From ddc4588ea5f18efd179c6f74378f1432c11de075 Mon Sep 17 00:00:00 2001 From: rottenstea Date: Tue, 30 Jan 2024 12:20:42 +0100 Subject: [PATCH] Updated .readthedocs.yaml file. Restored overwritten minor changes in some scripts. --- .coverage | Bin 0 -> 53248 bytes docs/build/doctrees/Examples.doctree | Bin 19434 -> 19434 bytes docs/build/doctrees/environment.pickle | Bin 41019 -> 41019 bytes docs/build/html/Examples.html | 12 ++--- ...f3d7270d1a4f610987840f194b80de03bf1506.png | Bin 0 -> 57956 bytes ...6a3239cd47686b1a32af1289ac6bb1403ea7fc.png | Bin 0 -> 51194 bytes docs/build/html/searchindex.js | 2 +- ...f3d7270d1a4f610987840f194b80de03bf1506.png | Bin 0 -> 57956 bytes ...6a3239cd47686b1a32af1289ac6bb1403ea7fc.png | Bin 0 -> 51194 bytes docs/build/jupyter_execute/Examples.ipynb | 48 +++++++++--------- 10 files changed, 31 insertions(+), 31 deletions(-) create mode 100644 .coverage create mode 100644 docs/build/html/_images/377fc301d988b684ab0a36df9df3d7270d1a4f610987840f194b80de03bf1506.png create mode 100644 docs/build/html/_images/8e4b2f10942e3723cef4cb70ca6a3239cd47686b1a32af1289ac6bb1403ea7fc.png create mode 100644 docs/build/jupyter_execute/377fc301d988b684ab0a36df9df3d7270d1a4f610987840f194b80de03bf1506.png create mode 100644 docs/build/jupyter_execute/8e4b2f10942e3723cef4cb70ca6a3239cd47686b1a32af1289ac6bb1403ea7fc.png diff --git a/.coverage b/.coverage new file mode 100644 index 0000000000000000000000000000000000000000..9d74663f3e42ec65fa011bccd0e796053d6d3df9 GIT binary patch literal 53248 zcmeI4O^h5z703H)x~JDW+abmb)+%g8#;jM_-N_0f6mqbaWF?lw_S!KK2$4?DOzm!) zneK6SkG(4q$CDsgLPA_QAP!u(aY4xyOB|3;q9|}d0tt{1Z;f8{pwZKRQGg0f8jYlkzzZHx?Unat30Hrs&YmMMNwwxTcd9gEJ_%~ z4#jFIJt;Y(th)0x=LKcf{I24>SUc~m%>JPEnIrGacJ1#R`Jv_6EjoYz0w4eaAn;%l z7+jdO>c@|(ufCjk&5leWuO*{wTYLKA#`>iVacTXF&uxe-Pn?<&6joNmx`@JSq9-G< z?RTW`gSOxD5p9X zpDmGlNtQuEq`wnz32`c~z9b^KEh8DUWSnVn%5N{tEWP&1j8#8+RJ|!vo4lw+pCe<| zP{zoV&219Y3Zph_-;BJVwJYOg;SDWpg{0?Rl35#t-9{3Mjvu6E2C<*`VIbt5Z1oe_ zzNdl946O(RuWSv;dWj8sDXW>Et3+p1`5ra%;(6t5QZ5J!tfPv2YO0*-9Q3IW;2)mjxR^ z9&qxAS%31Vs*qR8z4%Ipes8&6KMB))mm1$)qs{EMKUTHs3k&MaE2*O}9=GWy@i1YJ zIn6M8g6r_{$$rDVWZX%(7j-%!+)ld;*A`jhkT;k6OrwC|McmOum=`2XKU8mHWl0Co z?1as6UrRkEmefILEGUX?_k$L9m6&a4g;!k&LI@wYN&1m}#pz#S98!PW11$*#Ctcg`lo7b|A{ zsbiBAXBFHv-kPs{T}xHIc|4`xr9q#+`k2a`GgA3kxxaGN>(FS@^ZbaqERDh03?R5* z+oQr>Gwdg+|MG6?o;>%A^vwi}_6zn@YAG#F-FqvHW1pr~p0?sI6uDw?*Nb@+iWfyQ z3_H>bvblk3Y{qm>KNhJDch5?vM>67lma%hnG1aM7N zyZdfG@#!5X`y}veg#<3#pTLskTLy_cIhDALJ$}g#H&5f~ju*%2djrT~eQJwK5=$yR zqmjVcR4SIFY^o%seh?{%jFSd$+zAfI_y6tMqsrV{&O+_c+KsvEb1Su9J3Z%(2dbOH zSP%dK5C8!X009sH0T2KI5KxpCjlpU4AWN;O*8lcJW3c!?5MNpxR=;Kpo|sPL2dw|C zEn{%vJ|&N>|IKp-y&-QZxIwjZgB%Ee00@8p2!H?xfB*=900@8p2pnnxx~eNRzW=W}w-x#zfB*=9 z00@8p2!H?xfB*=900@8p2pmEJx?Z!>=l`80#rdoAC+Bz0_ne!~x11N8bCiVu0w4ea zAOHd&00JNY0w4eaAOHdn9)T0Kq1s=vSJkKVKb-#QTiW;k^D~VosLDf%ax2B5DQC->3?q$nJ&iQYpsNAt{eQlMfdB#^00JNY0w4ea zAOHd&00JNY0w8dB3Gn@Ytp5*h`@%91009sH0T2KI5C8!X009sH0T5sU{QN)G{|o^E b1V8`;KmY_l00ck)1V8`;KmY^|FM0k+PjkiRZY2E|Qx5947yHHaj@ z09@Oes9VC(-mJQt&kkSyQSuTVs|Ia_!Oo_00l*ZSOO)3`L^Ll82%CRW%IHB4R5YkjQ{`u delta 350 zcma)%u}T9$6h+xpSc#35R>9REib9yT^WK{otF`nGw6NHnH$xgNqDIAEu-icD;12}0 zv6Os_MLxmGEn;V3cP`uu=dNbSYL+Y}{S9!`zVwgNH7t`R94t4%I%>`izkcDp{TQTa zX{>l)FzKe>d8>dd^C6=xYeVwP%znb_!OABSb6U6e0QoJXAu~s6utA z;t&AE>KZ}2_S(K?S0@+aP~~-acnaYz_mAUAxIfQf2#f%Rwdy`9R<1W)EB$lOo|d26 EKfj-2nE(I) diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle index 7f1578e41b558c6fc3cf8a677448aac00ecf61a6..6d1b70c183cc893f3b01c2493934b8b618a003eb 100644 GIT binary patch delta 1160 zcmb`GTWAzl7{{I67-LLO*ISIYR)#0i!$71%H&4k|pH}{TssleLtRaoBT6oRByg_ zAUu%&X5HJgf5RDf||@vfjCqbIPOttyHsDWYMr zh9KFFYCD20^D=95hUiH6Jw;YT*5OpqR9HL83Z}z_SjlUb@phEXegfBmJf!$f!7qkJ zxI&l+axlnl1S{lOvoqfIUQGN!WFf>=<75f`=2UOiZDAAS3!9-{SjVh~>%k@PfM1I_ zdJu2Rjf-JO1?NDESPZZ0@eyz#j;xf{`Qcl24Ya8mY^huWzo|`(4&PL+hM2Joj#WNh zME{NZgo6GTw;&Ipll1zt0l2HJf|@!Vs`OzZ?3&NO<(By{6 ztT*R8+MUQ1Zeu$ZdoPhAdW?aTol6!pk5LgIH(K`R3UN;-17&rq;6H6AjMphJueFs- z>|4gb+=g7{Ps0-dvfS#RZh)M(Zx+p^3$LB&t-99l>JabTzLa{AtmolCuNDsUDB+<~ zLVoG2^D#|C=)N_F(a68OS7$Lg89y0eifJzC#gf>mD0zfwf@E?(@}FcB+1%fZywM*) zE*hZz@c{$*^MHk{PQ{VeQ`A{7=pv5}n#hNP+mIg*)gU{Eb|a^U8jz*wy~xAq9n?wJ zBTF(gdpKh<8r;vskm2EOSebN!uqm3bg5&7cpFE_ lcV|AxFA4XbsQoE5tE;EIJKh$}R&P?aj&?|QG|0OsKL@%9if#Y^ delta 1174 zcmb`GTWm~07{{HhOVOsf(yF_kQlSQfq1A?GXNe+^rLW$EZiK506ji^*o z9CqH0ktzoQM5Kz~7m463+a767C%k24pq?pQSME@#Mr7(B4nlcF4k+js5C|1zK@uHQ z6NxAVc}gTnmWasv9YLok2UVF$q9*w@hiR8GD@vwIU=Cji8w3JZh%`QBR`#p9!M^mz z3agT>Jm+n2MW_LbvpOjfljyE5Z2{$kf8Z69GYx|)?Z+O z)hMoCU@<4Ija?b#?WSmEqHl?CP+B(|KDpMy`MN&ip*xR*y!wnocEc$aSdFWVEt!ef z)W*Rh*8ogvZZ{2?!w%ktu8S{$8n;+>ou;_(*b zhj;+laJT_^^{^LN(9QIH-74~Bw}z}qgprpMOqtxHBlq<9kuQ2yA{X}7BHMa5A@B6o zBc~;O$lb{`Oi8Xs7NuD3?vx)J^(+-aR`2qVMk zdgQgV8(DbdHTrx#G7~xND5HY(7@Ln?w{)ejNPJ^@1CFW0ivRL24yN_w@3w#az0QC6 yz6aAC?5HOu;EOzE+&eyJY>}<$*nxA2aqS(EShzKiu34r$xO>jMuM3. Add uncertainties and plot the result -
@@ -281,7 +281,7 @@

6. Calculate the difference between the curves -
Area between curves: 1.1641176307170609
+
Area between curves: 0.690393920974019
 
diff --git a/docs/build/html/_images/377fc301d988b684ab0a36df9df3d7270d1a4f610987840f194b80de03bf1506.png b/docs/build/html/_images/377fc301d988b684ab0a36df9df3d7270d1a4f610987840f194b80de03bf1506.png new file mode 100644 index 0000000000000000000000000000000000000000..a0c707b2a74039181a5e5e38b94c9bb471113002 GIT binary patch literal 57956 zcma&ObySs6_bq&o7C}Nl8Wa#oY3Y(qfkR12cXyW}B_&+~(%oIs-3`*+-EjAL-{1F* zamToKjQa<};o)$e=h=JhwdR~_t`npnCyxG{@HqqmL6?;HqzHk)r9&Xk_)w6*E79xS z#^4_=2T?T#C2J!G=dX5#5ZSK|HWtgo^yDTE4mS4OOiY&l z{~H*s?TnddImkr8hoIU>sM|vzFTcWm;Bp0WOd*h!QOQq2$}Y+Ki_R{}(A(CNqm)!_ zNtE<}kq~7#QNdt|G71_FWlbX5+!;|-)yo1HE z{aYf7ei87BnvY;8&^Yy7g8SxBos7{xt^>ZP{CrwJaumN21U6YMI3Y}gl~pRg2-ph- zpD?izgfJ6BQG~%8grl*9Brp+#OjzEapo0I)iXl*dcc=IMAg4s}BWEMP3IJ~opw2Yk zeU36XoZ|eicPNEtu|+=qgYVTp_u;kfqnR@QhQs>)hr6E0w>R6F;ky;V_ow|#yifOM zkjAISyHGNLX6<1eYEDl4oN>udpFU-EL!lejCugW&y>leaN|bzDj#rRkZ^ZgEqMn$oL0}YX0>Z zr+H5GRMA;?|0IzCPviX0HL%J3Dk?24e0+yeKp-uJ$N99x`yphnxZx+xJ2~ZB7bw*A zY>+d7#qjyl-O|%X$K6*(6$D9xVrFKvbSj0*hYd%Ybz7iJWlc@jXDgy%0Sds=U z<|>2A^t-i73+emsAMcLB6bimy?3J{ff<;pOvYDM^B^+zW?X*85QI$`_&!0-bYNX4N zG-_70;4m&5O2QLcTKa*7g+;C00JY`elBl=0_x`}zdo51Ki-MQ8ae?dcEbZxdCnxP0 zCILb3(&HuP?d3s;O2NiRx`@Z)%@!pURhi3)o&z_@)0Owr^s6{pm-nOC*!cz@ULRjw zAurb~d7W)D^Ee+;^6(J(w~a(V&27r*r==6VU*7JO=yN1RQU-zbORKZrV)3}Pal72_ z-5$+M;It-{7kFTUBqSsZqzSYvtSKofE@)*jGc(hxmj~>O=Zv>_d*7b#v|H9JcCB`X z?9A6NK?EMJ-`d*RhPj3LIpYXP7%Wl|MY=gjqxyPpOfDEyK;q?ex?>; zpNxz*V`F0rS4aPvh#=9u9k{BRpEuUr&$oqaY(79hfD}kqA*K^EQ&TFNUmver-`y!` zY7Qi_o4;l^Q;spLv0jq1vSOr;&YQE_Dp#ZTxLS0+Kj|hrRM%>2Ydb$&Oaj}Tii$%` zE~!|w*J3(O?RB$(zq-2GGc?p?!ZucI`Q`gdvY|@T@gJd~^s0~d37&#=OW`CuU0|gp zWn~?gYQPTSF=@YOH7{xETJMb}+91@|*H7TGrzRjEZ~(VGSH9&$GH1bYH9W25OtM(- z*ltymISzfYRlqwQ@@yoZh=Hxg3nchV@o*!sAca~Dc!BM{+9f5G7V4@CF{;`@X=zJ{ z!=B5na7IJPl14^Gb$7$bT}Q*U1s~$QD87CB#(Orv3O22I;lZgP z<*oQnoAn;7=KE9W$CGexo3${`sqF>!(TM4pO!1e_ob%s)$<|GquvJeUtmARkyPH8+i&kmii<90n(S`1%)d*!BL} z_OSWRYQTuKxw(14wwpxLwi6ct5iv40wyQ6OPQA{K%KdVG#oGIhNZ|e$o}ZtebaL9L z;$+$XWx4Z_cI(Ag&#e^au_|-bE18y(mPf*n&cF7=YhJCNDbZyIY?H#~DcY4c#ThwX4s&!iZEe?f3sR%|ARL z9Pd{QukP)Av37ig07_5zufeGP{(ic+G33@2n^LC(jn)cvTkpr4oV%@bkwBF%P8~n6 ze9WEx)fGkO6Z5)6+~0dZtZG-jn+bd1CRa5)|UAt?=j@=@&I0Q zF~GX%LM4n^5L`D2nal$-r1M$pM4nRJ%6FpOEH6I=F^6tcQUYeZPj!rSJXHZd6oM zP%I}&d^D=eIze%e+!{*Zs7Ea6#Jn z8f)XJLiIzzsb)`i{=0ovaCo*x*KkEwE~a&iM>9kZ@2r|{jI>=ha4R(|i}t8cCIQws zp80|G_W0~9^Ut4v$pTgTovgTW!+t#QXsFMh*DueACzQurfece=z4Yk!<;BFO**Z8o zJ3B_T=EBfXlfvnpQFPa^81)Jxba~#B0C&B1*wO7K^VT#aOzr!aBA4pANpMB~(I;`J2A-T|BD?~Pq&58zk~r1H&^_=x=^?p4+C z+^~fxzWSDv>eff%Q>noKtF-T)MU2n@tY!Acg2K$rjTFAVZPr!<>$mK-Co<61j0G7eR zIRE92BKUdUUB>i(KL#IVGYM67y>}7Hr2{o|;>W0o!9?z7dY$HEcw`KS4M+{s+y3$e zlc!xo);6GcuGxHa*(<7#Y}Ty(%G`cgy9$Cr}kb=%uCMg8$(JeU2Zi^n4}sf*9W z-n9MkvJl8(qI!C7oEIJOLF((&D=P&>w)u9K&iUA7wRXNUiE=3pl2Sot1{C zXJ@XfLGSVxz5Y&5$AL3lH%6JNQV?Ui))g5U`T6h>+<7}mDcG2>=U?0fPJ7<+-fm}J z*oEQSb(1*P*68I1F}2)BQHXrE0Z2@v$}J-^b8)fMPeBy`Y27?QH6cbs5MnQc_Y2UyR}q(`PG; z^*_8;Yxdv*=<)jI=CiW$gvqoTM_xvC-xM~guo5=I|B#R%7$^CE=lP zi%M0JQI7XkQf(gu@nEwetWu~ZBqjCS%gYM}$pB|55aW4FmHzw+)K=qIdiB32Yu(IA zgP+93S>4V}Kt>i)P*4aP+PVmVa$5fz06@9l7aqB1c(@zvhSg#{GpK#ATBDJ3G~D|> zgX(@*5sce=;bEjt3*pj?(Umso?(CPuY10srM6peuzKD) zTplfjYnS9m$1wtI5FHzf)LN)s0ixR|Z1`qG6YO1Glu(D#((b3^{K9n&sq6Pro0A&38%Xw>%1YS02>#W%q&@$|{|H+!1{t`5u zzQcZQu3%8DWZ^Wi$3?nea3KEqAGPw;Eo!3T;Dr9cK7e(@I0vYeGtHhnumWj1{vA+?4<6UYgwvCB{t@BfF9Af$uO7&U z7C@#MBMn)30d?P%iPEgO<$ni*3WrwyZ3nj%UwyIjEF?P{17e zn%NH=i+byr1GN{$DZajD{=TCo^s3d|R8&-lX~u(z-zX*N)k=M8Yd=<7FAYgEH3jq< z=xy}H-0$f;<@ZvtKgEs!AihP4dDa2qFMpA`E;siFV8Ib_ae)BK%JbhC6zxKnbQ}n! z)cL+hc{atkkR+zQD-rT+eq%WPUGmI3R+0NZ!a$!Rfq z(P|5Xh+X*mo9k;EkQQ}W65?5nF<=b77KB<*SXk4tYdRuA`t7fzq<#>p!vI)DPzFtF zyN3bMVPaR)QEOysMnmJj*VUHxLcf3D>+f3L+mjX&5~^FaZ7x@DGi1ovjhCUm8U_l6 z6Y_6+*;L*Hkkca)6Z=5eHN8U_OyP-Zd3rb^jk`KI$vc1i^M{huWf=||2WQlTZ2AU`KQlBksyD8=I9hu0+Zs2k0-2V` z=i%;3Rs9g4YrzYp_TjBbArnA3cmac$IdFp24Cf`!?%zWGiS-)bSe0#-s#RI!eg!8r znb)=a?+Hi^cs_0Z$m4(}hYz_fI!?otx?Px!jgQk2FO`0U&yh=FXzl74HE!-tivzyqstop`wb1wWjj5P zmY0KzDoarVYQ?OhI0T4T;r$-`uZ*IRkz)U38 z5QaAaL;U*nE4^lIshBAxICEwN1TRqGj#opNu*t~eJv?}EsAYbG(h3k*eYYP#{92|+ z2S6f;2GIeaQV&oE4x5*BKfuzk%~8{p9pJjfO_v&a`udTSy(AHgE%$b*o|m(PljC&$ zBS$SyhjOCn<2x>ZofQDA+47VEk}ZcvC%81BBnTE5{{>*_eSu2R8wv`z6uEA2`w1MD zglk=41t(ndRp#AeS<>p2CRhckCDiZVqZX-1FEx86u$f{5IZZUDKwa&mkG#@+n(=BF z4B!pn^rCNWRW z_Ewt!h>bok>~AiJMKK5}MB0{qTV@by5hwP?D@aq!ZTc-|4IQ~fLz<>S1O@}}B!N_U ztf=Mhi9&06A<;^;;`O>}m4S(kDT7B2v+cOryx!@29Wmk&1d}=y!V`xP4q}BWhY?|V=UWY!I(i|=_RZ{5<$op6|9MG* z_Ca-N>s;kOdg;X5Af%png_az1l~2ye|3`UM|34oj@#i3q0LX4&ixNXkPywu&cvq%Y zCH6`Bzv?RhWUzba(3?!eVxUO3!$AH%N!O-lx|@h19HLm=ENC)L`t z<%9N7?4EHLFDVA`|0hFku7UcJ3N&y)vcR< zMi}8oR)*PMO9j*H%%I+Fm!WIRgKY;QxGPp?4UXK>kVHO?=TO>Y?4;?CS5@%G+Lu0| zblt(7d43Aw85GK_t2o{LGwoUo1R{sGX8kuiRflQq;SY#{PQ%UUs?6Y{q<+lWYIhNg zyo6ZxGKZ6`rKLU>lnk8to*PB3srd&)n8Ck6kf40PxUki?;yC{s3rzj6J+Lm^9ny$_kFC9-wvX+*?3|gG0fdw{hoy_fs~qTG~PYEmW$#cb?csI!NC zIG@`&(AW6MX=$JPP)Wxg|3zc^;Qi=<^x}0Zke~VZjny#;1-y8HGAq?IF<#IeFyx8l z_4MEjw9Ele7hQo=II`ma1mrY;m^d8S_hRy23XcZD|1P7{D)lJvvw-}X`uwlSGn1Sx zYO}P$%+8LbKbAoxbMzSC+y;2eR-h)<9yQ-V0AlqD8*<-|FGy+unU=jkfxVFfg?%Dq z1e@ko7s57_ffhSyU{p_vgEbog#YRZSV$iC8r5+1wAppo$Yy$(%$hrU({>jR6_4rpF z8-XHBYLbhePNh%<2a!lcNDp=RT?tO9@FKf^Hb7Iv5P(h#&s_`*C`U&}A^Qt;zCLF z){(!~cZ01#3XU=C<9`Chn2&o4vUu0^9_4D zO;&9Y5s?C3W0<(@>gq~5nO;a&Tv{4oUR;Ny9=q6GZ87^7Acpo|@0DCYD30u1kfz`? zeuQ1krg)S0d&zYryr8+X?ey8gE$JY;J!SU`!6gS(=VZd!dUYKoY1P?1ayCXle>NX) zVel|23j68^h)f1RF2e0oFH-T5f>$QU991jc|Mm-!B5AOTp=RMP;Lef&{`L+H8G&Gj zAx3~N2>jbx1s+dc$}{!4`zwevqHF=BC|9eKP(;pH0)dQ*ByG$s^~+M>uV+`oU49;r z`?(ql@_RlO9YReWLpq|a9RT{5E^PENt^YbAlyfTxH zK!VE1rv;&G6P^bTgVlkgZa)CqO7*%mZGL)mKdfED2=5O2?{eD|Cnvv=BKx=hdR+zK z*-t;ESDUY}@bDChn>B`17Vuub5R{bSuHHurr$DWGE2->46415LYp$S@U3YqQb(Nb8 z04>0BGZxjf{Q&(e@5h~>)d6t^_EW&utlRbs?7n(~QxS?V`pKJQX{c#68Fe|uGf3D& zXv5E~sjDcJM+;eo)>Y-wZvk-RDZN(J(`&McXG?>f87n&e*-IMil#~H}e$Rk*P(ZK5 z@dDhNN?dTvI8fsM3-V5`nYDRDc_=9nevj$|YzmGxbhWWvE=YwV6FP(*VD@c%_PwsM z9Sj~fNHeXxMfKw}M`Ep9eD9c#hLo3AoE*t6SpnpkK3R#6X&E$-ZHLqv>;Lbh@}bNu*rQmRFugQ-_0^F!OaEJltOHF2h;ltg1+6ww!0w%>iKMa?X8!tIzR+5($L7+?KDGhw z07dc6LVdD@9Io0-RN@gS9S%bJW@5XS@LG2`vL@PR`BYx@m1{uT(OLoiF`chIKpe(@ z_3D#L?Ow$yP*VV-+np?sl#>H84y#k)R+7G(C1(B+e!6HRrE*FEkD{IOKdPMH8Tq=X zPL86t>l?rG6?CJ^eoRG>SDJuysp)=D)l)tIDEq=5bz6+A(aPU%5Z?0<5nR%wKljN%f84EHPAyjYCQYtE<>UTw+%!QI2+ULPA0?XPnvPST|cXsjJp@&CFv6$VIV0 zi97?!Fb+O`H^^-$&!6i74RFD2uPBt5tGsLLe3yIzlSx=Qz1Cl0Ltj{^Yiv?DzhF-` zhElopD%r9HQ7E@AJMFh;EI2`6o$}cVgrPvTRXsQXd~Iqk&bb6bSfK&GjVSl~nCTp} zGGG8h^*Hj^m?TP85m}0uLno@=h)W|sidNwQLptr$^WH4hWy((WEu9!mp`Kh^En7c@ zcY_8pxmlQLAGM_>8;rW4li1HcY>%Xz?Mi1Y+KFD~<7dEd8|NtYsbU`@HMI#lHdZsz zsq{2z!m0fzcM1YwM|=eNgs43sjv4AF%u~g~2|g$SMTiJ>(+md1R~iilLiOy-CQLHV zq^`njau0i&V;f*U@aIr`TE56xVe z8OU@s{z@;ZMC)bcv!6zBY&Hi7Z9G8~>4{iEJt29A@ddeNJLZ0O;qjYw;Yq$UhTvX2p&>~ zxwf1_cQC(NGiXuL)&d_Qj2+%^G)z;*uC|EK_9f`B_CFVVpFKvRFCCRnuVi9hzG;B* z-ck=Ty&h10(1d33CLBO@bZM}%)Jb!7Ub)mLDLt(E(NMd2XC!jUItMxjXeXtU8ZJV* zF9467uhK4y$)vCg==E)DHF&;#E>?;5R^eVI#ObU0*n<@fBgvROj8*UF|- z0l^GJf&05|bf_VaR;H~N`MbORDn4s{8>iQj>59TbWa@I7h5UpCEsU!k;jXTR(JvR6vAvw25T;d zu?_E2ysewnjdR98lOEOFaTFIqxj*<08t`asBL`v$3ZLT*DeS!2kDP2upQ-SW_*x?Li z$|3wqo{RsASU9Z)(S7}5<7dq!=SpUD=||}4TtofZvnYAH$LwXizyaUFH}n|aav^UQ zhZ0IL53E0_D33|)Z?j|b341P993re_jALq zvg%`%gPtEFC-QqvWOlX}5K-uCe6qOjAp2poVfEXUM0M3{&)-3pTb22MUQACP#iiH$WP z5rZEPn?-La|6gK>kLupR4tYI9?~F`r)AaTJ!uaXMnENF>`L2y-U3Y;Xoeuo8vt?)e z&-B-htMcNQ0rfa(l=!IP*U;Q3xD+lp%aawm?t66OhV?P`3*_I>zgVH7h#P%bxU(Z} zH#ICmxvb1I%5UGGXi+L_kzXE{LE^_+7@X;6{vb;VL(@OfM=e~IN#sk-Kk)RY!I$>F z;Y=o17Vr2Cj`H>!y|899h|;bqdD7z5mBmJP-S`W+tA-aoUfq|!+&xMq154BbXi1vTt%4lJOb8+H6=$!;3!G^$dBTW zLb=)^GE&E@S1BmM_&AawS&I*lYfA6+)ZgT3I6e@?TMV%nN{5r~Z3=v5ZjR9Y`ESda z(^0>yzlwU`(XCcU46v%YJO^|yv6cq(jKz>Z+nW}q_5d&s^92Az{k`U&TS#(p@XbVH z0=pYweiyRViO%+E4gBv(iR;~}-2CADd^LE#p4|m_$U`>zVfSX@fraGI+ofH~rCo!) z9gp(P%Oy~De5aAq0THwZ`d69B=$ojhs2{<>Z&+BOfMin!x*MPqf%KDR+(Mnu_DF)B0aWxox(Y4K;U%2n;)qF0PY*-pK%Iga zd>-%5be3;D>-0Q2Mj7wCi99(Us zrtrD6;zO^ZzkX{SXgcDM@{0N zJ_X#Vf$pnXsV*GQQUCn;15~|T>O#}Cs0VkwkXks%QndB62n`n}PGu;RYtbB1E*H+R z!Is#el+0ME{4xAF@i246wFI?vxY1`_M>eSkM4@9+ZIS@sq=IYB{hSHhO(izGpx^%Z zpcTUUbX#zGP|^gI+^>MVX2s8B;13qsyUosutu{&KZ#KBxNAvl*cyz5CNmpF>pzqYP zFT;>q843(>?RsS}O4}7qCJ)#l0gC|&Xah14aahzI`}6$*=95-m_?@XDBEZ(!y&3_3 zhOq}An)|<3%2rm--WO5*%vdZMZzpJNfi+E$zUsa!%l-X&Y;IVgSmr+BGvu|mR-aEU z`LnReqx-K;KNy-2(=EgtJ(tXYOTr%XLV>&MKJeGCS1>&iK%XQ|>rG!|(q)0C8~KzH zC=?2)ya@1A6%DUU3gybD@xxju&7OBEZoHhFaVb1n>TsY#v=9$9$6F{$4^10Q3b!|P zz+6tOE6T?dSco}SZm~pryy4QEW_Z?OhF2hl{No`2A-yi1$C(jy_Hsb`17=#I*KUjl zz1B0(p#43*1M3fg24>N?y$1k~7W36ba$Co{1x6>`9YV_CF*B`7FY66)`+q2jhgmtYx;;h69e89aZRDS70E8kMi7QTL)qEJK{G#qR0lSAI8* zJEEOeyCUHzE%vEOR7;z`TQ@CE_pBLfVlSP6WB{0DeH7ugj_m)|KjQfO`SYPZAla(` zS;Ol--rrO;4*{7S_+>0X+uF<%qxOfh3XmY5`cF5CEzwE6uD|~M``7IJy0kR5Dn=;g zqUl_x)C{*PG%aZVju@WD!C~%R>Hnib5PZ-T%xdBVRE3Ak>zcy->X3?oAq@1SC${f{GmaPRhrgDo z!MYYOS548L+h?Tor~55|Lu&}IbHOBPVC1p03pPQmh@$Gf$S$aFPB{**M^w7KnsMg$ zt!uy9_(@8{pNf^%98&4USJ!Zv=@3fw37&$Y*jm8+W!7iq`n~*&zs=*W#1g$C1>@zVo=ibkB`~J{UdyyHI8^ zHTPU4&CI14w0R&%7{qEjCqO3$eFWfNGXz>b2+KUNttVizm~C)o0>M_xTNOxD#;`1x#ayD@7~WCWQ`VccCUgqAw>OKrJj3*H%Uj4Ya`M>a-eYgTprA; zs#C){bR8WXgeiBxYX&n*0OP<3(CMe@e;P6-k}HD_8~jV&R={Q;tsOx)H$dF_KuEMT z?`ofYUFpoEi_U+;vc`?vkYjPTQ?*T&4Ck}cP|~XC)ubR(YW?j@Qt^i0B1P;?RnJgr zXogsVP)@Z9IRbxL3^64XY`}{-kGPtL$?_LPmxMjjpYeDlTAN z@w`;ucjAHVEpWq}UY9}ZXzJI1`Lh-{0sy;1UjFBPv;n-HRujy@n?uBB2-y>&+fqNV zm5v3h_ReZ5klkfISmk4zc}t)O^a83& z`>R4jD`Xh`dw#cYf3r_q%tZ&VPqhLLRtxwg0lV3+?(l-2pjH(Y(jPXS$wfs+11sx2 zICfjr^H%1&X6!uq{IBizE3V1hFv`IT2aa(hmqyHO69g51a3v_1_ zHuOlNoP7@>PAht6Z>W%1!DI%FRMiE|m$!MNE|=eqVXoNgmB3G8Vl2i(#NniCs3nI# zE9MVCbJriZxz64AK!2qfMR2mTvWYB5$C>RXu?LPe6-7>fBkC;i@cXZWBjyo~Zs+b! zne#0rfAy&(Gn8_f9yE~a;W2&6qVVJmuh;{0Gk<=F)ispcuWJ{Z?7iUenn}Fi&QUh_v=l=el zw*OZcqH8(t2Iy*Tfq<7uVEIN@(pav&tJY;MfDR%p1drhvAnPZm=t>Mg z$0iKgWYmwvf&HZe{dGmGo#~+f*KWf|lb`ic$CvGkEh(9ndx_rur%&ik59wR#`>$pV z{(4+o$H@5)(Nsq%t&-EW_QY8Fzjx}{W>bve+6KgIVmf2`Y*-x!SRE;;sa2Bt8Q9rz zeE>l~OSPWNheGaw#tHj@#uBj_y->JNgBk)|sk6IVNkIWpYvi!M*ibWf3X~C(P_rtO zPOYbxBA3>cj{AQa);NC>cEQ`!i+h*r)ni7w5RV(D>AJ2G{7ijsWGuxGaSQ8+ms{DF z>3uuBs=*V005)qZ$MJ!E2}lasKy+2Fu}X1o8o6O%WtEhchPQcVTPz1keNbp<;dwl0 z9|Q5|&<@EzUGw{Qw39jV37}E^B;lEwm^6uem4*?oPuhL7z86~FDB|aZ;N&3`HRCki zv~YZBzrEEY-mB%U@4P#kz>Xnm*q%pBzg0}4NWqvH@spw%;fK}76}^!ci7>rtYw78c z6L>h*fw{M%t1Fi05n!)pAApDg8l>)RXM;(cC4Kq;V;tg*z}#M=H$xkf`oh8o3HnBF zljd;#7}+FT?7tpa!NTbY-3cDm3_Td+q@zEqP%d}DT~BQfetD<`+m#hnPC>Rm}Ee2o}9$t3fP5>=RkwA>1<66-9WVK!W z^w0BZQG?ff5VYTvdr58izQMJRel-r=U}$AmV*I-NA<7+H(70ywAo{AV(G#WVE&S{8 z_sN%SxU9QK1da}<7X>ygfW^N9awn*nzQFGX^i2^Ux&cKS7@Fc;&o6LWU%lDScAv>T@kLXd1L}U(W?aN^Er+>M{CH@M|sf|d6hP$h$-7Q&vQfun3 zSa)VG{~h2n&O8f>jZk2iZ9$H`eEH1Au-9B7A07&o+?h?gZd1+pY*5J5w9a^BuWd7G zPK9BNi<71$oH{8aC!3O`=dtMS@nYO4 zT?*UsQO%ceh#m29Y+D!D9aF^gTmlsoLke?io89tr4U!Ief=w`hOT{l@84gM&BN^un z`7m&a)f`+vWlx=r<{j3E1ZnYZdM4=exf`ADOxz!Nlh5Zs?SeK6 zRenQvXDNQYkBXT8aq#x!cOX4&!EGO1f0MXDf!st|&axgFLH>B(r?88&_95aosraiz z(OM91Dr+STqWaZfy%lB$%F=Qq4i^=%jpkphb_7c0;_{}wf8XuSChkg;Jbv(dp{$)! zB@ZwxO-}KQwfw!2(LgQYY^eb4P@sePiCbhXnkC(*wg#pCJeA|_{Q?&gwfv!4wjRxg zS*J0usMf;?LC3Sxfe$aIugrp(kk8EQ(1O`a_rBaJJs5bhfYzAqRLTF#!41x5<>$Bf31P@s{kh&!JQ1Y!w&m%s zMV?3aop4h0KD*Ux{cHHs`h8Mp)7|d-KaTr9do>4Q(jFQX^yM~x zP0$+3Ym}wflNmbEu744|N+GW_06loex03PtX^6T%&Umh7BJwB8SK(9>)0+2Uu{cOOf@3 z>@rqP@%2?(ON4=Hf#_SIyJe|t;{sY7?wU6p;yOEL9Y{Br785CF4S5Ske&m(Buv^HM zBIF=CL|$gu;(R^%=BjKdCne?22af|L2b7bq9yJnT-QQOV>@9tA@@ez)-_X&z;5i!k0O+DKo4cx&OhOo|tzr-NUTkdowX7e1mQc=z>@65P*I|p7D$AUu;&ki^jRDN9J4=DLMC9?Ow;pX65_Bo6$WORfEdwIYBWd)>qLX08ZqD+g4+f& zN}x%D;SJ1T1pFQ!@j|`uekpr8OS`xBrfnhV|6`83#$A;M7HN*R~#RO5P5js$oGc=IX0kM3ZIok8|u=JEZ4qX%%0N@yq zW?18S@rv)b6&~1h%Rot;<8K;~iK(o^C*Y%)@?6icOz+U1vfu?G1w9L4lf(1PH($4TW}+dk|%)=x0q% z=;zs}UtdhgxuLpWFY+`WC5H4xq?