Jurnal Teknik Sipil Unika Soegijapranata : G-SMART (Geoteknik, Struktur, Manajemen Konstruksi, Sumber Daya Air, Transfortasi)
Jurnal G - SMART : Jurnal Teknik Sipil Unika Soegijapranata yang meliputi Geoteknik, Struktur, Manajemen Konstruksi, Sumber Daya Air dan Transportasi.
Articles
6 Documents
Search results for
, issue
"Vol 6, No 1: Juni 2022"
:
6 Documents
clear
<![CDATA[Pengaruh Bahan Tambah Anti Retak Terhadap Kuat Tekan Dan Terjadinya Retak Pada Mortar ]]>
<![CDATA[Abram Arry Purwadana]]>;
<![CDATA[Rendra Willy Saputra]]>;
<![CDATA[Yohanes Yuli Mulyanto]]>;
<![CDATA[David Widianto]]>
<![CDATA[ G-SMART Vol 6, No 1: Juni 2022 ]]>
Publisher : <![CDATA[Universitas Katolik Soegijapranata Semarang ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24167/gsmart.v6i1.3374
<![CDATA[Monplas adalah zat admixture yang berfungsi untuk mencegah retak pada beton, berupa bubuk yang berbeda dengan zat admixture lainnya yang biasanya berupa cairan. Monplas yang ditambahkan dalam campuran mortar atau beton, ternyata dapat mengurangi porositas beton yaitu perbandingan volume pori-pori (volume yang ditempati oleh air) terhadap volume total beton. Penambahan Monplas juga dapat meningkatkan daya rekat antara pasta semen dengan agregat dan mempermudah pengerjaan plesteran pada dinding. Meningkatnya daya rekat antara pasta semen dengan agregat akan meningkatkan kuat tekan beton. Salah satu bahan penyusun mortar adalah pasir. Pasir yang digunakan dalam penelitian kali ini adalah Pasir Ambarawa, yang memiliki kandungan lumpur cukup tinggi. Dengan penambahan zat anti retak (Monplas) ini diharapkan dapat mengurangi pengaruh buruk lumpur terhadap mortar. Pengujian yang dilakukan penelitian ini adalah analisis keretakan plat mortar dengan ukuran 25 cm × 25 cm × 2 cm dan 25 cm × 25 cm × 4 cm, serta uji kuat tekan kubus mortar dengan ukuran 5 cm × 5 cm × 5 cm. Jumlah benda uji dari analisis keretakan plat mortar adalah 16 buah dan jumlah benda uji dari uji kuat tekan kubus mortar adalah 24 buah. Penelitian ini bertujuan untuk mengetahui pengaruh zat anti retak (Monplas) terhadap terjadinya retak pada plat mortar akibat pengeringan dan adanya lumpur dan untuk mengetahui kuat tekan kubus mortar yang maksimal akibat penambahan zat anti retak (Monplas).]]>
<![CDATA[Analisa Debit Puncak Menggunakan Pendekatan Metode Hidrograf Satuan Sintetis (HSS) Snyder dan HEC-HMS (Studi Kasus: DAS Silandak, Kota Semarang) ]]>
<![CDATA[Monika Indriyani]]>;
<![CDATA[Rahma Shafira Amalia]]>;
<![CDATA[Budi Santosa]]>;
<![CDATA[Daniel Hartanto]]>
<![CDATA[ G-SMART Vol 6, No 1: Juni 2022 ]]>
Publisher : <![CDATA[Universitas Katolik Soegijapranata Semarang ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24167/gsmart.v6i1.4031
<![CDATA[Lahan memiliki peran penting pada kehidupan manusia karena dapat digunakan sebagai tempat aktivitas manusia seperti mencari nafkah dan tempat pemukiman. Kebutuhan pengunaan lahan di perkotaan menyebabkan ketersediaan lahan menjadi terbatas. Jika permasalahan ini dibiarkan maka akan terjadi permasalahan penurunan pada Daerah Aliran Sungai (DAS). Salah satunya berada di Kota Semarang yaitu Sungai Silandak.Permasalahan perubahan tata guna lahan menunjukkan perlu diadakannya penelitian analisis debit puncak di Sungai Silandak. Analisis debit puncak dapat menggunakan pendekatan metode Hidrograf Satuan Sintetis (HSS) Snyder, kemudian dilakukan pemodelan menggunakan program HEC-HMS. Penelitian ini juga melakukan prediksi hidrograf DAS Silandak pada Tahun 2045.Perbandingan debit puncak Sungai Silandak metode HSS Snyder dengan program HEC-HMS memiliki hasil selisih debit puncak maksimum sebesar 1,78%. Perubahan penggunaan lahan DAS Silandak dengan asumsi secara linear. Sungai Silandak akan mengalami kenaikan debit yang terjadi pada tahun 2045 sebesar 8,86% sampai 17,22%.]]>
<![CDATA[Studi Pengaruh Variasi Kadar Air Terhadap Immediate Settlement Fondasi Dangkal dengan Model Fondasi Telapak Persegi (Studi Kasus Desa Kalikayen, Kecamatan Ungaran Timur, Kabupaten Semarang) ]]>
<![CDATA[Ramon Yanuar Wibisono]]>;
<![CDATA[Kevin Anggoro Putro]]>;
<![CDATA[Budi Setiadi]]>;
<![CDATA[Yohanes Yuli Mulyanto]]>
<![CDATA[ G-SMART Vol 6, No 1: Juni 2022 ]]>
Publisher : <![CDATA[Universitas Katolik Soegijapranata Semarang ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24167/gsmart.v6i1.3364
<![CDATA[Desa Kalikayen merupakan salah satu desa yang terletak di Kecamatan Ungaran Timur Kabupaten Semarang Provinsi Jawa Tengah. Desa kalikayen memiliki penduduk dengan jumlah 1306 kepala keluarga. Desa kalikayen terdapat kurang lebih 300 rumah tinggal sederhana, atau sekitar 23 persen rumah yang mengalami kerusakan yang diakibatkan oleh karakteristik tanah di desa tersebut. Kegagalan dan kerusakan pada suatu konstruksi dapat dipengaruhi oleh berbagai macam faktor. Sumber kegagalan dalam konstruksi seringkali dipengaruhi oleh faktor alam dan perilaku manusia. Tujuan dilakukannya penilitian ini adalah menguji karakteristik tanah yang terdapat di Desa Kalikayen, dan mengukur penurunan fondasi dangkal pelat setempat akibat memiliki kadar air tanah berbeda. Pengujian yang dilakukan berupa uji analisis saringan dan hidrometer, uji indeks properties, uji atterberg limit, uji analisis sandcone, uji proctor standard, uji direct shear, dan uji dynamic cone penetrometer. Pengujian analisis prosentase butiran tanah dengan uji saringan dan hidrometer pada tanah di Desa Kalikayen digolongkan tanah yang bergradasi buruk dengan didominasi dengan jenis tanah berlanau (silt). Pengujian Atterberg Limit, berdasarkan USCS, hasil pengujian klasifikasi dan karakteristik tanah di Desa Kalikayen digolongkan dalam klasifikasi MH yaitu lanau tak organik dengan potensi plastisitas pengembangannya yang rendah. Pengujian kuat geser tanah di Desa Kalikayen memiliki tekstur lembut dan karakteristiknya dapat dibentuk oleh tekanan jari yang ringan dan tergolong dalam tanah lempung padat. Pengujian DCP mendapatkan hasil jenis tanah dengan tingkat kepadatan yang buruk (poor). Penurunan terjadi tiap penambahan kadar air, dalam penurunan tanahnya tidak terjadi pengembangan tanah dan penurunan yang terjadi dalam skala model termasuk penurunan yang sangat besarKata Kunci: Tanah Ekspansif, Karakteristik Tanah, Daya Dukung Tanah, Kadar Air, Desa Kalikayen]]>
<![CDATA[Kajian Potensi Sedimentasi Pada Waduk Jatibarang Dengan Pemodelan SWAT (Soil and Water Assesment Tool) ]]>
<![CDATA[Han Lois Herlambang]]>;
<![CDATA[Montana Raisya Putri]]>;
<![CDATA[Budi Santosa]]>;
<![CDATA[Djoko Suwarno]]>
<![CDATA[ G-SMART Vol 6, No 1: Juni 2022 ]]>
Publisher : <![CDATA[Universitas Katolik Soegijapranata Semarang ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24167/gsmart.v6i1.3130
<![CDATA[Sedimentasi menjadi salah satu permasalahan dalam pengelolaan waduk. Sedimen yang mengendap pada waduk akan mempengaruhi kapasitas tampungan mati dan umur waduk tersebut. Tujuan dari penelitian yaitu menghitung besaran potensi sedimentasi dan hubungan volume sedimentasi dengan umur perkiraan Waduk Jatibarang. Hasil pemodelan Soil and Water Assesment Tool (SWAT) menunjukan potensi volume sedimentasi dari Mei 2014 sampai Desember 2019 mencapai 1.361.811,915 m3 dan Maret 2034 diprediksi tampungan mati pada Waduk Jatibarang akan penuh. Hubungan volume sedimen (x) dengan umur perkiraan Waduk Jatibarang (y) berdasarkan grafik regresi yaitu y = -0,1215x3 + 81,822x2 + 71490.img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAB4AAAAQ4CAYAAADo08FDAAAgAElEQVR4AeydCXwV1b3HQ/f6nlVb7eIKLS61rdWq4NZKq622Lt20VeuzT3zWBoMCAgIJRMAQwYUICAVBEAIIqCyyCgYIJqyRfScQyL6QELIRIPm9zzkzZ+6Z5d7cm9ybhfzu53OZm5kzZ/md7yzMb/7nRB0+modwfI/mFOBEeQXq6uvBDxWgAlSACoRfgVOnalFQVBqWc3Y4zvvMIzzXT+pIHckAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIANkIJwMRIUjs9ITJ8PvdDBHKkAFqAAV8FTgVO1pZOcW0QgO0wtM4bgOMg/enJEBMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAbIQGthoEkG8NHsAtScqvU0KLiSClABKkAFIqdAfX09ikrKaALTBCYDZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIANkgAyQATJABmwMNNoAzsouwOkzZyLnbjBnKkAFqAAVaFCBktJy20m9tbxdxHrwTTcyQAbIABkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADLcNAow1gMRclP1SAClABKtDyCrTIvMDH8nDkWD4OH82V38yjucjMyjO+5jqxTaY51jIXON5YUHcyQAbIABkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGWiPDDTKABYRZ/xQASpABahA61DgzJmzzRIFbBi+eRBmb6gXTLWPyiPU/ZmeN2lkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAGgmMgZANYPLw/e7audbgerAUVoAJUgApIBSI6FLQV6RvchaXBC3BWHg7LPMOUH+d2CNmQb7CPqCk1JQNkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADLRZBkI2gAuLy2i3UAEqQAWoQCtToLb2dNgvREeOiSGdc5EZgYu8yFPkLcqgGUkNyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADISPgZAN4JMVVa3M9mB1qAAVoAJUQChwNKeAZmoEzGredITvpoNaUksyQAbIABkgA2SADJABMkAGyAAZIANkgAyQATJABshA5BkI2QAWUWb8UAEqQAWoQOtToKColAYwDWAyQAbIABkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSAD7ZyBkA1gzv/b+kwf1ogKUAEqIBQoPn6CF/V2flHnm3ORf3OOGlNjMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAZaOwMhG8C0WagAFaACVKB1KlB6ooIGMA1gMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA+2cARrArdPHYa2oABWgAiErUEYDmDc17fymprW/dcf68c1QMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAaag4FWZQDX19dD/wr3ox71SFv3OVLXrgVQJw2R+vo6LV3IHgl3oAJUgAqckwrQAOaNQ3PcOLAMckYGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAbIABlo3Qy0KgPY6cjU1p7Bjp37MWniGEyaOBrbt+1FbW2tMxn/pgJUgApQAQA0gFv3BZc3ROwfMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAbaKgNRUVEI5dtW29lQvf/6yN/wyKN/D2k0SrGP+DaUdzi3twoDuK7eiOwFzmBrxnZ8PG8+5n6QjA9mTsMHM17F9i13YucXt2N28nDMFus+SMaH8z5GxpYvIPYRHxE5LOKF+aECVIAKtFcFaADz5jGcNwjMizyRATJABsgAGSADZIAMkAEyQAbIABkgA2SADJABMqAYEOav+t3QMpS0DeXVGreHYgK3hPkrNGtRA1gN9yzMmqqqaqxalY4pE1/CptQu2PPFj7Bry7U4uv8yVB3/GqpKv4bswz/Arq3XYM/Wq7FhXRe8924ffLric1RVVUm/x5cfjeD2aoCx3VSgPSvQkgbwxi3b8cQ/u+NPj/4dq1PTg74RaI0Xb9aJN7VkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADJABOwOhmLqhpG2rOgdjAreU+Ss0bTEDWJi1dXViLl+gqLAIs5KnYtKEp5G5+0rgzJdQnPMtFBw7H9mHzkfOoQtweO+FyD18HqpPfh3ZBy4C6jogc+8VeHdCd8yc+R4KCwtlXkaeKqK4PVtBbHu4FdiZdA/uShJR523jUzK/J+56fgFK2kZ1WcswKNCSBvCbSeNwV7d75Hf8pPdoAB+13xy11ZsY1pv9SAbIABkgA2SADJABMkAGyAAZIANkgAyQATJABtovA8LIDeWrWGkPBrBoayATuCXNX1G3FjOAlVFbX38WCxZ8giXz/4Cq8v9G4bELsW3D5Ti44yJs33QptqR3w2fL78ZnS3+NjA2/xK6M72LnpouQl3kxThT+N6pP/DeWLHwQCxcsQn29MJSFsdyUCOAvMM40MZSZcVe3nvgkLwzuTFOzyFuAfo669ZvfmIrl4ZPnDaPG10bz71ZjcBr90Lj2NVVo7/2bywCW5YShn5vNADa5HJfhrVuoa2X7I2xcVx9MwYLtxaFWrdWnb5wBnBsWs1Y3gMVvdaFv2jI8dWtaHdrvzR11Y9+TATJABsgAGSADZIAMkAEyQAbIABkgA2SADJCB9s1AKEaunlb/fa4z5GUCt7T5KzRvYQO4HqWlJzBlUgIKjl6GE4XnYd/272HXlu9i/drHsHvXShw8kIoPZz+Cjz94HIcOfo5dO1chfd3j2Lv1Yhzc9T2cLD4PuVmXYvKkESgrqzAN4EZGAGeMkdFrTiNrZ5JuABvGpDNNczhDJfPH2I1os76hm6SmARwus1cagLpG4VCjBQ1gP+2JvAFsvnzg7JeMMQi9jwEawP45jLQB3LNXH9z/4MM4cPCg30qIbSKNSBuuT+MM4PDcwETGAA5P3c71Gwy2j5yQATJABsgAGSADZIAMkAEyQAbIABkgA2SADJABMhAJBkIxcvW0+u9I1Ku15ambwK3B/BX6tJgBrAyPlZ+mY9GH/4fioxcg+9B3sHPL97H+85EoK61GxclMzJ31IH5/z3fw4G8vwUcfPCTXlZXWIG3dSOzd/l3s2/Y9FB69EAs+ehqrVq5X2TZiGawp2nIGsFejGhctGWxbvUr0WOfHMPVI2TZW+WlPpA1gadh2G4OdYVKp2QzgMNW3ObOJtAH8178/Ll8m8WcCK/NXROCLtOH6hGoAZ4ZxmOJIGcDhrGNruylgfXhTTgbIABkgA2SADJABMkAGyAAZIANkgAyQATJABloXA8K4bOz3XOzLUIxcPa3++1zUxatNwvi9/Ior5LDQXtube12LGcBHjx7Eyk9XYNb0UTi06yfIPnwRDu65AOs/j0N1TT3q66qRsvLfePC3F+HWn3fFzTd0xZ/uvxhrV0Wjvr5GpklPHYJdGZfg2IFvI3PvdUieNhzLly1H1pEjjfBTgo04bV0GcONMPhrAAQFpIQO4cWa+/5Y0jg3/+Z1LWyJtAAuD974HHvY0gXXzV6QRf4frE6oBHM4LTqQM4HDWkXm1rptp9gf7gwyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADLRuBkIxcvW0+u/20sfCAL7s8svxyKN/D9MUiU1jo8UM4MnvvodJEwYic9+PUZJzPrL2fhsbPv81CvILAdTJSN933rodnS77Dh579FH87S9/wQ8vuwgT3r4dlRWHZZrCgnysX9MNuZkXoKbsmzi2/0cYP7YX3p30XqP8FGnABYjANLY75s61DddrDuFrzd/qjOb0mcdGtKcvr8YM8Ssa2bio1OAMYCtvaYh61dXMx2qvkcbelgY0scxWX17G/sZ+el4+Q9ORp60PfF3v7K9xGe48fanFL18d9LmRVR0a1kPPzVHHAFxZe/kZgtzaLn/47ztZP23uXL96edTFaptZB6P9alhvR1ucept82IZFt+UjuLAfC07+79Lq7WyHar9rH0eeIt2B9/8X3WfuA0pS8W7flzEwbgiGDk/A3C9OqGz8LE+hZP827Nm7F4cPH0FuXh5O1pz1kza41V4mcCTNX1ErGsBNuyC2lxsRtpOckAEyQAbIABkgA2SADJABMkAGyAAZIANkgAyQATIQDAOhGLl6Wv13MOW09TT6sM/id2swgVvMAD52NAezZ72DnCPXoiT3Quzb9t/4YtNo1JnT95YUrsWrQ36Gqy69FKPfHIW3Ro3EVZf+AImv/BwlRWulA3P2LLB10xvYs/VbyMv6NvKyOmHWjLdw7FhecA6NK5XP6FKmnysJjDQ2s0skMk0wfT9pZNlMKmPffs/3tM/p2si5fA1DzG6suevrtca/iainNup/D3RzDl4mpWXi6nsHqYm5r9DkE1u3mVrN9630GYBamz10t4xczVSE2W/C2NT7yFFj408/7QlND3s5bhY8SzYMfWGo2+qup/Xfd7IMbT+pl2DNxqAyuTUN1YsEolzL3DXTyf21vvHS21xnHROSEW0fmb+vPDe3efgkaQFKzGY622H1p60d5ssP3Xpiab5PH2kAP/tv9HgrFeVq9ZHleO31N5F6TK1wLmtQuGsjvsg+6dtwphJVTTSARWa6Cfy7PzyA3/3hQRkVHO7IX1XxSBvAG7dsx4R3p+LNt8e5vv/37+dl28QxJn57pRHrVqemh/j2U26I6Xnj1tZvllh/MkwGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAZaBwOhGLl6Wv33ud6Xuvmr2toaTOAWM4BP1Vbjk0XLsTH1LhRkXYStmy7Fgf2rpI+Rn7cGiz9+CI8+fCn+8vDD2LlzG3bt2o6//PFh/P2Pl2LxgoeQl5ci02YeWIH0lMtweM+3sTm9CxbMX4xTp2qUH9KopWX0eZqF3gaw27QSRTtNTONvn8nmq57bFPNt03/pdfPKR0/r/7cyAX1RvSri1TLxLFPQZ9wZ+XkYkIEMU82QNPZ3aOJlKMqEjnQADI3sxqJI6tJeGpDOensb0kadHP8Gao/DhLTMScs49aiPn/Y4SvX9aZrssk9c+nnob+7p1MGfXm4ulZnq0Mysh9Mwd5ajXn5Q7MhyXfX2NU/ur+nl22L8cuXvrz/NiO17x22zsjAM4NnItNaIH2XYNvNNJK3Otq31/VGGrA0bkaP5v75tTf8lTODf/v4B3NXtN9Ig/e3vHwzrsM96DUM1gEOdX/ePj/zNMnnVOcO3NNpn/K3/tp9nnvhn95AM3VDrqC6wXLaOG0T2A/uBDJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMtF0GQjFy9bT673O5/73MX9XeljaBW8wArqk5hXnz5mLrhp/ibO1XsOuLK3Dk8HaUl+/D3Jl345ddz8fDD/wJq1amIDc3Hzm5+Vi5cjX+8LsHcfdt/415s36F8vK9OHJkO3ZnXI66s1/C9s3XY96c2aiubpoBrAwVaUTZoiLFFsOYVGaXkdZrndjiNOv8pQOMyFq3uanq4rlURmEAM81zP1e9vFP5M+pcBp2nYeqvrQ5NTAPYrqeoj7G/bj76MxYNo9NnXrrqZzXPnae1Sf/h2R7TJPXQ2l5ekO3Wy/P3W/WvzXR26Kfta6+HaZh7GrHuPOS+zrb56RtnOU4DWEWJ+3tBwegve4S01gyXoe9ZN3MHkde9943HHvNvawhoPUMAOSvfRNLcHahyrDf+NCOAtx5AWa1ngiatFAawivwV5qiIBBbrIvFpCwbw4089TQP4aNu94VM3L1yyD8kAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyMC5z0AoRq5Iq3/PdT4Cmb+q7S1pAreYAVxYWIrpU0cg98j3AEThwK6LcfDABuze/iaefPQ7+P63L8aoV+/CoYPzcOzoNhzN2oFDB2Yjcegd+P53LsZTj38bu3a8joP7N+DgzotkHvlHL8aMaa8gP/94+LwV04TzGZQeBp9plPki4ewRbz4jzGNfVVNZTogGsNi3Ufu5DUBVDX3pz3jzNgAddQ9WEz9ma+MN4EBtawYDONh260IH/G3U2ceQ//Y5+8WfYe5+McGPuW22xce+UVFnOS4DWCSz6eAz562mWua2e7hre/7+2yvyCo8BbNSqMts3B3BJ5Rmrqk35IYze+x982Ir8NSKB75HrImECh2oAHz4a2vDKYvjm8ZPew5tJ41xf1xDQHmnEfmIYaXXxC24ZWh2Dy/PcvzGjDuxjMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAaaykCoBnBTy2sr+wdj/qq2tJQJ3GIGcOahY5g1/WWcLL4AqItCQfZX8cXmCVj+yTO48ccX46fXXI4VC67De/+5Bu+O74J3x3XBtIk/wrJF1+L6ay7DzT+9CJ8ueQZbN01A0bEOQH0UKo6fj1nT++Lgfn9DvTbGynEaUF4mrtc6r7ICpJOGmIdR5pWNvs6PSacncf92tsmdQqyRRpwzKlSt1yNLZR0cBrBnpLRHOZ77inSGVqFHAAdqmztPjxqZ5qWzPcHqEaCPPQtreKURMetjI9h+acgA1rX1zNMPW3aD1mf2Oo1io2Vmf3Rz62lsN/S6S4tydubvWTdTtnAawFZPVJcgNy8PxytPW6sa80M3f9Wcv2Kd+C1eFhHGcLhN4NAN4PDdAAlzV70EI36rixuX4dOYWlJLMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAaakwEawG7eQjF/VV+1hAncYgZwSclxJE+fhG2bf4GaE19F/pHzsXrl75A89bf4ywMX4mfXXoj77r4E//PoJUieeieSp9yFfzxyCX5393fx02svwiMPXYBZU3+Ltat+h+Lsb+JU+VexM+MGTJ/2DoqLwxgBbA6X7DPLvAy+QKajbh2ZZlcwpqq+W6DfrTUCOMhhpo1IUS9z0NDKp7v/IY2dBqnzb0s+M+pUz9Papv/wY0r7MyLthmWwLOgFBv7tNHLt5al9TbY0Y97QwUNbD2PXs20e6URprvL9pFM1U2a+t0GsDGRfPZ35++1PkzHXHMAz9/mKNn8FHgLalRxnK4txvLwG9e5NQa3xMn/VjpE0gWkAuy/G6gLLJbUhA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMhMaAPqRzML/bg74v9nqpUQFQT3f/v0bt11hNW8wAFmbI2jVbMPP9f6Cy9JvI3P19ZKy/BAs/6o4tG17DzKkPYNzo2zFnxkM4sG8J9uxaiFnvP4R3Rt+OmVP/gE0bRmLBvO7YtvE7OHbwu6gq/SY+mPEoUlI2AI2ybYSB5ouyVGaNNKNs6/0YfH7MxZ1Jep6mSdftHuhmmGFw2dep8n3LLzBOM/fketN4sxuaZhkeJrMvLz9t8CWQvzxNQS8D0CNaV2YQjCayDT7zz1cFox1625xGqErrNghNDWx6+bTX81R52JfussX2oPUIpt32AuVfIn+dC7nSzMu23iN/g1P7cMqKq7u8dLCt89M2P8auLEvf35GuZP4YfJKnNVDW19fH9mPCNPa1Y8yVv3qZQEsjcjfaPAa7taIaNwdwGbKOlGu5nEZlcdMigB957AkZDasif7XM5U/dBBZpw/UJ1QDODONctJGKAA5nHRt7oeR+od0UUi/qRQbIABkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGWhZBlrMAK6vr8f+/Ycx/f3BKC38HkrzLsC+bd/Dtk2/wPZtn+LUqRPIykrDls1LkbElHVs2pSJjyyJkHVkjt+3c/il2bPkFsvZfjMrj30BJ3ncxY9pgHDhwGPWNCtvzGYRqGFO51I0u5dKYBpzcrhutphGm7283G40yxmWYBmw3NVewzxxTRXgtLZPP2s/DMDTNWN+csV45OctX9bAbiLI8vX1mVm6DTpl4Rj62Njekidzu1X63CRu8ASwq6uxPYcS78/RSR6yzzNNu90C1JxQ97HPgeujiUbBX/97lZ+hkvX6CN2EQO/vF0kvnVbDjr0+d6x3GrqqysxzVVmVSO+vmbIO7nfpLEu522MrV2Lcb20aqRhvAGzbii62+OYBzT5xSxTZqGfNibznUc6AhnpUJLNKG6xOqARzOC3CkDOBw1pF5tewNB/Wn/mSADJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMkIHmYaBFDeCammp8smgJZk7vgWOZVyEn8yLs3/5tbF3fGVs2jMeGtJVYuWwiVix9GyuWjsPqz95HxubPsWXDBGxOuxpH9p2PvKPfQkHODzA7uQeWLl6O2tpTEOZy6/woA7h11u7crxX1P/f7uH23sHEGcG5Yhp2IjAEcnrrxhqJ5biioM3UmA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMtA4GWswArqurk05NdXUlVq1ah/ffG4HM3T/B8ZwLcXDHD7Bv2wXYnNYFm9Kexca0/ti8fgC2bIjBFxu6Yu/2C5C559s4UXgeSosuxtzZfbBkySrU1FTJPFXerc8KogHZon3iGIq4RevCwqlABBRonAEcnouRbgCPn/ReWExl3iiEp2+oI3UkA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMtC8GWswAFlG6wqg1gnXrsXr1Jsyf0xO1J7+GUye+iaLsi5Cb+V84tOs87N9xPrZvvBAbUy9C5t4LUHDsApQVXoTqE/+FjZ/fiblzFqC62mf+MgI4As5SW8pSDF3sZzhjNZxzW2oO60oFglWgJQ3g1anpePypp/HHR/6GjVu20wAO4/zKvDFrXzdm7G/2NxkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADTWWgxQxgZWioaN3i4uOY8u5IrFx6Jz5P+R02b7gDRdnfQ1XpV1Fe9HWcLDoPVWVfR2nht7Bjyy1Y+FEMPpk/FG+PfhHLli4FIAzls614+GfRYkYAq36P7NLQWZ+LWc2TG9lymTsVaFkFWtIAburFiPvzhoYMkAEyQAbIABkgA2SADJABMkAGyAAZIANkgAyQATJABshAeBhocQNY2SWnTtVg+vSp+Gjux1iTshEfzVuAOTN7Yd/OO7Bzyx3Y/UUX5GXdgE+XPoYZ06di44ZtOLDvCNatXY/t27erbLikAlSACrRbBWgAh+fCyBsM6kgGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA22ZgRY3gNVwzWfPnsXxkhLUnqoB6s/IIZ3T0rbgP++MxbsT38XECeMxYdzr+HDuIhQWFAE4K2J+ZeRvvWn3iOGkVX7t1gFiw6kAFWi3CtAA5g1JW74hYd3JLxkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZCA8DLS4AdxunRo2nApQASoQZgVoAIfnwsgbDOpIBsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIANtmQEawGE2YJgdFaACVKClFKABzBuStnxDwrqTXzJABsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyEB4GAjJAD5yLL+lfA2WSwWoABWgAg0oUFZeAV4cw3NxpI7UkQyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAG2ioDIRnA2bli7l1+qAAVoAJUoDUqUFFZTQP4KG9I2uoNCetNdskAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIAPhYSAkA7iwuLQ1eh6sExWgAlSACgCorT1NA5gGMBkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMkIF2zkBIBnD5yUqaLFSAClABKtCKFcjKLgjrhV0M/Z95NDeseYo3uCKRJ98MC8+bYdSROpIBMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEyQAbaNgMhGcCnz5xpxbYHq0YFqAAVoAJFJWVhN2uPiDelssJ3scvMyoXMs52/gcUbqPAxRS2pJRkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZMDHQNAGcH7RcTorVIAKUAEq0MoVOBXxYaCbEg3clH19Fy5exKkFGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIANkgAyQAf8MBGUAiyFAz5w928ptD1aPClABKkAFhALFx0+EPQrYdSE9lgcRySsjg9VSRfSKaGG1TkYO50e+PqpsLqk1GSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIANkgAy0cwaCMoArq2roqlABKkAFqEAbUaC+vh45+cW8wLfzC7zLtKcePCbIABkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSAD7YKBBg3gEycr24jlwWpSASpABaiAUuDs2Tpk5xW1iwsZjU7/w3xQG2pDBsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZaH8M+DWAs7LzUV19SnkJXFIBKkAFqEAbU6Curg55BSU0gflGGxkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMkIF2xICnAZxfdBxnznDO3zbm9bC6VIAKUAFPBU5WVOFYTiEv7u3o4s43+trfG33sc/Y5GSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIAOKgaisY/lymFBh+paeOImamlpPA4ErqQAVoAJUoG0rUFVdg8LiMuTkFeHIsXwawjSEyQAZIANkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADJyDDES1bTuDtacCVIAKUAEqQAWoABWgAlSAClABKkAFqAAVoAJUgApQASpABagAFaACVIAKUAGlAA1gpQSXVIAKUAEqQAWoABWgAlSAClABKkAFqAAVoAJUgApQASpABagAFaACVIAKUIE2rgAN4Dbegaw+FaACVIAKUAEqQAWoABWgAlSAClABKkAFqAAVoAJUgApQASpABagAFaACVEApQANYKXpc2TQAACAASURBVMElFaACVIAKUAEqQAWoABWgAlSAClABKkAFqAAVoAJUgApQASpABagAFaACVKCNK0ADuI13IKtPBagAFaACVIAKUAEqQAWoABWgAlSAClABKkAFqAAVoAJUgApQASpABagAFVAK0ABWSnBJBagAFaACVIAKUAEqQAWoABWgAlSAClABKkAFqAAVoAJUgApQASpABagAFWjjCtAAbuMdyOoDdXX1qD19BjWnalFVXYOKqmqUV1TySw3IABkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZCAgA+J5sniuLJ4vi+fM4nkzP1TgXFbgxPp0HBkxDNsfvh/pna/gt5k0EHpnJQ5H+aYNzYIXDeBmkZmFhFuBs2fPorrmFE5WVgW8eNMIphFOBsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIAOhMCCeO4vnz+I5ND9U4FxR4PiKZdj2kM/03fbAvch++y2UrfkMFRmbUX1gH2oL8nGm9Di/TdRA6Cj0rMjYJPU99tZIbL3/N5bZvv3PD0D0RyQ/NIAjqS7zDrsCdfX18m2sUC7WTMubOzJABsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZaAwDVTU1EM+l+aECbVWB00WF2PWPv0nzccNPr8aR4UNQue0LmrxNNHkbY5QLo/3wK7HYcP2PZH/sfuoxnC4siAhaNIAjIiszDbcC9fX1qDl1itG+HK6l9TFwkjfOjblx5j7khgyQATJABsgAGSADZIAMkAEyQAbIABkgA+2UgTb6PE08nxbPqfmhAm1JgbLPVmLTL34izcZDL7+EmsxDNH5bwPh1msXVmQdxsH9v2S+bbr0BZatTwo4VDeCwS8oMw62AuKZWVnNeX94Qt9MbYpr+rc/0Z5+wT8gAGSADZIAMkAEyQAbIABkgA2SADJABMtAuGRDPqflp3wroLwGcPnsWO4sKMHVHBv6xaA5+OXMSLn/nNXz9jSFyKf4W68V2ke702TOWeHo+1sow/8j9zzvSYNz2h9+iavdOGr+twPh1GsFVO7dj6x/ukf2UN3VyWAmgARxWOZlZuBUQQ2twnl8anzS/yQAZIANkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA62BgYqqag4JHW4joA3mN3P3NvxxfjIuTBqOqNGvIOqNIYh6PQ5Ro+IQNTLWWIq/xfrRr8h0f5w/E7N2b2+W1mYOHihNxT3P/i9q8/No/rZC81eZwbV5udjd/UnZX0eGDg4bHzSAwyYlMwq3AmfP1uFkJW9qWsNNDetADskAGSADZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIAMGA+K59dm6unA/Emd+rVQBPVp38aG9uDN5IqJGxSLq7WGIGjkIXxk1GF8aFSe/HUbGQn3VOrFdpJPpR8Xh7lnvYsXh/VZr9fytlU34kT12tDQTsxKG0vhtxcavMoDVUszNnN75CmSPS2pC7/t2pQHs04K/WpkCFZVV7XIYEd5E8UaaDJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMkAEy0LoZEJHA/LQfBWrPnsXLa5ajw+uDEfVmvDR7v2KaviLiV5m+MvpXRAA71gkz2Er/Zjw6jIrDy6uXI9wvEhz/dLk0EQ/0ep7mbxsyf5UJfKDPC7L/SlNWNfngogHcZAmZQSQUqKquofnLeUTIABkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGSADZKDVMiCeYzfHp/7UKdi+tervGrketr/FOt8Xzn3F31Z6I5/maENbLKPOjPIurKrAo/NnIWr0UGn0fnlUnFxKk1f7rZu/+m9pDptDQ4vf1v6jX8H/LJqD0poqKU9TI4Erd+/E+p90xs5H/4TTxUU0gNugASz6beff/4wNP7sGVfv2NumwoQHcJPm4cyQUqD19ptVe0PnWXet+6y4c/fPu5PcgvuHIi3mc+7ywj9nHZIAMkAEyQAbIABkgA2SADJABMkAGyAAZaN8MiOfZkfwI47fwvp+jqNt1KBDfX12LgruvQ/7dxu/8u6+Vv31/m9tEml+Jbca3QCx/dR3EUuwv8hJ5irxFGS39OXr0GOYvXAyxbC0fYQCLCN3HF81B1JhX8bU3hviMX0eEr274ev1WEcJiKbaLpcgvasxwPLl4riynKQZwfV0dvvjNXdjyy644dewozd82aP6qKGDRf1t+1RVb7/9Nkw6FFjeA9+7zjXPepJa04M7lJ0+2YOmNL7qqqgp79x2QX/G7oU8waRrKI5jtnPe3fd8wtfQNMw1g8tfSDLJ8MkgGyAAZIANkgAyQATJABsgAGSADZIAMkIHwMfB5ejrEN1KaiufZkfwIc7bgV9eg+PZOKLitIwq7XoXC2zqi4PZOKDTX5Xe9EgW3dULhHT9CwZ1Xo+COq1F4549kmvzbrkJB1yt9+5h5iLxknr+6psUN4NTP0/HPZ/5tfcXfLf1RZuwr61YhavQr0qz9kmbeRr02CPIr1qnf+tK5XvtbmcAiP2kCj34F8anGkL+q3FDbX/jBTGvoYGUkcnm8RYzw6j07Ib5N0f/4yhWyP4s+mhcqClb6FjWAJ02ZJg9osWyrn63bduDTVSnYtbtpodjN1f7i4hLMnD0XL/WPtU6m6sQq1oltIo3zI064Hy/4xLk67H/X1NZG7EIcqQs88w3fzVhr0JIG8LnVn62BKdaBTJEBMkAGyAAZIANkgAyQATJABsgAGSADZKDlGEgYMRIjEl+L6HNn8Vw7Uh9pAItI3ds7If/2Tsi7raOxvP2H8nfebZ2Qf9c1yLuzE/K7/AB5v7hYfvNv/T7y7rgKeb+8Gvl3Xo282zsh97aO5v5GHtJA7nZdixvA/47pZfMrhFfRkh9lwn58YJec81fM32szf00j2CvS11onzOAA6XQTWOQv5hYW5YmPKj9YDepqa7H59pux68m/Ncl0bIphyX0Nsznv5Rex/8ar5TdvQK8m9ceux/+KzXfcAtG/jfm0mAGszF9hPibPntOYureKffbtPyAN4LZgAgudldnb0FIMtaA+6u2bSBvAYjiF5rgRyi8sapZymqMtLCP8N440gMOvKTmlpmSADJABMkAGyAAZIANkgAyQATJABsgAGSADLcHA4axj6P7Ms/IrfkeyDqGadur5e0NL3QAWBm7+bR2R2/Uq5HS9CnldO8pv7i0/QO7Pv4Pcn16A3J+dj9wbxPdbyL3h28i96XvIveVS5Ha5Evldr5L7ijzEt7UYwF5+RUO6RHK76MvK07X42ZS30eGteHzl9cFyyGZl2qqI3w6vDYLx9YgCVhG/iQONffXoYNMcFvmJr8z/rXhZXoWYn7m+PqTm5YwfK6NFyzdtaJLhSBO3aRHDlZvWW+avMoGbEglctna17NfcdyeExINK3CIGsG7+tuXoXyXizt17Wr0JnDR2vGX+9uk/CMs/XWUbS1+Mqy/WiW3qZPvulPehzF+xLtIGcHNE/4qL/OikMRG90EfyJoJ5R/5GuekGcBbmdL8J19w/ButKIl/flmYiM/kpdOzUGbFpLdfWorQxuO/am/D03Czt2E5HbKfO6BgXueF9mkv7zLnP4mfXPoDRace19gXQ+8gsPNGpM55I1vUIkL5CbDuMJcN7Ibr/VGwqbSht47anj4tBdI/xSJflNS6P5tF8I8b2iEH0uI3B6d3q29OatW5jddswHtE9YjB2Qxurd6MZPYyF8TGIjl+Mg43Oo3FalWyZin49emHYssPt+jhskg4mr0MWNZ+GBxcNRXSPoViY2bh+b55zPOtGnckAGSADZIAMkAEy0N4YmDZ9hmUAi9+RbH+kooB1AzjvdmH4XoW8LsLIvRIi+jf35u8j58ffQM4tVyDvj/cg/+m/y2/eX+9H7p0/Rs715yPnJ99E3s0/kOnzTCM4XwwZLYaQbuYIYOE5iAA0/as8CX2pbxe/16WtV5ZMsyzHbUlH1BtDLPNXRvMmDjSiel8biKjXBqJDQn985dX+iHq1H6LENqfJK/4W64f3w1df7Y8OCS8bf6t8zKUwgb88Kk6WN+GLjSG374tf34FtD97Xhs3f/dj15BVIj1vdhttwHOE2gIUhv+3392Drvb8KmQmxQ7MbwOea+atUb80msK55Q9HWYp5fYfTqJ1r1O9IGcEVlVUQvwOLiPmHiJHnBX7kqJcJlrcdb5ptlQ5fnBSjLTDdwAQ4088PVSN7stOW8aQCH9h8hGsCh6dWYYyNiBnDecgzrEYNhy/JpANvOvy1hAGdgcp8Y9J6SEeB6EXnWGsNnc+2TsywB0T0SsCSvBXVodQZwpLlp2wawnZky7Fw5CSPiB6CneMFDfF8YgGFT0pDleuklH3tXz8CI+L5W2p6xIzFtXXazH58tawCHfi4MrwEcSp85zwtlyFo9Hv0CvHSUs205xg7XeRiMEe978WDkbaRXTPRC7+FTkXq0rNmZaK5zLstxMsW/yQQZIANkgAyQgbbKgBgJ8vmYFywDWPyO5OiQ4vl2JD66ASxMW2HgShP4zs7I/fklyLnxEhT+319xYtY0VKenoXrrVuObno6KTz7G8cRY5P/l18jt2hE5t14u9xWRwPm3N38EsO5VKN8hlGVzBRSW1VTj1vffQYfRQ/GVUYOl6Sujf83I3ajEQfh64gC88vlnWHBgD7ovnoeoV3obw0RrRrDcZ+hLeOmzJVh4cC/6pCw1zGKVj4ggNoeJ/ooYBjppKO6Y8R+Un6oJGqXTxUUySvToyIQwmaersbXzFdg4fb+f/IztW9c2LVrWHm18bhjAok22IaBfftGPhsFrl5U4TPbv6ZLioJlQCZvVANYP7uY6UFVDm2PZGk1gPYJXRPgG+9H7Sp2AI2kA19XVR/wByu69+62Lfd9+L0f0Yl9e4TOAuz/zJlYW+btRDJcBXIaM+W8iLmYSPrcZGf7K5Xp/N65NN4Dbl7atwQD27stzJwLYu30BOAsyAnjvzMGI7jEGqS7zI0DeTTi/MALYv64l68YgusdgJO/3nyZkDprQV81TVhm2LhqDYX2mBhEVfgDJsTGITkpDScTbdRipE0diUKJH1GsrM4Ajz03LGcDeDDaFmcNYkpiA0RNnY8m6NKSuW47kpKGGwTvc0deZizHkhQEYMc5Mu2wGRvQ3TOMRK8ULM+E+TkNpVwhlNzkCuKUN4BD6zOqTMkijNr6XYfL7M4C3TJV93zN+DKYtWit5mJZomsFOHioqcXCReAElBj3jx2Ph6jSkLJpkMpHAaGdL+xDY5D4ROI9Q//Cfm6kpNSUDZIAMnCsMiCAgMfzz4MHx8it+RzowSDznDvdHN4DzbrvKiPrt2gm5t34fOT//Dgoe/z0qU1OhihY1UF9Rl9rjZSibkYz8B7og5/r/Qq6YS/iOH8rhoAtv64iCu5tvDmDlNTRlGW59vfJbn3MUX3vrFRmV2+E1Y5hmGQGsfo8YiP8aMQDrjmXJ3XcU5eP8kYPQYcQAI0JYDvschw6v9sPlScOQffKETDf/wB5EDeuLDioC2DSChQks5hgWcwF//Y14fFGQ61Utz3UFs2dKg/BE+romm42GKdu2DODMuNYXOSyGfW7K0M+6OX7i81TZv4VzZ3v2f6CVzWYA64biuWj+KpFbmwmshnQWQ0AH+9FNY/1EHEkD+FTt6Yj/RzhhxEjLABYX+zlzP4xgmYax+6+BsXjpmWfRIykVBZ4PO8JlAGfio4FiLou3aQB76hz8jTsN4OC1Ev8ZoAEcml7N8h+ooAzgSEcOunWhAezWxOAhH0uGxyB6+HLkNPH81Sx8ha2Oprnoz6DRy9kyFb179MXkLf40DOd60/TyGva4VRnAzcFNazOAw8/MwbliyOIYjF6nRXKW5iPH+WJMURrG9onUcNghtEs/Lhr63eYNYO/j2rPPhBZHV2HEC4ZR3zP+LdOg9TPtwJZ5mLzFbeZ75r1/Ngb1iEHvcRvt9/KlezBNvJjida5oqG+4PYL/B/Pmpm1dH9kG9hcZIANkgAyQgXAyIIxfZfpaZvCQVyJ6PyKec4f7oxvAYu7fvNt/iLzbfojs676C3HuuQ3nydNTV1KKuthanMg+ictVSVK5egVOHDuDsyZM4U1OLk0sWo+CPXZFz7VeNYaBvNw1gNQR0zalwV9szP91vaOxvz4zDvHLkhlREjTYNYDNC1zCAB1kG7zdHDMDSzP04ffYsas+exV/mvY+o+BeNoZxfG2Qsh7yI55Z9JGsn0szcvQ1Rw/vKeYNt+cn5go25gEW5b23+POgWZcYPwuauN4XJ/BWRqTSAdQO2NfzefNsvcHhoXNBMqITNYgC3F/NXidpaTGAxr686iRYXl6jqBVz6M39FPpE0gKtrTkX0wvt5errN/BUXfjHkh5gTOJw3Fb68TGM3KQUbxvVE92d6Yuwm7eGi9eCHBrBPs9Zxg0sDOLR+oAEcml7NwnsQBnDkIwfdutAAdmsieTDNBZsBZV0j/OxzTmwP1vQqQ2pSDKJjZ2Nvs7S7jRjAzcJNWzWAQ2BGRPv2iEHD8+SaWvSZiq1h5zDYYyHE88E5agCX++uzzMUYETsGyRuyUVLRSE2PLpZTI/SessP6/8HOmQP8zmtcsro9jt4QIodhP15YfrPcS7LfrHMA9eYxRwbIABloGwyIIZ0ztm6T35WfpWDuvA/l9z8T35XPg9Wwz/pw0GKbSif2UfuHY3ho8Zw73B/dAM67rSPyhQF8+49w7EcdUPD4b1C9fTvq64HTBcU4/mpf5P7kfOR1uQSFjz+AsokTcHLRQhT986/IvekHyL31UjkUtBhKOv+2jmAEsHdv/W7Oe+jwxhAZkdthZJxh+upGcOIgfCPhZaQcPYx9JUUorKzAjF3b8KVXevvM3cSB+Mar/bDyyCEcOF6MY+Un8OG+XYga9pIxVLSe30gjylhEAItyfzvnPe+Keazd91x37P6fx2gAlwY/rHJrMHVDqcPuJ/+OfT3+z6P3A6+KuAHc3sxfJXdrMIGFYSuM27j44apaAZeBzN9IG8CV1dUR/U9W33795QVfvPUlIoHV32JO4MjczCkDeD3Ki9bjrZhn0T1mEjJc/5kOZACX4cjaqRg6sCf+Zc4n/K+YWIyavhlHtHwOzI91mdvC4O6etL7Bth3ZNAOj9Px7xWPCJuecxXnIWPw24mKizXKi8dLrC5CR630TmL11Cd4a0seqc/fn+iBu1n6zLpouWhuMPvDapq0r2oWPEvvIOsTN14370OrXUH833QDOwvQnO6Njp3isc7UxC6smPI9Hfn0TOnYSaW5Ct0cHYHJalquvDGP1KUw/4tbZa5u+LjNlDB65oTM6Xptg1CEtXpYXm1aJoh0fIvbJrrhGlH9tVzzUfxa2lbjLKD+yBu9EP4ZuIh+R9oZ78XTSGmQ62hSUARzIkPTcpg3fXLITc+Kews3Xinpcj5sfHoDpO47b9TLb90SyrqOWh1bnoh1T8cS1nXHNw2Ow0Wp3PjbOjcfT95u6+CtHy0fnKHvzh4jt/oBZx8645pY/o2/yThR5pvco6/5nMX2fRx+Y+/vXOB8bkwf4eLrhz3huwhpk7puFJzp1hl0PPX+vyEGvh+XmOhndlI3U90ein4qu6pOAyX7mwyw5mobJ2ryKYsjMJbuL4d8AzsfWZeMxrI8asrMXBiUtxlZtrteclSNllJ7bpNkh584V5uBOT70rUa5FbRp10+dwNOqm92d5hTbsadEeLBmXgN6q3bFjsHB3sZ0/PX1pNlKnaOn7JGDssj32qDFHPTdN6YvoPlOxybG+vCJfDpE8yCxbzFc6YmYGcvyYH1lbZmO0Pmdp/wR7hJumQ86W2RjR39T7haGYpiLhjqbBGga1Ry/0S1qMnR5TGAgdpyUOtXSJfqGvMZeqow36fKBZ66ZiiGzLJHy6yIi6lPOwqvlYxXLcRoe2lSi3zVWtcSy0fn8khmjcGHNyamnk0K2irKGew7Tq9RMMGIya88Nq9bK40zQs2C3mD/WxJJj10qq8ogxZ6xzzyfYZitEzM5Dl0MvJ3sI3hPEUg2GL3HPPenNTjL2rp2KY6tsevdA7fiSWWEOLa2wHKtvapp8DnDya86VaaQ3dfZqWYe/K8Wafx6Bn/zFYst94EU5qZw3R2wtDxDy8jnzUcau0N/J1901IzDjLEH/7OZ7s54RKlJduNCKAHcOQR/xYCGTieh0D8ZOQqs6dfvc1mYz1nXO957MNwEveDixM8p0DevY35kj29b/9OHTp6dUXwa4Lqs+8rmlB1Kl0LUaLY3+ibz52/9cuHz+RGRo8iPoGqxnTua8t1ISakAEyQAbIABk4JxgQZu1bo9/2fi5qPksVz0j157/it3xuqm13/i3SNMUIFs+5w/2xGcAyAvhHyLu9E3I6RaHo6d+j5uABnD17FqdLy1A2/g1k/+IqHLvsazj2/Sjk/vxbyP/tdci9+TLk3nSpHP5ZRhGLOYBpAPvtqmsmvYmoUXHSqFVz9KohoOUycSC+nvAyUo8dwaojBxG/bhWqz5xGx3GJiBreD2I+36hhfXDTlLdxtq4OL65aLI3i+ft3G0NAa3MAy/yUASxM4VFx+MnkJL91c27Y8cffY3/Pf7eoAWwNw3xwJjZ2vkIOWZwulk/ORIGHMVsw/SlfGjnf8GrsetI5lLM5L7C//Na+bstDltf5dWRq5cl6afuHd95ib8O5ctN65A3oJb/idyhGr7+0+3s8ix1/ftDZ9Q3+HVEDWMw5qyJQm7oMZf7aBlsdZIJ9+w/g01UpYfmKaNzm/ohhn4XuybPnNHfRIZd3srIqYjceYqhndSHfsnWbLMdrXVgfTqk5gE0TtmDt2+jxzLN4afouRzv9GcB5WP26iBx+Fv8a+DY++iwVqz9bgLHDDAO0+5AFOGDerJYc2ozVa5fgrV5iCOhXMXltKlaL706nkWt/kHRgvjEEyovDxhv5LxZmcDQGzM/U6liMz5NEPaIxIGkBVq5NxaLpb2LAc8LQfhuf24yBYmyYaBjt/+r1KiYvFvVIwUdT3sSAiZvNPDVD13Wz7bVNrUvBytdF+4yvr46h1M/efn/9HTEDOHcN+v7aMF2fiJuFpSlrsDQ5Ac/df700Np9IPqDproZWboQBvGwqHpLmsmZCKwM4eRaeuOUx9J3yIValfIh3oh+QRvA10Z8g29Yfhnl6zf3PY2jyCqxKWYHpcX+WabsNT7cZm/7NSU1vT5PX3O65TZm3szD9ya54pP9UzElZgzkTnsd9wgi+9nnM119ACNYAFsao2P/X8Vhnmb9K65usclbNnYinZV89hTkeBryNHbP+PxNG/tw1hq7d7zX6dK5uSFeivCQDox8W/X0THoqeKNu0atksvNP/KYxO0/Sy9YWqX2cIA99X9gHM6S5eJLge95l5KZ66PfkU7gtkAHtGDno9LFfmzwwsHDcA/RInmXMfKlOnLyZv0+tUiYINk9BPPDx/YSjGmvMqGvNsJmBYvDBvnMNxCmO4L6J79MKQcYuRsi4NS2aOMUyjPuORbp1jDuMDsb9Ypw3NapgN7nr4dNIM4LmLMewFj3J69MWELfoIDcr0mIeFw3uhX+IMOWfoEmGAS1PQOeejPb2aIzJ1mTBkDYOl98QM77lrS9Ok2TBopv34LxfRa2JY6B4xmu7GnJO9hyfIeihjTLRVzU+p+kiVradRhtroiZPQT5g1y8Q8lqovByN5izHE7SDZD2uxcJyYIzoG0YmrHENTm+3tPxITZB/70jrbqcygD1YbQ6gahu94rMvMkHNujpXzqgrjSMzJmobU3e4hWf3NVW2YMgMwYqLBjWiLGKY1us8kbHIxEpwBnLNb1GMGRoh8+o8354pNw6ZMkw9lAEuWBmDE+8utuUNl21xzh+YjNUnw7Zs7NHX1YkxINIzdaFd