XTQgyz>4ni|G|t76n65f#)g;5lQePoMD6Ki=fXv9ipL-ps}a3SXP=?ClS9 z?DD}ARYb_RZyLj^B7u1(ycp{9}B(2$<96ZQS4qO~-28qlzh zMbBwy@P$MMDX=3dUO8yc74la2*;iMQbrUNbrV_z~-r>x1KRlj3m4)oel$ntckIp)} z3&P&=KT3~iPmjAAIW@$}2vK+aU^?yBSQ-bs<8*D^qrvv1{SSlBx%r+?ZM$eIbsunl z!^Tg(&f#Aw7bi4bUU$+X)F`W?vs2<_Cu2qD??C6k`5sNu(djawCdof0f9x1^xS(}* zO6U6N(=6#%zY7eB-uV4fx5#}PDd&R{7LhKvMME#-TQYJ3s#s$kPmhzXAFgA5I^{u! zE&J;|`Wuqlzkffjr?(NMpHNCl{B#Y{3W9ZCK0M{xaiKhDUxO!~+O6p5%S*mot5Zv} zybxd_*7t{9MrUgK>JTP=bKAh8Pi~f{t@7Uchb;AqWR6p&eY4PdpXl+>F8yF1X60e2 zKhd5ZMlV`=m(j`!=&Uo4d)=SZztGsCC_T*DrRUMcQqpv~e@aoq@weW$4^a83w(AV9 zZ$(poiSx=$h7j6-mInd;5Z*L#5`_ctGH9pNWcdbmD)>gC6Y{75httYRovcHnNd*SZRn>WG{ z%E^3JXp6TRG?uU_&C0Zj3~yv+J`fQa4lCE%+VxXi*rR&OM4`g~eIb*xm2n%R%003}OPQzpBp&re3zOk%U;&OSDW=Pzg*6**WU&CWzNTl}lCX za_UoU<3Kh~ujVU#Y=POe`?_oFbc@O}{S=Bfpaz5#WR7mH+0i-hj4p#1gCGslo|v}~ zuh?Pv^+bJ=328&~mbBu5K)^_klk8oF4Z^}tu+tXA*iG4xmbALKEl}-J@DpF@T96lC zw)>(?7o;nWqLBXH!-rjCgY61lLR665pQs$Z^guH~-vl%Dn6p>*+1X z=^b71Eh)e;zM6f*wyK>8pMbcs4MaiP+&z_8^v6#WyJlrrhM$({SyW%cIETOQhBBgJ ziy1_*>LAgh|48iemkiz)6?lm7O55>-^^)To4u&VXh8< zC-Iv5i`LR;Ggb}a%Ta2^XA1`{q{cpQZhmdB8W(d&w%+L2jB`^q#1S_}R0X@5OvdfH zr)cqK^Ntz?BuEVyE*?_0(mpRXqd*y?fY8WU>EWL0wL&&~tWTa#er*rF$pBT`F{cA8 zn$~~GPG0J;TfOl(IW^C2oLbSYn)l6;lRS#I$aCW?QNPlGFpwFe2I=Ti$&ReCq9!YLc@sfDM{&}y8Uo{6=`IYBE zPk!!TZV3HM-RL*m{yctqv7lY@g7^Y?gpan?H`fvD9n4Rzc4O2&9JxJTZyjnKYM8!v zWk)QdHa*lUrn#YP~VUmGn6}1Uvuh!EV&D}?22=Kbor)}#~YqIKhv>nd^AGHRO`?)>@-?4 z*Y1fcqu%~PoYPjq^nI)MeT`~1@ulPiVY{L=bA+LTxvDgJ@3l4R913=VsdNSheBm5r zd#-xn%vR}80<2qc=^2}NV)00hgLgD%GRLBq+VP8>o}Zk(Sdbul7oK}}HpVAFo_nGA z>vA1)n`IY8J5J2}^J((uRl>{b2KFaVFN%yzw7$NPiB|*!ROEVXC%@TaWRPPhmq;0= zx94ndqAydGP_CXmdlC6_m40u*!iCyg6>(}ezfL}W+XYgY{6y`?gL(Yiw)^d(vlq?K_x2yiPvx5yH)pcXVl|%u z;!4JJSw*|93JzVm=C9d$)&A-pZ~sf5llD{U3zRoWeM@FVo~m#UH70hwufW+CAAF$Zzx#h zQH#tyj?LuPQz=L3d1vBe4SpJJB|cJ)T=RL&ecG=TB8_z=WM8b@c9ndSPtyOFO9cD= z(CoWxGaKFA{g&W1rir{F{<$M|7;%q1;gvL(ylt|iTZpyg-PXC=GZ$TB`+<>PN~R;` zq_NOmJFR1&#L3Ex2ellDGHe~+;50RNu^r*t#-0>Qy8GomY!6FWyY%Ph$Ftiz;&sar zfs3ux?G($Xbqc?DUi@>6VEjX|R%eX&+;wTt(`cI?27OAxKyZDa1^t@XW_Gyw(Ogdr zrRlsP%^sSQRjTuQ!||42>gMYnvP&fh%>c1Px~w3%i6`Z?Pu=f2`8s?FpM6T^C0GZy zA$k)_6xqIf$@5D|i?z3h%Acx4U-Q1X%aV7+cXev+i6H6L^6gT`-GlSHMIEK; zz}ycY;0tLO(*F$L>`7YDiS*9Ob?aOaOhG9|XRxh+X2e_SnlOab-ZnS;qp#>vdjHOm zzPgh-{v6UaIzlXTjU3lH+=Q>)>@3MMN!s94Bf2;jl<0>@aw99l#Qj)pOZ;X03Et4n zTL{5E1xUjX=}NBSFZj$!qxB#()P|r56lc+W498k|DSPV5^yKjIiQS}Q64G%*n+zJj z(7yWGlr9FGLi12mFMshdKXKjcOavnOzqN{QyE?IrT;yo&s3sf3S()$H(yZ4C-g&^Q zEW2&RAr5H(xuLP&zlG1fyT5VNU-Tjqn!2R`8iJwoDfRnnAR6X9p*>oWRR)x?cBe7R zQ6G^2gpQ=C1I?K6aOl*9L%)7)k&_^>voi0Nv0z;TWX= zaT5)-|Fs=A`Kp5nG;rT&W&VEBEpc^#jZzh%Dj0JE%5@MU@&yY0J^H;2*a|APnH^@3 z#(DqYL#)iPqep3sWj7q%TCqjDd+~U8cJ&q8>`oSnbdOWZg#^i|8;8f0)u$ALME*v^ z|1~l>6%#7^{~MVc7`Tj1CEWP8#?&3yDT$XkrL2V@#Rf|l14&*e=1E`^yhR)%@L$6c z^SYNMZqEcXZK|RZ)mwXInkWleU$^tAyPvRG`c(d#`tLxw3nw9hGbd~FlgJ8R%r;k1 zY(;;)0pe2;<67w9?SW<&x~Z}|gbL8-9f!xX&pXzM!{)tRHbQ5huiNV`r9g6b8Ja%N zbi}@U$X-kunjb+6fd~*ot?3wNoT0Gy=`_o2nKr-j-nREtch)~MeOS?3-QKR-5#~_S z-m4asb~oj5`PWAqgAX9sx%WFTh3;2Dxu*=zfV|%oM|L*0`@X*G5DU;Gac$YMl7mC5 z<01ehku!n@a2EsvupB}LA6cLtaMG|@G4LQ!x{5QZ;(^BSwYnroT2sZ`{4;%oRvW^a z)==fEA82iD6@EUVUOzNkdXl2i%zZzHXLoQNUs#aFx2v)w+8YL3N>#Xsvb#~*O%tkd) zH~#4WZb`f#h0wlF6C+p+&7 z!mw8O4uX-b$6qkyplj){oZL(O;%A#TZx%9ZLn@XYUCnQ%yr2ww4g!Znlp00UPrbYr zlPCbYn@!x*9;mn+ifd4~s!g-vJudxg4cLOfYr|a+|E$o+c^0^BbI`fg-f!=$=4_Y~qih1xF+(pLlu6L48dv!#Xx|@gZAVse|o~9UAC8g)&<^1h*kW`5DJIDDgP} z<*NP(1f7fQO*VA8mY@w1nuo35zI_0h(dVG0th@%|u{w<@X8O~1npMXeOsI@dl52fE zMIu#n#``fot%%?uoC}^L<9MSBBQKrQz?aNjkOIr-8+>!BSKt4Ui;G@ok;fLJvj?tn z*CkP`((9|DV@Q%3Y!H8lKpbDx2L6U5fxRyuZPl3da*Qulj|YR2e3u|jAFKl<{ys#`p> z-+6XjpFI{_xQE}3+5k`Cxi1_hU(hz)v}gXv+whG>$6M=)=FYTb<}=MRkGZQpLawp$ z&2ZJS`QMzxZzSdfxY%TIyb!Bd$Tjo9(?`4i#M~kX2e(8#IdU>_#$m5?0&@LOS2Io& zpYWsf8t~10ylR<>sVv#LLB_b7d{nZbVbp$37|UH0S999t*o&#G`5QQb6F!q^E^c`1 z?Bttvi>#QOS~=s@Ezf*#-!3NP7tZbyqlI{3$69znAb)=*y`bsE~IwL1UgmAC(e3nSx zETHNmmtJmOdOk~e?q)uEh>yA4yVpw8w0G~$;;Y}ZENFh2Lh^HKo*v)*0me4;WXLj@ zGd(DOB7Sv0&=7PVD>S6kH5-b((Ny`7s9($keY`z^2On5NX%wpYwD?~==!NQkKDcdD zm^$=O@sqC`WmBq(xR@w>i`z|#uimQA0;vH`c=|xR)9)_)`1SmibcIK! z9o@Q`Xw*S*?;Nyy!TUKZ;Oq?uV6!xCd3PreEp*3K>(V zT2du9U0KJ$;TXRa^2%LsLEAiN1Gz$B4I`h+P=S4c_cbyd>hp8MC+_*a|Jff7(wGOP~9Y@FQkeX1s{L=k_^8Bk7p0D}^z2U~t z{f5W~5$_}lm(cfxLgERxi+1-e7M0l&VKe-g-H%8cic$)ug9!VH3&{uAxMhZeZ>^ho z6&{*ZU3i3BTE)qE99o19{ZK(K78R2((y~jGy*an+%M{yMdSQ+m?I!w-8V}`W>jRbt2h%LSv2I5t-CtLI8Z2}B+c zKW9C}hxK>*4vvm4S}!i{1znQ`E7;jfpot>i__z1SZLc?LnHNDL$csy$QQ>xx;D@#v3nYAs=(1i zqZjHjgz_ijJK)5(OoG)eqAhEqB*G z{h(xE^0X)<2uPUkzj5@>xW|OO6~@NKVqhmRTEnOr{PV9TiOb~vubKP4&VE;mk6-Fu{W+PTO;rpgmN>0eKyhu0z*ZA%y?Z8R22$)mhZG z8X^5kgDK_T?>hf=2_Y%|XJLvnpg;XaJrNLTF{_B-9{48uMwem?P}pfwA7eXiKCu)0 zGln93tBq~f*Y1UoDin60b#06J0YuWaV7CEwC^SmAV~|9;4$0x{wrjjDA`{fb;g&Nr zNgMZ;tlwFXGL`S|AnzneTA4IFBLcFJClwYJCZQtb|AGQP(|4AZmUgJ+_Htni*$7vS zCZghxq(@jF=$&yc_JPY*m3eTWaqo8YlGR(?>py_Pe-D!|GmAq(AqY+uS;<;0p-sDY za|90VGZ%miE5c#3A1!;4ko=0*Fy5eqN67YveBnat-pFJj)&~p_UdH~%EA|%R#@a^T zi>rbS>cV5^J&E|S?B5(vd4%`9P+_KllJ1=4W%Dr_ZTIh5)uHrC{>s<8-Y zxjP559xAo9@Mg!g6bxhxAM+8pkOy`9Ye3>hf_0Uylmq8b&tX_IuT`Et+3wIYUc=oi z5Y@Xccj>&p3Rb=q{pJndmuubZmE-BjsaAC1_*f2Vyz6~erGa+gL_$zys6Tm~ZL zbmeti`m$BCxQs0tNC^zT%6f7ykgQ+9%zOya`|^oqN;{SNXRufPpuFubY2<%}4eyG} zzo^@15M?4^PnkDhUaQK+ePH8|fYlG^CuvxS@m>fMkuN$n{aBVFGk>wKaVGelCCiox zBuGPJ9CGl9%B)-Txn#zM22J0-jjVLhoWc6<8QsTvcJ1E%0&-@|^&IT%M@|a&w20<8|+gT{;g$f`Bt_(=KfrEadElH!m>W zd3L8SW_xH88TS-S3MqQ^K*?pui9Ni0*2|vt7^9oSzjwju6EWeG^aiaQLrix|B>_x(ob!F)xNaE+a@Kx-qbEUu=huMrBXiKuufK$K9FR%Ap{44Hg#4<6FdSdQX8ru# z&Bev+fuCFEc{G87Qrk$aOdqJg*C$+%)zDyr3OxsM^ZIo=x9QK@RjGnyS(27tb5P{~ zbjw8~>b=D-lk~`GJ|^Ok)YaA1l1|F!I*MiyjbHqTtKW-YKLvbF20DTKiZ^N4IsGg8 z=3xEB=#{LjMG)gwVlr`8dLq+(q+sXlTk<{pNXY^b!%z0u{?AFsfoclRQ@%m>HMn;~ z&kjV({~Wb#tf(7`^cX?%4)XijtWHmbpIq5J96TS*MJt0B$M%9hrWUM#b(r%T#%UGL#_xPH*OMJjz(H-8nM|sCE=%=_P0+JCC6GUE4Nr*Hy|OvN_{MKbR7iLsIZa9^;MDKj zy~|X86J!%f-ml$Z@G0yh*T_Iqag6R;Ar=M&Z($mHFui&^efy&^-eDI^R9jT~0FUV# z0I46Kw(B@2e*b>QUbNcdr* z8v}_3pxq7dQEqocfLHX$oJ;cia3S~q zD9l)at0%QVfVhUuS<;AF&!LX8@#dc?PpLwTfI!`Z2<`2F91F}!&;{L!$!itaH*das z#Cfx>PZg77U=2nJq1HwL?o-%$GPe1u+IyhDdN*y;w}n$f6ZbSC+I}8F$^Ku2E8}Rq zrTPyKKfn8R##{OL-sFs6Yzv^eX2(U^!&2Il7l7!2J!y^kj44O=rHOIV>~dmkh%eoSU`gLBE}Vvr#0Em z`G;cca1sh&WQdty#t&++lrP)fyKO>gS6^J+8(V~i6x5ged6J9KRDVO`Oyx6iC8?ww zw6$GxOxoFWD|DzZUWQ61QJvn{ALs?c12A3S zyNd~N;}lVF!XM6Xi}hW!MFYf)RjLrTs%-_Ku~yQO8w3A>!LO6TH3(5%|MeD=99FDd z`vLHVib(vUZY%(S`G~F)qUaFN*(2*2jQ2KTo&x#nfdQK4HW2Y%m~?}qY{7g2Or9FT z#!v@jT?!y|DTgX2=xCiorfFm&8wy%z zgf$Tszts^ELTLxePslhSoHS#oh?nMJI`}12e~@WAbk8fWBmmKM3o@bONXx*I1NUDv zQX;8nWY<-EXpTcVZ)U@D?!Q)R#HOe30^6m7h}=`!02=-DOJzSYGcpz+%8m|?>{KyI znnM_+uj8(I?3wlxyg83bSV0u-nWiqLnm3jYU@X^*9+^KIh`uF3GcyXX&J{5A3(Mz$ z=QkKm>M)-vKcvpLyqx3N{D}4c`vc8+V1qZqo%3it9)6%D?kJOj z0q@H>ue1Z_Y8i^xI=Dc2(9**E;*1;Nfs}?^Ps^L_#DQxa{~^3*K70K|nU_LRiaMUT@rUA^bFIV8>x9*f{~ODY zL!1tupkI5|uAF>_BU_(1Q zI}!!M3?t`Us`oF2xda*C`C42IQt=hLObUOAsyF-+Q|cd7tpYJHkT)M=0Byk zV85&!JEVGBal(-X@K5woe_*`^$@mn2{y6had5HOzlF2{@-z(OZD;v$)v0(9EMYgEw zyw9@z7G?o05CT|X63}=L)BsvUAz-TJjhZY-J*d?RQJ@XTz$)TQi00a|rl#jaNVRO9 zUL(;6=(XiJFsTnQ1GC6 z>Ee|8t^a9Ja3~lozP}i(tTwx6$LO;lr@P&^1bj4OEe8|RJIrTuwJiZJjA?VPF+mH% zj8WNW-QjkKj$zk*SJ!srH3Cqo=O=D<3x&{xwoJO*{4hIP=H9(~2>meQuWDcSQ3ZvJ zbJw|!zxareUvwtgap#sG`rl&Rt$!XVh>?kVA;>Z}{ArYXXV;y0m?zp5HKFl;@qRWC z4R%e`PGx089;YjYH*=o_M|YJ+oG1&zL(;@H)CoK{?Qr5jc`yc z7~PrCWATW6*E7^GG;oHzevPqs2jDiAEMA=QTTF!xBY1FY!K%?(*4DLj#tM_YsyX|= zb2NoAcXd~e9PU(7zPZMX33S^QtQSuuGfI#{Q+UnPe=yD@n9l_8+(wSs(=S@oZqj-n z`;Xo9;G>%qGU5k}6d6=#-Rj6J#7bYY9Bd;G_R#r1c4vNbVHR# zD0w^nlSb;@%-^k;JV!=k4Rw5={QTbRkExcQ!c}-DV%`q67ZQMbeZ>euQ}Ta6nk0(F zJ4+_0VWUv3U}1TWkwxzTUc$68B{6eSYNYn8C9(&3%90<;Y|wxREH$6er9QSSi}pX$ zZg)VtW$k%=5&2*YxPJFw-61Hog5e}rq^fnTAgc^Tt1K8MMMRD~6-kvSK`r$C8~@v$_3$^6Ms-biDqTRNXVCgqMaXOm7JE>_H4N?g!N)j)WV!!n%K z4s+AWXZ*|IlDLx5A#<^|&VjBu=0T2Bir$|~OsAkPjPX7X`wXQv^Fbke4x~Oa1 zA83077n$3^+_-q2YzoFL===pnJjmxE=F`jm@zArsabo{{eLi0&j};bTonr%h$cL~I ztNHY8{>=C17v&C8Zv1ATG^GskIxybQeTbi+XxMoCt zb3yGd1S2|oKF{#ECqg#i`+utfW^U@gf0j#|e`4hHx{2ZSvn(a)?%&&?o?{$KJZSyWMP}ur3-gkqlj+9=sr-waC zN!6SXO~Mjw?4A7nAUk;%?d{yu2iS6M@))5@>PY0}AtAr90AbRS<;%NaLDDYqIbd+% zDh>|2qyFCHPa8OFFJuvHD1OSWg%PtZqobn*zH0hm28FaVyNry?{eva@(pG_jHZa%< zkF<~!<*VM{!~O3+^`ifghW#VEAo8fi4dUxKtTFsfB3(j>0TuqR)u^>&v}JsXF$@&^ z>1Gj;pW#mHdn%&V_q|<~ISXbBKlrzI_V)I6JacxBoZM~4Kg`OAs?~p%{`{vCvSDB4 z10U^@9z*tu6~F?yv(?PZg&+|G(*J<=n;WlA=I8;(xIKSva?=i`7E|k%VZ0fdl2XYm zxA^nN9nQi)LrUsI%gFmpkKECY`cEFuJuaEne<~h<6d4H7fZAOK05E&vNM`xBW&5{FJ)(bm?+jEmwn6Nv-Ue$jKRY1CJF+4ox&ymEm3 zj@UMWI#LRj_t5*^3}Ob=g?n{$bncZ|C6c5m3Z%p>zml3z<~*8KV33;hIlDT>U@-I&jAwwBhp zEx|zuO%-{Tjx%z)PN=1%r?1AQt}?Qc8p4LgzewryH#*Z-lx36Ef_goHO-B;GAdHEt)Y zo>1QpJ?wiB*iXOwS(kbwb&A;2{ESl|cDnm7G0f^@hy@E>D+*0~R>JVOVb znj}3~FP(6e%T?(LDc6Xx{HAnXY;XRtnOpCDgo(f)!=AoC5$`1d9r{yoM;|WF&yc=f zAmCy;_{%pWYgG!?#6#>?2(ZeL}^MqE@-Bht}-;YSTI`wfSTT~7fj(oT3TU@h$NMVfc)0eMCn>-8}A7ox?-^4WLGp4pb+(mXULG;Nxw1Gd! zxcltMA^OzR)XHdWe=;u$3iH%I&~Gz{k%uv;kPTN3+lM*vq%&_SvlO+W=v=D9^d0sR z5H=*(0Ed!b`1uwFYI~9Y@CIxLzj-NR@ZgJUU291m9pxpk8~0K6hx&jDJ2s?MF^;Mj z8$f;*1Chau_~diuQmP{u&mTB-?dWkpc%&z7k#VvF`el)BD*`I$gR5i4k|cuF_4i=U_FkM0fszx-{X4Gf_RFI_;eiMlrZ0nVch32$@%}C$Wv&V zrl&k_NPK<#X$)`1zM#H;v)@IS#H?gSLV&Q)sqM(CBHIfwb|;iIQ=ko<@LQ&Ek#_^v zNM22Rhi5WMDFFc|L^bVJjC{ZO$CqRm@EV`MsM3cV((<4oiGn-Y!1T~xMB+GUY?|6%^c>cJR=oF$;MZl$Z#n zUFoOWgSIf#;?SeWhtyu;g&@PM$pr4ji*;J_90@f^jPgexQCD~$yWihJsJlNli}_JQbVmDSBOkMv8J7$UzhLJGfc8a0@b`?&c?EEq^@n!O$%(Wu)F!Q_qXJo#}-P_-R))^ zy=hTpshBZf({1);qEQ2Hv18=wm1m1xr&@nc?k2b!H@h)E^_no4m1SsnzB-R3d=fdwbm~1JnuUD7b zyz2fsv11>9G4ThsaqKrKP(|J#AS~=&dAU;XRB&+csGln%5)nuoZa|5{9*b7xlP7QE zuzYH9`@d~4!|-?1S1hud9zTzY@X@STso{@1DE9H^%f7^ql~+|U-tsxr5C@DG3ZiIB$=-GadMD`5NPE zq9P(KWMXu-=Uqof(l@BrfLY$CAYehBmg1wjycuMGW=&?rGyXF=7caUZsZWRJ$ zxx*3_2tyxhiyi&nvVL?G|S=n-w7Bi1F*~wh`!xq_pv5s@)%7DrU z8Vbn*7x<&p@8~3|;z;o>QX;p*!+B5(ziGpUy&AlE)zzmo%5+hTKw5=kF$#?o4N}O& z^!41_U)?zGHnJ{#(DkCKdirj|Z?VXvwj+lQEh;T7MJc-j-bDMZfqWD*1b1XMp>y>6 zZ~dgkPtUf;(K%A1Nc#Qz_c`D$gmiN37roo~^aF*$#KiPy>_TPqGx|$#!-|VGe6G&t zEDm0NX>4Is!wdDh^@*WTQ6w8fCho3bW)6&vU738TDGyV%zhCEAv}n=b`2`CWu&i6x zY+-fzWomc-$TBK=divNK2M*B4A30LMvEk+TL`;1A@PcmdEnHk@yFPliT|rp~@PR!@ zsGRrj7Ylnc;E7~hjJ(5y|3yh<`ghU#w$h3E%E~()ysCOA#Y?dr7w+lpRa8~w8ll4_ zzlw@l25=hr0+WcAqn=|Q5-fPn9boeb;f7oE70?8YG&pT5y6YB zu#=AuYwWA%n3atszKw}!6jD|L1MZ5Fc$c@!&g$v4barlG(god*+;ahvoy#|E+T`x; zPN66$D6DsrGerSc(CgQE6&0&tOmcuh9>N8Z5@`9GEXRGHy$}=-C2e^RaI39iHPK*N7W%HXfyHl%a$!8w#y8o zzD`}wW@BS}{PgLjEAEY$YpexB#*|#P&K79GYAs`?y))!y)*vH2ODaS=xs_d21N2U4r`d++c80~KeNr(&%c0?A0 z%v~ClYQ8-kZI4@pW9F1BefTDA;ATW5i&^ak+~?=jx-bhU2v~;7tQ8BX00E5Dv}B~D z*pQrxiH*(u6d)U``<8YRT*j!z=~n>(RAk6F+SMPzmh2Jm41_s(_wL!GS}>=GZTs5P})WCZEam$ZcWW-)HRFg>FH19<+rl4 z|44s#Oj|;yB2^N(I{eL>JNND_;o;$_%&MFmbgdEUZy)UcHLk0wy9|<*0W8Oam3b&nxFnsO!o{g656geShd7-X2-8oEG%q`SZ#Q%l$p74 zJx;%|C*?H0?ZGdtoz^!_ezCD9l>Dac*1AKK1-j-6hg- zYaPkF@O0v#qkPA#p}w9KRDJsQ>kIeh0Ht$G)c0F)D6unXKhOE|Vz_`tj9hYk9&8g5 z5SM<{qB>{8Vrn}ix1Dxh#yx^cAp$ z*vOWamd2A>jY?8iY|OJLcQpELa*}(Ep|P>@MTSQ%%5UoVPxCh)lbZk)p@GgBJve74QQUnKf|Aa}un8swip ze+n7b3ZX=_`PU1)Vx(;1_wU~<;->2n;(z+|Nh*$sO< zAPI)!Ff!PTuupJcq-fz0iZ<>QV)o^Bls$j#>B-B>qXxF4*bjG?$*x%V{+w`ZKLY;s zi>XomxrkDWne}*%QJU#3eSHj?nwo&dg5qe*gS-gsjvYH#SXuQzmw-2Uq@-bGWd*x* z3x?Lx$_ifcHf#j<8afmov>27(1o|wQz+#X6`w0B7lN}Voh9SiaFB+F>rCg>pqNZ|_$4QM`_h<&!Z?2M->sMYf2KpI;G6i|V*s z02t(jpc^6xZo>gJE3S@?_wIer><$eJb5Q1SM6cV>@UY^kQ+J`AffUX*Mlb9^$JA5_ zfIUxkJ)#;$i~T>v{1o-A0Z+juoL@bc0>dsb5L74-t&eL@)7+4-l9 zO-vr3Q;t9&l<)uo0TkSM_KfLcNy+zXk*HR$tgdbYe{jcPuLYIQ@dI6N8@af;vkFv!6=4ymu_6?EWu61TG*C36BGZS7D*&Q@ z8QGLUn>&N%qff_DU(Wo+gcPXYz&gOa1>c*W6X%UtxqBN)8yg!tdqF?QiRI{^g_qlp zE>Kd>OGX3&@Og<`SVhr+IQv&LyT=UpICR#sM^4;$6Xr?0mq{|fPoeX%pk zx`YPa9MxDa2TX~TqnJ!}X>nU=jBY@2;~FyT6p28%xrYdw^nmD2W5g-tCHy@)dh-#W zn2rzWSJu=7Mny%HSftU>)9dQ%Z(-7+v~+b{QB6np0WDYz^7e&CM0~ETU3~UzyVGwz zM@L6fOUpI%f)tirSNO2)kNNNBXVONWs1rPV?K`~TAY4bKE}uNPnkdkK57cTD!i!`RO&85tc>p|o%7)4e<%uMn>_ zU8=&1wQ|J@3StH%wiaYhjjVgdrv}fE()66>$@;~Qi#tb+{XIM!5xc#usbNNSB>@Z& zK|v5f3dAY)`!}X`Pkg`1KoJq~DPCD%GW=^mbW#6E-YN=;tHBsJkaz`8=JAJf0Oicz zn{G!frR3)3${jiK7EtW*lPA>L+Ra>PI&|2L#81W{YN0|Jvd)1__UOil$`2nCT0PR z6Gnjmc6fM;w0hC(3`4XMW8FIU0?eQa|ANKGtMc;lo*A;PNU`h(h-o1O`NE zFF$+wm!SKzXG!CYPq!Y;!`ru#g~b{9V^Xk2X8b9w!}m2ZtXE#RaDi-Mte7!_3J`?Zwq3hx4c@|r1F#`i= zkxlMec$MA(W|&U>wt{gE02l{_BW~WY7(L^+qqBa~AyG;DY0@uF^kOx-Z#mAF`sD&L zBdVaKlw_U+XP%2($BEOYok0c#OPG$HoeKvL$`(H2ECgQ{Ug>%shAby%58U~ph9nbN zKu0o78x>m4CL*Gugr2~yGxo-QljJhQI&+p$h86))< zmtS|~@OgPcDu2OBIb}7qB~b5DR#uk!dFTB|HEa-?=@62~SKWKKKRn+y=;0j@M~Bas z6oS24!^o%$aiUKZ6(_HXSJDEldw6)jfiiV#Sm|TiJ2^Qm0?lsOtd%#>X>;b{f~YHU z1eNaBJf^A1j%b;PHz0l8>E?8PH^Z~EnSZP7MCaMssfp1-03LK@aE5mH%mQlX&|=IR z-3NOKqSFPsb^rd0v$Fl{)0N&C)q3!`=JgKo*%!p-96zrZFu=(Yw-wTA{1VgR5gz7= zBs|z?a}GB0YjxzhqM{;-h|FdA6$?cV9T?r@S*)n7{Rp=wAlgg|eg`T^`_#I%VD{5XL_2 zCb_C>lhx*rhkCfZT>GPgw_1O??WJZb{R;dT1p&B+&!(A-@2iI|!^7#eZrwU6CBV(0 z{6aATUMor?l^Q%vq6{Z_i4iEKSbke||G|SQR{E9y?a0RiPLKmUd-iPfhNayHRiSjmMCVdXW`CEjf*c{ zy!iFow^r}-FLDuPRI#tJqLTSDxdYWGIu|Z1*}EbJrTxL}c<%5B@ZmI@S1s9k)aMQw zfa zl$x4%nrz^)sMoJ)A3l6on__l0qEKe6WdV3iQjU}h<3R_a5L7L$AY5Fjrw?ojIucxv z+u4AOGkoA!q0F=cVdqNFlN|%%Gbkivlb9H@YLo^^61{mB8W!J!{;gAy>W(Dy0Mgq_ z+-xI4iMt2|sdWUN*dWes2c7GP8!5Nz3S{N}8rId*6TW!qQpRLoAD=aNR{2Uc$SnaIYyz4T+45 zM9jwAu!f0=hr$i492zAQM!#KDRK*sg#K!|luGpxK_!esI&X8EX0HhZq9nBvTW#$oE z=>jmAW{{6JHSFbjLj^plp4G2myN?lu}%@`RODfTG# zT0kLo1bZ~tmJP+hKsSZ9L0sVgesF~(%s`A`;Z{kWD^gvrl)g|+CM#+tRI*c~(*TEF z;fo;M)BmWu|_v z1{d_wvJnAgeSN+BxHVcifmPhb<#;y0POGXGYHaox`tf5As2QNHF>^Dsy?gf9kL?&% z{6+3L8M>iZnY@Am8lZRLNzs}015G<&yF_|AfY;4N`qa$Q5tIQ}Ajl-GQQ+$x(2Phx zADYAVC@3%>ECniv%z7Dil5XkJ14xTz{h7WF6L8OhahAK*(bKyH@en;Evc4jCfqjGk z%Q7q@vaJV8KA$`vZ#}3-IzF&&vMMT!N+(aoUT)rvXl*<5;o$rC@8_pR^D{6odgv<#AH7Kg}{!gCVLc~NN%})!7aTptW3DRFFYz=bE zu`Zi}qh8{90=*ps!Gn8iX=$-XpCd^QQ@mU&V}&?Xj-LQ~V6|vQ{BM6{omuIOqnoj? zvu0e0YL1?KycXBi|x~>AkWxMrMnY@e$By z3nrPc(%3|(51~+MQ!TjQ>P$O}7(u}VfE=?%wm3$wz~$6g(CiRRA}L{t2(#tgyLW5R z1={@r1dyKJ%z~0iKzA2j3buIqSiG;VZ~1m?agbA#J-WIZNW_j^f*J#QBupzpj)S<; zNHwPc?j3!AU~TVYT}}=KoEJAQ@Ab+@05ivDHcDkD3kyr5C__x9+~y}c6OpbwRnN4L z$~<-Q@Ev@Kec?=u3gi?Zd)1_&u8xWVuG%`YuYlDL5Wit_S($YxSe(5MLtG8g3|P9$$AZaXFfT8=`&f|EP|0vv)% zhlb3Nq&|!Ex6qCq3n=;T-nEeh2CGgg6qHp|HV6tXM+6i;^%5rwn6c3U=b^0$Qusu@ z7*s+u}qH2NPqJAd7IYdr~0z%>$Jztp?eDTKK&wlo^_v?qpXbGaz)TdD>6p@sqm@Eo)42?qJUOI^n z-*6Q@OoRXMTi#c)lrzz>wAL`!MoDW}ni`r|8tT2g@LJp4LeIpQlZ}^+oAtsgOG{G= z0d{ty|6IUkVy?@+7#;l#9&*Z5@|gt+MWTWH59fy{Mh}JZn3WQ{BX1Kq(`Rijuduhj z*b%sb#$_fwSw#7r0Qa=(=WCvxY%DK(6w+9yQQQ>-zbE z=`E)m~C!4SsL*_#$>`{$rKF_Dvu9S4)r!I;=xyKr`t?YLw`z7aXQ29J+Cl?+iA_E;BcpWF+$6q- z2bb=A(Yo6AiTUDfHZMx{6!Svs`F>r?s19`}x{wBi)b+j1W~cGJ?Rn8})4Y_Nx=o|- zXWg;-An)^>arM(DNa(d1!?}Njah@nB+S|vAu8WaS#lD!qA&|y6*JWX0;X&$bcNRgS zLdo`7GQ9`Ly66se8>A+$>|kOXUoH+;DSV7!6%~ysEiDyLuc@iQsLdYx*)ywq_Dp!d zz|J`DuLxe>&E*M2nn;n2!DECKFUEg`!3a4wmtUQ9babRID)x{xh*eko;K7w{Hd6gN zRbBLNs(N$iP0f>pgrobrCHp5zDb?-E?o+CYsi@GxEta$0K_xq5?0iv84`R%g!o$bsHo`H+H6Dl zJA%Yar_H4?!t=L|J2^S!zn-m6Of6Q%Sjkz8|GLP>7rL{v!;-3M(a2p{S(#hXr0%%+ zPAcFk*|~G~Z{J2m30jX=)0ha2O(-&nh(zDitX`;NiWxNJODGg^+OtQVwlGv7_2|*) zT8{}vw>kRw@#CcD&({Shs?~vc7!;wc3?grFa^?-ar#VSLa7jog@>zzCf?%WZ@_1t} zSefNyD;^B%<;$13i`6vzjyt*Ak%&2n?k)PFEa!T=gvT>ae~u&PQ}&D zZ4->o_TLxx+NP%QNlZ-2s>MWej0_r0T(UcB0v;o@`bSR1adT{DprqvQ6F-H-r;Biz z`SxrM`I$52%gv(AE0b+f4<0byx^;%b301sMPVm9UXY98GL)E0^Qm3Zx?`)$UgKN$Ach|}3>6>6jHdoqY z42s09bebaTl5_g&tp^-xswmZGM2fW=D6)hF;VA1}?fnpP^Z<5pC6;D&`594vDy z+*xYyrs4fK+mjRX*Wy^2_h-Q&(Z)9uvtzj8qW-(nEy5!{K z74UkS*{qJvY$F=c-4${QuXo_vk$nZ$%Vj4R7E+ydy?*?-=1g5OA0HndY0<<#Ix%6< zp=wPAMkF|2SaBsprJO0ozFa#*_37kJ$^P!VQu5O|0E6`ObepMoOenv_Rnh$&i>Q+E zaKoN#AB$$;kd~Imdn*{xp^=daF!lOevk|4Vmv|NKBqx5EZd8)Xm@YT+avFAWq-SJo zj)kaq{?s@|sbY$QYQxCr_GBCN+D=4WzI^#paB%f-l^5(of_2(iGCw;`F|pXPUb7my z>bm{Rk92~6QQlyX-|IKwqwsNeEvJMV_t-I?^76auX|NLKqXewXMMX^qopGrA{QRmv zkTdnxlxz$W9OFPXX+6!I!7=wi1gfH=qocFHI(54w?;E7{-MCMxaBG6>P2YImCNNP4D;sxFu>o)*bA?7DS~BlyPi zago9|5T>bleZlqmx-Hk-#$BHmSAe*g83{fec z>EP|4WkIVctzY5X4ZAzhZ{}{IGy!zyH2L}Y#V4Agd>|-POjX=l3j!yp5NmA}tT+P8GMjk>w8tB_+7v#n%qo=$e=%u7J-Y6ru?QkQB#MEQ{k zEiEl7=S8sIm~?4~3-{$##l*s$V`3OGbemJmg)Uqu-Q{Cqa$i}oY!Y5qSz2E1%Cpc- zju8YWfe_c*+zj8AMrJESoFc#4l4YQ{z6>#ml$v_VF|}<{tIq$*qX-_K++4nO+rE4& z&85-0EXU%imqYc}Q?<%m@kYnT^L?FGeoJJU3`GC_CUGp6fWdxuwWA%KDyRy9^HJEX zckCrQ{)L4?rL<&QuqEejX`K|dTS2in&C?N|sPSdMJkK$H>+YVRQSrVlf7}(10HR0l z>mH*yO`ZrJF!hZ3ymP6~m6Rmy>;x`}d!zVfr=J$?{nV)F9guS#9DHG1wEC2oUZ{3$ zw&!}3=$kb|dk2TUW*N*tq$f<^_t*Q#1lUybbA4;7tCu1McHRT9_(eq#g*wfFRckg! z3%5Hy1xzn4E@o9Pj`a5S=F|`Iki3V4emz`p?9>%E{V=1RY_l%y5Hbo1aR5#Dn-yhn zZGC;hs)gX|8Kp_vXC4U+B;iaYIWxQ3^U@C=e*65{8A6Z(e`>yFd)Q4)d^|indvGfh zELr-CGF&V&QOBog*4%Q~vZQxddGht^*W8uXhqlwnIoDWN656;EI4#B>EiEl=412Mo zGVb;POkF?s?%K6$gJ0a~8AU|sA(p{SuX?g?goTA!ZS^Y#hK5QS8nObU2Yp4K$W zLPrkH70h215D0g6Ms;T!Jp}u6$=?m@u-u(WQFz*T^XAR8)otj!YI<4O%NVeAJn;G^uBzR2vXG8`d008#*o0RMZ|NHl<+WUM3xW@el z59-fnJrRp7Mz~h^?W!m5Z^5v<=>&tNBX|}8o)_B{)zfSiUq;(6NjVDy6=ZiAw$t;X z(|n)YE6hm|_oljY_bx7j)6Pwly2I)@Sg&89H!B=Ig0%(6h?s?(5;Y$^$=h#p$?XJ5 z3YV;v09*0K%kuK_P*Eq57b$odU4|+StL<|ZbA`)jdZ!(;l>8|ck-ZH~iW|z609YTq zy$%1!jwq^Hol7m*6DZm4o8JJpd6xOgui%=5W(Xg9+gYcztn-{YgxhPgBM?Mm)k_=; zA^Ju-taTy(g-7R2(7&GVZzPuyaw#bhB@x-UQ1oVf9O#x&`fE>*z$aibi=W0CLM(PR z%=#U-jpmBCjgetqeH8jwZz_r@%b}kq<7`FieD~I}Yux4SwZC(WCq z0WzW71{C`nHKMu0p4W2+T?wd!?JSFUB4_`^lS}y0C!bk)J=?7?X)7*{|1gAY41)0l zgwC<_2DTAb0=6Gq$;pq56bNLB_v$)ud)tHoz~m>I1<1kFuW)eutj>l2GdwcVSJR!T zR{^%QIp{{hXZerx7(U^kp9FpUN^y#6!IHb^j>~;7iZrX~r=DJ3n>C_)zdO}EJtWT| z%#mJp?fJfE$rw8u+xWo#UJfQ){zIdVX8GGw2s^vX#8lur-&YUFH@R z5oN8EYkCp(P2qb7=dD`_-j;;aTqi%bS{6BMuces`6bqE+(Q1Nidf~nCjJRp0A6IT ztoy7eA?~mDze$zCJZv9_Rn!2y@}}nY>@hAN!nDF#US|Zy?cEIR;}IrL3nn`HtOpv^_qP-&*wudh z`~58svZu73*}|=qTt1m z8cw~|%QCzq98Na-K-lwOOKf4_AAEf$(rV~6Yd+FhC2T3`0MZHVZH!n>|Mkge7Aa^o zfM2vBJwn_Q-gSn8q8j3o4Y10-`{Yv<`dQ|U+#L%5GMwN`ckkY1Dcb9`Xx7N+LM~xu zW!3ug;|c4t^jNilH;L`_uq$=K>%A3D``hY}PKKzMpF+HuZ#pT1B}x#o3Ix~?Vhc&s zaODSk;Ke~Kl(>X+0)a?6RJc@somC~5G^C-*<=BY?BJ}Uyzmp(|+@34&rBt(V0se(g zNL32lwF;PnWw*MF5zEIU1xv_iTXIa)pQfnP71}P_41ZuU%~K&{5Q*I1TQ8XtjzrDn zPqP*8EIkAq6?^i84Cvc1(9^^>BLf>7HYs`I)WK}3^>5~j-203%im7V$z`h>Eh!mBT zTqX1CRw6XnYLA0Vm7pz7T2Px=4-)QRaRb6e9Ph(9l|N-AC~9lD)0#z>(K2mmyIPfBP3Q_gZFE;D(5u#m2@C zPE6F)`d!-W8Q6wT|KJ~If=BGJYlGha@54NL!FsEYU@>dE`W$xx}QtE;l6rhv0NJ~Mw%o=2D+ zZZvR}d-3AJmoHzYc7~t)A2-liJuCkMMMc!)w%(=Eru2{+y zhF1)g8t2FcXx?WR-jq(IBZK+NM86~BAYHBKO8FQ`*o4JL>DPrOjtBR*L-Nu2+ z@Y!#0!1joK^J6+tR~AEuhhM_Iuy{b*?eh86n#atasHk|Cl$5y2(PbI+1OvbfoANbX zFmmb2M=PQrkJB0xAfF(hVW7f<^+IEf&%d>YXUyYzc`y0ARK9ADd(+q8(<+AP!h*xsgB7O z{(#Wpe|-hKkgw3jIPLKREl?{e`HMh=@SC*-$XCx$Q`bAJ_tgY4%XJnz2!i_|N$FWi z%H;|YQPQ(#Dh_|A>C^Z?w~%Eyz|f7<5#E@W7Di z0^~n?3nAyE3c-!WU)2p);-;!m+Xsx zn;=X`#da*{@|7z$Au#~rO>#SgO|^Gk=D~yEq>QGQwVy6J^G}T@pN$lHWuihjia6wNPv_5O_rRY7Xm|{fkOi4oBVB2s z&tE>X_1Z5tBKiur!^a!XvpKYCNfA3kAu`v? zmyC!+B85ilfC$zL!HV9!-%OBGC*`TLS|F7eJaS@TC)Vj0E}dH;|?EG>D9j>jeXd zeubsPkRkN#Dg%=bLpVARcUzz*wxIt^^+i|5#@o@Kr5`1@9bIuWj`pHA)Y3p3vY{yi${s~fM9V~Qqp5P57bT&2M`si*Sz5d z!k^y0eQOF1)CT$pf;=cBi9r^{mtMHGw)RC=x;E%kG|ukyb{>#nwgDml?cUg$PVGyz zrNLt&VWBarXV=Ts&_I@GQDlE-LNpK2B*AJuJUxetx92Vi3KrD$m<>3r`}zBquXd>W zHtLLkhN0aWE7fV3l{!z&sq^Uj1myGn{%88_rf(djMG%FMd<){gsSJ&!KosJzv?BJQ zz^K^@7w+z@raIw_tI2~VIs#f7XsD(z_@yCt2A&C;g7e$=?_Xv`Zzj-$G~5TU&6`R{+-OkWYen5y5y4DpVgiV`hDYxVDUVcv=O$2WBwbmoqU1LnM3rndnh5oArDBFj>CciWxlU=p|v;P5_p1?^L5SrH!5C=H?9xWpa3D8|p#s#by*S%^>;W*^2woGB z*=E%oV>$>g(_uWR{s=hTal=>OcU<}R1Z=YRbB90|0JF4>jmdou`phtcU#hfs zFJYPA3#!MF6JZe=f8swt9&{7#7=x-xilq>sB;u02mTl6s;KT+gdG8@qkV6dK-`hpf zT=ZrhlT16vjU<}Y-em&=kYQ~7v{@Wxna_jD3uG%N;MJhmzdONTPwHN=leYv99tSp| z4Ww6zm4cPRtDq5iLb^5qNQoj4WW~hA&0zxm5fRglyYFd?UqDtZ1TnC(y7~-AymZ#R zL&Z-WAPAUEeh)cAON%J=h;#vJ@LUJ4QFkSXu@b;8fHD%&3xz^1gy&pYDF%4)KuqlT zojZ3{W_v>L2q^v(+_2Ix`6Cme9F%G%YjzT`K-$fP9KL3i?folmCXbUbU9+!KO7`p! zxq{wi5C=92wZA>EZz>R_0@V+Yt8M`Tf`%jl$=@bqYq^jR{DaK4;yqE~Dm7b(7sSL! zz(&WtO9{37&q+5Ox*N>;4EMH@ zl2TA}Z9{`5K!rCgzrWS=Uq29-L4ElZ$#22(u0p#Zn2d&|Azixx#9($#onJ3nKHov0 zEz423-N8Zoi(ZxIIRIhP8aitZkPL#^)rm`i%C=CYO&>a&OkeDKVXGve{`bW7`Z=Ex3uD z!ExiF(^gx|$&)89@bOU<^r0U;dgRj)4)PUH#zG)($MM3-06)~Vz;lE^(Gio7I7UiF zRt7SFN2AU+NUl^Yf8S?S&CgUT)0=GlZrGLn?$`-pQU(T+QXpIp2Z|k@fp|enO%=ES5!ohWq;jiUjni|lcH4$c$hW_Nhrh$gw}g4dVzVfKF{{{q2av+Qh}!z z&D=y0=tLZ#&_Y-#hxpzI(n9?)5}}sQ9Y1~;hO3PUkk(|f}6!08KHUK!!wG5KaZyKy}5<97V*w@3h3HfvW< z1ZErtwu01pK?VKxrl<{!ul9S0T76cBT0^PJF|Y`N0_*vdWnIV}BESmF09Du14k~+z zim7pO7&IatLCNzi*hD~RsL~{@y1IHKS~s}^@Q2*i)^<)4A*4?egMiol&1=Mbo0%50 z{P$_Q6A-cP*RNREhB-~p?+4dQ_Ju)+9EKES0t#m4B}j~#cU%`lXv^M$yXXQi2;K+J z8?N!$x_oXO4D`d0Az7;5I3pBSA?kCO^b0}SRS!IR&@uVV`W&lTVQ71zBC^GZkoPo! zN)cO>0Qp&`F}w<@KuUS$S4e~wZhyDPx1LAK%AP@73K45JCt|F9YXc$O0`7AR{M`@g z9T1HZR1AQCZ)|UK8vJENs(4^jxywz0c>rO(Z7Wj^la@%)`9TikC>$E)#}SzuumjlL zF@uhjF_?iaSOKzLuCBNUm0ucbK#IChSk;1Z2$nZNEyx`~0&qlN%lJsm$T2w$W{qQQ z+UkMyA4q1Hw@LFtt*b0nDu5+fVrw~O{}=GuM))fguQ4r1@W70dn_>*Ils6%^g2Mj- zif;&^MdYTSro2)AhZ_)~ngJ52xL%RMUXCM_(6R}PDG$n^{PTs&PzEr{y7K$jv16M6 z)_i8e$H4-|Jg=v`0LqIb9GLaSAL7QwY`RfaPrvs-at0+=dw?5odJdgmR3K3!iN?mi zZ@#FXU4}>`1Sv6^Uf9kQjPIuHk`|J}l@e-M_nMtRRBy1>SkRSsAXbQstVMfPaZD-w zEPe;o-K#*Blai9!)c886Kr0N{)4bTjnY^>Rw5KAR^bHenIXSRm=mnIIpgi=wo>s>% zF7E#iC(|d4Wka{upqXg?70lwfKG-Mvi(Ow24{M+0*RNgwJBW+AJG;n;w5u*YP{Gf;f936lfrT(Qk)AL_>9n-8OeiO~-+M@ju7Z>k zvRq^zjcQdSpp->)O8^7!vNsx>*Zkfx#K<{tuoB7sjXHuOR@ZJsK}3m-MS36bFjwO~ z_^B}pmCkH*H(+Ir%55;<4-2=|ZwDbO1UiSGYe0y{NiK;<`DZf77uYLKt;-h)9rn?f zz|^jkA8UZ6Nr=X-a?TUer87eZL6s39oP}a=G2GO9_zjbg{cE}_FVi3uwfObw71i^X~)BYQp~KYXi} znPu^Rzg=8U8=BYL^V1sFi#q6V%6V+Mbc<}xe^hzmV9{>CdOXTKr1l-K6SuUl)Nvk7 z$^a&HUb_8YNkr7hA`xBr%$YMto5;q(5L7|3(evA2Qh*T%Hkr|MzAeu>m4e;Zjzt^O zEr5woL2EV=(H#yXy9eBT6wdV_Gc!}Jcph>!B*#X|ZKC^| zGRAph6re^)1Ch2F3sOWneSq;LEefMC0b!iFOYrd4?+-(+8XAop8O3_qo2B8Zs;VUQ zl4#rI@jTyW$xi{YO2fGg^z8>gVi7NRJ)1ijhXjc+=F}(h@*r0GZQH(n&4VI#KjvPs zJQSNmq`m&dkq3nyrLeuf9lOex$L?w4zxBXa|hv}Lg`JrR0xa*{6!4HDgT zI^T~Ub)aI}UaZ@mpa7Zgz6Mkvtn#a&0$BFVS44Si1Jqs^ztAiXZ*Y|t<*}c<6}X*} zkEC<~-lB~HGaqO>JgKBP(0n$uUUR-;8HFZ|SYlyrwkXcixPe|`R zdd`b6Iu;9~PYOS5X;!dA_&lYA$vk=Tq|=Z`R!;6Z9n`F@T)i4szlp?5*rZ2M0__gJ z#>{bED1aq^n?p%=ig@>d~Z`z*+J&i0TME&34{)|@0R&!Ez89ERJ#}GF+V}PS)cWP$Tn2C+@uMM z2pTxA_A<@=F8o~EDujX38~b3*%bD^~djyzPhE5|Qb`jF>cta0IFtiYW$q<#oV#&bx zZJ|&B){21|ZBRc0Jw5T`F&m3>!13B~*(zA2`q};rv`J&dOTASg`beE$p=AKWHqd?~ zDJ7)=IRw;7T2wh0nVC-|wvQ;ZMR>RCUt}$H_qIQAev|kR)7S?W2aj{;Hqk=tmzyge*gGZFg}x!>vaUfhKZD$AEP;Cvriev9Xg#Nxa3_jmtvIGsDUOY z;`U@Fp9e?ZmG_lN9eRHM?Xo(8`?;8@Lp8aQ2K@4i$LCfujL;F}90SOae@c7zAQKlW zbOTgixla5g!47#ZWB(m^M365Z^C3cEFBcgGP3hoghc*N0s1Q9_qkWgq!{@?a(Czrz!g zo<4l%KY9q*(E#98^{2&N9b%|1Ky+HV6*}zjcjS&L1mKS*Bn1;1k0A{YR5ne4< zbFqu12HW73ClR@HG-T|xcgJe~d+qg@grguM15y3ukJH&PPkhnd!r%ccysGZnIAb$Lc$mLy zfO|X7@NrVL>?Y>_m?}869&pe0R5Mr4pw%M-ICUBwO+lsC-|<+1gk^3l_K-Emz_U3j z=pxb18uD*GJ~-6sfYe}u@R__aPI_7-3V#QuiJQVUCEI|pV>XWuXNH#jh{Gj2vczZb zaGkWrS|m3aI!GhsY40L4s>}dOx^4E%v_6rUFDTjU$VZr9gItD{#Utzg3pC`&rJM3a zQxE+mjt8A{Z#m>%*lWARBUw_+%<~f1pCMG3kA*kor-Ntx<-4>{Dt~2UyyYB zbyGfOOTLH%1?>6(RCN3>s$|C6+1zSi{1a@!*6%7H%ne+~CKN=6wbGPMlC-ED6se=Z zrf&3BT}1z}d63Ifb`HVq#gl*xL(vH#A;j;W%<_+csU2|3SmuLQGwG6@oltn=`G)<- z<+zw(`a|T$UppW3Z^6?%N3yC1wNJ7 zdtVq`LLVenjKin?ANgjr1@ytnfeLaL@+lB7p~=Ss(b`Tu@A0T#Gp`q1l`l%dJ;A29 z8ZnA>ZOMw||2H10-)zzrM+9;K3h8Wt62h-&;RtBHU4~8*ZnFlOJ2wm>>*J>K2y2;H z^%9<9y)Dy@o&=38aEt{%N7|howpNCqXB+9P<{hxl=w7bzp{aqMTX851Al*G63-N*g z{Q}6LbnlY*;|6Lb^@5-a0J(=zN4jpV&Wnn z!z%;o&CnB9r{B!X!t(XUkJ?=!K|vandxcBI&?X~+wvj0x?I6v2k{6>4nArE(?@nxe zQk)r8dMz?rVIT4Hduyx0louoYK?;4q{RE=sze%{sLB}Kz>VN6>AD`_v*Mk% z-)>Z-qIe#(%t}o2LSvD{K=NaY0F#~#2=Z%|i5F8JK4=0lc2F+J{DQtQT1PO=t{XUxoq>G?s-y%LHhH(w$RN{ItYK8xRc4*|!n* z`2>o?w)f;o{pVvlzHNUkYzEBo*Xe2l@0dyVspyrltlno}kl~e3=070u2r;F3+GUuT zzwpWwG$6>^p^~XQX``>t0!j;aF_d3gp?-$KC!(%|VkXk@0^KrjuwVoFmHFpDZ&ZkC z?2C3jd9Ah-!$(k_i2seJY`nu?b#y6V?P0@^krQvMm7Eho=COq&jmW0;mTy%Tp*i5Z zkPQd))>$!FyZ|tb!c!7^7d?)UI+K zF?0p(xVPiPqY%J>z97Kx_}uC`j)X$PG^KiiBZem#0Ku0>+aU76=`Vb#-Ex@+39V!s zgfO1sJ1>?w89LHWr5uJ{E+PO=%{2LIq)*z^(Ep2hwW=3}VY2^=rQgzV$+Bk0{tKc2 z;6A`D|73;)9OAd0EWqWDU}@8a|AgUKX28o!>mC9BL;g%giT_iABZ38Z0P0;p{vzhded+Gx6(yJrzQbwMi&5gzx_Xuckp1FG{dFUA;-y1SuTpyVR%iDH! z7+>jZCO+i#l5(&l;y7gANeHji0x3(Mv^!J~S~sT7MM6tZ zUl19z8?G%a$d9O@$1R0t$FPb6_Ik(Vh=HHbJCA~11Ed92so?bu1cH5q*Oc6NezqrA zv15?r=1_XjGh985hL%QckULRG;~1RK@dXWd8Jbg?XdO?dUEfBazUNxlKgZKO#QzcEjF$FI-e>O@{!UI3L3F**>9La zO~;7?&IPE!IT?JT7l{fy!}13I;lEtjc6b;f8Xlxfj*FZ~B83BG(ENbZ44Osv?U5}w z%@UEI=wNm-=n^I3+j;`91%TJkC4l<*>Ng`>$&Pu_)9cWLd;vPc@6dGWE2xZUQ7Ndg z^`LTEhQ7888P*3M1WV*jP{Bu_{b2$+#_ZSotl?k{nR8|)7nBNVkQsGRWBl)$jw;&n zcQ$|Q)5qbOIa*cW=ce;1JxDPt+nu46r8E@`0!x}ipVI-e=T<+26!?{dB)1(smWNRuynWe z@)WlM^r;~|>qx&pH1+(09_pc?A!xI7DjPHBwxoH^Ztda`zGi+4z{LkE!AXuJba=Eu z0jShzZ<%2ankPB+|6D^oO;)bDmq3As#Ng2ZP=ap0byE&(Cnq#%kkwe zH`?fd*S*+@vl>+Ru;uZ}(4Nc4*qZPMU^ZM5g2NsB+(-qrxz4L6fnr5|J>!oa`B}VoVcaPe)GZeYog3XbBT^18{iTP8 zfd)clb!bJMZvJt{+`m*33BQR9X4Fao!Ku z?mC=6Glpf&wP6r{UuT_lM|qrD#;AHQphL>CwR{AyF3rUS>!=8ja?i};mbP{sul|8F zBIyRv_Vt}CnRd6O{|1N!h)$}oF;X~ZC)#b4pGhq>9(m9p{1j!v(Yf=h218{<-6BHk zTsg9-HF}QsPQ`zBOgBwlX+qvYYU$@~1_22?oS&N>hnY6lWjxGyX;IT;C9@2Tl7OlV z%@B6fcdGnHpHaR4UF&lo{Ry9q40jVqGQ<5x zL+RP4e^EHcV>GG!>Z?!$N+hR05B{M&-fmP`H&7$q97>AfF*us<6H|R++@8?&tm8~S zI8XbZmdj8F9la7eN5 zr*KF8>t}llN(|I+W<-N~YKgGQyB#GO=qXv&0ON?NPJ6<=Dwu=`7Mvn#|rKCfI!Sp zG+g>gT|8zDyHJv|@J25IV^@Nfi;T`5w;5>BZgdhB)Oi|MYrPQz^Bd}Kh+iWE;bWNX zVaj0|ql+$!het}A;@}6TSakn5ln8Yn!Plms3uv0MBq!xOJIu$MLg6uH)CQ5C3)B0H zHS@G61*qenVBe7JcK8$OtLyG726|_W(x->U7fA-2ILy_-cgObGlJublrz-|;ILR83 zVEwhpZnZ+wC>)9x{jj0|pX~xKTl?~9Yfy<_;=<}nv14+k`e?KTxr%f2 z&5Ik|Nm}RlB!$#+zMjFZgKQYQMb?)aUHtmG!|+|4&RDC1%zyRk;GakkN!uMNPrZ0N zDS(l7KXP^vqr-it|(w(L<>TD0OZ-ovr}e`M0?#rFIN4QdF!p$P}ZLAvKO8y5RW z%imggW8E1U(m&esVjeM3cip}E;`x1AIIx%&+&EG;8MD8`l+$ZY0Ot|opnCv0rU0$r zOUSX0H$d}BnxR*!>GK^oBmprgT*N=99q^bn2!D>ggnpX%4rg)PvZ&ELs|j0~9JTBc zwq1lS9^{lb99ZbB0k%SZ_0bC$m(`XxRBWN*3=PonYpY+sGD7~>+nkY+fdeTtAMHoZ zR}K}|4DLmB57T%;Ivw*l_6KQFwtzauN#&a8oN!a>2d3QNq)xl+r^@MVkW~9T+C>s- zq(D^j-b!FV!WSO{oduC-COBLX^ie`WA_K}b0uI&CcPs(TPB4xiYpam4xx#s_%=$&> z3xrl~n=K#X%gFKkRa&nnq(u&qHUDq9=yj^sX(A${gt))8(Cr9$J6rA` zuD!jzzVJZj`S;&ByiQF-;yn?bvX9EhAh2DYWRSd(dCR!m2G=2Cm7$2swQUxrEA>Cq zRp6mXW)s?KvyhiR3$1>C{``4RBPS<^^uLe2iLo6&k5HTpt-3RCs^swqoO$}+{5iR4 z_LR44Ijg;A#voTW1H% zh1xZAwB^cbxToJG0aBQ>=pZA!de&*PK^-{$njg6~+LRvCirxg8ZUwnRZNk!o=7Nhy;=+*z-g2pnC3aa4{xY&aSr`_<0UJjMN zn{y?DUTUS}vCTPXKaYcw|MisIudNe8aP(LR{&@)LF3aYVtWhsRQV+CWzqsN5vz(N= zvIBKEpMeV|jOZf~2SfY}82DLxYWWO9t>5rTEGV@n(I!u-;@KdYHpTilzT z+(8)%M0PnJM!7Bkh6qk2&{U@*{}aNZ0IqnoFQHfAdydcd_&y&34CWpnD!&^y`tg_B zl|zpRD_(sT|1T^`KT{~e`twn|425`!Z+H+d8@>=9#hz&&DgJ+a;Nr73@2}K7l!(lxZ7QFX zb-^|#`gH?eH7})h*6nHL5p^DdiWEdXfeLBUS)S{=JrQlIJVyYX z49oD1Qw5o>WmMaE#WSMcj946^kjCD^jsAQXA(1t}J_83o2p>Zyk-^Mj#&i4I0W)EP zFjQMqJtM25oxKwS^_*y&r-yEkE@w%e9#*(@W?G7g5pf(&E) z*xvZ7-(inByiTuubFe|Z#}S=Rb^3DZ0A7)WHBYrjaB?~6{K4TH&PL5w)j&Q~-EQP` z2bmuQtQ7LQKn5(d5)hn+W-uBO4GdnM|whC$|Lf> zk5R6c)#wbl_thw6Ur#O*!K(hTc@RibT&Z7Ip89MdPs;moim+6@r2mfDhx!0)qqDQC z+;Y3KK_pAKg(L4*SBI{c=$ZlpVxE7x*q^x+kvUw#!;m^L?D54jp_*@W-Lo@(;^tV4 z9ic@mj4%j~NkZi81n)ly^_zUrj<)l zZKD>tQYAV+1^)hV*hRwwYZ~^(M{We4$r*>PJkQ+pL@BGxoO!$uwhoX<55GSnPclpR z=S#VExwfM^?p~Pv+O*%*JgixG@B*=Is$Vm!=RciN&3>+*tulsx!urHu-8;d$>nwUJ z1_#BvV=z+I1i=mWdrx>SC+qn??B^43LHoJHj-6ecAA1uq8jiI>C>H;T?6UvdQ8hkd z6vJD0Wp{>$KD3p_xkHiu!laF3fXYGrC;-;Cpt$YVHk~?8ou#ld!Il_j!t={jSJ?Kl zUq}R~$YCdsy{bvGOq9@EZm6YM+FS}*1j_X)eV2DVvPwm%X6t^~>|&7%hSxMlAk2P? zf%i8&55Q1G@GCjW*C8wF3?{KI1$&?kQ8$%cAGEE8vz6{R-X$r=weJk`uSgV~so}`X z!DDFkB?l9OgUk?TZ`_s)?f#_R5yMwK1}&EZPQdIAo~t7o7gmFzO1v_ZL8T%zhm20 zp=~V3XS%+ogidOE0d>ZAf^&DQy)aEyZXJ8^7;Fo3e&mVbi=P4rB^>pZ8c62Ombn%* zYnzu)L8?&VnBf-Dzxj^bwo1C60t+(lVeMr%Htsdo!DymW6t6-Lg;TRoLl+tfLX?4(w0+VsAC^Duucgr^0z6WNwJpWaroKBwXKYtl`E2 zMOHo&gZgLoWz(idH`<7R^q;{*{B``L-gdW>YZ)2fa92fh{IB%L3HNbf$KM73)e6bB z!zne{_PN$OvzuE@zgJ8c#C3|@A_jKf)f9K5p|hY(8p{Ua$?-73aXrTuPPrys_Lb>K zympbrW4~aQ)|k5Qyfd$pQ0YpDqQwQ_=878!*GIX^JscrN311EK6_!^`y$W=nM6K6- z{}=ULkfxsdYFR8UU*CK=LMFot;vsS>7G}V>Zdue^q?509f8>qC@@$_bRev54G|9~E znO?GX+PJ>`am+4X4{HqVvZneU@>NkHE}z1VOYqv|bGLh*TGrjWaVb~#u5}W{#!Jmx zFp&tWR7ADEz32s`Ts$Xf<({}cIbKLf_WlK$*QFXxvNG5sQ*r;5JaBvi^24w__7 z9r6rO%y{+uG+W5JPbdN&lGEQ{yKOfui#+kG+?T79F0zIRzCV9&crokQ=9Qan&j+42 zzjaC;bjy-DDIofX!jYK%tm&kURB z?xzWjJLJFnEyFhQUHeU4y|qn#7}f|*gAvFV-)Y&!T~4Ef6-O65cA6{rNog?dGto@B zdX?>0%t|j~^qw*0rTyYSiIVQ>A#ZybUaT)GLrNK(bY2?n`WX`y(L7u3DH>H%qC*&~ z_~_(j6}o?G@q%WIT2mjxUOi+)M|a^McWqz(xn1#L_fvj*TXH-vLqt$R(^P4WbxcD6 zFR`Y4jwH0tu=8BC_`RH%yXF(Ksj+_ZoIe8Ne&U+YtPxALiFYsO)X!xDi+r_5PBJD zw`eJc^qs`wwRp%q?9e>Zxih$-CfP&$+d;VREB?8GtDhv;CL16&q`h3fS==4?%bza( zGJW$zmG&E3vo19|ad!@@7p#;d9+xh%)V4_@p6;h33EQ|#a1%2T(oyazcixGC zCSa?YBi@A2_Wl*tzOZV=2>)kk(^Lhr7M)qw+;u5tb#A+J#1VUpe8owte0RbozYDvk zkFN1$;X7c$%JjA;O#AoUD2msZYMYy`92?2idO`aPkGQxexEy&_(L7%Si7wz7g)e(& zSB4@o;6$rrtC%^P&!U9SuoUze$~;_c0>P`29Agd_vPrs_mu(B z&nt7DH8agSSXK7&j2Jqdrh(IIZ%m0GoaoM?(70NQTP}wadi30Ky{Ch>t=)OvqN0!5 z1+AH)fyi#Zs*G>{XLeD^0jgbkf?rhGWpZi_EWHUwQx^O398?sG2g0h~h+auIml1eq z9hYXQOHJ2v+*FFHhC;E~BSc*L;SG zBHl0WGE|$l{cC!=)gvX~*E~Qmqg6@%FmK%{qSNvkz#PKK{I154VgAO>b9F99@vEBj zIz$`$C{DNXgq~oZt0*FWvoscWsj%RxpHW?xefl0pOp@p?XJQQ%-mm0xC#u^ML&cta z2>6r4_)+JaDVXQCXYaJeDLLaLo;OWWfB61RQRFPVL(drYEg(7oR#~rSsMGjWPet2} zB|DsA9v#BjT7`SVo2!qn?yCmWc0~B5!~Q$%XmR?oUt_=eo4K`DB`3G?zW!?sy$dWv z;$dSrldqm$1ew2GZN8mhjq~$8suG%>ASnmUpU=*H#_p>N?CTj)9M$Tw{wh!t(wtT- zy~2qgu6NO0;w#WRPNMQB!qAHU9?<(ODd_;!CN(+f6l^w_UUl>&WBUWOl+*qp&U*xD~@>(tupcS5R2T95F<9YH?j}iXFS>5V#%e&^U>7vN?CR z)I6rfCn>m}^CZ4oEc$kSKrlRZWOGJ17?N> z{=$`lPfW#qbzTi?U{UB_^g*`^NcY7zJdyQ_y_%5F(S1DIrAf1~rn@b^3^B?bwcjfS z4B`eSWEqk2zq?XcXwUF1Mx}ax+mPTy+cNc!Rm4AJ zY49+AB_oD-XdoIY5`WNLoUd7$vU1~3)Z_y$HohNOxw)^@M7PZQb5$}J69NC;A!F+> zgaL73c3dwa+3eCq#3KK=wCiig4p4~{&C-hGTOA*<%dXNc<&E$)UnEG(of8$!urm>O zuVIrPkG%AT|6h2(9lsV^!Wng)ryYXUDVXP%t$>42^?{L%+KS_g)fx=q8wT+F9$B$>UM!r1y%M?8rQc1{jS?80gQhE4p&9jVsJ`@GPiZ`*D zuO!jrpZ}}1w~nf^?b^Lj1VvJ%Q$R%N?ovUJmQG1QLb_X#5EMk|5Rh&Vq(N{YNGsh) zv*=zl-(2_eyn8?2JKjI`9%D1SheK~!taV=JbzU=$`8%>ll{Q%&YvsD{GYFRl%y(T@ z`+6OD3uuD4z|v-J59r_zlx*Ytx@6xbUrUd>2Q3f?t-^> zt5Buu_O^$FsJat6&Oec4zC=W_*4acbgSSl7({#v%?RJfs;ny&uQJ@JqRE32;>Pk6T zq*FwEWfALPyUkxmq|N{HT8O(HB9IIvy#5p&u~{XEQ6{5do-p`W#RZTvjAxz;@P-zt zrhImlHUMPDvP1|V80gkr);Ot6&i-5ZdqHfZidZ5UN05V0@E1v5@St_Ntjjg=FOLqp zw<0hgh5Aa*ox!L0yp&xyd~d=uc0^O2+^ zlQNlX`E}usx=m5Z#c5pweR!sWD_F!AH`5srK=!G0@eP!-)CU61pvHc#({6db)}#XpVp=` z+TYaw7z3?lY9slKy_rw%y;jt_%W1!7%w^>X{uM9?=tr14 z{`HV}!rV0uk;J7^y)@Z6<74-0W>P0y*e=(yyzBn5JpY3mmU73EBsMtxI!brZS1Ch= zIUH|?iDM#lglm^n+l|gHI4k$IQQ^>zm1lbbmRPw5q0vj_nNRy6M;6XJRmtNCNwQ2t ze{BkOQA;l5!Og9YbnCw#5QV#E-hha1WaDY_xOfCwVx71UX0&Ud-WgXqQN_{QD))2VGT_k#1R5+-XQ2+j=yks+W3tQz+Voo}28W6Z@S7y|KX^k|vCSL0#omBI)E`m4IeDcb&fC^ZeYlqPKCs3@^oK7# z$Hua$L-ea}uVN)hgiRnw*SxP4F|U1*-l!F5myYerfaeuLC2h3@DOlzM;8cPJ+}+n(Ta9ax};OX zb_=uT+y;(r-Vsn%Kuo!4Z3rvtDc>09Ww-6+n;y?ox^3nq&7JLi2XSkRZ|q(?vuEe` z_Y7&E{*pN>Gl}VbT!0&il>@j=fQ!O>c1%PLu%K?;>Ng(V-rWV-WJ!l3K(R_zY-#OP z;+##6{r}FbmfD?i4*eDqy13N)O;#-X{;{b~CgFAzy&}a3Ef=l|wbN|m>?${ zGF;Ei9BHjh(G7{I`#c|PLfmJ=nrT=_`l|QVJb)n8_J>+)O`>(j(8}Uz#I2)xl={uh zv*HnSbW81|`;ykH;ngeDCp_I+^w%4Ej_q+!T2;pPE zm>Wp@V0b4YCvmWLzmc5dnAyjd@N|p#jWptSlK3Qx6;`1ZuHhJVf7Z*=oFp|yNFJ&p zS6gEOVSIDe(5GU9Xxdh|V|G2Si#DZ+X34d{QKevD?V*HDQp;7FPjcM?!v=cn4t^ys zim685I@iez3Rzo}=`7zOlTWQywWAu2Nq%^>07YYYRBTo_67$$ei=GvgSq`zX|0NOW zD_oVb`j6eiO;y_*Oc9qUSM|~7QND*u{uIm-qp2LwSTF$@5}F7%zpzkKux9w50z6!K z+vvqKnmMvs>QcM^!Ai)AGlG88;iPUp_8qJ;dr)q2bn5r;1$Xxh(p~C?qD0uG(bNo+ANrh8X;UP^1T`U;DbpYNYT7v`K z4{{hP#UJNOxli%~nSLhlZU2Fj;BxG}dO#_rs^ltJAM9 z>L@NV(wkJ|=rhe~dbI`bOerCtcKaS(C^~D~Iow^+_jK=mfX)EJmD<;oI$cvG`RHHU z$hyq_@Z&xlrMfE(!F266+;sgqB0GsH+@qgNrxnxG@Acfd0-=+L4mu_)H6R_-JEmR! z!|~?Twh3NXq_L`xkocFtvhkH?4;TxYn$aINd!dwh5KrE_-wB>ks_RFUeQF1=G86R0 z-gQK_@2dsY6`5#z&CYwD5XV%*24`oim7d+q*kWerOY{T*c#gTHC5-rM<#bT|b1wZ0 z7&2?Pt6`{oc<429#D5sn{C@hOi;+r|JZ04I!B2~(85i!0r90=}%movU7M?3%`o1)9 z)ABB+`SW(FOzC1%$I#kN;6V@%qMcjQTGd-Y(Nka8%>ua&7INux*X+=d?_>{Q0*pN-6UCK%uX=kP)*j>!Wq?YT&Y#O$B zKBnu4t^;^UhhQu&wv2x)M@LEM6dtL1H;KTq4Cz36q4zauSyi%Ub1-7pTZXq*KY9py z_Z6zwm7T0F-Qe22b=WH{)OdB#2&=sD%JglODn)6^00`;4U0|6Xp^Fg4*kOzbM^I%U zS{~oJP>L?{TygB|rkvTrXEXF2 z+C28ir}Tix&y5wTD)XmPf0CyQXx0&$gR0V*S*i{n$AZ3vtV-}B`lF2g`j^kFpqjHi zzcH{s4JdhUxBf8kG%-;0n~4LnvtBx4=5K=vnX%P$2&2;cdfCZa`UOE%jJMT8ny z7a1mH^pUv<%WW>p62g03r*f6N(~V~CK^Fr9)VLNtzH)S(+Ek#NO22h|Oi4wGsi@J6x{pQ%KUNyrbZdFL z8x~)*M`*;Zapmmqzs2W&q_OFSw??#4JYq?Xy-HxQHAZ+cxpW!M;-xCHS~%CcC^S*K z<>Tc28SG|W6$>+Yz9UJoogZnee7^I>?7yX06H4rk$QTtno8-WD5BuBqz)=xNr=a05 z_AKNLyW~EM355pZrvbyZ8HWY^tr^9U zL!)bUS8vf4Uo25z&u1aZQlQLLhDljm#L)Kzz*`BwnG6+eET&C$Rf=`pFE**IB!L}?~#k>Bc zfi}-hm~Opz45t8%$$sM;Bt*u(rr42w-%|ceeyMg*rM`92$~V@i_t{0PDikUqYx3L$ zJZ_=a{wAi=yuFsMCzi>bX-=}!`?K!Q{LI84xMqe=>RDO;q_*FAfGax$%A} z1)7Qe9pT`;m$lBfiQB|$YJWwh{ zSMHD{vWI)aj2MSwMF!l}n1b&&6o)IDm4r0K4Buud_a!QObVxNmRtpzM>lmGGJ(_oKdI;$25CyTO}#y_}N>^v1Pv zu@sRJ=n)x(sHUWFq|IN8ChfP0a$9|_KbwE@z^4%hf4Db3c!)&?B9EYUJJ;m6d+zY~ zQV;=|sKU5E4`?K>(NU$Qjz~S!;7S>bXVj!&#C#ih&DPD|E{Bo#dpv6B&d$L~AayTm ztLdv7DU9gabNiWTA{(CIo0~b|->xbX&2Bz|(5hrgLAn0Zf#Xi8g?_mI&;HW2k^rn? zk6XuvcG#K8(JPp0CKmW~=C4APKcwLGnC_~Yy9+HTlXGGE?CBR}_t~C&sgT=WkA$EU z_B7jgLMsHeQ1xivXB71u9H>5Pb2@TT=P|NVwD7m$m*m3LfL)GY!W`$VccvbiVhzJozmtl*?QibuGYSD~FUX+1Ns z@l=t9yba6uOT&SUYb_qSmcFZis=nxfDIKn_3U`)V!c8@X<)B8$pOlw)d{JwXqAUQ~ z%uk}p6jOT1D= z!|o{#U5RK58C7H{FH^{uzSorK3^&VCG1N0$VAESVM1!Rg6t^}9G)quBEr(5x+J=O6 z!pV;8?p{Q(wko{7eO30>z>gG2N`OUJ`C!7|gp*_W*5vK!D%dD3d(;xT)vx32&V)W{ zN}F1h%8Pwgd6ltv)`Ky2<*2Vr>2^xS>t&K#52vfSj$4BIS`}oi-LmGlR>FLJYVIf8 zj5}g9-5gOxH?zt1Bbl;X_V%CzXRE-Gy0dIq<>Xi5hF;;LhOxoAmFJI~V2!72v9o>K zx|)cg{MP^cgT97mM)e4nKU9~0=GsNQTOnN-?7yLp_#UbBq!~#}oJ{$l6DPGRc-<(P zu6!g-iHw)}+o~bu2d~5oIadmCmX25Zn@uVg!M4tc_>IjD2W;eyRBze@dxjah>p11Z z`^Szm`k!y@zMAvdw&B68q-Dw}Jq@X){nKo~TgVufI{2!zsrBL+H5AiD3kY}q)IOTm zIGo{uFfVf1*eg0X;~97Q-aDN1m%otj7hwy}pv!@9wNP@(ak;ncM5=iEdpA^<=&FZl z#G0WT|93c35yX+cHI@$vi)kq%Cx=Sam#kMJgH0URszNjSh+;e#QZwf~;cBS#z4bvY zYrC2vPLWjTG>B_gLLi#p#wA*u_F$7zXm&n3Gm(Uo+?kGUl^2 zDfs@Bi{FGzu_T+D*7;AV;mQZF=0AlEGss7ozCJnM7>p4-J$XU?xSS%r;Qi}3!XFSJytrr=MXWTizADCK&j`_32t;?2=#wIJ7B9}+np>w}{%cgjG6&4$Ib8RKQ z_10~j)&(APyHwkMWQib+6jyPB3}N5q^4!?RBSj*o(6|#;`N&$GN0tY7q9h3GkgLWB zFAndWnMd5O$A;STP84htu|J#@4oX=E4GKtC?3d6d7$Wx#WzJ1fk>pb+u0T3e7P^!T z1+AJ3f&gKfa-$P2ROkS-E>`M&ADC^md`BOyN+CQ)j+>5t6LCGQnTl%yxKEq?q_IzK zlB{WavHBah)xRvIOTXk+f)8UtIUs!QBFA1cyk3wRh$$IOw<$8kcIS`hJNYkyMEf#m z7DhJAS{m7k{Wwki#6rTpJSGro6YOe!JWA8^!m$y7oEk21%~3xD3kYuzY6H_C&X%T%Vn8~yb^6nzV6VRy8IO?KxLO( z+t+$08p+W6xk1CR#(w=_mtZd2mP84g3?GWm~eUa2N zhROVkRbszlKpoPmP`n*RmX_gqLIJu9H%0A86@5(y5iG163$`O|=PTAHOUBUzd2IxI zm>Qc3&Dji5mJfaZ$=RO64Gd`k-Dz?QY@o?iYoC`|9BX8VLBuQt+-5zJY0no#4~-3P zZWc=X`cwFDw;XN`s)5f`vhLZIiv4y0c#C>pu=LeE)fY zVK^oap7c%nTdw@banZiJ~1$V~>- z=^BbQ@`*ZJ8pc4-l}nw3VvL1c9jKFn?Ev8sCygtwAdRGFz7_PV;2{|GZu#chZqpf$ zXE)lM!k{lR>rw1!kXBw_hY-qwYqWB` zbFlPV?Z=1>BDgI(T^Vo23xCPb)}VuDZ0bSk-~E`F;c*Pe8CoGwq4)!b>G*u!Ic%;w zpMP=UtLswt+`G+G@F9BbA+%Q23?4N{d=Z?$D4yaOu=CzPF6qaJ!%Z zi43o|#$||Uee`BlT_}Kp{uBq+N3N4&R>$s!)o2iPC;P09+YKvWnME7nAoFBm;-rVL z0}gJysvsmxdt?=FZ8Rgn^K1AFH@0H!A(S6`BE9>ejqj0lKi0TdlWM5uy?2pzN&E+| z_e5~KCI2cQ&zGlLBHq2o-m|XA%XQ8A>vA0gLUL1%Iw^rSvq~hTSo8sCn1QgGll!xWmNDr+paL~^N$g^uZ zLr`HjGp&D8YRrw3wKb#)dOitwy=toEo9SN8IL}ZiX95?JF*b z<`|d?()K*lDN0$cWbr^*V|Sd}5E2;g$PG!&Sw2+vF?6ZF-?i9UO;;qy)K0lc22~j2 z5ZLiAA`~fto1vQu&Fk2ceX5=(f8k*FnEb2;EzUk?){s0iVVUG#tgV-Iib&VAa0LoT zl1OZ|Y>>NsNk8kW#@Te(7i+W%unahcY)7PD*jmCRcf3;`z?gug`FJmX4)P!lF$`Rd zgxAYv}1Fkz`S zRIePe$>T)x=*7fAy5Z9xoN#1AsHs;l0P)%bKQ}jOcDe+S@7kiEYpUVXuzLT(kZxp$ks@^dsv?q~n_6yk@(-@zD0o2N|jW+ExJ zX)^SEr$^WiOYScgDcVs|PvXf6#)jl|wd{;XaCY|Mzvac$(79SJl4i901eGOt@q5P% z|EVyP99~^H8cl!)3~#WTxxN!AU9ot}(sx>Vd}5Zw<@ZZ~c6WLw81c zl_6^Ap6zW=`oOt_3R{G#Qb5gPYkNJ8?{}Y<(zoMjwC#pEHoRQq^Hd_wQ-_bSEY&nFsm4&-Fv82GYP4`H$Tyf47gSvAic!B&=%%I?^+-%664-A5m0sSY8bQ; ziyc@61p5%Ww#5bc)s-waM)>GzRo-y>zd1BfI$n4iszD60xSeuQk6H@oj00k%!p^Vx zx8obn0^GRrV=2vOth(=k>=%LJ;a&PmWflSQzGW5M7-ffB_Am!8wyyMN%q`j0pY8vs0g(U-@Ys!vQ>)=M|=b#@udso#`rye3h3 zxORItxk-RX)r*c?_o&QYXk&SFN1}6{BRSZq#ArR(Fb+3f2l^Qr!oKeJkrfiT0Z#% z8qcqD%|9MNiO*99y}tFq$jez$!cKyti)UIp{`nLS0iTZgS`$}*;AcU?H$Rg!FEiF@ zR=Wn3M&L`%YN}PHJJeDvGSt1AtTHJ`m#;Ou6<6FE(`QJ{&4D|6$lxMr`q5h<>-y-*Z7g$2U#MGIZ@3zYbOv zZ}0sc-bbqEj=xy(r9F}S)S@PKw|#c_#|~b{`w{iieNouN9Or9sM~kQCD*!>o$1G5% z`-0(KezW8l5|D&w#G@Dmoh$+MG-ex0t9qT+zK5Z_ROWaipKg{4ulVM@`(kIr~SI)Vq-7hm>YU08b4l3>02 z^s$6*e0y=wm-Owl?8F19$B%L>5M~jYzq>5f>iyjUy*c4xO0V=-^9!QzH?JA?mYnK6 ziK6hZm9V(IgP%W5xJHUA?ZRWry|;cyNpOZouG#CTQsk06Wtn3OIjmG&BiF3JvVWE^(?Al5#iJDg zxzX3`o{WLFP$r`ecwWkUC&{o%SK(sFAwVUpfoeVRxlrZ(r9qA5EZn{Ilr&SV^5HSZ zy&l0F;#gwM6agJI9j~=aS54-V1*Khy3SXqFY+{vL!>T0zZ?3M&jngqa1*>tE@3ig$ zdyV8?&#ut_SsY$+O6;dIWLmK4GhkXk4bnJ^827rDIyQQ~=Ui&~7}Cvf=aC(cpvA!* zM8Mko4pH*g(fShAwU+BH7>5VUhoqq^IFom!ssVJQ=^)Lq z;j=U0U=w9;*86OPYD_XDc0n;l&cyMI`cG{BF5fMeJ{`K?wa4%?A(HIEQ%~vPM)c(Q zg}MvVBbj;G)=$T%V_40~9{jks%s)tNh-)+LFr7quYvxoE5sWfkU;PksMN$mE;B!!8 zTtbHGdaqse>R=0!YZy`UNDW!^S9*Ubq%tJ_Txk5@IjRwJuY#`G%RGf5wBNm1h4Ym- z#?8lZ*m*b>Q8$%j!Tj)XHh7b;C;e0t!SCJNo7PXZRKBEmjB`^PG2?21)zlE)O%=bI zJ=?=V7ZXNjS6nAjdfCkftFDos^;&G%)%c9Np!A{rL|LU~EOq5wZRdo8=dj>bf2YOm ziJdafa5_8e+-K@k*)2W~9wRmCiY!bbquD=HX81H{$&l(>Ewr4+*k?@>#vz(FPO)5) zc(81qaI6_!@{Vho%32hu3iHQ?XZ|CNCFf?&`L6Gv;*9!)_PQNt5&Xqg{M+;0(S)w4 zGLGVLJKpUlHn#-_4N_f}Eu9(7xQ695lNpxju*L5t^>5Wi*dKQXy>wf4&hu0_C-L+8 zN&SG;#{I=rayQ&$@Y;Kw+=;_X0ELdCh5kF`gxda%_Hu&(1C`p7IpbK;Qqxw8-CSK< zmF{mn74$F@-fngJcO?zB;gwC^jbGh*XxinVuSMNrU9{>B0_e<}0E&vL{W?l-_ra5D zTXZ+%@Es<}>j9O;ii(d9%U!%m!n;ZbtfF=K5L7KGSaIL4lZjau&*`D)c(>R*$+g6A zFiV1Gz6Vx{ckgyy7l_srR-ClPCX@BsPo@#W-^%XFV_HFiAXLwpiwJce$VO+B8( zlBscU(6suXXRBo-R^3<6?peKZQY4WjBjuxj8>mq|n(t}5%YU(E+n6Qj9n_Z9RwTik z;@syvecPG1PcZkiOeO7MGMEErz+O-@A`P#J)JWpsS{7U^tM7a7o8jewB5bASM(bSv zICuZaNqr_D`@zq%zuuMHI##Y%vGDxt0Ha*>v7#jJy`Ou$h>!j{{eCp?Jl=h{i*1o` z+Mv*VJEod4%$X&1(@ClfGe1FmWWM9aKzn+J;0SdLn>RJl(^`N1@tu<nGYc;)EsP@a|p*;SM@& zv5m%(#r=;A&Mw75z4awRYVJF`{m=LB*jZ0kf&h=e=IW2&xNTy4Fy=Jm@Um286Gbq4*Np~3))n>Ob>3_`8-gm1aOUrZgk zXXXhhbTw+m;{@q0RDCp^pdaN@_QKmJH9V;9@GPc0C(zm*IdebE{GKFn4r3SRJI$N} zg<~sZ*2R%*-ab1v5|_SReEDJcE;o1Q`z7Y-I_fOOK0lJmA6w#9NqCYZ4ciaVOJjO| zHHB-eK1IklICm?;Le;wKGU@wn)B9(yT88`CxoZp-UgZf5v!(dwx5)@wVEw3{`{3Ti z#`iJK?(>{ewEgwX2U zzfO{!5IZ&QQ$SlFL^8Oj?>UCd)1W|#9=XPiGUJxZKYFUwT@^<4rRs{7w`cX&leqJb zS=Bqfu0akxZ;BGRo}&;JyU$(RXe)1(B(||Aksah&P&x(;7d|f;W!?M!=~zGJ9Laa` zcyul-quTXY)QY#a=+OP^+O{rl_n!lcf4sC=Z2Cv*pCHQhx{*PC%~Ey8{t+2zE_%z{ zkj`pqex~Ea)P9nFg!pXaa75@wV&6DOQ{vDi`0JFuK#e^AKG8QtCW5Qe>^e=+xXiQa z(Kt2tKd8^R?d;a`?OyGi=o^mkI%eIvoqF4OuT`>(x}ogE9CJWZSbC9GzC-(l zNygJw2X)Jma4mAuR3rYg&X}YDvkHw{vde_YL6*F4X|11CLArnJXZ7dnGgj|D$I{qa zBqgx^Lk8u$Q&8j+_L;J+r9U_tcSLW;g?WIg$$RaV(gd7888{XAScS8^lz;+SjWuO-I zs1@!D`&WAVzbRcY&tHFi2bcm5p@sQ*4Dd|YocR~PFjVkYdpr31tVJ*BysK>~AZ=N2 zib_sa1a}S6@SpwN^rE6k@S1=^l78_bHz$d)DE|1%e<6eap^e3Y2iW{P5jdj_daY+!e_JY`hdkhH*t>~?gM&ul14U@4*l-nj z_X+Di%y94~oSmJ8nG>}2RLnC$yg;-S5IB4T6%1{z;C-;Rt!S1d;|-uRauJt%;Ajcl z@d&H_Y!J*A%P$dwj}Dk`fW7$>2L~=Ni)QBMAAH0f8@mQm(G~!**-(-JzvlL;X}?uJ zL*J)jNYK=Zg7GEbq1${FeZL|BU-%1zjV++W@`MkL#_t1g$s8;}GPANgYpwcz0IQ4} z{33u-on>w05B}C3@Ls_sOZyPe|2WsLo5H_^_aWe@kd>tm+DSB{9&M`)Q}?Yi4qN~$ z03Y3nrBfJLUjmcLS@2k-W7R6WEi9Y>#F~k~qS)Acz~!F;0L}93cpp$OoXKFVindV# z_iTKq?)9RbHA)(fSpfH!>tf*Bhl#fx3ZBIj@S{RbYWk6Uu!!$q^#4a-(Z?ZdE{T&h zUX*iO=X0=UC0CI=t2oiIu*jZSTCzl271F*)ueb})cx+?v82Q14SH1}jedK7{m5C*A z96(^a19J(F{DeNV{GJ@J2*I%B6qS`D{(v!*890fzj+B|b2hWdjF1)jo<@;a?6!32* z0+?_8Cli6zHle}|tov>=F=eSu&4zrpyq&4I$vL3974hpm*V3LKCnut z0wh&PHK4Q5(696JbMRt}?$Zz_ z1kWl!0&3>@d`wJ~S5$l#qQ~^Q?jp}#UOkc5lEBFSj2|c$8L$~P<^UH6&L*D{5_FM1 z`?6MSfF?kDe}YTaE|_p}!G;8HZ{d9zD<@b(W_EV8D=1anWW=PMC79BPfqr*n-3>6} zgUsT9VaEKQ0fAnn&-=z)HzpF|KwU2OAe!ldesvX24L{A>gNZRSORtva!CR&mq*GN(O1v^Y}E)k)gYQ8>W;RZxWmDL zzWF_i|MW4SuSQp@WGZLl;p-0{h*0&XrKMbOZd}8~oy$(LLyPRuR;_RbqRmUe5~e-$ z2BX-7mlY%hNp17(pOEk~z!e?+8ep4@W^?9o%74Pe!Er1>vE3pjmNqxfJgGi5?*{7W5roU% zrbjsew>@4{wc{KMjX(G>RnG)dVH^U?Flf;FIhe?U7M&Y>Ue4h>5QH;@Urs?`4)766 z;Pvz-D2Us*2?K1;MA3*1DQMS3!uu;HM~|BPi=53c^>5#-|C6WZ{6&?sWcpT-BXyhP z650EN2S=Z{N9FDiGj+6J<3762koROn?%X_MKsuCPw46vl`aJ`#e^}N{Dt}TPR-Dna zk#}{fEAwu>o9=b*5>EUE^PE2~ogPVas`TzsV_>imC1b!>)8%Fy^zZ-q#{fxV^5CK2 zVT2(z#^0nH@b7K_B=k|RiH}JAGy7@3fWz<%nX3}nde?Q@Pb8~ZWWaM55B0V{o`lYR{&wAP=3=>(0%NWuz zQBgPe`T3Fa^U@NjDn&&_B9fAEcf=(n3$n8x1AIe7L`02?d|+dv_&zz-iNecN zR9EMM&Aocv^ky9VG9h2t*wDI7bhymQ%Bt?@SY}~i!6zzOke*HtAEX`WBL7i9P*Bsz zsAP53rpAB+%rwZA&dxv;p%LQnqy?Api1$4`b5 zFJVa1@hW2kgzg+4=O-mmsq4c*2^IoOPnwNYnV6XJb8~<9^?f8DB;*$qWPY-9hA zqv`Ek*V@|Z;_jYve(ncbp?$&W$w&B`fyv1tU;+*f4Xtc%KRr1)S=rpYn0j>?!;kni zdO>XM?K{`qlE%PI*45FG9(fk&4vW5mL`IFT5AE!H1;YfUC*X4;Dk@4zPOfTYl}Akw zl9-st$IrjNU3_rh)=*#n!plo9FfdSFNlDY$c^8FGgt5iAtu2lrH2_X4Ha0faFJ4@8 zzmE}c4*{zIU!~}UgD>1QM_537tyD~m#_RBr;mi2d-z(_fNw59i{PFxUYe8n_pR%i} Q=nE(I) literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/bar graph.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/bar graph.png new file mode 100644 index 0000000000000000000000000000000000000000..8bc39c89082551e5d0966fcc71c090d0b866796d GIT binary patch literal 39556 zcmd3OXH=72)Flc+P^ySPq>6%qQbTV7N)Z8tAfWUjAV}}M2?(JoO-cl$BTb}9F9B(x zC_(8pGzmR)=Ehmy%%Ax&GvBN=-@DekFeK!;&%O6KXYYOXx$mB8C{tdBUM3*C8Ylof&u`c!K zZ_^kFziB+y$FJ*R1)r4EB%|&l{njV9HB=|oH6D0hGC(!f>;q_$`#`oaI=ZlOe z!Y2!f{?Fciy7nEXUWM=SX@bLqZ2{bCh^3RgOvd+#&!@_o0vSGSNr?_%rUdE9-xKcvjo`Qfhi^=`cV zpDG(cr@0Q-61Dr^;P;wOwkx`CM!`?uTI%ME?>`HPx~=~7Jl(_02b>=pOYigvSDc?6 zE3b`yG0$)tElkOI_345pWNo@RKzh5Ib0wYTsZBSovX^hD$?tf~;=MZ0(&)+RT3K^U ztlXKneeG=6^5l1q^{Nq#p)AF4YjEvO=0)6>nyJVgw459ZZ`WSh^a#|rM`f0V{iy@ks;gmP7<0o7+cmIxyf%g;joI2@8xYu?3F3b2HY`#lIe}R8l;vG50 zHM7-By1(=VLtTN6+kNfNcK`c_-Zlw7;)zcAeCetwf^_&1gW)ybrCoHunXpJ4m-u~90w`;wP;0{*&8G>17W4-kJw-0RATF0SUeD;lw2}pVKNQ(TFw-6Umt_h&oTa19!0w^Yds>m&0KNji+g<6A0=DP zf3IC~r;=HFN>qELlKINc)BD{!o45w5{ftBM4!Ll@?k=NWvW_JsQRef!JC%M*oEG@i zU%X$!@!r35bk%V;dIilU*Fy#Czd57X@plBry1duEBpX?MpJ0RepBz+a?7!dn;lJq8 z=Uz+dIsIE~;F6))p}s#-pKPrMqqO3+pr>agd)|j^-u{zp>@P8YYW}-u0iV6wP@!I` z%;nF${S9TEmb+#;xqjogPqbJP-)HRo*OFOmM<5_m4}3>gU&Zrpc9!eh*r4NbBkz@5 zCj0}f-xkP}ZCR&*?Za*iaqp5J)=KBJ^d^#bfE-7U4RQO>#GUArPSGS!^BqJG^JtOL z2>Z$U+}Di9s%{9|SWF$}i|Tu>3b0MkwYrHj)g4#WKD#J(B2K>;H~SyGe2-)5?Ls## z+Oi`x{rPLD#51LJPUk+5B9+ zGnCk(+nP@n`3nWVt(AVyLuoJCJ0Pa;$J6Jslu&uRI2VsFtccZbcL+9gM{e(@_J}U@ zj06JJy{8zlI#yv0vmL!BlE)fwvQ@#f*AKJXBXV-kXU-7qkTq#4+?G+3qv~NC9>$KHDr};TZz}j`#j8ABio&vn@B04AL@f>Gi@k_A-7C~9^X2y zXeGVzIk3~GeV^PE(V)zjSE16L4=9+qj~^>0t;O`5XT!J6K^cIQd^EsxZuI_nYYGp660v3m*j`c7`j(SDqh22 zs)ypEcg;^q&N=Y9&)a_CWmXV17i_QRX>4d`xpcZTfyN12*KamNiCZ zf6P_g(dgi1yVuP-TT)$h3;4K=*amK9hP9>oxuf}dJFrBF#KVq%1p>QAH03g6ADHRK zyfc4k`{moPPxo}$Fg0|HG=#zF@0QWFSlp>a!0#o|al7}WUi%e!GD3<+B6>{ks~%(r z$%i1qZc{QsLlFteit(hEqhAIq*wdg(gizf5Fad}9mAs!bIkS&)@?dd+N^?58hKWg7 zI_ISvXh-!J8B~S8>A>tYBdxdf80~fIxGhy!Sr93cJVJ>cpCUjV6gAIbSFQogwnO^m z3qER3Bc15wZ%+5uxD@WSlaF1e>v|xNW7@qPnmXZmOWcv4g_Ha$>)7>Z$I;HS$}(m) ztV5#CbJa4e5)(EBB{!RZlA@!OtXAENH>ny@y3u*GR)$|swAEB`-oUml)rGFu5;o$rpo5a%kWhI}Z^DzNZ;5bo@h^y=xn9Qw`B9gp7Lw-D zE`gPqJ&9$O5E41C855$8wu|Aw$x#|!G)H+CR+lql*wU97a z(1!;D^|i8NR2+c;bYpd-zdhPiSzBXUTBHqfLK!d8V>ogAa@eC;M)4`;fy20A}?A3vG95befJB(=?OD0Hkz7j4BaqrBGuvZ)LX{ImxQ*|y!yx9W4&U; z9$k_b+Ov$jj#+#0fllNaLRp0-PrOE2DR`}Z*Q4-SnUkz|asyjkLgyY_#}YAZIpBBp zAaveBV&HZ&vB4U%80JDV(zdkjl_Z;8xJw`IW>(}oeER%s;|z1WRo^|t zP70aHXoqt>h>Ru$a{?PY28aKc7=`pW*cC@+``hrB7SS2L?K!x-wlxK#5?8pc?8n~ zpxp+-2E^;$;-Pc`Dt2`K@0^NW+ zN!x4{`GF(B#`w*8&(yzqnQmO&x#bj7rvXt2Whre&Z2rJe=m-vo$>ndiAC~ewwY=9Q zT3G7BTE|rwJkZZ6@QNPg$$!8e`~ZF2?Z1_1o8r>$)-CebWbUXpE4f7@&VMF|Y}lt$ z2%b&Eo(SZl7^3U>BdPlJEY@(AIc=atp070 zT(Bu_M?Zvy!V+wL4%g-c#oxHyti+hpszIFg>49R555`($SlsLwcCQdNNMue!RIfR7 zCtL7QPHfAgkZ4l9CfpYoVn`sb;@i%ERDP)@Gug2`<_Xl?4p~Isr9PjCv9{29mL-T5 z9D2L4*-ow5rOGK9P7a-dheLcqFYI3d*B?|-+?WZW)}S<~R?A8JTVecFA+Bfg2vX=u zpWDl68u`ZQ9<1*-6{SwmMYzY9Rq&13M0|uxTZ8N39P`kp1;1{cclxOr0!oatDb5Tc z1N=Bs`x0%DAHSXr5CXp z5~=Fez4l{yq8WUc((y_@GIL6}lxcw0Si=6INY~3lk362lc1DZ`b|7QKe@iO8xTGZZ zY5U&OqwjtGjxh!7v`+Yckc^3|B zKMg%>4-2D?=4oT$hzgUUyaknnJ+u*^RXAYMVS_5biXif^T^qaMf|7e;3(ks}hc=&` zC*YEv(Mq@JnW3ZbN7js2X{@b>XXa1JnJGPkZyS@te1*{U1xf<^vpGWh@5987dnEE& z2Rgj{sk%D+onpoUpxGs{Zz|>1rLZw!;#uKg?kmJ@Hhsf1R%R@4D(jLZ43-{R5AI#F z^r~}7I@^FS?#lQQqbIl-FY)jO^hw&&zNTa&5BPyzre#X#JZKs*&#{gTBHBE zPzqKUo%Q=L&l6WRzKi>M_c#oO0St^vo$cnAbzSh45N7Jkpdb{l| zh8*L4=Ew11+mr$$(9D05d1^pI+@-Qj$G52+|8O(j)K^xqv}e+RuVd@Mf361xXh?i?^| zIOky8CwY0!R8q!7s(RtAyAshU#>A9gdZOjpNGP44(lEW$@UUByWe9r}5-O-lpQd7_ z65JB@g#0q>lb%&6=|UW84bE--L|c8n)}}*vsMh@0H@7W`8(JFr9Qt>iSUw_5e7uag z+qz@K+DdNe+OeWYi21D#gVue&U@;*$uZ+jk(dtXwA2v_R-kr`dyYOuvUZPxTKsR`- zTP@P`NQaU`n|&cqy{Qg+n!Ow(sNn*I53j;J**r7w@qzLpQ7GXH5j360Kbj@ZNe+9) z`*ByIcX|>jljiY(Zrd)S%8%-Hp)=F#H<}d>+lltW*Annii_Qf(k5OlvKAmm~2dU%K zQqJGv)~a2nCAvs1DKNB#p3ZuAiyH+??a(24adl{_BZ5km~YERAg{)P8-`3Z3*=tVT5Wu zfl1pqCT3?PefR1w2~rC|kaG3vqP7pU9b%GEE>t2U0?+{htxtCw)pzRV2tTo?-yK#P zX@N|nCCI6kF{8xuU76C;!g!)Bf=Machc!3U7I|pbto)%-&F+lzjq}XUORv()n|Q9lm(4U_PKNU|x9wr7hw=x-h9 zl(BHFd&=`N(_)_6Ke*2q8s&fxGfy3Gptzd%L(~iDd9Ke!FBVMQC|e}PHpd{)BY^@xb^+P^34>-M#n}WHd92PyvdSZk*`Kk zoAinO_V*r%d5=%qdvg5c8uj(VEZYd-fe1xv8CbNE_nxz zBA286WGVB<>7pNp^$tuny?TpU>KkPLm=VUb_UV~!T|5=kt6|_F=ZAn~Gkqg-DcG&z zKdf@d-$(J7{_Q8Q5|F7oEjr&QtJTK}8gO4jPEFvXvG+?{J`dKyZ`3*N5Q?CB?1hHNhs?%hf~T)dSFG#j2(@~jKDbB=jU*8_>ERAL+1TdvxZ`yxuc7ZY{! zhL|L*c=;}++y-kNt~uKeOFs)D7g@Fb^ZWTsIroADqu$%i2kdtY zlUz_<4`k&M1s(ixJI=X!WR$)N*MHR(P3=fmXf~X~k>X1J$by(>&$5D1!Y7O=p>c{t zoDq|*BkFh4`!{eZsD^vO#cQc+8T0%y(+zT=j0(5dsGeqUexOkhN1v3A+!sfpf47RJ zB=_7qPW-+<(EC8i>X!mgdVpeT5-0M}407l9g$9E{LZhHP2jV?pjS4KO#<@=UhJ7uW43~c2uCE zG#~IPjnt9F!g^dVPp6C($gug>3|9}BCi{7G#kNHr%%{0&zrE{M#;fTSm^@6=jw8j; zB;F~?NBDM!RFhjzaH_T}Ow~wy;S%KU?OXMp@t&=p^}f@2CfH4ejh=Secx&dWRAj-- zjZbrud$A!ZDRm(Az%ughR;H621Kz!#_v8)7?j~ym4qnXoJHhs*F&PQWKiTSe?%e6; zwcGL^ESYrT`EtTp-1X{{J*j2!KErUm_z57Qp#dC)1Fmd*yPft9Oq4_t_rflluTMFc%~@F)T$cC5K?80d0UWZS+Pn-0ipGB2w@C^(U;6k&h zRGqq_wi9Myj4+m)zjq(9*f8K_>XTlkWze3UES*A$eaqe!&ew+|yJXsI#jryc$5f4c zy~G(Soxr1!jw_0Z!oMd{OyQt7Gq8MjxZ~u^viV(gF%m}}cn|IKglJ*n1CJlSXFv+l zQsTUUx}mG?%3Zph3JPPd=AGj%uZ4+n3LTNrR_S!BrpF)gfG@mehO)vOA?Ch+o;;n^ zwukD$A|4NwXJtLk2}RK$w@27-!k$`YZ#`Cw!us}818Tv0+$~rU3!AX68m3vaf@SXr z%#sMyrw#pm_W-qQ>&l(8rNTIOP{31874tr>!@E$a&lVQ3?GZ%HM?Z<9yaNP>1X~PsYnbjG78yVHy3{e zUU-msLGzz-$F@#)jGCs2LAtaaE__@}wXsXv5#?<-FG)U~lbn(14zSW=!(G7#IN9@( zaSqVqi19Zn`Mo6e!^=qKd^5I;HZPC`tcmBRPxs*1dMldOui)6^eT@Q$I9JGIclC!a zz6-NiQAF-g{)Ighf^x$Gt?vzOX0Ftie(|4LpHWouIbIgu>)-ytKl)6xt35IqdIK8+A>Gc`k zZF0#(>cNBFt}Y_t2@jMvwkk`_JoeoM3P{MI?~sZ`z*xXWepV3LPnF{Ov!e*2feX}= zOAW)PA4r9@*4WuwVo6A8p@m zK71Rt7KM)v6TvZHdC2bWhbu{}-4fWGa-MWHq@Aj5TKTAC&C%_2HpV|?8_bUpqr=<^ zGMi}$vUxyu5kgNF6CEaXjQYfB0Ql)C_T#Ld#S9r~_bju(FdH?;(y_kCD!JFmz^2p> z$%FF19ki_D`ueyFS|+)=x5Bwm*b{<%zg8)1lvj)=QlXm zAze`Z&Q1CRke}AV&MY?V>+;8HfWc7ox3a=Z9csU&KT9&b7&#mR?h5w9PU~{m3FVCB z%%3HkivK2Td?1JGYSWHSYxQr2sVk-GrN*SIGtea*6dykn9e-H6p%+H4`O8`haxv`;FgXt)RWeo=mj~@>`%@$N8P6Jf#BPeO{Z#18u?G}ntDnTFV zh>!-Tlc+*heOEQx6T@6UNlME+os^GK0Gb^dJ*)&!B=qG8V&e&HU2lKmJ5GZm0wqc* z4ef;SU||b=RHMBzygs-_k3X9G$S`isZKq6|bmvT_4}r>bgZ-}Zts;*C7yNmlP0YNw zm*`9xZS#~s1&lbfy`d`?0x|e*SnsNexx*1}n}A0wlDjk*OH)XO^S60WJ(NIfoe6th zkx%Hkg3WYPBjOY6y0{hl)W zEIwu<$ROur!+mY^zM+_boDLx7{4vRHn^I^pu)o(+SV}?!en`yu3NJ{nalvS5>NLEh zJ6Jp>;{5|4;te&S0x`|oKDtZ+a*$;Tz7DqsMBIadfuyq$_{cq)0-o^f6YyA)_BzFQ zo{ures?2&MyZj(xF;GsAI^m!Q*r{DgiM8}Rhq#5l9=IP8Omh}>cFc9Zpah}%f_>|q zIQ>OgjyzfgVq_RC0}60o`fXSY5X)>{~} z9t&9|r!-&UgbeFhjHmZX$hXI#jHn{(j=JlXP8|D4jCi78_FnvIPE^+A&dd$d4P-7y zcV(mXiiq!_kI^#9GZSCg;L>Aq)#&3sr&nKH8vEA`Xtl)mnQ6wZ?^GH>Hw|L#-Ybch zjikKtnyQ)jl$XZc)$3(-x=xJ|;mCb6UcC}RQe3y5|ACaBGn2slY! zor;m#NGT;7xN>YrU;X1uSb?MKap(JK+87V}t;}-iX6lnn=aR!yH1=LI_erLZ-r)6@ zcJWjE`#~;`MD82o>da8nB&EDDw{@jb_1NUNpVHNm8^Ey#X&v8MaW}D)4GewA=_{p| zs(<+OR)Pn2!fA3-GN4^AX&5xm6SGhi#|cuh?}+`s|fIif`VOJ7v^M=mByF zbQvaKT>?rXL2!v%gHO#_mvZBkLqfvXW^=9u@T7*5-lSxJnv_J5UXQjPRaeYhBv-BD z(3p>~bk0d4h4y~fP@W=#+L*9HU*=k~kI>|A!T(t2aCF*wdF{)HRa#e7_?`71jpZA# z%zo2iW*awQIW%xYG-Td5DG5=MI7TQ-Qm+MTh3SA zRsH+C2TRS&k6hT1+$raG`Qy28G8|}m=v&(2^-o=O8tvB|P!pBHjF$}P*wbLm(YPC3 zElxX$F0Dtu#ip=5ICCR89CJY330~ppO0oM>$ck9g;noEfgQ z&R__O6`zZM@y|xj9v9Q0;?N9T10T@3O-8@1_T$$=**h@}u_yLJEOBm*{-E-5GV|?3 zs{6P_v_-J;+~7E!p}Nzy0qJY`{a%+4vv9AIdWGy%@yXPdQThG-x5!1?uxYlWA0XqF z8!?19!5~# z5G(g*xi>9ThEHa&a(TePvGc`1B->fJ^X)3rFFGzG^UceoGoL;xB+J(4Xx-I+`fN5! z;bCWZX(L5Xo5b9iVEqfe?k>K<6HwQ=RfrgpiM}Aps2AolS}PaD_l6`+`Xg(O?eP8h zp1~k8)|C3eevO(|=ZEZ;w;l)I!AA;0E>E&ZY_Q6B!+)#mCPbP6??@rSX_^}UNHCaH zhkXObVf~Dpv%m>SKe^4=64c5Fib-E1Z!= zj}zc1#<-vhhT9?KOq8+g3T_d6K8VcjuWO9;nL{KDuC5~%FeNUYK!msoV~*J!)twu> z<_WhF1(o`9jynC!C%6-pMM!d>&au}x=N9A18Fu-+L!X7YTm4k1zom88Vpla-e+80~ z0Fx6y5Nt167uNIc5dLxLf4R(AQUjD}2;b%bZyr#Fk*#yijkLoK@7sd6}`06Y^hU3(bHEn2pIqK-X z_KQ2vwK*jd`_Ls@OT>#uPtBO@nV0fjkM=gKYqHvV+E-{&m`Z!^F7NuO*V4WOm;Q(x z;>-Wr46F@ZA8kt|l+nWXz6-doeW^jIi%ovG$iz|1qy7>0?oIV?u6iK1D#gyV#!|~3 zn0TK(rV_F(sZb)+bt&<^jx8i#5qnpU2rzNCr5j@$Ak+A~#(r|wHwkdXj-;3Nslhrc z?=l5U6%dSqH(5c=v5G~3iF#@R*dB(@Hht+b_k?O7X417gpa>o9G>>BHAee*>i5{h# z;-}@PWDjP3o^i+Z$5dW1KRw3B`kx-3_7c zOQdp92h@$VB5vAMoDf_Mtf4=29VPX`9_*d$p!3O;gl_Ta2o@Ppq^i-(&&J<)Q}wLK zvx2o+({Vm4jpR`q3*9e~>Rw4t)D^S@2m1i!=w90u{tnY{mZT|*{r1%qFg!Sga|`gX zAS+QE;mlX_Gu&USdeyXqRTOIH=e^t2uU~U$K6Srr2)s#7uIpohF%nBDdR7^3*&etl zr{ljhT?bq9BWqHBtF$kxhDrw0QHQUC0xmPKhZM$g8&WFAFsEwVS|qFlOb5Mert)oV zwYW@Ul6}0&=6wSHqKX2P8q=`d!>b)J?uIeczFi_8Lb{Um-eb~Dmx4`J`t2PB=EU!H zt!ETBMDI~aZ?=qq!OsESQ0k6RChSO;@O=rH`4|v-#z1*^zE2pPp0n@u`>mh?Bi&;U zKL9F+ignAbRTey;MHMift{I<4o}b~H3wzD-H8Qfjc9vEa2K#aExHBUHPUhL}vJ1*h z(yLa7kW&7$Fa7yuo2+rKOgrcZls@Lpj&Yik4CJB72F|K5`w4NKUe652E5D$9y8vE|su^C?k0}kC5LVJvu7Bvv4>csymmANMx;bt#>H5e* zinpX(p=hu|6OJB3A{ECh4A-e099JGL#?U+-TrhB4*Z80Rb*j4*udDIwjx3y2RG4?= z(R};CmG*f?(b@|?=`qr1N>cp|VKYZH$wL2QMPy5|za)jFPf?9u3|MrEPjlTb+W$kOyh! zJyG4k;#$$X`Sa30{aKG>b!%RQ4R%Jvcd>XFFgvzf5a!yjJ>Ef{rx!W@kE;}^5Nu*U z-gD>ERFA%}%?0F>rT&Pv+}WeaV73S1;HuoWvz>TIuB+2ey@W3NO0iREaMt5Y7=nM2 z`Q($nE|@TUs+Qpk07y22@zRUW*vQ@g`?u?d3kFlt-wpee|K}mYqk591$mdjW2@4(i zK*+PueCF&Fq|NgkEN16u$JzJGYYC&?@gF;a{S;XV&)7627C#(}AkSdtN9}B9G~sOi zo{~z0J-+y*q@7VmaO29nKTpvkX%AlAXvkw%roQ%HBN_2!xe%2J2hye6cNY2HmZb5$ z%}qgW091iNpZKCx-gQs1s5xmu4cUG(1mB#zZAFh7qh2zdJoK{kGV}8117Ba*kmy#N z>61?|{akbPoMK26+}OKl`ifvnGQ3W1Djkk6#R|7Ep&89@-l~u`P7MGuqXuz+fZWca zW9O+A#Z`r5m0;Q(!JeDrW?oC?-M($QcdJ{QM!&oii|!CFW)Cxv=UmVcA>0X1fF%ox zQQvWSFzasM(6=(zTkXs!$die(z3pE9e0f=jZs={E*XAgM>LfF{386v1 z3MyPjU*U|P4RikW4p(R-^7`i;%CMmthw0^!e9hHi6^PI7kn(({&xY#cmDKPcIfyw) zEwJc)4iGMyr4*ZpD{_!lUI!k;Xuzn%F4cdj{==hFH%1jy0&JRhts8-}Y3QpJdiQ}% z6Ptj^18svN=Tq*A%pV|KCQ?}N(b}FfdQP=PLYq|AIo)#E@ zSaXTo3_b#RQDOzsl?EM}+Wc&SK8`Oul&|Q;6N3HYvNL>`Q8wWF-)gmARld{=t+A_2 zy-%4q?_8Z5ljE_KKJWtj{E4xPZjVH#jIA_rba~C$(OUk{^?;2tVZtDq5v$ec-bx`< z+%^eoQ)%^|*LRtJfrvPlFQ=q~p!o?bOs-nMT6B$I4_tMwUCB#R!f#CG*o@@SyPVU^ zc+%{G>0ttZME$Y`yraPW*@~G_Fk@o*aI3=ds!D;mUxP+x%wuMH5rrFNUmJ(XG}XXW zi|Stc>Ha$SyCYHb9N`Y!k!*QBUm<2B>>HHDh<0-#>LN4vw*rGLDE<9<2IpADoaugjdW&)6~^;MnyB6uQ|h#o zYL!>6S5Lqn3H~g<-XN1L8H)>n0tP1kB&Ytb%gZgoTX3R(k@psTivSm4PW}gq`S;2H zows4J>gP-2DdLB{p2ze2OHuFqOp)M=VF87ElX#vcjPFKqSySX}dwACcGG-d!3X2v- zOA9BxcwMMx%^|#ZVljcgu z2ta{Kd?s)ir0aCArPPX_T56pNS5gbH++~e;8)l#J!Cg21LF+`z`E9?Cxn&8rEcp?~ zw~Rb(wK|(4F}`0UhZ@ed>CY2-6y3(LVHHAVjJ(u>bA!k9MhuXY-xVTuouKVRz4^)o*9hZ=5`&1DQaHRAG>{^N$K=Wg4` zZfz_S3NC!nTuOU)8V|xkdL^a#KlAxkC&L!OJKph*&b%#@d<%dV6o_^VAhW((8Oc{( z%x3%H29UfB>yqU^6!aA>8|Bb+xWv7)<1i}hwY>l{UJJG#PQ**2U z^Lr%tE?Euftq$?c7UFq;ykfo%Nb<7!Znj=4*K@d=WF;du>8hRX{>O&kT+e^=)c*t* zaGs`MvS{-@7f?Fj5C_I$zq^QM zZbjPp8U!Qx5U@EHysWXmSHGMscUcwuHkx3h?U!?$X}Q+-T;KAaJzd*z&h6swF1CPl z9{baNmVydjx-~1^@@k z09nHvrlgZVs%8=!7_!{l>S9CEPF0WFe}}6}oou$}0Ma4oywDB**7K`s;+Ny*Osf-M zz+OrP!7IIUN7p_FdCxdxW-)dYadg09PhOc!DX3FhXiQbBXn!>_OU=L&LS zA~|EkZ&v?)m3D1nESBJdX9*`nppV7tZDR$`a6i%dIDMRIsV?I&s(g)CJ5um(8-dZaea(eMVqT^kk> zu_E(6PQscl@q8E9AARZ28O7hk_{|ohfw$T^1y1rC9urQ=(z}C-g|AU9tl&-0pG7*n zZe*X2Ip}$dEYsdp>#x4<2GFC~7Y3jKfP!E2%--D|mUa#LEV;iw?vT%} zx8;a4iBOSIUozRUi7~|0psV?${V6jrul0oobTSLe6t_rcMGA@G<}b=d`o!L z_!r!3kOquTbuoXvjWOgE%`1qe>!pU-up4urpCT#%uo0)f-!OT{-@*#wfuRd=-Pr@UB22<)EnolV@ z#!g^!Ff$Iri);kbbHXg4`5>6FHH_!lB!v7SyauA0>zNVv0c$li5$%|2nRNK$1m3&6 zt&$tvqFipqlw^6X$6#7Q zLk#)xlW{3MwVQ78tFp!L`Mnv*Q!i3^_RJe3@>kMwh{snAk0B333k<%1^7%VAVYzJ~ zfWR*@^)9r^9`sZ`X)ro094`rR+X7DevxYA{kiZGzu0}iHN6ru&GEA^fObp5VcbnSo zrWEi>##jDeA|qm0q)_#1rD>$|CMHy*Jw(JdPgib|ESfxoWG8fDv`*3rU5zf%pAX0t zmuw69_K)->-JKNeU3jCT?& zGzea*1P`rPy$8-{>%9uGxj^MjYF#cGL+2m2?^aQQL@1+c_g-C86`v$n#9@=R8y7ESO{e*YGWV)hp2RC2RYG^MhEO8b2dKb=pM~Z;a5~9Xm?Rc;8fEt~| zn_y};DlI2$)vhvJ2JBQHZ=A`UnFBP(?>hisBmb4Uk0RECpIkR52KYpUNAioDVDIz&7|B%k$=I)Mj@*BnD(C z|Ef3RqAXITWe}P0=-6gCAs$xdtqotn`_*b0?(zHd8N1RFs73#NnJ{2w zJYQ@G8MVgFj&M@e#V*OhB-)aXVh)*0+_##5k+tx~ZM1@UN5|3LTK-H|)0Xi58=zl3 z&Wbe=1#8lif-KPK*F?PP-w}2>(@@=+I{BGfWOKThqu(eAwpnI?3ry@J;H2xdf!HGf z2-q5YK?D-yJt&kF#rF=#Zjax6IBtLJlmah-Sipa&l&9ZPGFy#v7pqXKKw`cF_ z!FSF9RZ*QgtH`GU@{pkPF*|p2tgs3uW!1Z%9b)qz)Bh5whbG-j*=i^w$c-S`H|P4a z>cvz3PC>Q;xi|1d=_ZF_KdOOFXA}CUy1k=4d1Y1QPRRt@ z2TRY4Q7g6{>ixfF%A$oV zS{zESrs?T{>r_Zt$M^U7&({;L!z?8NmDLxCSide2vFfBDNecq8R!b)tAHSJ8Xg(e} z$+l^fv>85m1Lkg?@S(%PkLR)I7em;5C8`+?)grH>SZ}$3I^5!ahu1|^|5*+QCh0$e z_y52Abz%hovR$X`+#UVs1`*>Y>sO9%sUCU#tDTG;Yd0Z!kD}kn?fTj@rHnD`195Wa zf148jmzj<`0Q>D>jJpWkvxGdRDSNoUJ+koQ{XF30MJdN*|7gzPV)7QSf9EZxj9V+q9KY&*HR zBVL)6Nyd9OA}3Z>@(eT#bOE~q1A!-WrvIZ2^?)|On^6cRy7q8tO`T%UO5}#B>ftHw zc+C6d8leribApy2NdEd>`$oQDVk+SubLow_jFesP-*}6~x<(?9b z!2u^j70c*-0(7zTLXX{yx|g7UVf9(31rs9o>Pf)y`1Bl5=@A4itzWtPX4NFXGb?M7 zYbEcCUcx(He0xm~AcxUE)&@S;w_Mtdc}K@hs32Sexgdr>vj}oOXtbjb z`wFkzTn<*LgwweZ?cz;;rW zIB2e(5lRYNMgbsV2f*L{L&h!yYD^@kf&z$T9`q+aN#y6zaV5LO{%mrtsf=3gL;w}b zhO8GB1!byB6^qHnvad0v85i{dcs2*@T@(LdQ2>QE?}||$F8~0>uJQ+0#atwB-Y4b6 z63gDC3NWNxzF2rWV|qwwL|Mc3CNnob*aSQMDDtAw@{?K@_hl)?1!2%o-x?bNw9;g-Gk zzCKyi=(dFqqM~mkCmkNl$7<`g)w`|bmB#gTiON5+Ba|xSI4QKqIhQM#d$qrqOOZ5a z0hr@l@@@3R-G+*@-}1>nQq>9jy2lt4a)N2-zYtT2v-{(}Pj}knXIxiiaf27h3XY+G zQ~(9t#j1eIS&-arV>E=WH0ecdKCDq1G>nggwj%7qDK2VBz-a*#z!av_cBCK|4_Hsq z_mXaQ2&Rx7x1Gp|^~tP(I{$6gB#nkw|A@-JYZg7}PZNs;x`Zrfj~1FYD&PM*t_*_9 z@Tn<9_5r{?f4KWRn@9E7yxBKn? z=GMupJ-6+Mpe>AiC~)&&p-{-kJd^p;HeUFO8cE?jkJNh^MSnE>@1sLbzVVQ#hP7F_ zb_03F2epfpJC`VJI$Cu#P9ub`?dPBz`)WD3JCJFDOlfe|NU$EdEvds>f3WopZi81y z$_-BZer>ovUO+eUu&^5NtE(p|avsJcYrK?pCMMKLIg&~YT}4G!xsYVn_J)(~-g(pw zhjhVbESw(%??n8&M0HE3;8VYzNurfkD)iBDk09pP+D{AwXbP4$x&oo0oUG7(-6gB1 z)Juz4l0t(OGZ{i}c6~E~2IWh!8J}$RodT+W@6;ku4C}LcsH9|8GGSOLv=L>l=NHzI zFZC*OIp)XaQRpK=U|IYE_%z-cc+Zq1Jhu|%#bl3`bC?Vd3gU*|3dVlwZUoyQ$;w}W zk(2%E2M8SD4hD3HF>vX>R?B!les+u8;-0cw)DToZjANVJ#OncdCa0414H<9O7fBCL z?gu^YE8g9M2Z+G~7ld<|2CxJ@3$2Mnb*)`lAh3idRd$#4`?QzgYFYf zLbz55F(rr!MFLxW{2TWP8V}SmUZC@YA}WC35Etl_mO#+XF+xHEge5uG7B~h&>j<># zzGAX6>*|x-sF{Z;wv+X4FZQFwrXqljg(4g~@UOP8i<_2{F}DK=L{o8|AhBzKM?(qf z3+RCMK|Nq)^PoJeLG8~9vwm6>Nt*!TXkyV*3ae(&%$ZBeP-sNEKxm-bm97jTCd(_0 z08HSGH#;l~aokdiMzD|8xnT9cF$u#VpS=oT<2PHL?PXsv4X0w!N>(g_*9nbgKZ@EF zZhHxW{Tz^+)Q(jjEV$J(juI*fD*wW%g(U-O`AB&grpDgRV?akRf-n=jA-$$6L<}UiH%9(|Bs#AdaHRbr?1B5xBZf{w z0h|&FQ^A`inr%|I(TBWBcNvgyB5>u!v%Ru_PLPIEStZp6i+yp|$3cZeJ>3b#bT^_R z1DvEWeV6@e2eYRlVQIkAhB&TVey)-m#TN$8A&6-3$?Vsieg+i&@w6$+r7B_y7oQo0 zl_FeO`X=er7E8lj?^-Y^iG03_5-qHHCQ;1X(c;edGsNoCGaYj&UrQz)vruWm?J0m& zC;WUt^M7~p$bUg8|NqUAD*uIVY%?mX0;sKAd74O85b_N>dBFlE+=BBWXe%KGPYCd| zvskX-i~wRmPY^2s#1h;W0XKRGpIagOb=e%aL2P!{F#JcmD|GE)lt9WnxY>9{(CrDh zC?DzXO#r1%9kj|F_iHAu(s4aeNfaV%l%ka)dK3__zA}QqK(MV4;4hB_NtM`?C+DRq zAmrTc7Y1$`PmtJ$AAb9Hy3OnQ*WndbnO9^OvA_+)^AOd>=(*WU^k|**d;5-wX zKfu9Z27qo%&9uK%o_gBzimHDB!~oo;$x|w>U?yX7bAV=|LH8B+CF8Zu#X%bJdO2xu30sH3GeYB@7~w|}@gygbAU34 zMi7nwI*Nb&w&Lye7k3CnJ=h(xNgAM?^}M<^%_?r|KWHC0Dr|nu9^o85&zV@$>}6A)*lcnW@`EMvVc?D7fS$r zM-w!uQc#m%lyqIz3|q(gRPTUO4>|}Z$uu8N;)dNd0LQ5X!0q4pIHqrmki>+wUMzfJ zig=CTO0&C4$gMyhzI}IHz>%yq%09CAOZAJ(_vgD}H7{5Jh3g5J#YDiAZYjkuGXYqy z$thmh2)@4x)P+qxDD#-Y`$mm?{vLoiWFz=nasZIL8$nx20JD*G0T3O4^Zh|W6%jOP z2_z&AEk@3Wzd*ezyxi630Ju@6)A@}qrMG`U$b1JBDTztB8eG#c3NRizkl?_<00Q;5 z=qmxR{|__{R-bUD5kVJz%N$Ib!=-h192|5sVtXR3n|k0MLMa+?J4r9wY^6@w#H%Wy5W7M^h&`NvPlKox^q5OF0+ksJnLq6)6;lPJ167>u&OeCU$0bq;SP>A zQK45XGKW+C+vYD!38&?#aae-A5(`eM5&duNy=PFA+qO1pKxq((B1vMSNP{E^g5(?} zbqgpc&`1(gq*0J4S!j|9f&q{q&?3RWLR6591Q8HH0m)HCf)XU%G26Y*-CxzMI(4eP zANSt+_8)84T1#Hucg``#c+%vSbHBYA2t0S*HcfUij%#2WowVnd=O~Hj5j^popVL`c zItPoiq8JN0b#mj2Zu#+*8L2xtrUN$pNF8!-YJUax6xms>j7)|L&#GlV9!6OXv-78d zH-1AL246>x!7coBA0$9o`jF=u%ltCsw#N_ud3lE%!~M-U9i$d{{^MWDJnx0_7c=oG zAM<>y^nC&;_KtAE_UF_|GTis@9854q)e(kV8sb+ugacUg%b@b$rB8$Gqw8C@2F5Xj zfnw5jSI)@ppcSxPF&Ud7vq_|koHe1fr?AR5T={T5r1Q3JxycqKSh6`CF{pyjsgkss zCTZ1&aR`?Q(v2prku-$sq%YAfvgpG&J}(=bLM#2yz2Q$VqsGlZhbqkNTsFe7ooTS& z@tg2q>H^u^IuTQ0Ose{JoB7-wa!Kk*ul6j+Sv{eI0rPUh)66e>rp{iFq$QqA%kJ=j z0mML@bSFQf*%i?|c08ZeD5nArI(cnzs1Y4i<5>!$wl!YE*wctn9R2*_6NU(@m2$Y~ zaMe(rZ)zfk^!8HK{^c{$E4mwherJ16z8C$DZwO)uz=VfmE2K^` z8ib4Bt`;gp3FAz^D=b|s`@R(&Le#cl;-`|^)gh+r>sFQzMSz2u}Ch*<%3nv}O z-u23@Et|Jbyq14_4(;sZDEA2I8ip{tvA2ZP^g?opCP9>GN?IXbSz1U4E5A9)zZH#e z(*d>QyxD8yDs#knN^Jr6oE{&G z_Q^*Kp})Pp9pgyiXblT6V{uX~vsA3}O5hlf<$?u9ZR=muaOQV1m*A|zWOndmGj_g7 zU|}+P?Cc$ysb{61{<~i4k21E9^$Fs`HiS6P<9HFBg(`au4iWY>FZ5T~mF93B(u8e0p+^aw%El zj0k5(ePUp<)`!J@$=!9CYmPwgSxP}k#9y=i1>g<`5V{77QZiTvvPvLBCAIlpZfK#;VX}FQDS&opNPMpMTppy-kJI!^7uNaQid^_z?szdLE77YH0 zly2{^;@N&CABZ~38PYhMO|QE$6eOd2$|-U0j#ijW)*dsdc7X7p7wCD57i4#KJ8rIP zTX2w{xE?DJw=RzTW$thsIAP175xy6QgPrfG+LXJt^gS)*Gqfh1iGNmAr7Ij*cl(vd z4ID0r9)POr1yEg%;7nRV2Me7CjRm|N1L$|iE;Znm9Bi}{PE?5k=;I{aYL)M zr5|1MUTRzed${h0ztzz{4H{dEgN*pbDM~pS;W8V%F2DAOI)^DFll2qVa^ufZYeWIm z2y5n`g~V?N8%x6KJ!<~&;Of^jietZ4H#CvIY^5U4PgYXS?&w2-R!B^7V)^1Z{FAA& zralF<9T8D#cEsv-J@^6A*&Z;N&3 z$xoY9@T6t24KB9Dqs@+dKIZ6Oa?gSd%jeu0i0^+a_jno({#c~E+WeKLmg}F7BqJnA zu51a^!C9D~#goc?{E7#6%_gwZhSZcbrY@)grgr==C-RMKw6`eL-I_ z0*ZnJ(1<7>GEOxsMdynFMG;;~`Eu-Jth90fXv#;B%bxATF+r7~)Ehrd)i!=jeSPE4 zJrt&)jKEDG``@$21__r!hr`?u)5cqJeRpb2*$SakZuu%jCY zGyc5$mkm*G?bRmNlXK&zUtETCsAJh&&7MXSf5?YvTmJjeV0lx2@ZF=`j6?>@El@!= zM6+PCg10v3VIS&(`)(8_tT=dklX`4ei4$ouxsC?Z)$$Tn3&wFUV9^AYDzu@|C`PzWkfx70sKS& z(fi_OIQG*jsoKZ8g|I%M*SX8`b|rnT{uc^v^l$c!OVmBKHkF+)0(5qf^e- zuaIT;OIc=?rwJIP?IvLuXA=`d);o|ePl zjEbn~pjG<&W1|eT3)I5%6IS>9dI_i!8{yF6L$eAKsfh6SWW6c+s|=1>!iSv7ifw>J zKl7{>-j}c&Bia#kqg;;RPXV{hGiNVIY4bpzL3kq*o-(GF@%Z;d3b9>z(HQM%H|=^V zG~Z>Su;DZVLTTf>vIYOKOUl(el63apK%@)=ibkMnpLKDtvZE?^OIEtmak?%)mLWf@DRgeTs{@W5M;K}1z!)qIhafYWuwnGwa&iaG_LMIAssLR@NJl;&gnk2Q81Fv0 z;b-%I|AP-dE}fw6+)mr@(ss2i<#d?yruzQ*dB7AcfKzAw{uPQ)u8CU-!RuJ0xW%0iYX5c^+72CD=&GkP@m42&CM`RN@L5A+H z0gym$bZpc=t|B9N2Sq1yLNGGyYN{5`4!5n{44lkJ zs`?AGUqBP{AgB={Tv6q;lU`=3gd=tZ_9d{LU-kR^pkZ|O7zK(r8YL<}`A4PPUGV^-6JGymp~g|8vk>rh zk$7NpK+V0glLTRI^-yw__oZW^xQ6EdCx}M=sw3XOvgfU$CbS&f4hUN$10Y0koaHZJ zc=!{*Ka&iZlnSl)_(0kF8HD5=xy6Io2?SRimbEF?`lx{r0w)JysqskXZ z*-tB_=B0 z-+^Ee4S4|Px!Vlv6>(67dV#Owk^8pqd6Ufd= zVJX27(6~;?IRe0<*I1HX!%tv5k=@Pl*Hi~;7#`t1L%?^Z%z;IuKd$M6U;6-p%)Y}x zjjRw2h+BDIjR0Y^n!iw2)!k7kU8_3eG%WH*T#>(+>HD@)Z3= z`e9d~e-j|Sx*l4geV}R3`(C*=D|*-y;y|UHTT?lu9kpM>_jl|2etK(jgZMCFe++EO z+)H&b$Q)7#)kQSgd|Jq!m3w+b{{<9AKBK{ZJU+{SboS13TcDC0bCXXR3dVcCl?hjf zPfKjLhJoox-ee8H6K;e!J%10W+wvQ>XcJBxBfkN*-K%;RM-FA*z|s`Aex_g|a|1^G zrG<8?;1J#?xV!%pEN0zwtFZpnFE2G*Pg(EAi53SXIMCYO(zrrYLGV)fxS9p%5mUY5yH3)1wl#IgG$*c5KsR>Nsf4iLkIw46?OaJKs2%5-pPMD|E!@!`LxJ zT2g`sfOPZ@C_VDadl)kBg<^}l2uUBP)x;Y-OsdqZT@bMwEt|98r}*@HD$&gI9&`=+ zK5;gM`ZuA3^A*sEbcJv(8Um;8Y%IWRPS>*Ya*0~F?9wz;_!yo2Ho^!>#Nqv3LLqPD zK3|xGv!iJW_{q7L08(i*a!`-XnpUy68|E z#u}RKH~e3eH^y}AD&R|wCms9evfNBP$64d$TqLb9fnkM&sQQ9GI*D1A>jMA}as8tp zc;qyckgn1XKav6umYa8AZCRRDY@h?{44}b@m-RY|zMVg+$$>90W+dTZ*j1~fc9p;Bpn_h11NBBeCmx_0KgBNqkJJVk06 z=nBZaz)o2HjxGwK!R&6$JdI_4)|tdOxqmnc*M)`xq?QMmUDfRsO)~VNx_2b(obj*o zPqD-!2tOlSxCR^M8Iq}e$53uI_~D1I1o4o~UL_&nXI zATqFdIhjG+s^WX$C(DWh&T^8Cr2wHnViAQ}H^bG1hUtAC1(m3(;x57(%*TvNTtmbO zNOas9-dK{foJcylJY$<;6%*2-!%&*<>k2!W?ZFv!>qNxR?+f$&4(zj=wSVYW@GT@S z#m>g!@8nyX=Z=U~lfhP~jeiU_Lya*pjRbn`?#F3uNZAlUUj3Z$T3M~Qe{YiKqSD&U z$>Ia=4LfpgY8Y~gk115Gwvh|KMNz)*Jy>ghYK^|v(i zScFsh-z55!zVFXXT%~)EYxwGrjO6viRqtaoYLLx`c|-~n9`jlcctGH68IGR;)1#3{ zN=Eln>PM!s*9VQAw%pX>u*7KjL4bS_eP6IC# zsFo=!$zp6MLa}<8Rj&#dU-Q0pq{SwGsM|RIo#`QR4XU@A4mr67O}K1JJWzyjUkmfWziQX?! zrdwu~y=AAJlyu_m>*2$*(?wRi;Ueigx`~d@wQ(m%NlpW+J~$&9T*aC+RJb?>E*W8; zf*c-fyH+;O=umZ-rCIiIh!76U4b}UQb4@42k#Fe%j-RRQk=P-Pc$erW14m zc6X(V2S`%fQkUVrhesv1wZ1}A+4(J8VksNwy#o4rdrnZX#KUb7x*4j07E(e|D!_QT z1>sJ&-V!6y9NTed>rlx6T+AR^$AY|tFP}3E-(2g$_#IFf;4WZ&D*iB*McD7K>>v|B zGJ6l#1d@=V`3o8wh1+gPeS%pA(NYVVeY&;zVX{y9bwKgKzmK2*O1 zId1HyA#OdCm0c3&K%@DoS{0l)(msl<7~*#|tXdh2?Qy;OyU0D|v~jd&j#}$8`e!ON zD1BDN>McOFhu5<}%>fjuQf4{OoQb~Qu3BiZXjmv`;rwIJ2#;aU=3#Z>{6#$T@bMt( zh7iGVt>H89#5XG~=0|)gn4WHsJuRmlF##|ihGijhS2>JPom#iKhNYt@r`~3N&?Cwvj2BEKNX?OB57tIugH)GgayzEDKi`+Q^^aWzLsz?}9{d*;ZHuwt)E>CA@PF0= z|NmY@@c&|c!+-N=W>*}(!;yUhl(R?BcAtWqWdPz40ZnKrnj=S$;}6{>gR}tB%Ui3k zi;#mb0qLv&L+HE=JX0J0pJr4(@E}cMo_h)Ya5;)N#O#} zBLKv{YBr#Us-$}S1D(=d2cxd#lrw^Jy%88pc?ag5I0&UjB-aX@;s+WJcpIa<07Ng< z738IJTb&K``LhZG)hU>KFvc`unjg>Iu}euojp8UkaIpxJ`+FIL2IV7C9|JTQ4?;#6 z1k|DK;{d?VRKX;WAa_C?#-)}Jyp<|VL^!8O%h<+oxO}He208KmrQ>~ybiDuMJIO)1 z1ZXDrBP4)2r$GKf9gO(A)Dc17oVP{ehG93PwC+PvC^Ce&@LWK+#v@4vU&$- z%@2UXa6dSH^+XHl#}_$y2t!JRL<@QYq(ZP`D#$YbjgWWnd9t~^;Z-6vo|L78A=HUejeunU z-8G^*hoa27O8{c72ey+P1ii+|MIei-52s_Z_)VVSTn>dLqc;yC;~W7!%y}5)DTSr$ zh(85jgA7nr?%M0rJL(Np(^*Xm;#zWXtJaa8o-evjN;}p?!=V+Yz62~}UQr@47Cyf) zpcGL8s@hx%cQraDr2%q>$$QAO!h*WsY+%710dFZ%u{0n88zG+J&p&9oL7qi)YQ7;$ zv~S$@V;E;Nlo!G=T|jvOsl)B5E=YXPEmN6yT*!gU-1x?hbkG)_!s46<5-hh!mA1lD zWZ*6$InIodfxxIgZy>8x*X<<+?Kt2-{y7~}4ht#IGug4~ldX5#bH1g#U+HDd)`LjNP@%CjJK*0? zr*e^WUDz7E58TB)+MHNfFUkGaBbc?XYEtaNC2$5bGNEkUk`#A*r{TPk!*|$Wri+&I z%>x*3ox*((n~|2m+#nOsu4LWAY9wwB`?B}Y&fpRTb_pCYS?^*i=e{uz9mW8%DiPO^ znnz7B7Fq?#_rJWqw#k8<**qgi5R}fV%iJ7xZtQLHD+%ZDrvM`tkiM>O6izhuOIZGS zAyYF3f_-iv;ZEAZ-AhLw0kR>9fC>B)1aX3!QHd;lO^{t$S95F)B}SMt!PXpzQ4E@j z(dWp=Z|Dw}1<<3%@=wbNLb{g!&51gjBgYCB76?0FdOYeYMQFh*vy zYltRGAlB4x^#X2l}KI2yI81!l9gv)cCiMGLKrmdDS<6QRPo=-27 z&3hkI4zLtNvovrD1%XxA)Q(M||5EL~=qdW9+mFxU>oIOLGP+7mvNZ=v zFvbXJsqL_2KMe!|5ly-TF+OpVa>q-Id}FO;3r#nWkR2KS+l)d$R6TAX7aRC6R(P%H zXtQr=SwD3pVdauqtnSuIDe;R)uqiT$Qxv*i=U#sIf z!Y5wy5v309;AHYSHi^90~OA^ z)rCN3nsUg!5+YP%0s#xVNPn)s=M%(?fLuYu0@LSw&(oqu7xhGPRv_T4_#=H;sC_$@ z8KG`oaJgHffyje>05>?^Evnl5gOHXAH3kM>q+!xS#PAz?l!s(X>d--c;Rf)wP=|KV z@8p`(7ud2CVjKVqHE>86`Un?ytw6{TH&RPba$W%b66f2LDaf@rFXbBfFi%Wq%@4|G z1G;MllCeBcun1G|p*i$yl$TJVIu0flh0x@}d@mN~t}jQHi1u^LWH{4q$37j}3;c~M z$dpdSYsly4n0I`EWM(4V9Tr#S+4r7vYA5Vo0!-N!b3*y!YYjkG-k&ue^{F`I44U)g zcowG5jLQk;53xfXCYMoa3A@r6k?;TYg8_v&;v;vzn*;|*-fU>N#F$|Z9O3D@wy(j= zV6j{W0P!J}mRSGy3(?WJ7%!3*ay*XSG?Jj|%LoH7c&p`rJdj(ADL?6_LLVT}T{0e% zph=5GcRsms%^FeJ2{_6i?T7olyO8$yTDjpo_p*oic5HyOw4}z9h1WxJJ5CW=@O&?% zTUtsoa$A@gY#v=6qVAES$##El{o8f@f6Fa^|4rZYfBrEP+W+y@ivPp62IpTT=r|EB zM+6hoJc>uNG*v;QG!;(=-Q5WEkp-!XTgLa~kAM+}A3ReQcehYt7?SQIfIU^&?=ltP ze$S6u(|IK11#Ie03S^PEi~yZ(eD*8?{{X`sfhO)r>e^Px1BA}EEdoIG=m#<;O%DQu zzy9tD`klLN;jths=Yd#JxzGuf-ye^GT!n~?*obz6YyVh)2!8^P#9Yo7v@(qL``wA3 zsNsaYD`g_S=Gjmi&T9uN~l2=8boJ`-iF7wQloS7Z~=VN z>)pXSb#QyuoicBbGBzT)DQdl;b$KZ2wcglFKAtpnXL8;afo30EDU)%Ph@_?m^M_+Aj(aH06)1{tIfB zfW>V9kUzDIE``XSA3gxZdLAM!^dOPK5lD(S6vKyZ7W||Ds#9NJP`YHGZryY*gFTHR z6ADXe=u4qh)^3dFMPdQOtAdX4BLabuwU_=3$or!~xYdZdJg8iDh?*7^=r}hI@T=i< za#1+RRM;bq_qaS#zoI;u??9WPI-GaT+U4ihHtSNuDS0dB`pD_RJU z92^A~wGlMlnkvoiPwhuh*a(p6k9EL4OGIK(WGRw|%MPu9YZMFmLj-H_2@vM>S+0p z>(!JfI1knGk$uy(f@nF9UMWCaWAQdb-qzYp)aij+q!fAi(6yr0?ghCPm~4xaaE&Fr z9e&(Nl7dso-dQ@VF%X`TZKm5$+=XRw>|32>U5b4`ZtO5{wie0cjACd!N}(xj%!-w` z8~O=oyW3~-z6mZu^sz(?zOwgF@^f}8Tj?XUS9+~*=L(~Io~bctT6Av{pnfG3d-yC? zN{4f_QX;e+ux%F9S=O5dV|-{1;XIK{-14f{L|%*FaO^6CA>PwuUqNu(qn`WZaC;^&=$?WU1Pz2%1bJ)h5(He#OE! z`!k`8i(Nkwn|Z>*ZwuLvHy=>L;-%qs!6a52{>9slU(sCTnXtN8<{TL)GBhrc2@ zk-ixLvo6LcNpT&;4FaE5^>_P>yI+SeK>iADi(H{?9iF8WX6;?L_74j%wNRW;*$`~?F$n;s>g1=ekuOo z+;JRhN}Apj!x500kvlc4M0@U`g)Z}`pJTYFu8GsHIx2JIkAmrjU6C|r|e)+2I#E}Oh0IjHQ)OgGqfJr1`nD>fVC{ROJu^c#5Ct`oyY(@;~IiIfB8@;*h~F zl8K)WVF7@THXtVfUYa^wT9h&fl4&&;$RK{RBT^FDZEQ)e0DFkv^D=Iw8nW%9!oSa-?R;L3OcYC$AMrzpP-9FH)mSB zm<8g`sBid;@3-%-OkhvQO2%*JPfNvDOa(KTm;rl}?Uq0w|{oc-&s6vE?= zds)TxmNh>80~m%5xL+*tiTpMx?!AbJ1Rtj901s6uf;@l0fI>(V!F2qQw}f(IrWZKl z2eVr{2#?Wm0~$|01dz;JYg()TNVJ@K{qI}uT#N<2xePSyh|0J89Y^1jY;}eUIVmid zM>n4~hh0LlI(fKggv#8E$H#mDpyok3i*5*n@=&#daPHx(`}1@TkETDNJVNnCyTm7S z7_GvO;w&E*J~f<)(bvz`JgJDk?#|ICY8UCrTFzOLP0^6GW)h6^OGWqV1wSjIlu_e~ zoMm{aHF^90_ssVH&j0;CPmT_p{|FS^&{PGH6sKBH0OAj*ePp7b7Q!|Si%lLV$sy@P zj3RXhX-AfxZ9*s@APh0c>cglwmWZ+fP_At}awUOvngiU0kN>4ZaN@kzh`LlxkW?e& z6e%-Mnk%wWqf58*A#e~`T)fcj&+y+9sYYgZsoGv;-DT|^99@v@MjaTD0|(l_M9t4= zganbRXvzE=RQ~S1lafyW!?6pp^B{& z0+LiGzxUj)+?eS5d3ADaxgaJ`+|luDZysgoMfAJHql@nb3v5i&Gbkd#dCn?rrjw2T z%m0_0bh*&|r_y}Ou6~(vsN%2;c>^J!NK{0OS3KlnY72c5ZX((jMT8=43N+Y_sNU$F zDkLlX0`U2S<#b=|kN~LWqv0+W8OWo{lU2eJ{((lT+%f)a4|_s_LD%|7s%MXhWkT$XA@RaC}#je%)tL_jPL|BABVpP>oyy0um zSQZ3AO@7sgGM2trp|5u)g z&25X8a`4BKsl{7;lh5aoCiECgH(i*S=N&Fl@W~y8>utHtqkI{%XG!&LHF_dKuqos> zAmkAx&p#r_LsQG8H5$C|E@2BZcg0*@B&6-aNcveXabvR5yQZ6@Z)3LX>=Fdk@(WX} zt#9tYnzx<#)8aGwBHL#EV*Er3HP+{zrT5tKH53=uzJKCpxI^JKl30%MJEY_5=dSYcZeJvEc?ZXeRt#dRvEO`eh6y-RfRtgGfhJIP{* z_L=G_K8s}SNXN)O;37hZU@?HpDr{UHu>a`$$F%DFy6WvU+I@e{p){WsYUWd00hepW z;+ZbHBqn#H{U`0|_+Hkrm$=BBcT?>X$<%4A4jo@W&>w(_Z-kt27HnT$FrMhZ7qhIg zm?$7C$eQLZ+-oaYef>_+>&|%rtTh1PauVf3q2;itM<5O>4s<`VsJ)L-%%RNFUIe+3 z7g(_yQ1%|`MISDkQj}Nz*JnCvu5JUMl4WoDt+JQ!akBT+BDoc{6IZ;uU1_B`&xNFj zE{z|BfytCm3en_xixX{PDTRKR6w=x;C^}t%Bw&xTgL7n0U#^YDk)WZNTyeJPrY1ox zzz2zh4|056OeUe@pck|g2JcdDl3+^e!bBqzAG+~*9!fH;wl5yJqN z8fJ?uJcD+p5lE*bO|I@|cjFgp=Q2?0gc5(eRL&96eCNeYqN%c;!M(GCL#9l>Ud^~4 zbfVHcrE-OAYnc18$z`@60KNEHSPZ8jAFJJK8xwn^QNq2`gFtAlz|d>)&wDs1zNlIJ zv9VQ99&rG{S7{BsSRKUKrxo$==-y>Vk3@}!g1>_o#rMEy64F7%HtGKx$YaPg21lbs zW11#&5X$L3cy6QGs)g?_kUbaS{d|c(J{0e0Um8{#Ry?9S>H-$y>1#Hi+$4esO221M zyXU;a-MeQp&;+oAc* z1$@j_HfWh|t$@(2Ys>`^Kgu>?lw~M(v(9&S~eez*&P1zh0!SMved0X9G1C2)vwc z!Y0%q+tKft?pQ<@!Qqk4-D9D<%^$>gS#TIhgDMe;qyNm6fZh#l_7S-hKi3IZxjd+Q{9}3%a#ut% zz4oq3nY7VoSbMk4X)yQf{n%n9?DqR)-CF5Ws#vTr#AP)$h zn6A}SRUX?aLeuxgK++s+B@`XO#iTr^PCpyIgj6&t!U0ISj2zz^yv^(~k13%J##J~~ z!7M>-W*+dCAd-$yd+NDslIlSa%-?Z@l8@@*9DVgqgQBdmb5B)G~X+rxk1YxkjUMMZ(txcmuHk9 z3(%HO(G7I6BQWLHa>QKyAb;iLmS{!B=K*6byUYw=vwv;j0im~K9=(QSPZcRETQSX? z{M-w{Da-M6OOqYNkwyIdtx6!Egmr-c6Yh_)WYb zLY56(Ng!{1T-e)r#r$I{s=U*dZgbns7|+V*5V*EXQNkm^V)as#`wa5=1Gwh}+Isfs zpiE?L*cgBl(6HlP)cHtt)Aqd=+J?A?YXvI4beY`UdUg`{Y=1A;-CHqJR<*&l>mqth zS<)tRINnRwby@aaP|clS+8^ASllD-o13*fZ>=s(Am(o-$ZuBSPK=$iB;zVKBP zDBzRu$WCkdq%J^8ieeHZM?5f z(%qV$;VRK+#yFzeDQ0%J+4G`10id>GeSF@)o9)^nkhk@}_VfP9(Zvucz2WYv4wBAd zd^LqzH0iP`+oH4qfeTvhioCFUxdoTT9NzH;TIQ~(M|Ic~IDdHST#~6g^GNpSI)8nj z%DRd}?