{ "cells": [ { "cell_type": "code", "execution_count": 49, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The autoreload extension is already loaded. To reload it, use:\n", " %reload_ext autoreload\n" ] } ], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING: pylab import has clobbered these variables: ['clf', 'grid']\n", "`%matplotlib` prevents importing * from pylab and numpy\n" ] } ], "source": [ "%pylab inline" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import dammit" ] }, { "cell_type": "code", "execution_count": 186, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from dammit.model import CRBL" ] }, { "cell_type": "code", "execution_count": 187, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 187, "metadata": {}, "output_type": "execute_result" } ], "source": [ "reload(dammit)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 100, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn import svm\n", "from sklearn import preprocessing\n", "from sklearn.naive_bayes import GaussianNB\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set_style('ticks')\n", "blue_ct_cmap = sns.cubehelix_palette(10, start=.5, rot=-.3, light=1, dark=.4, as_cmap=True)\n", "red_ct_cmap = sns.cubehelix_palette(10, start=1.5, rot=-.5, light=1, dark=.4, as_cmap=True)\n", "\n", "sns.palplot(blue_ct_cmap.colors[np.linspace(0, 255, 10, dtype=int)])\n", "sns.palplot(red_ct_cmap.colors[np.linspace(0, 255, 10, dtype=int)])" ] }, { "cell_type": "code", "execution_count": 88, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def get_grid(mins, maxs, clf):\n", " xx, yy = np.meshgrid(np.linspace(mins, maxs, 1000),\n", " np.linspace(mins, maxs, 1000))\n", " '''\n", " if hasattr(clf, 'decision_function'):\n", " Z = clf.decision_function(np.c_[xx.ravel(), yy.ravel()])\n", " else:\n", " Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n", " '''\n", " Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n", " Z = Z.reshape(xx.shape)\n", " return xx, yy, Z" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def scale_evalue(col):\n", " col.ix[col == 0.0] = 1e-256\n", " return -np.log10(col)" ] }, { "cell_type": "code", "execution_count": 238, "metadata": { "collapsed": true }, "outputs": [], "source": [ "test_aln_A = pd.DataFrame([[0.0, 0.0, 200, 2000, 'tr_Aa', 200, '+', 70, 70, 'pr_Ba', 0, '+', 200, 200.0],\n", " [1e-100, 1e-100, 200, 2000, 'tr_Aa', 200, '+', 70, 70, 'pr_Bb', 0, '+', 200, 200.0],\n", " [0.0, 0.0, 200, 2000, 'tr_Ab', 200, '+', 70, 70, 'pr_Ba', 0, '+', 200, 200.0],\n", " [0.0, 0.0, 200, 2000, 'tr_Ac', 200, '+', 70, 70, 'pr_Bc', 0, '+', 200, 200.0]],\n", " columns=[u'E', u'EG2', u'q_aln_len', u'q_len', u'q_name', u'q_start',\n", " u'q_strand', u's_aln_len', u's_len', u's_name', u's_start', u's_strand',\n", " u'score', u'bitscore'])" ] }, { "cell_type": "code", "execution_count": 239, "metadata": { "collapsed": false }, "outputs": [], "source": [ "test_aln_B = pd.DataFrame([[0.0, 0.0, 200, 2000, 'pr_Ba', 200, '+', 70, 70, 'tr_Aa', 0, '+', 200, 200.0],\n", " [0.0, 0.0, 200, 2000, 'pr_Ba', 200, '+', 70, 70, 'tr_Ac', 0, '+', 200, 200.0],\n", " [1e-100, 1e-100, 200, 2000, 'pr_Ba', 200, '+', 70, 70, 'tr_Ab', 0, '+', 200, 200.0],\n", " [0.0, 0.0, 200, 2000, 'pr_Bb', 200, '+', 70, 70, 'tr_Aa', 0, '+', 200, 200.0]],\n", " columns=[u'E', u'EG2', u'q_aln_len', u'q_len', u'q_name', u'q_start',\n", " u'q_strand', u's_aln_len', u's_len', u's_name', u's_start', u's_strand',\n", " u'score', u'bitscore'])5" ] }, { "cell_type": "code", "execution_count": 240, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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EEG2_xq_aln_lenq_lenq_nameq_start_xq_strand_xs_aln_len_xs_len_xs_start_x...s_lens_nameq_start_yq_strand_ys_aln_len_ys_len_ys_start_ys_strand_yscore_ybitscore_y
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1 rows × 26 columns

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" ], "text/plain": [ " E EG2_x q_aln_len q_len q_name q_start_x q_strand_x s_aln_len_x \\\n", "0 0 0 200 2000 tr_Aa 200 + 70 \n", "\n", " s_len_x s_start_x ... s_len s_name q_start_y q_strand_y \\\n", "0 70 0 ... 2000 pr_Ba 200 + \n", "\n", " s_aln_len_y s_len_y s_start_y s_strand_y score_y bitscore_y \n", "0 70 70 0 + 200 200 \n", "\n", "[1 rows x 26 columns]" ] }, "execution_count": 240, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CRBL.reciprocal_best_hits(test_aln_A, test_aln_B)" ] }, { "cell_type": "code", "execution_count": 228, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Index([u'E', u'EG2', u'q_aln_len', u'q_len', u'q_name', u'q_start',\n", " u'q_strand', u's_aln_len', u's_len', u's_name', u's_start', u's_strand',\n", " u'score', u'bitscore', u'RBH'],\n", " dtype='object')" ] }, "execution_count": 228, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bh_df.columns" ] }, { "cell_type": "code", "execution_count": 191, "metadata": { "collapsed": false }, "outputs": [], "source": [ "rbh_df = pd.read_csv('pom.500.fa.dammit/pom.500.fa.transdecoder.pep.rbhx.pep.fa.csv')\n", "rbh_df['E'] = scale_evalue(rbh_df['E'].copy())" ] }, { "cell_type": "code", "execution_count": 192, "metadata": { "collapsed": false }, "outputs": [], "source": [ "bh_df = pd.concat([group for group in dammit.parsers.maf_to_df_iter('pom.500.fa.dammit/pom.500.fa.x.pep.fa.maf')])\n", "bh_df['E'] = scale_evalue(bh_df['E'].copy())" ] }, { "cell_type": "code", "execution_count": 193, "metadata": { "collapsed": true }, "outputs": [], "source": [ "bh_df['RBH'] = False\n", "bh_df.ix[rbh_df.index, 'RBH'] = True" ] }, { "cell_type": "code", "execution_count": 200, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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EEG2q_aln_lenq_lenq_nameq_startq_strands_aln_lens_lens_names_starts_strandscorebitscoreRBH
17251.9208191.400000e-442102270SPAPJ695.02_74452_76721_-1_SPAPJ695.02_I_prote...811+7070SPAPJ695.02_SPAPJ695.02_I_Schizosaccharomyces0+385205.442170True
16899.4317983.900000e-86351587SPAPJ695.01c_77480_78066_-1_SPAPJ695.01c_I_pro...135+117117SPAPJ695.01c_SPAPJ695.01c_I_S.0+647343.501215True
54114.1549021.600000e-101399747SPAC977.18_31140_32345_-1_SPAC977.18_I_protein...158+133133SPAC977.18_SPAC977.18_I_conserved0+744394.614678True
167256.0000000.000000e+0017943603SPAC977.17_66219_69821_1_SPAC977.17_I_protein_...924+598598SPAC977.17_SPAC977.17_I_MIP0+34471818.941394True
153256.0000000.000000e+0017732421SPAC977.16c_64559_66980_-1_dak2_I_protein_codi...300+591591SPAC977.16c_dak2_I_dihydroxyacetone0+32541717.241410True
160237.9208194.400000e-212741902SPAC977.15_62961_63862_1_SPAC977.15_I_protein_...28+247247SPAC977.15_SPAC977.15_I_dienelactone0+1441761.893894True
159282.5228793.100000e-2589751294SPAC977.14c_59614_60907_-1_SPAC977.14c_I_prote...215+325325SPAC750.01_SPAC750.01_I_aldo_keto0+1732915.234284True
155320.8862608.100000e-29310681364SPAC977.12_56373_57736_1_SPAC977.12_I_protein_...119+356356SPAC977.12_SPAC977.12_I_L-asparaginase0+19501030.107841True
157290.4202162.900000e-2649331250SPAC977.11_55059_56308_1_SPAC977.11_I_protein_...215+311311SPAC977.11_SPAC977.11_I_CRCB0+1770935.258115True
82256.0000000.000000e+0014042836SPAC977.10_50946_53858_1_sod2_I_protein_coding...1171+468468SPAC977.10_sod2_I_plasma0+26091377.363226True
85298.7212461.400000e-28717132461SPAC977.09c_45875_48399_-1_SPAC977.09c_I_prote...413+570623SPCC1450.09c_SPCC1450.09c_III_phospholipase51+19171012.718725True
86215.0915158.000000e-191708825SPAC977.08_44644_45468_1_SPAC977.08_I_protein_...60+236236SPAC977.08_SPAC977.08_I_short0+1307691.283543True
83256.0000000.000000e+0012481251SPAC977.07c_42057_43307_-1_pfl6_I_protein_codi...0+416416SPAC977.07c_pfl6_I_cell0+23571244.573610True
91176.3565474.500000e-153592607SPAC977.06_39416_40072_1_SPAC977.06_I_protein_...15+198230SPBC1348.07_SPBC1348.07_II_S.0+1069565.871128True
30191.8860572.100000e-166612615SPAC977.05c_35768_36382_-1_SPAC977.05c_I_prote...0+204204SPAC977.05c_SPAC977.05c_I_conserved0+1153610.134333True
39151.7212463.000000e-133501681SPAC977.04_34298_34978_1_SPAC977.04_I_protein_...15+167485SPAC750.02c_SPAC750.02c_I_transmembrane318+944500.003263True
46133.7958808.800000e-113435438SPAC977.03_33835_34272_1_SPAC977.03_I_protein_...0+145145SPAC977.03_SPAC977.03_I_methyltransferase0+815432.027626True
44124.3372422.100000e-113438979SPAC977.02_32034_33012_1_SPAC977.02_I_protein_...196+146146SPAC977.02_SPAC977.02_I_S.0+819434.135398True
20296.6989706.300000e-2719481306SPAC977.01_29764_31069_1_SPAC977.01_I_protein_...2+316316SPAC977.01_SPAC977.01_I_S.0+1812957.389718True
361305.7447271.900000e-29310382372SPAC5H10.13c_167766_170137_-1_gmh2_I_protein_c...287+346346SPAC5H10.13c_gmh2_I_alpha-10+19541032.215613True
348256.0000000.000000e+0011132013SPAC5H10.12c_165814_167826_-1_SPAC5H10.12c_I_p...291+371371SPAC5H10.12c_SPAC5H10.12c_I_acetylglucosaminyl...0+21321126.011453True
349295.7695512.000000e-2779871766SPAC5H10.11_164570_166335_1_gmh1_I_protein_cod...158+329329SPAC5H10.11_gmh1_I_alpha-10+1853978.994378True
347256.0000000.000000e+0011761880SPAC5H10.10_162756_164635_1_SPAC5H10.10_I_prot...204+392392SPAC5H10.10_SPAC5H10.10_I_NADPH0+22621194.514033True
351249.7958805.800000e-221801846SPAC5H10.09c_160977_161822_-1_ecm31_I_protein_...42+267267SPAC5H10.09c_ecm31_I_3-methyl-2-oxobutanoatehy...0+1497791.402698True
350257.7212461.500000e-2328491066SPAC5H10.08c_159880_160945_-1_pan6_I_protein_c...0+283283SPAC5H10.08c_pan6_I_pantoate-beta-alanine0+1570829.869531True
34373.4685216.400000e-64267696SPAC5H10.07_158777_159472_1_SPAC5H10.07_I_prot...426+8989SPAC5H10.07_SPAC5H10.07_I_Schizosaccharomyces0+507269.729206True
340256.0000000.000000e+0011371878SPAC5H10.06c_156430_158307_-1_adh4_I_protein_c...620+379379SPAC5H10.06c_adh4_I_alcohol0+21171118.107309True
344256.0000000.000000e+0011462514SPAC5H10.05c_153070_155583_-1_SPAC5H10.05c_I_p...317-382382SPAC5H10.04_SPAC5H10.04_I_NADPH0+22031163.424400True
339256.0000000.000000e+0011462665SPAC5H10.04_152851_155515_1_SPAC5H10.04_I_prot...536+382382SPAC5H10.04_SPAC5H10.04_I_NADPH0+22031163.424400True
332186.1611519.100000e-1796573464SPAC5H10.03_149446_152909_1_SPAC5H10.03_I_prot...2467+219219SPAC5H10.03_SPAC5H10.03_I_phosphoglycerate0+1231651.235881True
................................................
412256.0000000.000000e+0025773066SPAC13G6.12c_195940_199051_-1_chs1_I_protein_c...336+859859SPAC13G6.12c_chs1_I_chitin0+48612564.038684True
414256.0000000.000000e+0012121279SPAC13G6.11c_194099_195626_-1_erg12_I_protein_...44+404404SPAC13G6.11c_erg12_I_mevalonate0+22131168.693829True
413256.0000000.000000e+0015902126SPAC13G6.10c_191928_194053_-1_asl1_I_protein_c...165+530530SPAC13G6.10c_asl1_I_cell0+29181540.188589True
415247.1674914.600000e-2328221611SPAC13G6.09_190192_191947_1_SPAC13G6.09_I_prot...130+274274SPAC13G6.09_SPAC13G6.09_I_SSU-rRNA0+1567828.288702True
405256.0000000.000000e+0016052331SPAC13G6.08_187701_190031_1_SPAC13G6.08_I_prot...676+535535SPAC13G6.08_SPAC13G6.08_I_Cdc20_Fizzy0+30411605.002568True
406209.4559324.200000e-1957171370SPAC13G6.07c_186314_187683_-1_rps601_I_protein...120+239239SPAC13G6.07c_rps601_I_40S0+1334705.511002True
404256.0000000.000000e+0030934022SPAC13G6.06c_182337_186358_-1_gcv2_I_protein_c...287+10311031SPAC13G6.06c_gcv2_I_glycine0+58393079.388861True
399231.1487424.100000e-208759996SPAC13G6.05c_180903_182254_-1_trs33_I_protein_...60+253253SPAC13G6.05c_trs33_I_TRAPP0+1416748.720321True
40273.1870871.700000e-62261573SPAC13G6.04_180272_181069_1_tim8_I_protein_cod...151+8787SPAC13G6.04_tim8_I_TIM220+498264.986720True
398256.0000000.000000e+0022744139SPAC13G6.03_175890_180028_1_gpi7_I_protein_cod...1402+758758SPAC13G6.03_gpi7_I_GPI0+42172224.687443True
400212.0915151.300000e-2017561791SPAC13G6.02c_174865_176655_-1_rps101_I_protein...884+252252SPAC13G6.02c_rps101_I_40S0+1375727.115662True
360256.0000000.000000e+0033994213SPAC13G6.01c_170489_174701_-1_rad8_I_protein_c...328+11331133SPAC13G6.01c_rad8_I_ubiquitin-protein0+63933371.315239True
20360.8239093.900000e-532311469SPAC11D3.19_106893_108361_1_SPAC11D3.19_I_prot...72+7777SPAC11D3.19_SPAC11D3.19_I_Schizosaccharomyces0+439233.897088True
325256.0000000.000000e+0014942075SPAC11D3.18c_144819_146935_-1_SPAC11D3.18c_I_p...535+498498SPAC11D3.18c_SPAC11D3.18c_I_plasma0+27611457.458550True
324256.0000000.000000e+0017553522SPAC11D3.17_141199_144768_1_SPAC11D3.17_I_prot...1428+585585SPAC11D3.17_SPAC11D3.17_I_transcription0+33431764.139330True
323110.2757247.800000e-1023931273SPAC11D3.16c_140381_141653_-1_SPAC11D3.16c_I_p...453+131131SPAC11D3.16c_SPAC11D3.16c_I_Schizosaccharomyces0+746395.668564True
321256.0000000.000000e+0039514227SPAC11D3.15_136139_140365_1_SPAC11D3.15_I_prot...192+13171317SPAC11D3.15_SPAC11D3.15_I_5-oxoprolinase0+73453872.964900True
319256.0000000.000000e+0037804547SPAC11D3.14c_131190_135736_-1_SPAC11D3.14c_I_p...635+12601260SPAC11D3.14c_SPAC11D3.14c_I_5-oxoprolinase0+70653725.420882True
303195.6777812.100000e-1796661121SPAC11D3.13_130148_131268_1_hsp3104_I_protein_...181+222222SPAC11D3.13_hsp3104_I_ThiJ0+1235653.343653True
299256.0000000.000000e+0010712279SPAC11D3.11c_126951_129316_-1_SPAC11D3.11c_I_p...131+357357SPAC11D3.11c_SPAC11D3.11c_I_zn(2)-C60+20781097.556535True
315307.1938201.200000e-29910264147SPAC11D3.10_124907_129053_1_SPAC11D3.10_I_prot...0-342357SPAC11D3.11c_SPAC11D3.11c_I_zn(2)-C615+19931052.766387True
285256.0000000.000000e+0011821930SPAC11D3.09_122187_124116_1_SPAC11D3.09_I_prot...658+394394SPAC11D3.09_SPAC11D3.09_I_agmatinase0+22191171.855487True
295272.6197896.700000e-2659393465SPAC11D3.08c_120321_123785_-1_SPAC11D3.08c_I_p...2524-313394SPAC11D3.09_SPAC11D3.09_I_agmatinase0+1774937.365887True
271256.0000000.000000e+0019114256SPAC11D3.07c_116054_120309_-1_toe4_I_protein_c...201+637637SPAC11D3.07c_toe4_I_transcription0+36001899.563661True
272256.0000000.000000e+0013651859SPAC11D3.06_116331_118189_1_SPAC11D3.06_I_prot...362+455455SPAC11D3.06_SPAC11D3.06_I_MatE0+24821310.441475True
253310.0457571.900000e-29315362013SPAC11D3.05_113950_115962_1_mfs2_I_protein_cod...232+508541SPBC530.02_SPBC530.02_II_transmembrane33+19541032.215613True
257104.1426681.900000e-963901865SPAC11D3.04c_112514_114445_-1_SPAC11D3.04c_I_p...1069+130130SPAC11D3.04c_SPAC11D3.04c_I_polyketide0+712377.752505True
254286.5686362.200000e-2659061501SPAC11D3.03c_110904_112499_-1_SPAC11D3.03c_I_p...491+302302SPAC11D3.03c_SPAC11D3.03c_I_conserved0+1777938.946716True
196132.3979401.800000e-115450627SPAC11D3.02c_109829_110455_-1_SPAC11D3.02c_I_p...174+150150SPAC11D3.02c_SPAC11D3.02c_I_ELLA0+832440.985656True
20267.8538722.600000e-56237464SPAC11D3.01c_108732_109195_-1_SPAC11D3.01c_I_p...48+7979SPAC11D3.01c_SPAC11D3.01c_I_conserved0+459244.435946True
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82 rows × 15 columns

\n", "
" ], "text/plain": [ " E EG2 q_aln_len q_len \\\n", "172 51.920819 1.400000e-44 210 2270 \n", "168 99.431798 3.900000e-86 351 587 \n", "54 114.154902 1.600000e-101 399 747 \n", "167 256.000000 0.000000e+00 1794 3603 \n", "153 256.000000 0.000000e+00 1773 2421 \n", "160 237.920819 4.400000e-212 741 902 \n", "159 282.522879 3.100000e-258 975 1294 \n", "155 320.886260 8.100000e-293 1068 1364 \n", "157 290.420216 2.900000e-264 933 1250 \n", "82 256.000000 0.000000e+00 1404 2836 \n", "85 298.721246 1.400000e-287 1713 2461 \n", "86 215.091515 8.000000e-191 708 825 \n", "83 256.000000 0.000000e+00 1248 1251 \n", "91 176.356547 4.500000e-153 592 607 \n", "30 191.886057 2.100000e-166 612 615 \n", "39 151.721246 3.000000e-133 501 681 \n", "46 133.795880 8.800000e-113 435 438 \n", "44 124.337242 2.100000e-113 438 979 \n", "20 296.698970 6.300000e-271 948 1306 \n", "361 305.744727 1.900000e-293 1038 2372 \n", "348 256.000000 0.000000e+00 1113 2013 \n", "349 295.769551 2.000000e-277 987 1766 \n", "347 256.000000 0.000000e+00 1176 1880 \n", "351 249.795880 5.800000e-221 801 846 \n", "350 257.721246 1.500000e-232 849 1066 \n", "343 73.468521 6.400000e-64 267 696 \n", "340 256.000000 0.000000e+00 1137 1878 \n", "344 256.000000 0.000000e+00 1146 2514 \n", "339 256.000000 0.000000e+00 1146 2665 \n", "332 186.161151 9.100000e-179 657 3464 \n", ".. ... ... ... ... \n", "412 256.000000 0.000000e+00 2577 3066 \n", "414 256.000000 0.000000e+00 1212 1279 \n", "413 256.000000 0.000000e+00 1590 2126 \n", "415 247.167491 4.600000e-232 822 1611 \n", "405 256.000000 0.000000e+00 1605 2331 \n", "406 209.455932 4.200000e-195 717 1370 \n", "404 256.000000 0.000000e+00 3093 4022 \n", "399 231.148742 4.100000e-208 759 996 \n", "402 73.187087 1.700000e-62 261 573 \n", "398 256.000000 0.000000e+00 2274 4139 \n", "400 212.091515 1.300000e-201 756 1791 \n", "360 256.000000 0.000000e+00 3399 4213 \n", "203 60.823909 3.900000e-53 231 1469 \n", "325 256.000000 0.000000e+00 1494 2075 \n", "324 256.000000 0.000000e+00 1755 3522 \n", "323 110.275724 7.800000e-102 393 1273 \n", "321 256.000000 0.000000e+00 3951 4227 \n", "319 256.000000 0.000000e+00 3780 4547 \n", "303 195.677781 2.100000e-179 666 1121 \n", "299 256.000000 0.000000e+00 1071 2279 \n", "315 307.193820 1.200000e-299 1026 4147 \n", "285 256.000000 0.000000e+00 1182 1930 \n", "295 272.619789 6.700000e-265 939 3465 \n", "271 256.000000 0.000000e+00 1911 4256 \n", "272 256.000000 0.000000e+00 1365 1859 \n", "253 310.045757 1.900000e-293 1536 2013 \n", "257 104.142668 1.900000e-96 390 1865 \n", "254 286.568636 2.200000e-265 906 1501 \n", "196 132.397940 1.800000e-115 450 627 \n", "202 67.853872 2.600000e-56 237 464 \n", "\n", " q_name q_start q_strand \\\n", "172 SPAPJ695.02_74452_76721_-1_SPAPJ695.02_I_prote... 811 + \n", "168 SPAPJ695.01c_77480_78066_-1_SPAPJ695.01c_I_pro... 135 + \n", "54 SPAC977.18_31140_32345_-1_SPAC977.18_I_protein... 158 + \n", "167 SPAC977.17_66219_69821_1_SPAC977.17_I_protein_... 924 + \n", "153 SPAC977.16c_64559_66980_-1_dak2_I_protein_codi... 300 + \n", "160 SPAC977.15_62961_63862_1_SPAC977.15_I_protein_... 28 + \n", "159 SPAC977.14c_59614_60907_-1_SPAC977.14c_I_prote... 215 + \n", "155 SPAC977.12_56373_57736_1_SPAC977.12_I_protein_... 119 + \n", "157 SPAC977.11_55059_56308_1_SPAC977.11_I_protein_... 215 + \n", "82 SPAC977.10_50946_53858_1_sod2_I_protein_coding... 1171 + \n", "85 SPAC977.09c_45875_48399_-1_SPAC977.09c_I_prote... 413 + \n", "86 SPAC977.08_44644_45468_1_SPAC977.08_I_protein_... 60 + \n", "83 SPAC977.07c_42057_43307_-1_pfl6_I_protein_codi... 0 + \n", "91 SPAC977.06_39416_40072_1_SPAC977.06_I_protein_... 15 + \n", "30 SPAC977.05c_35768_36382_-1_SPAC977.05c_I_prote... 0 + \n", "39 SPAC977.04_34298_34978_1_SPAC977.04_I_protein_... 15 + \n", "46 SPAC977.03_33835_34272_1_SPAC977.03_I_protein_... 0 + \n", "44 SPAC977.02_32034_33012_1_SPAC977.02_I_protein_... 196 + \n", "20 SPAC977.01_29764_31069_1_SPAC977.01_I_protein_... 2 + \n", "361 SPAC5H10.13c_167766_170137_-1_gmh2_I_protein_c... 287 + \n", "348 SPAC5H10.12c_165814_167826_-1_SPAC5H10.12c_I_p... 291 + \n", "349 SPAC5H10.11_164570_166335_1_gmh1_I_protein_cod... 158 + \n", "347 SPAC5H10.10_162756_164635_1_SPAC5H10.10_I_prot... 204 + \n", "351 SPAC5H10.09c_160977_161822_-1_ecm31_I_protein_... 42 + \n", "350 SPAC5H10.08c_159880_160945_-1_pan6_I_protein_c... 0 + \n", "343 SPAC5H10.07_158777_159472_1_SPAC5H10.07_I_prot... 426 + \n", "340 SPAC5H10.06c_156430_158307_-1_adh4_I_protein_c... 620 + \n", "344 SPAC5H10.05c_153070_155583_-1_SPAC5H10.05c_I_p... 317 - \n", "339 SPAC5H10.04_152851_155515_1_SPAC5H10.04_I_prot... 536 + \n", "332 SPAC5H10.03_149446_152909_1_SPAC5H10.03_I_prot... 2467 + \n", ".. ... ... ... \n", "412 SPAC13G6.12c_195940_199051_-1_chs1_I_protein_c... 336 + \n", "414 SPAC13G6.11c_194099_195626_-1_erg12_I_protein_... 44 + \n", "413 SPAC13G6.10c_191928_194053_-1_asl1_I_protein_c... 165 + \n", "415 SPAC13G6.09_190192_191947_1_SPAC13G6.09_I_prot... 130 + \n", "405 SPAC13G6.08_187701_190031_1_SPAC13G6.08_I_prot... 676 + \n", "406 SPAC13G6.07c_186314_187683_-1_rps601_I_protein... 120 + \n", "404 SPAC13G6.06c_182337_186358_-1_gcv2_I_protein_c... 287 + \n", "399 SPAC13G6.05c_180903_182254_-1_trs33_I_protein_... 60 + \n", "402 SPAC13G6.04_180272_181069_1_tim8_I_protein_cod... 151 + \n", "398 SPAC13G6.03_175890_180028_1_gpi7_I_protein_cod... 1402 + \n", "400 SPAC13G6.02c_174865_176655_-1_rps101_I_protein... 884 + \n", "360 SPAC13G6.01c_170489_174701_-1_rad8_I_protein_c... 328 + \n", "203 SPAC11D3.19_106893_108361_1_SPAC11D3.19_I_prot... 72 + \n", "325 SPAC11D3.18c_144819_146935_-1_SPAC11D3.18c_I_p... 535 + \n", "324 SPAC11D3.17_141199_144768_1_SPAC11D3.17_I_prot... 1428 + \n", "323 SPAC11D3.16c_140381_141653_-1_SPAC11D3.16c_I_p... 453 + \n", "321 SPAC11D3.15_136139_140365_1_SPAC11D3.15_I_prot... 192 + \n", "319 SPAC11D3.14c_131190_135736_-1_SPAC11D3.14c_I_p... 635 + \n", "303 SPAC11D3.13_130148_131268_1_hsp3104_I_protein_... 181 + \n", "299 SPAC11D3.11c_126951_129316_-1_SPAC11D3.11c_I_p... 131 + \n", "315 SPAC11D3.10_124907_129053_1_SPAC11D3.10_I_prot... 0 - \n", "285 SPAC11D3.09_122187_124116_1_SPAC11D3.09_I_prot... 658 + \n", "295 SPAC11D3.08c_120321_123785_-1_SPAC11D3.08c_I_p... 2524 - \n", "271 SPAC11D3.07c_116054_120309_-1_toe4_I_protein_c... 201 + \n", "272 SPAC11D3.06_116331_118189_1_SPAC11D3.06_I_prot... 362 + \n", "253 SPAC11D3.05_113950_115962_1_mfs2_I_protein_cod... 232 + \n", "257 SPAC11D3.04c_112514_114445_-1_SPAC11D3.04c_I_p... 1069 + \n", "254 SPAC11D3.03c_110904_112499_-1_SPAC11D3.03c_I_p... 491 + \n", "196 SPAC11D3.02c_109829_110455_-1_SPAC11D3.02c_I_p... 174 + \n", "202 SPAC11D3.01c_108732_109195_-1_SPAC11D3.01c_I_p... 48 + \n", "\n", " s_aln_len s_len s_name \\\n", "172 70 70 SPAPJ695.02_SPAPJ695.02_I_Schizosaccharomyces \n", "168 117 117 SPAPJ695.01c_SPAPJ695.01c_I_S. \n", "54 133 133 SPAC977.18_SPAC977.18_I_conserved \n", "167 598 598 SPAC977.17_SPAC977.17_I_MIP \n", "153 591 591 SPAC977.16c_dak2_I_dihydroxyacetone \n", "160 247 247 SPAC977.15_SPAC977.15_I_dienelactone \n", "159 325 325 SPAC750.01_SPAC750.01_I_aldo_keto \n", "155 356 356 SPAC977.12_SPAC977.12_I_L-asparaginase \n", "157 311 311 SPAC977.11_SPAC977.11_I_CRCB \n", "82 468 468 SPAC977.10_sod2_I_plasma \n", "85 570 623 SPCC1450.09c_SPCC1450.09c_III_phospholipase \n", "86 236 236 SPAC977.08_SPAC977.08_I_short \n", "83 416 416 SPAC977.07c_pfl6_I_cell \n", "91 198 230 SPBC1348.07_SPBC1348.07_II_S. \n", "30 204 204 SPAC977.05c_SPAC977.05c_I_conserved \n", "39 167 485 SPAC750.02c_SPAC750.02c_I_transmembrane \n", "46 145 145 SPAC977.03_SPAC977.03_I_methyltransferase \n", "44 146 146 SPAC977.02_SPAC977.02_I_S. \n", "20 316 316 SPAC977.01_SPAC977.01_I_S. \n", "361 346 346 SPAC5H10.13c_gmh2_I_alpha-1 \n", "348 371 371 SPAC5H10.12c_SPAC5H10.12c_I_acetylglucosaminyl... \n", "349 329 329 SPAC5H10.11_gmh1_I_alpha-1 \n", "347 392 392 SPAC5H10.10_SPAC5H10.10_I_NADPH \n", "351 267 267 SPAC5H10.09c_ecm31_I_3-methyl-2-oxobutanoatehy... \n", "350 283 283 SPAC5H10.08c_pan6_I_pantoate-beta-alanine \n", "343 89 89 SPAC5H10.07_SPAC5H10.07_I_Schizosaccharomyces \n", "340 379 379 SPAC5H10.06c_adh4_I_alcohol \n", "344 382 382 SPAC5H10.04_SPAC5H10.04_I_NADPH \n", "339 382 382 SPAC5H10.04_SPAC5H10.04_I_NADPH \n", "332 219 219 SPAC5H10.03_SPAC5H10.03_I_phosphoglycerate \n", ".. ... ... ... \n", "412 859 859 SPAC13G6.12c_chs1_I_chitin \n", "414 404 404 SPAC13G6.11c_erg12_I_mevalonate \n", "413 530 530 SPAC13G6.10c_asl1_I_cell \n", "415 274 274 SPAC13G6.09_SPAC13G6.09_I_SSU-rRNA \n", "405 535 535 SPAC13G6.08_SPAC13G6.08_I_Cdc20_Fizzy \n", "406 239 239 SPAC13G6.07c_rps601_I_40S \n", "404 1031 1031 SPAC13G6.06c_gcv2_I_glycine \n", "399 253 253 SPAC13G6.05c_trs33_I_TRAPP \n", "402 87 87 SPAC13G6.04_tim8_I_TIM22 \n", "398 758 758 SPAC13G6.03_gpi7_I_GPI \n", "400 252 252 SPAC13G6.02c_rps101_I_40S \n", "360 1133 1133 SPAC13G6.01c_rad8_I_ubiquitin-protein \n", "203 77 77 SPAC11D3.19_SPAC11D3.19_I_Schizosaccharomyces \n", "325 498 498 SPAC11D3.18c_SPAC11D3.18c_I_plasma \n", "324 585 585 SPAC11D3.17_SPAC11D3.17_I_transcription \n", "323 131 131 SPAC11D3.16c_SPAC11D3.16c_I_Schizosaccharomyces \n", "321 1317 1317 SPAC11D3.15_SPAC11D3.15_I_5-oxoprolinase \n", "319 1260 1260 SPAC11D3.14c_SPAC11D3.14c_I_5-oxoprolinase \n", "303 222 222 SPAC11D3.13_hsp3104_I_ThiJ \n", "299 357 357 SPAC11D3.11c_SPAC11D3.11c_I_zn(2)-C6 \n", "315 342 357 SPAC11D3.11c_SPAC11D3.11c_I_zn(2)-C6 \n", "285 394 394 SPAC11D3.09_SPAC11D3.09_I_agmatinase \n", "295 313 394 SPAC11D3.09_SPAC11D3.09_I_agmatinase \n", "271 637 637 SPAC11D3.07c_toe4_I_transcription \n", "272 455 455 SPAC11D3.06_SPAC11D3.06_I_MatE \n", "253 508 541 SPBC530.02_SPBC530.02_II_transmembrane \n", "257 130 130 SPAC11D3.04c_SPAC11D3.04c_I_polyketide \n", "254 302 302 SPAC11D3.03c_SPAC11D3.03c_I_conserved \n", "196 150 150 SPAC11D3.02c_SPAC11D3.02c_I_ELLA \n", "202 79 79 SPAC11D3.01c_SPAC11D3.01c_I_conserved \n", "\n", " s_start s_strand score bitscore RBH \n", "172 0 + 385 205.442170 True \n", "168 0 + 647 343.501215 True \n", "54 0 + 744 394.614678 True \n", "167 0 + 3447 1818.941394 True \n", "153 0 + 3254 1717.241410 True \n", "160 0 + 1441 761.893894 True \n", "159 0 + 1732 915.234284 True \n", "155 0 + 1950 1030.107841 True \n", "157 0 + 1770 935.258115 True \n", "82 0 + 2609 1377.363226 True \n", "85 51 + 1917 1012.718725 True \n", "86 0 + 1307 691.283543 True \n", "83 0 + 2357 1244.573610 True \n", "91 0 + 1069 565.871128 True \n", "30 0 + 1153 610.134333 True \n", "39 318 + 944 500.003263 True \n", "46 0 + 815 432.027626 True \n", "44 0 + 819 434.135398 True \n", "20 0 + 1812 957.389718 True \n", "361 0 + 1954 1032.215613 True \n", "348 0 + 2132 1126.011453 True \n", "349 0 + 1853 978.994378 True \n", "347 0 + 2262 1194.514033 True \n", "351 0 + 1497 791.402698 True \n", "350 0 + 1570 829.869531 True \n", "343 0 + 507 269.729206 True \n", "340 0 + 2117 1118.107309 True \n", "344 0 + 2203 1163.424400 True \n", "339 0 + 2203 1163.424400 True \n", "332 0 + 1231 651.235881 True \n", ".. ... ... ... ... ... \n", "412 0 + 4861 2564.038684 True \n", "414 0 + 2213 1168.693829 True \n", "413 0 + 2918 1540.188589 True \n", "415 0 + 1567 828.288702 True \n", "405 0 + 3041 1605.002568 True \n", "406 0 + 1334 705.511002 True \n", "404 0 + 5839 3079.388861 True \n", "399 0 + 1416 748.720321 True \n", "402 0 + 498 264.986720 True \n", "398 0 + 4217 2224.687443 True \n", "400 0 + 1375 727.115662 True \n", "360 0 + 6393 3371.315239 True \n", "203 0 + 439 233.897088 True \n", "325 0 + 2761 1457.458550 True \n", "324 0 + 3343 1764.139330 True \n", "323 0 + 746 395.668564 True \n", "321 0 + 7345 3872.964900 True \n", "319 0 + 7065 3725.420882 True \n", "303 0 + 1235 653.343653 True \n", "299 0 + 2078 1097.556535 True \n", "315 15 + 1993 1052.766387 True \n", "285 0 + 2219 1171.855487 True \n", "295 0 + 1774 937.365887 True \n", "271 0 + 3600 1899.563661 True \n", "272 0 + 2482 1310.441475 True \n", "253 33 + 1954 1032.215613 True \n", "257 0 + 712 377.752505 True \n", "254 0 + 1777 938.946716 True \n", "196 0 + 832 440.985656 True \n", "202 0 + 459 244.435946 True \n", "\n", "[82 rows x 15 columns]" ] }, "execution_count": 200, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bh_df.sort_values(by=['q_name', 'E'], ascending=False).drop_duplicates(subset='q_name').query('RBH == True')" ] }, { "cell_type": "code", "execution_count": 208, "metadata": { "collapsed": false }, "outputs": [], "source": [ "pep_x_db_df = pd.concat([group for group in dammit.parsers.maf_to_df_iter('pom.500.fa.dammit/pom.500.fa.transdecoder.pep.x.pep.fa.maf')])" ] }, { "cell_type": "code", "execution_count": 209, "metadata": { "collapsed": true }, "outputs": [], "source": [ "db_x_pep_df = pd.concat([group for group in dammit.parsers.maf_to_df_iter('pom.500.fa.dammit/pep.fa.x.pom.500.fa.transdecoder.pep.maf')])" ] }, { "cell_type": "code", "execution_count": 210, "metadata": { "collapsed": false }, "outputs": [], "source": [ "rbh_pep_df = CRBL.reciprocal_best_hits(pep_x_db_df, db_x_pep_df)" ] }, { "cell_type": "code", "execution_count": 223, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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20.000000e+000.000000e+00600601SPAC10F6.03c_1211195_1213553_-1_cts1_I_protein...0+6006000...600SPAC10F6.03c_cts1_I_CTP0+6006010+31231381.689000
31.500000e-2751.100000e-234351352SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr...0+3513510...351SPAC10F6.04_SPAC10F6.04_I_RCC0+3513520+1889837.037300
53.700000e-1733.700000e-143227243SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein...15+2272270...227SPAC10F6.05c_ubc6_I_ubiquitin0+22724315+1200532.932745
61.600000e-1843.000000e-153257258SPAC10F6.06_1217077_1218228_1_vip1_I_protein_c...0+2572570...257SPAC10F6.06_vip1_I_RNA-binding0+2572580+1276566.476934
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82.100000e-2491.600000e-212341358SPAC10F6.08c_1219667_1220847_-1_nht1_I_protein...16+3413410...341SPAC10F6.08c_nht1_I_Ino800+34135816+1722763.328358
90.000000e+000.000000e+00908916SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein...8+90811940...1194SPAC10F6.09c_psm3_I_mitotic0+9089168+45322003.580608
103.400000e-578.700000e-407996SPAC11D3.01c_108732_109195_-1_SPAC11D3.01c_I_p...16+79790...79SPAC11D3.01c_SPAC11D3.01c_I_conserved0+799616+422189.546179
119.200000e-1103.700000e-86150151SPAC11D3.02c_109829_110455_-1_SPAC11D3.02c_I_p...0+1501500...150SPAC11D3.02c_SPAC11D3.02c_I_ELLA0+1501510+771343.584626
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133.200000e-921.300000e-70130131SPAC11D3.04c_112514_114445_-1_SPAC11D3.04c_I_p...0+1301300...130SPAC11D3.04c_SPAC11D3.04c_I_polyketide0+1301310+654291.944229
150.000000e+000.000000e+00546547SPAC11D3.05_113950_115962_1_mfs2_I_protein_cod...0+5465460...546SPAC11D3.05_mfs2_I_MFS0+5465470+29051285.470142
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180.000000e+000.000000e+00637638SPAC11D3.07c_116054_120309_-1_toe4_I_protein_c...0+6376370...637SPAC11D3.07c_toe4_I_transcription0+6376380+33301473.052777
190.000000e+000.000000e+00550551SPAC11D3.08c_120321_123785_-1_SPAC11D3.08c_I_p...0+5505500...550SPAC11D3.08c_SPAC11D3.08c_I_amino0+5505510+28331253.691437
212.000000e-2981.100000e-255394395SPAC11D3.09_122187_124116_1_SPAC11D3.09_I_prot...0+3943940...394SPAC11D3.09_SPAC11D3.09_I_agmatinase0+3943950+2047906.773903
220.000000e+006.100000e-281434435SPAC11D3.10_124907_129053_1_SPAC11D3.10_I_prot...0+4344340...434SPAC11D3.10_SPAC11D3.10_I_nifs0+4344350+2237990.634376
241.100000e-2813.800000e-240357358SPAC11D3.11c_126951_129316_-1_SPAC11D3.11c_I_p...0+3573570...357SPAC11D3.11c_SPAC11D3.11c_I_zn(2)-C60+3573580+1930855.133507
272.700000e-1657.600000e-136222223SPAC11D3.13_130148_131268_1_hsp3104_I_protein_...0+2222220...222SPAC11D3.13_hsp3104_I_ThiJ0+2222230+1145508.657345
280.000000e+000.000000e+0012601261SPAC11D3.14c_131190_135736_-1_SPAC11D3.14c_I_p...0+126012600...1260SPAC11D3.14c_SPAC11D3.14c_I_5-oxoprolinase0+126012610+65262883.674197
290.000000e+000.000000e+0013171318SPAC11D3.15_136139_140365_1_SPAC11D3.15_I_prot...0+131713170...1317SPAC11D3.15_SPAC11D3.15_I_5-oxoprolinase0+131713180+67872998.872004
301.000000e-972.900000e-75131132SPAC11D3.16c_140381_141653_-1_SPAC11D3.16c_I_p...0+1311310...131SPAC11D3.16c_SPAC11D3.16c_I_Schizosaccharomyces0+1311320+689307.392211
310.000000e+000.000000e+00585586SPAC11D3.17_141199_144768_1_SPAC11D3.17_I_prot...0+5855850...585SPAC11D3.17_SPAC11D3.17_I_transcription0+5855860+31051373.744323
320.000000e+000.000000e+00498499SPAC11D3.18c_144819_146935_-1_SPAC11D3.18c_I_p...0+4984980...498SPAC11D3.18c_SPAC11D3.18c_I_plasma0+4984990+25541130.548953
330.000000e+000.000000e+00542543SPAC1296.01c_707948_710479_-1_SPAC1296.01c_I_p...0+5425420...542SPAC1296.01c_SPAC1296.01c_I_phosphoacetylgluco...0+5425430+27451214.850797
345.300000e-1224.700000e-97164165SPAC1296.02_711238_712354_1_cox4_I_protein_cod...0+1641640...164SPAC1296.02_cox4_I_cytochrome0+1641650+853379.777040
350.000000e+000.000000e+00507508SPAC1296.03c_712217_714070_-1_sxa2_I_protein_c...0+5075070...507SPAC1296.03c_sxa2_I_serine0+5075080+26531174.244673
364.700000e-1901.200000e-157248249SPAC1296.04_715377_716978_1_mug65_I_protein_co...0+2482480...248SPAC1296.04_mug65_I_spore0+2482490+1309581.042174
..................................................................
