From 12cea6f7b03e98151bfe1d6f0cfad97ccf1227a4 Mon Sep 17 00:00:00 2001 From: R-icntay <63848664+R-icntay@users.noreply.github.com> Date: Mon, 23 Aug 2021 17:20:40 +0300 Subject: [PATCH 1/5] Add artwork --- .../2-Classifiers-1/images/parsnip.jpg | Bin 0 -> 594365 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 4-Classification/2-Classifiers-1/images/parsnip.jpg diff --git a/4-Classification/2-Classifiers-1/images/parsnip.jpg b/4-Classification/2-Classifiers-1/images/parsnip.jpg new file mode 100644 index 0000000000000000000000000000000000000000..30678668cffe7cc2daf55025d792592773e78fc0 GIT binary patch literal 594365 zcmeFYXH=6-7&aJ0KtaF)(m|z3m)?oxr3;ZRO{7b2(n%sBptMMbP$In(>AfhuLx6?op6aP*74myiZB>fQo|R{^R=( z9?{U!(%z${qkl|8|B!~3=HDM7BEI?NHpyKQlDjmN6qGdox65@a;K3a-9*Q7hqGy0x z4~U2#5M8$e*Z=?`l7B}_L zDJ3oQ<{w2RWffI59bG+rgZG9;mR8m_wx8_mJwAJSdHeYK1$_$+3H|;fEG9NCJ|QtF z8J?Myos*lFUr<b$(PAx7iudJ@EZ)|QI9$}A9 zaHnVI7ysfS0ucYNu>L2q{{yZEH@I%yzD<0a>|b0&x4dsE@q^nWPlZVzzS1HycYE|q zB=8Q+>*$QKKX=(hwGU`5+(*bCbBHZ+9{vmMe<1t62JGwqBV_***#C}e3UH5@=w|VV z9{_*=f=*`GbHIP~zd87i1OIX0KMwrIf&V!09|!*9z<(V0j|2a4;6D!h$ASMi@c%Lg zVj{u-Mm&<#MjCzF>dD?jV>$sHEE_XC9)im(id_5luUq{_>u*}+hAhvu_i^HKBNSAb zDGd=zk#kuz=ReZBWw8)Gd{@u2aat`T&AmOB-asD&&rFxXIPgP;zX#;Gd}{b-J*7I$ zy$KvmkuMv)4KP?dBFo=HsEHyvA-}N1lXd4|?VQIkRR)wvFlA z&q?g*L3slbxzAoB@(Zp;vzJyvcaov5Cp3?V3p#8F1@*yZxz8Cx)}H>PR)g)@Qz-4Q zb}B`koUo;_T3iEsAf9l{#KIFAgyT#eIni#%n}Ph2M{H#_>5E&>v2g7I-4R4cav_85Fn%nE5otmSwC7m2fAu%+aRS#5_L#jxXrkOk_Sh z&akP>E^QGyW5>N6o@=g5w?`}$Qhx4#!3MXTVu~3pjPTRqN8R0M5yH}y+vF~8YhYt9 z|5jXK2Is{jSzhKtFdR<($;Df?G#M^uY-{3*6=wZrMifM2fri%r$7POGFfV5_ zOcZZUijIDD&G9wh#m$%>J>B>VlLj^!A{=F3-t*X=7y~*cNQ(^B`WeV!>p$;8w-0&V zIZk0|+%>pU5p%TPg>npuL>^Wi`c1oYEK3zHBeW8F=P~(Lr2|1C)JrtY7R$0BeC)e# z4;Lip{dJ*EiLSC|$E}44zMAqv(Cu1(Qm6Cqf7j)*4O{F|EiuQ@mDl?`>Krao+y=Gj zV4JRVae$bu2^Ce?_M2&)qxM*eM?(0D}DMg zj!%OUdly=`rM{m<4NahnKcP@^>Z0!1%(CXW7m`k_lj6+v+0nnxb&-|>CRn_H_<+#% z0ZC}=#LXMAI%Yy%^fkZip}1`K=j;%$XxNnW+(Y#xGfX$aT%ogyHc9+TNmcCX)qyzs zhpyk{-Ca}lS#Wckln69Js2^c1UN1DFOQ-WAE^Ppj^I}Uia(a3*Do$>cJSJd!|J6?3 z1S+#YU?G;oY5}GhH!1YZhw0R|h1TUo20d0XuMgj`vwHLY%^+md3eNoW-_3!&qfF}} z@%t+Ly8rh;PCx6Q;udeL{qv&Q`k#K5@b@RTe;#aKjPtkMn-`L)ZAxvRdtMls|AfQY zBrtY>ZR){+NS!?CRtwU+C5@~i(PEa?&_%B-g6-^n&ZU)a=OUuS44p6U`?HR7qD;}i zcw^!)M&9lk@aa{LR8iEki1@Leb!HYuyh4@AgvD325uWx)C(wD~95b>^fR=8G{pu{w zw}-H(p_hw`x$Lk}2(wK>%(11(y2@{jW#Y{9E48h(bf1383ul|2v4q{z@kz}US z`l0r6KHnNqt&jCC%Sr}p@if44n3@r3f>yFrnaOMZu))Z#I+{An%ik9~5gmTNX`H(+ zml9r2Cy{S) zar)uf@uW_^fyx{@0Sm@N!Ip%wic=Umc9&cF#%{jv`)+sq=DnB0`F5%cfk$DuWu99P#-y$GED~Rn(Aa z$ONm2rJ7lXyA2h2Qd>moH-Dg}&y_!Q`wEGNPfkhSX7h{8esZC&=P|VnCe3e0U;4$9 z!8|)i@oe=z7y2)M9xr|A!o#~Rq4#@n55yreN+9PhnsA?v5YecU1S`u<_vg1y#Syqw z|Gk^Nmn+tcW%73PW~vV69f>9pUc-7V9=zEl(~fni^{0oMIW1UO4P$ni$kq)nL;alh zH7QLh;M;a&Wk0~BwcA5E+|wYhrTh?<^V~AB2j+?r_ z!9H1QrHXJ11JiJvn?Tj1l&k?zO#u^6>_Yq2wsvS)6>B@J51o1+xnE0w^M`*e))bK! zRma8F{uI^=zaYNQcILhYVBQlTg(E5f->Yz04X*Tg;C#t>69T37Iy&l;VZ7&I%2nk8ZTW#^!iFqeD!*e?nSIZ~ z(!5h9?9aNrh|#>6fV>)xf5IUG*YUJo-p>+M7L1+|+?@-7Rno64tYuw-n;-``()t-m zBu(4XK@IC3S8q}!Yd#DLK{6_#Imi3hV@Ocx8lZK_#0O7zHE%0WNL@?8wd(_F$wtLv z#jXL;!Ubf^(eHX*#KyeX9L;q*R|)mHY2$$wgLrY|$| z_`D+Mcw41H%=bxj>}Xjrux4!~$Hn^s%eS>L>CmprQPwISEHst)>B%~Kg#JGm29~=6 z&t`miNf)l>;`4AjaZ^r4e{qbAn?R=Kk8Y{n*uh4B z+t~a%^X{u51X>oa0Sj@zPbG~A27L2`tU$FIk~kJbhy#^sMD*Tl?Qw^MG=srD^QG=J zpjcdbm(%m;8t@fZRK#+pR^Mdzykbafs0tyv)(SL11JmaB5GKPIqT24+(O6UMp&XZO zvoj9fJ7W$weeSQK8pg{a=`TEH&>xl~oLe(ir-ObP)v)xGcM z$+FF0b#$Pjt*kLX;9*?$Sa&bjudYLb4SahqKbehV-Wa;T8B}89!VROL#j;Nn$Szciq9l9vQ#stmfumUOo>srZqVUvTEL;w4+sHJMkYOJ9N?)I(=8k2IafYs%N{g@PFa`Cys|0G_0?97 zmiU%0FhDZKsn1Mm_N##LV2?yeH(kS;@8{$)Ycf}AIqeS6XeBR2Up+zFx?Xt4QGC*; zPf)%tf2mpUmhhjOvyr8E?3&DaDzzG;p_U4|-^NTLW_Q-fdP#w}_iKr} z`2$IQ{DrU~zin1lxy6Ml>3rJ=y^hXPm zobW-ShH(kxLWG#iI3oZd_%Ao-%W3X`c(ybM1pkWA)M!?s!NK~dyy{>!!L>q_amZB}*)M@yphh>s zt{6p^yr&h$uK{;EE7sP5hX-EQfO&c0-LQ)t1@$Dg2l-p>3PWZ+h{6TD;J_ix`F1bO z^v1Nyx)o+=2%T4ZewUk}aKLNvj{emAV6y@t`Nj|7y9O{iJf3@WnAJWNx9${`8+QNg zH2^!P$V@8#z0=QNyxi0yxV&8CbMabXhv@2iCc292ydJX6v+ipZBd(Y3MV$ zp!8-(eLE6zq_n43F{As_w5QQUZk<{5)m=UDUokNK@FbqlSB0%v zx6o(tlt?(y`v>BX$kq{I6JP4lJJ=RMVm)9kHrYKJaS;~J$ubR8>t#4z-IGsDxdsR~ z%FLi^YGr?0y+aHl*2=3-;$Pw&nEL-^l6=9O@At3d%Y+Ogok0_exO&fqn-64UQk)88 zd8TVzS-^JYkKM0op(NMU z^->(Fl&PMR@Yg$YxgAE^qY&)C;*7XTUasloIp}vcw*MltEROlspQGdzkpilFl=Io1 zDHvO0>AoCssM7%*`;vbZ{{uJB@1rm?2J-1jPr{W>9FmRC%duSCtO=|L`)RBEu) zgRakzPFNJntL#W`e&3;C^t(Dv&82o~dwY}n?N-a9v}?LUMT1DWLJ5Sjt)*h9epO_a z8*jJDodVcCIdod^>16@^hm>%)bF^5Zbu0Z^l5=QckWu65WKEw$N5uS?du=rTS)5zuckci)5G-ud0R^ zJvh;um^Qor`13suz$sZ6T>g_-r(AcV)k9_RLD3NT0p8x`56l5=wd=HL3OxPnLVh_n z9={Og3NZH=@y}=I^xA9C;GHV~nK%#^ml7Yer!zPb0sC7At#ZBdv5TdC*d^z~UEZXv zJosK-$M^!GDt|t2d-Pb;N2)0rCDABX5i-^5d+yPpK~)}EA?n)3&IfD7Jga%-vp)_0 z*Uy64e%^df}%(vdsSmeb-MO+KnjaDi|-#h7DW!GrG?gu_oaa z-PJ`3W*h8SF0@r$>0xu`iD&S7AV#JvawVQ%a1J%?xrk{FwZMGOlH%TcJ*T8X{}EK> zUhtU9}x>l1SnVNtoj z@VOMy{?LBipH0{k;Wex2pm3xVE5dkK9(8z*F7=8=*z7ttjb7F7y!opt%ObJ3tqxyJ zeD}0$O;`uR3(S$c)M$I|MI!U1juyJ@MawY*r6s&K(@FFw&aBHp-})W7Dn(ZKRa9G| zYPBbb{Wgo#`ZWM)8od-jVcAd3gV)@Sj%PwsF^w z@<~G(c#HD+qZ6a1$Spp~03ByzXY`O`6z|kl!UE@&B8Ct+H zlBKAtzA*300Lr`3>N0znSN%>q{MbIU8A^&Fk3@0qJI0wAAzM77?o#aAYR=D0tj8eY z!$qh#-LZH?vK-Rk;fR(%zXnPX7%4jl3u7eos_I7H|8wpCUzRtr zv%~gEh4&l_$U7`yg7-w0b~L5*s>s2h-yw?2QI-`ts$JU}T5^(${4_F8FR>x5%? zXFbj_G!+v^Q`dkWkoGar=)tX5UPY&fs3r&QUE*Ifov9a)_&*9y+|XRQgU>f_|yv$UB z1KTbKbKG&^-bRwYXA1q0Kvcha5gSn*TT&Iub%`@qz_m_Z-AtT zXH9Pv`QpaU6ki5@Kp2@-dCEf>3u?7PaK(=ms`ggh>mJzd0@j}cWfU7c&lUCgWl^8y zm>FS6eGT!aN6&idy|$pdAn6M9FSAlRb^oh)AqIV;UeG?3t{Td=WmDrJE5uT3h4uKJ zzGh|io`SZS)G<3SnAKJ;Ec~!*S(ADjG~Kf?;T|>PZKYFZ)`S?$oRJMP6D7diis(;h zf7IL<=pi)RC<`k*U2^Nqrjh#noSV&u$h~Yjk^&BTaiL8oo>*x-j@FzYa5NL#S>fM<7)-)m<%B>ryhMJ&V1+La@F?s`|eg2ALi zLawzYp8*7c&M9;pp**@^)EEcthOc7TA8n(OY8Go{1CIwD_UH3)3$#skH^rX}i1h{m z75I2c!$iv;_3UfTI`>-j40#Ued~m@v+DzrfW4uSZF%#1ss#f}gOrGMUw0`g`$}tMU zVpN)jbg96~O32lXTUMFH>#Y+>P~170NJB2`1U0bM7N9lS*hwom(jP_e5uNF}&G||L ztl0ckqFi?J?8`NL>2{nem44O(e)ioUG_4|?foOg4?a;;E4&uO$eU(M|A_U3Ur{Rl5 z@NxL5we^vhZp_A~s*&mV_00hhzQ6N)gncdDkgFGsY<>=^RewIJ91rr^CXZ|DIM4s& zb+9;&Rk-u;BW@{nH~8gDo)@sE5MlS`s8UUMKUPcS;hT8vmPl(I5%_6==6==uR!Bh! zT#O?rhGRpSn5&4h?JiA1&%T~?M1)(IOEQ+Z8tf~+HrBt&!*%R^)zUq#qc6^A<@_oi zt}+qO4|XNdHGJR(*Ef%dQZ8}e_s=ig0acVq!Ji+!DN{)5khijV_uwws*_Q#GPE{!& zI<*-3EgFU^Gt}wmy(khAI+Nu2L-%-dygJ^+B>|4PSJHi6NG+Un)TPj{fu)V2HlM+O zFuYRJ2-M1vVEeZFc3=c{237p`G5@O>pFy{GzFC-)>^Y{dcXP|M^(*(Cf)cxHaPbsB z)7umB`{#L<5gzZ7X*Gp4u(Hdr65Yd!gebEwaStTZy2wSN*2TWQ?)$2mA76o&8(EW- z^LP(7Z}_0-9#dplgNp5!zN#G9QD&!cc23Hg+KK=B_dL{FdOhr;g=kOL*zg+&4MIXn zynmf*Z_hMvb#`zDVMH75x&89ZYz1h#Q*?lHhq< z$@gfF=_O6)?HZbXi8;y_duB`92HFi<-!fGen_gu*#;*h(i$5&bMxej8<++r&`#Ui? zxSy*g(ziYd1Ie;n1Joi^3SEh4+XJl5iYyPHf9P1BG*&z0QvEibe)=ate~{Fl>Mr-N zfd*@UqRL1{aZ0($Mw_|)GM_T_Yq`SrctVX|*-c->1$t0$cz!x~?=Ku(MTQ=+hM&|+ z9m4VP-rl(UXm3H7n!U?L0|>;n!;T`HOu)|_sTjr%CgJB?Y2ZI8?vbL=_D%Ep|_Y-Xb1AK z!-pql2;}^hfk(;)ay1g@19i_|;YI!eP{kk10b?7Fs#N|WdBZ>s`&ec4LCZb$9}c>C zyI}a&rd==&wY>%@aQ^5PB|B1Azq{1ffO9>}8EU5vswXYVe``BN%R05B?^sdkXyA7G z>D^ILX{@5Q(I&1EMlgqfQmx39?w{)^cIur&=L2giPb59k)T$GFcgj21* z@9lpc{JhkpUJt_u*E@XoybHHA_bM;*=3bkl=2oafVp_?VkL0(Hu*;_*JB{3jK^=?` zgg47-euG_n){`9}Y|@}?0VkB4016b=@^lz>(2w1(hGp(SdKR6Z2_wVW#EavsYivfZ z0jTI>$sa9F-;ZIzS8Nr-bh~qc@W0}Xb!n<$sFxCDPY91Zw*e&7_ln_YdfB1|yKi z(|?K_ELdziZaZV&+c3S^q?ZR>+8%U(1-Y8_{(fG4u5`lf?NWIKe%4Y{v3sa@q(Gd- zGa9@#)}X#C+k6eM;d2?OSciR^FGGakeeW?w)i3|O_$SHw^0jkaG;|Vn1}TB%_)|v$ zEvWC<%~PMKiutF#s+u;oO=l|l@yC!sw;KIYIOwa?ios}K?BD{BvF$9dAU9|M_`qIN zrGT;;As5j#C4n5|?(of(eRTJ=Chyir)bz>LmF@EQ*}Po8@b7q;#_(h#;b}0!(5&S6 z2*|zTk~`|+v@ej_;pXzJk149K_Z1nI_F{68#kx^r(UeWkrN!5lvW;Ye;tBW307Mao zL<2)E9N}hd^Y^C8ct`B2xBAjU`;0EGSrCAhKH>7O%%CDT`QMG6So91)T$Br?or)wGK z(4IVN*E?P7?}~IC45{P2II+~X?_JU0VtJ{g^WRv)5`p_#wa0&hOoa>hf` z1MmK6wx@!-d1Cvb%z=6}E$&2FLN)v3>v|8Gx6l*UmygYVzG};i0UG%xW%CMxR#6ISL@&0&I&oU!wgFcqFAW*OKX)bu~ z7?pP9;8UQSLr|^iX%BCpxl6}7Zkjpc5es)ofHo?cRTr=` z9Iins5yE@aOMGxW{ayi)I`w;teyMCFl7nQaVL@K#6`REV2(M@5xaRMr+L$T2hy$>l zVsB~?s_=(5m5fe2!VYln67!GS!`PAe74@(DMT%n*@*bL(uXBax>%wJeqm2^-?Sy zB09uo^vhXdnOzK>Oz+O4&Kgtmf)E`rQ}^yJzTg^Q?^NpyazuYv;e}Y9>oj(BQrKdP zEn)CWv+sl$p@A2lu+gbH`iDNmHH(H<&I#F%XpR98cc^PtW+1eO|srZ82SAfRWw4W6aoa!=?l#$svEL zo}ZgSB*O9S2l%0sf-+n|ruXxuE8@DByxLi(f4cj-m{){7#cGCCK~i7 zyYY<1hX;$40>%ne#i!mTztgW!8iUUsxjf&{^@t){RcHGyIO{r?(fqZXAz2rn`gw~7 z?fpRc#r%WBiE0x62SbN*Q^G#U9SVE;^F1bQTL-IWTH|&yT~jTd(zhHB1JP9u3C4X- z+ADpmr70*Ljn0)SmdX+bV)Dc<1`XQ93bb|IJawlgi)yX`E_N-)L%gLdH9mYyl~syD zOsmv2h`sx6`j4%L1S!EK{MNkl6jCOPT$wQm4Jzc%Gr#;-|4-(CM^wq~MpLl)H(^dx zwP8l z)6k{;vLN0k<0#fSdq&>=5w8&c0z{n2^ffR7I# z@qctzk-kCav%K`uhB5*xMOtaeK?S9tU3`>IK1=C_JE{Yp_zTGH+ci3>XE&o zk9p8>sb6x(9R~?aca9p!Qbl44WYjMc$iUfi+?subI`?0zo%0W#EN_a4)EEnH-BPrP zd?|Ebb+MKK-}e6JR#{2h>*+xL$_7w5D)7G@4J*8rx6;4&2qSO(Eq;GE@K3f)yh zHLVf?dU2o1ozK{waL>R&m8`ua`ZHtBC*u8w<5nk$D+bR5#0EVQ29!`0p7!D1AMEP5 zGJWd$@}Fl~2YBa*kZx;*C|&~+d=+-zbmu_ckNJ=6I~yX9i-v+UGq7yJPDhc$fpyc3BIuh zXQS@&&oc`ec8I!i7}!=uI=Bol@RW!TWR6;hfE%%^E)V?q{^Hf?rutdznU2V(*?lA4 zu<4uJj`vX3yd#=#qZFA3CbpXzzR@x*@`ap6!bX+NpQH_+DvTxPD~vEn-cC5p_RnDY z7`Buk7-KT1)^XI_{-+`A-N2@vb;DDlS3m7(TfCg|DE2o^V*B%TV!~rFdjdKxI_hv~ zc?TXOhhaqvkA_32%}hkAKU!pPBPY{&4&g(Hh=h#yssQP=h; z!q0&7?ZsVg`p5YS#gleAmvb{?8lDdksPd@|2~D?|QKLl`CBCTK0K^}QajLbV51H$$ zczf8Mz9 zXOyz-@|Y!8UtI&vEI~GQ;;qrHZ4tV6=WJ@gm?S4P%Z5$Lew(8`#&Q`1*E<-;Q) zdr!&+d4)tB{4Hs9hCJrtt)$OW#9dyj+yBLR@mB_xjV;e*+A)=i*dg?XhR1AK8x7=5 z{+Z%Yd{_({dIJ9RDDV#`uiyS*&vcV;&N4lIz_pKNp)zs%g3)~@WtTsQ=nHFdKHOrR z^GH$Db@_LW9TVo5wuAqlwGtj#q3t?*9>-v;g2@B8UM#b&A#s@GJ+D%0Bh|Up_lSO) zh^y2w@-D8lhUs&3SYvi@uZl_ZXqcjNvXs~$bTYe3UJ+Co|F3Yg5!T&{=xQWy_d`k+LE~j9u$$&!aE5w= zuP{x~33=nHJ~QHKhhoQxt^uD>&WdbM?n%4!w-JrIzylfc2y9GCxJ|vawwnR&CN|re zxTU6EOXwjSflx_SCMRMNH;tsqzjF8FMPrXkRdv0qT9A#Ep?Ash*wk)^{(hEJ>_;>p zxHK0ZlfPTLqrxHQrjALQ$j3E!U^dmOHRBttxkt(!rGx_35A&Sx1?eW?L2%QO?F;nC z^!u`aE{GVai$yv|?}=5lolln>I#Qy6=<%ik!pMQgW+hPDTo!?b&%I}6HsIK-u7dus zizLf^uNA!KbCa3_Qj_aAUiw`=Igzoz?bUPA5pWH-bhRt+KKN&_A-Tkpo`da89SDmA z8`6!QAfFIQvQ!lSXDPwG=l6j7M+U=IdbDzVl$cLSr5 z-Q)x+LL}q~8(qNDno-W5;<(VK6|TMtTIZR-=$oiD5pqmwn|SxRb|>e7EKs@T#)ymJ z5Rb~cj470bzoMz*FVtP?iUNjwCcrOoIY(Xj&yv?)+!kKmRIzfZ+cXRR0N;R0Pr|IU z0@ERJ*3w!-M#eC{?-|{yNG(}7qrOKpuYh_A9o>7S!=Vb}{w!<3UVwqffk;{4kou_yb zc3D<;(4xsvhlha68S`8}zV+-6kwNy`DJEP1w zuSouCYQpg`HSQf=2#eod0ZpZ-Ty>r8E(NoBE$P-XL&3By=?AQ&E zTW_`8MoejLl9tCWL65|ZL-O@sI=-q||7_5zrs=A5A z^zL$$3wwJ>^Q-o7TwpfWJAuIoKzclrV5qOCVQ=}}-O_Py`fLWka_y6!iUI2dSM7&B z2Cb~m$4WheN*p9`E&>tyhxA$6NtQoV`BiQcjlwUYC~T~1iIWy zwrrLu8!C72!ls42($ok{@xE-VBq^sOb<>TBs=t^X%1baiz|~Rz_{<`!UroGoiawm- z4j_H!3Q6v;ULvKQTq>}9h*BFGhqgikdzNg>b`Im*MvOGvTi)-U=AAL71ny$y8i{dZ zhr$U^artBW)B->GoSR%%yGlrQkC*N5SJ^A1Wi4PFIk_6BR;c^AMWq4AFRT+4GycO zEW~uot=@ZD2Ju0N?XS3+J1FO2IeyG;kx`;AqF9C0)aE6N2oE;Tek2#$eEMBEyR2w@ zHRsnd;+G-y5!xAVkVk)`cqU2u`)i-4loKh8pD(>@&RaE#aiU*#A)ILQ9x2=e+VobC zsI;&ChzN$5`PS~>Os%t*Plki+-lQ~iw4fF=I9Q1p=TC?T2H6O_Y z19ER`%;+uvH#KHFdb*ZP=0;AS(Ow)k#%B2>$B^D*di&kFHv|1?9&d%9B>B74lvC%c zg>tSLnOGH?&y-q(w22d%7F$R|%RS6%9L&#Za|SZ>2L53p*H^@E83Wgg?9zdwBwPLt zH(Llp8p$IX*7u3d#&)url&fR~EVWaSS$MU#!Qqx9Av|w|(K zy_E*`e8?&~0t*Zs=iBgV}1ct!7mmz`PAJm@;6SLp_V-|>md75xn|o?{lQ&%vjqb_(y2zG zi+8P5h`}Tq`3gkI)1T?mrFS)D5^eaTj|p};F!mg-#o?fHt>_N-UIX-M_?pNlda<4{ z+~-&MjjLXoqw6;H%HfzxlJzVbE6LWRo#juuZkL}( zd{%a*69R1NFsO{(J`3x}P8B42M~x107mfS{5A-^r5lm^ZEje9;rgVuqp9Xau+xz7Hy!2-vALK|GzH$k!(9H}`&~!X?y#S;vk#;#kgD zPjup2KU?8>J;yjA?s0H4Q;yt%#(THj&zx#kMJD2DJ}%?)D<~Ju;=OD!%;P^i$&zvb z5mDKX5;Eu8=^o@OhRqy~DUpaQ>ouhSew%n)R^7!HZDoaJXa*N7aq}JDMEX8JJ0Qw@ z5vf&Smp56PkCz)`Y*p}tWT0;p-~wZ8`yzp)y@*HaYq!JqijMYTXU+#yIk5h&O;aiu z$6X15*_Y;6zSvrrnHqunn}CICs77Cl!Y0mln0PO)OWnw{_TLx7 zqhe`WEb}{un%eTh8W#5IvmWNX4b)ijYXF^C#@V1d*e*$H`Z$N4rEpo=aiUmG1^j6? zb}rVFq$n$G+Wk$x^kx@2a&F8fO5V=2DXGnCXJjhsdCu0YC}AZHNrc)5uyo$Q2%vF9 zg*u<`Nuli|&(q-=kVMf{LNm~Xg1xxV|1jc7L7kbz5Gm`nubZ3xg+7Zba?B>YG=dmm zR9V?kN1_A4Y3MYEXvDp7uJ>%1{x1<3aVM9t+!EQ&bY!gEYTlW4ujb2+;MPX zF4RaGwe^@S_9V;oB;ROD+^KFYwSwExxzjBy_FxmwOZ1JigjE6MVpR^npt;;y-~r)tun;JEQbwfD(sDm z5_gg_newDFQYce}YjNxvfxwdYE@26)x+S^(jS&vBgm zq^~%1ym>E1Mq^QT5^AeOi&EB(tqJH%0W^c!lAXaJv;-B+A7gj zlo(X3_dD4Ofq#tW#Zu}$2doa6xD0qirMr}9I&J<8LS-x^{I4o!B5oW5=_SEa#vc;< z+E8-2zsfDO`Q9J3)*!mgWoyjYb9P&Ia`$#Ll}~c{13{o1p=5-)a& zVj@Tn?Pab~;UI-Lh;Gv+l{9V8@GrbwN&1){qo!|h4o4@;rrV6RGmZmw!b17F0)Thh z)I46%@jcGDRrNi18dJhdRq3&*G-|N%O%P0K=ev7`0?(vI5I)ULd_?~^C7N{3V;yTy z1_}?Mk{hIPxNNMbL4U&5QU&wN)*i8ljHb;7OjK{!p+sKW3DC2}LdOr$#H)d8pTcLT|wh-=&nplD8Hn??eZALIc{(E<+f?uyxe1Pemg%kX!RYBnR(pv-zcF3+>WFMsZ#MVF%O&qF*d06v z96jGI8Obu+yB{?*$IhPuZG5?*&>TPilTfq(nvQ){KME20lizE&TSalFpMRFn_GF7&Wu5}w|eJz$LqAFC*D9LK5z17S~2nulWuwB}9_*>jjyzdmbFY$MGf1E}&w+|Z(mt_VSAY8pKaMu)r5eu-Ih>a?zZxx|T>(~Q ze+7PlaP_&*slhJs@!Qi;^Pt{le?rX(>~{c@`s-_eJTB`V*f03r`Z;+QJFIfx#cScM>3$~~khp!UUFcEjGcQI7nYdSZZYau?FjoKp+6rVaCXhIoR73j{U zguc%KMgrd4HN_-sS-(^6xd}``_kTGQP8kyin)T{sXh*7Q!|k=4fO;8t1EX&T+PmSwnUTaB3GZo~!Z+>%Aao}FPQLQLTUp$5XMaihRfzxM%ZCbfAK28l0c zv{AUaKDxR+3r=L&USd3HnJQ}6SQ3hYuuJ#rYbFR^-Weml2EZNzBYks&e%UKLM+TJwdr~N}_i_JtS=W7{vy%ID6UspnHDSZT!6-{f`mt0(P2i;uN>9_fR~>)pp(}Cn&W|2y3boib-ZND zWqAk^=xe|Zb#cF61zX-SX*9)HhKf1m?@VitQjlyfLaG@ulsz_;iuv|flu%=twv&*!jb_QROJ$Z6&n zf?nVG!xk^}cAYfv3w1wP4ut*j(s=S2(Yfg%@GorP#zH+Ao|F(sTlqnM4al`xrC!Q5 zm|-hxiGclRrktASUM&@~o9hV#wn9Dw-%0=%#22A8lHZi#4%? zLUh@IdNT+S3Y>;M?Ct3s<>RIL({F1>rw)49Kk~ilY28z+fanp(QWV!`L_v=zZQ`u4 zM(QWPY|-v!_C;QwT0#40t;94;gV5LoF|PQmR)Hx%F6M797`|6t;^IkIV9zIyT@JBOz#+%W#mu1JkP_}ycz>|{SaRmnul`XxRs>EgP z@?*2LfrGdLS4nEMD!t21d;I@G-g!Q<-M)R8wz#V;t=h9KwW+;HwKYQRy=w~rK8R*L9ws<2cdhi3LGd(oj zaiOa>JiRk71L;NnBQChd)pia-M`*&Cw?f9XIu|LOw*G2cQibv*a_K$wPt$wo(B?^U z0q-d@D%H;~S=!|BJ1l=sa4pvlh)FItTGn@OTIv|Oz{FvWXeTeCN0ZLz)&Y+JZaQ}Y z$ef#MTmO-KPBhkiwP5G`yiV+m`|0Ub zCmDS&geNgIFw^-xkqX_MB~inlqL=PtD$JoAW3j=rX`I7{4!^G!*RpXB*DP|%O_9^O>&8yA;b8nL3J0g|&3_>a!Y}(|& zv%>3k)`^pH(o?5TgI&v&m+sAxmgNoy{Q{zEA4BXbrAK2IWBfD9TE^M21wO`T`kX2T z`MUjnPIdYF5&P=1nsJ-zSNfqj>f}-}Y${-*C!4`@)(puRcs|PFJA4;~_T8JJ*peQq z9