=`*$9UwH66<1u|4wsEMPpb;x_{fan=SVs^jk|kx1-l?9@K-rs5&vxLWUUro zM-7&3YCy1B>e1P~g0WlumwU6k@HUJNtuD2vk~`E#=4nX^C_~0wcAgF!=RrGbb`IZL zV5jb*{u*cnWVz&+Q4e%1>Vq z6wJOPGb35sZ|N|;CAQfx=OE-MK!-ld3R8Syz3UD9v6Z@t=fwecnsRhinspZ4i*(sM)Wq@y6|6rDjSx}CTpeR2iFPY5FYqiHGsQx+pA{gV`|5UI#O7)wS zPFR|nHp6Q3VFKy*5EE-~4yQz_VEA;6zSg^kXLoHbR=@~h*`v*^i&P$2FlkK--VK*3 z;@H7cp0dt#f~#jo9F{NeZQjRRw&1Api(zy1QEL6J?E+F~)OKtw&v_{E4Ye%Gmi#>v zBRG|#tCb<620AY(Us`^g_k)nFyp_a6rh9$@vUU$k!Pt?<6pT4{6P+^LO6&6vx3`Iq zR~!5;xQ;u!)_jIhIT)hfij5En|{FEOGHS*;L+XA}vrL9HeGvnAp za%TPDfz5b)`bynh|Kpf*$~@8j%CE1`6me~)T=JaLU}|p=PMwdYxkfS*%#Na6-ZHcC zA)Pq)l9u@gkE+vqe&tDd#{9ajBX^5Ru6VOE5dRS7r-cTTR*3cdf~p!LyZv_)hq~ND zIhRS7B%^|JXezGFDf918jysn=Uz}UQ`b;;1%)%^tpQWEI*uBtKl3;KObe^@P=r66wbTm zsvrB0eEhQ+I)7--#>~Rr5B*}gR!1eYD%j@v1?*xlj+;rW`Qhdo54w-qU{+=CFSK=b zwm%%v_%L~qsfXdA_*I=-Z{<+f1THvufoKJO-a+n~R|BUAF;ybZ-O8QIuPpdz`A1es zu6`MQ?0Mkaznez>>Hi(rlY8JYbj1e^a7HM+90lT)*0CDZ(Tf!_qqITs=ZP5#hBqfJ zZh|ul=Z{QpoJDAtz0Q zSq87U!x>2ereOD>)^m2p> zm<(SZg9yV>Fqjx=gsWcxnS32kleiR#i!?3BH4ssR%vokjz%QL#$KQOO`Sf0vuv?`% zGd7yJVJaSJ{U6Onk_M1eqBGZSE4H^T0keloX^I;7bMy46u$j zTm!st(FQLX%L+l7P|!l;`yQsQ{}#Ki!{lb*h+K+8AhI3zWnTLYtyoUXfdPhT-KNVl zhjBjm;;9q*5wRQhlEHH!h=dIvRlFC*-kF1q3*oHUP=L%KPfWHQ9NTR09_>+5JAf<+ zDB7{}+W{tU&3LV^%)9w5-Jx(3YE0xm3qQ$*iO(%405BOZlpHYofV7A@lTn!AO^O$} zC&NdbsubJN)hS9>@9+Es1KH_E%|tha58xWi+wg^%vCF^F4{I;+tW^fN9vY|tkA=@p z(BFS8Veserz`lb95!gCr49eg6$eZN3uLIwz-K>sai2L9}b>#!R8_vsVn|afnC~toB;uZqz$?2|5=yB)M=QS?0Vt z)TkL92vcy^CbMx`LWsW9=zW$7Ytu75C`Xhefw6BjvNGGjzgDBPdOxM)-5;vj66&f; z_?Lh|zBSs3QDyJJK4kht=|9_(?Hks^QNWPwE_}+tkKn#XQzd(ROb@W%X%y}7D3nw~ z&oF33FnFk8dg&eelQe+D^=L$E?2s)F!U3XT0VoqPrgj@dXL8rA(>z0|oiLEFpy7ye z9~sT5f)>#AcZCRsV>Nd1Qp}zizF4?U8U}HaWcPbNzgY zF`sA>vq6OD&(j2qJPlupgX5Yp3WZ?PI7<7{)~n^10!h&6tfEN3L1R`So5+yHHTA0o z@p0a|L!&O?VoR|xhbChw*lx-9rYNgV=hkAIDx_T|%ozzRo;halM-8gJ#c+Q92Q!gv zW)FqxT4QHDXp|_@G>2+-E~}dFtwq@+JLm`Ydz%T4vEVS$5Mgs2}an_Wm5`JI;D{O9Zm+d>-_C#jwDwH6Pdqed>VeW#H@i+XY_ZxDyB=8OSDqg4%Vs-s|QdNO8oO9}(yy8XD zot!?QwVI7{5DS5l?e>U=?i<*4v10nsu^-R7sMk>-b1+iik%GCG6*->zZasqprDcUuatmdFZ)(MoeJSY?IgYp*)AGxZX!Hn`0p*`&bc?3`wzZ^ zLeJzK6T`Zbh%PHJT0Y|Sb3Z|#W9#9Q_qROB3`J@mKzCWr77+PxH~#feBC=z7!Zewi$}f`5w0@s+Ha$E1JI!aHCBNo1 zkcw_j+Bm2FSI-g206=;=PCi_w#?Wnws8+5<@n4>Giw@A-YsW~Z#BiiNKLY;+LniGV zQ+A$7TFjys4Ut9)Lg*A%#bem&a zy2bpi)O`Dx_2QeWgk61Uz`K7Na#>vy-@3Qav{n;9x?>A^xvp(O2<|g|geqczqh83l zGX|YZKwRb2m>+q!)4^=7P{^1|03pJVY5Vz;*U3^1>TI%`TpvS|_R$@~yOfK>eNcEN z;f-&?Fou^RDXB_N>~&F$Hp9sz+U`sX?fN+X;{0ta%K1B3rZ^oE%@h?dD&))h_D(8f zd+RR`WLlP;&BwEaQhsh_W$C?0ni-NDIFji7ZppXGR}E7@FbVezbs%gvyXlVG5;BB3 zvyy3U+M^yBAyS93j|*6Jen(wb!0?gB8UxJ`-ZQ{Nx9#XH+L25i-o;YJ(67)Zbt?H@ z*k62(hHeL3NFXJ!YuRx;hE*_nPM0%VjDO9DqZ;`>H;9UJN_~(bdG^7OhO4kPt7ESz z?lR2>iv!r}iRulj4zK!a>*vi`gcDEx^J=nPaJ@9cBQ{eB7~Ef~rTq6f(%TUvPm+AF z9Ba^-fNU9yyC~-Ptn#gx$ygQ={87!%DI8WUUmhG&qW!`CEvBZi)vVM}SPe%cjS{68 zKGj}U9!k9~ZCJb40j~JyYx(AKuhr-n_WOspo3p-n->G;|%+87s-+bp;yqv*Z9cN~s z<9fkd)T6)Li*n^Uy$!@0>&Jx4@17R0W%cc4+QG7RvvySShJRmqW89+2Kds2b)3EfJ zgL1#WtD$Ny@#ZfgT*VH3WoAs>h6O{xd#M?GHeA1lovj)X>lUQglAW5ivGkv=mm#S9 zN;Blyp72)JC-Rcs;UWK;eRe{hcPAIZ9RFzT8C(a)jZ+L)m}Mir3TM#ea8jo~6iOTB zZg$-ZrE{Pp;d0wXHqKmGDmm=ddoY)58OglJ|IcNXLiqSbpp5b5@ne`eG z8<<1OEhD(Nuuhq>b?^c8C%74?$ nKmVp*?D&5UJq_|<+2SX7?U=*5TnOC;|1;1zpXHAECa7Xc9?NWxo1-eL%lkN}Z@r7c58HTLtIgi3*kiwAR(j*0)o7n1OkMB2!sR(2!Rkt*o&Rn*`4+e*y;GgoqNu?&phXx z=RWuOe(t$;+QW6%cGz|R0Ct@`;d}-FHo61AhMsL(p^>>y*Sw*d9qG6)$(s;Lq6EiY z1l)s3(U%CMOA+7gCtr*uMi8Q`EUYcQ`D%YSi4;w=x3t9n$H0OR8)kVh^|deLZuOMmud_{&2=E4wrq}inwWi*!_^5_qD9NFEWd8A$JV!-#n9_@=&;N^+xE=f6t_2H-{8& zEoq-6jqCdqk3CCgH4cmf1eEe^SE}t+xNBksZ*gd8A>104u@MO3CLX2&KuXCG>kYtW zX9M8K|2F*WR{*14#~yJSKz2%6G8&lLlM)sF>ZhvRy@L@Ofo)gKfRvQ*_l>_q5XgPw z?Kui$R+vDqBS$>qSS?-7vtN*9DeCp${Uf7n-zT7%c3LWYVURCyMa_x(Yho^-(Me+( zf=IpOQAEkLOjBJY2)ghmXXV_L88kXhef3zR>J=_f932ykwepEXl zy4_7Eerg%(v@)&K6)XT~r+28Pf20VsZE(;sFkvq9F1*WqK`AYb zx=o2odNX*36D84v(vR&G<#mT!+xr6y*e7S{8gPO4->;Q& zI2=C=rU;CbOY15+9Em+`w%<6UyOq}FN1a#m41QL@>0HeZD4)oUdtQ7;^}KZGbOCSljlHIwAfH_!=sKo_RgrP+w-cL0 zcqlKLbiziBuDbr5xj9dsy8?fd%p&@80yL8#sG0Pq^oCjR!1~K$&sD7(sBuFtUXgw; zp|XvBetvR{P4YuSi7vHvYM$K=PqPSmS5~X21%+Xqxt!RsR{PQhCCQO^(P(*QaLoPP{+#ja&!S5>0T#$9=x$x)8{1&up#npUO zA0t^oQK-vZp_jHvABknvs^4m!@wMqe8$nPm7rDu=T-4uT7GOA#k>6&)E%vY-`N3Xx zFEz5|*H6%BRilBYpg|vntqAMXW$irCYqbJ>X^o#W$ZN`7$u*r^Ph??#uAjF-hvqZ_ zmH{j4Jt%*h?zk^$Ev>+_a6UBPtWRYCrXh`2G8ET308M!P;Dn%pzb4hRplJCZsJkrX z;TE5-RW?j)BDuTL_o0;zqsTaA=`GQ9t|7GK1CB9XlB(fMGfx*Ej-;80?&RHi96$GZ zg15~vQt)U!6G#Askx}xd)q0YapCal+qK`>D%Hju|P1bFYwO^&H>2{}NP%2{zW<8#IiH%IBH ze0ai}n5UcTigh2Jf?#T8I)F*#rp&aC+L6CB@GuITkGd_LI+S8j?3EG8q$EJavUaY> zM%c^O3?jzv(s}$Q7CDxUsjknj!?|P?JUI9^K9lL99O5bFnrU9Hbt7uOiYD&XORQ!h zDTL*t^v9h;`fmzE+$*Ucd8>Je!k*!)#YjwVr{l!SetflK+!&u$o^b5(EBTFPVlS5H zo`z$y*@)OTEik*-5WIL$cSirI#rT7)%p$IGnG>{;+`>S6`k;kYxMXiBSEZ-gONiIb ziwMh2&k_}1G$Srp*Vf!JcDD-an2LtPD}od9;=14Ckdvw@;o3v^_x>*@4Tikt#}lme z>PYL`*J_pqG|EHGnI&Uw@Iq~%Lx{q$nPpu9_t(W&xIEY~Fyr8!W zk9}ADz4^2x#SaEeLcLII*OXU^#nerzesO1@6~tJO3A%cy@)7OwM5nyRj>YcXDdEE~ zFiz}quy(fYynF7Al5noldYY@O=R}V@gMA(J+kBM`q)Jwyr`XshZ;$H_GtKT<#TR@a z+c`ijh~QEf9(H3l{Gd5aVjA}h6q`_|${pJq)uah5M7bkGI41WM=uN?wnbfs_-;Pl>Mt6{$tb; z>uyqx4WVS8Rj2@8Ejj0Q%YyxcI3enJ=$3;t?AmoI_uD6iU-@=T9g>+j8@N|Pe6#M) zB!2jcu)veG4)g6S6kmJ+`YEZ28I2tN?Mgd5HR>qj7LUgxLRx-hv-I@gSg7NEcN5Fi4j|3Y`5vF= zzSZYl@3+2Li^V!KXYX^)&i}ry-#$SKauPWApWO$6KsZv8uM|NbR4)(+g#ZH$_$G+; zCK&jK1W}X_0~HUDYyk(T#-g&KAW&HZ*0t_E;26_JQWXLM5zzelLy}T_egFd9%5uEmwjZXmpQiVYnnpd|KsubX&qJztkR=G8E}hVriudqS43FYY zQcs6=*MPyJZbu8%GQ*GG-!ba#gRnrzulAeHE>As|MUX|`#yhk8@aemg=R@A>tOHf< zw+gwHRGjizz4ym^_}@=dpIwd6qkj)V^gx0Ce4w3dpjZEV)>fW^sQ&rb*Lpr}m;=jqA64v|Tp-wGV%8v+%Ed^KW zX#-ph>}m&H4TP=IwN}XRD6RG|kn70Myo`uS8Y%QA30{nG`#e!u3ZkY*!I0^3N*540q;w>}n46*!w7K#ayOp+(vZbO|jEgp)y-9F9csZ(R{~gZ`~&SWBl3 zAuD0m?=PadJTl&Hx~$bt&{eOpW*2B_YoB`wC0kEm$)I24fGn;h=idTDtz)e15^6VDHHdO{;2 z$2M7$I2K##3gib8xFyeiL{@dfuH73A#pR-(zd~)ftANi6H`>2Rznv7H$nK=1rG3i| zR;1zQ7jJ8C@966juWxW$zdU(K|FWJoO;eDakI!sZb^wo*l%8lS4+dd>&W>!kM?sjOTRn%F{Vmkxy`4}MHOO1H{W^8I_9bV9Jq;s{fFy9LDfJ}y?=ap>coo&gSbx196KOOq630i2CG%PB|;qHp+Aza+uE)ogY58TgH{Djg=OYwSodSW{| zoP&ZxBQuvol9E$nTU#l&SS>X^XuRa)JQv8-Qub6>{)WoP^!4P`b>_e&d|)P2bYBk z)8O58Ky+%X&aaNow{6f^Fbs73Jt3qOq8NHBt>y`Eap&r+|H*}>b$NjlE&q0r1XjMa z%_}pthIN&9RjDlt6w2mmIh9$m-_;v(atpNQ=I1&VC)L}K-8*5|ke_Nrjm}5kW4RsX zO5?_Ade*-i-CQm~6FYqGNu^HX$$U54jlJ2B&dvOC=sy|DRh_bty!QFzla*fVs{qvC zmWYItSy%~p^4Xe#Xxs^OVQwCFwY1N|ptRQ4+~j6(R%|(=%A(!efnCo2ob`nQopD;4 zCZFz-SFf!VdKT`%iT7VrfY4(7`1h0=48k|!^*x}TA?XF9V>^C25@zI zaS97hR$erf_mON6a~BS;l6AY7NCt)`a_zJGOd)|I^-}oJX9QSSq{-MVo82arrYlX0 z3RO&JNW6`}QN(0K;~)*sJJ9T$)DS$8Lb$N|LTS3uC9SZ-)@p{Nwf0@5i#!V*RBml! zqaX$>IN)Rz15=-9S%gQud$?cYV$Cu;_fAUc@aRDNtQRi3ZC_aK2)nZn8V%?kD4P`SaJ0sKpFS>@@~r$CL0+ zVhuXp1SaGMyh6R|>kW0DZsyqax0JH0^u2d!O7PA~EOtj#m-d18?aIa~O%_sfbjnkv z6xdnXO|pY((8~IuR|eZoLm(V(=pfu;ZFkIu)Sqtnx2oxyyvX8F^-dFp(5 z?MUtgffwix$i}6>XdhF!OX5~m*iFs1hhlJe(NyXB;@7tfmZRi_DU1gROj25IPIYfw zjou{hOf^freOoLIk!F~k!xRt{G~5~yn67cE`LtJo+vkT!sDz!h92OhlQ>p8n?OECt z9oKVkX2H4(l}C2PJVU%@eQqkk&rbvI*4BE&>lIijPpyO#`XC0dGbb;&(FbQD;yIyZD=(#j9>j4bVV1uX)Jm|?y+|mj$&VeYN)nvs2*f8_ zqiektdZa7##t(I_^yERf^9k$?$1dAVz}2wvw3|=L`v* zlO6VFD_o({_h1ja1DD+sr?s&ygyOq*Or&X=^#(?xd7ONr?Y0p*bi7^d?c!vtmd!KA za#_^S_l84=b~V_5$ygU`$qTVX$y6C zMB1>Iys~kP5!qg&aRu|ecD99)&j?oDp9_Ms1~-=<^D++Oxfl6zkb>++;hXB$H=j5& zwY3+&T86KtiU!RF6dHzpWY%VmU-_bFx#90`B&bYPz~pIK{K_|=rw(zCorec%I3~v~ z#FlmA_|YLvD^;z^>>G2o5y-^Da=u)v!s8lNdkA&QUz_)lsNxWB*pi;>Uu=tqZF5}Z z=jLk8^s781RNjH_-3K}JjYWo`h>#VhAsM7l4Pp3ZTD?_PPT=6?PQlbH`tb2%Q_HgL z`}Z*(q*uCkuLrR$y6Ez9Dy$XM+|ZuWQNBHj$)@3Almxqs=(QObs-<@LqP-pbQObeO5S25Hw{Ra{&s z@XlQSR)(c?Wz2TOX<2PFZbzDv&KgsJMOY$Pmz2rL#nm^Qou8Yz6#St2$gbi!6X&$+ z6JF%jz&M74w>k=5KnLlnyf7r~phB!ACKYPd+Nh$T``cfLxVi?PytG4Q_flfi{^GzF zo&{skVE6g@HVw2|E9`U|eSCr|sbo~2S0A$)iB$Q?G@Y5B&vCA@&UBT16rKpm5OC2N zNN0#lUl1y?jEsx3Y6>RtM(BBXgm=7>FiXkcw$xHn$`W0BpU(nK0uwrX@!w%MW?AE@ zyoheJ2#N@a!_OZu)mBtf%W5U71Ah|q2}qiv^KS2L|U zrJL&QeaTsX-?~WovRZYb;^i|j%MH5(}QJP_%|avB(Tzo z?s93QzCOTNjYk+^L;6F9)%(lH2??ozq44Ka^d4)+>BFTO1iZ}xA0(y#)c@-TWCAaQ zFNY)6>Ne72S}qG(qVqF6)NYSh?i9&aFPs+LCsW6sY37}8j*aEWB>P}@6R|re>>G30 zo294kjR*_8JRxmjw+o?Ru6-LpH4>KQ4pbiXR@rj&QzAY0lXi#W2fZi$4{%6cqh6SU zFsl4FjS@3muFfSti4~rzK9yMxp2pV5wbgrx^6!bOn zyF>Ez+yt%Y&!3UEHaDGxN6}9n9MqPUDrk9J7+$pEdQj{)BEp-kY$wHR@a0EM?_FGM z`cw5omqg+`;@L1p3q@$5=myhj%Q3}6By)|2R-Ig}0<-$nubV^0mkc+u_ z%0dv1^Z}HO{FuqZ6&x}#5uP&psiU%vcfi&`sH2h>MFfFD_;s)0j0^{Pe3DxV0x2MB zIgoRza!8STH?lbPWd5+l zYk66ho|!qmX2Dfj>(k-uZ{NNRe;C`@u~4lr3M9{`oULbsA>0BJrM?N(AQIwzgJt_I*xZ8b^=$>Nh zb$8Ppud(ymuCl*E_4S9XO?A(zZxcuA55ZOX!XogMQsnzh5w?J&LB6!RZb@q8g!>^mb#=1cE3ZNxvd;|FP}qd>k_^N_Vo-)^u#+~*dXcZb(Be(E%0zbh&mwoB z?D_JOfqrgn4SPK(ciC&X^SBsrYNozhZ@DJC_^I6TvgKyBg-QFojqsS7OkZlMVo-!N=BmXxUO)m zoc?ROs}>)8=n*Qn&o=RsU3Y1Z#91G*=+qWUZ9ps-H~N5vPfF-glkv5zk4$h#56#% zxxqvR`7-epXKZY`pvv>QQPA+UTH)T=yRzNkL(Fd`d$I6hA(%*SAXdT@D>K9S3k;H# zbJ5em{wHouqmC82Nr@#HC843=3zZiBLcB1JVJ>n)+ya>Hzr&8e?_WA_?j z@*)trMC4%0a7N6W4=L3dvfzq-H#W1=Wlen&?wEIh4RcxYn5-Kpl{XgYWTTeh?r`Rm zEP1(#*-BV)52*iQ?>|LngnBV|AULP1n2J{I&llkE{C^^H&qS%BO|HgJ*^P zc-AbqhwMJ1Uzb2PJj6dymnZgXrJq_YrYAgQ@@UDb7mN?pO;QbTv9vewdM@GjlWAkC zo${lrj*cW6TG{g-@2RreIG4c0pA(mLb?de73ft=J-41HPsyh^sQX8qWsjSr00zPQX z-6uQ2y1bl%hqoCJO0(Le>PP#lJ%r4Xh|0;(vIe#l`S!4lwg!p{4n(Dg>%k!j6S|m+ zu`XoZfz$WCY@N!SF~NDbZ?GoxB)XTFCApb-#cVe>H(%h`4KU-$)@=AR8$v_B<@ei? z*+NpTWXLxXq07ZiSZQIq-xZ!Z^+Yqe?3B4j$0gCin2L^KGHw-tc03~TVm65YjLK^3 zt&~uhf-rS{l}Hq^=&a0->PtmUWuN4r>{Jrpn#qrYL_lm^Omf4v=M2J#!AA9D1$7lI zc)o|DHiz?xprD{!*4HV&6@IIulWBzOj!0RICBHlG=C<^_?Y^toQH!Ide1Yu}kja`9 zQL}M1E#&S)tvEko7~VXKeKkh!E=0OIkG{d!5h)QNU5)%Ju)>$ z^&SqHBY3JD0L;|XZSBX7YnqyZY67t&;CZogF}#r4k35XT#prpwtY$(W&d)kqB?Sc#Q8y0DkzUY$Nxgj{C9e zn-u+#&@Na))8h#mTj84z*RUE==eq zcT?di)Mm;bOiduaTNBP1u4DnvLZ9>>Gg3P>d$@V`+nkplkvjE z3ku9$AiQ!~g*76iOzoSW%H^JS9=z_Cl^QJ`nkZr?CnwJiT35lw15je?#;ht&S2s7q z`Fe+EV;8k}jKP6{tTD&fs%3hevg$@^-(UHon*BTz`$m%-=D-!tJheux_8^PrhNhe+??|Au3xb`O15-Dhyw-ZXjf8_scWAT z$r+H%P^N;5OKz<42lWyv2?`AR3$vhwddFF=xpSR51H)WtdwXAtnM$RJ675{1;QONs zlYIq+%2Cv;razdv)zxMVQph$Kp7Zl-Qc<@Xu6A*j+qRow;^4&p{HeC94Yf5vtVFZp z{Ip)El)H-F*};Z!yt2_7?W%f2M)pfmbL}%i^CAI5YD&=eS|k(|AFWT7joOth1*3V| zONC~X7|l}`Tx9=zGtwP!$XzarSJ};rPaIE{754B$*Aags%Q?yGkRIM4<)zd8Cr0X3 z?AjAWn%_DHhHp1#Ym(Sp?d@|oIBTGB1(Ws`Qcj7q(}{OeE)ZR^MXtiZeT?hjl@6a= zRgCM*7xr#$4OX(Uvd=(mlf{}1c_(gosBM-j@87>S++S!iicHPzYZH24-+!*kbC?BA zZ>T$|hJH}?nI3d)MK;|gitLSN{$>fj+i&t2nHK))gengDTKZkJ&F9*{-SLZ6tt|ho zFl|1q!}R3V2w$Db@C)^X9O%f}(;)2IO?6#r{mr+sAikG&;e#T6)JLd2Nij4x+cCN;`rS%HBUBFh zW(aP?>L>NgjA(7mz-%`|JBf>hnR#^QiQVJN1o|Mh?i0AIc~#yM+WXM!=_*JFAd761 z#tgv|N@7c4X{h>PFCZG!PrVH#nmvS)Da#P)Ovyodr;&u(b0tXc9%!YZ_ubo@E|aRD zEZxCUeZjv!{jx7%J;~O)q59$iD`6Tgw`vr=jW^w_pPf!!HpkXcd2za%V$d1<3G8wj znV{|R9$4EMXmX?L${cyRuOpt-c9WtmdTazT&*EU;AA`K)LZwm=zvt~~^qS{EYer@! zh%|+wkBOdM)G<+?f1%RB%`M;A#Z5{_#4G*%@W#?-D&C+ZV%?xiV7YCd9&kqWoJW$& zN=?6Or{EZQmmfVG>LwwdQcXT_kw5>OwyS3~LNLcOq1ehU^L?JbYoWyHDtwEHtaW$= zzMSl>#*IL?k+?%<&Dz`FpIjO!)9+qu^TSF$^r;uA0IMFDf7z4Q)B94W*`Ne;^zYI`P|TO@_ndgl8Oth#R$U2 zbZ)6d06Odf)omCg*RC#4^>);_x~KP;M|0rh9UiOewph|wrDNZ~`qt3}XR2$9RBHm+*K4o(fUd%XN)Td4=-Y=5lv<eHK0c%d7FEuZ`yv$ zAn{p!gp|QqkkAK+X(L<`KX6VGT-~l5*gq}JXWI=_x=5Sz1LE8e{Ap^jTHS|VdLKhP z%Wx=zM$s###|G%6JT@O9AdKq2B-n5WD(UHNgK`8!X5bUh!rB~9dO5*1?(z``|1P8I zx|mE@+1h4SK;A4#tGhP2wcx-*1&^z=Ev}LRYl9Si%**)3ImS`=Sx;}=MRe@b5^ru) z+Q<{c0KdfA&NTA3qJqgEsPoP94b?rucL>i>S80>J@NhXCg8`xVzTTJX8-p#+jR!O$ zlV@DFRqHjOWBvV-af?^;EWLa4v&Xy|rD9D5dwUC8>tV7?cJQ6ozt;HQo%E2*2Pqo~Z$RfV#$ zvRsu*fyIxMloT6&tI78GfNegqh~|y>$ka65df4uWAZsBK1><_#eCtXZtmiqi*ykH} zE9gk85YDck;=%wm^2J3TiR8$$2fRdB;JZ)j>7hBvuVb+6S{6i8RlLR}O# ziTZZSEAkRdC_rPQqXm7D#TxX(tDh2;H`88HQOVHZPERMn6C;LpFi19@Hc}nrSqceQ z0M3mUjl@634K3eWx`#Xi1qIt2Kjx;#i|!5fxReSQUGfYLEgi|EOioOsaIr*(4=@|O z;X&%6hti&Z&3#i;v}?CFNAvA_G3SkR!U^L%Gf5whwqB5a_||)?TyoW0P6tJs!{BOu zUflTnZ0jC&cWEl*OZbh*u7CzloxvqU<3%MxR&B2yq|o3l&0Twe7No4#TTWM^K=tw(XlZ+nsIFK03;iXp>InE~{ z{cF>%QA|E4og)3?tQP+D6JuF&YUO?xjn2PkS0?_s&e{r1@Ncv7%RN@Z+fGG>6syr1 z`cXg;_;X$d)zH7m2Uuea_1kgCHJ<*y9>?7=vkupSJ$>RyLp{ZB!x-?T+w>-3Re!R< z`f=jJ==k@u$W|snHki~ci%B#8*w@fbaO_`q^@B#o>Cs;o!@ElYo+wZHhX%J~=U?`# z5oliOx99t?4DDY-ISPO7=$F;|J4-6N&=7Q$odL_c^j=RP~`x$do<9UJp>p=K?l5kx<bjk0-_*;7VLr?(D`VT* z-Hr42NBdS-7&|he_)8SJymTdc`ZThqN6LH=0+_lDzbz36J2zBUQ1lS zxm)O4t{PexGVZQ7)~^=tnjb%T(sOW7TD5_W2Xz7TruAv#jPaY6<6M@W$(CD(8#0WY z4~N(*KJ30XJU8rI1JH- zc7_mgt{TH>_s(yvn@-|M1e_JLGveZCfWSL0Huf=$jL&Ati$v(t`OS}qS^-{vV2Vl+ zqtA?vb5>ehCsHoX&XP7ZrE6FD|hTh3p@ z*6Q|~uQ~)Ie8s^#-h373AEX<84xuck4PuKdrV5oBrkC2d%duKlP++%nZ2^V z&vNhHy-PmSSR*Z;L83o2%;)oSXTZ75M$^aZP_4KB2AJw<+D#AHA(88ltr42(a>J0F zg(h{SA~hO7!?~Opbl-!l?Cmi>dGh4h4$-q`(ap_5u**8vlkd-IXiR^YbOt|(PD^7d zP%fERH(Fj^wp(ty2P7Pxq(ES(zWUt}hp*co(Gpv~j~VTZdk1wfFj&jO864CKc3@ao zSV%_l&DF-}Kt)A0!82z5ME=;^%F1eDC%v&z0OuMN4b2RWtCf+Q{LYtY$xK!!@U=OhOzk*SJ(RWd8fs={ZAYGuF6Gq#Cx@z z4YlReM(kb+jL#f=6zHJc-QAZzE0Z>mq+1Sv9B4G5kCGc&Qc_Zkh?iX~&IQZv`Un3E zf$&A9a;u%ni_3FKAa9G=YFRRuwWt)Xv8~o}MuQoi`+ZQn#H2cgr=JCD)L!~;AQ6ds z-5l2A&U(^f_*%lR2Co_abZjJQzH5(h-zuq@Kc}z%XZiAsJq7v`NCkQ<- zwX_`1R8Un-(r9#k2X<4~FkbBnvl|pVGs(p0tFKI~xCksH`y`L*ZDwZ1VPn7E`viup zR;K4S=XrN?`D_f7Je@)GFJo2-D(&jsOVP)R1;&o33gf}v!_{uir?H8NU;Anzry-Ze zrm!*5AvEc>NLYpYmE&}SQwj5|m>0$s#ZzC<0KU9H*0cb|b^jQ7TX``$nX`!F?o4i9 zD;@`*=WV0M;M|j@%yD8KrwYe7$2M@rO1 zl^(>~`2_@+vzagwZ*Oh6wA|vxyDz&Kpi#c?-62KwGNK6eakmL5U0Be9Jx;FM<&XbF zDdM|?%kF8U|2t}d3CotV-IXEW6b3UCCNXJgMGkIORatrR_V$%%E+F!Eb41f3(952_ zzR@o*6)JyO3a^OAG!ARk50#wlY+k@!a$AG z*;rk7k4d-Fy8S-zqU(ffB~M4!8)+k>?*_((lFrUwoq?%QUcMwY{-dO=ZIZpCW8c(N zVpYw}r<(%#-o@K>a+QcwV?8~w`g*tA=5MM$0T8REM%&*%pksbsQ;Aufie3uy(L(~W zT_$!RAxc0q{3Uqez?ep6Ct2FtsaMw5=~E_);ycb&Ffk5lPH#or^($iImERgG*Bs+w zo2su0VsKo&Nj#(GrV75V=;+_k`C8gUvh+O3vGDu%n2L@2 zfTnq~v=sRZgQJ)ccquk3ut0*y%4%KN-e#zBzyU&{*OmxxZ&7n=yJ|q2?18f0)S2FG zew92tJe;^~{Qh0(mp<)*cJqi=zLpm^$2dn)&M~i}<5lwNyu@r{eZAKG`z3D^Oo2Rg zfjs<&hVUS%`7&p_M%aMF`!^|9X6^JrQZh0pKlkThSec$zOGa&7T@PS65aFLlnVQyp zP#TwnKvHDnbF=dg^p70`UNvU<$357zHP1Jk}<9GRGCMSP3V#m?RsDzul9 zNwq@U-ilfx#2^nWElt7t4p-F|{x}8e7a4a7(J+$E@vyk`NI+uwHT>X)KiZGO4Oahw z4tcG-a%kCpd0p&u-J!~Be_jhvYIx8CZaTzxK|;?zkXpIN{7cp5PeDXbBNGs^&jheO zO=F$n9H_C~Rh+KSZ#sdx;3<4FXD7Xl)8lo#Y}BByr_CRD(tFXy@Q9d{emLskv&r}ihdtV-FFh`AUVC5{m4KhfHkqUKz6(NgYERpbfs4+i@lN_$veun+M zusAOH@{OsLDWN=zyt`&1(ZRq|V)BG%;4C4x<>*GYV_yyCmvQCWa0gC@k%9}zpz{GentBWfa9ImAMX)&c^&s4{VB+<_~3xG z2L_9E+n=Z8cTD73G@1FdNQR@Q#og`Lz$?V7lSaNdh&U==%W^+UzWr1{w$GphH}?dj zdMZF=9+{svN2@@o-W?<)u5^);%M$<;eV{GCQYL$Pp8!6U&fJTc#(ZTuOMtf$!6W}) zj1Jz&JqoWiY3Fj1`S2k}?uAn#Vq>C+*x=;5VRQ>ecdBy5^S(y(rzxRfVdgsIgs`cF z0UsI$3X zlB=mB8tv%r+$;@GZu($HV zHxDDH8?EA=({#+UgT`hTOYkc`fiq`n2e2!-N)iCvRJ2RpT|Y*nNr_e~o$L}}tiyiT zR&v%ygIHL)e|H1uUbF~sq~V7TO2tW%`1moSqI7pDo_W~>(jW})^z-wlnArE7?}CZY ziU99L2~7bDMMTb@p$mGAdH;TFULFCj=WVosLEc->MXyxe5bR7~VF^dN{Ca(@;d0ZIn5?ed6@@OvGyDG$u4@|%bUa>{eteUdsEo;2C{pM zj;haE=M^Tot0)kFC<&RwxAFotrvs~V&8@}&@9wGJa-8T>S-I*uRx?Oxv=^o(V zY`KXHco&kRdZb^DY~3zbHw(C0T882B$afFOZJRjnJ+?8Q&R9dkzL`I_}L; z$qSzFlD6!4u4-CBLWx%UYmFjYgl!&T5mpR!&$40IE8p{)F*hu)(3OLcURgW?1w-b4 zEpwR^Z*QB+O;^o=LPCaHM-K6g*ERva;b@H4Ww**Hr~bQKbo3*G&ZAGe3VU4XWMuWR zhNf247PGZVT*aF7^g)Lc%GU6$tt`>>IBA4IAK-Slb}DLypQOBc{RaASv`a;)T0mF= zMesauk_8-trBPPG9RqK^MZ)>HL|yJ#oP>`TpRhYu{cfUIgSMdm_PmyZTiWLxRH)5- zAI>0NtN7lr=`FBDBDN8-B*<&KQm9pzbul{0O|fp&=61YkYKhSA9^7PCOxDH#6{%Hy zNI*ghwuiwahah<{UAqEkK&wsnqQWV4n21918U;jvMg1U)O}I_ z-qDZ|6~RyrL&yrJThaEckpKezTP>?R0K;->RtRr&(yNCp@;$$IPx(23cgHjKaCu^x zUOI`^;7)&@eA_3>uN@6Yr+qG?3m88$cw8oA!f{PbF_CY1njaq1ZHQ(7v7|Dt8u%Y9+`x|Qr7JP?siNbUN$WsF6fe!ylnJPB*k_C`2z>v zqkc@1lCWTmNzTRE6@MK?BiHZF&aO~EKVWWef994`t^8rq%>9cBcxb-LJtl{i?rrLY z028Mw&=6>JDO(jk?bc7A)u)tTXVIdvlgXv?vHT)nbv_dbBh2|WmA=K?lj$u^8B96^ z-?0vBHgm`)kWy|sw#tkg2mz#0Ur!ADTv$1CI`pfh7bA}y39`t=1#hxx5Lb7{(<+3G z-+62j$I`h39uOHM=0vRy!KM2v&vAwqI+~ zY@u50>;?wCa^gnwBA`qyEwjgY6BJzO>gFQ#&UOpO^KA2d<@T z*JIg-HTTbDC(rBH-W%xHC`>ke@#rlwn~X$ceuWr1q>=F0Y22R4Yejlq9wLrr)B|$z zir-BXsnHh1vplr6wicAi(o%>>n$z_P3A!hz2KLc#La+grmybBOuhXW6mC8*gb4duU8wN;w>3>Ip@LDXRPZRW&&O2W@hpT)l2QY zNPMtJX5jE^xY4btZFAu#vjyLcpl=H*nL$|#Mt|%~Gg(oHDxVX4()!|DU(spfBU-%0BgL>74 ztM|L$t`>=oRzs}iyjQhmNv_IaX=pL}jO6ae;H$MBI zC+e{sZN<<&JmTuEBkIO^fIV-YDzDaEx3|3=(wcGdq@EP|MIwdTCbSF;aA6U~$4rR~ zz>MlXKQ|3OCN`1$;ZWg4Un85oz4cF$bF0uu9r7wro@U0G-=h5C61e0JWt9l3R6OJTmb(i!p}W#SfYeGAXqg+}?naU{m37VsSyuf$;F8d=A$xFUt) zAI+aD=_Nh2dJ>^C3B@Sc>8C5Ce}H*^q#=|^J(|H>i7}2;eWGumh&Z>TMZ5Rq_u~O= zNvBDMb0MKivhaaAF}9c!pAwh>N|^#_l)1Q#N{LE%L`cI{Hwtoog8u+~Yxx@yL$WB; zFzZ44_|g^^`6z@go>rH)%K|Faig5M>D56n@gQqo#2r_o^QVo48(g!4GGw`Vd%RP=- zonV@rd-oF7kCU+M&JQqM4kxd2^QuLusM-w?a0fM?P?CThE|LxXYyc=)<+%g302G(g zHqWFxo9A+;XaGeBzGZl*OK2Kr14Pch$%rC(BP!0%J)d?OZtqkf3;J4KuK0k2hXPP- zi>=PDv#SAB`YkY78tr}3fF6hrZFU6VA073vELJ`t)QqDis&O|Cjo}@Uh!P9)Lf#_* zpP~AkbgQV(EplgGja;{4qW4wXjI_?IOl?Z4re`ql_h;UxOM}N(Zvn$m;Q6Jqw4_3& z+zVEu)*y3QFa{m%+?KJ8i6kA3s5g>~51k#*9s{>-N$~xF#Usw`fIp4oi z%=h_nJ!j2lf){&EEd|6vcVBlsZ%XcRPdtC=g8K(4_t4OK0ic^~LdDFbhTcl5InO7V$onu0?RA=qJU$Aa@WNv0w)+|@6tFfr6JH6=U5)_KJr4%>b8p%C6XvghSZa#{Om`ne3B=t)bBg*kpSzP88=X&$% zm9K$;0W|mtgVoH+ib5fw>C!371AmhX#$saBaK<>cpY7A-sNOffPjuWf%^ z`?A6g5W+QD4rf0wkw`z?{m86zvi~_@tr;bHkXw*1!N=F|OPujBog$Ymx7jFiL!l@hsOQ#|(`}v-8@mgbH=d%RE}q z>i}3^^hTm@J<0TA254;o;c3x7XV93aG(Wzl%O51%91o%~vhh-{qH5o^@q3VRB*6aldF8Vct(VJcuiun)9eIJ9!%Lp_A$vK zF?VrP7_pM{*RA}50`uI$!nR+CmZg@(Ko~$Vl)H@bsWuQ;re{sl5l@uF%Mwo}H`9IS zW~?;?1CdAoWFwq3rN5R>8Q{V=BSTmD+e4r1*BMtZYRA*n;%fm~jC~3lE-!lc>`3|B zQKzw<NJvhu!OtjH^^$(RoA`F*27f zKy9X)|1!bMCz-eT-FY;0+fdQHDP*+ZR&?@d3E}|}>Ta{7doMUCrFt;SUB?v#y-`sw zr7bLCcNVHX0((hwOG>moE&yPwO=l9nzpF~xa4`I2f_kI12joqbsv`}%6OPx_WTTr2 z{{Aco8+TG435l$*rOR!9e}hg?5ZD_r^?VZc91AHey4lQo3!-n6zho=+_`a}an0PD!nF)vqUS}2 z*S|Be^VdP08J`@KKAPNxF7a6!TO zD%hZQZ9kXOGj51R0Q8iU*g@lS^Yi~=SN*lji>cazYwOAjv4D;UTSVFh@ls8P;tJn< zyW%89Zj~9kl9CCH5dgDwY5uT7l=s)>D{Hx4;Cw6oW?ToNV;7f!6k|sgsZVU7gsR)H z;q8Wdp>{=DH#wGqEIHYyr*#C&$+;Inhmz1I-21pnQ?-wPD56-qr5K6AJ`s>D zqmz@(+}9_7crqs|OLQA)ePhG35Hw_Mcil1l8Xwg5WOZPGnTRbdu_2|QP$P+j-^n71 z)Clj1soZG-O9B+@?l4%RPL0al9i@6_Q>PhO1bS;~VHSrXAqS1nKCepU)6Q&thH4gR z`Cdbf`JQqJ=PX*4Z_ErW8{Oa-^6jyUO;VX_fD~A0R49I-rtWB;*F=%$VavKj z5-KSyjtNN!$@A252m|&pnU-#*GZ8x+ao5z=fEnXKc%OxV-G#lA&8H1V>hd0MY&zNL z*|bW`;7mQ~WIy0WKj)=i7MSIPD6^6h5Dsk93%o(#cRcA{QOyx7&LHc zZyzjP1i}5@F#IMwoOwHL4dZz5D;S(fnH#Q&UG=*{<+=IeCAH*tU` zGkttD{~!HNz?iXkBvETM`u-w4W**Gke0zP-<60U}aH7dJ010q&dwbMTA`(nZ z{d)G=V-y~gXWdji&cjr@2rMOXi$8uh^&UeDwac@svUyK^x zF1Q+KtIYUSI$*0rO*=9qCVu=d0d)a;Sz6znpZwUIV5JwyD0lCs1!IO+r8hl9#>2SP z8S!dm;KfC@gf8?CblG`hz`}npr4BD7FcX^3dd@Xyjdc6`OL=jCBHB850`xA>%8QKR zQDP7jeKx-cFN#i?6zWYS6_uQ%%CAkY!ds&W8R^0}SMM|OOYrL#dan}gy5G3wenJJC>H-{Mr9Oo4T^3rY#=Oe#Ln4-n{Z5m!$ft)|cY(F{7F62%K2Fhs0E8rmNKmCK zDl(FSo}PX}*-Cc1;W(SRXfjvFIV_t%A7oONQUbzrukC#FUznkum=$CItQbM%vJW?* zP)Wc7i&^hWkk-&hJ=qBm&%-MBQyAjqh(4FZ~quyOdv)i@k5setJ4=z z0@i<7z<*vhGK^g6=8psZ_XQn+BtGZ8Me$nGhO3WQ|IL+fW9E?jkHtn=>+IVJ|DD?x zKW{^T@xse&Lnr*hIKhMo9~3j9{WjSi);W6x{~;Yf?`xW`;x((240V|Qe4Xs6f$S*p z2g3UQcty%Ea$<6Eh5iQ2@6V|S+`~Badzw3yf4xQI@7H=%f~=x!_48q!*6;t&5KNIt zA|aaGlYegef2_jAqIk_|vkDLSzn+UJR2@yrqPp%6jP&WY3!WwNs}0IKN*uqSpUA?H51Wf_~yzi;4Zs zFaNxB<8S(^<)%aHBBn&h^#3sS)^Sm8Z`Ah?0!oXDbc0GsgET0JG$*;z9{_kVn$aGB?3t#VUl(C^O!+lmhZ`+w=ne|jmgci_RP zB_f(}+5YuCP{5Tj9AOC1v84s4fASNaTK^@v`y}NR1YShWe)6DGb`Y>Dz z4h~g3UQTb>;IbAFz{#ek8>}y#qwm~RkL)WZ#v>xCIIc`B;j4Vrc+wuK0`&DE+Zc5> zgrR{MDm(h*A@0X?!W6?>AINFNgZgJTKhgdoXKc?HD-MoV{LOQwk2H_FEI{_gi-n?CPvt4hm2TIXhax< z-^#|O%>C25T{olv(d@!vWrmoqfr)1{98^;5jNRqOmW?D0_AeTbr!`eVH))xf)rN-U zsVI2IU5UxAuH2y)ySss0Z7x~WSrW#^>)90*>ZvpqQc@$8ZBBPCJ38f8 zdYNX@R^$>$yu9Fsf2!ocKS?s7TR&y;$SauMe?I;}tAgkHfaHa>ocB@i20k}5BRJV@ z80HTh?EHSPd#yP2NxRTMEvUT;9YzQOir3P>{K6=Oi;aWBSY+4w*KXa}8QxNtF?Qu9 z^JqF4(M6Yq@^P~!auL8ZJkffc)Ni%DZJyJ6sn`1U;$)IAxuVi3#ONSRz-&Wmc-hbe zzrVgt^!S{kYfwDfIy*z- z#e0J6@=9gngvspuOi{o%prjj+hQDwHXZ>!d7{{j_<>4WQ07i{ST#S^jq%xj(lsyI@ zgj1+7!=r4BY`s4M0Ap;T*`v*3Z95nLCuNwLIoP#;oDpt?i-CLao zQdgGrI)%@-+1$Dn#&st=TDx4g`agdb(sk5*iO_p_iD2qLBbc}nr*p0~yj&-dXfabS zrI2t%^h+y;LZKiC^W6YyE75nzIa?#iZlQebo+v8vtbTU6p~3XvY)-E)+i0zGe=UF{ zj3)K891MnAg3Wlca%#akMuUQeHiGKQ8L&Oxpbo-qR421d^42yi*`*mODw7ixBs43+ zf9d0vv778>O>UDSTdD)cdsa-~4mO8I^PxA7S6B!Rtp8!*QkJKSL|=k=C{R(b`;#iZ zFFPFgnJ6{`-b~O#$Re3~J9B+;@z;@Rhvpf$1Fo~&?=UQ ziHgPoFRyAz*5uOGR%T0zG_Pyw=5(E?RB9usMI1Z7qV7 zq-^gm2#thrWz7NEg7Nf3^nOjh`wMt@_(O6n8=D}t8o5u9FdWjnq%bTK>RmE?Q%<9{ zHy!w*mf!C%d#;DUeSr+PcJxTZCUaMH$VK;K}zJtibpP}veT(VaQjA1}NA`Or)?d;GdvKPlxSKlY1BjUFb2_fdD z2g94lF%1{d_XX>eAdICz*FT2gM;L&^>22H*(L8tf^PzU|RfPDpvJ5t~8s z5wWncLfANgyD-(7f{sHtN7lun2@&~pZHQ6#dVp08?=y2-nE_+hLl#S3;F3sUnf#cU zyHr#ay6WP81*j&<7neD)0pSZ+kRMo=m7)@h2*9)Ha@k29A)O+yXatwNMkFGOXKTc} z!*X3P$3#Kgva-AHb>8N$&!rP`b`l~{#l?_AO6ptCb|!93$;;acCV9qZrD~nsy-~}{ z?88-ey24MSKo}P2d4Q)P6%$L>IZDNPT1UFle1uOx>cF<;|u1_30fPj)1jX@z9%(VWd%K2D#^*r4_1j zWet}yv`WAsp_iK&cjvy7y?WL~&!Wjz!rku+Tl6$iN&l&ycVIX2&6ENL49nip*SY>1 z!^YX>^B&&^p=9X`cG6oqUT+O)nuKB8W|h!7$q1{0c`G6G1O29YsWILpkY6bncG` z-PkCN)b2eAjPy#!UfU%2;6B89xInS&@`|IPyR%>k|FBacFlMCs!QRPHi%NNTm-9edWg*;kEjTFo^95^ zudQtj>p3bbuK_6>8wH}}q$6RQRmtU@oR=Ix`vt|F{DBwkQAgvaeM)P>30E{mWMTl?z@FgcV658e!Xtml6t*~MzxK**7?Z? zq!8Z(vz5NP361ATQBhGw0^ZBG&|8S_K3-r{O!mdw=!zNaHjNEh9vA^pK4KOMs)2>GXZZMT zr(zW_ZJ6lKv2vaYl5v$gxroLh`96LV^j163;||@h5O3;C3t7?ENMaIt_vJXGq>cuF z0Ho{C{7x>Em1`k`%6Cl-%tp-2>^X3^EXsQQJ#pSjXcibn>_Zil$R6oPSGLl2A>_5CV-R_ z78e&qnqt!yXp8)sne9A8)qb+4sklc0juZ_dQ;<_oAPzj%S%AZXgk)YH!HYb__vUhRsckPoxLQUo zB%E?j2>;F9ld*-Yh9Y?Y@gofFh-r3@%NqHaqYksaA!7UcI4|o#xfhLIx#e zpa*W1cgssd!w;s@wHj9!iJFnQ*WW{zLSe(fcv0dJ5DpiWPPnQO^AB(`pfqT1zT3Jq zn3^eax71w*Q?F9X#K*hz>8_W}gTCB2oOz+Irg0|~4z{a}TKcX&!FCy;%M;k7lNUEgAN#zP*3-*Y ztF{yjA>yXal}e7FRV;q)=GK6Qj&3wyfOIUHhH@SqogO%1;Xh^@hmn?%A;h3wYdbtT zGGf@~jiWE^(zJ#mGAD(fl9NfmfwM|BJV4YV zi4(3<5+f3cE-s01bg_5cqO1<80#$3JC8XBqX8;Xw`z9WZwI&PpeU>d=cK@dCM6FN3 z+3HHv{&fNA&soh8Qty!%ZIKP}a~9snmbEbKx~O*i`%rp|t=T)oAW9%IQGs$-7X3KD5fyH`%{M?fajTJ2`C z7bKz`sT1PaGM3H1b4Nq#T9V;2g3j|{7%c`+k`((IWZ|LrdZG`%XN-^aCb#I-){W~U z`QCgcD;o~7C9~lmPRk!_;kKc=Z{Trku#fAphr7>zy>cD3F;-%NWr%cD9e#FjanRo# z&tgz$z>n|VHvc(b2}Y{QO>th&*-~t}@LS^%IebfsJx;Jad~7h>mA3G z%Qw4mYKSkSKV3K=D?eXsXlQ8hV>@vqm@db^5lPZNB^?0Qr_~ymO@sYE;hho_5II=k z!_d{s%E{@9p;uiD7bUJSQjKVOIrRl6R8xFIi%mK3E1Kx1-#hqO2-SH0+XwR;5 zVypHP-iLgOet}48_0@FwEw6bMKLK-@>!n0u;==8AYB$b?PX)^S=F6NZ<)vQcJ$avI zxy%Q*^(H2}H++_~JexdR(FId4X&8;L9&k|$ZL7vIiZRV6aIt1K)M=J^$XG(ZEN$#B za7cCVH$hYCEq4o@)N)E1)MRO{p-?6+y9%KM?w##g6c#rV9i5;ge$5BD{c2$jn8eYF z8cwPvLFw%6An9I##mZ$)ooU%~$h0aC4-c+1$9flMN8?nVpHvwPw{F|SP?%FCl1GA{ zg#h~CFDg+3e5h6Tw>XB+&DQT~>^T4864iWujPymFz-px#%tbpusyyoYyg+kEuc4pk z(hla*)ip5afZEY6(Q3NO@m-(wKmH&cgi*>lSQVVWL{>V(S~uL|r9X`J^nj_6gqv!`twi}L{_F}u5#T-J+$_2=7la&mI}?pUjlpKhmo zEl}*nZQQ-_GjFtAV^9@H@C3aM*|UvR693_d(rwR-&o;<%d9QHr@yRdU5MXPvV3n5_ zSy7R1Wk~R?G0%R}yajCHdpYOxqwf#rWwP*&++?nim3h>cIg^tkifN2&m_?IGN8oS8 z+2u00qL<{GtVMxyhjsafmqI;RPU;%(O*LZjk9_rq9gDffPS7#Lt?VK<`R$aePHw$e zGJfTAc!>Gpm3&>j-SYdW5msZX^*W*$!`C+-Zg=?98P1vG2ZREan?M|CAsdeW02Y#G zlGc;^Ow*|pyu42y$!+xY__K?`nIn?x;|AtT`grp71+5kg3IgB%4C~&r9|)SFcGfxp z)@kCu)@8e|t9gNmlT!vz&i1Dm4h_PO6U<2%6mB3RccsPelCM_koKv6mP`E5r0n>wd zwVu7UP!f{YcAZ7QX1zg>RFbmGn|nCHik4pYR%DW-Kldhe%+8Jh7XaZ{I5u`|Pi;Zn zNe*hrQwIX@a>*njPXhLZ?$$)bZEb4Y!NI}hEZfwJd6KJi@J95?=jru=#|0*cc8)Ho zrH=GC8=^6nuP!H{;|T@Le+lTr@EP*=r*6;=j^yxGW!b&PGD1>ZGkOTj?POc}6hL4W z6&1<)s8u`1X^t9PfW}hZ+bf1#Wz@Ehr~6_c;Na*u>cboa9X{P(T2Cht$ra+`jyP2d zMS`97gV+KR1vddIN2M0JIJTo67L?5vfsgy}#6szjiS@8;828xFA>x@&yF)jL$2OS2 z((rvtnW%eaU(`A5EKpD;zlcdPNj0gs_}o=D?&w7VYCD%P8`*9T+hLzq+@TqLGMf4QBhH;_;xUKF-35TH?!A@1CJ+EA{}_HH)w6^ z^e5^oS`UwMB*Bh8MrODTu=G$A(lpTFlO^BvqCvP&E^llTpEg~e<%0G1N^>dk`mDs_ z+i{bV%vjY|u6EG@3{_yVP}NNK|9${~I?Jxy zRDfOMj14x3`iT&%m`C$pd`tm91}jfc04Wqi##nI-m%5_8g$5ZLPcsO4onO}0)g6Ui zMK+TnM1D~`Zs$9AFyW>-nh2BThozrVPd>q1kf)2q9RK|EqcjVFuR&UiAFJ8 zDsZ5WH=1QOBD=fuS#M3)fkc0qhMmLUr+i>9oSDv5<(D(-<@Z_MsVnf1dEyMsc7TX8 zQnQxPaC0dH2`pf!XR}ETeH*1OQg5)Xt(NOrPhb;%Kt(O2{n_V;GBjJ8>Z{~F^o>xy z(e^;|!06I=1QuS-vt;DnFK`6jPgy?nmmVT2r-Wy*dFxja9+d4p@zAt*a|=Bp8}E(t z$p=VNT@@cz$Wk%@^n#Pho1k~2bzaXzGBEqXlDRodu;9h@U-V?bjr%PUqQI*+s$^6Z zPgj~X6e^dgm6i@sJ$WL;Zl*#D-Vlc%H<&*Z$0{m=V?-K%%TK<|Ps_%0d;41Aojkh= zfVbhj`qQux;wh{nA7lyuH>1VR5)GceeCcbd)TF|0re@OSn*Kz;g+384&=L*4yZS31 zbVEM3uX}A6*ZiBYB)5Z|y~!?Kg;&@b7dK8UA6E}Wn3;E)n}kG^xstOl7rJ*>^((Fr z2iFjM$wk6dTFbu-8jKsG#ZhW3A%f?b7PInq{ug0=NG;F8kAWzoqIq2~$5 zNm0isd}W$GqgyRwDs|^eBhl7iDm>cUlTsm0NkuJpKHoP30I`k7LoT?wpDya7zM+7L z(m-m^&hRL2gO-y+-kFQ%T3xWy#xlQ&Fgls;?dY+p=W@2yo9z6^NB&r7_LZMXot+MJ zKZ3KKwM{9YRP*AS3cO22VZoDPck2OA+tOBvZ{W(vnvlQ;Icl>8iu)#+oS1F+vN;Xd z!2&AH z5>uNj0exbC&HGpO}W zKNbs-4vem>lqxz=kX1Hoh%m=pekdpi2ekZrWpgpHo3)1wfH4iswXNO3Ht-1Whf*(D zc2K$A;OS&w&@jBsT*jOU!eWUTuQqzeHLAFFW5NN0F#IGWWz-je8!1k{BpI}o(?L^1`cw0U?-UMv)+XMs!-A&6v>@sq45r@ae zFN}=V&Yxv+Sj@PN-SD(*tu8AQ7m=V@-d<*)Rb1}wBT_wlii3yE@Y|8`HbHE-h1t3X zXt=g^N2^6M*zW{nTU~k<(QsHtSRQ~xlxF>IsnNN%P4Mw#W$y|t#8YGYsZVipk7}N@4g7nxD#C#{4QXdwFW%}uHm>QnhIT;N%eG6FK zCW(SpGF%cZkPB6~54bAR!KICiP|_~wR!q6|YX#Nen6?Hf_QDUwV+nmu0-Edt9%#aEQ=*AK^*-l{TkKV`>=QP!hseQqyT z$QLjt^Gvt^Nk=9RPyKeOgPb;n9Y09u6FFf)KHX+Q^unTpKB%5PKfXIYnyESrkuiyN zFR2a;b3%t)u2#tJSL|F30Y^m~8ju4d$|k~YdN~^nKU)c~?cAyux&_eTuiq6od3#^M ztP_1BOPU=a&5IzE3G$Q-qm4Hd82|!j@d3p&$j$k~Og&oKNy0Ed&gA>D0@WRS;Xa=w zrr~xc|1SwlVBGP;K%v`4uig`^1WDv5VsmrPIA*F=>VSkTM_g}su70Km#v~XygucFx7IGN$3=0BH=tlB1l}E$}%$<(2 zNd7aN@kX~gn2kbkl^>eP9|7o1SD`$6UvNgt{)Pas#sULHH9GhDRazTnjMpW#mzP%r z$ZLCLs(wZN+ulIX0;K?moh|lDliEjMGy0cu-_c6eq5Th!!5?;nj5CLBJ;i^>$3TbH zta&xisxWz2vi=)Y^AGtJJ}%Krr>ysn7MKG}rhBRur=c6amFa&--a6Z*v~_=a1XLg> zAHF&H#D^9K{PGR_saAt9cKMGm_NPB2Vo%cUL*z;GKdc7-_>!iF2RkECW*myraK9hM zJx>u&(>f!pj*E@=zrGdtZOr9|ouqVm&Zkb6;w^Yhc*(6LHQh`LTz5iADu@S#P6thL z7fog_vyXl}kE;j-?1eEa9#_KPhX0UarJiYV^-^Tkr4yzT?yY@4SDnQ=>EPUmm&PEA z0V?UkM~@=jzkg(8Y#adyzo6U(Z~(BxBqgJhk_Z9a>Z8Vr+I1CE2z7C@>1JiGKNC*ZHZX@&Z9*BvHM@G{suJISL7Z2Bl<&=~jz=$)lvShuzz4#pf zT>Ui-%bN$}JVEr8zCDB}Qc=_G6-eFj)&R_`T7&Z|;6r40hPWM1LU|zEB&dlm**!x=&DMH4Gj&}s{>?ijn&mk$6J#$*ZtQA z*BvC6gCt_EuJzmC%TKOjVq)&aCnb%HLA=HJul7QZ*a{SieuBg=`mfbW%gT;cF2Mh+ zLyFM<6Pcs5|4KuH0S*qXRJZdsIur(Ft~4DdC*UxTT3t2lJr>mO2RWriBsfxC)FZ&P zDJ?RatX!)Ec_pY?JdBz$|qSV*=zAM-1^ca2}xNcGwFc2CB2C0o}N-*in&CMM> zZ8`b8&w%I~_Hkilg{ID7Cq}P3#^_zz;h`-I-Y|-mkWcFi!7;vOWoLh3XIF7}bkqqb zIJ(0*lCV{T-{xSs7oSI{ZJ@{cG2**lHwmCqQ863Mnsu3?M3J%}dnMHnq_mImKSJ@% z=*?^JnL~Ta1*W78nhVG+ae!C^T4zSlh)76C&^Jj7knwl{%`GB2I=dfX9RW}nb^_1^ zNf2#zU3w5bWC&1N$muu|z1%*cp_Q~=Ra8{qv;Mwgx1CYilK35@+=2I}WA>tVcB=dm zpo@nSo(KyIkJ6gQ#K%A6w%;5mB+}h<-EoQe!eHys3=N9&g6#!vi<5CE}mG&)7r0B0Osrc+!6h_rO^@nmmvih zRcwuohbjroTRnDCcz;Y8ogIp5COMkUB%WM|eR%Ep!X%gVg;KOf|sFKlcSoa<=P?Fi-c7afa^ zV#Wl_vwcH8|IYU7V#QV#&;7uP+MT;>?ntaDDzo%??syweRU!aVsOZQ?yC0a5@p(Sc z&v2N2OKXXbR}n(FN;_qN=k7pRUtJw2=@$Sjsf>85tu{n zUpSvX*VY_C`F(XPlbENlt@No@P7?agp>J2;ut9j{$Rl53uq>smB<0T?FwdazU|$X3 zvET>=c9HEoEP=Bbg_11J=k*=)hoM6KV6AYDWt@6uio_he>$a=18LIl3!f{F8J#XPU zfZ_WuD=Ta*O^l^GG3zNK9`ue&V7+$7YRx@!$j(sK;FmT1;TbC}`P*_yNkgU7UtK&n z=0TSkpivInLI~BKy07(r;e9mYyc~I+3&MV9XZ;?<4(GMkSLb>FlA2KCV@jxtJTIkP z&Bk*}@OnJ;G9KL1hFV5b^k~mAWeK4{nimD2HyvK_=fBYmVO=zaMB*rGwj&? z!Qy9ZIE;XempuB`zZS3=`f7iLWua#LHV;y->o59tE<*J2nINnn@cxvQq_NZ@`Qmdb z56n}yTUN!`rPyRL+u~OM-PJWrU?ltkwkqxpfRwm+MA97>gzPCZhv$GM9BwdzK2d1~ zLfX%aa-;x-+Q~jW)P2X7Xc3SpEQcV zzz!}2J(>=mL~9r}ruZdm=LU^9fX2xDxX7W4e=&B3xMgZ;-wX-G=h3A!dTV{|<>i#% zQ8d3>XXMbl;F418lvjWSs9VPx7;gMMQ5V?Qb_r4+v< zb(GE5c=wN=&8_srv#3lOoF8xPkN3MP0F#&9*;vmIb3HLXYWHUuS7=ey%+MTWjC=YF zR;dRTq7b&>Yor0X9te5HSuF!UT%#mx{eA=terl zh1QxSdtg9)j{M;%T7`$Di4$UCm>8mxyFZma3jDl5U%fxTHGt;^JO;?XCmqOY-)mrg zw89d7T7Jp|9K1^K%O`s6@B;R2b)J8{)dE;pbdc(_Q#V86*;w>%BkJOJ>_1F#aMg}) z-}V0fEU>Ajc8Z;wGiZ><|K7fh{xa}pwEpP^RnoRAsIwT?`@CatW%ug$!toDO9_Kmo z@1^T30Mh-#zB^p!sbwSiuU}#aS8Z-P`7G4~z&UgB@B;h&q>Kljak=~b##2l|&O41XZ*JWz_ix!Gv_`=gza zEGbPWJzDQS%LYel{r6MjSZ9Z)T`fp18*XO`QMJ|EH(qRR1?_|7 z(2!S!kevJz<>z(Pj7;*@_IB0tgZJ-MYHag64(X?vd3dz9%%sgnMY)6Cz73-iFVzFq zg{KMqE8tCj>|lj^hwx*{$EsHLKvZ;ergo<;+gbCr$BjACt7~hK6BEu4AF%$c!J`jp zbo+>M^JYZw;aVdV1B1vUVY`#Mx{uL8!O+Z1jbUG|{XOlrhhQ2V5qHM|x{CtXBO?cg z0|Osy;}-BQU%av_s^rbp?87x|d*_VN`yv(;WAgTa&|`Lby4bB=uJVd(NhmT>QNxzO zXaBGJ7yTX&z%vJG?o3YoJYvExn?8W|9nlv#r`PkEZ(V{-8gYMex}ARyC3~kO$}cW2 zb&uBdU;^TJgGpkcX4Q)rMon_AWkizubNp_f);5Q3B1p4>7_I}0**2`P4)ndP7FP7y z00|F=ccON6;y=-61%kIvMM_>p&0_om_V1;zT*#yUouy?lvWm~5g zDikYlbRE^Q=bLRsr4KUQWJSmk@F3Yc+P}?V!amEvSqPW&`Nr7NORH!#CjOFoxRQ8` zU0IhC>ZP2H^TC;&utCEuGDM# zFGy)>g(y83}+j1EXLorpTCVhn@9}^@ax#^$U{m1uY>7y6`ems z2At}6PUpv<+7zro@ z6#1-eEg_C84*(8IeyPRmVYMFZgzJ)AC)>h3!~{{vrcePJ3k#CTDZ#xxrU|gqDU5ta zFxCO$hin7E&8i~$@40eojb;IACm&Y>(3dvF#H3i=&H)T)GMJ#sY^0HjgG2uNg0`-y zsaojX_BQb(@ygHMJpAXjb_>sN^)fc!!;XEzpIS{WF|1H+dr!Q7a(+6-#uQ^1`(s7< zE&JKR-$_%nu#9HzF1G?rZqaZf)?>(?In=pX6_aR&NdBz%%PFa(>Unsx-q#2# z=u^K?G5vxL4p#Gb)JkGAW4o6&EAW+56Un(1bUXd2@|jtgbMUxh9}!SeFvuZ1N9lvW zi!|}6b z!)$dO?cMUg1}&y4-Sh?2J9?&uo;tg%Z6p~n-SEU3=p3@G#>cOf+N|7jTF>tnla~(y0PkqU9(@pHhn(vWmq`dYPk;U}&?_p*S9Fk`wqhB16%0;%_Ti%5u|@!Cv7 zUGEn%Q5H81HZ%8aHLsTmg7Pk+xlct!JKw+R1|SZ>l5Nsmkt$3vG71Wvq0xzA9|bfS zpr2)pgKdGb1VMVTx2qfLBn<_bT&&mKsIggQ2E>c6@Zb`Lk*i{hduOn@ICF<%{N@O_#u{8I*IFL}?ugStkuXSe%FCHU9dv2W&(FF-wi3%r+MnGaTuCD3 z#)$kbNiZ51$|e0;nF9Xy#Ik;2;0av(?cUy^p@~uRi3W9Qn(^f-)XS5O)jYKZ6>{Ji zo9IKC$SgXCB2o4qax>-3asl`dv{wg_uahfm++SyWw!fcn;UArP)woB`qxB?#n|bcu?J8ZVR0U?O=W zVFEx&z+aVl@nXAF59x~rUiX7iy``wN4cV&4R8*ZwqAYeE)@T!t8EM2LBEB#6j0a6D z19q{=to5;4`kH3nTI>6)EJQbpT@C<rPx?3s=|!#pR^TY zjF~w*JBKN&^PK%X62s7>j(hE`;}H>S$L+0qI{Lvg+B3)_O)8aiiuEgG8*zN`4_}rD z7mgQC9(t(VLl6kULdt!Bkr0MOgA<7(r=n1-jLl-%iiYsM3*^8-Vej*@@V`uv7Sy*^ zZx=_$bkEHp`z;PEZ|P(C{iweCB%w=#a%FprVeB7P6`QMn)-$r%!iw78i)bWMUXy7d z5F1UlJ3P%#>7LUsI7c(J$$}8ijkhPO!eMCX_;P)cPeh>o0*>spZxfyeNy!PS=xotI zm1BIRsGx@hBV&W{)XyqBiw1dY(lPFkOl>lP&(e>%Iht$=)$JM)wBh71r zv(NmeZwmp!3yen#8#?eF3kqAp`CVR0G|8HV*bt7fSSFnu9*YB3+US0B1UjrEWq4V3 zF#PswC#|_j4Whrr%0FBT&Z<+0i)Xchle9``<{6G`$+VCdsm>2 z_en=mORG>YFicvDBJzc&C&fjj?I3_SzXEWjv=$dLz;ppHS9t-7C#6dFT*0wUt=3jd z!{gEpb|zjL$(NVY3}yRH!tZvQhTE0Vww8i|g2OB*TPh?ro)Qu9G^lC(Lx^2%TmL(n z+evC4w(lOvfB09sWPwt#*X3hbiqc5XyoJ8`y7OMC1y;u%JBa~lB8p$CaL*n$&l73{ z;mlzi-xloN`?q!v?(wsT#kn~=b`8XBpGiLD^~*PaHI) zj|=+b?;^VwCC&JXeQ4>rKi4{wa|^;5>aIvgNWGyc7J)j>veq2!T8?@5e8YvK5NJjz z5!^M%Y3xVqxx1T$6w$NdGkVf=7cm@vqIRjL!gvj+s2>D8)QRtLVjg+i!#R8ym*o`C zhve2Jzz;nj@G<kIw zVc@V3RXLI=@#MEu*5FQCPG#nhwXwVN^bxTGB)~Ia#8qTaK>B9e6o9{OGMO`gxWoY& z?Tw=+vU7y(?ppJ&ifUN7ZBori+UQqRu{hhF(I(NZ=qt{1wyWLrlGzMO5YR=q&oBWB zf`DXJQC{8w>wn>%Jq!6Ur}a3C^$2f*)pw>|EYes5yCGmBT{f94V;&0+tZY@y#{6K% zlggTy6dbAZsQ^PL;JPcNxNLKQO-ru%g!@sqW?Y}nm-;n^t705%dQu5Kd~Rp3DKvIE zTD;pC7!+aF&0;HtcS{h5p7M@kqiz24okP1b>yLoDXxM;qr^9V~r?G@XzWLo9U@plN zcYYISJ_gEsmWDxS2c+D}PY+5oC;I0wv8QFhFQ5*qvf{0l`{;C_@AUl*jV`RfYFBU$ zd2kXS_SeC9?P3LBK#FePxuc6@xpG)Rf?UcB_HJOHMZe!c5js^)->Lb?TpQF9HNksJ z;3V<1NhUgy6Lic#`ou%K&QTWU?ima zzz+tXzF2Y=PSm9l>8zd7rB`~F>P2hqP!=Ej38<=R(l=3_dbsP5DM({VZ`pk4pVDJF z>`dq1*&!K_Aa#A3_?@>|F0Qon1wG-dhxuYT(>1;mc!#%m+URw35}X2;@NG6M=c?P8 znS#wMgG|9YoGUc}e0;(cTnB6YM~ir)gPS%C0;8PF4?4K8cxJ#sbCa3CxPHEJu{|_( zu#W3{1KCP*^$oY~JiJU&A2aF=GxlBq)_$FMw&P@In1r5+fFtT=W6fhAWquebNJ|rd zaq=~<_G6a_W>5Wp%rzOboWZ(7NlPovcey6r4I`~j6MI}(p`+Zz#odS~4n+`mgsCmC zPRB(shio*eTS=KFH(zDlB!=J*N2zDY=!ik2n15Ized^-p*dxEi68fY~HaCZjDhR2H ziujo{8?Z~<`SkgdEx*L0z)i%Kdw0x41dzKSz*sk{xqRdPDQ040b~|B{5|V!c|9y!Y zXXl1qhEo{Cf}|3C`g1ls{5;IOEhy-$2qnrbsC4JX>#NbIdUn>8hn``Cw&BH+Q=WY zy{&6{D*9}yJPCV&m+)u39-0WJKJfT5-K1`O5D^sgvg|Cbk+@$cczAlao82J-pdmYZ zJ0tpC^-Dmpm7(RC0l$mvj*Q=l@75+yb(kM&IcLE4I7|*3@@p>f?!O^X>eCJQyOacR zH_N}-{kW}mUitw_M#OoGb8(@5-@nu)&?<37C^`m`!7?1T6Fi9-TjMno7=e9wO|Ybg^c1A0NBMQj&<=#DBw>CVzICQIyU(yuxSzAJDW<9Ac`GHJkc`0 zWXh;}2h0JdI$!+t)KTnsfk+J|y(EF_N;%C6x zmR(dQ-52#zT+A$p0sDE#&0$aU+Aq6lkT)Eu6j(1`4%4l48)s)1NGEW+WPjn|lT*sU z6B3ivayDS9C-%yo7-itH{rK|j`$Wn|tk3u57btldgo56YL;OIA!DC(rJJNJ#-!hsZhy*FL~1I9l@*gp)?IN{ zg<`cw(tLY?Svk~e`;YH{WSCunwKW>GaVwP`415k;DS)-AxO$^7FArt>gL{SPMD=L! zk&s=Fw<dNyO4)ILEB++&?S7Otj1$%M$d!BRVidjmEou)_bK8v6%hE z7zo9(iUs&f74nK%*#(-`w=>!D7U#Fg%$7~QS#~=j=38=uOB%UgMVctFu18 z;va0~g<9ShUl6(py+`M^$8Hwl$xOWP=`KTIedV<$679grz?L}6We4EVWr1=N!4+C$ zjQZS#XwPN{Iy1!_;XV8ex2_&P3+vl9Ntrt$GB_>lh~q*%R*hD}_$>OG*|>(YT$WE~ zxSb~|kBa}+-GXixn_uiZ;WgQR1wI(_bnNd9Ys6Nl*1ad6*x^X0{2S`))ne$B$(fjP ze9#gb50IF>0gKoU#D_=ujhl<+WjR(a&JLh#ckJy)z|3X-t(Ad6Y;c@Z&vdW4LU9ks z;Z}BFumrvhM&a-oyX`d3uK})SalmG7jv<=XW?^G{2w2|E1rAUBfR0Fh64!}GZJ1{u zqxSMqljFQzGUuGaC(r~;dRk^`RP4HC(nQ;Iv}hoqY7vw5#WA^XiN14`jxMWQ=S*Mk z)jKB(z8SdzZY@B%%G>Z1=n3y$+PAPsju@sIR_3iH;x2W@LaB9Z(0JmE{ACsm%7T+& zi+A7ng7kdZ*)1`tL4jiBg~=h?gPx1E-fpnu$eoBHVa*+6tv*J-ddX%78+yyhXykUc z$Z3CGYOHW7C8v;$^%AtR$*p(DSL<5Gj#`ff-KP&9HzCLP5V1AUR({%d&bQba9TP=F zUi~?U98d(7(KTjtUD5elyinNKoy=;FN$!<0E&thC$>R6c?wr}3O1s(8`|tvt58pT! ztJT?O>%)_+mRSvhD$x(VbJ2=35mhr!D36XLdjc&>LBA0Cd$NJB@bHY4{_~w#BWk|A z+QQ4+WzP2L@d@rHju>{g%Q>L2;e$-*w#JFG4xykXX?18g_448wmrahq#KdHL_!{Zq zw1;jR-NT1s3F*O*$&~3yz{z(3DV6Q7=w4EED_h&!gYS|M%-+5xh}oj1p^95@EtoRt zOaBu@HB5eOufFc+aKn?K!!h3tL10^}mc09=wQX2;rb=`_5#QG~g|ktR93o{@HiY3hTQ_$dT1CJ4d8qdqVe>+^{kif4ymq-y0j-%t#LG2crX!+O-X1;7yF<5Qq9?l7&pJEHnN zuQ2>zrPnvTVc2=p{ZGXU1a*7`)0X7UiejC~QBlOJu`W6#Lk3qSYR@a|rQKAk4lyt~ zeen(hZa~GXZL4)@o{4*wR5_}&*bi`j2@Ww4$S9LHeB`&!96;z<#X~tpI|Zp zk=xASVX~}g;zQ>CuVtTFrWJOJjV|f+9sd;W&oh8ERKOBvJP~vc)?T2FV^`}rfoevz zTD3wq)V=`wN^l|E*VW-dqc&{GNfo^0N2Gi#YreC}dU?u*enl5U@PMxJA-A!LB*_Y1 z!d)-zf%{b>qod*=E{a!WyC!F1odOV1ogK~9RO&!aDDSmOe_vcII7xUU57usRNy*Wh z7gOY4%Critw=byjS#@GDhG)YLK#P>&Y=j;(=8G>-udweM8=A(5`zdB;SE!Rre*L?b z0zs+Re0BC(%wN+TAi4O7jg)Vn=6XA*i(VimsY-_nAjV<`@RX0Fa2kVFEf*P zT@)+`W@l$h#`%HCsj|`f9I&ba12-+eJ$pD0{@rmGs54;&T75`AME4t>?zJfJ0<)IW zkTA1HVe@^Ob@p2kM;l`%=xMWv-Hn#qC$pE+v(ccXNxA>_--5Ur_}TO3ntA6w*&5H= zuOwwC@hiNs=!DFES%YfXW_-ea*(-l5u?H9x8$io2t?P_B;8K_ti_rplQ!1(f-0yGrhvNJX|K&v@^R?83gU!;C=5P7?H%jQ~pM`@5 zn0V|;#(HD#eiZ=y6)qaD8eoNKl|MURJFVBh*SO9;-Uw{7m>_1GL+;ksnmxgEw%!+?o2>$#J|3F)% z_Qrb7pA7dt`~93b@ZvV1^87MZJuN2w!wkBd%J9*;Y=`=rTI~PU;yiu2NJv}ued&i< zse%<5NshBHilBnh%4W9T)hYL*|IbbBe_WuK*N4)~yB7xl3bNPJ6*15RrQLfjQJ!K& zj|S=e1e^)sCa0ga_4YrP@aw`1HwBrk`_Vg%+A#A_MkwgKJhwc8VEulw|8PVY&KTV! zJs_zwr-PUL8{3o@Pa2fWf&2Rf`SZ!R=Q&9qs{sRj$t(WZi1}18XKJ(VCi{Qk!IG&V zy>u0&YkxWuVEzm3Z)$gbKaC8(=};q>|JD8>v)0KhBTVbU|K6bkhHLnf}XB;^a{9sT(}z`2W2y|KIwWK(i4@ zJ?ZMlvGFP`&<`sVoE&p zV1M7Z#=7Du7>MiX`kHM^gon@XkgUkcVt?P-%5Hbk(|f1ZD3{^Z4Lq)}QYftx=Ck=R zl2T&&Br%&8L{|N3!w z3tYrql85C5Mi&kbhNk{B(*mW%mJLKAE1YPz9GPsKuSdR!ayR%sH^$CS99+yyX6 ztbc-|j*bQ!vwxN?8P77avVwlys_y=N#SC%^N?LC9h}#QPtgKH{L3BAbGPh4$SUB?V z*!^@*BIM@Hn+bdY30FM8lM(uVI6KRzth(;qgQRo`(jYC}-AIQ;mvnbYmy~pOw{$m% zL3cOO-Q8#1&-?iP&p2m{^Wpf3p+nf*d+oL7n)AAT*I9eJ7ceG_thKhaeSk*@0=#{E zz>-v0_Ty4Y{Bqq05KY~DbFF1%;y?;r*48^a^2iG!F&xdxFS$W<`+8rzJ_N#iS(*8N zi2sHp~3BDlx^QAS*%syP&pGTiuzXu7$5+ZitGX4GsbO^l~clr7&G&dq&g*T2il@oAu8lAd5ERTW zuNO5pKOlsX1>j#0q11Dp*a^|#Y@ffur(>vwNN@}rVHX;-1+>oFfB-K64AFn|8r__F zxUP?*gZ$C?jbFVEr<kgotK*{*VWx!raE?TdU-keX}FN2 zeK>96ss|Vz*HOne5zt5`WgMJUnv+FJCkN=YX7LFPQu&e8Y5Eg3dc}?X0u3HO7`WA0 z!?IAR?(l$gEb%{VCkV$lhMIhKePt zO~p++C1qsua)71v19aAD7n?jfe=VXW-JzCl)MLGAf0~H&&9F9pI0AAO5*#&xwuLnM)>Y1Df+u;Z42Vt;X{) zIA=~u54@i%4t3M1c%MhFuC%k1wBcz&f#_GFrYB$R(+y@}xS|S-@a||PRK-E_@AwR(7jEAC%Qc1wtAeKCy)nL!B}vr z((7Wd0{A7Xd53NNz|s@tl7zmsNa4~Fijgf2&N|ZsA;5`baoo*8(PaSTlHVd)Y9Ua{ zs==5>pI%+XD-fz$ytZ)yNhJSo@YA_A>?GEp&vUvwfE5DDYo*@a*sYDa>E%&u-u8OS z8?5om69{H!X=$n2`al+leBw0NpZ|RCdnKQm$>*s9lqDjGeAG#6grYfdaXY=Ryj|nt z;!~wM1**(@yD9RTx+5U59$Pfaf@+!y%&ij`2gggU&V56A>CAQxr#IBIq1&rpF#_(I zmAY(L>5zOBquhJS@6(zoEw`NPMJ~2#V)DA}lytiV0LRc7&H9{EHxeB^W~P$t=~8qo zBxkQJ$Lz&DRR^DQfU}5u7ZVebPTxrK7GOBOdbpAXiUT+i_&v=>m=h=P$a$*@*2e8z6 zstE@M1f+OYbIfDlY4`AsR8ZWREH=l3U||BfW{uY`UT}^rFEhu+#!l%-kit9@WwLyC zeqO}>4tQJ?6cjWx19oDhcP>CD52Pj~lV$!#0HHruq_Mk~y58eXlRtu@6WyKxiB3v; z$sbS=*-)xpr*;3}!Flb_2@LQ;;o*aT=4D1l+nCcIeQI9=Fj=!eEb$CqL|Pdg1!;tA zDObwg!3k?; zk2I=uz_AQdf;5Q*W+0!d%R&_$)l~6>rFv1j{)(|=*MLNv={;r_m$Tqqf^fH*fz z0^qLIJMaesoPh$7n(uuCv9JMkS0YDNSiUr(o4#LIiYnrl9B=aOPffI4v?fEird`8e zB$gipvYXJlU3C-_bmGLKuph4KEH*UUclMja0M;xGp3b%tLzHYHni8-KK#bBL4~xuD zDl3woCDrC<8#A*+hl0UKQsENy)#uOc<`Bp~i4Lt83K30vtXT!}*T zEYHgGzWb6lNj7!oNW-Y%5pqrz4e+kkaL_pkd4oR^bRXjyOt6GCeuD7!^CMNhDqIlsF(|$d*h8$)s3}T;Ph_=*XK5D(E)>+cwYwzUsu?F5%>n;jWQD0+^_t|T4vp_P+LH32}d(Vi; z$e=3=wd-k!6y-#i64MJ@v*m~?-dXfbFtxO9VF5`N4&>-x{|M@rz z#OL+_w$1rj@)o!|)`~i$Pe@pb&Jcf>h?vUgf|W<~L~kc7YJlCtVBp2vIH#9&nl#yB zb4iI5I}Jp}plbT;**)d=W!=cw%le_zsXhv_FW7>Y$Q=HR_9$%cMiO|2PF&`frtHQS zC*j|1x8{CGlz>k*NGI~&(A{RXO{35z@Lg{LY)A)pkS2or8!A!A=MP$f$s71PIZvs` zj~q@t-+PL}QrGa3MW+e*^RjDH=iCwUN^GQ$(75mpU#Uz_Q8*n4ri{j75r3PN=#UAz z@#=YP&y5{*9sCK1#IQ(p)Z6oS+J6&m^+d59ECMOrY-&yRh^vJ~s*a`TB0p$D{ z*fr9#9bN~No*0i88gRmPt(R6wIM(o!K<$FOcZdSvaZUJ9-0NXax4)mcg8^v#`cMh| zgccVU-zzIqA)paOP3wAVXL?^Py5tuYcHb&?;8RBv6B9S5?T_Wlaa$=Ugc~yiLpQZK zwAIqE>ga7*N06SFA2O z*OP>Ns5B5C*FiVS;>u?!x}>pQxsQN9@0UmGTb+tzL71NgY^K!EMfemcF; zAl%5j{}?P0B+nO^QlDjuEgNWX;7cb9Q<@CIpupz)ifhdEI@sefI7t z+_cK|iRbEcY(Rn`kt7v#r!%|l%KK$KJ@KLJG5myhf?nk!b$Zm^EQI#Qs-*6<7Yr)o zYU*as`x@XH;NkFtc}UYxbS2v}xg$wQ>sFsPT>3}F^$*^{2(zzXwr8pgASuxRgB}h1 zn5gFiOAud|IKr&ZH6YY#Gz10)D&fq&!L0llgx(Lyx(Bg|6AJScUN^|>*CeC#e&A@H ziSw1++j);o1`$1mev$^W!pzeyXCUo} ziQlo)5Z+di>oq1MBANV-WepeUH@Z``GNlR{OImn-!g_k-)mHP8>P`B^t;av;?N3&X zP_0+}kY=YR0M7}8Q{t8LtZ#10nwl2DyPlq&uD9PE#?oYbUVX4yZui`b zyKg35IV`Yw(bQ8=J;vDK$l2pf7Ad|9kD*lwQQl979Th!aBJ_0;M!tGahSp?e+|&Td||8aFrh zbFe^BNd8%%VM~IbV5%pTWv>}H%IV(!*M((}!%xSEIm9qtxo z-`8R~4OjwBxBWNiL1G7)UjuRJDr`o#F}_OXMhtJI$FO{7EVCM;Gk94^`2`M4fV4A> z8=S}pb5!qeTH&S-=VG+k8tUf%;FN<8)sduLH;=5(6xYi!;#H z?5Btnc=Zn<3K;w1f#JBfrzZ;Z&6V13Co9am&@!YxZHN8{(AUw)Xg`YdI?uJJH|keO z5#=tBQx}AqDA~zP%2+X0WT52}xQF$>=}yvI021B17y}GP3!9^fIa$-ak;+e~*C-oS za{@C&kuw!m(koictca3XjCN@TQ3M3I_Jb3Ac^W}qU{gh{6Khi-dw8h!IUdhYbVh{! z=1&khtB8}(O@;?2v18u&T@0j*w|kq}mET{?&7PJ`vTxAK751k)uu=6Oj5A2Qf_eD$ z^I=ygFF#lFlzula+o>|j!CF6$3H!;FWl*FrY_dUG%_s6#Ae?lP@SdJ$MkizoFYxYU zrVw~_o?@m$i$+XBQXo2%4VM!_jpPo6*v)(UoB_%2(VZ6Eh1-+FfCxv(1geKsb#5U| z9P>{n)}0!!Gi|B$SHR_KP*51WZOJAKIw9Y+&Z&^RV@?v5J8W`K_t@ya+6jCSo105P z1%{R?Wm*gtD$J9qYH5eknZr$yk&qj7aS;zdU=~>j>O2rXu1SWgq{V%f4m#h+sD38R zR}Jz;HPZGKF_Tx0h^E+%j)_dl=D4zMZeQUW_K$78{{}ozzlo_yiz;5QGq)DDXuf7r z-Z5Z64#N&kuXhFU(Rq~S@2qi@A%&E?yL(HjU~Tva5wCZ9Xom=<}|e^Ot}dhmdED( zJfF{Z8f->VQ_*U?cGV_!{Enm(bjrLFSCRAwDg^BkZ&*(>XXWkun*N(Mj?~cB);QDW zm&6Q0veQAKT3WOpRi{m>w&-}1RTnY4>_{;FR1B}_myg{GVkmH2uC>+|D9!-@vm{bM z-^>cn)x}wSX{jTleAvmLX+)FF8*nGWq%<_{$hW=0oK!}Hs4)p|Yo zgc@<12n$%>(qcwy8lC`-Wv?F`GDORj^4t+p=&S_b8Ey@w6Cm!g<5A>71C>OC)ZB4h z$g}ZiG-9E0nu7pj2ZuSH_DEv>e7R_5EuQIG*K(jD*fmEF z#T}gV^Hy6~{}J$vj)9@7?JJRQ`{i{AyBqh+QWt>rHMhQwaL;>3LF;&;pRL6}Ti^C| zzj9XuYvN;fh&R$2AsXQ4s{uEYCZ%-u8zeqo*j;4g^CDW##EUd?!#MGQ3uH_N7KA4n4gF&im;D=h}DB!G>)(|EFFY27cT&#srx0pQ0wh2KLMY<=B zlUJtJu7*%u^l+A9=8!h?6q9r8DA;(%N`|@FDEXSxTtn|0F`KsvgKm*asNEKpmDlRJ zdVl@R#5$t7F!SQ2={-lXP*zs8sKx07M}v%erSm-<`9g#rQB(u7+ z`Hh=|W#qe8cj)U4|J)lkW_Cs6JPA3&k*#UEBAbJ#4^)%(+pAQl_X~pDa>6-YgM+pO zc`95-f;R3Ptgu0_z18_=bwlU{o;P=QeWymDhUV4@_$Kl(pypHsi$D88aFGYrX{3Hz zIO+id508RAfpLOv|Kb95)vU|s<KpPezCzXB+=M!OTmDO7;${mEo{WQ2B6Tbr%dC`LXr zgQ7o?DK1}bQ_fVn5;z=Gbi9mefIC6OB9~=y)D8ybfo~E~u5InB)i>T^26mX44P#_< ztGtne+o&0;6`8s3Po=ZTHsi@YMC|lkrkr z7TJ-&M$N!EIa-cPE2b&iunL_ziB}XqII`~Vkt_N~4GJBFOX_b1k)X08(EWtnhZ1_q zKfI~F`&gC6P&~GU{o|RTf=pz0fntr;YGELU06qEh4Fyb7Qb$+jpteaTqao!#)p`(@%M&H_sMLW+?syRVDd^! z#lC$rx2&K99t0_3`UMeDGbo}hi)n^fz_+v7!qWlX1tOl;bxuxhLsZ>*3yWi8IlgOP z5Uk$rkv)|mBOMkym*O^S+Qr!OvA9??)nRT?O{{?MmLLq%F1Pa6`GJZPJqRAZdIja! z%D^@3}94>&ri2+bo09}4B$3A+~tEJS+6E_hjul!<| z3^~dJnDR7ShS*^Eoc*tlSdU8mMG+AE@(OWeV(61{KP<9t*K_(g@lG%I>% zys$rx?gNMImn*;xsL2hSLg)9qt(}sW{DZjh$#^h@3QR6;*~zZYhxm_7wT<{CKm4m$ zFdb0%avhl)b>knF3GxUO@M?a@Zt33isjh>FVH?N0vBY*tK!zEo#Dleh8gH++SuRf& zPU3=KRc=bafZG*Z1t;Q100n~Ra;9V?r_lYRlBfboGaHt@G-0G2HV2}Q06F<|+WTR; z*+<37s;u>5N)saYM@3xuA8yEKqsVG#JhxOjkaY+>UK^x4*8$DR&D?Z*0d#U>BM+#c zrhMK4;*IeQ3Mv$NKf-wDVe6SUZv&b2?pH}X3m(qkAF@AknuQ1 z{EKxgrb?r0YdN&vd0y;J-ZmB$Nndr|Q8@gMS3l>S51&9%N`RS85B!hX^5v(;t5Xnd zD+yRHMyRWQT;1(90h=g&E?}QTSXemyHb6rd^xDbWnIHtBV z!os>-R&$gU?YG}R+lQWy5yi<>F+-rZ&hywSsXaghjl>|I8P;R}P3j2=;xU;fqG)zX z3ITvhjeQydifhLWW?*E?z+|WvKYlJs0sAHD!C;u+e`e8LB+nQgm~fZiYjw~PK1kUb zT?cL*TsW2^aC$_+eWBCtnG$s#T7EoO-u=iVKkW7d+O@XqyH|e%-;H;Zp#1ouDsBNY zyW(niNv39~`<}#?_@0R3Ao6z&h6I4;EKNT?>e51eAwE$!MveN$;qfzd1>vtmCM9@o zZf;{-NjTml(^JLk@hnrfrtSC#a9`Bh*aKj%?jXc+}JPSWwpRFoA;eGVWmjlvwFx5f(B}LxWn5G`kJEGF!V!K$I z6~utlO7T&gn**gDgcy5T!~6qW!^9jdv%)cFh%7EYWYV@nev=lR&+ah~GI*y}I&n(( zME}6y^H)_>u{mtYt2f$aEAGiEDNP&AZ4IUtiV~F$1@L?o-1eWI^%woQ;%YfFOfpf0 z;3YXniZNY<5UQoEjQ}HdYx+_mDC*mnjbC2J{-iw(?H7zU%ugE~+c8Gc+SSaufx}h* zaEo}2{&L(X2yCOhkZm3xeXGqc%x_lEy=e)#EE|pQ9`xBX`%~YrToB4}o{adv+?p-3_|>7k2~qNKD@7A%fhhyWDmed5+y^xpcR8c5G8J<@#6^oo#ln0gWR*) z=}yK3ff9k53+v^}qJV4zef?S{3?2U;a5!1(jzazhG;$UQC{cZ(KWr52H-Nq_gK95GvjPAqivNDD53$O;Nu2SLPo zpgja5egBUtD!Wp!`uioGK)k%;h4_ao%3%2Ak8j$DtDnqY`UxW9tgt4ycVnG=_SDzU z`4SMYvsby#uM-4?*?0L#Sf1|Z9!oeXeK`3Z0>0FB@^K2#O$Br5$>MpL!n(YzMEo6k zJjmi=b#3g;{#UA``69-YMGi@nXyDr|$aLo123s6{8Dp*0JQwOK@*zJI5|M-<(2V6w z@_#RIcXgClV=`?1X)DA+RT|QIjL6!@hB)1%++KJg>SuTP`ynswcZfn z5{8*X5?0{F;X5_cZ7*@|zaPsm$YxjOwrf`4lGhmD=1vIfDNljFHV_R~S{MN7!PNa#-dx13?>x(qw} z=5~)??0M@nPqBB>CzH_lbl?7&QgS|{iB&pARFGuixHIq%$|{v~H8_i^3k7GR1n~(= zfA5rPg~y;2d;2_9Ft!^F(#yv2lsq7%JcL>z1Yd_q`b9o)5Vj|OVHYvDa~R(D1;0T?N-dLMj->iNcz z;$NGSsN*IBc{?paT&1FK5yv|)M8%LWH_O^?cS}?+I|HXb{hY206#Oe=lqO2oc@r^; zLWYCL=e(bEP~1U;^d?uIbE+k?CkYy&c1wchc!Yc<;b>r;kCN5bT`CMWu*2?C8OQ&O z=Mwd|-`hHZ-$8*w!efD+l@bEq6tVyP-rB>*@eQSQo+`TC_-0Uu0luJstgtNF@E04Q zy(R($6Le0tZg=2TB`p3|3{DOXExNam4<7P|W5K6U&10N&%q+aoQdL2l>~pUt8+_TPMAGMUT%4^@VCBG&B@afx!sE^aK#V4?8(I z?cAP&eMXg$Lg_z0Lc%eg{zF-56K@MWG@1O0*ms0k;p^aTHTU*{0?9{5JLs31(08z=sy2_r1tR5cH@<~OkAj-)>l_^)CEAX*i4=UC~WQ< zCnKmI+Wq|eDEav{feVGMVbM9Yobqp^BL`N0w_2J2;yT->lH&!C35*YZ=@j9l&G_Wx zVrUX(<_Zh*`#-D+Ay+3Sqp1Cz6u}(P|G!U6^Z77g-fb_pWn^hLKaF}!#;x}+3c9(= zFo!0rNx-Na*AN0!$CTN#?=a|)gnLRxMunJ|nDd)#O$d!Ka)7keIS0Y}@3w}5nl*B2 z@}ZoeVb)9D#K}n`61BjU{0`y6_sThl1i1X#sqFx4uUhaK|NfV9WatFw(t4wlL3Qoq zXIvjaLW;o6dMv@r&8wW8ob`@}h9_$9Zm&0?rdEWecx8{4_KfS12M%nc;PI0E@V(Fb zr1Yb@E7DAyp^Vq=6XtLp?L7OC5l~G&1DO(&72udVa5-Rddv}*#R;G{`0%p@7EEgjg zXx{%ZvV!V#UI!Z+qAncLGq?Y;z{)*%8QcZO<~y%piEb*8R$&&a(A~#rlpY*RU9QOp z_3_4H58lTE1Iq0d7a3}Ddb&T=rkxHf-g*;wJylpAa|;Vj9>>Rf*TGx$YQqq~_FEp2 z&-!O?AfPXe;d=b6Aka?I6B;k+i{t?8cC(D&WOGyV{$`yT zvW;cLP|_(9K@n8JVqTsBsJKD*$469YOfo7x(K>PtVBY_kTau z;GPso6evBJtC5knAz@*y#^MR+1#V#K*#9E{*(u~2yw+q@RTB>;|E_b@@mKvYN!o^! zK!SA%@RgpJK-kud<6&b{k;d<$$j8rb_1_1$dFuE@LuoB<3n3bm-mD7)dZhk{wYBx? z>JKEmzu!*gzrUlKCi$rz7#a-!vUDd`nHsRuXx)W z2K$qPF(`O6G&MJVq6^1?6V1W50|=D&0MM2};@oHP%cEsxAt9ma&nNmP7Z-K^{m;Rr zhTx7DIJmmGnfq>K6N1v={MWBvJqt|^8<3;WI(RGAmuk1DsG?E)`+&aMYoZ2HR2DK2 z{27y;&Ip>p@%)F4;)h@g)&!_~jz71q791iWj8NcK%^&aZ^Y?e!_-_Jnbp|H854A!H zC1^wvz-rVOhc7ryYZII|fm`IH*jk&2cUM?+3yWy=c$r!}3r9`lnuZ^UHnp zR`YovjtMMGD_yF;`&K_HO7J;)qna}zODa1dD-7cJcaU6=4-j{db8cY2ryVoz(D|Uhh?# z`;{!n#4(0-a&*+Hu}k?2YklBNGB%o3I3B(9=gS6LF04J|7#t7~Fa{XqqNJ9Pf@mw# zTj!rSH^iNL12DQKH@}&^>?Q--sSK0HK%MC&@1Y|-O550fxIc9`(trlulq*h zTOwY23GhDPsM-1zf_+;D8Hq!%ob>Z@%x!t|po}OK{qH@hCP{=IIAdedY9w2Jyleo% zyN%QB+(>h%qPjX|msc_b^Y%eD!x-p^>FL7$4nRo_0i4!>6izvRK3&69P~%)*U(YQ44OiYaZ#A-W z2v>uhTU^x6$<3u=Wj#T*n!&61@5>Le?ABL*gdqK07`Kl3jL0@a`?9E6>?T7!VC6G( zc6L@<&ay#RZ!)ox@)*sM($c{T05yb#i)-v|tgnws_KJWWr7Tjo;AJH96cmAX=|5$F zbv}W}8x0uKnuF+zEcmxmHcy3T(@@p?PP=iI3ytqGJTKKjM(R(zxh0P?1v5*_+BTTK z%S64G6FLhJja|31gVy(SpPI|zFW=MyK(@(`3aGztCIf`C$f!p1$-(>KVr^_Fv3Fa5 zUEG(#X#t5z(KXcsJ&x;}o7pAbf1hbn{icm)BH&N~bbR!n5fKYo9p2fD?Cc*BBmTat z3GnF+mgJ{leHxMeF2isx!lxZhyjfDpW|Z*TkZWTq(*{{EJW7_e&a9Q|D>^JH5JfqL-& zo-Z-OVY=|GsS}}bADULHx-+9lpVnEy?rZPhFsVF!@8S9D=eYR7;)3DWdM}`%Q3K=i z*yJQtBJ0* zy)vuAl|$<}j~KHv9fyGiIR}USFQ#W9_TR*hg~`4vc?_@~9vo1`Drll7J>A|i$w^5S z*1MMQPSN;q&X~*%y{l`7uMcB|`^~5LBaOj%*zsH^;jrCnhda`48M)$& z>u$|y$++eyvZ5jNfq(F-@+fkPCiy{dz}>w?30L=w@BSfdYx!1_=Jon0D#C_+M_r`z zg4+49E%zF(?#b!pgdK9m-tHj;Wd*2&6KAyHs9}VjgGrbNM>`w5GY#j-Ys=?5U=lmF z7~Z~7ZDm7%YU+?C^#DR^`z?;OzH)U}MLf376W#GtjBVRF{kF3n%C7e^KF#Yb2p`?l z9y8@1I+^*lIW!m>&Md?T(p~FK(x!iVySkaC@xaCKs6UB&H!8NUyPz3rp zus)zUPf5Y944V05`1r+Gz{&Zz>1Q=v?s*F4LA}KvwrB?6<|N`WGG2jkAJ;+0TdY+B z$G4j5>WnSIOU#-}%j8BziH>jI4KDH%}Y|AS0F#Y_mYtj_i)}u5(?2bX{-QkR`orziG^lfPQDxnlHu6K zCj3J+iwVspETpD?-&StOMWN=GHA?f_$-Xv6hH0unR@J7XNzE41TZy|j6fJJYI2HFr z(cM+@LyH@8zs{MUq6()>$c-1{A|hWXe8_t-&%t)+Y8LX30$MboC9at#Z10|l_(FqV z&@?i+gn?-p3d6=rYBwt84cas;w1{ddC{T$Y z5u{38T7b~33L0?{9AuBVhB(UOx`JA#9=p(iBPBp*N_ffK^YecZG&9j^B7bOU)K zVqVp3>N(R;UmraOHvK}{{@R+sxt*LGeNCk#^dUy>U?NjGv&&+WSr{{L;IcQ{sUT3@AuIwt7uL@4@DEL_|bfbu|*u96==`K zYKNK5=|bc6D1PURH*L;B-8cMU^;zrh<(~?Ccefi_R-vDp(2SwsJ~!`Jn9sLtymig> z&{!h7AYR1UJ7OG#&cIqdD90B`)Zoj{Z&CW;DfnwJfp=nJlD?ZhHLsve%CB{SYRn@O zu?8+>cyGY{k08H0^WN1l`?7m$T7`8yccd;`ci6#mAS`(qVF&9Qh3VUJf{#y^^3Hv| z=ec10XvN63xUP^3=xd&jXuB;*WR+D`O5CNtWzYDfz<5soIb$th6!XOka!_4HF$;c9 zyuSV{6K*!2lY{lZ|0cDtfZAeHIUm2G2BcpZ8a583@hXtG9V?z(UB#xP@L4$+2CX&I zQBl3SOF{zua`V*gF3Db)tBPs6gc^$(&-W>484ZHfB$2@)A&n00jc_+}8Foyi=K|1r z$IDYwPw>((0$ zuyjBHn&qxAEne?z5iaWmN+qESn%VjX1BqaWwKlr=Lk$&e@PTzuQg=YJ3a`p6B~>_a z4DKqui}9O&3ij2F%K=&$l+y&{x-xt41Ca=X`qRFd?IjQgaK2xdDThwIP=9xtzrfSP zO(Tg*6)5|`q{0|Jox8&7;1HW~nhY6nR`B_zplU&2zvl=2jm`x%^+e2KXmXDy#;w=+ z)ph-s+NMSQo3Ba>3#DXb`wWkkls4j3m&g9Fg$ue*ou2N*VR%G7Cwmx;D z?XW!Ddm1mWvD>6HNuxE#P)S9MmKr%^qzRe?E{V9#5*>lxFwD}`yT#aU$#YsGnbSSR zxYTwuebo04TNky%=DLiPRa>k1+j1musAyOnHzgXbDjyMCk zqta$(0j(F8L37JlxNkuymZ4Gptj?QYsL6UKIVIf=L#b;ymBtQAxI5{}hL*g5TUkX3 zpPOx(#YAQ~Pxr`!H?N4>JP9g8jxXXCdPHQ#;*Sui z;r2R^Jvk*ce-_>S(&IHqDTr4R7A%-eC-tZl2dM|tRtE<$2?=@7#;U41FCzmN=#pci zGZ=tM72ndqp*1lDMb^%p#OJQ1V*>c>=kgig#LRjkqVK>wW?3ZGxqLUA*(^&vj9~b}ot_%0@ z>yE7J=9h3Ym!zNJbOfgEhO%UnI5byZ<&?2r5Et)sKy=$JsV$UL-Fr~aI}zovMN)G| zcn^=`l93Hj45M!eiPzH39J{d#99I;R6B7#or7YRmrRBXAAzU_R&EUNb3o80=&0ag6 zA#Iu#S$(n6`jhC~LJp|uxw-NV^z*YM6^)Nt1umg$`ngsWl*e|NmUF{zV3?EqCYOcD z%44a`y3ov_IbAMxCs^*znQhs1(a-J2^@qxeHrQFnXy^SK6)aRU+tI{3SV+-NY}4}s zGTuq>&Gc&*hUoF(XLLLGzbT;E+oBag9msCPEjY?Kk{rZ_^Eho==h^(Dd3VtAbNUpxIQGO2_E#TG_Zqvorj>=kx6>2?+-iib#YfBo|JB6Ua+F_yS z4K;hUm7RY=vNd;R4T4%}grMLko=}bnDi;%RZe9@hg?8N5j=}GnR_|7|VS>U1K zbdB^$2~`4&g}bZ0pY+OKvdcy-2AbtJzWsT!IJV%XU<`XpR4e#MZHo{KPd>m#^-2Vn z^2_d5?Ut{*>s$Ooz35BAn*w&x3tpVGY~4dHt1MLMlq z9K0k@sn5x`}q8j`QBCU?qplU4fIA+vQw3x?Vu1A(7eYAP#bb#K)e#ry&* zVwPT$=K>4SHt7gg_h*ly_WneL)CO}O><&^qJe@}kXnW(bW>%POYC?w33)CjV8Sx;! z_8)xB?`|(hswN7`-T4>hXLVx7UOdpR9-OWN6_ZUVc|_MJ{fnX8h?0>x7aoX_l0_dj zuTv})Sz1FkdD6196;ju7A8hbQg9uo>pFWcu47Qj?h-09-_!=1GT&&(+hm2Q0eb+0S z_N_IShZgswFWvmSb**VBol=L4U`xd_A^1kBOrlfU>85?=_d7N0HTQTV5Y~S4#a&`U0r54 zI5;rNKe4Fq>q9#8Jkb$g*fGD1MKFJ}Eu%SpZ>3w?NoEnl`+P-lUKcAVFB%o)d{3Lu zqZU2x*p3!Y^AEzo!<#$kW}!SuX6A?E;KChn%GE zN}KYkv=eQHx$kCm{guBv<4wvsX(meCxTj42>Psx>>V?_lY%r48tz~W9{OA-qg+YK+ z(S3yUyHH7)vmXKPn_>0Nox|W&#tTBqPMx&|Sb@>4rm+UHZG&cj%TkU(xQLc^HB`i)K}Uyf3l(IB>KVkL` zGsm!-oNlZ|qW1)8y6ocQ&)euyt*m6%gE&)`MdWd4+ohi;2c$l$^QubxVwwJYs@JI^ z4~W&Qg}W4q1RL)i3K`_k5@)MAWAG0vN*u_q+4-5&5}l-+N0N6tQ!o%m44S9z@V+@x zF&iEj2HfqO9u|{(@uf2`Q%e_md1|SZ%)Sv{(I@zwE8MKc$d7FCYtbpjHIn7wkygla z@Hfe*0vpd{k+$2w4Q6uhw)jXQO8)q-fius)RkbQ;LF!t`|#w-f4gLFZSvN>Lz8p?5JjEWab$vzdo zz4u*>bOox_TOy`r)qjbDPVON6ni6!NYW$;~$7N>PxF-$=De|zgzQbkGq6Hn_VNOlw zAsjnQ_Tx>ch``S0@S=f0=GNw)5QjsPk)c`$99ZzuT3TToT%2;^2CVqu*c#*n9feUS8gdKIM7K{%YGX6_?8l!M^d?!xu+?n*e0;T0R9_{oQbLh% zUXchD>85WlBiq0mF`H*;xE z08~UrP%5lj^A1OOeMTqUQqpL^!`__xub)oU?Pzy7pV?K;#e7X$(bNTL4=r_Pky#E( zYKz5}gfz2%7ql&CZCr-Y_C_F%Om^}(lF^HPg7!5!-$>uoN=d^3?!jy@*r~PIVf7}R zoUEH89SsK+g^n4A)so&&x|%v8%b#5?DLd0JlaXZuPIY5w-c8w5ZmvCEtPc}FXlbQO zyuPzhOkaMXOERJ?k6DzPik_`hVl&jo22G~*=@Y?AMU`s zWdZXK-n;UgCc(Drc_2|P&BYQ4-D?I;Qg@@d2_kJ)7^{diAqIwDwXU^HcA7@;<)$w7 zD2LMeWC4C(eMO6G(L9o)fU(Y!DgVf9#C@@TJ&&8y%) zF*h>D&$VF;FbyTLodn^}2qF-Jr*eSKh693^!9_OWX@ zRffViw}#`^VHpd3UT^~QRan~~bMgt|?cV;rV@POZRb5jMtVODn4Dc@0CZEx&6zBtM z#U)ooQE3bTJMKWAbnNvPHR77A%+7DEMHazOw0`z#sF7=lslz0ns!lft7~B)ykRfvV z{`mQG<8t06F*q2Jm=XnzY+*2jK@~Fb3=a=4h%KvW+db2R^2hmdVr0tMq@rQm=Mw zmrqYAbFn{cIYI*ppom!ukqA=ZGC5ul$Qw4}{U_KsvsA6>Z9)oHcg%W7$O)ga*~zMF zO0?7JI)0OF_Q>Vy=665{ZGU^t3zA*ql<5;qHM@VmG3%P&pJg|k{6>{R?g%;{X4ac* z$GLFhUxA#ONm;qBTAw%K3@#=yvBb)I>y~qF`OlA=fmvkx%YD55&uz+|TwS=?nPzm} zQgpvgsr}53B!tIN+dC>3ek${>%=q#b9GbB*IX~@4zk=#@^V|8?q|%5B2V9L&GH=jO3a0{$sKqo> zqEkcJ#3%MH2H;#bGX6yi@VsdeGMj^g>{jjH(}WA?zxhZ_{nFnXByq3FNxOB@-;(-t;3;>!sU# zh9H8`U4)XQy9S=hs*IdM3<7E6xYkRCgr-ece|~p4%PA*VpM}JP2Hl)AI^Y`4@zJp=77X{qC%b;2ny=+%ni!|II5cCe zmsJDpM{lajvrKmh}abMdP;9`GN2H#1+! z<+>7^BkIXcgX56jE!W_>4Dv<%?-0F|MT6nTn`8ZWV<@L2WUjOK#ij>w*ztn|pQ~-W zNUX8`Y%p1ivqf}`-R!Eko?TNtaH}Ub;79%`c=0Ty5vr>Z4(~TDb)=ch&Q34i3p!dB zk-{@BPR@B9nTQ|Zab6DJ;d5$)agtd<_egONO9|bD*W>!jj;2ubeP{qs<6^~? zf5%}CQ}<9vEzBJpY&80YUvih!5dc9TaIstSdOyCZc_;b&nb{0D?4I*Tr7C4+S}El+1g+C-_gBZ#bANq}d^(5#gUUUjh;oG2lmU z4kYLLW_37PzII2Dj*f8}#CqGVgzjfv);puNQ&IjhPo<&il1p^;*dDQSJqUNn&ui4;Ybhn( zPD2DEQ*Yb*RcparTtnl6oj3T^UL#K#00+;&YCX!vB|p5tWP7ql71x}``eChgAk1rY`AYzh!Vnl7uY6;+3Jefgol8<)x7)es5UU;y2t4LMWE_-SE;6HO7y(Q|Qo*eE$)WD0qs+-wCr1+rn3z8IydStD{)%iyo|kz4KUJ*|7|D zkk{fxWK*``D9He#lo zb>`W(bNKRzqyZh4)BrgH5tCTqbG{bUu@O2MYPk3&*XiowgJM{U!*Odtl%O&?pq%GI z{#DK*|3Vp9pTD0K>ABu>?4aZt29xtr8JJA~TSYySKWq5)$vWNh?5ct{zc!KA7?#0Wh4 zzwa3Vd4-81ZQcKe36HW1Smpk83#pCB)l@TueEPd^ZisGR3SRK@Q+vWB^m#3t($!> zWPR%o2Vw{>&I4c#Zv-*=`@Tc*kaM(G1^>LV?w&v119V)0+vSf_f0PFP@$e$78UOt1 z3Y;3d@?0{(-%lj& zW$&C)mSvcUW=&n7lgl*Wpi_-E9bx8L#(0C|40WzxWIAh{Kx+N zuN}Ip=C&kdJOKAc3<3WkhA=*d*tg#IcO-%oNVETMd)K6I>p3H;b$=7yLyP*qZuY(U zSSJ5Lgc1k;evC{e4y;@+E|$L!@;?uaKlctEr0!R2kY9Bx(TM3kJ5+xFyi-<>|KIn< zQAg_jnZ)wX5!5*=0gF>$`M*AwK@nwEfOPw3yG;5*p4*fTBc6x#{}VwW{jbl=k{XBd zO!6PX!aokK|N70pKJ;b~ru&U{O+>Vrjp~LjLQf%&o2V{;WA^s;DgmVAEUP{#N#;`u z?Qgd8^K(fRm1+?5-s}PigBfkXP$7-$tE>1h?dARb*Turq4fU@q=gp=Yq_3_f*Y#W5 z+S)3bs|ha%fufGtG}821+tl2AVx=)JPvrqS1C#MXP-3D#KQK{Id-(vR5RR<>1(uAG zHuCb?C0On=IzryAOr9SdVabp5Zw@RSuX*rxYG_PnH)aW6pMKRP4M}({pIYedD&W=Z z;} z?y%gpdR3)81nV}o=(YEYuP)CjKAlTwTrBR~zMX6D(zmH6bQ_>Aw|3WvJ55~p8gQwB za?ZA4aKigKWCi@0&!RX!({ZOtSvO9g0*&h>ryHs3@oB-3Zwit<2h08^;lP(qp7KPnnYP zKd6&bPY+3S-m_3ZoqS#+@7|NYOF?)o3Z~Kcp^YGN2AT8GFP*_JXfnFNN+;4gtSeJ# zo*y62y@QS@DQqeRV)g-@+z3-_V)IStRE^23Vz!~P+(+J z66vI|2coEzm?`@0pMpuIOUrwZm##g*S(|g@j|8Vr0O2ZY^ucGNpj3*bWwK07${~Q* zD5O_8%gUxCH!BbyG*&|^+?!bAQ4#UnLHNAPrqx2N%HEs&bw^NKt!lxy!dPBcbhDYb zSgqj}gpkzLYy@!mTt&-fnHrg_E61m;Xgck7&?NjY1+0W(d69LIleho6aV|HwyHQ)` zlxMwlPUl-Nle>$FVLKiYuU}ov>ss~MGJfsz^*Ia>s6}ax`y(&Snc?FnxG=-Qx@oIv#T=E0W<9BxX0(tIYPLv(UC^ z#2R+|s;E);igw5bFFzCHKjl&P{(M!X`)irHS~MXU>Tsr^k>Y2Wx_(ql8@>5ERcBQ>KF*c0kcmb>ypm4X5(gpMNYjHTyDh~Sz%N;5WVHHr zT}ECqLp5oZF5amu5a-FIMsaXhN1(1xe`{(Qs;WL?gfSq{$AU34F$o7<@;$M18hs8f zO|;q#s^ApGI&|vMl>>s^8ycE5&_Wz}dwtQ{5ro5L@*D?;5}evbBM~|Y@QXA15H!tC zPMUNE67?Vvx!J6-kpR&nxb{(NbgAr1;*j?h6ZRGO*Jbva`$ziM)d#=Z&%5ge^Xar% z<*)j@eRv*&+2HzT#r$T~WQ&g?qjKa9uUWshp&*C(-KL_|l6|q+} zHaNvy=TbX8Ur-`lH*z#NOqi9;G`I~Hz@ek5nT5+WB-r#6cazMUkI=|sn1KySFg!j+ zbChw1myDN~F)}nq6Nfj`w?nh$WLgwGR=sVm?|Vzm*M47jAB*}S#I7(~x&J+@gsE1L zkwzc8FT~T@@yH%hxyN=+ugun)3;*cqAQ_pFFM)?rp3r5Jo_D{Xz#Jrp@&uar5!Aa&m($@=A~(@}v_AK7JPi#^1iBk3;xQS6GbYq5=pTlzgvi z1U25j&zxE!0j~C%M;l`g@XNL>;j32^7_-gV<%%g~i?k=GBw1Vl?8-=X{5Bz+dq3vk)pusd6;@FSx|CauW`_B;Yy!QjnD7w$)nC3eQAE)$*`pN05^8prWY%bO2ga zIeGw{lJ)j-G;K8}j-xk%j1r_Pv>vPsf?U?t@(;$2_;Ww+^J%u;GauN!`~7;2HI8O? zxx1CG3%x-MP4uqk9^YGu5YBz`daf>l_#UsGs{qHeauzB0kv9SkJA z5mOQNLYhj37!3^S6C_wRdmPIj-y!kH+>cNI9aunLUy>1hq;GM;YXMJO{Dt_)P_(IA zB=lbMl4i0;I6;;=Ii;V|XEOaD4@QpsqM|qz%L(!Br`Bc`u{>5fIXbAQs7su4q&D@l z-)BsO81o7XW#IX9a&o2zfIM+4T9juO0z$hi*v={dz3yX^4|UtoScts8(z!1%LM90> z2enub0vCxqXOiE()E_|z=Xlz@L=t%C3=9mqLCc!MUwL7*`cFk3w;(=^ryvAlMkR*y zI{g+{9-HsCtB>bn!&cjY=R~NBV1;a{^Sg2jcqgOTIV zS_w{%n^SPCRJxV`BbND9*Gpe^4jj{O6oOgsK>GboH%|i|>*RZM!@wt{?xB)*NQKp@gR}Uw@$lr7g_Qk3+=? zw8vx1?Usq2mR>Y8IhoR^*}InS+5TuS0`rOu&}ojddCrJ#mNSaOL;_{oPScxdVzbnia;ifb>Fnc^yHCJ}Ihfy*9g4yiEXw^(hIP=J>1s#ql z&F%QB+)&+K)r`FqcCPId{QhKKdASnHr*Mi2BPgC)rCH2FCi@en50~SDd$kda9uYzW zCMIYLhy|J4gp~%73oyA9Hv|E}NRawnSOJ2nG0-t)J^JG3MX5fF37pVlGC0imuE3}# z%u0+BmX?+i=;&nB26w@q5Kff+^KoA?hK#O<$kI)ZN5xyReII11tFM(-v}?fr(f){u zK6vO3xn>DnUd`0+PCFcMJ}fRL_SPRvAkTk_rclU3hB;k!qvg)Zx~+&v{Cp1)w{E83ZSIf@z0Npk|NMUO)7_Q)M`?3flsjF- zCzBH+S{FSfX3^N?MCnEHv17k#0};Vd5HtEk;K{1n{3+Wg?i+KH7z{b=q=U8BBg;R@ znOlrC^W0?LZw@f!aL}`>=Ow0cIw%jsZCcw1`W(q5;7Vg-M}KKfOCx{XuJu7P`pzys zGsxxhX34uu*p)Nwk+8wZQlgEacM(qsvECRDtnIvfWEp0Q>VXs2XREEC`h6rnf|`}} z#K#IYrCcI7Q4q9Bob%n%k(G@v*3MjMot{<)YmVK%?uU5%BXL=}_P|iL zy0&H-VcNhjPvn=gH#x$C)#u!i0)=JK71f1HA=*Y5niNdRT7T+-s@cMp1?4i-eZTm5 ze`$+EZ=LkzoH-zi#JU51-nfizwH%O;b9SH8&QV!HAf$rl7|QB2R8+B{p#?$a)$!~M z%<$C7Uw#mUpci8Mwupez4*=Ko7AA}sbOie0-H7nwjqbj@t51LBd-WJNy}4hYjlk~L znHS0V3hw!VA%W6<10b)Asowt>*ML*H=iajGqgM40i3$&bJ=x zt%X=7p7{#M>AS|^)8$75=CZ5B6Vml8!PcoyZseQqMc;gXU3B{lXP2@(lI-+46aw8r zk+jaNsh75~NjG|(h0*%bkgD*L<5053yBmB#c|VEgzE2tM zx1q1<20+K&XI~EEn%?pK6&w?=t0YGF=Bu@F$kYnmrVJGHen}epHg|G&eXw(eT4twk zLOED989?B}MRgZUOAyS3Nh|~<NqQ zax#DxrKro+K|E;X6#-t^2OB2w(AKYA69eKbC79i##K%9pUdNVOnp%!g^r}S}*{3rI zGFmonHK$#!l&sc1k?&@>KlALJXue9v=l!Iv?MVRnSy0jWiVOW#RK)3l!iu& z)r3^b2u4~yrO-r8kISK)okjYY4n1AJn38%;)|xVQi$k+!@0^0@!JO$sKHA`4n#O>r zhVHRB06hvdbxjQUcy*95*j$~s0cb#AF}eb)iwFtNyQ5p4w0Ymb63~3Ys6TIo+R!$K z1nCFUXlXiKN~e|N*G>f^RsDr~q^PsGx!xRgv6UN}C>U}YY~a6jQt*{HIyx$|n&XBJ z;-U+Z8$4c0L|m~!aPwbq`)M2cs)UnaS+&y~6V1%pdgAuo8(pg1umiu1y@RmZJ=zl- zFGP{Rr?C>RT;hnRrA->Z8O*OJc|Pig(BdkH(Wi)w45ka;GkK!pJqhu8wkWZs`HT$$ zPaQ%v8A#e5A6cruL71`<0>3qolRFgBI>$;o7aS7_;tLPl$EK!r1y>$gFgjqO*hKAy zW18odx>(BQ4&Tac({68Y&Jv7Nygzw2GYf=f0&LF-F{&U_$ zi$aZK{T&telEj-YHL(Z68_)i!u0cD{ED3t?Of4CUjH$H=&n=Syv6=F8qYf@+lla*oOjC{C!=+$8)So0!Z(Hi`%_)f)?=WMc&&m4cezvcyC z2eis&Nk~#gW|X#f$)=E`*xLu{da*y2uQ~~))Z+MEPZ~R0ZG$bH7zxAnN;;anR`6#A zS3JQ!1AC1B^x!A6v0^qKNzUW3LM-S{j6jny5N4_*JqH60Qig^@pSSlnC&$Y{4BL^$ zpqge_YD$L{`SXQH9rkdQf1aIQL17_d$Y-&R5|5891WE1fPPOiHQgj~5Dhuf}Jop?q z7_97r>&RELpJwc|=ukv8tF7kp&lF8g(f-3+8I){c%7P^JQ2rE;NS$pBrvMLWcb26U z{U9b9-s3Q&8MnpnQ7Chq$;q~kgdH?#zX$k#m3ZEYJFicvthN=^SJd46^n;M|@~RzZ zMy~AolF&YLyXteEDqVR7M&Js8fxQ*P9Lkf0CFbGaWN^FUZ5<$&s|yn%iKm80xDBS0 zbVz0fqI+6@zA-h~8D3i~Wo@Y6q6vTTUSXtgq(&3k5tkNM|9pZ?I>Q-#q}7Gt!aP?& zR=PfVyjsH5vBc;(!JF^H)CRxnnw@2pT&tgtRmHojL;2i?$42rBfUQdZW8WQ=)|7mX}B7)w3Pha8`3;AY+O(dGk`(k4YAuXQE4Tj(CQN!(TqAN!|u-KnzFu;3}tXwUYrQ3wZ z?D?Ytcf3y=ejtrs$Ex}EQ;|&w;`K<{U3P*1h)GsCUb;EyWSf&%nrGV=Kd@b_HW#|q z%z~@yMm=OYwek#@3aD!;_eVTjp8J{D&vHt=1!h3GEJF}>e~k2t569N`7aZ%P%Wyl8 zU}l+|HhZz>3ib|=7yOurbuNiI=q)XbxcSQ)Ga{e$NIFCKqJ zpBS9X_R|y=@~Pb0QU}gR^7a8~tF%<(@D17&?)9vl(yk`*($#+uiUN_(hEbxdS0j ztNySkXbaKp<)P`L&4t^)5V6yEB99?K1BaU5qRRq+1e;I)scP%g9AaT76CgOedH2= zU>Nmv$ACye&-q>&D3RD;(|F?e!sK-EWhY8wRk8NSr&7DNLkU-1uV%1FCn*gn80BD{ zPR)6h1HL1$f4HFJPUOV1i|epNH=9Cea{`}Xoo5X(IaN35_&)QcL90qQ`Pf)d?a*z& z(k(!T=SZ)`^TsA4$S3_JafS{Ndj0}cQ;01xj^az)KmmPj>|E!LfZviX20si$A4yAz zc#WTf*kJ^iNw_D!+-6W(5n7v9%P*s)QQo;+rSRYJUt8v#doBH~IgZ>9sXKa70p;{O z8pawUAp(=Wz;4;l!K$H825;8WMJV2q2!oC|MejOw33h({t=?_vjFV8B4=NS{7msXO zq{Wpbg17(i(Gl~lTjo@W{PzNLu20!0#)q6lXxmxVVPRoIaCgGaF3#IEIrqn2KrpjY zAzoLDX;yV=BnPIiljRm-(_)YBVBm!H^z`rweuE)$Mk%UWlR?kZIR#`q(WI=*On|nl z1PSZc;VSP6Eh1I=h7%YBlp-53>Iq{~zJ4v{dkN0PObw|JEg3TO589YwyMF0Y(S~@v zIB$Cb;pqhu`;4ED9?>5jhPCm-jg%b=W`D%j0AEDnWyo_s> zPOAWl($B$t`=Z`k__{hA_Cf@ISQdXdCr!IS3I=)`Plc-|AhH+SuMXZ)uwJeYJt*2OdXY zgGMqK`_0{&amtmyb4 z-wex8ROHlAah(0_U4EN(%^#JUk(1JK{c#|%TCqRYcri;Kgfqahw?|4TmpX(;xLU)< z!pQx5i>ZjR>f@!*!vq1*$3|tZxPIbSnIURL37^AuG8c(fMPs1V`;Q-!-=5~wv;GK% zeFK*S){-CixPgH*4keYJGt~!5rr(TXXH33*FN~!-u$<7~b!N%ynR6@|$+=Kcd}`S0 z!&NqlzXB2}WoK zVef))g8D?e)QrS9kyrRNrHP%wlKdw@K)ez|JRKLcl6cd904q6t$X5|9Z(x1rD8#lG z5QO%#Wy6{@a}E>gTCWKc(!@hknI{r7NfJ8IuVCBpepv8)eA&ifuun|=h$9iR{cEV0 z?z}vU@9^;ODv$w;Zs{5KCl86>ycOHiNAUcCF%N$$BO>xSwnI<=`PypoM{6)t-t-5u zp}m3-5>t$55cZaNfOguyExJE3g5FcG!i?8-b%Ei6ISlf>KsL`31e`%0hPC5!->fhd z?F0!3to{kwP1vz;y01nco&JP%d}?#t4_0oSA;xBO#1>0fdeg0@Ph#{=khd7Bord0C zUQINUO9Fo`Z%fyV#z8JLCCV`ennl`%G}F+i1&_1JIXflziP-FZksh6$b|{%cKM-+E zfe0Cv^kz=G?tKT^*LS*!n({Bd;bP(AlfwdRI)Q6)oysLN#^A>?K`#GtKQovbY<9)b ztEIOF;Ev=0qlYuI`MUj{4rsBoPb4SwFB?^R`QDqRDR*9S85L&MXKLA zT`4w3k5+Dv0t!VTA>}ExX@sCUvdb|!&YqILb&TxZanGeRsGoR=O)P2D*7P!J>-*<6 zZ4TYLHoKE+dSwYmoo0GUqSc*z*z6;_((h{Q1XSToD9n4WRw6u3$`O%}%+BS-TmrYu z?SRdemL=6Tt}Q^mn|&m0LxZotxqfx6pWz1_=lvD_@^XmFG!2Ieqzk^;<&S zEHXQhuKR{wJyD}VK5xhyLRPhy4#V3&0=4CHcM0X{FRv`&x4j7teKC;ITfOV>?%%Rq z0!Oa;WqCQt%M1qPpKC^kC>YUwV2GeHXgrd8_mneW$%y)?yuWq)(&vwZ5=H=l9ZE;{ zVVNZICMopN*3d8y9fPP#Olxl&0lWsUPq3xy?(Y1_gw&U;bo%3=Eb+73BYYz{l9g^k z*0ORS?>(7j40s|MbqJrSigicQ4JUN<)JI6-NZ9Pzxv(#>z~}n0Z&GvO!-c%R7-uEF)bX{W=`5kYXjU`%!^G(Jdvv=#G{{j9#lp-q_i5Pk6jrlg zG|Q9T+c>sosFwXc?O@56*xw4u85~ z3Qa}>WRM)~%`i!U>^;nJ)PUP<^>f43^o$E-k#ARR8)FfAD-r&T>J|+PnP}devx}3I zzEYH1g=O{bY^D6jcoE@^H^_hgtbv717aOTw{P|MQa5Ugc=-1KKsk_?%2g4tLdsOHC z4bMRXGdkv~rgFipGe(8er>r?c8$vL*yu_`>oaJLEshlhm@?<1up8r6+zU?k0wA**OfP3+5bZ;y)wtwyi2V$3O{MDxULO)YX0fh>Ogw$QjRN~)#524QUjFS z+s@Cs?h?u`LC_{?ZT1q5Kq*q6F@$yabOBiGV}K8NC$QA3l*|V+zB3f&k&m69D22;P zpcqov<6XGWC8YE^< zP(R@i!zdttEXnX~&L3{Lds|QwL8%&Zrv~VK*o2YGWnsG5nL`v7UNSu;?;_4XBsy|B z-<`s{5yUk4O-qTxGC7ey!}01aBfj9g{h9pcB3g(y)yv1iSs9olZP5${h#9)9nR>`* zyr+Z0Wk60^w72r@4-^8G;MK4+|A4Nz34O8}$H(`&)QexfFwSH}WT={Fab4=-ksV}) z(A(R*e0zC$xw(yw{4;|dGxTJAU3rgItzOrDsvI?Xh!=K>N>)&^BlE z{H<=M&|H?x8`ShP$>UkiEa||ndg3D z3hk?=dNCHmPNlRhYb=DH?|)dGV6k~0lBH|M1aO7A^Un5(kMdpKq@hj;RTiZrwys#R z6P?rz_>#~xsc5|l)I#5U&ggi;8^B=A7dy|dPO5W17I0NA|GY-G1qd+k)vPy-F%`rX ze1g_f_X)Az5Sv$6-3hFuRlK0 z5^B6)?qqNJT`}(j`NTuyDtXTT7o;GvO5V-ee8+<#6GDs>%R4(4mR$g#R}%wxPN^MFAiMaCxq`!rxd70`UhI5rZ_ zR}c8DWqw(iA}Y}oyufd9GF0S~t;4Wt96=%PoZw(I_xX3vC}05dV<5Wn%0E5n1x#Ix z>_e5Q8WA|Qm||gxX@1C5sv|fkY;5%E+?5p{`UMls;))I;ZOI`YE;8*;>g88}GT$DK z=1W=V4Q|LH#(zM%^0HAoQ3+F_a3sMLYxfP z`@4hV3(xxtJQzIf!GCj5UkXu1!U~(XSbB?8LWnWfe~OBVN-8Qw${qab?;n5S7YWLf z*baRQiTcV3xG_TibFbo#O_cvU{ZgOWKm6NJys%Bq!cFrBjt4o}ziyc*A%DYkb!$xU z|9OyZL0_eo!uo%pC6Q-%e{)g)g*f2=3)9-4c;D*kAE4C6E-t(BKcHVoP=xYA*{{yO z`7aUlG8eCosU4Vqo(X}zDopMlTnP{7|6sT>nYu^^IdJ~i9>UB&u&-9HQw=A;-ckHb zSef*x@wPnF;{N+4Yw|Y(25i8wAs;yYfDz}8lX;OJ_Wr+a|HUTaGh1BIHT?57ZDKF> z2@?PPJb!Xvtm}w*UQbkA{vZPXU=Hr^72PlpU&iVx$tV^{y~%f6H(%2zsW>fkiPVt}*c zf^de4C(WZ5c(Om*Jza|cPJN+gWDlNfpy$;67iU+zQT1r*cvrreem-@-%GjjPlHXpi z={)RJc5TtfIa&mWx^#1ALY}S_0GG+~^Z&4-|AmC1$_SQiukZe`yEzmGJIwwh*8XH3 zS9DvJ@3}yQ(7z8d6To0v88$+JC+Y9q@#kA)qN$nWpq~Pr`sdit@81^0HpYPa=YRe@ z+H9HZf5nXb36=s>)rbCn@@;rH@UeFTwSPVs$^Y7!{@5B-+kbF`nYK*ewMzZ3*Q#%| z>7t>0GjPYkP4mwS1}v=Af3vWEZax!-VrK~0{C|kYKaagX-^oAjMQV5a=AX9@e8ipp z^%2MRe*N!{xLtguFl|2}j2$kcMcTsgKa_dmOHeA>J~8nx85HziGAQ|yimFObUr=xw zKXCmo?rxC%0%WY}i=eL8*+rGIiBs!YonvDkW~K-57gDuTmqBSjUa931qO7Ngp&(j*bsdpjrLJ+1Zq~U{((hSe|aoU-29Q ze^^h{>x8Bpm9Wd)Tx=l7Vd{E&jV&&l`gW?K&7|V;Hs+S>G3$RhFSfdE7`SQF ze~Y!aLeVszy6nvqV5!5iJ7E+$)xS?TBCZ+hF=AYw&@|JFzjC+ER=hr$YS2k-Gt~gf z&1lwDySlVT`fqRHnR_}q&ha>om^NSuW;SX1{4o1r*EdY|HX}oe3Ac8dX+hX`QZKTX z{D}2Blg_Q-?Wud`&vRj%RrC8A!NeJE%K_E2q@;r1o2o-yr!3mOx3ya;K!=AE27$U!m04`TeGLi1c7*)QFD#5r;ko#Qq~R#3 zHbp_uH@qn+FVAGjH&X!=PhY}@o?%S8U36U=_FnT;KzX=d_Y-$~2k|U&a2^_)sL#Vg z16*-r?ffnB=!9?IJPVdj~JRT2#$9*p!n~2?b2sxAb%vNja%- z!*$gGa78y6PqhaIH_$kKOD9RWG(HA4HV5!*6&>v&zu@pUq_HK8loPdyRX&V$N3>BI zfTH1?>}(l^@FFu>c!3v{A$G+TQhdBBRl@=GX;g1GW1u(4}oSHesgKpyyq(8JxwEzu1a%DMSZ#F zjqso0J|$NBI>gKYWTaVb#cpX)F^!%shp-9S>N~c^z_R+Yb0B?5zM@F za_jPvV=!Z?2;Q$h!cdXEeIIs`v(A|Yur}C@>1l2*+vQ+@I$_tUDv&;T5>nN;B}Q@> z1(L24LJwCRcW(zzk2aM6*;j_oZLj&Om&U?XV+JG)Ty9G@*4$Bnxfc?-%JbJZ_79ZD zSo^E12#uWDjx%<(vz}`Gsay;JVabC$Xe`FEQ4IX{VeK7aJ58&c2HE5ZQGJmVCkD3! z1!uM88^>!S!d<7KYakzb+^w=d62w_myYhB+j-o{~dI{a#RXiX%_Cq}Ehj`Glu#G}A zMa^0#B<%ALNxf|VXx#b!?R#)+d_*jI0`#j?jtdS+g!eV&Ut9S@&?^kx+=9_{iQE?D zc-I*;sls`4Z)c{bDJXfgnl7OMYytsZEL@1VRNmfqE-HkMOAOf0B^7kN$P@1fa7;IM zOfA~ugB}2&9$}1m%PU9ETBlNp^IfiQQ+}rFzwgF52xE75(V$-SFGzk2d+(;r^PwD` z4Y#1du{p>VT~#hgnd7mlR$NayLlLCDqQq_G+a^LG85QdDSF7>QKa88LV-N@BjW?(` z2nQKm5j(Nau)G^yCS`rL(~oj;_s9juHUx_#7&Xaj zI(>OR&e5ZNlIUw3c)CFz@$DOO0t+DTYCIc1`#l1}l+xXqi~P|E4k@r=>ULIu@$1x- zE774BlCK}Ww*q>(=jXK(xl|R^i}w-}BMq)DVM4pUiUCD4f?tIx0zNivJOy>WB;Jz8 zzTd=}W3#6q-`%PgLZUZV1e>SFO~{{SiUi>=HfZt>pdF$E$tR!@l60Q0xU}}XXxN=^ z)XDRk^IRYRBup{922iN15*Ymm?2DSKzjzRt9TwlHvaBdnT$k$St)6kr$K<8Xr*~Zh z5bckeI!ed&#jW*X2c|JFM2bICoU|PZ+9f*O0ewo{ouF{0C-06Nqz8kMBi`N&@-jP^ zRUtfjH2q*JQZlQncLhL)j4wt>!&PjwY&cK*Gp$@MM^fKU=et{pTPMT4*1tUOuH>h? zfPb*t7h|5ndEJ_rocu7hfl&+-aimdEpUhxslohDHzYS;&Tt-S=p2|cR-4UB_^ox$H zWyCjQ6n+8JpQGg<$9xg{scq~dlDA#4(Y{CJ&gH z<8$l>Y1EgYbsopPsFf~xb1yhbpnJyH_L~ki<#IWu?9$z5XP%z-FfNcQ5?1gT(dop# z3irHSiz>S;x>(yBib`Y;F%{>my8qpUlT(``nwdpP&cxJzDwqnuwk#WOHuH7XuffQ1 zdpv{HyD|UM48`$yBq%hY$+b7u@_65s2$Y)saS@e89 z3m{34A|#?7(i1GR5X+@aPWtvYN>6X>dzC6{MuFO3`coRfK9c=_9RhHe^#+T%I_W&A z1C9xP;1j4SiHy-JqBFnWXm|;e=w)+(*!m@Uw6&!l^zY=<<;vwf);;`8`&AJ#q^zb! zR$4mr6c;!5dMHFViHw4P(gI=JCL{Q=L#48ot5!wxd*ruG3E6v!u0ZZP( zP83b+!k&KVF0Q5J>k&%(wfNx_C8Jal)su8iT|Thi%?Mw7Q$zD#QYaAPz~`lS@#4e! zr1-Vt&H>yMwP=T-OZCeUmmVgn!(jco`BR$sNN*2Br99K!MNV-6q%H<#11vA$MI_5G z55(KI52B@yD9EQ1`J+zIBE$rCs`Fs4pyseRY*oU1+^fD?%vNlf+U>3SLhtzQMVJ)k zb-j6brOHfUcnb0s6?Nz%W@d=OF7CmB@jMYM{`ECk%gPp$YWLKPo5+*2yIxgf=RsW} zHnrx^M1CjF21IZ38+IUz z#!y@hHd$$_Q&00-kZ(NGaI=i;k z52r5+0S8sp_6ZJZ6jbzuS*9){&vV3zZr0PIqj6%)A(5<+FW_$-C%FXwGN<^V@i&mA zJ#i~dHE(MZ7Dsa%Bp$ssHQN~^4o4jS>C48czrpPs$tT9Nxj)aBZ*4UaoUtPqlGa~L zn9p`iQsb-JFVT_wF5p{cv82@ZZSv+qbvf)PLk8{CrBFA|~d~0wYpQJ}=x*``0mO*ZK(eu^Q>GkhQJ=W3k0hyjZ?= z6y%Zi2bq(Rt}lDFaW3(1_UDfUSBlH>aP3Q>J!-lFNwJCK7@k{%DNnrw+H<61CJ<7# zI*D(IMx<=t1yguyBx+Q`>?&+RFcF0KKhu(Aenn(!vq{dX;rDsO+3)J&Pq5+czRqcl zrEzL7eL3W+?dD@%7 zwON*Dq$TQ>edv|`9v9>EmwCqXv1vCRQE%^VTzZbw67L+g{Mw5Ms--QuM^ZAAm=bKhHwHn4BF8T5d{E&XXl$*tS@6= zx6~Kl$GNTd<)Ud@272-{GzH-e?xl+D8rX1 zJ+A%W)@{ic1w)5gW4SyOMBd3y7n?w4a4a!Rk_@Kt;pw#TM??ZB%JlWK9t;z8%pats zld!48S~c-_g|D&g-_-cJLH+Qr@J~0YTKI-USe%lRY*G6|s#c~9Rc-b0H#qN(s%;v* z9z7Z6YsEfoMIInT!!tX)9DoyP)3f+On;8^mW^lhHME$*RL}(Csw_W^mu+s@n)hr1=BJHfv?a!?r>h{eMQ$D$X9Hp#JMrc3n$-roIQdC+rfmp7hoOXmvjcS>}e zKQ{kq7Z7juS?0APhm7oT<2pTDEbYbld2DFE9G#*}=n%U#fdxbcUib}xo}y~$%(R;+e&25kCjPZo(4%`8{uFHX=U4ci zp8R_O3j97MnWgfst?x|{$ZV49F=$@y8qo)WU{%h*jV#(Z%Q#`soD7HoeC!85wshlv zf*-q}>h2$2KEg?FyDE z10~2LSn24rW7iC~-+WBNABa1i_HWfar+bXc?~6)hZ;lkUCKj=@7XSZm1U)_UtV02rp6&PH6ZFYzi~pJ}$7GGF9k)TWn!6 z{-OQ{UOex!4!%8b4Ip&++o=iBr!4BD{ge}}@WGm`L(4}h=y2j&$!30KOyP{J*0JW< z?2JnHALD~`H$iR91l}&QtgTNbK@}ki+F`l71Ev||H6^8qXV{p5vs{iwROK~_@j(ae zGZ>$i7J*tYqF4irdJHa$kx5ktD5C*#Q|*Wc+!8pt*pThFM}a<#nhAc1`w71LQ2#R} zyoU)a$OOsYt&^K)^jm&;4duisYTv6)(Ly{Ovi#QV&zw8J*R1wXSgN=i>Kk>$zRL z>;@l8{pUAZY>T}gLvB94Xa&=La`x9QKNu@acf!MowMhB6xZbJAzG3pjcsP~0HMXGa1)K*Vb5=eG_vgTXz+g z78WPskFZ%9ET9==IXyv1dAuewL?Ic962+w^$xPvFv*nKP#a~W;LMEo)3i^6`6VJ`_ z2JQFdp_`I@0`xXVa%xSbB(PP<2X^o$;bNYtVUGQB`H8fHZSx5gajzKM$>=i<<+WPNy~k=*7T%u|f+|7#k5VWhPY1grW^UV}HP73(G7LUsq(4`I zoq9{M@yEASsX(^#HdZ|JO#HZ%C=wly--K$Fc3+FR&t^|bdTLK_9Hg>tKjPj}BG#UV z;0HjS!Sw*lqU;k?ac{sD9s$RqK!q+Qh6YDkN-DGAcv=I5yhu_$f&fVuBmLvSYEYwP za=w0bW=`Ic%)+pWqph}tz5;hj7e5ZdH-bj9+3M9+eymA+h?XH91|7$u>ejRX8K0kR z=muuK%HPeirt+$wFE3gXj=YtRmE96w=e^8&{$yrn^+T}`MDAf~uinqzI zUtH{~)ToKr-iDtBwIonn7%qO4T)G^Whnuyy<0_{;TF0mQ#=}rMwy#fOR3<%ipO8!G zJ;{L86q$ppCHI{9t&izb!qt-I078U>KBh1MtULG3q{JDX)%Sw6@5eZ#qb?JE=x~&2 z0uu5^rg9Y#9~sWC@8s-nRo9L3B-{+Tzb%N-eg76G%M)r2V?lbz+8h+VNIc@nFeLgc z{E0!LVppj7IPF8i_JNQ!*b%RXp2^Y-G_x+>Z4(^{x}mI z8Lkda+uv`JlzkQ#AKcWCh;p9W9+X;}&Doe9W#t*TpS}kD1gPyChudg;#(McMn2(vr zt|>uZfsl|8IVYzo2Z9$U8L~%xLXey^J30By!M8t|E2}jPh-=*M23mV||3Wb;ySGHV z`q5w!M^jMH9}f!BBFZ_BKqzM1+UKs^uQ9e#uD8vyB;_OrTXORP@^HTyC2pKNta#Qf(eonSZ|XDt$Qkn9VnVj^ zM?eZpSV2Ssuh8`e`IXmrqy3v z8W&74pFf!u$uF@U4Ss<~5Krj4!bMIc;pXm6F;d}>$`wFbfX(LhVA-0f+KUBe?M1H) zMD=lD%q;f8Arvo;_vfG4?S9NpenT5KyzK&gEYyOSz~cZds$oapgZ!VZVUN~p&x;AaqN7H4j0{tdkx0S0HJom|l6^)8 z^BIOO*GaGN3wO%a7B#nWa$*t%-}U2id&`tN-$WxQmZ#gn1x)_ zwcfd%+e3#hj?TxEC{0Zz*B!C4gVa==@y?2{VSe%3_k&3j94-tV(K*bZmg8KGH=%(# zG1ZDb{XVEgdgzVXfnNjN*nT9r9uM7l_CG#%Es^g&)h23d}wT_6lL}N{Ec< zQc_akqtWCkZwB>J0fF_yV*bWEI!0?*bec-g|ASJL=}8rOqxn~E0n>cRNKB%Ft`%5_ zca`agtD>U1#~L~_sEu|3bp>nvXXXY*^Y5Xd0`<#IU4FQPWagQTSxWTD41?3stMSRZ zXpQ<)dh}>8I6V>{x@@f$Y_PmN9tm<>S1{V)@55Cmwo=0-AeZIj-*M&Jj2kMqZv6nG%K45+VE^I#~P&r^Ifv-`A{~eP&`}pN`2|hI)jx zmmHD$9mlu^`GGq#8q9Ka4cjM*UIL7%YZpeE;LXJPx{V};n6h2J_IMg z>4C*5b}lKR`V9!6Og%$K;S9!_j(=&`ozogItFrW3k_sBxy*Kz=s9vcW%b@Y?mdhut zXx$p6)dRuDW&~5eD|1SQS%7qdbR*K;UDDlMcd)!P$hY~Az2w^$SQ4^Kh;H#$ zTzbCfGf~`UTo%DmTs>cqoZO0Es@ln-PP<2@RA9mhc36rhgdkW1 zdEq@w;uzTAO_!IFlA0h5LW4y?7p`>L?^}7=5){&WJ0rDcD$kCuTfa&mrNIM`M#OtP zw>F6knIGeX5h1ATvy$FNPp3#As45P`S{-Tiwux@8rp2&3K_w)ccPT8Dhc+J5-sUc+ zSvvSu{ag654R1jEKjYhX4b*2kR?fld0>V!lwwJhgS2>CXF9kDaU0vUB7+YWBd5hl8 zCA-#5o2faZim>g4ydPRazdNuBK*3Sy|l6JbQvsK^#7Puo97IAcow&r z+w(?czsIo_zYv<aQp44*Qf60H=eFf==f4w6ig$Qx>t%a&vM9SNhoA^}KoX_i%Jc4@^=xOYd#Um$GaC6F>xWc``4n zA8v>Akx>bQWVjCKXIkgyb%qriQD&F`F_9$d&lH3ljPY!ZgSV|jY@c5f#^0lLK1?~0 z(!nk@65n| zOsUICcRl-l=N$h0>i;xh)x+R&ypLY|F}n@KwJ#a^V*>mqNe1AFdP+-nJx`&1YQM+H zdb{6Q0~~n%hkwCOVhr9oed;sUFKfY$guRnhF|2BQLdf#;2Uz70t4|Gi8==~HJ z;ln?eoj(W4OCOqk-0=zgez!doKR@jBR=4~fE&un)e8HcokH4T!|1rF_BeXvC+r5MP z?MDCWgNM*^G0W|0ale|;q?=AoWpk=lNY7Go?qv7qGSx5`o;wkjsd&?OFxd+)ilQ!_xn8~Rg&HBjp>TEipx?8H?Kd0 z17rI23b@Zw0}V8@Rt+_{ScfJj>47FP8Z1G9K`{)lX&#`WK4M{EnP!mK!aO-U+u8yT zepH~Nf3K1%EGz^&-SkSCa$z7n^)K<4aQ9NPFc1scp6~0@v#`Xht{OsKy?q;*o}Rvb zc6f5~7#|;h7E1VUw35U(7_meqjf##ZR&^9bb%$T;t`ECagnw0o;IHh97k)_Y+pcbI zK#TJdMDwUv>W{@o~%K0x4%DpWSN5Ul`vk&r7-spw*PRe=0%p zNOnJz0qo5zB*^xo(olLJD5iA*mgjh+y(0lgVuhmuBd#A4XM6nnV5s|&8 zD2xdp1s`6`-)ZZ7cfYW`n7_O7>;|_%tzOn2W?0tGCBuGGyf{}a{Vq8sCns$IQlUHd zUEaNln%!wvb9UbuDBStEwtuw-#Mk?fzt+)#0-u{1D>9)l(07iEGpUzJixdJ2ZOW}iNC z-nA=-thr7@8NLZZF6~_wypTE9BN7uC@5Rd4*!Q@?k&hVKAs;bIU6^$m@*Uhmo9zyl zWgcK)jD1v4R*wGJ+A0H#elsp>NjPL=MPA>$z2P7v+IEXS5a}5hhT}!d#tTRH@JUDt z$~{;6p+$t!v2e=3VD9jF|2x>#{`R1@HZiAc}V#kM0*8Ld=&&$mRI}0mAwi zRjKs)`r6)A8I;Ej_sEM!fJ^WSNb{scML!l2A*t4*HdE#=`@L%^COehFdgw(}hm;qf z3r)@Q(e>1Sw0LrQCRP0VS|@VD3xNR_g{-cwmpdrr9X@A#^V%DES(+S!-B0oY> zsw-B>Y&YqqT7<4!xXBGq#7($Vb;1KfrTMZNu_de zapAw|?n^F!2LskN4DUDMKxI8C(g9bhaCZONW;r5-@=*GzzI7y{|31^g0*tNOg&&&% z1^mIuqEeZ^IC)k@h4SgnG#!9O3^JyGoh~r+70y2K+}CzQ=}QU5ocms1uN9w=z@>zO zg#z#(K!v)60bJ}MQ(~t?BH4R-P&~s=H#=P3#f|laSbu!Lq2uhoHZ|}j_m6@kgToDwy;1fQn z2XM}el9GciGngx#I_Ebc?YF8g(3*dzxIRn5Dqp$o)t@cjo6b#Cx}%xEMMK>CLo5_Y zO*ppCKu4a`i;VFk8AN!|eBf!DKUS-_hYg)%BS`lY>nnY@^I6G~At`yL7kg~s}Q zZ31o>tcw&?RkP!yoC9wF2FD(eO&|65lSF0RV8`t}DBkdnnAchqUNk2sM-eE{LD?b< z^hURoU%$3C$i>gJqmVV)7|MvB^oeRKemF@7bx$M1#(KVBd>?S`0q&}CdVNp>CsO?y z6f_C}wcTf+RU9>2>$GKighJj6DqrmE?1gd~3D-bgW;b^T#viXM?)gmritJftrgw-| zTZ#EQ*VImd+YQ)4piDT`4m~Z@p61{j`=Ix28L)9>0bgy0aLr+Tsm1niSm~Y_h(pTQ zJ;w6*F6GIcmib(rnzri(jfsiL;D#E?I#?&MyKFznG}q-P$TXx__d$mx$_PY~Mn%;9~pktWNn^3^`SosaelN+Lt05|9N;Lr=7kNw_=sLNi+qyuskZoL#S zUW+RkR=WR>duP89qLPXE4xbXU&fUti;_!&>e}CM#>}BzwdjfTz1ozIN%=E51k4-w9 z1pB4NfSu_|GZ?VRU})HNyfIuJjOopR(w*{|WAlz&2?dq}__$|D5uCxQUXE1m=DBhh zNoIJeC6>1c3O7X_3T#?-_S2+WKNADhQqpG1_b|pNf8U|6 zGR#BM!wdx$JD{KQOlZ}vhbDdSo5il4nVpkH!r7^ehFJn95S*c}7N!;4^c?H}8vcY9`D5E(;MdZ^+PkvyG5*pqt5bZJgaRq-$QQQ~R@Z=ZtUP^q!Yp^(Mmk zo5SEf-(}USwH#KCxk5&G$En%t{Ih>ps}6+PoefHbjhrR}VSz|cR>LUdIJP0ZzYZxz z!#OA`ArIlwd2=no{De1NpeDU_dwSYwayv^wYmtBQMcsbw@gXZ&dlAa1L>!zy|5M%u z8>Z!*9Y}`A9>-cAKj={qv{$)PRz+og6uLQ@?+j3A&dK0d}BUj62^}UQ)Uq?B>+>Zdltge73^Px&veF*`- z45#NfiGUK!0ATLeJ?9u@WMo2{KEgm6fOVExD>uA=Y$qBB9c6A?DIv*{D$k$iGitI< zRHkRrd?^a4JY~AVBo3>byA-{OjvnKlp0mHdi&KMrYe0V^udbd11;Y$TcQq((WTCTk zf+}xDW@aBqcltNMc*@AjhtkNdc9)s(O|8Oa_727feqS`W53#*f8UM?f_~Z!_Lo`by zkjB08OnwTq9-wByS`Fer!sphXHu^(kEi96b&or(S7Yq?U4ltuE5Z9?vNIhg&`S8xC z%<;G*U4|Klbb%_M^cM{ay&|R0wSK8fUtvkT?8BZ0GAMmiT0AXi_>YLf7rkr$0xt?g-eMF#f|_xegU4qpW)fMM zyC*r;R`$al4VlR+|C6VSgM~SzX{P`btPWtLj5u-1A6x57?v7FDMYM5J2HTOZdlm#Z*U{V{br4Q!*TBg5Y%t|X zUk+%NUOEtI0bVpaUNZJxJ*IBRGHeXMMhlM?B4^E0)dzEl^>eS!8JA37zK5=t4 zOQEK=!9M`9IudibNG}i(TQed5&d3pnr=Y9Rf@oG0zK*-N$IUYIuk;&B<7G6lh=+RS zs-f8c02myLaq?RqL?tDqPKvCL_v<_j1w%ZOX{+g5HcE-ZeetvPr0bLv(doQ(N!_oO zPEH|)V%y+mtIgK#G>K3xF8GEb57rAB9?m`q0AChI;o-I*ca>iid)Jp(O`gEh$Z~Id zBq=iYxPqr=DT)*v9-r};ehD7Uad~)g7A7gl#?zS_22BA%Gavs)s15PctI3Xon9QaN#`Krt8k4?ur2+Y85<%u<0X3 z1N9HS=dlOWndcZQOB4DKdy2SKMT3{{Yd1zM|Hh6j}py6OT3j&M0 zHwJ;D<2)T<-{@AdC$W4*A37Kq1PQmXX{)O<&t>+50Rb-AF!JDflfAbZN0yAfM3wox zSA#*(g-{~vjuwSg{Y~mAPc~v?QWCS8nn{JqV9*cTSiQ`>xl)6Kx~n;5RFmX94ujEo9R1=-RAQNV8yt=Vd^vF@9 zq-vp|w_!aBDs*&7(E+5OWjU7u3FNEJ(nN&bzUDQVMK69D1`gV{N6r}d%F+%>2_uz` zT@^~LL&HvL;PdLVaLHlkVtby}WA^-}zIV%;nucBVx*ix)0|!6FQ!~fE^NoLgJGZOC zt)sw`^o(2Zy@b!}n0=t)D|OgnPI?w3$0JWibLqbQik4gsUzC-S#(}jMEalX43Uh{Y z;Ihwr7{3ga%DOK4^DTshE%6vlsHOJ4iG1A5i71@EbP5>+6K+ywkcvrJ0OOWv1hV!-!tc?rd%zoj_D>|zintpmAS*Pe|9pk*=mmnwrii-X{Z$8 zSz;WV3@rrKns6vMsXRD5z|~Q3+SuBQ@y?YjxB}3yte3eNS#~8 zfe`SqcOqj!80~kmONhC+!|AbUJ-I${eeqRfUBzDhHt##eHI`AcgAG{b1Ww98R0o^T zHd-N_O*me|#OGuF-w4~w-re2vsb7i4?tR_B|5scs(OP$4)Zrvo5Cql&kkU_WyFMWm?4P`U2mJ^bJiX7~VnQ-npF6GyW6 z;@Y9Va>3T{z*OoaFUo1+)0}A3$0v$|yad-``k ziQ|$9C@xm3d!fnW`J{Di81wLmP_jfQ6ZkEt)zDy{JND!Udb>hjRA-)BzqH3Y9}6o= z%68RfFus9b0f?}(!eV-P)@eSf1IxMGmC%t|cFn|xsZcE)4($3u&Wn9u8y_W+>7l>mK^=jU^}O*6kSt}Lsxb3KtB z;L*!D9UTs*8R?hx5n^$7SG?UHeB(0c{u5^p1qt{m%?e?ZVQS6Wyw;2AXJ*Qj2ewCy zJ7t51GJfG3w#jN{H@fs1pp%Yrd*a#4qM$}jny|4m(5MGU=p`iK6=>LpLU(l(Ibsnx zudhWpu@|3`CYl?J-XVDk8yUpqz17c)jE*+lU+d+Wk9?KD-T8^kBO5mL@X+?+d@1Cl zdJXES4d&HY)XzW)uA+iPnE;Qj>ObRe!H?<0%x%25e zt)OQV!ph)Dp9zdb`ANPI^Za!{o2I}4C8aJ!KK=6f7Du&}laf*{nlY{j!fWZfJMARx zxHISUs*M6d3jjvS%d{^o-K(nPmU-joNY;!D3#y|7{Ag4MN3Zb}sva4bA>Hi}!Kk$24zu2SiqVv=<1Mo6$ss`D$X$ zS_XQxlSmvvyyy?FxgS)wy! zV>ZnyEN63@(}uGYww6SYz0ybo96OdmM3{kUVx4Q+tf)aBX=!$~(sD<~O+leZp6kbh znOStuKQF3g2#lz&tgN)RcQmCCwGFIr*?OO#M?{cm4ziPxpK5F6d$%^X4HJfa{b6V` z5mE;DHq}Y4k3Sbu`@Gw$tE*pOdphyhBrQ|I&XEFkCRgkvpD%QLAy=D8OK3u26Tg6E#Jnx$8iF16?S5cIiwP$JqFDD0@M_?RI;H|G_4x)ZP`c9x z`>wWYNlsmtCtC(5o1^#S(Ppx`(*V&Rzn?!P0JJ<6nEQmr%_sSke!l2wa#Q_e!Bqtx zNKeF7?m*-#Ef+Wp*D9X6&!G%sW^5eZCdq8Ib&s8792*-k%T!PdH?ix_+qy>hNA0&| ziXibQN{9gw7J1|nY^y{N*=uUc{r5GCHoNz=L?I!garTnA60>#G0*7)-wQp*UgZ|nWd_9Ylc zLe}zGF|I!M80d6ui-l73BR5SN^umi8PBB6=Q}#sNvY_~CvFX7_!E`T;un zsL6Xf;QIK8#s0B))^XaR6zr$lvFDBK1T-aW)zt~QfY95rl*r{E*L0}?!z-(h03tKw zkJj&hrR6VtD7i&^#YK1acjRqxfB&`CBE>WI`@&RuZtmFW%bGXFb_i6c4+9*UI02c4 zlIjQNlGL;y<69pQw!yF(Uk)U-WdgK1dp~L?rvs39GdMp`h1%JTw|Cf!i+;Gby0M+! zw#@gdOcTe^8SClS`F;BI+4Ex~hB@}<1;3Vc(fJ`T)dJA+4B#HPM`5jJquehow}$p? z28q@ySso|^U*uca3@;Hs+1#Y43dvU|KAH&q(n{p|ZRyfNc;ltWks3IzK>Q^Hf^{3E zh^4lzVC@Ey`}G=g^UOg(y+rO6F<1+H_WIcyKI95gPDS=7+N5afv6-8@8xi4ChShK9 zpMfzo4F|2n7Q%&djm%5^;$4-|5n8bBT0Mafq5U{6h+lOy+1d{K45KsaRD4IK`3CLk zgGe12w|jr-r6GNuS+!#5)OdGNV;=UzRapNeo}Few!;_oN_w($$$-46&XvQ##d7aMN zp97>tSqjE$Fzx}Vw=FVLu*V7dKO2ZCH+HpPqy)hzx=QQD{xCvfw3PFjp7nYAfP;9Epn;J)!*~SaiSwu>IrN z>wlnSMl+I_AAxEcxb6h*qdta3ut~H&8Ht^2RlH4KrQWQ5;H99DXYmf($Q1jEf-sZz ziVVx-GC*{PrNgFE=E32Dk5d;&4pGz7YjZ#VVBTOX-{dd@c`v-$&S-tl;Oi>dKK0rVUc6wUn1quXh@sCeP3~?LA!21U8!MtDE;Z&1t^u_Ma35Vbw-MMde;<&oh$6n$4yCS7MO_Y({6<^#Z;iyZ`|KIl1qz{-*AJq~=6`$aaO0*Vb9+oDYomqW13Q7|5k1i+V_1QIIswA-Ug?oNBE zI_}OeL`4~cb{6lC{(c1?th0HiPxltU)qh9F2&(|fMn+jOmzuimOVI`cD+!K6Ne3H> zA+wsG4tytvoDMtC-Si~#Y1wA!zsx6;7#$huoP$8S3TLk}N>XK9={mZ;Jc2caSqwIi zwoW;Z(-Y+2c=z2aGqyr%-fq9?4bx98Ma8~`R{Emz>|!a=qhJAL05mlpUZwD{05tpjVPYRR_$G4e$!Hq{rMKa2U@knm838){A8NM6!4?Izx7*dQVCuYAKd5|WjC)L6&HAwPZFSIt$kSPX6+CQ0@W&wsW=*RQT^6vhcUTR7O& z;wp2km+twEzKZYk87G(a&G}Guy1u;|5wQwUz*UhId-pAodw$DaEofPVTUuNr3;ZtW z^zPw}i^t+SCz|f(9s@&r{oy%Ob+?W#YdtKUhvS86wBP}L_vO4dBLvuF!G7e3AA@)A z303BI4HqIVxJ6(Jn7gjOoKCjUMivofY!?wS0eh$vi_N8neFivK%ZZJs08Gc)yLCSS zz46IWUza#KI$9Y>6|Z?1E5z}XoLrQptYoi5uibv7*km|!1D8!Im3$6pNGMW#1omUu zKk}2v$UF#-4^Ic``M%Q~0mcL#PjUl;nDpA(_S0v!2)psRuczk5QYS^T;Uf*1BTLwE zkQ9)65T`O5`-m!ltx|1P0K3n{$23+U-m7A5(bI=7PY~PkJ3>@<`$GH( zn>5!a<0pchc@~W<;3Q$>hZ1_BE@D>hhJ#L}%$qm#J|f@H7>dgO3X|EC3<457Wlqi) zb+Yw|5~agKhJ=iPGJyb50Sqxcx$m`0!SC+(Z+BWsu7%;Q*PX0;sPy30`mO_B5S;^1 z&APwI1_=K~`k}5GC+I~f68Fd268&Yq8(hUl{hCn|uQW~)W!wjKnrV319`Ka=?ylU4 zZs3iUQF4<=+1^z{BsVoR7MyMqL5WpxNr{czb~;IAgd;6q+y;jod)8VH-v0Z0D1oeApTprr|d&uZu>SRdxG102iJAc!WrcS;ZRV}I~q2A&nyU=6+jK6Tg>VY{T-kx43}L@{Cn53I;$#r4E= z<2Zpq3O_=?-rdS;CLTe3h=~zOegye-;OCE*V`@51(()S1HP^-Bjb*O>&ljdmD9sQ? zj@sArX;Lqg@?0PZhOiC^P&HfJ(tvRN#bvZ!R-(>rDBB~Lhx_BVdY$3brPg9$r%V$M zs_W~Ou1Nk)tR3M$E93NkcOPM5vl*~ zCH@0ZZmdmsiUBYRCx!^I`-6v-pNrNVU|L`H`FozS$Vs5!?N8ISZzUkUX8Pj&eSA&R z+TSVaUR{KN>4j56So$$Vz_Fw6>d6X%lM~1lkMk&J% zRk9%;R*kLF72M*Q85JjsV#TbXeC>lp?|-yaoT4$d5^VPSoD|YdHO?n4b*!7SMQ|kE z$JmlWDl5+u?1&+#eHTxf9dLJo8~kedYcRO@ipx+fJRpGNVQe?kWNK+Sn(%Cy=$J+o z>2%y1X}!Bd4W-XPpF(}~2ffK*n@Bg!N@iT|{$72-M5eN~w^7No85;==L3OkYO=#PfpuFA;tO4|tQv4BE~E}x2tNzQ%ksiqFK z+njaa#o#Ikt!QnI4h*C`vJebmnq^aMD||mOYWBnTL7(TwYEbLHGB;sbLCP@e%G}Cu zqK>v^h#$2>#~Ddry27B7yfFH4xmF$LYGuY@j5-aP4^dIeF|aBi?T&lAp^H9DGh3UR z_U){=UXrt9bzpyH_@e0VY+Bf3HP09(w>@}6fZ$bp*7D=WeU{^JLNBBf(_SG=#lg^wb%)+0T-0{D;DN?L}2p zyajhYCrLn}L$rMlJ6q8vBqY3#TXZ*J3I2`vpfnSIOw>)MbG_!#Ejf0$6}>T3`x z+w?bX<+Cx`?>LwsMnHc4jqV=%z(44f!OsL3rK%^zzcX*2&3}vL4taY^t3B43P)Qv7 zVgCq`t^N^T`t$D-!TLns727@hJ)d8;X<2;CK<4-d-lX^Ugq!Nu)QYn5Rk0h!@9(hh zUc&hYJVP}64`+t5^tWHIW66JWd%*a&JxGK->=}0H}K~{JFF86*n=~~5O`vA3%}DaJQ-7QnPaqkK&LD~_E+9x z(75X}X3SLp?dQg#$|J(VDjRLeIrF`+$oMEGOvqj1OK1DQBf_i8);kYLkE)`1i>q*<@5}p?32B^PYGai)#jVHI(^!?#zFO zFl$yykp3O*#11m~=OBi)qwkd&jAGXQK36SW95Mem`1(g!zfX~6mzv?Rj|P}Wo_$s$ z$^YvCrcC(#&kABZb`+krpZ!X9`umg&`kYE0`VP|#+3WxMZ*?qjwn$cbSFY+h{qu?k znXCrJP@Dev`$B(D^nv|Sg1oz}hD>}uRqM~QXW(nppKq{Z_4haT*EaWQC<|==R&O3w zv0-bM*r5H675(`xB!31)YpHGgan*J#A)V+MM@7BE6!`sS|M(GU*ldxA`n{O7Pk4;a zURZkij4B9Gg@}|)T^O6ApzOzlhQ0^uZ)_1A9l|v(`OB+Iu!dEdnwkQwM3?vPn=VXk zku8qi8zo%vP1oI(+Lt*=GfdA=UEkOwBby{#U0s0g9=pXH3(2aWm4$^~f*V1fOBux3 zIkqss(n_kf@}-p(^yu*zXWzwS*FfQe2R6T!b_yV!K?~Py)pPeL1)=&rqYcB0t1B6h zhao*bIsw@;^Fk?;jhgY=!UB1{V_MQ+dy3M}a-5x6%QnU&Frv<~ezrhrYt@>V7wt>K5pKA!s0I_z973+R-!z}|CvE}J3m0l1ojyH8{ ze!77`s3+WmU_{7{I5-=5sD3gCYG2c`MA^Vn^cih$(J9=DxSYnY@RO-2c!(umPcz&- zi&HZJU-E-ZF$-*kd97_(f%~{O@?KB{#+>JI@_7{%@?g7;=E-g8t7i;(8Q>uod`h1{ zl5cpGLoNYdCZ0--4$Jsx2f7;_GHx}`w2j(sWG{!2hWn3tDW{Tsg{ z*QGX#(#qwJr)S9RBVL8M51r;+aO=iP(`W#p0 zGumS^D;5akZiPY7wnp(~-`kgJuOiBvmLxkk_J+Y@XZ z1<2thN4RQL#nQXnk923Eq!zMDb0x3gugiN$g7qPRwSwk$<1QdGna~gQ{4`VhAx@JU z->A&x#fzvpt$=`_u)yQDLVIkw3*=+69t z-cT|)To&Bn;I_IvHmzN1@;yI4P_n%|R$CM3&M`vSw zcUTms^wWnHpVt24cLbO&L~tT=2WsqnM*7q4oaXb2jBbuG_gA?4^Zb0(i^pFAzgmMQ zTQnFgJx0Wj-abBDM@AdrE`UZ&1ro+z^5?7GIWEO?9>0m`v8y_=J70fb!sL(j#~4YE_=qcea%LvY zi3O8{zYQkz$$R?QMXL5!^Y!z`G;Ri2N4y~I!>MB$^~Gg!XkdccY^;u@y!=EHZWRdt zQP^!h1S1g#lk!oBXxto+I<~)2v=xOH)6