5131.900000e-2642.100000e-225357358SPAC821.05_988076_989866_1_tif38_I_protein_cod...0+3573570...357SPAC821.05_tif38_I_translation0+3573580+1819806.141336
5143.100000e-2502.200000e-212331332SPAC821.06_990192_991889_1_spn2_I_protein_codi...0+3313310...331SPAC821.06_spn2_I_mitotic0+3313320+1721762.886988
5150.000000e+000.000000e+00508509SPAC821.07c_991632_994230_-1_moc3_I_protein_co...0+5085080...508SPAC821.07c_moc3_I_transcription0+5085090+26741183.513462
5160.000000e+000.000000e+00488489SPAC821.08c_994941_997625_-1_slp1_I_protein_co...0+4884880...488SPAC821.08c_slp1_I_substrate-specific0+4884890+25741139.376372
5172.100000e-1121.500000e-88154155SPAC821.10c_1002838_1003600_-1_sod1_I_protein_...0+1541540...154SPAC821.10c_sod1_I_superoxide0+1541550+789351.529302
5180.000000e+001.600000e-282451452SPAC821.11_1006259_1008003_1_pro1_I_protein_co...0+4514510...451SPAC821.11_pro1_I_gamma-glutamyl0+4514520+2249995.930827
5190.000000e+000.000000e+00469470SPAC821.12_1008215_1010318_1_orb6_I_protein_co...0+4694690...469SPAC821.12_orb6_I_serine_threonine0+4694700+24821098.770248
5200.000000e+000.000000e+0015621563SPAC821.13c_1010343_1015415_-1_dnf1_I_protein_...0+156215620...1562SPAC821.13c_dnf1_I_Trans-golgi0+156215630+80353549.702896
5211.100000e-2432.900000e-206316317SPAC977.01_29764_31069_1_SPAC977.01_I_protein_...0+3163160...316SPAC977.01_SPAC977.01_I_S.0+3163170+1675742.583926
5227.400000e-1082.000000e-84146147SPAC977.02_32034_33012_1_SPAC977.02_I_protein_...0+1461460...146SPAC977.02_SPAC977.02_I_S.0+1461470+758337.846804
5238.900000e-1082.700000e-84145146SPAC977.03_33835_34272_1_SPAC977.03_I_protein_...0+1451450...145SPAC977.03_SPAC977.03_I_methyltransferase0+1451460+757337.405433
5249.500000e-1261.700000e-100169173SPAC977.04_34298_34978_1_SPAC977.04_I_protein_...3+169485316...485SPAC750.02c_SPAC750.02c_I_transmembrane316+1691733+879391.252684
5257.200000e-1549.500000e-126204205SPAC977.05c_35768_36382_-1_SPAC977.05c_I_prote...0+2042040...204SPAC977.05c_SPAC977.05c_I_conserved0+2042050+1069475.113156
5262.200000e-1422.200000e-115189195SPAC977.06_39416_40072_1_SPAC977.06_I_protein_...5+1891890...189SPAC977.06_SPAC977.06_I_S.0+1891955+991440.686225
5275.780568e-3221.500000e-276416417SPAC977.07c_42057_43307_-1_pfl6_I_protein_codi...0+4164160...416SPAC977.07c_pfl6_I_cell0+4164170+2204976.069136
5285.800000e-1745.900000e-144236237SPAC977.08_44644_45468_1_SPAC977.08_I_protein_...0+2362360...236SPAC977.08_SPAC977.08_I_short0+2362370+1206535.580970
5290.000000e+000.000000e+00673674SPAC977.09c_45875_48399_-1_SPAC977.09c_I_prote...0+6736730...673SPAC977.09c_SPAC977.09c_I_phospholipase0+6736740+35811583.836875
5300.000000e+000.000000e+00468544SPAC977.10_50946_53858_1_sod2_I_protein_coding...75+4684680...468SPAC977.10_sod2_I_plasma0+46854475+24331077.143074
5312.300000e-2392.100000e-202311312SPAC977.11_55059_56308_1_SPAC977.11_I_protein_...0+3113110...311SPAC977.11_SPAC977.11_I_CRCB0+3113120+1646729.784169
5327.400000e-2623.900000e-223356357SPAC977.12_56373_57736_1_SPAC977.12_I_protein_...0+3563560...356SPAC977.12_SPAC977.12_I_L-asparaginase0+3563570+1802798.638031
5333.100000e-2661.000000e-226351352SPAC977.14c_59614_60907_-1_SPAC977.14c_I_prote...0+3513510...351SPAC977.14c_SPAC977.14c_I_aldo_keto0+3513520+1829810.555046
5347.600000e-1941.300000e-161247257SPAC977.15_62961_63862_1_SPAC977.15_I_protein_...9+2472470...247SPAC977.15_SPAC977.15_I_dienelactone0+2472579+1339594.283301
5350.000000e+000.000000e+00591592SPAC977.16c_64559_66980_-1_dak2_I_protein_codi...0+5915910...591SPAC977.16c_dak2_I_dihydroxyacetone0+5915920+30141333.579571
5370.000000e+000.000000e+00598599SPAC977.17_66219_69821_1_SPAC977.17_I_protein_...0+5985980...598SPAC977.17_SPAC977.17_I_MIP0+5985990+31801406.847141
5388.700000e-982.200000e-75133134SPAC977.18_31140_32345_-1_SPAC977.18_I_protein...0+1331330...133SPAC977.18_SPAC977.18_I_conserved0+1331340+690307.833582
5390.000000e+000.000000e+0016871688SPAPB21F2.02_492335_497927_1_SPAPB21F2.02_I_pr...0+168716870...1687SPAPB21F2.02_SPAPB21F2.02_I_Dopey0+168716880+86093803.049797
5402.600000e-1218.700000e-97172173SPAPB21F2.03_498111_499027_1_slx9_I_protein_co...0+1721720...172SPAPB21F2.03_slx9_I_ribosome0+1721730+851378.894298
5412.100000e-863.700000e-65117118SPAPJ695.01c_77480_78066_-1_SPAPJ695.01c_I_pro...0+1171170...117SPAPJ695.01c_SPAPJ695.01c_I_S.0+1171180+613273.848022
5420.000000e+000.000000e+00549550SPAPJ696.01c_719090_723684_-1_vps17_I_protein_...0+5495490...549SPAPJ696.01c_vps17_I_retromer0+5495500+27951236.919342
5434.900143e-3202.300000e-275430431SPAPJ696.02_724145_725946_1_lsb4_I_protein_cod...0+4304300...430SPAPJ696.02_lsb4_I_actin0+4304310+2195972.096798
\n", "

477 rows × 26 columns

\n", "
" ], "text/plain": [ " E EG2_x q_aln_len q_len \\\n", "0 0.000000e+00 0.000000e+00 1473 1474 \n", "1 0.000000e+00 0.000000e+00 1168 1169 \n", "2 0.000000e+00 0.000000e+00 600 601 \n", "3 1.500000e-275 1.100000e-234 351 352 \n", "5 3.700000e-173 3.700000e-143 227 243 \n", "6 1.600000e-184 3.000000e-153 257 258 \n", "7 1.400000e-142 1.600000e-115 188 189 \n", "8 2.100000e-249 1.600000e-212 341 358 \n", "9 0.000000e+00 0.000000e+00 908 916 \n", "10 3.400000e-57 8.700000e-40 79 96 \n", "11 9.200000e-110 3.700000e-86 150 151 \n", "12 8.600000e-241 2.400000e-203 302 303 \n", "13 3.200000e-92 1.300000e-70 130 131 \n", "15 0.000000e+00 0.000000e+00 546 547 \n", "16 0.000000e+00 5.700000e-290 455 456 \n", "18 0.000000e+00 0.000000e+00 637 638 \n", "19 0.000000e+00 0.000000e+00 550 551 \n", "21 2.000000e-298 1.100000e-255 394 395 \n", "22 0.000000e+00 6.100000e-281 434 435 \n", "24 1.100000e-281 3.800000e-240 357 358 \n", "27 2.700000e-165 7.600000e-136 222 223 \n", "28 0.000000e+00 0.000000e+00 1260 1261 \n", "29 0.000000e+00 0.000000e+00 1317 1318 \n", "30 1.000000e-97 2.900000e-75 131 132 \n", "31 0.000000e+00 0.000000e+00 585 586 \n", "32 0.000000e+00 0.000000e+00 498 499 \n", "33 0.000000e+00 0.000000e+00 542 543 \n", "34 5.300000e-122 4.700000e-97 164 165 \n", "35 0.000000e+00 0.000000e+00 507 508 \n", "36 4.700000e-190 1.200000e-157 248 249 \n", ".. ... ... ... ... \n", "513 1.900000e-264 2.100000e-225 357 358 \n", "514 3.100000e-250 2.200000e-212 331 332 \n", "515 0.000000e+00 0.000000e+00 508 509 \n", "516 0.000000e+00 0.000000e+00 488 489 \n", "517 2.100000e-112 1.500000e-88 154 155 \n", "518 0.000000e+00 1.600000e-282 451 452 \n", "519 0.000000e+00 0.000000e+00 469 470 \n", "520 0.000000e+00 0.000000e+00 1562 1563 \n", "521 1.100000e-243 2.900000e-206 316 317 \n", "522 7.400000e-108 2.000000e-84 146 147 \n", "523 8.900000e-108 2.700000e-84 145 146 \n", "524 9.500000e-126 1.700000e-100 169 173 \n", "525 7.200000e-154 9.500000e-126 204 205 \n", "526 2.200000e-142 2.200000e-115 189 195 \n", "527 5.780568e-322 1.500000e-276 416 417 \n", "528 5.800000e-174 5.900000e-144 236 237 \n", "529 0.000000e+00 0.000000e+00 673 674 \n", "530 0.000000e+00 0.000000e+00 468 544 \n", "531 2.300000e-239 2.100000e-202 311 312 \n", "532 7.400000e-262 3.900000e-223 356 357 \n", "533 3.100000e-266 1.000000e-226 351 352 \n", "534 7.600000e-194 1.300000e-161 247 257 \n", "535 0.000000e+00 0.000000e+00 591 592 \n", "537 0.000000e+00 0.000000e+00 598 599 \n", "538 8.700000e-98 2.200000e-75 133 134 \n", "539 0.000000e+00 0.000000e+00 1687 1688 \n", "540 2.600000e-121 8.700000e-97 172 173 \n", "541 2.100000e-86 3.700000e-65 117 118 \n", "542 0.000000e+00 0.000000e+00 549 550 \n", "543 4.900143e-320 2.300000e-275 430 431 \n", "\n", " q_name q_start_x q_strand_x \\\n", "0 SPAC10F6.01c_1200916_1206090_-1_sir1_I_protein... 0 + \n", "1 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 0 + \n", "2 SPAC10F6.03c_1211195_1213553_-1_cts1_I_protein... 0 + \n", "3 SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr... 0 + \n", "5 SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein... 15 + \n", "6 SPAC10F6.06_1217077_1218228_1_vip1_I_protein_c... 0 + \n", "7 SPAC10F6.07c_1218321_1218887_-1_mug94_I_protei... 0 + \n", "8 SPAC10F6.08c_1219667_1220847_-1_nht1_I_protein... 16 + \n", "9 SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein... 8 + \n", "10 SPAC11D3.01c_108732_109195_-1_SPAC11D3.01c_I_p... 16 + \n", "11 SPAC11D3.02c_109829_110455_-1_SPAC11D3.02c_I_p... 0 + \n", "12 SPAC11D3.03c_110904_112499_-1_SPAC11D3.03c_I_p... 0 + \n", "13 SPAC11D3.04c_112514_114445_-1_SPAC11D3.04c_I_p... 0 + \n", "15 SPAC11D3.05_113950_115962_1_mfs2_I_protein_cod... 0 + \n", "16 SPAC11D3.06_116331_118189_1_SPAC11D3.06_I_prot... 0 + \n", "18 SPAC11D3.07c_116054_120309_-1_toe4_I_protein_c... 0 + \n", "19 SPAC11D3.08c_120321_123785_-1_SPAC11D3.08c_I_p... 0 + \n", "21 SPAC11D3.09_122187_124116_1_SPAC11D3.09_I_prot... 0 + \n", "22 SPAC11D3.10_124907_129053_1_SPAC11D3.10_I_prot... 0 + \n", "24 SPAC11D3.11c_126951_129316_-1_SPAC11D3.11c_I_p... 0 + \n", "27 SPAC11D3.13_130148_131268_1_hsp3104_I_protein_... 0 + \n", "28 SPAC11D3.14c_131190_135736_-1_SPAC11D3.14c_I_p... 0 + \n", "29 SPAC11D3.15_136139_140365_1_SPAC11D3.15_I_prot... 0 + \n", "30 SPAC11D3.16c_140381_141653_-1_SPAC11D3.16c_I_p... 0 + \n", "31 SPAC11D3.17_141199_144768_1_SPAC11D3.17_I_prot... 0 + \n", "32 SPAC11D3.18c_144819_146935_-1_SPAC11D3.18c_I_p... 0 + \n", "33 SPAC1296.01c_707948_710479_-1_SPAC1296.01c_I_p... 0 + \n", "34 SPAC1296.02_711238_712354_1_cox4_I_protein_cod... 0 + \n", "35 SPAC1296.03c_712217_714070_-1_sxa2_I_protein_c... 0 + \n", "36 SPAC1296.04_715377_716978_1_mug65_I_protein_co... 0 + \n", ".. ... ... ... \n", "513 SPAC821.05_988076_989866_1_tif38_I_protein_cod... 0 + \n", "514 SPAC821.06_990192_991889_1_spn2_I_protein_codi... 0 + \n", "515 SPAC821.07c_991632_994230_-1_moc3_I_protein_co... 0 + \n", "516 SPAC821.08c_994941_997625_-1_slp1_I_protein_co... 0 + \n", "517 SPAC821.10c_1002838_1003600_-1_sod1_I_protein_... 0 + \n", "518 SPAC821.11_1006259_1008003_1_pro1_I_protein_co... 0 + \n", "519 SPAC821.12_1008215_1010318_1_orb6_I_protein_co... 0 + \n", "520 SPAC821.13c_1010343_1015415_-1_dnf1_I_protein_... 0 + \n", "521 SPAC977.01_29764_31069_1_SPAC977.01_I_protein_... 0 + \n", "522 SPAC977.02_32034_33012_1_SPAC977.02_I_protein_... 0 + \n", "523 SPAC977.03_33835_34272_1_SPAC977.03_I_protein_... 0 + \n", "524 SPAC977.04_34298_34978_1_SPAC977.04_I_protein_... 3 + \n", "525 SPAC977.05c_35768_36382_-1_SPAC977.05c_I_prote... 0 + \n", "526 SPAC977.06_39416_40072_1_SPAC977.06_I_protein_... 5 + \n", "527 SPAC977.07c_42057_43307_-1_pfl6_I_protein_codi... 0 + \n", "528 SPAC977.08_44644_45468_1_SPAC977.08_I_protein_... 0 + \n", "529 SPAC977.09c_45875_48399_-1_SPAC977.09c_I_prote... 0 + \n", "530 SPAC977.10_50946_53858_1_sod2_I_protein_coding... 75 + \n", "531 SPAC977.11_55059_56308_1_SPAC977.11_I_protein_... 0 + \n", "532 SPAC977.12_56373_57736_1_SPAC977.12_I_protein_... 0 + \n", "533 SPAC977.14c_59614_60907_-1_SPAC977.14c_I_prote... 0 + \n", "534 SPAC977.15_62961_63862_1_SPAC977.15_I_protein_... 9 + \n", "535 SPAC977.16c_64559_66980_-1_dak2_I_protein_codi... 0 + \n", "537 SPAC977.17_66219_69821_1_SPAC977.17_I_protein_... 0 + \n", "538 SPAC977.18_31140_32345_-1_SPAC977.18_I_protein... 0 + \n", "539 SPAPB21F2.02_492335_497927_1_SPAPB21F2.02_I_pr... 0 + \n", "540 SPAPB21F2.03_498111_499027_1_slx9_I_protein_co... 0 + \n", "541 SPAPJ695.01c_77480_78066_-1_SPAPJ695.01c_I_pro... 0 + \n", "542 SPAPJ696.01c_719090_723684_-1_vps17_I_protein_... 0 + \n", "543 SPAPJ696.02_724145_725946_1_lsb4_I_protein_cod... 0 + \n", "\n", " s_aln_len_x s_len_x s_start_x ... s_len \\\n", "0 1473 1473 0 ... 1473 \n", "1 1168 1168 0 ... 1168 \n", "2 600 600 0 ... 600 \n", "3 351 351 0 ... 351 \n", "5 227 227 0 ... 227 \n", "6 257 257 0 ... 257 \n", "7 188 188 0 ... 188 \n", "8 341 341 0 ... 341 \n", "9 908 1194 0 ... 1194 \n", "10 79 79 0 ... 79 \n", "11 150 150 0 ... 150 \n", "12 302 302 0 ... 302 \n", "13 130 130 0 ... 130 \n", "15 546 546 0 ... 546 \n", "16 455 455 0 ... 455 \n", "18 637 637 0 ... 637 \n", "19 550 550 0 ... 550 \n", "21 394 394 0 ... 394 \n", "22 434 434 0 ... 434 \n", "24 357 357 0 ... 357 \n", "27 222 222 0 ... 222 \n", "28 1260 1260 0 ... 1260 \n", "29 1317 1317 0 ... 1317 \n", "30 131 131 0 ... 131 \n", "31 585 585 0 ... 585 \n", "32 498 498 0 ... 498 \n", "33 542 542 0 ... 542 \n", "34 164 164 0 ... 164 \n", "35 507 507 0 ... 507 \n", "36 248 248 0 ... 248 \n", ".. ... ... ... ... ... \n", "513 357 357 0 ... 357 \n", "514 331 331 0 ... 331 \n", "515 508 508 0 ... 508 \n", "516 488 488 0 ... 488 \n", "517 154 154 0 ... 154 \n", "518 451 451 0 ... 451 \n", "519 469 469 0 ... 469 \n", "520 1562 1562 0 ... 1562 \n", "521 316 316 0 ... 316 \n", "522 146 146 0 ... 146 \n", "523 145 145 0 ... 145 \n", "524 169 485 316 ... 485 \n", "525 204 204 0 ... 204 \n", "526 189 189 0 ... 189 \n", "527 416 416 0 ... 416 \n", "528 236 236 0 ... 236 \n", "529 673 673 0 ... 673 \n", "530 468 468 0 ... 468 \n", "531 311 311 0 ... 311 \n", "532 356 356 0 ... 356 \n", "533 351 351 0 ... 351 \n", "534 247 247 0 ... 247 \n", "535 591 591 0 ... 591 \n", "537 598 598 0 ... 598 \n", "538 133 133 0 ... 133 \n", "539 1687 1687 0 ... 1687 \n", "540 172 172 0 ... 172 \n", "541 117 117 0 ... 117 \n", "542 549 549 0 ... 549 \n", "543 430 430 0 ... 430 \n", "\n", " s_name q_start_y q_strand_y \\\n", "0 SPAC10F6.01c_sir1_I_sulfite 0 + \n", "1 SPAC10F6.02c_prp22_I_ATP-dependent 0 + \n", "2 SPAC10F6.03c_cts1_I_CTP 0 + \n", "3 SPAC10F6.04_SPAC10F6.04_I_RCC 0 + \n", "5 SPAC10F6.05c_ubc6_I_ubiquitin 0 + \n", "6 SPAC10F6.06_vip1_I_RNA-binding 0 + \n", "7 SPAC10F6.07c_mug94_I_Schizosaccharomyces 0 + \n", "8 SPAC10F6.08c_nht1_I_Ino80 0 + \n", "9 SPAC10F6.09c_psm3_I_mitotic 0 + \n", "10 SPAC11D3.01c_SPAC11D3.01c_I_conserved 0 + \n", "11 SPAC11D3.02c_SPAC11D3.02c_I_ELLA 0 + \n", "12 SPAC11D3.03c_SPAC11D3.03c_I_conserved 0 + \n", "13 SPAC11D3.04c_SPAC11D3.04c_I_polyketide 0 + \n", "15 SPAC11D3.05_mfs2_I_MFS 0 + \n", "16 SPAC11D3.06_SPAC11D3.06_I_MatE 0 + \n", "18 SPAC11D3.07c_toe4_I_transcription 0 + \n", "19 SPAC11D3.08c_SPAC11D3.08c_I_amino 0 + \n", "21 SPAC11D3.09_SPAC11D3.09_I_agmatinase 0 + \n", "22 SPAC11D3.10_SPAC11D3.10_I_nifs 0 + \n", "24 SPAC11D3.11c_SPAC11D3.11c_I_zn(2)-C6 0 + \n", "27 SPAC11D3.13_hsp3104_I_ThiJ 0 + \n", "28 SPAC11D3.14c_SPAC11D3.14c_I_5-oxoprolinase 0 + \n", "29 SPAC11D3.15_SPAC11D3.15_I_5-oxoprolinase 0 + \n", "30 SPAC11D3.16c_SPAC11D3.16c_I_Schizosaccharomyces 0 + \n", "31 SPAC11D3.17_SPAC11D3.17_I_transcription 0 + \n", "32 SPAC11D3.18c_SPAC11D3.18c_I_plasma 0 + \n", "33 SPAC1296.01c_SPAC1296.01c_I_phosphoacetylgluco... 0 + \n", "34 SPAC1296.02_cox4_I_cytochrome 0 + \n", "35 SPAC1296.03c_sxa2_I_serine 0 + \n", "36 SPAC1296.04_mug65_I_spore 0 + \n", ".. ... ... ... \n", "513 SPAC821.05_tif38_I_translation 0 + \n", "514 SPAC821.06_spn2_I_mitotic 0 + \n", "515 SPAC821.07c_moc3_I_transcription 0 + \n", "516 SPAC821.08c_slp1_I_substrate-specific 0 + \n", "517 SPAC821.10c_sod1_I_superoxide 0 + \n", "518 SPAC821.11_pro1_I_gamma-glutamyl 0 + \n", "519 SPAC821.12_orb6_I_serine_threonine 0 + \n", "520 SPAC821.13c_dnf1_I_Trans-golgi 0 + \n", "521 SPAC977.01_SPAC977.01_I_S. 0 + \n", "522 SPAC977.02_SPAC977.02_I_S. 0 + \n", "523 SPAC977.03_SPAC977.03_I_methyltransferase 0 + \n", "524 SPAC750.02c_SPAC750.02c_I_transmembrane 316 + \n", "525 SPAC977.05c_SPAC977.05c_I_conserved 0 + \n", "526 SPAC977.06_SPAC977.06_I_S. 0 + \n", "527 SPAC977.07c_pfl6_I_cell 0 + \n", "528 SPAC977.08_SPAC977.08_I_short 0 + \n", "529 SPAC977.09c_SPAC977.09c_I_phospholipase 0 + \n", "530 SPAC977.10_sod2_I_plasma 0 + \n", "531 SPAC977.11_SPAC977.11_I_CRCB 0 + \n", "532 SPAC977.12_SPAC977.12_I_L-asparaginase 0 + \n", "533 SPAC977.14c_SPAC977.14c_I_aldo_keto 0 + \n", "534 SPAC977.15_SPAC977.15_I_dienelactone 0 + \n", "535 SPAC977.16c_dak2_I_dihydroxyacetone 0 + \n", "537 SPAC977.17_SPAC977.17_I_MIP 0 + \n", "538 SPAC977.18_SPAC977.18_I_conserved 0 + \n", "539 SPAPB21F2.02_SPAPB21F2.02_I_Dopey 0 + \n", "540 SPAPB21F2.03_slx9_I_ribosome 0 + \n", "541 SPAPJ695.01c_SPAPJ695.01c_I_S. 0 + \n", "542 SPAPJ696.01c_vps17_I_retromer 0 + \n", "543 SPAPJ696.02_lsb4_I_actin 0 + \n", "\n", " s_aln_len_y s_len_y s_start_y s_strand_y score_y bitscore_y \n", "0 1473 1474 0 + 7597 3356.382439 \n", "1 1168 1169 0 + 6008 2655.044067 \n", "2 600 601 0 + 3123 1381.689000 \n", "3 351 352 0 + 1889 837.037300 \n", "5 227 243 15 + 1200 532.932745 \n", "6 257 258 0 + 1276 566.476934 \n", "7 188 189 0 + 992 441.127596 \n", "8 341 358 16 + 1722 763.328358 \n", "9 908 916 8 + 4532 2003.580608 \n", "10 79 96 16 + 422 189.546179 \n", "11 150 151 0 + 771 343.584626 \n", "12 302 303 0 + 1653 732.873766 \n", "13 130 131 0 + 654 291.944229 \n", "15 546 547 0 + 2905 1285.470142 \n", "16 455 456 0 + 2305 1020.647597 \n", "18 637 638 0 + 3330 1473.052777 \n", "19 550 551 0 + 2833 1253.691437 \n", "21 394 395 0 + 2047 906.773903 \n", "22 434 435 0 + 2237 990.634376 \n", "24 357 358 0 + 1930 855.133507 \n", "27 222 223 0 + 1145 508.657345 \n", "28 1260 1261 0 + 6526 2883.674197 \n", "29 1317 1318 0 + 6787 2998.872004 \n", "30 131 132 0 + 689 307.392211 \n", "31 585 586 0 + 3105 1373.744323 \n", "32 498 499 0 + 2554 1130.548953 \n", "33 542 543 0 + 2745 1214.850797 \n", "34 164 165 0 + 853 379.777040 \n", "35 507 508 0 + 2653 1174.244673 \n", "36 248 249 0 + 1309 581.042174 \n", ".. ... ... ... ... ... ... \n", "513 357 358 0 + 1819 806.141336 \n", "514 331 332 0 + 1721 762.886988 \n", "515 508 509 0 + 2674 1183.513462 \n", "516 488 489 0 + 2574 1139.376372 \n", "517 154 155 0 + 789 351.529302 \n", "518 451 452 0 + 2249 995.930827 \n", "519 469 470 0 + 2482 1098.770248 \n", "520 1562 1563 0 + 8035 3549.702896 \n", "521 316 317 0 + 1675 742.583926 \n", "522 146 147 0 + 758 337.846804 \n", "523 145 146 0 + 757 337.405433 \n", "524 169 173 3 + 879 391.252684 \n", "525 204 205 0 + 1069 475.113156 \n", "526 189 195 5 + 991 440.686225 \n", "527 416 417 0 + 2204 976.069136 \n", "528 236 237 0 + 1206 535.580970 \n", "529 673 674 0 + 3581 1583.836875 \n", "530 468 544 75 + 2433 1077.143074 \n", "531 311 312 0 + 1646 729.784169 \n", "532 356 357 0 + 1802 798.638031 \n", "533 351 352 0 + 1829 810.555046 \n", "534 247 257 9 + 1339 594.283301 \n", "535 591 592 0 + 3014 1333.579571 \n", "537 598 599 0 + 3180 1406.847141 \n", "538 133 134 0 + 690 307.833582 \n", "539 1687 1688 0 + 8609 3803.049797 \n", "540 172 173 0 + 851 378.894298 \n", "541 117 118 0 + 613 273.848022 \n", "542 549 550 0 + 2795 1236.919342 \n", "543 430 431 0 + 2195 972.096798 \n", "\n", "[477 rows x 26 columns]" ] }, "execution_count": 223, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rbh_pep_df" ] }, { "cell_type": "code", "execution_count": 227, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SPAC10F6.01c_1200916_1206090_-1_sir1_I_protein_coding_sulfite|m.826 \tSPAC10F6.01c_sir1_I_sulfite \n", "\n", "SPAC10F6.02c_1206812_1210630_-1_prp22_I_protein_coding_ATP-dependent|m.834 \tSPAC10F6.02c_prp22_I_ATP-dependent \n", "\n", "SPAC10F6.03c_1211195_1213553_-1_cts1_I_protein_coding_CTP|m.835 \tSPAC10F6.03c_cts1_I_CTP \n", "\n", "SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_protein_coding_RCC|m.839 \tSPAC10F6.04_SPAC10F6.04_I_RCC \n", "\n", "SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein_coding_ubiquitin|m.841 \tSPAC10F6.05c_ubc6_I_ubiquitin \n", "\n", "SPAC10F6.06_1217077_1218228_1_vip1_I_protein_coding_RNA-binding|m.843 \tSPAC10F6.06_vip1_I_RNA-binding \n", "\n", "SPAC10F6.07c_1218321_1218887_-1_mug94_I_protein_coding_Schizosaccharomyces|m.844 \tSPAC10F6.07c_mug94_I_Schizosaccharomyces \n", "\n", "SPAC10F6.08c_1219667_1220847_-1_nht1_I_protein_coding_Ino80|m.846 \tSPAC10F6.08c_nht1_I_Ino80 \n", "\n", "SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein_coding_mitotic|m.847 \tSPAC10F6.09c_psm3_I_mitotic \n", "\n", "SPAC10F6.10_1225464_1227365_1_rio1_I_protein_coding_protein|m.848 \tSPAC10F6.10_rio1_I_protein \n", "\n", "SPAC11D3.01c_108732_109195_-1_SPAC11D3.01c_I_protein_coding_conserved|m.52 \tSPAC11D3.01c_SPAC11D3.01c_I_conserved \n", "\n", "SPAC11D3.02c_109829_110455_-1_SPAC11D3.02c_I_protein_coding_ELLA|m.53 \tSPAC11D3.02c_SPAC11D3.02c_I_ELLA \n", "\n", "SPAC11D3.03c_110904_112499_-1_SPAC11D3.03c_I_protein_coding_conserved|m.54 \tSPAC11D3.03c_SPAC11D3.03c_I_conserved \n", "\n", "SPAC11D3.04c_112514_114445_-1_SPAC11D3.04c_I_protein_coding_polyketide|m.56 \tSPAC11D3.04c_SPAC11D3.04c_I_polyketide \n", "\n", "SPAC11D3.05_113950_115962_1_mfs2_I_protein_coding_MFS|m.58 \tSPAC11D3.05_mfs2_I_MFS \n", "\n", "SPAC11D3.06_116331_118189_1_SPAC11D3.06_I_protein_coding_MatE|m.65 \tSPAC11D3.06_SPAC11D3.06_I_MatE \n", "\n", "SPAC11D3.07c_116054_120309_-1_toe4_I_protein_coding_transcription|m.61 \tSPAC11D3.07c_toe4_I_transcription \n", "\n", "SPAC11D3.08c_120321_123785_-1_SPAC11D3.08c_I_protein_coding_amino|m.67 \tSPAC11D3.08c_SPAC11D3.08c_I_amino \n", "\n", "SPAC11D3.09_122187_124116_1_SPAC11D3.09_I_protein_coding_agmatinase|m.71 \tSPAC11D3.09_SPAC11D3.09_I_agmatinase \n", "\n", "SPAC11D3.10_124907_129053_1_SPAC11D3.10_I_protein_coding_nifs|m.74 \tSPAC11D3.10_SPAC11D3.10_I_nifs \n", "\n", "SPAC11D3.11c_126951_129316_-1_SPAC11D3.11c_I_protein_coding_zn(2)-C6|m.78 \tSPAC11D3.11c_SPAC11D3.11c_I_zn(2)-C6 \n", "\n", "SPAC11D3.13_130148_131268_1_hsp3104_I_protein_coding_ThiJ|m.80 \tSPAC11D3.13_hsp3104_I_ThiJ \n", "\n", "SPAC11D3.14c_131190_135736_-1_SPAC11D3.14c_I_protein_coding_5-oxoprolinase|m.81 \tSPAC11D3.14c_SPAC11D3.14c_I_5-oxoprolinase \n", "\n", "SPAC11D3.15_136139_140365_1_SPAC11D3.15_I_protein_coding_5-oxoprolinase|m.83 \tSPAC11D3.15_SPAC11D3.15_I_5-oxoprolinase \n", "\n", "SPAC11D3.16c_140381_141653_-1_SPAC11D3.16c_I_protein_coding_Schizosaccharomyces|m.86 \tSPAC11D3.16c_SPAC11D3.16c_I_Schizosaccharomyces \n", "\n", "SPAC11D3.17_141199_144768_1_SPAC11D3.17_I_protein_coding_transcription|m.87 \tSPAC11D3.17_SPAC11D3.17_I_transcription \n", "\n", "SPAC11D3.18c_144819_146935_-1_SPAC11D3.18c_I_protein_coding_plasma|m.89 \tSPAC11D3.18c_SPAC11D3.18c_I_plasma \n", "\n", "SPAC1296.01c_707948_710479_-1_SPAC1296.01c_I_protein_coding_phosphoacetylglucosamine|m.466 \tSPAC1296.01c_SPAC1296.01c_I_phosphoacetylglucosamine \n", "\n", "SPAC1296.02_711238_712354_1_cox4_I_protein_coding_cytochrome|m.468 \tSPAC1296.02_cox4_I_cytochrome \n", "\n", "SPAC1296.03c_712217_714070_-1_sxa2_I_protein_coding_serine|m.469 \tSPAC1296.03c_sxa2_I_serine \n", "\n", "SPAC1296.04_715377_716978_1_mug65_I_protein_coding_spore|m.470 \tSPAC1296.04_mug65_I_spore \n", "\n", "SPAC1296.05c_716874_718168_-1_lcp1_I_protein_coding_cyclin|m.472 \tSPAC1296.05c_lcp1_I_cyclin \n", "\n", "SPAC1296.06_719380_721549_1_tah18_I_protein_coding_NADPH-dependent|m.476 \tSPAC1296.06_tah18_I_NADPH-dependent \n", "\n", "SPAC12G12.01c_346795_350151_1_sea4_I_protein_coding_SEA|m.220 \tSPAC12G12.01c_sea4_I_SEA \n", "\n", "SPAC12G12.02_345234_347735_-1_efg1_I_protein_coding_rRNA|m.218 \tSPAC12G12.02_efg1_I_rRNA \n", "\n", "SPAC12G12.03_342090_345182_-1_cip2_I_protein_coding_RNA-binding|m.215 \tSPAC12G12.03_cip2_I_RNA-binding \n", "\n", "SPAC12G12.04_339766_342080_-1_mcp60_I_protein_coding_mitochondrial|m.213 \tSPAC12G12.04_mcp60_I_mitochondrial \n", "\n", "SPAC12G12.05c_338286_339763_1_taf9_I_protein_coding_SAGA|m.211 \tSPAC12G12.05c_taf9_I_SAGA \n", "\n", "SPAC12G12.06c_336308_338157_1_rcl1_I_protein_coding_rRNA|m.209 \tSPAC12G12.06c_rcl1_I_rRNA \n", "\n", "SPAC12G12.07c_334615_336131_1_SPAC12G12.07c_I_protein_coding_conserved|m.208 \tSPAC12G12.07c_SPAC12G12.07c_I_conserved \n", "\n", "SPAC12G12.08_333178_334621_-1_mrpl1602_I_protein_coding_mitochondrial|m.206 \tSPAC12G12.08_mrpl1602_I_mitochondrial \n", "\n", "SPAC12G12.09_329810_332816_-1_eti1_I_protein_coding_conserved|m.204 \tSPAC12G12.09_eti1_I_conserved \n", "\n", "SPAC12G12.10_328196_329545_-1_wdr21_I_protein_coding_WD|m.203 \tSPAC12G12.10_wdr21_I_WD \n", "\n", "SPAC12G12.11c_326440_328122_1_SPAC12G12.11c_I_protein_coding_DUF544|m.202 \tSPAC12G12.11c_SPAC12G12.11c_I_DUF544 \n", "\n", "SPAC12G12.12_324042_325517_-1_gms2_I_protein_coding_UDP-galactose|m.201 \tSPAC12G12.12_gms2_I_UDP-galactose \n", "\n", "SPAC12G12.13c_321764_324129_1_cid14_I_protein_coding_poly(A)|m.200 \tSPAC12G12.13c_cid14_I_poly(A) \n", "\n", "SPAC12G12.14c_319815_321825_1_pfs2_I_protein_coding_WD|m.198 \tSPAC12G12.14c_pfs2_I_WD \n", "\n", "SPAC12G12.15_316996_319185_-1_sif3_I_protein_coding_mitochondrial|m.196 \tSPAC12G12.15_sif3_I_mitochondrial \n", "\n", "SPAC12G12.16c_315394_317585_1_SPAC12G12.16c_I_protein_coding_Fen1|m.194 \tSPAC12G12.16c_SPAC12G12.16c_I_Fen1 \n", "\n", "SPAC139.02c_1019248_1020838_-1_oac1_I_protein_coding_mitochondrial|m.669 \tSPAC139.02c_oac1_I_mitochondrial \n", "\n", "SPAC139.03_1021695_1024135_1_toe2_I_protein_coding_transcription|m.671 \tSPAC139.03_toe2_I_transcription \n", "\n", "SPAC139.04c_1024002_1025903_-1_fap2_I_protein_coding_L-saccharopine|m.672 \tSPAC139.04c_fap2_I_L-saccharopine \n", "\n", "SPAC139.05_1027811_1029993_1_SPAC139.05_I_protein_coding_succinate-semialdehyde|m.673 \tSPAC139.05_SPAC139.05_I_succinate-semialdehyde \n", "\n", "SPAC139.06_1030125_1031941_1_hat1_I_protein_coding_histone|m.674 \tSPAC139.06_hat1_I_histone \n", "\n", "SPAC13A11.01c_570753_574417_-1_rga8_I_protein_coding_Rho-type|m.376 \tSPAC13A11.01c_rga8_I_Rho-type \n", "\n", "SPAC2F7.17_569550_571876_1_mrf1_I_protein_coding_mitochondrial|m.375 \tSPAC2F7.17_mrf1_I_mitochondrial \n", "\n", "SPAC13A11.02c_574652_577171_-1_erg11_I_protein_coding_sterol|m.378 \tSPAC13A11.02c_erg11_I_sterol \n", "\n", "SPAC13A11.03_578392_579948_1_mcp7_I_protein_coding_meiosis|m.380 \tSPAC13A11.03_mcp7_I_meiosis \n", "\n", "SPAC13A11.04c_579353_581553_-1_ubp8_I_protein_coding_SAGA|m.381 \tSPAC13A11.04c_ubp8_I_SAGA \n", "\n", "SPAC13A11.05_582273_584402_1_ysp2_I_protein_coding_peptidase|m.383 \tSPAC13A11.05_ysp2_I_peptidase \n", "\n", "SPAC13A11.06_585355_587495_1_SPAC13A11.06_I_protein_coding_pyruvate|m.385 \tSPAC13A11.06_SPAC13A11.06_I_pyruvate \n", "\n", "SPAC13C5.01c_423926_425256_-1_pre9_I_protein_coding_20S|m.283 \tSPAC13C5.01c_pre9_I_20S \n", "\n", "SPAC13C5.02_425631_427415_1_dre4_I_protein_coding_splicing|m.284 \tSPAC13C5.02_dre4_I_splicing \n", "\n", "SPAC13C5.03_427350_430121_1_tht1_I_protein_coding_nuclear|m.285 \tSPAC13C5.03_tht1_I_nuclear \n", "\n", "SPAC13C5.04_430056_431032_1_SPAC13C5.04_I_protein_coding_amidotransferase|m.286 \tSPAC13C5.04_SPAC13C5.04_I_amidotransferase \n", "\n", "SPAC13C5.05c_431367_433274_-1_SPAC13C5.05c_I_protein_coding_N-acetylglucosamine-phosphate|m.287 \tSPAC13C5.05c_SPAC13C5.05c_I_N-acetylglucosamine-phosphate \n", "\n", "SPAC13C5.06c_434102_435179_-1_mug121_I_protein_coding_Schizosaccharomyces|m.288 \tSPAC13C5.06c_mug121_I_Schizosaccharomyces \n", "\n", "SPAC13C5.07_435170_439980_1_mre11_I_protein_coding_Mre11|m.289 \tSPAC13C5.07_mre11_I_Mre11 \n", "\n", "SPAC13G6.01c_170489_174701_-1_rad8_I_protein_coding_ubiquitin-protein|m.110 \tSPAC13G6.01c_rad8_I_ubiquitin-protein \n", "\n", "SPAC13G6.02c_174865_176655_-1_rps101_I_protein_coding_40S|m.113 \tSPAC13G6.02c_rps101_I_40S \n", "\n", "SPAC13G6.03_175890_180028_1_gpi7_I_protein_coding_GPI|m.114 \tSPAC13G6.03_gpi7_I_GPI \n", "\n", "SPAC13G6.04_180272_181069_1_tim8_I_protein_coding_TIM22|m.115 \tSPAC13G6.04_tim8_I_TIM22 \n", "\n", "SPAC13G6.05c_180903_182254_-1_trs33_I_protein_coding_TRAPP|m.116 \tSPAC13G6.05c_trs33_I_TRAPP \n", "\n", "SPAC13G6.06c_182337_186358_-1_gcv2_I_protein_coding_glycine|m.117 \tSPAC13G6.06c_gcv2_I_glycine \n", "\n", "SPAC13G6.07c_186314_187683_-1_rps601_I_protein_coding_40S|m.118 \tSPAC13G6.07c_rps601_I_40S \n", "\n", "SPAC13G6.08_187701_190031_1_SPAC13G6.08_I_protein_coding_Cdc20_Fizzy|m.120 \tSPAC13G6.08_SPAC13G6.08_I_Cdc20_Fizzy \n", "\n", "SPAC13G6.09_190192_191947_1_SPAC13G6.09_I_protein_coding_SSU-rRNA|m.122 \tSPAC13G6.09_SPAC13G6.09_I_SSU-rRNA \n", "\n", "SPAC13G6.10c_191928_194053_-1_asl1_I_protein_coding_cell|m.123 \tSPAC13G6.10c_asl1_I_cell \n", "\n", "SPAC13G6.11c_194099_195626_-1_erg12_I_protein_coding_mevalonate|m.124 \tSPAC13G6.11c_erg12_I_mevalonate \n", "\n", "SPAC13G6.12c_195940_199051_-1_chs1_I_protein_coding_chitin|m.125 \tSPAC13G6.12c_chs1_I_chitin \n", "\n", "SPAC13G6.13_198884_199231_1_SPAC13G6.13_I_protein_coding_Schizosaccharomyces|m.126 \tSPAC13G6.13_SPAC13G6.13_I_Schizosaccharomyces \n", "\n", "SPAC13G6.14_200121_201517_1_aps1_I_protein_coding_diadenosine|m.127 \tSPAC13G6.14_aps1_I_diadenosine \n", "\n", "SPAC13G6.15c_201729_203346_-1_SPAC13G6.15c_I_protein_coding_calcipressin|m.128 \tSPAC13G6.15c_SPAC13G6.15c_I_calcipressin \n", "\n", "SPAC1639.01c_251173_254600_-1_SPAC1639.01c_I_protein_coding_GNS1_SUR4|m.163 \tSPAC1639.01c_SPAC1639.01c_I_GNS1_SUR4 \n", "\n", "SPAC1639.02c_255881_259505_-1_trk2_I_protein_coding_potassium|m.165 \tSPAC1639.02c_trk2_I_potassium \n", "\n", "SPAC1687.01_903042_903861_1_rpc19_I_protein_coding_DNA-directed|m.587 \tSPAC1687.01_rpc19_I_DNA-directed \n", "\n", "SPAC1687.03c_905077_906465_-1_rfc4_I_protein_coding_DNA|m.591 \tSPAC1687.03c_rfc4_I_DNA \n", "\n", "SPAC1687.02_904026_906347_1_SPAC1687.02_I_protein_coding_CAAX|m.589 \tSPAC1687.02_SPAC1687.02_I_CAAX \n", "\n", "SPAC1687.04_906778_908799_1_mcb1_I_protein_coding_MCM|m.592 \tSPAC1687.04_mcb1_I_MCM \n", "\n", "SPAC1687.05_908736_911854_1_pli1_I_protein_coding_SUMO|m.593 \tSPAC1687.05_pli1_I_SUMO \n", "\n", "SPAC1687.05_908736_911854_1_pli1_I_protein_coding_SUMO|m.594 \tSPAC1687.06c_rpl44_I_60S \n", "\n", "SPAC1687.07_913657_914031_1_SPAC1687.07_I_protein_coding_conserved|m.598 \tSPAC1687.07_SPAC1687.07_I_conserved \n", "\n", "SPAC1687.08_914328_914618_1_SPAC1687.08_I_protein_coding_Schizosaccharomyces|m.599 \tSPAC1687.08_SPAC1687.08_I_Schizosaccharomyces \n", "\n", "SPAC1687.09_914940_919775_1_tax4_I_protein_coding_autophagy_CVT|m.600 \tSPAC1687.09_tax4_I_autophagy_CVT \n", "\n", "SPAC1687.10_919726_922098_1_mcp1_I_protein_coding_microtubule|m.602 \tSPAC1687.10_mcp1_I_microtubule \n", "\n", "SPAC1687.11_922271_925133_1_spb1_I_protein_coding_rRNA|m.603 \tSPAC1687.11_spb1_I_rRNA \n", "\n", "SPAC1687.12c_925111_926289_-1_coq4_I_protein_coding_ubiquinone|m.604 \tSPAC1687.12c_coq4_I_ubiquinone \n", "\n", "SPAC1687.13c_926394_927671_-1_csn5_I_protein_coding_COP9_signalosome|m.605 \tSPAC1687.13c_csn5_I_COP9_signalosome \n", "\n", "SPAC1687.15_929843_932197_1_gsk3_I_protein_coding_serine_threonine|m.607 \tSPAC1687.15_gsk3_I_serine_threonine \n", "\n", "SPAC1687.16c_932425_934021_-1_erg31_I_protein_coding_C-5|m.610 \tSPAC1687.16c_erg31_I_C-5 \n", "\n", "SPAC1687.17c_934941_936081_-1_SPAC1687.17c_I_protein_coding_Der1-like|m.612 \tSPAC1687.17c_SPAC1687.17c_I_Der1-like \n", "\n", "SPAC1687.18c_936188_938157_-1_ssl3_I_protein_coding_cohesin|m.613 \tSPAC1687.18c_ssl3_I_cohesin \n", "\n", "SPAC1687.19c_938311_939831_-1_qtr1_I_protein_coding_queuine|m.614 \tSPAC1687.19c_qtr1_I_queuine \n", "\n", "SPAC1687.20c_939770_941944_-1_mis6_I_protein_coding_inner|m.615 \tSPAC1687.20c_mis6_I_inner \n", "\n", "SPAC1687.21_941942_943335_1_SPAC1687.21_I_protein_coding_phosphoglycerate|m.616 \tSPAC1687.21_SPAC1687.21_I_phosphoglycerate \n", "\n", "SPAC1687.22c_943265_946909_-1_puf3_I_protein_coding_RNA-binding|m.617 \tSPAC1687.22c_puf3_I_RNA-binding \n", "\n", "SPAC1687.23c_929156_929654_-1_SPAC1687.23c_I_protein_coding_Schizosaccharomyces|m.606 \tSPAC1687.23c_SPAC1687.23c_I_Schizosaccharomyces \n", "\n", "SPAC16C9.01c_790245_792274_-1_SPAC16C9.01c_I_protein_coding_carbohydrate|m.519 \tSPAC16C9.01c_SPAC16C9.01c_I_carbohydrate \n", "\n", "SPAC16C9.02c_792521_793937_-1_SPAC16C9.02c_I_protein_coding_S-methyl-5-thioadenosine|m.520 \tSPAC16C9.02c_SPAC16C9.02c_I_S-methyl-5-thioadenosine \n", "\n", "SPAC16C9.03_794866_796821_1_nmd3_I_protein_coding_export|m.522 \tSPAC16C9.03_nmd3_I_export \n", "\n", "SPAC16C9.04c_796876_798833_-1_mot2_I_protein_coding_CCR4-Not|m.523 \tSPAC16C9.04c_mot2_I_CCR4-Not \n", "\n", "SPAC16C9.05_799341_800981_1_cph1_I_protein_coding_Clr6|m.525 \tSPAC16C9.05_cph1_I_Clr6 \n", "\n", "SPAC16C9.06c_801141_804123_-1_upf1_I_protein_coding_ATP-dependent|m.526 \tSPAC16C9.06c_upf1_I_ATP-dependent \n", "\n", "SPAC16C9.07_804574_807722_1_pom2_I_protein_coding_DYRK|m.527 \tSPAC16C9.07_pom2_I_DYRK \n", "\n", "SPAC1751.01c_377844_384751_-1_gti1_I_protein_coding_gluconate|m.245 \tSPAC1751.01c_gti1_I_gluconate \n", "\n", "SPAC1751.02c_384886_386195_-1_rsm19_I_protein_coding_mitochondrial|m.254 \tSPAC1751.02c_rsm19_I_mitochondrial \n", "\n", "SPAC1751.03_386266_387856_1_SPAC1751.03_I_protein_coding_translation|m.255 \tSPAC1751.03_SPAC1751.03_I_translation \n", "\n", "SPAC1751.04_383580_385433_1_loc1_I_protein_coding_ribosome|m.252 \tSPAC1751.04_loc1_I_ribosome \n", "\n", "SPAC18B11.02c_313974_315335_1_SPAC18B11.02c_I_protein_coding_tRNA|m.192 \tSPAC18B11.02c_SPAC18B11.02c_I_tRNA \n", "\n", "SPAC18B11.03c_311920_314040_1_SPAC18B11.03c_I_protein_coding_N-acetyltransferase|m.191 \tSPAC18B11.03c_SPAC18B11.03c_I_N-acetyltransferase \n", "\n", "SPAC18B11.04_310157_311712_-1_ncs1_I_protein_coding_neuronal|m.190 \tSPAC18B11.04_ncs1_I_neuronal \n", "\n", "SPAC18B11.06_306764_308031_-1_lcp5_I_protein_coding_U3|m.187 \tSPAC18B11.06_lcp5_I_U3 \n", "\n", "SPAC18B11.07c_305602_306762_1_rhp6_I_protein_coding_Rad6|m.185 \tSPAC18B11.07c_rhp6_I_Rad6 \n", "\n", "SPAC18B11.08c_304355_305168_1_SPAC18B11.08c_I_protein_coding_conserved|m.184 \tSPAC18B11.08c_SPAC18B11.08c_I_conserved \n", "\n", "SPAC18B11.09c_303004_304161_1_SPAC18B11.09c_I_protein_coding_serine|m.183 \tSPAC18B11.09c_SPAC18B11.09c_I_serine \n", "\n", "SPAC18B11.10_299278_301837_-1_tup11_I_protein_coding_transcriptional|m.182 \tSPAC18B11.10_tup11_I_transcriptional \n", "\n", "SPAC18B11.11_294591_299154_-1_SPAC18B11.11_I_protein_coding_GTPase|m.181 \tSPAC18B11.11_SPAC18B11.11_I_GTPase \n", "\n", "SPAC1A6.01c_1066192_1070006_-1_SPAC1A6.01c_I_protein_coding_human|m.708 \tSPAC1A6.01c_SPAC1A6.01c_I_human \n", "\n", "SPAC1A6.01c_1066192_1070006_-1_SPAC1A6.01c_I_protein_coding_human|m.709 \tSPAC1A6.02_SPAC1A6.02_I_WD \n", "\n", "SPAC23C4.19_1063729_1066954_1_spt5_I_protein_coding_DSIF|m.700 \tSPAC23C4.19_spt5_I_DSIF \n", "\n", "SPAC1A6.03c_1069923_1072343_-1_SPAC1A6.03c_I_protein_coding_phospholipase|m.714 \tSPAC1A6.03c_SPAC1A6.03c_I_phospholipase \n", "\n", "SPAC1A6.04c_1074331_1077514_-1_plb1_I_protein_coding_phospholipase|m.719 \tSPAC1A6.04c_plb1_I_phospholipase \n", "\n", "SPAC1A6.05c_1079635_1081713_-1_ptl3_I_protein_coding_triacylglycerol|m.725 \tSPAC1A6.05c_ptl3_I_triacylglycerol \n", "\n", "SPAC1A6.06c_1081916_1083616_-1_meu31_I_protein_coding_Schizosaccharomyces|m.726 \tSPAC1A6.06c_meu31_I_Schizosaccharomyces \n", "\n", "SPAC1A6.07_1084068_1086426_1_sle1_I_protein_coding_eisosome|m.727 \tSPAC1A6.07_sle1_I_eisosome \n", "\n", "SPAC1A6.08c_1086242_1087505_-1_mug125_I_protein_coding_Schizosaccharomyces|m.729 \tSPAC1A6.08c_mug125_I_Schizosaccharomyces \n", "\n", "SPAC1A6.09c_1087443_1089673_-1_lag1_I_protein_coding_sphingosine|m.730 \tSPAC1A6.09c_lag1_I_sphingosine \n", "\n", "SPAC1A6.10_1090678_1092303_1_tcd1_I_protein_coding_tRNA|m.731 \tSPAC1A6.10_tcd1_I_tRNA \n", "\n", "SPAC1D4.01_639405_641280_1_tls1_I_protein_coding_splicing|m.416 \tSPAC1D4.01_tls1_I_splicing \n", "\n", "SPAC1D4.02c_639545_641680_-1_grh1_I_protein_coding_human|m.420 \tSPAC1D4.02c_grh1_I_human \n", "\n", "SPAC1D4.03c_641845_643775_-1_aut12_I_protein_coding_autophagy|m.423 \tSPAC1D4.03c_aut12_I_autophagy \n", "\n", "SPAC1D4.04_644667_646547_1_cct2_I_protein_coding_chaperonin-containing|m.427 \tSPAC1D4.04_cct2_I_chaperonin-containing \n", "\n", "SPAC1D4.05c_644623_648097_-1_SPAC1D4.05c_I_protein_coding_Erd1|m.426 \tSPAC1D4.05c_SPAC1D4.05c_I_Erd1 \n", "\n", "SPAC1D4.06c_648301_649393_-1_csk1_I_protein_coding_cyclin-dependent|m.428 \tSPAC1D4.06c_csk1_I_cyclin-dependent \n", "\n", "SPAC1D4.08_650465_652224_1_pis1_I_protein_coding_CDP-diacylglycerol--inositol|m.430 \tSPAC1D4.08_pis1_I_CDP-diacylglycerol--inositol \n", "\n", "SPAC1D4.09c_652225_653321_-1_rtf2_I_protein_coding_replication|m.431 \tSPAC1D4.09c_rtf2_I_replication \n", "\n", "SPAC1D4.10_653449_656657_1_trz1_I_protein_coding_nuclear|m.432 \tSPAC1D4.10_trz1_I_nuclear \n", "\n", "SPAC1D4.11c_656076_660381_-1_lkh1_I_protein_coding_dual|m.434 \tSPAC1D4.11c_lkh1_I_dual \n", "\n", "SPAC1D4.12_664310_667647_1_rad15_I_protein_coding_transcription|m.436 \tSPAC1D4.12_rad15_I_transcription \n", "\n", "SPAC1D4.13_667815_669742_1_byr1_I_protein_coding_MAP|m.438 \tSPAC1D4.13_byr1_I_MAP \n", "\n", "SPAC1D4.14_670203_675444_1_tho2_I_protein_coding_THO|m.439 \tSPAC1D4.14_tho2_I_THO \n", "\n", "SPAC1F3.01_610842_613338_1_rrp6_I_protein_coding_exosome|m.399 \tSPAC1F3.01_rrp6_I_exosome \n", "\n", "SPAC1F3.02c_613369_617324_-1_mkh1_I_protein_coding_MEK|m.400 \tSPAC1F3.02c_mkh1_I_MEK \n", "\n", "SPAC1F3.03_617816_622703_1_sro7_I_protein_coding_Lgl|m.402 \tSPAC1F3.03_sro7_I_Lgl \n", "\n", "SPAC1F3.04c_621054_622267_-1_tsr3_I_protein_coding_SSU-rRNA|m.404 \tSPAC1F3.04c_tsr3_I_SSU-rRNA \n", "\n", "SPAC1F3.05_623091_625407_1_gga21_I_protein_coding_Golgi|m.406 \tSPAC1F3.05_gga21_I_Golgi \n", "\n", "SPAC1F3.06c_625173_631401_-1_spo15_I_protein_coding_sporulation|m.407 \tSPAC1F3.06c_spo15_I_sporulation \n", "\n", "SPAC1F3.07c_631511_633102_-1_rsc58_I_protein_coding_RSC|m.410 \tSPAC1F3.07c_rsc58_I_RSC \n", "\n", "SPAC1F3.09_633652_636959_1_mug161_I_protein_coding_CwfJ|m.412 \tSPAC1F3.09_mug161_I_CwfJ \n", "\n", "SPAC1F3.10c_634898_639430_-1_oct1_I_protein_coding_mitochondrial|m.413 \tSPAC1F3.10c_oct1_I_mitochondrial \n", "\n", "SPAC1F5.02_291979_293771_-1_pdi1_I_protein_coding_protein|m.180 \tSPAC1F5.02_pdi1_I_protein \n", "\n", "SPAC1F5.03c_289790_291927_1_SPAC1F5.03c_I_protein_coding_FAD-dependent|m.179 \tSPAC1F5.03c_SPAC1F5.03c_I_FAD-dependent \n", "\n", "SPAC1F5.04c_283287_289200_1_cdc12_I_protein_coding_formin|m.176 \tSPAC1F5.04c_cdc12_I_formin \n", "\n", "SPAC1F5.05c_281774_282745_1_mso1_I_protein_coding_endocytic|m.175 \tSPAC1F5.05c_mso1_I_endocytic \n", "\n", "SPAC1F5.06_276657_281347_-1_lsh1_I_protein_coding_ER|m.172 \tSPAC1F5.06_lsh1_I_ER \n", "\n", "SPAC1F5.06_276657_281347_-1_lsh1_I_protein_coding_ER|m.173 \tSPAC1F5.07c_hem14_I_protoporphyrinogen \n", "\n", "SPAC1F5.08c_275089_276661_1_yam8_I_protein_coding_stretch-activated|m.171 \tSPAC1F5.08c_yam8_I_stretch-activated \n", "\n", "SPAC1F5.09c_273152_274921_1_shk2_I_protein_coding_PAK-related|m.169 \tSPAC1F5.09c_shk2_I_PAK-related \n", "\n", "SPAC1F5.10_270893_272610_-1_SPAC1F5.10_I_protein_coding_ATP-dependent|m.167 \tSPAC1F5.10_SPAC1F5.10_I_ATP-dependent \n", "\n", "SPAC1F5.11c_259603_271053_1_tra2_I_protein_coding_NuA4|m.166 \tSPAC1F5.11c_tra2_I_NuA4 \n", "\n", "SPAC1F8.01_82746_84786_1_ght3_I_protein_coding_hexose|m.34 \tSPAC1F8.01_ght3_I_hexose \n", "\n", "SPAC1F8.02c_85566_86324_-1_shu1_I_protein_coding_heme|m.35 \tSPAC1F8.02c_shu1_I_heme \n", "\n", "SPAC1F8.03c_88201_90300_-1_str3_I_protein_coding_siderophore-iron|m.37 \tSPAC1F8.03c_str3_I_siderophore-iron \n", "\n", "SPAC1F8.04c_92387_93931_-1_SPAC1F8.04c_I_protein_coding_hydrolase|m.38 \tSPAC1F8.04c_SPAC1F8.04c_I_hydrolase \n", "\n", "SPAC1F8.05_95961_96966_1_isp3_I_protein_coding_Schizosaccharomyces|m.42 \tSPAC1F8.05_isp3_I_Schizosaccharomyces \n", "\n", "SPAC1F8.06_99871_101431_1_fta5_I_protein_coding_cell|m.45 \tSPAC1F8.06_fta5_I_cell \n", "\n", "SPAC1F8.07c_101715_103594_-1_SPAC1F8.07c_I_protein_coding_pyruvate|m.47 \tSPAC1F8.07c_SPAC1F8.07c_I_pyruvate \n", "\n", "SPAC1F8.08_103941_104953_1_SPAC1F8.08_I_protein_coding_Schizosaccharomyces|m.51 \tSPAC1F8.08_SPAC1F8.08_I_Schizosaccharomyces \n", "\n", "SPAC212.01c_28738_29657_1_SPAC212.01c_I_protein_coding_S.|m.10 \tSPAC212.01c_SPAC212.01c_I_S. \n", "\n", "SPAC212.02_27353_27763_-1_SPAC212.02_I_protein_coding_Schizosaccharomyces|m.9 \tSPAC212.02_SPAC212.02_I_Schizosaccharomyces \n", "\n", "SPAC212.03_23589_24054_-1_SPAC212.03_I_protein_coding_hypothetical|m.8 \tSPAC212.03_SPAC212.03_I_hypothetical \n", "\n", "SPAC212.04c_21381_23050_1_SPAC212.04c_I_protein_coding_S.|m.7 \tSPAC212.04c_SPAC212.04c_I_S. \n", "\n", "SPAC212.06c_18042_18974_1_SPAC212.06c_I_protein_coding_DNA|m.6 \tSPAC212.06c_SPAC212.06c_I_DNA \n", "\n", "SPAC212.08c_11784_12994_1_SPAC212.08c_I_protein_coding_S.|m.4 \tSPAC212.08c_SPAC212.08c_I_S. \n", "\n", "SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ|m.1 \tSPAC212.11_tlh1_I_RecQ \n", "\n", "SPAC212.12_15855_16226_1_SPAC212.12_I_protein_coding_S.|m.5 \tSPAC212.12_SPAC212.12_I_S. \n", "\n", "SPAC222.03c_947876_948800_-1_tim10_I_protein_coding_Tim9-Tim10|m.618 \tSPAC222.03c_tim10_I_Tim9-Tim10 \n", "\n", "SPAC222.04c_950120_950813_-1_ies6_I_protein_coding_Ino80|m.620 \tSPAC222.04c_ies6_I_Ino80 \n", "\n", "SPAC222.05c_950912_953006_-1_mss1_I_protein_coding_mitochondrial|m.621 \tSPAC222.05c_mss1_I_mitochondrial \n", "\n", "SPAC222.06_953095_954325_1_mak16_I_protein_coding_nuclear|m.624 \tSPAC222.06_mak16_I_nuclear \n", "\n", "SPAC222.07c_954279_956707_-1_hri2_I_protein_coding_eIF2|m.626 \tSPAC222.07c_hri2_I_eIF2 \n", "\n", "SPAC222.08c_957367_958774_-1_sno1_I_protein_coding_glutamine|m.627 \tSPAC222.08c_sno1_I_glutamine \n", "\n", "SPAC222.09_959867_962227_1_seb1_I_protein_coding_RNA-binding|m.629 \tSPAC222.09_seb1_I_RNA-binding \n", "\n", "SPAC222.10c_962314_964867_-1_byr4_I_protein_coding_two-component|m.632 \tSPAC222.10c_byr4_I_two-component \n", "\n", "SPAC222.11_966164_967591_1_hem13_I_protein_coding_coproporphyrinogen|m.637 \tSPAC222.11_hem13_I_coproporphyrinogen \n", "\n", "SPAC222.12c_968507_970412_-1_atp2_I_protein_coding_F1-ATPase|m.641 \tSPAC222.12c_atp2_I_F1-ATPase \n", "\n", "SPAC222.13c_970875_973548_-1_SPAC222.13c_I_protein_coding_6-phosphofructo-2-kinase|m.643 \tSPAC222.13c_SPAC222.13c_I_6-phosphofructo-2-kinase \n", "\n", "SPAC222.14c_973843_976782_-1_sey1_I_protein_coding_GTP|m.644 \tSPAC222.14c_sey1_I_GTP \n", "\n", "SPAC222.15_977709_978637_1_meu13_I_protein_coding_Tat|m.645 \tSPAC222.15_meu13_I_Tat \n", "\n", "SPAC222.16c_979482_981161_-1_csn3_I_protein_coding_COP9_signalosome|m.647 \tSPAC222.16c_csn3_I_COP9_signalosome \n", "\n", "SPAC222.17_967583_968302_-1_SPAC222.17_I_protein_coding_conserved|m.640 \tSPAC222.17_SPAC222.17_I_conserved \n", "\n", "SPAC222.18_978722_979643_1_SPAC222.18_I_protein_coding_Srp1|m.646 \tSPAC222.18_SPAC222.18_I_Srp1 \n", "\n", "SPAC222.19_949646_950047_1_tam1_I_protein_coding_Schizosaccharomyces|m.619 \tSPAC222.19_tam1_I_Schizosaccharomyces \n", "\n", "SPAC227.01c_498878_500674_-1_erd1_I_protein_coding_Erd1|m.323 \tSPAC227.01c_erd1_I_Erd1 \n", "\n", "SPAC227.02c_501751_502444_-1_rrp15_I_protein_coding_rRNA|m.325 \tSPAC227.02c_rrp15_I_rRNA \n", "\n", "SPAC227.03c_502577_504324_-1_yea6_I_protein_coding_mitochondrial|m.326 \tSPAC227.03c_yea6_I_mitochondrial \n", "\n", "SPAC227.04_504835_505775_1_atg10_I_protein_coding_Atg12|m.327 \tSPAC227.04_atg10_I_Atg12 \n", "\n", "SPAC227.05_505902_506355_1_gim3_I_protein_coding_prefoldin|m.328 \tSPAC227.05_gim3_I_prefoldin \n", "\n", "SPAC227.06_506520_507605_1_yip5_I_protein_coding_Rab|m.329 \tSPAC227.06_yip5_I_Rab \n", "\n", "SPAC227.07c_507522_509960_-1_pab1_I_protein_coding_protein|m.330 \tSPAC227.07c_pab1_I_protein \n", "\n", "SPAC227.08c_510410_511433_-1_yth1_I_protein_coding_mRNA|m.331 \tSPAC227.08c_yth1_I_mRNA \n", "\n", "SPAC227.09_511350_513382_1_fol3_I_protein_coding_folylpolyglutamate|m.332 \tSPAC227.09_fol3_I_folylpolyglutamate \n", "\n", "SPAC227.11c_513967_517252_-1_yos9_I_protein_coding_sensor|m.338 \tSPAC227.11c_yos9_I_sensor \n", "\n", "SPAC227.10_513820_514921_1_gim4_I_protein_coding_prefoldin|m.336 \tSPAC227.10_gim4_I_prefoldin \n", "\n", "SPAC227.12_515661_517504_1_rna4_I_protein_coding_U4_U6|m.341 \tSPAC227.12_rna4_I_U4_U6 \n", "\n", "SPAC227.13c_517416_519017_-1_isu1_I_protein_coding_mitochondrial|m.342 \tSPAC227.13c_isu1_I_mitochondrial \n", "\n", "SPAC227.14_520174_522766_1_yfh7_I_protein_coding_uridine|m.343 \tSPAC227.14_yfh7_I_uridine \n", "\n", "SPAC227.15_523097_526412_1_reg1_I_protein_coding_protein|m.345 \tSPAC227.15_reg1_I_protein \n", "\n", "SPAC227.16c_527782_528906_-1_psf3_I_protein_coding_GINS|m.349 \tSPAC227.16c_psf3_I_GINS \n", "\n", "SPAC227.17c_529167_530275_-1_SPAC227.17c_I_protein_coding_conserved|m.350 \tSPAC227.17c_SPAC227.17c_I_conserved \n", "\n", "SPAC227.18_530261_531981_1_lys3_I_protein_coding_saccharopine|m.351 \tSPAC227.18_lys3_I_saccharopine \n", "\n", "SPAC227.19c_501117_501485_-1_SPAC227.19c_I_protein_coding_conserved|m.324 \tSPAC227.19c_SPAC227.19c_I_conserved \n", "\n", "SPAC22A12.01c_1156487_1159594_-1_pso2_I_protein_coding_DNA|m.785 \tSPAC22A12.01c_pso2_I_DNA \n", "\n", "SPAC22A12.02c_1159626_1160000_-1_mug103_I_protein_coding_Schizosaccharomyces|m.786 \tSPAC22A12.02c_mug103_I_Schizosaccharomyces \n", "\n", "SPAC22A12.03c_1160118_1161595_-1_csn4_I_protein_coding_COP9_signalosome|m.787 \tSPAC22A12.03c_csn4_I_COP9_signalosome \n", "\n", "SPAC22A12.04c_1162203_1162901_-1_rps2201_I_protein_coding_40S|m.788 \tSPAC22A12.04c_rps2201_I_40S \n", "\n", "SPAC22A12.05_1163057_1163522_1_rpc11_I_protein_coding_DNA-directed|m.789 \tSPAC22A12.05_rpc11_I_DNA-directed \n", "\n", "SPAC22A12.06c_1163745_1165581_-1_SPAC22A12.06c_I_protein_coding_serine|m.791 \tSPAC22A12.06c_SPAC22A12.06c_I_serine \n", "\n", "SPAC22A12.07c_1166562_1169743_-1_ogm1_I_protein_coding_protein|m.794 \tSPAC22A12.07c_ogm1_I_protein \n", "\n", "SPAC22A12.08c_1170196_1172171_-1_SPAC22A12.08c_I_protein_coding_cardiolipin|m.796 \tSPAC22A12.08c_SPAC22A12.08c_I_cardiolipin \n", "\n", "SPAC22A12.09c_1172351_1174497_-1_sap114_I_protein_coding_U2|m.801 \tSPAC22A12.09c_sap114_I_U2 \n", "\n", "SPAC22A12.10_1172209_1176801_1_ept1_I_protein_coding_diacylglycerol|m.797 \tSPAC22A12.10_ept1_I_diacylglycerol \n", "\n", "SPAC22A12.11_1176703_1178897_1_dak1_I_protein_coding_dihydroxyacetone|m.802 \tSPAC22A12.11_dak1_I_dihydroxyacetone \n", "\n", "SPAC22A12.12c_1178856_1180072_-1_rrp40_I_protein_coding_exosome|m.805 \tSPAC22A12.12c_rrp40_I_exosome \n", "\n", "SPAC22A12.13_1180184_1181157_1_mug84_I_protein_coding_pig-P|m.806 \tSPAC22A12.13_mug84_I_pig-P \n", "\n", "SPAC22A12.14c_1180999_1182528_-1_SPAC22A12.14c_I_protein_coding_BSD|m.807 \tSPAC22A12.14c_SPAC22A12.14c_I_BSD \n", "\n", "SPAC22A12.15c_1182693_1185497_-1_bip1_I_protein_coding_ER|m.808 \tSPAC22A12.15c_bip1_I_ER \n", "\n", "SPAC22A12.16_1186205_1187928_1_SPAC22A12.16_I_protein_coding_ATP-citrate|m.815 \tSPAC22A12.16_SPAC22A12.16_I_ATP-citrate \n", "\n", "SPAC22A12.17c_1185837_1189506_-1_SPAC22A12.17c_I_protein_coding_short|m.810 \tSPAC22A12.17c_SPAC22A12.17c_I_short \n", "\n", "SPAC22F3.02_705042_708014_-1_atf31_I_protein_coding_transcription|m.462 \tSPAC22F3.02_atf31_I_transcription \n", "\n", "SPAC22F3.03c_703669_707990_1_rdh54_I_protein_coding_ATP-dependent|m.460 \tSPAC22F3.03c_rdh54_I_ATP-dependent \n", "\n", "SPAC22F3.04_697960_702755_-1_mug62_I_protein_coding_AMP|m.458 \tSPAC22F3.04_mug62_I_AMP \n", "\n", "SPAC22F3.05c_697191_703040_1_alp41_I_protein_coding_GTP-binding|m.457 \tSPAC22F3.05c_alp41_I_GTP-binding \n", "\n", "SPAC22F3.06c_693514_697130_1_lon1_I_protein_coding_Lon|m.454 \tSPAC22F3.06c_lon1_I_Lon \n", "\n", "SPAC22F3.07c_691472_692077_1_atp20_I_protein_coding_F0-ATPase|m.452 \tSPAC22F3.07c_atp20_I_F0-ATPase \n", "\n", "SPAC22F3.08c_689345_691122_1_rok1_I_protein_coding_ATP-dependent|m.450 \tSPAC22F3.08c_rok1_I_ATP-dependent \n", "\n", "SPAC22F3.09c_686543_689179_1_res2_I_protein_coding_MBF|m.448 \tSPAC22F3.09c_res2_I_MBF \n", "\n", "SPAC22F3.10c_683990_686347_1_gcs1_I_protein_coding_glutamate-cysteine|m.447 \tSPAC22F3.10c_gcs1_I_glutamate-cysteine \n", "\n", "SPAC22F3.11c_682835_683660_1_snu23_I_protein_coding_U4_U6|m.446 \tSPAC22F3.11c_snu23_I_U4_U6 \n", "\n", "SPAC22F3.12c_679062_681890_1_rgs1_I_protein_coding_regulator|m.445 \tSPAC22F3.12c_rgs1_I_regulator \n", "\n", "SPAC22F3.13_673984_678307_-1_tsc1_I_protein_coding_hamartin|m.441 \tSPAC22F3.13_tsc1_I_hamartin \n", "\n", "SPAC22F3.15_692567_693061_1_SPAC22F3.15_I_protein_coding_GatB_YqeY|m.453 \tSPAC22F3.15_SPAC22F3.15_I_GatB_YqeY \n", "\n", "SPAC22G7.01c_725865_728242_-1_fra1_I_protein_coding_iron|m.479 \tSPAC22G7.01c_fra1_I_iron \n", "\n", "SPAC22G7.02_728335_731867_1_kap111_I_protein_coding_karyopherin|m.482 \tSPAC22G7.02_kap111_I_karyopherin \n", "\n", "SPAC22G7.03_731933_732759_1_SPAC22G7.03_I_protein_coding_Schizosaccharomyces|m.483 \tSPAC22G7.03_SPAC22G7.03_I_Schizosaccharomyces \n", "\n", "SPAC22G7.04_732826_736603_1_pan2_I_protein_coding_ubiquitin|m.484 \tSPAC22G7.04_pan2_I_ubiquitin \n", "\n", "SPAC22G7.05_736722_738782_1_kri1_I_protein_coding_ribosome|m.485 \tSPAC22G7.05_kri1_I_ribosome \n", "\n", "SPAC22G7.06c_739167_746117_-1_ura1_I_protein_coding_carbamoyl-phosphate|m.486 \tSPAC22G7.06c_ura1_I_carbamoyl-phosphate \n", "\n", "SPAC22G7.07c_746537_748971_-1_ime4_I_protein_coding_mRNA|m.489 \tSPAC22G7.07c_ime4_I_mRNA \n", "\n", "SPAC22G7.08_749523_751846_1_ppk8_I_protein_coding_serine_threonine|m.490 \tSPAC22G7.08_ppk8_I_serine_threonine \n", "\n", "SPAC22G7.09c_751647_753492_-1_nup45_I_protein_coding_nucleoporin|m.491 \tSPAC22G7.09c_nup45_I_nucleoporin \n", "\n", "SPAC22G7.10_753624_755676_1_iss1_I_protein_coding_mRNA|m.492 \tSPAC22G7.10_iss1_I_mRNA \n", "\n", "SPAC22G7.10_753624_755676_1_iss1_I_protein_coding_mRNA|m.493 \tSPAC22G7.11c_cum1_I_conserved \n", "\n", "SPAC22H12.01c_893278_894532_-1_mug35_I_protein_coding_Schizosaccharomyces|m.578 \tSPAC22H12.01c_mug35_I_Schizosaccharomyces \n", "\n", "SPAC22H12.02_893996_896547_1_tfg3_I_protein_coding_transcription|m.579 \tSPAC22H12.02_tfg3_I_transcription \n", "\n", "SPAC22H12.03_896668_897900_1_SPAC22H12.03_I_protein_coding_mitochondrial|m.581 \tSPAC22H12.03_SPAC22H12.03_I_mitochondrial \n", "\n", "SPAC22H12.04c_898045_898994_-1_rps102_I_protein_coding_40S|m.582 \tSPAC22H12.04c_rps102_I_40S \n", "\n", "SPAC22H12.05c_899283_902080_-1_fsc1_I_protein_coding_fasciclin|m.585 \tSPAC22H12.05c_fsc1_I_fasciclin \n", "\n", "SPAC23C4.02_1032085_1034167_1_crn1_I_protein_coding_actin|m.675 \tSPAC23C4.02_crn1_I_actin \n", "\n", "SPAC23C4.03_1034296_1035992_1_hrk1_I_protein_coding_haspin|m.677 \tSPAC23C4.03_hrk1_I_haspin \n", "\n", "SPAC23C4.04c_1036033_1036508_1_SPAC23C4.04c_I_protein_coding_Schizosaccharomyces|m.678 \tSPAC23C4.04c_SPAC23C4.04c_I_Schizosaccharomyces \n", "\n", "SPAC23C4.05c_1036639_1038267_-1_SPAC23C4.05c_I_protein_coding_LEA|m.679 \tSPAC23C4.05c_SPAC23C4.05c_I_LEA \n", "\n", "SPAC23C4.08_1041414_1043083_1_rho3_I_protein_coding_Rho|m.685 \tSPAC23C4.08_rho3_I_Rho \n", "\n", "SPAC23C4.09c_1041980_1044240_-1_SPAC23C4.09c_I_protein_coding_DNA-binding|m.687 \tSPAC23C4.09c_SPAC23C4.09c_I_DNA-binding \n", "\n", "SPAC23C4.10_1044844_1046788_1_sec2_I_protein_coding_guanyl-nucleotide|m.688 \tSPAC23C4.10_sec2_I_guanyl-nucleotide \n", "\n", "SPAC23C4.12_1048957_1051136_1_hhp2_I_protein_coding_serine_threonine|m.689 \tSPAC23C4.12_hhp2_I_serine_threonine \n", "\n", "SPAC23C4.13_1051665_1052724_1_bet1_I_protein_coding_SNARE|m.690 \tSPAC23C4.13_bet1_I_SNARE \n", "\n", "SPAC23C4.14_1052875_1054468_1_alg1_I_protein_coding_mannosyltransferase|m.691 \tSPAC23C4.14_alg1_I_mannosyltransferase \n", "\n", "SPAC23C4.15_1054665_1055906_1_rpb5_I_protein_coding_DNA-directed|m.692 \tSPAC23C4.15_rpb5_I_DNA-directed \n", "\n", "SPAC23C4.16c_1055849_1057578_-1_atg15_I_protein_coding_autophagy|m.693 \tSPAC23C4.16c_atg15_I_autophagy \n", "\n", "SPAC23C4.17_1057701_1061166_1_trm402_I_protein_coding_tRNA|m.694 \tSPAC23C4.17_trm402_I_tRNA \n", "\n", "SPAC23C4.18c_1058646_1063306_-1_rad4_I_protein_coding_BRCT|m.696 \tSPAC23C4.18c_rad4_I_BRCT \n", "\n", "SPAC23E2.01_442201_445721_1_fep1_I_protein_coding_iron-sensing|m.291 \tSPAC23E2.01_fep1_I_iron-sensing \n", "\n", "SPAC23E2.02_446491_450726_1_lsd2_I_protein_coding_histone|m.292 \tSPAC23E2.02_lsd2_I_histone \n", "\n", "SPAC23E2.03c_450860_453603_-1_ste7_I_protein_coding_arrestin|m.293 \tSPAC23E2.03c_ste7_I_arrestin \n", "\n", "SPAC23G3.01_850591_854385_1_rpb2_I_protein_coding_RNA|m.556 \tSPAC23G3.01_rpb2_I_RNA \n", "\n", "SPAC23G3.02c_854453_869704_-1_sib1_I_protein_coding_ferrichrome|m.559 \tSPAC23G3.02c_sib1_I_ferrichrome \n", "\n", "SPAC23G3.03_870740_872773_1_sib2_I_protein_coding_ornithine|m.560 \tSPAC23G3.03_sib2_I_ornithine \n", "\n", "SPAC23G3.04_872883_874248_1_ies4_I_protein_coding_Ino80|m.562 \tSPAC23G3.04_ies4_I_Ino80 \n", "\n", "SPAC23G3.05c_874160_875763_-1_SPAC23G3.05c_I_protein_coding_regulator|m.564 \tSPAC23G3.05c_SPAC23G3.05c_I_regulator \n", "\n", "SPAC23G3.06_876862_878930_1_nop58_I_protein_coding_U3|m.565 \tSPAC23G3.06_nop58_I_U3 \n", "\n", "SPAC23G3.07c_879147_880546_-1_snf30_I_protein_coding_SWI_SNF|m.567 \tSPAC23G3.07c_snf30_I_SWI_SNF \n", "\n", "SPAC23G3.08c_880660_884231_-1_ubp7_I_protein_coding_ubiquitin|m.568 \tSPAC23G3.08c_ubp7_I_ubiquitin \n", "\n", "SPAC23G3.09_884365_885989_1_taf4_I_protein_coding_transcription|m.570 \tSPAC23G3.09_taf4_I_transcription \n", "\n", "SPAC23G3.10c_884513_887531_-1_ssr3_I_protein_coding_SWI_SNF|m.571 \tSPAC23G3.10c_ssr3_I_SWI_SNF \n", "\n", "SPAC23G3.11_885944_889096_1_rpn6_I_protein_coding_19S|m.573 \tSPAC23G3.11_rpn6_I_19S \n", "\n", "SPAC23G3.12c_889058_892211_-1_SPAC23G3.12c_I_protein_coding_serine|m.575 \tSPAC23G3.12c_SPAC23G3.12c_I_serine \n", "\n", "SPAC24B11.05_204386_206081_1_SPAC24B11.05_I_protein_coding_pyrimidine|m.129 \tSPAC24B11.05_SPAC24B11.05_I_pyrimidine \n", "\n", "SPAC24B11.06c_206476_208044_-1_sty1_I_protein_coding_MAP|m.130 \tSPAC24B11.06c_sty1_I_MAP \n", "\n", "SPAC24B11.07c_208839_211275_-1_SPAC24B11.07c_I_protein_coding_oxidoreductase|m.131 \tSPAC24B11.07c_SPAC24B11.07c_I_oxidoreductase \n", "\n", "SPAC24B11.08c_211714_213591_-1_SPAC24B11.08c_I_protein_coding_COPII-coated|m.133 \tSPAC24B11.08c_SPAC24B11.08c_I_COPII-coated \n", "\n", "SPAC24B11.09_214093_216962_1_mpc2_I_protein_coding_mitochondrial|m.136 \tSPAC24B11.09_mpc2_I_mitochondrial \n", "\n", "SPAC24B11.10c_218260_221562_-1_cfh1_I_protein_coding_chitin|m.138 \tSPAC24B11.10c_cfh1_I_chitin \n", "\n", "SPAC24B11.11c_221694_223991_-1_sid2_I_protein_coding_NDR|m.139 \tSPAC24B11.11c_sid2_I_NDR \n", "\n", "SPAC24B11.12c_224080_229307_-1_SPAC24B11.12c_I_protein_coding_P-type|m.142 \tSPAC24B11.12c_SPAC24B11.12c_I_P-type \n", "\n", "SPAC24B11.13_231311_233488_1_hem3_I_protein_coding_hydroxymethylbilane|m.148 \tSPAC24B11.13_hem3_I_hydroxymethylbilane \n", "\n", "SPAC806.02c_233032_235164_-1_SPAC806.02c_I_protein_coding_Par|m.152 \tSPAC806.02c_SPAC806.02c_I_Par \n", "\n", "SPAC24B11.14_230545_231136_1_SPAC24B11.14_I_protein_coding_dubious|m.147 \tSPAC24B11.14_SPAC24B11.14_I_dubious \n", "\n", "SPAC24H6.01c_489871_492181_1_SPAC24H6.01c_I_protein_coding_membrane|m.318 \tSPAC24H6.01c_SPAC24H6.01c_I_membrane \n", "\n", "SPAC24H6.02c_488339_489482_1_tim15_I_protein_coding_TIM23|m.317 \tSPAC24H6.02c_tim15_I_TIM23 \n", "\n", "SPAC24H6.03_485723_488811_-1_cul3_I_protein_coding_cullin|m.316 \tSPAC24H6.03_cul3_I_cullin \n", "\n", "SPAC24H6.04_482607_485408_-1_hxk1_I_protein_coding_hexokinase|m.315 \tSPAC24H6.04_hxk1_I_hexokinase \n", "\n", "SPAC24H6.05_479228_482556_-1_cdc25_I_protein_coding_M|m.311 \tSPAC24H6.05_cdc25_I_M \n", "\n", "SPAC24H6.06_476474_478803_-1_sld3_I_protein_coding_DNA|m.309 \tSPAC24H6.06_sld3_I_DNA \n", "\n", "SPAC24H6.07_475354_476128_-1_rps901_I_protein_coding_40S|m.307 \tSPAC24H6.07_rps901_I_40S \n", "\n", "SPAC24H6.08_473792_475041_-1_SPAC24H6.08_I_protein_coding_Schizosaccharomyces|m.306 \tSPAC24H6.08_SPAC24H6.08_I_Schizosaccharomyces \n", "\n", "SPAC24H6.09_469981_472993_-1_gef1_I_protein_coding_Cdc42|m.304 \tSPAC24H6.09_gef1_I_Cdc42 \n", "\n", "SPAC24H6.10c_468664_469890_1_SPAC24H6.10c_I_protein_coding_phospho-2-dehydro-3-deoxyheptonate|m.303 \tSPAC24H6.10c_SPAC24H6.10c_I_phospho-2-dehydro-3-deoxyheptonate \n", "\n", "SPAC24H6.11c_464120_468581_1_SPAC24H6.11c_I_protein_coding_sulfate|m.301 \tSPAC24H6.11c_SPAC24H6.11c_I_sulfate \n", "\n", "SPAC24H6.12c_461686_463599_1_uba3_I_protein_coding_NEDD8|m.299 \tSPAC24H6.12c_uba3_I_NEDD8 \n", "\n", "SPAC24H6.13_456931_460811_-1_SPAC24H6.13_I_protein_coding_DUF221|m.296 \tSPAC24H6.13_SPAC24H6.13_I_DUF221 \n", "\n", "SPAC2F7.02c_531794_533731_-1_psr1_I_protein_coding_NLI|m.352 \tSPAC2F7.02c_psr1_I_NLI \n", "\n", "SPAC2F7.03c_534120_537869_-1_pom1_I_protein_coding_DYRK|m.353 \tSPAC2F7.03c_pom1_I_DYRK \n", "\n", "SPAC2F7.04_537888_540012_1_pmc2_I_protein_coding_mediator|m.356 \tSPAC2F7.04_pmc2_I_mediator \n", "\n", "SPAC2F7.05c_539919_541640_-1_tif5_I_protein_coding_translation|m.357 \tSPAC2F7.05c_tif5_I_translation \n", "\n", "SPAC2F7.06c_541576_543735_-1_pol4_I_protein_coding_DNA|m.359 \tSPAC2F7.06c_pol4_I_DNA \n", "\n", "SPAC2F7.07c_544127_546240_-1_cph2_I_protein_coding_Clr6|m.361 \tSPAC2F7.07c_cph2_I_Clr6 \n", "\n", "SPAC2F7.08c_546664_548562_-1_snf5_I_protein_coding_SWI_SNF|m.363 \tSPAC2F7.08c_snf5_I_SWI_SNF \n", "\n", "SPAC2F7.09c_548768_550726_-1_gep3_I_protein_coding_mitochondrial|m.364 \tSPAC2F7.09c_gep3_I_mitochondrial \n", "\n", "SPAC2F7.10_550630_553595_1_akr1_I_protein_coding_palmitoyltransferase|m.365 \tSPAC2F7.10_akr1_I_palmitoyltransferase \n", "\n", "SPAC2F7.11_555277_559051_1_nrd1_I_protein_coding_RNA-binding|m.366 \tSPAC2F7.11_nrd1_I_RNA-binding \n", "\n", "SPAC2F7.13c_558909_560549_-1_wrs1_I_protein_coding_cytoplasmic|m.369 \tSPAC2F7.13c_wrs1_I_cytoplasmic \n", "\n", "SPAC2F7.14c_560824_562179_-1_rrp4_I_protein_coding_exosome|m.370 \tSPAC2F7.14c_rrp4_I_exosome \n", "\n", "SPAC2F7.15_563698_565073_1_rsm24_I_protein_coding_mitochondrial|m.371 \tSPAC2F7.15_rsm24_I_mitochondrial \n", "\n", "SPAC2F7.16c_565035_569485_-1_pld1_I_protein_coding_phospholipase|m.372 \tSPAC2F7.16c_pld1_I_phospholipase \n", "\n", "SPAC2G11.02_807894_812194_1_urb2_I_protein_coding_ribosome|m.528 \tSPAC2G11.02_urb2_I_ribosome \n", "\n", "SPAC2G11.03c_811443_814228_-1_vps45_I_protein_coding_vacuolar|m.530 \tSPAC2G11.03c_vps45_I_vacuolar \n", "\n", "SPAC2G11.04_814218_815490_1_SPAC2G11.04_I_protein_coding_RNA-binding|m.533 \tSPAC2G11.04_SPAC2G11.04_I_RNA-binding \n", "\n", "SPAC2G11.05c_815388_817984_-1_rim20_I_protein_coding_BRO1|m.534 \tSPAC2G11.05c_rim20_I_BRO1 \n", "\n", "SPAC2G11.06_817996_819739_1_vps4_I_protein_coding_AAA|m.535 \tSPAC2G11.06_vps4_I_AAA \n", "\n", "SPAC2G11.07c_819768_821920_-1_ptc3_I_protein_coding_protein|m.536 \tSPAC2G11.07c_ptc3_I_protein \n", "\n", "SPAC2G11.08c_822092_823278_-1_smn1_I_protein_coding_SMN|m.538 \tSPAC2G11.08c_smn1_I_SMN \n", "\n", "SPAC2G11.09_823493_826399_1_SPAC2G11.09_I_protein_coding_calcium|m.539 \tSPAC2G11.09_SPAC2G11.09_I_calcium \n", "\n", "SPAC2G11.10c_826313_828123_-1_uba42_I_protein_coding_thiosulfate|m.540 \tSPAC2G11.10c_uba42_I_thiosulfate \n", "\n", "SPAC2G11.11c_828321_831629_-1_prh1_I_protein_coding_ATP-dependent|m.541 \tSPAC2G11.11c_prh1_I_ATP-dependent \n", "\n", "SPAC2G11.12_831918_836094_1_rqh1_I_protein_coding_RecQ|m.542 \tSPAC2G11.12_rqh1_I_RecQ \n", "\n", "SPAC2G11.13_836206_838256_1_atg22_I_protein_coding_vacuolar|m.544 \tSPAC2G11.13_atg22_I_vacuolar \n", "\n", "SPAC2G11.14_838228_841562_1_taf111_I_protein_coding_transcription|m.545 \tSPAC2G11.14_taf111_I_transcription \n", "\n", "SPAC2G11.15c_841471_842624_-1_tgs1_I_protein_coding_rRNA|m.547 \tSPAC2G11.15c_tgs1_I_rRNA \n", "\n", "SPAC30D11.01c_1119880_1123773_1_gto2_I_protein_coding_alpha-glucosidase|m.752 \tSPAC30D11.01c_gto2_I_alpha-glucosidase \n", "\n", "SPAC30D11.02c_1118926_1119763_1_SPAC30D11.02c_I_protein_coding_Schizosaccharomyces|m.751 \tSPAC30D11.02c_SPAC30D11.02c_I_Schizosaccharomyces \n", "\n", "SPAC30D11.03_1115899_1118412_-1_ddx27_I_protein_coding_ATP-dependent|m.749 \tSPAC30D11.03_ddx27_I_ATP-dependent \n", "\n", "SPAC30D11.04c_1112170_1115868_1_nup124_I_protein_coding_nucleoporin|m.743 \tSPAC30D11.04c_nup124_I_nucleoporin \n", "\n", "SPAC30D11.06c_1108485_1110686_1_hfl1_I_protein_coding_Lazarus1|m.740 \tSPAC30D11.06c_hfl1_I_Lazarus1 \n", "\n", "SPAC30D11.05_1109349_1111221_-1_aps3_I_protein_coding_AP-3|m.742 \tSPAC30D11.05_aps3_I_AP-3 \n", "\n", "SPAC30D11.07_1106430_1107885_-1_nth1_I_protein_coding_DNA|m.739 \tSPAC30D11.07_nth1_I_DNA \n", "\n", "SPAC30D11.08c_1104753_1106608_1_phf2_I_protein_coding_Lsd1_2|m.738 \tSPAC30D11.08c_phf2_I_Lsd1_2 \n", "\n", "SPAC30D11.09_1101685_1103890_-1_cwf19_I_protein_coding_complexed|m.737 \tSPAC30D11.09_cwf19_I_complexed \n", "\n", "SPAC30D11.10_1099489_1101583_-1_rad52_I_protein_coding_DNA|m.736 \tSPAC30D11.10_rad52_I_DNA \n", "\n", "SPAC30D11.11_1097449_1099554_-1_SPAC30D11.11_I_protein_coding_Haemolysin-III|m.735 \tSPAC30D11.11_SPAC30D11.11_I_Haemolysin-III \n", "\n", "SPAC30D11.13_1094262_1095547_-1_hus5_I_protein_coding_SUMO|m.734 \tSPAC30D11.13_hus5_I_SUMO \n", "\n", "SPAC30D11.14c_1092387_1094379_1_SPAC30D11.14c_I_protein_coding_RNA-binding|m.732 \tSPAC30D11.14c_SPAC30D11.14c_I_RNA-binding \n", "\n", "SPAC31A2.02_388233_389229_1_trm112_I_protein_coding_protein|m.256 \tSPAC31A2.02_trm112_I_protein \n", "\n", "SPAC31A2.03_389391_390520_1_mrp11_I_protein_coding_mitochondrial|m.257 \tSPAC31A2.03_mrp11_I_mitochondrial \n", "\n", "SPAC31A2.04c_390407_391260_-1_pre1_I_protein_coding_20S|m.258 \tSPAC31A2.04c_pre1_I_20S \n", "\n", "SPAC31A2.07c_399462_402266_-1_dbp10_I_protein_coding_ATP-dependent|m.267 \tSPAC31A2.07c_dbp10_I_ATP-dependent \n", "\n", "SPAC31A2.06_397426_402487_1_atp25_I_protein_coding_mitochondrial|m.263 \tSPAC31A2.06_atp25_I_mitochondrial \n", "\n", "SPAC31A2.08_402841_403862_1_mrp20_I_protein_coding_mitochondrial|m.270 \tSPAC31A2.08_mrp20_I_mitochondrial \n", "\n", "SPAC31A2.09c_402719_405389_-1_apm4_I_protein_coding_AP-2|m.268 \tSPAC31A2.09c_apm4_I_AP-2 \n", "\n", "SPAC31A2.10_405582_407710_1_SPAC31A2.10_I_protein_coding_Ran|m.271 \tSPAC31A2.10_SPAC31A2.10_I_Ran \n", "\n", "SPAC31A2.11c_407714_409872_-1_cuf1_I_protein_coding_nutritional|m.272 \tSPAC31A2.11c_cuf1_I_nutritional \n", "\n", "SPAC31A2.12_411651_414448_1_rod1_I_protein_coding_arrestin_PY|m.274 \tSPAC31A2.12_rod1_I_arrestin_PY \n", "\n", "SPAC31A2.13c_414245_414930_-1_sft1_I_protein_coding_SNARE|m.276 \tSPAC31A2.13c_sft1_I_SNARE \n", "\n", "SPAC31A2.14_414942_418504_1_bun107_I_protein_coding_WD|m.277 \tSPAC31A2.14_bun107_I_WD \n", "\n", "SPAC31A2.15c_417823_419996_-1_dcc1_I_protein_coding_Ctf18|m.279 \tSPAC31A2.15c_dcc1_I_Ctf18 \n", "\n", "SPAC31A2.16_419958_423991_1_gef2_I_protein_coding_RhoGEF|m.282 \tSPAC31A2.16_gef2_I_RhoGEF \n", "\n", "SPAC3H8.02_588543_590751_1_csr102_I_protein_coding_sec14|m.387 \tSPAC3H8.02_csr102_I_sec14 \n", "\n", "SPAC3H8.03_590691_592152_1_img2_I_protein_coding_mitochondrial|m.388 \tSPAC3H8.03_img2_I_mitochondrial \n", "\n", "SPAC3H8.04_592226_593906_1_SPAC3H8.04_I_protein_coding_possible|m.389 \tSPAC3H8.04_SPAC3H8.04_I_possible \n", "\n", "SPAC3H8.05c_593901_597586_-1_mms1_I_protein_coding_E3|m.390 \tSPAC3H8.05c_mms1_I_E3 \n", "\n", "SPAC3H8.06_598473_600805_1_aur1_I_protein_coding_inositol|m.391 \tSPAC3H8.06_aur1_I_inositol \n", "\n", "SPAC3H8.07c_600826_601749_-1_pac10_I_protein_coding_prefoldin|m.394 \tSPAC3H8.07c_pac10_I_prefoldin \n", "\n", "SPAC3H8.08c_601848_603993_-1_SPAC3H8.08c_I_protein_coding_transcription|m.395 \tSPAC3H8.08c_SPAC3H8.08c_I_transcription \n", "\n", "SPAC3H8.09c_604312_607742_-1_nab3_I_protein_coding_poly(A)|m.397 \tSPAC3H8.09c_nab3_I_poly(A) \n", "\n", "SPAC3H8.10_608893_610703_1_spo20_I_protein_coding_sec14|m.398 \tSPAC3H8.10_spo20_I_sec14 \n", "\n", "SPAC4C5.01_1192210_1193756_1_SPAC4C5.01_I_protein_coding_pseudouridine-5'-phosphatase|m.818 \tSPAC4C5.01_SPAC4C5.01_I_pseudouridine-5'-phosphatase \n", "\n", "SPAC4C5.02c_1192702_1195167_-1_ryh1_I_protein_coding_GTPase|m.821 \tSPAC4C5.02c_ryh1_I_GTPase \n", "\n", "SPAC4C5.03_1196723_1198284_1_SPAC4C5.03_I_protein_coding_CTNS|m.824 \tSPAC4C5.03_SPAC4C5.03_I_CTNS \n", "\n", "SPAC4C5.04_1198224_1199733_1_rad31_I_protein_coding_SUMO|m.825 \tSPAC4C5.04_rad31_I_SUMO \n", "\n", "SPAC4G8.03c_757915_762714_-1_SPAC4G8.03c_I_protein_coding_RNA-binding|m.497 \tSPAC4G8.03c_SPAC4G8.03c_I_RNA-binding \n", "\n", "SPAC4G8.04_767446_770246_1_SPAC4G8.04_I_protein_coding_GTPase|m.499 \tSPAC4G8.04_SPAC4G8.04_I_GTPase \n", "\n", "SPAC4G8.05_770502_772666_1_ppk14_I_protein_coding_serine_threonine|m.500 \tSPAC4G8.05_ppk14_I_serine_threonine \n", "\n", "SPAC4G8.06c_772650_774027_-1_trm12_I_protein_coding_tRNA|m.502 \tSPAC4G8.06c_trm12_I_tRNA \n", "\n", "SPAC4G8.07c_774000_776062_-1_trm2_I_protein_coding_tRNA|m.503 \tSPAC4G8.07c_trm2_I_tRNA \n", "\n", "SPAC4G8.08_777177_778498_1_SPAC4G8.08_I_protein_coding_mitochondrial|m.505 \tSPAC4G8.08_SPAC4G8.08_I_mitochondrial \n", "\n", "SPAC4G8.09_778431_781324_1_SPAC4G8.09_I_protein_coding_mitochondrial|m.506 \tSPAC4G8.09_SPAC4G8.09_I_mitochondrial \n", "\n", "SPAC4G8.10_781348_783419_1_gos1_I_protein_coding_SNARE|m.511 \tSPAC4G8.10_gos1_I_SNARE \n", "\n", "SPAC4G8.11c_781347_783634_-1_atp10_I_protein_coding_mitochondrial|m.509 \tSPAC4G8.11c_atp10_I_mitochondrial \n", "\n", "SPAC4G8.13c_786778_790219_-1_prz1_I_protein_coding_calcineurin|m.517 \tSPAC4G8.13c_prz1_I_calcineurin \n", "\n", "SPAC521.02_843197_844165_1_SPAC521.02_I_protein_coding_WLM|m.548 \tSPAC521.02_SPAC521.02_I_WLM \n", "\n", "SPAC521.03_844948_846142_1_SPAC521.03_I_protein_coding_short|m.549 \tSPAC521.03_SPAC521.03_I_short \n", "\n", "SPAC521.04c_846022_849480_-1_sst1_I_protein_coding_calcium|m.552 \tSPAC521.04c_sst1_I_calcium \n", "\n", "SPAC521.05_849421_850259_1_rps802_I_protein_coding_40S|m.553 \tSPAC521.05_rps802_I_40S \n", "\n", "SPAC56F8.02_1124058_1129104_1_SPAC56F8.02_I_protein_coding_AMP|m.753 \tSPAC56F8.02_SPAC56F8.02_I_AMP \n", "\n", "SPAC56F8.03_1129519_1133089_1_SPAC56F8.03_I_protein_coding_translation|m.756 \tSPAC56F8.03_SPAC56F8.03_I_translation \n", "\n", "SPAC56F8.04c_1133226_1134356_-1_ppt1_I_protein_coding_para-hydroxybenzoate--polyprenyltransferase|m.759 \tSPAC56F8.04c_ppt1_I_para-hydroxybenzoate--polyprenyltransferase \n", "\n", "SPAC56F8.05c_1134418_1136038_-1_mug64_I_protein_coding_BAR|m.760 \tSPAC56F8.05c_mug64_I_BAR \n", "\n", "SPAC56F8.06c_1136196_1138046_-1_alg10_I_protein_coding_dolichyl-phosphate-glucose-glycolipid|m.761 \tSPAC56F8.06c_alg10_I_dolichyl-phosphate-glucose-glycolipid \n", "\n", "SPAC56F8.07_1138566_1139117_1_SPAC56F8.07_I_protein_coding_conserved|m.763 \tSPAC56F8.07_SPAC56F8.07_I_conserved \n", "\n", "SPAC56F8.08_1139130_1140325_1_mud1_I_protein_coding_UBA|m.764 \tSPAC56F8.08_mud1_I_UBA \n", "\n", "SPAC56F8.09_1140580_1142002_1_rrp8_I_protein_coding_rRNA|m.765 \tSPAC56F8.09_rrp8_I_rRNA \n", "\n", "SPAC56F8.10_1143063_1145256_1_met9_I_protein_coding_methylenetetrahydrofolate|m.766 \tSPAC56F8.10_met9_I_methylenetetrahydrofolate \n", "\n", "SPAC56F8.11_1145305_1146800_1_spc3_I_protein_coding_signal|m.769 \tSPAC56F8.11_spc3_I_signal \n", "\n", "SPAC56F8.12_1146833_1148085_1_SPAC56F8.12_I_protein_coding_conserved|m.770 \tSPAC56F8.12_SPAC56F8.12_I_conserved \n", "\n", "SPAC56F8.13_1149078_1150659_1_SPAC56F8.13_I_protein_coding_dubious|m.778 \tSPAC56F8.13_SPAC56F8.13_I_dubious \n", "\n", "SPAC56F8.14c_1148131_1152178_-1_mug115_I_protein_coding_Schizosaccharomyces|m.773 \tSPAC56F8.14c_mug115_I_Schizosaccharomyces \n", "\n", "SPAC56F8.15_1151431_1153638_1_SPAC56F8.15_I_protein_coding_Schizosaccharomyces|m.781 \tSPAC56F8.15_SPAC56F8.15_I_Schizosaccharomyces \n", "\n", "SPAC56F8.16_1153572_1156804_1_esc1_I_protein_coding_transcription|m.783 \tSPAC56F8.16_esc1_I_transcription \n", "\n", "SPAC5H10.01_146974_148055_1_SPAC5H10.01_I_protein_coding_DUF1445|m.90 \tSPAC5H10.01_SPAC5H10.01_I_DUF1445 \n", "\n", "SPAC5H10.02c_148038_150331_-1_hsp3102_I_protein_coding_glyoxylase|m.91 \tSPAC5H10.02c_hsp3102_I_glyoxylase \n", "\n", "SPAC5H10.03_149446_152909_1_SPAC5H10.03_I_protein_coding_phosphoglycerate|m.94 \tSPAC5H10.03_SPAC5H10.03_I_phosphoglycerate \n", "\n", "SPAC5H10.04_152851_155515_1_SPAC5H10.04_I_protein_coding_NADPH|m.95 \tSPAC5H10.04_SPAC5H10.04_I_NADPH \n", "\n", "SPAC5H10.04_152851_155515_1_SPAC5H10.04_I_protein_coding_NADPH|m.96 \tSPAC5H10.05c_SPAC5H10.05c_I_FAD \n", "\n", "SPAC5H10.06c_156430_158307_-1_adh4_I_protein_coding_alcohol|m.99 \tSPAC5H10.06c_adh4_I_alcohol \n", "\n", "SPAC5H10.08c_159880_160945_-1_pan6_I_protein_coding_pantoate-beta-alanine|m.103 \tSPAC5H10.08c_pan6_I_pantoate-beta-alanine \n", "\n", "SPAC5H10.09c_160977_161822_-1_ecm31_I_protein_coding_3-methyl-2-oxobutanoatehydroxymethyltransferase|m.104 \tSPAC5H10.09c_ecm31_I_3-methyl-2-oxobutanoatehydroxymethyltransferase \n", "\n", "SPAC5H10.10_162756_164635_1_SPAC5H10.10_I_protein_coding_NADPH|m.106 \tSPAC5H10.10_SPAC5H10.10_I_NADPH \n", "\n", "SPAC5H10.12c_165814_167826_-1_SPAC5H10.12c_I_protein_coding_acetylglucosaminyltransferase|m.108 \tSPAC5H10.12c_SPAC5H10.12c_I_acetylglucosaminyltransferase \n", "\n", "SPAC630.03_350406_352296_1_arp3_I_protein_coding_Arp2_3|m.225 \tSPAC630.03_arp3_I_Arp2_3 \n", "\n", "SPAC630.04c_350239_353340_-1_SPAC630.04c_I_protein_coding_Schizosaccharomyces|m.223 \tSPAC630.04c_SPAC630.04c_I_Schizosaccharomyces \n", "\n", "SPAC630.05_353783_356580_1_gyp7_I_protein_coding_GTPase|m.229 \tSPAC630.05_gyp7_I_GTPase \n", "\n", "SPAC630.06c_353705_357205_-1_SPAC630.06c_I_protein_coding_conserved|m.227 \tSPAC630.06c_SPAC630.06c_I_conserved \n", "\n", "SPAC630.07c_357325_359228_-1_SPAC630.07c_I_protein_coding_Schizosaccharomyces|m.231 \tSPAC630.07c_SPAC630.07c_I_Schizosaccharomyces \n", "\n", "SPAC630.08c_359638_361266_-1_erg25_I_protein_coding_C-4|m.233 \tSPAC630.08c_erg25_I_C-4 \n", "\n", "SPAC630.09c_362248_363714_-1_mug58_I_protein_coding_GLYK|m.238 \tSPAC630.09c_mug58_I_GLYK \n", "\n", "SPAC630.10_365204_366442_1_bmt2_I_protein_coding_rRNA|m.239 \tSPAC630.10_bmt2_I_rRNA \n", "\n", "SPAC630.11_366634_367890_1_vps55_I_protein_coding_vacuolar|m.240 \tSPAC630.11_vps55_I_vacuolar \n", "\n", "SPAC630.12_368040_369950_1_SPAC630.12_I_protein_coding_ER|m.242 \tSPAC630.12_SPAC630.12_I_ER \n", "\n", "SPAC630.13c_369791_374217_-1_tsc2_I_protein_coding_tuberin|m.243 \tSPAC630.13c_tsc2_I_tuberin \n", "\n", "SPAC630.14c_374316_377908_-1_tup12_I_protein_coding_transcriptional|m.244 \tSPAC630.14c_tup12_I_transcriptional \n", "\n", "SPAC806.03c_235533_236104_-1_rps2601_I_protein_coding_40S|m.154 \tSPAC806.03c_rps2601_I_40S \n", "\n", "SPAC806.04c_241008_243122_-1_SPAC806.04c_I_protein_coding_protein-glutamate|m.156 \tSPAC806.04c_SPAC806.04c_I_protein-glutamate \n", "\n", "SPAC806.05_244214_247574_1_SPAC806.05_I_protein_coding_mitochondrial|m.159 \tSPAC806.06c_SPAC806.06c_I_nicotinamide \n", "\n", "SPAC806.05_244214_247574_1_SPAC806.05_I_protein_coding_mitochondrial|m.160 \tSPAC806.05_SPAC806.05_I_mitochondrial \n", "\n", "SPAC806.07_247821_248560_1_ndk1_I_protein_coding_nucleoside|m.161 \tSPAC806.07_ndk1_I_nucleoside \n", "\n", "SPAC806.08c_248579_250983_-1_mod21_I_protein_coding_gamma|m.162 \tSPAC806.08c_mod21_I_gamma \n", "\n", "SPAC821.03c_981473_983481_-1_slf1_I_protein_coding_cell|m.648 \tSPAC821.03c_slf1_I_cell \n", "\n", "SPAC821.04c_983567_987084_-1_cid13_I_protein_coding_poly(A)|m.649 \tSPAC821.04c_cid13_I_poly(A) \n", "\n", "SPAC821.05_988076_989866_1_tif38_I_protein_coding_translation|m.651 \tSPAC821.05_tif38_I_translation \n", "\n", "SPAC821.06_990192_991889_1_spn2_I_protein_coding_mitotic|m.652 \tSPAC821.06_spn2_I_mitotic \n", "\n", "SPAC821.07c_991632_994230_-1_moc3_I_protein_coding_transcription|m.654 \tSPAC821.07c_moc3_I_transcription \n", "\n", "SPAC821.08c_994941_997625_-1_slp1_I_protein_coding_substrate-specific|m.655 \tSPAC821.08c_slp1_I_substrate-specific \n", "\n", "SPAC821.10c_1002838_1003600_-1_sod1_I_protein_coding_superoxide|m.660 \tSPAC821.10c_sod1_I_superoxide \n", "\n", "SPAC821.11_1006259_1008003_1_pro1_I_protein_coding_gamma-glutamyl|m.662 \tSPAC821.11_pro1_I_gamma-glutamyl \n", "\n", "SPAC821.12_1008215_1010318_1_orb6_I_protein_coding_serine_threonine|m.664 \tSPAC821.12_orb6_I_serine_threonine \n", "\n", "SPAC821.13c_1010343_1015415_-1_dnf1_I_protein_coding_Trans-golgi|m.665 \tSPAC821.13c_dnf1_I_Trans-golgi \n", "\n", "SPAC977.01_29764_31069_1_SPAC977.01_I_protein_coding_S.|m.11 \tSPAC977.01_SPAC977.01_I_S. \n", "\n", "SPAC977.02_32034_33012_1_SPAC977.02_I_protein_coding_S.|m.13 \tSPAC977.02_SPAC977.02_I_S. \n", "\n", "SPAC977.03_33835_34272_1_SPAC977.03_I_protein_coding_methyltransferase|m.14 \tSPAC977.03_SPAC977.03_I_methyltransferase \n", "\n", "SPAC977.04_34298_34978_1_SPAC977.04_I_protein_coding_truncated|m.15 \tSPAC750.02c_SPAC750.02c_I_transmembrane \n", "\n", "SPAC977.05c_35768_36382_-1_SPAC977.05c_I_protein_coding_conserved|m.16 \tSPAC977.05c_SPAC977.05c_I_conserved \n", "\n", "SPAC977.06_39416_40072_1_SPAC977.06_I_protein_coding_S.|m.17 \tSPAC977.06_SPAC977.06_I_S. \n", "\n", "SPAC977.07c_42057_43307_-1_pfl6_I_protein_coding_cell|m.18 \tSPAC977.07c_pfl6_I_cell \n", "\n", "SPAC977.08_44644_45468_1_SPAC977.08_I_protein_coding_short|m.19 \tSPAC977.08_SPAC977.08_I_short \n", "\n", "SPAC977.09c_45875_48399_-1_SPAC977.09c_I_protein_coding_phospholipase|m.20 \tSPAC977.09c_SPAC977.09c_I_phospholipase \n", "\n", "SPAC977.10_50946_53858_1_sod2_I_protein_coding_plasma|m.22 \tSPAC977.10_sod2_I_plasma \n", "\n", "SPAC977.11_55059_56308_1_SPAC977.11_I_protein_coding_CRCB|m.23 \tSPAC977.11_SPAC977.11_I_CRCB \n", "\n", "SPAC977.12_56373_57736_1_SPAC977.12_I_protein_coding_L-asparaginase|m.24 \tSPAC977.12_SPAC977.12_I_L-asparaginase \n", "\n", "SPAC977.14c_59614_60907_-1_SPAC977.14c_I_protein_coding_aldo_keto|m.25 \tSPAC977.14c_SPAC977.14c_I_aldo_keto \n", "\n", "SPAC977.15_62961_63862_1_SPAC977.15_I_protein_coding_dienelactone|m.26 \tSPAC977.15_SPAC977.15_I_dienelactone \n", "\n", "SPAC977.16c_64559_66980_-1_dak2_I_protein_coding_dihydroxyacetone|m.27 \tSPAC977.16c_dak2_I_dihydroxyacetone \n", "\n", "SPAC977.17_66219_69821_1_SPAC977.17_I_protein_coding_MIP|m.30 \tSPAC977.17_SPAC977.17_I_MIP \n", "\n", "SPAC977.18_31140_32345_-1_SPAC977.18_I_protein_coding_conserved|m.12 \tSPAC977.18_SPAC977.18_I_conserved \n", "\n", "SPAPB21F2.02_492335_497927_1_SPAPB21F2.02_I_protein_coding_Dopey|m.319 \tSPAPB21F2.02_SPAPB21F2.02_I_Dopey \n", "\n", "SPAPB21F2.03_498111_499027_1_slx9_I_protein_coding_ribosome|m.321 \tSPAPB21F2.03_slx9_I_ribosome \n", "\n", "SPAPJ695.01c_77480_78066_-1_SPAPJ695.01c_I_protein_coding_S.|m.33 \tSPAPJ695.01c_SPAPJ695.01c_I_S. \n", "\n", "SPAPJ696.01c_719090_723684_-1_vps17_I_protein_coding_retromer|m.473 \tSPAPJ696.01c_vps17_I_retromer \n", "\n", "SPAPJ696.02_724145_725946_1_lsb4_I_protein_coding_actin|m.477 \tSPAPJ696.02_lsb4_I_actin \n", "\n" ] } ], "source": [ "for key, row in rbh_df.iterrows():\n", " print row.q_name, '\\t', row.s_name, '\\n'" ] }, { "cell_type": "code", "execution_count": 206, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "'SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ|m.1'" ] }, "execution_count": 206, "metadata": {}, "output_type": "execute_result" } ], "source": [ "db_x_pep_df.s_name[0]" ] }, { "cell_type": "code", "execution_count": 183, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "478" ] }, "execution_count": 183, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(bh_df.query('RBH == True'))" ] }, { "cell_type": "code", "execution_count": 116, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "StandardScaler(copy=True, with_mean=True, with_std=True)" ] }, "execution_count": 116, "metadata": {}, "output_type": "execute_result" } ], "source": [ "scaler = preprocessing.StandardScaler()\n", "scaler.fit(bh_df.query('RBH == True')[['E', 'q_len']])" ] }, { "cell_type": "code", "execution_count": 117, "metadata": { "collapsed": false }, "outputs": [], "source": [ "rbh_df[['E', 'q_len']] = scaler.transform(rbh_df[['E', 'q_len']])" ] }, { "cell_type": "code", "execution_count": 118, "metadata": { "collapsed": false }, "outputs": [], "source": [ "bh_df[['E', 'q_len']] = scaler.transform(bh_df[['E', 'q_len']])" ] }, { "cell_type": "code", "execution_count": 190, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "500" ] }, "execution_count": 190, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(bh_df)" ] }, { "cell_type": "code", "execution_count": 188, "metadata": { "collapsed": false }, "outputs": [], "source": [ "CRBL.best_hits(bh_df)" ] }, { "cell_type": "code", "execution_count": 189, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "81" ] }, "execution_count": 189, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(bh_df.query('RBH == True'))" ] }, { "cell_type": "code", "execution_count": 120, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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/lRRf4e4HJP2MZVnHK11Ys0gsTbAIetscrmRlfcHiSvJ0YpaADAAAoLVt0rso6WOSjBXu\ne1DSJ03TfME0zV+raGVNYjkg19EKcrlS68dcauUeZAAAgFazakC2LOsLknJ3uPtzkj4u6UlJ7zFN\n80MVrK0pJLLFCRb1GpAjgQ4ZMjS7SEAGAACQNr9J7/csy1qQJNM0n5F0v6Rn7vRg0zSflvSpTV6z\nobylxWLR4WJW4HG51REIa25xXrZtyzBWeqEAAACgqYyYpnn7bZ+2LOtpaRMB2TTNiKQ3TdM8JCmp\n4iryZ+/2OUsXffq25xmW1LSDeBPZWy0W6XpMyJK6AhFFUwtKZhfrdqUbAACggnZZljV6pzvXM+DW\nliTTNH/KNM1fsiwrKunXJB2T9LykU5ZlfW0zlTaj0iEhQW/9Bs/utuIYtznaLAAAANa2gryUsN+1\n9P7nym7/nIp9yLiDRCYpn9srr7t+R053lQJyKqptkS0OVwMAAOAsjkirskQ2Wderx9KtgMxGPQAA\nAAJyVWXzOWXy2brv6434wzIMQ3OL806XAgAA4DgCchXd2qBXn4eElLhdbnX6OzSXWpBt206XAwAA\n4CgCchXdGvFW3yvIUrHNIpvPLod6AACAVkVArqJ6PySkXBeTLAAAACQRkKvqLYeE1Dk26gEAABQR\nkKtoOSA3wApyd4AVZAAAAImAXFWN1GLREQjLZbiYZAEAAFoeAbmKkpmk3IZLfrfP6VJW5TJc6gww\nyQIAAICAXEXxbFJBX7sMw3C6lDXpaosoV8gpnkk4XQoAAIBjCMhVUigUtJhNNcSIt5KuABv1AAAA\nCMhVklzuP67/CRYl3Yx6AwAAICBXS+nAjfZGWkEuBeQUG/UAAEDrIiBXSSJTXEEONcAEi5KwPyS3\n4WYFGQAAtDQCcpUsryA3UIuFy3Cps604yaJgF5wuBwAAwBEE5CopHRISaqAWC6m4US9fyCuWZpIF\nAABoTQTkKikdEtLeQC0WEhv1AAAACMhVksgkZchQuzfgdCnrcmujHgEZAAC0JgJylSQySbV5A3IZ\njfVP3NXWKUkcOQ0AAFpWY6W3BmHbthLZRQUbrL1CksK+oDwuJlkAAIDWRUCuglQurYJdUNDbOBMs\nSgzDUFcgwiQLAADQsgjIVVAa8daIK8hSsQ+5YBcUX/o6AAAAWgkBuQpKh4QEG2zEW0kk0CFJWsjE\nHa4EAACg9gjIVZAsjXhrsAkWJRF/WJIUyzALGQAAtB4CchWkc2lJUsDjd7iSjYkElgJyloAMAABa\nDwG5ClKNHpCXV5BpsQAAAK2HgFwFqVxGUuMGZI/bo6C3TQu0WAAAgBZEQK6C0gqyv0EDslTcqJfM\nLSqTzzpdCgAAQE0RkKsgnUvLkCGf2+t0KRvWsdRmMZWccbgSAACA2iIgV0Eqn5Hf45NhGE6XsmGd\nSxv1JhLTDlcCAABQWwTkKkjn0g3bf1zSUQrISQIyAABoLQTkCrNtW+lcpqH7jyWp088KMgAAaE0E\n5ApL5zOyZTf8CnLYH5IhaZIVZAAA0GIIyBV265AQn8OVbI7b5VbQ265JNukBAIAWQ0CusNIMZL+7\nsVeQJSnsDSqaji0fnQ0AANAKCMgV1ujHTJcL+0KSpPHYlMOVAAAA1A4BucJSTdJiIUkdvqAkaSw+\n4XAlAAAAtUNArrDlFosmWkEeYwUZAAC0EAJyhaXzTdRi4V1aQY6xggwAAFoHAbnCUk3Ugxz0tslt\nuDUem3S6FAAAgJohIFdYKSD7m6AH2WW41NferbE4LRYAAKB1EJArLL3UgxxogjFvkjTQ3qt4JqFY\nOu50KQAAADVBQK6wVC4tr9srl6s5/mn7gz2SpDHaLAAAQItojhRXR9K5tALuxm+vKOlv75VEQAYA\nAK2DgFxBtm0rlcs0xQa9koHgUkCOE5ABAEBrICBXUK6QV97ON8UM5JIBVpABAECLISBXUDMdM13S\nGeiQz+1l1BsAAGgZBOQKSuWb55jpEpfh0mCoX2PxSdm27XQ5AAAAVUdArqBmOma63GC4T6lcWvOp\nBadLAQAAqDoCcgU1Y4uFJG0ND0iiDxkAALQGAnIFNdMpeuUGQ/2SpLHYhMOVAAAAVB8BuYKWV5Cb\n5BS9kq3hpYDMkdMAAKAFeJwuoJmUVpAD3uYKyINhVpABANLIzahsWxre0iGXy3C6HKBqCMgVVNqk\n12wryBF/WG2eAKPeAKBFZXMFPX/ius6NzkmSQm1eHdnTq0O7uhXwEyXQfPiurqD0cg9ycwVkwzA0\nGO7T9eiYCnZBLoPOHABoFbMLKX3tpVHNLaTV19Wmge52nRud0/dOjemVM+O6d2+v3nlkiwyDFWU0\nDwJyBaVyabkNlzwut9OlVNxgqF8jc9c0txhVT3uX0+UAAGrAujKr575/Q7l8QUf29urdR7bI7Xbp\n0Xu26OzIrN68OKXj56fUE2mTuZPfDWgeLAVWUCqfkd/jb8q/ogdCxSOnJ9ioBwAtYWI2qWdfvSaX\nS/rAO3fqsaNDcruLscHvdevo/j599L175XG79J03bmgxnXO4YqByCMgVlM6lm24GcslgqE+SNE5A\nBoCmZ9u2vndyTJL0Q+/cpT1DnSs+riPo0yOHB5XK5PXiGzdrWSJQVQTkCikUCsrks003A7mEgAwA\nrePaRFw3puLaMRDWtv7QXR97795e9Xe1ybo6p6vjnLiK5kBArpBUvjlP0SsZWArIE/FphysBAFST\nbdt66VRx9fjRI1tWfbzLZeiJB7fLMKTnvn9D2Vy+2iUCVUdArpB0acRbkwbkrraIvC6PxuOMegOA\nZnbx+rym5he1b3un+jrb1vQ5vZ1tun9/n2LJjF45zcx8ND4CcoUsHzPdZDOQS1yGSwOhPk3Ep2Xb\nttPlAACqIF+w9fLpcbkM6ZHDg+v63IcODaoj6NMbF6Y0H0tXqUKgNgjIFbJ8zHST9iBLxUkWyeyi\n4pmE06UAAKrg7MiMovGMDu/uUSS0vgUfj9ulRw4PypZ0dnSmOgUCNcIc5ApJNWGLRaFQUDQaXf64\ny9shSbo4PqLdnTve9vhwOCyXi7+5AKARZXMFvXp2Qh63Sw8eHNjQc+weisjvdevs6JwePrxFbo6j\nRoMiIFdIqglP0VtMLOqbsy+ou7dbkjS/WNyd/O0rL+nq3PW3PDYZT+qDR55SJBKpeZ0AgM27eH1e\nyVROD5j9Cga8G3oOj9ul/Tu7dPLitK6ML2j3Vn4noDGx3FchqSZtsWgLtisYDikYDqkv0iNJyhjZ\n5dtKb+2hdocrBQBsxoWrc5KkQ7u6N/U8h4aLn392ZHbTNQFOISBXSLrJx7xJUoe/OAszmo47XAkA\noJKSqayuT8Y10N2+7t7j2/V2tqm/q01XxhYUX8xWqEKgtgjIFVLqQW6mFovbhXxBGTK0QEAGgKZy\n8fq8bEn7tq98Yt56HRzuli3p3CiryGhMBOQKSefSMmTI726uFotybpdbIV+7FtIxp0sBAFTQhavz\nMiTtrVBA3rejSx63obOjs4wGRUMiIFdIKpeWz+OTYTT3jt0Of1iL2ZSyeV42A4BmEEtmNT6b1FB/\naMOb827n97q1d1unFhIZ3ZhiNCgaDwG5QtK5jAJNvHpc0hEo9iHTZgEAzWFkrBhgK9VeUXKwtFmP\nmchoQATkCrBtW6lcuqk36JV0+MOSCMgA0Cwuj8XlchnaM1TZgLylN6jOkF+XrkeVyuQq+txAtRGQ\nKyBbyMqWLX+TjXhbSWmSBX3IAND4rk3ENR/PaudgWH6fu6LPbRiGDu7qVr5g6/KN6OqfANQRAnIF\npPOlU/QCDldSfRFWkAGgaXz31KQkaf+Orqo8/+6h4kEho2MLVXl+oFoIyBVwKyA3/wpyuLSCnCIg\nA0Ajs21bL52elMdtaHhLR1Wu0RnyqzPs17WJuHL5QlWuAVQDAbkC0i0wA7nE6/aozRugxQIAGpx1\nZU5T8yntHAjK465eHBge7FAuX9DEbKpq1wAqjYBcAbdWkJs/IEvFNot4Jql8Ie90KQCADXrp1Jgk\naXgwWNXrlFanr00tVvU6QCURkCugFJBbYZOeVNyoZ8tWPMNsSwBoVMetKXnchrb0VHf/zGBvUD6v\nS9enkhwagoZBQK6A5RVkd2usIJcmWUTZqAcADWkultLlm1GZOyJVba+QJLfL0I6BsOKLOd2YSlb1\nWkClEJAroNVaLG7NQqYPGQAa0YnzU5KkI3u6a3K9UpvF8QscGoLGQECugNYLyEyyAIBGdtwqjnc7\nsrs2AXnHYDEgnyAgo0GsKSCbpvmIaZrHVrj9w6ZpvmKa5ndN0/zFypfXGFquBznACjIANKpCwdbx\n81PqDPu1Y6C6G/RK2vwe9Xf6df5aVLFkpibXBDZj1YBsmua/kfQZSf7bbvdK+l1J75f0Xkn/3DTN\n/moUWe/S+Yy8Lo/crsqeQlSv/G6ffG4vh4UAQAO6Mr6g+Vha9+/vk2EYNbvutr522bb0+rnJml0T\n2Ki1rCBflPQxSbf/FB2UdNGyrKhlWVlJ35H0WIXrawjpXKYlZiCXGIahDn9YsXScHckA0GC+vxRQ\nH6jxmtb2/nZJ0qtnxmt6XWAjVg3IlmV9QVJuhbs6JJUfrh6TFKlQXQ0lnc+0xCl65Tr8IeXtghJZ\ndiQDQCM5fr4YkI/ur21A7gx51RPx6/Vzk8pzqh7qnGcTnxuVFC77OCxp7m6fYJrm05I+tYlr1p1M\nPqu8nW+pFWTprRv1Qr7a9LABADYnlc7p9OVZ7R6KqDPsVzRau9PtDMPQ/ft69OxrN3V2dFb37Omt\n2bWBFYyYpnn7bZ+2LOtpaXMB+ZykfaZpdklKqNhe8dt3+4Sliz5dfptpmsOSRjZRh6NKK6itMsGi\n5NZGvbi2asDhagAAa3Hq8oxy+ULN2ytKji4F5NfOThCQ4bRdlmWN3unO9QRkW5JM0/wpSSHLsj5j\nmuavSvq6iq0an7Usa2wzlTaiZK54dKbf3XotFhKTLACgkZTGu91v9jly/QM7I3K7DJ28NO3I9YG1\nWlNAXkrY71p6/3Nlt39Z0perUlmDSGSLAbnlVpD9t1aQAQCN4fj5SQV8bh0crs3849sFfB7t39El\n68qsEotZBdu8jtQBrIaDQjYpuRSQW2UGcknQ2ya3y61oihVkAGgEU3OLujYR1z17euX1ODeW9N69\nvSrY0ukRDg1B/SIgb1KpB7nVNukZhqGIP6xoOsaoNwBoAKXpFU71H5cc2VvsPT55kTYL1C8C8iaV\nepADLdaDLBXbLHKFnBaztdsFDQDYmDcuTEmSju53pv+45MBwt7wel968QEBG/SIgb1JiucWitVaQ\nJSmyNMkiykY9AKhrtm3r9OUZdYb92tYfcrQWv9etAzu7NTLGsdOoXwTkTWrVHmRJiixt1KMPGQDq\n28RsUjPRlA7v7qnp8dJ3cmRvr2xbOsU0C9QpAvImJVq4xeLWCvKCw5UAAO7m1KXihrjDu3ocrqTo\n3qU+ZNosUK8IyJtUarHwteIKcoAVZABoBKcvFwPyPXvqIyDv39Elv8+tN1lBRp0iIG9SMrsor8sr\nl9F6/5RtnoC8Lg89yABQ506PzCjY5tWOwQ6nS5EkeT0uHRzu1tXxmOZibPRG/Wm9VFdhydxiy52i\nV2IYhjoCYS2k4ox6A4A6NRNd1Nh0Qod2dcvtcr7/uKTUZnHqIvOQUX8IyJuUyC7K727dk4Ai/rDy\ndl7JHCsAAFCPzlyelVQ//ccly33ItFmgDhGQNyGTyyhbyMrXoivI0q0+5FiGI6cBoB6dulwMoIfr\npP+4ZO+2TrX5PTp5ccrpUoC3ISBvQjyzdIpeKwfkpVFvC9mEw5UAAFZyZmRWfp9be4Y6nS7lLdxu\nlw7v7tGNqYRmootOlwO8BQF5E+KZYij0tXKLBSvIAFC3YsmMRscWdGBnl7ye+vuVv9xmwbHTqDP1\n99PSQEoBmRVkKZZhBRkA6s2Zy/U1//h2R5YC8kkCMuoMAXkTaLEoHrHtc3sVo8UCAOrOqVJArrP+\n45JdWyMKBjzLc5qBekFA3oRbLRatG5ANw1DEH1Y8k1DBLjhdDgCgzJmRGXnchvbv6HK6lBW5XYYO\nDHfr5nRCcwtMQ0L9ICBvwq0Wi9btQZakSKBDBdmaWZxzuhQAwJLFdE4Xr0e1d1unAj6P0+Xc0eHd\nxdXtMyMwLOZWAAAgAElEQVSzDlcC3EJA3oRYmhVk6dZGvYkEL5EBQL04NzqrQsFeDqD16tBSf/Tp\nEX6HoH4QkDeBHuSi0ka9ySSbLACgXpT6eu/Z0+twJXe3b3unPG6XzhCQUUcIyJvAFIuijgABGQDq\nzemRGRmGdGC42+lS7srndWv/jk6N3Igqmco6XQ4giYC8KcxBLiqtINNiAQD1IZcv6PzVee0c7FCo\nrf5/Rx3e3aOCLZ0bZS8L6gMBeRPimaQCbr9cRmv/M/o9PvndPk2wggwAdeHyjagy2bwO1vnqcUmp\nD5k2C9SL1k52mxRPJxT0tjldRl0Ie4OaWZxTrpB3uhQAaHnnRosTIQ7uaoyAfGC4W4bBRj3UDwLy\nJsQzCbV7250uoy50+EIq2AVNJlhFBgCnnS0F5AZZQQ61eTW8pUPnr8wpm2OhBc4jIG9QJp9VOp9R\n0MMKsiSFfUFJ0nhs0uFKAKC12bats6Oz6gz7NdDdOIs4h3b1KJMr6NL1qNOlAATkjUosjXhrp8VC\nUrHFQpLGCMgA4Kip+UXNRFM6ONwtwzCcLmfNDpfmIXPsNOoAAXmDShMs6EEuCvtCkqSxOAEZAJx0\nrsHaK0oO7S7WSx8y6gEBeYNKp+i102Ih6VaLBSvIAOCssyONGZB7Im0a7GnX2ZHiCYCAkwjIG8QK\n8lt5XR5F/GF6kAHAYWevzMrrcWnPtojTpazboV09ii9mdW0i5nQpaHEE5A2KL/cgN84GiGobaO/V\ndHJOmTwnIQGAExbTOY3cXNDebZ3yetxOl7NupXnItFnAaQTkDWIF+e36gz2yZWsyzqg3AHDChWtz\nKhTshmuvKDlc6kNmox4cRkDeoFJApgf5lv72Xkls1AMAp5T6jw80aEAe6gspEvLpzNLXATiFgLxB\npRYLVpBvGQgWA/LNhQmHKwGA1lQ6IOTAcJfDlWyMYRg6tKtH0/OLmpxNOl0OWhgBeYPiaVosbrcl\n2C9Jur4w5nAlANB6CgVb567MaUtvUF3hgNPlbBh9yKgHBOQNosXi7frbe+R1eXQtetPpUgCg5Vyb\njCmxmG3Y/uOSQ7uK9dNmAScRkDconkmozROQ29V4u4Srxe1ya6hjUNcXxlQoFJwuBwBayrnRxu4/\nLtkzFFHA52ajHhxFQN6geCapkI8Rb7fbHtmqTD6riQSTLACglkr9x4caPCC73S4d2NmtaxMxLSQy\nTpeDFkVA3qB4JqHQ0ulxuGVHZEiSaLMAgBo7Nzqr9oBH2wfCTpeyaYd2F/uQz9KHDIcQkDcgl88p\nlUsr5Ccg3257ZKsk6SoBGQBqJhpP68ZUQgd2dsvlMpwuZ9NKfcin6UOGQwjIG1DaoMcK8tvtWA7I\nNxyuBABaR7P0H5eYO7vkdhk6Qx8yHEJA3oDSDGR6kN+up71Lbd4ALRYAUEPN0n9cEvB5tHdbpy5e\nn1cqnXO6HLQgAvIGsIJ8Z4ZhaEfHVo3FJpXNZ50uBwBawtnRWbkMad+OTqdLqZiDu7qVL9g6f23O\n6VLQggjIG0BAvrvtka0q2AXdjHGiHgBUWzZX0IVr8xreElF7wOt0ORVzeGmj3unL9CGj9gjIG1Bq\nsQizSW9FOzqLkyyuztNmAQDVdvnGvLK5gg7uao72ipLSgSf0IcMJBOQNiKVLK8j0IK+kNMni2gIB\nGQCq7exosQWhWTbolURCfm0fCOnclVnl8xw+hdoiIG8ALRZ3t71jiyRGvQFALZwdLa6wNvoR0ys5\ntKtHqUxel29GnS4FLYaAvAEE5LvrCIQVCXQwyQIAqsy2bZ0dmVV3h1/9XW1Ol1Nx9CHDKQTkDWDM\n2+p2RLZqKjGjxWzK6VIAoGlNzi1qLpbWweEeGUbjHxByu8O7igH5DCfqocYIyBvACvLqlvuQWUUG\ngKo522QHhNyur6tNvZGAzozMyLZtp8tBCyEgb0A8nVDA45fH7XG6lLq1g4AMAFV3dqTUf9zlcCXV\nYRiGDu/uVTSe0fXJuNPloIUQkDcgnkmweryKHZHiqDcCMgBUz7nROfk8Lu0eap4DQm53z55im8Wp\nS9MOV4JWQkDegHgmSf/xKrZ1DEpikgUAVEsyldXoWFT7dnTJ62neX+e3AjJ9yKid5v2JqpJcIa/F\nXIoV5FUEvAH1B3tYQQaAKjl/dU4FWzqwsznbK0qG+kLqDPt18tI0fcioGQLyOiXYoLdmOyJDiqZj\niqYWnC4FAJpO6YCQZpx/XM4wDB3Z06u5WFo3pxNOl4MWQUBep1gpIHPM9KqYZAEA1XOuySdYlKMP\nGbVGQF6neJoZyGtVCsj0IQNAZRUKts5dmdVQX1CRkN/pcqrunqUDQ05epA8ZtUFAXidmIK/drVFv\nYw5XAgDN5cr4gpKpXEusHkvS9oGwIiGfTl2mDxm1QUBeJwLy2m0ND8htuGixAIAKO325uJJaWllt\ndoZh6J7dvZqJpjQ+k3S6HLQAAvI6ccz02nncHm0ND+ha9CZ/8QNABZUC8qEWCcgSfcioLQLyOpVW\nkMNs0luT7Z1DWsylNJ2cdboUAGgKtm3r9OUZdXf4taWndX4X3bOnV5J0koCMGiAgr1M8TYvFepT6\nkEfmrjlcCQA0h7GZhOZiaR3a1SPDMJwup2Z2DIQVbvfp1GU26qH6CMjrRA/y+uzv2S1JOj9z2eFK\nAKA5nGmx/uMSl8vQPXt6NDW3qIlZ+pBRXQTkdSr1IAfpQV6Tvd075TJcsqYJyABQCadasP+45Na4\nN9osUF0E5HWKZxLyu33yub1Ol9IQAt6AdnYO6fLsFWXzWafLAYCGd+byrIJtXu0c7HC6lJo7srfY\nh3zqMgEZ1UVAXqd4JsEpeutk9u5RtpCjDxkANmkmuqixmYQO7eqWy9U6/cclOwc7FGrz6tQl+pBR\nXQTkdYqlE/Qfr5PZW+xDps0CADbnzOXiRKDDu1qvvUIq9iEf3t2jidmkJulDRhURkNchk8toMZdS\nZyDsdCkNxezZI0myZi45XAkANLZSa8HhPa0ZkCXp3qU2izcuTDlcCZoZAXkd5tMxSVLE33p9X5vR\n096l7rZOWdOXOTAEADbhzMisfF639gx1Ol2KY47u75MknThPQEb1EJDXIZpakCR1sIK8LoZhyOzd\no2hqQZMJNlYAwEbEkhmNji3owM4ueT2t++t7+0BY3R0BnbgwpUKBRRdUR+v+hG1ANFVcQabFYv3o\nQwaAzTk7stR/3ILj3coZhqH7zT4tJDK6fDPqdDloUgTkdSitINNisX6lA0OsafqQAWAjSvOPWz0g\nS9LR/f2SaLNA9RCQ1yFa6kEOEJDXa7hru3xur86zggwAG3Lm8ozcLkPmzi6nS3Hc0X2lPuRJhytB\nsyIgr8P80goyLRbr53G5tbd7WFejN5XMLjpdDgA0lFQ6p4vX57V3e6cCPo/T5TiuM+zXrq0dOjMy\nq3Q273Q5aEIE5HUo9SCzgrwx+3t3y5atizOjTpcCAA3l3JVZ5Qt2y84/Xsn9+/uVzRV0+jKHhqDy\nCMjrUOpBDvtDDlfSmMze4jzkc/QhA8C6vHGhOAHo3n29DldSP0rj3o5btFmg8gjI6xBNxRT2BeVx\nuZ0upSHt79klSfQhA8A6nbgwJY/bYAW5zKHdPfJ6XGzUQ1UQkNchmo7RXrEJYX9IQ+FBXZgZUaFQ\ncLocAGgIsWRGl67P68BwtwJ++o9L/F63Du/q0ejYguZiKafLQZMhIK9RrpBXPJNQhA16m7K/d7cW\ncyldjd50uhQAaAhvXpyWbd+a3IBb7jeL/yZvsIqMCuNP0TVaYIPeXRUKBUWjqw9s3x7cIkk6N31R\nw13bql0WADS8Uvi7j4D8NsV5yGd0/PyUHn9wu9PloIkQkNdoecSbnxXklSwmFvXN2RfU3dt918eV\nZkmfGT+vD+x7vAaVAUBje+PClNr8Hu3b3ul0KXVneEuHIiGfTpyflG3bMgzD6ZLQJAjIaxRNFwNy\nBy0Wd9QWbFcwfPcJH+2hoHxXvbo0d6VGVQFA45qcTermdEKPHB6U201X5O1cLkP37evT88dv6OpE\nTDsHeZUXlXHXgGyapkvSf5F0r6S0pF+0LOtS2f2/IukXJJWafz5uWdb5KtXqqNIM5E5aLDbFMAz1\ntXXrRmJCk/Fp9YcYWQQAd/LGBdorVvOA2a/nj9/Q62cnCMiomNX+HP2oJJ9lWe+S9GuSfue2+x+Q\n9DOWZT2x9NaU4Vi61WJBD/LmbQsNSpJeufGGw5UAQH07sRSQSzN/8XbvODgglyG9fHrc6VLQRFYL\nyO+W9DVJsizrZUnvuO3+ByV90jTNF0zT/LUq1Fc3ljfp0YO8aUOhARky9CoBGQDuqFCw9caFKXV3\n+LWtnwOq7iQS8uvAcLfOjc4qGk87XQ6axGoBuUPSQtnH+aW2i5LPSfq4pCclvcc0zQ9VuL66MZ+m\nxaJS2jwB7e7coXPTF5f/8AAAvNWV8QVF4xndt6+PzWereOTwFhVs6dUzrCKjMlYLyAuSypdMXZZl\nlZ/w8HuWZc1alpWV9Iyk+ytdYL0oHTPNJr3KuH/gsGzb1ms3TzpdCgDUpdLx0rRXrO7Re4qtey+d\nIiCjMlabYvGipA9L+jvTNB+V9GbpDtM0I5LeNE3zkKSkiqvIn73bk5mm+bSkT22mYKdEUzG1eQPy\nub1Ol9IU7u8/pL+3vqJXb5zQk7vf5XQ5AFB32KC3dlv7Qto+ENLx81NKZXIK+BjShVWNmKZ5+22f\ntizraWn1gPxFSe83TfPFpY9/zjTNn5IUsizrM0t9x8dUnHDxrGVZX7vbky1d9Ony20zTHJY0suqX\n4bBoakGdftorKqU/2Kvtka16c/ysUtmUAt6A0yUBQN3I5go6dWla2wdC6om0OV1OQ3j40KA+f+yi\n3rwwrYcPDzpdDurfLsuyRu90510DsmVZtqR/edvN58vu/5yKfchNrVAoaCET15Zwv9OlNJWHhu7T\nF858VSfGz+jR7Q84XQ4A1I3zV+eUyuR1315Wj9fq0Xu26PPHLuqlU2MEZGwaU8fXYCETl23bjHir\nsIeH7pMkplkAwG1ePzchSbqP/uM127+jS51hv149M6F8wXa6HDQ4AvIaRJdnILNBr5J2de1QT3uX\nvn/zpHKFvNPlAEDdePXMhLwel47Sf7xmLpehhw8Naj6e1vkrc06XgwZHQF4DTtGrDsMw9NDQfUpk\nF3VmsmnPmAGAdRmfSWh0bEH37etTwM9ms/V4ZGmaxcunxxyuBI2OgLwGpYDcwSEhFVdqs3jlxgmH\nKwGA+vDK0izfR+ijXbf79vXJ73Mz7g2bRkBeg2i62GLBCnLlHezbp6CvXa/deFMFu7D6JwBAk3tl\n6cjkhw4NOFxJ4/F73XrA7NeNqbiuT3IQFTaOgLwG86VjpulBrji3y60Htx7R7OK8Ls9edbocAHBU\nfDGrU5dmtG97J+PdNqi08s4qMjaDgLwGtzbpsYJcDQ8PHZVEmwUAfP9ccQID7RUb9/DhQXncLn37\n+9edLgUNjIC8BqWA3EkPclXcN3hIPrdX37v6ugoF2iwAtK6Xl9ormOO7ceF2nx46NKDRsQWN3Iw6\nXQ4aFAF5DaKpmPxuH6e9VYnf49N7djykicS0jo+fdrocAHBELl/Q62cn1N/VpuEtvGK5GU88uE2S\n9K3XrjlcCRoVAXkNoumYOug/rqoP7HtCkvTV88ccrgQAnHH68owSqZwePjwowzCcLqehvePggEJt\nXj1//DqHhmBDCMirsG1b0XSM9ooqG+7apkN9+/TmxFldjzK/EkDrKU2voP9487wet37g6JBmF9J6\n48KU0+WgARGQV5HIJJUv5NmgVwMf3P+kJOmrF1hFBtBabNvWy6fH1R7w6PDuXqfLaQpPPLhdknTs\nddossH4E5FXMp5lgUSsPbj2ivvZuPT/6suKZhNPlAEDNXB2PaWI2qQcPDMjr4VdzJRwY7tKWnqC+\nd3JMi+mc0+WgwfBTuIooM5Brxu1y6wf3vVfpfEbHLn/P6XIAoGZeWjoamekVlWMYhh5/cJvSmby+\nd5LWPawPAXkVyyPeWEGuiSd3vVs+t1dfu/gcI98AtATbtvX88RvyuF16x4F+p8tpKo8vTbOgzQLr\nRUBexfxSQO5gk15NhPxBPTb8qKYSM3p97KTT5QBA1V2+EdXV8ZgePjygULvP6XKaytbekA7s7NKb\nF6Y0E110uhw0EALyKhbSxRaLTlosauaH9j0uSfrK+W85WwgA1MC3llY3S5vKUFlPvGO7CrY4WQ/r\nQkBexfxyDzItFpVSKBQUjUbv+NahoA727NXpyfM6fd2i1QJA08rnC3r++zcUbvfpwQMDTpfTlH7g\n6JC8Hpe+9tIVFZiJjDXyOF1AvSv1ILNJr3IWE4v65uwL6u7tvuNj+gPdOivps9//G30q/L8rEonU\nrkAAqJHj56c0H0/rQ+/exfSKKgm3+/T4A9v0jVeu6tUz43rkni1Ol4QGwE/jKqKpmDwuj4LedqdL\naSptwXYFw6E7vu0f3KPe9i5dXxzXyDybKwA0p2OvldortjlcSXP7yGN7JEn/4/nLDleCRkFAXkU0\ntaCIP8yxnzVmGIbeuf1BSdJ/O/cl2TYviwFoLslUVi+dGtNQX1D7d3Q5XU5TG97SoaP7+nTy0rQu\n34g6XQ4aAAH5Lmzb1nw6RnuFQ7aE+7UjtEWX5q/qu9dec7ocAKioF9+4qUyuoCce3M4iTA38yHtL\nq8iXHK4EjYCAfBeLuZSy+SwB2UFH+w7JY7j1l298UZlcxulyAKBijr1enKrwONMrauIBs1/b+kN6\n/vh1zS6knC4HdY6AfBfLp+j5mWDhlLAvqKeG36OZ5Jy+fP6bTpcDABUxOZvUyUvTOry7RwPd7HGp\nBZfL0Ece26Nc3tYzL444XQ7qHAH5Ljhmuj58cM8TivjD+uLZr2t2cd7pcgBg055bmsn75DtYPa6l\nJx7cpnC7V1/97qjS2bzT5aCOEZDvIpoujXhjBdlJbZ6AfvLIR5TOpfU3b/6D0+UAwKbkC7a+8coV\n+TwuvfverU6X01ICPo8+8M5hxZKZ5QkiwEoIyHdRmoHMKXrOe3LXu7QzMqRvj76kizOjTpcDABv2\nvZM3NT6T1JMP7VCwzet0OS3nQ+/eJY/b0Befu6hcnoOosDIC8l1wil79cLlc+rkH/mfZsvX7L/+p\nUrm00yUBwLrZtq0vHLsow5A+ujRVAbXVE2nT+x/eqZvTCf3jy1ecLgd1ioB8F8un6PlZQa4Hh/r3\n60P736ex2KT+/MTnnS4HANbt9OUZXbg2r0cOD2qoL+R0OS3rp37QVJvfrb/++jklU1mny0EdIiDf\nBZv06s9P3fsj2hEZ0rOXXtBrN95wuhwAWJcvPlecwfujj+91uJLW1hUO6GNP7FM0ntHnj110uhzU\nIQLyXUwmpuVzexX281e+UwqFgqLR6PLbYjypn7vnJ+RxefRfXv4LXZ28/pb7CwX6yQDUp2sTMb1y\nZlwHdnbp0K4ep8tpeR99bI+6O/z679++pJnootPloM54nC6gXtm2rbH4lAZD/XIZ/B3hlMXEor45\n+4K6e7vfcvt9PaZenzqt33nlM3pi6BEZhqFkPKkPHnlKkUjEoWoB4M7++7dZPa4nAb9H//QDB/Wf\n//aE/vKr5/SJf3K/0yWhjpD87mAuFVU6l9ZguM/pUlpeW7BdwXDoLW8P7LhXQx2DGktMajR1U8Fw\nSO0hhu0DqE9zCyl967Vr2tIb1CP3bHG6HCx58qEdGt7SoW++dlUjN6NOl4M6QkC+g/HYpCRpa3jA\n4UqwEsMw9Pjwo/J7/Hr52glNJWadLgkA7ujLL44oly/oo+/dI7fLcLocLHG7DP3sDx+SbUt/+qXT\nsm3b6ZJQJwjIdzC2FJAHQ/0OV4I7Cfra9fjwo8rbeX394reVzKWcLgkA3iYaT+uZF0fUEfRxcl4d\nesDs1/37+3T8/JS+xeEhWEIP8h2MxUsryATkerazc0iPbDuql6+f0LdvvKL37X6P0yU1tUKhoFgs\nVrPrhcNhuVz8HY/G9hdfPavEYla/9CP3KODj1269MQxD/+onjupf/V/H9MdfPKnDu3s02BN0uiw4\njJ/UO1heQSYg1717Bw5qbjGq8zMj+q8n/17/+rF/IcPgJcxqiMVi+ofnzqi9vfq/PJLJhD7y+CE2\nXaKhXbg2p398+Yp2Dob1oXfvcroc3EF/d7v+xceO6D997rj+0+e+r//wy++hFabFEZDvYDw2qTZP\ngENCGoBhGPqBnQ9rLhnVq+Nv6vNnvqIfP/whp8tqWu3tQQVDnC6Jt+MVhrcqFGz98RdOyralj3/s\nXrnd9VsrpCce3K5XTk/oxTdv6gvHLugn3rff6ZLgIALyCgp2QePxKW2PbGUlskG4XW49tvUhPXfj\nZf3tqS9rqGNQ79z+oNNlAS2FVxje6luvXZV1dU6PHR3SkT29TpeDVRiGoV/+8ft0dnRGf/31c3rA\n7NeebZ1OlwWHEJBXMJOcU7aQo72iwfhcXv3s/h/TH5z+C/3+S38mV9bQgZ49d3x8va8+AY2IVxiK\n4otZ/dkzZ+T3ufVzHz7sdDlYo46gT5/4yQf0qc98T7/z16/rdz/xXgX8RKVWxP/qKyj1H29hgkVD\nWUws6syspXdveUDP3XhFv/fan+h929+p3rbutz2WQ0UAVNNff/2covGM/pcPHlRvZ5vT5WAdHjjQ\nrx9+zy59+Tsj+j//8jX9xs8+THtMCyIgr2A5ILOC3HDagu3a3t8rt9+rZy99R8duvKwPm0+pp73L\n6dKAZfTqNreTF6f1zIsj2tob1Effe+dXsVC/fv7D9+j6ZFyvnpnQH33hTf2vP34fLZcthoC8gtKI\nNwJy49rVtV2P73pUx0a+p6+cP6YPH3hKnQFe9kV9oFe3eU3OJvVbf/6qDEn/20/eL6/H7XRJ2ACv\nx6Vf/2cP6df/8EV9/aUr6uts00++33S6LNQQAXkF47RYNIV9PbuUzef0nauv6pnz39JHzPcr7Ge2\nJeoDvbrNJ5XJ6f/401e0kMjol3/sXh3e3eN0SdiE9oBXn/qlR/Wv//Pz+suvnVNPpE1PPbzD6bJQ\nI7zmtoKx2KTCvqBChKmGd6h/nx4eOqpEJqkvW89qIR13uiQATci2bf3+fzuhyzej+sFHd+qH3sXM\n42bQ3RHQp3/pnQq1efUHf3dCL7550+mSUCME5NvkC3lNJqaZYNFEjm45pHdsPaJYJqEvWc8qmlpw\nuiQATeaLz13U8ydu6OBwtz7+o/c6XQ4qaPtAWP/25x+Rz+vSf/zzV/WV7444XRJqgBaL20wlZpS3\nC/QfN5kHth6Ry3DrlRsn9CXrm3py6FGnSwLQJL7x8hX912fOqLsjoF//Zw/J62HtyWmV3gi7rcej\nT/7MUf32597UH33+TY1PRfWx9w4vb9xjI2zzISDf5ib9x03r6JZD8rjc+u611/WNay/qwaF72bgE\nYMMKBVt/+bWz+rtvXlC43at/+/MPq6sj4HRZUPU2wj71wIC+8dq4vvj8FZ2+PKtHD/UolUqyEbYJ\nEZBvM84Ei6Z2z4Apl8ul71x5Vb/98h/rVwu/qJ2Rbat+HqsD1ZfNFbSQyGgxnVMqk1N0Ia5YalSG\ny6tsrqBsLq9c3pZhSB63a+nNkMfjkrf0scclr8elgM8tv8+jgM+tgM8jv9ct/9L7Ab9bAZ9bHrdr\nU2Ob8gVb2VxemWxBmWxeqUxOqXRei5mc0pl88etI5976cSavVDqnWGJR1yfjKtiTyuYLyuUKyuVt\n2bJl28V+VklyGYZcLmP5v36vSz6ve/nN73XL53Ut/det9oBHwYBX7W1e+Tyb+/pwd5lsXv/33xzX\nCyduaEtvUE//4qPa2hfa9PPWegRgNBpd/n5rNtXYCBsMST/2vg59+TsjOn89pmTG1rsPv33WPhof\nAfk2t2YgDzhcCarlUN8+JaJxHZ8/q996+f/R40MPa6D9zsfAcqhIZeXzBU1HU5qYTWp6flHReFrR\neFqJVO7tDz4zU7U6XC5jKUC75XK55DIkGYZcRvHI2dJ/DaO4UpjJFZTNFpTJ5ZXJFsN6JXjcxVDv\ndhnF67q0HGwLheK1s4WCCgVbcwt5rfWqHrdLwTaPAl6Xzl1LaLA3rO6OgLo6AurpCKg7ElB3R0Bt\nnBK2bjPRRf3HP39NZ0dndXC4W7/xcw8rEvJX5LlrOQJQkqanJhQMRRQK1+RyTSEY8OpH37tH33jl\nqkbHFvQP0UXt3taldx3ld0Qz4f8Zb1MKyIOhPocrQTXtbN8qr8er12ZO6dj1l/XUnvdoZ+eQ02U1\npXy+oJvTCV0dj+nmdFzT8ykVbluxCrf7tK0/pI6gT+0Br9r8bhmFrN55ZIu6uzrk9bjk9biXeztz\nuUJx5XV59bW4ApvNFVdz00sruulMvrhqW3o/nVc6W1zJTS/dnsrkVSjYsm1bhYKtgm2rsLSKa9tS\nwbblMgz5vC6F2r3yeQLyLa3kej1LK7oetwJ+t9r8Hvl9brX5PAr4PWrzF1ey25ZXrov/zaaT+t6b\nNxWJRNa1ymvb5V/jra81s/SWTOWUSGWVWMwqkcopmcoqGs9oYi4laXLF52zze9TdEVDPUmDuLgvP\n3R0Bhdq9CrV5FQx45fe5W3pVejGd0xeOXdQXv31R6Uxejx0d0if+yf3yeSs767iWIwATidqtVhcK\nBUWj0Zpcq9or4z6vWx9817DeuDCt7568qd/6izf0o1ej+ugP7JTLVd2fEV7RrA0C8m3G4pPqDHSo\nzUsfWbPb1j6onq5ufePSC/rHi8/r8V2Pal8Po5kqYTGd06UbUY3ejOrGVEK5fEFScdW2t7NNA91t\n6u9uV19nuzpDvhWPcU3EF3RkT3dTrtxHo3l5N9ACYRjGcnvFWl/Mjy1E9Y5DW5S1vZpbSGl2IaWZ\nhZRmo8X3S283plYfgeh2GQq2eYtvAY+Cbf9/e3ceJsddHnj8W0ff3dNzX5oZaXRM6ZZsS7Js+ZBt\n2QHz4gQAAB+zSURBVHFsAwaMAzgESGDZwLMPYZdk2YQQeJ4c7JMHdrMJx8JiCISHw6xtvI4ty2B8\nSbItydYxOkq3NPfZ09P3VbV/dEtqnSPJo+nWzPvx0+6rqvqdmVL1W796f7+fI39S4Mgn/thZ+oai\neDwJHLp6uhQm/7ioHEYvfv1M63m5ylk2v9t+kp88v5/R8RRVARefft8y7l3Tds2ToekkkYjxwtYQ\n1dXXfnzoqWgZVxSFlR11uJQYW/eP8+Qrx3l9dx/rltQS9DuvyWfKxD9TRxLkIplchuHYKAvr5pc6\nFDFFWoPNPNBxNxsPvczvjm0lncuwpL6j1GFdl9LZHMd7xzl4MkTXQASr0HhTVeGiraGC2Y0Bmmp9\n6BdIhsW1o6oK1RWuCb9QM1nrvAQ6FEkSjWfOtEonzjweCSdJZ3IX2dqVtRIqcF7SnH+soGv5Vnqv\n61SrfP6GlaJ/JI7m9OJz65OeYOdyFp1HRti8u5etnX2MRVI4HRp/cG8HH7xrgZSmXCWPZ2pax6ey\nZbymwsH9q+rZfSLJkZ4wz2zpZc3iRlZ21MkJ1HVM/oUXGYgOY2PTJOUVM0qjv473GBt47uDv2Hxy\nO7F0nNWzVlzVF+6VdrCZDpfKRsJJOo8OY54IkcnmW4rrKj0saKtk3qxKKnxX15IylZdjT5kOf4+r\n5dBV6qu91Fd7L3udTLZQwlIoXRkeDbNldy+6w0M2ZxV1QLTIZM+UxJwpj7HJ5HKF+zPvxzIZslmL\nnHXpS+TPv9kHgK4pVPicVPhcVPpdVPidBP0ugj4nFYX7oN9FsPC6z+1AUSCbs06XqgyP5TtOdg9G\n6B6M0nlkhEg8DUDQ7+SBW+fwoXs6qK30XP0vWUxbTofK/bfM4Uj3GK+808PWzj4Od49x16pW6mSf\nuS5JglykrzCChUwSMvPUeKt478J72XjoZXb272M8FWV9+1p09cr+iUQiEZ7b8xu8/omTjOu5859l\n2xztCbPn8DC9wzEA/B4HKxbU0dFaOSlDXU3l5ViQS5dXI18XrhEo7O4Bl8WRLje+Sbqubdk22axF\nKpMfBeT0yCCpHOORGNVBD4k0hGMpxqNpBkNxjvdNPBGQqipQqDW/mOoKFw+ua+fW5U0saa+5YBmQ\nEOea11LJrHo/m3f1cuBEiCd+c5Cl82pYs6QRt1NSruuJ/LWKnOqg1ywjWMxIQXeA9y26j02HX+Vo\n6CSxdJz75t9xxdvx+r34Au9+uKdylM7mMLvG2Xu8h/FYvnWtpd7Psnm1zGmqmPTLiVN1OVaUJ7Wo\n5jrgPftKRCzqYsOa2eed0GSyOcLRdH50lFia8cJ9frSU/P14LI2iUDRUnkZVwEVLvZ+W+gAt9X4q\nA66yrosW5cvt1LlndRsLWqt4bWcPe46McKhrjJuXNrG4vRpV9qvrgiTIRWQEC+HWXTzYcTevHH+T\nw6PHefrAJtY3ryl1WCWXSGV5fssxnnz5MOFoGlVVWDK3hhULaqkKSIdWUT4cukZtpUdKIUTJtTUG\n+PB9Hew+NMy2/QO88nY3+46OcPvKWTTVTs0wfuLqSYJc5NQkIZIgz2yaqnFX+y1UuPy83dfJxhOv\nUukN8mDFBlRlZl1mTWVyPL/lGL966RDhaBq3U2Npe5BVi2fh8zhKHZ64DNNpaC0hrjeaqnKDUU9H\nWxVb9/Rhngzx5MuH6Wir4tZlTXIcLWOSIBfpiwxS663GqV+b4VnE9UNRFFbNWk7QHeD1E9v4yd6n\n2DHYyWdW/+GMmGUxk7V48a0T/OLFg4yOJ/G6dT5yn8H6lbVs3d0rB/XryHQbWkuI65HP42DDmjaW\nzK3htZ09HDwZ4lhvmFWLGlgxv1Zq3MuQJMgFyWyK0cQYyxqMUociysiCmnYqFT/Hoj3sHNzHF1/4\nWx5d8hAPGfegqZM7OUA5sG2bNzr7+eGze+kbjuFyajxy9wLev34+FT7nlI8qISbHdBxaa6pHOZnJ\nI5yIydNU6+ORexaw/9gob3T2sXVPH3uPjrBuRTPtTRVS915GJEEu6I8MAdDklw564mxeh4fP3vAx\n9keO8PiOX/DT3U+x8fDL3NS8jFXNK1hSvwCHdv23qB7uHuMHz3TSeWQEVVV4aF07j97bITXGoixN\nZcu4jHAiJpOq5PtwzGsJsm3fAHuODPP8luO01Pu5bUUzNUGpny8HkiAX9MsQb+ISFEXhltabWFpv\n8PM9z7Dl5HY2HX6VTYdfxa27WN64iEZ/PWQtusN9+JI+dFXDoTpwaDq6quPQdDy6e9JnabRtG/Pg\nEayrXH8smuGFbQO8cyiMDSxqC/DA2gbqK1309XbTV7RsJBIhnshMy5ElpFb3+iOjnIjrmdupc/vK\nWSyZW8PmXb2cHIjwixcPsmRuflg4mYymtOS3X3A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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.distplot(rbh_df['E'], label='E')\n", "sns.distplot(rbh_df['q_len'], label='Length')" ] }, { "cell_type": "code", "execution_count": 148, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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7NEXqxYUQQogrQ5JxMSRlZufwyS9844znXvrt01yX4MUeWSllerrOa7/6L771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\niovGX/GCREIIIa7M5Sbj8ikthLj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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "figsize(12,8)\n", "scatter(bh_df.q_len, bh_df.E, c=bh_df.RBH, cmap=plt.cm.Paired, alpha=0.8)\n", "xlabel('Query Length (scaled)')\n", "ylabel('$\\log10 Evalue$ (scaled)')\n", "title('LAST hits, RBH and regular', fontsize=14)\n", "savefig('sigh.svg')" ] }, { "cell_type": "code", "execution_count": 168, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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L9bJtan6AJCKV4SWT+DgqgBaRpqKgQRrKapP4YoXNt+3bVfZqQr10hF5rZygR\nWR8VQItIM9LaqgjkahjWspGC61pabecnEVk/b3ZWBdAi0pQUNEjTyBY2L6Y9FtNeRQqbRaS5eMlx\nFUCLSFNS0CBNx8/8W4962TY1GyBlKUAS2bhcAbSISBNSTYM0jWzKTltml6RsTUO5k+mNbptaqyLq\nauz8JNLMvLExFUCLSNNS0CCyDuud8OcXUY/fcSeb7nl3VSf0ChZEKkcF0CLSzJSeJE0j7JSd/CLq\nz+6+kf/n+S5+81OPc/TEmZqNQUTWx5uehoXFsIchIhIarTRIU4lCys75ts18e+tVudvrTZMSkdrx\nxschrgJoEWleWmmQhjI/MMD8wMCqx5S6vWqlFRZRO1u24LS11XwcIlIe33Xxp7VlsYg0N600SMMY\nufsdLJx8HIC2Azex/dMPhTyi5RKHD/Gyu+7kdadG+MbQPKCdjUSizh0b0yqDiDQ9BQ3SEOYHBnIB\nA8DCyceZHxig/eDBEEdVXEtfHz/X18cdmWZrChhEos2fnATtmSQiTU5Bg0hIFCyIRJ+XSgWNXRQz\niEiTi0zQYIx5JfD71tpbC+5/L/ALwMXMXfdaa/+p1uOTaGs/eJC2AzctSU+K4iqDiNQXd3wctM2q\niEg0ggZjzG8A7wSmijx8PfAua+0TtR2V1Jvtn34oVwStgEFENspbWIDZWYhH4k+liEioorJ70tPA\nmyi+AHwDcL8x5m+MMR+o7bCk3rQfPKiAQUQqwhsbU8AgIpIRiaDBWvsFIL3Cw58B7gVeC/yYMeYn\nazYwqVvpwUHSg4NhD0NE6pTv+/hTxRa/RUSaUz1cQvmItXYSwBjzZWA/8OWVDjbGPAB8qDZDkyhK\nPXgk13m5s7+fxOFDIY+oPEPaVUkkdN74OD6O6p9FRDIiHTQYY7YATxpjXgbMEKw2fGy151hrHwAe\nKDjPHuCZqgxSIiU9OJgLGABmjx+n8647aenrC3FUpTt64gyPPjUMBP0b7rl5b8gjEmlO3uQkjgqg\nRURyIpGelMcHMMa83RjzS9baCeADwKPACeD71tqvhDlAkUoZSs7kVhWyt7MBA8CjTw0veVxEasOb\nnYWFhbCHISISKZFZabDWngV+NPP1Z/Lu/wxBXYPImlr6+ujs71+SnlSNVYaNphBpRUEkurzkOMTU\nAVpEJF9kggaRSkkcPkTnXXcCVCVg2OiEv9iKwm37dtHb08Wt1+xccm7VNYjUlu95+NNTChpERAoo\naJCGVK1w27VLAAAgAElEQVQahtUm/JVwz817uW3fLkCF0CJhcEdHFTCIiBQRtZoGkUgorDeopOyK\nQlbhikJvT5cCBpGQ+JOTYQ9BRCSStNIgUmC19KNKpRBpRUEketzJyWA7Dm2aJCKyjIIGkTylpB9V\nasKvYEEkWryJCdA2qyIiRSloEFkHTfhFGos3NwezsxDXn0URkWJU0yBNrbB2Ya16AxFpTN5YUgGD\niMgq9BtSGl56cBBYvqPSSrULqjcQaS7aZlVEZG0KGqShpR48sqTRW+LwIaB47cK1fZewc0uHdi8S\naTLu2JgCBhGRNSg9SRpWenAwFzAAzB4/nlt1KDSamucPvvwU9x87xdETZ2o1RBGJAG2zKiKyNgUN\n0pTyaxcW0x4AbS3Bfw6PPjVctR4NpUoPDq4Y4IhI5XipFHh+2MMQEYk8pSdJw2rp66Ozv39JelJ+\nXcM9N+/l2r5LGEnN89BjZ0Ma5XIrpVSJSOW54+PaZlVEpAQKGqShJQ4fovOuO4HVC6G3dLYyMbsI\nhLtjUrGUqs677lw2dhHZOG9hAebmVM8gIlICBQ3S0IaSM5DYviwIKCyEnphd5NfvMLlC6IqPgfrZ\nianexiuyXt7oqAIGEZESKWiQhrXSlqorqUbAUO4Y1kqpqrZyxytSr4JtVqfBUWmfiEgpFDRIQyq2\npWq29wK8WAidP0GuxgpDsTGs9TqrpVRV03rHK1KP3LExBQwiImVQ0CBN4/Mnn+O7Z8eAF6+iR7WJ\nm2oYRKrLn5gAVAAtIlIqXWaRhpS/pSrADXu25gIGgIdPn+OJs2NVbeRWOIYwC6xLUW/jFVkvd3IS\ntMuqiEhZHN9v/N+cxpg9wDOPPPIIl112WdjDkRrK77dw/7FTQNDILTW3yKU9Xdy+b3fVVxvqrbC4\n3sYrUq7FwUFYTIc9DBGJqnSaVvNSLUUWUHqSNIXsVfSHT58jNbdIoqOV1pYYnzs5yMOnz9HWEqta\n4W+9Tb7rbbwi5fBmZ2F+XrsmiYiUSUGDNKxiOwFd23cJ//HLT9HaEmMx7QUBRGcroMJfkWbgjSUV\nMIiIrINqGqQhDSVnePj0ORbSHhAEBEPJGfbv2crt+3bnjkt0tNLWov8MKm0oObMkNUwkCnzXDbZZ\nFRGRsmmlQRrS508+l5u0Jjpa2ZZozz2Wv2vS106fr+q2q+uVHhwE6nMXJfV6kKhyR0YgrlUGEZH1\nUNAgDWcoOcN3z46R6GglNbdIam6R2/ftXhIQZL++bd8uru27pCqN3dYr9eCRJc3dEocPhTyi0qnX\ng0SV7/v4qSlwVNsoIrIeChqkYW1LtLM5U6/w5gOXL3s8ilfE04ODuYABYPb4cTrvurMuVxxEosRL\nJvFRZwYRkfVSMrc0nPx+A60tsWWrDFD8irhy8DdOvR4kqryJCRytMoiIrJtWGqQhRbnb82pa+vro\n7O9fkp5Ub6sM9frZS+PypqYg7UJM18lERNZLQYM0rNUmrNkr4sWKoMNubpY4fIjOu+4E6rMQGhQs\nSLS44+MKGERENkhBgzStYlfEo1LnUK/BQqXU8+5REi3e/DzMzqo3g4jIBilokIZVyopB/mPa+Sca\n6nn3KIkeb3RMAYOISAUoaJCGkR8kRGXFQMqj3aOkknLN3JSaJCKyYQoapCHkBwk37NnKd8+O5R4r\ndcVgtToHEak/7oULChhERCpEQYPUvcK0ooGnR/CBtpbyJwva+SdcjbB7lESDt7CAn0pBXH/mREQq\nQb9NpeG0tsSWrDaUu2KgYCFcjbB7lITPu3BBAYOISAXpN6rUvWJpRffcvDf0rVNl/RQsyEZ4c3P4\n2jFJRKSiFDRIQ7jn5r3ckj4PwJ5M0fNKwYKCCZHG5l68qIBBRKTCFDRIQxi5+x20nXw8+PrATWz/\n9ENFj6v1rkoKUERqy5uahrk5BQ0iIhWmbSWk7s0PDLCQCRgAFk4+zvzAwLLjivVhyE7qq+HoiTPc\nf+wU9x87xdETZ6r2OpU2lJyp6uciUk3uiFYZRESqQSsNIlVQr43i1N9C6pmXSsFiWtusiohUgX6z\nSt1rP3iQtgM35W63HbiJ9oMHlx2XLZjOUh+GpbKBzkLaYyHtVX0lRqTS3JERBQwiIlWilQZpCNs/\n/VAuJalYwJBVrA/DUHKG4Yk5dm7pqEgQkR4cZAfUZaO40dQ8qblFABIdrRU5p+o6pBbcZBI/7eIo\naBARqQoFDVL30oODwOrBQr78yevRE2f43MlBUnOLJDpaecuBvg2l5KQePJJrTPam/n5ue+fPL3vN\nZqJ0J6kF3/fxRscUMIiIVJF+w0pdSz14hLF772Ps3vtIPXikrOcOJWf46ulzuSvrqblFHj59jqHk\nDOnBwVwwUqr04GAuYACYPX6cHamRUAOGcouatyXaubSni0t7utiWaN/wa6+38Hw9n780L3d0FD/s\nQYiINDitNEjdKjZJ77zrzg03Bps6+gniX/ocAF1vfCOJw4fWfa6h1AItyZlQAodyr/IXa5IXxrjz\nV2s6+/s39PlL4/M9D398HMfRNTARkWrSb1lpWr09Xdy+b3cudz/R0cptfZ0kPvlR3GcHcZ8dZOpP\n/7TkK94tfX109vfnbn/xx9/BB795MZQtV9d7lf+em/fy4bddx4ffdt2GU4nWU3heLBDUioOsxh2+\nAAoYRESqTisNUreyk/T8q9LlrjJkC6OzhdDb7JOMTkzie15wwMQk7tBQyedNHD5E5113MpRa4LFv\nXszdXy9brkJl6y+KFZ6LVIq3sIA/lVJfBhGRGlDQIHUtO0kH1p2W1NvTlZvQpnt7IR4POsoCdHcT\n7+0t63wtfX20JGeAi2seWy1RSTXKjqVUlQgEpXm4wxcUMIiI1IiCBql7lZ5UOps24S8s5L5ej/VO\n2iu5PWm9XuWvRCAojc+bmoa5WQUNIiI1oqBBZBkfYs6LX69TOZP2oeQMnz/5HN89OwZUbnvSegoW\n8ilYkLW4F7XKICJSSwoaRJZx8nZicVY9ci2lTNqPnjjDV0+f44XkDImOVrYl2uuqBkKk1tyxMXA9\ncDb236eIiJROQYNIgfiOl+BfsgUAp62tqq9VuMtRam6RRGcrbS3aDUakGN/38caSChhERGpMMxOR\nPNlCXKetDaetrWaFuK0tsdzWrxBu4bJIlLkXLypgEBEJgVYaRArkb5ua7u0lUcXXyi+Y3pZo5/Z9\nu3nzgcsVMIgU4S0u4k9MQkzXu0REak1Bg0gRD51N8+hTF4GLFStKXkm97nIURZXcfUqix7twQQGD\niEhIFDSIFCjWTbnaRcma5G7c0RNnlmxxW81AT2rPm5nBn5nRjkkiIiHRJRsRqXvFAr3sqoM0BveC\ntlgVEQmTggaRAtk6gywVJYuEyx0fh7Qb9jBERJqa0pOkYW0kvz3sOoP04CCgJmelWm8Hbok+3/Pw\nRka1Y5KISMgUNEhDqkR+e1iTztSDR5g9fhyAzv5+EocPhTKOehN2oCfVoS1WRUSiQelJ0nDqOb89\nPTiYCxgAZo8fz6061MpQcqain1elz7ea3p4uBQwNxFtYwJ+cDHsYIiKCVhpE6kKtthKt9A5E2tFI\nNsIdVvGziEhUaKVBGk49FzJnO1Jndfb389DZNPcfO8X9x05x9MSZqr12pVdo6nnFR8LnpVIwNxv2\nMEREJEMrDdKQapnfXumi5WxHaoALie08euxU7rFa9IwQiQJ3ZESrDCIiEaKVBmlYtchvTz14hLF7\n72Ps3vtIPXhkXecolvPf0tdX852TKr1CU88rPhIud2QE3/XCHoaIiOTRSoPIOhUrWu68686yJvtr\n5fzXeivRSq/QaEcjKZfvunjj4ziOrmmJiESJggaRkBTL+S+WelTriXelX0PBgpTDHR4GBQwiIpGj\n38wi61SsaHmtVYb04OC6tlDVVqLSDLyZGfzp6bCHISIiRWilQepOrbYfLUV+0fJaAUNh07bew4fU\nxVgkj3tBW6yKiESVggapK1Hc97+U1QV3aKho/YNy/kUC7tgYpF11fxYRiSgFDVI3Sq0BWEult0hd\nTXZ1wV9YwBsfJ75jx7JjFCxIs/M9Dy+ZVMAgIhJhChqkqRSmCCUOH6raa+XvruS0tQEO/sICTltb\nSfUP9SxKKWRZURyTBNzhYUABg4hIlClokLqx0e1HK7FF6kbEd7yELR/6IPHe3mWv2UgT2iimkEVx\nTBLwZmbwp6ZUyyAiEnEKGqSu1FMNQHZ3pfyVjfaDB5cd10gT2kqlkDX6mORFKn4WEakPChqk7qx3\nsldsEl/tVYa1dlfShFaamYqfRUTqR2SCBmPMK4Hft9beWnD/G4B/B6SBj1trPxrG+KQxrDSJr2Z6\nUCPXLhSqVAfrShar17qrtpTG9zy8sTE1chMRqRORCBqMMb8BvBOYKri/Ffgj4EZgBviWMebPrbUX\naj9KaRSFE9Ew04MacUK70RSyahSr11NaW7NQ52cRkfoSiaABeBp4E/DJgvuvAZ621k4AGGO+CdwM\nfK62w5OoqPR2qdVIDyp3jI04oV3v+6hmsXqjfLaNwJubU/GziEidiUTQYK39gjFmT5GHNgMTebdT\nwJaaDEoip5bbpa7XeseoCa00ExU/i4jUn6ivDU8AibzbCSC52hOMMQ8YY/z8f8Az1RykVF+xK9DZ\nK/obkU0PytpIelC1xthMssXqWY3ez6IZeVPTMD8f9jBERKRMkVhpWMU/AlcbY3qAaYLUpD9Y7QnW\n2geAB/Lvy6xiKHCQohoxPaierbXjlNQ3d3REqwwiInUoaisNPoAx5u3GmF+y1i4C7wMeBh4DPmat\nPRfmACUc1b4C3dvTteGAQVfJK6elr0+fXQPypqZgfiHsYYiIyDo4vu+HPYaqy640PPLII1x22WVh\nD0c2oNKF0NVQOMZG6vYsshGLZ8+C64U9DBGR1aXTtJqXqoFMgainJ4ksUUqwEPYkPX+MjdTtWWQj\nvFQKFtMQi9oCt4iIlEJBgzSU7CR9Me1x8KrtvPnA5UA4AUS9dnsOO+iSxuSOjChgEBGpYwoapK7M\nDwwA0H7w4LLHspP00dQ8qblF/mzgWf7y1BA7tnToKn+J6n1lpFIBjwKnynInJoK0JEer/SIi9UpB\ng9SNkbvfwcLJxwFoO3AT2z/90LJjFtMeqblFPN/H9X2m5tP0pL1QrvLXU7fnoeQMwxNzdbkyklWp\ngKfeA6co8sbGFDCIiNQ5BQ1SF+YHBnIBA8DCyceZHxhYsuLQ29PFwau28/nHg0LkuOMQC3meUg/b\nuWYnyQtpj9TsItsS7SU9L0pF6ZVKBavXlLIoc8fHtcogItIAFDRIQzl8hwHg20+PkJpdBKC1JZa7\nyh9G2kmUJ5z5k+S2liDffDHtLfnMiqmH7twSDVplEBFpDAoapC60HzxI24GblqQnFatrgCBwyBZA\nZ/X2dCntpATbEu38+h2GnVs6VgwYinW+7rzrzlBXHCqVClZPKWX1wB0bw3c9HBVAi4jUPQUNUje2\nf/qhVQuh8xVO9JR2UlyxSfL+PVtDHtX6VCoVrB5SyuqFl0wqYBARaRAKGqSurBUsSPnKnSRnO1/n\npydFoa4BKjfJV7CwcW4yie8rM0lEpFE0VdDgpVJhD0FCspG0k/XUQVS6dqLatRjlnjdx+BCdd90J\nRKMQWqLHGx/HUcQgItIwmitoSCbxXRcnHg97KFIlq02u15N2sp46iPzn3NLbzruu276hiXVUazEU\nLMhKvFQK0q6auYmINJAm+43u4J47F/YgpEqOnjjD/cdOcf+xUxw9caboMb09XWWtMBTWQWSDklKe\n4164wCPf+D7/cPg3SD14pMR3sfExiITNTSYVMIiINJim+63uz87iTU6GPQypsKhNrv2FBfyJidzt\n2ePHc30NKiE9OLjsfMXuE6k1b3oa5ufDHoaIiFRY0wUNxOK4Fy7ie17YI5EqWEh7LKQr873dkRrh\nlt4XG52VUgeRrZ3IetXY0+xaWH+QWni+W6/ZSeJTH2fs3vsYu/e+3ApG6sEjy+4TCUOwyqAUUBGR\nRtNUNQ05TpCm1HLppWGPRCqkt6eLLZ2tnBpMAnBdX8+Gioazzct+Enj1HXey6Z53l3y+bO3E1NGn\nuOTvvwNsbIeh/FqMHakRxn5vaY+EtptujFzfBGlO3twczM4qaBARaUDNGTQA/swMXipFLJEIeyiy\nDoUFz0PJGSZmF7k0c3tidpGh5My6AofC5mWXPPznbH1TP/SUPgnv7emC99xH+k39wMaLhrPvI13m\nBmBhdMCW5uWNjilgEBFpUE0bNBCL4w5fwOnuVvOhOrPabkKtLZX/Xp5v28xcaoH1TPsrfbW/WI+E\n9oMHi/ZNiOquS9KYvMVF/OkpiDfvnxURkUbW3L/dHQf3/HlaenvDHomUaLXOzuvtw5B/boDevIn5\nZ3ffyMCVNxD/5kVuHY1FYuJdrEdC4X3qgC215o2MKGAQEWlgTf8b3p+expuaJrapO+yhyAatpw9D\n1rKr8ocPkXztT3Dy6y8Qb2sDojXxLraCoRoGCYvvefhT09pmVUSkgek3fCyOe/FC2KOQEhXbTSh/\nEl/Yh2EoOVNWbwV4cbvWlt5enEzAUG/W+pxEKskdGVHAICLS4Jp+pQHAdz3c0VHi27aFPRRZQX5B\nb6krChvN6a9EylOYVvucVCAtleL7Pv7kJDgKGkREGpmCBsBxHLzxcWI9PSqKjqDs5N9fWODH9yT4\nuTdcv+Zkt5yc/tWCg42kPG1EpSb1xZ5fywJpBSeNzx0dxcfBCXsgIiJSVQoachzc4WFadu8OeyCS\nJzv5dy9cwEuO81fPwKt/cJKXvue+ir7OasFBrSe81ZzU17JAWrs3NT7f9/HHJ3AchQwiIo1Ol9Xz\n+FNTQXMiiRR/YQFvZBQWFmBhgZnPfZ704GDRY9ODg6QHB9eV019YDxGGleor6k2jvA9ZnZdM4oc9\nCBERqQmtNOSLxXGHh4ldcUXYI5GM3p4ubt7q87DvQCzOa85+hx3nn8UdGlq2W1C2izMEvQruOXwo\nlNSiaqhkutJadRpKKZJSecmkVhlERJqEgoZCi2nc8XHil1wS9kgkI7Z5Mzg+uD6kXYjHiRf01sh2\ncT7fthmAXceP03nXnfTW2TakxSb1Xzt9vqJpPqulYlUqpajei8hlbe7YGL4PihlERJqDgoZCjoM3\nMkpsyxZdQYuAoeQMf302RSsALgN7b+A1k8+wo8ixn919I9/eehUArxp7mntrOM61lHP1Pn9SD3D/\nsVO5rytVg1Ds+ZWudwiriFxqwxsf1+9IEZEmoqChGMfBHb5Ay66dax8rNeG0tuDH4wDEtm1d9viF\nxHYGrrwBJiYAGLjyBn46sZ0we31nA4X1rBRkJ9n1XgegYKExuePj+K6n3eZERJqIgoYV+JMTeFt7\niNVpc69G0dvTxWuvu5y/Gh+HiQleNfY0V77+x4p2P47v2IGfSSvLb8qWLZpeqWNyNXL4s2k+i2mP\nydlFtiXagfKv3hem+dzS286O1Aj0VD7tSilFUiovmVTAICLSZBQ0rCTeEhRFX3552CNpetk0l/TQ\nEL2JH18y+c+f8Beb8BYWRycOH1py7mpsC1qY5pOaWyTR2Upby/omWdn3P3X0E1zyX/+cMYq/l0pQ\nSpGsxZ2YANdTMYOISJNR0LCauXnciQniW7aEPZKm19vTBT1XLbmv2IQ/f8KbLY7Oms0UR2eDjlr0\nLGhtiZHoaM3dXu/V+x2pEVoe/vPc7ZkvfpG2m26k/eDB3H1rraiUQjsnyVq8ZFIBg4hIE1LQsJpY\nLCiKTiS0FB8xtWxSVq7CVY+3HOir6NV798IF/IlJxn/rt+l64xtJHD605opKKdSMTdbipVKwmAb9\nPhQRaTr6zV8Cd/hC2EOQdWjp66Ozvz93u7O/f8lV+PU0gCvVPTfv5cNvu44Pv+067rl574Ybx2Xf\ni7+wgD8xibNlC05bG7PHjzM/MLBsRWWl5ncrUTM2KYU7NqaAQUSkSWmloQT+VApv7hJiHR1hD0Uy\nSi3aTRw+ROdddwLF03aqmcNf6fMlDh8i3nc5qT/8I5zu7oqeW2Qt3tQULCwqaBARaVIKGkqhTtGR\nVOqEf60c/5V6Fqx13lrLpiB509MwPUN8x0vo7O+n/eBBOvv7l6QnlVvXkB+ETc+nuf6Knki9dwmf\nVhlERJqbgoZSqVN0JK014V/P5D/M3P6Vxptf1B3fsQN/YYEtH/pgrhB6rRWVUtxz814e++eLPHNh\njodPn+P8xBwfefeN630r0kC8qWmYn4dYPOyhiIhISBQ0lMpx8EZHiW3erKLoCCmcZOdP+Ld0tjIx\nuwiUPvkPs8C6nGDFaWsj3ru0dd1Gdk0CeOLsGPbcZG5jnFODSZ44O8b+Pcub6UlzcUdHFDCIiDQ5\nzX7L4uAOD699mNTE0RNnuP/YKe4/doqjJ84smfAvpD1ODSZZTHtA9At71ypEXquoe7XzVvN9V/v8\nEj5vagrmF8IehoiIhEwrDWXyp6bwZmaIdSnfO0zFJtnX9m08dSzKXZFXSkFaKaWp3DSr/Xu2cl1f\nD6cGkwBc19ez6iqDtmhtDu7ICMS1yiAi0uwUNJQrWxR95ZVhj0QK7NzSkZvwt7XEuK6vZ0l6UqmT\n/1IKrOcHBgCWNFfbiFKDlcLVhZUm7utNs/rIu2/kibNjAKsGDFHukyGVo74MIiKSpaBhHXzXwx0Z\nIb59e9hDaVorTbILJ/zr3QVpteNH7n4HCycfB6DtwE1s//RD63kLy5S7/Wu1Ju47t2hrYQloxyQR\nEclS0LAOjuPgJcdxtmwh1toa9nCa1kqT7JW+Xk22GdpadQLzAwMsnHwc3wtqJRZOPs78wEBFVxwq\ndZ71pFmVmnIU5TQuqQwvlVJfBhERyVHQsF6xGO75YWKXXxb2SJpaJSaq2f4HEBQYp97586ue219c\nBNcNvg4x13utiXu1Vy6q2RhPwueOjipgEBGRHAUNGzE7izc5SWzz5rBHIuuUHhzkmb/6JrRtZtfC\nJJ944gIneRynra3olfZ4by9ORwf+9DQATkfHsq1Pa2mtiXu5k/nsblOtLaVNFhUsNCZ3YgLSLrn9\nd0VEpOkpaNiIeBz34gjOpk3q3VCnPnlqhEeu7sf3fK6dGOR0zxVk1w5WutLesvfKF4OG7u4aj3i5\nSk3cv3b6PJOzi6TmFkl0tPKWA30VOXcUu2vL6ryxMQUMIiKyhIKGCnCHL9Cye1fYw5AyDSVn+MbQ\nfLCd5NwM3+2+DKellZa2thWfk+2XkJ/OtNGmalGQTU3almgn0RnU6WRXMDZC27LWH3diAlxPQYOI\niCyhoKEC/KkU3sxm9W6ImFKucPsLC0F9QlsbrcC+0TM8dWlvLj2p2HNX6pcQVaUWeWe1lZiatJZs\nILKQ12BP27JGnzc6qoBBRESWUdBQCerdEDmlXOHu7enix/ckeORZcGIOrxp7mree+w5z7/mXtPT2\nrjq5dYeGgOgHDYVF3onDh4oeV63dkEZT86Tmgl4ZiQ7tNBZ17vg4vusp3VJERJZR0FAhvuuRHhmh\nRb0bQlfOLkA/94brefUPTjL36F+za2GSzv5+drz8qlXPX60+DZWWHhzMBQwAs8eP03nXnSsGOtoN\nqbn5noc3NqaAQUREilLQUCGO4+Anx/HUu6HuvPQ995F+Uz9Qep+G4e5twR1/f4aprz/Gntf+aLWH\nWROVDha2JdrZnKmRKHVHJgmHOzQEftijEBGRqFLQUEmxGO7588QuvzzskTS19aTalJNm9PmX38bA\n5a8g2bEZHHjJEzO8tuVM5Ip8s0Xbz/zVNwG48vU/VtN0KjWAqx/u2Bj+7Jz6MoiIyIoUNFTa/ALu\n6CjxbdvCHklTq1aqzai5lr/94R9lcXae6fZOiMXo6eisSpFvJbYq/cJ1/XydfSy4Hj/60l4OV2pw\nJVLKU/R5s7PBFqsKGEREZBUKGirNcYK84E2biLW3hz2aplatSWrL3r24k1Mw4+HEqzPRqsRWpdna\njrF5n9Rcms8/HuyidPgOU9GxrkXBQnT5nhekJTkKGEREZHX6S1ENsTjuuXNhj0KqIJty0755E5u7\n20l0tNLaEqtI6s1Qcib3r7CQO7vqUK6FtJfbvQhg4OmRdZ9LGo/7wguAtlcVEZG1aaWhSvy0S3p4\nmJadO8MeilRYfspN1kYDhvyVhRv2bF32eHpoiHSqrayahN6eLl511fbcCkM2wBEBcEdH8efmlZYk\nIiIlUdBQJY7j4E9O4m3aRKy7O+zhNL1K1Afkq3TtQv7KwnfPjnHDnq189+wYAD86foaO9/8OY6ze\na6GYbCrSwNMjFVsRkfr3Yh1DPOyhiIhInVDQUE2xOO758zhXXqm9z0NUifqAWnvzgct584HLSQ8N\n0fH+38ndv1avhWIO32F484FgRy8FDJKrY1DAICIiZdBMtuoc3PPnwx5E06pkfUC1ZOsksrKrAb09\nXfQm2ir2GqUGDNm6ipVuS31LP686BhERKZ9WGmrAn57Gm5wktnlz2EORiMrWSQxPzLFzS0fu/myv\nhWxn587+/qr2WihclQEisUqTHgzqMmrZZ6IRpc+dw19YwHEUNIiISHkUNNRCLI578SJ0dqpbdJk2\nWotQTw3Gvnb6PI8+Ncxi2uPgVdtz9QiJw4fovOtOoLqT5sJVma+ePocPtGWKp6vRi6IUqQePLAma\nyqnpkBelR0bwp6aVKikiIuuioKFmHNwXXiC2Z0/YA6kblapFKGwwVumi6ErITthHU/Ok5haX9VRo\n1ivs6cHBXMAA66vpEHDHx/GTSdUxiIjIuumSUw35aZf0+eG1D5SK1yJkc/qPnjjD/cdOcf+xUxw9\ncaYSQ62YxYKeCt+ucU+FwtqK2/ft5o59u3O3o7xKIyvzpqbxLl5UwCAiIhuilYYachwHPzWJ19Wp\n+oYQFAtEwki3Kaa3p4uDBT0V2kLoqVC4KgMsu11Lta7paDTe3Bzu+XMKGEREZMMUNNRaLI47fAE6\nOoJXZUkAACAASURBVIi1VWZnnEZUT7UIlZJNRfr20yO0hdhTofA1w/7ca1XT0Wi8xUXcF4bA0YKy\niIhsnIKGMMRiuM8/H/Rv0C4mKyp21TtrfmAAgPaDB0s+Xz0EIlHoqRDFmg8FC+XxPQ/3+efDHoaI\niDQQBQ1h8cEdGqLl0kvDHkmkFZu4jtz9DuYH/haA9oOvZPunHyr5fKsFIrUQxQk5vDiu7A5OUD+N\n8GQp3/dJP/cceH7YQxERkQaioCFE/sws7tgY8a1bwx5K3ZgfGGD+W4+B6wa3v/UY8wMDZa84hKGU\n3aDC6F6dfc2FtEdqdpFtiXYgWjUfUjr3hRfwF9NaxRQRkYpSsmuYYjG80VG82dmwR1I33OHhXMAQ\n3OEG90VcKbtBhdG9uvA1U3OLLKa9qr5mM6l1N+30+WH8eTVvExGRytNKQ9hicdyhIZy9e/WHvgRt\n+/fjdHfjT08D4HR307Z/f8ijKp+/sEB6aAh6rsrdNzwxx0LaC2XXJAiauCU6Xmw+uFbNh7o0r67W\nq0bpkRH8VArUvE1ERKpAQUMkOLjnh2nZvSvsgUReS18fiUO/xsxnPwtA11vfWheT1vwibPfCBQ4+\n8106jn+HVKbDcXaCmZoN+jRsS7TXpFC7sDj8LQf6Sqr5UJfm1dV6e183mVTzNhERqSoFDRHhT6Xw\nphPEurvDHkrk1esWnPfcvJdb0ueZ/D+fgNZWzrdtZtfx4yRf+xM8+tRFIAgWFtMev36HYf+e2tS6\nlFscri7N0eKlUngjIwoYRESkqhQ0REUsjjs8rG1YS1SPE9TUg0fo/OIX+dImw8CeG0i3tbF//Fnu\nLjiutSXGzi0dNR2bip0rq1bb+3rT07jnzytgEBGRqlPQECU+uMMXaNm1M+yR1JXCbUyjuK1p9ur8\n8KbtDOy5gWRrN9Pt3fxl7za6n3cj3z8in7o0l6ba2/v6nod7TgGDiIjUhoKGiPFTk3ibE8S6ojtp\njJLCYlMg8n0G0m1tTLd3Q2srTjzGwNMj/MHd+0PtH1Guek0Rq7Vqfi/dc+dAq5IiIlIjoQcNxpgY\n8F+Ba4F54BettT/Ie/y9wC8AFzN33Wut/aeaD7RWYnHc8+eVplSCwmLTr54+x8xCmpZ4jO72lkj1\nGchend91/Dj7x5/lL3u34cSD3YpaM7slRWGc5VCwEB4vlcKfmdEqg4iI1EzoQQPwRqDNWvujxphX\nAn+YuS/reuBd1tonQhldCHzPx714kZYdO8IeSl0ZSs4yt+iCA12tcS7fHq2i8uzV+fcD3U/NMvD0\nCK0tscinI0m0+J6HO3xBAYOIiNRUFIKGVwNfAbDW/q0x5saCx28A7jfG7AK+bK39/VoPsNYcx8Gf\nmMDbvJlYR20LYutJfrHpzHyaRdcjHnNwfZ+ZRRezKxG5yXj26vyvMMhdl+2kpbc3cmOUaFNakoiI\nhCEKXYA2A5N5t91MylLWZ4B7gdcCP2aM+claDi40mTQlWd09N+/lw2+7jl+69SpiMYdYzKEtHqMt\nHuMnrusNe3hFpR48wti999Hx/n9F4lMfD3s4soZad3VeTS4tSUREpMaiEDRMAom82zFrrZd3+yPW\n2jFr7SLwZaD+2v+uk592SV+8uPaBTa63p4uh5CytMYdF18P1fF5xRU/N+hysJT04mOueXKzHQfYx\niZ6jJ85w/7FT3H/sFEdPnAl1LEpLEhGRMEUhPelbwBuAzxpjDgJPZh8wxmwBnjTGvAyYIVht+Nhq\nJzPGPAB8qGqjrSHHcfDHx/E6OoklNoU9nMjKFkRfvr2bmfk0AP/2DS8LeVSBws7J2R2HJPpq3dV5\nLUpLEhGRMEVhpeF/A3PGmG8RFEG/1xjzdmPML1lrJ4APAI8CJ4DvW2u/strJrLUPWGud/H/AldV+\nE1UTi+MOn8dbWAh7JHWhq72FrvYoxMLFVxUgCB6yotLjIEopOLKc0pJERCRsoc+urLU+8CsFd/9T\n3uOfIahraF5ODPeFF3D27NE2rEXUqvtupUStx0Fhr4so9rYIQ1R+rpSWJCIiURB60CAl8nzcF16g\n5bLLwh5JJGTrALKT7o123y08XyWs1jk5CsECRC8FJ2qq3dV5Lb7nkX72WaUliYhI6BQ01BF/dg53\ndJT4tm1hDyVUhXUCicOHgPVP6lY6XyVEbVVByhdWAJULGDw/lNcXERHJF4WaBilVLIaXTOJNTYc9\nktBUevehWuxm1NLXF9mAIZuCkxX11K5moYBBRESiRisN9caJ4Q6fh/Y+Yq2tYY+maWSLhHt7upgf\nGACg/eDBMIdUMWGn4MhSChhERCSKFDTUJScojL7iiqYrjF6tTqBa58svFD7w5F/zxof/BIDWfT9C\nz0f+c2RXEcqhYCEaFDCIiEhUOb7f+H+cjDF7gGce/pM/5dKdO9c6vG44He20XHpp2MMIRaULl1c6\n31ByhvuPnQLAn5om/cwzvP9vPs6O8fPgurTsvZKut761onUQ0pwUMIiIREQ6Tat5aXNdlS2Bahrq\nmD8zizs6GvYwQlHpOoFyzuf7Hrhu7ra6OstG+b4f/AwpYBARkYhS0FDPYjG8sTG86eYtjK62/EJh\nZ1M3r/ZH2DkVBGpOdzdOd3eYw5MG4V64gJ921z5QREQkJKppqHexOO75Yei7XIXRVbKkUPjeVzE/\ncCszX/jfLJ4+DUSnq7PUJ29mBn9yEkfN20REJMKaKmjwGrh+oxkKo4vVHeTvarSaUo9b6fj857Uf\nPEj7wYNVaQgnzcX3fdxz59TtWUREIq+pgoZzUwtsW3Tpam3AP9Cuhzs01LCF0cUasD34sOWEvUBr\nPMYd+3Zzz817iz43f/ejW6/ZueJx5R6/WrBQbpAizck9fx5o3EBfREQaR1PVNDg4/5e99w6P6zzv\ntO/3nKnoHQQogqRYjkSJoiopWYWqkUXbKrYT2yq286U5603y7TrZbJw4jv3tlTjN19pO300i2ZId\n25IsyY56I9VIqpJU4SEpggQJgABBtJnBlFPe748zMxgAgzIABvW9dY0wc+ozAwJ4fu/TOD1k0zNk\nz7cpRWGpFEZ39A1lnW7IP4DtOw++zo93H+dk7xBtPTEe3Ns24pzca2UEAMALH3TlPW66x+fjvl1H\n+epP9vHVn+zjvl1HJz1+9Puda+y2NlXIPQ+4kQgyGp1vMxQKhUKhmBLLKtIAIIQgZjkkBl0aSn0E\n9CWkm9KF0SIUQlukBbpTWeU/Fajg5eNRnHS6mSMlA/EUXQMJGiI9wPylDOUTHTdtXjFuxKHQKMhs\nky+Coyg+0nFwurpVWpJCoVAoFg1LyGOeOkIIXKAjYtGfXGJRB03H6ezETSTm25KCyXW4U/EkT73l\nRQ8yA9gyhK67lkAogJ5Tv1EW9FP6yE/o/a0v0ftbXyLyvb8DRnY/As8xnyhlqNDjC3lvo6MJsxHV\nmAn5Ijgq4jA3OB0dsITrjxQKhUKx9Fh2kYZcNE0wkHCIpVwaSnz4l0rUQWg47R2w6iy0QGC+rSmY\n06fOELW85z/6p0f5yh99jvLf+a+Eb7sVgIaWFn5p11Ee3NvGYNyiNOjjl8+tpOofHsteI/7444Rv\nuxVfS8vI7kdTEACFHp9Lc3UJl6yp4bUjPQR8Gted28gzB07NazRBsbBw+vuRiSRoS+T3jUKhUCiW\nBctaNIAXdXAktEcsKgI61WF9yXQgck6cXFStWJurS7io1sfDJ7zXpXaCt89YtL13hJbz1o9IOco4\n9l0DCRorQzREeujNc83pFiRPN7pw366jvHmsFwFcsqaGmzavyE6UhpHpSpmoRq6gmMvC6UwEJzc9\nSXWCKi6uZeH29CjBoFAoFIpFx7IXDRk0TRCxHGK2S13YR9i/NP6oO21tsHo1mm9xfKvvOLeaV155\nHxwHv2sj9ZF257Y5zTjeHX1DdJfXUT7KAX7gmM0LH3gO+1ys8OemG/l9Gm8e6+Uqo37Cc2YS1cjc\nc7rnAiMiOEowFBfpODgnToBYGr9bFAqFQrG8WBye5BwhhEAC3UMWYZ9GXYkPbdFHHQROWxtizRrE\nIljdbC4PcHXrG+xuPh+Ay0++TXP5jUD+ot0RhcRbdnBX2gHuLq/jhXFW+OeSxsrQpNGEmUQ1ZiPt\nSYmF4iMdB/v4cVi6o2IUCoVCscRRoiEPQggSjuTEYIrqkE5FcJF/TBLs48fxrV694IWD09HBp959\niiuP7gVgxVAfTsddAGOKdvuu/ygvfHA6u80TBls8J3ySguJizFEYL91optGEfBTapUkxf7i27UX8\nlGBQKBQKxSJmkXvDxUUIQV/CIZJ0qSvxEfQtbId7QlyJ3dbmCYcFHD3Rm5sRlZWsGOgDQFRWojc3\nF3ydieoFitnmdDyBoJz55YlrWV5KkhIMCoVCoVjkKNEwCUIIHOBU1KbEL6hdzClLjot94gT+BZyO\n4mtpoeyLX2DokUcAKLn99mz6zOii3Ybz1nPdGW3c1J98DvxcrNDPhUCY7yJqxeS4luVFGNTEZ4VC\noVAsAYSUS38JzDCMNUDrv3/3X2hsaJzs8AmRrqQyrFO1SFOWpJRo4RC+lSvn25QJyS14nmx7IalG\nHX1DI7oZAfz5r2wp2OEuRnrTdFgodihG4loWzvE2NYtBoVAoFiO2jd/YqH6Bj2Jxer7ziEjPdoim\nXGpCOiX+xTXRVQiBjCewu7rwNc5MQBWT8Ypz820f7TCPJzgyx850hX6+pzjnosTCwsNNJnFOtivB\noFAoFIolhRIN00AIgSvhdMzGpzvUhRdZvYMQyMFBHJ8PvbZ2vq2ZVfJ1WBrNTAqTVQGyYiLcwUGc\nrm41h0GhUCgUSw71l20GCM0bDHcqZtEVtbAcd75NmjqajtvXhzswMN+WzBp2W9uYDkuZqMNoMjMe\n5oKOvqFsGpFi6WJ3deF0dY0QDB0Ri46INY9WKRQKhUIxO6hIwywghCDpStojFuUBnZrFMlVaaDjd\n3aD70MpK59uaRUFzdQnbm4O8eCyCCAQmTW+6b9dRnjrQCcDNm5vmNZVJURyk62KfbIdUCrThdMUf\nHOhlZ1sUgO0tZdyzuWa+TFQoFAqFYsaoSMMsommCmO1yImIxZDnzbc7U0HSczk7ceHy+LZkxvpYW\nwjt2ZF+Hd+yY9cFlke/9HR/7hz/hK8/+I1+N75tQBHT0DfHg3rZspCHzXLF0cJNJ7NZWsKwRNQwd\nESsrGAB2tkVVxEGhUCgUixoVaSgS3TGbsN+lfjG0aNU0nI5OWHUWWiAw39bMiPLf+a+E01OhZ1sw\n5KY/rUgNwlOPYX9yfGHSNZAgkhh2FCMJi66BhKp/WCKo+gWFQqFQLCfUX7sioWmCZHqqdCS5OKIO\nzokTuLY932bMGF9Ly6wLhunQWBmiPOTPvi4P+WmsDM2jRYrZwhMMXeMKhuZyP9tbyrKvt7eU0Vzu\nz3usQqFQKBSLARVpKDJCCHoTNtGUS12Jjl9fyDpN4LS1IdasQajV0zFk0p9yuzNNJE6aq0v49NYW\nnk7XNPzS5iYVZZgmE7XRnWvcSCQtGCZut3zP5hpuWFMOoASDQqFQKBY9BQ13MwyjElgHuECraZqL\novXObA53mwlSSqpCOpULfTCcruFbvXreirln00FM7t4NQPDyy2d8rQyF2qcGsM2MqbTRnSvcSBSn\n6xQIJaoVCoViyaKGu+VlSt6rYRi3AH8IbAJOAhawyjCMg8Bfm6b5RPFMXDoIIehPOMRSkvqFHHVw\nXOwTJ/G3rJrzWxfiIE7mjPfceRfJ19Ki4YrLqfvhA7Ni40JY7V6ozHZEIF8b3fBtt87L98CNxnBO\ndU4aYVAoFAqFYikyqWgwDONeoAv4smma743adz7wa4Zh3GWa5t3FMXFpIYTAlpKOiEV1WKdigUYd\nZCqF3d6Ob+XKObtnIQ7iRFOZk7t3k3rvPZIvvQyuNzsj+dLLJHfvntWIw1RYSNOji81CigjMNm5M\nCQaFQqFQLG+mstT9x6Zp/uFowQBgmua7pmn+N+CPZt+0pY3QBH0Jh86IheNOPUVsrhBCIOMJ7FNd\nkx88x+SbypyJOvTceRdn7v48g9/8X1nBAIDrknpvzD/hebNzqVHIYL1CmIs2upPhxuM4nZ0qJUmh\nUCgUy5qpLHPfaBiGBASQ+Ur6OaZpft80zRNFsm9JI4TAkpKTgykqwzpVCy3qIAQyEsEG9MaGotc4\nFFpoPJrk7t2k9r7uvRhdyK1pBM47b7ZMVcwhxWyjOxluPI7T3q4Eg0KhUCiWPVPxUi/DEwjnAuuB\nRwAH+BhwEPh+0axbJghNMJBwiCZdasM+wv4F5KBoGm40ioxF0RtXFH1ydK6DCN4K9mhHsbm6hOvO\nbRyR9tNcXUIy5xih60hNA10HTRC8/PI5T00az86lyEwF31SuP9c4fX24PT0qJUmhUCgUCgronmQY\nxi7gNtM0+9KvK4AnTNO8soj2zQoLpXvSVJBSEtI16kp86NoCK9x3HURJCfqKFQi9uI7UVPLj8xVC\n99x5VzbaENh6GeW/+zvA7HZPKpTl1D1pIbVGnS5SSpxTp5DRqBIMCoVCsRxR3ZPyUkg+TCMwmPM6\nAdTPrjkKIQRJ10tZqgjqVIcXUMqSpiMTSezWVrSaGvSamqLcZqoF0fmc8LofPlCUNqszYTmIhQyL\nWSwAuJaF096OtB2EEgwKhUKhUGQpxCP9OfCcYRgP4hVQfxb4UVGsUiA0wWDKIWq51IZ1SvwLyIER\nGm5vH+7gIHpTE1owON8WjaDYYmGi1fSlsNK+XHGjMW8GA2LeZpQoFAqFQrFQKUQ0/AHwSeBavBqH\nvzBN8+fFMErhIYRAAqdjNgF9gU2UFgIcF6ftBLKhHr2yctYuncmPj/3kJwCU/sqvLBgnfKK0qaXc\ncnQpI6XEOXMG2den0pFG0RGxADXRWqFQKBRTa7kKgGmaEggBEeCrQHFyUxRjEJrXZak9YnFmyKaQ\nKd5FR9Nwu7uxO0/Nql3J117D6ejA6egg+dprs3bdmZBJm5KpFDKVGtFWdLZajnb0DS3ZtqwLDWnb\n2F1d2B8exe0fUIJhFD840Muf7urkT3d18oMDvfNtjkKhUCjmmSmLBsMw/hLYAdwB+IEvGobx7WIZ\nphiLpglitsuJwRSDSXu+zRlG03FjMezjx3Eta8aXy7ROFUJDCI3U3tezdQrzjdPdjXO8zXt0d8/q\nte/bdZSv/mQfX/3JPu7bdXRWr60Yxo1GsU62Yx89iozGQKh0pNF0RCx2tkWzr3e2RbNRB4VCoVAs\nTwrJdbkZuAdIpDso3QTcUhSrFBMjvMFw7YMp4pY7+fFzgMikKx0/jhuJTOsa+VbZu0pr6SqtnQ0T\nZwmR9/lMh5Atp0Fw84F0XeyeHqzWVpzOU5BMgr6AmgwoFAqFQrHAKeSvpjPqdTDPNsUcIYTAAbqH\nLEI+jbrwAmnRKjScri7coSF8jVNvb3vfrqMj5hl8bOtl/ChWxe5VFyJKS7gp1cAXimVzAegN9cgq\nr35DBAIj9k00hGw5tV3NZb7ftzs0hNvXjxyKDacfjR78pxhDc7mf7S1l2WjD9pYyVdegUCgUy5xC\nRMNPgf8AagzD+G94UQfVPWmeEUKQdCQnIynK/TrVYX3+Uy2EhhuJYiUS6M3NaP6JnY18q+wX/Pn3\neOOht/ABoqyUFz7o4qbNK+bV6Z7KALN80YXRgugL15w95pilOAhuKu+7GEgpcXt7vYiXZXliQdUr\nFMw9m2u4YU05oAqhFQqFQlGAaDBN81uGYXwUaANWAX9qmuYvimaZoiCEEEQsh6jtUhvSKQ3Mr5Mk\nhADbwTl+HBob0crLC79GkadPT4eJogkwtuVqPkE0nvj5wjVnc9PmFcDIlfnF2Ma1kPc9W0gpcXp6\nkAMDyEzbVCUWZoQSCwqFQqHIUFBSr2maTwJPFskWxQzJRBh64jYDSZf6hdCiVWg4p07hxobQGxvy\nRkHyrbJftKZmwa68j+e8T6XlqkylsDs6oHp93mtk3mNGKMQffWzENSN3/z8jjlN4uNEYzulupON6\nBfTzbZBCoVAoFEuMSUWDYRgvTLBbmqZ5/Szao5gFhBDY6RatFYEFkLKk6bjRKDIR