+CLduZv_Q)_J4i)wchoGv;QduL)g-*aA{J@>20 zb;M*zkO9(_b}e~CbhN)p0fRH>eQsaGlpteiFgB^QTRkv9&TSrj)3Qq!P8gz(;C>IM z^`kQMWm-nOOc8$QJK+5DEXWm)Bf0PWm0E$)N^1hPb3tY+wLRN(RY-w$X5O*o=OvW8 zKxBf-*F#B~SlXT3?}RXE^BpmF7wTAnGZW@cn2ZII3yGD;6&sbm-@RO+M z1$2g(QWDc!Tt4GIPb&xxI|P3@cF^@^!2R*3e#m& z0fw|xCyFkGE7<;syq?lH{wXTXYFW_1C^YZG#DCE z1nh@&N~l^Dnng)AoSmGfFnp|;aj^kLsq$;kuoA;PO%aJ{343K^KGC37DqTiPkX@a$`-?{sVab}P(0WcY z84q74MH(W8QKoa{n9~iY4yPBsssDBdQmF}L5ZxStE!%XctcuB+b?$NcQRet6c%Z8M zeBwU#Xl;w`-!a=bhvGjZ9pX@h?LX&K@`3OMHVbVEFq;6TNr7JwWC~&dFXDzpIpF5A z-yB#0WWY%PIQ4?Sou2l-O9P{x>RV`-iTD*FP7EBA2sRxbFnoMZSM3ayi@q04FCeuV zws^rGqM~f@%qyZ5?aMJNU*Q-pu&&5(qd&a4C&0#)Xn>3(?nNu;ZW#FDh7>C3#?3~4 zrkpxML6<93y3kBHO#@pAvt@woTx@&C#PpJkjI7@2pbyBMbTa&EAQX}Ow^^@LhU|?( zNIuA=hkL%~Td&$?A6|~|ph07E7uV{JC*!B&WeA!{A(E)mbNGg!p1+&e8U@wca_~iL zQW41wCygFDv#Rzxb26)uj? zhHI(HBI(YQ=-?PktSR-rmQ&vhkd<^T6o~0R)t@|S)JW&w3ZvMe%v+G*1@=6Zre-2s z(f7_k6o8G)kdY0GlX)tq$wS}4v^nILq!znoE>x0HujlJ<;WPcWaS1+YEK@>m-y7Q_ z#uhOza;)GP6vh4wyvh(L4F`x$#ZB%a`4vBh`ih{@=d2Cdaju!bOE@tHLR6iU?`=i! zAAa!t2tcA7yPS|osbAx;TIjjIIRj!($p@Zd7BB#)tCd=;P0VE%092{cyn>ZU2SRku zFUWA@-(&(UpRy{-!{mJNSPGk8&1-5oeft_o{MwEEfwO2eSf?d>a&a0bRa>HZcBn4F z+CUWU-L~`>sYyenk7;62+tYn%UPZeHrwBs1;#H4QF2~D4FijMLl=sJ=QNf3%>ILO5 zMX|uIUCF{<=;n@e2P zPp_x1EM((KPYsoEe~q*ktn#mfB7Ds|=1Ex~2!7MnC1z`>_m#2p-xYwLk z#A%+F1fUS*^Bils?PS3w1}~J>xZ}a7@yW@_g6mdFr5RN-A?Np|yc-LLdZS)0>=q-z z`3Sr2asB$piK>?xqS@t6D_M=W z5K*zn7+8iF4Hp*@$z{iI|NQ15)4wk!glMIY-MRPs2C>XA6K8vIs1h{NFouIvrXMdL zo03qNU1^W}S9G)p7#!W6Da*WTK3r^wBO;5U4BATbCjBjGoDQr}FbPl@x=}T)-EM$Q zW)PNM>)_@PM4dcd?+dv$WHS7;h2ke;9QgLB{+>2jgTxYhjqCVM<#fPF^^Fql6*{im zWgU7OwYUS zdA39#HL^oJ{XNb@kMM*Xeg`f5M$MJD#yi?L&hx*HIiyhLa5Y>yMunU&Rz8=^^Pmg( zpu>k3xUl||#&F<>S(Dg=9?eSt}83_%ME`uzNIU|@!& z`PNC?Sm4J2!#s{T=9s_?2m5LQ6E;F^_XGCOu3KqF0z8!meyKrOrAba+UY~y?UrsuW zB&IO__%{;W?WBFgJ9ntF6Gwj04hW3GKLT#zC$#S`-|ZzYex_P>aY9X?ayqQbz~PUv z2$;sMtZX5&rUcHntf`}QBCA?ocJrxY@TCZLcLz1B?w1x|T2x*^0Tav><2>A6WEu~r zdH@&qD_mUm-d6{(kpp1l2SAS>m?Kre5MJ+l+M3v`x+u!&q~iB`dl9&brvt=OVOjo- zNu)oQ)DtctfO^_VY5Iyy5&bxF=kly6PCxs{P?_MwH!r^x4YlZ|pp%Fym{c~gJ)X|9 z&}*k%!fUKE!zgL*9Qu!JpOPAQYhCMNE0TM;XbYQg29qvrU|b4x7{SyHK>hPp4d^-J zy|9TMbj}6X_&xAZkFpwB&y@NCk9iP)V<$8E;gfea!z66hhc(&7B`Q%L%-D%1wY~*^ z`m({KVaihHsq6kM)VKwiWbbHhE_1$_p^z&PH8@xdYTL(Bo&ku6oO)XxjqIcM9JUU! z?b$v%CZTGInA?);771(?8%zj`&$iCO##rY$K*Llla|Nb@?-rC4yIY#;!qh`bN=lnv zs<;tgBekmmYY0gNvk728tqZscXLBza)Ov!Y6q~>OD}uM({t{W}DEoro>%tGYf|cSn z5;z6lYp=LW32bnf-b>0*1FiR20env3n>5zXU*)Bmd2*7;**IaAn29=l&(rl@nN;4J zeN;zoSO5X|AgiH4crah{j;-=ESr`31HFfq}f(@t>9ac5Kt|?+-LIY+JEj#A4hz&$H zYSz>ZVrJg=JK2n}{luVhN9nnV@skUWH0Mt`%%l7e@Jp`A#Cw%o>(Y|yaJTo6Gc6@b-CwHJurnSE=Zmqg9Z z9s}h3QcXyP78J)Z( zlnqCI3psjnrz6^0L!F0~M9Zk7#^<~$qt|FY-n^Bp!|CVSRC}U(eYe)_aAW>1s@*qZ z^f$1Q;ToumMhU+470SedlfcYpc0SYuLwGO(b`5$xprigww>OHa5g3_arervHqz|An zgb#rQ<#2|$-R|UoFZggDF{=XJO<3~8W6GTA zIq)jdb!X$_L`9nzR7faG^-sJJ9h>|`^}p>#`>9X=Cj&I>i%4M5LUt+W-X=< zV6?GdxM|q4rA>DkxDAcLcQ=3|QVPCCg4AuBB79F{F9=n~;{=h+^BfD%++7xvxW!jx zS*N1nC6hL?H4@(|(X-{1F&~i_@-uAIcnEzkcKPoo7VH=Zp<_0yQ5294(tjdlvc;9( zJU=x3wq+E?G%MUuEdbm1e>GJ*48fKY%#LNtBq*+c@ry%SNBLpZ>?wwHFc;+w;3m+% zUDqSUfBg6%m}Aa`hB96BWqJZyOY^#t(CrgKgo??^Ou`!j+~;hge@xxR#JFVSFXWv* z^g?UdrjmC@(;kylvFzE3`_Ay@4Ws@SV{aXm<+{E51JVd0odSY@NJy8Y0umxfNJ=+I zw=|L>B_J&gFWrrxBHf+R(h>qHb>_SG`2K!poN@j*dyF;q+G~&DdU<)C`=0Zf*Y%lB zikpP9Rg-u)(kB0BNG}D>2eBm(c=hGaizj#4}0_Q?`m6D4K9}1-TYFpLYCr$+68h}gJ3XZKjj=b%05$wO`=VJ(s z2Yghq>Mt4|rm9J)>J#HJIk@+@s=F;0C;rkAg=;O&pZ+%ib!EY-aDtlj4$6&B*&}KC zyhcg-YV{aWtXz=5{WQDIZH7~Ld~{@eLIb9FPGo2oYMfP=E9dxKU$N`dgn^hrm0mD; z+Z0}(G!fSbu#wDWNH>IiOLR+ZBwLgs*z1WA$&txtN$oxJP$ZJqKSv|P3eF5FK=Al4@-p>?6>AC_=f|N7`mv(9etZ!dGCMtzWrHs`bF%!wN2ko!y%_n8%2 z%*@Cb1i3?d^%#CqF#!F5Wfq1|P8~%vfezZ|gqSrrvfhK+zZhq^QGUOe%9?ok1S1*y zjQ10Qtw5o9O(gL>UJ)YVZql`=n#Ob{GczkTdGu{Y*@q5Gl4pB4(c*}jG;be${!0(D z%(>dV0WYvj{DnZ377zlUV15Wu#}<%OTK;Vp^NTz$#d2zL|1}7u!Vugh;gON60NVg2 zL(Obt+13}<4sUo0^Y)}SZ&OMdmnHuxktSHz?_?Fvj<2E((oxdn{+k5xky|>Wny_|VV4&hf#O|qGpnLAUp|JCi_mr`8bwmq1_ft{hy&kvzmxtcOC z+Ac&WR~mM8>2Ii?UAYK1#7{GxPm7;2$2imnqL9eQQTWCc`VuheQr7TGPre1u&+EZ)K#vAux-aI`^z)E> zti~67n6|%1UQ6gozKs{tvw#0y?ko#|Td0ARnio1I&sDO(PA7FBfb^dm{@?P8b9fnC zY;3*h4CfHCFRtkaZVmkG(qKP_`x$vC)05o3y_^xifXzR_!WK4(D$8nzk9w240aKqp z@5jG5(UbO~G2)Mz&$P^O+1RQ|GUA_|@BU4z>WyHe6q4~`%?juD8NKt8d=A=&NcKJ; z6!o=wkm}v{={;)KNL=Ok-y)6%iQLO@Ni9Qq2goW7(WQEgapbQ&Q2pVV%RF!xs@E=Z zC8UC;jOBU88tA>XVs9O8^NN}tv6syVn@JVcdWv1@P#=!izyvD|lej?i1YNI`0fjUH z+m8`5{X1=mUMn4uvdq1qmBO_dppPAc%K{1CQBD);2*x4)2w6j5r$YFm4U z9z6HAMu0+syxYLL#z9t!%O4k`7C5kFJ(8=?dOt=dM@@l(yeT>~#NFKb`m~I*aUcGg zW^~-2ce*k6_MpClo5F>PMB{!E>r^f=<)h&I37XMUf18kbI78ZzM@4uzyfpzWEsrp7 z-RW=fJVq?om$F5Rol+S1{=El?eQ9-7&B{|g4sroLcA3ftJR$=#?g@e4d_JbylJajJ+Bd{Ql8SW z+mHzA`X)SZ#Y0}$?%kNH;$}#FO!?N-N+g!qH7|mil1Q}(w?j8$igBVp^K5Kv z@Ia<{V<^*LeM1H!frW*vX9K1@MzuO1tGI7h4+fHtet7NX9`m5mgelN;)^XbBLdEYT zRm>}I!6frh%~(>Q51Q@iL9@KI2BP~E(;3T^8Rg?-=viByG{JYgce&xcM#9p#S`N^V zf&I5UNqSB=$P@PmP$N*n6kKOh1j;s^G`6>z$vKo|?6l2sP7Z7q&OHgW z{_pN)LZ_;Gr&SclZI6*;qxqp05uMURa1u7u$B_mjKGO2UF=fRvxjA!0AhN1!q8*fP z#7sAmccOOuNr~K~@N1vASAZ}jZ*1CCUe`=3qorPnRAs57xlI+#B#-ZOta%56p?Jcp z1Et33D<<-3+Tt$NjAV~QHO}(FndwBaTW6Hds6@4Y^Lw16J(L z@89E~kO7~G%>_CZ0nH}}mjO3&@=xWL&U-xVVP$-C0ZdYl9(TW(TV_mn7&Gzd%W_+i z$tgZPlVJRy+-XC-`>@s0(MJdMT9;Y3EjU)L9>w0%c_O`f`&kwhd|-XI8M8t}FSOX! z7wA9U9OK6^aU(e#5}FMSF3~q#PW+M<7_4S`pP}50_m$02b=-{FrF0@iNwRZ$cK$Np z-nsIa$S~HPr_WCWZlk&Ak3F$x)&Y63WlspvpL>!7LxU8kT(Al?f(cA5?_|D#Rsm@g z1u`LMFe*C=xa6TK1~*!Dus)3`>>Jj+Y$Br;e z8MPokBQ!YIo3$&L`n6|pZCp#UT2d57Isw3JMuB_#kj9T3&Of$lj7;0I)J z1^@+=wY4<|Kp()<8a!bw12Yh2eQZ0W+(%;{`)(BQN; z6mF)B0+_#fDmKgy}+QL#@(tuBqC!I6lArR&xM8#K0fq~9Lk+uNzvr! z!basQWKjH0L1|!qJGa#(TLNx)s7C`2?0jvwxHb z^2t|HvOi^iP@Y?iO_M9{mQ?aOyeD61Ky;G1yp)~!QH3^LSq{L6pivF*ptJ&RObH6Z zAAZ-g4yB%KtgK7m9$p6{dP$9_s-=!ykWWL7pQ!Yk-}@!lh+Lx^V<;4PmvlNbxwSj} zhh;t^Y&>7D^a2qGA+ss8NuM5Jly_TH+D28#f0C}87SUbCf&FZtm{;@)yvc81xVCxX zg%tMSDg1_{?bKKiLl*TLkR;*%HxY;=JsF6SFE`VRp8T^}yDzoa`mR6{pHWNXE6M;B ziOl*?Y&_bR_SCQpd~PXObqbIzI> z+m@3_T@)xWLqXhXPVEL_Xbb$vFmI2IkN*l1W=a)8n)L1srFXmYxKWd}I|$+%e!Xg_ z4GQNRg}9EFA@St%5$)NJFn66=-#b~A$oC1FxOR6(L}aUYIn%myBfQaqA;!=Js3iEq zfL_JI%p9Wox-sv|p}#-M)z#VOW0>WRfaij_Fl#CNz0nnV@^AXarja_f_=-Z`CsuKr zr3)e1W0gkZQ7G?pFY&u^5!rY9c$QI_>sU4%UYDmLGVq_=El3+CMA9q3AX($OqlqFL zeMf)&W-GOQORV>PW9Ta&@0m{oQ$5_|n-{ORaT~R4E!XWCy)Mbi;p9)(L@F~5>rDOP zS5NX-Ml61PAFX5{rAyBr#oz0#^MBgSX>Rw1OvZRj6fngQ2L|&creqSQKE&gZ>NDuvjmumj9xGH+61Y9z`K;vDrh&$ zXFib92{hZ8Iy-7$r)+eR8<;{{l3P$9==cod`AHb=lbl%AMClo(W}U}Vn-X#w8k13N zIK?BOrv=Z4&&x{-5el!v)1@QRyZw*rJYp1BY>V08H)ZG;^WeolAe|k|(yPB%p>pxv ztDX7-G6vH04{szRyp7O_#6T(?a=xAbim9Blxk4RR`Qb*jO|7mrl_mZfgN#Ks$fj;S zbCl2Brm)@(tMe-0!gHMorA)W7dxGkP#(N7go;vRx1q;dq*S?|%g{%p<1;ZD@JMTwM zbtu|{nNfNbF=0G$d_Up~__>8VkCYzT|7~{?hL$JJTmqr zp#3?~QS)1qfH8Loc)>qmdWHl5gSlmL^TNo8+{doUriAorSlk)m6(Ac3xhx|a{peKNI4DgPgR)q5Fumdt1zEa3!X)r6j6xV zc{cT8TQ{8mRrcCj=o!c(k>0jZd1>Zv-S&yNy57tNv&6`p*gP=^14N zVx(%{5I6eWR>wP|^spf|WBoT|Kg%tLc<1I(u?=4u6O_K2RZzPg4-sr7;79;~m3DHI z*z+5vN(U>*Svdo(^T6WU`g|UND@kq61`DmyAuY$HV760 z(+s6{mV0s{VT|WBM`_!{f|m?N)`aE5&6??&(rM;Kf!5~1KNz2m<}}o}&;N`F?2#nx zzcOeVW6S-Sd^oamAh`X&=kd$aEYrHa71x8RRQNpl^7t;tnqcw(w&&0I=i(gz@Qe1l z2m(R|s3Ty40F>atMyfqLgI_@=f=i2TJMT*dTOZEL1&?UupVrs{T`rHM*Ez#+?=p{< z|DI#EHKY=lc=GO)!ly=;`yBINPNN>p;WC12xSI!oAR6nX^Pfaze%I7{y-TX?c5ORu zZMg^MI>d8N3ZSb5)kivx2{{6K4Ybya%gYBJke~!l2py?vBmla!R++T42+~ey4gg_e z>q~p&NrXr8rpH^noB?|9cUh;(DgXxxvLp3YT5U6LJ>W-|4q6Hb=CHq^1md+0L9 zhSIj+OQfxO$h-Ypp$g2@M#cIKVSDE3Q$B!~ysh7niboZZ!h26q)Bo0rk~pya~rOXXNP<%)brI z6O%%}+Drb8X?jQWxqLR^{aax?zlSnkv4ZC!fOo&qT$9GZwOJPZ;OedH^1{Z#`7hdE+MdUW8!k zgY>zC_z$FbRXR?Zs_M`MYZpr6Vp&xq8Bk=HFo@@ zRMk)KtygUuQbnGnGk^Kv|2fN;If|&cKQWj$%IjI6`)w<4>-a7psFD|PT44`PC(a%zkk004)=NrVr!{WGZH7BA816I zt~yGXv{X?cQAegnA2frlswnLA0@W;*l5DOq+rRzz{I$FRrFx)eaZQh)fV|>DlIpQ& zh|ze0A8-wK<$Jysh26vr9Hy|Q4F=qdq>&K=a$;XM52tfaUmsHMuJu9a@FpuE;~vO6 z79^2iAd$d-kSZ*Ysg|JpBukyGeK?bsjQ>UnlL@Cr2j8m|6HC_Dbsn#s|GWJ`Y{ZPX z17FWb`a$gnhk+D(RSnYAg@CWiDJ2ektuc$L9i$nLRhM%HaA2URy$smo7z$zp(%}F| zRbmZ|WC+m#ji%H=45GHnFp>2OFQ|vZ@@zs0u`V|H7@(lf zMn#CXnY%Z8=?W&Su@3}q-`(cdmt!tkR7NuJCTnl+oM^tZdxSB-KhR&iTRf-R#*Ap zoh9~!QaV|&_{q2$ASJJnB;=J9V_N}g1i}fdClQg6hi7L$!Q5mDV9FB>gXOyx<5m>3 z#NSI>vm5FZA3%k7GYbFb#?@X!iP{5YYB^`=HuNAhBg>E$mxS|2>bUpNu9Q+vL` zKJc;hetJP^(Gf@4-C_rxf?zYOu}aZSp;!kaGfLv^^NrH&7Qz+4lA85?xW7AB9}SAF zn!0*05X)#q-H@{pNHC7eiD6{v(0;wxqSzQ}$grDk^Cn0?er?ilC^)HI_ESA{e|OXG z-s4ldrF^r@gI|>8*<;qwETQBO1W85a^`fjQ1nbzk$5~VoYd^PogD&L&f~ta|;#cUA z$;d)pm0KJvbs)*BqgCK;f%q$o#x`|csuMoSLa^CXix3V@=#?3KrS-jDHh6pd=WmKP zMS~yjCBd)U^FyJP=F_fEV-L%`v6R=6D@k;QM2BYH^;TtPPX%UbwXk8Ilua%;BK6hE zt~O%K+}b?RMU;rnU+TXnDk62q-@{jUBP&Hn-diLY z!s9nBKp_$IUa6Y4z)9e;>al7Mk7yVU;$tjCzKOkhMmL3Dw5!~89;IyUOb}IJk*~RR zXr@)5`P+tC+NFXk{RzD~0o8;y za1=7T=`}T%KfJLPtu|8_x6_=qaNi{66A%wrC1P>mxmtE41i}%Q;CU%9q@k|T6lPQ= zOo4Fwv_`_6k&fVVs+j&?tJ6-DNff6Kza6kpbEdX8NciPHo3tvsT=kw@IK^h+!P|PH zY;G5?9I5)iD8BEPliO93rgq+Z9pT;u{>}G@k6F469(> zAWFWGXd|IR&(m;3ZCe-4$25^1G>-y4*&C~d+PdAatZigmw(q3ZRE zNL%=qz+)?;Q7J-N$MmyG-u>3rU>&-RQ)AB=@99ZX+Sl}RV+WB2tG^aPW^e6S1}h$L zr`p$Ln$84#V9R`rk$vOY%{@ZdAKfTtmwRZ>TnI=P2BnXY*cI{%a9=O+h|B z39_)`|I$FcT0$O)Yu&L(Xfc3Ro%%TH55QZi*&Oex0rE5zuenlGuVUOcfK98;6%eCG z3n{Q*rOky@ikhD0YxOuh>RD}?dB=U(%iK5d#``j;|MHAcuhO0Nb5uj@xAzOGs@$73 zB-*>^e>D2vtDHvtR#(P(Ku|!uZDXj{rE>AkOG(3)np5vxO52w4|BIVL53rIz-xZ0- z2GVL+RMb5#u4u>v!?p`#MFdtl?L1Mtmtc=Vj^U$UgP(an6C*2227}^I%wDyq)rH$S z`!)95uF1$#Ha|R%=ry-W+qU0qDEnIf7$Qnm99Xq%mC@dje$Gt)aW5`Lzdz%{8{aUX z2F2CN1`dCK8@3PTh)6Bv^YxWzBsrHk_^evMT)*ie0)pibh{j^#KcIN^fDTKA<5OB20-FI`4JYSy3*x<;!Nm*rU7tHCA#&_T=oacR0s0ps5+6g$-)=vc0z7#yj$+_njWPVG%! ze!g9Z``d~b?wi<0)#-)wbS_j{?ky{I1QFSv05tR7)ZynRf+)WZ>FP0>@4*nEMXtqw zN(lz}sYvC%62`TT+vE4eFAg5V5B2Mi01L_cL?C!zm;l(aEvGIp%JLwI?MML&z}Fq% zQqkWRE(Qyt3s^2+RrH%gi+xABx*+Ue0G_#5a|J}fRENBqNL#CB!Mlkf!{MhFMD8hT z5bsILVy_eH<{J~8-@O+0e#~XkS(uvKvSIUD|LVTCw|+>8;K9#WrB^BAx9qmY>s#-8 zPKaBy0e)_v8#trDTLt6CFwDbnyMX2DhWyZ{`wNQDRD+z}xFqZjzy=kwpcR<$Au-WV zqk#o=(~;16SlKp8_A4G&i$BP808O^-hR=wrB*M|bEY^leTW>)1^~TrchfUr#0;1*X zVL4pPJ-t2wzp9MKNsbiAD_*sFQX+6=G)1|%X1Y>>%3hnc=5N<4%&hF;vwXw!kUpM% z&dSLNzUdoSKuZ9U26WdbU<~o>Kz6{u;j+K_JLKmCcsNa+{9PZE4}E3M4EW-4R1_3X z!C(k8ORG)zKx|fgM8E>@s>hd=`8ri+QGsCgqCDm0^ANjEeMsw1J@w|9p%G_Qwy`_w zg(rKw$rc7k#0^UV1b%ts4m{0AaGhpxL&1(Z42=v#b}_Obp^lgF9GJGo->~zQ(-mNh z@_+;BZ3Kck%I0WZWS6Vmhpk5tbi5l-G|WDojw@37M8NKE<)1q!ua6D7vlx8jEvN7e zij(J(xLgukg&ccvSq4cC_sW=#6m4s6@fba_C!24iexKfdUrP0XfdP{q6V*ez=g{0V z>T0NEJ3Bd{VB_PLR;7R#<-c>>ScXKmAESGn?LUKtvm5g^lBGgi^_C5E98 zqcV#TRY+w>x3sdfQSqK(46PpDkN)(O=&Sp+)EP0B3To)ro`CT;Jdq_NS~TA*NO=qG zumxWc4Y;<>ej0na-lX{6oV4=D!K<+hXL)5bX2FqB_8k(fy+4PvUt7_ZXii;eVLqPN z%6TVi(pXh%RzK$n)=AjuM50q#_kHek+{^e2@6aQ)b#5pt=Juc$jDt6oUOw(4Eeju> zNNGr=*zCdT{*xLVF}%pkm1}A9;jV^IJAJt--){8pwgx@FJMlj9dZR{YDk=vghgDQZ zzKAv>9T6XocJO1II*Blzh`m{&+<9WeAkVasg3PZKI1EiGU3R&V z^X%Lr^Oj?2D5!yyUfBE!#)mEmt122$1HwR-GLFgfchoPK{;g+t?-%W<0jP0%j1#^3 zvH8NXi_;o~FK1)w+=YaZPJ3vJ(}L(t@rv-%t%3%xJ|4~JhT8>WwStM7JF_Va_kQ%h z6eVtKd(Ow=98oDU#2KTZL5dUp_EgNJzFmS$gb}ba0>U$oycPXnvNTTc;@U~*OnhvE3QMJBC ziCdEJE1T^>1x$tCLqv>?Fcz$Cu{ zZaWiLT~Ld#DGeG1IqcP3D6Vw8t`A>)zwrYCrZ;bt-e?{0UE_KOi+^w3rRM(_yr;kA zB9bxZd->tkz6WON*Kh=@rK^P?!nqrl3MVZ>XDf+a<89Cu#?454xd&~*`g|#m$@cz- zfL$blWvoq>3ZZnWbZ;;%Bl{#E>AjO>1SnpSYmc0B z400SCcVOz_;P(IL&ObrRdMDEzd?Sw_Z-tB=z@7!TkG4tt+rQH1vMRLBqh|>Z+wkuz zVSA;M;S6u_mDK7F`Of80Fo_EO{u6tW6n$eUqw`v7)g?~NH1B1wgqSW?qT6}%U>2G_ z3Z3)Y#2U<~V1F`=o@@ z`BD^5Adeqp_{^H59kHV7u2=r5b^GE84Afy0mPn=?;kH6?EX6FtyC|0G5i5Rlj6dMq zg1hQDZsuBT1=ePvM91N8OhiP)L+Jm1kH|qiI;p5HhAVA65VT|mR;nij0e149 zU>pefR>LUL-W`fuk0L&}yX42iV0yo=;MwxOXuq|5euK)|9|^n9(b8pu1~#5(>ixot zms0F{=m!}Lm=v=;0&?h6wzO_`Qb0hCpP92f8|>^a!o}3oWh9J9sH# z-fnq4ir_L*2Ff}TtM9#g4V98HKu=MC9S@6g609@5!H%m3e|KkMEQkI#)OlVmJW`hO zO)}`C94jrQ4fm!^s5>zGw90<}P46q4e)6Sh&_%>CusPA^TZ@%*m|`z8``WIOaIwBD zqtscqWF5=8p`-e)m!>*tj;8LiZ^t=bXgJPN3d0$^^~kMpRn`-1Ac+8l7a5wj8q4Q? zJuehJRQn(J_us#N|BGEPqojVsP?Vjl_F!g4hO|jPg;756;J}|u?MMD;Z*^Nr+KHfr;2TIIh%62H%93E6M2^8bj)ZY09nC-2f`@4qpf=eV-D@jAgPK@Gh z>W;T2iN6JFw6?lCz3wa%`R^COAzwO$lYq=y0(Sil@E6#V+H~WXz@FCG`<~`?clN$k#T6+XT?Z`YtaMM$rcBE5emvdjdgIa;&&oEvS7j5DzLv6| zu5W2(+4Zn412Ih-t7f{M!@;secDp@HdD$4Xo?fLZaTuImjjQiPr(uquTmVYZ0?dl0 zt1WK97D5&v92b}W!<7yieM*$nS+|lOK)XqDyM3tB-LZtPr|8&GEP_CGPv`Mx#xgN2 zc1`a_`yz2nj-c64qLrL-ht~yY0tH_JYS0LBN%i30 zE9>!bMuFC0fnB>*T!u?tVdmjycO2G1In@qx=e&I@@)gAb&9cK_8!s87(WKT^^|NQH zr0N>?800{OLK|nm28zAKw5gpwbFZ=a}HNg;srw+Jp@?1kX96^h8I{8Im>Ltx}l!*#)#l*WD5DxQ2BCUs$AUoy|LcRLaM_-%YLf>eU@M@R^a`**HZ`qjrB(q-KX)Qh7HrNTnk=u39@Zy-M0G zmJ}Xrtc0u*){L9}*9-TA7;A2dHzYi8zkZK9P2=>I`woZ)cT;cVMNpVHvhE6}4_%F4 zU^Y=nSzdu`3A~Z5@gic#$xI|3!$vFsxxpX_0yEZtMoEBa;4!?PV9=F@0|LG!V=$Q` zo03QHIfQ85%a$h%zj^yFV2ilOVNbqsI{id6?#JXj&o88rHJ*1RUp_MOoR}yJ z12(NnV+;^g4WWa210yGjDA~z!gI~%94A>|yzlV&7zyr;A`?ldXm4EIJT>heduo*q$bO?`NhX?d0yCTiNA1C6v|Nb&vA*)nttf_rY1$9X}3sER=52hRr}br%}L29scQ1N?0)Q_Dwh6FSmf95l(Y&W?=_ zZ%ULgB+^3`N2I=4kTBTPTGmpjYb^W8jBOQ4DATQqmkgym6th{cEH_yF+qGeGa`>17 zU)C-3opP~Mjw41zFY_09A|Z_g+VCO*D9GE;Y3BoM-ue#p zKf1~ehZV-JTEkaUjyhN^JU z{Ppo8)&&VgjSgd16+Pp}iKJz_w`CmeMQZgmt*KAARtu?5rgvM9+mLN1TVi^aC>zw? zWn_fI&j7h54vL;t$Rj{xcnSPia8Oc;dGUcnV;?7vg95t)$&gMr7y+9D=mz>V!&)8W zEac(C7R6g~AQ~ibd{m9yJRl!S)c^VT z)f(OMbK_kTxeO-9&J_va`J!7kT&ZC%LwSvH8k$alZL_w4;v2cE?4_o1n$MwJQi@5|n#NJNH8FUs)B zyp4A_8@(koQbsL5k{&aF+a`_~c&Xo!>zrzMnn@nq+q5}8dYkFl*2^Du1;-xrbqOzr z-dW?~U%rY_xSlu@Zq*2K6`>P#yD6gzohzP*{_2?>Io##2MFwVes7Rs&l>5&?aDmlZ z@EFkj$E^>?95V5W+&#rF?x(EWH%%oKr)S@k_~OTgp=1M>j!ahjHdDXc^C3fGs7O%0 zS&-cYT|0p!T2+2ZOW{}@%thl2h7|4 zZcrl~G02JA)ZIzgQRD!p6H0b=HmqP1q~NnuS+LQ)0lTW!ASDf>!2{4?2`M&bTly{e zoM318b@X#jy^( zxUxBS3QCNfyV==1VhH}BH~pjO{QDuXFzH3(b%AGp^Qth3_Ogc;!;PjoS&ikR_se>V z+%*1aMAQbqI5S_4@Tcm^Fv^>fYFp8<2dem3ADl@)ez)pj4{<+YVmR;{z(wr=L!rLB zHRQD~?6ejpn(7A14D73v%z6G6Y1=>ne^`~k<F9&QVvi4HGeVA+@FT7}*LlqJ*kN~-!W(OGiwN7aLH^_QNpzuNvFXkUm&|ne`UlTVFt>Dq{ z1hwek@X!b>swbLO&jJ5-!vU;~AnWV}z0%Yqd_+pR_7(qfZuyri^6~x6W27jtO>QZ?p};x;o@g+zV~2kJH(% z>jJdEgt^07CD;w+2UE$$D%b$ic+V{j5usV!0U7yUHj+89)5eqoaoM^kD!)Q2G-vv+ zwy%dpXg_G}LjIBo4B?dFRs7Orn$hy*_i~0Kkd3XXs(P5>0Lzt9?9)R=j|3b8r5>@3%N*&<$8(OW)+R69MGkYR^&BxK4%AZc+{3B#jfh~UBg?dM>4foQ)% z&g8QL0+5wvN9_v{2$-%NayOFYT&cJSHnS%&Zb^AcXM1-rFog>VdxBX$@IqnPN8?Lx*z=hQ zD-)2q5{WR3M*%BJ41k5R*-1&*1L^_(VrV0g+bSV<XSW^r2IlfQCG$*9g`Fv?JR)frcd zvet=o_w$+vh$80+jKb6BCk-0EhB3%h{C`n z&rP8hPDM+A1$$L+!A%YV=A>?(7(aAwi5$A$VY#`2x;hDT^^mlAi(FJ_GszBV%F)f4 zR*YYxIj)35dJFN%IZZ~a__AKD1oCkeh_;sW^IN#<^tlvEQh(+~FIV@n3^6-$1EV5U0<7@RVue*n$VqDiO*tuga)cxaY z#$y)YWs7bD;xEV11B_e^3Epn$%5WAYJWOQfn6SPFy8@}?rOUZ8PZe@TU_!S!#~g-| zlTlWBG4jgr_)$kSoY%=s9&7PYS`TKHDmazAIPmuARLg(ba>B4=8%g+qWE{9n!HH#P zNDt@@S1yH<<6}nHp$yCLU?0z>1|&n-#>Cjd+V-Sl+DVlZx+34tdRJE%<`)l>VDBe) zsYPyNJ5MWA+ck?^q8pR|ee94vJGRbjY&rjW?V!tsm@MjdfQ=%oulVeTY@O{_*SP zMVQScdCsiVKZ$7yz7ULh@wdtauJ!(WR0n7LFt3Vb!pTuyZ90BL74>~VCTE2z^N81y z@(#7~4hr{o?d0#)I0JeOMN&G_*Nyfbtr^vgg|3Q)@0jF+-@Z-2lU$m;@`kL+D@uR# zEVdi7p`)DRLt^qBmg6~7O&ZbZ$RVq#-mi&O#m?BrrdhlI zt8d*oB(l0%_kyw;3S4s#B)YVwq;p!1OgD`=zg0Ynk>4lcbNoO?W!4fh`!}1=u`)TJm z1-e}h6?2liu*{2Km!QGkk_8fRH%0K>WX$?{Y)LdY2D~*>>~uxu-m=J-Eoj>*zeS6@ zp(Z(In|XJbe!*gKp7vz{{Rc=Qfn2J>d|i<@HTZhI3;Md zB%kAIc4GU`FKrlST&>Vi*peaHM(Ub-&yD)R+1uvh+B?P{r8&*Kew?7D8tZ?X_Upk& zq-G3cYntx;M)s5`DGDGnCd1GX><%R=8*ro`rA}Bsd;p{wCs;u>QB)N;Ow)tt&G;=% zj6$i}Tr?IHs44qbN)_Y~Gu_uyuE`Y94MfNXm|TU6+Fxo_+c2 z)rSYzCq^**CMQbU&virKk%$pF^RxIIh?1XB8O&n=L>DJqC>GzHN+;CDyaUU@0lCrVL z<2(Py7Y6`NpfA0Jy^!j~=fYVP!cnRbyATp6V|pn~P$cR#)%#E598#jup}<^n;5GR=b0y z65SVhVH;SFE6ze;$%G>jpK+SiR&&HVD$L_=q|Z3KRg>1sY2H^vGb@9c5g#J6a(r$7 zYj8COG1wLDx8GWA#(b{ul->v*8#mCu;a8YW!mLiIYmuwn2%@%j-_^j{hC}@l@maIE zfjkMJUK$p7_ft2sB7IEo?v82d<>LAI>Y$Q&RcvrD(^t>)l*E1@FY&}DTMP;hc`A>c zyx9@PEom=xSUr;KDPv>!Wc>$?YN&j^C#l)m%l2{Cg7oKk-7bkK^07DmV%ddV6cxOk z0#-3sks6l-(ky8XXmI=4PFG}gts-;V@cs&Kd^GuYt`hjLgf{W^P{W##bb_-w?W6|Z z@kEDT zbyIvVlfJ2JY~#pSK<4wwd{dAd^{+0oBTel#%nn@_YWTKO9r z5pl58aPe+~B4=Z6-;SLCHH;ULqB8JUoTrUKmmP#08udWF2!+@G(~bx<*nEDMI|hxw z-o~mq41B299TzO0c;H@%5!9JYL0TCk5n8puHxMc@oZ+QkZhqvk>NB6@_F#kYvLEp; z1yAB1R(Yl;Mha%Jn`U)ZLxw?yBSo^j8;UGTXDq3G&X=u_r4@~wh`>W3ohK`3A|+g< z7Rs-5%6(bl*<+JfLq^W6ABu2t&)?qG-)jh96=#zt0{^MR((z4l#yqmrLR$9&62V4o zgT-LXk7nT)=ntrSqdJRI^5ZkjEsP`5r>4kPk1*e@1Z8alamJIJ&e`m3*Y76kfD$ z4IAkdS9U0AKXR6+7xTPTum78m(;JOh{^tUI-bap&r4=n&{kVsW?*Br{UAZ4^;#+>; ztBXzAZnq{1cuJvToUckqkgYD~5~3ZkAnmCCz+8qWWc*A0(+h*KXS+`1{x^8a%GMLj zZu#dEVOx5h|8go&&thJ#L%l7 z7(Cb3rUYp-vI%AkNdQVf%ALsVvNyjy#`zNFrX!`6f$c{F6Qs5Idu=6r#&OfND!0Fp2lQNg(k1MHcAN*Lvc1P(~ zS2R@odaib?9~v~je@YVGrBxx_LvCn*jr9@#{w?PDEc#tvVjVdIK3oxIXZGc@v28#* z{rvfUNA6S0h<8i@5}$4hvrlC+AF7N!ev~~Q<{FW7Y_s^uVMo0!S%6MsLRAU(Rc6G* z-7Hp~@{)x<`@yvL=q0mikzEBjMP3eCoDHN;4lWRw_#AiO8=y$_+PuehGqHoUn)s`l z^yM#{Qtj#x$adA>=)9mf^GmDr5-M#cnW%euM2`_>!;_ z3>H`qqwu{XG!A_}A@oR)G?d><@-C;7#3w`g+1>Pk$fzka!