Q{}LeOl8z&SGlr3ULtd^dUJc&>8M5O z^W^E-+|^?XH+@-q`(hC%zoNK0BqRiBP*nyNo3|BKEMwb`5N43%bb{GH0xzDJ6T)Yy zZqxItCU*U4wS~GDAmxa0MDkco(r09RI%#|7u9<(UrD&UWOENXxC002IdQ+szvm?*; zc6pz@3o5`N#G!VYi>4a3Q=}1~SB}vmVJV9EUjFKmm$O4hUBFFWt5fDk^E>lNjhjE= zcRA}038^~YPY4~IU9NmuvrlcXDR4;esIi;9F3Y*eo<&$l^_w8kXg8*_YH;{r8Jq5G zN54YuJ}wWgLV1Ata9~A0*^vS9V}->mjazS3doJ)$nv=kMz+Pv2_VnrN)t=;3u`j&| zP8}5%wafd9ORk^JlbmiDTWe(ZvI}OCj${!X`n>|JtnOWFSFWDCcAoVgd5 zoRqtV`QSLFCfadrsF(t5kE`=!vogrg#(6%P6k*eCX6K`N1ONQ|44~OFbk7?;Z~tUh zQJJ|h0hUydobA5aYh<}^F#P4z0fU{+d)S0k-GM)7EDUN^1^cROAcjuUg(8fC^m*c@t`mI8;y}lEvG5n2zIIZv-WMic z;YL`QnvSgus}emT#m)c(AA8zIqbxm6}GJ!Hf6c{_3U}dY(QC1pC;F+!1I1!vE6vhT0 zUi)>iFrrrJGjkHir4}3Orwa{_ONLieH#Yukdx5Ft+^1rU^-Fys71@hNKQCp1vKk3r zb42-T(3i1bf=52PyZu?&-y|PCT&9%vQs-LcNAnKV{roE*bpOX-5O%er6Ff3&0}xlF z;2d|w&?`G5?8+6IXWeYc7!4#A8m5mIvu976RQ95gNvot9Dop(Z&lezyoJN^r6XIk) z$$i}xg6pAB=vZR2k^UoX=-}Aoph7mEW$nBu-5bbXv95{3SRd)>^kl^iR&b>T{_=k zc6~gEU_Y0ejdybNH$2UQx+*7oF22)h3utQLA-j!tze$aXNBk+!xa(Cy9IXHrOB)h} z1?98H^U$J_5l_NyifMZ_9Pbo%+FWNfowsk(88vyOw4E364=?ljJBmCm9$m~ikqsu$ zS=E;-$I$53NhkZ{?|&lI%$c+@lABjjdt-4)QE_onoTrjaD4x|OA-$8qJ!zM#2+un) zRS(nw!HGqqqUf6lsq&cK;@OjSYZj06UmB(%eNMi4pLKm66m;0%cqQTS-LewtAm&x~ zAo&~T0i&g#)1^v1M~|qRj(N7ulEUv!+K?_5^T@i7$neaPC`NGN!y-0&U_R(boU(6H zJ&~IW9aYlSW(I@k(hscNH|_pPJ8WK3`|FqRIcIvXNa@l_5?TJUy8H9?H{n%Y&9IQU?z&)-m@R)r@%ocK z-(;!PG&`*bGsA(8CU!IQ3+c@c6NO{#WqiVzce~o2$(Zq9e3REM1r~SQqb>2^5<7@A z%ZjCOaF+C2+6rtpN7Q;Pzl8zLxjY=&v zO2#&yGS3;cQ9`=}Jg>i>a=1MDP9q|sLTA2QlWLYtSh+CeTrP5VjV@Rw;C)@ycNkoI zMJ`^KxtfMY+U6A~&)6vL$W-yEoiDfnDhPkm0TxZinGfOmvmN{b8Llw~)>5HOrA4hu z?OVG#6UmU?F`vU<{`H5oOjib1gLXBVsMF1QVfg;O6E*dz8RGCSP?$p$zD9coBE*>o z_xL{DU@MXuT)!N{xH&48C7D&6p2?h)m;llS*EG4_mqTaBmsedI@sjAA4kxE3^AfwC z9LqO#8){RnhB6s}$z=?4cbV$^XvfM^qv0rNZ+-2aQw}lXziQzi9* zd2Mf>zRl3;@I}D0dfFOkpfkci{U_N8e<)&!(;lqLQLmH3mLcO3Q(`PQv>sNAt6Fzl*fV;ok09ZG|^@#UA%rO!~Q>7;G8+}Dtp zEyrEez9^hWgF2@2?K+He36CNu*yD3=P_9gC-|Fn`>2L1xZxFibgGvd( z_?iCC9oq^g;Hm|1Vv0#{DaS%~jRHVbQZY&_8!}#jqVDm`%_00`6SOwP9)RvFI zR!dITL9%;ove0t2QQ)*tb9PiqM}}v?I>RS#t@hgQXli+)eW`5T20*6H4$0V}tA}?$+>ja`FD_VNXo_ z780;dqXNpTnq~YKb~}RSq%s5oOYWpo8*=ozc8x#SA?`wITS~!oE zmY?V}>O?cgS+xZTA08KZFieXujm=IvN9@n9ZS7=q*WlqBc6-)Z6<#0l#B_#`X+OI= zYDQc=Ag1q-9fBykist|1^a1PT^wUk{rJo5Sc*;?k+ zt7uuKf}tL6Cqg9YiMaG;xwic$fV`UNwP^OjSFbYmZ2{fjPXl)57I`IAqWvt)vF`Z! zMi!`hsa8yf`{f4ddiEfBrJ+5YOwRLY|D z>##P=+r~d;e1I4JQANX?u>8mjLR?43v882Ax>(AA+6IwzgR-@Bv2chPllS9o^%-~w zXP@2-VClfms5YOMfT3Q$%QlMRjkCWdhsiI5YP(4|up`n@<`Cgt=ka}e-czFA%#h*E zftN0<9Dtgi=9DakClONtR4BVJz2q+{@eHXg*ptsx+|QlvoCaK3Yu-R?4*SLLaQ8(L@j!Zd;usJ10+9+83;_V7HvWsi;feZk1M>_oSNSoOTn-%F5Q$G4bi@@R}+0D;E0K zB@V{PMttKd#ofr1?S~YMkS8>69YYmcxlP&u0fSy{9hE-#h z6T=&Fr}OiZqoS848@luYZrU$F4}{0_tPtt*ZM1OgZH@DAR!@?E?4H=$NR{q5jsoQvL(tXo!J9MqFdSV2Px|$qO(+606}`rvm|fEJChWuxF9pEmzK3 z)(Axs8H_P9%uKM+Nnq~OoBu^LbNthRUGVz*5wQgc4vu~s;~);U*OZ7b(K#6d7m(jr z1UGEm3Fm^=}rTOTZo#F=?T1M$Qm zDyiU(xq3GThV#-=c0v)4I%aI~tS)k`yr7l7hx)N9$m+&NKsvDs; z&2uGr5;Zk$`ip6laUy#d^iN~6Yuf>P<+)*R%`0RLWDH_(JM02$b`|pViackieE6FI ztGVk`ZYjeql}6V}uq(`2L=*|iUM7$Swj{f%yK~=l=nw*|lM}exe^Lm|Qk)fO7DgE8 z>yrrEY66b>nmhh1BLYv!+Z3=B_l&_z#ObZd=w@|D!9v&%kCF;)4zx}o>m5)_ir{-u zDLdPW#AkCDc)FN~Pz!Adqr|+Mg=fDCCIl@SL)y+aQ&~Mw5slj`%m%B%Z*lP(;1w3h zPjx^52|TlzeGjXZ?>&E z(A5>Cjbi8q4#2{ z;YZSQj*5@%81E4g5o@+lMSYSFbI=XNx{X9HBQ$PtX1wbup~~ z74@ihjaVyMrLOiZmWI)|(%m4ul$t|ZAFMVp;zVF2{pUr%i>IO)PY1 z@SdR;VtNI}-TliG%yA!cHP61<)Dt(0D2q8mhXuT}eC2XZEn}Xmh${&OPl(3eBjU zrKrVPa?Z2;>DPT@M`vo06gDzD&GIgY$+j*{8Z*~nsktvg+#Tr%g?I&~C3%It zy=(+uUz{hI4(gtT>0Ws3067yz5;U1SRqQq%ec5CQ?)gsvVcE8eK=XtUe+v!APErn| z(%f@j)#|<5T59%ZKfpjX&=m%SkPlEd_?wNvj?#Tw06=Z+=?NYRvjEUTG>Z;%m|-!i z<|7mVPl_u#0Mn`rmV)UdaSTj_!J;+JMjxCU&47P4(@G3A;IAB^Mh||BAJYZBEfaI% zShR%S^%CHnz^EP8e9uZRN|Iu3SE68-zV7GVp9~M8%l!03*+Y$V9DRCXFkV<6 zztOf3;zkjGwez*VLozOuV=i!oopZt`AIfDm7sFw&RxXcT4MYGP51nGSX!~psro+Q= zsHu57$~?2oryFEr4wCuolJ)R-#Gv=nse1Vj=D|(EZ43mJXk;BVx%s)HuA<5f{=v#H z+5N|e6KNzGmC*mQHLIp`f1Pfk(9FQ|igBUC=iHl`LND&Ho;iQr9e97k*Y_KztOkx+ zFnfH}mA#bz%xi^gOT)!0XHq!1`7RVP-V>J-(g<95FzPXT^oi-S*9Tv{QMFZ1VBfhb zYf?PB_@pO3;5PuSDk^+dUcR)K+2Qe-2WeN_&1Xaa*TQFCV4q(o&a{6{#JAQ1=RXAL z+q7R-Qf6pWuyKo(XKA~W_%-rM>hZ!ml^wfUwY}=Wx=piUA zz1W)n+pJ=l$k}21di_%w1Qx_Q`bwpU#qEgz?m{qDuwnih5Kzo^dS4(j>)(?NGc~@< z{^l0nWXI}QduORU_pzuBuE;Hi|5~16sHlD{RTY^Zr}&`1jy2h)h6i4 zwm%=wKYjWCr+nb@hhT%$MSK4ITCbw5eHWP9B9s_Rc?*za z_ZXM=1!2fh921W#9xzJycYhVT9n$PQ@?1U2B)q|j+4hm&3+iT@L02XLO{tvo^|5wY cA4BJ#`X3elG@Y|fonZh1Pgg&ebxsLQ07blg4gdfE literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/histogram.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/histogram.png new file mode 100644 index 0000000000000000000000000000000000000000..d6a51938b80c005f40871544fb10b2ec1458a1e4 GIT binary patch literal 63808 zcmbTdcRZV6_Xli?nZ%4OM$szK+Ix?xS#4>p2vs#h5qm{Mt?Dpp6>ZU~U8`oSs@0;z z7Aa~KHEX`n=l4AC`}gbf$wzYM&V66^xz0J)xxVN7jW;(nV4~-yCnFtWfsrIkb^hKYsK8*M~pvUMgT?2Z1a+ieEeFtc&hOP0C%H@@C8#^U6_mtr)zOhx12{jwNoDC#|v|jfchfmnm4*XuvItTu4$-Mh}&3o`X z$8YH4r>i(LNE-k}g9OarR z^X8HFs3>na`nvk#gX=(+LY;mRw~eW(sV}p|$V8+62hZ82iI%e?_xp8TIiI}eX1Qe_ zg0lSj)j!_*^z}};{l>WW+StdB0UMKdKHT~ElUKB((x%=gf7@@S0hkP{2QU38t-gC7Zs%_9onK;+rw>%kkFthyDbtreNKraEGO^jz1n`AXp zh1bmlWO+_hbsg=l5Ha!;MY8=_3Pa%spXVmByj$G*(ymr}%``T&=k}J`eIDyh;&DCy zI~1|rdVX5I(XgB=_4WN~w$S@aH!~c^?E-TIs%HY{W@7X0p8&uSB3|fXs3Y4|hn8uk z6B$G|{_|#wyLanpZS&sPeffZO>*JH1q0_6P-8wUk{t2PgeJQ6qLmJ-YO@E#w@hT0c z7bSAbeN{i4r#${un9_7c&A@SZggVoan0pPIdL)FVZW~4uJN&vsRZ{vv9gDM zC(NHj?*C&p1>)+uh5X`CEm@)Xi;XQ zOJ<)foT55BS>r|=C-<3Y*&Q~P58i!vVE=d>|GkG3v&LA+4c_X%K6L0>mib`dmFRLY zf6K`q<5q))p~k>XFIs`n3h%paT?5ZVjn}^$2>1_i9CSsJQ`-J4;<1;X`=Ugifk=QJ*;sc^LkG!r@v&q z=~i0v&Y()mRaIb+*NcOoOXy-Hk{4U(%+qoMY4p3+%3HlQThCi~H~}n-jEva7JIlu@ zir(Tfzv$yynvPaK1dt|W;{5DDBjST{&>v?7d-cCRS<7QKAx=#a-7u;|Fk@v^%eM0| zfA}FhlCB+EiV+nQPWp zhU3JH1r!`&kyp$Q5Li&1uY{gFns1BpI$>>LpKm0YJ;W|D@YlEYWeNIDrg8f5VUlZX zbj$Aq{+?D+GT4h$T%Il1T^k?TjIF}*{MP$z@!PFQewq^f;2n>y*bw(`1pR^Fl#JW3 zh(I{Wc+}E5ksfUeWP(-E!WyhxiVY}Z0em5*nlALA@!`nS4aJEGo zvRYDf(!&ckhv?Gl4-?`9ywV-Q8`3vP(Gbwh7scStQ@M`({K!Huh6jf-? zCpZcq{@uwt_qc24|B^>M@dKb~uj`@CeE%!CD@u2)Xd&OOKj`=A;L_Q99mD)g>?5d& zS5R{2ZtKy@xgzxXZMo8&ni13L&4}~kfR(rDlX{$XKZTeoqXT~qs%-9Zim6^1W`ZV` zvX;Z75l@6|%>YJC5rCYnVSNDD;a`MpQ4a8Yg?C^k0$X;}r#))-n*u+tG>zxwlM}x=1%sE&ptg!q0!EWk|2>xYVE7 z%l)3C6QWO_%RAe)6Hs4(+-bVK#H0bgQgcx3HlN={1jmKKP;}cA^Piv|@jJHQa$8

YRm~z7XT^*G;68nRP7nj>@V5kF)N>VT;}^Mxo+3v(TnFj8dDb+)Rhf)Bpw2T>!g@5N z7^k#zB#qTTwJ(()62WP%0uv7sJAJYxM%z)fG9D2&^VuWv3Bj~L{`GOuy*Idqg#nc* z+@6E2HTSIEWV{a$RHb{!G44yKkX<5X#1h$)xsLnfx*reH9`iYB(0MzlmnkKy9dqxe z?+pBb4Dp)HD?0^0vgV%Z-1qacj;NQy^AD0Q$M3!4Hz=e1UFb6aJyX>8pzTRg#?uah zr-mAUvLQ}#S{6u9@2;DBazG%kbSsnEkDymruf-rT%}W01Ox z*XZQ&eEQ{q9?_N2nu>p|9q-JK8~@#U9uE92yh3iowUr3>7~YRU*jlSP*2CX`^$$tW zIW_e{^>lZ{o|6VPm9%{@HFq{P9#4n^Evh<6o{_?TcmGDV8F#Aimxl&_=3{_I+w-=5 zrg-(*SaaR|EMl8HhUO5G;33@okg(G&{8`*->0Q~i2&8MN}|n;69-9|_*?Ma>dWjuOfMz8GUCD(C+D;M>?iIf%N-kM2rcKN z(`aQ2+A7{5<&e3syr|$9GJ2sb{e$y^i1X!f&XFx{SkAE+7QJN|y@!;t(HLhv;2Kx% zi6Rd8lK+O5-A`s;R&h2)gg1%WI*i7qnq_dTxlWUo#D(Rw#tHsa<|$il%Pyuh+^v59 z7s1J3-s!u%3K%SpeeG81WM(~qf8G`;seMN-nRYK!Q8LjtF|#TfI+%rjb_2QRlz5GgGS;(A(1}-23Umpg0tw>f zOdM9*$9Je%LOLMUO+Vfy3r^y)TxPeNeBkD{@N)SHZH9|1p zGLB4Uo+6uaEFQ1{bF~AtGFbky|d!kMXnUmKEd6;b0|2c@I4 ziR}9+h%cvYN}9Sp(mpNqcVWMk;%tR&b!=&GBF?^wWIwMk;q4g4ignVAvr;4?dSrg8 z);#+0b@RTxtk3zDHknpWaJ_WLUJBXI@Fm5#V@|@C(}6>>p1ifos6fSV59vKR=t4ZH zgq9&MWEM_k>7?uU!@{UMtB!cHO(Q_0?|3cg7zurXB05;MhgfjHOktfe0F9F^9fzUU zS~2TCpPSWI52;U0LBVNpP;_P234mdeaq9tROq^RBuP;_1`Q10K_{}DE1I6uq0b;^N zM~3oxMMqOO?l0^O?6HjoMoI`8`8^rduBdZZAxXH?^p{`xadA111ug(F%1*1#Ps6nX z4aaLt>ZM-J1Zh!mFXy;nW#3iLx#kAFt4na?XLLxsrwUxZ1usk{cFQ~3R<}apYGw-f zRjr$@ihaDM%}C5Sb)Iwk(1jF~jYne1F`^r0mmwVogg!&d`ZTsfl%9+*zz26 z#W5`F>^Dy8W$Nvy18S`={z-Me-aI$`voD)uHd9BIoav(2n)%tt3u9n0pfAe~b2*d)TGXBrf!xrgWI20+&w2RT{kcEKS=%L4`8^E_!HCbsS8%Z)IUp$v!K|=) zz|exHI1Pjbh7sSgz@I^kjbH`kK?{!~UtT*(1)oczJQ& zGz=kmtG!;o0xs(mNn1`$ut0%eKViuLB?6NQMlH{cDv3O~y@SVhiD{x?%ZrigT4&PZ zWG)I)d~?HKGI*J28SP${*mj6^j$#1h1*8V@qRB#E7T%9h4+pWYGhjI3N*-p`X^6gU zI2PMxh?wyZ#t7*POvQsS-`W8B=JR&+vtomkeHA9ojUB%_M!IF*m@ai0>e~7;g72(H zpsELDdW1VX79aW_0-5z6AFQ^#(Mbny%*|@_US5^9)sP|5jis=}4c1>fPu3LIpAhk^~ zF<_7(7QtCdSx&x8+pec5FaoOV;S0<*W0<|QFO3dF4j^+|4w^UFYjTLMmTZMo@%qVH z^??&WRZiRUQigI6X_@V9)|%lJNY)sa)=okTue195m@1ChQeu&Ve6y*;sDO?=6N2(0 zFE|`quO%+Xrj&--D9#HZi)z0f?a4HSA)|-8@#-W?FDGzP+G=2twV5HYo=c5HMWh`P zDCmrTu%uV)b7G?~EC&_{|8Fhma$ z0SSNr(GLafw;)zjtMuFFP+n|Z+gobN7#A5;*d^o3kV`I6jS@{--CyzrZ@})sBDKZo zF<=afy<{zQ3>fip2%-Sdmehf(w_H!E`va-yPic?UibrA;+YUP;8M?3MMt{T5b^t5e zs(7y?J{bP)bXX~=&rQSOZ;4-eHt#9dhdA8c=ORAyboq=oojvqh$JfGg{JLAHgq0vq zUKFTa8I2KiRs)dNK5w*^hrF?MmW@g>b_hi12C&$kCzw>skK zJLG*!@q-0r0`yZuK~5o0C}a{9F#bs9;sp2D;Eqo*j>K#lt+s2n#~#8x95QIo&tPqF za8(>Y|EcdB;S&MRzAU$B3w3S?&ycn)8tvWJfz3`}hH?Hpom%x{;=BxKsj0yRf=zp~ z<(>LkH-X(Ejnm$df%EN@h?*(y)){JgT-+K3`QYBIVYz|IpBcWb6%pCe`^{UYQ2?Dc zJN@l_9S!r`jv6I-AquvvB?sR1(w2lq`XQP9oVDaNGXU7^qUvvVRNc`TNYQ}mG>LX) zbUV&}3^UT#cWZ;R73=6$l>LEFL7))7bX#AecxstD9C#^4E=Cfi`x(-Z-;#Z`h@V1?__&36 zJk%a$4QA7857H78EZ!>HTFP4!eEj=sCHy#pmhw|YJspj(5Dns*hu9RBFmxot4Za5X zT7ps0sb%PRcG~UJ4Y|sc&00%`{3-))7Hu|i4Z(A;++y=THUCu}Z?)8vDNSESmkf4F z^54mHzl8o|0V|l0r}sVqH$d5*AJY+Z4h8HlCClXBM*XT+hnQ(S<)B^WL$quKneh$n z#q<=YF3_Ytr9b}KuxRU>41&K^Gbr(q{?1I3!f?#n^vd=YFN110mZ#GQj!dOL?mX>P z_f_3?LPj8&s31dfLt!0q;3aA4(e}Nr03@U0!D7%Q0Q3>fMPcfAn7R~~$GnTJ>%lhs zDo8lF8el}D@74}#gOFZNyEF|+1rE(l6(1xVVlT>`xKyRt+_WO9pXbsmvR9pV+OKld zwDK-X^-f;hF2n^8SrrX%w3#hMOmphNj+Es4Q;f5hvE(A zIn>$!(lOTxe~HmzNuum*xavCMxhGLku;NK$xH!Os(KFfI0>m8axadOGlVDzqTNKmy z8-KdyaPEtE<(}t4@1W77`ue)bAPFa1LF+7oIoD5HFde+S>g(09nC(fQ}KBNWr%lmC| zw6rRQ+omTjPyXbVP7!3)b{4y^t|p8sDC_2Z2)6;Eb7!BGGN!Jzi!0EDx+7Va0%8L( zgqVqP5xb(`U4KMh=5Xo7wv*uynuqkrGqzcLby(BhCFl;u2_3W$8BEYtflSKh_zfz}cB8i{apRX31W`HKQ58v|;A9s#4wbg7i1EC7Rr2nz zl2fqFki})*ySZ0UgMfiTGodCcTL)V|t&9zi^9h>$qz!SmtjuoIpy-a}S7Swob%nJn zre7GK3m4F(9Aje4d}aQ3Wqnl*Jmdj77A?>6k{l|Az6tJG*qjlwG7uO8L7JD=C9W3I#1xI3ifupK_x^tV; z3y#315}tB$iCj8XZM=`eNOlztvU z-+&cY(Ee5GWkBu%PWH*Pdxngls$nfye}fnx#`!bYDqDD1pOw45+K;;|6Ssq2%isEB z#c{)rzmH)Eq74d)kDh19f7RsZ7-GyY#Yx4~6N#`GJ?)ZBrW;Y@aIrCfTdMhFpI3QR zg9;u%k;1x6F#->{y+-ndOYCGQ0G#bu6HiV{3u~Z0uO|zv5hO2L%j|jW8XeA6A;Y6b-n-ntTgjv;g_m^42Hh^;gU{Y1|s@)%Gmg z#dFuc128aRV0~br*t*1Z7Y~hDM(ssIsWw!Z!qOGyGA`{|`nno__@f=*>-6F*7P2WxVDCcB?^EMJ_vrW&Y`A)uGk_QO1YqKc?PfVM>)T zb+b+CAx}+xq*x7vBzHB-(JtSC_9EqH}( zhq_!BHeLK2bH3|m0v?&i3zeB+Ll$>O}{ZTlt8X6t;E8(F*b9&zK?`qf9qDO(CS5QQsC~H|rcCjyJqiBRp7}e*X^Xtqn2AX) zGFxB$ZpsYerT1euT(WR7uPZ**$Sv4DD5!@Y%UqMWr{v`!ynHpsC)v;@QLBG@xoQ4% z0bl8r%wzvu@Lq3rchmHBTUvn7(J;YQNFAiGd*!+Z9>#gjy8~-h{C9+S4?{n1Y z$NY3`5Nf-9FU@F32CBO#d=XSpbt!M)qHIhtjGI*Y&~7E~M43@bV-$leB>YgO*i9I; z#H5CQo*fx38NT_{EKB<&&?I9(eOSBzhSo5|ZkdyRpsg)3 zHcvYF>N13w<&Jib+A^CAiVXn)=T?gHejjT?#12>w9$E+%gS(yG3)LXwpu837I2Si! zjLeWfXV141!AA{ZZerNT(1m!hlZ=so#G#A+NYngxg1QI;pObjoXPshU) zhzu^Nc=SvI_O7=I1MTIp+s{E59zE2h#l?d-sQ6CbIoc8=v;kGjR8$L~7zW{V#LGva zl_tE`gHMW18HB(ckndeG-EDegGD$%)hhHy0-l7L%dTPP1u&(rGEI5YB?tM6wP!&Gy zW-Ji{>lEzz*5${7JHO0>+fzJP&J8K6GZA_L+~kmE1jS|FAC%#TXftGz3gb{{=miMh zy7bVsL#~VD^RYXTcd`ES{*Gq_O+|n!s`=}}{Jd0F^_Pm%kCQwCk$X}VX11SEdfUO< z6j339sDy@qzx}5@VO?sSa?e(~7F1S#gAJ!YOs4?!?A5oPT|!g)&TTjSY+Sg$Bdkl> z%v@Rye)fX_dW|1<6~Nj7ScuDwjzSw06-R%MMYd%vlIimlh&O#_+_4nXID=R6G>)RQwh zC3C@JARVP~VUAw{NJ+UtGA1smZUoZj!MeAd z0LA`GmAx=)lecKzq+o*$4O3w>8dU0OfuRHyr6uFG2c|Z0Y=OUTP#(8!>z*L(70cGm z9zo!4wXF4JN@i#|q?!-^_Sn1|c{0~Br3Fv2T#w{5t*tv+rIN{3r8L1ssTRvlb$v}A zl1h`g7zNeF`ul}de1yzD*6sCgQzCF9xVu%y8S``uMaCJ%DWUIfB5b;;@%m!}4f@&0 zW~50~vu#~Ib5p6U^i2jI4;%g=$PQ-<&5dZz%h-ryrk+?&;KtVg{nc9N15}!iWJl2A z8BV23X|bt-Ihl1_q9EHn9nmfW&mASU`{Vw22pq8Wr2233B2!grSC^?c2i6U>mm0FUpb5aSN{Nh=y;`z@%XO;%Hn2qrRZN zW{?g7cF9_xn--)0{>x?h{i_fQ$n|zjgh~meaQuc7_fEwCFKwdkyJ|DS)gahOW=b$V z#fpekwn^Kol+5GmX{nlnybom-0tv^Twr9}yB(02^5Uh*FfN+~MhQ4db8%}&E#x1IO zCE*b+J|Cek#R}Q(`|*D}4hz~K&H{>Kr7`|hS3Ovd2cGVc8omytDx>UF&|@^AKj<6ut;TFWM-6+3p%MJL;!{tc{pv-yP=Mi}`|982 zdN|fER54&3sI%&Pj%O}wUr450b5@xEzC*mZMQ?|;Wmc;?b6zhKc5m!$@CGXk-YN7J)vc~z!Le}!oP{f&E1ffj{tlh~O z&jUppQmWpQ8H4p(CSC7F9D<{D6a{A$hwnNBExz=6%pw1?ihQ<-waVZ#9itnXc~+9~ zHuNiHG@Uo68v(2$67jnE$Dn-`X&a_Kad71_8g!e?`#D{a&<=<9Q#xb%iTW?k^ohtO z1(dk9xP?4D&peY_PC1Kqw@e#Dlz|TR5AHPXE;Eo>I}@f;b{(pFlDe!9fDV&+X8o=w zG6UD3rIOBWIAbl9$Zz3K0?0(DUfWsL;)cv0{j#!v-qe0U-Sm!xbBlu}^|6iw9}QBm zky;Pd#>z&YJWt9-0WD7qNEMR$X+XwuqBN|*Ce{Ou&I>6$Us}0ha~{?QPcNDRZUiBh*>n) zo(4lDd}9CS*pP)2^VWn$2q}yPxkb`m2R@?LAPWVi+~>!4x%je@2o2Zxr~sK#a}noZ zn+hrFZ$X!w`%eY~TZqz|zgqHZzRACAnf&FQ7*OJTPXrhBo6%6zEEu&a#YEbA{bNL6 zEp@Ui3Rt=mxrl`E8rQ-(`QfpVPvoagsr?Aot%a0E``{JPO>{bEG}J|%BF+uvHK=hO z3M5FGba!z7h!;~%jL|H-rOYAxE(c1>^2tzD1-a2g&6Grg%tHEP#QoLjiEiJ}%YkQ- z5di}EP@%oTODnIF_x{kN{Y56dmA~oCHD>mUjwxP3vLo0UbJROo(4F{iWCfR4k6z)V ziq0ifuiyuq0ir5UKF5)Ru|dIX&;9j@{q^dh;6O4-GT)m2c233b z9E(C#1zy7i{7Uc9-nheo?E6pySjET%9LE=NvOTLJ&o>VBP<&Y5f6<;lCV|pT)k>=b z-SxV;@Z9hhl<}7teF{KwyuX0zhix+mNu6d%zoV6+5a2NSB^9Yk|7@POD>bOdc1bLo zRj<6a1ZVsoQ@+x#sC2s$Gt-}Nu5q@Va#7W!_4?`1SZII$HOifJ7T9{6BW(~idP=%u zqnat;fXg)-UX&AX&$oA>L}q~|KXN>l5*Bv!*t-ecM-PtSjE%Y3VT;yX9?S_-rHxl? zBaLtBl3DILQDp+19^sz?JZ-6z97L1N z@^&&2ydUTIOt_?r7O|NnffdA6&>aH`bL&h`9u~_!{3aM^hNQ?yHgCTbeV2xqN4ZaG z%+09DqtV|PP$~RsO)}D6WpM)Gcsn~1dKJ${>eEa4)YqHGr>OqHh6E+6{xLkD$%o8^ z9oTWIqO)^CemB?)2+>zYp&Ium-NXKpQ_`SX*{2m{Ya2-wR2WZh@^15H*pTw$U*=0$ z@gus$ykZf9*-9<;K~ev>KsO93-d2D^_Er}yRPe4p=%#9NyZ?^3;wSyxJ>5lo-bXuX zaEMYWsyA&Fz0sH7Nc@B4S)X(`UA_Cev&~e$?F}Xu-Z8>Ks&{@@GDy|8g>NS~tdH)0 zlv%)ht0J)nCb|Gl#B9Goq)d!C`KXjiU!atg`cSq~wWiPf_x7A0Wp*lg7+N%C>{F<% z$Ke)1Dr2jEI$+9EDs)hF=O(8b>b^A%ka21|PUEEAjC&PHV(a*k8W6rEL@>;j7h6W+ zvwYVB=ZbW4H2b9QJy>`{bZaCrMow|?5b^(n&|}Aar_ZNn2d#DLVMkUWm&4b`OB`-i z=h=pRG&%pnQ2p`#vs=Rq@|SDHrGHgEztwKxvtHQ~?3YsY7-q+h)R7&#eb;W0ISQ(S z!AlfnFMw~6zruj30@gm(HEwAEDmO$Y+T`@7RgZoZ?&A?D4YZgTyF)Mx3zz=C>>FG*CFhOSL4bh z@01up3hjRLry57!Q*2+)H$!EU_T>Q5=wTbz9GAPcNWCamQRnCNYh|B3rt6XW7laHo zm9Dqd#K&xluXLwDHv;>v)}d61Sg^3|1PxN`-$Xy5$)Yc3I!)PL$mEmw@%x^YY3ULZqGst z3|#|BZXTqbgl4{4<8`_SSI5FJ5~VR*RS<17}nJ zDGOZ|xB-jr-r}F5w5bOU)sv~;42$X~UbzMttJivc_7ES=?WBwR$Xk$q!&pyE0l!_8 z8@$S#%k#|tl(gST&ReFjh~&h?qzqqrkr+CTx`juoia~c1p}Al*MM=i?pr9nF-d7yu z*P&vv=?AEFFhr-vQc>A%k?2LA;`oEV+;(3j7a84nj9if6`kY*YQaFc|rm0Y^fN)R#_D%e3Ml*BIUkv2I-4}1Eh_8){enF z=%m!7+)HFrxWaAYHFa9bvCus%;^mR$sWUCf?>%$B^vYOn=l)eAO*Xxtsp*H0)Vf=;x`SIoIJ%0Ip6tA?mH) zpjY~Y=p~^`-tx4(@Qx_mjHeDfL(J$spLq~Wk5AJ|@)Zo7ETi%E4XFq;k3c@Hj||iD zK}PF9Nr}0ug>uc(;{X06!syofHOu7jQuI@=l37;GEJtMutbS~_Gw5L8>xgxv$AJ~r zxnMvg|IyWZHR3-4^g?W|&ubzMSqEcrZ$2`VEIf3r-fTH;ti$lV3p4(e&DyTb{ZLh2 zHd#nA>8T7o0l_QM$z(*Y=p&iJkn9iDe8M6$YJ8jylh#=>Xk!zz&Cp1k%S=cSp~J#d zHO1%5!~Z?U*>pL{x z^>oBdseX4^;hC3QRj1l(uSX!MzN15)hA~rr?|AxL`k$9C017C9#;=}aoxK$HsPL@( zv|VrhP&sNQLA>2f^K$?d)4t5c7q>NCA=+1NFyJ>+{y6FY)eQn2m&kRQ0vcNC4I-CW zC;L9BV-IwvLfL@i#oKTc(Udofa*OqJHMg2z4vHv%a3_F*92xaRP=YMah65Vo^O_RM z!Y23#;9AIZGxE94Gm37gx=$e#jh8p2$31!8A6hDar(qKt!OLH>tl$%kYNO-N$Lam6 z9y(tNPqA(XaazQh}ld1|J=M|K5#oRVt&GIk)9pIk)3VxQY7J#P9 zQ?kbLX#da-xZX*&Ks^r0{9&Hd?ys)~5SUyRRL)4DOf-bsg^C?>iJ|=~q}YDFkhm4f zg`4(Ct(00I`+c6mO_JRGh?1`FY1zO(};d;r1R@o#5BGU^a5SUHrHkBvrt4zcEpRWaf3K| zdaoFJmy@G;E@z&sJNpU)6)WQi3;%f*z2_wXZ1SSg^V>e5&6T-7yoM#JB>aRn!0{=M z+3>YLYRl{#udaDZ9UvXU*KLLkM-CQ9h*679{%;a%Y5F)rw+(a$GhlLz^w=N8iU@t! z>W3vU>)NC-@AuwJq=e!p-{yB?d6bQxvwD8sb5eCKU2E?@(6M&fXa!F*6At6C(*KeQ!uxDU}^~0+9f>!SweX4%71#%fQ{Vw)3f0mTBP8ee{8x zB*v!}*~Ex;nb+hGSgv-SVtt)8jW_cw7ka=*Ea&ItRP!1#BB^XMJm?pE1+siDX14G4 zbN&I>G=iL2QH;ddGxdpmV$2jp3XvuSXI~u<69lFSb^A}*@^Bh!<|h$jUK~G~VX6uh zp?f{Rut4)Ep`r~DU8Mtl7ogo)7Mr0--&e&r?*_N;q>0@mPeZ6zWfMf{lXA_AODXfa zlyBX3wZ?cB&bPyP_o^7D?t76%7&5v|JG|48EE)R~VA;0TV#3k~l}76TLo zt321tZ1Ol zg4kLE6dSBDYt8m%NGq-J=aJXjd)b1kP=nw9TJ7-Eb5HlYPuF8D{>CFdWLeMJjhj+( z{pG<=;{IO$n2S4zUHwb5By9_vlW>WexL(5lr6zbm=Lx`wlX|ZR$@e3%Gs)*9s)}94 zF)jVt?vMm9Cnwcyk5ra*y&JT32C8XHmNjqK9B=SR>vy=Wr$+=0=7#Pej-AGw`uc`a zRwsj8O0WB?e63b{>b3_H=zCL`d$kw-M&>qfPb9ssuiRR#KkuHIcx6eExrLfrnOM;5 zf~8q~xwhJLAeV(%)s||>_dVUWTh}Ws*W&3%syKBGoO3yUkh{9DDV!3octonP*)R?P z`9EHIf_q1p~9#g%e~^wgRlFD3SV>b2?`rbq;;@9DrbXKjF*zvJBczL5Xx z;A;M%Z|^qzp37**HG8ug6K-nXD;n3LYJPMyeMd?6Zn}IF>+dPGFVOg50US3#?wQlC z#xEhx3dF1UZ^(XBUZdN2_nCigcC{>ygKE#9v>}RJb&GIu!0`)^wB_rs`7m z@!sd}e+sF^uiP!KtIX^7-5h8YCf_A(A}YV9wq?o$mY5ZmMSB{R714+7E7)(o%|!5_aCcfJw2g zNeosjs1UDw;IFN_^n*B(QG^+#%(OML@V{-W_Tt6g8}G$RKfqqz1{OXk6_Zh#Mf=n| zR=%S>v%(nm;em)(6)571E|4+&r%&AuNMb-ICWth>zP+@}z}y=j#V#+FxQ?WKtPTC4 z9OAw%d%PASyn%^maWre$PaUwSS7o^@0>myYo6(0(Rk$S#ylU;|4-Kz5-Tr-dV=Tm> z4w*Ml>2hW4_QR0S2IrFX;EX$y!Pc(U0iS~lc5X|M+-`U^{zm>SE0Nn4KsZlm*~%Vz z>-pm!9Szb<{YAk~ii(4^?J})_<9crI7nDDY1{W;fQLIIl^h6{S23w|otPL)}HI%Oh zhyHys`n>-eKvfC`PTMb^`8bX&U9AmWRL+v|E-}e!R(xNb z_G55B0{^b6ZJp$Pk`6xETsAZrGse3`K5F03ueG13j6Uae;0Vq9W#-~#CjP_DjFb%C zi}B`d{I2Z$Y1wh|z6h1kTD4|$_21c*A4wic*P~Rnx0Q)>iTc~D8*!~9*T?pVtk-*bgSpSa_+*XF|7H5u_p}T5 zfPHb6U@Nm;s|RX?>APsfan{xM0IvIHyK(TK-kRXo*H-EL1-&jeX=M%uEC`!)jb9Mv zs}dE}Ss&_DyBXVynAW21bEzsVP7LWf=zS7K-Wpo{F|fD!p9N@%v}!(5MOoMCMbk)| z=rvu9d|krFPWNwrVI|=eJZ}SUgYk*F@X6>ckdVBKUB@Faz*E`FDbYtG^~sO)|9kXi zTkQX`Qn^YCjs|ahaW)D3^Jh`LtnQeRyl~}4XtKnA(Ku%cti7pl$nV+NfHnNrSF&D?N}u||-Ijlj)+#qBy}S8u;VcfW(AX+{(}3RVWQ*sq zAeQjaWxg}v#zQF^r{Kp2HRR2W*6GPtKibGLr&d=_DJZbW4P?nbhL48T)snPHUcOH* zMs_Xs@D)=xL0mR0bjExoSkuG~ArX=g5EQ`*{SZzZ$mtErV9#v1pQkW#zz4sZZL zg7*G-^JnXrBmdGn8w&^A(k4XxJyA72hzDIYnBVK%Rn;0#+T{Fb{&s5jIXcLRf z!OMkIQLG5OajGa)WiD&Z9S2p+fB zVeqN68=iK`HMUY>dZN8~<3tjFdg6xT*=se8u4? zgZLTk`05@4&v3)@ZH-741shC4)(ae^@R0xyNF<4Sw7Pl!mtzlbwns|!ucOM!m#~d* zr@{Ey8D;C9+N-v|c2~!~GxOj_O!?&7^uAT-gxo)n+OXXfO#4??g>4z%Y&S(BS#3&@ z)iwd>X5$^x;F;cwDaewfn#$SVR~7et-cdiX^QllwknqSez|E;gPiVP^lXsEu$d#|P z)h@I_AU9H%T9N$ zvtzm1ACSgxxeSvN8Cd z!xv1_QHUgcEqr|@TUPk$zhNN63cwW>Gb>&xq#|c0dCmWYk^WQDZLl|-^1lIOr9f?; z)j3`>?_Zt#xa>{v|NC=8c7YXfk~ZX@*x(|t3MMDgcppfU0`9*N(^mVdq)N`_VqT%| z6Tj>O0u0AqLCchcMnYA{EqlADnb)u_-K5weY-#qIN!T1aUWBOb%b1zeI=L#Xf-1So zcu|}9gk(YOVe=-hv41%yV+(_hqwAVWb6)Gvy}0iW`b&UXfV7QE7WR)2@_8&e&fpP2 zYXSJQQ}SQH-)0Uld~e4>Pa$?B;P<|*dcj|8ob}elg2xZ44`Y~a-Hy2TZ~Pd7keJ&C z^D11-Es(PQ=L}i4|4T8cdQ@>(v?|c)f38AN z<_!`^jn7Tfo{7KR_41)~?7usLelWZjzKwoU=y-IiVCaA8)>(C1uIH9!q=@>P5||+~ zg0$46rTV&Ev|qGG0nV-1VUlI_s8XCwACLJJ!aZBWivA(o&fItjC8McW7WX0@e4S&( z+Yg7zEHR3tlU;mFgdaWHc?!rYWI5%$c-Sw13ghS`7Bo{H(WE9uN`1JY@OEYLs@}pS z1|xRG1_>dtmh^^;K|Z3#3;+HYPakmO&V)F`&Ax!o%-Cp508!A)HbI{r08%D=1OT6* z9RB>fs_ry@{1XOldU+#xF430i-W*d`x-~4xoVfDMElv0@;PamsQL2r795X|xHMAV9 zzxphx+wk`K<9=XiXOg%emiJ$t)_s}k6yyB182l3Re`YTZc;lu>QT+LfssZ8cTgM}V z4v2u~e?T#kKl6<9YN6g#)_;jtzi{DyGYh>IMZv_PYv_{hd@A$5MJw_3-^RbwCT z-zQxxEZk9f4gUF(Y4*bej;nu=B(-4eg(&1`f5TlZc(-D5_r`5z{H6WVZXWL%*SxT? z3*Aq7wS9ANuhQkXkKcc2_Rc-JgOFnU=SB}J>PP}iS+2R;E(R}Ok{V1CB<1FMG=o&d z%2Ys|vYHu|S$F0aO*jdo^ytr!kwRH&IYT|Hd;EsfT!jsiYwBi$ z`|Kl5{afSJNxF;s^*)4vwO)~@^;-B*-i9j|o>l+!QJnKfiReJlzcPHN8JWPDQ3x_d zJVPy{_LKz1BlEwLw!g=-2QAC=C-1Vn{tQvlGS|>BakHTe{`~pl@%PW-K1l;SbkRl? zPzXKrIo|M&a3_IO)u)F&8nuNf>XT|}N=i!Vd|OTbdIM+2oA=YD?ABL5l-JIkEGhi1 z%vADwH$ximemkvz$g(N6SkyQTf1we@#UDwvp7>XJ zLNrHo>0%NN5bOBL-5WU7|1#AKbU+px0=Qb%#}3Hue>Ly~m(T^nVm zFW^Fw95lr<`3p3NIdq&{=t{6tCHaCtZULzmR$mWSpFBn@Z%u~&T}=P|GCyqKTfUAb zNf!KxnNQhzC|B)NWlF!8C-+TG>^o=`NV8Oot;w7*^NxjWr>-cL2NSF#bm1;H$wEZ% z;!U9g94gfJ<)P}sC7LX2TmD@yxP`qyFaV%Q5_Jcl_j$dlPxT}Lc73v8euhqv;-Ml& zA+}a|EARZIC;Vt6Z<5sO3p<_|3V#4p-HNPxPG>|1;=^)K8G3n@U9^g*EyxJE3*>0_ zKEY?!n7`Xg^KwpSR#AG-D5#k8A9>IoTUb8io=SSEC0lu#U!hLV|N2Q=2Q=kbC=bhN zdhtJ3=#C0o2r#a&DHuZ5+1SpBbQuKSC^%ERMS`89$z){UI4bY{lpgAoFIu#GKl2>I z_HKue3^St=4bXf%-vDnQ>GE*t!n=uE*Cr>{Ng6}`8<;jIRgwq=O5f110!h?A`1v&I zsKzc=UKzN0|$-uYh5NDw`yO>sVw za{WRdOrqLNbaVljgm<_y`we>&p8|y9w&a?w)Kn{-9TGQ6s|Ww=Uq{^qu}H=_3b7@+ zY-J1Hum*NmfusQZolHAbjB8HE85(lba<89(a_iT`C|Um1uJ9LPSsUtmZjM-Q-)z!hJ;Sg7ZIPoWdO93yUrA-1bn)CdGnZGN}Mk#>oqDYlVCr?L5U0Z zhc4&>c&22sORN4nLpcm`-m}xO^q%$r@{U{4oYY#8hV866LS#(>H#-n4IGl3e?{$K6 z|B&o6z&CYF;}!tig1L*?zFEYK8=|z#WJ9SY%rb(yM71!6;@JrV5e$E)c-}N zYRv?6ZPM%W#vSutsxK0~*JJ)!AImAFzExTeFfxljJ5)aLyLr)sw}^zmtrd5#02oc# zoT$8+b_CTy>RRS7hsywg?zlwf&?17y#)INGb9uB8S-Z|L_vC=!8$++QYojS!1v5;s zfAN?KMyTIt%tP&m77@q_;OM~q^#}qB3;Tt2wXqqgYyvB|wdBf*sEhbvK{=DayFckR9QTGw^0Yt3|Jo)Hhg6)YYoxm+YW zuz131c0G!zq;G=7!=g7;Cwc>knLOB3T4Pz9vsI#hbxV-5a^RrAr#a2(bLC=YlrQUz z;8H}(x~ar6Z=?*Ujeqwd^w`^+91qoiF`5HX;08UDb3e27=EUbO-OxF-Mg*uZHfast zjq;b_2?&dHzhCMs-LGzTCSIyNnv2}rF&*EYnA!MS$eQ`SQ}k|raBX;KDUO1{nFI^}6WJ8w3wl|gI~MjVwt7+19C{4N}u{9y8l zvde8vTX&%HU9 zcL;l*q|ZIpv4>%-6&?RoIg;0t9{Hh4eITAP1=fSb43oa{SLARr2y0yVAaaBN6!v&M zICFREkk%Raq3IVNyIrJ6r%2z8-IsGjpt!=Q@%#rbZ|IYs&zE)Fm`)==|A`T7ShSH# zjG?-UfK$TwBK}o>Wo{5?Pyv$a&MNWw8rn1UZ?T}BHp8^CY}J*Zm8#I$@>-= zXa-jJe`WIx0r`YK{mKmtaEbqlER5DynQQ8qi7);>4f%MnW9sNo{>9H5(8q7Y3o_=& z`%&?0@d8}&H1;NiSn!g%;-JIXVnf2u9vbK_3=ktsBP=FtzBn};QjYOzejIYSA;`(3 z$}r$eG4fjCi9;ir-~jB;F<_+f7#MTJ#{%aZV|Rh5gM%SF5=+yp#bhC2_uuASL=>B#1g5%qccchL}tY6RFJ)kQ~m#0}n+7(4~F z$JjzgB9!-+0&&QFpyAp$nvbo7d^g4_9M`5&@tILy>jXFnUXw72jzE;&e(l-8xJl3U zY|};~k>K93o15GEhsvoENavGxEA_?0cNS1po=zgoacW8~BT{S8siXv5{buk6j&}du z%w~G5eu`Jw!QZlx6l?i5+l&b7`PS$sp_Y>Xl{acLeyMxK4jwBG)pVyTH`xoP*@H$o!>6xj_;jWRc% zFF*O7ak0NZFXG$BpK!)G4+PB}CS2tn)VvP$kt<#JOBoUG9k<+4dZWGPJxmq}}A4{jxBQ-%@ z85sw@E>s!Tf&95y(qnZ2%kup6w}95OY~Zsr1O!-Qa!pD~4SYC-AzP3&Q1$%^hn0D+ ze=F*Cl$oH@_6VBHHv4YY!7|yLDX2d;gEEaZd7v_`(%I;&+zZfw&V0N-O=NP(f7mHo0^2(7SwdO&matDut0wUyuspP^EMwF#x$4Big70a zcgXeW1e9cspy)AE@Uc-GTF#-ou2l0%FI&Z%$-)it=OS9=y5rs!!xX7yqD%KL?1L<5 zc%qb=oT(J^^JFmje4jA~s`X z1(l@;DMl0K=B|y(X{W%WCYJS&HJiWU#BR%Hc#heotA7vy;hY?;L-Tw=96CHOTKF}b zn=0=sJ=Fbv)vq9mV-m&&pW}@+#ql1;DUlX~s>=xIjAX7}VhXHqnjC8*W09QzYOV&; z^X@dMnq`DmwCmHQJYWeV;KGAp8k_Ok|8dWRrIYnddsf)dRg&@w>h4J{VTux^nUaej z4}w!U2u{;U!t{LKu((r^ln=7WsM7qPo3RiUaLAIAh_5y^WajORdFNmgDGdCnYG#6o z90Ee>KJ0vXYqT*@-KYIl{hQ;s-Gg1x@v+#9GHph#dq?6k@gOxnX}GR(w>Kv2n8!~= zEnfU7sZ5GC595aQZKdz|?9X+{IL}b10Ckb+|sl< ziX?}kdwwk0a+@vcN?=9S_sgT;o+>J3cR$?!JRH`8xKsA&23CB?y*#5*E7=b&a|7Ne1HqNB5$;j6?_G+FQ)eGF(BjcT4bsH$ zaD0%H1k5=`pf8^59kv$SA)&UNITQWzqmi<(yTgfY$+v3}9?kUNUx$W=%84hCk)<<@ z9-Ll$?!{SA^}V)7U%4EU3dtoDyg-qv6eJV{U}B>%xofwP(L|{Z-jAU>$x?Z0J2%H= zq?mvIE<}brfyfY$35V7$geYcRy!aIDp!Nuy7zf(o8z6yzF~c%19$}D5$k@#J%iy!~ z8tdHr3gIMu3J>lf>VMIGWGkhYD`iJav)nzFl?G+)UyuHKnQW9UWSY0pIk_A|I0fdDMWSKj|&kV{OAtyZ(2o6mJz$3ttyFt8o_0UWeV0Ts-{s$>_Krb%pI){7! zly@LC;gq;}xl_Lf$_YUN#b?+CWVDW;MWQ0$?3ih&!K)QuXEl%MhpvN|2buN(cSl|c z>wR(q-;D)b=-sjnG+4NfbMD+c$ax}HI!iai;|k0px7cPu=&Jw)@2EiC-fgKrr@I>v zp3L{Ls*%}$PY+6MiQdc|0n5X65Tr{Z1*+SfYIjs<5%$9$Z)xB9`fG3(0E=T#m(8QL zP+Ak4dLW+mXM$zb*48de5Wv-lXaz2S?T?=q89rsWfp|9#e4!qtN_yD2b+3koD>(r^ zBny#oL9PhXo3xu%KCW**|LO4Smb+fZCEjdM76iiWqpB37S;aTMoH)^nfrGV(Qd_(M zGA|j0Fg!+3%I+`sH31AiQQSLpq{=m$h*(;7An#TwNI+0&u#`rVWXQ;d*?WQfaNT`# zVzi}8V(GOxNDPYmvQ@`{^W^M44qOtJ3f?-%UcP$`8Cj1)y$~SbtMpAa3HWVEdl%*P zj**m%EaLU@`tFC-dfN(H%3VLY&D4CmO$x>j}5L9s=OT3c%9L+6RlN z&SSuv)A8%m%bxw}+@F`yTfPS zpA+%p!vir1RV*ZFmNh6zM8WY%s{tjW{=hM(1d=2VM;tDL9MsD-M2O9R)R`hUVh3Hy zWboJY!R6N!?N`0m{Yz>@>0vx>kjtv1YpTsA@LhTtD9v*6w@ z)+_zFUz`>lr@z$Qbeb5cll>kZ4$B+>)~KnV*@P&ok%0KNsV}+KpeBzo4@@L1bo|(W zMp_C5K%-OBgn!6R&mt+*=rj6onS^LhwJc-eijf#l@4n|))h^`w2tn*mS@r4DW5EgO zJx;4w2N!@c`8t4BrRPTd4!$JM$|`9ib;I%-6+{$3b&GP?$IDqEMK{qnyYMezJOm>4 zL*HA7=3#O~DMRpU7^YeUpvWH4emr}%u?ESAXdE61KpMCfb-}J3`~;N@9}l_~F*9=L z-e9@;apuV6LSoX6OgO;jOznz8!%UOADb6CUL#zcCFkqZtNg|+c3ULEHG~O!0((JHH z!bu3iWLh{ySzp6^h*0Jk5yGlPAvF~)8g`glM2m^M>`Xkz^}Q1wOBjJg2l{@_ph%#H za;A$_#X~fowkV`wlA(4aW*=I@6YmbrmsOa*K-hJh$>KD4!34!>><#GhY;fAL0(xuPsil)^|Gi%I~+uiv&nhIKru{eZ#zq-JZ7|mJL4hT>@G!NcyAHfZE9ydeCNA< z71d3-oEWlQ8vOBZU*dd@!x)`-c!nPZ*1gS=U5HakctQvrn;3CD>T34IvAjhLqckf@ z#pY1)*QK#;I9mni=%`+@0!O&Eo<`71ggV!R~erTAxOB0+02{4%vvK;lixag*=(TPZ2o$-y@3@ z;$~b;{bmnD1{I8>tW7HFT$b_5cwkat>+k>G2qHfw|1nt}2)lD19N55( zAT$|F7!|t}Q(s-e3MRHj-BB#LgzSavNTE--VJ&x(a<;50R|0j51b`IUhu210wyd5W zn4lddDuI4Q##Z+GHjGNbSdHUYu)LHT*45Ve-n)zGJWnl0L=~r&+Y`}v4m#V%taflC z7z+idu2|=KRF;6+1*eS0a3}j1`pN=9#t@S=xE+O&bztc`z8d^W?% zqjnetdVdu%Zn)>9j0t5Zo-itofyN~<2xO?0V^nN_Go?v-xMgBln6a0U1cjj3(9!1( z+qJCefDm0urwYr7R&hrJ*sL{qk{`EvmJl2Dj-1a4m;dGHZ?sgZb(5YdSCCOo4>X8j zaepCv+lonLmhl+@9&!(b;*L`S?A0QrfvGJcKqe}45e89shZd4b`7_1}RI{e){4how z!b}rjy2gz%fb+r_hg!COFJ&B3eMgzVCH$=FFl>tmY(_;~XEMcSl5ixM%w8N(W{=#T ziOOipD$KIqbMK4P1wC^49*dO9ror8aa}JFtaL9xmh;opyqNC2Op+o9qAmiM^Yr-`= znn`NtMm{+GzANKpalS_4kYRC@3ki7m9Fh9veS}UA%t`@?q#i$$I zJZg_Gp`I<%Jtwx#$l!#{nf%YZHjMB4>2x#HF zBVCWHZO6-WXd&&mt(3!Sp<0`J3lx}`;E%>NJ}`RbE45tcp!kR=c$s;OL~ETWEFrDj zHdCNkJww)iB2vF9UKU}6AwO5f(M!d0-^XX$nKPKPx;>|QuMwpWM z_%<=rhG%jQmeR?A^4x|K;F>mFq&Qi;1fFU|$~=943fa@<*f$&T>>P>sr|mB}@J8>G zlTdxZ-y))Kg8_r{)I)6h~Y)wJBxVsT;IZ{!iwOVog znxJVaAi!0&3ikkEd|1{?O|JRco8Ur&V!!RP)Vx0MO<59v<4>FQ6S;2v5}oaQ za8N25o^D>gHW+yzCUYJR(Cx7y{#1vK{6F_Qe^UMhnp>Y>!{9hrSL1DyV-Ld+jt(|T z`V6MnFwz$dAtAcz)S_R#R?TF};!S0q7o}&RNrci@3Oct_e0bR$co}I$)Q3NXzfm8# z$n2WFnsj78{)FV*JkWr<8s_3=@YUoDGTnm|+0<`~D#QMjkMI=f1b;~27mc)!aVI2$ zG<_g{?hr=t;FwY#;$JKh7S54dQF)6-wE3VgL98Qh$Lav z-|{;X`yW)>9*u^n`|02hrokn4{?*rDv>I^Ld^8I0+@komQWt*uu9w+$_Si%MduF1nAQR32|8i#_cd`(h*B zzX>_KSbmPHQ~pDnaWPc?v6)zeo+U)lzHg~tesW*K3^&4~1rowFelq{Kl0Rsb{Ldj> z4AGvta}Kpfo1g#hvv76JG{iBc?N8VwQzLc z!H=_7v7n#DB2x^<5347+K(g|!gw)*#M|qr*+tL;Se6|hu5d1A`(6JBd-m4Esq_6RS z)~54qHSG(1PrgQxLa-yndg8XkaRxQ3Y=3pBiGOWu9zZ!Mk)+Nlt3bH5)$z9_;m+kn z&y5@=3Tc4vZd$^#h}&bRajSYGKEj@*b3%z}zHpI30_S^Nl9L`*?<*G?eNY%Rd%D!M zoxXxDhr|okdv-bfLoXK|`?a*TuWJV$Ij)?LhW_FtfYZxob&*7$59nvffuit#Xv?*K zVLCR-ub&f6lSykgQBwb>9tu8EQ;ECdvr}!P8uf3joAv6qil5(rN?yOF8E)TFv*bMH zpUdQXR&a)oYQb4-o8HG3mqdUc$90HI=Y9Ucry6<+u8JKcjuMLQ+U_s;JV27f!U21A zn!lhN+7kuk4E-c#T!CwMJ3FWCQbm`%XKRq!o((H80+%}@37ZPbl@nqZ8(aHtC#+#^ zfEtvTjD(pv(_$Zzy&;o=5Rs_NLX(;XtF8xj+1%Ylm91LkUTr$1R|javeo@==%N?8k z`kl}jfto*n&4rnkxO}i6itxNnK%O7~M5vPYZg)YSQJOFK%`86wXJk4HxS@CCIGsZ| zURDReKM&@lGR8>$pt?U+ujrk${E@LFlRgac7k2#OIF+!(%(O^3ssMH*K6fpui-y9{ z2`;g6wJ)Pt5+Dx%*4|P=86IJ?OK5|)phmmtAMtG{C#l-Kg@IAVHt%esA^spXTxIOW zr$CE=C4pi{JbzE~?%0Fuw_|CsUmOE#*EoGw(sUe#PICpqYB|;@cESfFeC@N&etsF=7z(Ukb#xv2IQ{&!k_F{vO9Lw6 z^W}Mjd8lFsZ|T1=V-)ioEMp9>*;!cELEqAo^_`b(qcXAe_TW30g+|_c!OO>huz66i zFh2Z#XmlO7)8X6qPYyf3e#n~0S+Y63k$E`IA@?@-=ov-E{IkDHwI7c;*_)`oB33rl zd@JxYx9emT3{}WEIJ}?l>!+Lze!okw?fT4J;?IN<3HE|Zw6r= zf6T+1Qz)#l$6Xvl_wWBfV{rc$<;3q!xF#OGq5*2n`0gYFuxz2-4B);?1#|37Eo)Xx z|I@{3eQjwIbF=`P`!3x6Zvc!JU0ql-Onq^y(0aIHs796BzD|?!{i9FXZgwl}(W^Ei zZ$57H7siuORv1l8%SAeHY|Md;cUbrLUNB{SMFGZ)z3(H_yiYG5Oy0m7|KjWA8h@K6 zKil!WRfYAiXJ1jlkB?msmKTs<(I|jWJJZH`d<*m03dEH7tAigB?bF6K%w*V2-5%FF z9fXv|7O|vx<)ryHULN|O$!I@VWa8Gnp^ox}xoM2X8B@-PhO)PdK6kW=JK(AAc@;wPsC|v1rUd z8%0dS;^VDZz~mdhw-QCwGkbP<#g_63ijQeOYbFZLQ#h+0skkNE00~J@*p)>8>OEMhbV;R^3luIl48dp{Bz8y*UFU}WuL6P%|=Z| zC^&%g0GH~^5w!W=A%nRh<4F=myyWnvQKAESjm0s16k=vl35QA00fbCqJHhS?y7ar1 z`TZWnnQM@~df~&*{eX6~0u_4+m@Cp{0_mkdVedZy8gZ}5$;nArcQ{N|{{Z64rOs$( znK4Lo2nnkEkASLg1c>VVeEuVVvR)~;Jx&f}2g2yvLwfW;x7Y-UMQT9tzacgKJH{9_ z8|n$cRnS-xNDB&NkK9Yw=of*0F>~0Xi9~D!Ko1T}XxksXB5!EdZ>uSxhhH z^m=%>+QVK7xR`B#Dzm(_Te5Ra>Q_7a2LSmERk_YD+~)i@a3NcZ%qgCJDu z21ArVsM5*7#s|R6K%8uKmF-lmw_5>Vwf_==Y?PQXdoArx*T<)-}$XcA84R?Uq@QPvHs+z3uhjXE%%0a{&ar*@ajq*3os<#n1W~ zDfq?3wCNNwFF#x0mfP8`n3#A-`%p*j%)NMAA8O@lYau3kuGYJt+`@A0zjU$!{{S=r zv^**^OSFjByWKh8a+Eq1Xvzc@;r_N@aT%V1oC=1F9Am$zbdo=b z!=5NL!@sGpU8aDo1A(h3uvKyH9H%prg1gEo}}VH^<% zqJvf2l_ycYY5=I52zG;(Qmws3CVB!U7I_xcM`o!+Fp>_wyYqhi|3K*dShQo*_a2%; z!VMx81_jqRaw^D5VA8FVUp9@HnAX@m9)e5UlAdj|lE(Sy&vLlJT|3TBm*fNu+dc*C z^ZD-esh-WaHQqK&6M5wWklc0PLUGlQmWlohVBH>G5Axv5RMH}ZQ*joZAs1o`dJ?XP z$kd!@3Z(Xgg8SoST1=e#^Nk_B_pE-`%7MqtS6tOu-O@{$HbCU<))$<3DO}#PFDN9) zQ{sD@Brt1_Q+s+KK{b@RN?>*$Xq2UAFYTL_($d@xg~W$D@;YyU$xlsW0uBHDs{T_T zmtDj{_vA~Fvf=}idG1gxQZW9h3=)KXtX}2ys^3XT4D!OgtX~yGVUh+kG`)<1`|G0v zE$}p0d`!%9PslmvRXE|>=f~_yUuN~_M57jy~t%P1g-Q=%m;|$r`L&c?WC0X)utWO~^#esyLX2FIX z98?Kko!U-9m`tv~IM?mhy?|ZCs=-b$e?1ss^@s)cQ(t$*XT`ZNCPnq6R%HXd7eIQt z-g{D z@NU6)B#9&e(&Q&WsEC`SfnhY_P*h_aW!wHzY?;O#V_)|VhWjf4b7v+nhp2GWZxvWOFJ7;ck`?Mbuq)I|b}Fp$FTQZ_|pJ7#D>#h2S|^4HXQdFfrEhqh&uH$uLx$b8{(hJ=p0l4yO(d{ zAI%@=vurGYX+axUHr52BSkx3^BFWs>q6!HeguZ>q7rmAQ2m+!BsbG{s1Jp)PoN>PQ zb}H{D07(;)q#-A?x|&voHQ@_^7a0Q9`_{7tHrj9B%yDT>!0Xr~|jScsRBI0|WQxVc!h#5BLT5 z$wgsTUInqDPz|x+p*(zSFWY^>5`%V-3got-yR7cV5nWNy6P3=7AYM-O-fa8V-%mp> z#ggdhLoTA@Gr5_Hb9kJ}<^j(cgXd$UHn$5c^7)0)2zjAnK5WIA?RT}{-!ThUfE3T0 zJy1A-97|<91!|6A++&x1hTZqnEk}u!frng0|a8P$yZlVI_Y?~Jtu z7(_*E;(c*;oM+Fg>3V7hA0^Bv`60~U^6RQRFk!-he-kCRaG54|_HZp;p=Qe z7CS@01`H)8wVSDLDY>xb1iwL?i43SSL)JxAAK%>2Ij(E)hG%{9R0(Y+VGQffikF?W zg_I-GN_0}stQWv&o*MAsJPvB6&$`W*Z44e6uw2g#vV;@5iz6MTAP=anz87Jn0XE~o zUf7j}deH~uBp9N(1Gou{qasb^4<_}}uHKvc5W3b-Zw)0onSy;<+_~^7<=b~2xpi>j zhJrp3Fa^xF_2L~ zFbkaQc0!i~BM2iHC)6+`NGy{pNK&)Q_o(auQ=mAw9JmP7hb}#YD=%#=kX-02$+N35 zGuKx}ip_%_M0)I|(MeYXF{v6*A4C&h>U|VfiltKpohf~GF*xkEWqxXlW&+UVfzw$ zAXLCg1D7P$XS|9FCoYTq48p2RHui2`yX|ssrin95&RngA;p>V1^D2d}Gya6T!a1a9 z+Tfg`BC`jIJPh9wEtBiTle;~QfmZxWUFOVc4M<>RewITwhsLmkDy!v!CN$T)e&CxG ztSv|&$G*8aTz_7EI25}RJ2ESUu(MEne1#1=yUqpwRZCD&rm3vrW#Hr=9O5a0i3dWX z8qB3;*j%u#$dGaZw&Ey6SASmCxJ7db<+v@5NZ)<|%{CnWiKF<%5lxuskn;*yWTTiP z2-=rhr3({1upO<{e4cJ2rsArN^2EhO9q`Q}{MGrJ8DDTj{r&n~&C04d@-B2a0QNBB zcj4u5f{QGaa_vQx^+Gv^mx}}t5cFh)DQM%r!Z0$BK_bfZZ{UMB!{~?Le7ToRl_)L` zsq@+h=OW}4HLTD?!ND#!nlEQ4@i46Y2Ia!TxHxCu-Zu&Y%y4CdMbz(zHTLf$nZfdG zNlg1C+7#@pQ)-6tbd0;R{ATovZw0Rmg&$=)l8?8@CfEd7!k)12C@fo)alpk;Z~jnSc%Zy7D;FZ6%#_>Cy4N8G^=bIY8z~OOqCZk7~rIrWd`<`UE?L z4$gq#trbSM7L%a-!KfRWq0pB<0p(H&6^^(>j^6F%J) za<=doj3HjGmbI$G0}qPbH6!TQQna`(F`QWW`E{?;Vzk)Qb~isX{;UHB4A^-p|9$2v zLG)$_UsMka3kUbC@rvJe1MbE{4J;kJDH_EN*nZaVZ6s+2!E!2IG4eL{s(Ib_kZ}CW zATI(vbR{>2ZRfmg76>4I$45mb8WSAAWmRtalRJwQo6% zk|0e|50w_9+eMq3mSwp2tEVr$YTZUTDYoA=1uv9JawYQ#OD$7wkggCCi)3}D8=e>T zMm}yvUBMv!EXt+0$Ye?Epz(DCEzr+TbzOUIOsS11D95m45NE$rlb8=HBSYA(z=AiE5ZUFdnvdu@Pixt zoX3gz8O}R7cP&ONKdS)F-NcK zu~(cBE2Hu)-gVDA&&Bl-u1eOg_HHUE`7`v;;znFjWBBS9DmDFg;4Pcst5m}g1UPg$rn1L*e=!3^ z2QpG>U`|l>V!>xlBeeNerPHLtpR+@+t?!VsAC$vopcs5|092(X+dxdeBhm|`Ar;u9 z;$Nkj{~6fppp$j$`vF!?zvdpd-Vu!sh_F6~n~spM1=v@PK=WL0yWuDhdxI9+-SwCCr@52B zr`{7NEH3m+HJ}S=gDmhU1Ui}^G0*++3P=9{z=qg8(*(>l2uD*h?7?mQKL7~{Pmi-8w~fkl{+r*8-Z z??QkR+l|?k*Y!7TLo9x0zj|~npyC3ry$ODbju5~_QvpK z)XxJBb8`i6kaQ(#KGQ3lZYpJt+lFo1PWehM5H+;`RdK~*{cO56g zZplU$#(<+)7+(t>*zpRW6sf&CG}q$^)$JobH-p?EGca{$zHJ;R$`@ANbR>&9O^CDH zGXTSkP2JS>Cbx@bGG{r#c`DS=8jiux*1C)`7`HQuIu=V1y%-bpc%hsIR$&rg-F%uuwlC%()8z|n_Nh-?a! z7U>VzJ+$6{*okbxnDTKJ?}328lRxVb_gcrlduuuZ>l^`xi#J{BBE`vD;He=h{f-EI z>lv(IFriSY8|(#0M+J2&th|BpP@lXqNTdfWkx$u(B5;xWjUfnWo|2!pFc>*ZqQ{!p zSX)Lo_G>@XL+7Kmb_h>Zm&aHg`U%tS&rUGg^ zxLkoWwB*lUs&?GNy9vVc55kgcUX9n#(j;S)7PC-< zx&}8u`cMQ6-=?7!BJo`(Cc2a`tJQYK!xfKJ)Qsy+)dqNor?eu7!m~#@c=4X zs2oWHNeu;!Ydp(AYqk+ECz#0AuUc4K=#h9VQ_2fJhl}@!H%zng#uTXP4nV##k`HXLpNs*?tKTummmRxa-K?-3;Ogwr zaZdmTLy|(;#Fe$)iqDYm&MVP(&JrCFlV|C({v@C|cSrispjmC=r| zG6%cQ66IdUR)mN_4hrOCby@Mb@0MLxsz?+Ln56y=I{8}AEFay!SQ7yyu|GKWN(0V( zQo-EsN%w(U2cY9%>>NON;}BBM5^$6WCRY#1+=Sd@!5J}j4*aRBm&t!<`UzUbN0-_4 zjR=VUgrDqNvag4+q**M*i1!|=V7(2Pl-!gMhyXIBLZ#G2&&FB*jT-AKRyCduwjSB8 ztDm5)=dp7u@-0cB1qMw7oDOiOnk)exYJ^*d^DQ z<&;1ry5F1x7ApM>tE#UnQ*||v28pO3Q$IQceCO(~2tUW4-;z3tv#MtXx8vjkf4!O6 z6|>gFydvm%jkgcnPjkze2J2JPgmONmiI-(CNma!X(IZK7r_<9mmP33;BUJZFDPxxH zRhi2w_cy2d?jwUi<1<(aDVHnMgSsfFnfr`POAT5`TTfZLvw3tA4S3-^e)MEqNQD)MwgT!T`);PAz5)?T z`xVqRb{oRR#j72*qrqEG-0BBzXUSb;bORNR51e(tm~c8;q0r1&M&TSttUgq1u4)fR z9k*xgB2~TKap-W3@1K0*Ink8{4K>#k0E(GHptA&5Na%{SJ4l;61lW7YCX^r!03=9< ztq64d`5w)NLs@{Q4oSfq=eqs7fZ`08JDYlJ2w7c#FqN^80Ct)OPCWQEHYL~hQs-e_ z>PODhe-i4AZ23Aopq0hgFH6QC(tdon<-EW8qZHV57^aFkUK14TIjMw9JZ^#%hE#Hy zRSI|&6oMVt!TC3FJi@CBewP0%1ip)H3~uU;0`}Ty>4g)5XAAYc5#SMO(G*Trd3HEG z4W=7g0-b(|vB!@)7Zf0~@A@p3+W!fyBr`*7ME8e38ao200m{(EAniM7nfwx-)rYSQ zq|oLY=YMUAv)CSAy=QrmAOLW^1ZwaEL?mIqOd@%7jFi`?CGFv0A<+Mq7F;LWz35nh zAv~KyRrk2>pbhLI&V{0&bg|UB=RnIQm;ZlZbrA25?bVLzd9BdquI32J4KQqaG84q0 zKgFO!a@?u@%(Di7YZnboJOBI@()8IDg$bq~%G%prTWImU>-|JBYYPaqvQQ#gAIas{ zuU{`Duu*36#eMjP4YSM{VeR^LF14- zq2|qrW+#2iNAuJFAhVkQPMVBM-VuH)~2`4u+(uObby zdhQWCP?pC*NGBKI7jFsis*toFOr|!2`gson2LKnekdRgFVoFKPOy_ga=mOdyU} z!`lY<=kl0m=nF}f9mNR0YpjTZ6UV;l+!H`;aSyUUzXTVkoN((T{WQ2!e4RPxh20De2GTDJn(o(3S)yc`pO&v-K zKv?`*$9LXPpBKI$Ik#R1KJq{Hm;uGrId*=|&oScq_Ke=IItkL;v|o!~|NUWorVHXD z{CG61K%*Y$Xz}^~^u9q}NnodIb{9VpA3%J_8k>SPVis4Bt4XD&nc-bt2-5%|z|Hp+ z*Ojgl;tK4Z)1aS2@14u--U25ieo0dARMD~U*hy19Ie#(p7$wWwne1Y|2M#)ir;uro zAXQ0r9bo+rfSbTk+*XveSVoi z1GI_=@&LDsf^w%x$$#%p@p%R~c0tK;5=SZ-3zdQ^If+o_RsmLMe>j+^E=dZOCbGJqET?+Ue$ascJEBSEDkDjw&+u{ zb}wmBh*s`VwRx2D(kzcDmTDWcnNYkd$pI-UbB`vs) z!Xe24E_&JXMjGcP1Q&p&j?Ud4Ip-ef-Kg+%e$c@Tl99#6uq_0&J8<@@HK1|t(Komn zQ}UgW$BzD6H&2i79rXrmcFB{^9byOyap)%7af(!nG$&Ld2>F?djOPTL-nkvl`SI`# zMl6A(%lK>Ub|aCf^OQ81LX%QrVxsx)-@lnl?$!tRgPg21&83lG>f8z#?%WbE_ROd3 zfv;Twa)`Hyi&6rjl2|fOFFd5r08J?O!Rg^o?@9KlAMiNq0Q%nF`%#9^HZUH9&uoK# z#pNmF=>v=v{R3F_8iBvk2I$D=-Bv3mZ8qAPs@nhvTM_8KbgU%4`T=s(S)-TnDFgi= z?JrHg0HuKUFEoHXZb*2Is#`DVKfL@9hj?WnvC->dalT`#wb?i2iBPA`<8q%Hb<1d4 zk1M52LxqX1Cy}%TX-iN0E|5Mr?~qz;E)_yK!ePKktrVJZa^G4T&(WUlR~iyqiv_gn z6FvJCT=W~P)4HuIgqcp7FRr<|Hnmjy{dS`jKsUS2Jte}sjFgjh=ly2ADv$O%-D$&R ziu?%bH>s^}z=Oe0+J8?A;Ja&<63yiMwE)-`4Lm_0ErNthg>WzW4LxqcPBP z;K1Uy9Ypjs&Qu_AX0{=OgX+u0845K+j<9ClDjH{xP#;xt%edZ6pO=lUrVN~eK+S^3 zWngc2%P{-3J_*Lpb)9d$3zosc!=Lzl!L&aC;qH1p$cAlFWQt0f2X)Voc8xflv2h-_ z2}#^rzG2;6)+tc)T}IGh8ekinX1PFzaS-_DFmUq@L3%QTA}6f_XSj`I^O$1r52jkE z_iKT_Lq!|2?+EB!um|MjyPjA~mSbOR;Hh~AnKRtBcvQPq3)1Z$?kma3<#e>_8{Ex* z&pRcKvvtcPhwNt^6ho1BzDEA2j{lkVk+$%{0nVW3*84BvqnXx!zOD{}c-O!1d6b4J zoF9a{eAUe&%fyAxSK|RXRDBp6tY$Ni7k$%Vq*rN>S4l43lfjvAzfYBv_A+-!oS3wt zJIAwS8(?Y>q=qQC+_`-QR5^P^S4iK*b z0Wp%RJhY(UNzFdG4gY$`+a6BeDSk)48GiZ=kdrrH`@jNQZ9>X=HSqJ1^Zl($_I-%$| z@!A_OekA$EQ@Ci&Mn!7)H$*KQ0XahS30NKPtq54b#V}VA*l@^*u`B_p>e^S zQi1>6BuHuwA|IVL1{{=Ti~@eo*ZDm~6bh#u;%A)%C!BubHUz2S#s@wA4K-gtQ(~m4 z*1=#UV})fSz<0^pJP7$}J5-nwN!pCh8gMiLU_U{aP&0Wj=BxpGpv+cZCm@bNF^ngR zxtYSzZhNGNxRcGrCZt&!CWWLdN>7*Zt>#gZ*Awf!I6z?JE(6zj%d^Qw;#YVEyCmr@ za^l9%HUq(NkfqNVkm*zi7*|)hvamWt#R&+%ztj9A#85$Nra*xMZsNI;`x44kml2PF zw_!EWm1e443a;=t`N!m{YU8g4H?UggR|s}*IKvpT&$MT?s2@_5v6#`DiKV9Y9Lm_RGm`HXe}&sc97b4QY-j zl{2L<;+=!5C`tI`%ZjCNakR^<@>M~U6dZ3*p`F&z=mNV0BYR}lBR#ZJgjK<7Ux;bB=d%0-uW!9O(la0{-L;3ow~I1N@tt|RC$zK zstl`Os};VH-f5;h01~#}vVR-BPzl-_vZhA1d>)M(I6lT=I>MJl5#+HVg>Ct7XJu{Uu?x}(#zuR4S+Zqd;lG~VgI(6Yogq=MW?9qj zMl&`TCvwRYi_QhcT9G0owrD<{pX$LXs|dTY@em8fd_YaERL4Q~m>!47BhK)WYmyyn ziFN`)S4SKVT|kY$@wB~26c}o3sd7Jul!tY9IJnjD9fZ%ubuFf?SYAK*IDUHif!QvF zuCgl$+t#zI-+DThjNPZ@PM6e*cqUjNbZ@=ji=&L16cH?}+gcNG@!2 zLg?Py&?<=vjTCuUgyPTBPFu}1`yNimBZzXesR?0KK%qS@V+D)K&{<-Lr6o}2BeIHf zYS-l7E%wG`{Dw2a1PP~DS5@8Pz^ZH%=1@>`BsZKeNtXp8diXG33nxvTzi&I zNN`OB9-l&jFi5CUcvF0axzcRTgSi@}_1;1JIfmiN9rvje7XS0b14nwEu1Dvh89@z=j-t2G!GX0wUsp0jVd$J{?L@!2< zqaRGDbkH-D;x*Y$inVUzR{c=GGX4VK1mH*J|_851K9#nz}DB-!oE zml;_ZK{V~WajC7oER9vah7>vuj;iB;;e!Rzb{AbB`J2W1=WX2d`VM8oK0%npf!4#o zJu_r@sYb@bo~vEt@%B&ub{jmZ_$-IC7Dm6(+Fm_NVBw6DywANM!xCZZgx8Erfi>wU zHj>6f*6w?47!)DAcuAjhsm-q*UiP!tUVmm5OFj0j4a$6DuiPv8E}bOVHP3x- zjdv_b*d9h;XZ5l@o{>u z$uqdhd0GcBJ5dZL-QRoAC)k)%-_(N2$CG;!!PjQ1#F@nIc}2~C4n>AXTE&Eit3Wu^ z@N+lVZ5Jpu6oiwZCgTNkQ>N(iRYKfd0(dN%Z20)dM!5TnDgGs+lRqCp8f|}&Ba-7M zxw3+gL9j?AyLUrqui8Shd@~VT_0J{j8N}Dv*dpv6NO`>a>OypBD|5Ea|NXOSHT((1 zqbYGUqALd``Zm1_N|;AmVmpY}B9C7;gE4`3^_!TwZO``?rS=UE|3nW}iFGZ_e!u8& zGs6pPErDF5$z`)6UwCo;xb%F#^!}z=B-7xz<9Tl55@~Yb zZ%2=;eEu%qJ7X%SJ@~UF9z*5skhwRSb^PS&ZYP3FlpgLygMgvNuRO$I)J1I4(t<$ zL$X8|@(K*}-YoXzPJ_bVby$NDU%D3dm!df`;T!rQ?3s2O{ai=fm6J5}SPhZ5bG=qu zD?w!(!(&=u&L)C3Cjx)8hsv#<*Ge7!EFKbeo4;K;yDZfI@s^;UOaJSWoq>EwG1$1C zu~yx{l4ib{*>M+wLjI&no%|B@T0QQP3O!RR@jh@O$J{vIZN1ZrQKRg~vhbbfnZ$YW z%kw;rU)3~FA{s1C#ReOrZul~_A^mSfR8e&@M8f{22o+-4)d9B>e+w( zvhj$l5jGyi?F%U3PdQV$3Hy!DX$Vap{!aQGZK?mDc!9SB(pU;E3SJn_J^RhB=liWv z6AB;URS!i}OsV>oQh&uUPk*HssG*N;(+XH>+4SUUPhYw5nV|+Qne|oA=qo`9!3sh) z0}e%z(yty+aCB{&VYt*D3|9*%;I0ro?n6}MRRfU{S)WH`%YLGxpWV5=C_=tMV}#ar z2+qwzh}N)r!1z$Uv$}7o&*px~*QwM?#3LCq1?IgtUR&uSc0GZQ1Q4Pi>{-B$D)Zv< z1-WSiI+ME0Glp^3%}3*SEHjGEI>pj)76qIKHxC3jlv2ASJZ9}EjD7g|(Zl2Bjy5qh z9I}8fV%dHol?M_Hx$4^u^`sGquLqqmxjXkw|GBN+cCtL)c3_*!7@^>9&YWV+^%3f$ z@$KO^)lwT-&u#O^MmSsI(~_9%hu6KziN$c8bY(iGAHJ#HpBP!qiJXXdSAKCIdIl4~ zpu<19r4{>#*sP0U*`uTOm$4iMuk2RYMpj?#_p?=l92iO(7fPPpGW%`WFQl=Ewu7E# zYNyuTY9)NILi*=%Pi+5&bDm^9&K~{O-Lg+@WKQe{R&%>Tsq8&_95pvpE|8~{fLa7b zYnqjR1VaTkZP4^yUHMePyhU{}#;QO|d^S@0pq2K3l7|iRuYe)9qT=`g$o2qjL3FG} z-Wd9@6VtVd1%}G0VA>VX-O7;eB?CBo=?U8Y+Cc+RBQsw|y(7 zQZ4`6-Zw6q(y_$c+Z6JCg45K<-6tkR(?HU38($N*Kfi8qiT>mb+Ge`+z?x{-(|VNqBAi_`cEz9$*^s~tVME3ZhyKjFSQ{3895Z%i*we_f`TMbK)f zDmwMicUcIY2szDzfDNW}G^J?lB=7Fk!ZC@m(qQ7H1JW0$j9+(ZO^PAgrO(T*c6qZ5 z=*@@SH7V7D{U1kOrpTj{6vxEH`rjK8O1L{R9*$E7*!}VOe0SL}i7o5dw8}Pf2+ydr zkIUSPM)B$E6^$C&-4{Z3gk6;sGBBdk_lRSU?&0*?4VrD$91M>i{#5tcgza`{K&BM& z=XHgrOa?hI`bdu;Cqjc?Z1#fT9N|l+F&q>j&{GN7DW2+ayiqHa>r!c$Ycw`$nvb7Z z66zbavs|4_Eb;a>Ti9d$Vh-Xr7dL(R2(-^n9xGLO^V>vMOSylLn(6w1e`5Pi^7ue` zXa42I@y)3ZLbTkx#G_huT+1|pD1XP_Yca(pR8Ey&h%tc86LtoT(M6`@hmr_K92BS_#~gF6&V2*vj(&B zyUtHpCLe`z1$?d$>(BC1rgiTg@BgHIJlp3nU0d4*Etu>|fk`o81kx*XRlZ{TyZUO3 zI!__OKvsm@S(nj8ZN2%R69lSQm$(>5Cr)+M+Sr@{ z`vU5%_~9*9&cWV%AG7?hgZ78*hSoV5n?Vyy^NL@+hn|%Po6q0g*$)dUeK^JeKEaPd z*~VqvmZr zwD&m~g}&^p_187vFZItoR_}|w6dZ_p7eFZ!xEXQi8ZWigjJ;m%)BcuP*usR(NZ5YU z!kMebc!Uc7^;vbjLD&FBy=pwwYlQ4ZzpN_;g*?07;>WpHt>XJJ)?nnWkb`Ztmur!| z;qV}j2JO)B?_^tDvx(U`_LXNF5=~OqTC8Au7HtlHubJj$Oys0E51xPV zQ2CaChwuenqZOlPne^_(QU_}eVij)RcWG(qLynFllliSu@{B|)M_Vwo2;5~x!iAZh zQmw9A8EYBh(I(|=gNfp>iCg0sAeL*Zp0N0>!Z_ou6We8Z2RfL#=+D&`WGoZ>%5INv z`hk}avOZWJL}+N@RCpbFgveA6BEAZXhG|{tuJUwYd{(5bFJeB85z9U0;!HK!;(Cz6 zE__lvw9{G6TjkTS*JW{7PE0GZ&SdLxW^TdZxkA_DL+iy$2ItPpaS7XXZZS?B{9f|# zh|M-4==9nSVI-0JF6 z*g*cKqW1&OP#LbX%3T^pRGXMTk0Z0ZsA#$dHeYoVL7drP@e2zp6Jfh?Q)E`ABD!E- zoW>N-{`rXzIxS~3!B>l8;XDh))B#cOKe7CrTg>K#jmyf@}wS#1FmpvoSa%p`|LJyPXaoC*_;?ybxr zgV0D@r9YbKLGlf9VeA9pF;R-L*X;wKC){VF4p$f`d%JxF*FpR=oP2w06d70Ff#!>6 z7=5a91hrr@0;{I2Z!?jU5OiO;!}#hhN*FS+HT&7V%9&5Zg@$y9FwnJ3T(B>Gce#Hs zHa~2)ThR0iCAZO(Om>^TT3|@;XX0eLgOw&>w|Guqh{)L5Qt z9IJeCUG4k2Ghy*aqF{YZcqK|Y&Gj`borc?N^*H2;5Uwb!#A4n&%DyxBZDz$dvSu~i zBJeHqcdHwrl9zLtD3=%@Ch z*=ci1q!*|)m&K&JZ9h-(z(_6i3;m4Y6)w!LVEXO?OF;qdb9Gd+ z$9#IPuk9fKV(uItOneHO9>tNBXBzfWMBcp5nmpMxCuiWChM>AiLb&CxE3Oj zKvQkW$qhv0>;%L>(!%ID8$A-Pb!9t%Re-|wj-+Un?42^-Hyy^G>h(Tqnq_i5FTj{z zP)>-eE03ZT$xTRM5r}5GztJ7#@!CFBfm>#VLN^d~K1kSZi!#r3o$!^X)lCKuFOAIi z55s8{x>g!}E-7dPUQSp}n4mQZW_cJvJK7Q<4cl{fjylVmyKM8t`1T8q_q<<10&v7h zw+~^uIg;rr1%A-8a|nVMM(!#fWpZuwGx_6b!01Dogs=`hRc?S~9=LEvAREG4s_Cf( z&Zayz)v^ND@70lkk@bXui#iXTieX05lOyogx%l&m-$X>t%Y2?YoYDw7Q0R~gjzI}M zi97rhww@N)sTPU$gC;)bvW(w^?bsv9?&E24YmUi9#I^%G;fg2_FgzW zd9r+CA{@&1JGQBWv$f=yGuP?NA_Bt$75uW8#p7#qKCtNS0G8Erwj0U*Mu0*lH_84r z-nODfzt!{62g#^zl+(Ennv7Qy;$z6wdC6H)wP8H-pT+X9wcLxmR(GgVj*m5iZ_N5B zw;XaER+;Qo1WhN`2l1&3?B_vQG<;CgXNL8jFEy^~Q$>1C zqRjE47Q=;I1U-#7_K;-hdwWrqlUXvy@1>458q!`+Pu(Q{7dvoMFnZjvjw}#@D~i?{ zFMT_kflJm0?pjI_W8eLEUJjTZPAW>*#4Y6}092fqQY2+|d#yJs@_3rEw!pxl`iFhR zT)e;YnA?EouOg)V^hXRK1ll#C$zx6r0{b zMDIZ!p_Dm`7!q~m1WzDyqZkY~L(oy1W1y0}_BKYT@$Cgk>D++D?VPsV$r9OnF9MMa zq@D|5gqhO`(r)YrPB+qYm;;$Eux&Hminid^y19NwY_sGS_j%?I$v-nXBMCC)^|C~@ zq***}zI_vTaG4Zl-2cK={-m4)}QNTPJwj&6gcsC3M32JN-yNA!L z-{>a7CG$g1I{yCM9`(RNL>`!R>XC)*dh&Ct~tx?U|_ zQR=nO-(O)!X!AY0X1Cplq13jmEIw!af`RMt%&Jja zl~2a)`#8=zsfpt|NT&LRPf9u-53?UU{h!@(A8gM^tiTzy%)-LvM&vnPF}+H?MV|A4 z8o+bV>J71%4qf)L`-tQ&tO_uOr6JgIAh)$UnO~H z3Q~^aCILjZCOF({Bv2qORgq>tND0TpwYj{hBj)o?Ap8#!wxlUGckU4U+YV4PW{ts< zu~seiyHD5fXOuqi-7@=C`U7LnxfkwW`Md)mP2S#4e5v~g$!r+TSH`wF{uxmKSHIV- zKnmzsPw#n*n3U$ojj6+RtAtdEK3|`qQ1>H~LnOzLLPSCKPSZ}G<~ZN)<@wJ83kD6O zpI-T`dq_+_k;;RaK1CiF#2Au;u|}JL4~gLj#-Y-++>k-am~<$=QpoP!gfZR=>|R=- zY=?k@HIoS`p8`YQ@o4vrnz1~{Ae1stipsk0b(-7q_kJX3(3mFG)yz+V`ElvmL{?5M_Sf*V zcj)tJc|@M2r8Z;jJ7bmV+eDh}U4ouBYVDzZeIB^Lsb7n7!i;76VYFE)sv1pU;cxh& z^HBU0Z+D7(J-1faruErpKP^S?-0$W7P~U5hoC=+rJe7xUQ4$x+<8E&-nvBcE6talW z2pXvF|M=pk(%eOQoTdPGWQ@jg^ ze^w_8+25R4>erCGz1*)VX|TIEG*lzx9d&#uX}w;Tr0^uV+iJ8RZGcrl_(>``iw0F@ zO;|YV=-8 zD2sj5Wylh(TLu#_7eV81dMc9T*&FP>@nr3kenQJ5)7B~a&`)BgTe_#%?aA?c2;ZVVjVLtUn0YT{e+&x3SQm72$exfeD5aI5ukf8sx`IgH{K;L?q_B$K9v9eNXP0 zdyGy>m-@XL8xtIVZDi;$!lfV#5M8V(9M|3P}=(>25@@Nn-0FS7L9JL9fSMPIoB$f50`MLNXFY#)P{1B0` z7n#_KsTMg=M`qB0#6VsD>%}r6ov-rl*4oQd{&uRI@8>*42vHVasF>`jPO842|L%<$ z!ZlXNn|)y@acRi;DPgq6DNU-~(3Djsg&aRQbZ3Q@VxiMP(C^|2f0M<{e~dztrT`5M=t#$JskkLDw)&0NW@%%kXH=iiS* zQ}9;eZTau^TD>t3IOc?iKqgz~jQSgR+FST0R|1RMfk@=#vVHCpp)|qZ-EcyQpMtFO z`M2{*tXwXPV0HOUI-u7duh1WQe7$F|^PA?|w{N>BVP=KLQ%3AJU7J3*?d&HIuAEqm zN3OLD9Qht`AJo`3i5t+2#pWw#%)cUy{3J8}JEQt&Elb#CT&K2n>y3Hwt=aoU*oRHV zea$a7SdtLYK>|p~!1eAE>q*Rq^cbhw)*!UtWxf2eNY1WP(}Vqf*JXDw*8;^uBy9h+xB}QrEk-oUyNh{$Jby^1@QpQT36rh7xHoh;gGeFaS*x&z z=mrj3)mi+sl%IZj<(GpHOM*k8RWap|!Gp|U-RQdQ`jJ@MzH+M*C8|34D&I4)7fpl{ z?FP%6E?hA%XY>&sX#n@&x?r-X`Nu150&i5&AI@lXAONZIpT1t=pS50jxnxwIoS4xb zws9xd{scUfNpTmYDlH?pQXUw z$+p8=ZIwjf7E3ZL(?|}S4h}TkIC{?@`lrh%Bb{7hkdTeYXVHp<&_}DrkyYlgnVpZc zv8pgMYp}u@9p#<&GE$|ha@$w9>$Xv8ps!Q zOrQBh?4WAuJ4UEIGgM$z>}91wbcRa8TnM6=VQ(6#G{Ci)$n$Jv*Vy<-m%L)raDn8RzAyX@P_;mRuxx$Vv{H-f-MA%c~F^| zobvHD=g4>zp0;k=w-IZ^5mB-%a$Aako)1nzQep5}uN~gsvJoCU2v0s{ zxU%kZ7a0ZxGL%rRu}F=Q)ps0VLfY=Sa0VVfd>MghLIo`GMv}(k3O8XYU0h6e>veCDE!I#RkKT#3Vtz{pF=j!Uy1srpi0Dz?~1o_-+cZL zP=ke+0imEbA0p!Vzdwh*1EI}-Mk&*`csl=SRau1Rbw29@}v zY>cN|N9OFc~?2*UtC-SNv3hj}rw$613b7@T{OS-W%qW3T5AJIgC|volH!*p;W3wXdkxL zQ+1T*TYGylzUvd4hyhW2B-dl&N<<{MOoKfC2zF(~W@+4?5)j5=N+YnAuU;fj*q5KR1drN4jO!039M zUdrCcj%BOQXE=_o6S=Az8M(e{URN@YJUYAF-^fR+NMa$e$;*80`|bL>)1iR8(`B;F z2vIfq^)$x3i=5e-tpnT#2sx_(G$&8R5~N2l_Tkn_l6_u%cGVjuyxpu z1qXhaQdFSB7jBEcnauVrP2E>t!SCK+CSWJ`7y+gR;kM@_`8*sq&P>UY_b$9e6$bH9 zVs}hJ5cAvugH`Q89lrZlZLD1Nka)c^DqhX$aHlIaRMfYRcSnEJ_$)E+Br`@72u9Fb zLPjDU3!Wx3)pR3EP03*D43wA;Rbj`a2VB0uVsiVQ%*SF)&sv*aG)1>>a0;BdZliB&j`rmG?JZ#W4 zLUMALWjD*1+CrcVn-3`Lt#NaKlZy1t3}HkOW2#7Bgm`vB$d|ykSQ@lH9@V)F^Fufz zk92>H&+vT-gh}?vDF73LEl`CKF98}V`hTh)mB4|o`xJ%Nj~|e$6{*>utBO^tMcbES zllREVGz4gGxE72i$f1#z|5L5oB3fBkL|=F3DNKkai0051!s zI}Ej%>1#&!8?Dej6y4)`Jjc57Y%8(|?!j=wUB0*o`q7r*l9PFjLR7|5TU(wToZw1X zaaOHv-*b#R{&mQ?=ks_-On#;8c8VEt41LZZr=l277D@sxDekkEI5Yc(_2hNzxnUj? z@$8uc%)hM=A99s)Av>fL=H*6=yjJICU}D%5hKCD*?lK(1u5JtS&+)HbIk+wNpPIN} zt}_?7O#L9^zG4(T$1UP_;++h5sVl}cqcCxsi$n?09sSZ zTYL09VM<~dunZG!1BSq=dfZm=4L4B-AzC4j1t}OYb_b)Z0hm3$-Q=|puR4xuC1V-i zkQ^y+dJelsJ1rwchLT>1t?%Jw1&$(f^_naCg~NIu?>g-FIQR@`=H+PzeAY8y_(A_= z`vWa~{5gu;zMH}HFG!%2Gy_I%5fV!GnBF@s^?Si>1}Xq6Y*kt2Ale7|7Q0S}tpb_DMkev$dKQbh z%$IY?4X%Ka;to>dh)D?jL(pG&%AcSF`i=p>GK}yffaLXl0#769Y9YuHLr6>zLij-_ z?`KII_b%|o?m@(u)H?6-}$I!=36SLLTmd_vff_VY+-zafqjqZ zUL2CMiwy8L^#I7jQe@OIz|ecMiRTIGL4M7_2d}8Vomnn|tF#rrtPdx)j}9}}_H=;E zb*U5tSHvO+v=-pxBn!aI8>HsgIBOOo9qeMXi`xgmB-;J69N z2HuJnw4}CY#-5N{0IwKh`12%L-E;Z6aHO+DDdkN%X_$`ERKmBjMKJ{e z4IO7n)_@_9AdOmX05MRknjv_i5f}&u3ypnEI}+Id(HBMd6dZd3+|RvY*MZ#k+fk&x zKRdZp48hOPBLhuqh??Y;LPL(hb$VSsV31Y-FBViq@I`1(2N&>GaejJJF&m?PO4>69 zQXB&>dI7tT>>9ee^K2n`CYg0GD&2?3^dT~3x(P%Kws0#vP6ZSuC;A=4O&jd4jrmBP zhUe6|1Wabold2NyJYY+FwV8XFjfN@iuNeSOdmq97JA#KOAmnY&LmaZF-Ap;uZ8*rF zF%oxVcxH-u2vp*+=l-v$z)?WRL{R@TfK+-TiofboUnrWnmg(|+DL@UEK#|@RvaEKlcQSWMjL7 zjr7ZNmtm_cPdz~eZ0a`43I8*D(58`mC%F0mVJ#hYIQY&`|3I=#jMHv*p&4TECdt~) zp@h(%5a)R>X0Tkmh}@rz&lP}F*Id~sm_Kg&YeASg83LHLO2HGnA_Ack3YKb5daY);wWM7n>lJhX~#HSQW zzLDJ3wt0HIOeEMLa91Z`G_|j~*|gSlgzC=?#8iB0d2KK1+L>rsS}GkO*1IaduZvp{ zu%N@Nkmx$ZVhIKo-mc8xGc5OrqWyPq(<$USG0_(kNPAJ2+e6NPkXRt{WkyGIHf*1| z>sKG+@JbxEoe#=5aBK{+MbFMbnmT5Fr$;pjVF=slU-4sM}7=Y@Wvtg z_g{UUZ#m^|PUEcO*_oq+yp=qd1ons&L-7@ESne@aUGaG8KIV4Y_=1zdACYtytwxgf zDb$fK<=7yIfDsrYdWtyo=1l%dO|FkR%8Kw(Kog!nt za&^kWHAeM;mt2L)(Dj%zl1zB`nKN}J;@_C=BGKmZlDuF^e^mFS2z{Y`92WSWsh&kV z3KaN+KdWN9(9{CC+A`x*eqXP8-OSr9T) z0kl~TA5$0EHP`#oQA{*X~}k!t^ufz=d%Erp9kB-v%nDa z>9c(+0Na-p7@gABKKiyJv^Jj9$oArzG-FM^T5dnw%kC z-H#ZY^1puoiQ_(!i*NLCo<7|Z1K*7;j3k}a??(wgxzAj^jU@B31b4BqOup46ol#YI zGJqp@NY(#Mm?=Ixc0D}}Y0A~!Rv5f_{)A8UG*J|NiM2=yCCpPrS8x8H z4VkQH8@beVYTWyPW0c#k@qp@X$Hpj8aWU_{(|J$(6Vq6w>VJL!+^$lAxepglDF2sT z^)QO=mj3iV?CC(Dv0EQ5xWSUV|;k+*bOU3idB7INTD!`E2ImyMh=ij5@pPvKK6 zv2{ju_UVn|0+i?B&U|xpqIfa-vt2Om%jqT0ED9Klq2pC>LNqr?E&_%NZPO0&r(3(g znH6$uVqrB8>g4mhWxPTqbp}uJ&aWG>)K06Y%v4MO#aAo*p!P>?VYD-b3oiSa{ z!LQzK!b?GX(yN%U*7z8nLP#LMCLtx`?OE6}TKnhjNck7wGh50Ino)#~DNep!FwR)> zfX9mf&p`zx=2W|Z_^zX6*;XTM&t1)M2B~DEZcCx--04FnWFKHwOr~>7>CUaZtfYS> z#{dBCgi z9*N-vE26g}c4Wt&vPTS#IyV=`ea|YOuw<{DB|@{1pVdA`#)j8QV7fyy@WkUsb#vDk zBvp=8e|%j1@pFz%#Lpyce^X3_bLa3`w4G5{c$ohFERzFW5^Z!5v2Q2 z35cPkk88aP#tx#e?u?u|+y#hdP|d9NbtWnGgKYYNT#&vZhJHlT#)5eB<? zss!}S+)lWWh1cU?DT#d$7~xMMSATjnhX@{=YrYb8yM8dpt&oEPLN%7)VF|%|IF@Iy z6_4C=ls407N=ImA(R+?~*SMF+|F6=E{JR|be=pS8*p#On>#BG0i^t+pp@8d$z1I{# z&`H1!X-#{)bdeU0O!)@Yk4x;vtHkt+9eq#sEes&#E}T}RGnk0l6buQuQpel9HFQ83 z1%^q<&DFR6wFDGnyJ})_?@%_ zeFdkzEtG^tWiT|nsf>8os$mAsy-R9$5Haj|NtBI0&XHk+%IE#C>VLr{+^-ApMS8Wr zeno0#$jT{(vbX_eP#+)=;o||nOFcGC%R0}U9YN~GA0KWN zLz8+KNH0Gz7r>NW4AAn^=w)zl7Mvx#Q2yoOf7z>Ooq(n}@XR@H7C~8L03&pWZQBUJ zOd%Qe!18SP29dx_!S z<>t~$XTI#XBuDOh)z2<9L7n@UR>rpq2|9*pu<2>+=_XiP{LZn+TmOra#qs~8!rAs97q}{j?OaQ8Gf)a<5ciQ8l+6|M3GXcpqb5uy zQFMiVnSCl@1RxyrUtGEsW3ct*N*<7&eZv6D!dy|h9r%)=(**ASCxkx!BI_#H9BAIh zoaU^vu*|k^u!sHlek&&TZpqhE8a!0|QWE-HW*1M3-1E771=&o}DqUgaLvRony&L=0 zzH)Vb^J*RWC)RGBi=7O5%TmDXaflbV<2w9FIc%FtoyRTY<)3J+}GsV##se1Kt z^seOJM&0W!XlD{GD7v3`@#T{<147)AciiFBJ}^5xolZaBK@A=Z3)2Qu`3(P^)sad! z%LE-G@6cqrfUdKt@-N~vStyKIPv3a@r=v`?6Gpyjy*!+q!)FXVxqmhndt=aBh&J*+yq!%1#Q&%JKm`|7l*KxMd7Q zoF0?xl*JWOQbt=I-xrNo>sR-p4*wpqo&{{;&5$>9#@+i&mdq*s-S{hJMu-Q^z2<^$ zK3om!d&GKl^QFvZuYPoJTk2D_zevL^%qHRi9wy1sc_8v5Cio(iWo_6bXZgI#1HA5* zv&vnZu`oiGFVm3CO%<*-r%=-7*bzndCr!BDG=R8vyorQ$0(ryThH$8(-X&M0aTUR7 za~_)=BaG@;=OSX1V&mZbLgbJvC5XVYz0>FfKAMna@bK8bea!=JIg8dTn_9u--))5@ zmT%3`so@Tr;@~Vz)$H}SB7eL^2(7G4)d08ij2VYUk{JRGstdp!fh6+LC4ZH=`r?Nj zG-Y2UA)0f|U5Uo(zCbtsgXTfVWUr>5wm~V}39JDV$vri6ErCytuMAFbIU>ed)y9R%46A=xeUCm_T(WKxe`^3Hv9 zhdwOPgvqEk^7lyEupI4JkGBxn3}KAfLX_qH9K`84YF`Dz`$QHSY_P)Jud=oN9!Pqq z*kn1zpE!%+Q1`xkOYyB8A>m<$wAJ&R~}*x1n`YZ{VrD&^{Lb?tU5ztGtQyqrJnRNsc~~CkepHEB0pGBm6l85QE_q$|bW z$vqbMLgFh7-;skmMe6Z{Vc~g^#pocbGqS~wQ*z1t4}vZ9?wh{4fq>3MZb#o@enQIl zd;d&q>eB_hFjzL{vfeg)i2bmNXU+1w;b+gAhgZ#Pn0OH=6;lt$0^r$e@beQE^&HMR&ZA()YB z0~Jhcc8wI#9;_%8^%mQlfqO3D$D5IUpMbI73EG(jXtHf(Uta%gYutdKhVnTa$}&VT z{#d!?N#Dm&e{%5p_FRl#=^m zU!4$-dVu;cFnt_=|B=y=BGxkN!W)FE?gcI3M(HYd5mK2D{OnYR}@MbJgA*Fxl&)31^2UO_HX>s6DZXzmJv z3|0#EPI!Kzu%A>7n#GobC~}IAM6xcgutG%2W@vy?1l^)u+^rnF{a+x0l_430hOIBn z(07t+d=4Mm5@Cki_ggY$uOn!XKHIB`HGQ_H-uK*64~HB(nmAYJeLaq4NY!}x_a5mC z!c85zzPi*1)hLg=^rM}!+TWpJq6@#+(1};@I~0Sj##fBKM;;`WExzrILX~NZ8L~0U z^AhT2jl_Bsjl}Ph!Tq$j$=z6XrFJQjVj=OFrI zBnUSHD>`5<^R)^FHVI3R+(_MY!-II{RM$&=#LMp)moDHQqU0e3_>Fg&FaeK4RYcTc zo+Ms9&Vv}E-Z$%t3(ldkN^+unBmGWvvrd>` zniDT^qnz(i@r_qNDYl$HRo;ZmhXqXhOTJyHNYIfZ;On z@4^o^82JOc>tbRFrm;8Wsz^t&m3?x#>1YXD#0WoHuBiJg6=^wb(1`MmPB=!ZU#a5h ztmf_(>()PtIVUutE`U74=x4Z6^7tRE*TmNiroZu=P{uFreY271R4^LFo+1+nWhS!z z@nKHC6Lk(R!apOxC!4encZt>GPUIwW-5Go9FEQ9>bCtbsL>}M~laqEcv=O3YBuQ?( z`kjLNn@sUt;kYA_0%{@t?wyv>)F9oNm3sQ9INkH7kEuA-2R5+0 zWfGVUZa2gJ#ma=DWez_34KJ}th3LzdSA%rZI&w4?IwHkaR$5{_X#26`&PMCNkOIOd zyQffK2N4CnRgOfXV|OC2r88g>EEBj4Gl?S_Y3vizef$>YSen&tVS6`p%6D|KE4hM( z<~A|%9nfdP45ruYbb=2DB(8HrzOaHTu5y77jBrP)f`xCnfpK#he*|`^(eM60nK*DU z2r`T*AQny#b$EvY#{ezCq5w{TUd&}HViU(jxHm`HfsI2UD46Ws^2 zidVZF<)Qp_oQKRWUp@-CZowwRbi5608gJtrX3f7;G<3!_SF?=9#8xzIE(Zmt<|pW8 zR%~4BW)gjw9~{?Z_}O(cR2ZB^er1hJ9C$SrC)5fZIr%l#2#-f=x~(x8>I3&p`4|jt zK4y{-Gpv<>YbM{dBATS(U>{yKRQbq(Qt^(>AZ~iVHF2OsAZ3d5d#;u#k9H0D!&He! zrGTqs+gF2U0(nmtk(+VnLN4nad8Cu#1x>)Qn1C1Wpm-8?oV=#BOULnD;il{Q_}D^8 z9sLT_8g4yLsp@@JtF}6~R?8EDnEZ735UcmVmIu6yJKxoLhk%4{cr{unY2VrL5!SFQ zRdhHKl)h0~fMP}uCb%p@6-CIKt9JVNa_7z}y?_F{SY7U_0?UzqISm{gKcR3NtXS3L zE(n;~q9_{Mv9m)iQ}fv1u}-@dlt$T8UnV|e*2MgzN^fc*YSj8fDY-n4OhjH%tFAl| zMH=W9;v>ql&@A1T#4-8 zAB`wmi_s5XAJDxZLHBSF`Qwjh{p@M^She#10H5{FT!qA7FQqrcQi?^5%b^w za)~PJQX*fj*^=n_puc_VK$N~5it+Rk{#De_wy*hwVj{>Nu-Pj}*K&N-gPd68ehDa= zuGH<#45Tmw1e$d$vaYYVHN{!tnJ_pjIAnN652SBR%86oiY)#bZq#RLN$D4$6r`Xt8!sOXhGVutypMuCwl973*#L(r;R<_hG;|6X90%PN495P`iiIG&Rew7C-;2z0;lKZK){KQgiT|HTGV~|%tIEC`eo4<5SslpK|I;!t zQS@+BgmEn7Yy4F?ozears;7TWHtKLnox}Kk*u-`CTd_=Z#hiXz=8P{~XFL5_PpW)A zd-z*->z+>pl6-TGGaEtl{FceBdlxs2txZk?#}$O@sMygoYNIXOm27{$AFx#K&pMfc z%u7<=lBk(Mz`n`mdSUbU<>|Y0DUct3hJrC?_DO*%J37+!xCyz)%^k6!TGyZh_VI6@ zDbob6UX;!6UcD&$Kr{Q)?;>!T7ld65jf`kD-}CN`KF58!HYWO~C zyXCg<#p@FEB*de--|wZy{Bz4bHSA&8Xk^TODj+le_cEZl&uAos{wD(~1X1kDK2r7I zcEuSFyiT75Q~G}k5Ega3X;wqzZT)-om`$Jldmr?#am=TO9{!(I2j8Tqq`-$Hgs@BLplRG&9?fhGA4ZCgX(m)wla-Za?abV{CLDM@|tncjWPAyQlFGDXp*Cwx5BI46}m!)Pv|oKWR;T zc7CHN&lT0|i0ke0GcD-CdRT(_A%U+~#r0g>-B=3xU=&L{laB9Td7IuxBZsXE`2}S% zDOOrUC*2I*zG301SGzbm?$|!yXfMP~qqWnjK1dHgvW&lS=O8cd?pDBY`R0Ox@ynms zK`4D(d5UIEX+4wC7_JIu85Xzt4%awj;ds!^U;aKplcfSua5Hf9C{1n9If9fi&Tqh84dAO_Awls08wrIil)qTGTzdLegeD1&MG)h8=CRe59 ziprVsdP^0K^ZEANz7-b;PrGbLlyS^5Tq*0Lf+>sSjUhQ&@g-d^`#o&hqfRzjG2eKN z#FD<6y?F_P-3BclOC4Ff=zI6uZs*wkYG>bBE7upEK3){|TO^=Vshq7}z0S-+H1Tt9 zM1L_vpoh{N*4Y5$(L<}q?i80vr&vW+UF|>FZ*L7OPn_0E441KUCex*}ZJ`ezOevFj z388DgFuQ7}Vt*cvwydq;eV{^bCOit;JC(m#bfP5BJS{#rWVBm7AU^T7_)@<0jn}~a zu^;TL4*q0fLQ0vE>X!d(66kY-4}nH#n(RBYGHqrtV?L<9DGXhJf0EJvU26WnUJ9Hb z0gL$XjdEluLa|!|^ON0Im`x%@PEdBxb7&hLDF);uqT5OB&&I+@EYfofU~imd^L5_1 zGADb$Z5Qr9g6O@#C%X!BGYRWR2N;=QtJ0K(QOMB>7*xm~0)f&RDJL0cz+YYnlK3EG z-KXRNd>s}E1?IPnO>Ze=l)}b(;VU7MI?%%kYoSqMvzLQr9?aGwFqpN+`eH|irk@b z26sVXK9#UR9jFXqJJ*Pt@eV9%ZAl{nFp-DgY>vSr)h09&a6@+GzEiqASO$?ezd|HN zu^+g|l(&&A2~dPbYW|#fP2idYIM&H+wF`Egx{w!kAaCeLr}#2Ar5teEi@j=@ zf4>dYpM(!$Qhw>Hq7)aMbl>Z+kAS&p6~PU`0N`8#_~P!udEc(~ct^dz9m@v)qeb~^ z4S=hG>B$a67FGMPcu@X76H@mlB7V2WP{o>tBGH*P<5d-eiEtSvnutv;p@AaoGJpM% zYQs`P1=4Wnf2U44@ds4=Vi=-pj8c&&JPsVJtTChvj#$8>)<*)U^58Gxx z7hR*Z&a&*&+{{j$4z-cE(O>GGbGIpp?#2L#?Tr@ebwk!o@7p;kC`k#--+i}}5oZ9+u8H#n-0FcQvIW`0cNiEA%Wv(t<=+Plgk)bL#7n*un$RTrgmEYJ z>DXYIbCKCCiK@~@XN#m~ZW5v7W$s@_bR-mG!dDAqf_B_XQex6ku2|I3%Qv z_mD^wr2WV?`cd}6tOCFT`@amy;@?S5v*g4*xhe)+ubK z^By}pMq~Aw`0(a&jGYHq{ot7x+R6EUjeU7El>Pg^vPLwrW+$>{NywTtMnxnMvW+FO z?}h9}$QsEOEn38oW$aBe(xiwiVPq>3vXnLId)@Us&*!h-IX{2R8Rv{~-|zeVzOL8x zTAJ!>H7BWlp3b!l_WM0GpOQ5^ROQ9fB<40Kb#o^|!l>U)dPGZU9XBxob~xuMwbG0V-+A|e(BX|)@U&+V_dJr)7v5R@=>((j>IbzqI>ZcmP6p6 zm9I5ZP7&3rb=tTtyJLoADjo@}MR=!0RfpO4i>IePeVF2_Zu~|5i;ToCN4d$YE{}@` ze#Q|*5;fllDcv^F`~5BWYWF_*J?Y0&i0}~``d-p5x4j+b=aSG zvi`UbS64c0^3eVxEFUj%jj_Doul*ktg-uwhcew>uN4td>GZfSftl;SCuC=syb@TLt z?{L1U%=+-%+n{Oa9OnD@s_SciSH-a>&+M*jEz72V6+Nt??yq%uJtA|4ICaLn`~Ar4 z5ifNs!S&#c0`@_c)&0L2<5!11nt0fJ9x!pTv$7u!*5#e`5YJxmPBiC^uO&9xM(5t{ z+8?rCu*y9unQK`Fne`%0yQ3}GVpU`?0VqJwvW{(M+#WU!SvuAzCY#EOEw)q!wB?#4 zx}AxA*KjaJQEQVQ>_QSNf!~TAkP&RAMu#(gq57^)_@q3pz;AZ*b=ZhrqD6Xd4Vzm1 zio5t_xystWK}Q+iwAASoV8`Lyeg>{^O2=yzWnHX-aj)1@JPE@w2Jx%g z+?JIWN1qu1~J zDPJ5U0;Mj77KDE*G?fTzVrLw=?&+3aw-PMLUU&1ndY|MYejjO{TwO<-hI%$*_a`wU zWFP6#1yN%&oFv=Ak~4X#@KU0nO>Gu^e)WC+t$v>VkY{wO9v9}o*v%%9xKMu4aOl1p zpAU7n7D4u;O!xdySEIoDzQgMHnuUuk9wiG^QUz&(xl>#LT1nRoGQS1C_(@W(&DvRr z`+TEr%F9JhJt;FOSl33ZmhEIHAuqHiPtAljV?)A#mxg+Gtg35ND7TCw9Dr#-kb@0p4U_IE+a8>jQr`GBu9JQGiv6~`s!pCgF5Pl zJ{A|Z;XTKjJ>0G$|8uup$kWS-0#@B7v%Rmq@eiAJX0K}n+c_nDrkgY2nDjFq66$}U zn*BNGer+KsbKT4EjCy-kMX>Ji8pQ>iscdc5M($lvd)4GXPVwJ5^G4w*rOYwAS*twy zrP87a)dX9`wx6Sm^GG5ljF;_3*z1IiOf*+5nqXYB05w>UCn~2HiCbW!k`S1oB$G#3=-*S?Ox@twNvAlA zr^6MNnr4sBjrRN6jaa{)3fKN~77Ns7@!m73$-B|^F1P?Db2_5q<|kgek?3>S&5tN{ zzj>8$&@MDRFe;R<_eec3AjIFxSfLJD=@`jtm+msx_}&cChyn2D<V)M;-LJ; z-2N++#irmv&v7Fatn+C}K>pXPNa*W^7>pb)5?yJ6C^dFpxdN$zUB>Dn_9kJ)9LDur zhwxW~Q&1|TMxi3mg(!tM>S?439{NAkkL@D*~A`yB`4>E5V) z$^*Q%{YaLww>Rl41uANRe4>JT@w}&SYa%y~zD0MDrsiQKKNW~CMPf`7f#03IahdH&b2>z`sqR z-o35tb=xkm$6%mr@zL6E?_YNlHRn^f%r7x45`TXTYf9z5xVA2QD#kQl*i$}%?jkj9 ztoEfN774Rw8D_>6RzxxS5BO8|+>bC7ac=krbQqxFe~!Qf)qFx2%+fePYjYbMs9lk! zMKkadB)(T6(M>=E%2Y~DY=qdi8wgiP+2J`A*HsXeKGlS(zo?vP;_QWgTeDZ3ug$_Q z8>-f(w!1D*wrlx_meQ~iv!&v&4(-CbxXBH#F5CM0Z(HEj(qDN}@P5j$H6q0S{--vB zJSyJvBjO;C$odu_Gko|zwvmPWY~N8@$+;>N4~AXb|9#G^t=l47 zY`k#I=^As0hxiBn>9p;%-y8di>1dOg&pvhtl4Kl4qD8}pS|hH`LBh4%KJW)OeG>#N z=G7dhVI7H^bpPU&)ltotU0t{Y4JP)NrMzXEPy3vJ{` z8ddO=9HUxkf9O3zVz(T468Z`76 zr~NzE97cunsPcLk>!?X%Lf+U;$%;aYY(_PaB^^DntQYBM1K=AudiFoQX|D6fqcK~X z+Ys3Xm7Pco#q6!nCtKfSY;;@H3La%vaS`SC(GoJ|;?uTyqGSq9+A~|g%9kCJUXh3X zLH0ON{`TB?I~PdD`u?3I9TT-IHPi<|_O?x+Psy~Yi$CQK9F!7OSX1F2jb&7#A&rDo zIS2%i2&ZkB0&6wgcNg^**{zkjaquHN&%fd^nPzW-!Z-dl+dcA>c4O^vHOnZ()K@&v zlt2AE4dy^TMCsT?Zho!{d3z!FheF2|MgFGL{SGCsxq;^OiK(=gL)&2i5xciwVDFGR4XEqOP|Fu<5X0X?mGw7 z7q_z*i<=O8VsMF{%Iju?@9NN?lj6`IoT2>~k0cR}`V&3%DCy{@@~GoTkPnh0lxyW} z-p-svgQL9ToSX*2ixCiulJc?7U34!we?*d6^7p;JRQ-wg3&4mgAN>xwzOXf-mo81K z@M-Q@O;u@ZT|P0W(h^t2zUYQni=ga!1mp|YmZeh`aaiBTJRyeZ7Z|D+iB??3kCUyU z0z{P*ou~)3%8ytPj1Hlmr>1OP!Yf=`8**#vw02C-reZ=3+&ycm*$Y&T0s!)6M9O@xCOj(v>nU|_^l>VMyD zmfn>6?1$9AE>^RZ;@_LavQfbPiC5$l9ADiF z98M6=(3(p5Zq1f8aXgggJbVFjZR>rptvr8FpPB3}h9-vbVZ`&h-n9sL5(d}rS^Qz& zmbCMktnAjZ2-ik`FY8hg`0w`d`UFN8SUgYu;&bh1KBy6gr(BGejO6U&%Su`(hpxUg^=J<%&v}=}Q1yMl#D09q z(1Sb%J`ZLjd93esRPUHtK}?J%J{oTw3|4sm@Gma{JZ-J8#Cu{#W9sqt5kzb z<7zo~4(B8W+fQ&p%>C26UNFW=BWx~&D=FZ*3*fT#qrIZCLXrd|$Zzrscv%LP#L|`l zaO6!O(N@6cVs#1Sujp^=!#JvT8Pxo5CBdStud(4^i)#Zfh4XKYDO7f5=2Z z#Yug`D7_}Cc~ZiC<%Wt!pHaY963w3{3%ND0UMjIXq``5gggNeFJ1ruXOGc&EqyIG* z6zr{=)4Zl%qCzXd_lqf?D(NVetRrfsLYfv@xs*(Uy3g@*|DTUvD!I@cT4fs84}#V8 zco`Yz1gyZ{XXEc_bpFXcA8>^4 zIa$dCY4n?`dB>85+{vn4G|nPw^3w8y*(7tprsu{DV`ONM7`2$c2DXeYWY%@p_dX{kAsd+5xBYreYUy zt!=v5DWud72{2h60{J7xx#PwvIft8J5gaj09l)oJU6HRfr!PpsrcvfPGVsA@u_|YJDDD zPnK)-t%`Nm1TyYCV1+dYZybB^6&S%3J$>3Z>1Wm7N7RG9S`<&wEnj!IU;GW)rr&gm zlBKB9P^sTyIxAJL9C06(^i-jgm7^RUhE*6YM6%OW8@?%hei-nYhfRj8&abm2l_R%9 zue~|dwmLVso)^72p+7I=)F6%ZZ7)68Xz$W6<2`)Nnw;O zrCk@=Y>fm-kygMCcu?-#M#92mZD-3Q8TfL3^oXcASkJr^X=_0^h{@+#D{bvv{b$y5 z(VDDkgx%6{5{ThMxqaJ5`sa@FeU`16lFk^3 zO$4;Wh@y`wSEShTKzb=6q(gXdNa!VHe@93oT=U4Oq`5a#c*v$9YZ|ay0m5iwHJjYf zQ^(8ykLLk3E^`@7&1?^2k=l)pAdlU7yh+TOb@!FS?M1HJuYCc8R6s7?L^P@k(z{h$TH#}Yk^zwaS zdtbuI?S@1P>adPkC*`|W2QOT>3dh#YAvVha0Dv}9%Y5&H?val~c{u>gb15 zW!rAZRPIA??B5^#3xNskh{U2HYI1?H=w!)PF2}Ac?d+{^r8tmi6+|OSd|384;@28g zh4sl_xJ*BV6k$2P4Ijkd=XmdAeXbB{9o_ilpNrNPjMQ%^+QzNKlGC2ho#>%)d>wL2 z8{_1KpX)r$NI7rb)+usZ9#;s3s*NwMi#0#`KEIzLm_;Kp117#LU%Hnf7sgLul@cO1 zATB7dzIW)E+Xxg0c73uS!nb3qs`#!h6DI+r`3W+O?pHU;c}Ct(y_=IPtlxx^++%AK zqU9AVDa;u8lv)$nOFg0typ$YYFI5QF(qPde#ionK%&GfL>My1xB{hSOwuV;bEiz&q zs0Tfh{(Ld4lm@$p!lvm zBB`$mLw1&ryYsp0_$q@5XOGB_9#Z#2tA4`KOucmBRE#hZzfxHYy>8hLuAZ31!gsSJ+Bwka(bBTa%?3UyJ9@W= z_P1B~Y8A!Ta0zB6%a=oq7x?Y4(Rw6Y_*AOOJP0cSLULdTG*T%?Ez0HJtiiuxq$NzW=r)d26mfur9&3mRM@eTpr z+GeJH0X?yEiJp>G=kBdftDkIpvv{Pf9wX(F#84{7rOTcMM3JVLz*36X3n$_@mjaPr zJJKlZ4dno4Qur1tt7s`TY$6iO{AzuR+X}dav9`AE=ob!q@IcagE?T;aS~%_v0trJ3 z0Of(aAY(`rxf&n`aU@#&DV$RKRag&V-j^01`m7jnWX#iBw+bV0$!q(FsS8!_}O&Sdf&wzmYW5lx!IHF z>2+eIdlAYo%Wsfn%2l+P+3br9 zyxu0bG%P26Ulz+1ICW(GadrNBG31-*Lpp7#>TFq8k;b+m7rUE*ds_B|XAG|y*1~q* zZ2snH*BDdVq}Y5O*>*6z0Xhattf2oq{mHj5dD$@x7_PY_5Zd+p5n@wa>v>*~kDMy0 zmM)MJ$`nIpRj_p~55QP%ZA_)L#97ZTkIKo|6ur6_Bk{SBLk5rYb&i=cIdkM2*4CNz zFuwH%VQ=sOhDs2H&=cPPUzNyd8PuznxM{9m^IU}Z_E6;2hSu$GB37HsFU9zn4$s~} zixS=%!WN5A2cl8@hmPN2;EH38PNtD!yWGW3Kx%j%C67EhTSAltNN%eYE`s z?e&>tD#MS@UiCXpyg>Bvy@kIyX6Gb|uu`keS2r`7X*6w18D7oU9YRa4?=IB-CbGPI zXR5tDUhtfneNcJNZu{_W+Z^4aQgrEpQu z4GQh+oXG{5vHDyUVpU4pYb)w0`Nzg=D#XX^Dh{_1Y<(J7n2;UiPxYpYwYp=o^zX}m zt&skwTZP~M|G#-B4ASP2*>KmH5ASk=9?hNnj+Zb#Yj|(pKVU%y8#~`x!pwc^gpNn- zbtV=vf4+rrJIs|YBZFxm791dr`A1B3-w7tyNIe858F<9RRu;@5KIN>;fLyq)L@#j|(FgFW1>(S* z;n<%~Du^N4!6!}lInvg7kACf3Y98NjE|`4XU=J-6wkMG42B}bZq3S@=CcSqgix3Bg-GBao-NE?@2W#LrEx5@g$4A;ODAeVv$p0}=NhuU4lv#qz!v|`fDH}6S zebjfKot^FLM<@Fl%3#v#eg34NMXGn7&5~C~GDD~Od9JFRjhhhquY6l=>OjHWjq0iQ zwIjxN%7%4ps`1#>l$74SlhC^I=$}h6pIaR~{+>MJR?)`%{_|_{k(Vf~XivY${&(La z0lnV?fA28VO>dCHh*0gn5+VqZKTw<(Ul1do$E5!cpRwp=R3JS&yTZ!Kic}YJ2}&Y1 zKEAlM^;FJq-;!Rh$|8c+a~?x5Rbj^aSBuy8H_{5;t@-)V9y4z7wRY2aU%qIy{O)0u zRaDfJkO=%am|kA0Teq4#cbxZ@!;oEOb$xwoqi(LOBZR2eq+&TQ*?#1z;ytI?>+n1l z7M9w(DeR!4MBM#euU$4g=p9R7cMIa2pS#EvrwuM1?*2)kP@eu~g(@v6z6#YFCp zZ$--*q+4tIX2xDqN-7u=3#-O*_y!p{d7ArUW8=)t)+2kFk>kIAYTP$;8fNTY1P5D> zmuTbR;R$UVynapGpC+OkO-eyg&>h2ATv<7y>VSdVHJB%g>_brzOKxs%s#i)jgp~IGS*u%ZfBxNhmb~-R zr?maAy>Hn@mxr@=1L=(8Fs=&JSOU+oqjScv}6bzz~_E84V#? z{tH(glf59`!Xk@Eo${?iQBkSsY&th>*HYyV8qOad^Z%bWZ{%A40oySgNvpSM_bz@3-xI~d?V(sTE zW-4+rTUS@O9v>5rp7X-4puSE^os@15l^Jico4m$zi-^dWerv&v`r%6p(YNZROKHgZ zkzXkKYZXyaRvfM#m`Ps5p&+4yTLcD)h85DbIb~-HobsLB`Au+F(n?UN|&c;`#&U;*Vhr?mFHJ{ zEa*UaoHc(x>^Ec1@+>R2+T3_H_MlHu=qCjt28c=lZH+Ag`%gCviFLubTAg6b?HRJgFJnI|Zh!V)a_2m~C{Y?MPku_1y6K zcXFaj2V+bv$EB33ZuQmkiSjIkcGLkmaK#owAN>V<9^#`vZaV@yO}imKT;=9kxg~}( zpJBaT&q*;RVbS7~Fg)w9VAEI6scRLMdqaPR2MZ#Jnqvs@mN8+z9EZJV(Ri6CTbiiP z{oeT{DaPQn#LgJE<_0;UmPXYw4to<^cu@K$8u4~%IL0j%RkA+_QgssI^A;*HvAj;( z+Pt5he7V(9)1=dzHkT);eF^KZ1+Fl{-z3HqU0sa!vJ)FGv8lYmL(kT;IOiZGRl<-b zX|-{xLt`Qe$G-jbefkSNO6IEhv#e#qUyMlt-RodSR^Gm1mJP=pVbx_F8=Dknn!5(~ zOp}10K29Ia6(dt;>9asjFy!`_aT84K6ILg=E$u8gH_UkXdgp$%|9KVS!vQxQ{k-Y; zda<&;chpZs8CAy&^Px6>+XVSPpBPpg^+Q5?k}sYd!D<-IdsY*dX;(=lCMH%+Z+Lxs z#n`&zqo^1~&aTJQG*h-RnqS=9tQS2tG?Xz}^@R1#oyT)0n;weZ{SYg8?7s?3Zn*oN z9nCEfVjs(PzvA=ts(%n45gI45FtSh8tfe|?8cTAm$YW2VI59ID<{{c^`eJCsb@lY< z*TgEiSY1!AB;L?ZyR)-1pQg(BhpeQuba8dH8jMb_}CXOS`TMQvfR0IZzJKu2k{x-{h8>Tzkil&Hl}Kv zn`ZC`2+$?kRivb(u2b7+G}_wE4joQ;*Ni*Sbwb}`C4zr;YfKl_+#~E=jGkQ_dfv=~ ztrbqUL35R=prJuVNNYL|&ZJZqc>H$BtuKmk>gwvUa&p4E0=&HNr}`6-Pu4Xo+}tVz z1O!X>o>*J23J(5lAY;{F;^0tx`t)g0adA^@9VW%5mPAM`joru{?-Z4+z=%kfp73z3 zh?kd!4L#^Ibv@FDonTQNpM|&e&(lNfR8>}f6B-&yN=N75dVM~t;j4X1!&?1~=OsxS z=F}gOnIE-EMx*sZUuRDr)?YzvMBxw(=R6%{Zx zbMqg9gO~7m!Tq>3=j!r@%f0OvIw%fJQxx}nZ85c2eWDc;$?Hl%g9G=w)^7U3adoVa zg_&7dTRYLq+gn{pDdYI~cr>zmaB!kXz4(?)dCOkX&%Q*L0TFa`Obi(bNv3=Xg~kldSM-kqO7GWb3fE3mV~aziTRCGmtgUv_I4<4 zN;TLFTlHL)2I3&kioPuuo19!MP3NlyYuE!19Lbfd@!U26EA9OFu^=O3er#=YbQC=` zRRpO+%l0Q~uU{?uu`w~(bEkWChd=q-3d_pa_5DwF8&40{M0Uwh9k5hVErjvEyNIaA z2$nfw`>ls}7o&H3#_`DF_^qZsQ)J(SP0pZuY%iw8Aqu-EDJcnwXY2Re{;q*TJxSAi zzq-?RWfU~|Yh4UPCPiV3?oGR5)IDm`Q>7tg)Y-4^N1e3Fcs!=ttZ)G{#g}}t_E5rI znX)||d`{`CZnjdgx(j!U4Six2SK{MFC!fm3qZF^U1Z)df0v`;BM&cpX)9SNBnc#pb zu|4O+xu3*brz}~ate8?6FIaucp1laaoWI8u6cFzOZlb(iiYxP3QWCA5YszJJJB_U8 zn0Itq@}>MZZ_t3X<}2f3a8xx_N*)rRxNk>VzxLj%Rx_WrZ4GU!awcC#A)IGrNJg$(y z`e6Dh#Ph|D_0rNIj$5jWlC%5G`yRQd@qB42h+U?x*I|8*X~1P-heq-hmUd+pSAC0! z*Ygn3mKxavVX^h&;Na==j^1q8RsDz7wwNYrTEFoQP@#GWHWK&=|b^4XU>Sd!A zL%rfO(b`Oyz!tI~|FFmFt`VjwiPy_(caunUZ41P7=afg%<<-)LjK_~ro}bYyV$5J| zLzVoib|Q_|kDL1>jyLC*g1dq&#jSH-or){6C(dW#7bT8M@!g+4mifl#BB#PPQqq)a z5I=ftxmQv}(C16CL8n51=$j+uPc`Kp-rg*rvX)UO4D*;PlM2h6E{-Z;)*=_43Bgf2z zcolz_3?CGCmQZ)yUTct--d$Pn>ZhV{aJ^OjXXK|TmRGBA9ueKp9}HAL=6f-JDs23n zZ$C|uY{Bg3BRggr9-&BM?wAj}3|x%>D%9XU7_?rD_ zoawjfsx0l>j9NyJ`xw1b#(nnS8yxZVPuvkQ_@m&shn<=~p%X8K5)h~@3@om?G@ftk zye4Ex|4gb+X8CsM)*Mv2CLWvJJUqpHm*Cc$L(1#Ev+97OaPCyw%a!1szej#%<6Wv= ze*3B;Jo1~HRA&gJZcM&W$z-LolCmNEb#?kZ1nz<%7v&f8UDy8T#0f{ zKN3968Ko_EXRT@MmN^kCZ+|Tg_iA5oU5QBT;uXI80E`>XpcO-mOr4^Py6dA1gDL07 zb~Cgz_?r}jAxKO-hJ8iq=vxM{F3zV5o|8;EiN7|1>6cQ@2S z@h%Ommw0Ap<5PnFYIIX6f^2?w%ckjv$*33nQ0~(w%XXB_+U95z)EfVA$nzCu2&p*Sc^-_%Ry3Rf$B-pvkBr&3H`i+dve)QKk&G@^| z|FE^*nOS}Wvlk7665^ehL%EuiUIC=Alr-j#z||gV`;}SiHtojn?=y4Vcx2cu&n*P7 zO@Jaem}|@bhCiqs_~Ln28&e*(H0PQStNy(PM|sZ2H@fvSr2lYJPI#y98*@@>oRRAt zcu;yr7I!;pN_+B-%vYN07wDg9lr}yo`gH5X%JiVa=p5k~)%nnu;5=Yd=T}PJG!ZAI z`7j$8NY8RhiGw{gvoFWd_vo+PVMc-q#2rU^IASQl;qlU>ar+3l2p*wO!&ms1hA!_b zXu3NGwf_0WS30R{>Us-#^aD5)pJ$866L0+>%qAwR{XCBnX>)CK4v}1Ky;ir!YCRpg$Ns^~0|3i?odLQc3Rd<@CWC6x(kzw)YfOg}x@FySkQY)F6z4kQYeNPT)L zyMp;E4UfvB4E4b~X<1Di)R|&FdU?NEoAqaW6|zmi_j$4*zZRuq7kayp6%%Ys{wRLkTu>Fh^H~ z$qYM83Ckphq#5AoOW0RmlyxhNP0zK7cbH1J{&JB#jN-)s2Nxa*XK$VtW_5eY#k$@y zXjs|tq7@gt*9IN?