99KVRtUCQP5V\n9vFW3hci402xbm5pyYofp7uby1vfJPT4G0QmmOOQER9uNIo7GMHX3ATA99/uZi+vIwKBOU33mQ5z\nlW4lXRfn1ClkzKtZmPfUPIVCoVAolihTiTR8I+f5AhoQoJgMTfNSlmL2/E+VHu6u1Iasr0Ovqhpz\nTD6ncjJHczGk7nzhmrO5rtal/6vfYUVqEBgWFaPtzogPp7sbt78fkikcAadXG7xWsx7HcRG2uyBq\nPCaj2KLP6e/HPXMGUGlICoVCoVAUm0lFg2maLwIYhhHCm9NQiteqVQfWADuLZ55ipuROlQ76PPEw\nrylLmoZ7ugc3EkVvWoHmm37by3zpQPMlIjJF0q3PvgzA2huvGmFDc3mAUFowTIZMpZADgwihIXU9\nW9DbV15DLGoDNuWhxZFrPltiQUqJTCaR8bj3+SQSkLJUJySFQqFQKOaIQjy2h4EwsAHYBVwDPFoM\noxSzj9AEKVfSEbWoDOpUheaxR72mQSqFc+wYsi5/1GEy8qUDuf39JF99FRi/pqCYPLxlB8+zGYDr\nt6wa0SJ2Kp2XMseFrr2W2H3fB0Crq0OrqqTi97+C9lYKEkt7wJa0bU8cJJPe81TK64Bk216cU8+J\nKCjBoFAoFArFnFGI52gA64HvAv8G/D7wz8UwSlE8hBAMJB2ilkttyEfYP4+Ol8hEHSLoK1ZM2pp1\nImQqReLFF7Ovx0v/KRaZbkGZ2Q350ocm67yUofJrfwJA4sUXEYEA4R07cC66kNrD+6gIe5+R37dw\nHGbpushEwntI6RUhaxpoGkLXQdcRuu6JAMsCx0G6LjjO8HPb9sSB6yI1HTFaEKj0I4VCoVAo5pVC\nREOXaZrSMIyDwAWmad5nGMaKYhmmKB5CCFzpDYYL+zTqSnxo81VAqmmQsnCOH0fW1KDX1EzptNEr\n96Frr2XokUeQA14KkKisKJrJM2GqIqbya39C6Rc+nz2nHCYtLJZSgmXhxuOec25ZSMsGO53Go/sQ\nmvBW630+zzHPOOdS5v+aBwmQSnnXtixwbK/FaToKkHumdF3vWlKCGD4mL+l5CqqUWaFQKBSKhUch\nouE9wzC+B/wj8IBhGM14U6EVixQhBAlHcnIgRVVYpyI4jylLQsPt7cMdHESvrZ3SXIfclXuAoUdy\ns+Xm1vUsRregjMCQrouMx7nrvEqua9TBdWkq92O1tYHrph8SpAsSpKaN7SLkuOCkRjr0M7IuB903\n7qc9JmKwjHE6OwDQm5rn2RKFQqFQKAqnEC/xS8BHTNN83zCMPwN+E7izKFYp5hZN0JdwiCRd6kp8\nBOcr9SXTYelUF05vL3ptHdokA94yjrXd1obeUI+sqvQulaet62TMtIh6NroFuckkcmjIK/ZNWZBK\neSv5QkNoGk2Zn9hkauSJQoDwVvEX60p9R8Sr18g3UGyxO9yx++8nudPrGRHcvp3Su++eZ4sUCoVC\noSiMQkTDl4FfBS4C9uHVN1wJvFsEuxRzjBACBzgVtSnxC2rnIWVphNNoOzidHTjBIHpdHVrJWCf8\n7WO9AFy0pmbKhcbjMZXBbBkmEhdTEQtSSi+XP5XyugElk146USo1ttgXJlzJXyr84EAvO9uiAGxv\nKeOezcNpaovd4XY6O7L2AyR37iR0w/WLVgApFAqFYnlSiGj4LWArgGmaxwzDuAjYiyqGXlIIDeKO\n5MRgiurQ3KUs5XUaNR0sG6e9HSccRq+qQisrA+D3vv8G+9r6ANjSUs13Pn/plAuNRzPeYLZ815iq\nuJBS4kYiyGgM6TjgekW/2XQiKb3owYhuQMuz2LcjYmW/9wA726LcsKac5nK/crgVCoVCoVggFJKH\n4gNycyJSgDu75igWCkJ4KUvtkRRJu7jf5ozTKIeGkEND7GyLZqMOgOdMJ1M4naewjh7ljXdas4IB\nYF9bXzbq4GtpKVrHpHziIhN1AJCOg9Pbi3XyJPaRIzjdp5HxuBdBsB0viiC8gmR8/omLghVLBr2p\nmeD27dnXwe3blehRKBQKxaKjkGXkR4DnDcP4MV7a9CeBx4pilWJBIITAkV7KUtgvitplyTlxwnOw\nAREOA00j9g+nLmnIWAzpShAgvP/NiJmkNrnxOHZ3tzdsLJHwBAHMWxegieoCFirN5X62t5SNiDRl\n7M843LnpSYvR4S69+25CN1wPLN66DIVCoVAsb6YsGkzT/EPDMH4Zb6ibBXzHNM1HimaZYsEgNEg4\nkhMDKW8wXHh2U5bqj77HNvM1drdcCMA28zXqj5bCFu91burSRY1h7jCquKAhzP7uOBLJBQ1hzvfF\nsXt60MJhREnJ2O5BkzCV1CZ91SqCN95I/PEnAEnoqqsQmo6MpFNr9HnsPsXEdQELnXs213DDGq9j\n1mjBs1Qc7sVsu0KhUCgUBXk5pmn+FPhpkWxRLHCEJhhIOUQsl5qQTmlg9tJrPvnu01x57E0AGgdP\n4/RciB9459QQz7RGCOiCM3Gbn5kD7O0Y4sa15Xx+czUAF64ogfQUYbuvHyFdCAS8Dkrpr1o4jJhk\neFy2xamUXnFyet6BTFnerAPbpuTWWwlu2wosLCdworqAqZwL8x+dmOj+C+mzVigUCoViOTJl0WAY\nxja8bkl/D/wcuBj4kmmaDxbJNsUCRAiBBE4P2QwkXWrD+oxbtPq3XIj/gs1wtMObDOz30/qzJ3m6\n3c9bVWvoiFiU+AVD1vBkgXxO8Qjn13GR8QTEE7hS4rqO15bU76djSCJ0jeYyn9fJKDPjwHG8567r\nTTb2jfrxEBoIz4F1OjtwOjsWvTM7k+jEYm+DqlAoFAqFYuoUEmn4LvA/gE8BcTzR8DCgRMMyRNME\ntpScilkENI2qkE7YP33x8Isv/jEvvNuB23OGcidBb6CcLqeK8rhFeUBjMOk5/RUBDb8+NvVowfsC\ndAAAIABJREFUtPN7Z10C8BxaIUQ2degH7/RM7CQLb2LyRMlNk7UAnY+V+4nqAsZjJtGJxd4GVaFQ\nKBQKRWEUIho00zR3GobxAPCQaZpthmGo9i/LHCEElpR0xSwCuqAqpFPiL+yfRcZ5FaEwts/PB2X1\n1CYGAYhYkpUVOhVBnfPqQhzqSwIjneLRzu8Lbx/n0r0P0JgcGOHQzsRJzjBZC9DprNzPlsiYqC5g\nNlFtUBUKhUKhWH4UIhqGDMP4feAG4HcMw/g9IFIcsxSLDS/yAKdjNn7dmZZ4ABChEAA+6VKmu0TT\nBc03ri3nns01kzrYMmXhRoaFQbEcWml5duTWSUxHlGRERsqRbGsu4cuX1s/IrkLEwnSiEwqFQqFQ\nKJYnk+aTGIYRSj+9CygFPmmaZi9eT8w708eEi2ahYlEhcsRDRyRF3Jp8xkNzuZ8reo/gdHSgD8U4\nTw4QamqkrraCO4xK/uK65uyKfXO5f4xjm3F+M3ykxwTgvfKz6ApWjnvcdJxkvakZUVGB096B096B\nqKgYV5DIlIV7umvM9o6IlX3sbItyJm7TEbH4mTnA379xuiB7pkrmfqO5Z3MN37ymiW9e0zRuVGT0\nuWrugEKhUCgUy4+pRBoeMAzjSeA/TNP8RmajaZr/0zCMCsMwvgzcBNxeLCMVi4+MeOiKWQR1jZoJ\nCqadzg42vv0SdYFSNkZP0ZgcYOiPvk5PSQ0NpWNFQj5yU3OeiJ7N/2y+mJgvRJku+VRPiHuaxh43\nnVV1p7MDOTiIvtJzkuXgYLYgOnfl3j1zhm0fvk740VeJ3XhjNkVqdPvYlCOJJIeF1d6OIe6IWCNs\nm2nB8WQpU1OJhIw+d6m0QZ2IhdJVSqFQKBSKhcBURMOvAL8NvG4YxgBwErCB1UAd8B3g00WzULGo\n0TSv5uFUzCKsa1SHdfz6SPHwB2/G2b/5lwE4d+AE33jvQZ4/ZbOrrweYem1Ac7nfW72vXEdMeMPL\no0LwbGtkRJrQbDiB47VvvWdzDdeVDtH/p39HQ+dxHGDo4YcJ3XA9XWX1I9KX3u6Kc15dMOuclucp\n8p5pwfFMW7FOdO5cioW57tS0mGdeKBQKhUJRDCYVDaZpOsDfGYbx98AWYAPgAB8C+03TlBOdv5D4\np7d6uHBtCKM2yNnVQQJ5uvAoioMQgoQraY9YlPg0KkNe5OGdU0PsH5Cga0jH5f3KVey++g529Q0L\ni+kULFOkydVTmVDcGOkh0N7qtXAFZF8/bnc3lI2tV7hncy1lAZ29HUP4dTEiZWqxFBwXe0U+dv/9\nJJ59FoBQTtSmWMxGwbxCoVAoFEuNQiZCS+Cd9GNR8kFPkkOJfgB8GpxdFcSoDXJObYgNNUFKAzOb\nN6CYHE3zxEM83ao1U/NgCx1X9wqn966+CKJj8++nQnO5n5vWlvOw2U8k6VIe0Lhx7ew6fNNNzWku\n93NNtcvOLgcR8GcFwpcvreeOWXK8Rzvw023FOtVzi70i73R2MPTww9mp25mozUITTgqFQqFQLHUK\nmgi92PFrgkz2uO3Cod4kh3qT/PzwIAI4q8KPURvEqA1h1ASpLVlWH8+ckmnV2lzhZ02lH7PXSycq\n8WucjFpc1Bjm7a44UHjBcqZuoTtmZWsiZju9ZaLraA0NiOpq5OAAAKKiEq2hgdj99/PxnTu5LFhJ\nYNs21n3sl7Pn5Ht/U4lq5DKeA19IHUe+a4x37lysyLvd3VnBACAjUdzu7qKKBtVVSqFQKBRzgWEY\n1wI/BMz0pirgfmBz+hHBa0L0z6Zp/l/DML4INJqm+Zc51/jANM1z58LeZeUVf+uGJob81Rw8k8Ds\n8QRDLL3SLYETgxYnBi2ebfWchdqwnhURG2uCnFXhRytS2styRQjBly6u51uvngIBZQENKSV3GFXc\nYVQB+R3dyVJicrssFWMQ2TunhgC4cEXJmH16UzMln7xjREoNkLWhMTkAu57GufHKSZ3fqUY1JnPg\nZ6OGYT7QGhoQ5eXIiNfdWZSXozU0FP2+czXzQqFQKBQLj0jKYcfXn9J2f+PmyVtAzgwJPGKa5n8B\nMAzDD7wLvA38tmmae9Pb3kvPSZvXkoBlJRp8QrChJsiGmiCf2ACu9HLszTNJzDMJzDNJzsSd7PFn\n4g6vnhzi1ZOeg1ji19hYE/QetUHWVQcI6CqlaaY0lPnYvrqc1ztjuNLrKuTToDKYv+NSISkxxagL\n+O/PtLO/24uCXNAQ5ts3rRxzzGhnPxPpGI+JRNBCTcWZ6or8TGoe8gmwufo8lFhQKBSK5UUk6dCf\ndLBSDnhjCYotGgByV6Or06+tnO1hoN80zbhhGHNgzvgUJBoMw/gE3hv6Ed6chirTNPcXw7C5QBOC\nVRUBVlUEuHGtt6rYM2RnRcSh3iQnB62srBuyXN7pivNOOm1GF7CmKsDGmuFoRGVIDcmeDrcZlVyx\nshTwRETCkQxFvSnTlUGd0oCO09lBZ9xlZ9vwz/Bcr4a/c2ooKxgA9nfHeefUUN6Ig1bfgIxGcTo6\nkPE4PuMcUm+9Ca6Lb+NGUntfR9o2b5yM0HomjuY6rCvXuaAuAEIgNA10HTR9+LnPhwgFEaEQIlyC\nCIcQoRANoRC/VGHzXK/A8fmnlVIznbScyVbkZ6PmYTm0d1UoFArF/DGQtBlMurhSIoRgDnNKBHCr\nYRjn4vnVp4HfAL4I/INhGIN4DYh+nHP8bxqG8dGcawTmythCIw06nuG3mab5oGEYlwOLVjTko67E\nR12JjytXeQ5sLOVwuDfFoV4vEvFhXwrL9WSEI+HDvhQf9qV44kMvfaKx1MfGdDRjY22QleUqpWmq\nNJSN/OeYmTLdE7dp/4+HCb/6IlFfGHfrXWi1tVO6ZqF1AZPiOFTH+qiJ9lET8x4VnRaDqSjuwADu\n4ABW3wAMDCBi0XEvk+roJPWiZ9M56UeGoWmadm36IUMh9MpKeisqEJUVaBWVaLW1aHW16HV1aPX1\naHV16HV12QncGaaTljPecbOZ7qTEgkKhUChmEyklAymHwaSLzIiFuffXJPCYaZq/bRjGRuBRoDW9\nL5Oe5AMeT/vcEq++4a8yFzAM44O5MrZQ0XAp8CReYQZAbKYGGIahAf8AXAAkgV83TfPDnP2fAL6G\nNxvi30zT/L8zvWchlAZ0LlwR5sIV3tBr25W09qc4lI5EHDqTZDA1vPLdFbPpitm8dML7aEp8gvVp\nAbGxJsS66gChcYacKfIjT58m+cbrJPxl6NLhkta3eKv82hEdiCai0JVqd3AQ52Q7Tkd7evJz+nnn\nKZrPnOHv3bHRykTO8/mWiCKRwE0kcLvGTqMec2xFBXpzE3pTM/rKZvTmZuqava+ytMGLcCxT1HA3\nhUKhWHpYjstAwvFqWgXzJRYyZG9smuYhwzC+CdwHHMvsM03TNgyjC2/hfsQ5c02houFxvJarBw3D\naAFWAf85QxtuBwKmaX7EMIxtwN+mt2UKQr6NJ1aGgFcMw3jMNM3uGd5z2vi04bqIj+Ep1a6Yl9Lk\niYgEHVE7e/yQLdnfnWB/dwIYQBPQUhHI1kVsqAlSG9bn8x/sokEIiSs0rj5jcqVxE9XNjayuCgKT\nO3ijxYKUEtnXh916DPtYK3brMZxjrdjHjiMHB6dlnywr54y/lFiolJjwEQuUcH60g1JpE9pxC3pj\nIyIcRpSUeF+DQfD5+M+jUfZ2JXF0ncvOKueOc70UHuk44LrevAfH8V7bDjIRRyYSyHjCex5Pv45E\ncQcHcQcHkAODuIODyMFB7P4BNNfJb/PgIPbgIPZBc+zOYBBfSwv6mjX41qzGt2Yt+po16M1NCH3i\nNLzM92OxdiFSw90UCoViaRFLOUSSLgnHRdMEQlsQfpckp7jZNM0fpTskfRa4ID1UWQAHTNN8xTCM\n9Ywthp6z4uiCRINpmq8ahnED8Ek8I/9yklOmwpV40QtM09xjGMalOfvOBY6YpjkAYBjGy8A1wIOz\ncN9ZQQjBijI/K8r8bF9dBnhV94fTUYjDvSNTmlwJxwZSHBtI8XSrF7CpDuleOlNNkPU1QdZUBsZM\nBl7OaA0NBC7bSur1vQAEL9tK+KwVSBe6YxZPfDiYjezkc/Ck6+K0d2AfMrHNQ1imiX30KHJgYOo2\n1NejNzWhNTZ6KT4N9Wh19ej19Wj1dWjV1XTGJd/e1YlMWTgdXuHz2R88SnlygPDHP4be1Iy1zxtz\n4t9yYfbatxuwdRqr2lNZCe+IWHx9Zzsl8SgVkT4qon3c3eRSHunD7TmN29WN09GBc+pUdhhdlmQS\n+/Bh7MOHSeZuDwTwnX02vo0b8W/cgG/jRnxr13oiiLEO9zevaSr4vc0nC7GLlEKhUCgKJ2W7xCyX\nqDVcr6AtDLEAgGmaO4Gdo7bdPMHx9+XZtqkIpuWl0ELoTwFvmqb5vbR4uAF4bIY2VAC5S7uOYRia\naZpuel+uZxcBKmd4v6JTHtC5eEUJF6eLY21Xcqw/5QmJXk9I9CWGHbS+hMPejiH2dnjZ7H4N1lYF\nsxGN9TUBqkPLqtHVGCI37CBVs4IG3SbwkY8AIDRoG7B4pjWCLrzC9J1tUW6oSFHTamK9954nFA4d\nRsYmz6TTamrQ1671VtdXNqM3r0Q/ayV6U1PWIZ6I5vLhlXWtvIzLW9+kMTmQraPo+8pXsPYfAMB/\nwWaq//Zvc84tzCEtZCVcCo1YSQWxkgo6G1cjr2mibNT9pG3jnj7tCYh2Ly3LbmvDOXbME0AyZyEj\nlcI+eBD74MHhtCxdx7d2Lam164nqK6lfuYGe2iblcCsUCoVizpBSErNchiyXhCNxXZkVCSqjY+YU\n6olWAn9lGMZq4BCesz9T0TAIlOe8zggG8ARD7r5yoG+iixmG8WfA12do06zi07y6hvU1QW7B+0fd\nE3c40pvM1kW0DaZIByOwcgbPZagL62kB4QmJ1ZUBfAtILReTR80Bdr/1ITJhc2HnB+zYuYuKP/qf\n3k7XYeXpNtZ0HGZN+2HWdBzBN3CaiRKMRFkZvg3r8a1di2+tl3LjW7sWraJixrYOFxI30RhtBHZk\nIwwZwQBg7T+Ate+dERGHqVLISvhUOyIJnw+9qQm9qQkuuWTEPplMegKi9Rj28WPYHx7FPnwY9/Tp\n4YMcB/vIEbQjR/hUetNQqJS25vWIjotIXbwF/3mbxhReL0TUcDeFQqFYHKRsl7jj4riQsF1SjkSI\nYYGwkKIKS4FC05P+Dfg3gHR7qMtnwYZXgE8AP83TjekgsMEwjGq8outrgL+exMY/A/4sd5thGGsY\nrkafd4QQ1Jf4qC/xccVZXpemhO1ytC/F4b4kh88kOdyXJJpTYN0Td+hpH+K19kw0QnB2dYD11elo\nRHWA6vDSi0Z0R232Hj2DTHhr2u+sOIcrXnuTyv/zT/i6Oll1YB9fmSCKIMrL02k0G/EZG/EZBnpz\nc1FXHLIOZnmeoutMEfUcFhjPdFCZCAbxb9iAf8OGEdvdvj6sw4exDx3CPnQIyzyE29mZ3V+SiHHO\n0X1wdB/9PwB8PvybNuG/+GICF1+Ef9MmRGDOOsUVhBruplAoFAuLTKqR7UpSrsRyJBLQc4SBEgnF\npdD0pK/h9YO93zTNDwzDOG8WbPgZcJNhGK+kX/+qYRifA8pM0/w/hmH8d+ApvCEb/2qaZud4F1rM\nhHwam+pDbKr3VmKllJyK2RxOpzMd6U1yImdmhOXK9DyJ4WhEbVj3IhHVS6s2onrwDOtb32Bjdysb\nTrdSnozBo4fzHuu2rMHddB7uuZtwjE34z1pJKOijLDi/8zP8Wy6EYAAG043HKsqnFWWA6a2EF8Px\n1aqrCW7dSnDr1uw2t68P69336HtrP+Lg+4jDJqRS3k7bxtq/H2v/fobuvRcCAfwXbCZw8cUELtuK\nb8P6BdWtSYkFhUKhmD9cKYmlXOKWS8IdmWoESiDMB0LKqRddG4bxa0An8DmgBdhlmubXimTbrJGJ\nNPz7d/+FxobG+TZn2sQtlw/7MyIixZHeJFFr/GGFmeFz69MiYn11gPoS38LP67NttPffQ3tjD9ob\ne9Hajuc9TOo60jgHd/MW3HPPwz3nXCgrH3tcuvip3K9RGdLnZW6Gte8d+n7/f4yINFT/zV9NWzjA\n4mgJKi0L+/ARrAP7Sb39Nta+/ePWl2g1NQS2bSWwbRuByy5DKx/7vVQoFArF0iVhu8RSXocja1Sq\n0VzipGw+/3i7f/c3brYnP3r5UGg+y0tAk2ma9xTDGMXEhP0a59eHOb/emxmRG404ko5I5EYjcofP\nPXXUW+GuCGqeiKgOsq4mwNlVQUr8C2B1d6Affc9uTyS8/SYiPnbEmRQCt3klctsVuBdciHveZgiH\nJ7xsd7r9bUOZj4jlMph0KE2LB78+D+97FlfSF7JYyCD8fvybzsW/6VxKPvMZpG1jHzrsCYi33iJ1\n4ACkU8/c3l4STzxJ4oknQdfxb9pE4IorCF5zNb6Wlnl+JwqFQqGYbUZEExwXRw6nG6lIwsJj0kiD\nYRg7gV14guFV0zSj6e07gJOmaS74idBLJdIwFRK2mxYKnpA40pdkIDl+NEIAK8v9rKsOsL4myLrq\nIGeV+0fkCBaN093ou19Fe/VltPcOIPIMTZPVNTiXXIZ76WW4F1wEBRQrP2oO8Hqnt6p9WVMptxnD\njbdcVxLSNSpCGiX+2U1dGi8CMFH3pKlcYzFEFgpFWhbWu++S2r2b5O49OK35S4/01asJXnM1wauv\nxmcYCz9aplAoFIoxSCkZslySjiRhuyRtiaYtvM5GCzXSYBjG3wCXACuAEuAo0G2a5mfm4v5TEQ3/\nL/AusB24AggBb+AVMG8wTfPPi23kTFlOomE0Ukp6hhyO5IiIYwMp7PF1BEFdZNOa1lUHWFc9ewPo\nREc72qsvob/6Ctqhg2Pt1TSkcQ7OpVtxL9mKPHvdtFbnu6M2331j5AzA3720gYaykcE115X4dEFZ\nQKMyMPP3OFkr1HxzGqZyjeUybMzp6ia1ZzfJPXuw3ngTGY+POUZrbCR41VUEr78O/3nnLag6CIVC\noVAM42ZEgu0JhZQjQTAvacKFMJuioX3lKm1l+4kJvK7CMQzjC4BhmuZXZ/O6kzFpepJpmv87/fRZ\nAMMwAsBWPAHxQfFMU8wGQgjqS33Ulw53arIcSdtgKisiPuxL0RUb/rlIOmOLrKuCOmenBcS6ai+t\nqTQwRWftTA/6SzvRd76Adnjs5GEZCOBedAnOR67CvXQbVOYfxWEf9P65+c45d0q3tdKjMCYKJGia\nwJUwkHAYSDiU+XUqgtq0Upem0go1VyyMF00YfY3N9aFlM2xMb2wgfOuthG+9FZlKkXrzLZIv7SL5\n8ivI/n4A3K4u4g89RPyhh9AaGwldfx3BG27At2HDglutUigUiuWG5bhEUy7xZd4CtX3lKh34JnBj\n+8pV3cAfrGw/MXa1dPoIAMMw7gVqgFq8DqOfMU3zc+l9p0zTXGEYxirgn4EwEAd+0zTNk4XesOAe\nnaZppoCXDcPw40UgFIsMvy7Szn+QzNjBSNLhw75UWkQkOdqXGlFk3Z90eOtUnLdODa/8NpX5siJi\nXXWQloqcbk3RCPorL6HtfAHtwD7EqIiWDJfgbt2Gc8VVuJdcNmltwuBffAvbPASAz9g4PKdhHF5r\njxGzHKIplzK/xk1nV4yJMuSS+YUWs10iKYegrlER1CgNFKfr0nKJHMwEEQgQvOJygldcjvyKg/Xu\nuyRfeonkrpdwT50CPAEx9KP/YOhH/4He0kLw+usJ3XQjvlWr5tl6hUKhWD4MWQ5DKZe4I3Fyuhwt\nJ5GQh9sg62Y1AX8K3FmE+0jgOdM0v2MYxvY8+wD+BviuaZpPpoczfwu4u9AbFdpy9QEgilfjsBv4\nZeAfCr2pYuFRHtS5cEWYC1cMF1l3xWyvNiJdI3F8VFpTZ9SmM2rz8gmvbkAXsNpnsb7rQza8v4cN\np47QPHAqKxhkKIR7+ZU411yLe9HF4J+8R3931MY5eoSgeQikd3PbPIR98INxIw7dUZvXO2NUhXRK\n02GGK1aW5j02X/RC0wSWlPTEbc4kHMp8XuF0bp2H09nhveem4VkMU22F2hHxplgDBHQxInKQ7xoX\nrihZ9sPGhK4T2LKFwJYtlH35y9iHDpF49jmSzz+fHTLntLUxdO+9DN17L77zziN8y0cJXn89WlnZ\ntO6ZiQRlWG6fuUKhUExEwnaJJh1iacdgOUYTJqF6ktezSSaNY/SHn3m9GfiqYRh/mN6Wms5NCo00\nPAvsAa4C/hI4MZ2bKhY+QghWlPlZUebnyvSire1Kjg943ZiO9nmpTZ3R4bQmR8JRy8/RmnN4+qpz\nAAhZCc5O9nF2XZi1RgtnN5RNue1rppBZxgNsXvcRfumDF70dBaQOTZSaNFn0ImNj1HYZHHQI+zTK\nAhr85Eckd+4EILh9O6V3D4v1qQwF+5nZn3VIy4MataOG8uW7xlwNG5tKsfV8F2QLIfAbBn7DoOy3\nv4S1/wDJ554l8eJO5MAAAPZ77xF57z0i3/s7gtdcQ/iWj+K/+GKEpk3J/kwk6MyQDQJqwz4VEVIo\nFMuelO0SSbkM2W42oqDSQsflaeAuINPB5cFZvPboDz0TUYjjRTUwDGM1XtoSeOUEf2Oa5muGYZwP\nbJvOTQsVDRWmab4PvA/8i2EYn5zOTRWLE582nNZEwoe+63USu1+gtTfOkbq1HGlYy+H6NfSWDjtW\nCX+I9/1NvJ8A9g0Cg5QFNM6u8uoi1lYHWFc1dpp1Jlrg3djHO2edx8Vt+6iL9UEggFZTO66dDWU+\nLmsqHdE5aXRqkn3wg6xggMmjF5omSLqSoeMdRPbsJ+wvpcxOwM6dhG64fkzEYTw6IhZvd8UpD2hE\nUi6RpMuNa8Jjzsl3jWI76VNJmVpoaVVC0whcuIXAhVso+73fI/X6GySeeorkyy97Q+WSSZLPPEPy\nmWfQGho4dOl1PLj6IwxW1Ixrf6auxHIkkfRU9vKAXNK1JAqFYvkhpcSR4LgSy5U4UuJKkNIrYPa+\ngov3PHOsSj2aGivbT5xoX7nqLuByoHNl+4nds3h5ybBQIOf5G0C/YRi78YTC0fT23wf+0TCMEF5d\nw+9O56aFioaDhmE8BTwKvAecDzw8nRsrFiei7Tj6E79Af+5pxNAQfuAC4IKOg8jaOpwbbqJny00c\nCdVytC/J0f4UR/tSxHLqI6Ipl/3dCfZ3J7LbqkM6a6sCnpioDlI+enaE34/eUIeWCCLCoUntvM2o\nzKYkjemY1N2N29s3vfcvBEJAwhcg7guguRIn6VLtSnzpX6ATrWS7p7uQKYvaEj8VQe9n/A6jalq2\nzCZTKeKeyjHzifD5sjUQbiRC4rnnSDz+BPZBr+7M7e5m/eM/5g/ETzm4/iL2Xng9HS030VwZnGfL\nFQqFoni4UpKwXJKuxHYkqfRXiScQvG5GU2t7qoRCYaxsP9EJ/Gy2r2ua5n05z38157kD3J7n+Fbg\nozO973TSkw4Bnwc+Bfz7TA1QLAIsC+21V/A9/nO0d0eO5ZA+P+4VH8G58WbcCy8GXacKuBS4tKnE\nO0ZKuodsjqZrI472pzjWnyLpDIvkvoRD36hC6xK/98spqAs2lWmU+AQiHCJw2Va0hoYJTc4d6pZL\n/NHHSL2+FwBRU41MiwefsdGLMkgJjusF/jQNdB103WvrqWvoa9cSvPIqEq+9BkDg6o+QXGdw0nYI\n4vKLA6fZ3TaAALavKuGeTZVIBGgasQceIPzcc2xd/RH2rLsMf23tsqhPmI90Jq28nJLbb6fk9tux\nW1tJPPEksSefRPT3o0uX8w6/yXmH30S+dD+x228lvGMHWlVV1s5MDUl5QAPh1Z4sh++VQqFY3Egp\nSTgucUtipQWC445tcyo0MSa/RaGYjEnnNORiGMYe4Od4XZMipmk+VyzDZpPlPKdhRvT14nv85+hP\n/Ceif+TKvNvUjHPLx3FuvLmggWvZ86WkPWJxtC/F0X6vW1Pb4MTzIwAagoK1deFsVGJN5djWr+MN\ndXO7u4l897sjjg3v2IFWU41vw0YIBdFKStBKSj2hMMGqS8eR4wA0r1+d3dY9GOfbTxzElaDhrcj8\nxac3c1ZVCKu1ldOf/RwMDALQ1bSamm99i5Vrm8CywLa94KJeWLem2XTIC01Puqba5a61gRGpWdO5\n5lwhLYtnH3iC8mcf5+y2Ud2i/X5CN95A+NOfxr9hAwDvnPKmkjeUep+tEgwKhWKhYbveHISU481B\nsBbJHISFzkId7jbfFBRpME0zWzhhGEaZYRifMU3zx7NvlmI+EUc/xPfoQ2g7X0TYwx1kpKbhbrsC\nZ8cncLdcNK2haxk0IVhVEWBVRYDtq73uNrYrOTGYojWd0tTan+LEYIqcgATdSUl3+xB72oey2xpL\nfaypCrC2KkB1UGd3ezTb6ej1zhhXrBxb0wDeioxv3Xr0tavRKqvQfFP7cfjZGyfY82EvANv6Ne64\ndGR7z0z01nFdOgeT6D4fdJ4hGUsSSn9mK7pOUOt38J91VtYWmUoh43HvazIFyYSXUDqOkJhth3wq\nxdaZY+KPPEL1I08zwNhi8AwLLZ1J+P3c9MVb6fjULdgn2ih/9nESTz6JjEbBskg88SSJJ57Ef9GF\n7LnsozxUeS5S0+Zd7CgUCkUG25XELIekJb10I1eO6Oyn0ocUxaTQlqu/BwSAH5um2WYYxqxOuFPM\nI66L9vpu9Ed/hr7/nRG7ZHUNzkc/hn3zDqirK5oJPk2wtirI2qog16/xtqUcT0h4IiJJa3+KkxEL\nN0dIdMVsumL2CCHh07y0poAuMM8kCAfClDc0ELhsK8m9e0BohK7dTvDSSwqysXswzp4Pe7Kv93zY\nw5Ub62ioCNNQEWbburrs/svX17OiqgTbldi19fQ0tcBghIBjESoJUdWwInsdIQQiGITgyPx6N5HA\njcWQ8QQkk+DYoPuK5pBP5fzG6GkGdj2dfZ3MUwy+kGku98OmdbDpdyj7zd8g8fzzxB9F4csVAAAg\nAElEQVR6CPvwEQCst9/h4rffYXVVA69d8kvsTl6zoGo3FArF8sFyXGK2S8qSJFyJm1OIDIwQDApF\nsSm0piGGV4n9LcMwVgKLIj1JMQGpFPrzz6A//FO0jvYRu9x167Fv+yTu1deCf34cpkDOIDrwVsFT\njsvxAYvW/mEh0T5KSNhuZkVG8k9vn4G3oTass3bFFay5+yrW1pWywWgBPCEA0FAx8YC57sE4PZGJ\nWxvfcekqGiq8Qu0rN9Znt/uamim/43bizzyLC8ibbuRUWS3a6SgBXSPg0wn6NcIBHV9OS1ktFEIL\nDRd+S8vCjUYRbgSE8CIRSO/5AmOqcyvmExEKEd6xg9Att2Dt20/8pz8l8fLLCCmp7e/m48/dzw0v\nP4zWcRvunb+CVqMiDgqFojjk1iOkHEnScZFyZPRARRIU88mkNQ3ptqrteG1WVwKNpmnunAPbZg1V\n05CHoSH0J36B75GHEH292c1SCNxtV2Df9knk+RcsSGc0H0nbpW3QExLH+pMc7k1xKjZSSOQj7NcR\nAgI+jfPPquJzV6ymrjw4pp7BS0nyIghlQT/RpJe2tW1d3Yj0pP/1yLsc7PRmBZzTVMmf3H7+iOvY\n6aFwvjyr8pn2dz5dENQ1An6d0oBOYJxhE/ftOsoLH3SB67L97Eru2VKHTCa9VqPTqI8ohNj99487\nq2I08z3XoVCcjg7e/OcfsuKVZwilhjt8EQgQvuWjhD/7WXwrV86fgQqFYkmQW4+QcjyhIKbYxUhR\nXFRNQ36mIhqexevn2mmaZp9hGI3AtcBx0zRns+ds0VCiIYeBfnyPPYL+i0cRseH0FhkM4dx0M86t\ndyCbF6ZD5HZ3A0zaOSlDypGc6E9wLCY5Fhe09sRoOx3FmaRnRFnIx9q6UtbUl7G2vpSKsI8HXj02\n4hf55686m7rywIjoxPvtA/z5Y++OuNZXbz2fTSsr895nKhEOx3XRNY2gT8Pv0ygN+gj4tKwtHX1e\nSlZzdcmI89xkEhmL0X46grQtmoMCHBuppTtBzQLWPi+Nzb/lwlm53kKjo6sf8dQT+B99KDt1GgBN\nI3jdtZTceWe2aFqhUCjykVkMStgudrqTke1C0nFxXNB1JRAWIgtVNKT92f3AmzmbnzdN8//Lc+y9\nwI9M03xqtu4/lfSkR03TfN8wjPVAn2maXcCPDcO4zjCMN03TLCwpXDE/nOnB9+CP0Z9+ApFMZjfL\nsnKcT9yG/fHboTK/c7sQyG2VGrhsK+Hbbs17XFZY1NUR0DU2bjyLc0o8h9ru7ODM1/+JjlAVJ0I1\nHCpdwb769aTS/aozRBM2B04OcODkQHabwItGBP0aAZ9GLGmxvrF82u8nN3KxbV0dV270akVGCwg9\n7eAnbZek7TIQt0BKdF0joGkEdB2fLoinbAI+PZvfqgWD3Len3YtEANed28jnr1yPTCS8h2UhLRus\nFFgWUp/alO4MhUQaJmIhRyGaG6vg859Dfu7TJJ59lqEHfojT1gauS/K550k+9zyBK66g9ItfwH9u\n/qGACoVi+ZC0XeKO681CcGRaJJB/DoIQxQwGKxYQl3/9KW33N26ezRrg90zTvG4Kx40eADdjpiIa\nMkncpYZhvAP8b+BB0zRfMAzj+dk0RlEEMmLhyf9EWDmdkGpqsW//FM5HPwYlJRNcYP5xu7uzggEg\n9fpegldcPibiEH/0sXSRsyB01dWU/8avj7mWT7q0xHtpifdyZd8RXrzmUvZ2JbEcyVk1JdSUBTl2\nOkrr6RjxlJM9TzLsuAP89X8eRBNwVk0Ja9JRiTX1paxvLOfwqQgA5zZX5o0yZIqpLdv7WX5yfwcv\nmd5K9kWrq7nnqrXjfha6F7sGSTqk7dnjxiQu3h8mXROciSR4+kCnF1MR8Ox7nWw/p55VdWXopaUj\nrikdB3doyBMTySQkU2Bb4MvvyDudHVnBANMvhF5I7VgnQvj9hG+5hdDNN5N65RViD/wQ+/33AUi9\n9hqp114jcPnllH7xi/g3KfGgUCx18g1Ls9Jt/kbUHChhsKy5/OtP6cA3gRsv//pT3cAf7P7GzQdn\n+z6GYejAPwNnAU3AY6Zpfi29WxiGsRFvrpqF1xH+TtM0TxqG8RfAVYAOfNs0zQcnu9dUREMLgGma\n+wzD+L5pmvfm7Ds0xfekmGt6zwyLhdRw8a7b1Izz6c/gXH8j+APzaODs4nR1kXx9L+g+NJ9Oau8e\n7I/vGFE74GtqJrR9O4m0wxvavp1PXXceV+dJE3KlpHswwbHTMVpPRzl2OsaRrgiRhJ1zDLSdGaLt\nzBC7zOH0FV2AT9dwpWTvh2dYU19K/ag6ib5YiljSRkpw06tRCcvmqQOeLRMJh3xomiCTdCSllyvr\n/QdIkK6kazCBm07N0jXQhZYVGboWQAsH0Es1fBr4hURGIhCPI+JDILQxaU0yLULFJEXy+aIJC60d\n61QQmkbw6qsJXHUV1jvvEPvBD7De8CLEqd27Se3eTWDbNkp/9Yv4N22aZ2sVCsVMcdItTZPpqEHK\nkVjjDEtTBcqKPNwG3Jx+3gT8KXDnLFx3k2EYL+S8/mPgNdM0/9UwjBBwAvhazv4bgd3AHwJXA5WG\nYWwG1pimeXX6nNcMw3jGNM0BJmAqouHXDMP4IrAXSBmGsRV42zRNC1AtVxcafb2eWHjiF2PEgv3Z\nu3Gvvb6oBbLFQEu3Ss1NT8pGGaT3y1svL0cLTC6CSu++m+AN1wPDxcj5ago0IVhRGWZFZZjL13up\nQ92DcQbjFpG4zbGeGK2nYxzvidLZnxhxriPBsV3ePTnAu+kUp5KAzuq6UlpKoCasYzsSr55IICXE\nU3a25vyd433cfMGKSbs5TUS+9q9NVaPqHqTETQuM3B9lLwdXggwggwFEoAI3FoN4AhJxRKiaSO0q\nHPMDhJT4z1lNqrweEbW8IdpCINLh+Ac/6OflE1E04U1U/vwFtdN+TwsFIQSBiy4icNFFpPbvJ3bv\nvcPiYc8eUnv2ENi2ldJf/3X8hjHP1ioUitE4acffciV2+veglGmRIL1FHMeV2d+Ko9uaKoGgmCLV\nk7yeLu/npicZhlEBfN4wjOuAQSC3d7sE/hVPMDwJDABfBTYDl+SIDx+wGq9eYlymIhr+C/AL4FK8\nMMYfA5cahnEScNLGKOabWAzfwz9Bf+RhRHLYifXEwl24196w6MRCLuHbbiV4xeUAIwSDCIXQ6+sR\nQoyJIuTrUAT5OxdNxugahNyOSfGUzfGeIQ6c7OPJfZ0kbZfUqNHWQymHDzoGGTWHGJ/uFcI5rkQT\nUBry4ffNzh+kOy5dNW6txEQIIfCNrm+oqMhO/raOHsUZiiEbV4AQWENxEqe6vO+LC5kUyu6ozYvH\nI9lLPN0a4ZzaIA2lfgSwpSHE3o4hhIBtzaUIIemKWunc3+FVPCHIplkJQOCJEp1MlESgzdME1MAF\nFxD49rdJHThA7N/vxXrjDQBSe/aS2rOX4HXXUvprv4avpWXObVMoljNSepGBuOPiOBLLJRslcCXZ\nhY3xarmEJli8fzEVC4SngbuAivTrSdN/pskXgX7TNL+Urj/+zZx9gv+fvTOPc6ys8v73uUv2VGrf\nurtoWiCItsjWsiMo6zsCI+iMCOKuo7ToiAougKI4I4ICLuP2Cij6KqKi0iPLyOZgy2KDDUIUmqK6\nu7qra69U1rs87x83SSWppCq1V3Xf7+dTndTNTfIkXVU5v+ec8ztOxuORWCz2hWg0+jYcAfEr4IFY\nLPaBaDSq4QiJbdM90bSiIRaL/TJ39dHcF9FoVACvBD5b80tyWRiyWdTf3YV2x08R8YkAbSWJhT3j\nTslPpanNxZT0MFgWIhxCa5oYNlcpi1CJaran1dyMphroBuD3aBzcWcfBnXVoisKfXxxASsnBnRFe\n0Rp2shI7h+juHSah+Uoe2ywad21LGE2aZAyb7/7hRfZrDha+VjX4S+Y31MpcshXVEH4fikfH1lQw\nbaS0qp9b9IEsAEUohV26c6L1HLPKmQbeGtIwigSHw9T9W7aU5M3fRO5shVLBoeSFhhBF1yeO5c9B\ngELpfRTFOabkMiei7LGL8axfj+eG6zG2PsP4D39YEA+ZBx4k8/Aj+M48g+A734lao/OXi4tL7Ugp\nSRk2acvpLTByPQZCTM4KFJdyurgsJJs/f/r2o6+65+3A0cCuzZ8/fb4cR8s/HO8HfhKNRo8AXgae\niEajnUXnPgHcGo1Gszj7bR+NxWJPRaPR10ej0YeBEPDLWCw2zjRMa7k6FdFo9OiVYLu6V1quWhbq\n/9yL9pMfIQYm6ullYxPmBe/AeuNpoM10dt/ic1dslMd3JQA4qiPIOdEaHJxsCxGpR6uvn/HzJX78\n45JsRN71Z6pMwp6xFDf8d2nv0r+feXDVgLyS+DB39TJy5VWMagF2+BvY7muk57Dj2JW02TOWmdbe\nQFUEqxv8TolTXkw0BYkE9CXx9E78+Mek7rsfAN8bTsH3f85CJhIgSj+OZ/X/u8RIOeGmJaXzFzf/\nDhe/08XiwxFERd8//RTilu9DrOjnRtcRZ5+L8q9vQ4lEJmVPnP4SUBFOYFMmblxcXJxyyrRpO6VF\nltNvYFgSoSxNttFl72S5Wq4uNXOKKleCYNjrkBLl8T+j/d/vouzYPnE4GMJ8y79i/dM54PNN8QDL\nhz3jZiGgBHh8V4JjVgWnzjhIG6WxETVcV/2cKpi7eguCASD90EN433AKQ8GGKTMJ5f0Br3tF85Q7\n+JVu0zo68Z90EuKhh6iPJzn8gFb8x3egdXSyfXCc6//7ebK5sqaM6bQrp42JEifLlrw8mOTlwSQU\nNV3X+XX2awoUhERXU5DVjX48mpNdqnXa9VwQioLW1IxsbMIeG8NOJhwHJlXlnGiEY1Y5bk3TZZKW\nC3kR4Hwz/fl5Tzu7WGmsPxS+ehPKn/+EdtsPUXq6HWvbO+/A/P0mzH95O9abzikxI8iLFVmWbMkb\nZuWXU7I+isRL0ZoFoihbUpRpEU7PiYKj75TCebMLtgpiyhU4LlOQzwrmf7TtXL9A/jL/c2/jnFT8\ne2BLZ66BmWtKlkwuK3JnHbi4LA7TfopHo9EG4EvAqUATzmfDIPAw8NlYLNa7oCt0KSC2vYj2g++g\nPr2lcEx6vVhn/zPmeW+F0OznBqwIbAu1uRUluPgWscX9AeAE4zMNxPPlU6lf/Zrsli1kt2zBd9JJ\neM8+D5+u4iua/PyxM6IIFLoHEvQMJpwSpz3j9MczJY85ljImz5QQ0BHxo6qC8bSBR1M4al0TFx63\n/7zsxOXFl/A4Tkd58aV1dKJGIqiRCLZpYo+NIpMpWgMClOVdIrcgCIF99LFkj3odykN/QLv9NpS+\n3YhEAv3/fhf17t9gvvO92MefCEJMiIFp/osmGW+Xp6lk0UF78knlmZT8raLssXLOvpUXUDhp4iLX\n1z+pBKxYWOTPFSX3FeUPV6GPZSJIzIsopSg7oxVluBZStxS/NorWtBRUqxLIB9wl2lM6wbeVb/ot\nnFPksEapYC0WsZacGFLmCGSZ96BwKHob8qWCyIkWp8LPUu5nJB/458+v9X10G5BdXJaWWrb+Pgn8\nGKcGKgsQjUYDwKHAx3NfLgvJ0CDaj29Bve8eRO6vulQUrNPOxHzbhVBU17+SaA1pHNURLClfqbob\nLW3UtjYU3+x3zCtZrmodnbQCr1pVz1MvD6NroiSTULxT31rnn7KMqVayWyZEX/qhh2h8wymTMhlt\nEUcYtUZ8bHhFE796YjsD8TRBr8qB7XXs3xKiZzDByzlRkcgUzZSQ0DuSKnnO323p5d6tu+lqCtDV\nFCxcrmkKEAnMzHp3T8IgrodoNqqXPyqahtLYBI1gZ9LYY3GnfGmK/ppae1tWHKqKfcqpZE84CXXT\n79B++mPEeBylbzee//wi9l2HYLznA8hXLo5N60wzKXOhROBUFDeVbpjq0cqO5AJbu8JDTPXSannG\n4pK0QjBdTSRRdD33/jrCJn9cOOG5LH1PyuP+ieOydJ1ymvcyvzxRdHNRgJ5f83xlhESuz6fq7bl/\n9sGtAheXvZpaPp2fjMVijxYfiMViSRxPV9cSZCFJp1F/9Qu0O3+GSE84IllHHIX57vcj91u7dGub\nJ2opX5GWidLWju3xIm3bKbVQBKoQBXvP4h3Twk5qLt2d31GzJfguuADt5JMBgdrRjmnZ3PXkDp7Z\nMYwtJYd01nPuEauBylObpypjmgtTOR0VN2IriuDFPXHOOWIVb3x1u/OapWRwPEvPYIKegQQ9g0le\n3BOfZAWbNW1e6Bvnhb7SYD/i11nTFGBNkZBY0xjA75n8/+G8J0NYr/4nXrvjGc7of2ZKpyoAxetD\nafFh19Vh9feDbU/aDl7OvQ/zJmZ0D9Y5b8Y65Y1o/+8nqHffhTBNlOf/hvcTl2KdcBLGu94He0vf\n1SJQ3E+yXCgE99KxFyzJ/NRKPqtS+H7B9Z2Li4vLtNTyKXhwNBr9DvA4kMT5OxjEyTRkgJ8t3PL2\nUaRE+d9H0H/wX4j+ifp1u2st5nvej33EUUu4uOkpTl0LKFhiqkIUfPyLCTV4SkoXSppDpYXWtgqt\nLoyuKqiKmNMumZQS2Xwgdk5l9A4n2fLyEJqqoKkQ2z2GYdnYUvL4tsHcDAN4/MVBDt2vvlBKkS/w\nEEwIEorECkzsxhWXBFXLdsDs+w6EEDSHvTSHvRy+dmKq8i8e6+HRf/STMW2aQ158ukrPYJLB8dIS\np9GUwWjRTIk8LWEva5oCrG50xETQq/KnF/pRhEBtauSvdcdw8tHn0nTAfjWtU/F6UVavxhweRo6N\nOQX3zLK3ZZFYEDETrsN83wex/s+b0G75PuqjfwRAfeQhlMc2Y57/L1hvfit4vdM8kIuLi4uLy+JR\ni+XqF6PR6AnAiUAbTsZxF/Cz8gyEy9wRPS+jfeebpX0L9fWYF74T69QzltQ+1ZYS23Z29TRFoCki\nN1nYCYoVBTThHNMVBVXMMQ0upeOS1Dxf81CKAvlc8K+pCkrZpOOA1/m1GE0axNPONOOwT+eg9jpO\nW9/BA8/1AXDyK9s4Yt1EaZjMiSW76NLKWf+Zlo1pS2xbErroQvSTT0Ei0Tunnxkx00bsPOdv6OKQ\nVU6Qm78ESGRMtg8mCtOs89cTmVKTiP54hv54hr90D5cc1xSBpir4dIWnEhrmYILO+totYbWGBuxw\nGGug32mYXqYstJiRnaswPn0V5jNb0X/wHZR/xBCZDPrtt6Hefy/mez+IffSxC1uk7+Li4uLiUiM1\nffrFYrFHgEfKj0ej0ZNisdhDFe7iMlOSCbSf/Aj1t79GWE59ulRVrHPejPmvb4dAcEGetryhLT8k\nS81d5jMDigIeIfBqyqTpmAuF8HrQWlroHU4C0Nkw/w3QnQ0BTn5lW4kQ6GwIFJ6znItPXMep69sr\nrqdckExJ04FYtiRjWGRNR1BYlo1pSUxpY9mUDCybzaC2av0XQa/GwZ0RDu6cEBJSSoYTWbYPJQsl\nTjuGnK9M2aA6x8XEIm1Y3PLwS4CTTWqP+AqZiTWNjotTRxUxoWgaSnsHVnyMVjFSe2/LXoh89Xqy\n19/kWCjf+gPEyIjT7/Clq7EOOwLz/R9CrnErQV1cXFxclpZa3JNOrHKTAN4FuKJhLkiJ8sD96D/8\nPmJ4qHDYOuxwzPd/eFKwUB7k5xvbygdQQWVXEicQpeADrwuRK/tZfI/r3rizi98Z1iffqAjU1au5\n9eFtPPBcH1nT5pgDmtl4enTe11FNCDSFvdT5nbXp2kTgOxfxYvb0AKB1dSF3bMcDBCpMC84Lioxh\nY1jOV0udD8t2AvzpMjjTDaQrRwhBY8hLY8jLoV0TmR1bSvrHMmwfTPBc7ygP/K2PtGEXyraK17tz\nOMXO4RSOuZpDiZhoCLA6Jyo66v3Oz124DiUU4tzAEMesGgHUZSMYZtSoP1cUBevUM7COPQHtJ7c5\nmwe2jbrlSZRL3u9sHrztIvAvnHWui4uLi4vLVNTyCRgFPgBsrXDbkfO7nH0Lsf1l9G/eiPLMxFtr\nt7ZhvOcDiGOPR1OcabT5gF5VnCDfoyklu9ArkR9tHeKhHqch96SuEBetbyy5XV29ml0jKR54ro/B\neIZ42uDOx52AeyGEQ7kQqJaByFMc/NdK/OZvkNq0CYA9LWuwR0dpz47hP+sswhsvKTlXVQQBr0ag\nrKzdtGzShkXasDFMm6xlYdkSTVmYGaeKELRFfLRFfHQ1B/jj3/vJWja6cCZhv+V1XcRTJttzmYne\nkRRWkaCoJiYUAe0RP6sbA7kvPx31zbRbSbCyy8aiddHnTASDmO/7N6zTznTKFP/6FMKy0H55B+oj\nD2J84BKnZMnFxcXFxWWRqaWn4XvRaNQTi8W+WX5bNBr90MIsa+9C5ryx8y4fqpFF+/lPEb/4GZi5\nOnJdx3fBBQQveBvqXr6b2Bs3CoIB4KGecd6wNuxkHKSN2tmJouuAQda0C30FAJtfGOC8DWvmrVRp\nqtKnahmI4uC/UsBfCbOnh9SmTez21LGp+VVs9bdDs4djR17kLZs24T/n7JoEiKYqhFSFUNH8PtOy\nSWQsMoZZyALMtg+iVoQQqIrgsP0aSidfWza7R9PsGEqyfTDJ5hcH2D2SwrBKMxN2zha2dyTFY9sm\nxIQAWsIeOgMqq8Iaq8IeOsM6q8I6AX1hhNF0LEXmQ+63FuNLX8F69I/o3/82or8f0d+P54tXYR19\nLMb7PwytrYu+LhcXFxeXfZdaPw2/W+lgLBb71jyuZUVj53ZXnWFDAk0INCV3XRH4NKcx2HjySeLX\n34C1c2fhvp7XbSD8sY+h1tAUu1djWygtLSgBJ0DvbAhwzAHNhQxD2KeXlAnNlXzpEziZhItPXDfp\nnHIxkQ/+86RmEPDf0XEkDzdF2e2NEEwnaLDT/KnxAE4Y/DuN0967OpqqEAkogFNKZVo242mTfz1m\nP449qBnblnTUz4/Iagh6CHnzJVuTM12aqhSyB+taUzzZPciapgBSOg3hp7+mg3jKZMdQkp1DSXYO\np0pKnSSwJ55lTxye6it97HqfSmdIK4iIzrBOZ0inwafunZOIhcA+7gQyhx+J9tMfof76TqdkafOj\nKFv+gvn2d2Cd/c+gLY9yLhcXFxeXvZtaG6ENgGg0ui4Wi20rvi0ajUZisdho5XvuPeSdcSSg51yD\ntNysAE0R+FSBpoqqJUP20BBj3/gmmfvvLxxTGhsJfWQj3pNP3juDnip0hnVO6gqVlCd1hnVEIIBa\nX19ybr4UafMLA+iaMqlMaLb0DicLggHggef6OHV9+4I0WwPsCTezef8jYMx5zQl/kHDaQJc2vpNf\nP6Myp+nQVIX6oDOwrS3ix7Rs4mmTjGGSMW1sOdn2thbmkr0QQuDRJmcmLFuyZyzNsztG2D2aZiSR\nZedwih3DSTJGaQP2SNpiJG3xt4FSy1ifJugMOUKiI6yzKuQIitaghjYPTftLPnTO78d89/uxXv8G\np5wx9hwik3amSv/hfoyNH0VGX7k0a3NxcXFx2WeY6afg26PR6J2xWOxvANFo9FTgvdFo9A+xWOw7\n87+8xUXmLEVFkaWopkxc92nKjIMQKSXp39/D+De+gYzHnYNC4D/nHILvey9KOLwAr2T5c9H6Rt6w\n1nntnWHdmR7aXnmo1cbTo5y3wXH+qbTzDzPrLZgLWlcX/rPO4qX7HW/9/d94fM3Prba24quvJ5w0\nGTdslKZVvOEVEQ560+ELstbi0quGoAdwhEQqa5LMmGQMm4xloVD77IuZuDjVIjJURbD5hYGScy45\nLYotJYPxjCMghpLsGIizsz/OzrjBeLZUTKRNybaRLNtGSu1bVQGtQY3OnIjoKFxqhDy19Uwsp6Fz\nct0ryF73ddR7NqHd8gNEYhylexueyy7FOvvNmBddDHOYmO7i4uLi4jIVMxUNXcA10Wj0llgs9lvg\nAmAjcPy8r2yByPcXgJMxKBYGuuJYis7H7iSA1ddH/KtfJfvnxwrHtAMOIHzZx9EPOWRenmMlU3BN\nsi3UNWumDFxb4zknoIaJAH30mi+SfvBBhMdTc29B4bmnaXSeil8eehZ/YD0Apxy6hotn+HzNHg+n\nr22c196McqYqvfJ7tMK0Z9uWxNMmyYxB2rBRapitMZPeiOlExlQuTy11PlrqfLx2vwk3J3N4mNH+\nYXYmLHaNG+yMG/TGDXaNG/QnrZLHtiTsGjfZNW7y5O5UyW11HoWOvJAIaXSEnCxFS2AiO7Esh84p\nCtaZ/4R19HHoP/gO6oP/g5AS7a47Uf78KObGj2EfetjSrc/FxcXFZa9lpp9+d8Visd9Fo9Gzct83\nxWKxPdFoNDPlvZYJAV2hya/NKmMwE6Rtk/rNb0h8+7+QqVyw4vEQfPe7CLz1rQi3BnkCKVEaG1F8\nvqqnVGo8Hr3miyRuvQ0AEambUW9BnqlmLlQjX9YkPM6u/UzKmqZ7vuLMwFwyKDMpvVIUQSSgEwno\nBQHR3R8nY1i0RfzzUjY3nw3YWkMDDeEwdXv28Moms2TwWca0cyLBERK943lBYWKUWcSOZW3GBjPE\nBkv/dOWzEx0hnYhXJZ6x0VVng2GRxpPURkMDxmWXY73+FPRvfh3R34+yexeez3wS87QzMd/zAQgu\nzGwXFxcXF5d9k5lGr6dHo9GTASMajaaAjmg02gY0zf/S5p96X+1lCbPF3L6D+Fe+gvH004Vj+mvW\nE/7Up9DWrFnQ516ReDyoTdV/fMobj1+6/4+k170W35+2kJ/FLEfHkGW9ELVSHEhv6XbmZBy2di5t\nyaWUB//VxEVxZuDYkW2c++DtQO3uTHMlL1ju27qbB57rQ0rJcQe2cM6Rq0kbFlIujMXvTPsk9ow5\nIry1sxOzfwCZTDijyAGvprC23sPaek/JfWwpGUxa9I4bBUGxa9ygd9xkJF09O1GOrsDNT/TTHtJo\nDzlN2O0hjbbg0jk72UduIPPN76Pd+gO0u38DgHbvf6M+8RjGhz+C/TrXntXFxRiZ9YcAACAASURB\nVMXFZX6YqWj4PLABeAaIAK8HrgLun+I++wTStkn94heMf/d7kHVqq4XfT/ADH8B/7jmIBfLRX9FI\nibaqdseoOzqO5O6215B4IkHwNW/jrGAXb95yNwC+18+tmfjS257g6Z5hAA7tauDGd1QeQTKTsqb4\nzd8g+etfAxA491zCGy+pmEHY0j3EvVt3oWsKMpvl4X6Loz11tGfHSjIotU7GnmnpVfEAvZFEloag\nB11TePSFAf7p8FXs1xwimTVJpA1SWRvLtlHn8ee51j6JXz2xnUdi/QCcEG3hn49cgzWiYY+OTDnX\nQRGClqBGS1Dj0LbSx08aNrtzYmLXuOkIi7jB7oRJtswm1rCp2DsBUO9VC2KiPaTRHnR6J1qDOh51\ngVMUgQDmv23EOuH16Dddj9K7EzE0iOeaq7BOfiPGBz4ModDCrsHFxcXFZa9npqKhE/gs0AgYwFti\nsdgn531VKwyrdxdjX/5yaXbhyCOp+8RlqB0dS7iyZYxtoXZ0ItSpMz/FjccPNx1EwhME2yahevnD\nqsM4eLCbo04+gsjnPjvrpWzpHioIBoCne4bZ0j1UNeNQS1mT2dPD+C23IEfHABi/5RbskREyjz4K\nTGQQbn14G797aid9o2kifp1Gb+UAsxZ72JmuEUpLmUYSWYaTWRIZkzq/TlN4YrJcwKMRyPVBZA2L\neNoglbXIWnJeSv2mK2HaM5bi93/tJZFxMgC//2uv0/tQX4/QPViD/SBmLmQCusK6Bi/rGkqn6NlS\nMpyyCmJi97jBroTBrrhJf9JElj3OSMZiJGPxfFm5kwAa/SrtIUdEtAd12nKX8+XulEe+ej3Zm7/j\n2LP+8g7HnvWB+1H++hTGpR/HPtydxeni4uLiMntmKhpOBo6PxWJ2NBrVgUuB5+d/WSsDKSXp3/2O\n8W98s9C7IIJBQpd8GN9ZZ+1TNqozQUqJUleHEqqt5jq88RLqTzkD5b7tEDcgk8VUVAZCjXzv8PPY\n/tpDeNcCr7mc6Xb7rd7egmDoCzYhDZtV992HyNWZpzZtYviUM/jFYzuIpw0sWzKUyFLnD3JSi0r7\ns859/WedxZ5wMw88NyFIa+2jmEmTdda0SWbNghVrPG1w2vqOio/h0VWadEfs5e1c01mz5kbq2TAQ\nzxYEA0AiYzIQz9Ja50cJBkDvwOrbjROmzx1FCJoCGk0BjVeXzVAzLMmepJnLSEyIit2JyeVOEhhM\nWQymLJ7tL30cATQHVNqCE9mJtqBGW8hpyJ5VhsLrxXzne7GOOwH9hq+gbO9BDA7gufIKzDP/CfPd\n74e9fHiki4uLi8vCMFPRsC0Wi9ngzG6IRqM9C7CmFYE1MED8K9eR3by5cEw/4gjqLv8Ualtl61AX\nB6GpaDN8j7pedQBnDCrc8aeXGMtt5oasDDo2D3bHOX04OWsnosPWNnJoV0NJedJc+xrUzk5EJMIv\nVm9g85rXgqJw7Og23rJnS+GcPeMG8bSBaUmsXKPu/i1B3v/ht2O+7QTAybTEc2VJC0G+lOmerbsA\nZ3ibL9f3k7e5nQpNVRw716AHKSXjaZNk1pz3PojmsIegVysIh6BXozk80bugeDyIVaswd+0Gyypp\nkJ5vdFWwKjdgrpyUYbM7YbB73Jy4zAmKcqtYCfQnLfqTFs9UEBSNfrWQmWgLOr0TbUGN1qBj5jAV\n8sAo2Ru/jfbjW1B/9QvHYem/f4ey5UmMj34C+er1c3wXXFxcXFz2NWYqGg6ORqMq0A/sB+w//0ta\n/qT/5w/Eb7hhYu6C10vogx/E/8/nur0L0yFt1M7Vs7prvuTmie//jNv3eNClhYhECk5Gc+HGdxw5\nr43QWlcX8Yvew+YeP4ZQUSJ1bG5p5oSRF2nPjuE/6yw6D9qPwEO7GUpM1Mg/2T1M73CSzqKeh7nY\nw9ZC/n2987Ht3Lt1F32jKUJenfu27p62DKoYIQRhv07Y7wTTyaxJMm2SzFqYto02h9+N1jo/Z7ym\nkz/mehqOj7ZMKmkSiorW2YnV14fMZhdUOFTDryvsX+9l/3rvpNvGsxa7x036cmKiLzEhLBLGZEFR\nyFAMTHoo6r0qbSGN1oCWExK5LEVQI+RRnGyPx+MMhXvdsehf+wrK7l2Ow9IVH8f65/MxL3on6HP/\n3XFxcXFx2TcQUpZX51YnGo16gY8DxwJPAVfHYrHJNiPLjGg0uhZ46Z4f3sKqOWQB7PFx4l/7Opn7\n7isc0151CHWf/rTrjFQLUqI01E/pllQrP/ztX3iwO47weGqq8V8KeoeTvP+7fyKetZyA2qfzzTNX\n0xn2FBqhv3zXM/zmLzsBZ9CZpgq+duERFYVLrY3Qc1nve7/3ZxIZEyEg7NP5zns2zMvzZQ2L8YxB\nMmuRNWcvIAruSdP0QJj9/U7J4AopEZwQFI6ocC6dLEW8LEMxHX5N0BbUacmJiNaARptu07npDtp+\neweqdB7P3n8dxic+jezabyFekouLi8uKxcqavGPTTn3z509f9jHuYjKjTEMsFssA1+a/j0aj7wO+\nN9+LWo4YW59h9JprsHfvdg5oGsF3v5vA2/512mZelxwefV4EA8C73nQ4py9wED0fCFVFiImgT+vs\nRCta78UnruORWD/jGRMlF6i3RarPrFhI+kbTJLNmIc6Opw36RtMzen+rzZfw6CqNukojEwPlUlln\noBzUXsZU68wHraUFc3AAOT5hybqcCXlUDmhUOaBxcoYiadglQqJv3GBPwqQvaTKUsiadnzIl3aNZ\nukfLXJ5aT0V9zxtpGR+kbaSPtng/Ld/7FS0bDqP5+KNpDWoEF9iS2sXFxcVl5TKtaIhGo1cAbwFG\nK9y8jr1cNEjTJHHbj0jedhvYToCj7rcfdVd+Dv3AA5d4dSsI256xk9R0A87mWyzMZCe/1lKmprCX\nuly5jl6hDr2zIcC/HL0f927dhWHZnBBtrfj8M3VPmg1tER9hn048bQAzFzCVhvBVonignJSSZMbp\ng0hl7TmXMRWjNTVjKipybHRKS9blTmCKkqesZbMnYToiIn+ZdERFf9LELEtSWAh2h5rZHWouPggP\nOZshAU3QGnQasVtyWYr8ZfNsm7NdXFxcXPYKask0PAr8Z74BupjcoLe9Fqt3F6PXXIP57LOFY/5z\nzyH0oQ8hpphg7FKGlChNjSj65MbRatQagM4XMwnKL73tCf7S7TRNH7527jMdLj5xHb0jSbZ0D/Nk\n9xC3Pryt5PlnMuF5LnQ2BDh/Qxf35pqiq7knVaJ8CF+tE7qFEAR9OkGf87NhmJbjxmRYZObBjUlr\naMBSFOyR4RUtHKrhURVW13lYXTe5N8GWkqGUlRMVBnuSE8JiT3JyYzZAslqWIke9T6UlkBcRakFU\ntAQ0Gv3zayHr4uLi4rK8mFY0xGKxh6a47YH5Xc7yIX3vfU6zc9LZfRaRCHWf+hTe449b4pWtQLwe\n1Mbam4tnG4DOlpkE5Vu6h3h82yA5syMe3zY455kON98T456/OoF62KdXff5i56CFotb5DguFrqk0\nhpzg3ral00ydMcmYNoY1uyyEGokgVBVrcGCvFA7VUISgOZchOKRl8iZH0rAZ6N7J4M9+SX8iS1+4\nmb5wC30d+9PvCWFUaKUYSVuMpC3+MZSZdFve8akl4IiI5pJL1RUVLi4uLiuchYs+VigylSJ+402k\ni4JWz1FHEb7iCtTm+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I7IyF+GPUruHOeYT3OFhovLQuOKBpfZYVuoHZ2L+kc672JUbT7A\nTCxDp6u9L94xFx4PJ7+yjVPXd+Tum5q0o593RMqYTikKwE33xPjhB44ped7ZNCaXOyNNlUVYTmVF\nebtXWDm9Db3DSR58fg9C05CG46L0hrXhWWccquHXVPy5v75SSlKGTcqUZC2nsXqlOjPZrz2c7Ne+\nif7Fq1G6t6H07nT6HD712WU7z8FlMuU9O9ORMZ3eiXiRsIhnK11axLM26Sr2tHkMW+ZmZFhQQ7kU\nOFO886Ji4iv3va4QzImNoO7cFswd97hZDReXmnFFg8usEH4/Sii4aM+XdzECZ3ZBeOMlJbcvRANu\ntZ37U9e3F+Yq5I8ftraRkE8jHc8CTmPhS/3j3Ld1F69aHanaaA3TD0nLM58fazPJyMz1sbJmlU7N\nZUxWCqQEzyLEEkIIAh6VQM58TEpJynQCq4zl9EVIVk5PhGzvIPvVr6PfeD3qIw8hEgn0qz+D+d4P\nYr3p3MrWYi4rGq+m0KIptARqCymylk08YxPP2oxlLeI5MRHPiYt4duJyPHdsmmQGloSRXMnVTNAU\nCOmqIyI8CkE995W7PnHMmZERzAmPQE5wuLjsS7iiwWXmSBu1o2NBHro4AM1fb40PFAQDQGrTJvzn\nnF1zsF2JWnsAyo9Vy2b0DifxezQE2UItsGFJvvfACwS82qTMx3QiqJi5OiOVc+vD2ybNc5gt1d6P\n/Ptb7CZ139bdk54r/3+cZ6kzEZ0NASJ+vVBqtr7ZO+9ZhukQQhDQVQJFT5syLVJZSca2yZgrIBPh\n82N88jPYXfuh334bwrbRv/stRM/LmB+8BDT3o2dfxqMqNAUUmmr8dXeEtGQ8LyRyomK86Hr++HjR\n8enKpgBMe3ZiA5wyqqDHERB5sRHQxYTAyNnw5kVG4Utzjruiw2Wl4f7ldpkR0rZRGxsWZM5FpTkG\nACd1evk/09x3No3AM+0BKM5mZE2be7buKgneg14NTRVOjTrOhmqgQsO02dMzSQQNn3IGWmfnvAfN\n5VmA3uFkIZCHorkQC2Cveur6du7duos6v46uKZNuz/9/D8YzgNO3sdS9D73DSUZTBqtyaxyzbHaO\nZVlVt7QzSIrLmWByT4SNU7O+rBAC620XIdd0oX/tOkQmg/b7uxE7d2BccSXU1S31Cl1WCI6QFgR0\nhdYZJLgNy7FCTmSdrEYiJyoShs244QiLRNa5nsjaJAxHcFSb7j3p8W1ZsMGdDZoCAW1CTPgLgkIU\nhIVfc4SIv0hs+DWBP3fdp4mV3Q/lsqJwRYPLjBC6htrUNO+PWx6QP90zzKqGALqm8FBvhuNOP5vI\nb38BQODccytmGWbTCDzdecVBd99omqxpE08ZhaD7zse2s/H0KJ0NAY5Y28g/dseBXCmRBMO0qzYu\n57mj40j+eN92hN5Xced/ts5IlbIAfaPpwtqh8lyI+aTaa8//fxumPWE369crZlEymzcD4D366AVZ\nYyUm1q0gpvn/WwrKRUTWtEmaNllLkrUkhi1Rlkk2wj7+JLLtHXiuuQoxOIC69WnExzdiXPkF5Jr9\nlnp5LnsxuipoUDUaZmjwZ9mSpJkXEkWXxuTvk0Vf+e+rDeYrx7QnZmnMBZ8m8GlFYkJTJo7pImfE\nIHLHnfN8Ref4NIFPdS7dHg+XqXBFg0vt2BZqR/tSr2JK5hL8lu/KV8p8jCSyjKUMFEUQ8mo82T1E\n73CSzoYA42kD25YIJnZ9DcsRDcWBvtbVhf+ss0ht2sRuTx2b9ttAYtwEzKo7/7UKouJyn0pZgFrm\nQtTa7zCdmJkPG9iBC95O9rHHAfBsOIrmn9w+o/vPlEprXhNdjfVyz7KeOVBu8WrZTl9EpkhILGU2\nQh5wEJmvfQPPNVeh/COWGwR3KcYVV2K/1p2f47K8UBWRc2iaeUZdSknalAUBkTLLxYUsERpJM3ee\nYZM0HVOEWsqqikmbkrRpUX2efe0IHBHi1RR8qiMqvJpwjqmOHW7+mFfNHctd92nO7d7cuZ7cdZ8q\n8KgKmrI8NjJcZo8rGlxqRoRCKIGF2ZEuDtY8msKhXQ0l5Un13/oNeJwSkfnoaSinfFf+1PXthe+N\nXOYj7NPQFGcQElKSzJqF0pre4SSPxPoL/QymLWkMerji7FeVNEznCW+8BP85Z9OzK0Hivh3YOcul\nuez8F7+GavMROhsCU86FmIkDFUwvZqrdXvz/HfY5xfueMnGV2by5IBgAso89Tmbz5gXPOFRas2xq\nxB4aXjFNvKoics4xE0FPPhthWJKMJZ25H4tp9drYRPY/rke/6XpnEFwigX7VpzEv+SjWqWcszhpc\nXBYYIQT+XDnRbMmL/pThZDxSOXGRMnLHc8dSZt55zbmeNieOpXNmCjOTjs4WRAAAIABJREFUH87n\nmzOHY3YlV1MhAG8um+HNCQnncuIrLzbyX3r+ulJ8noKuTNymK0Xn5o5rikB3Rcq844oGl9qQErWt\nbUGfojxYK26EHprqjnOkUm3+a7rqS87JGDZpI1v4XtVK/xD1jaZJZk00RWDlctMnHNxSMqehHK2r\ni85wEvX+nWRyDkMBvfK05+mC+fLX8GT3EEesbSzYnhYH49UC+dk6UM329uJ11PpYc2EmjlHl56iN\njdiJBGRrs39cjpRnI2w5savpZCNsLNtJqCzYB63Xi3HZFcjO1Wg//RHCstBvvB6xexfmhe9cMaLM\nxWUhmRD9c3scWzq/23k3tryQKP++/DJjFX1vSTKmJJMTJEattVcVkOSzIvnHmH9hUo6uOA3rWk5c\n5MWGXiIuBFr+vNxxVc7+de7NuKLBZXpsG6W1BbEI5Rnlu9EANEyU84DjNjSfWYZKtEV8hZ3wlGFN\n2q0JeTWCPr0wGbq47EdRIOTVufiE2hp6K017LrZjzQfzeevSWoP58zas4bwNa4DJQfBSuxTlmWod\n3qOPxrPhqJLypNlmGWaaQakkMNSODqzubhDLt0xpJigiZx9ZdMy0HSGRtWyythNwSDnPdq9CYL79\nHdjtHeg334AwTWeC9O5dGJdeVsgouri4zA1FiELfwnxhy5yIsBxRkbEcQZG2JNnc8YzluLxl89dz\nGxOZvI10LtuZMaXzd8ac+HuTmUV2ZCoM22lYp8bmdpepcUWDy/T4vKiRaUaILjD5ch6ofa5BrVSr\nvc/vhP8x1s8N//18yX3GUgbJrEVnV0MhsDx/Qxd3P7WTdNbkmANbag7My6c9b7vpuwz8+RHaZQr/\nWWfBhe9mMJ4p6UOoRLXMwlzfh6Wk+Se3z7kReqYZlGoCQ9E0ZEsL9p49oMy/e9hyQFMEYa8KTLw+\n05YkDAvDkhi5D//5mBthv+FUjJZW9C9djUiMOyVL/f1kP3M1LPHfGxcXl8oohfIrKP47MV9IKbEk\nBcFhFDKhuS974u+QkRMaRtFxo+yy+LiZP25LR0zkyjQNO3dpyWnngezrLKloiEajfuDHQAsQBy6O\nxWIDZefcCByXu10C58ZisbHFXus+i22htq1e6lUA8y8Wiikvlck3N3c2BDg+2sLN9/4dw5pwuGit\n8+H3aIymjMK5AHvGMmQMi9891Uv3QILvvOd1Uz5veaAe3LWdbw8EYd0ZHLPned66aRPmKVPXe5f3\nMpy3Yc2sg/3ZOFAtNIvpmjSdwFAjEeT4ODKdWbQ1LTWaIoh4Sz8q8kLCzH0oZy2JPYvSJvs1h5L9\n6o3oV38GpW83yt+ecSZIX/0l5Krl8XfHxcVl8RBCoAnn705gDn0hs0VKiWlDJm3wgft2LfrzL3eW\nOs/+b8DTsVjsROA24LMVzjkcOC0Wi50ci8VOcQXD4iLq6lD2kXKBzoYA923dzad//jSf/vnT3Prw\ntsJtr2gLUR/Q8WgCAfTHM4ylJurbe4eT/O6pnaRzpUyWLXm6Z4Qv3/XMtM978YnruPath3LJa+sZ\nGUsVjv+p9WB2Cz/gZCNWNQRY1RCgKewted7yXoa5khdLewt5YZZnrhmUhRpsuJLIC4mmgE5HyMN+\nES9rIh6a/BohXcGrOL8nti0LTf7VkGu6yF5/E3b0lQCOs9InPoqIPT/l/VxcXFzmGyGcnoa5NLLv\nzSz1u3Ic8Pvc9d8Dbyy+MRqNKsCBwPei0egfo9HouxZ5ffs2UqK2ti71KhaNSrvM+SxC73CKkaRB\nNldvadqS4USWI9Y2FgJQ05rstf2HZ/smTT0ufr7y24QiMHQPRq78xXv06+h61QGc/Mq2wuyA4ues\n5TVVe/59ibwwu/ath07Zz1CLwBCK4vxe2AvfxLeS0HLNm41+jbaQzpo6D10RD21BjTqvQlDLuZkA\nllUmJuobyF57HdaxJwAgxkbxfPoTKI//eWlejIuLi4vLJBatPCkajb4H+GjZ4T4gnzmIA+WFrAHg\nJuAGnLU+EI1Gn4jFYlsXcq0ugG2jtrW6dmXAfVt3lQxEAxDSKWs/PtoCOMHmKYe085NHu0uauJJZ\nk2d3jBbOyTc4395tVpx+nQw3MGg47/mrtSTRK98HOEHvWMrg4dge/vTCAHV+nYtPXDdlH8JMm39r\nZSYuRDM5d6GpdQ21lGgp4RD2eBiZdAXZVChCTBpEB04JQMpwmicNS5K2bGzNA5/6DPL7/4X2218j\nMmn0a650LFlPO3NpXoCLi8uC8Xy/k1k/uMW/xCtxqZVFEw2xWOwHwA+Kj0Wj0TuBcO7bMEyaTZIE\nborFYunc+X8ADgWqioZoNHo1cNX8rHofxudFqatb6lUsKtUC8Gd3jFJeYWEDulJqj7rx9CgvDyT4\n49/7C8ck8N0HXiDo1Th2ZBvnPng7uz113H/k21BbW0umX0tgQPHSFNHQFMGIr6Eo05Hk3iLxUjwE\nrlKQO1v71Om49eFt3JOb8VBpenX5ufMhWoqdpBaLWt4ntb0N86WXmFerj30EIQQBj0rxu2zaztCr\n7Ic+jNncgvLD7yFsG/2mG2BgAOttF7qWrC4uewn/8b99PD+YBuDgJh+XH7ewlu4u88NSuyf9L3AW\n8DhwJvBw2e1R4KfRaPRwnDb944FbpnrAWCx2NXB1yYNEo2uBl+ZhvfsGy6j5ebGpFIC/anUEXVVK\nGqF1Bbx6qXPErQ9vY2f/KKpw4khNUbClRFcVZDbLw/0WR3scIZYdi6OE6xD6RL/IcCKLYUn2JE1n\nqnTS4I7/eZZLzz+KvtF0SbajfAhcsVhYKHqHk/zisZ6KwqXSufMhWuI3f6PEaje88ZI5vIL5RQiB\n2t6OtXPnXuumtJhoiqDOq4JXhXddSKqzhfh//CdYFvpPbsM7Moj88EewhIqZcztx7GDdAU4uLiuJ\n5/tTBcEA8Pxgmuf7U27GYQWw1KLh28Ct0Wj0ESADXAAQjUY/BrwQi8V+G41GbwP+BBjALbFY7Lkl\nW+0+wr7U/FyJSoHtK9pCDI9nGUpkyM+2SWZN7nxsOxtPj9I7nOT+h7Zij40T0AKkPT6a6/wYpo1H\nU5ATc+F4pOkg4pqfRNygzi84tKuB/niGVNbEp6ukDQukJJhO8Pjm3fx9x5O0XfyOwhwIcGxXy4fA\nle/sz7d96nTCZb4xe3oKggEWZhL4XFECAexIBHss7gau84z/9NNRGxsZ/eznkKkU9qa78YwM0/z5\nqxFexwzAtB2v+LxdYiZX7iSURZx07eLi4rKPsKSiIRaLpYC3Vjj+taLrN+D0NLgsEvtS83Mx1erv\ni8uWxtIGqayFLcCjKDzZPUTvcBKzt5fBpMmorwFbCBRbckSLh9VrWnnguT6Ex8OJLSr8A/7UeABN\nAY2GRmes1qfedAh9o2m+erejh7cPOpOH602n3jP9wIOse/NZnL+hi3tzpUGnre+YdprztW89dFb2\nqdXeh+IBdlBZuFR6z6C6aFlOPQ+zRWttxUgmoUIjvMvc8Bx1FPU338ToJz+FPTRE9tFHGfn4ZUS+\nfC1KOFxovi4m3y+RsZ1hU3m/dldIuLgsDw5u8XNwk6+kPMnNMqwMljrT4LKcyE9+XqYfrAsZYE5X\nf3/xiet4TVc91/7mWfpGnD90li0xzIlA0QLsovfu2f407zqrvShwP4aeZ1+H+oedCI+nZCxOW8TH\n0Qc082T3EHVeFTuVRpc2xwy9QHt2rLCG6URAfj15p6WZvldTvQ+dDYEphQuU9h9Mt97p3nOta/En\ngc8WtaMDq6fHLVNaAPSDDqLhW99i5LLLsHbswPjrXxm59KNErvsKalPTpPMr9UtImZtga9nOgKfc\nfAlbOm0SrphwcVlcLj+uzW2EXoG4osFlgmUw+bkaC+UEBDOrv0+kTWwpsaRElYKjD2h2GpXpRHif\nR9pO8GEpgpGsU8dU/DhdrzqAUwaVktdy39bdZcPZDmX81ttIP/Ag7dkxvMceW7h/NRHQ2RAg4tfZ\n8vIwAIft1zBjwVDL+zCVEKjUf1BtDbW+5+GNl+A56khg8Ye8Qe2iS/F6kY2N2MMjbrPuAqB2dtDw\njZsZ+cQnMf/xD8wXXmDkko3UX389auf0czOEEPg0gU8rdRm3cuVN2VyPRH5irCVBEW6vhIvLQuKK\nhZWHKxpcHJZh83NxU295gPmarnraIr5ZZR1mk7G49eFt3Lt1V2Ggm64KQl6d8zasKZyT0XxgTHj3\nVzPVKZ8+/emfP13IEDzZPcR5G9Zw0Ec/iPnms0jcehuZRx8l8+ijUzYC9w4n2bZnvPCs2/aMl0yq\nnk8qPeZC9R/Eb/4GyV//GoDAuecuSiP0bAWq2tSEnUiAYS7k8vZZlMZG6m/8OqNXfBrj6aexdu5k\n+MMfpv76r6Ktm90mgqoIgh6VYNlxy5akTJtsUVbCsiW4WQkXF5d9mKUe7uayTBCh8LJqfr714W2F\nycx3Pra95LbBeIbr7n5u0tTmmT5u/r7TDfTK74oblo2iOIFGe8RPa1E9f99oetLk26km4RZPXR6M\nZ9g5nGTncJI9o2n6RtPOULZ4lsyjjxbuk9q0qVD+U06+SVkRAkWIQpPyTJjvyclzfS6zp4fxW27B\nerkH62XnerXXP1/k/6+zpk3WtAsD/mpF7egA6fY2LBRKKET9V6/Dc9xxANiDgwxv/AjGM9NPXp8J\napVBdS1+jbBHwa8KNOGUPVk1TL12cXFx2RtwMw0uIG3U1palXkWB8tKVJ7uHOGJtI092DxV25D25\nMoOZWHlOVRIzXf39YDzDaCqLZUmEAMOyibaHC+e2RXwoZRuQWWNmwaNpScZSBp/5+dOoiqDRK9jQ\ncSRv2fXEtPfNNymPphybpojfU7VJeSpq6ZuoxFT9B9UyO/k+EYDD1jaW3Gb29JDdsgU5OlY4JkfH\nsHp7F7yvYTCeKWn2ngmKriObm7H7BxwvUJd5R3i9RK75AvGvXEf6979HxuMM//vHiXzxGrwbNizY\n8yqielaipMTJlpi28/ssBCjlfxhcXFxcViiuaHBB1NUh1OXdwHnehjWct2ENfaNpbrwntiDPMVWQ\nnMyYGJazmyikZDCe4Z6tu9g9mubGdzg19+W7jVnLrsmStCnsxedR6RtJI5HE0yaqAmF/gM37H8EJ\ng3+nPTs2ZSNwZ0OAda0htnQPAbCuNbTojkThjZfgP+dsYGIQ21SlPtUGxeV7I2Q2C6oKllPyJSIR\n1M7ORXs9s0Wtr8ceG3PLlBYQoWmEL/8Uoq6O1M9/Duk0o5dfQeTqq/CeeOKirqVaiZOUkmyu+dqy\nwZKOoMhfl9IpJlRdUeHi4rJCcEXDvo6UqC3LJ8sAU9t11mrlOdPHnYq+0TSWlGgCbAmWBIkEBE/3\nDBcCdcOceYlCfk0/2/wy2YJlp0RKJ5BQW1upu/QjRAIKf2s/CLqHJu3Kw0RPQ75xc7Y9DbXU80/V\nE1IsaqbK7FQbFNcaHyhkK4THgwgFUYJB0HUC5567KO5JTWEv/pyNZ8A7uz+Ramsr1vbtrpvSAiIU\nhdCHP4RSHyHx3e+BaTJ61dXUXXE5vtNOW+rlIYTAqwm8WuWMk5RORiKVmzORsWwMy23CdnFxWb64\nomEfRkqJ2lC/LD+cpiqTKW8knklwPJvym7aIz7FXLao2qvSeCUFJ93PIp9VUInTq+nZ+99RORlMG\ndtEOJMCxI9sIXHc7lx50Ds/VDyN0jUO7GgrZjTz5nob8smYzeK0WR6OZNgmXW8CWrzdPfr2tZfGV\n2tpK5KorUTs7F0Uw5F2ouvvHATi0a+YuVACKz4cdDCJTM+srcZkZQgiCF16I8AcYv/FGsCzGvnQt\nMp3Gf/bZS728KRFCoKugl2V5i5uwLek4OpnSOS5xBYWLi8vS4YqGfRghHEeS5cpUwVpnQ2DWLjcz\nDQL7RtMUVx4JHMGFcKY5H7a2kd7hJI0hLwPjmcK5a5uDNT+XriroqnAcWoCOej//fmTj/2fv3ePj\nquv8/+e5zJlLZjKZJE3atA2hFgJiKaVQi5cqIlbrLvgVl33susru7/d1l+8Kooir4LqrrOINFYV1\n77uiX93fqvAAL2jBtVIRarG0JbC1UEua0qRJk0wmcz+3z++PM+dkJjO5Nm1u58mDx6OZOTPnM2eS\nmff7836/3i/aP/kZnou2cSi2GiwLoSpedaO84jAT47XZMj6p+PnB41zZZNN+0fqaxz/WdZLRvEG6\nYBALBXjXlvYKDUit9aqJxiptRHlL0pk2g+tN5kjlDVrqnWuXyhuznkKltLRgvtTtaxvOApHr3okU\nDpH+whfBtknf/SVEoUDk+irv0AWPUsOwDkqia4HjgF3aWRDefWPH2KWfbVH5s9sS5U+A8vHxmS1+\n0rBcEQJ5RfOi3bEqn3IDMxNEzxb3SimyxM1v6eS8lTEvcG9LRHjLhlV879fHEAJi4QBF055WwNmW\niLB9wyq++cujFG1QJIlVDWEuWVXH8DTX5hqv/fjACQDefsnqGV+LmbRvWQMDiFSKkTv+gcSbX1c1\nCtV9f2LhACFNIaDIFdWhyYziyrUR+Yd/wPBf3AjAQ298N082rPPWNpdeHeWcjhC6HElV6ZOCiHSO\nttjsn8dneoR37EAKhhj99KfBssjc9/eIfJ7Ie9+7aD/nypEkZ2JTrYRiutjCaYPSLUdbYdqOL4Xp\nG935+PhMAz9pWK6oyoI1cpsucxXcuZS7GZfTGg8RDMjkdEeQG1DlioTBZfuhXTyRjgGgyVFg+jv9\nV29YyaNdfRiWTUCRSeUNBmLNxHbs4FWPPMKF6RMcamhHKqtu1CKgnN6u9mTtW25S8fODxxGplOdW\nPZEnw1Tvz2TnUtvbK7wfTmr17D5loUR0JE07K0ni6XL/7qPsfLYPYehcfW6M92xYuFW9pULoqjch\nhYKk/vaToOtk/+3fEbk8dTf+xZJIHE4XWZIIqwrhGt/8li0omja6EFiW047pToMSwimY+dfQx2d5\n4ycNyxHLQmltme9VLChquRmXs7apjlzRJJU3KBoWX/zxoYqJP2ZPDw07f8Cla17LMw0d6KMZXnNh\n25RBrec7EGsmoMoIKk3h3F33+4AuOwpUjyeFsZ39wCxG0Y5nssfcsG0dVzbZjNzxD6zURyc87nQx\ne3qwenvP2PNPxlwIocuF3kLAg78d4aqOmF9xOAsEX/taGj73WUbu+DgUCuT+8z8RepHoBz7gB72T\noMgSEU2h1l+/WRorWzFStiyhkGS/QuHjsxzwk4blSCiIHI3O9ypOm6ZYkPqwE4SNF9rOhKncjN0d\n9ke7+igalrdrvrOrryIw/96qy3im4RyG1TAy8Exfjvt3H+WGbetq9uKXux3H3vEO4vGtHDiWBOCS\nc8YEuO46Ns36FU79+svPMxXtF60n8ebXeddsZPs1mLFmxg9DrfX+lF+HiTQp5QmcnEhg9ffTqg+y\nbYXCkyUDwtMxnptMFzFXQuhyobckQVq3GcgaftJwltAuu4yGL91N6q8+ishmyT/wIFgW0Q9+EMnX\nmMwYdQKdBTjJg16qUNjjWp5crYXvVeHjszTwk4blhm2hNK+c+rgFzumMXp0NrhHZF398iHRJHAvw\nwN7j3Ly9k4FYM4+cs4W0AYasIEtgyiq7DvUzmjfYVxrL6gbHrtuxa17264d/wYtvvsCrMrx4Ml0l\ndp6M2V6PqSosE+FWQL51cJDHevLwnf0VlZda63ms66T3s2vW5+JWRspHrgIYh19AioSRNI0/iiS5\nfHsnULvaMh2mEs+7QujVpWs3WyH0eKF3fThAS8QPVs8m2oYNNHz5S4x8+DZEJkP+oYcRlk3sw7f6\nicMcosoS6gQVCrs0/alglTwqyrwqXB2F7FcpfHwWDX7SsMyQwmHkyMLtA58Js3UvHo/a3k5gwwb0\nPXuQ6uomNFHb1NHIFeubeeBpZ2c+Fgqwr3uY3mSO/lSBrBIEyUZYYOG4Rgtgz5HBqrahpt5eL2F4\n4KKr2XXuFpJ5yzN6SuZ07vrB8/zeJau9wHaqyUEzvR4TVVgGYs3Teo6BWDMPHj5a5bXgPm78aNw7\nvnvQ+/eeI4MIxpy9ayF0HZFKITfEkTSNb+4fYC9dSJo2KyH0dEbKupxO5QomEHo3a6Drp/W8PjMj\ncOGFNHzlK4zceisinabwwx+CZRH7yG0L3tByKSBLEpoqoU0QaVi2QLcdYbZpOWZ4uuVMfPJN73x8\nFh5+0rCcsEzkljXzvYo5ZS6qC4N//G6Ke34NQqBdsnHS3fbrtqxlz5FBoDKwdHeWk1kdV5WQKZi8\nbWNbxY66i9LWhhSPc9JU2bP2EihVJ9yRq4osEVBkL7At36U/k5ODvnVwkMd7T0zrPBN5LZS/J+6/\n3YTHJaDKFdUGrzKSaK8YuSrF65E0jZNaPU81rscN886UEHouK1jjkzhb17GOHfMN384ygc7zabjn\nK4zc+mFEKkXhkUecxOFjH/UTh3lGkSXCcrUwWzdtciWzO90SGJbw3bN9fBYAftKwjJDqosilnvCl\nwunO7S/u2UPxV0+C5UxG0p/ZT/fPn0TbdElVwNuWiNCWiLB1fbOXOJQHlW/ZsIrv7+1BkSXqgiqJ\nOo3rtqylPhyoDkIT7UT/9AaUn+wiGU2QDdY5Ik0hUGSoC6nohSIBTaE/VZjWDvlMfSvU9soAfWT7\nNTzeW5zyPC4z8YaoFYxPpPUYP3J1LIGIY8gqmPaEFYqp9ArTSQjmqoI1/vGypmFHY4hcbpJH+JwJ\nAuedR+Ker5D80K2IkREKO3ciLIv6O25HUv2vwYWGpspVf+NuImGWkgi91N4E/qhYH5+zhf9puVyw\nLeQVzfO9ijlltuZu5Vj9/U7CUFLsPXjRW3j66RTyiwe58sJWgIpzADx1ZBDDstm6vrninBNVISYK\nQmM330TDm96K/KNjSIYNlvAEg6mczqgQrCykqHvoEIQ3TuiuDLP3rXAD9N60TrauEXYervnc/akC\nrfFQVRVhIq+F8se6x84kGHfbw9z1NQKNvxjgYI8jFK8lUJ7O78NcJgSzQWltwXzpJcZcP3zOFuor\nXkHiq/cw8qFbsYeHKf7sZ4zaNvV//XE/cVgE1EokrFLiYFi245pdMrCzhJNYuBUKX4jt4zM3+J+U\nywQpUrekqgxzZe6mbdoEgQDoOv3RZvacuxm1pPl4tKuvou/+0a4+klmdnG5iC8FPDvZy3Za13jlr\nVSHctU60rqG6Ruqj/Wi6yWBaRwhn8ogkBKptMaxFeflXP6P+6lfxbDIPTDzRZyhdJJV3eubj4em/\n19/uNtnZ1Q/0syIWJJU3vPU/1nXSGx3qujqXB+OTBeG1gvjyY6ab9Knt7SWB8okJBcoz0StM9Tsy\nF8noREiy7EyEGhr2xbjzgHruuTR89R5GPvgh7KEhij//OaOyRP3HP+63Ki1CFFlCAQKTvHemLcga\nlqOZsJ1EwvKN7Hx8ZoX/rbUcWIJVBnCC5N5kjt5kjqG001bj/jwTpPJkapIdKcOyyRQNrzyezOnc\n/8uj3v337z7Kvu5hBM50IHDEv3d89yD37z5a9Xz37z7KPT/s4mQyx8lUAd2yMUsVD8HYXvRwIEKq\naHntUamy6U3l5Iqmt7uWK5rTeu2un4B73Y4OZHj3azq4ZXsnV29Yyc6uPq/9KF0weLSrr+rc7rrG\nP+/4IL78cVPdPxEBVT5tkfJkuOvKFk2yRXPa65oJSmMjUsDfr5kv1HPOoeFrX0VuagKg+LP/ZvSz\nn0WUWhR9lhaqLBEPqjRFAqyKarTHg7TXa6wIq8Q0mbDiOG0LW2DbolS9EFM/sY/PMsT/5loGLEUt\nQy0e2Hu8arTpVFi9vYhCASSJ1uwQW1/ax286zgVN4y0bVgFj7Umbzknwi0MGo6UgWpEknjue8oJK\n9zhNlXnqyCBmyd1ZUO3p0JvM8bPHu9BHMxRDCWxZBiTHKEkCgYQNvCp9gou3vJIfaRqTvYP9qQKW\nEGglR2hLiCpR8kSPKxczJ7M6/7LrCJGg6iU+C4Gp9AhzKWA+PpglZzgBZCRwZnafleYVWH29vih6\nnlDXrnXE0bd80GlVevQx0rJC7KN/5VcclgGKLFGnKdSNu90WzjhYw7IxhNP6JIQ75cmZ8OS3O/ks\nZ/ykYaljmcjNTfO9ijNCuXnYRKNNpx04lnaW3tm1k9+/9b1omzZ6j716w0ovIVFkCVmSUGWJ+nBg\nwl3vkaxOtmh605BURfI8HQDM3l5EKoUpB7BLAmhJkhA4O2OmBagBAutfwfk3v5krx7XMjH9drijZ\nbU+qD2kTipJrPS5dMLzdtUAp8djXPcwV65t5tFRtiIUCNXULtTgTQf5UeoSJ7p+JWL4/VaBYankD\nKJr2tJKvmSJH67AjEUShOPXBPmcE9ZxzaLjnKyRv+SAimaTw05+CLBP7q4/4rWPLFFmSkJWp251y\nhuOObVhjRnb47U4+ywA/aVjiSNHYkqwyjA86x5uFTRelrQ3MslYe02TN+jWo44JE97lb4iEsIajT\nFOojWkWw664nW2oNqguqJHOlIF4b83RoS0Roi2lcMXyE3U2dyKVg3ZYBAYbl1BkU0+LZfoNffelf\nueHD/3vSgLktEWFdS5T9pXWua4lOO7h3xcyGZZPXrYpE6Lota7luy9qaQuipmG2QP9V6Z3L/bPQJ\nqiIhl/KGM7mjKLe0YHUfc9ytfOYFtaODxFe+7CQO7jhWRSb24Q/7iYNPTVRZoj5YmVTYQlAwbIql\nREIvmdn5Y2J9lhr+p+JSZolqGVxu2LaOu67fyF3Xb+Tm7Z2e8Bhm4Ij8L/8yrdtchtJFioaFojg+\nA+NFwZs7GrEsm3RBx7QFAUUmoMgk6ioTN7W9nfduauGOA/8fv398LytVE02RiYVUR8sg8Nyhi3v2\nYPb0TOh54N52dCDj/Xx0IDPtXvwbtq3ji3+8iXves5l3bRkztXOvYVsiwqaOxlntttfSO8zk/tNh\nNrqJTR2NNMdCnslUcyw0a/fpqZADAaSGOMLvn55X1HXrSNzzFaTcYNHhAAAgAElEQVR4HIDCD39E\n5itf8d8Xn2kjSxIRTSERUmmpC7CmXuOcuMbKqEq9JhNWHd2Eq5nw8Vms+JWGJYxUF0UOBOZ7GWeU\n8oBzNjvXxX3PTHmbW9Uob9OpC6oVlQNwglR3wpJpg5E3CAcUoiHnz2zzuMC7+NRTNL/4PO958Xle\nLaf4183vQgCGmaVYkhlcmD7BqzK9ANy78zBPHRlEU+WqXfP+VIFkVscqBTrJrD6jtppaLs7zMZJ0\nvulN5igalqcNKRrWpNOvTheluRkxOnpGnttn+qiveAUNX/4SIx/8ECKdJv/wD0BViX7gA45/io/P\nDJEkibBa27gub9lYNl5Fwq9K+CwW/ErDUmWJVxkmYqY714Hzz5vWbTdsW8dtb7+QtkSEWDjgjXot\npz9VIJXTsWyBJDnTjxJRjdec14zAaXFypygV9+yh+MsnwDDAMDj/sQdptPPOTrgkcZ5a5JOHH+LO\nFx4mvGMH/3AozwNP93iTos7EVB84fbO8hYSb7LlMp/rkCsNl2ekacl2uzxSSJKG0tIBd/fvkc3YJ\nnHceDV/+MlI0CkD+gQfJ/vO/+BUHnzlFU2XiQZXGsMrK6FhVYnU0QDwoE1EllFJVwp/i5LPQ8CsN\nSxQpuvSrDHOBtmEDhe89UHVbLTZ1NLIiFpzQYOyJw6ewSjtGCKf3VZUlul5OeV4PrkA79vzzFYFi\nf6SRkdE8qxNOK0zBCtH/Z+9n/TkxzLY29nxnv3dsumAQC1e+t63xEIk6jdGSx0J9uNKdeTrJwJn0\nJ5iIM52kzLRyMhOX67lCjsWwRkZAN6Y+2OeMEug8n4Yv3c3Ih25F5HLkvv1tpFCIuhveO99L81nC\nSJKEpkoV5nVCCPKGTcESFC0b3fQnN/nMP37SsBSxLeTm5VdlmC49zx8BoP2i9Sg1rtNAbAVHuoer\nhL+OwZhR02CsN5ljX/ew08pQ5rWwqSNB1/EUumlXfCFoF11Umq1a2kmSJORQGEWVOT6UJVu0+OpQ\njn/eP8g7L3PEyeXB7BXrm6ftzlwrGRgfrM+VWd5MOFtJykxeg3sdf3zgBABvv2T1Wam6KC0tWD09\n/gjWBUDgwguJf/5zjNz2ESgWyf7bvyGFgkT+8A/ne2k+ywippJMo//SpaVRnO1VRv43O52zgJw1L\nkOVQZTB7egBHUDwT/vnz32b3KWcG/7YVv+ZPLohW3P/gxrfxyOEA2cP7iIedEaPlrs/AhGNW+5J5\nZ/ReCcsW/PRgH6osYQnhOSq3JSKYbW0Vj23NDPLG8xv54e8yjjGbcOzd8rrFjw6c4PcuWc2+7mHq\nwwG2rm/2RreWU2tXvZYYeDRv1PSzGEoXK3bYzyTzkaTMhIAiY1i2V7k508jBIHZdFJHPn5Xz+UyO\ntnEjDXd9hpGP3Q6GQebvv44UChG+9tr5XprPMsY1qivHtAUF00a3RJWfhCT5yYTP3OInDUsNy1zy\nVYb0vfeRf+QRAMI7dhC7+aZpPa7n+SNewgCw+5TFG6Ru3LShP9rMj175ZkZNCSSboUyR7+/t4akj\ng2zfsIobtq3zxqrqpl21218wql2Yi6aNUCSaY0HCmuoF9fnHHhurMgAIwfDh32FYjaUe6tIHvYB0\n3uB1nSu4bstaYPKd86mCbt20a/pZzAdnM0mZLm4yM5o3SBcMHnjaSU5rJWlzjdzchNXdDYr/sbwQ\n0C6/nPidnyL1158AyyL9pS9DMEj4rW+d76X5+HioskRUq65QlicTpu2PgfWZG3wh9BJjqU9MMnt6\nvIQBIP/II17VAZygbyYCYbXjXO/fg3UJ8loIkEDguYHC2LhOd6yqRKWwuT9VmHBHR7cEg5lixa71\n+Laob15+HQ9nYqSKFso48Zv7+T6b8aTjxcBXrG8moMropl0h5u5PFagPB1idiLA6EaEpFpzReSai\nN5ljf2nK1Gwxe3oq3uMzjW7aFS7Ze44MnhHR+XhkTUOqi059oM9ZI/ja11L/N5/wvDTSn/s8hV27\n5nlVPj5T4yYTjeGxMbAdDUFPcB0NyARlR3QthFOl8IXXPlPhb2ktJWwLuenMzJRfDEzVI99+0Xq2\nrfh1WXuSwpr2FgZL9zdnk0T1HCktiNtlFA2pFVoEV7sgcIJLd6e+NR4ioqkUDZ3xH7tKDafQyLXX\nMvrFu7G6j9EfbeYXF7wOAwlsgSzLSEIgCeGUo+tC0xbj1hIWj29buuWbv6kQcz/WddLbXQfHaXvz\nHHgT3L/7KN/f2+ONqX3XlvaK96QpFiRc2iGLBGt/FM22qjRb2hIRrljf7FUYYqGJXb/PBHJTo6Nt\n8KsNC4bQlVciikXSd30WbJvRO/8OKRQmeMXW+V6aj8+M0VS54jvNxWltsilaTnuT61XjO137lON/\nMy0lwhHk0Jmd9DLfqO3thHfsqAgk1fb2mr37tXrk//yj7+atZULoQ5/4NPloM62ZQVozg7ztf37O\nry57K3bzChJ1GsXSbrw7rtMdeTq+raYtEeFtG9v4z6e6veqELDll4ObSrn1Yq/xzW/nEL0n/27/R\nXdAoJuMolsASAgsJd2aroim8s7OelvQgJCbXb9y/+yg7S87O2zpbKlpqyjUO5WLuwXSRnV19aKpM\nUyxIKqfTHA2yr3uYfd3DsxYou54V6YKBEDCaN9jZ1ee9J22JCPFwgO5TjiHd+ElUULuqFL72mhnr\nWGbKzds7yRQN9ncniQTVaRsFzgVyKIQVqYNi8aycz2d6hN/6VijqpL/0JbAsUn/zNzTc/UW0jRvn\ne2k+PnOCIkuE5UpfCSEEBcsmbzii64JlY9ugKH4SsVzxk4algm2hNCbmexVnhdjNNxG+9hpg5kJo\ncJIFcILsn0kXYF91I1u79/HOgz/hnQd/wps3txN/z61ekgDTm8Dz3MsjjDf7bIoGGRgtYNsQCSo8\n1nWSd3c4f3b5h39A/pFHiGn11F36J6RlDSwwAU2VEEJg6gbnfPPrDGd6Gdl+DdEb3ltzLb3JHN/f\n28Nwtohtw3/tOQaM9eKPb69xd8+NUlKkmza9yTwFw+LkSIFIUGFtU91pC5TNUiIEMFIynHOZaBLV\nTDgTI1vv332UruMpBFS5fp8NlOYmrOPH/UlKC4zwtddg57Jk/+EfoVgk9bHbafjqPQTOP3++l+bj\nc0aoZVBn2oKMYaGbgmJJfO0LrpcPftKwVAgGkSMLY/LM2WB8suD27pe3J00WSHqViaBTBdjTsZnX\n/u5pWjODrOlYRaz02FrP0RQLUh8OYFg2ask5eH/3MF09I1XHZgumZ8dQNGx+8ovn2LTvO7QM9yLS\naU6d4wT1LSP9jDasQZIlZFtg22DZgIBfNF3AoVgbT70cQfm/T/OmjWurAtn+VIHhTBGrlLSYtuCX\nhwe4bstar/3IvS7l1+ktG1bxTPcwz3QPYVgl+bUEOd0iVzQnbBuaKlhvS0TYur6ZY4NZABRJomhY\n3P3jQwRU2Wt/mqyD1q0qZb/7XQDqrr++4n0/EyNb3eQrldcBeLSrr2p61plGDoWwwmEo6mftnD7T\no+6P/ggxmib37W8jsllGbvsIib+/D3Xt2vlemo/PWUGVJRqCKpRkb5YtyJs2ecOmWJrc5CcRSxc/\naVgK2DZK4/LTMowPXGdq5AUgqdV/ArW8G1zc5KS8V/+xrpO0JcKM9/S1BWSKpjcIybIFRj6LPTSE\n1dvLgxdcxZ5zLmcwkiATCKNIEtFQgLxhkdctJCBkGRyOreQwqwgIR4sxk93//lShqm3rrus3VkxM\n2nWonxWxEH0jBa9/1bIFpmXXTL6m4/sAcN2WtTx1ZJC87kyVSmbHguB93cMEVXnS9iSA4lNPYfX2\nev92NQ3TbUebKf2pAsms7lVHkqXqyNkeBas0NmKdOOFXGxYgdX/+PuzRUQo//CFiZISRWz9M4r77\nUFpb5ntpPj5nHaUkuHYnONlCkDOcJML1kvB1EUsHP2lYCgRU5Ojymroy0S7zdIM7N/j/76ec6sDW\n7n20Zga9+yfbSb96w0oe7eqjPuyIZHcd6ueW7Z1IVO6cS9LYeDJLOILoLUNHaDl5jP7YCvaceymG\nLZFXNGxJQkEiUzRZGQ9hWk4KoqWLiFKsLcXjSJpW8/W0xkOEAgpZ3UksZAle39kyoYC6XOMAUB/R\nSOUMcobz+LCmVGkw3OOn6/vQloiUHLRz2EIQUOSKtijdtCdtTyru2YO+92nvoup7n6a4Zw/BrUtf\ngCpHIlihkO8SvQCRJInYrR9CZDIUd+3C7u9n5MMfJnHfvcgNDfO9PB+feUWWqpMIN4EoN6XzR78u\nTvyRq4sdIZATy0PL4FIrcJ3NSMwbtq3jzsvjfHjXP/HOgz9xbpRl/jMT547vHuSO7x70RqqOJ6DK\nFVN1BtPVwlVZkohHNKKhAJoiE49oNLS3IYSNsC0vGJaEAAGGZWNYNok6jbVNdQxndU7KYVrP6+Ct\n2y5EaXF2MidqvYoEVYKqjKZINEQ0r62mfORquaDbDdLd+9c213HVK1tZnQhzTnOdlxBNdm1d3weX\n8uPLRddrG+uIaKqnodi6vhmtdA0nm04kDAN0HXTd+XeJiV7X6dIaD5Go0wjIEgFZIlGnTXty1Vyj\nJBrBtqY+8AzQmzboTfsJy0RIikL9X38c7dVbALB6ehi57SPY2ew8r8zHZ2EhSxJ1mkIipLKiLsDq\nWO3RrzJg2wLbFiWvIp+FiF9pWOzIEko8Pt+rWLSsWb8Gzc4jSqXTgRVr2D0sIZU29Gu1vdTST0B1\nf76z27+C/ceS1IVUwgGFJ4rNvLq1ndYTL7G1ex97OjYT0guYIcVpT4oEyRRM0gXT24UfFTLbX3cB\nl5RExJsmGIc60QjT8W1btao05e1Kd3z34ITXa/xrv2J9s1dlmAg3KWiKBblleyet8VDNdYwP+pW2\nNqRQCFEKxKRQiP5YM2op2ZluO9pMxNJtiQjrWqIcOOaMpF3XEj2tZOR0hNpytA4rGIQapoFnkm91\nDfN4j9M29ob2KO/ZsPxaH6eDFAgQv/NORj58G8Zzz2G+8AKp2++g4YtfQArOjc+Jj89SZaLRr64p\nXcGwyZeE1rJfkVgw+EnDIkYIgbLMqgwwc9HzVKjrzvUCUyWxalqPGR+w7u8ermpPesOFrURDAXqT\neSwhUCSoL5jIK1ogPcg7D/6E1/7uaQbrEvzra96N1dxMqC7mPb58B/6BvcfZ1z2MYdpsXd9c5VA8\n1QjT8nakWlqA8uOmurZTJSHu8e5z7ezqA2D7hlUVCc8N29ZxcbvTzjFRIlT+3nx//RvY+/MTSNop\nL9mZ6n2fqVjarY641YXZTnWazblroTQ2YvWd9MzFzjS9acNLGAAe78lwVUeMttjSNYw8HaRwmPjn\nP8fIB27B/N3vMA4cYPTTn6H+k3+LpPh6FB+fmaKO00iYtiBTtMibAt2yEb4+Yl7xk4ZFjCRJy641\nycUNXNP/8i+s3GvAtttm9TzuhJ7cQw8BcO6bX8ebNq6dVkIy/nZJGnOQBnjDBS18Y/dRBE77kSXw\nxNJyXR32cNLzh0jkR/ittBopmWNje4JLOxq9NWzuaGRf97DnD+Eaj5UnDm6wWx9y/qTHB7uTtRi5\nCYn7et1r258qTKmJgMkF6KN5A9OyCSjVQe9UQXX5e9MfjLPn3M0oJU1HrWRnPLMVSw+liySzTrtZ\nom52O8ZzJdSWo1EsLQDm/LQp+UyNHIsRv/uLJP/y/dh9fRQff5zMPfcQvfVWf4KMj88kHDjpfC9d\nsnLiz0VVlmgIqzTgbJTmDJucYVPwqxDzgp80LGKkeP2y/lISl20kWiiQATL/8E+s/t2Lc/K8U7W9\nmD1O0D5+7KssSdhlWcPOZ/ucSTzlY5WCThCuJBKITAaRHKE/2kymvpGWRB2mZXMqXeTqDSu9XfjW\neIg9RwY9QzmAp44MVo0C/V1/2plUASRzY8eOD87LKwluQqKXtAZucDt+TOtUu+S1rtO9Ow9XOCuX\nB861guqL2xu81qVyhK4jZEcNni06rTp1QbVmsjMXDGWKnt/GUGb+TdaUxkask/1npdrQFgvwhvZo\nRXuSX2WYGqWpiYa77yb5/vcjRkbIP/wD5KYm6v70T+d7aT4+C5JbHzvBswN5AC5uCfPlq1dP+Rip\npI+oK1UhDMsmo9vkTZuiKZBlf9TrmcZPGhYrwkZpaprvVcwbqbvvhsKYURiFAqm77yZ+28wqDhO5\nDreVJQTlfenpe+8j/8gjnNTqCV35Rs7/4I2AE9hb45zdfvXCqaqeTTkSoeGuT9MY08g//AMy3/wm\ncriBkYYVjCRzjtumLPGpB7sq3Ki3rm+uCMDHP+/zL6e8hAHAsATPv5wCHK8B11Oi1sjVR7v6PF+C\neFijP1Xg0VJLkSuGnukueW8yVyGQThcMYuGJg8+hdNHzcHATALOnh8w3voE9nKSZE2QuTtNnOknX\nynioQksxXe3JVK/hicOnKgz6bOHcdv3Wc6b92md77omQYzGs4eGzVm14z4ZGrupw2uT8hGH6qGvX\n0PDFLzDygVsQ+TzZf/8P5ESjZ0Tp4+PjcOBkzksYAJ4dyHPgZG7SikMtAopMIiyTwJnSlC0lEAXL\nEVT7VYi5x08aFilSpM7PqOcIa2AAO+mMXpUTlSMTy3fpNzWpXPmzJ/j+2jfyfHwN4ZdNrvrhM/zZ\n71/K8y+nqoTQAjAtG02RAAlJgkSdhtrWBulBJyBOjmBHJTJFG6sUn1lCcKh3lDWNETR1LNAHp8Kg\nlQLrydqj3F+NB/Ye59hgtqSpcKYBQaXGIVc0MUzngbmiyU8P9nJ82EmU4uEATbHZtegEVJlYKOBV\nSK5Y31yld/jRgRPeeFlXw+EmAC939TAixblI7+f51vMYCCdcywtOjRbQVHlC8zmXmXp3uNdnqtum\nw/hzT1Shmg7KihVn1bfBTxZmR6Czk/in/46Rj34MTJP0V76CnGgguG3bfC/Nx2dJI0sSsaBCLOh8\nRuqmTcawKZg2uu8VMWf4I1cXI7aF3Lg8tQwudddf77k5AxAKzbjK4CIy2bGxnpmxkYnlLTRD6SIP\nHkpy86v+mEdXbqA3nOCEFucX3elJ9QLRUIBgQMEWNqGAwls2rKItEcHq7cUeHAJdZzAQxSgLBoWo\n1Ea43Ly9k7v/eBN3Xb+xqhXn6g2riIXGAr1YKMBFa+I8VdrtF8IRlI2vhvSnCl5FA6BgWPzitwPY\ntsCwbJJZnc0djTPeJXeTgpCm0Fincd3l7VXi7We6hxlIFRhKF8nplROCPvVgFx/5TYbPvOUW7nzr\nB0mG49iSDDgf/jZw/qp67/iptCfTXf/VG1ZRX1YRqQ8HuHrD9MTxk507fe99DP/FjQz/xY2k771v\nxs8jRyIQCs96HTPFH7k6e7TLL6f+43c4P9g2qTv/Dv3AxBPJfHyWG5esjHBxy9jn2cUt4RlXGaZC\nU2UawyptMY1z4horwirRgExAdrQR478LfaaHX2lYjGgacmh+ZscvBNL33kfuoYdQz+1Aamwi+OrL\nZ50wWL29YFngOkNbFlZvb8VucLZoksrrCBtMJQBICCEoqBo5fbwP9BiKLBELBziRzCEEjBYMnuke\nnlbv/frWKMWSAdr2UqIBE++WO6LnMNGSELo+HKA/VcCw7Jozr6sSndIGjBCQL1qoioRcetjrOldM\nud5aPNM9zMnSa3/u5ZGK+/Z3D3OwJ+mIxCUoGja5okkkqNK5KsbOZ/u8Rf229TzedPhXhMwiBc35\nooloCn/55vO85xsv+J5tK1Ct61h+rWbzvBO1wM204qC0tmAdO3bGqw3+yNXTJ3TVVdjDSTL33gu6\nTuqOO0jc+zXUV7xivpfm47Mg+PLVq6clhJ4LPC1E2W26aZOzbHRDkC9Vu/3ujanxk4ZFhhACJRab\n+sAlitfnXmonOlWUaHzbO5itU4XS1oawLCgZhwlJqvACiIcDHB3IYFgCTQLhRteShAA21gvaEhFP\nP1BOLKTSP5L3qgZCwDPdSfZ3D7OhrQ25uRl7eJjfdGxCkpwQWZKgIaJxaUcjvzw8MOPXEwqMBZRP\nHD5FtmBSJnWgaFg8sPe4V4G4Yn0ziTqNkZxeWrOzy57TTafcGwrMytxsf/cwTx8d8vQBB3tG+OzD\nz3H7ta/yjjEtgVW6OIok8b4r13PRmjj9qQI7n+1DUmSEIoNtkzCz/MHoIX7R+ToA3n7J6qoAfi5G\nnLqUVxvOlOB6psiahh2NInL5qQ+eJf7I1bkj8gfvwh4eJvftbyMyGUb+6qMk/uHrnkmjj89y50wn\nC5Ph+USUGhbypkVOF+RNG9MWNav9Pn7SsOiQWH4O0OV4bT2WxYMXv409525G/Wk3bxqSeXeH8+s8\nkx1cq7cXbNsTATx40dX85qfdSNFTbO5oJJU3WNsYIZnVyRQMEGOVhaCp897XrAegORaE0mhVACQ8\n9+NaqO3tBDrPp+e5Izy/6nwarCKjAad3/vWdK3i0q8/TAnx/b8+UQmQ3wTnY45iSda6qZ1/3MNGQ\nSjLrJASqDIZt86MDJygajqj20a4+2hJhL2k4b2WM9a0xfnl4gIAie+1UM+XFk2nGV3+ffPGUNwa2\nNR4iGJDJFp11BDWZi9bEvXaeje0JDvYkkYJBNsQl3nDPp3jL1q28Y4JKgttKNn4K1GzbqlxvifHm\ndbN5Xnd0rFttCO/YMStdA4DS0oL50ksg+Z2li4G6P38f9tAQhZ/+FPvUKSdxuO9e5Gh0vpfm4+NT\nRlhVCJciYsOyyeQEjE1J9ynhJw2LDKnOF0AD9Eeb2dNxqffzzx7vYtOX/pOV+ijhHTuI3XzTtJ6n\nL2eTbFhJS+YUT7RvYtf6K3DrOE8dGUTCEei2xEPUKWCdGADbwpQUQoxNs+l/6USls5sAhKApFuRk\nyclZAi7tSLCpoxGzpwc7mURpbYGAhhACCYEkSWR1s2K8arpg0J8amxRVK2DuTxVI5Q3PRTpdMJ21\nKzKS5EwBMmwIylDQLU8oPZo30E3bExg/2zNC30geVZHZur551rvq562MVflWhDS14nXoZUmVPi7B\n+up7L2N/KVgvN36bLFh3fSyACn3HbJjrv7DYzTd5U3RmmzAASIqCFI8jRtNztbQK/JGrc4skScT+\n6iNYg4MYv/kN1tGjpD7xNzR84fNIAf+6+vgsRJypTCp7PrXdTxrG4ScNiwnLRG5c3v3FSqmtB0MG\nWQLF+RUWqbH2oOn2jN+/+yi7XpQw33oTGd1iOJLAUFRSBVgbdcqXro8BwI7z42R//UN+eM5W8lqY\nqJHnv4+O8mcXQXNExckUxsJN3RKkcjqaImMLm7pggI/+/iu9+62BAZqTI1wUf46fXvBGwGmLeWkg\nS0RTPXFwLBTgicOnvJai7RtWecG825JjmDajeaNi0tHmjkb2HBmsCNwtW1AfDpApOsF1WFPJ5A1s\nt0hiWZwcKRCPBNjXPTwtN+RaOoJNHY1sWdfktSjVaQptDWG+uvMwAGsaIzVHxI5/jrONW7FwJznt\n6x6u+B04ndGpp5MslKM0N2OeoaQB/JGrc42kqsT/7k5Gbv4A5pEjGPv2Mfr5z1P/8Y/7G0A+Pj6L\nCj9pWEyEQsjB2Y2/XCqo7e1E//QGVj/0EK9JH2PP+i2gBbhi+Agr9dFpP0/5ZKTi6nb6h3KoMsgC\ncrpFtmjye5es5oZt67yguCU9yBe/pZIviXERgl90p9mezJGMNJRmnpZOIIGiSBQMG1UBWZYomhb9\nqYIXdIpMFopFMC2EsKE00UEAb9vY5vkcbF3fXLNdCfBegxvkZosmAUX2EovWeIgv/+S3XipjCUhE\nNafVCmhrCHM4b1SNi00XDMKaUrHeWkymI7i0o5G+kTwFw+Li9gZeHh7rxe/qGal6LreNajzlo0on\nEzo3xYKeFiGgzl37znVb1nLdlrUTnvds4zjBN2APJ8dm684xfrIwt8h1dcS/8HmSN/4f7IEBio8+\nRra1lej73jffS/PxmTfcCW3+583iwU8aFgnLXQBdTuzmm9Auv4z/Dfyvzoud2+gi77Shz6pnXOCM\nJEUIZCF4T/EI12x7PTAWKHbvf5n9Ky/wxNAZLUxdznEMdgJeqaKvRTdtBGBYIEmCSED2RMVWby+i\nUKA/2szj66/AkBSwYbgUONeHA9z29gu953KN3WCsXcl9rnLthERla815K2OosuQJjmVgMF30djh7\nR/JV2gN37cmszld3Hp5Q/DuZjsC9L69bpAsGu387QDQYoGWGomrXTA/goTe+mycbnHWMX9NcmamN\n1zRsn6Wm40yjNDZip1LUfPN8FiRKczMNX/wCyfffhMhkyH3r/6K0thK+xjd/81l++FPaFid+0rBI\nkBDIDQ1TH7gMKA8kY65+YYY94+VBZkCRCciSZzKm2SYdT+zE/MOrKp5Lbm3hVN2A46lQCrqzQuax\nrpNc3F793thiLIBXJaqNyGybBze+jVSkvuJmSwi+v7eHnV19XotULBSocG1ujYcqxM9CgFoa8SoY\nC+A3dTSy+dxGDhxzBNLnttTx0oDjRSFJkC1U+iM467axBWSKJseHspOKfyfTERimzUgpqVJk2Umg\nTJuAKnPeyhj9o4XxT1dB+ajSk1o9u09ZKBEdSdNqrmmmRm6Tntta+K2sSnMzVt9JUM6O4ZvP6aOe\ney7xz3yakds+AoZB+stfQW5uJvia18z30nx8zhrulDa91KLqT2lbPPhJwyJBikb9/lcmn3k/0+qC\nG2T2pwp84r/2M5x2gvKwXbtN5mT3SXSl8kMtV7TYdah/QoM3iZLSocZ711+/gv1rX1V1eyZvIMsy\nsVKrzb7uYdoSYUbzTnC+riXq7ean8objNmzZ9CbzHB/KIEkS8fCYi/FX33sZj5V2zn/bO8qRkxnP\nITqsKaTHJQ7CTXZKrVq5YnViMRVtiQjZoonhacUFrfEQt2zvpDUe4vmXUzzxwqmKx8zWeXn8eU+H\n3mSO7+/tmdHkqvlCjsWwkkkwZv7++Mwf2qZN1N/+MUbv/EIBu6QAACAASURBVDvH/O2TnyJx79cI\ndHZO/WAfnyXCUN4kXXQ2Z2JBfxrcYsF/pxYDtrXsBdBT0ZvMTerMPBHu+M/hvImtqNiyyogaIXTl\nG6uSECs5jGxbFX3kRVswmjfYfyyJUiOncxIGHBOzMpS2NuREI4qo3tG2BNhCkC4lCbppkymYrGmM\nsKYxQipveK/VKE0+CigythAYliMqLg/07999lP/YfZR/3nWER7v6SNRpqLKEJME1l66p8CSIaApS\nyYOiNACKTR2JCYPmpliQ1YkIqxORChH2/u5hBtNF72fDEnSujLGp5C7dHAsil10vWXLH1o7hjioF\nWKmPsm2FgqQ5icXpCJInoz9VIF0wsIVw3oNxk6sWGkpjozMy2GdREXrzm6m78S+cHwoFUh+7Hat/\n5r4sPj6LlvHTBn0WBX6lYTEQDCJrp78Lu9goF8C61Jp5/+1uk12HDgJjve4zcQZ+4vCpUmu4o0mw\nJYUDW9/G+eOOu3zbJax98hGONneU3SrxytVxjg5kKkzUXNzAW1hUBPJqeztr2ldw9ZEn+c7G30OU\nzd1XZIiHA4zkdFRF4k2vXFnhFeDyWNdJRvMG6YJBMKAgSxKK5CzCEsILdt2dc1sIbBvqQipS6bVm\nigaWNTZyVQhBQJWxDAshIKzJ3PD62mNX2xIRNnc08tSRQTRVrgjkB9NFLCGc/Kp0XS5b1+Q9tjUe\nIqwpnk9DWFNqmsiVjyr98/Z2fu80HZ+nojUeQpEcATtAnSbPytzubCFHo1gBFRZBO5VPJZE/+iOs\n3j4KP/gB9tAQIx/9KIm/vw+5rm7qB/v4LHKaIir1QefLIVBrx81nQeInDQscIQRKfLZ+x4uXct3C\neN+F8kByINbMru8e9O7bdaif0bwxLQffyspEpTHbRMT0PO5oVUnYdK6I8JdvPo8v/fgQRwcyEz9Q\ngqJpe9OIXJ+GbOt5lMXVgBP/uYLo/lSBI/3pKpGv+1qbYkFi4QCmZZMtGBhu7Cg57UDuzjmALEkY\nts1ozgDJqSo8fXSYrD7mN5E3bNoSYdRSGaBKh1HG/buPsq97GAlnvGv5db5oTZyIppDTLe9cF62p\n/D2OaCrF0rkj2sTnKU8az3abkL0IbEHleBxraNhvX1xkSJJE7IO3YJ88ib53L9bRo4x+8pPEP/tZ\nJNX/avZZuvh+MIsXvz1pgSMBcn39lMctJWrpFtyqg8tEGgbDtD0/A2BCvcH9u49yx3cPcsd3D/Li\n0T6ksthQErBOqn7M07sPcLDtAtysQkgyI6k8t31nv6c3qIWmSGiKjDpuN6U3bbC34VzsSdx9bQEH\njiW5uL2Bu67fyF3Xb6xKgjRVxrRsx9i6tDoh8CYsxUIBbCGwbBtZclqZAoqMVZq8U74qCXjl6jiR\noEokqE7YBlQ+sjagyp6ng0tbIsJ7X7eOVfEQK2JB3rF5bdXzjOR0TAGmwHOknm/6UwWKZdOo8obN\n/b88Oo8rmhq5oWHOzeh8zg6SqlL/qU+irHP+pvVf7yXzta8hFkGy6uNzOrxnQyM3bW7mps3N/uSk\nRYSfNCxwpKjvAD0Z7hQkl63rm9GmmNFfHvACPDeQJ27kUIWFKiwSRoaWaPWux76TecaXIU4ZEr3J\nHN2D2ZrnCqtOG5Akwcb2RIVhmZ1KVVomT4B7SFsi4gXe5a97KF0kq1sIiVJSIHkJSlsiwrqWKFLp\nv5CmEI8EAKdn//J1jUSCldN3XugbZXNHI7ds7/SmEc2WgmEzkjN4tKuP+3ePBd/Pv5yqae5WC7On\npyppPJOMD9j2dydnpZc5W0iShBRfXhsLSwm5ro6Gz3/O063lH3qY/Pe+N8+r8vE5s3yra5j79g1y\n375BvtVV3X7rszDxa6ALmWXqAO3qFnIPPQRA5B3vmHQy0vhRm+MNxyZqaUmVdrfjkRBX1xfZO+wE\nhlc1S7RftL7q+I6mMIzzj3PFvPmyFh8Hp91pdbKP/7PaJHLdO9nU0egFnw3799M63EdYz1c+psae\nsSzXdke+Yds6Lm5v4O4fHyKgyuSKFoZlY1mCNfGwd75U3qAp6mhiDKtkICeclqBoMOD5LLgr6E8V\neOg3x/nl4QHUMqO4cqbyRehN5ni0q89znk4XDHZ29c14ElH63vsqfg/Sf/L/eOc/E7TGQ2iqTL7U\n5+W+v1OZ3M03SlMT5sgIyP741cWI0tpK/HOfJXnzB6BYJPP3X0dZtYrg618/30vz8Zlz3JGrWd35\nnPVHri4e/KRhIROJLEsBtIvQJ29ZKRc7uwFdbzLH1RtWTjqv3xlXmvdairJFi2/c/kf85teHALjs\n1RdWPQbgVec0Ix1NIcoqPzYSCk7Lj2mXJQ6lzep0IEzfvl/R8brXcn/PiBdkvw6F9tbzOFnfMsVV\nANMS7O8erpk4tMZDBFQZw7RRZACJRCRANKR61+f4YNbTLYQDMqoiI+E4VP/gmZcrdvzBafEqAsZI\nAVmeeOzoVL4IyazuPLeYnXGx2dND5hvfwE467tH3//IoT/M0kqZNqlU5XaKhALpZ9HzT0gVzUpO7\nhYAky0jRKCKXn/pgnwVJ4IILiP/NJ0j99SdACFJ3/p0zivWCC+Z7aT4+c87xUZ284XzIhgN+N8Vi\nwW9PWqgIsey0DC5esNh3ErvvJJlvfKOqPeU/fvgMt//fp7njuwe9tpdyncIDe49P+PyPdfVVaBBG\n8wZ//b2D3HdghPsOjFS00ZTz7HMvVd8obFrqQ7zl4lptPIKRQB1fW/cWPvTTHr6x+3fePQ8Nadz3\nhj8jp5UH27U/OK1JXH/L25RMy2k5GskbDJXGnfanCuSNSqFzpmBi2DamJWpUSMCtO4hpjB0tT9jG\no8iSpy+3hTMG1j12OiNXrd5e7MEh0HX6tXqeWnEB6M77Npk3xlygKrIzlpYx/4gzfc7TRW5qArv6\n/fRZPARf/3qi7/9L54dikdTtd2AN+KNYfZYWA1kD3Rz7XtNNwUB2Yl2gz8LBTxoWKhIoyzRpsHp7\nEamxPiCRGsXq7fV+fuGef+S/H38O69gxrIEBdh3qZ3/3sLeLP5Qu8sDTPdz2nf01E4CnXjxVdduu\n/xnTOEwUHDYpdkWVASAhm7zvyvVcdm5T5cESSEJgSDKGomDaTsDeN5LHMG3SFqjYyDV8GsYzlerh\nhm3ruO3tFxJQJGzhfABnShOTBtNjO+be0kovwRKCsDZxO4thC3TTMYGbzdjR8ueWgOFskf2lqVbu\nyNXyY6dzDt0WFe1UZwqBMy52MemJZE1DiizcFiqf6RH+gz8g/I5rAbCHhkjd8XFE3q8g+SwtFFki\noDj/K/Li+Zxd7vhJwwJFisXmewnzhtLWhhSPI2wbYdtI8ThKWxvgVCEKu34BgCHJ6KPpijYmw7QZ\nzeuemLVWAlDL4diyKw3R+lMFzzDOffyxxrVVj8tLGt9+sptvVCUnEkJWsGUFgewF/rmiSV43iWkK\nSArKNHeGXzyZntLATuCMVZWAgulM/Rm/ew8QCwe8CUqvXt/MVJ/XwcDkffK11tWWiLCpI+G9boFT\nCSknoqloioymyDVHriptbcjNzaCqtBZGiNk6vQVBbzJHPBw4oxoDCQlJkgiqMoZlo5v2GTOUm0vk\nRMKvNixyJEki+oEPELhsMwDmCy8wetdnEb6Jn88S4ZKVES5uCXvT/i5uCXPJyoX92erj4GsaFiKW\nhdLUNPVxSxS1vZ1A5/kUf/1rAAKd51cIoVfqo0SNPIdiqwHYGFTY1NHIG9qC7PzNMbACaLZOcbAA\nzU1VItaW+sl3tOPhAF/dedhr8WmKBbnywlbSJ/qBSq+BsDAwTJueodrTk8YjBJiWTcG0GIw2ARKy\nsJGEwFIm/nN89vgID+17GaCmMLk1HiKiqSRzulOlkiSeO57iFS3VyadtC5qiGhetjnPd5Wv5+fMn\nJ11zNDS5V0O5GLp8XW+9uI0f7DsxeaVEmvhetb0dKRwCw6A/2kw6VMeaRsf4ynXFPlNBvFdgkMbG\n2C4G5EgEKxgEozox9lk8SKpK/FOfInnj/8E6fpzi44+T/ff/IPq//9/5XpqPz5zw5atXc+Cks9nk\nJwyLB7/SsACR6iJIyvKdguIan6kdHagdHdjJZIU79Mj2a8gEwqwsplil2YwKhRfu+Ud23PNXfPSh\nL1BfGCWthjlhBTg+mOWrOw9XtCmtaap2XF3bFOae92zmlu2dpPIGummTLjhuy7miyX/tOcaufITK\nZiFBVHF+nkR2UPnabMGptE5GH3uALcnYFW0womQjLbzzPX10yNvR//7enpo7+2/b2EZAlgnIMok6\njYAqe/345RQNm8F0kSdeOMXXdh6ecs2SJE3q1ZAtmqRyOju7+qrWFVAdobgqUXsU7thLrF7nnj1Y\nx8q0LLqOWsgTmGKk7unSFAuyOhGhpT6EZQtURSagygte0+AiNzRMa5Svz8JGjsWIf+5zXtU5981v\nUnjssXlelY/P3HHJyoifMCwy/KRhoWFZyPGG