j$=H35Zu|Cvam!E_k%8hv{e8WG@HEQfjd$pDF1dcHJ(ZK$4~Uau;omo?mr1wI zD2|GW=?KzG<7#Wz?C%2{0Yo994Zr1XT-9j%2y3#FEYXUY|xx5y;b@ ztA!X^UjMm^g1VO9qrT|Dmr5o4809_)RgrbD-W_jXh-;0?_e;2OmD1Zz(Z?i+pA{@a z25$uTRHdd|Vm+Dw8rDBeBnrFuUri5R28j)9I2ZEVhl~n1%NA5{UENn@k4hX!%sk46 z*&u6qU&mNdVQB4P;f1`qVfB}9cz36e1lcPj8Rn>1SkW^qt-|Qyp>16^Ijm6y;D0NQ ze$`#(j1`&Yxbq*!Yb(9TG;9q6t4P5uua2YkKYnqa{qWV{KSktyxA+!n4vD>!$|;na z#ntst&9gz`6(_{h5h%%v`GcC3_&%I0{ksBk^M_1PkLfD~&vk)QYe%N5ko@AXj{ay? zV%JE*yzB_1zLe*v+)H)hAIZqqFF~U3!+d|R1cLv2&!LyiABZ;AyI#6E9>>DH@5Oxf z+}H7K>bdIg8bCu{bt*(VG@VXED*8I0gH@Rs&K*fIevXN=s}m&lH3*4 zaXo6)8GINryB@dmO;T4Vh0Z}K|UF6;3* zJ_SpM8aLhkw2-%hirfB_A%lYQp4h^rx0f#S@{}PbqzjQOr6laBEoE9*yW7A~xs({L zj0ZO$kjr{5cWa!u3iqnqvFh5a#6fE{8%_^f1Qz1@3q}Ubgv{#KIRdxO3Yxqu&?)T84TGl| zUS*{NFQ&IlYW-S#e|l#j1Is5RjiB7NEs1RM2G%Z|Oe`6g4o3xlp{4colBs)QR-Y+f zEhFXX9T@9?-I{ zqFHf?_UcFhXG-FtGN`4@Nvs6cK8eNG^BFX~njbxh-(${q`(#Qp*R#i8E=G)3;{Tg^ zKWuuW6jA7D_}kebWnuImNm5=>td3_|SwUcSU{kF)@L)5a<2=uvY}?ZBnUUA=u@^zKF2>l)hv zV}N)HR<`7CI$O9#qMsrk-T2$%H^)>uHoM1Uk2XL4Bf;wCAgRO66$4B3XZGv~9_BKm zD$PMDs+(7T%HIfTo=kqQ{*{9%q0M_e7EorCmtA66&>gJXcdWfa91!j zoVKi(&COx*`WeFr+h7jj6f*k6U|aLlUxv<4E9A+O_zu3^$Nmz_fDWitw;y-oXS*hw zFAW^kFUU&U)a;Xhapw|Z$?cR2X&re_gZ$T_FR`~$M&1)Trx@oVH2)64Kj(&7??Ydi z%$^nPb9QY5XGU9BoSC9HZ~3K%Rp#dDnJEMKLL5qyQ& z)m{!{EB%3QUH`O{5Xx^5im+X5vg3P2z7v-Eo4^szVe^~0xpT{y`(%o!a9J0fE_)P_ zfSCCpGvHRLS+84(*1GP@A{gH6PTnEV-AdGhO0zeww{q$g*7BsL;A+Mcy*2BpTorE+ ze=tZHn}z8j1{PdWX3D8ZO;t))QB;rBmWz zRpH@kP#4thSJN5DFbj=;(?_+a*KSXn)wHFg@4g5@%s`QjK_78bfr}J{ENVr3vYHME zJELztgT;ceZHM=7_;2-kxPtLM>y<{3hTiX+DNRg+oRhSI5#K~Fr}cl!5*H)^#6>~f zob28CSEFMTC~MMd7aUo;*-^FIL$%He<@9|LxWPSJ2acS>Xcf#JxhFQdAQ!wZ-FjQFGm>8X!vo{(gWE&;q#}~IVhn1IImgk?0 zuX!Xm<2+C|41KyAv9i4y5x8}L0DQe*cE>ui)MA%8v;&(}E?N28O+ue4u0o7@!|mi6 zMctbTi-bLtR3!Jc_h7kfOs-xxWl6Qgd4~4D3;&T23+~m+pz>8AyA8EKkCyrtuJ?g8 zSdmk_hL>6immhqlxmP&BIieW4W+Kf$vt)xa5x1u#XBVRmYal9M}ZfF^f7vDKW0vbE! z-HwBvUs&BB265hLBaeTy`=qx40r>L1CP4c>g}K|8zlkFtLx#q;|dyo=!h`CFIx|KNpPb}OV^kp#w(N=wA% z(r#VgNOtEdM}t%O#6K~a=LlRNQ3jFN%UNMDV59p7womdg`42mnO)qgD{sDRs-jt@q zpWboZY^*CX zccu6GS}B}ow(jZ0WO|Eus4+N{;8m5P-CBX`Kay?D@Gi9rnD{!o0ajti9t8KQoyBXa zU6cdbTRK_~06%3}-p8(F2bO$)-IO(%mXY060w41UHM`VG9EN{o{tSipy`Whd^jBz2 z>m?dC+?hKN=Z`hLj|I#EIUjgIZADsG;fJ(Rfcqw&aPyBnP+DP9cf?#7D3yu*(Rdp- z!ax_bk2}NKo{~VrDbKX8qf7DkSE4leNi`%}Vq(FwXU;V1pfxXPitte0^3Z=IzDYNF z{d29RN~}Jc;i0OJnu2W(YQvMxWHL8pC2e%;8fPS~WAEXT(MaMYW9q*2p25xFI7_wv%`Dhh}9a(PEOY#<^wmuuX`IF>yei>eO|@e zHdTx_}9Wjm#xR2mYTuXeIXJ=ZR{7dzA zS?!_a4P_I?`t|h_+?Oo?t3*az=F=&=??VWu#kSP&6^(}LDo%nJJEJeZn@su2^`9mD zG~x70?UBKa)9QtFRRbseKa%||FaZQ;ziK+KKAOa(tR^(uTTPl~9HuKaN{)|KS{2` zcRj}XExQ~%jR}}zEYN$#N<6cfC{ExbHebz4W|f`=Wa=8EHBW)LD5jXG1omG<+Auvy zIk#<|<@u&~9%1`DYsVtxnebfQL3c3b8SqPwq8Px9$@X z(eB+$Mwa9PZ2KnNQ%dLsydc5p;!8W5|Jo9DFSKCw24>z6obi=$;IG+#_%t0nWoOLI zXZ(91$qw&dDZt3KI2(&njsciJV!y`!sI}>^KY+VS;Z86rLEW0JqmFhl88$z$k0SWH z6olJ0{2@ZeSukqC6PKW?$Bko~=0+4O`2gZ~fpExFG@V0p3}nV6*}BF*am}Oe;-+4v z>uKL)LTx(|8{4jg9l^m$gOBDgO3j5vi#jJ`{QrTUwKv7AQ_#HTFV7eLk6%@pBN8|s zKGT&sC0S>|G4kEb`xmi6IZod7rSsuX34&_-%q_KbX;F2BlfW8*GwFVk^as^IJio6^ zL(Hm=03X2hB%EzCl7r@Vn!s;#vzd)KaxSh+y6J8nbwl8+rDZksfv^|Q-II>-?JlYr zZdrMwe3w%t8_7a~N!NOiba&$CCICabuY1uN3R!uqlMcV_$SNjHe+i-qOZ} zaQ6>N+C*wzD#@8u`R%A%tNyeEub#4;M-wx%PlYAk=R4hX*!zo$CdU zat*~h5pvWnLK3a?;u!NKBsk1NLAiX%)!SJBBg>mT+(8>k=A7vubMS1y+wS?^)@$|3 zg@e7HX;)TD!qHN`y+6`v?OSTZ&P{`YR6KZ=jsMydF2~G+LnDuQ&gYJnKOyIF+DM&; zOL2(}Z|@rqhpHU|wq$l~gz>L%+bF=-TJ_ek8r~ZF0hnt@xi5RB+VVe=k4|Mciq(}^ z!t>t@uO`sY6&bgo==58mmPcU`+?_c%?`s;DpjU;nagr1>;GmnBKN&d&TNa1X+nOm+ zI1>|RqwobHV8=@!|XT)9MYX^AC+`Pqeuan>HK!|k0kmGM!8*T zn-7|qcg#DBnh}ZEflOUPCmtM*hG@GZ7~?{ozkWcauBkSo1sK`9fRScH4y4736{Kj` zhqLNE0ws5AyS{fi#?SQ(6^POEpx5)3=F=0%1y0Ap+!KcbfpsKmA9t)SWXr`P`MQ7tFgzawcg#jkO*ADxHIA;9kAEYL~yHZsE^m*s@)H zsaC4jgE=ldWoSB;KG-E4mm5l3M;FkxLA?H;De`kc~Rd|9k{whE-{ z2cUT(68rRr#QE;LyCHkYX4EW%i+Rnh%yc7QSkc6ju8)|{@accCVCo0>X{@!}A37?J zW`&G*xCMInvDOIP)HGtiAR={j38ZYkGE(t49et5uqTs;16<3HK2#Kw61e2c06n|~9 zzn!R2jD}l!zZ$Lg1W-2cG>Np_(-Jvo9_9IQYR_1<{BG&bM;$Rf*6%zG^ynSd&!bXQ zr0YM>9F_!$(Vo`ZTJm1uzlsbug#x4UzJ`ovu51I_l+x%oy{K=qw;M3Rbxn>WM|ibD z^I9}nYWX_)Uva&ECoLf{+Qh_E1yX4!@v3$2#Ot#y*N=-_O}>q^#2m~BQ|Igrg?U(m zl)$(mronfV8wP!4Imrb#{DB@*f`9NygXG!bhcJzJu>I{^@~renHM^s}s(hh&%%NZN zlU>I2h}_J;`npz`*`l8%G;w2#BPOUV{}$2OK;E{-S2!}Zzj5GzT<(>YmR&mQ2Qnvj zyW3wOW1F_j7C1{4{?xMn=LJ|bTrXWR*NV07>uPVZy;w(Fl&ze9#x2isvG+j?!~QHS zec2x3xtcEFy7_D52fp@;u>Q$>AO^{mN+*UfQcOg$eA?c`269#_xwQp1yiKQRd^GkF z<5nW6hX#vf>gcq^O-BwOt#AF60~cw`1bnN4ou6@-zd@E8W{=@v zxa(C-3_aC<_jo%3Np}+4q z8x1n<8!r3H46SC(_Bt_cd3%jpgd_}m`n9s~4EtduNoB_#$f>ckI`ec$RCxuN^qRmF zV0?e+Y^AQC*1SdgN)3p{!5YQD!W)nu)p`O$gN7DZlux!8X_xtmQQ0O4eA3ZeDg}LQ zI{YHP<`uc@w)P^Zt!9jm$oD@A6@J>CeZ#xVCwoOHgOzMpQND+^Z(yHW&pf$8r*r;+ zT8`r1lHvJ075UmaJ}8}qOj{25+@tR228_8%IWmrTV@u|@X|sq<31@>x+8iwEu0ne{ zP4L&idQ?J#;mQknwQcpL{wRS+)X{8hQrMVEMPuoQFtz9R`S3Pkf%p$zXYq~5=A1&Diu2_yv8#u_I?20z26e`WV-VDen0}ZH zFPHzm-X$WLLZbf(-;^6%T5WO?zzN+iF1e%2?<<;~A*Ma`C+K`)DV1Z8?$$O!9&64TC#M1C(GtpX;5m zMN|7p6te|NvL6nl^AzzFZ_qzq1hi=hH7QVf@W6E{?-ztWq$}>6`C`mgpS5~_lF4%s zs>*YHHgLPm*Z^2=p`Xn5t>biG^-x)BUa8)BQl_HC%$TjK3-D872nqEjrlX~eZ$aa- zd#evcP7`=fS!PmP*zN+9Uy}HcCz!c={_z~z)t(El6#qT1YMe4gS06|pANk|yVm$>| zj&Lh~Iq>pJ{_n#fyqn7NP!#!*MZQY)`Ew?gzI0#J)-+pM1_1m{hr{Xq zYgRyz!^_X2MH%CY-a4{a?p&@5$w>79`P9gH5F>{!fLZlDUlEv1AlcZQK85Q^;(Adw zWI4spTkXl?m>&Xr@>KI=+^b8aEsDI3PfkEy+j(r!7>XnuvOJVuki%T*u*3ZDT@BBV z6Qo4ycyEkWF`W{&;?tnj9*BwP43d?A`PC$cYS3BiYAlWMbs5ZmYg|5SC5r|RZMiIl zJ`l|ag7zP)#Y=FInO34Z%FRJizx^uGy*@97Qh4Kx&v>W%4dYoASc}eqR$Xt>hV{Js zG|&fo>#5SY72#9?b*jfVia3hK`zY=KNslu{}^Kxd$~W2U#-fk2yeMWe+ev_gy=ZkwLeM!73s zxnT)7#MH#e*{z?=?&oEZl2hcRSc1=*`r@^L_c%FxZHpz@9r1pmX>$ys_nlD@)Rz8d zChORWYe|z;mgZ+MFQ_1Q_@WlY=ly2eF*5|+ax=A%oO}T4n{NBr;R^98}5jX?0ti$$7 zLJjCM3z73g8Ul(>oDR^5>#AA93VM0vPgJ5p&vszoZ0BFrBDhObA{);7!ELjdY>ajy z*|eS>2B9MwEtD7(-o5f!dWE4KVQ%mE%+N&a{&7dva(^f^idN*|IH$x2r?ddQ4YTNb;+pk!pq(ng9rOy5S zRM0mbSLms>lNm9RgwZyA_uQecn_nELv(S!bO=^0Y7WJP}-(#Icd33}A6mJ8yzye6y zTUy|ym%hjL-6^ zB3Ec=OE%#+XjEGlpg3R0d7SSvygmL|APXIgm7mcYPeok34~?J!tlD+@<8B`_buxwM zAbo*ce8s1~I=x6nO>Dt|kc2bBulmNQAq% zGu3m%D+x6^%)x^uiATceB`e2J`3`(8x=(M1*m$A|oK{;VV(v{dISY(DiE;|H1h?ie zqw6Z$(M->J0fQO6IGZs!&7+nZ7U=71?+DOLaYZiU2LWQU5+Uka3Mm$nU6 zO_IV$;#{$Stjdjm=>4C}qepVbbGIgz7iu?r!;uiRKMDsNWv6Xy79uaCJjIj|JH z?qsXf_fQ)n7&oDR+&umz>Jwn{NG=oLLa=PaPXgX{s7oGG?AIMtS+Vr%;*i5a^I;`- zOd=^BE%J8r{7t3qW4?AC(`_O6{#@6h);RWy_AhWfFAXeS;vTYvOa&#rl7EEkk{+rv zNnJ;M(cT3K6DKlo#CaY-44(de8XME@mwd?3H41K@xU_IySJdcLnUaVN9(p$EF)!WH zNU@ppE&20}nA;zK(@L~hh$^nMaG_o0Y=MHIDL$^`&67yLp%ewi`fp`e&-uyj1Mc+o z#>Ppe+NUiIr_YtQn?)#gV=fLO0hAIPpOrY|!10fV1p5?6H|E5~mcA-}*rT}Br8e5! zM#{>H`jEDx<>xwU+}6>c>3-z{0FB{LLJ7ADyoS7uO4=md%B>o|m%6*{wX*qD7Fq1J z8Xf!$$g|KKw7#p?O84%6^)*|R2jwD;r@yr^!jBqe>v=@a$?^dp5XMPy44;05;!03F zwP7SIa!?Pz)`ed5&(shwx;nK>wP&ZgA#q{l2>h*1laF;T%2AFHnaI3Jye6Kg6TXdV zm-|g9&Cn#1KA1KSkCB6S*c>V5p97CC@Z7Mw?m|T=p@f)~cd4R7yyW(Pi*b%4W-N@x z?OT9H@74E8&wI-D?$3V{HT=)MbDqH?x*PysUiZLg^Cqjf{ub}X2yrOh>97N2n-Ius zf?Vkv=Zj#z_WsPH?%ph~1sy^+-zjq>!CAhZ;5J+8Q*7E`9Vfx?PGZ4j9pY!i3YSZp zJwRVhw@Dv9-#Wx`q=zXT4-_7=^!s0(m-7W@77xC~*F3o{>HI(?kPWW^18fzAwcHD0 z`x!*G1^*IDoX!u#5)Tf?0IVi2uC>C(l{j$D#CnPPw1TvUh}4C(%Gv4gI9D!W5K&E1 zC3E|b^2VF2pGi@p-ctq$2pSTQ_zvX>4gz_f(THBBx-!lAw~zO%Fej+Z^chyQTG3BGYbmY`m_Xt1H9Hu7~k|E8dTX|U$IM-LA*!r>a=LhY zyMan{{i?xG%{8P$LX^ia!jvx!#B^9c@X^%_gv$*ZY}+NXHHY%WKRvtQYmYmPQMDb@ zc1zapN&=C3=&JC@j(b!xv5CS4vYT1$p+m2K9Oz~&Eq}Y!d3Mw5q4BC4U4IU8^8yP` zYA@gn1^dqOz5RBvxf;@Qehx+Alb%JX17Ws$2b?LR@}7X+tLamfvwNa`S)MMK>y=9G zBl)oU?00M>7xD!AItK3`VqbDhR7;qz^81EQso&OtJk{>PY4JODxlq??JqFM#-taPxW5&W#6_&UlbN`$y&c z`4rGNd6huUZIOfe83)34q2RE{1Bs0+LoLw)iCT=p`Zss%dK5(?-%o+j?^pTC3u%Fv zZQ!>>r{t)Gep{{#1ejyFfQA(YJ1Us_N$N42GNL_xiQEhYh;9L!F;AluV95-Yb0r5@?d`W4)F3aRf%N_5$4O7()j|HTKhLKmG7>tK_@>eWwb`NTX z^n?;3dV@onm@a#I=vqu$wGt0$w#lb$e-<}Yx|^JNQ2i=YXrXQCHd)(F`ZoPD#Wtt9&MV;{REkz?=$lj zlrVY&HGvwvG%=R?hN6+&d?5ap8hk|84D-jYK%IiTZmAfndb_lYz9O+}gKd`i>QWAW zy?mu(e_;}?Yh$;FNlCau5+W-*TyEsM$|53}S_6-eD<(7eF=Tnh+ho_$&xDl_<>+lA zkZC!ct#|V4q+9%qxX=$qXE6FKjdDl@l$@tq{p!8UFP`}kb)c$LkNP+Sp1N$?x^=3y zw2RCOE}6xZNw;c$*npY;3TPFvp}8K`^T-8cbhhOC=alVxnq(d8-qd8yomcUpX>$vH zxMn)e*flHIFHT^*yuvBRl0ht=f+vk%Rh~ZX_tccuFplwi@z(_uSVo)j$9q&_NwxeN zKWv_S(JALtYJ;?2#q#g3#qZ38p`*9Mdq}-PU8$SIA0_phoKmLDr-U5@h0$RQfA5Yh zU*;91znZyZ3TIYLYaSsqP->So^J^<^EB(2<#-N0fP%wPoabr{BbxDZ~S!@iIEf^Hm z_5vj=w62DdiF3}h52r0%LwQrctj9#l?0hapL64~Y+25R?8~$qkT8l>dZ6jaS1a3;B z{xCT58-4=nv8##A&mb$Dr{+#kii)4kgEZzb&#{q-3uxOPz6Ccc%+jefN5NY?IL=Ta>ILl&_Imqb#{34Mmof!|O!;g&%Bsr`G}{;*kPhhdTgin* zq@(hUM4u;}UMuNqzYXM6U_R8<<6VugP6L00Ui<*Dbb*~AX{WtN2nj@w>JO3p*~CK`B>LY6-l9MftpkG%Y~?7nV+m;%xlSdS~KLA7slmVQ+{P z3`oLRX1ppFe_){?ByPR@@09JZOv-ZR=2z@Y&~FCjD0j|XYv`g|pBQg)xUsO{UUd&zL;2@xi)^gS*rIB(_npJ1tND$O7qY z|B?Ylx94+~O>&9@&%n=hI<8fp z=XBOD?glwIT}~hIAVNs)bV@59%xFS$P{ct@!oMMnnav64l)&A%sbL^IfL4w56q(sf zp!EPOt$$if5FpRNGG=DNgTkn7keOX@TJSc4HaX^$F~=F1qOifN8*x45Ztb~J2--Va zIC%*6FsJ)+6(jW#Z>dY`lwdL^LGC^01T|}e29>hO=BAz!LtJ96=MV1SA;6Uu3DIXM zkn^i4ja~+rHlMUF<2ux`fd^pTKjfog>bIDEJIwbo=~_47>JZVzB#HiRcW&<9yM3PI zy!j?>-;Sd69Z+%iY`Wml=3*qJm`)De-u3gcUT`mu#mP8XBVhGA1Y|{Y?P;_m9N<+AZ^zE66#o&pY@3{a%*ph&>tiBSc2 zy>)8S2>;@W5bS!sF?+GZKax}|!FN*U@A>n^)OXIsC}kaE_Nj@wD}#s^mHy8e@@q13 z!{-^V{`4xr(nx0;z2Ac9ASpBTAu&&#*eLAPN3-V&KzTwDLlV?79~W0iIXvU%J7dG%8-T+6+WF^;iZn4V)H@($YB8I`V4^d`GeH zt_ErrsU-njA@2XzKG5ijz%cmn`qdI`55}XwiT|Dk`G_) zj=5TXvIhOZ3YzkjMG3udGdo{8{BvFPe2u?dk~&!#7V7>Q&a zcpd&y;+m?r*!=5nFW>V7+tbZC7soNsWk`zU1eoJ4&i~^4&xP!@j^hjLhuUwAow{uE z$K`XBZG?BLgr#@4)aJ&0r}S7VZNjBr!Uqt$*6e7Q0YZ~h@4A6lvZnb*B6-O<4{(Hi z)kKX)o_|{$c9`}FF|!2AI_Uz4ABZ`|8d!H=$hhKS@K-l!1kUhZ6vs+4^JpumQ#D!Y z!NL((DbDTeHqW<_nB(ShA;Rz9#e*F~*CUwLOTaJ0_;HkWZN*GT?1iu5=IK%h zY|VZw+@&kJ>!>b_VTWF7A`tpB_uBm%+uJWxhT-jn(dz=IZNO<^JfM7@m?n}WhQ~%E zbe62N)pi81W;IvD99M%{w;5i(+!EKN+$gp+tA)1ir8#xuQ|P2P62;6xudMHmKh@SB z5d{y2KRE9)#a{(p!K}Jvm-rR_YV%#!`NyBPO&~CnV>jcaVKjK7YFz2+wUymq-s1kF zWpfPr(>tYiYPmbq5Gz>5B1sFD?$Uo1@CEvhq}R&9HHhrmY)thpC#R1W{K87-PI!`a z{`&X=^}sUsAIHh3F$gvBr@*R;w7!BzpJ?mYTFx=calIdp6B!7I=X;qud#Fv!roG@u zZ@bMb#}rpbD$JxJ1QzU5JwA_Gf2$;ei<8*B`*|MxCF-x0wh@{~?9uM0TSSSJTlr0N z2>nGT?~Hy)ou?r2QeG9ExR&!-ARzdDgqTh z>}Z9h;-BM!osZz%tzjSE{{lW^cl^B?UiqWN@5=e(9$6^E!}pgBOVo zFtIQP`z-PE)a9$4tH!8i9D?({@-T^nY zHKr3;$ncD3UFrm~khdN&T~vF%KkOdal(V=MSZBN13o3qjLXbqki1jpwdvK-zyx(`mZOc!0&M))90|7r1XK=j=!*vz4ks88S;x_77D|qN^dATjW-dF+M zq7#!%ZS#eL+IRH74-RdOwp0fY-pg;qgwRV9qptaM|E67=4E<7mNlxRehFGnjV($}X zy5i_^%BizdbGK>N#G#h@g|<-Tz2{A7FZ6YuR}TMNJB@E9s)Dma#3ns_!lSd9Yo>q} z*P(L%6&p;OK4H8{fJK6uB7I~fKbAEn+RbNR_M?{W|HZDvq3f%OPQ5*u*e_j8e8^(v zkoMLN5BT?a4*$MI6GAmIAE>{vF})kyRFwU)zXL>6s~_;i&va61EYz)%5d>2-l*~QA zMc*zIW=x3Oe%ngSE5vM!c36EDCa3uKuin1w%i_SypeeWP&y;%2{*|2E0?+iGUClg|G2Wsd&+15S|Cgj>)hqBOy0f-Z!KMvl26xODUM$(%r z`tK`JU|xq(VBU)POMKE=E^2wsi+^rva~k93-1IEssbXox2DZv?a<1TGT|)iRa)-;J zd^X6R3SC>5vY0E)8jL&uZ%keY%M>mWT@3t4iKPoVe3Z{&;;(dY_>JK{(K9eA51DDO zEMKS3-Av9oD;QXwl8C;|os{8>EIZm#e6y%1Q@FI%Tz~>0PV$+y!sQac5maHRRF^Wv zqF`XY2YYJcH1% z`mBEed&$Xlg(R09)rz|)Wc9gK{#S~D)A&L{T9I{%?|j`r)9!!sQlV}Rb6j-! zp4Spduhd-eoVUR*x}=RrM`V4P%;2o9 z>|I|FxBTbD2Vm{BB>m)_+cR2=_Ay4_4+lj890#8uV{R;nY?1mS>Q4>hG&`imP$MTEAT#}hed37lcm*39j(eGC`gJFVXs9{+OR2dD4I88j=)UZ#)VitU5+h4~ z&dD@f4POB{o3b0`&Brup!aFRFo~ssOC3!10XNB-7PZvqti{sXdtu+2N60ly2akHTc z<76hQPbcmJP2r>8}e+oJl@10peR4Mv~at&674 z2Nps5^S-6(sl4pV`=0o#sGCPZZ=d+2px7?Cz)nw7b#l(|Z%33=j7{521~RWvd_1RO zV=9ctHUS-HVD@F>{-oLYg&wvfb;_UZt2i)4PjU)!Wa?BtTBgQO?j3_FPw1U6$wKl= zYzifLOOo|>e|aY$dQPW|t%)l;HoGvN9Qw8Cz1(Rcw*H=;J$9oMo-9|oR~%RCHE>?+Ca2Rn_<5RgXq2tWQzdSbfU4^^ww&>p!ah|UL?)%F-b3fDa9BRZP1E~b z7uJgJLTyBR6lP-;CbVrH#HY#An{TTL=t)jydqQ-XR0AxTnf<^8vp)?)Qd2JWx4M2$ z7+8HRNc!Q`6)z&{_&oE$p>AMgB9BDomu<_(1Kt{&Cy%9D)-#*k5vaG$LRnA`MYn9< zh6@cnu2U)zUb7#8zfunPTAVhrCK5vouYr{YY~L!yr46nOWQj7&1f_bgWL%ks_NhNx z+dWtnaeO2)9fIeR-R;*5&7iV`Lo~Ch?#h%9@=~~*(i=97x8!LcS||krZ%uv7Z+Zq# z#XzDBYrM2zDFQfNV(Nzij#oY>Z7xA~qV9)DaM%O;<&$M-nRv-XmRE9EQ4 z;`E3XpqI3JWyj_vZB{jpHvD!qhxSKh+!5OK#dje60H^(COJ^cLB(tw7?|hX13>xt; z>pUNHW$@#}w%!4jc9D4^&L0Kb-32ye&L>4t@X!V`C%VM>v!^aCHIGVf+ElW1@ZDG! zp7ZxMkrSDsSL(Y^H&KK&NVdBe8<@~LmF+SX1a&c3h>`Z*wR-eR@i8g>1)Iyt?Co37 zKp8Zw>E0y8a%*nH>BGCS#pMSGoMEs9#W%i?&Ok4LT1E?>=6WtcHG>$f?kuOwO?VYZ z3cTI#TgKXPx0bEVzd_!}*&yXC4uwm%vN>(UeWagjs)VfFA-KE+uZ0BCJwXoiR+FH)=#6Ke0qJ7!b89L6Q z{wIq;`ez(BLGQ+`VUes?kIhtd%Gjdo$hz6&k#+Gag^~tUD)Pe=yB1zk$rJaKyL>+I z72jrcJ}$0}MA0#g+ahaH&A0SvH#Sg51zVvHc*YjjQ|`|VRp60~%=)1^+rWrjs8rGx zzmRam!zM*>Rdp0COuD21lae)K`8(Gv=A1TjZj?j|W2FcE`NQKARN5%H6Nci1cB!LA``&`P&w#ovifVL_IGD1fR`)-WNBO_4TO|0)usr~Co0K9l zcRHSqZ!XfF7x{ra&BgTbfjqQvgAB4|8=;Kkr%e(|y~Ocg&yHv@irW^PMOqG1E3YbE zP}CIuI_(*KjY*mgO#s2UGQFq-c+g75rhtQq#PfhMH;JrM?d8P{0@1fxeaV!GDj(k? zny_(E8*D{Fa%(*Y|9!2oN%|RhXj8VraQGdurW1?dVuKnX2(iz)_yw+;wpKL$hB=xq zjNLnkgYATZf$XMQm-+i}9M5R0+8T^;v8E@uEr8Ibmq-}3F$??>j74`^-hA4}cSQy5 z&7rkS<8Gd5T!BnC*wgR}>(e$K1DC07z!$BLY;xDp_cH0EF<0~<{aAFGsk%Bw(opn$ z7WG(^&_aq$irVkfOHI+W42NTFelPWHD12-gMZ0y>ixIjsdBe#@_Z6~ZW;%D@9=o1o zXipa1@Pmy~O_J>!!o*lci4qMG~>&ES>p zOq8{nQpa}GTl;$v#GA$KS@;Z8BdUUH#W)5?>8KdQ{1(>EoRlf>Yhog7Yt(k+_wfDf z;>y?Fx2%)}X{vCA`U%-NagPkZX9UB{o_)=~SQUX{pDemmA-zAtGhPnmdlP1Y)RK_J$(_Z*b88Fexqp=V`Xn59wA@3rK zW5S;x!0#i}rKMYn1$!V^XW zQdF0KI4iq~%5^I=9S`&uvoL=d1$0WQF3B(DL3WDb%CD^hA`Fl3d<&3T1({2>xhMF2 zHMhtLf3!$7tr(55M(ZV^#9Nc2n7F?0FL8x(YkspApHE;kD)3L4c+s=F5ei59D%|jz zDPGc{yXp@6%Ex1DsP?g;8vmiD?0)P!xeU;&TC%PB4RR)0&K5!_7B1=E^={ztC{^Jh#2EHWPtMIxahoC1MT?r2yZxtlu4{)|V{Z=B=MRwP0G?8K*XuES1*~lH6$k@K;rWC4Rng3rx#t zYe>z9tEw49;64eQd9Q}|ksfod6(yCok#`tgE3W?|nRHl%A)@eZn*icKyfxfWQ=iJL zklkPVs;3#No^@4sB8~?=`etBz_Q%xM6ayyNOsy&O&{mHRqN|oq204zN58}zfuzeD1 zeN6Yo`306gp)cJfPgXX<{*m<6+xCS3bi{HxwuC*tPud6(xtz)U_lYk-wOj^oj)BZT zmQNLNIZ+fPoXt5+uRm&{{ZMqcXC+nP3OgYe#|-DPN0=Dl!p@_cNt_p2b@50r%&|sk z6s!9nDHn~3V48NyD8Q`(TR$i6#esX2F&1nj(4$2C;MNS(` zJ<~?qFeL#GR22BOWbgu*ayvJaYwI+6lV=*n7t?P%VB~u&?v=Szy%M9)v#o9`kf6e; z8icM1Io|TxQV>HGa%#vKs&&ye@0r9{Pc%5NmV~YH5u9^NbgtX=i)7Y|#HX0wwB5Mu z67^*1*X;)W_m7I{@*R@B7YbRLH$k_Za{y`b=y4KagW9V_=nnVV&7y&S5TzeASDZnp zI>*m9`A-=9MEl9=CfQS0N^U?F^EDS0BJ<1jtXIfeDx8nER9=6NU_+*EB&%>&pR5rUj9KAK@eEVAp5yiSFlmrud*a}sC~vOdY>pem(pFQJDt-)&=doP( z)A6;4L)9Yv_sxS%Mwy%r(jIHGfJ%`5jwIS>mk_xtMZk+Epet|3weSa}~HB={8jaB2Z~GQRY8_Eqh&-u^jx=)84Qw$AceF6}p)GVz7ankt}4Kz=xi zA`0A>Mt2Y=kO@wqUJY+ zAOFnMM-1!`OOMDsfIV6}X5BlBP)22rdib-7_60PkOFvws<(5{`$_#qd5a82sTtZGC z+O~f78%#%jt)$7vtCYQ(oscM{KRI_MEFN{YUnDy=(S*L+51lB%MqMSBjyF8XcJSdA z!;r0pg$2=Xcj#gsXI5*8IfOq)t|v6nsBjX#{v|LHM$^f$6~52X!}3ITY4Y7|JZZuW zv?t=(8x=#Ft#6u(s%X}PDHq?e>}Y%%Q<}1kf2$79zXRgCYH3&GX+AdmQMur*@w3a{ zLUxD|h-laVmobt}PhEiTVMTsngvroDAAclH7If=GAugafs0agRPpDi@y`Th+LeWUG znN<(G2y?|P)iuD|<3;wuJC41>9RnO!9EHu%OM&UXohov#Wmxhr$(~$?&kk77;UkRG z90Z}GMX5HA(O?gB1$Zn&fv2`XRAb&cZgAK)?;>uAHpO=jXP{H4mGX2woSuDQHIDh^ zlg*Hyhdp*9$qT0UP!dkrr7IACOW&qSc)}eTM831gQeA7+fT27#qNRXkwM#Vzl~}N+ z1v(fD3vUP%AN7_Fz_C1+(T1HFtRF{LGKQ*;Z@#&RMt_BZ`~WH7p30Ts8QE7E0rz3a z_WbVS%rqm|TnjZpbJeFV%@9l}tN<#F0d$0IfZ<`imF821m3$)ch?a5CZl`GajYDO&F75erOo4XZ|wnhS9CM}1)J&}*CeD8QJ3&H zhe~EoaTX6;!OXMO?%9v;RLbRBKzP@qV*CP@q&7?E>uvCPat`P$9e+J1 z#lT-f3fCKr&P_$LbOiIZ(~bxx0V7=1j}WGPY2QDn7@G#8>TErGzMZJDFDUShvvCaM zS+bp9V1on(3IIA(ajIy$o(V_hpNh3fj@TC|Ch19Sh0E*K&4ttvzauop687EtABJ^? z0Irsz|1VrE*~mYinZtR<6XdfPfmujCGxEdOYoF|Fs5YtkCj^&{C^0C+T`l`j)kJ>< ztI`W}%cZ_AfkUh5gq!*~+07SIeUVCNVc*;oc(^;9a^Ebc@(XydmEA8(sF=n61mDBz z#usNV@^J1};!&6H`^eKfFHf$OV0%XrQTGOZS8WRI+aMU*rxYc2Ue1OW+3}Xqw zPzI+(G#|Q7WtNiAb=_7QSpaB2w@>)i$+T5ve@(!=PvDjzmP? z?%;PeKlK{gDxR-`!!i0C&pa~JnFR#2%Wf*TCIxCaKah-uBPG@ewn8sn-^^xRgvqm| zHRZ+Xto^#N@9nhl#5`BiXUh<7oE5jA|05KbSLx4MHZSQnE-0zDv0IMM{t3=~c?0#` zHG+>%B?x$`#TZJgzlEi8Y`ZD&@uqma-O;pSi|=4KN;ORQzE#YoQugQXu*hYBB(X2& z`1P#|{4THLmP{!%U6@OlWN3a&#a1SA{p5}mOrB!Y()yzG5kmG&bQJ=#vD zbo9yG_M$9B>9q|As@sfH&*E_A^Vqd;R>Hm z?&pbIjf<|5y<`X$ch67*F{$;hvF^pG#_Xx0Ys6ckc}+syBcnZHVLDiVOd5?Z_Zr2q0Hz@tJ=V&ggXx>;HYq zaymjwsxY!=(oHL?)S|UvIrsH+5@FdY-I^0gbuW9tes4pDK`BJTW%G*qabRR*~K3KDNbnz_CZ1b3jGhn!=`NM&DR#~*mP-;3eN36{zQOFB__Rc!g}{{THV~J|082%-aYH5boK7% z`7%A`it$~&2RgsxG(2^}>bXSp&?kVix1bj2bLbldf$~Dd9AlkR@A(DB2m09%F+k*+kIo68XwO`*4>b~l9tz%AQVWDa3@~=Dz=-H(f3uSYr z%HYrYb0s{7n8bUFdUA~P&bC;zKpB0AXpS^QrOdykl{F+}g{=M87@9k=4b5D7p57g| z*|RV*j=rSOGKmJIy$(h6-u06Do0Yzq(6GLYvrgI-Yb)Uu(g!-HQFk7~Iq_Ev!b-+4 zGDatRZj9*srxar*(a_$jn0aCq%`iGtN=;KfM{|7lNa=?1=*z1LjcGZ{an-&vCVJ-j zM+m3;H@1B`E+FGqLn91b?tR769qHNZ!zr}~TS)1*uBiBB%&37Rdclfi%4e*S3|up zQ*evdZ|Otq?8tqoNAIr{pd2Y95gIqD;^{6PE{NE<*#}Rr*cB`iLa63O5Ys9UXt28D8b07 z`q;$Ff86aIT`=#{hVg#w>R4V~Z$T&X45X;)S1Lb!3wQJ+0)3UrW=~~%W*wfgYZB`$ zU{fqo5mOl1GVASf1lXvnM+) zpuaeOhEk@38W6goq9sAc1z)hpQ=%h-0$=#g#38^BIGc_RXn1wDrzPG>#Vg-&!+Wh% z)zh!Bb+9aShj0GxlZUSRe03JxU_Xe6AIl~jDzwu7!!oXx^G2DsSj0T@gI>@l923+^ zer@q@{EQmsSBGda@gtEWH&VW5F+Q!g;BrghGKpFnC(>Xz$`^DS@8H9Z;ZL&J6@ett z;ViCI1|KauM^>j-KLfA!^PkGLj8bQ%8eWh}Le6kY9vlRl39I|#$UPi;Afdyh2t<0w z+5HZY+H;~ucg9zan;KavlbJhKk_NcsQ9XnKbKG+|7yB#z&SZB?G!%Aq4I1wG5(znY z6l9q)Rm|gNQcBx8%_^eV;~tJbGBQo}47!I=`dQ*hs?zdGhc2 zJOGkn#{R@^_zWYSj%>I>Z3xk$|GDBPJ$yl9c9*XG1j%N7!; zY};*`TqmskBP!2`Xj$RGO64e@(AS|B_MeSt(Z~NI>M^pPy0m1=Y2oVmi2Tx}-=V%Q z*?a)+c4y)I%g|qI6!=5pQh|Ml^zANDwqtQLj1P>ZWrYE;r0HdOsxH4J=X93FV)+8BOKq9ZdZu35_xkqbKT^?Y;!SHos0Cx8*LEk_Bkh~ zEa_`|l2I7?IShpKPZm-)k?kxHPl%n=*-pH=P(fK5v2iPO@zHvOW07ORr-Aek_2iaH z?*mGy&XgT-K`O(rj>ku*&sR!W*c+GjsX8!<^X%=y-~4L2mLBG$eaKPV%jcEv*qPxOm?M}&(mfGYS)rB7pTcvZISv`SoKnlKq-9#X18I^_| z=;Nc+&|G^8fAPKUYsX~9?j9LF(1HWJzr`BxJcveS8S)nv1fAfsTevSXsOwH~S!~w7`9XNXxPJ~N zGwnNlrE#7FTHw4#8zc?-QJR19`csSei0ILNYI_My@gp=|SRV`B4YEkzi0ya3U#t0J z0T!~`LaCs#PuqBT18u|wiEmuh=P3DL_G3<$89Z0hHvLhq=z%Uq?Tq;Q3+_TK$^SWx z=H9jsJ_&V~-9slnNAS*4?ba78z(u;1BPpU9)1&*| zeJ|hO*-6i3e%PLBs+agtd+6G;%+EH!@8h9K1w?mh1BZNd9uJnZuXGOj&$8#D&uY&c zbRz>opXjE4(@h|eq;gl0?%pTRp7#TJ5Ie@*i015SQjr>*7Kco$1C#H3){$4{E!cOa z9T(G1Q*g>S&D)oZoXbG2z;)qeC^V5K;`_7jKW~TYW#n}^_R(QPOtD9+JqLY(+1NjO z?~a`^Y+NmDp8hy04F;vRF2`#r(<|KDn+m@G&rDr>uEDPSUby))s~~5J?!U>ImF$^!6&`+DcI669(JjjmaaqQ|(f3ZxQ;Ya9Si+-?d+VJ(U6o0%zf!2k)ZexMu z1bWJ(u)6qg4p|gvAWZo!^ig_RDKf)-cmAu0@~g`%Cs4!*?NDO}FFYpsVV!itYgBm0kGe z+?;IXhU&Bvw-Fte+iBC>l>8x7WFcueh|U~`3sl3c9&WxC9O{e`h?O$1mf=2?IG5TN zJnr)pwAaB@t^5B$pW0Y5xL8{a0H>PgTlQnwe?(fCgug*_#~Ld(=RQWTprU%fEQ$6G zOt@zEQGoq8_7Uy5RFn2xjJs!!mAvnDVV{&Wo=-E@RPjo#i@%afH!Mw+qAkF~J ziT$;Rpe)N4=ZdFpisyhv{jjwa znCuPv?93hlAJ;t}cg-GQH-Th#r=ipKYv_htiJP_@tPKwF6!`p_GE*Vl(|qEccQNWM z7(_N?RUrTMV?_ogr#w1Sj~KoJ?kie&-)G!5@X4%<(~&dw`-Jj)K$j+gMPeQq)M1-2 zXyf{jZxws>b4pGsPr?!h;B3=#kYX5nqiF#7v2J%gP?}evHfh*#wtHnD%qHE{k84`& zTc3uDxZ`hNhF^=_HsjAIL`5DxX2)L462^{6)8ylxjrf%RAyCNZ{v)EW(ox?!WEV*> zM;hzV8v-sh{KyoXdi&mr8T~udGLgyjY>z$L-QjVqtTVbQW~WG(7e{()C-2!?8jcIg z)>v5ETcT`u_40Z97Wx)ir0VuZ-u&FexvK8~&nyMC4oHpk@Ux}PtbxcQiU05mJ6S#i zYE(A7bTG7@xBGD9~eu*iB8!8N>Z1v_f&Yr))Xc%Mi#d2T>CA9&zM4Wi8-&#kYQ4d>;x$1z+j|KDe(gqkFL`~2E{ ziN(M@pUEEK)C-j=lTb!?huvvaOi*?-A|t}*HW|cXxnA7QWqnafMw9k&XKAKSj+N#& zcfG{mz-M2XGdkKS6WW!8z}deUS{Yy468s;pNf_+zTEaJG!KR)=0f+qIzwf)bM2v1n z)72EpKJudT7Efu4*Lw(gDWtxfy3AV=M4lzeT4bO*Z5?CzKIoEr4OPI=~)az3>mig z^Y*r#GGnZAo{`d$?5S?54SaP`tb%OqHF(OA{d_HzD_zuFA*0~bQu_2HTOj4SmPJo6 zs+KH0jdzIA+=Z7Rp6K(v3%U*+O~Xw{{+|=}2hwd082C2>JMoRhpu+wDpx)gUdPs&qC8bCWw!iBvJ zM@sl^8q?|wcdjB5sC`XXT;I(P^>L+r78zpxd}O2s>|)@faHvfC=^=E`2>#4)n`ceB zEz5RSW$(QmT9pv;K-|VvuHr0vHc(7QJjIV#wQ9t|ob!0pEg-)_y{v&sS(#^U7kWQ6 z^)G(s)f977TKo&MKcP4jn@`TQUUmJG$0=By@)`y_^nSX6y^OM1IAzw3Dk>3rj^{av z1`nxEPrxXYne%W6NveY`DUMWk@boz3A^wFFb+OQqo$?K@_kTBbSz(C=KRf4Tfh-*H zbX&Hi5K+~82MC2wMA-~{-ID=t+b3_G#IS4=d6xZ<$)0*4y5m^2TS-tQt>+2arDq&5 z_VM>jbZ4Y%pG;20=eo@97rS@FGxui-eDs=o`R{Y$$xgF|dsuWOFNRk%=TaR>6sufv z`bS^$5CFoZN^;-z(98aFn2e!(GCs(RVY_9cs2ff1bV5ukMQf zex=|`n?mlfhCy1%a0-jhOR*SGr8l4O=oH8F6T}@roy)pLMlClUjvTeLJbTBH=G4mK zPHdZ5bA$=LJiML6Y{y?9d6jDBw`IT@1H0ObCK=>Nz=V)fkulX)G&Gyq80;R2avdQ} zo6`Dw&}tK|E(+qB0&zm%Vny1qjgR20Cn1-vfBHgTX!tKM2vg{end#l+A>(7R=q zsBRO>+elmxK@ulJfO>qgbb=Q{@Ky;ywm)CTRi+&c93h8>*ZgOPjSqqn%i7M3omy&k zm9Gx)JGCSE`QNW9B6Xbjmq=TL5)=YAy-g!|K^Zc1ps*v9I0Z~_lt$yXLi;Buc_&KZAr5mryDFxgpw+; z(ueC?IkoEQXWhn)J9R7*mTBgv%5*H!41(QwT z1zgfjIZ18GG7@_I`?c~9?6?=wAslJ4ZsZ z0t)iin%t!q&iH?pZQTJZ$sDGR4#Zy~PxXH}_OM{Ug0&Bop`1986K~FI6E>o3=*(ZD z5jwV`#BhqV-rlnzsiBIWZY7bOP}R9eUc_q9Dhg%MO5!RANP`G-I1a`1Z;<8XxfL1<7v335e=g{ zhqur2`lR=8TGZD)$N8Iy29G%%*my*uuk%yjm$nPLVw&3m!oRXwHlYkpvis9Dh)OTr zwYNorw9!bRjkC<>BMY<*U)a5G6{`&0Jq69`W_)RW-UHf(UCT~wCIlrD#_~9^tZPqX zy1szocuNO?*6t-C8cq<|{{*mo0i^2NFXuAgGo|%*f-6DA<2KQO@Tb;!^|&_*4X7sz3-=&#YT z)`_lw8(k-qq(!r&Op|QOej?=3@*K$M^ z6Xf_K6*cR`@wsN*NwtI{#oAm)1rbF2(g#|eT}rO5BZOPNyhmpAT$g@H=_h4cl0T=) z^XF@*cntoW4-4ReR^9zE2?i=&76-Mr2A@EbUsh7i42dFyiTXzIT zk@6EKKUJAs$=GUD9bGv{J1w<|Nj-^6_gN?*E?fJ*|N7-NSZx#&>PogG(b+@(+Ph&p(fh`i{ZahJ`^Ysq79mEv z%fN@bOXnqk=3I*~rlJ?S)wak0bWX2cS&R$+aXuef1B|Ko$hHEl7dzbVCXqd=-6aUZ!bM|VRNZ`V9^ayLV$9xPEsdwY zy)o9dJh7+lba0;fzfZZ$u^*2+RI!FDJ|0nmQc~3J9s}0{KSTzkYBKlvi?3d86@#2> zd;FlJkfAOVbV1B#J_OHkL zF{c9}@n!Ls!7T;5&34=PZmjp396W4M9OZfK@T($8>`z7u>PYkrVM_SwEpF2DA0Z7fD}Zr z&Eys5SXaF7h*}^&f2v23F(7f-2!#*0KYP{uFaTZAl&CR*M>nVEZU?w0ZTRL+U>Ib> zbt{@$5ZV&{sVT*yhRC8H1i^CN3B6l6!E#Q=O^V2dHN025 zzdPtnM1A=yRn#BepZK(v3>5N|!x`3J(s!2>T9i9|k?X`-uCP)eMp#- zf(mUwPoWO!Ry41lYs{6N(=GRDjOKk!8Pd;72R6sKyfQtI_7V}ZH_YH`aYv3kQ=OCf zM>r;V0JNV_Dpdd9YqE@Z?OOPXDN5YR4^VvmkzCDJHVc0F`cbboLVx(s5R-i};EFF$ zG9aNF(~z4_{J5kEZBU2ZVcGhP=k+>km8dM`dXa8KIN+el;6+|Fkc8WepebNXKlu6I z+e!fuWo&@GHmYVT6;)ctRX3q7_r8I8p<70Lq+u*Y-0A+j2z!W}3;*SiqSX`TO_mR_ z(C5_dnllY0P_JtyxDBt90wMK`$$8@rhGZKX5KKo--TStaec5P>N z#jyHD9*BT)d(u-VbE_bxA$dKG5k?}?{an-2uV2D zk31_)`A6h5bVq_Z1mTn?9j7_2=RshkizocHzi=k2kotuwAvHv0B>zSo$BUKrNh87K#yR-)@g`|gl5;+ulqlWb87dEQoFY^ zC!VtO7i6m2*azw@jx#eMG+VzagjG-Q^?tM9MAJcjYX!QA=M;g3+ zLzSi8frD0k3{B#4CT{QeRQtMAHI!yE{dEg*)d<(G@2*s8wUy{T{a+3y|F0G%^jJYL zVPxJ;_onbee1XMJvK63iO^Y9Ximvm0 zl9EoAHgrOH>Kb)JttRc$WEnwk+||(+N`6J6Z@ja)ml2@%Fp)BLCVPZss%=$FK*KNg zqQZG14U@}I{9uQDlU+(dCYO;hk)iA5ro7GJ7Ak(@N~UMBaimDfA2N!L_qQ2nli8A> zv52&e^LEP6god;T_t)+k>>7Vx7X;Uc(Ft4;nJ!^HVXSfxP-GXLhtHV_dDS z@Go&Ut}mht>%i=EpKpO6eY^HPMFmV+6*Nks{mPPFU*)@!Z>O{n+l&eb4Z72LXDx-W>C>g2%Gj>~} z>j)6XjxA?IKECv3qsGwX)K+H;VA|FC*!&(V6MYVJ4F_1}4XzBPnztJNPS2T06~`6n0gu ziRSTW`0Y+}B~P6qf5SVc?013e_SsQ$jrOHu>t}xN&EZ&>Zl`#6N7Gt=8zdX45uMRr zoAcY>=y4ot-?lqeSFL&_PIXHPD1M@{7g94&e-nzw$CP446dTd%mTU5to4=pc(4+!O zN?*dU%vljj+J$g@c@dfJ2wQb(|1VYAW;-VF+$|t8@_RCZ>fFuKVicfi^yLp=} zgxuUfvf6QDE^=d*7kurv?x%|eRq_WCBk@Ex(4eE&IQ?r-E2-0`=PGRR0awGb1{TAV z|Mm9#qy+Odm2~q0(IVn19H;ml@?Ia>_Ti5FqK$#TwD5{&&&!s7@;0loSSN8<4EtP) zr<=Iztk$f@MdGB1e{ z{(nU8els$A=dNj-3`4zPsVMgm#CW;q z4u3QeFf$BcGr5$eJ>tBy+tzk7eiKvV@0sIwibG%gi5p@Uc0dek2dcQHUjetUVi7EaZ-N`)&`!-hnGSY%wEpBU#g+QC~{(SAYI4~oxgv7gwqWI>}_C%E>?uB-rV9a?j z?XwE-(Sr$7PrIOHSzV(n&FmQMs`lht1!ZgDW3RNvsD|RM!WLsp%0?zL)kA*<{C;0b zmVrVHb~StHvF;h9A4I*Wt`%&{d8=)>X;(DGQ{>WB(WRtta;E)duE~a1S9KvuH_od2 zmtqyue3lqxRmMfNlZ&5M_GwC<+UCXh(I3eRg(1!q8OKbDv!iziWtlc2ss!-RCt^+t z9O5P^Gx+pV%BG`Eu0SsG70OGu_WFKQE;q^VvmS|Hgh_?|t@b`( zY_Hw-#GseGSQ&-ycoH)guF6uQNom0sQyqz9eVG&V8S`#_#SH>b^A_@qXfHPFOd=K# zbG;C;r3@t3z6C(6mhX0JOb0BKrh4?|i!f{|hd9`BY1`hGPW?GYTH&cqN zNv&2JFLNoO3!Rrd%w<_WWVuGnsLgdIGXIZit2}n_ZlR%>8kHP(Cf*PZM?`dmw{6m` zv-j$nxVr~m>4dV9YYozmf6>l$`#vk_QNHo-k%&@ zzohEWJlTf^^z03}F3~j$LLv78_$4a}6)*k~89LgAJv3F1rVDHWe>C%9q2dth(rx>& z!aI?Niqx5?xe2JT>K09n|5P&5v?@%qL!d)hk5{Eki_hIvHuq1w+wyWZFihgKCJN*P zr-F)BvayUEdQR!WD@{Q&D~fAhdoZ_}^?{X~cPE5iqI+DTq563~$hs^thO!>VbAE2o zS0dEX;G+VJ3ldg%dT2T;JPVpkIk*{A`l_I+B|FIVOT`T8gm%93s=#`7HS?f_W)Z}@ zIa`E6WnjWD6;S#vY78hS1N|Or7x+NH4d$DZ-XSeo?adx#$Dr@$>YnKX9XRAXCF;EZ z(i8NGo=!z?^qlpfHd|Ki!h6-5fjncetLJpMMEq+ZqE1+O&mE1bF-_AYzeJIlb9sTL zMZLi5WzZaXE1M`n&VDW#FXgk&W2XAzd)z-F4cecI#o-s*LQflOqF3+f*m5$*zWr|X zarf?WI6kcOEf$P9?SkArdH|h@^3DD=IBSM}9MTimG{FBjC0nepujF8Ol#z|hlKXsKL_QMom)@^zR0%jaYZZ>xbdFH z8SN$xdxiy5`wf54#d@kPYg6p)3e(|NSzYWkznVNba=xtW@!zdD=?gdzi#a46NnUqeIZQMw%nQK9ggl3338zQ}})vbZRvwttKZ|C0EF`C$*?ggq(feF@xo>ZG*2 zEJ;B5R^?x8y;JI1qh+cwaL%&%M?_RsS~==!mydZ|N9j+IMl@ zR4OucmG;9gAN}%qs@j#7 z`}o7sUFW-af!^8?-r{8I1k3fD8 zx+08&n8}dr)i&(}Txcffpl$DTHvFc8@a*!NpI$NGh3Ehtmb8CFGkS6@fN`(|V{?&% zbzh?nRpc7;*t@P1J}R;dy%Re$POm`BjSP6HM28z8bI~+v#TwVjm+QLb3)u{#y~~Y_ zMYf~&6`2?;*GSI~1C6dFf>1%!Sl#1^N;8io=A-HXX%qXvHH$kvGHjtuLe6s)tu+6L z3eo5JK|hs2DN}8 zBa@Ij*Z~!6@XDNq^Xqz(A;sl@;!C6Vo(8N*Y=3J05^*&L-u#e%R)~eHIBpE*Q~bj0 zdgts;E^58Ld%<_qwo?o5C0T3^IVHE*pu^L5$rwE17{>T|k(O5GYC0+#E67P!Iyzie z`LlC;|C(!{6;c1rPUw($HElh^*bL>-su;fkrINjWl~)q`Zli(m!VMI0o_%5zDmL`) zJi7xTX=fzV|I`p`*q*Sldj5FEH{#}3YlC&bkP}4P^%sOqVKo+XzVZ-zj00T9v zY$$X!R!fPtiHhsCZ?J;zyl0^~?=3}*1TP9GN@1;54oq2519oMDn)gn%90CYWGP;|e z-XQTD|A_9wyKbyF-~*K{A7P}jG~A1TDzd}S{TdWBY5=29WWfFcM#GnvzfeEU8a}}$ z8-woz#?w)N>q-}-;r9ft`G5at?>?!wTR>((xb1Q5qx1S-GiWTa0p?Wl=tg66-E#Z& zgP=*9N&*VTM!ymi?h(aj<@^Yu?B&>Y&1nOFe*KTgBS@ieB|=UPXx!~-OiX$t2uOd) z3GKvKBL+ft`nlA1yiy*v#k_H%N@n&*tMO-JbRhTz*#}u-h(*vq%Pqq;CWj!NsV9(w zy~@D{y)u>G{}Ju)%i^dM?6O$6?`#C1E(->Z;u~NgFyjh4m$qXe-64Lp%9ax-!1AJi z6&uY45Mf#EkHb3tsK=|rX%=~;yg6bR_BNgpwh#R?+M6tn3kuz9WDfB9LI(r256HBK zf*2#Zrg{v2anSJh1LtqzZ~Rqs*QyxBo3i)G<~n}=h+pKW&ZDHcr} zt+(oyuZOtsg0o0AmJmDQ6Oo9@Usr3_fx%#BpZwZUh4 ztFlBIhK8C1J`uQ{D;UUO+U`cUVig+I^o+0*-RLrQ5 zuY@)=!x$m=HJLoTYtBA?r_$(@+Ipw0i|wO)C`fH^TteNEZPH|~A<3cmk7=Ly$!#TE ztP6izfbX@vk4lG|y5pbM?yKqvYaZPFHDouZeRxuZy&X{@`r%qcZdw0xbiw3-u%}<& zEdSP*y2ZcJ%#Rm)sP4?WrjjIKlaiOdp9HcbAk$`si2zhWq3E%&7VT& zNPqpykWJOruUZ0MsQMaHLO0;DHSF`ZVjZ?ps?b!=Om!S#T-LMCBa39sVr(0h26hGW zjXd~*dsViM*-@OfhOYft&+owhj!1ysyCuXFbX+l`-o0^XwT$-3Gt{E~M^zrRC(-)*MIbNSA-YLw5mpDp@=_L%5 zn=@d(Pb5x>Gmq8qMHqqID-(ugb`XzWO!si?8PzvY28Ndv)L1Sj^yKCA`Rr;ky3TDB zU3?mpy}3gzR{BN_%@keQ1aMTiHoyakuhiF<2* zAi3*owhu$n#QB-B@+(Af0Y-npN4y`gx*zKWQfo${-HqU)j4$uz1=2->j48gqXB|3Y zDA=MeGmr>ro9PJXSo}i|=5#C@R{CI{{vQf2XYC}R@rqJ*iQu>JuB;S|IJq&oD91Yg z5&O^H4I+ynggBg#V1JVBK~xf42(D=$tVY{-QA4|E>{Vq^)YFjo^GN3tg=Xf^7?<|~ zY550k=JI63Hw{z65!Wt047D%W%9uRnC%?bIXGl!gf~v?mN*}(B=~|U`4F}nx|?8>pm2!7?Mn8)g`Mws|Btj&U1KkgL3iYUYRSj&Yi{+-hdxnp<)-kh{yvSLRU+Cqj7>(KppA!<4TohO-qfW-^BJ z3)9K^LHA>gNDhdriKK}pl+8>yX0p$ezr{9&KOani>&|AWa_V^q4EjGGvJva0^4`K^ zx!0()N)#3{FShGdiW6o|R#F^3+bCAP_FD4NEFKHx7ry*){kg; zl!}X`Rv6#(d4Z0`DMg{9V(6dK>Y9a*0ROh2X+W>CEGLeEVDJh2Zd`Q1y;6iSdO~B< zn(ry*WziWd2Xx660zq8C@SpK`s+W7#OnKx&;nSU(zwu1tpp zMIrjeHRfBakWtzJtZfF)@%p|_4B$3eg*4~wGS6l?>i@1IQan39P2H&1llMg zC&b%{EC-r4)A8ylqv1nv0HXI)AI_=fXBWX%wwO0wpSEYHH}wKy3KcaNlJT{M}~NMT~zI$l?a;K)ZzG(=F8z-|p%Mzlm*dE?0M(5OSm$ z{}D_bADrPAvJvCb20-!3H3DW<;d62Aek`c2KRY#u{opUpwQs9zn*i{G=qYykgJXj0 zX#i8sf3VQ&&3{Cr{O5z*-vXe~e+qR5))Oz0cR_ek9q^Hgp4}0ur!`@ENNYd-jOu5XmFd1@wp8w7d&|?MlBO^JN zm(L3*J!3^(_lDS^+@I&qOH((el&$kFm1|}bp&vwLF&g$0X1M~yM^mRoSZB+5Q6Ggs zK2>3gm?VN$wim;YL#}7`_X|mXx<=Pk%j1mT^WslBu2xnOy|{vhAY(kDw${J!ht1E! zSQVk3@whn1Z%9?x_c>K8eaWlh(8gG1eVHwa<-d6Sx1}RYge#n!RlzTfsKNAeJ0ARR z+J8hcEwwm@9C$@8ueZ%K`!N`(0ZM1(^;e~c%Co&_EZzHn3aF2NKjb5~d=TB~<$hQW zoH~F8W%ay3BM&UGCU)!IoqpbbM9o@3o(IQE*>+vJrH&K$rqxjIo5F6H5QCd(4YYau z6!&JzRXUrZXrZ~gd4^YLFf|N?Aj>@|&^70bfeQ;pqBW?DX30q`b3m@vAjn7v_K(>&+QU}`EK#nQ?4#xO_lt~wB ze+F1c-vW0F#B{dNaP^~y;mW5(ca5_2Vx*m#VK#3t7HUW&T>A=!43r{YWusPX{iIji zXPk1K`^Z=-*Wls)*p&_BcT1Uho+tGeFPDe+Dw=D9OQi)^VB6L$^7e-r(_E(n!JL*y zfz#*a3Kb8T067*HM(`A zbyF^;OCIt;lY_`}+3>1qfNiU**=kf%;pzgZU3*L$=z}!UuVvt#MTU~be9gN(F5Uc1 z$}0a#{U6aCYRr>KK;}XDYKYwpDk(V`;6Y(H2*N!#1We;)r6DFApbDGM2kBzWLzd30 zuEEJ^*;~gSA-^&z4Jx>!T5O$J%v4S#hN~nR-*553H@LU|wAeP%XSIX|u>OWJ%w3S* z74%`T;?M{6w^Yjm0+es&BrAhqHUo?jTlZB#-C2s@JKXa6#u2zF0&zuME5pK-F1}BJ zDP>c2A@6kFyRUT3O1v3OXtt?veoC+`#0x<6k!PR;PB%4wmO#Fjoaq_Z1J8C;#bylq z(}tY0tid?>nDAuAl&>OKoupH<@NbAl&KZ`0g8xn{rknyb-epMV+@!{Jsg)gcE87=D z$<|!<#+i|pBb-o+p*h{KF!6|l?b?!DC8>3=$h~iWyC?AZ18j?=?ud*{Al3}l5IkEM z&2;aSJoyJRYlFUFuFjt-kA~c;WZHs_Fdd?z-pj-7K)&&2yYlDj(FteCj&?~#0&kcb z9WPBc^WvMP#`gpcqfoJiPJCU~+XrGw$zJdmRY=HKvM2P@^S_1s3nc|3hl*a=zLqFp zt8TqoF0eg z3#y?PlGkq^FB$vPiK+n6M6#t9KP=m$GKsqlD2K|(+}Cek_S-e?4*J4bhH z;}Lgcl|p0ZEHp?O(Or9ap$53A*Gx)|jgkaL>{sqSlD+fI1X znEB`_t8JjhWK;|dVGMp)Y8XVcsWTsa*!xv3=`8Q^nw!IuSo2SzCqujDYFbUTcXra7 zmI5EFy7(z8?*K<*FadNZr^<&K*_VS|4%SRN!B}G}?Tx8rc<{$xsqwRiCUG0lASMIB zI-qVhYGyUdBP#_Nf?g{5wAzNE`8M^s!L?8J9}O=#x%~=nvqw@_7tkMcP$2AP3;BTJQoz9d#YW$pQ>(lXeYF9qh9|BYb$5VH#x;|lZXOUS)8*i3s zYle|RNoH?E??$J-r*?<_C&1Yb$_*C3QcG(*XxVwp%;76_wauatC)@M>Hf04~H-6T- zM%iD1U)|($SoyEbPG(d;2bATqBdI%Nrcyp9a!|RS?-BXnY{5sJFDvxK| zGPMd($0y@se84Ob-ub2I z@`6D{%)S*4-pR0Wz9LX>OvsfJ79#!k_Qv2S+<`gLpATi1+{t{ieP&4RNRpJ2MwY;C zlGqZKYJ)1$GbQvVH}v~47}Twuq8hmN7>;g_7W=|7xL<%H;gy?w0;nbF3HePhK5_*n zo>N7 zTS%X;x*uq4z7kj0)2Q)9>{Sq7&cH_Cj4KmCdF5zZwc0YRPHCrss5U+XOJGrbG@)fTZ7&$qNOR)uyM>yl)SYL zxvsR=Ax}!hI+ofw&d|Lz;%hj6?{sc`1?vG^_0_nQ54dqwBy%W4{o=Vd zDE@SP;S6ZdY)mwP3S(alFcqzq-M5rrWXug)N8j%-m2x8bL0Rk5`voMWSlt^f=tIFn zb}$`Zc)Q}}HxbFLG+7E#G=sgO)=!hLPscHi`JaG-^<>Vq+7eIS`MNFY(D{iad`p(h z1IRhQ^41_b_U}#r7&jWez(p1EaQcB~QzD$W#r&nuOxxgGN<27T$wh9QdSY3IikWd6n-eRVs3&1iZzYWHi5Bhm~_4(YXZ+;U$!uQSB%}!FcrY!g_h~s-FJQT%L6)H{<<+u4~(r;0;F07eBtEix9?PB#;=J|pXXKum)x~B zfbueAB;L@B$3lUFv?=i+*>Gz3!_fHX(fmq-#8(VQvk*2}OELDFEKyfrKI&KBOcK~O z$}WX`1!{*gq}+g3G@rqlp-+TpMH};LHR%@Kz4%9yEw>B~Xr~C^B)D}btiLONC=L*R zgU?Q?oxSv%jucAX7cNs290QLBJYd53^kvYMH7AtNsAo8>iq-m>J4)F*0Wpfc4Gkn3 zk&N))kD|fdiXq;kUR7h5z29H9Yn5yRJ*?mC%kFnu<<@5onFyuE9?O!Y639F_gUBrR z)cYzG1zZxOG(8|eYju2(i_{dp2pe=j)WF+yoy@;!SK$ugg!cZj%0A}MuxY*YhaS=0 z0&#H3xIub~ooWLDd{IZUb6Qwfm6uRQNHnVJZa(PK8Vy~8JaUGbc0u4QScZqAZjH)1 z#rYIXZ(}Vi2b#PuIB0CLNHH}RpvXl5TPQuBSRZb%xme+WYJG#4#p1a^Wq?`PnX6$F z?YEMM#tdhhydy;RyNfYsB{0e`=*dAU$)VC-=24fi5$oR`8XCnkivO7dImv(On0HM* z>hCg(x>+pErTMgrfK>?+JN@!`hegE6!nNL2<@ZV@4}(K%qQmV|PN^pEtAxml;Ilq* zrL05*VS+k!CkerY5W&v2l0!-i#-}253|fGreq}DS;WRS>#s%fWg?C$d5GC3b#R<8) zu}_TKU(hJ8eJ2&G6o}M15iPznU+>?x!wuCh7E~3uxZ1A&$q_h(1e8$8;SS~H=Q^8G z3K{d{Bp&b(Db^bYC$R^tl()D`oGEUr+^VrT5^5>TQWH27R;9L6YHqPaC#a(z34_-= zWZ!&h!u_0LAqCdJ(^0Ow47lWCx?u`{VR5tZF@ug65zZS8K)va89>}rp_`W@ z-J9i$C^(oCDEa{1H9fiLSr8fdtTHj7BZv*}%sYkFC57GD`|UnG$2SI&cH9YSJBi*-xk=Rv8gNQuf#|*L$MF5Y9T+r*iU%=`ZlL zD!tgCvoOXRL0 zoSZ=FHaOkR&qZ3k%dpjM+|HzQfx0)xTnII}zN~{d>zTW6rdKL|DVW0`v`ffEH~!i@ zR_8l=bcs}QWV*_=KZKK5DeD|Ichp^0W~nT)$yLx0g>U9!{9?ywXPd7E8l3Gc4au%| zj#c!=Yni1WEECcw^}VPVo?6kMvb5El=dOF*DkDhK0S>sH-3FBWYVn6vHa&&zFeLs@ zArsI%3?%2mtEZSoiXcy0zb&F49U0zvc`#h{DN0!ppiMTy zBEESd_x60eh9<5V(U8O5BOiz{_XykzZ&RV4YF3p$wi(@nwAfP4 zlR_)-D>dgy-RjCtbSqbWC>DHf)`55cQk~uNExSYoqVk0=n;wVJ?TmGeM%(!+sP8s5 zqL%^^HuSyy5kJx(`w=*Up`HMV11Rk8}?e`7}>Twi~e}4hXCk^4N-)AZB~WWDq7_yyBujQyh%yEk%LdkqTzQU z%5BqjykQXRGcgQ_64f0{Gg?VVY*4WIP-gBtS6~1jOg; zf~BYo%Nod6^an?$Nyv2Cj;GBjmpAtM-7(w z5&7<3oWj?1S3$EmD+RIlQg*DR$A1OAKvccaI(w5mE$&->(|5PCL@rH9t>n7@Acn27dwCnun8R$modVgx{5g*aof z_NIzVdw|SGT7e+Z{&i6&o%Td|HG=R8!Lf~t@Fi7bEgXWG8|r|wmzPxoIjExdX0->`*~4DV%-6jV6VQ)6w}^f5 z2Ezed%0MyW7&E3+uA}O)lLh@kH65w@eE(>C5UDCZ5qZ$-IJV`UuP}Ce{^m2BQ1CV( zitn?Yf!f|yN0?#EHL4_eq}A79RYf58F3!?yWaH+Y0wU-TlXd@Guq_b)^0M&9mfnsNHte{g}Z8za;1ynUXEw(S+ zA9WOPpD%$Ti#`Z_Kn-l5VPpi}~ zS^%(3*Xpxu9&pK7oU@vh8zo5hciF#zijy-niU@X_fP;;Udk=#Q>fym~&T2%o^`)_9 z!(6V&Tb~V_98}27{TVy#&We9^nxEyHNF>XED6)|IR3A2-kv6j2HWbF*20MJ!=irxV*9 z$`@jx#&G}m&rj^=Q`+9$FQ0+t=jdt7S@$^Qp>GIYx*MhA1Y*;9S2*`GcK_B@b25*#*t%^ceVBEIT?pspLNJ>W{6eFu4;VDhFJG8LM1vixOE5*meD*r6 z+#BbrANt!(hk(Kpu&poP|Mi+rQ6F6ay;@)it*;!`+*@RIu0&} zc@6IP8Kd+(-B~dlfATEN64MvQ{Jgx`T~4Gk-08|`liP@8cjX-tquFAyBBgra&-886 zqc!_wA^E{kE5j-!V~TRIG9XcCvj@(EO{hYhiAAc4)TUp5uWmZ(|QmV^gE!AI(?Z zo(>?}>~5M+ThI<$_=|I4y{*+o1f>NQ4;95{=R?i0(Wtt-+IEc4K#@X#-?Q~w7s2x^ z;4}eAY*N7zm<98}zonrLT^$(HlHzTrJRYNZUOsmQ!?$^0!+UO8HC1iZg{T% z4f-D$*%N-_<6vlZvxjf~hEfvn@ys2*r%VR{4+vQ^C*W^j)-n|?UwSGTxo1d8YkjtL zhP=1mE-|KrcVbYu<`|25yUs>?gsRw}xgx(VQOrrk@ zRUTOx^JG-Kb?qk2-x6Xk=sc4^4Szf70pRNrvEq|vA$j{14H*&EdiaNU~3k9rsH;*1B>hkx5cg(%e=@)>*m%cv7-#cHb0Na>j5lhFwtn;8@)f{ zO4X0;gt z)+P+(-I&k7fj5(Ht~DHnD|A^lOeQLr@3{T=RX|r|;-o8UK9k=FkT6NKe5gS`LxE5$ z><$IeV?F?#!_R*-jhIz^xxG1T`!am(bp_xc8PHoY!uj&uF@I0Fn)*GdI!oHc=C3$c z7WDypSu~dF&$ti-I+$Ky7O5z7%-#?d1HxLj1VEO3mz(N-XMM;uTf4A&{oTE3+;p=H zhQyZ(HDmK@E{U5v@vPGFtaZ1Vt~1@h`U*x;rm%F1f2EaNq~j^f zw9QCR`E)BwbiWRr=X5e%tu>)G?v+y$=#Sz#>-vZ@CoGu5V;)1>{f6|A z!C6yPepd98mUV_egiO+Aa`agV%e~zF-8GL|^mXW^kM4lrlQ(^Y8Ie<@tCW%jRa)POzx`Mt?Sl) zx$)}a*KFdtG3NO$H!9>^vU2E73P}Th_5S{&X`ablE3@x2>aRqdyahwt2UItotZ1#p z1TvZ)1M1g2SK0m21KeM)HF6eBSMY7p@WkTu(HoKUI7=BQh9o{Yo~<8Zg_rccfDN=5lPFl1 z+UtRMR;|Gu`yC887&ki+?Jr+$^0@gT_%O~Of4<1>1qCPk(@y=P-4|*d&2bAgm>&J` zy{Uwhb90@-6%FFA=BZV=?tR*&gB0HN=(8%tjXB+j--nbj#4-p*E`~=TI3L1T@Q(sb zjLal9{yuq93ZML=0Y5V>qJ|DkZ9*cHw2FM2ESe@xoeG-Kje$qnnMhI#2|8o4+KOw<;h z-ebA~%XqQ}<4`i+# z3N)(PqN<}ro8V(F`6SPG55aW!p*8~IbF)@J_72vMYZ6(5ZrmML%-YeoJ#}Jw9XG}7 zn;ujWlqdniH0S7x6nKs5qmAt|%M(Yo^g9i@y1I}FKy?@!$!wHbc$+ALL10lk>MT0_ zX!6LWpk7(^K&--#o`LPNqB}SfP=)Eb4&x%dtZIyZE|Wg`&^1S7eYz){P}D|%Orl?s z+Wq=g3sq`JVk?OM;Dr}cl^wO%iG;)_1To^UYst5|Vn@O}7ANoe&Y&MsVfdyw5UADC z7|jr`O50aNUMbcD@YmA)0d?;)0JoFHdW(YW@(TFAiVojkqK+Gb?dwzqB`i~zP7 z?vHP7LOB2LvB)Mta$mA&0h(kYC8{HmgtFB8o5dfe$9}pd2-H6RLq*KV~_6i&ZZKkR#YCYoqU2x_q=ZJNXp2tk2lfD64hI@ zoKo6*AF4R;@v-vrH;F;Nd3L;mEg_xEF#^1JJJ%-5$^Wb#ALxj=qn0UO6`4K099l~d zpHs%KFI#*=FyhrU^CuD>coi``wh#zqtCBz6QXT@uN}SSX8XP$_^+!A^&wqcUE6wRG z(jbi1#-6u{LvHGaK@fvRl1G!0;Lfyz!`!~V!?3?rItKTt!zp}IsKshVYASBI3K7$f#5XSeBCIVei)`Y(VLT= zi{m9FY#xC-yZ zn>x3|AIw6tti{7zjONRUiZ>2JXSFK8M`vGu3rSXpTFMadXPcv z;@LmIB>Dk+Tw~LcyUO(UozrwA7@z&4sjsHHYUvpdGTc(Uaikyrj8+(pQc}RmUH_89 zFckT=*u=jWv=om2N0VkX)m{r-Q1<8M&doD5ogTw+MasfC9hn14cT5#C$M{ko**=0Z zoB*`{B3<$Ci1+b1J(3;pVgz18rijMY>FYU2lu!z_*_lRWlcb44B;c?yV^?T*jU=~& z#Kt|g-3m9c6Y3j1U|v=TeEx%6x?CW{ouA{9-2Ap|=E;2C{$AM)5jBwo*sZ zy7*$QS18aPg7w$I5l3vY8=Xm1md8#3q6`{}gDkDTjfJxJ^myWJ_yLW9%O`Lt0tvvN~@e-Ltmdbf?a$=O>)_TQC(*kq;DXqB` z(~+Wpk!^bilTdLZg&efUX|PkDN97AVuZ?K%u^?p2sSgdoMD?tSgl=X9cvVl7^1pA4 zeDd^`py+Pa=Ox^9!Cn3$ zqezn35vm0Ww6)MN#G2SXNp3kqgv0#_K)eStqmyQ!qdxwA0Xe!aR#R46HNMq87V22c zI(>=`f!Ab(;zT-GKA8G{OykUP)2wy4$EqgnHIwll_t~E|r01hRr=!*7fssml=yF7d z^U7?mTu~_jvHIrEcdz*)0j&XZT{_y}pA_GdHBaETXgcr(Q&;aq`;R(V~_ zOdyzUz&nu<=I1daD|q1!*E!AgX;qiXo8NE0=P-gqF_Cw7z|+JP@4QtB<{f`dYHDip*TBI>4cDMz2mWFpKwiK7bXTG%zwn=oZurPCyq;`-2*M=RUQ^WB~X#|7A`r~U97;U7(Vrr9Hz{;;I3lv~k?Cc-@7 zu%~jw7ilNH30vEtF`UM}0USWbOa(}_c)9JC+)%Uh^Y zvJEhmS^@}c!&yiYPUQ})(iVT8G{1uR+H%iF9{{ZxJq3MM=Qq$16>k(TV0V2jjrc@W z>-!|s(?;@rkG{2}e&{QH`rX0AXfA{Ii&>BSpFD?qj6uw#s|^>8sYeO)xh{$Uyzfz? zAW(PC>_9vlqU`ll%{NzuEz`!@Ulil$jE6FVZ`^)Dj`vSxJ+~)1jiN<$(sXm<7wUfL zj5~_iegg2oWE>FJNKeoDGprotXvz|UYI#inor_HwPT`?lc7md6!>MWvy;fWEh?5d zJWPOZbbg}{ISdX%SAj!N{Il&x+t}U4-!v@;+1zfo$RSGiNkc9Ey4~ULyd2-A>sG}x zyzRzj8z@VvK{*{xqWXSM7wAZ|4%Wy}!i3XgiJ9W61}M!fyOtmqc0qWpXr-aW(y zeSk6@J>+#(Na3lT3wrgK2@hxw?AZkyLiNb;B-s_bUDGfNRH1nF&O4r3s^+>H(Sa}~ zMMK?JftPm$Xr}B(Wt*N}^vi~_1(!7N z0GC(Z-kz6Xi4L0pxRrbpuY(I#$5;I%H)+>PTB&{Uc_(%C4fj79S>+VC;{MFJo2}uA zJ~)|*GA8*IL*;O4`3-s61|KX~Uuw(-U9le&++?1k(v*9#OkX~fH>B%7YW2Ef100XUH=@eO zO%lLSC4R@pSLcc}N$+V1Q+>Y+QXh+)r!Y^V$C)p??b5f_YoTj*s2W{SEtn?3lC|c_ zG4K_N!(l&%B#q7c2F>SxLZi{}3|{8-Gp^g;KeB)H9cQC%hO$zjpep`8htFTpoNVN= zv{a`KPjp#C`sAk{sI!^lQB&uH3u^3ki-6m^tba7xwvq#Ga|S9i7by%BFW^}q=C=8t zR=7_b!8FtU%>H4QOSfORJx4u<=%PBi*z?d9i@RyF&VA7X&XNG_kZyktw*VYy@oNi} z*W42r^ItcRc5JlRxBTouvq+iXvsB{c9cK8c^YhIrF?h2Wu+sv)%s){HTpx4^r=-?+ zFKw)TEpXicr>YD-L?oV`0rz+c*@sDHj-WqvueIuw`y{E)AE(tXU~@`)vpK#s4v{r= zp#|QaiXJgovUCdMr{ZoB-v;U_ioWp^S-(J7D|b51gC4n zOa6J z?2nf86mrk8B*dz(nX=$EJCQ$0oVf0sM&M(9;Z0Zhr)iH%2yxa)W?_CYieXGo$1`lG zlQ}Jk@%B8R-F4lv1fUpdZ0+>zwbJ{ptn$-M@*???YAO!S_Y~L~ z5oby0@2h5cIV8|e-wzmLJpVn#Y~qXd|VU+)mI6-ri>%=SD&eL*Z=XlHkIH^ zU+a;jvBhX%rMI}L;@ErZe(UVa(1uufmeB0r$97+3PYtuPr2Rhy8p(7bN9C#zt90F= zB&p$GyzyMXpM9aI=$G|?j^A-sKX81bmPd`J>a6YcWq_r@gx<}tk7Ng;1#uuPZ16&Y z4GNY#>=qrZpsWWNE$f!_oGQ(DsLe!K?UI~9$LZYNx=-Dd-fm=$%f`KlJh6aPp@Gy7c>-zjwm zjCT{0?kGpd{2u<5gXM`@&k9(=LK7+XKsVVT*=W9c+G#>pEasH z662I6X>wQax#aUxV662TSygTn(aD=hn{w##C=M@V7H2|ci zvrGRj961zoZz7isQou-mbyM&w6V?K;W8KH)wJ*V8DnI7kGXR5#sa>rex9P*kwfOrk z8qe!V4vVcUc>9DXTpWHh?r47qV4nE1lZa_|F#g;+r@pANP13zlzv{-Julw{X+&Yf( zV`*r7-`q8I`iXW;@r0af62h?WHpt_G+1WcbmTz7*~FC6X8) zz8cyEy-qb}fExzGu?K8zMBTZ6G^>SThj#YwuR0y~P;Rt95wi%Uy^!M3uPz%>!GEsg z&``pUWQheqBZ)4Gt$qR2^rs*Be)#o|N+@tD);ql%yoJT6+4(#y^%*8-t-b7mPDe1j zUM-H#5k!d%|D%CWZ`#97OtoB;srvA*Bk^~l=Y-roXu4+aPT-s4P(DPyt_S=EjAs|f ztwhatFns9I5BAWRY8wTw6118jpPfjnJ@#)( zr`VM2pHvl@xE$y%Q0W@UFSfJwBuyd#EwK-EdkHY3`OF!bNZsj=3D&MfWuX@>9{8zE zs$Q<(%&U47HGtE3Uaj-a{qgMX>-Kt+IP}C&tYLI%Kqj>?dC8C!*1UNZf(?Nw;Q_18 zoZ!rInW9;xvpDuf0C8Il7TT($WfAHdOCOUX{BtcwAFOd*CKnL^)fo`>Sou&qp2rD$ z3u{Mn=HtP*bB(&B)xHtZGxcQu(&<+XH{h@7Avo+*v*sTS)3$jrgGPV@jO<9shZ$T$Y^Ss+-UV&To zsBS-%_->BGJcj8I;EoqV@>%sXq=)G$K9=|4pQrL*5k-5;^mW(`jWL_znK6#^7* zo?E?X(l!|#|3{NVpJR?nve*pnkJru%1iK#J|DeJ%3Kc9+E7)rE%1^Li4b=(YHn~UR z-TuWK5CM#q{o$=3@Z*c72ptE>**tgG$fL-6alZ+jz7u#uOHA-9J^?G&N=;h%Xg$@X z!e2R_`6Hx}<#Iz**6#fdTKo!{Pes}n{2UAFl3@Fw!iz>2j8yMV)dp=WG459{hiT9; z#$`!It)SlmKOiHoV||t|5l}s_-8^UaEvdK!cadHJm5|LXMwrNuQnI0z%;2bwAeWC# z{9ipSl?&t{IL8I>q$I3+RctD~y{qs!W1RpzQdguVS#-4b_~~A3%D_B(4tvY$As8<- z)T#Si_eED0U7AUP-Wx8XT9fxLCF<{e_P@$du!A}!F#rBX6L5r#LNBEO89bu_%UaU(*(=dpjaP6QIqzz;E}$W1VJg*=}rpUq}au$Gp(m4tkky31k- ztm#zQ67@KSSLv^Jw_V}J=YF;vzAyuHNPZp!!4*yzSWuRiZX;g@-J+1)EK-3X4TMg0d!O!mro>jz+#5o@=zY0qeN- z)1OoX6hfb3`7dH$h18(RN-WTF;_@GC-jQg(cLpA0Dv}bh$;-?U6j|R|W@ai?$Em5H zLr2>7g|mR0Z5%pOW5b^z?E=V1;_KgfYs%)HVdNk*!0X{18AF=z#&|K4=wXIX>vwVz zHsKib1vg3*=iRbO_O>zwj~|@2m@NMuThO%i*vc99ztk0w-1d)VT4M#=C0}+}zDG5? zir3#gG`(Wyb*icHH?XQ2U{35g^C3r)IIxc<7b(=XNM~iZA<*PN(txw)?q!8*z*%C? zxF_=G8EIw~v}&dFZgrOmQE7L*IvnNDvtTU5FOJ?^khM*QNRTeEh4)>wkX~HC(^X#K zsp&75m#E(rNHh>;^`h(is}BqH?+B?A8S8(M5%^|mc#$2ivxNC??kg0ytShLg8k;sd zDC==x!6UNcRAMIx6cW~4gNsrO27P5}Y`z~)QJYPPWUUoP6Kr~q;!O2~?&K+f{Yr{dEN zPb1j0Bh}uQeiMdv8}3%Tp@!ZsQik`MSwV&|6S#jgB=&yo#&Ov7t>m4~Hk;BrKLV6o zep0*$8sXg9+!V=vNqh~l&O{CbaW;UJ2^}lAN51YD)CmA&!RcWD4Acl8`V$Y*yZbcL zVEgScw>z(wk4oQ9L_69+g_|TZ47-Vc(%)gtR~6IOz3|NEhEnfZ&tpwYXXiPIj^jd& z$bqlzXv0*)Lm$;}y(uft(g7%Z{ZB6O#+`fA7Wx^<>2y--hE!*IGNuN0ev&XyC9(fX zz|e~x-VC|2XxqS7#@rDNVM?zH#h~I;%Z%gL8 zTc1b|NBM9VQk8wU=frj(?=Ngy96}4n4&wWsa8!!R_FW?^J^n}2+EQ}DwX)gqP;3?O z*-PTauKLUBW}4g)Ko$@C`aR2Yx;mJeFLIAaWd1-sT+ok7`d&z#6@Kjne(@i3*9;gt z96rfC*_hQl;gKarf5CZ(4m2xu+gj=y7)wR6hDdPEpR_0_nD@O-EMFU|Hat&<41vT- zKs-09xtao@O$fs(7w68PfT>M1iGz)C1wdXFzQwKvDUvo0Du_P``4}jy zPgTyEZdIbBj~Y(8V2;#GW|@N!AWyR@kH~o%U&`jFZ**WAZgbTn87sZKaQO9b9OOmG zZ~s%v*wseoNWS_Q^p-J@E_%kEnyW4FhL4?ZXEIudz0SEyVhonv!cbY%okf=wAeP~} zZ$&h4K+r%{#H;_&NW8{nlKiTx?B{EDe2?>J>ntTq1jl4A>{cXLoe(#ny6(k}Q$C7= zHSkB)T91!3JD2VQe(K{5Nj9sDkQKRa5~ur)8@ew{$AvM1tM?LGjrl)w(=e-ovk?__ zd*QBB=|nXS@ok^gmDBQe{OG9NWrsoyIy#E^cRygqutyptrfmry&?>-7*mx*fztcB} z;m~sJ<)rZH@9b|-u~}5_A~M5tJ?1+&oW%AQ2*Kb*GACP{oXerwSUfTEP*q zkb($6hkx3wvd3CX+U0IIw)yN;%A@#rw5dt_Mo0_f)&rI1Q5BP16N?lPKqv(S zuP3LpF8rgJ%5_by$g@f%&I}1=RZBnE%1xsh?k|kXhZ=58GyXgV(^5~@YYD38mZoxx z^Hvd>bp&~WL~|e&pXjR$Q$Gt`{OPP=*2?+{X1YV=%=ab!B6p ztOu6(+fV&mcC)1zP9=~O&xdL#bGI$E5G3DShUmcX~p>!taC3&s-cN8yx6Sjn-nA5@$q!Cx{1|KK_+Xow#W{+9Rr$Q*C;vN~*W z@^6M;rMM$fI%ZGvwm)+bk{78>MySwZNZ$Cw0{o}(YECc?S7=rECul))9=@n_|NJg` zhVLN8Fw|}6*eJeT{gVOwoz^4!PN2 zV#lJAm*7ke1kUIWNs3lcIt({&FB|z262`OE63k0yy05^KRRn!QV^`<9CQC#ZWNw{# z5`;*jTN?ya`a|YnN%{Lr%XT>B>BIY8t?XHEwj9b5&qxkj8$0+jWY2nk0F~~X8){l- zjy;^6TVgEeVGi>txlHXCud5{9n%_>Qfp&gL3d!18vJt44-T#~IF(mWI{~QSs9+XPG z3V9*Zs$yQ9n~TWbKG*#)Wi%^QqAgq0=rMx`6X2h!VZMq_08PqV2uvA{xfrYnuW@*O zT%x?8UVk+}Ca4_*$JVMy7g2h4!JC)i^VDcfjOAEjX$BAq(}hjI7{0Z_tC^!tnmmv8 z%}*BETY~;xP7!FWpxp+0!rPvbGzpunZ11EmqH}i)EeezcKWfr#?1Sf3l$YG*)!G$& zIF?rrAA!ISbEQdGygqT}C{<})gH1^ZK~hx7x=>cgx$ViG6Z7?oY-YtY?>`zKpK-0q zIDU?D1GE%qVT}cbHLKY%By*Z8cNY0q1VQtDJes+7a>Whg+>TbE{VR_Z=(XyO*k5W#V-E=Bn5% z>uik$8c*8UT$4+U$J6i88C3`O$`FuK{Fk=pdD-#S(zUddq)5su7mwa3@C7-arx1tZa08*^A@EmBdC|)~i_oMVY`JSvcGt_LNCn z#Epj}nMB9g7|xSAGdyV*(dx~*OF#zvSRVy5?73ju340Of7@tUR;V3GYp8asW4 z0^-Eo>88s468x5?3$E)fGRj-)*OB-sO&$QTuI3X_aq4;?rq%tVW!7a1wtpVC^tzWr zbSEcs)JJXT;k3cN3z_Ovd7}FLld`U<@3r>(F^77bTz;U^I@Rt)NyUq$yzar8@P>*w7@@INnIGiUhv+OHfxgklnY)~u5mbkizvL{o~lpn-E zEDoGmj8g}k{Ej1+O{D)$bGd(MhY)w<&uJ%7iFWdv1vT(2sBy;|3dewxT|)@(4-1Er z4AE81Q zyOdCVkEy)d8Po?BgK}|QTA$)oLc*&@?3>v+nVxo{kT0-l1iiD8@sbbD_?M_7;qgHn zUck8l_!wc3djR-)2&OmPiH)q5hgvL?bu^kq_NLAbU5NglJ9q?Ek;`Dl9YiH_C%v-! zUYYYlZVFkmk$81cqz+RjZVHMx`fF->1JC8#m6lwK79?m6T%Cbc|OkM zeVMtf-yEyFE*wHmfY+41tozAeyx6Z>;SR!;4&vX~5Q(?esFXWRKxhEhY@9kfUw|ns zHhh@`riaoM_y*cqL}V}AJC33K(<81?_ij(D>X=Pw=?3NHO0x?WKVr4Q&x8DTXHb81 zR^dtYHmv8Hxm2Q-{JzJ^;he_`n^TtTZ){i7%9z$yT}7tjKhi@ZPyW$h)KT7}o=uq^ zM%81bzoe}ew10Q;p4!_`Mg4R5Ol0p$>{poJ#Jx`&8x(s3J=p(o_ttMse}CLKCJG{o zfb>)lL_#_TGv2f?X~`)mOj??4CP+(54yAL_&6FA;-8s5zvMhY>$?Ak`vh0c63*hlJL@_^TG7^r($2zYzW5Z8HZ^NOzwaTW~{gWA(yi zvuN?P&455UkwPPiS47{KFSbXOTWinfDseCpi@%`b6%@Tye3%fm;S4EBv7w}=@IKC?b#}mzlz?D(kC)X^owEs#C zX>E#!mGdqq!7jdAPA>m7YpI^R{o^qDZwf8*OwHa1ZujzeAHFfi6tJ0?O|yXSg;AiU zk{{g-w)>s0ZO>Fo(ndAUOK^Im0G-S0kQKd-zRy4#)xS>4T1yd%g9jzgFki+#kbT2c zS`>JdL$Ys!B*}JGl@`-ScY^r~3Z3#8Lh=)T{w*D3&vT~(+Rwi>kf$PK>2>^9{SF5| zL|T>}jK~PoPSY{lD=CVPo&oaD*SuOk2=ZaY&m?Y{waT5t&3Hmi0?2oT66mEQ_)^=0 z#K^2LMpXE1pX{X_^S6bNdC^F!$Sz;rM|=*_Yblp^fjHH;L(w!$qG@LV6-3$u5#vfz zE1~R&>-m!>bIjOffA`Hba$#D|m^(7CQp;a)qg(r$Jy!aw3UL}T{`_u&p@RP{xjwva zJo}Mg3-&JX>1d_C6(QcDium>DunawiYs=eVK>8YKdHgQ2)z?1VTPnNaEE_9<-7>?@ zE9CS7^z#^#0dyZ^wpTjPahH6k?;lfr#YUIUPv!Pe_R6X%>>f(;!$x!_tADI~8RgRB z3YHll`*H>vwlo&w%YHwVwHW%s>qs^uwJge>QtJe6=SGmnR@_=j?-4c^P_4|=r&k#DLzV%Y8q}aUnA6=Sv5GIE)Va@x$7rUgd zpak*0x`5Q?_Lp7~CNo<6ThC`WBAcWi8(WuNIWr)6tlbSg|6?ZL?q8gM?LjW-^RM5y z0RyQ>y#I$>N}WI)+WA?z;LF+2OQfS-_SixWv47BK~otkFs5y zYXb)1edi`|V?QJcm&C7}@C-@)Tw;pL=+Q|IPZWKZr0TeT1JTR>eD=IB#VMjw>AY5{ z@1p!yXmHTEMKOKmr29FahxmQ3-PoaOmZsfj_&%cx7JC$y9dBCX153`f^@-JJg;gfC z6{y||(rP-$na$aFJLVI1-Dn2_SZn_Nj(lv&Jde7(3Aq6_&U?dU?$*#4_sW5s-()sD zaSh$_YjR56!M5)Ea@@@L82;Dkry*`D-*$uc zR=zHhYmdkz0D18V4q_CZz!Z78IaX7WQ&judUk_Qy?{#$}sjdbA)pOevAZOykr{?zxyEi!p_^ga?@4(~~{mtrxR|GcTGu&!*1-)DD= z?D9*ZkNTr-=#jD-Vd(lIK-bI)>)qf#na<&_(CYZ4C45RTRsZOvVPbrlpJWs z6xr(9!ybK3>r|w2d@UW}OTIR%BN)EeV_W-&x3@98pCF|G`B{SU@*~9$;oLu$m0Q#J z++&dj&P+k1I1>L1PEE;jHagF<;X{WC{Lpam_*VrnZ*k)BZ(W1=bN}dEn2-rBDp#n$ zXyqh&xFeNN(XM|z+C2`1_sBwz7VYR$1w z^I%w8J#txID(Lq9Y3tm%3LO=C-I`yIC5FEIEeDx+bwSLhMk@n(JzLuq{gW3JD$M;O@uc1cqI9h()jT$V<*2>64$8@h_IzVXei(1p{gw(5s{&k!wr~jkR4$NFi`R;+JZkiv-2Ry6}ECF6Jb3V%4Mv) zxVS)lhSsW2q7z3$15cujr`BmNa^na!pYOoYou(TZx$xv*80zK(uR~3T0#T3Twyi$~ z2FSr97KJ${7KOp=m`-D3PJxW~%;sdBlR#?nP7psFz6fHqxIc!y!}7%G4ioS9&8xgX z-8X=&TEmtBSn-?V9cviJ=C`Y&M#|tzG&6_Rcm@ zQM?m4PJmkV-$5=Kc>v}4`MkW|2w`AlBmXN_`p`d?C}+RMfa0n>iyd48RiZ=e#%YXx ziFa(7T&^@4inxQTuX*fM-cYT@^c9jTPJR=Lk-S8sv!|?NhbpDtiprngJgYl%&!Sy| zT^&D@K0>tGyxFfZufm2H6sM`M+Oku{Q%KTtJtGN%c&{z|g!Tx^-miXHZd}>|H_qeY z1v8Aq|8Fn(Fo{5I!F?3+j1Y8*-&dY}?@&;a+tLH}LPL6Or9jgjbd5@A zYHJ1?)~$(c2AJmJ-{b+Neq(b?i|n8%iQ7|_1oB27J~HIvP$Q}|r1Q+`PsOO{nqhF5 z-8bYlCS)nDTyu0ZisQogi0N{l&w)}D{8;FZdD02?(~n<$pFBfo>pkFf7i7q)3EL>KEt8FZWPSEiLt&PjatGwL9IgvPch8s>Mm z7K3Y4Bh*OZY}S(8+hO)0;Wd>oUX8g&+qkNxwWiT+&qc}dxRu=P=yQMy4hV;{Q2XxZ z;yCDSXW7y#t;HIlB=S-3+%d1n;*Qs|=KZ-c-<(a89XJAhH|&k2XE7wN37PX+{@vU0 z9&|OT^<{2ZIUy&4+dedL2enQBf!Sej&513sOsEyhtM=MkZuXX`{l|rul(Mctfs;S;WRNp? zr1R>ZEm%B>Kjsf+(Cs}^8FT}Ad;Rnv=04@>iE>t7Q0KlBV$!E($qJ?Edh-icr2?9f z+Y9SxGHZpo8c>;LaS-})Q%hE#e_-j4ZDPBMvD}(J{g(dDR{SD* zkygo?+e~h*SNrZoFIxukI1(`Hd*}UJ74fX1-f!kI*unqkPRK(bpK@yt}fc)}^7o4ApwSW>Ki zzu@&J6k&!2$J~cvvjDg9@ybh{Tf}h!NGdQxw&d3m<0~G!GgCChl_>8-fVbQ-s~0eD zudl4WZFddmV%*WYHBTXYqo@uPC;0w8O`bMA?lPaQ!CoextO&Rjh(p)HNO<6-t3KYr zrMk>hMa}Qd!<-d-&x&n75aW(86AIj){IC+ZfxkrL=gj$GWBc7FLHM?MSvHZP+{pDo zjIgjFOnQ}916n)e&6p}uYd*I*rylk)?NyfWA9@1Yk;b+yfx+rgdy@67+L*|U>`0aR zxE8%n0>FguN8Q?(Jqv^(rrk;|dfoCe%2JbYLmPZU`e5)7+aA zQePX77`4hV0(ri?hCql=FA#3ghv3|;RXJ-ORtX7?b!QtdbU3A_NT2!v4`2g89eamy=PV|LBgE z`*VTm>Up6}ySpYbbnnkcuRwnT5c@+rmsR!8?;bL5=n%(AR$|BC^G~?GDGE@X2)kcz z#425&j@`@Lpgy?%WQR1e9$M9NS$!5QS+S{=ecd#xnwf0OQlp@-F_n(9wB^mmzkV4| zp{fU6OX(#T`dhP&rGGWH;GC!#k}Fz{0BWI9$P(L@6PBUTN=eehO3Gc?^F{QQbqDmx zVg-*JubW~EBq)~0)?WY#AD;mI>P^Lj1R1|mVD`QSOclI2fI;Bs!6if%nPvKWGtZXc zJC;pH&}U~6svu#greZ$gx#?88ERdv=cg9DPCW-}s)Y5Uy()z*n${{NG_79~znJtG+ z709DB8=2i8YNf#4R8GuwYNf3GAke)-SSb_mvP*?)%^TlhNEfVU`xO--=A=(FhTHkn zxcSJ)0tNYi#yiX}@^@faMEECwh|akp!!}OFyx$c% zEV9&OuR7Q!bM`-HWugjixst6;G+7VyTIdQTYjF><19^<`<$uLmKgZd=n-)6i^?8<} zy<@o=Z{#yzEHaXYJ}KCGD7AboaIuioUmMrRmn=3^Y%$UQU?wcAN!6d#@vvm03;X4! zKx|_&3Ob_JAe|LAaeQIRf*pCsiGx`(z^lG4`Dbizb@y%6umxD*xz!@7@WnBBQ;bdDIS>7GXK7gqhpm;PV;d*WyG z)c4xR(U|_d1pYf?#x|RV@uvFilQT=0)YJDjrD2)1K3x+>618qV4CKPvq0;rYwPRYlzFRp_XF!t3#Q#OCCqQ-RwqK(y9q$C{2BHEncOtI=^V5@JG^IuBj?ENB(|529Vwo$CtNX zs_pb-*J6ZI=bh}Wr?b-~=6wq>!(%b=Qir{6hSv*4VsmW5H6lK$3C?Bla~4d0!fD&u z*7f?0KFCikunc$1WnR$Z@ofh^ST`kfZ{2lnU&hYN zBGcm?He%5k7*w~!E72HOKCvd!`RSP(b<0)Sz|Q#37>(~VqDikb=hc1iv(BgHINj^4&g_w9+L>ETxX_)))M z{I|~L?7`Kj9#V?KIBlKw?x&($#z=gj);jjwB>i`<4rwz!$yy84m927Z{Joc!(uj*L zDdPwIHLGyoX@;Y?gTJU=fC=v9nkPJErRR-*6+HQhIk)bU+LT+)uoqn96`EK$pv<+}(q zOX4|RE{bujXF77|+&d6qH3%4M`Zn#%1@NKyM>n4at0=UtM6(`GzvyDDY7S*B>L9cw zaj2#hqOEYhFkwg#QR;M2D6$fAZKKfq(5NA5418^8Wk-5~Pi8(xglg^Y zCUCXpIr((K8O}wq+IpM{36SGpGkj8x@qXN2+#7jgn>9?prBkxnN?KuPNzpdj)<_u~{k`e`b^9G#l5h+@t)Y z*8|4Y{J;r+iN*;>ijA0=y|uYFciun4XHfw+T1Gq%Z@7?Td zAKX`H5jO|`Og)IgNgemc!B*K6@bE6U$BKt>_Sx%BdGXr+RM$fwCqvEmO5AS3&(M(+ zT~x8NR99e;v#%H!^U++3x8l8O9vwoYnn>7pIGjgfGuKl-*ydZmsh&#c&WP!`i|B;R ziqvc}p-N}&C%jS+5&i8x;?PtSfhH~kIpRl+&0G8n@V=L!-8Iln+`14ztaxD&Jvj$= z_dJVRG%?rChg95V)1ogDJpL(U$U&N8|O@Ilg1 zsTm@#Om0UWDtRVg3{&0K!jfn+2#3q2txtP0!-^+<%go1K$45D-4t$;Y#$2NAmNku2 z9VNxvYL9s;y9kv-Zld1ofSpi$&37yw{ML0|r+Ko|s*X?;nIk;FQFx8LLUdGXI0(`& zrk3~GMNm$vi=^q}CR2SzA$xqI3qZwtKe?Qm+kB^V_NVTDf3fOnZ)sIa<+=jlTn!bX zw$8$e4AN=LdRmk%s$E_yQCz(9z-cK-M);v@NqwAAiWbRQtNEnHaA8*KMS;GCuQxGW zsMRf`zP}yCy@9+vkV#h0$=4~xj&_d1w7>QnbYYr^Qv0eheC|H& z=T@kjAWj_ji#I6~6d43)94>AVg_u7!^XV*6)o;k6Z=6qTwmD==$pCcYh~T|U^Rtyw z!^CS^N4+QxB7RZUa!WSj$%ph`wZ2Yf6mRw&(v$V1cPpidXOR_R>Tbqn`lWr%b-=M z*?FX0SJ~jQxt&;?Hd5t6T`f#@nyqnEl$jKW`MQm)(l1TT%#}G%RYz&Jk9^$hHI_4T z@aTF?H02}!5%)>$(IHBEpZ8`B#I$FA>PC>HqEi&<2j9yM0}aGT(4@*%kf2;M{VnM2 zU{_h;F6~E!9=_1!L4zDlwGInu0(Zw8{L6s0=Ag=|DQlc;wVT;>nTh z3E*i!4lt`uw_iYo8df#^)xKLpxVj>s|NGX5PPY>reY4W|0IE`G8@JFubwLAGgKDd2 zlj}6;H~sR&`yZXn6N*#DtcEQt1;&AOL~#e*9N~l9aC&>@L;bZmmK-|#P7KHH*JiXgz8pqgb)%)rVQG4o2 zC3a8UkD|`pguw4VIyv3Pwh5OUMc@7}gLPb><$kN8oS}S0hON+G?I~upPi|l2YpoUZ zHXxL%T39NXM}tjI3${+%dm74BD1si(ZoU~gwO^~5L%f{$flT1)6nJ42Y{Gf1@uP~G z`07SY zzd#dN_)*&lCmZLR9|PZZ;>+Y_R-(=N^}Az|z`=ZqUx5AclQ&x+l0_3r{IyW?MypuE z?q2>NHt1F%7(}}|?pKWk2}P#5rDx4NSmWj7J~MqpwxxKYBCu@YHsxv9;3IXo@+JC} zZ=XU1&nm8~yvK+U5lhr(3w;Io&Po>kzBNkT9U0|OWubAl5~p-&fr~{H$iDGEx;8hi zH*;LWx8+k3x-EWezegwcmq!4t>yfji(5Dtcut=oG&V9YlwwGzWb?I89z-p}%PgU+M zsYEUXO>fkS9m0@&j@CyYR=jlkT2I9!XK$2$KdQ9@iJtNo*X|ZfQ!%ITqyJu|QI}q3 z(C;JDfu(6NHw}50-=>62b*(0x8=3dS&7{Tc!rdaM+tC64=%m2UmPDbvj>i?+r6WlV z+K;w}p}NZ0Fl)D}Xn-R0a(=xKj%>~v{RMbqMqY-xA__i7CFd-uXaVUhi+ew2ZJBYZ z+~FO~4C9rI@7Z~^yWu7ZeeyqEpw2&`h!FTr`dsAB7RO#01p0Fc@wN)zq5Z^q-*#Pq zMPsWRKmVg!xJJ!vgug2Lni&fad9rf59)Clvt7B_aBa$0`MEvy(h#m5X{I7A5WPf_7 zv8$@{RXFfhVG{&XOVuX|E$$KZnpub%Fab`t%1&!T0MR`E1x4}W+A+~XAgd1cD7RYM zvD0X}>F2(9xybxpw_xyR_i}NSW*^WO1Xw_E=@_#@lj+9(@=F3Gmar*R=uqSvQ3oc` znJv)i*9(UA|NZFXLu*q`fK!CFZ*-hDfgD}01(8@y*CqN(f*1kyj7o(_u^+>_U2si( zI7Iy!6@G+2zv)R>WuO`Z`yIdR?s)Sboo!Ojp%i5P`+*BFX6X{`B!QEX%XTJKhiU@$ zzITr(h-k@cN3*m*rQVQ0p9^TRXON8u+d=s_aAwux@;u5#ieIfoARfyOCi6{%66qw9_i2qqEOyzkb8} z<1o`_L`gRCC9?R2oHdAw4q|f4E1j?#j$H^<6x5R1MeY5BQ#sE5bEs(9&jm5+={`KR z4Sc)AQ3sfnOwVAJgXA=Hby$|iI**Y63LmD=^^G|o;;+w#i~tYyr3q6~Yd`mn*KTpw z=T`?zg8Y_tw5s!a_IG#?y2{%P)A!$>o{udM4w7K>wJYw#zKcZ^LL|<(*vEUUU#3_! zZQ5-*Auc>Sz|t75tOLB|+@cCjcJ>ctTPuKlx5zqRDQ#0rgfAX;8WssMQ_C#Jaj;5U zqz&-{VYe+$3$rSirG*JluWo3VF`_u*T@bz&xY43Ja*++iZ zDDxU@9TfV@|Iud-o(8rY4IZ%Ac(R%NXQ5o=lJ}%EtuqMx82y4wxDb6^2j8>rfYz0dFa+5Z(ZS-QbK8w zqnodz7w>F#PqXmCHz}oz&w#Cn;vGAnL|%$bvxumClQYZwtOjhmrPCC6d^Rq;gbL+j zCpzXv0=_@9xslGeE3S5=Y}K%=M97nuSY{fS$her(I!%PNB?crcp6?j`zWRIj=5K+( zu;Y#8$r4M}3a*#_^*867S=_D5tFX7^4N}k*o|dzig7xRE`JAe&DMKvk6C2@oc&;CP zi7xnaiec#wOg)G`T;_RoZd*7~*v9k8iD1^T5E`~Kfveajlya|e z!Tc?*`_W%zdeW5*E2B<278rEgq*h*N8(Qa~AOt+1_$P*e%;{T?gS@t9k4f?C@l| z7q$f2xsI#~C*+-Ij0Qb8<-&e8(1oe5Omzm0%Pmcyder!4$b40YMI!2di*wBM7-Bv$ z=b$og<+NCf*=?GeeB7)o(1sGi4}2p^PGXMqWITTDk+P0$pArOP7E7dfHME*T49dR+ z#ZA}RtIpvj4o$(!hAoG%?|hetF^iz!v&`lJSx!+rq%mYq?ZMGIFlY_tNa3XB%Rocb zd8G|s9zk!^bpL8VuFn6X8^ZtQpk-i_G(>tL!Ja?8h83sYN6_`tQQZvmQBrnKAxcr^pPaEO469A#2QC zm!?03^;t?AzNJdVEH|T1bzd4gEF+xCpPhWq{!E=@E$FXpw^H=%)wU3nK1gwRBwe;# z!Gcmc%R9OCf$Ok?C073HP7?Zg9VQv9mRB9K$fVca!8Nt{QWF68I%x@ekg||)fK|@y z2UI};k;`(DR%W6_vTa3N4)Pm`ckDu_OsIkkk)eX`?tF@`Z^e0hj zGfUY?#~|*nF!>2bCq`wI1`bjkhkN8!5FA4 z_#6w;^$Askven}U3X@iE&Py_mMfeLO(Jl!jEe37BF-Ett2c8V08L)Qi2-cZ9J|^jKp9pl_^cgRue}R@O27SJ5I+pnc2-JQQu#Q=pdM};Ae~Jw_AKx5st={!}n;%Bb&)5bQvfHlEq0f z^(O_g1igx8Bsw@@E)HkSTKn7Idk}K>HaP8Qxt$akJ-VBHe;={`m?E+an*`cd_B?`!b>&DEqiNNCQ{zW1#{?g09=)oi z|5nCYCg1UC%RTiUH`&)7bB}Q+uN?yo-XeO z*8V;$Fi#O88$SFdfLay~eu_UBEQGwZJY7+<~Q|E31}WZTT#`)iDM}ClHIa{Ij3K>{Bzerk6-k9etobFtM*rz|+hVTR_$-CUX{DyhymIvtr?1wV+DOQ`( zN^~ql*-+H>+X;y9%Q>!p@!OG8a>Kx56RWLT)R52P)eCuC+b>zY ze;cwL_IS6Bqf4a>Iu#y=&6srpr%&817dE%Ty}RRJ8)jAdnES~YgKw-qiImlK9FKfQ zdRZDQ;{}RGeSvhvmtH-OUdH%RoJ^gMlVs|YX*R3d>ilny3#wzHoTi7jGzEDUq)mG+ zjRa5M=y)g?iSUXJ2((1+jv)PLt4#Jn*FR}LGvnvwJ{#8JX`Y|*WV~qQ+5|O1i>YGCi-Apvb+;zoTnd$`YEkUEq zE$3`&zLf~SJ)ddQh&ze*fqtMpv(tgf4jJYlo0q+~GYU$rI`!Q~@%4W^$?-~Rt`*{Icu#w5 z+9Er!fx1C~{(OU-R6;hPY;*S<$tsnrvNHi0Dju+nnovvb(519QMHBW)Cs_k&SFI|$ z>}o6TgJae3n_6Qb4;?qs$8y|qTMlNep1H6b3_V|9MQF+5fD(=ueDz01ulHiFJU{Wy z_viTc&&Su;R)2WsYueSB<+`Z=@e=xWoue{%gqX&`cXR~8b zfI~E@#F7!A+P!$@HKhC|MV;~@W|tLdqm7yXV}Y$1{E2AYSO{rr_tGl{mbD6V7JH6$S9xCz!R>ju?V#ecj(Upi-Tgt6SmZYwkF#I;!q_$sdQ%86bJa6|253~%Am&i$#J;|snQA$Ibh zU5hd*GlW`vlV|;f&2GGtr1XE;AZq_(gD{W}Pu>t6z4xaVHt(Nt$XaPbt7h6}Z8%!) zo?gJz$=1!I-qWrU1KpF9^uCn@rIoBqC+EQ2Exu6bN)P#m!)Uq$!}iS}$InsF_@Q_S zO1DA$c8*-NiEa+-@oe=@Rn?&fM~<0i`A=$34Wr|e;mqbjAklI5s&s> zWHRs9E&JN*@B6To6+ZiY-dO2O=tOE?dy^(L0@hG+4c89udH<{PF#Dq8CaXO47&gcA zx=n^?dbiz?jg1OS66c_rn6wmZ%(gMQ;#17=qgL4YsUX>XS9Ip&L-bu~nTb^=DBkNB zk}HyD#;iM$?N)NOVo zAa&FI%*aYbe@TqLRUgFtLCOw#*G4fV3~A48q$yC0Vu<4#IZbW8KKnCIrxy|~bS(Wa zkYZkeB_y12lNE^B#D;m=C*`hHOLO(N4)e=0ju#-tQz$MfeghO!`2G2He_i-hB?F{^ zy`%>^@ z%B6ctG4Is_Y-*`n;hB39ju-h<)?*j=BeOkOWG*Eq|DwAP3(a9jt@lLqT?(oo8zBd7 zYPfmLW0+>>6At}!Xa@5bw?MPt* z@9eBw9RQ^wI_$z?NSjD_xEW_<;0>3z<$m_`t8ui8{%7Z`VQQi=m3sQ4F*xJbA4RBd zy2{hUpCt`+?`w~2sHyo5`%tDwo43!tsu_kw1b_^Yf5zSa(Yg7R_j$*(B@Sr*;C9n^ zh5C-c*oBGV-agN&ewjl2bi&_!fE0E%0ZNSMNb#qa0}^7TDWRB}lUj)HG3F41SY(ybXtj)U1BoCz_fS#ZHa#dk8 z{1Bp8bmVptFuF9Rdd<(k-ljttT7e}GmOY~s9mY2AQ6rA+n}~ANwU@T5t}ZHWU!SC> z1q0zp8}uK~aEya(B^zVWvk$tEJ}Sk3kQ=IhPk9G-FL*KdCNc83x^<_=Q1ods$8kV= zYJ__Dj}BaCI71pEgKp7gOm13G9uJh-(o1jDI;eDawvxC=hw7uHGQ8G329>XBOuPgL zlIxtB{Kss^@;fUw&5oZiA6;z3Gi{@xVj+jJ2QH|5+O3hisCmna4j4YOKbZT99e7XG zyvw9tgj#ZVsCZtiQ+jryy7(^c{`a(4#34+N){bQ`H5n~!gy;XMpZXKQer`PYdvrRE zoH-9N+<{3>Pj~ryu-^FLpX2^DtH8#cehrp~Wdd`dnJM&HZ*J^d?wd6+v5ppARR@kZ z3B==90N_o`8lo-D=HGLd^0Yl_Ab4+(`d?{==05bjS(?W4o`Da#uV&?jHQyp=PUyye zbQ#zZR2oy!cF^WiDJ=h+_E*H|R!QP;OF(sqC%V45#?Om7#=ipj@P{Jeb(;P>4WWCj zWH!iYWLIAn=^J-E_$-E^y0gJK*eRT!cMg|l??$zK<^ ztxVzM`k(8-uxXXkrY+VJDu`7_s>V@GU>J-tt@eUlAs)sSr z-I72FFf_R{&$1GyT1yS4Kvp&~1jn@_4|I6rU7{ZAH-!u&Lc5#D0J795JO6U>c-C|1 zPxbDNhE+t(7^`NvU$mAyuFk91i~+Gx?rgT=ng%>(Z8$r!2G2 z4|@4~MR+P>B^`uD;;eHK^QHXZwW)0B4#YWa>DZOeY%4t+`9-ShnoW^G-ev5{ zij&}OgW@`xXdoZSz-l~2?z^tV<-|FgJR7AW*(J24b4|+fd5jvjj!1gp*X#<=V|w#5 z+#hrqZ=-`^qaj8HS5P%<>P)>BAx&a9#b2U4+{d&Mjb(V*$A(@>xSIL?#hboOA@1HK z>;;$S*P9vHhvhejYog{2OaX$H&3JOcb8iKT5}F5){l^DcEeVA!8AsD@Hc5PYo&+bK zfVOcXsNZG8@d-2&je8x>z2x0+eS05T!VTr%zl@C{ z4!1SmU2@zmt1wy@^48ITo* z<;eF`wID0l2L1yvA$0z&nEXFF@f8CI37kXHJQL+^Vnt@XId$057+#|f75nKy%#=mg z32|re|q*Bue8#=G)MaCLy zPSQrP<+LlrFTrfP7fpc5@7$%IJ62KnB`PuzUf=Nu%ws9fUK|Y>=DEt6dfg)lfS732v*}Me8~HZz}kmhS02Bm4im>aVEYDE&wBRp zAK%g~>hy&EquYyD0~+qF?Y?w%_&k;fW=_tfv2u?q@G@Z{C`F z%leM}nG>^<&_RweQVtA0u&hHs0RqAVUc_9WOf@%kfrHr& z0nzkH>o)2<-;$F_{irKQHS?k+Ex0+6oTs?%w_z<5{yi^jsdy~sqySjh_xC{qc;OK7 z%drPoe1YJ&>u)NPWXx#uI_q(&s~3-*V}UuGZIgK=g%Y(@w^zNf|~9~It?dn*~% z>@KF0Co8U+!&uQhPj3u{UVZ+xiw1TmooZ(d>-*8kQ#~9JIGk0L$U&*5E+b>Uac@5K z{$gvdIo+#3{@eIr18si%tCmw;Ycwjo@$Z_xteq?I9S~9%ySe=P#~+45Ped2SxS}>} zbC!?uVp&Y<1#88tlKK5Yxig?O>yY`9$GXlgEeD?jB50Q5yECB3NMR~8K?I{*b2@#X zDleD00&>p4K>^pcEywQvCs{@RhbhJCErz*1B!x`qvVI!W@&xP=wk^*8uvmegckA-v zNEiPlfi%ZeP&f9$;$PM>PiT_iSPS%9r@Dg;L(~I%Lp+=3OVAsuuOYccp2#XaO?R(Y zk%KT|K)k7lDTUcY%7A|=wNA13zX_9;vI{dtxxB4ut4Td{gt^90gZRpovKpzoCf9)G zc0-#V_JT>ft8&@n1?g_Xm{i___0fr4&Dsv>7qt)ZB0TR_vk!cts<@SfE_sS5CF!4z zhFSk-Sq5IJl6T^jPy?4&@I>QeTJdblI%BJup3>hGvX|-!I(Uo>v#pu=3f=1n7gmoA zbPl)AzJ*}=Fi4(FOFoNwQA6Of@NZeG?-gD{#q|XSUSTD_*C9$=0ahvMEeS93*1FDK z)NaKMrPShj1@W0cq&JNq>(n7f!x}zqd&`bh0${hI$OeELgx%@`#7u)5?F{?8&L!^8$VxpF}H3nJdnKrOiV)uKlJ ze?|}&r4N{9nW4HY32*+<<=^>7H@E@Ioq5pVWt|k|zPjYR3rw5=qR`hK7+HxF<5lww z_0SUZ3_9~bwKavpWO%5e^HpFPog^6iEy^R>(@74?V-qdbPv9|Z(s6PhcswMz@nQ24 z(habGc;2ia*t94ny-=O(e!phurS+x@w;gw|r3U9eIuDMxUE1ie#*PzN*9l#L`8e}L zR6av;#MW;39c4MsP4&qnDa4MPAs`l++xY3kn8?h$P2Ep|4$SIT^<;Oy31)2GBeSR65{owc?h^x@(}>V~`#C*K}h^Jz%dr2nMh2EVOXU?Dd;3A53&? zlLuGU`29EwpE_A6D5wOCJRg!~n_-QrBFanQW2kGT1)-zUq2@4lLL^0JwVoL z(E{T7cJBg|xw}(9z1wQ`oj+pK-xy%G9PgrQAUl4|Y{PD z%v5;^r3jECM|-`txo5}Ru_>aoG;77*J6she*;XHWRwWh)h*yu8fi!fs=6e)%KFLv+ z8e(8;>{Wi2M?D_?qqj4DsFF^nl*fTD>yqYxRn^`FzfawZ7J=cM_i+ZrrJ2CF)P*?* z2@}1ugZTFa6Bex4fd#np>3_iAEp^mH}6-TAsZyS0hA%rgRYPE^~t@S7DlbL z$IqJt1`F-jy+)P|)R6qTMI87H=Qusi4`8Yj%abl1#3ht?;ZW1CYRIIBGtvl&_qYNG zfc9>7-g=e7s3m#)0m!3Z+XsDdAmAb^LChBa=t@T){irlhc5~0B(ZyLG1M7M1eLGph zN-N@OWse3R02YRAm|=f8hKyTLvnz$IjMY1!p-wH%{s=hrG@)Yx!n2@jG!qJ&evsje(x8rNmXYR^_3p zBJE@HM?W?ibfiQn)+=?@&3A@+Pg2W_J!rnDl_%gquI!(!M2hoyW-s-p86u!J-TMDE zyYV=DZ}V=y)ANWCdag-Q$4pG)Cr6vdm)sqpvU?f3M(=gihvZ){IgHpg2wOh)`rXbi ze44d-T*!6OluLBfMjMXFa=S=FYq)dj>*F=Jm_40_a~=*GZM1jmP6|}H<;0k-j3z~y zei|4J++sv%k69>p+BQ@rYinKWX%mUT*p1PjkVA$J9)Y z6u_Vom$ZL$e#|*8rpy-fX2V6CPdx&abI~b2PM_^^ORF@xA)MHGbn{KZ&;EQrIiP(# z4(>suUfRx9O$`9}ndg?Kny(Pk_mkQ|^pwX_kT97pQCCID=c;cUVSDOJ!Jz!zOUR)e zzN(HObD|+|k3?iJHtp{=xRz_&OZ+(h;7}|F*K?1rjc>N&31*|8nc~&w=UD}257b|D zPZ3<+Ghl4AZ;Yjx!OGu|W_)zD>%D%~*%PG~`X~BN>KgZ5%WUUS9M(!$;%9_)= z;8&R$a-v^`{$AUqO2d9mlFI3M;RF%f9ODR*huCAfKUbLgsB${^L+AQ$#5mtyiPnkn zO`&Z^f;K7)cHyW1V|Q3(bw4WEn;(>Xa;~hu?kV=G>@iZsUHp6`7mt0c+C$?hV?`wU zYTXZgRJfCG5XNV+Cw572y2WJHR@>Vi$0!2hrNC6P5YW*GkPi(g z0$f5*cpMX;H1semD3%I^fcW0tH(u`V?k4NduGZ|2%0gKEK6RYF*o%Jt_2p!uHF#3d zhkoSF1=?l!;uQ5YHI#BEgPEG%D0{GjHezx1x;4{@e?(JY!D1T`i&yO$ISrY$ru+)j zlc@E3!c;=E2!QMn{Kc4E!VLm73}-8bSK7I;lfO^0@g4MQ>U$-qL7Dkx|qxg6sfzlOgt%WoUnwidn5=iu!f`ccr+Xmb-<* z(+p0&E2@q;@&YeUC*euB6#)}s`95yC6^Y*CXLTFIt-z2$g_A-llsxL^AZ@S;Sz}$I zF~d?RTY927fMqZdXoC>%ypV(l|_OQW`sp=O|2Cq@PVFWDuTDkoJg;?uQ@UymIl z(5F9a{}*}ILsT^T|G4|^f41KLeXXiil@5v;(V~i~y=tVbmnur^O{%uk-YcmpS~XgV z)=FE{mfBlt#wa01>=Ap%iXch9=l%Hn7vCT9;92CMD^~Dvus(?aOsb3MyRGt zL!mRb{-+!~QvXZ;bEO5p&Z;x9_r;Mi@)A&opaz$^XNag#TI8{W2L$)-5}CQl8TW04 zr4cM@0uR2=_ye_~T#Ef(PLA9=KRy9uVSc(^g(M^!4tH~(!>4=A_)alTEVV~T+tex@5Ouu_gR-`&|Kd2QQ*^u|wmjN&LAMC1}%t3I1 zB+h<_Ls+fu2xWz*=;o238qK3eR^3~EQ}@$dcbwddVlVnaKO?GEF~!)#x$8S}p0iJW zOsvf5RNB+Z9_(*{TUL|FETd;YDCjw(xXSTYVi;;N%Se%063l$~U;ZtK9|@3fVgfs$G%i7?!&_q<)8?U8YotGHurKIM85mbw+o1u@hWFbZqm zg!ZWP6*~`4mCqwJy&@=>snY}Jxu{jUd)y?t&@9D zlaPOevyU^?qJmuylAtj-XlzQE@AuEBR z39p6SNI7!!{07g&A0yv{xwlR5X+j_V^}g1QCndP|7Zi5prsN)m)xc7ZH&RQ;e>WLF zlv>J(boR>EWU&GiwYM-bfJOsQ?7RFn1!*ncUzX~;M+E^wFJE=qXnubknP?C7=5bbW zRz$H=(-6+wo)gDyf%;f~z8u0;t(4ue9M1TskrlF7g1>;{XJtny_In4NR|>ROu1YVL zh>MR?es^TPWSLO1-%Q^}T_u0iCnhx8m8_dd{7-pb*(&SIV9rCcdA}oe$U*u=jr~O~ zC1^ES&7bvIsk$vcZZ2&ANJp!t-|}-@y#nE?)M9(W(@=J&Y?Bc zYBJYT?Hxa+{G6HD1wLzM`R$gO>6jS5;*;dw^qn!W7`+S~{#RfbOXbFh&pNj|3f})P zU}IovVxa%des3+g1;GR`E=9F(7K#{E=r%qCh#H~|TGIDEM=0_b1}9E`Hgr<3UQLIH zaE8x|T~VlfxLG7HbHrB1F!7xskt%DOc(l1|n_n%3S#gDH@R-$pakfZMk4;bzD_I+{dG(L(VhyYz5K<)j z4v4bRm_TNL*jg@=(-y>cW=yBB!!zY9dG4vvkXMMP=EP0w8|BZKbBpOeJ!xe>MHRWG zhAh7$-Hxg<3-B$}dijlBpm6I6DhBPcJ26g?&NvHva_~?^PI)_MY6Yes93|Yqhasv~ zQnwfKim5ri_MbbsNNi1KPUz2S&Z+mz6Ebm89=ZAo&WiN2iCGYy;o1Ta5>d_Z z4iW{I+}QcNRXtKO*S;2*2xNtVuAbnN&8896tL+vl(0TLfDaEFK&Huy&qM+Zlr*;#= zb1wpZ0mTcw|L9Cqgb3!|!c2A!%OO=a^5n*droh4(D<8NE$KV#+LbY`o2JfSw0ND~u z-0YkzY0!-8?`-)Y6X~ol*;D{9oqjniMq^)O@@0ik!++ASXjWM{NF~{@EdYAr8W8Oh zPV>=Rw{_+UYEB{A%3B1;T(&e3_d9v@LugjoXVfpiQk6@t+&kx?>9>=K{B>Z=HZgAH zj}xri;sj^#C-yZs4>bdRmz=Q@)9yO~Y_L`RFIssYwew<#?5FIG`Bv)&4@^x5CpvP@ zy?oD4KS(DUjAAIb=$gupq3d4oJ;BdUq~T;_N`oAO!$e5F$r)!kJ*SyB{@$Zq%2@(4 z(b{W|nNbALwRX3!ed_rg4xYbO0MIcM@)mH&L&VH7Cn?$ExJ?_ZUo9HjNpmf-bv={TQBdbr86cE9EN^3G|niJrPnn`U}x!U z=zG_}mTp+ynV-u}&w{GOGkYV|9FTAI7kE6>ENaO+a@$tm%)v##n5-;BU~b6@WnQI@ z-IF=}jT)oe|9i`-tKQ#fD^CqV;o@K*_wXuO?2mmQzLT!HDfr%Ntu-=+H5!i;LNC0bCL{NVp`rbb)|GZxGw~inKVty= z($6g+l6;RbWBDomVz!ZEvR#)}kjv5Y66{yxmp5{TFQ&>XL;kXbc;vf~?)}ZOo7xhY zl0PPV=Q;Z9N`v-F25*Tbnc~17t_HvFo#^Ht@mx`$PZ%MIzoEN8b-Tx!Ey-$^-mB38 z2XV?`W{bOAPEMVLhh^ny^_WEq@VEcmlMmQ)-Kl9jLsgYtPh=$(w|65f+*|}IkGs^W zX7YlC=Ss!GW?1P$3~z}lDv@%xM{@ZrENIOTZUImwMvDP7)^QJmKd+@m(E4cu^h3+^4&{RAATtA zzB4QTg}YWX_o4K~b3GVElH3}!x;A2&i0agd*RtMUPy4pEMg5_EjEc5wOK^ zGuqaJGdXKB9Hd)~P6H@HfgR_-l(OOK!7H(9fCBgm$zc8)HluDbdTFEdZU>UQv3i8E zA%YUCfSf4q+A&#JUb+a~ft~R2Cp9Ha-uKi{Gre-K6A5*IQQFf?oW1+&CU;zxNN3d| zXIF-<-;fC45szhux@u$6*ASJcb}VbuzKWEqPp^+)lejWsu_F=JxDD2-99l4c?ap5j z_3V~%(3l+P4ZCxnzktfHgMWgCnZKE5L&>->5!L6*yeQkh-2e5Js3~IZOWsM1ueMKG z$BxpXpzp~_`e0PgCK-pc);HsiuO^%|e;9Fv0^Shul3mRq!x{8%rP6hC>M;uj`LDXW zfO0zy?f%gp^4?OmS1DPSj&?&XJf})R324sp0gd=G6_bSzPe0x6`j3+PzkJu-S%wi( zn0HL#!PB2W1zz!%@%nu50WgUO+WL8J5&&_G)S2WHiC+XxzXq^_e z_2OR?DPm~_zfFTZ;FbrtXKYPb90zfaxe}?y1vZ*pjh`wyQ9w__6Up26sAKOK4lkR5UVpx6s4Zsl0 zOgU~EF}~0L@N-*HOG~X^8PyRsUA9KaO;U)~OwbTr)2_(w@Mk}Y*-|Dzr12dM^gWT> znxQvVGkJ0r_aOsK+>0^Mn0K@XK^c%I?==>6IY6z#1B?repeR3N1?oNGH(bWmp!}}* zQ>6z;?7UU2mMz${#j;7rW@-+Su!Cv-*Il=0?&7vUC4+eOnyXX2!gES#~ zyhXA}>(ZP%bUY^#i5bL~{|ij+st*&v*wrP!`As(6?YnG{z70clu}G{ukTJP0v=25{ z=^j5{zH8KNH#p1{tr&TLN}*kXk6GFvW42`>Tz%rD{ppwNMpBqRh@N{RNOyyig|f=N zag40Ow1;wrwG)Dzc5VTgdEhs;;M=ro15Ij#zeteEh2L_b7S&u&Grl-9$S&Thw&5#w z`n=G0)$m5Gm~+7=uJ_jpj(UpHf8{v;9M=skux_C)ZeKbI6lXEua9k9Jhv1-!J&f*LOSQ911hzwK&Z*^7aG zkdZTg)Rw4U5TuPKzS>QHw^_S_!jre0`wE@HSG)836RlbX?1Y#&MZ8b1vgIG!{-z@1 zde4N%e!GJHShI*_m3UMpOo}SM?b(I8)mHvKc{}^ncTPI#VrKY7^t0EmU*fjhw@UBo zSUta{$#$LJSc8X-ZX3!#!;d}1FGd&g1E5O=EI1Kxf=IPPkSr;_?Vi`Xn_w98^zoD) zopCLrnCE$l;LPlO_(z8X9{IZ_F&c=H!qVakh(p(#75FV1zu$ z$&iLN>pqO+7N@+JOR*2aYu-MN^q)~sc6Ye%o~Yt)d)>aZ9*JY^_Cf7=HM{`|2O4lVL8+ zO>7x*%XK@KoNr#?KR$Mx{GZt{i$>_~mO^2$ni{@D{pGal>`T5zK`8AZdKhubMN@YE zh2!(hoi^CABD!~V#GXT*w{rWjo}>{yF01axy1|b7xaU}MDiHd+!jLq6Vg-_;&3rm( zVIuZ-fk!u3`MjxX0Qv!hqA{H%lg7$rDEBHec&s+OYgZD`V=dgM!<;`2v-r2`>L>n=Bxl8lN{xg`T-dzAG~cA zWFd#RxtWAXiRRo|gwI!c*qw;t@i^I+=Q2Zl`w^1ly$l^tC+afC&cXsGWqB7(6_NP7 z>~v$bv~S$hczyP#3qBJ$mbSdgB|MovbTiJGoiZgJ!gEFM=W7ky+n;M$0uP>Iuu4>y z{rwLAlG0yMNFn&N<)t&tXt_?1%!3*qNnS7Y0;*+;Rc&3U&inlL+eyMK`Gb+4p@Hx* z8t4(GwQqe<7n^V0?mtWpeC;`OKsIZwrhN4PS6z<&0p)& zv$}3CTxUq1IuX|{q55|;86%-Zy^*Te-@pXjJ6qU7v$P1g1-z23;dt%&V2+1#IysSi zxtqd(u%zq^n7G z!RWplr%3Um&+)5V{)QeKBI~_48JUw_iR##Z@^MVw;0A%LJ!2j1JlI5R)sPjVrP*bLH*B?czqo zYtF^dDQz0_J3gpyyJY` z^W_w_YIrz)L*j#<@g8H0zv@HiQDAC?)#uIn=d|h*M6er4!FNhqO7P*(Z;Y20A_Wl^ z&f}|Lbsysxzp3{V+3Q`q%GyC9-Z-{~)T153UEI)&?&5J7xx+iZYDGidSOJ}{K_FF; z6m76MV%CEw=lJk0B>#OASm6EvL1#QdB`Mz?9*0f|cQYGYL8np7duI>OF_U8d2a>bxO`n{zUIoH=*t$2HKuP0^{ zeCOZ7s1f3$zAx6k0fcZIv`Je*8y(E4?Ps2hG~J4sy9v1G6Tme+h5M8I;y!5#COt1I zxFVzQlJOo|7Je`2H+c~=xl)^C-_YRnQ8kD05_tEM*lF6@QBogoM~bhOgfFWua6CM} z0ljbQJJ_n8p08jp(|%jFCH$z(Q9sbwwH~}@ z9EzBif~=_cq2&15YN+*p=+{J=R?=42GpYAaY8GQ@&z#fgcDg6Qk0`*4`!>cl_#Yj& z?3z?!XFI82TA)2d)npLrWn%`mojTAdDY;# z1+@JYAB#1BM5fct*l`Pm}flNE+7w@Q+#VhSk>4J-`kOt4Dy zznjJRq5i>ls@oT<4dFW%UQDztovvgtrM$FM?N#PO=4of^_`O8j_I)P5Y!QQNSkycH zTJOibR9y3TpZ0E;*w_;M!C+Wej-C;CjuE?hQ7^vIyPZ|en{?r;-{HT>uh}ckWgcL) z*`J)nl^|wIm4k(&XWkiEXkS|9`~fb=%^uqcGRQaoPyKVH^P$}OvyW~Y+o$karSPB4 z$kkJG|8M^KPY>pBrJ6GC7czPFOY$Q&)1zB2xD7?0#Mnm|J?HKd?GU@!bx}7wo4s$m z%S=hwS?pG+F~bP}=uGo=n1#=W>Zk6%(7)($?gE}Gzw`FBqz4{GYmfq4a zF8^TX-=+3V?lhmt&ZwiP5;kMyUw^=rXSQ`>IF0)mD|U3S^fvbX_w)as{w^)YJqH}= z9=ZI2r12;AR$nT}>zal2b}iW3_}XH-CvSKU{s|NFkopu7YNCUheK@#kw;elPXXx|% zQr7sGLBfQ^hrmzCnc+jwEW$> zS}YL;ms^^e-LyAI;A(zTFewu`08X*wbX-k;`yUg;8t$LsCOSQpAiegumtzDj%SUA$ zG5Q*f71-~5I3Rf*+17-14mi>Eoc8!f_qdLfYsf0>xumPp6>P%xjjIQkBNgK{%l4(+zD$}`ZS)NPcHdwzlNk_y zBax?W&fmTw8i9C0XCVN2u6!N#a!-H94?-e?{4X{YdN*okT z-)H4Pv_e|=T)ZpDp3g^{bbKSLv!z^FLLJJ*PsHIysYDRlO0q%QylB;Fog#|D6jr>a zoc|$*q2x13A3KN#HiuQm+x-ikZv$#AC1RE$J7#5DpLkx`sjcwbebHVBn&vqrwD6OA z&VniWwY{*%+JU;Jo)hG&-7w~_HTAx9 zu$*WAZ^->4K>|822=Zqm2t+m{Yz!?$m!-pZkO%uAVu3)b@lOMv#_QI;>F;RNoiO)B z&ud|jJ;&K*!j<)-a3|V}ro<#I716s1v5y#dn5b;jD1?19+4m~C1H?UfVNZ5%^~JE0 z?d$6?rx+lY==U1<9muE)yOn=-#bu7s7T-aWfrWc^iPE>yooxFZBotFmfFODL+R|_v z)e!^tR}1AwatAHKLDf;63rH5?-!ES4J_9g~`=v_!4eB`|zTzB>XuT^EX$sY)=vUKe zPvxiLkZyus3+5FDP5o*Iv;G!mCZvF-avhiy^_B7aD&^PB#%M8vMG~PLrcPm?2IX|h zXJ93Z4Dt!TLQ2P%IbOgNSxwD$jL#=Nc&0gTFLzqylp_6v&a4kzYqoU|xR=(N+CYo+ zBqg%Bh%Uc;axgQMZ7H?U`)nDs%W`xk9GPkIZlOgiU&XIp#PnnC5-CwePn={uq}7tv zIJofFE2;R&zS~&-RbZxK_DD#HcVW5dBp; zHz+AaEN+M28>7$@?#t=kKHYpa_8?dJ-n%bJ@;vMUhoV7S8sYSe6gG9jp}d#}{*f#$ z3Nx8I9P>4t{IVV(vEsMkf~+C3=doM6i;x7% zpX%RTOZhTEuTQH7MPQe95A0XKTV=X|Ug)>Mpo{HifpL5KgAs%O!riK^euToSF)#mJ)w$Xfp|Y17qz=VPl0{Y z{wi)M<}c<#Ztfz`CjwR9!+fU0a7sX; zwtOXvRjh9DfX~Q@`{0wtB$?-(&8`@_up-9A^k>W=nXJ93HRqyi($n=<%iP)`$ip_z zT)a%1F@H^`@XcX`z(RGC*wR=Q#*f?et4_C3&_N#@alYy~VcNFfWcguE|A_sNB8*gH$4b_ZDvBn=)z?E!fH1nP8KkE3VEawY zO=CxmMr+C|GGs5U6Uxx^*x&QY2FNMt@eRVH$s9vlWL8--HPK)kKMiDG%>T5#zIUS& zwy63D!3@22uHg;Ww)rZGJ_OEBbzAL%kcBZ(VXksr`SY8}3#xigttZ)~EtEkTXG6fJ z+()%|5%C__bEkF8MN5cn*xs&dDSv^iU3c@a;|~;iW=6ZffCx3|41z8S+8eP8X>#H$ ztF&ZN9yh1n@zlnV$doVxG>KDd1FRs)vJ~cXa2M6 zrbj5gAm?^dcmLv`NS$H#w31r0&t2$3R7a{=Z8Gz11>UbOV-;jeM;hTyE$&oKqS{nC zS8g-X(;>5z_AoT;1g@!h+No?YY<8rIB@OJYMzsipy>1w#2>aENpbpWOcNU)(KIr+R zy;{&Ulubtc{2$#D2K4GZF?VXiBew&lR8{&D8~3_;Paq3sTXn)x5i`Q^+Xq&Ld%q%F-aCZGKb_@| zB!7IK11g12`vH8TF@!dcRf|z%3$i)+A6>62Jip&-3-J*Q843K&yY6G0Ez+1E!r}{U zvjRCN|5e4vW+c8g3^~v}o3Uc6|GK5k@(BNtHo?aQJb+@7?_N{`-LPd_TKA*Oj*V3i z@!IHCgr?zih>65CmjL*^!6V*#ha6StnxsknCf>3rKqjv?8N~7V65-d1cRVfSF6n3OphQJnizr-i4q&*^~TXe7lbK0qlyGv>ny}G&`3t-W5tfYn9%K?ZRDg**D}IlQchg zL&rra2D*snIxeA9UTJlJx(4k*k7~@V7H?H=4@fvY~id( zRXn;pdaue=(dfZzUgPXPi(JR3HpQEY?MoDcH2clI)J)OVUK=)#FBylr*#pvXMGG5G z#ehz9;~6*X%1<~h`_i|TExd&LKRU!+KTsk2DFMe4Ndd~}>N9CtH~P9Cz)GCtD<_EG zK(MYq;+>r7^Y-dHThTKSXjQK8#y%E1ObqPDGos|qAh;{?y$2q5+fDkUt{3-dh$zYl zHlN6rm7$zNL-&vCMi=hGieHb{2fn> zU9i2INkx+U;U2TSfq;q-QgJ%KhhK$;s9L$&A15x4RW|7m!i8HWg~rNDX93tTwZImZ z@!@{mLK=Yk9@2%w2%d3ZP?Pgs zyD^8F;K;-|Ik}hHQ|-*dPp%GshNS&L|1u+m!A9u@XL{xA%+Ze4wUbwxSi?Q zL$Qc%NG4!*5lypFALgFI9_>6c?W{bAdo_FVN*I4pv^zIX!XpvaB* zZ$3ALjf!}BfKqNK{duJv(SxZD;eHSrB!{7xk;54~cF%2O^QPN*95dbKdXG&L&CI#J z{ux^?w@Wx!hZ|E)Z?gHvPjeEn> z5#^d}d96d!yXvbW#t$BIf|r7>tpqP5GJ3b%NEKk!lRZ3k(_fB-4fJ&BjN16QoW_2& zRD7S$t1@(o%G(UltM{nA?Nsa-?lBjj1IS?^K(lSnBP|cc$30Tw|E+ZRMO|&s&h0>^ zh)c^KRHg8M)u$^n&Z=fD*Cpeuy90#Fs~bT{ToXL@9f5i_D6B; zoh?Gc5%w3xM7+#?JAAqiPDb{&IH9TmV>v`r8W03Z{YUqq`g!)`rkQcVB-cgG$N9?d zx9jE;U#h~6=D5noRah?&3heLI7wval-WBoHSZhl12`>p)6wG;&KXNMAWmdbc6O+$= zq$^9odZH(BL{bj32-BAdK%}twt7p_eVsb3ep(J)T=S@w^v z9Sl-IEN~mw42S6k)pX03C~!NQ@I?kGg0xQs2%1|acEvV2p$k`^$j11XuODY*(;+78 zQVjrZ8v7{P5%eL%>RQ8%xrae8<*##UWI+%P-69F+_u}BPyIY=82tEybZ=eg-Ix9Wt ztX>Hn>ag3C2u6L=G^GB53vGOs^$Ge#5b{7f$0}yfPED|z)_j$Oc>4~sdyB@So^o7R zN>xKvF1Qe-KKzf)5&a<~(w=s`tLC`AE}oGVWrK+UzXG$(v4uOE4j&dA9B8tvFJa(s z9wKhqfHuJ~DpDLqtkA1~YH2u+QKBLJH5`9c$0_Z{7`&5DZOs4K7)3eMTXhHN%w%mP zTV~ZQ^#1Q&C;D`cGf&@`MYC#~3?-8fLLn_^9*!0(Zvgm`5SQfiy& z6WV0_211T~Y=`-gGv60?Et8y2j$GQm?MAM5mu;cB9-z52xgdo6`#m9@ztDGn5q26t zU*t%MTS}<#%GQvbr0rz;kjlFWKOAfk#&Y}MxGD=3CBimL=W{@F*3#g0+U6&)_AzKY z(GmuJKUwpwZmVUuZ+pv9;Q~Bvl$JrRjmpm=-V<#W54LA2himR7lU!bu?dua=?UyEg;a@S;m7EBcfbrQ|PO=E0*d`14-Vqh-C$XDV|{ z^>ZFmk(J5Yn&NY4?SmTX4;r@wW#ATL!W5R)XOK84vrw@gW?_%aMN)J_fkzkPxdni5 zWYPS8ba%}v3Mr@^RZvP7LKJ2PnfcQhJp8}c>#7nqwgk}1fXV6ha2)8W4}wrs1#k(0 zB9h?tk8YGjAk-1i)(}k~wEy6}`TOX)LzGh5Tl5p{Cjdq#_7}a7r*<1f={Lo!vjL~o z5Z;y|&e5X3vQjI6_3T4FE#F(1dZieB76k?d=*pRt*ilvQyE4VLb))HJIII`F@JsFX z@t%t2Ix}#%4DB{-pFv+Cdq+QsF-5ku1jp+ zlL5;BLv+<~yFn&7o|XFhe<#cX%Ej+wSVEWnlLKQ$mo_5gQ8Zz#wISvn4<+y=zup{J)vu;=rdL zYr4eZJB4eCN4xDthl6W{z@*jx-NP5aO)Vq4AXXG40e0a3#(-`}uy0e-{`XiQfZ~nS z&g=v_9kMA+68R8ddW> zL3#{fWy%s=j{dXUpr^(~;*0m|(Dk|9U#$Jy+FRh$G&%mLW)?TOWS0T3W#Ht+AWqKB zbV7VXjsiU9++O>F3iy@^tJ>Fq_QJ|559*F)B0Fgfy85F|7}Kn;sDA&ZzHwB z0y?FnW%uPJfIzUqk50c^m9c~a_HOw^NIR0_!JylqT+5GZQ!F{J&;N}aBsr46(PF2X zZD@A%NaJ#FrZv$gP!}fZ6I#{Kd1RGe)Yt%z=3rYps~o40i0C*uG{eUEv!|mE{Tj=n zwx{FUhhm=bb=*EuhD;}+^WmRm|2e5`AnapgRf5?=<54w_ow7p>y5xP4#!%qrL2jA%_LtN z+Q%~)iuTyjWsayF_cU6Ft@Kkgc@JekL~e^<5sR61za>o+Woc>uQ;Q191FI&c;h+QAsRa>q;m1keDa4o>dAp@{(FVED9M*&JT*z zMM6fl2rU(v?n##yr%S}P6(!yyMjrs`&n(4*BHdYqO7Ab$HceYQO#|t2;VBx*ui+N1 zr(vh1N6jfEx^n#;AKARW_W)tM4Dg(_hG3juxEe-DzGkoe^PF20Ev1L7GY@^M!dirI zT{~ryg!)#PIeo%xR(dNVn05k%pY)(`VHSJBS1{FHRTZa(QKBl?xmwvgF+bhhBuiN7 zEXGvqT5)x6)#IjeKD%Grf=fKOC65c|Vj<1hl42)h0-JLwZ)mz_YVimm<2NECA{M@D zy_lyEaA{Sx>E%Jc;@#5`i{_Z}J;ZkD!lL71serjjM@UrKm;Q~t8dln)K3mp>W;+TP z5KSA!eIf-KOkd4sTz-kj1FS35!|tXL@R5Yt-!6+|4}@eUzv;2>OLjwE?_mqr4;bHp z9U(lMaQ;}l$uLV|zF_1whi`Z8YpgPzu(xV4^*XUVu?|6fo*y|N<(03Z;&{1B_ufKa zUvG9rlcnwUk*VrmRhLk1t*!8WK~p$Cj;Zg)%(!j)fhK=%4>w93sH382kKhB7we6}; z7Y&B_GxUi~@eRuFxYNgP9t&dfAJ4Fkwd___#&!*GyX17}ca?t^{#if=f1B$vrs3!^ zIuyZR^(nmggf#+qWhCbxwD}Xovft4j`3z}^XW@<=Qn66kq2(czsB}{RSoA(>aQ7yy ze~y)6;)Unn1I6MN>ZQ$}4?0g5W#!V?BVcEI6y<1LtZTuvgnud-AW0{@ft|6k9!4#= zefd&6RC@Wyx*XxVYIc$v@)4wscST-eE~jHo9yH6Ns8X}TV0+gIN%$Ax%6f44Tmd~> zXt?q9R0>0Q=K?g6#!U1~^+R4Yx9S7UWIv}&Aa-kesIcE>OMG^zl6`fg{?9k=tJkj@bSgOI5v2!JrjU zz2WlfCDq(kQ42p(1VNGX(Bi>@Btb8>X#Ms~fA&)ZPWcKApZY4aD;K`X2&^)^N@)!Q z>hpkFM`7ZRii-jBBQ%4}L`ul#*iZ6Fmo`%w_fd-pHmuxVDbv&+vS~wb8FB?9=Uk8n z2jCL>9DFERex|UQX35%xxT;zPnan>EECRi4{byE{?U!C>##Z}blK{7x@&#zDx5=VtNXs4a?O_5q(x3M{byBfx z_`D-e*Zi`1_$Bsz6XcfWqKMp(r+2}6xvL!ww)FX1?3rfV>Ud@-o;3Hi$^Vms3K%NU z?=2d)XlP`OKmNJMzB73o2+=4T)2w`p(#}%gQs%2a<5)va%w6`7u<@FV{_!BzdsJVP zbwn<7*g3K)do&GLxGzrxf!ZzMF~7uwvf`c!&cydmmmdoz!K=%LmOvT8=sd*zy#R08 z@73|YxXT5jnVFtw@onyt{oG)GH_;THv$$!qTD7`dS0v94V~wc#@ssXjLb97Q9wSSV z9xjOOtWaWHSJ$MCF>t2yVys+?$=-lafeZ7&(?#u|nV#bvK$@1P(uqUFn zK{?SLIZ(--Rf!MJa?SD^B?ds=TgwMy`l_2GzCB48>y5P=l7BsUw{)_-{^TsKJ*D{{ zJtTfTk%2PPx_150oM5lqKVvsPP|s6xooNiQXGnx~wpy0hKANZEG#JQ9%Mzxzw7Cbk z`=HUOKJRCXM ze8(ISw1{V0(H~#<;BiE*F-l*Qe&PS1@0?LmwL%d3U?;o(^{{K^=ZtsBA5Po}Q05Id z>zIdZsqKJ{*cvx0PbBCmt5@iClf!1qGxg?#1HGo~t{s^#>9gwGsKHpO5IKg3Y)9Ta zT&}_cb)?cDd}Bi*)dh0)Ksl5r(d{I$3tBGmUiKs}xjm$`rqC0adIdY(pZH=wA4m-l zdq?qHnEpq{^!sGf+^yeITl;W%7B?z*rZ+aZ>pPVfpKo9pA`<}=%x)4NEUm9x+Ph-& zGmf>ol?MR8!rgl)x<-49+q`=m9jUvXz67iH{C3d^{ie)k9{Suz`E#^>@QtdIIQIqE zw|{h#wSJ!wlA~&AXA%^xQ9-ePbeA?QB1X$r6QqFh*KDH8mP zNpjqECG#L6X?I~X#yy4>RNjW!_34g^#Mm4dVEYAWLP~KW>e4(CrWoWxPMhMu(I^VAPhW8PEL}#Bm95K$)hE57| zBMk5mtOIT-3FV7wYy01*NZIaVo7A(e@i>F!gk(RH&wG?)oyEB8{f}-V&(ve_@K>2$ zaQ?0JPq34U&H9ydPMfv&GO%DF70F!)v-gMtu3<-Pyu|D~W&xUwtir$JZUb}5eJ}q~ zJz@@R^M3PR=5LVZ4D{!Xa+85zRK`C#fPh}pJl`mBW2!SFi%&P1o#!jh8^msED@7N6 zG@pN6{SIN$ShRO!Piz9bC!YzTUHF37Uc~(wSuR3V4xYr!qvO*4Aa2Tv+nPfvf`f2nN8(RSYAUMY^U|GF?nWfR zEd7>E-7@b^XH@8zPE81^dIURfYwX>mU4up|$Pe~Z8jZ;~UmSkRmN*NZZwfaz`{O?s z1|#Qr?>TqjZx^z%WL?{T?LL0M^Y{q7Ewx1To-7BH{`YnX!f}WF7YDE54GCIw-LX=A z^{33V6xvU~osO+ZWx>oy+KpW>%MyF?x&?IRBL>~|wenr_IvnFmSq3a8@gxPJCW-OQ z!|L^%slXE5uj2_}@Ao+lUSal82vsFYQFdZ(>kn7?5ck+irQ&zY@5Tj~aDsYEB|Us3 z)lz6)-cAUk4+nouJq-cduw>VOSe)20+vkOmw5p6WZ}n{&4_r2*ay-^!cs7kOnXZgM}@6GKSF=6r0nSs-pz{9<}&nZ zTKtn}opvlZNxB>HpKHD73*@Lb=L0#Grnx#eNc` z8u~*X6S${Lh-18_)12nv!=Su%7D(3tXN%`LW^=#ugmJUq)sc6I<3Pw{d}490Fjdo> z%)>$k?3LFLmZ_Z2b~6bbvYk6K2Xa znb%U6XTnq`MgMu^hLp|q2KfG+iBc{{C-42luZ3qNk@=;3_L52(7Y-HIH9lu65nw)j z!WvyH2$mx_VP!)D>{4r8tDHV(N9hcaT*>s9qN*LFLsCt(*h`<`oi7mKj)vz>4=hs$ ze*DHZAsawS>}f7hoHf+$kc8?Gj>+k_t&NiFiQ1>u)pbwgeaFn?-JNgYJWVGbi+bA# zM;|H6o7;b?%`C<6+$Pu?v-Y|3`r<)R{q4e##Lk&35t zE-q~zo;xVnYzyn1XX-m*``Vw7Dy7^S%7_<7$)*BQDLh7DT{GPj-4{FzXMY9-FO2DB z`Yor#1df*#m*+7sNrBm)pQIx{BVRDZL~G5|xN{wfN%Zwtvosg# zcwm7*xT@%dBDJsctDD->g%)eJ3xD_{j!?ZwvWRdy&}nl4^B_BKzi~a}b-OeSshder zzfDJ6EN5IfzKXP@nz}M2c!@1YkVT8QRIbm9G+uqS;C=J~(T4UVLS?d{UFL4GIJbsO z-m$*442W_kTo{=cBhOnqNLj9}PTz+-yyTFzmsMV9pJ>hWyMgZ~h91%&JPAmZnNF=} zm)nK_giFUtF!w^TR+Ft}1#%r)EUsDwt5Gyw{PZ*eI>N^vgnoE&;Figekcr~6u-W0X zfYH*Phf~x0zrTfcs%L3WlE6%U$Y?c5yp53_v8+18d_GwI#&7U@YqR_yFiDWyvnaxt zGJkSd;3K1k617C(nFB$8Zd2d5Kh>R+xIzWWn<$eMAPj90+YA@}8ZL0)_8E3ABA;t7P-m0yw2ly6-Qc8tMGBqY% z*M)U&86zxDVa>*w{c7{Q7j&=CCKj8&unM^IL7hw+m+NVo%=__b4D%elUS`W_!-yA* zjPrRO1W_zJoqrO3tBDz--X27spiumaO;I^T3i+-;_53H!cN`4Od!1Pd0Yuh@PM?*ZLME76OJA^ixLV&;uBMfAU?X-y zhDbW7mT6WH|Dx}1e0y_Ewg5j}7Oj~cbfM0=m3ARW*@#2E!$V~vvn#!-pIziYHYBfp z#2a*zc%sr_{8plWnQheJQnw87Sz(KN$N15c8HfCEya|GLW2|rz5N?-m-Q*`?nQGf? zQd_T7oCl0>mums?s^ft>upO#iXcAQx8uqO2gG{AQmztt zE-unw*?!l3q%9tit>Jcsadri(a_Qto8~p>rNqhGpwi}ED*z5I(ZBHd<>!Vkia1n{o zL`4zt9f!5Q@Z&s*{_McmId9-&nBJbsLDt;ABq&<>F-qL7WGO2lr}Fqlr>Yw2ISHvk zSAt4b(&x?<;vR3E>>i;03Br#>EL+D8GND)z;#|zoe^&tJN|zPXQowZZtvMxt4;D&U zISG7Ct(YdNi_#o;RNJ&s%-X#BGDESUPcj=$ADNko%0fg3t_yadu4;VYp2|%4U3E-b zJGn}!tjvx+xM5OfBa93g=7(xw>il4iiu;g090pM7l8vZo=4{BHU+}N9f zOb;38C%FDXa4(By{E`{6T`-m4BDmFW%PzP!5^|wSY6$9_=TGR$kNNf$3VPXC9z7@l z%X}Y`wcdxBz|7@aOW9CBaP+A{FpU$Qz4`>j z$j2Jh8N)5!F7G_d14^`onM(6g#bN8T)P}3pW=(I=H`Jw42%E&Zl;?jB5)ERRo|sHC zf!x;Vqp+{SOL@33UxJzEM8iM7p$rD(6QD9nrfsHp={l_Ee> zcBySEh7)B}Zj-U)y=gr&#QmmBsDx2im@iqOc}Ge_bEiZjLZMe#rhu|>h|&kF5G8_p z>dsFw1XJmck2W5M)j_T5K)4?MJzQJ`i{iY>WV_1hzERv7WVb&uP(K1v@&?%F0~sbJ z_%_qW?6kz$cd*=6<1mSxeutxS(N_Bdah?Jxgu+dKkZQ?# zEC~GAM+MQl&FgG?a!MN|0T4Hzqks99rt`fvU{7Gsposqgc+$oin*cC}3ST&S{)C~_ z`DxO%KoQn`DbUna>+k}c+o`G0itgywHgg@#0$_s0&6nWeH z9gTqfCY89n->tRd%rMNKU5L4i;-NV?bh3m&%Zc$%w>ezH9g)lufLU%Q{1RQF^5=x} z7r)F4tF=ef#NGgHZl~B?e$QqToY|7)S!;eWl|0T45EG1V6Hb)F31L3#)N@|2ov>|;1Qo> znwn+}XvUQ9$5Df&UQw%t>wLV$9}tSvmOryYd{sjZ*dA=o#Iwia@q~JE ztS6E8UOg%(HERQ(Uz$c1+t*h10^KB{8F z2eJ<~?I72?(Ob_yFZU?K%PXxu7Ce>;CRO2!2|lN$+#~Qh{@rf&A4d2xL!6vL83!L_ zxbRYu0>G6#UN9%>B00F9C1fUtMW0moGOdd(yn`R|WGL>`x3i_GOxdGt(mD&|9ZwRY z<7=a5nI8ssjW|?cOD#3q=h~(BkXg=eHVG>010=se+)-0=m51@h-@{_e($vp5PbnTH zV37u3Wf%w>lE zpisPl>~9f_mwaV9cJkWP?yTkbC$I8{fBtp?6)e@egBJ=_`cmHXu|q8J#m9o+mI^Xt z9kXBnZ76^Bo=PjDqYVFf%TiF+u&)4f$%u~H%~&Xs?{Z;3@B*PS_|yUqnNkj!%d6p&En?QI5!9!ci$(CE)Qs~aZbSZd7DNw^c~6ed zL`7ZYB2O9my#JDZE3I9C#enmBK#jv~m1J>MqYnA-1hQS;=>exexk2$X?Q`GAK=37E z)39?xrgA|J={MQVIUaMk(9r=8_|nj^R}w)IRH1A=GBk5q;8dY!Fx(|!adUakxwYI&SZqy4*0?FW z5mcEI%tj0xNU2Z}FnII~!9Lj_BJ#*UnX<(KkJBIxm60uteWE6UO-1g3?gIdo} zoFUZcn`vX5#Pg6k$|6&b-~+q!;dVXFnj3yr;X{tY^@iG1e3vekFde`N6{on{>vH=5 zax#3hyG5ZjNjZ$760Bk&${u;rj__kW{ld7~f+*Kd9nD-^oXn1I9oJ4=^r%bUxpTjC z{x+)`95S;Q;HPGs4LU)#<9E=WvbBKpZ$Uj75a0(L#tOShT&BH;BtO_)!ET}-7y*k| zAbYL8{10O@Jm;}MrWynSUIpW<^?pDv2>;$j2NL-JLwyP8g%Ajw<}U^RhhhA` z-$~{{@$C!1MH~SD`cFZ(-+`qT>nq62;0Jfm5Nr2174?h`% z43eV$!@vSi_;mno{rA_o=;5{kz}3G1+w^$%^3hh0ej_7ItQYtJz3upo!;#LQ!#m^C z?0`NHz7NE7kyhhs4$_l{X21&tZ4W^np3px00sWr~eR#-im(;mZxG~NkAY6srp_3nM z_V4K*xEz~4BG-I5Z-5K`6||7H&7 zJ$mmaVVpQa8Fp~*FzjD#Tts66axQ0$I??GEdG;XQ05oBwc%p^sg}Z%m2A-HHaX916 zDj$i>Ga}H2r#jJGi{2@t6+g0fCkozD_Aib%x79h&H?g)Z?0I{Yezoi4t0O;mxNR&X zjnvuF^8$9+qW`Ir8s-VJuY71H@;r*-4w8-j1QGGFIA|!s$P_>)@M3`LqlY6Mnh3CU zgRY9oI`3lT@IQQsgi50KraG+5W81D1EsTPrYV$Sc7yH$ro~)(&BcK9>s{}xHQ9d;B zi(lS{9}U|!4^o=uGwOO@S}q;Az=sOR?+_MACWC+jOm+6oKOhclT;pZZg%8bK0mWXs zUj(N9uII<&yI>ab`E8Vo2I~s4?!s+yNe$<&cV*2iP-4E54fBgJUfEn5YbrDR0>G-| z23r+49yuP`e`!yvlyId!*Ml>`2WwGv#=Oq$7s*-PuwSYMK)Us0IuCK-U1cXOUsz}A zxu@}X?%jc^0674elJD5`Hw*)GE>gh*@50t+Tot*e$I{C_W+!khW9OyueCF9YoI=}1 zsUg$$8#c9r}xI!|GV=;CNKHRGah=i4)bLeoIdiR^}fi zjaijK2W=phqC8svmJG1v00}OdkzS*T!Sc#_vLQ0`NgwsO9)bP9c}>!|FRN)u-y6BV zQkSb+8SuW>2nHQIq?%mi)iybah5d-C&Cm;~j5MQue^uAq@`-xt$8Hf}%BoZC{t}Be zM=x?>Hl_ODzZWG}_F3+eZl>bd)pD>;!4GyDD+}{u+MLf8ISxphqPNHn$jZS0%9{_p!h-6X7z9%Hq)7)%aH4N*c&1HORXiKUd?Dd9gByXp;|r zzE6+U1t16lRCV@7f+zb{A77-C3y^OAhw;8F;QAu6XehjYdv5AM3v?zfHX((xfA=<` z-yhf)cAV)UTI)9WHq3>aX7=>~99;l;<;$tjp}|^y?0=1|@R^)BcFo!Ht zA;|6Rx{e5etv^FB_Z=zb$4!RS<-}iE$1%Iad0nj5)He)qDR( zT|aT2ab8v%B&qmq$(yCCUQ#F78O`u8#3S`lWq9_eQK&dkqMlhLN2|yNvkz-0?}0hX z^1yXuR5Og<;6zs9g4y6ZM#Eu5=SXQJ-%gm*La*87f&uNn=->d-o3agwX44^0+{37& z~0oD;La!llz)`!Wiz9J#0#c9yYy~XP*sG%$&I>^3Q$W!yHMz6hpvY zkCoZ3%)&`;%wm=%n*y*pwb;!Rs%H2GhD5I3i)St>;aAqbPYiqhfS7MvhL3D2pT9~V zgvq<@^=Blk9?~DBjTJ^r*$0^Ush(i3bb%;sMMy?Jn)pwjoBc8o%Zu)+XyCV7!}+%` z5-P!0JMC~SXAg1rb|kvnk=yW>Q9EKiSeaK?Mfho+6gN)9Ksu!gOXTeSJ~Q7NjX$3B zp@mocU<^{w%@4DlXErm9riAjuc0BdqN5hM^`p)+ZZ>t!&qNhD)Xxv>zIYo1VLq?|SnFIp z>fZ|fW$}fBwsd-z;P{V@U;klzjXB-otiKLN8T&8@gngo5a9mz0dmrogCYvKJ4(%GmGl3=_KVnI zFo%p=^72V5ex<>t*JY25SO+wvUH(R_h#MZiMa)YLI-%Cf$6BzT(vuh+2u|zaOFX8i_=S)dA*);ZwWv!$qxw+YXve z1C-KtwIx1oW7ji1@-^P-RY06wkJS>FvcM`%$=Q8*&K9(s{15AglWUVurab~O4i)}) znvOxqv`qhDP^1%X`0`FurQvC@E;^1>@*~Y>_UN(PmE$1 zS0I$$>ISUOJ47&*Az_%SKR|IPp?hm^m&Llr<*Ehm=LtAlFuc5Ym>b|*`{)oX*H9fH zN3k_kuHfIJ!=icT8?oQQSvx zZWNzq!@cWKLUA70!N`ACkGIJWejTcZ5c_Q?>~wCYf43K%Hh2my%rIRM9A25p@!@Bs z2;%y*O?<~xF|S@#c^W81tbvgm!Sp{In*q#zQWHQr#L_!;ER7p5E0o-7QN=L&5<{XR zW*&#Fn4g=G)eBZuqIcKS2}KV=YI+}Y*)M+)hPj!UtD$H-Qz!)K@iXwb7A`8>N}X>a zyb!i!jBfv7C=uAHWxi-~CrMG0A{jL$R+GZ`zxg21yILH1g_M}GjOeLlnkn2JvD7qQ zKZ+vVB9)WP}*~ z^=&pbh((w~PyiE8dT4Q*Hq@J>Qn@;yf5v#m)w*XP%IelR8+yh4BQh%b<;{dkdvQBg)hhIM!DX6*T}DrA@ui2t6=Z=64?))VQ3UCA~*6B z`OsMNHSVE-?b8)K?oBWnH~Ci^*$vO9BD|7b-b;XP73!Y~erHx|K&0N&CIQfHQ}kZ6 zz1XQfTK+zb0&2ZhV%VB7!b|t(1`1kbC|=NZ(-%EGcA6>95Fjak+7n-Y#R3TY-Wq$Bb?pT##r-S6KW zt^vjNR@-5|vE8r@roNV)yx7_N&a8N_Ki&^pXAq~AT^12~5>x-X$e{l9#7^yA|=tEkK6!f;HngGqVCiN?|(cq+q02y zSOLVy2zg<)V#^I=x%;I*9L@UxZbs&9A7CqdJ3(0}R~)Zoy+A?P@E?Xxya(^F(tEM3 z_$c3Ls*xNI>PuUm)Q+bU;0&-r&7~Nw-$*Xz3iDxv0Q^p!C2%srV+yNW%5cT}9qw<1 z1`j?5m1EPy&u$oL#03+drBew-Da3{!;rBXqQdC;53MB;3Z-%is`SNke!{tNnDwVDdP zTl%aHH(ndMoFNwY#TG31aV^a-|9VKTXyzdZ^&|^h_N9O@@n-a7;3Z!nD8;X{9?JG5 z29a$Qcv*CKNp&~QInW~*Kzu?jvs9M%h5;iA)S2036~%O0*-PBRL*%otwwT!w1qzF9 zg(anLNeCN{$B0&5zyYJ|%2U__@rr^?8}$uHbs^9JA%_XN9RDDL{#}s;G}^Gcm`cE1 zqgdg)(YK|J%g5#aFdpODfS-C$xDCwyF>|}YVsYB1ptPfvM;DkLN6&PwR5_N;3m%fM z3U}EP6_?^e=3;f915Pm|kC-Q$|6$nOfKtBC%tkS=&Lj>6@JMh{-?t3EJ{~~J9AHLo zF?wz)S{QN3ffD5h^TYy`Ze;@O9xgq0{5$QV9YtT=OoR_W3A1V$sT=d>k-1Y0s47}6 z{0yq^kIZ9mx-9WW8;`yp*bMZ?$h{?fZ%rgGvY%iq&Z3r|VO|x+luVj?u2=d!>Uw_h z%y>1TBCqWI*VGrRvIJeleqjFMi#jQ?ysIR@V};;h?xu;=Q_*0O?W^zzjDNvWJf|J2 zmYZ`oDUKvRlH;djMv-u)p#Q_T9^z42XfudKA6g!6soRGJUUpNa2R3DCrH{wJjpaLL z$JhOqL&naxkAjsu>+mF2y7(fm+q8SH4AiopO*^frGNZpO^5mu={9P}L;AHf%(Piq% zv25B=0-#49v6>yCO(pzRX{P(xdEVm)&ok1T%_x!e<+o9fr}ACSJ6|>dP$JRB zek(R8pX2sILjz*6?Cl%b%o62IoG21)aYHZ};%VtgaNVBx{-)N^FMDY<*cF!s(u$Sm=}urW=)Q zSQDa$c0YIRwE9lx>9a98Kl9&ffqI}aa6gjJ{)$1k+H30j4|)q-9LvWf3eo#&?fVwf zMJ6e@CyRyALpA@@wxm7|PoS^B@_f6k1r>wp@Q+PQWWNP_A>7J#x^$}D&fIab-Eyof zy&XF3wsDlY9Q2xBJ!6|#CL)FU4JviMZ(4Y$&JRRMv}oum5I#Hho4Owo*qcfo46^?1 zwisdwb0{47n5W3@n873*`<59t5K$0<*jVd5YDqPk7DMRpz7PGQ00i;iLU?agMc+)BHoPLVM5F3#YN{zqoN8LFN{f>a2=q>`GN7#+}eZE(D; zJXUA3Z=473Y3h7=7XNIHV(SwzKI{8!ko=Iot^hBKa7Y}MS($!k{|ke}pBhapW$j6M z&fkfI=+BkE=~M+I=4=}dy#DugQ0l(8mxy@k{9_8H{T~$60W@7Pm!DX7K{qeao~mR< zj%6t)rWvPyYlWXLSjh74bW!F5jEx!nI^voCxkhKbL+ZMH6Ks7enNuO)X;Y@76+7Ir zR~lf`RrryO zC!Yt>0=RwpgBgQVdg0wlfs?L+=P8BV)*wooxoz;Prplo)E2L#NVo2 z`m{z$RH~Fhzav`Q;S?{qBzu6_m;6rQr~`J>VU%Tpv;NV>-2|oNYZ0AfJpLVRpyps3uUM?s=7?n$c&snCRv5LZ@YP5H zUBqg_dwm5Y6_S6dd*`#ewb(ApZlS!c$;4>CmP&gaJLa#&xChzv*EjI2LmH0QOH*%)%0pM@ZKdUOOqCABM*A{QwAjEbn%i&Au?YN|7uJW>S zd3A18ttBR|YoE&9t*&4FWSY;Z?S-*p?HS~O7A)dRiZH(Xhg^usg2A0*-A{~ zyse%Xu=`xj!@}9V;g@b)MuA;iJ?hrL1*XoIi_XO~PNbn6H#RyYO)Qi_SDhWPy5BX2 zqHFJo062V5?)3*MvcGCOpDJe1G2>Ui*>b3X3h_UTi+N-C?za1y+ypf1`Vn8~aLpu` zPTF5!`)-oAv$B4G0RTxNcH7rzX_<#-sL!X9P+gUaOc){HhcB%VsursGaS<3>rQ5_* z#vEhs)50U~4)_7bw6Iv-6CQ5#`wYObo+FU*1G9Zqlt)y}uk6ydl)1PX4RmR9CaesA zz82A2dAULpV|~OAbsk>beyl8DY}6oPTNTSdE^1YYu*<#`KC|M63uCH~@blcod8$Zi z^hmPurk-g5Q&8$ixhw56NvgD6$e(o&a*MwGU=>3G?w~ILe0fRz#wX8CV}!P%loq24 zzIy+Tpym#H}A*4AWMRM$u~IDIjw>}=%AkKBZYwobd8 zchcFv3clFT&{N?B>;u9bS*!1{3|Q&!EpTok2)a%YB{@Y&V-l3G1k^LcH;KyGVWD3A zWnMN1hXUgjGSzJ?LKjvZ(RY7(Jl7 z)%I(nNVK&2Ht4s?%JJ!8pC#47M@`w;Zi>%|%7R(YQq8#fb1oBdftcvBJUH4hkv5r< zOZvxaWr#-xkdEdm$BdT2bg}#OLgaT^&8-{?!*W`THwiH|NF3&#tC`B+f1i1(AiSwf zl@qx@kJ;Qe_ZFXb$2LQtxL+Sf2>GmDCCp;e^>E^{#G{QSiWD1dVN_CAc^4_Cuv*zZ zo%8%bM|jG5t!K9Jz{T}pmqzrLna49LsQbG(R@-w)UCW^s2MPcLuzl`!zyEEeFE-cy zpth8$J@V)0YMc=Cyy#b=Kf?ks$0$# z98k{N$_4si21?c&>R~rp`SF<78gJ|!yK!jGH3IkpX+SIn>b-v=vLtsOZM*+@#$*r^RhASVy7fx*>k8AK?xx*(0>(WVDnCD@ccb6da3U%M zuU-}pbpqh27S;_Cys|&DpYAm+)a#X|gv1ixd*MVoEc<$#ZysEm!2K}fAB_iQ5DnoK z@h&$Mm9s{b6}@e-*Z|~!ENj2y{D#XH@rlsJqu-v8wxS4pR%9ml22v{+oJ0KzpGbIH z3f+DJ^gJ@Hn{3A2eDN3)3+=4wLVA}B5P=PkVEr@cEIY=zoRBO988Ym)d@au~{#eE4 zI38gZ9+mMn1*gIhZhDM7^2G;Sz2!cFp^qN@ z_$}MT1@mQ7sZuKR4sS@_>(egTPY9!|k<-7Ehg<`1s!!89Vc2}%+-cv~D&fpim9^Gz z-^MG;sFv&q^@-v3-hl39yf{(O^Cl;k`-OS7ZRT}?qdyB@WH_nyT8ub*9UFgubjTdI zTin3b78XKcc3<0=vg!(-J#^5ezI{9(1}W;m(Emh?DvATf0;u8@UO#uxwyDT`f&1<( zRo2P0TUs2vYdo8372HTF*yRmYQdCT0oKr@48V$LuEZWXA*Ry)I^G;OXvZQuh4& zH##O~wE~8XEmnAG;N2`J;lDJA z@3oc1MaDVC(%w|+V26u8vk_KAr^45uJkVF_JhWP6lNw)L?M#_Ad&x-zPKx5%BL%IO zdQrq#dNhG;wYCPWic6_XvHCa3=SAS&UVdVaot7At>7s8l*}Zo|YW1S#rE9AW z(^HLZ&8?&*K&rOFejS%7_s9Qu+;XCEwbnawAD&l@#W^HXOqbwWik*!~Q%FBx0WH4B z-FUkwFf%Av{(zpj$y`;z%d@aQq`8v1;OVOgh^06?mv2M95au2It8tZ*LN^OMH52{D zkaA7C1VPOD@o@bw4=9WY5L10qziF&JlY}0Wpq3!JdAla66WyO?XIv}Wekk94e#=#% zUXVC`CB&lUJAXX2_a6o+o4<-p1pMRjiU%-$)igNuf#pJSvWiAk6pg$1W@Sz>3(G?(WfoYMonfm( zEFkgYRHfY5f$DGfLtys{p*6^M1%(6T@3ph!Xvh-+!EJW~6RXUy+)01=q227Z;h5>I1y2 z14a>eZ*H_F?auc56@Gn0eT{wjZTrs%|1bLf#>e@}5skE3cRqE&zP`&L^{kzy4e1i} z*q(Jo1oWz^-a)ya%Z8*drd=)cqT8 zeQaYN8aWtRf40A|q}vCm8B75W-g6RyBVgp4Dy=?t$8pB+avs`)L~-&H;{$ImHi!)b zQ`U>XXAH6e7J(d0-TjBraK;Vud9Zj)cWmnhr1CG8)29ABEE4S-SNkzntVqPU-Fk&% z>9kV%PbA-FDFbt0SN`q0_c|=tbOzYseMPK}DB?mcpDerEx5iZ?`4jM0sk8W;#ObXn zn;PCG`VnS7gy{WQ=waHTJWmM@x{PBW%$b@o(4N6MHMSM&^L zsY5a18X5T*x3DNZylKlgho+-j{H1V2z48W49fmlTC({FJ>~}}@WqL7xptAqBKxKvU zJnw|W1wX6AUqKcT{4|fpACYh707%R3D|5nk&xoH!{r93@8X)r*j6H zF-5MsnckUyPvbqprh-7uNW_+Yh+O?GJj9AmdrqsTXw?R|gf)@15UpWcW!H~V2w1@% zZ78^BwS1ReS_^{h)g2r!8CLw%YJAXIgq$VRy;t?}9;0tFG+HX5!D#}q$7*(Nc#&iW zH3iWo^5j3rX!Rt_7I8f$OmK!qv#gJ#U8P@a)IQ-7A0m+Wi=AA{aM|N=uB>G&DX;0z zyl*$l_sZPyui12hs8xJ~Ne_4Phh&$lr_;aM*8iNyIkk>V$5uCs!m)f9Y2`iBkUz5D z9BUn2nvw@EntK#Em`WUqDK7XBO(zdC2CvL#Xo^N0MB90yh+7UfHYT9IC%2d5hm4Qn zwT?J);2)|GP^9bxR(Wg8wi&rB32|^sEhsT=NY-RFrrt>Rdi)Cpj##)BjnhOd~+puIg&M zgEKZ>D~1d^7pr$a6gY#c07@keRy|g+Zu=AP&0F4Uy8&sl(7$34KDnG!mQ@de2!_VB zLk=`sAIVg{Mu|_!yYCRa34ku*yB&eX%G_1fymePz0beCIwIX>cjKVTX8mv5tSJ*4Z zV{-Ov{Y#Tta&M!odxU+=nABoNrsHEe(`&2u#972kAePcb0W6%%X^P)nCt8i^(>`y#+W?AAX?f_>+{Nkh+pXw#=EWNkfhJ^Z z#IeVkYfQ~t8ozbE%4WymA&4{-Y8*f<2HRvtm$u7O7V-E4FOeD=0!jLgb9sIlRuH{$ zzOCtyrdZ{n)a|g_Di?9E?1D5VIp|nBdNxbEw*%AoDhW~NBE5+t{v%f{!IR3epi-?* zoQNj1_!?Y80B7cwEYeqId zj;S%N0LhRGnzoeqG?+0M*{&B`_R)QrEBj&qQ=Ln~*eD>8qF7^8u%XmIZ!FE#gY}lj zkp%~2Fd1nkm_*jO>M80~)LZ2FABJ8AVvyL;o>MZ5g;;xmTvwI3&ggj9xffPyN?2{8{s6%YPqp zX&q1Ya5F68ugCWrB4LBmA!+)z%^q1QPd(t~Cy)JEbe32@`i1yeLN*b<+UtUrrI_qd zsXEssZ-s8#dn(GKo$!^%myj9ePyHrGcj^gni$A|zlH4AhELpqFF-wl7O};2EUdzzh z#7c6X@Yt>l8Y}hp9{Hl~O&8~pjYS8(U+%1J|Ffx$am$; zJ>%RbzUwWpDQX$LZTmtZ{(M(`$n@%JbDryW7F60!dO-j0e2YYY$4hm;z7{ZhX*Pq;!|HmEErid*8yr6giBxbZU~e(`go9I2 zU*IM~B-DQhF$O18s%};Zw>`GX83d1y3u;m-za|R z^3X-<&u+38Hp#qKUd>B<2UZuTgqJ+URE_`Pfx8E(`sxLFKZ8ZiWXmvta?Ft&DX?Or zVTnq%J9#?|ms{%QO^?@{qW?9P`D4eUoGd`IZsskbSuu`;PAty#*ie05rh%8?9O~Y! zSa($tG<`$ORR-ulls9=%O!$qLIO(H*#hg0J_v5^Gw_@nvzzW+FjV|MNYlP}2GiTvm zl=moDlLg`{Wo!foD^Rg~3;P$4Uk*t$zOuhPm=CaXYMq5u@YTrBJ|;U?mU!Dru0k^+ zTy`eb^sy5zx6_VbDpH@d*O`f~HOjQ2Kq+CjfY1`lMpfQN^2>9TQ@xkfFBCLg;&*uE zvYa)+@zXzRh(unN4@MC!BS~hSqha!5e;QVC!xOsq=0HYpJG$ujuJNALp1}>;mKL*J zz1W4JvlqF#pPj!2CeiB6I*K=56r=YkdW3}3Jb(K{e1lIKoqiT|vnxBa&RZ#yVu-aL z=Y1}4wU3-3sj56um3w5F^k5m~jm^->Q(=Qg7*x)b_jasP@i!tX!h6=Ae^l{vVVSp% zm4;V)_#SmTC_c5vT-Er;V!qHSOFi9SlGH8NE$+de#FD31jf?6!8U7nsJ>wu`9q5th zPzHUCb5_))7kyM9f-1={5Z!xoZ`+X0taGfUr1kcF?*NR zy^TE=obNTQE*3<7H78;G-{fYdZ0C}`$Ne}Yp!?C(Z3^W|sGvb_A?P5~qxFg3(Cyo` zMVsZ09L84DFMBq6Z7+@>32@yPh@ukA#dOU(m{!>RYDY0cPd zpZ+VFOw}~v%kqe{!XJ&p@IPLO~xzV~83rL@7LsDI`qd1`;=rb#_k%G^44o=Q$ z^8)r(8{ehe6+Zq`uP&4CYc{Nya0NNMt>%qHa3P=Kk`4>~?fgzdC|p)hf1Wo_4RGXZ zz*-c2*DvF~u6pX?T$Zs|ye>@0p|QIHw7xsE+agnktSBmPJ$=vR-%EAO4H-8~Y-ltV zgh~q$yxWSd9Ii~9Ym6QgfS%syP*wF;rW^H@cteaoJR47Kg$GrXTB}XX7boIBZkJ?%V0vA}g&5+e8{wC#B_jdm?)w ziLM70dPbNe-&$i^a~m76vfREE)0kNf+mPJEe(LByhu#6$7+L|(crQp?)Ak*zqnYQ2UpS0DrJ`SljMuiv3&k@oJumr#sLJg4 zd8uc0C%n}9ktW3iO>+GBIWA~i5WeZ!F&0uj$tYeTVw_LR?j82NoBGL+5t)-t*2B69S5=3x zD*$;MjkD)2Y?B?kdp`8z*~s-UwrrD0l;oB&G;`1j{J?URj2|z$;fO82krkF5H*M$5 zB~2+&dkOB}nds_zb5OwAx^!3+SBEa*taVftq&sua`gy)dlb#1Sa89~Nmt2252dzHU zC{IEK;0cIoLfW(`Z|Dj)NxF4A*}LZSmh1t=K7m#~4nct2Fthl1tN}UQ&IYm@pHR=^9OU&nSn+Y`l7XXa>8!p4ovN5}X2I*$z_^|G60v}lFk_5bxkC_8( zKz!a*GEnvIGtR2A^F7zH7tkPM^26Y6`O$?^^RkJStROMmR`gm4mk996BE*>yke)rOE-n)b^Is-bTr13s7VF+*Wp4+8_(ZkwAqe$Mp$DC1fw66=#sMbnc>G|Z zmoBxqa7q2!NUj(3ugVEs$>wd$!n%`rTK_p*5InM0?}0OAC`i=LJ)_rG_GHA9TiP{* zQ>%l%xW+fy#L>xeJz*TBsCK5)mQYVpT;&yHyeMER%lz5Ty|@kQZ-K8(7BIPq(jLB-T>fC<@O3JD1I4a-%t)1m=OvuJSHk31V85+i$JIxLcl^FFwG zu)|VyqP9b-sK?`Kmqbc&xW?If4M(n&mdS?-vU%6ElE|)i8@RWA(j?=sk5?B~nilRZ zq|ss-3}i^kL?bMlW4@oJop>`qA9vu(qG|4*6QF``^mwEp)}EN1ozi8b#4Dbg%8Q zDVZmD+{6c@37}Cz(;+YxCI`{#))XL@Gi#+60y+J!?E$-O_U*dN2yHWp#6_HEculwL zC|#&m7o+sgoRope3FBMN&8_RUt;<^hVQsaW*q>v48DZPwF}%e+awQYG15R;&NyN!z zKa}*6t9-_3C)u3t7$IUDE_l0TTUby@l(8Vad6$)t9!L$&YGoPZl5=P1{cG9dtjsHK zZzv)27@E+e zTv7v$^*%$l9rA+3qBeD`*c23woGRQ=w_sOKB5veTz^I0eQI5}V(!u$V7dmG#NV z|G22+M%b~Judo(QoGanf8V;^hNtXovy(lb*lU@|SxGp*S{3?BOl}1XchURy~X4c!- zxv~HYMC2t4f4;mdeS8F5Al`x3h07PL2hH=8l%C(pq;X)2q|;WLOF1m~oIdsJpUJ4t zlz!w3`lrER-A*;;cN$vq01o+3668j|l(igo`cGM;&~sPpt3 zb~Wsx$LBJ8himt3fg8tUq*i6hyUu!EXrGnO8Q}j2)=i;LNZ?Kd3j))=y{VLyqAL4_ zT;rqC&QOGMz>d%(OSLsuO_Z``yIMU7;_om;!^#P9WhG3X#vM=_+75m2&+E&#o7ZZq zFN}{TnH{FQ@0G@l-Fwa-d2$T!;zQa<=LVeCREYGg#|*g6&BHm4cN=Gu-ub-g_L&_u z)fQsWgpxRVBdWbD6ofyO%JyGj&9{F1HJBIV?Z-N#8sA))e@l6U@)g`R%`*xY6g9f` zwKeZHjdOq!aaU)+hi%L!Hng9=i)Va{*R#tVa_mTS20!4WnNJH2%ZJ6I@Ai$v;0>&R z_>3{QqF!m2j!?Gqp=gsTxcloEvPZ&f1*)BEUC+SdS4c>N>pP`AVYT?TN2|SgbcS~e ztx?5qGX9mji)Q(m@K!KJK&H+5+i?14BjBh+@s>FGPphaYX&Yqh?#E(b@d=j4Oyp;2 zTj_1glzI~JPHcy{k%@w@B%bCGa||%1#>T`BEu3rkJ|3?LNeWC-&qq<9da$zZ4KK~+ z9}vsV;YCB)1~xI#bgQ0_oTePoEU1oI-NQ~JxwbkAP_>ELRmsJS-qgGDVNZyAdM`dk zwkL~qQMT{8snnXQ`)Q{Fwwbn5Q@q{qaam}J$o&(6e~(-&l2%K-t$nR6bD_yNb$#9S zg_NPqIm?ZTOjJka_~7T~>q;B(hT`wY$ORD zs(=3{p&FLvJ<`e`qb(Aw@?8x0|Dx_KgWCMNcVAlC(gKAF6oWM_sS%YOouA@fb`r&;N#-eKsMvG5< zW)?Kc%GIJA-A8kZMbgU8L*eLVLEwYW8z;sGT@%N`?Kn)wss5T2rX@XV;Umsq+uhr~7dN=tgFf%aqK3OCHc3;wP_C8R*3sV%R&i;Rk|P z`--1U33e!ON@v2?lViBRWM)adhMYoWyfaiu7P0E zCW&6m_L;cJZF+rnu3Y{lsQYxwQ^b?ODn>~{C*kpwYsqsBHk=L_b8l9AYBt2eN`a}=f9A-7iv7QKjRM5DcIS-%_t}gvtR-@Scf#3n}+cKuB zSbT;L#)DU9b}Qv>1!~%X;D7KySUO;S=iFE2r&gd&p%JcHt@i9OdD=-!pjzi?X&9U} zK=aPpm5N0>>L0viA@J;O7l4-D?Q#+%qR__x@o^p3mMu0_A&@A)RHML;!SNHF8ga$p z&^t#oR`*)#MH+DNlTzIZ+ZG9kTGI(8J5US1Wm}M2l$m&9V^`4J?v*Ax`I>qBsMl%+N8BQ=z5V_; zc@u+tqTwnfD)XkLZneqyyn6yr4YDeweFNCpfAJSIFQ$rfr2C2CnQssrm5SWLxVp2C zhq$6<%AJcZs5<|G_&VY*EWY(f+VuZmYOH3Nw z2Fs#%TkS~`P9=P4xH2DXzxtHNv^{2r6`M|dI~e06{WuT*)+}^n(yA5Fl6aQR@1yB4 zEv&tO`=@Y@-V`8!$zKQN6~EcXImfLq-zGk0Zf2fk%J<+4VC1Tl`V)CUIK}mXC`zCkhW#oG!yf4DIDTi!#{qX{pNL)FDUHN z8le%%o_Xl;NMduJfIgwD#yx-_@G9^}qS^Jd zn%)`5ng!D3mK`{rcO~o0As~Mk^mQuk5AmO)Rv7V6V{(_I+ssBBdOW50zCgeuck5kXa`Bo0!86rOWK}SmeM)RXh^`PW<~AFuBDoWW3uk# zoZ9?;=|$xyhwZ+C5H)ePSUuOCGcvY!)nTs80~SGG!-D27xQzx!=vY+jFKDSXPshe* z(|}W@Dv#m7s+OrVA?n;JI6GtKi49!X#`*@b2wS=SP^~_Q(?| zZaAzE>K0L1c~)rPF#ArQT0QllC>no8 zt&eK{q|y=horFHtXW1IHYAy=hjP(S`vzx~S9O-8x)jE7N;&)XeOlKn?-+@_)FusY# zC^p#buCwSxfdeO2)6#)qK;W?de6Euc33gvRt0z%#{BY`(ClTPHHORT1ysKKoneH&+ zyPfW%O50_U>s7k)A^dg^eN?>tY_B;$P#L;Fev^k15B7U~4o&i`H3KEH577U0p%GS~ ztKW=~n3$do9lJe%@fx)f+6?Q<+4YUd;Ju!g zh~QqnT{A1dkl&0?JGPUEZAoz+1J9F=ZZ3_{o3ZZGpBPe#hj$+L^zSz@^cCN@ZH6gU=A+jgys|TH+UboxgKhu7qxii$x4J9htZY*3hS=xmn6SWah!fgH5JMK;Bi! z9wM5X>LTXt;r&bcX_^-WvLwJ90nf6F!jsNYfa2_3pA#4T?T*M;Mha)AuP>@Ez$i}z zrbjoJI6}bkJ=@Pk-(?HLXN4EDvsk1QO^1B02}X)LP?8&K73KO7?Ft>*r)rg#{CZ%4 z8<==NZi<7_JrI!rOds>CJ>+YoG?0git>zL;XMEn_r-roS-J6u*I6hkP>XMD7|DV~$ z-^h@?B?Yn?JflaVWQcqmM8=PPGB+f#ISm_zfn^W&I1bk1vrb4(*3?uCD#$ntOcri5 zIF)rYeXs9+D&{aP!mP5qt9PrYYPS~_)zZ6WRh}vK#66DJD72uq()QV!0DQ|ArDiVa zmerlHo{?)yCU>uRk2T8Sn~6v&nV+)-=)xHQlVMH^7_F0%^+BeYeQW>Fh!V=wbAGIT zsjbw;sVm3~PEm&#ig;MD2sWM$Nx6@|0W>V_k0yQx5biWp?+=NYo)yrRpP3vd?72;s z4LA}&zA?H=TdDbwT_Fzd$2Sf=o$x(7M}F_-pMZwSFy@>d>W%Q8yG(x>*(Fgq7wbI> zOOWxA6>wG6Al8f!s(yX%)k>z93%2-cVmfW${g62yts$Q*?fmA+*1<7U+GJ~HzIA3Dfcbz!dn8stCE6mE=;d?_f21Q17WVH*jd-IV$r8Aqf zE)s_3UG`OU?i}($_J;s_H+_!02w;6YN#sk}&%e<%qk>t(neIA|#f zJXt(o*W$iv7e#gj)gJ7Zu3BRv4&C0kdnc{^K`cYlJ4)(oCed@H`ybK|&b!$w0@BL~ zErun6rnCPhkx#aq1FMrVVK(k(iR;hVap{<`!+8#3zI-8ajj`KW$zvjqx}WT-*yNmC zLS#ull3r?O1MzZ61MKgZT7_B#Sv8ksza~tJYU42m-A;_0M#ASCS=PCZ@VB{n znYGe>QhEp~sIMThm_zxb?$AvPwXV%4-QVP&OIP{+r+b%C!i$QE_)#=em8S5GwB}CW zH#J>Xw%c3KY2L_Of30~F@M@QpZ~r=8OC6Xg zVzL|iN4qqvmqT#^@`M-1Wa^_Fcvhn(t6Qx(;4okgF0Mlc8oV2?MFHc}*=cag0#M>z zzAL4CU+@HZyxAV?W8%`t2iYd+2?0aT(>~U@)Ym+D!BL)F4kD2PCY;$X{W{wW0Mk9`$b^)#hFRzeR8Xii0#D%j?}G1)J=)IBFVEG2yR^JNRi3%%wfGU~hBjgMlJ=M(R6CUZhBEMqS+rdjR* zJ!JN-XhR?&g#|p1F@76Z4XlR<3c!h6yIeZfz#})Gj;Lw_WO2gQ_?*_Sb#^yc;Wp^e zU%%iu5X_e{lYH>_g<7!cRqIr054oa5`fBjoa-yC>vROu}SOVzo>v6N%1&V`OJCekE zW}X=G*6XxLi0}}zS3STW07pWHT6e&a5u=TRN)3hw_zKInvQVyM`%AVMVe1DFdowGOox+zvnlK_Owy3nKi`O zwyr0ny$26GT2=1EYDvjgW z8a1`LU9hmOcZ8J7czp_UopZlUvgHgoJhXCpuG+ZJ;Y7j}5hnUAUe!PxDeas%0t#Q{*BYQG~k(Y_((PS}jfUsxu6Eu8f9jIPE_EE zpIz)e8A|B~ppiN#%A5*LKg1OEMuS6wjIx+aTfJwAMGuh1J4u6g!&CTBt&z)EWf_j7#KxX`zaJEYf||AeBk+rDfG~OxYdR?gy^_(g{OJtjdM*3MSStRN+(AmBf-a| z*{`JKrRqdK+ZC(Dy~BB}J%+ZH@-KBitiIV_uJ-_`v<6*aaIB$+^p`O$Z*L5TQ?eIq z)=%8a9s5E?KJcv0moKdOY3Ja&$?ZTyUinNbN$RHR$rZGqpA2M|bFAJyt+ zDIc?jl~!HlFg=Ol8ttv`UWu&%eiC4t9>Mn7&0Y#hEJ?&(Vj3_gE=hmlOsjd`SV?MbUm z_c!a&PV2KKZP=yP=Nfy2x@v|=DE|a&@yprweXM1V8l1vFIF8OA1~BxeXA9j?O}1-P zoAAQuF9$S1qkJ11Luqwj@?F1i#Vg2-)J#ipq4KM8G-utpvTyNCqlM(J>=A(0j?0XT z9=cMpF^tdt=}%P^jG0661LE7Ws;T4 zB+yCYm5MA-SxWZ3xv*kFS=6|&IDfZB0A)bZ!_gc#4v~wBtC!gRW3t5T~)BC!^A{Blx&rvXr zPR(&LCz~WCL6|`wZglru)3%-aDAfdG!kXWVn{sEh9Zw_2l-KLTBpQ_ND5dglQgIbe znM1d9=H%tsujjg+KM?cFxLed|OCJ(=j~hGt>9*vX+wcim(|VCJU>VB}{-&Fgm&&*f zydAJC&HR4X6_DQ^xuB{+VeF^Sw{3I)R5XSBeTT`+qnzjb;}T^tNif8LV%=E_8uTw zGfXL7?K6jVR)b%l@YFsof{i|D=O~jfFP9BQ!)b#68GbO^s1@xK>icV2FHbO@1C_{> z-R6^hyx@ae%+f69+Ab1dZigJ?UN`dTt>b=(7}ieZ@+Bg<%gjZd|vR+7S>@k4>4 ztn(Rew}XsP^u6G8e94<{>jc7m^iN7v2!(cMOV#e0UtuD;6~`4Dnc{otG9n81ldd`m z|G@j^I4c8qmcG0QW}M3v=WfB6@X5Gn{7rYNj+RlC2*8b+zw32(OqZv=I($<$Olp*0 zB;0v=(+3bVr1kZcts9p4#1c&$CfemU6T{G>m>!T0L8Xq+etzl2m#Q-_5uDs}?1tS* zN{PAbkZnEa7DLwF2un6Mk{!ojr=B#4HwMe{@6?x)@~xB%B=eG7+a(5Eyeo((0C{g> z(RCT|q5t4HYpAh1A|~?j$eVe?7OZWE-L6LGKJV1&z3x+$)&8PuMgtZS$rck$&>QVOq%)b^#oJQGkIMm#>oO)m>3e7wO+}4 zNM4Rr$ukwKdmapN~8!kpGWmgQoi+q>gws2EJ%oYlIO zz{f^EiaUs!XkXm@g3L_Jspb*+Rv!l#HM1QpKVTZ^c%$$-C~ExbF@Kx+86q_DLbQj; ztWb_hYxt4C`%|CceRSKyz63>W_tIQDk@P<@#`IlV2Jl?lKZP#BNrt}dm0b0d+2%=3HhKgK;#sM|? zF4=}}Z0*x;A0ysSVjieB#i~4I4syMVH=0G}8_XGK(|twCO6%dwkdGT3xoD(Qk(m-y zOr{}BAo1zyQD%3wnJ=j3pp^w#af7nF<&2U~J>s0JV%+cKZfHZo`{OTz^{01VlpbaJ>sw#B!3Je~Q^ENVAn?G`Q( z$HCpLq)x0=$0{KnEz?F$?Up6E$r0k9C{h;v@l3+388&bWg%Gq8!~g zlMP6}+7Fcma_DqFuC9i9_7JbVzN?Ne#I0v^>2c>*`#nf*p~^hdK}_1;WJyrXqnOYr z@QJyit8Ye(s{9!)69@Z#OwzJc0dA+>3A-n9Sg}^wFUwzbZXt})fY9t+=LT+oAZd{W=$_Q~d<2mUenvJL3Dlw_CTEvupBdK3qB1emp#vCLI`_aib{=M53Ilg<_`1IYXhJb_qu2uL& z0%KjEq5VQG^ea5C8MWaIBvO;G^PJR_0%%uGz4So*ar0we3#7AK_bpFIXfhn@olqIX zjf=AXPg>4+wkXj5?y{Uf}pvAk3YvtOU`0k9JMVjbS*mzo7Z^AJ5Vb{>#)=JMqdL zzpB-olJK>!ei{yx^C)uZg-NwHj+f-8)wWyna-VgnyCoRLp`#bWaskzE;rP?36Eip3 z#Mv~Qf5!JrqV8p-(NAI=yP$C|`yK?kKV(hcD35JC%4wEaYQBHxo)&9DP)&)ZytNH! zan#43OUj>KF|itUCGpjG_v+5p5Rii-)xlu$=if6JSj>4LuLJuA92lF+;< zH0V`X2tNEOT>n+!D}WZo%jopkR~1^b{)*A1-Clj!d*Uyvbi} zd|xo?tI4hQXUVoU`H%H*2zql-{;qn<#F|T*1>$jTk+p!Mq^U(lTz()6ee%4A_$S{r z__p^bV`fs4H`gF^fu-WddpRj{btqP{CA>4h?fKulsDdLV?R|nanvs3b4{7`+GhNsi z_Y)?}TV{eQ?F+AQH=_LtY%y8O;0`aAkRNnody-0AZ>=URe|X>PQFOB#aK+C(?^Nm` z=sq*$)<{_+BfsN*yu8Dy+5v7Q!?a;SQ7UY(cY5La_~U#KiV7~0Abqi`jH5aZX*VC10z1X6b=`5m3VV zzPSJ)^1kr`MQF*fdOwXcytUOI&I|4(^;|u!{HGqdF@XjX=b67x&tT8f&#*i7jufA? zosM}om404p6qDHc{}$}U!fyn8;z>q(f)sGJKF|F5J!Ro=qxW!^b-l6;M!s~{heSl? z&0i{B&Y!_fAJaW9xiW3Z9_;=6^mchTG&;$BNNIy_A8HF}ScRQ%|JXB$uJ!8TP3mt3 z=zXEsbR)I%!u1XIUw*7EHC>R=>K3^ZW|>C6R;~FEMLG?ET%S>5ilR}jJS@{jdH2rp z-uR_Yv|MOm3!fKz3LBlyKK!%LvYP06Gf|VX3HC~`=)SiJ1NhY;LnH7;?4p0U4BOt^ zf49_0>IkuPfHi#mBv^Q@Vb7C2m`;bMUelhcwMD#K%T8qIuvv#(d~OKOy{I3c#m!O5 zNjk~1-Iz0FxxL=G^{?jGd?j>84WRis$;^Z4@mc>FlL9XQ+npxs`4{EP zrKu@eN!Zc+0pIl>t^HrSv=TAxZzA*23}SGmm?^oG8s|k<4Z^udU<^4Sk@+oJO*ox^ z*qk^(KhZEt)4x`$KJpJIMywDWktg=T)DKS(yECb(KUli{x$|~YZ0K7+GWV<|-gVH& z`9iZM2UmM7|#MQ=pLDA;#C=j=}rq{M8BCeCHJ{>-?saW?n&;lUcLJH9kWMYuR_wQfxY6 z1cTe-6{=pBFR#KR4g~l3W!D!6K0Cz1bab43T;-|(0|x?u)u=t1S)CZKg&^%H z9}7}nERIJ1Bi7sUjA718qiME=+o)q2gL7$^_d89$1ySGnU`mH$FF7fGVw?5bq*-Lz zl8K_lKgGawo-S9%xWta&LWn4$3qS1d20Uwgz+6tSogUTH4wce z3e>#LuJYK%Ac0gTvnH1VWaAY@*}|t_;6HdQk@SRKIZfg3$alnk57pl3LbGCU^MT;y z)6!1HkGYr3S9I6`_~W?RZ|cF+zdpN)1jYK6CGWBtxfq4e(&@#Z1e3?~B+@IEOI^!psra%#JyphkFHL7@TvgGrQ zE9cChjuM^=6f`@V5|p^D&CAHYAVLw78^htpEd3LVVOw{Bczsmfh7H0rPfi)RvpG9? zNXHXRab+}OS+BpM(Se!t)0bBj0{CT_f(8&i^$=b4uf8C|NOfgaS5n^0s;&K>scTbp z?pLrcB|ZoVDXOM2i+I)fOa63iL{M)zWgj!O%KYM1%Y`{RD(cmSTpXieoqCT)e$8Uq zeU8`ymgr8OOwq^)Y<*3R0#RoVp5L+0Y3N|u)#2;DbWCqFo#7_zwXb$b3C0MXIchcnL7 z|D756`qUjT`&{6Gr7FGj>e&cFfj;8}&w@n&ry?z5MC)PEJCEXx>094#>}KdO+CO@9 z9pwV#VX;kzUzF)(l1K$!iJ?jRki|D5q)CuIe5!)m&=>7BC*oQIKWt{1Y62`lhPcfy zAS!iWC{OYDK$MW=$%x`NJ*kd_e#zdEdvR6`>$TBtA>FW%-Le_CRu^)q_rs)sVNpNDZc%h$xio5Vd3C4O@7JeJ`zqR%9)R9>O#3UTpU&d+7)LP1xt@pM(R{87YN21V z2Wz z4SX;9(dq>=$bnm4en#x2Eb!V&ukp|IkSFktSHctyw4V__x_Q{03q4NuN-Nor7 z%{C_}u{puB0#(gE`gTv2u`PC+oRSa!+ng-qw24drpYnZG_HH7mO79c4B8S4?H$}j0 z<-2jIM4ZdQN>t~zb&zOM3v?cNu9e(Ca)?(hWEeYQZw;Y8+-qBrgf14B8))0{P-RVQ;@OR z?$FPZsCZNn67$7em}cAagolvWTG$c1nN0dr*j6352Hs4Vg~(<+lM+2EWEnGwBPQk( zdsJmpVrN+=UcR2egvwSdnI0TW{1p1RGvHuQii7;3{m;iS^* zVf4rRRd(|4yurOLaRK$n`2nLw*}$ak+USPgn9?kGyK9x9q|%1ra7eVFnQLhwBinG6 zBUzOD>y2WF0u6uHItki^5rb@+X`8R4j$4S6Vcb5)&GWdD0v^gZzU-c!hS?0qdv>;8BAR}cO6 zrBNEy3DYM_oQ<}R=&44<`OaP+*$qR9~u=*laca4U zy#K(J2Lr;FHx%n6xUDk)I)X_qOr# z{elkTkJGqQB=vH`_?Uc3cX{6K`Bm~nUf)hM^kQq3UE8=3G9vB130#!{v*k2=!MQVk z-~a#l^}v!i?|GarinqwtibB%TEiQl)UL;;oJXfP1-%EZ<`yoZOXN75p*O$G@!*oY6 z{cOiYUG_IRn;!BaC#DHEwGO$8cw6i+1QK3#?iZ#H8<*94p81f!!5vNt)N}lZ8S=p} zj*dMOMEa_|8x;Hwz*m1I`}eyoA#47V3*mMSHOSsnG+DT&k|%mwMPw;RMv+|O7`wH& z+m=^$q&P7tmi3XeGJW$&ER0eA`gs;i(Q-bWFsk=z6Hi-m<)gSx-Wp%qQr$JJI<-{O zOK5!FVjJzXhVj?d2qYmG8n`2*z4LK}fiu2K(*`@z*mvjQ-%a}I(k#cuxnP5FTb*1? zLT5>!Tmfy#y1uWkO$8XXM#j+3e<~^#-k?qR!S0BkW5S z|9~afQp*5b+B@&|^pPUfH$vX*i;>k$FXn1%Qv?ecE`~Wz=g&uR<8LfuR#i`QcK2jm zy;4`ttx&YiT^?$V;Yj(`$HVD64ko~&%&P?z9I@7P!482y-eVLQ-qy(*F4Mz5=T9<3 zvd~QaHCnfs;?5Z32n;9EMx&<|t@dKl=^Dg=LsBP)%`L|N@}l3!B;!@Ro=j^of>6=K zs@Q7|G?34PO(b59KP>nu)y@FpWbaYcn{}k1s+|Da^Gew%H_FjwnJTuv!)=iwH9FSl z<&d`iFdWOiwmcW#84VVDD{b{D_5(PuVsA{b3*8GOf7lWJrQw(Y(qP?>)yftC(6PIL4~bbYsc);X zv7dl5^X}~0ku$yaVj>5xt_WIi8_91vH7(AX?}o-qefMf#{U1EDnD=fqE&VY{X*WCy2Mya-hnL$kXph3Bt@SyOzTx9MnJjap-2caA!!TQC^#2p0pK zMK**p0naI|oM)5liNNVfz`@M9Y5aUWV?%+fzZOL9TU?tp8L!~niis<%9Sq@dmz~P7 zT9Zx)CV`oGJ8dN#er`7D;luEehY>wSO{j@1)3Bh*?B3D|NtMo(x(R{osJ0d(dDoih z(j^C8$np?&*g%?brYj%ml0R(u^+p=_Re(ch-}0NOf|ReeNzGUhI|-R%I~dX3M3!frw=}Xm0E>8F@+1WE7zEF8D#cuT8|PB zQaalfuguR*N@6IcxaQh8F*dDMI9FbWM*!Cn zAP(d07|2ZL8e9*DGh6lVo73F>eVonpHVRt|u9Wd@RqtF*i#Hw}$kaFZsn;#Q-=6JY zCPPROG@hSRb=^!}`t~Md@Fu>5zf|UaI=S}m`x!EJ*_3-Bp3K~2n&JO$ZR5ZFS$^N! z?vTYFg=>i#TpooOqJmH%hav&m3#9Kautov38zjBvb3M~|fHE~l$Wpbfb=wK#C#HrIl*p-?zHqILavvw(QuR|19!9{TTV;V&cDTD{TFOj z;YO;tdNLjw95F1ky3T5WKk#tJMODFz4Ahml#mW7vyiZIBa!M{3(Yn&T^jkmitN8^P zDMHgqfZs}tB>{ZAYsP`PV?yGper>-0IWZ9zqZa8;r*N(&rjw*z{UQ{)BA7U z14G!wZ#77r=f1m6lV_?6bU7(X2K+9rMz>ZUMgmrz-lj{s`BwS}4w-z*5o_n>e{SNp z5`pCuPds-{TK;S(dO9Rme?+hso!@uNcpgO;&M2G_l<2h`hM3(gI}Zno5oEqQy?Pb*i3K`Z3n>Br>($7n-gw^mY=Q^NRR)N#GVKB*i-z+*$KtS1>BbMZ`2%`nS0oX`6QVWh|N@HjsHC zjk&4*WKGic`pY-4pDV=%gZjH!nB=##SQO0PE%&lmeTU zz{UbQ8l`ww^Iq&Lf1JveB964Y@+?oKl6B7yQVI8YvxUc)w|Up@||KZ-}B#{d+;KCO_!2#6gLkh^vI-ep#`4f4h0%J$(&D!E~NbUX-wOo!cjU3Ln2_1W-9uzd*0GTVdvtGvqBcM8VVgBF7FomN(r_Pd=X8!iQtYE;p z!#s_Tl(L>HoR83NJw5$sUegM+dKllzr+re21ljP;)^-|K0mB^J_gywC8_VPKDkiy( zH#&6iIvG4I=q+8XicmSG3|GsX-u^q1OCYT*i^+uEyPqRh@NORy6!wjR)UbqIyS7nr_U zl;>e1{)P~mWMT897;ZCPK2ax>t74`C1PnK55{yy#X-=g|zqfTJMEX@L&bi4vwldBo zk+EY*7F+CIdUO4VvIC-J0)#TpuXn^R0;`c^o@AXk#f{TDSsJR* z3H4#qOpE6ND-+n?@67}cRSczcLr?Ts8Tb)0x3k;0JyRbyC8nqa$2n5Vuk5#K>~@$l z;|*X@~ueO{DQG!d00!?M479B9EMn^I{- zk-YhU(6y^?>50+23a9G{r-#AESgPT`Z_hP0svV1t%i6kW=mM(;jG2zCwtB3%wF3IG*EF^glJhv9&+ZlDXo5?v6YN(c5^?Ur# z>GDzL7!T}WNE(vB&fOCpAFqdVVwSE&1e?-~zL3$Y9@Tm;2fd<)$L<_lDBuy%kD}2m;m?^F`pY%RAc^$TZa60+{+>!#?gNJNa?QL6 z>*ya9aenmO4J%HRJp&Uk(e47gLeWys0s_^N=Iz<5Kv^P6bcN_m0E@y!Ik5=Fz}0Tj zm#Qv;X5)eLCv6on-uDD6N_s1oy!Z-wxf_QY?B-VIe26pG_@lJPl1PO|u)5I~Xr=@j z+IMFNDCc}E$@)%8MG{XdvYSB%?w4;qzh(OTQwU==S?f_uXM*6#`8mRu(`Jpz6&#tD z(U^z2*^{$LhRRF+z{H7aM^QZeQeuA4w!T2KbN(6McNdL zT7a9KdKXHlx6P??kePi_7`*R{oV*zqumf|J(DGqA@ewNOatn?^4Jip1a}?>zxZ`Un z{X*|7ToXp{j-~TFCTO-+Rn)EaQ9M?7EfRTeay4z^_nk0y_jS2rfe>VZYs1)zA)H3q zj6SO1xIl{;XfGD?p}wqnS5K@VebP?04^u~-r2ax9@t{oT`ucI7f)URat~Fcqza*sL zBm?)VEt5lGF4M&94|cAPK?^7`4zdrPKX^6my3WSqWXYR+qrnSmsHYQHt%GvIVcagH~zu3Ii2oygVi-jz=kMO9i!J1S90+l@j(3x;D0+ZV?>&z>+! zo>?9|)kD6MnGDTv^@?2tJl#Ju1eaMppbhR7zRuK+)!CsPznuODZ}U_NEG(7h--Uan zv+w@1j3}Z=(XXVYmw>MSS$z{)F!GwtEg-4{bTOsIrL&d}Rpeadr-c4WbyLRv>s+k= zFHad)jomv|9IdlN=&ZevEs>c1;?0xYa^QpT_zEU-CqKKANZZi9@bme;gHw8OxEJ+r z`snt2G6S@P2$tW)9Z#1qL;BAZe>5xTJg93qnaPQYpM;j4!}9y}`AwBH z$C1GPQGV9l_$zE5Vs7YYs&&>MP#|+VLxI8N|H6!kcq20BW^ji*K7>ql`a2zmp|h7A8&k5xeUGBq#tgG9BdTr<$v{<9v()IFCF{9Cl)KX}0)3vRs|izUX%m5H~1 zZ=r)e6}LnIQ@8dLcO#uEm@W-e#a-zoz4mzw+11TPxdqBZ!PQHea@XMA}rkzptEk= zrs~G2>h;EjnhR4_nlk{86R34rx?;%cI#Apt36@^3u>=Is23F_ve9UV60Xw~G9qjgg z#|z>sJ!x(&tvhLbbl2M;owYu)sw``$W%|Pb;YJ4d7fTr|rCJ&||D zN2L1rw2YC-O`&-c|(t*}}b`3a7;qu)e@35+4e#3f|gNMn(Sk&q zw?+I|3Vg5K>H0a&AN${Y3G%mb8S`8l9ZPe4j>}6?hsMXqiBFe7FU@ZNy7+ggRX8$L zk6ue)PECky`x4I|#dOPD>FV;!ct4VdQ%zn(x9bwPMPIps%TuM6jy^`c`h7m!(s~S+ z|0no%UO?uxP0xjwMWAeh6ks(u+bPKFfwt1^`V|e9a|)KGUC`KYD!Li`vqnq$57=h& z{c*$p;O@PHqH4D{Q4EM8h)Md9h~iV=AJrp&iA`_?$lJ>sryG)Ls#v+d%wNk6`u7xYxM+Yu=nIl4S>+aXHn_LCkCW`LLId$x0F{S1RKkcD9e&*e&I~O6} zZNJSrzHmVyBf1j-5^~_-YP&C0iNcx1nA_ENaRIPtqcr$saJ~s@bcMjeQ#KrAkw2&G#MHMi$fE3(}vGJ#a-}PR;PMheVBRwUNdbRwlObuRuvKs6%LD=flFMKW!BhFl~IbORe4qhM8W zXIA7!&vZ=uJLS_#8AldyNj?RkMA|`nj0;=qApyu5Y z?ULIv;L7QJMo6yto)q#z`g9+k!Y4#REOJ^13|6K@2V$Ly{8sVTx9NJ-3yHIJ*~ImC54zGt@*^Q zn?AyBi@7s%7_e5(HZMnbhSljl+Z^4j(SD*>{TeVw`E(q71xl10^3J?xmLY&NZoC?qQ3P#Q*tJpY`~O1wF(`_B12uuiH5?X`+j>F zlKJ}Cdb+MUTH^wPwawRz^nRGVyRWr9ZnQvNb;3NP>cJU9Epo%&L;dBv{Fh18iYe^{l+>J!?lXviEXA}vvA$JTDkC-qMupVWt5zlZhb_s z1sq4|#0BO)UZ?3Sm=eBSx@QrXdbazno^kBh0T_4Kd>nD3N`qQS%1IW?>L#Qf>#YNW-ETC`rY zx8TNVxry!ZNZrYGow~T@u*fXo{fCijPD9_R;L@Rds+x&M3qEjNVW=9b;f`+J!Wp@k zJt*>rywv2&(CwVa4$WEJvkBsmb$wlz6bCLnI) zriY$A2V4c-zrWZETPZo;anOFP4E}H;oMqF`Kk&-}W`E49A1(o|r?b3yp_^(ulgtAz z(oPS(kgb1rBLi1;#?#49Uwmbx#WIxAU9K$7}Pc)E0ILAYYHc>7{v-`gH;x6gESEWo7Ca+Qr z847jgfd-y{4P$x zKCgf9UXG;BnTlW#$*F`Bg)VMb{YW&aCCM%(9|HbDLHfo>TCi49kGTKJ)tLNqsZ~C= zgQEoyPr0iCW4X>tYUs%aVd%SIHrQSfr2}Pf%UThq1G7D17u~B6ki)=|S7_UO{BRu8 z)4Ww73048e+3w7q#pit>`U&Jy5=)sL8 zeN*6T3oqAH@XN0IjrYZGm?oR_Mkp$6Z(~v14@gI36=YobOzfM;;>;)RFZ_xLO7X!# zN2aiGr!=3Q8hYOh@fVA z$>+nC-e}SL*JHZlC!BW~g^ia!;hATxIW4wNc@$0-ig?%OLhM8J$g)ImQg46KQ?>#j z=29nlD>Nqy!JcOr{77VFdStQ>>lmk}^D$3(fqynEHf{u%C!gE)9}qx4lDj6AZgi{3 z@`UgWhYjubhm>#dwb*Jczn?g8C)BJ}Eb;g9$O(7L6MkQ(a1V##cI~yVx{TKXkdL*$-SK}c0LWw^ur2cuGPI|_z%R(^ z*UU6LUiVz^(qwFemD*Nw&TgCg=dLy~x&@SYr#c^utq()1ojYY(+L0gC|`0f=q zr_j6Epr%g>eL#_Db7;@|St8oBTk)kY7}GkH=q5@}-$qIslbwWsS6?o^w;$CuYtk2i z#^U1a8|wsjrXvM~-vQ58_1^(X|I?qrd!51)(@-gBBd<1j>a1}0YgsQBoJ$HHL0bYJ zoWUm}A3`3WeA{PJ3%DifY4sfqom<+TIPI9mnU>;Wcp{s?wig$-$18^lXFn~yTHs}! z^T79m-51t~lMn;QER9)Luop4K`a|VtfTIWB4k+BNGqqSQsJ zWUShvD?J%ekP3Dp`L(|q;`Zw9C6QLFx@j`QYch2;d&*He4@%*floG>^ae0687p$jb zPU*yzHX#@tY!2fQIE1Hy4kS-GJ(bCnApFqbi_!acWG>Dy^&a^B$pB72SyYDGl+Ltn zS>`8_Qo9FaDvjqSKnq2$iRL>3f~ZPl($M5%v{iE1V6KTAdynN7;o>hV^7HJ3%$e=@ z0*4&^Rtv|B>*8K*JUgbUI$nO&@q{pe{dy^#SYB$Fz=mc#Fu9W z`$V6XK}`cV_t63ZwLWPO(PzzXGJbu`&y35psZ+MJ>52Ku{$i+pD!EIFhRHAUv<{>|`R=`G}U z(Q(++QKEt)z{fM4%BlHfGKbK4w=g@9Kr#L}TGZlgK_2x@n#3j^6a%vDa3vxQ8(!#L zh6+$1Y21lxpuQt5F|}o&Gg)<9j{XjtG!%H2*j&1zPsY++Ym{I=_Rg>$kMYVBSle;F&9 zhdw=iJ;kG2(amvBS9I}}jlM`b&&@_<9M60RgqbKCw%X>)1cPOD)LgH^okSJ@xhh=m|sc~cL<)F12G z4U&r7T%DC%#VN1_ocX2(LeP7SxtU140ys47o~ zPNV>%ulL-ExjQ3e0l(Km>+qTmmxD#kM)5-m+%9|G+>0n}g;d_uU;yt_j6vUXZwF@GXAc?A zTUSkNYOh*QN}$hPfli%*ws_YR;*mQ!1T7#B_90I~FWiCWwywwN(1Q?2jf2Z(*`f=u zX1sfXaEEIQo5DS+GN8#KRW7b?Y~_o%b1z;rm=Hkp%FNa{_%)?1$XGYjq~Zo@UN-7i zYiCi;0^RM_pnOfWWEG-le@V*{PutY=W!;!`%sRZj3CB^iZ{Hy zWa(r&^JF$tjg@VBcAB3!n5&v87c0lGVN%tgst7YbDSh=R=ZMRf9JX${^DXNUNp-HL z#gVp;t|=Ll)yQ#YkE>TNT~z_OvW>(d-TdvF@8_|^27xj&1<5x?*0La@CPDO%`g8kJ z1T|mS(Wg4WoIH=b>t6J0fMf)8AS(5?KYg9A0 zc=C3ZWk@}#?P*qeXzAZ>Q^9%JtnbU3)<4XQN--dz)s-AaFO#;00c$ZTE33kK=y&{% zE^q!34{~xc-OeGGJXTRjJ>W$8Kmhem<<>RH#<}*^%Y?BCi#TiJJ{J&uc2&(Y1=xxt zWVU7VVFt5GMg#P*;Gd-J+M`edG+hf@`p?7zk(!~kZ4gJCnS!hGuWOQwe-*BVqj9q6 z8g(E_iaF#38zA#HPcyOvp*?r^b7dQ^+3Ou+GCZA^s8!(X)Inubm$F z4_XjcGH6V)+Ii9wJSVu&@*vL-VN}b1hSzevISSPu$tyasNJ}`+R-9s*+}v-q zIXuC)mmP0RZ|6HHeh$ENyd`ZVvblkT?5FCc5ewC>zkuNN+dm&qQ6}3NK3-WmYL(mB zqsl@lBXlZX*LD{q3O%7a-+W3hyGJfCkft&B0!e!Yz9}^ny2s1vDij%-I&|zWwPI5p zl^*BAmx$$gvQ`+NGs$V_Zs(0r8a+FOepodx%hw){1ACZ$*pHE>>rf`kEt730D&!-6 zXRs9P=*J^EAy8#qxyvM%lCd-aI=ZIJTZ6M?~nBqa%-sKfQ1H$VYOM2HQ;f zsUHO=Akv}th@K)fB{Ow8`3eZF{qo~plWiy#I;QUIO`lC{RQQ|InJ*1QZbSuOZ1Q18 z1!w(UNiqp-S052RP>P`?K985a3>Jp7CRr4D)-fGENBs+`S$>PA5k>ns3D$Sx8^Lu- znHjs&)yqw$g8hs^N~FP4vCYT2zi>fyKxXynvL!u~?S^VQ&htFX`mqO;AsbYZ@1tC2 zxO4PLEi0DaH(5K|DqM+|Fe8ukdb4idyGVl1>alQte{Np^v);Q#?&M!`y~baStFTO% z@nC0$POhv|exk}%kc^7)8s!oeoW)rxl8{F8T(QvT+}e6$qw!SX$}=I`^iTxnU*Jz+ zk#q;ex%VsVX<%6@!J3}1&&I;yix1swi{UZ~*bV!8b6(C>@%z84@m!nk3%y-~Fr+Fjl&(5thJ zxL>HJvWC=0imN8KuLzHhM0U)O>K&?!kb2Rb31=Ap#JN~sgJ_LUXC)wAE890`F+IP+ zx$~SK4?eMb$__h7o}RLB^%LR_v!EDn8aQ1G$>FZz8C7fdChnehhDo>P74&In=)T@o zR?-5}N#3CU2#2(UDWeRr=UeEE7)1?rU2_K+;~1UKsTqA-kx3$huA~s|Uk`q&Bjyu- z9qmty&DExSp2uV!sTO%|h=jUy<`%hG^A_DvilY_KBb6C7 zFj)M>Hd{`>1>3C)So}?x7J%PT0hR`^u>Sz(WZ&c~Y=cpH$%wk^AG{m9}qw8yKn5!jZKpJyZpV-_@cbxz*`FLdo%O`R+e11yXEN z9@#(0E{Et$k%vma#cSbC>|qO@Yyt)sZGJ|`LV9l^ep7t zJG@(Kn$f)R8;|~*t}1Zc#ZlRgDRE_^UN%!hqoI|PRuCQlKvw!i@L)59)08sZ(FvCo z{uB%sqVD>?@q}Q$z%_^ScLBg_)>Vh*Vjn+e26U)Q`5Hd~T_(zf`2pG|#9U5RMxvCO zI8nPM=+XXwsgY9Ls$a&bx=Fl~W&%n7{K+%t&AfolKlX^~;$s6a#tzAQwAGd(D>9#X z6;l*VE+XP+`Wuf<^Kv>*w+~!J@CEm4)q(M4_!lKA;*L-fOvSflX9PJ=5_Y*VnIk11 zg_Z6r8Sn?h(9ETd&$&U-x7`Vl%&5NSIuhWQXgX z?NnCW@=pYI!O$nQ(Z4`%rx|(a>tyeotjv*zRaT4aTBJ`@{!%mpJeh7rJgDiO3sMDl z_IPi4JKBPt&Mz2cxeq(W5U%jbsFSf(gMd|Bc6U|CnVAE2^8K-Pc7mJPcgcsF<^u$eyT4S>!iaVgJSd$7R3C+reS7XcOeFb& zyx5rPMCd{k6`DD3p#oY^H8r$DQM=D#gpj6RDi+M|(vkHBlnD=7JmI3I8%8r26ajhm z=ep^zY)$-nLw%dAh7`r0^h=9i#VgjKt_$zuqf7V5?nQfzjje$ON-xqqEGxZ`$hJbsH|3pfUSu?<-O*a9N{y5xl>!_{Xf9|mw(t4cDi^3#}- z`_dK0U)5^d9b|0Yc6W|88&_#Ao5g6 zcj)d<$=e5wz-1j{3iNjq9h%Z|=H)!C-hGtM4%^UUI2o%c{fntkXfklvYGD=@G!<=_ zz5oQJ-rIlN3k~i8Fee=L8qg>8o0_AjEZT)&M?Bcu)7^`N#)}-|&AZu9X;X7A5KbnE zCj+`I+Z4%!6KDi$dDk3%pp6AG_o&r>TGan=SN|Vp^KzW*d@HdGxp{1Pu@-{;%x;ol z-VKtE!a9WbwVGF`okwumW22^Ara{LIuWGXthkFna9ECo~$F}@!ze24eRAhlRN?#2@ zJ!`EoT)3He;4JsyxG-VA~U~deMzq7)qQPOefjMrL+%q^wUh@bD(27SrZJG8 z>0gcxZlxO`fSy*(@BOVI7WZvGD!t2Q4i8qV-Asb4AQ`?#ha&=ZJ&R^JnkNV9Q~BKv z)^gy=I<04k@%Ed1+t(#q4LQ8=POoTuw%KAFHG{ecw=Q)m$qQYG>VztpvpcZnIj$1h zNTIv#hZ=HOZ9fhZYh^sTIa^y#I26}?^)H?n>PPai>U?sQ zS^==Cjz7Qs|Eu5ag{#|RqkE<$Im6FB^L4}Rd#$-Uzpp1EU5T6~r^|DY;1+yOJF4;)CsG?W+%xWa_3W|9;dBONWrbZGOFu^%%p4IX`H*oul;jkGE3s{hC|{ z2k*_kSJ%HVD3gl|adJBJDE!6EQuEE~$M@6gO|sb>4?GN#%R6Mb`!&WBw( zY<)6m(Pd$Lu&0w$o?7W-*)S~Y6f!H;G%{X-JBkdQ9Xm^sv?gWF+~tU%as!=_uL_Q1 z#O>t1+?Q2pr}a+#-px=93XR}%NeqkM;*xls#Y|BxsR2x|dUN{muky~%t8*CL>a5`U z%aw?mzO}L9kvd6#ij9`a^wFUO^SKLX?{+^FR7jJU!`4gPM z^ZW8;Q||OR_KGi61$A*N%W~|02j7?Qwp%uSG_Uld^~LAR`b-d0-~Gr~ zSG0I%)FXrPp!hf5Vt{`=&yTB3-S~D;hBs&;{;)b4S80jtD$UiV)grMgb0jZcMe!bHC--h@=nvP$zWbt}P`lby>cUoXJv z5&!H)17X=zu?h>0#^36FxAe1iX;M`?p4u~0mH^N2wqg8`RC?de-+1ldAL9(P{j-zc z!wgMmn-fDkc$BKyxxu_v4AlH1Syvo%80u4j4B6MAWowxgD&E8ly6Rp{rR57b9a@Nm?EcXmNQ zv-kb+0z1)C~N-ITcA4*bnC^e~1fG?Q5Qx^7s0c?aC?b z_U>Tha0z#9*q}b4o(|Xt@K}+y8YsnV1x>j^WV96#NzL-Kv$i0Y5S_+SU#xGzy?lRr z%i{MZKKmGkJCO?WvJ%~#QYqjpXIELXc==&%^X4e{tI-*$INRqf$J04u>Eh8}0bgjZ z2F#66H1xaf*Kul}BV%O4Cf*rGEmGf^Lf$yxsT3=5p*f*7Ind4cs`cBx*5@8sMu>+L~Mb|UsPt$x7 z!cZ(OEf@^cO=Q;em_|twK#MftV%a>I_Xxiif8#N-AM1M-*iXM;|K$(sU){tnhrPZx zStB{8@H+q>-Mky^lRTy_gQwu+%v{*dq+HqQFpJ7dxW3BOj_z&66kHEIY+Ea(0x$RV zSF6^Hku#G7rA%h0;U8~O-=NCv;H+vONi&tWCryJg60 z&2+5HOs2b~TwMTcW%hr`@BTYBC_nJPrGxEEP|?AF3iaGlYM$_mR+tpas~jr7*NrlA zPS0wBEN{@(YsD#K7l*1Kw%Lj`yXg5G2xTfOWqh+~f55&4R?}Ciwlzs4s5co(zOc}V z3E6n@0rnDsHOKMF#6rnq)u_Hd5eJFtrqg9T=aP!0BGl#X$^}wqDXUOB)r# zR*NWg@MaL_l*L>v%kabx3a_JPsjdAc_sCu>-uxZGRKxK3du)~jHChzqgjVX9ZnDDkDaS{>l{Pjm z!6D9#&RkorkfyO^B_J=@NBzL1%6Are8p*ScaSEg!51ITCP;E21i4n9cvim1^W;0BQ&LEqP_XP#I$u&wf)@sc|B)Z;+|Uykzk>dx0{i7F(nfZ znsGO@rQ|3Ao-2H?mnnlg&3J=_?C)4XZcRKP@om~eUx~hc$MrIqha26zJA#IuYa?}A z4`-%Tnve`(erC7ok#{vJ?>EJ)969N7~{Fk;vBZ;x*j>U{R=;l%SnAJ!WJ3}`Qh0|A+i9Lba^BcN~W&Y6=H;bKXe5`9oP_NEX zq+Y@HKr^(AjN>5bJLIvq>wnJ5H*-3SL2p977oF1lB`BMPNh zy+~dnP2ywZauDZVJc&H-R>|m4x09%k)hS|>kDB*;k<~3%WlBz~@j|0)GGjcPt7w|X zRJWt>X~_UEI}~lYOoAahY?G2m1ZdcS)=fl{>rW`v>>~&eX;} z!m--Z@mpIpg&7ZC9*5Q)FEBWas{L9tL{OA07!1=5R`f81+8T+8MSbgQ|9BhFs30T% zh|>NRaKlUik617&2AG^SOWU4!y|;;&L0Q%d%^6)Tzm&)cjq}e!bD^9Y_>WlIz9~>e zK)$+qEqk8m)qpR04KQn{+5&LL@N7X>^}A^8O2+IKRSCx11c*$W;8pL>9lNw`ACDBO z4iAsfxm@~?KkSTe{mrxduVtVcI_RZKCVvXy3lSQD`g&|X?oK#Ty7SI*b8x`Zsg$ZD zadu}cxmu*r+9i=U zlS8MLoQDZ1Jf5n}tV=b0*rh_2H7a}sjp5Br550&CynoDVs$t99Ug+hiGX7(|bgBZy zXnB(GP`33s5x5~It=q!n?$L1D;Oa1?{v6*y<)_OFf=6#P$B`lo;r`+UwpCXRcAJi& zUJ+(Bz{ZZu1&^n}NuTA>+qUPO>(f(Y=1mmFjgKv08DuNUf8zz~)dj8BRYg8|cIngf zgTqL&87=P`cSclS;=dapSUy>_Tzi~W6Y+|KR_xaD$zpB6FCH$Z$7uBkVhwQoEQ(0l zqxl4&V$`YTz@KIw4du}l&FRJ2I&6A8>t?-mN34PM5}qr#(I>S(dMe;dC|GOnK5nuL zx!ko`lCAJ@e}k`v*YXHY3`j6*Bi;V>kw!uzmhe`Pdk=RFnCzTZ*`|4@E;Wwsb&q06 z0zNl@RtUPdG*|9ba;M~WO4RWy>KwE^fAvl3o$(bC1Y{r=`jXI zquLs@xWF6ylpBIWBEteURCi33qInh-0Dgt|ifjsy>b~)6{omFP^#A+` zx%k9#9vip=4w&Lh;)_RbyDKgEDa=(hP3aOf!o}w2r(JetZUT$j`F9!P|I=qT7&{Hx zZGAYWdDn(|TS&E!)tL~a; zn{W%cXg_QUP6&;S9g}ozlVYKNT5k6Ej`zKrp<)ky1vyPed9hp;HYnIt9}K*HEg1=r zddPPxmxA&UgRzceOK)IKY5z$)bWCx9UQs6=I`)+;uq9G{Le6uK?xZo zdAw|(;@uCeHD<}c9s?KY9Kkx2!nqHuCt2bV3*Yvyy?FDBs=M02OQJ3Ok(PIAimCJu zAO?0x?UeBjzvyDW`@klL&16t~9Vd-}+`3pbY4pBueE7@%Nf^n*W>Y-;{<0m0tA7-l z@+F=n@kFvL^oSK1U(32U=?Eq0KF$T^1aVA3x7po+F~Z94npo4uk}yQLYWnUG0o@OB zYg{fo_4!87mL%{{u^~nliC=HCzi3ktm4}PV^hzScu_^d3ZGwy1^Ci1Nk5j;_*gZp; zjaYuTM@Xzwf0VIx43br5l3G0*BC2{cPeg*=&GMP?Tf-0W2v-72f|qH#8b#j@<%fP& z>anOk2`kvJc=DkKtZK03PV!JeNMr6o0lRh)iPD)FXeap?j*#?WuGQw~N}Sl{;YlkG z4=dw%^p3w51Bz^%px+5$;0#D@Hpm|u^}ec89n@j5qH^X#mZ@P_0)3lsehzkgm9uvgrH4S1i6-Fj7h;Vj5vj`Gc)CR z11y1I-lX54E+8mphgB#(s%=5|Lp)~C6fR8?bgr7HvbUEJeD3t4z9hZeo#eqzo&M9! z0|93Yp{MXVC;~~@A?-{Zs6=w#k;a3{33Yq_tT;4oXWXFNZt|0`jXK<`uKfi*Fb!s_ zg7+B8pm?%i(={7kqAxLAHV3p~U{m2glTpfujroy&#Tf|GcUX6gu|RwQ~BGv zM}&;KxUtIeV(?VaaFIPFSDoQpF!*c)Pz6UR6p@M^Om#I#aZYiq%CAkZXqzOj28MoZ6mrHgowHr;)dlY=~Qor#QO!JDlZ>J(wEFRTY@na!tUNJ%i zvXK*MLbY)laFr!+4;J)^Z`#0#!Ehxa>I{K1g{76R)Dy+Ht>xUoDm#ro4suwLA2HK< zqq%$Jb7pK;%aEmFG_(TXrZ@i{GY#u&lxNUX>&-QkyT}QHw&cfJaedoc>^RkVyZE>w z@*o~)OHl@ra(Xz(dcPy@z*}&fh|BJ@Ixjtkb>wX6E^2des!d$!xW}AULyeE{{8qVy z>so>Mt{LQJk{NOBLJe2M`+Joe;oLbuflV?5yl|6nVl;qZS8P2HXc$dj27ZB>-Yy;H z_w&HF#2^%kP2Gis>I0HY2Ts7{?_xQy)|o}q{&%NnVs!_)xR!W~+bVpf%`z~o<>PK+ z(en}sula@=*aW-SwQFj=7YnLlFhStO51r)(+zd?=XBYTtGS1S?QS>u z>2E;qLIFz`uWPvC@6}(`w^FurJU9%sFpxE-mIJ~uoxnekvBaTKWZx9`#5;*Ls1&5+ zXdu=4s{^hFbV;)*q0f*|BoA%KU&?YqNnY5|LhBhx)*&L8mk387_x%Yd=^_Q3v6tk~ z#W!r%PPa2{E$`(JfjBNYbc7@Xnt(BP9^k~%1Bti4p5A>!P#BKI=Z4_#`M6iM)CL)O zA|#2GOq3`iDh>VHSijuxI6lGbKv$%uPGA)|*eioG#)x2!O@q`}XZ5np`Lje&|2~e% zzNF+t=g#y<_R@yVIx5YrA6-wSc2ypOBhT;B@K=^9SFPQq6lRCepJND$-pm_G4g}3( z3CxV%E=o1k#!8g5$tmaG##L6Q?LAJ$8D`H=O0yZLUL4lfekpE}( zWX0rohWm%~k<}QI{*i+WW4MPQot3o5oWs&_US6~;b6DOsjQw9HZW_odNY^?S#&KM?8!kdi6yxziB4NuE) zaWS03{1hIX6Me^9Ut>@L5<9DzI67i>!5qf*aILGD!~$l_vHQ0V+YQ=2phWF_B@frW z!i{?J@6{TrQ_-Oy(kK0lJhF`2_Eya`CO3<;xAQe(J*?Oj-VRGlADA2(G{j5ShJCWx z=|0UT90;RUp;mc87Y^}CY~4E(wVd_KQ`vA_TrGbRbYLx?VLY^jN4VwLl3?2T^629=II~+_uSl$2BGNQa z(#%XRTb@!?h>1MpvhC)0ofZ{HVt;Bk8KfGNGLlCFyGvK0UKJlYG4a}WG*C$fPdJg! zZbI$4<>Xwr!EBpk;c{KrTa(JbTze@Ki%*z^8ILO+CBOMp+nhuRO1?}u>vUy~#ytbekJ*K)1k$INO`9lQT+)nGPduqvrYpiu z75juGZhvOU^z;;a5|ZpWfygcNC036O*%YO_LBC`$)eF~2k)PE4vNN8W4@#TRrCvJ> zYr2gxwm(6^J87)HRC;>rQr;MHx&T@@NVVwp!yYs*=h5F7(Xo|yl4fthUZ?)422f^5 zSFuiW-i-ppG30w@E(6xWD6%BuEB{03k&I995ZohLOw-A}{q^MO_2zKs@}K@@etzRG z(kfv=h3hN2ij_+okypDc2mUSO>sQlZI5yOnGd- z&^ljyc1^tOQu^Y^;5M%CL{fjIw0KJOdgE!A@1P|Mi`X)hUd6yC%>h&p+I<$ySS zzR-}X(_aDlEYw|dnrg(?thWE5(e&XB+u}J!)!pipryMY zVouh(p`U9jeD5~#hiSSi>n01m9c}>>&o|}{-l3oCcPJmz9Ou6~xaZSpcy%n{)4=;N zwNwW>Z4o{}+R;qqr|iDkOpWjq3))z7^3HKe>9$fIy?+mAdNr+YS7LX*gWsS;rZlRh zJ^2X_kBUC-X{QN}fmoH8UXOA6XvV-xFSnJvL+g;GFr+bWQQJKw$dn_JquASI!dvT_ zYG3AY{$awt@^S9GJy=sG+o#~6}v;B5Y^Vz;1?!DV`H9Bu2h zbne>pdFalZ>Csmyn-MsZxEg)Y4QRg*Aoo{wUToHH!pDu^?qbvY`0A>I1RpSs=AuoK zoIll7SYY^Ae0-kuNQMV+dBwEYIXA7T&XF}5khWEikCikKAa8WQ?)Vu)R!N8uuG?3W zNtm(@FSAtj>5Q~(ts}_t31^DJ;#5LFd%#q^w>A^NtH;kDjv~3IulEm2BqY0nLko~e&@=Db=k|VP>UZ~^v z5Dn#67m_lus(LDyIXzdlFbQ?Xe?ib0iJk;2xXH#Q(?w!^>tsD z>W~S>i}`Tl2%aDyvW}WWo~j^B#t^7^F!fyr>K=yB{Kx{`IoOL2+n_}NW-1@a3Nk$S z12bJ>nz0!VbSch%`9O6Dk%y6s#E=3#KWPa4R`qqzPjD?PuKBt%YPw{?lLBdC*n1OM zSkjY4FGNk0^O4x=)V_{iQ!Xd0t(*F#meur;P3Oe+ns=uBnryV(oBVt}1xdVO_^RCd z%_E_z(OjEx8|EVGbKJ@W`40G20A*EjsaK#*u){dftRY~obx4pUXOfMe9fY|Vp~)C} zFTg6eA2QX^z^?;=GGiU)ccm!2$h=tFS8VVQx_Z$Y&Gp-`7nl>H=@78(U1F)L&9SyN z!wgcY&i<0y@*+$;8sGYIClJH>5L5BBsHk$pom&mbTq3JE?30r) z{lrxcD>ruaw(Uv`7tUsa#(y(!Rr#KH&(iCu)7{MBn2iP^e^~{Q$5$7JM(01fL=%Nb zWu9J(t6kN?!=yzb@dEY&bEG@nnh8(!D;Tcr#82ZD4ixdTQ-K=4S{y&Eu5_T7HmE)> z)@1fppbVBq5W9#)eVW&q7DK$TH!m4Y*%ykBJZ}1p=l>f|Q@pK-iKgS$ojJ-;lJ6F@ z-52lA&gcpPa!|rYihaiy>PUi6cjnR~Tx<(d!Lv__9X6X57g|I%yAg4xfXu25d>i3W z%GC(_HpT+9>im9ud!;=3c5aHm+2<}4k+zdnZ)kXC#n}n2dj7I1bQj}$w0Y4gOxw`v zol|b+sAgd&N#1Q?6y#bl6?VSH%A3^0FAw`x1^MxsxVNA=s7A+O#bd@vJd@n%CMJ~ zo+7;B-C%Ztpo~@qe6tb2Di~4r6?6gW6cxNH&A}#*#@oCd$YZT0fF=3737Em})9NOU z966P6(TlgIM-|w(+tOt(0ECuz!UIOQyi{bY1julgyEkS0eY3jPcd7uF@4*C!o#Sx# zeo<#O_&GC0b$}&co1k5Mwa|RAYoS*I5n?JPu)KAP)E;*L1k>;aw&7nRGl1aq|EKS- z94$!7Jq5X5*}wGM@GJq+Rh>UKi*Nj#_mf4oci|p`;#_{>N8FA)9kJiJ)yJ*P4)(WI zH>7}?c-;Rz^cA&Wp)u5|Evv-aLarj|s`BHU8Cx%`oURQ-R4NLNoo?0KqtDkZT_p3f zv+`$mC^jLr@l5-vMSBE3vlx^Z4#yM+@gK8x%4imQ1MzS}=gJuMDYMNSqc zq|Gr8?ECvsZt8Ufye~a3mS5fJQ+6{}aSsV}peufNM}lzcpust74)I`?GhDpff#-f- z-qi&L^kKTe0$S_{fGReC1_O{4HES+bG|}6F9VduSd%ttxHst`h4c5MUS0!_Tosp+d zv{yD!k`K6F`2#|>e1o_XgMBRqexmjB+~i4-6ZtO+FI@T7(t8TS(&9c7rhd}BQS2w= z3R23JuczAT`L@O&y<<#ro-*XRiTjwPY;J|_D?*t!Tu!Cw8`!SJ*=uWOMoQHjO~F^< zg4Hdxd8J%}1KMX`_IntfHCw?#!}d9elPgAZeJ-FLx z2#N1lJE+A0dU`kV!cy173pWnE9}4=mO3V{w*c~dIApIJ`j;&aZ<;(`;aA2#4c)38> zU)$w%UZiKOuy!w)1Cm%&#FcL7U+|dg;yXRBNd!e<(z-7l$|u?>YEQqeE_7&NE2YEv zaX-Hs`38;ynS8Y-*x0nq=^EZhqw2c9FBdMMHaode{UM|*sD$@79v3aTdv2^YajVnZ zXo*RP4{qFh+zn)}ph1zB|Aa38(QWQ-m00Iy$_Ju7Mgl3rNAL~f%>;jJh6Q=oLQps8 z(8R&`-q+RavT&{gQa@0O6%_}#$jE9wqbxnWsxI{S0Vg+;^t@K(f8*}0-1If$ba&@~kz++{gU~ z+{gEa9ot~AI?vbZ`FuPdk>48ooik3IXh)4Tj@#CB3cy1xhxDmeC?1IZ=)C8uH{~G% z7@?J@G+eWUVkA;Mno=EN5U(X`ew`K0fI`>CT!b&eXY)_tc{NSOhX9N&Jy0VS5wi0& zgRqI`DkkD+p`m&X)nk_O^G2H+WXaL-DQIeGDyiFd8pasYxhw3O_}m*S0|J4*0btql zgBrO!$LgS;N!VHZ&9^Y$_WGQ@cL^cn55YSDyP^dvoUTXgKl7?H`8X}&R9MsE$5LJc zJcWOsdc?^XtBLKb5AK?^S8DRhsR8GLZ^P7bU+r3r?>-@R*A9yDbxOo$zbI0lE#~- z4prYcHu9>1RMcgQoKw)DxQk7^Ih)u>L8-9rb%!FVA@wtlGHAg!s>B08LnYf~C;@0d zjkn2$8eho^pQbG=_s)8H{?rqUzRy+7Uv&0-c9L+nTx%N`kp+9KZK%dUM!^$l&9uP* z+i6!sg>l{~o|m!AerYKPx0Qk)rX%z6*KuXK1dmw~@tNph_+$^|RkrThUUVqWtr6MR zv=o<$rAkheT)|Nqek8}Ki(h;lzO%va8zIZz6vLklyoLJPAL4!H3n8unEKvi#!dO3% z4u`wocMBE*ImOpf=ZE9>_(2EyyBEA5+20yE&o%R2 z%e)(bj88Y9bo?Eq1bZyz*7bBjRy7NgI|1^A{_m4I=-O;WxfVBsbVYT3Q@fsBY%G_>dEjxS4vbHSy@pEewz0DuSi*H7@IpM0e zp|8tvWigXndS~UnV#7WP@8gfq1&2PN)|kWB-*ldrMwt55j1v?9UxXirpZ@#g$_A$X zP|)ByzHRelvqVXO$Tu!6Ut+!sYGkzO|Fn=k!n5-0`U>rvb10;>o^xI*5jaNp0hR$> zTlLuj|GKaw&^SqPaT&|hM3*+Uk0Y-w57_JJmL8W}uYyFJ zVdAPEL&UP<84*VelTQOM#D-0tT#~cTC1y#k;ZiP&+o(Q99)u+<8atea8>F}#%UFbO z;z9XlCbkixIZwz9_I&uWkruFb(3!H9y5LL*KRn7!(Oy$)-(B&wilFavsvuGTw~Ds2 z?hg*s+|DreMTu{+i-#G;h!bsB5cuF&VV1vJ`T4ItwpHoQh=5P-~X}JBVC}8qEEy{1%Y4d75vVo4v9h zni^3rX<%iD(AWNIcbbHFBkTQT?dYbxKI(Pg2#Hdax<5vXgd@N7RTS~(T7MTKF)KI4 zy;3C)I3x1LK72pCw{|SIw);;9VP{PLzBJEeTbT5!gb0=QIBYDwV(7?zA}zi8@06MR zZ87T6yDcyA6Iy(Sy*68j<5TZ6D+Vf-siE6R69+*Ez9Q5YV@siv32nxFegBE0Zs{H zT`(OGKDs{WB1Fq@r6N)Kr>ix^Bbp+96Yy-1KI>Ah{m%f>VL=gHAZth|E)6dtD>@k~c*!NQ$&MH6paLhWM3t ztfCVh=IQ*f)RRoG%q#W~?0V5XA?e$t&F#V5_2T~Lf>zF7Wuw9F*Py+K-Xb$oCTJCr z&QXDMVcq%&&DOs_9Nkey0mKgyGRBv~6A?-pmG0NlFk=*qwv8S)Vux5hVm~5Pa*RvT zocAwv-jfE$R=Te))GZSGb77$EowYHo^}_Y&c4D`g=^lC$%Q1xpKMD_Rv-E;(y_uZ4 z&>gB2q3H&{pqW}V`QMUZVaTj8JlIEC>@j-d)lj!(3LC?xNPaimWJpZgWd7XJ0S+Yd z-Moy7K3xnxbmlY-YJpQXKOzigJZi4N`jxymR_8t-&&layaGB|T*?&3x;tj9*-dUIL zRSdEpI-NuyF)zYeugtc=AGgm`r`-7>Ek_5>F+RJ(QJe;ihYjqF<208SAKC@-4s)MI zJ<_Nd7jEco|7AMU%_Kp2enWqKISRI~X2~%>7qEc`KVorSWHN zm~Sc2kMA1=tg$G}&6Y0-z84&FP6OdFf9jFb@V3o16tTY$<(G9;w|i#d;FIA9K)mL^ z((Hse2uCg3`CE-wWjhI}jKGJuA=Wd>+_HHtcm=DVn2MkDXQ%~t{eOsTyT+1U0X6HL zlU>%)_YP>w%dbD=uwF%!nsQqqJ~3$ORX*%1S(?RSb**D9=1#`E8;+NohZ=AJvvlZ_ zz_AR@qz>o<2Wc6rWW=cM+XqODiLxBa(F|Dfq zX=Hd>Hjak~`j7ILSA+ME15fel!&o}p%U{yO%Le#IOY5o0u$RGo1kL=wC zN{HfU#8@Cb7XAVowZwNH5G{({EiyFyB{;3zUx-O#SXX8tMF0VY$>WuSQ3S@T9AVQ( zzkikFwF*~PeA2gF@q>A@n7pQ}`BQGWPGnPdTAWFWjXP*f>8Fc|w=noaOTS;AQ5X;v zz_Lt1XGf5#T(l*qDqhPNk2$zTC^}eZI6SSR=F&gKUqM)?!Zwm5M@NrN1n?5efNQFm zeV|AUCSX54-&=9tGZw(krHm#mdx|r_gpK0;2S*QHXwRaB>}$bVi|jE(t43+_e93g_Ek4%%Vw zq~74Fb7`AoeO%$BkD#`A=SkEu16Fs1>&J$~yP8X3E8qRE!Jz)hJ^+?u3KofpFmjI! z$@&$pis&K=nW@7YgF^y%^)J(80I!9K&li!C=Tj--@Lk{lCAzfIwFKnwh5WLg62rMR zV)FiuNM%qylQ9s(BY;>Selo+&w7RxMp3(!8#Brnr47;62_ zZGs{bb_{@O=$!oDy~h79uXEqbvRI!`;$R#eoW2jjzvQlrc@fi9KV@wVK5Z%Fv3`1y zUY?8|8^=ybUT>1p|ClhGPCKA8e0KHXFGBR{U%-&2iPFZ)zQz0k+x#>tC%f+)L~t7`FSc%uR~Cf5owN&R<|8d_K3`%wjKkkP~5W!1CzJHCx?s z1HV<=Wa_Yjw{Btm$cF8a{n%OD2Jbd*{48;~#4$VKDs3IId@Ol7vfOTQ>b@7=SZsDeIjjt*Sv(YE-?ASV){7AV8y3LI0zcn9A?zSm55X#HQ!- zEmqaQbCphuobg&t7Y=!!z}sn=D_lWYH3o%!XnJl1g|U-e=oh1R?ROCwi*xzrIKAMR zv(!Sxn~epo*zVuIjgIIN=M76)?yQIol6MjLZB%;K$Hj0*cqjL`R*dH7c6up>IS1bE zmjwBGSh$4<+Qxa$NKi`h|JGi}R3LJuTZmzcaV1%6=@LNYm7SLykYgjwZdTX5hYXtl zK2LzTRP}y|MN^HpwP|--CZ?3aV0e9apWk&@pjR0@Xf$wH|C1?1!A%x~5lgL}KsN_| zd48}Lu$vvH5Goq`XG}9L;HHrm&1}SHw1wR>=g&gw{gsh{BTii*#sI{JhSQ@ z$&Tx=?48WeT8sSPEo1+!Sjf_JGJ8Dx$YQR#<*;cEmw8wMrNF+EtKLAnvFiXw4@KR1 z&S7r6)0ulCH{16U#`xJ?(`QDe2CYCU0*xNum#X;O+0R+xwcniK^)fK~TF@ims1nGA zXAAV)rQ=Qd*U0+U9K|Ys7pi|V=5ovHPmobMr;V=4Xhlgm-zFLQxiW_sHUx;hw{68L%K<;Ye2sjrc727qT& z`oSeJ^N_9uPD~{l=EPkl|FosD?53*>O*CW$cJd}ONWlA~aN_*w{PwvA{L`_lpTOWR z35R9&L6Kqi(*Us07U&^fW7J)yC*OYJEE>EX%Fsy1A({`zT3@M4XmCeZnxXR z$<-`v;nz;@fZhijDbw8kiXL@)HM3bcX%bPcF|Y2sc<6X^gZQR!qF)x zG2*ahV{p(V%^@;j{Kk*QgvEsuJo)v@Ri`hGsaK5ei}i<@7vQ4ck%}B_{0drroiLi3 zF>zS<57ASz-%da6^la|i>6JbBhv>~maEaY3J=w=1a)j>d4J@DgY`2wegHoVtgRv#; zQ#j;8kr?2|DRRN|uy2(Sb~C!fEo0Aw#2rfR5ApYsiTr>Yd~*9#dC2;jijn=HRB&GH4V zrkGg??%E%eLmQS;qrr58(Fl|^GkgVfb%uu^%A&K^E${iUzERy_e##1IxKE$UQ>k{$Yf zP(nZWaWdch4_EDw$2unIlY__87-`<=Z*bCxF?gm?o{M8I5=0am8Qy}WXPk5PPVDuk zLDb$xN?qKJaf#_|YOH1$+c94l2$Uj(A%ZS7BuO;J=I$$Z`D<5CezpbNAC%?(Yd&%F zihOH&r}|*3x)aC5HO$o)8|hdqS#fLA_+=x4O*%2&@X)u&*{*ac4udFDylGZr@c+ zL4hjy>3==-zjj05J~4umRcm@S!)20cd#F1eh)J4@yr#Xw)wf%57=X#>K~Js!l!n*a zuiz-7feNxj@$Y&hs@z^y&foj%2|;ADzB8UJ)|thcG^&?>UuJihD<0Dtcr*;0ZRWV} zFYnpxv3kO4kC}rKS!*W6OMEx+wEO{*1{M9THcajMayr!j@FM3EK%RLw(d!PX;Eb{* zqg;f7(r~J|#mI~CRlx04le4lFyHm1Z`R`B8E(cCUz8KbdQVpQxJ0`uzBAiZiZii|g z69S6JRhaDVb)#8oo&nNj2P)}-qQ5v(EV;GKW&Z#HGazPrk`;an0t;}lUPf=mJ!T{k zpxOmU2BT)9k6%J&m|Nf6=^BVe$(uEzlopK8d!?ep0;`x;ivzO;=N%)OaFk zt9#};X*nzcixFIX3+8mej??v4U=$L6EDDFx8e^?iPfN@iqZOVH&Zqzu=9}?ffnMy! zO}7PMPg7YckVp3Bk;u?EnHxkhBb}A2J<~@vD}IVXs(|PC?DH>YuTrq2iiP*P=gfkV zhq|F;keu17g`Z9jPkHa25yu*!6O8vPEV}A$!S{&x{l0tIP;;({|A(lv z++Sn1sv+jgGiIb3Pl?)klxYb5Q9Rksn+JUPeb^)eR9UmZvJ)H6kD|AX3snwNHb9?o z-@BOrMy>aQXH4LnV^x@JijOYD?SAEqtx19pMmh)RZ<~C|%P)&- zoTi!)&QBUY8#XYo?Dv8!{PYc-2dIkUuN~zt{X@igkf$YLu}=2hQ!)EpUHnk{ShgV_ z1JaR97uZx|xc4Z1%Q|%9^~+)oOk06LN#kAB6!kY4D_-kq$M76jiJ{rRy1Zm#dgz_O zk%z_IFA|j-)Ce`=Cz8p z(EyRXaLzx>^4oVic&L7~ca`{WUz!F^JO&Y+JRTADVQ#{7oG9&`ZIV{oDm{7)KB3wV zD9XJmZWcGi-@vN6lx`;$xfPqLSBolYeqV|GEo(`>{DPHy6G$j3hS7CJOUro`?C9&$ zl_CS4C;EL!b?fe`lg<1=g#(i~FP>#5@;$<{?j;?AkML)*D3%^V1D})e5<~%TaY@>+ zH*PENJ}_>as4D6~+SGmPbMcVckF#NC&pZy_dmAd{Jt6*$nWIH_+fbH%7^+m|k#Mg1 zl(e^rdZzj@D*uP+5U7KiEge=#J1_C_bC-~xW!l@$8`mxJjvhJJR(|NqRuA;SZ8rN%QEEZ@GdRH$?%K&Cafprm*{mAOAvWr2nEc zx8BF<8nTo~uoR9cy@&?4FHlrZ-tQ**v`7Ao7+K*vsd_0w7+c`K`i3_=vv@X!=aNot z9$JfEd+XbGSDNKAnw&o%QF*st+6LL>0e8upH!wFBkACa&L>48#ZN_93@>4I><1ygf zb~<-~AH5w`qIRi(TD|fDyAvMcwGJ0MA-4>$nXNOQ?CDHLP8p=tWlvoBbY14?c43E` zXS!E;RjBFAt}k%Mcg=?byM^{M>icXldEe86BgUAnC~l$b@l>lkEGyK(C&-7kVz7X0 zduN`G%H7U&mfAhJ?k6Wt!ttq$pAsMX!l=uz3+5jZNq}1wS7bi9_d5+H{3|M#65o^e za;e0=GvV(pO#0fzz+(Tw4a)L;w1lJXIq$1#>9{CL{XtMAbvqBF70`h+a^)HIE2LFF zQhnC&s9cffgYxbCyIm8_FD4SeFp)=FzFa-cjQH24FXtZBcIG{ttpI{WiqK}McEyI! zYio0z?f(#wJHuI&>nqt+c1##yN8nE1?8OIQTR7d0d2ozdp{m0zaz*LE=K|;uP1J9mWeeNx^0~Q`O}!fPG!)S7Ch`|^Gs{_?RYcGmf+4!y+QOpM6kLz?T`mA za}_NDZjD~(XGS|syYf|8omb5F=yT^8UL{=E2V7xhJ5>*3mexxn@+9b*)+>G0J|P!q zUH~Qlp8!Z6u!R^-k{e#CWT>UjcG8!D{T25nt(>>ti+R{h>kgBiwc|&Do=Ep96*0m2 zUccT;T{rn0DI#{~Sk)8Qk1RZrWqB~qP{Gnd1-oKO=b{?Iwcz#_7y5tYPyWf5l2}Lh zXXxW+lU4VvqdR6b(!akG-s=K-=;kj@Sh4^Iwu^PY4$@&f0}>2IAG`X*`*$cQ>JFjzL5M0TiaA zB>foCCZ}a5@*T;hVJ3xd6hhZs8i+&i>bF;oJXWEVA`^%e@e?HRmdm{od5!r1w_DC+ zjV#W3GC}-AzF%)Tgyk0LYWjJc>{xyV;9)o8lT&~nhCc83(#+U}tVZN?FtIAkrnYHk1V+MxFBGQ~jwD5VC~%1bs{!_83m{0g`F@4&bAU5 z4pYg5`_Fo$&mTUySPR%Bshfihr;CW!sdMs3;hXj6(Z^dp-*#M86w}h;^)4>V`V>%o z1zQWG*e^NW%g84c#zm@^%vn3FxJQ(So4NW!xK9f1W!>>?*y(qWgXi7&-A(XaY}SGD zP~a21>KLD5jtiS`iQu~VgL_e7_M*RA`T!8USXm=cCALB(LI=m)lG7u%(o`ZoY z@4asF=qdF)9iqs*S>B$8*)|+&l~c*#vX3*~bWVIpkgP!=Pn&k`L1wtxYRHNnSBz!w$Zjv$ z6{Ay@U-L29aq<@i{PAY1Gkcsf6V~JaoHMt&v^uocwK5w5kbsrhW}$A0m`=m+fn`H^ zI=a+S!jMIr1(<3Z1cES+0R{HsMZFP6y`$b`FC}J7rUiw3#vK_haLY_*L&^3d6Yn5J zQ*w+WYZT9f+9l%lI=r*)f;HYrHDFUo+Ui{uYA!(G@ObrR28!7TcJuwIXlr)Y=j=1k zyzKn$h}_k(!G+Um{OC-xC{pF{b|*cGg4;K+r1@NRive&~nEHq4{@JdPVxFSwSlj8x zJWShfX8IVca9?%RF>K{+p#sxCaaOYzB`%;U{m-asS@x=MhK`)s zXDAaq`nU`r8+`y^=t&gek1Wv02g8?nW9z}Zu$A*T-}KG(LHrG#01@b!f4RUe&}*!3 z!z-=hGL_+Nfi}6r3RK7JV>i`o94C`BT7Cd(8dASB9g!g{N&kX()@V#3cQ5=JK|HtW zZGhZi4dn5em)6G+dUI%2H2iz%&M*H5urnyx%$j+2e;5Y5Y&?#WCCRL4Yn6p&P` ziKy@cL$1pI`0WA3>Hk%$`~UjSp9{@4iRvG%TAxtGjR=XZbjen2SPBfciqM<>616R? zCN~o8VGUX+(YGQgY!cDr`TK_FuK#Cz9j*F#^|D`RTX#`Y^IRvh#8tOr2$8*3db5{H zqUtWii>x^M0wXKhKae;2)Mq8PpV7?Ek#PdK2p_l>d3Qa}Hj?vt>P4aQ+9sqefW>fL zUNsxbn0}a<*&s;WbR5MmYzx4k|N2~?m(J>@mfo@((;^OS9?L_0O=j2|ydz0cWITh; z3CVaJdOZ6ze2&7+K;(j4Ho-__oo;j^$<*n}m+6^uZSRPeIY3WK`-?XG$0LGKQg_!> zPuaOV5ChiKu`P;RzwKSVDj~PPz5O(u_mQip(os$dgpC$NUtRE?97{DQCpFv6NKSE_ z>y7AC`5O*atHEcztep?hL+WL4J`8g6v^_EZ9AS1AdF-IAlWEW#x3e4}#dO<>@k8Oa z4NDdwfj)sA;h95vhxrUu2SCL2U$gW7K1_y2PW#e%Iy)CByuV|xzWQF~0gn;(@$If9 zV_vt1Cex>d8e%BywCqIR$NdtNa(wDbVLu}FobDTtYsjDPh-PlC zu?0Y{#k?jp1tOpQGDKhYoP$#e+hv^ZWq>^ttDNV+ruzJLa;?L|N8QlZJ9v5F``g;I zL*nKkP(8F+fC0*5OBv{SnE!(h{TnCxKdwckg$fyEv5K4b-+0!P?ZFz5+(`K$r{=|+ zwx<%#qGDruu>mBC0HkOH#PBZjyp1y?e{gFBHgHh7fZI1*JdpS!bKBgMFS3fUfH8&1 zcoUvyZjx@rK9oqQ4_ywLp(hM`ksM?Kp+>pZ5etWOVMtR%<)DjO?=rtGsb2QE|oz4tjp4Wamc11jd>Iu z87YVF@K3Z_9x(B^5aNtAEiU)&FRjio{CJ}yd zvkizQ1YMBe`3|9Ib_`^BS#J3Nw2O1McYSKS>5V!FeFlGhMSc}SkoKNkJ#TAL)x~t? zr&R4{=F@ZeB+fHC@%1W6RTJIq^XLdvO2c|ZE%(Bq3ASUo>GcJ$tWjNTrfKYoC6u0K zW)RwqqnA^g$%gK&5fUaQd6pM1?oyo7)u-TVnEoO1ZK6PxU~W?CGFocV1)%x}Rang{ z*r)p*tO&;GPwML39)uF|%(nC+Pla7WrH+S=D>rAi<5Mv3$VK`RS^C+l6r%c2lygJe zeCqmV&}ux6{Pb8c2Q%Acls=r^DCgqz=auJgOF8rhaC%^Df^&$!$1~k&_VGpNt9lUl zJLWMoVeITt<3^2YUTOZ-{j!OY1Ly1uEx1R+6`5Jwt1qfjoP0$L`kkO#z+^GXNppf_ zL|P7Xmc|{$K5Ox!ytObV`8zr7iyIlIC)9ZM1v=YT=Ygzcw%^`y)RIr($YDXWtp;-< z9%^!xxa^tBe~6R{CW8i!@E&{)>Uo^T1%@Kn^uz*WNVJ^ePV5gh)i7~g;({K6#}P#* zXomT+eP%D?{-F+%L^zZ_-B6tga&QMwgCH_f3((;+*d|Ptn(xHXqB_~FAp6L5ea=aG zMK7_MD(~}_L5gW?P)Dp;SNgE1!J}?=*0q3Ze{HJBmipOlrIlR-`{dko&*&>z^ja@J zl?4m0@Hq@B-9q1NtVcok`p=MI@Y`yYo<}>yH|V|Y$n^=FTEM0&XX({==gli?qVIHB zX@DjBKD~5_zI{}}F?&@!378_7n5;`Q;Xq$?(spW|)Ag|hR#A-)P9u(K9yXD4c1El? zfK`+BQc4QvrcFQ@z=YQL?p|+zOwm2)7_;AQgr90=r9ly4Un4{{x;@CmBfnGl+bZkA z#7<_OlMwB1j$<}z{Rkhy1k?12UA4H4i9x4KVHd~kjan0ebw29{cZSK1#rsug%XR|K zm?K~IH>%`VX6vVx8p$CEprz zUz9tanHs8`ZMYB<79AG;Q`GZRj+LUfad(*-{Ur0D^qU!xg>NZtJ@h@qtRbD$ar7)B zOz&_?BGNJj zdb#Ujhs_bVixjOhm%L}<^G(rnon?XpH$rK3_VpAyDXL)Gbm;w}{AAuzI{iD8Olc%t zH6vmSpv{zp5n&00^Wn?@U;WPx%di|%fGX>`lW=Ky@i!zzS#cAB#= z7baT!2Miy590-u%7`#UEy&mHdY%$xM%5^G}_KfyY*8`T`G%Ds5fM-bUtH!KKs>qfD;Xt69kK(& z_n1p^&@tw!>-&Y%RVO}wYH{AFw@Io8vd_1!6c0M5KFT39t$?=};Y$#F*wq)v#p0Y# z=;#)l^F-~jCR@C%%4Q$&(MmDBIDIh(e2F>rj7HMuwQQQ+;p#Lpg6tonc=%cNKSbtT zIe;VL{tF0bFCG^cv%BZ_c!7)ezlS0=hvU~92^)Hw10 zsK@4h00VZSQm@Xh`(>XX`zkR2;jk#Hc=5sSv#7^wmd_M1SUSjC37{)7@$n7*l@Z6L zGzP~Fc>JN+AR4z$d82KbN5jggrRN6=&Ml`}TU4kmkfW@b~+xo}4AmpGB+m zWEX$=SLrqt)=^*86h2+DO7C%5*di)Z?x!b1m2Iz1z3$n(s#fxatu}GFua8B!tH3fP zI-E=3q4AswOtA0K`&b{cZ6i%ALQ6gq>{Y=b68}2;*3D2wAKFg4$P*cAEyEW{A5}hHBRN9}awo23KzKUJQq4PZNa>dsWS~h$hwwpz{{PP z&d!yUGlQjya8aM^?;pZHxEf>#gimmynd2JDE{HF+1BX-cx(+}lZ=S_1w&MI_$dkh-H zk0(K>KZ;~vPW*Cke5JBI)?#-7gsz@lM;iH#>Sa{!-}o|<7yZL1`T0k4PVXI>opyK9 z49N&hDGrg=2-49R+$Hs1&4mo@_&MuZ5ddW+i@j z_dE zT?S0dhXWZX^6Am{g|aG12YlEV`|b7DMa(+AoUp{#TVGxZnUw1*ecClr-Kq~xEU$m9 zakVw5c|{i3PWZh@16V%teXLgs!#|^}x7rN*VZc`zQQ+T$@O&28@JkF)Wjx!!akFNfBR36s`rjKcWGFwm zFS$m7U;OOsW?&yp{^xm*=P2$1l)Cwy+}<@}G!YG|bSMxz`~fmT3Ztd2&o^;Oavjpu z)}JPEue%4DQ5`|hQKa?YcIeIBVj=s9gZBa9b?hhcC&-eb9=KghNI6~|>%r|Qa8ch0 z)aI~Cv!l1>t4w=MGA*UH2L;0~O%fj2e3-JQrgLbWGkP=BD=El?z=iL+1AcNw!K7LH zcS`je___go_S2@C3&Ws>#YM$wy%Cm)^#)A z7-JA4uQ$uQXLb%&&RcoB+9a)iR2LP#sz!?RJ{H}rQ;j4?ajd4fnJFwor^#nq&n#&C zwPo6T)F?kXw41lxH+V>s_MpSup9hnXFLiL1oB7Kqs8;tO+sm>7^!!kWpP%;y5vsaZVRN>D|UJYNhB1ZBjb9R!zhw=VW zVw1{QE8y?^pmus%kkRq$WG(?bffZF${6n;nXi5{-^`0bzneS}*A>A&5^P0)-pkEi z9ZE7?$#At2?)krM!fKbwlq@BhlCP-McxE#Wi#os4@a5l^T4@fi;;?paYGP!ofle;@ zkJD8N);G6SS1t_V@cR9i;lI%SjCs@8=F9e?jphO`$Hd|hSzQ+GulGHB)+REN3ubmD z1DZ~wT1^e-p2R&zNa$$~g;ziY(|)>F%I4(%8Q2}aSDTS1(zOe}gMYfh_;Q1ADPI$Z zTUJi==uKp`bRk;Gbmc;3rP)Y29(q!4w`Nt2UqNKXn#r~&ef5J+V19YkLzVPD-QOn@ zr)CN2y9KDQ2c@NqVDch>uf|@36RUS%Hnj1%_;~x$DpBI@WiHFO%R&PQ7u4ao2wG+h ziB0yS=>Xg8*EqGE$hwr(k2TX^A9YFg`#N-fbSO3BmV6u`&|cQPRJs(jpWzmB7MQRt zsg{uW8~SOV_d2nq#mL-djO23I6Wsb|qXQ@RT~ifH;|5#DM6riYQuvom7(!{cluF*> zUmP;#wVTp03KDi!7KV8(Yh$0VoX@IziYm>EjB>w$3Fj84HeA@EO83^HAM0ql&(G+Y zmCO?|S-t((elGJ(AHO(Uud}T>pf*K^i--$k|DkOTas!p3|3*3MoyT9AA(+%uP zFj|HCy>uUT6P_?>t0Sn~lEC2Dy|zg;w99lap77YACQ?MT$o-HImRmnPTPpt&dof=w z5LNe^=~Lt6(mzD)QuiP<-VyB?oGu8lFUqNEO^wei{JiIr`bfQRymj_nY5104+nW_5 zy1%%P1c@74c5%0&b2Ojdk~V7yfURupSupcc&PlX%eYO5t+lJDKa9q%kVX?`<+@d6{{Cs^FVp z&7xITf6>+QoZl6!W5?LIpxBY6wkBaILv$`qamq^e$0Tz?LPpn{f&y8qIw~a>7sm9) zivHggUr3|7egOO58t1@3+x(o0bgF+3O@#vut&BI4|0+uwQ1#uZX)Q5~t)7E^w4@#g zO1f+hpcFCXbSzOGH8s%7&mT=t8aBah>eSa^Lst8~3>(bBs5dQ6S^SnLS{_{JZ^qH$c0DtlFLX z!^!Kd89l7@F>cg9zJzD36;SGB$bRJ-l6|L4uKfSo$A?12xjL z?g96U6GrgY(nuLGz2dj^$zw^Z#xgs9uEAiWEZMgC;A`P2;an%}#l#(-$X^fow&>M__%nM*Ha!I>#ZC#jkX;VI}loC6@1S!?n0c(AnUX6kzvo z4TyO=p;qXj^#Mmo{l9qtR>8lokJSf>-4Tt^*0{k?#T=QTbk?^IERqv2)cV^Z}_lTV%mS;9GkDfIR(|G>9s**uE&Yt&`6B zvgk^Ux2TXUl|1mIwJ!<~ zN@(XJq!{AtDm9_0)oc5M9Kg$c@!yc}-`iB13s39Ce5=|V=L$XfhV<1|q70^tK3j;V zI10_{*Of9=#BZ?y53~kw(f=f&{VxaPHP5JoZ)hut8=fLtzM?-wWMm~!G5fVA=4Kwo zvb5u<3Z!%$`IGM-;L|cuI;P);=YjWECI^srZqu)FwLRPOT*8-?DxU)#&}I>&{X>-F zt}FudhNQokX$=5S{}%8I%>J@NE#nwzE7k&oysF~H@2;ug z+>MHlI&zwkrC?U0GvfWmZG3yCw87^mq z_1IV?Jc;1=@*wq!qsBi(KD0Wjm%lOzadpwBq=nTJP*GGj7TgK_#ooDit4NvfAi#oZ zmn~M(Bv49j9;ZLNcnFaZGCo9xNjoghdnq>$@1qZv>+eI28~Khqbq-tLg8~WQweJ`EiOXlES*;+JCmzsh^v z{F#H|jb=3M@&a=F79CSFstuEd+E#v=MP};G+eg~~fn(#$KvmC$(>FGeDehcYk+^;M zOJo*Efo)lP5DWco{h)Fz23cD5#s~wL<*xFCwesEE$#~Y#KJrRBg3DxSP+(bqI|K3y zX*ssv++zjIX&=z*?*OhOXRQ=Z6$8BZ3Ve`{U%Sh|zz z0bT^-3;#WPAPX1mPt*@efL)H9Tkf30pA{?{q)Q-SeX(l>RBN&M(ALSy2_5HX!8>_X23uB!_(W@%TYwz;*ZHC-&>v`zZFA z%D$~99t=WN4QP&9n=0U zP-Guh$-mXiUmreSV>h|%#J#pR+%3j;%(BC^$zNNb9y*hU9CYf*u#${w8#;1|T%fNx zM75>nRJ}YlQ)LhYJJ-#*ppRBD#ejdhyktOe4Z!@JWqmLi{}D%Q+SRG@s(QvD{zLcr z{72liEBnb0cs{m>>d_F3`X_Rx0DOM$mOX zy3qA6(+@O?7G_9K%zJufh{n|O1dUA+uMB={24OsNalz#fOOL1hxl>W)Agwz~m*MAR zTBEJL*KOJZxj!aDL}vo&k1bO+kj+xq+iiYH3PbeT>5xZeqRXe7IDJz|KHkhqk8!bG zuX8Q}+i=YIqL^gN<~cL6Z821|nPF5PGF1G`o!zfi>wpFBlZp>NF@}bTZG%$%5A6;= z#+_@0bS-gpRt?TXwBzE0C4FbNMX#tFhOPsK>|QJS?MOxw!<>zjs1>d#fHP5*vDW$8 z5-VjRQ}oGu?ndGEfSyxv$|qE+7d$qoM6OS@ry0kxdszhFV8Hl%Oj?y;B)V)m_W)C@ zii|QN8U4d8Y&@@$gfLNl0J*^Fw=q#QV`Ek+Xr^|InhLRywlld1yWJ;o#?>q!v6^)= z6jfJ~&(z*T^~2ZcG}`L()H02w`>7`qyB2vWN52((Vb})5oFmFMO7o*BpUS9v#~>-o zG5u+=>R==j&$xJ!amF(Oy4E0!AbHcLQpj%{S;GqUKHid??6VN^??p9m9@V_tYhHin zlOSM_yaia1@O5wR;Y0X02-$-&hhZbq=IRQp6Z@`-Xx1zZKyvznV29Uu;-5>>qqkX=@kv%7Ps~W)P z2L9-O{c>alIDlN%#Td3=sD8?XZ$?L)f^Tr{uL2s{`Ud_jQc0 z%!Y_L$!`?`&iNA`7yDA@ji7nq6ULp3hjatAhf$GpKWrhF z?BOW#GCMJqmzjzyCBcs<&Zlpq1bHlw(i3BpvnXF?yxNpsx50z`AG=aYTXd&!&kcwHX zNA`@_^=BV}0@jZPoNi&}%`4hdo%|J8j4r6oYGs96CM#VYxGyd=pCXsMPs@D|CsH@? zv^|r-Z*x9a z4%x&Tn^7gwhzPNc6u)?SuXdFcSSeJZs>>`n#9Ihev)eOdodqz~Au1_)$Iex0>jwMf zc~1A8yufz=LT<-#lzo};;g0!NR~ZE!pEWPK=rG>7o@<0vif;r)uDl_Cm8$~wSYdPa zPC2tEgXbpku7K0@Se0GUifFP$dHL@(A>p@&DrA#Kr71e;dLvt@ml2UZ(aou>76$Va ziZ?)==?ZUEHmL8X`ec8pM^J%37U6R1M00NN$Citay@UIF=(NSKyux+-{=8;GMmYD~ z^w>^e*3+c;p@W{ihxw{e_&`%+R~MpIM&#+$}kcc zd;7e{aSo0EkB0LV6$~==Y}7H)Hio6}%zRtdwwqC%gLZqO=B}3$!*Cj+blF7z%P9nX z?|_HgJZzn5vo3FDH*~NK?HF}==BazCE6z%&%FNzI7n*flKWs8>qHeOCKcOA+2CL3Q z`8`>0HXx)AxSw=q8CWV0IVjK&&t&Q)d~FSXP8)1*_*s{jHDj#hH~>O;sSiCJMTtfgo z==D-z=xu0HB8R|d!bGv4ZR~$WOw?h zfWX!t@8XB_HxAGxm-;6D$`jVufTg}%U=;|wE8Q?#YYcMu%B1t)A0qCqT{F}rJa9zY z`?eh9nzt{2=ZSlV~d1f52sV1b#f)1WFCwV|&MF9Dgi03AN5J&BNe=>NyZi-7ruh@_!DwLWV6 z>L%6yN8NirH5GpSq9`g#5gT2IN)tj6kPeA}fOKi0gVG^Fq<3Niq((qML5R{j(mSE| zA~p0Xy(QETLcII?-g)0Mch30(&ix@F12ZJ^?Cj@R>(dr9H}g(#A9Lpo71>A1&K6_M zWA*vPhCK#j5uLv*zaGo!v-eSt%h?xz4Z59Ul`D2(ocXbpCeeBC-T2$RU}CUae{@}C zQuzz*3prnkju`YhmsM&OJ!8B#mhW6wsa~XcVHH2Iq{#k0PbW#iclG$WTYBMmdv>y9lt9`LEL>nF<$$2wOOJY#Xs^2-T7 ziX6JW4VylR6qrEJ_Q`pe#g!l)OVeK89Pt0z6Yai??f+3kCi{dx^>L6W3qH8>Hp#m%*f(Vh`sh;0G=_q(qDDvn%);$N_U77=V_C17 zke0s=`PCVGy|I%Yt@=r7@p2`%hqO$8V5r8CNhC_#&VsNnKQ`jjYVjNyi&17!GM^|4 zgk}u{`3byj;Se2>QiywdO{X!?ZHa59OipqoY$xkA{@OthqODvxV>>QzR0*hxGiIyv zx@Hk>Eqk)q&rZm4boA8~r{sz3-8Jo6%=+q z&WM*U{iC27SmstMLKJ3}BhGw7y}kr1VI~@^I)df2tmlpfBp5w^eD05WV#fO}V-}m| zh%U2=@SKs=QXg$+^!Cq-k_BA+Au60-g>DS3nhYh%jC;SyuZi#!$lmoR$7dJWWjnrg zWDWda@$Jw=`|YK{8^^rKiyPxjpum^7<-L@)s_FJ;i%qGIZH{MtkQ4eX2qP|xZa1rc zIm;;hqZsx549aByag_Qz&9O|-`Jk36&k&zOC|4V+I%67kb^W{!4_2wHi;7X!&~o(z zK%W^AXolTyis*qE};j~RC9hV1UcLR$T!^yWzalj?*8%ikvPL>Si26LuEG0( z@U}Jvtx+^d1dnPKjvfh=A2WI}p5-Jb?MaI7sqi4#T*L#zHBZdNR6S@t6t@NR9(%^# zH2fO%f!@tZi2NViv@;pYA&5I}5@g;V6IcOlg>Unt_R?0WP4mvBNbcn3nvbn@$6X}# zHJ2(QJrLp4gG7t03GfHmbk#<-wXx}J`vwt9woBH0ndP42#Dnv~XEMlj!KxF$-V``| z{NHE+mHf&+H8e(!GuP26S1p^So^<=DYbSb1X9si5YCA5QXKa1yuFpZn%CYrALO_QtP^jX7hm2+PHCk`j=FLTs zn)f{E zwcL0T&)S*J#qZV(BIo0ELS>9*#J>woxhM7j(V0!N^rPbYCldcC>?&d)i?$bV{!!1( z&3ZYx>1u8c<$B2-IW_tEtLW2Vfd9Nz95->m)=qafj3c$}IK zqXR3@btn}EPW>foK>51P3VehAXKW;W1T3VQuSkm51k3qx7N!MZ(G+4f%KOmSM+26( zZk|m4e*c33Z6n|DNoic1UQGXGAVKH~#DG zLY3f>P$kQ&CPAtUyO8$NV>0HYI2>~Dx11Rp!XC6mc=(Pp)&%>z5b?#&)qCPBGoPO+ z`)KQ`GceBh39te`|38oH%CAaK?C*Q#Iu`K_j3)o^dFDbH8{3_gZyGptP1N7Bpz?Im zfBUwY!7~Q4mrYubxvXFvWh;Hyjpm+3BbGvE-j{V;pgG~|&?3L7V)<8&me9L1B(e%a zet^_jf~%`-{r9Xdd%!6om7AN60e{VsmR6f9?{XyqDpCID|9h$N0w@*kzPqOOlOBTI zr&}wMU0;PwViY;@v@WQAT|1XdVii-bH!fJ^=I<^BvQ_7;K zw-#I~B@TWJ+*-NFDw;l|p|h5kH~_yFrOSz}ahHwQGwVp^&$S;HG`O8+$5NcD|06LL z>Ej$Sh9*K|dF*i~eFY?AefM+hlR*6ron04~Plx4T`P< zr$IzNx^*;s3Q`tnuum;Y!8=dc83V0}5Rf-PwhLfQjfsm`o#{kOkI@6|>~X#XKB3Ez z6BJ&=s1t>>!7C9PwYyA|-F8=Knugn-!jsXND1j$r3sJV$$2laVQ?g3X{Md{ z5!v?=62TX}EU184T}1t4$nSQOx5a=CK;t>HdmF`gT?P* zCrhn8M7#ANjeIVjutIFz2i9c1X`kS>(tI9za%{-jV;6iDxZb8mZrE{-h& zl$|c#YmkFQE)0ES4~vb3&2j-?5AOR>$Lh>a|L6+#8Usq17gr$R?=o=F+D5C{KR-(y zQ467`*EWQYyG41qRKzK(Ue6x0@t&GQwrb=Y-DQNlr-RQ}ID4OX%sJhD=5_Zjja}1h z=|1O&8NaTP3>@~ua=D%C^HU3r-%G&>Gi?ZXX0D&{)219EHQ9aHQl_mnqs=zFqG`4c zNS!lNUOPTeop>$EZ{Q-Q(*TsAq@hsAli-#GR;1&F@d9Cg`6Nw{()FWSd1-=+OP5RO zJ|%SbKH7gN0}%4cwK)IW0^Os4d~q^?7A6n{{Yun?V7FIGPU|PkM7+7fxlY9w_3>=s zj-v*-*q0Hz*M%>t59KFU4YJR&i&njZgR4n*pvvo@+a;)9(z~s0PV7W31Sht^g*x2OzdfRUhfnWj@f%bh! z&;)&_Kw4!Ye~3Dwcf=|g`F?$@d#mJw6B)D?{LIJ=ce-K})x@%u=wr(J*$WK!)(y@;?d!S4#BI5&~2}zZ7Ov)^aqr?Z zf-Wz#!?v_RFY45oQ5Mman1@z~uoVd7;IAD^9y&<;De|ZyY4+`fDqCohob_HkvKgvG zW+OctX?pA{tbrGb7VUEgy5;`!@E*F0&0q9K#1WlXI}O71_h6x76j(SXEBJY!JRuTq zbD}dLWbFdTjx{S1-q(#(rbsi+D@x4`N>rb#BV~y6Eg0NOcB@XtQ^umDMoFEqFPBj# zVV-Ua)Nefq*cFzpFhY}`L31T6WG^$bI0+r#W7M=hH@d9(=vSc2ig;Z)3A%_j4)i4y z(SHnl=;e05UN{>T(aQrBd!Zt^GOQ|&^Aza`@?_#(jjgpA1EM0Q@H&x|n9rsyjbrNp zeQ^@$kCt?U?s+r#C=Y9=Wt;qVcpZiGH2U**%0e#k#?HQ9AM)Tx_3x}wD$?0V??VM= zrqS9$UU#4-LDy-8PM)Wn#-(7Ut4dnt#yc_-Ijl19EPIPJ?1LBf&hufNyM7)sJ)KLl zpbhvAqj+oJ3xbowN~D#Hd=-#Me(J-#)OBh#7I0G1&{LihQc0`SAOl&z(bG^xd0zCQ z>HnJJBvFEa%Gs^YXTsS4lLfMFKI{xTg1p(F2q5~7fg)na_H#8lp}4cPWl#g4>DcG% z6J7=%MzB<(!%Po5o@yaP@2g!wyBi*JWB`-vDVNsUyDJ@E)qGgp-Fy8?sURVaiCt6` zst6wIvg1$jZMf55*I?v|2TaZd?Bc&0N~VX$<*{cRQ!D$7Egs9!V4X%cy4LoeVR~Xo zoVZQPjHM#~5qW+nzs=hNS%w!1T!*MlD+xHdQu1?!Rd}*1I@ghd32!Q2@kXe!NW`{A zkLGYK4<-+d6yFL4UF6GIxc!_qcQOrrzm%9P5SzLA`IBv0)C_9d)Ou?qC-LQ)3-78A zHtQdSUVg7go8rFGyeFE*H^;d8{JH6i(L#K@UtafvD0=fM{z`J*q80UDLVPEnJgug| z>fnehe(Va!I;i?tQoE%Lo+^r04DLUEk_$}9%l5WoIkNnSV~8uWnQl_|CB7vy$e#6( zBNieZ61O{{w1{o;3nEZ0o@7-I8~()Uga}lGbY49MmUoXH^OH2-Hxv#LAz(Uhb{Sxc zvlTs7Id`Ih?zvg|mK#Kh`z7FO^0yN`0vi(}_h70|w+(U&=h5$r5v(c#dxL<8FJ6zk ztI@V_oPS{7@_F8mhU|79j$>aXWClBAY-tce80A^6C*vpBEU20v|z3J>6l7s|O zW6wVrbx5abtih#*8cow?5-sgfA=JNSdQHTg3g#p_0aqL)tj#D z`s7;$*Fx3mb&I4=!H)&^ql7Ey)HT3Xo-K@>t-H=^rQtpv%YapT+S(Q3#qR#A7jYq*y;#$a%3IP3E-CUt5$OkaOq0bE9K;^}ru zBD($L^lnhr9=HAB>noq^dOD>zDYL;_!c$!*c?2a~*pf>Xs>HW-dep#aH4X0jD$(M* z9BqE=k4y6y$tJF8%PGQpaRslF6nNzv!ULpfb2YeuEL{v)Lsq!Hjs{9Pr!kOb>lrxwrc@$8~8CK zxqwBO8-N~jpOUF_{!uK$@tqN8{hsPu4ikYzY4-zMpf0NcS8T zHB$q1ebM_)J|L2o<1}z6K7(AD^Te06BR7kpTY;@Uflwcz{@qvp3nsJ(P@y0IocRmu zkO;dq26PC03y?7`^dBT!G?BL}Jm*FS9e~qer5Btviger$N$!Mn;c42+@BTqLs?cx2 zan2EkTfSlmn5E@>VM8V&r*hiZ_SIALpU{*Q#7#H_8y!-kaY*OUf#lHN@v@yO6giTLGIxE3clNO%=>ChnU+VhmWqF9bpjg@Np) z08ph40BF5KK08Vv`1}l>g0com810~M9fva@L-%ywLh(5GC<(X^u1XVnew9TlTCiC~ zd6~_yMaJ^4q`1384wh469OZ93s_@dK!ZW62yaMKkZx|+Gn=LuSjj`hwzt5&B+$7*AQyg=%O8q5GRa2PUpc)z4}cn%;+;x#DjTYs zLhP&3z~53bztng^KbL%NUo17|bGOb@r>}^&`o6%T;*9rs4wU?E_x`JuIEr17R33-O~Y`)y11QIY~xLV#--5%Q$(Nc>zvZP^}tb6j9LxqyC6 zjZZjn2zM-JI_1e-Bu}5pm8SMt^u?g6R+m&k75Tx~uF)IG)7wHGAz$8G_(U`@%sEA_ zJEiPDpcMENy|TG&(zC>-_B#CI5ZgVyUPAX9kC_RKR|}p)=iAbX6}_&ScU8f-D@MPi zgeq(#zcgGj+{^6K4WSITN9$5fH!