#6*7XipLt^+W4GrR`e9#zvINlqj$XY)xK^|t%ga2U2Wk3{iceruj5djs7?wyPtWXWoHOG-@em(8KNhBE@m_o=?@%qHA_7uNQ|M22p>yy*5Lq zS2&rt?d7wJ(SLTrIHij=Ik$oiWZX(V$A9{lDcM(9zjfFhp77@_cfYvmR-LKJ&o-Cg z@8?@bHRT;12_Bbo87bX;CQn!Sayx@yJ-U$f;AWPrs=Bf>hI89%bJY37&7-E3zpKol zk0SH+{Y6nK8us|2q(-%g@$BG819aVfLFsg62C7ONvlLt`69bRZqRNeiO<2R*;NGqk z<`yfe_vg6Do;iVe6nUI#3e&*Ij>%A1<*LM2yZQtXGZ@nXAg1FN!>u2m! zE!UL0U%AtW4wqFP67KrdUMZTq)fse=8iqnU={*PmUDtGjm}v&3l2LJ@)obxU`x!)`Yk1LVqEC=ca~nH>hvY~WBF0L z7}dDD?Gn%R?du}>T&?}xibIQa(O-sHWkN4s9{WzBT-gEmpQkHaUVCX)Qy$HdZTcQs zgT6XtanwDrainFs47tlw>lY$IiDJ547d#e|guT_BvrfiR+sj1rVI~lyRzruKdLH9z zsy#Al8;Bz&$$4rTC0W)=qvz!h7Hq~h~8c6J0Imy(D# z|MCMu)y@U^;NHwje?Y1!~4V?4ZfdaeqP ziKZC8kqx^v3=zc3S2_+nYpfW(5_!a*e%{LQqEC|>!e=bGw zx>}FExkyH1r#3vy;QQ|E<5NQizEnN5E99;!SDSSf#k%_c$K?m>GP^($8V>dW(K4k*#(tXQ5OCK-~R&Gb&{dDa1D$*Vyf*YvrLB z^ZF5|8Jm{IF5`8)-BknCvi2SF6R25+zc#qsmT5cPE#DP8`y&RfnTp>&CCztF8yg$@ z>2EufVP#vRI{hFSLrzc{?DAu5~MhEPQvP#d>9Rv@FyD zTf4s!TZ{CHrLs?gyhiVQEH~8CHdR;2sHqCX?25;dg`?JNVpQq_0RSH8{;!Ju=vQ0$ z*qEAps*w8MzkhqWy9M3)dg55gXlP1DMpOW)U0w*G8)q$V&ieMv1pd=urF-}vW>QgVT86L?mbOj8`g!Tx%`<6}DtZq8)&6~{j z_WNu))sJ4hc#%(|s-;!X^s7}jn#cdtr&Pa5!@f=zzR;<*d}GU(EERd38L$F2-P%Xd z*9k)!8ymkn3XDxo78-X1KV4-*J#nqhl+gE8Fu%>EM>@MQwf-=IhCGwk+eV=@7%*2y z2B@t6Z>s($zIL**p?-j6SRZUH$SNpkn3?6Y{*Ej6MDAS;8>Ueu18`z^BxcH+Ni)cW ztpFA*(X7=d$g7z~;&Qv(-?30Ed3kvNG1Q>gj-(SSi;N^}+4^w#$vyYZP_mxhUR48w zwAIzsi-OF-EPxY!Th%}gYrofau>@usxh1d7b~p*%yQJO2J=q35`}0zk<9mg8LUeQ% z;0UTwtgNhY(b3N1rmzA!Iy$7()ZXJ0ep~Nxs05vJzAY}25ff+VI<%;#`~2>vY&)wo z?^RP%%gM^R(b;u3wc$!7=e-(aF&BBWFSDOydMw!(*|+(fCeas zLe>1DoScUMqXW9G{@}qg!15J^8N|d4i#1B4Z?)`A*(BY45(#-Fe1QN8X=$`^adCxk z&1jzd=+;69NOy(ftG{!>7A3&`lP%j+y1w z&@$8gHV99M$BU#5Nz?LeNAlVB-h{9A`>)frqJeyXwaYeb?{eD{;@N)k%LV|38BX@e zWdXm9$d!(WNJl9SJ5dYQpemv9FNJgEVkKfH9p+HXpI5P*p9jWY`B(#Z@F+Qwr(j}5 z$Zk%sUDM}`swr6V;!2nQWU**|@A)I;AjtaZc)U}1k3pW>6-+^cU2g>W76i63!tvUb z-Ho_&@XFx1IPT6U6sV0pY9%G)r&I0xP{5DX$38+lx8Qks4~hL@ZgZ=IG_{bMI)iRP zyGJ5KU@`AlBtP9tvpz3QIH2e_T==uWP(~#|ALMW(s}Q|@$@p+1BxJIL7KMV*oN9S& z1pz>8{m`~xSUEt>gfH234xR1#u2vo@xAO#>li~%jK-8vazNpAZ`^*D;%D-2Gnb{b$ zdd2R<(XHPDS32-a95QFPoeZW6LPC<-3$1P-)2f*^@SZq-1UJM7|r>^YtP~Odm^GpRm z10!OjT6NGE9Vs2Tx&gqjg)6D&XSw7kN}Bhamw%7!^zIX`=CXC|e3|%kUV2jm2nV$b z`Z(7cM7uVmE@V-7fd_M4JTPYYs+_w=8-f&?0T_^q3EJMVQ+jNfQ5kas&cEkJn$gj* z;k7Z{rbud}RH6ugS-zOw7-tMwbJLb8>9dG|OQRC*-P1{Ywcsb>3Te2%6#a#Ptddp< zz;W=eb-uO$fG|@Fk4>fty@i<6#O_9I>@4sgcrS z*)SCim3jk+?MKYl=rtJ3T>-s` zvIEED8_zLek?@nK8E^I4M&o%@G9qIK!#$=6>COEe9P1_BAGx+xx*UN0;Wkx;=Y!ZJs>+6?S z%Rra#Yuk~cP;Fq+rvnR(?zsvWd1nEjIBAYbYL;UqN7mvfL`*+12em{!1rRR1h%+Y z+`udR+Xu`V3qVewcn$~w{7Ob4URRo0n35gO=NZsDn$9sh3-7P4ZkpD>FM@BtjSCxd zF;2|;4sW5Tn@I;I!!c(JC6d9v9+VJ zi9h^8*SZ%sMg0wIpVZ?LQpkKp4ppHYvT~g5OhH@T>4S7RVA$kPoUfN$XsIjLP>7#C zw?b6K0@bm>Q{RxR=UAjh69syz*~3p z{WS2Vi3D=4Yq(w+S0>3%X`-lp!~xq-Qq12zGW zwT8*V*YI!U@o}W=F*)C?&(}{)35+e0&)w4V@yk9eo?`-vo)3YTu~alASZKTRvx)_q z+lEH3jlCMDh1I+E52K(s6he?C-aS7bC|KN5(}+}OxjRf)dI9U-ab-sQ&hLF|r~ z8Feo!5QoT1=-Rv!#FRJyv+uL=_dG-3-5!O=p*M|$Zu^4gC=a`Go8OgINDp?ug>hIP z?QMW;W1?olptzT#O>a>2sO0c4K^k*z(X~N+a;$KnkM07y7F7Nz_H~5l%6fbhsCi1I&P}99k;%ql^ zY?=`oA1ZX+B*eUC=PF)bVi6O1?!VIA2ZVzlXY;-uj^C;#}DSSuyy*W$msI0(4~z|dXp`^WE1!*^cs8GdItr z^;*tUH6$V;nlOzL`MK>FzQ8pT8T(wxyUhd?xarqEz^Ibmkl38>|FgrIjgL`&J2z`;Ym3Uu6({suA|OlN z{cxGXQ;3>#o+YXAmQ3L=oEH3`Ajf1A39Op*4MwO^WKLLufQd@GapT6$MBAx4q9$Tv zLv#3TUsimAbx}`JHUCB+7U}yTKBN1PKmzc%{763pYTWab=30T_i=hR_N71u>M|LxQ zM;oEx;p-FK6D8W&eSMFC{1Vyzc-7DgkvUzy#vVIkKe4kis%~K5x7yG}=db79q!0A3 z7wm(gZwm-~{wxh@YG}Nztg6~w$xq*7z5I_12p(k3>zOzqBf0tAwMpIi`QM+gJV}0J zA3zKPRG;=#tz9yxf~bHiWoBCbDz_&L3M>D!6GXHGf~Vczy&Rx_I;b|)DAOxkUbc*T z`*!s`4&7J>k=Pv>7It3y08hqD&w1 z`qqSf0pcvW#ZMp0B54h<$ICMgwF(T5Ko zTv{!F9tDOQ#7Rmby`dJ4Y0mE52A=B9Ly zeVq+lXKiIQ45VUCu3WrqG-$2J$jIDC9H>tVDl1f@W66P=zX+lQ6+m$S1&1h3jqogb z0WM|Shmtsi*Oi_={ad(@9gQ%@sk;aNU0?+TMEWj8F}mpU=SNUy6ciQ7-nHlx*rwz!RWc zA-i_1*Nl7j=;Qy&Bi~~HvYRkOf{l$WG$KM|%|=yKH4ao|AS#d(671Wtec?D+X|7Xi zn|OFMI<&oO^2Ev36Z_Va7iDAl*$;sn+X<1#--=Z@5Okl_lueaJA-!uaNwvRXiZJ2 z$azRS87mhK+TGm+aAUaIYSgT1Qo;8GNb7q?|GQN5{b+=%#=cC>#Kyv; zwzH!)x205%qPjXwN=izvy~!sWKTbLn)p#m0@aL_xyB9_j3hNuyW!@|qyrKf&7$;_W zL-bd)hse!wZPB=7cOR@5%E&HefxGJgjMw9s15`>GMs}&s!MlwzZ;WS-Iw`B?;r?>~&8D?Q-y^uAbvC*zE_<6HF zWESe0`ng@S-jDV5^}Wtc_T3;MSp(JPZ&&c7>m`;NW{v?jo+k`mzz<$GCV@aKRfKpd08efMr$Vq)RJf#=Cu+v%Fo4~S}#i`@h(s@aKR zxcGUHa=Gma0xsThKIZEXj{Q&83~fLyI@Rb_OhrwN{_>>&ybSU$hr8weB3hKs!Zaqw zn5$%DUzvPn;!FVDQ@05p7veuTJO;!Mj{gj<{fIXl|NQ2rqA%Ocn-Uz&ThG(HHwB|Y zu-MflRpYPRd`@b)G2yC>!uoiAKnnnG{^8zq9$*K)rHI|$-`!5sR~O*KTzlK(^jJjs028~#~P3V&T{-uCVWcBYG?Gh$Z}Op*7aQ_s z7fDj_CKehAcLfrHVS06$#3ql5EZ1Xi<#xXNz+_YndnTxFA2(KeUdtoGgW#OdJa$QJ z9Hx6OCGViJBVH1yI|jTkhQ;xuN51XJQ^>8HxiC)#n0jUO2e*todBXT}9B2MAjLdn; z`?~e&x~YU$dsw*qD>cn@)eyyVdvp+||M>dP-{bdcX8BS313$%#_9B*Vh9k~&MaCiXMt4@CTHv%*?V>ocL-KkZ$U3Q79!<6jO;#q$3-TeTB+S1N>oQlgWXPP_A!JRlI*rh@59LDr^X3Q5YrbK^G; z00KOR)j&$pUJlQ{RqeK4*ifZtHH?1^+vi!g*~s^W;VHioZBRubM=4+~3k;{=*jBti)jqWlOD*GN(PA76r1P2M61`$kAV&kEj{$Huk!v@%nh@NK1FDPn|OYQ-|4cx`>TmF-Sdr%(t$>AS9#O#eO z;L-aS06PtP_>%}zlnMBAAnt5{@&G$!f=1nXWAopg3>3#r*VvwX&Rqzx z=AgOr?g$#aG`2R)5^=uB8N?s*)p^_iy1l>f00SA?t53O7*5W#`X>+b>_I2klzyT1V zK04;6jDK*R(VGFFE~Gb+sYt{RnCdx56f|hPwyEl(Nq0nqDe*aCF@}unO8Yl%0AH@a zg&F`j-Ga3bj?O@Zk^jtHY5At3UgwJ7g#q-y#-*zdBhH$Nypu-Uh^fKl5Eo<_Cr+jf z$m&u2h6UD!lOh|6s}k^{mx4kzxGQ-1({{(shrDb619%Y-M1o38rh^elt$5v-;}){o zU%Sq&E3YoQt!i&xfg(;B%J`hdTH0L!y%J75d}VDJl14sZW&h(Gy$umUB%9<`u=#8WxBIUs~!$sDcBVoyjAUA8j517tUijGn+8zZXC zaW}zJA5a}dKc%cZ!oAxUP)7g2TwGYFgvn^GWN;>Fo+<|}Fqn|K2Y7yg7@gt`Y-p@ZZ3I zw#%2QS0^qr7S)zYi!p!w&zmod6{@O(=()0zdv|ZI2nrcsSo3LO($mY;i#24T4ZJsa z`xEaDbp8D}IW=1S1tQDwZIR0L*DV=HDtxE^uYh-P%!KZzX`Q+P^ zpsn!dk{?Rn0PI#mE*^we`uZ5I>=`&GJQW5YIx9LNVb z+6#ZM%`dLGBOmE7EC?&Tqs`)Vwkn^3Z@RLk1-C=qRysD?RQ>-XDemk@9 zG(7?3=_uZnS#?QUa02(mz&q}OS|*a$-CDo{2P3760OZ5zbrBPJHwlu?-~dLj0}uK{ ziauz)}v*5djj+*tHtFIA~;uW5|(QVHJFZ=u<&~_1VmX z2ZrbmLqsdEFG}r8_SQzdoRb=uZ+8sXRFGe~X936Zg1mY3Gqi@#1hQ*?|aB1N|qn&J# zeR4F53^WA|kJ8bOLs5XP*)Pa!(adF>8k^b>*l>G~@%D`MrExmhr@_24@G$>6tmrXisD;a~j(}>-tCcJ6bdENJlDq5roXj-h7m(@+Z%MnxZFb`|3 zAI$`4A5<^Q!|y9~9w)t~y6r7a!ODPzYQ}@jFMbY%k!K>vFl9&{K!R{M;sPX4KaH>T z@MD|uG>)15D+~5iYMFG}vI(3co7*zm3w-)9aT%aR2S`U!2|jrO_24fp}*!rixZf007m>3vXbdPBd*>CNnSMUAje;Y+zHfj zI={#!fNalNbG{NMW}Hw)K~sL8wT%J`>&LNAk%)?twb(G~rvRRIX^W zRV(p(n_f(i>*nRMP-uT}#oM?v;Edfcp*`w*L&<{FCg0vK={v~#Gafp#Tu@-=OM zKY-l4jI7FlPa`~wcPB4MR>j*+=U=Dkc|QUX%fyFf9{uE)f0E<=1_NFW-1&r4)6A64 zYyrtvnhPiy6~_!ope={{ud1rS0wd}i8%eUpv)qkP!b?MJF)G!L)=8DoKqKR!wz%NL zrb4O@+B9Przd&Gh0 zNgmvQfmSXmr=C zEikfqG5b|JccNCE#X~D-GeuOKU-5dL67|_S7D}P34S!2$x+j_E>BH*2V<~DB`%B2- zKYJ_JGQJiDjGDPK28(V3bSAl*G(L5YPyqrfN0nn^y-k*tIz_iZZw3g)d#HgN({7F0g(n{r8EgPP`#o*$d*Fy!ru=Vk#0&*uXFB zgr{<#+W>L>(KiD{k}y!5p0Hn3l0W3BXs>2n08>Gg6N5|{OrD34^#QfqT1{bzaucgA zB1tU1dzI%N!^h>9Ac%elD-G-yi_la7t8^EFwp>if|F!y52Y8{M5%S~erdM{l-+1|| zOl2TSn(zZ9Xyka1{Y^WO6y*bbo(2n+68Qi~0knZ?)`EjJVRqXZdKRD)3b=cNv!;s2 zpg?xDQ^*?L1~wL?C*|)NN*+Y>_}+qIIH0ado2}8rwHbVeHO#A2*i)R9KeiC0=BL}N zrm^t@PXtj1co0E8{Ja@~NHr1Y9;)U;=5~{DX!DY%Bq?PxkC@UM&-mMRrluM3YC>Wn zVi;^Z`z9u8AkY`rSOBmvd1)$;soZf7W}(PSV1`yzpNT2T!}^D1#)PDz*Li0g6Hvgf)%qj55$JI0{sM^~$3_ zcXb|C4iOzt?vj#_8o53^hhiw~U9q{Y zVh|I-=CyNdvkFpJ|9K-NGZKyuSVutHOM z3ZER-vIaIBI9ZUm^1~@IdJS#8D+4Px)zD+P`}-4?{jF4XcS_KXP+N_#VG<0Z z&x@LloMRv)O6q}y*s_7}efaao&6@R4{7zWT@lEUgzdyVX_elt9El(6@jxw%s0$}LS zqG49ggaYP(_F9pHK9|bAURv3gclS@02bIVM*A%1bAj;-YB9>4S_#)5QdQZvoMa zQa}`;sT5@&j-IUgZ}uSa$g^J&ElIm{bgTPoM8%~|gK%Crb2vkYgD0U0c;SHtupUTB zK5q_5U0J`(81LjIXb)Cy)7LBl-R+Qr*c~)KhvEePlSsA4Vtn;Ds1$10;7Pslf|Z-5 zX2!5l^LOAO_z=zoP}?lb;T`haFw!NFVWB^F93)CuqmIfJ&F7526Q&uA0VN zrf?nsvXJf4;ffI>zpg1Nue{;|sTm2*BO?4VT0cHw2;Ovc82JPm|c8v|-(oO0@HMcTydd~$g;2-<#o8Wk4z zYBi$BH_@4(hrfv#FtJETe=)W9$2f?i`YXG-%}gwbQ1c@fbovpQk9}G~79_uii;O>5 zzNlm_iHa0~(?{kHvVUyscf%s6V-Y<1i!;xX_&|qlod>EgNW7qjTo#EXXU-C}2%rZD z$#S~kTsCx{n1)EQaEM5)RL~!bSJF{fTt0v!eR1Z~2*{kuDQFxVuRxkjMr|?LqG@Ki zQu1aBI*htzXUp~D`VkfgL>Gu(fkA}g8L#1?P65k&ud8Nr1@(T1&{ZfTF=7JoFs& z151~UAXK(?eQ8gTTrzUi4w({{03GnARSgoh>(MQ z(+7l|JLX1gB55W}YLCVNJrK%(_?c7p`5@2|@H%-`3wd3~qsj2^((=6;FnmwwzF&V5 zZ%OaH0l;oz6?Rj8Yta?^_{pDkY! zWt&JVB8N8vNJ(P{$bGAr<^j-Xf6l*c*8j{mH!sf`nsA{3R#QP?pzyy@?g(&zAVCIC ze~~aI9bag0GqEe^yu>9^MYh=0!LycKzgo`P^|2TPT(HqK#aY@o)>CFxNxZOGfF^*iV!8W= z0ONoHl)j**1}!Zsuu9R@|M9{Sjaj_Qmv=|gPu0$K*uMKsbN^R7eB*j$Z){4+9T_|# zB29PqTEKyrf<(VTr#*nyQ2v-B&^x=Vv)Mby9C-QpWu#YypgB*bsaV0@oP_dv2ADl! z0v~Z}H8AI?p&`7us3`XBTlZBbYwIFDhgqL-(-Mv18#iyFq2C=4r~U-4#p($Sb@kM} zso%eyH@;Lz0BW~CrrVB!9`VEa9EH15ojumZ%nqmkhr7v-|1I0{jxVtT(E+Aof%NC? zhO8nP*mmI?s`xA2COoL-B*n7z;n~@;Y5OL5MbW=Gz-tY7_QBgys!claWK;mOGWyg( z8Jl9MX|5W-nQn)8L=+awkoEY#39gEFlmt?{L6TuW#c84_^ zz)DGnjk0lF$VKk3JaU6JR|eq+(DT8a%;Ech%0VX_C%|D#i@sW?RHxOa;padqYyN2A zZMnBh{QR0xqK5^D00M9|P%B+c*83OX?C zzPx)dD0bHTDS|rx)m28>Xj<=et{KM;f;2B`3Y0ue%anVy%v|c-DTLXgxWWDv-W2f) z99+RwyO}A&nLN-Bc{y*;pBx5CAW0xu_M%(oa*W5dzt}7R?@hqW?6W02bwI}tg8cBv zg}T`<%DHsSm8viH2gib{3;fz5=bQoCXtZ&;va_A(<*TNWA0@YX-v0xxaC~fs0&)0= z^~F$>WuSVW4lb3RxzBR>)(?}Q+B|9%zQ=_1wAYo0IEq8E9wGON2eCGT+w}Jy)yd1C z?Nn7jz^AS^Qv|svl1jtPcjIXoHMQ#! zXTLl>uAZ1Iu|VFDLjN^yz##uQW*^d#V#W)-tT#XtsT-jEKqCwk+}JvO(7!-x`S*Cx zLc5Iq<$5>2~YyO?F4BKBdBKL7MQO(!z8;(UQqw; zzIOjQBR>9ZD665fXN+aYWV~e9=^Xoigp2o%=`OP#@CJrnn_(`v0A_lnvV$yrY;;Mj zt|QkVM9z00=4^WH-pQZ{VSJ-k>guXnQPo6d@E&cAyWscZ56)LDVo0g2RmFqknU&vD z!QmP!AjZ~VeicxTtn4_gK;{Z17haW9A(Ti!gN$}BWNCzvUUyVpa%`AcU3MyfzBPi4 zmLj{gaS(6_#EcL3-JtUrI9Mf~AR0wZ)Vv?+w1O`H!dpkefz5 zbuf(hbSu~jUeffJ2>Sa(*~To;ISa!{Joj|qJq*B2*DPwqjMLo9EcSmY4iyV-`@o6=gl;m@9yPZGb|M9>?%YJgx5imKt_9-e2@zgk*<$@WfU8kZYuua zyzAkDk4n2wA0&-nSD?P9NXdg#&wa!D~t<1;?hus9y87X>f zJA;7=j1qr|p$W|crP9>9=xqefLFL~~mTxrHs~kU`mlbJn%xd(aXRPK;280r3d-^^1)1a4SS}4MCfaWD?7c&|c@_XP$Nr;Mg+&eXgl#e${CP zQfcg0@KT3u-LAr|(?sO`4s-@z%FGAJ3iEQOmo3|01Kl3r^<=Pn?&l0r-k}^xKIKal zZZ+NA9h`Wwk{vCie^k8dWxfWmeu)&GC*~2c$^Dj=d>s%iQ;`ii!iXH5K)>yKRHU55 z&nH84_Oy=n^balahJ!8#n)3ZH8=M{Q^EXY(JNfWsZX znVNa#VHzpQQaFKZ(ZAq!FeyyGZ@Nj0njI;)P@MPsEMlOAzp$>2U#=tTIr7E;FH`9_ z@KxE_7!sH-h_OC^UqWZ$0bDf#`7T0%2GCo$n$#Pd4LsHt6f)55q2ApI$t|)oe@{8D z!WBY{Wg;zEC96=q1}g-D1yF7z{`(THe(GfCV^BIN1XvHMC+aRD)!CPpiI4Lzj%WkK z7NB_e2(TOJbt9x`LT%M^0o5?eo6UQV;UV;!=T1(X(sAdoCO{gv!bz6*U0A zKzNw|x|h)OE^=4e+TEfVc}q-aRAfOz)x@$^z+fivw`c?krD;)MOG$#p6bRnZeNfEx z%8c;mMJXXKF@U#4LEj3X|2_a0$FIYD%|C{)I6OokEx36PC3)sic`YlvZm5d7cV{?L zh_4do@Rg*wqYU9hjg8II7}^GC9`fOTW#CQwj`yaW6qmnBZtl8eB4xsoMM#2Xroe!R_R2j z)HpOKO~N3Rq>Uki9L6z*CR9ckU&wF_Gdf)5$=e@36!*ykTKfn9FzxVh4oW^7p z`-hNu0Th=_S?3}DXI`KZ`GLe#GE6m1j5`COdlZ~9tjnAu?XX?rj@ZyotYC5mUZ)mV zds)~VU-~3UEH(QHg>~yY~V8A%b1O8PJT_9c#KN)qOMKSEp>z=hd5DxNn1X zzSEgd1f|V16qv~)495`(K&V>rmk31vC$75daJr3x#oNN#hu1lqtX6&~;pa6xM z-*9H5D{W6z*WNPy&RG0!1*6_`M3^yF^YVPftG!_EA8QdC2DZ=x9`YIeo)>I<6{unH zPsx3x;Xdw;_s87S{~Ew_7I~BsH3M(yCr&%4sG7rRAsQ^Q5)=I25C+95Pd0ckG%}L8 zoI||Hw9TlyrN1F=;ga*!HJATndNj)H{`k=b&b*Viq`Hq!b51G&#!nux@)cVu3gS7pvg2n@zAx# zPFZ*F*bb95hGkHJ2&WjmL@WRpkE{|2r==L7$()DY72Vn(%5A@VS_JczPtZoUUw6-| z^P3q7xC%ocnI_^@;`Z3-@`Vh&j*voJY15HD>awA`N}5ZzdMZTsU&c_vJL$mPCa2Jl2Y3<&?aF5 zYaiE-IZQgg?6JoFR@=C}9eDpvTXI%XA4<*4=#=11=p_k1U2+GlM-HMM=(0xNXibs; zh7#MeV$H3EPJu~ z&MoG}d5P(dDPE%XAB(ZrxQEIn4J&`RVjFYgcl{V;fX%hvW=r;Gfm?|%%@R+Eh5NT9 z3FBR>xHEKRONgF|K9=b<&aGhKZ`i!@gp_MHZp$)vFri`Z>u(FrU8vfJ;X!qP?b%LY9B2C4B;YtlbBf2SW_m7jW%6bO1CH3vsA@x66g6KM*kqtFS?=O$E? zV1b`r-5*6XqzbG!ar(FI)%bpze{EKgyyA`mbBk?6HFC@Z2_)UNi>0qi#}oV3n)HVqHda)Xw~J?& zn(X@W$Qt}G{w&cs{dtsi{6$}SvWp)ukWzO=&*k)z9pX@q5AzXTKUNOLcdNLodjET5d}+6ZO6NBa}aBt01ephcpQZ zdcM|1vaQs|#k=R-P^aw~P>)n>0G|^fII~bZn~^j!zIA$__3}WaYjtDaePib_!Ki3j z^i&)YGbee;iCPXaY`7S8CX_IuiB0ZT)zL)zpN6k-sN`pZVZES4LT?dF?p#@O8hUet zB81OBQ5(n@lTW%x3qM_*#gOs-hrzXRBkiBwmZ>LSnW}e zL6mo%kJqb6=#BQ}^c00OhygRjj#4wk28bWc_X${t15u}PUeAOWTq4^Io1xpNS5|70 zX#Q$T^hbqgdOuP!Mt><^44|HQ+>i4s2@u$cqF`_hb^gAhiPyAVbz}ERSt0*WVv%Tt zK=>jxL|`|oLhAW%?xA|GL4dgrzi%1=^#M2arZV>gU?3PUY>TS^-jFc+P4DzC6QYgwo7#RtC%IK0 zzyO^#V#iZ&%|TrioBiGS0c4ZcQLa~oHO$9`9w5m<{6~P!Vg?C4EVFmK`3NY~A%usH4l!DXywqM~v|*`wdkT%b&U{L>pXu3N1ow zwvgMh)EX@3o%v6Ne(LeoFs~C19c&UTS3zUF0}k5m(P|eP1)NsJQT|{eK`!CeuVde% zkmW!%HdKE3&8#!}+n-^oBa?_l&wscFt~{bltVCOy{ruS~X?QT*c7~C_O06bptUN4y z#Eve+c!JTpY7-u02&B3w)Qn9|@Hjf)u=a#!;Iwo>msBUMn4k%{#N1yTmyLsiJ*CUx z-jOrt7v36R1Rl>l(R}xs-dgJsMtT;r*iz;)R}eMLa)`{c@O!VlnF4z?U#!*xa)0KX1QU z{T<5du^T_(w1R-TMo26mNCtc145cG$VrSGD^lObdJ&ZW>*!h=qbj@H-RoSq{%&Tq< zKu;^HednL}v`Ic0(54w}|I4;QwBp380BiaN_|P>pG#LL=Q3ay`N$e$w4117ah#v=A z3oI++WyJ0?gHwwsua9yxxI#^*EZ+eu`-oF8h7jTz`qY8i(`to0E6+5edgZ;NgW1Ld z**zB~&LQ6Tu@trw70qo_V%+edi&^Ch*c$X1*P$~J>WE#`zrk{ELhI#pTUPrHUfj+G4!T0 z<-CY;e<-9(5rh)b5J^OWT9Ub}NgP2nfd|PAu=&E-P;Efkl6gDdlF5rWI3OyUaVY+g z9IB`uxg<}ewQ*Cyx<}42@nAy{nGR+vyE7QAG`rDIA6b-29nMqqPjOQ z8&XvG2_g9C%}iBxES@9`fb+8Ig96%%h`13`VyZb-kuH&MZxc(D1+xhRzE^vk*FU#ij#G}HB{x62n6(91&|P@o92{CQD>E}QTi8cO?Bnk_FyW%wgA8b( zj4JNW&(^y*T3fHB@O2oukEX{`=>y)ssR=SWo*T}d>xnQ$aQupp&VUdE4Ozb71{Qb! z3Sb?e*pW*Ew^rrKc*O5P!oY115Q#P~!gb2^a;PX7#lC?bn91o%c-m`&c#8%jxdjt!nQIn0YSX+PPO9GYV`ZJ0`l%l`C2O`_ z2$;(~FKx&MjL3utE+MG%@mIi~S0?udd9=>YGqK`%%p@*!NshI#wPlPSvDsR2qNk<2 zqO+*Hq8qPD?^-4rfNX!s*5-`-o;uCXrQdT9onQ|iX0X{)XI;na)|gQ!yN!%0GAoh4 zU`nBA^lZZu3;Zvgn}%yx>0!F>U$&m+UrN^|@AyyT>MNONtf<)X;HcONyppe8#iqDQ z`BV}Y0>24y<@ovKB5N7oTV%^N$k-fM2NUH6;ODGQ);NslO@hi{sf`MS8F%lR;did7 z9danEL7WvHwoE+l{|nNiX!dAevjhTC^Ojc3Dae!Zw?Uq@o9E`u3z`;hp3}5w^K!hB zuS>a3TEvuy*-iCvgC+>V<1_j(vGHB*pNY=Ib$IgDs^yZif2FI~D+1!hdDt5z$EB*{$=N4i2T3Ouw42Dx)*7H#pr zJlQy`Fh7f384C0~K{%p*gE&256&@oi;Ht-mXQrbiBUc{r*I7#Z9!N9_{RJtfLtmT2%$$ck7 zw%4;pE~HL9n~rsz>fTj3gp26Vr;db#gcMA|Y%+vY)`F*9-@khF;b#=m5Wm)k)q}KR z9x}Iw>Ta17j}5j~;?4(f=UeDQ==xUp{N2)*j?#6@z5KtWs3g@jwC9}q*+u`z^+&DV zATQtdAou#9!}^UIxy~WHwK%M-R6c;nR(tpsqoh~5belERG(*Zt!eQ?>`;eHE_q5`N zKF!@-(I0H8s;aJOAH6TPUR&F#xw#pYp*w#rKj@*L&xbv67|6^w;0kU(c<_K453d_% z0-7J>q`kB)y}6!x#}kn(3F$2@4q``eLPEkGM@R2{hDYw@J1d4SzoCbG`5X{2-c<=} z87HR#20ML#!L!^e7lTE*&RH#NU6H%0YD^cJdI@dcrzaN?|DH{*3zLybcaVt?)_HM~ z%;aHoi+Wvt*`L{|AI{h6sOx%qiglQ8flCTxWe1tj%6{=%!|7+N#g)6cstlpFiK&IC=$U>JyJ8HS4x* z+r2#2=s>=Ghp4f@Vi5;Lr9&VP)E_F~-O(CmQw!Qdv*mQd{OKOWzTt!72c{PMZcpOH zi)2BUl#~$RD!hAj_d0KDYHD&D8)@%2#25QKPC6U0>`VuiX#(+O^TJ1}jh~AzoPeUh zPYJU?cu$hrA*+4+-ez_=A4{+A3!d)X5~;!Z+6!-ps=}?WzXkOyuH}gdX>_vL90wiQyLjzLdEjA#G5nD+ar#cmhR ztx|tC!B5p==_JVMe178|{<$-`hQ?!0efm>(tkC^0{(zJvi8(R`Fy5feu!M;D-@a}? zm6x~mmMjjfIQf!a|3D?LqThH$!9}8X*{aA)LST>BEYEkG@Z}X*Bgwf?-t0;m^v0P? zra6ztE5g8#lxXv7Dij&|_zk%MnA2|&cN`X9Fp)wdgnu;Kb=s8Z-I1@%ee*_vq8UD( zM_j*HGyP{2b83H|HFsgyFxtC64+h~z!YksWwI29&=q_5NW~S^>!$nn9J=CH?Wc9i1 zPw=~3&uVP6L4uTklsm}6Qgp(|P8iXv=vsHf;FKICY;33jZ^GsAHX-6^W;}kT7C#C* zqa@#v5MoLChgo1M&B|t`hgCy`o`>4m_Hak1A|tqL<YF!b;@s<(8DJdyC!cu`jBbrbmE!9V@HB--V<8qB3<96xBH~Z+0 zzVT7}v&;WQZ{Ye38%(uAhS=$B35jIM!x-I1|A3=AD<`M1k?FXW0v;DzbW!&iMImw$ zOcNGMYo@zb#;sRY&UfXXjfts6`5ncELP@}O2OI2W4jTZrE3)qpX#l_T=u5@i{;-b8 z6f(MGw<1G3TsrwSu#k){dGN>_kg+UQKBBv&bo?fBDC!(LcGBqBu^%BnodW*Sro`q4{QAL5NBPdNlD?~Jz>^d9w;{KW9V?4DOMY+? zcz(uR#n|iEF=pAIaD6#;ELB=n@wT47#X9-SBYnRRDiz&dhg-kWS}OYLDc8?; ztQjDYPr_^GE<5rw)1NTW#?;(1ofx#@oq#z$t2ViPkMlO)f|^;@T-+@+jjRrVxTjo< zzRw?AN)D;(k*0cWQ7BZg;LTM{I`!m~Rh!_}#*#5({6SiOz%;+6$Gvo6;6r_VJfeyl zQonwSuMe`YH0+nz)Bkz`Jo`dp@cZ#kVNaNTKfIG=_4OM8k4LX=82#|C!)sjs)~T4S z7oO=`l*jDii@gFX#xdu&s@FcMck6q{+SdGCLQt{^@$DYTPjYY=!q5SjnzBKRe zS;mesx*(68V~Sqvih~EC^v>}QnZC!?9l)^L5lz4g+-?>kx_ONRC&>Idw#m>Jwg&t9 zCb)d9L`i|*C{P8ArD$?&^HqbP>(B|S8!3KcSB-1!O7h%2uf#1689M%WGhQS0*1b{j zqR|U8PgMQXbZsg?$L>B`lqs+B2pt|7`z$zLWZ9_g>+1Ru_b=lIt(I(F=zymbHX+>rlYy=y1kCz8S6-e=w0=8w zQvu>%<|vxiRsVbh`QG&Anx>=E!_gB~Z`{q4t0i1t)gPKPai{G@NOt#qp#8cW`KtvG z#@qG|H1=ciwB@b?N?%taR^6_f08tlD*#bi6-Es^4R*!l+s!}V^I&240t@R-)!)z~H z6BpUc>q4GA8qnao1*2Wn;L4gk@pU;_y?Omlhas^_c4;$VQtZJycXN-O>EJY|4%g)o zZ;ya8h9<6sKZC8QZ^>_jVUG{dwK-aG_jn<8n?ERLp$A_nS5L*3q#S^a1H=U3(oQk8 z)?mFra;5*t^ZD%T%}N;#mvS*h4)7Q83Zq$Tgq!#h>2miEX8(%KL@mqQGj}z$?~n(o zF85}6Xw8&*XL6~P2SylMX9>r8(gv7W2I}O+PsC)mHrbXp_*8;KQNmKynL?G};pFwj zdxO5ORt2_GBy7TqoQ;Zk8&4uOdKS7Q- zR4BF_iwTFXE0zun%Kai$!fAR%QpLQ9BB#@J*nY)!b>$S~ojQtAEu%WZ460b^|9GLVBM3J zPZiokpb|En`NUHwyOl4NkL#{?!b{Aeqz;5L*g||O1*pTOVky#VkzBAH#V>yIA^pE7 zw$RK4@8nx8FH8Ks4gSn$ukv{ zEM?2h5&I@j&Wxwl<|cEBwV@6ZF=kOY1Y=+?zMQ1u|4bo$N@o(p84)CIZf5a5K^IlR z0IcS$#yJwd9yLFFC{7hBmQp2e$^qFk1TJcUYERG6PI8`Cg0gP8!>~%va1c*=prmw-b*H8%IW56K+3%LdLgZY?>oxdmm$L$=oz)O@|G_D^b7 zT6}pV_~kz0QRO1TZOzK-C1To(gM6aC@5z^jU+yOrE@cB zEJ`5<(@RSfqvxTn9&XGG5Ms5^`iK-nx5`4N)=Pv?aFq1V#pC4~b{{fd^QM{aiFMWA zyYe-++X<)e_DBkjK$Thof2iBFY3EgQ64}md*&PXeLKCY17hxS>1tgq8fFMAUPh^hPE%t9Dsc-7vaJ8CjOT-GH*_0OQM@S4I7i2o(jU29&u%MQ=#mqY7%Qk)JYqh;^~D> z-jmp}Kt7}X>ha9=EUR3r_T2eSGwHfdpsnx?QY5^2G1b$Hq5!eGr@6E~eu2-3J;=9` z{2_m)1kj@kk2oUF`@G~ z_8lGj7LjA#>W)?U7y2L=d}x~*aYC5)$!7GAqrx*cWF;jXeiUK@uXLBup*0%gl4q=mZWU-jVfGqJgt6TC^>$Vg+k09e zJ>HdT<~M=9A-PQ|+p=zk@~zA3f3Z~` z&{j@s^xJNi$AaRj;At%niE%0A!9zL_y9-5>*q5qArm>STW~5UA2XEcfC``nN?D^O? zddxSBuE%XPJvrG8KiUx|L@B!g>*PcPBnM9x;+V23<8>4&bvn6F9MZB{AuM&&0*XcC zi_>1cP!x(VHMwk7IWd;qT&S#;S8@k|jT*{K7@K+^tW_8)O689u(yB&J#!zkU!D&V_ zy`y6@{bGiJ{Qd0m!E}i#vR6sJ3L|;s6p=@!37I|%4}L-Zyzc<96W?Qv56?X9+;&aO z==LyVh364@~ocU z&E&htUQGo9K`q$fWk|ph%_vW1uGL8)5#i157I>p}xh?U@ZUyQny3uLrHe_DAlv$}o z#yi*2BWgb(7x>TF1@%rYQr*@B(k|e`{@hh3?JH}DfaO)V#ww5k-4fY1&_LQK5=}l& z8cQ$O$?@_uK^W&4LU;V0Byi38j%;%iBWA;fO!x1>LiK?!{@$?s_e6M%^WVZ(e<|lT z=q%e*ZD};SBUDiA6`G@dJE7+V%q{ey?ZbgrJ+*uGX7v$GSn!<_uk0G{T1(PKH+9sU|g>DLSC-KgmXGUMU6Zs;E)=**j;8d%_p`tl`c4CWH9wKB&{o# za%rAi7tJHi&8lNM;hJv5l}$Z+PIcgoikw~g15CV`_7u`DJk+OBP#>DU**v$MOk{(L z@lvvmJ!ST2=NB%Ij_0w38mC6`%DSXO#fsU*&}?81`*IIl+B#nx=Zo&`K8(%11>arc z&Na<2Mlk|vE&IndAxL^WK-;NxNXx)O~&9t+$PhoI+<6uSc_g+$*j| zO<(szP31Yh3{&JXkrmi?#P$q~x%n$Of&3gr8ll> zy_!ZIR>VYVIf$6b&)*K{DP<8e4|WA->}~IE1W!|^5(s;NjWs0Z8AV|pf6mn@wXf_4HAf^SM- zEKjn)sC%V(E$wH7vTD8qMvvUfTf1{ss}SNT?Te1a+k2)tMZ>UZNtw?os*lHJ$!}{6 zV3VfVnDsVJeZtZqzu2W6Vi=qp|6I;f_{rLuG-=PO(z-_^MI8P-&)s)==o*gMW%y|l z(vTr(2oB5Mrzh>UDzAj7gCeW(?49@IFR_(@iL4?81be%x-di!l52kAN{nRE z)r3NUF&4^5CW@p1;)N52Cv!R@J_`!RZRL7mU>;hu(=4=qAo`*&2?D>z<-3>vATRP4 zyehUMHSnf6DRXagi-R))D5?#K;i7!Sm|n+-@F2Mo%zF6Sq4FaL_@g(>*C#42q(B5> zcY0GWA;hv`mM3+KYkDLf(;HQ%6BLpzMX&63OZMng?65m+K&_=5=jNWQ*t|9J58C4! z9DW*s(E_zK%&S2T1P|L{a(p#XK^4w%yqD;EoM_zOr5(ZZ!xtcS*dqRZs&5)}kiMz? z;cg*5DQSdt2(c74>yz9__qrQ(HGJC_Zg*{Y8DD z_@CEY*@*apS?Wh|%A zC-_54?GgU=lO^`BaS3g<4Yt>qB2t}*_i#v!S-p-g=mMHj=m9It%~1S4?Iv58E+MbW_*kv@sI63(D(SKkXWJ zM|72Whxs5wv9oMNaF-St`;-hho+EHPk#&t|j>`!RF~}LKiJoK(-YDLB!ilxYz8GvV zY2|)M!H)^wyg2Cer1RZR{W3acbGzrUbFuNh8;A#{bZIq4isV77OlXQqfa3F!YOK9c z1DCnwLd%(V5)^4CQsCm?sEKv@X0(;ta8fsT%?g~vuXUEzUG)Urky(R7s)M^g;)%{Q z+o{3Y$hQid+0L4#`C^HQ&@b0rhBn%x#(3aT%CbF6AGi2$SDl4qCj%}ZGwy1yDO{-N z3nOw!Bl)T{gF24hH&SU)!q(|WO=4aSHay?x(f=KY`nPB{Zt?U^Na2RFU)MB$jpGy5 zKM1cyU)U-G?w#?Sbr-p}V(?6;1*$8ml4lGbo%T z45)<>`D}>px2^#BQz5_5Xk|%~L1ugIm*wQiJrUUV`HmLP{q*37`ps5nFl zP~4rw)rmAm_xbmEyNTLSsCaI@bF9G0JIu_S zRN3!^nG{uc4e*hIZH>Y; zRozvA>QXosxA^qbD`G#aey(pan3!cVdue257-Xh!aLDc;(zB8Fc3R`LI@a8>UK=zgkR8(VA$T@SD z_9Sk(mED5-sA?D4`#k1hLW1*I)YxJceHhEc!CvcLpV@UwDOeLobakz$mc4={12&vc zJ*Ig<*j3nQ635D0svP%#u10k?oA}}R>@+7fkr}eOswOb~v5=4JKYk)4-Ami3oJIV=c##BqoMCjnr)74ppJ%fO9uN;sl z&1j4B6ib$lcXmi|Q#Scm4Pgv*e1?#oYK!x88-%W8I3#>><27=*VWh1>N`0={^IjX- z>-tto$g+9HqLesxxG33;kQYbx)=TcH^fQy#Xr5`8S}4f4vGS+aU@hl%--eNv!85z& zz-KPuM8(+$0hLXFWmkC3P_yA)ke56pKX2RXbBHkF;j<=|!!f_3U+gTrj#hVdv2Wxi z46`sr`Qk#B>3*p>K?JiG2hGsvlce~E25uJv4|PikTEEe>K$-CWOlSS=UhyZA?5|+` z=S0Ss2*xNNDn&1C4LJgLdog0E>$9`i^87wwaS{!(376S9RRKTPEnG_K>~QL~S#|Vi zp3G{=g46MwyScrI-z8U`HQmrDwpQV^Y*2pqm*#V`vBG^}NUDI#k-49H$Knft5kxkeKAy zg(vn)sP0x;Km60#!_L52Vahx`DSNf&=%w1KtMYfGXDMG$Zy9 zqR5{|!v%YwqvT7-_kWZE8ZvH0iNjxjvkD}=dn%K#dvlA0T0N;e;A~8h>=lH|i+q*Q z8cSL7=X~+O35GG~3Z-0&oWDV;tB{BA<*t#3DM1N}&YZ~JBkKtpLV5l6?4Crm9wu?t z0^nt?JiJYW$q89lHaiPgHb(c&oz{2IztZ@p4MFCY-Dv*UyHp2ZG0ztrT9$iEmvkQr z8%d_6@uAn)N`T^{hj(oPD$L)v$whPFr;EuqjD%_JHO$?sS@SSOdoq?2Gq&Kq4xY*7 zD`O#Ax-hNNq|l5X?H}a_DXV&QSbUODxMh$*KF~+@T7THkIcmxmqg8lDV_-S^P$6U= zg!P?jF5zMS2^LKq$Z?#z`0}K4zkb4Ch{W_)R ze~Epm*cnN~>_%c#*jCv6H8RBs9v66LI7vH}?A%rzl-Fg5mb-^YnZ zyM$t0gjh-)tvLgwMi+T1`a8AE+hf;E_j)JzAvHv=Gst!W8`b1v=0XMtPZ~= zS%^*USOpxi2Y(PQwo!$rWWCT--BF1EJ+1l$gj`f=WmO_#=O?XhpA!2iJg?x zPB|VoR%dXZNyV9f<{E(GF*Uq%wB}r+4sxaiUh<5>mM)QWg2k)lpzElP zY@|5YswTF)*Gvsi<5SuNiV)+hyGlwMmP0LlG}tli0?hie)wfIhewF~TQ?<|CZ((V} zOpH~({xey3Jf894wJDLH`4rO={OF~Zruot_bYn-Fu0qvrT{TBbpo0ZE*AXbQ{3zc& z@ND6k&@(4-2VM+e6`jRVdq>t=Gq&(@8>NE>2b0?9QE1}%#NE82rZ1Q}9GImmcI5%G zS1rT&j0BfClJN3gdrYTT@_~HQ0;|GX$1in1pTsq}FfJeU-2zgsuif%eC(Xknp}WV+ ztTxgO_;?IQ0D2>Qx0}vw>N+<)X^Ys*K7Adnpa9UOyL)sh?VC2pn?L&}XiIO^@waJB z2v;|Ie~4M`5Fshx=4aFb_!8ijHGbRf*aq8Lpb7>molyx$=-HF}G#;ooEIf|zJO1wn zIYk}@7J@2F!!Pyll_wT#P6NSlnZl~J41hBCMmE~f1b66LGMSl0(Cj3M*V z1D~+YGN~H2v6W3TM^7F4R+HejmGmZKC?b+VXF6e&T1PyDz>coi6RQ)q8(#h7*k=f* zF(5_%{QHLRisj#;?f)W|orh)^x;GjaHj2{Ypt>B!Tg8m(Ik}BlJu>$acroWAu=${5 zf?~@Sr<~ZWuD0w29_vxwXnR|uqD~px*tti7@3zgPr%epp8%v6$rg?EHe2fA=8{_s< z=I|Qs;K`-Uv*)y3Cs-t<(u!KIdp@YuyxGF`UIfO$XW=-du=K38fA=& zwA`}3>s3VZoX8U92^bvuD~?vT?PM&H+8XWxVvdl2Vp!#)KFI{ z$QPgR)je`KaInTq&;s&hyvB%}PuG(ssQ~CV7@yPD@O5@+ZQcm*5uk6iU<+{7_N6*&rOLuQA3e5$-PO9r6K zR|fcPQLY0}1Nw~wEeQEBPz}7Xb=Aw#bbstrcEp29i{TL zWobXlF^dGBVK~o(R(~u9BIzSPMUHT#!R3B$TM?t0vsMxa#T*fKm8i(w>+Z{gKI=U26+{nAA{qmhu^eaOBT#L&s-o)6q zbIlT#@;=4nehdakYs!IblyOxEGs_!U?~cfy^YegxWTbEcI{e-SkOw;ImqW$1oV)vd znyjkIOhe{;4~!?JAa)qMuQ~yDfV$nMmfw#1H2A3WkGjcjcH_a^_LEi#L%WGQaFcS$ zFh;&d$BK(#YCxh+c?yeZa!Z*5zxy>VNMluEJ<;PTSW07E_l=o6f35nae$lgzy(h9O z;r(}p*z>5l}w=(Yo*HPIX zwPTy~Ht}RcgSsobZR(uE+0BPZvTPM6L5As4EeeGncNT|!NYZ@Fn7DRzZ(*%pT6piH zB&#G`s?KW`OQ`&4reZ%v-*aL$ghz^M%2Olh9-4XY@fih^+jT)HFbTMn#m&5`Wx5wW zD}xw)^KbRY&;N{b>svkY;GGKS$!vLcOVN^xK10)66$G}>HCWBUYa4+ie0kEJP%!*T z`HRDL5XWVL={99@scyvyVwa%htA;(>1Z2WZ*R8%vr#nX9gOleO^X$U0OOmJPOT}7?JTkuT!0*d>JH?&RKifV?<;fJ`f8Myb0*b;8@@>jr%O!=a_a|W3q zcDc43txg-A&b?buBQdIY3w3dKv6h;TZ&qdVAB9aP1y>q}vpE4~oNB^$?TW1Bp9#!R zbGOp4Pis|uTe{2TRHJmC3E6P&OJ=`}=kZN&jwM!(^B7fv#xib5mBnhWT`{+2MP;d^ z&2eBP7^+xI-sQ$!9Ob!}U0=+|UuBuI>K$|op!#bxbuG(ki_K5I@Z5cmalu{fnZ)C@ z$EgkZE;qmIw{*;&)l{zD5*~>bFf2;EaN6(;am!2BE>puLEJukc`4;z}Z1cFnZu_9* z>o1XMgMy2Bz7zIp4UrAiBQlFTm0h*;Jb>Qy7OvH27wVii)$NixHN^jHh9ji8t-d^< zQ}F)au~2ydchN|A?Dz&)@Yx!#FtWAbI2JHop`B+v70_8 z;Zg&t^r~iyM)u=5LYIQtc}bB{oY^+hqnFq=M(~3|eoHKu*UrJ_?4LlgTLEtOvn8BC0InlQjh{DxF5yzt!VaVRMPZoETg{jZu z6$b+&uzs1W{GBrEtCft9ThbvSS!)Zbioq$jnzhW7f$Zi%Gj;u=`Sm!yYH)c_X#W^f zkCO=QOB?|=vxOuSLi|+QYVhoF`5X)z)$om21aH_?Ek_Y&d|3B(X9OT}B<4cf!5fMG zQ%97js6!pSxz2z+9#jGz-cAtxbiR*vTK@8LHXi?X-)|1{xhogA+Y3sDp$50)1o20! ztw=({!Gsd8>crmtFe~#2W~0eXd7s?i>a|k3zFc5Jtne*|7lN01bBflV!F#V}`Amo9Ye2XW>Aax6RQya-I@? zLK_`YwjKiyIFi5yLc>87;hnl73$jGSquC?|{6~7o&DU0fMK(k|%xJum%oqsM%x?#E~p1aI_yKoUr6qGM`)d;lv0h3i=t z6C*MQDdsxFMv8SCevOIx6d+)95Q*r+t!xJ2ayXpP<`S>am+hlL@JLUH-=uKXa}j_i z#T49N^y|F=vCHo8?y^Vk$U|6Wt5=+tXNhPtgz-X(>!oI=OwhRt7m7{-riKUNEsq@) zs15X%i7*_Cj)lGOb)NQeo#l!Ci0EeQjy*p3`UZq&Sp}4b5!hpDIN6*xI2VNGegGdZ z?qe)?vjf;Z&`m`a83&IksyEDJ07KFN&o@8Pzi9;j?>7=pzMeJ|-5e=OVUwVh?5lcD97a82ET0~ljd}lay z{Nf0o)We+PAMq~HYNn=oF1EEIdjrWYcLM1lcIe>Xtl+>&K*4lX&Wxv6p+HN^QVWXf zU^mnaj^Y|U$8NXnPQRX^qybRzOS2XT@xrjkOH@k6$haV-Nz#Bc@-&$bP zzOajpp{wENcSTWxwEVo)XA8)kN}Bc(*JE}gN8)F_I&oa-WpK#W5PjH=6tZ_gFeFYc z1t9-suNl(2Pmw;3&**3K{uirN79qpWqp7Dr%33N^dQdlUzMeryPs>e$v22T|)oPaj+V zW<+WZp)>FLW_~@DVr99W7=Hrp45R0fikc2IY~U(fU!`1*ndD4SScwus7Vx z*en33lfyWkl%S1#C^&%uRj5An?$*y|M~}J^+m^a!XKq-$hfSSFuf%h8)2vSjix$(- zCV4vpp^7Oh;?kNFuAJiJ;jUkOl=nE>?@n$d84CrxP3_a3vrme3E>u`Pq*UhXXxafl z2SyQ2AoM0}X#GTI3)rf3S6%cygN>U&6B}^u+e=b$84CL3oDjEC_cglZ`YS|$or#cY8PD{Wi&O2UOcQz7WOY=rU%GJIi&*gJ zID1acC&kAUHRYIE;5Ew#i%A|^xZ~`Lm?*z4@F>MZ7v{EqASXTS0{>yMtH1f0Em}JJ zjBwS_g(5QJ?@c1d{%Pm$oSCKoNYgP4Br41nJ39Hf&5yOIeO(kzIi3>O?g1n@tR$&3 zAS+*~dB_CV#DmcMTETDhhU(IacsAEGA$Nxw8&0fL>p4ftof?6`s!;-6pd_Gt6i=)Z2)vk-SV zmFkzsSl|uaPbbc*_RVTc3)-knh^0GIbW!n5E`Sczh}wI(w+PrfVKRa+H`Lz&`lg*m zsG??HlUk#ZqT8*)%VT_HS(SN@UvIDRVZ4=q+NjE(0blCInT{xCz`_s6eTRi^I?vJq zs9aykb=QNLhGxEd1CcY<)w_yKS2y`bq1AY>&ESqWY0=?^*OQRN?;~C4ZPwHMupd|Z zO&2-X%PnOi)qJ};FyKLN*!kUro)iro1eSC53a2dEJt0pnFt8o$t#SNR`1dH{I%wR~ zz9jP+Lk;_wTQG@JWS)i;faY6J(SNKk2bBL&UqGzes-+(@3Pu?m5XM4I$#P%wr;U@b@pp-!MAc0FacT z1=a!A&2s=Y6`$0t1r{-5BuJBz@8}*50Ww*ofJTlv7!31AnYGCDt zy4$O}BxMH?bvfAmg`m@`Cno{x?=AmaH@?I^@oWG&DhDm6BJc=~vF83{(wyv)WWF*W zr5){t>I9%EVau;0pZLse@kBGgAEtvU!fLL@jvckT0b*>uae(>2vw*>UgtEnTuv7Z4 z7y)9sglcg0J;qavGzQ~2D0bnLGemKmAS&44$o1$rfS2b47g=t29e0~1Do9TOTC8*P zZqWtshd}STPg*VAVEW%-{;~hqu>h!$hn=)+d;>3i$o_ie?Zhp$EDqb2PQIELMvt~L z3dJr*vzZdcv#}On>vRR-{on$PBUSsI>>pSFgNT|R$ThurPT{Tvml4l7=a1~snUOCI zKb!EFEUDjX9FyTLi}!{up3KkZG}4+N#LVJS#*)BkMftPW9<{X5R@1w7E5uPKA&*-) znETbVRWp6!FqLgr`(;{2LSc#x7U1!_%S7!&4Dr+$OL}w2;m+|NFIuNnPOL=>l3N;~mt+^6Qn|1QxB<&A~xBu`a;0&1u3WS+%{^-itL-b+3-mL;&f zsKInV>%)iqJSUN!##af|Cs~n%wXp{x z4u8W`2b;`_>x)$70v4LtZG3_$=;{EJXr&w_HwqL`>*FQKa$7On$WttUQ@sETBqa_K zQXGDWT7FB<17KBs86BN@2a%xH`8u$19TY}ja-nBS%Nt-_T{OamY%F7*m;aB}>zjA5 zWfXN|gV3-FY?%=XUMd`?qn+PJNdMlM^%tSOHhG1zNDnyoHewtl$1OXbP{_}|yk^D6 zQSt$kV0-f<*8q>nZ!I&sOQ%BnzE|f@F`~qHVcI|+$rZd52u{%gQqAhFjXCLKnxx7$ zU?w!L&b>$8WP|t@eE6e>)3EfsFZVrQ=X>m&GF+>(RyUz=&oJM1eWbJ4Yx${NovjhV z$F)Qngow~&NxQS`q`6u5gYbAV7PMS9n4xNt&yVN|sr>PH8hg;lUXVCOvo34lsn6%| z$=#XISBomM<05OUmaggbg%eBRg{eiN0eTfvM!xT55(X3kin9A;w9*R_yYPW$&oA>G zJ4Vg)FWu&)l>k?(p7MI_U422Fw55Z~X)xOoy@b18^5b2^2NUh0};VFYv;Vn+*dk%XX)9Zns+G(b=YvQ<-iTaN7QNUG{$vIQ0k z_f<&scU8oxHS(L@)&ev5TFXH``U5&z;^-3qw@RqVk2Vrx21s z6%H<$ZJiS_ufrW`H27tU09&k-2qBTi!-kl7d*dZ%oWLf)M&=Z1BI}*SQ^Z+|<1OX& zP?%m9h$@yPbM$HHckLmJ?pry3&ij)H__cfVfKYin6P_;zv&sQgELgI>Y7>>K-uC#t zCp3^$Z}CTa;ZKFzAH?I>n8u*h>$E}3O{f__(mgA5x5D#532S0W{aqq!31CbO`us`} z+2`>7e#Ljn^V1eC(Q2jg){W`+sdlWdVrCBBLpMr>Ucz|9OH;&#hzxSjJ7Ax@=DcJzVR21T z;l8jkJNs*lz>L3+8r#F+r=>s*<=kZR7V5MOwgZP$TUD_{UYbQ{JZ2>Ht*8>{f@Xm7 zWfUZ`Ir&U$eL&ZI0lL2DjLy>t{0v~^ID|~@eun|TQZN*YNjak?EQPlZZR&sa#gN^< z;_A2|01us=n9)_{jL$CvHP+6I*zG~X5kPY9;m?R=g8QQL$Ty5m=l>Jv<*)87tA)gb zaK&t7?;z6|Ok$gO%816N*fPl~XA$-IeUZ(2puLqR*|g+gykaj5Jusla>s5h#FPoy; zjS6xSPq7`MmnQnB`x^(ai60}lYyhn?%4U7g&! zSX{t?^_^3K98gx+-{x$WQe=AFTo};}%8bvEe^>+A;zuAQWs|N z#h~lOO5<&0%tS-vL-n)HqqfjLwMMbrheFe(!hq5#!-FaAt>7qBVk?i+vqzTbAW|5$ zgGnpTMhejdk@%L+=A#CniJQ?FH>&+x|4XEfV)E&Jl^sPuMkZU$f1Yh+Sq%eNh_k@@ zy&>Ps8AHU5Wu=7{JcuJ~uyCS;WVj7GWP$G05SXHZ2bp$%~Eusj%>`!4Ti%MOu+)PEC&2E!Q?x zoJ_cCGgss~qIPm`I8r?l&&8-}+v*{Vr=K#X_-_L>_i}7xBS(PA&;d4yFKP54z^UL< za&{^KPn7H^eNra-n_+0;24JqujJhD~j3-90$#TS2TR;v@fN@9i!5$fZCpJu@>P#BD z86c~N9|tpg^bONLLM8Yn1gi$vAoIDw%0zo>BtbTXHzAU}$c1^VO%|#+3=<%peDT2V zi?oZ3j%vVLA3%xM7>zXtvx7o-Nr$C)m2_|K$+7Ig*=m(F1dCl%+d=C0E$r=x<^m&` zu}DBOVJ(W9O$*MvQ1>-V=0ouDozXx;oWWLTsLtWfF&n{G$6~+l;!Wec9NSx1!U(oQ z8yvhNq#$ZC|5w+k=N>#!z;BndDWR05d%AlLK3bVO)oOYBLI`O{SzDU)RCvJ z?Y?g^3{@T5*d3Iu(?nn=-GY^lwphUck><<;2rIAX`ck+*C~sTJu0Tyq+VBcg=euSX z|B&~xt!ROc7DcBQjxtGx%PKfD)9KXnP1j@mq5?HOGi(6XT}|IE{W4cb(hK2?W&<{S z!2sZ^oRo14Y=e3H?6&!eFnwAau)R+;mI#Fp{P6rq)lI*tiymBGgn?AjsYv9(hO2E%Tq%xU5Fo3DQ6OA2AtA9Zw#RzEDYVWs*jak$8jdNk;8SbU){ zA?I*Eo=VqH;!5a~O+l38L@O10z0Fl5p6<+X(cFpu#M3CINo4A2?z1W`?TsBu@ciuX z%x5BoS(R*r^0EHV)N=WC=EY;Djww^C*ZM<_9ebzVsd{?MQ@*9@rL9guQDp!<&im95 zJ4}wx;=RHGA+YOl$8R%XzJb8>LCgNFyEs22fa;7rb0C+Q*Q5^juB}zWXL#e&jW#7r()Xk~A{9$@MoND3F6w z`K50B*Y;APh%`kc=&?-DlvnxYC}48)B9&POP#i?5M`0UMJr;`aE{a?uW`6{zvY_P_jS)t;Y#fu zo`tF~U@AoU8Pc{zZdv>};m?EKTj}fkiP7FbddLw@&iD}*%2ITzpz_o?@&95(H`<>% zorW4_V)9&(9|Mv)@8?8(vtKG#HnD1>DF%HHHe>*BNh>|dxz?+y5dT}9K2YbyQw4>n z5!3g^X#ec>si|MjtO5g7P#0O!hB*U6u?bXnjqbc1z+86s;6YteTeAgwH`ns~j3>ly z<8+oM{>oW1*&isS-&g#vJA#Z8pfk6W5LhO0!SeZNJYdhw4zl3q2?V$mA9%6RpcWR@ zx}*qnX6asbzx4-tefSId$%y*PoSt=rfND>z;tL<8&W4<}ErKSzdnE0=FrR&6vQIQI zvAemi`~8r%ZTfM0zMO+!j9WZXbs4}jHmo%~+ayA(M10}90}QlHE5Df05r^0ho2#wV z`0QX1Ed~#{N6Bgp7FqndD&I09g-SS6IM#MKfRffbQQcW97Ib!Y zz^|91$(R>Amdy)B3o`*u8p~U+#=cVzfEiJk%1gRX^HyN;lwh)VzL>a#GtlUd;u0zt z0J6lwKxAX!!tJoy44~oP9j79lUXC|pJRQh2I+cG$c;(xefIr)o=dS{#kG6X{1KEW! zGc8f&8N~xEGs?|rJq?&_D4;OJo{e}>PQ=Vye#&a6OSd}^51 zscce5q+|kK4o5T{4elT3r~kDwUTJ~&VSX__jVl%ySP#F{WJWqi<}5thr$bTJ7B;Or zTKBpdLPpY%;uAheK8lF?M%Hz;_Cwono7K_qBE#~@#wQgA1-NCjg@2t-$30mn<|R+D z*Y+3Dg%JajPSmefO?v-nVf!bc`;R$leW7^LLcY$){QWgw-hjprGN)nmNtV={K^f%? z&wG89llc{fUP_+MZ19~eFMTX*v8bggbRb@I0%YkuTREFqsgq#@5egW{7--p(xgZJJszj;jvm z%sy~oMmZ0zfuzd-W~2e5u?&xJEbK`Wx5R;VywoFN51|4@)nR<}dMT7zcHcsN)c`Ut z_a*AZ(l)%}-q%0--~$o_j7b&{JBpBzd_SY`B&y-Zi%_#MdPz^1uz$axI5sl>%)9#w zQXBxT(e=k_NEoS$9lNNLRVU76q~7-;iMGUEj+x%-M)-*_5lwf9mjc;}(sc^=)1%k< z;B*!A*>A(`-mx#v{&T~${_YO{=lvi5=Ux9lx&pr~d)9o}+zq`K!2Yfp0CBu&i+sO^ zQ^jCf1-}mZ3R|chjxHFuV6pv}F;3MMm~zR% zYa3N`rOY>`J@WwX`J>l4Iax+;Kl1^CQ-js?w}Dnb7Wp5hmYaItrkDMNBL}9-eNS)z z@4C({YI~5Ei|pP12mLyKY-9gtk^j%Gz|x3hwMu;ns#J4?->h!gXJa(wa6+gc#HT~1 z)wN$Or`#xQkO8N{m1W8LHMh-q{@euOD4Vn%4coKvWVgTeSEnU#ufJC#FWx{V4Ff}` z0Mo$?_=xvlTpWN8vVgB+Y*N`#q=#5f0Q~prZw24hBnP~R4xh#5o;lv~edY4MwY-E4 zh;F$IaDAXFl(ShX`njA=!_Z*$|5e+0#x8>`L%-#sRCOShtAI$9c$(^Z4Ym?SJWR&n`RolCpzb zh8oE6D_ImeUfh>_$d-wD0)v9iq*|Iep%miPl`O{8gm#ryqf2HputS}X?fx!u(zy63 zNys1(n7u}8q9M$Jy%PXqsofl|qJsY|NmP~3?6ez|#m$Pv#~e9imVh7>r-va*I^n6n zvpcch$xd$B!p5>eUo=56=(kg!!fC`cU{a9irK76mGwq4hGEsD|VJ*p{PaGu86NpLc zqfKBvNUjI8x;fZ-JdZTN1UHhjO40pAPZ{Ei2 zvE0_99&6q9-u7w}Iq{@gS@i#-3jMpvvp-;`uNs=Ob8lpoN+Wgfd)F=Mcyc=O3ewdK zc=q41mN2q$Vn2#8UT-57D#U;gp9nCNJb6Hp%sArxywuvmDTlRWWLtu2dz6yD0Y0Vg z2%n9w0_o-wPt?7XdcYyNVCx(u)Iam6`0mr_@C7R{in|Q<>o4vsm!&FsFfm3=&fJApQ1?yk}P9#*Zq*_6B^IC{g1mEqu8D5+}kE&AAz-v zW}9VhEbJupBe#~;H@k5Bvn&?6B1GPV$ovJnpLznFiV{1R0r_QI8ODAf;Rsl73y$8Z zd-)Hc?rsgrAM2!=KF$89qk8rzK$=-qR8h)@{wOTV1nv!}n@a<4OIbEN`*G z7r`f@u3M|d760J(?^~*~ezN6498d)m8N~Fyc4~vc7P%`ynj?5~-CAEImqON4AkKSF z3l)iy0C38ZW>T|shc-tr2KYB6^tI6Z<6t!dfPUEJOdH^3%IvUK9HnxXIstZR`H8pp zvb~g2Lr>1FN{;qBmF0P@mBn|H`Fp}AaQMNI%gQcmT&Cjn+;Qi|3sI+YQ4JFX9rt{`zKz6AA z@k(f379au+6ZAVG&D)JMDkXbN+CzT&beeOj`ZP$LyaMbrQZET+x>%vM!+pN=jBap z4dk4T{(8WK@=UpPe_U|tBYRkVsWjqb;>Gyj4{OF-za*MJzrvfUq~?=C?EFa;VFGS> z+v#xim;S^8dOfD6^-jT=Vj{lI*j4Y_KYlFy)mG(kT@AwJ?X{4%BFO|y6eN7jJPc?Z zdwg0Qj^6uLZA>t(2&QqMwj@p&q6bvn!ra;al&RhVlZATtjFy&x?sE^+ePlBGK9z93 zenH)b4iUjG^ifZ9Hyn*eFH+I37x#WNuSo28oX$dBrliIyw8Gmmyt-?2+|-WZo#ImC zNXT{aZ?IH$oC%)%zbqCSHIP~$% z#szL2vEFkVo@XxKuVQQB?5a-h+gC{@I%b;Gm9MwS{hvep z{zR|;^?)}zkX^Jl;(?lq@7b?b7J>X-VT3`I@!DDFkxb@e8M08;lJT5_uGrLvP*W9q z=A{w*;X`iLzN}8rdF)9qvW=tOS+^1eoJCq9!UI@Kga=c?sW5<;JWMWDJuZ%47V)Zl zEKzP5%IXJj0`wm8>4^W`sn1H+ros5=nMtT~OzncfsO#{<&Vhbq%g#R1DeHe7c_2ae z|K!Qyk*7g^-uHi*5L*wwdQjULTYAzp)DSr7V@sIWoQ`4FVB>#{S*>#5xRt;s&Qff3 zst!F84n48zJvzxgCiG!sIwCLAn@&@+OydO^Y86%P#+{#Lp3a9hiIZyIOSbjycB#;)JUz&ULldiL!OIa#dJ%rsbLf&TEP3>)*bAZM2hdHO>eoi!`xt zKR`>c7D;Q`9T`_)JtP?qsf71Wngo5Eko5nnUEw@}Iod+XKwag(}U zs#AI{>ff9Urh~|!j>NwE@A&j(0A79Z#GlzGPfd-k&U@~HUsuz2?Vsc=16~dryVyJR zR*-9_ExA5y#<`;484Pz`kRBs?`6y@=ZMeP#ScC0 zep5viD7swXZ@!ToN$CO5N}G6_C@-uUn4&nUQUz`ZKbYC)SNiHUIac}G+M3l~^z%Q^ zxQ&lyq|?Z#RI=F7%813Y+34bL@LSIkZtvoGSv7dm@Kf+)<|mQ4?+Qb2-TfZE{^0k^ z_~2(`)K=J=txDotO>3L@vyWKl$O`?H9k^+M4QuuH!mCPKmHl(g zn`|B9kYcTZSPSmbg139^rLXE<^{}fKx|kW^TCw*d2kZ8Iop-~=G8W8rk#Vkbk%w7I zR*ecFzI(iLAe6L8NhQ4XQ6wBLIq3dX%-+`#9g-q1x4*&zi12K5>tWrhP9v{JoSV|`l?F-JKFlMHb7g)!S69{iU9o>vO<`kpr4xJ?;_ z?DN`l0YQqmtAXORS^$=CY52pszbddqnfYY7zw`o``Z`v6)RbpsfLzm=w#JZXhUX>>}g@F8i^5Bxk|chDsfTj zCSODhd-v}1#6Y<%yJLB%IBFo!C!rCD4%Y%1t0>BMjSeEZ{8%UWK8KEbM zx%GM}B1l$7J~)q@D@gwJxK&c|lR`7npQoQCS2&`T=MzuvO2zzzEhwqI1=9-H2_=J? zmT+9{^k1XHIQjUD=yU2DNFzrN;xjvUlEBy}YJ#37L3H!l4Rnb@Z4)%US9v+10NMQ& z)QyO}@(b`@&XmvJ-9R%t|438(!ziQc^Z2CbpV=9ZFJxOXV4xMmSn?(y_K?Lm6ZGeA zEusD|^!3;zT$j{57@zagMBpxjnKvrfd>4;9OR4aT9()S~h#i2v~ILB7~mn4$koY z@hUIb8Q=V8B%I!?|SwhNna zJ%DaqJ9Fz%;yI*o^@$7;zaAlMwkdG=MKCsk?(j?=aV9a*?y_JKpK#{jT5#5TpUKs8 zeBM&r$v$q|2gh^5UAr*C>}C7E%uO#otJ)Ko`vP(d3NYHJsc~|^0!ymD>^U(AFG2|% zzSze*C$B_0xq>@ukXljsrN8{vhsX{~AqW??UP(0#nAT2u*6H54P9Iige%+_f55JZd zm%FN`q%2Q%0NKW4?E?Nmr!_yK+H3oRQ}^I^xI*e&8xznpkEV=^cd-Y+X-+zI|JAkW z1Er(I58LtG9JjB^9r?-f&t^QdX{FG?6zZzEk+M#*LqmGvUp)6Hpk@#k{N^s?uhv>K za0O9fnNnp5;Z+~G%Kf@9YQ53joiSDv$~u`DHpwdoe)Und-XgiqS2<$LfD- zS$wF1*KwJDinxQh0{PHk4VI$NbOZj(`04yJ+)CCa=FR|!G=Jr}vfReSLH6wxKYY^4 zyXuiu2lH@uMtb3nQ$WfbXN0R#!zgqLqQZS1FBBbRM2MK2>WI>c&!zi{UX%P&e*mP| z7+tLgTn&B$yp#F%7HjuQdW(8_h5J?AM3k8`*4-LKrY^!Jz>r^P(<0pI`TLQjb5Xg% zRrA#|KSS=Hq0~y}Wa{Vh1|A{5dHOTw116AspzPY~+CO}P`-x_L6W}IF?m#L<_R|`?ZOHZffz);chVMC* z@Emd=)tY2XKy}zEB%It-)^|;4?D56J_NtUiBrIkm(9J&Uf|52r7N_8@d;+|Kn-E_P zaC;1p7(xMee5=))*Q*(*tZDuk@QJSyU?oX9TU1#Cv7K?vjkjv0w6f|7#@!>&HC7Cx z^#LqOz#C<3RMp6<(XE!cO-|lEPx(W4%TK=Z1mbb_i$ECI0CEXmBvf(yVnWXWp!K5t zFdc0v?m+rTT^2Rj7_0lCo;GXb5OLAoG6#eNa`|xaePV336FwVg`@`R|LjY2BoVb&) zXy(ZZuA0r&=;V}AtInpKW^4(T=QwvWi7DeC9=xsiP@>EwuyPnurx~hX-$-J|l!E5F%NYtUG%vUe%a0-A=O1xzk{_ z^D8DZ-*K;p%VAuDTYLG&{MF7YExV~^mNvJ6sL~YdAhI@l z?FDNI)2ga_Z5CkOcfCyaIza(j^t%pu_;k^X|9kgee!wJeSfEu<>byWaD$FDl8$mMh z>rw}GQaBhCKX;BR&7r^GX z5{Z1L#%2`XJG9+Z>LeC994Y&?>@e=_n}4f8JgfgzgBZ?vKYP{QOlbSPS5{Vn71UvX z%job`hcyM<(ukNszra@AehYN6H5c;Fb}%N@=Ej ztGD{HsAyyz3lLw&4cKK7n!to(u^#=zF*kE(kk}bMcSBYnt`651+7-JFMC}9)rFNUB zHvTwq*G%2|!!PPk)3}GQ{gV{BZI8Y4iN^otXMd-L@F;VF0qA}=={~1H9{sf&_`Nag z-h5NH+Yw!M_8Krg*KE9-&;`c1(I$PS1w^lQ=isAb5?K6n%mDnMHn;ZiH%uAB! z0G;(6s(D1R?vM3kBUwKq^-Y$RVR0C0p7FAQJfrteh}*qdVMjn!r^-DJ5zAkl!#B6f z!nMED?;PxHsIXK)7s&4f#o-sJ{Za{ zP~^pg7cn){Q__^&Ov|E;!4Okmph$Em#zhYx$=IJyA^MtJ+l}-0`veJ`{^>X(uzA%p z(O0SP4#|O-=7GR;Ox#|d1#fT=Xa70nUmz5Ef?W7sQGvLsNeim&s_7tP=ccXUz~3QE z|J$?o7vBG?;7;e3KxqI}yslLnWCT5`(%KDd-ayawqc|gqw^g8~2F;YyK9u$j^9#h% zo#X9y30{lO*g04G;Vv4fGOf*H0&(IVZlzxHf$RKnCZVPo&Nd0GelzQP;>t~*e;`o% zb&OM{yhH0bYJU?4To}9#>s>p!uZ3XXn*Gn8bkd8Zg1Ghf%A8}fG2*+z+7j3jEg^V+z-!f?fDV*U2( zgoTxtfStnP?~(pdc%)=;*3~6&xC;qS^~w7Wh#qf7{m~!T($ge)W1r1Xme-FgdF`@3tl0`8TL{f}S9r z1ib%dyb#94Wiz?wv0iI?ICa^OOfjF&Ot@Ua@@%5Hm3#ygOh=ykp;+lK?_g`j;DniC zy)+d)AKB8|KSGYqCUcBV^8vYrG$aZKfhDJQbZ>S&X$d+DY0bv&6CZE^|xF1nz2rkq;s{x8+@>&^E{UVZq`jhol)bb#Ya6}Qe zyt3fi82ywgpd|pMM!ZJ(C&jzk&!ifHB)=s()*QA`Ngo^X(sN{q;MQUe|9Il&<*bsc zUPA>WfC~E4wp<0B!g5ox;+5Beaws#zd68m5r4YIVR@xBid*ijuR0_$iTquWi42;tQV}6P)gKK%;ZramB z>#j0~2l_c38?K(~Ca2-RsJ$4L6g@l5^}L5XIOwTbJ_DK)0!SxJ8~8j(zMB#&n=a6$ z9Cy!;K5w6LWlmX%oJ|=)U3>--BwV#>|J1k7-1^HQRM^w2(!T zTNzW-yl1`|U%Bk#Fmuia`Mivy49+}wA*ILF-fbdWajyU@0qg*93QzY&&FBf$3z4)2 z3rE~{%tx|cz53H2cJ11QGcSHig_sFs!49f-9bi#5_gMrFU!~3I^NLJaBxzfy*W%K@ zh2$X|FJe^X(v=^xjOFp&6WV(D;qKGqcZxCtA_5xXyahQ!A~$5}j<0VL&LORCiqw8A zrHmbTqWeb1GoLS~QmQqkLf6a<8q?f%Jj{L@8P&<7Pm;xY-D@hqJ8?#IV~2L#ElDSk zZoNcVLF7R{8UMFoW0F7cp{wS*UgOdtoxSu_eN zx4(fyPWLOy6+UPIofu)4`KTk?N+53XcMo-$UghRCqKtQqfPW5XSH4Y99}TOfvmXdzno zPN12)_451=N4^iX>mNwMjh=IvZuf_Wb>sy}fyhSf+eF-kNi!*$Bj)sYF#CtK=@p&^ z5wCwB;B_SJ9^emLy1x%Rk3-HijR(O%ED!3li;Ki*bo-B^oI^a%no`rJIbzN z^gzcX+@Pwg^y>k_s`zOT4c=hm$VpnsljJzGZ&?;9Lp#)2n|1r6OHHL82KOZIyBqZ04OMerP;6L9RC zWE{qxRJs(`3&oK-Zj7VnPL)5#NMwGCXPmhaSJ~9_$csS zlN0MQ7EPI$cmCeW@7K{0rpLA#E)(B9JaNqDj&C*-h%0la5?%y*8tcC1Ivk-ONjVpP zYWXgB4!G28sRPH+Rx(CQJ89H<=u^DEi#)WdF6$$QRTO-};8EhXk;7Op=y=d}kzUww z6hJuDl&;te8S*%6@yLaiBA|A;6KtrvMJfKCzNjkk!!clFx}V2vJW|@>YMz^`zn9^(;D-*VT``YS0McJJJ|R- zn_OnA!IJj^Ed(iQu$`XyHCaMjkLZM{5m*$Q`;aH?DX?(evs7hb30M>+22}04p24U1AVQ@{ofmo1@WfsOtc_($x>1JWX@{e`AW=Hl64biU^UPn@7=PozKYI} z^sw5bgbXR0rSBG=RQ5*Y+8*OX1e24O4sqMRM@9_(Mmm_1Nc2zdT4V zrWS3z^>%Y)`&{TnfTL}`Xdy2t#QH{%;mYo-d~FjJ_oEfb|!1txhLs#MNdw;>wpPT>@zPsV9tLqbqY46 z-u6+fckSZl-@6P*_bP>qDQXCQsOr#C#4NWd;W1s}0&4XN2orw@ejy=i<3w_uxky5No zTlG@lOJBJ%2_S7Z{yq+qPO>uOp@-4t!_i8ITtMwDZVq}Zpx4PB^kja*p7FW@_r?7T z&;5?dpoh?g0_yR*#<}qVB;%tzl0M$gd@~Ixm6#V^qp5P)E1JV^77Y|+8itn!*whC_ zPDVusT}$UDp@tMgmnMAF)d~X^J7ZUbi@0{0wmdzt@6v2;#QWZea*<1I_DZn5XB&Be zMrZ?F+|FCE2PWuD!%c(7@%lSQGL!2~ zizxK&S*Y+KUZUcIN^_56#Op58mZc0{&jv+ct1rve92VD0vv@~ksz4am3ZOX8{cG_u z78YABB~PyJAy-K0YQVW?*1fzvoX}%LE0o2qt)Ng;>nzl#I|VZs$tH|z6Owt0a=VvT z)l6w(IJ08=NDGwsyYRs{`rJ+1+R*;JY20e>+N#zvYkOFqK?b|_nm{e0!n{olWea=%lBw)1v7k?AQ@!%{vm6%rD)v za%CPE+Iby4G{&%x?IvxW0?9RG7?))vcb;$od&Sm0W{<9DM7@m9?tC`*ja+|QfbJkA zS7<5nR+RHn8H<901xRXEL-}wa@za)TRF{U6(+p)KdQuWOlrpLePg>cM!|_>hn7$-~ zR)`i4W!?o>t*$ZD6pH-<=0?_50D{p%;#$+9RD-2yjE?FNJX^b^VYxOMaUNmU;=^9r zGv0<&p60TvH}PT6?g(x(86iFDqxI-n$d!2$cW|u0roxS@j`00u>Xy(I5@9i+*(+2!BRT9NR&1=DA4-PeeQEQ#BQOV1R-LnXOgQA# zD^(^OLDGy%baivy?CiHTEibv8^q4KSj^7p_2_6qse_YK^qL9T{ybeMAis3m`^x2=d zG4QWs`(aF1r|c(Qd$gl*_A8kNZikd&w; zk5KK{*xEACGe93)7wTzWQCba!s107i}P~5LGt7pRF`$n`3jgY@EUWn z@I9-{G^|j}jgi$Fw*2uUZqpH6y{9T}|H^=@*ErY`j-RjFag;fAm~F_OQ$Jo7Kc5RZ zdOLv_^no^r)V(dOT5>*3@RaR<6&!xdq|sBJIPoXYDm~`@gdGp+Q2;wh8)*jvE{o^jU;(aRmB$TsHL^t}i}Q5Y?QnQ}r!%V7~|gwR-CHdeSokqnh5 ztycJyXc(qgjgQSV)M^9Fen!WN=LL07e2$Lc&?=UARU^^KoVm9?7;ScLfmjTGIJv&+ zVb>toe3RHx0zZ1g67PE@(03>(HlcrEMbh1B(NjR*QvF#1!DILuv#BV!T^=LMkhpG^ zCdgJS7ka{2VwK+Iy-ZFrB#k{bMk#m@K2=%5>pFGE;F+XaAtxnGIF7now9-?4ZBdG) zO@IUh>m#R~7VhVih>Vlrkj^E{$cLwjmy*XhU656I<-x%%9QQs`+!M%DA7e`(wW*j0 z@5PVt>s!7;GoAGAK_UZ8h@+uzn^}^xy0M{Yapy*(?hR9HbQip`PVju4SuYD7_$55y z^_S&VaP}0A*pG<2DOPKq(-Lk8UI$;Dpbhc{!raD|1SI{gFu>8W(F*D_&|;}k>?506 zv{80Fr`egw9}G9a-z^N{wzKEpFm0nk%Pl^KQzyrUu|<>gNj}Oa7xqIV(Aq~lP~pk~ zx0-7~>FnBg(r*R9UDiE>nEr(HSNH10z_%yvNNLgTqySG`q?^rV{IUPSBqsQ&#eHqa zPPT5<@|GZYGn$U`GAdW>nl}BSQ#s2Q?~pr!VF*|6Bh_5@${m4n#rwKvmsWBut=~a! z0rq0hA6}PV{^R`2y}m4ZYVjhM1Z%x2jloZ|k*v&W`l;;N){!j6^<@1{**Lct!fNUC zlP?b7ym8ahvr|^j#ruk%%w55)5iiF3vh-%AADa7T8YU-Q7qnMWv&Bs5-q}8D>&Wcxx#jdN%swbZ|l+BrTSFo3_$BuA;D_w_##Hgj`z%?`H zNi}Pv)up8yH4(MK2N(`$`a&=kp>N$)oBj6I>=Uu6{GN`FMeGc+p_EpaTxQ>KaeLK0 zQJYRcTNZ$Y4a#alHLe>mi+q|^jfM`hQ{e-&0KoN`h!=$#k(THypfB;a|JTWwq|)#W{(dFYFCNHeU3C&{FFW5MU^c}WxuuT z2B=To9HQ7b?hnB&dcuak@O9PmX}Qo*rLk)_aN5bueY)dqeQ>U;9Ii0wk)13g$$fFT zNJgOeWLp=ov_)*usuRyh;(fihchJZhtXK}acB8!f2b-y|EpdMN`hC}H=9f%`3n&O{ zpIT0MkNs~X#B^?u@Cm%$`I4!tbMQO_%*mnB3lnXqo7~a!0&YZ$t*o}x>76{pT6=WIMc9$rz!npi~}mHZrYqMn8%>K&u?>*4)*%iZf=q~ z+$}RE8Z{D(macf(g`+2rz}*-WmbDNBi$e=`2+h&BcTM{pc$qm=2@x;a3@&E|9|n6O zJ3XnHHRHZ~`HB0O?TzvhyRxWAi|BK0sp&Ms*K+Il#|k^%T9%g{dhg1O9&WP zZ2ECu**uvYUiy}yfw}IL^;5>EDB^F8UdcXAqfb^7&F?=(+i&jhA~p=54OcUQ7cvTX zp$)y*;EsLe-3{&6#B5O#PBh~m&$r}%n!`%}4OZBiO2y7;DcD=+t5jDW7iBj0+JgPA zQe4(V3dgC(8}{s#h@1hJoy%4+vqeht>PO^zcCnk&B7>#rm(q($Mucc>R07M>LyRl3 zWO%9O-9k_8`p_lkf9={~9tg*wAv@a3C)oUs)uYm5TBHTuy0f$#22!c=x zdsXH+?oCBw{2)EaW%L=zgwo(T!la^c+<++bk?Kn^Mt{Tv*06 zf~sv2ygr2^E&6hw#7{}G^;U3dG9{D-}1WVA2BHoIDIVLVUQ zh86ajuY1S|g>mJCZ-!wk!5q8N&9`()BZGa!&v^PBqP$leEqPvlCCf%b-amVlNpD}DPsIfCee-4>rRJ?9t)IrO_t9g-cuqy! zS;-t(ZaR0*PjAI8!nph3uGf!P=f@%(m|E=#w4qVk-SdZ}0UL~r)0ZDb&rip=KOP_+ z3{!(Yy*wDNxv;`bXfyu&aJ%<9;&cW9r)f)>A}bRQ#N%BCrEN}KbcmR4!AHs_DKFXu zM;p2Ess1$N+n5V4*I&9SHp9$*mUweIewc!ST&m5-#s@fWUsN81WBr1yn46@lt0dM! zH~NL9Yfr9z!X~UASzS4;ZQ~zZul1z%Ie<@-B$L)zo!R9%HQdzKqmE^(S-K`d>9#zg zxv#glNtwKSyKk>gXMpI_$RD>=aOc6TE60Dvl#Va`-_ryK-g9f$ZNP$et>-HzE2;B> z?M_d*yUs)RQTuH>iruG{SfauyHhBY=YNML4r&+(Mcx06?Hm^?zo+IjZKA0=+J9qxZ zFvFuhc-T-m;>*L(MN|r}ds{KiE^O2>yg;#A$f6CRWq-04Yd^B@&)WsLxH-%;6IeD5 zpYO~E+hkO(!55BYk@3D7G7-h^H{O9`RKC~Ev?_D5*->j=aS}4#xl@&FMa7nIJInl1 z^j1K}YF(26N!ONafmJQWON` zsd5FLwO8>l;J9|cIv^K#(~z=499nrRyCQ{x4;uy>;V~GN5Rp>53JO2`8vmWV?*s~q znOME~C#z07MTZ3g=i@X7(pOdO5%?$Cp_zt#$;o#VVD-vsS4R{2mr^2Q?Rrf#3?>-p zV~ds5Y+)ZI?wY9V=%(M9VhIm8^1-3;VxAYm>-3{k2Zc1$3Kg}~Lr=VF-QqUPy18(J zOh!qT7>bQK@=>w4B;;a>v|aX7?jds76_#1C@{fOZj z@RRVNe!1{+gY(w`gJvNr?$gPyFt+u~igTyUS?#^I*gTV7E#79s=ZxQEvrQz8d&Td1 zajrStn_S8$3acLMP7C7y0vMDJ_Rf(kkH=o&mvpM}6!soAI-%BPQ5snr?W^i5= z7*(CL;xZMgRFp;9M2U47lnaIxql{ELQ5-I13LX7Qpk6snSw1`p$TTcCb&lw9w|#et zgz}p-y9g}LIA;*XHxY=(M7H%QDH6ZW1Pw=%*?4ylHLNp6-%Bad1#Ct$>p&;sEHkv> zlCj0nvdk&tqRf&v+*SM76xSHKUA*5<74PsQqh(Sn>+CaVlCaM3kVGnbtv@Rl^0@ju zcpra3$jcvbE%|MWw`46W`LY5XNSU(z)-h`jw@{j9v%iA}h zk{~YsXdZRt$w9AX;evsLM@nGna=7$Fq)S=KAGvuo&`RDWPPbNm4KJOMc8+Ak%KdbGoPM zOyl&ZZ_K|&jCl5O;nA0a;o?EuhuJoMl5xl9rFn--e(?^^_2k4V+8~f_MWCig_Pfi&&;bhTk-jjw{w_2AvoY}{ZqfIq3xWL9 z04qGV!ULq0NDcM7`_1<8zA~5es&=rh^0nQ1+G4*uNVc|(36P{2Zo=MpG^{BlFdMi7 z8M((*WZ~C+=A!~-mqJohyl+NbKw{73!N~Ej{fT?|a*jMAYk~!l zG#w?S;`X|EX<7V+citPy*d4A2hIK_&Eenw32BpKDn6ueOUV5i3_MINIfvUTDZc}Uq zJL5){`K>?G7MXg=aD@~#NMQ|sRzp~8fJOww!raOiJP~(lLc@kB@(y1!sTSJJs_taVL=~4FqWMR$m^(jm7f~FmoU#?wIkf!4kC;9bv7`Q!~A^Z>{k4jyRI-Z zpL?1&D?0YHXfPD_YBVC9=U4Y)p2{jXwt6KbMORiPT?bcvQdoPS8V|IAm&iIj5RDK% z9!HXAa2gZ!OgzQp5_u5!*Y$#*sFi?-YxMUDXc?$`6p1BDR6CDA@58h0QdRsFOp4m} zuf#xe&A`R7*F5R?bx!2mNz?xnJ;fjuV##Cboa=N2{jcgHZ>!y-+`665K2qqWS})@5 zFKwg6eX)GC>gl4iT2-cDU^O3EuAm+M*4Wa$WR@<$d;Jt(S(@*a!BJ*C#B%q-~J)KZXDH z@xD7BVDAk{K9m2=gSmg$W(f7}$pPz2G&KV3MT48I9W;GUPLdht6L*)tZV`|YD*@hj zEfQA(dq0hD_XhI22F1uz$*Nk^k)L^w9Wfgq6Heq0oyX#J55`+ph32ruH4#g4tS6kS zl;_V}z8Jkc7#5POT?2hsFp&fBOT367J)KI^p$)U^S+%63wvYw-{?Yu6DJ1W zKKIP$y)+O`Wji0uZ+sz-#$S$Rz6}WQqsN;A9`yh^#L!f{(7=t54(bZt^?hz|e8lOn z5>ml`_LltAY0=X~aY3ce6iP0q;gex!Zg~{cugX_#5);7G#O2SV$|3gfZ=5CnSDzpJ lMwEuItFxYQDlao=BE|4_z{T~%*D$M`@ literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/modelloss.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/modelloss.png new file mode 100644 index 0000000000000000000000000000000000000000..4870b192efeca54d0590f68f9468601c8e5527b9 GIT binary patch literal 33507 zcmb4r1yoh-_vQrzq(zVvP!Lh+mR1A-DFNwj>9}-DD^f}~iXhV6jdV$O!=<}(-b?)c z|Cu$jX6CNN_vz)F^VZ(ae)hBX@$-8r5iE2PbO;23B_=8)3xOcHK_CdTcTvDMCHKjZ z!T-2ygq3XMEDUVywXO9blG-+wrWQ7)Mmmq|^sS*r7UrxBYz!=Pk3QPiSVFlO8O{E4 z0fU9LAtSBVtP*$#nx&{R6avA(ga05vV&aG(5YP8wLa#qK#H~%(JABYTY1-a=@*So1 z$&-)}#5;GX(c--+lMoR-zhEI?*l9m-p8AoIU2&pnOHWH+s`OjoJ%Y@uFa14__hP&W z1i6=?Ztf5LbMc=?$Fxu!PV427&8a%oa`kdc{9 zhnc3rfj{!&jtiC{pGp$(yS#)H7rpq-11p0|@AKTE9_;g@yFUxYk@eXm1aA8%Pow8d^75<@`A)sL7x}o?PIfxWayOv1mwx>dBLo z9V&YIENkP%l+$~xvZZ!Iy!oA)pNO?*nmgZ zQ%9=RgXwlxpaAa2F(Kl%S#lhDL`j(-Stl(dWE`LT#%~9l1dH>5Xa z1KhDa*Ze&;HXt|{2ip&ck?~xa5I0n=PxCG=Zn~{Xk?~(bO_w?(9Nt&wC;P`2rkS$lpsC0*sT?;jALJ6>vK=(-W9 z=@t#nx-A%fNF(}@+rjQ7!nCeOq`wnSoZ=XwW-bmJ{a$+;;_0G*@N^qD( zgYaLTL3MO>tzJH?Je+j?N+D4F?lN9Ts1Z8+bq)_Ma z@LwoZF@XFb9KZt}DXEDqF&qvlDI z_=Nw@kV#(9bUo6zsOFMS!X+*l2}Qsgrf8vp*?-f3q{v~dA&VzbhZRx#0~sOf53pGTAE@~yE^Xm)PS z5!fsJV`SJz*Z7_M~S7KJ+w)(S;pHos(6D(t!0!dlT$6uP4FQ?*V zYZiXQtvNp+H5tm*2PQ$MSsmxNyIA(;!&S^kN4B=Mc7Vm(cOAQVpvI z;JGt@WUsb7h2W+77A+&Az}$JNbfT1~sDHqpKjaLnE775$uYbM`e8Je<*qCdx+*?p? zakw$DJW;_3oSDeC4sMMuE|nSY9$atd!Pz0H=tQjIui)r=3)7p5)CmViebNG*0F9S> zl99kE9i5)aFCHj;J)6NMF;R048@$qAx-y%FSOZO;CRBvC|$rLynTITKYS3f zwq^mpQ;D{gi&AKduWnNYl|mwAfAsuJ}D4LXGLPL^n!q?vu*YsDv-=o|*tXjf{-KBm4UL z0B-YVoVtNKY*q&YYinOY;Bgh8uQa+Fl}J#g#Eh7jnEZ#bE9)yAjefiMM?8{2U1}I( zGpl5BcFdv%`4K&RV3ul00{&SHhuJ&em5`HgNSm00TvmL z9q)pMqnn#sxTdqS^X1G*EoA1jmB31#o+NHh}RPh%aEs*0wh8 zP3Xh9{At6IF-NdL#7tU{?d@$$GVU zCFC)i#bjKu*;sG2tMh1yMK_=!3;*$syXfeY0s@y|&DKz8x?&Ew?MlCPU#cXXa(+r% z*VrF&k^}; z9UANN?nv>WBP;N}b5)pL%{&buHWROGW=yT5*Yef`qEpQvV| zg^wRSn)Z%IVyHQ@hQ}=cIYtA29!!+mX5{aloSyEs(j-~}y7Ym={^?Q3wq8nw=-54V7Eo=2v^S05(DMVg9m$E3#GckZ#i0j#N`~2Pa z$pgQxOkR}!*ECEAO$PfFmc~^$Y2*fX4_3Z@RBgw|?r^=G+JM_gJDY;@C)4+ zi0Wms{pO_UaPB9bjZ&}PUfDP)8cp|eb{QENxXteE*}Qo1!eKGmkch){7}<5q@J(F~ z$rB;2sJL%UpDOQ@pq#3z2f-IDn#BhAJh|J^OxrXkAir)W%QWOJTdyBtqk?_^0bCN$ z_@g)!Q{c^Bod&wVSODC7zBoUHb91;AkvlCtHm^Q5cqcBN{`eX|jsv66}PSv^1=IHT$P<070SI zSVS|q^VhTlr!TZQmEQnqDO(xi`!on9Fc>Q0l{k2Ol@BSc_>!7WgQP=eXTBAal;bO$ za79PAetAHvROQ4DP6|*2#nv(qUY`QLfBWhc1Vm1qt~jnj(~)oCw2HmOW~vtlB{kdi z7>plU%P#!ip8a{9lo&sp%Wb@MWnwyc+6}%|-F%0ZOFfSPY&C~Hm%EFD)7;$bR|bXU z14apT>j3j(b~|$bTh;&;G+bbalciFm19Am6lfkcmvV{P$n`^hOqEccm`SIhkl5uN{ z$B!So9L@MK95G0zPAf{@|MBoeG!maAd#C#)^TR0S@7pm`EX)Dlr36E%?lQu}F6!YtDQY+9P*?r%x{|_y7*N zS$&#~QQiK11hawZ&w>O)L|B;6yLVp(^y3D{pv5~Yne>^?*#fUG_!S~S{s0L4I*0kV zD2VL?`VQXLK5rDL$u9O49Yw3}!X<$A$`e9I-^%f2hza&@VrhKSeM6u9_R8hDnm}So z#H`bZHUzS(Jey_NfEU~X=xzf~cw2&V%d1U?RryYBuH3c7#{{enMAzc-uNbN62?LD= z1)=vA9@!?6R9>0(`od%Sw{*6Ehk^T_J#MRuI7beXf0@N_9iT^#Pfx#xhyU8LM*#T| zEiHz-`z5qIG1W=or?)8TuLn}ah6Fw3$qg&kS2Oz~56B{5hrn7@{=*(SxF$q^XHk=z zZRJ0vlD?+2#$*%}6d*nt+Y%RjgFh~HA8Gq=yO;Yq*H2df(`gxNf1BZpEqnOl8Zt!p zWwtU5K8x@;8^6xDTHXgjF| zymCk0dl6oP6bBd~GbkrMb$|6wUBLC@fHZ*d;@2m@;kf0kQ*MWS)xdIo{a?W`HVUp`}H zh?8kr+@LLPq}*14e`I9fk*MDdw=M+_^0`mh*_9xbrhOAUX6wM1VfPl2l2YRK)+jT? zuXX_!Cw1B|x$(CymWDNb_SN!)c%#AHDsS)1tn2sP9Ea8ONR*mrR>NKpjAv(O;jB%X zo8SGyh1+(;d%_$BV1j#Q7|_Y3sTu*m37$N8l4~-=pcr9{=1yS|!}+@%@kTQEVf4anUgau6J<6tInb#*l+1%Dh! z)&cV$9#$GHGVzNX`m7I90a*tV zs(q1RVPSzzDc1ueEa3nf3Ur&X0eIN=!g;Sai2MLyfLAEEC(A$L?_FCf)6U^`zRqDx zO6iV-MMS^o2KVu#!8cJUss1-5TUy#HXn@_ZL#q&I;r`PXI5rfC4%*|M!1aN)f1TxP3 z`}fu4|19)RUwMa+TC09tw|U7fV4SR4wGhC0h`DW^0T#!5x>g_&%Yo$qR)mL#*8sBN zRH1kB~On&K+m;ueZ{5p!M&6W!NTUJ~IBRSj?XdxH*;m^`elG z1vu}?F?u`_sJO;0e}D03M`Z|%jHKH)!Gx0G$29CI@E+6gNWZ>iT=8qCY77L|efEBa zD)NqYI9&eYtv6`npN$I%rXaoQyH1N!+5oruOo01oxXSeQiSkl)-I7NmRi80%`fsxI z4_sg---sS$;@;qtHM*Pm69AiaXZKll#sA~U{+@}Xw?1nHpS>*c8QX;1m4p2W0l!4c zo_ixv1qr-Cws6@kC@Wehz`8}1o4noO9=PrMy#=l2WWk`Y2vzl)jQ8%<*UPm`@Idh& zH%^|08QlMId!T(0E3;)F9f6O$AlOK1A#RYn`e_s0qBJ`|sn~b^HX-s#ZD9LumJ&(=-*xJ@s7N2n z)2>iijR}l9P_BIsLVB>MqIRv;_S=A=U$jj5J=M1DAGzLGhA1#J&)|(w&kKT8PaJM=<~=tnD}#W?)78(2d{o!W+P&T^46s>E zrW~;&)514e$~+<%qO9>5YAnvYoWe}u4PvJ!1LIN?4D;%>rWs?!xHSsnXJ8$X_l)cg z`fp&BOB0NeZFF7^jO<3yp05Pc5>>UVV{^1TIgS)}Jj z0}y~@)0fTwRHQ>I`&tz8ManbOD_nn=$8myAlvGQL!H;0evF-Mc!L6f7u&Epy<-hv75v%IRx_=yRX3Qg2}G`yKRd>8TaVmH?i`2yx$$c*5xWeGm*Mu4 zj(#A0#KpsdHjM?6@kHe5HY0{aM=O*4Qhs;iSo1FbJN({+=i0ei2%D9=*g$Oo`TBh# zA_rNoC?LYHSkH?>fGGDT+krD2IQTzLvakrA?V^mw*Q_Rv?0>>=AW0Yi43~&vn#tVY zaXUL|%V`cI6?ylr?RkagAO}E=wilSifs?B0-ta_v)`I`wv{eO?hr}PI4FJQ_4o)t(B4i za|XOMx#~KZozDa}zXE%5ut@M-UCH>?>j9(xOe!7lR9a19u-|!Fa}yaZAvwpx{9t0IZ^?)kPp3 z-_F-u3asm$zcu6*$Ic#uss53v;s&Yz?ei}}!1EUt^r`q+L~qF9jvp8$xAC_Y$3}a@ zGTSYBj7Nbh0o6^)E%co53s$-TEYpGzF{FqNha6a~=_$h`iMeW}CnhnFK00 zt!6&mB0noYi5WQZzrQYLTc@AWv_VnB33-E^1@}9Ib*8aO3ZS>lhLD z%`?$Y)F0EJ?}GP5obTWFD;O!c=N6^#O1bz8J$;%rDij;zaf@<>F&7fZJMCdjE zo^|O{{jU%XJ9`Q4gx8LMa*$|ax;C8mgqk`OLSDG!MZM76W(d1p$SAs{Q8jVTUZ!A(2M|`{)GIXJPn@LF2M8JTi#QO0N@x%2EDz# zFBsF(((uU0Tn7)kLD2`O)zgWWXEZ?YfeL>nUp)l+4T0j7n^11l>en#>1sy2C`B0b? zP=2D>jP84(;sAL$A|k>Xl+LU{io>GUa!)aQDKBOqCm?4+{Kk>*SZZ$-jICD!JsXpV z$>ZqA!55qCosJG=H~%RekVcWTj&~Ls8ymM4A~jh+jTQhqLKKTW`Yx>75Y(+~mU=#c zVo&8x%wI=w!ldSfTtQc&kUwa9o^qsu*NWb^kFu(JmOtWDvO` zs%mQz(JfiA6)nf&fTclGzPkQbicKK5wfjCCIC$4ps+=+i|9ciGckW2f4Y>iX_rdmj zjSVX!<0hzrZ}hfhusJ?5UXkZe73sQeFE}maQTuO{!QTh?#xTh9VsD?V0G_S&ITYmm zH$p(aF>nI9@fqp!R{|WruUV34R_Zhij%X`uSAwT(JMijKaG0t%i*hO(x7;ibFmpd~ zf9v-O+PUjmpKeV<7>ud*A4KT41J7sR$Yem^2l`>gjfh}O3orq;uK&|kFXRRj`gPFV zie3Te|DTwd4gzwG%A?0^uidP;mPdqd0|Jl@GLV5)A{2&Jz(El%r7B_+ez{xUo_Z64 zio!iL>F-UiN*17ex&c60ae%=0K|td$zE&kt6aaKn!$D^rKNOmBo57~Uz_0r(gAI{9 zyb=!5!9E&)K5F?{Cw&uGjX|tb`QesCfr~A0lX&zCf&~CjyHzHNKs=%c`Ax^57czdN z{B4x^@UsBj4b)Aag2FVYOR3vW2&YNKN3okkWSD$^5dl<%dZXO^SGU_K%FdlJeYo9B zF=zP_TtommCR{F#VZ7&iec9QPf0P9Ey&~0aHLevKg}QDgOb95Ab@}5`f!s2)QmX5b zF0xAx>dt|RIvOPK&FcH1A=Mk-FpdUuiRZCT1x!yOkv|>*2_+;kF*q_Z0`(%9TRYdD zosL}BmKx&VIO4B(Et`a@z%qNsL?~PvK~X|VyFp6v%Z%v~hix5DRTc(ffTqhfGGp}-WnEoec6KN0p39wg z7+S|73W|sz-l2=r4nvRpZ_G-RohxJ7ezWROHcg6bFjKj~B&X^vsMM5!<_vZ9SVMnN zZvrH(<%;*luEX#A*^nwyuO)$ga>EB_Yj!+9rUx^%zUd9v+1&*Md_^->KLCr^N-YU`rIvW83&pt5Yzg^l$E11Om-himcRLFp1V}@UVFVJ zwkDX9z8;Bv_KIQ42E@s4#qv6`fPxUb>ITH_5Fn1jYuJiIi^@*?h-J=N=R*pLg7DPQ zxhV3gU@dB9rBIgx1l)0#-Ol;N#T`&Kn%>;ZVRwW55q7^T?crnL(FdxbAo^m@hg<$m zYV75{LX{LJ_;3KM)XQzIszhyJ&u!L6!*i-n+6Iao2^bldwwd(Iy|Vd+T`>npL$XFYD@ul3Rr%!f`2<|8vi5 zrsovU*6TslveTmG9Hq7;l&b7t)I?n+s(B|1Y2rdp>Ug|{oTNA}Wes`>$J? z*xg>ge*N-c(0BeIbw=3pB=RQ{+8fLE4r$cXPsoRE7%lG@v6rTs8$a-58rO#v7s2ot zu8^ey%G=GrJ6w9Vk9T2x>2fq{cBf)vZ(L56(+WTS^CX~G*;-CZOqeT?N3tQs(y&uH zE2d5hPA7a7Qlm~hkVP%gK54#N1{F)WdWhi42ZYYn()>wXP?7?Y;8iV`P*TAg$gw~9R5 zJ*V>Z+d*%}PoRn&ot&_^99e>96{mVL&}LyYluf3gK@+hJ3gZ8AGzA3Tyn)veK`~i( zu_GFYe%yq7cNVB~=helf5<$|{SM36bA~o!qpsmd0Pe=Z@YJ5m&=*-UP;IsX?N7_tu zm-oJ8xVPy8^Z${L&av5@a{#?su;{*(@>T}6ZgUXz^XH#aQl5a`t1JfC*`5Q@yPZc1 z-;D)qhf=kVMyrSpE_9l@rliCig^S?rG~kmB=oTRvnWTz}%EAJ0H&BGn*sBI5X24>6 z03#t``)D~MtopbdkF5efq7q5}?|{=vleTTtg_iU;oz?A}<=Cam6BoD9T#AOC{%bu( z8fc=Cad91>=sQvdr2$P|5;1I_K`&3@fGaAn-%RC#maeX+JUp>r1DS!+rxneN20RF8 zlJF8SI2LvJKl?Enh%)ihC7g9eoi^>_DjZr(Z>o-(2R@sQCN@8~RIg2}Q5H9F`%Jxm zl|6_KFw20N3{{?a|YPpj=N(GFT+Sy!*Db#U1BU|g0<`A5PF{>iT!WX)uJ zI-ri-~_82|gTu=;+zN^Sj6-7FosTC<;FwuIIo6=7eN^0P}$DBih7 zV)Iwq)542uN&|!xD4~W%&)nnT8iL~P;&Kv54Ex>rhOuwQv)S4G+j-EpVvQS-`&6{MjAhx_Zvc?D;!z=zN`MfUu2^7okBZYQmhI*yqONiTB(V6q`CG-daT;TwbYB zR)*+q8>zcy(-ep`Rob@HY4{JP8#Gb=?(R}W_E2T>=bRNrSLbxjH5aK|UZMPKHV~x( zHSgIFqs6*;baW~xLRIqiS6L1QpFAD!dm!S0^OGi1Z|O8ZIW|Gp*63<#I|ASynIRc1 z9Hzs4D3p*rryB=nZ+>BQ6jX#Cdre&gHm7FJyh<3nyh=n$F~H(KlvHyqK-cwJBumO; z1m@TEbsZv`I$Y0WFKoo1)tUv7lQ|b{?uHfvC)WxpCrEp;%Y!)t7|C_b$Y76vq?d+T zycj9MIP)z6%V8ZxzvpU3-Z!{*djkd#$TC8jdJa&On6ZN%7MI6BdtYW^Z%+0`i&0hJ z$~OC<(q!wjI0q=lN8B!?2&9KRtK0X&$Uf=oW@XP;+L#bD6`nfpY_5*w@vPn*`g$BF zLX%^lX&yT8>uN3iFTnoN@sg`xdH&jbE%s?(Adb+2k@U@X((P5eNb9LzoyXb}{3n&% z!JKX*f->nhTkruDY{Aej?z1-E@I+b=i6ut3e?URaUlvAH~o zRNC#ffyq^v^draYdHl6_QJjmVC@vnn!1y&W;GznDgn`ie34zxnx~VD!Pfe`AYSf z?z6VM@)%=6ay{Rg;oS1^<7MkbbN-LFSBiseT0OoSw)mzE&{>_&Kni<0*%ugr`|0b6 zDY8HsdG77#DbtGIg^RsP+qGIN-Ye+YvPb+@9E#kwx2NK7tExUn{7hH#!>} z*4o)6loJeY7xucY8?W%;-F;O+*6NrtvzugXUDjP}R9UK2*rr=^hIambo4A>-4k++| zqCPSog|8Q>)@rwcqAnLGVKxOVNlXpSoUK>vyX=ff-Ap16w8*4=WWDo{dGUAR^yXY= zMTw2UE1f&t?ul)vyY@=z->z&`A0(GP6NC)q6bE#keBxkydcX-BPE)1S{xN)Wmzrvc zDjUnZ*@XM(ZV4%US@-UtV@&0i-!GY&TmKu|z-=k%_e|s1h}GgOANglQju$+|3mt7X zw?&Zkaak1{5~$0$^h8R(7pi3|Y+kpq{@3IUkJjPAEC3u?g_-&7i!7k1C`3Mm+k`AV z=m9b+A4lT1ohjkW%5KbZa2`22++Q!v6W0Y%rc0ca!)X302pVI7?U19v=bpk|t@e)N zQ&5~!0I+ekI?6FVScRqw+nhe$lzVV-<-`i_w|0dlM7%mN2+oIA-i-%!8qAf|eI6eu zcs@t4K5H?R)x7-S=n7W4L9+hY^Jnq|lhQFUz8*NfvAhw}v-K|y8&!o|bCDY}%NB#O z$y-;Ui(I0vTW;UsUYoeq$SLsk2vZJHY3z@Gyqu47%dPz{>!Dsm=j`hJV>XObiXEWmF6dLD}jR`Jgfm0Zr1S>&0X6-V;zSuiWbu z&!+1u*muI;IjkFP1&ch`SQ!a(SBr09B*kG`*?oW?`TXn(Ck!nC=LAhepc@Kwbb0mn ze|RbtCu(fGf>v_8^fUN3AiZP7W^%Q2G9V@7u#u&z282H z66=;*9z&uH$Ur4a3SU4m#cYsO`!hNqY{C&O6e_21r))Xb0?RZJ$)v`cdb2Lhy&fmH zevL4xvVY~pFOm`U{o4Ot#Q|NHeCuW)Nd|d1{7nUr1A<)Oou1wkk)Ve&;AI9HHnx8G zUryCWb@xUw3C^0&MnQ)eWeH~r6qA3F10I9M_%)hn?4RJxZ|d4A!~KGki#F*QDLPJF zXyzP0c3o&gjV1%{hPCocIz{^;GQxhx82&@=y2}BR29_?un<91Jq z{MVz8#EFw5KGTpZYb%5JYMU3?K3Og8v0Lh&Ss%{(@o<{$6zde_b^QC^suYL~k9o;g zyyK5#N-j1vPf=rYuwa#UcQrrx3oY4M*j`}x3#$>FfpkJlTs)&PE+Ik6#%Axi1t{OY zadhM=D=Pzi*v#7Xci>4ac+&wiT&0NwlLHfp!#@Mv1+5@gMF53*>w%J4;?b$QP)$#t zoC^0X+O|)H`niV8dgh+koNvy;Bf_kOD@4~OIW`h=zp3)8wZZIdAEyN6P#5{fC1nyt zRN+WEMUlA(3pKjVZ~BENMpGH5kwj;_?8FymOq>%`dB$dnWE+HGX4@czZEIJvo3Y(n zQ(G6f)u)-{ChouLd@+^Ne-~8lT3cI9C(6Tt;Bz0m1OwXbqnNbo(MpJU9hef`PM%Lx z*u%R|en=Mq4B7DYjbQdzb*!%m={7mcl+~&r+ zkLo@Gc|DT@TkFqu14E~qEH7EM&~nRP;Nl`cRTfiXA5;B}lXav^@?rb*JBTK@mh5td z@Plg~LsjMU=;6#9!qxzp<>ABM6pDN>0`XzYhL@eC+di@2B_HsT5YvMP58yA}obBhh zFN_!_!V^l6xXG!hbpTOJsmS;Ncv}db%^7sY$h?1FOJ+X~&#ry7Et|>g;Vq|e+iIZ2 z1RP`Oit0AzU&k#c(vNm%n5W}0BykTGE5w@xCljbcBF)Knu{__ZCt2Bl9Ph+To8-^k z!iu`I*uwJubm?3ChAujQ-(CFap-Y6|_gwC;H5H^-o?W|S9HG1NGT4C3?Ox!laCoFt zXl(@aoaR`zepgTg5DlrRLKYA}8gkdGHn6fEshIJaG!U(F=C}hIJ3`ewSoJAEDS0Jj z+CIXdMvKF-%$=*>V&-Hw{K4y{wka=-QI=<|?7_&wF$kMVJpmteySN0xy-2lJK0*ug z7ZxlRR;T@~UC%Fd{}sO(-#0>+d3+&JnnsF?eQBKY+Bm&~e(~AVWH`tNi1xl5i#YAv z9X?^@4MD79R#1FSDO;g${^`(3Fu;vzEg+_kP5+Sc$cBlnipV?$angJQMX1ZuGx03@ z5#HoS-D=Cqll4FDXHx+=whiP6731b#Emfu86wj;4yk=zTSq$A^p+}7 zIAt8r=fQzC)3k$buV!!Oa@+?$p4-g|O3~1{;ur|v@Y_zeT}H_z2DeTkTiAa(%Ft>N zi3kT%TIHgho@<}!At0*4^rXzpUK-Cl!moC}S03oweyMNEZk^B-_8A{$5?hPXV|6E! z2({|cTKlJgF9KIZr$>o%=<#un!ERI}j*vae&;yPQ?7;GvfG|eyNKQ2yfkKkIedKKJ zTv?YSC^g9YI*e<1-LE54lU?i-70oXlh#Q(17AM7LLFugL1*Jb^s_(1Pm$=}yiAB-F zY-I2sd5icn!56Da3li%zgyArD%zV5_ug~VI1p3>0~>)N5L zv(>MBN%>;bn8VQqR%y$kdWd}l8=2}>MnD}*eEB1?rki(>5Hqmig8v8Mz`vr-r*TqB z+h}KJ_DnC5Hm8!?MWM;o?8@IG8d|#LUWOTzZ-q$WEUO*cI!gm&O7}Ss` z*NL~ofrM##Co*}CK8<36f!@31duJ1b%AM~#%m^3PDll_>YeTrF5(hK!Jv7zfBIk=W zk-!~0dhaoJCe0zSz#r)e*7-S`%oY0ll^c6hR=<1}W6E`3Gn#RQEygx`l9FLLig;;w z9T{V(hg7%eMqYYIe?Z=#LpAWhsYfkA0q1#n=?%RSso>paq zL`=_)K#?>Dj>7UE7;<4)6nj43cuNf#yxH>0DY;P5-K_JGNIUFPgEmo=LePxF-Ef>v z2R#ZN=0?XllVdmrmX{APA~blgf7e>nhKfdgH>dqXIyluCoUzL{c^D}NRd=$FN#g>9m3>ZF?*bv};-zUEO6dB`3Ug0x)_}bH3wrx}Acmx$ z?hHGO-_!&?Q17!kT zlLJf#vP*V}1dErUW(6|=s~tH!<2rWe#U}1jxLhL2V>1)vA{E+F2br9q#TSTp<{pEJ z^;n52tOep-ps_JdWt0WlCv`bJ#bd^?Veb3X8A~Iwc!q}+LZJVqTV!UodE(%d8Pf}N zlN#I|cV@e{(XQJ)Lls_vma*zw-=YP&dJOhgbq)s^wSsfk38PLR_~hOJi5?ok(ds7M zLxreX`*%w1t%{_avt{1x%*1aPMD_#EugmB;q6GAAf+-^dFEplp*;_it`+QY<@4k3( zv~`)VMMGvyJ+<_kO#zVg#DRt}t|}_OI)TRB$-i9I!*O^RY6FVfw7NFhIytvp-Ntp(9NE@L|7Q-n$7VmcZo>h5= zzY6^zi+$)+xVQxP3=*I)z|t-SnlPsdPrhpZg$4KFXO-VJf9vJxu>W zSYlc`mF=IVFBIYvj;?jF9e2v8v`28KIVupM<6Jt;`)d*7{!hdW)jvfh&0*xsm+FuW zb(@{oS7pmg+AklDLy#`?Ifl09389qMZgEmarnw_`HmmuA8;t{cAC<*h5&JgEPTq_f%bIFS_|kZ;^DUytGLje%BjgN@`V15d!>^6X`d03n z1b?xPxm+eEvPiG4o&keXLSCuJi< z#(!TPovA=ObN%nWIxs&v-dudUP9~zHF1i236lbUsW4XN}%a2!g?YDx=*7woBCD~=! zux#bUA+TtR&HW`pJJ8>H+{|tkb^M-@n?1WZK)^iZa&`B}sKJd_uXf6nY}CN6D}MLK z2;WXMb&vI{{rJnB$PRXsg2bF^X!*~4odT}cmS4GgFGVUVr}JxK$Ba|xeQ-|ele4mO zlTp}tK@moJZUs^?T*y=CS6!1jq!mw#go{6lG#ljnlpfPGplRQ9V#d; z$kJ1K9_@880Ih)-^y&TN*Q^VqpwqsRkal^c(ni+Ts}dG3qK4e>aJnGc3TBi9{#IoS$8W5fa|q47hp@QYO8GOTEK=rCqZ&u=CB?no zmKEbnXsg^k0U|dyl;R6hzzneQ&r%L{w*9KRqXNRbD7ALznHD&p2nDDWh4L?1DOUbs zDAMFRy7Mbu*guwbEsF3u22Jsc#2}vSnsg9MbLaA?C!De9aY z03;Cl{h+kH>--|HqK*&x=p{)tkxuqHkQitTgUgVm3&cD3Yl@;HBg>FwgeYBXY4ptV zfXj)479fD@31tT2=be4p5`;>uBR^r;V^vk9Mb30J{FAX2PHYRY^2`6xua$iU76v3h zh7)%oWe+v+pq*k;b>X4R%4(m|mQt0_#9mERQWdwQWn@ot7&L<*Y4Bb)rw=v8kx%|e z9O;>9Ztg6KrIh6%LXmLpIV&%g+CI~)w$(loDyVC3oOvGxQY&i$&`MdmHfp~;x0U8| zj{tQl$Q!NU5og0no7#)gARPA!mQTvTYJ$O~CzU&W1}D`V!J9)sU9N%3gct=8x!dQA ztglT@JzB;-bhPTZcnXCcC0?4_Wo6R4IU`|b`q66oc{mXsD7n36azO-zL%K`I({YF} zm%Pj`|I&)^#JZp|gUER&Ng(sMdb4?IYexM{)||}dY%~V_v!Qc9p0K~TgQUR%+pg*B zTw8<9JpK(jK)+V8e?~jB`HMTs0$ob9k=+j;l0bx^rylfociwI@|U z(Uy{tk?6?c*)R@5RqGlLJiCA>6?kei-l--~HK!Q0ub7b$Dv&fyvr|)9nSAPMIYkL2SvtgtCM_bL zG_uuau$S3AIooHzSrY94n`1YqXK}ta&`rVuyb5BnNm&v)AG! zg?;~Tj6za_4PAQ&zkz{L1>rKTzkLG3n3eKbeRoUud7gE!@wjcMz2Ar3!(AozJtnEO ztRJw5wfNE6$~~!L9$vJ^r?d?u@D}1F_uQ6cZw^+T6ZK;hy-ZJgMo;QZ&%T18T1V#* z(1jSKnOGWj%3#*Dw|~04JDPI_gV8^HKEQ?zDeh*!6v&L%vE!_8=J0M-RUe?JSaaOk zVJ5|Q$fwrT+I&Z}hu)6`?c~yNj*-+{;b4kAUius44^!SpHcd1$N0MV41k#ae4Pla_ z=Fv9ua24>xc{X5HU5y5;L&kv`I@LX~$80VxTzclkjSVm3USi9W^;BZ#5m<0I!jBs`a*`4ARGY7+S%HnCkisd8xvR!~)aR2qE$ z87=qm$rst*Q}<)k?gTP=E=d`nX7A?e9BOMEX;Yc>T7M+O>zK+GO%m@jo{a2zXVgA3 zCS&QqV^cM>7PgG1Wh)QM&Lo;#Mz?b>h?bE=%Q9?O_O|kxo_%X^ zKIKJl-swtuPBs8F$4z(gMZoi|&-O7W0E<;n`~ZD8ib8RKAc8r*-&eLC|3ZFNB3iUg zdS30pLpIg&G$|kd;(G%ZdvzI=^YixP)4T}fqExG)9%mDi zYY;O2Gl18@(3x<+lV5Hci#6x>s{NC}kaSjHCU|*?GCPDD%RsT;Kh!E_`TN89kO zKFp@-a&yRWth;Kko^H5cIL^Mt5Eq1K289yGH+no!w%k@>gGamp>@vc?9(;|j@j6^I zORG1s6zNvl*d!APsi6rZmye1C?_k|~sAR~XL9zAC@asI0FPFOQ<_ia{@YTUO`Ls3l zt*(EU&7AH=6AC0eZa&XTVk~+vNpU30RptEr;}R=f7c>30gi6mvd?I#>=GCE&5;@Ju zIes~`_N-vu)<3?vh^ihq6G=!jrzIlxTj*Ci@E_nlgpT@+B&v4M3YaafhA;Qy>@ECr z%K~nA*MgCAq-MjE2xWeqJq?vy;{2QnTEHc%T7rOi!B|N0(e{`8>hxQO5>%V&&T&}w zQ&!BQHRBc~qwHqBhRYFStBWIjh@5772ZWu`nW=5g>1$gu24gHJ1Q-&woYNWM=QNoM7(I~zB?*T3CU z^tCUMjgyLkor0ves61x3WLB=AtS#IksxxZ*wG4+u8J1la>k#7MdBv&u{$t8i_U|)e zp^Ixl8;8p3lAVeg#^!!S_7BFH8`fAKF~I-58dwuN6^{M+se&+?%F8EuF^_xS9p{rI z0}GN@B&V-7lkU0O1-mO1XcXHsBkR%x%+%4Vb|t6g$<)KV)2R?e%jv_hBfqE_2FjVk zq@koDm~W-r^ETfS?&zu0bpa(#z8%4NgIb=6M}LsUxjU<>{l2h7Z9hqIF|Gb&Ie|KD z2zu=N&+^XBnNn%lKI;48SINk+qq6{sW^wgPC^REyIU*xGGD_}Lb-P zW7(6s;W#!MBSFV}P_o=9>UaotJW0wY7)`|KF7LXz;F}Y{PS$b$jH1OK61@H>mqE)N ztzDas(_vmagJwDR5{Vp2?&il%;0NQ_&urhjpYiwDa5mH9 zkkNNm4G1(YChz?Qb^G#-1z}ZYHMNoUQIavf(o8%nU;LewPN`j>oO|xL3{JHx#=Lz^ zo1N$9qgY-hQ#r~Ol?3E0CA%tolW|xJ>!{m`f_|~dBfrc!xif)PWGhA?gPfk?!FUPE zS9Hu+LZ0=`XjS~?joO2~iZc?YVvE4_4>fyONINVShFFtUfeMh^XtSMQ29)GPsWH`rAI|%~?>i9Dxrqlqg80Y4%F}NG7oUv44j;GTrCCL--GidLJ zdU`Exe#?DXx=T~yjJqkbScM4H^lne^OTYm=2hs9j4aJGt1BAH?G?o#sKhP8?E5@!q zPD&VfkN{pL^8Zlt4N+7RrGijngpaeFVoEaBQp<4P?YOyr zO=_7-{YZX3p7h{ouxKfEM@!C}^|ExLrqVz{IF7eI^Kf#?c(5>&%CB?Oo{?=V?(o8- z^KKSpLJL!e%Jq zZ}d-RTr>qmdj$}e8=V%Y!+vFHby~1K8!h(0ZhGozDhwe4dOPKP>9|zoF_J7LdPAJb zcvFtYWixmg8C(TeQ+1Ig17Ga}rGHiSt0|VPK>cgl;torl9h9h>=*ha zGX4EiND_Ihob4Jj#aeP9a&8*EsH8S9!@wIMsXrsv&Z;9W0!R*g>Bv+z>1( z1|GyyGW{&o~>__LlJ=haE+W zk{X6SWfNV0wsV(JpFbeQS=JD_{l7Jui+ zp%1i&xT^T|RoEg?dLd;p6dXL`(+N5mNJpiDmBCaZfku{w78rwy`x*3z%y4vj=WHTQ zy(+ar6tXWarwkp{Zp+GbMERuan2Gu zV`neoBTAnB%v9F2WMK2=IiSgnnkPT1VEGZ4&=acWIFwQFY7%@dX|^xPNQW8#TfLOE zGigrcFY7Z{YBo(k!1HVPLgNP>e0C_tnyQa1c{5e> zCPxI+%MVmo(Lg@jYTxi6r)-0l8aae}Ag-RU{~VDi zpHgj{Bx-cU@}uV!1?iR~-u>I~u9KyS7jd8|DM>@!c01GB7p~R4iJkfMV56@r6HwmY ze2@CaIa~X3U}RsYgife;tP z0lsYQ+JwJg5?E7$%E=?=6?2_E7jG?vRZ;YHBGuXlgw3*B=sPvI&P z)~6eeX@yU*gzI~H#^J2KS5V+;w49)-4;}@v%?dr`{P?gb)0V!&<^8Bbi_$ad3|f}X zlh_fv^QO-UgeSFX($-^#Tjy`KR>cJ^bgDO_MsW#>8p&sPQ60OT zQbuUer$Kn&0E%!1Ke*y|x3HlkuCc30bM!sGO|snINP^c>WPiSlM=|MzMpbZq{~x8D zbySqy+wVaTR7w;?T0q61Q(6VV1QqE9Y3Uql2nj_%luiRdQo1FjJBMzD?(TElKF{y0 z_q^+zv({P1Kac@t=AOOxz4x`ReSJUQqG-}=4i+kRA5yeafq)F2^PirijQHa(S|3*! zd3HF99fFIzeM0lwJlcMF#|1@jUJ!-Z-om1SvrY1qj7^S%OhS*sJ4c^xV=jIC%{^N6 z!?zIhbHlmCxIWf)#~B+%;?Vj)C9D67{+45(I2G5G{BWUAULDKyg{U;Zn@nVpVktKk z3~cx;$MYpALP91NmL6aXzJ`AH$l5Z+a30-y;do|b9-ljQJj^1^IXw3&<4Dn&MK`Rt z8bki2$y|YBoY5h@j0ca(h>9hie=li%r@UORljEPna&9?JV^Vd~xfJrr_ZV$XMoJ7k z$|su(1d01fI$<;&-?pI;EabK=?1*VZWsG-t!IJqf{kiJ$Reg+3&b?-=*J3>z{uh;_ z;!W{^E7yetD6~ohn#FJXk9x!(zcJ^BG$}v-;qD!%DqKE1OXHB2NRUc5aIU=UjlfXW zL3E2fhtqQwcjlSNg_0JryE4b;NCsig7Sjj;(PH4GBc0t{d518LJ7-K;qdhonzVDTA zyJZ&Hb8hRdc8)qA>tLw8AtjGP*FEf;*4GVi)8CE(!OIE%lrr%Nkcepc z{GX+!K9cPKCsD#}qWkzgPv81yp-`IzHp?){r`a$Awb+d@zA%PSaY6_hU#x4rE9at)=Su!Us!p^mR z)FN<|UI^cVyxpykdN)nec^TACQc{6%Kpnk3qhwB%Wi2Nli&r(jA2s+Omvm+#jN}Yy zI}v`xke)f_l#R3R7oQ%R*7)Od{-XjS8Unuyomy4orxrcDEh7_ z%tOAj(eluycvH-VDLWPhZ~xC5UTqm3!$g%$gsLQbCDsBfsj_K?_n;Z3h_i{FM3(m~ zUf5pf!ffTi!{}l+`@==exV${6 zUV9s|-vW|j0}dMKvQ3KJpNzI;^cgP0TQjN2>)TZp7FF-9u(m_+7ZY_`vW4~B(S{X& z#w{DV+7F7DyOjdk&ZD+|2!Mp%_LB`v0R&md)g);_uG0QYHw%KTV@3wRF#f) z9K^97WO1SR&JZw=d=R`^V`)}rVzmC^6WPhq8v%-<1uBf4Z1e_mGy1goF^#G^Hp<2^ zrHW0NhafD_yVJ$U^@q@@%RL?QjS1H+74M?5ida?mI>^eeoFOhK&feHq`i&jPbjIF& zMF^^uWC2j4bHv^dvB5q?2rht&DLhy%K|x8h+#SHoQ~~j+5qKzPh=}w6k^(TWQwWI! zAb<}*7OSbL36wE9G}>o5eRg%rry>RQG^y)L;i1t(QI5-TmU~8b+1P|Q z_`;&@@rWIq33{qo-6|>LIF)@VgPweoh=;b+#bLANl`n1TG2KCLM9UN5p|o}f@p+$n zqlRA(jxsl0mG?7>lCAuYE!RG`-{_w|Hyw1jcI9ho=^wgEc21$?;z=)+vmuNQhxdOu zgvA#pu1Xn=&`#{%pY%7W)r?Ye^W?wS9Bkn&9{iYtb`2^^z5wj(5J*d)FZu|@#DCsh zeDv_)&(anEC{_bj0R?)72#_+3x*f28W|d0>>J(5F)}VsB3*b(`fdkfM<=_Fu0gCPi z2!E2z8gIoMPDk6h6fws##p*fE73c3dmRORpBwZ9QCbsTsk>+%}r?AsUslR&9!X_xO z;|bFj%^op(GldwUrrIi`;HJRf_xLAPD6>~oQgohXbl;r*7_6J2-_q~OH%3pQLwSvA zdskB&TV^1Bj5RD_?86Im6R%rvJ=JWNFgSxOy23A=asF((V_lo2X-QN)O41EE8a*6} zCGYwb8EV;CNV4d1KaoB}FcW~~Y>DE>)BX?QZA{Q^{uPi7gm8R_sjCoFm(JzpD1LuH zQgy(`#i^>w{V6Xsh2C>?URz;W^2?yApe=theOHrvWoYQ#6*QF{%htLloUKF3`B3TW z=mvb!^53`zn99|&=Uf$PB>L#qW}P?_T=4ymiQD$!Zaqd`t)c9U|bl{?w zrg;>=B}qvJ?@ulpRAe8V99y-1T`K$~mp8uUJ-^2la;a+hL8h6&n|Kn5qZ(1HAFRgF zJKhH2_hZ{rBuqvVNqF40fPG2q*qAnS zU0=375tQ*Dk{Uq$td3WsKp`V1{1>e$V$X&X85x0};d6g9ZK06(GmT&NX~78BNFo%N1dSQH2381EymyRPBgAfHyH2sdMxkU>x{)R zxD$=KuVJD&dpS`TR5dej9P{62GwFF#uLqv~{q4<0gq#MiEo6=VT#d%PaieO$DOL3$ zi%m&rYk}kgp+yapEuSSRn5CDhE zu;N9mCoK=HHCX$U7WnO0%r!r-+Dbi^x<}Gt9$YSJSk~uX;y&8)WQ1GmF4T*Pr2cRN9z`!5gB(%MJE|2_We z{d7I1?F0Ps9K)dn^fY$d5>6-m#1$ggNT$_3zbki@W2kYWcRc#yun%n&qP7I$A}1JR5Z6$lJ%NsaA4|I6_`vgC~%n zbQ&9d!C5ISlNd^t7sWA6~d{gb0vL2GW?iY9KN|Kuy_hn4{_RSMv)0Q7^{X%#vkjLeAT-64A zFg27hK^Y-4A799$&({?My!L>`=LooADCHyuupRp3pjqA>iEiA&)n3*9Y?D{cp5&4v zHmY$A7x=Zm#31m@_mN=LG-tGFc&m5U*~tudsA=8gv7va82IF^YG~(a}!vL`k`xlH} z`?k-#R;q%=VJML zDNWmx`RJ52#g(06P)C`|^M||QbTRsxj(C#_Drh{j9*>djyVFC5E1JnLUlWC!Ic%AE zpsF#vXCpk`9`;>cAUyiSg3KJJ+L+-NW^-pQiu)1v#;a$?Zl<1xN13k6D*?KJuOl&n zZ%lnE3d;;Ge&c;Me0Z#*ymxa*=!vt!dnDd?X(|*;@T+y8S)|-N$sv`X)K#8!eqUjH z_8Hc|rY%jDWh_OoZCSj(q~(Bbj#Lo+gPg))+O{f;+Muq-HI=C_xPPF0^30C9o+w^RPoQ(|oVAH@#y&r zQhk|bE=Bt(beVX~OsD)XcJ~*NTvZw7gjz&Ra3Tm67Xg*WwLH=uql-lzk}qPGmK%(5>+6 z2I2AG+4%xbk;HfuzQwd5*Ani(d)^qW6knZ+K&=+?3NimL=7mD%};S8qByax^K?7pmP2+j5(m9Pd&PPML~qW#pl^1aO)wBC-Ixt&FEYTice+#%z`0pK ziK<4d-{41Ha|?rQ#35J042J>5Od`Weh) z6UoE79*VfUT~XBMGHcNU^=v73nq-e4w&;1ur7BNMb8;E0cV-uU?q|>b6BqI0vTd9; zvl}c_8Q+@eTr+NX8HB?g%unqFz!HKVJ7))49~pU#?Er8-};NY;jgD- zt#QxTGoAxo*%MCZe-Gbce%ZuFnp%z7(UdBg)s~i1Zh%^H%gPm8CscI>T2fQ^(Ej~( zPAJD_=l!~pbIw&JG(?HZ2C~STd*?o#>=B{&?CE`po}hH^-o7N>6CKY`7SS|OjWVv4 z?)@>Ns*&O6*KLVF29kfgZ@T4Z+h~&bYp`vJs%E`8^sJ+^##l%d=ZbqvSIdj?kF{94 z(}ZxWYok>tV%S^utTG6;QMc_4H(FAN-PB8hhQ9HDJcXywl@DY8A@N!6PwCI-xf}lKLbaJ8}fuA+R#{K1vS$PJRU)s}PG zZI0Z=BuVQ$g@Gpv4P+N?7xP^TS6H=~$1PI}tt@4a1mN2Q3%xpqJF1fYo1bOO=x-#?^LaXt63hKa|bv$JUXyxFXY&f4=KIS_e-BK%4aIGWD>i358m%q6% zuW)+lRxcm3lw4Vd30oSr{>Ykw+q@B3ZW5=jP4n6A+St|I0G-UU1)soMLTw(Ux&*(A z+zIZvxd;~5c|U6a&~Olx^)NFVnn9x%ptED3f}oVYl;!9mZQOy^WrD-q%Y1K$9yz>n z4K~+q@^C3riLC7Ipx`6c>I&QEwUml1+YYyf& zGHSsv7eFQwAy(gWj|&&ND3EiS!!arIB?eQwN9N<&n%toEnvM>oP5}JLU{h@k`@D@= z(&hac8PLV=zbFh(w3s^D6LFlu$`YHXop$Dea=N!I3=xIz4U^2T zu$1^EaaaU|6G>+cY3Mu>k}&IQD@f(pH5+7#A;=9niv@zRrNY6D`FIPKn2k;46GgUu zR76sl=99r$Z5r?1Dpwvn7Ks75rt+cAa zVlZbHBwf6im873(o)J#ChzJoXyn!5+nh8MS@S0GI{duT3 zuR~y{^~P|Z?KnO!1(cK3&JWLkz@oG0*9y7FyyDzjhL;Hdd$qQdLY$c151Pocq-YV0 zEuWy0oXN{JGigy;@80q0g+Xqos>hnKd65!iAE2VXAm=)}?-8nIQ_in_#Fv@*@7pj! z*zf_eior~{qT>1_nDP=oD+k-Ph?_p}VV-KlR>DB(bIQbFw4nX1=53>qWW-@cxtz}u zqm=7ERj?F*LXVJgm}tgBW)y@#1zB%qbj*(&Z`SC`7V{HL*O(3%5fPIoZ*?Qc#nypO z^eP_?*-lF^T8I~kMGACODu&y(zJGihxHNUen{)=|eQlkwzTCtQO3QODQm(H= zz1Hs;cILPz8o+T&XnZ5~v27`yjrHK+O+E8vsTIX>cw1GO$4yWzS6BQ&z1MImOPnP< zop8g7;iw6d>!txWLkmCsH)A?QUKy?ehWeS50;3o%)YK>W!9Q;ThDUF=@7kSH zi!MU*%%HRStnj?5iC184`n@g4tsJq9_yku?_LKY^uOkCH`6c1T`y#y|Yk{S<8E6zs zz3^Jaa48smw1GaQB-BM|P4)WD2KV&qQyFJv28{^KzI#3TK$>V~%LQ`=136A2o7^O# zNpd_1gJLWwmr>RotUTrOyZkbYBY9~%3FBMq>l(f&Y{?d=W#v{BNgUlQqiJZjA4ti{ zAaKnTb$GL#0Idd?Sw!1e17!~K((=!TYN^-y{KlS%6N(CN3Y7GwJMh26FeL*ceSnU{ z(d?VoJIh^^RJ{mgHJ77Nr-_?#NqEEe;?H!nCU%c{OyqjW%^lI?Fe||iyGkpQOESU~ z?(EriaA=;Oi1cN>I>KwY=RX;kmjuFYSp6@p{t0kI_XZ0VB7vuCNBT@uyONN|NJOAT?T5 zJNp9!$FQ^BJlA}7xB6hQjU8LVD8Hw(B(7UMzdAG~#bGyj6N&^4q2^9XN*!R#BXKza z7`G9q^Whr#{ezbj9lzm}HpHTzHfkC;K_8u6bbI09^xDs{$@`j5xy-(K8lQjloAzf( zPTri5`pGgghcR_4VS)X2A9<@Dko^z^Hz_upYdkI^*Z-_g(gEj?lb>Nyh9S`T2=a~V zd6ll8r@Sy0rTaiC#RJ)A6%Ju;ccSJO^8R=et~by(ND;*Eowl{tG1jkFL+9=_##NX5 zmd<{}8IUII5~z(y>A&81Px;IJ5ym~EaoOWF$y;q2p%qJFQK}k&O;dC?^855FP+0u}BoLww5svYzp)MB+6y((H-xVJe>2VgzWF$RN(6g zmKI|NhzoAxjTCRH_pY>D6D#?-?iO$#PgePJ_+`qcM#BT#3Rx-CK9$4qiJ969Ol3tY z-)M@aYZ)6jIVRx-%(g;{GmeHmZM(F^xy#)}$~eBaBDmUA>jg&^Q;bRlUrlo|Z~au1 zO4vu{n}>P*g`7bm;wrK*9EYQPgNp@&KE#YlYJ#vJ6t|5S6{woSkX}s3!KU9HO>|~; z3wuE5bYXTz$QeU_lYJ&XC_KwVj&vmmgm=4sw_Fe7<;hlI@&)RN6)Z8wqBk_V-aSaD zMV9$slRVA>Kal-SJij;B@p0x$OGj|&nEQs>3G0l(Tp$|=IL<0L_+cd^2c7>ol}}`! zgT>SP!64aMZvcH!wnoU4R{2+|m7v0NL?7E9x|Slb6D(Q@iYvi4nEAbs{(Q*3iRDy7 z9fh-leu-Z2Dt~ry3=tx&8{t$$+5lDqXCK=@t39Ct!%M3>$+XIaOXtnL(U&?tQxoPp zXSIiVAk~V2C`ge5*a40|4-WoxfbP6acDN$n>$GCH&B(170!aR~fZl5zc1o$&HgWkZ z&ewyiX1rX`eo9;OET(LO776ZzWFDtZ9|BhK5i-{QNFvJz#6OT3MrvlQMIL&8!E)C`eX@iD#LWVV5#F}wg@7lr_ z4W?>Z9DiC6r9L?YRMg6l7sDw1ha&b2x276TIHtT;2t%y9HZQ#);2Fnd$ zzi5JCoS)+rWSS0Et-vhTpe+{h2}JK0Q|eQKrc*eb47)P6rIl~#nshmiF=kfr>xv_j zoy#63&unkGj6v$oA;M)Vz>u5|tO)9}+ECw{MqXEm65*f0u&73&G%emu~+y=qHIi(=lTUlyk^-a6g}PW=n@Y(-{*Jese@qK-xA)A3miu z^eH0S)IW)=YfC0f15Gvl-yKr2UEFV;V9@W13hVO|ZuqBj5V|vBmM7o+>TT!E5Qi1= z?XTYkWm3kVUqSoWYp>UvcW-TAuNwbaemaE8p5b=RdfF(XffLT&hwKs zLuBc|`q8X`g=mH3XT=U!Eo(;xs6i(CWFh&SMzr_Zq}T7=rZ2s0193ITMF9f)<;#q@ zcxGLsbO+l0Cme9X{8n!NqI7RF=ly$I@kAU z&(UjG?jF2yCh1|~x#R9&zTBMTU|(r`8PVJU@8GJKT9?Fwg#A8ZvVP0!|G`TDgC+UJ zx_?vQM7no~(w)fT=bZQFcNLpZn8X>&4Z(2Id_7DSV;VBDWJ6kB~Pn$r*%KkRSMU1=*yLmQ%hhnMQuX&dXG(NK+KyRCTpXfWyZ0Wh61{(j#3* zKAsWxOeI&$AAMXH-1=<3KNvMKg3>n{CEB9`~U8r$Z^Lkb#CH~#>mlY ziHu6Lf4*Cu;*54gn{!K!YCSc7L49#$PWpbx_eO@2{5~j0OA+f&d)%Zmz5J%vVCto+ zdEhx|f&-<%Gxl%Pg9JKA4;T5-YQ*G1f??@v(Ly%Y$;39#BSJgZonZt<#YzWAk#TSe z(XV+=iO3>R>#qSNb316IKgaj&TYMz%&wxH$oT_5)53T_Yz<3mC$DyIJ?=4hw zn&$~Dk`&SJ}ssR5+InPs3EF%agw3(F1s}at?l~# z{D9!O@jwQw9n1u1t=oknzGs{4H`XjfaQ!TIJFGISxV^7dX{D3fEwxSbr0g?#Nn6P$m?Az?wEOc)%e%6a4jC z=ecFNf*3pMqEcrYRu1$2iU&Q7k-Lu09Rk-Q^0_OA2E;D8OP;>QYI{DmR5ZZK-yXLe z#9x5{_h-8k7#gy^+8R-K7KD3__22qsneCz^fNVA4Oci2?xBgMSH=p{eSvF57mUux zTpro9pW*w!c}lr~@{5EL2egyY^`T()UW*{Z)bzG>3` zpJWP!$N2CM@tc#_$f|rqpXijZcg9- zuj*mMaiDB}{&t+p`Xew@SzTYR8Xb*40Jpcd2SLD7{OdDxUm9kMWMNlT8B2$@M3+KK zRw{n7$#sEXv}1hsIaac#$~A}Vk%tHS_Ugk-`(!IDz1hyr!4QT5Hxt%!+-A~Wh)6uV z8}BfC4M*$O(>l0^%v-7p*~DYY*2txNyGPisBB$z5O@y@eVR|G*xRBNEAbbwb<9Fnn zCLK6H_s~jzIP)7dNWHgr4v_Z1ZLw1C=eST(u&om^Ka-si2h?`NuL2b8fOUKZ20It8 zKfS`uowY8YSNlN+z>bJ_7oxkh0N1da@`*94caUE6@bH+Qzsbz3>j8{s$q}_b8Is;l z(LbrUw`9wAG`+jVf*VpJ^9?xL$YgEjq*q_Mg0V_kUn~;baXC-kv!}a-j|4o>Lr^e& z4>n;zj4h4zH+6e`j+zH7-StaI<;VGqW>=HYy7+Ksbp9~DA)a)`cA8QaHfBK%Zo{=< zc&GW!k!W|0kRtuz za%GA_Du9^~E_`T%BwH z#x_K^LgxYP?%q#JhD5vxi^3nexG)6UW@dr-+aFTp+$~zj_{ z_vL}3wtk-}Exk+c!cL5=mzDs7cJr@6(0odIU6EK`?hlDB;qRbOP38$ZjfjMipivmf z0adOmA~P`oMsq&TBh-o%T-OrQsw>~5V95=oVA4!VXlru`5V!SubwYmO3l=}OT~{avdmI3j%TkHo5%^Q92UpIcIP=1fkYScVV5;q zj4rF&RAm=Z{au5Lw4pql*v*-#U*<6qoK$%oqMTb5k@zUOSO6Q3$+aq>+R_cs>$)1` zUD0DKbeTZv^g-9mY;gsw7i?;iVM^+?Lr_$fH;z+oF8)x*__T+cJ%?G3`|&%Hx#1LC z@G0q0Y{MSyl?qyjKv&cZ8cgoDc6=x<6w2Dli_iPVLX$lC0_fOycbB|vjcFRMvD2THoB7hfpWJF0WLuV)kRY!)KGkUd0vU^tFAeLx z#{ZAw#jD77P1~z87QMJ!na?DTo%Lk$lEQNok+!B+Is9Z|e|9)t=|c+vJ*_u%1%7yq zOgpn^=40ug0z(F~*6d0;JA6Nq)N1!XKFGkRlV&pC^QoyU)fHDQ{LC4)ms zeBPVtYtK2Bz}nKJwbYBzY;Wg?bqzUvgW+*>u~|08N`c~5s$^^MOL2|dXt_&ES7#nl z4@Y?;(-kyVd94fC%YOm!f0mZo*bTO?^Wq=pFP#TKzvtni`cMk)(F99jt^(fu`Ix@F z?A)P-&R7GRFlbh2U3{1Z;l(;7zB0jj;g>QV-9i->!fVyfAg-M0g@?M98$fDcyMhIn z(`*<^SX^RS)gybIo4!FI)`giNi&Z?NRAH8of-M+)FNy3>AcY$ORb6b50D+l+$GPhs zDP@F529z^x`UhQM?u&oW=sF z5$ly}E!0Cy^C1VOjSVn6KyHY)g8t^Tr4BV5B)nG8>w|mw==mW;onfO&!&wxUcqU*6hxROS_DeS`v$e%p`S zHU&^=M!JRPT9jibZ$8(HFT-yx^CA?s=Y8R7&BsF%jpPM-jCES#mlgp}o#a9X-Ly5o z`-&j9U2lBpRXAQt8*UlD1mEp{EFv6lRC6g8Z*b{h&GjmKCGqzLi_)Fh95(&z_5`SB zz9p1;;uT$kG`y~sIk&Toe_yzKbJ-B{Hp5YjYrSTdUjh!lN&tQbb7xI zj+=H=1OD;om;qxT$VXg;fs(}`7LKei5n2Un<5l!SeLuK&HchbW1cI>qkWPhXawhqK zJbF=rqj{-`-M~VY8&dhQ#afo`WRSsxkiQ+my%+Eu0bx5=Uwr0w7Ax39_lOmqL()R< z&(RM;s#51ChWYf(Gs9XAtNjzhE?KVy;S32Y7tWWY;#C30Pe4zgkXcu=- zzyN(SCl(#vdV0Sf3{O~juDSyUGq@60hVwwlO#{+Evh zbE_J@BGr5`@u=oZme0Zb_{srQ5x80Ab;WK_unm#;a&c> zj-h`S4fqWIPyWgOe=nBvuYJHzt#WZNX+S*hfb9)TOKm%9YdSI37R|)52n!dlJ9I+8D2E!Aa1y&dvkXrI zC%Iek{@|Yk#=n-02lF%4Etjn;f$0Vqu_ z_ z`!+AQw87@3L0+8EXRWS$aB3)aesA|+^u!!-{x&Qf?Js5cr=c8!#P@%$K`~_fdW0K{ zIq8W`MZ!@bIu@JU*`PPL@Xy z&`|7;n2Z8E9}HX#?Nk^nwio*mqs;5iqLeirr(3VpP+g>6{{VNq%>_&lSaT`L{Ox#|lj9@s^29-27^t$hAE$=OZn?w+N9ww!i`oDIU!0_3C13a zO3%~K|Lxx%_{%e3V7ACo({T4orJ$g&Jleu+)Y4jvS>BPo(+i|x`<0Pr+S*r;da5YX z3>_HumlRY**whO@0=1u%LG&RsmeFuAKUhL%_2~DQAY9yNfdJrS&n4*XQ)fXjBe?gf zX!zhDaB2AT2+}%9G-K4P2eAS~2)305Icv?lZL58HL2JM@SJO~T7qpuA!yC9g2Q!k< zpI_&o1n<8(cy)~+g|S0J>fkJzlGi$rke2oVW{0?Fi?YatjFRPqNx04b+RKvANP*=t zOc^Q5Jf@*~5*LANt?s;(2XL{)gh}+K%~b_cFqQ;AWMuLD95`o~un#A!uVgJo3M?4m zk6DMMC0Kh*f%|_5-mTy>eVlvmFvzXoQ4jn**mTiya&j)i9WQ?