6xdJapIioZ8mbR3SqJzdl2DTRPJaSjLlr1TylYzeo41Tl72G06y8yWOcg/RzQF9LkW5aGQG1QfT52YoI1X6rv2BmDlG0iwrIvhinthhv66BGX8vh1mJclYWDGdl4w21gQVASnOk/5OfYjeSw4dLDakLkKr4shqbVzpzjuxyaOwZJMs7/97GucL3znNsVJdA8/7XO+mJEpzqWibHUMrMXCieL82BfDhvuPlrXqbvGluAxtGVyfeV3TgihHDjcfA93Q3Spe0vHzEkn57tmu83G42sl8guivJrJEjakxGSADZIAMkIFzhwGnqTtt+gw59Z8YEVI8C9bNXPFbrBPbxPNhkVY9bxRL3SxuLCMVlVUhPxtvaAdpAN99nYzWze16JfLuMIeAvvrLKPzjrahY9Zmc/7e+vg6nMjNx8uOPUfrmayjp9Xfk338dsn98HnJ+/F/IveVy5Mjho69EbpcrkX97JxQ28xDQe/fth/gKz6KxntH8hYshvpH0XC5MGiajfm3mrx6xKyKARwzA2uwsbMo9ip9MfBNn6uoQ8+lCRA15EV9+fQiiBr+ANzasRVlNDTqNH4miygrMP7BbDgEt5vtVxq++VOVdMiahISys7WJ44EOx/cNiNBoGZOhDQEuj9cmnsNFm+Br5OE1gw5TVjVrN6I1b7WvH2texcfp+39/m0NTpeprS47DMZ834PVNq5qnXxzSMI2kC1x7LwsG7bsL+G6+WX/Hbn6kbyvpDA17Clrtutfo82B8RNYD16N/GHsxqv5aYN1iP4m2qESzyau7PiJFvypNoJIduDlebGntBbWg/cVEXw3yoC7mXATwi8TXNVAnXzY8yLlUUbrFpYMZi5iG9DDPdQJ+hK9qUvfxVWec4mxlr7HdksbHtpekqqlasD3UO4F2YJgzjfh9YRrKhZRmyc31GiFGPWMzc51sn0x36AAPE3MYTDUNdrCv47E1Z5x5J6wNEuzl18dDCFrms9IlF3JAZyNDq5tMpuPoZ7dPL8/4dGQM4H/Ojr0fHa5/yiPTMwhyxrdOfMVmLAtUjep1199pmrHsMTzz5x/QNaQAAIABJREFUAPouO2AzactNg9Rd/nEs7e8uu7wiHXOmZDhMYZXWbr5G1ADudD2cxnjRsgHSiH5oimaYBWMAl6QjVpi6v+6D+ZrOQtvMhVOx1Gn07jCM9DuSfFFAzn6Qfx/5BJOXOYzeip2Y/HBndLxzDDZaDyeVfvciNs0RwWyl8WbSS+Pshc/jGg99yisOYPqTok/9RwB7Rw56PSxX6zzmPtxtGnq2aDgzGtdm3BptKtgwHr2lmWU3gI3I3qH4wIwMtDTOnCeHZbWZQmaZg2buMc7ZRUakli2Nl5amCSIe4LvKyTOjvWzDC5smmYy8PGy7PhjGQwz6qTrI8nzph8w94DB6800jbzCSrShMXz/nLEuAMF2WqIg9s/4q4nnYInv5ujHsM3f3IFkYqbHzcNDW/jLk5GnnbqVDn/FItYz1SggDQxqnPWJgaSvzKTbr7jRPM7Bw5g6HKazSjsQKrS2GGTgYQ+IHYPTqww5tFF92JiwGZB38z1W9adFsW5S42E/1j27eKENyoTLFNI28t5n96TWvp9LQZZSp9g9A8m6tf83IdXc/ViJrmRHVbjf/VdlDMWy4aJ/Wf1q9PbkpNVkel2ZjVkSS51j9bebvNPRk3l7bVB+Jc0Cao8/LsPN94yUBffhyQ1MxL6qdR9U3wtQevVqPot+DZDGPqvPlEE/zUtWncczY2CrNxs7VkyT7g97f4WDT14flFcr8HYAJG/R6izTNcCx46qA0cxq2er19L7/4zhWVKN9mzKc9dp3jZQs1x7HthQ8vJvKxIlH0l0fZwhiW53nnOcN/dL16ycFYBupXEYUdbJ8JHYJhxaGX9eLNGKRqL5GUm6awaw7gimwskVp4vKShHa827rjecX5y9gH/Ji9kgAyQATJABshA4xlY9MkS6/lv334vY/de/bmpd74ijUirnhuLPMLVB+F6Zq7yqa85hYJu10mzNu82EbnbCXldOyLnxguR2+UylMT2xelj2ag7W4e6unrUnzmDulO1OF1cjMrUdShJeAX5v70ROTdejNwulyP3tqvk/i0RAazaJJYZX2xttAmsfCMxqmkkPl9/fTCiXhskh4DWDVrrd+IgGQG85ugRHCkrwdeG9cWSQwdwqKQYHRJeRlRCf5w3Kg6l1VX4z9ZN8u9TZ07jw/1iCOi+nkNAi7zFENCiXFF+sB8R+ZqVMDQsRmOTDGBH9K3My4wItkxX+fdT2HXQGT1rmsUOc9dpksrIYd3U9WcAS7PXXY5hVHtHJTvLaszfFSmfWuavMoHFusbkpe9zZFi8jHaWY70HCwaAiBrAoh5i+GF1MAoTV73hEeoyhDaFNWlpaRka89XN4/UbN4W1TsFm1pYigMN1cXXm43wDzMsAFhf5latSwnaBN+rgYXTmrsBQEcE6UDddlcGpG8D7Ma2fMGdnYI/ngyJze68Z2G5tb6QB3GuqlofzZsgsx2bIqjR5WDpMN5DN8mMmYYNVJ5VWX3roYqX32maueyYei/SIT7lPKPXT6xD4d0QM4H2GmWgzLa12V6Lc3H7flJ0Wh4bpF2oEcGd4GpamQarnr44VYagKszA2JbAuIr1XnbzMSZW3tfSM8jXL89xmRgDfPxXbdJ3E75IV6CsinOPWWFopg9s+5LGKIk6HZYp6GvD+2q3v7y+N//Xr4rQIbFFvs52e/eNso+Nvt8YHDIP54ane54jNY3CHPwPYM3JQtMPrYblaNwYp+sNwWT+36WjMKxwD3QyyGKgwh522mTwHDOPH04wyTQaHqWlEYgmT0Yx2dER7+srT+sY0UHpP8TbzjfkdB+MDyyA0TQ/PYZnTMFYYHDaTLVB6w2AVkcOD5jrNXLP9NhNd1NtcbzOl3e3xmTpmX/Sf4X8YbNFnpg5281rka+7fw93PxvyWMfBFkGr1cHDqZaYqM9Bbe8WXf9Mn5LmqPYaG9aqX4sR7m9mfAQxgz/asGy8jdseuUxo10I+qn/vrw5ebZXu8FKDqbPHh5EYZwG+sDfASlpm/5zHntU31kfslBVkfVaZ2PKg+H73aYV6rtLb2Glp5zrHqaXyq+jSWGaWvMDDFdygmbxHzxao+cy+NaNm+GOsyf91pVR95caV08WTH8/xr5u+lg7lu2DKHietsh2tfc25kL7YrKmGcX8cj1crHgwlzBAn7iws+LeQLRh7RskZ0vRnpryL+Xcs9jpcMRL6h95nRDw2zovrLWOYjVY5G4dXX6iUAMZT5SIydOAkTJo7HCPHiTdIYvB7UHNI+jezlcj31IANkgAyQATJABshAOBkQz3eVmSsCggKZwGKbHjQU7mfDwT6/DzadHgEszd8uV0FEAufe3gm5N12MvDs7onhAL1R8loLTpcdRX1uL+rNnUQ9IU/hMSSlOzpuD/Ae6IOfH34SYR1gMIZ3ftSMKu16Fgl9dh/ra8M9dHEz7/h3Ty/KPlI8UyvKl/rHBFBNymsveec2IAH7NO1I3yowAXp11GMXVVYga2gdPLpgty/n1zEn40svP4Z+L5uBMfT3umT4B542MRX19Pebt2xk4Atgs7/LxI4Ou86Zbf46DL7/UZJPRZzg2MgLY07y15+Vl4BrlmhG7HnkYEcPasNIOo9krAthrnSjHGHpajz52GtFN+1tGAN95o2UCH7zzxrD0y8H+fbC5y41BM6ESRtwArqqqspnAkXojQzWoNSxz8/KtYaOF+Xv69OkWqZaaA3jwK682unzRf83xEUNjhPOCL/ISF3J10VdLfwaweNtLHw6k6XXxMjMroYZd9kX2mun0CGDTKNaja5312TDOGO55qWWKhmoA++oih5hOz3Q/AFWGdYA5Mbo/8zY+Fw8KS1MwSqQbp4Z69ncD662L0T6vbR76qAeTodRP7RPEMhIGsIjW7NjpVxi92Z8u6RgqhibWhmL2MlsVB17b3CahVpZpAHuavJ7Rs2Lf49izeQWmT0hAbPRjuM+aH9c+FHHAcpXeniavWT/Pbcp81UxelVeFue3JWb75iD3boPIQw0gb0deTnXMHW3lWojx3J9bNnYqhwwfg6fsf8M19rJejp7f9zse2tA8xeXgC+nZ/APdZczz7DHzDaL8eQ23DOGt9ZMvPvt6lce4neK6TH7Nf5OOpqZGnZ+SgLNvrYbm5zmHCGhy60/vMWXv9FbeueRTzVhlD7UojRhkyzqXD6DGj1MQwyIN69MXYdc6IPI+yTRPEZUgpzc3tPpNTmR7OSEqRt7nNZqCY65LWus+jsgyVn2PYXRlV1heTtzjqrIwybQ5KpaFcepqcIpLYHGZ4gzPS1sxftdMyKFW5AfpZ7WMNIaz2KcPBbWux8P1JGJs4FP2sOWftZrEyvXzaqv3F0s2QrZ3qpYHhyz1MISOfkswdSFk0AxPGjcSQ/gPQU7GkGZxeZpwqx3ubVx+b9VZ6uDT0GeyWMW/yHShCfdNEwbseNR2gbMWrP26sSFUxbPgMpOzO9+DRD4t+OTX7yMO0NTQ0t2vHg6Gp/kKF6nNVtvu48uwHU2tLT1nHpjKTj53KdJTDJRvM9Bw+23v+ZrMP7ZHxqj1qGeFjwUMHwzBPwMKjqg5+lq59zVEa1HHiudSjd1Wf+c5dxugE/ofd9+xLxW6jliH2mVVGQ6xomuXtQPJwMVz/AExwRkZb+TnmqlfznptRz3ZOtbyt/blOnXe5JAtkgAyQATJABshApBkQz36VsSuWh7OOuZ45i3V6mkBGcWPqG5EhoGtPSZNWmLXCuM299UrkdREG8NXI63olcn78DRzr/GXk//4nOP7ysygb8xbKP/4INQcPou50rTSCz5ysxPH4fsj+6beRd/MPkHtbRxlJXNjlShTcfR2EydwSn6YawH36D4pItX8xdZwxB/CoWKhhmWX0rzKEEwfimyMGIOVoJoqrqvC11wbhopGxOHayHB/u3o6ol59DWnYWdhUXIuqVPrjs7QTZD/P27pIGcAd/cwCPMuYAFuUH+9l2/2+w99l/hsVoNMxYu2nrM4aVOWpst6J6/UXhyiGZ7Xn5j8B1G8DWPMGaKexl4LrNXm1I6c66cax+R84AFlrJOYBffhF5L78of7v1UzoGv9z7zP9g2x/uDRYJK13EDWBRUnsygVuL+St0F2Pgq7dliotLrE4P9ofYJzqmNyL1Fo1ej8rqatfFuDEXWH2fhBEjXQbw4CGvQAz5rA/vocxhMe+Dvn/TfnuZmeImLxMfDdHNWw+D89ACObyyb55b983hgfmx6P5MLD6yhpMO3QAuryjDkbWTjPl8hXn7XCzeWrzLFzlk1uPFpCXGnMJqbmHbcpcxTHAQdTb09KeLaKPXNq91ph6h1C+EB3CRMIC9DFs7X1mY/mRndNTMxkD7eG3zWmeVoQxgL/PRyzzd9wleEMMld7oeN9//LPoOT8A7ySswJ+4BI1pYy8co124KW+Uq3QMYkt5mpTJvRfSuk/8QDeBrr5dDRt/cf419WGwr3+PYmGTMb9zxhnvxSHQ8hg4Xcw5PxNMi0ljrE3ddKlG0eQweEuZ9p5vQ7dHnETs8Qc4F/E53sc5nAAfsH6suzrYaf7s0DqSnyMvvdn8Rp6Icr4flbnPHp4E7vcvgdbTLtd00MvuNE/Oo+osMc0eEqeGRo4cvR5ajDF/9NC2VaecyMc00ru1u08OXr7lNM7wsU1gzHX3pRRle+ZmReF5Rvh4Gry0/z+1lyFo31Zg7WZg6Yg7mZXt853Ohk6udSqMA/ey1jzX3qIiGS4CYU3jaorVYMs6Y11Y3ewObQW6GbO30nKvaV+cVbxhzx0a/MADDkiZhwvuLkbJsvDFPs9YXgergvc2rj/2xourj09cygjz7SUsv524e6phb1IsVfZ8A3MhjIR9bF41BPzk/q5jHWMyvnK2dRwPl77UtABuyPPd2b01FG7zyN9rmuY/JnqWnXp5tJAFNn4DMaOlkXubfathi29DHvm1DethfarAx2hzHgocOrnOp3h79t2tfsw8SZwQ452bgoDXig7vPPPtKK7Oh7Tb9tP1CWh+oz6w8Gzi/mOkKds825jOOnYTUhgx1K2+NJTmkdgBGvPbhOu2cpGlJXagLGSADZIAMkAEyEEYGxPy+6nmvV8CPWKe2i7Qh3Y8GUU/xnDvcH3sEcEfkyQjgjsjpchlyf/495HbphLz7rjeM4O9E4Vin85B729Uo7NkdlatTUHfmDOrrzuLE1MnIEabxjRcgt8sVyL/9hyjsahrALRAB3JqHgP7LxzPR4Y0h+PKowXYDWM3dmzhIGsAiArig4iS++eYriIqNwcSMdBwqO45fznoXRVWVePmzpYgaGI3Lxr0G4QDP22cYwF5zAAujWZb3xhCI8oP97PrH37DjLw+F0QB2m7E2E9NjGGe3CavMTbtZHHQEsHPoaHN+3+AMYH/zAqs6tb3l9j/9AXueeixYJKx0zWIAi9Lagwncmsxf1cPiDRhhAr89boJaFfRSzSEcqbdo9IpU15wK68VWv9CrC7pYDh4cD2EM9+3X37rQq+3izS+vm4LG3QQEMi6N+XO7v56CAmV66hHARxcgzjG/rrMOGRN7ovszb2Kl9ZCuMQaweuhShiPpC/DWwGipiRV5bNaj4ajeSpQHUWejDQF0UVrYhpwOkD6U+gVxc6Y0jogBPPepBiKAMzD6zs7o2H+FZVIGMgy9tnmtU21SQyTHasatc5tv+OR8zBHm5Z3xWGVFmBusuIxIa1joVmwAx63BnuSn5Hy5DyVlWPpa7VfDJU/R5hSWvHgYzS6OzH570j0UszEEtGYAN8iAOh7dS5fupsHrNaS3bJc/A9hv5KAo0+thudvcsXTzSG+YEu5hhNU+LtPiqDlfpL9IV5feop5GBFvvPsL88x+FpsqUSy8TU8tbGcoTrEhct+nhy8/cFooBrCKd9XbmLZdzZXoO4aqMcds8wxoXAY3FMmRtWIyx8SKaLQa26FO/OgToZ9c+5lDeYh5hba5foY9h/NiNkMBmkBdzvnZ6z1VtbDci2UUEuGMIXFOb6NZgAJt82/pA405oZkTN68dMIPYqUR6IG1ve+di7eoYxRG2PGPjmRA6Uv9e2AGzI8syI0uGLrZcx/Pe5V/5Gf3ru4zIvRdrGM+M7hn2MqXWp40QktmO0AdE+sw89j1MVoR7pY8FDB3fkuLtNsm2ufTMwQbwgovWX0sB76e4zo6/sc13r+3r2ZUWY5gDWGPfbZ1aawKyIOqu56QdNyfA7yoDeNq/fRnv1KH4/fWHVi9u9dOQ6ckEGyAAZIANkgAyEmwE1FLR4DqzyFs989ee+6tlwuId+FuWJ59zh/tgMYBEFfFsn5HbtiNyfX4S8uzqjeFBfVCxdiuMJ8cjr9mPk3HAecjp9FTldrkb55P+gvq5OzgtcNnmCZQDn3CoM4B+hsMsVzRoBLKYGzfhiG2bOnmsFr6kgtmCXYuRT8RUBcJH6vPPFBkSNHoqvjBJzAWvDQKvfiQPxjYQBWJV1CLkV5fj6G0MQ9Upv/GxyEkprqpF78gTyK8rx/TEJcnjo749NxNm6OszZu8NvBLAoR5aXNBSi/GA/+1+MxsYbr8fp4yVhM4G9jFZlAnuZuNIAdgzNLNM75+J1/m0au2dMwzddRft6GsAqstcewetlPgeqv2pHW1meLi7Chp9ejQO9ewaLhJWu2QxgUeK5bAK3RvNXaC6G3FYnzuWfrrI6vqEfavhosa94EyfSn1O1p60LsrowN2WpLuLK3FVLf0NAq+1izuCmlOvbN4BxWVGJ7dOFAd0Tb61NwVg5L7A+B/A2TIgJYg5g2xzBx8zIYnNI5kY9aMrEzIEiOnm8OY+vWQ/bXMP+bkobqrPaz0w3ZAGOOOtoRvR2D9YArgilfqr8hpeRMIDLTZOxoTmA9e3GsNHeQwavi7veFl0quAufAew/+nZj0q8aFwFsDll8zXCPtyrT4mWErs+AFn3kvw7WNj0y1yuK2ZbHcayLu1dGND+RbDd6/epm1jlgBLA/o7UiH/Oj7RHADTLgPB60v10GcIU5ZHj3D40IfC2tYCF77rOyn+yaNhQ56PWwPJD5406ftUgMQ+wxpLGsXwYm93GaLKZ55Hd4Wffx6htm2iw/Vp8/1Z1enpNNE8Q9961Ib+pim//WbXr4zu3mNi8D2E87rLmRtTlR984cjOgeY5BqvcSj112ZNN5DHxvmZwzskZH6/uL3YXwQL/SehE2KD1MHPULXaFeAfnbt418bo29CMYCzsXC4kwmzHX7nqja2u14mUG00o/F0A9ht8Pu0MvLRh7wV20z9bX1s7uPSw5eXirD29YvJt1eUt6yv1xzB/vUVfRWYG60uSg9zyHSf4ec2bC22Pcxzn+Gqm9RaOWbErX5s+TMAwxMB3HhmrHYqbbRlw2ai1mZrP/99FdZjwWTOx1UlFNPe861rdXXta86tbjvfaemttql1Hm3cMkm+XBLQFA/rHMCqLvZlw33mvkbZGDCjiIfNPeAxVLq9LNt+No3M48k5H7ctTbB5MZ1/nakNtSEDZIAMkAEyQAZCZ2Da9BkyyEU95130yRI55LMI/lm0eKl89iu2iefBIm24NRbPucP9EfPzinl6xRDQ+bd1lMM353W5AjnXno+SF/4Xp3NyUHf6DM4UFaNq/ecomzQGJSOHo3zOTJw6nCkN4LrqGpQmxCH7+ouRd8v3zSGgzQjgZpwDWHkVTVmGW1+v/LYW5klTV0TlimhdaxhoNXSzHAL6ZaRmH8GJU9X42qg4RCUOlObu4oN7ZJYTMtZL8zcq4WX8YMwIue7j/bsRNewlOIeAVuV8aVQcvvFGPLYW5npVy3Nd7qTxSO98BcrWfBY2A/hMqRG5m/7kTBQok1YspYF7BfThn4WRahjAV8AycEVap6kr8/EycdU6fX+zfGUIW/P3imGc7Qawt9nrv/7OukfCCK7esxPiG468S1d9Kvs3b+q7nv0faGWzGsCiIueiCdxazV/V8ZOmTLNMYPFmTaCP6J93p7xvpRf7Nsenrq4+bBdbcVFXhq5z2ZABLNKHZ96HwAZwecUuTOv3LLrHvIqhYqlHAFeI+XnFEM/PwjdXsO9m58jiV+W2ocvzbJp9niTMWz0q2LeP+0amGNmO6E5hhKx8XdRpEjLMh1dGpLF3PbLXLsBKbbi8PdLUfhZxs/YHeJhmlvFMLGZaw1eLehZjdZKIan4WwRvAlQilfm4NvPWJiAFcYQ7xfO1TmL7PWW4W5kSLOWqfx3y9T3ZMxX1intc4x9DF+2bhCTE0sTa8sGibXyNT9GVIQ0Cb5qvTXBTlyqGO7dG+bnPS2T7x905Mvt+MKi7Rtx8whr7u1Bl2szLcBrAoU5QljPOb8PRcnwls1N85P7MyjBsYAto0gO9IyrAdi0Vp8ejm6qMDmPxwZ3T0ZEDXxP3bS2PDjL8XsWnHbWWXl6QjVg7f7dC0wchBr4flAYxBr0g8swxhNh10PAA/KM1ht9mnjJJhiw7b21FRiZx1i5GinWPKTXPPMkLMvwPPz+kbmlfMtbpEz0+LAOs9bqN23vIwPaz2mNts5qC5TkRaLtOH261EedFGjBXGd5/xSLfMXsMM7z3Fzo1+jpLRr2KO4w2OOY5Vfj10A7gYOY5oXHE+T0kS5U7FVlV3v+ZlgH527WO21TkvrxqS1TFcrn8z0ODcX9S4/7mq9f0SsMTW7sOmoRwD3QAu3z1bDgvde1yafUjszHkQw/tGu8wqUw8vQ9+lh3a8usw2X1S0F99Zy0ZKI80XnSvyCsReA9yU5iPHYkzVaw+S+8cg2hre2OSix1B8kKnSiGUxUseZQ2pr0dM+AzgGg6bssOsnzgHSwLcb6P773H/bPPfx0FMcI41l5uDKGViyv8x1nilX7IZs4jXPseB+saAS5eYLEuK84ozE188jXvsq81ic8wrUucFcluxfjCXWSAj+eDRf5hHntCKdIV9ErfuYsqez1dFRB31b0/rM65rmq4e89vSZ6ntBJkA99Dr5fuebx8xgJO/25evbznXUggyQATJABsgAGSADLcmAiPwVzxjFdH9iKkD5vFE8czS/Yp0yicV0geGuq3jOHe6PFQHc5UrkizmAu14lh3DO/sm3Ufi/f0XV+g2oO1sn55gVZZ+tOYXTJyugqlJXV4eKJUtR8KdfIue685DXtaOcSzi/61UovK1js0YABzJ+k2fPgYgQFstA6cKtr1d+J2pq0PX98eggo4DjIOb/lSawigAeMQjfSByA6bu2YlNejs8AHtoH982Zij0lRbhl6lhEDesLYQBf8naCXPf2lnRpEkcpI/m1QZa5/JVRceiQNBS/nDkJFSEMyV2bny8NwqzEYWExHH2mpWbMWnPp2s1XlVZF4RpmrJpr9wpsnL7fo07OfJ/CroPmOs3wtQxks2yRV0CzV6bT6+cs5wq4DG3d3A7TbzH37/4br5bfvAG9PNof2hDUR4bHy/6tLSjwQjXgumY3gEVtziUTuLWbv6r3k8aOt06aYk7fFSs/s4ZIEP2xd98BzF+4WM75q06uzWX+qjpWVFY1+YIrhvIQb3OpC3pjluImoOkX/oYM4EqUb52EHurmw2EAG3MFG0My/2vg2/jos1Ss/mwBxg7rg3+J4aGT1rse3GUvNm5ueiTOwMq1SzB21uYA7RD1i8aLw8Ybea9dgmmJxrDYNtO5aD3G9jJukKy0i2dglBwuWp+DWNzYivmNVZ3fxLTFqVi9NgUfTXkTAyb66lKyabzRbjHn8PwU2S4x/HSPpLeREKIBXB5S/YK7+Y6MAVyJ8n0f4ukbhAHYFU/EzcLSlDVYmpyA5x6+CR07eRh5FVmYIw3L63Ff9ETMSVmDOROex303PIXYuMciaAAfx7rhRrSsVe6UAXjkhnvxXLQotyEDOAtzut+Ejjc8izlHfJpnzhXDMHfGNfc/j3fmrsGquRPx3P034Ym4eDzSLAZwJcpLdmKy1FTT+8iHhrF9w2OITV6BVctmYWj0A/hZ9POuOYCL0sbgvmuvx31J6eZQ0qqPbsIjsk9XYPpw0UfP4znHHMDynKIz0F/MM7xGlvdO/6cw2hye212GMvftuvuM3pvwiJnXHNlP1+O5pDHyJQHdVG84ctDrYXkAY9DLAJbDAIsoYGPu0QmL1iJ19WJMSBwgjcjJXsOsFm3EBGFQ9YhBv8RJWLg6DanLZmO0HMJYN5Z80ZQ7rQf1yrTymVklW6ZKs6/flAyfoWsaSa+PG4/eLwzF6JlizuG1WDhuKHqKurqMDP9GlWXQeRnAb4zH2D69MCRpNpasS0PKovHmnLx2I9eICB6M5P2+48N1zbGM3l4YMm4xUtalYcnMMRjyQi+8/v5UaVxaRrg0DXv59Fu3HMlviAjjGNiMR7/mZYB+du1Thk0TDaOwX+IM2U6jXn0xItEoU48w9jT2rP6rhIpm7v3GbKSsW44Jc4UpHmiuakOzki2T0NvkbNoyHzO9E0dikFjvNDGlUSkYM+v8/kj0eyEBY8eJOuucGfkbBnwMBk1cjtTVszFtpfmCgksPrQ/Nbb5+EduESWoMx90zfrzBt3lMCPbcJpx/9hrkRkbw+viTx95wY6h0/UUCSzsxT7R5jIohw3uPG4/XvbQTkeSxYzA6VmNsmRhe2miXjTFrKHC3ptaxY+sbQz9PTjz1bDwzRhlaG1YvxrQkf+cAs1/z0uQLHD2HL3e91CJesoj8seB7gcXOlTBbJxnzXb8wACMmGucIce4cmzgGS5S576mhzuQYJIvjR2NSP3799ZkaOlnMNW6cT5cjWWo5EpOnOOe11o4R7dh3nfM8tjWqz6x8vK5pqi7mtj7GHOYi8sP9nYdN1gsmh7EkMQGjxTzj8tw+yRxevS9eV+cGq1xVBpfB9DHTkBMyQAbIABkgA2QgUgx4PQ8WZrD4em0LZz3E8+1IfGwRwGII6C5XIq/rVci59XLkiGGc//EATkxMQtXa1ajZuw+1BUWoPX4Ctdm5qNmxA+XzZqPw8d8j98bvIOfmS6SBnN/YOxHDAAAgAElEQVS1o4wmLry9Ewq6XYf6CAxd7aWF8h6cS+copIHmB/bKNxLrRm/6HB3eekUOy2xFACcOkmawjPZNHIjvvDEE330j3oj+Fabua4Pw5dcG4dK3XkEHEREs1iUOxJfkuqG48PUhRlqxTcwnbC5F/l8WUcRvDME7GetDbs72B+/D9j/e32SzURm6oS6VARzqfuda+spN6y3zV5nATY0E3v7A77DjT78PmQmxQ4sYwKJg3QQW5mRb/WzdtgOfrkrB+o2bcPp0+Id3CKcu+rDOzhOs82+Rtrk/NadqAxiWwd0Uqbe3vC7moawTcwg37eIfhAFcUYYN48yoV5cBLNqbh4zFbyOul2Gqivr/q9+rmLz2mM/YsD1wOobVE2OlQdxdmLvTdwVoQx4+n/IqBsSovKPRY6CfvEtFvvF48Tn1plw0XhzyNhZttUcgG3qZdbbyfRb/6hWPt9Zm2upyZO0kxKk0z/VE3MRUHAl1DmDV9pDq1zBHETOARX1zMzAn7lncd4uIRDXM4IeiJ2KVZpTauCvZien9/4ybZeTt9bj54QGYvuO4Z7Rv+CKAhUZZWJX0LLoJw7qTs1y7EemOTvU2gMsrjmNb8gA8ZLb9mlv+jL7JO1HkOYxyJCKAzb63ImR9JnDRjlno+3BXaVB3vOFePJ20BplqCGltqGkvc1aYyr4+ugnduo+R/emcA9jqV5MBQ1uDgfu6x2OpyYBXGW6NzbbkZmhli356Hu+kZKHcpWkDkYPyWPJ6WB7AGPRjAAtTJGvdVAzrY5hD0S/0xbBxy7GzSEXuecyzWZqN1CkJ6PeCYQRH9+iFfsPHY8k23/yuRqRwX0zY4ojgU/PrmlHHgQxgYWz4q5vVP1IL/yacZYh4GcDC2DqahsnD+xrGco9e6C3asVuP4jXn0HVG0Krzmb7M24GFSYPNvGLQM3Ykpq3LhohYFJGrPkMoH+nvj8QQpbkoN95IW6Ln59e8DNDPnvsY/dXb7K+esWOwcHdxI+YAFhyLvEwTTvS7mPc44FzVJvsVzr4cjNGL9qDAcxhjEYm9x6GlXmcPs1KmH2D14+jVJoueeph18jTbxLZ8bF02HsNMw1QY86ovbf0TkL0guCndgxXjAh9HinPXcTAlDVme0ccaGy4NTR51xprBAG40M+I8YztOYtCzfwLGLtqILFfktNmnAQ1gkSbCx4LQ1i9XlSg5moZpib5zhDjfDkmch62qPX73zcfWRWMaPmd4MmFok7NtsXwpQL7w06MXBiXOQOpRFfX+/+zdf3Ac533neWxd6q7usld7f+RqWVu3myinxNbFia1sdiklyyTmyXcX1bk20q1Ku77j3WqlxdE3cY6SYJGiZNIUCJkiaVpEGKFkk5YpC4yWEBnRFrQSTZEOTVKBGYExcSFN2SQsSiAsAysKkECIoKHP1TMzz8zTz3T3dM/0DH7MW1WsGcxMdz/9er7dgPozz9Mhx5RXJ7YWYx9r6bPSdsJ+pxX7tfT7y/7OCXt092FU3/d+R5n9PXzOPbfbdfMY26el/sEJJ2qAGqAGqAFqgBpoXA2Y2R/da8Bdjz4WmO3RzPxoXnM/Y2eMzKJfpq9ebcgl9dII4JsKoa0ZAXxp6T/RpZt+VSO//Ut664Zf0Fsf/4e69Ok/0E//tF1jXQ/rP23ZqLFH1ujtf3enLv3uR/XWx35RI7/zDzVy8/XFALkwmng+jAC+74G1oW4r/2RVaVCbm1+EfjjjFz/88ENdnr6iG772lUIIvOUL+ZG6pSC4GPa2PbpG+X/2Z/vYtVptjxUC4XwIvOlBtT26Wm2PFkNh87niqGKzzl8w69+2Xr+5a3t+9K/Zfpr/Lj7+5fwo0XePHZ2TEJgAuDCqN+sA+N0Tx/L9+uafP56mHEqfnbMA2LTAhMAmaBwbGy81aKE9uXLlin58/sK8D3+tq7E2UyiYk6p70jTPzQnVvDdX/TH7Yf3TQJtf2Fn8y2Ya6Mb9MZPFHySsI7x/MguA79ijM1zoCgT/1Fx4zTXaperIwcVep3GhXSb7HhcYe31evGdq1Xt3xrWrOPV1cOpgbztxy8/r96rdq3qx7GfK/ciibuZ1v6f0COwLNdPo3yGsv576ZFnqhxqgBqgBaoAaoAaogWbXgB3la2aI/M6hw5HXpcx7dhZJs0xW7Uwb2tlr9tUezehcM0rXjNbNTwF906/o0j//ZZlRvJeW/mO99TtL9NbH/1u99Zv/QG99/O/rrd82/35Rb934X+mtj//XGvn4L+mt3/lHeuumX9aIGflrppC+qXA/YXNfYXN/YTPKuBn/uTOV2nzi0ce+HLpp87r9jH1s1qylti/7fjikv7flCzL35jX3ArahbX70rhPg2p/zoW/+9cK00eXXzRTSD5eme3bXY9Zr1t+2+WHtP/f/5S3s9kNhQl6cGR/TX//Gr+n0//ZpAuCMpnKudXRyYAro1f9vXf1x+rb/VX/9Wx/RtcuXQ3q9+ktzGgBXbx6faKRAYernc/l59ecq9PX3b/qDDzL7hZvVL27W01p/rNYfABfvd/vAy8VpglvLj+NlvvV3gpGDgTBlvrU/g/bMowA4P7VwXfedfF+F6bzXLM77Tla9V3UG9bAA6z2Lulm052Zqhr+bF+AxvWiPR/qC45EaoAaoAWqAGqAG5kENmNG95hYf5jaB1f7uMp8xnzXLVPtskvfNde1G/ZefAtoJgE0IfMmEwGZE8M2/qku/9+u69HtmZO8/0qVP/ANd+s2/r5GP/Zca+a1f1KV/+ksavflXdOn3fi1/39/ycmbZ6/Khcn4K6CYFwMbo6LET+YGBZnCg+Wd+Dvsv6efCls3iNRvCrj96SG1f+aL+863rgiFwfrRvIRQujPJ1RvyasNiOBraP+dcKr9uRxCb8Nes169/wvUP5Ztvtpt2HN/98e3606PgLB+oKHWsJPhkBHLyvr5n2ud6pn8cO7M/351tP1j6DMgFw2qOIzzdUwJzckvxC5TOteRG8Gf1edwB8slu/e931umtvefraZrSbbXBMUAMRNTCPAuB6+2j8XJ8eMfdpDUxBHbHf8+B/vOvdX5anb6kBaoAaoAaoAWqAGqAGqAFqgBqgBtLUQC2zOtayTFibag3tklxsz48A/v1f15i5X68Jfc2o3Zt+pTAi+KZf0U+X/hPlp3L+3f9eb//ur+vtf/ERvb3so3p72Uf09u/9Wv5zb9/0yzKjfc0oYvPZ/Mjfm36lsM7f/3WZaab5r1JgdnZWP5+d1b/+1rNq+7OufFhrw1vzaP+5I32jntvPusvnw98/26j/84Xn9KE+lNlerf/Nzszob/7FP9ff/N4/0/TwhaaHwLUExywTDI6tx5XzP9LJpTfqtT/8XZl+rfU/AuBa5ViuYQJZ3As47Jcwr/EHY5IaqDcA/lfmvrmf7NYA4Qtf5qAG5kcNLMAA+Effekyf7+xWz+4XdPh7x3X0yAv6xuPFe+X+aZcOnOd8nuR8zmeoE2qAGqAGqAFqgBqgBqgBaoAaoAaogWbUQKPu/WsvwJtw9u3/+eP62R9+ND8V9OgffFSjf/ARjf7+R5R//vsf0aXi80v2vT/4iC6Zz/zBR/XT/Hvm54/ml/mpff0PP5pfp1k3AbDVDj7aQHb0vUn979/6D2rb9sX8NND/2ebydM5/z3keG/6aaZ6LobFZPv/ZbV/Uv33hOY1PvZ/fsN1esBXJf3rvbwf16g2/qtP/6l9qZuxnhMBzPB20DXTTPF792U/1t5/+X/Tqb1yv9/9uKHnnh3ySADgEhZfmXuD9qSvzIzggwKEfUtbApx/Yo78d54/rZvxxzTaos0Q1sAAD4PG/O6SeL23Q5//0T/RZM+L3//kTfe6+DXp091/p7CX6PVG/pzx3s07qihqgBqgBaoAaoAaoAWqAGqAGqAFqoJYaMNexm/GfCWhL/67a59P5e/eWXv9gWh9G/vug+FnzGfvcrofRv0n60IzQ3XDslcI00F9enx/9+wvm3sBOsGtH99og2I76NT+bz5nP5z/z5fX59Txy7BVlPXp87IVv5acO/tHq+wmAF2AAfO5P/u98//2ngy8lKcvYzxAAx/Lw5lwJfPih9N77U4SPXMCmBqgBaoAaoAaoAWqAGqAGqAFqgBqgBqgBaoAaoAaoAWqAGph3NWCuX5vr2Py3+AXckPboxQv6H/9iV2EE7/ZH1PbYWv3C5i/kA14T8trQ1zyanwvB7xfyn2vLf/6h/PJHLw6X4Nz1l16s48nFr2zNh4jDj6wnBF5AIfCFDQ/n++3NP/tKHb1fXpQAuGzBs3kmMPvhh5p8n2+e1fLNM5ahbqgBaoAaoAaoAWqAGqAGqAFqgBqgBqgBaoAaoAaoAWqAGmhMDUy+977M9Wv+a12Bv/i7H+hf/mWv/pvHO9X2lS+qbes6tW15WG12emfzaH42r3/li/nPmc//xZkfNAXtJ10b8mHi2fa7dPWnowTB8zgIvnppRGf+3YpCaN/1SGb1QQCcGSUraoSA+ebLe0wHPe++3cYfjo35wxFXXKkBaoAaoAaoAWqAGqAGqAFqgBqgBqgBaoAaoAaogfldA+Z6ddYjNhtxbZ11NkbA9L3t/5mfX9PQz36qp06/lr9H8LLer+q/+/NN+i+2rss/mp//j2/t1TeGXst/znze/OeuozGtLKz17ef26tWPXqe/vfUWTZ07Swg8D0Pg98/+nU79T3+Y76ef7dubaTkQAGfKycoaJTA1PU0IyjQv1AA1QA1QA9QANUANUAPUADVADVAD1AA1QA1QA9QANUANUANzVgNTV6YbdQmc9SLQEIHJwb/R9//pxzTw8Rv0k00b9cEbwwTB8yAInh6+oOGNGzTw8Y/q+//s45ocfC3z/icAzpyUFTZKYObaNZmpNfgGHAbzqgYm6Y951R+cIzhHUgPUADVADVAD1AA1QA1QA9QANUANUAPUADUwv2tgAV5PM9elZ2YKozcbdf2b9SLQKIFr77yjnzzaqb/+2K/pr3/rI7rwyBd0+buvEATPQRB8+fB3dGH92kJffOzX9MbmR/Xzdy83pOsJgBvCykobJWBuq3Dlgw/m9x8w/IFJ/1AD1AA1QA1QA9QANUANUAPUADVADVAD1AA1QA1QA9QANbAoauDK9Afidr+NuuLPepspMDM+ng9/B278jfz9Zgc+8T/ozL//t3rzzx7Xz577D5p49Zg+uPgTguEMguHpnwznPY3rm91f0Zl7/q/8KOwT1//j/Ijs4Y1flOmPRv5HANxIXdbdMIGf/3xWTAvNyFNGnlID1AA1QA1QA9QANUANUAPUADVADVAD1AA1QA1QA9QANdCIGjDXn811aP5DYNEJzFzVu391RD9+sEPfv+m382GwCSb51ziDkzf/tn689vN69+h39eHMTFNKigC4KcxspJEC1679XOZbWO9PXdF7709p8v2pRfHNskb80cI6+WOYGqAGqAFqgBqgBqgBaoAaoAaoAWqAGqAGqAFqgBqgBqiBcg2Y68nmurK5vmxmn7z285838nI260ZgfgnMzurqT0c1+drfaOzbz+utJ/9cb3x5E//qNBj56p9r/IUDedeZn47qw9nmf5mEAHh+HWq0BgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEKhZgAC4ZjoWRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBOaXAAHw/OoPWoMAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjULEAAXDMdCyKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALzS4AAeH71B61BAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEahYgAK6ZjgURQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACB+SXQ9vqPfyL+YUANUAPUADVADVAD1AA1QA1QA9QANUANUAPUADVADVAD1AA1QA1QA9QANUANUAPUwMKvAUYAz69AntYggAACCCCAAAIINFig66/e1tjUNf7VYWAM+Q8BBBBAAAEEEEAAAQQQQAABBBBAIL3AxMSEGv2PADh9v7AEAggggAACCCCAwAIWIACuP/wmAF7ABwBNRwABBBBAAAEEEEAAAQQQQACBORVodPhr1k8APKddzMYRQAABBBBAAAEEmi1AAEwA3OyaY3sIIIAAAggggAACCCCAAAIIIICAFSAAthI8IoAAAggggAACCCCQkQABMAFwRqXEahBAAAEEEEAAAQQQQAABBBBAAIHUAgTAqclYAAEEEEAAAQQQQACBeAECYALg+ArhXQQQQAABBBBAAAEEEEAAAQQQQKBxAgTAjbNlzQgggAACCCCAAAItKkAATADcoqXPbiOAAAIIIIAAAggggAACCCCAwDwQIACeB51AExBAAAEEEEAAAQQWl4AJgPlXv8Hiqgr2BgEEEEAAAQQQQAABBBBAAAEEEGiOAAFwc5zZCgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIINBwAQLghhOzAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKA5AgTAzXFmKwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDDBQiAG07MBhBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIHmCKQNgP/4j/9YaZdpa86usBUEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEECgtQXShLkm/LX/0ixHANzaNcbeI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAkwSSBrk2+HUfky5LANykzmQzCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDQ2gJJQlw39PWfJ1meALi1a4y9RwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBJglUC3D9wDfs52rrIABuUmeyGQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQaG2BuPA2LOyNei1uPQTArV1j7D0CCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCDRJIC64zeo9AuAmdSabQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACB1hbIKuSNWw8BcGvXGHuPAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJNEogLbrN6jwC4SZ3JZhBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoLUFsgp549ZDANzaNcbeI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAkwTigtus3iMAblJnshkEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEGhtgaxC3rj1EAC3do2x9wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg0CSBuOA2q/cIgJvUmWwGAQQQQAABBBBAAIG0Apde7FSuvV3t7T0adBce6Vdnrl3tHTs1OOW+kfT5kHab5dvb1RNYcdLl+dxCFhh7uTPf9+3r+nWpaTsyo7FXd6vzvlxh2+05reodatrWF8+GpjT49Q61t+fU+WJtvTc3/b94eqDanozuuV1tbW1qW7IxeN6utuCrGwvLtX1G+0adDw/v093Xt2nJJzfqxHvO60me1rNskvU37DMX1LviuoLHIycatpVGrLjm/m9EY1gnAggggAACCCCAwLwVyCrkjVsPAfC87X4ahgACCCCAAAIIINBQgTO7tSofrhaCUBOGhv2by4D00gvri20KBsDne1eV2lpb+wbVU9zf2pZvaM80eeUTOrI5vO+D9RDsgyY3MtPNleqqiQHwxOFNpZq1rp0vjmW6X2Erm3l7UP1Pdqrjc8E+zt3XofWb+zSUNlAL20gzX3vviLbZc1WN/TcX/d9MotTbmn5F95vANv/vfr0ynXoNwQVskHtHr9wcN/ihkJ/e7NXt+TZslBt5num+udi2Nm181V3usvofXK6br/dfL38metnyZ+bns1H13lHskwUWAKvW/p+fHUGrEEAAAQQQQAABBBokEBfcZvUeAXCDOo/VIoAAAggggAACCMxzgdF+rbdBSszjnAak3+8phGYPPx8YqTnzg93qWNmu3OrdGvqgFudLev7hQiA2p/tXS9MbsMzgk8Fw0AaUwcfFEwDL1lWNAWL6LriovgeN8Sr1HJ/QTPoV1LTE1GBPlS95LMQ+vaSDXTm1r8xp08u1jQBufv/X1H1NW2j64P1qa7tRN9+0JB+03n+wzgS41gAwIgCePrlVy5e06bo/2qrBQNNsSHq7et8M54peNvzz8+nVE18oBMC3P31hPjWreltq7f/qa+YTCCCAAAIIIIAAAotIIKuQN249BMCLqGDYFQQQQAABBBBAAIEUAjYAjgrBZmc0NTGhqWalVWFNHywGwFFtDFsm0WuX1L+uEMjtPpNogUX9IRsAR4bhH0xpYmKqacFlw7FtXW0+oomGb0zSB8fUbb5ksXKnmjbp8ztHtGml2eZa7Xz1oqacL0rMvHdRZ7+zR5u+0swpsJsBnXAbze7/hM2am49d1r672tT2ia06cfghLTEjcD//igI5a9qG1RoARgTA0ZuvHgBHLzv/3znxSDEA3pNqHPXc71it/T/3LacFCCCAAAIIIIAAAk0UiAtus3qPALiJHcqmEEAAAQQQQAABBOaRQLUAuMlNvfTdbnUU78u76XBxalwb1DQsAF6v/gV2bb0R3VI1AG7ERudynbaunmzSDaDDjrXZGc008MsVdsrpjr3n51J6fm672f0/PxUKrSqGrsu/ekGafkUPLTGh493aV8/s5LUGgBkFwNN1pdfzp7MIgOdPX9ASBBBAAAEEEEAAgewFsgp549ZDAJx9v7FGBBBAAAEEEEAAgYUgYEMpb3rluKaff269OjpyWpsPlWY09uoebXowV7q3aa6jU7uPXtRUxEomfnhQPV0dypmRifkRkTl1dPXo4Jkj6rGvtberNBLVBjVeAHzxQKc6Vnco1+mPYCy2ad0q5UrTWue0avV6bXr5otMqOwK4GABPnNVB9z6puVVa392noXFnkQyezrw9oD2b15b3/3Md6nzyoM5WDEM9r751Her43Fr1mfxuZkwDvZu01t7HdaVx261jFyulp4b2aL0J0nOdOpgw3E4VAE8cU/fqDq3Kdar/bWnqR/3qtjWQW6WOnmPB/i/ariqG++3GdvMeDbxdmX5OHO1Wx+pVynUfy482LtRLuS9z961X93NDGpuN6Qyzva9v0vr7nLq8b732DDnbs3WVD4Ara6ZaHcds3XnL1lj09Nr5Ok/qOTWkPevMPuXUmWDqY3uf21XfSDHmuNSWwtTQYz/oU7dzLMX5T108pr6eTVpv+q907LXLWPZ856wm/D4rbatbx8zo5LA6CTsGJwa00xwb9+XK5wmrXjxO3L439daxbpMO/sR+SFJT+t/ZXv5p+Pky1Mb9vONv+r7yXOZvJ93PF75+q9rabtXOHxWWG9x8Y34a6NuTjDodPaHeR+7W8o8Vpo5uu/5m3f1Ivy4c3li4Z2/UPYAvX1B/d06333Rd4XNLbtCtn92pwaHwewBfePpuLf/Uct2wwt5T+IQ2lu5ZXLxPrvuzc8/cymU9n2ujeuXr9+tu25a263TzHTntOBx+8jzz1du1/JM36FYTmEsaPbxDuU/fUBg53bZEN3zybm198ULlCOr3Lqj/6w8pd0fhnsWF+y23acnHluvuR/bpzGWvXZJqDoAvn9G+zY5vW5uuu+l27TgZnoxfHtqnrZ+9VTfkw//4NgVaWXP/n9G+R+7O37s573D9zbr9szv0Sji5ZPbHrbO2QhuX37VVJ0LcAm3kBwQQQAABBBBAAIF5KxAX3Gb1HgHwvO1+GoYAAggggAACCCDQUAEbALcnvw/opQNrC8Htjud18MurSsFv8F6x7Vr1zbMVTb/0Qmfk5/PLdz2vi840tfkVjDyvtSZM8gLg83s7CuvyXo/bht+mgR4TzK3Vnhd3a60TPgf2ZeUmHXmnYldqemHseHf0/VgrwtryPYq7//Kgtt0XFSKuUnAK62DouP6FZPdITRUAa1A9xYCv54V+dXp2nd8pp9lTP+qreL/ku7JDu3/ghLJG1d6b9+E96v9msdacMLG0bMTUzWPHe/L3hi59zll25w+cbrN1VUMdO2up8jTYF2FtKnzRIZmnDXTz6/HqPrQhNuRc2am+H5b7JPSz9kU7VXX7WvU8GXO8mi9eeIGuraGw/cy/5n9ZY3agWEcpj8FSG50vipj2z15Sf2fC46Qp/W9RTdvGdGxH9Pky13UwcI9zs2Sac5mzpZRPB7X1E21qu2ufSjnaqa260YSpf7RTcXeenX51Y/6+vDbIdB+XLCkGwmFTSQ/v093Xh4S2ZptLlhSC1E8Ft33hq8uDgfL0K7rfDXy95zduK4/sr1jWFRrujW6LCU3v2ldhcOHp2wtteXCn9n3u5sJzb/vG4manDflN2lHRIZ/N2y35jPZ59zG220oUxhf36/LBhyL6ZYk2nnR33jy/rBOPLi+G1yF9smS5Nr4aHhrX2v/TZ3fqM8Wg2a2ZgsFybfVD6vdOaONNIW3LO+bUXypcf9/4GQEEEEAAAQQQQGC+C2QV8sathwB4vlcB7UMAAQQQQAABBBBojEBcAJy//2/lPV9njneXQtzcut06dn5MM8UgaGb8rPpKAUxxVJ9tud3Wyg71fOe8Joq538zURQ183QZ9a9XnDtI1y9rlvMCrFIa5r08c0SYT+K3q1pGL5babbQw+t0093w2GYKXAamWHNvUO6OJ7xUbNzujS0XKQuPY5p1E2VHOCxfDAy5taeqQYlOY6tWfwYum+yqZtpWAoEGrO6Fi3DbNyWv+NYzo/Xm7f2BknWAdyz1QAACAASURBVC2Oli1Qn1ffartcuzpfTDaPq7VI9vlgsLn26wO65Af3pjFTg+oxwXWxz8fsZz4Y09m9xXDxvt066waJ5/vUYW07tqkvyqq9ozAy2tZXfnM9hYA9t167zT1vbY2Nn9exb/QER0PbumpvV26dGYE+Vv78O2fV11UcPbyyWwO23Qrud3i/F+39qaXt9tx6LbU9uN4oz9KXHoxPZ7+q9uzsefU9WK6Fjk17NDBSRClt238ypJ020L8v6K8PLmnwLzpLo3uDX6iY0LGvbdKe75wtH0dm1R+M6fx37Bcf/C8rOLW6skPbnhvUxVKnTeniUbtcu4LTWDuBeTnnk53yelX3kfJ6NKOpi4Pq+0qPjriHv+2PJvW/DXNzXXs0WDo3mbYdU3fxyx2bDjsNTHku83sx6c/T+Xv+LtFDh92Q74J2/pEJ3G7U1lMRa3pzXynEu+6uHToxXF5+emxQvTYYdUbi5tc0PVgK85Z88iHtO3u5PFL2vQt65dFbC2GkN3J4dE8xdPVel+xI4I06EdHUyGVL+7BEtz76ii68V1zB9GUN7snp5mJQe/MjJ8ptlDR98P5S6HvdHVvV7+yD2fedK4rhd9v9eqXMossvblSue58Gh5191rQun92nh4oBpxtcm9bYticNgE0om2/39bdr6+ELmr5W2KfpsTPq37zRC5inNfhoMcC+KafeU+V2TQ+/oo2fLu7Hks+od9jDLdmZkDxF/9swd8lyPbT/jC5bH2P+1c8U+v6mrXIOaw1uK45If2Kw/Pm8W7+2/vsdgc96reRHBBBAAAEEEEAAgXkuEBfcZvUeAfA8LwKahwACCCCAAAIIINAgAScECQ+zQkYG2wD04ed10Q3ubBPfOajOfIAXDOhseOWODrWLSBM62FUIqioCSNtGPzizI0Xd13+wsxBOdx2UE6WUN+M9s6Fnz/e9N4o/Dn2jOGLPDVjt/tuQMvLRDYAndOTLZv+K0zn7m5s9rz350HZTIKSy7Vv7l04A7Sw78Z1iiLq6T+5dXi+9XAjpcuv6dLYUXjoLhjy124ocMRzo6wkd2VwMFru96Z6ddZ/vLfh1H6+cplqa0rG8iRcK2v5u79ZAWFY5O6Tdqwrb7j7ufOCDQfWY11d2qn/EaUTUU7udqOnPQ+s4GNSGHzNFl1QBcDJPjR5UZ35q7/XqO+Pse9Q+mtcnhrT74WKbirWaW92tvsGx/BTblYvafezQnuKUwP5nLh1YXzjOAuG4/yn35/KXGYL1ZbfVru5Xw/cn9BhUeXR8aap4SUNfL+xn+DnGbY/zxZJm9P/EEW0zofqDfTofOI6KbfrRnsKXHtwvgKQ8l3l7l/DHy9p3lxl1+1AgqDQLX95/dz7kXPLgK4Hws7Diab3yYCEcXLKit2KEbP4zdhSxFwAXpptuU9tNG3XCBq5uay/3K2eCVz/o/d5DhdDVfz1BAKzQZcv74Ae8tjkX9hQDSWd67Px7diTvbcFRynY5je3T3fnweHlpWu3SexFPSqGyt3+pAuDpE9poRnOHBbZh2/3RTt1q2hn1eRvWmumWA3VQtkvb/2e6TeC8RPcftMmv27Bp9X/O/+LBqPatMK/dEP1lBHcVPEcAAQQQQAABBBBYUAJZhbxx6yEAXlAlQWMRQAABBBBAAAEEMhOwIVhkiBkSANtl3OA10KByqOOGMzZgdF9zF7MjeoMBkRPU+NuzQaw7EtK2rd2MmI0YlepstFqbStMR+9t21pHoqR3NF7We2Rkd21EIr1yfSBO70dL+hvST/UzCR2sRHmq6YXZhhfbzUeG5dLYQ1K7s0WBY6KUZXdxbGPkd7HM7ujN6n+y23eXsyPTE97u1dlF9EhEyJuSs/FiV7dl9ivasXGXiV2YndPHobq2394+2QfC6PRqq+KbEWGkaZbcWA9v6YEDdxVHCSdtr98/tM7NO+3rktuxxHuin8jnGndbbHi/t+RHgl0ozEwTabn+o0h/KsP/tyGR/321TVJrS2ql5276E57LSutI8KQaAN252x1sWV1AKMUOm2C1Nv7xcOypn+i+s4M3ivXwDAfAF7fxUYSrf3IthAaBZtDii1wtCZUPXFfsUvE1s9RHAocvaoLntbu2LHEpfnB67rU2f2ets1e6b38aS/ah67yjs58ZXSy/GP7H7560zTQBsQ+TQ/gzZuh1ZG/d5+0WAtiUbyyNta+7/oueS6NHaF75aGOntjng+8UjxywafvD8/SjlkV3gJAQQQQAABBBBAYIEKxAW3Wb1HALxAi4NmI4AAAggggAACCNQpUAoZnODBXeXMTOUoQbtMIJBxFwoPZ2zQE5hOubSYHQ3aLjfQyb8dtT0bDAVGWk5p8En3Pps5dWzeo2M/qUi58qu2baoaPrkhc6nNKZ7YtkYG7eURmm5bbKAVGRxZm5U7NZSiOWEftRapA+CQ7Ci/ftu2BPsc3L/kAbA7WtyO/nT9wvaz9JptX8o6Li2f9kmV7Vn/xO1Pu33zeTO1+at7tKmjXG/t9/Vo0BugXb0t5ZA42HdmIzMaO3NQfT2btH51h1aZEctODfifr7ote+wEjkF7jvG+mGCnHLfby5mp3Y/pYtjhX6U/TADcv67Q9opzUkp7u4+uQ/hz9zyc7lyWskn5jw9uLkytW3Ef1uLUx/b1u/d7N1k9ubEwVa8bCvoNsCGpew/g0X36TH7dn9E+J08NLloMdL17AJdC3ECgbJZMEQC7y9rA9baIEczFRg0+WpwG2V3W7psX1pb3wwbAYffcNV9qGtS+rz+k3B3Ltfym60rTSee9vXWmCYBtW5OFzraNbXroe+WWVzwr9dnt6rX3J661/62bV1+2ztxHNwDWcG9punHzmSUf+4w27jmh0eL01hVt5gUEEEAAAQQQQACBBSOQVcgbtx4C4AVTDjQUAQQQQAABBBBAIFMBG4K0u8FDlS3YZaoGZ8Fwxo6C8+8HG7gHsH8/WNMUe09Yf3s2GAoEwCbkmtBQ7/rSfUpt0NLxlSO65I1EtcFMZOgWtY0qRBVv2/XYYMp7zHV0qGN14d8eJ8lNHAD7NhUNqP6CtfADutKSae1snXj7avsjd195n7cddofgJQ+A3X6z7XdfK7U97IltX6SdDQCDdRy2qkSvVdle6vYn2mjUh2Y09upOrbX3+t0xEPiiR5K2DPQUwtFAvUxVTjdt+9s+Bj6fZgRw4DiP6ZuJIe1ZV7x/s609c3/hw5eCGFX6oxwA19//1tMaBB5X5krHfsfqPcEvcqQ4lwV3LsFP06/ooSWFUapu8Bb6/I+8qY5teOqFlYGt2rDP/Yx9rS16BGhkoGu36Qax+Q3WGQC77QvsQOEHG8C2udu1+xG5rA1XndA0v7ppDW4r3uM4KgT11nnhq8vzAXEgEA1pp3npxCNpRh3bNrYpPjC2vs6+2L7w2hpoVpiRfS1i36+7abmWf6rw7/5ved8QGN6n+z9ZDOPt8tffrh2nokaSB1rDDwgggAACCCCAAALzVCAuuM3qPQLgedr5NAsBBBBAAAEEEECgwQI2BGlCAKzZS6WpZQMBiBPS7PSHIprdt+GpH9TZ1wPBkOM1cVHHejepwxmBuKpnQO5gRxvMRIaG1bbhbC72qV1Pz0Dsx/w351UA7DWuqp2trah7rHrrK/9YXwAcuC9weaWVz2z7/LoqfTImZCx9JsWTKtur6pliU0k/OvX9Hq3KH3/BL4BUb0v5Hrxlb+f4frhH/d8/r7GJqVKwbNfZ8AC4uPMTPzmmPZs7nC+CrFLP952jv0p/NCIATjpddkX/JTiXVSxT5QU7te/yr16I/mRpqt8bg/dftQGgP0rXXZMN+9yQ0L7Wdn/FPYfLi9rA0QuJ7TbdIDa/UMTnyytU6Ohhu76EI4Bvf9pxsvvh7pu7Pdlw1QlNzcDfvcV7Ci+5VQ/teUVnRi9r2o5ite3x1mlD3TQBcPj9dQMNNK0pTVOdbATwQzphV2HbWmv/VzG3mwl7HH21Vxv/zQ2FEej5IPh29Q6HfZLXEEAAAQQQQAABBBaCQFYhb9x6CIAXQiXQRgQQQAABBBBAAIHsBWwI0owA2LR+4pi6czmt6nBG6H2uQ51P9mvw7Znw/bPhqR/U2dc3H1HYDK+llc1O6OwL24pB1yYdKX3YBnztShUA2+3a4Dry0Rk5aEcxr+rR4AelllV9shAC4E2HS6DB/Snd19RxCH4i4qfaAmBr1d51ML4e7FZtP/p1Zd8vTQHstr9cM6FfYnBrwf9igj3WIgJxG5BGepbaleUTa92p/rfL67VtiQws3zmozvy+Oja2xh/s03lvtLhZc2md3pThUa+XWmP7KeBp+2GVdp8pfTL8ycRZ9X+5OC28e66w621C/5/f25GfBnvVk4OlQDy8sVVejTyXVVmu4u0L2vlHZrTocu38UcWbzgvTeuXB4v1X3eD11FbdmA/f4u6fe0IPmc+4gWbpvrteoOxsUbqg3ttM2yIC4M/2KzghtQ2AQ+5VbNdrA0t32dI+BENau0jh0TotCY6SrSkAtvc/vjXc3LbRdXZG9SYJgEujle/a5xkF96rw02X1f7YwYniJt03309OHHyqErW4/luxS9n/pCwVx5u7WY56PvqKNny7U5o3bvJNKzGK8hQACCCCAAAIIIDC/BOKC26zeIwCeX31OaxBAAAEEEEAAAQSaJWBDqTQB8MjzWmvCn6rBiR+sFkcIphwFW3UEcGQ7XEQ7YtEJrEoBn99OZ7mwkMi+5oZ9oc/dbV1U34OFKXNXPTmgiZCAzNlq6emlA2vzwZE/arL0gYj+u/TdbepY2a5cV3/FtNelZb0nNoiL3Fbqz89oYEfx/q+dz+tiRL7vrVaaHVBP3jM4KtX9XGhbS6Fkuzpf8Kb7dRe2z20/RtaPDRnd+ii/VnMAHHGshe6Tbat9HD2ibeb+vblO9Y/YF+t4nDqmbcbau4d0fFumNNBTDFTdsN16BoLacttsQO8H3HYq6apfwgj0U7kfIpcrb1oKO2fZ9gbW6y4Uto3ya6n6/2Jf4ZzZbkYhR3xhwt107POQc9nsJR35SiFk7vjGUPWQ2QZ4cSM4i22YPnh/4R61Sx5yRu0OausnCuHhjV84ofBJeEMCYF3WvrsKy5lg2BlT6+xxlQDYDSLzS9m2xITKNlwNLGuXa1PUPph9X2JC7E9sVSBiHO7V7X647eyBO7q2PL2yDaq9YNsuZ0NlN6ROGQBrbJ/uzgfzS/SZPeG6dnPm0Y4Cb2uLGkVrA/A2Be8DXd3OTOVd8QUAOV8oWNGrC3b0s9uoNM+/91ChNt0Ae8pOAZ9T58sJfg+k2R6fRQABBBBAAAEEEMhcIKuQN249BMCZdxsrRAABBBBAAAEEEFgQAhEBYrntM5qamNCEM5VrZCBbWsgGFG5wJunt/sKowfu6dezihKaSjoS1Qc2q3Tpb2kbE1NA/2K31ZjTxxSnN2JB1ZkoXj3YXRgCv7NGgfT1JAPz9nnwAGx12uw2q8vzM7uIo5Hbl1u3WsfNjmqoSisYHcSoHW4FQ8ax2ryoGr+3t8gO3qFZW3Za3YKLPv3NEm+x9Zju2qW/wYvV+r1qTkg0N/bD60gudhf5qb9fanoM6+3Z5CmKv+dFTi5c+GFHHpfdTPrF1HOir8jqSeJ79ZjF4NaGtO5q1vJrAs5lXe7S+u69Qa87xNjM1oYuDfYUwub1dq74ZOLJKo3XbH96pAXMsFdc6M35W/cWgsb19rfrOO5uz9b1qk54/M1FeZmpM54/u1vriVOzBPisHqpFBbugxGL7c0DfXq+eFQV18z7ZYMvcYP7aj6OaG07Y/YgLg5x8uHEeRbXN2v9rTct/ltP4bx3Q+rjbNytKcy+y+VPnihG3j4OYb88FZopGTpVGbbcp9qzz2tjSdcdsSLf/CPp0p3cZ7WpeHT2jn524uhHOB0FWaPrlRN+dDyjZdd9cOnXizHB9Pj55R/6P2HrleUBoa4po9mtYrny+OZF2xU