^ZZZ1#0`Q-IGsSpD^Ej z$wuVgwouL9NPmRN|4)%&nSx|}C(dhI$J-!8aWkOMaFzwmbwIR#1AjSi1~PKqi$oyz z;U*<@K?Bp>*JrZW;(4)r%Wo+=k`p-}LmGIH--pnqjt|?9$(n;_u6QT=H;Q{SC)YL% zs1-bSnsKW}iG;G~@zfls9b{r1zflIT^6;O1&N%*)dvz0qhZCMsjaz|bSvjjGMbk<= zFKI+$8^U&5(2J8vyni~0#s=Kat!X5Y z>*r|O_91!nM3n@Ra;-OPis)}L*h`vdG{(o7bDit7yir{wDa%-(%iJ&PETBSdryV|^ z&)NyL>Ala~2*A;yM*G}~ER>RmJ0Md~MYX%53DqS%mNAR@|sNfu3OqtviJQ_b>59|nrx z1_6xJ$>)T?hu^jz`LcVgs)}d336QZU72tX<+~FX@ErS^f1)uuCK6$0;_5v z&|!F>JM8E077}I3)c!P8oDY27(|azf1ixFg^0Z@xMYw9kOgI`Y19c~2O@-MAXG%7f zq$f8$vo)^b|5i9LpfpDIYF!LuqU2btpI{vPL(?J+&-lleWtf|jv$dDB%`8Y~Pi!^! zWogHqFa=#ch-Yr2+SJhBBn{Q> zc>O|4fAQPKtU%plZKYFYwLt*3WaP(8R25U4_`4>Rtjj0TZpF#f?`irj!jrqJY)QIr zE?#^7I3bx(LcvROIZ{wwI5ZOagsvX-U6aeaN9glV`N|2_Fdx3KF{>(zmlnahtVW_( zjwvo<V`_S{NjWX=G3ton-#gXv9oGCtwQQC|C5!rfbt#DlDR&to2cN1p zbR83xJ|pP%-|4z|Tgl(4iub}jNw^4Mhr?;fA2>2iA{sAuFD8?WZsN|fu`fxQ(RB6Y z*OdN&!_=*_&kH5c0#Kr&qH^=|vso)&7P;r{4l$k*Q+XuVy_(dNWtmk{tmeIccji-0 z*{jeKvnbo5*9?RY0Me7)(v9fE#mz1&ba7&eEKW~GhgYdUQ1V6 z3MH{PXUUMIDu&NaVQL`G>!E`xoKhsrU{po8}#N;O!+DvhY?F@^aDBlC?I2g|-H-KW*H zT-dH3*M0XSbyoN$$C8zJnBxPPD8S97flATkTrt z{9}-L*L4y;-77`-?`a~_`vH05!9pNUbUGWq=1Jsy(Qw8ho?R8t!(>vM67{Iia6w2- z5Kq%g`@1bq9C^v@pMTo@2zGicf^Jrm+peYkT4W#`hT8tZmo(ELuW^7vz~x;1s>zxh zfryPAUThvw=V1F^biHL%R!{gY42nufBZ9PaOE(D864KpBcQ;5$Bi-HI-QC?S-7Q^b zp5OnRcfB9Z`NUcewfF4VGxuEg75w}&A?sXqbHDq_WR+Kzch}@lT!3pj;XfZ5v8`@3 z>?rL+C6H;yO8+4k4euunCMoxto-Bqex>>vr=u?pq6Y-NbU-^Ks$onC^BQs{s%u2$~ zsLr%+xixe2CS>&wU;4)78zU127wtwQtq(IcD`Il&4zgq&a=$Hun{S_}EW(k4#oYA& z`HPO8@SJ}nh5bg-VX|@Cymw`b862phC&!^D&e|6yO%5d*86p;25g%iv;3pc9wC-$A z-Dd6rHA9_+n|oP*s9CJ(_+|fVAHflJ!*Z(?R8_)?*|N!VW2J^1VPb|^OSP469d?jxt$O{_*!g{^+aIH zTyd^uele7QpQ=K?bJ6?W~e_1_X<%Z_UEv{8x_XVrH@!cQy-L||F{Vw z+?+UZ*JCLllW`l>FY`)Nc4JT3QWRKjx2X*>3^2aQiiGmUwsE=5EadcP8_ZkED$0h{ zKrvN#(C>bm0YWY=fj{JplZ1u_9%P9GsX%B~S69Gq4_hqq7JTat$kA|DJp@qvgFb&x z=HLiMzno&HqmQx83uC0BVAp_=&#KQS5y7_{em79*i>p3uGK`09D;lJ$e$#46WO|K# z`AsCHBJk8)E36RPmRq=tteyU&M4y48({q&oFMaWj5AAmTr)shov znFF_Abf7}}39G@XSK4?$wYca)SM3D)IdZD1gFs<11maD5fmT=wD zm|0%kUjCb8NZ67h zKJv-xkd{3K?hicM)>G)?qAYCe4qQH`rAI~5mFwa7XT~$}PmAm~{mp-O94BUKzxheE zEy^+JkIje@B2Ic%mjH7FYPHVCnp!)2M9>9K=7>t_>w>)HdpM_U?z;CHl{HBel(izeSLdyLFKtG!cUT+Pl1;iysp62P6`pFcMGGd9MI z|44y>UKqu*cT6uxAD+2&@9~M}DYZH^*mm45URD=R8Vdd-Q(m3BAgVsT$fkq1CNg7p zkf`zQ_zp#PEdWjcoI)Y7&N<)XUO`kxK;Jxdd=BZQLV-%0s-U1C#iH$YBN+O2D@yvz ziQ8vfmuMF8ALr>JEB&_Qv1hQXRsV=CgWnvYSfp={*~VUAg0jT%40;Gh*0mnV07YL_ z7f)c^(C9nD&3B>8=U0>Y7)PpkNsIT2g@=j8##dh~)j5%hI7}GwN{wX-Y;dkw%WH~% zY0Qk|FShf(tI%erMYm~Mfv8sjN*D!6DY0DT_PDM}JBO6Q^QW$Wc@IoPzkw5G_U7wwd*go+F>p1jR3(&$ z8H3E+2+b)9`p}Cj3ExfCNRpAV%ai;4-X(#1K4=ceyk|gpN1j%j>ZhiZUci}XBENk7 zM*bCa=#CmEFC|_Jq=CCG8caSiwvn6P z(^W`_`pVYwMsiN2Wo#g5<1H_(aeC#9=|7L?zxQd{o&5QEdhf%ryKGF@O-I?4^1TI& z3>BkvG58cPuq9>dTMpQ6-N-1smWp4(9~<4*(>KoFp4};c8dcm7=g>hx55D9bJpPpR z%AcX*u3h9GvU7tUg=&h|=K2qDZr0IicKkyjbW@;NVE{JMywA6Kt1gGMyifn+AcArU zGW74UH0z*rKf1YtPzpi&vGujZE||=q-cEMf2yEf3Ehq^5+U~?;$Aa-OGCBD@mhrOp zxLOIG3vUEpT#Zu}*}a+@m1~McqwK^+PGwEYnepBx;FxV`v-pmGkuXY;7B!0Esv7Xk z#NsEfzDvO^tWT#<9`0?HiQ$V{i_tyokub>70F>}lk4)yFk$ z9+2~0e}&zPIf=t9sUdhpv8~85i?^O%earb3-fDX#iOz937EAPpoWtWXQZEi=Q>2hV z_zX>CtN}LR-ed;Pt?~p=`y+pn+Bo#@YJb(hSGYb${o-Hv)=?V~X~@|fT3*snz~3in zEV(y4oaGvN3T`Ia^c2y#xi?iP!j&N5gYkIU%j<@JJ1r;(5TUfZ!cWjx)i~L{24X@i zFCdrsAv5vdo&|Y?z;dV^LS9`ZTK}4G?b+W?JalXs6y}Fd?3d}Zb>0#a>!2OufLt3f zySje#PoGQc#5{d1OnWX+c-TS=m|sI!n4Gug_a5itY@SA^yE(b*F0ab{J9o{p(h~FUObmZRK=!YWX75AFr++);{qg zcxY36yS);R3}Mr-T%`WDx=zU|%0Okv#+5Z!G%_msw~Enl+FsSFG<);VO5B602}j+i zaWrhPRvWLre>Hsi84>@hi5A0#l0Alyuo4S~%IEY0ijFtMk=evz@R8Z;m!`@RjGApy z?u0(%HyWLIn=fzqyw_H*KC3ZaP>PSdY2S_edgEPc`!b|uy>utSNXPW6BnNSw^$_*f zk5|bf_`?S1<|Uf5xqVE|@*B{+O+Hy{r+(uM#2OTGB~2XGgt)#yJnHJc3V{&-aPk}U za=p%$AASW45bD=00WRUKTPyyqt3VxiA?#fx90k6itt@QYfyGDo-35AygtV=l=NW%_ z+co@aa+cBIt!Q?5oY01J=A?x4fnHu-JgwjCQJw1vy}vbeG;lJqUum#mR@~eFz{vVq z&;uSi0?ZidlP(xN8sk0fe{S-KlDM!b+PchZGwxsQC3L`l*EPEA7o1I5;cF?FRmBN}x zY!ew+hcp%**Wp3`zIS7C{7zLZ%dx3OnMOm3V|s4x^=m$IUeD)8O@bvg1`cwPAx1!6 zeBBs64fglMPkP&q9v;tLydFM%W24$ouP7|8WhcnQQ*gy|!GT-YgDNjfa{YFhM4|;N zlaqT0Ryb0>_%0zX&Y$D+1MP?fQKgH6h_I};b@4#9c9lxG>d5*LXOtM+btDP?{1X#* zA$D%Zt+B##&Hd>*ei(iFhRwtIJGq*w$Rk{(FYvH$QuZV`>|kL+w%)cCLXhhhRV5n6 z?YA9p@6k z&EncF7g6S*POB;2dm>c{WX?=)HtT0o?w=>~5`{K!0DH+$Jy&yTI3(&Sn~U_-t5Kw`M@s+gZuT%npv53BoiBm<$0yMm8uoux+sxU-n-8rB?VA| zEIZ?X?{4i7t1l}$UNOh{FN`XFqxDWdD2M``J!Mp?uI*xw8Y2#um+rUpRhzX*$hX?OR91W?ymaYo!fnmRWQwS9V7ZdPR4sXz!5prQ8U6%uo_R zf3V7MEH@{|PwR2xOTO$^T?^HbGaBs)|^bXn9RViH%gc3 z^d$_H8#;6nlYYBoHJ`zW=$eCPqDz?*D_EJBcPjLPN4&f`+}Z~hHJape+rD@Q5w9MO zwUEr0BnQ8eV0~F< zeY;!G>=6_6iCj;1BR+b9x1-F2v!wNF9fG6Zub9ZlSL53s&;GnlKqnAoc(_sr(-rLL zbPZc*5YtsDU{eQZM1qo%h&44efLH-J4*{s??e_W9=5Ti3744aC{UcQobyC-w2a~G% z@KDg{Re9K#%ACcl7Yh=?6^r#->-}Py!k+%=Sq4h@$lT3YJB&B-3gneG-Za!OufW67 zt4cg`dfi_s=$7nfAlYT2Fh9;5^CFKoawF{S_hQKS<|f+q@Se>{J5@$)V)M1wb>!c2 zZPuh8`dMF19*~M%ZeK_TMAOeu{$|5rugf35txHqL33ZZ3Ec$HwIIlms(U?|*1%fMf zb;_SptLPya#X!RqzF@k&z1`kE7I>pDeC-Pb6a`&C+%W=}jZ(l_)z8n*sYNr4@7W3B zH8Ki#&lwiFapJ1YGF|jF7JP`AbaMfjhn(9bnnB4Hi4W}je4HJ<$;l)ewD53>=x_Fs zW&sT1aL3+47$rw;c=3eI@o1;X8);^Cj8aJO5$(PXO-8Ikm$ep2I-o8xR#!wuAFSWf z7#f1Xd`Op0h*JJT4#j`FBPH`qjF`CiSP+F3V`;=B2%t9nTluYbbc}V8b#h;vB7l}qj*g+i^tPmZm*d4z%$~Y#{SLrp8DOaJ5mw+#e zN$XCnrP;vsFrk+q99bGf*Lp^jRFF|fVXX_tjAP>-o<4xnW~rHrJ#;Ftye`)@#@k@#7Js?7~e03JE^@gBG1Mmd({k{I?m z#!QVct$OI7PGEBL{^uMnCfZ*?Cgey>Z_4P~_5Ap@Uc%JHCkyDfUs$XKW*j_fH_=m* zY(6y>PVL!6q;3$dS_sYA*D5hPsQxR!v2UHQcXGBTqIR77{2fgMKrN&LQb8l#I{W8O zZvMgnIzMXP{RM{lndRkwfC3EAg8Bg)*x14XY3$7k=xUMtzT$deX|KQn2eRx> z`?Y(V1B&P`w8c6Lv*MFzW;EP1Nt7yq!Yk~Y(RYEjO%VZ_-!Qm|6oauNPoGD6Mq0t>L8K1AjBW4BhB)=i6nw^P!7rUU= zLqSjOCzD#CT4$ZwhXjQ1e&Gm`ARJZa%|rLwS5zieD^f;>epcGB&$zHgMvYR0=^Hmi z%iOyHmq zVwa81L&T3ol7)+T5oOk`7HttuX<~OSCPr*ZooM{;R;)Jh%MhBewZTrP1wD+3qJAhg&dY1wmmFJJ~hfE(r z?zOEy-WAl%C+yJZozEhlyJ)9EFuRj~Ix}IswX--G{(u!>=GA8tHjV-$OnP?QrXEr50JpcD#!Fso z^$LD$=@kZ!=4ol@H*K$N9WOFn<0vIOE`VyXxx+)B_w; zkW?S;mWW>yj}>Cx{2(4lLS`qb+%H{i&y_~_9j!r(bvmE~ck#8jek9aaeQ$w(dj5kC z6yo_u;oe;qq!T(l_=X+2icUHAuI%pC5|V{m!Ixw*meyZN8oYbBUVazu=O^|arhUAK zd$H&!J6LzlF9n?gNpmK}sNqMr1b2^A-+3|!Y#bpJTb`7;#!30K%w;HS@X8j9LZSgV z-#~BfqT(ub;pUKyVSOAJwJQq(dpZJzlHU8QAKDC*;$JQ$JM|;8T3LorasJxlh9Qh# z`(c*760Ky2He{u&7u!1hunTn-Osr_N`(BUXu!M^*JG}v30dY342!1v)Yximz8u1aI zFYt-xCrhLtvJcWSsp5Z6h(rwSvJzdiDxo|{{{pQTBm0E!O%simb1(>je}`z?%2#9SkfmBkbcZ* z>mQN+LkY0gFtoHsAM>m%SsRN&Ndlhsz8(Q=)VNHX5psQGwu1hfUUgQE_A-OLAAS@V zoy$%vwi0E2pXryX&gd6L6W|x-{x~wcJ}s8uzBY!n^|XR(t#_4lCBSAXYzyZ38|q>4m=D>sCjJG#S_oI8JbHO*EVfo8Z9 z6ougO*jsACxpq>LH;KLZ@IFv1gBO)w6y?5PaXTw};hQPnjt{4JMPh}+yeIjP&VIB# zxft4}?6JCwK3yDM!qEBVq-c5KUGB1&aTS+tKCLd6$YsJsVMEf0 zhzPHN?6bC6CQ1uQV(L=AQ@n~m*IW-|uO>&2_W4;(W;|65kKA3dDE+#Vy2YwOlgG`= zlqb(j-*`xJ6->>&!k}skv&*%Xnca5{9PsKbsPArEUXXoqu}(`>mSiLk5!112j*)2c zYgh;ju~8lfs?!b@ zz#uudAhYUQhbb7FuZ+&NVr@$&-S6-VLh}kyym`oBz5H%dHy^sb@+Xb7ll%hZvFf&?k zSJ177!K|?x#bfU#v)Dh{ID2-tX$DR}QK%tCXW=(EP z*m?>EI?@bavIXaP^wQ^Q1bk<;wRxhWqg4woG-hscQ-9oZRcE*47JCrmJuCX8byR#Z zbIF1h*zMa2dHh}ic}e{dWhoumUcavG?WvPYmgcwZE`^-Y(@so*iS#$2q;UI~5&0VX z)vyH}#rTMr_Tgd}G#{Q&P&3YSm@GyRNGImv*mAR0$sqDa$mm}`@aNhUQX9fl7Y~!* zo+HgFdqB63W%X7;b}o7t+O zF5UUUfJ@(35?h>jQJGjV=p=9|GK=4D`fdKz9R>ssWDCAw)|j(qZMt=lrY(!X?VX*4 zW0&ByNO|Uq-AZY1>}DW&$Ngx$#K z&gQ3GqPv!AdI&bAEF_$R?xwAqlx|tAO}Kj9)CY~7CnPRzA`8WR@{B^p`1GrA}= zD>Tk2ZgB4(!>zIWV{MVs6`$Bstj$`3JT#yI3>nOIdt2XOW z3sVIZmE-Vj{ON|s`NLxrlvD8;-~200Zq1mD3o`E2ul2Mmh;L$NYtFClN1Hst?C?0_ zUpoXUfZ$$%AB7{s*<0-3a&J7X_#`C)H@6rDa8pwH3-sjJKQpCP_2yW+Xi{0{o)nqC zCJ}^bVs7#qcA^F_&1FTrWHK*hRNBbEW_+_e<7P=VNAdb!baB`XGJz*%ViZbc z+TO*CKQaT>-2_*#P;pYXiDGaw+_9dFq_z4N+)@^lcf-nD7(XbfO8MvPX~cJ>r70iz z%1eqXw8pYfxFCzQ56ysyZgiJ7tukGo3BaN#NR*d+{*Z_%W5C&d88TO|3_Tw>zLc_P z6HnnnIoigeoEHkUXfEuHJ;40L18t(pE%S@KI_8^eulny7Z(HFAG+afS%1HKyeC`uX zW}KybJ?k7=!3g`4gez2wo=$W0vA2KcdZ-8NS<;O^)r8U|UzKn>-!aV7iq{qN`hAeB zcZb#u7M(mn040DarIWq1_rs&=LWs& z#S-}88kd)QC&)ioKx0qi=am_y@!zd|juc+$Z{fMG+wSI+qS?BgKD^0L1CO%vi;j$b z*qG$bLll$p7rGdXq==*O8MmMr5?kfz$H?w@7#yy{#mp1*MLk#}WPuL9B5-ov9bZ)o zYR2kv3(CZL2{ZCZ{E|}WlvTffYT)imC$`MJ@0u_Am~X(;$94khkop#A-Ua2(QE@|d zN@BM_cCDhmu_yvF{=>dhiLQuv^#AH29T+$xPN{GL%deXO#W1dHRIMqd}Ra71@t9wgcwlwhT~0itSW_8u)(G1IBYxAmh6E_Sl2_z}1)XODmC zP^rsTbVgM8X@k_%brl{WKkMse6e7Kmn5$i!UX~&|TsM$1rMi+||I;c)0}H5d0H&4~ z^3C*R+lKHeec@))q9Q!b3XC0InsEJi0ZpCdIvx@`s;OTzQXO;(@0P%l_Yj&ogC}kj zBYLLA+!6ZOjyin1kI2(Ujk$WRm-op*p~Py`ch)mxc9MBHGtxr#a;~2RMNsEj+A5+o z6eM5Y_`(r;Ls*dlW~IhGc}p#hD{ouufN>yhwGHPwXh& zWi}@ivJ%YD@tIO3W>LB9k_pDW{q(`|r-j4kbAva(Ro3&51R0MoceZn_22eTF?QV@s z7Mq*vs{9WWwen;+GuX4Th>84Mg=G|wzEE*Aw-khwegCA~(nNNEYkI6Sg;{PRFU+yK zYuQtxT+jBx40S?v7v1gkPIAh~*0my?iE02pX2CGqzb@@`o8IC4#6J@C>5ce*l|%+s zW!X24N^zxKg_|ywEb^~HN%Y)XcKHR44{(BRw+CO%1!H^%3LFeV#kD28W4xKUE^Qs%J_@GGN2N}7KzP$*J~&}fDZC*&R?^J@Ga3pO#j5VllV zSC~B8qJR6hBa2r!mRS>*CHVOI{p4#p4~=^csF4!QVluxdq@l3>@nEE{Xn(H`-OkJ@ z!&~Y&-p(PzX`u2`_{Vd)O~qhybm268T5*$E81_$8$M?~vKEF{hLeWd z*PKj(G#1cD@*Rd5(&62qOQrYhKGUF}T{Khd?6Nkf3an>GP%H}EdYW!!g3tEm83haN zfLbicXj;l|-g7c}(u6KqliPFO(ELi!KMA2)Vv8#w8(Q)%J$y7gwvb9l^_c+(8w*CX zfE^yyrzI!XZ^mV5O*%qbMmLaosV^>$8~dY$PTM81rSCIfGJl;~z^?F={yIfz7V-=3 zfOoK5EgoYc2{2zs>wcpNqo}JfIl~agah7s=iNDH;h_TU-64P}`}(5nQeXJzDJ zv2=qCr51FMZ)(HfEdN=y@Au)^d}3kno8sTFsJ^`x_d0s`* zRh&%Ho72reN}PI`YiO(PK~-4ln5g%M1g@yZ7wsU$4%MxgjH7v5Xpc2-NjhOF)ODDp zdaocv+HA}4jg}9I^-cX0bbYHE?ZT>oon2VV-3MG&+q`@Gj7t6tk!d?TW8Y`Q0FDe$ zDpK?+e@OVp&V*!p)AI!(#e$c@c*`fUS7&0goPv=9>HD<(9S_X7a#h_x*Flg0>r72W zVRHhfBUDl4OI>bT@ExzG)smU?*Ue3ytKt%)+|F$gMg7TRO!4HCd@A?|2{ONZjsXli zWps>BgIo@7E^%E=210Lpq|~0vpz9y{KXg;_KF2XeD2Uz7|AVTFD}`y_Mm!tcq%F40>dDJI?8W^qla&YS_^aT(g#~FpsrTwGBq)#9~4cKwT$N`+&k*RT&lM{)n#8J>&fFO z9VL4>ZFr=>Q9w=x5nXOGo}H>-Y7=VRVTRfD_TfO|Ge1#pAfa7=@num;8G>Ewi8kz?T6k=!ocL$t!o&bPRq zk=_WZBX}-qXu>FVcQtggh}gFFNJ)W1J6pDk(KMJN{p&~jSxeG{YRV%DP>&A1;%FoI zin$Vhr?$?O?PIvSTZq!MHVf)nb?);8r8v#x^WGGXuM#gR%Z?$WeYifj!(tWG6-W!& zBm4)VNM(QgXa}wIiDL$UaxUA?X(T%=8smZ>OI(m?2#MYUHWi7pv)?T7Br9hyW~$=6 zFicNbf1)zVKAL-7nw+IW#J>-lr=Pgw4ZOn`fxJ!S`uBZDwn!E}XoEvH|QEkR} zjES+3A5Zw3?~sIsj3b$sR!AMW7k9j^b*1kByr}h6{+)|^=8c{=+ky@?A)iNfc4E7f zpnc~MpNcO`FP1~oeTI%VUwG%cIjSxqxJW1kM-dAWrL4_^_Yix^QE_}B!5ko$Xmyie zD2{#?w6%6a*;dmF3xh!Lm8`7ne5*SbBnIcBx)rp7g2KCkp000|Gu=nSPLVY5Vwip^ z3Fjoigv{Aw;N5eS=avJHHZ7%nzI)ZYP-%Y8pl&LZD}DXnTjho^Y|Z7wPlh|wkJVC? ztAUE>K{OF2b-ur6I59C5^x=}k_U+s)Y;cDh^H|teU=`VIBvWIprgeLG-vA|XG{-xtwX$`A;wL>oY4t5_{| z%bI>tV3uuUXCFaITu@E$iu%&yr$Q2XaZh&RN4NQPvF5E@PLP;i9h zQ7&9sAe5!F=YM(3EG$<}M{6(7j^M6yRvMo8xNddcz*`1HSP z+V}qQ7p)|PFTSNvO0K(e#wj?Ei9FkOT}LIEgDB-TfVOjU7@m)pF-|{;qj^m_pdwy@ zjEgd?xSM_2qBVFoZ$4`$_T+IL_kt1Kx$#IB%EMz`H8)TG^5+FRuOxoBkWvHfJkG@f zi|QhGexj85H)?z>D7eKN{2;8ij}IT4?(b;u+;qkBErlges3<9QI=tUNB5u5rEE)ro zlanpNwVE7gp@5ZwpbTf53OO)K0B!)#^B}^4uv!`AtrCA>%TR{A+Q%0ElUW=Uj06B! z`4>^xHA@F|2{^{26$cF`$W>*QR;i89aJzh_lpEU&-f@oC56ug6{z#JY?jm$`T;anZ z*0Jf^^x9U$y1DRDpF)%Vpykwb6pO0v)J4Tt2N^1(l(V7ngz^dsLO*|!0!sN7@ax_M zqj!3K3k<%a0L3I8*hJMV=?Um96mtGs(D5EuswAcCU}m5^}0P6gM(!bAOw zSeO*el11pvXBF>hc7!OVji%qQ|1i|tHqk_%y)8cEB-UI(y7Pv7j{eB#tq%%=wf`3VFu z009jya4h`<^z>_|=fHSzgi|uq=N7e&3^lDO2)palsf;wM z+R{BN%Jv64UL;{t-;vm(X_1DJN+DQ%-`^Fs6!ja(iYkZsjmq_bEhh9IY`E5T(}nQ! zlO)_&$)e;pHM^PHb%9~Hs}Vr-dJWn}CoMOc!21Zf-Mntazi0C1eMQIpH=JU=)eH-t zdfer?^`!&M=cc+}$iXnv}Xj+*%K(=z2EefKv?4I^H`Fo)QTGS;P8M8JiYjdl~Xe$fF=Rav0kzqJ~se}aB~vCQF%aZ&gj}aE zxn-U<#X!lZDAY^yo!Mc2hJ}(cEF?sbu3vPETY>3S1kL$*E&S|hiHO|Q8ONj?E)WJt zhb6T84#P-sUdXr+l=LXRV26)6hX@Fw$Ns0YxdXM~hQV2wT<-h3K(6$uk5RsZ)-W-($g1HcQ(Q!n_NFUS-^GQJYoGQ{1r08F~YgRU(;yO4m0Zlbd;AHf+{ezNvho$Gk(rXu;Z+=7~L4be; zu3qyus2~kg;FT6)N&5qsE>#Mm8vja_OikgDEJ;+~zmhplNJ$A0ir{cOpcqWz=|=-ZXOjSAF zJ)}iWRu=+^%e<{CawEgmD!8dho!fmao<6)@#cFE*cb`ahXdX?Cl8*%D$ z(!_rVgy?(vaw5@-hs_oBFXWCwBu_l_y7BN1dO`5Po*<6McJ3E4j<7klm2nRa5Oc#*F?A`<_^t(^sE=Ks0t22eSms84#%TxxiY{wXDCzfDtA(F&i1t-5I^(1& zlEVX1`rwqiZ*9P>L4r5k_@pcW&lk@bR7L*t&;FjqNaG(`g%Oz<#0?twUEJ7_;${6- zDsxzR8$=^ctr%uP6|}qWGxkvGY(H79MA+vO|47QVcU|=eSI8;&Y4JW7Pj8ZRtAtcr zM}=g<)V=My)z)mNYAllu{W9EbhGJr3vH{A)+=>bymWFx0u4}ViG|v0)(nR(998;iG z=fYdE1umI0EO#?FP~-%|2g-!Q9sL~KXj$;O4j*=izjJzW+#{wYy1+y6tvzsvLF>^S zUY7i9Zu5}7ZJiP($5Hz}o?%Fc4Q;VKs-x(uZ0C1RV&F3l44;LCgx-LpH$bn3q=jZ! zL=wJFkU^rp6d~79$mAQjm(|Fq?CGjBk7=&V@g5642bQJD@V8C|>$sG}Gjk$S&&a#2)FX_+~JPPky8`@Bbj+d;T3$HGf*0ZYym z&FT!gG3+HJgbM-$`V~! zpPMmCd3eirLlhXWeOm$L`xP{C%k;KQg-(}0emEacQy>Y0xz^7y44=21m$~nf=j#Ld z15$U*jG`;y_D$ZP zJ6WHSm15m+e56(HyQUXmsHqG}Lg3qQWTJ!8?mAIbUDia~2>DxUwP@4~&7%H^B061L zK_9KS%aCogL;2sQA!m7FPFTO$N4sk6j#m(K>pyD5u*4!t*p?%!doE_QsC-;BWE&EU zCjmNTrQXv0s99)tnb}0#p3zbI#PmH#?e)ci9**bSm@7BLVUlYD*}f)0WkX)B>w`Q+ zw})F%l#baMuY+GKN$FRrp`eOX)E>~RFHAhF?LsLe1=y*~wen&9m zeLf$ZwNX4RFmyL2wlt&3Dr~sa)zGeKakrjiE#kYv5;Dto!-Fm+J$a}0ShvE-rEWO=-mwD5eWrAZvUKG^AS z3G(G91f4xtuZoTp(D)in{4>hXAf_zo{^B&h@>kbXlG@zkLmqj%q3a=~r9)L?Hgq1j z*A%+8z1ZuT4)}RK4reNQ1&?scPko!^xA_l0xhu16PyN|C38b`6@;9F6S~q6nTHDJ^ zZX1;^F*ww6`oD4gnyi4o{i>lG15i@J_wn~ge$r2gQa^*)s6_Xw%cK)|SwpL{1wE>+ z46EN3XNOz%c!mu>CTb)rT$?*7j~>cVmRfB1y_oB%I_S!m#&_w$zu;Q3SnEq&Xg|4h z5~6@%_5GqSRbYE(boS33mHMmrZ)Z}W*hUF$(OPT{8DlusXRB@N{PRs`r(Geae!giP zn&sz_r1@8^`GX5!s2J&JQwi`n{8bt#aoKoN((ss45e&9$u645Noo2Dn%(@8Wq-f-i zSpeS84;AtzCoPUcMPaqu@FBUl%xv}4-w97r%J#>fllDweb{cr{t(?d-GsEjWlHp2U zmDu>06hQ}XTDP={eK>XN1LoBdo?p@?hM5$c&pnI{tuCdD*D~x;W2bYS_S?O=oa{M- z!C8GddNTSpk(*d)_~9eVbtNNy8Elzy)o=K**j)bo!{q*~wTwU+w-ZmXu(Pv4-;8JD2=-;ix%u!MjVfECY z1+RP`L1SHxIBU^RVRGA+*~t%qqy{exW)vVPWi;S)+hxUbMLeaQE!}C_# z@-;ym^W+AT=5DeRbwtkg5m~~&`q4{jQb~N)x!TIIv_tE`M4suUkZKc!DdVdGxAH2? zGLrMtrBPiUQ%w5kPsU643RZ~^I8wB$P-qxRb!Tmo5BFE~oo6K8f1tbo_h9ZX{L9gt zodc`GsIMctA-_iJRO? z=ZP@eVUg;*%-ZZJt1+I7%Hd!#Af<=y;&xna^KB*NzRG6*8)wz0L?5xm=Do^9V6lF< z!qVb_Yx(u?ayi!O40KeX()T9_q@bYBdqc4)Yfth#iNBwds7T_bqK;MDy{o13Z@qSy z=WMPIF6q7@C!Y`x8d=^ym7EHt|JElpKtxR&(d4l9HH#klf^gHD%;NE&=FB=t{JJe6 zW$Ji$O^w>=r!B|Jb7`co;|t@nZwD#3XRMzp!j7Ujc+@6VJt3f7Pdtg&o%CTC57XAb zj$vyyB@BUI@<|!XB=RSwgt(z>Bk{pKT!8~9XS)n`&WFN#B4YbmTtDI@ZKlAlNk94~ z#BfEB29DJ#oSn?MHhOra&yXUn<7*d5|FpMuPg`0f(5*0812^i6m#_|?-<0z})*XW$ zCNh4Q4CTl){mtl#f#is^&U!%{V^(zZNVDO+jJN6{OpF_FJ$ORiU9Q$zCBgVLKwb
ZFbapZ*$Yhdr5j2$S6yv+&4Fe0hwVY^K5JpA;Ds4BsqE{q_r@%=;iX$ z7=b+pl$tlrnms932WF|GEjnjE z8_l*3H_A5C@MKnMv45pU)~j+mV2xg(D$!5IgsiwCu3<}+-H9CT9M@&yD8!?v6o#GD z8U4?R5f>AF5)U^nZgJbXa~y0auwb`nfxHtnGK(8{2RpFeif8gJti@iRo*Mt{+IX9I z|EKbF&aT>f+xfDpI{|c^H#Z!9?MishDG?7t*xc;N z&!^NysT($GMv-vI^&@YZop8yXV%+TTreAam=$kpNpefr~JKZ$D_%}1VX9(<=@Ipb? zM8`{sn2V3X(!F@&x4FnX*ukImPV%J>pdDUMUkoa_DmS!LO7G&+OcFkQEQ0(Oz&+u4romMefTrmFu&4GRltE*- z!!9PfoUf9`dI9du<9ekY7RxRptGosbqSe;iVZ!ywqSfg^(#BJsIYL)Btbl-WpWV`P z_8NQzaTk6{<4T;oh1WTy15FSH9aof*0%uAU{Uo|sva3Ari|8}QkQNuRLwilxGpa}x zI#koo_$`&d^?F`FHGt*%Jc26K#v+C`HF@-HiBLxrh~f>^BSSHY0-FV?t19nfW#Y6M ztZg*m<)&~Yq#dm$=P@KMez|WsJy9u0T4?e<7)JjLBhAVARkV7G&Kf1*k{K$=qdx@K zHTC80fbji0zzmeCAe-7z5-X=jnKbtM7AzKfU+tey4Tp*TJLl$+Vd_8*ke|!@(Hh`p z@jn`n?Sm+MMj7d<|Xm@HGJAxD_>x zQ6RcrdqN!5%hxAk0O#+Nd#G8d`S#%f=IpgDa+awSB_S6_*hNK@iu1ZX)Z^Y2UzDPp zf9YZI>dZr%?94_*a_MNM< zsx}_q?6+rc5`~QCNr}3h)Vp}l8RZrF+91ob5LNrygG`)Zga%R^SpQ)*LDl*iOcn?BqnM= z%>D}tb;JOwS}<~L$2=U1zsM$-X)roQ3nTEGjTE|zIAkh2m3m}J>9X#8k(NGBZ@P800totz5jw_TQgjLfah1#fe0YU8` zx6P0B6|zu=?5)=W--Q?;UjoTJp_*%XH8n9Hg);$s04ztj0!q+f_))G6yRZL0oPPHK zn6rG7mzRGp5DdQ8t*x#V+MhbUSYz67P*`MSdbmWj7elR7X|_hWhd2@1Y)p7>tNth~U$Kl|JS$d=x-S1Wym}0GT*~86g$;WwmlkKlw_8^c+5Dp6!7F^psOY}; zdJC050gUABe7R#iKpOXcuVHEuX;mupwN7>on_}Rc&K}~mDWPoj1DSyjMAr+#cE5lN z07;fc?Z4L#4%M*W)aJiOp6BBH|Nej;U6TD$S55;1^cjDDsJbX)J5kuHr3uIBCEAvi!B#}iTfiY)kQ(%8F7?XBmLWF>a z!W`Yd?10tt-x%E*N{t}a1f(<7t&ft(?acV=Yx>d>o7p@HFC8y$>f__1&orYBdsQOI zGO8bY@nC?8FgYx-BDfZyZEfmXLV$;dst3M=@obi>9Y&E~Ug1XUXq($3Xe#v4d>B;{Ts16VaX~t|6>QD z_(HQ_p%Ob}jRznJ0AKmNxhHTSiFzrPPy-Qce?Cl6lNuUJ6D9>CGbeQ?Y6apl$6Z6??PAqRN+!i#1z-4!Xe~e0Y7A4AP%;CNhN}0BgNE9WYfmyK{r!8IVpNaGJTg zONOivgzrg=|IoSHy*%AO@|z&B2Ym#d!)lf-J)j*p2p}2%0e#(pNK!Z8zTCpAMTqjZ z@vyWDypG`gtaQ0Dd44+etO5}o9v4w*f3I8`fM2tbnc0yXm(c&L8(@>3`}qIV`8L9P z0qE=BeKN%J6sYe*@Ocu!l!i?jdFut-lL0IVi5q2RW4qi4roS#I`R|guj` z3Z{(0m6Vjo%&F1DN?kI2t)H8mF(*}J;mCv6v?3)Zhpt&xw{+>}ts>2n)PD)&S*sQVb@aRM z|C{$ZFnbnzCDg!r67=`h?Kqow$e1moVq<5EF8zS2@N8K+`zzts@87?djbVRAgKQDH z!;oGX1vT~Ib^OJJ4b;Wu<&A4=adENL-~E$hU|En~xcGlY5=9Rzq0rT39}n^y8#$Xr zuRsjc(ais9?d-#$PS-d-B1vpqrN$;q)0K*~qzhB>GPAZ9CsfDOZcP|TwUI(zLnSGa zj-upkwNWHtb}-aLO|;%>b>($dau`g~pyd60pXv0^o_~+)a_Ns|<~Psp`905lKllCp zd>NN5->Oh>u+?sSY#}EjF_Fb)vkThSl5LF{#~7(IQ}Cb-{9U9Jn!KgZw~I*u!)wVk z9nE1JbIy5i=w+7m?=EP@)QF-cf=ADgq@G1_0vzQoQJ&k?(crFgODUyrb>1j0;qk6! zWv##oY1Vxk%rNbZCyfCA>V{FPdQR+Qn6+-$2Rp)G2Tu0$bEoh>bNJgrR_8ckZHUnZ zZD-%fR!`XYWUW?BG;qo;D`QwK^~dJq2V8T2pmR-5Dn$E?|E`#q1m38P5v&o9$8#%b z*M@Cc7nj?(<2-_b}ME{JoHS!h4bTvTA&HFiI1yG+n8)KJKo4q z&YWhvjiD1zG&#Jq<#Ja*jRuP(qC+P=0TPN*)|aiHR_M4|S^ZhkBW5QG=(1+v%r(NL zGP?qa7o-2T#8N0kCwWOss^w|hNWJO4%}2$8YuE;(Ncn>${*9G_Zk}g7CyqmT^Z+Xg zE;e!1_Nsn=vRJSS_SdUhbUcQz=e*#C=@9ncUQ{b{%F49uci_1)O35w^9NLew@#X0{ z>FYfIaJKlEF!HXru?W)fUwxuAR`y15>uitp8;)}P{LCymd==~K>vbZgWcT)!{fkhX ziI);lvl1hwwzi+cWwEZKd)W5WAYvE}O2+bmgDRRoXk4V7ExcXuA`nhCx3J0rk%{WG z&6OKBv>$n6!