`d7j5!XE?>vQuiooy0x$?wZJqJ=~ z{=oVInaarQ>We|TTHb)?$Zlj#m_$Xs)U)e!{}JK59Wbbin0-9vB=HycW*E4bi1XCj zH!4)xzq&!mOs?Dz#K9J-3LX<%p`A574Uh6x6n+*BKj`K>?Da49x36o1k< zkd`8Pf|A2O3iM}SqOL)u@Xdj2v$G+7nZL9`9!BcfCNi-GV}5l`*uDD}j7PIx=r4dzd|x!zEzKymy&B7{c7WC1V3N!(Q8ZvJCzQjSlZ^Nx=7dcv7HiKg`)JmwQZS} zC1xhb{di3m$g2NLH+1n@DY+l;bNr*|!7Rq_II+LPdnI`R^G8$(qu7o_s=P12D3Tb7 zQDNgB$Yw3cUgVzSs_Kal-Oj>1$S51(oIKt*pJgZD8kjq1{6*D&#_G1yE^yf>f(#;- zo~T~YH68209lySAQEb6D-x!f_y@z{pzq9t$0uU{=u47@^Q)dB0iw7B{4V$ALWQ-ti zV#LCLw3zCN-4Wj*5-rTK(X+`eA|tQ=XKHp$FMsaeFB!TzX(tEw-);$=%8LhkUkbL? zrnrv{TG|Dj3k|J`##d)g8-;blV5Jdzmo@d=YnkQUj5+wRlwjj#Kx!y&jNAa+yhxOIqtJk$%f7_3 zcOe$s8gpF*6o~fdqt<&Jno*)o2QxcWF|7K;QwLI^u^%Bolq52J8 zMW-E41K1tkrr{1l{gJ9u&Yhecf`!J8&aU3=#gT_KS-iZxnzibce7mJuMiLH}C|6*Xs z)ece9Pf}1966*K5XCJZt;Bk5`-2eUPjz$i#Q`TtPbTo&5)L^BapRZ?%X(M;H`XUYb zWKAo>?KBT8QMmJH5FI3x>KWf2Y_~w!V@#&(IU7~7ZE4j-&uuID59<4aKnzsD+ z#z!1NBdjWTLm74T;fFJM;-ELNSrY_3|#_U zTi^1Z@-1b31}w5t^Si=NQL^o-yJ}roqt1XE`*rEP-whR9MFZt#k~2Lgs(qfe`jXU=MteT;^>LwDx$m=P9c#?L zJ1aZCH%%+jv`cXQ&X#2e%Nx!wHnpp8E@v}*JYC3XnBF&BX`+&^`ybXSnu*gnl{GKJ zU~BB2IV>+BKl#7ds_}e7=iDN_f|pmboPC`Oi}b+ymz#lC#lWkVSC;ac$N0yNonL7v zKVkLWqA*p`crixNnafdVaL4l}^@stTevjdN=5^cr5yNo)@|RalLJVS^j}iuaM~J5y z!`!vMY1T6MtowcldqjlyC<^KP`tdifqvr^)R51&pK4&Bj&f5jSMul>z1gPfCPl3D+ zqcIFl6NwtgAbdDoaxL|UWPe_{7BeDAtbZrQ#mW0_OY+iI&P0<~&A@Rjwqp5pW2hEZ zR~RQk7C({SmQ}z@WGo@?8pDZi)@BS!>omG~v?aQWYCuD0*j9&c#`a%%Rh$RSpgrU$ zLg2(#w?A%i<2(N-c!^@fD}|u@zQUS>kfq2u8Xz*Ntj_#S7;O}wr{AI%PrxCT?NFV< zp%4yyQ0RE1ex(UlxOQNkY9AL8$3zRI-m!IK72}8yg`d@Ba;v!Bg~3%1pqz0Dd{2)Y z2}$kfvLO@+oU7rov}?((p*?5~bv&@898RdA+JIA-JmAICK55tF z$A888c-pxDS#li3mOpm7tlK^|wXSr)mv^^z*&Da8b5^9xa#>5;@y#_IS(9oB=;C8| z4{=pZCsD?HFb2}-Uz%Cv0^%eO!cHya2&kppeHFsrF_@0vwab}E=?fS}Q!7yLoW|F2 zV8ye6@9XFh_Dgj}w<79K^{SO8Heql}+at(ird?0twsur-ztKF<%st2zE_A5``&2hn zM{H3sJLWvwT6pQ~&yR|iYwG}&`@AD*av^q5JN2QU?TU4gTS49jIR_>DSPXzFGWyzh z&fmde_1^oN%-?2P`QyNkR42woY=!a^%FOwtj+It!>u4B#E3;qw!=*&T9(Q^6n5jlCrESAu?-=OH~@qQsr1}5-F?b8kz;6i zb6uAU{?z4uL~#^#+3)TL$5;G~Iu|NZ58_lPr)!NqSmowsE)f?&X`z9VFJ;@9& zCzUwUe)_g&+95#~bNN{wa0}X(eD?p+U#D*N@gD`$$PM*JL_Fuj1+eVgsk6f7p--}$ zkT*XfvA>SJPCNFmY!>#pEk}!(_~#EYlfM@`pP!@a9M2L^8yS3iUvUA=c!R^y4-2dYpZ^XVXi;C%w`H_PBj zOWq`?{qRu%Qs;>p4-~&-zPrDxfWN%?EjtVDoI`kBp$)xrqa;HR33S6@Rhgh2VOh}O z^s)*txYZ8l(@gYj=U^OFz3>d{2j*Or>ui4ygs@7U2_M>CXo#S@Oy>dFTpZ*Hwn@Zy zsC}Y*dJFQXK5fKnio51jZr{c;%7{Ir9hwq-%a^dtbSvI2Q*|xx)!R|Y>r|uh1ZrYa zUrXJ!FcqJ!RbU*dPiwW^o{+~y>5fM|F-0B9oqpO(X$vSDx6__~OV6FOi z_CJBfkRTvB(UE{ucYzyMRZ#4D_r*@Ba*+)#ZCgNqy@st;A3Eudqr#!gmktzF)Yr1O(h7tL)Ezr1)|_3lfv#r;BG1mQ%Y18wF8W zK*UJ~FOzSIcU`h}i}4$q(LdwUtJ^->b?48ak_(n}{=R`qDXWR=S&HSrkJY-z>Ggxn z>Ho`PdpSTB#iI$Tn}h3>f>k<^qVk_eeWZd-(LzJ??-bw*@jwtzvmY(~?~K*|3SRlY z>2D0$WV*I~c2(2b7b;61M`}y&aemI;?51W+QWWQ3erH0g{!&zOZ=mUnb0?g%&Ddlk+b%QNqnZg=5TWe{B6rqO4ggNN z;qEu!-6$Ss>AEh}#=RS?|HHkRl*ZZpKlE{}ch}h?Ene$w< z5_Z;z?5hlGWhCcn(AH5c+r{QHa)KfN=UzmI_LN?U75T^ zW9@3g6jlF8w#gcjVAfu(f>r(YF*NW22}vAZO5y-FpxZGsuT2%Mu$C^q^+5JR<|_}2@*c2>yLeUgo+IvH!|R^WW#TR=)zutX-=R32FnY25U57+F zruv}hBpY)(2xeh24Ns2WtcrX@Ve(B_+(n4farpbV4~5^OhAp+s`2Bk5dDqjC_G9Vd zg&pQPx5%{oQ||@*Q({?Vu|If=ark2UGj?nFmy2_U|C}n}K9+(ZB|RQ!l;Lt{Zx*(V z?4%P0W|9|ZG340s*x?PCa}-Oqltk8L|3WZK3gce{N1CTNRco-xnsw)9a3yfwJGbE3 zJAsNaYh=6CKPouqy~KQ|o}HE(+?s6kW|OUxvEbA?7DK_$i2q^L_GW#nwVbK-KTM-I z2*$uqP{G$#Xb{l2JYumf-5Pp`6w;&MC4h;VA-FsvVt~fA+)K;fMfbJ|+&w^2WN^0tVSP7<4Z-_&ZW7KLPuwAs#u#I18@QnFXOCJ%-Fqup#Z3aX&6VP-zB zyz86t5(wxYEW9oSMMZ8Og zAoal)uI52fxn}zHuGOLdrCD4Q$ZOsBJo?yq5L=O=1(Ef*=PN*X6Xy;#WhT+7MJWO(C(&Ag2wP!#vI%7CZN%KNAvy~udg+_RsI+9fpRk)gP& z$0eMtnxbHS=1DP6y&Rrm<)6+#%UCeFhu#FHm-~S3WmC3YhbNt;~Zdq2^u8wgr_^4|3?tDd3YxR15 zCv?$^HZBO=eic*ib^#dTeK-C%;anr|lXB-1XO*ZKXXg`sqrr4y4jm=kQepgYsx}N ztfyImviBRus<#qJZw6@XB5dO_#DiRxEn@+y`&~p4@V)8g!IEnu{zNc-uPRv%0(bO_ z=(hD1IgeIY&&>qecBZP22c?R8PfixKM=|Ikg%WbE)-~5qrmZD1!x&modD-TcEzV*B z`At)6m>)Hf;a~@Gc2-FPSYN>*G99Yd>+ZW4_ajMMmEiYixAAY)uTL)3K9>AE-m#G) z0y-YXJ{)}2k)MaNpkE3%8w`PcdTW>y^t}WX!whYSsVzTEPGK2zfADecsFp$$~_2Sm|e| z!j;{B6N;Ch6Do1^u5^wq%PA&Ov8J3y-G$tt1sq{de|u$&tPL=jva3(5>}iM1NEL9V z{lLmb#%!#*xy=C*Aie)cRWDhd>r{*jPSea7BObgCjaU}1Axm6D1J>=cX$z%h zVo>U+$4TmAHfgc#Z{1felmnC*HeMaxx3>}sD znx1ExawypJffYo*8Au=nK`v zC!nS(ultDpXK1=qoY)rq(WWKcGX2%#J@?I)g~M1%NdPC>-OEz zVN-o15c|80GwOr<^%5W9fr3R4{{%axuM`{Bp&c4&IEfd$N$%?uyjJZ&X*@qk3Uyzo zfBms}2#Xu=Px^4oEc6ua`{0YlJ&_PKDtzvWc=J{=KS>xbd4idoKW!7cW6Ina+{J0L zM(x{`Gf^i@?VF)9h8SqSTC`Y~kjVAz4X>0mfJLGm{H}W zl;+LL?wTmPaz|yu{|S&G{xvIyf7shJ_<3W|AHq;8S-R>s;iCkmXl4lMA{W>2M}cRg zqa2lcWu2q7F+i8FxkO)985-;2M%OT7s`%$F`1gibe24E^!p}_^XuIl2pzgX*D#DFR z@0;;Mslm~-UTx_k@ohRhyv33#N_lCHqm%DeU|9=AvQ?+*zE!@xvA=k}zUM}-Ywv`2 zbe&aDu$~rHrxBUINlRv8dYJ}7ZT8eS4tC6WMok=DMD2WB*=O?= z6}0IfKN%%+6lQW)rR14%&dEJg;pVrs_`bvJ5QXjI;3JG9m-&jhHC`;$B+y##&WPo5 zg21#kxDsg1m{9Szic>MouDm$Kg~2F$6IAEYLnRuirRlkYeAKFU+@Xu)hJVeAkq9f} zEYCWtW2oxGi}#TG(~j`WZ8Y0*;vcoOH&N4yN?uX|JI{umc0*qyr^<%N5VFvBRN%IR z6CjO5;0eQ)RK&d0UeeTnGIBNNI$5=@^qVnB%C-rKqaS64+UQK_K|p};gQI~EGl_g? z3IMI8Ry!qb?Uqkt^s%dWF7Y!z<<~;A1FKa&{~4qyru=Q`AH@a-H0%tN{~uQ&Fo*TW z{#Z~_`zc-huSkm!Ocp>-w1|*tok95Z`MRo04<+j2 zijiOevW4?ikBmdR-z{&ZWMgQ4&jomKS8{nM`Y13ctb@3lE#oH>)l2nve9941In=2` zpKuOpck!ViNisovNk3TE17$mp#M{N?*~VZvunjnfIH-a4asTLCj}nFWT3ox67-x8(b8PlNJXYrz_%%b*S9BR%5D|} z<+OVce(GDMEG-bgywQRzOr|*d$UI)WcwyO0DXEWsq}C2}=dFK^3T75_b{Vt8ljD2w zj{>KI4pca20(3CL$V!sjc$P9*_Nm!BV}6%~7zltFPs?B~o|a4UKL<8jf0v@+8^_FmM`>kBY8Q0&|(>-Kzact zVxQIwMTzcu(5ChX{l;t#Mv{k`$H@#p_#%$Jg9tw5BZEjZgaKE3lq$|DJW-ciH7qzc z7&N+et>Lf(jngXmkj6QGlC1J;Y11sj2|HAQY_^>RYeFNZtR&03mh$zI(!ELgq#J3f zFl^3KfHXdYa)2{&nD!Dz0*_r%8<}Uk!od>#x-stI8DC3DV*>zPU5O8m1T0mc3gp~J zqp~>yA_{c@;7pwuoYq1#$6XV<@{yfDjmw@cJUdJX0%eH!$u~=>rNC*((DqAgCRUjI zHBO24~U9Eik_){5W< zF%vl8_JbVTsT1QQ92PkQId3c5|Of(={vr}RlGlbEAG%~(MVrWQHj zA8peDPsPs-7KF)hBgoGy-)x@jC+Z=g1Q~P{t%-7k=Q z@PQn*Ets=+U-o34v2sVd~qWPr03-GCV7=sc!b;8?G zy~xOM4qC^t3_iv5^3q-L_2db(e8SEEzeJZiO!KX~hh>;KCi?H0Am_2bLbp+pV9Yi5 zgvjL;0Cg(`R-fv)D8CKw_m3jn8HrUOMSI&V?0a5l@dY|2wdTmk(5oQUO^>6O#8SbV z56KDT`Y2e3!LfA#9uWG1-*taDj|2nPP;=%CCixMwGKf6wIw*?PAS;|gj|VUbHolT% zc~|HHsJAg0OuoAfl}f!$z84b;ByTXUQ)^}X(HnktKfv0G@zp!kl&GMqUM^0QUZG;g zy5&BCpFgk>j0vdzl=mt*PIaYw1d=HyrSnGPyQF7)>J_NxbYc#%) zv7=<&GgxrxQg_9Sm`s1a0;LmWqt|%I3e`+bCuTmL$a?f!iezE_oUhj zeGL~heH6z-dXZmkdB48={aUr*Zpn zPXUMTw8gSlCBXdBDNg){?hP`)W)ACeJjgrAD`|jKoO9UgCgsNx^o+799On#m#$fc3 zoDuBu5}gsd4_K%#ZNM=!sX^9-P64u3L*z@DBKJphOMCP}!GB^cV#2eghccT-nq&HJ z2&l?C_xbwhAkKU!H`HWxy|}e?{bfDb+La}er4s6rq4nUB;b`@`tYyzy-~$bK zMK76M+bG7Uh#g_@o%&@YP@&)R-=) z@WWx34)1PtJrIPyx*O$!Knf^M+|XFDdEvdsv3N(dret6M0&i3@4xcuvsjqCstI1cjs+2>y?2pt!JYao7EG^#oxhZ&WU#fP7Zlr zHm`$}ECKD?+kyM%H}mx>-0tmd_LXm;eS4g^$Ne&~^D9p(@b^|3s~1QYMk+x!&MnA; zcY%{WectKwsIM%{KCad6@VZ%E2&&ppzH6j`N}Ong)99FIzbMBzL}F;*vU;aIQ!%uO z@wrP$7ZWWU`EJ`*X~;Vej%_G4$u7^=!LnL{81gklt*eh8N&7jV;HI+2+t46^KI-3- z1)UW_$p|YS6|@gi7I|bfv0Cb2);8bcH5@aqRB|X32Vjt5Y27)n{SUz$1k^H5wt$>$ zmbtUOEy59dyHnm`h#HdJ6oEtTXtDn`L$Ud$v1yCGd5WG_I}%cXJ|tj`Zn`>kW8zO0cyi@7Wr#@ea)EX%{HZm+Nt8K8Cx;)Pq5B*ZoC?|8Pw{^+EgT7A*dSw>aQVn$lNt1`xui{m40(Nj zPA)?@)o5Nz6&I00(jCxekpkzM_{6^;sA>^z~gr~8>tw%?ZpBmGT7;yYY^-?4}IH|t?W|ik4uvC zR;cbUmsGe{%?Jn&Tuvv}lxu`7GVn%`(2K4V8c*I?clw%=Dxg>BxX;9bRNY{k zxF^)JIU#7_*;I8NC?PnJRG!CS5*!@%1f^dve$RjMPXjcc5a)I?A$x91?;nNt1Y`VR z^D@S{z%=!`Or>oGL%nNH;MB(9;xx34t z>%UnCBLlKyhUB;&5+!ve8UlrazS=mS(+Y{Es+~l?=(*^ra$p_HKC|Ik$WyS*Gu(>n z(aT_bMbX1car1aDC5cfz*0LT-L!!ZVMP!(`cuKqMPP*Q;jHQmwKB-myCq}X&>9yv$HynWmEj#Dz4GK}F6*i9NaKqV%TeJS)bcm1 z$kwz$*r;bDFk=Mv26$SJ0Tf9_9B4Q4>K{-)^>W6t5fzr;!4Drl_(!p+cB_;C$S#F% zuSNhefgMB>6=7S;{*JHvmZ8;hHTVHklXXp;j>=$oHjA9%W8apWc1>puyp1ziGyIOM zwayy@5Q!Dxp7Lz*yfFe7y8oRx)XT_->Q_!^$=k`~2$Yx576nY4HsPUj$n=+6YKGG} zaX+1(DR3J(mvTRAeFyF_bmcVBjU5vO1}OfCs9DbMd4}R@szP2Sd`k`0g1lAGAI^|B z+5&U7CqEuRFf1ZOI~V=FypYY?1+qEGLVvIpBetI}t#=)^FYI0##g{xCF06zyXgDpM zKW05R%X&08rMk~PWQ-mA@m5~7F>p{qq%AuOw}*BGWMZqOzl{SrNU|k>ZHIFoaJnEn zI_H)Vp{M1mZWkpvU`d_2cmUp8i6$hUpBvOExY`(9om_ke2hhbyj}zqy2>Vtd=r&2m z%`Mxx1TJ@LLsY5kg;HF7)|*q^FEz|V^59*6vfXl&J!|%B{jHeIJ))I^D>-Mmc7i_& zuW!IUI(K$VP3R+2gO{%+gD8EirNsnB`vL?kn*|(^5^+rfC4&nycg-O@7uk^3o7Tf` zetjfgG3rNL&;gNXy@@0G!tm|^=OMmgvC&8#Aj3Fdd}-oO-FU$koE~b!RuzUd}P(Sa6bNIwvx_Mv(pI zfz2j{fFi&sWnXlBj}+Nb>&YHAk#twA0mK7=k8$f!l=1^{GZyGG|H?}s$VCdCVN%zS zr8lL);``e?8AS5U{<8&Rg2M8`6|q@ICYSuF7|q8|2&aH}fVzK#%+<*wG2K``Im9hya zCuY-U;T?vXQR93fNYq-egIjjy+Zy@INXT`&&sJGZ$aF zr)aEcc9N(?Wb;R~VQ8GL(xJni)_Yq?b%9_Rii7VLk*kpKHNcpSn^K-P(-TE5_O+K)&c1o;_COPY7?x5cq{g(FoS!#oa{jrQ8Ej0V)6Cjg zTzk7B0y0Wp#r~>iy}n|g8>0JOJ3RuAdf#~b8p!{8@E@YJz|^a2YVQ*7^;y;eWdqwK zZY~4c4{IqEQPOKzz zPGY{V1D5k*W-euHEyXGoo41?ao8t|9co@Y!7$_>xkm{o+Y>YQN=hB3D^vxSQDGn>q zjN58em>|XZY3VOgYFRJ)c2xW)(gw9WxPP*Z8S#1Hby_EC=L$L=9)+6#^7X<1bWAX7 z7{qFN9lF!@o|s&zSXdRwFudVu6lW3qCowV>k*P@zReMHO{CzBpN-k>GO!SsGdE@`0 zy<7FDXys#((EEOrPkNJg9bs-c;Qi;->S{pG@b)9=&_oh?Pfph>mDs*T?})>6!wQ7+ zPaVy>iNU{;4`_nz(xkf1U9SdaxGe`+ZbQ6t{CJR!vdCx$xe;~uy+P!(bWx%?vD>_B z1awQz&*c}vea%8rw=(`^@8@9)^8-IAqCp)~r`1iR3^R>f=f_EiI~AoWQSB1a%#;&N z&If2Gm*@&FspXQ*V7Bqfj=7votYlL@4|4 zb=--X$Op!o^f`LqB=m|hP}Jm&<{(dh2otb;a2%=wYdn)a2*gaJh3KCpr#8_OVpyU) z+OFJ`3H=6IO5&8`#mGT!vz0U=E(8%bzkeoUs{yphT)bznzy)TnJh9a_ zI1`Biy$us2({AaI>xk3Br%I9pLqae$>dYk{*fMJ{?by_TucJHU6T9XOJNfP*~^( zCsaW%G8^ptt?(v?ND^;*abc{s=Zb?(XZ8eQ4?1Bv3q2pHCXB1Z{vh=mpC_Mg1cM0v z^!3@#yDrMi&XWIxwfP%1$u&xhBX{E_Kr;rMIDO;?-tF6Foa@}t3;#u2rcIQCA64jq zq14o0bViyIV8{Y_K^^HKBy#;E9?TlP<5sx`>_i{= zMv;2l%cyuME?jinv1s);hBz)mZ~%xy8*~BdSbCGa@s2@tF8MHiTI*OEd3UpF0;c=) zR-tXv4R(Ll@nM%&@fuYg00rpYq2gQ}iIs5%sZkw>+q8-LCCfo~{sw0^%2e{oRo!*> zSqlo%vYp9HB_?aI3eOq-Kg7LfSW|1;Es9G43mO3dDH4?`5sMaO*#?jHPWSbLNB5Bgc?GUwdeZ2{k{8K`}{xWN5XXx2+Wx|pXa{E821?9 zC&1czO6`B0SP95dQZeLJN7N@XuWzkqzrY)&T)$^?XF+7!`R-o|H|N&@E3QFkuD?Nc zU*gz4aHaEQL7Rhspv@bwFn4-upI?eoT6?>7DU-!}%&M#QCv={4a?8qI3pQQhKPb3W z2hAz_g2hYK8>Q%(FSN>9b8N8S>F(>JbJ$!@wxN_~lS?9EWa@fd_t;IC;u7H7PzBvV zuUK4t<^Zm*qHvyRqG9psC+LI+Xo%Sz~BA2PuVqm<(- zBz$b^qB01}Bn2()a4DAC@r#X+TrH6|oTMYU?%7$tXY^|j6F=k>th#1pyBG>@GiaYs zeMEHAY`XtGxO+NJYhKDIt~T~r*?r?T@pH8xPAS>^;S8;wBnx3*wt0uqa^79Tc z$Oo|I#g%2Ce<;Kd7P|6*6S?$dp|Wz{GcpZ{yj!3DhNUG&UNRUk<%xGLlRJB&y}hnnW3Csh|~$5LdtWw?ql( z;TSU4|5Sc8-EdC)P(I&9{8v`oPqi8pH62Q4FDzUgE*;4}|?z8+FsSJ#S*v((>#x@dPuhmT7p;aDB zE6}$?Pm0H*kS%%8VWAGArSNK6SCU~I?cftIb7r1f4D2Cx7J&xe8q}Gh*XLdXYL{O0 z0y1X%iR{VXjP>^z;s@x-;9rek(tGAO>bScmR^AP@)JNv^s5!Z%NjnfpZ^-2gQri^9 zC}M|bcSxR`rJ~}L%7vOIk~C`>tpU7ko-NH{r@}p9@fVW|4SAX1IIbHo@-7Jhtma_D=0argK!rN+0D-5X}OFpN$0@*kV zZh0bHAMabNqHD?O1ti{`%4QT*6@a;Vyj{R^$&8fC$ya;j?zh}KAB$r)q(CbP zbGhv4Kg?$xcM!KLQ}&NYsa6weH{p#jV+R80?INPy)ol;{a^2=Qjhfodp>T}5IR0(k zgQywDeYfc)N4Z0ow?djK$ol85gwCqVsWXjwjb(Ej(&Ov27H#v{PrM^KQ|F4{PF<^(qTWCJumdzt2*xQR-t z;A*F_a!qx7biFSb^;8kDw;#~6Iea|&CQozE4q4yF8(<9=FI+Ue>a8jL4;?FH5z}^2 z!6Yw-^`Qo-gVT6_Z1w|O!Y96kjB1^Q?@W38(s<1+VQziF{lxrQ=v*UWaiF~j%F6F$ z8eCG98TD7^xqs-$M;oiY=62xHSCzqIxg+GAkwN1$$++WDPt~ma0z=2*l!P44tMY3@ zzBEG~Q);AhZ-^{lg6c338nJNf2svZ`MF9O>)L-+6sIJmw!d z*AJE@-)TMbEDFl6tF=Wl5~N<06t~5lqY>#AaOsilRs?koHlqhvZ?dzWv3VYM4EE=b z+3KB>3}07&1~fQX;RB=943*w@K1NCSNnYD)hNpdi!RP#H3OxT7ePAV_^Z3?C=Ga{< z@%ZOd4Lo&QHd!tF(EF^-p9wZh77q>pFANqf?p@h1b7ltTbLCuXILo*M3lsMYd^TJL7fQs~e5T^y@0SQGkgUONY-pkZJ%U6~qd(^Al zy5v?PG*{Qhczm6-g!#!#V&Ciq5i>lB3>OddDg~T6J<$8j?{C+yb&+CS0ME-2Zn8Q&yTU-6^*lt4SS*F zkQNla!hRJ@+Tx;Cm)_Lal_P*ZLq}o2H8GJ+TDDt_2+s9Z z)kT_l-5dwg5zDsKiBnJGpA#Q$mga!Ru~}~3?|j)lV0;)`dGG1f4TO4>81RCo?`MCd zy{$Z~fpZCEwZ95-MXxWB)8hYR9*YES(QeWL)-lsa)}S`%g$Bb_nSuAkPW(Z?9QFjt z$do9?4NDpP07*c#HC?|qkg-jEHRR4&S@+OP8}zSCEOGNp0UVhI4I6H-(>!gL0VLE_ z!0G+$D|i=rq&D9h_%%iZNI#Wz5GPsB;(HL?2(%>m2sNe2=;t(}XLte2$(}l84>~Utgc&uZ#_{w@Me__mj3m_rf@q1||*wbgS(NpJNllh*eEcwY*!Z zdQfdt6itTo!5ZoQ!$Q^F&Q&J2*UnAz{8vwqvvaRO;O;wEVSu0v5cbnJiAUk(M6nM5Z{22XbM&hRmC46Pz$7&Z zA)6%tqv=k-b#w+tyV~UZbXt9F+HOv68I*nbj47{!shri`*1$&n#FBzk4`MpldgIAg zau1Hv-XcIn0v_Q@?3&3D@O8hE)mXnqvHN-U=mR}ql0O7V(A$g1px<|D_Dh~KUH{PeaE0QND6DXN=lfn97e9Lw@cI`rV!NiZK^)+71LEQ0TTQpd0>tyx zt%@D0O)a+H09MbyA)##l!m6z-mP%#=PDaElE4|ozssx3BU}HjF0Q#NJ%< z0zITaa>{U4wJlv|1&U;@(SASJpp9>bxJbzkfz4b1S8kCqiP_*)d@GNLD@J1OK6GYT zU>6(W|^Hk-r92rj zMo6dX#1g!`XynvpoeUM)x9i03hmUA^fF*Zuv`c+P98u6^ZZOpo{AYZ}ohAug*8!0o zfQY5^L_}oXrjG$KEIfb@Xmxq&vgHP%*GGR*qSO`md zZ8&yKdKzeJ=ex@&+(2$K4!Vb0F`a7eNb*2V$iy!UkWOlWOAje>B8(wv7E^HR9-SmT zc@bcgKnfTo_`Gh<*|whN9R`&3BdXB;dPlqh^Z+r0_JU@X&NYQT9&X?`fvxrztF|=) zR%n=vM}O7cQZL5?D{3I)I;6Bz{;1j~ABi&r#0cA&LHpUXCF-?erM6E&3 zXr9#@o>)_ga!U0(uBP??x}Z1c@y4hug^54D@O?XF5T5Txg+QpkGSJs|pT6eU9ioxqXbj2ufBmg;ph-h0*0|x@A$Ph^-Mi zlF2nVG@Q-_=sR1H6<2(2pJny|GC7U*Z%~8V7q(uXe(jWT=t=4+OxxT$GH1RJpvF8I zw=Cy0dEdT)Bg*rxVRUcFqQFVHQy8ign{#$0Tx?2!wt0?hkgz43^!H2%EgxvK|AWido(f1o0_T$bnj3_qAYu=cDEOL?hkbC6_TE< zMbHwjvoThCMHtGv zHjkUH(PLHXd)eo2SK>a1wf%=KN)Gy0khrnq)0OW-GWXaaW$0Ki6oP)627Zk=gdBe* z=`ZX}v9>hv5O3fj^X8^{v(&91YYIY1q4R04jYg=G-pK7h8+Uid9W*5Vw&^w z)T8!Z$)lup@yEMK2*ldpZh$(mr&CEJcIvDRmTE>bX`z{dzO!`<6wFyjIFzm?p!9}W zQ;txVC?I6`kfy_8XNb&0C(T~n9zmsH2FdLClzk^vt-4|H-TN+1%Yd)Pmv(8%(s32W z3(WB0i2z;>F}P8SezbH+j$Q^aUSOp~UYExAUw zol^EpKX03aWm*iYH&{C})-V!f_F>zW0El_T1ovaw;R@(?#93mi5v-|JjWZ4byWIPj zrFMxR18gs!W!`y*c}NvkrReE|s0(DpJHJcVp>#n`>iy9p3YSC@BnN_E$3V<*Q2)K@ zA=#Zt9>!MWB>E|#v4JZz#)d27$KS3wW>v2vC;yyvPCq2$26?X$RYNPnLyGI*$6oPV zEMF!%7|aGgM8O8ITuP4|;1>@^rHUL)j}`<+G^3k*AG^3uy3ZHvz(o=B%uRPmWLvZ$ zQGqN|p5BwU@w_cxQSzELUenh^OSvQC-fJV*nEb|%-Vp^zyN$~Tl|-Bu)zedttgt`&a=*x?!Qyt_6@*8^X`CfuZKTbY-`+4<`H_mE z;VFg&P`7T>6sN=v$7yxxyX^!{kCkv&g;uQSMPH&iBI{$S zcaz+z+c8rb&q=SXHT?}UG$uc>c`cn}0N8L_a$5<&Ji$J=0?@TH&7n zhQ(en79ge1aV+HoEfwW5B_iu(=~Ug63J$R~_l^3rN(g_-JSK2s#Tl4%&OBB|?Hnz( zLslJ9j;hb1xt9RN3fqJ|wmRwK?(*{_!_oV|cAPZLqKb!k`fx;GZAjAakSg9sKcQ1o z=3l~{$LGDyUik=dE}w5cY=1|iC#h%ooLQC+FOBx6h`arqee9w`I#p2|V4F7k-G8NB zKW*J#O?Zw{?o{NGlg+nU;DZiFWaJnmrE#nek`)p(d>Wdep^G8XYN81 zZ0s}ck5i-ssY0-(5wk}?6RL~`@a++Kwdp(Q7SPL` zBeYPnwZBYHrn*-uHUa8NeNp2NzBoXTNs(Y4}lBPzG5AkpNAfLEi9y=N(q`dP@-`@@rX&8I`qUg?dWpzlm!pmx2c4C0{F^f#Y#$8LZ zKcV#ejJHwQOt>O7#3xd+P1ErBy0}DbG^%VlDEkQW7_4dVeYZ-Xwfu#D1Q|I6rZq z1ImT4iu$pqn_%T~{4zublvNl(y-zB^D-)2d&>LF-CL<>Qc0d2f>60);o$a*!OwPxf z#scE<0amyMOUKv>^p40+TS`j`v2f$5rI+dmVbnkX#w?nJ6-EA`N)j?qKn5OAPE`a- z(Q!Xk`+nP_`#a-NpW~ok$~`p4y+>VLyDhQbMB@C;#cLQV-6pb36qz-L*6>|8)}}Q= zCgM}ZD@|lHI^5L4wU`wdN#lW{0{`Xl|DRZ7KnlalGDIXourGj)-5 z*|`W9I;@~i%8Xe#eLiMT6$nCvo~}t3)VyaM+R|2FTdy9o^~KzV_w0<&N3OdWS-a3 zm*w@h4w*#7tyHAv{|1Jt>;9eK{(p%*{(t`-hL5<{=A;kY9MUC*Hjb;6$-H7+4B+2w_g24?E zcCnZ08m#`IQ^5a*hD$$ccWznBvao2ib`fZAE4aWMJ-{D&IeRq443Uo!UCOw`ZvTcm z?)f7o#U~haKp?RN%sfmg>}*%NBqtp zpXnp#X3Q49iV;ky2wZ%&~(I;gFbwg%D% zJg{^gP4$f{G9QCR*fx*RbkbqJ&r~wKAMI6$092+eZebv#BxS0_DwY)9(vvEdL3H`~(%6t@sTn{2$oTZBJMHk)6IlgA#%h8Gq zsY6B`8ewajG6YRh1S4)YSYO~lmv|dt&j-l3pdMJ5BeAlK>-4W^1F+1J%G9U6uoxYs z@2CySW(`);Vv%kU)4yJH3ONxlE#oyE@jRcrW0SEZh-nf`rJ^%F*CcP4eqg`E6cRF; zRvj z{qg2=fE7ANLl2jB;oAqgoYnrJb0{;ZtIA6G7NOH*9=V^;?{idYz6Ac%zL+kr-w>~j zIpy)(eERN}?Z5sW7kxXEfSix*AlboEdHRb;A&d@2oYcpWXh+jjc0o^p+l9={VL zjP+hv?tC}N+Y5l47`U#5|I5O(dgy`bo64-@SY?kn;lai7YK>I;hO+u=9C?aY-DUQj zjPVi_JU z_HLLC2IZ*(XKR2bH&ET%;e?NtT)kiF-Tdpd|JNfOB!I2qN>diS&AOWkRX5C0pU^#H zoFJl#>OSUsvseJbUBzPHU#!{8D|y8C3(z5~_3IRpqk=p`TCSCFgNBQBTHRtdC197_ zy3{?mhGy^-A-SZ&ke$2CR76GT6-{eI$x{%w%@k4r<_~|8p-Rn?vd|q1x7@cf4iYop z$PeTPfWMVDJ_X(m*8(}Uw=8WfPhCCcQzUYUS@5e(R9?_q)ObY^M~j>D@bL+Zk32r6 zC9hCZ7}*!1DcC0p){lH)_pN!&+~cX%Ut@t9x=9AL2S28`Z=O@7Gc<)ntlHgK0-aub zj@&>W$qWP95siPfBfxP2fKC!sWQLpxE_qAxthPU<{YH)AhF{}kO`Zbk(0}M+arz_) z+XPj`Hlwm+fmrJ&W8W4G64v0Hm95`5s#xkCn|0lTK_-?^TP6gWA+C|yFuRhb zNefLk%F1Pw8!W>Ins#sLz&@|=bJGcE2c*mpn#ygbUO&f4+>dB;vZXu1Frx4biSz#b z+J#0T*huN3xWDF9@`h;eHTdv1%oTfs7FDLgKDVP^$YocgedbPqM2;QgRx=){ZN7`p<52NMjE&*F}h3m7S_|P-nqXj9U~_0;n(ge zzt)9khwfz346mZv^31Q)|J_>u+?C8#REVfbNzAbe>Hd7BHHzm0Tqbl;VeKA9D5A9q z#!+~Zq=l>Q@5~J;(bB6NP{~TY63%C&cawQkzvzG=%_8}mkx(RdnH_sHh~zW#jK((u zqhImcTNbCtvstJCLSyM!z}?B=2|qRDmy){Q1cYse&0#$BdkML?%Zx+UH>SFyrDo@~ zbZVQVZ{GFqOluQ#nqD%iO)^dPN05Bh&k66LFRwv*O1>$SUxG6;I=D?KmE@9K_7!J> z>5nJ@!j08Ik>s*W`hzWRj8E%Z$XSj4kg`P~Ik2X(JVJs3=`+Tx7RIf{S9KohMMUVv z`~k|DUH~%w-{lnF1H=1mbPVc>MW2Wq?R|2Z2|FGY@{M>xz>hXzHNnouRJSt|SyEu4EFPHk&W#~7UoMwC{u7!ve% z#7+BRJC>fQfn4FosVvb zsk!GxHWpQb}AJ$L!*B{W2G1`xYA|s+~QE8P6X0_&4 zZ0bd&h=**+@L`e?IP*jHQ2Bmb1>`rdfkmV<8@{hdP<0`MbJo+D7xJKdgiuGttgqE4Sxe>?#9%J5Pk%e{fDkM zoM`JLU~iyn@zt94@@Nw3;BuY)RC-oMHPZw{>(gsJdx?0Vnwn#*_ISq*zKQ6x2Vk!< zw==T|Oedw^u&uVvo7@V_N}r@cr`%Znt{=Rm>Q4XLWi_j=L}=;cQ>CC`3Vul&INi_( z>DkkelvB3|d{L`!pz>~e=g>cN=>uA!oVKHItN_#)Gu%0yqScs(_!90heda%^xbQ`8 zLkD5WI@F-dsj2a@s{T*M1|N6mP$=I4CUVC`s4N+964vmA<-|TR0*7H<5YU}KT8;hN zSVuF@)F;gcF_V8EyW)rpP5#WS52GF*f0IwD?xLOrsp702;us?>J0)_v(eMbU40hF< zSBRQ=*wgOo@pw}D)Gtg7>dSe|m`_D?9l0?16fGvqCo8Z_w`T~U);?+%Y@9COhLx_8 zlE0G{|C*Tfg?&3M-c>SD9YkIy!?YEcXP*-KxHMRSPD$9tYW)f3ZmE^oWY4)&UBiMN zbrpxlm=xTaJ1z;dLh3j7(uYlIdkQOxuVDqXn^b?hs5SiSFaF5s zj4bRo(o*wVF|khv&R6OYCRWq+@S~kZILXZWOzb%P*hG$N$*qpqLrUP!h%Ij7poz`Z znH5&$Jt2Y?OJj*bE!AZ9EdJ_`L<8yZw)+v!7%sfA&cCJX>lJ#&Mo}8VQz_ml4YPA( zOX%L$Dah0|<(ZXV#8ChD2Y+VU;W5v@*l-&A^WgRa6?$ZP?%WrUkNbfs97B{JY?PfD zz7$}3z7$qOFXY4xGnzFe8=oRfslkVe@HU*>c^D$_FQ5mwU4!T3d6n;`-828gw~z~< zEUgy<0o}6`zG-+)aJH#`d!;dE0dN_dia5H{VM0}c+eLnL`Vli9SRLfN-H`zg&h6__ zQ97s}+22_&MxhVE6V<=v@2f>Sh-FrjFhbr!`?q144$$)r;GB+d_Rzc#tyCv{RNF^H zQ&vNomTxkCb_*{cZq(mxu%Tm=t0i$50ndCfqFh#Hczs$WRfVx_v>WSU7Kzrx6)E;$joqKT}zq;dbL)giIMf8 zui(zfTiVj)ulI~-{QA)QL3aW53M3%#d$Vjwd z4M2VYqRH7r*ry{+9&t)l%FH)ZO{`nq0cKt#Vz>Y5)7hQf?=h=@5#*1*H(LjTn=#{( zSdQ{2(QH&6*U%oJXU`P5oQERuBJM!>{Cz z@~|E8cF=@2pd4ri%Q`ejXMjiFtnJisviG6&-oJ%L;5xBv(1nC1@xg#I>|a~Q8G@DO z3BQ`awzZw#9|?ETPBD|eP&XbTr7PtRJl>Esfr0W55KL2NsF_gP@Hp@O{yczb@^uEW z(&oS%K{rliiKGt=%DJ7L6P~}F85A!h&p`nkNPiI+y}$CCSKR(B#V&7#BzyYv$AazZ zAll-$v+fbR11qiI3k;KiuN*P_BEmyuu3mfhP6>C;z~uzKTfLy^R=H`L25JpZ)t)X? zf8-?Z1UcORA`EQ}%6Tl=_Pgf0;bQ~q+AXvPgA}J+BsIj zu5R}Xg_bcijgrIx01-$)$Ywwjg`R8LPKU@>C0>AC*(IVA0BiP2lC8_4mTQ9c)*~6X zV`AYz9Ad-_8n69_e3`TTa!+F63er#UF@B!H(%C$B_W+}Csl>v^lK88o`#?@MZ-Vz0 zQkD#Bo9Dn`s==xS>^2^xjs^i;@05gvwM1ypbNa88yc$Hf&>;fv4*|+`PmJQf-A} zvv!=cL|I8u0u_!bR?m(Hvy8QH6B^AR#l2+)za$F(bGF< zr7-m=;P6<25=iNV4suhsDC6?cX~!I2swPEut?ieets6u|V0chWk^FD}b*Rp}0M>D^ zo8wwG!F&EB9?O8ILR+ZT<)+4<=W7}tJB(J zV#q})!nTjTU7^}bA|}V(t#y4mBq)k4o8lJ(ae^3fX*IO24tc6DYiFEY^ZEmw zeRPajjk&wPvlZ%Ml%tp{aJ&f2D^w>EPd8QrEjb=!MhuG$l+!8|J0eV9P-YIFVkWj& zO}|s@8S|&jM;yTD|p04a50Nz7*x#C_X8@!*4$!8CNXNY?guy zlNT5OAC6EESu%bv_X`(oz<$Z9CWNZl5i>XWggs05CHsuW#^=Q@0t%=a02{dc<@Y#a z7zN@|Vpb#ZQClF8s@fP7->LwI^I^2NI0}@3)Okzo!hO2|yd?QyvOC5rkPL+%C}4p~ zcK>QTtq!~l@yf0oGaLF`@6IQcIbPc86VFG<%rLjzIXGnB$5}APJHvj zN$+9kV*@7tl&wruPsnxTP`6LG11>Pu>GSqw27CdAhhcH#H2fR<9_kvZc> zk&G>q)+M($h)|Cj-e5Ayp6SD{P^}+ z(B7Magp)Q$&;ezOpd^;dG#%r{Q<~Lqcg+w(D77KAooWHrd7#ACj>=oz008mfF|-*i z>QJZLU$9C|KL4#lZD7ANsl|n%*cjaq?TlpE>m8A$~t78vEqqb)LXmWbleePr+{SWL14SSAfe7mAp!tLivFwxQGU z3tF)`)6K-kt&&e}#pFqf9yRd4^>$6jP(b>VLNQ8}#1*TMwpI>x!%&LUcF>299nWq( zG0MXc0wet_b7kZGZ}keTT3*hGdK_%w9$-9HTr5^{=pR`kJlnZqE-l42hn`(3c{d7k zky?4T-f2evv{7xWfV&HEytDfG zBQotoe9gdrD?xOIy! zJR~j1qtjlf*QGvw`#YG#hGcRT{3|JpR}j|C8q|?yARxS(Ami%|P_faiqqMk%2A=gd zhpUI4JbC+m;!XFU$xCu|D{H6*c%e_dkqU?0FJ$)9HKpf#pL9vqM~a*KmHL1Y{MMP& zx!}wstAfP`Lo1(H)WyOfe21nw220(M4gzjaX0{#fm!k_eGv+LLJQqI0M}sOyA%*}! zh%yI_s%VUaosY}UJoBYdd%vVU01zN8VHtgi;#5kJ8I$&h?3H(Am5evvO{?2` z8{^LeXpSrw&urJXFaftJ#=cwNJB}gItrgC>pv|6B7$F1R%Ca!eyuZH0cUBl5fWoCn zU{jn$(QIv(i}%f+v&ZSe-5jtjYn{9das0R&>L-&Iqku|)Ty8q|kZ}6W6XJQAM0LZ^ zLd*dLGeW^##jA^(L4OxAR+0Wf6rrU)`WKIrha$=qzHY&5`o&|Cf=rRGQFtj)abyPF zKc(4K{9A!k$TX$;(CCQI|4eyhsg=++V@|-O7@WHvx#()m77(V)N@*JlHHbRktLm$l?lzH%}QtPkq zI_i_M$){$7Amwx>lKXKR$u#5ExLwS2hx}Vho5U=-xrv+C6rU`}(`1N@(G=Dq%44GP z@rTl>${*RbXBOHjx6-ve`Mw}3;B4jrcL8H&`%2r z%xh7te)*X*JH5;3N^CuXg38CfMomF<3FxSby-SWKS3Psh(PCXc-hNBvlz0QEaF`an z9<~QwIWzT*l>BB-H$G44vfP;_e9HP9hu zWPXZkdT0LfTRVlC5yMDUYS%-|3Qe?Uosh@9a#}?%?C&ceU7?-gnx{K`HaE-yOcXt; zeoL)>f1tkPpt8FuFGL+LP3lRY9cY}|+hqZXc%Ur3 z-~4CjoBGp_19;^13Hz$wl%c1zH=n%e4#Ba&KJF~DxE-UF@tBid=2(9J;^NrmYk#ymX|Y7SrKv<;C(w$=>;YI_b=w4v;^+fp)m9cT zZ$BnzytqW&KL-wR=M@HO*{}db0*~!Lt5M=F5hf7_uQ~e*UUSp1{k|YiDBHbN7LWb= z{98)LZq?l!(b#r9rhUiN1n5dT$ChAL6Hu(5j{(e5+=<-nA-wpGTh}I0l5jP-b6b_} zmW^3K&2v1%coPL({08rno=#`I8=ZN5@ubzJH$)f84JckUYWV@lMLFfB7Si|K_KX+) zK_Qd{(c_7U0CNSr;hFOZuc%qxOx*q%OUf4|4{Eb9&)p1c8cbR`k@A@$52|VFtmGtjHD; zH62g9uY2hTqV{_1E~MwJutM|RemwdFv9Nb*f?EIF*T7c8eHE1Vj22k5UUNRYkO&10 zOn066u_Qd2#|PA_pLRb!iAzBF$%q&=cS{9PJc5vf^+UjM9@Az_VI^)VO758zmvLAaQh!Rs}D3olJfU0R+6{*$dQIEL@{kco_VwQ z8supNEg@t55h|3dn_YZK=D6Dgia=nRCR!V`#LlEdAWKt(mjk{m{;YxgXbDfXLDZn zdP_XwA5BRLzm0R@GN@6BdKX^*oopbpVi1+JBVf(pSp#$t$#?#PQ~wWM{oh|1CGe=v zO}s?6a`*-@GI)3uJlk~|gN;FS%j``q84TOXS#pml>@=0BBo&T(n^4atUKVS9a>P=rc_k(>LZtG29_*{o%%^cK9^@xxoL+5;F<$} zMSrbP4%w5R8rwYQPq`ZRrgF!iwvFsdqE-c#CURD{O$?9#p~Kes8_c>9uwi*8LPs7V z)rJ&Pb}rIM9H}nYcqZMd;cGmR^%J^CPs+5poAd5Te%!mvH__#%_=-COyY{$gvldRJ zVj{5hXO3rVjj0E&nRe*-6<``UwkCsENzbRIsHKY+69c3eXlyh#iXV=Tu(t?}SrPX86q!zAV6Hd}p71w6aEn~K_Y^7J8hmJcfFUIbBE~e*MKLupsua1D{?|=RG;|D|U zTmEQckGtuH(x-ANI{(mJHNyKXiy3f|`IL|BHV_p*d^~8y~)&kme z((VTSw?~uos96;?lJ_g7Q{yLr&WTpp?Fg?>s&$QZutV5CW~U$6L=3$Rq9>USFsO-% z4NzsjEgiOdutPx#a(SZ|DR`xXP@E-yHQ{soKKfuxshQF@^;=}+j0RONR@I&RWPiiShOfGY zt%Se`qYV%!mim%$UCL}6 zS{_p(c6B@tL3bE!G5}Dx`6Xi)*}758HNb)2KP;+68>RS%EqW^(w-mg}dGAL|Sq{2L zLMRh0s{`$drnx_>UHDnLpZ&SjLkXBpjJ**1>p}O=X3V!Bo*D3Eie=0wrQkUE?F9I# z8aSVg^^>*mn-U=+ERUFYrUvTXXHG&&kYzUDoGJF`)s#i8EY*sen61>!n2k zWpTtPfw=2JD-((usfoTX4*qyp@bg(H`KoYR{04= zj}Y`-M*H#x$E&rz%4ihMeqhT)RlSR)T4)rCJHKOy&|94`7hbzyfOvi3e$EQ&Hm>jW zFY*|qU)NL-xp2d7=tZ|-7~cgw*oUepCM2h6&)rnan_qRV#yJ}F7SaIIzf3C z%i2Cx-${yk05JZDb&W9P_J%UvxI6l!C|FO>^*VV_j5H3q-$8gj|8yF3fYHCSH(cnvfR|tRY0gZ??vd{a;d!8V;wH+i`Tj3roQ!WUdGGaWnZ6r6j z6RIit*qbcu53dCBU-*ZvK@HpsYjEU>?TX-w>1{o|ywzK%l9r%4cC$MxkNa0&e=b|C z2-JrboNK39s4cFt-+3mZolybn8ErE_oALFf`}X`X5;XrTP~IuCICm-jObE}fQ{8j6 zaT^-*H|8DYGLiKbD_-G%_kwq%+=80RG6L6)^(oS$*#mmwWCPDt)w&^7OVt5Q%y(fd!w%^PwmD(p1lvY6>{=0B`e?v!t$|N)RyXNv2)zo~{JA$}W5{7gd$}D` zVX}uaBF;~#GvA3*?ofqB`vTY08ebcDZRD#J&kFu=&nhf+ZPoGF-lx9b7? zf!J{O1G6o-@N7SykTI%vcsGfb9DnK#s0)JMw9mF6ea}$n!G}mt~ z6)3iwh#g@~8XdV#?e^B~%uMrds>tfG05mJx)lrBjY!LAQd>KhksFc&ZItdFT{=VzN zLS6)T9x~^HC)i^UO)F}O#rXM*jA{I%oU^?~&FvMqo-X)Q&-RAKtfU_~G%6?fQ^+Y$ zF_sbmYY(qjyc=cyvcXX-xkzezywNqEyE*|}!_7y`4%_w3cCgovvH6bvnnRMot_AvL zlZ-~3MXLDUIqOM-;yuS@+7hyVPMdZJ`%|wUV!!^x-y%0YbLo|1Po5lUeCTjb5HsT) z88)uzBU5KizptF3#TkaqQOWnS3&f$f6Q@kBIJ#^=sx{wIn8!A8j50zejgZZ3$Rd=> z2X^`;eUQgHv|sDOL7LR&R}~5uv@?I8cX`328xb6(ybcAW9C+!a@$ny9Jw=FnBram- zJ^aPRp38x|iIA<15jJ>@Re`YMp7y|*dkCoj7pCOlE0+ZDaulvLcNX%9QgbSBBeae2 zgp@ZX`js(OvO>rNO_h!eY`bgveZA(1$bd?msD`}J2IVB{JllWNHCjj0ZZF{8d~Gdg z7qCGeHn_G3Vw#*P@A9C$40u;HOWLjt@!8|1XDa&oUz$A$`L(p(2^xtS&wq}FNtXKw zr4Oul_h<8Kbl+b7v%qAo<;i#25%JzBuat>Edpv8ryi@DgTGKuX+@`o@ew)!^8`%ZV zi)4~*SP4g5ma6>zF*N@IePz*LzXaSZaD>R10LG-)PWrJn;EDOaprRtsJ;Jp5f%T7c zit`+V!K9-%2K5gF;|4g-Gzw1>%oTF%Rcb?ONxoKbp|fN%PUg^Och4CN(jF5wCh8_8 zBq)4u?0!K@2|pkKo(?kybSGK5iN^1dXEaK&q-KJpL0 zv&2NrhDa=fPm2*g>sMWLIa!1}eVzSUC|TSIcrJ_{OawD$sM^J7&cft{NP5ADo##V#0&FKZcX?8dy%9mu|PI{$|jw=bkcK zMG*exD|9tVBKY#7FWQ4oextQjp-KS@DN|tXg>zyU^QkNRPviJ%!IooP*zi zR^AhkX$DoFagbrH8(0YIrwk-|XSzr;mps#hX0oxK1)2$fyAb>yQnuHro1i10N5;&~4p<#}(WL8nvjDf}ignIPe zq?7HZr4Ky$Z=)*DGXGLZtWNGBk$aAw^jEia?ftTan3U#4Pgr)k{ew&fXKFv((~3Ojhv5O5 z&Z9)eck8V+iZ3kf3&%ebT`3;8B+tG2aU8U%{-r_4vtONJ(nl5!keNPmA_MlJ0K^zt|KdA{ENJhQ_OGr+T`^-?2`Q(w9pblRsEKlf9uXeyih96H(87_Sa>jR zGJ_~gV#gO>j!KOZNH=^A3I4N^0M#G~cVrHk-t?ZhL+(mLEa=(D!7m`^j&d3Kn3D%ZQZS1ovlsPFW59Oo&NOoi(`m2ACv_C*rmlR1` zy>O9lu9f(YXVm4VVkR9&&wK=pCvi1t&Lr;2*&d4LBLaNT%L?dci}eCNgae+TH9&bi z5*qa#(KCf2+=2j7&1lMFgl@Yx;@h}zs10N_9l@kd{$>l%y>Ysx1%&ha6!SYk<9|y9 zcjwW*xb1<2DQd>XnI`gxq?tlw9H98Za}$a8{`daN3cqrTqzxk6;~zB_{jAxIm~~bB zSrsmt0J_gPBL0`^7l1>oCvMqCE)o?;f{+EhoAAe#@Pd{@2@8oH0GCThLCjGn?%@i5 zRD46aaWD2b^)BOcr9v`xxx;W=S&n?ON%YIQMR@>Abd-Ec-dM|)5WQQd?A5DuFmPr| z8vhyF;!SsE#(rEJ69#XWV;Sc!*mBdcs{$&49-;ZY)G=Sdb>#l5Wy%#Z46}UOu}u%V zaNeR?{MIv7vlayolrM8*W|a0skicL*So7_(q!+JT4m8LRt zUuC0&!CD%{;q3@Iid6Q|Rx+c#@n}#aRJE09@8liz1keavfi|wli*y+$cmpcp`OxkA z7m(WCQdT!w%zI*nACbfX>iS}2qtxJXk4>MKxe{*o z75r>W^}?X5$}9GdX_vG6&4dXC$;n4aw6zSQcYLXFHu3Tt%MrZfZv6gf*0~yZPxi&q z;p7Q&Id^>=RoFfkk@cCs_FMw5$*f1O3^yX3YzCSMNrd+$?KY^Y&!sTpL)pBKA zJ5BSJi`==@C=l*@)9vBOO=;#+><%C;ye5fP4$`QM#t#Q^K}KJv3#7eB4;Pj@ z2<(I3YE5TY`c?lYA_hJV=@NJfRxZcUYz5xCFOAlnEv|vWQ3v#c&f(Cq`H%8a_PfqY z^S7tw2dX}JFh0>1(5t(N_X8>@A0cl_c9<#YA z;0Ji{8Yw!+pMZVgkco_VqCCKOQkL~RsM?t_2(KbcwB&!8bs;o-@(YMT;gHItHh2t) zm7FPi1HY|uKb>hjv!+^)I#9-qyEbSti|_dvE7u7@)z{V)ZKe+MzM4?=?3wDrBw87f zt?RNu2Ect`X3#9tR*A`Ukdo2QahlGot@z&Y2xQ4mh;4a|mepbiGH)&$$D41TM9oV$ z?JWlP6#^6v=zojLC*RbDra{VVNq3hiavq@YXRfWTgs6TYTwK{6YcIjAsIWH`JO^2Ywhp%`C&%K} zBH4f*^{32@c6;aTKrXI7oS}|!gxhny}@AoJ65e%0#iNirbe<8q*rnFG9`p&qiNwXhgj0L+HD`|L20P!*U_*x43(RR85Q&Ff9r4Z%dY7TdSJ z`7bn_xe7@WNe3*X+G1++(-ME+dpdZ%e+SXYwN0Mi5&$y%7lqif#B(+>Ba##bw2t54p&W=Hux|GM;khTW1rCtiomchwE71T|a2xfXw?su2 zN#!Clt5#a;M#NUjBwL-@iY!;nD6g~1z!CGrL`7QN((WX87Q=r`4D(Cf%q@T$3O7Kl z#3HxN+FS*L>)#lF4)J8zMya>02}y9fg^X3G{O^jI{}hXvp4TfPProDhcecaF8l4$Y z7XUBAVDLSzBZaaJxJf`-$+w3A+yW*2s#?RhYTJN?asc{SyjTC1>W#CQVJhl;2ay&i z`3e^(?FG%B3?Zbv*dRnI|3U+HB3+#TMes6rH9~mKfU*TJW0)4(L}4P{4-&`%mfhsl0pbz-xLTG`xr;N1gu|E0|!pWi3>;%<`vQ&W zSTKvA`VUv98mck(B*@GfZHh{A^pp10d3k)lm^3oKR~Xr#gIKMAjPEK$tuPDxg(k%K z1TvjubV7f%Z(OSE$Cdp!2*BL2KU2`cQzL!mz34jskfq$A|G+1V)nSn9^`PSRke3#& zE9ws@%pTJ~ae6rtAwy!9k7@Ej#w-;Ch(#a*pm~H<^Boql3C6&ex!| z0y>d2Z4$I7q}64KC@oGo`+!)Dy#P7XVeHE~L`KVZ=sG9pLH3D*#IbUi7Q?1dN0PJX zA-x`Ci9aFMQ!>$|*80dvPNVl8D$8|I%fJW3LFbYw+4a*|v9Zxzcy0cka z#m<;IW$(kNL*)&Q7jYB)CE^Ds%rWDR9}>?S68mK{nT7!*NW-@(*Cc%$CUk8kNtF+G(_o zwqQZ})5qA*1MKH5mvL&}D63*HQ_=LC0351+l9*Np8uPGVbI}efHRheXr?;i&SAf~n z(#Ot5g(or>==tTAzU>|}5MIV&4BnI_P(Pn}?zC_UNeg5+2sI2{=4(n*Z}zJTZ8YR5 zjrBG~*3N&Lg008LRKP(#?ara*vXwYh**f-9!(7T%7fCSiYbV5*1Z(5sC`_|vXkYMX zU3_2g5<{Lf!$IEq5~iNz)AVESCBq{Q`d})x2NaBNu6eskTDn21fpdB zR1Gm?1N`Jp$|W~`BV*+6D;F3w;rSH8MPA>N(_!9TPaPCH&tmbp>sto3} z+JqGE#WYnF%N)&(T=P)Ug@M8Xj?sw@ZHnXmYKDZKBARO>)ir|NR`~k|&qNNM>23)e zKUFk9ihD!AS;oa$W`jjonsaYxJ`z1|?9-zL{284LGEG@eF3ABE9H56GapT4BOIGPj zpF1}`U4-OO3g>EwyE4RP;~2FFuOMR0$8$qJ&_Qu`^F>cPo0YPlmCs))Bi60ZQMT^6 ziP^-q^EA(ln}Vi4YYvWP5dw#l`lORM#|7;4i)IG<3tVir&(b)fqv!R1dWhJw@9BBI zoQ13OcYr{4sbFC3ar>K49*vO)fvJ+@zLA@{0V~`wSLyF}G&3M*`#D-;Vva z%~+E2x?IZnL=E5{@O8BDDdAp==4i|mqU`%FoSO5OO!S|NrFsVznQGHlZy_ObB?#L- zZ*%4JErZ`W9-H!hVj6r?f2m>*Wgk&Sw?T~Jb-b%NHI+d~eHRD@UPK_a%6NYv@n+6# zJyVc~Pfr+mU8cNtO=o4@*^g9DP+-9GbzpC?EFbAr{2M2L@Ra{Rx#SN039XPXN_PHY zJjzJd1hWaET;`x8Vb>t{?fz0Zy52U4eGEKJmhU?b=j)jjkH1Z+AxkXw(={7|L+BiFU`BZ+y44pKw@*PQZ&i-3<@9^Iiz>S3R zDBC7)vTh=Qjm{0B8o0pdu1Up{;hadV?UEw>_1<{2j`FXEF{r7!6k zoUhf;?+=N1BeA(K!gg}Eus3_Qm%1CJ@e_qsFhze&R8;Rs)UJ-%TFz{` zK@1uJjDKOFvG&oGmzntNtYX8+So*kC!t+C&43Np=`9eQj(#5JE7dyS;8?=U7aSHiN zzKP(!9FAq!64{h`_HA!%>Bb|DPS><-Ka|6MvCwLHQf4||2oQ<#R0nbeDhTguFB{UkZ$rVD!4k}c9 zq9#;cE53WEbqsm91hg?X!XkckJ?S#b8A3Zp_l^CK5GZs$@n!^9?u4CySnOrY+OsXA zy00F#vu2rPqnc~J)$>|ER%3l6-@$!??Y-yurEqU7h#0HfOtz#~>p4gMdcQ7LIFJ*f!t<;%m;)F+#7LWS$9XAGy4uWM zC&z6Rcvw3+2kxI=X+g6qrY9=8cu^kUs@nO4A+^gAXy;`<4h<*v+1mmwg)x@-B*{d8 zL@JhU=!>b4NfzLuXEyBn*oz09P9TRf$LiH8F*K7A?uBk0(#ylu+=)xp+PW+Djen`u ztas4AnV(R9;-+^RaAcW!n`T80EAnKMMS7;u>-hQZCYoDh3FO{~rx5*sC zsQduj@z3I84n)0-p5m6cS2++G^5(zK>%G{u9MO7L*30~ts#Y2jZ&>rgWV+|+MwrPV z^IB~GnXYUpXa73SXtzGY#<+2CV+O0g@70f0u zp?FvCf9uju2qVP&d%{{YH8QmLV(QiNc7ZH}S&_MGpZwrdPxu(~vef6S5zs7tfw`g)s4|P^0cCxSnQ6kvZ@G8$Q7Qi+`XjF5pVn zJ~`Dw!_0g467Y32mmM6bn5%=OzjYmPB2O>^5Sony(3W`JTlriOt!!(=Xz}5)+?Aq8h_a=xeBeay#$}RM%htAX_FRSdN#c{X?H%XUue> zi&_~QF!HZ@Y{GS9?afI}z5k4(O&s=!e7!S&JA&}C5b+^EZuq^;JkJxy`Sh2s{ux+A z_SebG32%xb#mGO4A_qR!FVsk$J*$!bxT$Q+Qg1bWWR%&N+Aly^LGU` zvw+F9>6cr*LcJgT^KX#_K9ZA9z+xKXA8r5@Q->JmRa^YT016i$^7Ue1Y#Y6jg0%b`_Oy=jLH}LAD*oy1 zQ2eX4MQTVO^DyNf)F|7jwZ)?lPL}ruKLX&t4g*xJyZ~@_+Ww*tgfIR})#BZub3jRP z`{&y3$aAhB&~Q48%i*p=01jJyRHANUUmyA4O~*qenhMD=smpaLa|&w>l7#*+r@;hO{8d46Dv~;30M2MtVd3r5r|I7+lMW<-)-J ze4~;$F;ZV|wtRXH2jp$hvkHc)T%UlBzB}~+pyS^*mHZlz=EuAt6;JV;nV>B^b!MP~ zge+f73|n)Z{NIPpFA4xW=)(#S#Iz~`i{(OzSe(=D!6NY<)}H^&&qWvvuDDh5ww-7l z%K-N}XH*-zTcKaX@K~U{mQ4FBV86rmUlgVJ&E+1x`-7`~FM#LR8}4{~oKO1HYfl|q z^ncQhs*v~KtR~dr3`AE0FPwfhex=*&P-*&eRJM1100hRHn|Rl)c%q9}>qGL{)_Cyi z(mS{YRs`xiO((`fN8COZn{+dryvluy9x|u(@|KQ*G;6GGMWyE{12GlMLAiGBM%%iY z{~XFYW`m69Y_5xT*qz84V3Ws#17788%x$ud$HWzX4l5MKSkYYcOat}mT$1uhfi9ut zRpnnQlcGNzC)HYbtdMSM{ zb5N|_rZMtIjmH$>aYA|3cva#I5k+}!M-e_~%*e`(^^zas`h6&B5r~I^wotcDRGi-5 z`&Bf!zWT7;6*`^{dMCy&&6pLQ^`u(UG{4YXczC3HPq}q13}Uzz-Y{PI{6fHTxtXo6 z(R*_Q@!J5>U6xx?Q#p|0Ea*cyWB{bAX(|EQuod5{0M=x4Nh`!x=#RM5(62r8-R>vT zZ`t>}%-IQ8EWt_fnVI-kNN}XzSulVD(6Ki}JB+WaIwO>5_M!EIJxx1E5NNrmqHW1)z14gR&bA#WNGC6Z85By=@ z9$Iux{lTgnV0SNJ?fkjxED%o5r@?$6^9pAB#gaE3TiGMCs%8lDynQq>4)G0?3`~*; ze3Rbkl69lvNf=>neQy>|bMY)gVSdKtK9#r=@X z%7~sox01{V)Q=}19T;9Mo?Bzek?t?!J4nBS6fImp9YAJ384KFa0#sIbM>#fM>~`Fu`YlMoXa zAw8E)B>!W5Uc2l-p=!lu;Qbl@2t;}5%i!=9dk(9Qh4PS?@xH`erbW!l%Ui}~V>PlI z?Xlo$i*WyeB(0&3ourr8OMCQwJM{v1_tr+HX^#83dt->zsUuOo z1@~wI+fssVWE1hvO@*q%9z6>5^NHLOJhjme|DP#xB9oBD z<6;~BmEwaWUH2fln(hWlFVaU%(S+SKcCZsq$)_Gpyedw=!w$N*_cUFSK%Ys7k*XW& zwwLOaq8GHeAvVA-V>=3et25wWv6i>?_8jC{b+YL?vFKn}tHl&Eu4hHUs)Bp=>_KAM z#+1hg>G=y}#i9yz{i;|3dx46aUR_ux7V~9Uhu_6pEB~CVrkf?DnQa_1E7u(Mq)_xf z@)GSaDhR=ZYD&)BJR4@poQ3qE&fl#QI;ybi=8lSPOTR|(an?!&wTQ8P(rw8~=+~&n zLFHM5bI9Ys(IQrbr#G|TGYn1y!-vdiq9j6F$MYB_6X+_mM*)EW*&oy#yU5pG$oWDU zsf@q5d!vfoai8VhwHE?b-<7R4_2A+p<6)9=mT-8Mic?mMVvK)ejsab#c6$B9+Bw`T z>i3#WNToBh#-mN5ZP%h-@t4}ce zOXb8eE3X)2U8>Y@ogz>W>Be(En7~6KIPP=Z9gr{i68Y;-c(+^@xPm@@uRg67G|0t* ze_M@wa>|lq-aw~hwhAf(rw{Z&^MJ+%eiPmfJW;9spD(=%fhP2%x-{#b=UgYM(k~te z4jIaGPGpZgPLO^}tzB(dRj{QSFYVTOIqXT%$0wUWZ*-FUFR@gVe4~(ItICx;9ZK5D zxtppxduN%|DUt_&>k!dnHos3>0t(yb-nv6!DKZw|Q%ae8tVOS8(#9!=LkcefHTN@0 zMLrDwY~r$E7uT{xv$hdgKT**t!57Y!dmyJau_W>3598(dGT2g}%>JI~lZ%NkokHdn zM*0ec7K9*DK3DY>^oreC_1>c&);#(bY%%qs^M>^m(ou^Y%O+lsJD%*OH?AiIZu2P> z`HS@wMvq68uOw~XHDE@QUYDoPxih^&)Jrpu7;aax#RNIKv&WL8*AI)PT?z3>w#wTL z^h+-@XU6fG)zQqM)kSsK+ij0u3tBmAW>!8aTGbR42{sxb7`naUaEB122|Z228( z4u27e-HBxJ)1-H@t-!|uor5|oOSgI$zT|E8d206Vk!S5Dw~(DsKw!Bz zCNFWY;_EJy>Qfhtm=4XqD29J-)Q*t~QHoN0@A<;W@ZD#b&jJ@uuv7#xk%=TjIN>-; zl)TbH;eF?|En~_5Ldsb}ekW*qpaJpk!F+gGs4z%Ac!ERfR$%|z zJ488TJ8<-Urp*a~Sd(pe_Oaq}N6jm7HRa#40_iQ~kjxjHMBsjI(%kV>tQe#S{H_h0 zzn=cE40#5g7E_Yer3|n5)1GsmekLOW5Jb7z9(lB-C*t-VdAtUlVW+aYcDn>+vpkr5 zFhx#z*5!8lc~g5iMjH~64XtlPq`q&^Uesx|EZsbmlTDwWNQPw0-Zvg0DdtQ&80+n@ zMWI|iE!I|kmvwu(cYWIcb}+KQx2v^0FuDF#RTh#j(H}KXyR2Amd0Kk0fVhGvuRiO8 z=fnGGlux) zaWdwMLH=r5d+Q3{8{Vau_0c1trI42WDcXKj35FTQ?piizl<*E$ny{qED0e z;DouaMK&>~0`iKu+CPf3lOCJm|7 zGEg3B0ZpRF6Wo`yg6AHg6!4lz&nyR*bc>qTPM|scjh?+5%w&^T{5|FNKhkgX<0l$4 zy=u=r&9VVGrQ-)-KH=o#b8&bZybo7t@EKuO_+-~{&5W*1ttRE)`tQ!p`oXm-I89|& zb0V~V4V4F+lwamXrt0?ISH3+;zYioHWn6W;1rG+!#et4(WDyArxch9WwK*?Yn;ZPP zPb&kYFhCgQaJQF$9e}-yE2-gJ*Yei#1p~c+=pms&E93VX9^>E>$vY1KN8nB}Yi8l* zRD5oU)wSKoUV{Yh>pWpgG`C}(Zs>(x)eEEe#F?5U9a|V2&uZ_?2rv$&XN_#WeUkr3 zTUS4N)IoAH-zel2-K820SHF6u6xHN$@tEDaJE|-NCC5A-m^6rvzvL9$4ykv1@m31Z zZR*G(Jfjpn-{GqxZa;n=c6-&%Lw@G?rGX!^dPF7YCez%;1v)q~XU5hF zJLTs-8c-kB53GMz+CE2_zvpM)<3su`mwLEmgZHvl(>C;*%nPj#h169}*)5XK*68;n z0u1sttBi$?PYr%GH1rB;FS~xej@@;-)nD59q{mwG&T1ZJfUbdvaqiwdoJ7$?0f&o^ z&KzvDX@_tiGvmhX47w;gc@8Ux3P|wu{vQW`@iQ$BAxZ=k)<%wb}ye}0`!?iM~p&W4u{P^ zlwM;*Cte2)S-=$p8}AT$v~-&sz8%}c*RYoJ>T!Rm*gibX>B|c&75KrM0%{VC9${UW_-*Q^ zn_#0=+lx~O`*E-xd@djnC<)Lvzy;Ixpp50U%|0Qxe_O$v0;PCw336s_L3UVy3ylNl zh(Xa7!(Xa8&j*x>UV=>^KLvE4dXcpkcy4NTv4>ZJY?dO_&hO1H8H8bck*$6|FJ@mL z#B{-J$oss5sjvx+ClB@=vsd8E)1SHoEO@2e(LNQU!|9w&4O%rD*ocP&@^YRQDU?g= zVv`oMX)FRCo|6h?FWy-N?M{J@vCIc+LXJ;xDZsEFwNta?wgV&>AUkH!q~YQwqKOHk?EdZ7xRZVWX#xx%4qpc#R_B*+y{i`u znjM4U2477mV-!#Wu;rP$;JOY zH|95jDX(asTAA3B^lb22F_RJbXFY3?5s&NK%qwEkBbW`xy9=9g*{Ar}CjH9N8=f1M z(euxJRyeH4Q>R%WSY?5DDUBnk3RL1bC#`7YJxu;qoWWB^yh+o9&ml=YcYO#=i!dGy zZD+gHNi77^`VQKgK@%o=)PfC3Z(u9^@#9;H zHQg9eq$QzSr}7m4j?`;%2qOD!_iW1isC9*5D7)%8?0t{G)CzsQ)yLYTZFG_Ijb^Li zGpi&H)FxS=U0w!0KE>C9f+!x$$1Z`H-{q@Jdp2a8#E0rYYUwAKH{Uibxqs;P5c%#F zzq{!u5y&v1MQ6hK_4F;bmp6{JQIddIz=cv~3wqYKm@W$*cOv(TO*SV34eRKRQdkK=OIocp>j&vUIh%=W!Ie=3^3yJik3HwpAL;zFMF)C0j`QsD z@uz7K56pdJI<}fa^aXF5qqht>uyo&t*IU(2tkI;a0jR8w(?~TcUs`WaOY-)1@9fci_3~v?svbh2*ml^YT1&;79YQOOK2m? zZq5=^`Ba0zpL8rkc_*;&J}47p@y>YrH!q^44cIyMYzWzldgIGXa1NW) z=Wo0m;+j}E-mIbF_ZYP>jEnD=ReYis0YtLfq(Xbo^W(EDi*w90Y14m3WyUlj$=NvD zls@pAT6|)#C%MW$wlStmrQF&Tu&6A^0^LV22ZC5U68*6~r&DzX3^X($u zaZxiilDC1r?GYCQ+-hAh2V!EEIFp$5R_X|qReT)m;&wA(7?cj#lG`pFuP_rOzDnwA zb;=RrqVHv|qV zSJLCa#WVKk8>7kgBk96X3` zstg^t5xjxc83$X8)@wboD3**|CVw?3K*E6_(Jn$u>j#=!*!VeU6G?TIpW`kZI+`Lv!X5|Y+>}lem?ln$n0QG!;#*o8`qyr zA`$zl$D30%phyUZu&k@c1w6HnI-2!2Cmj)mST#Ls14m4uTT_-;DvFa>$$bUsR44M7 zee(bel&-~;^M{RZ*iw{8OuE31F7a;SzX`S20sZMw%D3*rdP%*PZ(5Xk3b*FH$#$uF8Zz}8uje> zSc0)arBv6;p%=qbG~h@^!MPRl?W-CY@K4n9Dt(!XW{OHgeh2t5G?8uv{H4M#FZ8W9 z0SWEmv}}R22j$6u^KT3wTYvs@%+U@qzUAqeGjFn0>)Upc-)TO~hktnbs4?zfE`Mzu|= z2Prcqd77_oPuAk(VurIlgZ^_9h$V5Mn`zq&@3<&G2s_rIC1iLSj!!LC&OKNFFy)uq zCq<|*z_bhXh4MI2d2G2mwV`5)es-oKofVO{b<0h=bFi~GLVI*YH1!Vb0xi_*LfDa$ zb-JCI_Ovj!LIbkBS_VlfdyN@eYgyv%c~0I;Z}PUkbyC+PbK{Z4=iF*eUFG_N$iq3~ z7qV2OQa?m#b1mp50V82;;vd6Ze+8*3*MY0>5LGJ8;?DE1_*^7<%YQfmCTv}EPUasw ztS!ybmkOViLnVuOr0GnzCc_v%ewOT^a}T00w-QoRX{S^QE@0B6N$(&6Kc9wXi#BtTCDOA}?vb9^C0f68SgNZS5u z`vP>DiZymCc6ZPCs9{qU0MPQwN86L*+uWA5w8c9r^z4xsrD2q@us{NrbHJ$J2}4Xu z?Z@ghhcH_@_81o`p20pN_=Cof3H53tUc)JsNj>*29|G^lrnz6K2!0CXzj5VxyX)KX6bW2C z!?TAjMkV7oP`h>c;tzl^VaaE$Cc}GFhk$MdvRv>#agoM1kgH&+(Fcmfp|fcWS1d zB?zj}N^`_QUy*>?{j-D5wt37P;@;Lc7fa~})(63jV;(fQ)OSDx2CSKDuIWZ?aRCyu zf982^#x?8oAnO&RJ~^BOUj`gTtWdWc0BpbgtLGn5TlwJ61j?3+yjh!?(wB>}U(4j! zO(;A-E&{});6lO_$gUr7z_WEhi;!UWWy0m2<~imv5#G_cz}eAWuBFwucjA$s(zU4G z-ExhtfUI1hr~%0rW&OAWui^s=n3lD~}V(WR*Qn&G=0@#8D4Oh>NibHm3@e5i_%} zur+&@S}K`@8i}5W;2!t=-(-Qz>fsN2h;fs4tzr?FSo6I(vxr!R-pEhKpq23xzod9y zLEX1$aUbIABezwLHV0c%nk9AKXQ|#FT!B}hTo)z{e%KnET7+$F6m72k==Rs7)W#IP zHPgJk+;Vn$-d87bq6w3WE4-t0eIdv^+VgouRf6u&-3nJYC}?-8x$NU_8>Jah`t!$) zs4GdM7^NKJA^p#rqdRD$Zeg7bgQ{_`BVueuUXBI08Zeco`?6#g^Kz@6ZKnF*B)DDm z<3qW@rLtmKb|&|mJL&ymrYQ5CXVCUw6nd+IdrBMC`fZnFVk><0)1v$`_i?_bkPZD# z*Gg5I5&l#8p_ri**WJcY-pj8clg}X->lx!dJL2QWEN3NVkHeX3_W5t}D=QoRQY}P@ z=c~>M?s+`rNm2W>V%e*#ds29^?sXAAmUsE-EX|pF$EvXxMYt~fvYu+_2z52yNXT1S zGetvkwo)ve%fOK{k~!FMY1>GISNY4u33I-4zVR%gAdP)mb|Tn>=4%E?MS|=toujEe zd(SR2Y+3AoP+@?MxM+5mOSb~8wLFXYl46vE@Q%w}@1OMQ6{%(>ZKB7~3UE&$-C;mI zrco85)mRv`YasCR7cfn|996~Ml|3tHCHMw!?r9#1HBaFbw!hR8T>;Mpq$ITVE>PdY znSXg`|1p~tGwLz0xJP2o{jucV!2&)+kJJ<=M8D+^enZ7U_0(ZJ2w2OH|7P&_%8Ael zjibP}mGKqVA_r!rYYG;Qr!W`#IVTN6tUJB>WQW;+WhBIw(;N6mt>#ByA^)3zqdVAD z{%9wcIop&faee~~K9&vJ?^-t0OB(55(Arbr{YwwOD6nV~M&oomu$TxdP5x&?51!2R z8daV$YocqTjb9n$yoAz(=WQ9pI$eC!R%C9!q@;28&DH1`*+7<2WFWVHAb$h%2#2Db za)PMWb^&h~06wg(L*S`LV6((ntm-sIHC~jWe z71k@G^jt=ta35l|ixErIah}*~+mi3B=OzIbM17VES@CJHUHN0*s-1~K-()XrE>o`# zrkTtFsJb>DHRLwFBhVKiY)Jo91*d%Q{$5X$E*9AXWRF6%#y!jyp6nQm3c+X5Gt;PZ zM<(Tg>PL+}gex9XP-OA(+4G~HF`|$uC7KJi3;D+Pp%Qk(Pj=q2xp~`27`&;t6YSA1!#0*zYeOxZ#h7g4`4k~wMeIzGUyMpH+oh$G!dh-zsFlu=J z_JfO{&xl9B>>li4qCV=_wIm(?`vME;ZiFyvTZ#yqS%J5YWH0*EglAbd0F*o+V?Ee+ zy*)f|N*E<6zuIIT&cS z8d9GPk6*@JUy-B;r8Bi}aH^bLMVxF;!g^)-7X8WKCEn4251V$m`b-Rm-)BV-Y^N>~ zkA9sj^3_V^P6)=zDfc13Ju_amFWlSh%k?;6#ubAe=UCyD$-8!@7pXUs@zc)koaVuW z;a_(x?5$nCHW*Gsk<@C;l(Z@y@21;O?`z=54vUaQG^SpCiRbfL+irOc&*aS|)7`5J zV!{wC^M+qSx`YX|Y_CQ78tu`*2fqo;d+0H|Nb0d_dT;<2_az;OVW)f;;KX)3uZ~u zS1lc}(Fqh(>DQd*w=?EW(Cdjjk_KKeJ={XBZM2zP{rZ&eitKU}^$Qdpn+RxP?X+$c zMf7kUucWS8TsevJ4J*Sd2aH=y+f)MJ*k&kg@GIx!7=PUuia5nxd9uRq(8FD=AhWO6BY;j-|%*(4Oxu);Wfk*30mCl?Q z3#_Xnr}$b$pB*}Wc*m8(ic2c08;D95s#$cl0H*)NlH25$nbMD+?pq(-A6pBA016j6 zg(dBdxo8&nb1bS@UVu=#{Gwty10eczYOP$eoFkz1M|l}dw-RGJWyE>`TA0jfDXF-a z(JgMJXhd0&Uo^l?N9CV;^QI&McInb(g(`dbKqKKxnzXhwqLgL9d?{D{q*Cg+uFKHkapY+8O(((<E)Ae_#3N6N1|+|$n0yq4<)(8=W?kQ22`de&6Dn^zcLu8Miax1c&X1)0 zZ&xEHR+&Yo`A=R%2F{r^Nw-_r`-5${jz$jV4`lt$8yQ1VX9jwpgsZRHMzO|@4fUT& zm4*zMUmdgLU`O5NZ;N;^<15URC;bag5MlCuxI6j@ah6%zh1?9c*Tu;{y>c>fO21bo z;l`LR87$}1(1vXS3SzSu>~7ltH9$rtp_So`TNbQLP3WpvZd9%zzssAIfLNUJ6cJ zH|Gt%!P?X$Op2L74qyVxurMZ{Amhf-J!TzPO|mUe>fDq5jqM{rmOeOh`G4p(vK>1- z#kos~uWRRyVz2Hbp!jlDYfs7|u=Me6gL*aF;BUN{BN_;7^kO3Pwr5Yk(yR^WxUZ=w z1<1zM_dP1g)e8JF(J;(>tBIBQVx=?;ycnz8EAJF>J{g_$+?qeI{i(qGo`=6c@A-I% z>WQ|Y_x$bS@cOu~zdLH#meRE(4m2QUklvIo4_UV=ae8)`IcuCe3L*ZS!r9@xY6d(e zo6)8zCTT6dEKGOTKTEt2eHkGy_q>?(U5SU;D75pNUg-451ZhD30JjTvz1>++D3RpH znz`6mu_Mn)2+i=Rl#rAfN}@M>|Iif9jE`(bxjVF~UqO%g{2sB*ZyMUa!~lx~|6+J9S8)-Zd(YofO_Qhj0B$Mhy$L zH-9mH`c5f*OgR+CvI*^-iU_o+oIvF}shDG7IYlOexVljZKW*FAS8GoKrVu#8HJ^w; zX>6wey88W}n-c8aL7(@`3|dwJd?Ksk%K_03QcMPt%dgaW_O8~aIyN8kc1)*fod>^V zm4IGeK1doulFt1lGq}3nV-V5Im63^wtr_Sk9hckNACA`!+<)DF1tifVYg7G?);R?GLb`twj~zky()XoIutOzv-nqKUBCFa;DwXD z^apzbM~dSGvlb1r?1{T}>3WtZ@1)niwGO1xhf+x}0khG)Ui@8?4mg9XNSaEaQQtI{gC=Ik z2%a`IoJrUEVA1zh*Stu4Ls zR|*LISmM*4@s2o-p#{VRs=q$`r6+rI)RFdVjHIiN6elfO=V@5w>TWr5g^(dF)#p?q zut0ua$tb*Fhuy9Rm><3jrq=&dFNCe;DrmO9rst0ZMUNMRUE03yob8BvPnnRv;$+0UjGq zC`k)lQ;BXCSuK=Ra4QxgArK6ED$(AZt4gq_GTL}vl+2*0rMS_^JS#7{#L+L zF0YEm9gFa1u^#&h^p_+*V=O&+$Y6GXR!u@;V&iUl2I4|x$M1!1@XA%joS>%2O#eYG zD!{uo)d>Gpb;8MONMKC6BH6a8G2A9XNeVE9FxNq)N&PT!JL;lklNtAOj)k4B82%fe zWO97&7FIstR3CmFds|EQ*>`MtUE+%7}q?1BR8P<6k~8=HT&cm2Q6 z+%)V2R~HcIv=p&9W{yku)Cfpe_@4*N2*7`0NbGw| zL57SIE=+!6RfH*JM9Q?kQP{D*p~}hLS|*uq@y}BKA1K8z51r$bHDVszOaI3tr+nhi{1 z7$R=Z10ix6H)sO9`eI*Xjb?`A7;WBWg%$kjW9`N33uF^z?v4a4U4#yt?m#CAoT~!R zPE`w`aGkQ#Dx5Wm;a{@TB$Q(&V^n|f3ffQIh{St!7?8AI1uU;T8C^(O5v+}Jeck1U zubqH8Btuiph3_C%3>V5do|>pk@&zj7n>a{YuQQ%Aa&d%g&i;e#Ey%hj`3#*wagjNb zdESnV*U>L2fS}}%7NIxG8wQYJ0-$*4&%5?>9J@PeE1Pw*^JqR|N7mq@B5Ksdv zFq3qn$1C0ASZTnEy|r`#{^lg;%5fZ!q{rB2| zbU5q^O-u&8hD&>6#BlXB4@+)JH-{~pmF8kk*1qG&-lhBWd?urde}aR{kgCXDOMm%c zGHw8`Md~ycBxV5iLjDAT((2n8`N*35!9T=NrQK3FD%i~h$grgs zf6bt<$^7dsjtG68?cd8^XaKPQ^m&PmV1ftZ8u>js7>AfEt{-XrhnBNdFIO3kSbvEi{JR8lrpy(G)6Q)-|7f|XHnwn{f5E|8Z(_&0C&cZiF6+NtYmb9j699gmP#@}) zg?G@-2FGJWkh$RDn7Z^Y$N`HY)$|;s-4`AliaHn8X*Vsl=sqypO#P$n96B2x0({TrW~{lyAMI>H9K=rQ`)?`Gpug zCxxpQkIeHXf1^A`PV0u`OowyuH*^)OZf!H+nDn((F=G0?E}?i;6pQ1JmYoHn*ZEG=<&b`oYpyTIYGhG{W;` zml>O>?ncgV4lL`$&_?Np!-etL-p6SNH)5kaIoVqRL)a-J^AKOV9KCC{&q&qsAlk3p z+C5{wEiTV(|Lzg(0*zO^I(?`P$xo1prEtJU-2<=_j%YR@XIFAGE9__Yz!)GP_tar} z9)hrI{+%m?cr6pBBx!9i@>N}3m#bT~TWu%2q(o$)l@2yW=j*)45AJ+YjOw@f_%jz6 zpRE0mZz=g(qjinIf@{n_Hc>a>oq1zZU!K%!BcEH)56iV_Ra~iOf0l!ouyDtSCLR&D zO|ytpF#4ZB$EakVjjUW$(bp3GOO`5piuduvV|`3@#r<>ru;SduHq8nUJ-kAF-3fZzRj1GWN@p{K`R*0;MDC<(sYYyl5X=qTj3>Quq1VfH9d$ z+$~#z{w|YR(E1C@hjnaJ{NfS#_zy}BzG4i!?O5w{yrK&{|ILzP)d$iWFki8M5$hh$ zgc*->cJ#qtCWGSbF|UVy$iFUIL@()o#?Kr!PBYndq$7$|C94{?N9F@_L2ply=mT|G z+XGiiQllX5uR6VQwO`SY*e;J`BYn=0raekm0g}O7Pqgfrtd-C5XPG^}A(-uzPK8+bQ@SPY$zl=_o4~gPwcHnNU~%Q?X;ME&v7e0;l4~zA#stmCYcp zS>*h!2hpxTpxXC6eNi1Kvr47@yAJ7=7gKH2>!Vdr^`4Hn4sM?~we47%WqFIGkC}GP zkeRTkG-282>z65`p$1EnAi)CMm?V0M&!LmBD!R#T%{SnEYpVSBr;fS)oSJY!rr*lyl;hEO1^|dS;k3ncx&UPy4`3Zj9U4M_(DJ1tK~sb)T%Uv zzW9rml~v<)YFhi9dnPbP*P3O%Vf(mx?D$a$3E?wq?N zaHzWir0>XTNfycLUxAX(m#4+i4@>7;+}XM1Q8>};bdgh`uVOTyS79>zP>rcXq^|(pz>m29?D+y4>W&cRx>`OMC*?bPUNx zL8$XIXxp?6k>m#X;cyd>2CNHSN&OYuq1=S^i8vB~zNu<)l&o%YSs-Rj&_>FpdlQx| z{A5qed=7e+Gw%cnN4AkzF`1#&L@K5ijY<38KXar%bn!TmfaOm81!!*j?+ z+uj~E98+0gOJMh#h$bM`UpH`-_IEtP}6eW-A`4;-d#-mI%T27o2G285o^+hU-9 zT7RQxh%u+&ee^fdFxk!R5|HAfbx}LrW zMeU4CP=8N2!En5FVYTktBRmo8xCP zB~^VX2Jk_w`Gi{m+!n{sz4Yj14-@PI$CxinCXQ&Ni!!zhUa^`dxtwdr z-)SnoM+}%K=0Y*JdvR=D*vk0)r;7ekmWTji5P}1&*6-1wx_Zqlz~}@-7rXt5RB)va ze`M;H^!Jstasyb`#GL7C@8~nR_2Wz!95R^Ey*Y#qxEH(D z@EGRRMNIwF2{>aXssR24)gUoiig51~(vto5$pkX(bnzO&7bR3X>Eh(JF)t2o1ULl9 zND#C7y)fI)R%Bm)NQ!kBa&(SOG9;aC+VaUx&SqRFx%<0x9+1DAMY>NSeCJ$$5>@EO z=FHms*zkTi>EITY+n_wZ8ZP~uyf@V!*0>JC0pwRq)sJSa<#gM@3{Pgdd z^YMeNOSoDuwgRA@)`IpyTPCfb_p|)@;D(sVoCC_D93Xoi#g(__^qh=7CwJB_%G&K1 zrG+%8s&XuPDXBeC;x9SLaVLj@7fq#-d@^8JN23n(#)ks0&pkGvgzf*Z1jN>jraa2E zckOPNPm$!tc61FCu=HsZg?a10d-`k4T^_#Pt6`4~0+NZO@wSy6uEy}{#7JF`lU4&t zZnfk0WlG_I`-zvVKSh5$BnHGI0)lac8b!}h=gFPKLdC*{GM*kc7<PSYaLpIT5qbcz!lvCznvP@PiORfs`5U+F`PajL_dT|I$}Nt zFb6K9!9Lj{=eZPSSVnf&huKs>u6yjN2=xob zx{IDOC;#h=4o4=i5I0z~j>{nO`*{xxEpt#QB-t5&mPpNVYStPk^oOQ|yXTbtG|!zR zj`PdIVfmG_Hgo2LxG=TU)WQXG5tF&5YgQ6PBSvOHjoq`$t}mjk2*1U^TKmDh!|mq?_eSupMVE5X#QEP~UY<+`y24M9@{DrN^N z*90^%J*}#S`Hu+@1F`SbIGFvvE5GMX$QT_$0o7oSfB>~Noia(HC^{0anvM>;_Kj}f$JVI5St>rvab&J&z!|Ywne>1 zARLx{7z!J^vhrhSRVL~*wo`^X}Ujk|f31I*}8S}qQh3WZ}G zvmu=eDaOgbvJ~;ViJ04LBLCW^eU8*H2M8ChUQ{CV!xMJ|lX;?M&g6twX9SSzAyy~P zV$~WmzOiMu%C_KE)?~Ul_NtT)D0pZ_48icVqx-vWHU88Us-M-r2S0HvmXdQ^7@ye!spLO&x0pMAtD@2&ZK;X7%9et8AnijV=C4vY+!s_VWYjlxo{ zP8N9sX$Zc+TB3?MtXaK%ewwcz}xNebHw2(e5PtupuD)F;~0|T)0ps#cz1Zm z%=1`U=MVt>y_#g>%v*v@%)U0pzX%NgH;?AR2gJVm;f9 zzxcfO+%?Oq8dum;+|26HgUf-S5*zM!-G6&1cn;Way7JBnfGyDX2blD+;;FcfC#5AZ z(}rEx6NZ*tjs4evT3ea2VC|Vx^Zer31V_!AOLb+Byd{m?UYHW`po(oMlk6MU0EWS=o&?Xr*(>iWZywRZ=A1zH=#`qPh!* z$X)u4H9MYvBw76)t+qB}7QeEl(VB^XGj@8(DXtwTlM8qXJt*RD6db>LYxBOs*TFLn zX>}d+11~J!)My$zFvx)~Jg5vaczPaf2i--mN&E zaUq|(aZmVVJLsbi3U=(z;Tt*#dca4}#o|ram@wb?uIQVaYN%{J=*(=8ABOh)Va#BZ z0;?ToMuV%mvoN-*HLZ;kSrZKQiFE6)-@VX}k-C5osr73{KfdaD>|I-qy2~7_&-RHr z0W*A%fR%JiIj9Rc$faU!A{KAoNRxUL4Zg*Zc@gZPSMaE$rPs0Oq#`B7=At-6%U_YR z#lt=J!*Kf18=K-*Cy77B8`q~&HH1MB%kkGZb^mM$FUn6U%%NhpPH0=w zbf=mwl*K%V5*^KT%TZ-d<9X7@IdW~XMW$`33LPbDTxpDCRI2(2k|rd4koz9El)<~3 zd50i^nfh#bLuEAU%g6Wg^-Cf_rYDz%+R$OC;YhJ!^9*g31i0uKoD0b~gjU?Ov#Nkh zB@kj)62XeewgwpXTF;^7l9!ZJuLO2ocPiYln%GVphq1;s{|lYBsL>sAgD&%0Jm|YG>!c;Q`YK1Ov=aY z8hU26@C{tf#xC!OtS&~dYmss3DFCLbMjB?y|Gvyj0SW~SuRRmh5tgo$P7^L~BOi$% zmGsqza;@@!jQfS&p{Ox&2`xGkU{0GrYEJU7w&8eMjjqd*yMQ)00x&fJ-`@8*4cEtA z597k7Joa_GV{{Q;nt;(I)!eFKm{oN^X61~D@{0^5CijNl`WL`JXB2KNh1~p?>|0|0 zo4@Ikj4~nWoP)VRQlRt?flnKO+d0<~NC;r-7vX1HIV*oov$M(3!neSV}XD z;HT3T#SZz$f3wgNtZx|^rzp|=awN+>i-S*KHEiAlDyLjr)z7uox{k#w;hS}f_ZIyr zJW`&lV^uH=QdR?pHTs0ED`hB0fAV;t*BveB4F1oq`1IX8Z3=|z zdi87&F!_bubZM`2X{O1ATGf;*la3!75a}O$bKuo59iC~wsMt!%Ag>%jWo2+@DE86T zKMvSz0$sOn+Dts_xqHkxeg@u}Y#%M|sn%3ca;-Sfw zoD@I9r5*m7fY_r-4tT_CXP9dlqJ#V%Qclc)6y~S$Iv&h*#{O!5GJDIt^={?8lZBTX zFeOsWrwYUbG8NFJ&Px8D;tc-x|5`~#Sqe>y8nf1_(U z=520My`zT|P;+w+ifgD*@=LflU|p6GezhC70EF>m`E$WVWCm|DYgE2!mzVFx(P%s8 zT(S^eCE=Dgi0Iw!^f&5I;Fti}%$&yPf zjypdCj8}@}Wcft0cYdvGS8Cn-k9Hi{R1=zSb zMIER~I=Jr?F$cP$eW)(}Tg4xXA5nQSWSiZg1<2fvCvx5q7&-Oxy3w58u~U|TkbPS~ zj#m^LhLT1zL?%dP> zlF_RHGHri9oQP5G1#kg`8#kVU6R~5jt?*WM-$rT2={jF=rrn;mku zNIs8iZJ;s?O_Fs5LzcZPuuU^Os}jmd75ZneNBRSrH?k{QHq2dbA3C@vG1X zb-ye0xgJ$dlJiYd_;2^6}!|`@9t3--oQ<1{&t^RS_eC=y3-}wN{jL%V+ zJdjn*p5Co}aQEZUQ{!y61tZ%NREX1N-Bfk?-idwJzw=!JlntLp~kzEliR%fFWDs{D#v!-wbf#ux0!FLNv;JB z+!%X$0DNThZ|%1IA1Avv9n12YKo+Jf};tvOSA{4n{Td40We_ zIFc$EwD+PSkdXY0!WmUnGoa*$`^W#^Db&#}gA+Ys#rC=>d-x@q2j1So*+CMmoVwm^ zvVQ?R=^KV-9hobrmFj;czv+Iblv7!F!fu$CF-g0Nx5nNFitMU&1@dxaoh3N zE~d^{TX?T1zshPNlj@f}YPZy_|`99#t?hwHLadhqnW|fTG4M$DE`5LD5+;63ixb1M<>+ z*TBC1DDBft^b2``Kvt|)8;H@=*Qd+hV|r0pHNs+0;%){<^p$Ytpih^3qkKis3Q=cD zXUuuC0$uZ6{nk*^58r9eCx{UA$5nH>e%u)OgM$9W$APzJCYeqX1k@M^@(fB zSTV5rUV*Y(`G|nI+Qm^YqQrK231q5Rfa|y}W2R94eOLa|xp7dVgtITIdJl(|?h~51 zEnvhKC}mX}#L-kR0q>C0YRWOsct(*Y;Ted;o54CDj6F^2G53A_EJg@k%nWp&Ygq`? z58g{lm+W~d}&nR|4 zs|!NZOpEO^xNCrCXS*jmzRW9gKU?19d^ZktWZ7xD!S-eS_i`ItXhUjXTrF zBKOK9f9&dv!ZQgV5p2^+PiN+R0w>lhCR|piurGhNHafv`!z>^NrK~&8OpGG_0Ek>5 z8q#PhW51ujZ6x1!xSjpIdBoyJ=wei6r>7Y12rIJ^8rDjK>&AD;bCw5CX-+h<>FAM| zXwl(XA9xBr5&X&mMX~0Yt6*v<@CPP^{bDtk2os@R?EkeTH)Cz@zLy-h#e8a&U}8?s zP=p-yUKGSEcxi3DG}`@1fk>Nbn(!u}>8>cVn|aUQ5sO8kvxaTi*2ky+lF=Jwmlfn4 z;tL8=L8Twz0wFDv=x~vHXu5>eg0J0*iMgyP@X4anAnl9sUFFh;%ZEP=%z7fK17u>V zhKgo;#N8_Ln94ZUY@<0bhw-<9e}wQh4Iak&ms*y|4F#SKnneon^~7ntXeq5@_nkGL z&27+~#;4_kvRNqZ(c2C%)+DX^haNcP_XMqIuxm$^TzWjDE?~cDi&}wlI-@MG;4qix z7_r58(P;kc#$o1)Ki%YM0rwqyB)m|2F;w=$G;u)&?r4tnq@1ZUF#GC!nV-Rj9gPLi zl%UC_Ux1Au|1d}Fssd|Sr`?#^81F>}7EO(Q0r(IoQ_RMP#+`qWALfYu?`vn#rlQos zg@0&4wNyKWE!)ZNRDE`R!qJK&G4H z_{_=3B5{f73*9M+{m>VcI4l`|?fY2kGsDzbULTVBPsEwo8Edso*JzTJ-0fpJ9);q14qim48boX=4^O=li(NY|3KwE#DPq=__CV z{E2&lFq7$~36@XdHyqH)Wmu9wnp%%Nn>MBA<7u3@py1NyYtwts^XZnI!xA+?sl-mW zETIsxeQ_McG4(Dv5ZLn44o@~W=REJ;@*;*jU_87MG$e}n<05>0PxNe)2|BpGUj*K< z$fbevXl12A=0Fa=xPZ(paN1XLp&o~RsKPTX z9Oq&c%0YK&7bb_dUO#A6U9aIAgfkQ-k?!_zVtwb1fx+&6$(3Vhy)OB8#SD3(VRPns zlVI1GybL{}D8k!cr2-2$Kn!Q$m_zVY`Wzrir~q3YZ8U)n0bRzH1EEtRz+R|--jfz+ z*@%!{OSwAVBi$VtdZMz#A!2>V# zZ-q-zNO8`#%&qhg=m7J_>SVM)&8kciMoojsQQ`5^f`qV@+^FyLaO~QF`PmBmi#!=I zjzCis_z!ksoq01aPieC{LW0Ac?E#mioLMRv-QKhz;Ol#gb{J+Qz{c}4^~P;RnkCX^ zw;AZFU9&yDid?^k`r0S!f6aW;@Jr`vvB$e49uxGQ$F^`3H7}#~0F8iN9ei>F6a}r^ z>IBUkszS{w&1^e(@E@=YiEnF{ZOPQ+Pi=`SF|Qo|2-XZ4l4yB})T}y(a%>xut7dZ6 z@~`7ws0nE%GszC~_wK&;bv&4s(Eczm%16d+f;Pykh**>E;=7b}a|`;>=KL<_Xgk^S=E`?z|LK z0r=_%Rd_UJukqZA^}nMjZ?Kexc*Je_2qn?#Zb@ceF?w0%?9kD}eCNDkp0(}#(Zd3_ z`MknyX>TN;+jzUZU0UP~A@qpF!C1EWd~3f4y>P*n#fa7n=-v$}y)4$%xXg7MZ?kYz zPeF3kZN_S;U`Xj%MR@w+SA#F1aXnbs$qWb9?liVW`}T*~S+}g$y~e(Ab-hZ{F-!b5 zBid^HnmNhK$-^<8{G#Bf7+>TQFjjwP{6LS9LA>spXa%q2_F4!iEXPY=mo>Mv`{21v zw46jI^I}wSB4lFpb<4A#;YmPf0U3;oUG?e~(+>kiERXcHwoJ>`)Hj(gi|2)6Kkx)N zO!K%W`P?B%GZlM|wICvaIc!sj(#E1AV-l@Tbb(XB?k&s91jE7eoI#WiRY=G3%6|Fy z+MV+V)u7&~lsSgLe%XFt=p)-MZ_iO&2QimcneubH|vxW_ZU;BRq_H-IsKMu?E?Q4M& z447o8HN3!>u+FJ_iyn8X+PStskjaWsCqA;{tZV4z`IKYJuO$*kRlNvmq>5ivVmW4F zYWnIV4Y~C2em-g4b?Z@ZXnR9z65JgO6ydJm;dgPiZ~pQt^H=Y^L9!2DXkY&V z=OMJ?s!C$$VSiyf=s&oerdU1vlUd#~kU=8@#B5{W@trIm&h30O4~%VgV9h0*F;0ak z_Dn-V+pyu}1t%yLwdOZOG)Jm55#cMtJ-*Je)8P}DS~&O!Q4lAS6+=bf$FzLXiAtnx zD%xx5J|`MYCdG(>_J{B83Wv-dfqtM3)-G-8o(4OuAUGbq8GmwhE#l-TYHHCS-qMcd zYDYaYI|eJ}OJP1ntC^X(9$1x%G8;PcA!-SYd_?3Sjb=Y*id*ZR4ukW8Xi6Z&DvkPJ z|Ab3ePOP~QrncAIw|yq8_cI%`^B&FkRD)qfhTbOfkvBBiDD;TK&xQSKTW(ni1XCqD zW;$0{eBbQ*)tO|OL92GjcD-`JA0zt|x%4LlJ+W7_ed$Z2{jappqt064*=KHx0^Et#{rRr|F64#aPMC51lFy zcD0yHokA9`O@w>k+=vcG!3Tu&7s4vS4*<;qC?b_aStLkIx?B+u=#ZEqByeE)^Z2v2 z88CCQ{&A|r4{$Uh1)9?(2FN!PDsa>qo-1~E|B-@)q&p|7>>};jOf`24oYhcJcSmHY z;GMZk|A2u-6(Tuk&7@`_W&HeS!<==&yuI<_M_$3sB&hAEHPdD8CHdOaDN=1C5bA2( z@MT78fhA`AwDfpZevbZ5OCs8}uqVZ?A!oa`PWmmsEYF|c=?gTF*)bS>TPdXZ?}Do1 zA3B~#%<4u;Ev4FsuwSrOEsE-u0dg;fjK#k`$Q(`?0}?!rQe&w#bH}{1ng{v5hk2NI zNL63m%f$ksh!gUXdCO+(EQWfhVWqL$3+#Ja`x3#s-LI_u?7udo55l}-1?dKA6CZM0 z*Yv}Z^gTK}mm;LkGe2EW`erWFn`RDrm^r6nQ$|hsiBaD{N9~F+y~|U&#lGyXCM3kV zGapFkazLM6Va>Hx0GBZ;QjAJRhBu~4!5Qvp#ZpOm{~B1q?0X_K>RSPq`|%+$2;BQu zTA$9zXrG|48qI4OV9$4?^XlOjWP$~bc{lJmI6WsDU|@*z65&Wc>Ke=vn=$T-Ywn zETIOHsApp^VF&MigX3AsKQEa)SZv4FzG_P#o=#W`dU1qp;n#TNf1>1TO(Jqo&xvBd z>Tb;=5~J8U)vV;?X8XLQ8DYA%rTzJ|l-J4q>hG%_cf1OwZV(I^_;O5{FsPIJl^Cxx z6)j-bq-y-r!OI&?Tf_3M7;Do1wRWN46ls7OzAn9`2<5%;IPGBydD(YgbOm_dr^TjfsBE zMn(5~zpIk|W4)agFD2bhwbUuSfFb$~2K0TgNNat2%QTwH?PT!JGE~Q+e5gS>f7ui9 zlRC1ZexPi|AcH3zFoe8%6s9q~$CVxXlV>ALd)KjihoPz_EIszId*oz(lHM2j8;s!n zNw3Y^3-xlU*ef5guCNk~w(hOx4&U9}8Z;w#T8O6*uPQB}cEl$y&Jja|pHc*Gk`_yh z%w|oe@h;0|S={2POrefZYT!p z15!bi%JEPVYif(FHsn=qQBzlna_+Aq22a-oB{veXO+I}WvPmEDU7_uaKFg`3(ZZUg z=OPqxYQH)*>d$(L<=&B_^5?GTt$boFrQ2IznAI@*-+X}HrrRv;K#sXYr^M-f5U)SI z8FOr5}ZiqOri>&BnAQ3g1d*)+&@U^vfHD5`MZ%YV6 zwwjM4+SR(Qc;i}dB`b~$JhRpAFApfHNWVUm3&P}mVe_%~7?b4p9%)~tjMz%x)$BU+ zV~VpMU!NS6u*gjIxD@k*S1taUg57v2G(6*+8x=&&0=R<2I(^sH#4;mK?N9qe!Sinv z`Ql6idpmN-$RQg*fB>wIG5>MS{H`uU!h^RLdt~#0Y?yO|q9?XEt$jBL`bJYqmf}(v z*!=!W7IAcU0jYIgE{hU$Og{w0mFSH>s`-=W(>XbGMfsGYG6cDXe z{piVZ!BzoZMNJO%vN;**kxeb)O=jG=39>WJ2c$b>7`M0hNxl$G%qDQ!z4^9i77Gl0 zmwyB9)vz+3cf=w-%hdtJ`X5)r!oP^uP-#|;7sW>&|FCTp!p2j^lNnMpqU+CMGZYD3 z9*~#=`ZeAzYxQY<1)zGKVV7pp!(8t|{>^vxIDja-8-EZSbEaZn++h4{%f_N zWa&P1>4CFgnJs5goQ=z-BWs!5ZgZ08HJjZJ1F?O>Vye0PJ)%90`JL8{-&Jn9$cAPs z=YDuMoT2X=ymokB%d4(`GZ2`Z~N|bDVWbGWXuAojl`+x&oHzECx(6} z1+)(h@HNl~=+vI0xm>fL^#Cda#K{QJ*1A;GhP^dUyFBHs?TI@P2cn+=aI_q~vMPc1 zP=owj19KapUB-9lWlyf_=jxq_qgXb~*_OYKSqix?kdQTPWQohFd$*J!V$?$^P@18* zjG`paVTYqAYC=QH;{JOQ7wYQ;o72N9<`paG=@P@n*{gH3%ZHZL%BcRO3=jHX=2iKcmPVr_z z^o<3N_9H6UL+%``-F@izfI1?AtcWYS^uN9SHQ;hvD_k^jqV%5_qNlBU3{>0n3O9$p zKB7{@=Nd**it~G|DEE2Dd*Tv}cPAKyt`Ow)TP#G=VBCf#q)fNEhP-Esjvi2_KY#1L~g`fjV39_ zD8BqXaD8>IF>W5;vlerplA<<6JUna*$)&m~@J$ieR zkDTjES>0V#PBb=MucC|7c(=Tx=UcmevEOwA`%mYVzSX*Oi`T`!T14ES*zkgf zN_Qs$M2f{ua0FfarB_*+A@!z_(vY;F*(5p<{rMsG2ajFeMcNG9-`?LUHOn25_t;fG z-ZXVgdj8sqyibS}Rn4_)Q#%T4-#;FrkJYz_bE zkC@xK%~#&2;(ke6p+AsBw)8B*=wEo-rRj-~F#<%MyRc;4pv*Pv-RUrNG@`#PTHf40 z7jvNm)u(uwb7M9U?bz>2C-8eVpZB8bWEAWJO()VsciH}oAOVS17#My@^=4A6y-@qW z;G-8MQeeZG@6fusUN<3;k*fnse~bQ#H%oQ&T!1oevL*pJJ7)w0_&hw8%(u#L>gPYO zY@wB`29jq@7Tr5wpO?Vdo|o3Q=z#NBD8u5(FW*03CBcwWeEW&U)uYI?yab3BU#w63kS za$iYcZPbShx!t;TpaX|`b!i;?0P%B1wY6s(M=d&lH9$O-c0ZX2+BD2Qe6 zfW6cvCY31gp-+z3KmLIKHn~ZnA2U3;ZINhMnWosj`S7_~_M%8+BtGRWzF2JM!;@m| zxVXdg_J$+6KrrSairu1k$KXPk_VY`#%9tE#$E;EsdfbsBM!zD}aQs=VWPdyL4s<&w z<)AmijhLljrCBg(auJjy0Uk)w<%3SNL|!d4NS{EK!q*mghzYAsqqqQlyJ2moKna?* z9`H{T6Bgb<^!Z(t>)#byXMC5ozl;^Mtw8eHA&C(SyjT?nYcU&zW4~mBikHcM;Dfi( zNP({ygQHc$&*b4QVofFK{utTsds=4dpo0}OZ%>3xF0W=~9=o4`ZoSc*xC50b0 z4?hGtS**uM9C=Oh6D_rI_vMT%J^_oGhG6&hCMKp^dE)7%aSA1__w3P4nB&z{mT&yZ zM0#064&fEXyANsL+1OB1het7iWqz?ra`K*)0>!f>iVtSDA?xb(ykaHwr|j+*1v)K+)$09rw}&+OKdzoO z5{zr`uQ~+7|-GU;Az)a?S7irg^=WUXHy?x%6+%#4#4l;Z9bZ{v``>3G=Qo zsCn-vulq$CeIpaUuIKO4j=mN6Y{Y83S)WfDIVJ!ey-&}HuTb{S1nB;PH{2HK+Giz6 zcX~#OOz0J9xkd^!8PkpQF0%1{wF?Ivao(dRZ}anmc%<^UxyI7y;$7a<6OCP$WwkfEBOkAeq&O7|R0OuFM>Fjz{5K_$ES}oSIs~jktUb zB{aeLWlyImWs;@}(#PBUZc85W;0^S*n|^YnyDDb^rx@{Ny+B%hYZB8)36K7BrO^`2 zzT!yV6PfMhg8*|vMU{aMF7rUVa>u$VB2H&Bs>!Dgwc8GyNylk!a^>c}_#6qu$!57& zLnkzJ*7j>f-bk4`ue(yG@uq7Tv6?7z#_O%HbC1w)yIKzVKo4 znQ+sE#E3gQ!9Uow^+w%^79fVjM@gT;7*C5FCn74}U~(^Wrwwmm!D|dLn9;d`RHB4ItOtFR)7Sk!@Nck! z8qgzo&Nj?gM~Ky&0Mg?}_2(Gap~{8It}E|)x`Y-Q+g;&S=pgantyR#;e6RbT9$+>q zYuK}uyfqGX3!Tg%fR{6~Flfqu$pEpcX7x0?*31gX&Nf}LXJN^^w3rF%&AtZb>L$uy z?4H$IZ9t>8Lujo!P=Z2hcLNt*tsFj=E!X{gc_zBV;JXKmIPX=jBUUD!TMq)yk{zE3 z#N=pKV`3mZVFLHO@BhrP{H6$aNf0rl7MQ*Xts$*||EN36_UO^a=l34d%gR2qTrUlx zJ%>^Osd!)Gr=Z36J!gQH-LABkgvS%Ep;^TR*@)7}V;bntM*S)BqYBgy8`-D}t zPu>TdsrDyjRXucxw>o;a`)A01)?|aaZ=Oy3j$O=}nMLN&;_bVelD19kL>&<_NTuB` z8kB4R{!Z{%*V31o&Bi2~726`G&SqO~o+yt)p(Ci60|XRKqQ%ut)Ue90DNXX(7_Z=8 z2QmPMQP^Hg*0UDHW!nRjG6MgxX!?8AGMqI`KRET`JcpEAu?wD&^#^E}V_q&~q!Ae1 zGjKUBM#BO>;5Y79F435oB7X7cT~;-IWhbcO3QZ@^Cj1eQU~9o^*!E^`_vqpIT%2(OcI85NnAY`D#1}3d&#^W zs7(-o=k_4r-b+2F02M=b8GQgR#ZkW@$gR~2)bPvSJ`SEMVoa=GbNo8+`RIhkU+%{E zCBB=De5(0cNo(>dm2i;offl7Op-fIY^qyQ>sWed|j^-x88{?nIAphboCy4hRLwGCN zUjp13{NmuA%poiTL@JtTqlK(>tm|BJP^4r}WF z|A#R#Kn%L3QtAllX2u&PARr)&o(M=xx^oKBF#!PqVbVD!-AuZqV{~^ngT?!I{Cuy^ z_rCx5{c~T}{l|6&oSltvIIrjP`Kaq`OUWxJ`Q$1R^Z>)Q{eBY|nxKxbcdh@W;xB$x zYD;|~WPX?^vQNNM)AZSksIp8xd}^Wa1?IT`1zZzUz-w(LBJ7_hOK)_QKZ4~v(P3ER z9x@&R;*3>(d|TKWIKMf+?KRXg!4ZUcPqE0_0?VmwHA|gGp#!b(J-Ffo6tY}SG}l9S z#c0YJdlGJ8)*0A$A6YYd&ft5W7I|&|s$x&fZ4BKMKu^- zFA7&Kpm!J=_}_N9dEeh|(3w0=Kf0_t{4wE8Y0OnA8YzXKiVU6`(Xn?L*DP7fxmQzEDuvN!(oRxSZ@UQbkK0$`6BqGQAISWPEm}!@gR&65fv>}VL&D6KL z1lj%In6)@>0Qy~dLtS!SoscP5pJ4d9ZlAl$am4^yLPPAB0yX{0AsjFEyjr0ZRUYJ$ zzg&1&Mf&wP9TH@6?TcceM{2Lcb4oV#4eE+3hJ%!cKFq^ew0i}NFL#-OJVd4*&l*lAhxIp82X3v_y^YbJ52cLVpj`iAOG?2zH@BUiw6Hqf%nWIi;r*}(cD6)GSCmz>{1YEe>Bx&B!XT< zW$8IQ&&DTtrvaU!C{qik_}*zCC;e!7kL)W?+=#&O;0yQ~bHuQlg2G-~p2$nf1$o{L z>sxoF?9)G(tx?$_4v{BA1j&8Q)5Yw{!W24Pd|Bl4xH4h^o2MXG)cv2=8s4}uNY5?G zd*lDOS4d9W%Hk=Xu5UvlKN37XD23^LckYn7kKbj{2qMVgFR9+q;MnbbToz*u&uR6Q z@Uv`Ol!~diTbI`r6gsgDm>>mfpW1{S!pE^DxP8gr_LnxivYMx7r>vtBEx#^ja)GN- zSE*oGum!z3xnJMIzFW&yDYx&qDa^zv8vL*k%!AYcy#6Ke|NN89?Dd5g`9Pk&cs&~7 zXBE1>1HKxTs0hp%N3w48JLDE6?o8O_*cTXNwU+t6nmpue!@$BkkS#C;Q0?6&_kU&q z?Y=2Rd^1U++_p#`(^|TOyqlWuOY3;yiVpWQ&BwWgjs#g=$uZJi7uHAEnq?Bow~& z%~TL4oFStL0Bf>x!4J2GY?}a_o+Ld+lj34`+SEI>2^j!S%|X#`l+ud>l?hF7%}--P z%7XRmZ(l3tkgG5m^l{1=(a@0xeBFaNdG=;<=E#1)p+JBXNFsp?ln@fg0n!oDz*0bFu{bPfjdLz;Xq4n`++5uQ-(T|XFu?XuriMcFkM9I zl>s@#yfPl3PEDz@DRz1!#|V>`r7!y;+9E{w18F|8voqXZ!KFGSV)NS~;<9MDYXIyW zsk67k8|PE=sMqmnIKKGcK1-zhh7(l5Q%KHIjMZXX~8v*)nZ!WHcsX*eW z{__y{HWk(2N=#O1Df&%y)XW4^RaIO?reogUOIqecSnWj_AP9c;V)5j* zarMh)3PZpvP5$pmo9xBxLW7l7>9}kM7C$!rpTEXlJ!(b5d}kB)M{Ih_s#kXYHevsC zJW8*dTm3jT7Viz5<3oUNX&JwZP~|gQrke+CbNULK@a^ZEeA$PzVU(jX zq)P?{O0OndLJRl;eULApkqA3Dr)ngmi0@?0cc$!oK$~}q`75(jx-KmpcJ_GsWfdx< z-G!ER>nzP3i*Ls$l`0L?1S>IH*nNRrDI^I`^$8|Qz41KY-QHp&A=VG-nwY)p0-@%8 zn9f5P4==6e5jV9Rha0WT46?7*6kTNOL;i^Cg?O?~zuGWI; zttsdpKv=GtIo^Ngi-0Z&1-&mFnjbFQBIWw*KC$L{S?Wxa%l8xVcyZGx5V1B%!j~hw|g3cR`Y-yt9 z?panU`Ru6yRCPnv|M1ln5>=nS1XdO^CRbUpt|!4xY5=Foe4yt0jfY^q^=y%fu}T|)Ou&;H(rDGE)fcM;H&iU7BrzgIQmp#i zciMWV>CJ}_kQOEY$IV_%V543Ha>3KJmctX?TL`|Yc9ZVzyK6Gz0P0frd%GC033mkI zt%Q6okMAc$EI%&`IVyM$L!YfbrlyclO%2cY?3;{L+bEo|n#J*tQtae@md50FQFT%e z--Ev<$qbkieCKNgMB2_hGDGa+^~}v@A1o)M4nKhpfN&CiyBi)V&Zn7!e#$_<-9f5U zXn!*1X}T!eSql-&0n}4W<A_1!o=sn_ z7f_0P*hZZ<(4xDe>0Gy^HY-o#hbH9g?ZJtXc^lH5q=Gndf{(H1oPJbkPNThC=e@~j zhwGZvpSc3?RIquyLhK#Y*c;_e?v#ebRj08!iJN!88$+tAIU9blFqDsZm57J`Ap1T? zgX1ypFR|H)utleEKy0PdO;STRJttkF+tg2eN=QrdXnyOzBUbwh$*;8Oc-ypbZdti# z3U?u-Y2oeW^DN7}L;Ad~dv(!kpeu!<5?NlbPX#wBH;`FgDW3RdG!p@;(Z5()iQk%- zt2px+JqR^h198Z}eojumbo)G)B>nY(Rgwl!Ux~7)WbAlN{rZB9>b$E1Z2v0%XGM2yEB2R-ghR$HI0ud~$GyLUMHU1Z9Z13yJ`X3%) zI5_`|t@k%I-@0nJ;aTtv_D`{PJf{@GDy7TW?g;>3!0vq41&9N3DNmK?M5I8URw@dj z_XFD#z3I6!tz(ZNl>Fn8e3MD0D+7pAWTRvTr}fW0-v;8i1=p9?bb0?$9m9)%qB7aFXq``wRmHZ zWbC?XbN$*n>)|nE3HDCCUwI825G+$sl^GGr0}MXgA@lH;F^x}3u>wDF*rrtz4)0!# zv~g>|CCy@JE}Z#E0L0|jCJfy8BSl%de!OdXx;e|y?T@SdUFwa754(hG>!gA#ykJ9n zR`1+=$OKNi^*upiQba?V{n0f@BG#L#KIm=*&#s-$Atic5b^1%To0l6}AJ^di=fk*?Xiw);BO^E9)7n(Mm?q-|Gi8xAhL79Eg_HN+^HK z!;TAFD=b*+ea^C^TM0a!7cz;(c{^=&b_o@{KCLXYJl9pj2duvS&ZAGA;eaSi50g$6j2fyr9A1sIZqHkVNw~B6H1a4# zsb^fp7!ZQa@t=jGeYsc4GLe;pVyI5YBH(giSZN@ivf|Uh1ewtcIEM|s7rmkRb}>As z=TEF3>=>9M=IgvK%&ru+^)Z)Xx@|_z?K=|3B8tY1=eRd8Wc-<$1z?>m(OLN;hbTgW z>Maqhll4W!E_;S=vh=MRpKnwv%-HpLpc~bE#7Cyg}LITrA4|P&#F4_E_0sRdti7ocjvxsOq)~oF99EI z3&&4e{gOm8RB!qFBt4{73%N?adRUuXJf=wk zN2djYJ={GB@7rhUa)q_OIv}$4RztE7ffcn0PEVU;-4qhjMpM+dyW{jV7Ay@F>9y{I zWA@8>RwrMgzdrWyUS$}?i!Q24#z+am;$CO?$zKc%araWuX0t3-L)1-QZfoS) zvbomy3TwmG$}DVASe;fz?>pbxP^H#@BTvhh<8U9V1FUxQ7IOoMk)=BA_ z!)x2DvCr6!VE0`2Rl4NPBw|&(86QB83lV)`rx5`5$y`4c4@^#}j?Pu~5q%*O)9s*- zw^6UY3T^5!H9W-Cb*7$pB4@rXe3Cz3)h#LgmkREF8FD=M41zH?_Ib8PE_!LBS$!12 zNO@6r*D!LNduc>p5J2T8izrX6+(`c3SsK{#XO?;db`^L*E6b`z{R9LQ<)tUTG z$K7X~(Z2h&2H(&R*$f>i>t^RktGf-4J!1BLY{dK{|3F7$2^<--I8&hPy!(tza)x`@ z{(E^V`L9d1pDtvy#Jr}H8&C-5@U+*%fFphq=ycxI$*exjcQW=Ku?F79#iaz3V-r=h zR}N2~0S4HO$_UsmXTW6=eaB{W!u2Pu-1g_xPp;g=3wkKWU6Tx=?D`6^<@D5}!~aSs zawhsWMP)ekx0hftQE)xRx;T0I{dUpx^ACYKn#xDi;*kY@T`)5~HT=R?H^W>NO1{Pc zHiK&N_ng+yr6mE?6Px||3=l7y>-3iod>;F=sXlrPWmOaS!K{++3)ms#@b`6x} zJ^=|lLejMquO}I&_zP*2HszgvHuwgB`r?^4emf~2(PylOQ5pQ-2sTfocOI5Ubc%)2 zm=(Ngd`40O^j4CNq4(pZGvonFQi!n1#t8^qzMa-VGT(nm5SoXFxqeSJAFa4srna_Z zs}0oLci^!luLp}iEGNe(_acsRPCA(QPJH)4;{mr>FA2_`t*#Uyv-~XW#3R-8X^_Eo zxKdYTe&&Un5uJ3U?goRS0;KB8%{!IUn?@&DH`T6r^zw!5Mh52=q1Eb8@WH$47aYsm zPxWAJy5Zf9Vfh3&fVNN(KZ@!XU726rZ#QH6lR5i3?zM>6$ERHm)ged^ z9V1#X2n(3VC-Ai!w4rDQnq6ABgP)MX5?q}bbGBs2!_YM=68pA?b9uY74H+we7&UM3&Cx!=vsxR0B-(! z6MZcc<&tFF_gyCB!yNe%GE#LO7pi6Zw#vS|bs9+HTr~L%=s#-86l@FA6?bG&x!B+y zDRe@j5!gR-GGo zX7Mp@fW-li!$+AZ{^{`wBL#@`z-D!K&`wlbX2tt?TdFR`L-W)Om{Tw7# zWuyA8_dszFK+E;JvTuOR0G#YDaZho?|%H+`i3+uO@4_jJxahkHDBZBItJAJz|0LP_%`aC2LwK=j6qCC=|A<+)F z>NC04m)fGq-$@6Bv!A3%;9nzhn(q?~7|}lYCrL*_cN2(NCy%coXK0%DicCpY1cUc- zT1{BBOeTaKPF|}khoFR^!yL_f*hBQ4w(q^*`8pieB8zmdRK5=Vaz@_st}IqSrq!eF zZhYoSlth*^^XDWiBHovbn6Gz=HT>CTfiB?}H#{r1AMBC&ci-=SNXkEfP3o?-cZFU% zgReCoa~@~R18B)jwiB27Atj4pF|F5#AC;Yl*p;l{c>}=tn)Dp8&o;k(`o%S1r5nK% z7X%S~=C?`bD(82xS|i}FXRm!BJ8Rz8bX3;6^(kZQ7dIB+%7M>Z`>lS}$AyEb&%@>; z%vSyo{0fEX;ReHxYqM)`(-KKrbE%aI-sAo8f~hj8--I0<5>7w-OGUIFZX|&B-83$2 zT+$fk$m$nFuTrB+iz&j}8xYo0P}JyC1p2z`;{}%(DP7qr<7-cznflYEU2V|cSBl~% zndMu@gVt>lVic)@R|O?Gewtyt6Pj@WCfvhy5Qc=Xazw5C<*%FR?Rs^}Vv%HGo?YhnQ&J;c^ z2}g}glZl3Dm`P`<;$91(+I3;(wmxO7yF@ASdBkJNnQ0jv<|BaJ@3tV4S8@1{SaE$B z&;F;0Z@sRV1gwEKIhbAykz`Fd;u9?y;__Xhcz&OwwRddDe$Nwqxq!)|eYZr{LD&t6 z<&_`yCYpzNjMXqe5?x!mmb+)=;{k{6(_4tki;SKj*UO%xR!8d=TR^4IKv(0wcX$K2%+*t&6+orqQ+Xs#RC;-Y zp8w;Tw<=}u-C7}kQ_YizJ%)!K#61w-O1)1`AVG72V_(;m zkC;)1bUy7wr7a#~CGc`L7eKU3l%auLfjb%^V*lijkEFyzHdqUJVu(=2 za^GpZr?OfSfw#yY$?<(m`tp5u8A?`jlQ8hDNMVkeUAW9(Mpo6817ie6F`^pR+h3*STD9*4mwv>kI+6;e5KRh#Mgr{-nPZJ3 z_ajAeDEX5pSsV;x($fI z66w;vRQD%Q=YSfwBy6+nFq~-iFO?e889taZcvW=6%T+@8F7u2s^TYf6f4rzxEOPNmt-~8leSxQ^}Iwe0_n*_lqhv@yyzVbI*ye=;xsCO^GLb7T#8ULi6JeP^4(XeDvN>SA-Ax%SVU%7@}>=JqCDUP&_q z?;K1+vcMu0tL_Bb0Fa}DMRzsm0dg6AIqStprDNvKdp%3QJO7Ylv$zSQ^{q~fd(Y57YKa?%mZ8j=IIRYSFTP^SFn9m?e~;ol&*YzpfAfjoj(v^ z;#<<~;D>ji?sEj&auSXhoSV+o6Zeqw3*9cd5>XGtr|Or!MWN9b>qJ|T9Ioa!9xtXJ7r0JX&~u?7>^Q zZx`lN9rZj2z7UCPfyHm?uD(cG7gQgxkLjUwu=FiIi-NXuK84dxguH8>{iE>A^BSZM zndPW(Wlue4U$%uN2x`?h?dU?9^YTTcjFv0AP8)bvi*kd(cDO3%&4;cpcSIE8HfHbnT_J!0ldXiE2de94 zJr&j2as1Ga(JkRyNMZPQ)`ZZqdcKDnCy%CFpG_toFl5ZZC-1=t5D&wqgnLE?r5{wm zy|xyBVT3F7)VtwtUg)Sg5RiVJ(~7dZg>}vG&AVy1!TNEV)foDNllp~Jhdj93RZUN9 zaK=V5Fl&)t{))>h)1>{_+b?QF-JY(g6`$Nk>5SWh-Rj9oto)s zIVb9m5~JMyzJRm)2_0eHbOH5+afW{Xa+TL2~|UZtsxVrB6~MWLb;r{iO%>Y(*}B_uxC=W!=7uFCj24Mt$<-| zMv%Z|mM01)_-SU%`fi8+5%J@|-8f|FS&7W$kkzk1u#K$O?!1zJdx~9E5ZuEueAAAH z@Wi&5j+OvM2~2MBF<}&|?a{}eObd2xRTiF?%=IbIQliL_FDUj*LJx2S+0)*=2z0_1 z!yfCXKGk92`}vbv5%j&Czc}5$cgrC^BagR1jSNUeZ1{##7n?Y5)({nvu7@4IeHm0G ze*Q#I!Oz^^P)CwKR&P+hCCX2~e*|F7#Yl_z*>-1pemQ{bK3f zF<@896y?X*ol%%jW3s;0E&JgKwPg=~ka{-Z92C_k|1*OqK=gQnH4O=JKS4i71;PLfRh5`pokcC*=f^$6Nd zD_cy(2)zKuCNWh;XGFWz{J3M3(*$C#Kzr24FQM0lKvSilsu}c46AX6!;Q>fSn79Nw z?Z?j75qVnn8Z6{$?-ja7)V2alSfv`#<3g-(q?cn10X|1$j|4(2^pED@QSkDBM2OXH z2sfbT(tUnL1wN6$u|aH<_9QX@Enk|qr5prp25IXTDc;Sw(Rsu&w3?U9)&(Dgq;CA}}r%20D zz%64s58z<=Jy#S_j^Vd=eSI|bEC==7+zH$%3!I#pe<|!2U`NI_t1s&e!z~-vI=r49 ziN6R_dkhxgV;&BVh#QhGZKm9>*uU~Up0On$I3o4!X!4_X&snb4iK>j)iFvnFSNImy zLqBi^)dw`6lQ{1e>o3R}Idc0B<5RSf14_pTa_xd1&^}t=w7tZoHxwB$`OR;=k8@@O zZH!sYpE0caD8+@cS>%pr<>GSH4lr@a=-Sd{tSpO6U9+Xv)N)Hy0Pm$nFQVw+RtCpk zWKv_jS;D*x1E-2|&Ok4u83<(Jd%yOY%B|%E#^JJ&WUW1cqf7(%oodYYg9qQv0kSfk z7dfF2#pD5fwZ9s4Onb?sI9zkke&K1KJz$Oj>4^Fn^#!)Z4r(PdFti@F&twQiaggxV zLhTC82KsrGtw4KP~j>eAQmS9$BX2)bODe~l|A8H zbMQJd;F?UiH|2=O0^L*j>Q-8TUr*}OX)0i@)Hv}a!e#oOh;O?~9o|yF*|Uo0ykzev zP`KYi6G=bt%O(0cP2sKQ)WuhEMWwGRpDg}K5)@g9h?^I$gCA#R94I`Av>CT>OFB0G z4`d&@hW!cwKGexO3gTA61j$yIN`vH3I(e%18D$_48G#&91bMh`Zo=XC{j1Kg3kUok z_n12-9EnM5co!g%)Xta8+TWtB1GEc1hJXO>203PE!96IO5HRm83?TC+vA67P=iy0| zaZkQWg&`u)+>R~q0XpX@Ep^=k^{rwN}Z5*wWIgqInLUL{4D`L;Vd+{}kf4(yy~%zahj$3_~zi~oq) zc#!TcpG1v7&LGwLXOp!uP9IOC_{CLp+*PL!4=6QkeuDVq7K5cz_(8X<8D|)nF$t4o zKt|mR&Iw4Pk!P@Ke&%pnwZ02|T(EtS&KzsLTk-WgKfM2?a`7u)`jA+0kMHL`bLT-(%503W+FE~J zNCJSmem7tj}EOUoYKmI&~8T;$cdstiUv}J z3RngwxK0L#>h7GRP&f84Vu~U%6ZEI;ZTvEJD}T+oA7T9gowl)d>qKi?LE)@g?gkTW zjq>Wp*e!YLUkfFNihnr_AO8Lg`}q9`_pa9CPdvyWfR^YQIiZD9?v<;t`TJKcKiv%{ zIa`4=nG8DOk~e--C5`^cr~C}63!kn~`D76-e6IE%?T+oX)CdKZd0-w6_+SjA=8Za5 zcsb2VT|bN&#du$Wf7Sf(A&7kseo0{ob|jBkJ85`0fITW$`*H#sJuuW@bFrFM`9%uF zHliYMH;y6xI7U}2wT<7bIfcwZL#xMY9|9K^YH`Z0q`crKr8=%OVcbu$Wch`Od*ek@kvgON&J~IM-s;C&N zTGcNbW3KrZj(<%(I3%j1b_o=#T9a54|D7&9S)IO%oi#o^MlnbtItoyv<=2>CI19Ma zA4evjzn>guZYT-%!~l1LA3i5?S?IcIO<$1eaW>(rK@@ag9+1pYsa-wWt6Jldp3Nd;-tqib=MonQa#`CAg9bTG~I{$x*W1!rg0XUl9fn8E>I> z3j3+XrM2#P&1ax2b8gD9jFI>7ZQFLoUERB@GrtzAP7Cf#dG}wPn7V{dsT$08Bt7#>H?=q!@SzDWW~NI%sA)aV!r-4HeY2U2!5 z&-ug2L_FHsBSL}X85xXoG~rL+{QFAy6c~TwC}CZw`#{tsO<-Uv9?4L4_DfK}vQoZl zzMVjctF>HIVLKj=%h1k23YOdK^fj2AmRHCXddp1IM z)HD$3d6S7o?SJv|>TIqr#u*z(vd-uzJlN%A=xC4IxTM4V>Cq8Gp0RYCYe=iQrn{=* zfnZs6_5=WR*Ogujs{b3n?#?bs8?fO~gal&MEskREv{<(f|4S9CTW8@ISoz7Fr|$qX zit$jH?HYO=Tv((rCxy+)q4dP5_yV&&Y-dXNRQjy59Y8PoF4b$+27`++0ySX;@++kr z?<2HVYvVu8fpnlt5%qQhMLI}oc49pu41Y^@ignYxb6>sK@N;h`m@c^NJAc}xB|ykQ z?Ae4{7zCF#Y5pX`&-@^tH($gpGS^2kyve6xrh0clRgobYkTL61?vKR2=-(};Ubnyb zO1^`gu8)4ucKpH|MW)K0h4hwDQ-Uz+u{AVAMQT5shQEZewz8(v=Kg%d`3crHd&LDm zD(7%|NDGv_k*gmdvu2-3J-!#@I_+s2{0AjQ<>{FXy9Cf@&6e(M@DF2bn7!>Dd*LQ!Y!yh$f-_F^d=@FA-5h>f z6BUqCCZaNMCi^zVOo|Ln8ak3beq|AJ_veG(v~7rLs6e}R9E?-d?qqgPj69;)gW&80 z&Z2wmxwd7V@gLfErr2Y*5Czy|0H1RekkAl+kR*XxIegg1dB!kc1(;}w*Gt}%#gNR( znpgg%Y6x`J;QN-*6P%lg!$#ie7G^zfRjAwToAn2#P7vJxC3S+mTfth+WD{+*`i+NUpupOiXi7f5$u2ogV=az1jj!O>By8;>}TjrTXs1G7qu;)PhCX2I1?8+m*bnK{N z?Z-sAdIWxKS;uJ230LwPz-LZA{THP9|GtgA@A~sfdUEYhl8N6pst6e$6TdCX!Uqu%g$59us>#(72Tc6DOt&6VVgvsDO z-fGWV#^Wd=R9q+P=dF#!cE+dstg4UC-}#ltIq%=F^GVjj_t)Mt`WCBW&HIyfk?XqLZtKz_tS{D1}a*0~1G9ZKZ@>kBU1HK$I(yAH06!2 zrF7X0Z5X7rY4-#lzF9rT_X0=645nMoB4c!!r!>)1S_6u2uJAk) zzo}a%;lFavg~>7C58LnKNj$^*80#%bCXRl9)zI?S!r}jV(?M*j^r;5-)YteA3hnmY zS0r_27LV{BzpCp7R|#=ZNO!@gKdh-%v+?H%oeC!2)>Gvs?)%+~R}vc0S5ymB!ku$_ zXA~pTqz*0GoRH(1oupcPI_&qqRFzC&ydw(y&odcK5m|a|45Dpk3U2n@??~X)LsFBz z-Bq1Dl7`~OIVrBMeC|(7s_zf&W*CKC`&-@M`k^h~l4onrX^YSVUF+Rwa@vCI;o;fs zecGDXG4m$^BAe=j&^;!D%2e|aIU%=p;a8wjZL{1C9(J!N#13{m{I>)!^?aGm{9dDC z!-0o9HRm%Z8rgOINasFX`)K{mmQ?zII@5Rj<@F+XoiZBsm#(*6X=EdS=p=e6-E1y8 z_O}J)Cc5rxSOSnEx;}=xllyLesC#{Gk)N9_5>ue6nzc9CiK$6N%=c&^C+JS>Q;u(% z+ItsT4^4LDKF!vdO2dzp1d+i96p!Wdq*pvIV%l0c*mB=FKv%#g@0*$?RZD{gduL<~ z_1w{21V81@ zxBmf*C2yGq>LuL*yA~J0!#q?rd}UJjLikU%t2FV;$Th@0SNk;s|IG;no`0zfGP=Kc zpO4c15kklUWrn9ZIDoH(sABi!6!jOdKRT>?5~vuOv)6a{FI52Ly`6Y3A^qOv_|wj2 zE?dZ8Wu=aq)|iQ&8j}``YXiI^QfT;l(Hf>c>UHj_0DjucZ^GzeFn!BkQ||G@qj$8* zdVWlGB8K&~WC9ALGKJmzA#Y*w%|IyM-@o6QLekS7ARZw+Y`;GT-ZQ~;T|gbZ}OAH>2Qc9z<#7vFaS z>B)4eyna-4*sLH|RjQ+xMf~Sdp$I2zecgnYOF-*1m)t%vcW9++R62Fk1AAUF%Jp#N zwqaR#GhJJiE#h}&lHa-jZg7sBl(7m5_SzPM-_u8^T-Ne*b`K=jH;(fsto!l{^@mpU;@Rfy%~AD89Z7?=bgP1Lw8g~?FxE& zj@rX|1u4YYaz-3JF}2jt$(QbWbU(oVsTKCs;{PrV)tPIj6UPVo)}t{q(~#*PhNUHfA!6D6O{9SdKldgTUEI4Xig9c-uy6Z?QM|PbUWNl-8m-0 zjtHJUEiaooDT%26;L$O^EU33JxfN3@Cu+2}lQ&zK2=-v@+` zZARV|Q>|7h6p;M7HBIH94av=w1LS!|gn%oVUM*i$1c0m^`UlshBO*{)&NL;H9hn8K z_nQUh-V#}Nqo_eG?6NTa1sR7NgL>(qq#V9S2Fh*wPRd(Dr3UhXr@|*?zrJ_i8zmO6 zCe@S<8GrNwwd1aVZjheU#E4B==Az15qdvtRqKKP(`wXkpsbD}K6845J6m;1Ib?+a^ z8NKwL$DC*fL4=Y7b-hZeO)bP+d@qLW1 z!n|C;_uKPT%X*eokU#iC3B>$TRWfg%hx2v1ldVbynKBtkl^Pv-!GEa|jj_9mHgSEG z&8s&rg*GidflR})Ga&mfRY|yq976gv1kHUB&!05N(w!y$SE22Rj9Uy4&4A-p7YIk4 zFM#HQ;MPnAA}V$dLgN>#xyBq`JxN_+KioC4ZxOope36cM!>hHt*6_LOeT&Hb+Q3VE z9KE7OD~R*v3r$iVyE)?aKUk>0J!BPoYhkS~`N(@93AVBv8&^Kt5KmyO4pb2fOa2&TZP{JKj3fIrGR-zpM>xLdnksqM~OOKFG5&MEN=W_ENrED){h;V+UczAH_5N^w3fz^FhpQrAOmBef0saoOivn~uJ)WEeH_+AIoGa&c z%;M`ZblWf>aaufu(_5*RrlN=kUUUnHK3!%fuAR2)i?0T!vA<<9&;n4=-nA1+`w*<&Y{9CUz&D77JPY%&DoT0Ho6bbpDJ zg8Wkw(awuG_UWdR5#5&R655G@;x$_|TiR2<3@5~D956qK3f8@nwYv1wLJ-j_!&=pOy zt1ou*2$%v3WChmYil7GP6<)pFB6y=rA4ET#f zIgBU|r9Q>B!&?Yot$l@zeBrxO^crWYpf0fgJ{{>xGI<2RDfuvf_r+{Ti7Ut5uH`;` zng?*oIkWhF-?r==hwN`Zsghvj&ln(3B>qjr@~`p?S4Pl92EwGfshfqdgw4l!}RiB$Wa~~@ZBLAgo ztB-wMMKnR%3!Q$o+%$m@Vfu9dUc1Go8CQwZnrVyaK7jSAet?42A; z2*)R@n``ba<2xa=yRoYKJAuyk&$wz|Q#>f;1XJ=qsCVQ%*J`uM0kO>Y#a-rAUvC97 z-y}^`(S7#2S+b9gU=gQ3#0We*oVYjm@++0X$OfpaFNk|YPBv##VtvK;^El7sgk&3C z|80oOK3#BwRP`QpNXGC_4e1--SHAqPe@V8cez~RZBblvgd17jDS@S~Rou9_I*RVJf zLvqZHm1u3ZQ*yn7BMdU1AqR0bt9f{G%CE51<&d+-jt6HG8k*t5CO4%GmYWi}W38#2 zcXwYy(@1jlR^`eVoWJ?>5!b&|7^Bl|8o$Q$ZikGkD-W)7k>}CW2&}6+B2Z%e3 z`Mn)4q`@-88lxgU_;IU~t@|SNB6{fxm4{H^oGSW`b#Z5x*gCpT`~(@2K|3!S7#??9 zP~iuxWx{rT==dfgdh{^^U_A}DCJ5;Tw3x7d4k#=r?Y4Jqr{1ThMf3XnlVnA*a3Y47 zkC`b1SaE?Oy(|Oe)Tl$nhU1JC2S4$ms_fxu`AF6V4kN=}A%R6}Rvvlk^NvIGA1_$c z_^gq2k=Z`Iy4Te3HP=9pQ9d6Lf=O^0%v2?>zRNf+ z6o9r*@Fsu7`@4ghsbAIJ>h1VM;Dv+YSH&dzS zXuVpq+JhT7*Adz44(U&j-OQdJ>|yqBjHCvfp7g3l!s`}V^o2T0`utmD<%2mGmcVpk zG;~z1I!iwteg<2WaJc&mi%hJkTmz3aTIdzJm1S6+dI{l3sFWU2(p4=?2)dqBpzk}a z;3ikltU$XDZBtz`)Vop?$3{BUy7&NvM=#o&p2PZ+6k=`n?7F&NmFrgjiuP$wtcuQ} z@KTKay4Dh2m-#Y|2#9Tde12m)O6m=i_4E2R0hZ(uyU>QlZjRRc6PwZ7`vPhw$#2QQ zQtyF%N!|KGpxG4?vM(;aa)L;X0|0_B)sYH6PyR{C9$^)q)ZQ>$?Z{aJhTL%;I}dN~ zEQ{u-OQ6;ol3_NYoIIfPBIA57d794ehRtwjwF0?VEK%kQuaYPGQ7WXF@|yUz`46AF zUIjl0^qy@3g`L*i>W|@&bu{eLpK3tS zYxve};w0R6PTq_tq-`%Tqi$=D3{pH&2#T+0c;xeTK+bGlr?fIKv(^%({qS8A)C8$= zP~E^~K=?3v?U*^|tHg^=X6hWX9wa*0yfK1U|vz&%p_5s1D{6hdl=7X|oD zcY==qwK+7{$21UE-c^7l21=gs`jQnM0tP|MHAuo;c(P1a$9_WigFT@yu4;B#mm2Tr zm68u0S2R2w5P}SER1|8E#V(!Uzxa)Dirn!~!mE|17~63-9!%bkB7^^QS0O-fk&Mr+ z{V598+-Dh&*6}V;h3aO(QH-wZZ?#I+hDfMr(sPWFN4NoyDDk6Hei*|g3ewg;(u7YQ ztv5w*sV9}FbPs@nRn(oF;nIEl?$A_c$rPpTl{+oPp01Rd?`9zE{;kT?&YNWjF=&k{3MWXtrd^vqP92omS|zD-IU+ zwdRKAv49Nb&6Og@nN7dV;SU&DbL99>p_|`jW(L`@E)qCqr1f>5T@?B@2uo7m30{7{ z@P80H0@6!Vq((rbw?suisR9C0BfW-52_2%e zfPhHvE%e?Yq^&d8fA4+H^PK10oC`?8%mt8{neQ9p9q*5-i2*+1bADkSm4oM(z)nQS zd>wvoZ4^Zkg8#sDKIHaVgzGispH*$`Z6-(GOrXSd<0cOw#7_uC|Fn?6IkU9CGb%0z zB|4*oF>vFx_=9&hx$(g(^>GuYixH6sE{g6R<)mR`eQ>Ec{MOVJVaIT1%htMkh7UjJ zs69T1gJH4Poog4~y*LR_6afE(@9jb}C4!CIWTUU&+vS*udvyMT0TTMg*HbT2reT~} zi$_#8mutPm&%n)1{&1Mmru3^vtV83PVXnIy&cNKR5mm>3cb`9XfsggjV$>shsJch7 zw`#^lepnNJeRYH?bnv-_f(9m z%ul9B8`KB7AFrRGa!^%l+nV{b0V}x;Y7`mNu8bJ+D?Cdd&V3^oQzzv0tN%7tGstxN zxFy|1Ze)6YaoPeAbwPi_;6g7k(_g2`%HT;#xKp zs&vfHSE`Y(B`1HcE^5__L^LURN#H)bMxA%L=W~S~Sl2C*aWf{zs#&V4J#7R0*PLlLhJv9Xc{Y=4 z%3skenMb8q5eM!&LGioMydYh2A?-@$KF{v6zroP?o_Z?_@6lLNe~{Bl9o?>XzPH|a zl=Ad{u47>Ox(x7pq@BVl-vr-~09$kw)Q6_=`;b)EWZd@h{=uPy!ZxCL%w&6VaF13m zA6g{T?zFVFJ`v_P0Q>Y?RJWI`)GBv(LC(A1V+h-0t9vm)fi6C?;0I8Ylw5wLWE^D9 zl)LFxNKjID_98}Zpvwu3(W-`A<`GsI3z9+hOZh2Oi;d8* z(mYvet*zqZF3xME>BF=m#1zT1kD0Vy0Egq8p%LZ?-r=Vb2aawkMy9vWPUpiJ$c4GA z1f2Oi{{u{$f4{vIKnat3&R~a zq3zj^RHxdyj|=hdfinGZVhgxv2G@#U5dwlzf6Akmn4(5p>T1I?6e&bOd5d*!zg>XhOWdux(p z2U-lDbz|rl#cIQpuCn$qO49#8>4}OIFq9Wi*a3|k1+mF?COF;X$@qCDe|GkbgnA6? zt>?FlE&OH@%g`(Y>@E`Fo@MaF2Wa->8Z#5F za*jHuctd7;Qr5^(R*J0Io+k6<3JsnxoxjiT@zHVMVg4T$ZAQvHcH}>o3%Y<_zLPP8 za@6PBaN^~tzw|OYbW2Xr=o-6-1+V4Cr{i00OVbxEO60-brVE2L4>=S5=cDnzkH>p- zXg-EEQrzcbMepqggL*yPhMbC>&|wne291-#JJxdF^@+-5gO;p_)3L!10*}|!pg%CR zG;YfM0ri{Ct^N8RAu7Q`vpVz%W~3ATk+Xm4u6u^x5Qxf!&Y>yIH;E{y0Wj(^-1=PP zb8x@TDX`N2qs~a{wL*RvWwCD8CJ~*VQ)frbpjcWY(W||123kouV|d+xfiss3?k>V zvxJA9>p(wN`^E%mi+`rc4Ok$5={)eG51RMipPt%a0LSanG8W3OwJu4Sx&|H39&7`e zg&7(H-d_5!y~Q*y2$_1y!g0WtLScuu$=Gk(v5#b{^}g*~Jd0efo|_^s-;Rl%mvsdz59E!jZS4} zx4AX*(xU^`8;AD4vt~8*EII-EV`j>=0euqsXWfX9$%(DZIp#r>4U&yNYi;uh%!N$-iHmfcfQpAnnK@gh2LJU&#{O|#*wo_2*(W-Gn8ZTkA=ch9BN z7JoIdS0I z=2!Zc?w^En)4XIPLIDnP9FPdkRF*%t z`K<23W4fdMeFd@rDjyLSd;=)oN$i0k*IeX*#qCJGjm^dwBl94cZ3jaZI0lNoEw=_K z0=d>M%5u@l?wPL}U)I(>D#<0G5Czpm|8wq_!`orZ6cNIb(OPN#C(YWvIL=Pr8Jtb!|Iw?@-4@^YcRmbl^D zLvE8U(|6-~$Ck$^>^%$Pb^BVW`!}K0*R1XC{b(5nFXycGc8`03Jo;UDIXDiedgvPo8%(cqc&=z4*6oh!k!HY|dX>)5qBi-)jTJDC4H;`Mn)@R6A}2J$cJN*8aoeP=Ubsb;{;) z#kUQkw;5S8$|#Xo{6Of}Rfz_l19A^=8ftT*v+-U<{c`BuUOo=GGy9|4r)uz#Y6F?E z$3rhFs^WS++xIx!+oX)hTFdA5305x&{867Oe{9RS;OOrlA(B zN0B$g9e)Bw^z+l@T;>Vr4*gn&(I(dk;Y+pSRR=>fhWQubYD(T}t^FNVrYEYU<5ko# z73ii_?uO{)_#;8u5Z}bjmu!(1aQ#rOo^}ks?{ncdtyg-|Xc9V4U z%cn|HpYUg-F$a5hiPsAsk>}`bd^6?3v(a++sqBNMw%eAhqasS@FExI9HZ3C#YZ8Cc z7|<;jPG zIleU6?KM^@TrpK_ZQ}s*&gu$w&;x5}!s1Q1_nAgG2B%WRM&N4|RVyXiLmGqs6V6B1 z+Js;HQ-31KGUd`Wo^WDQ3;qe%B~{G}&Huo-<&sC6Jms34f_+_Ux^9wZtdA8bVvP)} zfyF1oP>V9(8{CKnJ*v~3yM0^Q!-(w8do zIQ`TE>P?I5)W6xr^B#QI4=O5GH8u28A|*=P?&kx*{v|dP<6@J!x4WEBSirSt`)Odf z(Ka~Ya;}p*hn9gS&r3dY8}k=+4^wZgDPgj^3Av)*Qr#~2ER3Y5ulbsB{!90&DxBBe z^&O&lBk&&PoUvD8;!Fm5W?C#_w4AlDtnyCR^j%m#1ztY#prxa*Pr=7dz3{zFVc538 zpAtd$e;(D7fFSk&eN!GE&jhk)&lss6{cg^?d6N!abA#zc+_5u_T9@b3xIo$@j z(jQ;=*Bo|NSkRy4t5O-xI6T^Fa1MhnF1$dkg5!X#LH)L?MhU!?W7+hh#^Fk%pb?K~ zY^0RfYzKaWDEdsfXBL?~0`|?YpELQsm${5B8(68sK;$BOau(=mBMf!-aybufI(!^G*)S@m~wDOD+ z#m85a%$G^$z^(OB{S5w5ZEpigJ!H1mSRuD=CDNhBxpFTX)%(NeX>RYWl=rbY^-wlT zjm2F)*z|NqOSgvlpNx=UUW5;}ESUF$ZGXY6tVp#f}!u=UV;c{+dhL3N?Dv z#>5%tG^_GvRjBcb*M1fPCJo|eMMD;j(Is8A8iK#oHtkvpMWU868l3-Ay$t;S6E8sG zAr0^NAO;fp_K&Uyd`R?k4?QgC{1upC($vAXM(>+Af)lmP9n68}!Ay*rca$YpA8{6y ztxLYzdPHKx2({Iki|l`AaZD8;_c9C*Uw3_~O|g#qQRe5-J}f>=Un*Q(dMY47T{IOQ z6Y*%^U>K6i+J36~mEO@!m!QAmNID;xEBNtPi8S;o;d{V6dMn+qrGjoD^8{Tw?*!8T zq0<5g@W6^LIKk9Kr~o2i2Ha181ddn=ZyI&WnI^bb(~BpXS_&8CrImEc(HRJim_eF1 zxP?n9`ybtas69(S28IJa0DzFc7Y3oGud==;1eOXO(W|C#m_eu;S00F#)$;%M@IMqK z5+G5U%>W4HojBxwQ7EPVb6a=%o#{G&mH>JM07KzFw$h8Fs}cmV7(~l}M|J?hLWdQ? z+qqUJj<|^Y$G1Gam{Nx+LE1OQkR&EocV=|JvL-MA)sbVrEvG~06t}Ee3{bA=(0@mY zjl5TK{t(tW3uMnz3(AfeTGF=%{XcacK1|R}jZ6Y>Z7=dCk&Iy9ZaiEERbTi>iDCPk z4iu(!!Gk#H=HcwsMEDJEwR{?K2{A)(Q!JhreQc@hOGeXP0B6FQHsQ|y3NRS;fi*oM zrP2BPXZ+w;hTQklcvb!2aCzS5F><9YE zOG-){kuBZb3u7l|g{BYn7mOZlKve1N0t#pYfCvo9p|P+jd40-ezReEFDv4qIHm#Yie^hY2wWh z29cxQ4LlA&#3M{}+*QIMGqkejp4VfwS7Zd|LGxTZDc|sN&s&>j zf@0{+ZZjiyshITUYHI~a6-&vLjgU+`6Y`Vbw^*XYf@zv;?5?s6?Qy= zQu;{&L)CjxqsUN*mtKG6+3|sXPxuglZJUVz|14k)?B_N>flsWj{;Z#W`{XW(G3wc0 zO3>bob~E%F$)<-zKV%*YK4hu9r#fFO+BOX8#QmdwmGW?i#_rGGrcoKAdi?0rkFm~W zMPS8?xTi+Paj?66TC6P@rF#Em9iSN%@7s)cLkEc3S%T$Xd{MpP8^Ra&L$_{c0$Z1`#|u8o=m*q!52l*p!I>(EIfkuKkd zCV#n0#(OU8pKi~G)m%Nf8-HU(RPXHEo3LPK@+Fc6ho2z-6EiL)Wm$^x+;Kp2ytSj+syd*-C zt7W-o;?T2-I)uNrp~FN#DW+xCY51k0SGZzMbp^Mf!h~tjZuf)TYTGPox@|Ssu(TZq zXZwKMt5fII9ldsGpEa>zqy2qvC`c8ycU$rFT+``^Ikiv@d=q}nAKXzD)j07qodxoP z-#AxTNzIV{PD2JSX>8>9)DrPRL-u>=-#{N*ldXRIVQ=EiFZTRQT-X`8D%$}fTHKAP zQu(Wopv;e77kn6Ib7x>L5R-FNuoJb8{&qR?LG9d4g zc;RngoO9rfwtJWs1PiT0ne9Wcl5o}HroYd&ug*cu#m_ZZk?;S~xm5;;yq_9v(WmA- z5HBQl6aE?c9zHob`>e)d;c4mD7}HpWI=L+e3M8yg`ta9_8wnrWdJ5JpeS&tE0SRQi zuz+N%2FE8CC6#-}6V1r3!!+-=vJd#UN?AXeIAhAx5ho*jm(mH6ssC&*cPZ;OAxWhJ zvY<~ltV{5L>O*WU&nRsac;`k(LAF{tVw(or$V+S}hPOB%%)y{mNI|>#Fe7J^0zFOmU_oZ&17^ z+G=y7u4H(9VS(FjIN$Ja#rD?Mw1nBymPnDYfmohclc*j6wpo)XFSn4qquOqlf9Y7w zsA<@5a{VluE$q#Ab@pEAOl9D2PtLR1_fr__!K{cs$}1HZSNYmFYD&SR{(!{v=eoYo zUz%NAol5IA3T<=T2J@1fmYdhK9CZ#7pRlTSjlT#F38HESLfgTU#=CYE^6LDx>AI1c z?X|`~4nG~)yusPwbgAc67g|)ih&Yfs<41vr-mgN+RaG&J@eLVYZFlcWAh?B>Ya0vW z!#bB0%Ni1Tr@XSgb7~WU#7^u=Mh_MHB-;Z~zdUYj>;Zu0oT|{apyLJnZHC+P{FlMQ z<~L;fJY^GF6uLU5&Yu@t8g{$mC=PKH5ll>QsmH7b<3zGQl#0J5r9xM>nE zo35u>>T4_MmY^58X5i4d(&b-SuRQS!n?OXAbPhPW6I*F-#8#yz-uB;D=9)B05;<|; z5TqHXWF?6X{L)MNic;|23Ti_P8aq4nG)D57;++v%pihJbKBkkjy@LF(7QJR+CYe$C|6t~O|GH|Go(Tp(kr;PLkrEgx%8@CO)8j9^VB+Wl@S;^;LO;!^WV z?qmXc607O36xfPZ{h6{XP`770ms!|NzjD0IQP<*H2|{5)r^4ICQjeV|yv~ZdATnT9xXYi>k1&-1-_}$gYSu^eZJ! zIPFA%(Y^t2)5h2R;yn^L1ce0;?1%omi8#OisX-2fbDv zNcr!G^{e`j`RWL}BP>1x>>1hqx9N8CIS`T@N?zGm|6#9O~?^ zd`#gS%wNuE6Wu_(@>tXK?{5daGls~f1R5`V+flcoppT9Il4HesT0j)d;TF)GYEAU3 z+7#+5<~gyT#nG0~Jr6t@)WQ4%;-Q9~o$0OX`njv0xDsOC8dwu0ATbhMa4r%?QguND&x6&6ZdF;ZqG0sH#D~3{W z23LhpNAWG0@sQ<5<6wY)If`SY0I;|(MEEn%EAxs*_5MruNURjMKbqClT zK5C{pZp?khIE@}ROa3CUjOG{HXcVmb8l?&)?G;6;;T|zqQI4tEU^ok$&@s{(p97JP zS&(~~!|qmP8@H>g{Rmm7c-$A{^Ml(_BKYLzz6TIl1Pq65 zt7!fGcmwMFrBv^J%(Dy+d%WVB*s8}zfbI-7-A{R%Hq}-WU(LCU7zpsZt@DDR0BSP# zj!l;o(T1#)CPH&Jls{$(*h1|Zs)Am?+0|`yZ(aBTnGR$%6kDkZb__^ePTF`uSkz0x z_!-FiZfrI3$;s@1x|g?Hdr((N-8DO;>T26#a=*%0lS?W5^kMbbP*ebKQmy$NcBl96 zEjRajT1oCH>QSBxnuEui3Px@ii$A><(e5r+v#xNj$M-+BvhsNE)2vHUaXvb$?EA13 z{5=p@Q1!RS1~ZQ}F%(0JA#yGG_Wrwfo9id{Pw#v=IbYX>iR^ka6s9!NIuKnfLMPlicg7YzB`=J(dHM+^ug$fF(#3CC@Q`jTYzZ5F^le{@rahPF3MP$CLEvurXDI(%X95>QZV#pQOr# zBNs|TbIrXynE#pgsRaOidV;2SgG0f}uKU!jBe|YUP$fPBBQtvQG?`_>`nu$1pH|tk zWeCHtS$%)WNG-z_TVh9aJV{bv@Hw$kzg$av%DJeX3)T%mB z+>6e2yh)FvR3(O<@engSE-W0sF^(uG1wNx5PUmJq)+Ukf50I^(_sabpL7mbH0I8W=omg={;WQ$lJ>{=FuB_f~3?zAo^ zeO>BY4d)MU5#ea{pHv=jh3_C^QJ=R>de`+JrJ(B+L!vn*SY#|V6+IQ;Q2F;y6JC@Q zYWI0hUwZ+>v8FtlE;hZ+(=Ow3`lTnd(zaf@wxUxr1h!w=Hp$kx8=>IKYBpzG8{O|X z7%lVrl5glVf6@Wl)@j3`9d57h*TL%H^@EG<@_jdg+xBfDfxk3x+~uuVXw;#0A>)@K z41?F2M?^z(%e4WYbTzKjBjRD%y3y*Loc`T;3M*3Dj)QDKQLL(H7^3(s46`isU%mJB z%zioirHpnB@|)Z=t$*&CY{$OHCslB%ZHH@et+@iH%%27AlX1xbO-7M^?l526LTFhL=OT>4gQ|Uycb0y9+rRNcg;WQ zajYSaSWy7Ts1Kp*4}0n+*>2_bS5eyVBlTe)0!85(0apj}f3o&VSYpfOW~X1|$xnA7 z#q^c>glj>&hK}GTgU4{aYDMQ)=G1`l2tsm}xT?MPqt;$dBS0aX0GI~vMCK}U{FmZ% zD@ zQaO&Q0$MF;IJdD~Mv5Zw{hf4tmY`R+o9+_rEf%Rwgn&*mUf~)+eZaE_`(D%$j+Ooi zKz~!bOnJB$iS*N{2Ay3LD=Y)i;g^Uv+u{LPxIqo*>f z+-~+Wo}STi?c2QxpyKs4I=&KcoY~6mJSvuOUZ~nS_v{}$$^7T4je&_efk*KZfPQ5> zyP1$MHfoJaSPQwtARY@#`IBx(NnAOunG@KzQ{tBw;{NjGS(4&>^tChdK~Tl+Rw)=S z5k&T~fk;qp7V2K;l|cvH{&nz_gbZkOI-iLD2>b_G7GXTjf#?3zpo?caoP}R}NuPeO z<<|*6Dg9~30EANbgZ1`CKhxC?d9VE=9Y=Vneps>7`xbI6NA~!{Yh-e_Rh#LfFWQU* zWQdvVj^%8ZZUt+zEqmfkec`9)E zY3?N5n$#l<&<31OC$$0FX3&GJN?+L8VW;-%($2+y=^leKLp;d=R_Ok%9)ir=!S5hT zhGG3&(ikvo_k*_+G->~sZm}2JpaCe9Er8NFapzWI$D0T0H~f}QP$b=yl^~^rlYkvQ zyxsxL4OHrFq={4kNBe~KrL>bh%eNhm|KwIfvwJF&VnT~eC&8&lor#M}!}c>5{>~HuMnmFg97PDI z{i`yp!lc(4s!0!WS%z7km9n%|vCfY*wcX3&T7orfa3Sv2NuSxOiYMx>XE{104E{2Z z#c;ZJ6Vj8(k;SADZY;c>cGMU5xWgo;X>IVMuXYlT>|(X1lata*$Z1|qi7QVA&uh(< zVE*6AX|vLAeIpgrovC$T$MF_1q8h~{=Vxw5psePP+)D@3ufFw{vg*kzUph@$2$A}!tQ`$&XQ}~?z@Z-Arq37Uch*y`a%}o5 zY`hooTHMcK(W6LUmwxTOss_PLqa&@Il$@^u^?LX!!QW_{?U9%$ggwtw=~ohkB`;X2Obc_PJ-2~!?QmZ$Hd5%3Wp%s&*$GCaq z+{01s1*vl3eQq9I&H~sy}1*@t4zvI0vCnm9Ew6>2Qh>7==pB+9QF@_0 z^2IRVJs^`DlQT{XG7N7s#K!&^&HUZn+a za@iaA3w+@K+A3wJoBnv6J@uFe#bvWXnPnm4lt0LZ+N`73z{%`4@s6k;Z#A)yW4zfe&^`PM5^Ep^Vs3+c+KK4B0f9to3=m{*4j@ z`-1cdN5uSYu}cehP!LcMpP$t2=%*wOH8#-JL_!_7AFv5#Z%KWr^&4r~{+A8{x&^yt za_xWeAjD>rK16zZHVuksc*pR)p01gRsZ!}hgWSQG+yce? zoOk!^{E_;@9ASSlUEbU(O1|)#_Ofo<`UFYzELV|R{ooDZYiO9rQCRuTvpezOfyKOe zFR0pSJEb64>83JU7>@+3J@mfd#LUH1fZU2}Y9r?s0%9UmC+#9NtA&2k3Q=FS&RL`U zF3|^_Bb#y|o`Qh9lv2~_@SOy2`|TxKOvd{+OpY{MYz)_VM9~Gjuf5>w{^_Rs;aIOy zxcQK)a!i|hLco+DneCAZ{m-%nI_jqZnz+AMJM&G0eY==Id`?>kH#iwy@Zo?dzxScG z)NxEGQj}tZM;vFrAV^s2`oJZONdqa_AC`we@!#1dmBkLgI@D~0&{{Oke!r$NJ5Vr1 z*p!lfx21}B5x9y*Bko}hpdCEZF1bIb!zPwmReif(E-^F*a2L3J?B3hG5tWppInvVY zqmcW=|MS6P&{JY)``@+wZ+}0#L;qnYtjDM}HK#wVb18hgGncO|7$+OO(=ijP$6t^R z>#@;nA8)x`x=XH39-zYfr~=zkb&4I5PAj^7S|}W6IhZq5 z)OMXR#+jQ*tyQn z9OBQyo@wk`Ykcxgd^&nm$__ZP>L(qlBUIeljgnFS82gvP}6baHNjYrNy)nl$O@}5n0GRJT9XBuzM(rsyaqFui$4(EPSF|l5?Nophpv9(z$HMI>=%Ss_!A! zi{}KaQ{T!&hSV2NE8Hf@$$Y`!oFt2j^ke~#$)SPBX*xy4Y!cUO#sW3N^sFj9OU%eB zqa^1;Ow%)Fro>B!Mm8$3O4ftlduuA6MG2Xh7jvwg+xQRb(zMI7ymyZD-`%WA1czw% zBOWF>{VKEnn6Iz&d5J;8r3%fCWmwUkM?7$aX5ffbp9w$&6jcF7TrKbmKtZ-ZZPy z3>laTP+$&e)!xl-48tlq>5ig$@++&e7HCV-)e&o#;47$e>j(aAgo~wys((*e z{L}-lvM!!wuyr<*`27Ca4@Y^zorbNx{sHGikhGv&`wUSJ*GRF7g> zk=dRM{lSsR6ZugX)!sfZ0YrXFw2Uom5)b2MIQxfC>sCqT&puACr+7-v`lo6y!T+Q+ zS+OS#X-6389dANl_k#Bm2|<`D7x&y zv`FEjTW~42h`>tx5A{$=+Rw2EF(+t1uzP777XkXy2xszia$*)BvY$WRg_%SHq*YJx z-%SbFDoxuB`Zgi%Z6FXLWIK?`bLnuvXw0`A4Jm&dMxoA~x zW9s2yWvWss^1wx&V;RLISQ)FQq9gH=930UbU`prKOt%PFr9_W~pO;w1vNI>zN#|GW z z0eTN*GGx(LFfB2OxqZI!vDMpUA})-qgaD0As~BfZJ{()a@C?yz`-iq3GP&uB)M?J+ zz4L9@9Lvd%h!J`4siy`fdZED1qwu!VS|ASrlVbk89^J>k_UBnXpJ5iD%#vzPo}DRo zxLnuY>@BTzH|D9gQDpnz;mI%sndCl(4vk!XyAkMbQEvVqTa&$n=_-TOk%Ed|gEvwP zykPF~1;4CSx(>zQfTSmOdxkmy@U?yZ|GKXKf4gD;hs+(>$^S72mpRkf>wiy!%h3tQ zNyjj|%FL|MITocBTb2mB(rLMdr6r|hJDz^0Ps{erPW$fnoqo2o>1!p#G%w*D!++RR zf-YL{D_tc7Fy|zq1^+{(zF$m$0-#fMf}ZKCqp5K{(^*b+PfOT}l8*%M76PN(0m2%#`?z(H=O(~?S?Ab_B9d&-<86j1`hU@r_ckTu-`<#hLa`6j& zI=Hoyl9a{%)t;KqKpI;;-7d_FQCJL{{`nkcF*S{Nlnw0i#kQdz8a6iPE(Z%0Rngtj z53@~w|MgKcQcmt{j1^~}X8&WinFf>&`at!bt)w|N2d)uH6K13nOo>wVxauEjxK|$I zSL!U{lFd88 zSaW>0x`_WrVvuHLT)6l88|Dy6VP20@qb{RkwT_T0WC6;JdZPUTJjThKg|ikd_U@8~81Fr(8wW-$u|R|JI>if6r=RR@vE>-<5>}1jsVn!3clDs9eXT zCS}EXcCy*D+B%D>$&pEraFt{sB8^9!xWhXq^&+@CpWJ_qNIE`9h72Lz9trw+jq}qjoiHq}nGm!)qM~A+T*DCK z|E@rCWOP0S&f7189vkk}qz3Kd2}|&znaeP<#-P&8Vy=7P*HXSL?VbDnb9=BQnixkm z_xD>U_?UH__`=2G&FJSP2_p2!+4I*u@N%wG=FG!>IbvV1`AKid%YE#O@-^RRv)uu| z9SRvVqNs|anuak~-ES2o*5}{vTjwg@vE|sw<$zC;nkgm=xb2IJsL+Pu6vE?Z#BC9jOYlBDxDp2B$?@~NdBH4R}RpPNm;UIm=j>0o9Wr+?{5_%D@*$EC4P&S|}Y&IWrMk?3K04Th7jBa%wEK{gQz4HS&~^tjDZB7ZHxh^kG0T5ZUR_{7)$$x- zgCtpDlW`QUq(Lkepq;l;BMR`a3_?CGOO@57BwjoigUpvXV~0+xO>T zL}&}^W{pt+xyOPwvF>c-}-`57vk zi2RhD`ReG-Cz}zes-Yh3-?VjET-#E}0GTV85BpaYZ~^!*`6QZ;(31sp>ZPndJQ7=j zarYO9t*5o`X{B&R%+D}E-#^iS+cS&i4m@R?!i>uF@=7V{df%?GI%_GTx%VIHPINk0 zb6d`CPyH5iIM8H4xJVpHXjve~gsP*z(e{kBH(}|>DmQd9fT$ra=dbg_rkF!LH}B@k zAQyj{uP5H~5p5IIx-189cTo$o*gX&-)WBI7i?znoxZK>3$=7fq5aKLCN?@< ziZ8a493L+tvu3jXQaPEvq{n-*4os4Px2nj}eG5(gRUIdda@;wuDu*0+r*fGe)@?2E z(vRPmD@={;G$oY${WYI6B2<M=t<*#J z%TObl%o-#+;AmkpCeDgi1LcO`0Pa~_!M}8WT23)ZG(KAAY0G6|qYL2%da66y8M&=Fz;Gi_6RZN_$C?Pc!o;ml_6!VbaWDe)?PqB<$( zSl)1qE%%~pSgU8Idft1{-d_=MtaJ_v;kt?yg)icND;^+5jsb4L_eTkeJjxra2ay zpe6#TyJ@aamZv4fdX+!y^Wym$_>o;sZB6(ej_}I~m%qNSk9kr=qBkDXGWgmi($*lI z^3Z*Io5*Wp+McACev4Osy+}(eNo-E9wsdgUuKnhyJSj8dB;`$hN7KBNg#%?yeGFWhXsb8DfP2~)bz>lRK-p7~weUB}WHQs77MQ0{Pxk_RZe2zR!td)Qnf{ucz5 zYhJFk_j|OI@IK`>!R`O~ra6Y!C4BPaIwR1(gi*!gxOgG#;Mc^gccFifq>)oe;7k-+ zM=(^>>^ptlHUHE9)9)Zn{TwH^@$pn1cd* z6ysuWSJA=O7Sy0dnLneT?+ac~&!j*74N3;Oy}!lC>sXb|^q%k;wRW^@%tkK+T#NyD zJvb(Mv6E+SuRO(T)g>)Be^=NfUah|%=;P|X$Y6^PW=)-;do|^GmS{uursY(%*<8r( zDJa_0%!$|i{?oi&p1{BsobQ}JP;(#|?E|blAjKCycG=qFs4YCTDjsD%W+6@rE?18z@P+}}ZM(@5rVq6h z$RI_J{$_t{WxckQ;p*^_3pKSt@U>0gJPEsL-KzFf5HLYOPj^6mE0pEHv}OPE*3uIvjOI>03b z!eF_dLUTWdEebh}$etSbIC(%t&Z8ZA5xo~66fX7d?Ln?%4=AIY?7-oW^)Il>4&s^KS%bpQ%lO#{tAZia7 z6y#YcB=A9Y<${XKce$Q7%{=0Jwe1j zpbBxEU3$oE&1W=R2C!d&{2j`k1!W(SEOIX~T;L6bXue6yD$Sc?(Sv@N_whMvPOro0 z?wRF0sK!-QP?zhc{-vW=6Ke}*DtVo(cT*MI4;rhZ056MV#IZ)+hEXqcCw=J)vJ%Ld&r?(4!m7*34krAd{=IIIh?Vg0 z%&Ji11sieyt1D{HWb(zr{8wOnY=h+s2=|BGK6>@9+g~)gzAeFz17z|WByLahFEkI% zUv`4Z;*yo0LFEuPJyX@*Ap>I{y>~k-N>;XrI~;pl9V(~qZ;_w5^KjX*I^x4vcmoR} zx^vcVfW=gle-+rQXmLZf?0`%NDXn31jCvAa#b3Op9K2T#%KZamTj5FXfHgcI&i*f% zk~3oA9S~+e2tKhcpX=}DBGsmnc+sY$emOB9{~G3wt?Z?MuzJ)W*K2?r;N*5uSv^E3H zKFd0yZ`(s?Ojcm`+ajDkRs2RjFx=>vRmGf+7#?Ad3+nXz{X)v(D+L0sc#ko_O&~uq zse;O9e7)QshkNj+uIu%?+2-c%^90VpuU$XavB8orNfkF)Xfnodcs z?hoWH$xKX-&z2A-Lyv9Wdquzk!_GF(Cb3YQ5-13dqxVZlSak`i!*#?#zm+z$(w(jR z;QUdTlo}#>R8{(JuD-K#LvTR?Hf7UdNFlj%I-QAdSASu9_Hc09;&X8qcS;d za;B?+`@mo3bk-RnoDz(&v&K#6;WIr1H-;TSzA`7=+36?srdB)F zWd(EDXmQe?M7gkRo)dNQ*!=ly ztwDI8X8}}YB=jb7`pR9S#U};Im-L1pdO^*LSXBI11~@&oy1tbuDnUvBm2`-RnezPt zAjyoLi60z;)2An5T&ccgj*dgZ>k+VwX0hiIPG^>hXRo& zDDcw7N1awK_#vg|HtNeI>%CB>K<-FX8b0@Fg%)4y>F=C?{C4Uqk&=UZJkv7fxvPWO zu9%w@xx>CpOEg-mLfm)6Uvl&D$4A}3|Ozws! zxCqtrIp!~_WS5?@Q{|&=@GgH?L6IOjd}gGWZa9NsNg6dnPUg#(D#t#%gL9?C1;onKsCayC;whK1yw zMg7_lOv1tfS#^HEgqiMiIRj-DQ1eh9y}A5}>N4h4pJ0cmk+-SHR%hndto_~hLS8`; z$M^G~uYz6J$a^_0j%PiSOw5_IJg80wq&gZ&6)QXKlVxl%&RT}XPv^${f{l8R0v|LU zW-}h~edl4oXlVRHJuURBd2RsE?jy{*5?H2~6P4 z%MNEbl4R4A9h02v7foB_9iTys^~F$2gXRc=`j)vKhj}5?t}d zfX;A6?Vc}3M8#OpYZpk?LK#N}OhI@`c8&tr^;V;!mG1fV%jJZu&3k&Qj(wb1liK|( zN9WK_*xmw7J+%sI#kGq`I1BxJ8{I+u&FPEa;YVxo+n-W-AKW3NW-6W=YbtQH zH*4p@t1qzM5abq4774hPCvIA@^1+FuinX{V2cLyz`M{*+)w?Sy@(<4)q1BC117$zt zR<#^CDXd=-_#eCL^RAY}hGPYXoVj%`QP59g22&n~=C&E_8CdP|oTcUgOpFG8FOjZ8 zOs!uW-ey^9Zdu3;vq^FRC^;+`SBKc1+BigQ8@QX3QTb0Y=@#x3xYHglCtwQFibq8X zl_8h4$f6^S@_OPZ4#QLG!JCa7I9~F5Xvp?~Q-lhuMAG!dj73A_z`b77n#5+kTwTP` zj7tI*Mqog-NXZ!{y)E$6G^)6RRU_AgKGLI$d$w{JJlt4;cfqkf#iJGl0W8(|a2IJl z{;Z52tV(qwJU5eky7BfX=1-y@U!>&;9rLC%y-k$TywMD2Aan;bHSwn$a>K`PNNmlV!;@x$fvoT=7zVmEzsNr`4YBmh3*u$dh`hfyd0|3U(diuWQ4=?hQ3) zhkb*bb(5}}0y zpr;~o!ceOTnTECi;Wdd>^ij@leW{6@#7u&u$1>e#C7I!mLdb*j{Ca zye+8=KQ7Ns#%Rg^ zEN0Felene&ra+VJ(kQZhQ~_*j8y8H>0G)XIx%Jwatd3`a5-%)w!kW;$@wC}m7Qts! z+>t?G+(-9|%<{IV-(7xy_=;skL}c39Ydw|^C7(i8?9o0iGeo$ZTd{`rjPIiA<#67E zGq_0}0A@;2(?Ba-lU=6qN2U!c!;-q%h1$q8MtyPqcDwbkMT^3(ZRx7sx&w%KQ(sx= z-K!US2O9t+qtuz>YeLLQ8@@3O4rF#ftM&41uE`MH&yi;duSbO|pxqApd@*ZldNnKG zR$>jB@-x1cY(hqirJnnDZCofwz}M?j_DNLHXR7j|=tK|_HIlIrsK#t*GVOpIscu5C zScIP5P%_yox4-oEwJ~%f>M=Tf!_Nc-AeYyjSR(m{o|WX0>3{#Pz}+XI88nrvgIj)H zupP#moNnWse>eV*4{hsweSNQZ%c_h=Nc&*C;J%-_oAuF$f%+PLRM{824K~3XpILAn zE=JCtk-A{fbv07-cn^-+-49rxauo@v{SewhuXqu)0MQWVN`*b${TGTQpX&+M4ALIn zMu z>8hs?cDwWTy@tF&MBZ$-mzTIhjIHUT4vhJtA0;Z$d0Cu$S<{XEC#Ks^1gG%G+KL67 zt7h!61M_``k1O_lHE#NPTv+py6HTcTgWyKy`EjvfsNgwo0JV{wQ>LnbXk>^`^nr71 z(pqdCuozcy3!1i&7{}_N#ik$5dA?3ZW;@PUeqroBPkkaE+wKOT^1F&pShfkKOinko zuMGEh%j>)PWe%%9^K zjPz>GS}w{AO2VEliy}c*V-?%0pJnNv)c49G+?Z;JRNjO+Jnll>Giuo{YiM9M2k$N2 z-!0t}b|21-fxCfIw9AY~}E@8TwY<>fLn_rz4{WrWRj z5V;y{8Co>~xlGf|OqPuq8Ee>HE!(@_@}5C4+r|qMDCj}btdn=FHeSm9usik>(*&A| zv-cZZqPz37)`7cfWG3TW{Ne&Uk{8Az@F2k8E;S`tt`4N{X%1;8zDY*HVB!V#?H=l~N-L9w}QG4$S}(L>UqH+36+^Wv!yLApFvYlKC9 z@aD_vtF(r6CrJy_jl2_*z5DcAv0E$=y>sS$Gb!q{>gX{%=*v1%X4z>wK1yXAvdXE{ zAfLh^|5zX4p=s==vd`=}Vu)L-lFCQTR8_4sa~KuHZ1~2;#;(EiE-RCNz^RK1RlX?DM~U8dAuebf?$i5+dgel4`{e0lnSQ#*5V z^muh#+0+!!&K% ziW(HT$(y!Q^2e1;{$#1JD7DkT*_1K!3$}+;#w4qV1?p%wW!m4T$w;n@C?}idpZPHJ zp?{AhKrY8=i*@X>>)pV-;a=4w^$LGh$b#VgC2btB2}SxA|3nn&s?# zt1T{~jIy&zTshKbH@X1JktC9r4&x;Qo;GRMp^`=`_<Oa&^FE6Is-30=U)`Cjg*|YAj$7lP@?L z#zSUqthi+mlUEoAu!@)rHR7xauJbj#EPYM+rB}Bw?O}fEG&M~h@CWoqe15++E>jTywd6(?d z{jr_(K$dZC19P`t9JOm$2W19f&3T9ZlEH68jW?P_!n{jk!AW|8t%FvuCrS|$3QQc? z>vnRIebS;zke&#CmjzqSp6cW}Bb3!k83k9g%!r#$gOrX?_Go1(-BL(T>To5v{rv0j z558yzHsYEaGoW@}E%_;{x76CL%$MG5O4DCR39&7+9tE9v+xHvy^Yz2x*s z&X5Nk`XH9WRaJZ|_d$iw{_Y-PtS1ZLh1S37ND+^xFH&!RYFc}7B5RjF#V=@-lHTys zWU8NEX7Vd3PEv1NXr*q%CiH&7+ot2SdT#--d`4+2HzB)r-n6Bn-tsz1&#$k-Vbt!Vc1x z-b0`H{IoczRSIG^_TZgZG+`aPc|NW$DshnYL2SqIiZ^9cR!%JJ7yGdEydBmoS-qyQ z_UB9;64;&^^-RYd*m}eJXH%W8PCv)f#w{agKQ6R!NL~OFjPiGrt!IdO5GUYlRf=yw z!J}GnQ-bd_Ysk17+gC`{c_i9Rg!PaxEYbH=%wCVw1GsZ`6Hps~{RI<9t5g$Q5Q zhxcfk50HR)JVjO;ykuBGj9T<+VbgNE_)74@5z5Xcl(9DI2fMHeUW@l{Z`e#aBh35^ zf^aZnxu9U(4yieIr2RdP;@Q*_zbI_9qAizra}NSwiXHJlLsEi*?c_e>uQxoW>w^0`RZ zWPV4rZXEQ3xn!_YuudT$Z+PYp5`U;&J|C5w^Hc<-xJzk_IlB*FXZELc>=BA;I z)KQC8LoB6|Jystoe)O3nlA_#P2V{8-1|uyR4S5kIb14e>Ac_l)<59Usp$4O3Db&BZ zB-`<^i`J%TkT|8Ry%6yBI9y8P)eA2xLhtd5!)J(FWr|!XA;wwXh>J}{ zCWn{+DZdAR8*%9vjwj2m@kMqk+j`o5xc5ZngM>Gk`Nc@rILYoi*=w~a5e%6W-=;A( z&@$TPl$M;pvHQ*BLR)rr=Q|vxJ6Qz=V}LyOVMYTMc=|69{QvO^Wihe;525G2M8{FK zbq>cvGE1FUjgCy~Gzv?dGTk!$SEFR%3vti-wcYc8C@=PcJ9c2Z&oc*U6z&BFigKz2 z!-`}8N5_jhJ4OS=o&169KkOZKK9heO9(5l57!B^&BK;Wca)8idz#S8#ZdVxd`*N?4 ze!QJJZ-I0F6WSPu3T@-s5i4YVuQXtd1dw%d@>c%Qd4RJR_46^=oV>Nv|6%t$nzPHQ zVq_RGQ0Gm%_CBRR-RX6=q<%cin=Ib={1EU%%80Scf3)<8Hy&UM9aH=#=j&P)64fpF zlzYrVJ@2wDFJNe-1$+tYm3P@4ndVh+2bpG@ciAI8&DM@LKHc`=Wy6@pWMYWqt%PX; z^O-Kx7$F9%GWQ{m%H#HxO9p<~*L$F*)N+>GzPDwj6=b&)4M?Xd&Az0Vxe4RJn2GllY@NteGL24z9EQN@l#Fb zl|nnXDWB3O%Lbp$-PO!6bl^E}b`)|@mwtWv1&qWEZjB#SV{ZdVSojM3sW+|MH#?}= zjh@HQFHw(`62>tlzKz5D%Buf%=;sq(u#+FRgC0W}IS_B9hDk?eMW_5CP3JBr3V47k zcuhE)DdKqMKff`5dCd3ikn@S59iNMHbY~29^zyPnsFdw7% zyYaKvgXy0%k>7m_a6l*OJV8sH{siaD3%WLMI3ck+!20?_j*ZE;XW#`ap>$S>MdERV zCBGs>bs=-&HvtmCzdpI+i~AAD^7_lLz(lwuiO0>OZo;Lgm~}a>d?J;q-tq?Xp{Zu- z-R+iJ2#q~E`7lqk(CU}>#&6>^6h4YEzig(OVLWEsys*>DCUm14I8zn{iC}u|26Q(! zY2D>OM60TkIZICs!WOZ7oZr>zmtKXh%sPwa&nN@w9^FGp`W>PzX{hcY9x4}Br*fuP{$hY) zdvtRRpbuw~Ay9}z|6Z!)77f*t5ns{l=A2Eb*PACdX-Z~h(hML?9;f>zjAw^9k&_l& zZiL&zi6=q6QfgF|=s16cwq3VaoR3lmi6{Y{ZW9Gld;_q+Dw z+1^C&L-JN@#+gJ>a(9jDp2DCa(S+kv$70Lq#e7R~=1wHaZ+D;jv~Ghi4TI?ATHVMt zvI73E4Sr?>N36WB96o!AhVf>0xd$cG?C>JtEcSqkGr%u%qI01t;Zu@(!18s^(ogJ4 zxHxZT6J9>j1=|HUwtZ5$@Qq@*Vfh>hq;{?xebmUjhS3@DLrH%a2X;bL@g+oX-#KhC z9>Wys$Bu^?eq9wVydPWaI79aKn1UV;)`H0TwOVl3jgc7VH><98&qZ$@-Kk`O5rxoscv`#}pj!sL)jxOxA z`_DcIXBgjBjJ&$NZz2KCe3;M2ESTf@`e%N(Hf_I~8vi0Dz=947U!OjL(Ad_xO+0m? zsSTkTs*P%?t$mo6tC4*7U?fzt+i1MaQ$rdT;;+Nu!h>X1pM1WF&JFmb?yaq z#aoFG+gFAgsxA}n6HsB}johZ2?r4RGD-pF{OnkbZJ>;nWrfh;kFp?(yt_@j#SZFJ? z6GLNdbtJ-4wOYxK^VZGD&fPO=sx>vec)u;)e2>H<4^K{q7(-_^Syr~EvXBykBn4)<>J$mE5o?B}d({LIZZ6721K0M(1{gxP6Ss57us<1+u!@}VO;72kS97DDA zgk&%jl)tkrP%L1EwyEk{F9J#)T7+qBF%qv^7z+@i&- zOExW_TLkXWqMdp*TQ)k!!r#5H$MMq5tz@m$T}v1}Ul$xX2slq+|F@Mg&Na4Gjx%OQ!fdliSu<9!3Fo2(=ERhfRF=c-ME%Y4@v@&Sj% zaBu@RvJwgP@K~KBq$+op&X)TB@5J|@pPackvUa=(O_mU1b;dKm;zP1$sW)7m|N2<$yG-w$?-OLLDEHYe${oa$=)+Sc4EXSCFQkRpkykf&{V1Ccw^dH{=fPwDyD5t`T2OohqEcW6(y?{Remm*mC~p=)1> z-AG&gi?RJ+jtAZNul+{0g(uglkn+*QkptwB(TY0QS*-Rvzbn_^IeT#K33|)5mrlc+ zj-~GR@%3B2+v>0BmS&>QLNlCmDc(%fj0yI$bl~X~3w3R3bW#Tzu3BRTIjh&=>CTLo zCBQl6zKSEf-Qm4}wYOENvPowx9xApnGtU*J&ftFzb``&&Q00Csn;n4SNRX)&%t&gI zE0>*NbN)+KyHvVYE`PyxHXeKLc={!w-CebTpCI%52saKn=573hd#@!OSiu8oSdmf|INQP~ zF8%0D`7UQ%hPm3v3*30$`x^n=F^@hNM~<<@YMQOp%6phn@pWM5&rkIkeW z316inwYtM_*#T|U`sMTC2QJ~5ZGEpzw6}8T7N+Yww%L0%HacW2rz;6?pev z?T-tVnDI^n6{p*t!^fm06;1*LvWPEKl3#gs8Fo={1ymUVr4#?nAEOZ+UROYO5-B*q zJ+^N(uw4^HxG`oJopsS?N?b+;nY*fnQJfU8 zQm+WD?VyXBa90o+T>}@wO~vy|F&gL6_M$G#^eX64=c)T95m5i82x1)`EQLdEzT?n} z?!S5@>suZd>XriR;37iEF^!%nzOG0pGWEL3Tjs83elIu| zzMWtA8T0`09=^)dM+?-(n+px~De6EO_08qsYg8F~!kPjQtfVyT;*Kl?D63%fui8# zYy2{TwpoVV1e2UcFlW>A>Y>%#s~s%KtkGkHi)v0KIFCwYbm`)QEq7@MiClT>6V9iiSaI*gej z*$SOmOlZx?bEY|_7zYA^;Oq}ABKk?rumPe1X*ml26f4pUc%~?b5JMJ|g=M(DA+pW7 z(sOD*zDaQSOQ!v${;)H(ESI3KraQ#7klmXQ-+q;b)mx+>ReS7+osm${;>V3+qFNgh z|H$azWiXs&&-{BAN*I6>D#{_`A zN~c!E>4=Mx`0eJY2B}qsTmV!W=p4`o7jAQwDTf^$bo`#$`XJjUwgc<_RLo?8r3+Dz zyKX1Pb6h|kC7RBoyq_L@KCvsS%F|%`ax-~a^*_jostL*KW?tYb`sLy0 z5dKZ&3b(x^gQr2gYqK~VYW81DgQ zGO5QBwsc{tDSIT$=ZhRFncn4R3=P?ZG2uyQ7HHF|U5cuqM5YDYNyQqLo|lsZ3ZV^|zNrL!SxI-pyV? zwAx!dvU_zq%RiYTUBxTIj!Bd_69Oht+UXQ7&?=4bD$f_rLxf{E#S~f6s!A#=VvO%q z1~T)=MlXl+yKKGOwm=Yzyb-Hgkc+KvTU8O`z`@3d5p$8O{|}DnSGJi^`*P^fi6qJ6 zUbku>%ciOS#X$e*kEAWTc#HEc+31Zj=$+T_i^R^MGBZ+k{s(C>rkHl&ED|pK21&9{ z$6NyIl(XLltg0R5Y5P=`j`;MVrGrBI`{hwXD%R$9OwzgHuLgHhlm%7^fD1XDr=i$+ zP7%~j4J+}fXsUZDsLf4fEtSmt1*q{YBG;Z}I^k{BI6^B z(jFh4hAH@+u>;DTgC3X%!=O~iV_16!txEk$faRv~nQC;~lJW{;=H z1lv+`(jS>v<8ctANJgdE__3NK^sNNcHWsOER4R|u5b2nnl9-nCo9wS{B zHK>y%-&bl{F7xnf)u_*v$<6m?zacA5Rl_d#G)0>tl>^2fU#H$G`gm*Z$>nnH^qdd* z4r$T-9|f*#@PA0V{4ez)x2!Z(r#5tYoT<7x?n{{vdX$?j)SRUD}5po%$-sxj09kULk@i;QVaRe+Zk(UFu9SYBxqg zLz2zizU`a1yEW!V=C^jDPxK!jVR5Tps2`&4u=t+GH3iOHui4&E?Dx|DFxsZCpRdvb z0?gayb#=h8zXvg+LgjU`#ru4b)6L9&YAqrQD!9JFbcNOO}V8q@%!j3)YP` zQuw|Y_JE_BO@^;*=??w$v!iiNuwWniXno+|S~uh65+!VEV>p;|HSNavDQ0ToL}#2N zZq{C4_spELC3p&&W2Wx%&z=ExQVWNUAgog-bIeV58hP=bKmML};;9TJNF=vvZ75F> zh=O~j@-h+^Mny&Gnm(T2xt&zg4fKJ;_V1UX|DY*8VCa11?K3{yp|?GUSD#siJ9pNJ zZuR-ZnwIO}-~G2in`KR(Z+&0iSv~E_W;dFKn2xX$qWaSwHuX%;0QV>)(RE{C&s!l2 zK6bJN1%9x$uo;boR)igP;xk|5p#gK`vVoa|VQ2casnmtEQ}owk8dbozDCOj2$+WI! zw)@ecsExa#I$sf)1K}w?0!;wn7^VkZR~4~wn;oAFeHxr$ddz%`c9 z{>Ykc=x+;3&J5tlI$_MmE-Xft;G|78*~M->pzxY_r1UajG<6f=Mi9k=GYKL?x`Uu# z#okNnbHC13VCc8IkV|a@zu(J;NQI#8hFwyKGpn{t%XQXSJ%;i>o@}C?cSe@x+T)A1{CyN#|K|Lxx3?Fq2RNoi32o|lA0t+@ ze0-ep<}_Vg1VIXg#w*`e6I0gG`X5(_reNUeD#jmuYlIio8`H%`UX?ffvWRsv5T`SN zr6_*5yzt{yBKJ_avp`q)V}nokNQ|#%=}ewGQ+bmGfv|fC*>j5RMOjW7f4)5VV^d6J zw@y&O4r+}v=aef?o$|%5hIe$%`S>vov!-vWpOkEy798u>)FclC1Q%ov_U(C&qy8kj zwC?n;Nc@gEvxgmuEXjptLzgsX#H(DK2z*h)4V}CG7h|b;o8H!iS>{u%qFk(@ix|;< z?{aaC?^OgkOS+#1*_c0GG5D$Jxe2=vr-Ksq&2f?(Ovn)GwlMb{i=f^_`!R3cUYY4v z%s;xp=2!8}kFkeaX4F#jr0+e;30HEDmXeQelmqio*2sEQ0Y{@q$wBK&W0%ezX~Te& z5*y#NRwq`@y?-`qE51+v)D6SQs`cMGDxI1jB*g}XvZa9r%AWV^d^xB1*)5U&kWu3;t!X2>Q}7Vo*K zNw#*I&#^Z!HdjSdQ1U@lG1!}SloJ)nPg}UlB(oke~+3z3m zqVaDs$07xV58I~QQd}H)V0-O{h+|Z;f3p(zn5m1=tP255Q+0+MSH9}zHnQ@w-@$>= zxw1=LXg4Kp-C*!Rc|^j%`VZ6Kd;bm=ZI|VJ@|kbky59l*=Av5_g7H*#rtn%Rb1?&S z_7UOjEW=C8Y7}=9Iak4j1TOSepF)G&=4TSWeg?^2-FhS(zJ7Mi=61N^=^4A^dRU>* z)2nOlN7|{$E+)BQ!svsLi^K*h?~S7cfA8!Ln$^)e&^fS}G~TabdINDC2sB%d;mXqr zcc^J5-)Io*Z(DcJ=q4_#c_kJSyNxwhFntG5x;t~5CnA@xcwM)8@8=Fw-CHNAep>8y ze4U3K=N<}rt*O+k&Z4oz0bd+ zk%QKK^!>kwrFvs||1|=6e*|13tN#bezy62ee-ioU`eD4yqwx>12dq7k1r`4VJ&_Hm z+gTyY;!XYm_S`W!kq&Xl82xS`GCLrZ+r`jCQ!fj!2Z9EM^N6RO~ta4Vv#RB|+T!=NLjOfR{=BXVPw!M=)# zvnFgJB^S$FjI7sNim#p?47u{1qTVpI)_}A9{>8#?KgKPqYDD3?TRuX@6%P+z&f~>1 zcLPuL+*YHanYn(gMjfEF3I}g&EIChUS?Ua_7_9P4;31$vJL&!Z2ACgarBT>v0EIHLBQ8Ju!zKRk z(KShC39@lXRu&hQ5acKNNP#c?Fr|beemvynz?TCsr;4TaIMl zi93z5o5vtV1IW=a=1!xC(a7ii=NZ8r^XZnlKvs-yFOOcl2AR55K}_$9(lJ@Ly$mZs#OX?xL$zqI& zTR+Q2fsYnw{*Rl4wlQ%tMr+@IJ8AwCCpYPz@x;H=_X+c#xMS?l++z%}K$H%^v$^&j ziK?$)iy8BX|HKnx@_99HUgL9i+BFM}fULY}katK{+BFv7I7cEiKy~;v`LxE-;1t@N z)PZl$xa^qlMN{=J*=PRFtt(!ZiWb=UU(Dn(68y>fqyuW&FEv5$q-{_$t9#>+dmZY50_mz`+g3 zb&4q#^K`6UjVc;t*4zk*ed`p%cycoP*lFL~Iz40ayi67LQ3!p*=ApxV@HAXijnVPO zjZ2@+nN>lMM<{;K&GqZXe5L>5Jn3#bsoqvjzdGEk8u4PEU(kFLYRj-YVY>4c-`mW> z*G6;8oDVXxH2U%V`g{K?tYw0<20(ybswCYcU&|>|KTmFOg{J1asheVI_sM^YlAnP` z8NfwhJy@f)?2xRi2@8z3l84X|+XP=&AQk;Xm7_WDsX0jB0U{7lCi1!Q?yQ=R?VIV8 zf>ielowtJN$0{9TN`GwT8{UNqqUi!MzXp}1UtwJFs@`d3`eERPi!)oD14z8BBHWC6 zhQl8#=9Hl9s>7_?{DD(KdpG4|PAQ9q%xU-qCDU7(HE1-1`0__0#YRcZnX4kzuwB8cF`e1o^DB5 zV4@pw8)HvHu7ZTZFUu-`@`Tl`RT(#ZT>tZwg}+~ST?&CV0|q!6nCIW`XEKQF+&DGJ021(iaH zZ=Ua3*r_Lvs;e*i`0o$)D04w%y;Igg8JNtUjNz!lB+-m>tPwT_^`mPFd$m7OIiF}# zEgI{W$E98Qh*xe0&r{)~l8ZMB?;LdK2vBkgx(mRAy9iKTnfd2mRbgo;(M@SxM6XaL zF*9@-9p3sjVSnr4d3luHwKz-M-lWN`)GSjX-S33}&T@31FAREn+OA|{x{Qox1kHVQ z1~bJM#F4nxVEG#V<>dTh%&htJ^b=Gh2r4jg%giinx9|&#;qu?7PjK-;gc2!s;`7``sHVQR#eS;8rEZU*(W; zW3%ZF7!VU|JP~iv27a4`SKT*`hx~fVdPUaqTXnyqrc#jx$10yrL(IsLjkam?Q5hTP z7YZ^teOlXya;u$iVOr+w1abIIdV{j9YKvbXMIF{20`lv&_ngMIWP|5f<#$TVS# zQ7NavZemd>o%hD+;}+$qUY3pWs4w~OdoQ4Mo62>U5uebd&G>-!L~lWw_(j{HD5U-Q zw#e^e0neu`xAKp}dzlQ&>ye=ZE`W-_!O+NwSo%(vmJfa!4&OAI7-tdLLFYjPN;h-` zQkQCzV4KLDqlL*6zZ*lgzyxMKfB-zi3uwjtM+;*1M3YE`n9CX=!o8Q-KtbNpGRuhBAqGHFqizfQH&U)n* zXJ>+-aEN59#&=A8xnGpc!AEJ`k%ws4v!NqB51raiObkg-y;s=z>_YkzQ+0Ob^-LPn z8FI@N5E+ASy+y-r-JiS98np)fBR-(Gn8NPB94SSQyx>371p4w3(`Q-m4y|SdmDKD< zl(f2G7h2AM9o^-)*fX=`N5`6TivFhN{g*fo2c8M$jVK90r#-JfDwziw6U@C>6g)O(P^pi9{wjg|9&N;@sgmy*W=pTfe}jDqf^$Fe|(+$1omI;KSU%WHU+8vnnF|50ozoY1GYJ=UGc-dHbF%%!l6{TocvL#qP|2rX-;= zmQyBL+vkVp6Emxgl8)m-dCOe7{(DQ=oQ)y?{=uVU%D(6h57IWWp+=P^2wr5x0G0re zyP2RRgU;$=Xgkv32QgU!&8DM4Y4DwFs+db}h@ftF{hD(5Ys8=|b=8WNiwiV@qC>EY z?~BgZdp1(V#RT2jl#*}U$6R*m$~l#b-f`h!h=kwMpKnFa1W&wD?&zb(HPtqGJTb8n z4-1^^#$#Q-^8e%tgT zBxRY?hh^%b?=S;J8aNFQISaa;(_qQg8&DGzfUumL7_{+n>HOWG94UuZ+89r^dU~ko zkQ*|jXFk<$DgRvV?wk)xAcp6=73DIIb(FQ3E;y`~m5VVVcPJUtixD^e z^1AF4%2wLUGP>swp@}q4=_RM(-Qiw?TcFEMY}>tgM_kotn`_}f36yzc)4nz(pEu_# zHnxY+hx5ReXTVEPuLq~PcMY>KAxFLFI@dfn_ZcGDi!yG>Uc{7q$D`!cig)TMI+@nY~$!sXto4MNkxRwT4S z-BbD%W-pI(xIi6c(SN$P2E#LF_bC~AhbPcKtBKKnN*cMOZ;j(kf+bHx$8O|$9H7PA zw+8&OBMhTnmm@cY;?U~FtHXVa3s+Rkl&NbZ9N53M*v%^r*YjQH`K+a9z{T2m4z#^F{<&Tn zqEP1B;9>LmzLA0Tc!&8WcSgK4y^|`Jf^+j9*4)5p-Dv}b1f$kLFE6fL=f1dSVMa9ri~cEh9g~^5#@wRt zCIz#YBE5Lzlt_OSNtKk2qvr0Jnkf&uIKV0k9R4K>W?~|V{a&k#H}A_*XL$40gN{_G zwrr7^MYvlN3$>FTYHC>i`%Gtj1Kal~nX_Y0y_1z;D8GK7 zUsQ?e;cuJuDe2X#s$8GEVyOcDxd{p0LB4V5%2)K@NSUwLZm9p2Ksmt$XMD*XXVeRR zz=KrCpgsKRpj70wbQbw>JM^P#0;b6#$BOQ>G>#(V&o`G3Ay;{z66)fa1APLf=6C!t8-XJB=c-EPstR6^bOJ0JUOBk1YttJvjBX!T8TOsECZ za15*-hYSUXB(vWV_nr$8CI=e*AGR0nRvFl33_a<9l2{(6kuZ9S(w#2Q2JH3y5^_@f zSiiw0k-_}wL%xD8$$RMFo3s&qL&22wjK}!sk4iSxayK_~1cWkKeBPu6zx%#jMK}VC zoN)H=5L@T&VJ%?*7CWO6a5D0JW2Sf}2wPDf=jV~prqU7mPk#WwWo@ZT4L)VKv&#@7 zh3pjULJkCzWheUp8I#YGN*58_zDIG|U2U#E1ZcWh?a6me6DY=MJ3gW%sLR>CCo-GS z)MLQf@D$bU?!chicb`!@=411RG?L>T0m{k9Oqs<=!-QUiov6rs^}FiUM|655c539@ zOvZV1z*1K7-0e>h`^pC^8;2>UELQ8jaItsJG4}~&oM77>QGiNKp`_N=?5b>T%!yuh ziWLJ)ipttWkc{J(^=U;kqJQn>3aV`_mBr5`NCxUl*)8hkGygcB zhF!hat|p)~CAR3`a0BSSZu)C7WVLM7#=t6#w-z6^0j~5g!_;VX^{#97Q`~8DIM&9( zTfxti-p~n*)ipbfd{z=_ywlFX;{KSi4yergK+&&mvYej%SgS*lB61V=jV76kPnYCy zJY$XXUZ?HbUQVsxv2|vaR{5&AQQa9MZ3|O_8yXmw)tR1p^{R?k{JbiE*pCDW!QIN= zy3+534hn0pAATb7fIo{^?{bG+fa&seHwixA*O@t8r=-cv4SmwO768W>%nbDI6XmgV z5pG+Wc>_2n5?#CaVr1HLop`O>@7k;VH9R?Rz4z&^OcFSLRGR#^89c>rUhX>Ba(JiU z*J|EFo;}Ej{YsH4eRiV#nKMI45uL^ ze3CI_6H@HVnH^YBHCM;BqB&p0*1L-)MWOzBrt&Rf`Ehp%; z{6Y&^K~$p#4aZ{2vI6h6VzSmRgO3bw1t?SMAoqntj_vz%(5+vn1rwq6oVh~{Xi$>3 z24z6Ts;QE+W4k9m5p)<#;2j0Vg!R2g^Dj;XHxXR543b)xO(Twqp&7oSN-i3Wp+yvk zO+AVdHo`K0(g2M(#(4YzHLMeq#Q+}$E9R8=EP5g6-GUkB@;K&54T`V7mRby4cb($g z3!s!ZN(exVC_?OS|2^@Qg@6C_xzZkp3g9jqxMws1&GsMWW~-pvEcY03m{`03)kE;& zNBl&YUA@s9-|G;^ysvvd7vV`>hMknLgS%y93xw)Tx4NtMiz%2fCB;5e1Rd2ymX)MLx1~iY&w9IiwV>u zrobczu8ee{vOA&A=_%2{QuDFq-5)v=Vl0ZMR46mE)rWGEY^H+4IfklKo9m4;fz|wt z=3K(!A=b*RJB~MO)UZb1hi?$V5IZB% z)E#SeN>_mdokYU`qCkje@x{+|g!*WgD~~4_qm&g6dLa|`2!hVk9ax$U!To@{z`-rb z|AUCHfD*|6%Nn?%wNXUjUbTasrqv+K&WO2Lt#Cu-G}oUErCzTU>PCvk1x2;BLRLTzpE8v*V|uZqan@C(!HB9ge-$g zmUzd~6{q>q+AmhC7kLg+n7gWlcEYTv7klSEA90B_vuDI_mZZDBJE5N?Mv(X=Ki{5o z>t$W5P$a>Z=|VA0*A&3FfrhW!B(XeS{h=63<#K%Li3F$hx%TrpCOVWK-Yo zc~qUe+(XSZ_LkYUZMg>u&3>@CnM-R_R{Zk;x6YSkr5~NM1BmjOIKlZIv8)(@=L8Y; z3PU_}nNsa8S9{4~!z2U7bNto!+N>Y{FLq98o9I_R8v>Sneese<-;N-CKwXRkyg=`Y zt^u;WLkm8=d9vE9wSl=zXYI*h;M>wKs8pZ*8NZ(`ujF2cLSd z-fXiDdy2P=7yga>K5}CRQ3{qd_6jOcI8uQ7j?@#M`YBGomEf(Xtuypfnf{qM$XuWw zt=;MkT20giPiLFzbK?qLUqz}UBTEw^i7A%~%3f@o4BEoE%i7A*wY0GCbTRFyPHD!@rOdLm2Sw)8C61dWja=qnR$98ruEJ(3# z>4p8gib=xpOlNVMRU60xbjq2l5Yf`+7Z)D?w&mGlnF(~cU|UoBqU{VX)I#eZABKE_ z&Q%E2?E6M_$EK=QyZ;Ddh6}6hXzDos%DJER)$9?GuVjEIb8Iray6k!T+etO84%&L{ zk>8f|ATS2tE3}8`ZNPbeY=4Vx)L8P>ud!Y0BAW*r{&$MYBTh$wrS4OXPYXA~4Cu(W z=oc1-aN~Io*BghU9k%)J9@&~zC=O?szB4QJ#*z(?a@ro^AKXG*cC_|OjC9s%YKA`T z(CjF1oO!aLIhD|@@k6iR7cqqa(-Zv8hM05qZ6EDwnz;6vel;Z!RJ^pq4EVfTQoIy& zI#`o~QP;LR^9-M-N2}X+wkGFyk#>L#3!nTD%_27}eBIAdZsV;lwU(KvkdpJb^)gXJZ(4^7?0<1zf-mU6*cC;+p>|fO| zOO|BBE(@7VFLR_bGv)}Mq|sVfa}0em?etq!haP>M9qF8xa=q%P&+l~CxtBh%)_9Fo z!=xlyyMM>w$MfRuYj;ZA+HVxT>213H^ZCuQ8*BGg_E}4u=B0RlB}jZY0s75kOa)rz z5R!ab69^K&aQ0we`6GZ;{+J?UC1$pXYM)pZXfxnCk2cvrN;%%CH1Ag}WPaCcdnc98oPb`SgQWGos-kg6td+#M8Y2=b~Xa>6iZvMw$v%A zwf@FxL4oHt^A1TR6nTZeCVDTT7t>IepBEd7w9Giv=~tQ3bo#N8%#Alx?0>bX&pg>e zdu6IR`gpn2F17ZeT92mg)c5YGN#GtDdDG(Fa9raF>(u_0y6aa0rh4h2(tFUraYfX$ zu-bB0HQI)kx(HAgCm2*M|xZO69ZKC%?(6NhJXHMc53i(^q0D{wN~wFdi0R!eZM-PQUm%Q z3comMjO)QA66K(ujcp#_H52!fSXh9O*`sKSgEDlgoHxtyZU21W$2|)F@)zLw|ND_y zCL#eWpE8S5&fZN_f`ow};YbPOYxb~&x9r_IVtVmFdKZL(Jl)dzH_RJ8bT&*Ai19)| zkCcHhuRIXu1rAkmqvX_hhSa#<-sFwZH5S-wH{gpd07S*hm7%*k(gNGa<@8 zH*`RoHsjy8@2dfTxu1EILZ=~VlEphYV4VnLg^?h)XanQBne7mRC?F6VMa(VM7)f{q z6anz2(6x&gdgVm$DeP&}PMf@2%oLAdr~}ERXD6szwQHC3(T=U(^+w4l1G!?`?6I8u z!G=N5vbPmihmv@ic)1#t~(a#B{u?2Zp&ketjq z??iNUKhE({9f}Y#EU)A4g_-zg^tYW21@`mzuxau)fH%PZq`m&!Z!i zNA0j08!z(srD|=r4(wyaNuPInl?kw%IP>9xgAdQuP176`w4SFeLpy$S-;%RDf|m{q z9`6fQ9I1#L8}iLVKlRzad2LopSQ~Z;ts5Hn2=bSuCv~=B%J;=!bRSB6-Ov01={@G3 zREFkIgjNtYDN4KiO&qMlxn{&O;~ z7B@TQZ#(_M_i_7A?`5e9ox^ZobLNPST>MG$QaKq@JG2l|?|q_nLzt~VhAd!ZF_lG; z>wo18s~G1*v$R4poF>M8+x>VEC>7VwLcbhKC)u(Q(ro-Dg2KSF;XEo2?u1VM)Nyc+ z#qM~ZBNy1wjZ-!RrgF5cma!@VUo8Xv;3~m1ML--{no%?B1cS#TEr71!S zKNM#O8y0mrMicAae$7evpo(OPa3#leWhUR97bpPZivnV9X7$IyliyzUp0q^>q6KGL z_1rS^6iB`eUw>A{dQMw-LqWj~2zemnVo53Bt65X_*7 z&yFFM?@)SEjfG!#xD*I#>JaVy?ZKKbvikbBCTUnMx^@%!VW!mfb2?!9IrkMoI1e4J zH?JgBxsL6ew>)^2PCx8 z?ydopUJsi;`vclhg~4rvUDf!fYbh!>4RW}R^vE;Ee8Q7R@4L|tY0LQ2|t`v))_Kq)^5Bt(zD*oA*hbgb}^N93U&7bFqN$@!N31D?FMt| zUG%98MtB@U_hkeLl(YhN4Ei|vW1+A308s=Fkn?_Yp{wN;iQqX4>v=8ODSKh1rSes> z7MN#$%X~Ou_r=W^h>$~aabp`Lue@Y1AJVDYr@=KS{J;=9tK{wJlshk&57#sA&o6gz z6x{|ev$fWO$<1?ONcytt)d{+Yu-rjD5)WY>VKkabqE>TW@E$3c`59r(#OPWhMTP@?l>GP7(JCoDE9L<3^nYk<`LM^NPfB_O)q1%htZk>yWiJ^=|fpp$J5bO?*_sD54 z9-da4IQ`hWVUd_hdGND%f^R=@3|(`i?a#IGv!Xn>=QigR-iP7A!60mlqhC3Xe1_K4 z4{j&9IN}jEB7-7?tD@Pt8{Utu#>t>Ry0bwUOMT34ey9Kd%rFkxJ=S5o*g3NzdO5Xb zo)wf$Wp(dD@!kOSV!YFw-<=U|izG+6jx%Tz99QXsP!$%Jh(mqAQ!wu!q}7&8J?pd` z*iQNQ61FR*_~}bAOq3jn*?7{EZMn<7*MaaF>NnG%7!F+Do-nJJr6Xoyo5RGD9qubo z?uk>oTF|}aZ=y__AI+=w1EDBLwBPI$hjwqg6??@|DhKnLaip(i|4VYWEP6);vt;N% z@%mwQ`P|9vKcLKD!xQa$bGxNn3pYhIsDbBy5EAIxi|afij%+xBmW6_M`5VYHw_}gA z!l{#JPPByFsgjR-!BX8kT}ATaxM7L&nT4V9cgorFQFF_4QtJs0kk#Srv1NlSIz?7i zU1pV=yaPl4hxHn;^z4M2EpSX>=| zEZv<4mApxS#srb5kVWWa`KwzMRxZpFB6L%gp)VFrPSAo>%q)&eOtw(F!G+#4Smrf$ zUS-4@vSE+*+VqDsSzLd4JRjrx`P2lr2c2s_b`LoiAlGRny>ibfn7nAz4)!Io_BTF) z-Eed0@MiDWRS9sUJiZ-Gl^1S5w$T|F3$ik1Gx<<1`t`Bikd`81a!lU+ZSPO#)}=B7 zb=@&+d%=LYUWv*+n+9pb<)VQ%HM^wQcZk{UB7&4mrc>_)}x?h@mO2R7JjmEE0e`CX%oa?O7RuI0GtmEVu z&cj41uZh1&GKW{%q)F79n%pVas(Ynh)^)^D!JVFz5 zUy?#z`JaBzJ9v)zn4WLd{J2!y-D%?nz@Y6Gjypqb1>U?}2T~MtX2o>)9CQ}I37AAv zuXPIzqsd1=V**wxwR+@+jXkP^iXc4WRt(rD_da#{#O{iT6$%8ZOx~T^=k3zB*46!@ z)+e}vZ|p$PffOs;=~FA!XcQQ=nu94qab zr%SiXVzr#Jz)8pn(lvPHbJ`Qh$Gt)Ex(p>(NIa$6Ep z)}>2mY;DD7wgkWXyYH~uz7;o>0NdcxVzqXpC2B1*)j_%vz`I z6-(;(k%}>jO#DwrM+3SeZJUZ$wH%p7v!(v8ndiT*9AJO`CO9!!4@YNisG-GhvjyPa zL1Y;0KqcDFpP{6}+FVjSRBHB-N;H5;W8V`00}47CkwOKTx*e>eN)zD&;@O9#eGPPk z9B><4Zly`)p6jh}wcbLBV6w@h7%3lNrgImLdE-_;ABv|H7*E9>%$!{-zhR^3a*HbP z7#!nJ`em$n|B)j5$t;b9huV8)B5Bl3KeY7heOcwLriUMo98vNP z>dOl|9is=Fh8Y^?o`#p#?8^!scX%t!3@GMR4f4Q6#b=Awjf+w8=*y<9)O_)*J=X5U zSIj zb8xT}eYmrS{#<9jj{2Bokzt^lv9)Xr?1ts=DAUf6n{ZS6rSeE`+56fNO@;>P6vS?9 z@UIEd`>hdj93vls;sa^zx43T=W$o4EB_=E)-AN{d;ttY#5~OlT9^Md6KMq9XmWk*V zY@P%1&tU0>h?2^5q~z0;na~J)%@i}BsCHAY>y*~vXP`cIF;EEb=Z(FGZ7#vkRMJV+ z#xjhm5i|IitEGYEA)kCAQ*(SdhZd>}R~t?7plDT>f`I(ZEHE*vy17UB1t7qE zzq7BR_WPWFg$mHfRZG=5P;`p6b_IA9Bqw`AIyY6s0_K zEDJq0CXzH|O)Xa`z-2&%YCEZK*j>+gnu{$sY%R3EVqW;bro>5vnxXlG((GLkC@<-$ z*eo2Wm@5*~$$3FE=xfu-8Bb^u`q3``2U%3Zy1~QBi<${!w?7~+4iDc77sR}d{KB~= zV;kv?n3ox2tA9XTR705#f!vKdfyw|6^QPvLEW?Ee*v*3=$O3baJb1T@&)q@(u}urx zGBoPt$%7SwtYNQ(+-V{ad+GE20~P6^;Kgsh&dkw~>o^FMy!Bk6L-~ulw!uV&w`%{lpO{& zi3U_NH{F;vo+n?*iHJIxQg9;Opx!2~OxK(49yQ9L=BAEfvKyC89^c^@eezI^bSU3~ z!y_(HUd~aWI*m`rjMiltk~p-j2+K%plxgLJ-mcj~;BLI)Yg963Uv$WgQrn{m0PLnC zqW(3vM@`Rb7)Kd>OaJ7WFQf0KQy*$uKyosJz1A}Jye8Ut=LBprXnj=xeiMG<)<}$} zmI<|ah&8FmiNBry0Q%88-BtJ#*NsP!Uw-W(z@d$&7FjhVqbH1V2o#ftN;{%dw815P zJ&wITkqsz>7Dr0wP#+%bSX^JksFNe+AxmXMiu0MM3kyR0F1^TOObhr@cwC;UgP}w; z*KUNC4#{w767i+_K{)EEL})z(K$%GPVlg=fk2U4goi0k|P7GAE?L&o6biLe%a32ck z2-isZT5~>tVNAGp2@!+Qea&s0W?%TRR?HQ;6rVlOIKlut1yJ1>MM@nCqJQ*Ax1a@W z4~74LCZRE)ms@ELD701gY2&e8oYFVIW|zVkAv*r`c0o)Zu;Wg)Nv>vGAu)k0y==bU zDOeK$cNpPA5g)9A&IQ6iE(uOSOI0uS zfD0jpKBMwn3(U!6ZP)Z3eTqRY=sm|j9~Ed><$zwJf33x=RkMFU=hmmChb;%heN?I{ zU$@gPJy~!4nV&n9_4HDK@x5l`#2D+1Dj6lDwXxA8(oo0L1h86P{iz=g>3k^n7F*zd zp4$0y6=w^$z^_gsoC#}N9ZIXfEXL4-U^{y$novJ_c;db(p{-PvZs4{m!nX%4MgfC;tI(w}*oD){rPw#oE=OUu6_E*qSVFQr#RPxO1B z2c#YvwY{(^#1>)Zdg+8^9G%|UOXr)%ZJ68LxWP$(54$d##ozF<(mkj_xifEl=1p%1 z_EXNMIN4EvFuBD!r^FgLk7cvBVCZ)&bFew&U|@JT!#f}W0uPcemC|ImyR#Yr4CnPn>#-rm|x7m z*WSyr*H-WJ+NOs5l@De5XwxGzB9q3FMwjBl)%bIOfg{VmC~Jc{ezm$0cOgHhW?Agv z;aro8X+uWR=;4_%3f(M|$GqXEf&(q)(Yme8tnZAxsHrL3N0kEqDF0q)$)%434VY=w zQ)Kep_=oa8?)dfUhob4JS#=<1Xo={ilkKch*{*1)WjIg*CaZQXzERP}2Yd(wU$-_8 z2KVSev}a=fdt&z9rF~YL#;o^qtxKn1=s))HVO z^GCt_1)3*c{iKXC78@qx6V{f%Q2FGn{^zdSD1-dc)gU#V?teq0QLQX60HjK?r4_;;JV;ATpTXaBMm6xUIo|!XX7~Rh|sHrZvW7+yiRxyiY zs#ZBzrjcG+^3Fpx3f$+7L6Xo5t*siE;Dn+Q0PZ!?s12S{0J>u1gLW&yDO<*voAu)B zXx1{zn+X%jA94MgzZXuIiIC-?Q-KCqF2+nDj&Q@mLvvsYHQ{xz>KiWez`0Yc{&I6IS74O)YK*hWQ)Khxv{H?vf53)*>A~s5 zV=9kDy?m1F{p+K@4qvnD6TWG^IAcC-lbzL%&al|0cQFPGL2bbFqsDN`!|FS`OJnDi zxNJqg8w-KS{36;}dHqo$zlk|)t0zMe9mMo0gou>-_wP3O{d?CwyamP%kcnoV&WhI5|IXeZ%}a;ShtKgsC0I)!vyq&UEp0#rvfuP zYdbsV$?{u1Iu^nZ+qzlb*|99gY(>5Ozbco|%fZK4Xlc;T0!=1uA-zU#?Xz>aN06U_`F%=QuDiCWhccBQ1=%NsewKDj=1vQCJoLuyQ+n)Q z9F!W@DA_c-$og@r%7H1!1^^vVsvI(tP1#s+F5ovRknzdjPVHY_&v z%!TFNORLTENNe{<*Zdpa0SWW+_mP2}jrPbOW{-P{0TiC-Q=uScrI7-5^Re$d-MkTE z16wP*aUoX_eA_Fcx2fwZ{ClhiEH3#E)9q?>Kn6Oam)_S7%q|C%%OqJCEa6^XQgNE+ zIRHAV9lYb~tff1?z6lH*TJmx&d}ort{naV+s?=!%H+oz?Mo+8Q;py57y$adb1J-fl z@r;=2<{QU`#G}IRaUv%}S`Ioskraeww(g2=ucZkfC*ULW|4%vLzb}^mx5qDiXCQnm z+Gp6U^gd^5gOCzg53@(--?F!)T4`G8JWM%Xlx>`|jl7NoS(O>S$>GYa4O3u@%q-cY#GHUwAB;YH>N^__LC(~ntKv&iW$~z8RDhKfFv%aHvIOcc#N{W{l3PIz6}tx;}9=b2>#p!qM)zQEF|YJ3uEg0)fFXKG_C)C7QP zX>HX55SH)hp00QdZ5`-w@(H*)H6pZ@-zra0u%PTfNRt24;_9m3 z1!zZ!xB9HNA4}VE_=|5-X6WMAS_S`$5|kD-FJ<^hHCxX3ZOX-aK-UB?9GelvWWZ$qT(odOk8p!nTTTZX;2ZX`ed5pR;lACQZ@6+(uze^^X#3i{{s z>-pO`JyqbBc$LK7A3RHxZr_~+rwJ?b!P+)iu?)qu2G8q~|G*>%nX92DW_X`l^6SI( zw_9Jl+K&xv8B;cyUsp)++5d$Fkpjq;o-$ADd4jYtO%)+{5$LJ5{Kwu-fWZUa6%DIZ zS;$M1D9f`z7GL{PqN*<1@6G(n;DWfuXP3$gBd3LBEAvI)%-HJ%b0c~WCJ$XHi4VK2 zJKz5hI1!O|vfj5XCT$$zb}_-Sqv8?#jc;IIZ)Y95~Kz-xUHYd&M| zr$6?xaowKL^(ydmyP+3~w)3`=^*pe!Az9^2Z=qr}q%v?B}M%GnNF)hg2(lA%<1cS$EaiW{!SP7dUmIktYvS=Bef{jDV|(r zxD=MXp7goEVv*rv1wvIHz(p3iGvu}0_4#ZA-Kv7@6DxB+xTV25fo4^?U^A!*qB+4L z0T^p-#nnIP-xOP(X);37bG07ibMyv}zk19@fI0g)vlxEux8QQ*Z_%f+>rl|pJvpS; zC3Yx>E9KJm&V2VlJlo-yCONZMNQC z5TJ;UtQ^PPha{4_;<5bE(CIHDkoj{_c$6QUGv1+x7d)*vLLm=#OQ;Upjd5BVJr7>` z5uBr3oIAC3Duxm76tFQ8{H9#sp0+vMyV&W{&IO?Au1rSVvxb-yQN%pmCe{wTMhVR+ zR+HQ=RKE@HWx0Y%H>VYgZTldDTSY8?K3rodn>`B6NiIbQT1yh+O?<;M3wkQN!zSkHkfu8`Cy=gzsgKD{zt1JTX} z-Jne=q#w=EeUrX9V$s^W@UT5gJ-Kf5nAhH@q{v22E$84=V#NShlB$~6n-+&Bui(pS zMQ6#ltKF403=pX7CiKZVYDC=OQty+p%O?L^Mqf)dj>v&5bo^&&doiNh9@uSpFxgI| z0+Vx|IKoV$42mmy{U39!kq+?s2nAIh4*7iM&IhGg!B84lg6CGMy|sHdd$dGBC zIry^ac92HI7V|()^at>h=@b&#N=!X&7!h@PX?cEL$S5>gwMbdIgz6UCpqa?N}@WM`;%6S#o%m-xu_pL8>dL8wc_P0>O z0x8Xs$vpwuG^O5@YyPqRlZO-VA1S?%ow8i;G3^sPkEPe8k7Ay=v3~a2tHjzz&NHXz zhH_&?0XQh&_gTZ9j&6?gx&}eF0^SRi5_+2wlVsD`!#DE$-)kM);TCj#W5syBipq*r zZ;dP(?XEOdHi?;!Ht<$F_uVjiNi+FwZ3_V*4gBg(W2-IJJ>;dd4+4|pVQhK6(-u*~ zAbH#%fsOMKrf=k{uQH+7-mt|p6>M4EW5_Aw0aiq$IjeBmm|cl5`p&bQA@q8{X)58A zx4x^|D=%v|e&o`u=fL^B$#&P_u+t|5Ar`6)J zG*jz%!Pmr_T3W};(-JX&Q4E9=MNzJjN#YS@HE};ie1od*@^~_*)4* zR(hf>_f5WRm6)?{W3*aLlSB&Z&W>L7U#mNT2er$h8&=U*%nUTn4GwpITYP!KEwpyu z72lO!np@~(?&*K?k)_p@gLNUn1*Pf$DF3(myl&Hq-D`zs`-8yK7EJc08*CL^yrX^` z!IBb(p0X+p$B0SSZjRPQA<;oSRC$AX9c$}~K_-5yQ2syxY%m{kvr{;h5YwanCEGC# z(yumGX}Yc6NnB2KVm#6M0}96%wGkjAipf5zyktVli~*|!jIBYd&K`hny$xQA2wdEH zMAe@mDgT{f-@MUzC)Bolg^^sHp665q&!^Rcdm-} z4!EV{IBq#(I${9|N|)|=I(eD-@Ul$}gUl0;+j`>85rzQo&MI|`X+#ogkKV>=;cM1r zT`6o|AM8euEaMi#Kg}k=kT4wFrM#Xiz?p%gXF3V}#GEN2V8^;O#^yExPJ=>GuWrb& zPFTOBBg5Y5uk4nmiB67P2GTRH&HV?ih`zt*o%FMDF2{j%XDh4mIPv`ak~Z4?JPfHa z7j_*+Q^;i&al8)L0V*dVE+ZywyK1Ak-xV1HUQ*jflLF8!2^2JMUeMQFWcAgCPFAV^ zK0dK&{C+~si*c86mRw2j75$f{oK8Wigc={Y=y>ehlfl?}DAU2%nY)_?R8ZQ4hP21eJi_2-^g++ ze2-JVJv*-*7^c~dbpb;?LW2eVTs<97{H;*$Tis@e zz#i|JdnZ6b$)a*vjG1fEn`O_~Ne1_8p99U5x-XuA8`BBKR}{Y=^xuXc{E5>**r3em z_zwttv;%-3b#RULfE0EpMtpkjs?->DH0?TJ zPh|KBwK2d%h4rZ^j6)g%-?d?4eY2p1EBga7wSDBX$!j2?o5lFRZzJ=OF3G&h1m(uZ zqVw$S|Ke1m%^_f#cCL~HM#y4%G0*7|jU(d!{@*2I0)?h!naMDF>DD-h`3unE`w?Kf zXSIxeWb6W_z_(7xU#>;|8Ue$htk*iHF9bdI(do&PqZ8SRPhyM(8Oj+8 z6s!SoxmvP1U>n|JAiGtTC&+x_y{TsTyrXgOik@MkKRqcD>v?`vEo1t@+wXPhIB`*; zMeF4AkpVOl^|4*O+}_sRmbkpgh~losS3%VH3iOX;&4svF;5s7(A$fAzM&F8+O}UHs)BCyqG%$ zI*1;Y+`%+mh`m~ijt5Lee7GA@qB5>7sMeysh7s_!ATht5osog}D^A z>ZnHy@@eSJmLR*&`6wz2NH@_B*IrMq6= zZyV}Izu9pj@f+_7&2GP2=%t?;Ws(@jA1JpBuV0Aa762W4(MBex;c>D=yG2#skay$_ zuY|jFMVwcTgHJWE-CDuJ_RQh68X`qtD+lPE%gLlJx(+m#%9B=#4Yzg|!z$?xj(UPw0SNzo>;# zZ)Wekec@h)uXEG<*X50{b;o=|i8^W0dyDUD9y5RV13K@H4NmxCYSdjG&*4u!Q95Sv zX4XTv_{x&(Q+*-*!>wxN29{7C=f+3s(}1Z-eX{RBh?!~ai~Wg1{+rk@g@fS_0rhqx zk4X95^xZhPH**c^8aysXS(>6=Aj{r8f5X6U>8~S}q=%=+rQ21oH~$J}ZD6juy(%~p zL=lrHx#iIXZ_GP#dSUU|+UgR<@#n91SNw#Cm)K^j$7+mft>+YX1V-W>zJVM;NZ&x!@%#kFWYJT{Gfp zZ=q-KapCqNFR#_7*=K}LxCT0)ki5$Kf9|S<`sEoZmv*nW^j;PTkGvSzA^}DXX6P*` z)MK_JQ-e34wumvb327`_#qSL-o+5OOdU#OC?(42vGBQ=o?0w2h(0b>F2ucQ*_m>LY z*nH(MLLV8fw%tVJJ-YiAxH|>Rob#0-AR2QrS7RG{d?DSNZ*OKf!J%z#tTX-pT_*sG zQVNvt05B=M39#(Ey0`HEYS5gQ)tVoWAZy%haPy)=zc8S{=F10f7Hp|$xcqhmg0;hi zNE~Q>Tf+Ugm{Mr5jZfHE0*lJmG3WeRnk>&VM)dHXk*fMxQ+$4j|7A$BJn3CJMY_*=kZ3%_sJ_5}uaii_)er&Li2>znzq3dIcjO=d- zE^xuz_GL8z&g@t8`SV}RA%=y`E2YoZlq<$HXKoJy^#Y%FpJ-G^1%sTCuI)Pg3T$ka zf-kF%a*Z>X6xfTVeTGJz>NaQ)tm3b)C~*CAeI*>FIioH6+U$d*Jkfu80~kr8%oR9a zn+zYlE9!P(8}TP%QNEtbZ>33#Ow$?Xi$t7W1E<_<1oR-A*lz`EnknZpGVy)1A4UGg zFV@Wl?CofN4dg!5JpUG~IrXet1f-T=Hi&Eiau-+6XASCa4bt30I^Rt_pH%(!F4Kml zp7!#0_P6}-9M(Eyr8r@b=7mXefx!?krUu5=x}X*GS_XM?K;G+x~KLPKZ0lOCaZrtAvxAF${hpU%y47)k~Jst>KUwq`2UpZa)^nfOdW2iE@rz)AUhCCqw3(V&tuB#x~*M6Yh03^^h zskT$0H)3#>5njSqL5*>#LdR28=Mazb48Qv=O#E8!d(J*or2k+RUVlu4I3_2@2*1z| zDASa=((IebAM`kVNjdZM52za**(xkT43QRP8f)cBsRYII&PI>gmc1J03$J5u$>Fsy zdG~JVfRbmz@vZRs!%E~y?R~BncFLjNqOEx{x4BibqksP@lqUzmlm|gAkZbI(A^$ADz0vaHO;%O5d3E1e$C(&-WUd-} zp6VbCXPCiDWUO*-aT!R7$3V>_BPKV!U`OGKI#J#5C?^BR0(_-m!5avq=h#GLck_W% z#ABY?%dH!y=U!6-z757-r<0%_WiR*v@1AmDIT{O5wwE3R2Eum}{*Hj3+ItUVCj33` z-=VKwCh!^%5bxjD%ZLT?0!el>z#zGkPZ(gry#$zWnzcj5yhr~Qk^Su+GmKJK;{|dJ zAfY;i9Yr;5F@JGTK9NC=ap)QZ#5hglkYouR;(&mJAj&Yt!4@P4jk3%#o^!S75qa!!<)S^J%!nm;ItLJfMse+(?L1B zVcfIPx~nZmn+erMP5O$G{p=(k=B^K)B*)x!M!%_eNVQ@*F>I(xhj8YlfHM=cwgP5h zYL~H}4@NuDOdahE{?CMdAjUNsM7ek8<(QqY6NVJjUS@*6H~nLTGgNm1u%tZir5Kn1 zwy=uOVR#1F)bmcisYj@Ivrx~3yFK$NlfSjgnwpBxHrcq7_&9p*TtrHaOR!<2PDr#)aE)!5 zXY^q$>0_a_!~OgN)jDB^-&O!l$FFs-*~_ACe#@g-*DIk1>yuONVY&RqnfWLGnbfkr z94IwQ?CX~f z^Z^iMXDs>EIoFe{W~N62La&M~pt)fH&FF;nH1TWeX5;=JkXS3)q6=Z{4}{wF+ik*G zMR@X2>#b*MqjdqWt%bD%r3P?`y|l)OnRPE`d1OCCCB_4D)gs8kyi^)9)4eC11jMqp zn=3tjIR7j9+L#l?J$3Dv*|Yco^+w==+47HFBx_qqvF(AqDc}uW{%Y7`IRDJS{C^Pk z)^Sb#f8X~M5fhYdRGJYA3?wHaE#0jmH3USuHWUSE0jVk7F(xrOR7y&k2}pP6V6gb! z2jBDjUHAF8t~>sibK~IQ=61yA`F_P+Cp0hFu~v)w=LmjR%ob0jTNI=^j;>_1uhCUE z1>6r%?;@*Nsm-VezVm;KlHm|n;TNs8U$DF};E>E3!!`dy?7R~Cm)Cz4WBqr@Fi?8H z%qdXmeH$i4)OAyOxFbP=qP&u&JvJtT3=5~@J&zQ+R`tXq7?Q$_!>*LMQ}=nf+5`(J z6N;h!7ofewGt;qU?=hI}O~o$(-fD~T)+xOgqQhLmhqUvE1vLnTX4ACVchoc%LV-nl z%CSV&cP+kjD)So+uSig#KJK*VcOznVy(e(wM&OFas;m5*tloXdq5uy3d3JS_hspOk zIks@gkm!hAH@i|6oh0)hWaL4%MM1#PI43>Y&RraCZPy5`Y(;JLt z(#`fRhJe18*ZzQ0CECQhm4~W5D_nbd%sGQ&dKbh=zSnSANcoBz`ha{&UPIf)KHPq8 zq++(96hZ~MU~~0!#|0Tk^H&dkVmd{>VmZ~}d`?3cTG^c^sf+-=Hv1Soseq#=kE?vQnav$wx-Gi)YaP&kdw;Yhc8X&jtxm zibS47pouCET#7vy;bw;KZQGh(4yj0N3yypcC{i*9?CLIcFep(S*Q}M;zl!n z2BhFzFOR_g!2F@IT{YbRWR9C(r!%a{*91}0V~xFSgA2g;a~s38#tSr@Y@U0 zm*)qN7A$x-Pm+srB8ivC zvHyu9mGrW`WwXX~(NaS*nmCkU+>+C*Gk(_FHN%x4#by>Q>l@Q}+eX@wlL4FAc2@1V zbb7-_v!!$sZy^7w?P6)yYDhBAWm9l=)adb^Iu~DnnbT4;*fVNKC!%c;h{W!hCh|Z-cr$vBVaX3;c9{@H*_vd48RG5j0=Q`JE|`5hF+?^qqMZd6 zo)r$&mFqSgS1vDvn&)6hh2Cu4@pqvYm`Oh0;|@f1D;2 z$}X00W9eBdxnVgUUtiFtJ|gUn z(beFNdg(~M^am}$k~Rm7`A$lP!b`C`f6s(PwPdGMdWW362JrziiZ4a(5Jgqc|%A?E6US>I5N5h-^M-1{d3QYhCXz;S#yBddMm`9YeaBSl~03@rI7zbye z=0i3)0itA|YEv1P#VC!}{O?>mH$&QvP`#Ffz@=$-aZTt1WM}U1DK(TdUhTM)(dx6R z@Jb|rt0UC*UQ1yyDFj64$z_uidxo2mGJY3K>6P#^QItcOCg4}|AVcLKMXozwe?qr+zmTQC&wi#@O$d?H`w3*s+5h^nf$WH0khJv3~%g2*QnA*kBf9 zHYB>o<18{o%8s|D%#1ifDRZhE3G2T214RX4bz>c)mpM|_T$0UQS%O4zhYB;tZQCOq zMl->PV268~gR}&^$w07Z|Kjb7FcT<`# z(A1cG5FOWN;vE=nLvybZB6e-PA>(QCf(&#u4lv=M|3>lweLSl)hjG}=K*>_WGBlOvK)TF`PXdbyy-BCixjs>|%s5m~ zsOQayGA<5NR=Uub={_2@V1@07o8TJjTboS@_Wr~ zj0HNJA>&3^jgxo7w)TR~Vq*{8BbPPxf2`0p`4|MtXQpK8G`Qll|D9=aDCb@TM*mk7 zl(IQqs(3wHYde3LIC=oT%V46mh6tjo-L~vxTCR&5wv))0j)ZI5d-R^i{xovXX@ypy z10>cp9Rh0mG(YAT{924gjFKr2n#>k{lj-RiBF*+U3W%=CDx z?av4i?t;bUjhdQPm=~^ilZHOEm*#(GPJ<(b40TNkH%Ba$ezk|k);wB_&cwE z`I!2JLs5d>PX2}maq|@X!B6+*&uXCdR)6&KWD~L`^4O#iQ-0QLPUz%k5H{4&9OnVD z1$T7r{}1l|f4Id9+is-L=IL{5aHp4)h-(}%cq$K~i5kT}3fF6ft*85@3?6m@!?Kc= z0X!Gs;UB+?0^Zin+^yJ;e=o3TA?$IAxPvs{Ff(^>O&*uNLS{zIo{C8{UVmR4nUq`W z8G)xGh%IiNokY#AhKFjq_W^mJ*Un;@4Q6;^CCwI(5Z(l} zAgR59k9i}w82i3YQXH<^Ge!g1_LrO37Q41(_$rQLD1LfMnpowXz1tf;dw&E3UfDfx z;Ej0U&vSzQi#L4hU+*zd?KN{B@wK&gcPnT{PJAYv3b^{_#(}j+<%)EF+atIl%eGUP zuZuVN5yu-y{EKlR7|i8?j)o@_+sEyOr?lV$#zdzh2EtEGp>C(3Zi0&af`XWV)#L^v zmV2B9m_)>v_R6~sRoO;q&m+~Xyqx|5wdy$|E&TX44WU;=2t-aota_Q+`g{bS`K+;0%H;HYt^{p^Q^ zMF}gsgtjTP!!3*(n4`u&;z~R+UAL(qTpM)z4NdTglro{QNIv7Z&8qEX>XB z33T%{9kyriC7OI{yDA8i^MysVbKXm_NG(|w`AjU`+;L%T{ra#mdNobv*_#uXf~`5? zxHSz|$KI@u(QIW}2AcT*yh;3Y@;DOQ4;K%DjVLm#3ttx*uMj6M400l7+?A~B(nBjh_VxMZwAa$6^m}c#y>OVd?>FZ4Vxc8r-Dr1`Ro7B zP1Lz(v`64#`cv-)paftn_FrVQ*tr@2qm;ZNAkhs!;EEt!HiSd-rnKY+ z$PZ=_CpqVIQN>R8a!$XD(?v}`*hf}xkmgN!$Ya*80vGLJpCFG=KzI#ZDG*cxat3s{ z&n@x+5;}IT;=H3o2x9_()1r&Rn5Qwu40W6T4Mo{zigS&CZQn>04{an=6b}K_Bv6Qh zbjbsNN)}x_avw&i;xgI1O7&|sL4z?HeXi#F7>fviU`m&IG&`!|+yLMyfGk%X`$888 z@X!#+?0`l(ud-jr@+YGg@~<2Jv8Z|uYrL*^Ia=HF9_)8a$&$z;*4q%Ph*Cg~8xP2F z0cI*yhW~eSA1Q!}8pJdhrw(ZT%R>7NqsLMwLqt`_WR1=G&6FQ88jbcE503T(=uy6h z$iFhZM0;gNr~#SgM4>Zff|RFHd_lmWK8oF|vnusm3&4tFga)Z}Ri6Fu;DLI7JT4vF zFket1nuJIS6sU=7oS3l&|E~}8KOgGLm(Tz1zqft}Z5q>jECl?VW&sGtW05Ayg@ zEkZ6!4m)2hsA2_4Xy+t)gD#C+%?A)EuLv(6z;XNOKZEoEfj<3b!z8Wy6p3qs(ynI1 zZ+spbCP>BClq4&Lm?UL{^Zap+OKzRswKO@7w;SHknRm9nRx+0Etu0a5AUcyo_gKI0f3bX%+J*ptyjYL8pg4&knb~LiRk1e!1v0!Ce~z} zyH;GImHHX2zPLnwT(51o&}BTb4NrKA$SOzr2^R{VR7e=60G4>lvy89%=CM%CTg!2{ zF>-j8#pKkVpWI?72*f~%Y_U5rY65K_5qEABg#9VVsytfaN>1cUFd=BimVJp;!3;j&Oacj00#iCUFw-IZz`tSWkW zwWE@2{=FTp+%59-tEy*g`?^q!D9{^!;Wj;MLS{$b(GQ72P z^JuOc7_R&C!lgKgO1P^St-7ZeR*U?szfJ1n4kUB5(pik=>fWR>&^ZRM4C8v+M4Rs^ z$L#wfkNkBfa}UW}&%l6dTk_Ib+6yAuBDp=Ciq1S+rDRANyQ^dbyG#9_55^n=`GJn_ zgXFlvj*?s(AL61({`hxjsD-3Rr8+0upjy-aDJe)%crJhQsJF4vzcqQ4G{zs z_}VSna%hw`PW)+9dr8gGb=j7T5sQ;|nk*Z5?trgS4)=y`(%?;*%sG8blL4+!y#PrZ z6PbTe~YcJbn9`8**-LTsoX9`SLHpZpexCkcY~sC66cL&@-Y_&Nfq z7+!|b-0X7~)a{YQM*modvA8H@+yC}YjmvPgwK@#xB@H@gTRB$PYzz+qr`%i|hu$w` zZEC%!u`aqpY6vFLgf9-<5?V309o?g!hDbZt;A-vNNbsHf4S{J@mt(urV0cc)jaDh?%~X}ms5o$yVeF&(>rimT zOcR$Mo@*lh)mNhcTVj!8%j(pof^{(K6j>o{nXQLT?Lk7V!|MM5(dkl6T4f?#Sb|a% zjyW@j>j3)sR9RFx`}(@{(u z@9oxH4>%vx7iFdacaQ#GZ(6ReP7FRSvhW`jsIY0@%ehg-er=5h+55BMDK;fh_?&rioD*+ zHP$BHq{)9kbSH*JTNJ)=9Y-NF&)2Ds6>b_*t>v>bhmL7+8 zn^qzCv<0+WziR+)mQ=4r^9#EqQ7oI_`K2+~{8&Ho-Ew55VypWHao4_p$Or#`U{G?i z{cO;~v27)%ak(TQW5g9GBRpMH!4no-MN;}Rw}qgSLWrNu?mrOKB+OF$k78o9AL*E$ zeB&W;8cnyRv zY(_2xY3!|7LIPtXtM{p&ikx(fjF*Tf$p|V+#=Rkj zHFfu37=5g6{Ze(!q^bUM=`B@&9GQAG+XVAH+n3TKtqmyK7QdAD`1n&pug_KixJ zj(l)pxULoKBsypRo5s$zc?hM;paXH%LW++`!tG;zcv?f8b3f(eWiZvo$9FOtd1oK= zn@@b8*H^lGzL%MLksMAmK5IC8@(4p4I*awSf>}I1XYDdM1UQD1AN+k{B4Th`{OHhb zzI50NaeMvj=CLpOW&!{>O@eq)C&{koAA^E*ko&(~b~Q7OZvWx-gImtxe_^znSB z@spH=V5kv9n|8n~&b9AuoFn^vqRT)K|Gxg0m#lHSa_;22WXQUS=^*Tu@c2PlMaG89 zkJ86Aw5Esv#h$Qxv7$_&^{cEWp`z94!);%_xbI##6dN^_vzhasI{?S*>%JSe4{W5I z;x~QoBv*fczm@WC_ew^61P zsbil+ZC{?(Q}+^i5^voS3rd`9O?qhfv7$*ZeZJ~zEBo7@k!R=4UzAsrbNVm=6O^#`JMslL!o@-O-&Dj zrm?SXXh){wdBkCQTI*Zg#UB0?t7G37Y~g{qEM>eH_` zyE$i)a531eUHkcgaOtyPR84O;>JRU51#MYf&n-3GRGLk*RwlTlEm3wKFl#T)W5cI( z#=I3&XP+c?T6BCVPb#p|`LL+6NV;cGqHcVu)VZ>4(>(|Mu)Q}hPds}vb7w5but=LH zr50IJA(Pk3R@QAezxeFB-TH78lW- z{f`HfLe*#Pj+#r!3NGDlQ=c6SSi+{^>C|N168JvTd3yz6MMkOHfGEgTf+pVh6~c+b zhfzCO|MxQe*X1WM)o`xv@gSO%y( zYAvTS_i;I2p3~5|a7@d`C@<@4-d2q6Ex#z8y_zJ&+!AXwXU8kO8h5+q6tsi%_ZyGH zM&UeGS_SJdykQ}zx6BXyNmEmk_2?)l3j}aNS7~@{yB4S-JYIw^>u&^W`;!prduU37 zo>7m~qkPMpb*@8ru&l458e3`)W_@@VnhH>ivx)^udV`YWXCPsX@1U1Rkmi~4u@fmC zCl+~Vxk=`Zb(Q!D`w_1`C9+$2#!s*&1Yo@hV&qP7SlCDh9Ey1`=^>I4CD5kvSHA7r zkqzm**g4P-^<4dV%!^3KwT~f`da@vaiz(qva)o}TY8W7)^x>;lBA?XgZxtEqfmQ!U zMkfF)^Zot-b)hH0N_cS2X^OCzckyRZ+|!u71Fl`^6TN`UpY^Simd7Q-~8;_V~OD(UT{ z{pYyAs5PS2GEcd=D`k`G4Ld@~mEVd54b5D@Ob8!WxXqM|lq#Sy#+BYF59V*aY zIQ|_4EQq+6RmPfVXSWs7*Px&5xqdfOr~qL-Z-b;qr9^P$75P=(;+9wG;X<>+tujSf zG-Lft$0c|}v@0W7a%A3TEhR7uipMj|I>ROR$aN)N+nzctH%GQk)K7^qaB-~K92ey# z=fnL=tUeL+nND`eNO2=oXp{Q7**Hpy{48r*J z?9JzO@DI7W#wi_QLq2L9b`KIew5m;h0qlanJ@B8Y_4z%kN$SvO^@|We4QkI0BP3R# z)I2%IX^kSYu3`W-@I|-0c)P|$T0oBw#+aX3W0sTHQ3lrvtC>Kd01(wlUegw59~exAKENU15*mEhc>f0T8_sW_+= z=AQECMo#AP@GD8sq@WK{3fSS!?*=a#yw$2nuO7U3t>Q`nj{{2i>OzQ!WvGQ7%B1E! zko155X!jAF@+3yY^kGTz@u~vYWPJ9L$0Jq~|L-WX0An_@3X9vZ0vB~Pf&Y;US^&ln z5#gl=ZCGepfGh+Boi6t@(+0`22GlZe2t3TXs#JKn=*Pm> zn;>;&!|_}bpnNmb@W)Y6@_A@9*eG%g1i6O5PAU$#;A__J$GI=u5uMhf*oV(r*}$Q#+tXEW=xz zZPG$H_oItbVhd}ZrqQU0D&S)i9Qm;l65^ES;ew$v#8YA9YZ^sivejeqwma(6`?uQ z`VVQ~n5SOFjDQEfUPEqM5eKmsd74n|_hWH5L~KY;?G4-R4WphPVM_fVk^h&q$Cc4Z zlf0~pp~I1?S(hPq^A(&?k8Z$RSS{@IDA@9!bmrOVRb*ZHJ9>dxflcAX{nIt)YMdnJT|2MY7 zB9VZiuu|{Rn{K20PlrG?tU2`J?rSpxnTq<9H?r&=fn zyl$X(Hrt_4&gjM{D0+-euMZ|A33^b}o$pW}p?8t7AW=!OQxXU@&OvH}SPE7m71ls` zIf;@WR#)I8uI_YRT!9kcuBxABX`SI0JH~RjgKbbSI>8g?ERklgKP#-r;nsgM(ZsB42KcG88cNgh*U(KG3 z!J$Y;mRM)Msf5e}G`4kl31Relm(o5+G0CVo-+eVva52Btcp@v&|>+;>8wot(-G9-@X)Dv2nlsTW=PNO;b^46>t zNm^b}O6&#lGdp~guNqjc>59t|PzK|@q*pyOCu)2Z6l)5eapyCHii8H?CQ%g0VEZNJ?Ggg`B_ ziX|dT?tiWJGk!E8!WV6=!+tE>4S$m)l~n`1ys+hFamecZI%#2}nJ2MjN)9Dj6EN%6 zX@YX{`qG`9_U^sB1p7rf)}BQ3s_41?M$!-Dnj*x{80X3W(R$q(D9WQm)X%`p{m*vutHl4!!}l)-&_15D9qFt{MszSnJg=FDXf-@>zRDckF!O!@X_ z8?tvMX}KTX{btHq#3#@+Y+No1f#DYdEOMwo{*a^HN@qSF=7jkwAd`vx+MxoQ_H8v6 z`&;BKyG@%}JICcN$}(`m#m*9_5E;I}I%=$8*k&8wJxMqy%qI>^-XHUTtUoT7ni)y* zv~-!WbkG02J0BNLp71;S+?|>wXE)%BBZ3VVpiwu=9JQ*0o-UsJF5E$%zzZ;LVt4nX z-!CeK3Kfjn?y3ipy_ck!XsxX@B+G2fnX4Y`0GE36&zilWa$0fhlh+ zFy&o&7N6B^XMjy1YVXVSzxJxTYPPsyNLpOCb^a+2v5l;<@DJwTZkj#la3ckXNqIS* z_6x^R2pekyfiknYhj2BCh1S~|3nKa}JReP$V-zS~0HHj&r*I0Iq zYK@n#h)`;|y1DUQll6tL7CT&{;;Y%({!sl0aeKq%P)By5Xm5ogA&NxOzSroR(p#8z zmKpx{uBbqt(I)yhz{E3{pb~)FYI#zT74!IQh~TJ!L>bIHRVX&^>jm2my00Y~zumTX z5Pm;z7cyJ{^X6E8sy5|c;QDxG^5J?dvNCC-qXtN&B{M8$2;;X!_We-Tby`9nbdmX* zo2a#-yP$6vttaMInv{}Xep~4>(GRY59}+=O{KdGlIG@=p(Hy6R@2UJEYWrg&S|rq5 z>RAuuY|rf754%r~N#I{1%lnS8c@HeqB;z?tFK$H#>*A4r!sp>B*#ar;lceVCT^CqT zw{9)RO?XnuYXg%cR|Fb*;J9QS7hzm#!=l5byOIH1b6&6@L+{k@0~ zUHcFh$dLGpezl$MH8bGeJiB2AFf-AQVW@jim(tHf;mkCgjJ=2G9WTCf9oGfu6YAm^ z;G>4y_dAL|+Ob~`7P^y#_ztLZ&KQ~Q{+!<~XvKOSzVdPY;!t~bETj#s;_`vMnO*U& z0Vc5CW{c+DuFASYx$>FSPp{JeDm}EteKWjg+i}4teglV<5iFc41`%irPqF>7*v?+U zsrh{E-!8Jn^skq&m2x<@-@Ew;g2#J=505d$5&HSu>tU0xbU5sxJdp>UZ8$k^`M##X zRZan?*gCQ$n)j`xZqGK#o8yhWH5N%-LyzjSYjUk-cs_c&(+>jcJXTQs&6eu9+|wBH z{GEal$47ZM!y)zupuBr8``5w0*VgiWvf#tZPslvL2zEH2UFx`D;ET&!`;sSOa}-$s zTv`pqBS|i8e}jcvndF;QR3Y9bBePmK%~_tf$VDrKS8X)xua=gD0$@9*mWNxoQ(*O$ z)0#cd{`1`I_y2eU(hZ3qFM~kpm6q4|`F$1Q^HM1wOMz7( zH~t`l&toj^+qO;d{%mLFUN~M+L3CI<1-sZwsS9Q%bnUO>vAqoVE>6ecP;yUOqj%;y z*BG&BVB(<*I7ZgxHl${z*>)}V9kz=#;|t(ib2QUB7PxX3Db_Nvd1$KGXCA?m;LkIp z0_O|f`|lC)g>gLpf(dG_u?~54M#~$z(fg)#Cu6p!6YADVR?aK3vK4y(tnr1(Xrk3b9_j$}Nu$SkmU#@WI+jAdnQ+-nIi?VB# zUvH`1Yu24d$DxA!v)VlA-xgj!M5CJ>0Q-HNp10-8F6S|XY8EwEV~lrrC)r5GCbl`% zG<(uo&EGBYi7)q!$ir)E^8BU2$(vi1T+^CxTL%CNV%PsNwbOoo!ANmiY+8GrGyxsL z9b)SbPRDIZNBkmPW@5=MFNvFoBH*qs!x_jmJ|8l_cnQz|PP-ntpYG@SE<&0wk zt`^&79cV`Evk=J1+xwrNAmt6Cchon%W|;T$$HQOesXyAy2;Tsw0zGkB$(n0x*&mC; zQxv4_*14$h2~+J-*$dAq-yU{lWGqf%Hdkh8@Ufe1C-DOmUj+%R!_Av*aK5U2(To(v zgPZu%MgAnn0ltsxThJaJ!F|NuDjp^-j|N0U`>Wx@5c1GlpQQz3t}_PU9MU2^I#)B4 zAM#DS|DfdL44bMUq$=J=ABe3=>G90n^%CzC=*%D70E=$ggt3482jn+14HjCp0P;U? zE~9g>1%62ns*BeHTe-6uM(-IhE@)+E%`Kyjtjqa1Y;#Rv~sMumd z^|cR<&dgP`U8C3%_-`n!B>;jUc}aVt0Ni0(tve%3*cWs6?xyvB!(8q#Cjf9L;l z+6lYLJKVI4pH16dY1*lF<}x8Z!Z+vOX-F(lFpEZ->Gk76v5cv>y*TV-oruJDP6a$E zn0<1jCNbOXZ}R;mQ3c)N6KH-Q|IdL5U#-2C-fd&}SWuUzWK46!2|voqwpzOL3e*7+ zcH9Eiro_1lap;T>ljUAK`DEEcu&@Vlboia>NMvA$rfu?6NqdvV2FHN^Iz!8S50#5= zl{n*ONHy+ot`0<`i2*fcoHy|Yin882>3DeVy94Rml*BZuwUV=&xtLr!4kIGk+&nO>Ja#+^xShwP6qi zF5P{zy)%yFfc))7HWUAkEZ!f5MV42coiE6Az!Ut#i{KNJ+P||2a`-QLBUxH8mTf=` z45MZne_vHP|Mw%|qTcw4n1JNaa!Y(wo2(lew#i$NZ_n^oxKPMIy{(vPO}}t0s0Dz;9smMQ?rG19YDwHLS;o4;I<=D3QPt6*#Q^Z@0pGlF|Aybge;JF(2%X4%oM zMoJ-|ElRjZN02AGv=kLMX|*a-Wtnq#Ap7VcJEmt0EFwpLq;R>dEx-zpK>k$hagf~RID8xM%B zbjTOnVZarq?%rW=d=fxHm}DBcbMTn`L^Zr=UUiD7sJ9F~DWjXFuWR(|8c@y9dJ7Ww zv0Rz4FpU?SK*0A>sT{2)JO1{q_wY*Oa1O zLEvK2hY!Dt11Zzfn^H_Y>tY3-8~ol108ts*!pQ)fspzPE`vDy(?{djEu_DV`$B{Q=~E)^ss5KLhWo@5)?G0`B$DL?CrPf34E&a2?S86?gp0 znRE9ioT72P0o?DvJyM~rdk9>-w1_x}cBCdd$O!9bC{|xkAd!Igps>7jU~R3lqT!Gf zC0DVbp`Z;^MF01qsgWiOal_j^V)Dp`)l22M!HpAPfB=tXTCB9c5PUAE+3YXSDO=O~ zp4UJV=v_naoy@PG_PK4Mw1?+K64M;Gmm&faTz18P!PRxI%nxU@=4Ps#%VCZU&kuji z&TpH**@@D_aMra4>yt0JeIy`lG#Ms48s+7!DfrST*lH5THKrKK%1trpGw!W#51Hpv zBrz#Vz*q$C6YvA5(X_3m+P+N{`s~Z&L0)rQ3Y&eJzoiEd7iEe{TK4-oOUEwCD4j@1 z*da!PO+H+a>0h(PpAwWNiBL?6`p}YAdVtCgp*J;iCyL~;eVhE^X&0su8=K!JOcD$RgJ;B=Y(dQHmNNO|1InwOyFx_b*$O3iL27qe0+efW^p~AC6^I$3m z*ach4=Ks$f5!f*w05ZSn>hajToDgs|_i(O@hv@@#qX50jffj@pIWD%Z#xs5#9-Nr5<-7#*}+zlhFw~w-@-)KvdkSM;iZEG#dQEeC--iab1QS0~|q!BQGAgRzc zJKy%(U$p^ z48hm?inP8bDtMQkLN^_vDI=i{K0iaZzhcYDzY&!?sQuM;bJsK9FcJ3PMgyQ+@>A}B zDfb?SHayo4aINvTA#O~padLi((-{#lg{d$v$NAV1p9Ut{LQ_|UezZDj+aTWIWCe#k z$F|^){T7d*_^Q1VjTECX;@vl1c-3_`;c3xJc4O~oADwjgZCW5nggfG&RF#zi6@O50@ka3(J14XBay8 zfjKT9rI3*8I%(TaWgRiWf_s=yTvhVF9+iGuPu+gRVsh*l3x0fE zV%_5PI(aOBjRU}4F{q5c9u_{wbzKbdCL0)gLyn>g6jvlVOiBM*67aLA;XI3&0HdhM5Kh3+r1|2w@Jx?lJcAjn9Qk6TH7tZr zBW~Z*p!D*(v1z_MaQ+h#yI(FhGS;R?QS`qKUjKCvb1^W$@Pg>a3yoYKU43e&TQral zlH7kPxdLJH%DVhuQ?I_5H9G(lscgIiOPVbG<#bVy4F!0Loo|`|+>jPxlvLu+THFIL zL6p%7EW@P469Q5K8?zwGo{p(HW?dUmaD0k``Ien#gn)H<9s6(&4x8qO%^=gdM3m!i zGVX=%ruj(sBZd{=VL!h`2Jr9@0#g20xhLeGiPA%Ag5Eg-L6e5s{1*9u^iRCjq8Myc z3BbsHpbG7zq!Oa2$`5GuVn9;oooI@xMZmW!cFcM*llvSFj@u1D=pZu4Y=^81siRLP z@?mzYAXUCpzkJC~yGH;g6=VfOdObJkK?Vj6=YUXC0tk20&i}8A1;(b64hz(F4NCGV zSdHtF>xR+^TB-c{f=a1nwQ0|n6t~WXT>N7(U!UcI1AFK@#6y%kQ>a*pDy%n3L zL!_xRC>^q%CQ2-)b0Hz_IJu&zEMN6&ZKT}YXrL4W25s8hBEIJ44tnzh(adJ5R_J%) zbJ3<0Q6+u8N~(!mC{7tF9>f)`)|DVQ@=5-j+s=!Z>^T8Xl)!Hl7t76LQ+eSHz<7qv z6!8X^O7%&|5`fN1R4$Ve9q3|J%w*#1i(k!ko}=lF`2iU!wY+Rs(hV84^i!5E)5sLgxUZ8KDqK zpK_Aw(5}rm6NO3Ra@&ae2yuY!{_p!NRx}z~=rk6vxno|^Z1@aK& z#f+}_`MN_R@K5nnxBJQVX=a=QSx~Pqz~7qFmpD8Wl)Sq#WFSX3_J#9jnc6kALBlol zx1YDOu5a(>>+Fx>~{HRaaL^e@MX zBpWx;jWnNIXFe?+l?VAar_9d_ybuxzaO!4L-ZLKVh4@H4MKkfNuOi_gP%I4eL1koA`dONN)Z*K;Y)wkN0h(?d zXm)pbD!-xlaPVq?WMuNS(% z(k!7h&Zb$@WR`L=QvMyth~e1Wmmd!L6V}L$JNx!^P4oWr`bi4Wb%CNB)>kx96Dkl2 zC?7mW^=&koS@pBE4a0tc`xU`Xfi@hPkogvk2WPBD4cX<+5oON4jOF4SItp=iwyrSCP>4mFIxrADr+J|--E6?bfa>f}PnrmOAwRa_mq@wE$JN6a-ac6SB!a#@v zLryd-X8mRu+7M8s08 z-p~&gd2kN|!8x;F;xlP0^yZ%cYHS2Z{{W* zu+a`I`sAY}I_y((w)&t6fU`L$R+I(JY_}ZO4)zT0_R=~#RBT8F-`yjKgi%bwFqPwP z+)K4ueeDO2cNu~VhlAwk;AhhCzOL(d>cTzrt$p9lZ8Zy@*uig4_YQ8*{6KWp%OPlN zV43S@n7PVYw;)0R?<{EyDD%|ySm>wtA+=&D!0ntue!-f26)<@E?k|_tM8cbiJ3?$+$DJYn<8h%Kw{P)(a5nk-Ujx4EZ)b z^ZQ+gQ7?d^d!%C63|FRp$=zBkT#Q_FqEK#Yh;o))P8zP66*ZnFuRr8I=nu{;1Z;+! z7lw8!S+)62wzj6*#i^mxnMpxPwpKwLO|s*mp3ijVgA168bXwCAU#POCS~lUF8XeEpTb7V+asWW#^#-kg1z zUpiS^CaSh>TlJi%(_66pG52ABh3%3bK9lm$?}yRP7tW))&5LIce5Rbf%~0ST^;o5= zw@j|W`;Tm=rVmPj=&-LU$NO&{#QvJHJb>W*bRfSxTvZ=_U?MFo;xX>+_*cGRK(Ixj z;5>T*Sv4QekNAGL0ai2E+bPbiU`l3U#P9s_I34#6P8S+2?aKK4ImK(ImEy1gAMnS# z!Fz6=cc>uqFTiC{v9ELfhl&Ixa+yX7|A76@z@j;(w4hJ;sF9EeRCFvl5I-YDbG`&q z|7Dli?BKc|^lD$iFJ*y}KsD{|1nBka^c8P zBg%MLOWndZRst-9o0R<|H%O(mw>h7Yzc0Q)o_d-wBZ#_7n^gBgdT9;-`U5T&A}8VA zGDjrUiEa10u4wkq_#Fkc=D^JN+R1Ux=LgvR;D0Teo1l*4!q53n;zKb@6r-;@8)+gl zu2D!JydhPkXoY5h zb~fE71`JY)-CC!~-WZvzoi_aJZma;7F)O`DePxODC^M2(J-O#Pj!Ry9xs^~@xJlgX zFWxSp7?yOIFIpec&iumcUQ}xMgfAjKOo_Q%_lNWs2joQD4QceKcX>-|*+Wlp{{nNZ z+x)v0!#E3QDguNkO96B{{`x6fui>o$~Eqjmm3x2gl>2)tpN+S-XL87CY^=uRpOrG!bb*K%}=sML-aUbOGtTMtTR4CenK^p?4B$D2aDC=RLpotoz=z?ppW$ z0W%r0U^2`k^XzBu&(_ZAfCez=1Np^sraaF`tYu}@JE`xkr>6!<;oWa*9Jq|ZV&Icg zfgDBpE1x@bj|@E@!!}*6(E%~wtZzr)X#x}WLCK<2^&piUrO*aL3ea-qef+cUW98QdqoRy+1Ve5}*>>p|0e#3Qqh5 zEl>o_-JP`^lQp7>hy*_$eTr1tgWId~{)8T$nMqVg- z$Dqj*$f2S-!XBE?5;Bkic645ufqM(1*ed3us|$0oi3t$Lml@3@X}$V+u2xJagg53!l`*8`kY+kn9j+a z@_pHHqcw}LkXa~`?ETRs0YUy((L{d@y~|2=b`ZbRujU0+Tot~WXWFEZ1azyZ&K6@` z>d>n<6YDitpKIBNmgDY3`%i?$Gj;nWda*nSQ)0dzhhj;}fse(SKOu2?EXuCdrAtIp zO0?|p^v)_r0;nc?vQre}@^+hVkF|SyIAN09woUj}D*}}B->T+|e=D3|4AzNq11UUu zcSscA-quFXU%A75$n~ReLpR`-WDIM1g~L{0R8%Q9@UQJH@}bH4PV3?#;-I|9%xAv^ z`v5Cbulh7f=>dpRKRD#vRWU0W_MCP zuY0W!;dkp2^fZV4_uKgEka6tD5{X9!5ZwfR6TWNkdgi%kI(95Lzs$KjKTz#GwzWLx zf50k#fAiUpqsv%td05l8Vh>#cGj1OqS~U03m4|FYzg-lT@ZNs?y8Iqv2vGtL*@EG6 z%)WJ9k8sPV+0L1%#Sr%8tuV@kqSZ94Q~#P1?~qSPyp>T6LxjflF(1l zWqw_jWpfVft9~^IdnR66^VOdt2!L1a?aaI<`WUREe?lf!pAc@RZdE+-DK_Cgv(CAH zz6SyP885t%ZhI2H<|a4g2|QV{U$7WZhgjUV=Lw&V+XRa7KfPe?a*s%N=3OzCz(8w0 zU6!Uc3{_q)RcN<|Vv4qmSL$Da48E7eq}S6b602qDH(IZ``Sd*e3mRIEevd@3)cG+T zg%E5OE?tQWD}UFK-t+dJQzu@I?TdoVdgHypim%sG@+RiUhqlJ9aqWqv0i$uCPO@Gp zo1m#wJ0fOZT?ja5JNfp-M_zDW8coYJw$pbpo#|n1DCad(dHpg!|Edbd0r=$PObaY|sV#!HCdEVc)=4+Re$aEiu4gA? z9+)efZ?69NFBeh+)BImhbCJ$M_K!T4ipm&za%cCJ_c9cD#nRToftNm&+=_qqOR7xO zby;8ahQXUWTn<*C2(M_!|8^1d7slt3+M9RmtuK<+)2wYy#O zpwLsQxz_xH>m$(y-kFzGp)bG6+Q@Xu^f(&q^)Wc>`I0bYL3N5!N==FT=jih0`HXi8pGr&o&^lww$ zZp5UUPV|}8Kg6vj3LyJa%3mW{!cnxIj&5Zse-21ik$m;3G`jj?-A|OTb+E_0N~m11$SI;rB+{!GyGK}R#{%DK$ZGtF{@ z{wB&zIQ(_wlZdFThcF-;@!Ybxe=pbWj zap)kGT5zj*U4zs^PEc?-p;}kH%N9)*Qj0j%Ey&5qviFi5Zd5)>r5-7xIu{e3M61@` z(B4j^+`OV%GF)fpEJvf)CK&<;@mz@6>FCja>#hHKlm!UetZM2EKv*4c%7S_%6V>Es z)4yu>UkZ75LG?T+PzDUNn}<0%OtVRHv^tu(qsiQt6nY-3E0&WE$hh+u)4}&&T+T;4 z6QfK<=%rqZ9{%H*%a|4Zo{wi;=U)DAgd3pxMi*Su)2Yy81sR8~g002#okw!lE)Cmc z!9zzLZ45ieF|i|R=<48LpAQO3Skk~I!9ZsH0p{sQ3XN${#f5Oarf&1gtDrvt z)O4+2fTb@GBR~0G@Ts@nc$ijDg=yfw*YiWg-m!q{SdG!ABaiZ@UC9u#bMPuw-S8r% z|0Qm347-w9A#6`|c}BAVC#;n2`U@^Z689y&bshev4ZK!>6ShLRg5@ZW39!Oe+#j~r z7DRx&k8+L}+WsYNf0txITnO7>yM=G%ry%F;r~N)J%0ct3IwNITL$U8U(&GUPD&zmU z6~9`+`DnQEhZ(7o&^#oa%V?}x4- zRUQ#JfQSIVMb$2n=GrgF^mYp^hKpWTB}ud|Ue-O(wo@^RyY}aM^!(NUw(%j(uOrZj z3S?FGm9+Ch(gz}M_;qet{+IIjf%Mn_ll$8_<9a4KzLJN{`pn>8_K<7*j?9@uJ1i4u zSrh+vBtQG+R;!)koct}nBlA|R((rqGU9}U$j^qx^^CmwqFjrA?y@s5K`;CmxLClhm zy84#KX4?jxmj|tY`$}V8{d4z}1&^@MHO;yWaR}<+)N;{Dh&<~}mm23hE6qDcyp(r+ zT>LaSN(D0GZk|?b6KKl3-XVfQa2YGOXl+yp0fb2Pxn1g!Z-?s!yNX2z3#Fc3Md8&e zqE-z9H3oc#_H{R<^S;sUBrCY!HwPr?coSLUc5 z(dS?ki=#Bh_?_^}T|oP{#MMS0x|qF9dvAzoK+i)$5j#}2Ptkh>+%iu1xYI|DN=TVO zqTn+Xc)iSmvzh*?q5JjlZ}6`ZCWpfjRSGUuNP)0-{0jo8`g6+P)p+p13Gp~q=Eke< z4`VnRKXivrs$>MX{HqP9u%L;-XlhCE`8KIfv$y)>L8NtecrR)a(9B;0nmK)qbbHTO zh~w&S^cyNt--FWZ>PT#r^42ObBf+iV`yHbr(c8#5XfqdiM@B&S)4N6zZE?4 zE!u6p$DOeeToH6tdkBKOA_5<}UljlZ`4!A=+ZNY1>N;0fTVx5CIS3Lx#&IrNes3}a z3c@o08ZUJ6XsBRfyQV9v5IsdcTgVxSnU%_KV^=O1d5;;vov@Kp)@0YDc%foD_Kqw% z;z*Q{ESbuyQ9*ITNX zVYq8}Q*00$#YaNW6`#Mq;{7ycLtT3aO-2){sF(8ZQ}2hm;Jkrk6!{a z6-r!tMYp6yF3orEK0e^ORLPAAXb5!M;655D%GPWuy66&rsnmeV~^t- z%{DZp3*0djKk{mN*wr08mmmSgkQ_v8midk{r%lBFB}@^^mN>4<4qGGS4y$w&uO zrt$%u(D0n!%SYnLwoeN4_vM4e3hHJ%=%Xgtf}OEl8FK9O6W936ojt&(4$Uw2_^DRa zvf=mI(iH6LE;L66(+QUX=#$XUR6y7w|0Bz_hO!)vJQZuz!Hts+oxuleSy@wvBa*`O zQ^Wo5EX|47#$Z8Z7TB@L*r7RvXT|$JdkK$`4%cdij&;+cG@#g-9M|#_NRTrH*+R+q z#2LA7fdfTUdrf($P3bnyMj@fCfubZD}--jD>?v7RB*noXe6*~0CM z8Hm1TRm5s zndtEt&0Vhhcad5~0qm7k2@5uc^8p^6d_k1{(_`C@1u32;<-hV@O~#80I9 zu_yqz)HX9DEeZFFWJ`8&xp&MO@HS3D$L#rFAG8PR=J84exQqyJL)U1!lWy+Z&XL4- ziL;veeJXf~_AfdVOh$1j{`_)ZM9J?vc6jBcs)MHNW=|5(DZUYG#tzgGNexcB#rKX;iFU-ja zi56a>U7`ONl|)sjfY7e6056IbRCqEE!TJ{!w8SqnnPW&0=B*?ZtueYy+Pqm!v|pJ#hP*$%?eGSG2N>k?5Ow=S{fg#OzPQUW4O#$| zHL+2e9#wxqCg2};7X7zFcHba*ZL314M86UZ*!RJ>)z-zoASQBCcJx6M`nNuRa#gNf zH_POaC+(T=9fO|>Jd0^?$C%e6v*EISBk{!B(W{2$x%~m&*EfU=LhEBIZHY|fcz3kl z2k<$^sfYut2+?u>cUpu$CjWcL`S~D8z<$z8OFCjsQR;cMQ@24H!TiWSd}dgMv-cbE zw*&q!DCJi*sR7;6G}o_f3XHCl@(vm7mpzMk4Bp1s6(FJVnkX;*j^1 zDK{S^@JlH742Jb^me55Ip*_A5_!3OI0l!mj8~6K5RioB<>N;p>s&#i79;Iu&zi-)ItPv9sf`KQSbIxVTIOZM~&Wj|v>u*22)_kkrn}w(Nd5URHVQJ6Z8i0C@8pyp=j$iXTquVt*Ohc5~ z)@Cv(D^t!rIy76Tg-z1`dQ0fQhAns7vTZcWPC3rIyqC2g6r*@Sc;!QRY|oWLqOcJ0 z`+i$4f1|8vskPK+<%7P1VoWR0pmQ?~cQw^@ zj?r$0@!hD*E3$QIm9^5*^h&3fhw`YH*C&fu>5CpNf8 z7(Tp0ZVCR%xtztbOmy1nY5!#wvAzj0H7`jT0!+TmTfs};ecvp_hAYXA>MzKPj0ioZ zz3!|&)M{bYnJ1Wx-cxG9vqDvq%#O{+W<|7v`buJ)dxc??OVBEd8fBTy&>Hlg>IhhE ztHD;`IpF**iDzZd()RrDAD^VT4yh&KTx*7qqTr#Ipck?u#uZBy^TtmYx*RftgM}Un z29dZ*$6WKI>+1A-N6$)mun`TPF}=ReuwM8$szqVAI&aMV@3*Itg|)-Z6ZM_aJ!FIK zcE@VPYqhJG33;E2*_@>0j4Yd%A2k52;O6Ex#W@;u%Yyxk#!+(iR4sFW!u_E_{T^47 zeUJFL;4UAjcQ9!-q^lWXV(|I=B|hadQr2F7V0?XyQ5I6hF(rTZBnf?0Nk$|b)OV?= z*YPrLOtKlT!BTa@VmUA^@Vm`pb>qZ{eeRZ%lLS?Kt?JI1`6)!A7e}bC%oLvRF&ft3 zQOX*@2rifII=D*TEHB5<&Ti84x#Of_*8?6j__v_QUsX*AWIg1{3zyYgHA~7|V`SmG zFD3Q*lgHh6$n2&D7tI@@u6vWHqk|>|63Y2R!@RjplNEO6hQypV?sxgJ;*^z27xkrl zPULqXdD~_sIqR{trnSv>m!7ZyM9q-AB0`2b?)>$vNq*y_V5AN3ah3DAk=uO3XQ2f0 zvU1Jv&hM7ZDIDfE-g8<}vY-fv@28+PphEg zy4Jk&0%t$*s=D9!D4g)Kkvq1X|Awc|Gvn;xOx+I_!sd?C-E!nIMEeEcQjrxd30gP` z;FBns?s4*A>D8)o*cbNa!oyA5fG@W5D#aQTOLhSkH` z%9(0QDK>}H!@H*jbi)S3{CacjZg5Je!z%jxUTz!4?)1tb=CkP8lQUn?ouOdZXE=QLW?H3^!`pg?}&rkJJiAsj|>FF}ENXxD)YmutJcI zfYvOzO%WTr_Z)woiu&hk=TLPau;)lJ!ZL?oP|wdDbaSHIoXn2PL~t4=>Z{CbFU>Dy zvvQhut*P>@U)8t+onb5&l+RFHD|AOr1;Zb@xPMIsSn$g zgJ>Z8A(hLGDR$15*e?N<{?QH!?MB3OvqHZ|z9*hViJxzF zXKt`GAZeun$dO)4Ua_3175u>(;5e~vM;RId>K;7MqD04m8>laFl7sK(YP|=fqW_+E z{`dNU`6t+wLsUpY`e(f&*KbqD$DxnN2mI8X7loo9GH`xw?NOwg`5(2kjo^WsG9ttj zb>ytSxLI@6J`lp8wxRAff-A!cpm9}7#`d>btBNU7JQr7iW~V3Ha1sUXK?Lqh{>$@0 z{@7d5zI&Fd5l!_SHN_!K-#jzE6s$(Ma?dg_X_W5Aoj|Poe|AvUWEFk{i0FN^x;z8V z_J5bOXU&9P3h^r{tST#fnC5jm6}*K0dVKC@{l#gwDS>kF0q#t8#g0%4#S2z=c0$b1vq=S?T+NvBY(06*K zW}8Cp8s(S`P#u`AC7KEu@7QEUMgZvlyzNc%L^fGM0KneGQ=iU#u3#3UI?=omev`BB zpDzPI#mAq~imu%oh&Xt1o`)DI&2>eknCn&VmQR$?Qq<^s>VfK0AohNJ*3RQJ#EO9o zG4!H(Xlc&gSqw;jdNXmO9@>}mBOiI5wHT7R@!=(JG6=GxTTRDZH=&=3P*enSJ$zu5 zL*`l~JpvxnL{dvXd`ZNWbZrc+lVTIpcKPuk=L6wdiiRgo-fR9tH zY!B!VB)*@XL%UC2`O%;C!s@-<4>6f*>k z|DdZ2>QheI!b8!+24D;lxFNbO{k;1$$Y0be)3KEQM_7|sb1LocKhT2?6Jh{~VUrq8 zBYvi0`4=Q>fI)X28^jW#j;`a9gK}Fqt3t$hUd>V&soxZWuGd>aV!R0FNC9u%CL{5%6XHXRITSlq3iK7p@l;as2P#Tp zCr80Q_3os&Y#>Z2o|NEvQYp!-Gp-f4oq6MBYH%tQ+|j$T|oj2h7WDqK?qigjb8l-?K)xY;y8> zNEJIvC$dnfHa>A?@5W#c)M$=4I~}$3;}w;&XUKu{9!F_0?3d8qcX0*-DRmq9etw(F z%p7*CN#kWDov+@hq{U~x>Q)na%yB3>N&3y+O6?*Iq3%Y;{AzZd=cO(s_}|UaY=Ce4H-iBi z^qMBK=ER7A@LLb1wN*6CemAI*9x%(Ok3_Y?BjlHiCa&H~yyN)lVa8Zfh41c}ug{1D9VmXM3HH)!USN$;L_) z0R^1}&fZP(=C-SxE(gEr&yGHpkOm2yi^@VNgjm(ZjSPpsnbgW@k9^D6^Bc{efP zgbzNte{3)PO85~2mrSAo0b2dHGd<-qJwUqewk}ed%vaL41W*%fF^()bVB^pISH|;~ zP=k322KTn*m|hk1kNlIrB?E}~dfot`LWcK1lnlvIN23Mk_Hs;V1z$&QA%IQZ|Fh}d zy8dGR*MkD*{wui~!*2SL6#%gUknQyVOM3s6n9U0hI^y-V9DNQV2?5^J;RHQz;ML2G z%{Bw7F3d)Fk8)$P%!bMCALKD+n8n=hCm&5&e-4ite1E5W7n@xqMX)6^$dXOeOa%=V zvAY4U77k2sbjeYv^6)5mgH(a>2?RKvS3nKdWY@F1T?Bf#h(B6{)vLR08l=j(_W#pj1^ zkG|)9KJwJPK&Qc`cgFTo=C;w0m~l0tH>tM&iqTw=jm8XOdfRA>7IC#dL9VCCjUapEsr%wdYD#@IwJo;j*u8VL`ROsQmf>`Q4c{}P;m8~RIP2vcv$?O zivnlVkUEGVOaZXqNB`RjO;N;o!I=V3Dq6s4ck!iforO&jG@#hl*HWIFC8s$F8A{LA z($h~YT=6g4d&Dn~W&Jc^FO}zjJ~m$g_n4paj`F{I`EUkv#$QfSYzPTiOr{Jy zH9WFiHJp@u>>>!;SnczeWgR}4CZ@OB{v`2#0xB0gG-$6j#@v;-{Mu*K;W+T1K^anR z*m93_^pkegM5hZCsZ^m9%s7%q>^nfM_?{?uuVmp;)T_JTYMf;#52@IiFnO$Fj(rpr z|1Y3*X0-nF8+`Z}J(G7}=sQFaOh9m)$p9ff`jB2p-GSLY+L@T3MFYokDU@}q8aWSJ zz1}tcpO;W_OAts z*UOIdDGd7RIXf1_ojqp@^*X0i z@ZodwP;>%Z0_KYMi$>X)y1wvigSVb^$G{1>z< zB=+;i%}w?-&Q^x)ogtLh+7~}3j$hz-7PC6trQyS01RH3$HZfQhe|$wyfNX_JsRU1=Cq(X)93JpUr7|| zOx3=~+j2ECy)^VY+}`=$<+I;w3Hr;~FOSJy^-<*AFE8?yuyOkM$J)sNHdv8cyfMC| z!A^*BT5-nW9+_~RHE_2KaGubFivjIO0c`JIB`JV^dR+ORcQyUwFW5Sw_lwFOk?||~ zSfxeyP?qH2i|pb#%g4h3k80E>m}6ojPS-_<8^^S?=Mq1L#JfC5@oyiW1pSu%SfA7J zf(pfi_{@YjnE?5`w_nSO9{V|@P+zub`bMwEH*SDq2kVc97{{d zCzzo}HUUCzC9e2K8ycb+#kJz2lTM8}%ja5chTJdnEgrftY^c9m&sW(kp0ahl!C!u3 z#?@RSxh89bI8`_e5rhfK?LmE}TO89n4(%YK5 z!LNEwHMW!f7i8!LHOyisdF{!`P8F>DA$?F$FoN{OYUvvT$L0C;reCn@R`@pmBoTc; zF{+69Y|6W!$!kRM>eG3lX12Y73c(|Laz;F2k?PA|5XDCKlDwOTQ|(Ac8hZo@$6=5R zWqA2V^~dAOZs2t`FtA57H+x)X;8IQuYt@sZlC@sd<_a!rEVtm~e{t?|&p74Ko{m*0OEtwvWOSHj2vUmy3=2u;pAZ>X` zXFi`-9rPd11+Mhic9p|orVhAfz?7zhnzVSFV`AEw0B!tw3~K`+)h2epIQbS%qh^r` z4OJepsqdI|HMvhT#K9zYbml*?7*e##@(+}I?9wK!D$9I^|8iR&a*rBr*JEe0?&HOn z6Cj@a+ctb6OQxAwN+!-E@C{%9bo|NbGfz{tep@BU&3bIU?>ouqldn_u2L0iU;Lw{A zl_EV>hxw+C4LW~8_x{XvyJ1{J@I5@w%pIP{0$O6Yud{FqPMbwXPf9^!IT4V+cPh7&@#i*=^? zjLfIk%lJmiI-Twx*p7!Bz^Kk&*H*X&8ETfd3~keeN}ff`)(?hY+g|=4{GKd#S_S5D zo?o~5(zVjv2rT*Bif zcQQzjVS|;`fO=CutW-09!A<~r_paq$H7RJeVgDD2y8)MGkRvgsV+kIJnJ-DdFXKdURXpNC&Ww&Q0e4%g4&|16Zxl7Vd?!56UW}Q@XMbfrS(@N*n zMrZV?9L&zz?K-u2Lp}pivUtNh%_|4NRu-%FcprMO?TX23w0!?47+FUepQAY!TI~8< zlpW5@RTog-9!i6MbXH0}{ud-|uv`^Ny0vLWH7f9CCw2dR$kQ)xQ`~|qx6QNXT|yq^ zrx@f8BV^+Cy}eE#=#_K9;GbBFZ`g(9r>fgihOWo;b!yMf!xcknh*3aFT>39Sb0@}K ztf5z+>kVO=%P40YauCuT62toEBz8|QKLW0nF$0+=$7hjRt2-3V*XzZMpznU@<+aUy z+pD~7h*srYDX~6ciD|w5@Xv@w6Gt9}#=B2d8XfBoBlEywWxzP2jPC&TF|L3OgF$A{&KV!;}Y^0 z1ouvf?oz|wVJYgF29XA-o&{#;<|Ycqo#mI2RE)}FH6EAAPWvfZsOya4`holz2F?x2 zE3_6ruG|Z!R4zJU2}FB?&c?7ZW0TTS_gAG}Q^UYlYs^2ZRkcaLws|3g6|z^lt#O+| zByKE>ux)kz)Nhstm^ZO{fs7{WHAr8($t-HG$i>wKUe%i**ua0NKe&}l8dr|jm%n?( zYwd~HX;n}~hURU!uzNj9*Efgm$)8XbQpR3+#i>V7Pl`3?d0hyj;h3w7Yl! zCEwg@4ih4}vMFSqpWumS{Ek{)MzNcrR=AGG_OqsC6x{e$Fjhq0UXNIvoj&=h(XHZa z<@9R(h~7){V@6h3!s~$7k>(T`$f4)%Ra-=mD+eM-H1fh}DT@a>|xzUBTi6aRb7!=DO9(Xy2)TdoO^=HoGkQQ*FA z(c&xB(wJV>IeBS_f_+zP^!0pyaI3tVSe-Rb=I7H4y7T-!LYzMOwi^_fZ*@>dqGa#( z>76zxXkxZ<;5Z<2LAkA@yZbY@~xQRss7ER&&6$jclL zG**Z_HJef#J_j^?h!G*85Rv%tIp0gt)}1>(RdC$4&!T&bWvz@jvlug~5qaUr?mRE( z_Eo{t8{-wV7gjqfVSBqydpV2KB(W=OoeP*RaM{4#0x3k?%wj+l2sMdJ>8eY)nyW{J1mGZE&MH z;+FgUx(QifLh{K|r6XgPP{(lU6bwf{#rgrHyaNc3Bd?U;nm%q9i%GGHKQLTQ&?zr@ z)yGjLD#&SJ`)9iVKP(rB33~;H8%)9Vsafnl?$S* zyej$Pvh&jt0Z`umLB0UOtvuei$6^PtpRkEyCwgg?`g8)3KA>8$(M!y%VeyIErXV+|aId6#4I9Vj7Ps^yZSA4$4~whoiMz_) z3Bv$0H~E(Z_euI-5%nA^LW1lgnL{3ik>Rl)rr1M?iz1GPQR0rG@r~kYBQzZM&7`I7dms#2h8n- z?i8|yzD?fUn4xg=_JxY}aD?vkaD=Og2z7D*HS?mQZ~OpEBwY1Bj3@ZP?gtbZ@X--2 z%fSdo+%^@sdi6{%!sQOt8mxY`6rJ}ol{)296UDg#KB^VJc6z0F@8Ot4aN_j#Y?o)t-+oP~4Ev)2N!GQVxdKp{( z?WmPl>lNdm4ncMgu7fpb;eX+#pcJjioaztQ8J@{>U8gwq>+zZhvyeI}skT5pBhos}=* zI;s+P`YL}}+zSYZ#r#V>liQ_y+WdrL{(3nhgo{f zmla=a83kK&aU|$lM|=_DYh8*O9G}V&Y!E!MPu%(oVm)V=5kWHT>w{Nfrp|BFodakI?^YmRL${ahab7j{KPO95K~~l-qffSjxV>$+ePcuoU5Lms~