@vM}@ADKtEMqeXC( z3yd+lMx-TR?ydZF?kX#54tSQ@FAqHeW;gVn?&?@2P~PBc=r9J^?1KU0cLy7dKU~CM zn9YGWF>iLr$f2T-4tA6>veY3}B%36EZ^-)`5m7^1+pj|>;GMJD65?$bPJvlOH5V~B zvER3}w4BZrvVEAVgJqfA-inLBueyYJsQlvu7sn_V$A5VTUxvC~UQL&^2XHNu(52jP!Eb=|HqB%x_kst~=DoWensR>p^k&P~#^t&3pGez>3^tYHI40W)d_C zFHo(&16Li)mIZ<0765Rt_B*z-A3KuTP6}-51TIwFrMPS7`Z4mO*@WMjS)6y;3!Xkd z@pw#jY1um;spnS4rtMf0_SQ3?8=_Wn&7#XzY~l<*y&lXLjc+qu%4WOyBO&CIoyLg? zkwQ_b%*|`hy3}2##3G$XcZjP$PVJNgv<>y>MJ3v5gx5_5ThZCj$$X06dbm8Q=Yq{( zc*N7T(Zf3u6Lhk4n_Kk)4$c>YGN)5GIIm<^@o;c{#*7i-;5-+qB!gdAdotqS+?~dk qz`=2EJnM#ogA;o35We2pImPdRCuq|7R0$s8JbEB2m2qF&^M3%-GensH literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Images/pie chart.png b/Loan Status Prediction/Bank Loan Approval Prediction/Images/pie chart.png new file mode 100644 index 0000000000000000000000000000000000000000..0a9fc52a8a9d27fdc4f62dfac8e4041bb073ac90 GIT binary patch literal 60503 zcmdSAXE>XG{6A{c-mMk0r8Pm*uJhzPI_LU7IS+D?`@VDE_xt^M@6YS??3RrMAGZWI6B85P zjq6u$GcmE4F+NaEcE*vHr|z{e{xFB%wlHOSKPt7x_;Lz*#rg^pQ$r399m2-=&J}Xq zDV&K(^uoUn^Nri*$xKY^8#k_AxdU_EIAVKx;a=37fN^0fBDy}hDDwOz&Ul@RdQgu^pCv56))YUlWF3o|L1bFkj8n&C7h<#@*da!{VJ*0y!ZLPUvX+@rJeiV8%g{> zZ{!u!s9(8$xn~i0`?WAH*2Kbs1LGRJHnlBZW+N|?BQKh9PLQ+w-8;UBHff!bcaM_l zzW~**$qD5<#CFP-m6cVyCH19v7kk5DFmW1OCMzrJ&1{Ry`w1Z)TTR5BJ(6K$a7x82 z{w>rmq?wRb- zss-#;*WSlKyn2tK$soC#5**o#@@;cQPv6(Qr_R`eN97DlL?*HgK za{f53Hy?uK`}a}`B_keixK!M>Vq601gid<%BGA{@qpq+;Hu&yaw?5At!<3*OpOhiCSMIzY(>XrgIx%vEQ?Bjyw8S1A zH1gNg*MITKD#9;^(Dy^>NAo9!$3Nl@gT!Tif^mPLaVd2%n*l@O9mfaj zV(lhL!CAs0(9zQF*Y-6p8!ke{BOK~g_gPt4FVdG+dA-C@F@K#z=HV(x6}Upjn#KcU z?15jYQOtd=Da)sRkN(W+=PM%2dnUTWY;tb7xyjlf!LPy6AH=BLy}hThr43SQkWt(u z0t!X>{OqdfGTX{>LqkKOYMni#bi8datUoJayb-a?y~#FNL;+vEeE%;)?*+xeX7Ix* zyUNs5xz)Int&^V!BH$7iX5+CjTd_qJ(k=-**(3{avfytEMCp(Sw4X8185u1AVnjB|%yo`O6 zOx!rynoJl%6Pkf8X}!@>k3r z>Vz8S5YbS2c$>TDj=w7}h0o{k?`8|b9`hGzlQse8ah8GvaKFQp}5^zbONWJB9Sr|hA(!5diAQ#-f!~B z`mU5T)Q-wKYlT)YxHYLXe%OT;{yV<^rN$^Z=J2mF(IRK;_t&@i8eVK8^E2!=*e_qd zRwoG_3e_K>QnHd`f0syRNwo`uQ$#?zQOdPKX1!tUgs)@c?jSlwrzE~MzA=5*{*y4t;PTWI2-e4BzxGU_<2sW!(3UG(I}43EBT!vP-Y%wjsTB2%{7BCS(RyOkJOLcwFrB*Oh&98TT8v%Qu64Rp5(V9ab1UQdqBpoGB z!+T=S!>iCrP(7FoF@fx1gp-`WT(||MDPk z@{^S_t|-#|J)iH}`fHmDhAk+OG9B0Sooh7*>VeYxs^EEU-8~TU9i5=JI6q5>2E~dugXbw zyq>(%4C>>lBj_FXsmE6ISe6hjKUMD^HUk$xmOsMyRNm8mHadU%h|W+%3v2}#%Idmi zP=b<^NlrBXu(=h(T52uXnWCdl7j-~>7;QrS7!m+Sd=9aR#SIerI~7UGYoqVX{lk0> zd4|u}g5$ShwxZv#9Lt^%dhn@vt##In!6z2 zeJlIkY5^-7m4GX0&&~G3y?vR`oaa)-4yQlgK8-+GU$L@}wMjNFicIQnTua_#Is0IWHXb#MIUFc@18BxuGs9q(86uFu6DZoZMaADKftsYsQ%?RPM7 zQ~h;I)dEze`Klz=%DE>XM6g@-Xk7Mnp}Nrt$!M?j$;%r?JlL-E(#WjH!ccrT02TNb zdYK|4S}P84)j4d!&=cdx0(XwxIXqTC$2RA>3cC#cw3z)Y^wa-g`F!d_F%v=tE{X%- zK{R|P{ib&~0KM0~6>~9r#^U*>Oc8zj#UME%Dl+u_oZgB$j&)NlNM@6HlZjZkoE_8k zu!H7vmtS1%5A;5rvFe1omuDYMTJMXUEV;c30jep>IjRA4Gd+!Di5ZdUq$U}6Coj0u zCx6Ylj)UKQR0MQC^TRH$4#jtO;X`vfyQWMSnta@gZW(7p^EN?cr%(=YN!ut_}NW}GrlO35T`ze`{%BW(j(?FJmjU?JQrI1ry6Hf*tn?XfMA zz%rUJvL5ECSHzxaiys&xkHPBQxAkih*@_?#I0%dptLqM+%3%0aEFA945}+Q7(B)nu zOWrfs(U$-0ypiRFDU_S6J%^*_A2c62<=UByjXBGu?U6nrMhg~eLLnCR9+4^ggDs0x zvXgjRrXmvC0_nRJiX~g=bYax_BqpEbt4$W{dEX~HA#5WJdp>w}$ZJ(_Hrg-+1y(Zn5s zWSce`;F=F%e;CHknm=cCX2oePud~5}5&sd94~+6I=)k}#uY%(ae_YH`u3Ww0B}LW4 zfv{N8dH5nkoVMNbsBx*pJ5}z5i1OB8bki_!PD!b@v9I&exPP@QDnmpkuBK)Av6BNJ zICJXgaPKYr`go6+c1qr2g*dTE6G;mc0F#;id|p?(@JpN>iG?j3IpJVNs8m{SqdG5Z zT$3xfC1-7Df9WH@2FFHB+H)_xRqIT7q7MsBw_Fj!UD}kRqVi?MU03X6`ss{3A_EIH zQl!ceQx^YAMUt%Flhsr2{(;GU4=6adPKy*MxE2e&yq%mx=mT1j03M}{8=yMPGJp|I z5f3C(h4{D|u{dSobMMW$=&id6$cQYGrdp8=MszZ_|Nh@+W9FK4IAx_Bz@LKJ z^ZE{a599kT{}3aK%3bTH7QMGJ_;zME2b@D1`_v#)Wmx_I>IgIZew{mN<-$4uU^JK4 z59C*kw|3T^nY*LXgkQVM4-y0^>H2W{u=sfR$cYB}fPL6~3J?pC!zNl4lcl@Q%t%|6MJ;E z9FpMdNCM2g?*=PgZ>cqpZOIBaM{^j`Lf=|&7BPItE7>ls6{cka|F$-fMtdHaost#& zsP>c}5a8-s*pn5RLc!U3X!DJwY0eJU3GeM#jjc8%cr1@J-;uc~Kdc8~>n2r;Wlnj2 z2NFQYOJ;cPbn`r1eq;u1Dj}bzZiM79<32l)HhO9c5AJQYT9HhbcFhyn`V!U$AI<7- zGW~Q)oGO(A)l+`4FFBbE@y2M#IwQr5jHz9ZAeD~p`-r{OuU^*%pgtI291!V~5E_(> z*n=`s8ch|h=J2%EU0lJngjU!&nb*brk}?eQYW0p?4$hQBE2~uA4gN33o2} zY`cl7Grh#GzaI2pRo~;Y-G46pD_pLH1nleEj5s5JtIH=uTBG%e@uAn9W0Yam-&IzE zQW7JxLa)X5)HkX&!tHB8^x?^2j!czw!|zYf0#u+IP+aDFz={g@6&W+fxl2V6nb8H0 zqh_3f9ZA4;-!=qkzgZ-f8;%38NpAv!E>i(i5LK8>)U8oTkhbyRCnLM4Y@XWcr|x59 zX#*B7ts%&Ya$*L6IP^v`Aih}4Y}j#lXP8Mqn=YO^k4r{7!W?ZBYa6K;nCK_^!?xqaQ>8dKoKD7GE8P` zH(4EiMZ`TNBPA(c0c-B*8!4#jJKRZMR#)*HH0=#{yg`Y5WH3o?QqCm|2TWWr5RniS zeMNw;fQIzyD?N(dWpz^K=%eZRB3gWM6&l3Yb-wV+;tK0v38$1CziU{Ns_Tw}WIYKk zBY8eW)U(A!rJg~#r-UnJkm@rkE=KFi<%{Lx-Y&OY8lEMiFzRu{Bk_59^c$wL^q+6a zFYRgNcvp9mDhE8l8nzQKAqj1qq2Uu=E(L3?SebF_^W5ZZXmr2UJyaALt-No5?c*+5$_nj+7OQq}wX4h$ z(n|>=U>k8Y2jRHgdvVpYNX86v0fJXqYi zhWd6ZG$FDupB*oODqF*XhdPxbR=>K>d0f_r-Pfgxq7w6kiRrYwsdB|M$gg&ULt%zl z6!U7RI~{0qJY#$awG3>M^AX=a-Q666V^+DruxH;lU5$ZkR4$8AP1z7xV%FNo2M9x` zT$1K{5^KRF?yu^xl#Dkw=1#wzCHTne2!Pa^hBbcHKI#;+^CD(-)fq&#fy*%_-OW$~!8OUBTJFP37;? zzlK7#y`Rx?DLvc6m$M^L-syfldQhV!kS6_u6Fg$BN%YmRt6gDyO0HZYsHPFcr07B) zy4R7=dDzxzpU;t1bhp)INC`*kuT6u&>a?TpyYNdeJ{ba#y4lAK%F@oNTjoc)D3fKr#q8_ytXYlKlfgI* zKIS^J#O{QL4^sCadXD4czG0rry_UI@D^~`fRT_{BeLKV$gt^wIrewdqeNQmZiZ^kY zjTr8nfA}aNKP4ys!u){pZE=MaK*}>nwPJ#4#vB_@hxWw6_*qRuCC;KPnA+B$7O`o} zxwoZa+&fNkB^t*ynNK0W`{?+i+5OpCV5CtW0F|+ZkFjz~Kj$z6=U+L8?ykNV#DjNpsJ_CCzR>QoW3sJ_yF}$AKAZBUYtAW)ztbhZCW9GK zEV&;vCw_0(cv!wLA+&GDU7x5(ARe`%Li;e-PC%>?2k}KHwx!usfwPlZI!L32g$`)q zEK#Ao^sb?7LN^Jb*OJ4MC~|Q!V-M=ONXdf~+bw9KfTR2L;X^CQ^d~8dmmNarKswwH zDEg6Z1qL|Ttr3i+(C7zudVS#baZ^0yW-vHeiddxXx%0@{<{nOf%Cm)qdV<}!Q}QC? z*9JAAGnU^~(C@yw498fVnJb}KJL))^w`drHj5RtC#*tvWQ5`-&Q%zNsx#z>uQ6y?G z0z0&Y5ycWnK2APHP}fTG5{N4G{nA5+;t8Y4hh#?;b;pFFh;#^vk}1hZlb+wn`n2W? z@86U$LaFctc(_l$v5v8wANAdf5$oZ!+N-NKT3tX)AWanx2XR#s0lcB5qp!HDgkp#CL|5a) zuO9-aXZb*E_t49H!msd4`vyFkS-V!IK^pEY`#ODDp_Z&xSNy8QDk>@(JT7ztn@o#l z!H<+-d@F#JGwCiJks3%})ktZH(Y4-6HUgAhZ|cpa4?qKmIgDsMmJn(ainYuz&kK&! z!sIQ6ldbb0M9Od~hJ7;G9KoKGGJe_&oH7qkujN%L=b9|;1ZB}wg^zg^`AC6?!0ELk z2m&G_pD9_u@dpa4Wt3T&vMbkCvHx<54ZI;*mSKO{&yZ)p)R&ID5fk z92<5pTJsq3&B09stxjCM4QV+ozK0R(lcBN@L&K7XppavT%tCC(G*H%tj}>pw$2sZV z2y~Bip9R)Y0Fg#0Xh->`$3fGJGI+4Vacw4|P|4JH9nIZ>aKAukA?erluAN)ltz$=P zV0(dMDNXe4<)@*xB^Jzt76_b?&c#$qY&80zUia&Vn*iyHp011Ys?M4ADg z*L#a#n1t&74xL^SM-3)NckV^|%U$~{qOYQDF+?ZE(R03*@bauzyF=W&E2b-i=!wSr ztlB+3pR=S*5c+By zbA)*oF0r4$&KRSj92@JlOuac zD8BgyZub{=HW|z^pi=Tu$`W2wCgp#3=@rD{ zFecp=iKFSsgsZG0jb;Q6>SYy<^m8%>fMZ;COWZLj?tQWD+T4l7$*SyY%s}I{95ofS zlpuej5A|UEdo0A9&@MD2yJ#r}z+S*nz?Xg9qw~UC$y#6}?+UAfie!{2gC0 zU)dt$H;R1_FO{2s@;56IgE2Z~EJ4rf`>+^BZOdTt<^?RaUSrND+RaFwdJ5v?GlTG- ze}C#bcRE+c*(SPXutphTuHa`CQ}d~+3ljTqsdoc~s@wpb>QENKJgscrPTqW`Fb!Gv znwGHiQU>y!FJc=y=L1sPWOo~lKpIw83b{ z;8UuYrrOf8E|mHypFj=);D z1Fk=ikA(nfVmpL{D1>)ZG~KQl_o%US_~P=nPczMak;W^~{92?e-#pVfWiVkLp<5eH z)8BPL_Cptgzfl|{D2@_W)1|r3NI0bnbIWtHqqW&ST(DGnQ6x~LF0KwP%-?cZ_$aPB zoB?-Uj-e^|_no0i*A2FKIW?9)_j2QVnX}74T`0q6NV9S&3{f zyZ3c(ccCA5FaaMretWmw1q6-&IvwNHn_{HtAhyhl07_U_n(GpCNy^2J8?1#{9RzxS*LoAkfu=y0M~AN`f(jG*dalcxdD=E$`GY_~C%;hiGu6X> z1L_>0I>ycvSTtcqB4dyYcMbS7cC#xzUHX~+_jp$(haE=c&a)U^p9h@Z_EU8P)_{ya0$d~ zV9d&k`81Jc-nt7+Xms~4u%~qJ&s5a#mexi=Mrlfkwb5*UET9N|c5X3bk6RA|7Dp<#cxBa^z>Y zuZF(Bu&8SeWxy^3KIv0^CA!-(rKfOt5p_Hnm+p4>(am0@9Tw%Y*)f^)o!<&e8yI**!99P;JAU+PFA)09~vZKEL2 zAJ*j)uOl_I+<=LcOSv9thKHPt0A>h!fGT1J=7~u%3fRxBLPfLcr{t86{CW}MO zDS8j835+p;_wmQ<&fDsa7rLNcu|6*Ks*~7(#t`j#sfJ9=cdOlA;gkJFe>J||H>neB zf4brP_;sOjx_AL!REm<`epv4f$l4{3;xW9Lx(cCrB9}B~q#--`@Rn5rp1tI=bH9dXR9&7|2~)qC zZ*X%tDAeva>QfyZ4w{nJu!ovbwL6hUe2OI=?}lE4S~h6Nj={D^p8Iu!ujFd)eh(a7 z4Dog-|3=AUlR@S5Bmsk+useVV2dyMr5y1>Qu;cT2vLy_)n{wG17PKN8aT}^PJ@^u7 zkuL3Ub(YXld|$_r3rJ{U@tSs&DG~#)yXKKJ`S(kyd{hqIl=#RbibtOS@g<=f+}~1l ztCT+_R}vzF2rz<{YHY$}4ukAWCcZfWWhdKkXpt3-@4V=Bmp=as-FlFj%EDa2C_MHf zk{2gW%%SB>c^g&zY??rXju!HuLHI+jBHbd3NWSkNBIoI?@1fk3dsHJik~kWmgT4=q=%dR_xkTEzgdJ<@hX11&U97B7T9 zT(Rfo>}jd2sP6V@fvH~OVze6DdNO8Me0n?*pi`k?RFnRuwJYF0wkOgyf~ERiTI55t zUh@Q_`=`pHvO@8Xs`M75EO{kS(H#(&6MyX^q9K4ib~`pRn){j#(eAl52cy7Q`3RHA z@!Urc#8Jb>wWU4@6kBz1svs(_G8M(kK?Q7bCo}rr#_#W~3(p6jwms9<0&kbO_f95PM z8x;t|ZXaV5gP7e;0c?y=`8km?sEkh&jf1LrAG>C8`P`r$UNa(=KVbN!Dp2+L#_EkK zf@N}Y2B6G54}pAt?=$3G`r2)ved8tqPyj+Tnn@d!Oz`2;GZ3W!)SeGW^a1i7kIIb> zMEwFKQja4~J6bF2)D|JZHnG?Akv5RuvBhspS&n9oKWtu(eU zVKPAyLdPS}#ob8W$wX_ZQk(c7Vy1mI6T|hNI>xZA_AOE;`oNO==-u7AxCdo;T~%(* zxg7RPxo7!e7JebW(!SRH@?WHGNAb!VcsCle@BvSJt_@&t(c5!y^UnvZ^V_!sS01F~ z(F$oVLT?lr5EJJS!8FxO0q)CDCi?|9G_*=E2GSTcK7BVC@nCor^gy!=VKeM$UtzN3 ze3^}7>U$N?QxD)u#J`wbO zHQCn#`Fz!D={Ittloxx#XTTN}qfqZjmBUEKst3v&h;Ow!dX%#@Y>OWwJN=U@lWET> zjLy99)(S_*7%)yF+wblE5>AY{<5pPxaP<;`_Ix?D>C2>O3{i6a)^h%#^8MAAWuCKJ zBQO;2rdSEqH;1NqMSv$rykgZIP`yvuEh=>STXf>|kS3WdP3`pV-?#eU4Y#WwYTfPW zr*~s)(wsh}>q6UN=f<}|fsfH}I7tvZ8Zrx69 z0yc(Ks(iVqT9_~eUG!vLj9GmKF^B3oE`}1D$TO<<6c>-2_FEd37MnCPwf=|-`wD9_ zM#NE4%RWCd`tJw7#~5WX^N4NXSqP^1o*v7W`63oW6c>qeM#l4B9Q7xso7@}ZkoxmhhhOcl|>`UhzlWd@@`eG)`OzEK_47A>UmL<0EG0le*K#54Kr ze%F&Q_{b?0_jG<7AMx3qPqFiyC>n50rVgLo;V>yo%+D9ccEJa@gD)1Orb=S5Mr=uo z9ukxp0I8PK5db3Coh2VzaY#727M5uN3iDL1$C7rPDnPSZ=^Gqo6%Ut#TuTUjxgnXl z5)KY67`4em%LQ#(Pgi;wEn}~`1$yk+TEvaYH!mX$w0ywa$%G<4&z#AlIN z-U*SYDbLGPBaCQ}=+@11SL}wumChnzAn83yAGs=n(+ z4o*Q$c@_D!%`~Udo-xE@jG_#P@euFN6ePHC%Dtr()!*Ri9_t0C7zy73BMJTBVQ_C2 ziQ1}!5w}UNR*6}Aect~zZ^IbqOg(T+uc4={l+>NT_7qXfmYkfBZ#>VW>Z|26=Eqrd zMOn+2zJDXJI}_i`#u!<~N`&}~;=2PH>Kg<#?I#z2ysD)b9aLg+F`!5;WAE(n4mgFe zbyAR!v`5@k^-W`lj^Q;>@t?~`$Rb?#90;L`&t-VT$4xqJTPLxn;8H}+&wqxg#X-?h01*nf8B>h-^JzGvRvZxrut|wu8~y;H zlV^&8mGu-dTxIYrKFdQpOIw)ZUzXXBl~8!(!V{xIF9NQ*zE_k@hD~x)j?gre{k1SX zG9x1RasxiSh*3FcsQKOV;h`E$KHEbJEEY*_J|sQ z>vwJ(9~F#m6zQ}ArDQGVQToGhmlFv+orsQtTi!+<2=7v08LjNl2`#QGsNq5@XiDLy7qoc72-VM);n7CKytP4CBQgW>3r7$5 znX`-v9q{z4(KCT4lspKU9zIpnn)}%jV(wlEn$$>ada7wpz`X)dfs7`cLyj*zg#M}3W+!tZb>AVfIUJ*i{A@+XWvho|j^a2~{ z+XjpsrYZ`-G3NC#b(yZ$zdC)0RNc{e?B9)1l z=@%Rs0JEJ#ksSRz%kTjpb+RjlJ%nHB7Fu$oYp%Zgt^TE940Z3Yu<@)-|Fp3aDK9GBLqYGU9OAo`L_~ z7Gward)mexOaGhJX6Gr|RyH?_ZEkLo505O*8`6H|=|%soJve5-o`1l$qUTlS7$EP9 z68{UMK6Rz#Is?|+=#8%rC)q4BS1R3a@JK#wR8>_4+ZnfL2$)j)>V;d;WWdBNuU)>y zlR#G6h%k8Ax-1I+ZI9|f8b;Sg?fO4@^r-ypTOQq?kMd4mSqu@EmzPhwDp%daK$l-U z^AAcs%=K4#$sFTa_x;}?!2cYQ_jy)pR*dk6JoPn3q_ znyym%W$(!k{DW-4f62?*#U$%-RWVTV)$)02+zG%-T70E32gv9@c1KC8YzK6ban9zC z=C_c)a!HIg7VQQ7TY~yxoJ`c}Iq?2Mq9rHew19K-!@FlxCp=$TDSTCgz7=I$>h(`J zvYK8J@+k2i5(jhe`>kUKT>snq2XD>u8sv9#T&41G7`Y^OVmyGt? z-*r2AOlLg$p2|08DwnluVrE8D>L|H-0n#{3^ZV&eY&AmvNRnFV&v z4g@*qujiBD1Co)ugIR}>*{)+>wO_g@bBXWjcK)#Rz#ZH>tz(}P`n`;-2PPXF`BU{{ z$Zd19pOElZM27HcssA_*FZ)wi6wB1pO9myA`Hj`N%ar9(d!WB#-<2ybdIrtbB|Wde z0#7KhTY}&fV~?2T?E|O|Htpk{^q){ZBs5{0z}|`3;LjVdhDi$$84< zEbpJ5wga1=dU^JX48xr(h8mKxPs^>;9Js;`4RpElYjdyZN#m~imVNWij2F)>c-|&k3BZX1?1x6@Bvw4sLG`MvsKA3OnzZjJIj+ z+V{RVdq?(vo=`ERP>}UNSVve}tl5eJD#$p8%urF!L5msc7wAH_71{Dn-`@H2vURN- z)^IBGyH$L+-Itdg_WQ3!>~=Kmc(tP>$2Wo;meNWN{;0$TleN0mcisdr2qT6J!bsA^ zr*qQjG7OfC$84X+Bsa{PY3+TpP!J(rtB%Xm>7PFh2}Z$R z+`k zu9Vk5*X-@DfwzK&dahD`0|{^2DKPQ_nNK^p$Wzni>=hxKQuh*iKx zyZxR1!;F}iuxHJRT3Xix`(D7}E~du4j|`30OccpwwkH-<_AhJe#)XD+FbA`a`Etvp z|MzY8TCVVKRqpdw1V#D&yp1N1SR2R`}xPs_3B{9?*=@pM-3$j{hPXMw+8Oq z-Cg;1>ce{#?*Ben_bF%_w_lr}+!tKoVJHNcQ-30m%+Ds++}(SY{WR+v8s49!%A~U9 z`YYE01GARyW?otSy~{eu>M#GgGE4cH+unMhJ64aG?tC@pZ@I4YFkYu?$}xON>GU&q zUti7|Ta>w;l(}542_xMyXe;%hMDq{L&DcdjfnuNmBeM3~?Y46-F2<)?ySvOKl$8tQ z$l$ui6W?$Js)8IYJG>InnP%OueJef1E7P~VddqJM+&wz=_(7k-hxZRm4n@no-?h$j z=>23e@NWXV8%o_k>4mbWx9^<()3#+)svpiSrsmQ`qmn59Al&;Cg&j%l(R)3_-0an! zjeiBiy>zEXkL)>j`wl|DaF$?esqWXS%F9CO(2SdIcX|@gJ@h7g$dc~1>rRq-xrVgz zW|`tNrMNP+YJB>oIb)x|EJ!lF=T*3K164cjtw*+$enKLLz?+e+Jx>PTYyRlZ6AFV$ zVAuN`2>mCkl#;Im_l)XxVxm8umv8BoQf6UL4D1}W;I!!m&-uPL5uraGz-(>$x2~S{ zwd`LU7i}>Xwvc@1c-`jf{w9?P*qev^(%#8$ zs=Gyctk-yB_vnC@LVy2L+?DUkObA)mY=x3vOgir-=vz&!ja{8X@NATvh{pneCI}%|(Sr8DUjpyX*unF}D)k=)j!!eKQZ&5$!v#y4) z7dkxbwT8s5C@-{jo{~8V?wX9_FO52thSUXpsI^z*wEySflO_VU{_X(IBVnh<+y0pE z)EJx57gKYijw8KX<5*iej8@N_F;PqX%wwmO<#j6&XvQ=E|hI{I00(^5h!=R&Q zY4q@-{Y3$dQ}%cTtknJcl{>CmV(=vM_UEFMO4iBONIhLH?%c<0_hyd#jD%ucyvLluhDr&!cGG zRz*wD9rY9Sp7|3a%~Sz1-M;Y)8iY-&Hp($YRBL&*y3F+5L_v0?yog3t03f1&xTI1s zOjIvQo%{>MByeIx-quZ@tNPM{DDA@_C*byHtrefWs5XjYUmegKYZBxr-S2} zBI@eF!j)g6rFTu!q-)flMV1}3WPgMn#4|U!WMfarfXT1XNRhp%v8$Ga(>N7J6C~L5@-LAEA*c$jG5?m z^4Xt1gT87p&_PqkbgX^!MdUfYTj++nXQfO)Qx-#Omlm7b#)uD1(gHH>N})sW#p+CE zXwFJt)KVN%&JlCS(z&xbO0IGhzZojKV;snzfqU7nNLlrKqpuo8XuobmyVIbbDUYqR z6W+e3VgEt7aibOdEwim&^Wss8f9_L1o9G48SGPwlLM;hbpOT&2$!9|jC>|E;*f`LSO2pjkrJSmr;qxv4e73f)g?#t;i9kDqm zwMtPZ;UKW`L$fJl(oumsQ<~L$j%CTrCkT=bw|zj#TSvYQT8kR6+qp%SGKjDmxjF)P zrBCr-aQGx7Bwji$X`C0TBzGbA@2Rq_;dZ7XWp^s$AtSiR-nFH`(TNg_|Nx4TGH1`*}gL}cGpnA z$flvmTiVY-0J6|raCdKyxK@M0O?4hW?j?qP^fwd>tQPe5_rJZK&!CO+>CT2E79%bT za=siDPI@Bm@rr#+%NmgVuVv)rRhrVAFWyHB^RhPt&S=)Uw%>2Ji)^2paLRwS%r%4r zKie3u8o*E#CW1S-M&RLEw=)*rX%Kh5d=^BucCghYnFBX03u6V}0Pgu2HqK|AA1`{= zo#(c&J5az9l>oO!bKZAz`CaAtmKMW0R$tlTxFHw)Y+CCt+Ub)lY=PN(679J>lt2CX zvC15ypSX(&IwLA7WTwsZV^}uwmk{`Pp9njqk%ahDb3IetQduuuy7aF@{ntXdL~nld z4GyledeR8#Di@THwfH6+(-6IN?RVGPfs%Q#lHPP5m+5wvdADz=Ro!n_UtYSyyZip^ zLrZURG%IxB4O`ytZPt;1_+42R2R8vm4KTZ66qVcZrsM1#ak&(KrcWiEzQm}pZo3mcjj*^0c0@=B9*STe-IACmc*5z`O<}I^j>+Zs+wF~Fnq5y06 z+>&)PYcE@iS;nx7o@qBq>)lqM?{;uW1rlB!G6g_n97*e4BWt|Jlo{QH+T`4O!eAHW z`QY!|@3ZGySy$U%E2Sp{RVSXR2z$=|MLS`{$KJJ^L8%O!u4is%~L*4ELfeD}_pOFAlL8u1(@Y`kH+GaF8T93AXho_+k}N#Urf{q*^QkvEIv zHEgO-+%KW4$H$5TGWskrnIMu{sP})8KFQBhKh=s1UKTho3@_=jdjc}72KedK%J1L14JSKk=q4v(n4RM-4gZw^`a{U$72*Li&T zAMg0`9s5&uzJI_1dq2l)pY{$T!y6ae^kfcMA`jF}FWI=l6 zq1|@gYH|Ez|W&ia;yL{6~`Ir=cPR1c`j4kH-k)cjE;*=hAOSJ{Z{6{Us`%1aZe{ARM!cg>dZ{B3;qqd~|YUj0w@ z&gV8RSIl^c&ii8@HerLFEH+mu!+}B;O44Fi{;OxsQi=b2sVhAo{{3bj|I~(Uubp4Q zEuS>;H|M5r6ragsu*{Bx_@yr=!Hw#Q$MiOKsHhXnZ}5YNs=;af@4SkIL)T?vr5RHN zi|u5way~?G`AV>N7B)Vy1hYTGk)XGgF8{D|IHAt8Z?U0me1U)QiQ3NMzsk2RL`d7t zlXDto5&Fw%@6Xb_|B|_%&Y2;OHP9WiTfge-1WCe6z=QSoZ8q8&cIVr-hgAG+__NPb zY4B=LfsD>G?>QK2E{ZNpNtL-XuOGT}`*Ai><Q*OdgW@_rR8y*EIlyt4TsY&3iM z^5rkZMjHmbx!w#6fX&yNmVTq<8x-R8_WjeRZNaZoMo5fQ8Uk zdR9+MNJGkwf~^X=5_$Q*y-`1Eb zAJpTM!~mo@+QP)&gRUX1?^nO&dT;SprbM>=YrV{jDb@};DCE8)F1V&*GrP(qS~B9* zi>U9tZmV-8OO@zPaQT#2HB^w!f(2eq-zVC-|586T<*L|No2+(Ic^Sz6H-uO6%wxyA zAk|IbH_0YOsdKAJrnElPY?H_MaEpWiGltH$K&xX3KCac1ax*XGx|x<%A@LMsJxQhF zB!gdlEo+ssIDfjEOa}7HfM5L$FOz+5{ppU`x;DrPG391aI(IhwW;On&uknr`6KFjQq|x7VzoXH5^kZ^aS6BSfe_0=a ziOshn80uqY%$VL97$2-w!8Simec6_r<(DWjCTZkjOjwBbBy_8JSuBf_&!T)po84>J=|wt%>2{;oh!E_8-RUPr^jE2CtLK6 z%$YMYr9zs2US4N1(4sS?y=Y>Vda-C%S z2j67x=j0E~G(|qwt;Hpu1bJK!ShN!o_ePYXGeqI<_j&uQHP7Qqx@U_bheyC3yH}9w zvuLdLyaV?B1Wugw7m5BmMO^^GCB)*3wkC~%%;0|r$M(Nf>!b8g{UI>4#HLU1NX~qVGR9c9 zC)n+a^2(XL1BsAN9Wp0@y* zqoc~`HkU*y8&BhN@Kdhtp@^7)ErJ^Gu-B(Nl8eDvG&d@;I5&#NuESj$}a+`lK=kk}fu{Vbw`cggkG zm6$k^J?-5M{kM=$kyQ6s+c7iCOX=+`%Kb4VarGenn5KL|24&V18HrIC17Dc&dPPWR zf4E^j5ISJ~CBNL>_)oHm$npnaNI5`dL+_wVK5XHuN3#n5IlkuI2Eq*)H3xuYQkgu6 zEPQzB(CrQvaTKCeE9eZ|7>-@YM@=O!>mp@ze3rBs)8Gf<;7TajD{bBGNvLMnUm`-7 zfu=A}S5;)kzNIDNB=+`*$O}I#03NG@<g^nBwB5@5b{M)^(gKyF7I^V0k!yMYenTG5+1D5O?`C+!x+~H3!DKYQ6(6Lo zI##xZ8VBr939DCUbYISXBZo)eNjE0CZov9 zrLj@!fNkWk1->LlxMUwAYRzB#6Oy5{9~9fTE}b~5#cUu$G*L!zuB*|5_LxWe2nn{z zSShdxa?7{Y9%jNpC49}hvdJ3~ae8mKTlrvxG6VE|C4zI?74q8Vo)^s-| zp?1e)-#7%%`<+t!zlZH2A!7SKJ4#)&ARS4DD|m-Kc2SPQ{&)~~hP1b&GQW{^6s^tc zRbQsnfd56z;eqY(=2_HH5O||zZ)RR6fn3b%z)dO4fe?})8nHb@AmlwWBxB1%G2v-02*1ZQ`63PF+ z7&2y+2}TMU6I`0G5RxtUs4H1Y$y1`As?1YpXh`9|e#b4>*ce1X1aYTo4`bu0=}rdkwp~&9|Jjjy+@4>GRdPo8;IRGvl<>QEpiGxNo;5f;yQ8R{eZP`sozh} z?Gb@ZqAFeYj^JHm?j6(bSh(_~w=HP=+FjS8C zH3;jo_6j7qrO-7&27M`tuGv2D9%o2hn{Mb0I}6~?k~YwljwOeK4WMi zKeTTQiZ=d26Oo&ZUdN8KJmcsx-bVhWZXx40!!soq~b6kf?Z( zpwpV2sorfIy-zOW_ez+y3?e$@zf;{%6$AC+#|(jE{%+XQT0tCn9zpbjHMcK&J0h8X z^&!*tCkn2SihoZkCq|5ssui#~ot91XITy4hWyS+Gqf8B?6|*w_)+TvB<6V!nGu19? zo?w<#jz?G-2sPgaRp5mfAd8CBEbzOM_8Wo# zwlyJ!lv!43$2PuX3YW8*bvi=mvsRrEpnw(DS`k5x%%~vONY1dv66D_+E+g5B$pr{a64+zn)skiT$ZKmSA-d*;Ay-?5)K!c}S}5x&M^6KpP!9 z;st3?06-5M`$~tpLVYLzS_j*ISFI3}Ov2AtB1AP~N68$AEFzD2 z3mkpUd`3VBSF#qFP$8?e!m&ns5LGbxl#4K+g5Mzn)}#R#5yt9osysGPdD_@5H!8bN zlT40uUj?(Btwe%&ImNXsPZWeh`@1ZE=S^3`lox2rzX&kxOi^!!Fh!_{Tc-{;TdSI5 z=G#d1sW$Xd-(Csi|6Y#<`lv{PD2b>wJ}jZ}RggHF+%?zL%j%#n8}#1|^+}*cZS{85 z82xAY?Tx7f5q6Ae22?EW2g`xJr> zs}dMNN#$-i3YYoJ7#tVtAmb}v!M^X{TjQRGK=cfPD(`PLVny@l_ z+AL`xs!Z_MMk&N14@#8#>WA|lBkt)$uElXjN?6Y+7q~do){6aO0`bGA8$Bzk5734` zvmgHp_xmqo5x+zov)S=t>pN=LtuETla2rVw~SGd}gO4$0U}R*>yeP3cZFdqg9eD~yUP$<@l2 zEA@G%?qNj4HOH z`5!Z^|H3bLMoXBoizHp80rpHGPd4Hu=o5QK$Xql#jr%@&Ow3sPC*DILyCaqbDZmP( zp%4>A1z6*H+fl%OF(nOEl-MfBxOd(CVM>|*dJx!*-ckiA?9)a;P=DAB55x99G$}Ol zB|xaV{+ft6AG)SAk*g-G6}vJX#QfQtC@4VJ!s|u|e4WHT7B;8j_-TOO&jz)CwjXn0 zTdhJ4Fmousb{Mc<9zPG|h+)vaqa`cDogMH(9Ka@v$y>kdde?h;K>jmT^5bfZS%#}# zI_nYg)NiGlzf(igpTccmGk_u5nu6=|1Cxn;1FTR3YKLBcW~mq|!qN^Ck1V>KG9S#) zJ;e`uAFfhXtHf4^f?VbwgwS8|k5Go#y*EqNwK0HKLjdkj5-0N@Sm;NH>T!zp9Qy1w zL79`%)k?0@){7ad)kKS;FyO&$f9G}ox4hkZIkH{RV?ZMCA6W-cx&X%RHgE%qs7y

cawJ&7_ZSK;-}S)>e1o#qx@pVB%6rdi1gDq12{HeFI&>&cHl)Pr=0l=zml+0 zc7f?65k(s=d_{H=Huak&hWn%BWUH5DXAoM&2Cw&x;okL>>gDAohlbho8f_qOF z<65e{R&|$Y4OqV%2`tanQe;5yAh#F;Y%A=o&)ZKw28_b26oa1AI$#tkp`x{#x%BYlz`t_1qjPWUzWwYm z;!WFW;X}4Tu@=Cuem52SHvdQ@S6nnsHZF!LCD|`$FD3$}(B)IWQTuD#2h2X|0|uk0 zQ}NTIE;&tv31tu-L|tV$+}Vh7afbJh$$RQKF0`Ti=;n6;akK;?((i&F8jl#z`0~RzCI2R^_#BThxoo-}q_WiyC z4bAL7L6Z=z9i8GgB)yKq>lUZ%EqUX|Y!Nl4^sPyQ1Dt6$rM=7OhxY}H7FO^Vy&#RuO3y^kX| zVVHOnrRI%!6iz%XAUFdshp=zil8GK*kjO1Mp?%3#m?uj~cHo@z_b*fiaeP^5Kwu_$ z9QvJDMVx;1vqyIe5fLy~H={oGb z2Ouk_zKYfB-d?$%Pw#7G&i))zp`m3L$X#51pvT093Lz}D_rEutMJ0DmEmKWD{B zl$5KLefy;sEBjmD?@xcOtP0_*caA$McZSI*Jj{?~5zXWdT&>xd@qkbWWYN8u4bGsI z#cuoSXSK6aLG!zSx36c?vq;H8H`G~7xG?erA)Q+>dG74d>I zjN>;I;rCzH8pq$nE2a|iU<*o{RH4cu;xxnrmY&;XT*8ARvIYkuv4SY`G3;#{T{6_u zV3_52B78a#nlGQ0Xr7keOp$^1F5=vveH_`-w49JFl--wY@%BI;|DozgSEji z3S?UZru^34!iCgU$Ho*e?Dv)#e6}v(AUB9-*}N?fq&-QT7eY`+w#H;nIwx#D{z>RA zWIw1q;I=JMi}2Xfb4M>MnAC+_}Hl>0jwf zxDkEUGdhj9yFZP`gV*|aFN{06x!y|z^${>!W@aIv2^)!c@IZuYS&1n< zXq(oXaEIx;QP(<&&yb&}US{PFvGtaOx|?yI+@->Jmc!~U39~KU5IJnSz*pQ2jeUe6 za?XnGpl`MN)8;mwbx%5bU&*=Q8BR8u(H*qx+RfY`=)a{o5-}9v4s1d+BaXG4->&SL zp-RnD+Qc4>L_^8;`hx#m-~j(UVXDDEmq#asrKmpCWR^Ul@+ZaP02}c-6{?%%k=+MI z6ARLdO#!eZ=RdR$SaoX@Vu>n43Ds7cIpX3W&QR6$^Zs;O63h_$0e2_xbg5-?w0JA*A{HbYA4ios5$$djiOpHxhd&ncP0_X)DiSo^nf@fUCS@?9_!Vxu zv^T_`SLT@Cq~4dmhxwj%WdV+sD%u70ozmWFI-~K5C(`i@&DWCcYC(mQM2zll$?pVg zLcf*}SayJ}&~`{y(>8)joK7w+T5(LqKMR>2HDk-~R5L}aw_|JGV53CGN5J06ETYN{ zIv@JmzAZSwE$ZMd=u=-0+tNTjICkH9zBdBfow*J*RZ4XqG2Oqz{irtHD;Tbo9YdWy zH3nvTG~qG~2Vt}Vp#%u}RvO8P4=e2XBbHug!nN| z^_xQOYK&MD&DC%MPZA693_i=!dJ2*QQo^!~pwV!(4I2^cC%VquPMi%&{b-c&4o33A z0|lO(L2d?_6nDn#5qaldG_X=31?mRK|kM!b;t~MSb9a5b7v;!T?oHNY` zwB+76XX~K`i+aQq{zr1K{VA8FB6B3@(45bOO(_?;dGB2!i zLuUv+wDqP$T-=E3+doOHatPjX$@)G9A)Ga`<(OXt(*IsPOy9*L-Re$V)3f^IU3)BQ zV#?nXz?7Q@{m?oyI}xzLg*g+LF1q3ENDKHQOb=VscWeqX9>NF#wW(rADnEw@S5VCj z%DjkHdbo_KA$XLCBk^vhVmkU&`P)F>!b;-BaY}KWUf&q@`pph9h7>l7N0)ARND~lC zWfqTA|5AfCPZKQ#{%LR8`90{+EqRrKe2~L2Qmt!8KM}6((aTcztYltw{!TYt)Ra8! zzxnol97suidUFB`U;KEo$$mpEpp+@V+zF(J;rY@lw?fgUbuLrsN`R`8=2BfrFeb7W z@opM_x<+t5qLqu7x9%%clq*dyo&{hFl;%|DjRjuPq3&DK2Zka#OVNMoRxa(l5T2Z2 zwOH7k-DYh{SAF8P{ASM#_2CRv(2NU!*{K*SRwj%OR4-a4M9U+>SiOy+s}1cfA8D zz57xlvq8z7UmkLAk{|4y#3^E3sLV8qV+){YCD$I?4~!E-Kzk0!zA0R6a%I@xag;(c zL43mIWHPj*N;oq|tfv=!M~l$|oHZ}z>(90dvdHr)9F-<_!|-n-m)%;B=DZ-v$iF_< zD)^>!b$&R=s_OoY*0kj>TQ$ghMX$8`-v4taM5`ABr^YLMrvpws(m|I(XQjud&kP)b zqQVXK4AI?0=RfJj&3Gc^-_ys;|LB$5;frxS|6n(7xSQ3gmY`;-8Oxj@?fVyg8P|=6 zv_Y8G)lrm-GKlXgN{iX`3_(&S79r4l2_wYg?KT?-d-DVC<;S9l$M1s#gBmzJU;Xdw ziIDIzIv|krAS>TCWSIF{KaCv+Pvoe5}`*dyrcsa~}UhXgXTBLR|>kv^{ zIT5kZSEdjE1y|CWR}@<^%NE}2OEvE=bzN;Eb4_s8f6eu(^Xt=DjpcUrcC=p$$60w% z+XV@~sdS~+AU7EITWdzL?P*wv6iT0jF^Glb0T!tS^8DF@8E|yP|8sPG%z&dqo!5`W zkecyuriu!LD)8o@paJP6>7ecKanoRif^=d?NpsQscT(x%8IGpuzyLGL4PG%2w=rz;V zoCDdwSO~8-e3>UQ%9tOjHKPUI8Tjv=P}q450`{OhaM*FWYF$Hreguxpx3Seh|uS%o>4Td=p2#My8d{aH8|j z1$;TkDgC&prPtUSi4$f_cl=C*eRw%$l>DV1v;+XV!k|b%rG}ex<9Hy zhf3=d!kjUG2&G7Hd|%Y~33ID^1t9DQxk{du>;(P~$yZk(@}Yedcs2RI{;Y{bJJX2e z;ghcmW7xsR;i1}4unka9Z=2v)Y&~zC`Mw~?sYXwU4-38MWO}h0>)`jRB;A4$Qb$p_ zONgo?;K)7`cSkiNjb1m*?oQ=K7SOVuB&Kj9+?d6>nQQ8t2y)vp=W;a(?YJ<< zdJE`#iZCp6>09ZwrS}ge9*lbkX$KCw7DKuJm0{aBV%l2df{W4uEweg$I7rt>7*n`$ z^NpGK`Rx7XkqcIw1?hYH&o!YTw4)Q@vjRS1K{&c~cI&{Y34jWS{y~n-RixrG{FTA~ zjhQO7zF?yT^B{F2x0b`p$PtYmqeqRrNU4AX%~vgTr$}Wsj_<6bauevQAI)tdo4|e zpzs-5$gxGsD7}AEuF8F&B)?>K(Z7r;1mU;Rcnta`o`6j7( z?-k1veNq`#q6Oec9>IN6Z$F&jQS$ds4G-m4eQ0D%pB$Xn+RCQ1L=zQgdc}-!c*S-i z@8~b)7G|dO>}A%!_N-^fX{KI{OEtLTlLt8ZJ$Tt@!G!zz%@7Ar=gu=vXYx|KEG@YL zJW5*lU6jSXrApVslLWplfS?@YFb)0#GLd4rG7!302wlnk#dixG3B1U+h_Nc!b{#0a z!eWtg%P))`V+spwx)lan9Dj1v<>8a&g}L4V1T-iO_`iVqHXOL|#cl7;8?01E;1WAUjj+auaiUxEbtuXpVjPy zY*#|B%>N{uum0CjS>#fvs?wY+$a5PyoeItCE)}~-XrTBtatH+6jT+Ss3A52}+_4PZ z&Ii^WUpzS45ZEnKzq|Hx0l76A8B^VCGI?XhRIM9K6z%xkK7@dA*;4^>lJ7q#{^CoM zMTzI$ZnrydKk@k@PRH_7FE(f?FO+6ZK<0EGy9C1#Wfh$<0e4l71f=3;F|GKIaWPu}2 z;$y#kq~cU-L)4i?FP!1ao=t;Q?I5Cm{)3gMTSFj|2LlWNX0?Kz_*VCFbxCtUl$A5$ z^cHG{j0%v?MV)zNYsYCu^e^)z6puLT3)BgY$n&Jj9p2gF#v?|KUUU}2=H!`#9$`%I zk@JVDYPx0TzB72>brADw$L?viB$3H%G%ftXPqWsRpxa5(`ctJt5LFTFfXs$+B;Sm# zM60%{_?^)5nSK2VBymf+pJkTBk{r3EJk;Li4fn?jMaaktX5faC@KpXA(C#qU7YI2%r7w0f~&9yXUTpH`s zGv?e)-gcvLhM@CjhaPjHd;y|_#?tgXojPxhbHgz0V~75xTK*j%2ov~rNBu)llY67^ zS||=2^3kp5X^tmDO6{D|{?|@Whp}wsCU|`jejM+8Wyr-<_dc`>X0GHq z;gKAnuQB$}=-q*gm<8p+9xP?heu8lUSu2$`JW9Eu8eWocadt%_7CNSn%o8o%mlZV_ z@m9i@;7%fj*$;*2mPg1Y)K>y$$jv!RGnz;nG*K|9Kn$&H+$Nx-CyApJuM9~TXYs!B zAOi{q)6>%>81cctcp0){-vfuem=h_n{SzOt{kLlkG^U+8iT`s^ng<7t7I3xW-^`;?1R+7v<}WD0@W0g z5B7bO1L8s6+qTnb_ah27(L=wkzGem_N}fJ`>eRWtyW0YUdxIbSpVS3%RD6yUje0I# z)-SepDE|tq+Vgkb3sLRXcEOax$@L#qmqGP!yi9fFSXo0*kD=|VEW$&xuD&-ST zXKL#kaZ;n`(sO*AdicU?(lApJGV&-BmKG1g&t9SbB!@t4;ZAXueGf2kV!L|UJwUe6WNVsd36JSkMpP%~HqA|o9`ILfSRYvI|3>O{K|K=g8g^US~L#!l~VAv)UJ6h)&thsVD;G zYR?;sJNYVXY4y|ss}V9B$(#QU2uIR0IE9iv2&Dp<{{6QI<`X{ONhWymewtuST)fh3 z+g1iHtcC{lqL76Byo9E|w4z`wgfO?w+5%BSx~W{*{$n4ifSYmeyY0jBZQv%R8P2g+ER?#$Rr!Y9x8ZN6CS8 zl6arlf7sHDUi6ItotyNR3tM3WYaZ!E;)mlB%FtP=T{J$Mcd*5!1OX6s5z zHb<=_1ECgIk9p`pdz#2M++J~C`D!TRGaqTRrSY7#(7uwkG6gItxtR*UED8i%eGa65bjZP-jarY!Y@|6+)lPNb_n;RIVmz9CQR#Dhb>h?CSvT56X{_qo>s3+vtt zry2^7g0`xOHX}wWdbQ&*RA#4&f>p>cv?f{|FD6&2MRTMSxmbd%Fbm;Ep?!658)NH1 zva=^py0wUqbB)+ousP19Kuy`Z0K}i5yUtKNYGA0!si z?y%Tm>9V(~KI+H8>RHWmyve*GxgrsmOI52(b-MS}J4sy2R4~h`kmVD$bAx14qkC)Z z1o$#j%s1}9#^|$$=V{AYq>wckDN5k({D@L{pQh%kp}y~#?5!9MNfe4cjR^N$7&PAj z^Irhn9^WxAaH;zQki1?zYh0N|R0_H+Hx?F#*uaL0XF{DptN;Kcl$e~f$IuZJ%)Fr! z13s#d_Nq5Bd2hVBHRM#%9=~Dmv9jk|HKt$4yUivbfRzPEBFyI0J72al$qnrs`OPdL z_-7e_rk^7PAi)n-MLi~#!enoAJj51*@s6lwWFF)1aV%uJpVNjxOH(*KnT=G>_6(=@ zp=y$L?{`YMDis%2R?1U1508%2a;Y(YR)wfR2nmEUV^F_F_tp4b0{}oB=OcB!4jnBZ z=@RUPJzP~F9dMl;UbK)G=!*xPmVKF0cBI4Oo5(c=%U*ov0i(bbe`Psi6%Q&#HZ&uY z1_Z-iO1fy{`+ai8qPh3$A%6+~BA-Y8_~5^6+bJQZTS~vQ&}(uhIgLIM^Nz?)L$^T< z=$`o!yrg>)F8)kCbHvkm8OqL>md*R}8{8993{;7mGIC`HrQ&gFOmK8?F_F_gT4W=i z_HH(Qr0%>zB<_~M&*q9;-K#E|ss2U@cJB#gW7S#K_XBdUxeo&1T8dw7jLpx)*Hzu@ z;BVao88L>g$6lf4+Ln8(DE$ zwCpl+VHT7SkI+H#`xPW+QRR*dm70Y(^_t$$ei7zeXh8aYK0ZY%tRRaro3v;g&oGU5 zXRP^Nby?RC9|*LnKP}LDBZc(_S5%Q#3G?m1di++a&id7lD0uC16>TE+%IuqEGH@l) z+IeIfR2@wt3I_inGVhBHZH%>*PTw}05`zjAz1EDH=3B(H&4froX0$k=XgV@t=pD&LKa?S%$5#e$sq2~t}F2;?a!%ExRQ3b1=!n!ky3M|H9&WZuYRA& z4pE}wiW8IM37H9tsncdi#`s`W*5Zhjj|6m!25_I-rMOikHhqX;fs8%~L}ca`e9H#Z z^=&~GrAt-c2V%w2=Ag}v^!0eZTO9^3V%K8^w?}a%oZm{rQjKqP=u%`iJW$nc)SGz- zXv3CFynr4h@uK(Xq$7hkX8&ezt;72JIJk9OSYivmw}y^LxpK?}hU`l&&4*3{u*G^U z5_+IgsBITaVfU6SZf5$et(qlWU~#0#LJ>Z{P%vOFa2SHta#1o zS*rR@6&@*>q}DWs!0}57PiL}M6{lhrG*jrFnM!tB$S$k|;dP!p6rVUhxS9TshBqo@ zJopJT*^G>#9RboLRcx~TO09C#eJvsX<~yn?-}bejKl}aEXU_Fm@@?qIEbd4 zAN#{sF1NivaV=>JW?Ddz zZ}49so`|d+&Lvy=&vrIT?fce!aJl+We?NW-5(jC+eGJ^1p5f-snb+<9q1qfCV>S^3_FXdaO{+(07wNJ(c}0r3eq1*dOts zu&GeI9Lm0-`;Sx&Zj`8OOM);B=%TZ9#P`LhooUi#rT6KGF{ zX%H?x;g2aEao$y46A@UO0q2mK~h-7Ga8E3!yfNuDk4KEQ}v$`b;k*_OJk{NFE zEc8{DJucN6P>o+6T+!WDq?uzfqO_VfUW(LxvH6j{D1>j{g~^Pgr=+24Do!2c*>>s7 z#QSY%Wv^Ymlj2_w@sa&__QTm?K-$>&tt*_`1KK{?(5EPBZkCR)aeT@7H~?tII!Mbv|%leC1JS{;5^M5pKU`|p-1 z(raUNcXA)LVc}Udf+_+sT^SrH&U(KWuLqx-m2cgfyPAnCGgs|;aRp(mK>5D0;ZT;V zKl&Z<@5(;8QOub73vi(`lGECW$pd))f@#K;hdy8}*pR0%ZJ?TPk#@BFZs@IMD}^qQ z;N#A{^T?~F{Cxz_A@*>XMVZ(Ognl1vV6DU-_n~4mxiCd)u?5{OlUp*;)VR?;&7KvA z6JLzXXMq(DjESnhjN8HvlASeZ2yJ!82x^Qlv+?ifV0mA8(h}j$M-hcL#LAGwk>UUHjsWHm4frr0ksq1EfV!#dV}`DYbOY5u zur0?-I~?tgHf;SyMbZ~WnMPi{^OaST_musO#<&+Go1gK- zw)Z4%+@pDpsc6r1j zyQdM$r2nu^!MHx>dJS3)L0h7&VO&s^kj0>*G_Dotq{)}!Hy?br7VQi8N35OmSjnYr z-|H>wdqRhvn}OVbu-jH*kD*AyO5mV+`E=S&wI}Cj&vWuP=#Xe~Dn{;m8~QEkJ2TyR zc`fXHRMF@byEnnV2(!Pe#@{UZkVLNgPLZypSmteKP1Fk3zawv^UI^9tvXwPTW|8el zPEk)+V5Puzwrr&xWkYz=2;>EjI=7zQb`op=d4aPTc|9G~+RQjHw&hGhP99*d*d*Bs zXbHx^N{0>M(F`3^BaxPCkfJVc{Z?wx3B*M`je$mf16I= z=})k?p!?8F>Y~mJsg>xPj;h(z<2BjQIiTnhZUWotM+R9Q5s7!;iWCQa5yX>m?g`7Q zsqU!+j&EKqa60~f4By{^_jBrgC-79OJzckQfgss}(}a^_EG^u{Pt3MS)XMEuDFXQNyV$M&_@tiu$}ftKKEIcEa+s&JR6F;K?Z|uJU~f+;y40DRX1)|2;j3M)*e?jtuv} z@q$^QE5pFDJMFIyg2#PxMriGT!X;sbTZ65X?G|;!kyfm*E6RHTaS!@jdoeoLSk~Mf%>YR5Am)d zZwwe+c07K6A^zou^vU-3_lbE0Y)y$eRVYKuW@Vgq26)_}3Gt$_Roa|9u6 z3up4j!{2(WofTSJ==;y)H}WX+a9P7&E#;ojJK%66xw{mY(iY|_W?Pw}=r)j}gEA)3 z;pFx{BMUDBCXXE8jX2j^(1rSgV^NGJ6DVUzWUUXLVGFd}O-?|9 zeb2g^ow@@Sqb2$}t^Mt@Ue`9(g|enENaC=w5ggc4MN!NGe2_^h_60P_rMIuHm6&-ur$B< z_-NnbAGIFnZDu?5?OtJn3dSO@^KUOMfcz3VbbqrR=!9W$f}fhJG!eEHfmV`L+1nE9 zPE~WlXBC@c&JZ=n@uw5*FhX#ua?$}$&6_VUPU#Uyfr+(x;C7GSRXwO0?(rYe`LmI#}baC{nF5^p{^3x&jy%p9Ttfja$Z=2fqgA-%_ zhxnSA54MSw@iR4CHVF0)&h3bd3-;X&i4^|_!?saS`g+esz_@!n?x73cmZ&3!-HZ!Rv|IAD9(ijB-X@Xjke0%*-dJ_mTJxx{@axXdxCd7a z`gFUb$OmwLx9i9Nt}dN3O&ANX{Stt$(*}GUSTM;F$#yNA^EX!vpIwg?NH*t8rpy`c z_Nj43O);1`Nn+N6(6;st`LJ?ko!RXBA}!E=-cg&#(DAgV06`_M87{s^tAL#-sUG1TGAM)j{Ink*rPBZBE=#Ipt}k zM=Z(GwmpHM?KP{m5y9{vgi2Wpqx`!eyCH9V=;}{ABX?h%jhKr;vqU#yzzvid1K~%m z^m}IZKZL+q1>B(TakplAsA0c&4y1BW z>6PvqaFY0rey$Y~EkCjr^qTs6TmR|HgTk$-02vl_rqMRN+=q0eLz4G=$-|?ap%F0a zJnZc$FV?EwsY2NRRgx*m!i-1W%0Hav=UTKA&C){dRCPYww-N=q+Xwz!eHoW@&Q_v$ zADn~A$BlmN1_Pxn*E$V4Cy6!xO9ub8A%mWGvEROUP_<#OTcnx^9Hd%s!ro7fJ;f?I z6&6lTNf$ys!U4+9F}mkM4%`q0+BCQxoXrXc(393i*bwhGnM&Uj-D#uGe{))ZEHIfb z(NyI=8S2;jiGL-8vp0ZM^JmjsZiC{V+8^e6ks-HJidXx?`wP|Mg@01E8EU7}K+80t zN}3q9s+9-s5F*>p#E-URcnwqpl* zi1Yo+s`CLQrRd#i9AmbucAiQ|sXGmTA1L^rAK)X4SYb)BN>a3 zRbFq^)=cs1EyeWTeF{)ZWUxl#*suNY?`r`9<~!cW^JfpyPL4PJoVFT-i% z>&N9YU}WjN+N10qY7|b;tHVO@iXb%p0n9cP7<+y4;Mco$23c(6%4h25-!49Pw*)(N zn|lo1eDL|)M(!^>6Fr;p_*qdIdxT)&3z^n8exv7qH@-N~H!Nx#QbZo4Y7TKOrg|U3 zL1+*?z5j*yWGVErc5SG>G7QI#k(~FV6)CB*Xq_cvK=J8m=I$Yy)7J%BTSaL_?}PBK zB?y+QCs)QM;^&LMw`*2q+EcB-I&HN$4neBcm!jWtN}O9^?NWd~-a1iC63i-5Q?-Xi zERQfvxfJ&*Y9wQ~gE6(Nl^T~Wew>8JmpeS^H9?K}oxM_)P)6Ofz5e$xQ#y?;OZ}UV zPxb>BGU9RGW*vtgz5lsNb=CjOf06gCF8RydCIF9D^9|#gQKFy2#Fvh24s>p$$Uf^t zDY$qHA7WY2I5ifFXx5g0S*`!z4Q{^moU z($cEhRV?=(h&GK#>qFfkP}kh0>1BUiDbz>GzoYW!>_Ooe&I8&m05QZ4Ng~d-lv^GK zzCD~&nSLAsjx9Jqi?HYr$od@C*+AL9bT6D>)cGciT|>z9JOuIo(DaVsd39aa@DXhvHM^xN(%1%M%W*UQ06KBf3_Xm81_;eh%WwJ?~8?R@FgX)iNxB)su1ue zSx(h|d$2d&oX9y16N0&vv$HH2i`gvWHXX&f@oLznc#2oZ7Voq%1)&1`?Jtt7cFggg zuZLIljRv_6-*2>w4Z1~wnZfXNXU$nF&Ve0@u{Q^B&=4sipa&(U4*E%1k{PSWd(br)wq?a3&l zI+Zn5^eGRn0Ml>e>7jSN~rxY7Z<_HlJf&FVV9_+kV&sEd0sV0zD;k+5j*C z`+tkz$%~L%>mZj(t-_5L1O4P}hqj9??Kinb5{({Av2UphC~T&3#e3Xrfh*|<3~yZ{ zYCZ$Ct&?$Nblm#P{Ewa#o?yKWfD3QtNQGFIxs>PypwlX8E|$zH!vNdg4^vL=06lm) zeiRf1?YPnh=GQ|c`H-nZw%dCCqiTP1>aK+cb@=$SD`MS+p)r24S}GNA+N*k>_mEuj z#u5tkoTv?v4jb=ekV7Yazp55d8le9Z%nUYh8o0sBIk#mdTw@D9$qUYM6^p~1F68Sq z@SYAlh-Y?!lIgn^+ok@-q+qMi=&A)Hz}F-YyKucoTECR$yKo$6!<=3BsB|0oGkMiN z&^$!|fJX+KW0w-M7WcCK6VE9uS{LcR$e}tzrAKBfQ7#SM*#_=(kZpdj>yPi>LNjHh zx|0vG#ZWj-ki(E8mbwV+n<qCP0I`hPy#2et>;s?& zSZ6+tb9*Q=w!)Nk=8v0adA$-x zj6mvUq!yY2w2l2^7csP!Vgrb{H7}4v!A<87XMh|0K$cr$R@M$jqZ10Bw<8j>o+d=U zM5Ku1UY#oiyc-{COWAx5h=@0Gh@(`_6;zVd?G))!_^a1Q#CGVB`J=`$S1=*99f7Wi@qv8MdgSfC z7vcXixSuaF?NC-jhzj9TaD&~2nG?mci9o9#J9CKiwYNyRkajkFPoUXO2#f`kq%LsE zGlL3QNiem;tUX{CtR$}H2-z&&H{4GLf~G=*N_7KzXOa}5#p194E{cc0j#UAGc7*fo zDUqHO`X0%`BVi2wVRLoQ_IVn+>yO;&@2}Snm&@s1esP0f@b}u=d!5 zb^&Q?aJ%r%hz-*7;cH&bPn7S$jySeYpqK7o?h&tN%tEi*TeiT@^`01${C;r*wo|8- z9eqlv%phX6glz7&XzfVQ04HDW4CC0Deh7R9Rw#tIT@TXrRrMIwid+7~{htyi>wlVc zvmr*oLe4^_&f6M{+y4FJ=WMBCLq%T<-Y#5B9y;AfU(Bvta(#va7{p(@n`;@oFHWwZ zEoygaUwm|lQtU>Z;7HMNblx;nG5fSlbWxGeYy|4&6|xOuDI*V5s<|-#A{?^LFOzX_ zk@SF-*B(y?Q)DCkm0(IOJ0@FtKpLpSbKlP<7L04)?g$z1rv|aD756ZS{ zGfcwpAY#l3bGTBV1US9as(;HjnEIa|mvx+N6f>lSjWW#cP94@co_?3RccypPihO+Z zair%CHk))}XY@gl((k%8F-9X)s1u!GSL)QJ7STp-jreG9=|JqWjV>@p5hD$!6dN+M zrR3AtAcKY*E6K_@)nSWOKZ*mX{h90~L{!jWj;X#{#Y0E?W^^1v+DJ7*)LV zWu7LIT@HDEXvl|EUoK|aJYr~Hyr&Pr&W*02+6pYVgO?lD-fWvUcT7cGl+5yayrA|E z54SH$agKrKbSsinJxUoI9dm8h60#5Qnh`l}5-bl$UE=Uj*qO07Xjmh21_0W2Q=ooj zMwEiQ`!s)K;gR#Se5vw$8^&CK{25uPV; zD^{mGuQqJzW&gOaHW!uJ@9gTWRWz^+>p=3KUhRt>d!mGq4?5M*C$vRj=^Qwx9dFQa zs-WdYK28K;@l_l&pXUBgQ@$Nq+kTNAEUTt$>tzDF;QGDGTDZN|6>r~yCYfQt{qq<+ z<$f9Gp$JzWQ;y215{n9#<6yf@CM|qvd(06XKt)}#P?7)1dH=pSEpMJ8L!yo3oIqimkw4zcZ+j-O0FFqRyi6C%{qeBOBG zY6SGfA!G_f#ugDMbqYp+h1qeZI{oxV12?X{WQZ!5jll*?H9_#>5Lo+^ zt}$q%^J1pu*X`CN9`QT7^0=N=$oq0eA+pdqr(;mwWgqxj57O^>yOV4N>yOoV)B&V@7dx^4i0rNU z%lIgK#^A*b?QKnJV=-`)TR5)-@D%9z_a-@TAzIw{(CWQ|g)YziCnD8+AE=}zjX;@6fYw2wV1&&l+fXy6|R&|X>dr&s;a;c=zN)+`vaQ&vJ- znWI)?%sa8&F1T<{c-A&}18)d*SzdIu$9X3A>*@zH80~vrNQTqT0BsmN)?9dXhCvBa z67f|0GgtUcL#wxMa}CO)B8r#^Z|Thn8wc+Ac83lR7X>{pJ zCQ}YJ3@O$IKsi}-6cq56i*?8{o#*cGC)D4%*QV5efnHl`W}3DtN62Yb8rW+0nDC{B zapqUmn z-K9FY4H;2{7=~r18eUx)QMt(z_rs1^TT^DRxZdtlF2IRXC@G)a7ivlSrS{$@pUmA4 z^}Xucfno@iWXPloUAjZziVXU++cv3Ynlnt6R<L# z{ikxlNjPcbYCbV-RQ?a_Ox_gM|=oE|WY)%LK zoI+OUTqV>$%_$2cZ(h&mme#@$6yE1;uY(x`eUMB?9f%jQ$AZ>W;LXb%K%27MGngtb zxVmGHj|J~bzPRr(b*w8Ha}^97$11(XsMYH`4vULeGlHQ1FuR-V+_KY@-( zMKFtI+F_`aVbKIm6akp=12F>Y%v?3m`Sf=6SuI?iM@TpZxog70y=3~y_?!6$5}C~u zeK_knOZXHB>{ z!{r6_Hu%^k%%G#h>mOFP9M6pDXM19iO1@Bu9J@oWa-s3@J(b@Kkgfk=+iHz}lzSDo z=0Q?~cN5;*X%|YB+jZ{{^KPzuQycS{zt{!Q8V1q(`)g8yx18*3mQ3oJHY=HFXc!zh zo_pUh^jp)kTevp2xt(rs1U1qyw(5OZ`b$Lf{A$$pAF4yngduFPv_&*uo;z%%DSx*nG$)B6cZg= zE-nYF>#aRo@y89F>J`LqLRr(cQ1ui3xCAr&-Pz;n$kxc3f9>zXc5QmGr46V|EOohU zwKFF|b;C!UzOQQ9UUnl^+36vVLl%^J^vasVH*Xw^f`HtA36y$vHXgIWrJ;z3JrVDu zz58s%zt?Z(u|n)^lz}VF1YJgoH}}88BSb_dOS# zHa-vLJz=GlcIiSzTiJCm+i;_akrOaoWfOE%U+N<@YVr5;U$zIfOnV(z%$OHR#Au0fIKl zR-|_kj3R8Jm!-@C0fdtf>N+jY-hRIvl!|5Jjk?7Fb8I6pExBY#wA32&OYaLPFrgq zBuy{Q0ZbN*xe}?~*{JSK;cA+MSOKIO?x4Bq3A4cceNg9DV*L0j8`>;cmnUL(^XpNp zD-V;pDk3{Z96L&NAw;$`y4l1Bj7}hUv2yh0zX<~p6fhbH?+`rrj1R8Y!=v#Rb2T;L zLMKeMxNNg#SGbY}P88v_;2c~P^RPo($7t@g?wF|1zh_Mx{*=9Z+dpaF5sG$~(iBfp zZlRt{G~gFY{udW39^t@NsC-|TG%T0YXJk4DtvR*VPdIYJn?KWuWh( zvMp7*KEz|#P~yB%qV(5q-qwxt75QQqCa(86w<5B(9SYVbbi79(0h}}lf93xxU@Z!R z3{$cu&_r@q$|F~XDd*$ZXkCqj16VxfMqoaJQ`h%vT$a2`;xWAoK%aF(r~>H>PKAIY zuby$6kF3uL7H8IaL6IR}R9uJDtrfsXRd<1{*~tL_99Ke?>5R3s=Wz6?ewvX}n)jPW zlQ_XmNag~0tTmnCGO7W4dpJa#ydu7B8@zGbvu zRN-3oCxrd{pJ6G#vHA^+G!$;pkwaDtzpBlW%wM5^aRr+)9bR}G^CrB4CsCLdq{&Vuj?97b-nAD$4QNIlr-R@A(=1a^ zG205!BVaNP+f+v5fEA@E1AQOPp4@{6)GEI>JfsB@Wr-*CZFm=1(>hr>T`MmX02wX>I#k zw$d6DUz!7Jm`d{Ns)>*u$Wt(+7D-(07MiEgU#geb6A4?#xGapAm&j0nLJv0IyG+fG z_d9#P#J@6V)`Tx$NZtXxK8i;WbRftSGtky-Bcwa$EZA;A&5gx!-=;s1``tcH9DyPb zYis;>>_vhwZwOhaBb^%s^k?ewqm_l>(^vD;qlQ%qA*>w1OSDo7ivv?&JeZ9@cJwXFmAwV zggy&7ofeA88Fg8+@j=+Uq?+HCE`OW`FVN4oD3^#LsaT{W8*znPs_s$5;uq|@LtZC{ z;i!uu*2itzj0t~3v^D(eUtPBgXS4<-RofjtKALUS!a&~nM~rqI!hnwH+D`8Y<8tB? z-pF+)WV`m>(ph#FzQ7ln=kfq26F^{18#qKNtnI)+#CoTK9$XkOZ-`$pthUskUa-QO$@9p_^HrfCQZwhsT0V(44)|;FqP%afe*sst z+|eJ?4>L&LzGfj!{>F#Q;)=r`^q(jLpmQZ5q~q5$Qc`LOxD2gReTYEZdNW7%gNcd4 zOraTjRaJUs5wNWQ+8q@o{T?Bc5GEw&>X7J6U`_4PFm zFj}Kj_|~A3T{&vsezwV&8j&UlM%%4-IaWP+yd+-JYjUeq7NUlR4V$)^cC5yEtHHxu z|7(45?Ax%UasLgV4JgN&p$D-1mVw?g_ zr@#i{G<=u7s!D-H-H@Q7tn5E1_N9xHdd5!|-+V_Rd#B!T#WavQZ8PJbn+-edGnb-y z3KL7-;!^`i#z~Pn<@^Ge9pQWcKJgeSZ81a{AUtrZYUs8n(_FEW?3oAk*fDS)I%a~P z(v_#*1C|rn9_a{o?y$f2IqI%=eDRa}!`zC^WFlnPZ@($>z$-a_I#&!MmhRDQZqWMc zL?lG+cq$7(qi*W|<4C-;1@BN_3!K$4QePk9BrlhV%ezm*uP&UYdYVBxN7>Ag|5^J| z$5?S)d6C~VR~7ia8(t5;^9HG$jYi^T#I&y``Wa(-VDDoo!f{J7Yyr5AY0w!#0$b}K zre^gjGq`2wv}Nt(7KDq<+JWdn-j{oz*K(cq7oJ%GrS8-)GD}-YAR05GVLe&aZMtaT z0wf>$9`)}%n&Ae{XX>50PjC-UMB^H|!c0!^eQRThYnQcp04IGKaNl%{$6)xv1V_;xX$bckm!dkqDXQu(Em-scJK6 zKc!;a@h@6VoEUP)>^F_8oAShx7X$U!lN>Q#@ZH&nc;*k>E3XH;lC(1*Dl@7paC-Cq ztrIeIyiVU*XovRn>Q>)>+yXRbGQUWT6otJ_Ho&SNO*&!>d(8Rj zKl>Sf0xmwoL3br>ugKvyXqT|6C8p<2v*UX?VxYm(u~gB4xSU_iK99)Vi4C?XG?(}Z z!5ZEzzsZ;(HG(tK!Lp}Z3eJK$ROdv4-wNBuN z5)fX?8meyapVknKn-1wW@MT(hGl-`!ITM`Xf#f9{nS?cGy{HTK9s(qawN=m%jhqW~ zQwRp@36gG?FA-;pK}`GQsXioGH?zMJ`$mKaY-+PJXR zlb3$-JB;9oFZQNENV&&2{NUiFipls%kQ(prSwIAM_Uh`ST%Mh|1yZ}BnX4|-5~aU&}!K9#C^Yo zZRMUR+(c3HiyBUcQ``Ub01`nkU5ZUxtIlL%Nm=|c1;RKn-)$QP$eNrgk@e7M?(;Xl zPk+~M6tFP&S3Q6}QVvl?18cF35PTQqyck^5&Uveryey@*UWwn&d{}kL`c&zjT};UD zA;!qLVcg>6)RcPbHc$RfxYU_$*0L`SK0olCqkjJ{_RY->GHh4 z_>^Z-cR|0Q@JS_UP=CX1TSCDNjN?p_9GN3>Zxg;;-~te3@w8~*?xv64A(rs&`Ca}D znkx>XT|OATI%>=pr6856B*m1v514>OW0?PUy;a1c!rZGlFn?Lo|EX5}cq8s?8Cuf< zocmkU){O+?FuI_8gB32cY6|Xl?yBx?Bfy-w1m>6!Fk<2IcBT-cg3s_R18JX~c!RZd zcQ{<Fi)`*Bu^as50sU*Y6o71tkz_OT=zulJ81=HDbY1YK$?Q36?KQe2}p>Wx1JX@Rt zcBFpSnCmK8$}Jz0F%CVMN0enrnq_H8e}ilZ)x8VMz72`NZE|kAo{&x~YwlP-K2Qbf zw*rPZzVw^UIvGdvklFeX(BD@u!PT;2IW?uX{&SVZ)>>~ zBh3DvMXmQcq=FQ1jlzc?6n$p_+(2?v2y!)h?i~HPDZLFnyq9|mz*ch$*7%{V^6d&I zP(gKN*o$5XlMHK|uX}AUBr_NSOj0hPpW*y}|NB5dfaYZXWeadAZJSHkOwvBIUJo9> zUCiZk3?(`BYnBU;B_lc(O4Qg=0+v+K$LtiC)}B;hwzlaPb86PX6*R@qaz@&hyrOE~ z_Cc>QU}-NltcL02XRLnoS-$b!zmuk)Mu{dVn+y~713Ta3-E)k=t~5{I`TBa=VHkeZ_FwmDfjKVs zwbzUgf4~@)Bqd8|?>P5cFxu%8;*gdm*6I(w>*f)s&gEFl)gskf6DyV)@T4wMv0!M@ zTk>D(hGXhSY248k^}F}9qw+W>Dn-=ij^4h8u}~@4ChDh^`PiL`&3JBK|JmlfbLw!B zaEPA05Ifm!9n)DkuDCknD*SzQPaxHM>`E_Z8PQ zjny#O1|QQRP7pRll&oW>Qx_My8a%MEQZ@JiCvnKrAz8T$t4QR7Q6(2+0|8rnmDH?F zoi5C}6;eCL{3ezhiHC#jm2eT3h|Q4d%h4UulwLtk6Ey!;2v%n-a*1P8uN;1rYCaxcx~>>tK^nWg-yiOQB5SQb^9hH=xc72< z=y@2&b+e-9u%F|xGtl93qRg1KJYCGrSe`Y;iE2Xlh;*p&!CS6TrQPjGDD?O3E1u1P zK&)h`(}3gmc~S!|UpQhBS3Ovi31n_%fgJv`hkrLqbi(jLdO^bxms;p@+h0Re^zsYf9=?uIc(BGw)n6?Nc+6yNni7|Ut zHi%|Q#{Jy@HF<=S_H+*9ic#GbA2?E(a|fJWvNLK*v6<4?{dUh=(%$#&Yk*{taFO)% zbiSw^pk8YT`0@t_1<3|zM;!oa!qL&urB}=)ltTAF4zbksXe}=!A;of>f3Z4o6Ahm)mK%!on+^}pYC)|uX`VK}nDM%4bdcO4?$`Z}0 z4@pz;TlF0%;xAve*_d>8rNYUnGhI^I!Y9%5u!Gi$uJIo`aabfjq=A9tAte7Buh@+nzJemA#vGRdFhPoHhfNQmr1gju7YzjQKI4&+6dZGE)oHc0wfpP*AL-1R zbbSA~7)<)hES!56Nbs9+l{&$O;lC2Z7t@3OZQvs=Z%O) zRAC|ENkiX*!%O$A-(`~`P)L-GYX<9)g;oG35Xg696J(2mk0Pc`k>&lQuwwCIUuv0U zS6FMUxd^RXu4F9F&9KVb5H;*^`0o{zI|+KQ;wP#&joqlUF5Y4@3M}~?0iHyFEvmo_ zHtK1xfl8i1n5?D1N-UD;mATSV^~ zeo#rD=xpM}<=`ftCUv)w_hQP5-E%1Aajkm0sJ#u~%`$vR$`*u;sr70v% zy8#6Wd9z&Sj{(pD#x2L0{&|q;{#vNJJ$UYm3A?wzt13=`hBT2LeM@Y3PkMMFwl3RG za>DIi|J1gYBw!j<+!L6Up#P1DS9KMkPb6OwL`k(PN&84hyX<0}Li-{seOLW$nAsw3 zpTHC=e%a%oGcX(Q*TrC;k?2S0CAlkA z0WXhujx3>??$_^-O-t9B#J7VSuS2(Ob0Y^ZHeQdtAY<)F$i;EVh&i^y_-d+yHMYTLZ;U=ys z%ut5}u$lp=31@kBZoH(daqdScyS-F zTE{VNG+(P`f9FKwrWin0V4k#sOb`c3-l8eFX!448E%TuFND>OGry7Xu^?wI*e{qzZ9YCK zm!~-vv__Khj`>=B9|_T)fg4Iz*78Ku?Zp&F&Hx$|=;};5@4(}|b4LshvBRg~ptCr% zyI0qohxN*}qVfqqgiy2gxB+NQUOpkAx<%7F>UokVco~NIrdh$Nlb122J#zvX z^95bxquX)#b`Vh;2xAfPhZ8+uqr5S5gWvGA2i*)J=MSnaa2)o~VUJ8USK&C41_Oov zJ3YUvJefS#w(AzFh0y!lF-hT?cbFnJuDFio3HIF%{dt&FV=5n&Pu75JFBjUvykT3+ zth-gB1TbOBse?yB%788Yqk^?-rv6Ub_x0XaXOUvJ!r=joMP`y%o%wv+jy*z=tGSeL zN+TzLsZ^-ma0m+43T5x_?<>fpP1H5$(j2zreZkKLTpQK%^M%M(^Z>$67j8Ug^FE)K zD@w^6nNEdJh8e1(Mnw`f=a!75aa-$!GOM{eM`=w^ui-1qZwN5Lff(+(ST`MaH{uo8 ziZ@uAIiU`5n-dIVtp$0=`m1OB*g+LciQm6BaM~h7BD1vjZ9;|#v#wvN$h$;Qns~X}zAClTT)AYqdRs zbA$$Dn*HFO$fnmB>g-z^E$7+63k*|kf1O&aCPQ^DqWkeBC6fFn;mu~13L7CC z^`(LLq-hb|69NkVKMInLN~E#rb^}|W`y^JZFv8M%B8X?ln8lvDs-_;herQCxZl0YW!Q^MmmS7&W0;?Yl-Mux4&!DtD9@nD+z7Ah{9Wl{+>nRm1(z zQ~6O_o8{eUB>>7_cRgWO{VlO-#Y@&6)c=tpm9g>5i#epumEtG&MkaJDVCz)%8Pfvj zOz2m)kEId4Y||o@lb@38wDMm`q~GKay%;0ZyJB=xXrHy|OJjP(@$D!FJV7&(R6>8q zY#U2*Mrd=#qwgltf$yg;Pp+#}6#UbP7p&iV93!VqP0yvt3r7>6`Yd~Hl%bO5 zc;;zU7uUs6F;ty~Qk^U2a0|1g@<~X@N;uYD7a2K$=28Ts2Z<;Zvf<`k6`DxAs@E|S zJzwaWEJG^~yo=49VHXTZ0om}J_c#=(ac8OY59uWQtSEF9DK-P?hX)emZO;%XF0$j) z)+;H}t&rR`Zb(wK)5ZwoN{OH!ot+cf2+l)GxRNoGNBGVqGjZwT2zDLlS|06Dqp<7H z)o-+eM;^>7euxnleZwNNbo`A#vC>`FHZ8aIv=_=WB*vnfKN!a zOlQ`eeINgSUfD-JiF6fFcFS zp(W!|l!_#w*?XH$@Gs{3RjjSM@nPnNZuJtWm zW)+T!7B5Dgv#MXuNW$n<2cOmtE3d^rT;NGZoZ&W@YE>?8HpYMi%84S9(}ucg^EA?) z)v6%iU)TUpkDi`CJ?{n>#gJOHV3CmbLZhLfz5J#UiYh1|$zk1;7ypp%l$Ug!%JwyC zTU)KnhW5Vl+m%KOFJV@JQ?)qOH$QqUf&TGB)&hWc{% z_G{eCtg|&1ow}w+gcIG!4rTrgzH{n(kI*mMrpmE-ml@jbiVpK9iQslNl$GG|K8ULa z`+Ty_33Akjwt)9G&$|gKr-NY_2LIwhgXq!`tyZ#7!E%Ira)nlnB-}GvpR3!v zy`D7xu;r1kQQ8h&vsP^fbI@e4Hqv(dP=mY58nv7kdV~%3VawZ44@{+qcrv3Y2k$ro zx&G-8Vum_BCLtXcpGO5ImSaq6y{v2nKhP%*;oTTLELJPh$@ z8eQy)jYk$cpdhDViGr2+DSeJ#oFyOL6is}7eZ3k1O`@|)i#d}wRIv&;g}a~E>3lA_ zH8-^W9MVayb5Vs{yz#MYf$b?_I*s3?+pyQw?*?dhS{V1%&$9?D0GBvP8UYN90$gmi z|3YA1n<7hs0P{`~AFGDIb8Icn^fAY?VBNr!xP?I<~Ax6 z(Vm;_gif2o1=7k=VSkh)@T$znzBM|bHS`FE0?boT;V6o=anK|ernr>ejfd&ugrjCR z=HM|X`NAa4DfH_Q^g60ShlH}S@8k3*&J^I2@KqQ))(#jA3m55(fAM-l14bEE^iH2v zjPF+a7*QsN=e3bP5!GVw5P)0Z;I?12Ek^*&wy6)b)QSv^XfQX)hvnO~c=L~79gckz zf?>U3h9axxcI|WdqLIhMwf1!8l}Z|Qo3l~cby)t+OT0pJymL~n&?*wON2 zL5wexh{_sT)UX8%hi$Q#F@NMwFkxBH?^qsV3!-X<)#@yj3VVOawO71x$9v`u5gyvX zr?Wxha!5wwy1v@VhksxrzPN@)+R}HkIth00rF`*>du zS~?CYrN=?RA<2Qv@0l;a?z}EfkYQD2p5XX%X7VzxesB%b82qKSZSYLWDdtqk;J|{ z5vxZHP*?B~7>2eYuxPu+0I}?E=YH!MxXoYv%pY+YjVYeWi)uHfDIP3_-uQXdA87U* zMkDoY)ly#VD4T~O3$4sJ52m^>q-WG*ct|62m?$zO^L!m}1D5c|lv#qUw4}koity`e z%x^`>rwFlRS7%{umk>VIZE2vg?ST;J`!nT<%JeJCB&6k11X+Bo5&Ad|ZipGb@Yb~a z;3IC?pK$6-m$D_Ms5=?$j?*FCX-U`#Z;Hk&hBip^_}fHSnkB~BeQ@ScCfo<`9F1J1 zyPSOp9!lH~_SVQwZ)1rQk?J|iApqyyw2)n#bYSq+MdY!|(c+=? zv3#g94Y@XFz;U0dz3R!qv)>nXs25d~u^gDXyBH1JjR{F2_FfZdtx$%y!(pA?iP(vf zF$vHWFjHHBzeyA;uRkj68&UM!`~2I(j}u!kh~?+pO%Gd*7WOM^m>03 z6F8D2JCBZd&s##@{!%W(7NymM8stbgyz=mCe+W7Cy`n$8lG|xsuPMoRB#sP1*N50H z7GQ6fz(1B?f{iBmMeKzRU$r(RZV->b6fyOn`9S>V(Iv`CD46mKitWC)u8Z=HGKDZdEeo!x)s_!NfGtaK8@7w^0 ze)X~Fc+L1UY}@#X7^w)yFzpzNrax-io(%rO2PE1kOfdt+&)BD3ThP*=iNuiGe4_13 z;!RY~QU@?a?qKz=e8%EbMj)GlDr;OEAmmQrAW_EyJF6PUaL*8n%}_f`JMJS(-L(X0 z@$oVJ)Xc_thHX+eatp1y9Sjhlw3mD^_@eF(34WpeFn`A)AGL#frd;72C*M%yB#JJu z6Ykv-qzVk$_DRCQPYN65yNZy{eD(svzT%6#T_SPSfZS6LX0Bvcv2}|+j*yJ`!AM4= zN-xXO0ycRbVhoO3RSd{qdD{Nc$-J5uMjPfA$}?_XzwvHIiwa>}o;B5AYLrMH7F3~# zKyZjH0;N#RZ!|An3D&%4zN1=8`p@%!YADMXSTT zbNeS^BjBM7AzCEbQT%U3)rbR`;y0*70>ZFWE2j5=C};^%t60~ok%3;QB-b(ja2p;oTtT+F^i4u&lL*plkUQCfZ5gPrgC3#NT*0-0UaXKUP2B6Pv#0f_`9kEgM3Y zMGXxetlnIC?!3S(W;~aRYGxE*Kix$Z%zHOLQB&F+>p!Ro%l)vVKCu#8WaIKI70ifh zu<3t&uvk@CK&`KcvNTVJqS8Fb%af#D*`Kixpu(W;=6jao2{f?4OP0+Y5{R^?{uj*= z_#|Q%!i`@Ic+Xm~n3LsB^6%eKz(zB4(2ksy{k}42ZK%YNy{ek9t3PnxtAH}`EZmwM zzEmF%(wLe}hjh}1Te0TpH}ZVFvnInB0y91MkvUG&_fPLgo9B3#;jT`+s+tI^S_GYK z4p%@@amSPDo2a$-@1^QK2xa9lSi<>q7nOU2fSynZs)|DZ4)A3M<4!{A1W z9UkRbjW?8$#hlYi5M_eA=RZ)lNrmRPrV+uF&ojz3)m(EOp+)|TTJaJZPna(hO z0|lwF{=$o#*1@FlgUz?{@2=ypH`wQn^`v}%n#tMFJo0F;zc`P(sa`&|HAr!jJby$Z z86Wb+pP*$@$yk3QiwHB7UGFSXQD8-4pbvNWFtd%$kHiA zGDd59D?4bNM=l4|-|eQhCx_)6V{Ms7KE*%qee#P*aKAeU#YboL#5Q6o<;%z_ZiwF{ZQ)A-Vul1UxDB3_E=%#>`0QW0SpYs@2!KcvO9t0Xyc87&}o!-GQlYwHWoB zpQP2vUdZLQ~;OT7N?pI82U|VR^*N#a>`I=0+JF+CGiD>{oW>0zCbfJ6UKA zno!;_&|mGsMI$z%=i!waP)E*0)*PKG99vAkdN=66g>ACd9ogP#%-s5I z$ORtk(;x4doD|#5cM~&*)J7S;1>3N%NbP$Mni{h>yj>FU5BrAN2kOx#E>l`>IMFcZ z#4^xxav)g@$DNiX0T6}P*%atMnHZAE$F>}j0* zGEaWgNk`=49&f;702xt^A(>g)SJ(AOeN;e?x; ziE6wgN+2;`VY;k0YHf_Mj2nkp7bZFo!e$}=c&c^+51~ReFP{Zr16Z#w(6-dRxQHGm zlfm3&4t_j8KH4tA}KgrJV zncp+?#InW4@F(C+<4x^`z-8F^&qi_^$IZ1O z1glNH*)dvX6i)Yh6JakKaR9o{(WnKH~#0z5zEK&RKKD+`G zE5uf88No#52I59XtL;S(MviT_fOlZND(S`U|Hs==UTl`AiwS2S^3bLVq%j8(IK#r8 z2w(pP1;rv8TTn%A(4l7BYePO&JoFo2cmlDIsT1vU0LE+@#BWK5Y0wfOM1T!B^38wD!*3&Du9FG1`H zhMb-vtWFH!DgpdPm^C{6JFCEo37`?&s{A?UMEx(*ZN%B~1InOhx{e>lW~yZAQ-mXl zY!Fl@{goRx(h>|#5E4znI#dxqysKSAKM_=_yqZ^)dj#|C$u0X&G0E+Ym&}tG`+~(% zq;7>jRq$`70jrHGv;4V7ztYEOFg873{AY+Zi6iw#_T{R5A>)>-}h0=O~D+@$xx_yqMTtzSKN77Pp z#Wh|*E_8~I_};(zMyFfGoUmt&H+VXws4V16hp-eL&NGT8}n%X)h;b>mk3Cl4{M=x0Qm+G%t*gRT`TZ-mSo_RT$Y zx_(MUJfO6Alq%FK-Ov=j=h*UGbFdC|-pHLVx&-;$53@=t<)vwRGcF$$hVZ>&uybNy zv=@~|lXvZnT;f;B#(eQ`hgfk7o(W*6yMUQaS@y=(YFf12CYt$Vj4uMXf2Ig*M3Z6E&hg`1wglP*%Fx=+}FL+NgQ=CgZQQ z`T#e@LjofzZ0;=`QeB^`UA4Yv1KJ-JE4lM*% zBx;GX%_0m!xgBWks-`LhC?52^Jk!h!_<|ZJIZCQeHWo7S3k=x4ROL=w*Z|8Tr-G3o z_iVs#8vkmO!CJ9Q+N2Af!4`SC*d&b%;#phrrZR>?wQDSb3RTWI#a9w$#@{V`a?23a zfq+eY^(rpgdK)W+rSrWxuy);2^bQ+M>Q4yF|IapAyVmV_VHsm06|WQ!OmtzGTWo={ z&9-c*$N^fZ^VF#@uIRbl_}9TWO;grZxUn3ZsdcYq_r4s=pDeCRYVI(1`0nPzNycZ~ zQsmru)vp6V(^JItf^BC|dZ6lBYe;+Qt367FD^l>EPIS9gErS<`%=*r=uGcU_Q$DT< z!+jx+5zYK#sx&{z9GOMgR!Z?+dp3;!*xw_&e7R|HKnbHksTi+>F^RsY z1_cjG+609p@u4j^W@aU3j78-dzxcEGZT5^iY{@yR zY7baVEks-&CN_{wn`VTl<=T)|ie@pmkr;zHF5!r!`_Z3Qx4hSB@Gg!`mBH-?2NO5O z4OUjwdwMaW*b~aKGjV^|o+ac^rLlecO= z5I5PGOihIcb$e2%iWxgH8W>0$8vV&9BSft}r>QpG_x%-)^kj=a4fcF*ou*}@AiN}k zf7U6%5*8qmW%FKzOxDhfXXdU!w*HcB<(LSn%b<}(%fgmn0i`|x>7U4p-XefWHNKX! zZ>zu=BcU}}&W_|IBray4cQ=j3rqN)P;P6Tg#fr%BuRQ2m(R3yeZsVBT_5@#=e(0bE z%2bQTBLlu8&)#5CGo<<>%3b^-csiU4Y5jB~Y{5anv_fP^{|)VX5eF&KbSeQ~I_=*- zZOan568U<1h_w02o%7PbP#Q{2XuJ=oY)$^;Qs&~~>5X=*>OR*z+e2hakP(q5;raKW zPfpt8RZOR7$m$atE&PCmDy|>MgSpC5k6VS>KE|#ZNP(kw6rYURROV-cpbIQqp-N1OvrjEiSQq z-4}z1X7P}8i4f-?i*Q?ccBQD6AX5kK3NBsiB2DJ*rW;9im1Bd2g+!&5GzilnUON>$ z3jV=|D1S-D^`a4Q3gTR$;Ywa2oYxwU#y#dT`x=TXeNG!6=lw!T?_^OC@Yf1Fd}e z@sj<Q?~M72fJCX9@{VO&C<71ryum%TDEB)<7F#n#JNVR47L~HC z(ejw(uj?0HU2Bs_!{I_WZQ%*J&J_TUY%7*AC}e@3^n1@ZQrv2o5rg4m>I~ty2Ij0e z$q;ZYAC1D&=Mz>d&o7&;cE_?4!!GOO_3|KQ$NQhh1l^V6b71^qWIfKR7lgPTTSXzX$X+GzC87iHTkfmTqJtF$Wl~@ zT=2#_`QN|&jB5InVZWk{Ua0NHA7wGXMuR~x-ubVOQ~r5U7s(rEsAhuvIRgLrM9DWo>di595VwbW9}vzU0NmmE+Nn=6%#6@Cco`rvQ(Hn4BnmC&TvMV2|oYNj7C-Twajy_L^w!nj7 z()OQ6u=o{@yF-(Qv~AhvOxBTu!ry1PYdyVlVN9W*`=SfK_>cRFX&TrDsvs;;RHhQ@ zKt^5?42!0d3LPE>8yI{8EKan8!nAt|<-LIW7G6Y2%z8g1fsH6V74$f2Ry2cjivtTq)EZG&h>CA`L|D2qH5nuKPW-0VHqNAd z>zczY7bs1+dTqhA+TL_=(H)BefdGKzM!ha*OTAU%ZV)7Mef+3Y>)Cfih!Q3ZscmPn zf3LiUh2fS=m@K7AfRO=B*OKYl_T}f8TPmq)*+?3MB^#jcAA&%z5|UjlB%$Y{sfzb` zt5D9fuX-Qok4s{g6>{3G3KI+f&>8j5AQN6n`zqO?&ENOxs9@d~S1ib!+gO#y_|>S8 zR^2+KaBOs-MYtmm3r8gWms++$)}-%z2D-Rc?8W9~htB>;*+2MW(tFNLF&-eYF(}VV zNKtB{f&~L2BrI~#%$ittTh>Kso7X*olZmVyJnjyx@@cBub@Zz{8Uve^BT~Zhmp;k1 zH4tLz%mEVU7`)-{xh*5X1D_I&n>f||uhsD=c4y@$qpR3nKdN_MwO)K@2mz0K0}4Ab zxBr#gXP!BV^~>V|in|^YQQOCxI(rE(2WWEI(Jw;WsVu%qioVF}cng=YrTP-uLw_hf zXmRe2=1cR}B6RZcqM%4|if196NejZm)&wG~H-tF$PhoEFH}R62$xt(Xz+(nMl7l1H zo@(CuG|r*SspavdmCirfnXjY zJw^Q2`(Eg*&MeB=_gm_KMXh;dXQvhcHr|hr4fJ~!`EL4hIyvdo`@(?y_uo5cBAK_( zT?=t^FW_m8vViG*t##hyS;!K}>Z)rTd$30tYTn+CADGVCdzjPC}HWlRy z&+Sy;KbBtaip#TeMqZb^@^7=ajWdAd)t^6Rr5gX`ny|tV=}2+$3AYVoJLW?rCcA8R zDAt8p3=0>nU zLndT3T_m)8+wZ4SlDm6N$`JLVdR^ayus`f>P_jfTzCqgoTGTYwo6<-6a>F%j6>BHy z`ca75mHEx3{?Un;Uy~P8L0SmDO-(c}np(H39*kkufpOhv-O~o)oB+#J$!84a zr_+{gjvUOlO3)C<@iUId)}dYd$u)p3jXLboZ)i9Xw~i!>)*oCSs|LX`1Lk}cuxv4Kb7S^VQF<)TK=LpShA_S!2^~Be+TiM6@<_;Yb)-xjzhU3aF+@t6 zFTTTNjVSPzk_n?eB$Vkr@5O!q^QLumNnpF0!t9T-jqP>?kB!;6u9ZlH{7b_Ym9c75 z`N3v-OuWwGZgwUBrugDQIw>g$0IeUTS{b3SA&F~IP#h|+nT?nc5LlB!Pam!^Nd#^&2k#OrG?*_y_3{G|a866id3Nhlhq}C;|AUr3gtz|LBSChhRrn zG>yLXfkS@9uWqi!=0Y_9&A&JC!!m3};x=uoCCau*hOh)cKK^UsbthEH^GEb@0gP^Zhp4mmE)9d|p8a zr1X_z>^rSOYKGR=vr63)x{_;Unr`cyvuWRNZZ;Vu;-L0|Ce~>(ar-t#@T&kF6A__{%?D~49m_@OxCA!R}DwschxyjF5pU`tq(v#^X zTrxTlol1z&HRY9zIrM&gb@`p=CDTS-w4U!RU0p$Ld1-<(>LA+7m?`2+QX?asn=^jp zW?!Z;SzbVF)ZmzJKPv6zMr*SKUWxAF9WHPy1i)FDL>X409N>3z&2Lwm7pvdV2bZ&+)$jA5vdw z9PPr!(L+~f?~Gn>UbC^ek!9iwmd3uT5v&wnE$n?y7|7nl_1IQzJc+$TlUI52V`xyS z4h_fv-@3=K@2>tv=^d~T-DFFqQE_PmQ?a9`hlg`r*4WYP#6voQ?8jFa48~V8-aTb% ztc!vfsuqv)z}~1S6}J+Gwjk6i>hO!9>D+UJa=9f@a1DWJ``U^O)b~@}OIA@k#SpqQFh> zxp%jP01PM_vTa&OU1?-F9l-ZAR!Vfz{h_SoT@y?3fpak>G>A9g^ddV3%)IRJ@2rf82LRObSqZE zz~p8Ms~~q7a)HicD$;u^oK8tcurdvo84Jr7sx?2KIc_4jtN|#f5#UMVICMHhQ$YimORlT{aL7yz^nSPrSyjGfj-wWd|!^7{ymEX?xlZBz03;>_ZkMp2nW} zCUvtQVTT(H#`+81^&t&e!7)Ww0#XUCl97%p)NoQ75>1638h+l)9K|A7FcAc?+jz{9 z?!7>ADJd=<+W7j|Vzk&4{)SVVZG5zRyl{u-#cLVBFm4|F{-wDnHG3K}BgS6i-!F4K z*C(|*#4S25xAd;cWT)cDLD;$WGI_^F6pbYW8QE5O!>d|Yd?pIEk1I;3D&ah7#DyRB;dmmmQF)jlU_6{F%vA$<59qsbkk|Ci~VM-GK&wAaF|=5wh`pqcw{gY@b?maDadTq5nE%x z6X$s6Umm#>gU*(Lg|dI-3mGi0?Swu=#tFo)4*Hw%(J=*lCdLh=P|3!LSJVf&a>j#Z zM}mIhoKL(spMUqO1HG04uE_KYf|rM_5{x9(1VQ zE|HnBcX`llC~@kPO|}mzCSN!Tm>lz&5B`LL$KsXdEo`1l0QhHE(=KKj5IvHw*>Veh;SLaHIQ5y+zSFTqrqEeUSb zGeHIkDE{G4SytV~A|u*xz!wXbtE7`heDl2$8l5H`m{nBegpnhPq&e+oC~>fzY9mdp zt7`XW5R|)c#{GCbT8V@ONGwy((6g_s-@J}n$J3r-sEkZr84nHrO}Zd1Jn^^5(i%tqZ>MzAy&3uHGh}qJOTS#_K84^V+r-ZZG zonf=>?MQKy6`F50bnBo<7+~~(5YGd$OVL%*&79!K6=#;LjufY34CD$MqELCau(!82 z60N7+FW)Mi3}T1uz1Fe3rVCN{y%T+I@97Ds6~-nyiu z0Yfez`3D>$>@lyJPVij~A`y-lZ`e-gCyb>jep~NgtNEl|(B1G9m>oU3E;9anaJ^Do zAl_5ot|qxx`QUfjTXE;Y!d{sIfkZ9Yia;P*h~vDfSWLqq@3E(wrMwlfdj3s#ph`l+aHc})>(aNsQi|lcBD@`^9cJ2J$1N@sC>dwsVU20P?~oNFp2!EBZYD#4TJhu2;eBKu44P3L$b-tD8?-kXMwT zl_Hoe@OZ<14oA{!>W88jxH!7rWtO{_ZW(<$TzH93~eP4u)xwL);QkZF%KdL%8h0 z2rIq55__DUpkAeIU6S3Y=)8VId}{0Yzi4;P)xgb)lhDWZK_;v1=ZB5qWwv;#>3#2p z(n2g8ws-CeCe>uUJ07cLizc*8WbvnCx8GWXV+$11xIJVB6-=XkJk(205CY2Qgr6D$ zo2zx7)_D5z;`^liX{Fw^CvwnqZ*j6cv9_$tYx~K~;g+slA|P1DF}-|z%$nV%Decc- z&hfTQrtXo1+Daq@A#kT13>}R?2HMw>@*IX#(M&vL3lZ0q(=Qrk*KtqLs4Q;|UHqdc zZPO55AlOGSdG6r5vf&1R#eMCu^4^LqaeqO@D->bTxewYZn?OJoGw2& z>Ze8k&4%Gv3b|~>DnCW#a5Uk`2!OM+Xzy z>Ag9AvSA1LwEWo5WQuyKv>$hjTV8(bFge^Uximt^-dextv*a18aiJYBL`P&mk>Bdg zUsIR%WNP5LEPdz{somcETaq!a0-cQ*ruE=U)G`G+vY3}cZp4iC&!^?aOZxwLvn|*r z##noAVUmN5qmASlIgw}z>)AQ~$t6(VdN~cL9-*6MOri^Rd_bcR?0DTRRppJgk8CXU zE5gf-Z;T&hy_BT9=}C#V6L?o#X_R-6TRd&esuwPna^=#IASwkpMtWc~za93!XUVfd z0jwz)Y7*j}t-t9De^U!^t`?uxXl0A{egp)I8nJLlyyOB)szR*dR`}lf#sXkQRM)9+uhyYeid4dJ zl@qzjy6m_SL|ZJ<8^5wTr~s7Dnvh&7X+Lw<1wVZSjRTM!klo8AnnW%vGMc@J^IP62 zm$GOgr?O}j=VRUhw(?q(m~tph_t$>w&zplo$%SUV?t^kK5O9)6C}M)wR(*L*^)9NKz2aI9yIQjI@!0( zB1kJ83@)byGznoGxMI+jM*+1g0Cp7&MuZob-%AA}K+xh)i}3&1|B5aUl)nRL-P=ps z^}AjBlycdvw(M+@or+{@tn6kOB{Kq;75*X-j3{OXBm~vH-$t!DS8}ycBJ}uite@R_e)SF-=GE&fyr+@mRzbD0?PmyMX3`L8ygz~1H;cv zU_rKjB%KH}E($$d?O&vCJ|Qk2=let;%!l20eMuBt6vf#hf$1dOLg&fKt@>D49k4bGv3X z#vMNGoeV}e-}^^r)mK2Sd$DEn_*W>#qWFu;tZduj{`Y#|G>iWU2%T_e@($2a|5}Yn zcxS4X8iyiEvU=zr`2U{ohP~?2$dHX*%?NllO0qpsrAqiQrlSa$4 zIna4;TZsaV(@5qef(Oe{kpS0UoB-3hBY+v#cjDvY9rGUqJ4ynl1;p;~q#$d#y-AeNCF1EH{aWh-kF6)E^NMkzj#G zEr=ZW%Se`aJMcv8@kmpZsGx^!1$aT`fOv=?A}WrhI=8+7yrx8InRpNpG4NhLh_xT_ zY!eZk&1$P7p7>a-r%?DmeOg(gJU~Us6Gx=;oa_c-oyN~C)247)=AtL4BV|eEV5-03 zaW&&swYXf*XhBT%Q31vr^64)3gKT?9Javw?QU$@#5Y@7H?6TYSFCf@Bnk@VJ8SThOhyCxr8RlAsH?RMR@q!@){x>M> z|L>rF2PgFMv?_)})z`P;6BcXy^y#O?g@w_X`q0d+GH{Ksj;?ONSc!cU4ZGaX?(S~J z*1PgYmX>awo}T6Ii#k8@^M8hfkaTu;|9t=c{W42rXHHt+>XB(};Dw;F@^nc_$+@S+ zywX^abtnysMBB81uI}E^3sn=7#1YLmZz>NqCPr>jQRN$?DfN5Hr$w_$zd1RfzRk$! zcM=Ba{&@NW)L$D0QA8h22Ti-yoV@&fw)wjnp?o~^-{jD}R3cSYzy5k9nfq=0EGMM; zjprI={x?GtlUHjag}<(jW3P%LINr3~cye`lVV=$_S9|t%>)c|Vjhvdvij;zOf24w9 ztM)4J>{rm4G-DfF<9*Tk`Z_~YgRIBW=+o!s_N5NJhXGqPXPfzSSsRP(d}(D@XSG+Q z6K=JC!>O5VY+K$(*1*w@Hz{>s<865+rR(9Wu0;tJZ@&MbDxeJ^rnpJ*E%RhKGuG@_ z=tWuEyLa!_@$)fJHG@hJZ1Ry)Vf9kytDKaVwyiPIHTTAK9zKlzZSDQnGeO9*W-{z_ zd$!RW;{sM6+3Qty11oI5oz~5(g+KS$82@>=l;k!}Z=hi9LFn;3iuNnYw~3C3I-2t9 z)retx^?Re-G?TSQ@p#zOZEQYP*_DF*bzB;Kfs^iy#R$&8<+GOC)4+9|YcCF+ex)~E zG|Mh}6g!WJiBO$6uZka^t`$zOx>Z?IF$iu`h;^hbKY8-xxB|AVe6m0v6z#_?Df#D$ zAw%4V6Zp~~n(pb#!(SqTS9{7=wn4{@oa@t97tmf_PQlehkuE#Y>j5kL3&Gv`uJ?uQ*4aXUj9@(n)E1tbMOzN)kNrhG2!K_%dM;N z6z{1OS}$O^?f;D-m8L^QmSQ}{K5g1~aPhC)6!TcpyP_7hs2Y`Wn_>&_HU*);tWsTG ze?3RCknf0#&+92TN4J8m{A$Y;?r#@yt3T(8c!ZG(G1XM_ts|yzF6CNq#4p=omcL55 zj57|)Zr72z#3~+chyN?i@&e6qro3L%=sX>8v{6J3MMTb5j9B=MMe?OCw}Jwe)F*KL zIlWxg&&X(9*}$ao?))p>6|R5f{1!hwpKP9=B__sx7^r%FKj_l`_sX}Vb8GUEjbx7= z6ancs;S44daveS1nZF1G(efU##qe$(E1j(m{*&XpGLU^ZY8zWoG@mTjfNQFsN6_*e z13^GN|Fk=xEY6WUQGGNu5hJ(CuPj35p3!(BWKz;(Ze7Ww_vL;)9FzjR0p;e9#j2J; zC#lq*o~!!A9zkAo=ZCgs21j3IXl8K>k0;%WP?;IsKg+m!t{I%p^MsS-haJlG&0U%1 z-|Hn&RNQ1tHYmR%TGxelx9|CzH}QcLCUa7tbc-D73+`!sgW4{EzUEwY zkj01fgpX&*a&xJSs?MDMU7C%GW%2k%&a2smuqnsEFM*5qEMNJ9y}?ErnD_(7Hp<7d zUx8d{X+%l5CnhEaQV+vSLId5ZdfhJhNI$9H0Ijt&C?N}s6Kvxbh(XUTTa7Xhi$RBt zm;7p@%EHWxO+Vk=W|e5$Kd_z7i)D&bRHBijrEDe0NDO0>3)pX}G<+-PBSj>B_AUWodM~!aaRfPFsZ}I&pej;}k2s3h51?Cy?$NortMcVt zg4o27iX)kq&WROLd7;ZK{n^ekSTo&Wg5sv=FaaSlNf2a{o{9w9&jf64ApHv{S~HT@ z`3{vxHaV5xL%zrF(E)~A&b@LE11`PDJg1&Ti1{-b=3wE;^ozK>Dg)oImA}Sf{CFov zW-qNx3;2$_&dY}+r{#+Y9Oc%Q#S={alUhgc{@C8z^6txfxg%e^ym%_I>2~K}#!;a_&aG;;R83 z`Tah%jfIZ}hjQOUsrp1V(yq>P`08g)FBkZfcc@>YDKD5z(%#H{O?K}Pn8LKWg3bI+ z%V2f6U=|}443utZbUh*bAZhyiTbi4$*z(wj(67n45%ea*5T#AVcWc+p>LZKZbH2z3 zr5fNUDsWRHVLTeE^4&92CnK)+8=^X*B(RI&ZE?C3lrMnDm8Wn@7#Z@2|b zSb`0uv9WLbP8Jh3{(4V)qR7@ig2>W{$^5Dy*(|k#h-hF9 zDUyVeuLgUZ5C5uJoTee9c&CoYPxH!igUox9&XRj6rXMN{89u9VI98ewX9shq>}4ov z$*4Per1;LvTP(<9cDEC6tj6|A*)LXAgb#7fC9c&sN_%RuKT>|EC=u19Mw<;`r*4QN zC$~nQsWn2Y7DRHQ{3gDUmAHw8<_(InA7gw3BurHZioMC}? zWlM8Hzm2|a$3~ArsOicYM^r9Wq8>W>jPVs32{WJ{2!hfzIeeR%@2{1zlSJ=nfDDyb z>{tKIrsYM_Kp!E7kXJ~~X1A!faOMan^^`Qf_691^hB(z^-D78D ztvfsZGl;uG&%B8JNOEh(cdiPbu)?4k02}wgS zm6C>-k7P%}JYuR7@S2yq3AK1f2V80{xCbuNW`*iy}dTBZ2nU>KEIX9r8~a(VnB4PB<`gIE9mpb zaMqu>_J3na0l8PrE&AFqt(%hM#)3w`JDwoVlS zn^aZ9$gA0^XErN^s=|TL*EIPUng!o2aL7HVba_5 zeERzyFL6fPWxARAYJXTFKJ0oZwiP)bo}gT@oH?|JFvD!;DgzU!*;{znF?cR1@Eu#y z^m?e+t{lN&4Cw$GgM~oJ%;03VGHCnN=C$D+#ot+18Bx8JW=F#^*m_)}Y)gO|gbSOy zHS-T_`1|t$c^e|5Fl2pXBfE|HCJYTd=#t%GvCmYHI9IUa62$Y#zDx%a+b`}c`Auf( zD5EEuC^HX$%vT$pJr_IGTLHacOcNf{hOQl5YLsW0diA)4Q8UIEMh#IetWM%d_ZpUd zR_$U(MdQoo-BKZ{R?WQK^aetdEq4aQ%m2_gqW8W{TrXtg-5&X-ADU<6qxh0knQ z4YLpFPYkxVH`*bgUNiWgaK$uaV10COHz(3rf@O3D5*` zUR}>!38b(YR6~XTRUtfk*~DvC>;KEhbN^$3x`n*CSEF+QrGK_aAJ6Q50R_`liPiv}jI zsAZHpdINohFg7eQEG08puv;hcG7P{9<7g5hXv;#WBwP{8Kgr9jgRm5QVHb}mlKC1! zPwl29{>5V?KJOUnchEI)MJv(>j6^s!I}JTWHWTr&5QiS;&_X=DRy_r=QbsKds#c@EM z%IsmNd*l_&ke3REs4LW#%K6Umq@h#+Y$D>#!i(L+Su>xM02GaYc)=aQyIebVCCl?( z#rgw+f1}!944U;!&5>KHA_jABHR9B6)~zF!YfikqV!)nz>eXVYzO0D|Hlb3}7*+UK zYBl-Is$RqgF>e0~X?|r@I+#xNBaYRNd+Pj;yfHdGkz3>iG+>NiGH0!T^hoFpMAv~G zr!%XSIftC@G0AGmsTFHS-Ot6T`JdZyf^?kb0dL_ruH>dV=@V z+fb=k3Q-oc=UexFnSMNsW1PgZVdjBt7g|urB~{dLc727xpXShav!fkr9YLRJ?`AnPk{$Q*UYG9jwRMX z{$`%5yps+?;JL4r4z+oWm*b>oYFK19v|fQ{+ZPiy0+j^WcQ8_2l`0)DpB{$wk~e^! z)1#UchmGuGc(I%~HQ5Tz`3H{3L!Xp`BswfeYLjvE2HKTN;eL28XIfOxE$k4y9~2XY znfIUDGT6Mm>D$qD(RC3P+I281xe4xQS8Q>JbZQ9YPlIt3&8?+v-C)?%Rbo|t%ujmI zabS~ld`cG?3ve}miD*EUx#;q*ek3_Nt&~>6)=Lt1l0Gk%bPAUi1|IxK{r+$nBjUso zI*d`88I@pzQQuC7sgV4V8t9iG;J=WjnyPX>Yx*`X1)pPIet+y&)7DsRgpV~!Iz|^XZT8{5?6CN~n z_yPf*miXY@>Gjau!$M8aBhcjrDzx;0tYb3NWRlfPKIZCh!p*O`lw;AZnuvRM^Y_-F zoYj{fy22GrYY}g71;`kv#*npNGjj+J-qg%NiDD-s{>{uK<&m`lNRZ>-<<{eit)S_e z^F@(~W=6~PT7f;cpfl4#QZkx@=_#>R)sqTK0r`Vb?DB)Ru$vV_l^>wO@b`arz;YY|Qr9?7knTgy(~2%YGN63q z4wOf4YuwQ7Cv=)pG_;)OmHg z=$gEm{Q3|27sX<0z!?zW*|7>4eu-n5H|S?58Z~7(jF71yTSAGn=idfjRNkn|Nzxkg zlmq9^#4gK7$kD{jXnEX&N^Uci?Tvmu|+Ra~UZ(7{pQ zpioS>?N?Kb_WT;MG3s_+J;aQpCgW^%T799ie$jrK3|^coZS#h-KT&vlzYKB(uUwJu zy#LgHN$YTSk8wsx-Eh}RPucxaGj2Cdh0{6w8C;v@SH(|oN5)xP`mGGs8QtF%B5pNB zC#rW|qe;~Wf$AjeBdEce!=Hs?0GZ?2tN#s3Q)KQmGip5sb@}V<(X=H30tF5lOa38J zgE-{7*o~0~9~{+Q{Z(^D|J6n}L}nVnMOQMSgm;TL3~RpiRAe9ArXr{}c3wglv5JAy zRpB3pId;@SW24abTb_O+Ze^aYLis~zU@O652#AASdMT~ydm}PreMN6BBb@~P3Yqiu z-;cu$o*H_@BZ=;kPdO3z=Gut+cSNZ~BaJoGKQM*Lw-Z9d_QukMb3exLdkA9F!b&36 zm<`r_n^WBcg(?!{D%T$(n2&|$6uwq6)cN^`%UBK*{2LrT_bI4;s3erC|J{pgS)26Z zarygZEkCu0;jmYYY7Lo>?>% zD<<3t&D!C)IO)hW{{U3DGgEi+lL9Rkil7&6$U4895H_<%FHLbU}Ic zO|!aqS`2e`CP-Ro2-6Jw%18I?`H~<0ZB9rNqhna|-2A?zIuS`^^TANsCRXgR!w#WQ z)?FE;*l=3>S6oKAC%&JS=}$=T`qeo>`L}VFvOs|8N=QAa9zJ$7{0+})NMn25!Rz^x zvEINXa0h<%{l)lHFM3&yhd)e9<(LE{=T2Nn!5L_Y0*l!6NcAB%C{;VCI`kTa>jqEcl9zE0^ zja!FxiXm1@)}bv)uz#6S!{+H)?wGvupb2^R2A3*8y2xXvUu~!ff~``C>X(q&WWdwc z$U|bC^snT|?`t}@HmtoqnK|B>3-_#Gl%XiFWFm%P6a7dDbhwVg;v$+5kZ5QT;<B zpC)>@G(ZdVjP1p1&L?l|Vbj}fw)^h!DY7T-z9 zI6d1AvMwuv@UhE3qP{GoQUzpvcRP&mSsW)bYCo`5EU!m6_#Hl!ec>0Negv@p>LG~C zh@_^5Y5(uL4|?4g)Nj)W8(d&IQi%wWAXV!AV=k7JiHIMVbcADnA4~}%o$o0Gfl7P< zp~xs`;Ah!NCrNL32C)!xO*J3zb7pAg4ih|XZyt|P>WQD{KIebzmtG8Rh;K;>UV%yt zF?#AU+l0|@bK%24y6Tdi?5kl;b%*DFUp&Xls(OjnLbsEpnOA1NB7^4t9atpgHx(j)5QC5}}>1FMhDkm5PrU5|$hoO6!!LT8Lx#V6B+oz9mFt2(dom2u)8~B(> zd27~9rFjC*ywEIy1S`bP-2)3Smn zf`ML*3XtNEJ<1Fgn(N$U5bL2GfOOe7=wh23%rQ7x03C*X9D*V@m_EPTkwM{@49~8? z_`Ia`s{RKwgpKWEuZkduS#<(rW@bK|Q_G$P-b?_f`F^$RWL8foRYtg6-B?x))F7|Z zjl7J2ph0O@d?iIORi?~jiNnF|9z3arw5xH`pzQnK;76Pz-|ivGV9qD!hN<5e#IB&J zK%GY~8nBlC>y4#tf%3HC&=wGm=T~~%Jc&HPm5ZsfY>DsRuC=o5nyGEF7YK|^Opchr z*|d~?VV8PtSa$abANH%&VmhI&$KH8gC2rT|Ks>e1!n z5PJZXtm+MT+Zd^WKy%0Wr0Kc!$XXbZ*GHS`k}w>EHexW`tjvrteztxgA2uq$6$#6Y z?N{hf0n($p+%aqI6{1wsNB7c33c~l&T_KgA-`^NGGLSbaM7~I3DC7!g3g7@!l1o2n zx=Fuj*~5(Mt!}CARzw3mn&>#5(xeR^W1H#8s4ku+hooNE1j^Eg59HINFvlR;p+%}r zH5%^JMMjbz;B)J5#5apu8KJYfSP>7Fd#62NJHtd2H;L;R??=O;X?si*{KvRe9gR&A zL|&_g;3*}(@No5U4b1Gy+1A6jLagdOabw?wYKLlkxG|$rq?~-OX6WRD0|dpEWbA18 z%GvQglJYntr)oX+f{tbW9D=|z5UU!4NYp_w6s<87I4w-V2B??ZsH@l!BdgpK1z}PJ z^F^Mf!!ltx=Q41auROzL=st{*<`C?nLaPtP(^||gGDtdS(Jw+{b9!bfGKH;H37dtyB+Qh7cbN`r2RCCDmo2A9`)Hq^t<--$O> ztCl?U2gTdMs#Mi_1L#$20Y+7LF7?!*-h?MUvX+#m%`gY_Y?J=9kNAw6tm7i`e!5cQ z4wNTZx)t1-t)I(UK->^^7SRh`bf`6h$8<{Jk3bJMA8$VB&|}75K{v69z|u>!$;m#!e4iuCW{}@ZYxi?yOnaTesvjRJZKU9?)G6BZ-6A& z;PfGVnAbh=Tc8dGs@6sE4sX&6R$1?Y{+M*yT;0jPTump*yUhRmGiz3nrlyYei`lbI zLh75{>-lu{aqC_O{b6^d8GX(3QO-qLPaVZ#x0)m$pBdv>g$ilt(GX)=5@dHtay9jg z7ST>>q1$81Lmt2_t==1%NEuJGZLc@_p8SJGqDY&HBhkt3jmdwPR3rVh_nJFvj^`e9 zZHIL-3evFPxGV@!Ot=sxs##b^-I{anr7SJd|4@yzV;UyFd#Rgr1c}Lu%C%M;o?Qze ze;c-!3AH&RqM_t|yZ2I_WyHsE8H&b!a+x<5Cxag}`g-`M6Wa#iOVNy!lHB(x+sm=Y z&Drt3a9(p-k)fO<$gnzz>EmjGXUTor{TIlRSEXj^Nvb z4m+^VNOq`H!(R9*Kf|cX2#YGKe5zab#5yN(K;=YIB`ucJeB zeq=WJ_%_R z%xi)gegZWuvk9Konl+|Z%52Lp$n5v1-$NcL;2grBxyupn!ori3%=bC7gPVy@R}6w! z0-l3l>fR;unjA3nGPh4nb9H@iQ$GAwOT#pJ2g%>g-@LZtEj=(2xwj`1D(-l+c1T$ zTXA|Yt#)b?-_-cTh38g(uMTkGBRC)^&|-qbTIbT0a)n`GFn4S0(wF>76q z;QnvKu^hKNJ50OfRa*@Wa~1wG9%~oU!nXm)6qc0$liP~78DQ!JgcwcfWZCPMs>3^rT0m^C-y8{=ekds^`OL&*rIuMG z@tbCMEF^`3n@;pgYU-xk+m$cB_-J|gAHc7ds5(0Q->RxfK>LwjUhc&T8yoNq34;jn z9g2smjs0@71oR%Bihao{*z{Y`*P;|Unwo^+d{YP0a_1e581kDrS=rVyF!c#8Iu-Tw zyu2=DKW1j;XHT9i)Fz#-Ya71P_-{gF-Bd9PUnQLsCZp9FR6{l3ya2Ez1mBt2i%7Sd zy{ZqTkY0PF^M6K9YybK4r`&7fg|{wJ6UjF?Fp%K{g2{c{W}XD(C2OH`b2gnlJ+8ar zqZWv#nzA6~y3Yfb{@?KgZqtTp$fN6Z{J{ToCC96g zMtU?9tmL@2)V+tZA16sXyZ0=w==WC5glpA~1}De6ygBu^C7PiujNb~- ze9iEmR7ah$ep?98P83ym5Xv1-wj04N2djTlaT7*)mbFuI?S@t897|_TGcd44$F5RTSa;0AkYreK2fV?VRD!UxZKu(XjHMwRmhIXy)9)1+A%d z$R)S(x#lhpEU*4ZxlS?#*q^Oe?e%y~qFTpxS~=b5@91G_#+3k7#JcJyQ3MqgRluuG zNd#t&EO57-PidiRwAeO@eZJ_&Y^vW%cEUP9@_38-?sZE~6j?WBY#nmM`B;x~6?_V( zxlY43M5N@@MVYZmOF0+kf9SVc_FYksFSr~Hia2C1j6yS3tv z#GO@oh&uJU-xmOPV`6|V!u_7I_AvFqY)*7zG2~7QEK7;Rt@ffkB7J4+XrA+GRJdwe zH7KRB@oB~tr)PxEyqiT1Ed?#xGHJ88qe2WHE&W-J5-R<8b88xCG3y%`90ibUG!*S4kkk0Y@X2;l5+H5j=aEADe#jhojv`?zCv&ec`%Af)#ZHl0=b(!<%Z;JO20zWc|Nh|!I!A3CX_*IZI9YmV zehhpMRz5F^C{A4ZAg9^1QQXSmHK5Hm253?OI;!h{uDsi|{Kgd!I2AY2%6BoUx5#f* z&CecR98UClO$T^yh2oL3s?*A}E5KWwfSzYo#1ueS=QT$$`kAUJ_fDTLNn3DO1OaR6 zB6;+1E=t6!|9tgFVWlyfm>p&V$Rw{RU&5Ha{Ki5n`6jf109M?O8)^T*t83P!mn_q- z5zVsL5GO@DtHTbP`)aEh;tuS(QnoGBeml*K=4SA_P<#ZNJBA(A1TF7XI>UbSg_nOm;C&DaWg^gNg0Cz*17k4i-82ifg~1rvC8lY&=PF~s zp7&!#4{FTm&B&ch{ifiC zJ=l{Yi^20@LPSBxJg`|m8%zwLi=adJE_ys4k62SKGpF+YS)021T;6J#nBx+vit+K{ z;s5c^kM&|OXK55Ceze1>xQoN&%g|HWk}|A_R9AjBFYrk_eQMyJ9=(bq z?3G;4K>2ezb1%8kxwcIt!aOl7*8A6_xmP=H0zQ4Nnw?UI3_{C|JNoN2(S1X3YnIKO z{goxew5moC;XC+Hx`H0F=G`HXbF4Hb9Re-ZbUb-?ub^m9U%tDSG2u2&+G$u&gr16I z6DZIRJnDBA&Hh3IkCqrQNopNYoSNFIy(Nf&QZ3LPhV%JJ6~mfTE4xI zMKCtfkB{)Z>vT_Xy?d+j)J07i*ly)guO(g&nCB?sL;4UyTzHTH+zJUsF+x9oq2xK> z$^iAxZO%f<(U6;(Ai4qG*>FRl)(6S3JV>-W$xh@)-})PjczW%&gvGa{wA&@Z=9NPa zjIA!uPlPkH)#vQ+VN&+T*eqjOP89wjhr(Fx8FF%*YLi3tCLb*<%#o~#;es1A4p9ct zowAW9NDsm10MX4<>946bohj-~kPV`%QiIbim;^N3S@&2DA0QJ4(z0kRZp5jbbMZsf z&BWE&YF8LBU$P9~+>s;5bEGl!5g=HtJaTGUQ5Brif253m3u>HsZ)DMvSQC!XP1ZG& z=s@eXLA246vd@S4Iy69ufnV0a@!_M3$KCac5l&H$b$$6+3xo-my+N0QSG28nw8K5J z{PESVVJdo$!1zdK14|<|jgI;=7&OvllyM~FFu|j7(Ux`C+T23T?6GvRuI8k8esC{W zzitO>fy3hh_}VOfj&43{*RY{dNT`rar=NS^G2D`$xnfv4voK0qZXn^w=h3BqyZa>p zjPIFssQnW~+By~sJ}JIfFG}O>cJFVB5)=_HR68{&ztseyHLn7i)7qnn$Q>Y7Yawy> zrKv)r;r~D+csjUNO-Xtj)3TA91UZKjw(F~GgPCE(VDqs^cpo)EAyH|k#f*j%#)5@ue^xT zclZ3SE{@JTeSy8q{Jlqt>QQVehAi7r)c*wB#$k1mc=GJm&z{Dqq#wKhLUkdE zIJ3_?IPk}YPUhv~R^Gf$RnS*GWCNB5vn_pb08rHK`B1lR_IsaW=t9>cY+;|FH5jpm zo_$T~B3hVT_?>qF)k0hllx5>(Zj$k`ZR8JKrX-}4y)A3QI{Ngx<>`x5pSehmuN3Nv zFn_jZ<+xbhjE|RJ_HB7rFu1T~;kUZ&l|mc6U-h&M-!X)$MW%Q4wjISCoxVG`MxOoA zaj)LbKcE9?bMJrRagK^pXDjAPrDOK~E-tQUr-x4=<0d!e(=!;;erKJ_soI&m71OkN zsIooFO_%Xf-&3^@^JF#7P$ocGmZ67x5ywFpRLZ3U{fzPa*2rUoDe_%@9O=~lW=NJK zaSa7jMQ26Y`$5eZgkWhC)mSRP_c@9xBudL+p$LHp07_RT#2KpY(wGc@xY;_dMNwx@ z%18Rwbe4Z;eSoOZiWc07)Bx#TeiPxIE38(fE@mfZaH!oEUzFjQ-Ii|Ez|X0FIEj91 zZ|E_cZAu&|3(}|i;=?W)srA60+g}@#oyHs5^w_Hj9;rbchIV{#e~?kCX6vPaO30(K zFI@b8u4h0;8eRo!itdb9#wkxLU+#c=Y59V0P(&NLi>YWxnr!0pF}5wm=be_9b0!Ni zpU?*@z4+?DM0pZ~=1b`wm@rT1C-Il!2Q9|w>q*v8OgAwA)?66HC)(kredeQ;hQ&SK z*YVJ&%qAm+p^^BHcA0~PpGvMqf-VvqJ`Kix=<*foOwu7=rM$jbgG{?IARRy*3+fl; zI%aB!AY)-GBeJ$SJrkV-(;7dH6r*A_`NZ?;$7=eb&X>nSS;#PkxU2u3K zvqcUYmN>p?dMASh*5tJwRRXIq23xnR!Crxin*yQX4{6Lb%O&O?hwt5laBIBo*NpdM z+Kt$&w+9;BWV~A&T81qN#EguipW~!G!+jnIy0e`k=H5O^dtaeFwyfD6$PaIAjHXr- zpH-QY;Z`t7TWj5c6E$N~VB7npDw_wqgf1_P)*%fx)Nt=w zc)G?dm)Okr%)eEQd6eRU+}PD7?_89 z%HFXDw;K*AZ^328M1s6;v!%&xyi0WF;rD~22=P0uIysNE*n7?Av2K71FYC`91qP%Q zPDpB6&d(xYXv_m(8Iq5Se0afRCXWx8l-{T0m3V0UwQHrcS7{0G#)9KUCu@{)mI|=eT0F@vVPK+6RG$<&oIFiy)hLyPYL!k7hy;FW=ja=pDYhLBe za_R%RZov59?2zL5xmVxg8nxeGG@G$@{ou$Xkz5lcuhRiF2U_cnw=p_o_C~Jp**RIi z)hfREN3&hi9~&eH?QcgXgtV*Sr=`m5S0~GyXKmV^;x245GU4 z$^#(z_HIY5j zIreHy>b^rdRY&Ei9OEawdSeq)X7m4;m}<)F35X4fvA>Yx3%l~?R(Eg`O^GtSf!kcPEX$iRcB;0d=@mB+k2Vt`Lk3_4g6XD3;QTWk#fN2 z^1{=T;N@|%^{#-x%D(MS?D+T#z%&zJn=(Aa&n(GseKkltHS>`2@7jazWv2tvwE(59 zfqw_CvkF$3WZ(IDjPvSP6JQ_K)&WNX5=II7nRdRwcUTMfQx3|;V!5erm!~#XXsIj@cy(Onnj)p_+90|QA0CW&t82<)*GYq~DUfl$t!l;qPt)sq zQvTX%Fh1RPN}$=ZR6fDp0^ z2s_KWlcc5Z(LqD-!B;1MLa?yr^k0{;lIC((m!REwpuDuZrqw>0Wp!j#~%y$D9$>b*Vuf#^RVRd;!M->cI10tDbRy-y!pj9YT+daBolH+cy_^t#f#j{Bgrxj%mFR7 z92NtN*%^hD%2WC~$AIN%{o-i)sATWKhxmAFpms04uJK*>Jl4zo>wG)1_4X5RL9N#k zc1tr86O(>PIoguSt@9cE-`-QzQnn}5@-O#Az3S0a>ywlOjS(QfypHwfXKvPOxsfrWN3e3hvpTVjiUuB}#L(A{pcj#d|`%@UW2%9IR zm8mn=M)UL#Y-1IdMr;AESE;CNi_ck$C`u1d&#_wXc6I5wbpi`s8GHGw>KULUT3vne@y-el-}PaL|6C&W;r9Xg>+}TL&0Hq_w^|bX7BXSJ{Qvo;&MW z>VNGz^Wry?y)GPG#2tF}PcxLlY1vn|`fD%O_#@iW(#%dQR-*jNsq{VzWEX0g~vZV zw^(8MmK~xb>0Wwq_tg6lqS*spz1JguS)VR)Q(BIbOql<+W;P9*OrMCM2T625*B8-7 zi@+0m%TZ37*r=}NCDq*za^^U!lhWHhyV@<;nU^c$91G&pNSoSsXS9s zO;R&$34FDeYdg+<>NGIb7Y!X{o zC%}QV^p^zk2J;~1!SC4M&~!fl`(F5zzUmcpLB4NXKYT z=&~Cs57i$w(Jw9o`kC0paR*E1a}3%nG*ft z?XDqXUaTvE$DLgOPPlG2jsyTzdo-adup+#>eh1R$2w4p;k?>5-(_}{pa**85GX5od zam!#p4(pG=W%<5Hk8KCo->rW*V6ENV53(8pfo{m@pl04&|{HGyYY@_gthB z8Ae^nXL~R0YEt>VOk5oWIkb}^)g?yh)Uj3oDEnIvL2{>W(NwC_iED+mQ_5KXV*}a6 zTgrDV=_a4#wGNI0V!o>G!GCmT8;76L^4jXxT(+-yP5Avf5&LHK-n`~$@vxBM!U^b^ zsJlgMWo^h}<9~63cV8-Bib6Sq1Ozbt4=1()9m1JMKNCE^{=McqTQKULl8zVg&<;@TMSQc3p1`_OX>;5V!%qFl0EP;Po z**xC=#+7;Rv-6sMJ^bKBXHA|=-`cEw-X9yd@Dl3j(FE1RTg_Q;i?i1^%3b>?f1Q=( z3{myhUXwIyVz2MvfehRL^oP5ZGsk7cANdRprC5wKLT(YPjf@0 zdjCTL)zMxPy}^FvtWr)7Udb%h@_dd_cnFeiCbIfg@BEsYt5;Wcmo{{%=_kry2GzgU8@08EC8#k^= zvuk2Y$o+{T#?yqf&z5Gf%PPpesE1P}|wVieAfh!=JLYNxwauSsI=gKgjCyz4;CUQ)yjG@PKHV&sjZt&qMS zI?7i7BgFbF`m3>*3SYHWPW;s#xT$kDAu2Si^TB)wvedBHE@Jl1u3a-dqXAKOJx%xN zlULz zbE2*db!Ux+7UheP;kLU?w@z`+;EsBVtcvVX?G1W%DNI&!8<;f7tzdi|w>=6jhNwzV zgtOu1+eVxh&hGnu))I$8HTyq0!oP4}bkun^D3?fs;N++(BtI&`(H8T*{~2r6bA&?Z5K%@U+x3+2RZTw(2A7{8~w9X08JjCT0 z$f76ulrZU73h{CIE?vH8Y$nnX`(;4}$EpSyb|jh9c};Xs7ostHE-M@(P%FSk2u+<0 zure=@CDhAd>@70=NQK2c<3K#w=?kRli}MQZd)BtC;hx_e)nN>>(wqhsF2P_js@8cM zcT@%9q-Z-hhuXi+=O5~A*lhUB%Z57|DkU78k51)@?B`!DX^@o9Hns(hDidz6g|{@) zbUkbyywxBlSWlVVl|n;nk9ZawtETPy@9MvKdEdG|dNL&dw1F4dH~^=*E)S*2OY~D0 zJMOg)yJ~g4x(5;(Cmt7RV(a0W{)?d>Co+>l(`Q6Vg>0FS@dWH&0DlCGp zuyXZo>?kY?^3_H3_I*8Lh!T2;GCIPLZ-a9~z~1%dxNO6(+LLZKmQGKg{r2Yg94N3} ze?*smSL~az9x!D5B8}NF=KENg@pn;j^{tcyNN3!2{Q3CO=(f;l@CZ@;_~$qCU#(e; zyoZ==;>221$N0s^iJ#N$yl-qf-RI3VZP*Gtk_UJ1DUZm$}5Ey{iRtRXbDi^ zd^mntj{PmJrGsdXZoZMlU14OnvcnjcBb(tr>S zpHpJStkyi{xfP&6>tG{oUjbGUnaR=frN;U|pEPjeVMo`=Am_rhqtZO!;7@d?d$2OfTW^ZjyyR_H5@47U=&c*2!d(%?){ z`R#Ga@muH{8>Dk@w*t%>;z%LMcZU}}E7ki8A=V9kXr;)$9oCU(ueihD^6x+U^ozO7 zMh)_eGX)=3M4(+M#|EF%A=-OkcL+Pt&qVBYiTVDy{N0Yf>Br>0`_XDS(T`%JyOPC2vZX2XE*emdpRp_&$_k+v9J zdkw~nObI^B)rX3PeshHEQ(hne!1*$WNt?_l5gYP>s&$Z-F`PB)yME@RnVH07{qUit z-LwMC9YN`78%h7UrG}8PH|vl#duP$O7(Eg!fzFR=2Fn)%Fk^jr>GHI9K zax8Dz^Wrl^9y-ohu=kYqS7X$%1$d`TBFJUAJothuUu=gy85gKDZ1l4zPF*9wAb1=@?M|o*i9m7yt zB^El)zU%fOzDKpk(>RoT-RyuzyIQzVxZUm3s`>29a=}7a#&lzXV`q$cp66;h~7>of_&gCQjj3tRRaJW909>v7xX9@$ll$*mg>Ayf>qm#`1xUWBPfd>_7QH#;#REw!g8Y_IFD`H*r zY9P@p%^9XBLz|$Vf@H3-ag970ae#$J)W(~0@K^9MlXB?oN>6SaMQjJ5>r2ucg8>zNr= zLT1O6y%os|mts#JSgp$xB@Q}P-s3mO`9-1ZJ};ffLSjs_c=?NiPs;d7-~8s7hz?H+ zEB^c@Vb!SYa=@dpVZ-t1?{kitwiKLF*zW#_i5s*c{9bp2l-_bo-g|l;f-S=P#Y_20 z?Zd^W@81o&ORTCGFQ6MPbnCmdsxAlT+$yH!*ujS7ztV+oKXsj>z%aQojyxB;C`%E| zNsI}%62fW|7`e|-8KfVskM-=KJI+BnSb4yOV@53?TFW*FLl-hp{_zcEX=Zr$Tv#N% z#xJWq_FOrUE)ji})X_CEUgzyp&4I4AoO5tnV3UdAWBCBVSW}8sZWlw7n_F$$U$P(psOeoIY^2 zTrSU9nO`AHOlJ24{R`$g>|zJKg`!du%`hllZ9j}olL&l>dPI4`fG?1rSi6u_=9uMy zr_Po_f*(>RBdt{yGJaBm$*mbE``fAAr6lt%@jqLcH{21?>!Fs`nayQWV@=G# zD_S|rx!gYRfPH#4GLj@>R%0RIt==vNW5pAjTCc?yCExjtnz{QDraIYwkX`HkF#DB! zm#2p@KkD^q?@>VT*Gn>XJ0xqghgI{9>As4GrS1CgX)FBUWK&F1;3OMwIU?Bqku0l? z{aJO__xwPrip)*JYa=Br2ItNA)79kVybi~)bROf#jEwut78{{8b-0;uLU!%aH4@G^ zN)@(4^7-^^JqKX5hQfng=poQClk&ODd12&P8WPt&$e& zZ+<2gSfbvWE@wU|8_O)2BA?E;C}eB1UpkboGQ%8j-y?V-qqvz#H|e%SAxqf(-vg{> zN5W<1yTCoX?w>5CG%{*^ZRQj$1Es3BN31O%81_itRz@XD;l8obutxnXbq z^I@f>`OnAJGDl!CAGs14*Y1bE(-*rRK45Up@~4KY z2$AND5~v+CUr5XR;j}t-Zs6eeH`E1mQfX1H>{z;MV0B(%pl40{nu5^vErCzt z50$xv79Nt;ZDBR9WhhEz{+%n=wTS(GXO*Ba@TH;yr`qkxnM09$7_}+cTxa#`2gG&Q z$fl1?X}`&fso^U3s2t4XuCB>*Ospwi&@eSG8!R>|S;!XW8~C)7iP+*A+S)|e0(xp% zGMzcRS$Si~G!roNf&}AHrrHtg@_AGQJoRynbOdbr?DIWGLPM?QzF=SVAD0bWh>6Ig zK4kV(%tB_!tBC4Vrpj4j5`q_wPmW*C2o?>ml;fRJzg`^T>`HL$tmrkNk#R$bkstMc zNEc1-hqT)jq}wXYEIZ3Q_DR%Z5dZkuNZz0YRWN|{dyA_2dPk_Iu7w!|>iZJ6J=$V4 zEpmu3U;kvg-nM$l`SkjMs+Cfv#TVx^O~&qa+f&h~ts$Z5?A1ymL%}8XL5(XJr@Gh9 zC`!;;@Amqi%;PWm4@e$9I|sa*kLvX&pM0RqkI^BRio8S4dKA$rm}Nv0rX?v0u>S1o z?r=Mvt~M zR$pIiF(vL1Yh*IFzTQtya(j{)q=r<=zISgO=I$@GJ)WA(t|~C7=a_LG?i4F}x*_7J zO{S%F$|(tbhheJZ>RgSOD5F}Os@L_jM=yI%j9 zZXtGKxiDaQ#QN9~z0$LM=8pTt`|okMnjJk?d1>j_kKBoB;dKub+6Ac9PU$k;OPMT* z!rGLx=N3$s^c`o6GCK9yJS;)3+Wt+t%e#(>kFM!Ao{=xh48KkZj4+p*Y6DIIJ4$ws z@k^&f9RX(o(Mw7DUo>i`Is%Vn9VAxgy{dX%nvV)eLq~Y{8HRTz67DZ9m+ZTS1pc|- zD_W8fDi8;@613t%6W%;TbA7ehYbz>zcXIc~6#kH2|>@cPcPejX? zM8}n*ezfm>P|fb&0k$e@Z8jZdorD`u`(-&D(TLqISd^Qgz7zGzlXN0!y@S`{J zcp~Z$5EoJ76t-P6VV~7Uam+ji#sD}KZ~B!W{wZ9DTg_p(DN6#?JY^i=wG3>YH@zGK zxwc%}>IwL8e@K1HY9KZlWe{Mvc+S)k+9nfQmz?fwE<{&7i6O|D74!V;>3ps0bh~c5 zx4ozJw==$iAgFu>QZ?YC_<;D5CkwaP@7POzkUaI2rfgK6vnV zJYyJfeHmW(O9{NC_ffeyxr^z>&hX^!g%#)ObKsar+yfyb;Gy8z<)_6zVsHaw8DID2 z$BzRmP^h!V%?zhcggi+y7D0TQ+S++|M$f6(RxcXGqEYdJQF*N9{+|y}Mjz0k-|gzn zf70n>kiJ{6QyDXQ`ZHh=l#fU+WoAlI`t;fOvpI&7SLTvS*`2{VI07+zRse27pF^0Z z)4Xk`Bd}eky?C(T?L{LKE7ObfekKm=|PJAXeqhgja)v&!TbDKOE%=YkGTo zhnK2}(K)M}Z}@>TP)C1p)Q=Rd9`|ZEWM^leimaY5>lK(3Mk8UEaM7^$+qZ#Sy|e|u z%-(9moEX^I{Jp!eI@MkPi=d;UW0sRNl=(`6eFAV~txiHk7CexiPV(!Q!<61g6 zI5_(#qaj$XDU6WRd1<&pPbA6q;~m{0S^Inz_Qc%E(*#p07fPA|q@>2nwag2f20mUimRwiU``@K;^!eI&28 zn4kwO+pD0p9!+o@Our%Y^z>YKdYhsc@t3iHlFz;>h|2U66ck*joPS+1_vQHzFnCtR zxw=L9`T4Vq=4bVS?g!90V?#hFBV&hWK)RWIQP@LaQpT!6Ooft0-dPnqgS!0xkLvoVNb!j`x= zU&+0E^~$9^S-6(H@=i>QOG702(q&GeG*5mLH^f9*$I3O~wBm#uS`0TcByyfVH}&!H z@qR@VwF>tlzP6nrZe2EjlJ0I$S8*LocWzwIoUCqt*&cY!%dWGo2oe04Zgv4e9*!9X zNxObvA(nn_=9hF8zX4VAk}d_r{F$E})imQ|OgsGT-T`JQ$0Qd2*-V^>xl3W$8FJ-% zq-wQ-gKJN2pm44A#EhM6k4;2{&t!zu>Vd?VrEO)RIl#oq@;$I$Rc>tW7a`5f0d(sz zuLmSg8*=h8^eam7e0w?nvH-xrhS9fwERN5kB|u9*!N?G$4nh+_PIpa{UDJyFi zsk({X0v&z{hk9f=6ZU&!kaH}=W6}k~%Yrh?nt@_=>l>X?BH$Xo(MwKRpXAxI;raZr z&+4b`r>eKJOr^e;G-p4rB90wN4q9Pc{=>b635Ffc%#c$kHMXd_5^Z2NJkZhrF73}G zI%@s0_u(lZq5a@&&olEl>Z@niY1XHudQHpSGdBdBV@pd<(M6%8%i07#KfmNhkABv> z1r$;YMMms3{;}j8470}K$$e)CY&WmG${X_doP<`7gxlFPNox)2 zNj+@w%CWMc*t*M99&34xiw!x$S6ix{y~xjB3w~_l#3iC#$Z?95blkP^B#E52zlK)v zr?KDhnyf3%Zd-0;1dZJDoch#7MeU$SUk*Bbj08j>u0>T3rlh9IU`fU)OtOx|pAVxs zav#G)z`O>DqUxPRR0-2J*h!gIz751}?m}qAVC9W@#f~75(POUev z?R_eFju0_QKb7r;l690vaMf?>!R+ABk-i7PSs^mD-gxIN`x#tAcqj$zZCmdhRtXK%91j+H;#i(3q}=GdF<-W&~BuDH%EhyCP3_4Z);*{zGQEDF7S zTprlF%Ut&rKR0J^`(ee!Nggj>H}q-znXR3u_-g0ntJjWZ!CPN42JZ*2agEt?X2v1c zR!@nxplWm+H!oED;1=1okKd)MlnJH`<$XcL?`pf^kJ(R4XZ)`wVndWYAKH`q+a>y;>;7fJ)a6eWu^0(z(ExY1qmU-&uR5Po{)3Kle zQLRCxUP`^rF~1%bXOqhuZVO#b_pj0OZ(Ga0o>Ga4$E^WT+2=*VA22x1 zoVD0W=x(_8!dmc5x=Q_c$KpL%u5*MQXX;6VM5qIcetS=_N?hbw;;^FJpwT?`j_Oi^ z`#N~&=Jc=c+*KepQCkduk$T7z+!d<}OE=Zt8zfwJSD)!jvqxeJ5AFd`TgB-V>jg+x zUCCn$;MA>1dHlr1FVzn!Ut3U4xu}1{Rj$ZO11nRivT0%|7n4=oUfh}4z7pJsy8;>Ij8o0EwpiWGRSVhK`=A&=ag*H zu}g`If7!s8Y7@{F{>xcgP2cN#IA`D+NTTsQjof{{juS^hmMMBK<-cQ7`pp&KxMIAd zyEhq^(JxT-*y`9FzJG<5Zz!u3?|X+YxdUJGjDrp(U+Z`qo_()?v&o%VJCb8FQk-Q| zPnOx^L|T8nKUrr(rK;|s?We``3JGM3xhK|JeTuAT`c>*51mCx0|DD^&{)WTGL(9Wh z-9+6_TjZ$KTO})r9!ve@`UN%0pd(Smr7ut6OZbG;C*MpAxP{gpgN+Xc#-A6;$+PZJ z60bgOpVPswZm1IGfjUeQUV?->G(1zd`j`OyYhWg&?G(|;f@FNtLjaZP!>8H!@)Mem z%5Zjmb+)#9517oMZtHV6dIm~6&Q>U3%@2hYgWBJhe;X6r_Ojji?6(uI@(a8}al6_i zs-Q`T+lKF&S)|;F7neEdc+%N?Q~p)nn9mb$_y{#_)ETv3JK8k7W=0wG{CT#ipI$|Q zu&EP>CjV79ccIc0;o(zizT*`$l7lgPEntcauJE^V=oWE+c#sHxJHGI?L7kaEcy)}I zvhTmjI)M%DFeg0D*WXc{4JX=#w;n#CGHGFL!A1R_l8{>oecDQ#udY!nzQ4i$PQQ>_ zQ>K|IzJ%viK))2tCQTe=RDv76R@B586@Mi^30q@?2+-3r8QO@?qKVt`)!MsT-c=Udz}Mgj=mweTk_M<%Q&UCp zCGbHsk}y7~95zA!JwqB+?0GxE6ICGGsGE~p2`kRd!a#nf8gYCh`V~InHkab+lm7-6 zJx@7eou*9g_Ot;{cRmuozOUc@?!$Zw*8)?k#>3lB7c#z$vFH%V+n1#mKav=NHDn*x zMtI`xLOGr-_gY71%b(yR;*Qlvo~D;-yPza{=0t)flnL}8BZoL8pcf;uqxANOerjf1 z2G@l?UJX9}U3}sb>yH&5|JN^T*xfz5G(4lO2LTCb6E*{=qKS?thnn> zNU%zENbMDUl@axR{$1}-WE=U#D;F65%@k1G&q}9!QGibFXz@{G`%pDZc5_EGb~sh* zZTRWMlrL3cRi8jYX>OQ&KKZi4TU^n^nTkeE=h@Sa>r_chg2!<>OpRTXVMgE*KjYXX*6w; z={wiAum&i#GkH`VCoM)ba&WL@pr3uJC9{wV?T`lF!Z$(<0~+pQc_W<|=w@!-J& zAz@zOg;y7m#&Z`L zl!j1K1}W%iQ`6ID`dn{KbUaq*n}!|ZY_d>v?Uo!U9;I*ox~4E5eymz3bZZNHS@2{D zN>6XEfmHjD0*m*-(%!R%Lm*HsC@=4qkdVkSEoEK5bncuba(L@yD37@Q^KU;CI9C^u zpZBT=>ECyMrLtYQ;PSw{d?v!@&$&z6ier{n(8{Og&3fU&1?hlwXApEg(t9lb?RE94 zPJ3(Xipk;?wV!V|G5h+AvUA^FT^fS^$N{Ao*FX;NI@GR}Enuro&B@6zxq9^pEiJ7{ zhH_A#!%+h6A4{lC2cO}9U03>Ch+BVQ9T5fdbuP`=QqY9LZC?ZT@;bQs2BCzvMmbE2 z5LI2e`Fo~{-&S?l6;!gYwX2M2K8607a2DB}kqfzI>*p&Gk%2u>s+T~&Qgz_WwKCc# z~Gi=8rKr81*88@gmC$e6^f!uvF{>Ye5C1oEWa78L_*H&0$PzvS|a^vuwx`ue&6 zL+Yb*Xc|5~Yi|BH&1p6XY^n|9d24HHc2egRwHa3TAgf?8=i$|2WTIxNKu)>fl^BbD za5v67Zb5%t^8AT^+ebFqugulWMuvvhpa}?hcEBn6S=6=1VwPc<&0v1rYMKJM^IJ%H z-(He$3VRiO;IX)Mq(X|y-#W^L8I}DCmf*kR>!7dbFL*clbLOk5rO5J+VJkp&-mMOL zni|(OeMD;)2Tcahu;q7T1Bu^jC-M%!N~sLyT7o8IMNxVJOi zzjL+7D&pZoL)rNaX{sa*Iq13`Sx!k&tD5lQ7bH?