=CE-K7zJp%>}?BW`KYD#@%7zch(t~JEwXr$jltJsCu&qy;W-RVM5h@ zNhFDaV9D!Pk^^AD?z_iYi+VEogU+7-uDbzwmhr>UoiI(07BH9zq}wU8WK?T{6lx`) zvyl2{->2)&J9D$u-#s#8Hp8y1#&vdLHy#VJo|0E7UAeBo3Ms#R3{-~|ncl6WiS_*h<%@e9+vVBLOd=@?fz#HbRvwgT*Z65C>OxUn@jn*nNo6 zN+A6S5rAvO z>Di>C41V~|O}alabt>kw$%pnKRYebgIjmrx9JwPyif2pr?Gh3H^=meYGABWF!A12q z`D9d8(s37S$X!&6v(wU_c^)Xu6&mw>L&NM+u8{BObxApH|~ z^7sJKs>r`x;Omx~n_D_DkhjLjNa>B2&7`()=3{~V!ajXs07^l34C#sy>jq8^miXb< z3W!#FDb{ zFn~=H;m87s-a@W4Y75u!Jay;3eRXH%E`Y@+sHT@?-PN1LGbnrvW4d2FcIs@MWaRiu z`=v5*V5htJ&EVnZ28`*^rt^ZIm{BjDd1qbx^kR`8)AZlA{826C22e8^@!9hpBf>MB z1Hq52TD9mplyb3{e5wl;{8Z}ep1gNL7otE`#~&>{BjZ8v0iY0S{9b;XXKhkI=oCub zEd|Ss=hE0{%Jg9FotP2Mj?I!G!H57VMFeXj1pZtF7hqkXc^ z6%`d{UmDp_`A<`^0G}~A@b#}ed-&ftNxqM(u!tms8Am1RxFLiRR76y7ulMIvOGb7;Rf)bF`7c^6p1|lKw*H`W_pZ@>7ckW2j}DqU!J}bO55_2gUlpPh`c|C zr_qZxUr9^bWcyug@5hjFJOdQV;Trnnsr0ii*>+S_@{;J>-1X+>MO=|8H2p``Z|_E= zOEWOYX_O2jteqOJr6A)thX~@dkFl1P7TLZ3$!4#pU5BiZBW&<9A=hYspc*5Os_X0S zLBbET5c}^cXv~prK$JzcF^ul2j&fo-G9i8z`~9QRrU1|>qNA0O*eM{uo_ZfB^k_(B zu-b50@tB>_`SH@I_1kad=U;*;EP9%dD6Q}*xru!1R;_)iIA2c{Bi|7$Nh6u#v`;te zE(8w;OS|JeW~RndBWA|or!^Mz<$Hd4!}qV}kB3#LT9t%}hA3yNgTuy5bNJDl<#MFW1(Gr0>?Uk=IRZfn+T_B83VrgMN!N^u z(yZndez>JK9fN%lW(!p$`9)sQez@w9jr4?1h3v;8zx=Y1lYuvf&Q>zbm$rCZ_9Sk9 zVKNb-mJ`STMhYUPW9KhgH5$}8!*kK#p2peAkN2D}FIYjQ0>WBmE+3JEX4P|9xTKIkPg=RPD?+d4+te+{wx|gsWMd)y6mow_EiLR$ zPQJ*r7uJ-`r6t9rCzx>2CE^vS8JA5gyz~3t!ThZ2&aL=4Z-5SXZ+gK_;~Sz@p~v5s zl0d*}@?9|nKrgpF#&52!ynqxyuedcX`*6ppF)@fMzxpKUs~K`F9jSc8ZIyQxdz)q#S!dApr095kZUF{G+1`4kwxbp*3?5!gN;Tj_T!15$=%^|4M^tp`G8@H70Sy#6=YL{sHdkVV@ zF;Q~pc+K|+RJ9=I!V2h>i|UYWDW>KS@p!}|q{qCv?P_m)*neex*v*dZ3gj5yye zAJFmG9V3u7=!~FzrmWm4Pwl2kXLw*Kz+DuLIW;GL1t!RfTEi1YQ| z*1(}US6hZhkNys3KDGJr&68EHo(znt=BQt!L6^A9KNwADxfNHUtviOP)NxJey{T#4 z@l2h|j}H1@%la+pC0}kSZohfRa5)udv`T2=(rkI zo&S`d^MEFB#^-8h{m(Z{_S$8Fu!np--`1!E?Py-TdWA{MlSEx?U$cP#n8>>V;ovTc}ytY=CslI!5z7)B1&`Djbol{zhU)*^4B+YYI2zN9j z$tV;pnpmrFY+8+mjs@I7)v_;Dgw%4p=){F@itj)BPc+zgwJY*Fk*9Nd)a)$5E$a0X z78d)(w)@p7+US2>%gumop*&1g3e3u)v(?B}i=Y(wG&QAFZoM^D*!uN(%;3bt`Zuj; ze8NcRXeC~MalrSM=W|R9J~ee@f2xSl_4&d1dUhmDKnZh`>zE#RtGo;o>z7rA<5*}1H-Sn-zMkc%nowljNmXeZE z`Thp{)U2g>DqQ(oZZJ7*{AsUH{`M-dNKE7WVlAD^`_k!pg~Jy{Q@qv$ehCT>mz9yZ z2TWyu)^%RUd(P+PGI8|nw^y{Hq7>u;Hf_GQN7QD#4~I`nN;ti4PR7}<5`(;A^@=-x zeZ-7TNeLSqRB_rG!v>bnK9nur*TcupPshT7c{b}x4Hm`1Ij)<>w11(ndhQpohK}FK z);KcsZ?^6$vFMnXPv54zuS!Cbw9z7QE8q$!SF}J?Z_`~wBUP; zCvDLB2^-;X2e(&y$dI1*iQ4h{5OS)BYlpzR7cwO1x=Rtq`u0OKy*wQ)ZHtw{=2)Tj zzr}I7rS>_8HF%!M?aejV_p()IeEoWFXlRI}G+REB%H)hqyUGgSPJsCxunUSCVwKk) zkfdd0Ki2I2+>&u}syJUwwhd@8z>`KVwVvi5D%O{PNrpY(k^2%Chd~?QwwCJJrlz6$ z2ttPztEO!T^}SDG2Q4adtPKqf-vN;M_vZck_j7i7<2kCe0)PFIj!sBm2Foqu?p}*0 z9WF>F;>Q+ocKOJr@UxQQL?x#Cqi zaFtT83kQ4x0=mVerH^viTsw7O$5}U>c4vg_H@?MV$f~x1g`p3?%PK8Z{hcE88p6A| zIwJ+RqV7wzEgNo)DupN z-swS@YRzIAh%e=p+%Wlqwt?5OB{PASPHEV`JmRNZ;#hh$crN z@!hHSfY@2e#u`L(yLWf1EPAzFF0D#5Ty>w2F-R?6J(%3KUNs;vFu7`NZB5(D_r;5l z(JL(4fV}VD@t+3b@KN54Y1_WN+0%Ocnx2lHzFkpZmf;~edFpw16apatSeX5^lepf0 z8hVqfluDrc(~0X5wMT>A8+G-No}L%@IJ%W>c`uYuN9Jb zyPYCtW@bnTahGK4fc=#3;EJDTY)k+%$nRu)^k@W8ou_6COZQd8x;_c@yh~$#7`Lc^QUmU9vUAX z-{St?Rz#pff(Hc$H=yA-suTc)SVuZ`lyX?(b+o#2C9#2^oC-xL* zmj0@^$w{^$aGkN2Pxi&3(>JX*+?%S*ui3~+ZUch~z>`i9a+DLjT+hzg$_9_j`uera zNypGIb9QShl%tVz=dP9dmWImb+)!0roiPCK-P!JJj-@AnDU!~Icj^MZ&uVPv#fOE? zcBYvEqI|RS^Yh!Qtfv*OIwB}p(tIw>RW&r2^n5Oi@d*j(Zx14U6Z&JKqlY%zo}$zG zoc~1|J{S-^3LE7{K|w)+pKs)*7wqQ7aUGyTEE+{bkc^jC{ovM#dN1qSvbN0_bfYpn zDk>ZM;kgko_H9Ng?P?poo#LXRs@gq&T=5c*TM*HwvC(JiTuGre5YlCJbyFuB2gI*_ zJKa`VjwkKZEk%gjgFrwuv{y2E*_$0HZgC=#=%(UnP%l*)=Z5|_ZOfo5iZ%xgY3!Z4 zhsVzi&t!2F=L#iM{}!j1=%^@~A3uJyZI0&4f`NS>jc1N}P`oAXeHrxW6Kd#9^{h+s zhVTnTMLug=E2|1mZ%R?O!3y7wum>bp)Sla1Fv+|(PeMImORbIMHZ?6)o=>0pZ=~dF z6ocUd@8myOEisuaGq!#q8X)Maj|Xhe!qSrMwCVb=H%q_Chd(km&OS^YI$x8xyAP4^ zn&ANpDu}BE(24&L&`r&<_rd0MSzX_B5L5xc#pJ4M-stI_#>L-2YK6TMkA}%c%c5G; z=;&w&zSJ36y?NasbnSVz8@{k$Q10!0dCb*d+o)x(rS*_eInAoF_{Tw$nzM7|>>eZC zIJe$_nCEH5!*ax)27LSolg!U)eDnQ{W}}zTuhv%8H*W$0seQ;I#V?uXeDAzve=`7+2zY@ZB9Ea?Lo8>ssHYorVPm zrVnqOOjKEuLm6N?{JqZWgD?EhwZA{PBhT zqa|z%gT&+GjbRY1_x;TA5?TzJrz$PE+z;PxPnLI9ga>)aySWLmq?8st0!zpVq7>jfV+B&rp9jC(lp{h< zy2WPY;5eH&OB1w5;xYN%oPKw0>a;o1UC`b>Jz~L^=5_cSa_Hy_Cl^RMy#XuG!8fks z-_|B$tHwdY35KYcZc_0@0fF{&0((Ux>V%96lG4&h&}7P!B!yY+*RTD-me2_aJ!lQY zb=^1BZ<#4Dk=(2 z?R$-{EPlZNLZ6DZb|_Pt8xrsw1fSOZgEssi-RJVVc|#~toE%iR)pu)a z(mwDQ+!!Y14q)y$l0^dh-Aw5<1raj0zbA-)0AfOQF@4@fsJu|Smexw?I^&m{?lZOP zhHZ<1jonTkDT)N0gY3k9xeI@LsuD90hw>L&^~~bR)P)2im5)-Py3ukM@ZZJ7cN73! zOeQ~kK!Tdrhq7lKT5!oYp=1GDx$z?1=;Y*3!1n$E_mfdjz;fB0F&}gOMYy@Og&>J! zSf~g_ihlq8!TK5D1)-s_pQ`1w=n4oi5M1JBL%C4+wohOl5g?+{(jwfCRug~vE2WF4 z>J|mjXq=;J`GyM_0l&@ph>{$!v5zX>;Vcd!2p~tCWLTONX87ubS|1OVI+L}e^G*`n z?!iGWHgY^SwXF#E@~H8?a)CGtU+rSa+eo_XOnsE6a=(Yj?ZA%X5Rs4|B8(g0Ia*eR z_MO=MfN&_}$7_k)1rsts3AkZQ7PeutI7dfEY^QwIvex1%BdJcplnxFK8O#{Br`1hD z-q&*to(I=Q155gMm!#6t(s&OahOG3)C;!xWkZwXysZm*3iNFdXS+2h2do_E8fPRu& z`N$97H=jB@tNHem+%r&+yQ307Q3AIy24rw?xN^SViYt^H8_Ed+lkeqlx*Io+GL z^`I2@n%G@%T@orxB^R7m{GIgU$CKf!jt;rutDJI6MBF}}|CW`76e)H}1{NM$a!%&~ z7V7IzJgEGwQ<$!J5K^@Li{E|80!#CEw*t@wn%B-$rQ7-6Kt-c!pW6%5_yNfE`rN+U za%}x%Twh*R7R975$(Uc4fAFyK`|ySx$W<3WzSstQ*l0@JXshXaM9nVwi6{S74u^(%*@YbT&Ar}^1ouxk}_c2zmE^eJbM;2QRiAb zd0TEekfhFCRkc45Ld>Etk1&(us;v_bF1rQE@;&8e&+q`bU#uM0BLt~>g}Ht_yKWo! zm*u7H*zsD!@t>EnfZ7{1q0>nm9Suk%7jaxSezw=tOjw_(El04IHtO4bwBbg};)b!! z7mNMe?8_i+ZmY3hYAe#M3&1-}0u1x}pc(JtkUVvzCTqbr%krF@jtb5x;4N&8X8;Pg zDalDl7{vk4<-cQAd+?3o6`*=7f|Bm=byUX6Li_u zgh_&cJ!$g50SA$4gIxOi`!OFv*|As`3fvKV2G{_=$ZjO$|-GfAgX0;d!@Z5!}?nMf+J zfEVA&n0Y`Tr47&tt}s7@&ufVB6{*~gyjBkG>UuWZ7!`$Qe|K{hO30*yP8%TTah#VR zXrC1n5kW#J;z9)8B?63*SQ;JB6$Vu7hYZ3_>omJHOE~tczaK=$#y$c}hHaCOf`XM% zF=;tX|6z1|AxK&41mUg&lD7he6N?N+d(v8jWFMsVr6FL6nh4v$;!%V1Db_GC$Lv3u!*5dcZcy! zHQQ@+hmYpH&r)lEO4Sb704vC_pCB?u#5h6ZW5=NqHB&zYoE#5CHInf_kh&qV$d7o^ zzZ1BgBIq8g`@b*yA*0FI+m|AuUEgh5Cm1xTo?FW?C0KeQMCJifb3!qXW4z%UMV|IV zutCAVHba0o5(@S^6r>ozAhhP=axN_`^{LA?Z57r1F7jT=2OqoxP?_U^>MtdFHsgrc zX~c?{rnz@)ZZ0db>HZv{3(l%iz5lm;$e)Pw#ful5hQIDz17xrM`AoyxTTCfUG#I3l zB#5Ybcyxr&@;FAm1l3!Eh}PBDC;Q?B2Eg%pT}nE-d_9kiNA$r^c}z(+x*DcCf_DZOKF*9afzE_Ld0cfbDjg! zYWJBHMDzN}%FAI8fSy($16oyYgGd$t7~W4W*i*X0Fl00ww>k_N8FmdFoiMO!GIDZR zMMXG~qKD{3b-O?L#jI#wB5v~e^JfSG8j|=2fB%CCqexmIp~;FSaAh*T^)KM4p~Jb# zMt~2^{dj_38O`zuSR>E7k zs76dSHa5;do(4f~APOO{%n2}Hz*K<(^ie&(9T4R}z|;!#o93*aVfF)>C%76hcEfdX@G$UsKRkGGJM z*?B7^1+!_oaRGq90bHaF$Sroj>fP(KVBLEJxc)8hd7mq6ke}tm3I%sL2H@ot6vzNV zkg4ujJoKd$-c?728PwG^PLQxW$@85row|qKs`{vCXpxMniv3Xz`!J=KcNbsVgvk#iVgN=AB-oIx+#)>9& zuX~9MKD0GprJ>7?TZEZb{*$Na{(ouML0volyBK~{7uy@$m4b(ajg1ZX5)O5?dVc1R zS$*Ro=SA_@wXb|*U@3emq?Cr!?Fk7`fDd1Xhlc}27z+rYLxY10#|IC?QNa=+XJ+ooWCHL9Ks@Wm z4-BBRU1Vwm2+(BcU%9?;$c1I8yN9$ke~ z0}2KJ8mKDL=zp^wzM^qhxpQ6iB*W}d4MXwkn=OS0qeZ8io0&;IeTob~Sl6KuFs5Ol zU@QBR|GE$#TsV;Wp9{JADHeY;#&;aq$q|%wj{axvH1eDz_rzU0kbsWt)1&5pE=U%Y z(sHMdMCx0;jCFfQP&0E;XZ(LFL`aNJOavMC#u?t--pmzY;72R|t44@!1F;_AgzOE+ zudp6)-$SVUK$ZOS!_oV4Blnq-QU@}wC>*f5DHLV$>h&@*Eg z6@Rt(qs^);jV<-80K=p@?&WBrdGrVcgr&CAooQeKh*T(yT7pXA_MCps`%E{mzZ{4w z2ofdee#oFL9CZC9f3byUK-B*uCMg||-hpm+zEeHF517Xyh)kW461PDJbh==&$I?br zQAEGi*HeH81Y|L50t^HY0vW6iW+reMp~kW6h9H10(-8=_xBx*Ag6CkRrG~&*QqW9` z+Q9aA99my53ZyR*Cgrp?poxDtKL?d1wZDKO1Sb0ubp9*y97eg$xuXF;L=;$n z!~8x4inBKaPvkKbu6SoRTzgunRcOibLdIt8huc07!O20Q(g742#c5Prs<5}^CNKyX zm5$EQ7^oF3=LX=3J5$kFO#b=y5(d%BM^sFZ0s;T)R|X0RABwkc-%=Glz;{n#S(E}c zZqlC;JTaje>J5S#^iNsfBX)rytU#_XF5cS6DEnoCx%(6S!Frcunj~AzpdV_@WZt(kSCehpTCF_F1t$ii`t^uHvgC8*Q+GQ^g zKyn-jqOZ1R>&B1g&Kb&TLH!3AI^CXJiWbI?cC8Viq5w%eNd5W7iuEG{0s_X={$K+n zxOfoz;v=x^FY)o&RaI4rYd?Vh0dkI5vCB}x=q;dn_a8U9``Tm!cY&HWhI7SUG0`33 zxV9tQ@cJnIt}RwWFBl|!R+DAltcjhulyYA#2ZEB8D#%emNd!b7a5E$@7o119|MB#) zG6G^^Vvy{WP6>SJVtR1gJa-}aoNCaWjFW~~<*GBiEGg;X@DO~DEIBEEZRj%ntpxt0JG+ZhfAQ1tJ4FpLGAdlBOw!W=^bnF8;y{h34 z`+`IhEgkoL3=C<2EC>Jrnb4QmSRrqma5?|=bu&=+paV#B63gHa*l^@Gy8+#^J3NEM zBb$1b%i&;RWAioGnwgb&lpCfrFtW1#Haej@e0j8nys-htgWK<)SltDoz&#gR5Mm1= z`Tr+oEqx@_YX+QtA23-XK%2x%08v)fi0o?mdh4?zK)Li+UX&PD*mW1H`SkbO zvM}%Fdd9^Q@?KBmnqKIt-$^e+c+Qtw33sTu=BjK^a zn7hlNW(RuZHiTFsojqg#>ScxEfh_;!%9r?eE6~e(NN2zGL7( zh?El{gGWV2{~b#2rTSNXq~i6tcC(tU!UjH2bGez%<#ld{s9PY)R~q`>#{3N@*44A0 zfC~e8X>?H(0Tl>k56hA}kDrH!5ENGv1Z>mfeMp+h9lqTR$WV=qxeaE^ECE)D{ zxwPo#<`XPRVItec3r2)8UJsrl&X*YW0)0v6{cR@5w*jm(b8rY0u0NAWTVff{C?3gf z7~F6I#bQ8x=_<4eL2cM(VS8^vqev=u)Bf+r=ArC038qId`G}h853o&B4V$LrH2Be>>n9GG zwO<)7fCOr=s<1Z}oR@kqp}znin1-Gnxz2S@&diJ%2rh_2V-^x6nuXt1%`_fDG zxEX%Ws@|qgL0T;_rI6PQ^SO60h zwZRKNTEqPj6>pP}pc6WoNZgh?o_o|ZVdVd3WJ_9QclkIna-=I5zWN*1)1z}rEVImD z+lGYo4CQB-@ZE(I|Ne4-osS7GzA9Pq z?+UFaz$HQ{Df`J&r;G0%p-mVG(t}})5Fo!)YcT?`6)Lfr6^{3DwfM186@n4(gMu&A zm0a4KRYweskia}wf1Y{BLDJmW`cSJy;{Ob7M$U+8 z_LC=1e(Oan$PmjkwkDTC$OWPwA@~R42ufuc_EBK!o0CLS@du}6Dnr^xkjCD0yzGqz>Z8OcOwm=f^?DI(XW+BzJ~Is_#+IBwd)QmDC}7;x2i5#MT? zohYJ*4=p_A2L}!Kn#oKHKz>~A5doxx*O0^5qj+d?ay31;>!_X*6HnkFbGO)CZ7(y8 zyZToDsM2>|Ux#7PaIlgTRY&GqZ6P4>&C*iT>@_Qy(4Xs$<{;$XlpUIQ=Q9s5XOi67 z_{{$l{P-cQpb#dT2tp?$34~hR+Z)R#HyaYgb+>m2}8WG(_F$DZnuyFWnm@*amsXoxbYyol$HD0 zFA0uiqx^@^Hy4_FgYW{xivYlB-huuUb>tv>mrzhGdAse1lGVF?S+Vn!26{3j= zZ*W|`irF$=xU2oKEO7#+ z3gTmhM!kWQU=ZywrOi7UqktYqAVzSs+E=p@r~UiC2fw(zbk4tCFD+d72MfvV7VpL2 z(kUOgutE@pSMMPYA#Nb3Owxiz57Yh>DG-uC(@(wbBL~?3i^|Z?Z=AT5{OWg_nw)gV zxY(ZDz1W4CHSrQe@iAx8+yG8u7dMRX{lQA>Ps{!m@*4w)QbRz6bSBC;Z$p!S7%<(NsaSfniLNqtGJjl36xF;KJ>4inj9)p9!%H$C0a#2%Us@m@&E3*@p z$8%?uxBBI$%#P}?xf4w2<8BnKgJi89ZWtA|(|f|RSZj)(I;H#Jpg(V^fQOLcp!bq;$Ie^Y=@|9VmN<4IK-L8S=& zIFbcR==qmrB+pg1Msb;C$`B-{J)1_w;`l;xf7G{e^A*q81qE$VuH)HgWD5VV6W~H- z;%ud0@RVDKr^YjDW!yQAol$DGspDpyzCV25YmI_Z=Ic_dw>lk30sHd@ezN6v>{JEE zt9(`WT$H`G%|Tm_N?R;wDs?##PGDTykQr7;C9~80J5kc9V&$|w)KA|Rg`0bsutzof zz4SYVdnE>bGvY3++LA#jgEj<_e3k{aYc!5oE^>uX>aBtIe2c*3rqqZYGlt!yaoqIF zmn(fz7EelSQcu1+I}6h=p>_4V!$glJoKjrO97R%9r*bec?fqUic_=j!;q<(;v7wP@ zB6hbs2`^gU+e8q`X-Vw~;CT&>5X7FT6??K4c2ivIW^stT<^5p@WdOjaE`hLys2ekC8V*b+OSe zMh_G4vRn#u8L6}iDaMC*)yX!TDE6dAitYs>3#@9}kcKz!@-8erqp{@8SR=fj1t+1x zSzbfN#+J-gTD@{`Sbou#EuSor`i4m8DAs;+mQ?=>kM3g(JR*j=SHIKx?5Sm%EaQU% zhm!cX@0+uWkPn&(P7|xvWtDNCV?tP!%^Ow*&hkP_#K1(Ra;LQ1{RbQBF0j-)xM;S< zx?$PL0?6Uv@D}JxEX;A$ZUzmYhcm(!9z7b1!EMm13JLhsWAj!)G6+d${=w-Pxl?l* z)-r@s03ZJ*J)>Xp8h)19$M_dD;S13HboplI%~X zXv+XjSf)$fEE5$xjF4PlN?E+h>OjXks0(uhgVT=Ru2m`#ZkA;oZ_OOLBq6@@dsjoo z@0sedW_TEuyJN8pygwPoMeF4u)Q z7`_VsWF!%Ul*R?yxO(4fOy2YUEI-@`m?p}@rHSxx@)c?y?H4bNL*?W?U0YF@rA5<{ z;?}KEZFO2tEpI*~ybxuiQY162d%{-Ps9!80aZ1k~0boXwr^seEXt=gnPrQKvL(_6h zv*^gMua^UPK%50FX&{X)CVu427E3lcR#7oibfnRup{!Gdf_PT8b^K!v(?cnu!La;f zCSopOD4ixLyuth`t#d0%FSbmsTRpYg~S3p)rIGZv3Ivi)DD@F zmbbUAl7(@`;r^rH?Dd27+gY;pei`si5?nM{d1N&;ZpMiuHQWU(cNy4#;OSD_i|N@S zNN9Rgz;!>1kSw$UKU0CSX5g$p^t9oM#* zs2x|KYxLl0X$UN|x(!+TehZaX~C8$m(+t0|W$LSn+bzmLcfPKkTTDvlu zwtW1U_1@#zEz{fWhAN%FdV58NvB$$k!+0j z3oN%BNKxB9vP4~BYzP!<$yB^goBn2XtrxbUTc;%f=0lM%=OiUfC(+*4+WxC`CCrUp zPScmO)EJZWA%g`e5!>KdHwni5g>?tu1{S!exK&N_2GHV?_1-}Ls@Kgj=w`0*Q)lUP z=H=C#pRX;q;#%>?%z^}Hh{-q!(Ra=26rBBZw)}&TK%b98b8X?pd1wgy`)lg~ClpXT z8c0Svv{VqCVP$B$JVn8LkM!$4OAu0meQC?{HTVR6RqswJ@^(sJ9B!6m&S(#8jmLC~ z{pin22a2w)=rO`C+43M}`-BGvCR2)-cz-a*Q{2?tf$9w518C=oeyGMbDMQG)w zy|)vfYrx^Ryi&vtQ@qs)jYLOVYu`Jg6}Y2zNC;ft=Rngrs7srOZ9o3?skXR}_ea1c z{FGGT*yP*QUXWxw`&c!#SWj$Uw=HO0f=_4)Er>qpxx9VJ0q&6HA~l4xX%l9<5vl3k9B!m4p^CEoA1LX}t4yy4-@)$sZ7V7p2igj?h-WJVy5uUG-OU`b)DCQ#n85WxJzs4cN z#l5=q+?xIf(a{?_0OwH}Lel*-IXADu7!x_0xa|SJAn!8ia0eCo!=T!aP{`)~JqypQcWI^6;=1 zEO8U)NqYIt$htGZW)=}5M1f(}Wv(n|XJVaKQP=6&5|Bg+mCC&Hr! zj28dO&imprFlf$?7m}kT6QYP39da2kLg70OqbS=BvLjRlZ;`R6Z9JVFL8$Qy!%`}L zDIOUdNNQf$98Dh=qednx&vQY8;np$QXIl*8rL>M0sU323rlZ>%wD40*UJg^Qn)qoB z!QGDlD-#FC6aN^)?z-m08@Tk{ZCW8NzI(71>{8Uk^Da>|;)KRR*^2GfnB(!#mT_-q ziqP(NLRE5iv4gzg;!eof=umAb=oBxW`BZpnarbBb^ z!`t%Z&0kgMhTfj$k2Uz15cgRE*-krX2~`EO6r2e9||1Q2is8#F%L~Nh+EJ@kYjwKCG-rYCRkr>S-f#ci$}}S7mWyIM8hJ5yL`7 zwrRXD0ezIo4M6Z?`mrGJs}=C{%Esb)it`Pofw91@Q8HW#gOrUYUHvirqeGHnxefGp z?V1Z2`*t*Zqo=p=`lzVbWixvExH@i`UiLXGhxk;_MG^h=DI%^oh$cYLv_%ho?x=Huy7BO6E>Fzq*76KYwOlrADVEQ`EeyhvXWSA+OmT@}st>EkhySU)Hdr@B) z^y%fgtO3Q-ZqC{W@x@tIy~|d_lEygaH*p!w)YH`cSKahz-g6It4VIC z85FdlO--RUKq%YX+*C+sdGZ90nwt7tncwGZSh>tImhb5&h@8Lcqf)SFd#o~PYB1W4 zFk-&G($K_PLDm8$yBi-#LrIze1J-?{2CABMIw9;Fw${Mj$J_$eWx6J(R+Bd&U9w&| z?b)?8HG-_VKZ!tP0|f%rAQWyWH1W@7|muWb^%rs-vEwsK?nZHnhWGRv~T0YOs|V zf#K$gAAFQmx+vS zPr?gZ&Vf%l7 zw7lFEhf615XSsL)&aWU2g|r}w;Gk*55F9E2tqq7Cm4i-++kbtuRKC~tuIjWj=9Q8* zMK{Y!S)qcf{$7|%e&l(?3%@+InBPO<;U?8AhY!HBxGlcuG_|I=AHh51j;zNBqERqG z+?@GUh>4CtTVnTD`g%+MPTI#u9HQak!UrA2ouG@G3lw5<2R3?8La$SmnCkRmUOVG`j%k}x)`8k6^KSf(|lAM!)#MFXS-^SNZ zN|Nz$2;G%U(^;C%=uFZVA{v(7+h!*^K_5yFua(29cW|!U;qG9zB#CCT9~DGF5vQ85 z%*_`)eCsSH`wvjX_Nl{fxTWwVn{wei+J615aM<^<(SST+ua$?#u^#7G4SFu&C9X!` zH~}f$%unLH;`mu+tKbM!_B!AX-@hwJcRi6WetJ8mL3F0v znVt^!6^ms0gJwSst9bK*FUb9{g=G&(GPu+R)psg<_n<6jK!T%AZSvI{2Gbhu%}GLL z)(X9<0<4J|)yB;&zgkCKEnN%!df|NHS~(|PmDdQ0;N8>$$;jAMv1GwrH@q^IR62V} z3+(iDgStHb46jH!SiWA<8m_BWkRi}cD0tU`RHUh3{i}^$(yX#MN0GawP!MaKZ zRu=r5I{ZLLGF~+zwwQe}!!b+pEAv|JfOFe`1oB=J?u>W!P2*$-Q)0IKk;w2OjDrIYy45qrC~}i4rIMFFBGk7iIJoHr6Q?fyL%Q| zPJ1^`Bweb!lDgj(cRg1SMN)98&`GH%`{R;$=y1{eAwPu>g&APF8wZ>uXN*@EP~+6S z{)hO{0zkAH5Mxs=pMIknZS{C#wD;B?1x3<|b#0d^7qs`P{QcWp+%z>;Jl?C;pPiiu z$3yuF``+B_L}SC6QB|H*Iy8r(V;04X_bsP~i`uAjN`H1{z3sjb|MDQMP=eR0f_tlh zbwlK#0}b~p#wS3~K(iB`g z(2SX45>K)CuiDqj@g=r94$Bi0{viAzN`W@Wpe1u-?gte%PCb6y+!bA>d{$zZ;!&My ze=PhyR32WpfHdhmtjAhZ9N*p99g~(%itir9|1jar{d;F6`u!QmF1avjdFX96ObpE* zABD(BAh4$=F8zgxDL7__OsdDMtw4n0wktHf;^?^YTN9k)GdFLpvA05@#Z(ZT@>@5% zu*G;f*@jPj4gij_KB_!Xzeop++-@1#ej6)zONAP*1{vS}*=v^NqLJoRsG%bvx+ zMT?-0FJGA~cjv()=_t~WfjuvT#%-XV6`ZTBd7F6@M=d}H*f*;zW z>1r#qr1sLN4Hf6h@R39Gt1QUK>SCRDru5MC5PoL{zY9Q0Z-YckdGKj5h_niC%pH@T zaG=rALE)%D!KFIS>?TU$2EZBQ!hEKSM~qbWBqOf!zMBilQAn^G{VpFUbN<4dkw zEhjV`ORzG*g-SW7g0T(!vfs}3CaB9X%t(MD5%g*b-23(ogzQ7X?2$Kn1_ONT6Mo8F8$I+*+{ww~M<-6KmaDv0r zS1X`JcOufT^&I|zc_E-3sd~JZBnl^(Eq+`BYGQ|!iqKqg9sf#YNoJ1rOcp$R_@3q2 z%llGq9}LzWT@<|m>QzgN!{%(#!-ZfbE%7;E*G7^^NZO)ZhD^#m=FZv##E*IpVX_8? z|25E!9{7N;u%6y9{`%EDZE>WqVjcg+SCKByb7Kk#oSh@6d0YxoEJ&lCx1|ViXWG3f z)^qsgJoo;bsLCy>x4pf4443x3gW*f}+U>OOqdh=^B{HZOYKA99#M?5X05nVQaM%}8 zrLi~J)XfG`Y7PFH#Kave86!C^2YI~`viPzsY&ZZkwrzAm zye44iT8jB7RaVhPzfFV(x9B*O`#svnaI>H+b$E*-Tst4m{y2i#G!J=J_{xQfH|%QhNi@%T;(40P%TNn^BS?V0SpdO(pqp2nD(Nt3M8B`3Qu} zdV@YCbybe_Hq`H~g!BMiY1k_5Mj z+5>6;SdmZtl(SYU8f1vbKxEtI>g=_hL^9(&d~Pxhg9rq<}WGs#PY1UAexm$5V z+-ymGSTI`cM^FlR8c4y?WELHU*+D!Q%q*EloH1YCPd%=J<2Cj`lM=ZAV@W|%#t)<} zYn{HJzQM(HNKC?LIsj^%i7LmNE9dSQm@5brRBXO9C2`BXRJ{2wwGgVpwcE)R6`+bsS}8F=57rE!D#LX|2t)ox1Rj< z*ew|8gZ*se(AM&Cov#ZW9@%}deRER-4Pin&I$sl=D|(ifb417Me`gN9eOoQp?@MDt z3l-+}jKd#?9bkZ=*_W1dq#^TcTP=+>%2Y_ zYa#~bMFD#szFLDz=Szyvry1*1g@#dBB=oDCKzV3aU0LiAVRWgHG2Q1l#+aBmGD5sU zbsYZi;OI^se0xmrD7Ds4-S@uM)U1?+hdY>v#$vdgzU{b2*OY7KS1Qy@DQwWpx)#B= z4j-OuW>RhD;PDGzg3l&e-KRa&09CW5=(yDxdyfXuqSs79DnwDCA$=+LDFkU^VoHs) z)7F|wRnzh--V~v|vr+`+CQP-=)6?_b(o!+pXvOpN-szsL?wN{(n0_s)_cy9#I#jU| zQyjZx?~E#RNtQcal#fWMMW}K`f3;|AR{sIKzm80CyudAsM$h|<0xV_@*IQ97HoHE) z<|MwuhU_h0-qu&Z1p=GV;iyqh*!OAf)z^lJt;_x6*#?ta-B8J~W(BQk&U!&JGmKXW{t z`Zc#{gyX!j3E~0&*pI6y47Ti#9s8o=^N%NIV+eZ~LNek6JES7}?(mE?HSgnR^;iOc-P>f14FiB+FuumBU{+_<4wj11#$((v**^ zvVq)Os&r;Gb4AjBr-)(JpM%5ohu}IR^gS*##whF=5$~~%OJccA9-_Os}w;& z_)3Sh)4$?ti3$#@wbecL8t8wp_Lc!vrft9XTC^aYBDqlMZUiL7AXPdgL{dUR8c|X} zlx|TFB&3l>k&qNAk(88{6r}cXIWy0m``OQa-!J>iIL^RYSDfc@9{Kx!tv9U9B0%#P zoYNI_SMqDHSMFO*V}3WGUeXeDs6N>sBnF8=U6T=)2Nu8bf86C$x-$Fg2@$zT3hp7N zMp5t@ha$D6>F)#7HUrdP`7U3X?S=pAIL7fjESbLT&TDi)jZ~5VU0cB6qJ|4&beZ*> zWSXFLl#f*MGfZ1lG4;m_aK=tTy^q=NsbF)=Rj!WCIgtsjxRr3X_qdL4G33>w0h1Y? z@v~^Hpg`=mQho*U?6hpsKk=L_N>+N5m5w_lE=D4)6supkS^`$wVQk8jn0R5BLchFy zgFW8O4FbZ=qhR7qQ)|jZ_W)j|*AeS>O*P{_M-Wo_z7wJW6EW^Z;-viI}`%yqq4 zQfP1Z4&ehn?vo#Pldc^8&bOE&BAP?pk0XTSXq67UBIUw%N4-yFXq<~4_KK1}^;M=i zmE7NBHa%M9f1E$xbDp?q|NV?bTY3hXoBO)s@?d9)tEF|Be-*W=G{+P?zFRs{6KPA~ z+?G$I9(<|)<7O6NyV&io7cv*>VOwh8{Tx(oT2sBiqI9gP)x%EQQ)x6ihXyxkqp8}} zio)f`Q=?CH**i*)Q05lZADo4`SQ*Y7-!pZ07lS0Rp!2kn?!YHLl>|$6AujIc%K-yJ zQaZ<9t_KzxrkTFXtuOW<7NU8o@h$DtisPI}9V(Lq9V@`{o5F0CzUR@-#a67%>t6M# zc;c5P_bn(XEHT(9kMZ-bhtkA*j|F35gwW^!I4Zwn;Y^U(sl06#tMEi-hUhN&NyCV0 zWQPCo$Q?;m90aSv{kDz*#=4rJ`N0{|rL2vjjrTF^$|{{t9)Q6(-Bt zR<()fp5V^*Ltpa9+YiqTJnCMk_XN91oo)ZF@MssNKYDLcO{IHx(K6o`A?M(FHeMXX z6ep~Yi(e%j{3>huP|#?<&aKPEtC`e4FR9)jR2omKi zn{E3=I=iBuyaC3Gw-$Osu4R9a`88%y$q$29fPfK(kw9ctr6Px3sgQ=&!w==v7R8$| zS#RjxSo6!I=+pp}1$ti;;+RRS`z}uJOXjbMp-q3`Z8J!B=*ju1X$9z-piMkqxV6C{ zlM*g$JuC4veqiuZN_Z6GTx{d&kJb-`Wd^>-`wPg-E?>BiR@8I=Y(FdGQ5;~jpCM|fl$e8L5mjSUx_hUSoQLw^5OczY_y@!3H` zW-X$F%5b-;;yw#ExPG^ybccoI-3GF-G8BtT# zVH}kS_>HCGoY7``5ykp{$_FrHBvH9+XJ zhy~{m%g86C>0w+s{XoMvbN7%(%1H?AaH<5hc8n>qv`@v!A!8nj|U;D39F}C~CtyqL~;H1Z* zw>8|>-id}aMQcTn)5_T2AI~rKa zqn;{Fu)@l!Z`zpI?Z)2iax<-$2BSl;(B@}p*^bVLDlI9_Nve^OR2*6v@f(R#IRA*O zhiL#t3V|U-c<^goJjJ>e259J{?sNQsY;AhgGu^A-q0uSO3nXEb%7m#*-~Tj_d&f?y(cRfs0R}8Qd zZ+}d5gadP|*c}}xYl_9snj_}Zp(gbK-s^F8PdKjG*)9knXUsL}x-fL`;rkjlNG$Dk z-W7q7v(mwVjJ-d#43^To`O`m@t=l@ewVF)Tf2(bN|0|Yh&w0aD9bO%|WA}}Rw|hCL zm$9B?T>1@z)y`Z~Ysp$ZG!3YDN@!}K zPoJ3{bB>Cl6fDY3PhZ;_e+v_G)t|6QQ2=alsrEa<@`lc|S{eqDZU4RvBn`>$g|%~h z(K9x*06cSE!