;cEN~t%tkcV_djV)!-EMH%5rph8ndI>LWSVM{ z)QiiVfS47`>$WX-6N89HaBga2;GhVE*2N0|;Rmx=d4)zZ89;|Q$Js@X+(bdkIcy&z zytR`7S~53pVwmg@;bi}g@NzyejRxX_)BAI zM;<4c5K5(p1)GyEx(~j=H z;$=LWr#ge^ZqEaX;V*}J<(INmNQdchAV9%=Vx}AV0A)4xpX5~Q4tT_5`kNP*-vBl2 zG8^JYsaH#KJ9A_d0r%VPi#Q)mH%tzN- z_d3kP`(e-PSx=?s^}PlV!(Syl~i>Ta^|ObRso)j&E5r2GwZs zs8yXD$+0{#pjFlGZD%I;t#mM~+*zV_fSq8JD zgTj>QxWnm%jL(W`bZ@1|;Ec7b+bfiE&8Yfm${qfLDP!})7xy71F8cOe$udm=eybz> zSV9M3=!8A868E~Odq1D{8M7G19-DaEgq}IR;q_x8)VsIcXI=bh0NQ2TK*a*9oZezm zl`uDRhjMRo(is-jSE@+sSTeFbUZP;98h ziM4h+L`>m8D;>?36@M*u|a_|N5Cuy+hcn!4lMn%B2_ zM9bM%wCHRnGK-exTtsh5Hs6CSeMS=!T-?5^J0vZIxLn$1&w`E>8pBT6;)quFC(lWeH~_Cmj%=LB`wo%D_qK4>7%6Q~ zFxI&eePX}wp%kFL#-PKQ@QBH^xCB%1^~%eQ6gppMdf*uf@Wrb)JgbWEKe4W#bj{au z&tW8j+q5erRS!Ah3QGD1%tRJ6Cl>)bO-rG7YeIR~pp5KQ-xT!@@VT!WTEJB0kwl!Bq1@nZPGnDcbh%T{Sv%sc+ui`dKvHfkxg)RyF}#^koSj>y&@fxrqRqfA2-hCty||A zYm$`KQMsL&8~S4regu<8$A^#@Z>0o3bLErbf!PsK< zq$A3Og(aiiIE@Tnew6e#R|kwpf_Bb1_TsdGPs@O!WI#FyB4+#2Uj4FAhoWEC+U`GB zOtJrByTH@5T!=E+C#0y7B}?6L68&-qVLHC8rxmHP#dEA5HQwDnEzdzONOLDdFK8Yi z_NtIsW#<1v?T=g4gx-U`JNtu4ObRGYhW>{Oa%QPHN zle&?gk;hfx=YT^iR1jovEqeHXJ;BNJ&mB$?UA-+75Dm~N3(m^cVCj+@l3{ zP1+5A^ABX(XBejx^bc`1CI^Th9{q-#37tbb%gwK?H{K@v1vz1R0DRPX1R~|NYxQck zB38|EgT`;@&Q#r4hk1ESou|QKSa!+H?VCjnYZfyRKTroOgsmvaHtXvAaReqt_2#mg z8q9Qe)up*>pK^S1ghzeiQ61+1$!53*r}p!vqNUR{J0EXn5XC-t0mj;7gP~r7y=>^e zAEj(JF%l~w@FDP@pIqTY8b6_&IsU`%O#i%#QY_^;x(nGfq3G~D@1vSf3D;gj=G!m4 z3+-c7V!g7RRZym0*|_4{cE|BS=q^y&BdbwD_)tvXPP*Ot785KjyJ~4XbN&}3nE!ZL zvjPV1cc_=JXA1G*vF8veereSVH}Zi|i*fQ<$-v)1IGnZyqtaYf-Yry9bZbFwf8vY6l0Tp0m+ ztORS4Vj5aK-0?m1PGRlK_cIHZ2hE#F4~FZd2fZo>BAjgmkmvk=QucS@Vl9vM>iE$k zKWWFJh*5N1EmLx&qSK)Y&Vk3SV>Va()Xhe4X9j+1EtOl{zH7A6#?ttHk|E}1(EVHc zW43+EW+k{J)in=3Z|3Ur0AC8~;b@`hFV;yUrJb5Bc4;n=8BvdSJsi7@N_LR5UKO!L zbB4lK=5&oq`bO#cRu*5qLyma&XhZ0O>(zfiE}H9y$42mcMIW^r>;KFJ@7LUM3URKC z^^h)mfx8~#Rg>}FxQ4W<2^16>{Cqc&XFI>IGb#e?M54-Qy>wI9es|-*X=@I6P`#=B z_>o8oHNi=uew0-^ar1KAY>`tlOysBAKkA9#Nv$AjaIkZ}I`chulHP$v7WRzBh;n*L ziL2%g$*pD6{OYzql}t?6l*F-#Bb>-Yu^?T*$#Q5zvFS!aeIO*;%^yK2r+>T+Fa&a^ z!e_}T!Tab?{~q5ezN;oLzsf+9F$la(bA#8LWy4hCpH0Hwj8lG(p*L7eSE7VMjz;Z` z$eNA5V)ilav6k`=9kV3!9Zoh$Ha}nOy>Zt;c;?^Cj&mJ6kqH5Y9d2wd4ZP-I!D#GA zc$bz^&CmyI6!Ep?l#EivTh|v9gN!Nk^)xI+t+knZ0jt1(%I0Oqcyi3DIg_lgiLXMW zl$5Kz!vp&0&}3uQYv7fCk8;S=?pUjU8LYkqK*Bg3J-IYU!+8C~tHO=8?x%t~YHT28vBkI{V)mX_(`rT;(z-#S&0x-=f9ICpF&mty?zNo~gb`%8@lov1 zB?Q!yUTcgZn=@6u$)y5d@G1Q@hGp+;Cio&Pjp{J@{&IKPz#RQ5PWM!_GAt$nc_l%@ zb{-OW=j+@#?$CR)fd9p-fkza^_kZDE69>xzRc1C9kg|J~%Kbd)AQ-$F66A%0s-6;9~<;bz-(Nf_1ePcUyE2@jT!SGmyY4d{|7`QmiC#nny zt3_U6D|U^yDtyfl#z?@(ldNS^kYe^__=w`5sTp}~0Leyh9D3T%XE}5*W%aAwKUQV} zt#3JUwGia(hH>#AGrLs`JbO!M3oIq@1g&_M~*MXY+0Nzk{mQtfESdwzM|2O0Be26h+P0 z+S(Mgx9C7??@d~JG(w3@S}V0`i@moRF(V>b}=GnCfv;-LSJc&&ux61X5=2 zqrQrnrclMr8*tJhH}Eyn#E37uxX341@zwJ~-T?*gzfau$&ujCDUGyAJq=JA0-a6ysIe^dM_a=-<%Y4u7bi-SL%7%bw^xjoD(Z0|XNeamr|6=at}KPTiPb z5PHw3YBKi19JIVO41a}gwDw-3Zptg0;_A8CeF2dsDcmOw@#QYQeZ@PCeT)@VIvwq1 zY*)Heo~u|sLzGGUFL3oAyx{L+YeDQ&fe8x~p?81DHR%AGIzL7pQY8>mv6=31f=+U0 zOv6h{GMEn7Il3R7G-L6DPSbnYVd1ZxxuZP%>}? zsI)F%M~XJ8JOP}HWH$*dQRZKgAaNERapNzhbEshgnS__M>dkLKz5x2LTcx{z0E{3( z;>FrTqZ3-z`jGi0JO6>C8vWmgUzS$rO9Kebj&w=VS*Dc9Dh9cqspx_C zX*_?QGzztBnGk-@&zIv1%tx+z6=UEawJZm{qLln+RV25EBedaaiJ-$`z6dQwlG}sf zTJsXiTMuc?hj$k87)u}08oLb&$>KCXcceWEhKfLiLwpAyo#@c`6hJL@-bND$=vAl_ zkjf+6Sta*BUnr3B^DX+@7_J9@jsz)>P^BlG@iPNBEgNaBmUJ!*0~nerjZxyr1LI(U zF28f0W|UNt*a5h*9U^-TRshrXb8^**qGx|4U;9XqZdUzhV5?_o0@4*^^YZC&1IGDKSXUYUA<1gYI4pY6OMLociGtqEe z0NfR)12oN!v`=+2|9}Qir+JoqW6eHKBn2tnD%p0hl_V?we93TFXeQ5HTOL>m z7KtP0ksHs+E*D5j58DJ^O}96y(6}3XHFn^s9SO}H#?XH#t`@@BSPdkubY2zyFFn}* zb**o*^;lMVJndZwiy%;OraQb)UgPaO!CXv)8SiIV8mAbfE+u{7Oad1lBa(V5Rj%#g zAPC50r!P@uQ%QJoJ~j+ZM;P^?K8^W807e?Z88$TkF|d#tNLfxElSs zI@2y+J#g#JVUe8pm-p3s^MQ-Hgv}yEA69b9?@bV*?uBwDgKh$}C z0DXD*$i!GG%>49fU+VmCS)|?ovGeFNChCLvL-d7HjH8RM%bVQJr0afs2rz@O9!8M4 zr?xb@rY3q+l%BS;z-1o`;b~-mwAUgU>bY6X#25|XVK!f8SB&Eb2XpXrxze%;?&1$K^-JA_HjO`^$v(ob35yRw;@ArzhZ+_}%|aMH0qB}?wTH!c^va^6LXxlO&Yj_$ zJH(__o};(eYSFW=t?MxC*E7XMsYuB?w*z0<=uXybnqfcKmp(G$cwM5F+c-U&cA%WL z%c`VXo^5cub$ibFS*qAQ7MUhF+F3Ehe}+FT$i`=d43bdct;neeyhNJvTw$?w`Yd zl3v3L{a!A`Vad}kP6gvyfndUZO=KO%D!TxNaN|^D)3{RQe$$(DB>+1l(=Vv@Eq^EU z4K@-Cz%=h52#Ln}v&rmcGQN%#o#mE6xBc~f7e$77txrkwPOM(7Uqndc(K@Knrf#Ld zuf)4PVC~&&1)FRME30aC&=X5HlEt+t?6xD>0>yU?p2xeEQ$Ai3CQdHuU^}C%&iEG( ztewZvTyOChsW})^mb=zFJoBE&i}TV5W^|648DON5HK_)fqeun3S7KaZPiEL@A#)IGFNVNQd9+N1jyI z(Ng6xCwA`}=(Jh~oAs@E+YOmsym@r}c9UY;)o@e}4yub~>aQLW6c$+}E;m~L!~-#p z=AUv1m+H;F;llK41|dyw6kh4aQA<`y5d2|`VA*C1isG>EiW2+Q6m$%)?&iGRG1z+c zVFP_|jDYkL!1J@0wwyRsjhs`67Dz!2;Xr*?B$PzgQD$Y>u~&0{+5Fox0^Lg@>D#dZ z9Mmf-R|R+>=AT2+YA4-C zKL-N3!L%D23X7c%s~co=OO9(#XPUJDca*(n*hVs2OKotS<$x(-B0 z(Qvk-rXI1&32!`GT&8}x`vx;@ip!A8FdjUo6(K~>*zJ2L;K^7MJMmRqxs0kd11hGVk)W(*9x3x=LcBK{{hiEC@_t{4~2v`)MbBO7i+X-IpV5S zNSg7kA8zI0;&}H&98FAxY4`O($T$sncWGd$N}!S>!f+ zE3?QUyXmW!6lV0wPs_S73w9Q9b64!`Ax(gP)mKnPw&jKAk_~gN8m6awL^`=a?^`rQ z<#xr8F=e>|N+z4NpIkx&mHmb0Zi-+Z-wtQLBLx_Fq862=q`vBOfZEK?DxL%GxQfed zouM9HY&AE^n+W{1`0katrRBzhcJuiApSsF_FxKC#w4_ZS71+{y#!GfH#^Ix>45HSz%9-X9&z-o)7|?TJjDkbEsboe>}(wD z?O;D+k$nY3m|NY7^v_~8n$W#YG%=UFm&Zysr$GQ3 zx>tVDv0Zm9BE1423^Ri6ekXrGZwzKS0%IPm_~;jc=YCx+b}+sZT0y1cZ%@DLDZBA|C+`>_N z0}Ot|SJgy1yZVtopii0W&72WtQ4CH!%nt<}3hONUF=In(kliI!>wBErHpLU;Krlxy zcdX)(J@@IduDuHa9tccVSXH%apA_Q3`(U{aoUW#KvRTB5ss%RYge|*xSLKJUox8ci zgiv+V?KX3jcdstkvb#wmqFt`??(jV2?0IYT@&;_-xewr+jKPY3zei9lr`Pgzb##Nd zJzbIojz?lw6dxnS8tSH7iBYHNPK-$96BI`nbA+bt^NuL(KZ0>CZ9ekK%zy-2z< z=C3qEm$5s$E0-R=Cg~DJH0qynK&w&*b+<5TAUUP{~c0y8iK*Zj7Uf9KB9 zc7QM!l?9dXGbJgC@dA{nz$lRfr)*|o;Mg0s>T;Varafj3u;+unO!-9Ug?3G=+JeO` zL(G>j6SLF=cKbOn4ZLUL*51O2x2OIgK7DLOFyP5BgT}y?M=CAV+gjS6s0GKLaw-cE zoYa$H^+^WGr*R4I0*OiaSOzq`As}{{;Y@U84D37BgLKs&HF+;+=s0e6N_F3w^U@xp zd-;$fsw}|tosl@3hR=pu?sf-C%eWnU9ck?nKQj&~{~`Hf;2}ps0l|6LX+_uFo}s|^ zUWEat+M&xuf|=P166>Jen=Fnd*;-3}M5cXmbw^Lhq!z6UQH%qbrNuuk1}jX~3^dAP zuk|j}RjZq+u$=^O79ApPV`p14fUdZyWi-qRy_BWGskmkjqmc{1AJ!}U0rBV|e*`uH zlP-3Uem{-Fl$ZdpP}7pyR#bx0n*Y7ebcuFlg$opKx8<1Oau=AZ5?0<>=pW!QV&#=y zpD$_~TfsO%UQn_LI#kvY-t z3;%DPocDiOI!o~!VSx+sIy7L-n)6Z~2j%xb39W96A1q3;2uQ6PFLTb9Zi!~}OBjPp zb6!-SScg#_w8tem9~MK7G0((n&XNw8u%@bQIA_jW+Z}x@5J>IAKY6anWq20xV(An@clt1B zFye)y%rH)cQ{?eZ|ck3!ZL)J}y-*@t^2(;BknUlva6X7GxS^&*|;+<8VJE zCB?j+Q#QKC*F`M?Qwr>kx6ed~lzj7^QCC-6WROMX_a}Q9gM<7X;e%k8zEI;(g;B|< z^SDF*dy9WSY&M8rlmd8CJ|*ttux`%cbc?N!-4wkS%%?=qtU zwu?fvUd|CmYs0Ybv5tEeqjCpRIgwuVA@Bo-qvLy1Tpo6LfPtAtL-5lD7w$-|C=weR zX%MaIUDP#?v&Y0it7}qH_n!5TQrWWr@QtPr9`upe4I?8M<@vmF(n3!VD_rm9zaCKf zqUHBH_Q}R0G18zDio)G9JF-=vgQ)K)H)A0>Un+zk?uPYI9>Gfd^vZht@EnyDyf|RT zXOHa5S{)z;B6e^*JFV(bGfJaPHd-1fcHg11+UZM&A~+t7h}(7L*z7M783jt3GUbj&W*E~B*eyN15=@);Qf=7_4WXwPEkvFd+0ylAml(HM0c z$QV1D5AsoNeX19}<%xLTEW5kCSnQ){jMP8v8P)6pU%6DKY?pqKk6%Jlnt$^>zMtIh zxwsZTYt!nH_gRwUY()An#JC+k8ZmF^)hRhVkUF!(@mMkLmkQPc1jIIvBaR%0o24D! ztt8MzRii3Wh5AY)|64*|@s6>_e~gITXYOLf>|Ik|+$uAK&MF+P ztUQRmA<(MM6rPlW;=Hrsq@1{^@tErQzo6k|nt!07d@>|mIbK=#x0~UBAVMOFJJM`y zsiFY07e?=Tjpw7N!eGHU4V>K#=&Na&e+j77&J2N(mUw5s|;qVd~92# z*!EH&6|i1CAUyrVEVbdPQkEzm!NJ`rD+gTbv4!{T}6KFjCXH{5C0mMjZjzd%z8Sm$hv?dPxJKdFHkP)ML;rKti`$=?I5g9aSR_w~%$LuzpFM6ai)^}cXN(=;1(v}f(CWk) zUM#XYVL^j`=vjHQD>d`|U+AvbOx}RQ3)r|wo93_Zig7OI~RMeO{uujlj((uzP+7&VeF6sgpc-zpgr-JQhTq7l@#y78RffG^`E{ZixbpZ zF9ab^EEZj;yXR(^H)YtSnqi*YEQg?7DE)hj!rf$RL5<5V9U5w#h@3di5~)Ig((8#p z_~r@VIR77`-hVIagpU0PvrJdJk#sv4Y(^09J^L~r$g%lg|M!;^u;K7%zAN|w0PJHv zD9|?i@?MX92c0%U4K_Fs{J#1+sL5x@dzOGjpmwJu1q2Ul-pv>6kMcNo@7=&-G9cB& zaaM~X7j&;Z_N_NHGZ{9L?ku@c4W<918%CpPuD&N%M|cLXwBI++f!crm0kxFDl;r1m zfdB4Y;sjKv%l!IZ{8!a#mI5KF0ZZf(_MoOlB~5U%}@GAElaCzF@NzB}AW+Vvq_ zq0s$IKo%FP_X-fqEfBccglSqBTc9W0K$!klNBz5@fu79R-1;l`v zl794q!NPzNu;h6->e4#EFaeYaECX^t(@?}?8GUILwSO)1=aH7R@RCkFhIjCPeGIfM zUE^YMmVsXZEUt_sug+D7@6O-sS&|HG(pB0dIS&$ky-sZvT_GTGk{_?<@SxZrnANxV_gHjYpbjh@Io>7miBW}DZiJ6NR>^Xc|8h095tE)sOw57tPDkO-07>9yO7|M$zFKFbm!%QF zFLnOwVZ$`3!P)b1mw-4z5a>YHrZia3`3Y?KyZvZHnxMj4@0I`vGR5*VT z4*p1_v*kbVG7o^4sfR0Y4ZVB`5@WSuF3-}dBSthJNJ5iA?C_qxJufMX?1*=9-p=y} zpD(3Rr3s@KBUKP#Pfap&$>VD$jb5d3(zJh*`J#XImPlo27q{;u5 zp#A4Vuer&u_(!SGj(Ac&J3Zh*D#-dai;Udx%4YL#Z&2m@NVL z9^I5mw?7aL7kW2aFX|%j76`?m*SeaO(M;?VJ%L*87O+?R{ER2J8o)VjQxcWbif|J> zR9+Jm{}(;bJqk5rUc{x-T|nS@U8j`kfzG2t#>D63r%ql+nC%`zsOJe2!f}!I-2x}> zD(AXsFH;{s<7z$o_>75TGQ@CFrkJ?7>#$e;GWHS2$O=+IDgl^6D@hw#bBs1*Ix;dv z=M0#da_}~Vg<2;{JFG z>AL~_UYf4A%02*5O6Mb?D3m~^0uzS+F*61%H*PM@exQp~VBOGulCk|8J$dV}%k6t0 z#M4iRi`SFCm0$UiKL6)0V@CASczf1C|q?~mGehksKv)_ zSMipGSHquynfhK|`Tj1xfmZIYOOdMs$_@t#>?6*uOY14|s|DTO;K7>2MfT}v-l0q) z<2X#oqZ&p{Fba4W)|#GRTUYJLnZ`78ieQDWh7CQ=3X#(m$Xp@1&B#hJaql0Xf-Iwsl{F zI^yu~H*mxip1r5NTFPkV#Zc6Jq%;DO9P@T(tF zX~b0BoZw<#0DfupV$;>u`KF}$w-P(IV@_;Y zKNz3LK{#I8uRmr!1oTftTg*#2*^j|yas)fNg&Re5=;$>yzy|o@G&Ysbz0A;DDN@}eJ zjXi`Ac#g<3HRmJ6`(r{ACc7g9rD2})#Q^b#V{7-jNfljQz6LMPw3EI+lrF<)^-G+I zUz{0X3d5F9&8ERA1?Ec^1r|&^xu^S(g_?{Dx#U*S{_W;h-nSWS>%N94sqLU?FLkgs z(_#@}A__Nf@65cquHvl{B%8myM(uSy9OGHjx{1&9Mhx(u3@ucDx|o6`JsR~f(2z9= z`?WV6^!N|R6TKKolsuZclVR`!lO$P!+?p1`OqU#h>9JZ=I?1%5PD&Qz>dESj)rQmz?~e#VC!h2&0IJoT1uH4ueXPdVDDr}AZZ#S& z!7~p1cxLw=%^dq#ss2OJ+I~DvEM^hZLFO zBDRJ?4AP17wUl+Q9J0`#oZ#wtU0AhD3AdMOuz+FfQu>skBpG!hXV z*)RoOjr-lIy9aUBFF!dgq;eR(oq`l}jLd^Cx_k{VT2OC5RF$e17VT|e&c41o*@=cl z`Dfm3=8?{2l}@=~Y=VLmuPoe>@nkK=IuosdUd4cjQw?+bbaY!=n7RS%c{F29z33k6 zGeQYP5yi!(okhB~k3=?{n(BhJO#bMr%E&(;f3~_K?LG|C5~@<9)ksbWuDU4n(%A53 zQdCVwUzQa1srxWB5vq2$$Lc7YuPa@)b-f@5m4+H3a(>yecE#uM#1wx!KOrYpi3Z#_ z74)ez9ll8%iGR z8yg-N)u(mw7%jwT7oB zsjGb1vGUO>nb%9NOhzr;u^8}>?F~8<`ufG*%DM2{X@Z%>2O{GJ>q_TNpMT6H(R)FncL;wqt5^}gv3yh#&D_BG=s6D9y=AjkikpIaf|e|IL=mi5ijUg_ zB_EsG*Edh&=<0I`juX9=;l3X7S@I4ZW{tBa96@Hu!yVn(eu^mQVY$iQ%9(n%zs5q;fw0XhlWQx6+mH0zW9Mwjg?>AW+_>_H zyYMXOZkZX*{dq;renE}3CgFYftzPC{M)y}ttOG}qcTm}d`Np^ijYf2eH;Y2#8>n&f zH^KM(Kf)?{eeyM2{9PT!Lw&ixzblvqE93_jhC2a`nDFXxcAt{3Cn8GH#FPx2DbLLU z&#?Ho^}Vi&VkFmP&Cw3?UTz~z^DZZ)R{u6{nI8siY}P^cw4W1ihlIP78cn}w^<+4^ zZcw6~+_PU82G?4AZ*hBC>?v35%S8juEnW%2YN3RFCO%hYv9;a_gYTBE+{k50bDd)s zGyQ$_F?9SjMpa4igZbKeD1Q?;)MZCH0}*;c@w4G4@%JZF?~g$g6AtsulR1X7tGE%6 zOW%9*KD82{L_(}>j^xSh_3rcp*C5S~5z$IG?XxGA(ns;nPG(zYDGp*tXC-^HBe-cb zwbJS^le=(E<~x5tA8$Q<887|C+?Xq__B0)@=R;u;e{)eiZ6MSKG%8#?XTM0XRWBGp z9Qv-Z8II>SDsT-M(MzzHfe_3KJ70-KU+)nv42`s&xw=eXsF@4$3Gm#F3EwV*$FtvE zSyZpl=umfUWR_PY%O>{;=T`d$Na7=j~>T*X4J4NoORzzFnNpENerz;F$GW! z5|kK(rlXScPzN(N5jaWzu^yXN}q^0m_rL}KKmC?e!!=6K_uqB9t1&#*wN-X`>-O4U7< zi%ntkGsS0LK7TabjvsHVgl!)(^*JPSX^aYQ1-JP(0=D~U=hO@CfntW`%va ze#6rqckaA^I1#rF1mPaeq?GU+bG2LRWB#{TpjmrQ8MU}&;Z1mebIA*k=+7Ohs(tvH z>~FR9;a!yMLbgzDoURA2vHnbVUcl^HeRdfYnV|YgavY%tFtLCy9mItA@lQ@D-$lhj z^UUv^Wa8-_ZJA9oLiR5TFqzyiHjI3dStvBA@asyHbkPqZAX6F<80b=9)a~gh_Q>UG zvM;wZC57LLYUj9++MRT(nor9~qtgA(HkQE@@PM>)Y8q3V5kreJc1v!|@7-f#k=GAw z+GJi_-MZnr$Y;|}kQbO->r(5M$&^IngnVcK`FxAq)greQmb}2NMT((c=0RpMFcAQt zBGe*=0DyYSDB`MWr(C=}Zw|^y!Q&hS@L``EU(M47Fl@R06Ba=&5Xsa4wU}uy+r5s# zZZ7ht{a1U?!Juu&1F9p9vv{suL9ga}*r;#a3sR)&@(K?r$KFZXurL1s^#@gv(EUz1 zgfnE4{247O0noxkqf{9 zWGwsAZgwbbw)d()RTq&=d+%4aVUB)6bIu zg2fk~(0h3E%EArGX@y?5cqo@eqzCS9{78)=SIg{7R5)xf82p+S@l%A3@EYK~AtMax z*k~YEC2*{Lv7Qb`brr0JPdM_xwPRz@x>QjR!%!Ex_Err~t8A;n0Yj1#Oh&5B^#BBo zpaH)@B=nqas{N&#x|=WtpEQZ0o_nzvLGTXDZ@;tPUkXR=bfW_QPpqof8!9^Qrdf2c zDYY3!-)uWoOV_oa_V-2I4{TYpv6>0bi+ew|DbmpT#s>|+s?^5efOS{$4Xb5h zedAxHO7#IxF~B!p##^PH^G%#50y3)gUsl{T+ULON`+v=m z{QEvcAqqI~y>(pBcog7RX0kIRxYPl=5YaY7*7LzzUtV5ouu*m%(z=QIM3fnl13T6k zcu%|DIh4lG_qxv`E>6o=$L68ki=U`9b*|~t zSsiZ#CGFENLUs(P$*JqZa~~Ob2AXXDs!G(4EonCt%lb3TKqV3Vez=IE9V9*B;qKx0>tgHqs)v&TP^|u5 zz#Z*YF>Rt95>E{EAaboZ0K1ddGLQdzPyAoE=>}2bJUT!`AK846+Y2M7KEg!<&aS3+ z&7Nl=o+3yBOKr7Kf_=%e)C20G*{3fN2ezY+Gx zV>uMyirGb^JN_2I@hW6Q#E@^0`0}|s_a5+m4=QMuNA!yoyT2$#Z7Ta72Hgj^xL?Pk z|0GW8s!E{0N==c?|JWy;L)&x7=6_`RsiZylk z83f-^tGK@Y{BtRNI4E7zz_N(TJjq6MF!*kyeo_0Q>+1%&0HG9x+-5QsHCO;F)3+d8 z?EGIX^G!bhUS=ip5P*XQ(LcQQSH`I~XWaA`gqD_v7hhV3d|@PUqaQ45;m;HJpXIN& z%O3NR4(q##>gO;y-+FlM6_bOg{vtd7lx03h>v}2Q^A7$tVDZ`e^fdA(@4nt#e|Yug zx-M_gV1aoe$!)z7en}?Y&lK>dRU-iXRLC=aHFQP};ssV2E{g>5F0Et&4@4&d8>Z~@ zCOeX0ZQ!dK24)?2^YS@>pv3bp6%T-B79NKPq^gudbTI31>yX6C&NCp_Pfth(`FNOw z;h>1SIQw(#;pa=-00qrf)VGo#F;~>TTPns{CGQ=H*N6i7dmz2k5f;G5>=4-z z%=c^r_Qv5i05y>yZNL+qRew%FSLN+UBe#r>X&{9TeX0HAEEAOlawF@#wmm>~=#9`4 z1~&ci`jN{;q=_TSx}#;lD*<>_H+6*1VF?LXM*Fq9WZ)Z`uCFpA%5qQ&5J>uzP6L6Qn)Zw;!toXWe5lkqV;OG0G$qfomQsQDY5GT80w z0Tr|g1r4k{yUU1ikD}UE@GmIq5F);9_$bK){IVOEEQPdm$eSZp7`0W*GclqYAxyU? zyZ(T@q+D{+p<}`^>h`Fe_r@jqcd9I=v?L6EzYBNoz-G#PgB^wPAu}{&MS+>8r!W6w ztuE}&nwkL8k@P2c(b9fgI-bqu(M@3b-9Z1sB7!NixWy#LTJlmIP=lQp)=_- zO|6=OCaI|pNEc)r*g|Ozo6z{WIAWA8CN=PLX+Q}Hex(duJkxUJYc}9nvi=1A*jeUl zz2(G}A%NxL|5XwDW6o|QBcVnttR69{d92=>+h0^B%*kk>a-3$xxg}%~*1;|}32mow z>%MFtD*!9m=gQCd_5v#zIc=5;-lFUe-J^P&x~zg{T}gU?UQjY)0OkTye|e*`ITg5f zr+dFq|H|!&IGdluBG`9@QP_p|Gh+HV7I;?L0Zd74{Iv!nxNSj1iXtyUT?{73bFFb_ zu)9?A*KAOzW=cSMQX=G1(C(5S#{vQ(GUxA@>a^;s_x0)(U2pfPGl61#Aq&fhLRQKA zOAUF@?4*S++8u(BPj_RiK7PBk@l{Mfc=dgk<(LYDNTYD;qx9 zR;N*_-iQpPK$=sC7Qby*p+`X_Jm#=&EfD?WCc*%g=Y4=#;9SfV6NhS=)1T2C;>T8s zBU+=)9lPFbTNLd<>?x3%hNqS_k)58@kz_yKCd93;`D1#)Ohjr24zl|Aqpk-c55348qIJ%6AMF+C)w}{R&b{7*n3}d1yC;oY z#+hGFiIIml)(^oGHx_afX>q^Zk+Ko~o^ln(;GS^&u@-VDfMI^jX@SbV(6EhOrTo0n z!Wh>uZ`*zf3qd)a3MbeHIDg#dPW;yScHj{^igI1f=OW&)c#)`(;a0xR#El=6984l5pF0smT8CgHNZ(KV3$bm*uv?NC+AWJVrb< zKJ;~hXHao-A}3Wy*Sd()og2Qe{M}zF1|i(v2(qPSI|6oy0pCCjfljWzA?10h6~nl; zZ`thkbj>e?@NK7fE`PeXmGZk*kAvR4ub$saz+Ax8_^2GYA_tSq_dFpx%Td3eb1H@N z=5+wXs`e@?&RY-im|n4-f?kss=xujZX63AJ;gMQCgQlI*Lgt%g8i|$Zsw$-o#O5tJ zy4~59X$xb+&ahL3ArM9Ci^XxrQ3BU4T64fk>-IE~3Xr-8v3s+f(vED&@U#>-eRI&A z^W1w$ENEyFSF9LVyln3r8@)uUHH?WlG#wHrN;D;MDxnU~49~RaLb}|t>{TX)&CI(8 zoKEoBPG1NjP0bU>zXTVEbHJz$KeEQk^Wk8c{84olPg5apUfuHH%y3^K4Nw?tD z?k0n7XIJQRGs-nrJ=>{=WqA*^Ec=SBWSCCRAeK;_?BZ>f`%>METjO>pgf5bsR*STb zlQH0N)xgMHm4K)3&@z}mP{Vf{xo8G4p8BTw@&izt!W*QG!;dog7!vQgX=c;j--qVN z2XH*j8O90|)eo)V>bi9!W$6nW2FV87esnKn^`BF*ktD3~mZ4j{S?|N_D%G$Nkpb-| z;9x}9aj8a^3uFYQZk*GqYZ{BPifj`3ag0x9N%=j%xsZTZHgnFH3smT);Xf z*IY!qHkOiqpplFADt0FKyk^h;y}*lxZ@D^>@^>L+prnE$%cu5nne2@~nV9eyX+}Z2 zA`0v4UqzT5lSl7golK^4y*;Na>z_W>80!DA=S|lwp3+6`KmiWU3+tP=;um}BV>6TE zVkE0h(yO#&>3&;^*c&y;aP{C1R`S)2mQKrm&MHZ6imulOz9W>kUSZ!Q7t?TjRx@Ar z#R7MwOsh1%F~6}{;CrNhTFO3_q$-j5XU@%PgRD4gP)_y2KLJ0p5$H@&>)Y)CG+MJ z?m4Q>F31THn+Gt{*IAG3Z1vaHS<`(t0?I@_*c&t?F$H10h|PuMeC8h~RmK|- zSr}D#4!-tU&Iu<3P_5VKj90AX?Wmm$DP!P=`QFvSa+Sa4BOy*ewFT>O7>g2eU;Pqb z77%CO#2+ARSPGc0!Xt8E=|q(7(x#O(ff_bkK_hu&U2_t2vASm0q|MKKk@0eo(%Bjv z__!0HfN7*Gua*?zS2v==O4x{>VEVHea61JX&te@0*cB|%=?Zq8#3b8=?513E9|uqS z`OJFajw7l2BvbzD8WQ8k(w8M$1Hf6CXv?ZmH8TUX0)I4oy9_17f+Zq%tGo3=7JA&< zS})!xYK8ltBT-gaRC=~{62%@T8F}@N1e94=I6f%+q@HPW-r_z-ZdmRaU41+Mb=;n1 zQAY`J4{{m zMV{_9>Y+_d_&jAd>(Ay$anqIJxf?h7d!02(vs;r0rR(Jc?bHEi6H;m2_81N(Tc|Ll zi?d`nk{iCWbdq~4AGG2_*DA00yM8LUXUyayj&qAvw(i%2IXCUYq5;K(k6s9vDp#e(!q07yZ)*P=6Pc zOEY@44iPrqOe$Q>!hdku3eEIBEraA_Vym2xiKTw@8VE#WV$#BPOwTgQV@)vwI{;&sa~_435Djslo@|RHnOs_ ze66s30Uw?ptdL+2X^*D6(=S6s_wNIB#0{d`jzQr9Cpk!mqzyH=k-O@~*QD{|IvY#Om|uFj$EtzD6^P4|*hy`O)x;>$dj9Ob|Jmbt zA*WkrecWLnN?gVwVvEEd%dw{+{>;0opX(Lr`%u_f!O_vzz9<+Qk~7>m;SrU5K^Rrg z${3pqP(a_L;cEtc`X=V0qL4P)a%9uPj07q_gk0uD@DG}Rxr){7Wh!^^H?@1JiAaEyH-CfjUs1<5lMkLJZXhs<8 z`K@>16C@Cx`Cg!~cstOVi+Hj=8q9T;0JTabkg?Z95MI8H$0cC`^FO?I8zURY7}YwX z*tF39m(B98)NP!bzSw4tlD+L*R=?pmzcVp(RPR{OxNGswMf7@)aVVV1^Y^QdF+XeO zcu8lsUY?qr2>H(KT$r(ONxyMsd~rdcgZCql%U4f{ON?)echlm|KKNH;z~2!K6Mz@V z6ewl_o{uE2EE~@%zO57-16n4#Ft8Z({N9vYg<+ao2Y4hU4bJZdm%JooWH|@^-hld) zo^D~mWwLhfzEx}_i`KD0^WvaHga(!7yN-?vHOP?1+;;asjML0YmAgl27hx|+CyiUa z=tx{=@4r3{rFgkx5Y%#PE81r{P|xbV0-FcvoR0%Kxe01x*8GL>1Had5@PsT>@d*k6gA+X zaD)D1_T7Me0LBAD+ot`*bA0^&|5qgk&gor{_tzYRci1-7Mo-_9tt5es7U*be>Wq^d zh5c6Fo%R4H-`F{zU=|>_Hl?#eKrwdujRabWg4+6$bLLL~rfcpFa zMYtYln~Pgi?9LdMU%$gA66A*(2uNA*czhpVNRW|q@}S_LcEDi}!sP-3d=<6m6@h&s z>JiG)FaYtk-XGeh-VpW&gvOo;EJy>DZY@CY*i}MWmez-3N?gqmpa6-hX~{;t1XSzF zl&5OVJZFssG>b9R?b8ygmbflxOEX;vbje<8&>}&s5X*UQK#A!zZSe08{;!tv|Bg)v z1o-}ili|p8ibz2!SN36sl0TrvNIK#>flUWo1o84|$)!fKg(f-J;i%{{iqo=30JAUM znjj2G#|YmK@*>2oYvbtmDYlLaPk@kQuy3@}p?unr9T5ICFLTCthV&A4 znH@<>zVWMJfU}t=iG@cw=mSxGOk!R|qXpUkx++dMELtocu_HBXH;mNdGvHz*k$CmB zL-cuvjD9L6AEa@;R6G2gWT`70q;+NeoUT==LvEWsC;te^Hw!OmY2sf}e|RnDoUG~J zHg2NqC$CjeYoO5&ark{ZSg3{nKtTW2KX;$gxV+nl$5kZGOr_;;{SW$MN+6?;`aefY zpUCLfhJcI!rWXSFs9)QD4%#jQpsmO8;nkdj;#}Y(GRZ^(c#SqmY}k(9>hLo~(F(9q z;c<2(i^!*Z=fXp`@W7kvnm~0BY0AXgO||AKP!3GP_|0d~P;!RmXVT27iNL=J8X^vA zH2)}1&p8`c1`hf9_t9WpO-BWHNa2pr zemW>u^y^8lIjqUH?;)eJfXo77iUSFg@&n~c+WvANjKJhUI_X8dGiAMcfZovUxI||) zy-vz6UkIcRh#lP);A&I)4`llIGaFEMpz1wPlkbYnB3HI zi0miTrFjq~7EEcMFVPBgSTjB+=>-nu09yM8F#fmPR$IxUq8~}45sa)%ckxt=`BfG2 zU?iYC!sTb}V^2;&rrEg1;aeWSCd}GCO1*MJ2{`Q4aQ=j-77}ijhh5y>c6>kmoSf-E zI*6?Y%US}cz$TzS2y|Ydim8wh-EaFt#LG(~F$<*{k59EsOsHfdifvyrg^Hoc)-BWw zaa>P^c3%xG*l@ProPrvUN1s;(cNEDpzG__5<&&Ym)`3VbC-+)bB!hWI}ZSp zmXrFv!YosIpjqCK(}CJ*7vA=JAeg?*d3!q*MA{Y%jRHb(ez#yIpDA!Qr9y+|yXY`X zJKuu(p;V1LEYU4iv54KVi3Av$w60h8sK5X7Pat~9xrr5Gh(0X)4W^t=InCB=vO)X- z^>io1nWx+8L9eF)_*>=`U`X`sqo1M^Y}HgV z|J2^mZOPClsAI}YTx}cr3?fhzG|B;Pv|Khb8W+jC|D6a=$D4wwS4weud^!h_&?moG z6mGQzcrpf>{Q>nHcUz37sK#*E^$5$m|D6-)8uS_qQG}ZJHx=*E~VCat)n4ib95rFo< zg=&1V_nL4{T=jM5B*TLZX$0-40>heddIF=6rHIW3>`6vRx;-f3r zw(uE=H7Io$H|f0Y_tYCIvt9gSShUttT`W>Sy&)PEv^oTgv(3K`sZUCAzw&uMFO10B zjvp2xkin*R7kA6}4b3l8yKyORju^fOKRT0LkcbFrs-bO~QJ`Bk_BP;P!?sB$-HtbX zGwY_0XqSHfW6cr5pYfh($*|1e&BIKqo!ik=}-`KjjN`F@znEJ~voUsnT9K(75ai?=W zU#Sq@1XIDz#PCdpR>LFv3J$Qn7GU*r(z}N2g*>@!?GDJKdjk$tTO!#u8n}ZVwPg!f zKVY}hY03XMo7Q2VT>}%)K_%SdMLc&29*k*#i!5FS!rC1JE;mfREq(0Ex!3s??Y9p_ z-m}=>--QC7ScJ_@m1pbCA;aFX1F^;;Zk06%=Ka+S4iBkHfzS+CvY_h@m^RFraI6aI zQ9+Bon@8$ii)+0^&MZHkP=a_N&ftgB>syyZ_kRWv!iLi^(-xAEzcz-QuS31$@qa+y z!5O&HHo?_!eld_M1#{`3ngzf|1STAF_93Obt8etm8!Y@_Ng z{S4@6Ux=Bsrv<@$Dagg^&D-em_Ip`s{}3e}d)Pl4_{Fbv@Uw6}z7V zmyCo24RUBVZsN**+yMETHYJcIeJCD{tW46}s=^IU)F`!wbrJ{XGcMoRQoB@W7vmAC zu#?)Y_i_;}(l*V1xNxbtUji4Z4HH4f=y&B4e|&`;$kHJnT5I%0p@HLHsa;RxPRF_1 zBSn+mO5_2pzMxz4je(c>1sCAt zpq3-=u`}sLrP^s7``TRKjI93w=tJWsPzy)E>!ez@y;TKGPaK<`Y4;@QB@Jf%@S|6s z!5-$C)4w*YXeKpYR6Pc!gt$IU-V53tRG&bjN^8k#?h!VTipzxx3PPyiRdnyRI$HV= zaL}@%Dxu5<#&!`HzkWVtyc%%DalPABp5gL-%jy<^@MPr5))$#XMlt!YYPK+T!#((f&>l1NE^;f{lB^G`}s-rP4e z?+4O@2uc{sMMIgTH7bf!#yrMDf@Rh@&-}n#*ua>NW(l@R$6qxZW_P=p>(g7{t4C%O z>x2AZJ8s>Mp#Y6B#lmqxi7Abia1FTnn2Te9E9{Dfr{zea{?D`CodVvs=k|C#+-Nf9 z#)niLS4}hggeB~xZ633k-!F2hLD+>FLlqT- zQr*?)yeC|+gWAz`A4a}&2kJSj55^UMq5(+)%joK8H8X3qMpx$;{D45c?>0~FavIw>mOy)0)_ufy z2qoEdF}Xe~PtuydX?Ne~SF-#X1ohj@{7Z5?Rg#l$rHNZL$a)b@T%j+F@>!>15V|Ok z=svfp1;ZORd^~drebQXWnyY#|FuO<`A~tpYtltaz9ctcxO=*%X-}yx@{|bCowWlfd z7uKZE@coPuQ~8DOvXON1!JtxQt06t_Jig+~Imv|>aB1S#Au#&wA6f2sFjFlWru8?Y zleYQ14|F0IJfML%(p+njUz_?`HmzS)J8Q;0bA3cnC*-gv5C|<^SQJm}RpPjr^h8wM z!ODLF5d+0g%9VBL^|yMxs>MT+FCUQ0UcPI+>%Q$UsJWf_Q`_-WmxQtG&}21JRRL?3 zuV?371?j$N*5ap)o}QL5yY)8vt(p4p%c~9R8rU+yRa+R10RCJB_yR-6C0$+J)2nTG zDgh)}Sd`@lEZ#1D0nA2{E_i5CJO-+8#CG-vrzWJI^H6?3;aqbz>2+$T6oDufkU%N7 z4mRJ{x%OG6f!0p{kq8zXYvfUPzw0~OkBjQ7<$IFq-Y?wZf}rKx-E9_=@!W5lWLJ^% z$Q3WFPxkHCdc2nF1bKI8;f&2adiyv5@aCKXt~$+5&BwYA$b?Y+34uDS$=Rkh}2Wj43YDKbku;&DT%LUz!-y&|c8 z^I2@t!1N=!zPaGhqmpc$lKFb7aYAQCTuSPoN2qRD@}5!4`~jf-ND`A?2?4?pen8fg zBB_nucJ`2x5G*oG?%6n2tu#an5}MoHvjm&2-M5s&^F}V%>fb{KCZ~cpEsyCq#3cZmQKYqWmga}1n*a*k8t84&e?qk zc@dO=hsdDp{3tF=%Ivkr6NvW&iRcEjK)8F0!8V>J=19&<1Uvp~+mClhQYNd9XK%SS z9ZPjxRJumEMU`ac&2UZ6FZgTj0mup}makuVp9SRxO z3*?~QPQT`NZQe&^?A|HHc=Tle(o=x$`5&TkWX^%e5fXF&Nlj8zwj8fUd@yfTY%Eo5YBY~WZ%2~J7a_3|W&OqX)nT7%&r?pd znfieuHUH%og&44|MO@OfVsPZ-&e*}tVy~oZjM7pS9HV6DUB5}@7Ubw)mA?`W?VPI# zAtWwJQ|3muo0cgk)?a3?G+ZKUusd#2ODs=>A_4t|tY4DH;$PTOB|;?WO@y#zRF^go zpqciWQlC{W3Uybho{{Sx!!LNAr5v;q-*hixv?EQhk`h*PPuIGFS2lw+m=QXtDuV;* z6O~;)_UqwZ@UUyJT)NbT-s#HRvHeI-!zDle;SZ4%u&8SCL!5*If9yY$A8+@{3N0RK zkwsfs0GRCGJ6r|_L1GWC16WcFO?FYs#PhW899;w!o&6!TYek@Xj@ajamx}@lE|F%W|5RYRva7mw#z^LSd)}Z0%DqTU zL)|`eGUD5&j?Y)Wxm(0;_LRgvES~?fyRR-jevk?mHjjv76o;O~9@A^~}!1R&8>FR*1XI;eT z7B1!Y^V9(vWA4oept$6}*Gc~U9ozyRg%g*Q!PLKv8h7z>(U`09)pmmuB!2^E65-?V zokxJ?`>ah+jM>M_sl=>_%-{Wxddbq&h_R|+{BU}I^n}eoaJOgGj}u$q!MZpfB?7)P=>J?laOxsphu=&}>mCqxAOmkXoFb(T%az^b*wJ0 zy9-n%`2gPOf*$d^>+uTp9j*N0o_wtu6z1pK;ao+LBGG%Oit8(~bvrpo*zNQ_jSOY* zAzI(LFnk}WJg|=A-kZW5;(rNW@x_dSwZ&*oPY>|7!tQ|tO?X=P*ZMr`WeK4tg88*e zW58iG=JNk#jQ|*mODJ)%_w^qr3Ohgp$BrzfD{Co+i6~MFRy<~sX`^W zSAz~jC!vY(QE}WQD3X^`sm`Qu{`I0{=jqQ;3fKW_hg!i*xA}S`_8NfZK7<^RAPszc z^PqMfv~4O}G-z>e2$>uO&cVO?}qJ zc++Fl&T*sojk>1#xDVg&ZvhkxysY8r<&{n3vjdRlRump}GY`dLt&4KV4Y*g zXq${y&fd>lT3UN>}%y!(b@yDr#u;x{h0c3i0N4HUzdBMjWA#of2tS< zroKm#3KqJ;1yc!Ce^@x|rFMNd!luo)h^}2P+Ln?8H9Uj-Q_U|wz}HJJyQCnwg|&x7~rKw{8I=13ZX;2^cP&Vpe`PQX$O00Pw0H+ zdDX~;`%eJ+?~633iw|H#dH_1jy{rAfIL?hagH(XWFxaM2NoN^2lQW=d5^}-eHZ!Jw zC8j~`ujz_!0WCcwsa#JA$JDL|YjSL=7Zhr#T@T@s&EqJPB@&aBvd+o@VCQ_8fQ`&c z5?@YhS~TGCuWTA4;kcp`9|GK@0;(>JNC33A`KP$~FU0@1y!pDbTfuar0{g+3^2ld8 z8@6qYv=b_|>vrf&o4EQhzL$59K;g}{W+OQIGk5n~k&@2GqH;B2YjTaBs9I&szo2tH zioPB-8Lpo6nNwMdZ6BN`{K|$XTWnj4t#}megWtINZ5{R(jLzHFV&8vxpAEpF(cfmb zrEQ1?(<;_sq#*+}86;HhMO3KGqOh?mayHq*MhT7o+FYKnlT9|a8nK>DPMnQSk(1g# z$g^&A5deqNZUX|(B)Ovfmv;pUrgH2Ne|P&`ei?u^liS$cw+tbIXj=Eb6CzRrKI**? zK-T#W2>q|iA5fQ|%f&6hvZx-T>U)PgtB!~7H^W@v*LXWJOYGXYtZSV^^O&J99^;_( z#qlEP3}~DB5Qa`=OK{J^sajITESKrGBv-rVuXzTTj0!O+>HAi_5TTVPB+9*IiBvpI z1^w1%P7RO0%}u$Kybgl7R5@3rWj-WjG|PGa0m^lZnPExpyv@0gtD+r091|USo_k@? z&!Qf%D5j7fQf!V#xu4bhy*uRLTSyOr{~EtK*X)=+*InE6(-4hw&&#PZi$iUZpEb zN>5X^cxsuZXvQ2t^Ma0MMVh@{B>0nunRjBkMAFe!ac>}qm+BigxV^TOLlza(SCJO# zceRTy-ZYIf!&Z~RTvf;kEOXYl$<~frq52Coe-iUw`l%0ipE%b~5blnapz`Ec{ z1Cy_FCzptC4eV_%y)%0})t@|^W9#>|Y_Gw)XfQRB@ftp0{YZE~-RPiM?fdWxt&BR_ zQrF_kzVq=I(c`(7xS|-J&L=CEM+&m89bDqFx+C4Tz(h+8IMM!_;^Nd+VkA;HzE2dp zY7y?w$<>;9^G2mDPNdMptfw;OCibTt3(N-8+NfNz<{E!L zMPtrd##(@b1Rl(PU&YXdAS;9w>>ozGrk%QWM_zRBrPTKLF+9+Zc|^<8%f-11w3^$w zPr3aYSB!NJ!HSmvHaKHFNC3VGr!+zktcJ^ zKhu6m%?>z9#3G*4ZH44~=)v3ju?LkDD<#UchaWGT7%HgD8-qA|O@G^X*p$FDxV1!M zOud{CZ(yp_$#0@Z1LX43xaa}_GAEeZhQTfmW`jPf8lHVQtD$`zJUAzUwJY4L!%vR5 z02ZDreag({%Z$e>&J*LqTHwMjeOwD4XM|O=C-$3{ix;?x#-5DD7v_zs)>Uh+K#C3e zrOMo`g=@DjCjfb~c(A$7e#phz($s^lF!0?cm}=rDYQG6L8kReuq&|Yo$*zTab`N?U zBra+UU;3n*yaSIdR%~hKWa^NMOq*aqiI-_g%WTlENfA6n!@E!6J?a&gW07}txPBKt zya+*;VT4ho*V3h=9>CZ2Xw`C4o8Q`-HG~#*(>=U<%=&QT+7EJH#?21M99aG&;T9(E zW~fzXVZFc)pXoq*>Xk>RF16!+UFjq4| zk=9oC8#Vvf7S8eAI&|@20>P7gTfMu~uv)qJn7WMJe;MSo z7&vxKUBur2YcIcqC~s5Sb1osjwUrSes5hF2R(L*dcm;qM&wSG3%wI2hhrXC~a4LW{ z)ZS<$Z(wnp@)%sOMjiysLI(lqw*Fp(X*RR0lmtt<#oU8WbFO;h?ThmgvxWVBjA$Ii zV+kfxcCtGEd-jya8g*1sd+k+9CovLW9sLk}M$4A-@}$%bW_c(|gjU zex#pL;$!oWyJr_OtCiDueN+yuO@g9)?{^~qbFFIqyn^BM$8>iaNk5KjG?9baoj}CJ zYFN2RKODdS+sTf5NuU|m2fz+rAXPn@U@2xziRxj%EfX?e>&PBDblY~bm-CNYn%g43Myh-k1s;aja25&7UIcIaFFQp() z=QM-M5a^H}H&bI$M>@m&vJel4P84dBFb|odI&PO9jmy_6-`CgkZSP63U;_=Q1Ct$l$8x8Rp#E`@!u~A+?|v&i zMQuY}YCBiBb4Qw3W)FCTGH(%%I84@!+;Qwl_G$Icg!XQ}da16pC;fDbFX}#joAfty z+8{9#_Yz}67J#j>Zad-fDdURGJxE-@E?MaVJu6ipGCsEE+M0+f8`+MqX@|h67ipQL zxz<4|=aH4*yROU1rW<$0!~941Y063wtdDpcU34$H*&uJ1pHHzgx7LF8L8F@E9)_+C zOFFB@N(8!-T(plsW_X!YUDVXm8K`2hD@I8rFo_AuFgct~?vV?k< zzOF&^ublx$(-}iYJ;wI#%FA%h6G@VlEstmRyef|a<~O*bK3I3oCD%^(57WSfw|o2i z+2fJ3D%_G~X3KMo6X&?ZlzolMnda8ft{~ z0fAskpA&KAWCrqfG`32f=bbi*3FC;E7dH}tb+u+DJG-aoOS?*423a)X9eluZH?kPl zc>;@PR(0+#OkP|*m`yVvFBvDV;z)Z<=!wxsr;(%VfB8f{_5COcR|QCLL%9(DVL8r| z^488`$*Dw?JWezho1&cFn)ZEbAGFhk976;7S1$F8)YbQ@&vMR-EwYmKNF5U`A_NGd zR}8p5MRXl;nK=qqIzjoc*G7cH-Le8qWa;vCgvUdViw)OS-ukjWD5f}DdVa{mqX3$V z1y-A{3vcbUt6mF+Rk94eMii{ogv`1tJ?@awU214K>JZPJb9P*T=a^9s&O@R&+1B=* zp_S*t3Dr$eU@3i1p*aLwLgv&2%Zy$9 zb>0S9b9)u@BLjQ{RDWr$Hh!_a!kkj%HgnUpKP zZUoY5d)mJ<+ej&9aqg4fRSe{}F3Br_kD2amw|TXfCVxyb?{EDkgI7gZ7T>=A{6~-H zbr-k-K5hLwO9%rrHLStuvE^mE2b`5&U)M)Uu?*~}jPKfM*Ky%LDkgS|vCP{r)MdE1E9(D-Ovs$(L^KF179A3e9Om4G*_O02AsRY#9z{(P0eSx@8%_2 z83epLKb3SBkRTY)UqN=17hl8#Kos)~3kN+!SjJC4dr+%Inf3iQTw&B@La5&SJMq*_&6!J79U*Jc{(kn4(NmP~*1r36w;#L^^K-_f zj4xjN&H3T>>3yuSb84M^roAfe5a|b!9G577HcR@k%m}=w>!`QfxISFNk^~;B1aI7o z_i-qMHj5kwUm*-)5XbDlYReTs$29t@u9R4I${^Ok2_N&kJ_+9}G{E^q*QN8mO-G8$dEaP>a?ZpmgrtP68a}eQ%juGT4XV;mPC|_ zcu9;yXl3Lz55Il=alWO|%4zM{CnG7oL`>Z~H`$N?h5$fr(+1c^$qTu#Q7gZDI={ad z*p7P;IN$CPelL#;U8%lgwfaLu+92$c#*IOSR2G~RB;#)?)tS;v0O9H@VKm3<5si?& z#+ys--y}71DEhDE<|3RGaaJ(i`vd~PqfoBHR`%94gdS%2W@Y4mjJ;My%;ysZ@-rajGrW5uc#`eQ86OexSdx zwh68ti8*zEB3K`ATV_1a3 zXJU+~q1=wDRH(u2!`HLfECKFEe$c4XnrDok%IeX7!w|8rM@cx~53uK$sp-Y0qzku{ zZRtkwMJ>i483OCRafC_2lHj{{pK5gHG;osh(E`Of_usFJWO4fqv9RzESaiE{HlIJ6 z+UX7Rk0O#9Z1hovLLG~Ym0Vr9RUNr$JQ-Jja)`8i*Af$DPfx)a!@l-8d9f!+#U^M; ziPi}pfAXEpZ4rzTkgE1{nB{J0yDGIr<3Hf-*1(;=z~}$;Q(C>~-WIO32oB?M-4%Kk zPAAZBzfLM-x&Mgp{`4XEsjRt9EVs;P0h~7brSE1wVcM9eW(2*oC#5oQWUoKEbJ^wa z^7jJX1O8K5+Q+Q{iz+p!o32XFn%JX>51alOgPJ*>`6T_dp(y0wlO*U%@3yy>fX^)N zzQe2g8e_n}@8bF2HSlda*woe<-F@?1*OxbI+x^O|;$JHdyIk_~^Xx8%vg{SGj35R4 z?rh|@ncQ#S&JUPl8~gAKxl??@VTb`Q5AVUEVe79FKF-gZU(ji7P@jimmbC~I*zRT0 zAJYk!uiiGFssheBbNHxI@wZAuk|)K)(yJZS_cxUNR3J(IHdAw%KI_giGu;BxJ8i&9 zA%Zm53srQg;JZ&C(wxZ#0K%=ce;ASf9E<-!SXfPXIOw2w=Dc}$Pxpu~M`Y~xvN2Z+ zo>$uT^k~N}6qDW6$fcQ5eGiOc?Y}O@D?>g~=*U1x&&63yw`S`C8BT|njF!j!eu%w$ z9}?p1IicRK_nQDH4Rn;wsRG=f&SeeZg|wX3y?wD-Qvx%6Y6SajX7!!_tAbG zoE?y!5!=xWWzO(U!gIholMM<>>@#bt;udNG+M;^tTUoFDklB%e=i^u}y|9sQN6ae6 zg&r6=tqGA-2Mc_eXPP0B0lfqFSkl|sYQIHgm&TW&rigVO12ZJV*&UX#O5V3*Jh zN-faplm5IYM(M`~ou}V383IIfM6N!KT`uO-^gk9}hB6|pVBX8FeRpPGB^ig>t}cvb znzp(t@6ESOoc@LfHLqX`OwG7LdU(%}_MNud@(HhdfP>(2`ST^{6i9@~HQb&VzS^Q+h%UQU&W^|AJeOc3jh@9@R7(M-VjET`!+LI9%DRBe*Yt71v@^JTtqjyE0 zz1D@#^B@d=hzt{?aE;;y7c<9&22r}WEqqZE%><4coB6aVI!z^}poPzFVV6RI%zxr; zXBnIku7}U_duHHch)sBrnQt#H8~bWt_~-ksjOf9L$tTOx)GMenEXeBD!Rb6TLX_R! z@;$&O{ra4tQB>iJV&CBE6E|8}KXa=P1CC1aH$|@)x+iK{G)A~qZNzmNr0<|DF6(^e zLzdvJ2m6KzumaVypJ3v5y~L`^FzO?D+vhkV)$g(C-6`Yx`a2)6dc~l5E6pvG8|YiL z9ija2>BUvZS09xC}PeXj+XTLQ(2-GHls zSD-h$@*_bBH&Ad;Dz>-OR+#F6X=+{#vpO8Nj+Mp#&hAbsK z_yBHIGEq{p4x-;!8cgcPNy$s_+N~Yd&*#{Yu zB4_u}pzV=AMCsgrh=9b(&k#Z$kY^64c0d0iYL?`hf8A6Q_S`^Bb0{kEXrvVGf8s_@ zqhZ>Zyp!)P5aLnJGe$X3Tjbd2eObBGbViVWBPt!vO)^!E6u67QFD7YWm&&70e}o!?8L{Fqs?l~J31%AfK8yOf z#hcMH2c1d1!)V4=Z^N9ee>0 z%*u+t6!5^xqe0V|NfVI1`va0NKR0CHyK)n|6#R%xWT4dDb3ICuFJYe`TZI;Cxu zS4{uXKRSQ;otHF^^pPYeU4ZrhSRtUOO~04~g$3vSWq*#9v@`W+cN_2gL&c$PJHS9l&M;bh4SaZnf)&0o+tbDzPk+uFS~aSmx&>;Wp+#Ih)s55ohRB zuKG(#bq$WZFB&{VVqT-0ML;3jYQ9^J`c&%NXBr^uc#DWrCpz^dv6waI*gp>ctmuTP zf5%?pJ zWOPA4*kV)5V*e%eN5Jub5GaaPBleU)SySql{k0$f;UTxlU!nxHDCa)2+JxlT1PxuI z8?#dt>gXqW5gnpPWSx^M^e@jriiXD6sh96S=EI1o+w9I$!fZtXvGdQgC)Gn^RzvE! zhmG>$4)VcGt%g5$%s}%J$%oVvn;??oP)6awMBj(NArVLlNb79b$=5{drB!6-^!*+X zZVr8LBJ*Q6R?+^~!yl6qGd5JuUJNxHmi^YEFTIq-K7wtLz`dV|+kUhpb4RX-;vplu zwstNPRR+yWbrfA0n&ueaw8+-Ej80s|!2U>@_wU3LLw4LF)Az-0vBpi&^-AkB=`Ox` z*8)EMa_%CsG&}VjCE@C&3aRQ0(AZZpee4c5(it71N?rmtm zWG4{SY@MF*;jpAB#JD9oG8L#`7uyap9-`tu9E0B7JV!H~g#x(G_gcLNmu0w)`b}1a z?2l2}!!=y3564;HK71o5$|L%gsx^{?9rN2~CI|3YtWsx51-0lRHYpU?{j}6o$`sdF zKf`%ecYpA3O6q!Bz>5A9)y7Er1~ZY|MYqI^y<+Iqyd zyop6qLqC4R_GOE<%G1Z8!fhOOWefSRlyz=aim_%x@sPq&gXcYm>8C%F&jTJAdJXql9^{0(}R*6f?l+; z`i1~+?&YK;gHB3q7r_&^%MOrj#dxZZw4O~Bj2|Kg{3p&X7zj_62eaD>3zuu;+zsjk zy#VKBj5lDp1MYb4xX9%nG5as^1zwm0i72e%qc?ypTFD8XFp+z@2Q^R@Vr>)RLDJ)h zHdbzI1ZwAkFX)+%jNQ7PN_pgxN?22yjz5Pv*KcacJ6;U9zyKfJrFqIS(B#h(uFArC z#c+c{`JU%~$38I)&^p76+#+eqtVZ{C6VhE*o-+oEX{EG0zH?mZjo>l z>v);ZWi;FEuEbsxEFa}eh1Anb$61wDt76^VUodQGSDWm?`%ohj9_&hG%~s*9kxQ}b z$8hny53kY&2;ZN>=+dkqW{zIX@4qUjUUDbRmmN@KyZQ?#nFEXb6@vB#<~1V;jgXf5 zB!D%pj`edXE$Hyac}hj-cP{P*G?DE;1!^R$VADoy1KlsHt0MSLzaD|P`=oh%UN#I{ z8nLLd&4I%tt6AFaACnSyeg=)pXc^~G{8l@}QGTVxzMFOlI+YTZjFLGPZ_M^#GQNqZFfSV4XqzC1eBFfB6< zbI}VQt8>~CNiJtzdW}#m73e+_-koBG^TKkbjr#5Fp2Rts+Ruz*-03|c(=4J~to+tO zM~1zS;CdWw6b_T_=w=?Nk}9&Z*%VB0aL4jJ-iyiAvvMmYjwL0b$RVrnju}G@ip&+B z&mDWtonXmg^Ja4PCeMrO-OcAk<`VkPij3VGMU~aNxM_V_RrLgSwc=I1qCOTlvbCeU zqKpem;<%8xAD0yD^z(FzLQq@?GmhwCbLF>Ob%=K`-AWk_p~_~}l5PMg`$8=5=s>+f zNrovI>UvRW|GY%%Rv||o+?OQGoGn&+a+&3B)BQ~^LpI>L-4y!H(w5X9p+)RiZpSy0 zdX>BOqt%R0Z}YnFNojW0)V5B?+$mb3K=q&}BeLKa&V#wR1MtJfo>M%BQ!TUaYkKVf zYA0e||FRFx9}`&7F5(vsABQ&JFIyWdpg%0`lx%39-ouXb#3rbQ^lZDFZThM*XEnZ9 zUSLKrKFw;XNbEdVO#npzGGQE3iHA9I$;|8tXUc8)zCgltQMe!Vrj}b+DfH6^=V!bE z?22AZk@9DBfCk9k%RJdvZVf=;_p(PNb>fhryvx6%G}QO_A@@Rhv@$`#6g%56oPizN z^@3rRKAmq~{jnK#wUHRn(i{AXz3P2k`;zyAJ$Ofo5Pz{2?ZTV&6_ka7WXL}anPjH*$ZLdp0KzEIu zYa3P9<(9Xs@v>0<+CkY%EmnelKK__9yud*2`Dh1d;Z?&CTL@I$q>r)FP9)g&L)Sfe z$}BPzeZzZyyf(nKFoOAH?HHM!Hf60@%%t(uJJdzxFD4bU2RW<&`3I}eSt1=*>bh(d zi8o;LU}4fkzvDv|?A-$TP}e7T8v_F|_>2pdCQwQ2pJ(o?lOg`VW!q(K%S&x7ga4se0bs)$YR`;LIICQ`;@ghjn%| zu-@Yv#EVZ?L=MuGY~mfL3A+l&Hm=KFP$BMIj527Lq9X2E%VxPa2);gFd;Bi zHTaOLeD(YD)IUURNKG$^2UdigyOG#ig}+IE(^2d6>Qsz@UyKX%fhO&tT-C;m%c4zs zdFhGAm0Pb$v^KkiE?{baST*tgs{8my1;S||MMPbnkL4vCkuBN{0drp9loSqe=ZS66 zHGo85`)%N12w}t9YTi4r58bB`&*ag}u{=lO5SGAG_4hMxkJ8`mQX?(1CMLeDOmzf~ z+berkV5@av2*#68AX|wI!Jubi?c~t&c=I-E z!V$?KC*lDxJw_V>Y&TfgFm={5bIJQLYcxQ+0-ko%8pb&8=3Il^A0qdp!StmY$t)L$ zc+H&}g6kSystD0h2mw}PE}EMuN$GYP`m#)p-3J(KvL)0J^9Z>b@RRva1gm39kRDsT z{LT@0$qiWd$Oz9WBZE+@(ydo3)-gW)ZE8i{)ohho7^*|@@d8^jN$VS>1&f^Wxjk#<_2D{u+xU-r@)@Gk8X??;vhr_& zNx0&(VY-_F3H5amR|uod=U}E{ALCIN@NL{PLRvV)LCPa&npm-pwug?1RX2%{Q#J)n zvwo|E^FW8L#;9^wBdYHc-=!_F#{di?p+8n$)>Gw}zWB}gJZW{0H?RIj!(qb!Guvhm>+jQDlD&-he?eRcymcqkRAg)PgTG`DL@hyc~_BNI!NG_j3EM&@>p zLWX_)j=;Col^q#bd4Gdz2u!at_79QXB!IPbrb$${Awnm`wPFPtvxV9nDev!ig`+#pM#ugw+w;-wBew#NNjTPKv_{tVcU4?ur_X3bjZi#^QuJ z_(t(FyCdAT!Cl1)IVKgE!a_x@GohAcYg72nTyf?W%Wa&xP)t+Ir`1tw4<+WGTioM9 zz8b!i+LdEG$+o8>B?Z3CfT8bT-yO%s;5Wa|i06mQL5@nczOe>b^E^R-vald3P1<-- zo$xavO-^U!&_DeLFpzt|^DdB02`#%&TCQB}KV zLV$3`H~9S4e>sIYuKyqch|s18d>YbHOnCDlh9&sD)$yvt?#|5n{*69Ry$;keaw{dMyHx8BZR*Tzxj8hxJe);lEItTw*FZ{V`W~Qr~F|3=Fo*C zl5Y*6->VYz_Cv(n{g5ZR%Q6UUIihO_=@9M%o)gP4;`=(tK%4|Gf}fq!Hh&Fj^1*0= zk%CpAO`iOFq|hqfw?mstF4k~u=STm|m&y7yzlk4e9(4m&8s+dXao4)mt9G(@YqXoA z?sN%%#vAqDg~b=y-#ttyTaWGWTO-)q3qHO+Y>CBl-9onzpfpm}w|4y>8ra$74&kwt z2`P@x74GpBWA`kBkq;bq`IrwQa9lDU3Zj#gIDoV|6mOqND4E-pEHx(q7S%fc^O)c8 zzQJ(l0|a1$ByiZN>cn)Fe~T+0H8VA>QgzUgnnsR%=EHg6Glb_Oj30~8mZJ5U>eGL1 zzMXs8>^}0{ZfxqG>1YJJcz6n2+2TuBg6cwQMx!r#KjLO*u-F*n;S&C^alA+Sfio|+UTtMg#}>I=;O zhP)^|Gbo^^2KeyhVf1MGoOH!Kn};Q6aiNA1rq(`*>a1g?^UYI^rsb_@m-pzTD+_+&{OyUM(Bf*O1{kBHNHJE9Eq9gc<<1EtCUtB@83kd z^`)sFQn;x+y;I%y+mC{wDLCu1v@{yDkmARZNVjRsHwH7o>TJ!4fsdyk-%-eglqSw< z9dU|yvTH@H?Apkh;sQi!o$A80*T$}zwWR^;{&GNw3o@7l* z8V!lraob@j25(6D_+DP$xKfG(!^#hX$&*+LdFQ(!I}EtjA=}=D1L_2=gzbwI6i@<# z9WSM%z_DSB&h2uA&ec^f-@S-L6(8a~h`{sdRq>7Zm;(zXexT3Ko4g4$dA$}GbvM^d zu8dE9a%FyZe+!A=>*m9<#h(5pk&pj!CI1ddY5I+iM_Rzx)elbc!+f-@>ilO{cWl|{ zgINczM}UG-K2g%axu5qHthz`wI=qSBjp5`du2{a{J`pj(8Z7eNvv$az$GWS;qY|vN ztF?f^?iza)$kde}h~R_)Td6vRN^K}RDzE&CB_dk2VOZoLi(?m#yQfF=YlNMchPq=k zdU}>bP(zgK#9^{}@ePPZ`mwyV-|gWYvrD5T|40FuE1IBPmLZ12q%()fn@e)33oJq7 zG*gwm5X+L6JOOQiq>Nw6lOx|d$@#W>C01^a{zk<=SXNR+&p+xp9lD%X9<>wl<|x^* z%c=wtZaT?0sI@45lblDMj$l=RZbNWKJk9WwjoWAr*zR5cRmVEfFP1h6v18$r$G@Up zbCTtJyyHX;q@G**ydPa3F+F&ZC~jmV)GM8Vsd^*hse6Q9`t)}9%eG1Q!5P{-QPaf% z*|>=YCOGSoeEpf2U0^IXGRgcUdW=I45|+n9rOEp_hI!56TP$W@q`TEGx)BbTv@S!A zinzsN7xj6msYe;?B(mplo|l%`{f?<;Q--(AGYkfD*`k{b`dy`7x`B9oYvIJ(-76#N zdc&bmtkP=ehhzJW%;%B4-rizP*fDah@>^ay5tbvtyq;}nrMG&-m_6l9DF+- z0cAjB`G{0TRU6F&_nbt~EcgkpjV(Q^yW@I)FX7`KBF&-iuOnl}7gRk8C`#P#_GQK9?;L;)Gwb!cz< z@Xbk1f}2m6RpAp(o>^*UJisKhY`3N*#cUhCAus=RXRlzat?U3!21z909n?yWbnO1Qdt!_#gE9w4r9j?CAAf{PNZ%vW-{GX z+HrD!sD3K4w^ZtPBjErK;j&s>R2{kYD%79y}C*kiH>_DFa(E(vZG(DiyS zSISxCu=8A~N%t6U?fh`n%$>nlRna|O3Z(xc^0iW;3)9bZ{tSWq_g)OHsse`DFZ`7| zxHOu^Mi7os&x87r;k@%lA!^yU5TmThHNjOX2ZT_^gQ?uy=~o3qDO6mQ-UdvU46BG@ zmh!oH7AMu8zTV?TFQ`SBzy1>5WUv~y@d@&@0ov6t!q&^#y$8MW7e0GFAgT|WgEzTx z>L@?tmq;L}dRZS%Z4d_DlV8pa+L}?)Ued2+03c_b(pL!mr$8PKk#2yO_J&UJE5u(< z!W|fpmQ%?M{-94(L4x|vr}_WuX#@$X3wU)S*I%UjgMRHjlvTn%vDZHX48m<1l>WwH zOG0$asIQxrbOJsKt~OUP(-Jw3tJ?aBvT|8@ibPQWhRr3+s8z&qWgDH72b22i;ZRrD zRM97LZ{)~s;_Q7%kufA?l|ihp&nZj9HS#x2?7vcpvObenY8Lz>?Y_0TtAu#iV|XVT^mJ#EX838{A0iK2zv0Oq%(LKyJ@3baiE5TO zzr-(#Q@XM?YHG(QJg_;{nwC`;{-Uw>+2{E6TpMPAkz<@cC}kOIN?!`JLN5uoB^oHX zesi;?P+c{2r9O@Ye8gv9Kg(hU0fU5n#5Df3wC`9L<$?c~b8SE{A}0{0omFBRZ9r^g z&2XBTsl28;({QuSKMtfmQn69`&VrQur&>HMy`nH@uSYj0`&OF2lu0X+hNm>7wWx#V z=)fUZ&m$AW8ZA>&!0UBW;M4F~^vX1n;(3PoAHZNvuN)GRk9m1Cy}E zI59w*{;LpK5jQJBpe^~!m+^6AdyGMxH`vsAWaw{xC3j4F0+{5tF7wLU1BTaES?bO9 zB>Vt+jSQzadII}lWZJQV2?VhMuspfj|KjXDqnhg8Zf~pzs91<}q5{$c1nDgz(#1#( zJt`dp1f+!$l_p)f)JQKeM0yA5(xvwjkX}O#A<6x2@Bj0h^Ne%8obi5u&7cf27@M`% zy5^j}2_pICw$CwIkDcsQBvCGiH4^lq=Nhf&wgwNzs&KPPtp}%`mD@}dW@_GfC8LDH z^w~7VS9{Ws?4C3IbOm`UB8Zq=@4D}RTP1S65LcqpkF_iX!C-JgDb2RhTy~E z)KBLPAts$?Jr*>&4i{u^_%;)MMH-^p;yLojDF8J+ z_wk}7!a(^r(W3WDM85kWc0>3&$vx3|Yd`8GU!y6r^ozuSiOWa zJER$57DW@XeH{{}iyEq2ioEx-AS_Il_h-I#n)_l?UcP}l`^t{D&21(QG0fRc5l{X zait7d^UA71iQL@h3af3{$yqLTviyqL6%pSV{AJ%`T&jteUN*ittvh!l9BO<$^^5bx zen{}WlmiH>*Phpu?RT+0(Z`(ZpFE!op{yV+0-sv7?su{zc}US_bD=bju$Ks0a?NB|N zGb$|eQQT^)YgzdF==~m}MPQt5Rq(#64nApvI1c_7~ z<$pYrjqCR@^4Yj?1X!BxCz}~(U#LIHhPwE=>{YEoF^6URWE2cd-w&@x0Q;j?2aJSJs2+?DeXH~2?U(onK5rNIWy3g1O>n!jS$3>{J#6H)l!Ivd zCX1HP{_w&0j;aKY!q3<56Q0dmVVCn4UHI^HD%NzXYE9c>HlPw`@7Kk~wVhm&Ummsc zT%|9$T)WHWdu7O zK0X4>FUP(_YYQvg6+R~Z+0IaV5> zqkM`}88XqUZe9eP^^y7hp}N_~Wrw6YRJJ?cbSPIP8NKx_dC{gc8`}2&J@Doq8*`oi5vUc z-r|^!!uK<&7{wFtPYzU&dkjf@Ok#oS3Z!lYc?38dkW;DcC#B#LIxPjE?vh#=`y<5aK$ZOXox`n-j>WEH zQ$;SpwGCw(g3WPZFm6zsVLuuv{tmL6Ndavc(?^McSxor9e`&aKEs~QDq~2QBJUQEP7o|CfC@WmHbjQ_RESW9L_7uHB3HqPl0SC4*g}Pis8&IKI2+ zS>Z1Q8eLux`G?B#w(0Y6(V5D1OW% z5bxABCcpSnlROGtx{~zyo6U&@u+PQo|Cx8QR3gX38IBmlwCY4Fx{0JRpuDG~e^HH|YU1LD_km{E;d9_Ab2CQQP z#-j=%MoI}K6|uNFF%&;A4|Qd!YU^{>>CV}-W2P{v(65^2isu-17=4O%GoNLvx~7T? zn$O5@vye)C-0`5uU^&_rPzUhbDT^k_bUmCJt7z%2JbgZQHH$S*lzqNLiNL!Lcd<@P z-aS?pxXl$qgk#N%-5%Z7Uxm3A^wlfW-Yl@MPL<@OsJ}4kBH1O3v)w;?zPD+kn;385 ztn-JMQ@Yo5_jpsEIh-w4{Uj%=&f-cdPBjR2)1aRje#+4z~`v7HmZq;(9OhJnB@*V39p)=dp+775!4SrxBLGUKXns=-HRT?==1Wy@u& z93M1Xy`vf0$+fi8Sx1%|NLsuu(X-FBj-Au14E0?1?;)ywo9QjXUwv%Ss3}q!h0aVKG z^M7FiqEISYV)(H)Ikh)OvH6A^&TmZBth{{8e=pCd_gG1YH4P2IubF3yj+ z6I5EcMiW2B^QmEe^%Cyd|E*J?G=?2&|!#e ziO!|v#mrwLSZkRpJ_O7b8PJo4AcT>>S!kcg%@&+R9}mI1@mB}NP&*)PF2Gk7S0kRR zRLy6fpGZ0RfmN=ojOqu4aa{>}M3q}r6*UG5M5A z4sBoJ2}_s@&-y!({JHS&GwGlya-LNT`bpuopRTTp{NbdgpuEXybsUj*$Nr>!KHQk6 zxrutlp|$3CHhm)dM)gIlM4oEg0;C#~>u;k85EPnh2V2cet)Q03(y=jCO_M@If9 z0AA0Nk;aiulk=i7GuKGB#!c6_QYG~&ONsq`0anixYuYeTH*-6z!_X#-J5=C2Dh7hl zT!h}}`aZ+()L@dnyRmVl1bvzvQC(?NK1X+XTSc~M1-U%kxH@4)04e%tpl*}S1Fo0u z0f0SU4GBly5t|Qc1pA;vjGX^mG%*f1kVT;EH(GEG77nWPA%NtQrQ-HCz4M|A)F|rv zX1Ecw=Ezw(P}G}aGPN3utoK7N3@~_Qzr+VuxD?sDRkV-v#Tp)R1We`PLn6e5*&M1^ ziVJ16HLf*t7hB(969(<(@#{|*Q{XHeB*kJj}P-jmuG&GuM#=OKbkUj4oq_U zgV!DtqFWg~8KzUVZOFDjbpht#$kDN?$%qMi>I06$(^QX!u?sRWZ z`PA_a2~x`TojP?=E=|l`V7muI4|j6DC9Z>oi?9o_^Ol?cxw1;+93f%4hv&uOy^?*wp{O{M+mQe)U?@LXS7rr?G=mD(2J=}Q0h*#LY zPWpFDDd7F$ZA~)xS7OW@oFu8>%~AP&pQhVVzTbJ`cn3eHc7y)Oy{u-k4y=)VwAE}$|R?y+(+w(Rkc86)%7vrYRxJ8i*{{>Yn&76BnM0h z!6(yrAyxNr)P9Nm=@y(}nP9Mp<@wXp-&q%g>viJhlU4R^+OJunVO5(@wpIvxY@FzS zdvtg2^^dQGlm}+nM_AX2p=}J~o#U7`$mA3L#pz$OKLnOb*qj9mv^7WP_Y6n_S(z=s z5|cD)0-RlImd22@M?MkEbF5Y;j-7{?X-J^K;KD3i{oW4e%WUF!78&I{hwM%h{C%i1 zdhj*sVK3TIH^H0xv;pcLeRcV;D&+A2@{emGlKzlY4w>b>CHqU$V6-^N!Sp9H$ueGeuBcbF|Xu&~-x$8Kk8;$SF%dVKb?0y)mUl$!RpK zjvc!7=o!S9B9G3SlF?b3s^PP+Qqg#)K|!R8KXO5Hs7qQ5ED_$v{ORapl{Dh=u!dl4 zrwD>W++mvQ&p9bZEp_LJX|WDJrVq2(%T8hL&rewOjdg+Aq^JyNVBRhh(;mT}cS-MF zGGkVqC4I|x)!g~}dHykY-rkcwp$h&>3Xfody^;$Q_f$0>+ zK#{jy`qAgsos(N98NtaONGezzKg{=M%8qNdwtX;orul0>FoYP<-j2OsYD!; zQzcnU_0u0~p$tYaZyl3-Pei|qV9_E}NSPDVXK-0Z3=T}6fuHS zh5)92>|4ZppcjBDL&SiSogct9MSb9o&<_MLyvf&~O1ShqJ69z;SEIr9yz;hASR`Tu z{e&K<&%UHS^?^a}Q%d=+29^F%ewZx-@xScxQaXY%z|lXK@}BB_&VPx(d@V6Rr@_Db zFJK-3fcl@zZg|(}U7P#BG)i|^XrARC54hxS>21H1r-IpIxea5{U4MP*rTT^Zf7J!! zd_mLHT;0UKY^0T4*n=WB&u_Gk_4$gnX6@tug&jc<4Z?_AKvU>TDKPcK(A166oc+H1 zes&{pG*c3hDNbcGU^G0I(5cZ6NDwvvJn00(8g-N|_3i3uQN$?19{47J-meYF5pxBA ziji9st6zg)$>%{(VR#T2ZlkycgV+yuEnZe=@`%&9f4h>AZJnPInbbff@pbfm+fd~V zC-FhM6on*fv_z(WS=We3YYXK;W5B~-ZdYf4r|+;6r1ubxJmu)1=IgK)KDjYmH@z$J z9&_i+_^Yyw(*eg8bvGbLY%}755;Hz68Pymux&1*qDjvyid~bYI9d+|kporlUDLST= z5+`S#ddJ~jz?PjVe#W8uQ_5Go$O0_aL|=ym<`bGd1Sow-Ii5ZP9x_Wox~z#3>Qn~r z?LW+h(GA{x$#_ugqm4h#bWivoScEL=@ptbXgy#>b|Hj+!6qoN5V@vEvGL63VM} zJ=bm*SzPwPXFv2)}4N%)*_pIAq#30P?@<8BH5Qb9)d>$?;#InlG5#^MLTs6x|q zNlh2K$BF>p@)qhhG3@9cs!N3RdPQ)Yr_=8lUSN!cKC2@60MReGdgZ;xqPQTrPA=!0 zLB@b7NBD025FwUgi#`c6P8TU?9KlahQ!ni z$sCew;&XXYqYe;2mO6!`yAwS^t#a?0*n;R!N)jQF?*Wc=v@m^d!+7=g&etr7Zy2uU z;Nff3^!U6B5ql2IiDN6#hTFW2L(xz(-L=U@gX0*FuNC4IBZ=5}IZyMBnpw>bV{25* zs`oxUE*v#h-RHd6+F5gV()sXot}*=fmsYt}=%w(id=2|Pbs$_-9QpR>nX-n$(UwmF zX2?vnhF*TWy3k=cfq+6AZSZ+J$Yr>q8U$`JA#M(XcK)7nxeNahz8X{+#I!OHT z5xBeQ14(BOF0v5yc3k*H@ui)U1c5`8*D*ufkNjcV(@^7}f*7SAgRE^Om zEiP)M#yPnAwrX;FQ=;*6?^(cXyh*$MC$_2QVM{sMz{QV#rTf4w0j1c-BhIQmmSxBP zAhufX`9s44KHmWZdPRFhcbPproLi$*9~74>qxtcw)x=?ei&*Z{y!$zJIxqmbx-;pt z^fIi2lM7RRE~DalN-Z|D$=kjw-)?sI!J6tBXA`i4e_LDbN&KY#4rLeZA-HwW)_JzO z7I1_)i+s9**MkZzP+zI%CDLvtvcC*-Ge02FuSIbzkgi{+_4-w;k`DIv$?V(i_kbua0NzNptb;7%tFm$bt3-07$Rs z9LJE8IO|J~)X{T-&4&j}ACOnaRTu%0b=nZ&WUyT|UkZ7Ojci%CpI}rV6izvp&C||T zwr_|3NErzP#+5;hyynMcAN&Q)$fzw$fk}ZMvRy_ZoV*sRh^c1B3u;CC50&_H zA~G@(HnkUgpErdY2n_9#qD8TczoYloyNCepa&ge1k#{8Z?KSrY$klkr2yG30V7*xp z5@WZd3(#a&r-{~$pbfl~B3fV9s*}?%G{neysA$kJYbsvgCdAt(A`o zVG0|Yx~k<;w&E$(CEpLh_{2-`&|GuSk8gO`)QjJA@pu4l$xFh_pMvG5N%xw*2Dl-w z`qwE*QxeK-_Cj8SUk0?Zfh^o5k4CW+=PLx2-L^+lT^J+dFWe^QYO)8OF6^Us;qn`( z^2UmHZFaTt6{W{^;TrRKmwe*A9Qax{*5RX7#EE@=m&;ZrP&?;mNu=A;hk&DcEyd%i zv9HtoToM52b5uQVQarI_m^7$&4*tL%a$C*^`!HfEXtZ96EByV90`SXoKxhj{IWxNp z8qe#GIJ-NfRu2Z!If@1Sl)6?IM}XA?=LhC{y^hzfTCU8fl=FRt7Z-e}6xZZK$uEI# z+?g^F@$U%Cne9Xu^%h#PKlyNz@H- zlV~O-oZ+&MpU~9B^hMoh>1nyD0;UC6U&1*0P`X@okn(_B1<-yqS8GyWqLQrBc5e|@ zAHO>wrAJml7skm}+jWdhiJ zahLW18aJymuhSHP%w2bqt9k9TIe;vFZ0`8Bl}6DVqv>GN7(GyhE|qy5g3+G3*_d>6 zxVtZZfAX?L$-3zg{HgmxOUs2Rkn!2f_|y$g;uvK_4@Z zQhH9x#s~kppic#&tFyev#25DV$?ZH=Rji>d`(JJ^oakJ1zRer{{A}#F)MbVE*ava_ zXp_P}STCCLblxleyNuX{6N4cUHNx8Y>v@g6q#VM$L0JHFq*!pfc!yElDPNr|;xGzfZ(J&Ku5h+)p&-(l;<-RP8=gB2|TZIQBzLKsFN~yP~BHh+#c| zMYfm#Ia5@^cq2T%&za7ivxqyQt|mK79;ILJX&bv|Nju3LWw{~We2DFzu#TP6OXRWr zqm*DJb$5IOUIw%jM{n~EtBhK;^|X|MN07!qFj`DD{qiYhhjEsRoedH8?fc*lD{e!! zPcp#bb<_5dS2)y`i%RYCo48uk9+s)TJh5ZL#5>8dq;iZQqgEsjD2G(sLw)YRP{&BO zk656NJ28g%JF&u!y@S#7K&*}Ibupm-m)EEh(V+@kC$l z^kQcoBc_rFC*~8ZE|y0$Jl|xpF`#+eFh%5hLa}Qj@2I6ifE}x2r0PJ_>QK!_MPc8n zJtO_bO3`?x3hfPbR{55&lju*tLbY|Y%`fO?u9C1_-rgAwLEUyfrq3I0%@R363+#`LpIhw;SyaJ~r>Xagm2?Sp zxl=nPYPt2V=XbE1=F0Bg@`oKJp&54c1|D4n=#8~M?=3K}UdkVT?Z~AFD}%9Hv~+c& zz*J_zgP7EgF+UJ^TVj;&nC<3oU86~UbEfAy?&;c(oVJMWE~pP@>UpHStIs|9IyzIx z4?UY1kPjt1qBKAQI#<2YRI0nTi~H73kUxcnY}g&{o4rxNG4O2a{i#WW*KawDMBQ=r zqmM(Uy$t^H0{*d%drQP`{jy(CPD;1%m7s8XtT6swU~UWy$pv&(_d4>6f8FXIQZFMZdXYAz zM}oxrBrV^+Y#nRY(#@piQwTNfK_mQ=+=`x;n6wSavH|C}4Rdw^qwIE)ezjo;Tu4C+ z5gdS%f7}{#sjO1p*NxM)6OT>oaJj<~=90M!`AK%*+M5^YsL%zU6?mM%J)y~~{xk&9 zAE%zio#t6H?j$Wldqcg)kDQlToh%Xj1wTOsXF%~o^8xpzrrP?Hy(ioSL%G}q7hOqSB`kfZ9n2n8k{ z4X-$+`W4$O${ro%Q~Kx2ifm(=7ooSNLz-SU0$+%^vDGW@u+BoFj;QXLIKQ*=?5+7*{7Hoe6Lsw$iMJWQyE0~c=%cw^xMm(RT!SO&kR&wIcU4I53n_gCyPJ&CUO&L&ChVNO1a z_as!7R6Nh{w__z}Q+x1y5P+JFZTU)O&)L_e_j(xnrD=(s+)Cr;WlJHol5-)pn*UHm zDF`TNsypIR8Lfu5rX!9;t0@Qm0nx@(tNxO{wqyPhUM-FmIu_T`yra6CP57KSye^DJ z>-eM`>HT5tak(I*W(7i2bi)U;)H1_;S5X5P+AScWNNTkK@3U8Sxtqw57q$;VBW z4AdOwZ`X4Zlul%6^{_=L{v<;1vDboTu3echF=oo{9EEdK)u{pD7pMAyTH}90lT=<6 zsY{*za7+CT)8x!HAnlE(6SCVPi+W!NCRG0Yi?ft04%}v4b z5&z^SE^wb!;MM)G+{>p#Ff8enUy6Pa2I2iTEfEQR!k}&1)CT#?V$+JcK2T(@^RfI5 zuiJsz><3T-El5P%LM6gGm&Y?!fd_|+>_mDDRSO)ZU= z@Z(Vxkk1@V($@)tLetcQgfJJHZ!hsxu78rY4NYLTNxOd#6i^v(PNPYIEk z1!zIfrp=~8&>Fl7GpeSt92)1rTeN}q!by+u5`|4YK0Y*IlG#A0xDZ5I)kwwYh>dOM zo}}5VrAu)t9Ul$#MkBSy8gx#V}G6+rF*?1tU5rE?_7 z72lu85bYcpy7lr9M%wY?07lAsN3pI)$YqO=GJ;K(@lv0WP%0$_0u(2m$TU8BM#wb?LzhvDtJ&9TsGB0sYMD?LfZB|3}z9LH)wbuphi z)JYxv{F{VJioX12zq{4%UA?7|$hW$LsEuUDCG+qU*FR^#KcdV^g1Y?VAd~Xj!0DN{5SfJ@`hg(U+WPm5L&5q%}$K9VH)`o(~)#8 ziFf)5o#sFTkA}y_r{HbKpP}vC?YXea52)Q#mXG?_e6*`+so>wl+}2fgEz}2c?=ohr zM9JGppzI;S-Cxg5Z>lcXu8zgwzg;5n0?jASts{JNZ}{uYzfJL6QUOf#ZI;rjMW9JHLzX_#nMP1e34A#vmL~3bzOWbxSj#qTY6XsBu$N>ZlbB%*#}@V zDe-jp8K<2l#ElP7nDF~@-QLBFn;_2aoiUW~0eye^>5xA|#R1RnaP??=Q|ck-Oa z-g~>pt8HlMbULN{j&ZFuCSNr12MIlfv=_c9k-9J~&(8xigmexBbVXiPBi@1mpu$OA z#T&N7{vX|*rq3(a=C{6ekxdSZ!NITRR6j6f&?FGzjA-8y&f@4V)|4{Z{1X*&y|K&_#5x|M}6lCtj4IH{pu0zk@|g`wxq(^uN3i8t@5|WxVs8{A z|J)4Fdt;uyQS0<&xfJSVuxL#A)V+7J=UopyGrXyg;BOU~2)VIYJy8aT4_`0_KqIg+ zVl~kip!5g~6+HtQg#YFn8vdK)1LzpPF?vDvr2qNp2Hx|%f5Q?0;b$TdkT-xR~+l?aL17sm;+;}Xia4xi)m~Oy!&5z#gm-;m;W|3 z|JTI(9NTQst2&jhmD}vAz zk!JY;29Sz7Iib?}t9HLd7;FZ!L(+))=c^ym^mK=?-1gKed8w|YAw9(AsGCLD)N`^{DPrve1l z8Pk%qLL4P zfc2z7XBGU_Akd5W8l6ew9#ZtM?aJYscxfHY%8+7hQ}*bni(hHHqL6iWn=#XHkbp&B zc=YbQK93?Hjl-$feH#oE{4}q3KC4ja`{clomG0V%e!II%!o84^@43vX?>$vq5=%UR zqV2-}doPf$%G!&&X*6@F&n!N)u5h8gVd{ius|4Zh++9*=oDTA?yUoYD({H6{O?5Ty zH|^{YiLqeA&>C9y3>o&KDZ#TA7W`K1%hi{`aTEkZ(70mJpm%O0sV^)lXc?HA9u{AIJNF5fjk4E#|aRW8BmM+L=>W?fu>X1DAU~N04MQH>gr)j0Y8>MPkNuZp82peEuc8;8l{Fwo2vUeFa3$51N|YyXvD~v zoO0gUjbw4U2}juA^a@0AWPI;fH+&IJPxv%ptC1)aSN?6-cYZeBe*~ULlxj#`A1PEG zI*yIi-tmnqoVTZO5o{Pc^X7bmy)Kc!S@M135EYhj|9AcC0#%oMV@>vM-%>LP291VB zI2^HPQ5B^SK2V4~oPUV7p!wX*yNJf|KyPyI>JIWY;XQmX!j3~W%ih6$L79>)uE)`} z)4Ryr?wiwHJjzQWqh$Hw!_=I*(mEfLU#C$3F&~%_!*kV@eTCdRCyQNPcv)t@h>v^0 zXTH8R3?yDYss0)tz$b7coMXI^sZ!A#gt&I&*=fKHTx2@eiTZMrj@x1ykKEF5#aZDyii?*f9l~*WSnj0?jfO-w)f=p zgF1Be+(11-o6ZODm?fQOdnGU(%&xA<#_g#ki!=m>vgh`K$@FA|;4L*sW4?G*7U_1V zsk%3()MiQ4CBI7TpUD&#>%IOoWJ-Q*qx#vvpX5XH_PqRHl&D|CwotEEw&JH1{r%!S zm>1i%Pbfg}g&k$zFOw1RoRgGbUOoZ6gX>T}3(m!d(ATlb`HA zFYLXf#)=c6;S-&4d;N?;I;$9+!T6?R#Rv1~B;gHzhfZ2UIX1?r0zh`du3C%;I$8{W z$5jS8Msd?ZIcKtVC$tgZ&TH?RT>@m;qS+j*r$A+)C0qdyRe|vC=D1QdFV~(xuQ+SS=us$GTC}Ue zKlvwC>71e-dO$F{kVt*`wS1naS7PHOt4%?O0C`n&VOu^?vMF^X7MegqS=*)f31p_& zZsY8%Ud0r2Sv2=-6KU8I6)i6tmjb#`|SO9iepC_fYnS;^WQs6QwZ`v~B1HbSQrQ-AyZ?PnS z#BF6=j3JP%1j?Q5+-}w20_tT!DN{ zG+|7>s`V^r6i{7fTXX8WYR4Aeruqa-&`@6xM=c^RZ&2uKZ`da~U*0`(jZTrKF8Z-B zE+?YLucaF?I)@$@Zc48dOJIqKejF84=+8+=d86qd`6OdwLL7@jMsYmeOCZ4{QbrCg zzWwUN>g&9v{4O456iPHYQopMyulTgJaJ|%buh=(V1 zr&d93^rNHD-gRjFe0LSZn%(=}h`Zmt>1#5AZAv59tC0H;{ywYgxrSD1&BfHv5n%-| zp>d8lO?LcV_nRa3-iAV;3tYZg>Z`D0u=AXU!#*-|$Hkqd$;#|)F>0j=kcqb|7JS0t zx9rRxhB9yM;O^-DSc`q2vAU51upz|{xc$G{Pgw`y(YTq!GO+CPku0z%Dua>jlRUF= zBQ>FLFT|Xni4o5$yr5~h<=JPt~VTyhX{T`2bL4*EJ4TC!^n|J~?|mDmLAt4m)e@IiLa(mD!-? zSgWIVVmwc4OB=&ZBI`PfphbQjGAQKKnZz{lvw~Od@K(kQc(R zX0Ucg>G!BmbKWw=z!2?p#x=IZ8e>vnG0fsD`;y5fld*nN3Lkk5m>Q@8hwJ~?82QCWLN1nRS(J zY=aWZoTvKsycc$$pXP6J;yZ(Jz{_3N7P`WdA;r0e2HzH=8q6!CCG`ZR0_|MBO+bC0 zD8Zp!{fe)u$P79|@_II&8C(8UvDl8wZ%xR8eB~QGO>y?m+LDS!2USR2YQnMoD)#$4 zv_4}B+H^Y}5~S+<*rboG;N7q05S+P_RY271pu%9_ZbBR)y>~6WbDt-PWJl#6n>RXG zH`*S_BL=op-ha4S>$^#Sg%MibOa;0eKcl$sBzn^MSuwOG#GE5-w)x*RW`*34x!ExX zks+z_)C*|DpTL0I6=}UH4l+HD)|wM7JC)Z);9yP*wpvatHbVe zJ_Y?8JXZzQQd!sB>7%%(@&s6trzginLrdD3 z8|R)Rg#YXud8c}WMG4Fy?cp~R-TZRwZc2GOwrcTG@9ZpGIE4kkHsuuZ*(#GDs98^o zLsF=^)!`|LvRM{JK%=|zz5HH>hKcuVaUng~#>2c!%nOOkt6ZzITm%2!5kIP;A^C?a)VJ+;O_3%E19uRk=23YT6rY)G3Q6-Gi~|x z-x&{!`D=n%qC3T+-Dp~qi=`=xfv8^xMAwdi6Ft;7to=~qWtFcE)43ezTdPOn?ts>OoYoR>5XS#_Y^#bNskNdqwY+Nsnbw4;>_~G z_cURR{NrycT{7yTpv&gVwLR+L7rH7HC!c_ly%*1HUGJ(SH$czV^VcgzwAnpnD>&;F z4oQ9hx3dPN%{wN|R6IHq4yfgbt5{WOi1&=!q3DlRbfjmsaKia#snwRizhOMyi<;BD z(T}^KJDu&8eeX(0LlA}4ICIm2MVHtH?;3^9Q6=_7%aN3yFC(Rji+grAPs)mG@$n8Z z&NRql)JH=^NT|>b!)e^9I(cNVX1zk`SES31{ePHZEX0Qo6w8Z*^iRqTe3#l7uuys) z$>khmAApWeDi(jLesdpLKdL;N^R|TRY=}Q`jsGYkPH>otVSF677yqt%WPG5IF!wrj z>9I8Yro60R(yx3r$9q3PHQ59YlTI*S`+FI1Ksd<8c>9q2fR*Vd?PIf$2y0t^=BRey z?^FCykM}1NL-~JK<`Q1}gzEfd9`%m`^J$`X<@fVab9Q&6M(RphiXvkD1U8!{=a1dB zu1m?OFRERb|1s}qyLA8F8k*SH{T(6^tevz>s>B#M4AKE|z@qA45Cbg2*O8npsKBI_;-3U+EX1q| zU(NZt2;P1bfO`9X>k$I~(Ifomaj2_}n7bM83`U{kBl92z^{e)u|Edt6(*pp_-K->M zV|$Z(Z!UyOvtxp^Hb4n>$SDJsn=kO^cZ%x0~P7-oF0y(n)|jlbJKc-43taaXRIu~JJjK`F4hwufjP{rYTvuraT z?k#Up=(p=FF<d#Be7Cije>Q&Q zXk5#eI+7#8df(0l3HZ(N#Z$%q3ycAtGMSn$FFTAvY<54&>fp3cfda!!_bg zRsRe%3x_#<@aOsXgdMhpK9d~4XSXTojK1;my_c`1FwApz_LuYxAkX(Z`gNx+Ja@!E=sq8^j-Z& zqvi15_uzl7rqJ+u=*pea3S?4F6yyt9K@bo5g0Zomua}dJnj39B%h2*??wB#_=}TDN zAGhm5t_vI?IoDmcu8$UBm5D%_3jPW8oI%^jp9{|&5_sqn3Drq=+NtA21L6h;I%yggq#2WZ+;eMmk7w-5t4rKBLFAEAYqG~;|3s8itzr% z7ud#ssNT%er*ke$nb$hT>C`7KDHJ^lL*j?wobBS|C?lz(I8A)hnvE__ey3jGxED_~ zNTHjVy4(iDWF)fJXgtWb8pawG$qg0z)_ZxMF+Xpc%TUys&cyxAS`QUUk_V%0kah6i zEiAuIIl=@SS{1I2``UO3zL$TntCuQufA0QIKd2%hg}minYDz}y5}c-?0JiR;PsCDJ zCF`DFpC=R?96?6OFHhQ2Jf>GXJ1>2X_da#x*i|O%?n@KPZ1QI9uiu%PQy(~^)k1g% z%L(MFUUel0?c{VkkITFOQ8L3+)OIo%W~q&MXn%x*zPk9yiKX!lITmB4_eLqIV++;h zUY`rc3N4A;$WG_peRf$~REbY;fk=*#`~V0f*POnXP8Cn(usye6t#89NBBc zMJEe3+~D+Ki!&{aVfp-&4YIq<1kTIif-3B~4SALL)-44Y_&!pSLpji-slL^P?C?g) zB$DD~rF!W_*zzZBbB%WHGLOx6jY|857xn`y zb{?qLrcUMax)`0X`-V3Wg7PYJUm3O=^TocNFIjPR(~F&W9*udRzTPg2(r{jS{`6q; zRL>E71|Q4m6RF8(zxeBzIJEkk)~s>lNNGN7u<;M~1gLN!5X7qVI%$?z< z6H8?I#`EDD^tnQQg-xru7dF)_syuUM{Qf`A-a4$w|8L_)P*GGc2t{Bj-5{N_Xz3m? z0m%u7gv3HcLQ=ZBV@$f4bc5vR?rsK*`CQ-c@BSUneIL(%&p+D%+aJ4*UHe?u=Y5{% z>-C=z?F3>NP@?*FJV1o#`RJ66}_ z5m<;U1lok<0W03VK$az*Bg@LHzC0#+4xDL+o-IU#9&mkU2dQUKJEU60dWRlx52LIu zz~uz3vY-64CxM@SQUQ?q`$VvaW+Q|F;Xtd~ai{jt1aZW^KG9#VB1-hpoZQ=4=4UOu6fB)O^zYVNrUc3PeMiHsD*QIpq9_`Ad>te|l0@!<*;+ zX;PX;Td8tG$NC6EM!`L>FcFaL1i6&ZCn|?fKFpqv(mJdq81Q@_Jg|Lr;iL>~D$)@4cHYjtTy4~@OJCnOOej(4DQ~B|C(sP|`4J!5gn_Ae zz_vdxs(H^z$>*WWc$@*#lYQUP+?}aPI<4msm(wl$Yu6BQ3!5W*G0oFzHosELe_4k9 zxtpMW+zJ;J3b@n`%KTL(5C=#0IG(b^Y#<$*!rbG>3SAn82$POS_w;9h#DcOhZW*I} z%93&#YW9Y9t=A#2JpT=N?E4)oyN6+$K>zh$u`2^%N&^q6B|7j`! zG!O!}&b(<954^FFO#n_Ry&xhgJXb8 zG>KHXw6@pK=oe~@dYf%!pv!t*5oj;a8vO62LHkQ8DNtV>0~X7W2PZAcT#wIH>u+Q1=bMdx*KZH=he zkz@(vYwMob0cF%cWkH6(2KOtw41v_!>l;Cro3G4t*cffdB<=d+%d88}a>*o-$4MV0 zM! z21;C|rvL@YR_f1HDh&~}5i+1CVFhp_Gjr!cz*a$_9k|CPtF2X5CX_QLOce+7cp~lM z*+N~m4DhQCd4if2xyZS_B8)2K9EvCn#w`*RaC6-4WAglI<#HN;!O!)(~$mMnsXX?2pJ_l zDN7-#{!#x>-)C~x7$RyG7qR9}C~)X+yWj3p9i#}ZtD`?!UwH_b&@m3(BQ_|MzZMT4 zME%(2eAZDde_Q5duVme%>OQrQfaock7;#-(lEwiR5j1gp$0`^Z;Kh4-Th8jPip);#%LkeBom4t|!IxwL!v zOj{ln_>qFZ4qj${;ez`iTTZ5iXt=@89Ro%)rZ7V98SY-5d)L8b=M=Eaddg4Pt-r?y z?8X-qw@bVNGhnsHkJbHw;UGxpOhg7EgU*b0md_Ji-SOGqDTLb&I_AFD!z z_q*Nj^klPm%W+n)ZBTA%&1Ynwn}=i?SyQ{lTc6;G=L`b7X6hqYW;OXl;1;7w`keYe=ue< zJF`=vrA;60@WrmODukXJF16huY44yX)go>ns^4`zy;7*Mk6^CNve_GUkm!f6m)cMv zreNibvRS{1XgsVMvW%^f)x|V4&6Na2p-QxZET_4-MF;4-zyB+4H-DA1sdSd))5&nAsmb=^agMSb@st+liS20LR6$u}DEp6CV{+4Vk7D)1Xf$mkzN-Iw~h?-rb~= z$0^tRWVrXJeR$uP-_QK8yg+UX1pe9UD$DaTJMandkc(K}@BT{Wd`aOVzx@bfal2X| zihc78RQ^$wh5_i2RzE17mGU1+JkpH7>xngb>EVdn27LtopcsWc?a<+XN=(-uo64d( zfuOJWeLa+we^i~T+iJd{ESMH@A$udWKIwyk-rz+!Dqhw*ut3&RN74{GbYyk99ks{~ z>@%B<5YNatMN6HQ8^EjKX0b?i8;n2i_EJr6ChNzI`cg?*oxleXmRV;DN3to>#4XEMS{6+(;K!1dPm;|44Ke! zFWNw>J$FQc8u#KZsUp}Tr`xx_1hlmp5voR&1s^d=zPq1|nX@7LS$h_eJ61ST_17>#euB1D3)b>+LxmA8UU?B%lyu)0K8XA-7`$_IkT4rc!W=gi|v zO9N^V%7TAvD~V71K5RT*^1{XFqX|m;tKZ>>dEMc6Wig8TFiCWa0O_;D&pZmZWp1w2 zh1Y!YFt_xr;39OE@A4v#GqJ5%7mqAxSoMz3RyFpgE=Mx#Cr*P#2KbSA_oiqAhda&h zTy6x7UveLLpVW;;;>G4i!?4d;)2c0ZWaTt3VarrwD)aVjX?ZjF^aU^