`K7Q)!;croER=)_E$F;p!g~igu z7&(F|@Mb&jZv9z@{`ThkkJH3qG#mrsweG{N{kYf{bwHFCfDZSr?!`kB^Dgk+7f7@EV&&=woB(htsuV>!%wy= z0@6LBZRm!bADVeaKlT}PV0E;oe};~M2#K0F(nqzTw0jVJDt*s(^zf{6n^5hZlEOCunV$6v{CN4J7Fsoj72-9=A z7DA@iSg0z5RoLU32>ANq9P8F}$kt67Ps&(esC7I8_T1~Z-f=0v8K0+V(>a78;C6jLwVIP ztabl|FBG26u@w$qczt>0M1IhCXr7RnFy-`QkjHXF9wN4CdSX`PQxId**5Ok_PISs% z*)6?oEy+8hIl%hDWN4=U&=Dfs2E(e|7e#Zf)mb{+mq939fGBk}F4Hfi?H4RMzf5cfdFkg%R6mv0+%VC{!7l)$4n!BVWi;)>!y7L{wnPYH= zv~|y9w*UZWI@o`u{|miy3&JRb7BMqmna4F(NjVel+Be;@siWmS7r7T6{)kTK@-^70 z-gJMtS5C%GLmk_3xJz*qs}T8Dm79}l%zs`u%=OY`a9(rz zc0TUR14MOqK48*6({M)wuD_GFhU(^j4vp;be( zVLj5t`z`_`gADkliWUKn70tM|g*M!? zHb!Jw^6n=H(%8LRq!zoE=zR9_6Hl+6@|#KVyT_i03JR`fKPsb<7)A{t^3_oCG?K>) zajb!jWzlVUr;{~h|5oP}srK9@kLorKj|Rf%70}4gG7?AdAJLn z9=G5gAhb2nOC8y*8}aF`4p@lD5$*4J7F+h4FWrq!zgi66A;{leKiZbPpf2Fg%RLRy zs!$%kM<1>xjE3$*i~a{;4!(w;1lEh2%z`TE0eP6`KmH^d*d;A`D?%Rg0GW%f-l`^- zEN1o*GS4Xv?Hh@@&g2pC)(_KnwM|Sd=A-3v9^~vH=!gT^x#GpddTEVCIr&qE()Ld} z3ObvAl+PG5MP)#AG<+;SReZ%<#l<938-_fFi&u?Zo!WZ;KApkUySh;C)`y-oNjC-V zB!jf=W#vme(WZ3@_mihWZFq)_o0KMra~znHXSm%1U#EtmYt!`cUzZN^)T_YPxbf)U zqN1wRjr0rf9aJnT3fi}{%7o8wcM0rLyt_?~t%;?6rfsfmLol9m72rAsBr%nk~bG zse9P`7kPzHvu6lv8jGRLAsV(0EiL*e8Z;xwJg-*0?QH|D&G;MdtAaQ8Uh|+4!Js+D zt!%2FajLzu<;HUf5HpUnf*dWs@-^ON$U$=u2DR|Jk;Fq^NJOyBw!BGVpqlzH6=&X4<7P)QeN&B1 z2miukLSsi_5ZF?cZG;~K4A6GmibZH0I3iwA;a~C%I(0EMbQ`l*(HodZvpJVBFh*#b z(PE&X7vYjOXazVtSolS7UQv!pfQ#aPt<8ODo>}YC>;5y~X=G%SUtNY+i*M;T2KW$2 zA`%YOk78R7${h~WcQb2~nsUNrF<}YV9SCiqQvhD7Re5*K*tGO|d}oHrScoVbhJ~W2 za&vhr?S2>DUtRSyt?<-8N zYQK`sbh$5A{pWZBAj-!4?w|R-Zl56+85Atz+^w`x3Z^^FKG#PH2{d#G2Fjb+q^-!@ zXMtMB#Ux{WTzU?iHb!M$bue~&*sFU0ipE7XcVt0P^z!s{2K%57?9M~yG+AsB3zM44 zFw(Yz;{jtn!2xQsugD7*RgbXPfVH%k#dp}F=aQ*GP*BZ<^XK~kaJGjS(RZe<6(4hT zQ>~z_?U71ImX(P<{SGGSYEH%}74Usqgh$lM=gu{~tV{JIy=ifghwGsGKs7#Y2PqBC+OwxmKQ!HETUJ|x#HAbWibD4HhTi)6u_^pTDeMzq)O{^tCD0y0clA1WgnW+N zfK&CBe45nCJmDa`m}~3DPN@B^oAS(b4<(s1-fI&(zH}0F z6^NFD1I|*=fqCl>-|u`x=QPpPa&I|{DzZ_Id&jC1D+fCWo*z4QZI=Dt!omg31}FKs zGa;BQ*`?Ai`XWTutt~CTlpmA_l_w36`uTEWWfS~oHKVo2tt3yEr}b&KWPUlRmJqS` z1X&F21DX{cb%v(cm^aR)%XyWVpbmQZ{lKwS?e?Oq^emz%33&=zz)ZTI;NYPp^nDbp z(bAc2R%5k6@8jxp%OCZHb}aWdrgR<3jEQUX!%W6I#0KcdDx4nEt^bXJmT;cWg*;M` z@(+D}>jUytu4YuQZoKf;?2 zH$+kTs`{bYaIF0>rDCB6mP4YNq>@3Tl0RX~PY1hqp zQn>wSG3m~`KjObs!!G&kdvZT+jf+QOw|nm)#5WF_e-3SFZ(=X5`X5o# zs=)s(?dm?T^41AZG_t7G7+#^C5ZXtD^w_HP1dRn;Gj>raD9_ubMIFn@?@8)hl-?EfP@sN~txI-pmuG%gk@NgVn1li+zvSV@JP>n|_7sudIAiRI0rc%C@6bH6-> zB_Zm)x`pm&gN6;WuHDb^o6Iw?LjN(84vSNcTZnSG{J+UThU{Hf4}a})Ce7U*NMvbR zrxE3cogBY;x$+7W2oW8#fBBJ+^h7`SMwY(_0cX!LgN%XW0rW=1&2e|#avf|snulDg zI!7UlX7(y$Bez<@AL{2=^)1z6_B~?j-&dUJ87;L^w)eIn;!d)PB3fED)4BO(g3ZGc z3k)Zz`i>z{8P`f=(2v)(&;zoHyq}0wF#GFy)#kQu@~gpPrwtQQ;4B^(Wi4i-5Lytg zRDHOiZn(mv##aBGLgEakD>DVhVeGr+2y4?VvL9N-`{;psz%fH?CS5iLi3AOQ?_(?I zuHLNEU@aMpqd&Z3FhJ#vK*6e5tRjXZEP=uA@?WM6YL7dzJ0Rq?M1f~~lT`k^je7tk z4t1nT2F(}$DSXLO0Q8coVPQiVlKoY|5Cuiy4OGT?gHr=*5xnHCRs7Z4u4t0mHN$@}=D z?3|HbPaBwZ!kMi|Hpt_n$}`=u1qcg$EPH}kHf`QCbgC6DpCjs?M?3r-(nPcH>GqiTYZmTf)v8`iGdO#FZ-XgYt`fh$H+6yW-enz4CyF zY#LU1`ly@ZNTGY|$B!RH9I3HiNhkzd9r>O3MLFi!FAj0>29R24wdFZ$waq=9;Y9mi zX(+|9r0_zIL#d`r2cwK5-6#J5oc#qbP{pdrgtLm(XKBcSjznA+F4C66Y7t4<*HvJy z;c%<@IWbl3@&|-{lmW-15`x2blq~DRn+RwL_^e7Qs7k1Y4%5+z4?w6^PHy&KZ;OGS zO9ds{dE3fMMlr7=X1z8zGIzdXAE`BE~2< zcov;%rP`!z2ZTMvG{B^R)L8}40GUD^3w?qPUD6GFqu~3=GK{9@X1`_B06Kq#)R=lT z035_F9oNoaI28?){+#cQJdsuK{U5UvtqNBwQKenGi9#_TGU@)}_Sk+cWv^a&8Uahw zHJeZFMBFMXjmK&%a;RK*_!dFN2kKO(Hay$6l+{4MLn1@A#ggD!e=UVfzAL?7H>jmU zQuh+pnxW~&@hoAgRgpHAS#?}O6torcx`x33VWU`)&Ewctm)@*X$s9`D-(LrNq^>+1 z2z!47*dAp{>5?zRJs1C#g;6jdUeg^OMJ;X;6;4i0NPed5CZ(2O8LriDIXVwTTvPLl z<5>lbq-}2@%;x25K|JMMnSh2e9sz}vERE;G$jrKQ<*Li(Usnx6e4E!cxK>^&jNc`ked>-_vU!SO(7nRp2K<(Zv%3qoE)?)STI& z+gUoebp_?<2!AupFTN-#hKNdYJv0q;5AE`r&^HD`h{%(a218ZuId*BtX59@UcmaPe zDg4F0jYF<^d%pL=P;Q$Z>mH5u37a;6VoE-7}u%(B5B{+Y>%=o zRjWK1M`OwZ2tn-;j=0W*6K}ry1l+Qjq3er&=-N;zdYFZm-xoDMkXPV>$R+rctxu6T#u4ss(9Vwu_>dz6`7yz%yC5Doiih~obWB)Sf?ccYb?ug86$E!I zK5}}!(y;{0lwxJ1-@1&kxWw(Q$=1YYZ;ti=MM7vonEa6X2LDOCws-_hP_;o+>dw)@ zvCtuOvE^~xQ{QzG7CX&G;T+`~eV#xQ;_jg?v!lD?5@__H=r{xSe~3huj1JSEw!)XH z6g79kzVp!(i98u?W1JeKyFB?Lj0s?`s$#D?jTh{u!Rk?QWB%evVc|a}?!ntbV}rI2 z&F#=}5sN59DG1Dcg(#Dbl_&(V?}Dhjd+D;2PRS>kYzC{~u_bRx7_Wz*KZTAkUkTnC zWdj)!IUK75N1Q&%S3e=EPNKB;ccOL_a!<2N;f5IrZO^E;;JeTsC0KxLE;2X%02Vax z#Z%-)9ccw;Z`Iy59FSKCJm+>&4C*P_(I+1E%icj9aAI6xqpaBad`!oyryDN1@$5A%n8#ojv$vn>oqwV zuAdr2r}ze@q3kL~$rb2O)_~c}s0BE}yM)QLylx4SmD$ofkw_KxFpYP|vw|9rw%vJj zlrHJQjSD@#xRrmv`^8fmEYPB-5X8R-rHwDgCU9|o-S(PmY<~SlM5bh2#4K^xQ+VH# zaOe{5s9gv(Q?e{$&b6?aeY#cfr>w~H*@KG@{`1$LMO5W{m(182t8++ir+24_ ztN*?kLlH5aNA&=N$);EBo{%DS3jVr8vdqIgA@4+)N&oCaO}3z~M`WV%^M&?>F`6jx z7#gO3rS?;BvzT}kmz0=Ri-l|;vF{OP_gnXvTUI0h-hib3wMWxM`6bWOWM;2#=T z8RkRMhDe4k#orw#MDJ?)L4-&@Y>Cd$jK?l%VAm(YK==eI3H&-^uA5QNFPEkHL2(W! zcXXim0N`4S$)>JFP`|F-St2Amw)SD?$ih;E?~pN@l5Ny|#bJ>Y_fYf7zW?asng18# z&vfh3Rll66$;rRjQo@<$fHFnbO9%0DsqoP9;CC1iK;PDge{382x0vGbI1v!wuMtD) zS;n_dQ4)96^H^EXGnoOj*Poy+lT2GK?WJ_Z)BL(2XCiI8dH#Z`Ezk< zf6WxlnO;M?h&-}2am^mvY}M&p6`(gU+RnZL5MIGa3wxxSLTTy5Jq+mY4~y_vA-jt? zz>R>>;>TPcBsFXN#a~L^v-7|D`7#T|a8YGR0)nV?2UoWUd!j;s13x8^0p|W8RXKj& zPh}j-S8#A+mZbJz9v#F(Eh1^89hJ03IIX7 zl>dG|Z2H#mfy;1tj|ED5L9xf63aB!1b#?V#bTI)CP#9F$Cq&GygYy2Osj1WM_Qr+_ z)SGS*5fMnwY+hw~r4g_m0OK~Qhn>5ffIctDRF4`2$*c>MphM1IuK54{8WZY!sm6&? z@JOttPg;KMcV!QX(l<(>_3Y`G5|%X z(i_d?g9N#I5RUg5SEKf*ux&p0OoRlbc;_zRmzz&x6d0f+hF`c`FkQzMWe6 z`t4gqMWp@!q-zbw=@=NeT~z;=n8dLR@{_L!@~nc&XgD4rXA9^s)yDx#6|ZyMsuraK ze&#)Qh63QKYG+-55Nw}i`+M6mM++C_{ILVDEsuTV4)cNLuozDJ8^YOak0d`XM4px*G1GEiK>jLE2-T01gA{q^v+tLt2Wn6qKaDsNSqT#a^D z4_+5MgB0;N2}ikIC!_DSRy_&TjAjSNFD+MxJXt3JVySgath|)eHxNwC>~bGw&InFJ zbsOJyJ{Ul@PyMi4RZ)Ae5lOaLt-_XdLR?pkqKn)1OsOm7&(PgswTU_v1|FVyKL*PrU%@rN2qm9-0Y8>OzZFP2p7l!_Ic^qKEB zB*(j&;evlr%o~Ims(E*g9x)cN%eA}mz9X1*Z++_x)Vn|N0g2(W*Fh~$6h);P!Gu+y zSLvWolPHhGzK^#Rzg1_3J5yl2-RZTj!qBlUm&i#u6)G`qm@iY%<7IWoy=yO}O5$e3{tfi*I7+ zx4E%skZ;)cM@lr?J>im|eo7YDwb`>@!ee{pyb)`-)6VDkne@9ri3+ZP4)dQRb|wJ? zI~)V{e?KG9-I`D&0FNZ`i$mZfH_D!N##l-ycDO}HfNyq!mloj z5Lu_43E z^Q{*Rq1lui<5n1kEShm_l`ly92Z2+X;=D&C7ZyK9<3UROtUT(p5qazsI)XKWZfEMD z#rlAYJ1=#T^X+RI*Esd(NEv9X!eUx#88)cTMSqd=_<@1oNaz41%DBU5{-znqO&ELX zPBS+5G%|c_wP7N#e;>RXxLbCMDN3t}@M8tJSK>yc@&nUO$DfYQdzG8(KZ@ys+<%jN zJho779_v)i3M)hSU*^iyOl|rws>h8&VYB(kWobd2oUqo(H9f|pjI;hYzN#{Q-L7i@ z{71v8WIyi86_aQj+q3gY1GColyt6u62MR0IurX#Qpw87~_6Xm&O~!5`r@YJGaNsA| z6=f)b$5gT;dmX^o+A149H4q!q^zqrjRQb+P18`Y5wZGplhH}27H2$wCK;!#2$P*i%!kk=NXMSKX@ zZh^j?DNgbOc)RkEEg5XZKL=f!g>n9pZBQ*JC4laEdR3%L*axYVd)WEs@s(ICs>CkO zikc*uew{UZEnaICy|tF(p%axAj>a&yPz?K`%Fz(DEx(rIF>=C zjITE-pmtxoOzfBV?Q!a(JiPfQ8Wn(~6t=VK+D2Wl#o_xBKIs1ag^1f!E69WRp*h7@ zr?I%dw<@Uy>!}M;=;!CHsdnS)P!HV4Nd7o(D?_X^{hN28CdWS}<}9xDV@B6mpFSeT zAea0w)gE@!i=Y{h2A#<{oO~h{aXag-`taGO$wXT}b;^uX3S!^-)rbfht(}*W!FJ|MUa$ zC~x;!U8YcnAP%lj8-0McqOu^Vevk8)D2df)c%ybRD!xyRMj7Ej0%P>39{tT`#&c!3 zF}Yq%X?qIRi`J*pp!zTcW{Xr8-Fhi96+8piMDWGh?&QRTgdb|2XFE^OCF?fB!Cq?E zb=*e>ajK-|r6#96aRQD;nT5;C|BZmD^?z%0BnrPDRp^Vi-d&%|n*$XM-fG|t1b^10 zTThvj6k2B1U%z;O?@PJy|0>iay#CAA{ePA3O7NJjs`~hskwVxlcs2gXFmc06DCYns z<}d$()Wc^l!`HrH53k1Ms)x_sMF0CieKaUWSW@rbd_WWPXqgAUlc2N9<`uf64m_W? zj%FSqfV0Hf(`#og_qr6spu}V~Y#BT-e?l_4uaF_YHzW2*ZkJC6P6863$IT&S^bNNJ z=tu%KApaPWnJ>P7J8It6c_Hne!@U4q{oyVfOP|as`{{tOR@h&`J0O5Z`UXKcGAjih z^kPyo!(OyyyB4Bk2%K^M`bij)KB{?WwW_i}7K5tF1L*rQ4KkE3#(n#47#a5tzxxEE zf94p?JdcNw=+XaLrYR>8x7{JftNrB3^%Ze0p+d6{k)Th!4Bo6dXTsZ19%LPx-#jX;tsP(UXQ zL8{5c3zuloX>;LJxNne$rq0|D$|(Pq06gf7n>D4ha98s!+A;D;dFP@$&teSmn_nsN zHp~-K@Ps8OC&?z^UlSL!6v%_HL~Rt(A@QC}h?~E2Rnup1hQij*1!MU6pJo5Lq_!yT zcs0loF0*N+F)h3nibNjDTeDoIAYQ(3@nYG{4?kbN6g(*)Pz1H_V0{E>kP3?BEikM2 z+}75X|N6B^rQPBA-hz?}uNhZgON)h)va;THd3kw7Q|%7}dkS&ZRp_4N*96E_W62FbHJmS#U3c#cMA&(vxA+t zQ*h`Hir4nIa`mb!fR3f=6mpHRO6!-0fWQ+L6&0;48$bsOY(tVN^X?mm^$}kSg}Lm+ z1=Mx`|72R@{}u(}1*d=hEZW5Zk)Z+GTS+zL<+59j?W&4gh5r!;j(D~Uqk!r5wzfO3 zIbhz?6`0zL1^ujAU$=J~`d)i`ar%o}8J8yOT*(}Ib~WU8--2RssMO($Gk`=sQx7g( z(btd7$u8{((7h5>3?0nl7BD)GYFxW=<wU7M=b7dZ2sM61OaTbyt-1|u=K#1V z%#(7T%XGBW7rFC$C`M7RID*Z+pRP>fz}W*nBH`6X@SxEv(65an`5f1K+?(wWPJYfE zh>>Rr`19?O`DM-nq7{=g+dnV8|M{9Za~dvUtf5`6BJ^P6G~k}-+@W=p$$QKXCC{Uy z#p(R8A5aZ&LBVnj{OQcsR5n`;Y75Q$=W>=DDHu<+XmD+-k2gzLH4-a88MkP$H)R1{ zbC8*OKP+||tL>4}us{8x%HpC*_qx8G_8$j2nF}t(!rwAf#L&=YO@Yv|ajM}$cE%*Q z02VE$kRQOcYS9izzSyduwE&Dar)=8oPtsO22X(Mpe<$wydQ^hiNXy*ga*d}m@(8{xrQ>e}>-9%4|B(YX^#gfoUr971@zdIy9F+;QF1 z2vd(fR?*BF&>zR4ZZ_MqOoP+IAao(BOZyWE`xaHCr8cCm@1Ggh{( z#CbqsIWbyR!>}ogco9+**p5+eLkPeCKy!;oL2(V~Y?iG9f|NslKNsSr>`axkPn!Zy z>)4sUcXGkGXGa?>!vD`)R+f+yMne}HC&L*_B|gw68(zdN=H=yOe)ET&^pVsa?(Sa! zn%f-Jqs-Nsmzf_@M*-};;jPL<`g#WRRFgqG?>B0e;r#J+$*LcBPAbOF!bP|oPbSkY zRg%qkc-6mk4~a%HIt$IaD|~`o1^NkBTw~!VIW%%n$>LbV=0wchmx z51?ZXa-6ej#F4SsMQXLkYsVBh169co1Vfxi|9Pjvs(omSip%tvr>Bh@y(wJ4Yqk&A z21A;1Cp)$YPFWSuI&{_zKXpGrJD{S>1{$2LT?0$Vy?R-C= zg4;hddU=0l>u2WaFW;SatRDU`L$VXWLN`aC66k+LqAS2(f&@e&P$yT&3|gy#k-QOV z6*aHB5k9!@2Q}|bM8st|PU!#8R048c??B6Kj+OCy5>!ES7;V&xKil+D^G~H=&&%ZX z?-dj|Wbkep%uR=C2P1icga5-!P%v}+JJ({tgUy4VYqk-R@aS?1*dVXCgU3q?l_H*3 z1a`mPf5PTu`iZdb8?zGZ8_ls$ByzE}!63(QCzXRfPc$HQ#vk>lshEex-_eT=4{zwc z_2kGM%rn;W!Lh!VmH$7y{%c^49t&8%5<&Clgi_lhT7Huc6D=Ocu7=gWlQVB?oEJUh z4vG@uV>N$>noMemMg}?DQ1O;mM+ptnQlgMc?(hJZ=Ao9*JV)}hdMVvHwUalNeU1Hu z7ZF+UIW7?{?i{?$xEWeSpZbkYG6OJ}aQHt6G2#$|i6GM9*Xh+5GtD56k4?=lw+`K&=`H?PrS(nc;yWm?5Evn` zigf&+(TiOX)Up<6JYo>kIIOr)z^WpEOChtLxjJn~ouPEMSu)zfnTl0*jJbV3haSt- z!*(Gk5|~Kr1>6j|i=Ax_RWT*vHK<(|0pUxqZPO$3<*+^X&DQJ{4oW2V=nXE#QMx4I zA6!>bEC4BeO;h&UK985#AM!G*lkER-ONJ1j?gK+gg+t2XfM8~ucZZQBK&v+%t$<5|@7-=J7*A0Te9r6MlIoMt5qzu5ea)O^okO9+TSsPPosY1VV{% zL+7B@CN??cIUtC;{`&B4yPd~7<@R|bxn9RqjGO(+uK{%*R$gz84Atph(-wLAuIq!d>@IzcJN4ux#rhUw2@8l6}hg3L*M1n@|D_yz2UQ( zJ-^*Q^IF&bu?DjL{dw~9E5k(HAg#@nbs9IBK85M+fu3#08>|NV_?q%VnbH4sBc4E_ zjuBA+er)0N0xc2DKKbaS6@%(LK>r?M%&eW7T3?X$?Rj8l{IL?M;C4L0g%6!m*b3U8 zTu5Ad`H@+03-KVM@o+HWw;lwidylz zaT1LW%Fs*FrL*)$IXg6;KYYa7LAP-Sbi{#H7Xywc%bJv#>=IXBChvX8FDxvl8t|T+ z(VGxhzVx{4dGf!z=*bLz=~w@-UlcdHc)nf;X0gg!aeb36yXFEB@0%H~kH&^(ekHvQ z$`HTZvQX8huK*`>@fLJ1RbhUSi*k(-OfPecg#J*cO1qc*1w{Ax{1o%O-YR0oqvNNj zMzajapJCK*;Y8+G=H=eU0RVmYRBxJldA9$Q&Hn*-+<%%VcrF-%)=>-e*?3oIBAWNy z!n@;nY~FCK!tOU9bxW;!RzTj-N-MV(A_;i;m;IoNFNQAu97P+w>Cx&}AR*UcaE>AG zZsrVK?Nf{#*%8k@B1%A4jMV~-FrM;1V7;*?E46Blj=VkGL+=-H1?2Q~it%mpFs!G# zW!CJrTR(Vg@_7Ty=J6~*1`cN?DVWvtkQ$Cd=z6DhoVbk;p%-B4d*GF+bt=~KNHy6q z@ScaLg5N3w6bVR4I_j5PRLM3ES9}7|%Q^3JhWo?SR*MxQhrbn?SceYqJLUcB$ALlF z<-P_sHu@Fs!UnH{YT|;H1QGZ-_`GPLO{g{9>!})iR*>`@03#{)!B_|z2}CA%%~upAD^^kD<7`|QqEQA4T;`?z91y(L#gFvhHLZe z%@sBCItu{3tmz49%w!s$#NN^`uTO`r82I5`O}ws`(WK;`vJUxMJw!Aap$#BGPp+hcx)xEzRe;v08{T< z<6nQRnK;zRRBxCaIh+JTYz-{5{&S#*z~_%mA17T~8zx#tNd1HalYbL_@BUKO8eTU( zN$)n28vNg74FeD%I}|px4gstLLG(y74S!kswp$q(+pfgV75>|u5)*1HfRW^b^82Mr zU`K;Y1p*f_Al!UrMvtXv``nsd%td1mKnA6^uo!NUK&6;Wy~!vbWM?dWr$b2-4hm z`L=Jnc86Kp0HWgqV8=(3)HiT5EKV@?|JZN^omCwEn}TWOEgmNTAnwKM528MlLz&mqq+qd9|JO(i)2&>O@)`dqZ9_1VrIiSgq~iA+V$t7tk&GLvXB1#Ir2C?IpKNL)wL(BVX`fJ#AOgWWttz_VQ|xO z*vNUkBu~zBL=^~^atpY=$3tv^zu>V&*TYYHRCVtsQlzM zr)VH2virXuDE?bGl92l(YH7Lq)8}qg)vkdr!lOl5Q|lV3U1IiPqb1Gx)nobDjrljS z&0f6ddST62Hu_!kJ567fKn@(^G?MdN_A_M@d7t0b$H+)In`3jOi`~zWGOmR#Ou_f^r5k!*Yd5>+s<9rc?FL4%}cf9L?2fT!nz7&R@e$bxZc2#15x=tx<;C;cAYzYm#I zK>C<62#%O+2)G3(9{?l^X7#lK0^2fx=smhvW=H`fE48P9k zd;?3q8{fhgjq;oNHZ+*(>8CvUb?)ykJxpUCW)J1SMGH#hUOtZjmPh+h-6m2*ki5LQ z5gj~wPKtGMMt@D#!Hsdutw?Jb0^|w)Yx0BYsbbx^n&~h8kG-R>s@hrI3fd!l9#Ek{ z_!X2RRpLhU83a@Qb$=l_IU=RRP_bxl&%2qpcE2HLotAW zrC=Nlh0X!q+rIzzcR{%vM zqE@x7Vk7~??6sO50kg~RZ?PMc%#y!4y+FD(gaM6koR`woR{C04b5b@8=H+5;YYSN` zLqv_5OL{Vx$R{ql)FfQlF*7A1f8BHoi;Y%dY^LM7*7`f{9W6`w{mr)zqQO`RQSJLm zty)4wSRkj0G$`yd1S6WD8hz)Hd`QwP0k{{~c})ex|NQq3mkY}wW(xp+4W&`{fJEC03X3OKi*N*4@S}k0lKuEwT8}F? z`+bIw?4_J)vgL^&5zJik=drFvaKCPnvs9SSolDMg%So^|)v z)fwnSD;Cr!7C1MZnbo!b$2tcLk)YO2rhN8x)ytkQkhKY9QDZs!C-HZ$E6)%xO{tVO z>_4M!{a2`b^LGLbIA0RnQm^saL&K@5Cu0o|y$SMMDXiXl;{%wZWsnUYPz{zZCXAK< z2Lmr)@VN@y{vu%SId{YDy_*z%OGH$JK(cr%t5e9^r0N4qhN(Rp?@#u0(r}1a2f`n{=p_;det;16skDPOX}SV9v~;|uNCNW|{9n!y99d+#atWO`7)S*~NBt(M8 z5-?QO-BgkoHdW448h=#8?j!=(IkYMS3gugMzd|Zpt;u@VP?r(Fh_+o z&%~T_71y$Y;BsrcWXd-mh;X14?P!S^CsBVi&r_2hDS5N!BC3!py|zE@Ygz)&J!pu` z+-5|&vSj|?(d^I|JE-+Ca<(Uy_G~7;d+a{{lXoh)_Z+l#ifbI1@xlN4Hx_{^{C9xy z2W0$wjlA~R+!YHXpD;AZIN&$WW7e`m`L<~C3N2o3h$5d8enCO;QfJ58@78TP-{3L( zYi@PReylHl>9_)hf#(OwjpOa!quT4hl>%bUpFm+RbrA|77xp1nN>B9F3}zhxKzG}= zcuS)tEr{|DIFgbUN6C24su3j?6b#dFo?8A(EEgGum}yeRseNRpVwkMB_~=V zNMy>2z^WoF;aQA)()fEPJco$VG_@&v$tw|sD?k|Sm=I*bUS4wKL!`qny9%so^+-;= z@F)VJnT(?3*7G28B`t)1QT3S1aDa z3`lNhQCFlClZU7>)v+^ol-2(!cHp0;E+LT*g3mY=zjf;y*YmQoQ=m)c#3dqZU_uH0 z{+DQ}#iMJPQa9r- zq8M+mt74?1eCv3n3=e4BwBb9MkWW4^Sz^qP8&kR(R`mMzg)gqwUm%yh&z%pTDI|nc z*n$A%-QoFO!?0W+T(DD`%?1t1V&B)nEOk|Rm1jFpmM)|qm5NIfX{2oBe+44|tNRqV z*pp%&|F;|=K`-H^4fjb7UkHi7&)cbEL)eU8{}5V6Qc_7SvPo^!Ux1_y#$p8Ybd(R| zJrWm}hz!~94!qnbQh$;C985k$xV_dvD%Ib-npuYj;&ASr%(|OpopDdcqu;Duk26w) ze@T0`NFE}f7=^+h-oi8qT=T-1Sh(br3ziG%+PDf+#c`M&w$1Hm%VzmtpUyf}NIdl- za5jqVyvJGrO<5qW4v`rBn9E6qck8Pq;x!SDQPxLsd!*NXz^k^b5D<#`)IyeCgd2YB zA^`y%wT|i+zFY%x7xzbH=&3M%279lot7cMj>$Co`0PlVBAt#&AG`UlG{9*Q8(78VL zmuhutF+LT_@z+3#u}rKn54Ypu1La4y)CLaR2~V9@$JZUr_tU^2bR7*-HB^t#kW&+CBrD%$M6@mQ*BzH6k|H_;l;Q%qoLj!<6h5nd zOM*o;T}KEhlZXR{o)0^tIn}scLLCEd`fm=zihf9;Iyw5B+ znb|FESOsm6Q_D!g-NR*vMqTR*`TXWc)rv(PPsc%s(8k_rA=kVV;Gg}#M2Fk~oR>c5#dt8J4u;7ysiw69+Gl68p-mfO9_7Pm*+7nd z5!x*-n-l#UPJj*Xz)V_$svVEuu`u~v8XOxcT;O&qR$@!84os8AnF+UN{V@D&E*GJ8L}7Pe^{`wk7a^jE;}1Tt4pD}0FGsz>`j@P39LQH7GSD2o zw_ekP+zeT!XLM>U<{)TVF-@s(GjFQ2NpsvpN;padOj@wwF^7Jrt7Mr!{e*dOO%L;} z;2HRiHrtu0ZG%z<0vFPS1f3lRmzu#*dny;93=tWIu08KQuAirNgU9b=TI4cQy9Lct z{jH6KY1G~UhNFAh75tAMjFxD0+8pH00fxw$iWJb{-a5?&^n>W39aZ^|x0tulbOEoL zE)u#!UtR|>4WHl%&z@i2-3D@Xk3eJ_Jia3ST;n`0+aS_MWWnVUHzS!CAfMtwHPVz0 z6=I|n_S2)pP*i3e-d5q ziaRqpwl)>7dT0emn9&v$+Z2u46yjxU zv6w9p3;J>3cY1uOLFJO9=Cj$V`sU}e9-RvFyepwjTj}t#npZ!QqEn_$c-$B(Qda?P z31wRV5bC(r!qlau_}HN-SQdn)b51$liJCTaqWU>_uK+Zd9Q>=-;+Tg{>HwR8dFt7X zSK30F7XRre;*)cjT0F)w1m2avoJ+41JX`U7mBW;)YQefbh#EacBZ4uXBmFwl12w{?xc~ z^du7qj)plClTK#Q&j3&UN1?E1l_7E3MBCrXF*X`R4y(ucS6{^JK8K@w&g zoSbUFapjjHkC}^a`Oe1&05sV9X&fx{{30hBubpkrPXBx7A(rkQJ^qfN;#dQuk5ZVf zZmo!eNscLCM)BffnuqHB4`cS=PjQ)!^z^=@eRnxaSr4^K_@<+agibgN64f0e)ZEi# zqhJpsx+!Ep7F;OC!+`3Xikvc*ueE{xsjO4aA26*FyCjBg|M2auHW$CQaiuz51Iv}= z;8fCvK@SI?Chatbjj?3V;pz$BuzLOcv0X1QYhz-#9>iz7dgHuBtgwa7?0|!O`zfM= zDYD4NIqKX5K#H{n@zyHSn#8c$jBA=7Qsw&-?H;{g%|EGsR`^Dm`*+-d*C?*B{c>bl zYU9+u*B|t6j3JBJksLlX@BoT;3VwH6ObPK=5>4QWe}wHPr9Ow3YIl(3_%nGA#eI-j zo5U*-YGK8$iula&Ltqt^Jd3L_$W&Ff0u<*`J{Cs~1Ww{zMI^;hlU~?PEXOZqzDtb} z4q{JRrz{?)>5&L73yN_H|BW*Jc^$zmKfFEl0CTm!n^u_yO+zc}RCT1Stjzp7%12W_ z{WO(A{3?^$p}vqIB19IZm8L@-@#wsYMA*~Y&+6%z;ZhZAYhJvep7Pxu=>YP*n>dC=n6bX&*Y9qib#9lBe`@jGb@b#v=NryIgZlRbwAZqylC2lY%*==@ROPWgPSTCjOqocZ zA+85q7dJZ^y)5Ely_;MsVr)8#Z)-wvN7QjLtajvvihMlf?EX<3x6jj9#yE%>1sR~q zlg^YRlCSn{Yz#uQ^tjrr*!IKFq^@KMWn;;$y)pn0_q?z17vjk?zN!(Rt437MwYOksUCZ#) zagp=>E_c{w(-Ia$V4mkfJ2UC14oPoyO&Kg&WUwoF)QEaUHuNUi8NMj=JNzzlwz<7~ zy0mAc-JcoL@Pl6cWCIaA8aJi8@&gh42skk9b#u7zIf7n4M4>RvQ%3|C?IWl>K`Z9O z=$@&DWhax|`4T3L_e_w;au90$6Waa-bJmgI&rSG7_&8>tcjEnaN4_!uf*Tb%vmA0A zEgW_L5Ix&2?UKiFRg+Z%^9RD#GL0FxuA2bJTjXM5CJA$lBXDNlPvkfgz+9hsC^XKF zbRgj}wQ8kk{%*9NEl)R}v*3Q7DjuERl_gjL^2Bu1nq<~37j7$;#v{W+k@TZgK{3@1Br#@pT6Jdy==+U$)Rgf*q6 zM&C@!VQHKNjN5H@(%S-$I zR-k-0B0;fIvFxaR+;%T}+!kBc=0lGNr9k6^L*5>P$;Ivny6}KP`swedYkDZjVHTZ_ z`3|6n2avlWI~cg$+AwOMOE7O0!!@W(nr%1>HMGP0j#e*4x7%X5B-rnMb+{VBUr$Tp z!-YuPDIN1_n-HtDs;;XAd|~u@oL<5Z6e8CAp8qf|qN`q^gev=LGn&5wdHeiiEuE{kzEi^p4v&xDdf!BFgs`( z3nvs?L~MlLXSAK0k7v1z=FmJ-BjE|iKl&O0R;45~fX0JcMCENM@QicHKGzAWE%cJz zU=pSh^K!n&7Unbaq{PAc8yAf<3sbBA%K6NG$H;6MoAPs2l|#6t?=Pr)_=hV9q?&H8 z=@BWo4zk!-QB4!I`75MBEHD1hW`eia_W!Ow;?+7OVYbNZ3eur*%)%%3L(}?2a)u!K zPX%@k!j7V&4Cf;+wjx@c#_AofB!kgm85kLW!DrELP}>2=aF+9az;jo21s?F;@6qAM zP)!0yMBbqR$oPc#rO*w6z5s|^Y-3#CykWqx`^Elc#t`LAA3PAltJ;YVTj+YPznA2#hVLCLQ0xQY~u*QFX>$o%jk zruzaNrHy+`U-PI^B4|`9fTUo`F0J$8^7Wzo_)?qsH_5UWsG8t{R+2rO%L4A6z}h|d z2fZot)D5&Q3|R&!u_6HLmn1(_5i*`5ggjFS7CVkivPjChc9YksP86nbc%PDWqDVve zk0@>8A0OMqMkAZL^u1DZW!7c-X^xHAr?UsVQeDhF7=3TWKbManP|Nv19pWlL!@I}T zzQtd7?30$FZ5%Ow7>EGilLg$?|9xkzmIEu9moNcdFgMvS=KPFNTnyhKfR<38DCV0M z3VS@vvM;2d7j)1_7D&}aZv}y3M&xdP&4L{S{&?N4SU2qig5OUgH!?$lizI%^Oj}Uj zu$0K&8?0XU-v$H9W0^5ECbftLaD3Gu{p74b9eQnUn~6Nyr#9@&PD3rH4wpNQsg{{lWX-+rT&)pZA5P7z zd0zUk+f}}uZHe)wn5Pv}aA`^Il(;5WKtWX~{cX!j4{0&@wO6Ej8%CYlb`&$0m^bTL zz%(A(+gz@}ut8J|GT)IjOszudqj4r)|JcYsZ1*c0Dk8giiXUklQ7UV+%QVK-*fc!z(tY1k*RU~HG zo_5iAz+P{QH_>#Ph!fMh0++9gStKOdJ1oSQBQ+l%a^3{==+_1vbSeSJ5ma|&&3^W< zu2!VcOv5KH*QOTvxcmKCQzF%k@>B?_Po5U++2l>b0<~NK$M-MyKUz?W4dnF$wDrGpZ?}=wA zW1RD1R)_R;FF~m{TYbZb0A)T(q$AZi@Zu+?yZm{hs5GsPtSc1oN~o`W)Emb4gX@LsptQjw3}ru&iUONibbsPYof z{G7p#eLN{UBNZEha$pAu>r=?IHO!c`bj5~1ll_|1nkZMw9d!_2a%R8Y_3oWyukh*R zDEN5}jyo$yPl}4qF;ZM&tmYqzD3^#xb#Gs)h*(XNu#Jfo%hMQ@OZmCWRIW0BETQ{FNju{555y>24a+Kz# zn>UMPx96L+lCCOdN)JQbVUJWVNH3W#_mIB!^5)OiBXMyojjuUoHL@wcfH`@d1wOd7 zYIl7rhnY!(B&U3BlPBw?VJ~4zzv)~v=ly$HqfP77XgsB~h#~UPr-R&F3DvZFq?BQi zX6*9eVmA8H6ds?}m^dY`bKkOi+8NlsyZUUjteJ*Bxxb?`vU}!EiR?GOkkgIF<{bwy z9wQr5tv#7}OMAeNoEn@U>i#{6Gz;${Q))JYhCAXnZ5(1;xHQA6;(z9~rmHoIC5s7N zScs9@B592&%XJF3{XG0k^sgvcFwN@_w)b4~KeDsd41-#Xd|{QOZo(qtZpXjwtOsfn zn5mFUxsPBsg9K|E9Mwg8C0$N!GKrjgQa?8spL!Xx>9oHh^3$psvQ0fg@v30Vr3J&M zn5mOM>8$3f&|o&}kK1Pb>vfxU8rv^s`$n#J9aoUzjI6sEL?svo6OSQY(`8c4u;u|} z$a!$%Rd6&n+HY6H?v2Leq<{E9 zXvmk*Th7}2;K19%uNf!KK=i8CdXCppWeC}UHS*yJY?pP(6qnxjf80);eTk-iD@}T= z85%lMry=RiP-k7%?k+|+KX_4|q=>K1nlGtGR%+s|zO@R1O^Alin2w4b#~#oBpfG~! z-J}~Gj;l`G*YcfGvm$%A1tVsZL)uBFas8&DOZjXwWS9%IPC|$tfw0fBpS;(`++p6Q z$NTMZ0+c;HUCGaMa|u$@>aH&EWPHb)3)jkgh`a9Y-e;~iiGy@3ks%r;0}@1@-N=+A zBrgkQMqNgl<*{*$c)jOb!lOvO=7dpB^uY634kp3cVD%HeN0)v1kHz3`TspqO?d)D; z{AnM^x{$X$@1;1|_u*cY^p)+t*1o6SvMmqoCYbCE*#tTD+P#YT3ZB9Ol^LJVII1Sy zyY#a4b?DWxR(Jrs%`Xebq|ha_nzy~vT5$QU*_F< z<8#56;uF&4{DRXcQKsz6O*&Fe6|q;=1iO^3hktWyrm@j)AYn|B8#$c4Qg&RB{>9oj zVlYWT|L5YXMZJ_4Y0J8|s8%g{f6A^)b_e=ImeRibugTkqJY85*(}A{0M6x%o_*nyI z&h~r7rl0NM>(}yvdnA`6`?DjHTWzs-a+lPah>iMFk#b^3i|_X1HaMTe5=AmY1*E29 zyryOz#Ds}GQ$Lo0XEb?FiS2qtVGeQyx?#o}?^@GnXURAC8`=HdI zbejI_>ctlA0oIRuMf({klB2~(ui{sS>~D&%fBpUR8lWVU$FF}1CChsEpcLJ^wRF@v z^561+K-*Ttb%O$(@7#lu&3cM(YmuIrbSc*Gm#VkPUaOD;l-Z@W^5=Yh(+;*5`6FfY z9I6&>&`qXMN{I<0s=|{s$g~sK*Wi|hI1+g}teK0d0*6qo;IS>5I#XKN`m$#a+YJZZ zrdxN(0{IQ;Xs=rjw(POznflJa^v2Lwk{Lck68>_=jEv&5CQy_IyU#vB;g#ndSp#T# z*8Pe6b%HIwfGqYERvmStshOlMTsK)imJ%!zK&-T)a%hpKa6lOsv9VmrbLTfhN&=cJ z$1?nq+;&&R4{4p&iT)q2f81unV-)USS<&SwCxTP@&cDjmCoH8t?~V3+I(bl2h}<31 zk#c9tWny^Jku5ur#PVE^`gSq@oYe}IOh>!auHwd-k{LbW%B>r&k33H;dO7*kd^6S~ zdVbf%a$)-VJaR>_sB}lTSznR!mbdOtz0M(HwZK%zFBSTYfmBltOr3CQOP0ZF`x?p$ zQ++{`IlMYturQn8?W=XIv)Zms=4leN@`go4XZHe&6=oWPiDq1&oQ1a8-Ai^?6}|n= zj@-G^DDG-brn#HT8C9Jgx_^kGq_d=mcDiw=h$Q%?D^$(G!-he+fWgoP6|)7Mhu7NM40p z3BKz@OEtWyBZcqilzZ#boZ_>)`D6ye90NZjSRJZK5~EvAL6pGQU7=EsuD~$XnN^^s ziw0D_ui}klX~l6BaauCh3XR&Y$)T-UQjJ`6q$xBP@eM0~Fv@UDoIHinV?B<3xPl9x z_k)pkEcdAL7$E#h$-@H=W(Pj+z*&;L{fGE)_HDyg;pR#H3m=P#l_ivkR#1jSU z9`0(uBg0~!5;v=!nkXp@C-08h04mbITk{b9#HCCvfuJzS>J49aK#;rSa;(D7=LIyM z!)N3Kl)^EeyPvzjKPKe8uo1sO9m|Mf`@Kc;ZPEJj<%p4J&6j0`StG7%c@>`dzgJ3( zj$B6zQaD{6ucjh zsuK}gwN~`teDI@EVApMygTVjg_I9^X!i$U(Y+eVE{)!A*D|X>el!uYmAABl#&vkP} zg}c&~NaOvreZFkPpRtT)y0z?^2MsTB{-v*+;X(nxkaM<3q=y3)y@%mY zN-xZv4+ywwsA%|AfYsLQ_Sy}9Zf0(suX~fmqu<>=6R-C_{{5)%wTeNuwqg3{T^8x9 z*2O#x4t8e}CGI)ld@Q!_)TYDFFURq8^mdmY_Z;{Vofy6eI7^B49!?)&^x55GjJg&@ zx_&MO@AK^&)6wF!U-UAsedLN`&DOkG@HC&_4bfyTQjv1p<7h(`;w-N?gCalI6i61X z>+MDMxlC-zty55oT$A10h~AE7?C#hTEC*4%m9JGQ`~$2p+KdcY9K;aKG2rr*Sn|Ib zK=ORr4#KZOR7;k=j$eYAuMtNhM0c6p-gn%OG3{>+iL8>IZRGjvbOG)w z(SuE%b9*H^&F>6NgLvF_|BTiYzU+8z9E|WJul1TweKF-xd*Lv9BmDqq)fgMlYt+2frRv#I~Qb z9=WWWzrXmN52aSsntRb_X1nic@pBd5kWlS$mXg1)C(<~x*rq9wj^9zgn$}|ky(Qw? zryMYIQ?9wp_v?e#-#BA`d4x$urO{&UX^4a|Gb}q~DLin6nW4q`OdU~`N!^!CM2o)-a+} z1Ou%e6KRDF#X8K~8|);~PRp`OkAe;pU`RtXf+d#`oU^H!oi;!{_OWhfh{(qH#vVJv zyYTfOo@jCcM-K-kZ4j4rQ-tp-y%@ZttZ&8XP(_FSD6xpBFva*;{CmAiR;5?E?S~1| zDyo&;!HW%ajk6W8oEJGm9Fy?s^Q5$tWfK=`QkhY-f8^K0;Flv96{P4$)rS(y*l^AC zq-{T_T27EGjspm_tg8s5BZ0brv+hJ45#R6>dv(k0J#`>DWkEEJF&iU%<4zNt)=+IC zc>Cggb_{na@LQ)bXaIG+#_F*wQ)wBK66;6unK)KB;i69jy=S> zcStp6pyJ1y>)L3J9({GpG|nbgVOk_%rpJ-#y;t>HwtaQvaoGO*_bHKlp|Z3-vfq0` z<~`&lQtOcThQ+v++ppJOQ`k0+9FHU8x{1At+>cZi!X&8w6*cheN+wCCwogl+Ksxz6 z_KB7QA0h$&BMNpk7grVf{kjL9Y0yc%oi3A-hv~_C8C9C8O@Z#!w9jx4avHk>yt9^m zT9ia1H7V7@*r3HHA6f|^n^6)yoRmgw)ynQuEA09HO^IWgSAAQaVhOoU)J@)>o_Z^l zo%3$_@q@pw^&`XbWJP~XbO3Uyj7(7z!Lrp zX6BZdvHesl>R2=Y-k>#!$stGmRHI@3VDkWL!zCj7S9Moa#t@A%Phea40H z2Bv!=gjgTCOckd{D|)yazNVza9Jy)L)Xiabu~>0m9M^zwftAh&rM=U|AyY0)UB7ZW z(MB@SwyrqZjZd@(_P@t0Bu09zI!4}c17bat7h6|vQ9aB<}x(+cpYz#|FNNn zWEXPeC*5H(jXl&TX}`cVI(r&xWSZb|bMySlxKq`EWV%%IuW%~_+zWr#j{Pn*RS)Mk zK14k3lcOjisNoh?io}gy(l5Kk6RA_cBQE$`h@mhm^odk91PFtL8wkI3(deS$Pag5B zjWaKUmyaW4U>yLcra{HpY;}8yjb;RR8S-9t;c+;p!Z=}F5xy=wadAEeWY1s=5f73~ zJ`}l=`&)-tVWoxaq6z8Rg6F^yhstRBLyp{>$2SyF=(Oppk2P8p59@`#xj*p`JO%*Z z{(IDq7-PIJ&$F>s)vk#|mJ)B1%J|h=+f|1)qvhS1?Cfb>4vj=yV{*_zgJM992;zO{ z?4vRYiDCb^afygT&_EL1V9| zl9=@t$b6Bg8!D}<%#=W`{q)RyHggzJ8eOCGoiU`I!`yqh_KR%uICS1Vc#!X68T;d) z_Rz;SgFQKTwey>_=!R$zR|#vy^rv0$d?dw`@rHPY%o78M2&uV{l?(r|e7NBl{!DwbE)nj|?WP zuD&7u*Z=oXmkKz0IQITq|NSNL@7lm<^X%J3d9hCxaT?s|lRs-O`rOLXjXa7jc zHIaYO)l28y)Vd*CeC0QzjoYeSoryD~{>uwr*5#Avl;9%KQ*m;2rY+Xqiirt|!|7O-bJUgNd* z2oUZ?MMU-^CVkxN?8d(v=;%bhTpjsavG=S7FwgyNEu$6A=@_>j`LG~9G|pr2HvZ0= zQ}2SuLkw%JD{tK}nHA+lM8MSEo5SJgit!iZVRKmzJWn0ZG72|2)`_aBX7TjI(>!Qfy^& zV>ZM&gCDFsnlk4>gvm=!yHGBRcCGi!>|Kl0;4vXMV=UMWyz-dF+QJ#dM?jXz6NtqY znhWJ5G>KxXZO6a=4x(aR!w6J_w!={q->egBfED*H;7|{s`>%p-Nj~gMM{%089%G#17H`h2JSl(sRek z9@Yme|GF;O3wyGcBJSg`AubXD83>R0nGW>0Kc)Hic(GUpj}6t~>LEX`3PZLKMg=Ep

Fpudj>cW7Rmb_Qu8yHL6e5KCAC?}Cr^3y|MMaa);zEQm%SY8D#T zj9pZ;up2GwW>z0~kAw{)D-s}c`$8$;X+@+LY250SJF5=<=BQ;~^Y;Pdh_C{fy?a6R z*a{R@uD5~(2w|{gO_inAi3K6&mpC@m8Kt|Gb{M8mG^9f1y4Ap-ob&H3dXwAsozjmD zD*MIOhi$x;c8408NR7N>1ScGF8X^d%(ImKvW9bD;q)>YPwYVy`^)krm_0y+MHe0jp zt~24{BNdJ_((2)(!Q>S#f9~Dn<13q}@$%x9yjBqeg`$#U4V$0$Iw7vQRU#Qkn{ZeO-~gE8MI75M|r|#)}9p&C+>!GMSRb`hEG8Q?{4!$tf=W~dO($D0zNsp9r!->e4@ zXr`f?%!Hex*#D+Qrn$E0;kMO5f`A6A zNtd=6)$Si7m3?v)V9Vil=isXG zf(nN5lh{zpQh3=%&sfV8UE$c4nvU|-(fPd_=rNX(KE#*!Z}GmY+n+An&(MSVXM5b_ zf%*~SZq?$`YVH}OaT%GhNzEH}H)m81Xsrt1@bmrG;#P%tNT;y+2SC+PRBYZl0>TL9 z{Hb5l-l>4xuKDPI#epZQMamnERI!6)L>3gO3(3=4ISJK310h>R-5R|r4G6s9z1|G9 zsD zgA;-Tu0+KJyq#M=1!fjGP%ydGC75vISf?vrX|vSzQRO+-N&)N!a?;9}S7z5ViLOkek8%sW(*sER8Oi!USIiYkvse6y_b|9-1Rlz*Va&XJ$pkrNLtv&~@Gb*~%K+c^MHE#u>5u`G z7x33n*AalYLYo)p5@r(7@Ifrn3}1rfO@!X`Uec+jZ{Eh{D9o2@ z?b&QnI5zgewC&cDJ|TQHE2~2WyyTK0^1b;B+jtX1m!oTy?KCT=Qca zFL*xBI_OkuB?~xI>ODa6&e%09?6leBI1oKs)D4f3K>RA;SUDk{oe*o8-^BE0$Q((S zrBbY?S1)G=cKdCHnm}D5f#*CLj%e3cC3$EVqlh)=_m+@5s+8R2mt2q3{lb`TKmR=o z3DbSki`U*cNV-emFY=vb4}(VHNsy{MtNG*fTG!u%ETja8p8DeJwL-A-?9;^pg+GLs zX#Stx&NHgXu1muflpqijQ0cuZEr1ZDNeERzEUySsq$2_nigXYR5PEMCDNz9%5EKkW zlwv{?L=;0Wp($MiM2d4BzbR|htob?PA6ZJuN;%Ko_u1#VMAjaysFN}f!71fh!#v0H z^sXK;(N+q0DUz7v#wb_$YVB)^f&I{wh=%a|!P&~EPa+eZ6lG71?R*%cbQ*myX*60Y z=M02|P>}Ywo&-en*aOSDa{|T2fe#ebobfPUPE}f-$C4SWS`i{}9t~qCPG%Y$^6~xn z07&jdw~KTpg`!YMjuiZdl7~U)XMBIE5SgAv|@Y{zNc~M7k$NI>dY8M#UHP#-6}@dIaf# z#+-FN$|=TFNOMGzJ=clzx7iBExrgzFTQ-El8~k$>r@9q3JjtdtJt1Naw|L#3J48gM z=steVv1$3|#ysBd3NTF@0NSaX0#kF zpM8I7ZGE6QZ)MAMQThF+P_(_(6S34Y zp_Ja6REE7PG9}$~5225!60l9_YyZj#22W&y;Jxv=;;*{Sc%-0+4U+EcjH^|8-iDS( z4YPQ&66agrvo#;LZ(kdZj$JRkP#A7q66C8p_m}iXs@4@(qJC~+$TUw%vFA&f8b>up zw=QbRYZe?k;d);wR4@pRO3+AGo23s^~lpbWtogd=C;GV>6EDR`Lyh23Xck(ZU zafDK`#G*K9>4+_``1}dNAVp8063)esixay;aL)|*-}m@F{<~_5X6X9hnS|3LG+78t zMfZPw&iS(RV-{H)=dqSc`ME_ECsh(F)sFegRe=bSGfwBcG0cG{sZzT*2=DT>+lJAO zB^!`>ack0_~+fi+(dO$$oLd!MS6a7N_yF02U~u!Jd>aC}9I)xIZBCRY@)saHXe+v?N*8L> z&77}zhnoa`a+u6m0Y|EsZvAKQh(|nWdhqBoVmiL;W}Z85Geg_XjxR#~eQ>W#MboZ0 zF9=4zom6~vFBTq*7QhW;uCOI_`4LTF1K&QdJY!sq(crVu*s!Yi`I)tsJ8Sk|x9qJ0 zCn5gy3p~}(#tJr18jJXp;M*_MnB_{HPjQo&8hLR}jVpVzAf#f%zuP9f{v3Ap2}mIS z^#+M3@hzRi1`-w3<8+tY`%jOG)D>(9> z?}6x=?v-G==0EMCGh&@ArHreGCoIE?220@g-7ghN7bx5XT1f0_1P%+q6;e8=D$kLr^@;`yq9_doEecFObl=OvvK z{6gXxD}*2!;BE+PhbG!=0*$CVm(Z>Hl6ez(|5CC5-U!5efF3CA1PFj2q>`u{lyia~ zu~ty=0Nwi4-w!1C@#f#pH2A+yK!ySRGUgHR3q!yB|8z%F{7JoNg+X=0WPUQhebOU# zXc2ViRP_+V%!ZD^%IWC5#j*c=+82CR#&sb}EhLnDsSv)Ju)z@eLqBrl$n(pkGeIdJ zAS4Kbsm)h*yWcHT9jQP_4Bd{1V44QHp9PJvt>lr=wGSMb18h+~ptjmbu-j=42XM}z z(_gI}^{=#x$t2g07+8$7H0s@o%#`PDs2kic=+g-nS@#4$VcqV7&D4~N< zKLD=M|Kh;#vv`lv;^L-`&Q3WswXXp1SGp|MGSPfLS|Y{e&!H5w|~R z-Nnu~?>&9-VtqF&C&v{6cZM3pZdlCd($s(`W_$bXpOAW>lJM*%sy9~nX?Msfiqb9E zGOS*EJ=pzOsC34&jxIcDVbaw99gl|nlC+oLR{!itf_96(zqpmCCO;8lv ziTZMlH8h?MO_)V73&9fAit~GLO07uk27XXd48cN4f6w)k( ze*zE5-0WM3mM0iEzF()r%vmR;s5RH&PoH+@DzF4p@iIwF+yg}QK7&MV`=i>wikO@a zb23S6vr27E#0q5>b(teF6W`YX^6J9a-s0E-04L-Wb)AhW+IjZ&_o?f3eowT3&tmDk zvAK&NtOJN9e{C%TG-|cb-b!q#wRy?Cg;UT6?7x54^snmuN@|r*8VKH4_?B`!z0;bm zh7V}tmh8N^ebU!{Oi{M@_E@6{wcVSprWO3Na&pokE3ebrDElM;@GgziyAGqiY%M#e zbhD;qDZ=u6&OJ0tsZs9H?4vQBtaYAmPF)7DUZL63K|h?9_hp4<2US+I3Azw}fMD>A zWI46YMV@$2M$Z=@4#P_v`bqv1feu~skBl=KdO9BMnHZ~!KAV{BIXep(fo(E@5%^ae zu%Ig2N2FoTeq-C{198x+w@Sz4Kc75xD$K5T6;Md*L?sSRK@U7f*-C3FYy!pFAdrA~_LZ1ky?AkgS;YTMSx&%*(_iU4 zu0(r4LBAOq-6oC(I2Dj*g0q_gP`CfmpnNGO&&WawyVqR8TYETMXxuM_@4skZ{ESy)y zs*l?jdUruQg_=8yRzr-G3?4rSU8S>z;Ui$t9I#cFV z_f3-Tw0kD&r+!R82hx&R-ySkCyd7k8BLHuCvp#So_uhRo1R^Kziptg8LdAdu`b5+; z2s_Dg*J~)(Cd$=^)iJNw(J~ZUKQBl+>IvnT9LaKLPM@g-A+JQMxEd1SdGJsdIK*WW z0>}i`)|dG6eFeBaqHTpDcF2XBQS%CFwf<-M9lXKP(6r4z2*HH`eMDX|Z&H}~TEJ*S z(BC-tfy;*2tnP-4L#AWu(9J4MkBY}2C$wZ{76t0q_Cs9OH*&0f;vV>RtB0?Mm;=ax zmfdZDoLI8{j=#@?=aeY#fCx6t92U;+?(Ubj5|*tNM^_mqT>6b*M`8`mAi{f`Y=(zyol}p6Zy(qW5DMv5%6#5*5&j{z|rk1#q5m zR-e_w5=hD~n4?ly70ew0GuFvNxb}ZEq^x>tQa|hVE0UNtr=XxbLt4r#jmLW-)%@;RUF*r`np;yD z8vuV35(4aiHr`jSUajks9fX79Rfr89M*D0};qrDe0zGj#`E)A`uB;c1b%|Ut{Q0sF zk%Rr>opbP~CE?tLau^Sn4^i*>K~Oq4c#q?Jc3Xt@#x153+r|8fyusl24S#A_npW3w zbY3$)5<7GEU=?%`PaC*Ek%b2LN5Dx|hz(wMu9^IvB2PTtdk50V-2vdD?O!;o_V(N< zyRG=$X}i70%VL;Pr=XVw)C(?xO~q5Wz`uC0M%rF|mzN8Ug>a4)PfXwBs)IX$&4{JxTNyhet&oX`HdD>Qb_yhEbMi#%A-NmOm21GhPM`8(~Y z(=Q@}&!v44zJ?~J4^RM=>ZotuezON>s&VYSSG_sJpWkD=-{*%FcTBiiVY_Jg+b=W` z=^)U2<~c2^-YpEnOjTrZr%ZaIs99ud@jK(eY2J75#bwA0!jpxllysK!lM`xhw@fdP zfPble0c@N6#Hz_x4p{IOqz2&~|LkoDjZF4lJZ*NuTPp`iC_L2_B{!;jcSF7?dB2_0K!tG?mP1T=~RcSFIk=X1V;3$ILaH;$(K@+p5d&I6OF0ty<5@Vk#5)NTz-LLdmFD8 z0X%6Fo@#zFDeQQMR@&Kjxr*{ftmfUV`R}DmQPRM+vXKu#Za4;+V;Se=$(pR4th1>Kg!+HOFxJ)?=h-YBqRN<_g`~NnqG2 zkvFKK@%K}^VgQ+1)E-UXlxCJ?mS9FnUB(n{i3F8O_01JPF6*-E`JJUmk5rTm6u0vXSS;N7qTzDJeNMtC=h}E}GAX zQ@Q{{Qq%gbd?We4qn|yN&K6BC#qv7RaAHsLyHM}XP^ewXvXSd_SN;fq1GZuNr^thg z>kga!xb3)gYqbIWdekK+0sgy?ncMCQZr>#7<2U5*8F>yBxB=V>jx8a1!bpM^61BZD zK0l^Nck5?TUz|h@s0!~OGhs%=W3BDLbFSHf2}XFFvdDkxEiP$De~Gnts0V_CA~ zxGx(sh;1lrzZ#NHbRYjM(sUCKIKV$$&7J<<@wb$GK_2ZJ?PpQ?fiO-QvS&gi!($z^ z6a*Qh)gzScR5Fpk2wht486`B$J{0umLL9FZjBP#YQ8XY_ z!sTDO@gW3YCd0>Ck2rAPFwAXqV`4cV<#*}7O)jm8ek4=18rLjrK(`-4P{YCNm`ufrJH0$Rgs_NMk#g;g6QBJQXgllY38RlvfEh<*3#Ub43wrFe^-Y{9)pQOPH$ z7pjB?Viz=iE0Auz$h!e5dZ^e2y{hHt-%|7cw6p#ArU4YK#7t;M1k{1{U@M`r=^iuG z05X)p!$VI-t^;h_du%R^Kq|!b_4TB4DW&Ifb9pb*|-B2E6tfvA&y~m1PO~%21w^qk@`lP!kS1;BESQL9O6xy1KfI zXABh;mB4Fnz-H=KozP#EkWW+9vT$)#Tb6a@K9E0xf^>T)46yK~=BH+6es2V^S1|K; z96xoH4)XsnAYvfuSXfxh7RGspUCa4;pfG3l+0&?=sN1ga(OF&B7^3hbl;D!;@7T>t58*Fbq}OA@eU@dw?DM z0>687J{7mr2hcTocl~QU>@d?bDE=3h>X&Ok$vaTzKfeH6^f+=y$V!mqYhd4P)IN}f z*aD}`47o_5+Iabh7CPB+5%dAoH~UHkfZsVROa!}KvNrbK4UDkDaPhjKsPJ?=Kc06I zZgF%qcNjrP;8LiG6%3Z1I4}ARk&SN&N(_m6Mv!h{pYlg1KH;~k zva)J|*WDw!Le@6rEUQ{af%!1vXutDNsALUo_N2W0hJW4>kwG0OChCo1(v5Q@Y#S=E z9$-^bRKau;F!;gyr*AC)#fIN10nw7yu+q#rf|^=ie*35KHYYijK6Tn-8FbM#DcZl= zY%s&k&@$5vh;Ks_+`|`E)g3kMvBfJ1(KHE0qS6(ui?L1go53;H&J&V1^|s)NHbiNjlA(#A*?+k zz+1^Ke9QT$rI_RxXd?;@VI1j_tRbxgq`WkXzZi!lGY()no*79C=A=Io#!rEc+GdU& zK-ycrL8Bl#$x-j#+dn3MfM#{{xooBiId!{Si^ySEC5B`yJKs#Vcp0UYrG4lg-q`rw?E|j}l{qZPUMHE;@s7K;tPvniimeo+ry;x+n$Uv|JBi zp74&Lg^6OTDCS3Y8XXw~lQSBmhQm3WuaWk#b7K5pl*S@J7srka(M)dk;WxspbSWET zn5!2i1l4r90_TIU#afLs;+L-|>s9`+B2U0|5ne5NwSH zSl2Js40!-LF-`qWmsme3PVF7oRs_>oQK{rS0=8ACM`Qt!6Im%BOpcZHwlA1zIY+vbWh^-#8V!tX1w*wam^E}B?3@Ue290=%SnbDh zVNxGuPQ{Gteb!g5yndwBrE1PY9%jzuRMnQGZE*eoT*6Tu+*}uupn80IWV~dX&h%5^ z&kuzSAornMm%-0*|6LEEp(0wuohqet7%*CjoMgpFskroq21!3WmF3e>3HWLj ztu)M=D?238bEUhE)Db8?(TywBe1CARtoE;jq(06aKR^ zVC8ZEIocm*K&o70^ZIU}4b0Uw;4ExD$}uJ-2MdDp$z$m_({DwPkLcw)!I55M6qm^^)*WX);KsK1Hj%^sotgh{OUwqrMe6ero?+j zM!EH!!@!nQ5M~;q8kN?kB0mi-5?U%|?FF|(8GHr%%_#ijc>1FyF;WtfF!9{5?vi<_X5bS8CdGP4Tk+GC}8M#J^uor-W+uo)#j zSSg4>Oyu&*OImk_ATX{AVk89F_<)%al||nE?$^{*J%;b3TNT{wWCbgW=3Q>5dhvZ^ z*^^8`T0P1o8B|x+p=o8ZjkeBm5?|+PE}iN|C;BJGpB2Hk zVf}7GFx~$a>0>~>l%|`?tw&XT?V!m>RBo_+1pbY19*lhdd+HDU3W)9gFH0&F#q9`( Xs3Z8=PsiWw1AmP5&9LQ|8&UrT5n-#d literal 0 HcmV?d00001 diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Model/FNN_TabNet_WDNN.ipynb b/Loan Status Prediction/Bank Loan Approval Prediction/Model/FNN_TabNet_WDNN.ipynb new file mode 100644 index 00000000..b96f77b5 --- /dev/null +++ b/Loan Status Prediction/Bank Loan Approval Prediction/Model/FNN_TabNet_WDNN.ipynb @@ -0,0 +1 @@ +{"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":8469482,"sourceType":"datasetVersion","datasetId":5049987}],"dockerImageVersionId":30698,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false},"colab":{"provenance":[],"gpuType":"T4"},"accelerator":"GPU"},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# About this notebook\n\nThis notebook presents three different Deep Learning models for training Universal Bank dataset. These are the models which are taken:\n\n- Feedforward Neural Network with k-Fold validation\n- TabNet model with k-Fold validation\n- Wide & Deep neural network architecture\n\nAmongst this, TabNet model is selected which gives 0.985 validation accuracy.","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nimport numpy as np","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","id":"PiYW-FFi9jwv","execution":{"iopub.status.busy":"2024-05-22T12:18:08.633837Z","iopub.execute_input":"2024-05-22T12:18:08.634916Z","iopub.status.idle":"2024-05-22T12:18:09.199354Z","shell.execute_reply.started":"2024-05-22T12:18:08.634873Z","shell.execute_reply":"2024-05-22T12:18:09.198173Z"},"trusted":true},"execution_count":1,"outputs":[]},{"cell_type":"code","source":"import warnings\nwarnings.filterwarnings(\"ignore\")","metadata":{"id":"TfIruao4X8ho","execution":{"iopub.status.busy":"2024-05-22T12:18:09.201292Z","iopub.execute_input":"2024-05-22T12:18:09.201753Z","iopub.status.idle":"2024-05-22T12:18:09.206470Z","shell.execute_reply.started":"2024-05-22T12:18:09.201723Z","shell.execute_reply":"2024-05-22T12:18:09.205330Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":"# Loading the Dataset","metadata":{}},{"cell_type":"code","source":"train = pd.read_csv('/kaggle/input/UniversalBank.csv')","metadata":{"id":"lkce0KVw95Y3","execution":{"iopub.status.busy":"2024-05-22T12:18:09.207871Z","iopub.execute_input":"2024-05-22T12:18:09.208222Z","iopub.status.idle":"2024-05-22T12:18:09.256617Z","shell.execute_reply.started":"2024-05-22T12:18:09.208194Z","shell.execute_reply":"2024-05-22T12:18:09.255506Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"markdown","source":"# Dataset Description\n\n#### Observations\n\n1. Minimum value of Experience is -3 which is not possible.\n2. ZIP Code is not a numeric data. It is to be considered as nominal data. Out of 5000 records, there are only 467 unique ZIP codes. Thus this represents that the dataset is restricted to a particular region.\n3. Education has 3 unique values {1: Bachelor, 2: Masters, 3: Advanced Degree}. So this is again not a numeric data. It is ordinal data.\n4. Personal Loan (Target Variable) is either 0 or 1. {0: Loan not approved, 1: Loan approved}. So this is binary data,\n5. Securities Account is binary data representing {0: doesn't have security account, 1: has security account}\n6. CD Account is binary data representing {0: doesn't have CD Account, 1: has CD Account}\n7. Online is binary data representing {0: doesn't use online banking, 1: uses online banking}\n8. Credit Card is binary data representing {0: doesn't have credit card, 1: has credit card}\n9. ID is the unique column representing IDs of records.\n\nRest are numeric data","metadata":{}},{"cell_type":"code","source":"train.describe()","metadata":{"id":"UENL5vRu9jwx","outputId":"1860a398-05d7-459d-c77d-07fc5cce2a1d","execution":{"iopub.status.busy":"2024-05-22T12:18:09.259813Z","iopub.execute_input":"2024-05-22T12:18:09.260277Z","iopub.status.idle":"2024-05-22T12:18:09.327621Z","shell.execute_reply.started":"2024-05-22T12:18:09.260236Z","shell.execute_reply":"2024-05-22T12:18:09.326203Z"},"trusted":true},"execution_count":4,"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":" ID Age Experience Income ZIP Code \\\ncount 5000.000000 5000.000000 5000.000000 5000.000000 5000.000000 \nmean 2500.500000 45.338400 20.104600 73.774200 93152.503000 \nstd 1443.520003 11.463166 11.467954 46.033729 2121.852197 \nmin 1.000000 23.000000 -3.000000 8.000000 9307.000000 \n25% 1250.750000 35.000000 10.000000 39.000000 91911.000000 \n50% 2500.500000 45.000000 20.000000 64.000000 93437.000000 \n75% 3750.250000 55.000000 30.000000 98.000000 94608.000000 \nmax 5000.000000 67.000000 43.000000 224.000000 96651.000000 \n\n Family CCAvg Education Mortgage Personal Loan \\\ncount 5000.000000 5000.000000 5000.000000 5000.000000 5000.000000 \nmean 2.396400 1.937938 1.881000 56.498800 0.096000 \nstd 1.147663 1.747659 0.839869 101.713802 0.294621 \nmin 1.000000 0.000000 1.000000 0.000000 0.000000 \n25% 1.000000 0.700000 1.000000 0.000000 0.000000 \n50% 2.000000 1.500000 2.000000 0.000000 0.000000 \n75% 3.000000 2.500000 3.000000 101.000000 0.000000 \nmax 4.000000 10.000000 3.000000 635.000000 1.000000 \n\n Securities Account CD Account Online CreditCard \ncount 5000.000000 5000.00000 5000.000000 5000.000000 \nmean 0.104400 0.06040 0.596800 0.294000 \nstd 0.305809 0.23825 0.490589 0.455637 \nmin 0.000000 0.00000 0.000000 0.000000 \n25% 0.000000 0.00000 0.000000 0.000000 \n50% 0.000000 0.00000 1.000000 0.000000 \n75% 0.000000 0.00000 1.000000 1.000000 \nmax 1.000000 1.00000 1.000000 1.000000 ","text/html":"

\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDAgeExperienceIncomeZIP CodeFamilyCCAvgEducationMortgagePersonal LoanSecurities AccountCD AccountOnlineCreditCard
count5000.0000005000.0000005000.0000005000.0000005000.0000005000.0000005000.0000005000.0000005000.0000005000.0000005000.0000005000.000005000.0000005000.000000
mean2500.50000045.33840020.10460073.77420093152.5030002.3964001.9379381.88100056.4988000.0960000.1044000.060400.5968000.294000
std1443.52000311.46316611.46795446.0337292121.8521971.1476631.7476590.839869101.7138020.2946210.3058090.238250.4905890.455637
min1.00000023.000000-3.0000008.0000009307.0000001.0000000.0000001.0000000.0000000.0000000.0000000.000000.0000000.000000
25%1250.75000035.00000010.00000039.00000091911.0000001.0000000.7000001.0000000.0000000.0000000.0000000.000000.0000000.000000
50%2500.50000045.00000020.00000064.00000093437.0000002.0000001.5000002.0000000.0000000.0000000.0000000.000001.0000000.000000
75%3750.25000055.00000030.00000098.00000094608.0000003.0000002.5000003.000000101.0000000.0000000.0000000.000001.0000001.000000
max5000.00000067.00000043.000000224.00000096651.0000004.00000010.0000003.000000635.0000001.0000001.0000001.000001.0000001.000000
\n
"},"metadata":{}}]},{"cell_type":"code","source":"train.info()","metadata":{"id":"k282xrot9jwy","outputId":"2ab9f04f-ad0a-4f2f-a840-7fdbfba27412","execution":{"iopub.status.busy":"2024-05-22T12:18:09.329105Z","iopub.execute_input":"2024-05-22T12:18:09.329534Z","iopub.status.idle":"2024-05-22T12:18:09.356863Z","shell.execute_reply.started":"2024-05-22T12:18:09.329495Z","shell.execute_reply":"2024-05-22T12:18:09.355640Z"},"trusted":true},"execution_count":5,"outputs":[{"name":"stdout","text":"\nRangeIndex: 5000 entries, 0 to 4999\nData columns (total 14 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 ID 5000 non-null int64 \n 1 Age 5000 non-null int64 \n 2 Experience 5000 non-null int64 \n 3 Income 5000 non-null int64 \n 4 ZIP Code 5000 non-null int64 \n 5 Family 5000 non-null int64 \n 6 CCAvg 5000 non-null float64\n 7 Education 5000 non-null int64 \n 8 Mortgage 5000 non-null int64 \n 9 Personal Loan 5000 non-null int64 \n 10 Securities Account 5000 non-null int64 \n 11 CD Account 5000 non-null int64 \n 12 Online 5000 non-null int64 \n 13 CreditCard 5000 non-null int64 \ndtypes: float64(1), int64(13)\nmemory usage: 547.0 KB\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# Checking for negative values if any\n\nIt can be seen that Experience field has 52 negative values. But this field should always be zero or positive.","metadata":{}},{"cell_type":"code","source":"(train < 0).sum()","metadata":{"id":"cMZ7mYX59jwy","outputId":"ece57ba4-57c2-4139-9df9-3ae716acabc2","execution":{"iopub.status.busy":"2024-05-22T12:18:09.360718Z","iopub.execute_input":"2024-05-22T12:18:09.361085Z","iopub.status.idle":"2024-05-22T12:18:09.372442Z","shell.execute_reply.started":"2024-05-22T12:18:09.361054Z","shell.execute_reply":"2024-05-22T12:18:09.371149Z"},"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"ID 0\nAge 0\nExperience 52\nIncome 0\nZIP Code 0\nFamily 0\nCCAvg 0\nEducation 0\nMortgage 0\nPersonal Loan 0\nSecurities Account 0\nCD Account 0\nOnline 0\nCreditCard 0\ndtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"# Type Casting\n\n1. Numeric to Boolean\n2. Numeric to String","metadata":{}},{"cell_type":"code","source":"train['ZIP Code'].nunique() # Out of 5000 records, there are 467 unique values","metadata":{"id":"xti6FLFY9jwz","outputId":"25f7ada3-7ff9-4bcd-f133-bd51160462c9","execution":{"iopub.status.busy":"2024-05-22T12:18:09.374428Z","iopub.execute_input":"2024-05-22T12:18:09.374875Z","iopub.status.idle":"2024-05-22T12:18:09.387246Z","shell.execute_reply.started":"2024-05-22T12:18:09.374814Z","shell.execute_reply":"2024-05-22T12:18:09.386091Z"},"trusted":true},"execution_count":7,"outputs":[{"execution_count":7,"output_type":"execute_result","data":{"text/plain":"467"},"metadata":{}}]},{"cell_type":"code","source":"train['CD Account'] = train['CD Account'].astype(bool)\ntrain['Online'] = train['Online'].astype(bool)\ntrain['CreditCard'] = train['CreditCard'].astype(bool)\ntrain['Personal Loan'] = train['Personal Loan'].astype(bool)\ntrain['ZIP Code'] = train['ZIP Code'].astype(str)\ntrain['Education'] = train['Education'].astype(str)\ntrain['Securities Account'] = train['Securities Account'].astype(bool)","metadata":{"id":"QRjZsRVX9jwz","execution":{"iopub.status.busy":"2024-05-22T12:18:09.389036Z","iopub.execute_input":"2024-05-22T12:18:09.389498Z","iopub.status.idle":"2024-05-22T12:18:09.412351Z","shell.execute_reply.started":"2024-05-22T12:18:09.389428Z","shell.execute_reply":"2024-05-22T12:18:09.411116Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":"# Checking the data where Experience is less than 0\n\nIt can be observed that other fields have valid records. So we can't drop these records. Instead we will replace it with appropriate values.","metadata":{}},{"cell_type":"code","source":"train[train['Experience']<0]","metadata":{"id":"CV2qIofA9jw0","outputId":"a92ff6bb-4acb-4e83-acaf-e7d6fa11b591","execution":{"iopub.status.busy":"2024-05-22T12:18:09.414487Z","iopub.execute_input":"2024-05-22T12:18:09.415155Z","iopub.status.idle":"2024-05-22T12:18:09.468384Z","shell.execute_reply.started":"2024-05-22T12:18:09.415110Z","shell.execute_reply":"2024-05-22T12:18:09.467107Z"},"trusted":true},"execution_count":9,"outputs":[{"execution_count":9,"output_type":"execute_result","data":{"text/plain":" ID Age Experience Income ZIP Code Family CCAvg Education \\\n89 90 25 -1 113 94303 4 2.30 3 \n226 227 24 -1 39 94085 2 1.70 2 \n315 316 24 -2 51 90630 3 0.30 3 \n451 452 28 -2 48 94132 2 1.75 3 \n524 525 24 -1 75 93014 4 0.20 1 \n536 537 25 -1 43 92173 3 2.40 2 \n540 541 25 -1 109 94010 4 2.30 3 \n576 577 25 -1 48 92870 3 0.30 3 \n583 584 24 -1 38 95045 2 1.70 2 \n597 598 24 -2 125 92835 2 7.20 1 \n649 650 25 -1 82 92677 4 2.10 3 \n670 671 23 -1 61 92374 4 2.60 1 \n686 687 24 -1 38 92612 4 0.60 2 \n793 794 24 -2 150 94720 2 2.00 1 \n889 890 24 -2 82 91103 2 1.60 3 \n909 910 23 -1 149 91709 1 6.33 1 \n1173 1174 24 -1 35 94305 2 1.70 2 \n1428 1429 25 -1 21 94583 4 0.40 1 \n1522 1523 25 -1 101 94720 4 2.30 3 \n1905 1906 25 -1 112 92507 2 2.00 1 \n2102 2103 25 -1 81 92647 2 1.60 3 \n2430 2431 23 -1 73 92120 4 2.60 1 \n2466 2467 24 -2 80 94105 2 1.60 3 \n2545 2546 25 -1 39 94720 3 2.40 2 \n2618 2619 23 -3 55 92704 3 2.40 2 \n2717 2718 23 -2 45 95422 4 0.60 2 \n2848 2849 24 -1 78 94720 2 1.80 2 \n2876 2877 24 -2 80 91107 2 1.60 3 \n2962 2963 23 -2 81 91711 2 1.80 2 \n2980 2981 25 -1 53 94305 3 2.40 2 \n3076 3077 29 -1 62 92672 2 1.75 3 \n3130 3131 23 -2 82 92152 2 1.80 2 \n3157 3158 23 -1 13 94720 4 1.00 1 \n3279 3280 26 -1 44 94901 1 2.00 2 \n3284 3285 25 -1 101 95819 4 2.10 3 \n3292 3293 25 -1 13 95616 4 0.40 1 \n3394 3395 25 -1 113 90089 4 2.10 3 \n3425 3426 23 -1 12 91605 4 1.00 1 \n3626 3627 24 -3 28 90089 4 1.00 3 \n3796 3797 24 -2 50 94920 3 2.40 2 \n3824 3825 23 -1 12 95064 4 1.00 1 \n3887 3888 24 -2 118 92634 2 7.20 1 \n3946 3947 25 -1 40 93117 3 2.40 2 \n4015 4016 25 -1 139 93106 2 2.00 1 \n4088 4089 29 -1 71 94801 2 1.75 3 \n4116 4117 24 -2 135 90065 2 7.20 1 \n4285 4286 23 -3 149 93555 2 7.20 1 \n4411 4412 23 -2 75 90291 2 1.80 2 \n4481 4482 25 -2 35 95045 4 1.00 3 \n4514 4515 24 -3 41 91768 4 1.00 3 \n4582 4583 25 -1 69 92691 3 0.30 3 \n4957 4958 29 -1 50 95842 2 1.75 3 \n\n Mortgage Personal Loan Securities Account CD Account Online \\\n89 0 False False False False \n226 0 False False False False \n315 0 False False False True \n451 89 False False False True \n524 0 False False False True \n536 176 False False False True \n540 314 False False False True \n576 0 False False False False \n583 0 False False False True \n597 0 False True False False \n649 0 False False False True \n670 239 False False False True \n686 0 False False False True \n793 0 False False False True \n889 0 False False False True \n909 305 False False False False \n1173 0 False False False False \n1428 90 False False False True \n1522 256 False False False False \n1905 241 False False False True \n2102 0 False False False True \n2430 0 False False False True \n2466 0 False False False True \n2545 0 False False False True \n2618 145 False False False True \n2717 0 False False False True \n2848 0 False False False False \n2876 238 False False False False \n2962 0 False False False False \n2980 0 False False False False \n3076 0 False False False False \n3130 0 False True False False \n3157 84 False False False True \n3279 0 False False False False \n3284 0 False False False False \n3292 0 False True False False \n3394 0 False False False True \n3425 90 False False False True \n3626 0 False False False False \n3796 0 False True False False \n3824 0 False True False False \n3887 0 False True False True \n3946 0 False False False True \n4015 0 False False False False \n4088 0 False False False False \n4116 0 False False False True \n4285 0 False False False True \n4411 0 False False False True \n4481 0 False False False True \n4514 0 False False False True \n4582 0 False False False True \n4957 0 False False False False \n\n CreditCard \n89 True \n226 False \n315 False \n451 False \n524 False \n536 False \n540 False \n576 True \n583 False \n597 True \n649 False \n670 False \n686 False \n793 False \n889 True \n909 True \n1173 False \n1428 False \n1522 True \n1905 False \n2102 True \n2430 False \n2466 False \n2545 False \n2618 False \n2717 True \n2848 False \n2876 False \n2962 False \n2980 False \n3076 True \n3130 True \n3157 False \n3279 False \n3284 True \n3292 False \n3394 False \n3425 False \n3626 False \n3796 False \n3824 True \n3887 False \n3946 False \n4015 True \n4088 False \n4116 False \n4285 False \n4411 True \n4481 False \n4514 False \n4582 False \n4957 True ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDAgeExperienceIncomeZIP CodeFamilyCCAvgEducationMortgagePersonal LoanSecurities AccountCD AccountOnlineCreditCard
899025-11139430342.3030FalseFalseFalseFalseTrue
22622724-1399408521.7020FalseFalseFalseFalseFalse
31531624-2519063030.3030FalseFalseFalseTrueFalse
45145228-2489413221.75389FalseFalseFalseTrueFalse
52452524-1759301440.2010FalseFalseFalseTrueFalse
53653725-1439217332.402176FalseFalseFalseTrueFalse
54054125-11099401042.303314FalseFalseFalseTrueFalse
57657725-1489287030.3030FalseFalseFalseFalseTrue
58358424-1389504521.7020FalseFalseFalseTrueFalse
59759824-21259283527.2010FalseTrueFalseFalseTrue
64965025-1829267742.1030FalseFalseFalseTrueFalse
67067123-1619237442.601239FalseFalseFalseTrueFalse
68668724-1389261240.6020FalseFalseFalseTrueFalse
79379424-21509472022.0010FalseFalseFalseTrueFalse
88989024-2829110321.6030FalseFalseFalseTrueTrue
90991023-11499170916.331305FalseFalseFalseFalseTrue
1173117424-1359430521.7020FalseFalseFalseFalseFalse
1428142925-1219458340.40190FalseFalseFalseTrueFalse
1522152325-11019472042.303256FalseFalseFalseFalseTrue
1905190625-11129250722.001241FalseFalseFalseTrueFalse
2102210325-1819264721.6030FalseFalseFalseTrueTrue
2430243123-1739212042.6010FalseFalseFalseTrueFalse
2466246724-2809410521.6030FalseFalseFalseTrueFalse
2545254625-1399472032.4020FalseFalseFalseTrueFalse
2618261923-3559270432.402145FalseFalseFalseTrueFalse
2717271823-2459542240.6020FalseFalseFalseTrueTrue
2848284924-1789472021.8020FalseFalseFalseFalseFalse
2876287724-2809110721.603238FalseFalseFalseFalseFalse
2962296323-2819171121.8020FalseFalseFalseFalseFalse
2980298125-1539430532.4020FalseFalseFalseFalseFalse
3076307729-1629267221.7530FalseFalseFalseFalseTrue
3130313123-2829215221.8020FalseTrueFalseFalseTrue
3157315823-1139472041.00184FalseFalseFalseTrueFalse
3279328026-1449490112.0020FalseFalseFalseFalseFalse
3284328525-11019581942.1030FalseFalseFalseFalseTrue
3292329325-1139561640.4010FalseTrueFalseFalseFalse
3394339525-11139008942.1030FalseFalseFalseTrueFalse
3425342623-1129160541.00190FalseFalseFalseTrueFalse
3626362724-3289008941.0030FalseFalseFalseFalseFalse
3796379724-2509492032.4020FalseTrueFalseFalseFalse
3824382523-1129506441.0010FalseTrueFalseFalseTrue
3887388824-21189263427.2010FalseTrueFalseTrueFalse
3946394725-1409311732.4020FalseFalseFalseTrueFalse
4015401625-11399310622.0010FalseFalseFalseFalseTrue
4088408929-1719480121.7530FalseFalseFalseFalseFalse
4116411724-21359006527.2010FalseFalseFalseTrueFalse
4285428623-31499355527.2010FalseFalseFalseTrueFalse
4411441223-2759029121.8020FalseFalseFalseTrueTrue
4481448225-2359504541.0030FalseFalseFalseTrueFalse
4514451524-3419176841.0030FalseFalseFalseTrueFalse
4582458325-1699269130.3030FalseFalseFalseTrueFalse
4957495829-1509584221.7530FalseFalseFalseFalseTrue
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"# Cheking the minimum difference between age and experience\n\nSo at age 23, people have no experience. So after 23, they can have n year experience.","metadata":{}},{"cell_type":"code","source":"n = 0\nwhile True:\n m = (train['Age'] - train['Experience'] <= n).sum()\n if m > 0:\n break\n n += 1\nprint(n)","metadata":{"id":"TSlPZHuz9jw0","outputId":"afbe85b6-044e-4595-926a-1eebe583c03e","execution":{"iopub.status.busy":"2024-05-22T12:18:09.472918Z","iopub.execute_input":"2024-05-22T12:18:09.473295Z","iopub.status.idle":"2024-05-22T12:18:09.490668Z","shell.execute_reply.started":"2024-05-22T12:18:09.473265Z","shell.execute_reply":"2024-05-22T12:18:09.489273Z"},"trusted":true},"execution_count":10,"outputs":[{"name":"stdout","text":"24\n","output_type":"stream"}]},{"cell_type":"code","source":"train.loc[train['Experience'] < 0, 'Experience'] = train.loc[train['Experience'] < 0, 'Age'] - 23","metadata":{"id":"QFNXs72J9jw1","execution":{"iopub.status.busy":"2024-05-22T12:18:09.546599Z","iopub.execute_input":"2024-05-22T12:18:09.546988Z","iopub.status.idle":"2024-05-22T12:18:09.562806Z","shell.execute_reply.started":"2024-05-22T12:18:09.546952Z","shell.execute_reply":"2024-05-22T12:18:09.561531Z"},"trusted":true},"execution_count":13,"outputs":[]},{"cell_type":"code","source":"train.describe() # checkong the minimum and maximum Experience value","metadata":{"id":"qpwCaO-H9jw1","outputId":"8cb33f4e-f982-43e7-c7ea-5a99b5233e79","execution":{"iopub.status.busy":"2024-05-22T12:18:09.564615Z","iopub.execute_input":"2024-05-22T12:18:09.565081Z","iopub.status.idle":"2024-05-22T12:18:09.601911Z","shell.execute_reply.started":"2024-05-22T12:18:09.565043Z","shell.execute_reply":"2024-05-22T12:18:09.600681Z"},"trusted":true},"execution_count":14,"outputs":[{"execution_count":14,"output_type":"execute_result","data":{"text/plain":" ID Age Experience Income Family \\\ncount 5000.000000 5000.000000 5000.000000 5000.000000 5000.000000 \nmean 2500.500000 45.338400 20.135400 73.774200 2.396400 \nstd 1443.520003 11.463166 11.414672 46.033729 1.147663 \nmin 1.000000 23.000000 0.000000 8.000000 1.000000 \n25% 1250.750000 35.000000 10.000000 39.000000 1.000000 \n50% 2500.500000 45.000000 20.000000 64.000000 2.000000 \n75% 3750.250000 55.000000 30.000000 98.000000 3.000000 \nmax 5000.000000 67.000000 43.000000 224.000000 4.000000 \n\n CCAvg Mortgage \ncount 5000.000000 5000.000000 \nmean 1.937938 56.498800 \nstd 1.747659 101.713802 \nmin 0.000000 0.000000 \n25% 0.700000 0.000000 \n50% 1.500000 0.000000 \n75% 2.500000 101.000000 \nmax 10.000000 635.000000 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDAgeExperienceIncomeFamilyCCAvgMortgage
count5000.0000005000.0000005000.0000005000.0000005000.0000005000.0000005000.000000
mean2500.50000045.33840020.13540073.7742002.3964001.93793856.498800
std1443.52000311.46316611.41467246.0337291.1476631.747659101.713802
min1.00000023.0000000.0000008.0000001.0000000.0000000.000000
25%1250.75000035.00000010.00000039.0000001.0000000.7000000.000000
50%2500.50000045.00000020.00000064.0000002.0000001.5000000.000000
75%3750.25000055.00000030.00000098.0000003.0000002.500000101.000000
max5000.00000067.00000043.000000224.0000004.00000010.000000635.000000
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"# Data-preprocessing\n\nThis code performs data preprocessing tasks, particularly encoding categorical variables and frequency encoding one of the features.\n\n#### Frequency Encoding for 'ZIP Code':\n\n- Calculates the frequency of each unique value in the 'ZIP Code' column by dividing the count of each value by the total number of samples in the DataFrame.\n- Maps these frequencies to the corresponding 'ZIP Code' values in the DataFrame, effectively encoding the 'ZIP Code' column with its frequency values.\n- Saves the frequency encoding dictionary (zip_code_freq) using the joblib.dump() function to a file named 'zip_code_freq_encoder.pkl'.\n\n#### Label Encoding for Categorical Columns:\n\n- Specifies a list of columns (columns_to_encode) that need to be label encoded: 'Education', 'Personal Loan', 'CD Account', 'Online', 'CreditCard', and 'Securities Account'.\n- Iterates over each column in columns_to_encode and applies label encoding using LabelEncoder() from scikit-learn.\n- Saves the trained label encoders for each column in a dictionary (label_encoders) where the column name is the key and the corresponding label encoder is the value.\n- Updates the DataFrame train by replacing the original categorical values with their encoded counterparts.\n\n#### Saving Label Encoders:\n\n- Saves the dictionary of label encoders (label_encoders) to a file named 'label_encoders.pkl' using the joblib.dump() function.","metadata":{}},{"cell_type":"code","source":"from sklearn.preprocessing import LabelEncoder\nimport joblib\n\n# Displaying the DataFrame structure\nprint(\"Original DataFrame:\")\nprint(train.info())\n\n# Frequency encoding for 'ZIP Code'\nzip_code_freq = train['ZIP Code'].value_counts() / len(train)\ntrain['ZIP Code'] = train['ZIP Code'].map(zip_code_freq)\n\n# Saving the frequency encoding\njoblib.dump(zip_code_freq, 'zip_code_freq_encoder.pkl')\n\n# Columns to encode using LabelEncoder\ncolumns_to_encode = ['Education', 'Personal Loan', 'CD Account', 'Online', 'CreditCard', 'Securities Account']\n\n# Initialize a single label encoder dictionary to store the label encoders\nlabel_encoders = {}\n\n# Encoding the columns using a single LabelEncoder\nfor col in columns_to_encode:\n le = LabelEncoder()\n train[col] = le.fit_transform(train[col])\n label_encoders[col] = le\n\n# Saving the single label encoder dictionary\njoblib.dump(label_encoders, 'label_encoders.pkl')\n\n# Displaying info of the updated DataFrame\nprint(\"\\nUpdated DataFrame Info:\")\nprint(train.info())","metadata":{"id":"6Ly_zuCb9jw1","outputId":"92a96947-ac03-462f-a302-fcf4711f47b4","execution":{"iopub.status.busy":"2024-05-22T12:18:09.603244Z","iopub.execute_input":"2024-05-22T12:18:09.603574Z","iopub.status.idle":"2024-05-22T12:18:10.178636Z","shell.execute_reply.started":"2024-05-22T12:18:09.603546Z","shell.execute_reply":"2024-05-22T12:18:10.177235Z"},"trusted":true},"execution_count":15,"outputs":[{"name":"stdout","text":"Original DataFrame:\n\nRangeIndex: 5000 entries, 0 to 4999\nData columns (total 14 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 ID 5000 non-null int64 \n 1 Age 5000 non-null int64 \n 2 Experience 5000 non-null int64 \n 3 Income 5000 non-null int64 \n 4 ZIP Code 5000 non-null object \n 5 Family 5000 non-null int64 \n 6 CCAvg 5000 non-null float64\n 7 Education 5000 non-null object \n 8 Mortgage 5000 non-null int64 \n 9 Personal Loan 5000 non-null bool \n 10 Securities Account 5000 non-null bool \n 11 CD Account 5000 non-null bool \n 12 Online 5000 non-null bool \n 13 CreditCard 5000 non-null bool \ndtypes: bool(5), float64(1), int64(6), object(2)\nmemory usage: 376.1+ KB\nNone\n\nUpdated DataFrame Info:\n\nRangeIndex: 5000 entries, 0 to 4999\nData columns (total 14 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 ID 5000 non-null int64 \n 1 Age 5000 non-null int64 \n 2 Experience 5000 non-null int64 \n 3 Income 5000 non-null int64 \n 4 ZIP Code 5000 non-null float64\n 5 Family 5000 non-null int64 \n 6 CCAvg 5000 non-null float64\n 7 Education 5000 non-null int64 \n 8 Mortgage 5000 non-null int64 \n 9 Personal Loan 5000 non-null int64 \n 10 Securities Account 5000 non-null int64 \n 11 CD Account 5000 non-null int64 \n 12 Online 5000 non-null int64 \n 13 CreditCard 5000 non-null int64 \ndtypes: float64(2), int64(12)\nmemory usage: 547.0 KB\nNone\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# Correlation Matrix","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\n\ncorrelation_matrix = train.corr()\n\n# Plotting the correlation matrix using seaborn\nplt.figure(figsize=(10, 8))\nsns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\", linewidths=0.5)\nplt.title('Correlation Matrix')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-22T13:41:20.611238Z","iopub.execute_input":"2024-05-22T13:41:20.611687Z","iopub.status.idle":"2024-05-22T13:41:21.686739Z","shell.execute_reply.started":"2024-05-22T13:41:20.611649Z","shell.execute_reply":"2024-05-22T13:41:21.685169Z"},"trusted":true},"execution_count":39,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"# Data Visualization\n\n#### Histogram of Age\n- This plot shows the distribution of ages in the dataset.\n- The histogram is stacked by the 'Personal Loan' variable, allowing us to see the distribution of ages for those who got and those who did not get personal loans.\n- It helps visualize if there are any differences in age distribution between those who got personal loans and those who did not.\n\n#### Boxplot of Income\n- This plot displays the distribution of income for each category of 'Personal Loan'.\n- The boxplot provides information about the median, quartiles, and potential outliers in income for each group.\n- It helps us to identify if there are significant differences in income between those who got personal loans and those who did not.\n\n#### Barplot of Education\n- This plot shows the count of individuals in each category of education, separated by the 'Personal Loan' variable.\n- It helps visualize the distribution of education levels among those who got personal loans and those who did not.\n- Differences in the proportions of education levels between the two groups can be observed.\n\n#### Violin Plot of CCAvg\n- This plot displays the distribution of average credit card spending (CCAvg) for each category of 'Personal Loan'.\n- It combines the features of a box plot and a kernel density plot, showing both summary statistics and the probability density of the data at different values.\n- It helps compare the distribution of CCAvg between individuals who got personal loans and those who did not.\n\n#### Boxen Plot of Mortgage\n- This plot shows the distribution of mortgage amounts for each category of 'Personal Loan'.\n- Similar to a box plot, it displays information about the median, quartiles, and potential outliers in mortgage amounts for each group.\n- It helps identify any differences in mortgage amounts between individuals who got personal loans and those who did not.\n\n#### Swarm Plot of Experience\n- This plot displays the distribution of work experience (in years) for each category of 'Personal Loan'.\n- It shows individual data points along the categorical axis, providing a clearer picture of the distribution compared to a traditional scatter plot.\n- It helps visualize if there are any patterns or differences in work experience between individuals who got personal loans and those who did not.\n\nThese plots collectively provide insights into how different variables relate to the likelihood of individuals accepting personal loans.","metadata":{}},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nimport seaborn as sns\n\n# Define the figure and axes\nfig, axs = plt.subplots(3, 2, figsize=(14, 18))\n\n# Plot 1: Histogram of Age\nsns.histplot(data=train, x='Age', hue='Personal Loan', multiple='stack', ax=axs[0, 0])\naxs[0, 0].set_title('Distribution of Age')\n\n# Plot 2: Boxplot of Income\nsns.boxplot(data=train, y='Income', x='Personal Loan', ax=axs[0, 1])\naxs[0, 1].set_title('Boxplot of Income')\n\n# Plot 3: Barplot of Education\nsns.countplot(data=train, x='Education', hue='Personal Loan', ax=axs[1, 0])\naxs[1, 0].set_title('Distribution of Education')\n\n# Plot 4: Violin Plot of CCAvg\nsns.violinplot(data=train, x='Personal Loan', y='CCAvg', ax=axs[1, 1])\naxs[1, 1].set_title('CCAvg Distribution by Personal Loan')\n\n# Plot 5: Boxen Plot of Mortgage\nsns.boxenplot(data=train, x='Personal Loan', y='Mortgage', ax=axs[2, 0])\naxs[2, 0].set_title('Mortgage Distribution by Personal Loan')\n\n# Plot 6: Swarm Plot of Experience\nsns.swarmplot(data=train, x='Personal Loan', y='Experience', ax=axs[2, 1])\naxs[2, 1].set_title('Experience Distribution by Personal Loan')\n\n# Adjust layout\nplt.tight_layout()\n\n# Show the plots\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-22T13:45:50.242161Z","iopub.execute_input":"2024-05-22T13:45:50.242579Z","iopub.status.idle":"2024-05-22T13:46:54.777627Z","shell.execute_reply.started":"2024-05-22T13:45:50.242547Z","shell.execute_reply":"2024-05-22T13:46:54.776311Z"},"trusted":true},"execution_count":42,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"X = train.drop(['ID', 'Personal Loan'], axis=1) # Features\ny = train['Personal Loan'] # Target","metadata":{"id":"k2K1KHWd9jw1","execution":{"iopub.status.busy":"2024-05-22T12:18:10.179991Z","iopub.execute_input":"2024-05-22T12:18:10.180353Z","iopub.status.idle":"2024-05-22T12:18:10.188571Z","shell.execute_reply.started":"2024-05-22T12:18:10.180316Z","shell.execute_reply":"2024-05-22T12:18:10.187218Z"},"trusted":true},"execution_count":16,"outputs":[]},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)","metadata":{"id":"9VNoR3Kx9jw2","execution":{"iopub.status.busy":"2024-05-22T12:18:10.190375Z","iopub.execute_input":"2024-05-22T12:18:10.190762Z","iopub.status.idle":"2024-05-22T12:18:10.294957Z","shell.execute_reply.started":"2024-05-22T12:18:10.190729Z","shell.execute_reply":"2024-05-22T12:18:10.293650Z"},"trusted":true},"execution_count":17,"outputs":[]},{"cell_type":"code","source":"# converting to numpy arrays\n\nX = X.to_numpy()\ny = y.to_numpy()","metadata":{"execution":{"iopub.status.busy":"2024-05-22T12:18:30.237376Z","iopub.execute_input":"2024-05-22T12:18:30.237867Z","iopub.status.idle":"2024-05-22T12:18:30.244769Z","shell.execute_reply.started":"2024-05-22T12:18:30.237836Z","shell.execute_reply":"2024-05-22T12:18:30.243713Z"},"trusted":true},"execution_count":20,"outputs":[]},{"cell_type":"code","source":"# import necessary modules\nfrom pytorch_tabnet.tab_model import TabNetClassifier\n \nimport os\nimport torch\n \nfrom sklearn.model_selection import KFold\nfrom sklearn.metrics import accuracy_score","metadata":{"execution":{"iopub.status.busy":"2024-05-22T12:18:26.987268Z","iopub.execute_input":"2024-05-22T12:18:26.987637Z","iopub.status.idle":"2024-05-22T12:18:30.235738Z","shell.execute_reply.started":"2024-05-22T12:18:26.987594Z","shell.execute_reply":"2024-05-22T12:18:30.234655Z"},"trusted":true},"execution_count":19,"outputs":[]},{"cell_type":"markdown","source":"# Feedforward Neural Network\n\nA Feedforward Neural Network (FNN) is a type of artificial neural network where connections between the nodes do not form a cycle. It is the simplest form of neural networks where the information moves in only one direction—forward—from the input nodes, through the hidden nodes (if any), and to the output nodes. There are no loops or cycles in the network.\n\n#### Key Components:\n- Input Layer: This layer receives the input data.\n- Hidden Layers: Intermediate layers where computations are performed. These layers apply transformations to the input data and pass it to the next layer.\n- Output Layer: Produces the final output of the network. For binary classification, a single neuron with a sigmoid activation function is typically used.\n- Activation Functions: Non-linear functions applied to each layer's output to introduce non-linearity into the network, allowing it to learn complex patterns.\n\nHere we implement a feedforward neural network for binary classification using TensorFlow and Keras. It uses K-Fold Cross-Validation to evaluate the model's performance, ensuring that the results are robust and generalize well to unseen data. Each fold involves training a new model and applying early stopping to prevent overfitting, with the best epoch's weights restored for evaluation.\n\n#### Layers:\n- The first dense layer has 64 neurons and uses the ReLU activation function.\n- The second dense layer has 32 neurons and also uses the ReLU activation function.\n- The output layer has 1 neuron and uses the sigmoid activation function to output a probability for binary classification.\n\n#### Compilation:\n- The loss function is binary_crossentropy, suitable for binary classification.\n- The optimizer is adam, an adaptive learning rate optimizer.\n- The metric is accuracy.\n\n#### K-Fold Cross-Validation:\n- The dataset is split into 5 parts (folds).\n\n

\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Accuracies over all folds
Fold 1Fold 2Fold 3Fold 4Fold 5
Best Epoch4745254745
Final Validation Loss0.12040.08330.10530.11130.0882
Final Validation Accuracy0.95490.96200.96600.96790.9710
\n\n\n\n
\nOverall Average Validation Loss: 0.10173177272081375