4Oldti9VXkKaK8tkftw7bIG99yv5fl7JN+sja+W25hfa2Rb7DZtiO3eX9eGpjcq9/SgLtvw89q0Rs/2a+sd14V62SmgE/WVpAt7itNMty3RrQ/u0+Co13bbRPM4PaiNNxUD+evv1o5XR0th/vSbr5TatMSEte5y7nTWKftfY/3KFe89veST92vnqxd0OaaJJkzf9/m7tePFMxp9r9yI6bFB7VxRGAHsjo62XzTJf0Ej8tgur4dnCCCAAAIIIIAAAnMrEBfcZvUeAfDc9jFbRwABBBBAAAEEEJgrgVLYVg4Mw0e2OaMxbdgQeXHVTivrBcA6rz33xW0np1WrO9XzwpDGSiGtE/T6wVlIO8ZeLAeAYfvR+aI7Iig8RHK7onQxOXJf3U9Xfz52vCc/MjesbYXXejTg7HvVUNAaBGyGtNOGru3tCgZu0W2suq3AomOl+zlXW//Uj/rU6dyHuXLf1+p5dzRrqSadmgtsu9xvldue0tA3C6OmK7fTrnZ3+mVrF9m3UXUcaEzyH+z2An1lF0/mOfR15/iJbLddp1QOHZ3l8iFh+eewUeK2FnI5Z6r2wHKrtO2weyyZbTr3AA581owwXqttXy70S8deNzUu92VUyBp+DIYtVzYM7fuVneofLdtU/yJLxv0/O6ZjPYVRuqHtM2bO7AhpzmUzx7tLX3xo90ZzO3tceDr9ih7KB3DetMYVH7QvXC5NFdwWGJ06qn4b8hYD3bbS4xItf3SjcuZnf/SspjXYbUPeYvhYWs6Ewhv1UH4KaG9K55jQtTRNsbOeNnd0c+Sy0xrcFt2WtiXLdf+3/OgzOlC2Ymb068ZiW8ojgJ17ALvtzD9folvvzelW89xttzMCuM0d5VreUMizKvvk3393uF85GwJXtKtN192xQ4NO8FreYK39L02f3am7r6/s+3L9uCOSB7WxGBiX33eWvWmjBp0A2U63nj/GOvsV9n2A8j7wDAEEEEAAAQQQQGCuBbIKeePWQwA8173M9hFAAAEEEEAAAQTmRsCO2vMDm4qfnTDOBlmRAVREcDI7ofMvm5G4OeU+Vw6gQsOQzn7ZeKkchDhtMHHTC+srRudO/OB5dXd1qOM+J7hamVNHV4/6f+BfCg4LkYLdELaN4Cdq+Gnioo71btJ69z7I7e3K3deh9d1HSvtt1myDuMqgs7hd2xdeqHjpxU7lin3Yfbw8GjK6tRM6srnQJ5HbCixctkv0+ZkxDb7Qo87Vq0rtyvf75zrU0dWns87oVNUVABcaOfGTY+rr7gzWgbnX9DeHyvcHtnZp6zjgkOIHuz2vrwprSOg50l8O07uPlUbZRrViYrBPPZvXBx1srW3eqf7BsdB12Lrr+f6YBr7RqQ57vK7Mae3mPRqIul/3zEUdebJTq2zgn7+/90GdNbMe2/13Qs58aLyuUHfpAuCwc8yEhv6yW52rO8rbN8dA8R7jQ+Oekm1Ps/q/uHlTm3tMn1jT/HFqvvyyXt3ftWc9KdW57IMh7TZTg6/s0DZnHd4e538sTencdr8zpXPYJ8uvXXj69sLo1DYvlNW0zuzfqLs/eUNhquS263TzHTntOGySdhuCeiN5i6u9/L0dyt1xs64rBqA3fPJubdx/Rpc1qt47TMAXvE9s6f623ihe28rRw1t1903FUbRLbtDyB8v3Cq627OUf9WvHZ2/VDXZk6seW6+5HenXC/cKA3ZB5jAyU7YfsvrsjgAvvXXhxY7Cdd23UviEzstou85BO2NWY0a8rimFn4gC4sLDZp52fv1vLrUlbm5aY/dp2ovL+wNdGdWKP0y7bjy9eqPxsqW3mSe39L7vNT9kaKOynaePyu3Y4oe4F9X8hp9s/tbzUPyYIvu6m25Xr7tcFP5wePVg4R+bWq+9Mkt99gR3iBwQQQAABBBBAAIEmC8QFt1m9RwDc5E5lcwgggAACCCCAAAKtJjClwSdXqf2+Hg1E3AJz5r0xnX1hW3GaZPf+ua1mlcX+2mmgO3XwnSzWxzrmi4Ad1dv5nYgDKYOGlgLgwI1PM1gxq0AAAQQQQAABBBBAAAEEEECgKJBVyBu3HgJgyg0BBBBAAAEEEEAAgUYKnO9TR6LpiO1ISALgurrjYp/WmpGFOwZCR3jWtW4WnkOBi+p70Iz07NaAO2o64xYRAGcMyuoQQAABBBBAAAEEEEAAAQQqBOKC26zeIwCuYOcFBBBAAAEEEEAAAQQyFChOt7rqycH4QHJqQD2r2tW+areGnHvhZtiSFljVTGG09cpNOsLo30XV3zODPfkR8psON270rwGzAXCy6cMXFTE7gwACCCCAAAIIIIAAAggg0CSBrELeuPUQADepM9kMAggggAACCCCAQIsK2BGp7e1a+/VjOv/2VCAInnnvos5+Z7fWF+8d2uiAazH3wlQ+JFylnsGpxbybrbdvU4Pqua9d5ksUje7ZgZ4094Nuva5gjxFAAAEEEEAAAQQQQAABBOoXiAtus3qPALj+fmINCCCAAAIIIIAAAgjEClx6oVPtZlriuH8rO7Tt8KXY9fBmnMCMzj+3TT3Hx+I+xHsLUGDmfJ+29RzTWMNHxttp2Nu1/gWOxQVYKjQZAQQQQAABBBBAAAEEEFgQAlmFvHHrIQBeEKVAIxFAAAEEEEAAAQQWusDEDw9q5+b16rgv5wTBOa1a3anu547pYmNntl3ofLQfgSYIEAA3AZlNIIAAAggggAACCCCAAAItLxAX3Gb1HgFwy5cZAAgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg0AyBrELeuPUQADejJ9kGAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgi0vEBccJvVewTALV9mACCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQDMEsgp549ZDANyMnmQbCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDQ8gJxwW1W7xEAt3yZAYAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAs0QyCrkjVsPAXAzepJtIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAywvEBbdZvUcA3PJlBgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCDRDIKuQN249BMDN6Em2gQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACLS8QF9xm9R4BcMuXGQAIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIINAMgaxC3rj1EAA3oyfZBgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIItLxAXHCb1XsEwC1fZgAggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEAzBLIKeePWQwDcjJ5kGwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg0PICccFtVu8RALd8mQGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALNEMgq5I1bDwFwM3qSbSCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQMsLxAW3Wb1HANzyZQYAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgg0QyCrkDduPQTAzehJtoEAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAi0vEBfcZvUeAXDLlxkACCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDQDIGsQt649RAAN6Mn2QYCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCLS8QFxwm9V7BMAtX2YAIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAMwSyCnnj1kMA3IyeZBsIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIINDyAnHBbVbvEQC3fJkBgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzRDIKuSNWw8BcDN6km0ggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDLC8QFt1m9RwDc8mUGAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIINEMgq5A3bj0EwM3oSbaBAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAItLxAX3Gb1HgFwy5cZAAgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg0AyBrELeuPUQADejJ9kGAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgi0vEBccJvVewTALV9mACCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQDMEsgp549ZDANyMnmQbCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDQ8gJxwW1W7xEAt3yZAYAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAs0QyCrkjVsPAXAzepJtIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAywvEBbdZvUcA3PJlBgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCDRDIKuQN249BMDN6Em2gQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACLS8QF9xm9R4BcMuXGQAIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIINAMgaxC3rj1EAA3oyfZBgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIItLxAXHCb1XsEwC1fZgAggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEAzBLIKeePWQwDcjJ5kGwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg0PICccFtVu8RALd8mQGAAAIIIIAAAgggvw+IFwAAIABJREFUgAACCCCAAAIIIIAAAggggAACCCCAAALNEMgq5I1bDwFwM3qSbSCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQMsLxAW3Wb1HANzyZQYAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgg0QyCrkDduPQTAzehJtoEAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAi0vEBfcZvUeAXDLlxkACCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDQDIGsQt649RAAN6Mn2QYCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCLS8QFxwm9V7BMAtX2YAIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAMwSyCnnj1kMA3IyeZBsIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIINDyAnHBbVbvEQC3fJkBgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACzRDIKuSNWw8BcDN6km0ggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDLC8QFt1m9RwDc8mUGAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIINEMgq5A3bj0EwM3oSbaBAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAItLxAX3Gb1HgFwy5cZAAgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg0AyBrELeuPUQADejJ9kGAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgi0vEBccJvVewTALV9mACCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQDMEsgp549ZDANyMnmQbCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCDQ8gJxwW1W7xEAt3yZAYAAAggggAACrSFwWnpgafnfM6dbY7fZSwQSCXB8JGLiQwgggAACCCCAAAIIIIAAAgggULdAViFv3HoIgOvuJlaAAAIIIIBAiwlcGZGO9km7Vktdd5YDRRMurrlV6loh7eqVBs5JV1rMZl7vLgHXvO4eGjfHAnN0fLxxUtq/pXDeXOt8QcOcT9feWTyf9kiHjktvjEuzc8zE5hFAAAEEEEAAAQQQQAABBBBAoG6BuOA2q/cIgOvuJlaAAAIIIIBAiwiMn5R2rAgGvu6I0qjnXeukgWHpWos4NXU3x6UtXmg0FNWAOQq4oprD6wjMK4EmHx+v9Uqdy9KfTx+4RereLg2NEAbPq/qZT43xavmBe6Wfzaf2LYC2vLal8thcs0W6ugDa3vJNpP5bvgQAQAABBBBAAAEEFohAViFv3HoIgBdIMdBMBBBAAAEE5kxgdlzam6u8GBoV+Ea9vvYe6dTknO1GwzZ86F7HZnvDNhO+4lYLgL0Lu4fGw1l4FYHUAl5tNWqK9NkR6Ws1fJGm4rxKqJe6ixfUAl49pjrXecsSAKfs+avSUxFfzjhJApwScw4+Tv3PATqbRAABBBBAAAEEEKhBIC64zeo9AuAaOoZFEEAAAQQQaBmBK8PS4yEXQs2o3qPnpMnJ4Ci0K5PSG6el/i3SwyHLpbqIvUCUCYCb2FHehd3FWE9N1GRTroBXW40IgE34232L84URM3r/FumJXun1kcop89+359PtUpe/HAGw23uL77lXj6nOdd6yBMDpymPyiHeMOrNsdL+Ubl18eg4EqP85QGeTCCCAAAIIIIAAAjUIZBXyxq2HALiGjmERBBBAAAEEWkLAhBV++LvmHum1FKMuh/qC05ymuoi9QJQJgJvYUd6F3cVYT03UZFOugFdbjQiAD7uzBSyVNnRJI24bqjx/d1jae6+0xgRSBMBVtBb42149pjrXectSK+lq4ehqJwC+R3rM/TLbaunddKvj080WoP6bLc72EEAAAQQQQAABBGoTiAtus3qPALi2vmEpBBBAAAEEFr/At+9xLoIuldbcK43WsNtmCulni+tKdRG7hm3NxSJzGgCn2WHvomgjAq40zanps94+LMZ6qsmFheoX8Gor6+Nj9py03hlJ+MA90hs1tnrynPRkF/d1rZFvYSzm1SPnuiZ1m3dbBTPi178fcH+ab200qdlsBgEEEEAAAQQQQAABBBacQFYhb9x6CIAXXFnQYAQQQAABBJog8LMDwfD3gTuloTrvfXeqRzqcYvRwE3Yzk00QAGfCmGwlhCLJnPhUegGvtrIOgF9/KnhO3XU8fRNZooUEvHokAG5O34/0BY/To+Y2F6eLo+6LX+D4Ul9z2sJWEEAAAQQQQAABBBBAYFELxAW3Wb1HALyoS4idQwABBBBAoEaBvbcFL4I+d67GFdWw2Pi5wj2Eu1YEL7puWCHt6pNezyhEnr0qDR2Qnsg59yteJnXmpP3HpcmEbV8MAfDVEelQj7TFNb9F6lotHTotXUto0fCPZRyKNKvWanEZPS3t3yL5x8HaOwv98qw5FkYa1zdXJ6XXT0r9PVL3Cqnz1uA5wdy71rRtV690ajibdlyblAb6Cttba0fLZlCHk8PFc8qdzj6Y9eakZw9Ib5iD3autrAPgoe3OtpdKWa+/lhpr1DJvnpSeXResmYdXSE/0SK8nPbHGNM70p3++WnOrtKV4b/pazlezk9Kp4u+DDc79lu16D51M/jshpunJ3/LqcS4C4Kx+R4bt9BvHpV2rnd+9SyVTI91bpIGMzidh26322rdXOMfpunKfB/4muk16vdqKqrxvzu/mGHFrzZzbTQ2b37l1ft9O9lwa+PvGzORSPE6yqmczLX2/+T3lnFvNfnRvl4bq+FttNObvwCe2S0fP1W8U1UX5fdru/T1UrE9zDjO/72ajFo553dT80+uCVg8U12v6fb/5XTRe27pjNstbCCCAAAIIIIAAAvNXIKuQN249BMDzt/9pGQIIIIAAAnMjcPVkMHh9oEn3vLsyLH3NvfhqA6CQx84uaTjJFVLvIroNXV57Knjh2VyE8/+tWSEdi5rq0Zsm0l826mf/Ir4/0tp93wQSFWFY8b6h7nXVxAF0iIXZxqEur79DLNbmpDPVghvPZMuB5PVbbR/88CzKN/D69ujtN6LWsuhL0+J3TkpbnAAqsE8hfWOC2D0no/e1lnf8fanahqWSqZEk9wf3121qPl+HW6RS6Bu2n8Vt/DDJcV/caTP9/N5c5bEdtj+d3rnHnitq8Qtbxq/hrNfvbtPf1pD7Ztxz7xzhno/8xQLHbPF+xOMJa7e7T7rir9D7OaxOriXsz7WrE/5+KG7z1FPVay9fM7dIe08mC2jCfOwuRn0h4WtHJL/vwmq14rWQc90zzjEUey72+tzWZd2/I+3Oeo8jL0md7j11nXa6+2V+/37NvWd2E+557U/T7o7S90fw763xS3GTpxOe32+RdnUFz12JjuOryX6n23ruP1e9nsNq2UxDv8u7TYjbf/b5lt7qx7pbIma9Sf8ONL/7nuiV3L+H7LoS179dQFKavwvMOebH1f4mKq57+ECymrdmJqR/OepvT6e9PEUAAQQQQAABBBBY8AJxwW1W7xEAL/gyYQcQQAABBBDIWMC/AO1eBM14U6XVvXNc2hBxIdheFKt4vFM6GXblr7TWylF9T/WluLho2hM19bUXdla0LWJf/EAlLOQwzY8NJLwL4YGLsyFBQInDu9C/Y0u6i5KRFnYDnkls6GCXKT5W2we/JhN5R1g0qtay6MvRA9XD+LB9T2Pt0Yf+6O9L2DZDX1smHapy4dpf9/6XEgYixWMq6b3IzcX8xxMETaH70YARumd6gmHO+qeqBy+hnZPgRf94SRQcmfV65wj/fOVuOnDMrpCeXh3cvyhX+/rjB+L336+TXdsThrRp6uSq9G03ZIw4b9s228fHEwTYAZ/iObvaFxLMcez3nd1m7GPIuS5xAOb1eWa/I91iKT4/5Y2Cj90nvy+833shq6/7pR+607Qvk15zv2wyLHU5bVqzPb5+wxozUuP53TpVO45nR6QnnZG4drlqjzb0D2uzeS1QyznpcG+6Y7HasW63O9yXbr12v8Lan7j+ixsfPVLb36DVbo1S0/HcgN8/1phHBBBAAAEEEEAAgXklkFXIG7ceAuB51eU0BgEEEEAAgXkg8Jw3/fOxhKMcam361dOVF962PFWY3ta9/jo+HDKaLyqgtY3xLm7bC4bmsWtdYapJdySa2caz3qiWDWFBjRd2uuuNe+4HKn7I8R9PJgiovQvhgYuzIUGApfDDnVI7l0k7eiu9R05XtmXNOund0gq9J55JmlCy2j7UdBE1xKKRtVZvX5rRZ4EvQdwiPXNAGjH3oHSo3zdTMx8vTB9qR8ymsXZWFfnU3ZeH75X6XypMTekej2aKaFMjz/gjbO+R3ohcs+Suu1SDJlhZJm0z04aOlKf2NFPQmm34ocYTR2I2IMkEIX742xlyvF8z6y9ONfqwFxaHhQrxW41/9+rxyoB07+lg38avIfm7/vFSLTgqrdk7X/rnq9Ln/FDICcbMSHAzvey4UyxXx6WBkFG2cbcWiKyT4nFhpkq1Uz2bOjHTq/oj50PP3c5OHPbCXzPqtN9v+6Q01Ff5ZZlqoVbgnHav9FqCka/zIQB2j8m6fkc6zuapP4LWjN70z2+mHydHpKO9Upc/C4L3e89bfSY/PuOcA9ZsKZ+H7Mr73b8N/IDYfiji8d0j3pd7ir933To2i06OF6Yi3+ZPub9Uij2OJ6VdXvhrZkox0xW7f+NcMcdir1fPVb64E6hl51g3I1X9PjS/F8zxEvhdtkyq9ndk2Jefov4OPOR9GSTsXJ0mAH7X/wLiMulrfYXfefYcY/rG/H24f12wH+O+kOT3uTm/mNuLuOdG2+dnXpJ23Vted9g+RZQWLyOAAAIIIIAAAggsXIG44Dar9wiAF2590HIEEEAAAQQaIDApPeFc4Hsgg3vdVWvlc+5Fy2XSt4fjlzCjRNY4bdzQU3mhtrQGL9AwF7erTlV7VXrGa1PchdfAxdGQ0LHUlpAnkSGHs3/uBfn8c+9CeOLth1iYC6zVBlEH1r9Uipz6soEBcInO24e4gKq0jPOkkbVWb18eW+cEhMukgQRfvMjfo9OMan/J2ckMnpp9MbWRvzdugvW95o3si7t4HeZkgoq46TQrAl3vGPCb6Ad73QfKYaH/2dLPXm3F7UNpmZRPAvcRLR7jYSFbytVWfHwuAmATbhw6F+88edILhmJuL1BRJyaUORDzBRQT/E965+6l0tGI48gPZzZskd6pkCy/YEbvPuX9Xjgcc/L0z5sV5/GQc3zgixxePaY91yUOwLztNOJ3pP/lFlMrpyL6pSwu/Uf3yyVVjnl3uVqe+7e+CPs9N9LnnKOXSolnRzF/Vznhsgm/q82UYPbhtS3B7cX9HRI45y2Tnqvy5ZJr3pdkTODtBsWuYUUtF4/FuC70A91AbbsrL35hZ4t7PCyrPgWyvX2Fqdewc3Xi+h8PfllozT3Vb3fhj+SOqoPAlynvkar8aZtXyd+7+SnJfDmI/xBAAAEEEEAAAQQWvUBWIW/cegiAF30ZsYMIIIAAAgikERiRHnMvxDX4ouu7LwUvcFYb2Wd35aR3YTTqIr8/6nVLX3xAYdfvhw9xoXTg4mhWAXDx3nb+6CDbPvcx8fa9C/1PHnfXEvN8RPqSUxNhI6PyS8/zALjRtebXTCnwSdiX7gXrB1LWUUzvNeetSanbqZGuvujN+k5PJ7ynqh9qnnRGmLpbM6O81zttif2CiLugd3yEhQrux2t5fiVktoNSnSyVHl4hdW+R9h+QzgxLkxH7WG3bvlVccBRYl2cQFzoGzjsrpB8HVhT9g3/u7o+YMtyvk/0J77l65XjwC0JfiqjFQBh/p/R6dJNL78wOB8+FcdN4B3ycelx7T/gowNJG7JMUfWEXcR/d80lc+Nb035HLpLjg3N2HgGGD/xYJ1OVt0g/dhtjn3nnugXVSXAhqF/OPx2cThnv+clHHsR9eRwWStj320f+dGPV3VKAfbpNeS7LTktwR1Q+EjKi27QjYRwS69rP+o7mn9P4Qz6T1HwjZl0lRv1f87R51p7wP+yJLHX8P+dviZwQQQAABBBBAAIFFKxAX3Gb1HgHwoi0fdgwBBBBAAIFaBLyLzo0OovwLi6EXXcP2wwsloy7y+xe3E4c6p4Mhggmpov4L7EPK4M4POUwYlGRUrtuWxNv3+jaxhaTAxc5lEVNR1nHBs9Z9iAuoXCPzPLCNqAv8/kLm54S1Vm9fuhesG33che1mva99e4XzZY6Y48B3StqH496XRV6OCA4DYUKaaVrrOD7S2Jl7UHe6owGdcNANg0vPb5G2rCtMqxw5/brXgKTBkbdY7fcAThHOmdGgbkAfFU7WWidmnwLhbkjbZr3ze3eKEfR+YBS4T6wDGjjfmD6+Rdp7MtkXkPKr8eox6XFim+CeT6KMw7aT+PeCZxj5O9K7d27k72rbcOcxYBjSj85H63vqBbsm2I/6L/C7MGaEeWn5q9Iu5xiP/AJVaYHyk6THcWD2iLAwsrzK4DOvbVFfwKu1HwKjknPSaHDrhZ88+7iRyGGLR72WqP69GW/SnAf8Kf0rpriu4++hqH3idQQQQAABBBBAAIFFJ5BVyBu3HgLgRVc27BACCCCAAAL1CHgXnRsaRHkX3+IuuobtUiBwujdiKmNvfxJf3E5x8S5wcTQm+ArbBz/kSDrKzV1X4u3XaiHJTOdYCqSWRkzPmMLMbb95Xus+JA5FmlBr9fbls24omHAKaN9xLn9O2oe+U+I+TFK/XqCxZnuKe+wmWX9GwPnpS7dI9h7O7rEV+zzB1KumiUmDo4rd8Qzi+ibQ3ynDuaedQMz8jnHvcW3bVHOdSDrlTUl+yq60+Ojfj7YivPE+7/7oBz9RozkDPilGSJe2laIvSss4TxIFYObz3nay/h35hjdtclxNOc3PPw0Ypqwxf11xP/sjYeNm/Jg8EvxdGBuuS/LrJbFv0uPYO+clHf1rPdyQdk2PfTX4WGs/JDkP+Z5p2x9safmnJPXv903S0b/5rZipo53zWMV5wHv/gYRTQJf3gGcIIIAAAggggAACLSAQF9xm9R4BcAsUEruIAAIIIIBAcgHvYnBDA2BvW5EjiCJa71/kD50e0dtG4ouvKcLMwMXROgPgNBfHLUvi7ddqYTaUZNkUZrbt9rHWfUjs5bW/EbVWT2BlHAIjC4sjBp85II1Mhgdk1q5Zj+PD0qnj0v4e6dktUteKwr8NtwQDkXyAGXMc1Ozk9WHoseyNLo0a0RZqlmT9oQvW/qK5h/MbJ6X9RU/33uZxQbC5T+UPY6aHThK8hLbaM4g7vgLHbMpwLsmyNdeJpGrLBrYfNTIxFKgwI4B7m4SoADCwjZQ++U2n6IuwpiYJwMK2E3pchW0g4fk+MDr1tmRTbdvN1W1oV1Tlsf8e5xx2T37Sh+glvMDVBHsRkxHk11HPlw0SHcfeOS9qZoSoHQpsI2JK61r7IbDupeEzh5zpceyXJp8ePGp/7OtJ6j/QN2nPA2aKaycADvtdE6irpZK59/X+49J4zLnbtp9HBBBAAAEEEEAAgZYQyCrkjVsPAXBLlBI7iQACCCCAQFKBkHsAjyddNuXn/Cldn0t4j0e7GX9UamhY4V1Ez/ritmlL4OJoTPBl2+0+Vgsq3M9GPU+8/VotzIa9i8yPh02ZmjAQCNuPWvchtM9DNtCMWqu3L2dHpC3OBeVAAHiL1LVaerZPOnVOer9JF5DHT0vPrK5hpGrMcVCzU4L69UeTVYzKCqmN0ksJ1l/6bAOfvD8pvXFaOton7VotPeyODHfqY01MqJgkeAndBc8g7vgKHLMxbQnbjj9N95mQD9VcJyGjLv06CIy2jwi9QppUeskfwVx6w3lSj09+NSn6wtls6akbTkWF1GHbyfp3ZKKZOkqtDj6p2zC4uvCfvCn+Y62Ka/C/rBM3YjhJrYc3LNlIfv+cF/i94ZwvEr0ecRzX2g9JzkOBLwhEhMRRPnGvJ6l/f9uJjCJMw+rmysngdPfu+tfcWpja397v/UrczvAeAggggAACCCCAwGIViAtus3qPAHixVg/7hQACCCCAQE0C/rR1K6Q3alpR9YXqucBv1p5oee8ietYXt007AhdHY4KvMJFE+xC2oPNa4u3XamG2lSTcTfIZp93u01r3IS6gctdfr3OS5ZN8xm1T2PMr56THIgI/9+Kxef7wPVL/6RT3FA3bYMRrs+PSs+6ouIiL3n6bSj/HHAc1OyWo35rXbRwSrD+Cq+Evj56WvubeY7nYH09F3Js8SfAS2mjPIO74ChyzEcFR6DYSTm3byL50w6FaZrlIsnw9Pnm3FH0R5uy2MSycKi3jbSfr35FuO9Ja121Y2snoJ4FRoEnu6SvJv4e0uX1F2DTmZqv17EOS49g/Tkrn4LTnbPP5iOO41n1I0v7AupscAPvbrscu6hgbPSJtSNgXG1ZLA8PRtRRdxbyDAAIIIIAAAgggsEAFsgp549ZDALxAi4NmI4AAAggg0DCBwOiopVKa+yOmaZR/4TIubAhbb6LlG3xx27QrcBExJviqeR/CFnReS7z9Wi3MtpKEu0k+47TbfVrrPiStmUS14jbIe55k+SSf8VYb+qOZFvi1XulLtwanxoy6ON25XXondE01vnhVeubOym2bEUtPbJf6X5JOnSxMTT05KU0WRyMn7cOanRLUb83rNlQJ1l+jaGaLBYzNlKIR9+xMEryENsoziDu+Am2JCI5Ct0EAHMUSfD1FXwQXLPzkBq9R4VT+k952Wi0A3ntb5bku6lwb+fpt0g/DOsH/+6AJx0lkG5OEkBHtq/VYT3IeCqx7EQbApiyuTUpHt0uht0sI6ZfuPokRwREHFC8jgAACCCCAAAKLSyAuuM3qPQLgxVUz7A0CCCCAAAL1CwSmLFwqhd3brP6tSM2YlrfmUCdFmBm4gLlYA+DTknt/0tB76KYw8+snsaEXVsQFVO42mlFrdYWPbmOd51eL0wEf6pWeyEVPB7whZgSas7pET/3pTc19Cw+dqz4qKWkf1uzk9X1YUOWvO9X9MBOsPxFgAz/kjzyMGrGXJHgJbaZnEHd8Bfo7IjgK3YYfikXce9Pvy7i2+Nvxl/XrIPAlJ6aAlhsahh1Xvm/+54TnezeINiOAo0bKhm2jnhoLW5//WsXxFBLGuTZxz6NG4wf2IaLW/XbZn5Mcx/7vtjTHid1OtcfAPqQ41pO0//C9wQB+qFpjEr7v1l3UFyAC206xXwmbEPqxK5PS6yel/h6pe0X07RUa9Xd3aKN4EQEEEEAAAQQQQGCuBLIKeePWQwA8V73LdhFAAAEEEJivAhX3lFstvduIxnphw67j6TZyanuCC4feNrK+uG1aHLg4ukgD4KvHg9ah92tOGAiE9XJiQ68/E1/s]]>
<![CDATA[Pengaruh Kasus Pandemi Virus Covid-19 Terhadap Kinerja Trans Semarang ]]>
<![CDATA[Megawati Takary Putri]]>;
<![CDATA[Joshua TH Panggabean]]>;
<![CDATA[Djoko Setijowarno]]>;
<![CDATA[Djoko Suwarno]]>
<![CDATA[ G-SMART Vol 6, No 1: Juni 2022 ]]>
Publisher : <![CDATA[Universitas Katolik Soegijapranata Semarang ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24167/gsmart.v6i1.3480
<![CDATA[Tugas akhir ini merupakan pengamatan pengaruh kasus pandemi virus covid-19 terhadap kinerja Trans Semarang studi kasus pada Koridor II Terminal Terboyo-Sisemut Ungaran. Metode yang digunakan untuk mendapatkan data primer adalah pengamatan atau survey lapangan dan penyebaran kuesioner. Sedangkan untuk data pembanding atau data sekunder diperoleh dari BLU UPTD Trans Semarang dan dari jurnal-jurnal atau sumber referensi lainnya. Hasil analisa waktu tempuh aktual rata-rata bus Trans Semarang rute Sisemut-Terboyo adalah 1 jam 22 menit dan rute Terboyo-Sisemut adalah 1 jam 25 menit. Selisih waktu kedatangan antar bus (Headway) rata-rata untuk rute Sisemut-Terboyo yaitu 6,62 menit sedangkan rute Terboyo-Sisemut 6,75 menit. Frekuensi kendaraan yang lewat dalam 1 jam berdasarkan rata rata headway aktual untuk rute Sisemut-Terboyo yaitu 9 kendaraan sedangkan rute Terboyo-Sisemut yaitu 10 kendaraan. Load factor tertinggi Bus Trans Semarang Koridor II per ruas halte untuk rute Sisemut-Terboyo adalah 105,88 sedangkan untuk rute Terboyo-Sisemut adalah 105,88. Tingkat kepuasan penumpang pada Bus Trans Semarang Koridor II di masa pandemi Covid-19 adalah sudah memuaskan karena kepuasan berada pada kuadran II pertahankan prestasi.]]>
<![CDATA[Pengaruh Penambahan Abu Sekam Padi Dan Cairan X Terhadap Kuat Tekan Mortar ]]>
<![CDATA[Edoardus Satria Wicaksana Putra]]>;
<![CDATA[Ade Eka Prayoga]]>;
<![CDATA[David Widianto]]>;
<![CDATA[Budi Setiadi]]>
<![CDATA[ G-SMART Vol 6, No 1: Juni 2022 ]]>
Publisher : <![CDATA[Universitas Katolik Soegijapranata Semarang ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24167/gsmart.v6i1.3192
<![CDATA[Mortar merupakan hasil campuran dari semen, agregat halus, dan air. Menurut SNI 03-6825-2002 menyatakan bahwa, mortar didefinisikan sebagai campuran material yang terdiri dari agregat halus (pasir), bahan perekat (tanah liat, kapur, semen portland composite) dan air dengan komposisi tertentu. Tujuan penelitian ini untuk mengetahui pengaruh bahan tambah abu sekam padi dan cairan x terhadap peningkatan kuat tekan mortar dan waktu pekerjaan pembuatan mortar. Serta untuk mengetahui perbandingan optimal penambahan abu sekam padi dan terdapatnya kandungan lumpur sebesar 10% terhadap nilai kuat tekan mortar dan waktu pekerjaan pembuatan mortar.Pada penelitian ini dilakukan beberapa pengujian material yang bertujuan untuk mendapatkan hasil kualitas material yang sesuai dengan standar aturan SNI yang berlaku. Pada pelaksanaan pembuatan benda uji mortar ini menggunakan pedoman SNI 03-6825-2002. Bahan tambah yang digunakan dalam pembuatan benda uji yaitu abu sekam padi dan cairan x yang termasuk bahan tambah tipe E yang memiliki fungsi ganda sebagai water reducing serta accelerating admixture. Dalam penelitian ini total jumlah benda uji sebanyak 96 benda uji.Hasil kuat tekan rata-rata benda uji menunjukkan bahwa nilai kuat tekan rata-rata maksimum di hasilkan oleh mortar dengan komposisi penambahan cairan x sebesar 0,5 % yaitu sebesar 22 MPa, untuk kuat tekan mortar minum didapat dengan komposisi penambahan abu sekam padi sebesar 15% dan lumpur sebesar 10% yaitu sebesar 6 MPa dan kuat tekan normal yaitu sebesar 12 MPa. Pada pengujian kuat tekan lanjutan untuk mortar umur 2 bulan mengalami sedikit penurunan nilai kuat tekan yaitu sebesar 12,6 MPa untuk kuat tekan maksimum dan 6,8 MPa untuk kuat tekan minimum pengujian kuat tekan lanjutan saat mortar berumur 2 bulan bertujuan untuk mengetahui mutu mortar setelah umur 28 hari dengan penambahan cairan x akan mengalami penurunan atau tidak tidak karena cairan x termasuk bahan tambah (admixture) tipe E yang kemungkinan akan mengalami penurunan nilai kuat tekan setelah mortar berumur lebih dari 28 hari. Hasil ini menunjukkan bahwa bahan tambah (admixture) yang dipakai pada penelitian ini dapat mempengaruhi nilai kuat tekan mortar. Kata kunci: Mortar normal, mortar dengan bahan tambah (admixture) abu sekam padi dan cairan x, kuat tekan, mortar]]>