+V7FgqA/2kx/tLnq9ugN70U55xxC7WsIta5A6LrX\nsjQYaWA45FYDJIxS21F5wFcrkO5cWU9bIlLVV2+YNr3JPMmcTkYJETQNFNukIZukMZdCjsYIqDKN\nddMfFTcWzklecCfKDd5E9cEF3fLyiPHCZDeZqA87U5Pc/OPKC1trtifpliOCNi3B7/ozznSjSdY7\nlC5OGCwfH8xyfChH30iB7lOZCgH6sz0jmBZYOAZumqpUTIDKFU0MW3jv0XiOHfwt/RHn+NbMIFtf\n2kcxnz+jrUKusNx9C2KhwJS+HwsNpb6eKXvOfBYF6to1xO+8E0qbSKOf/wLG88/P86p8fHyWK4vr\n23A5EFCRo9U74csJtb2dh974br5w3g6+cN4OHnrjuyvak9oSEd60cS1SaRztGztirNRHkTSNZONK\nbLn0a12Km8xxZYCL1sQrRLiyBEdPZb12lysvbEVTnbGklnD0DhJQsAQho4Bq20SMIq8/8ms+d/Ua\nbtneyek1sEyy3V6Gbtnolo0ijwmT3YlRH/nOfr6/t4eGOo3GqEZIU7h6w0oGSy1WVUiOEBocjcNk\ncXG2aPL8y6mqxKE/VSBXNn3JFnii9N5kjh8fOIEoe10Fw/SE0P2pApYQnqbBEqIiEbp/91E+k1nD\nl666kQc3vs1btBwMnZVWIQlnjO66lqh320LTNEymcZHjcd9VeImgbb6U2Ac/6Pyg66Q+/tdY/f2T\nP8jHx8fnDOBrGhYYy1kA7dKbzPFkwzqUiCNwflLT+L1x/evjPQLS3TvIP/IIF6h5wpJNHrUkDIZw\nQKkI+NoSEc5fGeNgjzP/PxxQ0FSZ519O0Z8qeKZpn/3B85wsBbK2LRCmSZ2eI55LYaoBnmu7gJ88\n9Cu2vPv3SRdmMS7Oth0XatsmYBnkIjEs19/NjfdKEXJAGRNTu6Lh8c7WyazOcFbHFs7Eowf2HueC\ntuoJXFpJ3Atw4ep6XnPeCv7zyZcYyZsVp3YRwNd/9gLxSKU/wmC6WHXsqdECX/zxITasiWNadkWX\nTPmIvdZ4iFgo4F23WCjgJULe69ICoMjs6dhM58kj7HnFZeiygmTZ7DrUP2OjuOngntttgUrlDW7Z\n3klrPHRWEoZy75HJmExLAiA3NmKPjMx+HWnnffHNlhYG4WuvwezuJv/AA9jDw6Ruv4OG++5F9qdl\n+SxifE3D4sNPGhYStoWyDB2gJ0KawtiuPLCK3XwT4WuvoRG4odvkxwdOAPD6zhau27K2yq24N5lH\nlpzd8aJpM5LV+czDzwGwsT3BR3//lUSCKvGwE9jKisRaM8vJYJRMfR2ysIkWszxRlNmCI26eKU25\nJKYSIBOsw5Zl6lQo2BK6Vb1D3BjVvAC9Llj9Z+vWKmzb6TUSwC8PD3BBWz2qLHnVFglYGQ8hgEvP\nSXD7ta/iXV/9Jam86T3PZJQH6xetiVOnKZ5xHDjBfzpv8JNne2u21buVj7ZEhHdtaefhfU4707Wb\n11YFyrplY6EQKDlH9EZXUBg1QDKITDHRaS45WwnDVImAi5vYuKNnayVQkiQhhSOzGtX5ra5hHu/J\nAPCG9ijv2eB/Ji0Eou//S6yXj6P/ei/mkSOk7/os9Xd+Ckn2GwZ8Fh+3PnaCZwecz6eLW8J8+erV\n87win+ngf9osIKS6qP8FQFlfua4jdH3CtpDx7Rlqeztqezs3bFvH7ddcxO3XXMTN2zurHtufKpDM\n6rib+pYtGM6MjW092JOkP1XgygtbiYUDtNSH2H7xKgw1QDEQREgSlqyQCsU4JYcYTBeZac4gCUHQ\nNCgEQqi2RUNuhLCeIxKQa2oaAqpMfypPfyrvjRstN3YDZ+pTQHFGrtq2oG8kz297R4mUJRmSJPH6\nzhb+/Mr1vHVjG4919XEimXOmBE3S96MqtX8vY+GA1y6kytBQp5HM6uimqHKaHs8z3cMMZXSGMjrP\nlNqWwHn/4+EAvaki/bFmokUngNWVgHdBiqY9oeHc6TD+ms5lS5LZ01NlUugyvmo0leh6KF3k5eEs\nLw9nvSlf45Eb4mDNbPxqb9rwEgaAx3syXtXBZ36RVJX6v/1blFKrZnH3bnLf/OY8r8rHZ+YcOJnj\n2YE8QgiEEDw7kPeqDj4LG7/SsFCwLeSEL4B2eefBR9j0sycAOJfXwbabKu6fbFd2uju25TvhlhDI\nNbrl3d72aDCApAVBrxTsSpOMSZ0MtdzUTQhGwnEkFOITCFi7T2VRS/cdHch4+ovyNq3P//B/+M1L\nw94kJyHgRwdOVLhf20Lwvb09CCGQJIm1TWMB8UQt8EHV8XSAsSD6/t1H+dGBE177FoBlQzqvV2lI\nXBTJ0ZMA7O8e5mBP0tM8HOxJsr97mE0djfQmc6TyBqsoYKeHyASjJMNxVNtCKDKSokya4EyHydqA\nxre+zQXpe+8j/8gjAIR37CB2801TPGJyckXTS8pqicihNH41oE5/tJfPgkeORol/9i6Sf3EjIpMh\n++//gbpuHcFt2+Z7aT4+M8K0hffRJE8yettnYeFvay8UNA05HJ7vVSwIzJ4e8o88wkp9lJX6KPlH\nHvF2aHuTuQr3Z6jclS1v3dBN27uvvCrRGg9VBbYBRca2BbYQbGxP0BoPeb3tAVVmX/cwW89rJmgU\nAIFsW8QLaVoawjTHgmiBmf0pCUXmD/c9zJrkCXRVw1AC2LJMsmhVaqpd92ZbOLoKRNX0JHCqJ6m8\nQaRM4C2EIJOv3iXWTRvDcpyVj53K0hTVJu1Lqg8HuPuPN3HX9Ru5Yds67xoXxiVQAlgZD08Y0Mcj\nle1mpuVUI4zSJKfxBKNRApZzjvMGu7mg/0UkWUaSnBay8klMM8EVj9/x3YM1HcMBr5IzF7i/zy7l\nv8/l55tuhWMqEXk5UjRa8/aJaIsFeEP72GPe0B71dQ0LDHXtWuo/+bdQqkqPfuYuzN/9bp5X5eMz\nfVrqAgTLpm8EVZmWGUwg9Jk//ErDAkAIgeILoKfErSA4rs8GTTXGiYLTulEusH1g73H2ldpfrryw\nFd2sbtmQEDTXh1BliUsnCEbt/n5kIZBKW/KKsHm9lqY1HqKlPsTxoVrlVTFO1OxE1G6MbKgaqm1i\nSzKmUFBF6ZgagbdhC7ChTpMrpie5SdJIVvf63MvPMRmWLbikPcHBniTJrI4lqisOp9JF+lOFiiB9\nKF0kmdUZz1BWR8YZszqeojF2a2s8RDAgky06twXLXpMbQO861I8Ui/Lq/3mC1mKKTw8/ya73vQuA\n67eeM/WLq0GtNqAzIaieDdOtcEwmIh+PkkhgJpMwg4rYezY0clWH83nkJwwLk+CWLURvvJHM17+O\nyOcZuePjNP7TPzoeHT4+i4C19QFGS5//9cHl60u12FgQlYbOzs7/1dnZ+e0J7ntfZ2fn052dnU91\ndna+/Wyv7WwgIZATiflexoJBbW8nvGOHp2kI79jBQKzZC/bcyTZugFxrV9YWTtXAsgVPHRn0bt91\nqJ++kWpxqGnZxBRBJKhWtDa5bO5oZO+owmgohpBkbFkhHYgQlGyefznFts6W2i+mhj4BQEIiVddA\nKhTDUFQsWUEgeWNQJ0MvCSjKA2DXS8CdGDV2nikojZuNhTVUpVaDlsNvjg5V/DyS0zFr6DgGUoUJ\nixbjdQgRTSUgSwRkyZsI5XLDtnXcdf1GvvCx/8Ufr/n/27vzMLmqOv/j73Nr6a6urt6AEEA0KHhk\nCbuIjLKogCDKpo7+cAmisgiyyCC4QFBRERGBRGSTzQ1QdESHzQHZ0QGCRAhnhjVAEkLW3pequr8/\nbnVS6fTe1X2quj6v5+mHulVdVZ++aarv995zztdgNt2Eb299IPPueJZ59zhOvfHxkX6yCRtuSdOx\n6P997pc69NANlhAeq/5J5Fs117FV4fZQRYaJx2EcK+xsmUmoYChzqX//JLUHHwRAfulS1p43lzCr\nTuBS/rbMJGhIxljZmWVlZ5aGZEyfNxXC+5UGa+2lwEHAgkEemwmcAuwBpICHrLX3OOc2PsVZwUx9\nPWaig7SrzCaZmmGXwgwLw4/CXI6wrxfi0ZnYlW099GXzA5YWzRP05ehevIJkQz2xGVEBUHzmF+De\np18nNOt/9foSSea/bjC/f5pgrP9+Bv6884Gsra2n+NA+ij341Yl+2VzIM6+tXTc/oN+Mxlp2b07x\ngFtOmA/py4+8GlJgDH25PIlYQCoZJ5vrHXEI/DOvrR1ykvNQ8xkgKuSKdfZkyYZDj8vfsrmOtd/9\nHu1/+S+e2fTtLGzYOsqWDXnipVUseHnVBlcnYOQlS4uvYsDQw4CK58XsMatloxW4xipzyskk370n\nADV77z3o94x2Lg6Mbd5FkMmQ616hz5hpxhhD5swzyS5+leyiRfQtWED7/PlkTj3VdzSRYS1p6+Ol\nteuX7H5pbQ9L2vpUOFQA70UD8DDwB+D4QR7bC3jYOdcH9Flrnwd2Bib/NONUyWUJtMzqBvrHgPcv\nudr1X//FjMM/ttHB3lBj2td09tKXBwhp6+hhvxef4pm37kSuJeounYgHxIqWIY3n8qRz0RnwcO1a\n9tt1/QHils116w5Ed9islqVtG9erYciorhAUy4fQFU8OvmRRPlx/f/8ST8XvR3Tm/8DZW2y0Tw6c\nPRO3rI3u3ixvDpK1WCwwJGKGdE2Ml9/sAKLVkFZ3bDwPYtZm68e5P/7Syo0eH43iXfTMa2vpy+dJ\nFiZY94/LLz4Azi5eTOctt0Aux+pUI3mzvldFLgz5/T8W89rq6KpR/1Wh0Rx0j3TAXXwFZ2VbD7//\nn8U8+vwKDp69xbAH8sNpu3weHbfcAkD6k5/caCL0eIZN9V+1GbFoaGgg/+abTKwBoZQjU1ND4wXf\nY/WXvkx+5Uq6fn8b8XdsS+qwaXlRXqaJ5R19rO7KrRtCu7orx/IOFQ2VYMqKBmvtccBpA+6e45y7\nxVq7/xBPywBri7bbgMYhvrcy1dURjNCPQCKjObv6zGtryRY6OBOG5IKAbTve4NDHF9L7jfOY99Qa\n1nZuuMJPNoixw6rX+NzrjwGww1f3X/dY8dnf7eqD6Mh3VGdsw41P8w94WltyiEmqo3j9J19ZzZLV\nnRvtkxseeJHu3hxru/oICv0ahqpncvmQd87M0JPN01AbfRSsGqRg6NdfPD32f+MrGvp/qhseeJH/\nfOJVstkQE4TEAkNDbXKjcfm5JUvId0bvud2Kl4nlc2QLY/NjgeHFNzvWDcu6a+HSaKWrwvZIB92j\nuWrQ2ZNlbVcvEF2NGe/8h+zixbTNm0/YERVmbfPmkzr8YxMaonTqjY/zz8WrgWhS+KWf23PI7zXG\nYNJpws7R92xQc7fKEdt006hwOOWr0NdH2yWXEN9mFokdd/QdTWRIxX+X1Ly+ckxZ0eCcuxa4doxP\nayU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5+2xMYyMAHTfcQN+//uU5lYiMl4qGMTKpFMYY3zFERLwIMhnfEaSCxDbdhIazzoo2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\nuuvJr1rlOZFIaahoEBG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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "g = sns.lmplot('q_len', 'E', bh_df, size=10, \n", " hue='RBH', order=2, palette=sns.color_palette('Set1'))\n", "g = (g.set_axis_labels(\"Query Length (scaled)\", \"$\\log10 Evalue$ (scaled)\"))\n", "title(r'$S. pombe$ LAST hits, RBH and regular', fontsize=14)\n", "axis(ymax=2, ymin=-2)\n", "savefig('sigh2.svg')" ] }, { "cell_type": "code", "execution_count": 139, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ ">" ] }, "execution_count": 139, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": 133, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ -1.50237213e+00, -1.47722045e+00, -1.45206877e+00,\n", " -1.42691709e+00, -1.40176541e+00, -1.37661374e+00,\n", " -1.35146206e+00, -1.32631038e+00, -1.30115870e+00,\n", " -1.27600702e+00, -1.25085534e+00, -1.22570366e+00,\n", " 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EEG2q_aln_lenq_lenq_nameq_startq_strands_aln_lens_lens_names_starts_strandscorebitscoreRBH
01.1648170.000000e+00566112.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ0+18871887SPAC212.11_tlh1_I_RecQ0+106765628.211770True
11.1648170.000000e+00566112.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ0+18871919SPBCPT2R1.08c_tlh2_II_RecQ0+106765628.211770True
21.2096651.300000e-2378341.858059SPAC212.08c_11784_12994_1_SPAC212.08c_I_protei...374+278278SPAC212.08c_SPAC212.08c_I_S.0+1602846.731705True
3-0.0955971.400000e-1164411.077528SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei...30+147147SPAC212.06c_SPAC212.06c_I_DNA0+839444.674256True
4-0.1530002.400000e-1114621.077528SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei...0+1681887SPAC212.11_tlh1_I_RecQ1477+806427.285140True
5-0.1530002.400000e-1114621.077528SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei...0+1681919SPBCPT2R1.08c_tlh2_II_RecQ1477+806427.285140True
6-0.2729484.700000e-10447412.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ4461+144147SPAC212.06c_SPAC212.06c_I_DNA0+760403.045765True
7-0.2968948.900000e-90369-0.188396SPAC212.12_15855_16226_1_SPAC212.12_I_protein_...0+123123SPAC212.12_SPAC212.12_I_S.0+670355.620902True
8-0.2968948.900000e-90369-0.188396SPAC212.12_15855_16226_1_SPAC212.12_I_protein_...0+123123SPAC750.07c_SPAC750.07c_I_S.0+670355.620902True
9-0.3371732.700000e-86371-0.188396SPAC212.12_15855_16226_1_SPAC212.12_I_protein_...0+127278SPAC212.08c_SPAC212.08c_I_S.0+648344.028158True
10-0.4730071.200000e-823791.858059SPAC212.08c_11784_12994_1_SPAC212.08c_I_protei...374+123123SPAC212.12_SPAC212.12_I_S.0+625331.908471True
11-0.4730071.200000e-823791.858059SPAC212.08c_11784_12994_1_SPAC212.08c_I_protei...374+123123SPAC750.07c_SPAC750.07c_I_S.0+625331.908471True
12-1.1513841.500000e-1594212.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ3633+3081328SPAC2G11.12_rqh1_I_RecQ539+202109.011615True
13-1.2670425.200000e-031351.077528SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei...9+451328SPAC2G11.12_rqh1_I_RecQ802+12367.383125True
14-1.3040873.700000e+0033612.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ4248+1151063SPAC23A1.19c_hrq1_I_RecQ552+10557.898152True
15-1.3466007.100000e+046612.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ1575+22867SPBC3B8.04c_SPBC3B8.04c_II_sodium205+7843.670693True
16-1.3324462.700000e+0325212.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ4523-77534SPBC215.13_SPBC215.13_II_serine-rich301+8748.413179True
17-1.3386511.100000e+0427012.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ4523-87534SPBC215.13_SPBC215.13_II_serine-rich284+8346.305408True
18-1.3403011.700000e+0448412.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ4291-157534SPBC215.13_SPBC215.13_II_serine-rich243+8245.778465True
19-1.3496971.500000e+054512.714760SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ441-15420SPBC17D11.01_nep1_II_NEDD8295+7642.616807True
201.5683736.300000e-2719482.089779SPAC977.01_29764_31069_1_SPAC977.01_I_protein_...2+316316SPAC977.01_SPAC977.01_I_S.0+1812957.389718True
211.5683736.300000e-2719482.089779SPAC977.01_29764_31069_1_SPAC977.01_I_protein_...2+316344SPBC1348.02_SPBC1348.02_II_S.28+1812957.389718True
221.5683736.300000e-2719482.089779SPAC977.01_29764_31069_1_SPAC977.01_I_protein_...2+316344SPBPB2B2.19c_SPBPB2B2.19c_II_S.28+1812957.389718True
231.5554731.200000e-2699482.089779SPAC977.01_29764_31069_1_SPAC977.01_I_protein_...2+316344SPAC750.05c_SPAC750.05c_I_S.28+1804953.174175True
241.1307935.500000e-2378642.843480SPAC212.04c_21381_23050_1_SPAC212.04c_I_protei...206+288288SPAC212.04c_SPAC212.04c_I_S.0+1598844.623933True
251.1945643.300000e-2298401.006792SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei...0+280280SPAC212.01c_SPAC212.01c_I_S.0+1549818.803730True
261.1945643.300000e-2298401.006792SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei...0+280280SPBCPT2R1.04c_SPBCPT2R1.04c_II_S.0+1549818.803730True
271.1787884.200000e-2288401.006792SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei...0+280280SPAC750.06c_SPAC750.06c_I_S.0+1542815.115129True
281.0248691.300000e-2148401.006792SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei...0+269269SPBC1348.01_SPBC1348.01_II_S.0+1457770.324981True
291.0248691.300000e-2148401.006792SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei...0+269269SPBCPT2R1.01c_SPBCPT2R1.01c_II_S.0+1457770.324981True
................................................
22741.1648170.000000e+00441911.526889SPAC10F6.01c_1200916_1206090_-1_sir1_I_protein...592+14731473SPAC10F6.01c_sir1_I_sulfite0+82284338.255499False
2275-1.1635652.800000e-1442611.526889SPAC10F6.01c_1200916_1206090_-1_sir1_I_protein...2779+138584SPAC1296.06_tah18_I_NADPH-dependent7+194104.796072False
22761.1648170.000000e+0035048.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...146+11681168SPAC10F6.02c_prp22_I_ATP-dependent0+65623460.368593False
22771.1648170.000000e+0018004.121599SPAC10F6.03c_1211195_1213553_-1_cts1_I_protein...85+600600SPAC10F6.03c_cts1_I_CTP0+33731779.947618False
22781.3771008.100000e-27019298.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...1649+6451055SPBC19C2.01_cdc28_II_ATP-dependent409+1805953.701118False
22791.3297964.600000e-26522328.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...1298+7311173SPBC1711.17_prp16_II_ATP-dependent377+1775937.892830False
22801.2602044.400000e-25818728.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...1658+635735SPBC16H5.10c_prp43_II_ATP-dependent69+1731914.707341False
22810.7316906.100000e-20518698.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...1658+623719SPAC2G11.11c_prh1_I_ATP-dependent90+1396738.181463False
22820.2304631.700000e-15418458.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...1661+619647SPAC20H4.09_SPAC20H4.09_I_ATP-dependent20+1078570.613614False
2283-0.6155962.600000e-6913628.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...1661+4861327SPCC895.09c_ucp12_III_ATP-dependent572+541287.645266False
2284-0.7493097.800000e-567208.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...1652+2571183SPAPB1A10.06c_SPAPB1A10.06c_I_ATP-dependent390+456242.855117False
2285-0.8125071.700000e-498438.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...2408+3141183SPAPB1A10.06c_SPAPB1A10.06c_I_ATP-dependent703+416221.777400False
2286-0.9305751.400000e-378348.090113SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei...2309+2801428SPBC15C4.05_dhx29_II_ATP-dependent905+341182.256681False
22871.7470756.900000e-30510535.787546SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr...427+351351SPAC10F6.04_SPAC10F6.04_I_RCC0+20261070.155503False
22881.7810614.800000e-28510231.528772SPAC10F6.08c_1219667_1220847_-1_nht1_I_protein...50+341341SPAC10F6.08c_nht1_I_Ino800+19011004.287638False
22890.8598549.800000e-2067711.714148SPAC10F6.06_1217077_1218228_1_vip1_I_protein_c...94+257257SPAC10F6.06_vip1_I_RNA-binding0+1401740.816178False
22900.6014828.000000e-1916814.163065SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein...1139+227227SPAC10F6.05c_ubc6_I_ubiquitin0+1307691.283543False
22910.3814839.400000e-1535640.287240SPAC10F6.07c_1218321_1218887_-1_mug94_I_protei...0+188188SPAC10F6.07c_mug94_I_Schizosaccharomyces0+1067564.817242False
2292-1.1973871.800000e-103334.163065SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein...1154+110147SPBC119.02_ubc4_II_ubiquitin1+17092.149442False
2293-1.2193673.000000e-082164.163065SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein...1139+73166SPBP16F5.04_ubc7_II_ubiquitin0+15684.772241False
2294-1.2414285.000000e-063244.163065SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein...1160+107148SPAC11E3.04c_ubc13_I_ubiquitin4+14277.395040False
2295-1.2571271.900000e-043274.163065SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein...1160+111160SPBC1198.09_ubc16_II_ubiquitin5+13272.125611False
2296-1.3107454.800000e+013364.163065SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein...1160+112217SPBC2D10.20_ubc1_II_ubiquitin6+9854.209552False
22970.4097812.900000e-1727385.787546SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr...259-218227SPAC10F6.05c_ubc6_I_ubiquitin9+1190629.631221False
2298-0.8755295.500000e-432135.787546SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr...2608-71600SPAC10F6.03c_cts1_I_CTP0+375200.172741False
2299-1.3135396.900000e+013995.787546SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr...265-104147SPBC119.02_ubc4_II_ubiquitin7+9753.682609False
2300-1.3229906.200000e+021355.787546SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr...259-47160SPBC1198.09_ubc16_II_ubiquitin7+9150.520951False
23011.1648170.000000e+0027245.611926SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein...26+9081194SPAC10F6.09c_psm3_I_mitotic0+49652618.840748False
2302-0.9714762.600000e-3321845.611926SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein...5+7431324SPBC146.03c_cut3_II_condensin116+314168.029222False
2303-1.0913003.000000e-216425.611926SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein...26+2211172SPBP4H10.06c_cut14_II_condensin0+238127.981560False
\n", "

2304 rows × 15 columns

\n", "
" ], "text/plain": [ " E EG2 q_aln_len q_len \\\n", "0 1.164817 0.000000e+00 5661 12.714760 \n", "1 1.164817 0.000000e+00 5661 12.714760 \n", "2 1.209665 1.300000e-237 834 1.858059 \n", "3 -0.095597 1.400000e-116 441 1.077528 \n", "4 -0.153000 2.400000e-111 462 1.077528 \n", "5 -0.153000 2.400000e-111 462 1.077528 \n", "6 -0.272948 4.700000e-104 474 12.714760 \n", "7 -0.296894 8.900000e-90 369 -0.188396 \n", "8 -0.296894 8.900000e-90 369 -0.188396 \n", "9 -0.337173 2.700000e-86 371 -0.188396 \n", "10 -0.473007 1.200000e-82 379 1.858059 \n", "11 -0.473007 1.200000e-82 379 1.858059 \n", "12 -1.151384 1.500000e-15 942 12.714760 \n", "13 -1.267042 5.200000e-03 135 1.077528 \n", "14 -1.304087 3.700000e+00 336 12.714760 \n", "15 -1.346600 7.100000e+04 66 12.714760 \n", "16 -1.332446 2.700000e+03 252 12.714760 \n", "17 -1.338651 1.100000e+04 270 12.714760 \n", "18 -1.340301 1.700000e+04 484 12.714760 \n", "19 -1.349697 1.500000e+05 45 12.714760 \n", "20 1.568373 6.300000e-271 948 2.089779 \n", "21 1.568373 6.300000e-271 948 2.089779 \n", "22 1.568373 6.300000e-271 948 2.089779 \n", "23 1.555473 1.200000e-269 948 2.089779 \n", "24 1.130793 5.500000e-237 864 2.843480 \n", "25 1.194564 3.300000e-229 840 1.006792 \n", "26 1.194564 3.300000e-229 840 1.006792 \n", "27 1.178788 4.200000e-228 840 1.006792 \n", "28 1.024869 1.300000e-214 840 1.006792 \n", "29 1.024869 1.300000e-214 840 1.006792 \n", "... ... ... ... ... \n", "2274 1.164817 0.000000e+00 4419 11.526889 \n", "2275 -1.163565 2.800000e-14 426 11.526889 \n", "2276 1.164817 0.000000e+00 3504 8.090113 \n", "2277 1.164817 0.000000e+00 1800 4.121599 \n", "2278 1.377100 8.100000e-270 1929 8.090113 \n", "2279 1.329796 4.600000e-265 2232 8.090113 \n", "2280 1.260204 4.400000e-258 1872 8.090113 \n", "2281 0.731690 6.100000e-205 1869 8.090113 \n", "2282 0.230463 1.700000e-154 1845 8.090113 \n", "2283 -0.615596 2.600000e-69 1362 8.090113 \n", "2284 -0.749309 7.800000e-56 720 8.090113 \n", "2285 -0.812507 1.700000e-49 843 8.090113 \n", "2286 -0.930575 1.400000e-37 834 8.090113 \n", "2287 1.747075 6.900000e-305 1053 5.787546 \n", "2288 1.781061 4.800000e-285 1023 1.528772 \n", "2289 0.859854 9.800000e-206 771 1.714148 \n", "2290 0.601482 8.000000e-191 681 4.163065 \n", "2291 0.381483 9.400000e-153 564 0.287240 \n", "2292 -1.197387 1.800000e-10 333 4.163065 \n", "2293 -1.219367 3.000000e-08 216 4.163065 \n", "2294 -1.241428 5.000000e-06 324 4.163065 \n", "2295 -1.257127 1.900000e-04 327 4.163065 \n", "2296 -1.310745 4.800000e+01 336 4.163065 \n", "2297 0.409781 2.900000e-172 738 5.787546 \n", "2298 -0.875529 5.500000e-43 213 5.787546 \n", "2299 -1.313539 6.900000e+01 399 5.787546 \n", "2300 -1.322990 6.200000e+02 135 5.787546 \n", "2301 1.164817 0.000000e+00 2724 5.611926 \n", "2302 -0.971476 2.600000e-33 2184 5.611926 \n", "2303 -1.091300 3.000000e-21 642 5.611926 \n", "\n", " q_name q_start q_strand \\\n", "0 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 0 + \n", "1 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 0 + \n", "2 SPAC212.08c_11784_12994_1_SPAC212.08c_I_protei... 374 + \n", "3 SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei... 30 + \n", "4 SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei... 0 + \n", "5 SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei... 0 + \n", "6 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 4461 + \n", "7 SPAC212.12_15855_16226_1_SPAC212.12_I_protein_... 0 + \n", "8 SPAC212.12_15855_16226_1_SPAC212.12_I_protein_... 0 + \n", "9 SPAC212.12_15855_16226_1_SPAC212.12_I_protein_... 0 + \n", "10 SPAC212.08c_11784_12994_1_SPAC212.08c_I_protei... 374 + \n", "11 SPAC212.08c_11784_12994_1_SPAC212.08c_I_protei... 374 + \n", "12 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 3633 + \n", "13 SPAC212.06c_18042_18974_1_SPAC212.06c_I_protei... 9 + \n", "14 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 4248 + \n", "15 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 1575 + \n", "16 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 4523 - \n", "17 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 4523 - \n", "18 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 4291 - \n", "19 SPAC212.11_1_5662_-1_tlh1_I_protein_coding_RecQ 441 - \n", "20 SPAC977.01_29764_31069_1_SPAC977.01_I_protein_... 2 + \n", "21 SPAC977.01_29764_31069_1_SPAC977.01_I_protein_... 2 + \n", "22 SPAC977.01_29764_31069_1_SPAC977.01_I_protein_... 2 + \n", "23 SPAC977.01_29764_31069_1_SPAC977.01_I_protein_... 2 + \n", "24 SPAC212.04c_21381_23050_1_SPAC212.04c_I_protei... 206 + \n", "25 SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei... 0 + \n", "26 SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei... 0 + \n", "27 SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei... 0 + \n", "28 SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei... 0 + \n", "29 SPAC212.01c_28738_29657_1_SPAC212.01c_I_protei... 0 + \n", "... ... ... ... \n", "2274 SPAC10F6.01c_1200916_1206090_-1_sir1_I_protein... 592 + \n", "2275 SPAC10F6.01c_1200916_1206090_-1_sir1_I_protein... 2779 + \n", "2276 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 146 + \n", "2277 SPAC10F6.03c_1211195_1213553_-1_cts1_I_protein... 85 + \n", "2278 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 1649 + \n", "2279 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 1298 + \n", "2280 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 1658 + \n", "2281 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 1658 + \n", "2282 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 1661 + \n", "2283 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 1661 + \n", "2284 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 1652 + \n", "2285 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 2408 + \n", "2286 SPAC10F6.02c_1206812_1210630_-1_prp22_I_protei... 2309 + \n", "2287 SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr... 427 + \n", "2288 SPAC10F6.08c_1219667_1220847_-1_nht1_I_protein... 50 + \n", "2289 SPAC10F6.06_1217077_1218228_1_vip1_I_protein_c... 94 + \n", "2290 SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein... 1139 + \n", "2291 SPAC10F6.07c_1218321_1218887_-1_mug94_I_protei... 0 + \n", "2292 SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein... 1154 + \n", "2293 SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein... 1139 + \n", "2294 SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein... 1160 + \n", "2295 SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein... 1160 + \n", "2296 SPAC10F6.05c_1214788_1217067_-1_ubc6_I_protein... 1160 + \n", "2297 SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr... 259 - \n", "2298 SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr... 2608 - \n", "2299 SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr... 265 - \n", "2300 SPAC10F6.04_1213255_1216120_1_SPAC10F6.04_I_pr... 259 - \n", "2301 SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein... 26 + \n", "2302 SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein... 5 + \n", "2303 SPAC10F6.09c_1220969_1224862_-1_psm3_I_protein... 26 + \n", "\n", " s_aln_len s_len s_name s_start \\\n", "0 1887 1887 SPAC212.11_tlh1_I_RecQ 0 \n", "1 1887 1919 SPBCPT2R1.08c_tlh2_II_RecQ 0 \n", "2 278 278 SPAC212.08c_SPAC212.08c_I_S. 0 \n", "3 147 147 SPAC212.06c_SPAC212.06c_I_DNA 0 \n", "4 168 1887 SPAC212.11_tlh1_I_RecQ 1477 \n", "5 168 1919 SPBCPT2R1.08c_tlh2_II_RecQ 1477 \n", "6 144 147 SPAC212.06c_SPAC212.06c_I_DNA 0 \n", "7 123 123 SPAC212.12_SPAC212.12_I_S. 0 \n", "8 123 123 SPAC750.07c_SPAC750.07c_I_S. 0 \n", "9 127 278 SPAC212.08c_SPAC212.08c_I_S. 0 \n", "10 123 123 SPAC212.12_SPAC212.12_I_S. 0 \n", "11 123 123 SPAC750.07c_SPAC750.07c_I_S. 0 \n", "12 308 1328 SPAC2G11.12_rqh1_I_RecQ 539 \n", "13 45 1328 SPAC2G11.12_rqh1_I_RecQ 802 \n", "14 115 1063 SPAC23A1.19c_hrq1_I_RecQ 552 \n", "15 22 867 SPBC3B8.04c_SPBC3B8.04c_II_sodium 205 \n", "16 77 534 SPBC215.13_SPBC215.13_II_serine-rich 301 \n", "17 87 534 SPBC215.13_SPBC215.13_II_serine-rich 284 \n", "18 157 534 SPBC215.13_SPBC215.13_II_serine-rich 243 \n", "19 15 420 SPBC17D11.01_nep1_II_NEDD8 295 \n", "20 316 316 SPAC977.01_SPAC977.01_I_S. 0 \n", "21 316 344 SPBC1348.02_SPBC1348.02_II_S. 28 \n", "22 316 344 SPBPB2B2.19c_SPBPB2B2.19c_II_S. 28 \n", "23 316 344 SPAC750.05c_SPAC750.05c_I_S. 28 \n", "24 288 288 SPAC212.04c_SPAC212.04c_I_S. 0 \n", "25 280 280 SPAC212.01c_SPAC212.01c_I_S. 0 \n", "26 280 280 SPBCPT2R1.04c_SPBCPT2R1.04c_II_S. 0 \n", "27 280 280 SPAC750.06c_SPAC750.06c_I_S. 0 \n", "28 269 269 SPBC1348.01_SPBC1348.01_II_S. 0 \n", "29 269 269 SPBCPT2R1.01c_SPBCPT2R1.01c_II_S. 0 \n", "... ... ... ... ... \n", "2274 1473 1473 SPAC10F6.01c_sir1_I_sulfite 0 \n", "2275 138 584 SPAC1296.06_tah18_I_NADPH-dependent 7 \n", "2276 1168 1168 SPAC10F6.02c_prp22_I_ATP-dependent 0 \n", "2277 600 600 SPAC10F6.03c_cts1_I_CTP 0 \n", "2278 645 1055 SPBC19C2.01_cdc28_II_ATP-dependent 409 \n", "2279 731 1173 SPBC1711.17_prp16_II_ATP-dependent 377 \n", "2280 635 735 SPBC16H5.10c_prp43_II_ATP-dependent 69 \n", "2281 623 719 SPAC2G11.11c_prh1_I_ATP-dependent 90 \n", "2282 619 647 SPAC20H4.09_SPAC20H4.09_I_ATP-dependent 20 \n", "2283 486 1327 SPCC895.09c_ucp12_III_ATP-dependent 572 \n", "2284 257 1183 SPAPB1A10.06c_SPAPB1A10.06c_I_ATP-dependent 390 \n", "2285 314 1183 SPAPB1A10.06c_SPAPB1A10.06c_I_ATP-dependent 703 \n", "2286 280 1428 SPBC15C4.05_dhx29_II_ATP-dependent 905 \n", "2287 351 351 SPAC10F6.04_SPAC10F6.04_I_RCC 0 \n", "2288 341 341 SPAC10F6.08c_nht1_I_Ino80 0 \n", "2289 257 257 SPAC10F6.06_vip1_I_RNA-binding 0 \n", "2290 227 227 SPAC10F6.05c_ubc6_I_ubiquitin 0 \n", "2291 188 188 SPAC10F6.07c_mug94_I_Schizosaccharomyces 0 \n", "2292 110 147 SPBC119.02_ubc4_II_ubiquitin 1 \n", "2293 73 166 SPBP16F5.04_ubc7_II_ubiquitin 0 \n", "2294 107 148 SPAC11E3.04c_ubc13_I_ubiquitin 4 \n", "2295 111 160 SPBC1198.09_ubc16_II_ubiquitin 5 \n", "2296 112 217 SPBC2D10.20_ubc1_II_ubiquitin 6 \n", "2297 218 227 SPAC10F6.05c_ubc6_I_ubiquitin 9 \n", "2298 71 600 SPAC10F6.03c_cts1_I_CTP 0 \n", "2299 104 147 SPBC119.02_ubc4_II_ubiquitin 7 \n", "2300 47 160 SPBC1198.09_ubc16_II_ubiquitin 7 \n", "2301 908 1194 SPAC10F6.09c_psm3_I_mitotic 0 \n", "2302 743 1324 SPBC146.03c_cut3_II_condensin 116 \n", "2303 221 1172 SPBP4H10.06c_cut14_II_condensin 0 \n", "\n", " s_strand score bitscore RBH \n", "0 + 10676 5628.211770 True \n", "1 + 10676 5628.211770 True \n", "2 + 1602 846.731705 True \n", "3 + 839 444.674256 True \n", "4 + 806 427.285140 True \n", "5 + 806 427.285140 True \n", "6 + 760 403.045765 True \n", "7 + 670 355.620902 True \n", "8 + 670 355.620902 True \n", "9 + 648 344.028158 True \n", "10 + 625 331.908471 True \n", "11 + 625 331.908471 True \n", "12 + 202 109.011615 True \n", "13 + 123 67.383125 True \n", "14 + 105 57.898152 True \n", "15 + 78 43.670693 True \n", "16 + 87 48.413179 True \n", "17 + 83 46.305408 True \n", "18 + 82 45.778465 True \n", "19 + 76 42.616807 True \n", "20 + 1812 957.389718 True \n", "21 + 1812 957.389718 True \n", "22 + 1812 957.389718 True \n", "23 + 1804 953.174175 True \n", "24 + 1598 844.623933 True \n", "25 + 1549 818.803730 True \n", "26 + 1549 818.803730 True \n", "27 + 1542 815.115129 True \n", "28 + 1457 770.324981 True \n", "29 + 1457 770.324981 True \n", "... ... ... ... ... \n", "2274 + 8228 4338.255499 False \n", "2275 + 194 104.796072 False \n", "2276 + 6562 3460.368593 False \n", "2277 + 3373 1779.947618 False \n", "2278 + 1805 953.701118 False \n", "2279 + 1775 937.892830 False \n", "2280 + 1731 914.707341 False \n", "2281 + 1396 738.181463 False \n", "2282 + 1078 570.613614 False \n", "2283 + 541 287.645266 False \n", "2284 + 456 242.855117 False \n", "2285 + 416 221.777400 False \n", "2286 + 341 182.256681 False \n", "2287 + 2026 1070.155503 False \n", "2288 + 1901 1004.287638 False \n", "2289 + 1401 740.816178 False \n", "2290 + 1307 691.283543 False \n", "2291 + 1067 564.817242 False \n", "2292 + 170 92.149442 False \n", "2293 + 156 84.772241 False \n", "2294 + 142 77.395040 False \n", "2295 + 132 72.125611 False \n", "2296 + 98 54.209552 False \n", "2297 + 1190 629.631221 False \n", "2298 + 375 200.172741 False \n", "2299 + 97 53.682609 False \n", "2300 + 91 50.520951 False \n", "2301 + 4965 2618.840748 False \n", "2302 + 314 168.029222 False \n", "2303 + 238 127.981560 False \n", "\n", "[2304 rows x 15 columns]" ] }, "execution_count": 106, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bh_df" ] }, { "cell_type": "code", "execution_count": 105, "metadata": { "collapsed": false }, "outputs": [], "source": [ "pred = gnb.fit(bh_df[['q_len', 'E']], bh_df.RBH.astype(int)).predict(bh_df[['q_len', 'E']])" ] }, { "cell_type": "code", "execution_count": 98, "metadata": { "collapsed": false }, "outputs": [], "source": [ "xx, yy, zz = get_grid(-5, 15, svc_clf)" ] }, { "cell_type": "code", "execution_count": 99, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(-5.0, 15.0)" ] }, "execution_count": 99, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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IKbHrBZlVkH3xfXKV137yRAA+FoEM/ApyePzqOLRDC1feKklKxCaUi0eUy6RltTumH1di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\nXQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "figsize(12,8)\n", "plt.contourf(xx, yy, zz, cmap=plt.cm.Paired, alpha=0.8)\n", "# Plot also the training points\n", "plt.scatter(bh_df['q_len'], bh_df['E'], c=bh_df.RBH.astype(int), cmap=plt.cm.Paired)\n", "plt.xlim(xx.min(), xx.max())\n", "plt.ylim(yy.min(), yy.max())" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.10" } }, "nbformat": 4, "nbformat_minor": 0 }