\nOverall Average Validation Accuracy: 0.9644000053405761","metadata":{}},{"cell_type":"code","source":"import tensorflow as tf\nfrom tensorflow.keras.callbacks import EarlyStopping\n\n# Feedforward Neural Network model architecture\n\ndef create_model():\n model = tf.keras.Sequential([\n tf.keras.layers.Dense(64, activation='relu', input_shape=(X_train.shape[1],)),\n tf.keras.layers.Dense(32, activation='relu'),\n tf.keras.layers.Dense(1, activation='sigmoid') # binary classification\n ])\n model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n return model\n\n# K-Fold parameters\nn_splits = 5\nrandom_state = 42\n\n# KFold object\nkf = KFold(n_splits=n_splits, random_state=random_state, shuffle=True)\n\n# Lists to store results\nCV_loss_history = []\nCV_accuracy_history = []\n\nfor fold_index, (train_index, test_index) in enumerate(kf.split(X)):\n\n # Spliting data into training and validation sets\n X_train, X_valid = X[train_index], X[test_index]\n y_train, y_valid = y[train_index], y[test_index]\n\n # Creating a new FNN model for each fold\n model = create_model()\n\n # Early stopping callback to track best epoch for validation accuracy\n early_stopping = EarlyStopping(monitor='val_accuracy', patience=20, restore_best_weights=True)\n\n # Training the model with early stopping\n history = model.fit(X_train, y_train, epochs=50, validation_data=(X_valid, y_valid), callbacks=[early_stopping])\n\n # Getting final validation loss and accuracy\n val_loss = history.history['val_loss'][-1]\n val_acc = history.history['val_accuracy'][-1]\n\n # Printing results, including best epoch from EarlyStopping callback\n print(f\"Fold: {fold_index+1}\")\n print(f\"Best Epoch (Validation Accuracy): {early_stopping.best_epoch}\")\n print(f\"Final Validation Loss: {val_loss}\")\n print(f\"Final Validation Accuracy: {val_acc}\")\n\n # Storing results\n CV_loss_history.append(val_loss)\n CV_accuracy_history.append(val_acc)\n\n# Printing K-Fold evaluation results (average loss, accuracy)\nprint(f\"\\nOverall Average Validation Loss: {np.mean(CV_loss_history)}\")\nprint(f\"Overall Average Validation Accuracy: {np.mean(CV_accuracy_history)}\")","metadata":{"execution":{"iopub.status.busy":"2024-05-22T12:18:30.246026Z","iopub.execute_input":"2024-05-22T12:18:30.246341Z","iopub.status.idle":"2024-05-22T12:19:55.118220Z","shell.execute_reply.started":"2024-05-22T12:18:30.246314Z","shell.execute_reply":"2024-05-22T12:19:55.117046Z"},"trusted":true},"execution_count":21,"outputs":[{"name":"stderr","text":"2024-05-22 12:18:32.657193: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n2024-05-22 12:18:32.657356: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n2024-05-22 12:18:32.825289: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","output_type":"stream"},{"name":"stdout","text":"Epoch 1/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 3ms/step - accuracy: 0.7604 - loss: 2.0709 - val_accuracy: 0.8840 - val_loss: 0.2505\nEpoch 2/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8849 - loss: 0.2689 - val_accuracy: 0.8920 - val_loss: 0.2284\nEpoch 3/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9030 - loss: 0.2360 - val_accuracy: 0.8850 - val_loss: 0.2547\nEpoch 4/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9062 - loss: 0.2424 - val_accuracy: 0.9230 - val_loss: 0.1737\nEpoch 5/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9182 - loss: 0.2145 - val_accuracy: 0.8950 - val_loss: 0.2883\nEpoch 6/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9202 - loss: 0.2049 - val_accuracy: 0.9140 - val_loss: 0.1784\nEpoch 7/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9265 - loss: 0.2213 - val_accuracy: 0.8990 - val_loss: 0.2929\nEpoch 8/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9101 - loss: 0.2290 - val_accuracy: 0.9470 - val_loss: 0.1400\nEpoch 9/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9379 - loss: 0.1595 - val_accuracy: 0.9370 - val_loss: 0.1479\nEpoch 10/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9271 - loss: 0.1711 - val_accuracy: 0.9400 - val_loss: 0.2831\nEpoch 11/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9386 - loss: 0.2146 - val_accuracy: 0.9400 - val_loss: 0.1642\nEpoch 12/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9325 - loss: 0.1668 - val_accuracy: 0.9360 - val_loss: 0.1461\nEpoch 13/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9390 - loss: 0.1680 - val_accuracy: 0.9090 - val_loss: 0.2305\nEpoch 14/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9370 - loss: 0.1783 - val_accuracy: 0.9400 - val_loss: 0.1325\nEpoch 15/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9411 - loss: 0.1560 - val_accuracy: 0.9340 - val_loss: 0.1460\nEpoch 16/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9430 - loss: 0.1460 - val_accuracy: 0.9520 - val_loss: 0.1164\nEpoch 17/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9414 - loss: 0.1356 - val_accuracy: 0.9460 - val_loss: 0.1325\nEpoch 18/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9506 - loss: 0.1530 - val_accuracy: 0.9580 - val_loss: 0.1195\nEpoch 19/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9463 - loss: 0.1443 - val_accuracy: 0.9390 - val_loss: 0.1545\nEpoch 20/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9589 - loss: 0.1179 - val_accuracy: 0.9540 - val_loss: 0.1131\nEpoch 21/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9554 - loss: 0.1236 - val_accuracy: 0.9700 - val_loss: 0.0934\nEpoch 22/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9501 - loss: 0.1260 - val_accuracy: 0.9670 - val_loss: 0.0901\nEpoch 23/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9550 - loss: 0.1148 - val_accuracy: 0.9640 - val_loss: 0.0943\nEpoch 24/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9588 - loss: 0.1211 - val_accuracy: 0.9570 - val_loss: 0.1009\nEpoch 25/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9571 - loss: 0.1087 - val_accuracy: 0.9510 - val_loss: 0.1120\nEpoch 26/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9613 - loss: 0.1068 - val_accuracy: 0.9550 - val_loss: 0.1156\nEpoch 27/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9612 - loss: 0.1045 - val_accuracy: 0.9610 - val_loss: 0.0986\nEpoch 28/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9586 - loss: 0.1205 - val_accuracy: 0.9590 - val_loss: 0.1086\nEpoch 29/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9609 - loss: 0.1043 - val_accuracy: 0.9650 - val_loss: 0.0812\nEpoch 30/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9580 - loss: 0.1154 - val_accuracy: 0.9530 - val_loss: 0.1167\nEpoch 31/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9618 - loss: 0.0877 - val_accuracy: 0.9640 - val_loss: 0.0901\nEpoch 32/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9631 - loss: 0.0952 - val_accuracy: 0.9690 - val_loss: 0.0891\nEpoch 33/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9650 - loss: 0.0914 - val_accuracy: 0.9610 - val_loss: 0.1032\nEpoch 34/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9618 - loss: 0.1116 - val_accuracy: 0.9640 - val_loss: 0.1078\nEpoch 35/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9599 - loss: 0.1027 - val_accuracy: 0.9300 - val_loss: 0.2101\nEpoch 36/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9632 - loss: 0.1064 - val_accuracy: 0.9730 - val_loss: 0.0803\nEpoch 37/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9692 - loss: 0.0823 - val_accuracy: 0.9550 - val_loss: 0.1091\nEpoch 38/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9621 - loss: 0.0958 - val_accuracy: 0.9690 - val_loss: 0.0801\nEpoch 39/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9644 - loss: 0.0952 - val_accuracy: 0.9670 - val_loss: 0.0836\nEpoch 40/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9639 - loss: 0.1028 - val_accuracy: 0.9750 - val_loss: 0.0721\nEpoch 41/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9661 - loss: 0.0901 - val_accuracy: 0.9710 - val_loss: 0.0776\nEpoch 42/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9656 - loss: 0.0935 - val_accuracy: 0.9790 - val_loss: 0.0617\nEpoch 43/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9669 - loss: 0.0910 - val_accuracy: 0.9510 - val_loss: 0.1182\nEpoch 44/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9667 - loss: 0.0917 - val_accuracy: 0.9620 - val_loss: 0.1175\nEpoch 45/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9541 - loss: 0.1713 - val_accuracy: 0.9690 - val_loss: 0.0936\nEpoch 46/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9654 - loss: 0.1012 - val_accuracy: 0.9790 - val_loss: 0.0602\nEpoch 47/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9707 - loss: 0.0833 - val_accuracy: 0.9730 - val_loss: 0.0660\nEpoch 48/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9697 - loss: 0.0972 - val_accuracy: 0.9800 - val_loss: 0.0570\nEpoch 49/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9737 - loss: 0.0715 - val_accuracy: 0.9680 - val_loss: 0.0827\nEpoch 50/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9653 - loss: 0.0848 - val_accuracy: 0.9550 - val_loss: 0.1204\nFold: 1\nBest Epoch (Validation Accuracy): 47\nFinal Validation Loss: 0.12036914378404617\nFinal Validation Accuracy: 0.9549999833106995\nEpoch 1/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 3ms/step - accuracy: 0.6778 - loss: 3.7896 - val_accuracy: 0.9050 - val_loss: 0.4054\nEpoch 2/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8911 - loss: 0.2998 - val_accuracy: 0.9120 - val_loss: 0.2791\nEpoch 3/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8917 - loss: 0.2772 - val_accuracy: 0.8560 - val_loss: 0.3306\nEpoch 4/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9143 - loss: 0.2232 - val_accuracy: 0.8550 - val_loss: 0.2987\nEpoch 5/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9089 - loss: 0.2321 - val_accuracy: 0.9070 - val_loss: 0.1895\nEpoch 6/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9290 - loss: 0.1914 - val_accuracy: 0.9170 - val_loss: 0.1749\nEpoch 7/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9338 - loss: 0.1629 - val_accuracy: 0.9310 - val_loss: 0.1578\nEpoch 8/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9413 - loss: 0.1561 - val_accuracy: 0.9450 - val_loss: 0.1429\nEpoch 9/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9306 - loss: 0.1869 - val_accuracy: 0.9190 - val_loss: 0.2120\nEpoch 10/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9183 - loss: 0.2035 - val_accuracy: 0.9490 - val_loss: 0.1330\nEpoch 11/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9538 - loss: 0.1332 - val_accuracy: 0.9470 - val_loss: 0.1360\nEpoch 12/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9399 - loss: 0.1596 - val_accuracy: 0.9390 - val_loss: 0.1509\nEpoch 13/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9444 - loss: 0.1556 - val_accuracy: 0.9450 - val_loss: 0.1337\nEpoch 14/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9455 - loss: 0.1499 - val_accuracy: 0.9460 - val_loss: 0.1405\nEpoch 15/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9522 - loss: 0.1230 - val_accuracy: 0.9410 - val_loss: 0.1631\nEpoch 16/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9489 - loss: 0.1425 - val_accuracy: 0.9430 - val_loss: 0.1856\nEpoch 17/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9526 - loss: 0.1263 - val_accuracy: 0.9340 - val_loss: 0.1707\nEpoch 18/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9573 - loss: 0.1308 - val_accuracy: 0.9400 - val_loss: 0.1468\nEpoch 19/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9488 - loss: 0.1312 - val_accuracy: 0.9510 - val_loss: 0.1282\nEpoch 20/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9550 - loss: 0.1211 - val_accuracy: 0.9360 - val_loss: 0.1548\nEpoch 21/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9606 - loss: 0.1077 - val_accuracy: 0.9380 - val_loss: 0.1532\nEpoch 22/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9523 - loss: 0.1281 - val_accuracy: 0.9360 - val_loss: 0.1785\nEpoch 23/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9498 - loss: 0.1374 - val_accuracy: 0.9320 - val_loss: 0.1753\nEpoch 24/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9584 - loss: 0.1111 - val_accuracy: 0.9520 - val_loss: 0.1261\nEpoch 25/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9608 - loss: 0.1107 - val_accuracy: 0.9520 - val_loss: 0.1141\nEpoch 26/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9625 - loss: 0.1150 - val_accuracy: 0.9440 - val_loss: 0.1384\nEpoch 27/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9636 - loss: 0.1030 - val_accuracy: 0.9440 - val_loss: 0.1106\nEpoch 28/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9652 - loss: 0.0947 - val_accuracy: 0.9390 - val_loss: 0.1547\nEpoch 29/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9537 - loss: 0.1152 - val_accuracy: 0.9520 - val_loss: 0.1288\nEpoch 30/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9613 - loss: 0.1008 - val_accuracy: 0.9530 - val_loss: 0.1175\nEpoch 31/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9701 - loss: 0.0880 - val_accuracy: 0.9570 - val_loss: 0.1025\nEpoch 32/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9611 - loss: 0.0986 - val_accuracy: 0.9550 - val_loss: 0.1156\nEpoch 33/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9669 - loss: 0.0976 - val_accuracy: 0.9570 - val_loss: 0.1017\nEpoch 34/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9738 - loss: 0.0846 - val_accuracy: 0.9360 - val_loss: 0.1452\nEpoch 35/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9581 - loss: 0.1219 - val_accuracy: 0.9540 - val_loss: 0.1214\nEpoch 36/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9615 - loss: 0.1098 - val_accuracy: 0.9540 - val_loss: 0.1335\nEpoch 37/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9532 - loss: 0.1368 - val_accuracy: 0.9620 - val_loss: 0.0979\nEpoch 38/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9679 - loss: 0.0930 - val_accuracy: 0.9580 - val_loss: 0.0974\nEpoch 39/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9623 - loss: 0.0945 - val_accuracy: 0.9450 - val_loss: 0.1339\nEpoch 40/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9651 - loss: 0.0936 - val_accuracy: 0.9630 - val_loss: 0.0943\nEpoch 41/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9701 - loss: 0.0765 - val_accuracy: 0.9590 - val_loss: 0.1024\nEpoch 42/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9702 - loss: 0.0849 - val_accuracy: 0.9540 - val_loss: 0.0970\nEpoch 43/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9717 - loss: 0.0793 - val_accuracy: 0.9600 - val_loss: 0.1090\nEpoch 44/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9637 - loss: 0.0956 - val_accuracy: 0.9550 - val_loss: 0.1118\nEpoch 45/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9730 - loss: 0.0760 - val_accuracy: 0.9580 - val_loss: 0.0873\nEpoch 46/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9743 - loss: 0.0741 - val_accuracy: 0.9640 - val_loss: 0.0924\nEpoch 47/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9658 - loss: 0.1005 - val_accuracy: 0.9380 - val_loss: 0.1596\nEpoch 48/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9694 - loss: 0.0925 - val_accuracy: 0.9480 - val_loss: 0.1400\nEpoch 49/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9666 - loss: 0.1096 - val_accuracy: 0.9530 - val_loss: 0.1163\nEpoch 50/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9743 - loss: 0.0793 - val_accuracy: 0.9620 - val_loss: 0.0833\nFold: 2\nBest Epoch (Validation Accuracy): 45\nFinal Validation Loss: 0.08333558589220047\nFinal Validation Accuracy: 0.9620000123977661\nEpoch 1/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 3ms/step - accuracy: 0.8735 - loss: 1.7570 - val_accuracy: 0.9060 - val_loss: 0.2252\nEpoch 2/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9006 - loss: 0.3184 - val_accuracy: 0.9040 - val_loss: 0.2341\nEpoch 3/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9074 - loss: 0.2320 - val_accuracy: 0.9250 - val_loss: 0.1863\nEpoch 4/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9218 - loss: 0.2257 - val_accuracy: 0.9280 - val_loss: 0.1756\nEpoch 5/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9358 - loss: 0.1668 - val_accuracy: 0.9350 - val_loss: 0.1818\nEpoch 6/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9268 - loss: 0.1933 - val_accuracy: 0.9270 - val_loss: 0.1938\nEpoch 7/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9339 - loss: 0.1710 - val_accuracy: 0.9330 - val_loss: 0.2191\nEpoch 8/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9416 - loss: 0.1499 - val_accuracy: 0.9390 - val_loss: 0.1589\nEpoch 9/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9401 - loss: 0.1400 - val_accuracy: 0.9330 - val_loss: 0.2054\nEpoch 10/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9318 - loss: 0.1738 - val_accuracy: 0.9220 - val_loss: 0.2180\nEpoch 11/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9470 - loss: 0.1393 - val_accuracy: 0.9470 - val_loss: 0.1407\nEpoch 12/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9474 - loss: 0.1546 - val_accuracy: 0.9380 - val_loss: 0.1665\nEpoch 13/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9506 - loss: 0.1207 - val_accuracy: 0.9420 - val_loss: 0.1852\nEpoch 14/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9449 - loss: 0.1560 - val_accuracy: 0.9490 - val_loss: 0.1414\nEpoch 15/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9405 - loss: 0.1527 - val_accuracy: 0.9510 - val_loss: 0.1530\nEpoch 16/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9560 - loss: 0.1172 - val_accuracy: 0.9530 - val_loss: 0.1387\nEpoch 17/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9577 - loss: 0.1204 - val_accuracy: 0.9590 - val_loss: 0.1386\nEpoch 18/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9618 - loss: 0.1121 - val_accuracy: 0.9520 - val_loss: 0.1302\nEpoch 19/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9499 - loss: 0.1350 - val_accuracy: 0.9580 - val_loss: 0.1212\nEpoch 20/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9633 - loss: 0.1057 - val_accuracy: 0.9390 - val_loss: 0.1737\nEpoch 21/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9558 - loss: 0.1176 - val_accuracy: 0.9350 - val_loss: 0.2096\nEpoch 22/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9528 - loss: 0.1310 - val_accuracy: 0.9560 - val_loss: 0.1609\nEpoch 23/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9563 - loss: 0.1194 - val_accuracy: 0.9570 - val_loss: 0.1206\nEpoch 24/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9556 - loss: 0.1165 - val_accuracy: 0.9500 - val_loss: 0.1586\nEpoch 25/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9611 - loss: 0.1076 - val_accuracy: 0.9610 - val_loss: 0.1102\nEpoch 26/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9597 - loss: 0.1108 - val_accuracy: 0.9700 - val_loss: 0.1094\nEpoch 27/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9551 - loss: 0.1207 - val_accuracy: 0.9600 - val_loss: 0.1278\nEpoch 28/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9554 - loss: 0.1191 - val_accuracy: 0.9560 - val_loss: 0.1371\nEpoch 29/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9636 - loss: 0.0912 - val_accuracy: 0.9650 - val_loss: 0.1236\nEpoch 30/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9625 - loss: 0.1031 - val_accuracy: 0.9620 - val_loss: 0.1121\nEpoch 31/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9628 - loss: 0.1084 - val_accuracy: 0.9400 - val_loss: 0.1745\nEpoch 32/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9600 - loss: 0.1141 - val_accuracy: 0.9640 - val_loss: 0.1067\nEpoch 33/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9643 - loss: 0.1119 - val_accuracy: 0.9450 - val_loss: 0.1593\nEpoch 34/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9669 - loss: 0.0939 - val_accuracy: 0.9530 - val_loss: 0.1055\nEpoch 35/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9595 - loss: 0.1102 - val_accuracy: 0.9620 - val_loss: 0.1494\nEpoch 36/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9597 - loss: 0.1146 - val_accuracy: 0.9340 - val_loss: 0.3022\nEpoch 37/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9615 - loss: 0.1134 - val_accuracy: 0.9560 - val_loss: 0.1184\nEpoch 38/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9651 - loss: 0.0943 - val_accuracy: 0.9690 - val_loss: 0.1055\nEpoch 39/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9708 - loss: 0.0852 - val_accuracy: 0.9640 - val_loss: 0.1242\nEpoch 40/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9667 - loss: 0.0855 - val_accuracy: 0.9620 - val_loss: 0.1060\nEpoch 41/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9566 - loss: 0.1282 - val_accuracy: 0.9480 - val_loss: 0.1676\nEpoch 42/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9670 - loss: 0.0939 - val_accuracy: 0.9600 - val_loss: 0.1165\nEpoch 43/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9655 - loss: 0.0891 - val_accuracy: 0.9480 - val_loss: 0.1867\nEpoch 44/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9667 - loss: 0.0931 - val_accuracy: 0.9550 - val_loss: 0.1302\nEpoch 45/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9615 - loss: 0.1170 - val_accuracy: 0.9670 - val_loss: 0.1246\nEpoch 46/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9665 - loss: 0.0827 - val_accuracy: 0.9660 - val_loss: 0.1053\nFold: 3\nBest Epoch (Validation Accuracy): 25\nFinal Validation Loss: 0.10532169044017792\nFinal Validation Accuracy: 0.9660000205039978\nEpoch 1/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 3ms/step - accuracy: 0.6624 - loss: 5.6476 - val_accuracy: 0.8940 - val_loss: 0.3736\nEpoch 2/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8885 - loss: 0.3064 - val_accuracy: 0.8990 - val_loss: 0.2515\nEpoch 3/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8942 - loss: 0.2579 - val_accuracy: 0.9210 - val_loss: 0.3262\nEpoch 4/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9136 - loss: 0.2265 - val_accuracy: 0.9210 - val_loss: 0.2154\nEpoch 5/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9126 - loss: 0.2125 - val_accuracy: 0.9290 - val_loss: 0.1743\nEpoch 6/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9195 - loss: 0.2050 - val_accuracy: 0.9190 - val_loss: 0.1870\nEpoch 7/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9312 - loss: 0.1799 - val_accuracy: 0.9430 - val_loss: 0.1595\nEpoch 8/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9287 - loss: 0.1784 - val_accuracy: 0.9520 - val_loss: 0.1495\nEpoch 9/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9437 - loss: 0.1507 - val_accuracy: 0.9030 - val_loss: 0.2205\nEpoch 10/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9342 - loss: 0.1880 - val_accuracy: 0.9470 - val_loss: 0.1427\nEpoch 11/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9293 - loss: 0.2022 - val_accuracy: 0.9500 - val_loss: 0.1316\nEpoch 12/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9468 - loss: 0.1434 - val_accuracy: 0.9430 - val_loss: 0.1418\nEpoch 13/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9431 - loss: 0.1513 - val_accuracy: 0.9230 - val_loss: 0.1695\nEpoch 14/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9320 - loss: 0.1690 - val_accuracy: 0.9430 - val_loss: 0.1375\nEpoch 15/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9429 - loss: 0.1620 - val_accuracy: 0.9300 - val_loss: 0.1874\nEpoch 16/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9403 - loss: 0.1495 - val_accuracy: 0.8530 - val_loss: 0.5481\nEpoch 17/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9365 - loss: 0.2068 - val_accuracy: 0.9470 - val_loss: 0.1466\nEpoch 18/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9454 - loss: 0.1579 - val_accuracy: 0.9550 - val_loss: 0.1165\nEpoch 19/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9538 - loss: 0.1331 - val_accuracy: 0.9290 - val_loss: 0.1511\nEpoch 20/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9456 - loss: 0.1571 - val_accuracy: 0.9240 - val_loss: 0.2146\nEpoch 21/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9451 - loss: 0.1441 - val_accuracy: 0.9470 - val_loss: 0.1630\nEpoch 22/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9469 - loss: 0.1621 - val_accuracy: 0.9610 - val_loss: 0.1103\nEpoch 23/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9561 - loss: 0.1265 - val_accuracy: 0.9560 - val_loss: 0.1261\nEpoch 24/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9561 - loss: 0.1314 - val_accuracy: 0.9610 - val_loss: 0.0898\nEpoch 25/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9544 - loss: 0.1244 - val_accuracy: 0.9520 - val_loss: 0.1657\nEpoch 26/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9555 - loss: 0.1274 - val_accuracy: 0.9390 - val_loss: 0.1344\nEpoch 27/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9509 - loss: 0.1494 - val_accuracy: 0.9630 - val_loss: 0.0951\nEpoch 28/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9594 - loss: 0.1116 - val_accuracy: 0.9440 - val_loss: 0.1753\nEpoch 29/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9604 - loss: 0.1031 - val_accuracy: 0.9520 - val_loss: 0.1172\nEpoch 30/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9613 - loss: 0.1047 - val_accuracy: 0.9660 - val_loss: 0.0832\nEpoch 31/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9679 - loss: 0.0930 - val_accuracy: 0.9450 - val_loss: 0.1203\nEpoch 32/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9642 - loss: 0.1054 - val_accuracy: 0.9220 - val_loss: 0.1622\nEpoch 33/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9584 - loss: 0.1115 - val_accuracy: 0.9670 - val_loss: 0.0878\nEpoch 34/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9649 - loss: 0.0954 - val_accuracy: 0.9700 - val_loss: 0.0824\nEpoch 35/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9582 - loss: 0.1173 - val_accuracy: 0.9630 - val_loss: 0.0835\nEpoch 36/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9703 - loss: 0.0828 - val_accuracy: 0.9610 - val_loss: 0.0911\nEpoch 37/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9636 - loss: 0.1006 - val_accuracy: 0.9520 - val_loss: 0.1155\nEpoch 38/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9655 - loss: 0.1001 - val_accuracy: 0.9720 - val_loss: 0.0720\nEpoch 39/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9593 - loss: 0.1049 - val_accuracy: 0.9520 - val_loss: 0.1329\nEpoch 40/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9418 - loss: 0.1776 - val_accuracy: 0.9690 - val_loss: 0.0735\nEpoch 41/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9642 - loss: 0.0976 - val_accuracy: 0.9700 - val_loss: 0.0984\nEpoch 42/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9652 - loss: 0.0896 - val_accuracy: 0.9540 - val_loss: 0.1443\nEpoch 43/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9697 - loss: 0.1016 - val_accuracy: 0.9700 - val_loss: 0.0830\nEpoch 44/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9607 - loss: 0.1012 - val_accuracy: 0.9570 - val_loss: 0.1045\nEpoch 45/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9697 - loss: 0.0879 - val_accuracy: 0.9620 - val_loss: 0.0991\nEpoch 46/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9693 - loss: 0.0924 - val_accuracy: 0.9660 - val_loss: 0.0854\nEpoch 47/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9614 - loss: 0.1063 - val_accuracy: 0.9610 - val_loss: 0.1080\nEpoch 48/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9701 - loss: 0.1010 - val_accuracy: 0.9730 - val_loss: 0.0716\nEpoch 49/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9649 - loss: 0.0917 - val_accuracy: 0.9690 - val_loss: 0.0837\nEpoch 50/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9576 - loss: 0.1125 - val_accuracy: 0.9680 - val_loss: 0.1114\nFold: 4\nBest Epoch (Validation Accuracy): 47\nFinal Validation Loss: 0.11137939989566803\nFinal Validation Accuracy: 0.9679999947547913\nEpoch 1/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 3ms/step - accuracy: 0.8189 - loss: 0.9018 - val_accuracy: 0.9110 - val_loss: 0.2100\nEpoch 2/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8866 - loss: 0.2767 - val_accuracy: 0.9090 - val_loss: 0.2921\nEpoch 3/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9030 - loss: 0.2494 - val_accuracy: 0.9300 - val_loss: 0.2141\nEpoch 4/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9086 - loss: 0.2271 - val_accuracy: 0.9090 - val_loss: 0.2797\nEpoch 5/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9281 - loss: 0.1890 - val_accuracy: 0.9270 - val_loss: 0.1811\nEpoch 6/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9303 - loss: 0.1790 - val_accuracy: 0.9440 - val_loss: 0.1567\nEpoch 7/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9343 - loss: 0.1729 - val_accuracy: 0.9480 - val_loss: 0.1415\nEpoch 8/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9329 - loss: 0.1731 - val_accuracy: 0.9450 - val_loss: 0.1441\nEpoch 9/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9365 - loss: 0.1669 - val_accuracy: 0.9490 - val_loss: 0.1597\nEpoch 10/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9343 - loss: 0.1755 - val_accuracy: 0.9460 - val_loss: 0.1384\nEpoch 11/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9324 - loss: 0.1802 - val_accuracy: 0.9330 - val_loss: 0.2057\nEpoch 12/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9304 - loss: 0.1635 - val_accuracy: 0.9600 - val_loss: 0.1184\nEpoch 13/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9471 - loss: 0.1295 - val_accuracy: 0.9480 - val_loss: 0.1442\nEpoch 14/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9451 - loss: 0.1394 - val_accuracy: 0.9520 - val_loss: 0.1241\nEpoch 15/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9530 - loss: 0.1247 - val_accuracy: 0.9670 - val_loss: 0.1176\nEpoch 16/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9443 - loss: 0.1415 - val_accuracy: 0.9460 - val_loss: 0.1500\nEpoch 17/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9530 - loss: 0.1196 - val_accuracy: 0.9510 - val_loss: 0.1344\nEpoch 18/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9508 - loss: 0.1264 - val_accuracy: 0.9620 - val_loss: 0.1057\nEpoch 19/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9536 - loss: 0.1173 - val_accuracy: 0.9690 - val_loss: 0.1046\nEpoch 20/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9516 - loss: 0.1254 - val_accuracy: 0.9600 - val_loss: 0.1248\nEpoch 21/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9510 - loss: 0.1355 - val_accuracy: 0.9430 - val_loss: 0.1629\nEpoch 22/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9487 - loss: 0.1421 - val_accuracy: 0.8690 - val_loss: 0.3047\nEpoch 23/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9523 - loss: 0.1316 - val_accuracy: 0.9500 - val_loss: 0.1270\nEpoch 24/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9576 - loss: 0.1123 - val_accuracy: 0.9610 - val_loss: 0.1247\nEpoch 25/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9547 - loss: 0.1232 - val_accuracy: 0.9660 - val_loss: 0.0986\nEpoch 26/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9605 - loss: 0.0999 - val_accuracy: 0.9600 - val_loss: 0.1083\nEpoch 27/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9590 - loss: 0.1056 - val_accuracy: 0.9650 - val_loss: 0.1034\nEpoch 28/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9632 - loss: 0.0934 - val_accuracy: 0.9660 - val_loss: 0.0985\nEpoch 29/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9528 - loss: 0.1142 - val_accuracy: 0.9720 - val_loss: 0.0884\nEpoch 30/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9599 - loss: 0.0980 - val_accuracy: 0.9720 - val_loss: 0.0877\nEpoch 31/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9652 - loss: 0.0982 - val_accuracy: 0.9640 - val_loss: 0.1016\nEpoch 32/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9643 - loss: 0.1049 - val_accuracy: 0.9660 - val_loss: 0.1027\nEpoch 33/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9607 - loss: 0.1029 - val_accuracy: 0.9620 - val_loss: 0.1115\nEpoch 34/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9723 - loss: 0.0815 - val_accuracy: 0.9340 - val_loss: 0.1601\nEpoch 35/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9590 - loss: 0.0930 - val_accuracy: 0.9660 - val_loss: 0.0955\nEpoch 36/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9704 - loss: 0.0815 - val_accuracy: 0.9680 - val_loss: 0.1022\nEpoch 37/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9743 - loss: 0.0685 - val_accuracy: 0.9770 - val_loss: 0.0782\nEpoch 38/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9722 - loss: 0.0738 - val_accuracy: 0.9680 - val_loss: 0.0887\nEpoch 39/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9657 - loss: 0.0990 - val_accuracy: 0.9670 - val_loss: 0.1161\nEpoch 40/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9673 - loss: 0.0952 - val_accuracy: 0.9540 - val_loss: 0.1181\nEpoch 41/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9667 - loss: 0.0920 - val_accuracy: 0.9690 - val_loss: 0.0895\nEpoch 42/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9712 - loss: 0.0790 - val_accuracy: 0.9740 - val_loss: 0.0827\nEpoch 43/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9722 - loss: 0.0791 - val_accuracy: 0.9500 - val_loss: 0.1326\nEpoch 44/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9637 - loss: 0.1023 - val_accuracy: 0.9720 - val_loss: 0.0882\nEpoch 45/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9664 - loss: 0.0857 - val_accuracy: 0.9750 - val_loss: 0.0863\nEpoch 46/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9657 - loss: 0.0802 - val_accuracy: 0.9790 - val_loss: 0.0799\nEpoch 47/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9771 - loss: 0.0722 - val_accuracy: 0.9710 - val_loss: 0.0958\nEpoch 48/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9593 - loss: 0.0954 - val_accuracy: 0.9670 - val_loss: 0.1057\nEpoch 49/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9693 - loss: 0.0811 - val_accuracy: 0.9700 - val_loss: 0.0889\nEpoch 50/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9650 - loss: 0.1138 - val_accuracy: 0.9710 - val_loss: 0.0883\nFold: 5\nBest Epoch (Validation Accuracy): 45\nFinal Validation Loss: 0.08825304359197617\nFinal Validation Accuracy: 0.9710000157356262\n\nOverall Average Validation Loss: 0.10173177272081375\nOverall Average Validation Accuracy: 0.9644000053405761\n","output_type":"stream"}]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\n\n# Assuming history is accessible from tb_cls.fit output\nhistory = history.history # Replace with appropriate method to access history\n\n# Extract accuracy and loss for training and validation sets\ntrain_acc = history['accuracy'] # Replace with actual metric names\nval_acc = history['val_accuracy']\ntrain_loss = history['loss']\nval_loss = history['val_loss']\n\n# Plotting accuracy\nplt.figure(figsize=(10, 6))\nplt.plot(train_acc, label='Training Accuracy')\nplt.plot(val_acc, label='Validation Accuracy')\nplt.xlabel('Epoch')\nplt.ylabel('Accuracy')\nplt.title('Training vs. Validation Accuracy')\nplt.legend()\nplt.grid(True)\nplt.show()\n\n# Plotting accuracy\nplt.figure(figsize=(10, 6))\nplt.plot(train_loss, label='Training Logloss')\nplt.plot(val_loss, label='Validation Logloss')\nplt.xlabel('Epoch')\nplt.ylabel('Loss')\nplt.title('Training vs. Validation Logloss')\nplt.legend()\nplt.grid(True)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-22T12:19:55.119618Z","iopub.execute_input":"2024-05-22T12:19:55.120323Z","iopub.status.idle":"2024-05-22T12:19:55.794314Z","shell.execute_reply.started":"2024-05-22T12:19:55.120288Z","shell.execute_reply":"2024-05-22T12:19:55.793216Z"},"trusted":true},"execution_count":22,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"# TabNet Model\n\nTabNet (Tabular Neural Network) is a neural network architecture designed specifically for tabular data, commonly encountered in structured data sets. It was introduced in the paper \"TabNet: Attentive Interpretable Tabular Learning\" by Sercan O. Arik and Tomas Pfister. TabNet is an interpretable and efficient neural network architecture that combines elements of deep learning with attention mechanisms and feature selection techniques. It aims to achieve state-of-the-art performance on tabular data while providing insights into feature importance and model decisions.\n\n#### Architecture:\n\nThe architecture of TabNet consists of several key components:\n\n- Feature Embedding Layer: Converts categorical variables into dense representations suitable for neural networks. This layer often utilizes techniques like embedding layers or one-hot encoding followed by dense layers.\n- Feature Transformation Blocks: These blocks contain multiple sequential attention-based feature transformation steps. Each step performs feature selection and transformation using the features' interactions and dependencies.\n- Decision Steps: In each feature transformation block, decision steps apply feature-wise gating mechanisms to select relevant features and suppress irrelevant ones based on their importance.\n- Final Prediction Layer: The output of the feature transformation blocks is passed through a final prediction layer, typically consisting of fully connected layers followed by softmax or sigmoid activation functions for classification or regression tasks, respectively.\n\n#### Training Process:\n\nThe training process involves optimizing the model parameters to minimize a defined loss function (e.g., cross-entropy loss for classification tasks). TabNet employs optimization techniques such as the Adam optimizer and learning rate scheduling to efficiently update the model parameters during training.\n\n\n

\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Accuracies over all folds
Fold 1Fold 2Fold 3Fold 4Fold 5
Best Epoch3545464124
Final Validation LogLoss0.04380.06230.06260.04660.0651
Final Validation Accuracy0.9800.9850.9780.9720.982
","metadata":{}},{"cell_type":"code","source":"y = y.flatten()\n\nkf = KFold(n_splits=5, random_state=42, shuffle=True)\nCV_score_array = []\nfor train_index, test_index in kf.split(X):\n X_train, X_valid = X[train_index], X[test_index]\n y_train, y_valid = y[train_index], y[test_index]\n tb_cls = TabNetClassifier(optimizer_fn=torch.optim.Adam,\n optimizer_params=dict(lr=1e-3),\n scheduler_params={\"step_size\":10, \"gamma\":0.9},\n scheduler_fn=torch.optim.lr_scheduler.StepLR,\n mask_type='entmax'\n )\n history = tb_cls.fit(X_train, y_train,\n eval_set=[(X_train, y_train), (X_valid, y_valid)],\n eval_name=['train', 'valid'],\n eval_metric=['accuracy', 'logloss'],\n max_epochs=50, patience=25,\n batch_size=28, drop_last=False) \n CV_score_array.append(tb_cls.best_cost)\n\nprint(CV_score_array)","metadata":{"id":"-dP8x8KhBdDG","execution":{"iopub.status.busy":"2024-05-22T12:47:17.692097Z","iopub.execute_input":"2024-05-22T12:47:17.692499Z","iopub.status.idle":"2024-05-22T13:06:01.486815Z","shell.execute_reply.started":"2024-05-22T12:47:17.692470Z","shell.execute_reply":"2024-05-22T13:06:01.484461Z"},"trusted":true},"execution_count":31,"outputs":[{"name":"stdout","text":"epoch 0 | loss: 0.42207 | train_accuracy: 0.907 | train_logloss: 0.33201 | valid_accuracy: 0.896 | valid_logloss: 0.35855 | 0:00:04s\nepoch 1 | loss: 0.30114 | train_accuracy: 0.909 | train_logloss: 0.25234 | valid_accuracy: 0.904 | valid_logloss: 0.25999 | 0:00:08s\nepoch 2 | loss: 0.25561 | train_accuracy: 0.91925 | train_logloss: 0.21899 | valid_accuracy: 0.91 | valid_logloss: 0.21791 | 0:00:13s\nepoch 3 | loss: 0.22671 | train_accuracy: 0.9295 | train_logloss: 0.1824 | valid_accuracy: 0.918 | valid_logloss: 0.19067 | 0:00:17s\nepoch 4 | loss: 0.19331 | train_accuracy: 0.944 | train_logloss: 0.15418 | valid_accuracy: 0.941 | valid_logloss: 0.16627 | 0:00:21s\nepoch 5 | loss: 0.16893 | train_accuracy: 0.95225 | train_logloss: 0.1341 | valid_accuracy: 0.955 | valid_logloss: 0.13194 | 0:00:25s\nepoch 6 | loss: 0.14958 | train_accuracy: 0.957 | train_logloss: 0.1205 | valid_accuracy: 0.963 | valid_logloss: 0.11347 | 0:00:30s\nepoch 7 | loss: 0.14176 | train_accuracy: 0.95925 | train_logloss: 0.10867 | valid_accuracy: 0.963 | valid_logloss: 0.10337 | 0:00:34s\nepoch 8 | loss: 0.13032 | train_accuracy: 0.96475 | train_logloss: 0.10007 | valid_accuracy: 0.965 | valid_logloss: 0.09991 | 0:00:39s\nepoch 9 | loss: 0.13104 | train_accuracy: 0.96525 | train_logloss: 0.0923 | valid_accuracy: 0.969 | valid_logloss: 0.08984 | 0:00:43s\nepoch 10 | loss: 0.11881 | train_accuracy: 0.97 | train_logloss: 0.08569 | valid_accuracy: 0.973 | valid_logloss: 0.07166 | 0:00:48s\nepoch 11 | loss: 0.12288 | train_accuracy: 0.971 | train_logloss: 0.07971 | valid_accuracy: 0.977 | valid_logloss: 0.06722 | 0:00:52s\nepoch 12 | loss: 0.10859 | train_accuracy: 0.97275 | train_logloss: 0.07488 | valid_accuracy: 0.98 | valid_logloss: 0.06311 | 0:00:56s\nepoch 13 | loss: 0.09959 | train_accuracy: 0.97575 | train_logloss: 0.07077 | valid_accuracy: 0.981 | valid_logloss: 0.05703 | 0:01:01s\nepoch 14 | loss: 0.11044 | train_accuracy: 0.97675 | train_logloss: 0.06478 | valid_accuracy: 0.981 | valid_logloss: 0.05323 | 0:01:05s\nepoch 15 | loss: 0.09365 | train_accuracy: 0.97825 | train_logloss: 0.06351 | valid_accuracy: 0.983 | valid_logloss: 0.05273 | 0:01:10s\nepoch 16 | loss: 0.09568 | train_accuracy: 0.978 | train_logloss: 0.06496 | valid_accuracy: 0.985 | valid_logloss: 0.05218 | 0:01:14s\nepoch 17 | loss: 0.09254 | train_accuracy: 0.97825 | train_logloss: 0.06358 | valid_accuracy: 0.981 | valid_logloss: 0.0546 | 0:01:19s\nepoch 18 | loss: 0.09126 | train_accuracy: 0.97825 | train_logloss: 0.06093 | valid_accuracy: 0.986 | valid_logloss: 0.05267 | 0:01:23s\nepoch 19 | loss: 0.08991 | train_accuracy: 0.9795 | train_logloss: 0.05804 | valid_accuracy: 0.98 | valid_logloss: 0.05269 | 0:01:27s\nepoch 20 | loss: 0.08765 | train_accuracy: 0.97925 | train_logloss: 0.05804 | valid_accuracy: 0.98 | valid_logloss: 0.05537 | 0:01:32s\nepoch 21 | loss: 0.08851 | train_accuracy: 0.98125 | train_logloss: 0.05462 | valid_accuracy: 0.98 | valid_logloss: 0.05074 | 0:01:36s\nepoch 22 | loss: 0.07648 | train_accuracy: 0.982 | train_logloss: 0.05536 | valid_accuracy: 0.978 | valid_logloss: 0.05296 | 0:01:41s\nepoch 23 | loss: 0.07967 | train_accuracy: 0.98375 | train_logloss: 0.05075 | valid_accuracy: 0.983 | valid_logloss: 0.04974 | 0:01:45s\nepoch 24 | loss: 0.08996 | train_accuracy: 0.982 | train_logloss: 0.05352 | valid_accuracy: 0.982 | valid_logloss: 0.05144 | 0:01:50s\nepoch 25 | loss: 0.08011 | train_accuracy: 0.9825 | train_logloss: 0.05317 | valid_accuracy: 0.982 | valid_logloss: 0.04918 | 0:01:54s\nepoch 26 | loss: 0.08016 | train_accuracy: 0.983 | train_logloss: 0.05019 | valid_accuracy: 0.984 | valid_logloss: 0.04679 | 0:01:59s\nepoch 27 | loss: 0.08013 | train_accuracy: 0.983 | train_logloss: 0.0512 | valid_accuracy: 0.983 | valid_logloss: 0.04714 | 0:02:03s\nepoch 28 | loss: 0.07712 | train_accuracy: 0.984 | train_logloss: 0.04933 | valid_accuracy: 0.982 | valid_logloss: 0.04968 | 0:02:07s\nepoch 29 | loss: 0.07443 | train_accuracy: 0.9845 | train_logloss: 0.04763 | valid_accuracy: 0.983 | valid_logloss: 0.04586 | 0:02:12s\nepoch 30 | loss: 0.07709 | train_accuracy: 0.984 | train_logloss: 0.04749 | valid_accuracy: 0.983 | valid_logloss: 0.04686 | 0:02:16s\nepoch 31 | loss: 0.07983 | train_accuracy: 0.983 | train_logloss: 0.04984 | valid_accuracy: 0.983 | valid_logloss: 0.04849 | 0:02:21s\nepoch 32 | loss: 0.07573 | train_accuracy: 0.9825 | train_logloss: 0.05021 | valid_accuracy: 0.984 | valid_logloss: 0.04748 | 0:02:26s\nepoch 33 | loss: 0.0813 | train_accuracy: 0.98275 | train_logloss: 0.05036 | valid_accuracy: 0.982 | valid_logloss: 0.0467 | 0:02:30s\nepoch 34 | loss: 0.07579 | train_accuracy: 0.98325 | train_logloss: 0.05043 | valid_accuracy: 0.981 | valid_logloss: 0.048 | 0:02:34s\nepoch 35 | loss: 0.07136 | train_accuracy: 0.9835 | train_logloss: 0.04823 | valid_accuracy: 0.984 | valid_logloss: 0.04387 | 0:02:39s\nepoch 36 | loss: 0.07236 | train_accuracy: 0.985 | train_logloss: 0.046 | valid_accuracy: 0.982 | valid_logloss: 0.0458 | 0:02:43s\nepoch 37 | loss: 0.07784 | train_accuracy: 0.9825 | train_logloss: 0.04768 | valid_accuracy: 0.985 | valid_logloss: 0.04597 | 0:02:47s\nepoch 38 | loss: 0.07219 | train_accuracy: 0.98425 | train_logloss: 0.04593 | valid_accuracy: 0.986 | valid_logloss: 0.04468 | 0:02:52s\nepoch 39 | loss: 0.06311 | train_accuracy: 0.9845 | train_logloss: 0.04456 | valid_accuracy: 0.983 | valid_logloss: 0.04716 | 0:02:56s\nepoch 40 | loss: 0.06948 | train_accuracy: 0.98375 | train_logloss: 0.04345 | valid_accuracy: 0.984 | valid_logloss: 0.04546 | 0:03:01s\nepoch 41 | loss: 0.07713 | train_accuracy: 0.9835 | train_logloss: 0.04617 | valid_accuracy: 0.984 | valid_logloss: 0.04554 | 0:03:05s\nepoch 42 | loss: 0.07477 | train_accuracy: 0.98475 | train_logloss: 0.04493 | valid_accuracy: 0.984 | valid_logloss: 0.04435 | 0:03:09s\nepoch 43 | loss: 0.07505 | train_accuracy: 0.98375 | train_logloss: 0.04604 | valid_accuracy: 0.981 | valid_logloss: 0.04917 | 0:03:14s\nepoch 44 | loss: 0.0709 | train_accuracy: 0.98375 | train_logloss: 0.04504 | valid_accuracy: 0.982 | valid_logloss: 0.04658 | 0:03:18s\nepoch 45 | loss: 0.07225 | train_accuracy: 0.984 | train_logloss: 0.04359 | valid_accuracy: 0.985 | valid_logloss: 0.04426 | 0:03:23s\nepoch 46 | loss: 0.06808 | train_accuracy: 0.98425 | train_logloss: 0.04434 | valid_accuracy: 0.983 | valid_logloss: 0.05234 | 0:03:27s\nepoch 47 | loss: 0.07627 | train_accuracy: 0.9845 | train_logloss: 0.04397 | valid_accuracy: 0.984 | valid_logloss: 0.04693 | 0:03:31s\nepoch 48 | loss: 0.07598 | train_accuracy: 0.9855 | train_logloss: 0.04326 | valid_accuracy: 0.984 | valid_logloss: 0.04756 | 0:03:35s\nepoch 49 | loss: 0.0772 | train_accuracy: 0.98475 | train_logloss: 0.04365 | valid_accuracy: 0.982 | valid_logloss: 0.05281 | 0:03:40s\nStop training because you reached max_epochs = 50 with best_epoch = 35 and best_valid_logloss = 0.04387\nepoch 0 | loss: 0.44162 | train_accuracy: 0.907 | train_logloss: 0.34878 | valid_accuracy: 0.904 | valid_logloss: 0.33155 | 0:00:04s\nepoch 1 | loss: 0.29105 | train_accuracy: 0.9155 | train_logloss: 0.24177 | valid_accuracy: 0.911 | valid_logloss: 0.25004 | 0:00:08s\nepoch 2 | loss: 0.22514 | train_accuracy: 0.934 | train_logloss: 0.19869 | valid_accuracy: 0.918 | valid_logloss: 0.23364 | 0:00:13s\nepoch 3 | loss: 0.21107 | train_accuracy: 0.9405 | train_logloss: 0.17373 | valid_accuracy: 0.929 | valid_logloss: 0.21763 | 0:00:17s\nepoch 4 | loss: 0.18267 | train_accuracy: 0.9515 | train_logloss: 0.1425 | valid_accuracy: 0.936 | valid_logloss: 0.18631 | 0:00:21s\nepoch 5 | loss: 0.15541 | train_accuracy: 0.955 | train_logloss: 0.12093 | valid_accuracy: 0.936 | valid_logloss: 0.17068 | 0:00:26s\nepoch 6 | loss: 0.14804 | train_accuracy: 0.962 | train_logloss: 0.10803 | valid_accuracy: 0.944 | valid_logloss: 0.14117 | 0:00:30s\nepoch 7 | loss: 0.14028 | train_accuracy: 0.965 | train_logloss: 0.09945 | valid_accuracy: 0.949 | valid_logloss: 0.1378 | 0:00:34s\nepoch 8 | loss: 0.13006 | train_accuracy: 0.968 | train_logloss: 0.09474 | valid_accuracy: 0.954 | valid_logloss: 0.1259 | 0:00:39s\nepoch 9 | loss: 0.11872 | train_accuracy: 0.97175 | train_logloss: 0.08775 | valid_accuracy: 0.961 | valid_logloss: 0.1105 | 0:00:44s\nepoch 10 | loss: 0.11965 | train_accuracy: 0.97 | train_logloss: 0.08771 | valid_accuracy: 0.958 | valid_logloss: 0.1192 | 0:00:48s\nepoch 11 | loss: 0.11073 | train_accuracy: 0.9705 | train_logloss: 0.08109 | valid_accuracy: 0.954 | valid_logloss: 0.11311 | 0:00:53s\nepoch 12 | loss: 0.11456 | train_accuracy: 0.9715 | train_logloss: 0.07999 | valid_accuracy: 0.958 | valid_logloss: 0.09727 | 0:00:57s\nepoch 13 | loss: 0.10879 | train_accuracy: 0.9745 | train_logloss: 0.07587 | valid_accuracy: 0.964 | valid_logloss: 0.08607 | 0:01:01s\nepoch 14 | loss: 0.11226 | train_accuracy: 0.9755 | train_logloss: 0.07492 | valid_accuracy: 0.964 | valid_logloss: 0.08654 | 0:01:06s\nepoch 15 | loss: 0.1003 | train_accuracy: 0.97525 | train_logloss: 0.07016 | valid_accuracy: 0.959 | valid_logloss: 0.08956 | 0:01:10s\nepoch 16 | loss: 0.09475 | train_accuracy: 0.9755 | train_logloss: 0.06973 | valid_accuracy: 0.967 | valid_logloss: 0.07974 | 0:01:15s\nepoch 17 | loss: 0.10278 | train_accuracy: 0.977 | train_logloss: 0.06926 | valid_accuracy: 0.969 | valid_logloss: 0.08138 | 0:01:19s\nepoch 18 | loss: 0.09521 | train_accuracy: 0.9765 | train_logloss: 0.06699 | valid_accuracy: 0.967 | valid_logloss: 0.07849 | 0:01:24s\nepoch 19 | loss: 0.09255 | train_accuracy: 0.97875 | train_logloss: 0.06213 | valid_accuracy: 0.965 | valid_logloss: 0.07659 | 0:01:28s\nepoch 20 | loss: 0.09022 | train_accuracy: 0.97925 | train_logloss: 0.06492 | valid_accuracy: 0.97 | valid_logloss: 0.07641 | 0:01:33s\nepoch 21 | loss: 0.08926 | train_accuracy: 0.97825 | train_logloss: 0.06136 | valid_accuracy: 0.967 | valid_logloss: 0.07648 | 0:01:37s\nepoch 22 | loss: 0.09057 | train_accuracy: 0.97975 | train_logloss: 0.059 | valid_accuracy: 0.968 | valid_logloss: 0.0734 | 0:01:41s\nepoch 23 | loss: 0.07961 | train_accuracy: 0.977 | train_logloss: 0.06066 | valid_accuracy: 0.965 | valid_logloss: 0.07639 | 0:01:46s\nepoch 24 | loss: 0.08915 | train_accuracy: 0.98125 | train_logloss: 0.06006 | valid_accuracy: 0.971 | valid_logloss: 0.0749 | 0:01:51s\nepoch 25 | loss: 0.09187 | train_accuracy: 0.9795 | train_logloss: 0.05702 | valid_accuracy: 0.969 | valid_logloss: 0.0752 | 0:01:55s\nepoch 26 | loss: 0.08385 | train_accuracy: 0.981 | train_logloss: 0.05546 | valid_accuracy: 0.971 | valid_logloss: 0.07015 | 0:01:59s\nepoch 27 | loss: 0.09047 | train_accuracy: 0.98125 | train_logloss: 0.05502 | valid_accuracy: 0.97 | valid_logloss: 0.07018 | 0:02:04s\nepoch 28 | loss: 0.07843 | train_accuracy: 0.9815 | train_logloss: 0.05456 | valid_accuracy: 0.973 | valid_logloss: 0.06845 | 0:02:08s\nepoch 29 | loss: 0.07733 | train_accuracy: 0.981 | train_logloss: 0.05446 | valid_accuracy: 0.97 | valid_logloss: 0.07279 | 0:02:13s\nepoch 30 | loss: 0.08278 | train_accuracy: 0.9825 | train_logloss: 0.05136 | valid_accuracy: 0.974 | valid_logloss: 0.07053 | 0:02:18s\nepoch 31 | loss: 0.08567 | train_accuracy: 0.9815 | train_logloss: 0.05244 | valid_accuracy: 0.973 | valid_logloss: 0.06946 | 0:02:22s\nepoch 32 | loss: 0.06783 | train_accuracy: 0.982 | train_logloss: 0.04925 | valid_accuracy: 0.974 | valid_logloss: 0.06719 | 0:02:27s\nepoch 33 | loss: 0.07998 | train_accuracy: 0.98225 | train_logloss: 0.0484 | valid_accuracy: 0.972 | valid_logloss: 0.07016 | 0:02:31s\nepoch 34 | loss: 0.07416 | train_accuracy: 0.984 | train_logloss: 0.04737 | valid_accuracy: 0.972 | valid_logloss: 0.06746 | 0:02:36s\nepoch 35 | loss: 0.08626 | train_accuracy: 0.9835 | train_logloss: 0.04785 | valid_accuracy: 0.972 | valid_logloss: 0.06714 | 0:02:40s\nepoch 36 | loss: 0.08041 | train_accuracy: 0.984 | train_logloss: 0.04653 | valid_accuracy: 0.971 | valid_logloss: 0.06712 | 0:02:45s\nepoch 37 | loss: 0.07387 | train_accuracy: 0.98325 | train_logloss: 0.04694 | valid_accuracy: 0.971 | valid_logloss: 0.06607 | 0:02:50s\nepoch 38 | loss: 0.07533 | train_accuracy: 0.98275 | train_logloss: 0.04647 | valid_accuracy: 0.972 | valid_logloss: 0.06481 | 0:02:54s\nepoch 39 | loss: 0.07776 | train_accuracy: 0.98425 | train_logloss: 0.04621 | valid_accuracy: 0.971 | valid_logloss: 0.06531 | 0:02:58s\nepoch 40 | loss: 0.07213 | train_accuracy: 0.9855 | train_logloss: 0.04351 | valid_accuracy: 0.973 | valid_logloss: 0.06248 | 0:03:03s\nepoch 41 | loss: 0.08365 | train_accuracy: 0.9855 | train_logloss: 0.04594 | valid_accuracy: 0.972 | valid_logloss: 0.06532 | 0:03:07s\nepoch 42 | loss: 0.06911 | train_accuracy: 0.9855 | train_logloss: 0.04389 | valid_accuracy: 0.971 | valid_logloss: 0.06554 | 0:03:12s\nepoch 43 | loss: 0.06544 | train_accuracy: 0.985 | train_logloss: 0.04361 | valid_accuracy: 0.973 | valid_logloss: 0.06453 | 0:03:16s\nepoch 44 | loss: 0.06843 | train_accuracy: 0.985 | train_logloss: 0.04339 | valid_accuracy: 0.972 | valid_logloss: 0.06909 | 0:03:21s\nepoch 45 | loss: 0.07661 | train_accuracy: 0.985 | train_logloss: 0.0418 | valid_accuracy: 0.974 | valid_logloss: 0.06235 | 0:03:25s\nepoch 46 | loss: 0.06785 | train_accuracy: 0.9855 | train_logloss: 0.04336 | valid_accuracy: 0.97 | valid_logloss: 0.0625 | 0:03:29s\nepoch 47 | loss: 0.07299 | train_accuracy: 0.9855 | train_logloss: 0.0442 | valid_accuracy: 0.97 | valid_logloss: 0.06629 | 0:03:34s\nepoch 48 | loss: 0.07223 | train_accuracy: 0.98425 | train_logloss: 0.04478 | valid_accuracy: 0.969 | valid_logloss: 0.06743 | 0:03:38s\nepoch 49 | loss: 0.0698 | train_accuracy: 0.98575 | train_logloss: 0.04154 | valid_accuracy: 0.972 | valid_logloss: 0.06499 | 0:03:43s\nStop training because you reached max_epochs = 50 with best_epoch = 45 and best_valid_logloss = 0.06235\nepoch 0 | loss: 0.42437 | train_accuracy: 0.90725 | train_logloss: 0.3316 | valid_accuracy: 0.894 | valid_logloss: 0.3534 | 0:00:05s\nepoch 1 | loss: 0.27753 | train_accuracy: 0.91375 | train_logloss: 0.24663 | valid_accuracy: 0.905 | valid_logloss: 0.23881 | 0:00:09s\nepoch 2 | loss: 0.24037 | train_accuracy: 0.9215 | train_logloss: 0.21762 | valid_accuracy: 0.913 | valid_logloss: 0.22503 | 0:00:14s\nepoch 3 | loss: 0.21682 | train_accuracy: 0.931 | train_logloss: 0.21127 | valid_accuracy: 0.92 | valid_logloss: 0.22107 | 0:00:19s\nepoch 4 | loss: 0.19298 | train_accuracy: 0.937 | train_logloss: 0.17673 | valid_accuracy: 0.936 | valid_logloss: 0.17538 | 0:00:23s\nepoch 5 | loss: 0.19004 | train_accuracy: 0.943 | train_logloss: 0.16582 | valid_accuracy: 0.937 | valid_logloss: 0.16929 | 0:00:27s\nepoch 6 | loss: 0.16657 | train_accuracy: 0.94875 | train_logloss: 0.14952 | valid_accuracy: 0.944 | valid_logloss: 0.14036 | 0:00:32s\nepoch 7 | loss: 0.14627 | train_accuracy: 0.953 | train_logloss: 0.13535 | valid_accuracy: 0.95 | valid_logloss: 0.13525 | 0:00:37s\nepoch 8 | loss: 0.14664 | train_accuracy: 0.955 | train_logloss: 0.11642 | valid_accuracy: 0.952 | valid_logloss: 0.12078 | 0:00:42s\nepoch 9 | loss: 0.13628 | train_accuracy: 0.95675 | train_logloss: 0.11134 | valid_accuracy: 0.956 | valid_logloss: 0.12118 | 0:00:46s\nepoch 10 | loss: 0.12352 | train_accuracy: 0.966 | train_logloss: 0.09231 | valid_accuracy: 0.957 | valid_logloss: 0.10628 | 0:00:50s\nepoch 11 | loss: 0.11648 | train_accuracy: 0.9675 | train_logloss: 0.08539 | valid_accuracy: 0.961 | valid_logloss: 0.10423 | 0:00:55s\nepoch 12 | loss: 0.11134 | train_accuracy: 0.968 | train_logloss: 0.08447 | valid_accuracy: 0.96 | valid_logloss: 0.10725 | 0:01:00s\nepoch 13 | loss: 0.10862 | train_accuracy: 0.9715 | train_logloss: 0.07693 | valid_accuracy: 0.963 | valid_logloss: 0.09969 | 0:01:05s\nepoch 14 | loss: 0.09714 | train_accuracy: 0.9715 | train_logloss: 0.07525 | valid_accuracy: 0.967 | valid_logloss: 0.09323 | 0:01:09s\nepoch 15 | loss: 0.11006 | train_accuracy: 0.9755 | train_logloss: 0.06899 | valid_accuracy: 0.966 | valid_logloss: 0.09066 | 0:01:14s\nepoch 16 | loss: 0.09265 | train_accuracy: 0.978 | train_logloss: 0.06438 | valid_accuracy: 0.968 | valid_logloss: 0.08326 | 0:01:19s\nepoch 17 | loss: 0.09309 | train_accuracy: 0.978 | train_logloss: 0.0625 | valid_accuracy: 0.968 | valid_logloss: 0.0821 | 0:01:23s\nepoch 18 | loss: 0.09399 | train_accuracy: 0.979 | train_logloss: 0.05801 | valid_accuracy: 0.968 | valid_logloss: 0.08182 | 0:01:28s\nepoch 19 | loss: 0.09151 | train_accuracy: 0.978 | train_logloss: 0.05727 | valid_accuracy: 0.968 | valid_logloss: 0.08163 | 0:01:32s\nepoch 20 | loss: 0.08726 | train_accuracy: 0.97875 | train_logloss: 0.05679 | valid_accuracy: 0.968 | valid_logloss: 0.07612 | 0:01:37s\nepoch 21 | loss: 0.09841 | train_accuracy: 0.97725 | train_logloss: 0.05787 | valid_accuracy: 0.968 | valid_logloss: 0.08044 | 0:01:41s\nepoch 22 | loss: 0.08624 | train_accuracy: 0.979 | train_logloss: 0.05672 | valid_accuracy: 0.966 | valid_logloss: 0.07781 | 0:01:46s\nepoch 23 | loss: 0.09706 | train_accuracy: 0.97975 | train_logloss: 0.05578 | valid_accuracy: 0.968 | valid_logloss: 0.08015 | 0:01:50s\nepoch 24 | loss: 0.08781 | train_accuracy: 0.9805 | train_logloss: 0.05371 | valid_accuracy: 0.969 | valid_logloss: 0.07508 | 0:01:55s\nepoch 25 | loss: 0.08722 | train_accuracy: 0.98025 | train_logloss: 0.05421 | valid_accuracy: 0.971 | valid_logloss: 0.07676 | 0:02:00s\nepoch 26 | loss: 0.08846 | train_accuracy: 0.97925 | train_logloss: 0.05677 | valid_accuracy: 0.967 | valid_logloss: 0.08083 | 0:02:04s\nepoch 27 | loss: 0.08208 | train_accuracy: 0.9805 | train_logloss: 0.05216 | valid_accuracy: 0.966 | valid_logloss: 0.0746 | 0:02:09s\nepoch 28 | loss: 0.0802 | train_accuracy: 0.982 | train_logloss: 0.04959 | valid_accuracy: 0.972 | valid_logloss: 0.06991 | 0:02:13s\nepoch 29 | loss: 0.08122 | train_accuracy: 0.981 | train_logloss: 0.05118 | valid_accuracy: 0.974 | valid_logloss: 0.07266 | 0:02:18s\nepoch 30 | loss: 0.08246 | train_accuracy: 0.98175 | train_logloss: 0.04998 | valid_accuracy: 0.973 | valid_logloss: 0.07253 | 0:02:23s\nepoch 31 | loss: 0.08155 | train_accuracy: 0.98225 | train_logloss: 0.049 | valid_accuracy: 0.975 | valid_logloss: 0.07262 | 0:02:27s\nepoch 32 | loss: 0.06693 | train_accuracy: 0.9825 | train_logloss: 0.04727 | valid_accuracy: 0.976 | valid_logloss: 0.0712 | 0:02:32s\nepoch 33 | loss: 0.08107 | train_accuracy: 0.98225 | train_logloss: 0.04823 | valid_accuracy: 0.975 | valid_logloss: 0.07259 | 0:02:37s\nepoch 34 | loss: 0.0773 | train_accuracy: 0.9825 | train_logloss: 0.04848 | valid_accuracy: 0.973 | valid_logloss: 0.07483 | 0:02:41s\nepoch 35 | loss: 0.06749 | train_accuracy: 0.98275 | train_logloss: 0.04669 | valid_accuracy: 0.974 | valid_logloss: 0.07042 | 0:02:46s\nepoch 36 | loss: 0.06486 | train_accuracy: 0.9845 | train_logloss: 0.04203 | valid_accuracy: 0.974 | valid_logloss: 0.0672 | 0:02:51s\nepoch 37 | loss: 0.07212 | train_accuracy: 0.9835 | train_logloss: 0.04314 | valid_accuracy: 0.975 | valid_logloss: 0.06677 | 0:02:55s\nepoch 38 | loss: 0.08632 | train_accuracy: 0.98325 | train_logloss: 0.04319 | valid_accuracy: 0.975 | valid_logloss: 0.0657 | 0:02:59s\nepoch 39 | loss: 0.07931 | train_accuracy: 0.986 | train_logloss: 0.04155 | valid_accuracy: 0.975 | valid_logloss: 0.06679 | 0:03:04s\nepoch 40 | loss: 0.07521 | train_accuracy: 0.98525 | train_logloss: 0.04325 | valid_accuracy: 0.976 | valid_logloss: 0.06773 | 0:03:08s\nepoch 41 | loss: 0.06992 | train_accuracy: 0.9845 | train_logloss: 0.04208 | valid_accuracy: 0.977 | valid_logloss: 0.06638 | 0:03:13s\nepoch 42 | loss: 0.07875 | train_accuracy: 0.9855 | train_logloss: 0.04137 | valid_accuracy: 0.978 | valid_logloss: 0.06706 | 0:03:18s\nepoch 43 | loss: 0.06669 | train_accuracy: 0.98425 | train_logloss: 0.04238 | valid_accuracy: 0.977 | valid_logloss: 0.06838 | 0:03:22s\nepoch 44 | loss: 0.07082 | train_accuracy: 0.9845 | train_logloss: 0.041 | valid_accuracy: 0.98 | valid_logloss: 0.06493 | 0:03:27s\nepoch 45 | loss: 0.06728 | train_accuracy: 0.98625 | train_logloss: 0.04007 | valid_accuracy: 0.98 | valid_logloss: 0.06575 | 0:03:31s\nepoch 46 | loss: 0.06965 | train_accuracy: 0.9855 | train_logloss: 0.04029 | valid_accuracy: 0.978 | valid_logloss: 0.0626 | 0:03:36s\nepoch 47 | loss: 0.07059 | train_accuracy: 0.986 | train_logloss: 0.03907 | valid_accuracy: 0.977 | valid_logloss: 0.06416 | 0:03:40s\nepoch 48 | loss: 0.06808 | train_accuracy: 0.98575 | train_logloss: 0.03844 | valid_accuracy: 0.978 | valid_logloss: 0.06484 | 0:03:45s\nepoch 49 | loss: 0.06402 | train_accuracy: 0.9855 | train_logloss: 0.04075 | valid_accuracy: 0.978 | valid_logloss: 0.06853 | 0:03:49s\nStop training because you reached max_epochs = 50 with best_epoch = 46 and best_valid_logloss = 0.0626\nepoch 0 | loss: 0.43983 | train_accuracy: 0.9035 | train_logloss: 0.34161 | valid_accuracy: 0.922 | valid_logloss: 0.32513 | 0:00:04s\nepoch 1 | loss: 0.29305 | train_accuracy: 0.909 | train_logloss: 0.25167 | valid_accuracy: 0.926 | valid_logloss: 0.23462 | 0:00:08s\nepoch 2 | loss: 0.24797 | train_accuracy: 0.92225 | train_logloss: 0.2053 | valid_accuracy: 0.935 | valid_logloss: 0.19918 | 0:00:13s\nepoch 3 | loss: 0.2138 | train_accuracy: 0.93225 | train_logloss: 0.18106 | valid_accuracy: 0.938 | valid_logloss: 0.17341 | 0:00:17s\nepoch 4 | loss: 0.18299 | train_accuracy: 0.93675 | train_logloss: 0.16705 | valid_accuracy: 0.941 | valid_logloss: 0.15843 | 0:00:22s\nepoch 5 | loss: 0.17684 | train_accuracy: 0.94875 | train_logloss: 0.13862 | valid_accuracy: 0.951 | valid_logloss: 0.13583 | 0:00:26s\nepoch 6 | loss: 0.15728 | train_accuracy: 0.9505 | train_logloss: 0.13352 | valid_accuracy: 0.949 | valid_logloss: 0.12484 | 0:00:31s\nepoch 7 | loss: 0.14769 | train_accuracy: 0.958 | train_logloss: 0.12498 | valid_accuracy: 0.952 | valid_logloss: 0.11141 | 0:00:35s\nepoch 8 | loss: 0.1319 | train_accuracy: 0.95925 | train_logloss: 0.11133 | valid_accuracy: 0.957 | valid_logloss: 0.10125 | 0:00:40s\nepoch 9 | loss: 0.13235 | train_accuracy: 0.96425 | train_logloss: 0.09682 | valid_accuracy: 0.963 | valid_logloss: 0.09174 | 0:00:44s\nepoch 10 | loss: 0.1277 | train_accuracy: 0.96725 | train_logloss: 0.0985 | valid_accuracy: 0.964 | valid_logloss: 0.09822 | 0:00:49s\nepoch 11 | loss: 0.11582 | train_accuracy: 0.96525 | train_logloss: 0.09291 | valid_accuracy: 0.966 | valid_logloss: 0.09259 | 0:00:53s\nepoch 12 | loss: 0.11284 | train_accuracy: 0.968 | train_logloss: 0.08491 | valid_accuracy: 0.971 | valid_logloss: 0.08385 | 0:00:58s\nepoch 13 | loss: 0.11282 | train_accuracy: 0.97025 | train_logloss: 0.08422 | valid_accuracy: 0.973 | valid_logloss: 0.08642 | 0:01:03s\nepoch 14 | loss: 0.10793 | train_accuracy: 0.97225 | train_logloss: 0.07847 | valid_accuracy: 0.979 | valid_logloss: 0.07843 | 0:01:07s\nepoch 15 | loss: 0.11153 | train_accuracy: 0.9735 | train_logloss: 0.07542 | valid_accuracy: 0.98 | valid_logloss: 0.07064 | 0:01:11s\nepoch 16 | loss: 0.10154 | train_accuracy: 0.9745 | train_logloss: 0.07269 | valid_accuracy: 0.978 | valid_logloss: 0.07036 | 0:01:16s\nepoch 17 | loss: 0.09563 | train_accuracy: 0.974 | train_logloss: 0.07036 | valid_accuracy: 0.976 | valid_logloss: 0.06593 | 0:01:20s\nepoch 18 | loss: 0.0968 | train_accuracy: 0.974 | train_logloss: 0.07055 | valid_accuracy: 0.978 | valid_logloss: 0.06645 | 0:01:24s\nepoch 19 | loss: 0.09838 | train_accuracy: 0.9755 | train_logloss: 0.06668 | valid_accuracy: 0.976 | valid_logloss: 0.06526 | 0:01:29s\nepoch 20 | loss: 0.09587 | train_accuracy: 0.97275 | train_logloss: 0.06666 | valid_accuracy: 0.976 | valid_logloss: 0.06359 | 0:01:34s\nepoch 21 | loss: 0.0978 | train_accuracy: 0.97425 | train_logloss: 0.06717 | valid_accuracy: 0.974 | valid_logloss: 0.06344 | 0:01:38s\nepoch 22 | loss: 0.09172 | train_accuracy: 0.97675 | train_logloss: 0.06448 | valid_accuracy: 0.974 | valid_logloss: 0.0633 | 0:01:43s\nepoch 23 | loss: 0.0951 | train_accuracy: 0.977 | train_logloss: 0.06532 | valid_accuracy: 0.976 | valid_logloss: 0.06138 | 0:01:47s\nepoch 24 | loss: 0.09797 | train_accuracy: 0.977 | train_logloss: 0.06554 | valid_accuracy: 0.979 | valid_logloss: 0.06284 | 0:01:52s\nepoch 25 | loss: 0.09377 | train_accuracy: 0.9765 | train_logloss: 0.06315 | valid_accuracy: 0.978 | valid_logloss: 0.06134 | 0:01:56s\nepoch 26 | loss: 0.09182 | train_accuracy: 0.97925 | train_logloss: 0.06071 | valid_accuracy: 0.98 | valid_logloss: 0.05766 | 0:02:01s\nepoch 27 | loss: 0.09595 | train_accuracy: 0.9775 | train_logloss: 0.06301 | valid_accuracy: 0.978 | valid_logloss: 0.06026 | 0:02:05s\nepoch 28 | loss: 0.0983 | train_accuracy: 0.97775 | train_logloss: 0.0599 | valid_accuracy: 0.98 | valid_logloss: 0.05427 | 0:02:10s\nepoch 29 | loss: 0.08057 | train_accuracy: 0.98075 | train_logloss: 0.05603 | valid_accuracy: 0.982 | valid_logloss: 0.05379 | 0:02:14s\nepoch 30 | loss: 0.08707 | train_accuracy: 0.9795 | train_logloss: 0.05882 | valid_accuracy: 0.985 | valid_logloss: 0.05308 | 0:02:19s\nepoch 31 | loss: 0.09317 | train_accuracy: 0.9795 | train_logloss: 0.05766 | valid_accuracy: 0.981 | valid_logloss: 0.05484 | 0:02:23s\nepoch 32 | loss: 0.08158 | train_accuracy: 0.981 | train_logloss: 0.05691 | valid_accuracy: 0.984 | valid_logloss: 0.05239 | 0:02:28s\nepoch 33 | loss: 0.08554 | train_accuracy: 0.982 | train_logloss: 0.05619 | valid_accuracy: 0.983 | valid_logloss: 0.05108 | 0:02:32s\nepoch 34 | loss: 0.08017 | train_accuracy: 0.98325 | train_logloss: 0.0552 | valid_accuracy: 0.984 | valid_logloss: 0.04733 | 0:02:37s\nepoch 35 | loss: 0.08786 | train_accuracy: 0.983 | train_logloss: 0.05533 | valid_accuracy: 0.982 | valid_logloss: 0.05018 | 0:02:42s\nepoch 36 | loss: 0.07885 | train_accuracy: 0.982 | train_logloss: 0.054 | valid_accuracy: 0.981 | valid_logloss: 0.05224 | 0:02:46s\nepoch 37 | loss: 0.08603 | train_accuracy: 0.981 | train_logloss: 0.05438 | valid_accuracy: 0.983 | valid_logloss: 0.04862 | 0:02:50s\nepoch 38 | loss: 0.07875 | train_accuracy: 0.9825 | train_logloss: 0.05365 | valid_accuracy: 0.983 | valid_logloss: 0.04908 | 0:02:55s\nepoch 39 | loss: 0.08308 | train_accuracy: 0.98275 | train_logloss: 0.05268 | valid_accuracy: 0.984 | valid_logloss: 0.04948 | 0:02:59s\nepoch 40 | loss: 0.0704 | train_accuracy: 0.9835 | train_logloss: 0.05157 | valid_accuracy: 0.986 | valid_logloss: 0.0469 | 0:03:03s\nepoch 41 | loss: 0.07966 | train_accuracy: 0.9835 | train_logloss: 0.04967 | valid_accuracy: 0.985 | valid_logloss: 0.04664 | 0:03:08s\nepoch 42 | loss: 0.07787 | train_accuracy: 0.98275 | train_logloss: 0.05298 | valid_accuracy: 0.983 | valid_logloss: 0.05028 | 0:03:13s\nepoch 43 | loss: 0.08037 | train_accuracy: 0.983 | train_logloss: 0.05124 | valid_accuracy: 0.987 | valid_logloss: 0.04894 | 0:03:17s\nepoch 44 | loss: 0.08094 | train_accuracy: 0.984 | train_logloss: 0.05019 | valid_accuracy: 0.986 | valid_logloss: 0.04792 | 0:03:21s\nepoch 45 | loss: 0.07437 | train_accuracy: 0.9835 | train_logloss: 0.04985 | valid_accuracy: 0.985 | valid_logloss: 0.04904 | 0:03:26s\nepoch 46 | loss: 0.07631 | train_accuracy: 0.982 | train_logloss: 0.05042 | valid_accuracy: 0.984 | valid_logloss: 0.05085 | 0:03:30s\nepoch 47 | loss: 0.07983 | train_accuracy: 0.9835 | train_logloss: 0.04996 | valid_accuracy: 0.984 | valid_logloss: 0.05336 | 0:03:35s\nepoch 48 | loss: 0.07086 | train_accuracy: 0.98375 | train_logloss: 0.04742 | valid_accuracy: 0.982 | valid_logloss: 0.05139 | 0:03:39s\nepoch 49 | loss: 0.07612 | train_accuracy: 0.984 | train_logloss: 0.04716 | valid_accuracy: 0.985 | valid_logloss: 0.05371 | 0:03:43s\nStop training because you reached max_epochs = 50 with best_epoch = 41 and best_valid_logloss = 0.04664\nepoch 0 | loss: 0.44012 | train_accuracy: 0.904 | train_logloss: 0.338 | valid_accuracy: 0.913 | valid_logloss: 0.33881 | 0:00:04s\nepoch 1 | loss: 0.28962 | train_accuracy: 0.91125 | train_logloss: 0.24961 | valid_accuracy: 0.917 | valid_logloss: 0.25271 | 0:00:08s\nepoch 2 | loss: 0.24651 | train_accuracy: 0.915 | train_logloss: 0.21412 | valid_accuracy: 0.932 | valid_logloss: 0.19067 | 0:00:13s\nepoch 3 | loss: 0.22374 | train_accuracy: 0.923 | train_logloss: 0.19464 | valid_accuracy: 0.943 | valid_logloss: 0.17182 | 0:00:17s\nepoch 4 | loss: 0.20625 | train_accuracy: 0.93325 | train_logloss: 0.17387 | valid_accuracy: 0.956 | valid_logloss: 0.16291 | 0:00:21s\nepoch 5 | loss: 0.17737 | train_accuracy: 0.94375 | train_logloss: 0.15067 | valid_accuracy: 0.954 | valid_logloss: 0.13248 | 0:00:26s\nepoch 6 | loss: 0.16654 | train_accuracy: 0.94875 | train_logloss: 0.14014 | valid_accuracy: 0.96 | valid_logloss: 0.1401 | 0:00:31s\nepoch 7 | loss: 0.15215 | train_accuracy: 0.957 | train_logloss: 0.11921 | valid_accuracy: 0.961 | valid_logloss: 0.14243 | 0:00:35s\nepoch 8 | loss: 0.13483 | train_accuracy: 0.96525 | train_logloss: 0.10815 | valid_accuracy: 0.964 | valid_logloss: 0.1086 | 0:00:39s\nepoch 9 | loss: 0.12576 | train_accuracy: 0.96775 | train_logloss: 0.09007 | valid_accuracy: 0.97 | valid_logloss: 0.09043 | 0:00:44s\nepoch 10 | loss: 0.11438 | train_accuracy: 0.96975 | train_logloss: 0.08317 | valid_accuracy: 0.973 | valid_logloss: 0.08804 | 0:00:48s\nepoch 11 | loss: 0.11108 | train_accuracy: 0.9725 | train_logloss: 0.07812 | valid_accuracy: 0.97 | valid_logloss: 0.08863 | 0:00:53s\nepoch 12 | loss: 0.11124 | train_accuracy: 0.97375 | train_logloss: 0.07421 | valid_accuracy: 0.969 | valid_logloss: 0.08436 | 0:00:57s\nepoch 13 | loss: 0.10238 | train_accuracy: 0.9725 | train_logloss: 0.07255 | valid_accuracy: 0.972 | valid_logloss: 0.083 | 0:01:02s\nepoch 14 | loss: 0.09749 | train_accuracy: 0.9745 | train_logloss: 0.06854 | valid_accuracy: 0.975 | valid_logloss: 0.08209 | 0:01:06s\nepoch 15 | loss: 0.0881 | train_accuracy: 0.977 | train_logloss: 0.06347 | valid_accuracy: 0.974 | valid_logloss: 0.07769 | 0:01:11s\nepoch 16 | loss: 0.08479 | train_accuracy: 0.98175 | train_logloss: 0.05552 | valid_accuracy: 0.975 | valid_logloss: 0.07069 | 0:01:15s\nepoch 17 | loss: 0.08593 | train_accuracy: 0.9795 | train_logloss: 0.05531 | valid_accuracy: 0.976 | valid_logloss: 0.07577 | 0:01:19s\nepoch 18 | loss: 0.08929 | train_accuracy: 0.97925 | train_logloss: 0.0573 | valid_accuracy: 0.976 | valid_logloss: 0.0758 | 0:01:24s\nepoch 19 | loss: 0.08786 | train_accuracy: 0.97725 | train_logloss: 0.05973 | valid_accuracy: 0.973 | valid_logloss: 0.07705 | 0:01:28s\nepoch 20 | loss: 0.08803 | train_accuracy: 0.98025 | train_logloss: 0.05474 | valid_accuracy: 0.975 | valid_logloss: 0.07163 | 0:01:33s\nepoch 21 | loss: 0.08108 | train_accuracy: 0.98025 | train_logloss: 0.05286 | valid_accuracy: 0.976 | valid_logloss: 0.07074 | 0:01:37s\nepoch 22 | loss: 0.08473 | train_accuracy: 0.98025 | train_logloss: 0.0539 | valid_accuracy: 0.978 | valid_logloss: 0.07218 | 0:01:41s\nepoch 23 | loss: 0.08437 | train_accuracy: 0.97975 | train_logloss: 0.05322 | valid_accuracy: 0.977 | valid_logloss: 0.06907 | 0:01:45s\nepoch 24 | loss: 0.08656 | train_accuracy: 0.98 | train_logloss: 0.05175 | valid_accuracy: 0.98 | valid_logloss: 0.06512 | 0:01:50s\nepoch 25 | loss: 0.0797 | train_accuracy: 0.98 | train_logloss: 0.05298 | valid_accuracy: 0.976 | valid_logloss: 0.07155 | 0:01:54s\nepoch 26 | loss: 0.08064 | train_accuracy: 0.98225 | train_logloss: 0.04712 | valid_accuracy: 0.978 | valid_logloss: 0.06808 | 0:01:58s\nepoch 27 | loss: 0.07343 | train_accuracy: 0.9845 | train_logloss: 0.04434 | valid_accuracy: 0.979 | valid_logloss: 0.06781 | 0:02:03s\nepoch 28 | loss: 0.0784 | train_accuracy: 0.9825 | train_logloss: 0.04726 | valid_accuracy: 0.978 | valid_logloss: 0.0711 | 0:02:07s\nepoch 29 | loss: 0.07789 | train_accuracy: 0.9835 | train_logloss: 0.04476 | valid_accuracy: 0.978 | valid_logloss: 0.06917 | 0:02:12s\nepoch 30 | loss: 0.06916 | train_accuracy: 0.98325 | train_logloss: 0.04429 | valid_accuracy: 0.979 | valid_logloss: 0.06651 | 0:02:16s\nepoch 31 | loss: 0.07809 | train_accuracy: 0.984 | train_logloss: 0.0462 | valid_accuracy: 0.976 | valid_logloss: 0.07049 | 0:02:20s\nepoch 32 | loss: 0.07897 | train_accuracy: 0.98525 | train_logloss: 0.04287 | valid_accuracy: 0.978 | valid_logloss: 0.06972 | 0:02:25s\nepoch 33 | loss: 0.07303 | train_accuracy: 0.9845 | train_logloss: 0.04104 | valid_accuracy: 0.976 | valid_logloss: 0.06694 | 0:02:29s\nepoch 34 | loss: 0.08032 | train_accuracy: 0.98475 | train_logloss: 0.04435 | valid_accuracy: 0.975 | valid_logloss: 0.06805 | 0:02:34s\nepoch 35 | loss: 0.0653 | train_accuracy: 0.98375 | train_logloss: 0.04362 | valid_accuracy: 0.977 | valid_logloss: 0.06721 | 0:02:38s\nepoch 36 | loss: 0.0806 | train_accuracy: 0.98325 | train_logloss: 0.04249 | valid_accuracy: 0.976 | valid_logloss: 0.06749 | 0:02:42s\nepoch 37 | loss: 0.0635 | train_accuracy: 0.9835 | train_logloss: 0.0439 | valid_accuracy: 0.973 | valid_logloss: 0.06919 | 0:02:47s\nepoch 38 | loss: 0.07094 | train_accuracy: 0.9845 | train_logloss: 0.04206 | valid_accuracy: 0.975 | valid_logloss: 0.07153 | 0:02:51s\nepoch 39 | loss: 0.06411 | train_accuracy: 0.9855 | train_logloss: 0.03874 | valid_accuracy: 0.979 | valid_logloss: 0.06744 | 0:02:55s\nepoch 40 | loss: 0.08585 | train_accuracy: 0.9865 | train_logloss: 0.03897 | valid_accuracy: 0.975 | valid_logloss: 0.06951 | 0:03:00s\nepoch 41 | loss: 0.07474 | train_accuracy: 0.98475 | train_logloss: 0.04078 | valid_accuracy: 0.977 | valid_logloss: 0.06912 | 0:03:04s\nepoch 42 | loss: 0.0615 | train_accuracy: 0.9865 | train_logloss: 0.03818 | valid_accuracy: 0.979 | valid_logloss: 0.06766 | 0:03:09s\nepoch 43 | loss: 0.07032 | train_accuracy: 0.98625 | train_logloss: 0.03913 | valid_accuracy: 0.98 | valid_logloss: 0.06813 | 0:03:13s\nepoch 44 | loss: 0.0589 | train_accuracy: 0.98575 | train_logloss: 0.04025 | valid_accuracy: 0.976 | valid_logloss: 0.07139 | 0:03:17s\nepoch 45 | loss: 0.06452 | train_accuracy: 0.98775 | train_logloss: 0.03583 | valid_accuracy: 0.981 | valid_logloss: 0.06973 | 0:03:22s\nepoch 46 | loss: 0.05851 | train_accuracy: 0.98575 | train_logloss: 0.03958 | valid_accuracy: 0.975 | valid_logloss: 0.07459 | 0:03:26s\nepoch 47 | loss: 0.07004 | train_accuracy: 0.98625 | train_logloss: 0.03794 | valid_accuracy: 0.976 | valid_logloss: 0.07326 | 0:03:31s\nepoch 48 | loss: 0.05869 | train_accuracy: 0.98775 | train_logloss: 0.03746 | valid_accuracy: 0.979 | valid_logloss: 0.07279 | 0:03:35s\nepoch 49 | loss: 0.06429 | train_accuracy: 0.988 | train_logloss: 0.03648 | valid_accuracy: 0.977 | valid_logloss: 0.0706 | 0:03:40s\n\nEarly stopping occurred at epoch 49 with best_epoch = 24 and best_valid_logloss = 0.06512\n[0.043866922779519965, 0.06235424959751099, 0.06259904950568762, 0.04663541300107883, 0.06512253974846269]\n","output_type":"stream"}]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\n\n# history accessible from tb_cls.fit output\nhistory = tb_cls.history \n\n# Extract accuracy and loss for training and validation sets\ntrain_acc = history['train_accuracy']\nval_acc = history['valid_accuracy']\ntrain_loss = history['train_logloss']\nval_loss = history['valid_logloss']\n\n# Plotting accuracy\nplt.figure(figsize=(10, 6))\nplt.plot(train_acc, label='Training Accuracy')\nplt.plot(val_acc, label='Validation Accuracy')\nplt.xlabel('Epoch')\nplt.ylabel('Accuracy')\nplt.title('Training vs. Validation Accuracy')\nplt.legend()\nplt.grid(True)\nplt.show()\n\n# Plotting accuracy\nplt.figure(figsize=(10, 6))\nplt.plot(train_loss, label='Training Logloss')\nplt.plot(val_loss, label='Validation Logloss')\nplt.xlabel('Epoch')\nplt.ylabel('Loss')\nplt.title('Training vs. Validation Logloss')\nplt.legend()\nplt.grid(True)\nplt.show()","metadata":{"id":"FG_I_RqcBdAr","execution":{"iopub.status.busy":"2024-05-22T13:12:46.370002Z","iopub.execute_input":"2024-05-22T13:12:46.370490Z","iopub.status.idle":"2024-05-22T13:12:46.960388Z","shell.execute_reply.started":"2024-05-22T13:12:46.370454Z","shell.execute_reply":"2024-05-22T13:12:46.959121Z"},"trusted":true},"execution_count":32,"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"# saving model\ntb_cls.save_model('/kaggle/working/best_model')","metadata":{"execution":{"iopub.status.busy":"2024-05-22T13:12:52.907272Z","iopub.execute_input":"2024-05-22T13:12:52.907670Z","iopub.status.idle":"2024-05-22T13:12:52.934212Z","shell.execute_reply.started":"2024-05-22T13:12:52.907640Z","shell.execute_reply":"2024-05-22T13:12:52.932957Z"},"trusted":true},"execution_count":33,"outputs":[{"name":"stdout","text":"Successfully saved model at /kaggle/working/best_model.zip\n","output_type":"stream"},{"execution_count":33,"output_type":"execute_result","data":{"text/plain":"'/kaggle/working/best_model.zip'"},"metadata":{}}]},{"cell_type":"markdown","source":"# Wide & Deep neural network architecture\n\nThis implements a Wide & Deep neural network architecture using TensorFlow's Keras API for binary classification tasks.