+<@{w&<%@oa#ok{Tfu|=6~-d3c?hR>V|V@NfpL_wedPG)Z}{@4>;rPYZB-zbe2DGBTc7N)L|GYkIf^+N+47RZH+%q3uF zlc;W;%szK{Mu;I4fQ_3%d^+(|Qy4n)z!a}xi5EYgQp=2h6u&3!IraxeEnWP>UyV^2 zjm2a?22Rn*d}ALzM22Y5eSI$V(UA5wb?jl7TKE5TB`&o6`CrF|H!mu3rfrZ4YjXQ` zC#00MsH$0}o}5{eJb^ypfBB^P-NZF%L~Ox0un5ra`~`90H&e%(;e9UxyG(;F?STKMK0j2}3D1RN zUVo7BAOUxy#Dbna078}iA8&5$cE-nj;-k{ncPWwQSFi5;2m>&DjYcF=_iWzx9jrY! zmhvsgzd&C7P>lYHyZN`05zU8v)Wb#H9CxyhMl`6w(t0ZgVrJ~AN4{4^e~ zz{sYtD~wX^E=L=5z`dH)7uqLqc5)Wsm@6}U zP)r%`gOSUsK6J?}EuC{Y_|;jYYqTE3fqLA6<(uKUmUzVPS`YnVF9)&s8-9!l!qKJ} z(n0h5=wOwd8OVp$HT2>=Y{Dj-jxra?E3SFIW4Pbo&MR>H;ZZ59BA8q8|NY#0>9P`& z%O@k2E7&W>s7yFWdK__eYyyjMSeyx;O5d!^B#SvomND!x+L`c{(~7ZZvmfWmP~Tm` zRZYSes>$xj^*kKBWs<%!bpDb3c|pI7l;W14_7FgcG`-HKG;;ia!y-W^;o5oxT}h-` z+)Y!GO{-Gi97Hj*(+4j3m}%e@w|V#9p@@l~dp*j_6Kf$XLf;n6%YmBjidiRR!g=(~0X^T-(I@_dmlOmq8;nI2=s#+Dluy^yagDqW`53V_eeCJH!KcdtSP9K9`r|HK02 zSX)~LL+RqYUlY$ybq(Y#3?FIc1-uXHzC?O2=y%fiBYN9F)~A4^4SeeyY%yDEn)~dalu;t;2t~K=33r zc`2UjY~CY*%C~zV|7wzn>d{rDk{c?-ZjJURu)i9nYGCvUM*d9m@MGFwjJLNJjc@9@ zCZR^{HM<5Dtr1E@N`mC{)4~h;`+@p%LmaqYzT%~AH0Cn0>5^%oLL$vhC~>=_Db20v z)isI3g*xapp(kGHu^i^klA~baJDKWDUHn?ZY-P3ky05#_wKLNdES=xVLn2G*yRsM4 zMU87bEyEo#o8?nZEDz#m<}|EfrZBKR-MAz%bWBxi_Oydkt zd6pC3%wfx-U-DE}Zrq$p1gO_jW440Gle@pEZXhEGJVWQTerQolshy1MTX)m*0hN&h@=8LWpi)Yr@K|-m&>HkU*D#>1j2@e)-T`YEW zR7J&ZC)D|dPdifpDxu;g^f&IjeD%>U;__|Q&#y^qq5Q;9fq5R9ay=mMOu)CmobHEl zYj2^do9?{vo=pWphf9;bgipuMCmSwK=ry@(XQ8Oiax>f0S$|9sZWDSh;dRTs5vr2a zIhsUebL26XV1YM{1PHWicSVXY1_s}`IWw4!a?eI^Xxcy377NvVYrsPv&bvn@nNRS?U|7&-LYhe+~gD$-ioDM2tku}4a)o=xQR z1SW0z%2O5=`!{`WJhPIdZKK0%io)ChK!}bq@H0zIik3KDkDVv9+->!zt9Ifth76R_ z>a&sxQBm!v6VDUhk#FdC(ye4M{AYi9XRJSyX4$1@@jtKWyM1^}A^VucmNq%+1ll?~ z1)2Du6qCznmmcuWvj$e7TX*g4yoa;X56MusTvQ3jaU14mE{*MoI-cNRHXksBi!048 zCszj0Syy5(F66M1m6Xnj-b1ruTv$o?*kKMA^ZyVc^8Z29PPt9POLb%_^E15vtsD!dWlj{%Xe4GIfxD^IX1--WKBDo>=&SRhpAcQ4PVg?B^7-V+H z!y|ui27Vk3R29pNFUc^--%$*p##C8fdYJUGE2$&Hg1NTjL0{lrTn4y`-M_y?GDkZM zVTGjo?&_nO0Pa?7JIGZ#2V}$R2qveze89f;TDG|p>!t;KK8^suSS$?UJOTLF?_H=f zYQ7JwB3%BupIBKhUm9+?Db2nF^a}xkWoawt+Hh(`#=h;xYp5Y`{o3e%34zc+_UHr8 z6>_a93;3ykl7L(p*Ms{tKraJ|8^T8eERge{w(fV}Cfe@U(<;qo{QZ%(y<-#8&OoF! zU-??{wal8d;pEtxLDB^WVJHGqI}{k*BLnOM@c?0f%ukYRLP7#I3T9!)4DMk{dpuW9 zv8GBzl>~4UBexOLydhWKH;{J|7Znp9KV+^S^qvLr_MumdmH?%YeIpFPNv{do*w|p9 zOno-yEZzdnuNA9dZ#tqRfWKi+s6H9Sn&FcAVj<-NK*L7}8XA%>U#nf&=ev@EoM&1` zq~{Uj!A%VrtKaqlbWT7AMre(T$C*gYIXYU!*;x>3&W1;>PY*Uc<^VqSH%iCQm!uWT z1<&8KA*>`oI}a_+A5&%4vNsVFIf;<$Cqf$fU$@c@%cPDN!|VGm=LfQ9I)tZ<`w z0z-tyq|5AkwVP^1$!pI_0#e^kCIEPb<=)hKr#Q6#jmf?ni$`Yd-AAl|+zPbH4IRvIx#n)0RqBUqujP|vL%ly*cFSF}A;B{zR0Wt3Y z#c{(o{8lX6Q~svMZ@YP!;O9}Z1r*&!K=Vty_&}nmtb(Ye-~0d7QkWIgN=tq0g3?uAtCe^7-nXZ zlA?$9*;W8BJ^`i+^ZWPjiw>@aw$J=~`Txb$cL~=08&8zA`@;Af6S7)?BH;w|M023n zzFR5nME2`F-H3v__Vyp4NiXU;Uo{T283Iu5BM@yiU^>>T))wiIK7@o-_1T#~e;^16 zV47CHmMFqD4F@=t;lS`P@XipzGX$Gtq|!eF66{pefJf-O)h$kh0v_{=8+kaWe!IRb z<%uH9zF;fX$$LGyHE1Gch9PSWId&#M4gG_k1OKMX7jQFJ0RTg&_TW;XIo|K}4~GOt zcxoyGG%K>a0fsPeXSjiy1*~2GVFNF1e%1CFvpLUCen{4+Kfyl^0>%N({ppP_*ZEJO z%pqk#a{&Ap929WMN&EXrHjCg!l>kU@Xg^tI9Sy`itN?_KC1WbM>HP%v7}nER*hZ5- zAcN8am}W}uFWx{wV-*|kE{vtK0b;c+nps6hCqBgPayO%d6KbY4QV{_(?-B!J6O4f* zN>W8S25?9Jer&4f6wlb$*r`7lO#t8-@;*;ZJ&n?fMsGFfcr!r**bp=<`zKOI6!3EF)QRCgWg42*wXB+ z*znlN60s^GUQ&xuPb|sS|j3hD{fk{sFJ(bkbFM z08om}4YMEvG*Qpp5oMnd`JaID%kqEX3{_X;UanAB7trypM3+3Qcsn*UGc>E zAOMXmt;6p!26yhe#wJ*d7J=CAv!hD=~R6N1cDrxIcfEbU5@7TG#!}d00H);xEBmI$I`X^uIYOsx<%R zsN4zaZm%6GGKLz%9##Y`f8|$QFfWp>^HZ~*o}1*J*%yY*H50C9CP1fo>(*=$*Ru?B z>7V>{{K%&Dg%u8n%v)nnQpsv)FadHRq|227f0hVA8<=C0q8InPf$yda#CC*VICg9d z1Ud=?4hck_C87YZNkMQ?R%{{LDOChsXUK_^%3uIz+&nAF!=xE`gZyh7Z_DWOrit_|y?%%6Ye}CU_OhMsB8Z z4Qx}Cq^ytNOnd!qXUMPx4*&A`u3v59zPD1lHoG{0(0C4L$zcPSYoYJ@qW=?EevmC|^ zjcaa=0hubt1r$YSTCpeRI}Wfm8M#;=IoUlY+^;}jb)aeR5s_#BAaVQXpmXS@p`>=* zGyq@$Q19K+oBU$GBQI1bQ9n3OK)DNo%;F44ASeK(4iJ)q^AC0qo-hjdp&}E02M#DX zsQ6uuVptq_fWQy{O>P0L?w;Ule7glsp-Uu~ANi=HOa2YrzOa5Ipg8EehBv{ytU4PF zWJCWKfNz3sYGH?)`Gb3)kl+jleOIz55#Z`SfL$~yP1ODCfOY~XPSv6`tZs)QA`n)g zp^SFtyLjTVH-E5Zbqr`jjL=G00$#`% z$e2J0Y@#T<`LLu%>A2wCyRV2`M;7Y+$CqgxAXftHFsG#f&X5k~i|(i4NOdfV^F7wH z#`q8W)My#P|#>%tKf?YyhT0xM|1;3Y;k^9SC^r&nyp! zZU9$$8eSwRU=3`%_4Mc(j(^*s9qV^=z^W$p37LW4jJy`JQM27`uDvoLh$9gkZ2mEnd=FGWR*vg{PK3yw^i|z61;S9) zy~&2X(aGcB!$Y5&XLN@~IK;(i0rbKSQXwGX5DJ_7_TJC$dyOXtmjHaIC(}xOi9hBo zAT`%jhjnh>W<^cGaW7muFLrO@321*H>l|6ceZWui0RpL5Z?*fX0f+{WgNe8d5NCua zjhyCy40gC_JY1k31iXZox^GQ>4Cd1!81cHgI_33K@rCF z9JLglsLq}qu{80E7e{T!p+4b^d>y!87hsSF%B+V_B*^kVIfj7hVgDip`99qRCRwG| z{Yc7O(4zHpgfAl1u^9amu;N|2^$4rj7l={<4vm0&TH(vGUcWHG0ada!wL?S?0tGb)u&VX+Pv_P%OY>;CRg_+vqJYmbyc;`5waI*_EG zFx;JDUGlc3#sIO9C^CS`0a>xb3Kq+y(l}4Lx%v5TYSK_W<_1le^Kck;R}K#kM*xwG z5QX97{1hueR}t&km3C1VMTSt8TN(fQ`0-$C<4wXCvPQHOuGvMHGyqU)LZVIdR0M-sE3UDb+z#MS~@Git3 zXcQ8Z^=~JG@i|JHE8U9zZxpw=TE1Ep$DKz0pbFu6ciOV zKs(1^g_MY>8JtNH6cQ>SySePB@aRDpR$M(|Y5f#|`GM?O@Z^(L`|pa-T?C%W6cUKm zJt%9Qd;mHhmX?+*LP8XzGTTpEj^V7Mg9k^F5e?ZV#SM4dA9dN+6R=RnhYObs$C()! ziG$vw($w+mO-Pkv8f5{Y2RLsF2vaz?xIO@u^+`bikI#0W3UGemu9G!hjHC*l!Rnce zJS1ID#sc)II5l)gY?fPY`%-@@J5JG5D|KeNQQ;BAAKF{P!UPv zZmg-P(O&q23^y(sD$utO!;ahVw!AMxJf|$oqn;*RGXH1c#CdktNSuD6NS=chsusP+?x_;Y%Kah6rSIsb>qfEn8i^n)Iq@gz_j(y-Z6SpS2wnO z42LDtk)uV`)A$+%(bWdn&?`eyvs-iT*hzWYa}4NIu-&zTcH1PKrQoQD#scByp=2qC4%7Tknc=L-gx~Do4$0ja5d`HqkHwvJiY+zUy*I6-0FAFLFx^K?>nbiYoy2TYW zHGsHkMl3vuin?rM#DFpbZYcD|l-qG#S5gAKv}P5+P8xx%4k`d3Y*U~mP;S5nB24`C z+s{T~YoSx21xV!42nreykMdA#kLNdaTyoiIXN%U8(d}R4b#RlRP$=J3DZTo#FY(UW zw|eiY?u;E!U-|&X3po$_D=UZgVJQkma_@r?wkk{AIJIg4@Q1R~S|E&)Zf~r+TU3=J zye$J&SqZnLSmmVBQX%AI@r3=rSkw>R5=u^14(_GGp!F+pJ|NA%Z&8rPc*FcRD>$-Q zHZ?;h2aPAq2#6RqD?<5)lgM-P6T9=c+wg4|5Y1V`lS(52nHqd1pP%wZuHB+JuEYSz z(~#c4K_T4XJ=m|jfZ6U+&(|r$VxbI#2AKZx`qI)bOWthWyuv6=ZEai>jWGvw?WkV; zXn3#wF|ej?!*3!<6Qs8Y_8>we5-QC5{zeMXN`@N|3I7kk-aLguG}{o&J2HHU$TL9XS`5>li1+bhqW&VF z!!6zIZEW&@dp7$Ww0%TdqM=FWd*17Gp+OBGSi_v0U`4Fs*gJC2xGDc869-nWE5DQW z*<<*zQxygd1|?OC2*w`aU+0v95A{cB3iT0T#P{rgVp38RF)+LlApFQN?6L?zciv25 zlJN=!v4n7#p;RMaMRw)h4D-p|Z~D07=!|QD9PU04x1w65LE*nYG3Xj_^MKD^PSou}~?K13#DI!Gi}yC!~;9RR<_Q z5Rkh0;9;Muxxa{kAAmUW&vSwR>}8%RK-nQA5IyPxJ4|uWeMMk(viNooL?|@=vj}iK z(RUcpkm<|U!lO$mT^3Ge~i$9w56uCOw@G zM4MpK(E`jXZ=?h)9_^&hR^-U96Np--!9}EjYXNv>D3~Ecs7wt3u+95t3=LIRLy7~* znnb|xZXZ~pzD9q4gvzx6xg^6_w?XinNFfbKgg6}eVG2e@sfbz~vYO9B8kBd}uEIdj z|JbK&D=t1h9I)>4F!rbd=L5*r@qw3(fsQ`&7)?YykLQIz1A@2zqq!6}USXH;?r3*Z z8IW_zpoV~eZb7Ic23&n}u&WqEo<|c@D(W=OKRPS5K?zHQoLuz1;D1Uo{*O58|1%S< z4o7&Z72wTA?*R!Gg9R@B=pd`D$A6_Df#$tFf{P%y_pd>w_T;-qSQ~)hg8_edPZ#(O z+Rh%=};`##{UNXd1GdC%Pw3$1G(9f!uR zP@f=R0+R2Ox_6xWf1HO$VBVj+ACdh9m;LFkog4Xw%|@)tkfUSqC#Rw`3j>O|%Kr)R zUR`<`0m~iMGK-iP4d8k~d~yF&Yfuw(Kq;j|;bFzr-X1Xif-px8xWvcch~ePkZY(A; zQ~p8VL9Yx4um&6)cwx}{L9;wB3@Rq!wVYDNo7w3@B34dTjqansc{7V$HWGhSDHd62G%`yi8}nk0k^JCPHKG7*yK^>`lV-_qdrh8PqEU&|Kq2Ey`24h(d^ z>dM9{*= zp-{mjjN#x`nk|0GMgo5ZsbP@h`vdI;rx*m`M7^Op5dn27S@_V*JfP(hfqUod><|`e z6af`{{5sJ1g2<{BbPNH?c)Jp^A8Xhs(EjUxK^;WPYw!rtv}Y0Ce^iv1Hz(m)!7!gB zZi_%IpzR}_MUbSfDKCN>ZiS8s?EjfJ3Mwt$>2Nq8Uj?b&W(aR1K$HXI40;%~FTj+y zHqYH9I6gms;$9$3=<8}f4{hf~8fElBnhEr-PNRNIHZ~3l{lnEBkr@VsL8LALH5F{6 z2y;O-5#~p0ZUdqK($V)FTEg0u2+)ez=t%3cw{u1G7%c`VbX&1rLVgB`c3VK4X6C*x zoQ^O}9Xe(YMT4AQ!1yjU$N{eh6#xPTUuA|76)NNxAh1@3ObfIW2Y>l;<5fN&MKyRCiNjvPeL0-Fs0kb9+adoo13?x)ln(-5D28C68X(cvl`b=?TyY^QN2$K}V1&Hr z2`=g<5@CSHAP-JLDx_p$#9{AbycYivlavzX%-zZ=EKcbaG%>2}0+Mn6uuWSVMj((= zPdk84nfDM13xNC$%4O;Sq%W4auFc{c z^Ar_3PKQYxpb}Teg$1uLF+RBpSFZhO)uu zPYe6*(*B(_{x1mk3m7^D2zRcIe{{)-C!~_0u7)vv&6oqfBNdC&vOU5K_6CmUws|C` zPmBwTjC8mj2Rj=2srF$yVQ(;z#14USuZ&ewA~bxE`7*Cuhq9rB=T8=Mb8`W35q13A ze(x+hw@~Y{aB}7q0*FnYtD=L=LTapqy2K1Z4zXWn3}sg0STUP4?iHBLfPZI}yZ)2V z{r+EsZnZfiaD=?WAJ3&_zpS(rdGin|j@DlyAg>7HHb;}kG@2vrYjEd!CFZ!`vLVrb z@|~i6a8^pp-eal4NDh*7$~#0VOGwdTrx!duQIMK?3<8H}NQ*bWZ9FCndLMv1X($|_ zkgT2&+)ny&UugTOqEK8VrDLSOECgIiCI|@>-P}Zr8h+cJW|n1u8L9K&K@+xz@pK%;J6j{W;oKuU?r=e+)xZ zRDeEHX+QE1Tz8na^Zy8TdO3c5@a%SC1$uvVXNY{%R_6_VxVU{@ zSbott_`=;4$l>5}%(?@18W9ZzB_oS3udae$B`^v`^cNZhou@X*H$KPdteM#S0+@0X zuwdWXd>u4{zmRLOxOh+hUu$Kx`3g!VAN8El1ByXMIFy47_|H)PeGep9H0r+rsr^r8 z<)5$mUBLAIbm#dg${M7w0)N2}DmgOR)C1YQ{{X@nJ>GtBkx@+$)fny8tKr8*FNqS$ zzhODOF3FJBeA9TBQE67h*QYpmSc^hWBSLH=Vb*%KifftEssBil@t zBGOe~gDCF6bV*JxI262o>;G6rH1(}3%t=uroMmZwQsmW7k+;z|x0u-pg?_u6DL7|6`y1LFJt{f{u_%E2}wyO1>N*c^9>fjK-#akzA*{ zv%CMfT9NMHy`JU#9ff;S%wE=~-Uq%7?4oQmMeg|JxkPcHvpr`tt4k>=QfygIA3LXk zGsk!A7}h>M_HB@hj}Pu0x`|=)(pZ6LDGG%&!vDcq_dnNE0o$gmE>BWQREkF7TH$hV za5n`X5~G?NbxCgITbX?Oi)nrFjDKV6WYtAaZkj#%RRP{@T(2KQbJ%2x)#zXs?Ct%{ zGJcO*a6ElLaYkvNp<1*CgbpC1Zxs0pB)gD;9)#IVR+IU;)cM@8WutMfupJ=5zZm=! z>!y`e_M*os-$XcW!{uz9kta0`6RY9iLO#IIkZB#vLl-|()&K{Lg<2V{>IK~dd-0c- zBV86f#Md1Mzqpsa`WK+u#cEFO76@PlQyNrCMFh~b~2-L-}l<>R^nOgLg1Em#=a z$+6>vH4unsL(Ig3tviSWz@7hA$a7u%l>-mQKs|YIb@ms(_3Qw?2!Y@ydkLkwCsCk&BlNn5pN2fYEplP`JP`UDdR1BF$IdJ;H(5P)4k5U}n5b0R%P|FCqC7+lkbQbnmQb75`f5eJ-X)k2t=pb@M z20O35CD|2ABCGM{Zx>F@Ny{L@&rzQhE~+lmo+4=SB;%-~CJN2<-Mj*I(^~h{51^Ii zwD=0;hR_4_ei+0H?D8A8mlMF zFVa$-^Plb=W+8tN(ndk5>wMw!BC%K3q%`xr!=HFPgXyM{k{3kqqD^-s3}r!nK-W>s zC!48|^|V5f`Ed}*U7;~W#=^_9+gBQGb~1OnGv3N$HlqU43kTt>!NH~yQ)?CAvJ1l0ddyMJGDG*{@~&7*TS#N-%F2Pd1#+<@aKaS$BU#= z4jx4r7lLX1iF4S#6i-1^WT~z+!D8#cPHXGX+56}T_P~y^7ssh^Q?(Yz9?rljE1)kt>^eulHg=V}u>6TEA3Y6`1LwX?63 zTiZ_;q|`-0c_l_SS0SZBog?5`ZhM7vaA$?|zkSfc5qsU=n63A$-IpL~u%8^zxU4fk zC}n#wxzMagyZj1cI$^zhG#ne{LzyPZ>Ft zAEZ@LO8EPxSFYlKKy2q#!R`Ih0_Q;a^YVfY!pPyUX|+1duigI&8`ZJYA;9iIB1Y>V zMl9XS*M7ON>frn5NsvYM_!Q`zJ#fJ5 zbup8K`>O+;QGtF7?O%zr!e&m&HQ_<>D`4O)es^C3#RoN(!` z=p!F{dp6-Z^iVbW!N zEzo8^dht?yP`|Lc#qs=pPJC4ALk5CW|11ucpA-D+?^#ZNHK?O*rU+(r^W{y+5hPnuO#xd$qTI{e z=+t}NbXDf5`d@Cxn#M;z89R-#hgQd7tvqc_kDD(`GW&eILkY<}R5D$xvRecd*fV>F z4ZB>F!TDJJ)}0SDPejf}S;4RWNp-*=r^YNXTh zCRTpKgW$E%X>0w+$zxsHIxi6o45|E{%Y9V#aE&EF6)#k6HtyoVB>6S0NZC;5T(HsaL++gO)72vs@*yfLi zA>`qzASBmNmZSc1u9ZM8Azu+pA4w>m|5_)oAdpb<3l zfgGLa91F=WrTtHqaVc9@{ZLKRMzI)HY_m8SCcHuQ7R6jUTNaZKe+<q&8KCFAE{Um-=5~!iSv5*T!0{!m*=^iyWUHzhtols+qXV@ z7W56&cf8BFe3O+;;p>t--yl;Fyhq-NQ{vBIr<~mq|F+_Vi?XT_GTQV{$ej9w72(TR z!N?0O&kyb4NX-c932WzsO|}Z>1kPu@b1CAO*BxgYzo}K|P(}wE6U&8Pw7m*eDA9d# z@QtL!aQ%x1*lA z#}ctu&wXVjb(;p33@!t!vNQwJT$Q=$Yp8(TYn@$e99#r(+}v8v4THXo8Qdx=5Gi~D zam?%~hMDh~Euc5v58*GEY7CqM>A>U|FZ%Md`Rz_qW@@HJPzb z->`fuQtY&<@_Ob4-#0&mqJ`!!3r0VP{f_S7w*$@naP%J*y5ui= ze0}w}y99GB>tSduTUX_v;~P=6HllYPJFc6it2^}PvW6^lx$$kNd9U4x{c7C#QpYr6 zJM})|@~l;Z2_i_N4Npw45V+_qR%=3zEH`Qla~KW`(6_6HYEAPp2Z%5mPXExOglxSx zfYe!~B^b^NUwitce|JCt3k$ry;1N9%yZo2S#9pyW*95Km8M?+rh8>Wz@}{qO}1lO@0R5@VFxji3dwXh6svDZaCHBIj2(^Z;{&G{5q_zDZ9i7!GU z@4J&^kGPvHKk;_}$X=aXP?*V=Zs zbZ!iUw>%7h3l=!5MPFt1w_kNS1DrZuE+D5kP> z*BJIlBVg4v`-^VaNZROhQfX7MvI?QKShYCba#tD5?>M}j8F|sGkpDB9hrB}7bfre; zhVS=%S56sfIpVUE;~e8U)wXwe*JCTzVXd9C6zMp^i9EQ*qw}C`^Rr<2%kI~)V7|7! z^AQSnjN;f3?p0!?F~&d$4BU13tP`O6;eta+Dt=cgB90eAX#y>Ur*v_lKc3$0JetGh z1$v7TPHM*YYt#o4EU1wz4))J#Xge&-X4_771n2SA=y1=T(X#b6!<>&9pVW1%^@e-b)z~Da;w{z0O z&C3jTX`s$p3y~_K0V~DV{IOXP@$13FD?IJ^?Q?MIZnE=hmeI7n|f&iD- zidd=~`lO$iJV(g&LSe7msoFF1COeKU5%fVOd>>$A%F-_XD&fY~>L);>zpqboaQ%<7 zqL|h|LhVLPbAXE@M(en%q#f3-F_PS><8Kt*ARMD8kko z6Gxu`_j3H`t%El)YxoX24OUl93qcr`mUjex(H&PBE}7XkbA_4wpB3L)!0jnHEd1Z_ z;xz-`^K|f^on73PDidTiLG=6;#Fa4(mhMf7a5Q34b8y&>i=u<^f^-2l#jCjS4?DgR>5<8TF33u+I~J ze#a3X2yOR;r`G#*j?2a6941GJB{yZc#$=IbC-*q_o7DmvCTq8OHLMLf$FRr049HM8C{@QAKibMoft99NZGNz+tXFw@K5snh-h1e)W z(h(XI#5#uu2VX$dY`YpV&X5oUJd6rdtVfrZIU(4a(RrfiE??O#bd~YBQ~7r8;HnDK z#p#|U@+3r@nv1LB{BR}!y6Zn;dE^~t-YBwND`3$x26SJR@{iEZV#5)K3EYrut{`P% zW~2jkZD^D;hq59n018-Ukkk?DH`puG7xWRjHyPit%4BkolV&Ja)qG?)H z`YwM-ld;s;2>O~v%RZ;FeSv!qHLSaKeUp^G5H!3&!v{T7d{Vj*JwNC_*)S`tyVo(r**<3Jn-(>_XQ^*n2ao-9RQ1DV8^?CXoImYzM4e7hl@Lk|ODBy)aoZ`Cnj-$G!?!6gm z$!w`IyLT8Hi$Lvm6*mS`+M7>V0xjBSQD4Q&lk_>u$RN|VJB}6~*|DZXY!soUb%REgahncQ3~gin z6A7O2GM8G~d52Q$mw5Q)kH<1JQuRLO`nR+!wdSuZl0zid2o3O(TyD!X2HJH7=p#<< z4JG{8M&lkwT{sXDbZZR?{{sb{Ap&ls2tB z;;2nrd-4F=KkfNV7ea^US-IE;*oPHr=mlNn7Y+t;+rOPg$D3uCyt~43QzpFGyYeW} zFGP6DF&(!K1?wj+lFv7+Ilrw<@kqF+G`fwCHL97ao`d}xd*H2V^0sb|jfP8u|G>wb ztIu7b$dEkT9}FtW3~3i`_UG4YL5>YnF?ep{*+jN-!6b6x%(kx*E^V3o0JJ z$o=KPJuYFlte-3w0Z58)g`zfo73LMuua$FQOYn|jv75ZU0>@Jl79oTb^|0oh6uT)POTfs znv6*GaV9^Es5GS#jPZH3Gq>FLW#nOHQKg`+_#5swNn7&H*Awgnj9X(q)peWnTe+!F z65{-*mm>R~rc`{Y_@rI7sO|N3i`~=Eu4^{h+(PQ{mJIa=9M|m6YegTlWcUZxSFJq$ zCC`teRAf{J&se7pgK4)CvJ8=K2!4n$1^3p=#};Jyol|L=H#Q2S=)%EwNt^!eds_zea{Tt26t-J%PAXG5D_dNqlCl z+v(#60-I^yoPy+AvYSSy85iz`g>v)@{%jX0JvTFO^xCZA$@u$`!S5gTHBzJf8xAup zWKAr**=&ttYF|-mxf9^9;CfKY6@{9d=cgEF^cGe0HGEt((n(E*$>M2kV#A(OJ5%eg zA{X)+`=Dm`#hY@j`56a?(GIBY)04Dt~lu2a`qzr#{c$fs1eF?LhHwsdy7MOMp*SKA6j3MkeFiGFPQ49Pzm+N`B z0>yW;++2!SF&$#3rG;Y8UHe*RDJ*u&o^Fe-aji`eLhJ_|i$o>weRx-K;=BXv0LN8qxu^~yYc`@&zJXH@Z$KBC81Wd7)l zhO(ccY>)S$^pDRaeI?}CyI%yO-#QdMo}$wHt;hKr@8Fq$Ii>?=NtU{%&4(#?t&e!l zhvOdCXR0DEGIA?QJf<`16z4_8hp0sNJ|EIYRY$)lswT-|nQqo*&Z^0xethW zVstpr@`+A}+$!MJy~p%8URAqU*4CuY;czI$!H&MlLgv%OnM%3!HN=4VgR+JRjyzd$ zrH{ja#YJza5kN~^f9&v>zV_+FyS;C|&7bCZRmIpb$t!f8sua&SZnqp#3r26*nlLQO z;=S%Xg;wYaeiZ1(%u{_m))=cBH+zJ_GUW7VeRI7mPd3d~*aBYedM>$t(Sck1_w$(K zb2!Gs!nQQ)i;IEXcY@kxplM3}O~`W{k;dR`e!j=~%~n75vda>t2SE-tA>&X;N}5qC zni`ipU6g57?bG#-nw&w|ouY|+GwnKStB#7*3}EB~0u>AAboSKuSg5ZT^OY-%zgCbb z2$qgsc^YFFb9OS5^Mxmb$@)eciAv|RK1>+ye$Ze1_-y358F?1%&`E!r|A%G=(wX)S zw%nrJ%Xx)VrRUgmJ01soek0;HPI{o|&hx8MUlzBVMX;q$(?WC~-Z|ALsqt!IyzOO;Xaozj!%Auu9*WT4qS zft}Kws`47P0B`@Q8G-&T)=S7mHQD!BDXP@qR&zgM^q5p&OpYiD3(Eta{wpSo2syb> z6GMIjL6f+xXovo~p}V7%K5mRbOykXql%-eF*JC|-Fe`06@p|%8yREefZF~O@i zi8SfGokHoike>GchIN;zK_Gd;&t76bG`LBma2r-mL?APWD;}ndRE0eQA_>+XXVx?UBrVRg;KCN3P6`x`ks{cgen<{o<`tgJ z>pU!q@MeL-=|Y3_>AW)mYq&LFzA zqc!ndTtfWas0ID+i=TM)qNkZKBA|lulXa$fm%ULVLT37ceOj8HIel-)*pbBT?IEn{ zB4+iCLLaPq_s2^~AK?9B_@(nP?-nimJ~H%p&qv+?`n}u(@AXjQnWC6CXn@(0amXtD z_kn4_(UsPPC z_%ToFL=-i|WWVbe?_I(7rNLobf70*JxtBtk;z_VaBkp%w#>ZL#HuAWpcmp{wtk3C~ zN0h>IHJl1>xvZx&0eCz6F#TBP;YQ#mBL1CbHGj&&aZsIqdnOYkEH|{WOEy$ZMKvY{3!ET+eU| zRIquVeZuw6UK8gqs|49pdnS6B2i2RbhH2EGRVz9JyLT3VNWFO2i3 z=(%1BR@_s65|jJxk=7z(Sz23gBMT2gV8W^?Hl&{+Yn@H{FWiWp0uTjI{UFSQ#gCVPAkG?Mrn~{SH405cu=h5>n zZo}NHqHPH&hxJ(hd#&%!Jz?d9AGG*64_>uItwSIL&_aS?+3NWzcm}>(Q}4>5#9yI7 z>owc}gu7>jl#JT~L4$sMt~)#uR!3t4)VGmkHFGjdafHgOep`xB#@khb3=Wx5+d)ll zOh&%#d+T<|)Z6fHOCTgTuqb|hz@1DQu(RQyVg8R!gsus=LTGpbfI0J|C?x4a+hIN zg+R?Z#j%HcX&)h#b4R!8J~a+#A9mc&d^4D6!7k?i-<_QTN$gTf<4{Vdu`iv1wjetA zjgt1!a@a^KHCc&*3#@v)+Ml(WS?`r2Ox-$5y+=kzLMz*jJReGz9CVbBX`AcBDK!p{ zF8`Eh3E}dJ5;0=kv)LF@jv|sOq?PyB-)B|dqaf$P$0Ads2S)gIK|TG}m~hH?g@L_4 zNiwX%c(v>OaX>WCLn~@MtwA#5e#D*?O$|9Yk-F+n_1`rhPWpD@JD$hm==Hsa;J&av zoAviHZE=$~wE9^1(opa`0;)50ZDvuOy*4z%me1SyWEk)Vog7+*iWSVpx7AWVFpD54*knx zb~j9#!=KJ)g?C(rSlb5X5nyXU-Z8OUHM?$8liTvHc@2kt1N&Iqxhu~_j&O|ToFw1_ zg(*RNnG7Z{4d!)Oi0!cz+y8`2yG^~4+B&7~06$L5cpbC(%Y*wJitXPb=Q7OSG6)_p z$|2>zE`?n3F@eQ;4#(2aP#=HJTWFva=cBP#F=quT@xD0{oZeYSNzZ)v`>K}=c;9LR z6ZJ58Kzp2b_|8@lU$K~{KR84*X1G^BMkQPAhO2zA^6U1Q`LwW`Hr?dgL{{=3%oH@6 zKBvtTxH%ZG}m)_{3Ghe@l$(EIRff zpUNjqI6|{wNs;GDL*tM>F?q|e0L zD*U%xTSrQnb)&G$mt)8-kmlGP?R%YJ2fx1%4ubtv=!XcOQ_axB2|sc+8k8 z8U`zGm4D7&eTAOImjo8gj;L9pT|0$p~>Ycy31D6>wj;Yw2QpaDIJYuWb<7YS@ z0ffk6{>Tu^lZl*{xp~c4am5Q+BcuS^~uzI z#pB$3B#z5^KL>q+R*Vw%>1NN4U(DmZ&lQp$Z4#^*_*-{7pG4uWol0nOFAMjbU(1MI|`a=oxiGvyUp+!&-0XH_L14YI$dwzSb0Qk&z zNznEt*fc+jdca%XUz}w@mVD^j?^8B(p=o;K>~&l4t<+l~n{8qvIFVMl9L`>d#bo)5 z&gIFO8all@55kt$Ngv)Zu=z1)3#JWM{oIas5J$|y+Scxdf*X&vN!+>{W?|K1rWRqF;E6dUFMki5Gne|;zqD)3zvKq7r$ zNeMcq7|r+=yM5bwcc$@xIHU%__r=Smn?YL)XJV%TxBO=8OC`K;^%E&`t;pa=hkLho z8_$>>9jEM1d@I*f+@H7$8T;*3e}V)$-1}JUrh%JD1k+imS^SyUhk-*&{w!_NOdt}I zwcUuh2mA2VMIc^BpXrW;7W@aS;s#m9K=@dx;okyW`HN0@xa}pXBm}H74kJ`%lzS=O~5fTanQ~~_pKv4O0dqoc1EhxJnXYt*~xcWJN#h+~r z#aY$-qKuMdqMZ`L&KR@XU>vB-t^P#*ao}T-OED^lg|WT5IU)C8{O(NshMeBeH7emM z?al0vB#k!m3);6s{Im}H2OFNDQmoq3C$1sNzdcVD7&P35$k~xpw1)Bb_}Tz{;sBH{ zE(Q|`w1Z0e&$}-r7(uDIg%?|T=Q}?3CHr7w=i}=>v0?5QbT^Dnd)p*g8gDcfmMY>L%Jg^hMp+*< z<1uY`mqj!(!x5gzXJf;ltP%pTyxcP6m<#yAl?s6X+Btp#3M*q^^3E811ZeiogXRR( z7|v{Y1F!}044a8=`b6+Pnf2K$KRM8s?>XZCo|kg?bKk@2OFUPV8rt@)KHA04BPj=clftx&Jgj&q<&Q4z&DtBH_{Q4h~#l7)JqacBu|de5$(gH$H)ka|rZ+ zK?{;5>29|_1S)U@sQFD0{fpWuNpON!E)+b0!|ei2Bb0iQRY$zbJzB zBsT%pJOnT-hB&n8?<7Xbp2?M)E6)vhTeFP5F~CuCkFJ-a-*~yTO+4#-`)p4gF7|`d zvvdp;tYSa_q=9^o<%jDA*i3O=u_YxNo0|luIlVAdMAeg1W^h)t(OS$*yc=vMQ+F+# zwrO6Z9Pxd%YaZ{4dE!u09R0K-UluuBB4#IYRru;N2ng0}bjV6)f>q$J4Ro;*f`Tw0 z?SKcwKIih$BqU&WZx1-~l$Eg@#ZC9Gkw|108G`$^Dq^AR`O-#0Jn}rq`5~2Int!Zw z0Ru|5vy=(gGbH-MzqbARC#A5q=Z$iHH?kDJCHiLz0k7r{c{b%(Em9V5Y278Sd{&ME zg0&>0SeBAzPp|A>`^Rr0xeM}fnHw8BzjiAtC#mDbU!0B>Cp9;L01!2E!p)NaLqo$Q zJT+tGl*bLu?$*lP;SDSxg)waPFqMJSO1$2&CpO~AyTW4bXIP032XKPQC8yj5JVd3` z;_UUyfhN}dG8v?rkAm(zO%zwNi}aBStI31|`=S(Is9R+uJc-*S$HQ zruGMULbXXb+k7|$mlE*4CBt$**4{QUn1E?cR5jX)j`Nv>fa4}`E(s60l{!n9Yl$(t zbZzrm3^nB+f*TmA``Pt~Gbx=yPCGC zDEpfGThaI41rLD20LFu>_8}Za+S(}+9T9MX1;XwR-+YMd*W-5MO}MvCV=>CB=qKBZ z*fICRl!r)d0Wl9P_a~x*ua;WMwoj8v8d<06vWyx`L?p2dM-x6OQ=9^9+H@35r-qz@{Cf+ zNpGaK7H?~Dn8NtNoD-?>X0&}7c-@r&E(Kjo4>EqkX6I*Q%zTcT=P#W_A`~B|fzz~0 zZeztNMEmGFyP3~mK@qG%=tEpdX+6>Rt@j<}4a>B)YpP>rLfLj6%f|e0E?