=S9XS(hB zls8Yx3zA3YxIDPaei>4H|9E&5gHCz0vUmcL0{5IXu?yUwr(X4ZXrL)$^!@1b zq{MI)lVaj&O?9WzT458B$wZKz|{fveIp&3R^$n$+GKj%VAM-{@Fohm6(-xx z)IO}gbq1v|6AaU6!CHf5QvNw3keaa{SGaGn^GL4xMgJuc0n)p}gjbgVF7--THG969 z6FNEUTViqH_YpM21EK^bnP9R<)t-DST)ooWbHmG3{6aV2Y##(KQY5^6=FCrYRrlh1~xLvf` zoiAdXNNs{s0VPC?PeD3MU>;`h#SdXo;4qq_S;7Nc(|HYXD4A~bj!%muA~fErD*Cy< zSX)OyxCBe`$dL+M9q*B+mPUA;I;Aq!E&QHnZ-Vn7sOCWIXd#7SCkKW`$|b^ox(WlX z9Fx;%g$EfYl)T)sW4ESrgD34DYL%Ab2NpRX^E46Ku{0JPQa_4rT|hd3f}UaM>7OF1 zh4zrued|^#noYqDdhTg8kDp;9DnQ3$k(ujwyY6ee{_^v#vxIQ3lo1aU^`-tT6)Fz6 zpvsP(Or)KgUsezFbS#JWxYi|E2=MUJETSe4Q2nfgb$MU}aoCEI?7v_$=~s0^$QDCG z&zSm3<)>M+kDjF@9<9__O3PIizDL!Jn1df&BXUNp&0c!;F6+|vZ1~a6FV~?!cyf%U zsWvExQPQ{%{6NoQzonT7W%*0;mG}KY*ED6-zWkltvy34dj0BWP4ZOUqKEh>*|0?D& z58k8iT|T~G6kK>qwgDt74`oOL=IIt5EXGuVzviHtnq_*(4|C6bkZst_>rle#=f@AH z4P3S3_rVij2tvD+-sQc$qP;uQay3zR9M#kWK59M`Sq9M@d!u2|he>gFx6dS9F{o#a zeaW&STng{|`+!wmyxF{jb0AHslH(F59?y}ERRhQT12LhJ!^`cpN;|<%AwenDgS`E_ zAn_T55cKtW!!^9E6a6~ih^ts-wh4d3%znAC0Oz*844qGS%t6$-$1T7(78H(>989HD zS+w5TXrLKd!byv>#5aNC7lsMF_ko!oLILg0inyHPeFux@iT-R5H_v2La9Dq15!}@v zif^AQ-vhPWQCIbGn-KCinLX}3Bima-QeSBWG_@<%stpJ+jmny!`Lv(nggc0#y%)<&EDitN4f3XSl}lWAIi#=5ZjmVqA%`Of5n`>|BG~WS?90f~~5OLLi0{IP^Mk z@L)C9F;xISl&?k@yPse*1vC@p<~Ufz8u`(hG9mV$B|Rtw1!l zc#+Xr>p1czle&quPu&{}e}isr_V*v=Ko-VnZE6zKU&1=(a2QA=Od(o<=>d&2qplVR zEbQq+(__=XsS$W*zLDW3xUEKUMJZC)p{OC>87iX{xh|yy%A9wKbo#iGO*GL&DU9;F zFuvm6mYv^rNS82V76%jak8DvuruU(e`MX1Vt+y8a21pbp%fp^#MZeLkSXH@PgsnDh zv~hm_j&d1w{7xXbNle)-z(hKpm99>LNjEC14qU1QH#*CZ`@TY_I(+^gKA1<%i7_OC?2s9YzWu+JK;xfE;uXqd|?kBlnGy=x}VX>+Bxt+})i*&P1vGkZur z?jP6}_JOQFM|vIjOslgK4O|TkRl~ciH8oK=RZ)R;A)gH5 z`7uQzQk@P(S++Z@=DW;^(d_m5m`zI1JVErO?}<)%0zPX5d$1Mi*J_>g2J!T#+ic9Vx_oZ)iSM~xfCsYkILRXxU~mFvo-7q*>>|H)b}Ge3hlqP21n3Lnv7H;#ibVBXs`VZ zUSaM+oyz9phi~_449AcM3$ITzou^X%ywhLJj=O-mdp8pKMvv8R;=P(D*iv$psm2zE z!i>!K(vk#}cD&x>ve&?XAP1q*9j$w8?YeOyW`BiP7B*?NW8%KIp5exPp(--Fs zXp3CVwb4q>Cx1!WmC%y^_GNI#?d$*WO?gyN`C&?6DRiF3qJ{X(gzW+K89fS zUuIZ#SkhQ&aVHxVw5Y~saHE^=clRk~0k&1t4fHM%uw>ixXkFW(9(nUE!w`c5067&v z{A6G0hA_~Sd+Fr`bW-#7_5fAioS(z`NXY7i6O(@4-K1~L_RgMy&Zy z2n#tlB{WvI+pcC< zB--Yer7EhTT{BJN^0bd_qD4SoXxsw&X+m2qvU>eqx`WU26dr@50Q{wXI{ zLlWU^`aWNty*g&8YO6_QT-%O+TZWDR3Ok&sPE$qXng-UtZ2c0~;&$TQt(p)509*z2 zT|#de7^Ih%7k>OpQlZa#mJG9hs@wQ1(daV?2o2MJjuH3b=o;86gMO-<>7QO(9=7dH zRzBD{MtNP{SS$_pB&-y21v^!-7_SwLa~CJCraR@RqV!#Qaf3ly<$e^}0&s z@IVirW-UU^)@fU9QYEx4BeviU*ZFX}z!XG-;?CT>0`~Pq-F=m3$k0oc@K*aWG~-`>To~ z8QEwM1*h$80ZtS|P^py!h^k++xDVIb+an8;0EZW2JTG%H$M;4QOmG8K1Htal-)XfA z72fTHGTYO5qx=V^H@4U?NJ+6>@P`X3t>?V=l>A~Xw7fW)IV2n zeg@e&>?*6FIxyWIkU_FRBfv+Hb#Ri9dhv8(Xqn=cM4ekdPg( zeTeWKsYt&NItKg7mTxat^9hN@@X^w#xE-mip7W|R3-tbqd++EUl`zh0bcRwq>-fd^ zkz?v{+VzIz;ywQF(!7orNzAGxp*eBFc1l2o6ea13`%Yk8NYD#V6;r_mVk7+(3Ho7B zdtw@HxwJ(gr95R7I|uhWUzb1CVeOvT1a#?daG{~Wgqr%(h03i>+R&V-O{Ry>r8T@+ zCg6Tfx(wmL!;622u5+^1+1&Ha3swIVN%dq84`QFUi~B?R%u@%g6J{c0+x;Y)Qng&y zlM0n-@V|u;;Pzh~tPeaf9c&n1oGfVmU0P}`Tl5Nujo|=VF0nYyY~9g=zgi00$RzIw z9kV>%K)DhnnMc94ceF3S^GPjFPwJOjK3>@nstWCdEd`u2pZppjABTgp^UmUysw_`P zIKTz^ePfu^MXs4i(MZQV7VIrz&X1-@M6}@}qXm0nN@`hIZ^My!1D~LJ-f@WDnv`R` z^@d>CpY0bt<3|OxYVNJl?Dd{wJnF-CZ6zaUbul`>^JPvgPd4WQYf-1=#B+1>Yiofv z3z6dG%R3S}xEVg-mfQ*9Mf_iqxP8a(xe})TaKz;vqM_nzc2gfqjzvT#KA|m$m5Y|V zgQmXNjS5P^@yZQJ0ezZJw2U1zns#ze^oHG=>27u9@Lu8jSHunoP8!p<|?vl5+w z4yobxV8Q!t8o)a(Vs8Eks7=ID9Z1!3`|r@Xs4-Ada;x1lw)S%zyoKcn;z>k`Of+#H zF=RY9On#&{6lXIi3ljb;#m+4sBxd3>YCHI-7_6uqD`l9c&eLm9o+_Ka^`4x zt~%g>gVY_!7U|pzD1DfEGhKpagEb! zM8d~3QddF&LXyF&8DGW*$pE-!{josQXf&uP_bmsRtl4Pp+wu&7{0Edkq)4D}^Xq8Y z4sB^p>g`DYhbCj&J5yRjhbFNy)^q)hmijtcS|q7)-5Ai_JO|@TR{`}70ILRF8JWDsR$ zcPUPd`fu8tHlI$|SD)%kpp;wc@cL;})?J3^&`TkB=xDvNw5F0{FQ{cL#Ehv@A-WyY zAxlu6eH~EDRQ~|6WO)h89hRjsR){WXP*Sjrb4%&b7emb5ach?tc#Zj&`SHw#20wKiT zyxL^cufPDGJ-T^|?;Yx-2I>08a6{W@elB+VMB;j#vJCt$2?O-B6J5{Tq9yNaFT`JH zKXia8YTRd(Y*;oyfvb+!tRNd+mN^0BqzlrhvXptF?fvIoQkr+_vVI9r6akLrj5{)c)xeaBiU8WI-qFsxUCr-j(TMo8TD}c+9Bu!y^`<2IGQN z112~_Zt(E1i0Pt6Mfsy>7xnh|9nCB`n{as{G$;HMkM?5lihXWY!XJtdvHQrGOlri020=Fq;{B=-5OyY^n|(x*Uo zFs$h>$?;}>Ww~!3fE_PX1pCNy>h;Vsau$>}=nf9DQ)T@Nt2=6X3fwp@E)iWvZ5x<= z4Gw$IZh$Vf0qS3dYPgP%isD9qWVATVf^I9Y!At2_j#5%_lMMJhEN!1{u*8!+-@exZ zV3fpi;cw~^xMBB=FsBJCcKPmH$8Nzfv5U%|);u3{6c??&E7)kK3C?wIRv9|DO>_>O z4_v_r*NyNUUuRobP(u7zJjjpQ80uOm2O!;y_nLt*iX`SPT)sL&z1HZKWpG^%#UMlC z++qL$7Xd&rE+#{e)fj9+6Oj{6KD5i1pf!*~?60c&G-y=S^R_))!Ih|cR_Sl39CH1U zk7y*vY{H-#Cm4Gu`yfbw&%kD3ZkzryHlre^&qW_m0KdJT9YvC8vy1r9#h_xf@Iqcj zk{HzrwXKYQpTN({UWVG~fBY1vl9m~0o!{p=vg7m=?(cZ2m!$qpDe9LDm*Nha-=%Sh z0&z1;b0uJ7)>(_-d6GkQGtZR$qLLDfh6J`j2%wGQ`j^NUexgXQocY>N^gh&yA&V2!!~LoaVm^i!4~!+?1MQq%*}gbV2nZj1eAH{yQrp_jgURgh6#Ud2Td zdnEbNa`0kWu+7ikCJyGLN#!Pt?HfOMqI_KF`O^5m!%eI`zA?3}8wa^+cmTPW1|_XT zr>ZF#DMKX{brHUtocU~CU zNWP!=UfnEtTLDxnF{eQeHtpP#I&m5ya+xO-igj<=vx zC`)xpchUioex})%xl;az&Yh^OwaIX&V`L9jHE(Y>vp1uR1QN%Pc!np zfWv(N1prkVZBg#tNBTKXksATi*|f*l?%{Rmmy4?4Mp=+7&0d|YL+9P{u=$IMKZ}vt zmxlmh9b;^o>9HE zvYXT)?#H~s4e#M|{S4a^PyJ?os;LeA!QhU#_(g`|tpJ&RhvR;FZgP%RKF`5HL6e#G zu6?=(L%*BH28~Bp%RI5B-TT&Y!V{ss5QRw9cX`cmIzFHjnwUJeT|7`gtXghV+vIkc z_H{ztK3{_ESDo&{Hf&+1YI53MxEo&6&b;kA0p6|NL0!HoucM=x!uhH1(I&IinF7_+ zp58$BigDwD;QB}~@*--_l#I&9F!WwkTh}&p+EjJDhX}76GT~1K3AYS1T^Q>`@rsPD zdqU3-?>k<1?{4|S`j^E2*Z>ZG*Zip>2OI(1{g>Wd8e!W@Y2Fn5OQO18KC+e68|+O3 z6s!R?&b}ThEnfB3dR3#xY+8K>%3Za^iIkU!%`PG(-eIU^Ml|AWT}8k;{Kq4$58Kxi zR~k~Tv@w8>rFD(-gV*Q79aT)EfXT|%sRAp*(3L>7GA?-~xSHy;=eA=@m9)%W)8S3J z09Tk8xYfzB8pS|S>9|)xRPkWh(+@qr9mM7W3^!NyiH`c z*dS%q6wn>!Wm5bIx-<=bLSu@Zk2C1RZ>tF<7xZU&7@~euUw1Tlw`n%zQ8THYTtWy@ zjyut&FV3O}OF(t^=JXaYsfc}dus<%%-eA9=U#l28S+>-bU1gLx*Vjf|NV~7}J>`LD z&Hirw)M@>^1E3X1Ea_{D1+e?B*D>$EYEudaNAoIT&Q&oPejo%G+*X_7L*&BZjTT^z z&%Cwzp}rnxN-A1KK7IhgJ!)I`zVhrPsnw*Rvd{$ z@5I@pc9B~9AVzzb+2i>546}^xo&-C+&dV*=5dE+)GmcW8k%9f zjRe)dkSuAhLYh~fmBBXMxOof1Dl_=*z^CnKKK4hKF+k%hS6G!ZCU|n>3@)zy2IB0z zXBxs6zU#M;y8XRO^IQ2S?u&rq9`|DK;8RE4XSMuWwV1Odl%Vlnk|5#gg_02Kp!|Y& zDQLHM8*=&~Il)P0cHLx}2lXP8rQ+v6b3h>>mP2pi_c;TQoI=QC^;Jp&ZlzC{`@aZ2 zkRqXZy^5L~pM^@^xWfL(=7yPk6#ueG5{WDJ_RekDXEuii-494*6LHbVF+EPu58+$C z1P&o}_PgaJ;3KYMkZvgZ{73LTl16$}gsBC5r>`2a6+lzll^Li2cMnT>b z`x7VX46?HnGZE7|$n-jgFOpQ(X5=jLRCo?}H2p&iL#}zGw5mU3|52w@Gx*Bh9@i~T z?km%4i;owH9~2);%Bm(=l-3u#424}bpT*;OnyHi}5{tD)^%O60e%$8yOLrTGNVn`pY?1A&rQH!yn0Q$UgdVy)1^|i?N>Uow zlQv+J-tB#i8Iwv&8qF*$z$B<2N&>A5s?YwCq*wzl`$)iT$=zAVH@Jf@-k@foeG%J& zsD3%Z2C6ij*i2AGjVg!Dl%Wo^0ZYyIL8`OUh(j8NWMTEW3Jc<)K9l29(7}Ms#e4AK zAKk)IOeyL|P*v9Uu|Hy8GI~FAw%NgZU*u{sU%g`uvwAvC{GYe~(Lyv(?GmFhKdlZ% zT*UQi|InXkZADEE$S)Yb5Gm#GTO+7d+ zs`0S2-W#m!Y7d152sjbh_=v&Su9ZN={%%2w9cR_TiV+sDtF9egO|)7OisC453I7AG zr_gII-p!vw5aGnCAW=&ngaZ;wui%HNa$hCgbWAM_Z>>oj)X!39&Bp#<161@CCu!J^ zTHs8LyJ}FHws<}hvcW4H%d2xuLzTp7 z0{l(T*Ojn|F8(uDs_F9xeV6p;VfvSA8W|+-{+qk}&oftE*tcAsmboj#e@NROD{lB_ z#f6Z5?G!n#+*-Ym=8KFbvhA~0!73hae^>%-v|E{NY9RYirB$Uys0aAyS)rdygMBYg z5sZF7D~-g^*WZ}m`2HY7j;K+Lit0a9G9+dRAq$O}0Kyw@sLM2=ejr6^O;d^e&Bc05 zvx&&jw#?`vH0h(i#9eQKDxeXCKw}n!-oE)*WiX>fke&?}EYPEVw+X@6ycq_{|nQPqsii zT)fZFmLe|o*h(hSmF){J9K3hEbYG~IHlEV&gLPdZp$EC7lx))f4tzdx9=0bommIvO z-=wh~4>vdJB=M?k14$oPgd^(7%?wec{Xi*57UAAr$&0TJ<+Wd!PL4uMfRj^(+6@%! zx%_V^^j{We-1bc52yAl_!PVten-@MaL;YMyIM_#*j3r`BKC4V>n< z?MYaiRs8EO`Cv>r@*NWRrIyiV?02`m?HGjM9eT$M44H%`d!433*TjngPYN%yiev?0 zq3LTw!lw61B2M4Ef82Qmz%kDPAI${`R!_0{uPvF>$S7~i>i$GOYgtC-&uV#)f6*kc zk6>(giq|K5yB}Tb;7v3vA5z3dyw|@8tjjm&fmY;#g`$8oKF6a=OL79RIn8zK6~+C5 zk^!9v{WJvK1}~MA8-~qSRW7Dq&CHKb1IPY*>B6dk4R5=*s)dhPP;}|O`b>JocK@I) zsS^N=k>Z(E@u>Mt1iPv~i&H4zd{LYp!>!brwQ6?STpHcpHC6dba>Zme#j);q?;*Q? zj5Lu3pTyhS660JqSp3-{Tvb7ihJcmm%1m6@nc2D!4%Y*OkSMZ$S#8tbo&`l)e7Od9 zzEC81p{Pw%=j$mx)#&h6EVzgt#=0?$3?PRmo z&xPDSv6IM_mD~lgSTm@c8F-szNd4L%5_5DPprlQyC;XSa|NlPcaFqq+=Nrb(aRH&b zYb2uObz<`})~%=A*6Hh&l2MJsTkhTVr|hX9$Z5Yfszi0A?x!8``E%RRJBRJrX_L|! z#m)q>Nz7owuf1KLqm&!##bY)TaC+BtO6ISmt5eCD7x4tF^kN|!l>PP9`a&GEqyd41 zcq9%LWuy<|7lE&@7!xd_sAckMS8b5&_Sq-J!4BCpc`&3Bjci5olzi#T*_d$1oU`sS z-zz?ObQSqte}Y|QG(`{MrFA2D1<>U}70N0+sW8Em3VSB!kB%0(__dU+t zY$GRw%E{pP+-RR}zAtoNthv+{Qg@}~=C}D5hfm-iyHGivguVTCZ$|>zLc--OEo0+} zhUw;=j+`i`Ed`PD)7$%UJVeUG#cqgHQSfJI{+jDhe!gd{u%;Yhpz8lFT>lM`Gkjj3 z`6A;yFSa$gz#pJTrgNA+aOB3qI?@zv>x46>%$N!@aSQ~T12B4!i7?uE&@ z5TEU#a{!ge$sI@McxwLRW5!g3mb>-uQkZ7u!H%NQPm(qT9D$3;{<{GREdgOhAXP{T5DEl+wSct(~hv#l{y>XUaMO^I0~f=&7?WoOeaVd7bkPJ zyd7+N&F%1no9rjD{7BumL1v@IB*^VNDbq7SUi3#)fCSU!OW9*Q?%vAShh`f3GNS<_ zC=}0LZ1nw*PE{v|dKUJVBq{9Zj_$CCiVWLSzn3#j;cI->N1({&2978LqYpxwCOOhZ ze}C7Z9>+ePOulUDnrjymU*8yivI47C>RV4Nhkq~TgmY~D-qYi&tPhO;wpET=#+ObL znchqYBsCu8X8VY@#5$45R$iET63Qz(jzrUoz_(psH=}M1tqc?GkaM{r1mox0t8=N z-w;w@DvP5gv5LT;rG%%4TiEXKO{_^jnqzcq$7#PzpFpHGrDcUpJ$oYaT-|xyaN@)p zHJ_x15Yw)JsdP{>iAtQ`RnS1lxvJbT6^{CRJ@rU!LTtmi{hqw8$&FrTG^C;8h+~fO zC=QC|(G(u!amr9){-q1#eIve*V2Wh#!S4;#fwCGA`4g=kMO|rAU1`y?;NPjIjQwcO zGd>mnz5+>?r1VNhOQK`PLFtDXUu`9wf&wqrT7cFL4>}9I@-t0F?6x+%c{1RlR%?JD zvQMU3Rh}%x2pN0upzLj-1<(r>C2}Cv8tNMZx&v3Xe`#Ab8PsX}aVore+2}G0xC=5Z za&8v+6t8mcW`5+X?hsBtC#heGbAihvN#T{oQr`IS(Ik|c;kBS}mj^@?*J0W|JYLck zm1VLS|D9HpcF@G6Z<0AcFubkd$6m}X|b)UxKWa{M<>WT^Z*5O_` zoHMPcHdhV^q<9^5U1w;#xpZaC=o{*a@oJmn1jVN626nTrK6rLksq?fIU6`rmYYP$wV558#0YF$De=C2H#oCLVyh3o7mCJ zGUSs6Mlz~N3G9ZVouFlv&ALMlF|806sdrU~n2uDl_h2{m_O#P>^ruw`St^>Zh7}rU zs&c03OZtt9iUQU1=ZQEv-!|z|;mX}^I8%4=##!HgpbN#jI>zdy}C_Nf%(c)Xc$&p;c zdYVF>v=Uowo))z{p%cAZd1hOHa>|44fq$R;@^AM;XOdXB^z^mwvsHs15qlayBj~J{ zSNs{X790uPzuW(Khs&n!14`el`)-S8)TYT4EZ)1XT`GDW2YPXXv>r8=({8V&`U&@H zpQf{+vc`;>?vq7N$m>(x(2wd22Y0+4!Z)AxZ16CCc$S@&?gr)6jVHkS*&4KyERSaR zqFH;}^@{$I80FxZ_!syoXYtzlDQ`!3d&{TTSF}5rOUb4{ke(^-4a@|z@#7}bUHUD} z&`R4NG4YK*#m!_#ETFyy-L6a6T%PnxvVbK}UTwY#&XKU`5P z9&sz5rLSiAG_}WkC%z8)C`KW}*^zjo=ykyuI)7fhYQ-JZ82o2(?)) zE}^BKWR;Y(PV)U$y-~1T=sjaoA=?^6a1v%OvuhB$@cGIa#abQBg*I<%i{1>|FBKPy z(2DU@yNeQrM6YkisH2-7eV;+~1Dw{fcKKT?@dZqe0g?fS!em9(VdW8JR!nvMQp!!qil(yP_?-WY7(n2ppYWw-hqTDZ^_P9KGRjJ`4|@WOUQZvcgU|zZGuwbMD`Z z5eeh|pDP6J9e0cn=X^EmWmZD}cq6Q!ETv!?wXWWA6mPuwa1e4pDkEB6#|e<*SKU3((`< z-(s)QKg@El&CK3W5|qOC^isXL=q(?2&w}y6qgI1gLH25NrCzm@&}Q|PBXJaavaYgL z{;tHt$+%I@0vn3{-0wvFJLbDcoKy3xJ?J|S(LXqyhZ-QeogNYyrep;hh_BDMsMd`> ze()%@X&8uEw&3HA;WK2N&S=NlOnwz>wSNH&S@o}SAZvv#VLjDF7mF>)j;+D&-)`s! zqc}#Zo^Y?0{&2Q3_<=$~6J)0HrK>1zT@(|3zQ0uETU=MFWQd4&2d&a9N--6s{e-RU zj)ULo3=v-DTEs+iP+xFGgU|003RZa#u+7l%N>y6$ZS=~dZ%tLSIl^NCEQhI>>ypKZ z24TaLh_sjLKNq?h`gtNzaard?zi{NxL|8rE=UVPXg_{jF@P7Nbe%LjU34-MaxV(Yg z{hPzUln2?`7xtqf0ezpu1tw-ejOK?W;?fqDY@*AC>mkKm;s!x?EODU!jJnQKYoX4E zd1(2boVeEZNmeUE2fUDTER%Y}cyXCFIy{lfW9&>LJ+W-!Bbu4}9>-Leox#GLkz%~g zExj#ep2=8in-20U&oS|)dYhr-e(Y-6@V$- zYflN`S_Qp;8Kq3q?-2o8_G(LdZO?^_?&qasYd0CnZm7wwtwSxEU32s&Oz(Xg z$fAxRfP2o2i9xmp5C?UgN&A=uz&vnI*Sz3oz=g%qElsphkW2o6Zj}#-VaPw`0arT! zM%pI%Z(dijl#xW0QO!H+RZ_l7>dokE$PZ7Q?g_v%5M?Klr(aH@SpIC-qFhl@gKRWq zjk7?V$VKvLsFq$XYm4KGULx=h2(Z5WkFVDC*--9(_r?GFnN*@yhgVy5BHfN8xMBOv z2dan*l>rG)e#dp$7mhZPjP~;~p4=Pj9|*I0pO#0Ipvv zqTU1`Vn@`I=!6$2%@lU(X70YANkG4v=K7pV|AkrP0fpDl&D0zH5M{m0)aygGs;nf` zRskHOj{^;ger67^6kOso^!&ng&aA}5acL|CbO z#tx=c=CAd5z#b3Bx+(b%odqnGL+@-rxbJz`vZ!1VEK!2cmqYJ^EwzgBH#`e&2b|vq z-!;!$*X87|CW4mSnjdR{X>)p`V5-w69Vf^AB5O#oy@tSBH|?96Keev}uq|$ejPydr zUfXu@%VuM>x-xiN#m&>JEmpC|D+o$P$pKwj|6;wT!+iEb@0~jW*B%Gh*C(E;`kUKQ z{X!d|ZknoiKUGwy?!;izUf)V`H(7n)TzHB#hU6!dxtA9xBIWK!3^)XR^SrBO@H(wdVeD?U`qMW-_i3k6nc}2zSwapP z)Be4v*yG%q=PM1T;Lue%a_6XF;$ytNjzskyF@+hlU_c5Ye5Ubp+57aV`Zps(>WqQeXo?c($)RwtT`@%Iay7p5LKe>%899`Fc;dO%E}nx)m~&N^lWzKqdw>woYB!z(EIiGF6t=0t#d^_4LiNYjufDlCcOHMNyx{63WQllYv1Cz=^sN=BnmDe`8_Au%s6hHP8FcjN3LLw} zv?R>-AIUs>6zy&iCcDVNylxy5BCKykAEa#fk@lUG+nu9ry}C#F9>2;X{Z>L(LN8|) zYET+4-pNz^>R|qZi;7va`+xZQ>bR!<|6ddl1!amLg20pzX%UcS#)lS=?oC8mN;<|Y zKw28<8V!>e4Wp6n?rs=01{?Dpzu#Zn-+kPB|JYgacyJzP=Y7uW^?KHO51`VC8S8Zq zCZV=`2Sb}*i8m3R?VJKWkEmt`Mr)`Dww!eNK-}P60{fM#TA%qWGc3!vSKyRLPjEQI z3_`zA8P&a5{dU~tq7|4dvsGzqyfRf{O&gm-EkurAg$uPx@7*f94RD%EZIOT`wXL5C zFT-9@|7okDppoH0*`*B**mlANhBEPO$)IMs282I##`jfFx08p2_*nLZJIwP4J>Qu6 z{h6?*CjOPS;2*Nri*pds-^EcakkZsv_1lWlv)m#ci1p%ho*a_o(|IJE-I5ZbsddMDC){y?}1z z#Hhp9Ys5PQMu4=QUpXf@8kTQ%mT;{W`OR2aG>bLyQM#5N#AuU+GW4yY-+yimjl!+v2Fw5Es!PKC1)DJ zmLati3g>Q&`VnF*XZ)=Pv|c_Z*e7CloEX7*JQW@&*f3jcf}WY|dRZq2{zZQ`J%4J` zX)on@4l~;!;JcbMDs8n}BgHWx=~*m6qt1Ng5_C#ivKoFOigis7>al^FJxL{k z2EpcP+4lu=c78>ik%~?PZRWUZMyNR~cd+0^t6t zWf5(ja9nukdON%ZP+VUiD%<7g> z#->{hXYQ9VnM{2A#hPr^_-EqVgJ_cI!OIPtrloq>$FHd|D`3z5U+agW+jFu9x3Tlz zM0rQV;}urhNCZa+-#Qi*$5!=ZTA403#ranX!J7oEK%R?NEyl6pK_|i?${6<5P{Op{ zp(^KAf6`(dZ<}t4X`oN9)FZ+P!Yx&}4D0Tyw2?OnbKxwPD?u)H6>eq0XU(_gI?w z8>9h#8(BrtwDSkq&{`{!&T;fdy&fQV^SwGX@uLxOH`Ly4|K2$$4)S}9NDeOSe$tIu z-(`ev149fXLreFRwEX=ufZ>j6J#QC7f$^P(_-w#TZgUnPFS_y3qquQ{fvGwYtvIm9MNqH|6j6v-D43Ff0 zhWFC_emY3L(Fh)^-1TwIwX&;WQO1oR&=_mtwKmV$vGQ}laI-PHS$EDM=v9r+oij7O zt`|))PHy+5TR#%6Yb8Jry>eLYhO6oj+;$Mp7mv;vlg(|^Xe;Yddc981z%b&218@9z zqof^iU92Rpvijuc&ML=+2PD+Zb&-|wKpRSa5D;9x&kb!pJQ1{;ct*K@hl6Iu37Tqm zK&_U@YNK-f)Hr+y18o!w&bo+>o)L*juoIo-*Ye)-4gZ{9LRUY@Exxg{Z&8bDSpVzE zfd^<19dVwl@Ouj+bXp|G*T-8e7f}h@(VU<_{ax##4nRzF8Dx{`owivM8R2Sb=LjMm z2dWwIRpRU?*-CMjQuD|6I0FZE|leYGMHWlV$p?6`; z1&`0O{*e8~PbG1^007bgXddJc@(2+7^V=>6eiq$r-)@ODO)OBjr**EEVmn`g_;PZy z_nkeT{_*vPjl}Ktf+i0nk!jGk5|#-ITp3+_t&IrK6x@fc0gwUg&J1v0HOiHBf$){w zX+hz~>+lY334(z|x{9tUwg!Ox+T13w64w6}uiH>h0L{LrF5lIaXZaQpK>9~7aXYni zKKMA+L2&2vxeMcC^)=q#Ma|W1{5q`W7h^~~7ozdd21_zmA(_AibIxqMLOTGuI8kI+ zz`_Xc%A%_?6=C$tQKkwNM^r)?<1>xxMg{M?w)OZ;r=)x-7wr%5Wyj8`lEPi7KxbBY z)c`?ZUkzkYw*r6?C0W0re;XBO zd~E+QiWijuu?W5L3!Q`#HWmR6X6aY*lQfVgJ^~W8829>!BM4KBKzfS0{~@CnCF?i0 z0KM*-|BWzQcuXFBfNY{QYAt-xWcJm#KYo7Bp=b2Mm#{mPR7|7ct3%|KOmF6&&9oXT zpy*~4sh67r{-Q6mV}#@qt+g67d3`jGe}#nYrPFxbwD&LnPL%VF((;x{ zBVRQqkfGG{Cu^vtOR+0u%d4Uz*1lByU$&n!%N0k7cF2hiSf|iLez>b;auM#ofYyk) zGFIrw!A_O-hEg~iFDp*RKrT99w27U*gr;28wE`l<{>F&??+@KH$gnwoDl)N_t6wR(Mc5iv;OJ|H=b}Kz;y+e1ePpC^&cQ#+njy zVv{RJl}UA#j2^GR2KVX(s7d<{VJG6 zR@{InIAl0A8M$myrTH*G0+^Cb+3YtiI5Ebui5rV}<_K=>|L#I64t`CVjeLOLJs2Ba zjEx`DRf}Uf-u}MS_s?@+a;(?l)qrwG*=WtrtDTBzl>o{uC6QfQ!@2{S9H(4Z-+z9V zFM0uM@sS8vB#Lpsw<7V#`A$#vB_WUMcRB8*lYgOQs3Wiid;xWW@83_>#8FF$b5z$P zw*nrDdzSAU$ym!T$@-V{rjl2oI3!o$Byh zN^HHlx6OF_^e}2rVaxVDPU9kex8asmUa{?u4yPr;@1~E>O)b753SMn*A*jyT{ww~Q z>Twpw1#R55wflN0dRpIkk-i2ON^96-@@?AUo)fXur z;QcsCw2$ST0~Y45)II0|K|fzqr!QCf*Jc%Z$X-!z|2M$e`uGo-AL)Kj`=qW)<)vZ) zq3%k&o&x~!CI_{Swd=;R)m0<8-1@7&v8(Y2=_&%Goi#pQKuP*)dB{Vp4@R@$959+~ zQq~i2@iJxJaP}h2SKP#lFqpB8UgWHa^6-pu+nj;~ zN5Vz$mnx-YbLMUq@GQy?Qcl2d;?G&HnuX!42eVJMSL8UtMM613OeR);hAD}3Jw|Pm ztu+6S)$s3?alMG23sd7iHN};(WOSmIB<0W0t3&d)sfWjtUIBhCBt~Pl4<#R!CjTA=vO-7DK+w%9rff z&EMEHV5qFJE1T!(zQ2i~u&F$KN2e|3?x=6r?d<&2Xu1`-5-U%YpP9#TOn+$E9zHd- zbgmK#Zlb+!s}UWg$9@{=b@u#XkTkfy2}^l@_DEQ&Xy;eSpaWOw2_k!4`oY>xct)Mw zfo(Gaq{p;YMp2IcjegxJ1i(ZBibR|7PYn+@5VYl5`Br-JYqQ23Y&Fr5&sct{tMMMG zZEe|Z2MP#0id^!fS&!A_>wzoD*lsvXaSjx(sq$b^w_Kf(oPC7G#Wm*ua zU-5V4zf0HYDirnR7&j3+nol2=q|HS=+jaqO#=v*iDIkxbE*h3qexc^29&1Is$Oz&+ zA36E*fBsxG9=;6thGkWP50r6~wf}zID%!_vJV*J&VUlu@l)BW- zjazVTG;mVy#$d;~Riac6>{IPycU`&B_43tNAA@O0(|6Ug>wH-T>{B&Joh>-bCZK)mV^R6Cq1ajF zk85p8FJ(>;aYUhRn6>P~gJ+j?WfK;D$ag7c_@!-R)_6v%_wf3O7A)0^;8`!nRzZ3 zJ9V(-H0}rkc<=aHRfydOx#*Rh3X|{wD^qUMy#=&)!;(gjE7wpRAvrzF+A8BmbBMPF zUUT5GM*mQ3&~q_|Wkug|jFwWBPWtt>OCv0JtExt-Z7=R=lr$zN8I1|w#M#o(&^`Y>*G*BAk{p=eB_|i?0u=ioS zpAfU0iU3{F&%$@q(5m9VKgOpZ9BmM7w)MN?{7E5dGVaY?1a0hPkDBsWp_6;2#87tx zIyQl0@R<5wjCIDOWn}LZ8tl3-yOl`@RcMR2QZF;cXO<- z4cqI#@&wy`1I7qC(j?d8j&{sdt}y9K9ubedyLAXA1vDSKo@yiNs=+Znrn@jppPL6S z4qz>zl1fJKwzOx??^hz@$x`!U3dJFJn9Z5aWFO8wRYeJe&3}cuTM)GZVrh$*$NVFM zl}M@i2==9mG(AtOdJ}sGt2FwH)#)ZKbyLq^Lr0y;H-~&Pp&OsKh{69;2QS?GonlNa z6v_ODtY7Rb?ra(Rw=9HRN0{PS&<1e~hJ`6_IX5x$Z4FK^!P7Sg&~Z2{$F+j+&wc10qTvZK2hYZ8y>h^SQBR}7 zmYk2-kr2m9N><9r=6pFg1Qg`^U}n0tt?;-Br+-0B18_j*jeRfI^(Pc__p+MCD+~Fq zLR@`O00vG??SHuXxv^anN<2YioC&tC&Qj}DWA{od^Cp#6XQzIbW`Z;(2&}20@LF@{ zY@#NXs`jxri|)8>jtj@z@chax-bG`O;khtQ=fKGd4Y}F(hs^mxU_xle!xbC`TCyEj zm}$~%>n1nS*U_z1nLg2jIkmKTFlgOmw&Ukg+6M+@m$pw+sF(O@)?2(zNO3MzDMJ>4 zVUi12-*0b8qRAodD3^;oz}Ogc%liCS`HK7C*&Xn?)z`21JYWUbHXrSu>2+F6FvKqB zFG2^sykzti;IalG`a~9K1zq&XB#CPP14tP?8`uL#Mz^Vf8WbwSk{ZvTpo!?DZzi)7fz`6E3gOCKq|nqah{J#N2feBKR6_U*BePL&Ch&99dz zfK|jI+(-c}$O83dTqRRnph%+a^Ij+Z5tVx|la_>I!v3UX+Z*Up!`aPK-Lo?bYepKG zams`f$T!3#yShs*q9)2qG79?B-*EzLUuBfnBPaH3*GftBJq1f>zf$m4UN0Q+oQ3?)NOsk#1vqW8ul$9Tp+pyctVJF92yP^kd)Va&p z?9|86SznCSUo}UZn)MfZLSDdR{A4<|O_(jikik8k+*0|rG3T?Dr*>PW%^s5RAIOvC z?A={A-^b0LfnSn3y=)lkm1&%?-8SVGhq*ge(O};{<6;-u+#IS^}qE{#pJd@Cs#Des&1hio~! z-g?d$3^p5ro|3NqAzNTI=4a)OLvPj36Dbf)(pp6^dhsw`v9 zvH=3BBZXca>>+!kXcTdIHb1(Gx=P^Q6Y+i-UO|9JPeqi#j*awRvE`h~HXpJ7Js*ab zxdrFFzW{0#Cz>wa`ygNro|>|`X08hni3q#hvG@tzQSXc?XZTFCUbO_UJFj7-+-`$R}gJ14MmdMAdQXZSLZ~tWTD4kLxQbwtFZWI- zch3q8cLn29??9}1Rr$?_iToAk`+H~tXr_a-K@#2{-iC?W)FAh&a{;3RVEHoIytziW_NtR0`2FKcB3`$q=RtOF6CJ(UiOK#`5_bvgQYlZ8W=Ga^d$g<1p9GH{%B4H(npbL6v(W<8@lL4JzD)mP5IjR%Z?z% z4&_i^v{!ReaU$0@7Bz_S$rEv#iTpvNJag}{^o#{tEK_v;XiVgmi8_t)ET^W7pR%-| z6Ok`x+fb;JPl%^A$Ss7dbr@1v%)df~ZI?&X*`9>xs{Sz5#0^9{j5>>+rY4vk8E@0h zmqwdAV6(0CH-{9M9=--6U4ZJ+DgT_RuQbWzWmt~2{ba9=QJxO{=>(rB(=D~IJfy>` zrIPp{boQtTlfyoLo1Q7XCTGE~pyP09^tA$~pdtpFN_sK_pvd_fK3O0%aOGe$e(M@R z=R4uemCdOfWq-+JtIIl@T7ou#k|W(?pE#gso|D`$B;d|Gk`mpvtZWSWz$H1B+{D)CDI5O?L{G5sBvysTY~H&-k&?9sg1cF%8B zdIi>w^lFHb>DizjZ0j1k=5hc?uZ}f^(GML@3No!9ItF)(f1`C@jD33inA*s{Xf0NlDZ9!07-aXovuquk&PNU`RTw_ z^Tut1IBLUjYGC`E(fx9nWs%bM(}g$x`r?QNjdbLd1)?&4LcIDC%J(P@`;y*V^%+$* ztbdaKbbvyMLg$BTL8SX%_hxIJyZc(dd9J2iOGL_PiYh$6VWw*1w5A$uB`WR3A7 zql+$oLvEGvtM0|pcNae)xj=hGLVeseG>lxZ)j}uchKN02OH^AqFc-==9>;MzC)dX9 z-1w2w3YC-xBdL2ToV;^I`3Wy2nMjS^MajuDBo<%_^ZqFO^adMiC=cSfad>>p&JQYQrZ51 z1`bOY%)q=wes0l#t}v{@wXL-L2XAYb8T0tDetMUbZ}5qn14l24OsXuqwq%^L{;Rk^ zb#QTbgxMjk7QAURQpBV@tFG+Nq*F1-c$bwq@`Lm`5CU^rG;Ja|*W(~mrNZZwbG2pC~+%zxuTJv(B9ml>pr6N?}Ev@au}8(CeF=^jVgunXHOUz=rs2KCH^~ zZGH#iw;UVI!D(~BK}gRIM{Z)h5_6t2l?r2*_{>ewSj$$)NMlT1hoxr0y#Th#nyuKu3UThiULfNkB55cET$1{hD_so7P)wO8Jc4l`3K z(o*o&aX_n>NH{w^P2Z{4C($<>dn9UB_1POxX1(Rt^uNBJbwd~=txH79NRjB26;n<;eD_0izP z?{ku?K*{RHyXl>`O#?&Li+#>z)DkOfzPzD>crn!5Cr`OBVj0 z3XX;kGy{3-2cn~fE%b%&#Le^v5L7{{cGB;u+JGsaOlosUO*fK{0)LqxoF$uej1-g@1lS%N%- z1}s0;YOADWh*ZoFVDw;YymvX*>YOFp&xxfszjRjqV_BK`XWTJrs#F@tNr+ydZQR~X zl_{+FI9a*63J70&|!Yr4`e$g$sjdmiDkL`)p3m9-YJW&t|G$)bB`d1US zmTibkXfAns+F9@=@u~)06@T#)lw zcWG$ruD`d^y>CBme}aEM$%^Wb{Fb`4>_NjxzSBrPhEZ*moQ$E0mPoKOkR6vTF5gntDohKsSsP) zyyUiUHbI<1)k$#!VB6XfM%{`<@|=|D+=;P=xx)TI+0IRESE}vjOge^xbUPnvB0XnE zDuR(HObX^fUV2^1%o=xA2!LF)YK!RY^m0|7-$vUm-_#wyS7S|?^@(W|jSqKcy@DI; z-pk4>ei^iua`zkQF}s)=D1D=1{x;wHj^rD^Qk(p2rtxLUHSN=_S{r}J_&xdQJNQaN z8t!Luy_5mj25m96o5e6AN*hPeOWf@3AH%v3lj23x4!3P|Q@8dxIx?BV$EsFiASJ?L z0dU6c5xvAI;){{=#+Y~U-o-aOY$k8?u+| z8w4xS1&vmY@(UcS%ye)O3VFk{ZC)(}%iHtY2Lq~-cZyn^UnE8fBMQF``dc4sO}~92 z3MSt){8I7uP{sA|+*fCXBzX~Y45s6Y)zix*F4->NsHXg0rs6 zaj*-i?|T(vIH@c5F#5?cyJ)M&@2Qa104FOZn}o zSEIU1Cf&FM@^%hxSEed#^!Jx|Fw0-{iCK2&JQwyqcvk3|Y_qm5@p4-0Vz9B;sI?{z z=bJFC#u>MwzGbTu&l9Oe#`vgi-)Iz5A$m0ebS{nHfRcbDhXhADD?m#7S5Euy2M|e@ zd+Bi=?VQ3!c2P@aFBdj}EM3mw)nZ;MnA2+7L)Nlg_mjlK`>dmEQ?+izr18exb~zg( zyntvs0GIVF53NSwRbds_ouP=sgp+I1!VU}?dg((80U2*7Qzr1wl%6P$tK{HiA3GXT zZI04Q-q0MNP_YxBHox>n=U2K1`Q`r^#PPqg`^ZpPfQce#au=QV;6UtqQP)H|$kzG+ zzCze}b850mv1VmG1&Hvr`ZUBgz4e-b3>OLjQx)|NRne@nO{|_MlL8NTYd7#5=mKOe`(^D>F6+JQ z50UCrQb1M4hAHqc^UuYSz%Z}!25#SA0Doy+7K&_BDcAiC{9FXBzJF`kkQb_Cd`@*k z9Dg+?Kk|c~>Zg37S;M@*ya!J@NmJM|03l!Yr5<7Ld(nko**dQQ7UjRUH;2cn_a_KA zZBlpGa0jbkdD}KfSZ#O>cEVmB20CDE`2~#940Ck=FmK?01i_Q(^`xT5cg0h0l*eKF z1B&U18s3Z`o+prZA>j>(>A#a2WdL@!MolqwFQobf8I`-sa@6Y@-GAvE)~*Mhg^e7* z;-}`&@Fi8~k@m>m`#MZ*Om>PVjlsl;$R$ndtg4@@F;fO6!BW-TLei1y&aeOL>;>Ix5Fp{j0U2iG7xAzq*Og|CEGo`v_CJ3QDVO@h1XZtP36tavEBE5OK&Hq5WN znqm)IN8SXE`}RRDXJTcOS!)Ylf{m)4Yd!;S(c#X=YX{{JY-^se?9bX%7y{j+8&+yK zSHf#D<>?-z-vpot6yFSQudJBQyHdQtBJOebvl7QFBct^Q(jbn$>_BD7A{pD#qGcl% z#=7{~$lHfFgu&}IvWgtUW-g;{8E;J`wHvH`@Y@NVQ~<)Bn`U_V*7DnyV*ZL^7Str0&P{7C%5T@z_ zJM}*S-g0Rvmb$qI!|b(zxzP%_ABqB0;Gd5yDnbzavcCDp~OxAjYI>)rr6VzHfR=|PJ@>euJHPKzS625;} zvPQT**9Mtl$9=BChvuqgSd~e$GFJNB)%xnuf=|3ieSsej(2zsCTAg$Q^R_5Z`-f&U z;0O)7Dc{~@6n?4C!M*Ay3M5Lq5Lns~`w>un=o#T2pj)uPBR!qN_{%r%lg`ZzkHlkb z7@u)tRuEy|M(~WdQAY@C2{5y9Xq()`QIg)(ZvBOw-w}4eSBT29H%dA{7bk2%B$Lji z_4vh%nm+KkrgW8$BJm6Wp9su2;6n5t2bcHND=Z1QWcN~v1pts<9*}mPZ2-=QfK3Z+ zl66~`eW&YN%R!TzK-rrfF&rS98tfkT~KV{WM4(DvL=RdrVt z#a|b}$wc9x_+(4$c86w5zB2!Dk*3gkL~Rg*>o5nqyy>u=I!tM(Rb{aU9pUP41y90%Vk> z_cl}2NMqnzkSK9!dWRg#UT@33lMC>gYCenFMj!9PP1 zUGy?P#rYx~+&b6qWzpL4hqf}GpxzJqD7h~cIF7{%T3)&*CL9qCPjf}x5$oJGzsDs0 zT4cU7^eoXDs=9A`(Ft4g4Q)o~WaTgxjBFxjF&xIDqKa>S=o zl7im~3-@Fv`O81TSbaJ;y9k#%P71uB;dWW=B;_?Fn)g4e-DTIxGwHGDgOom+Fvjwf zz4PwX>F)g<-$VuKeo?(!QMTrTh^8Y#pug2LelS%TR^&lhPNzAfNtQ`JfHwlbi0{(Y zk3>QRY~zo<3f+GP)|1xz<>8LgOp!AX?KOWV^ZFTg)rHtINQ`$pbCgg|A$BCuWG;B$ z3*HeP()UFCChw>c&Ja`Wo6|olA(D!O2O@p@NY{p+z|>+d{*cwXONnhffhf-hEb4u= zlfToFU;})34bs<8lX_{5RxeMJdLNN~cp~0U!C>RELRvjfr2*MEqADC@Z{oS$=+b() z{kA7P)^10Lvej+30i|7EvNLt>V)q$eG1>3RI@$Lh;9{<@vFZ}z+dtog%WyHCaiNwS zdNx{|d|`&h=sN+4hQ8nxpYbFuBT?j%I?WdJ&M4)&bm~3s@J5P zwAtBg(`)||SCYpRq4l)}{%y5>W2&KUxTJROOPXfY&Lhu-Hy=SFm={6zG8<&G+r5na zFA~I$d%V8hbt~9)V}K7aYu8B5HFd;wIKXza$2WrtB%i1EBr^b zyPcep(<&U(E_E)9tARm!47ws#3JL1(otJorn}=NsRAPDEoM1%)!$z`#*p&1I%q$iBJ z&{`AXCTWrt7pFcXK31Re5O5JP0jU?I;)I8oag42%|?=F+X;`7C8Y>KYuDg0J#*|PRTB8yd$U%8P)s^~C= z>c|H-G(MjoiPn$FEAYI&BKtv5)*o2b1wic$&x38l094S7YpHS zduv{XNB~fNU!yj9R%)RZGxi!-6kt2*JSRSSrwIWPm5LARFPXfz*tjw6#s#2J!byi} z>R#uyxYW^vj>R3_AV&xLAz{+imyVOm4eGN{b>=0RY}tDryVpp9B#LmYuel%J=9uhD z_)?Q@wgJvXJ{M6Z%Xg7Q8-2b?nMS#Xo-;YNW?1$^)a6dmIiDM2m|vvF8<7%h5-Ya4 z>x3R(m9fb1bRph`5A5YL>^wT^wQ?HASZSMB`@o^r4iL2lGRI~8`JnN1i9)Y z^YUp7I!)%cyvF$t1l192D%e;O@oBgG_`$Pum;9NdlB>(-yTomrk30)7_=ok39V*XN zR4zaARe4#~>x+z&$(SYmAsc#prfC~cm7tU*wHgszCiYQHiMW{$ZzSPPNevb8uXZowowPgYfWV#7Enzj z$|kIzfmW!`P1Qv~Jm>%xs9+OzR=nH@xd*`V0r6kDOx<%VA9byBQWg)7st;Ac8%CUA z$%`dAzhdY=NYA{l$=o}*=OvzRALGF-cPblJaZzN~1IA!y=G-rYYbey$>hvBi3r-oe z%Cc2>n+RMxmU6#m%?>}hy>Xu${HfQ2gyFZ=JdBrfppNIyK&viPcg)Om%VA^&X>EHb~ zFmYQH@bDsQNx`=8D`$`7s)qM7XE^9z zD>gq&mXx2qmkHmn-4l0^M#dd29ONJKIIQ5N%Zx~r?dxYUuiYOBUfVUi?|DKPew}fibCG00roEJs!FVDBwl4d%N4Nrxc z1@4fy=={P<9JLwloz|{}_Jc14wl0f*iSg0)G^&psGcNAvs|KP}vfjbfSCwkFl{!%^ znvi$ZnZOP6mJKVzXxd15cMiJt+p3BB756LdltT^CSoK}0j4ii=mZf`%N_FHnrEQ>; zr^_+tZ-MlqqU=y4ykO&F-4SE7*oid(MtP8NYrw&24K2h>gH zS-elTr(Oq7_g2ZVW6dIr)!PNZ9y|`@TW&YuW_h!{)coali%Xw&68U2YRpK( zNFqe}+((`1os$Tc++fg}u7e&X;;72^c6vY&Q+|2soS} z=nt|vo&SPiDMwIwykns@F(@MS^_bR#iWP86v|RfAAPPzWRD)h|ynD7|-NMrHIKAUkiRI+%_U6ncoLCANMK6}dcfP4zn*)+{6ov7c zd-OER$4JV#I*^68@ya9)d9Mg{8UJ#>BZaeKuy7@e(c(rg-_NO_Ob)^YZy`PztFDQ+ zHM^TO9wTib)_6gFoV4S&;6t%Uei8Q z+6kqf`(2`<4bv|VF9ht*bf#O!YzJyD?xMq33o8QataM@rE$Rh$uh;3>OTKzY%nMyw zF}ABTJ9*2i^QD;7ncw^lJV^}mPeFeMmJ$2CSJ$E?Hh{j}@ZI*QtSRj^vn%g?T8Oq* z3tRj<7T6f%(7bRK3~5+d6Dc}XR1UWdN;IzfP3>wg)7UHbsGiT3FsrIl&ldiuURs7( zjn()VX+eMj_c)=vXlZS28xE2xDZtgWxFMBV`RLi`=I2QGr{eIII49d0-_!2}VFf&k z^`Rb_99uOUOL(6<2J>YUh^I z1+T+me;8Zk0n1K8bSZ~e>2>M&j&6=`Kj_voh#iMT+-t{c%XiVj<8n}jWR7XBnI!<~=PH>{Z$0uanyO|Ir{t%*|J7yvXSen5 z=c`In87Fz~cQsDau1#fn#pFNRe12Q><%yK`>&KUCgFd$zcztdo)BOQJdxlPL6w5EE zz0k=rtbUL`#80LfW0O>%w@UvnVDGR<^QW!6dA=4undNH$(JSJP&3j#MMJ`}ocs7RS zGVD+O`+BKt4T{ctI_A?20C|7$ypXZ_=99u&KL7v}qaG_0ps+ROw=fnoBM&^^6e)PqqPg zQaNNKR0B;W-;rP^;U_Xcev@kxz63dkiEQwgaTUdw!iYoiXAx%qZJ_IP_I zppJUE+}$97qO(?B%A2v7?7|QM1QMZwCB1qDqJR0NT(9-Ka{a;zj-#ZwM)+aKPwdux zrm>0JzVV7mGG*m_XXC2*40JrV(9N9oKCpu^2?bUnqdY3bU za=3UL*I;9fXgM!oJ)Q;p7=v)!uLX@->TRl;I5<1=?aw_u@h zA?K#mW2G*?W5A@@-is=1JFrV<5r_j3;r04g~Fpz+^RtdFa z6~3;*5|DDYw9cXs5GQV@cYC-S6RxDbua+|9`hxh3X|8E!TwxCC7%ji&@U;t5o5`)}uEH-ad=4}b7`*x7J2bA`bRqJ1zlE6V4#Upur#8Q|wuYHZEtLu8E7w*JV6A~V`Z>-Zu84c007H!Zd|zD@*1**%(a zznMIkDiCb`u=5k3#(y87@rSHg%KV}oFbnLpc^7B*p+MV6DJ9AIwF`YF6!4e2^SC8r z@>R(5oQpl1W2Zt}G#$_R<2HVNbM7wKo$5}bJFr{(hW5~+lIDUfL)GGv4{vL~D}goo zuF0n1MBk;L6QY9Gg3Bb(Y8y)ebriWqLZrTtSVe-IOEvqnW8vulQRULZ@{OF11BJ&; z7q&xjMT!}|qVa^qAoY5eZaz#|+w#9m4P3YYUdSr4(d&zN|6 zX^YOT7cMebI9P6<9^pTxHSl!`U_gFeWb^@}x*f_BC6pqk)Y{;(nMmKjCdlMjz2{=d z0d&xoHL$o~72^#nIi93*oalYqK(;Mlx5?BZd}-@53IfXPG|@msOJ1^yBiu`zTEAzDZmgCTMKRKk9Bw zy7AfI>;v!M?}txvvJhJHhp78P3$L3jd9TZfDQDWLyJXg`9l_4TRQq15z4)#_DxYx5 zaU5s9zJ|F&*^%<79*;wVfdvjt5Xw6B z<=)aJyNjr7R^Mqaq&o=5P=FBhx_I@)<5>d*!To-pirgryV0UU(wEDz=M!}GFU862# z9;?Q+b1I1(k%WiPnm~=8jrh~g^zKl=sTUyM+yG8xdH60|AK4#hf9JhW2p#(Ox&hDg|@-JMTk*)?XFg!lmY5u?6%3}2Mev8YF=)KDD5IEAA=E&R`TgS)y0MbyN zf2Bve{nMq)v(r~HF3PK`Q&}A+6DNgH-minW7SHmacQiPlg-_P8^xjI?-LSB)o!>>0 zS9}f2x7VEXYg}EvF`%@*AQijc)9G3iElJ&ERG)fu6*|bphoG4cb@HkV-**t>%m`M* z)Q|QrPgQR$Z0n8jbk{x-S>+FZUN^#Demw6i?T8}S1vS;;KW7`&6#Clz-uqoeezXmB z5E(L7gz8x{pIAzW)@ON;w=&_P9_5&3t2kSH3l~!CHY*-bGr|@pX+I?vM;678hl*Fk zta8%3m)3eW1g$HSgt#V3)r+-Gx#ju!Fa8riGUz<4+#ai!k!6{lu@g|vN#fRGjQ=&+rFzIBqTMK*x|21rP-@niW6@l~vhv&uRcSwZmim2C zkQOld3|*AmRf}4Srccbf|Di?-AvlF`iRvo4Zg@O7Jg?uMJyXYUJAM_K_J>Sp*SJ4O z8kFTxL0dW2*c-y%>LW=K-Dir8%fZ*GhG|D|Dwtqr|9P>!;T>*sBm+|bQm8{1xWl%V z_kNww9~v`s#M6kRVZ|qSJaUOHbA8iQ^DvzQg`%;XWO1$57sCZ~;}$-j4-yx}zWWHj z>rf9x9sBHf`8u<`$HMjlWQIl^R13m@+9Tw zW4yD0%s%W%r~lq?mwj(|OoM-#s_dL>1ZowQFp?vw>6lwMF7IaAOewj`yau48P284=Nn;&@kUWL^o?vQl;kahYh)Wg@QK=?&0CSP37 zZ}Yu~3=-y5R|&6++n&MKxjoa*0|W*TmP(L@{NffbP7@N)z!31AD3Jx6!xrrifdTPI zOOq@siwOS{#B>sZs0u$=O%16H$jx*-p(lvUUB_;_4!E?Ol!gBx3(P+RsH#BQwJj~2 z*-1M2rT~mb(?IRBEhCzHtY`wYSTmSh{gik=t@5J96p+f>%C0YfTD&nQDU<`9!2j!H zIHMvX2KBwP+4vSQe{{(4>d>tm_dz~Bu_05!22ZE}B5%13r zYD&3`-ODRB=s|h9icq9gzI9&xR44{PneKV%hLfoHmww|uFRI>nKt=(20!STl$@kH3 z^2zRzr_rIYF_lC*XA@0;2Sc$rL_;#!2_}w=%Vh)6lM3ZH7(O1)wgu4Y)hd7gAv>oH zA|nU{oym@qsJIp;6$uLd=qk$m_*7uei?+ejM~k7um!8_XeLHz-aFrYoE(GRhv2rFX7u?MQoIi)RXoZXPt8VB);>LvhA;QRmh^&9=nMOW8R)F6 z6H$l@n-SJU;apy;j=ZmqB;%y3k_G$=|1Ib9f;6dr(@Uk7R*ayxDo^~#w6)A^M#!8Q zzbnkBa48^#>$ZTtoJpCo%c`#OEyJ>+i$oG7CJg=0xTux#Ml32?7rZ^=c1}fr-iy2z zDL%sSFDRVMEkEH=u;t>cz`WWoKVbebz{VEh$a8|=aJmaOg0xE>4N)t00OhjS2%%8m zuDGF3fp0osh0@KEt}pxSASH1D0y5q@&uZrN(DUo>*_~9VF1l%JScct;an9YkQ-n^g zVTe=^C!@l%FT1x(%?FVlT51khRrKf%P0J{pPS22Ha76wV9cQ9?J@Ot={TS+im7cMG zDz0yRAQR#c2*~l#f`M}!iCPUGe|^!Nn*qmi?8u@!0HjvW6np$DI`ic>Pc!=W5eHAB zbGW#rDgac}fp#-{zVZBI z^BzGJ{~Z4E0jbb-(POHz^!K*l+A8eqDZnhJ>YuUvUyQwXR8w8MFNzh#!mEHtjY^X) zy%QAy0qKN5Xd+Dr9qEwR5Tr%AG(!tLgcf@59ce*&@4Z6^dGGSucaL-T828+J{>TU< zizLjsvgUlAUmF;in?(^IbV20Es7 z>0gReMiMCC{ki?l9oE76$;6AhjH(C99UlP9(~vd$zxA5XDRi;t7yA#?0cEfn7w%#A zcSGv(@(!uNxi-HqCHW+rYScAcMAiw~s?T|mKsi(GHrX&4CQYf&`2$7#r8K1HQSGU? zzKZ>D&N6LsU!tl?r{L1)u15c!)JEo9>S0Di#z2khlTN13`T4>(3 z&BZa5gx9ovuJ#vaTpng`a-SOfvP zq?3c1Rau&}@eN}8n7~O;k9|XGV+Rg8KoTCOeJ8`){WY*u=b1Yz3AJR(ov|Lr$WMZL z^gJ-=XZrSnr4eVc+uss$=bZunwvescqqdu8o<26y^}_Q#@>blwF!~rKyYdnf2O>Jv zx!3P1v;@07Qip~AI z{(1m-35cbv-=8uQt!m%7`I#x4EzI{a<+S_?$_{f5L@B&4-jq}4 zUkapr{j-P1bh^hed+kB8e4^F-0*8ObP1}|Y%^yY=M>IG#QM`X~&+~sNy4pwHdO@#zJINEY71(jACT+V{)wiM^!duBBxaq4F zQOtr%g0u8=eZAS!#^P&E0vt#~4r_2uF6ktrgKp2g2(owg$W96@KC|p^#V1C^Gn|sX z8Yx;jLj#w7)yW^5=ly=8LrA0fu#fkTJQH~^As}G!0V}tQujL}wM2ric=~nndL_KV` zId1Nc7QF=6hx)(;^4ed$wWQ5-q@AwQ#k)T(ptME}UT5;~tozVDN8{#R4?MYJ0fC~X=ifWFc! zmcaDYs}X3mKj2??g|E5FhI@~w427O~Lw4Xqwv~g>Whr$@4Xx#6kLl^GX0mzawpjfF z>Mkz8&pdDKxkMb?xs!DpBNB6QBcIPA1(%$oK9Iws3u`UC(B2-(&U-2L(1m&ywpUx#iR}EEwSPRlWN2|OeNb6cH+j^RmfQ<3-*ufV^kFH+k5O?vtCt>Uh|{rbrrA`=L25;#V(#Y{WQ&v#qWXp@AdOm z*hpqfmg4f%WL+yuU>?n%OP#p1diWjo{<&IuZAkyvcESUq^dcgMID#9?npz^pW|WtkwRwA+Rjdhj5O9NXa)Yqotse|Ev!0;U?0oj07dxk!$N{gah$%MV+{ z4Y>Q3pRPphl3acek8QpCd@^>*J)IiuBaZu<(cfX3t^5!4zX{RxSXfPk{&@#rF~6e^ zdi_@RhUS8HDT88{+hpI5E|#*D3X-%hWKd2RH_%-_TQGo;S>?91ck1tNTTliDp?@N^ zw|O^EL1g;!)38~l>es4WgDnE~i~myC-%bT-w=b9suL}rtaWQ`Pw~oyL60?rW;P7>q zzQj4d!TZ3j$_0uPJarh24QvrDEx7?JpfWU)Oay}NY}P!`F6)=UM--nf`~pI@VrE%LpBmF)gpcbmtS^q^5l zUwd6N44*M09+hi2oo>Fhtn%Vt3inUBd^2G@VN*)*<@Da`8Nb?ps}5=iS|b9D-Uv9% z$0Ig_m=SDZ2NGLmxwlX>tK&X(inV#F-K!==q}W>AEV&jGgkV~Q-h3MQ8XG%p>I(Vo z@aTLO(2_s%b03`tf}OTt?^&!qUoPudcfH%%*iO3Tj+krxc{<$5-6eQh0Cume?;s(+ zIlF#ylI%p@QQP@*K(^)9(6m#>u9*e09Y0ziM1$-eh;J!JPM4Z^(xELjsK-z(9um{n z$ek+xQVeZodPH7#N`#9mTw1$;x75kC+fuix!#6cT!!5kUU9SdQpF8R|b2Fx^865Ad zWBUFCk(l-_>wvbcS%^K>qLV8Jm({k?&lIcOjnRZT_)e>cmY!|o98}20t;dHMf3V5e z$x5`XMLw=Pk{zguTRKcfZI5=LUrRU>wX3J&C_FM64s(BtQOvB+lGVjS2QN)}$`1OW zVX9zh{fCvB+sj`#p)9p`IFWs}!rXtLaz@7vqxquXp!>-8#_e`-4^X#tR9_ZcbUAC< ze}wxUXYa8l=dCBO#KcTOb;dJr5|MMC9eHT)OZInp;iwksMX$5e$N000s8t+jKk(4T4k&)BiRc4-cRfV=r4nnE z+uhWD)Rw@WD%yw9zAIB0OC%&169*lSF&&xdi!zUTnR+?bRrBalw%SKUzbU-FCNMBv z(3r;9v!yMJRxM1g?+&(4ti3LmS4C^N;3j6sZSch@J4gF7jy4f0ivf2(uYCsh(zcz7 z;rYJWs(%(JCa@lO8Kb!9tnQxvOP`e~cyPdBdVT*!W80dZ&0cm|iTC5_>>f(v+oRgM zGb#?6t>eaml!^DEMZR%(X{i9>(aCisxqc8!NWg7=Sox_g(zWvFZj#C;z0Xt>HQ^O3 za8)75W41?Bl`M#aGI03f_BJ4fgQ4)y@ci~SkzVHzKn>TfS_F8Xg6xucXmf@E?^7t| zO>HhmP8^V&ihnXhk9{qpb!8MIXZzRU)DyU`Z`Cx7rl<|z8PpA+kg~O<$MFAGJ+toc z{{ff*=7)bJaJTJ3Pjc+UQ*I=rnd?5wp47T}TYC5|Pq)u7-_y%^!Jl8~C+XdNdO0Hm zl0oPC0ZEukCbuWFN`_6a z#b^C}nPs>Q;vN#~9ep6z($5!a_-8Q+Dpsp~r27CHySndV+J8~lFZ-%(gxq`;JJfmgOS)34x~D1YX={${ zgvBtM(Wx>MdGpKOD!f0t0CozK46rMz)Q$@8Aqu`Y4M;ovVyEz-un)NuI>U=##SgB? zhAaA|4n;H;;F^*5@u<67sNQp{Y{02dBx%-{HLcE!?#D&GY@H^lFME`1v8sx7%Y>QU z)^uP-?>sF~RyeIpTd&qxO4R&$oCpAkGmtT(DFyF`kvDbT_bY{cqC22_4{hoic{1;= zWCzQ9YkGR?O;u-*TnVz!70hNpkG_jzW1r|}?p~eY#wn!Xv%+zjTV})4Vm7QwmQ6D~aG?1DsM?~z~l;~5|O=@jlp4EF87<>rOfHbwBlOj5)NP@ zXEyY)^UuUgsPXb+!OqV$)Jj0JP($qU6;>2G=n!N#BloQZWt<5G_I)D>^MCJ zap-U{XT-~TU6W4rpry(*q0zefCs!eT=~2!a6sV$-GzU{>122Cv#oclt`o}O z5?am&xYOBODc znEl~-1LUix6RmcEhE-+19UdxQ0zQu?g9IA&43@_L@&b5uo>^S8^Lt>R$(JQhxN2g$MpwT8UX{j|DlNad#TAwaEx)wGroaM7w|2& zA|_PN&D`n78N2-4iYDz_9I_s*Re2;jVJ7m$_rAUu9X?Ok-}73XyZEyq*s+oWQBbTz zrJM?ks@~$8HJ&`0Y+f=;DF{v!?Q~*N;mvo+?zEP?T!HnSzb>JWdHY!6F8J^sS!`B` zZm$H8u|-PVk5O`mW#VnpTkF=}em#8AE%6(A6YI6VfBwPa<5=^MGgyk`i=YF_J&ax4 z$4mTE!&wv*CVz;ROk?Ki$4-n1{PF`xS=e*)=wL;`$HY%VXQP}>$(GCoXaUMbcDqP1u?3AT&|7@@L6|cPfA?M2s*-;@;CpO>56JS_|XP|GxYr&`c<9SP<5^ zXA`hZ0u^XtrnhV@C;~OB)_v}op6@EmUq!J09(rB*wkj6=P&Si1gxavZAXDGmjzqPj-zqwc%Spt)=oKeF{;0ZZT8#NfymplIgRqmERrDXn@I+bo~ z<|=|4W-!(`SF0U60lx=#ZKrZ|E2_Qg!?=xj?8h-ka$z!lWOT=XI(A)b?jp&P^#Z>9 zF9ofavfeHt#r{af;+DG#CHJEv-RU~rn=QC+Y0yddjpU$P{sG zJvOvg^cwj5Cu*XzBjSbo&aI}5JAiPw+J5FeS?DfG2$$3yRbYw-ZYIl17~S`Yo2wfo3##>cG*=ajVD$HJgj0 z#6?k?YEB=JH^}G?8}g+b4=SXNX;ofSUxE-E=haa4Wii@c z6WLbNMSaz)dhTw<36TluxW