\n\n### Components of the Model:\n\n#### Normalization of Data:\n\n- The input data is normalized using mean and standard deviation calculated from the training data. This step helps in stabilizing the training process and improving convergence.\n\n#### Wide Component:\n\n- The wide component is a linear model that directly connects the input features to the output layer without any non-linear transformations. It is represented by a single Dense layer.\n\n#### Deep Component:\n\n- The deep component is a neural network consisting of multiple layers. Each layer is followed by Batch Normalization, LeakyReLU activation, and Dropout for regularization.\n- It comprises three Dense layers with 128, 64, and 32 units, respectively.\n\n#### Combining Wide and Deep Components:\n\n- The outputs from the wide and deep components are concatenated using the Concatenate layer.\n- This allows the model to learn both low-level and high-level feature representations simultaneously.\n\n#### Final Output Layer:\n\n- The concatenated output is passed through a final Dense layer with a sigmoid activation function, which outputs the predicted probability of the positive class (binary classification).\n\n# Metrics\n\n- Training Accuracy: 0.9715\n- Training Loss: 0.0752\n- val_accuracy: 0.9760\n- val_loss: 0.0531 \n- learning_rate: 1.0000e-05","metadata":{}},{"cell_type":"code","source":"import numpy as np\nimport tensorflow as tf\nfrom tensorflow.keras.layers import Dense, Input, Concatenate, Dropout, BatchNormalization, LeakyReLU\nfrom tensorflow.keras.models import Model\nfrom tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau\n\n# Normalize the data\nX_train = np.array(X_train).astype('float32')\nX_test = np.array(X_test).astype('float32')\n\nmean = X_train.mean(axis=0)\nstd = X_train.std(axis=0)\n\nX_train -= mean\nX_train /= std\nX_test -= mean\nX_test /= std\n\n# Define input layers\ninputs = Input(shape=(12,))\n\n# Wide component (linear model)\nwide_output = Dense(1)(inputs)\n\n# Deep component (neural network)\ndeep_layer1 = Dense(128)(inputs)\ndeep_layer1 = BatchNormalization()(deep_layer1)\ndeep_layer1 = LeakyReLU()(deep_layer1)\ndeep_layer1 = Dropout(0.3)(deep_layer1)\n\ndeep_layer2 = Dense(64)(deep_layer1)\ndeep_layer2 = BatchNormalization()(deep_layer2)\ndeep_layer2 = LeakyReLU()(deep_layer2)\ndeep_layer2 = Dropout(0.3)(deep_layer2)\n\ndeep_layer3 = Dense(32)(deep_layer2)\ndeep_layer3 = BatchNormalization()(deep_layer3)\ndeep_layer3 = LeakyReLU()(deep_layer3)\ndeep_layer3 = Dropout(0.3)(deep_layer3)\n\ndeep_output = Dense(1)(deep_layer3)\n\n# Combine wide and deep components\ncombined = Concatenate()([wide_output, deep_output])\n\n# Final output layer\nfinal_output = Dense(1, activation='sigmoid')(combined)\n\n# Define model\nmodel_wd = Model(inputs=inputs, outputs=final_output)\n\n# Compile model with a lower learning rate and class weighting\noptimizer = tf.keras.optimizers.Adam(learning_rate=0.001)\nmodel_wd.compile(optimizer=optimizer, loss='binary_crossentropy', metrics=['accuracy'])\n\n# Callbacks\nearly_stopping = EarlyStopping(monitor='val_loss', patience=10, restore_best_weights=True)\nreduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=5, min_lr=0.00001)\n\n# Train model\nhistory = model_wd.fit(\n X_train, y_train,\n epochs=50,\n batch_size=32,\n validation_data=(X_test, y_test),\n callbacks=[early_stopping, reduce_lr]\n)\n\n# Plotting the training history\nimport matplotlib.pyplot as plt\n\n# Extract the history dictionary\nhistory_dict = history.history\n\n# Extract accuracy and loss for training and validation sets\ntrain_acc = history_dict['accuracy']\nval_acc = history_dict['val_accuracy']\ntrain_loss = history_dict['loss']\nval_loss = history_dict['val_loss']\n\n# Plotting accuracy\nplt.figure(figsize=(10, 6))\nplt.plot(train_acc, label='Training Accuracy')\nplt.plot(val_acc, label='Validation Accuracy')\nplt.xlabel('Epoch')\nplt.ylabel('Accuracy')\nplt.title('Training vs. Validation Accuracy')\nplt.legend()\nplt.grid(True)\nplt.show()\n\n# Plotting loss\nplt.figure(figsize=(10, 6))\nplt.plot(train_loss, label='Training Loss')\nplt.plot(val_loss, label='Validation Loss')\nplt.xlabel('Epoch')\nplt.ylabel('Loss')\nplt.title('Training vs. Validation Loss')\nplt.legend()\nplt.grid(True)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-22T12:38:08.000159Z","iopub.execute_input":"2024-05-22T12:38:08.000603Z","iopub.status.idle":"2024-05-22T12:38:33.303819Z","shell.execute_reply.started":"2024-05-22T12:38:08.000562Z","shell.execute_reply":"2024-05-22T12:38:33.302541Z"},"trusted":true},"execution_count":26,"outputs":[{"name":"stdout","text":"Epoch 1/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 6ms/step - accuracy: 0.7249 - loss: 0.5691 - val_accuracy: 0.9360 - val_loss: 0.3547 - learning_rate: 0.0010\nEpoch 2/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9137 - loss: 0.2822 - val_accuracy: 0.9670 - val_loss: 0.1513 - learning_rate: 0.0010\nEpoch 3/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - accuracy: 0.9409 - loss: 0.1778 - val_accuracy: 0.9670 - val_loss: 0.1021 - learning_rate: 0.0010\nEpoch 4/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9478 - loss: 0.1414 - val_accuracy: 0.9720 - val_loss: 0.0841 - learning_rate: 0.0010\nEpoch 5/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9511 - loss: 0.1274 - val_accuracy: 0.9710 - val_loss: 0.0867 - learning_rate: 0.0010\nEpoch 6/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9462 - loss: 0.1290 - val_accuracy: 0.9690 - val_loss: 0.0793 - learning_rate: 0.0010\nEpoch 7/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9552 - loss: 0.1181 - val_accuracy: 0.9720 - val_loss: 0.0761 - learning_rate: 0.0010\nEpoch 8/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9555 - loss: 0.1201 - val_accuracy: 0.9710 - val_loss: 0.0752 - learning_rate: 0.0010\nEpoch 9/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9596 - loss: 0.1096 - val_accuracy: 0.9710 - val_loss: 0.0673 - learning_rate: 0.0010\nEpoch 10/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9657 - loss: 0.1043 - val_accuracy: 0.9740 - val_loss: 0.0661 - learning_rate: 0.0010\nEpoch 11/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9609 - loss: 0.1009 - val_accuracy: 0.9770 - val_loss: 0.0659 - learning_rate: 0.0010\nEpoch 12/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9610 - loss: 0.1045 - val_accuracy: 0.9720 - val_loss: 0.0635 - learning_rate: 0.0010\nEpoch 13/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9604 - loss: 0.0993 - val_accuracy: 0.9710 - val_loss: 0.0648 - learning_rate: 0.0010\nEpoch 14/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9676 - loss: 0.0999 - val_accuracy: 0.9710 - val_loss: 0.0618 - learning_rate: 0.0010\nEpoch 15/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9633 - loss: 0.1089 - val_accuracy: 0.9720 - val_loss: 0.0613 - learning_rate: 0.0010\nEpoch 16/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9640 - loss: 0.0956 - val_accuracy: 0.9800 - val_loss: 0.0575 - learning_rate: 0.0010\nEpoch 17/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9679 - loss: 0.0873 - val_accuracy: 0.9730 - val_loss: 0.0626 - learning_rate: 0.0010\nEpoch 18/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9648 - loss: 0.0899 - val_accuracy: 0.9740 - val_loss: 0.0624 - learning_rate: 0.0010\nEpoch 19/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9675 - loss: 0.0975 - val_accuracy: 0.9780 - val_loss: 0.0553 - learning_rate: 0.0010\nEpoch 20/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - accuracy: 0.9698 - loss: 0.0864 - val_accuracy: 0.9740 - val_loss: 0.0583 - learning_rate: 0.0010\nEpoch 21/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9685 - loss: 0.0949 - val_accuracy: 0.9730 - val_loss: 0.0613 - learning_rate: 0.0010\nEpoch 22/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9707 - loss: 0.0921 - val_accuracy: 0.9760 - val_loss: 0.0568 - learning_rate: 0.0010\nEpoch 23/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9645 - loss: 0.0910 - val_accuracy: 0.9760 - val_loss: 0.0563 - learning_rate: 0.0010\nEpoch 24/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9739 - loss: 0.0896 - val_accuracy: 0.9770 - val_loss: 0.0559 - learning_rate: 0.0010\nEpoch 25/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9696 - loss: 0.0836 - val_accuracy: 0.9760 - val_loss: 0.0552 - learning_rate: 2.0000e-04\nEpoch 26/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9770 - loss: 0.0802 - val_accuracy: 0.9780 - val_loss: 0.0538 - learning_rate: 2.0000e-04\nEpoch 27/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9632 - loss: 0.0912 - val_accuracy: 0.9780 - val_loss: 0.0547 - learning_rate: 2.0000e-04\nEpoch 28/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9734 - loss: 0.0827 - val_accuracy: 0.9770 - val_loss: 0.0548 - learning_rate: 2.0000e-04\nEpoch 29/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9718 - loss: 0.0775 - val_accuracy: 0.9760 - val_loss: 0.0548 - learning_rate: 2.0000e-04\nEpoch 30/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9729 - loss: 0.0781 - val_accuracy: 0.9760 - val_loss: 0.0550 - learning_rate: 2.0000e-04\nEpoch 31/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9726 - loss: 0.0843 - val_accuracy: 0.9760 - val_loss: 0.0549 - learning_rate: 2.0000e-04\nEpoch 32/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9744 - loss: 0.0800 - val_accuracy: 0.9770 - val_loss: 0.0533 - learning_rate: 4.0000e-05\nEpoch 33/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9708 - loss: 0.0835 - val_accuracy: 0.9760 - val_loss: 0.0534 - learning_rate: 4.0000e-05\nEpoch 34/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9724 - loss: 0.0856 - val_accuracy: 0.9760 - val_loss: 0.0530 - learning_rate: 4.0000e-05\nEpoch 35/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9635 - loss: 0.1027 - val_accuracy: 0.9770 - val_loss: 0.0530 - learning_rate: 4.0000e-05\nEpoch 36/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - accuracy: 0.9723 - loss: 0.0834 - val_accuracy: 0.9760 - val_loss: 0.0540 - learning_rate: 4.0000e-05\nEpoch 37/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9765 - loss: 0.0675 - val_accuracy: 0.9760 - val_loss: 0.0540 - learning_rate: 4.0000e-05\nEpoch 38/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9756 - loss: 0.0809 - val_accuracy: 0.9760 - val_loss: 0.0544 - learning_rate: 4.0000e-05\nEpoch 39/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9723 - loss: 0.0763 - val_accuracy: 0.9760 - val_loss: 0.0535 - learning_rate: 4.0000e-05\nEpoch 40/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9749 - loss: 0.0772 - val_accuracy: 0.9760 - val_loss: 0.0539 - learning_rate: 1.0000e-05\nEpoch 41/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9720 - loss: 0.0810 - val_accuracy: 0.9760 - val_loss: 0.0534 - learning_rate: 1.0000e-05\nEpoch 42/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9674 - loss: 0.0870 - val_accuracy: 0.9760 - val_loss: 0.0531 - learning_rate: 1.0000e-05\nEpoch 43/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9651 - loss: 0.0818 - val_accuracy: 0.9750 - val_loss: 0.0533 - learning_rate: 1.0000e-05\nEpoch 44/50\n\u001b[1m125/125\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - accuracy: 0.9715 - loss: 0.0752 - val_accuracy: 0.9760 - val_loss: 0.0531 - learning_rate: 1.0000e-05\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"# How prediction can be made using trained TabNet model","metadata":{}},{"cell_type":"code","source":"import joblib\nimport pandas as pd\nfrom sklearn.preprocessing import LabelEncoder\nfrom pytorch_tabnet.tab_model import TabNetClassifier\n\n# Load the frequency encoding for 'ZIP Code'\nzip_code_freq = joblib.load('/kaggle/working/zip_code_freq_encoder.pkl')\n\n# Load the label encoders\nlabel_encoders = joblib.load('/kaggle/working/label_encoders.pkl')\n\ntb_cls = TabNetClassifier()\ntb_cls.load_model('/kaggle/working/best_model.zip')\n\nnew_data = {\n 'Age': [25],\n 'Experience': [1],\n 'Income': [49],\n 'ZIP Code': ['91107'],\n 'Family': [4],\n 'CCAvg': [1.60],\n 'Education': ['1'],\n 'Mortgage': [0],\n 'Securities Account': [False],\n 'CD Account': [False],\n 'Online': [True],\n 'CreditCard': [False]\n}\n\n# Convert new_data to DataFrame\nnew_data = pd.DataFrame(new_data)\n\n# Display the structure of new_data\nprint(\"New DataFrame:\")\nprint(new_data.info())\n\n# Apply the same frequency encoding to 'ZIP Code'\nnew_data['ZIP Code'] = new_data['ZIP Code'].map(zip_code_freq)\n\n# Apply the same label encoding to other columns\ncolumns_to_encode = ['Education', 'CD Account', 'Online', 'CreditCard', 'Securities Account']\nfor col in columns_to_encode:\n le = label_encoders[col]\n new_data[col] = le.transform(new_data[col])\n\n# Convert the DataFrame to numpy array if necessary\nnew_data_np = new_data.to_numpy()\n\n# Make predictions using the loaded model\npredictions = tb_cls.predict(new_data_np)\n\n# If you need probabilities instead of class labels\nprobabilities = tb_cls.predict_proba(new_data_np)\n\nprint(\"Predictions:\")\nprint(predictions)\n\nprint(\"Probabilities:\")\nprint(probabilities)","metadata":{"execution":{"iopub.status.busy":"2024-05-22T13:16:12.939289Z","iopub.execute_input":"2024-05-22T13:16:12.939746Z","iopub.status.idle":"2024-05-22T13:16:13.029696Z","shell.execute_reply.started":"2024-05-22T13:16:12.939712Z","shell.execute_reply":"2024-05-22T13:16:13.028572Z"},"trusted":true},"execution_count":38,"outputs":[{"name":"stdout","text":"New DataFrame:\n\nRangeIndex: 1 entries, 0 to 0\nData columns (total 12 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 Age 1 non-null int64 \n 1 Experience 1 non-null int64 \n 2 Income 1 non-null int64 \n 3 ZIP Code 1 non-null object \n 4 Family 1 non-null int64 \n 5 CCAvg 1 non-null float64\n 6 Education 1 non-null object \n 7 Mortgage 1 non-null int64 \n 8 Securities Account 1 non-null bool \n 9 CD Account 1 non-null bool \n 10 Online 1 non-null bool \n 11 CreditCard 1 non-null bool \ndtypes: bool(4), float64(1), int64(5), object(2)\nmemory usage: 196.0+ bytes\nNone\nPredictions:\n[0]\nProbabilities:\n[[0.99735236 0.00264766]]\n","output_type":"stream"}]}]} \ No newline at end of file diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Model/README.md b/Loan Status Prediction/Bank Loan Approval Prediction/Model/README.md new file mode 100644 index 00000000..0fdac088 --- /dev/null +++ b/Loan Status Prediction/Bank Loan Approval Prediction/Model/README.md @@ -0,0 +1,149 @@ +## **BANK LOAN APPROVAL PREDICTION** + +### 🎯 **Goal** + + The main goal of this project is to come up with Deep Learning multi-layer neural network model for predicting approval for personal bank loans on the basis of customer's information which includes their age, experience, income, geographical information and many more. + +### 🧵 **Dataset** + +The Universal Bank dataset is taken from [Kaggle](https://www.kaggle.com/datasets/vinod00725/svm-classification?select=UniversalBank.csv) and can be found [here](https://github.com/abhisheks008/DL-Simplified/tree/main/Bank%20Loan%20Approval%20Prediction/Dataset). The dataset for this project consists of labeled data. The target column is called 'Personal Loan' which is used to predict whether a customer gets approved for loan or not. + +### 🧾 **Description** + +For training the model, different Deep Learning approches are considered. These are the deep learning algorithms which are considered. + +* Feedforward Neural-Network +* Feedforward Neural Network with k-Fold validation +* TabNet model with k-Fold validation +* Wide & Deep neural network architecture + +### 🧾 Data Preprocessing + +These are the observations which are made on dataset. + +* The minimum value of Experience is -3 and it also contains numeric values which are less than 0 which is not possible. It is observed that this field has 52 negative values. Further it was observed that minimum age and experience diffrence is 23. So wherever the experience was less than 0, it was replaced with their age minus 23. +* ZIP Code was initially represented as a numeric data. But it is a nominal data. Out of 5000 records, there are only 467 unique ZIP codes. Thus this represents that the dataset is restricted to a particular region. So this was converted to appropriate nominal data format. +* Education was also initially represented as a numeric data having 3 unique values {1: Bachelor, 2: Masters, 3: Advanced Degree}. So this is again not a numeric data. It is ordinal data and was converted to appropriate data format. +* Personal Loan (Target Variable) is either 0 or 1. {0: Loan not approved, 1: Loan approved}. So this is binary data, +* Securities Account is binary data representing {0: doesn't have security account, 1: has security account} +* CD Account is binary data representing {0: doesn't have CD Account, 1: has CD Account} +* Online is binary data representing {0: doesn't use online banking, 1: uses online banking} +* Credit Card is binary data representing {0: doesn't have credit card, 1: has credit card} + +All these binary data were initally numeric data, so these were changed to boolean data format. Rest are numeric data. + +### 🚀 **Models Implemented** + +Three deep learning algorithms are implemented which give more than 90% validation accuracy. These models are described as follows: + +#### Feedforward Neural Network with k-Fold validation + +Here we implement a feedforward neural network for binary classification using TensorFlow and Keras. It uses K-Fold Cross-Validation to evaluate the model's performance, ensuring that the results are reliable and generalize well to unseen data. Each fold involves training a new model and applying early stopping to prevent overfitting, with the best epoch's weights restored for evaluation. + +Layers: +* The first dense layer has 64 neurons and uses the ReLU activation function. +* The second dense layer has 32 neurons and also uses the ReLU activation function. +* The output layer has 1 neuron and uses the sigmoid activation function to output a probability for binary classification. + +Compilation: +* The loss function is binary_crossentropy, suitable for binary classification. +* The optimizer is adam, an adaptive learning rate optimizer. +* The metric is accuracy. + +K-Fold Cross-Validation: +* The dataset is split into 5 parts (folds). + +Accuracies over all folds + +| Fold | Fold 1 | Fold 2 | Fold 3 | Fold 4 | Fold 5 | +|----------------------|--------|--------|--------|--------|--------| +| **Best Epoch** | 47 | 45 | 25 | 47 | 45 | +| **Final Validation Loss** | 0.1204 | 0.0833 | 0.1053 | 0.1113 | 0.0882 | +| **Final Validation Accuracy** | 0.9549 | 0.9620 | 0.9660 | 0.9679 | 0.9710 | + +* Overall Average Validation Loss: 0.1017 +* Overall Average Validation Accuracy: 0.964 + +| ![image](https://github.com/theiturhs/DL-Simplified/assets/96874023/9352f641-2a02-4d11-b177-18a9c6b2a2f4) | ![image](https://github.com/theiturhs/DL-Simplified/assets/96874023/92325127-5511-41cb-8237-ec2da884e6f5) | +| ---- | ---- | +| Training vs Validation Accuracy : FNN Model | Training vs Validation Loss : FNN Model | + + +#### TabNet Model + +In this code, we implement a TabNet-based classifier for binary classification using PyTorch. The model's performance is evaluated using K-Fold Cross-Validation, ensuring that the results are reliable and generalize well to unseen data. Each fold involves training a new model and applying early stopping to prevent overfitting, with the best epoch's weights restored for evaluation. + +Components: + +* Model Architecture: TabNet is a deep learning model specifically designed for tabular data, with capabilities for feature selection and interpretability. +* Optimizer: Adam, an adaptive learning rate optimizer. +* Learning Rate Scheduler: Reduces the learning rate by a factor of 0.9 every 10 epochs. +* Evaluation Metrics: Accuracy and logloss are used to evaluate the model's performance. +* K-Fold Cross-Validation: The dataset is split into 5 folds to ensure robust evaluation. Each fold involves training a new model and storing the best validation loss. + +Accuracies over all folds + +| Fold | Fold 1 | Fold 2 | Fold 3 | Fold 4 | Fold 5 | +|------------------------------|--------|--------|--------|--------|--------| +| **Best Epoch** | 35 | 45 | 46 | 41 | 24 | +| **Final Validation LogLoss** | 0.0438 | 0.0623 | 0.0626 | 0.0466 | 0.0651 | +| **Final Validation Accuracy**| 0.980 | 0.985 | 0.978 | 0.972 | 0.982 | + +The parameters that yield better accuracy are selected. + +| ![image](https://github.com/theiturhs/DL-Simplified/assets/96874023/3da4eb3c-07b8-4d6b-85a9-192f8d58d397) | ![image](https://github.com/theiturhs/DL-Simplified/assets/96874023/2957e428-68d7-4208-b435-a68ed23dea38) | +| ---- | ----| +| Training vs Validation Accuracy : TabNet Model | Training vs Validation Loss : TabNet Model | + +#### Wide & Deep neural network architecture + +This implements a Wide & Deep neural network architecture using TensorFlow's Keras API for binary classification tasks. + +Components of the Model: +* Normalization of Data: The input data is normalized using mean and standard deviation calculated from the training data. This step helps in stabilizing the training process and improving convergence. +* Wide Component: The wide component is a linear model that directly connects the input features to the output layer without any non-linear transformations. It is represented by a single Dense layer. +* Deep Component: The deep component is a neural network consisting of multiple layers. Each layer is followed by Batch Normalization, LeakyReLU activation, and Dropout for regularization. It comprises three Dense layers with 128, 64, and 32 units, respectively. +* Combining Wide and Deep Components: The outputs from the wide and deep components are concatenated using the Concatenate layer. This allows the model to learn both low-level and high-level feature representations simultaneously. +* Final Output Layer: The concatenated output is passed through a final Dense layer with a sigmoid activation function, which outputs the predicted probability of the positive class (binary classification). + +Metrics +* Training Accuracy: 0.9715 +* Training Loss: 0.0752 +* val_accuracy: 0.9760 +* val_loss: 0.0531 + +| ![image](https://github.com/theiturhs/DL-Simplified/assets/96874023/39126a2b-c038-4678-a346-936604bc8f1e) | ![image](https://github.com/theiturhs/DL-Simplified/assets/96874023/0d4d3df9-5e95-41f9-9058-0f8f92e77146) | +| ---- | ---- | +| Training vs Validation Accuracy : WDNN Model | Training vs Validation Loss : WDNN Model | + +### 📚 **Libraries Needed** + +* pandas +* numpy +* matplotlib +* seaborn +* tensorflow +* joblib +* pytorch_tabnet +* sklearn + +### 📊 **Exploratory Data Analysis Results** + +| ![Age Distribution](https://github.com/theiturhs/DL-Simplified/assets/96874023/17709677-b86a-4d5a-8595-ac9a419de225) | ![Box Plot of income](https://github.com/theiturhs/DL-Simplified/assets/96874023/64ecfa44-e3be-4f35-9105-9aaed87bd940) | +| --- | --- | +| Distribution of Age | Box Plot of Income | +| ![CCAvg Distribution by Personal Loan](https://github.com/theiturhs/DL-Simplified/assets/96874023/0be9aab1-de5e-4170-a042-8e9620c6db15) | ![Distribution of Education](https://github.com/theiturhs/DL-Simplified/assets/96874023/36bb6796-132f-4c8c-9f1d-52c157222ff3) | +| CCAvg Distribution by Personal Loan | Distribution of Education | + +### 📈 **Performance of the Models based on the Accuracy Scores** + +Summary of model and their accuracy scores + +| Models | ANN | FNN | TabNet Model | WDNN Model | +| --- | --- | --- | --- | --- | +| Accuracy | 0.9820 | 0.9710 | 0.985 | 0.9760 | + +### 📢 **Conclusion** + +Concluding, this project aimed to classifies Bank Loan Approval using Deep Learning models. Among the models developed, the TabNet model achieved the highest validation score of 0.985. Using K-Fold Cross-Validation, it ensured that the results are reliable and generalize well to unseen data. + diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/Model/bank-loan-approval-using-AI.ipynb b/Loan Status Prediction/Bank Loan Approval Prediction/Model/bank-loan-approval-using-AI.ipynb new file mode 100644 index 00000000..2fc9e80b --- /dev/null +++ b/Loan Status Prediction/Bank Loan Approval Prediction/Model/bank-loan-approval-using-AI.ipynb @@ -0,0 +1,1864 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "cathedral-nightlife", + "metadata": {}, + "source": [ + "# Bank Loan Approval Prediction using Artificial Neural Network" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "maritime-marketing", + "metadata": {}, + "source": [ + "In this project, we will build and train a deep neural network model to predict the likelyhood of a liability customer buying personal loans based on customer features." + ] + }, + { + "cell_type": "code", + "execution_count": 340, + "id": "olive-lease", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import seaborn as sns\n", + "\n", + "import tensorflow as tf\n", + "from tensorflow import keras\n", + "from tensorflow.keras.layers import Dense, Activation, Dropout\n", + "from tensorflow.keras.optimizers import Adam\n", + "from tensorflow.keras.metrics import Accuracy\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 341, + "id": "recreational-direction", + "metadata": {}, + "outputs": [], + "source": [ + "bank_df = pd.read_csv(\"UniversalBank.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 342, + "id": "unable-sphere", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
IDAgeExperienceIncomeZIP CodeFamilyCCAvgEducationMortgagePersonal LoanSecurities AccountCD AccountOnlineCreditCard
01251499110741.61001000
124519349008931.51001000
233915119472011.01000000
343591009411212.72000000
45358459133041.02000001
\n", + "
" + ], + "text/plain": [ + " ID Age Experience Income ZIP Code Family CCAvg Education Mortgage \\\n", + "0 1 25 1 49 91107 4 1.6 1 0 \n", + "1 2 45 19 34 90089 3 1.5 1 0 \n", + "2 3 39 15 11 94720 1 1.0 1 0 \n", + "3 4 35 9 100 94112 1 2.7 2 0 \n", + "4 5 35 8 45 91330 4 1.0 2 0 \n", + "\n", + " Personal Loan Securities Account CD Account Online CreditCard \n", + "0 0 1 0 0 0 \n", + "1 0 1 0 0 0 \n", + "2 0 0 0 0 0 \n", + "3 0 0 0 0 0 \n", + "4 0 0 0 0 1 " + ] + }, + "execution_count": 342, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bank_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 343, + "id": "quiet-pittsburgh", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(5000, 14)" + ] + }, + "execution_count": 343, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bank_df.shape" + ] + }, + { + "cell_type": "markdown", + "id": "framed-strain", + "metadata": {}, + "source": [ + "- ID: Customer ID\n", + "- Age: Customer Age\n", + "- Experience: Amount of work experience in years\n", + "- Income: Amount of annual income (in thousands)\n", + "- Zipcode: Zipcode of where customer lives\n", + "- Family: Number of family members\n", + "- CCAvg: Average monthly credit card spendings\n", + "- Education: Education level (1: Bachelor, 2: Master, 3: Advanced Degree)\n", + "- Mortgage: Mortgage of house (in thousands)\n", + "- Securities Account: Boolean of whether customer has a securities account\n", + "- CD Account: Boolean of whether customer has Certificate of Deposit account\n", + "- Online: Boolean of whether customer uses online banking\n", + "- CreditCard: Does the customer use credit card issued by the bank?\n", + "- Personal Loan: This is the target variable (Binary Classification Problem)" + ] + }, + { + "cell_type": "markdown", + "id": "opening-shock", + "metadata": {}, + "source": [ + "## Exploratory Data Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 344, + "id": "separated-arthur", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 5000 entries, 0 to 4999\n", + "Data columns (total 14 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 ID 5000 non-null int64 \n", + " 1 Age 5000 non-null int64 \n", + " 2 Experience 5000 non-null int64 \n", + " 3 Income 5000 non-null int64 \n", + " 4 ZIP Code 5000 non-null int64 \n", + " 5 Family 5000 non-null int64 \n", + " 6 CCAvg 5000 non-null float64\n", + " 7 Education 5000 non-null int64 \n", + " 8 Mortgage 5000 non-null int64 \n", + " 9 Personal Loan 5000 non-null int64 \n", + " 10 Securities Account 5000 non-null int64 \n", + " 11 CD Account 5000 non-null int64 \n", + " 12 Online 5000 non-null int64 \n", + " 13 CreditCard 5000 non-null int64 \n", + "dtypes: float64(1), int64(13)\n", + "memory usage: 547.0 KB\n" + ] + } + ], + "source": [ + "bank_df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 345, + "id": "religious-seeking", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countmeanstdmin25%50%75%max
ID5000.02500.5000001443.5200031.01250.752500.53750.255000.0
Age5000.045.33840011.46316623.035.0045.055.0067.0
Experience5000.020.10460011.467954-3.010.0020.030.0043.0
Income5000.073.77420046.0337298.039.0064.098.00224.0
ZIP Code5000.093152.5030002121.8521979307.091911.0093437.094608.0096651.0
Family5000.02.3964001.1476631.01.002.03.004.0
CCAvg5000.01.9379381.7476590.00.701.52.5010.0
Education5000.01.8810000.8398691.01.002.03.003.0
Mortgage5000.056.498800101.7138020.00.000.0101.00635.0
Personal Loan5000.00.0960000.2946210.00.000.00.001.0
Securities Account5000.00.1044000.3058090.00.000.00.001.0
CD Account5000.00.0604000.2382500.00.000.00.001.0
Online5000.00.5968000.4905890.00.001.01.001.0
CreditCard5000.00.2940000.4556370.00.000.01.001.0
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% \\\n", + "ID 5000.0 2500.500000 1443.520003 1.0 1250.75 \n", + "Age 5000.0 45.338400 11.463166 23.0 35.00 \n", + "Experience 5000.0 20.104600 11.467954 -3.0 10.00 \n", + "Income 5000.0 73.774200 46.033729 8.0 39.00 \n", + "ZIP Code 5000.0 93152.503000 2121.852197 9307.0 91911.00 \n", + "Family 5000.0 2.396400 1.147663 1.0 1.00 \n", + "CCAvg 5000.0 1.937938 1.747659 0.0 0.70 \n", + "Education 5000.0 1.881000 0.839869 1.0 1.00 \n", + "Mortgage 5000.0 56.498800 101.713802 0.0 0.00 \n", + "Personal Loan 5000.0 0.096000 0.294621 0.0 0.00 \n", + "Securities Account 5000.0 0.104400 0.305809 0.0 0.00 \n", + "CD Account 5000.0 0.060400 0.238250 0.0 0.00 \n", + "Online 5000.0 0.596800 0.490589 0.0 0.00 \n", + "CreditCard 5000.0 0.294000 0.455637 0.0 0.00 \n", + "\n", + " 50% 75% max \n", + "ID 2500.5 3750.25 5000.0 \n", + "Age 45.0 55.00 67.0 \n", + "Experience 20.0 30.00 43.0 \n", + "Income 64.0 98.00 224.0 \n", + "ZIP Code 93437.0 94608.00 96651.0 \n", + "Family 2.0 3.00 4.0 \n", + "CCAvg 1.5 2.50 10.0 \n", + "Education 2.0 3.00 3.0 \n", + "Mortgage 0.0 101.00 635.0 \n", + "Personal Loan 0.0 0.00 1.0 \n", + "Securities Account 0.0 0.00 1.0 \n", + "CD Account 0.0 0.00 1.0 \n", + "Online 1.0 1.00 1.0 \n", + "CreditCard 0.0 1.00 1.0 " + ] + }, + "execution_count": 345, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bank_df.describe().transpose()" + ] + }, + { + "cell_type": "code", + "execution_count": 346, + "id": "applied-dayton", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "ID 0\n", + "Age 0\n", + "Experience 0\n", + "Income 0\n", + "ZIP Code 0\n", + "Family 0\n", + "CCAvg 0\n", + "Education 0\n", + "Mortgage 0\n", + "Personal Loan 0\n", + "Securities Account 0\n", + "CD Account 0\n", + "Online 0\n", + "CreditCard 0\n", + "dtype: int64" + ] + }, + "execution_count": 346, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bank_df.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "id": "injured-bumper", + "metadata": {}, + "source": [ + "Great, we have no missing values!" + ] + }, + { + "cell_type": "code", + "execution_count": 347, + "id": "adopted-olympus", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The average age of this dataset is 45.3.\n" + ] + } + ], + "source": [ + "avg_age = bank_df[\"Age\"].mean()\n", + "print (\"The average age of this dataset is {:.1f}.\".format(avg_age))" + ] + }, + { + "cell_type": "code", + "execution_count": 348, + "id": "adjusted-birmingham", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The percentage of customers that own the bank's credit card is 29.40%.\n" + ] + } + ], + "source": [ + "percent_cc = sum(bank_df[\"CreditCard\"] == 1)/len(bank_df)\n", + "print (\"The percentage of customers that own the bank's credit card is {:.2%}.\".format(percent_cc))" + ] + }, + { + "cell_type": "code", + "execution_count": 349, + "id": "fiscal-ghana", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The percentage of customers that took out a personal loan is 9.60%.\n" + ] + } + ], + "source": [ + "percent_loan = sum(bank_df[\"Personal Loan\"] == 1)/len(bank_df)\n", + "print (\"The percentage of customers that took out a personal loan is {:.2%}.\".format(percent_loan))" + ] + }, + { + "cell_type": "markdown", + "id": "distinct-filename", + "metadata": {}, + "source": [ + "## Data Visualization" + ] + }, + { + "cell_type": "code", + "execution_count": 350, + "id": "proprietary-liverpool", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(x=bank_df[\"Personal Loan\"])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 351, + "id": "33e3fe5f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(x=bank_df[\"Education\"])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 352, + "id": "eaf499c5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(x=bank_df[\"CreditCard\"])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 353, + "id": "5bf41e48", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(20,10))\n", + "sns.countplot(x=bank_df[\"Age\"])\n", + "plt.savefig('Age.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 354, + "id": "bright-temperature", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gaura\\AppData\\Local\\Temp\\ipykernel_21132\\2679948862.py:3: UserWarning: \n", + "\n", + "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n", + "\n", + "Please adapt your code to use either `displot` (a figure-level function with\n", + "similar flexibility) or `histplot` (an axes-level function for histograms).\n", + "\n", + "For a guide to updating your code to use the new functions, please see\n", + "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n", + "\n", + " sns.distplot(bank_df[\"Income\"])\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# lets look at the distribution of the income\n", + "plt.figure(figsize=(15,8))\n", + "sns.distplot(bank_df[\"Income\"])\n", + "plt.savefig('Income.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 355, + "id": "annoying-transport", + "metadata": {}, + "outputs": [], + "source": [ + "# lets create 2 dataframes: one with personal loans and one without personal loans\n", + "personal_loans = bank_df[bank_df['Personal Loan'] == 1].copy()\n", + "no_personal_loans = bank_df[bank_df['Personal Loan'] == 0].copy()" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "id": "heard-layer", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countmeanstdmin25%50%75%max
ID480.02390.6500001394.39367410.01166.502342.03566.00004981.0
Age480.045.06666711.59096426.035.0045.055.000065.0
Experience480.019.84375011.5824430.09.0020.030.000041.0
Income480.0144.74583331.58442960.0122.00142.5172.0000203.0
ZIP Code480.093153.2020831759.22375390016.091908.7593407.094705.500096008.0
Family480.02.6125001.1153931.02.003.04.00004.0
CCAvg480.03.9053542.0976810.02.603.85.347510.0
Education480.02.2333330.7533731.02.002.03.00003.0
Mortgage480.0100.845833160.8478620.00.000.0192.5000617.0
Personal Loan480.01.0000000.0000001.01.001.01.00001.0
Securities Account480.00.1250000.3310640.00.000.00.00001.0
CD Account480.00.2916670.4550040.00.000.01.00001.0
Online480.00.6062500.4890900.00.001.01.00001.0
CreditCard480.00.2979170.4578200.00.000.01.00001.0
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% \\\n", + "ID 480.0 2390.650000 1394.393674 10.0 1166.50 \n", + "Age 480.0 45.066667 11.590964 26.0 35.00 \n", + "Experience 480.0 19.843750 11.582443 0.0 9.00 \n", + "Income 480.0 144.745833 31.584429 60.0 122.00 \n", + "ZIP Code 480.0 93153.202083 1759.223753 90016.0 91908.75 \n", + "Family 480.0 2.612500 1.115393 1.0 2.00 \n", + "CCAvg 480.0 3.905354 2.097681 0.0 2.60 \n", + "Education 480.0 2.233333 0.753373 1.0 2.00 \n", + "Mortgage 480.0 100.845833 160.847862 0.0 0.00 \n", + "Personal Loan 480.0 1.000000 0.000000 1.0 1.00 \n", + "Securities Account 480.0 0.125000 0.331064 0.0 0.00 \n", + "CD Account 480.0 0.291667 0.455004 0.0 0.00 \n", + "Online 480.0 0.606250 0.489090 0.0 0.00 \n", + "CreditCard 480.0 0.297917 0.457820 0.0 0.00 \n", + "\n", + " 50% 75% max \n", + "ID 2342.0 3566.0000 4981.0 \n", + "Age 45.0 55.0000 65.0 \n", + "Experience 20.0 30.0000 41.0 \n", + "Income 142.5 172.0000 203.0 \n", + "ZIP Code 93407.0 94705.5000 96008.0 \n", + "Family 3.0 4.0000 4.0 \n", + "CCAvg 3.8 5.3475 10.0 \n", + "Education 2.0 3.0000 3.0 \n", + "Mortgage 0.0 192.5000 617.0 \n", + "Personal Loan 1.0 1.0000 1.0 \n", + "Securities Account 0.0 0.0000 1.0 \n", + "CD Account 0.0 1.0000 1.0 \n", + "Online 1.0 1.0000 1.0 \n", + "CreditCard 0.0 1.0000 1.0 " + ] + }, + "execution_count": 356, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "personal_loans.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 357, + "id": "beneficial-tribute", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countmeanstdmin25%50%75%max
ID4520.02512.1654871448.2993311.01259.752518.53768.255000.0
Age4520.045.36725711.45042723.035.0045.055.0067.0
Experience4520.020.13230111.456672-3.010.0020.030.0043.0
Income4520.066.23738940.5785348.035.0059.084.00224.0
ZIP Code4520.093152.4287612156.9496549307.091911.0093437.094608.0096651.0
Family4520.02.3734511.1487711.01.002.03.004.0
CCAvg4520.01.7290091.5676470.00.601.42.308.8
Education4520.01.8435840.8399751.01.002.03.003.0
Mortgage4520.051.78938192.0389310.00.000.098.00635.0
Personal Loan4520.00.0000000.0000000.00.000.00.000.0
Securities Account4520.00.1022120.3029610.00.000.00.001.0
CD Account4520.00.0358410.1859130.00.000.00.001.0
Online4520.00.5957960.4907920.00.001.01.001.0
CreditCard4520.00.2935840.4554540.00.000.01.001.0
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% \\\n", + "ID 4520.0 2512.165487 1448.299331 1.0 1259.75 \n", + "Age 4520.0 45.367257 11.450427 23.0 35.00 \n", + "Experience 4520.0 20.132301 11.456672 -3.0 10.00 \n", + "Income 4520.0 66.237389 40.578534 8.0 35.00 \n", + "ZIP Code 4520.0 93152.428761 2156.949654 9307.0 91911.00 \n", + "Family 4520.0 2.373451 1.148771 1.0 1.00 \n", + "CCAvg 4520.0 1.729009 1.567647 0.0 0.60 \n", + "Education 4520.0 1.843584 0.839975 1.0 1.00 \n", + "Mortgage 4520.0 51.789381 92.038931 0.0 0.00 \n", + "Personal Loan 4520.0 0.000000 0.000000 0.0 0.00 \n", + "Securities Account 4520.0 0.102212 0.302961 0.0 0.00 \n", + "CD Account 4520.0 0.035841 0.185913 0.0 0.00 \n", + "Online 4520.0 0.595796 0.490792 0.0 0.00 \n", + "CreditCard 4520.0 0.293584 0.455454 0.0 0.00 \n", + "\n", + " 50% 75% max \n", + "ID 2518.5 3768.25 5000.0 \n", + "Age 45.0 55.00 67.0 \n", + "Experience 20.0 30.00 43.0 \n", + "Income 59.0 84.00 224.0 \n", + "ZIP Code 93437.0 94608.00 96651.0 \n", + "Family 2.0 3.00 4.0 \n", + "CCAvg 1.4 2.30 8.8 \n", + "Education 2.0 3.00 3.0 \n", + "Mortgage 0.0 98.00 635.0 \n", + "Personal Loan 0.0 0.00 0.0 \n", + "Securities Account 0.0 0.00 1.0 \n", + "CD Account 0.0 0.00 1.0 \n", + "Online 1.0 1.00 1.0 \n", + "CreditCard 0.0 1.00 1.0 " + ] + }, + "execution_count": 357, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "no_personal_loans.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 358, + "id": "shared-abortion", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gaura\\AppData\\Local\\Temp\\ipykernel_21132\\3634644339.py:2: UserWarning: \n", + "\n", + "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n", + "\n", + "Please adapt your code to use either `displot` (a figure-level function with\n", + "similar flexibility) or `histplot` (an axes-level function for histograms).\n", + "\n", + "For a guide to updating your code to use the new functions, please see\n", + "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n", + "\n", + " sns.distplot(personal_loans[\"Income\"], label='Approved')\n", + "C:\\Users\\gaura\\AppData\\Local\\Temp\\ipykernel_21132\\3634644339.py:3: UserWarning: \n", + "\n", + "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n", + "\n", + "Please adapt your code to use either `displot` (a figure-level function with\n", + "similar flexibility) or `histplot` (an axes-level function for histograms).\n", + "\n", + "For a guide to updating your code to use the new functions, please see\n", + "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n", + "\n", + " sns.distplot(no_personal_loans[\"Income\"], label='Not Approved')\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(15,8))\n", + "sns.distplot(personal_loans[\"Income\"], label='Approved')\n", + "sns.distplot(no_personal_loans[\"Income\"], label='Not Approved')\n", + "plt.legend()\n", + "plt.savefig('Approved_Not_Approved.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 359, + "id": "compressed-brazilian", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "cm = bank_df.corr()\n", + "plt.figure(figsize=(20,20))\n", + "sns.heatmap(cm, annot=True)\n", + "plt.savefig('Heatmap.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 360, + "id": "final-buddy", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gaura\\AppData\\Local\\Temp\\ipykernel_21132\\1815586844.py:3: UserWarning: \n", + "\n", + "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n", + "\n", + "Please adapt your code to use either `displot` (a figure-level function with\n", + "similar flexibility) or `histplot` (an axes-level function for histograms).\n", + "\n", + "For a guide to updating your code to use the new functions, please see\n", + "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n", + "\n", + " sns.distplot(bank_df[\"CCAvg\"])\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# lets look at the distribution of average credit card spending\n", + "plt.figure(figsize=(15,8))\n", + "sns.distplot(bank_df[\"CCAvg\"])\n", + "plt.savefig('Average CC Spending.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 361, + "id": "crude-yemen", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\gaura\\AppData\\Local\\Temp\\ipykernel_21132\\2192030919.py:2: UserWarning: \n", + "\n", + "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n", + "\n", + "Please adapt your code to use either `displot` (a figure-level function with\n", + "similar flexibility) or `histplot` (an axes-level function for histograms).\n", + "\n", + "For a guide to updating your code to use the new functions, please see\n", + "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n", + "\n", + " sns.distplot(personal_loans[\"CCAvg\"])\n", + "C:\\Users\\gaura\\AppData\\Local\\Temp\\ipykernel_21132\\2192030919.py:3: UserWarning: \n", + "\n", + "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n", + "\n", + "Please adapt your code to use either `displot` (a figure-level function with\n", + "similar flexibility) or `histplot` (an axes-level function for histograms).\n", + "\n", + "For a guide to updating your code to use the new functions, please see\n", + "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n", + "\n", + " sns.distplot(no_personal_loans[\"CCAvg\"])\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(15,8))\n", + "sns.distplot(personal_loans[\"CCAvg\"])\n", + "sns.distplot(no_personal_loans[\"CCAvg\"])\n", + "plt.savefig('Personal loans.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "shaped-gospel", + "metadata": {}, + "source": [ + "## Data Preparation" + ] + }, + { + "cell_type": "code", + "execution_count": 362, + "id": "sunrise-mapping", + "metadata": {}, + "outputs": [], + "source": [ + "from tensorflow.keras.utils import to_categorical\n", + "\n", + "X = bank_df.drop(columns=[\"Personal Loan\"])\n", + "y = bank_df[\"Personal Loan\"]\n", + "\n", + "y = to_categorical(y)" + ] + }, + { + "cell_type": "code", + "execution_count": 363, + "id": "floral-saint", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((4500, 13), (500, 13), (4500, 2), (500, 2))" + ] + }, + "execution_count": 363, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1)\n", + "\n", + "sc = StandardScaler()\n", + "X_train = sc.fit_transform(X_train)\n", + "X_test = sc.transform(X_test)\n", + "\n", + "X_train.shape, X_test.shape, y_train.shape, y_test.shape" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "diagnostic-walnut", + "metadata": {}, + "source": [ + "## Building a multi-layer neural network model" + ] + }, + { + "cell_type": "code", + "execution_count": 364, + "id": "official-concern", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"sequential_9\"\n", + "_________________________________________________________________\n", + " Layer (type) Output Shape Param # \n", + "=================================================================\n", + " dense_54 (Dense) (None, 250) 3500 \n", + " \n", + " dropout_45 (Dropout) (None, 250) 0 \n", + " \n", + " dense_55 (Dense) (None, 500) 125500 \n", + " \n", + " dropout_46 (Dropout) (None, 500) 0 \n", + " \n", + " dense_56 (Dense) (None, 500) 250500 \n", + " \n", + " dropout_47 (Dropout) (None, 500) 0 \n", + " \n", + " dense_57 (Dense) (None, 500) 250500 \n", + " \n", + " dropout_48 (Dropout) (None, 500) 0 \n", + " \n", + " dense_58 (Dense) (None, 250) 125250 \n", + " \n", + " dropout_49 (Dropout) (None, 250) 0 \n", + " \n", + " dense_59 (Dense) (None, 2) 502 \n", + " \n", + "=================================================================\n", + "Total params: 755,752\n", + "Trainable params: 755,752\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "# sequential model\n", + "ann_model = keras.Sequential()\n", + "\n", + "# adding dense layer\n", + "ann_model.add(Dense(250, input_dim=13, kernel_initializer='normal', activation='relu'))\n", + "ann_model.add(Dropout(0.3))\n", + "ann_model.add(Dense(500, activation='relu'))\n", + "ann_model.add(Dropout(0.3))\n", + "ann_model.add(Dense(500, activation='relu'))\n", + "ann_model.add(Dropout(0.3))\n", + "ann_model.add(Dense(500, activation='relu'))\n", + "ann_model.add(Dropout(0.4))\n", + "ann_model.add(Dense(250, activation='linear'))\n", + "ann_model.add(Dropout(0.4))\n", + "\n", + "# adding dense layer with softmax activation/output layer\n", + "ann_model.add(Dense(2, activation='softmax'))\n", + "ann_model.summary()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "failing-hawaii", + "metadata": {}, + "source": [ + "## Compilation and training of deep learning model" + ] + }, + { + "cell_type": "code", + "execution_count": 365, + "id": "optional-scotland", + "metadata": {}, + "outputs": [], + "source": [ + "# custom functions for f1, precision and recall\n", + "\n", + "from keras import backend as K\n", + "\n", + "def recall_m(y_true, y_pred):\n", + " true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n", + " possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))\n", + " recall = true_positives / (possible_positives + K.epsilon())\n", + " return recall\n", + "\n", + "def precision_m(y_true, y_pred):\n", + " true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n", + " predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))\n", + " precision = true_positives / (predicted_positives + K.epsilon())\n", + " return precision\n", + "\n", + "def f1_m(y_true, y_pred):\n", + " precision = precision_m(y_true, y_pred)\n", + " recall = recall_m(y_true, y_pred)\n", + " return 2*((precision*recall)/(precision+recall+K.epsilon()))" + ] + }, + { + "cell_type": "code", + "execution_count": 366, + "id": "accredited-spending", + "metadata": {}, + "outputs": [], + "source": [ + "ann_model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=[f1_m]) # metrics=['accuracy']" + ] + }, + { + "cell_type": "code", + "execution_count": 367, + "id": "rolled-inquiry", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/20\n", + "113/113 [==============================] - 2s 9ms/step - loss: 0.1776 - f1_m: 0.9394 - val_loss: 0.1069 - val_f1_m: 0.9677\n", + "Epoch 2/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0999 - f1_m: 0.9676 - val_loss: 0.0757 - val_f1_m: 0.9655\n", + "Epoch 3/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0916 - f1_m: 0.9682 - val_loss: 0.0792 - val_f1_m: 0.9688\n", + "Epoch 4/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0773 - f1_m: 0.9715 - val_loss: 0.0696 - val_f1_m: 0.9752\n", + "Epoch 5/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0745 - f1_m: 0.9765 - val_loss: 0.0701 - val_f1_m: 0.9698\n", + "Epoch 6/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0662 - f1_m: 0.9776 - val_loss: 0.0666 - val_f1_m: 0.9752\n", + "Epoch 7/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0619 - f1_m: 0.9787 - val_loss: 0.0691 - val_f1_m: 0.9720\n", + "Epoch 8/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0612 - f1_m: 0.9795 - val_loss: 0.0791 - val_f1_m: 0.9720\n", + "Epoch 9/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0484 - f1_m: 0.9823 - val_loss: 0.0539 - val_f1_m: 0.9784\n", + "Epoch 10/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0513 - f1_m: 0.9815 - val_loss: 0.0762 - val_f1_m: 0.9752\n", + "Epoch 11/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0566 - f1_m: 0.9829 - val_loss: 0.0640 - val_f1_m: 0.9763\n", + "Epoch 12/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0367 - f1_m: 0.9870 - val_loss: 0.0568 - val_f1_m: 0.9784\n", + "Epoch 13/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0520 - f1_m: 0.9831 - val_loss: 0.0574 - val_f1_m: 0.9752\n", + "Epoch 14/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0431 - f1_m: 0.9876 - val_loss: 0.0606 - val_f1_m: 0.9795\n", + "Epoch 15/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0399 - f1_m: 0.9848 - val_loss: 0.0610 - val_f1_m: 0.9774\n", + "Epoch 16/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0355 - f1_m: 0.9881 - val_loss: 0.0570 - val_f1_m: 0.9763\n", + "Epoch 17/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0401 - f1_m: 0.9862 - val_loss: 0.0791 - val_f1_m: 0.9763\n", + "Epoch 18/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0331 - f1_m: 0.9870 - val_loss: 0.0802 - val_f1_m: 0.9688\n", + "Epoch 19/20\n", + "113/113 [==============================] - 1s 7ms/step - loss: 0.0347 - f1_m: 0.9842 - val_loss: 0.0625 - val_f1_m: 0.9720\n", + "Epoch 20/20\n", + "113/113 [==============================] - 1s 8ms/step - loss: 0.0359 - f1_m: 0.9856 - val_loss: 0.0680 - val_f1_m: 0.9774\n" + ] + } + ], + "source": [ + "history = ann_model.fit(X_train, y_train, epochs=20, validation_split=0.2, verbose=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 368, + "id": "incorporate-fleet", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the model performance across epochs\n", + "plt.figure(figsize=(15,8))\n", + "plt.plot(history.history['loss'])\n", + "plt.plot(history.history['val_loss'])\n", + "plt.title('model Loss')\n", + "plt.ylabel('loss')\n", + "plt.legend(['train_loss','val_loss'], loc = 'upper right')\n", + "plt.savefig('modelloss.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "adapted-royalty", + "metadata": {}, + "source": [ + "## Evaluating model performance" + ] + }, + { + "cell_type": "code", + "execution_count": 369, + "id": "operational-degree", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "16/16 [==============================] - 0s 2ms/step\n" + ] + } + ], + "source": [ + "predictions = ann_model.predict(X_test)\n", + "predict = []\n", + "\n", + "for i in predictions:\n", + " predict.append(np.argmax(i))" + ] + }, + { + "cell_type": "code", + "execution_count": 370, + "id": "injured-central", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "F1 Score: 0.9217.\n", + "Precision: 0.9636.\n", + "Recall: 0.8833.\n", + "Accuracy: 0.9820.\n" + ] + } + ], + "source": [ + "from sklearn import metrics\n", + "y_test = np.argmax(y_test, axis=1)\n", + "\n", + "f1_test = metrics.f1_score(y_test, predict)\n", + "prec = metrics.precision_score(y_test, predict)\n", + "rec = metrics.recall_score(y_test, predict)\n", + "acc = metrics.accuracy_score(y_test, predict)\n", + "\n", + "print (\"F1 Score: {:.4f}.\".format(f1_test))\n", + "print (\"Precision: {:.4f}.\".format(prec))\n", + "print (\"Recall: {:.4f}.\".format(rec))\n", + "print (\"Accuracy: {:.4f}.\".format(acc)) # note this is not a good measure of performance for this project as dataset is unbalanced." + ] + }, + { + "cell_type": "code", + "execution_count": 371, + "id": "incident-pulse", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "conf_mat = metrics.confusion_matrix(y_test, predict)\n", + "plt.figure(figsize=(10,8))\n", + "sns.heatmap(conf_mat, annot=True, cbar=False)\n", + "plt.savefig('conf_matrix.png', facecolor='w', bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 372, + "id": "mature-trademark", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 0.98 1.00 0.99 440\n", + " 1 0.96 0.88 0.92 60\n", + "\n", + " accuracy 0.98 500\n", + " macro avg 0.97 0.94 0.96 500\n", + "weighted avg 0.98 0.98 0.98 500\n", + "\n" + ] + } + ], + "source": [ + "print(metrics.classification_report(y_test, predict))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.8.3" + }, + "vscode": { + "interpreter": { + "hash": "45899fa507a1304a3c6b832619928507c52e1988c6511a7c9c5f49ebe874162e" + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/README.md b/Loan Status Prediction/Bank Loan Approval Prediction/README.md new file mode 100644 index 00000000..a5fdf095 --- /dev/null +++ b/Loan Status Prediction/Bank Loan Approval Prediction/README.md @@ -0,0 +1,16 @@ +## Web Application for Bank Loan Approval Prediction using Flask + +### Goal 🎯 +The main goal is to develop a user-friendly web application that predicts whether the customer's bank loan will be approved or rejected using deep learning models. This application will allow users to enter necessary details and receive predictions. + +The backend of this web application utilizes Tabular Neural Network for Bank Loan Approval prediction. It has been trained on [Universal Bank Dataset](https://www.kaggle.com/datasets/jangedoo/utkface-new) that contains around 5000 data. + +Deep Learning models which are considered for training: + +* Feedforward Neural Network +* Feedforward Neural Network with k-Fold validation +* TabNet model with k-Fold validation +* Wide & Deep neural network architecture + +Amongst this, **TabNet model** is selected which gives 0.985 validation accuracy. + diff --git a/Loan Status Prediction/Bank Loan Approval Prediction/requirements.txt b/Loan Status Prediction/Bank Loan Approval Prediction/requirements.txt new file mode 100644 index 00000000..a60825e6 --- /dev/null +++ b/Loan Status Prediction/Bank Loan Approval Prediction/requirements.txt @@ -0,0 +1,10 @@ +python == 3.9.0 +numpy == 1.22.4 +pandas == 1.4.2 +seaborn == 0.11.2 +matplotlib == 3.5.1 +sklearn==0.2 +tensorflow == 2.8.2 +keras == 2.8.2 +pytorch_tabnet == 4.1.0 +joblib == 1.3.1 \ No newline at end of file