(vsMsZH?G(eZSy18+!Mx`^?rxw>= z_UC8wMRg7cX-N}Ln(xEY9n6AI0H75gc^Z z25p6vJ35SDWd&(F=@x7li2kPb?qaw2`~e9bt3mUkJ8-h<3~L9bI{OmD*wH-;emOo~ zDvW}CYnKW7_BSN7a^D69pMs7IFayevZdKus; z?T_4J!GO$pEt8-lnDb}j^-A#rU%qq%TptJIfqoNc7!Cj&R)NxnqLOG(!Gx|}T)sAi zaw!TyjAa=EjZ|!Iyz$sL`IcuH42upQ9LeQ)=`Ntg!aLBA+zeDP9n$H&2nF=+baZ~g z{T=A4*tCglV8!Ono+6x1eb`er&#o#vn|abv+)E}q(HRB*QV5RBtyNS`H>ZhnI27M(Ad``x-bCE8D0Uq7|CT)CSGhi}FQ;ps3kx9z%hW_=A>yk$`P z%Z^UU;DD!h77_E?rEI9k$q+u0#uKu={Y&K&({}Z_oJe_4r`X|rLvxcJXFWddO?v2PZhC$7CljIH$vaJp1C7U5Mw3$;Vk!r%F+2p ztcl@IuW(g_c>j@#uxX#fPW83rhEp4g3lU%b$vw zambT+h-D&|Ks1d$MOcQO4PErwRQX zdPsbHU5Sq>gkbCLkZL4cc8qnw|1(J?@7efmcBDr~dk72z97=%CfnKh)_C2L{a`nov z&904WQ>M|`k}fU_qPicO(oUT&!GGuJ9ZjOS6t$i!guIAV`it*kRvzR{oU1-YG$w3R zoNFDP38V$aihF|=AXbF-f!5UO6y0Q=cestoYq2VbS0<<@ZuY~X9Zy+JHSvi~w6@*6c484~+7oWQi= zNAO46XPQ}t`X)CHX_UlZ)zS=<;U-=i66)-N^T7+a+t{Hy0o=>{5Hz zu^ciib=SN;r5Dws?4&bNU+SXURtQHl(t1I;RGswsE3Uqcg(tW;x^x8#@(X$TYU*h+ za^yW0()-9WCc<+++K{zDmo)Th_HL_ywd&@d;c4oT;NUkniM)^TUx2PBuYXf6Vg%Wy zbbHA~1+l7Z4-e0ex;R_G;go@3H75gAv&JHpG4;Z8VHv9`I#1LLRR@$@iA7N`QnQsT zKE3DuSfPjU)82em9*dv_!aRYvB=j>JjqF95q>5)w3RpE@yVP8z!`th6aA{SCgwldV zM#V$tXkIN&0M|J;`&(A929se`KOO8lp`0O>sU`knqwc`HX$_7S2gC^!z5lKtG<}nU zG7Lvg>_I=4zZQ6g`mbi>MC{1Nz!N5h z0X)jZcv@`tdWAi+2OLB_%+#L{o#CEhaJ-2{1Zt+f!L9WZ5gFOAQnO%1@eN2fMJ;Hb zLp|E$?5w!gZm#h^Jn_wW!%A3%;1pWK>NKBk+){*Z1_$AdU{`;AL0rbtZaiK~obx^J zkJaiMUJ|BPyLImAj@fJ9YzsOZb7D299=NV<6V9SmwvQB_>IWxqO)6h!JzraeUo;vk zXDM6C*hMu8-i+Ot?IvA^Bbd48&!lwd!D?ZW-)yg;NzE-N)>%)&zzMm} z>UHEd7WpKorVu#R_`VVy|I|tfw7+n|ac4sKIBrY8#QDk8P%Cctofj4g;J~#%q?JnP zKbtUBG8Gz|(Ic3y3E;uN$TDfB*4;I@m7??(s@6^M%ejx}dO-l9)Cw`blp&byTFMh3 zreV@1EA3R>IY`5_a@}dZ++B>k|CBjfeiG!^>IRvXN9yL+l~Bjn@r(Fg7-pXlqR)DI zL)D)12F`8lBKJWYc{Y=#PKCD&rVvA+o7F$P6gE|+biC22|DmU8YFo$Q_38&B7f5^WM`iS%(u zp0sLDT-Z-vF0=R@>Y!b> zj92TO8~*PYUi@JGeR7jbPI8c(!uI{hjhg3caXQ{=^mA&q{Pmbp!^huTqqbWzeg&7_ z%&T|8q4VHaZE7n4i-}R-m@pqlu%j-ryhqc z*o`;`D#@j~q@HlKQcTPBNW1WyoQh`8BK}(|M7C5i+E!kfSCm(aGD$G=kxqk0k&(%0 z>HRjDi|*c@Ty$71^;;>I>!?cz62ZX-yTq=1jQ+F0$W8{@G;xt+7oe^?IVs)Cn z8ST7Pc39pqF*vbGBc=Zo+8I=w@33gwZ0y!-KiJ2-_ZV}=B_Kcm^c9p`zy(cT5D z1sL99_Mv_4?^ZpFGi;u#x}kknflS!bx1{U4&An zEhtxD754Ii`XAFwvtW5s1huoVCQ?%1!}(NFs`?C)VElxLHFCv3(iN%aAw!kS2D!~` zlOGcGl0#+~+((Y>Esxp)36Gq&!yfX5l{*MQxq)_lE~yhPRli^+!J8Ex@5$@j@?z)q zsMy%M)&jYmtC}Sd?(FxGX57lRPM1R7kLQLR`Mo=$#OEX2y%lMkOQ_)WT>(FQP;Xv` zV~$iN!05@52%V&!JF7JD%Ci$_^-%8yYosbriT5*gB0-=-@#4R@WEzO=9h?NALe_B& z-*!?1mdG9jmnd9FZ^ zP4g^+mVCqu#B%K^Kwxmo%yaT|P%D#JA}%O5D2)VvfHNoIU&M`rJk3h3vHSdtv;p^> zctG`*b$QjJ5)Lt8855C)-HAn~10_FG9G^!CqTiP9iKe5M1uYPG+{Gq_PD0j<5KcwH z&BvsWLACdroWK5^PomnBn_io?R8}S(_G919OJLIc5Cakl=q^k(D?mhv8@JwsTvIo% z{=rYLS9l-?CyeoM@(MLPI)@!&rRc5dJu1?KkhxpGqiq*`{QLIv?DWU`Nz+BXv#nK5 zMpqW{K9;~UB?RF{<}chNMyje&6eNxj=gdb;txYA`0MD*i-5pGbh5VHiBxQuFkJEYp zH;*$Uf%q|dh5rfE@nNrS6C6Pd9-*cS7ljLHuaMvSjQYd^0#VAlPw32%{gf^u4d8`N zcoKgS#SX|}iLBE8%#H^~*z>(tM{sfK1lRUO<;hD$-?n}BnRlfsRzRnRpzP7gd}hK- zv{|QV9=1;VL)61bgCDGd(TrtP2mx{~`X@J#d{n*H_Ph4smd6n*UQnGE1ZBy@p2Uj7 zVTp_&nh!^-%&@!b0Z^Skgk^76f=?OY2(uXnQ0@Res;G8QvI#!P;P~|yOU1>61=23T zM@@=5m6CiUbof#VIM?#mv88P&$!*DS0klet4ef5@&&a9FYILkOe1Fof!%H z+Vyep=l|~>uiTab+#2eGR=~CFw5#nFC1zI>9>f7p|M;O;=hj#$2IQtzX8Tvc zHpbs4^A~G(U@(}%%a<>Ef!k;Sj|55F(-;V5DK?sS9~vr{g0hwT!#rDVTK@>3g{r21 z9>_3}7x4Ty<~Q}|meaM2$$A$SM{x$UZw90hF9Eka{%N}s{58uuCP*mQNjZAnWLocx z1KFAT#6Tu@!b;6&6i6h{z`EOa2aZUWpaF%-w)OdyUNbMIof_8OKHCTAv!&yFC7ub%Ao<|Hrp2X zV+|LV%HmL0@N})8_4VjR!+%-2hA0=aWHc`b@w)`L!FNSPk(Gwwk$-$Po8m#d2RKPYcTo>k%v^iu zp5)tR;|Hw2PPp#*lDdPw-q%oEW(+{$L#M3^xy;F+Tj>E;3v~?FQnf+p4TI9#D^FfD z%QkeGYHPRO$t3q+lOmwdH~*!vl-uZ_yrZPyrTZcOacCbZS%{jP2)^K$oIPQDy=(#~zfLm|$gqYIkbIguK5#tV=G zpkF?d5BTUX1qK8i89{T2KYaYyv3$_(TyF!~I-q&a2jIC_^a?dpXXZmAxf#(bn_c8q z1&}E<0Uc{!(jX0L)QxoVvLjzyDb{p4q zW%;7p*AEw~QOunMsTR>QGiGQ2E5LNOozL#+%8Er>yShRFN#|8pCJ8;m`umloOpych zxX8z53kLu{v0U?2Af#d&jrjq1_6PtSTLvuUZl;$rNn48}_)Qhd((|XJ;8M)!F00!5 zH$Hv(7Z8C81N4?@eN4G}mO0Tcbb zPnuYC;nRlgist=((IEwB=tHubHm?3^a)UgSG42@TTqbvMnEwJh;Tn#h-1sxV*tvr8 ziyiRg;CpxTE&))w8}P=oO-$%t%mW8+ELu{wyV4n`34+Y>leIf-QAC0*LSxEbV3|3| zG46d`=N5!`J|(kp!|oR_T9xNf>af2_ROWK?9{Y$aVn2e6j(A`HyL6Xs{r_ zbIR>-|8YCOF-L$)F9Q&pI+zv0f3s4Je$68HiP>^mm6R+2<}w-{6)ZX^!7aa^DRF7UEJ9{~Jd=%2Q)tC*07`ud8{(8z*E zQHOdZU`W1yL%v=X_B;E_`;8!D>9M@}l^W?X7t|*LP>YnZGSQ1ba}w1Yp60yx110JbMBX2*g6Z2r(9&}9JN6vpYJ>i`(h4A;LcufyKw z_)G1y0=bIr`|x+-MsQd=MVMm_>hJ zo4{X+whnc^3Ge@Hj)Tm%Spa2y;Pby)kpH)VcCWGI-a$iLoQeTL5CTzE(SlbfSq1+O DS?QRl literal 0 HcmV?d00001 diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js index 13abe66..2953b49 100644 --- a/docs/build/html/searchindex.js +++ b/docs/build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["Examples", "Extraction", "IsoModulator", "My_tools", "index"], "filenames": ["Examples.md", "Extraction.rst", "IsoModulator.rst", "My_tools.rst", "index.rst"], "titles": ["IsoModulator example", "Extraction", "IsoModulator", "Utility tools", "Welcome to EmpiricalArchive\u2019s Documentation!"], "terms": {"import": [0, 1, 3], "os": 0, "sy": 0, "insert": 0, "0": [0, 2, 3, 4], "abspath": 0, "paperi": [0, 2], "from": [0, 1, 2, 3, 4], "empiricalarch": [0, 1, 2, 3], "simulation_funct": [0, 2], "itertool": 0, "product": 0, "seaborn": 0, "sn": 0, "extract": [0, 2, 3], "pre_process": [0, 1], "cluster_df_list": 0, "classfil": [0, 1], "star_clust": [0, 2, 4], "my_tool": [0, 3], "my_util": [0, 3], "plotting_essenti": [0, 3], "cmd_density_design": [0, 3], "scipi": 0, "integr": 0, "simp": 0, "output_path": [0, 1], "set_output_path": [0, 3], "main_path": [0, 3], "user": [0, 1, 2, 3], "alena": [0, 2, 3, 4], "librari": [0, 3], "cloudstorag": [0, 3], "onedr": [0, 3], "person": [0, 3], "work": [0, 1, 3], "phd": [0, 3], "project": [0, 3], "isochrone_arch": [0, 3], "coding_log": [0, 3], "mastertable_path": 0, "pycharmproject": [0, 2], "data": [0, 1, 2, 3, 4], "mastertable_arch": 0, "csv": [0, 1, 2, 3], "results_path": 0, "simul": [0, 2], "hp_file": [0, 1], "hyperparamet": [0, 1, 3], "simulations_1": 0, "setup_hp": [0, 3], "dict": [0, 1, 3], "grid": [0, 1], "none": [0, 1, 2, 3], "set_styl": 0, "darkgrid": 0, "plt": 0, "rcparam": 0, "mathtext": 0, "fontset": 0, "stix": 0, "font": 0, "famili": 0, "stixgener": 0, "size": [0, 3], "18": 0, "cluster": [0, 1, 2, 3, 4], "melotte_22": 0, "load": 0, "filter": [0, 1], "tabl": [0, 1], "cluster_data_t": 0, "mastert": 0, "pd": [0, 1], "read_csv": 0, "filtered_df": 0, "isin": 0, "archive_df": 0, "concat": 0, "axi": [0, 3], "cmd1": 0, "simulated_cmd": [0, 4], "cluster_nam": [0, 2], "isochrone_df": [0, 2], "cluster_data_df": [0, 2], "cmd": [0, 1, 2, 3, 4], "type": [0, 1, 2], "set_cmd_typ": [0, 2], "cmd_data": 0, "fig": 0, "ax": 0, "plot_verif": [0, 2], "show": [0, 2], "py": 0, "195": 0, "settingwithcopywarn": 0, "A": [0, 1, 2, 3], "try": 0, "copi": 0, "slice": 0, "datafram": [0, 1, 2, 3], "us": [0, 1, 2], "loc": 0, "row_index": 0, "col_index": 0, "instead": 0, "see": 0, "caveat": 0, "document": 0, "http": 0, "panda": 0, "pydata": 0, "org": 0, "doc": 0, "stabl": 0, "user_guid": 0, "index": [0, 1, 2, 4], "html": [0, 3], "return": [0, 1, 2, 3], "view": 0, "versu": 0, "No": 0, "artist": 0, "label": [0, 2, 3], "found": 0, "put": 0, "legend": 0, "note": 0, "whose": 0, "start": 0, "an": [0, 1, 2, 3], "underscor": 0, "ar": [0, 1, 2], "ignor": 0, "when": [0, 1], "call": [0, 1, 2], "argument": [0, 1], "var": 0, "folder": [0, 3], "z6": 0, "y4rdkpdx3vlbwtmngx04x_1w0000gp": 0, "t": 0, "ipykernel_18950": 0, "3922852537": 0, "userwarn": 0, "matplotlib": 0, "current": [0, 1, 2, 3], "matplotlib_inlin": 0, "backend_inlin": 0, "which": [0, 1, 2], "non": 0, "gui": 0, "backend": 0, "so": [0, 1], "cannot": 0, "figur": [0, 2, 3], "oc": 0, "name": [0, 1, 2, 3], "catalog": [0, 1, 2], "dataset_id": [0, 1], "create_cmd_quick_n_dirti": [0, 1], "cmd_param": [0, 1], "gmag": 0, "bp": [0, 2, 3], "rp": [0, 2, 3], "no_error": [0, 1], "true": [0, 1, 3], "do": [0, 1], "some": 0, "hp": [0, 1, 3], "tune": [0, 1], "necessari": [0, 1], "param": [0, 1], "svr_read_from_fil": [0, 1], "except": 0, "indexerror": 0, "print": 0, "f": 0, "were": 0, "curve_extract": [0, 1], "svr_data": [0, 1], "pca_xi": [0, 1], "svr_weight": [0, 1], "weight": [0, 1], "svr_predict": [0, 1], "creat": [0, 1, 2, 3, 4], "robust": 0, "border": [0, 1], "bootstrap": [0, 1, 4], "n_boot": [0, 1], "100": [0, 1], "result_df": 0, "isochrone_and_interv": [0, 1], "output_loc": [0, 1], "The": [0, 1, 2], "flag": [0, 1], "activ": 0, "all": [0, 1, 2, 3], "svr": [0, 1], "one": [0, 1, 2, 3], "resampl": [0, 1], "took": 0, "16": 0, "07006287574768": 0, "s": [0, 3], "parallel": [0, 1], "job": [0, 1], "cluster_obj": [0, 3], "l_x": 0, "l_y": 0, "color": [0, 1, 2, 3, 4], "grei": 0, "perc": [0, 1], "m_x": 0, "m_y": 0, "red": 0, "u_x": 0, "u_i": 0, "95": [0, 1], "cax": [0, 1], "abs_g": 0, "orang": 0, "old": 0, "interpol": 0, "second": [0, 1], "onto": 0, "x": [0, 1, 3], "first": [0, 1, 2], "y2_interp": 0, "np": 0, "interp": 0, "absolut": [0, 1, 2], "two": [0, 3], "ab": 0, "euclidean_dist": 0, "sqrt": 0, "area": 0, "trapezoid": 0, "rule": 0, "area_between_curv": 0, "1641176307170609": 0, "input": [1, 2], "identifi": [1, 2], "photometri": 1, "parallax": [1, 2], "observ": [1, 4], "instanc": [1, 3], "For": [1, 2], "thi": [1, 3, 4], "object": [1, 2, 3, 4], "variou": [1, 2, 3, 4], "method": [1, 2], "avail": 1, "perform": 1, "comput": [1, 2, 4], "step": [1, 2], "full": 1, "pipelin": 1, "In": [1, 2], "short": 1, "workflow": 1, "follow": 1, "magnitud": [1, 2, 4], "diagram": [1, 2], "transform": [1, 2], "princip": 1, "compon": 1, "analysi": 1, "create_cmd": 1, "quick": 1, "n": 1, "dirti": 1, "version": [1, 3, 4], "well": [1, 2, 3], "map": [1, 3], "uncertainti": [1, 2, 4], "create_weight": 1, "support": 1, "vector": 1, "regress": 1, "save": [1, 3], "best": 1, "result": [1, 3, 4], "svr_hyperparameter_tun": 1, "gridsearch_and_rank": 1, "case": [1, 2, 4], "have": 1, "alreadi": 1, "been": 1, "determin": [1, 2], "singl": 1, "curv": [1, 4], "larg": 1, "number": 1, "resample_curv": 1, "calcul": [1, 2, 3, 4], "median": 1, "bound": 1, "interval_stat": 1, "last": [1, 2], "three": 1, "can": [1, 2], "simuntan": 1, "str": [1, 2, 3], "base": [1, 2, 4], "input_arrai": 1, "ndarrai": 1, "weight_data": 1, "output_fil": 1, "option": [1, 2, 3], "take": 1, "2d": [1, 3], "along": [1, 2], "1d": 1, "arrai": [1, 2, 3], "stack": 1, "them": [1, 2], "after": [1, 2, 3], "finish": 1, "written": 1, "global": 1, "file": [1, 3], "specifi": [1, 2], "dataset": 1, "As": 1, "itself": 1, "paramet": [1, 2, 3, 4], "should": [1, 2, 3], "set": [1, 2, 3, 4], "attribut": 1, "path": [1, 2, 3, 4], "collect": [1, 4], "dictionari": [1, 3], "custom": [1, 3], "read": [1, 3], "specif": [1, 3], "hold": 1, "locat": [1, 3], "__init__": [1, 2], "initi": [1, 2, 4], "minimum": 1, "amount": 1, "onli": [1, 3], "right": 1, "part": 1, "big": 1, "includ": 1, "escap": 1, "charact": 1, "standard": 1, "column": [1, 2, 3], "uniqu": 1, "more": [1, 3], "than": 1, "mai": 1, "exist": [1, 2], "list": [1, 2, 3], "return_error": 1, "bool": [1, 3], "fals": [1, 3], "error": 1, "each": [1, 2], "datapoint": 1, "scatterplot": 1, "variabl": [1, 3], "span": 1, "either": [1, 2, 3], "y": [1, 3], "mag": [1, 2], "befor": 1, "If": 1, "raw": 1, "engag": 1, "sorting_id": 1, "nan_id": 1, "plx_or_d_col": 1, "return_delta": 1, "dimension": [1, 3], "scalar": [1, 2], "valu": [1, 2, 4], "consid": 1, "sort": 1, "same": 1, "manner": 1, "wa": 1, "done": 1, "clean": 1, "nan": 1, "encount": 1, "distanc": [1, 2], "plx": 1, "always_tun": 1, "possibl": 1, "els": 1, "Then": 1, "origin": [1, 2], "back": 1, "space": 1, "subject": 1, "pca": 1, "contain": [1, 2, 3], "predict": 1, "i": 1, "e": 1, "upon": 1, "train": 1, "model": 1, "still": 1, "need": 1, "otherwis": 1, "confid": 1, "smooth": 1, "want": 1, "forc": 1, "algorithm": 1, "even": 1, "static": 1, "x_train": 1, "y_train": 1, "weight_train": 1, "search_funct": 1, "rkf_function": 1, "gridsearch": 1, "5": [1, 4], "fold": 1, "cross": 1, "valid": 1, "optim": 1, "point": 1, "evalu": 1, "fulli": 1, "defin": [1, 2, 4], "default": [1, 2, 3], "gridsearchcv": 1, "altern": 1, "g": [1, 2], "bayessearchcv": 1, "halvinggridsearchcv": 1, "test": 1, "score": 1, "form": 1, "n_resampl": 1, "int": [1, 2, 3], "original_arrai": 1, "original_weight": 1, "njob": 1, "kwarg": [1, 3], "provid": [1, 2], "its": [1, 2, 3], "store": [1, 3, 4], "output": [1, 3], "here": 1, "5th": 1, "95th": 1, "percentil": 1, "gener": [1, 2, 3, 4], "typic": 1, "1000": 1, "correspond": 1, "pass": 1, "other": 1, "tree": 1, "parallel_job": 1, "directori": [1, 3], "where": [1, 2, 3], "keyword": 1, "idx": 1, "sampling_arrai": 1, "sampling_weight": 1, "run": 1, "routin": [1, 2, 3], "produc": 1, "given": [1, 2, 3], "alloc": 1, "self": 1, "belong": 1, "sampl": [1, 2], "command": 1, "through": 1, "write": [1, 3], "assign": 1, "subsidiari": [1, 2], "rss": 1, "e1": 1, "float": [1, 2, 3], "e2": 1, "root": 1, "sum": 1, "squar": 1, "formula": 1, "1": [1, 2, 4], "2": [1, 2, 4], "abs_mag_error": 1, "w": 1, "delta_w": 1, "delta_m": 1, "term": 1, "deriv": 1, "modulu": 1, "appar": [1, 2], "master": 1, "archiv": [1, 2, 3], "empirical_iso_read": 1, "build_empirical_df": 1, "csv_folder": 1, "age_fil": 1, "col_nam": 1, "name_split": 1, "filename_kei": 1, "filename_exclud": 1, "filter_funct": 1, "separ": 1, "knit": 1, "grab": [1, 3], "kei": [1, 3], "individu": 1, "refer": [1, 3], "ag": [1, 2, 3], "thei": 1, "ad": [1, 2], "inform": 1, "string": [1, 2, 3], "split": 1, "filenam": 1, "respect": [1, 2], "combi": 1, "opposit": 1, "appli": 1, "give": 1, "out": 1, "updat": 1, "convert": [1, 2], "retain": 1, "It": [1, 2, 4], "automat": [1, 2, 3], "8": 1, "differ": [1, 4], "main": [1, 2, 4], "script": [1, 3], "just": 1, "python": 1, "create_df": 1, "filepath": 1, "quality_filt": 1, "reformat": 1, "uniform": 1, "code": [1, 3, 4], "addit": [1, 2], "qualiti": 1, "requir": [1, 2], "limit": [1, 3], "upper": [1, 3], "lower": [1, 3], "numer": 1, "namelist": [1, 3], "format": [1, 2], "create_reference_csv": 1, "df_list": 1, "ref_kei": 1, "master_ref": 1, "id_col": [1, 3], "cluster_id": [1, 3], "often": 1, "literatur": 1, "design": 1, "choos": 1, "usual": 1, "new": [1, 2, 3, 4], "av": [1, 2], "order": [1, 2], "prefer": 1, "chose": 1, "ref": 1, "maximum": 1, "3": [1, 2, 4], "containt": 1, "modul": [2, 3], "supplementari": 2, "allow": 2, "empir": [2, 3, 4], "isochron": [2, 3, 4], "unresolv": 2, "binari": 2, "fraction": 2, "field": 2, "contamin": 2, "extinct": 2, "level": 2, "posit": 2, "consist": [2, 3], "n_clustermemb": 2, "synthet": 2, "star": 2, "place": 2, "assum": 2, "resid": 2, "mean": 2, "cmd_type": 2, "gaia": 2, "vs": 2, "absg": 2, "iter": 2, "normal": 2, "compar": 2, "metric": 2, "classobject": 2, "indic": [2, 3], "compris": 2, "astrometr": 2, "photometr": 2, "add_binary_fract": 2, "binarity_frac": 2, "artifici": 2, "random": 2, "binary_frac": 2, "increas": 2, "753": 2, "equal": 2, "mass": 2, "sequenc": 2, "recommend": 2, "add_extinct": 2, "extinction_level": 2, "constant": 2, "both": 2, "directli": 2, "excess": 2, "multipli": 2, "dr3": 2, "coeffici": [2, 3], "approxim": 2, "drain": 2, "2003": 2, "r_v": 2, "assumpt": 2, "flat": 2, "sed": 2, "subtract": 2, "band": 2, "789": 2, "add_field_contamin": 2, "contamination_frac": 2, "field_data_path": 2, "gaia_dr3": 2, "gaia_dr3_500pc_1perc": 2, "randomli": 2, "binar": 2, "sourc": 2, "within": 2, "500": 2, "pc": 2, "add_parallax_uncertainti": 2, "delta_plx": 2, "combin": [2, 4], "rel": 2, "drawn": 2, "distribut": [2, 4], "ha": 2, "extrema": 2, "99": 2, "7": [2, 3], "coverag": 2, "nat": 2, "delta": 2, "again": 2, "visual": 2, "present": 2, "chang": 2, "subplot": 2, "brought": 2, "add": [2, 4], "four": 2, "implement": 2, "also": 2, "process": [2, 4], "insid": 2, "final": 2, "apparent_g": 2, "m": 2, "dist": 2, "aim": 3, "correct": 3, "pointer": 3, "fundament": 3, "summari": [3, 4], "3d": 3, "interact": 3, "toward": 3, "up": 3, "hyperparemt": 3, "date": 3, "log": 3, "filepath_and_nam": 3, "name_str": 3, "accept": 3, "flexibl": 3, "head": 3, "open": [3, 4], "archive_plot_2d": 3, "isochrone_data": 3, "age_info": 3, "plotting_dict": 3, "scalar_mapp": 3, "one_panel": 3, "masterplot": 3, "boundari": 3, "colormap": 3, "colorbar": 3, "archive_plot_interact": 3, "line_data": 3, "cluster_list": 3, "color_list": 3, "gamma": 3, "to_rbg": 3, "from_rbg": 3, "marker": 3, "50": 3, "density_plot": 3, "kde": 3, "fig_spec": 3, "title_axes_spec": 3, "densiti": 3, "scatter": 3, "accord": 3, "power": 3, "norm": 3, "lighter": 3, "darker": 3, "style": 3, "titl": 3, "x_densiti": 3, "y_densiti": 3, "age_col": 3, "ref_ag": 3, "interactive_plot": 3, "age_limit": 3, "save_plot_path": 3, "most": 3, "boolean": 3, "whether": 3, "util": 4, "tool": 