+I6d0t#%pb$lh{p!%E#Grkb)uIx+%*ZCorFio?lLa5Gq?% z4mqWMHI$8N9J**b*_<5G%*NFL*3)yo+9c;^AFFN{Xhb_ zT@KzK(6NKlazP=UOTIs0nNje37`_(J>^Q7TvCbajp6q!xPhc-4%>NPVMVU1Cbshl( znB$KM6fZjDZe&>9#u!|tzRGw37waq>%jegI!EFH_#o6?Zp5g?CXt^UG1Oz#oz8uUu z?B}vO#U8G9!7W~K_G`)q{UhumRauZ+L6H0a(%#;UCv? z?EH{E2r-DHBB`0O?p~k*4nrIyG(I_OJ<`ez7CJ@y45kH>Es~aWG~7I$Jp6-Icps$& z|LW>9c{%qez*7d)J)JD=h85FDsQL9>Ak9@9>U(#nbPcbD`ApZ%npMb(UrP{2-9_0w z3AO6yyXee(4`YV$XDgmzoa)G#r5nUAU%hk~I5@tyOsk z3qa<%VBf#|pON8a_?*K&dsju20>6jeGC6-M9?!AzMfRpw=AvVu7Qx*9%qBJXJ~*Vn zsQg90Sn|0(;*Zk8R^9DgmgPT{zyT>vwPR^t!>2+}DMz^Av2v};oouR0KVz+>_}T$N z^Iw@7x2x^blxvgz?zEQ{nQXj@H}>sBwq06Z>sP=Ba> zTCk*b<7t%YP?o7VWd=a|x_9zoZM5Lor4pcX(jktxH}rN-IgI~WU$r~Ujl-Oe?;Ymc z+s0^j`(7-vQW9!?4KCuybQ_6v1GCA(;!g8;rH_C&&sS*nz;lqa9lFq_X=1Bwn#D-d zVyL5*ox1T;ftuD|iNL9;aiZXZjR(`8-@l8d?%?-#QKayb%11Uz9^Gh^hK6CYV{ZP};yIpXE3GYl{i%;^C6f?tHH=WJYJqs7W_7Niw@rbrG3umz6}=E1LgC z4?5xC{Q0ILpNbzLAXh-&^Sj8V3#?DQr;vH(Q`s-pE>@<_JkI+|8s64nS-nY`yTAs$ zUR=&OTM&mmoRHey&Q$Y#|4%1hF*DCo2KIzsbuTWm4hly?r%;2N3|C$BX5fX zEvP`yelPM5B`$~ca~(QxpYe>$ua%YYpg0bQ=Sq_-GWa=Xdmu+-2DjtF>5;TYZDqxg zYRJ2=q6fQ+DBuKM!tAR4HdV5CSPfRruD<{LP2DWsC0c!fwFw5r}h*;(o)-v_3ic zj^DjKqdCXC-Sn1z%=(qS@+d*LSNcs^L|uy~OWyG`695VM)P|07SPi8gpw1j?`o`TM z>e5LjfcLAHBW=y+8?)grGSWVBRn%2hK@7J!An z_BW@PtoG`gp3JdZJ28`B2;Bwjo44!~`J(mgonM zx%F`JX5^!1Y)(bylkSodOnqoY!|?@}d!e_tSPW5x4B!95ynP(qA;^m87L(mTz;btUDy-Jp~kc!?fn zBsRl_`49|#-~`KCECq4z*#fBdo-t|ptF*6}-7zs%^LH0(=`l4-&hU`?lN4o^xn~4e z<}_KUoDV>e98Rs}C!k->gRv4U-+K}Uss$74XCu!$etz09Gaz@{IsocX0HPN&949Kq zR~KD!Iem*F)T#2WBQKe$k~^gn%3^S9t#w|@;m&nE88l~DuSpikq23hqxQ#6pRQxE*y9>E+3ei=61W^ac7mmm2x?= z&i)qQ8t*?m@`m1DQE&?$yHDB(Hhj6T!?rdlxe7k-I4w6%6kLua)Xj5Sc5h?0qPm0teL@}gG&JI*h zh>=D;j=;!b*sWmV%(2U!6N#Pmvf53wJ0TXZHIS11+5Z&DhdRCEhpIr^9chj=w^FB) zUIurfAB-niQ|fq4%Ugm?0iMApMk1N6z2>^DX8d`{iCMo>TYHa-z)cI`wK3n{Cvn}# zre!2R$U!#o?%hA{LRn#s1?CzSmd~4a-y(%fz0I`9!{aQqqhCKmTJ9&bf9sB_!2Z z)T#o&xG|vuD!~{5ZjS+Hn)h@^{hLGCxB9-sEfM`x6v>4i_ODA17xnb?c78?kJ>g(cb2`}Y35m?aycP>h1wWF*K8|N zu%{Fjj`PiI<>BF}#(2K6K?!DidiB+gE!=1SnbsprVPx%+kL0<##i%RYQB9l1wQ*>H3Xr z>3Fdq5_XRVZ6ldW*+S#kc`uE4Das(Ab}j6%_k(VOPB<}Hbf5Ta%6OIf`@_6zroJx0 znd2>k*L!ei>xTUN!EJebsk2^ssrua4^g9t=({)2}_7`^7q~g4l>;-(EGvSziAW^Fkk08Cfn1 zTuOq6Vs0~~dt@Br&+}$7r~3N(cMx=`AUb{8D;T3t=oq?x(9@G&SwB5@z#~t4i2avz z2}oN@S^xe=PStoBJr&(77)6X7Bzq8$<3!kQ5E4p{QYgbmo*ZZDg*>N{8UBJ-!gElt ztPKwklAqr-jV`5n`k$UtmagsL|L~XpZ{E`1dqSqz>*2PP8*5=YjBu^1>e_|>0U-?Z z1bCXMz6Vg~yJ$&|#Io4Y(_VrQ@?PUz2q_WoFNfyoEdjY%PexRrSPGl2x)BX4EQ5Yd zSLvl>o)HE@=`su>{rkFJx8V>D4}XJ4I|JYY=iFZ?!j@11{2PD8I3|Nf*u;RpPJD!q zLXPxUYh!+U0A1(?@S7S3)RV0EbvJq#Ey&w`9Q~5$@$zi;Sv}1 zjKz`I?>q1rO}2@y!V)ZGM7!!6z)@<_&-%8dNXTJT(g!Dz>EcY3zq~zjtN+#8=GKs5228PmS@`c8WJ}PvegJdd(4^b3`8=$V z7@V&7CM^TY@qsdH70e{?_7-cNodA7SGIiHX&>G++w@340q$y};keixRlDG)Q`mHE> zLH3RL9o|)%#ho#=m8SWdFn0=n3mX|eK!?)@B~mys-Fq z(C(35+S$L%+miP~AGN!To^>p`l`D4~ypNSxh-ALCC5p>?es*!^!#J|l?C#7gQ(2kC zxFy>Wj1X$nP->HFl{8 za$r-`f#$3@dz$qJ_C+KUf&yDoKPqB&lb&w~tF8YXG{k>K237 z<3N_iTm{9VK145Q$?WSM{pVAAh=C?sw5_tKl?1ns>*|c}6gpvfnsopx+07sMc|Bv| zune^)j3rs>P;hpU!Gro?%ooIBp91c-kt?!0o0Ju>3;`%RFB0s4#;jnvjrbSe{=w zFtJPTIT)2LxK9*pNlW;`Bl6ZQ3e0iYtv3zRFuY)<7n!FwJd#j)4V+P+t=K+J=bwC zm#@!syM;K$!T~M5&cRkTtGNcT*i(vUZxWJXAam-_ALRQYZ!}eis1EuB%mOs_&0Exb zTw|lGl~SY)Lc=MjCfD^5Q-e)$LXdWGi!a8yXeLV@MDv}O1MbiKll|2B){K=Y7R=m!<{ z$TPMrTkWiuRLM`XTkRu@fp$+-*ysOUS2W|Zi0DAuU5RIAJ;NVzTLGKrM~gaF#y)gE zEZumR65x@BTiJo&`|rWtYb{$(iBLzlFUEW2wZu*z6d)_eyLs=|K-0XD@tKl~WHzX{f1d^g>fm%G; z@)4;JHwBu9=k8KBZW*5g6b!p?GiSQDo zS3&hU84G(jMYC~<%>))~ZD!E5MVEZ5jJOkpD-0BFr_km-YfrR=a2Id$=}?PwSQ~^* zQgTRz-#sSLe`?F&-FBD_w=3q=k<$$lc)*XI!bE=9d(nIw12k0I3yk-zeqo`9kYdTLod7JrZ0zS$I#A@u~sSZ$O#g?+Z;Ky#`e3 zdsj5>KYlGHIVyglHV}AXG@`j?*7k6kIaZ-HI(6PCM<>P#31=uv9P$?HS)k8IXEjt- zD#epl?!wS@@{W6P!P|be^S8ou)*f(1QAG&8dhr{=LIbPbJ z^3le=FRx=A&MX{$1ozDjXE3U-kZU~36(fhuIvc{f)@BQTgccT138@)Wz&hQl;DnXJ zXm9&6`IcSHP<~m5l;-U59|Z`*)P5n!b?U?8JjS;83?M9eMRoXb_~O&45z~!ke&h&iLe6bacm7P*(8gmBTsou)0eAg9&`_J zd!6+kVbitqBbG<52DkrOw7vIaUD(U6dq^^_-hGo}<6U>4Xwl={-Msy4dSnA}>9i6) zuM!@W-&SQ>%^)Nz>>OD*8_=&n?j(r-zNPob*CsYt9nIRxUJ$`*u@) z>9ViuNZsIS)~GE!@39!z114PS4Qi#nm6_;O6;`$NZFXLfZN*E_Rj(Tu{ zJm~qwbTM?n0}Aq3bD#75int54J?TZhvWb6Ha$B~r4_q@XU%%@in?EB+JZ98$*x`rb zNGzz^X~|DS?IGW8WR4!R%<;H7CzQZM5s#mC-FJyBd7((FcmMyW9X&*n+r68$$JF9% z3$wS3m5SAoHvqz$`*zC%j;J5PW5@O5uV}iI;QLX$MzZ zusAt!Om@<$nkq?BKr>D~oA*}BW`8iw1@_GhrUG7uG%8=!p5Ad?h`N}uo5rn~-kIZw zX|yORx;QK|>#FascR)q-2u+Wj^B}30fq_93c$xpr1O{%GMXu?nG%!cP=gh_@j>{bE z)cUWUasmR$jMnV+-{m5|zCHbkqp zTgDHpzcWguvR3nQ6ZsBk)Y<#yGboE$|D=1X>9kH)q0R}kZ4^q%>vTUy<#an6=RmXZ zYh+-kpz}5Z*Jz<3hyf5w+9@0(9+A;i>=nBuuOsy!2nqPx;#a|pNBjA>dr9xozc%xh zkEWRz?JLXK{cdjTvynMh_w!?AEJrt)vQ_}#Oigzg@vkO~wL^JQ_hMg~NbPfaawK{l z^4+n3{g*AHVaB^1wxkjvDRwk0yuLu#7)>29#}?3xgAz2WFJwTsf?70bB&2{aIMcnJ z|C96lKhVpd*RA>MCA%|bDE$Ee+4zPrc1IEBoGAlOP*-IYFXOQ7Ja-o$`&EL89>23A zifmw+j%NnPd%^e`32!=ryi-wE!Pj%gM!E->a~DGaCG?!pcWP?@hq#~++lSEYf!CE3 z`};S|vP7|GKhGa}$QKSE9dDSf3Sj3vgC~DkmQ>vB2AUCXMb1Wl%U?SUOYwU>NS;ZV z!Hx@DExK1`@O^XL8<16tC`zuJgxCXm(B?AHCA}3OmspqM9X(`U#hvVrG47g$9&T{}D0h@ySSW7FqQHVcq2! z_O4}x$bz#r9thSA9@8a=OkS1-IeU?KHR>;?!|KewhrtkAufdhL4c$)?^ltlA>jWd- zc!!m+v|sc>olLjs-a5Y^+3^6~?z|@MIb=v&$;(gt_}8&V&(|uJ%z(MnK{D>GlN-B> zB6^-h7demHf)C8NQa9R+JD&kX@9(Go?ar_&do@C3zWNdmCDV6`(1Y+hzJuaRbO$G2 zCY-*P0$a$;rdl#6j_$OcS^1(k33rUtN0c<~1F&m$eJ$~c6&;6=?a^5%YT%!g1+0v_ zh-m1aHp%RzN@D{1Bs7LOTnWBCb^U#f)$Va``LdjX=8azRp%=ISK6{ZrrNO(28XJX3 zqnm1_Zgv}Xauku6*bdFjGMvQ>@&P}dvLqxISsi_)O*FA-u%JA&UJRHp5bNa2m)C5>Nv9qGp>o;(4eA(HNUbK@>fSH{tJ>=%5`a z)Z{&N9Z-L&r!s3FpRKPC3ZrUmjPg{ObY)|m>Mv*6n5h#YseYNO59lbjBonH1 z>5{-x3)eahwTZLPwIrdqp{BuD&+x&2PW@((1K#LgE)S#u|C+96K7D5NX9!%!zUDZ5 z{?Um0>lz^oPKW%&o@y&u(b_ojWw7p+Dea8$1&<0Qa@{5YYHJk{B2(09&BdNz%{%8N z+mvY&@{1>P$7<|@^4QYpL#tB*^PIz}6Mut7*6oo^vtn|g=uVL97|s67xHR?2k3dk0 z-99L%*WpycRQ}1aeoTkEFtBESd zX||l8#+zRrl-ANfA?(e(6Ef6F44_2GX~K0H-`jiddD$G!t}kCJ3wc z(T61X0{@j4wR@a+IL6?mRZT@yH>6!t$Dd*y5pz^y^C?N>^++aeO9x+t$J7hfoQ2c0 zDH*zDX-|xmBiWDYS58>>&bd$ZGJMK|tTaFmobSs}$9IrCPz}Q~40Vt0h|KSN-O_(! zw5F3WO5tI9gYsVr=9N91!QkeHnSi>>uj88x);wC5qN)oStcfK^>C?QHgroLg*%!z> zph}^ z&j7#H*exR3jN}UJ*30W2ZU|*h@mJl-Xy||H2^s`8flmZK?e)59-Qa{*`m!gui<2eccPqrVI^rmZ+NDDPXFcBJ1P32&BMr<~O!gngOp z$6rB^?HW^@L*aAy1q7 zC6$E1jCDwyoQgQ<=tx>CnO+NqfU&bbZkE|d0c`KH7Q;-Dpw(a8sM z-#gG{R5<85pm3VVg1i{j!FU-D~ry zQB>O}s^C=4O8fXm8~LVOm3iQk@Xe77M&CFeEfq_rf6bFiJxTOcWcGoI2-G@Hv1lQS zc{1V-)J`%Y$eC3OaU*dpn;y;lxn#}=f|~nnB;u9XJ3HzvU*lP|vn$3~N!)&O8z#5- z!|?VS;m}*YgEoq8IAzd1+)sa%hFoE<&mQO1|M-g-@;{Qxk!@Zx`LHXRhKEY8&AxB+ zlQwL@qK_I|Xx6uTCjAlb0=^U9WC7mrLFW3CZ3ZK)%QfD)3+V^NoCb`T1m zE}dW7AnGvCj<9zwZ;JG=)?-+$9!>PqiU!pz(Bb1=2{>+EZP-(*p3YHmhUw&?`Y=Y> z3vJ6+&!Gw_gZj$S`H4Pp^wZzo*27YWu?t^y)r~6Yw+qxI=Xm5S-xS$_?`9?}#XSOe zx8HIV{GWWOba@pw=y0aDTuj7jz}dkCN~2cTtTokth^W4j*u8_Hgde8hBCIJ@?jP;8 z#_jG2xz?vH6b;%uF*6p~xo-{Gb?!?JXoLcPer`iYTYnvl z^-wI!T$xVQ=bZtt=34zib+Gp;xPbRP9#lP@gjF}gsFW^9&X>kANRF|IeYc$|1WC}& z-IQCqoZz#aMr#a7pxrQ;=DR9S8Wa{D=|~lR+Pt;#va<~N>bh!EU z@-irkPGxNvIi+@UPWoXd-BU}g4Vt#zA_2O^D_afKEqdnmyZO-(A*Dn;!fw0>AU}o0 znKD z^|tHy^>9n0)}Qthj8#eQo%8uBbA)gAz^^Pm{t?@hwhnN}EVU0|;H8fAUcb~qcBg9x z`kT1s_?QXX>jLRR7~lG_nnJalv%&ctTT>ksfZz~WKL5^7eivJpgDFplk7wuFT|g6R znVQKg(k3kdcj?MdDNOZk*{3#YDqh&)@PxPc;%JKK3k)E zuq-~@%?BxTu0oJ`7M|gEwQP&GgsAW=&~U8sbDB13y}e;>eHuK4>X($9$aK|sX|1by z0NN7ftCu(aksanUbWOFCB5yi_Wi4bJJ^qooHs^3;Lu2bXRcUF6MhfMBcky-CqKW?x zXa4_XLiKkGq@a$mQ>C!bRhP?&zQpA6#$2Z`laV5zGW)0Aa+)3BIi*!R5(^86!&5-q zvn^qz^QnLFmJo;~tR6r*9(;VNiq}xYazFSF*djc_9b3AjiV@bj{$|ba00$cdkdqIc zgpa~Ds(s0DQ$WMvxAvTY1_$e@)WG9~2_{{D^_d!gxh{;SISh1r zgd*IG*Snr|n0qs9x~c13jL&Dydb|&)88x0cNNTm1@6hjZ3t;?8@$)CK>c}j6zFuS@ z{AT~brkv~qU)GkbPL&I)?N?Z*axT8CddT7kai`UMci2uTuN1>id|y9XQVkHB0H0Cn zhd0^JsgEHWZpVqYx#Tg3HBw#|o_cJ>WH+o7{nnk}Q2t=*pNXfe>po<DQy4! z$-ZIvd&ldCB;x2X^410WDO^+=lROxEKMNU-o}ufhb1B~Tc6S{wBHUg1JYa$hlBYe5 zYp(ufbiMKuatV*yxi04{Mb`o3;6gs>vnbqVB&T$_P2%KJkCO6esDAI<r?FZ9+??*NviW0V&bNxM!FcE|&Vnop*N>1QEU-+wi}UgZY%|0Of(j z&%fUd*VhAO+VRx6N&2;@P%*3o$Y!|UAL=p#!s zF_$bz0u!2xa6737inl`x>T=!8M7^9EiKC$c33r&(D~8$4YRt`IRyxn%LNqSSqrH;R9Ma3aAdcHAq zvkA!7{(lVLs_=Q*$*3lg-&Glb!r=`yLpP4zTav$3@mN+=`Em#|{&fYt!srG&M zM12)S6ane&RZygf^q!zd7myC2MCl~-8fsJolokO2sZr@5L@81PqO?fwy$1*oYN!E1 zJlpT@%$%87>-=WT{ILlu?65bRU7qK@uIqDuX&Tl&X(6H*C&L()wQWa7zt&jTgLfEB z2?K6|Ksw3!D)Q$=w@QnHXgqXODHnGSW9@l$O%K@n2S8av<^ow<%NJd7j=IhW5gkl3 z!5zFgR4$1*keZL@qlTf*4qd?uw1eQ48SHkY=~CAI1K!J8Z__28=TYlHl2PK9T9 zJ$+@V{Cl|Z=fG$dX6ve(XAx$ng1Y^=(U-~?cJB{OR~-1LM;Lh2*rxv7rZl!1VDX8t zjk4MQF2X#g{u&Ani()vPH*sIc7CISkA>S85!i=eAd=@r;e~FRjMOS8I*Y_4`3!~*2 z-*q?iT_Hm3`26TVcad($=M+Rvka|FJsLXrk&PHSEiCwYY&XF-{OIk9Fi)Db@iP!4M z(B!WJg%}aL#b!u#Q=nxf!{KFEZ$>*|8gC&0RAH)Kn?Hd)LeeLTX{)4Pyjhj<2`B|V zJwN}A#$WJ!Q|k^D?L6N{Yt_abZd09)$-Mh3sr5d=(n$~Mz6=Ph>Hq+ z=rbCqdq1lpv}7!X-h;tT(*PH>dW-yXl3(rfx=-rR+o_8~SszqbuoG0% zC28~ZEW_qwPqyXCE-86iag(vOD}L{x8cl?%z$dH4`ZD}o{Obm9pbT!HTdw~~SYUE( zM#o~L;toM2@a4vkM~yqP#UON%YQJ@>*TYp!C)!$2^%|CzDlYqaz$IfizlxybzGc1i z6IqW0Hn$GG0pfE7z|7L`l2~F6WqPXdaVdTF!~$%R&-Giq${am_BG=3BQ2;fZ&3>F| zXim;u{zC&6+Gg9l}{Pt|GKQy(8s2jgSfUT(6 zdg2)v<`DL#nfk-eA6T~{F9FTrz2J)2FY*!mo#aJ&|E`yfQdq3D>M9 zSN=Rw1MF?G#vp7l)S284nSwm~V-K;wOCkq6O#m0tJ;gga z{6e>PC|DmkY59c9SYJ*@Y@)Wt@5>CD@*{I{tS%0wsMmsj+e7BZ-;F0J=_WOAu`f0{ zOnDdf{PvzM2u2N?CsK^bYTol}0>geIA=xYm27xt)o~B0>;!!I@LgT?7YhOl^uPE@PmoqO4MgWrwT5^o|Mu+)E%^N3H;>51Lm+GNP z=?l#4H*4``TOmh3sTi^+zO)$Q^Lcd$9wI&3&{eY9Tce+iD3*3bM3|t=NY|*j?ranM zIRP2+W3SQ`c$9`@upHLbuJ5L7wYWu`14(kDU&xv*+jwAVSpP`2B~Y>*%I6<~?vgo( zANvWtIF0bp6IlJqGmygOCME9{wt428LBxm4bs(55o?H^nD%kjv>$G@rYo<;m;2ENs4&?D1MpMJz&jOxwbDATw6`tH-vUrZ1{(EF)Ewg zHGhvS6&DEWQS{EecvG6E1e5%N0e?m?IaU^zk4GU$45_=Rd*C!Zoi$C6EHMS4CMEBaPW5# zS?-%+KFs7}@SAAhS;$NQ-EBaznH$!~GCtT$NP4igs<2C@mw^@J6^%Jr-M+v~@z%$Ow6BCB_e!XHN((M6_=?2_$vv z>oO?M5@S!JB8L{EPmbnf?9-MLg2K`1CVKzB|#IE6H$kMA=7jzlwq_< z9`Rj8T;Hr_=#%i#N$h>2Nh!+oUL^Gu){t^xUWIP~6X_PJ@(EH_7Fjayy{9$Tx)t(G zIT;`b(}lCTplK<5t_x>O+?wojDqW~q>rTxcezfu0_%m~RRp5;HUyE;(DCzQ$Soe+Z z9u9m*zYj`J4y$?NogD1bxn4t!Z5{pn?<}|Uhll1X2CDFZm#8FC}&XEzP4ajgb?Yjf9?WxPva*Rl6*v-|Gp zoV_>K=elOj0g(@8BxGeL-Ts@W(VpN(lP5^8`W6hLAy3W1>=tw;t(>t(Q{&;)JF?Yf zw&YmT`r+y;vxME{?j)TRfn-RIGO0Zu0GgyJHsuQ?Sz0X_EX0T0{# z$;uo_YZC``bs&F%xHw`{g#%Z=1Ls0h>pbxF#s8lLv~-5@j~)(ZjJ3St`E|C7ZsoM_ zIxSThK3)0?X|KduLpJsGYB|4Xn3%T8qPdR=#w;b=HB9i0c{-I15CJI$cQNgK$zTsL z74xS%`G+8<1Q+eYixz-~*{7-Ctakfc?M`-i__N9`RGWHeCA8m~qvtF#nm|3GzVCa4 z`U!YKFx9gE*>OnHEVH+y#$_WMhl)t$U{xRenj0r|Wiwg)j(z~cPk#!$r``Tj1f;Fg z=5u*3<^FXltwY8d>jFiertB!vY)a^Ru*+JD?{Sv0u$wQ6LR~4%`<7h0b zK9r@sn6)&eh`6iyT_9oFMg z9pc#KPf~hqpa-%+KW0V3^!^>EsD5v{x(l@|o+19$Nj!F^tmD+fWKPXj zKQF2d_^Z~zL!w@yPVd)I;ZSM&oiap8^hjlJS6)WiEarGRfvfBwt|ED}a2mjewFFRE zMkw-RWC)45)zI~@WMHbCm$1&kD2N%}KVO7UYlcL}S9gVpJc$h*WFu+iO}RgOaZf9t?XrSJ zF3$~Qjz0Voxsjx^h}Wn){Y-Kh{i6PbHhyj&@UWm(MP95_ySLVD_;P%?%dB(ru*S+2 zsXh>TCb>Y#u(+&jCI}gt>pW9|8WyUMZwgaQYI9jgY@p^}sNH+NDMBub9|`aJ0Ed+` z@=ZTExkbVy(Dz))TE{mQlw>n#ox$1<{LqFF3!oIq=BC5`u_E`%%D34&lsCe+g5>*V zIF|5DoRy8WLms(x)j7IWZ+e$f*@TH<4_RuygsPKdv5tp&YSvBl)hf?}w9HOkj*&1! z71RfS|VdGhWgt(P_jtjHzYCdA5_b)CD&eJ`&3mJ3>a~-GM;)57SP2HRx43l&P2xs2* z+Ins=a_5E#C9Ts&Ax_ECLwD!uvDtD#p0H{rh3KUr%O6hZ0&h7}1Ag)r6zP>)X&&in zAt%_+;4Vg4bM@t}bpFDjbc7Gj5Ayd^Xjppt@Ivf%@*}jRKCrxuw$_MCYJk>;|6!jt zl6t~3ynC{{k$~yunJnomv3l5|UDwE#Y@KPN(5Di%XLuZ0pKSB43!I@DDw&TA*HjmL z^XTk1k_}cY+vqjtKSFydV##royHh?sUxfR#+H&C$pF_3mC(*fZbI($fi+jJRCVlye z_3!z4m=sgw+bnN!YIrPBr6-NQ$DNv${vMQN_R5?2k*_JCqFNGP9E7~zg7&p)eqXqg zt^;G3l@_{EV%Xy?(eaQI85A!%c%xRWt}(ae%3}@#Y(k&@lRZa zV+ViN7-gl_IIP<*%P!|Un%(cXo8t3DdtVsF?4{HMlk&nsW~EmIgVuK?{hzbAtSZXm z%sGl%U)(?cLikg?VZSjaSzKpkAnQmIToWl%7v$u)#2tQ9rllH)-ne+Is!QsQns!K! zvg#4zX76*?7^tZiB8`vx@8V_^C~%%_p1Nx%!%ho7jt$5(=_eQbSyJm0 z-465F9@do?IgYRf<-wVWtJ8C;JXpJ*@I|4}Bzh ztYbLqZi-Ahp*CtQFbD1RVFMph3ug(SQI0f%#YLI3uMQq0&x+6B&Lt@m35bLQ|#`R{OjCqB_0(VELo!lK2FUVS=cJ@UVUUL(Y++Hp4`_ zTV}aD!VPv`+V7qB;}LEiHjGKX2((p^JS-Zkev<8SUY$jFh$&x(#%tXupg>G}P4zk? z&|9l&Ve|!e6;XXn$K_m?j*yVq3m(<~IW9NUFDO&|-ww+-hu@cJt6m;%FBXb=!3mQx zGG>4JkDIV8iv%I}x$2DvMd`2rNPOxGkq6sP>;Gy9W7RaqiLk0za|a0KHo%DbDOdyK?AC8hl!wm)j5=+St!sO0%tjNhsHra8!kyyoXk<| zu0@s6JfGGatthu&x2j0cKz+V zVAeLv5=lH#Sp{cm{Y~OfKB}tps$h6lmn+6fw<_^)!pYu>K}P=w<$S^yetP)1$#MtX z7KUsNu}@gs{BBRR*$RI~`;90v-XKA0Q5}<2NA%=d=UmSG&~fNV!YtZ8*b$GdHSMgX z14BMG%?M2Cp7xW|vg^{)k4(JxVXHIf^wpHeax&K=(rt9j+Skq%Dx_o+dAjOrC40nZ z(_HaOSdW=LIzHk8IVK59_iK@K4C0@fC-%l$9K?Dj9hXWq8ODv|m7_RGv>V(1WabT2 zv%WrzTJ_*N>L)bJ*^;4nD8m*!URL`P^ce1W+IB*Mnhih)vgG!o7e&)jQxy%{hM;>S zh#6pGaHIMdDNm;RbFA|)#Be}lg@2Y_{}gr2X2>ty|I%+R{w+dN1i+9{jqQjXI zU4^S8=PevZZ8C3U<^^!1^OMPgp{-hy{%7RG3juzBl*-Z%<5eaA`l|bJLYFK1M(!-0mUiA9zb0D~Z=x@^M(ncZ>Y!ZD`W( z+A@2j#+u9cd+fjoylI_$CZaQCGbXyjY!>ulwT4lI>Occm96NkP_Adpeg?yfKodAeo zu}ok2j=G%p%PXG@g~~1J+Jhqx#yv7QWOwDdRo)Q6!kq~r8P8|d@J`rGg0q1%&M+|2 zRXh_w+4zfSeIv5|{zzJ}`u6jrcxCr)eWu={si%7VPbw0~%2XhUlA0Wt*RwqHXh6;` znD0}`PT!q|S6bP*-UILF$7URJZrOj`RO4YWQaMaJ2LB+0>C?u3^MfP^3E{So%Vgg8 zuuoI7jxToesJmlwVFf*f-vz8O&OFy31ECJ=U*yQf{ZDB5;{E9pr`uk!YK@0I#LVu7 zo?gu`H2qphK$(sNm!s3{_krv(uegA<&yaLIj$T06;GUn;`OS{Di`j*Ju)ceT<)bc*!`#vCOd z)xRqXu{gOvy;=A&V3EogOApkY+e`FzXn#uigeuYToj8leQZnj*Rsw2x$Ca0UTvt_Y zZ%o3*2Dh2+$_eNW?-9MgiX<_)!wk~QTd3^G7XTEdL)|TBcc+3PzPk)u=AerPl zl^+B`FN!m2N_$Nb<&3m8Somp!?1E{OMlo?sx5=6K*+NIp;Ky5hj@2o72%AmZg<`?k zrbM#T4hXl<69YT>8MA2XFg>VnN$KI)h#(edD03!c6)S?UYGw}(eQs&Dcg5G|A;?wN zhB?{1%JhA~SP~(m^GEm^!53kGZ%STBmnnU-*=?xdm^9LvK0?!RM|DHVS*H0Rsni<9 z>tI%aI=YOh422eJ=8+978q+?^SEj0Mzg9M1$>zOIN|0;imQ`$Wk1FJIlrO4P&v(5$ zZ8L=xOKo!OG)m|`U|{ys^ie1de?8QhNuSI&f1oG*v!KA^>Ku=di9|6see@ajB+)KFJu_# zyi2X-6(YY)K_C^`l|dY4t;0uIL0Klx!=}tfAw`(GbC0KCdIuoO=*57fx$xdKFh9^> zq;26?qOKgc4F)TcFgGFjX>Y4T5MyrMHk~oKU$1+KV94N|)FXUAmE5J8fwB)=rC^!n{OiQIC0l29@kwRn*XnA!q|43q51{X(h*t6^geD$LA4M7OR@3@K zR*?DiC!?6$JA6TfJ^p?}x<~?Ka^2i###PgI&4KhiLQv0ajC#s)n_Q{xk&$2ghvxg| zCdbcMAaY^8x}Qn8cn4v#3Xw(+N z7Z7f!3?I)EObp1SPL@egnKp0yq3JdoqEcgyQ)7_CGx1|`%R0li{T0d`2uSLz5RN(_ zVi&c6;kQ#PK!&g~I6V;|=m2GV^EG5&JD)`usvxs%QutuR9eG7v6Id-ZcIs&)c18h{ z;c6PQFAyg5ho*ENoBjS9&%plc9ECyt#Xewu<$opb56$a!t@cpBG~0A7l*F3r&nm0` zhvo^PdVgwDhp5`%zSUb>l&YyCOqm;-_BSro$*s=r^M>-cUi(8MHW6OrI*6FkQtz7# zMAjEH6v%jCl`er=Zk{YsyK@181eCx3q`^SP^Nph2KC>L<26j`e!blt)&TUW~? zsbRyX17JXQEnLN*%RnNCgfW^~(VqdS50H>mKn_WeGn}_wBXufOiJDL~8i?t<_xY}& za{<5wr*OaX*FniB;<=NUg{nU^altHve`W!b+R)?Qls3N;8lCJ&QQKY|#iE*oG;Z8?J zai@}0w?Fti(Tt`_r^frF?FcKpGQ%k=Of-$YXz?uOkk~!ipyXVx`F3&Y-f5*EJ-EFQ zrjXlMDxRUpZ*!LWyY%ypTs)@XYMI#Pr@h;5qK8Whjs^zytFZFAg^-?Wv5LpvkMR!N z;h+?h&G-iERmEQ>zwq-VhDBuphwzi*!jfU)5lpil)I1W8H`}NaHe~PtPgK6Cw;g7rEI_8BwXP7Ys4m$KQQHPT?TYE zda`0Dhc&}$0v5EJZxlf&ECGc!RMZZY=Y6k#r3-)4%PC}1%J6fTsGS_FsWQY0F z>Vzdpg3^ax9?g=k0IA0O6?tzyymSF6xve)-vR2wL2@V6KO4ksSH?-8tJf4G(Sw~*E zgu+RzB?TX&+P)CbEpa zK@L7`o~)V-$h{JU2eJ<5yeHltU20SUz$9&l1G7BLRv)S(c)lO$2fYTaWz-QeCAg;5 zfX0&ihelmOc6>XRtIQ*M2dxH3#)g^FoQYlwipCfsJBzdapxxpiIr#i!> zr3;|}Qlm(qp~jO9{CXqe(jlwcZsiW&>*JOk{jU=JocaHp1y* z4$3S@e0-zS(0T+^qKo;LNZW1pB@N-unTOmr;Dk_?R6XP9b;k!S!iWq#9P<^CPNNZ9 z^I0()pT^rmX2iv7UB4IIgVB#DAo8Yj+2t=XXQ^_yWviTbT?f>)Gm%L0=BHJNew{1m zU4Pz~PM@#mh4U|#o_|$z76jUeaf%Rkkym%Oxbfi4>C}c*<0P1$+1Hez8XKnIqIKs= zT{W%#r)X)LhDax81t%vJNt|@Y9gC-xUrl*>)Iy5X?0MI?ayk_=mi>8*Y#!-+f`w8 zXBE}yZSmHwRHy1B63E~@{QcjGtGR+NJMw_86i(=u*YKsk8+6N6HIgql&9d>Wj|YM` zVn};#Lk!6acVb%`S-VQZm=y0B=G=zeP{dB8%?nN#F|ZkDr$0o>QHt^GEVKE41?~wRN$)3E8N>Gr{K{{fS=r=D)yBA)K|$p$mNUL6M#w z$;<1Ua!6m(P{D=VBCY%7Y^+3|66718R|AJ-9F$`JK9_RFLnda?Y34to{!zn^Hmc)+Iqx7SIJ39>CQ8Ox-{;4 zhdh9>&J$0Il14=}F=I*B>%7D^#Fzz72jzfHQ5yy{=F6z|zPJorJBHI59-Jv{*7+nr zR;eO&z&VmP??ABbBR$_65NH&12T}2drd4sdqi*>AoZ#s<%-=>+v^3^2y4wFs!Mthm zu6a-E&70nhM<}~z5SsBFXv6`O7m?cXaKIh1ZPfHm^QQgB11FXD*R}UqPCo63 z&*vlp-idc>vbQ{BI9>n%#-~$JwP}2x6J8*V;IGe;kj@rV2C_9=v6XK2{>bf1?k#tF z`F}@-ov?x$0x%zo{(~0z{9nXunv$cV0oOx}a!>V5=XGPPbxv0MNW&y}ud*TLJI2pG z4nHXs$u|qCCQid4XvTL^ZpAMprtqs;rYF!`D8BnuyJNz`(7<|hqd_5W znh1H_<>~4Xxs-@~cZ7Kfk`9G5lJoJdf}#U!?~+nSkLSfP!(;ZR+M!-Z9vJ4+nv~>f zYJ!?1X{B~Pd2`K{1v=Eg*4!nSd(drkMj4}?{}J4T^(IY3$*nUTdXdfXz-bkpgZTA7 zSZ6NQ&)k`r$2wpKB_WSgBUj*5KhWQ6oBGt>;Pjhum6&3acfO@NfN8_E{pA!w=8O z$H?eXa}TKpEzkIS-ejPF>`VgNg*WY8sjs;xO?z=ar;?C#jRmWUQD4U^t5ToOyrSfi z)@(cSDBwZA1L(eKI*z0z$800bDnxhD#G>ENl>JO(Z`zsLs340e?oR^P=O!SF*fL`@YqNn%ES} zpZ1m2Xb1h+9-QMRHDHveZO!H_+P0rlWAhIKcg?1X&xYfw6h?5aRqUuAbAHhFpG zWpbY*Ph{v3P`?ytQf_pYdJ+)(@MZ0WhXs-YkV5;zWu_?pO(b0GeLjuBP%t2{J)Tn@ zD3p5~JbyMY9=LAH;X9AMFuhp|Z_#xA?)bIma zMX5QVkGP=Y53ceaF)8UXDbH@0Lpu(QxxpYAaFN)6*3=;l+hk>3h` zml1NcjU(^OrLVZ{Ruq_1NbdS{zxD~89UJ?)#==yFCm%#_*utEr_DtwHs0zK3q1Q56 z(p>xFhhOf&iE&^sordqa$!CKH+k>w(%VDgEnxVtYFh*6$tx^D6pI9iQ!l*nJpx!h4 zDx;6+ZLzz)>UG=f9oqJyNwQ(ae8rEAzK859d*#392?wds)?On^K-1y%ZN+P=$XIZ^ z=ABmWh*ZM^nND|?j^n8Ww2Yc`9B$hKbTGr+C`WSfR}(9~o9r|)imi^(VEIOQOtKtY zXOonZOx$QN^X^bS$OnuDw(L44qquLn7j!Zvm)B&32&(1F?@j1WqZ`$eLIxo1S@t`n zJm2!!U2lpH5BjePAwG7zT!X;iML~iJFq_h8swtO_P{FgN;bVt3zZ!?Bw66jo1N9}< z<2-+8gx_L7*tcc&8U~-P=NbBE4pXaU@D)qLbXi`)mxj5Iz@7EE5m||Sq9(W9s+vEH z=`^<49S>?#r9F5o_cpD*a9UNe#WnpN30YptC?ntqo>%sQN2I)B`%Roq-_b%=6Ikcy z6bfUZuDK5hPFvnjL=B9OGy0N9q_)SNa)Ed2`6E-R6rAHCHzx81FK*Qp3Dhai7oBAE zo@zTyUe{CNI079EaZ93Fy~Dgmu$7|H-80bLf^D8D86&k@eD{8B>Y08x!{;89=c`-! z#^aZJ99g@5H1Fqbas_ji9%*(re;9h)Xl-m#*U*_Nm~5#O+J$rlRRy(`D(bF!ziI^{ z_L~BzEkObtu^@2xme42PG8B-lenfcQWyWc0ij&^X5-d?>@;TWV!VLvDY_-&l{oa)eGcE#k7iiZcqthvRk>1+-_hQ;)+B=!DsiZFu6 zPDHGp2YeDh+=a0W68H3<0SpUFridR>&DnqPgIQT~we6kKcV#pNO#7vYVh@={ey6?= zeN-KAXU%j03ag|0yHa^`qi}=BV0m-ZIlDV+=FcG*rjb>%zpDkal=PR`M7o^s7BT+> zDW&^=zTNuwQ^Hju=C>gl!WU z1{iCy>LnFr&=go!tm@4?mJ4E5iLf7KH0IuhlEdBA%wjaoa5JpiVEJbvL@I{V{6I?u zKFxt>Lr}4HerL7>rUw_6!Wd*ua2N2VrO%=7)0O}h>Y8LshCaHxue4redt4l!M)r+5 z;mlVLuhh>g*3(zYU0oDp%}|lCkbI>;o2YJwus2~dYf?kc;)bTpX2R1RRe9eW(c0+C zFO)G7)*2oNH7p?qsGj&!Mhg{$<9E?TYd}K*pnl9ropK9qiwk@^>jKiG)N}4~ip&F^ zn=Ll{Fi@&{@E~h$N;efr=5`lvocg^{_@-2IKJmajnks_uY_&4uI{2QAU5+2ynmU*t zgM1Nq+NmbA+UX;LkJ+q3bJ!wiTPlf6Fk{H%FOCe=Zk-oO&&GDmS;9EH-Y<&kKSX(1 z?V6cG$=q&(2eAh#-Js_}bCacaN}VexPUOadP@bJkSfGoi%+;t}=`%&Cy_qM$_x25k zbDEpMa&v$+=3oUdC zGgL(5F09*%;8EQ0S*bcHxMF@AsrRwRcsz3E;ZI7blFs0ke<|5*V?K#MaGK&aj7tUg zhm2X3AUxG}V3|DXOQQz_Yn8I(&6tTds}}T?3=g59p)XqoAe^XZf4#etT(O&q#NI2| zkq%{b7V7KKFd7zngW>Y3%->sI$_1+HfC>KFn6DIAiA_;mq>bo zFHqV1fF9cYcul9SkX(VJzX8OKp7d=$^%-E;7OyEP14K;3JZ01|VHT~k z^qc-N|Gx(;#O1miL7`SreO9xi(~ONVlfY-BlpU577*iz_m8@bkN}MyQOh5=&ZW3%d zi9YO{D>7x=6AG!fJ^%&cIhmDk7LpW2jwAr_pF)#04urry8;Gh8e`pvgG7dZVwHJkd zNK+5 z;a9|Dv1t)IgKc8E*n2h;d|1wW2(A{%Bd5;qyW->cJ|~~S$v@&L+MPfxsbvFiLFXI& zEt~yx^yqyFE~QisD^kB|6rUl1bOW4)9til*#t?E9ZVR19$L8E2BMW9NR*wwZJbeOF zQXiahu}{~ndQ(aVvGDa2B#R5{;O)7E`=wUsM>@Da2z_2G<&>)`0{%N0WtCbqwoPdii`p8r0% zx447JKssSBqHY4<+(W+^$2`m=nm^*MH#_AR$Zw4efO#5RLfLlKpXLb3+RidmSk2FG zdHHA#_`peM?!7pJ8!JJ`=wstiqloP9gw%Hios120y3zo%MFcHMaU)?Ug5Vp~T(xsy zDRrk}HOg*kaj4=B3j8&P0F9)p2;g>fLPd(;^`4S5jiUoH?a1Hbam-JYP9v#E9cpHe zlxSfKh}9J4s(I~lv&6b=N-oRUn#$aloVST2seWKojE&HpKT}awFMG^pS&Q$aVE?^UB-d$)9@gLI?lhBoLET)#kd@^|+}xzDwW3^e_9N-A z3aB>E$Af>fYE}!H#4veSw`*{!`phi@aKjJefH`n9Frs9>c>}URXqdCRq{q-Ec(A;7 zz9i=+KzIWbJ!;{OGqHhhp>?l2@W&O!l>FI&BPLtVD)C4~5|MdJpP zQ*p_?483XgPsF#!p}6%;+w9M9*`|Mo?64KdJ=O2OYSU^=w)v=3hyZ~Y7YrZzBAH`j zQ(*T%%vg43b3PAoJRa>Ucs(P(5((QIWj{w|81+V zmyN&-~C}6(xrE=C*gK%&>hsghKe=@Qxz|$ zNe)~v`Tj!ldA`MC%cXGn3!)n#$$I^vT+bKIe62@5KA9yBeW}#a{P!Zwy~E#vMEK7? zG%(M%?%n}8H@;@xX!~w;Xnd4eg4@54yrr2R{x+tk63n^R@FU90$ZzMp>#x3!cE-aL zPU2AL`|TO`?zSC359Mf*m<`n(fm{s;aX&wU_4dr-0MwM!1eGva*q+Wk%)a>T-@8<< zt~JLXM;SVkk)-XJno)y**^MqQpa3-oBm@2z<;OHrgu^p$g7eH`|K_Hge)7{y*iOW@ zTt1u}(HgAz!q4mnHrsvPHg;smQ&lNrzHL!x!L_be`%bB+Lql)9iG3$=B=oCQ#byG^ zv#|WIrFQ9uA4?}9c9AtU&qgNYRaY62A9ee;2OVVqgT?=eX>dEnS;Nj##`9f>f2WvzRJkP`4C?~s_0M2OI;}}XMW2ES(M7HVPh`UzLSPph3{oI*`NTcU@7tX4XjRGO+u%riHVtJqi z8IH6oyOUeCVNcd%I1c<$v@%i7vuE52v_d-Xxf9GW)FUx$vjEX0;MS<}F^^bxnXgbO zp_t{-dZmyePktt~+nv$%S!1c%%q{$yw#x)jv(M&IF?(aw*YKlA7~F#&WV2 zbtY*Y8u1QY2TRzzW@EI`5QtJwm0gnLj(`f8eSeEDGice3uBb=g5PKhx7A^1q=vgh_T*2$`KriK0t<2ahMwzA&>HTC3G0x_1DANqtC|2!9KdLkuIUR-$$o zq!{#Vw{QoeR@qcDe2Z!7NwNm=?REId9Rrp$gIP05`iy?A?Y`xrvD%%6vYSN!I^?gY zme3di**VLpV-?h^c)8n+MIhf`8Cc_Q$~INu zCDgoX5`^1cPBEMGtQub-RAwciclfr@`C-iS$hY-!3D2*>#V593bWL=7Ev}s{Y>6yo zBwbmmPQM$a5o6K2oOp%4aF`ML&b#k*9Uq5=#RtuCJM7AmIUpTkd2TlPrDa#$F6Whz znLz6yPUnG~__pL$pGSHLZ|Lu_BOkuQv6GnNqc+gh5eiq(5-hdshTu|qxC<~W_s14O z_A%$E{mc``X0`%mbT4>a3ZHj$UY#bPC{zbxx}gRs)A zW0=|30OdsQl!NhwEtbj`iv?1b3kE&3cO5)*YFyIpV=?@2uS1?C zGX!Hbx%~7PwF#|%UZH%EKFqq0;gJN!^o~OQm!wG`%z3yGpD*mUt>EIC#FqT?OPQK& z%rHyrQBwG;uiO5yvE8qxm`_VhR7JfmX=93_I5cOA`tE;M$_F6mQm60EG(>vR*w*5d=a}8Bhsyq zNQVJ83z=^8oXR5xz{Bl&64sPre=$2x_hQvOCi(tn_gJ!lJIrO*@QXWV<*3{#vFhyl zd1TPk4~Z>YU0DfL51(+m7`@27=&z%w9**gua`E{_G=C9O3M;GyLVBd=k1RC{Xa?DD z-UKbW$xpzw88X>`T4Zb61TTOh4%5$D6Menioebtcg*+D#`B=(LK3ss;mj^DqJP9)M z40n-KC1}YGlumi{GtQp>^g|=t9(dO#WOJG%MIZRpwigZDD=zGV?v1jKFg_}YqY)Z8 zCSZ3A`QH4y_lfL>I#~n*zQjUgOKSu24~;6rbzr(u{D+3TiPUWu780lesfG3Rmx%0* zBY&wYhs^=d6!2juuuUUD%1tXA|2D$2WpkeybyoaDb5)FGhYnE0H5#5%Y+3sI1_*qo zG8QN*odW(jwer`AF7k&r;9B9NIh_Q$K}EHX!ZY8RT}3?Y5J>t@8z!`>$U-f0K2P!U zV$Y6D<{z56B6+F{d^WrVkD7Fz?@m2wkfbQan*G{cc8bfQ)X8>;RpJfvJ9~#p|9x>Euz#s#FIKl1! z78&kGucye-YIPo+p~HQ6vlpPJlVSHJ!$ek3Q9z9&PvF?wWe9aBPD1ynJIsXx{{c2p zlL~V9?Dpg=l?iEf^W6M6=zR*Y9<_lZ8SD0C&%2wFhNs#q87N*Ecp2~|a)f%Vi}=2n zPOsy9-e{5#--nO%ceqN|=f(pMLwNazhw#@M-LvnvKXLWaYA}#j?nxj<7nX*JtjtA* zpQ|E8qpCLfp~IULnf#=?4fVr!Zn(epd9>ATS7OwNYRPPa2C4YPPt!YT}Of4`>jRU86 z?|*3JHo9K1Q7^u?2ijwZPT}Nh)u+OB-=t^cXL(Ub7F9{4Ibh*DRW#|aOPj(JahGf{JG$iy^!E2b21btk%r{`cJue41a zQDntNwwb8+=uSc}{4HZjoKB%&lS=7SRhX%=}1*N0@8c$ zy@VPd#52C%*=K)y-@Dhncdh$RG8wXxNtn#@Jiq$=30{6ee=BAHx=yovGq0PksSfO` zs1xTmSbjpwf)r_1k=`g}D-lxKR#kWqasOgL)4x!GIP?vbBZ{86kWqSLN<%%~G@CgY zW=)6m=T-E#yA-j5OuAUHt86kfQ;1e2 z;VZsD4{js%&e+L9dHXbd&!cJ^$ZNUMjfdorM4h4raZz`z>yk@}+Ur}^nH&_a2Si;! zcPo$H>Vt!A%pRd!WgEH_#$b-U!*W1pdF9jaR7|s^k6dTX4`S3UI@+^cT3c7m} zU%6E|ZYGacU{@FHhOT+NzuA8!rWExDB&P+xhe+r7-dW|>CnM3jjFBS;F8{q3^al=b z!C)7-C|+syF7D+)(E1GKMluj!GJ=puRyaubcFQ@(bdR2+0omsV{<)ic!`Jz^bhJ~{ z5@ke6@An7P_c-Rj{z?5%o3dZ?LQVsA)F#USC)*g-+VS8Gg(~WMubqI*t6H1{^j5S? zWv?{XryLS>b>l+5#)+%WvE<)8CCba01!tra z`@04ODNm^!&z6E+r$awi59*eR-pqO;?0Pl2G8Ub?wi7L2BdK7LXxMUMD=!g+GGl%% zPElhE1Qh~e33<-4NVYqODchY$GM5cECE}1c?Ax~*US)SGULo9E)b#D2t>~fdHQz3e1|QcEzshTqXShU5sjKFg)S| zC;5Jrwyl=kRbKOf7BZ0V&L5Dwq%%;DHZM?B_Om%W0q=$D+6$ScW}xJT$aXV2a%=(@ zpwDgG%7%OBiUFg(xG{JBiYG@A;e(TQp?tlqNzqXT6AGy<4%Fm@RxMe6q3AqPl%mcO zrO)#6x54MO!N(-wGw)_d`h_2R7EH-D!m1-_+=UYO$}-14j3kGk$zKs^#kx;9_sP{f z{BW&qIY@tEIe}wd-Laxp<|9uy;Cx_*y~C+da-8f`F>jsc(3iqVlbw^d#6;Bw0zF0cP8(mOrb zihR&_sO@|6wf}Xfol4(ay*`|{PU@Dk42PfaWlR}oG1psuXq{T{GT&@w0@flZvwt>Q*;@-bR|Cf}d_uA6^ho$)d$T&0Db0&|fo{Zs8Xl3R{cJThzLRTBw&fp&*~o7@IJ_`6Q8^om6!{ zlW1Q9_GWm4z*igf07(MkIUZEcy!N;4;ET3SLg2mssrTUT{;wMORUi%^z<|`&W+@j) zjWZqT$@RtNw)5`{8U zdTQnSsR<$^^ln9uHDFFk&SL|G^I?VDD4y6tmGlvU40g-n7y0NHK!4A^EcFaS$h%?z z-h0#pCP7Z~6e1;`(a~<_;0uO*hCaEyJKZU3qL8gEo*}du3d$F(Xa@J4zBCY`<>|c!< z>J6Wi%bP|V$R_Nw1$zBKeSU}~dk+Ma-S|`*@Z>f90N*MRDUhQxBmy1uX;(f|S0 zL9`L@wtGXfN{&>bFF&>l(2IGl=aZI~8Olf2f&`PV0iX z=*Lw=LE87XkBb8+;#vYI29OvgnC)gAFCbeVsUm3FyK2;Ak>xr%-Zw@BTa5yc;XaG# zTnP*K_9kjAg}Zwa{|me?wCB%Ph>2?Phc8)$WHU4s-w4Y!ib#;qYhuw0cW#Ib1lX)= zfl^jWo$cFzBWHXtD;#Dc)~nW7uyWyGwjK4W0pECgnd`lj^n&!8VU0o2r=qvo%x6o& z8GGJhx;8YVpy>nu=(N;Bq3@r^id(P9(HpAYWXqzS;wIe9c;9^Y6&AIiUp+$7lxLeg zw@VIPUXAv5J`Y`YpJg#2*GV2y_ed>9cx%X;-ab(6)L0M%8_Y_^mwkV2@AiG!jOhlB zjC>t#>Zdpe)f`H|Kd3VbP=+tb%d$LO;=d<&*ZS<9aMVfIq4=4B8zjxqj}+5ZhYu4A zD=5Q{4QYJ2jOxWi68bAXLXg9d#=jH2?H3^7b1Y+}aS~!V+*M7Q?TU=64>hXwnioWm zCyDQ>esb2hHykf1V~v`ce?A3mnkpS1xsdww$U8uc(s4E+_SiqbD1Eok0CiQY=;cu4 zPwGM;mF$1)V&4|sg^qG^z2e*ail^8Z_8XWnZX;*23kEXK{asJ}RnHry)!@J0x^R4Y zii_~a8!ev^EG3q=y|GY(tRo>;RWGhuX+NYrM-mktX9P7Um@R9NPT6|6JUp$@y4G4c zq)1Qaaew7aF;?&gfIq(#cw1==WAqJ~T8y7}o{^=yehPAiKf&59?nmKSj2q^d$L-%Y z&j%%)JDw=g^*6)DFk&^BDA@2yg=Ixeu)@^tD?R2#!+_n6Q+KNRzP*4RaVMa zrbBSWz1!s}i{xQB-4f5E@Y{v>Ds_$E0G?0#)}9#$)cuF(W7^<~-xS?0sRBCh`?yu8 zU(<2z+RRSE_UC3B;f1{$quaD+;FkfvE~q6Ct%)PFHPnO=SCE?19R{ z#%VUyHjao~$=Mao0KLX?Z51rJ7=yHYj5GPJo463H!<>_lUZ3&#ZBeMfdG? z!}^WmZ%=-Yt(wbF9L#oxOQ|8P$B=KwV?UpneFTbH2h7JO@Q*Pv@dsRseGMKlY$DwJ zCH4jjeOw-IJ+|7$JChl==kAU1yG!1-E4G`qnrBLvX97D%DwtxL!=%)fuapI=%A|%A z>)9e+@i5tK6h}UW8+95p>O{HDe1B8sgzwGrRwpq%UiYsY>N7MwQ~o_wPP06)E2=RS z*KyW%mA2z{avVJGjGIWlAY2gqEUH1{C;dTpOfVUL>Ko$91`;cHLIMJjWuW|Cjtz6o zg#uMprNckw=^8W+_BGNwRnj5lD($%9&ov*-MiYk`GVV&T^|(fY4alfl2C_`lh1bf} z+Bs9bhg`NY(mv)6k8CvCk{VsgFMT;(EKd+ClONAw^Zo-G2=cYsnO<-|NDPGPeAiQ* zHM-)Mtew0IzTZF0j~(xl$j@^{+0u%SSBSRHwtnS^xu{^tZ@jj=d=_GPz#ecICm(C`oS0Hypx1UlcqWj_?+@>)_K*)a&0j@)$ZI;&;%) z&Mxm`4Opb=>w?uT?9msZ$Segeet<-H3V8_~$SD7vnTWWZFvHY{S}AB9e)1Z(z5MGK z@)1H;il>=3c{5?lU_Wyu-3h&_G>DG__XpEyl;?zQFJ5V>hq zRh4|()Oz#LmC0d8=?e>hk~)tTR7WCL@SbOzE6si*DNysn^z?lIa}n|6WRujLD(+ zN|(9uefbc*@>^&rWSuVLwbS8MFC2gUvRPmrfn1k*mL}z|Q9R(02kz_#G^$g6%9tf- z${WLe4@f#dQy1aIN8*8x^pE16`I+JX>6+$odY;kfhqSY86wY+u_y$IOFEtYz$+UM!dOicY-66V^b8yn7VcW)pW6D>g-wd_!_#2_y-!Ch!GTf_ zDW5Vi?D#!ia+I{soA$e+l%Jot90P|)LBv0~-*~T)%(?bdsFfU3lBp8?>?b<2+qFbp zDMW8WT4uyY8DS*z36-#>clc|oiWaFim@{VbJoMQLl&56V^0z!I`K%DG2v`N4^zZT^ zICbzbbn91H+eWl^`P<$`3g2u;7+E~cV+vrQYmjWm3#qx?9DUVz_IYQ#Q_jj)C5ZeM--p{tzgSl7 zp{~_wmX$GUbKrqeoLUKNGeHIA>NE{?{=sA(>kmSEVI2?V+f6~^(Tv-wX$-Fd1}P<- zoLhNg#zmLLq6%>k3{BqQeX8ju?8IR#*~b9Z#?sEy$N}>j9d|Q-M;RIO2)%KcPS$2p zj0clhWFFH!g^!VJL@-h{mqKOreG{1NuiyOk?E3>kEJG>-(3dmV)jN;<#72_!h;po_ zgnh*hp5Shw6YQF>g_xKIdnOO3_ES;;@guPpKN`X%?sbC5RSxa?DV13C2^ua=(ZvUj zA1h4nEjAZf#;g`==OTN25A(BQ?M>jb^%dK5D??wL0L_Bej=fYE!)g-uSxMMFg#wvA z#hN(U_D9_aSN+@W2W-Pt`sfW3FWstiB!{tEUY_)APgq*}q~yvI{KkTwic9f}pSt(B zzLoX^2CO^of|On8Rq7A*H9$M;k?Y$d!7l5|m*ykB92khg72A4Q(uIM+(Rf00*i%V< z8Gkw1=&ZM?Ry5m9H?X4YDFRhetzZ-6ehn6yTUGX@v7AbaTt@JmWKV9h`0&1fJE}sX;6uvWG`-``}dl4pWM=*VD~~#YNjN z$h(ILH{U!HlQCes?3_tHL{oW{uft;Y1oI70%jfT{ZodB>MGNRLWh3@Qjk1rrf8~2B zKRBgX4B*A=p_Y5vE2@=32U94f6uJ=}(m>O4fUV#82zGl3Q#+5eCJHetEB&!@c^_ZZ zDeoX92+nZw>$80wumAM&5u^<<4arj`nf8(qzT4@EqWEzCJg52;u79>`;KuQ~fsNGJuCZO{GM}ofx5Qew?9y3Rj z^UZY;&KfVT#Q-vTDF3B2j{4JLQ*d1n&i3MDija*0pQmv^zHQnL?`^PY7ZfWwFi;Ly zBZuPpo3l61GRzVe8bA8y;<>PY!xpE0Zx;m9L02& zRO_LL92)b)=YG1mD>HfZz~!i#{a=ZRO`%tD2us7JM|R5S?QadHcgy0|?%WhFCqK7D zUglt<7G;?ocU&*|GiZ&cz1G`3K3aeK<}c9!lvPF{i9_hX3&hC6Q*_g)9Jd~U?j4W> zN#xiVBclNdmHmQ$Q8T8UAxKyA5r{Ce(E7i)YDx*0J=^=h3;pjLs%CY}j}|&D%wNnp z3jqeBJ&o5U8evj;`CeSDHB)P4ZV5i_Un~tRTqitOa??R)=wJO&a7Iy$NEY!F{dz&i z{AWp(mrR)JhFgG?BNxwHKp2fdhl@hM*c{FAlaS|UXXW%v?}D@@bv;0@$n#$B!1tnl zCHzg~#$0up1AO!6V$E%dpqh&`xjn%%E@xbXPIjP#s$htzz_1g)ln%;>;15Wu>egTF z5Gn;8l|lLT^CRpw+!*15R|FS|{?w9XskgX<`5BdgxFQ_c3Gu$|)ER{@$7VBj8!;~9 z^y4T8p+6w$5>`kT$$?LLM~A=4A)}G?lwC;DKWC?{c5JBq4)IvVZNyv0uyhHGbbbs` zX_%k++a9(l;m^bM%qaLv6S%Q0mG_xCT9Q1epaoAj)PP(NY@w5(^LowT1|4%4k?yTs z^}p*&a>4+tY-BjR$GEnzo|j3|kcP`YphO(it}qTfy4WWef(O=$(6#kanl(7H%%f>P zzJuu`Lyoc1FQ}61SM#S`$24PJ`yGJZ8@PJSZcBu}dlMA!yk8h%0fymDFlUjX&8UsZ%d&LmD1VNfAJm9-ChL9l8ZT>fF*KZ8tC6h3$Mjg+_4&6?j{ex-w;C<&f39( z+D~@+oIRb^lr5rHfO%-KwibMNle?HdDgrnmlm1I|<-f;R{=e8Ji+JBvq9}VmW*d%7 zCm$=pDJ~w7C-sGWlB=X?rLqiLg>ve^@{U_?=>vn zD6;|K4(`rQpKj}QGhv=orz!KXSCwz0J&`kN4C)MxE%EAfU>_A1p@`97VWd=e=oSBt zJAZ$cn`rpv=^-m`WlXUUaOyH8k8AB3m{N_hjUG!HC3Ory?YQxjPgrZ9W$4ugH!Jmq zMN!KXrDF#&tu#6nvdvuOlS05clFtK%d7)XA3Mmi_rj;ao!tMEMF)1TUDcIo`P;j!{ zqg_SU7q+n+A$<@?ywb^9BJl?AN1i-z+I@h@tPfd=QOXJEp9-&r(6|MKN7r0?!LBu{ zLWTPQ0oEbA(m84Ji$k*oJqEMv$Vnq^#PI_-pN&u6SXiMEeDbCJ-tLStQ`o2h)OQ&j z#jqbGB~d3ma<6)9rC5DzVeQRR`tAj*RFX?T^V70;_*NbMxml!id1_a%uFn`d)5+I1 z*7ps&b#FD|dz0GLnR;ic)$nod6^}T}mwA+*S`@l=w{`nPuLhze`8RE0k+?*grW4ue zF>H!DPu#jVQYc=@nlJHyCyG~5xRY>Z=^NKreq7LNIzZuwUe{%>wP9pWkXaYq82+IS zrz+dj>9JK^@{nMRFeO?LJKD$wQvZaOM0C%jlDllA)x_O>L=JS9n~-@L0y)eUg|@z% zmX~{-)0su62P`AuK;@inie@m?dl!GepP;n!lX<4HP@t=-cG&!@nQ;YC5osYUxGo~; zBArOzYo*ryum*SCjb`=^UvqP|P`o=3`aaroXcCNnL_97EPGyYw-q^2F(q!y~XFDGf z{kbD_QW~#dPbFxLA2e&y;0#VePz6*euWu*xaV1HtU#roDYx|?$3>%XLS{)bQPIue& z?SkMwA*GE^XeyoXiY}#f<-?LJ`N=~>TcgUQx3+8_i#NI}k^Q!LL*X{Vd)lWsu2iLW z^mr(_*ZC)E`I-CE)z8Cnt;S$j={VsNV$Lkb)2_}&k=c$M5MFPbfiL^}+DM0B6$jX) z8`rs0IoqG^RpeqT>GMjLyol;dk+0~9ZR`|R3{kKI{i#ne z$C^*9T{*qqYP}Sb6167sKoMUu7pEBtSt=^uCTZYaD{C4UWqj&@6rI=Le~*nyYIk;E zwH>KEXF!!mzH%#IZ?@b5CLo&Kxup{en@Z+>C&owgM$0MYhsO8bt|VKf&K61V73zfQ zmo4{D>1!k}PboU&r^Ib5E5MZBzUKL51kBHQfEC_JP&k%sp z4aQI%RoCtGm;Zs%%g`!l0CLw4ioAEf~v+upO}jOej@vL<^Q-|1c0J z!w6gMu@c2f0@g@g3+gr+-T}f9pdKdaeI5+tRY)Xc`>Z>Ym|t>0lLz`Y=WX#tWn%#d zsm(7DNMrLK#gOjzxBoZb|3A&oqK5`$?_|dpa)WYhVcgfmPI8gSHcNqQuhk0Ggn~fN zd$h_&){`TGK(alW5~J0ypoBo4uBz){P-a_V7$}c*)P@pWH|l*a@G)m(K_9c-%XmfW z4MJA0t&f8zsF0i@Dy3anx}#3Raf%aEVNS{A=MBOeOEOjQ?#zxeN`{_71H=$l+J6iv zjx!4XVEVFjv=k>x<)v(=rSI2(XSytf6ecmn|X#~2QG z0%bC5kp;c+C@FVEYk&+e579FZ*AI^weaebxtLdJi5E zus`W|h(OLxT-<4aTl9lglZ^`_^?rhr zN*MbD?2J<#HTFp^yN6L9;?kJk_zH(_N_LuMg<7u}=LEBKK_0ZGpGxTXfWIxyguP9@ZgRF1H<}!)p?6-|X(54%9eA-z*(ox=~Uy zcIwP+(fXJMqO!DosQ#$4!NbCQFN=oe9FP3HHu1@{4m!jmIDP_*?@e?V4cP-|N1ELa z8LGxXktF+U->)y5?JasgzW^<`NlPB1tv_7?!AS(1XB|S%O1B0>97SdE?yc7zmkUjh zeZYtw0(J|TtX2QI<*xX>2S<$N<#!&3A9T))(Bx%e9d$4Y2bDu5`Hi)ZR?2mjm1CMw z+h#&PyPQeUk*SBV&vW=!B)Wdd1g-@>k>D}>Cj^f0eeSDJm4D1r5S2^x0y-qI6MXx) zyOgo-E323%{a()@KIcXgH9GGP$ZXbE2>U_Nb3=Pe^be@h=tA?xT;ZE3%RE=x**7lD zpB#s3_dic*oT5MO{V*AN77}-`ePP)MUvmFkGtO44_0E|^W5gLx)80=q^OIdbIF?88 zf+7@j(R1pHslh!Y|1ifeYN{nVQGIWm-TlbyoKa>Sgcse2KY;JFqTx0^4vo3;?xOXE zrjB|_Y>e-SPc+7wK9*r)(37ti%baqsma_9`81|tOki9I{R{$uv%_oXnf)rP>1gvYf zu11DpJ*F#&QiQnzjosC`_dab&(habd0CG=@`Atu~5xr7pdHoTG-V#pT|X8 z^P>JnaWH2iWV$!$E%^>p%q{L2gJIK(s&kg`6JUB9_bAJ1>I zWZB5YaS_)|Jg`0wSh<38x3eY@^I2NpU_71U`MXI#kyf|Kjh2(r$!G-vHWRPfGXT|~ zMi~-Uy!X@tYqqGroejf-qPDd%f@G*5M?@cv95JQkp<7Y(7!et!-+#Z6QONlNUlRDQ zrsXg2pa5#qH8YHHAA1bY<5<40fm05M~mfs27av+*sLkt7=L z@RWW_zk&6VheweMj^Lmz!yRpQ@sj+AW>W-;Qfem?%Q~<;!Mg*mFV^h^Bi~{Bm4B6X z%n7bkp1V_ZnECee`~^4=F#A5jC3w$V=Bq5Chm(N zJhK(Jz<<=|{`n;yh#=X8YXtnBr<0k;c|OW%=H+9e1irc9BLR-CCZD8bd#@r4H_~?})7uCjK9L;n~sgLSH)T?r!v7w(j zRQoxHp~f4&VHp~)-w--4%Q^eYyyx^MeA9=U2J=*IdR2{|G(W#~5H3eFNCJ~RO=33W zTvLWObDPzgeAfwcyN`X|km+=%h?2{bE;KJ1ag}_sAy{%kO18wEZs&UXnLe6QE0WG? zVi|vd_9X2btz{HMhg{U7HI#nk^;r3uo(4emk2V56{KTHAQXl99?3@A(EPp_v7fhC@ z{HyZGK%E8`Bu%Gq(nK&FTcq7Cr2OY_cNBP!q!9AyxW43k%0Bn|b{!4yzuXZViX$iY zsMg{0*3&r3j~d0$BdYznCo>qe;D)BS#|Mpgzu9{eRCA&e2$gkr^1uN4`tA?A`u2d+ zZFL61O6osna-6*QP*tnr^|qG(xfusm1vp80)>R*tRNG{T51I}Z1^m|Gwj8ctiLCP+VM>lDpQB(9u?Wn%(K0l=jk_{q{_pR%*(}DQ@$4^&CX}@287=!*g6z z3L4&KuE;L4x|-OzXE@<3or@8gi*|`<6p?mnT-YQ^=R7q9SaiaGB-tskJIL#9tSP2{ zKnISeMsb~U%u&W;C%4>sBvVtYU&)%gZ#KjYu#6t!!MNMvq=~wlCLy@On+#2gHy5Cj8kGocf z?!|zMe_*M6TLw*b4gZZV?>#rHoDZWi_f5H$_d`zWq@rXB-NqAlWK`XsI^x@)i*zNX zY|MJ&ZGFETJ!U5{@w~q)fjYN}0jbv*vUQj;LA0SwPb}0!SlVFxJ+^20xme1s+x?2Z zf!QbLv{!?34VUev(xVM#kVL*Dl&W7s^g7EV9+Ovn(AN}0IkO$9*EP$ML4UQ3XhM7p zsOmD;iX7L*n5@)zKCUQr<)3Z!`z+Hupm#2+>d!g5D-zgKYoCDW+-E-p&%$5pov7K` ztD5`j&yC5j)qH+^7ooFncns3(lj+;D(7a(Y6_Cik638288nc*j3sqDSixwe(1i3*f zQsQxF*^xr`be~U{2Khn!PLSFU8HCMO~Vq%Bnb&&NeATwyaxx(tF zIOepxZm#ea15L^b9~oCPf_%UeUA-LfAi^v{jy0mF=n;sy7(*tt6lI>S^C7VTFIFeG zdg33jym8nI7T@0z)HnhIxX=RE2$9~XsHzFAM*78}#rv`Ag6xq_AeuMI_vj{P-?N4% zm<1A}{NR_$ICn>STS_lqg{0C5hlykb2<89~S!}R2WqdkhI6vjrMCR(3CtBbgv)V)3 zI&W)y-5*%ROX95RusLWEvAscSj}rYkrmH`o)Bf*hJ^-n#`LSSaQS0^EX|R&*3O<@a zs-0V`_S;b(xPE&Ag z$QGDc%D7DI5>7Vx$X@Q4Y!*;`&N~jc!VA(_4uHsBHOl@ML-uCn!zIfU^4H}_iXi>4 zF09?b{tK+pA|sf5mmSYg~WebebStK+Cd*cccPJDCrJ>$GyN zzP^m4WbGeRI&)Ez#3$%F)b4WC`zNmzBDqI+0VzF@_!R2APvv`43VBP=8)xqZ@7cOI z_sLL5cy*pplRS((j|CL|xC{Rmx=^U*#I&ljGi&R06_XX$z#@q_?eSmmD!~q*bWJ3k zVo(6$0hID}1YqzBGV#Ya=@|X~vM_Ru7yRazf=B*j5A`{p!2J3HKBeFX;B@&wI;mw% zrH2|>cc@Y4)zNJKSVM9s-^DiZ$DDUrcf?qvzJ-=6wTu+<#=54A22pF71i$`2vhDw` zc|-r#=M$G~HgOI&FfQ8Bd6tad5MonAruB9ApYNJ}AZqEm;}TW3MHj#(x;VJuQK$Yf zaq5HP_wUB7bm!IKPA~dlLp9hcgq;;>-IUy%_I0ve?;jm6(4DRV%n8zUNws$TyY~)k_t&k&M^ddZq4x zpWdow_-sb9xOlvndg4>zSHu}Uu6%7Za!}WNENjXmm}?m5p!0s%>-hpfQff5UC}F@o zJueM2^y9zm^nlflaMX5zc`pbJkGkKDr4Ny<74%FfBv+Uj_OWK=MC=2}(c z_}KI5QiWCR;g@)jzUMU9`OR*6OQZFxSv~ix@G{<%3W*yr3i2EanjQw9Z`i z&(_l>uZL~~6V?kQJR1BSyMNt|Rps&@iSp<~(h$BhD(rJpOqtE$(KX^!Ui+3ir=g=oFTIK4aN`Y76hL~Y zHAQ#%J8O!(^R^`1vgHxbqvgGwaccKs$kF_@4h@OTcj+)r6*J|?s`QKe0ePj$)3qXI zIc4F;?`Fo`9=UTAEA=lu-Vx>Mq4m7-6f+4EBt9yN5}J7?DyQ0UpR_F$#WApUSOGeJ++>;pd>% zOFaXY+wcCL;Pl(7%72F&ZOv<;Fco(YzeI|vED6uH8WI4SxC`$kU&zArPdnliVb8B;hnM5YO8Vp4ulQ% zo$|Qg4WM8BdnCYt0ytJjB?0?i0c)gaF$D^w%rN?qhJhsQULZ@c4tM_jLQPEo+zRC> z*5=M67F3B*5YY{jC9Zm+Er@z*P0;c|;kGOp^=kg`#(&UO1U;(%=1%^1r}DpV2dDgp zi1nsTe#VQIK(<`gbVZv=0($BpUVZ9TS&F}12CXDOmjQ42h(MK1LN-u0to|3?GO@h{ zU|K-qv50#itKQR`%sYjD!7SJjAYhFQ6y^jnRsc|{dJVXrQ5p+;1fWyx7BdO}LUmHo z^SOX9qc#j>Vcb3*y5YbIC{%q0h^3urEKKD8?sx#GT7@);rT+oGBI_8F?0DA%Dhb{> zgH8E_0c7i>P1;UuiK-9u8c@V$3G4suJ&^I*AY?Jv%8kiT8TrbaS}aRn&H;_F#f9kQ z!a&(QTEfZI+nPXVjHQlNm4QXUgyxMKRg04R7U7ZUy1<2INaohX#W-7m*NxL@&e?=j zX$gkow*JZ+4aR$+u2Kl8|e$@|>VU8aWpQ_wV8_ z9>7ngp(2&nj`6AJ?JoXo`UI<+IWx(@bs528OUoSzjKR-+b8%k=h#S4s=O8z{{6%I( zuanL6J2eOBUySXAE&2Abo^Twc8&q6&&4%2O9FwLdP(6*tYT5W_N6~LYKXkcI>dR#J zj+G_WY{V1&l@D;_kQ?PU9^fX81+c3%v9ljMnL@Gm_GYGL)d;q!$^(?B326S#H+=SY zY6?Z8+O6;ZzPC4K@c9DNdJc_&W(V|F&;iPW1{z$Vg=rzd2 z=vw@C28G#?l%NoPJ13wPU$x>!@b19F@f!|~5zUm;_EOzFc@ST5k$jd6bJ@-{z|WzC33!f<3@)Wf>-%?PJ@uJviZitB~?y4N~ta{0CJ3 z06f;v9&leBvAPgdM3N2x_slIl#vf`P^_G{$j*ki+@mq@crsvRxh+0ENw>(4eJG*#M z3qKn)Qq2~NmIwDzzMe{74$Gth`=;)kCjBAVxd5G@Vw{A>sj zJ-`C8DM%7e#f?~>{R0v*HOET6 znS46^h#~R6G@^$r+<~CHJaL>rImS_oMz79z$Gx#j3V0B|1tsGs{}MTp+&j9)reoYoZ#jl2O$m55eFTa(HZ_~kC}9R-I26YC8sJK)(> zUQ_c%HOkAt$)`?B!4jMG2lS4_?k9rW$08ayaf%R!7XAUvM|h<&K$xz$C4KA*zr>D! zr^K~)b74`J)}zaFwg`WOkWx~{JiJ#62wi}-?qAS!0wgwIHSLbto`_nG0HMW?d?gvni*xmSXC+wkER2Az~NKrh#vI zc`}1Y3$W-grf6+=AVJl25E@q4*Js7$_T3&MK7)1OZ686YM?96B{)(3e1R1y$+zyah zAO*>lX)KvC$ol#92meN6|Ees*92wRb?X@LWrEO5gg&>bGCD~tahWXG((+M zi@V1^?d%bbZ^q4E(@RIGW>`ee$T~-sK{m&gVXJ{-d2zXVi&1sH2$t&fDL{8bPXa0n$ozULEvY#4|4*g02 z3PUwM42tdv~?1oc!RtNfNRs*9`rtx?pfuQ@m0=3edQ z{bW+6$LD0BRfciidDx1DxkfUiJ2k9LznD6N4Kxg-#}+$p`4AqL61Qj2l=@jL_=Dv~ z_$iGVpEjAuR-1geLvYgZ_!v+zp4ww#hW1&8l+M}wqBRc0i4Ud5hnpS_byQ^efJ#P#qVPu``-*Uc(Cd_D9Bh9m0Kq0tvarxzW6!J=TrR{6Fxx0t7ktw6LrqNSBN zxG<=&a%l-~+o^u9;aka@@0zF(Az4nm(c3ySw%#!E~%;W5 z#fy6Gvsk3YXfS#bd+A&Vp+9WzLZ%7ZzimRumIn2ooi=K_U(Iz93GvC#3`r`d=Kh**z?(p(^-&4kBs(gdHDWZ(>_`#52^BSe=0= zZ}Ja-d1pw6_iqfIS^M?_g4Orl@b`Gq`E4TsL8VDl-D)S-hU9pa7vkpyG-wfQ86^Mi zNR3k*aZ>!)6q}fDBbiH<)-kn5d-dy#e{C9cdh-GA)!|Waae)`boupVL z;r7r~9V0F~)vAMtm)N)Z!cD@)qj`v~;|vNv)#2l`L0CqOapa>{3?z?ac(Dw2L~ z-Y|;RXEa~86Pp;{;Omz%#26_bY;}{?N62BF*goSz0rw_GgVL);2V*jx;{VjWznjD< z9PQB82eKB(86JDd0D^FpBoC%hpMueP+5ahAsSuBq7g#9IKWMPEDn0oXKT$u6}uUq_5$u~ z`YCTy$e@FUHUkDK&cZq{ONeqj^O++gqzb;05S)hD5p;e0vh7iikm;W*bBS?{U0XDPcZ@U$v?*CO?DUoglKuOz=XPd))OpH>YW zZ|L7vHNW{e=R{_$vLL(p%lcE@xYXI{(Td$zE&XQ-G>h|wj1}^kSvrF;lFD>r3=@Y8+?lir0%pYkr?56aYI5bha!xQ?-q_ zMgx%6F){bQ)?>zl$G-D-ZL5?LP z_E%<U3X9St0fHxbfVqAcXu(38B;HYx3WW_@?fd;bqRm1EU{j5`9MxYaH%)c=&!B z?ui8b6*|hY_+P>T1_%Av4u-8Sp8vx0jF|D=B!*bZ|NIiQx)l(Aj&gS9Uu~=C=j)Ry zF;!-NYWc=RS-M*ky$qqVO_#xlp4OMli1uBrq|8PsFvlxd5C-y5{@0ql4WLsRC};UB z!&y1Fb2stpr>~q(A|%U77=67R1=!wG+i=FbXXWl@Kc+cD?3^6D7YuHqGfJr)+4lU! z;>ngYUhoV~-!Ap+&Zp~ZRmJ?Q4VM={w0YM1mIgglNRWeP0P%tSr$C&zRn8{nV=z&x z*i(!4C`yB6xl-<(pJ~N%9K6jVZejr9%8dPG7Z(PJhM#{gB zWJoXf={`fO)PZk>w)N0x_3aJ-v#txB@PCP6|5YLW|HpQMU5Eq8dHLgb0>$N2f&r-3 z!u+Q*Q_j~??WniJxXR96d=Fj}il;aQ?2ltKX2~pQ>QC>VZ8#sJnz6zAx30a4v z(UXr_f=F$D3 zmAk@n$#sWB^d7jrH?}oe-tXRZbqEdBJ5`<+@sou=%-MwsQODgg4P;uE?vphdD^@GS z<=){wE$N9cbMO$C89g3xa_7ocYCicqtXLUWbf6)sZ+8*_gc+qVFZIO58a1iuHq_4^ z-gyOh?3D=j4P&HCa@-734Bt%LZdc&U+#O!MQq$~{Hh;dKe44&;@}kO5(=|dT@7c>g?KKRwH)6xZ}mnd6RH>Dqz<)aa9(z69Q!>1VyG^~2WLmE}fEk?OE&fLsxl`=69r|9ATnViN)h z{vu(%gS!g+AnNRBogff*ruNV~paRq>mwFWjav2_r&DD}6)6(W%OU}+SozWy5(Cw;h zgQfpP>a=t^D!cwsnLV^iu3{L`Lc#t@)y9A#(mVf(UH%6P)UbU|w}lh>M+_IlOJ`O* z&?!sV$_x*d2&TKx!Zk-^|H6jA(XkE?F2lZs zX?0Y+1^~k_ouXkHTX*ISf?rjF~En^IL*~khr>Wx8o4mjFCYe| zTo??bhx`vpr&t-#5B~eW{XcEz=4A)cD?ACc|7QRZEzH&ZGQ>^r<)hB$+-+Hk7&VJN z6@^Ekpm&K7KoN%$J}dZYeJuwi&-zy(Hx|hAqDtRjTMmeB<^WmrF>5DFj3rCtiMSEO ziTp+KF2;HXPl~8IfrMoWeTz1|Mk#-6~000zNVyPtPHnJCJ=6NHJv6N3LvMDshZc+9+{pf+6{bPD}>u#lUf;<_DAjZ_sKFrcM0k0hL7vx*Lz~3@oa$O z$&|~qA47@QbtIkX9L-@>z>#{j|MLyf4B#Lm(3cpGw8v=${j2|rwfBx|qIIMPg=_nED@#wu>N$lcCm2lYJ?H7B zN%wLgbJ9$&PL6$vJaskB(`J`da!Y@{WmHU*zgcdWP4h=ILXq4JWzOU6p51yLx^c4y=!Yg6* z*iX=3<%n^_&)S3-H_68<8X{#fxuradx69fY^#^-4;>pH~xJ*vbC1eM;5y|2!fnkID zojIyRKRR;^eQ4R=U@N=#1~~YKs-{keZScpLzqZSI&tp;ag(#R|wj4ZT!;xA+1| zAm@)i=rp&O5;ra@EGIs_@UUM`Ur@!V#Z!GB6oW1nligE~rjQ-B#1&eh+VtO$59kjE zBBD9&*zNx0{0EYW$(w>ip$MkbMgvoI()_cI%Fm?AXXLJV4Ypm<0KH9*;a=71dJ#e8 zK;k!~9Ekps9MwozG2#y5=hvm&qXq86mUY{)0WdXPh)Zi4P6Anf4|bru;3$MbS~MbW z`5GTc%;8S_2&Wa}=2Z9An_LB_;Po3KyDK!cCqPVG9wMb7PB-Zb4Q8o6dtM9}y;j@~ ztE#F(k zDxX9NPz~i7h_QNct`{i3FE`k974?5&D7j^7j=;O@=zM)SqvqeVZmV}|;`3`Eq!6Ka z`U7k$@>$E4$-1oSa{nDU4QM2)ur*-{l1+EaUfXe3Wou2{>7|jECi% z*<@&?Xl-v*2u~vlPqPu&_dV*Q*?72R#_dA4Z>5|8bfrk6!c}9)Z;0uI`2@WcxotoG*~B`yrpKV{D?GcdSrM9@ynQwl&KpWf53gn zeZ(&iuYkCV7)Q^!jZEne@M(Di7j&k(U&(^5r9&xk(vNT4y;(B*S+ZR@AEA8Ul1|ic z948M2Gp{W&f8P0(r)O{Yk!|=BNkPzpm8yB2Ju*B!$n08xK>x)&)Njb907iKB%;$sD zH&{wx*L6Q$xcx*|mAFy6@)x}C%;FnAIemk}!pqR@=G8@Lvi9K+#tSh!7=dvL)r%;p z4r<=nxsT*Z!xcu;gwJm}B_H(UT*kQ<|A-2Ed>E;KD{QJLZcw0{$yP1kKbsBuM{-O& zPpyes9AbahbVr`nxTT2j+`@KJD*i3vTk)tmXXCXSUzNVUAi^K~xEOauxw6TxdP?lP zgpbqHVKcMQ;Wj>=^R0K@QoU3LWoC}vQ=_j3<|~a&3qt|)M zvo^}ls1!?xVYIXX7P~M$dbfL$k3BI(XE1a*ovfK@!t>yFs|Ow6RQ)kf09Fx ztZnMpAEOjo@FofGCozWbhdj;wAmR|l6dGL>Y$T|3Ve`bMKMj>y5O4C3buXD`aX~ zK``y9rF1wlN;x23)2|;U!Bpo8ONH|_ba}@c;~9o-NVy^Ip?(y3wJOCL6QX*>O_YSc zqDlGR!4KXeCy`fdetJWhSp9uRdiIy$J1@-4MBxm5_ek>E=)LA&=${Sa*!r4=w|j+* ze)oHb*Yct@_rnSXx6XCqj||aX#WQjFGk}lM2P}H2aEl!)8#uNPwqGMB+ zK#C@xiMZ>It1CX~{K!(Gm51ZO)YK2<)Fhgmwsi{)#}D1@*Q1*)xuS@O`!&P0Y&QzE zbqyuuZAX7q!$`)& z=*E;O%ixM<_LA$d^d%{IBemaz9bJ>2k!II~r<@&)YjBq^&$1_f3^6}HYoWq2_s$W~ zLYD0hxZ)MJXxRVw+O`xp@-_Qm__L3Odq~=?ak-!~o2w?sizMcEL}MJwm}!%yX0Q`4 z5ViU384ZVq^Ds$JKoe*cl0iYHl>bdD4OD*rt2&(oV`8P1PV%{VUYIG+eg zWHCZ6ImsTKm3QnwT22lZ5`4&$EfzebKa*WXcR{}O4WcAZp2oGSw{G`e4oLqNP7AWe zNnUFd%5JlK0s&S-$;@7uhg-^_VtbvI^Ue~h0^wg<7r(5@tH@CxViBBV2?r#5jhjND zrwP66Rm(45`CnUhoj`ALfwxPr4`Mx(055OSydWL2dpihJvS!8$Qg`EgZyk$^+!5f@ zU7H|MC{Ka^_DDtD|~;JgJl*Kx8NQ*W&8g#V~*MZmfV&qr$>WXV3HdR$0z(k+- zc#0o9$xeA3ji4m@;IYz8u9t3p>*NZ4{LtV!*Q{J?1EKSXj&>J2f|+&Q|JaMadB37F z-5I=o*k5;D0J4@i#iO(2y&WatBdZq`j)a>Gdqh2?uVgCO=r<&B_29Vz>_)S%y{`bw zBjB1d#q=!4%qtV2Ya83oQ8`WFU+7Is)BAx0u%z^A-Zt< zQ2lEGR0RFo*Z4nQK9gotYkI||{H#dmgYPqC63Hi4n6>l!zpTA_RDWx}CG$3|Yv8Wf zdabAYYN9W4qHW2aX2x;Y@BOgq^?ECg-NL}GXHBvFM`f3UKdkZtER9hZh|4CidT3u(*V#lF7e z6Z7(%i3}PZUHMZyY62^e6FVckV<`Y{XWm2J+^zDCpp`2TmShcpau?Z*PK59DF}-+} z?eH*b?Fm2kW?NK{_Oh)O!NyfoM}7RfteDBX5vzbqC9g|-|MJnyqL#ML-jcg@?TS?E zex{4dbqA>@SntXLfp4oZZD-K=62(4K`f3q(h5hCN{bdtcutSaF(Ljqm(HNoG`C{FSFJq?d@zZk@qoU7_4CLbbCZt%CbdaGb#9)6H z_E3JF4C7y0!nRsrZkYw1KJh3|%(aIZSG>hv{z0`Aa{Z8{$bb2B;3MVAlC$G9Q<=NG}Zq5{q36L?q6u6i2wGe19 z)K$@f!hb{P?;gbZVnC*;~&YNg%e z)p?nE+T&W{Ry2+a--N>JL2thE-_zffKy-R_x+!}B(xr?;nLr>}T7q_vtb9r3SxrVr zMOJoZHW*4fbOgX(Mqe$e0SA4~Wz=oGc2HlIugTWOeOz@$)#CuvM9rlRe?&axw0hbi z$2uQSxz+&H5E8J$d;ze(J~n`51yBH6E$fOG??F{->HLp(0Y>2B9cbw>C2;D<;MMu= z6Wz*&(?CQdi=}g?;1S=&ylr{-FGUeWk20VJ(n4fw>D(dsG)$E8LzHYehdX3x7Ngyw z9wF54)=ibBTFTaE6`9u@19*UZrGK#$kX>+^;9LQBL6f?l(_{a-R5l+X!Z|$rteIwCXhTJ#Tke*0g58QDt+$@1y%iLODOK% z&(&!$dB>|CCktsykWG{DD7toBsfJTzDQ+>|X)=ALJXpMOHHD6K8W;zk+sh}suEj{r z2tgJ%j5mM}O1&{(zht7)7kwBTl&$$=jL#Xj2wyp%O8m*Jpdh}&1^WS{V)x8H;0l0p8 zWXXIapavkeDo~Rb?+V*E4d1~WAU~>{F=h)n9z~jx-IL*h1!5L&b4wx566&%8ToWoC ztM_f>2J%gw8dv7Yu=8|Nj;Sm*ajeoHr7Xkx8l8Gg&NuBRrv*c*qcB$s}at#4N>Ed{JHWEbk- zOF=G!cC%&Vc~}j9!0W1y0p1UOYL(+2KR2M+>GVcN$~kBIDGntY^w$(UY2`k1VOn2V zQGhDhK2}5gL+2itc;`0(e47WSAQvaRJKcd;c+w*YZ>Y$_&BJR`) zp^3Gp$U6v_;Rv!gIrukZnhEb2e^Ioppe^aHvXd5d7s{~STxqbM<4~oxF6%cWPxwV$ zjoKN(jmNhhXjKxa9UVua21>&)X}!v~k>eb+J4is5DQ7jLe?#_)nbOfbJ{fpxk{+W% z-!!`D-hY7drI$%ADfYb&*|4S!b48h$SQ;TH#EYBv~lEw-~`20CdOm#?HWU6I)_S-hu@S z^e^n{;`LR93uHEI>5DE9HV+f>Y_9m1nUnjY2^bYp`uMD_-ctV1`2`FafvrSF0pR@` zBJ+%JN7LwB&;Bp8>Em2?1I(LZ#367!c-KMBX zmtF80XJO4bhR8Eqwt~MOG9BFzP5vTn6i5_IQu;Vque_*lmyaD>a~;W|0aFQKcZ3P5 zg+_%HrTgZ$`^h%ZYd*fjM(1A_=^fyNE5M4BbQKy`5`F+h0l1*NJxIjuLrM zh6Ugw>KG>EpC<=nI*KJ_h<<^i*TP&656ODTzxGK5$k;n@#L+OArnZOh3%ud6%Om{c z)-nJiljqe)XeS>tz>XBcp{ur}d&--SNPw8o7@9C5H-(Y|kg*S{II-SFU9NyMF`ZK7Zm`wWj-tK5TqdgN8rIBrjN2rp5F zh5GC~bGe-M;SuT86Jq4@!~uy;{8p>wmDbO$9~ydq5xi{-WA-{bCZ|ELRUzaZC|hLz zMivTfVv~F7Lb-AMk{2Opbyu>-@P~;-zIW<`NN3FYi4LOLcG{^Y`Pa;Yn)cPaq7!feNTcm z>g$0)OW!m;`g(m&1g(x)QIB0@S2N<=RUEvLo-F~8j)mjzvb=3*P*Eoz6FHTacnc>2}O|0 zvzFb8$0xqKV1|A?VVFmVE7aybNMzTlw%)xdjUV9K;d3gobu|FwXO&|zyM!-Y#;d0e zH$4B6;y>mEI{o0dduF&x_|BGJ>xpEeQDTj6Qf8$`x#wz=YFT@2fCD6t=~EOSF> z2L6gGo}UTVOSBtRq-)|6QZI4dPdSBCLk0YY9e*0wOLbF;D+#HW%10)<trUpC_Rk!=uB@Ke-)=Azu2_74@U2Zh#=N!4%T{y&WYTE$N1{Yums%0R!dy8BfI74p5o|+^-t`;Y+y+e}{YG0xtIB%>~ z@+(~rFkKXRzP|xjZRF|(G-6LZ1_S?7yWfy8>_?Ds-YC(c>3RP5dM5D<6%|j*?BysV^Q=J8zUSo))CJ{Xpn6O*h*SP2&V_Ukx;6(owdy*LZo* zjn(Eu7ldI!Q&D)kWwxt%U2_%@kukt)FXCRol9_D7f)Q?FxkTedd^`m>-tK053=&JkDsze#qy!bAL2B21uTbjwC%)SvBCU)en4gF%9&ALmD41>p)>j9X5^(^V-^Ow z2sks@#Av+fGEC73+8ZeM{6TNQ-n!1HW>Iifb%h%sDcX33miWJ8LoQ*@_;FLe4EDdP z#Z&$9ta(=+uj_(wBJ!L{3~EqI+9c~Kas<|1yMq06i}1Rx(v%=Z zFZPsS!he3WCmzYjpRc@cmc@_nYbV&luJTbC;RqMw@-G z{rd%*Gx3eS&=3WtiUF7Q8vL-cYm#*|2SZkVfS*@l<8!jukm#PXs!h`Nd`B_YM4&G% z$@YbpBS8tfA0h;+3hF^hVA}$Gp3BK~u&!CHrH~f!+&5I%j9JISsyT`;w(-|W#XGY* z9%&s?2y}`Hx+&6kGFJSdIMx9vD4{bGu0?4R-rG|K$PF_cOAuo=u>-MDxHiBiX^el? z!BlJ$Kxov&_)J*>Vi^u#9-lx)Cm=_T8AVmW{uoG1%!>FilZ1MxMX9ZZ690!h>HRZp zJdOWWrbmeSJ-23k*oQ*6ju=zajbRpk4nV^}^`q6i*`%yR#kW7Q?V>5YKHHRku#J&O z#P6`UGz)Jh@wQ`p9o{cFmd`~U88R&B)yB#(j+XSZLb|ghFDp-gs4!FuR~lPjxPCr_yk_fGhcdOHK*~Fq}U+7zGpF!?vhew7xhE?EN-Zx$Y?$u4rj*>)ukAsLkJLyTP$P?R$_{-7zf6y&M(Eq(n2G zH=6(S)U$cCWD8F6aaW$2sM1v0NL@UAY$st1>piXiBaOM^>FnLa5w#DLbEE+o38}oY z)v}4}X@r(&qb`qkPoFx}#Pe3M9U1-QpHZ8MjhfZu$Qf_Y{Lx*}&!rpxHdhA2TmuL~Rf=t8%eSPjKX%|WAP~qeROwJDXg&)2+W9u-f8Bl0tq7;y) zZq32=QuTIHt=W-&=DfDKyScn^_Q=c2^&g=bHwo}jm^3uj=29oCq$7>G`}HK>H_;Ov zt<}6k7(M!@ni>J6)J%PB;&0{$ehBNW$fw(EK1@Xo^OVUQYUm6;1dq()|5eS>|9U?l zBy@VzMnHc)(gOYY1t@X4r9+|71QDS`Jz<2TeiRe}+6CGug9J=Mtg-_{pGhckcfjO> zK_Ew%ZYs#~dkunoKd`$0TcZFfh|)|VB`|KviWlz3dh%p{2KG9>S|`37s|!H6(nlag zSZ;!-o$&ZWQRJTj!h}bWB_gxS+NLcg=ahQ`d0r~Sex~za6#pYycobRK098e?kaBl{ zw&87y;Z^iVBAo{)dZKuQ9w}(zloBB2&WU$ZrAFqra7x`;0mKAl3#Un>?1Nd1cn0K} zy@8dgliR@i-at-J(PZKvVgyg2h67$A`(M07>BBH}cn)A5j-?846E8+cir&j8IN&9O zQ2x9!K)GP=<8R04kpj`p&Jsw0==A*Ud<5KlR{mI_fG^^I`>(3A!n;8BzxgAo2kFiB zyI^txg_u`1$tq=mR~~799SC8~9=4;zfGoekumiIRBD~f%s=M z7Q*Qjq50Nh_XY!Hs$a`vL}w-eOEGo_*!qYZb<@bWxf(~0?iIY7q5V-25-2nJT3B|5 zZOJxhq&O=mAM$MH-e7hoy{kHdg;01mLF*((k-o~+{12aVbs7Lep*)CDfimUrNSZvT z>ZZA!ecv--+E1BcWN$g%lMsV5i>u8%j4Gpsc-3WRJa%YtDIM|(Qn#CP5spo|k>4A5 zCEHa*XM5zqV^#x}oa_{a8~xYP`!5zKdbO_^+W~LWB{ksQAxUiRa{q2kGfEbEadxZ=3 z*Uj9_;}WNL%e8~^SN+AUw42O~?siiPI2lMT8yH+JRcM#1f`nPK3z^4wyHi|hm(r^i z^h7~Ioxzru5ibL;4lA|CTZ^`XEnMd6CE8!KPTaN|)^%cZVx&0RF4aFu%}x!u_cfwa z>buf+#dB+g0JJ_vz5-@X_#xe(x$yTT{ck;7&|=dEcaDZ)h)j50Sd-YL7Q63hz4=8V zYpcVzFDvBt?G)BY5YG6EHlMluAnuIOIc3HN*O?T*QDV7fH@J^J(Zo(CZ}QbHj>y+q zANr(Cv~MN#T8#LL)FP)YfiaH!Orb;=_yLCobg%k9!B*=MO69xqZM+=sINNM7pD zl-JKqUXW9qVC*h9y)~F9wwV!*^S(8e>~0a%zq5?E`B(p_I=eaq-pSEleY|k5lO@M9 zK`L1l62@pXl5srAn;qpf!wNDWJRvstwpre){wvm7Ki{t$XeeKVX`eef*gqOdB;MXS zn}ri@8e}^e%e5L7-=Gqnr$W@2_=Z#^8Q~FIi)wh|sZLnKk=~sv<(d;J=mcYi3C}%% z_|CAyUt8>no`g zisDXw8EH=0wmnewOeOdXeRm5zcMVNBz)u)SQ0}OyGnebqqzFE0GVPc){jmL@@4?T- zXX0&qiNK^FWi;A(!@ok`Sxu{~*PW2K+7>s_J0cZlY&HdQsC;=tZLm^A)51VuSI}-w z*RTAau5%F;aT+~@7ySg1@Dd)$i%FXO92^ogp;_WXJQBMZ&Gb5wEjn@X^E`s3PRPPf z52rU&U?FnjlAyH{@&&90IU=wA!~+lr1j9Wt^BHC8yDWZk-jA3bqk}%q>u5ZE?u2Hv zOdnO6bXd8JrhJz%x(*g0sCXv6Ne4hW_}UAZmpG@K%AUy>RT_by!u6^FwQ#~0&h7xn z2f#fjjYQj}IYX3DQvHecQd%c`?V41|B1$N@Mx^@odrCl4yHOqIG#a4$TTf#ovI$Vi zmpIR)H}MHjB-)GXSZ$>-QgE{52p;nlaF{c@9mU5UjpL7UX3YS{<+ICZ;)Sq)VE#yp zg17_%c*T=~;%Z8E6yh3&)=Q24w^E}~2AXb>Hy?~YehQnASW4HETS!Y|5*5TS{W#!v z3|7e6%FOTM7QXyl_pO6S$@`prZD>hU8W2kXA6s^=57{>T>4}>+q0PB}^%%F%tBS7h zq0bwr{=6UZ?4hVhBHSf43VjpUI_O{cck`wHWUvU}#D9C=ahg_54ZIdJQr`vA%B02x z(rO7b$p+E_JHbFk-KNV~6bTT06CV_{Jc#Q`ucF{gLirG({D&BI{oPgFKjO|mNuA>a z)T~JINyO3*V1rs3?}z zyDX$^N~5dGCfDJ;spaT|?hqkRu3iNKz07;e8bE~FO*IYTJx*mh4nN3ldQ!|E&BU{^h;GlBEq?8)N>q%M(nu`~-(6)hBf5tYuPr7wcn#hulu*P<_&db(7&I0Q2!g_PzL2s76o|eck2L9R z%|Mm&bh8;7=B3&fA0qxl$10F;aAnneNRL zi;5iK%te}NZI0IhWiX(T@z5obS3#t2K#hS1Xf8nYv7&rG?=XKgwW560cxM!Zc_+Gk z^;uK$5A#>TyFt+Rc0lDye$HR3`n(~5;u%5m7$Jh@1;LprnJfFbz4z7?xy)z8=nium zMZC+3riZV1-lq3wcC-8{c)}2tgEtV)aE;NT`FV4==JA{!J-di6U(VFI;d*lHj|r~} z`adrO$^jx@wRw;zn~-z%Jt`ov`uwKF8|k0|=3Dm;^=0J5pH?2yL%hq%w>GtU*9R9E z0IL|c-SPt)>SmUu!Emy6yLsY3^N^PHDtUQbU(yw_tZ+p{`0iji4W?;3x$$`l!`akY z8g2aT?7NM_=I|$4sp?I*uExjw8lme9eMbr3aJG@jS~Iqn_Av({eK|+K88a(f z&X`nwxwP!?+EtjqGIny=!g)sQLPm|NqaC4uf&S{QCb`zyQFdTI`=Q&(vQjdb@T4xY zs3{M1{UT-H)kw)Vo`8c~?aS4?0%ps$+eQ#F1G!U^=dcHM+oruBK?-YkRn-(E9ZPp= z%68K_TvZ{?jGH30f^ub?*+8~&{AQd0WQBInvJyiE7UvvR?Z{r4{n&4H$HvW`0Hw|5@A0EceZ%iw3c1BxVYASR-8RG!}NrQaCgGC>~UbP zrxf)vH_qxC?G1GZuPa`xUOGU0(6YE(NqmFLD*Go*R{!9^3-UP!^0j`E*$)ceUAY+& zELhNw$dY@SA#$wKldpX4MwJ$bH&|V3`GqurR8Pas{vt|kbtT@&eNYrUa@*(fK_P6Q zRK_FXu482#G4$3hXRtYr|4o4(+@nr&{2O*v(1=Rd|k3iE8f;>n!s z%nvp@u!$wiisR3P4;y^m92=f8eEALu=_C0qANXl+>2X4G_5Mz7i}o!8`bSQwrBsbG z=AF9iZayN}+(6WY+`H^73_Rx3kmj-1{M7A(=^ll1+ba~I> z$8f=XjM(WmzB6=&8OC^X?v^%med+oxPdGzdpxjZ*_gwMHr;h1;#G4#O^@fI*KITLU z)sF_RE3#fX(ov#eaubPFrYtzrtJ8<*ZXW?Qu#Po@drxU)6%J#NHH(KUm#H&!v9&YjimUa)|@J&((J!{7Cx z(7|=DI-2NEj1Mx3-dq{#B=2=3uOdQbYHl~r0`}R`?afb@&2i-70aRI2GD}tHTvqB1 zOi5@kF{>ljg13g7x2pUvdB+{&QuRCJJyM^)jVms*;B!FM)%`iBy(!VI0dJXRaH9~l zfbz*;H}}L!B|n+}Xd$A+26DXLU2?6oHA*dYY8U8Tc4Scc@RP7Ln&xMdUNT2JZjs2Lm%;LRO_Nu@1 z*zZ5y?n2io9~kBkX?%$FLz2Fe7aW-rGBchWJU@6^(x-l<&4xeP(BqS%9*(JAGj~PW zB&N0cl3Hbgf%ejwi!Y4H`VhVCrR|l;Se1D#YJ@0SG~Zh<>9}iwjYF}@v5HK7SRZ$( zUbBZ$_ak_|Ue|-OUQ_u7@fko1l@VEIe9=_+$Uc*jl9KAGQs*AtHS1aW;V-A=fPqOJ z_AxfFh$ym^G9W3ShY!`#+7X{?ti5lwJlVfEQum^;s~S1lHNzv6>%PfQ^&(KAO@OR3 zfCo7Mu3NfF-C5N%Nv}2vW>I#c#;e=PER@ zWJ?`XJ$RC^coc+Sfx@>#@d6-#>p+}fz*7TTjto0fFeUaqiOoaTsp{__?Xsx_ydYB; z3hfGGQUJjogttd;)(B$Y17JvK~uR%k9F8YRJ**>5|6N zR|cmJd?mSeeSRTE?@c=m7A)tR!9^8}7K+|K+oOfwpZm-cy~30?f0b)GsNx$&d}VdB-D1l4vy1{wOrOL>;DH zS?90QIrV}r-0G9jls~;+=zus!yF%yq;mzuiyF-=DeqQ(tXan+etH>Cq$rj6cbkz}d z8bNEO1{BA|KNeITTW+kk@ocMmA{pg8JaFty@h0hWuW#r~h_9VZ?AO4s?Bv%Bg97j^eS&X z3d4^5v<{4dVJVkB#Nc0pS6A%1aAg@3vr>%JmPplc& z0sc9;5Z()t5EoG5Z~#(Jf8@%~j={+vto$VPyig!XYVf%m_U5&i_YYX8be{2Rwf z3j}HzjLunF6l%S|=1L2annX=2SRY91gQA>CN)4noi82TVKY>gJ8Tug51~jUb$(J|k z@M8xlSuhW3#tjLe7gJ<77K{O@SiwC`h%6{a`vn62f6S_g;sm`XO@`B`Kpr4OJ7F$# z%M!B%Kjwj94gerTp28@dIz|oor>1)F$4xcc`Ph5CSlJFVjFzQ7a+U0?P;Vxuey zMF?Zbe{w$jW5M`;uuURg76rcZHC;f&1F)7Z*W25D;-Qd~$;a?MRy)dKk^3D69{_NG zYvXlp%um4UK(i#U!*z}98>1)_kbp!dBNAAUYrqTEGY(n!P ze|0f{sat_2t-FifR`X9)+T~;1aOW5{B)Yi*LbxLgU;yW1$dH~iIZ|8zu!15-|2}yD z>|O_`0b6Qo_6Igpt^-eZfD8>6Pk*;Zi$pGaSA$Bw z`U_cIsY#GjMVxwwU74pRZ#6wvr&sDmt3sw>)0b*=-}cP;4yH$~KD%3_l6^zzq*P0j zyYs2tObH2!R_PGwxi;YJ=7J3s7~MPOtdr!lo?> zGkjc!TQay5L9hrsoq|2)>MSm4bNnv3Bvk5z| zOcWlj1)8gUL{ZL~U_di=JcWVfc%L+OULD3@dr)Xk07-Xu?R`e_QVIjp@h;fsKL>=> z`r7`|C8Wl$36e%2I0n4o0T-~{<|kfe<_g^|d_wNh+~^@CC66&ufS_nAaLfnV{uY07 zv74;Fff()quWR%g_yQ^fs2X6?6qUQM*vBha8f3|fzcN{|HED-KJ&0lOQhySlhqP%S zb@c`+n7IatIJ$;Kxh*gpI-YAM>zfQs(-~giSaD(|)ERa9o05{D2k<*mFRWlk9d^Ht zVp&rdKCY4Jme0Snt*T7!e=Ini;L@zp?oOKG8&jGtnQxZ zo840Q^f5nj^IHOBr*(tA2DQxBqWiY}30%Pu^GVfmb8!r-{^K-B-NzaGYC4QkL=JuM z2sUjvyY*?T;&kR%IpK>qIfi1^(4Za;>DmB zy|Gl@xm$|d!n`Gl;20-Yh?2Q&I5pdn{!DvU&>UMH!SsM!4@euX0AGB77p$rgH^FbVvUhFdn@uJ?5Lk& zCv_xvU1OUj!=DXX#L%caMBqiPuYq7%@&>sf`J8Fq(cRyW(GDa|f?~%tYF%y4*RZ#P za0b7-SKAX0!uj8j^EzT{g0pEuIz6GJ(rDlt0q%SaN-p8(NkDzTt(LoI?7_As`D&noB^V{P{V~fxw*v)FM>hfvq#W}=G9);;Rj&XlDpQ)l7~vLk;ZE0WMuM_!e@IkJzFZI2T2z*de1g*T5b#@j5ab zwj`Yv@DyB(1QN7rAO|H#AGf-w2o*i#>aSBS^#>nG2c7v1IXY`M`4LN0hi-i*gBB?Z z5r@a0+fCB}T55ag@TWER8b$jwR^h`tZQ zTKCh|$OF5J#Ovh|*d^gKD8U}6sm`mzzF%=e5oB zWP+C~nJ-Yml>jS++U^&oq1WIzDzeWqKY0QK{%^o|6~coLB9Xv}P=Y5N+(sGyPOi#3XE+QaaS;4(GwmWbELJz9Vbi~rokpGe!Z*8Rd%^qMB_BB9C{RLf$?&F?3R zG#g!d>}~(xGTu{QFYk<5v)Gd^;gFX_?|l=g8an{0u_+kASRZ_ zOpNZ!;NN3+Xp3DlR`f&&m;KZchcCZPsQU>HT|D0#ht>HE9E* zYr54ldtU&AeUoxlx(&QjF_`FYb(cdomt@}|Yi%zBMCE|NBlN>Im!D(Ed)4S=MUI1L z00Y)d)l(;w57tGQS1&RwYn6s$4pO56a^Vo`LkVxmbm#UxmZLtus1=wjqzjN0j>>IZ zsnM+|bl?ind?f*0>&nBVY$|EMXyl6(_w0k{rV}*t$EdB5`~8ywZwCB?RSEiis+)|k zBPEZZixVI}{~YFc_eU_#$@6ICC=-}1=)t=bpXRjZ4C05E2=Wjc@MJP&?E5HmDYDkV zx#0HxpyL8|)inw>PW=D2<{J2?`JY?$ccTv=G8jxACgmt}DzYYlJyGi>NZb8% z&~3qIDD)?(+k?{r-LjwJPt&OK{Y(-#ZNCIMg@H71Ihw`YCtage<_4q6|LhAKwF^=ynVle&uDL0I0|oEqsp@vJVLq08CJlxy81BPUgjBMaFRVBy+QEdpZdU z%?^nqM5*bvJsTS&=WBEaMo9?7`1->Sv<9L%uS5n4J4+-ww8X2-cT@WVaMbRr0}?t? zz0OUV^S#F~iT;G%sJgVP2}sI0=STs06}PbZKi~+YaGVIJu;>RBIR>x9 z^`5|cOD>}Vp(o65<+E63r$mc!TeG`2|Jpe%` zj*}+GKYw2nWjBOc#vs<&Hwb>hCBQ|WCHC18Isj1+nkm-n^bsf0p54x_?pVV!L*Kqd8HCB4Wa zUxhpOt1{4|H0Wi9lv#)6>&CG`ni8N6UEpUtfh|J<6yH#K$qu^jgTzOOov?yqKn?Kv zmH!*xRLP`({0D$IiX3C0Mcy)4G`|L5&?kAU31nfhe6`88696Kf{c%SHM=&}pER^r( zUNjw20oX@7VH8yIROVOV^fJo|P>wF8s*V=m=(k0%rMmAXN2*x!{c}H-P4rW|;NcoD zQS%vlH-S-cRb+W;O3?Sdyq{kwLdva)1J5pMOHYKR)CruG;yze?*WIs9?@+=uaORF8 zYXrbG1cO9Vf}S%q#HK`|fuYpy&u@tB`n@CX}CPMStl0FoBkpI%6p#sFMzvGY- z)*Acf;Mefx}7*9TMvE-k8lio7orE1JM+f!)@~;5ehv=`$+G)#5h(9fzS(QZkvtc(#4Z zCK9`8dXnr;aj5yl2jw$bOzO8eq8nNbPHupm`Xz9Q%+h-mx;Cs#X3C-o*$uO}(z})l z-TgVvd`Jr+hJ?cFDt<%st)Gbz-WHK#F^*e1jR!$eWcGnYuA*P<4ZzE(a7bW%=9T5G zC>nwgwTdD%8UQ?MKkw&3%t0Py(7oBqWXsZZqz(2>`FnA^m@XAL;j-oeJRqY-5&GfM zZ^&2MrrVK8jB&7|RXGsq6&u8sui4@>rUKp7ypXFIYgUJBB;M3O*lqCQeT01zefGpxmL z}m%!oS6&K)bAJaE;->wCj23qv2C zom_tmQ2Z8@6j!?qBL4-=U!mVzV9&ktltF|}i`+L!lU@^<1~IpOfkThKA9#p{9hX%F zs1|5QK}3as#W#DBM-8mGy#e2=42i`!>m`6Z2N?DWb3u=fwjsTo0@dyoVsDXHONMQq z4CysikFMC+Qw)Ut6G;BTLO@4^^OIirDOPU#sbzvE!2C)SGR`3!`=u+KdBaimTJn~l zGPw=m0-j1*vw+4rxv<-!5^u2M6_1F$#dD+xGPm-9)9xW`yhfY2x>+SawX+AbS!-02|4NnNuqKn zm=bT2)Et4`cOY?rb`qj>C-D1SB-d9SkI3squJZ|9iPM^4;ISX{GBrZvzXH*8Kr%SL z*dYu0K_}$wtTHx;TxC)PjIQ;d>IpC`T^M=$JR*;YZqV}py82h7=0P_bg!tJ}r&dWJ zHF4i#kLf6jKg8V|J7_Njo<^t8BYhbn#dKKI8^7Bb6$iy=q5#$Q>>6NwhL$s0zGJD( zFIaD7zH1@Z>LIV_rQ>O~wh^_{oHxl-mtavT44ufY1RekQ5v)=H(xxzE$ha%yGMZee zb`{B&*YQ8td+)HO-fmkoh>8sm1w~p^P>?DLqJRWNKtK$=7irQ2M0!h5q!=jz0t!Ot zEkL9Mq)RV~^e!EwLqZ9Ggm_;3?Qged?{oM5&e`YQ^W6Q1CRxc!$XZ$R9dphx#*7%2 zm@3&FO+Tmw7_D1T^K580XI5(ZdhJ(DeO1XE6q)F?f}Hc@IE%fUyvoiYbX`xxmV>Tt z8EjPv)SFg7%(*}o!SN3JVOB5HnpIyaGAF1m?K$G)_U&)16IrGA6Pi8|H}gQJCYyGa zvB*bL6^rxJbR#n?FQd5|y`R-?_gp)>`?RQ_)*Q`NpWc8>Gx9k;tGU-A3l;Z^{or6f zzE*3A3>jFtZ>v)VK{D%tQiKM*#W(^)Gp4+{v8gw+EfhkO1XWd*OPpwGXIqL@t|DEV z@j3g3!i(YU8BW-JTDUGvGfjV2sl3Zg%8k=NGh3=FN0O$!wyJ51>^%0N{fHJBkNJ0#c_Iwy9p?T-9SZkf{jw5D@V{s5mT=n(3 zRf7)uRdrl7#Oeb)L!vDoUQE_xn;7xGDIM<=y=vg#wEF1QK`znzNIP|4tHBBMe5uBl z!m%H0LAC%<7wrWNkg6`SrZ3tKlHT3p<@UT`_0eA)-tfKz{%%wPK@$(oN4 z2Yrup0UhZIxUj##Ds!M6Qutj4v!0L_k5Y4PqrVn%DzAUS(VpoZwx_vA)oC}U&~WjxA> zXW@4X_dl$h$enU_BoFio1OY~$SybZiJ5aeFYJw_Po7 zWB#q{y=HGSOoBx0AW_HsFbb^Ixl*3?_Yay94F;#>dp;f(PdR*-kA{dJ2o=>*lQ%fs z1n5uz@Wbr>Li}`c=fT@+4Vi-h9|y8r z*UC)%uF4R3v(7Rwxe(Hbi zs~Y57B1mrz7?&F1HirNY%;0}+%5mu5Wy$_e_KRjNQKNP5(Of*1e6&~JwomQw6&En0 zcBQ1*sOyNkX?v;_Mi9p?1jfjL>D>K9lm5ezT}NFb`}Hs7-vLH zCL>Cg2Gm6SP(P3v5Z`4XEKVzGaHIx{+m8~wO*Rb?hW5!F!fswIT>+33PIsRUEu7+x z9Qh=&!AwK2jIHU{QE@ULPqz?V@bq!U^p1@AjXywqFB7CPc?!22g`TqY4_|f6LmG9_ z&GQbc;FAltXvG}|>-K)6MHJbdAH1_TH!216rx^n^oIQD3CmnA6fJk~hzYM&^boNCD>ax(2 z`qU;FsfxO!8Kn}s;>SM}XL03Lj4Yw?k2b%^~TKeMsQ0j$|$r`kuD{>LHJhRp0>JBT0 zH3;36g&!MgRV1iZ$nC`+K#F(0)YG2aDlNlRylKsf$ifs@cK)&{!=lc`lYTdT{A5Vd zt`ON^Nt1_&TL3TU`w?a+xBr*G*#Ayo_h0>9N-FXY-2^zUoHc&rf+E>DfYM|+?n&1m z8HDJaS{3%)7O}nnOA_!#K_=ILtuw5O=i8Lf_2~T}cTg9q?}J&PgDL{f?!P2j97yVK z@KQTWisd1m#uF>{_`RuzA$GA@)Q@BHzajTEjrMm|q^5Er_IN|Yr9hKJRpSoqoxz?4 z_`OJ}?Z5u2NrawTbF824q}{TccY>MKo^3%FFOLB9x-R%;pWZJEqzvrYh-T#J{2OL( zRY7~HK*9%3l{w-vI8ij%h+z>NzYwJcn-6PzjJ(*t$14v(Sep1U5jui=fvMBdVmP?a z%wfuP)p(imtoc=gt7(pOnpe_MFlpVTd~QCoS2yl1&~9j`oC|%o)b7V>o?`#RemmZe ztA2q=JfKeaIyV(Ijc(9w=*&F)kjvEB8NKIlsB^Yb! z72gg1$Puvph>H6$fvD3FJYGWZtLLh>zv9$)JDCyHQJbB~jw#aCZqlM!wKnakn0jLt1%0TE~ zdn-QSTl$dAA)(A@e2#k$C=h1n+(I4jylwv?eA9x$AR34!|GMQnB(1S3w#Juy)EtGl z3#{B6hzFIzQvVC6Yos(M9OMQH0o=Q8!~x$bS^6e++rAP=M@gmaL?AOH!KO+0ntKoO`z(Q9L8^rf?{{lGh4fG~K2Tz&*0~f-bZ-K@f^%rG&R{cN* zr}uCX`1AbrhrK>1@^$mkoRLh_2vi0FJ|>-X?JWM@ejAzt?7*K7xZhwCEi=vHV^9Db z1+eKH3UW<0;}AG5kdl%EB7?@X|Cz*60Ji=!nzz5_wF=B5eqx|tYat|qf&|8G0`DHb z+C&MnyV*b)_u!kZZ|vQi%$~DMz0;!JrSs2u_DkNJHSFNj@m8ApC@46Dh@|xAWEGonn zHpS3?m0X&E9DgFvXKO?IZE)&GhQzpy`Cch91`e(F0<9oJKQ`o-*PsV#5)Inv6eQh> z()YpQ+9E(6f*r4dahy$XUhf?M`?#N|B+JiH)_d$--1zN|K#cOUwEIbz37^b+P4J-dzsA!Z-o^0 zD+6&>&%^5U9lBpqnrzi&Ij-z{MF&?zTEGHaUl?K(Z3@vHvIT}(`;pZ1OAjKah{e2A zKgSHyU(MCP^kw&(&VC?;&J)%J63{!f!-e`tW1~)EqHs8I~zO5+dAg-$AOmCo*>_Ftr1F=Xf+)$C)E zg@(T{{P2T=SteBU(T4r@j2hlO0He_6le)NLH}+s4dzjMnLNab;89%74bCz^dg}tKW z`mW;UeR>E&-%G549uW!tB9HpzjYrorRYvuRF)HXp%P zcbrL+YIJo9Y_{Pwt^Ku===1G*i%Fto@7xW)-O}8}K`yU() zZvKWuWJB{IzMXTuz7<3VQ=&R4E#0yclt-&#V96qOm!^*Z%M_;7j8XWgN|8VJs7fiiG|mB{a4zm>`lw3T zi2vofjFaHimGlrr@Ptx{W+_?iu-UcyKn+;OcjzKmcHSw%nGUx3U7NC#SB?Y=W$X<* z?eKKHCHZiF?t=vf+|>^4I&2pssR)0#)cCxMmK&AFgXkkoE$Udj29Ms3 zf9z5+-938KAhu`M`$=ZWM}mYufwidjNpOZ~5ZB+9qI>jzmMPZU6;Ta&79-#(@2cMa zWrmoJk}N;)iA%#cwyVP5v$jMg!d0?aM8Jpi1UU zm7jy<7Gei7^gB9=rR4NaCK5-Y0YO)l{|M4m5cSo zrMS~2mWac;D-Lqb)<>pel8*h-tkXYzecy(bfPJ!^zOlTWrbD_psp?u-gAWRmlF%Wu zU4w-{2G8apT53<=JOH8R*s>ldW1mf0YrnQv*Dazbf1hF3yY$Xz>35W`*l91PmkB@5}+s~<&gald; zv%H>Wo$hUPr8(5H3fJ4ub&D8DDxASV?icpG<$P2~)_ThV?vu4JoR2>DeWQoS7W!x{ zvnYS=Tc(FRh}3=^lo8HW$RX25!~DEIdy1ID9hBDsVmODmBcERmp?`$S*G8e z^=?jA!>X=%z=;2aQ{vvNwr0U2SUEZzgy%Y0n`D;C>X%EoPF6eAa1dP|URu z2762$WCV6w;5piqgD?xV`z!X+foN?S#Bcd$_v9le{_<0P*FYb?0aPhPffh3Tj}-E+ zXsa47Sxm)lPAcPjV4;&nWI$vwXD&ZD$a_jEhS@PSYDc?i^Ek z;F3#4!RJju9{|d5@N^=A@%o|(fA2c8Uw=iJryf;4&}$7xzCh9F?*Axe=%;kPI%f76 ze6mRu5e4>%mYlDLvU%F7*d;OduXJ%ZMRgFVPt42p9g@cHM=5l}c8pkHk=WrA%>&XG zl08w}Tsf(>dno8s1x^X}A(^q&Nniv7wc5wx>%*E;$dC*1@RNqa4<}kIxa;<=jqd3t z+1Gwn48ZD-stjx!i*U~=UXu(U`2(pTN#GkXV`F(~--URHz?s`R0)OK=im%Ews>k2- zasHy4xQs4RY}}_;fifa(E>ZDrvn^rW)R>imc%=QsaNogFU9?6HGB28$f{|{ zu>106UY_QRbYBj{cT(*b6ICgo!%LM^=QL!}2+2N_9iGIExy+9Q0;~sG+o*g&vF#v# z0YUA{O*%Skk)TrZjb8b4e@sxip3R|(28}#%E3+IxmnnEh)*>|MoMHR?PVI>26o#om zGhN*Lw#^~dDU4`?rs5HU@DmUeAOEb{Ru1>80{J5l#ZxTqe6|F+9)LF?Hx6RiRz?t8 zH7IzztJ6&h3Ngdr8)Oe(?_U5>&|7=KEcwvEYq}4jqz#SPU(j;M4Aa#hdlD!){vs`b zAO|pI8VGV_%&w5a1MNoC?LF;3UOw7^2HbyDF*3COIs1ymS@r}5AH_BYXrB`2VeQP91v8Ik2$rAHD^5vFslj58aLm8RQ(|q~6gMew@3OnhX zo6>tf&!aU!eF0zP8s(Sx^+k+kH}o^WO!R)s1&9_TqnrHIo|CIrA2*N87E$39 zRiLlGA2g;{8aC}_)xtC}3Rq))*MOX1<3)ppp!lly{7M{wPF~kDPsr`zV0BC@&pu0O z{G=N?xP}Km3SCt_sa8l!$}D?Qnb4cH2y7;ZT)3wg0J~U0^9{a8&H`wJOJ2h$czZ$ z)j`-w4`TbrB5uZ?7c?C-g+Z(KFC_LSNG1I7qoC=|(EnpY#?%5rl1467>mPcw%9w|# z=|E_v%e>7@6Azj#NB$6r4qOM1qYMoGmspek%=zlS-{+rP!2T~f7V&F^Io3~d)2@7& zJn{W)Q#{WO*8}fnG|z5JY}rG@jSjJdVH%7)v&R2t&UE_4>vb1E%b)IM0f=o`Z%!tv zG>rK5){eg$&2|A&307FX7qOho>j~A`&Fk4wil!!J{j7}+*fXzA0##Cb{r#|Yv+)td zkV~H|1UP4}94EF%Q!qgTFl#8MO>!AgwkCo+ppl0rt<&%6j`pe1%{!({Rm0^Y)B41g zF}#|ucmtz%QLk>>Z|T@v{t}vAn3wIzzjO?i_`7E)%7POoo?E?hjnOy8i-Z03m#t zBx0QFjCFGG4UK!}epPh~$BHlW*#F}FRi0;svl+F|QRLJPqKDk$U~#<7uQx@+s5h+2 zGASN0LY;`>yPG?!)^!+=Y;;pzq5q_bHZ<=Vbj^bjnL!3=LvuN(K<=PM*P3zwidNLR znZ;iKryLqH6tFb>i?0oAZoWJBD01qD+0b+YGKliSo;-yTKq=4CP7kwFUzI(PhPx|& z;!9TUL1pcPvNy2rK^Xu8n*`hcU*&bW+ys~An-mzydK%7T&|LI$allDTiFZsSRM@Xb z-ZzVUh1zQ(K^SbZ!q30KUFpxm9lH{BqbpVH%;mLR_m>;*j@1#d3gJf!F25$6#-)1o z6Z$@HPX#Bg3q_P>r=m6^9{lUI{a-&8_)tztoRWgEC{E>2@7y`Vm#}I=G1co9Zx8war zO&qGc@3Yb#%I@CV$+zuEw0+V0)~U5ULr*y3f&6W!%e{{S$F!L&M?$z4w6ZVEe2O;B zB<2f@)c5i!p{}`cCU8XjsD9*lNRO}geLDI^`P`F2LUVh%#kq3hH#VuLjZUq9eE|Q( zV{9PeCSsT>jz>4E>OSh0|0Ky3;qGA2V?&#e_+?ywFLX21f@_=jD>%2MU?ConaV7?} zF)sC5XNflZ3Cv(i^fud&-u(>KjKcY;!airsL`k2P7u(G0CSD7FS)=MQ5^l~YzDAsG zcuM8%*J)a7JAFT-=i#KAL+(((QJ+NcAU~dyYusXyHPUPqKmBwhJFOhkk2hVN zBE-(<5gs6Ddb6%&E~Y%K9r~#%bt)HXrNM9)j`L>a;3&lPUrAkF@EW36J{RNE#Vk}c zk;=(F_7$0F;&J}T5z4*XS9H}XLzJ8)z|e{IfMpQdU*S7faRilnHA)5B_I@uW?)cb` zTG9k3Tb_{jKo`MRQmkgGZ-H5j%|{ay-7hz&@??LhtBZQ%Qhd>0YUZva@LX9HCySDF zbx0Puc8Cl3)zXA%dSPhEz5N7+h8rRx?ELr%Vdv%-NBj))W2Tn!pvCYs_vPhUti>D) zM=z7o%-u9&jX@{XYN@0|yu=J5jPR}ATDvzgU&LWZ-Y2W|YZZfn;@v(X%v5>Hn?l(4 zFW5FjhU#`1vRu1#aMOyH=XWV0U$B4{!f@ZT>jM92B zXj)dK4g7~&m%9zq;9Gr6B|){&3i$pgQiN7uRXOkGtx<*D<}O8H#0RczBoRy#lW3Tr zZA!Cs`5>O}naq@O+ zyFa5Mca(SNbhS6Ltw!4Rr~4H?!az{X81Y?ns7mK1`KFNF4du-Q-8r~roX5V~ZF*kf z8sTW7CmJ6~lBBWu4cT1UkmK!hIt=Zp`A9M&xHKToi&-F(O}xUm4ils4i)CAiMY2*j z*d_>!fv(7Nwi|lOk`4tKwio#=zJy$--0UKwNWsmL^qniwgk|MESFcPY!-V<0v$s?X zV;esguIXmOlt)fCSVV{My?|$yJ(|Xt-e|RA`%+Oe5@0J~uPm{gxj_Dbvb=ev@tWW> zHVL)%hA-R~dzb5Fw*GdZ{ad#J(57+0UTONN%6$+0azjyVm`$<)qnSEN-lg^0KgewiFa?v|l^IZ9>#zTU@{ZVVrZA)16m%DWBOx&u} zbVR5@Mx**zXBx>?@2%gB@%xo=h3_M3T6&XLP242>De$aC+dP%2eS-#MW4;(1>8V0(*WAcgQ`6=;-u^;;D=F?d7dCSvqxMs}Xc>cVapyBvVw3aJ z_t|}Er>w3xIxVk1=u^tz@zG{hH@)%1_YHxTxQ0AN(WvUmm%dB?D==$}T_qv*!<$+D z=PLng{tV9`c8!O4o(Ye6;x4`gy1xVOZ284044i8qLA7C%;XKr>qbhbZ+l zb0;||amBuipgh;@dg^JQ=k1y({&b-BCGKH%hQ(tP9~LbNyImuQ=&LG=WPxC|p7y*mPPbTxolTWe=KS$E(-1Mczo#uP6(DfgbyrQn)ubi)|L! z<)@1MhJ0?CpoZD)o8Wb2=(~{1^*}l-pYM0eK_O96%!u0o_P{}%CnhYHFSW+9@!$Hj z{jY4>bs_eUwx=TkZ+Idf;;Y*iiziyHH0~rBR66LKVDdOb#}nneXpCKnAq41<>hL4> z9j-0H`B`J)>BY@24>#CYnbScgCue%9G^r=VkCClkX0%8N55htffMdmEq6d2w`^+(y z9r0rcP(2{{?%#?|Q6US9Yx%A1dlXj36_;=KgA;h`$=@&q_jP$NbMa*q9HMCvb2U`j zu^_Db{Vdz=TOx&UD=UR^vpX+Oc&;Qstyc8suAo*cD)3d5lyx?d1?WKPqH5ApX(r{ls!WHv()r}u96q|)pM|El1QO;p3$sKjzxzeXGwa4a{o4osd$%l! zIi4OW1I%y7BnOtq^_8sPKQxe46mrRTI8>JH9{oEhi zRYKa)nF`1lA8pN|FZOTWR()!YdS?371=wA8#!Z~0$Y&HzWJxc;!hgP@o4vCyaB-;Z z+31z9X{WV{cSwW17sRO)dsn%jSlQZOO-jz7&bh&FrN73n4fZ^sr!3I^%1*&V%9->c z@e}u}+YBx2=1IxsbaOqQMP$xadEN5JZ7BNwWnYn`Mn`kdF0y|yUnhwR9xt)ga;Z4` zMf*yrr=fisxA*nBxLh95Zh8nBJTPbsDRKvuvP4V0Kt$ z(u7X563J<5@yhH=H^Hm=52?h?ih%u}nXh-}=SQXIa$U#l1mfUuN7o zPufyvoUi=-7xpKW-87b2$Ncu7`rW2Hj1lPbH5V$7^;T2pGJV=j)ho5J&Z|6L@b9`f zUxEGPDiMONLwALA9ANDWsUCVOQ zT?B6?m=x9QGxfJ4q#E@g=vI^hFh+Z7;ZK(%wnSOq$HHud6kE9XYVomw-o$a%-r4Jq zpO|M7wQrj@y2*OdrZlU1-{zoyU!i_nT7eBfsaK6#GqqI%E;L5zFQ2 zCY~>Hk7?*(<)lP(I=$pxYT*yYoUh{F;MOw{FA;)a=@ATI07Li?nT}is>n(*{iT*y%n4ppN7Q< z&v0Bg?am#Ftx@EZd4+x7XtrdQE2*s=FN0+a$wFo3_INznWE^q!@TDPq{S7&&D2SRe zAR6CR5`((-^9v%V_w2|K#Dtm2^Wm@+4q$em+fZ8wrF^>e<~PJ-&~)z_X6Z)f?m2TA zWaP#$ni7it4H4Pr+ZP2xRcAU2|DOOF`=xqOBDOh9S?+4B8?SpMAVRmaVTWyN``W0B zRBci}$I;D3TgY5S)iKxw(S7^X+b&d77`%^E!1EgtCos4Lvk-G1OCN^no&F7(NiEPi zC(0`5FmqQ!+_d#XQjO@EU+NHFuH-;@7Rf_3L9JipN$-jod-|91cbEBgu2!9ItSvKb z5IR9vUA@xhRup{Hp518-ns&#CdZ>bL%HA9nc=U(&Q0{HybccxM0vHpErALfGPq{5; zPga!oi7B{5+@KEbSS+;~Lc@H1MCR!&@424ebC{JNY8H?Rgnmli-af2uNN>nU(Gy={ zb{2Dn*2g0P+xb$o~3>Hf*Rl!>`52J>PEhLNs8|*BPfJE2&v5v7n-IG=SpMYx98t=beeBblh%V}Np0!aPf!%woO^CF?IoPWF3*j1==U82< z;WT=uosSx`Z6sMc0%(zyduemG!6_@ghxFO9Ucjzwtnz~MeYm*rDfL@$GJPnalaM$L-4yG2(S01psh=Tly^wUVS6a!M zSk0@3>&tg3`+@stX|!j_g-elpEd2efhVDJ^4#1DqHi@a*aof+FCKwQIi!YxOwElhKuiN%FZ0iR|=HW zKUEusfI6t$ON_O7sDioh^{ipx0;>mIAqU$!rYYyKYxbw6Vv_+w`s2+hHjlk2jSYyyCeT>MbAT zN4whkGc(#}u}cV3U)Sg#z$D#$yT1UobwglVacX)6PZy*`>=ja^-Z!A6kP2NzYIsQ% zZg~c$X z6mRh|!daAha*CyWi25YeJPIf2N&Kx!XO4>3gBr$Sr)x-)^e;bi&4+$+jy7qKXJN^0 zuU67dTB#6AyZ^~n&XQTjcn2lsC!$f-yDn}hU`USGzSV1VS&5gN`&iXZM^(H$*LDTK zkxPNh+QxEPMLib!B94>AVd1ntm9vj;wTW$eUosgf>PI~A)tjH*d5c_;0O2VuzE*Qv z1jWVJJtN{Xoyaw&XuQ)6On9_+;RIf_vc4K#&v@d1<(HBK-7oRi((dTW-8}tu=dg>Z zMZ@R!c3KXuip>P(89q&=ZR_RmfZvddccrM+X+T^cZ;Jf{Uv0wI%Jr;XROwJrkL6=x zH5e+DI06Z+8JVk{n&#q&Zag=zI2Cr!HST%Qc-xKRr_b)ZwzxyvD?TMyeBsszATEo1 z-!ZWbc%{^Dik|gzl2<(3=5oqKVKgmL4&(jm2ECVJGvkO)o$1kEw+v$X;)9CIJctgj zf+JnJ%6X5YUC?%u844M;8=7Im3)=aQL+>mpw{BMm%yzI-Ph6TZ#7uEzOoi#falBl< zFBC_wCP|j4o4(H>++s}g;&m!HrHnNrkQfuhW2I*psMs~_^1~pcy z$3I)lPA!r)oX(f1<6`e~8#6%`FAgwW$c(;lN%4tP)N{yA0bf&FcK-0_HNMR8*1^=O z;K|z6J5#W*kqqL;bVV(344 zI&H-q-sF6{?wtFGAL-A&=jddaaP@pDcw>V-MetZf<16buBJ9Mya38zgO$@vL(xU72 zx&)t8RR?RwY8$@HpyDBKO>NIf4zD=kYXzCSj6%|&@;8E`bbEAJ%J9kmlr%?~Ai6Q-MGTr|yrvb*Va%P^9D?A;pXkyLF{;QY}16_HtcyVlB&$8G{j zxxmC8%U=9kksQ)N`HKDA3Z|0Wui?%$je15}+1bG@n2~Ec(h;dPl0w*EF++O(c2SnZ z_s5;iFtq1FsM-jy9F97Sq0OU|TeGqjh-@m4p5-~@eebBzbUKqs+3cg<0ARh$HsdehUV%YuF7%rHy?QeHuXZMjWEOkbb! zjexnRV&R*igJQ;AU|7VFKxQqE^GpW!H{twpCr*__UDsA$Qd*Qfqi*7YL3E=}ZK;&u zstBc#981qzi`VP+3haIA(ah4^GtptRjoyyAposBfWD2-1t$&)|%AdQRXVJkYR(;{M zeb4)H3$ck@Nfck|XNeO6a}y()#O8>pqzqV)^p#U=!6BDfE2WhqMg#xdPK@%&SJn!H`dKP!~O=hkwGqHS=l(&8|D0^}FYFXi4g1qlp zd@abG7~;H+V8d3-2E=|{G9msDWofh^Hz~H0wjgX|WPOc5PnAQm{<6W96^}iK5hs*Q zCtV-YP(U4B#`9@B3m(3MQS5)_F}ZnywV#}oyRaj^@XyN93EUww)_0jLyXYDwPN%`x zYM-g7(r?~M$oi>hw*WtMTdPgv*J!OI`HdF8|53=~2~r&KUMQ(-X6LQ1BHzzNmd44w z3t%lig(5pvhkpC{i7!8mWe0t}etA?K8}8Hp3EgH>vwFWOfcTnpsFowYL|j#u%y6VIQ*Q+-b;X)McIx*wJE7CN*tSGu=v=LvDRT`*g2Cd4ii_!r%;Wh|D)suzp7 zcct@p^aZNXz+wziQJsE|)8A{q1M5K0znA@K4B%|Ugt*8WzviM71BHg*N~meGE;D>^7kC3K1#elH zo>QOx$uskggmdWzt9g>e}bWw7^shQw^TT_nl>EIhu(V!sOa8^UaZWY~I{ z0{5`Zf_rMJe<{AACp;0UAACuvbMR2jr|dPM>B_*VB%XL)R-0M1cEyyVH7<<$Y8bXK zld)6gD{H>JWV&S&-hmnpyN-fRH;*iN&$Ex?2_HWcOnegHQVxh{jNh|MD=R|{Fr!#| zSl^jhgx${uqmH6tFXv))w9nx74kwP)qxcG5-2WG>VSc`~m}QYowRk`?&Q3rsq!|TM&ZfdiNuK?89acN3(%U28&y|aY z(fi*14H@fq-ff(iGNPlLEr65qq|KoDp+dV4k+c>OVuX*`JxAe!znD^J) ze&IeoKxzA1aUW(=JLC`f3Opfff8fq^@;Js4#PZrRoRjX_byUR}px(s7i)DYN1|Ip~ z{b?(=`|IE;=3%wvemgYzH-xP+eZ0lln)R??WVT}Hw#Mz`V?7%_QVXkVs5XvartfJS zdrZ0`mJ#cc*uLo^?404ga?kkLss`Q!Zjno}3o@A@mZkA~dp;2Y=GVg>eV{URn!3oc zE!7S3%Q32}8yVbl{Swdo9$A_^VEn21w$qx!rSBZ9(X6LrXJ0PL=fw@4o1Q*7RG@T0 z^u`m$XWPt>I2p#?tT}EQcIwA6Xk^}E)p;J@I?2|%98U(mElI?7r@@~dGpAddJv>XS z%L;Qm;!w;punHuq+}zvA3?`~3$cQfD5xY>%0=HZ%FTI3dXmHSMh%Q+Ykm-Bzka@Lsy0x>jCLhKH_<_f)3;GXDjiJzF{Ve39|M@h=u_hO{Gevm33ats zMaHMwQdB}l?xJf*h2;*?&#^0ZVcQN(KvMc7|sDDoYW;>ZW9urW z+{fEL^-Tk8w)xubUcK@n`aQZhZzL&9iK#@}BeW6yFe8&A~fO zL&Iw>=`9%uCwO5OOf4UpmEojnIxg}ez;L>E9tcj%0!Am}llhbM{dg6ReeQXiE=;u9 z)9LCoC#(IN{a}PUJT&QO73uEuD%)t2xAp+W&9Yn0*6Br&R3W!Nb37@HXis{R?khmT zWs=?+*$zG~d*zBOZuuo+a0Bxat*L}Te6Kwt4V%iBGwGL>xcV_u@4?d~l{aapn7#ST zRiF6slB|&gpJpQBLa$@~%36Vj(&0hFQa*V>??c`v_KbwjpA4?=%VPV~?NQmQDjo5$ z$(*1Us?8sj_3etiklSGAcd`m_D|q$V^Bf>ycDrFVM_p}C!xGr0ah)W-rUr%OG*98% z6C}&pYC*bwb;ZqW*9j8ut>hsI>aEg0|1sag&)#=7fp-vpok~K`(Ad zSiQ)Q`_61q43VyxF`SE)B#@fFR_SW6^aRn7H9D2`iOkT@AHmXK2VOKhqm-pcCnn*YjRQVJrI0rJ{6#gFf!gnqxrQ3A;bs{#CX!(!L@YbLnlS( zhvsLsL*chzBknUWS%H||-;ih6x3|u|VSICDf%dz{Ip-VbHhDj8Jd((S9}mvF=QWeJ zTv3I(u#y%THNr?lXq=2({^X;ZVFzsSoazmi@0>F|He$e^^L=2Wjh(N>D2VFzqQy$g zv?x&6YP^l=9m&DqpzotUFy~h=IF|xC>&K8ztvI3k^b##2u58}zb?0>p$L6lxm2Um< z5V}fB(jAH&WHK>ql0GBYrJU09;EoQsRPNTXkjAEMTuHu)xlI{Pk_N`gu{9QsPJDNc zNB;!9#JA+@OK0p%AysF^3M`SI1+6~JQu5lt_luVNwlFotwxwOLYJt7-UBH}|pCxe> z_;npJ4L9W~fxVREOeA8CG;MdR1WDOTJ)`qIRmg*fv{IHeCwH1U*k=?2dQH1yZ7j}| zoE75rqtZ(fR6U zE>6Hga3>c!f~I0#vl6Sa2H6$pUdUT33WRghu$9EEv+p|qnAlTlD<~tQm0PK)vQ)$Som~X{fY42=@=7cVZ=Cy@(t>3C9vIvC85*=g z1$yqLeWbu1lZi(}T(4Xe0R{?zoF%Gq_*^*O2vL3$4LeUrg% z$jSYr6KoUtat(SIA?1mji3^^s=}|G57(HDU|7`ZcMc$NyXz`RQ5z}M85l!?UMY!P; zril^RQqs4g9t*l1gI{bsf(IX!ZGgZ}cN0*R5{Pho}Ce z@-2Y&fx-Rzuav%KVBf+9S+SlVC+t>*OtHeJb>pqL_3T|C+`g&Jx?!f ztgXOa`*llH?}Hg%MgJ|+koAa((z%FN>%y+k!-_`>F^!L0mNX~>UDqdbUs4N$2WiJ^ z?i1*m(IGW5eUIXjt`3M?b(F9E)XBz243}o?si++;BRclUNZOw<`l)mkJ>?^D(#zib1gpT``V z%fBIvz1>jm$Kg`9_g9rRD;Ht@{Fu zU$28>>3bhP>(rK@RW`Q%QCEEL64}yILUy3$*m8Vq+KC3Q%-7|(iZEuSUu!3_AK%a} zdlJ!tL-z9oahmpdMx!DPb%?e-ZfzZYU??{)aX<(IsG1vWICi;pxlP3xQs zzpVF0)H;1M%KY_N|3kpH`!}S-3oA?VAv02B38jfF`@1-NM@gEiZMNf0rlAjgzO`@Y zMyip-tNV!#&$iwoLrgA}=&u(b9QenrT7zJ_s{s_%(Jq(qng(og%hTm!)cjXUe2YkM zTyM^Qz9ZL!&6_cFG#CXasFi{vEt18T(KM?i|(7AE-D+K}1 zE;?j!ce+%-8|ee^`B)Nf=rrujI8R8DWzRk6Ym7#7JWFCxDcc7FB|z#$1lMTe+sYJUhm&HPhmDW zGtPv6Rvk;VqRc?2OgUpU1C6Y1Yw5x%5k(#Rk7F6q7c0f7)@jr>7`q!XG>N9qvFiRM zYEREv)f-`RwYU5%r&z=N!|$y&d9}23jz%#uj2kV;Kpu*pY;6m7FgL3?HuU^~3dIuX zN!Z55NQ)5OYU7>iSCRFSD%EMr9=2Ede>wzhXrK5n*z3IHcYEEqY^8;KV~pb1hgR=P zQeiwk+*V{e!|D^aJg4B}Q}%3cuRT*wjc7)S_M~3EBd+75Mpw^N$ScDy zT%0RMA8PmvF7v(uJ{~Sp<8fT*sjx8~`t^;dzbb5oj~c!n?-;%kAQ&<-#v zPomP_!r!y@c;56WMOOKobYj--bWL0y`XovBA>QQe(dd-LE?aNc3&T#1m0H$0JG_0H zddPEBUR(4r-;>#%5t>p1G({($KkxmHn6+3!UObNd*r>AnA&y_P>}EF<9{jd$DvhnD zmcKvJSBum#g$$_RB}Rl`8-=cd5G3cib4uzmpi_LsM)+ET>ccUDPKwuMlJ$enJ%Yur zeSZFY31nu3?qu#EzwYaAtX~N4;J-b& zKO|g>M?UZ@4Im?Z@As}n;sgMuEgRcxnJp1iOtx}l>|?{jLS*=5ZWA)Ar_Tkfv}jgF zEw_zTe*5WCc9&r4NwEYjW6*I=UiB*cey*pkdeNH#`JSq%2inZV0vOTBmwhh;Hmi5T zYGPLAqU#2JVFE#j0){SJ!q%r87!34sHiZVa%l8QQr=pDYrgRsdI|jGnQXgML30xhn z?mP5-o>b2BgwUc)j++X?Bw@3fr-;4wQmf5LxM|GaQL;v%%9>#hhIMGu^>x~p>cQAJe1Mo zgcx<}~GIkFQLM>U0*`haXH*Pzj#v?DFegNv%Fw0~Kvl zWI-kBt@h5P?A&qW(lZjgrh?q;6WB~3c9CYBXFvpnPdUg;MldYA`0!D^#_(-qL;3az zu>SB?`z;a#8Uc$kkOCtxlvmp8>2*k+-N$D+Eu$zoB#Vq;&&p|&H%F^|=ra?YJ$d_t z3(}9hy8bBYoW&9i*DlunQVM$~i#Yz7XF2h*PS81qpXA>V(}5PyEi8twSUAiGF^o3J z+}WJ@T%mp?Hu@~<$b-8)krnNI330Wt*Fs2fc5VDUMWfvxdvP}`PPO`6)bwbF#8#BnxjAab7 zbf5oSUf%ouzQhaW@q5niobUOZ?^$Fh7?5jm+d@CuWHt0L&>H8Qdxl;0Ykh;~5UfMZ z4vKQs#SE_tDyL;UmH=xvHjD0#0am^A(c6D4GKZK57)enxoWjZ+0*tr^{be{gxi{(& zQ{ag5rAg`*z&tX}W5gNRTE`~foTSX@pm!nVc#mY}z8)*j;Dtdxi8UYhv63ZUV@tWf zLi3#I;6t=c>J!(9wytcGgFWnBObYnL_S6*Y1k@oA+?rBInM$agN+v`WAeS=y<%7|L zqdf|EN{9G`s!PhV8uOUcD^iw`)&}oPQn`SI6arpt*gIMraOsg2b+}>eV8_nsMVH1A zugt&CiT%*Z*^gP=zK&5AZ}U}q`C_S}3?y^_tb((O$ct!)`!KQPT>%kHA?m_{a+$AI zQo#$6YmKv+@47Evkz>-!z0ohn#$&-Qu-Lf^HOX7F)`PCOtMvudH&xBnch2iC!M=%{ zC3z;zgU(K_WC(xoSNAJE`CvgPW%lEN(@4r#5!{q~oN7ZDkM(o$z&Z^Vrb1}iXYu2_ zqs;GCsaApy9U5;fOB`Vh6|;)_c0Fkz)Ng}su@t-#O>~~AA(6{{edEAbVa}X2m{o5r7~dtFMpSDM%9a0vIDFd0+>Z1+W&+)F!GFixLHx4$~-cz z8hYKodgNNIW!!7k=LZd6o@_^{VoWe1jPg8rL_bpw_goZwC?JJ7{h{LG@bo8y>vg$0 z!kQ9RijMjO_>O~O5Z9WhMWMNlFUEm>)lz&qH`mDKjq_5sgaa;wce9Nv9rPhyF@DT%hiaFGEd{43m8SGqN^|E`+3u}1H0TLlJaX?b_k(3 zxnjvpj*zF=2OeE+9h@lyAk@H~7sTWMtdr?5ATxilZ7DTEm=OVRB*KVsL+4-)2o^;vLrL z((jfC)l z!6>#qV4kU#Kt>IMo32g9pk69L`AnL}tFF4d$9cJ?(=@`eCyoEHT+*IJd5$h4zhe^d z?H~a@y=3zmyUj}bAO5@Vz2X^xPk_1=GuT7+=IbW+Tc!@%!74SIG%K@?C)l`TXE)~U zWDHQC)IxZBFG=}p;n?FOpm}60)xU3YeO-67ysCGi>D~0BjJfBrY|rARZJ&9!^3v|W zlEC~I+X3-~et8}1)D+Vplk>DvOuTQt?0hL^-$>(S8o_JwiMO|1~AzHbPDP? z$N8?$SAUq8dP%#gTk3HVZXDl%@wiGuX< z)&t%>3Hn8&P8n|^jDzYYrUk98N*~gn_O0mzC#x)*GjZT^8plXT!dzu}V2Weqk1?e? zKi+x#P8TtLeDc`E^T(dza?YL%`N-dUGF^QyFF0k|=m`0Vu#hk0|MZ(xYEgTr$2wD+ z2xR+yjI9C%pmK^cGbm0Vl=<1JXnfqV06E+$6nBz0&o-J3a(?2J3eYY#sx^LOO= zW7Edu9a8i|-nO;V^}y1m&)q^AV#vpFG|11EYgN;Y1Hi6dSX9D$vdQVB+YtaI<^Y+s$JTv(C^|8aHB~rlCrd$QR>bO%!`y zkm4b~WOTFLRC_(VjrKNFYA?%cl=LHTt#}6jKBj-u$4`(|zm;-HJg*I)dNDkMFzv93 zLfjm9m^gB44BxJNK4CE1C?IQnA_jK_*&K%^)^1o3x1$jJP2=>`!h%QeI)zFq2J$a zSORJHa0x(!K@FHhYBNrS!SU#)PQ!1 zx^CwrV=t}Zr0cTkz>^KtV%Q}u*}#zbalojZd}c>X-e9r)WP?|lYuBs1)o#s_@XL=} z_{)RORr(K?xPEz?yF-^151N%)9~4D1ippEMXSc&|gh}O0^$-;QDs$N@GK^5_`0D{~uGtHYWIRnZVs? zqBD<=PwB{T&Tif$YKw95j%}h#5y9Mm%8CT|!tftk$bq3FSJo&K-*pyf{2ww9jy&Hg;yXzM-ppb8qPE znOYr_6L3yyX1mMgW6B~@P$NZzP;cmW)Z4A!CnYxjTI2r>Tavr z#CPbWo3=!MN$ivs5wU70YlfVml4*K@?-o3(Z=|`s24Y~>qMe(Z8fR^#0jgyg|7I$s z4f~@I$SnC**^6wcPal+tLCKf9%}>4emn_u==$=Q6C?@M*w{a7$}7V9q(T9 z-c<}d{1|X0p5eXky7tztFV7mMS@)Olrz>MzigB-;B@0ew?B9km{DI_a^SX=ld?c8%zqj!qh7r zXCqxAdoekv*PQRX8It*c_U32X=bf!QX>RaSC>H3-Xu$Jt)upG}+br+W{FNkYhoOaKhNZU!5cvIyo z8iH=;&7(b}JJwMf$%aP{oLvWBPYMp0MnX<%w;P~ro}dd(hWgQNFn^DM&(OhcM3dmb zTN?Hu{2zjfxhEdRN0?2L4>BBc`N-^g4vg>5mE}IgVYKMjBaWAu1Ci-IT=!nTnLsv}>Jv}CVk%QZi1=`kYc=5xm34orHG(L^ zoi`4{z(Ha<6STir#}WlQQhyRrH`34J)_}#i8fxbZ=dJcN71p@Fg&kJ)|5!p!EKCY3 zsrsWNwhBfXE7PbKh+MEv*lCTM#p}iG)(t;wvcE!0m&MpbN5iq>A zX}VvxyRm8elRLFX01<@s{`#Y-iG|a*U8OJ z7bPdwmIoI6bq}Rnn;X$#HT>P#>Y1%-=6FB^`Yojc$vp$oyK3VMM#LHpknNfc4t{8snK z>aDS|=~}f#p4Dd&d1X*W<_Lt>SdxdDa%SnxFP}ue>ToeDdh;&cn$g6#6&eYQ$Sg0f zT>Woaz;;fth1p9&)CXl_T`O`N0C@T`Xw_b+3+_^>BR?5UqodSo_}+`$QOd8e?kFWTudUGUz&M_dL3$KX`ij< zza#CzztER107%fz`Vu?aj-l#4CE};0YC=Usc>qgctMxm2lAGD(wM1drc7K;`>k*IF z(@)0ii~egWmfr$RT_#j_{&}O}`t>kk-ZK-B?C|=iu@(!GY%4^VIik`>9Ju6eKCybf zey1SSh>vCOt#qWNu)^kCv*7`Sos^X(F5}0r<81O)%&{*I9e=(+#@N|9i1T&ZmHb_I z&ec*EsPRrj)&3-y7Y=7nb_W<0?icMfCopRAU!*Gs@IdYBdU`pdt&ey*A+X~Pc5od= z0v+luJ9Rdnkoie2!ii#^zm*R;s+Swszt(~$*~BYug97bM$M=fh)0ZbAVsnavKoItXdeqNw7cBNblcZk3LHbz9z24<{p+c(UVjqZnfwC1 z-*bDY*h{KX=F8t73th|S%`hgg8H3g^)`=VZV=*kX}l;W zC;{`vHfYe_yokSdaE9i;ws!flo98W;#JM@~TRXp6tt|b-a^AMMQB!HJo{NAQ(%RcH zLIM+4O$VwQ`8R8km0inpx&3ms1$?KB?*gvl2J>>Dc!tT%>pL!i)0}?S(AhJn!)NGn zg;hry(42E46}FX}7I%M8oe=U|e$B=#>S|-m2q}DZpr|~CutIoT{4{luf;!CcGj12o zw8;TUzPLEQDVYFs9E64=S?3pJsOq)vCEO2-H-RhnB2Z|+ zS98~iEwzC*VCSJk?k{c^kyjnSIMmcTYwBj+#A-l>Oirr1t2gDt?FU;M{;91J@sE#e z1W1hw60t33XVz4-1aju4h)nUgM-pL%_lkZ^=VXnK54Kt*9=8qnirzmI=8#Rst^4r; zIvaBgeMw1rn;h9!r&;zT4!l@jjsjL~Zj)snQn7^ft3+W4EQ+#uwc$rYYJmGY?* z!|Z{M%1MqNLsj;drDRXd%=CGA37Lp@uH{xrhM6AEQN<)Rxf1LLSOW{K{wT3to?ES~ zZt7zf=ah8-86Kq&up0ti3m}e_sr}{nXK`G5V|Or>(~r1*320B(qqAJgrPjSm*ft2# zrn4%Hv#~ytz91v!09LrPMI+E|-8>u;dW+KY$5&NHV4-R%`yJ`hfC(bvd9~zg+C9<%bdF;}nn@;&gEt7u__dozVm!FfxkqmrR zqk2K8_({gYmh_qSluX-=r*JqFE2!ZQUXueZ?mRBUXZUrX-0`-inOPGIr* z&qv4!Euf{T&3j}3tuGUNEhkhpnwn&F9-7Kyhp&W;|am~ z{OI;nXK{c*-l}XOsMc@T(ZLOLc1U&e&xcS?f{J1e`RY73B~xvWclT5g*{f@+Z+CVs zu+}bvkVwRPCfz+^xeE%zSTR0goqI9y;}Ujb8TQ=l_TArq0J)6nT1?1|EqoY-w$P4c zZ@Nr?^1Io&MpaFR$TSKnyexkP+N?Zo%P{dD>6qUc-zaL&fFgms`d(HZ*Lf{|>IIrh zVEWIa>T)!3da_BI(9JK}`zl~&nw9>7;c#}%cf);8)?}p2FF|YSsONQkWqpEk)boC; z!6|X*ri1}e_QaaV zx#o}Eez~g2=+6p_-O zyDKMyf)L#6sr9h7+G{+2ogweQ)oh7cQZQrjk-vjgKDeG?#X~zq&WSr`_`r^uCH*7R z==+n1LaXmg@dm~QEXGr66Eg{-*bl#kp2BtINLM5t*fwcvCS><`8rjD5)LXRr3+?{l znQJL&7~b?MGpX*YQn|FD{LwjHo@X_@Go;$rkl!Fg@Zwf_FH>lA#B5M>7d8K%g~I|k z`e1BqYJa9h;*b2L2j$a#9qwz%eqzDOzMHUIt;^&~XyWE6ob6EgrEN%4tV@)ore!>n zZN%m$tY*Bm>@uPDonoKsJ^K(&88-*zPaK;&UyVKegpbz{ey;dJUFjFvJI1l3q`8nxRo3;zzN4!omNtp=W?bnjuL8JSr36I4PuekC|DNhG0IhrK?$ z`{S<^z0)Urj-8R`ZU*8`wH6>gv-AA~^G`?4kfuV*v?^{R7YkZA7^!q8w|TFGDUqUY z4l-q7iA1%(zLA!4a@{~Oeu|sTh$p=0PRP1f-ISd9JJ%Ii9CxDNe}jI&EAI9JwraDx zBwe*K&HZZO5IFN=SS`8-%@S@%uK9KVAsUs5;Qd!h_iAtJ^KZzjc@CPXoacu!2MQDSU*ZV!1>qt30}W*%Lx;ug*Y zKnH6e%wAHjb=bq`U3_&2XP&?M^Nuop>ffUtd z7G0U%^$vCcF+d6ow{Nn_)PA$Me>3|B@^$^$&`D*qk2^}C&Ei#*#M!EJFU{B@Ub1Kf zwU=B1Tx2KcDvZL?U(WUEQf`H9`k6ip-}hJ>MNYz{7G$TLh_KjdiA>XxC#21^g{7&< zd!=_b>u1j6c8+Y&bQm?e1pbm58BjVC3mE?-J$YL1bzPbuYPJ?QP^3hW{pmGTcPgy^=VDoe6dh8OT$0uE7Ww{4P^@qp&) zDdVW=Gp$Dr7qiLm>x~(-jA7m;6qn)Jif47CzB6YKPzU~Fp9$sH z!G3J}nqf-QHo&?MOE(J?; zqh&8y284QiC)$ig&T?kwZl8Q9Zo>h@j#& zkQxz=GS&11#Sjmu;Y5{KIy7%`HDj(Zq-4_Wfpe`4}K|j!;}+yD9lrdcNJnbCo}3O;PZ6cMYJKTNApK)O!Plg`V2SXi4zEx^=L2~KgCZMu|& zp!eV4ECf0qnB3xf_w3SlJQWRVxNdOyy8eMQE)rJGQjX~W{aEe@xCH&l*55uyCgNgPk<~XBKwE#CyIri79}Tw+H(8^{@4NSJKhGm_N1_Frpd@?f zqrJ?@VGRZ&u%mM;X;Fo(1$Na z5@{tdmFSyapH72W?rI&D`WC-tWJwy>c^%R3#N}FJEqVawlP_jzREsZQ=g|>_w}Imm zAf#@kcy-9~79Lbpfj{KY-N%7Fv(vsRtx^Uo1F0oHabyFweGDL!ybYN-&6IMl2uL?j zrHjMJMPJG-l-3VF!`fY25Yy=M<#2Y=2e&DB-$`b(T;=XLLfScnn;^4D0J5{e!75#U z)@!K+5;j~vZ7Ld_?l{=R9Z*st6G8CUf zk`M+-_Z9v-rgPvd^@8>IYvJHEVYz*mI3xGoC{6*t6G1O=k^LL-`&7L@_Wzm%RA`)HJn=-=tFlk;fMhn67vH*Zo>lvh)R2K zagm%}xpPfYqm-0T{82dW3nrhCbLXSE?XyQuy;EO5wnRPDHGrv{ak-XNpQnPfIO}$+ z@UO&A&~YjrxR$EeqRYzmLhp4Qwb40;NI$;53Xcs?zHM2KsOQHFHyEE;78)A+IOEjS zXVNvM^PwK7(J`uFx&Qa=@W)jjC(damm5+9VV;4t5%B~IVnC!FxNkQPV3x`%cH;!|L zsJ)*R1BdFA3;lhdz&7 zuZjX*A`N%>`SS%N5l9{~sU?rEQk^S)D+*E4qdz63ePjv4T3AK3K zy5m;;$0%2lsN-+pf{a`|0a{DH>ZnoCSS1+3|D}#64bXAC$BWD+qXIEz+Qi#~@k-ua zkn3=$A*rV_IMw^s$oh>b=!L|z&_=Ywpd+{#F$%;V#c3VI;HL5I#H-acKFiD_7VeJm zL@H{*6@>sp4G7z;ZWmTFo}s0OOW;cow%_Twvfr22Z7o_ybAC9KH2&H1e#AWWb}1k1 zrc&ipg7oi--sC0gtrL+k9$J?Jm0D)RvSeodWR?D4J&*^#@lMlJrIgz*xVBG&BQnO@ zFW)gKTfCw$5Fhj-b~GDBoC!GwyGQ4uvKP>=4o?yFpgJ8Y>@^|3;ordZ{2MI{$f~0g z&Bv}P7#UH0a=uezaCxm5czv}odXdjVoe&AnTWu|nS~fZcIXf`_4ZJw(^GTmz{-+&e>7l7gQq^iv%SuYUD{PLQAE1V zJzIMB`50hh)zk=Cc5H{C!QZ(PzYc0$f1xFqc27pB#NwKSm--c3P^Svh>WItXu>A5` zU6Jm~eV78gk|7gV)Oe-9EuPN@B3`G|=IKLsDEdT=wF%dvY# zHZ#co*H0&w&^yu{a6mCxs01(>0uy#*cH|65^*GQ|I2e$jc*q}yUgYqRO1<7aCx+@d zvu&&0xd6U6OW~S(O zNn7!BK)L&y7n>gO!7C~RlY z-ch))D#&9C5m}5(^ZFR>yN0#Q-|jO5;(`-5M#3BZ!iqIC;^gxZQq@YdY>pIEm>ld* z%k;~`w?d}Zd5{Z(zod5mj*YpmfAc6?aPz$Gm#8}8^V^gKWbVEfPFbr~0aY?~7qoO4 zrDzD+i`fUe#>8pyMt8zMuTR!JB(1LB`fL@Y{d^n1_T#0X`LBhdjOJ9G`^|1D{Ptcn``|M+)9twTxxY>zv+7wrAXCbuR4Al2t{ri)+PUO94}W%PQ~R!1%; zHS=1g9C6T-$(PEC;m@gMzWxfg@-S;xuR1pB)Y*=&l)RzZtid`_PjGH3Qy<$18oEuCF1g{mk^hE%b5U+7->%APF%69- z3hdRd4dwv^1!gXN9`S{)LJ~of23pl^q7^4bJvP3a?q`$l9-TQ#Q&SqYyreQVm7Qf{ z9l$edZ}?>)gYQft_bdHVO}h(xxNQ!)z~BLg7KgY8LJdvML3)skn zTB2*j00ZDs_FjzQdDiE|srzKLt;JYOb>Gu@{gYLXrrr&jh4ShnpSr93G;MJ0@Zwf# zFLn1Swm(e7aWpzRBm>OI%yr%;w{zN<`9{k=RK60_c-MhgXB?!Ue|NUv>9z8Kn?ynr?QKTA0KU#~Enuj+b8`mctx=f#8z+raa6F`)Uc&?M3D7Q= zIDTMS_m1oU443~g2}Xq>pVg8AenJFaAg`tC$Gh`?h&;d>#(iSUQ}&9%(n-T}a&r z+e$6Ls5kt+q!5tNGM)nt-Osb9cq(g}&vN{#e@r=kGdtK(PkSl4OYO`J#2InoL-ytDV z3A49ur=^`My}OX^MfBami80)F(G;2CCnMPBUfhQ(LiU~B>fwwfU`hFL_dQ~B|22$+ z^+k1YWD}{*Kf>zf_}XmC17P6zkagoYRtxKeju~3VpO>cJJW)mwzH~C#k}az4{WEl{ zGOA;IMFwHX9H}`_26(Bam$hnhG(^bjQECB}_Jx zGjvh%cKsLqK)I9Qdv2LKN?msSH{%u6x)H%oeSjRf4pff1 zGJZ-u^qWWpLUcstxIr~wwP6IcLb%#cllNU$tB}#4`v@KS!+$Kv&BRjRZ2ByN4;Ur; z7~Ov??=_>;Lvz546E=(ZE}H)^Qz39lzVVS#W&!KE)NRIT%!q76i{daml(elg_PU5p zd*qSC{v^ugA@4|H$2s?P---H%UlglqS5Qg6zUIYX*qQ-B({Inr0oO4gYzJ2&iBuDf ze)Ct+{F8v+e|b-rZu^Ehj_bPRW0tr<6EL`U%X|`agE@!14B0{myQv7lYXvL2ko*Mj z5f5lh&I+2GSIp`6nasJ8&I+}16_5;m}+p#+8=Iqp)kj0 zdB`2#@8=)Q&?J|4j$^IqAc6__CzEejQTWzXt|;{J*7FCdLKO!RVzdmJ27Dpy@k01l z#;Vs5gBA?p3yY{UepXS9;NQT?HXMFXWl}nwq_H1362+e`l6rP?^RkzqF5a#qho3 zJ;S_@@M8GvUI+q_gvS5sN7FTn0x`BVLscO+tA+KJYT7-HZw07!|2#U5prKW&+H;eIM&> z{y|H;n1-DPUFf)oM4FZ|`SJjye;%z(zs`75-RwqaA&;&MzN`bfV#?h@e{Mbu}2 zB*T3iu0~pJH{n&pa;-jeOUv61a+1Bu+^tvwM*3t)C`vdfx{K>Nd)2JrW$44tyL%<+ z>>7|676fVFo&vNmR^!PRDj1SXvmY(pYqTAyH1L%#Wc?!o`C~KSRAKwu1mfzrPQ#Ma z(YkNi=1C)rd`|E-vUTO987vbmgmp*pQhRZ}-2@q*U0u?CR;G0F$f1W8c&X$-P4nU& zKL(2sSQG3jBhlK&TdutOHC9*=XH-Yo?1FXFeGlVpFk z7-OzkU?-Y>(aAm=N#Gc4?W|9c2rywq|g_*}pVMn1;d)wOz$t7dp|7UO=rU9YG>nv_>`L zWN=f96+BTN&#=h|R$K{wHogXG<;2v$g-Mo^{hQZDKyBinp@zD*W<~c>A8Y`Vwmzgi zXVc~vKC_7U&6V6Zs_)jl|N1>md6eS#UYaI#QlEYpMgOY9kQ!a@1H0MM@nJ1$4z5h` zWR<0GhExg1W(=V3H(?dhdCNs|caTYB(1xr;I!)X5mUm0r3UVRrAB!PF0`uEzqGiz@ zuyqvaJ-K_W4wW)4CjvHPs9}6#_-J;>Sy-mVEfM5K0y2pCfL_KZ76oP^pUVnz+y6wW zjsdap87AC~>_vPngXH`4d4=F5YZZMyi@7CB8alb>Ugrcit~!&suQ93J zLH-Tph^r_r{sy=s086#^inXo`<&9Sf8=0i)=mvR+Hx_LP8={x(0HVsEY6~?uW%3C9 zzUA1+Ee$rZy-q!T36j4?E=^did5Af3!8&Ts921t>(O*dX09PZYcUiwsK2$ILUAHGw zhg4^nkwof2u}v2~uT_9Qrl;NRYn*+5;plHmJJ@mPqI-D>{S$dci;=bdFcfr{7mO8S zYUxst2?({ja7Bbi1;&|#R2l9Yss}gQ&u-#|S_&9gE#BF{@OE`rd=*vDO)>P3WAT|J&*iJkxLM>JhKrE~wCwHT2W*0eF>#|>{0kM9bIO!6LG2l3jKLj?%tzKLmj%yNWZOxs}o z#~%KI5%DqxvP7h49$2dyESswGj&2NVe6%VzAF6=^(PTn3Nz3!w5n2}~KWZrDwm#ix zeAb{A1XN(bI^9RFDdl|3%L)Y9i4H)bPf_+pOKkWCp^ZJ(9fir26q1RPe*GZ*n46!= zIEPb;ZPUZVxIiuQM&ML(QY<#=h_ zPMrxrcq(uQTB;x(lO1!EKJw3Di_qKU(xVdD-#LKT8ml!U^;-)J=lD(~6YM>1tsOz- zxB9)b#?}H!lO@$-XwXUj@Pklx$DYz6zEZY5fsa_*nJLTdPMlxewKutWX(-6^5ua$5h}510 zCAn4w5D0w2Ytp3veor)D4+G@+PM2F{Q#}GYz|9g^oeHPx7gd*mnE^D;OD3d>;_tP z)48s+Twc+`42C8q8tdg19+3B_h8kWltw=GyS2LBK_VweVKm%@?nDAH1mEiH(B&$db zXdxvvy*xS^ZJzBQPM|>XU$y}+3YqL`^u{iMyVB#D?X$Fd&5QCa8?7$*)ZtHsV7 z6_KV&6t<)~^VVQ;D?eT8I(W77asNhpQqDq>{XZ5Sq{nuQh}!Vd_X?V9l=KqxhcHl( zzgg4hQUj6B0d01oys?#o@z=7R=>V*6I(N+r5t599qlXj67_xlJsq>UK8}n8JGI5g*Ib7jSXtRwNtTzVyET zz{!YrJpH$~lyA~G0k4gZh}MkgDdq_=vBjx18y?0nN&Hv?erl@U2tT>q#d)sV==J+I zD?e_6^WjQ%?lglodo|`uTCo*~@**o>k)A|?Y+&cV(SykC?dqYw5q@74E>Dg&@W$}9 z9(}iCSYi556RtKjLrkqlov#RjJ6*)7YauPXVf1@~42g2))ekw6av|bOS9E(tTw9M3 zFhcd~zY58B?Oux~qp|5M+=LY5_wf^*acaqvLsl<=ghCfsGEcQ6m2UGqS4Q0YNeb00rl>`2Dgmr>Z_^1b;E|ZBPEWhsEoJw zGeI4L$sFhc{UN|V=5|p+mZ%M@RA+fw{UH+uImzCWrlp)5>g6=kB8d2nhJxQ4PfZ&xP{=SsJMJ8#Cl9ahv)@1t*UYJyc%l#$mp|B`OIUc(m~lPq{xNeRHX&r zlzw}LKjI2`t-z7>=WTqj3@QponiCi*gN}Tg{kpM~zwg=sV+9CwG!Oj=X=y9(D>aJi zS`R0tvPr(G-t}}@BPULecOSN~O#{C`pWLc;&(`mVwpAJY`gBU%Irg*~e)mG!=5*X5 z_;FA;Ty=b5tD#`KUkqp)9rTG5GD8ea&mNZ5a8NTTbwPA5 z+TB2lHW^Xz&qjfF2Uz-U3AEI)?qF)%0YqooLZ^je}BwR~T^Vrbcz6qokP+Aoc)VZd658Gq5gZ*yE)%!9K+3`51q$c35#93-?c} z;-4hh1Vwy|Bk%D3rlfPm(AMncEO1zbXTv)-m9cX3K_cQ~z>1Y$P0i8nF8{J4yWo=aTUmRjx!Qm(EV zE7_Q-w2H3U1_+~QB*(t9Lh)L|S6OH0(_jUKc!h;Q%M^5BnK$VBK)CB4gdl$1hUeq- zqlVeDTLm||{va>OIyT?I$)dITN`m*b?wniD68-#*ZWd9`P=_rafedU~u{Dbp&#{7v zv!`TMflEh8<i{^b0<@oVY*I{pxX0A!!Jm@+rGwTF&2AH;jB}Q#T(SY$Md0Y$A_x>=*qQk#|g_( z*J>VqzxB!EJ2&K}``7X_R*$U9ZuZu1FWEkL{L1p1#Y%c#v;E2LkOTrU#D{A<6lWwIYGJl3`b-8%_y{;vbQ{Nqt~Gr6p{J?GL~w^hZK5oiha zY!F%{mr5eP%9pxso|1@LF5J|l-C6;$(zy#>9O-@e26LE!ak`mI-};l!Pht^Ta#x_p zQSAwkxRzVwlhJXn@tZd`UnUbz?B?7qM2ykCx_(=S86swn3`Vq0bo=C8$C=e;{bOk` zlGybIl&YV>pDU?@A@{-#U5S+g1}SzRGYj`g~lb?-{8A6za{IW_QI5kH9{xFl?YN9r^%E+P6d_}Lj^%?c(d^+l?dn#!))RvT6s z?5Qh7(|#dA8&d{kFd@uPFny8HR7OW9c0mp|^QWs0fzDerv-2b(M`p zr=hDOqbbPElM7FNt5W__lZ}7nt?sLzSo2W8D^wQLj+bdKgn&8jYe3+v!5?W#&HM+Id7L)JS7KvNGudjK{;?p3 zfvM5&$ZbUc48$t%(;plvQ1}4B>VJNu$21HeP^}6hUNYOwPXpDQum*_uy@8c^cnWJ! zGSdH#WiCCJVIoP_?*go;GR-Jp)|r4^&pe<@;-s__-G*nGrJIr|34{`j61?dp0I^6v zw}dA>bl*TyZ$zbQ;@-ez5J?K!?%xcAejID_LM;u9l)b`|AYhJn0|J5R9p*oO*I35_ zo*{=izb2pTPvz}m?Ac=|0=%=8Ixy-7sYfZnEe!H!qsY!7DL?EUy32#7v81dQ3+M#-oRU*ca9K*6ya zd4yX&QasdFWeWu8k%gY>BP*hej8Y$~`S90=-TzgOH&=9S!q#E$r+7!^&XD^eHVh&8 zFU%@=)-UFPkJvG#J+Rug(RS?GI`h~d#I_39VYF+Wq6e(el_iLoxEIbCNBEtos9@XW zJ-kE0=|cG64@mv#uLE?yy?CfA=NTZSI*Z1Dvk|o~(ryQ)w;%XBS9*N2YtoHAfSw*$ zbl(9#tQc*%NY_rDvs9kyibQa1fpC|XAb-NR{|t2t6RbIb+asC-YIejpV{pRY;*0Z& z4~t9w9Q%2(x3TV}j7xoe>Xq8aGs#9*+j8F|8*H#(vZ_GSy@Vxv^tHy(Q(vAGM~L{N zg^N;T6a7^W9}E=n?jkqYX;61C|CRLnLswJoky^n`(f+Ot!cA?eoXlTz1I(>No7fVI zG_xhBJ+oTDa&fYkIgI9y?t;Xot56bg_bXsO+}371?;_mf)^O+osY=G%{U?QVA9w4Q zp^e5lS2PVj0PJWTgoS==T*H~P+cBq@DuM$B4;M4og@YPXk&)m@RyD7-GDLT9I>l>~ zeg074jr5K-02gx+%#v~#`+;5wG zUEQgCsi`vKIC$Dn6#X^RZ_gv>QNF7^ulSHU5~iS@xTB>9^j;zZ#l4zD z2|&KrDdO_IUfCCDV&wSz5BAZS{O~XK> z!uzHU9`@S1<=m(sM1O>D0=H=3z$tkgs4)3fn5%Xjjx)x(YMV@7Ku;eL^x5OV9PVI#Fi7GW7W)Y^}7 z5wF<6+RZqkl*RoMkEHhwmTNI!y4jto0yiJ?E}J&^054ei%8wa`o@Vd4n-gNuGRpQY z%=E{f*C2;u!rwd(>O(_2@wOeSJ?Og%nmP9ykpfTS$uEOdp~L`6VjTg3jl>CeL#TEH zQy7B6m38icU(Q*;{=ihF!E2VCM}mbYOfk+zl!B~w|8>IJwIILD8J_T(e8I0r%>)h#f@txNFM%j zW|^YKx5wfIdmKx<;#d|}=(6UwI1TV<{=)FhpYv|s99dnEO_xnGV#!q&Nq!rCooIA6 zg=g90-o10MD{cErC%{heTVU@*7}ReQUdPz+%|%na9xvupVJzqpN|jd;23z>@MS+de`M?|aPb9^w0;xxk<$9xUWVl*oy(zgyVRkxmHdcxot|Bm z-aF+|47Xu-sNkh840CD)9;r}xx;!j@$+x_Rn#g|{=}Qi_a1Nvl_$f22VJv@1OXO_8 zr*%cQ==KY`{25fcwd|yREuz@0E^X^PbiLb4sSXxXHJf)~ zyo!lGD8LXyk(L&+;+D?(Y4$tGy!4lMp(#+nNhlZ{32-3>cx~SNX!(XLE9j+D;$&D| zFiC-^t@q{A>v;y(XbR3;gs$AZJ@+3*{|5{PX{_0{f2((5$>umt1PtoW%v@W^N* zi}PIF#=Dt~N9K~3OwhEY+TM5TIN_cv|1)!eS|ieE-Jc?Pkfj@&D^crK_DZ^Z)nVIc z4qkWLA+A=ubi)3VTBlklt;Tl&9k-@v}27hgu&r4eIe`)&rujE0O@)TyQ!{`u-!u$GVe~7f|fo zb1yTrS}dOp)v#PFJJg;_njgM|Yzy2DDV;NhoE@=Gp&YN?yR~E`&~^V!rdU(lyVmEj zjh^G4SO7AVXT8MgONFdYTTl?G%O7qB2nhHNDO{=-p%0nuQp5;xyOtnYtgGCf#iCcu$ORj*WmH5eDr&D49h!=WlP?IPA zhI_x2!FCW0M9`HC@+;a|cos-;mSI)-j!ja@?r^v-MN_Iv$D$cGHv757o39|EaYm|* zsKjqmAHlsH{wTy9H|3Ge7>zuhj9Z=+Klrd|8-m<|nh+mcH7{d?_iEtm zX0Hkc#qX?6?s+|#4*=P)H(v71kxFhEt6#4* zglbP1_bo9gu&pfJB+OzvI~F;@x|;YOC-Hy&EUuE|&GJ#i#I|Vr4l-vg7vc8JSxfxD z9aCJFG@5%-A%pt%0Ub;C+B(PR5jkjNmHM;?EjgaMmJ?!${` z*S`%VI|cH55#Sr1KNLSXDLVOVm#m&d^=3edmhY4au-l+~cD>oO_vz<4-(SHmSGP=q z(q?y$e~#(1b;(o4JlcZ=Fr7%&T-Hhba_ePjvae>;YHrDtMkk3sbnxn=mEoEA{Z4o$ z%G~6SEcl>Q9Kf8xfII03s=I#$!l-K$isZV4WuVtI2} zIoESvW%-tQPKhs%{%W#=A~lGGib&}Uj(LpCgu8x#$ggC60YfIXUyG9tMUdI0(p@07 zaRtNtpM}n+BHL18v}P0-ucUh~E+$8ccb$9OvlHyX19sUoBrLzC#6iOSmu8_<*;tYpAh`J!UbB-7)R7z zQ8a!r4;zW%S(CZBwEtYC zCa-hpmt>!|U9mjwdA%#i@>t8y94Z3s`;9^+*rg588g9<&)(zCp4@6UPb-&=?WQkv`4D_#BvTW`F`exb{j4OzCZF1t1+En4YPP|SM zZ4?!2wp@qTrW-dvo!6U74!t#eJSRUbmnBv0teY_X`K&>6q22?i8uTb8138}4IN}`` z$oVS0;iAyHux`3Xz&Q&+^RBu6g%4VLzG`?2nrHPCw}<%90x5EA`U-|+g;JRhgFI8L z!@{O9Ng+&E$sxQrK+=l&Bw_(jxEGTUkzBDb&-EpH#>C~BJc|mum5~4HmRUH7*J=q6 zI+!j$72z)MY2?wiq zyhgrj@x5dWQNtxhnm=b)CX+Lvsyii`>RS2XDp<>wJuno}>P)E$K-d3kD&42lz_I8w<@ zxmW=|v6t8>mOc&rZdSasLEC-xuJ3wnBSM*Ul?EC~zhg=u^NGqw-w zHv@V0peq@}3?aAhim6%dPZwrY*g9U(?b{!&89%{Te3i9Nk|Q{1X!7l|Xga8WS&Q0}z2BceX2*3Stm9*7yaQ9!AL0&H zqG#;Tv<>g2VFi#<2+O4^tS4wFqXHU`+*aqHKj!wWFhea0co=MKRh&sw? zu>eU`+%8lEH&<-b#aUfKJ4_RU5jyy&aDONK{7%!ep}Qrj3O6A8@Aqe`yOSp|_7*MGAaf-kx4OBskG1?Ao zGTs1`Uwyx6WAjk=%_+tWGxS_+$y5EGiP4&~FWmTg+zo4I@LHW_;r+4Kg_r z-D+m)4kTD$%PA&`b-iU_40CHikIFJrIUa6}hm=6#&(6EO4H2kzpT6_khJXUk!GQ2kLWD|UKwDu|Ps zkwYoaFzwbq^|keZg#af@06NUJV8!Pw*As8;l9g_fshR;AsDaB}AeNE4^(!=C^1=Wx z&=xuuIVo(wpsmY%{Ng+-=v0os`hGgLN_XvRS+n3h1u4Vuj)Bbk&HE=$nrjnIr(6P+ zHw%>Gdy6=4qa|&wKEXJ*vKX?*Tx;YJKVB6HB)U+N)zQX?aV=%a>|qpa&>GK*+U@B* z6#CP(Ga3WtQK|BY6RuvT%->7iX=%xVYukt+xVyt$!{M16xRZo&xbN+qKR3ww;+S42 z{!oT6A5-!V7wQ=ll&JXZ2hsEPl(EUaokT=IY>_}0Xz@OwEJOvX$m~kj(=qG#$&!}Y ziPg2^oz`7FycVvVeaiOio)!F+Bzp#bcm;z0xdI%1Ce)CNWP z!eu3dE8_>Zy3zuOP3eu#;{&tAM#xhDKI*sVeM(>fD|1mUY!*wudmo z3rtCXzZypLD!0IN`_a~EsZTQd*@&c2My}I^g1tNyi_4>7+}z75MBg>2HmUN}s(~>C zXoj>k9+O+F`N0;0JL(5D0i{r=cyC)S6b>C>gSP8Q>&0RE#qd&+ioME=Ogvp8dST75%=F z`Z~!9kQG~aOB$YEo0jKuL_~7rtLWHu z!`&7n$zknR5IjC4P%I+M3V)-jW8btwobVMh3jJ}gTe#}N9^E7z+oEJcVjK5qgpDLx zh&&jYe*EmYS8k?v?B&oS+j`4H zMMGNTUtGD#Co}#!$LzGyACF@BT2LnvOYj}y@aMF9dcV({C7R*TwGit|IZ{{stWcvZ z)}1}@*;E;K{iuyK&%w3+nlhO-g*~Q?;ytLts8R??n8}z4;smrNlfY3FVfpV1cejL( zY~Ls)GO@kNrKY$3sFID$AaTPwNR;^6F)FDp(eZR%AwD^xlw z;ccTe-cXd!`1jUM5x{F%&20Op_-Rao@991f4$G9Ri=j?Z&9l6vBc^&d9lOu_L%CYH zZ=3BAy`A;P7u$E8w5*1lL%)1`efe6(Uu6y6cFEGJze*k^SoS8M0%};#&lPGwPTl)Y z)!(9Yh{$pY2_SC+@igFXN3CoM)T;X1==|ysTnbR8=-8NTrE3kruv3S=?x*}IREYSr z%=51B*@VCAF&IujU$PQhup0?cF@=-DKE=Q92wT?~+BM9I+~L`mB4gSpR6C=g*^~k^ zj_gXrOI>rfwxw*psZM;Bdjnri$v;>eQ*Ly>P}Wif(94a?RrV^rGc)i{BK>&_EOC{M zwuL?*z9N(dVukNnnNZy|$ek~rk6>Qth_E3e_mCN`&PKLv&c7RZ_+W@j+b-R z(cO=~G`PML^Rv94zX>H($MNaeM39Q@`$)Y*?+=6b&+?zXfG{gKxMMZNEfBAp0`wO5<)bxXw_DjfR0hN1*k23=F-h@dGSaRa z&PclVEe}=JdItD1tL@2?9CAp%g1VYE+O%(3YLI<2xuYe2{&qBs5JA6nG87_*Q!4C) z-*hA~S0(BG>__N^?9jMiN$H)J{5h=L#9?O+U@i4cSBhpBJf;K2N zHJ0rBs0Uhk&#!D%Ousv3VO5Zi6k|O% zJ|p`BRubDt)C{Fp3WChapsci=_qGF)1*M36;6S@D*Gi0G-nFk^Lvsr(Q zwB=ycBeQ@Kp}5mf1k=?g63sUHHjEkdrF`IlvwxbVzko>HS`=T&1Ap&`4OVZfa_rrE zn66od?7YQ-OZA;V!F=ec<$u7HM!qguwZ>-V_1@0cktFvs49J9;~LDy_0H9FFTMUE7!FGPMC{Edjib zk>lwXJlLoX8Y&`mG%^dTDeD%}@>wWXp6A^~?g_hA)ELSH&qI7ru(78#OCHA|wYF|M zQ66mviuibRPI)nz(DqwmmDRmj5<_A+0V^$gp8Kk*UqAnT0q-O^ZY!Anqa1~+Esq;m zSs>S&5LQckU==>(;It9H~JM2o`em}yON}YF) zQO1Jxq*wyjM-=DO3eE6ec|ou@mDK{TkEwS>&zUcv0KTtHn}YbDDqZmQl&Y{B86$JV zIC-XyyaU;-Q!>hpF2jD@F^@J4$O+tvazB>yIIgx(3NYwWPvtL!CtYbP1CefRxJ(ux z1yK`a@!Bt4dAicy`k&4$u&}4T&baJbO_4lA#6gz7B}vXF1wgxoeM*&9THyiT5HbdOB(f z&K($kdt*6=l|A>f)RhJ_V&`pyMmYxs~D9?zCzBqZv*sWka&n&fV z?)vx`XE4dsK5Lc;RaEmRC)dhpv5IG>7+hwLWB;*V?d!RcC2uRAsBd zMlI;W%<_l;;XPZNx;ddedlLb)6FJnc-1y9naFpqUk7(Qu| z7oC;y+0pw!nRUd?yFZ8(lp#(o0TuJ&`MJ z*MA@Gr`E3Y&>;QRL*3{9;{ri1H8%yZ+V4nWHA)K{Gc4gCd}Z=Kn2LA6hcGQq6bure z>>rwFVIi5pez6@F25`3cp+(F?X$w{)f?*u=YxI+hH_ z%YFHMT|4+2j10*!)HIR{@4G|wew4bTF?ls-DUjMhObw&3dzQ|O_kS{;7UXi_1;WUB zN{Su@)6qyCm#etD)92mqys1hpT4azQNm)YvoNSX%t@FMqmao6mJXULe1Gqh$PS)Ld zvyhh~zQa#Yz5dpx-ZId%Un;gWSr#Iad+^G)(j!Cw$fXvM^H(kJ;^gQ1D6t0uiuG>9 z(#^Z(O5-Ox&}wHRso97+|3GP7ff(SgILgdsJMG+A8F0Nf@5dLjssT3KWHLa-(YCdK zPR4=FSnn$mq-XXlrzKhZDEM?I@)-$i(c)Hi=rq-%#AfhL1@eymglAVCCJb@d6H-{4 zU6}6(MF;$+y7cO_{wnnZ8Ef_A2VNz7Y|&NyCj+LgT8&fe)@4E-{v*ZBV9FE7Oxg+n zvTM(Zz-^|N;RlN~J)bVLh3~(fsl0w;>6!|-5t-L*^K4?EcwFx+rRG@rQ}TP2vMI&{ z1(rf!b!HZ>?3pqhU%h-l-F)wnKQ)cbotvTjezE7%Kf8+sNB>$zUk6A7p)|{du|kr^ zll!&h&wEDZBt`{Xu1ha2KS)#g&s@Qd{FXi37P>hO}I4_fwml57A zV0lyD5GN;ccDoeNzGhYl_n90&wv@uC|IkmoRrXTy=fPhSms9!lY2x*Q$FxAidQ5+A zdHFmeXq;KX&*+Vj-DO^a%2=zw zJt-63#;3u+Z25|4zYKL71{}JU@yws5Rx4wK3{H%w-qD~$vqCU8E}z2&cc{Bk5WV_$G!D&+pey%c| z1t5VkrRhvl>v%Sjn8-!P4K7iFy$q1jFCgr^{D}K=Vi|JwtCU2)wT8Ol8--7fOB7Z^ zY@X$@9;rjQy@5pRzhXm37XIi|5KYL!bHE=s1}zk1fwC(XJN;Sc;z}Mix$b- zJv26Af1pnV4$}Hn^t0E%8-6c@#tw&RXI6+b`Dc zT!1vO!Y|jk`mevy#+yi$TZl}mj1;Tii5W4;D~h)vR0QbjQEYFTwG(}1@2jfoK+nqg z8B(&I$IqS~@MuE+X*7xA)-Ev%cn=)A<`*&wYY$a3Ma;dG(VcN?H>QoJYk>QpH>RA+ z+w;ohVT)dla9v5@dh~jN?~1G&oEp2vb?&g5wfiEUu%Xj{QDFDI_gBfU9@X7^{ZrG= zC)NqJJk$4g`F{_ppGpv_3l}9QR%%*xJhI+S`BGBM z1sKW?pWeWOibHSp#tZKqyDHEQJ2*T}U+F#br%8deVCGOXI9TE`gvQJkY=__~7N09^0ebUiQkYF7|u#uV>k36g2I!60=jRGuZbyKSDTMG5{pB zE&Ky>?O4|$i=`q(d-~!2Q>C+&7-9tM+o;v9cZ*tly5?Cu@d4C@bLFo7>Fr4$?Z~FO z9ACRh1ygDpmtZO-4!Y8T?>wnqaz0F;lMYf3i5`eVJMFX>AS z+KUm}I*XH`4(j=vY`2blqFS!gomsi5 z>5DRLKcP?eYJ`kE(xr9WCxeY)(zOOKqi6Bmx?7{pOw&ef*mUGM^9djGLdYanRy*U> zUxbsDU^G(*8{RG6nr2qmt<2&D?e@M%8;y4?LH$$_mw;NTxgFz?ZaEU{ntMcA<8yZv%(28c2+eP)N)4cR~=spM_-|wgKIr;{i?J-`;Z!NJM z%ZFIpm4;T`J(b5cr;(Sr$))gQ%HD2`j9tz*^06<`_j3%N^;h{#6N9#0iiNQ>0jReq zn2jQ?=<1LZ}&6;ctf`XlK5@Yp3YkoiXrmtDXKQ#VJwm;FH`fd0@u2K{IA-C%6^#WC#hrF7JO#o*e7W0=@`Afh9`y7DL_ zCT5GYs)m$(0G!q9_p!BYTgC)`WA15Dx7Ec^f21g1a#aA^|&A>C(3Ft74q zmkcP1dV9!+L;wQcVf_ZQ&=B8CdG(2hvg?Zk^neG}5s-X8|q*$MPWXJj;R2qlRf`f5KUm>FRm zS0^6d#HYx!(iHKY8_%5#d>%WMDelcbINR2k%DL7?BL$_xx6oF^K%MZZ#La#R zRy=yvdxRW=#sg;z1<`EcBaEc0xMk&peQQmy`NP@3Y<-OO;<-o||o)&pwQF+=~e zm+{}f|Nls|F$zUSOAHL^ZD@q))Me<@T`Qxs8H12PIayWwX78qQ1 z9xcd)`IDf(Vc9_B!1uQNXJp37un{=uPXcGoj4E5yX=-VaxL}RI9H-8AHwQ(}zGdGE z_0zXk1qUdRowN&3ZNZ%BHf@_*cKWbK{D=s3o~R6`$A$u?RhzTdux&sr4&u|a;9u>x z*mq?2c_ll>L`66>>lN_tmNNn6t^WYC{{d(JKe?{8ho}*jR@lRjpADF)5OzRPyh8Q-7d|=);|Vla-dOh0QLxtDBtv60$R@ zvo$7vR$;QYqz>~}M8)z)G!Ryn&7q7m)aqFIKc-rSx#oz|bUxEimRAmSE~`Z=J2pZ^ z?fw1xKbwX2dt3F&<%~{~)UFm1wt<$lw>}mc<@z_-orArfrE>$H7^VHATdPqVJLh<) ztFheDJ)+d22#8Nku?kPwyMFhT`+?LdyT)qVNw<&T!iO#u+7+(yH)-<$vdU0}I(nym z)nY9@qs?zM0IsS*JAj|12P7~aLbXzQLe5_v?PK-mhfjUaDj?K{H6|tLh3( zbX)5Sa#f^YF63RSwNt@5yZD(0*ZQ{0)@SwT)q&8y;Bpr7MDAGcjQ{^zWCCKyE2Ow;K< z;$5l4tg9;eF0e8w^HqpbFi+Mu10zKloW7480wf>uo$J#WQq8`7TbM*Ycy)98fc>(K zHFmV*lO4GeKZUBQrASUJpYs24G1319Bq^mkgAuVy6u!eWGk1n^Im)Iot=o=t!>(n{ zkX3~4j6Eyook-y=?)5DiuWrO0>;~h=dtrA8m9wPQJnihQDZjCfC8x(sGdN*cT#SmDqh*+a^5OSp`A@9OWopsi^ z;a+>R{0N9*^``Gu>_uekRwpKvxuo>&sBTEbCNZWKkO3=gRej5WgVkW{>dx(d_CoYT zFE9&`AKJSZPaLdg1B$;BN66BN`{S`PwcwM!r(!Y!ubFypkQtBG7#GG4mSBr7=1L0tF7^=emceO zIz#e#miDNDgkrEZUMkJK*va1$YBJQEo6azw2S?OGD{iOzIgIzHsj3NW0d=6)-*a-B znj-tjGqH}#5x31$P56pVxQ@#fczT!_(BiKOT;yQcVuz!%^LcR)GN+l^VA}1MV!G}| zE~82hKm3oG3w}Xh@i`(*E(-YBn9dSFL0BE~LnN|v75bMKyvH~ojE&j#5BS?bw2jM9IpBGQJF6_-3KJUw>;+#CI2syOo-PQm^#2$ zsDi9@vf?iWxu81gsLR34utwsokO!;U@g!-&U&V@3xkxKMH=)!zuNs{$$c&+4tCn_a za3c@ps`%&NHxs;Pp`naW{lQ=2B}^f$-x~90d`=v;>4DvN7jgNA3v*PA4bCB^mO}E8 z+XO(xTUY>Z=_xTC4uD=iW_9=)=Z~z~=^8vtKbPWNDczZrthO9hxsg!#89;elNX|si z1F#%Mv?GF&2%>T?QoD$(*lCoQQ(z+7waBCm4LrWx5(U)Q>wD6CO9ae%BPt{=8Qz8# z%x-G+DXP(1AhIjsglX(Q&$63jzi99ug^o)5ABvTy|A{+MOi_zbzgVg|@umL;^cZNJ z7Wqc^d@Z^6<@dl_Hxsq*_g9jl=4u@=!~J66U*D9CZY!&)N>=JBd7~~WV$A*>`l=k5-7He{q3pjG})r9ndpEh&nzaIbabsYH`fO{k>G!wwbHLb$RW-{n-d?czv3oYz zrE#@!&#H*YS5#?sY*<_xe7xyckqG8U#Wm!w;lJRACM|%_ zrnLmiQ6y=4}yPH3qE${cGpw8P*GIGvfW< zWb}JrQ3AJM(Cp|g7hP@3>CjwDBO_C%ZQ}cTp*xt;PqszYoC&3>C0>4-K;Ql}l&#F8 zlP$8?a%Dw+(1%pR4XDM#JF^&%n_VEZ=KV`{-dv0fhi_BGl<$y_;1l-@Pz*$JTv`WH z#l8fKDhlJ1&DGfSX@GllXe5~Ws5^*_{{1ge&(2U?L)h@Sd*Qqzu7(Zjw%m9*rvogt zVL1TO{r&p?ekC}q*2U+gE5%B#HCK|sxEsxfKP-}u{}#0fXjV#i?qRUh^BQ1_mInFo zO_3h5wmz`;E~bRDCY{J_^YbX-{i3i+JgQRyk|J_fN$XF0uMRa`jJ(5(QKqF3vD~Lm z1Dd}B*#PB#MGB+@p%;JDiN2N8F6p@MF6{0#YG(FKxYENS>G=(XV2lwXl{u54PG@(& z_M12tqr#}LV#C>I$4&f*5t2ZFtp$!6EM}=DuSofa!1zKUd+LkFxi^T<-;2nd4hHZb zAZ~lY+6_r_9YLJi*;?Sakl&9GP2bO>FR-l&AeGOn+x;n&f(^~`o5{O#V1v}pB=@CLtIB8ZgkER*lEvM7uAFI^0M-0(S3(ivK2HG5C^mTELZ4SXqZv} zIS_5;`8=ltZAp{&Qh$#PGxj|9~!4c?Igx?m|LO0#;ZSzM&WpNMD>i@T*{)H*L< z5E{F-gp(SDH->tl38(OKfX}_Rvp$H0-27N>V_PsjBPe}ws~7NKPMKi z{T#?U5B?FT&<-zflyraSl8%T<$N;)du(j3I#6- z{8;x+;a%6;q~H(0j`9lpQ!rDs_SKs;geTOt^IQuoo4|6Pk8bU^)~R28@TmgpI9p_Z z*+h!cpnbV-@E3sgAO`QY#ugq|M#I;%NwuL>&`iL*phuH@`FAbS%B9q2E6|lyr@YMk zr=5*f;3I77?9S;S&gai_W`iazIA8dJjYJ`1l*a0%76`4*wcdJQ$H{DDXDN%T*&g1r|TwZq`762kFjcI!PU z^xfYEGfL*oEU&dnJGfk@xXH@i-^zfNE>%WBqfdQv2V^93FNez`)B;K@Ce{N6O29%_ zU*HaC5J3goifSx3Rn0LmDa&yPOo<=0RX0NV9k9-cQrg88Kaqb9QsaYRVDhRyiNpwtC)-`uj76ZU*+&|pQ*ZQKZE z6PF9b$%uzW!qF{G-vdXFaryXD?yW(dH?F!G zk#8Dep2keQp1*DU>SNpS+QdM8^wy_`jj-?Hc$ z+s*Q?x<>=^#&8v?>9Sld^l0yXWm9Ahl|tsuBhDM!su#vQ*`#?Zh4BOW6Mjo!!#dKl zkYp+tb>W5ag5Gi&wp`eyFD*F;*k{kHe{Xcj+|f?{f|jTOp8!4Y<%2z5K%2PxZMOZG z??R)i)K(-kLBn;lcP+GZYG)N6prCxaG&=^^<5jL)wh=**9I4!t`An7ouED~7zYqBn zh14z}y(JI}X|D36Gi*}kQ8!QHf-g`j7HM6G8v!monQYC7EQxjo(B=~ zvbrs2pa0hM8)znEk*qDqmkIf!v|6;j-p}&>vPT-^^o_;BiQl0m>Jt6sh&@`tu40xn z9pv_@DZj(X&Ngb-diaxWwt({DmxUphMPlG;x$w$xq}xfW8B}QYendQsSOMF9wyzno zfM>ZPKOMkLbp5F@)pBK+RIT6(55Ck4@c={#efBdSjai2EXZbsSRTrK_^rIu(`R8suJh7w4VR1CG)eu5ta@k{X|ezT_zn)&9O|1ZEoDlW3J%aDD4) zd%v6R9vM4k5jjP}CeuGLnbQRSveg+`dBQ9G!Ob_nWq&^_?M)L1aw$!;caP0vOj^>j z13e!1%OAR}uml9LwMDJbuP z@*L3xuQ~fb;&2gjT%tZ!tqVicDR8JpZ#9#z#|789u=g^jmR@Ry0Jy4fbB#t9IMtS( z)H&mRgnrcLgk9}^G^yz#qaA!}6b9P#*fM*XZZ`M*JcB9Fyjk9tYl>KdtJ2E(ov}3< zlo?$9VQ9Pmk?Ez}eLpYg!}O)JA4lM~h!yv}TfsDQPx0n+^B~yJY$Ewqgk|ng$sXQ& zm8U%>$DPT^!DLMOmQ%hVXO?R2GW%KSPSXbJNoW{})-q%}F|UrwR$L>==kXIrCfrQ7 z`>2*_Tob~vy{1h=ZhSYUnCWS7qb0;(I00>6Zs7v0adCd4VRN}x9d6sVl-f?**>@(~ zIMq)ZAgpBDzQfN8lU@LB#|IZJgJwU}>(9S_Ws_DwxgG$_FfO2$7|65mAJ_`aG{hw8 zQW}eiU8SmdRXR_bJFDk%A_YhYIz9`@iqDj=u$B81f4=-r;s@=Vf!AUX0mxwz1>Qmj z?Wtu2&wkajD1-q^gglr2(Q_sjaUA37@Ix=0NxrGp(kZ> z301}BHD>Xv6{^$?q6I1j6r_@*oW67Mxtz8 z(r?J#7`eKzmwizasm!I69Jinpv4c*ZV8vIhh_dU*n|AlPUK(36YY#L zohSp0QbG3yO@jyQuOO+5h0PItPXt)=O|8mOuH@nEV704A*i&sM2q!VylbF+ znfDLF-p{$yNC@r$)Csd*-@Xu}eVb^8>pu63+P#SLRG(Y7pI#Kr z|5m;dJbjeJAm89lyJOA9>rPI9Y<)p-;qRt}AK!gtI+1@U@YdStH(W_KQ}L3f9OeKR zYD6GIJn%Usp_!+y4^I2e8riLzA z7ko(x!grJfkeYYphGQk&=@(yeX$l%Gj{85>SWbN#6tPOWWre05%T2bEtnMFe`8E+M z?A~L3&KV{14RC3uuFI(Lhi5I<9Vt=)b9xv0-Lc6+8YT7N(!n_Km1I)ifctHD)cWJb z6CQ-y2_^t}3L&^-`Hjsrg)}MGD(FJN_GF;0T)M(T1n5`;`Mp}vq5V{L0MBRauH@he1(exEFfV|oXxn* zJ~lRvZGbG->vY22^}}bZ6SIP@?p%FS2=&Kvt_a1KI@1Nt#zxgOrafBXa*bco6VYyz zJnzIJX*IFv2hL5Cy%&2gx7AZY8K1wx$X0R4R?P{hwlwL4bCbG59{7;Y;~UnY+KW*!&+q;wsj+66cLm z+9uWkx4uHQwWQ05ghj5T!st#dbAEI;d$E-i9?DR zoEFE1?0k=jw?YkZ=BL8rEs!d2`eFdre!H&ixd$Ph0S*<;%n2V%oV2 zKW%*jgXwcEUivllw9nLKcJ1|q4hA0VO0JfBcTr$9IrS&pB&p1m0BPUxCyBWNCL%YF z!rpmWLiPrLuLwJFqVeAM20iE7bL_DBgT$G7yA$<6|U0$~{E zkBks~D|P(ps@*|%yxGtc6Bpw7xXtVG@?nr|#I=0uZ7t7Da6xOvGJuk@D-Up$%wh{I zkag!=a4neYvvD*?0KLNad$f{=93%ay672%--L)0(9+Y(jEgCg7AA~Y2qFmn&Fnz)J zi0yII!*M}E3#OaUYk!luC_=EQrJ%5KQ2OI6hcp_=BD)Ui!!abX(PEDKvaAQA^y5VtFYF5jiuyfF+wY&c0ifxpQpMSSE?XgQAFwGq0AQJ)w4bRd?H); zR-JA^DK=2w%gn9IgO^ny4;Cv6?r0^)MkPEUcrUZLbm@~V+0+X@bReuj_=K@t#=kL< zK5W6O4qee@skXjl&S!T8&cqIBef`1x^1;`1J7(yqJ7;Y@hbEj3exLatsv8;kelh4c z{Ks#+D{E!^Ae5rT6wleS#CQ^+sjh>XEc{Z%kmX#y9(VdW88MPRI}W#p#5Cpq7-kIL z&rxQ&zA^^H0+eYrG?2(g5MM!u2g#Xjp2nWVeYbEHen*LlXf(dW#51GxS~( zrAt*1P!J-$6X`vnBOo9((jlQkAfbdnihKY5J3F(lcAlA?XJ?;he8Iq*gqi#Pe9LuR zpE6t8Rwz~G6^b5OSYJ(wLGcC5F30!#mpaX)#TZ8o_MCqv@auyf*y2=(|T2*V9s+zIqIu9}4^!FY@J_;0&O75C~>f{~O z7i}fnFo1-E3jXVs6e3Rva-`pskEVfZ*ysr^lw=f$)|M^+CX5Gd0>qj;-OzPFyzzZa zAeow!ffYaD9GrwX4j%+Wn@k*9D?gN%)+w_1KIHBo;CGTZS3f%Wt{s_=x(+!1WUOYP z0I_So&nNq?%5>Kxusco0t`qd);!%$YErx#6f}GOL6CGD~&m=%5&FnSK^8+bN3If`x zl-ymIB+)|sIXqRZSe+eC{F|q$(=FRxqi8nADx&E^QFk+XUe@V5tkhx-HDkLd0wE7# zX9twTx)b69M?!(r6Xa#)O`C_rIMQ8f5uK*VRyKc6-iQI@5kL_=JDq;S4aApU?)SW|!(RTOIm-0;`}X|{vL_uBW3maR6U|%qOH9zLV(*-P zuIxs|EntWvcNxw@@h16C6%d&_AQ$F`dkQJnJAVY9*cZZyGpD;!U86m=9@9fy(-Yd@ zjOLRH)42fi^A;anjoXdQ+AL5eEQ*F>=GS16Y<1!8E6qz(&i+37` zy3^0yF~TLtaRiT|IyhF4IdzFD`+W`$zIOaONg{7PF#R)>rV6xrkdN?63+Y}pn0^rs{qvvJFU??GydDCU(=g=oRnRX?N4Cl+)z=pecPw#6 z@w=LuPtj~-GahLSmCkFetn*86L(BrUd!|r~1Xu-f;lRCUwzdb}syPqoeh=oEM*rHo;(xq+=|nDJCa9OMmXb zTUh_ES!&hrjWDg#jFZJBP>;39(%w7qBMM#^YC)dK3|7GTs%yNImzLaYXM8({f#4vs z&--Avwf`E6EQ-Q^vXd)W113nJ4f^dYGVm*1X-yq zp8`wXz=@Pu2$^MXVjZRi8%YPBt1MsPspYB64C;Al7qf223HgT(%mUcm zshZ2Q=bg>*6&^mm+R!`RX;-TRZPj8m1^W2QR>j%K;9dl`Y+vvtT_DnMOzuwW=Qw}@ zjTZFCBO;rDc_`bPGJ@&D=HS_gR!kj#;g(j-YHwLqRbk*?_Q}B+L~_wJjYRz;(NN>( z*9ywZ_d<8-$F>V7{3o))sgghrRoBDLvG1i{WN`^B<+DbXB&?;Gju=4;1KC8bszx#CDZlVXW-hnpoqv2@ zWlzR50>&{qt20}%@D4h6RP);JR^cs080(C_KMh(~ksWB4OCG`YmWb9*H8;H5Gq1V* zEAX3snE>Yj$LJ#L$0EC^=umg|^_FA_DU+MpeDL}CTYxWP2G3>K$EKw_u@85{7YC^))j1T0ScMHtT`&p0#5J}RFyZe1 z(o95vVuYj}*_2Qi=WY@pv47zOa(ICd0E4&x@iZUv6u4_1eYxByXJBf5g0Z}YN^oY7iy{-vLgBGph<%i#MT%9UjNxu2CCnj^A2^E&JrMzbjs8XezFF4b?4Px zLWf(#)P3ynFV)HjQaWN;N*AOvl!JLr9Nz|%PniiTdF%EB1~2BSrp6d~=v-5U-k|xY z1=4bVGq@z^_snFiN4E+E-bE~LnCGVLGtG)^@?Gchsyb@t%PtygMR$PDgai_Aj^JnH z-l|Nw56sUsckyL!4QuQbSEiFp$okGi9ju(JLidbZ>ec4Ph{Mk{5%CoEeiGLnB==hv zf9w4lT2=qP5zYl17Jr`kWx5qu>H9bW$JZd5|7A>1mtJ23-D^v37{p1Khg#uVZKT}O zPVb!hX|AmxYB+mT#m(x%z^roxg9?)KvriNFpxIoF?&4kQ={ z=5?_EjA)MrEsZ7|A2%c#kqR^yL+VSycduUbv94LfyM@dy~Z`&E~q%Flr=HTg`+ zkMC0JJzx%ue5M<90dRb}`#SaFB#0g`ZwaRV3rx>zOh@glo_`+Xi0UxP@NkoywwZMc zG*8nFH*&!W@;({bJ)R>kE~R$_qZ2ZY=${=+Ittpd8XKL3623@?ax$D%Tx**eB%MhI zZDvb7gKtJAk=wk`-?Dy2W7CiqRfY=c!542}=IeGmO|QKQbh8tc<0%pq%@|e1_rgmY||C`yoZt_#i|64br>dct7QOzQx8A;i{{_>vh1ap;q=w!&s9xh{Ns z*#?o;A}Dy}MxFIa8P%q1XFsH9!Nx~JMCZQ-gs2B%1KFii!hQUnXr7NIDsFKS)uOT6 zWsBS)Hkhn@=<^<)Olr?nnF7t~#2YXMqXl*Xy^5HJwQhTxRRFk26{cY~_x;Z5Xs!Rc zOg!W`)g>G+4@VRFy1qH{@Mlrv&uHMG3^9Bfg8@xjU}&}x*wr7 zA@&XRMX7q(LNTQS`KyE4s+>od7O-rHIsw@WW3IOZx^EfTDQ-n^MKO`jXGPKeM5G5T z1MDKE{}?0MDv6yv5kIsnygF+$SHCG{MacQI|LkzRXbd&iTo-jZV;TG@IpB_A(v4Vd zbNy!zw?qy!NpWPjD*=NYM&@sBt~!rYZ_P-+C-dU*0_`ho1`$O zw;5GZc03XPimCGPJ?yt}H~AX@%hV=pP$-74?KlWZqI$&*DKM6lzqAaZ2> z;vR<#9YW}9LFk$cs^Qra67Q0?j~VbVXN^bBC^$Yy>I`hZcLONc^=R9 zLbYsVF&4txYD&zsytRdODi_eLZ&uAwvshWW%!cZlpmTiRvUxD!D}H%X>2l4rg3Scc z_nk_C$#UjNB^#<`c(!SwrON`>epXOzD=nfi$du6h=i=0$M?qKFG;N22&oWnp_JqhW zN77KPF|k<|De1THelt4t84cs^kS|51>|ZD<972N^dc48vm_vv(u1Pe+l7KX;X--}= zBJ}2JW}Zt-VwB+T4N7t!M(xl(!_?T~1wa{tMv^^PsG{Z!2h;g($G5_Xa|BJhqe?Um z(m4x`vtdMyt|!3eN?%nqs=oZf_Az`T2xJGz2GSNnoC66-*r?1>Egp79FXDpu%q zDeMcPn4@#+8P2LckL02d8*E9y)XdBa6zSiw5$NggwgF59iViGKLB)0ZZ1{O13zj{X ztTgrV{gbHEBO@H_%C8BEy=33FLu6&eu3&RRqSGf8!+SoqKTEioP~5cU!;3qpJI+cq zXQ9Yi;&nL%R^EEel_gBKhl8-ObcRdird*pLO%^V=(HQ2Pc-AWGHR3C}dU0pGDCFt* zD@&z(2qLAF_}C z-{7DApZv~!#7ykIB{)p&Z%Id~3%Rf1zWL8wC(FK&-z{@d1DCSw9)5^`LmQk%zkfH~ zDkA)4GGU)%C>4A+kuUTrZ+J-(GTANIx5 zY-2#A&r$HdtsCRToTpOa-7?!wL9(gqW-Q#H3MR!l_ikqd7uE*31uZ7EhUNoF#`D89 z<$AZGBxA75>z^sNt^h}!>za53oqZDRgnTznKIk6h`1yKOK)r=+zUleLNbgD0GJ*AN zUBXBggcml3x*gpOlTC(-cX@v4Vj9a#0ejt0J+r%xYzuYHb*fk68-x1H%gre3@Y-MN zxomglpCTbXKE7Lf@+~{M3MM0Ey=_j7%S(GVjx#rA@Y5jC5P|t+#0;h=T4q@Q*)opnM7vZCYi8RlDg+IJ7!izXChbr+67mB*MO2=k+gZjl_D?_D#tHJX_={3-7@MDLu5NYfM)7SM4 z;%;MC@;v6yr97k~OyLxY9qu~IkKt63Y_vu%O01t?u2C#E5i_9kzTA>2&fe#NLli|q zj3&6khWvr}dckG1^l`S8IHTLTvUL<#_%Q$E+qd-ndi3*^`yd+3Tg?Y8Vuo1U7UR|LW=&xWgjPnA!d3(8Zi zvjQl9IMzV+|Iu)8oRm5M`@**?f4p&NiN5~%BBKK%||0mnZ9 z7r-*xuh%;ossfkl!(s%edyA|E-V^UfJce~PKd}fAo!INd>I~_2xIc^e3YUgxVPast zr-4;u_5v*pwQ+Ax`QS^WhSpCxo4YWx&j+X5(-muNsNX z)QSSGrzui)4Z~)DXK)dWdy?IXu#j5Z>#ynWd}Ay0Gb7xBdQ7X7sT-rKxKd1A=JGlD zmC_Qt;1aHQ`1HCFPaoh|JjXPr9`-0S)&b~dely&Sh362OICnjN zWeC7i;AFtQgry8j{T6bf)VI6P`U_jqhD;t+$OtMKKexYH|Vp}=~8bC{6pn9 zshIrSlc=-Y!YU^yS5u%(8Z=8U&*KW{YqH5+GVK8|!z8!i=R$N<@$n*_=eqja#&@N1 z|H;SAo9lUa&JnG-p`6)-mUi0=QtiSb=^&XhK6$nTpQY!%)pFsPKP8PINqL;zw|P_;?gD44>{&BC+6+viq*bK zP%Rm!?; zI-Rft_=3EE-%#hk#D=Kee(Ug2J(vZA?KSw#kYS3>#{He`fq!bvk?%mh50uy5O=}K~ zfezE<_l$z-PRi&(AWPTnH75(e*gk0HA@EW&s98U2U6I#ZNEX(yqUq_$?{!*J3IkpX^y3{zcgG+!fhGM}Zn->)K-n z`;_3*_RH|v!$Z;NdE6FwN%7Ql%tnd~UtWx9hWu)Mm_NHEac!SF<+_Hxuk8RL2boI0 zL+?EHs}Nfcla=)66qT7*um7%^rWZ{=$2|4LyEO?g{#l!#W$6Q&ulqiSY1uCW{Tx!| zRc@Rt&(fJsTte-Z;oKWGGF6sCmyGKs#lAE9*1nAe(ruN(cU)c2B6a##$Ro=FwMc*G z(f}8_+{puWAM-xn4*|A7<1Uky0=#bbn*p=EAVMrT%C@Y13Mpe+{zmuO)6ji|7vAxJ z*Cye>jWwH{P1Nm5b&0mf$!vcGXn7+@L6k1LRjzg`Gkzi4l#0RnE;azmDo)W!8e)-lMj|?1wWj2#bmYez1ldQXf>%#3xjzMAir+% zBFNey<`N00K9ZI}exJar{eMnzvYSg4^g;{91u1tXD!O!z_V;l+ixiG zNz|`5^h=1|wwcx|Vm};`hJ-cfc(89s17#jahaCG(D7zFEUSB;)B~jUcNxHlK<%*&> z6-A^*L}>LS-odRW4+?N|Mpi_|(6)$caOV(F^w@OG-Ot4e4B78)MS&`RGYsU@npD(g z(mP#s)!DtBnHh9IhV}4be zZV1fP>;n+HO}`mFV%E?@0!ApHBL&6$?38|Lf!fnu(Dx1cT042jnfecdKrJ zo?s43VyhbmzHL0*`QCNFR2FqZ`e__{>hp9lod&?zcVKJeTTS9?0S8T9*#LOzZ-(Iw znqDr-lF)$1EpKOX^~LxoZ(sU}R;-$pc?zHIKL-PUuC&9-<0n1gwql5IpXhIC{}^p4 zy*2SU*6P&=?FZN_n}kGf!-gs!=-N!fB4*WlAuaGtf*RZzF6QQgu1EB0$+R&7EGnrb zwY<=}BSv0$Nd#Yn!fy8!Rpz#kw@WR1J7}&A)98Fog7%44VKX=yFx}B54)!LTugchR zE;w*M(g`zvd5$`~6V&i^%k@(Cj8cGpUr<^)d+oczEpfL>nwjR`3<#JAX$Qd=F+kW8 zE>d$zTT36&Iq}n}1}pbrU2($YuW?QbgR3+b7}9VuRLRb>Xl5X&|9ZpPnKBM)=VVsW zFOyP$W^2d=oCyt+Wyp9H5pOE1t*G7B?GgG95q!`I8;M@4rXT*mvv<3=pDHLzn&VY_ zx*NOq1HEq&LV^ptMir%^WqcRERW6c^n$y&dNwvW1MtfpLCr@w$X40qhrTWYVALQbj z(=xsNN$>K_W1oC}R^-&n_VfVqnk$UEU|s&J3k9Ddjk#|V&cE1RP$Mix z;w{!qFg}zEM)tLsdqo6p;9adCXV^)tNj*GJOjPT2huBUJyXMI+Hv*p>X<Cti&S?+hxfBBLBgvL)WH7<6K{N zWo>d@xInsnU9Il)3_-t3Dge9;j;#GWkxww|bug58+%ViuSxpFmP=u+hjpPs54cQ@$ z>GUoot6WV-NZOi%qFHn?a~ib;v!NPV#AA2Qu;{T+S4*ijWTia4qH?k1fC_$;zxo_x z?5c{Q)Zjp~dpg&)v#(FQVd!_4Z2?)AmxB)lZ5{&DM%g%QbdRdCeyhH;PAwCO7_4+x z0ztSdto9lC6C4)ZxEmW}hNQDB+tS*E?P9WC1V z(3^~)=d7Jq+T{1twZ%pHk)7+Qv0WPV!8>cUP%t$On6r{z8{|vod*=4>Fq8s*c>D}N z^a!$3f9w$oLTmGx79xP6#nWll^|{{{2@1pDL!Q&HMsOmC4ZiFMczXHV>!ej{bx+05 z7d~!+eeQtd@f>@J+Dj;AT~^nR)PZQ`QAgyZasU(5f_uAD2r>OAup{Cv3Bg-ep*Os4 z3B7IBox+8S(7s)&eJ=hz(-qaA*i#(P?yKhPLa@kq4HXVn&K3V=FfY|^^WOf(fG!Bp zAv9obmH@$9H+ZTo(V4ID&|o{E0sABcAGL^UA9l}&&Mq&`q%0T3$Q(AQ-Dw!l7rrzL ziHiMK?MpnUJ%a|01A2*qHe^NZpUDtr%}F(D-$iR#HRW6M;Z$W)17miIb*OmG<|!=8 zIe(_l)d9+yRcm+g^0f$cfp!n!ArBNgd36cG=jy06s-o!{TD+9{_VM2yN_bHQ_s*75 zs`s@=D1ng17=`}rQfIo*!dQu3x%(4sq~NmqENb5wCgfEAL;u5-w94>$3sYcE|5_33 zzN7ETitgZYh-Z@ueYCt{JMq3l1I{3l07U09dKWwM2*p8PItzXibM~+EGT;k~4-L16 zw?_sR?F>?MEJAKowf?N5xW*;i3`C7yp86`?zQWMu+-tNXz{b1{LAI(|Ek<^u#|Q&W(@~KJKV`TYB({YtTpb%F0$7GLmjr}sUyW3&0%R%E#Ho><5tz_ zMc?|7*NFc3`Q^?HS)fc;%Ko^U$JkB(lcm-6t zy^|NUI>25s{Hi0*=P)DobG&ig#>UgtpIrcv^KKlcA_af(2x7knYjK6%SBHKy7m{$0OdQE6OJuP$>+^J~>Rgd;%aT(m+ zqU&fhEC0^T_nvxh*T=e;{7>-$>wa?xt25)-HKg+sEaa4)G{qD9+NhA=GT@Y$F55ex zn(#_4Q~&*zNC?;VJ9gl2Z2?K98I(l~-Pb_(h@jh4M{3Is21!4n`^kI7h?7mn*Nfye zpiqj!v@bT?%$P!OL3d-{Hw3+YT7+?x%Aiu-tmI|NE?lRM)7Xl!W{ZrlF-Xag{|-i> zk<7WY#;p803{?CIG}ekE?ToKAku3|XH41X;Ca(@AcI0_nqss za5HH6)%wbq$6(wp5Wlmb&o21&vf9n_3T~7)ts+R4W3NEX%mA-`B&RzJ;FttA6W7>nh4t7h>d}aV$ zYLli&N*^q`2v=)`rZNwxK_)du;0SGspGO<(L%MqzTxKd~iwh%aen=eP73fa*-af=76IFngD~L<_ zRk-w+*m+J!zzyMne*c^%atMf$(DpPP3K%yMRW-IW1l%v*{`;F@f`#@svJSVQu=YMZ zKzvwp#N!7tEEz9!@>eB0uCA$>tcbf19V%yc@&I1o?>iXsJYp_HhG_J{zCPXiH$!d) zijDEXQ{(%7AK@~g5AJwB%h-p1Ajt1z38fPcI{Osn93jIOMS!|!X7!c(o9tWr-fw<# zOVSnaMD%`&ZmGhc#lfEe!MZLnd z3@IUoIxQXS+`SvDu8#gVt0sP{aC z8O{ua9z)We&yrJ?{JY;=aAoz^Y?_PjT77>d0v^Z>6u4W9tn>u|p2o4C+s$`#?23g$ zwqM;e%R*1z4r87|##O7la(EX7W&}B3R2KuY8DVVg15+>G;kK<3Pu6bx%}_B?G#z&T z)!#;!lY>~OL$o{4bWZi%9GvG+JONaHw+u&<3gzrd z^Kw#px?LT(k|HmCf2)b_RyMg`t?n~LlzP6IoPZ66!j0;ksNzLWZj0SovK}ZB;W>Td zVMeiQ^C8d;$*&@nEn2_H#GvGkYXFkQuWGQeE8}PK7vhGa%v<)}Y zeW#HlWb(4gzg2vXS;iMa@YHd~hOBX;{if%MqpJ{aEh1?8c=?p7O|Hn@eBNvSErE{l zlkA99dxChS0O>{RPCmM4e8%W9gAxmQopkQ!%VbJV^Z4CY34hllv@u@a0rQugnEpCK z^5Gm}hSZR7zYLwVBX|bnmV)<{k{2|jIePG4j+0pmB!DjfjN>@^VeqkL%8qlhk9TD7 zFA(8x1epW&&U6Ue01jtD5{`9=mko9iTFujfS8};MiU@P;2bF59eWCht5xmDP!N~On zZ2E#bVi{HS_G20mLj|^$Mp|mf>kwyxqlUA+cwk|8(GRl~gm|RTR-`K&XWFUE77utn zYBqa91Fs#FBP9`cpGjOidj2y>zaV6U!b~3AQM-p}l@@u+e|Ra7L5Oal;n5yy{1(VU z$IKi>g=$plWKCrA@7JDSX};9m1gU}dKcqH#OHp5tt3_1y{c#(@UL2h{VAQUOQ|WG% z3*~Fe+Zc0B%J+G0{h}rHP$+OCZLT4y{v0&{5M-pFzWG_vY;RerfX3^?aUV9{87XQdso1d*;@Wo z;49Mw)sTih4Mz0ii6GOB8=htYVtITI?DVHGuJfrCaD|5EJ|^TWvM}>q4+<8q{^u8*MyxP~hIZfXv(8=NlBS zNW~UKAY0)aqtwx3g{MZ6AMI?if849QgiY_=yA%S7{Xq^}vsGPqDmOJ6m@Ji8k=Qji zb^MmnqAEi-svEM%8xrUK+Onj6NY2aC|K3^y2< z&WqhJ(X?GhbE>gyEOLn*PE4!;%HQ5c{j&A)913&Mf;sJ{rv7%00tiQU*9*7q37VyN z_Rr)o3Zc&y&yC4bU}!-Y0zq>)lgyo+CPJT z>n-75`*JhJZujwB0siNg{4w2)xC9=bb>R=OhG~0k^^HKs`)(hI7~I)lBL_rauwL&s zMn1sDc2;^^3gfy=S}|eUSznrWY=>XkIn46oXh4~-ru3V#R+(3y5d@m82|>Ob4Rz@? zBx`Z+w@W31H>;Wt?(Lsg9JBOJsBnLEsXl3FzKie`vOciL1O14d&aKw1NbG+kZIaPs z(WhHGF1Wvgx2;Q}eCxdm`^PxrUcTWI;qL@rvN#fnS5SGaHbM*k*1r~rP{UnJdbQBh zKOFS34I3-slImbMH_wqMdiP2i+f1-{gOJcxXY9Rly`@~h@DRyG?x#E;!vVL_ildgS zM|)3DW>efV)5a0s(f)roUrUw}nck?}5m3ICK1m{*Hx9byA+ALi#75Ut@aBnhqPV{i z+@pPH>^d=BK+s1Q3wz4jx$KoAu*GC%QN;@TiZ)I|QJ)>S??CZ(*S-pswC`ESJSU~BkU~b%gMH9n zz4|gUW{!aYa?QPyMbbywr#-s(Hi>698t&`}=Q}%v6&dQVf7V@g_Upd9faEyG7MhtZ z0Bpn+WK z&q8vrZer(IZ$Y*UZA;4VdK%bb)2Wi`=l^NV;8~A}R}%C(CH2El)Zn*9`5}!AebgRN zLdAb6OB^c{>0ZnFQcx^)W+_#{{)Ja%Q57>&>%mgd&PZ+u=Oofs2l{B+1l^d_ukFV1 zOkKe1AI1^|K8k6Tfz`(vKI_XegpXUYdcl=Rr&Qgd$Q;9R*J1gOezrDXXNoYHX{0Z@ zN5oEf?gZe$S;}Y14LEmI3;HO6*TN?Vl1h!5H{8>R&vo#J=`!A4Q#3?HU;#7JYaiQ zK)$IcaH|Gr`&2Eg+*;^_QimuS@;P%7zZksxI1bf0=F`^{$}5o#o%(4e4Vpzi)_QE6 zaDVS?_ilRwNaw8~_(vViv+Enyn_RuqYT5igk6UdW$V9F+uwwsGsy*z6-x~hZqkgZ? z-V1#rSn0Oo2zxf-foABMRWKeuTkt}j@FL&expmI{Wp@>| z3Sw*kd9Lx;O zf@^u`i0nxoG0&a)K%eUb?oWA%105e?w$2}|ScHB#e%_dPLD1RW?x%2k$_Wd#;#DK@ zxI1h#;aI7+ES0e-%?*4ge7bPfJ2k{axC|AGKZdr^HKV)ds){t?IZYjCL5LDH&D zW(#sUZ-hn=d6ZlK77E2i!gidlhBEZ%K$3M2v};4Vjgub&c?UN*_WSThuPr<19F2H> zDp15N8m#{(;hAr$mI$7O#-@aA_0!Fm>{7qqrIE53P?2%4 z=e=4@O=tb|BFDIa+qI!=0|s$Mp9N&V4I+F3SEsmV6OM1~VK=;0AY$+6YHuxjGe`{OVPvYPHC zgA5(3Cp8_u7tZH?@H*46C7~s_P=z{AWgb_%;OtMdSkNh1TvVz(_WG)y`f#T7D}hP- zcqk~6V?$G_r|$wmIFF<|j|7jbRt*q7-m!jZ6?#+voJUBR?f)=?RCsa7or3%jEN+eO{^l+XEsz0 zq9}%6KXCY5|DMV8jpBL+MIctBXQ(Db&)eLz$70jm-28SB7auDhDziw_v9bWFqgyxS zLy6*i7AnJKFIIgcwPMYGbt?CGr{ z155)IN46t?JHZ#1z`ue#DBcgIfxyu+QNc@VG9+b7+G*6ey?6d&Xn>>0 z&QUohWpz!TPv%UxSLWUvEhv>p5S-&mwoKM$+_X7X_Z%Ja^pWsxf1Xt`G+!qEpyg0g z{V4~_rx>gQ2&ODisndsG2@xU6DH{>*CSA#gYD;|o@qIJbaU%ho{GXm57aJCsc0aB?Th?yrZ5yT2F)FhTg)o;D}qx|>&f zYfHVLVs;c2-5tw2F{dw4X`?Vuhr52&==A1v*TfBShd^wd7}OjB9bm{mT$58nbY(BRmf~sN>6r23vjc&_#K&b zB>sy9hu5Si_e#<-RW6kYwz8F?*j7Y#EJSL~bSq|CvN=SRPXx+N3*bnyaZ@wHeqzTT-9{M4QW;W#{rl&1?oSj)B zV!56P-%5OQW~|)6%8ZKP{oJp^X)rMBXYQT#GJ>&EJ?bjZbEzdILxcyA;^^;t++~Q&+n;daODkbMBOoZ3yZBOzH2zz=a zH#_#B&%hm$xXEnT`NFz#)e6+-!p|%t?rI0Vslp64U-?$n$55TQu}3vlv+Q4{jEQp1 zCZm@6n_m<}Sw+vwKS|h`KT^9$D?~AnTb>ek8?eF3yb10a6OOJ(waKSROq#-5iVSv9 zoAEwKjzn>Gasj@!TNh$te_~tPT?75i;2YQj`}W*KM&piwQFi{7I?^uzC1g}rXMzih z8%zJftcXiFARPgz#w<7cmJSpsB??>Axzfvy)S$HYbVgSYE5?8bipizi%mbQ)9WS-S zZOOO+4L2`n8~)+~*5mg$G1E=K=T-;zvgoodWpQ=dg?^lDjs zxy&G$JvncnSLhsH5}tV0R~#@%b3WO_H0FinuzK-V4s5!h~Q~VJssqU zhMJ!5rSX=_I6dDSp0U+%m%VCK`Ec16TOnN=lhHuL1Ntbat`~ttUYRG`bz}$6E{Lc5 zmkdOyjvi}G9E?2DQxFoU8>9o_yFx@r5~ln3*|mJ9XfI{9G@WFLSXIC9#?z2G3|X0U zsoC1Vo~RjP3svR4%PPzJ-=}eodYWwG#WG{ z;N~Fkn!|yHIRUBCI~u~oV`c!d$WWmhBW)VUXN^TRi7bJBCGPD21zbGjVDV`d_!b~d zuEs1*9)@^dv06qE<7nW={mcE{FRt$_o&eP+1c7+=Kl@7m`TPGT9{qpPT^KlqLbM28 z)PD$f8Nw`?_w8UP z5&`MUh@@2_XN+TQf>=)SB`2u;!R4ObO9D(knF6+lLiN=-Hr75D3d(nfI$p=fCXbq% z^L Date: Mon, 23 Aug 2021 17:24:01 +0300 Subject: [PATCH 2/5] Add R resources for lesson 11: Introduction to classifiers --- .../solution/lesson_11-R.ipynb | 1108 +++++++++++++++++ .../2-Classifiers-1/solution/lesson_11.Rmd | 349 ++++++ 2 files changed, 1457 insertions(+) create mode 100644 4-Classification/2-Classifiers-1/solution/lesson_11-R.ipynb create mode 100644 4-Classification/2-Classifiers-1/solution/lesson_11.Rmd diff --git a/4-Classification/2-Classifiers-1/solution/lesson_11-R.ipynb b/4-Classification/2-Classifiers-1/solution/lesson_11-R.ipynb new file mode 100644 index 000000000..30fb66c7c --- /dev/null +++ b/4-Classification/2-Classifiers-1/solution/lesson_11-R.ipynb @@ -0,0 +1,1108 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "lesson_11-R.ipynb", + "provenance": [], + "collapsed_sections": [], + "toc_visible": true + }, + "kernelspec": { + "name": "ir", + "display_name": "R" + }, + "language_info": { + "name": "R" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "zs2woWv_HoE8" + }, + "source": [ + "# Build a classification model: Delicious Asian and Indian Cuisines" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iDFOb3ebHwQC" + }, + "source": [ + "## Cuisine classifiers 1\n", + "\n", + "In this lesson, we'll explore a variety of classifiers to *predict a given national cuisine based on a group of ingredients.* While doing so, we'll learn more about some of the ways that algorithms can be leveraged for classification tasks.\n", + "\n", + "### [**Pre-lecture quiz**](https://white-water-09ec41f0f.azurestaticapps.net/quiz/21/)\n", + "\n", + "### **Preparation**\n", + "\n", + "This lesson builds up on our [previous lesson](https://github.com/microsoft/ML-For-Beginners/blob/main/4-Classification/1-Introduction/solution/lesson_10-R.ipynb) where we:\n", + "\n", + "- Made a gentle introduction to classifications using a dataset about all the brilliant cuisines of Asia and India 😋.\n", + "\n", + "- Explored some [dplyr verbs](https://dplyr.tidyverse.org/) to prep and clean our data.\n", + "\n", + "- Made beautiful visualizations using ggplot2.\n", + "\n", + "- Demonstrated how to deal with imbalanced data by preprocessing it using [recipes](https://recipes.tidymodels.org/articles/Simple_Example.html).\n", + "\n", + "- Demonstrated how to `prep` and `bake` our recipe to confirm that it will work as supposed to.\n", + "\n", + "#### **Prerequisite**\n", + "\n", + "For this lesson, we'll require the following packages to clean, prep and visualize our data:\n", + "\n", + "- `tidyverse`: The [tidyverse](https://www.tidyverse.org/) is a [collection of R packages](https://www.tidyverse.org/packages) designed to makes data science faster, easier and more fun!\n", + "\n", + "- `tidymodels`: The [tidymodels](https://www.tidymodels.org/) framework is a [collection of packages](https://www.tidymodels.org/packages/) for modeling and machine learning.\n", + "\n", + "\n", + "- `themis`: The [themis package](https://themis.tidymodels.org/) provides Extra Recipes Steps for Dealing with Unbalanced Data.\n", + "\n", + "- `nnet`: The [nnet package](https://cran.r-project.org/web/packages/nnet/nnet.pdf) provides functions for estimating feed-forward neural networks with a single hidden layer, and for multinomial logistic regression models.\n", + "\n", + "You can have them installed as:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4V85BGCjII7F" + }, + "source": [ + "\n", + "`install.packages(c(\"tidyverse\", \"tidymodels\", \"DataExplorer\", \"here\"))`\n", + "\n", + "Alternatively, the script below checks whether you have the packages required to complete this module and installs them for you in case they are missing." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "an5NPyyKIKNR", + "outputId": "834d5e74-f4b8-49f9-8ab5-4c52ff2d7bc8" + }, + "source": [ + "suppressWarnings(if (!require(\"pacman\"))install.packages(\"pacman\"))\n", + "\n", + "pacman::p_load(tidyverse, tidymodels, themis, here)" + ], + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Loading required package: pacman\n", + "\n" + ], + "name": "stderr" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0ax9GQLBINVv" + }, + "source": [ + "Now, let's hit the ground running!\n", + "\n", + "## 1. Split the data into training and test sets.\n", + "\n", + "We'll start by picking a few steps from our previous lesson.\n", + "\n", + "### Drop the most common ingredients that create confusion between distinct cuisines, using `dplyr::select()`.\n", + "\n", + "Everyone loves rice, garlic and ginger!\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 735 + }, + "id": "jhCrrH22IWVR", + "outputId": "d444a85c-1d8b-485f-bc4f-8be2e8f8217c" + }, + "source": [ + "# Load the original cuisines data\n", + "df <- read_csv(file = \"https://raw.githubusercontent.com/microsoft/ML-For-Beginners/main/4-Classification/data/cuisines.csv\")\n", + "\n", + "# Drop id column, rice, garlic and ginger from our original data set\n", + "df_select <- df %>% \n", + " select(-c(1, rice, garlic, ginger)) %>%\n", + " # Encode cuisine column as categorical\n", + " mutate(cuisine = factor(cuisine))\n", + "\n", + "# Display new data set\n", + "df_select %>% \n", + " slice_head(n = 5)\n", + "\n", + "# Display distribution of cuisines\n", + "df_select %>% \n", + " count(cuisine) %>% \n", + " arrange(desc(n))" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "stream", + "text": [ + "New names:\n", + "* `` -> ...1\n", + "\n", + "\u001b[1m\u001b[1mRows: \u001b[1m\u001b[22m\u001b[34m\u001b[34m2448\u001b[34m\u001b[39m \u001b[1m\u001b[1mColumns: \u001b[1m\u001b[22m\u001b[34m\u001b[34m385\u001b[34m\u001b[39m\n", + "\n", + "\u001b[36m──\u001b[39m \u001b[1m\u001b[1mColumn specification\u001b[1m\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n", + "\u001b[1mDelimiter:\u001b[22m \",\"\n", + "\u001b[31mchr\u001b[39m (1): cuisine\n", + "\u001b[32mdbl\u001b[39m (384): ...1, almond, angelica, anise, anise_seed, apple, apple_brandy, a...\n", + "\n", + "\n", + "\u001b[36mℹ\u001b[39m Use \u001b[30m\u001b[47m\u001b[30m\u001b[47m`spec()`\u001b[47m\u001b[30m\u001b[49m\u001b[39m to retrieve the full column specification for this data.\n", + "\u001b[36mℹ\u001b[39m Specify the column types or set \u001b[30m\u001b[47m\u001b[30m\u001b[47m`show_col_types = FALSE`\u001b[47m\u001b[30m\u001b[49m\u001b[39m to quiet this message.\n", + "\n" + ], + "name": "stderr" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + " cuisine almond angelica anise anise_seed apple apple_brandy apricot armagnac\n", + "1 indian 0 0 0 0 0 0 0 0 \n", + "2 indian 1 0 0 0 0 0 0 0 \n", + "3 indian 0 0 0 0 0 0 0 0 \n", + "4 indian 0 0 0 0 0 0 0 0 \n", + "5 indian 0 0 0 0 0 0 0 0 \n", + " artemisia ⋯ whiskey white_bread white_wine whole_grain_wheat_flour wine wood\n", + "1 0 ⋯ 0 0 0 0 0 0 \n", + "2 0 ⋯ 0 0 0 0 0 0 \n", + "3 0 ⋯ 0 0 0 0 0 0 \n", + "4 0 ⋯ 0 0 0 0 0 0 \n", + "5 0 ⋯ 0 0 0 0 0 0 \n", + " yam yeast yogurt zucchini\n", + "1 0 0 0 0 \n", + "2 0 0 0 0 \n", + "3 0 0 0 0 \n", + "4 0 0 0 0 \n", + "5 0 0 1 0 " + ], + "text/latex": "A tibble: 5 × 381\n\\begin{tabular}{lllllllllllllllllllll}\n cuisine & almond & angelica & anise & anise\\_seed & apple & apple\\_brandy & apricot & armagnac & artemisia & ⋯ & whiskey & white\\_bread & white\\_wine & whole\\_grain\\_wheat\\_flour & wine & wood & yam & yeast & yogurt & zucchini\\\\\n & & & & & & & & & & ⋯ & & & & & & & & & & \\\\\n\\hline\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n\\end{tabular}\n", + "text/markdown": "\nA tibble: 5 × 381\n\n| cuisine <fct> | almond <dbl> | angelica <dbl> | anise <dbl> | anise_seed <dbl> | apple <dbl> | apple_brandy <dbl> | apricot <dbl> | armagnac <dbl> | artemisia <dbl> | ⋯ ⋯ | whiskey <dbl> | white_bread <dbl> | white_wine <dbl> | whole_grain_wheat_flour <dbl> | wine <dbl> | wood <dbl> | yam <dbl> | yeast <dbl> | yogurt <dbl> | zucchini <dbl> |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |\n\n", + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 5 × 381
cuisinealmondangelicaaniseanise_seedappleapple_brandyapricotarmagnacartemisia⋯whiskeywhite_breadwhite_winewhole_grain_wheat_flourwinewoodyamyeastyogurtzucchini
<fct><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>⋯<dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>
indian000000000⋯0000000000
indian100000000⋯0000000000
indian000000000⋯0000000000
indian000000000⋯0000000000
indian000000000⋯0000000010
\n" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + " cuisine n \n", + "1 korean 799\n", + "2 indian 598\n", + "3 chinese 442\n", + "4 japanese 320\n", + "5 thai 289" + ], + "text/latex": "A tibble: 5 × 2\n\\begin{tabular}{ll}\n cuisine & n\\\\\n & \\\\\n\\hline\n\t korean & 799\\\\\n\t indian & 598\\\\\n\t chinese & 442\\\\\n\t japanese & 320\\\\\n\t thai & 289\\\\\n\\end{tabular}\n", + "text/markdown": "\nA tibble: 5 × 2\n\n| cuisine <fct> | n <int> |\n|---|---|\n| korean | 799 |\n| indian | 598 |\n| chinese | 442 |\n| japanese | 320 |\n| thai | 289 |\n\n", + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 5 × 2
cuisinen
<fct><int>
korean 799
indian 598
chinese 442
japanese320
thai 289
\n" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "AYTjVyajIdny" + }, + "source": [ + "Perfect! Now, time to split the data such that 70% of the data goes to training and 30% goes to testing. We'll also apply a `stratification` technique when splitting the data to `maintain the proportion of each cuisine` in the training and validation datasets.\n", + "\n", + "[rsample](https://rsample.tidymodels.org/), a package in Tidymodels, provides infrastructure for efficient data splitting and resampling:" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 535 + }, + "id": "w5FWIkEiIjdN", + "outputId": "2e195fd9-1a8f-4b91-9573-cce5582242df" + }, + "source": [ + "# Load the core Tidymodels packages into R session\n", + "library(tidymodels)\n", + "\n", + "# Create split specification\n", + "set.seed(2056)\n", + "cuisines_split <- initial_split(data = df_select,\n", + " strata = cuisine,\n", + " prop = 0.7)\n", + "\n", + "# Extract the data in each split\n", + "cuisines_train <- training(cuisines_split)\n", + "cuisines_test <- testing(cuisines_split)\n", + "\n", + "# Print the number of cases in each split\n", + "cat(\"Training cases: \", nrow(cuisines_train), \"\\n\",\n", + " \"Test cases: \", nrow(cuisines_test), sep = \"\")\n", + "\n", + "# Display the first few rows of the training set\n", + "cuisines_train %>% \n", + " slice_head(n = 5)\n", + "\n", + "\n", + "# Display distribution of cuisines in the training set\n", + "cuisines_train %>% \n", + " count(cuisine) %>% \n", + " arrange(desc(n))" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Training cases: 1712\n", + "Test cases: 736" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + " cuisine almond angelica anise anise_seed apple apple_brandy apricot armagnac\n", + "1 chinese 0 0 0 0 0 0 0 0 \n", + "2 chinese 0 0 0 0 0 0 0 0 \n", + "3 chinese 0 0 0 0 0 0 0 0 \n", + "4 chinese 0 0 0 0 0 0 0 0 \n", + "5 chinese 0 0 0 0 0 0 0 0 \n", + " artemisia ⋯ whiskey white_bread white_wine whole_grain_wheat_flour wine wood\n", + "1 0 ⋯ 0 0 0 0 1 0 \n", + "2 0 ⋯ 0 0 0 0 1 0 \n", + "3 0 ⋯ 0 0 0 0 0 0 \n", + "4 0 ⋯ 0 0 0 0 0 0 \n", + "5 0 ⋯ 0 0 0 0 0 0 \n", + " yam yeast yogurt zucchini\n", + "1 0 0 0 0 \n", + "2 0 0 0 0 \n", + "3 0 0 0 0 \n", + "4 0 0 0 0 \n", + "5 0 0 0 0 " + ], + "text/latex": "A tibble: 5 × 381\n\\begin{tabular}{lllllllllllllllllllll}\n cuisine & almond & angelica & anise & anise\\_seed & apple & apple\\_brandy & apricot & armagnac & artemisia & ⋯ & whiskey & white\\_bread & white\\_wine & whole\\_grain\\_wheat\\_flour & wine & wood & yam & yeast & yogurt & zucchini\\\\\n & & & & & & & & & & ⋯ & & & & & & & & & & \\\\\n\\hline\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\\end{tabular}\n", + "text/markdown": "\nA tibble: 5 × 381\n\n| cuisine <fct> | almond <dbl> | angelica <dbl> | anise <dbl> | anise_seed <dbl> | apple <dbl> | apple_brandy <dbl> | apricot <dbl> | armagnac <dbl> | artemisia <dbl> | ⋯ ⋯ | whiskey <dbl> | white_bread <dbl> | white_wine <dbl> | whole_grain_wheat_flour <dbl> | wine <dbl> | wood <dbl> | yam <dbl> | yeast <dbl> | yogurt <dbl> | zucchini <dbl> |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n\n", + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 5 × 381
cuisinealmondangelicaaniseanise_seedappleapple_brandyapricotarmagnacartemisia⋯whiskeywhite_breadwhite_winewhole_grain_wheat_flourwinewoodyamyeastyogurtzucchini
<fct><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>⋯<dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl>
chinese000000000⋯0000100000
chinese000000000⋯0000100000
chinese000000000⋯0000000000
chinese000000000⋯0000000000
chinese000000000⋯0000000000
\n" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + " cuisine n \n", + "1 korean 559\n", + "2 indian 418\n", + "3 chinese 309\n", + "4 japanese 224\n", + "5 thai 202" + ], + "text/latex": "A tibble: 5 × 2\n\\begin{tabular}{ll}\n cuisine & n\\\\\n & \\\\\n\\hline\n\t korean & 559\\\\\n\t indian & 418\\\\\n\t chinese & 309\\\\\n\t japanese & 224\\\\\n\t thai & 202\\\\\n\\end{tabular}\n", + "text/markdown": "\nA tibble: 5 × 2\n\n| cuisine <fct> | n <int> |\n|---|---|\n| korean | 559 |\n| indian | 418 |\n| chinese | 309 |\n| japanese | 224 |\n| thai | 202 |\n\n", + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 5 × 2
cuisinen
<fct><int>
korean 559
indian 418
chinese 309
japanese224
thai 202
\n" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "daBi9qJNIwqW" + }, + "source": [ + "## 2. Deal with imbalanced data\n", + "\n", + "As you might have noticed in the original data set as well as in our training set, there is quite an unequal distribution in the number of cuisines. Korean cuisines are *almost* 3 times Thai cuisines. Imbalanced data often has negative effects on the model performance. Many models perform best when the number of observations is equal and, thus, tend to struggle with unbalanced data.\n", + "\n", + "There are majorly two ways of dealing with imbalanced data sets:\n", + "\n", + "- adding observations to the minority class: `Over-sampling` e.g using a SMOTE algorithm which synthetically generates new examples of the minority class using nearest neighbors of these cases.\n", + "\n", + "- removing observations from majority class: `Under-sampling`\n", + "\n", + "In our previous lesson, we demonstrated how to deal with imbalanced data sets using a `recipe`. A recipe can be thought of as a blueprint that describes what steps should be applied to a data set in order to get it ready for data analysis. In our case, we want to have an equal distribution in the number of our cuisines for our `training set`. Let's get right into it." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 200 + }, + "id": "Az6LFBGxI1X0", + "outputId": "29d71d85-64b0-4e62-871e-bcd5398573b6" + }, + "source": [ + "# Load themis package for dealing with imbalanced data\n", + "library(themis)\n", + "\n", + "# Create a recipe for preprocessing training data\n", + "cuisines_recipe <- recipe(cuisine ~ ., data = cuisines_train) %>% \n", + " step_smote(cuisine)\n", + "\n", + "# Print recipe\n", + "cuisines_recipe" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Data Recipe\n", + "\n", + "Inputs:\n", + "\n", + " role #variables\n", + " outcome 1\n", + " predictor 380\n", + "\n", + "Operations:\n", + "\n", + "SMOTE based on cuisine" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NBL3PqIWJBBB" + }, + "source": [ + "You can of course go ahead and confirm (using prep+bake) that the recipe will work as you expect it - all the cuisine labels having `559` observations.\n", + "\n", + "Since we'll be using this recipe as a preprocessor for modeling, a `workflow()` will do all the prep and bake for us, so we won't have to manually estimate the recipe.\n", + "\n", + "Now we are ready to train a model 👩‍💻👨‍💻!\n", + "\n", + "## 3. Choosing your classifier\n", + "\n", + "