4, "function": 4, "basic": 4, "plot": 4, "class": 4, "further": 4, "reader": 4, "pre": 4, "exampl": 4, "preliminari": 4, "setup": 4, "4": 4, "6": 4, "between": 4, "pure": 4, "nearbi": 4, "search": 4, "page": 4, "small": 4, "vital": 4, "core": 4, "centerpiec": 4, "respons": 4, "everi": 4, "desir": 4, "influenc": 4, "edg": 4, "shape": 4, "therefor": 4, "report": 4, "mainli": 4, "serv": 4, "quantif": 4, "reliabl": 4, "author": 4, "rottenstein": 4, "2024": 4, "01": 4, "20": 4}, "objects": {"EmpiricalArchive": [[4, 0, 0, "-", "Extraction"], [4, 0, 0, "-", "IsoModulator"], [4, 0, 0, "-", "My_tools"]], "EmpiricalArchive.Extraction": [[1, 0, 0, "-", "Classfile"], [1, 0, 0, "-", "Empirical_iso_reader"], [1, 0, 0, "-", "pre_processing"]], "EmpiricalArchive.Extraction.Classfile": [[1, 1, 1, "", "RSS"], [1, 1, 1, "", "abs_mag_error"], [1, 2, 1, "", "star_cluster"]], "EmpiricalArchive.Extraction.Classfile.star_cluster": [[1, 3, 1, "", "SVR_Hyperparameter_tuning"], [1, 3, 1, "", "SVR_read_from_file"], [1, 3, 1, "", "__init__"], [1, 3, 1, "", "create_CMD"], [1, 3, 1, "", "create_CMD_quick_n_dirty"], [1, 3, 1, "", "create_weights"], [1, 3, 1, "", "curve_extraction"], [1, 3, 1, "", "gridsearch_and_ranking"], [1, 3, 1, "", "interval_stats"], [1, 3, 1, "", "isochrone_and_intervals"], [1, 3, 1, "", "resample_curves"]], "EmpiricalArchive.Extraction.Empirical_iso_reader": [[1, 1, 1, "", "build_empirical_df"]], "EmpiricalArchive.Extraction.pre_processing": [[1, 1, 1, "", "create_df"], [1, 1, 1, "", "create_reference_csv"]], "EmpiricalArchive.IsoModulator": [[2, 0, 0, "-", "Simulation_functions"]], "EmpiricalArchive.IsoModulator.Simulation_functions": [[2, 1, 1, "", "apparent_G"], [2, 2, 1, "", "simulated_CMD"]], "EmpiricalArchive.IsoModulator.Simulation_functions.simulated_CMD": [[2, 3, 1, "", "__init__"], [2, 3, 1, "", "add_binary_fraction"], [2, 3, 1, "", "add_extinction"], [2, 3, 1, "", "add_field_contamination"], [2, 3, 1, "", "add_parallax_uncertainty"], [2, 3, 1, "", "plot_verification"], [2, 3, 1, "", "set_CMD_type"], [2, 3, 1, "", "simulate"]]}, "objtypes": {"0": "py:module", "1": "py:function", "2": "py:class", "3": "py:method"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "function", "Python function"], "2": ["py", "class", "Python class"], "3": ["py", "method", "Python method"]}, "titleterms": {"isomodul": [0, 2, 4], "exampl": 0, "preliminari": 0, "setup": 0, "modul": [0, 4], "set": 0, "path": 0, "plot": [0, 3], "kwarg": 0, "1": 0, "defin": 0, "paramet": 0, "uncertainti": 0, "valu": 0, "2": 0, "initi": 0, "class": [0, 1, 2], "object": 0, "3": 0, "add": 0, "result": 0, "4": 0, "calcul": 0, "new": 0, "isochron": [0, 1], "5": 0, "6": 0, "differ": 0, "between": 0, "curv": 0, "extract": [1, 4], "star_clust": 1, "further": [1, 2], "function": [1, 2, 3], "empir": 1, "reader": 1, "pre": 1, "process": 1, "simulated_cmd": 2, "util": 3, "tool": 3, "basic": 3, "content": 4, "welcom": 4, "empiricalarch": 4, "s": 4, "document": 4, "indic": 4, "tabl": 4, "my_tool": 4}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 6, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx": 56}}) \ No newline at end of file +Search.setIndex({"docnames": ["Examples", "Extraction", "IsoModulator", "My_tools", "index"], "filenames": ["Examples.md", "Extraction.rst", "IsoModulator.rst", "My_tools.rst", "index.rst"], "titles": ["IsoModulator example", "Extraction", "IsoModulator", "Utility tools", "Welcome to EmpiricalArchive\u2019s Documentation!"], "terms": {"import": [0, 1, 3], "os": 0, "sy": 0, "insert": 0, "0": [0, 2, 3, 4], "abspath": 0, "paperi": [0, 2], "from": [0, 1, 2, 3, 4], "empiricalarch": [0, 1, 2, 3], "simulation_funct": [0, 2], "itertool": 0, "product": 0, "seaborn": 0, "sn": 0, "extract": [0, 2, 3], "pre_process": [0, 1], "cluster_df_list": 0, "classfil": [0, 1], "star_clust": [0, 2, 4], "my_tool": [0, 3], "my_util": [0, 3], "plotting_essenti": [0, 3], "cmd_density_design": [0, 3], "scipi": 0, "integr": 0, "simp": 0, "output_path": [0, 1], "set_output_path": [0, 3], "main_path": [0, 3], "user": [0, 1, 2, 3], "alena": [0, 2, 3, 4], "librari": [0, 3], "cloudstorag": [0, 3], "onedr": [0, 3], "person": [0, 3], "work": [0, 1, 3], "phd": [0, 3], "project": [0, 3], "isochrone_arch": [0, 3], "coding_log": [0, 3], "mastertable_path": 0, "pycharmproject": [0, 2], "data": [0, 1, 2, 3, 4], "mastertable_arch": 0, "csv": [0, 1, 2, 3], "results_path": 0, "simul": [0, 2], "hp_file": [0, 1], "hyperparamet": [0, 1, 3], "simulations_1": 0, "setup_hp": [0, 3], "dict": [0, 1, 3], "grid": [0, 1], "none": [0, 1, 2, 3], "set_styl": 0, "darkgrid": 0, "plt": 0, "rcparam": 0, "mathtext": 0, "fontset": 0, "stix": 0, "font": 0, "famili": 0, "stixgener": 0, "size": [0, 3], "18": 0, "cluster": [0, 1, 2, 3, 4], "melotte_22": 0, "load": 0, "filter": [0, 1], "tabl": [0, 1], "cluster_data_t": 0, "mastert": 0, "pd": [0, 1], "read_csv": 0, "filtered_df": 0, "isin": 0, "archive_df": 0, "concat": 0, "axi": [0, 3], "cmd1": 0, "simulated_cmd": [0, 4], "cluster_nam": [0, 2], "isochrone_df": [0, 2], "cluster_data_df": [0, 2], "cmd": [0, 1, 2, 3, 4], "type": [0, 1, 2], "set_cmd_typ": [0, 2], "cmd_data": 0, "fig": 0, "ax": 0, "plot_verif": [0, 2], "show": [0, 2], "py": 0, "201": 0, "settingwithcopywarn": 0, "A": [0, 1, 2, 3], "try": 0, "copi": 0, "slice": 0, "datafram": [0, 1, 2, 3], "us": [0, 1, 2], "loc": 0, "row_index": 0, "col_index": 0, "instead": 0, "see": 0, "caveat": 0, "document": 0, "http": 0, "panda": 0, "pydata": 0, "org": 0, "doc": 0, "stabl": 0, "user_guid": 0, "index": [0, 1, 2, 4], "html": [0, 3], "return": [0, 1, 2, 3], "view": 0, "versu": 0, "No": 0, "artist": 0, "label": [0, 2, 3], "found": 0, "put": 0, "legend": 0, "note": 0, "whose": 0, "start": 0, "an": [0, 1, 2, 3], "underscor": 0, "ar": [0, 1, 2], "ignor": 0, "when": [0, 1], "call": [0, 1, 2], "argument": [0, 1], "var": 0, "folder": [0, 3], "z6": 0, "y4rdkpdx3vlbwtmngx04x_1w0000gp": 0, "t": 0, "ipykernel_24080": 0, "3922852537": 0, "userwarn": 0, "matplotlib": 0, "current": [0, 1, 2, 3], "matplotlib_inlin": 0, "backend_inlin": 0, "which": [0, 1, 2], "non": 0, "gui": 0, "backend": 0, "so": [0, 1], "cannot": 0, "figur": [0, 2, 3], "oc": 0, "name": [0, 1, 2, 3], "catalog": [0, 1, 2], "dataset_id": [0, 1], "create_cmd_quick_n_dirti": [0, 1], "cmd_param": [0, 1], "gmag": 0, "bp": [0, 2, 3], "rp": [0, 2, 3], "no_error": [0, 1], "true": [0, 1, 3], "do": [0, 1], "some": 0, "hp": [0, 1, 3], "tune": [0, 1], "necessari": [0, 1], "param": [0, 1], "svr_read_from_fil": [0, 1], "except": 0, "indexerror": 0, "print": 0, "f": 0, "were": 0, "curve_extract": [0, 1], "svr_data": [0, 1], "pca_xi": [0, 1], "svr_weight": [0, 1], "weight": [0, 1], "svr_predict": [0, 1], "creat": [0, 1, 2, 3, 4], "robust": 0, "border": [0, 1], "bootstrap": [0, 1, 4], "n_boot": [0, 1], "100": [0, 1], "result_df": 0, "isochrone_and_interv": [0, 1], "output_loc": [0, 1], "The": [0, 1, 2], "flag": [0, 1], "activ": 0, "all": [0, 1, 2, 3], "svr": [0, 1], "one": [0, 1, 2, 3], "resampl": [0, 1], "took": 0, "15": 0, "633490800857544": 0, "s": [0, 3], "parallel": [0, 1], "job": [0, 1], "cluster_obj": [0, 3], "l_x": 0, "l_y": 0, "color": [0, 1, 2, 3, 4], "grei": 0, "perc": [0, 1], "m_x": 0, "m_y": 0, "red": 0, "u_x": 0, "u_i": 0, "95": [0, 1], "cax": [0, 1], "abs_g": 0, "orang": 0, "old": 0, "interpol": 0, "second": [0, 1], "onto": 0, "x": [0, 1, 3], "first": [0, 1, 2], "y2_interp": 0, "np": 0, "interp": 0, "absolut": [0, 1, 2], "two": [0, 3], "ab": 0, "euclidean_dist": 0, "sqrt": 0, "area": 0, "trapezoid": 0, "rule": 0, "area_between_curv": 0, "690393920974019": 0, "input": [1, 2], "identifi": [1, 2], "photometri": 1, "parallax": [1, 2], "observ": [1, 4], "instanc": [1, 3], "For": [1, 2], "thi": [1, 3, 4], "object": [1, 2, 3, 4], "variou": [1, 2, 3, 4], "method": [1, 2], "avail": 1, "perform": 1, "comput": [1, 2, 4], "step": [1, 2], "full": 1, "pipelin": 1, "In": [1, 2], "short": 1, "workflow": 1, "follow": 1, "magnitud": [1, 2, 4], "diagram": [1, 2], "transform": [1, 2], "princip": 1, "compon": 1, "analysi": 1, "create_cmd": 1, "quick": 1, "n": 1, "dirti": 1, "version": [1, 3, 4], "well": [1, 2, 3], "map": [1, 3], "uncertainti": [1, 2, 4], "create_weight": 1, "support": 1, "vector": 1, "regress": 1, "save": [1, 3], "best": 1, "result": [1, 3, 4], "svr_hyperparameter_tun": 1, "gridsearch_and_rank": 1, "case": [1, 2, 4], "have": 1, "alreadi": 1, "been": 1, "determin": [1, 2], "singl": 1, "curv": [1, 4], "larg": 1, "number": 1, "resample_curv": 1, "calcul": [1, 2, 3, 4], "median": 1, "bound": 1, "interval_stat": 1, "last": [1, 2], "three": 1, "can": [1, 2], "simuntan": 1, "str": [1, 2, 3], "base": [1, 2, 4], "input_arrai": 1, "ndarrai": 1, "weight_data": 1, "output_fil": 1, "option": [1, 2, 3], "take": 1, "2d": [1, 3], "along": [1, 2], "1d": 1, "arrai": [1, 2, 3], "stack": 1, "them": [1, 2], "after": [1, 2, 3], "finish": 1, "written": 1, "global": 1, "file": [1, 3], "specifi": [1, 2], "dataset": 1, "As": 1, "itself": 1, "paramet": [1, 2, 3, 4], "should": [1, 2, 3], "set": [1, 2, 3, 4], "attribut": 1, "path": [1, 2, 3, 4], "collect": [1, 4], "dictionari": [1, 3], "custom": [1, 3], "read": [1, 3], "specif": [1, 3], "hold": 1, "locat": [1, 3], "__init__": [1, 2], "initi": [1, 2, 4], "minimum": 1, "amount": 1, "onli": [1, 3], "right": 1, "part": 1, "big": 1, "includ": 1, "escap": 1, "charact": 1, "standard": 1, "column": [1, 2, 3], "uniqu": 1, "more": [1, 3], "than": 1, "mai": 1, "exist": [1, 2], "list": [1, 2, 3], "return_error": 1, "bool": [1, 3], "fals": [1, 3], "error": 1, "each": [1, 2], "datapoint": 1, "scatterplot": 1, "variabl": [1, 3], "span": 1, "either": [1, 2, 3], "y": [1, 3], "mag": [1, 2], "befor": 1, "If": 1, "raw": 1, "engag": 1, "sorting_id": 1, "nan_id": 1, "plx_or_d_col": 1, "return_delta": 1, "dimension": [1, 3], "scalar": [1, 2], "valu": [1, 2, 4], "consid": 1, "sort": 1, "same": 1, "manner": 1, "wa": 1, "done": 1, "clean": 1, "nan": 1, "encount": 1, "distanc": [1, 2], "plx": 1, "always_tun": 1, "possibl": 1, "els": 1, "Then": 1, "origin": [1, 2], "back": 1, "space": 1, "subject": 1, "pca": 1, "contain": [1, 2, 3], "predict": 1, "i": 1, "e": 1, "upon": 1, "train": 1, "model": 1, "still": 1, "need": 1, "otherwis": 1, "confid": 1, "smooth": 1, "want": 1, "forc": 1, "algorithm": 1, "even": 1, "static": 1, "x_train": 1, "y_train": 1, "weight_train": 1, "search_funct": 1, "rkf_function": 1, "gridsearch": 1, "5": [1, 4], "fold": 1, "cross": 1, "valid": 1, "optim": 1, "point": 1, "evalu": 1, "fulli": 1, "defin": [1, 2, 4], "default": [1, 2, 3], "gridsearchcv": 1, "altern": 1, "g": [1, 2], "bayessearchcv": 1, "halvinggridsearchcv": 1, "test": 1, "score": 1, "form": 1, "n_resampl": 1, "int": [1, 2, 3], "original_arrai": 1, "original_weight": 1, "njob": 1, "kwarg": [1, 3], "provid": [1, 2], "its": [1, 2, 3], "store": [1, 3, 4], "output": [1, 3], "here": 1, "5th": 1, "95th": 1, "percentil": 1, "gener": [1, 2, 3, 4], "typic": 1, "1000": 1, "correspond": 1, "pass": 1, "other": 1, "tree": 1, "parallel_job": 1, "directori": [1, 3], "where": [1, 2, 3], "keyword": 1, "idx": 1, "sampling_arrai": 1, "sampling_weight": 1, "run": 1, "routin": [1, 2, 3], "produc": 1, "given": [1, 2, 3], "alloc": 1, "self": 1, "belong": 1, "sampl": [1, 2], "command": 1, "through": 1, "write": [1, 3], "assign": 1, "subsidiari": [1, 2], "rss": 1, "e1": 1, "float": [1, 2, 3], "e2": 1, "root": 1, "sum": 1, "squar": 1, "formula": 1, "1": [1, 2, 4], "2": [1, 2, 4], "abs_mag_error": 1, "w": 1, "delta_w": 1, "delta_m": 1, "term": 1, "deriv": 1, "modulu": 1, "appar": [1, 2], "master": 1, "archiv": [1, 2, 3], "empirical_iso_read": 1, "build_empirical_df": 1, "csv_folder": 1, "age_fil": 1, "col_nam": 1, "name_split": 1, "filename_kei": 1, "filename_exclud": 1, "filter_funct": 1, "separ": 1, "knit": 1, "grab": [1, 3], "kei": [1, 3], "individu": 1, "refer": [1, 3], "ag": [1, 2, 3], "thei": 1, "ad": [1, 2], "inform": 1, "string": [1, 2, 3], "split": 1, "filenam": 1, "respect": [1, 2], "combi": 1, "opposit": 1, "appli": 1, "give": 1, "out": 1, "updat": 1, "convert": [1, 2], "retain": 1, "It": [1, 2, 4], "automat": [1, 2, 3], "8": 1, "differ": [1, 4], "main": [1, 2, 4], "script": [1, 3], "just": 1, "python": 1, "create_df": 1, "filepath": 1, "quality_filt": 1, "reformat": 1, "uniform": 1, "code": [1, 3, 4], "addit": [1, 2], "qualiti": 1, "requir": [1, 2], "limit": [1, 3], "upper": [1, 3], "lower": [1, 3], "numer": 1, "namelist": [1, 3], "format": [1, 2], "create_reference_csv": 1, "df_list": 1, "ref_kei": 1, "master_ref": 1, "id_col": [1, 3], "cluster_id": [1, 3], "often": 1, "literatur": 1, "design": 1, "choos": 1, "usual": 1, "new": [1, 2, 3, 4], "av": [1, 2], "order": [1, 2], "prefer": 1, "chose": 1, "ref": 1, "maximum": 1, "3": [1, 2, 4], "containt": 1, "modul": [2, 3], "supplementari": 2, "allow": 2, "empir": [2, 3, 4], "isochron": [2, 3, 4], "unresolv": 2, "binari": 2, "fraction": 2, "field": 2, "contamin": 2, "extinct": 2, "level": 2, "posit": 2, "consist": [2, 3], "n_clustermemb": 2, "synthet": 2, "star": 2, "place": 2, "assum": 2, "resid": 2, "mean": 2, "cmd_type": 2, "gaia": 2, "vs": 2, "absg": 2, "iter": 2, "normal": 2, "compar": 2, "metric": 2, "classobject": 2, "indic": [2, 3], "compris": 2, "astrometr": 2, "photometr": 2, "add_binary_fract": 2, "binarity_frac": 2, "artifici": 2, "random": 2, "binary_frac": 2, "increas": 2, "753": 2, "equal": 2, "mass": 2, "sequenc": 2, "recommend": 2, "add_extinct": 2, "extinction_level": 2, "constant": 2, "both": 2, "directli": 2, "excess": 2, "multipli": 2, "dr3": 2, "coeffici": [2, 3], "approxim": 2, "drain": 2, "2003": 2, "r_v": 2, "assumpt": 2, "flat": 2, "sed": 2, "subtract": 2, "band": 2, "789": 2, "add_field_contamin": 2, "contamination_frac": 2, "field_data_path": 2, "gaia_dr3": 2, "gaia_dr3_500pc_1perc": 2, "randomli": 2, "binar": 2, "sourc": 2, "within": 2, "500": 2, "pc": 2, "add_parallax_uncertainti": 2, "delta_plx": 2, "combin": [2, 4], "rel": 2, "drawn": 2, "distribut": [2, 4], "ha": 2, "extrema": 2, "99": 2, "7": [2, 3], "coverag": 2, "nat": 2, "delta": 2, "again": 2, "visual": 2, "present": 2, "chang": 2, "subplot": 2, "brought": 2, "add": [2, 4], "four": 2, "implement": 2, "also": 2, "process": [2, 4], "insid": 2, "final": 2, "apparent_g": 2, "m": 2, "dist": 2, "aim": 3, "correct": 3, "pointer": 3, "fundament": 3, "summari": [3, 4], "3d": 3, "interact": 3, "toward": 3, "up": 3, "hyperparemt": 3, "date": 3, "log": 3, "filepath_and_nam": 3, "name_str": 3, "accept": 3, "flexibl": 3, "head": 3, "open": [3, 4], "archive_plot_2d": 3, "isochrone_data": 3, "age_info": 3, "plotting_dict": 3, "scalar_mapp": 3, "one_panel": 3, "masterplot": 3, "boundari": 3, "colormap": 3, "colorbar": 3, "archive_plot_interact": 3, "line_data": 3, "cluster_list": 3, "color_list": 3, "gamma": 3, "to_rbg": 3, "from_rbg": 3, "marker": 3, "50": 3, "density_plot": 3, "kde": 3, "fig_spec": 3, "title_axes_spec": 3, "densiti": 3, "scatter": 3, "accord": 3, "power": 3, "norm": 3, "lighter": 3, "darker": 3, "style": 3, "titl": 3, "x_densiti": 3, "y_densiti": 3, "age_col": 3, "ref_ag": 3, "interactive_plot": 3, "age_limit": 3, "save_plot_path": 3, "most": 3, "boolean": 3, "whether": 3, "util": 4, "tool": 4, "function": 4, "basic": 4, "plot": 4, "class": 4, "further": 4, "reader": 4, "pre": 4, "exampl": 4, "preliminari": 4, "setup": 4, "4": 4, "6": 4, "between": 4, "pure": 4, "nearbi": 4, "search": 4, "page": 4, "small": 4, "vital": 4, "core": 4, "centerpiec": 4, "respons": 4, "everi": 4, "desir": 4, "influenc": 4, "edg": 4, "shape": 4, "therefor": 4, "report": 4, "mainli": 4, "serv": 4, "quantif": 4, "reliabl": 4, "author": 4, "rottenstein": 4, "2024": 4, "01": 4, "20": 4}, "objects": {"EmpiricalArchive": [[4, 0, 0, "-", "Extraction"], [4, 0, 0, "-", "IsoModulator"], [4, 0, 0, "-", "My_tools"]], "EmpiricalArchive.Extraction": [[1, 0, 0, "-", "Classfile"], [1, 0, 0, "-", "Empirical_iso_reader"], [1, 0, 0, "-", "pre_processing"]], "EmpiricalArchive.Extraction.Classfile": [[1, 1, 1, "", "RSS"], [1, 1, 1, "", "abs_mag_error"], [1, 2, 1, "", "star_cluster"]], "EmpiricalArchive.Extraction.Classfile.star_cluster": [[1, 3, 1, "", "SVR_Hyperparameter_tuning"], [1, 3, 1, "", "SVR_read_from_file"], [1, 3, 1, "", "__init__"], [1, 3, 1, "", "create_CMD"], [1, 3, 1, "", "create_CMD_quick_n_dirty"], [1, 3, 1, "", "create_weights"], [1, 3, 1, "", "curve_extraction"], [1, 3, 1, "", "gridsearch_and_ranking"], [1, 3, 1, "", "interval_stats"], [1, 3, 1, "", "isochrone_and_intervals"], [1, 3, 1, "", "resample_curves"]], "EmpiricalArchive.Extraction.Empirical_iso_reader": [[1, 1, 1, "", "build_empirical_df"]], "EmpiricalArchive.Extraction.pre_processing": [[1, 1, 1, "", "create_df"], [1, 1, 1, "", "create_reference_csv"]], "EmpiricalArchive.IsoModulator": [[2, 0, 0, "-", "Simulation_functions"]], "EmpiricalArchive.IsoModulator.Simulation_functions": [[2, 1, 1, "", "apparent_G"], [2, 2, 1, "", "simulated_CMD"]], "EmpiricalArchive.IsoModulator.Simulation_functions.simulated_CMD": [[2, 3, 1, "", "__init__"], [2, 3, 1, "", "add_binary_fraction"], [2, 3, 1, "", "add_extinction"], [2, 3, 1, "", "add_field_contamination"], [2, 3, 1, "", "add_parallax_uncertainty"], [2, 3, 1, "", "plot_verification"], [2, 3, 1, "", "set_CMD_type"], [2, 3, 1, "", "simulate"]]}, "objtypes": {"0": "py:module", "1": "py:function", "2": "py:class", "3": "py:method"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "function", "Python function"], "2": ["py", "class", "Python class"], "3": ["py", "method", "Python method"]}, "titleterms": {"isomodul": [0, 2, 4], "exampl": 0, "preliminari": 0, "setup": 0, "modul": [0, 4], "set": 0, "path": 0, "plot": [0, 3], "kwarg": 0, "1": 0, "defin": 0, "paramet": 0, "uncertainti": 0, "valu": 0, "2": 0, "initi": 0, "class": [0, 1, 2], "object": 0, "3": 0, "add": 0, "result": 0, "4": 0, "calcul": 0, "new": 0, "isochron": [0, 1], "5": 0, "6": 0, "differ": 0, "between": 0, "curv": 0, "extract": [1, 4], "star_clust": 1, "further": [1, 2], "function": [1, 2, 3], "empir": 1, "reader": 1, "pre": 1, "process": 1, "simulated_cmd": 2, "util": 3, "tool": 3, "basic": 3, "content": 4, "welcom": 4, "empiricalarch": 4, "s": 4, "document": 4, "indic": 4, "tabl": 4, "my_tool": 4}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 6, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx": 56}}) \ No newline at end of file diff --git a/docs/build/jupyter_execute/377fc301d988b684ab0a36df9df3d7270d1a4f610987840f194b80de03bf1506.png b/docs/build/jupyter_execute/377fc301d988b684ab0a36df9df3d7270d1a4f610987840f194b80de03bf1506.png new file mode 100644 index 0000000000000000000000000000000000000000..a0c707b2a74039181a5e5e38b94c9bb471113002 GIT binary patch literal 57956 zcma&ObySs6_bq&o7C}Nl8Wa#oY3Y(qfkR12cXyW}B_&+~(%oIs-3`*+-EjAL-{1F* zamToKjQa<};o)$e=h=JhwdR~_t`npnCyxG{@HqqmL6?;HqzHk)r9&Xk_)w6*E79xS z#^4_=2T?T#C2J!G=dX5#5ZSK|HWtgo^yDTE4mS4OOiY&l z{~H*s?TnddImkr8hoIU>sM|vzFTcWm;Bp0WOd*h!QOQq2$}Y+Ki_R{}(A(CNqm)!