\n", + " \n", + "

Artwork by @allison_horst
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "a6DLAZ3vJZ14" + }, + "source": [ + "Now we have to decide which algorithm to use for the job 🤔.\n", + "\n", + "In Tidymodels, the [`parsnip package`](https://parsnip.tidymodels.org/index.html) provides consistent interface for working with models across different engines (packages). Please see the parsnip documentation to explore [model types & engines](https://www.tidymodels.org/find/parsnip/#models) and their corresponding [model arguements](https://www.tidymodels.org/find/parsnip/#model-args). The variety is quite bewildering at first sight. For instance, the following methods all include classification techniques:\n", + "\n", + "- C5.0 Rule-Based Classification Models\n", + "\n", + "- Flexible Discriminant Models\n", + "\n", + "- Linear Discriminant Models\n", + "\n", + "- Regularized Discriminant Models\n", + "\n", + "- Logistic Regression Models\n", + "\n", + "- Multinomial Regression Models\n", + "\n", + "- Naive Bayes Models\n", + "\n", + "- Support Vector Machines\n", + "\n", + "- Nearest Neighbors\n", + "\n", + "- Decision Trees\n", + "\n", + "- Ensemble methods\n", + "\n", + "- Neural Networks\n", + "\n", + "The list goes on!\n", + "\n", + "### **What classifier to go with?**\n", + "\n", + "So, which classifier should you choose? Often, running through several and looking for a good result is a way to test.\n", + "\n", + "> AutoML solves this problem neatly by running these comparisons in the cloud, allowing you to choose the best algorithm for your data. Try it [here](https://docs.microsoft.com/learn/modules/automate-model-selection-with-azure-automl/?WT.mc_id=academic-15963-cxa)\n", + "\n", + "Also the choice of classifier depends on our problem. For instance, when the outcome can be categorized into `more than two classes`, like in our case, you must use a `multiclass classification algorithm` as opposed to `binary classification.`\n", + "\n", + "### **A better approach**\n", + "\n", + "A better way than wildly guessing, however, is to follow the ideas on this downloadable [ML Cheat sheet](https://docs.microsoft.com/azure/machine-learning/algorithm-cheat-sheet?WT.mc_id=academic-15963-cxa). Here, we discover that, for our multiclass problem, we have some choices:\n", + "\n", + "

\n", + " \n", + "

A section of Microsoft's Algorithm Cheat Sheet, detailing multiclass classification options
\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gWMsVcbBJemu" + }, + "source": [ + "### **Reasoning**\n", + "\n", + "Let's see if we can reason our way through different approaches given the constraints we have:\n", + "\n", + "- **Deep Neural networks are too heavy**. Given our clean, but minimal dataset, and the fact that we are running training locally via notebooks, deep neural networks are too heavyweight for this task.\n", + "\n", + "- **No two-class classifier**. We do not use a two-class classifier, so that rules out one-vs-all.\n", + "\n", + "- **Decision tree or logistic regression could work**. A decision tree might work, or multinomial regression/multiclass logistic regression for multiclass data.\n", + "\n", + "- **Multiclass Boosted Decision Trees solve a different problem**. The multiclass boosted decision tree is most suitable for nonparametric tasks, e.g. tasks designed to build rankings, so it is not useful for us.\n", + "\n", + "Also, normally before embarking on more complex machine learning models e.g ensemble methods, it's a good idea to build the simplest possible model to get an idea of what is going on. So for this lesson, we'll start with a `multinomial regression` model.\n", + "\n", + "> Logistic regression is a technique used when the outcome variable is categorical (or nominal). For Binary logistic regression the number of outcome variables is two, whereas the number of outcome variables for multinomial logistic regression is more than two. See [Advanced Regression Methods](https://bookdown.org/chua/ber642_advanced_regression/multinomial-logistic-regression.html) for further reading.\n", + "\n", + "## 4. Train and evaluate a Multinomial logistic regression model.\n", + "\n", + "In Tidymodels, `parsnip::multinom_reg()`, defines a model that uses linear predictors to predict multiclass data using the multinomial distribution. See `?multinom_reg()` for the different ways/engines you can use to fit this model.\n", + "\n", + "For this example, we'll fit a Multinomial regression model via the default [nnet](https://cran.r-project.org/web/packages/nnet/nnet.pdf) engine.\n", + "\n", + "> I picked a value for `penalty` sort of randomly. There are better ways to choose this value that is, by using `resampling` and `tuning` the model which we'll discuss later.\n", + ">\n", + "> See [Tidymodels: Get Started](https://www.tidymodels.org/start/tuning/) in case you want to learn more on how to tune model hyperparameters." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 166 + }, + "id": "Wq_fcyQiJvfG", + "outputId": "c30449c7-3864-4be7-f810-72a003743e2d" + }, + "source": [ + "# Create a multinomial regression model specification\n", + "mr_spec <- multinom_reg(penalty = 1) %>% \n", + " set_engine(\"nnet\", MaxNWts = 2086) %>% \n", + " set_mode(\"classification\")\n", + "\n", + "# Print model specification\n", + "mr_spec" + ], + "execution_count": 6, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Multinomial Regression Model Specification (classification)\n", + "\n", + "Main Arguments:\n", + " penalty = 1\n", + "\n", + "Engine-Specific Arguments:\n", + " MaxNWts = 2086\n", + "\n", + "Computational engine: nnet \n" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NlSbzDfgJ0zh" + }, + "source": [ + "Great job 🥳! Now that we have a recipe and a model specification, we need to find a way of bundling them together into an object that will first preprocess the data then fit the model on the preprocessed data and also allow for potential post-processing activities. In Tidymodels, this convenient object is called a [`workflow`](https://workflows.tidymodels.org/) and conveniently holds your modeling components! This is what we'd call *pipelines* in *Python*.\n", + "\n", + "So let's bundle everything up into a workflow!📦" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 333 + }, + "id": "Sc1TfPA4Ke3_", + "outputId": "82c70013-e431-4e7e-cef6-9fcf8aad4a6c" + }, + "source": [ + "# Bundle recipe and model specification\n", + "mr_wf <- workflow() %>% \n", + " add_recipe(cuisines_recipe) %>% \n", + " add_model(mr_spec)\n", + "\n", + "# Print out workflow\n", + "mr_wf" + ], + "execution_count": 7, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "══ Workflow ════════════════════════════════════════════════════════════════════\n", + "\u001b[3mPreprocessor:\u001b[23m Recipe\n", + "\u001b[3mModel:\u001b[23m multinom_reg()\n", + "\n", + "── Preprocessor ────────────────────────────────────────────────────────────────\n", + "1 Recipe Step\n", + "\n", + "• step_smote()\n", + "\n", + "── Model ───────────────────────────────────────────────────────────────────────\n", + "Multinomial Regression Model Specification (classification)\n", + "\n", + "Main Arguments:\n", + " penalty = 1\n", + "\n", + "Engine-Specific Arguments:\n", + " MaxNWts = 2086\n", + "\n", + "Computational engine: nnet \n" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TNQ8i85aKf9L" + }, + "source": [ + "Workflows 👌👌! A **`workflow()`** can be fit in much the same way a model can. So, time to train a model!" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "GMbdfVmTKkJI", + "outputId": "adf9ebdf-d69d-4a64-e9fd-e06e5322292e" + }, + "source": [ + "# Train a multinomial regression model\n", + "mr_fit <- fit(object = mr_wf, data = cuisines_train)\n", + "\n", + "mr_fit" + ], + "execution_count": 8, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "══ Workflow [trained] ══════════════════════════════════════════════════════════\n", + "\u001b[3mPreprocessor:\u001b[23m Recipe\n", + "\u001b[3mModel:\u001b[23m multinom_reg()\n", + "\n", + "── Preprocessor ────────────────────────────────────────────────────────────────\n", + "1 Recipe Step\n", + "\n", + "• step_smote()\n", + "\n", + "── Model ───────────────────────────────────────────────────────────────────────\n", + "Call:\n", + "nnet::multinom(formula = ..y ~ ., data = data, decay = ~1, MaxNWts = ~2086, \n", + " trace = FALSE)\n", + "\n", + "Coefficients:\n", + " (Intercept) almond angelica anise anise_seed apple\n", + "indian 0.19723325 0.2409661 0 -5.004955e-05 -0.1657635 -0.05769734\n", + "japanese 0.13961959 -0.6262400 0 -1.169155e-04 -0.4893596 -0.08585717\n", + "korean 0.22377347 -0.1833485 0 -5.560395e-05 -0.2489401 -0.15657804\n", + "thai -0.04336577 -0.6106258 0 4.903828e-04 -0.5782866 0.63451105\n", + " apple_brandy apricot armagnac artemisia artichoke asparagus\n", + "indian 0 0.37042636 0 -0.09122797 0 -0.27181970\n", + "japanese 0 0.28895643 0 -0.12651100 0 0.14054037\n", + "korean 0 -0.07981259 0 0.55756709 0 -0.66979948\n", + "thai 0 -0.33160904 0 -0.10725182 0 -0.02602152\n", + " avocado bacon baked_potato balm banana barley\n", + "indian -0.46624197 0.16008055 0 0 -0.2838796 0.2230625\n", + "japanese 0.90341344 0.02932727 0 0 -0.4142787 2.0953906\n", + "korean -0.06925382 -0.35804134 0 0 -0.2686963 -0.7233404\n", + "thai -0.21473955 -0.75594439 0 0 0.6784880 -0.4363320\n", + " bartlett_pear basil bay bean beech\n", + "indian 0 -0.7128756 0.1011587 -0.8777275 -0.0004380795\n", + "japanese 0 0.1288697 0.9425626 -0.2380748 0.3373437611\n", + "korean 0 -0.2445193 -0.4744318 -0.8957870 -0.0048784496\n", + "thai 0 1.5365848 0.1333256 0.2196970 -0.0113078024\n", + " beef beef_broth beef_liver beer beet\n", + "indian -0.7985278 0.2430186 -0.035598065 -0.002173738 0.01005813\n", + "japanese 0.2241875 -0.3653020 -0.139551027 0.128905553 0.04923911\n", + "korean 0.5366515 -0.6153237 0.213455197 -0.010828645 0.27325423\n", + "thai 0.1570012 -0.9364154 -0.008032213 -0.035063746 -0.28279823\n", + " bell_pepper bergamot berry bitter_orange black_bean\n", + "indian 0.49074330 0 0.58947607 0.191256164 -0.1945233\n", + "japanese 0.09074167 0 -0.25917977 -0.118915977 -0.3442400\n", + "korean -0.57876763 0 -0.07874180 -0.007729435 -0.5220672\n", + "thai 0.92554006 0 -0.07210196 -0.002983296 -0.4614426\n", + " black_currant black_mustard_seed_oil black_pepper black_raspberry\n", + "indian 0 0.38935801 -0.4453495 0\n", + "japanese 0 -0.05452887 -0.5440869 0\n", + "korean 0 -0.03929970 0.8025454 0\n", + "thai 0 -0.21498372 -0.9854806 0\n", + " black_sesame_seed black_tea blackberry blackberry_brandy\n", + "indian -0.2759246 0.3079977 0.191256164 0\n", + "japanese -0.6101687 -0.1671913 -0.118915977 0\n", + "korean 1.5197674 -0.3036261 -0.007729435 0\n", + "thai -0.1755656 -0.1487033 -0.002983296 0\n", + " blue_cheese blueberry bone_oil bourbon_whiskey brandy\n", + "indian 0 0.216164294 -0.2276744 0 0.22427587\n", + "japanese 0 -0.119186087 0.3913019 0 -0.15595599\n", + "korean 0 -0.007821986 0.2854487 0 -0.02562342\n", + "thai 0 -0.004947048 -0.0253658 0 -0.05715244\n", + "\n", + "...\n", + "and 308 more lines." + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tt2BfOxrKmcJ" + }, + "source": [ + "The output shows the coefficients that the model learned during training.\n", + "\n", + "### Evaluate the Trained Model\n", + "\n", + "It's time to see how the model performed 📏 by evaluating it on a test set! Let's begin by making predictions on the test set." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 248 + }, + "id": "CqtckvtsKqax", + "outputId": "e57fe557-6a68-4217-fe82-173328c5436d" + }, + "source": [ + "# Make predictions on the test set\n", + "results <- cuisines_test %>% select(cuisine) %>% \n", + " bind_cols(mr_fit %>% predict(new_data = cuisines_test))\n", + "\n", + "# Print out results\n", + "results %>% \n", + " slice_head(n = 5)" + ], + "execution_count": 9, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + " cuisine .pred_class\n", + "1 indian thai \n", + "2 indian indian \n", + "3 indian indian \n", + "4 indian indian \n", + "5 indian indian " + ], + "text/latex": "A tibble: 5 × 2\n\\begin{tabular}{ll}\n cuisine & .pred\\_class\\\\\n & \\\\\n\\hline\n\t indian & thai \\\\\n\t indian & indian\\\\\n\t indian & indian\\\\\n\t indian & indian\\\\\n\t indian & indian\\\\\n\\end{tabular}\n", + "text/markdown": "\nA tibble: 5 × 2\n\n| cuisine <fct> | .pred_class <fct> |\n|---|---|\n| indian | thai |\n| indian | indian |\n| indian | indian |\n| indian | indian |\n| indian | indian |\n\n", + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 5 × 2
cuisine.pred_class
<fct><fct>
indianthai
indianindian
indianindian
indianindian
indianindian
\n" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8w5N6XsBKss7" + }, + "source": [ + "Great job! In Tidymodels, evaluating model performance can be done using [yardstick](https://yardstick.tidymodels.org/) - a package used to measure the effectiveness of models using performance metrics. As we did in our logistic regression lesson, let's begin by computing a confusion matrix." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 133 + }, + "id": "YvODvsLkK0iG", + "outputId": "bb69da84-1266-47ad-b174-d43b88ca2988" + }, + "source": [ + "# Confusion matrix for categorical data\n", + "conf_mat(data = results, truth = cuisine, estimate = .pred_class)\n" + ], + "execution_count": 10, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + " Truth\n", + "Prediction chinese indian japanese korean thai\n", + " chinese 83 1 8 15 10\n", + " indian 4 163 1 2 6\n", + " japanese 21 5 73 25 1\n", + " korean 15 0 11 191 0\n", + " thai 10 11 3 7 70" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "c0HfPL16Lr6U" + }, + "source": [ + "When dealing with multiple classes, it's generally more intuitive to visualize this as a heat map, like this:" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 436 + }, + "id": "HsAtwukyLsvt", + "outputId": "3032a224-a2c8-4270-b4f2-7bb620317400" + }, + "source": [ + "update_geom_defaults(geom = \"tile\", new = list(color = \"black\", alpha = 0.7))\n", + "# Visualize confusion matrix\n", + "results %>% \n", + " conf_mat(cuisine, .pred_class) %>% \n", + " autoplot(type = \"heatmap\")" + ], + "execution_count": 11, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME\nBAQFBQUGBgYHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUW\nFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJyco\nKCgpKSkqKiorKyssLCwtLS0uLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU2NjY3Nzc4ODg5OTk6\nOjo7Ozs8PDw9PT0+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpLS0tM\nTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1e\nXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29w\ncHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGC\ngoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OU\nlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSlpaWm\npqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e4\nuLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnK\nysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc\n3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u\n7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7////i\nsF19AAAACXBIWXMAABJ0AAASdAHeZh94AAAgAElEQVR4nO3deWBU9b3//0+ibApWrbYuvYor\nXaxoaatWvVqpqG2HsCmLBAqoVXBDjCKbKMqOQUDFFVxKqyhVFLUqWKJsxg3Lz2IFGilLiEqp\ntMX0hpzvnJkMCbx5/W5vz5k5Z+D5/OOc85nEz3w8Mw9mMjmo84gocC7qBRDtCQGJKISARBRC\nQCIKISARhRCQiEIISEQhBCSiEAISUQgBiSiEgEQUQkAiCiEgEYUQkIhCCEhEIQQkohACElEI\nAYkohIBEFEJAIgohIBGFEJCIQijHkLb+NUZVRb2Ahn26OeoVNCxWpyZWi/mbeGbnGNJl42PU\nmbNiVM+7nohRlz4ao/o/HqOuFc/sHEMasShGdfwsRt3+1qYYNXJ9jLq9MkZNE89sIMUkIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSbI+EVLQktatJvB8FpNGtv9LoqMteTx7d/f2vND6h5M3oIS07xT0Xxjyh\nQJpx+sGNj79pbfCJgkJ6o7V72t/f4FKdFSmkRa3dnNTBgnYHNPneY7GCVPvB1ggg3ezaTZra\nq+C8RYvGF7a64cbW7rLIIU1sdmR8IE1ynX4957qC9pFDGtvsiDSkywsn+D0eJaRxycWkIC1p\ncdzYSecUzIwTpP+0YJBOONJ/CTqncP6iI49YsGjRwqMOjhrSS03GTY0PpJNaVia3P92nImJI\nc5vcWZqG1LVFoInCgPRCkzF3pyF1bLa8snLdd1pGC+nTOy8uvvdLr+iVEZ2KF/hv7WoTC0f0\n7zvf8zaP79Vl8CrPe+2qzsX3Vu8YZgHS8cf624sKF5RdO84/+plbEDGk8oWfxQjSt7/pb7vu\n80ngmYJBWvTa+jpIPz0ickhLFlSmIa1vVuSPR7lXI4V0w9jN6wdM94qu+fCfj3XZ5v+MVDRw\ni/dKl23eoPFfVD/es3pj+/e3b7xudmaYDUjD3C+fmz+6aee64Zsnfz3QdOF82BAjSFPckOV/\nnrFfv+AzBf6woQ7SWa3Wr18dLaRkaUiL3FB/MMdNjhLS6sTG5KbcK3ra8zYmKlKQ5nrepsQn\nqxKbkz8zdStblVjtedu9zDD5zyxpn+wPIUJadFsz5wp7pz5i+P1vH2i372gg7dT9+yfPz/WV\nwScKC1Lrlh0PdAddvyYOkJ5zd/mDN9ywKCG92b42tS9anHwvl/g4BSl9WJZINbv2ng4ls9Z7\nmWHye9/4cbL3QoR0T/MzRt91SWHqI4bJzh0+KdBsex6kZw/4yYzfXL7PzfGB1LKw20P3F7mL\n4gDpSTfVHyxzN0YJaVH77WlIS+ohpQ+XJjJv4zbNG9mhrH64uwJBeuPwE/0Xo66FTya3L44f\n2ragF5AatPGo7/ovRlcULo0NpLff87dd3ZwYQHrOTfIHZW54lJDWJCo876MXdgNpbWJl8usb\nvZotyd30wZlhFiA97VJwJrjMLL9wDwGpvrfddf7uCXdPbCCle8IFmi8kSEvcLf7gqfQLU1SQ\nvEEjKtddd+9uIHlDS6pqXuzy+at9Pq7dPGRKZpgVSD383Wg3+PkbHkyTugVI9ZW7/v7uEXdX\nbCCtXOlv73fjYgBpQ4uf+4MhrixSSFvu6NJz2rbdQdo8ruslJSu82ll9Ova6+++ZYRYgvdH8\nmDeSuw7usRcLT/WPLnGTgVTfxq+02pjc9Xa/jwukdwsv9AfnFbwRA0iVlzZ5p7Jy7bHfDjTX\nHnGt3UB32qgJFxe2XbSo2H332pLzC77zRsSQ5pWW9nADSkvfiQOkTXe6Hz/wxOWFRcFnCgbp\n2QkTurorJ0xYvL6Paztu1OmuX6DpgkGaO2lSN9d/0qRlle8dfPTQO37QaA6QFo06qWmjlleW\nLVr0Zkmrps2O7fFqoNlCgNQ7fS2ZezAWkDY9+P39Gp8wZH3wiYJB6ll3Vu5dv3ZM6xZNT5kY\naLaAkHrVLWZ6ZeWiC1s0Pe2ZQLPtIZDCjau/ZVz9rQKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEiqmEDqOSJGnXJf\njOpw+z0xqtOUGNU76rPRsMvEMzvHkEa+GqMuHBajznv8tRg1IOoFNGzgKzFqiHhm5xjSvZ/G\nqF/MjFHd3on6zWXD7ox6AQ27oypG3Sue2UCKSUCSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyhQTpraYHhzDLL/7zp/3Y\nY9zg1MFDHQ7Z92sXz0ge3fTt5o2O6j0jWkjLTnHPhTFPGJDmt23e/OTSquAThQFpXcl/NW45\nbFPwiUKEVJN4f6fxpkTFrjdlGVLVmS5aSL0bH1wH6QeFF155puswc+b1BUf37HWi6xQppInN\njowNpJcbtbx90jnuluAzhQEpsc9V0y9xJcEnChFS7Qdbd4W0601ZhjSp8bmRQhrWqPiyNKQS\n1y25/f43Z8z82qEPzJz58GEHRAnppSbjpsYG0o8O+ONnn1V9Z7+NgWcKAdJsd1ty+/Mzg78k\nZfGtXRLSv/29oUD6wwEll0YKadyomXWQftT0ofRND/e4zt+d7R6IEFL5ws/iA2nydH/bx/0p\n8EwhQOrSfF3wSVKF+9auNrFwRP++8z1v9aAuVy9Mv7WrGN6964gN3o4vZQ/SRSeujxZSsjpI\nh540c2aDH4tmnPDV/3TCkD5siA+kdOceGnyOECAdfW5VVWXwaapC/xmpaOAW75Uu22r7lW6r\nGpKGdGXptn+MKfEyX8oepIcK5n0aE0gzCs7t8/WC/S9KvQw9dNfw0/e5BkgNe9jdHnyS4JA2\nFfaadEzBQf0/iR+kuf5buk/+mNjoeUvSkLZ+6XmLO9RmvpT8xgVtkr0dNqQ/HdL307hAut8d\neuxVN15Y0Ma/qcS5Q274jyfcIyH9utlFsfjUrsId9b0Hnrqq8Gfxg7TY8zYnPi5rv93zPklD\nWj6kuLhboibzpeQ3lvdM9mHYkLoeviY2kB50zacndz9xtya3U6+/7LSCBJDqG7dPpw0hTBMc\n0l/cQWuSu8vcK7GDtCSlZX77Ws9bk4K0odPsam+pD2lJBtJuCg7pqYKHKyoquh1csS4GkGY2\n+6a/HeT61N3cPkUKSKmudIM+DWOeEH5GanGmv/2NuyvwTNmBtDxR6XllKUhlRTWe92j2IfVz\ndZ0fB0itDvO317orphQP948Gur5AqmtgQWkIs3wWCqQzjve3j7l7As+UHUjVPUq3rrs5BWll\nYsW/Fg5OVGUb0tsv+LU74IU34wCplytJbs8oHD+14Jv+p3ftUmMgJXvahfWJRQiQxrunk9su\n+7wVeKbsQPI+ur7z1e8k/uzfNKN7jylbB3bblGVI6aL9GWlonz5nu4v69Jkw86GWTdr3+6E7\nf+bMn7nju/c+veC4//QaoTAgzSst7eEGlJYGnyq4gcrjDipN9V7gqUKAtK71foPuLnKXB59p\nz7rWLmJIP657d3nVzJn3tv3KPocVJ/XM6H1046bfuGj6fzpnGJB6163rwcAzBYf0UeYt+GOB\npwrjEqGP+3yt0XFj43WtXZC4+lvF1d8yrv62AUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAcl28S9jVKt2\nMer4blGfjob9KOoFNOxnV8Soi8QzO8eQ7loVo7r/JUYNf/KNGDXkTzFq1PoYNU08s3MMafLa\nGNUz6rcJDbvtmWUxanhFjIrV+8z7xDMbSDEJSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIs/yBt6n1EoUsFpFwHJFn+Qbp4\n37a9+6UCUq4Dkiz/IH312WwBAtL/FpBk+QdpvyogRRWQZPkH6ezXgRRVQJLlH6S3f7gYSBEF\nJFn+QTrzv9x+R6cCUq4Dkiz/IJ3dNhOQch2QZPkHKfsBSQUkWT5C+uyFBx56+Qsg5T4gyfIP\n0vZBjfzLGvYfD6ScByRZ/kEa7zo+/OIL91/gHgVSrgOSLP8gfeuG9P6K7wEp1wFJln+QmsxP\n7+c1A1KuA5Is/yDt/3x6/2xzIOU6IMnyD9JZP672d9vanQukXAckWf5Bmldw1JWjbr/8iMJX\ngZTrgCTLP0jeb7/pf/z93XnZcgQkGZBkeQjJ89a/VV6ZNUZA0gFJlpeQshyQVECS5RmkVqO9\nVjsCUq4DkizPIJ1W6p22IyDlOiDJ8gxSTgKSCkiy/IPU5sP0/ulvASnXAUmWf5BceWr3P7c1\nBlKuA5Is3yC5+rhoNecBSZZvkN6/2xWl/uuQl434C5ByHZBk+QbJ8y74U7YAAel/C0iy/IPk\nbZyS3FTdtglIOQ9IsvyDtPIw/1OGCnfYaiDlOiDJ8g9Sh+Pf8ncfHt8JSLkOSLL8g3ToI+n9\n/S2AlOuAJMs/SM2eSO9/tV9MIc07t3nzk8ZW+Ie/P9k9GT2kkvSvC86OGtJrmV9cjF+2bNoP\nvtL4xMFLo4T0/Dn773/SmDUVFdenV3Vm9JCWneKeC2OefwvSjy6o8Xdf/ODMzC01ifdjBOnZ\nfY8eNuYsd2PycHSzI+IA6ZeFd/n9OmpIbw5JdX7Br5ZNKmx1402nuCsihPTbfY8eOvosN6ii\nom/hWL+ZkUOa2OzIHEJ6ueDYASNH9Dm08OXMLbUfbI0RpNNbvLt2bcW391uz9rdNRk2KA6Tu\nBwSfI10Yb+1eP7TDsmXfOLJs2bJFRx8cIaTTWrxdUbHmW/utqri4RaCJQoP0UpNxU3MIyXul\njf9CfHJc/4bs+Lv9bbFbvrbsd2tjAelnRwafI10YkC458NVliwdO9A9/7sqigzRusr/t6d6r\nuPDweEAqX/hZTiF53mcf/H8N/4vF/lu7iuHdu47Y4FUnXh7cr+9SLzOuTSwc0b/vfM/bPL5X\nl8GrPO+1qzoX31u9Y5gFSOnOPiS1iwWks1tVVa0NPk1VKJCeLCzJHC5tfVigqcL4sOHsQyoq\nzjyxomJlDCAlyzGkXfIhXVm67R9jSpKH1/3Ve7XDlszYKxq4xXulyzZv0Pgvqh/vWb2x/fvb\nN143OzNM/sP/XJfsy7Ah3eeGxQfSKcd0PsgdNOgvsYB0/qFvpPZvzH34gn3HRg3pHje0ouLk\nlkUHuoOu/WhvgrTbvyHrQ9qatLC4Q21N4jnP2971lczYK5rreZsSn6xKbE7+LNWtbFVidfLr\nXmaY/IcXtEn2dsiQZjZrVxEfSMcU9pj5UEf30+AzBYf0ZOGg9MFU5w4vDTZXcEiPNDt/TUVF\ny8JL7r8n4S7YmyDt9m/I+pCWDyku7paoqUksS95w1azM2CtanHxbl/i4LJFqdu09HUpmrfcy\nw+T3rrg52c4XSQSGNGqfotVr4wPp/RX+trubG3im4JC6Nn49ffC7icPPL/hFtJBu36f9x8nd\nknJ/cLF7ai+CtNuSkDZ0ml3tLfUh+f9fzCt+nRl7RUtSkJYmquu+edO8kR3K6oe7Kyikfu7a\nT9bGCFK637hRgecIDGnp13/UYNTXzYgSUl93zZ/rR4+6EUB6v6yoxvMe9SE97XnVnV/LjDOQ\n1iZWJr9xo1ezJbmbPjgzzAqkqwvG7jiOBaTVq/3tQ25i4JkCQ3rE3eLvXip5xN/d5YZGCGlA\nwZj0wYoV/vYeN3ovgrR/g3b8DdkkpJWJFf9aODhRVZMYUFE9q+PfMuMMJG9oSVXNi10+f7XP\nx7Wbh0zJDLMB6VduZP0gDpA+KLzI37UtWBI9pKvdr/zd7wq/tyS56+qmRgfp8cwr0LLCdv7u\n3ILX9yJIXZO1anRG5w6nFLS5ugEkb0b3HlO2Duy2IfHiTZ37lXuZ8aYMpM3jul5SssKrndWn\nY6+7/54ZZgHSmmMPHDvOb8naOePGXeJ+OW7cm9FCqurnzp8w+gx3efCZAkP6uft9at/bnXz9\nze0KTloSGaRVxxw4JnVBw6KK3u680SN/6PoEmS4MSPNKS3u4AaWl7+QAUrLZJ23wdyu/Obch\npB2H74g5/g8FgvR+5oKyB9deWnc0LWJIG8efckDTU0uDTxQc0tmF6f3Swa2aNjuu5+uBJgsE\n6d3M4/RAxeo7Tm7RtPW4QI7CgNQ788zJDaSTnkrv72tdd8P2jxI7PnWLHlLYcfW3jKu/Vf8W\npMavpfezm9TdsLDDqFog5SQgyfIP0hGXpna1XQ8PTgZI/7eAJMs/SLe67147atSAb7nBQMp1\nQJLlH6TacYf7P5EdMrwGSLkOSLL8g5Sk9Mmypau3Z4sRkHRAkuUjpG1vzfnU+x8g5T4gyfIQ\n0sQWzi3xhvwia5SApAKSLP8gPeDaT09CenTf8UDKdUCS5R+kk6/0tiUhebecCKRcByRZ/kFq\n+moa0u8aASnXAUmWf5C+9nwa0lMHACnXAUmWf5B+cs4/fUifn9QOSLkOSLL8g/T6Psdf5/r2\nPqDRm0DKdUCS5R8k77VT/Ssbfvj7bDkCkgxIsjyE5Hmb3ntvc9YYAUkHJFn+QToje/+JVSD9\nLwFJln+QvjEJSFEFJFn+QXruW7/9F5CiCUiy/IN09ndd4yOO9gNSrgOSLP8gnXle27qAlOuA\nJMs/SNkPSCogyfIO0rZlb24BUkQBSZZvkCa3cK5R/y/FNwIpuwFJlmeQnnEtbxh2lrtafCOQ\nshuQZHkG6eyW/v8utm+jvwEpioAkyzNIzYf727dc1i5YBdL/X0CS5Rkkd7+/3eBeFt8JpKwG\nJFm+QXrQ3250LwEpioAkAxKQ/v2AJMs3SLcsSTbPlfo7IOU6IMnyDVLDgJTrgCTLM0i3NgxI\nuQ5IsjyDlJOApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZOvQM0Yd/4sYdWq7TjHqB5fGqJ/2iVEXimd2\njiFNWR+jij+PUaOWboxRiWkxanTUj03DYvKKBCQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiRbUEhvtHZP\n+/sbXKqzIodUduEBTdr8KoSJAkNa1No9s+tRFJBGHOWuSx1cf3zjxifcsPNtkUEK7XEKBVJN\n4p1oIY1tdkQa0uWFE/wejxrS2y2OmzD53IIngs8UFNK45Kl5ZpejKCB1a3xQGs2V7shLLj1s\n35sa3hYZpPAepz0C0twmd5amIXVtEWii0CB1bvbh559vOumY4DMFhPR8k9GT03zqj6KANKjR\nJT3TaA498K5p0ya0aNXwtsgghfc47RGQFr22vg7ST4+IBaSqZh393Wj3euCpAkJaPH9jHZ/6\noygg3XrLtDSaMe4sf9y2YHz9bZFBCvFxCg1SzbCRNX8d36tzyYfe9sTv+k32No/v1WXwKs+r\nGN6964gNXm1i4Yj+fednBVKyOkhntVq/fnX0kJa54f5urpsaeKrgHzbU84kQUrI0mjvcef6g\nixtYf1tkkEJ8nEKDVFrypTfo1i1fPtz1b17RwFX/9AaN/6L68Z7V3pWl2/4xpsRL3rjFe6XL\ntuS3f74s2d+yAql1y44HuoOuXxMxpBfc3f5uiRsReKo9DdLU/Y7yB23cZTGAFOLjFBakJ/p/\n4a1OrPW86osXeEVPet6qxGbPq+1W5m390vMWd6j1iuZ63qbEJ8lvX9Am2dtZgdSysNtD9xe5\niyKG9Iy7z9+9424KPNWeBmlawv33yNsuaOH6xgBSiI9TSJDGJv7geW+2r00O+v/GKyrzvLJE\nqtne8iHFxd0SNV7RYs/bnPcB240AABDoSURBVPg4+R2rpyRblxVIb7/nb7u6OdFCmucm+7vF\n7tbAU+1xkO4+r8C5b13qrowBpBAfp5Ag9RsxsKYO0lVPeEVLPG9pojr1tQ2dZlcnBzWpG9OQ\ndlNYkNI94UZGC+ltN8zfzUn/gReoPQ7StGljS+5M/ow0LAaQQnycQoJUvrXPI94a/43bts7z\nU2bWJlYmv7LRKyuq8bxHcwVp5Up/e78bFy2kT1sk/N1wtzjwVHsgJL/v7jclBpBCfJxC+7Bh\nRYd3vZKRX2y7r+c/Uma8oSVVNS92+XxlYsW/Fg5OVOUE0ruFF/qD8wreiBbS58VNln/++YZj\nvxN8pj0O0umHTp42bXDhORZX7iGF+DiF93ukx4u3VN3R89Lbkj/8pCBtHtf1kpIVnjeje48p\nWwd225RFSM9OmNDVXTlhwuL1fVzbcaNOd/0CTRcCpD98teXwMT9sNDf4TAEhzZ04sZu7auLE\npQ2OooB0Q48ep7u2PXqMnHZFwQnFHZp/dWzD2yKDFN7jtEdca9czfYWdu3f92jGtWzQ9ZWKg\n2UK51m7ZRS2anvFcCBMFhFRcd2rua3AUBaSz6u69z7Rpfb7RqPlpd+58W1SQwnuc9ghIIcfV\n3zKu/lYByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSRUTSB2LY9SJfWJUm469Y1TLs2NUIurHpmEXimd2\njiFNq4xRvaP+c79ht77zWYwatSlGXV8eo24Xz2wgxSQgyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSLagkBa1\ndnNSBwvaHdDke49FCym5mGd2PYoW0pz/PrjJSZM+DT5RcEh/cnXNjBbSgsw6JpSXzzq7eeOT\n7oo1pKIlOw1rEu9nBdK4ZkekIS1pcdzYSecUzIwSkr+YZ3Y5ihbSrMKTx0443Q2OA6R1d6Uq\nKng9WkiLh6Y6v2BW+Zz9j7p56GkFE+MKafnHBlLtB1uzAemFJmPuTkPq2Gx5ZeW677SMENLz\nTUZPTvOpP4oYUsuj13322cbjD40DpHSrDy8OPkkIb+0WHtqxvPyCpi+Vly894RtxhXTbiwaS\nLBikJQsq05DWNyvyx6Pcq9FBWjx/Yx2f+qNoIVXe8YS/6+HWxQbSZQd/FHySECB1PXB++bKm\n5/uHg9wT8YQ0pH2n672iV0Z0Kl7geRXDu3cdsSFrb+0q6yAtckP9wRw3OTpIyer5xAJSuk9P\n+0bwSUKC9Gbh2BBmCQ5pduHN5eVPuwH+8XQ3Ip6QvH7+K9I1H/7zsS7bvCtLt/1jTEkdpPXP\nJKvKBqTn3F3+4A03DEg7tWH5y50bzQw+T0iQOhz+lxBmCQ6p3aGLyssfcMP846fc1XGG9LTn\nbUxUeFu/9LzFHWrTkBa0SfZ2NiA96ab6g2XuRiDt1DPOHfWbEOYJB9KbhXeGMU1gSLMLb0xu\np7nb/MGz7vI4Q1rseZsTH3vLhxQXd0vUZP8VaZI/KHPDgbRTH/1qaseCgcHnCQfS5Y1XhzFN\nYEjdGi9Mbh90Q/3BU+6aOENakoK0odPsam9pBtJuCgnSEneLP3gq/cIEpJ0a5F4NPEcokCqP\n+EkY0wSG9NbXz/R3c1x/f3dP+oUp3pDKimo879HsQ9rQ4uf+YIgrA1J9fxz3O3/3azc5HpBe\ncpPCmCYwpBnpl6Jl+5/n7wa4p2IKqf/Df89AWplY8a+FgxNV2YZUeWmTdyor1x777UBz7WmQ\nPio8syq5+6V7Jh6Qhrvgv4z1CwrpGjcrte/Q+Pny8kX/dUKgybIIaW7nPhlI3ozuPaZsHdht\nQ3YgzZ00qZvrP2nSssr3Dj566B0/aDQnQkhzJ07s5q6aOHFpg6NoIX12nfvhqImdCr5fFQ9I\n3d2aMKYJDCnhFqb28w48csCgk/edHldI/5eCQepVd9nU9MrKRRe2aHraM4FmCwipuG4x9zU4\nihjSp5NObrb/t66uCD5TKJAuKAxjluCQ/ruw7uDpc/Zvcup9wSbbIyCFHFd/y7j6WwUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkVUwgzXg8Rg2MegENGzY16hU07NqoF9CwWD1O08QzO8eQiPbMgEQU\nQkAiCiEgEYUQkIhCCEhEIQQkohACElEIAYkohIBEFEJAIgohIBGFEJCIQghIRCGUl5CmTY56\nBQ2ad+emqJdQ34d3Lo16CfV9eeesqJfQoBl3ZnX6vISUaBf1Chp0R5uPo15Cfa+2eTzqJdS3\ntc3VUS+hQb2/n9XpgRQ0IKmAFPeApAKSDEg2IKmAJAMSUfwDElEIAYkohPIDUtGS1K4m8X7E\nCzFL2JSoyPmqYnAaTDWJd6Jegq7u6ZMpK+cvryDVfrA14oWYJSQh5XxVMTgNpthCWv6xgZSV\n85dXkGJYElLUS4hFsYV024u5efrEHNKnd15cfO+XXtErIzoVL/Bfk2sTC0f07zvf8zaP79Vl\n8CrPe+2qzsX3Vu8YZruGS1g9qMvVC9Nv7SqGd+86YoO340vZXkPmDqsTLw/u13epZxaQ69Pj\nQ6oZNrLmr+N7dS750Nue+F2/yTvuNadnZ+eGtO90febpk1nH3vjW7oaxm9cPmO4VXfPhPx/r\nss0/A0UDt3ivdNnmDRr/RfXjPas3tn9/+8brZmeGWV9QgyXU9ivdVjUkDenK0m3/GFPi7Vhd\n1tdQd4c1iev+6r3aYYtZQK5Pjw+ptORLb9CtW758uOvfkutY9c8d95rTs7NL/fxXpPTTp/6k\n7XWQVic2JjflXtHTnrcx/ZQtmuu/n/pkVWJz8s1ut7JVidWet93LDLO+ogZL+KO/uCXpVW39\n0vMWd6jNfCn7a6i7w5rEc8l//a6v7LqAnJ+eJKQn+n+RfMDWel71xQu8oie9+nvN6dnZpRSk\n9NOn/qTtdZDebF+b2hctTr5ZSXycehanD8sSqWbX3tOhZNZ6LzPM+ooaLqH9ds/7JA1p+ZDi\n4m6JmsyXsr+GujusSSxL3nDVrF0XkPPTU5MYm/hD5gHr/xuvKIl2x73m9OzsUgpS3f3uOGl7\nHaRF/nPVS/+0mIGUPlyayLxP2TRvZIey+mGWa7CE+f6TZk0K0oZOs6u9pf5TZUluIGXusCaR\nfI54V/x61wXk/PTUJPqNGFhTB+mqJ1LryNxrbs/OLvV7ccfTp/6k7XWQ1vifiX30wm4grU2s\nTH59o1ezJbmbPjgzzHoNlrA8Uen/qetDKiuq8bxHcwgpc4c1ieS7lurOr+26gJyfnppE+dY+\njyQfsOQbt22d56fWkbnX3J6dXWoAqf6k7XWQvEEjKtddd+9uIHlDS6pqXuzy+at9Pq7dPGRK\nZpj1BTVYQnWP0q3rbk5BWplY8a+FgxNVOYOUucOaxICK6lkd/2YWkOvT43/YsKLDu17JyC+2\n3dfzH+lPnOvuNbdnZ5f6P/z3zP3Wn7S9D9KWO7r0nLZtd5A2j+t6SckKr3ZWn4697v57Zpj1\nGi7ho+s7X/1O4s/+TTO695iydWC3TbmClLnDDYkXb+rcr9wzC8j16Un9Hunx4i1Vd/S89LZ1\ndb+6ydxrTs/OLs3t3GfHA7bjpO19kGg3NfgTNba/B93rAlLetf0j/zPtdECKS0DKuxZ2GFWb\nOQZSXAISUQgBiSiEgEQUQkAiCiEgEYUQkPK3X7pMp+32622Pzu169uqAlL+9PnXq1Gtd5+TW\nXNb9nv+4AimHASm/e92V7u7mKUDKcUDK7+ognXn28984w2vd2j8u+qp3QfLtXhuv7XFrLmze\n/JLsX8lLQMr36iCdd/I373mhHtKfilz5h17blq1HP3tjwS+iXeFeEpDyuzpIbd2c5HYHJK+f\n23Hjj74W4fL2noCU32UgNf6XZyE19a/J61UY4fL2noCU32UgHeFvd4V0tD/sx0OcizjL+V0G\n0tH+FkjRxVnO73aCdOpJ/vY0IEUQZzm/2wnSeYckfyja1CwJ6TL3P0DKaZzl/G4nSJPdmMp3\nf/ydJKQR7rangZTLOMv53U6Qqm84sknr5we08Ly/nNqoFZByGWeZKISARBRCQCIKISARhRCQ\niEIISEQhBCSiEAISUQgBiSiEgEQUQkAiCiEgEYXQ/wMhANIDIZLX1QAAAABJRU5ErkJggg==", + "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "width": 420, + "height": 420 + } + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oOJC87dkLwPr" + }, + "source": [ + "The darker squares in the confusion matrix plot indicate high numbers of cases, and you can hopefully see a diagonal line of darker squares indicating cases where the predicted and actual label are the same.\n", + "\n", + "Let's now calculate summary statistics for the confusion matrix." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 494 + }, + "id": "OYqetUyzL5Wz", + "outputId": "6a84d65e-113d-4281-dfc1-16e8b70f37e6" + }, + "source": [ + "# Summary stats for confusion matrix\n", + "conf_mat(data = results, truth = cuisine, estimate = .pred_class) %>% \n", + "summary()" + ], + "execution_count": 12, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + " .metric .estimator .estimate\n", + "1 accuracy multiclass 0.7880435\n", + "2 kap multiclass 0.7276583\n", + "3 sens macro 0.7780927\n", + "4 spec macro 0.9477598\n", + "5 ppv macro 0.7585583\n", + "6 npv macro 0.9460080\n", + "7 mcc multiclass 0.7292724\n", + "8 j_index macro 0.7258524\n", + "9 bal_accuracy macro 0.8629262\n", + "10 detection_prevalence macro 0.2000000\n", + "11 precision macro 0.7585583\n", + "12 recall macro 0.7780927\n", + "13 f_meas macro 0.7641862" + ], + "text/latex": "A tibble: 13 × 3\n\\begin{tabular}{lll}\n .metric & .estimator & .estimate\\\\\n & & \\\\\n\\hline\n\t accuracy & multiclass & 0.7880435\\\\\n\t kap & multiclass & 0.7276583\\\\\n\t sens & macro & 0.7780927\\\\\n\t spec & macro & 0.9477598\\\\\n\t ppv & macro & 0.7585583\\\\\n\t npv & macro & 0.9460080\\\\\n\t mcc & multiclass & 0.7292724\\\\\n\t j\\_index & macro & 0.7258524\\\\\n\t bal\\_accuracy & macro & 0.8629262\\\\\n\t detection\\_prevalence & macro & 0.2000000\\\\\n\t precision & macro & 0.7585583\\\\\n\t recall & macro & 0.7780927\\\\\n\t f\\_meas & macro & 0.7641862\\\\\n\\end{tabular}\n", + "text/markdown": "\nA tibble: 13 × 3\n\n| .metric <chr> | .estimator <chr> | .estimate <dbl> |\n|---|---|---|\n| accuracy | multiclass | 0.7880435 |\n| kap | multiclass | 0.7276583 |\n| sens | macro | 0.7780927 |\n| spec | macro | 0.9477598 |\n| ppv | macro | 0.7585583 |\n| npv | macro | 0.9460080 |\n| mcc | multiclass | 0.7292724 |\n| j_index | macro | 0.7258524 |\n| bal_accuracy | macro | 0.8629262 |\n| detection_prevalence | macro | 0.2000000 |\n| precision | macro | 0.7585583 |\n| recall | macro | 0.7780927 |\n| f_meas | macro | 0.7641862 |\n\n", + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 13 × 3
.metric.estimator.estimate
<chr><chr><dbl>
accuracy multiclass0.7880435
kap multiclass0.7276583
sens macro 0.7780927
spec macro 0.9477598
ppv macro 0.7585583
npv macro 0.9460080
mcc multiclass0.7292724
j_index macro 0.7258524
bal_accuracy macro 0.8629262
detection_prevalencemacro 0.2000000
precision macro 0.7585583
recall macro 0.7780927
f_meas macro 0.7641862
\n" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "43t7vz8vMJtW" + }, + "source": [ + "If we narrow down to some metrics such as accuracy, sensitivity, ppv, we are not badly off for a start 🥳!\n", + "\n", + "## 4. Digging Deeper\n", + "\n", + "Let's ask one subtle question: What criteria is used to settle for a given type of cuisine as the predicted outcome?\n", + "\n", + "Well, Statistical machine learning algorithms, like logistic regression, are based on `probability`; so what actually gets predicted by a classifier is a probability distribution over a set of possible outcomes. The class with the highest probability is then chosen as the most likely outcome for the given observations.\n", + "\n", + "Let's see this in action by making both hard class predictions and probabilities." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 248 + }, + "id": "xdKNs-ZPMTJL", + "outputId": "68f6ac5a-725a-4eff-9ea6-481fef00e008" + }, + "source": [ + "# Make hard class prediction and probabilities\n", + "results_prob <- cuisines_test %>%\n", + " select(cuisine) %>% \n", + " bind_cols(mr_fit %>% predict(new_data = cuisines_test)) %>% \n", + " bind_cols(mr_fit %>% predict(new_data = cuisines_test, type = \"prob\"))\n", + "\n", + "# Print out results\n", + "results_prob %>% \n", + " slice_head(n = 5)" + ], + "execution_count": 13, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + " cuisine .pred_class .pred_chinese .pred_indian .pred_japanese .pred_korean\n", + "1 indian thai 1.551259e-03 0.4587877 5.988039e-04 2.428503e-04\n", + "2 indian indian 2.637133e-05 0.9999488 6.648651e-07 2.259993e-05\n", + "3 indian indian 1.049433e-03 0.9909982 1.060937e-03 1.644947e-05\n", + "4 indian indian 6.237482e-02 0.4763035 9.136702e-02 3.660913e-01\n", + "5 indian indian 1.431745e-02 0.9418551 2.945239e-02 8.721782e-03\n", + " .pred_thai \n", + "1 5.388194e-01\n", + "2 1.577948e-06\n", + "3 6.874989e-03\n", + "4 3.863391e-03\n", + "5 5.653283e-03" + ], + "text/latex": "A tibble: 5 × 7\n\\begin{tabular}{lllllll}\n cuisine & .pred\\_class & .pred\\_chinese & .pred\\_indian & .pred\\_japanese & .pred\\_korean & .pred\\_thai\\\\\n & & & & & & \\\\\n\\hline\n\t indian & thai & 1.551259e-03 & 0.4587877 & 5.988039e-04 & 2.428503e-04 & 5.388194e-01\\\\\n\t indian & indian & 2.637133e-05 & 0.9999488 & 6.648651e-07 & 2.259993e-05 & 1.577948e-06\\\\\n\t indian & indian & 1.049433e-03 & 0.9909982 & 1.060937e-03 & 1.644947e-05 & 6.874989e-03\\\\\n\t indian & indian & 6.237482e-02 & 0.4763035 & 9.136702e-02 & 3.660913e-01 & 3.863391e-03\\\\\n\t indian & indian & 1.431745e-02 & 0.9418551 & 2.945239e-02 & 8.721782e-03 & 5.653283e-03\\\\\n\\end{tabular}\n", + "text/markdown": "\nA tibble: 5 × 7\n\n| cuisine <fct> | .pred_class <fct> | .pred_chinese <dbl> | .pred_indian <dbl> | .pred_japanese <dbl> | .pred_korean <dbl> | .pred_thai <dbl> |\n|---|---|---|---|---|---|---|\n| indian | thai | 1.551259e-03 | 0.4587877 | 5.988039e-04 | 2.428503e-04 | 5.388194e-01 |\n| indian | indian | 2.637133e-05 | 0.9999488 | 6.648651e-07 | 2.259993e-05 | 1.577948e-06 |\n| indian | indian | 1.049433e-03 | 0.9909982 | 1.060937e-03 | 1.644947e-05 | 6.874989e-03 |\n| indian | indian | 6.237482e-02 | 0.4763035 | 9.136702e-02 | 3.660913e-01 | 3.863391e-03 |\n| indian | indian | 1.431745e-02 | 0.9418551 | 2.945239e-02 | 8.721782e-03 | 5.653283e-03 |\n\n", + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A tibble: 5 × 7
cuisine.pred_class.pred_chinese.pred_indian.pred_japanese.pred_korean.pred_thai
<fct><fct><dbl><dbl><dbl><dbl><dbl>
indianthai 1.551259e-030.45878775.988039e-042.428503e-045.388194e-01
indianindian2.637133e-050.99994886.648651e-072.259993e-051.577948e-06
indianindian1.049433e-030.99099821.060937e-031.644947e-056.874989e-03
indianindian6.237482e-020.47630359.136702e-023.660913e-013.863391e-03
indianindian1.431745e-020.94185512.945239e-028.721782e-035.653283e-03
\n" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2tWVHMeLMYdM" + }, + "source": [ + "Much better!\n", + "\n", + "✅ Can you explain why the model is pretty sure that the first observation is Thai?\n", + "\n", + "## **🚀Challenge**\n", + "\n", + "In this lesson, you used your cleaned data to build a machine learning model that can predict a national cuisine based on a series of ingredients. Take some time to read through the [many options](https://www.tidymodels.org/find/parsnip/#models) Tidymodels provides to classify data and [other ways](https://parsnip.tidymodels.org/articles/articles/Examples.html#multinom_reg-models) to fit multinomial regression.\n", + "\n", + "#### THANK YOU TO:\n", + "\n", + "[`Allison Horst`](https://twitter.com/allison_horst/) for creating the amazing illustrations that make R more welcoming and engaging. Find more illustrations at her [gallery](https://www.google.com/url?q=https://github.com/allisonhorst/stats-illustrations&sa=D&source=editors&ust=1626380772530000&usg=AOvVaw3zcfyCizFQZpkSLzxiiQEM).\n", + "\n", + "[Cassie Breviu](https://www.twitter.com/cassieview) and [Jen Looper](https://www.twitter.com/jenlooper) for creating the original Python version of this module ♥️\n", + "\n", + "
\n", + "Would have thrown in some jokes but I donut understand food puns 😅.\n", + "\n", + "
\n", + "\n", + "Happy Learning,\n", + "\n", + "[Eric](https://twitter.com/ericntay), Gold Microsoft Learn Student Ambassador.\n" + ] + } + ] +} \ No newline at end of file diff --git a/4-Classification/2-Classifiers-1/solution/lesson_11.Rmd b/4-Classification/2-Classifiers-1/solution/lesson_11.Rmd new file mode 100644 index 000000000..f7dab06ac --- /dev/null +++ b/4-Classification/2-Classifiers-1/solution/lesson_11.Rmd @@ -0,0 +1,349 @@ +--- +title: 'Build a classification model: Delicious Asian and Indian Cuisines' +output: + html_document: + df_print: paged + theme: flatly + highlight: breezedark + toc: yes + toc_float: yes + code_download: yes +--- + +## Cuisine classifiers 1 + +In this lesson, we'll explore a variety of classifiers to *predict a given national cuisine based on a group of ingredients.* While doing so, we'll learn more about some of the ways that algorithms can be leveraged for classification tasks. + +### [**Pre-lecture quiz**](https://white-water-09ec41f0f.azurestaticapps.net/quiz/21/) + +### **Preparation** + +This lesson builds up on our [previous lesson](https://github.com/microsoft/ML-For-Beginners/blob/main/4-Classification/1-Introduction/solution/lesson_10-R.ipynb) where we: + +- Made a gentle introduction to classifications using a dataset about all the brilliant cuisines of Asia and India 😋. + +- Explored some [dplyr verbs](https://dplyr.tidyverse.org/) to prep and clean our data. + +- Made beautiful visualizations using ggplot2. + +- Demonstrated how to deal with imbalanced data by preprocessing it using [recipes](https://recipes.tidymodels.org/articles/Simple_Example.html). + +- Demonstrated how to `prep` and `bake` our recipe to confirm that it will work as supposed to. + +#### **Prerequisite** + +For this lesson, we'll require the following packages to clean, prep and visualize our data: + +- `tidyverse`: The [tidyverse](https://www.tidyverse.org/) is a [collection of R packages](https://www.tidyverse.org/packages) designed to makes data science faster, easier and more fun! + +- `tidymodels`: The [tidymodels](https://www.tidymodels.org/) framework is a [collection of packages](https://www.tidymodels.org/packages/) for modeling and machine learning. + +- `DataExplorer`: The [DataExplorer package](https://cran.r-project.org/web/packages/DataExplorer/vignettes/dataexplorer-intro.html) is meant to simplify and automate EDA process and report generation. + +- `themis`: The [themis package](https://themis.tidymodels.org/) provides Extra Recipes Steps for Dealing with Unbalanced Data. + +- `nnet`: The [nnet package](https://cran.r-project.org/web/packages/nnet/nnet.pdf) provides functions for estimating feed-forward neural networks with a single hidden layer, and for multinomial logistic regression models. + +You can have them installed as: + +`install.packages(c("tidyverse", "tidymodels", "DataExplorer", "here"))` + +Alternatively, the script below checks whether you have the packages required to complete this module and installs them for you in case they are missing. + +```{r, message=F, warning=F} +suppressWarnings(if (!require("pacman"))install.packages("pacman")) + +pacman::p_load(tidyverse, tidymodels, DataExplorer, themis, here) +``` + +Now, let's hit the ground running! + +## 1. Split the data into training and test sets. + +We'll start by picking a few steps from our previous lesson. + +### Drop the most common ingredients that create confusion between distinct cuisines, using `dplyr::select()`. + +Everyone loves rice, garlic and ginger! + +```{r recap_drop} +# Load the original cuisines data +df <- read_csv(file = "https://raw.githubusercontent.com/microsoft/ML-For-Beginners/main/4-Classification/data/cuisines.csv") + +# Drop id column, rice, garlic and ginger from our original data set +df_select <- df %>% + select(-c(1, rice, garlic, ginger)) %>% + # Encode cuisine column as categorical + mutate(cuisine = factor(cuisine)) + +# Display new data set +df_select %>% + slice_head(n = 5) + +# Display distribution of cuisines +df_select %>% + count(cuisine) %>% + arrange(desc(n)) +``` + +Perfect! Now, time to split the data such that 70% of the data goes to training and 30% goes to testing. We'll also apply a `stratification` technique when splitting the data to `maintain the proportion of each cuisine` in the training and validation datasets. + +[rsample](https://rsample.tidymodels.org/), a package in Tidymodels, provides infrastructure for efficient data splitting and resampling: + +```{r data_split} +# Load the core Tidymodels packages into R session +library(tidymodels) + +# Create split specification +set.seed(2056) +cuisines_split <- initial_split(data = df_select, + strata = cuisine, + prop = 0.7) + +# Extract the data in each split +cuisines_train <- training(cuisines_split) +cuisines_test <- testing(cuisines_split) + +# Print the number of cases in each split +cat("Training cases: ", nrow(cuisines_train), "\n", + "Test cases: ", nrow(cuisines_test), sep = "") + +# Display the first few rows of the training set +cuisines_train %>% + slice_head(n = 5) + + +# Display distribution of cuisines in the training set +cuisines_train %>% + count(cuisine) %>% + arrange(desc(n)) + + +``` + +## 2. Deal with imbalanced data + +As you might have noticed in the original data set as well as in our training set, there is quite an unequal distribution in the number of cuisines. Korean cuisines are *almost* 3 times Thai cuisines. Imbalanced data often has negative effects on the model performance. Many models perform best when the number of observations is equal and, thus, tend to struggle with unbalanced data. + +There are majorly two ways of dealing with imbalanced data sets: + +- adding observations to the minority class: `Over-sampling` e.g using a SMOTE algorithm which synthetically generates new examples of the minority class using nearest neighbors of these cases. + +- removing observations from majority class: `Under-sampling` + +In our previous lesson, we demonstrated how to deal with imbalanced data sets using a `recipe`. A recipe can be thought of as a blueprint that describes what steps should be applied to a data set in order to get it ready for data analysis. In our case, we want to have an equal distribution in the number of our cuisines for our `training set`. Let's get right into it. + +```{r recap_balance} +# Load themis package for dealing with imbalanced data +library(themis) + +# Create a recipe for preprocessing training data +cuisines_recipe <- recipe(cuisine ~ ., data = cuisines_train) %>% + step_smote(cuisine) + +# Print recipe +cuisines_recipe + +``` + +You can of course go ahead and confirm (using prep+bake) that the recipe will work as you expect it - all the cuisine labels having `559` observations. + +Since we'll be using this recipe as a preprocessor for modeling, a `workflow()` will do all the prep and bake for us, so we won't have to manually estimate the recipe. + +Now we are ready to train a model 👩‍💻👨‍💻! + +## 3. Choosing your classifier + +![Artwork by \@allison_horst](../images/parsnip.jpg){width="600"} + +Now we have to decide which algorithm to use for the job 🤔. + +In Tidymodels, the [`parsnip package`](https://parsnip.tidymodels.org/index.html) provides consistent interface for working with models across different engines (packages). Please see the parsnip documentation to explore [model types & engines](https://www.tidymodels.org/find/parsnip/#models) and their corresponding [model arguements](https://www.tidymodels.org/find/parsnip/#model-args). The variety is quite bewildering at first sight. For instance, the following methods all include classification techniques: + +- C5.0 Rule-Based Classification Models + +- Flexible Discriminant Models + +- Linear Discriminant Models + +- Regularized Discriminant Models + +- Logistic Regression Models + +- Multinomial Regression Models + +- Naive Bayes Models + +- Support Vector Machines + +- Nearest Neighbors + +- Decision Trees + +- Ensemble methods + +- Neural Networks + +The list goes on! + +### **What classifier to go with?** + +So, which classifier should you choose? Often, running through several and looking for a good result is a way to test. + +> AutoML solves this problem neatly by running these comparisons in the cloud, allowing you to choose the best algorithm for your data. Try it [here](https://docs.microsoft.com/learn/modules/automate-model-selection-with-azure-automl/?WT.mc_id=academic-15963-cxa) + +Also the choice of classifier depends on our problem. For instance, when the outcome can be categorized into `more than two classes`, like in our case, you must use a `multiclass classification algorithm` as opposed to `binary classification.` + +### **A better approach** + +A better way than wildly guessing, however, is to follow the ideas on this downloadable [ML Cheat sheet](https://docs.microsoft.com/azure/machine-learning/algorithm-cheat-sheet?WT.mc_id=academic-15963-cxa). Here, we discover that, for our multiclass problem, we have some choices: + +![A section of Microsoft's Algorithm Cheat Sheet, detailing multiclass classification options](../images/cheatsheet.png){width="500"} + +### **Reasoning** + +Let's see if we can reason our way through different approaches given the constraints we have: + +- **Deep Neural networks are too heavy**. Given our clean, but minimal dataset, and the fact that we are running training locally via notebooks, deep neural networks are too heavyweight for this task. + +- **No two-class classifier**. We do not use a two-class classifier, so that rules out one-vs-all. + +- **Decision tree or logistic regression could work**. A decision tree might work, or multinomial regression/multiclass logistic regression for multiclass data. + +- **Multiclass Boosted Decision Trees solve a different problem**. The multiclass boosted decision tree is most suitable for nonparametric tasks, e.g. tasks designed to build rankings, so it is not useful for us. + +Also, normally before embarking on more complex machine learning models e.g ensemble methods, it's a good idea to build the simplest possible model to get an idea of what is going on. So for this lesson, we'll start with a `multinomial logistic regression` model. + +> Logistic regression is a technique used when the outcome variable is categorical (or nominal). For Binary logistic regression the number of outcome variables is two, whereas the number of outcome variables for multinomial logistic regression is more than two. See [Advanced Regression Methods](https://bookdown.org/chua/ber642_advanced_regression/multinomial-logistic-regression.html) for further reading. + +## 4. Train and evaluate a Multinomial logistic regression model. + +In Tidymodels, `parsnip::multinom_reg()`, defines a model that uses linear predictors to predict multiclass data using the multinomial distribution. See `?multinom_reg()` for the different ways/engines you can use to fit this model. + +For this example, we'll fit a Multinomial regression model via the default [nnet](https://cran.r-project.org/web/packages/nnet/nnet.pdf) engine. + +> I picked a value for `penalty` sort of randomly. There are better ways to choose this value that is, by using `resampling` and `tuning` the model which we'll discuss later. +> +> See [Tidymodels: Get Started](https://www.tidymodels.org/start/tuning/) in case you want to learn more on how to tune model hyperparameters. + +```{r multinorm_reg} +# Create a multinomial regression model specification +mr_spec <- multinom_reg(penalty = 1) %>% + set_engine("nnet", MaxNWts = 2086) %>% + set_mode("classification") + +# Print model specification +mr_spec + +``` + +Great job 🥳! Now that we have a recipe and a model specification, we need to find a way of bundling them together into an object that will first preprocess the data then fit the model on the preprocessed data and also allow for potential post-processing activities. In Tidymodels, this convenient object is called a [`workflow`](https://workflows.tidymodels.org/) and conveniently holds your modeling components! This is what we'd call *pipelines* in *Python*. + +So let's bundle everything up into a workflow!📦 + +```{r workflow} +# Bundle recipe and model specification +mr_wf <- workflow() %>% + add_recipe(cuisines_recipe) %>% + add_model(mr_spec) + +# Print out workflow +mr_wf + +``` + +Workflows 👌👌! A **`workflow()`** can be fit in much the same way a model can. So, time to train a model! + +```{r train} +# Train a multinomial regression model +mr_fit <- fit(object = mr_wf, data = cuisines_train) + +mr_fit +``` + +The output shows the coefficients that the model learned during training. + +### Evaluate the Trained Model + +It's time to see how the model performed 📏 by evaluating it on a test set! Let's begin by making predictions on the test set. + +```{r test} +# Make predictions on the test set +results <- cuisines_test %>% select(cuisine) %>% + bind_cols(mr_fit %>% predict(new_data = cuisines_test)) + +# Print out results +results %>% + slice_head(n = 5) + +``` + +Great job! In Tidymodels, evaluating model performance can be done using [yardstick](https://yardstick.tidymodels.org/) - a package used to measure the effectiveness of models using performance metrics. As we did in our logistic regression lesson, let's begin by computing a confusion matrix. + +```{r conf_mat} +# Confusion matrix for categorical data +conf_mat(data = results, truth = cuisine, estimate = .pred_class) + + +``` + +When dealing with multiple classes, it's generally more intuitive to visualize this as a heat map, like this: + +```{r conf_viz} +update_geom_defaults(geom = "tile", new = list(color = "black", alpha = 0.7)) +# Visualize confusion matrix +results %>% + conf_mat(cuisine, .pred_class) %>% + autoplot(type = "heatmap") +``` + +The darker squares in the confusion matrix plot indicate high numbers of cases, and you can hopefully see a diagonal line of darker squares indicating cases where the predicted and actual label are the same. + +Let's now calculate summary statistics for the confusion matrix. + +```{r conf_stats} +# Summary stats for confusion matrix +conf_mat(data = results, truth = cuisine, estimate = .pred_class) %>% summary() +``` + +If we narrow down to some metrics such as accuracy, sensitivity, ppv, we are not badly off for a start 🥳! + +## 4. Digging Deeper + +Let's ask one subtle question: What criteria is used to settle for a given type of cuisine as the predicted outcome? + +Well, Statistical machine learning algorithms, like logistic regression, are based on `probability`; so what actually gets predicted by a classifier is a probability distribution over a set of possible outcomes. The class with the highest probability is then chosen as the most likely outcome for the given observations. + +Let's see this in action by making both hard class predictions and probabilities. + +```{r pred_prob} +# Make hard class prediction and probabilities +results_prob <- cuisines_test %>% + select(cuisine) %>% + bind_cols(mr_fit %>% predict(new_data = cuisines_test)) %>% + bind_cols(mr_fit %>% predict(new_data = cuisines_test, type = "prob")) + +# Print out results +results_prob %>% + slice_head(n = 5) + + +``` + +Much better! + +✅ Can you explain why the model is pretty sure that the first observation is Thai? + +## **🚀Challenge** + +In this lesson, you used your cleaned data to build a machine learning model that can predict a national cuisine based on a series of ingredients. Take some time to read through the [many options](https://www.tidymodels.org/find/parsnip/#models) Tidymodels provides to classify data and [other ways](https://parsnip.tidymodels.org/articles/articles/Examples.html#multinom_reg-models) to fit multinomial regression. + +#### THANK YOU TO: + +[`Allison Horst`](https://twitter.com/allison_horst/) for creating the amazing illustrations that make R more welcoming and engaging. Find more illustrations at her [gallery](https://www.google.com/url?q=https://github.com/allisonhorst/stats-illustrations&sa=D&source=editors&ust=1626380772530000&usg=AOvVaw3zcfyCizFQZpkSLzxiiQEM). + +[Cassie Breviu](https://www.twitter.com/cassieview) and [Jen Looper](https://www.twitter.com/jenlooper) for creating the original Python version of this module ♥️ + +Happy Learning, + +[Eric](https://twitter.com/ericntay), Gold Microsoft Learn Student Ambassador. From 9c63b155b53e5e4df63cc6d68336ec9f98b3280d Mon Sep 17 00:00:00 2001 From: R-icntay <63848664+R-icntay@users.noreply.github.com> Date: Mon, 23 Aug 2021 18:40:25 +0300 Subject: [PATCH 3/5] Update and add R Notebooks to the R folder --- .../2-Classifiers-1/solution/R/README.md | 1 - .../solution/{ => R}/lesson_11-R.ipynb | 844 +++++++++++------- .../solution/{ => R}/lesson_11.Rmd | 4 +- 3 files changed, 516 insertions(+), 333 deletions(-) delete mode 100644 4-Classification/2-Classifiers-1/solution/R/README.md rename 4-Classification/2-Classifiers-1/solution/{ => R}/lesson_11-R.ipynb (59%) rename 4-Classification/2-Classifiers-1/solution/{ => R}/lesson_11.Rmd (99%) diff --git a/4-Classification/2-Classifiers-1/solution/R/README.md b/4-Classification/2-Classifiers-1/solution/R/README.md deleted file mode 100644 index f59c07cc0..000000000 --- a/4-Classification/2-Classifiers-1/solution/R/README.md +++ /dev/null @@ -1 +0,0 @@ -this is a temporary placeholder \ No newline at end of file diff --git a/4-Classification/2-Classifiers-1/solution/lesson_11-R.ipynb b/4-Classification/2-Classifiers-1/solution/R/lesson_11-R.ipynb similarity index 59% rename from 4-Classification/2-Classifiers-1/solution/lesson_11-R.ipynb rename to 4-Classification/2-Classifiers-1/solution/R/lesson_11-R.ipynb index 30fb66c7c..bd1aa914b 100644 --- a/4-Classification/2-Classifiers-1/solution/lesson_11-R.ipynb +++ b/4-Classification/2-Classifiers-1/solution/R/lesson_11-R.ipynb @@ -1,6 +1,6 @@ { "nbformat": 4, - "nbformat_minor": 0, + "nbformat_minor": 2, "metadata": { "colab": { "name": "lesson_11-R.ipynb", @@ -19,18 +19,15 @@ "cells": [ { "cell_type": "markdown", - "metadata": { - "id": "zs2woWv_HoE8" - }, "source": [ "# Build a classification model: Delicious Asian and Indian Cuisines" - ] + ], + "metadata": { + "id": "zs2woWv_HoE8" + } }, { "cell_type": "markdown", - "metadata": { - "id": "iDFOb3ebHwQC" - }, "source": [ "## Cuisine classifiers 1\n", "\n", @@ -66,51 +63,51 @@ "- `nnet`: The [nnet package](https://cran.r-project.org/web/packages/nnet/nnet.pdf) provides functions for estimating feed-forward neural networks with a single hidden layer, and for multinomial logistic regression models.\n", "\n", "You can have them installed as:" - ] + ], + "metadata": { + "id": "iDFOb3ebHwQC" + } }, { "cell_type": "markdown", - "metadata": { - "id": "4V85BGCjII7F" - }, "source": [ "\n", "`install.packages(c(\"tidyverse\", \"tidymodels\", \"DataExplorer\", \"here\"))`\n", "\n", "Alternatively, the script below checks whether you have the packages required to complete this module and installs them for you in case they are missing." - ] + ], + "metadata": { + "id": "4V85BGCjII7F" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "an5NPyyKIKNR", - "outputId": "834d5e74-f4b8-49f9-8ab5-4c52ff2d7bc8" - }, + "execution_count": 2, "source": [ - "suppressWarnings(if (!require(\"pacman\"))install.packages(\"pacman\"))\n", - "\n", + "suppressWarnings(if (!require(\"pacman\"))install.packages(\"pacman\"))\r\n", + "\r\n", "pacman::p_load(tidyverse, tidymodels, themis, here)" ], - "execution_count": 2, "outputs": [ { "output_type": "stream", + "name": "stderr", "text": [ "Loading required package: pacman\n", "\n" - ], - "name": "stderr" + ] } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "an5NPyyKIKNR", + "outputId": "834d5e74-f4b8-49f9-8ab5-4c52ff2d7bc8" + } }, { "cell_type": "markdown", - "metadata": { - "id": "0ax9GQLBINVv" - }, "source": [ "Now, let's hit the ground running!\n", "\n", @@ -121,41 +118,37 @@ "### Drop the most common ingredients that create confusion between distinct cuisines, using `dplyr::select()`.\n", "\n", "Everyone loves rice, garlic and ginger!\n" - ] + ], + "metadata": { + "id": "0ax9GQLBINVv" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 735 - }, - "id": "jhCrrH22IWVR", - "outputId": "d444a85c-1d8b-485f-bc4f-8be2e8f8217c" - }, + "execution_count": 3, "source": [ - "# Load the original cuisines data\n", - "df <- read_csv(file = \"https://raw.githubusercontent.com/microsoft/ML-For-Beginners/main/4-Classification/data/cuisines.csv\")\n", - "\n", - "# Drop id column, rice, garlic and ginger from our original data set\n", - "df_select <- df %>% \n", - " select(-c(1, rice, garlic, ginger)) %>%\n", - " # Encode cuisine column as categorical\n", - " mutate(cuisine = factor(cuisine))\n", - "\n", - "# Display new data set\n", - "df_select %>% \n", - " slice_head(n = 5)\n", - "\n", - "# Display distribution of cuisines\n", - "df_select %>% \n", - " count(cuisine) %>% \n", + "# Load the original cuisines data\r\n", + "df <- read_csv(file = \"https://raw.githubusercontent.com/microsoft/ML-For-Beginners/main/4-Classification/data/cuisines.csv\")\r\n", + "\r\n", + "# Drop id column, rice, garlic and ginger from our original data set\r\n", + "df_select <- df %>% \r\n", + " select(-c(1, rice, garlic, ginger)) %>%\r\n", + " # Encode cuisine column as categorical\r\n", + " mutate(cuisine = factor(cuisine))\r\n", + "\r\n", + "# Display new data set\r\n", + "df_select %>% \r\n", + " slice_head(n = 5)\r\n", + "\r\n", + "# Display distribution of cuisines\r\n", + "df_select %>% \r\n", + " count(cuisine) %>% \r\n", " arrange(desc(n))" ], - "execution_count": 3, "outputs": [ { "output_type": "stream", + "name": "stderr", "text": [ "New names:\n", "* `` -> ...1\n", @@ -171,8 +164,7 @@ "\u001b[36mℹ\u001b[39m Use \u001b[30m\u001b[47m\u001b[30m\u001b[47m`spec()`\u001b[47m\u001b[30m\u001b[49m\u001b[39m to retrieve the full column specification for this data.\n", "\u001b[36mℹ\u001b[39m Specify the column types or set \u001b[30m\u001b[47m\u001b[30m\u001b[47m`show_col_types = FALSE`\u001b[47m\u001b[30m\u001b[49m\u001b[39m to quiet this message.\n", "\n" - ], - "name": "stderr" + ] }, { "output_type": "display_data", @@ -197,8 +189,32 @@ "4 0 0 0 0 \n", "5 0 0 1 0 " ], - "text/latex": "A tibble: 5 × 381\n\\begin{tabular}{lllllllllllllllllllll}\n cuisine & almond & angelica & anise & anise\\_seed & apple & apple\\_brandy & apricot & armagnac & artemisia & ⋯ & whiskey & white\\_bread & white\\_wine & whole\\_grain\\_wheat\\_flour & wine & wood & yam & yeast & yogurt & zucchini\\\\\n & & & & & & & & & & ⋯ & & & & & & & & & & \\\\\n\\hline\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n\\end{tabular}\n", - "text/markdown": "\nA tibble: 5 × 381\n\n| cuisine <fct> | almond <dbl> | angelica <dbl> | anise <dbl> | anise_seed <dbl> | apple <dbl> | apple_brandy <dbl> | apricot <dbl> | armagnac <dbl> | artemisia <dbl> | ⋯ ⋯ | whiskey <dbl> | white_bread <dbl> | white_wine <dbl> | whole_grain_wheat_flour <dbl> | wine <dbl> | wood <dbl> | yam <dbl> | yeast <dbl> | yogurt <dbl> | zucchini <dbl> |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |\n\n", + "text/markdown": [ + "\n", + "A tibble: 5 × 381\n", + "\n", + "| cuisine <fct> | almond <dbl> | angelica <dbl> | anise <dbl> | anise_seed <dbl> | apple <dbl> | apple_brandy <dbl> | apricot <dbl> | armagnac <dbl> | artemisia <dbl> | ⋯ ⋯ | whiskey <dbl> | white_bread <dbl> | white_wine <dbl> | whole_grain_wheat_flour <dbl> | wine <dbl> | wood <dbl> | yam <dbl> | yeast <dbl> | yogurt <dbl> | zucchini <dbl> |\n", + "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", + "| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", + "| indian | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", + "| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", + "| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", + "| indian | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |\n", + "\n" + ], + "text/latex": [ + "A tibble: 5 × 381\n", + "\\begin{tabular}{lllllllllllllllllllll}\n", + " cuisine & almond & angelica & anise & anise\\_seed & apple & apple\\_brandy & apricot & armagnac & artemisia & ⋯ & whiskey & white\\_bread & white\\_wine & whole\\_grain\\_wheat\\_flour & wine & wood & yam & yeast & yogurt & zucchini\\\\\n", + " & & & & & & & & & & ⋯ & & & & & & & & & & \\\\\n", + "\\hline\n", + "\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t indian & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t indian & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n", + "\\end{tabular}\n" + ], "text/html": [ "\n", "\n", @@ -229,8 +245,32 @@ "4 japanese 320\n", "5 thai 289" ], - "text/latex": "A tibble: 5 × 2\n\\begin{tabular}{ll}\n cuisine & n\\\\\n & \\\\\n\\hline\n\t korean & 799\\\\\n\t indian & 598\\\\\n\t chinese & 442\\\\\n\t japanese & 320\\\\\n\t thai & 289\\\\\n\\end{tabular}\n", - "text/markdown": "\nA tibble: 5 × 2\n\n| cuisine <fct> | n <int> |\n|---|---|\n| korean | 799 |\n| indian | 598 |\n| chinese | 442 |\n| japanese | 320 |\n| thai | 289 |\n\n", + "text/markdown": [ + "\n", + "A tibble: 5 × 2\n", + "\n", + "| cuisine <fct> | n <int> |\n", + "|---|---|\n", + "| korean | 799 |\n", + "| indian | 598 |\n", + "| chinese | 442 |\n", + "| japanese | 320 |\n", + "| thai | 289 |\n", + "\n" + ], + "text/latex": [ + "A tibble: 5 × 2\n", + "\\begin{tabular}{ll}\n", + " cuisine & n\\\\\n", + " & \\\\\n", + "\\hline\n", + "\t korean & 799\\\\\n", + "\t indian & 598\\\\\n", + "\t chinese & 442\\\\\n", + "\t japanese & 320\\\\\n", + "\t thai & 289\\\\\n", + "\\end{tabular}\n" + ], "text/html": [ "
A tibble: 5 × 381
\n", "\n", @@ -250,66 +290,66 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 735 + }, + "id": "jhCrrH22IWVR", + "outputId": "d444a85c-1d8b-485f-bc4f-8be2e8f8217c" + } }, { "cell_type": "markdown", - "metadata": { - "id": "AYTjVyajIdny" - }, "source": [ "Perfect! Now, time to split the data such that 70% of the data goes to training and 30% goes to testing. We'll also apply a `stratification` technique when splitting the data to `maintain the proportion of each cuisine` in the training and validation datasets.\n", "\n", "[rsample](https://rsample.tidymodels.org/), a package in Tidymodels, provides infrastructure for efficient data splitting and resampling:" - ] + ], + "metadata": { + "id": "AYTjVyajIdny" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 535 - }, - "id": "w5FWIkEiIjdN", - "outputId": "2e195fd9-1a8f-4b91-9573-cce5582242df" - }, + "execution_count": 4, "source": [ - "# Load the core Tidymodels packages into R session\n", - "library(tidymodels)\n", - "\n", - "# Create split specification\n", - "set.seed(2056)\n", - "cuisines_split <- initial_split(data = df_select,\n", - " strata = cuisine,\n", - " prop = 0.7)\n", - "\n", - "# Extract the data in each split\n", - "cuisines_train <- training(cuisines_split)\n", - "cuisines_test <- testing(cuisines_split)\n", - "\n", - "# Print the number of cases in each split\n", - "cat(\"Training cases: \", nrow(cuisines_train), \"\\n\",\n", - " \"Test cases: \", nrow(cuisines_test), sep = \"\")\n", - "\n", - "# Display the first few rows of the training set\n", - "cuisines_train %>% \n", - " slice_head(n = 5)\n", - "\n", - "\n", - "# Display distribution of cuisines in the training set\n", - "cuisines_train %>% \n", - " count(cuisine) %>% \n", + "# Load the core Tidymodels packages into R session\r\n", + "library(tidymodels)\r\n", + "\r\n", + "# Create split specification\r\n", + "set.seed(2056)\r\n", + "cuisines_split <- initial_split(data = df_select,\r\n", + " strata = cuisine,\r\n", + " prop = 0.7)\r\n", + "\r\n", + "# Extract the data in each split\r\n", + "cuisines_train <- training(cuisines_split)\r\n", + "cuisines_test <- testing(cuisines_split)\r\n", + "\r\n", + "# Print the number of cases in each split\r\n", + "cat(\"Training cases: \", nrow(cuisines_train), \"\\n\",\r\n", + " \"Test cases: \", nrow(cuisines_test), sep = \"\")\r\n", + "\r\n", + "# Display the first few rows of the training set\r\n", + "cuisines_train %>% \r\n", + " slice_head(n = 5)\r\n", + "\r\n", + "\r\n", + "# Display distribution of cuisines in the training set\r\n", + "cuisines_train %>% \r\n", + " count(cuisine) %>% \r\n", " arrange(desc(n))" ], - "execution_count": 4, "outputs": [ { "output_type": "stream", + "name": "stdout", "text": [ "Training cases: 1712\n", "Test cases: 736" - ], - "name": "stdout" + ] }, { "output_type": "display_data", @@ -334,8 +374,32 @@ "4 0 0 0 0 \n", "5 0 0 0 0 " ], - "text/latex": "A tibble: 5 × 381\n\\begin{tabular}{lllllllllllllllllllll}\n cuisine & almond & angelica & anise & anise\\_seed & apple & apple\\_brandy & apricot & armagnac & artemisia & ⋯ & whiskey & white\\_bread & white\\_wine & whole\\_grain\\_wheat\\_flour & wine & wood & yam & yeast & yogurt & zucchini\\\\\n & & & & & & & & & & ⋯ & & & & & & & & & & \\\\\n\\hline\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n\\end{tabular}\n", - "text/markdown": "\nA tibble: 5 × 381\n\n| cuisine <fct> | almond <dbl> | angelica <dbl> | anise <dbl> | anise_seed <dbl> | apple <dbl> | apple_brandy <dbl> | apricot <dbl> | armagnac <dbl> | artemisia <dbl> | ⋯ ⋯ | whiskey <dbl> | white_bread <dbl> | white_wine <dbl> | whole_grain_wheat_flour <dbl> | wine <dbl> | wood <dbl> | yam <dbl> | yeast <dbl> | yogurt <dbl> | zucchini <dbl> |\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n\n", + "text/markdown": [ + "\n", + "A tibble: 5 × 381\n", + "\n", + "| cuisine <fct> | almond <dbl> | angelica <dbl> | anise <dbl> | anise_seed <dbl> | apple <dbl> | apple_brandy <dbl> | apricot <dbl> | armagnac <dbl> | artemisia <dbl> | ⋯ ⋯ | whiskey <dbl> | white_bread <dbl> | white_wine <dbl> | whole_grain_wheat_flour <dbl> | wine <dbl> | wood <dbl> | yam <dbl> | yeast <dbl> | yogurt <dbl> | zucchini <dbl> |\n", + "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", + "| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |\n", + "| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |\n", + "| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", + "| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", + "| chinese | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", + "\n" + ], + "text/latex": [ + "A tibble: 5 × 381\n", + "\\begin{tabular}{lllllllllllllllllllll}\n", + " cuisine & almond & angelica & anise & anise\\_seed & apple & apple\\_brandy & apricot & armagnac & artemisia & ⋯ & whiskey & white\\_bread & white\\_wine & whole\\_grain\\_wheat\\_flour & wine & wood & yam & yeast & yogurt & zucchini\\\\\n", + " & & & & & & & & & & ⋯ & & & & & & & & & & \\\\\n", + "\\hline\n", + "\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\t chinese & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & ⋯ & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\\end{tabular}\n" + ], "text/html": [ "
A tibble: 5 × 2
\n", "\n", @@ -366,8 +430,32 @@ "4 japanese 224\n", "5 thai 202" ], - "text/latex": "A tibble: 5 × 2\n\\begin{tabular}{ll}\n cuisine & n\\\\\n & \\\\\n\\hline\n\t korean & 559\\\\\n\t indian & 418\\\\\n\t chinese & 309\\\\\n\t japanese & 224\\\\\n\t thai & 202\\\\\n\\end{tabular}\n", - "text/markdown": "\nA tibble: 5 × 2\n\n| cuisine <fct> | n <int> |\n|---|---|\n| korean | 559 |\n| indian | 418 |\n| chinese | 309 |\n| japanese | 224 |\n| thai | 202 |\n\n", + "text/markdown": [ + "\n", + "A tibble: 5 × 2\n", + "\n", + "| cuisine <fct> | n <int> |\n", + "|---|---|\n", + "| korean | 559 |\n", + "| indian | 418 |\n", + "| chinese | 309 |\n", + "| japanese | 224 |\n", + "| thai | 202 |\n", + "\n" + ], + "text/latex": [ + "A tibble: 5 × 2\n", + "\\begin{tabular}{ll}\n", + " cuisine & n\\\\\n", + " & \\\\\n", + "\\hline\n", + "\t korean & 559\\\\\n", + "\t indian & 418\\\\\n", + "\t chinese & 309\\\\\n", + "\t japanese & 224\\\\\n", + "\t thai & 202\\\\\n", + "\\end{tabular}\n" + ], "text/html": [ "
A tibble: 5 × 381
\n", "\n", @@ -387,13 +475,18 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 535 + }, + "id": "w5FWIkEiIjdN", + "outputId": "2e195fd9-1a8f-4b91-9573-cce5582242df" + } }, { "cell_type": "markdown", - "metadata": { - "id": "daBi9qJNIwqW" - }, "source": [ "## 2. Deal with imbalanced data\n", "\n", @@ -406,30 +499,25 @@ "- removing observations from majority class: `Under-sampling`\n", "\n", "In our previous lesson, we demonstrated how to deal with imbalanced data sets using a `recipe`. A recipe can be thought of as a blueprint that describes what steps should be applied to a data set in order to get it ready for data analysis. In our case, we want to have an equal distribution in the number of our cuisines for our `training set`. Let's get right into it." - ] + ], + "metadata": { + "id": "daBi9qJNIwqW" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 200 - }, - "id": "Az6LFBGxI1X0", - "outputId": "29d71d85-64b0-4e62-871e-bcd5398573b6" - }, + "execution_count": 5, "source": [ - "# Load themis package for dealing with imbalanced data\n", - "library(themis)\n", - "\n", - "# Create a recipe for preprocessing training data\n", - "cuisines_recipe <- recipe(cuisine ~ ., data = cuisines_train) %>% \n", - " step_smote(cuisine)\n", - "\n", - "# Print recipe\n", + "# Load themis package for dealing with imbalanced data\r\n", + "library(themis)\r\n", + "\r\n", + "# Create a recipe for preprocessing training data\r\n", + "cuisines_recipe <- recipe(cuisine ~ ., data = cuisines_train) %>% \r\n", + " step_smote(cuisine)\r\n", + "\r\n", + "# Print recipe\r\n", "cuisines_recipe" ], - "execution_count": 5, "outputs": [ { "output_type": "display_data", @@ -450,88 +538,93 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 200 + }, + "id": "Az6LFBGxI1X0", + "outputId": "29d71d85-64b0-4e62-871e-bcd5398573b6" + } }, { "cell_type": "markdown", + "source": [ + "You can of course go ahead and confirm (using prep+bake) that the recipe will work as you expect it - all the cuisine labels having `559` observations.\r\n", + "\r\n", + "Since we'll be using this recipe as a preprocessor for modeling, a `workflow()` will do all the prep and bake for us, so we won't have to manually estimate the recipe.\r\n", + "\r\n", + "Now we are ready to train a model 👩‍💻👨‍💻!\r\n", + "\r\n", + "## 3. Choosing your classifier\r\n", + "\r\n", + "

\r\n", + " \r\n", + "

Artwork by @allison_horst
\r\n" + ], "metadata": { "id": "NBL3PqIWJBBB" - }, - "source": [ - "You can of course go ahead and confirm (using prep+bake) that the recipe will work as you expect it - all the cuisine labels having `559` observations.\n", - "\n", - "Since we'll be using this recipe as a preprocessor for modeling, a `workflow()` will do all the prep and bake for us, so we won't have to manually estimate the recipe.\n", - "\n", - "Now we are ready to train a model 👩‍💻👨‍💻!\n", - "\n", - "## 3. Choosing your classifier\n", - "\n", - "

\n", - " \n", - "

Artwork by @allison_horst
\n" - ] + } }, { "cell_type": "markdown", + "source": [ + "Now we have to decide which algorithm to use for the job 🤔.\r\n", + "\r\n", + "In Tidymodels, the [`parsnip package`](https://parsnip.tidymodels.org/index.html) provides consistent interface for working with models across different engines (packages). Please see the parsnip documentation to explore [model types & engines](https://www.tidymodels.org/find/parsnip/#models) and their corresponding [model arguements](https://www.tidymodels.org/find/parsnip/#model-args). The variety is quite bewildering at first sight. For instance, the following methods all include classification techniques:\r\n", + "\r\n", + "- C5.0 Rule-Based Classification Models\r\n", + "\r\n", + "- Flexible Discriminant Models\r\n", + "\r\n", + "- Linear Discriminant Models\r\n", + "\r\n", + "- Regularized Discriminant Models\r\n", + "\r\n", + "- Logistic Regression Models\r\n", + "\r\n", + "- Multinomial Regression Models\r\n", + "\r\n", + "- Naive Bayes Models\r\n", + "\r\n", + "- Support Vector Machines\r\n", + "\r\n", + "- Nearest Neighbors\r\n", + "\r\n", + "- Decision Trees\r\n", + "\r\n", + "- Ensemble methods\r\n", + "\r\n", + "- Neural Networks\r\n", + "\r\n", + "The list goes on!\r\n", + "\r\n", + "### **What classifier to go with?**\r\n", + "\r\n", + "So, which classifier should you choose? Often, running through several and looking for a good result is a way to test.\r\n", + "\r\n", + "> AutoML solves this problem neatly by running these comparisons in the cloud, allowing you to choose the best algorithm for your data. Try it [here](https://docs.microsoft.com/learn/modules/automate-model-selection-with-azure-automl/?WT.mc_id=academic-15963-cxa)\r\n", + "\r\n", + "Also the choice of classifier depends on our problem. For instance, when the outcome can be categorized into `more than two classes`, like in our case, you must use a `multiclass classification algorithm` as opposed to `binary classification.`\r\n", + "\r\n", + "### **A better approach**\r\n", + "\r\n", + "A better way than wildly guessing, however, is to follow the ideas on this downloadable [ML Cheat sheet](https://docs.microsoft.com/azure/machine-learning/algorithm-cheat-sheet?WT.mc_id=academic-15963-cxa). Here, we discover that, for our multiclass problem, we have some choices:\r\n", + "\r\n", + "

\r\n", + " \r\n", + "

A section of Microsoft's Algorithm Cheat Sheet, detailing multiclass classification options
\r\n", + "\r\n" + ], "metadata": { "id": "a6DLAZ3vJZ14" - }, - "source": [ - "Now we have to decide which algorithm to use for the job 🤔.\n", - "\n", - "In Tidymodels, the [`parsnip package`](https://parsnip.tidymodels.org/index.html) provides consistent interface for working with models across different engines (packages). Please see the parsnip documentation to explore [model types & engines](https://www.tidymodels.org/find/parsnip/#models) and their corresponding [model arguements](https://www.tidymodels.org/find/parsnip/#model-args). The variety is quite bewildering at first sight. For instance, the following methods all include classification techniques:\n", - "\n", - "- C5.0 Rule-Based Classification Models\n", - "\n", - "- Flexible Discriminant Models\n", - "\n", - "- Linear Discriminant Models\n", - "\n", - "- Regularized Discriminant Models\n", - "\n", - "- Logistic Regression Models\n", - "\n", - "- Multinomial Regression Models\n", - "\n", - "- Naive Bayes Models\n", - "\n", - "- Support Vector Machines\n", - "\n", - "- Nearest Neighbors\n", - "\n", - "- Decision Trees\n", - "\n", - "- Ensemble methods\n", - "\n", - "- Neural Networks\n", - "\n", - "The list goes on!\n", - "\n", - "### **What classifier to go with?**\n", - "\n", - "So, which classifier should you choose? Often, running through several and looking for a good result is a way to test.\n", - "\n", - "> AutoML solves this problem neatly by running these comparisons in the cloud, allowing you to choose the best algorithm for your data. Try it [here](https://docs.microsoft.com/learn/modules/automate-model-selection-with-azure-automl/?WT.mc_id=academic-15963-cxa)\n", - "\n", - "Also the choice of classifier depends on our problem. For instance, when the outcome can be categorized into `more than two classes`, like in our case, you must use a `multiclass classification algorithm` as opposed to `binary classification.`\n", - "\n", - "### **A better approach**\n", - "\n", - "A better way than wildly guessing, however, is to follow the ideas on this downloadable [ML Cheat sheet](https://docs.microsoft.com/azure/machine-learning/algorithm-cheat-sheet?WT.mc_id=academic-15963-cxa). Here, we discover that, for our multiclass problem, we have some choices:\n", - "\n", - "

\n", - " \n", - "

A section of Microsoft's Algorithm Cheat Sheet, detailing multiclass classification options
\n", - "\n" - ] + } }, { "cell_type": "markdown", - "metadata": { - "id": "gWMsVcbBJemu" - }, "source": [ "### **Reasoning**\n", "\n", @@ -558,28 +651,23 @@ "> I picked a value for `penalty` sort of randomly. There are better ways to choose this value that is, by using `resampling` and `tuning` the model which we'll discuss later.\n", ">\n", "> See [Tidymodels: Get Started](https://www.tidymodels.org/start/tuning/) in case you want to learn more on how to tune model hyperparameters." - ] + ], + "metadata": { + "id": "gWMsVcbBJemu" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 166 - }, - "id": "Wq_fcyQiJvfG", - "outputId": "c30449c7-3864-4be7-f810-72a003743e2d" - }, + "execution_count": 6, "source": [ - "# Create a multinomial regression model specification\n", - "mr_spec <- multinom_reg(penalty = 1) %>% \n", - " set_engine(\"nnet\", MaxNWts = 2086) %>% \n", - " set_mode(\"classification\")\n", - "\n", - "# Print model specification\n", + "# Create a multinomial regression model specification\r\n", + "mr_spec <- multinom_reg(penalty = 1) %>% \r\n", + " set_engine(\"nnet\", MaxNWts = 2086) %>% \r\n", + " set_mode(\"classification\")\r\n", + "\r\n", + "# Print model specification\r\n", "mr_spec" ], - "execution_count": 6, "outputs": [ { "output_type": "display_data", @@ -598,39 +686,39 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 166 + }, + "id": "Wq_fcyQiJvfG", + "outputId": "c30449c7-3864-4be7-f810-72a003743e2d" + } }, { "cell_type": "markdown", - "metadata": { - "id": "NlSbzDfgJ0zh" - }, "source": [ "Great job 🥳! Now that we have a recipe and a model specification, we need to find a way of bundling them together into an object that will first preprocess the data then fit the model on the preprocessed data and also allow for potential post-processing activities. In Tidymodels, this convenient object is called a [`workflow`](https://workflows.tidymodels.org/) and conveniently holds your modeling components! This is what we'd call *pipelines* in *Python*.\n", "\n", "So let's bundle everything up into a workflow!📦" - ] + ], + "metadata": { + "id": "NlSbzDfgJ0zh" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 333 - }, - "id": "Sc1TfPA4Ke3_", - "outputId": "82c70013-e431-4e7e-cef6-9fcf8aad4a6c" - }, + "execution_count": 7, "source": [ - "# Bundle recipe and model specification\n", - "mr_wf <- workflow() %>% \n", - " add_recipe(cuisines_recipe) %>% \n", - " add_model(mr_spec)\n", - "\n", - "# Print out workflow\n", + "# Bundle recipe and model specification\r\n", + "mr_wf <- workflow() %>% \r\n", + " add_recipe(cuisines_recipe) %>% \r\n", + " add_model(mr_spec)\r\n", + "\r\n", + "# Print out workflow\r\n", "mr_wf" ], - "execution_count": 7, "outputs": [ { "output_type": "display_data", @@ -659,34 +747,34 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 333 + }, + "id": "Sc1TfPA4Ke3_", + "outputId": "82c70013-e431-4e7e-cef6-9fcf8aad4a6c" + } }, { "cell_type": "markdown", - "metadata": { - "id": "TNQ8i85aKf9L" - }, "source": [ "Workflows 👌👌! A **`workflow()`** can be fit in much the same way a model can. So, time to train a model!" - ] + ], + "metadata": { + "id": "TNQ8i85aKf9L" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 1000 - }, - "id": "GMbdfVmTKkJI", - "outputId": "adf9ebdf-d69d-4a64-e9fd-e06e5322292e" - }, + "execution_count": 8, "source": [ "# Train a multinomial regression model\n", "mr_fit <- fit(object = mr_wf, data = cuisines_train)\n", "\n", "mr_fit" ], - "execution_count": 8, "outputs": [ { "output_type": "display_data", @@ -759,31 +847,32 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "GMbdfVmTKkJI", + "outputId": "adf9ebdf-d69d-4a64-e9fd-e06e5322292e" + } }, { "cell_type": "markdown", - "metadata": { - "id": "tt2BfOxrKmcJ" - }, "source": [ "The output shows the coefficients that the model learned during training.\n", "\n", "### Evaluate the Trained Model\n", "\n", "It's time to see how the model performed 📏 by evaluating it on a test set! Let's begin by making predictions on the test set." - ] + ], + "metadata": { + "id": "tt2BfOxrKmcJ" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 248 - }, - "id": "CqtckvtsKqax", - "outputId": "e57fe557-6a68-4217-fe82-173328c5436d" - }, + "execution_count": 9, "source": [ "# Make predictions on the test set\n", "results <- cuisines_test %>% select(cuisine) %>% \n", @@ -793,7 +882,6 @@ "results %>% \n", " slice_head(n = 5)" ], - "execution_count": 9, "outputs": [ { "output_type": "display_data", @@ -806,8 +894,32 @@ "4 indian indian \n", "5 indian indian " ], - "text/latex": "A tibble: 5 × 2\n\\begin{tabular}{ll}\n cuisine & .pred\\_class\\\\\n & \\\\\n\\hline\n\t indian & thai \\\\\n\t indian & indian\\\\\n\t indian & indian\\\\\n\t indian & indian\\\\\n\t indian & indian\\\\\n\\end{tabular}\n", - "text/markdown": "\nA tibble: 5 × 2\n\n| cuisine <fct> | .pred_class <fct> |\n|---|---|\n| indian | thai |\n| indian | indian |\n| indian | indian |\n| indian | indian |\n| indian | indian |\n\n", + "text/markdown": [ + "\n", + "A tibble: 5 × 2\n", + "\n", + "| cuisine <fct> | .pred_class <fct> |\n", + "|---|---|\n", + "| indian | thai |\n", + "| indian | indian |\n", + "| indian | indian |\n", + "| indian | indian |\n", + "| indian | indian |\n", + "\n" + ], + "text/latex": [ + "A tibble: 5 × 2\n", + "\\begin{tabular}{ll}\n", + " cuisine & .pred\\_class\\\\\n", + " & \\\\\n", + "\\hline\n", + "\t indian & thai \\\\\n", + "\t indian & indian\\\\\n", + "\t indian & indian\\\\\n", + "\t indian & indian\\\\\n", + "\t indian & indian\\\\\n", + "\\end{tabular}\n" + ], "text/html": [ "
A tibble: 5 × 2
\n", "\n", @@ -827,32 +939,32 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 248 + }, + "id": "CqtckvtsKqax", + "outputId": "e57fe557-6a68-4217-fe82-173328c5436d" + } }, { "cell_type": "markdown", - "metadata": { - "id": "8w5N6XsBKss7" - }, "source": [ "Great job! In Tidymodels, evaluating model performance can be done using [yardstick](https://yardstick.tidymodels.org/) - a package used to measure the effectiveness of models using performance metrics. As we did in our logistic regression lesson, let's begin by computing a confusion matrix." - ] + ], + "metadata": { + "id": "8w5N6XsBKss7" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 133 - }, - "id": "YvODvsLkK0iG", - "outputId": "bb69da84-1266-47ad-b174-d43b88ca2988" - }, + "execution_count": 10, "source": [ "# Confusion matrix for categorical data\n", "conf_mat(data = results, truth = cuisine, estimate = .pred_class)\n" ], - "execution_count": 10, "outputs": [ { "output_type": "display_data", @@ -869,27 +981,28 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 133 + }, + "id": "YvODvsLkK0iG", + "outputId": "bb69da84-1266-47ad-b174-d43b88ca2988" + } }, { "cell_type": "markdown", - "metadata": { - "id": "c0HfPL16Lr6U" - }, "source": [ "When dealing with multiple classes, it's generally more intuitive to visualize this as a heat map, like this:" - ] + ], + "metadata": { + "id": "c0HfPL16Lr6U" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 436 - }, - "id": "HsAtwukyLsvt", - "outputId": "3032a224-a2c8-4270-b4f2-7bb620317400" - }, + "execution_count": 11, "source": [ "update_geom_defaults(geom = \"tile\", new = list(color = \"black\", alpha = 0.7))\n", "# Visualize confusion matrix\n", @@ -897,15 +1010,14 @@ " conf_mat(cuisine, .pred_class) %>% \n", " autoplot(type = \"heatmap\")" ], - "execution_count": 11, "outputs": [ { "output_type": "display_data", "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME\nBAQFBQUGBgYHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUW\nFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJyco\nKCgpKSkqKiorKyssLCwtLS0uLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU2NjY3Nzc4ODg5OTk6\nOjo7Ozs8PDw9PT0+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpLS0tM\nTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1e\nXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29w\ncHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGC\ngoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OU\nlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSlpaWm\npqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e4\nuLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnK\nysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc\n3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u\n7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7////i\nsF19AAAACXBIWXMAABJ0AAASdAHeZh94AAAgAElEQVR4nO3deWBU9b3//0+ibApWrbYuvYor\nXaxoaatWvVqpqG2HsCmLBAqoVXBDjCKbKMqOQUDFFVxKqyhVFLUqWKJsxg3Lz2IFGilLiEqp\ntMX0hpzvnJkMCbx5/W5vz5k5Z+D5/OOc85nEz3w8Mw9mMjmo84gocC7qBRDtCQGJKISARBRC\nQCIKISARhRCQiEIISEQhBCSiEAISUQgBiSiEgEQUQkAiCiEgEYUQkIhCCEhEIQQkohACElEI\nAYkohIBEFEJAIgohIBGFEJCIQijHkLb+NUZVRb2Ahn26OeoVNCxWpyZWi/mbeGbnGNJl42PU\nmbNiVM+7nohRlz4ao/o/HqOuFc/sHEMasShGdfwsRt3+1qYYNXJ9jLq9MkZNE89sIMUkIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSbI+EVLQktatJvB8FpNGtv9LoqMteTx7d/f2vND6h5M3oIS07xT0Xxjyh\nQJpx+sGNj79pbfCJgkJ6o7V72t/f4FKdFSmkRa3dnNTBgnYHNPneY7GCVPvB1ggg3ezaTZra\nq+C8RYvGF7a64cbW7rLIIU1sdmR8IE1ynX4957qC9pFDGtvsiDSkywsn+D0eJaRxycWkIC1p\ncdzYSecUzIwTpP+0YJBOONJ/CTqncP6iI49YsGjRwqMOjhrSS03GTY0PpJNaVia3P92nImJI\nc5vcWZqG1LVFoInCgPRCkzF3pyF1bLa8snLdd1pGC+nTOy8uvvdLr+iVEZ2KF/hv7WoTC0f0\n7zvf8zaP79Vl8CrPe+2qzsX3Vu8YZgHS8cf624sKF5RdO84/+plbEDGk8oWfxQjSt7/pb7vu\n80ngmYJBWvTa+jpIPz0ickhLFlSmIa1vVuSPR7lXI4V0w9jN6wdM94qu+fCfj3XZ5v+MVDRw\ni/dKl23eoPFfVD/es3pj+/e3b7xudmaYDUjD3C+fmz+6aee64Zsnfz3QdOF82BAjSFPckOV/\nnrFfv+AzBf6woQ7SWa3Wr18dLaRkaUiL3FB/MMdNjhLS6sTG5KbcK3ra8zYmKlKQ5nrepsQn\nqxKbkz8zdStblVjtedu9zDD5zyxpn+wPIUJadFsz5wp7pz5i+P1vH2i372gg7dT9+yfPz/WV\nwScKC1Lrlh0PdAddvyYOkJ5zd/mDN9ywKCG92b42tS9anHwvl/g4BSl9WJZINbv2ng4ls9Z7\nmWHye9/4cbL3QoR0T/MzRt91SWHqI4bJzh0+KdBsex6kZw/4yYzfXL7PzfGB1LKw20P3F7mL\n4gDpSTfVHyxzN0YJaVH77WlIS+ohpQ+XJjJv4zbNG9mhrH64uwJBeuPwE/0Xo66FTya3L44f\n2ragF5AatPGo7/ovRlcULo0NpLff87dd3ZwYQHrOTfIHZW54lJDWJCo876MXdgNpbWJl8usb\nvZotyd30wZlhFiA97VJwJrjMLL9wDwGpvrfddf7uCXdPbCCle8IFmi8kSEvcLf7gqfQLU1SQ\nvEEjKtddd+9uIHlDS6pqXuzy+at9Pq7dPGRKZpgVSD383Wg3+PkbHkyTugVI9ZW7/v7uEXdX\nbCCtXOlv73fjYgBpQ4uf+4MhrixSSFvu6NJz2rbdQdo8ruslJSu82ll9Ova6+++ZYRYgvdH8\nmDeSuw7usRcLT/WPLnGTgVTfxq+02pjc9Xa/jwukdwsv9AfnFbwRA0iVlzZ5p7Jy7bHfDjTX\nHnGt3UB32qgJFxe2XbSo2H332pLzC77zRsSQ5pWW9nADSkvfiQOkTXe6Hz/wxOWFRcFnCgbp\n2QkTurorJ0xYvL6Paztu1OmuX6DpgkGaO2lSN9d/0qRlle8dfPTQO37QaA6QFo06qWmjlleW\nLVr0Zkmrps2O7fFqoNlCgNQ7fS2ZezAWkDY9+P39Gp8wZH3wiYJB6ll3Vu5dv3ZM6xZNT5kY\naLaAkHrVLWZ6ZeWiC1s0Pe2ZQLPtIZDCjau/ZVz9rQKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2\nIMmApAKSDUgyIKmAZAOSDEgqINmAJAOSCkg2IMmApAKSDUgyIKmAZAOSDEiqmEDqOSJGnXJf\njOpw+z0xqtOUGNU76rPRsMvEMzvHkEa+GqMuHBajznv8tRg1IOoFNGzgKzFqiHhm5xjSvZ/G\nqF/MjFHd3on6zWXD7ox6AQ27oypG3Sue2UCKSUCSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQ\nVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyhQTpraYHhzDLL/7zp/3Y\nY9zg1MFDHQ7Z92sXz0ge3fTt5o2O6j0jWkjLTnHPhTFPGJDmt23e/OTSquAThQFpXcl/NW45\nbFPwiUKEVJN4f6fxpkTFrjdlGVLVmS5aSL0bH1wH6QeFF155puswc+b1BUf37HWi6xQppInN\njowNpJcbtbx90jnuluAzhQEpsc9V0y9xJcEnChFS7Qdbd4W0601ZhjSp8bmRQhrWqPiyNKQS\n1y25/f43Z8z82qEPzJz58GEHRAnppSbjpsYG0o8O+ONnn1V9Z7+NgWcKAdJsd1ty+/Mzg78k\nZfGtXRLSv/29oUD6wwEll0YKadyomXWQftT0ofRND/e4zt+d7R6IEFL5ws/iA2nydH/bx/0p\n8EwhQOrSfF3wSVKF+9auNrFwRP++8z1v9aAuVy9Mv7WrGN6964gN3o4vZQ/SRSeujxZSsjpI\nh540c2aDH4tmnPDV/3TCkD5siA+kdOceGnyOECAdfW5VVWXwaapC/xmpaOAW75Uu22r7lW6r\nGpKGdGXptn+MKfEyX8oepIcK5n0aE0gzCs7t8/WC/S9KvQw9dNfw0/e5BkgNe9jdHnyS4JA2\nFfaadEzBQf0/iR+kuf5buk/+mNjoeUvSkLZ+6XmLO9RmvpT8xgVtkr0dNqQ/HdL307hAut8d\neuxVN15Y0Ma/qcS5Q274jyfcIyH9utlFsfjUrsId9b0Hnrqq8Gfxg7TY8zYnPi5rv93zPklD\nWj6kuLhboibzpeQ3lvdM9mHYkLoeviY2kB50zacndz9xtya3U6+/7LSCBJDqG7dPpw0hTBMc\n0l/cQWuSu8vcK7GDtCSlZX77Ws9bk4K0odPsam+pD2lJBtJuCg7pqYKHKyoquh1csS4GkGY2\n+6a/HeT61N3cPkUKSKmudIM+DWOeEH5GanGmv/2NuyvwTNmBtDxR6XllKUhlRTWe92j2IfVz\ndZ0fB0itDvO317orphQP948Gur5AqmtgQWkIs3wWCqQzjve3j7l7As+UHUjVPUq3rrs5BWll\nYsW/Fg5OVGUb0tsv+LU74IU34wCplytJbs8oHD+14Jv+p3ftUmMgJXvahfWJRQiQxrunk9su\n+7wVeKbsQPI+ur7z1e8k/uzfNKN7jylbB3bblGVI6aL9GWlonz5nu4v69Jkw86GWTdr3+6E7\nf+bMn7nju/c+veC4//QaoTAgzSst7eEGlJYGnyq4gcrjDipN9V7gqUKAtK71foPuLnKXB59p\nz7rWLmJIP657d3nVzJn3tv3KPocVJ/XM6H1046bfuGj6fzpnGJB6163rwcAzBYf0UeYt+GOB\npwrjEqGP+3yt0XFj43WtXZC4+lvF1d8yrv62AUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECy\nAUkFJBmQbEBSAUkGJBuQVECSAckGJBWQZECyAUkFJBmQbEBSAUkGJBuQVECSAcl28S9jVKt2\nMer4blGfjob9KOoFNOxnV8Soi8QzO8eQ7loVo7r/JUYNf/KNGDXkTzFq1PoYNU08s3MMafLa\nGNUz6rcJDbvtmWUxanhFjIrV+8z7xDMbSDEJSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IK\nSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIs/yBt6n1EoUsFpFwHJFn+Qbp4\n37a9+6UCUq4Dkiz/IH312WwBAtL/FpBk+QdpvyogRRWQZPkH6ezXgRRVQJLlH6S3f7gYSBEF\nJFn+QTrzv9x+R6cCUq4Dkiz/IJ3dNhOQch2QZPkHKfsBSQUkWT5C+uyFBx56+Qsg5T4gyfIP\n0vZBjfzLGvYfD6ScByRZ/kEa7zo+/OIL91/gHgVSrgOSLP8gfeuG9P6K7wEp1wFJln+QmsxP\n7+c1A1KuA5Is/yDt/3x6/2xzIOU6IMnyD9JZP672d9vanQukXAckWf5Bmldw1JWjbr/8iMJX\ngZTrgCTLP0jeb7/pf/z93XnZcgQkGZBkeQjJ89a/VV6ZNUZA0gFJlpeQshyQVECS5RmkVqO9\nVjsCUq4DkizPIJ1W6p22IyDlOiDJ8gxSTgKSCkiy/IPU5sP0/ulvASnXAUmWf5BceWr3P7c1\nBlKuA5Is3yC5+rhoNecBSZZvkN6/2xWl/uuQl434C5ByHZBk+QbJ8y74U7YAAel/C0iy/IPk\nbZyS3FTdtglIOQ9IsvyDtPIw/1OGCnfYaiDlOiDJ8g9Sh+Pf8ncfHt8JSLkOSLL8g3ToI+n9\n/S2AlOuAJMs/SM2eSO9/tV9MIc07t3nzk8ZW+Ie/P9k9GT2kkvSvC86OGtJrmV9cjF+2bNoP\nvtL4xMFLo4T0/Dn773/SmDUVFdenV3Vm9JCWneKeC2OefwvSjy6o8Xdf/ODMzC01ifdjBOnZ\nfY8eNuYsd2PycHSzI+IA6ZeFd/n9OmpIbw5JdX7Br5ZNKmx1402nuCsihPTbfY8eOvosN6ii\nom/hWL+ZkUOa2OzIHEJ6ueDYASNH9Dm08OXMLbUfbI0RpNNbvLt2bcW391uz9rdNRk2KA6Tu\nBwSfI10Yb+1eP7TDsmXfOLJs2bJFRx8cIaTTWrxdUbHmW/utqri4RaCJQoP0UpNxU3MIyXul\njf9CfHJc/4bs+Lv9bbFbvrbsd2tjAelnRwafI10YkC458NVliwdO9A9/7sqigzRusr/t6d6r\nuPDweEAqX/hZTiF53mcf/H8N/4vF/lu7iuHdu47Y4FUnXh7cr+9SLzOuTSwc0b/vfM/bPL5X\nl8GrPO+1qzoX31u9Y5gFSOnOPiS1iwWks1tVVa0NPk1VKJCeLCzJHC5tfVigqcL4sOHsQyoq\nzjyxomJlDCAlyzGkXfIhXVm67R9jSpKH1/3Ve7XDlszYKxq4xXulyzZv0Pgvqh/vWb2x/fvb\nN143OzNM/sP/XJfsy7Ah3eeGxQfSKcd0PsgdNOgvsYB0/qFvpPZvzH34gn3HRg3pHje0ouLk\nlkUHuoOu/WhvgrTbvyHrQ9qatLC4Q21N4jnP2971lczYK5rreZsSn6xKbE7+LNWtbFVidfLr\nXmaY/IcXtEn2dsiQZjZrVxEfSMcU9pj5UEf30+AzBYf0ZOGg9MFU5w4vDTZXcEiPNDt/TUVF\ny8JL7r8n4S7YmyDt9m/I+pCWDyku7paoqUksS95w1azM2CtanHxbl/i4LJFqdu09HUpmrfcy\nw+T3rrg52c4XSQSGNGqfotVr4wPp/RX+trubG3im4JC6Nn49ffC7icPPL/hFtJBu36f9x8nd\nknJ/cLF7ai+CtNuSkDZ0ml3tLfUh+f9fzCt+nRl7RUtSkJYmquu+edO8kR3K6oe7Kyikfu7a\nT9bGCFK637hRgecIDGnp13/UYNTXzYgSUl93zZ/rR4+6EUB6v6yoxvMe9SE97XnVnV/LjDOQ\n1iZWJr9xo1ezJbmbPjgzzAqkqwvG7jiOBaTVq/3tQ25i4JkCQ3rE3eLvXip5xN/d5YZGCGlA\nwZj0wYoV/vYeN3ovgrR/g3b8DdkkpJWJFf9aODhRVZMYUFE9q+PfMuMMJG9oSVXNi10+f7XP\nx7Wbh0zJDLMB6VduZP0gDpA+KLzI37UtWBI9pKvdr/zd7wq/tyS56+qmRgfp8cwr0LLCdv7u\n3ILX9yJIXZO1anRG5w6nFLS5ugEkb0b3HlO2Duy2IfHiTZ37lXuZ8aYMpM3jul5SssKrndWn\nY6+7/54ZZgHSmmMPHDvOb8naOePGXeJ+OW7cm9FCqurnzp8w+gx3efCZAkP6uft9at/bnXz9\nze0KTloSGaRVxxw4JnVBw6KK3u680SN/6PoEmS4MSPNKS3u4AaWl7+QAUrLZJ23wdyu/Obch\npB2H74g5/g8FgvR+5oKyB9deWnc0LWJIG8efckDTU0uDTxQc0tmF6f3Swa2aNjuu5+uBJgsE\n6d3M4/RAxeo7Tm7RtPW4QI7CgNQ788zJDaSTnkrv72tdd8P2jxI7PnWLHlLYcfW3jKu/Vf8W\npMavpfezm9TdsLDDqFog5SQgyfIP0hGXpna1XQ8PTgZI/7eAJMs/SLe67147atSAb7nBQMp1\nQJLlH6TacYf7P5EdMrwGSLkOSLL8g5Sk9Mmypau3Z4sRkHRAkuUjpG1vzfnU+x8g5T4gyfIQ\n0sQWzi3xhvwia5SApAKSLP8gPeDaT09CenTf8UDKdUCS5R+kk6/0tiUhebecCKRcByRZ/kFq\n+moa0u8aASnXAUmWf5C+9nwa0lMHACnXAUmWf5B+cs4/fUifn9QOSLkOSLL8g/T6Psdf5/r2\nPqDRm0DKdUCS5R8k77VT/Ssbfvj7bDkCkgxIsjyE5Hmb3ntvc9YYAUkHJFn+QToje/+JVSD9\nLwFJln+QvjEJSFEFJFn+QXruW7/9F5CiCUiy/IN09ndd4yOO9gNSrgOSLP8gnXle27qAlOuA\nJMs/SNkPSCogyfIO0rZlb24BUkQBSZZvkCa3cK5R/y/FNwIpuwFJlmeQnnEtbxh2lrtafCOQ\nshuQZHkG6eyW/v8utm+jvwEpioAkyzNIzYf727dc1i5YBdL/X0CS5Rkkd7+/3eBeFt8JpKwG\nJFm+QXrQ3250LwEpioAkAxKQ/v2AJMs3SLcsSTbPlfo7IOU6IMnyDVLDgJTrgCTLM0i3NgxI\nuQ5IsjyDlJOApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmA\nZAOSCkgyINmApAKSDEg2IKmAJAOSDUgqIMmAZOvQM0Yd/4sYdWq7TjHqB5fGqJ/2iVEXimd2\njiFNWR+jij+PUaOWboxRiWkxanTUj03DYvKKBCQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJ\nBiQVkGRAsgFJBSQZkGxAUgFJBiQbkFRAkgHJBiQVkGRAsgFJBSQZkGxAUgFJBiRbUEhvtHZP\n+/sbXKqzIodUduEBTdr8KoSJAkNa1No9s+tRFJBGHOWuSx1cf3zjxifcsPNtkUEK7XEKBVJN\n4p1oIY1tdkQa0uWFE/wejxrS2y2OmzD53IIngs8UFNK45Kl5ZpejKCB1a3xQGs2V7shLLj1s\n35sa3hYZpPAepz0C0twmd5amIXVtEWii0CB1bvbh559vOumY4DMFhPR8k9GT03zqj6KANKjR\nJT3TaA498K5p0ya0aNXwtsgghfc47RGQFr22vg7ST4+IBaSqZh393Wj3euCpAkJaPH9jHZ/6\noygg3XrLtDSaMe4sf9y2YHz9bZFBCvFxCg1SzbCRNX8d36tzyYfe9sTv+k32No/v1WXwKs+r\nGN6964gNXm1i4Yj+fednBVKyOkhntVq/fnX0kJa54f5urpsaeKrgHzbU84kQUrI0mjvcef6g\nixtYf1tkkEJ8nEKDVFrypTfo1i1fPtz1b17RwFX/9AaN/6L68Z7V3pWl2/4xpsRL3rjFe6XL\ntuS3f74s2d+yAql1y44HuoOuXxMxpBfc3f5uiRsReKo9DdLU/Y7yB23cZTGAFOLjFBakJ/p/\n4a1OrPW86osXeEVPet6qxGbPq+1W5m390vMWd6j1iuZ63qbEJ8lvX9Am2dtZgdSysNtD9xe5\niyKG9Iy7z9+9424KPNWeBmlawv33yNsuaOH6xgBSiI9TSJDGJv7geW+2r00O+v/GKyrzvLJE\nqtne8iHFxd0SNV7RYs/bnPcB240AABDoSURBVPg4+R2rpyRblxVIb7/nb7u6OdFCmucm+7vF\n7tbAU+1xkO4+r8C5b13qrowBpBAfp5Ag9RsxsKYO0lVPeEVLPG9pojr1tQ2dZlcnBzWpG9OQ\ndlNYkNI94UZGC+ltN8zfzUn/gReoPQ7StGljS+5M/ow0LAaQQnycQoJUvrXPI94a/43bts7z\nU2bWJlYmv7LRKyuq8bxHcwVp5Up/e78bFy2kT1sk/N1wtzjwVHsgJL/v7jclBpBCfJxC+7Bh\nRYd3vZKRX2y7r+c/Uma8oSVVNS92+XxlYsW/Fg5OVOUE0ruFF/qD8wreiBbS58VNln/++YZj\nvxN8pj0O0umHTp42bXDhORZX7iGF+DiF93ukx4u3VN3R89Lbkj/8pCBtHtf1kpIVnjeje48p\nWwd225RFSM9OmNDVXTlhwuL1fVzbcaNOd/0CTRcCpD98teXwMT9sNDf4TAEhzZ04sZu7auLE\npQ2OooB0Q48ep7u2PXqMnHZFwQnFHZp/dWzD2yKDFN7jtEdca9czfYWdu3f92jGtWzQ9ZWKg\n2UK51m7ZRS2anvFcCBMFhFRcd2rua3AUBaSz6u69z7Rpfb7RqPlpd+58W1SQwnuc9ghIIcfV\n3zKu/lYByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUk\nG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSRUTSB2LY9SJfWJUm469Y1TLs2NUIurHpmEXimd2\njiFNq4xRvaP+c79ht77zWYwatSlGXV8eo24Xz2wgxSQgyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAk\nA5INSCogyYBkA5IKSDIg2YCkApIMSDYgqYAkA5INSCogyYBkA5IKSDIg2YCkApIMSLagkBa1\ndnNSBwvaHdDke49FCym5mGd2PYoW0pz/PrjJSZM+DT5RcEh/cnXNjBbSgsw6JpSXzzq7eeOT\n7oo1pKIlOw1rEu9nBdK4ZkekIS1pcdzYSecUzIwSkr+YZ3Y5ihbSrMKTx0443Q2OA6R1d6Uq\nKng9WkiLh6Y6v2BW+Zz9j7p56GkFE+MKafnHBlLtB1uzAemFJmPuTkPq2Gx5ZeW677SMENLz\nTUZPTvOpP4oYUsuj13322cbjD40DpHSrDy8OPkkIb+0WHtqxvPyCpi+Vly894RtxhXTbiwaS\nLBikJQsq05DWNyvyx6Pcq9FBWjx/Yx2f+qNoIVXe8YS/6+HWxQbSZQd/FHySECB1PXB++bKm\n5/uHg9wT8YQ0pH2n672iV0Z0Kl7geRXDu3cdsSFrb+0q6yAtckP9wRw3OTpIyer5xAJSuk9P\n+0bwSUKC9Gbh2BBmCQ5pduHN5eVPuwH+8XQ3Ip6QvH7+K9I1H/7zsS7bvCtLt/1jTEkdpPXP\nJKvKBqTn3F3+4A03DEg7tWH5y50bzQw+T0iQOhz+lxBmCQ6p3aGLyssfcMP846fc1XGG9LTn\nbUxUeFu/9LzFHWrTkBa0SfZ2NiA96ab6g2XuRiDt1DPOHfWbEOYJB9KbhXeGMU1gSLMLb0xu\np7nb/MGz7vI4Q1rseZsTH3vLhxQXd0vUZP8VaZI/KHPDgbRTH/1qaseCgcHnCQfS5Y1XhzFN\nYEjdGi9Mbh90Q/3BU+6aOENakoK0odPsam9pBtJuCgnSEneLP3gq/cIEpJ0a5F4NPEcokCqP\n+EkY0wSG9NbXz/R3c1x/f3dP+oUp3pDKimo879HsQ9rQ4uf+YIgrA1J9fxz3O3/3azc5HpBe\ncpPCmCYwpBnpl6Jl+5/n7wa4p2IKqf/Df89AWplY8a+FgxNV2YZUeWmTdyor1x777UBz7WmQ\nPio8syq5+6V7Jh6Qhrvgv4z1CwrpGjcrte/Q+Pny8kX/dUKgybIIaW7nPhlI3ozuPaZsHdht\nQ3YgzZ00qZvrP2nSssr3Dj566B0/aDQnQkhzJ07s5q6aOHFpg6NoIX12nfvhqImdCr5fFQ9I\n3d2aMKYJDCnhFqb28w48csCgk/edHldI/5eCQepVd9nU9MrKRRe2aHraM4FmCwipuG4x9zU4\nihjSp5NObrb/t66uCD5TKJAuKAxjluCQ/ruw7uDpc/Zvcup9wSbbIyCFHFd/y7j6WwUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5BkQFIByQYkGZBUQLIBSQYkFZBsQJIBSQUkG5Bk\nQFIByQYkGZBUQLIBSQYkVUwgzXg8Rg2MegENGzY16hU07NqoF9CwWD1O08QzO8eQiPbMgEQU\nQkAiCiEgEYUQkIhCCEhEIQQkohACElEIAYkohIBEFEJAIgohIBGFEJCIQghIRCGUl5CmTY56\nBQ2ad+emqJdQ34d3Lo16CfV9eeesqJfQoBl3ZnX6vISUaBf1Chp0R5uPo15Cfa+2eTzqJdS3\ntc3VUS+hQb2/n9XpgRQ0IKmAFPeApAKSDEg2IKmAJAMSUfwDElEIAYkohPIDUtGS1K4m8X7E\nCzFL2JSoyPmqYnAaTDWJd6Jegq7u6ZMpK+cvryDVfrA14oWYJSQh5XxVMTgNpthCWv6xgZSV\n85dXkGJYElLUS4hFsYV024u5efrEHNKnd15cfO+XXtErIzoVL/Bfk2sTC0f07zvf8zaP79Vl\n8CrPe+2qzsX3Vu8YZruGS1g9qMvVC9Nv7SqGd+86YoO340vZXkPmDqsTLw/u13epZxaQ69Pj\nQ6oZNrLmr+N7dS750Nue+F2/yTvuNadnZ+eGtO90febpk1nH3vjW7oaxm9cPmO4VXfPhPx/r\nss0/A0UDt3ivdNnmDRr/RfXjPas3tn9/+8brZmeGWV9QgyXU9ivdVjUkDenK0m3/GFPi7Vhd\n1tdQd4c1iev+6r3aYYtZQK5Pjw+ptORLb9CtW758uOvfkutY9c8d95rTs7NL/fxXpPTTp/6k\n7XWQVic2JjflXtHTnrcx/ZQtmuu/n/pkVWJz8s1ut7JVidWet93LDLO+ogZL+KO/uCXpVW39\n0vMWd6jNfCn7a6i7w5rEc8l//a6v7LqAnJ+eJKQn+n+RfMDWel71xQu8oie9+nvN6dnZpRSk\n9NOn/qTtdZDebF+b2hctTr5ZSXycehanD8sSqWbX3tOhZNZ6LzPM+ooaLqH9ds/7JA1p+ZDi\n4m6JmsyXsr+GujusSSxL3nDVrF0XkPPTU5MYm/hD5gHr/xuvKIl2x73m9OzsUgpS3f3uOGl7\nHaRF/nPVS/+0mIGUPlyayLxP2TRvZIey+mGWa7CE+f6TZk0K0oZOs6u9pf5TZUluIGXusCaR\nfI54V/x61wXk/PTUJPqNGFhTB+mqJ1LryNxrbs/OLvV7ccfTp/6k7XWQ1vifiX30wm4grU2s\nTH59o1ezJbmbPjgzzHoNlrA8Uen/qetDKiuq8bxHcwgpc4c1ieS7lurOr+26gJyfnppE+dY+\njyQfsOQbt22d56fWkbnX3J6dXWoAqf6k7XWQvEEjKtddd+9uIHlDS6pqXuzy+at9Pq7dPGRK\nZpj1BTVYQnWP0q3rbk5BWplY8a+FgxNVOYOUucOaxICK6lkd/2YWkOvT43/YsKLDu17JyC+2\n3dfzH+lPnOvuNbdnZ5f6P/z3zP3Wn7S9D9KWO7r0nLZtd5A2j+t6SckKr3ZWn4697v57Zpj1\nGi7ho+s7X/1O4s/+TTO695iydWC3TbmClLnDDYkXb+rcr9wzC8j16Un9Hunx4i1Vd/S89LZ1\ndb+6ydxrTs/OLs3t3GfHA7bjpO19kGg3NfgTNba/B93rAlLetf0j/zPtdECKS0DKuxZ2GFWb\nOQZSXAISUQgBiSiEgEQUQkAiCiEgEYUQkPK3X7pMp+32622Pzu169uqAlL+9PnXq1Gtd5+TW\nXNb9nv+4AimHASm/e92V7u7mKUDKcUDK7+ognXn28984w2vd2j8u+qp3QfLtXhuv7XFrLmze\n/JLsX8lLQMr36iCdd/I373mhHtKfilz5h17blq1HP3tjwS+iXeFeEpDyuzpIbd2c5HYHJK+f\n23Hjj74W4fL2noCU32UgNf6XZyE19a/J61UY4fL2noCU32UgHeFvd4V0tD/sx0OcizjL+V0G\n0tH+FkjRxVnO73aCdOpJ/vY0IEUQZzm/2wnSeYckfyja1CwJ6TL3P0DKaZzl/G4nSJPdmMp3\nf/ydJKQR7rangZTLOMv53U6Qqm84sknr5we08Ly/nNqoFZByGWeZKISARBRCQCIKISARhRCQ\niEIISEQhBCSiEAISUQgBiSiEgEQUQkAiCiEgEYXQ/wMhANIDIZLX1QAAAABJRU5ErkJggg==", "text/plain": [ "plot without title" - ] + ], + "image/png": "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" }, "metadata": { "image/png": { @@ -914,35 +1026,35 @@ } } } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 436 + }, + "id": "HsAtwukyLsvt", + "outputId": "3032a224-a2c8-4270-b4f2-7bb620317400" + } }, { "cell_type": "markdown", - "metadata": { - "id": "oOJC87dkLwPr" - }, "source": [ "The darker squares in the confusion matrix plot indicate high numbers of cases, and you can hopefully see a diagonal line of darker squares indicating cases where the predicted and actual label are the same.\n", "\n", "Let's now calculate summary statistics for the confusion matrix." - ] + ], + "metadata": { + "id": "oOJC87dkLwPr" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 494 - }, - "id": "OYqetUyzL5Wz", - "outputId": "6a84d65e-113d-4281-dfc1-16e8b70f37e6" - }, + "execution_count": 12, "source": [ "# Summary stats for confusion matrix\n", "conf_mat(data = results, truth = cuisine, estimate = .pred_class) %>% \n", "summary()" ], - "execution_count": 12, "outputs": [ { "output_type": "display_data", @@ -963,8 +1075,48 @@ "12 recall macro 0.7780927\n", "13 f_meas macro 0.7641862" ], - "text/latex": "A tibble: 13 × 3\n\\begin{tabular}{lll}\n .metric & .estimator & .estimate\\\\\n & & \\\\\n\\hline\n\t accuracy & multiclass & 0.7880435\\\\\n\t kap & multiclass & 0.7276583\\\\\n\t sens & macro & 0.7780927\\\\\n\t spec & macro & 0.9477598\\\\\n\t ppv & macro & 0.7585583\\\\\n\t npv & macro & 0.9460080\\\\\n\t mcc & multiclass & 0.7292724\\\\\n\t j\\_index & macro & 0.7258524\\\\\n\t bal\\_accuracy & macro & 0.8629262\\\\\n\t detection\\_prevalence & macro & 0.2000000\\\\\n\t precision & macro & 0.7585583\\\\\n\t recall & macro & 0.7780927\\\\\n\t f\\_meas & macro & 0.7641862\\\\\n\\end{tabular}\n", - "text/markdown": "\nA tibble: 13 × 3\n\n| .metric <chr> | .estimator <chr> | .estimate <dbl> |\n|---|---|---|\n| accuracy | multiclass | 0.7880435 |\n| kap | multiclass | 0.7276583 |\n| sens | macro | 0.7780927 |\n| spec | macro | 0.9477598 |\n| ppv | macro | 0.7585583 |\n| npv | macro | 0.9460080 |\n| mcc | multiclass | 0.7292724 |\n| j_index | macro | 0.7258524 |\n| bal_accuracy | macro | 0.8629262 |\n| detection_prevalence | macro | 0.2000000 |\n| precision | macro | 0.7585583 |\n| recall | macro | 0.7780927 |\n| f_meas | macro | 0.7641862 |\n\n", + "text/markdown": [ + "\n", + "A tibble: 13 × 3\n", + "\n", + "| .metric <chr> | .estimator <chr> | .estimate <dbl> |\n", + "|---|---|---|\n", + "| accuracy | multiclass | 0.7880435 |\n", + "| kap | multiclass | 0.7276583 |\n", + "| sens | macro | 0.7780927 |\n", + "| spec | macro | 0.9477598 |\n", + "| ppv | macro | 0.7585583 |\n", + "| npv | macro | 0.9460080 |\n", + "| mcc | multiclass | 0.7292724 |\n", + "| j_index | macro | 0.7258524 |\n", + "| bal_accuracy | macro | 0.8629262 |\n", + "| detection_prevalence | macro | 0.2000000 |\n", + "| precision | macro | 0.7585583 |\n", + "| recall | macro | 0.7780927 |\n", + "| f_meas | macro | 0.7641862 |\n", + "\n" + ], + "text/latex": [ + "A tibble: 13 × 3\n", + "\\begin{tabular}{lll}\n", + " .metric & .estimator & .estimate\\\\\n", + " & & \\\\\n", + "\\hline\n", + "\t accuracy & multiclass & 0.7880435\\\\\n", + "\t kap & multiclass & 0.7276583\\\\\n", + "\t sens & macro & 0.7780927\\\\\n", + "\t spec & macro & 0.9477598\\\\\n", + "\t ppv & macro & 0.7585583\\\\\n", + "\t npv & macro & 0.9460080\\\\\n", + "\t mcc & multiclass & 0.7292724\\\\\n", + "\t j\\_index & macro & 0.7258524\\\\\n", + "\t bal\\_accuracy & macro & 0.8629262\\\\\n", + "\t detection\\_prevalence & macro & 0.2000000\\\\\n", + "\t precision & macro & 0.7585583\\\\\n", + "\t recall & macro & 0.7780927\\\\\n", + "\t f\\_meas & macro & 0.7641862\\\\\n", + "\\end{tabular}\n" + ], "text/html": [ "
A tibble: 5 × 2
\n", "\n", @@ -992,13 +1144,18 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 494 + }, + "id": "OYqetUyzL5Wz", + "outputId": "6a84d65e-113d-4281-dfc1-16e8b70f37e6" + } }, { "cell_type": "markdown", - "metadata": { - "id": "43t7vz8vMJtW" - }, "source": [ "If we narrow down to some metrics such as accuracy, sensitivity, ppv, we are not badly off for a start 🥳!\n", "\n", @@ -1009,18 +1166,14 @@ "Well, Statistical machine learning algorithms, like logistic regression, are based on `probability`; so what actually gets predicted by a classifier is a probability distribution over a set of possible outcomes. The class with the highest probability is then chosen as the most likely outcome for the given observations.\n", "\n", "Let's see this in action by making both hard class predictions and probabilities." - ] + ], + "metadata": { + "id": "43t7vz8vMJtW" + } }, { "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 248 - }, - "id": "xdKNs-ZPMTJL", - "outputId": "68f6ac5a-725a-4eff-9ea6-481fef00e008" - }, + "execution_count": 13, "source": [ "# Make hard class prediction and probabilities\n", "results_prob <- cuisines_test %>%\n", @@ -1032,7 +1185,6 @@ "results_prob %>% \n", " slice_head(n = 5)" ], - "execution_count": 13, "outputs": [ { "output_type": "display_data", @@ -1051,8 +1203,32 @@ "4 3.863391e-03\n", "5 5.653283e-03" ], - "text/latex": "A tibble: 5 × 7\n\\begin{tabular}{lllllll}\n cuisine & .pred\\_class & .pred\\_chinese & .pred\\_indian & .pred\\_japanese & .pred\\_korean & .pred\\_thai\\\\\n & & & & & & \\\\\n\\hline\n\t indian & thai & 1.551259e-03 & 0.4587877 & 5.988039e-04 & 2.428503e-04 & 5.388194e-01\\\\\n\t indian & indian & 2.637133e-05 & 0.9999488 & 6.648651e-07 & 2.259993e-05 & 1.577948e-06\\\\\n\t indian & indian & 1.049433e-03 & 0.9909982 & 1.060937e-03 & 1.644947e-05 & 6.874989e-03\\\\\n\t indian & indian & 6.237482e-02 & 0.4763035 & 9.136702e-02 & 3.660913e-01 & 3.863391e-03\\\\\n\t indian & indian & 1.431745e-02 & 0.9418551 & 2.945239e-02 & 8.721782e-03 & 5.653283e-03\\\\\n\\end{tabular}\n", - "text/markdown": "\nA tibble: 5 × 7\n\n| cuisine <fct> | .pred_class <fct> | .pred_chinese <dbl> | .pred_indian <dbl> | .pred_japanese <dbl> | .pred_korean <dbl> | .pred_thai <dbl> |\n|---|---|---|---|---|---|---|\n| indian | thai | 1.551259e-03 | 0.4587877 | 5.988039e-04 | 2.428503e-04 | 5.388194e-01 |\n| indian | indian | 2.637133e-05 | 0.9999488 | 6.648651e-07 | 2.259993e-05 | 1.577948e-06 |\n| indian | indian | 1.049433e-03 | 0.9909982 | 1.060937e-03 | 1.644947e-05 | 6.874989e-03 |\n| indian | indian | 6.237482e-02 | 0.4763035 | 9.136702e-02 | 3.660913e-01 | 3.863391e-03 |\n| indian | indian | 1.431745e-02 | 0.9418551 | 2.945239e-02 | 8.721782e-03 | 5.653283e-03 |\n\n", + "text/markdown": [ + "\n", + "A tibble: 5 × 7\n", + "\n", + "| cuisine <fct> | .pred_class <fct> | .pred_chinese <dbl> | .pred_indian <dbl> | .pred_japanese <dbl> | .pred_korean <dbl> | .pred_thai <dbl> |\n", + "|---|---|---|---|---|---|---|\n", + "| indian | thai | 1.551259e-03 | 0.4587877 | 5.988039e-04 | 2.428503e-04 | 5.388194e-01 |\n", + "| indian | indian | 2.637133e-05 | 0.9999488 | 6.648651e-07 | 2.259993e-05 | 1.577948e-06 |\n", + "| indian | indian | 1.049433e-03 | 0.9909982 | 1.060937e-03 | 1.644947e-05 | 6.874989e-03 |\n", + "| indian | indian | 6.237482e-02 | 0.4763035 | 9.136702e-02 | 3.660913e-01 | 3.863391e-03 |\n", + "| indian | indian | 1.431745e-02 | 0.9418551 | 2.945239e-02 | 8.721782e-03 | 5.653283e-03 |\n", + "\n" + ], + "text/latex": [ + "A tibble: 5 × 7\n", + "\\begin{tabular}{lllllll}\n", + " cuisine & .pred\\_class & .pred\\_chinese & .pred\\_indian & .pred\\_japanese & .pred\\_korean & .pred\\_thai\\\\\n", + " & & & & & & \\\\\n", + "\\hline\n", + "\t indian & thai & 1.551259e-03 & 0.4587877 & 5.988039e-04 & 2.428503e-04 & 5.388194e-01\\\\\n", + "\t indian & indian & 2.637133e-05 & 0.9999488 & 6.648651e-07 & 2.259993e-05 & 1.577948e-06\\\\\n", + "\t indian & indian & 1.049433e-03 & 0.9909982 & 1.060937e-03 & 1.644947e-05 & 6.874989e-03\\\\\n", + "\t indian & indian & 6.237482e-02 & 0.4763035 & 9.136702e-02 & 3.660913e-01 & 3.863391e-03\\\\\n", + "\t indian & indian & 1.431745e-02 & 0.9418551 & 2.945239e-02 & 8.721782e-03 & 5.653283e-03\\\\\n", + "\\end{tabular}\n" + ], "text/html": [ "
A tibble: 13 × 3
\n", "\n", @@ -1072,13 +1248,18 @@ }, "metadata": {} } - ] + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 248 + }, + "id": "xdKNs-ZPMTJL", + "outputId": "68f6ac5a-725a-4eff-9ea6-481fef00e008" + } }, { "cell_type": "markdown", - "metadata": { - "id": "2tWVHMeLMYdM" - }, "source": [ "Much better!\n", "\n", @@ -1102,7 +1283,10 @@ "Happy Learning,\n", "\n", "[Eric](https://twitter.com/ericntay), Gold Microsoft Learn Student Ambassador.\n" - ] + ], + "metadata": { + "id": "2tWVHMeLMYdM" + } } ] } \ No newline at end of file diff --git a/4-Classification/2-Classifiers-1/solution/lesson_11.Rmd b/4-Classification/2-Classifiers-1/solution/R/lesson_11.Rmd similarity index 99% rename from 4-Classification/2-Classifiers-1/solution/lesson_11.Rmd rename to 4-Classification/2-Classifiers-1/solution/R/lesson_11.Rmd index f7dab06ac..a4221217b 100644 --- a/4-Classification/2-Classifiers-1/solution/lesson_11.Rmd +++ b/4-Classification/2-Classifiers-1/solution/R/lesson_11.Rmd @@ -154,7 +154,7 @@ Now we are ready to train a model 👩‍💻👨‍💻! ## 3. Choosing your classifier -![Artwork by \@allison_horst](../images/parsnip.jpg){width="600"} +![Artwork by \@allison_horst](../../images/parsnip.jpg){width="600"} Now we have to decide which algorithm to use for the job 🤔. @@ -198,7 +198,7 @@ Also the choice of classifier depends on our problem. For instance, when the out A better way than wildly guessing, however, is to follow the ideas on this downloadable [ML Cheat sheet](https://docs.microsoft.com/azure/machine-learning/algorithm-cheat-sheet?WT.mc_id=academic-15963-cxa). Here, we discover that, for our multiclass problem, we have some choices: -![A section of Microsoft's Algorithm Cheat Sheet, detailing multiclass classification options](../images/cheatsheet.png){width="500"} +![A section of Microsoft's Algorithm Cheat Sheet, detailing multiclass classification options](../../images/cheatsheet.png){width="500"} ### **Reasoning** From db6ba0675559c716c658e28f7c4b4966702a4eb3 Mon Sep 17 00:00:00 2001 From: R-icntay <63848664+R-icntay@users.noreply.github.com> Date: Mon, 23 Aug 2021 19:06:30 +0300 Subject: [PATCH 4/5] Explain what tibble is --- .../solution/R/lesson_10-R.ipynb | 90 ++++++++++--------- .../1-Introduction/solution/R/lesson_10.Rmd | 8 +- 2 files changed, 51 insertions(+), 47 deletions(-) diff --git a/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb b/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb index 251bbe082..87c33b5ea 100644 --- a/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb +++ b/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb @@ -163,12 +163,12 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Basic information about the data\n", - "df %>%\n", - " introduce()\n", - "\n", - "# Visualize basic information above\n", - "df %>% \n", + "# Basic information about the data\r\n", + "df %>%\r\n", + " introduce()\r\n", + "\r\n", + "# Visualize basic information above\r\n", + "df %>% \r\n", " plot_intro(ggtheme = theme_light())" ], "outputs": [], @@ -193,17 +193,17 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Count observations per cuisine\n", - "df %>% \n", - " count(cuisine) %>% \n", - " arrange(n)\n", - "\n", - "# Plot the distribution\n", - "theme_set(theme_light())\n", - "df %>% \n", - " count(cuisine) %>% \n", - " ggplot(mapping = aes(x = n, y = reorder(cuisine, -n))) +\n", - " geom_col(fill = \"midnightblue\", alpha = 0.7) +\n", + "# Count observations per cuisine\r\n", + "df %>% \r\n", + " count(cuisine) %>% \r\n", + " arrange(n)\r\n", + "\r\n", + "# Plot the distribution\r\n", + "theme_set(theme_light())\r\n", + "df %>% \r\n", + " count(cuisine) %>% \r\n", + " ggplot(mapping = aes(x = n, y = reorder(cuisine, -n))) +\r\n", + " geom_col(fill = \"midnightblue\", alpha = 0.7) +\r\n", " ylab(\"cuisine\")" ], "outputs": [], @@ -214,15 +214,17 @@ { "cell_type": "markdown", "source": [ - "There are a finite number of cuisines, but the distribution of data is uneven. You can fix that! Before doing so, explore a little more.\n", - "\n", - "Next, let's assign each cuisine into its individual table and find out how much data is available (rows, columns) per cuisine.\n", - "\n", - "

\n", - " \n", - "

Artwork by @allison_horst
\n", - "\n" + "There are a finite number of cuisines, but the distribution of data is uneven. You can fix that! Before doing so, explore a little more.\r\n", + "\r\n", + "Next, let's assign each cuisine into its individual tibble and find out how much data is available (rows, columns) per cuisine.\r\n", + "\r\n", + "> A tibble is a modern reimagining of the data frame, keeping what time has proven to be effective, and throwing out what is not.\r\n", + "\r\n", + "

\r\n", + " \r\n", + "

Artwork by @allison_horst
\r\n", + "\r\n" ], "metadata": { "id": "vVvyDb1kG2in" @@ -232,24 +234,24 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Create individual tables for the cuisines\n", - "thai_df <- df %>% \n", - " filter(cuisine == \"thai\")\n", - "japanese_df <- df %>% \n", - " filter(cuisine == \"japanese\")\n", - "chinese_df <- df %>% \n", - " filter(cuisine == \"chinese\")\n", - "indian_df <- df %>% \n", - " filter(cuisine == \"indian\")\n", - "korean_df <- df %>% \n", - " filter(cuisine == \"korean\")\n", - "\n", - "\n", - "# Find out how much data is avilable per cuisine\n", - "cat(\" thai df:\", dim(thai_df), \"\\n\",\n", - " \"japanese df:\", dim(japanese_df), \"\\n\",\n", - " \"chinese_df:\", dim(chinese_df), \"\\n\",\n", - " \"indian_df:\", dim(indian_df), \"\\n\",\n", + "# Create individual tibble for the cuisines\r\n", + "thai_df <- df %>% \r\n", + " filter(cuisine == \"thai\")\r\n", + "japanese_df <- df %>% \r\n", + " filter(cuisine == \"japanese\")\r\n", + "chinese_df <- df %>% \r\n", + " filter(cuisine == \"chinese\")\r\n", + "indian_df <- df %>% \r\n", + " filter(cuisine == \"indian\")\r\n", + "korean_df <- df %>% \r\n", + " filter(cuisine == \"korean\")\r\n", + "\r\n", + "\r\n", + "# Find out how much data is avilable per cuisine\r\n", + "cat(\" thai df:\", dim(thai_df), \"\\n\",\r\n", + " \"japanese df:\", dim(japanese_df), \"\\n\",\r\n", + " \"chinese_df:\", dim(chinese_df), \"\\n\",\r\n", + " \"indian_df:\", dim(indian_df), \"\\n\",\r\n", " \"korean_df:\", dim(korean_df))" ], "outputs": [], diff --git a/4-Classification/1-Introduction/solution/R/lesson_10.Rmd b/4-Classification/1-Introduction/solution/R/lesson_10.Rmd index 783543d1e..b979d56fe 100644 --- a/4-Classification/1-Introduction/solution/R/lesson_10.Rmd +++ b/4-Classification/1-Introduction/solution/R/lesson_10.Rmd @@ -34,7 +34,7 @@ Classification is one of the fundamental activities of the machine learning rese To state the process in a more scientific way, your classification method creates a predictive model that enables you to map the relationship between input variables to output variables. -![Binary vs. multiclass problems for classification algorithms to handle. Infographic by Jen Looper](../images/binary-multiclass.png) +![Binary vs. multiclass problems for classification algorithms to handle. Infographic by Jen Looper](../../images/binary-multiclass.png){width="500"} Before starting the process of cleaning our data, visualizing it, and prepping it for our ML tasks, let's learn a bit about the various ways machine learning can be leveraged to classify data. @@ -127,7 +127,9 @@ There are a finite number of cuisines, but the distribution of data is uneven. Y 2. Next, let's assign each cuisine into it's individual tibble and find out how much data is available (rows, columns) per cuisine. -![Artwork by \@allison_horst](../images/dplyr_filter.jpg) +> A tibble, or tbl_df, is a modern reimagining of the data.frame, keeping what time has proven to be effective, and throwing out what is not. + +![Artwork by \@allison_horst](../../images/dplyr_filter.jpg) ```{r cuisine_df} # Create individual tibbles for the cuisines @@ -297,7 +299,7 @@ df_select %>% ## Preprocessing data using recipes 👩‍🍳👨‍🍳 - Dealing with imbalanced data ⚖️ -![Artwork by \@allison_horst](../images/recipes.png) +![Artwork by \@allison_horst](../../images/recipes.png) Given that this lesson is about cuisines, we have to put `recipes` into context . From 76eca32cdb68ece9f54fa3ed2895ba24145fa2ea Mon Sep 17 00:00:00 2001 From: R-icntay <63848664+R-icntay@users.noreply.github.com> Date: Mon, 23 Aug 2021 19:19:34 +0300 Subject: [PATCH 5/5] Update lesson_10-R.ipynb --- .../solution/R/lesson_10-R.ipynb | 260 +++++++++--------- 1 file changed, 130 insertions(+), 130 deletions(-) diff --git a/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb b/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb index 87c33b5ea..4592429f9 100644 --- a/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb +++ b/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb @@ -103,8 +103,8 @@ "cell_type": "code", "execution_count": null, "source": [ - "suppressWarnings(if (!require(\"pacman\"))install.packages(\"pacman\"))\n", - "\n", + "suppressWarnings(if (!require(\"pacman\"))install.packages(\"pacman\"))\r\n", + "\r\n", "pacman::p_load(tidyverse, tidymodels, DataExplorer, themis, here)" ], "outputs": [], @@ -138,12 +138,12 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Import data\n", - "df <- read_csv(file = \"https://raw.githubusercontent.com/microsoft/ML-For-Beginners/main/4-Classification/data/cuisines.csv\")\n", - "\n", - "# View the first 5 rows\n", - "df %>% \n", - " slice_head(n = 5)\n" + "# Import data\r\n", + "df <- read_csv(file = \"https://raw.githubusercontent.com/microsoft/ML-For-Beginners/main/4-Classification/data/cuisines.csv\")\r\n", + "\r\n", + "# View the first 5 rows\r\n", + "df %>% \r\n", + " slice_head(n = 5)\r\n" ], "outputs": [], "metadata": { @@ -218,7 +218,7 @@ "\r\n", "Next, let's assign each cuisine into its individual tibble and find out how much data is available (rows, columns) per cuisine.\r\n", "\r\n", - "> A tibble is a modern reimagining of the data frame, keeping what time has proven to be effective, and throwing out what is not.\r\n", + "> A [tibble](https://tibble.tidyverse.org/) is a modern data frame.\r\n", "\r\n", "

\r\n", " % select(-1) %>% \n", - " # Transpose data to a long format\n", - " pivot_longer(!cuisine, names_to = \"ingredients\", values_to = \"count\") %>% \n", - " # Find the top most ingredients for a particular cuisine\n", - " group_by(ingredients) %>% \n", - " summarise(n_instances = sum(count)) %>% \n", - " filter(n_instances != 0) %>% \n", - " # Arrange by descending order\n", - " arrange(desc(n_instances)) %>% \n", - " mutate(ingredients = factor(ingredients) %>% fct_inorder())\n", - " \n", - " \n", - " return(ingredient_df)\n", + "# Creates a functions that returns the top ingredients by class\r\n", + "\r\n", + "create_ingredient <- function(df){\r\n", + " \r\n", + " # Drop the id column which is the first colum\r\n", + " ingredient_df = df %>% select(-1) %>% \r\n", + " # Transpose data to a long format\r\n", + " pivot_longer(!cuisine, names_to = \"ingredients\", values_to = \"count\") %>% \r\n", + " # Find the top most ingredients for a particular cuisine\r\n", + " group_by(ingredients) %>% \r\n", + " summarise(n_instances = sum(count)) %>% \r\n", + " filter(n_instances != 0) %>% \r\n", + " # Arrange by descending order\r\n", + " arrange(desc(n_instances)) %>% \r\n", + " mutate(ingredients = factor(ingredients) %>% fct_inorder())\r\n", + " \r\n", + " \r\n", + " return(ingredient_df)\r\n", "} # End of function" ], "outputs": [], @@ -343,10 +343,10 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Call create_ingredient and display popular ingredients\n", - "thai_ingredient_df <- create_ingredient(df = thai_df)\n", - "\n", - "thai_ingredient_df %>% \n", + "# Call create_ingredient and display popular ingredients\r\n", + "thai_ingredient_df <- create_ingredient(df = thai_df)\r\n", + "\r\n", + "thai_ingredient_df %>% \r\n", " slice_head(n = 10)" ], "outputs": [], @@ -367,11 +367,11 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Make a bar chart for popular thai cuisines\n", - "thai_ingredient_df %>% \n", - " slice_head(n = 10) %>% \n", - " ggplot(aes(x = n_instances, y = ingredients)) +\n", - " geom_bar(stat = \"identity\", width = 0.5, fill = \"steelblue\") +\n", + "# Make a bar chart for popular thai cuisines\r\n", + "thai_ingredient_df %>% \r\n", + " slice_head(n = 10) %>% \r\n", + " ggplot(aes(x = n_instances, y = ingredients)) +\r\n", + " geom_bar(stat = \"identity\", width = 0.5, fill = \"steelblue\") +\r\n", " xlab(\"\") + ylab(\"\")" ], "outputs": [], @@ -392,12 +392,12 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Get popular ingredients for Japanese cuisines and make bar chart\n", - "create_ingredient(df = japanese_df) %>% \n", - " slice_head(n = 10) %>%\n", - " ggplot(aes(x = n_instances, y = ingredients)) +\n", - " geom_bar(stat = \"identity\", width = 0.5, fill = \"darkorange\", alpha = 0.8) +\n", - " xlab(\"\") + ylab(\"\")\n" + "# Get popular ingredients for Japanese cuisines and make bar chart\r\n", + "create_ingredient(df = japanese_df) %>% \r\n", + " slice_head(n = 10) %>%\r\n", + " ggplot(aes(x = n_instances, y = ingredients)) +\r\n", + " geom_bar(stat = \"identity\", width = 0.5, fill = \"darkorange\", alpha = 0.8) +\r\n", + " xlab(\"\") + ylab(\"\")\r\n" ], "outputs": [], "metadata": { @@ -417,11 +417,11 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Get popular ingredients for Chinese cuisines and make bar chart\n", - "create_ingredient(df = chinese_df) %>% \n", - " slice_head(n = 10) %>%\n", - " ggplot(aes(x = n_instances, y = ingredients)) +\n", - " geom_bar(stat = \"identity\", width = 0.5, fill = \"cyan4\", alpha = 0.8) +\n", + "# Get popular ingredients for Chinese cuisines and make bar chart\r\n", + "create_ingredient(df = chinese_df) %>% \r\n", + " slice_head(n = 10) %>%\r\n", + " ggplot(aes(x = n_instances, y = ingredients)) +\r\n", + " geom_bar(stat = \"identity\", width = 0.5, fill = \"cyan4\", alpha = 0.8) +\r\n", " xlab(\"\") + ylab(\"\")" ], "outputs": [], @@ -442,11 +442,11 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Get popular ingredients for Indian cuisines and make bar chart\n", - "create_ingredient(df = indian_df) %>% \n", - " slice_head(n = 10) %>%\n", - " ggplot(aes(x = n_instances, y = ingredients)) +\n", - " geom_bar(stat = \"identity\", width = 0.5, fill = \"#041E42FF\", alpha = 0.8) +\n", + "# Get popular ingredients for Indian cuisines and make bar chart\r\n", + "create_ingredient(df = indian_df) %>% \r\n", + " slice_head(n = 10) %>%\r\n", + " ggplot(aes(x = n_instances, y = ingredients)) +\r\n", + " geom_bar(stat = \"identity\", width = 0.5, fill = \"#041E42FF\", alpha = 0.8) +\r\n", " xlab(\"\") + ylab(\"\")" ], "outputs": [], @@ -467,11 +467,11 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Get popular ingredients for Korean cuisines and make bar chart\n", - "create_ingredient(df = korean_df) %>% \n", - " slice_head(n = 10) %>%\n", - " ggplot(aes(x = n_instances, y = ingredients)) +\n", - " geom_bar(stat = \"identity\", width = 0.5, fill = \"#852419FF\", alpha = 0.8) +\n", + "# Get popular ingredients for Korean cuisines and make bar chart\r\n", + "create_ingredient(df = korean_df) %>% \r\n", + " slice_head(n = 10) %>%\r\n", + " ggplot(aes(x = n_instances, y = ingredients)) +\r\n", + " geom_bar(stat = \"identity\", width = 0.5, fill = \"#852419FF\", alpha = 0.8) +\r\n", " xlab(\"\") + ylab(\"\")" ], "outputs": [], @@ -494,12 +494,12 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Drop id column, rice, garlic and ginger from our original data set\n", - "df_select <- df %>% \n", - " select(-c(1, rice, garlic, ginger))\n", - "\n", - "# Display new data set\n", - "df_select %>% \n", + "# Drop id column, rice, garlic and ginger from our original data set\r\n", + "df_select <- df %>% \r\n", + " select(-c(1, rice, garlic, ginger))\r\n", + "\r\n", + "# Display new data set\r\n", + "df_select %>% \r\n", " slice_head(n = 5)" ], "outputs": [], @@ -510,16 +510,16 @@ { "cell_type": "markdown", "source": [ - "## Preprocessing data using recipes 👩‍🍳👨‍🍳 - Dealing with imbalanced data ⚖️\n", - "\n", - "

\n", - " \n", - "

Artwork by @allison_horst
\n", - "\n", - "Given that this lesson is about cuisines, we have to put `recipes` into context .\n", - "\n", - "Tidymodels provides yet another neat package: `recipes`- a package for preprocessing data.\n" + "## Preprocessing data using recipes 👩‍🍳👨‍🍳 - Dealing with imbalanced data ⚖️\r\n", + "\r\n", + "

\r\n", + " \r\n", + "

Artwork by @allison_horst
\r\n", + "\r\n", + "Given that this lesson is about cuisines, we have to put `recipes` into context .\r\n", + "\r\n", + "Tidymodels provides yet another neat package: `recipes`- a package for preprocessing data.\r\n" ], "metadata": { "id": "kkFd-JxdIaL6" @@ -538,11 +538,11 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Distribution of cuisines\n", - "old_label_count <- df_select %>% \n", - " count(cuisine) %>% \n", - " arrange(desc(n))\n", - "\n", + "# Distribution of cuisines\r\n", + "old_label_count <- df_select %>% \r\n", + " count(cuisine) %>% \r\n", + " arrange(desc(n))\r\n", + "\r\n", "old_label_count" ], "outputs": [], @@ -572,13 +572,13 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Load themis package for dealing with imbalanced data\n", - "library(themis)\n", - "\n", - "# Create a recipe for preprocessing data\n", - "cuisines_recipe <- recipe(cuisine ~ ., data = df_select) %>% \n", - " step_smote(cuisine)\n", - "\n", + "# Load themis package for dealing with imbalanced data\r\n", + "library(themis)\r\n", + "\r\n", + "# Create a recipe for preprocessing data\r\n", + "cuisines_recipe <- recipe(cuisine ~ ., data = df_select) %>% \r\n", + " step_smote(cuisine)\r\n", + "\r\n", "cuisines_recipe" ], "outputs": [], @@ -609,18 +609,18 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Prep and bake the recipe\n", - "preprocessed_df <- cuisines_recipe %>% \n", - " prep() %>% \n", - " bake(new_data = NULL) %>% \n", - " relocate(cuisine)\n", - "\n", - "# Display data\n", - "preprocessed_df %>% \n", - " slice_head(n = 5)\n", - "\n", - "# Quick summary stats\n", - "preprocessed_df %>% \n", + "# Prep and bake the recipe\r\n", + "preprocessed_df <- cuisines_recipe %>% \r\n", + " prep() %>% \r\n", + " bake(new_data = NULL) %>% \r\n", + " relocate(cuisine)\r\n", + "\r\n", + "# Display data\r\n", + "preprocessed_df %>% \r\n", + " slice_head(n = 5)\r\n", + "\r\n", + "# Quick summary stats\r\n", + "preprocessed_df %>% \r\n", " introduce()" ], "outputs": [], @@ -641,12 +641,12 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Distribution of cuisines\n", - "new_label_count <- preprocessed_df %>% \n", - " count(cuisine) %>% \n", - " arrange(desc(n))\n", - "\n", - "list(new_label_count = new_label_count,\n", + "# Distribution of cuisines\r\n", + "new_label_count <- preprocessed_df %>% \r\n", + " count(cuisine) %>% \r\n", + " arrange(desc(n))\r\n", + "\r\n", + "list(new_label_count = new_label_count,\r\n", " old_label_count = old_label_count)" ], "outputs": [], @@ -675,7 +675,7 @@ "cell_type": "code", "execution_count": null, "source": [ - "# Save preprocessed data\n", + "# Save preprocessed data\r\n", "write_csv(preprocessed_df, \"../../../data/cleaned_cuisines_R.csv\")" ], "outputs": [], @@ -686,32 +686,32 @@ { "cell_type": "markdown", "source": [ - "This fresh CSV can now be found in the root data folder.\n", - "\n", - "**🚀Challenge**\n", - "\n", - "This curriculum contains several interesting datasets. Dig through the `data` folders and see if any contain datasets that would be appropriate for binary or multi-class classification? What questions would you ask of this dataset?\n", - "\n", - "## [**Post-lecture quiz**](https://white-water-09ec41f0f.azurestaticapps.net/quiz/20/)\n", - "\n", - "## **Review & Self Study**\n", - "\n", - "- Check out [package themis](https://github.com/tidymodels/themis). What other techniques could we use to deal with imbalanced data?\n", - "\n", - "- Tidy models [reference website](https://www.tidymodels.org/start/).\n", - "\n", - "- H. Wickham and G. Grolemund, [*R for Data Science: Visualize, Model, Transform, Tidy, and Import Data*](https://r4ds.had.co.nz/).\n", - "\n", - "#### THANK YOU TO:\n", - "\n", - "[`Allison Horst`](https://twitter.com/allison_horst/) for creating the amazing illustrations that make R more welcoming and engaging. Find more illustrations at her [gallery](https://www.google.com/url?q=https://github.com/allisonhorst/stats-illustrations&sa=D&source=editors&ust=1626380772530000&usg=AOvVaw3zcfyCizFQZpkSLzxiiQEM).\n", - "\n", - "[Cassie Breviu](https://www.twitter.com/cassieview) and [Jen Looper](https://www.twitter.com/jenlooper) for creating the original Python version of this module ♥️\n", - "\n", - "

\n", - " \n", - "

Artwork by @allison_horst
\n" + "This fresh CSV can now be found in the root data folder.\r\n", + "\r\n", + "**🚀Challenge**\r\n", + "\r\n", + "This curriculum contains several interesting datasets. Dig through the `data` folders and see if any contain datasets that would be appropriate for binary or multi-class classification? What questions would you ask of this dataset?\r\n", + "\r\n", + "## [**Post-lecture quiz**](https://white-water-09ec41f0f.azurestaticapps.net/quiz/20/)\r\n", + "\r\n", + "## **Review & Self Study**\r\n", + "\r\n", + "- Check out [package themis](https://github.com/tidymodels/themis). What other techniques could we use to deal with imbalanced data?\r\n", + "\r\n", + "- Tidy models [reference website](https://www.tidymodels.org/start/).\r\n", + "\r\n", + "- H. Wickham and G. Grolemund, [*R for Data Science: Visualize, Model, Transform, Tidy, and Import Data*](https://r4ds.had.co.nz/).\r\n", + "\r\n", + "#### THANK YOU TO:\r\n", + "\r\n", + "[`Allison Horst`](https://twitter.com/allison_horst/) for creating the amazing illustrations that make R more welcoming and engaging. Find more illustrations at her [gallery](https://www.google.com/url?q=https://github.com/allisonhorst/stats-illustrations&sa=D&source=editors&ust=1626380772530000&usg=AOvVaw3zcfyCizFQZpkSLzxiiQEM).\r\n", + "\r\n", + "[Cassie Breviu](https://www.twitter.com/cassieview) and [Jen Looper](https://www.twitter.com/jenlooper) for creating the original Python version of this module ♥️\r\n", + "\r\n", + "

\r\n", + " \r\n", + "

Artwork by @allison_horst
\r\n" ], "metadata": { "id": "WQs5621pMGwf"
A tibble: 5 × 7