_ zNtE<}kq~7#QNdt|G71_FWlbX5+!;|-)yo1HE z{aYf7ei87BnvY;8&^Yy7g8SxBos7{xt^>ZP{CrwJaumN21U6YMI3Y}gl~pRg2-ph- zpD?izgfJ6BQG~%8grl*9Brp+#OjzEapo0I)iXl*dcc=IMAg4s}BWEMP3IJ~opw2Yk zeU36XoZ|eicPNEtu|+=qgYVTp_u;kfqnR@QhQs>)hr6E0w>R6F;ky;V_ow|#yifOM zkjAISyHGNLX6<1eYEDl4oN>udpFU-EL!lejCugW&y>leaN|bzDj#rRkZ^ZgEqMn$oL0}YX0>Z zr+H5GRMA;?|0IzCPviX0HL%J3Dk?24e0+yeKp-uJ$N99x`yphnxZx+xJ2~ZB7bw*A zY>+d7#qjyl-O|%X$K6*(6$D9xVrFKvbSj0*hYd%Ybz7iJWlc@jXDgy%0Sds=U z<|>2A^t-i73+emsAMcLB6bimy?3J{ff<;pOvYDM^B^+zW?X*85QI$`_&!0-bYNX4N zG-_70;4m&5O2QLcTKa*7g+;C00JY`elBl=0_x`}zdo51Ki-MQ8ae?dcEbZxdCnxP0 zCILb3(&HuP?d3s;O2NiRx`@Z)%@!pURhi3)o&z_@)0Owr^s6{pm-nOC*!cz@ULRjw zAurb~d7W)D^Ee+;^6(J(w~a(V&27r*r==6VU*7JO=yN1RQU-zbORKZrV)3}Pal72_ z-5$+M;It-{7kFTUBqSsZqzSYvtSKofE@)*jGc(hxmj~>O=Zv>_d*7b#v|H9JcCB`X z?9A6NK?EMJ-`d*RhPj3LIpYXP7%Wl|MY=gjqxyPpOfDEyK;q?ex?>; zpNxz*V`F0rS4aPvh#=9u9k{BRpEuUr&$oqaY(79hfD}kqA*K^EQ&TFNUmver-`y!` zY7Qi_o4;l^Q;spLv0jq1vSOr;&YQE_Dp#ZTxLS0+Kj|hrRM%>2Ydb$&Oaj}Tii$%` zE~!|w*J3(O?RB$(zq-2GGc?p?!ZucI`Q`gdvY|@T@gJd~^s0~d37&#=OW`CuU0|gp zWn~?gYQPTSF=@YOH7{xETJMb}+91@|*H7TGrzRjEZ~(VGSH9&$GH1bYH9W25OtM(- z*ltymISzfYRlqwQ@@yoZh=Hxg3nchV@o*!sAca~Dc!BM{+9f5G7V4@CF{;`@X=zJ{ z!=B5na7IJPl14^Gb$7$bT}Q*U1s~$QD87CB#(Orv3O22I;lZgP z<*oQnoAn;7=KE9W$CGexo3${`sqF>!(TM4pO!1e_ob%s)$<|GquvJeUtmARkyPH8+i&kmii<90n(S`1%)d*!BL} z_OSWRYQTuKxw(14wwpxLwi6ct5iv40wyQ6OPQA{K%KdVG#oGIhNZ|e$o}ZtebaL9L z;$+$XWx4Z_cI(Ag&#e^au_|-bE18y(mPf*n&cF7=YhJCNDbZyIY?H#~DcY4c#ThwX4s&!iZEe?f3sR%|ARL z9Pd{QukP)Av37ig07_5zufeGP{(ic+G33@2n^LC(jn)cvTkpr4oV%@bkwBF%P8~n6 ze9WEx)fGkO6Z5)6+~0dZtZG-jn+bd1CRa5)|UAt?=j@=@&I0Q zF~GX%LM4n^5L`D2nal$-r1M$pM4nRJ%6FpOEH6I=F^6tcQUYeZPj!rSJXHZd6oM zP%I}&d^D=eIze%e+!{*Zs7Ea6#Jn z8f)XJLiIzzsb)`i{=0ovaCo*x*KkEwE~a&iM>9kZ@2r|{jI>=ha4R(|i}t8cCIQws zp80|G_W0~9^Ut4v$pTgTovgTW!+t#QXsFMh*DueACzQurfece=z4Yk!<;BFO**Z8o zJ3B_T=EBfXlfvnpQFPa^81)Jxba~#B0C&B1*wO7K^VT#aOzr!aBA4pANpMB~(I;`J2A-T|BD?~Pq&58zk~r1H&^_=x=^?p4+C z+^~fxzWSDv>eff%Q>noKtF-T)MU2n@tY!Acg2K$rjTFAVZPr!<>$mK-Co<61j0G7eR zIRE92BKUdUUB>i(KL#IVGYM67y>}7Hr2{o|;>W0o!9?z7dY$HEcw`KS4M+{s+y3$e zlc!xo);6GcuGxHa*(<7#Y}Ty(%G`cgy9$Cr}kb=%uCMg8$(JeU2Zi^n4}sf*9W z-n9MkvJl8(qI!C7oEIJOLF((&D=P&>w)u9K&iUA7wRXNUiE=3pl2Sot1{C zXJ@XfLGSVxz5Y&5$AL3lH%6JNQV?Ui))g5U`T6h>+<7}mDcG2>=U?0fPJ7<+-fm}J z*oEQSb(1*P*68I1F}2)BQHXrE0Z2@v$}J-^b8)fMPeBy`Y27?QH6cbs5MnQc_Y2UyR}q(`PG; z^*_8;Yxdv*=<)jI=CiW$gvqoTM_xvC-xM~guo5=I|B#R%7$^CE=lP zi%M0JQI7XkQf(gu@nEwetWu~ZBqjCS%gYM}$pB|55aW4FmHzw+)K=qIdiB32Yu(IA zgP+93S>4V}Kt>i)P*4aP+PVmVa$5fz06@9l7aqB1c(@zvhSg#{GpK#ATBDJ3G~D|> zgX(@*5sce=;bEjt3*pj?(Umso?(CPuY10srM6peuzKD) zTplfjYnS9m$1wtI5FHzf)LN)s0ixR|Z1`qG6YO1Glu(D#((b3^{K9n&sq6Pro0A&38%Xw>%1YS02>#W%q&@$|{|H+!1{t`5u zzQcZQu3%8DWZ^Wi$3?nea3KEqAGPw;Eo!3T;Dr9cK7e(@I0vYeGtHhnumWj1{vA+?4<6UYgwvCB{t@BfF9Af$uO7&U z7C@#MBMn)30d?P%iPEgO<$ni*3WrwyZ3nj%UwyIjEF?P{17e zn%NH=i+byr1GN{$DZajD{=TCo^s3d|R8&-lX~u(z-zX*N)k=M8Yd=<7FAYgEH3jq< z=xy}H-0$f;<@ZvtKgEs!AihP4dDa2qFMpA`E;siFV8Ib_ae)BK%JbhC6zxKnbQ}n! z)cL+hc{atkkR+zQD-rT+eq%WPUGmI3R+0NZ!a$!Rfq z(P|5Xh+X*mo9k;EkQQ}W65?5nF<=b77KB<*SXk4tYdRuA`t7fzq<#>p!vI)DPzFtF zyN3bMVPaR)QEOysMnmJj*VUHxLcf3D>+f3L+mjX&5~^FaZ7x@DGi1ovjhCUm8U_l6 z6Y_6+*;L*Hkkca)6Z=5eHN8U_OyP-Zd3rb^jk`KI$vc1i^M{huWf=||2WQlTZ2AU`KQlBksyD8=I9hu0+Zs2k0-2V` z=i%;3Rs9g4YrzYp_TjBbArnA3cmac$IdFp24Cf`!?%zWGiS-)bSe0#-s#RI!eg!8r znb)=a?+Hi^cs_0Z$m4(}hYz_fI!?otx?Px!jgQk2FO`0U&yh=FXzl74HE!-tivzyqstop`wb1wWjj5P zmY0KzDoarVYQ?OhI0T4T;r$-`uZ*IRkz)U38 z5QaAaL;U*nE4^lIshBAxICEwN1TRqGj#opNu*t~eJv?}EsAYbG(h3k*eYYP#{92|+ z2S6f;2GIeaQV&oE4x5*BKfuzk%~8{p9pJjfO_v&a`udTSy(AHgE%$b*o|m(PljC&$ zBS$SyhjOCn<2x>ZofQDA+47VEk}ZcvC%81BBnTE5{{>*_eSu2R8wv`z6uEA2`w1MD zglk=41t(ndRp#AeS<>p2CRhckCDiZVqZX-1FEx86u$f{5IZZUDKwa&mkG#@+n(=BF z4B!pn^rCNWRW z_Ewt!h>bok>~AiJMKK5}MB0{qTV@by5hwP?D@aq!ZTc-|4IQ~fLz<>S1O@}}B!N_U ztf=Mhi9&06A<;^;;`O>}m4S(kDT7B2v+cOryx!@29Wmk&1d}=y!V`xP4q}BWhY?|V=UWY!I(i|=_RZ{5<$op6|9MG* z_Ca-N>s;kOdg;X5Af%png_az1l~2ye|3`UM|34oj@#i3q0LX4&ixNXkPywu&cvq%Y zCH6`Bzv?RhWUzba(3?!eVxUO3!$AH%N!O-lx|@h19HLm=ENC)L`t z<%9N7?4EHLFDVA`|0hFku7UcJ3N&y)vcR< zMi}8oR)*PMO9j*H%%I+Fm!WIRgKY;QxGPp?4UXK>kVHO?=TO>Y?4;?CS5@%G+Lu0| zblt(7d43Aw85GK_t2o{LGwoUo1R{sGX8kuiRflQq;SY#{PQ%UUs?6Y{q<+lWYIhNg zyo6ZxGKZ6`rKLU>lnk8to*PB3srd&)n8Ck6kf40PxUki?;yC{s3rzj6J+Lm^9ny$_kFC9-wvX+*?3|gG0fdw{hoy_fs~qTG~PYEmW$#cb?csI!NC zIG@`&(AW6MX=$JPP)Wxg|3zc^;Qi=<^x}0Zke~VZjny#;1-y8HGAq?IF<#IeFyx8l z_4MEjw9Ele7hQo=II`ma1mrY;m^d8S_hRy23XcZD|1P7{D)lJvvw-}X`uwlSGn1Sx zYO}P$%+8LbKbAoxbMzSC+y;2eR-h)<9yQ-V0AlqD8*<-|FGy+unU=jkfxVFfg?%Dq z1e@ko7s57_ffhSyU{p_vgEbog#YRZSV$iC8r5+1wAppo$Yy$(%$hrU({>jR6_4rpF z8-XHBYLbhePNh%<2a!lcNDp=RT?tO9@FKf^Hb7Iv5P(h#&s_`*C`U&}A^Qt;zCLF z){(!~cZ01#3XU=C<9`Chn2&o4vUu0^9_4D zO;&9Y5s?C3W0<(@>gq~5nO;a&Tv{4oUR;Ny9=q6GZ87^7Acpo|@0DCYD30u1kfz`? zeuQ1krg)S0d&zYryr8+X?ey8gE$JY;J!SU`!6gS(=VZd!dUYKoY1P?1ayCXle>NX) zVel|23j68^h)f1RF2e0oFH-T5f>$QU991jc|Mm-!B5AOTp=RMP;Lef&{`L+H8G&Gj zAx3~N2>jbx1s+dc$}{!4`zwevqHF=BC|9eKP(;pH0)dQ*ByG$s^~+M>uV+`oU49;r z`?(ql@_RlO9YReWLpq|a9RT{5E^PENt^YbAlyfTxH zK!VE1rv;&G6P^bTgVlkgZa)CqO7*%mZGL)mKdfED2=5O2?{eD|Cnvv=BKx=hdR+zK z*-t;ESDUY}@bDChn>B`17Vuub5R{bSuHHurr$DWGE2->46415LYp$S@U3YqQb(Nb8 z04>0BGZxjf{Q&(e@5h~>)d6t^_EW&utlRbs?7n(~QxS?V`pKJQX{c#68Fe|uGf3D& zXv5E~sjDcJM+;eo)>Y-wZvk-RDZN(J(`&McXG?>f87n&e*-IMil#~H}e$Rk*P(ZK5 z@dDhNN?dTvI8fsM3-V5`nYDRDc_=9nevj$|YzmGxbhWWvE=YwV6FP(*VD@c%_PwsM z9Sj~fNHeXxMfKw}M`Ep9eD9c#hLo3AoE*t6SpnpkK3R#6X&E$-ZHLqv>;Lbh@}bNu*rQmRFugQ-_0^F!OaEJltOHF2h;ltg1+6ww!0w%>iKMa?X8!tIzR+5($L7+?KDGhw z07dc6LVdD@9Io0-RN@gS9S%bJW@5XS@LG2`vL@PR`BYx@m1{uT(OLoiF`chIKpe(@ z_3D#L?Ow$yP*VV-+np?sl#>H84y#k)R+7G(C1(B+e!6HRrE*FEkD{IOKdPMH8Tq=X zPL86t>l?rG6?CJ^eoRG>SDJuysp)=D)l)tIDEq=5bz6+A(aPU%5Z?0<5nR%wKljN%f84EHPAyjYCQYtE<>UTw+%!QI2+ULPA0?XPnvPST|cXsjJp@&CFv6$VIV0 zi97?!Fb+O`H^^-$&!6i74RFD2uPBt5tGsLLe3yIzlSx=Qz1Cl0Ltj{^Yiv?DzhF-` zhElopD%r9HQ7E@AJMFh;EI2`6o$}cVgrPvTRXsQXd~Iqk&bb6bSfK&GjVSl~nCTp} zGGG8h^*Hj^m?TP85m}0uLno@=h)W|sidNwQLptr$^WH4hWy((WEu9!mp`Kh^En7c@ zcY_8pxmlQLAGM_>8;rW4li1HcY>%Xz?Mi1Y+KFD~<7dEd8|NtYsbU`@HMI#lHdZsz zsq{2z!m0fzcM1YwM|=eNgs43sjv4AF%u~g~2|g$SMTiJ>(+md1R~iilLiOy-CQLHV zq^`njau0i&V;f*U@aIr`TE56xVe z8OU@s{z@;ZMC)bcv!6zBY&Hi7Z9G8~>4{iEJt29A@ddeNJLZ0O;qjYw;Yq$UhTvX2p&>~ zxwf1_cQC(NGiXuL)&d_Qj2+%^G)z;*uC|EK_9f`B_CFVVpFKvRFCCRnuVi9hzG;B* z-ck=Ty&h10(1d33CLBO@bZM}%)Jb!7Ub)mLDLt(E(NMd2XC!jUItMxjXeXtU8ZJV* zF9467uhK4y$)vCg==E)DHF&;#E>?;5R^eVI#ObU0*n<@fBgvROj8*UF|- z0l^GJf&05|bf_VaR;H~N`MbORDn4s{8>iQj>59TbWa@I7h5UpCEsU!k;jXTR(JvR6vAvw25T;d zu?_E2ysewnjdR98lOEOFaTFIqxj*<08t`asBL`v$3ZLT*DeS!2kDP2upQ-SW_*x?Li z$|3wqo{RsASU9Z)(S7}5<7dq!=SpUD=||}4TtofZvnYAH$LwXizyaUFH}n|aav^UQ zhZ0IL53E0_D33|)Z?j|b341P993re_jALq zvg%`%gPtEFC-QqvWOlX}5K-uCe6qOjAp2poVfEXUM0M3{&)-3pTb22MUQACP#iiH$WP z5rZEPn?-La|6gK>kLupR4tYI9?~F`r)AaTJ!uaXMnENF>`L2y-U3Y;Xoeuo8vt?)e z&-B-htMcNQ0rfa(l=!IP*U;Q3xD+lp%aawm?t66OhV?P`3*_I>zgVH7h#P%bxU(Z} zH#ICmxvb1I%5UGGXi+L_kzXE{LE^_+7@X;6{vb;VL(@OfM=e~IN#sk-Kk)RY!I$>F z;Y=o17Vr2Cj`H>!y|899h|;bqdD7z5mBmJP-S`W+tA-aoUfq|!+&xMq154BbXi1vTt%4lJOb8+H6=$!;3!G^$dBTW zLb=)^GE&E@S1BmM_&AawS&I*lYfA6+)ZgT3I6e@?TMV%nN{5r~Z3=v5ZjR9Y`ESda z(^0>yzlwU`(XCcU46v%YJO^|yv6cq(jKz>Z+nW}q_5d&s^92Az{k`U&TS#(p@XbVH z0=pYweiyRViO%+E4gBv(iR;~}-2CADd^LE#p4|m_$U`>zVfSX@fraGI+ofH~rCo!) z9gp(P%Oy~De5aAq0THwZ`d69B=$ojhs2{<>Z&+BOfMin!x*MPqf%KDR+(Mnu_DF)B0aWxox(Y4K;U%2n;)qF0PY*-pK%Iga zd>-%5be3;D>-0Q2Mj7wCi99(Us zrtrD6;zO^ZzkX{SXgcDM@{0N zJ_X#Vf$pnXsV*GQQUCn;15~|T>O#}Cs0VkwkXks%QndB62n`n}PGu;RYtbB1E*H+R z!Is#el+0ME{4xAF@i246wFI?vxY1`_M>eSkM4@9+ZIS@sq=IYB{hSHhO(izGpx^%Z zpcTUUbX#zGP|^gI+^>MVX2s8B;13qsyUosutu{&KZ#KBxNAvl*cyz5CNmpF>pzqYP zFT;>q843(>?RsS}O4}7qCJ)#l0gC|&Xah14aahzI`}6$*=95-m_?@XDBEZ(!y&3_3 zhOq}An)|<3%2rm--WO5*%vdZMZzpJNfi+E$zUsa!%l-X&Y;IVgSmr+BGvu|mR-aEU z`LnReqx-K;KNy-2(=EgtJ(tXYOTr%XLV>&MKJeGCS1>&iK%XQ|>rG!|(q)0C8~KzH zC=?2)ya@1A6%DUU3gybD@xxju&7OBEZoHhFaVb1n>TsY#v=9$9$6F{$4^10Q3b!|P zz+6tOE6T?dSco}SZm~pryy4QEW_Z?OhF2hl{No`2A-yi1$C(jy_Hsb`17=#I*KUjl zz1B0(p#43*1M3fg24>N?y$1k~7W36ba$Co{1x6>`9YV_CF*B`7FY66)`+q2jhgmtYx;;h69e89aZRDS70E8kMi7QTL)qEJK{G#qR0lSAI8* zJEEOeyCUHzE%vEOR7;z`TQ@CE_pBLfVlSP6WB{0DeH7ugj_m)|KjQfO`SYPZAla(` zS;Ol--rrO;4*{7S_+>0X+uF<%qxOfh3XmY5`cF5CEzwE6uD|~M``7IJy0kR5Dn=;g zqUl_x)C{*PG%aZVju@WD!C~%R>Hnib5PZ-T%xdBVRE3Ak>zcy->X3?oAq@1SC${f{GmaPRhrgDo z!MYYOS548L+h?Tor~55|Lu&}IbHOBPVC1p03pPQmh@$Gf$S$aFPB{**M^w7KnsMg$ zt!uy9_(@8{pNf^%98&4USJ!Zv=@3fw37&$Y*jm8+W!7iq`n~*&zs=*W#1g$C1>@zVo=ibkB`~J{UdyyHI8^ zHTPU4&CI14w0R&%7{qEjCqO3$eFWfNGXz>b2+KUNttVizm~C)o0>M_xTNOxD#;`1x#ayD@7~WCWQ`VccCUgqAw>OKrJj3*H%Uj4Ya`M>a-eYgTprA; zs#C){bR8WXgeiBxYX&n*0OP<3(CMe@e;P6-k}HD_8~jV&R={Q;tsOx)H$dF_KuEMT z?`ofYUFpoEi_U+;vc`?vkYjPTQ?*T&4Ck}cP|~XC)ubR(YW?j@Qt^i0B1P;?RnJgr zXogsVP)@Z9IRbxL3^64XY`}{-kGPtL$?_LPmxMjjpYeDlTAN z@w`;ucjAHVEpWq}UY9}ZXzJI1`Lh-{0sy;1UjFBPv;n-HRujy@n?uBB2-y>&+fqNV zm5v3h_ReZ5klkfISmk4zc}t)O^a83& z`>R4jD`Xh`dw#cYf3r_q%tZ&VPqhLLRtxwg0lV3+?(l-2pjH(Y(jPXS$wfs+11sx2 zICfjr^H%1&X6!uq{IBizE3V1hFv`IT2aa(hmqyHO69g51a3v_1_ zHuOlNoP7@>PAht6Z>W%1!DI%FRMiE|m$!MNE|=eqVXoNgmB3G8Vl2i(#NniCs3nI# zE9MVCbJriZxz64AK!2qfMR2mTvWYB5$C>RXu?LPe6-7>fBkC;i@cXZWBjyo~Zs+b! zne#0rfAy&(Gn8_f9yE~a;W2&6qVVJmuh;{0Gk<=F)ispcuWJ{Z?7iUenn}Fi&QUh_v=l=el zw*OZcqH8(t2Iy*Tfq<7uVEIN@(pav&tJY;MfDR%p1drhvAnPZm=t>Mg z$0iKgWYmwvf&HZe{dGmGo#~+f*KWf|lb`ic$CvGkEh(9ndx_rur%&ik59wR#`>$pV z{(4+o$H@5)(Nsq%t&-EW_QY8Fzjx}{W>bve+6KgIVmf2`Y*-x!SRE;;sa2Bt8Q9rz zeE>l~OSPWNheGaw#tHj@#uBj_y->JNgBk)|sk6IVNkIWpYvi!M*ibWf3X~C(P_rtO zPOYbxBA3>cj{AQa);NC>cEQ`!i+h*r)ni7w5RV(D>AJ2G{7ijsWGuxGaSQ8+ms{DF z>3uuBs=*V005)qZ$MJ!E2}lasKy+2Fu}X1o8o6O%WtEhchPQcVTPz1keNbp<;dwl0 z9|Q5|&<@EzUGw{Qw39jV37}E^B;lEwm^6uem4*?oPuhL7z86~FDB|aZ;N&3`HRCki zv~YZBzrEEY-mB%U@4P#kz>Xnm*q%pBzg0}4NWqvH@spw%;fK}76}^!ci7>rtYw78c z6L>h*fw{M%t1Fi05n!)pAApDg8l>)RXM;(cC4Kq;V;tg*z}#M=H$xkf`oh8o3HnBF zljd;#7}+FT?7tpa!NTbY-3cDm3_Td+q@zEqP%d}DT~BQfetD<`+m#hnPC>Rm}Ee2o}9$t3fP5>=RkwA>1<66-9WVK!W z^w0BZQG?ff5VYTvdr58izQMJRel-r=U}$AmV*I-NA<7+H(70ywAo{AV(G#WVE&S{8 z_sN%SxU9QK1da}<7X>ygfW^N9awn*nzQFGX^i2^Ux&cKS7@Fc;&o6LWU%lDScAv>T@kLXd1L}U(W?aN^Er+>M{CH@M|sf|d6hP$h$-7Q&vQfun3 zSa)VG{~h2n&O8f>jZk2iZ9$H`eEH1Au-9B7A07&o+?h?gZd1+pY*5J5w9a^BuWd7G zPK9BNi<71$oH{8aC!3O`=dtMS@nYO4 zT?*UsQO%ceh#m29Y+D!D9aF^gTmlsoLke?io89tr4U!Ief=w`hOT{l@84gM&BN^un z`7m&a)f`+vWlx=r<{j3E1ZnYZdM4=exf`ADOxz!Nlh5Zs?SeK6 zRenQvXDNQYkBXT8aq#x!cOX4&!EGO1f0MXDf!st|&axgFLH>B(r?88&_95aosraiz z(OM91Dr+STqWaZfy%lB$%F=Qq4i^=%jpkphb_7c0;_{}wf8XuSChkg;Jbv(dp{$)! zB@ZwxO-}KQwfw!2(LgQYY^eb4P@sePiCbhXnkC(*wg#pCJeA|_{Q?&gwfv!4wjRxg zS*J0usMf;?LC3Sxfe$aIugrp(kk8EQ(1O`a_rBaJJs5bhfYzAqRLTF#!41x5<>$Bf31P@s{kh&!JQ1Y!w&m%s zMV?3aop4h0KD*Ux{cHHs`h8Mp)7|d-KaTr9do>4Q(jFQX^yM~x zP0$+3Ym}wflNmbEu744|N+GW_06loex03PtX^6T%&Umh7BJwB8SK(9>)0+2Uu{cOOf@3 z>@rqP@%2?(ON4=Hf#_SIyJe|t;{sY7?wU6p;yOEL9Y{Br785CF4S5Ske&m(Buv^HM zBIF=CL|$gu;(R^%=BjKdCne?22af|L2b7bq9yJnT-QQOV>@9tA@@ez)-_X&z;5i!k0O+DKo4cx&OhOo|tzr-NUTkdowX7e1mQc=z>@65P*I|p7D$AUu;&ki^jRDN9J4=DLMC9?Ow;pX65_Bo6$WORfEdwIYBWd)>qLX08ZqD+g4+f& zN}x%D;SJ1T1pFQ!@j|`uekpr8OS`xBrfnhV|6`83#$A;M7HN*R~#RO5P5js$oGc=IX0kM3ZIok8|u=JEZ4qX%%0N@yq zW?18S@rv)b6&~1h%Rot;<8K;~iK(o^C*Y%)@?6icOz+U1vfu?G1w9L4lf(1PH($4TW}+dk|%)=x0q% z=;zs}UtdhgxuLpWFY+`WC5H4xq?+CLduZv_Q)_J4i)wchoGv;QduL)g-*aA{J@>20 zb;M*zkO9(_b}e~CbhN)p0fRH>eQsaGlpteiFgB^QTRkv9&TSrj)3Qq!P8gz(;C>IM z^`kQMWm-nOOc8$QJK+5DEXWm)Bf0PWm0E$)N^1hPb3tY+wLRN(RY-w$X5O*o=OvW8 zKxBf-*F#B~SlXT3?}RXE^BpmF7wTAnGZW@cn2ZII3yGD;6&sbm-@RO+M z1$2g(QWDc!Tt4GIPb&xxI|P3@cF^@^!2R*3e#m& z0fw|xCyFkGE7<;syq?lH{wXTXYFW_1C^YZG#DCE z1nh@&N~l^Dnng)AoSmGfFnp|;aj^kLsq$;kuoA;PO%aJ{343K^KGC37DqTiPkX@a$`-?{sVab}P(0WcY z84q74MH(W8QKoa{n9~iY4yPBsssDBdQmF}L5ZxStE!%XctcuB+b?$NcQRet6c%Z8M zeBwU#Xl;w`-!a=bhvGjZ9pX@h?LX&K@`3OMHVbVEFq;6TNr7JwWC~&dFXDzpIpF5A z-yB#0WWY%PIQ4?Sou2l-O9P{x>RV`-iTD*FP7EBA2sRxbFnoMZSM3ayi@q04FCeuV zws^rGqM~f@%qyZ5?aMJNU*Q-pu&&5(qd&a4C&0#)Xn>3(?nNu;ZW#FDh7>C3#?3~4 zrkpxML6<93y3kBHO#@pAvt@woTx@&C#PpJkjI7@2pbyBMbTa&EAQX}Ow^^@LhU|?( zNIuA=hkL%~Td&$?A6|~|ph07E7uV{JC*!B&WeA!{A(E)mbNGg!p1+&e8U@wca_~iL zQW41wCygFDv#Rzxb26)uj? zhHI(HBI(YQ=-?PktSR-rmQ&vhkd<^T6o~0R)t@|S)JW&w3ZvMe%v+G*1@=6Zre-2s z(f7_k6o8G)kdY0GlX)tq$wS}4v^nILq!znoE>x0HujlJ<;WPcWaS1+YEK@>m-y7Q_ z#uhOza;)GP6vh4wyvh(L4F`x$#ZB%a`4vBh`ih{@=d2Cdaju!bOE@tHLR6iU?`=i! zAAa!t2tcA7yPS|osbAx;TIjjIIRj!($p@Zd7BB#)tCd=;P0VE%092{cyn>ZU2SRku zFUWA@-(&(UpRy{-!{mJNSPGk8&1-5oeft_o{MwEEfwO2eSf?d>a&a0bRa>HZcBn4F z+CUWU-L~`>sYyenk7;62+tYn%UPZeHrwBs1;#H4QF2~D4FijMLl=sJ=QNf3%>ILO5 zMX|uIUCF{<=;n@e2P zPp_x1EM((KPYsoEe~q*ktn#mfB7Ds|=1Ex~2!7MnC1z`>_m#2p-xYwLk z#A%+F1fUS*^Bils?PS3w1}~J>xZ}a7@yW@_g6mdFr5RN-A?Np|yc-LLdZS)0>=q-z z`3Sr2asB$piK>?xqS@t6D_M=W z5K*zn7+8iF4Hp*@$z{iI|NQ15)4wk!glMIY-MRPs2C>XA6K8vIs1h{NFouIvrXMdL zo03qNU1^W}S9G)p7#!W6Da*WTK3r^wBO;5U4BATbCjBjGoDQr}FbPl@x=}T)-EM$Q zW)PNM>)_@PM4dcd?+dv$WHS7;h2ke;9QgLB{+>2jgTxYhjqCVM<#fPF^^Fql6*{im zWgU7OwYUS zdA39#HL^oJ{XNb@kMM*Xeg`f5M$MJD#yi?L&hx*HIiyhLa5Y>yMunU&Rz8=^^Pmg( zpu>k3xUl||#&F<>S(Dg=9?eSt}83_%ME`uzNIU|@!& z`PNC?Sm4J2!#s{T=9s_?2m5LQ6E;F^_XGCOu3KqF0z8!meyKrOrAba+UY~y?UrsuW zB&IO__%{;W?WBFgJ9ntF6Gwj04hW3GKLT#zC$#S`-|ZzYex_P>aY9X?ayqQbz~PUv z2$;sMtZX5&rUcHntf`}QBCA?ocJrxY@TCZLcLz1B?w1x|T2x*^0Tav><2>A6WEu~r zdH@&qD_mUm-d6{(kpp1l2SAS>m?Kre5MJ+l+M3v`x+u!&q~iB`dl9&brvt=OVOjo- zNu)oQ)DtctfO^_VY5Iyy5&bxF=kly6PCxs{P?_MwH!r^x4YlZ|pp%Fym{c~gJ)X|9 z&}*k%!fUKE!zgL*9Qu!JpOPAQYhCMNE0TM;XbYQg29qvrU|b4x7{SyHK>hPp4d^-J zy|9TMbj}6X_&xAZkFpwB&y@NCk9iP)V<$8E;gfea!z66hhc(&7B`Q%L%-D%1wY~*^ z`m({KVaihHsq6kM)VKwiWbbHhE_1$_p^z&PH8@xdYTL(Bo&ku6oO)XxjqIcM9JUU! z?b$v%CZTGInA?);771(?8%zj`&$iCO##rY$K*Llla|Nb@?-rC4yIY#;!qh`bN=lnv zs<;tgBekmmYY0gNvk728tqZscXLBza)Ov!Y6q~>OD}uM({t{W}DEoro>%tGYf|cSn z5;z6lYp=LW32bnf-b>0*1FiR20env3n>5zXU*)Bmd2*7;**IaAn29=l&(rl@nN;4J zeN;zoSO5X|AgiH4crah{j;-=ESr`31HFfq}f(@t>9ac5Kt|?+-LIY+JEj#A4hz&$H zYSz>ZVrJg=JK2n}{luVhN9nnV@skUWH0Mt`%%l7e@Jp`A#Cw%o>(Y|yaJTo6Gc6@b-CwHJurnSE=Zmqg9Z z9s}h3QcXyP78J)Z( zlnqCI3psjnrz6^0L!F0~M9Zk7#^<~$qt|FY-n^Bp!|CVSRC}U(eYe)_aAW>1s@*qZ z^f$1Q;ToumMhU+470SedlfcYpc0SYuLwGO(b`5$xprigww>OHa5g3_arervHqz|An zgb#rQ<#2|$-R|UoFZggDF{=XJO<3~8W6GTA zIq)jdb!X$_L`9nzR7faG^-sJJ9h>|`^}p>#`>9X=Cj&I>i%4M5LUt+W-X=< zV6?GdxM|q4rA>DkxDAcLcQ=3|QVPCCg4AuBB79F{F9=n~;{=h+^BfD%++7xvxW!jx zS*N1nC6hL?H4@(|(X-{1F&~i_@-uAIcnEzkcKPoo7VH=Zp<_0yQ5294(tjdlvc;9( zJU=x3wq+E?G%MUuEdbm1e>GJ*48fKY%#LNtBq*+c@ry%SNBLpZ>?wwHFc;+w;3m+% zUDqSUfBg6%m}Aa`hB96BWqJZyOY^#t(CrgKgo??^Ou`!j+~;hge@xxR#JFVSFXWv* z^g?UdrjmC@(;kylvFzE3`_Ay@4Ws@SV{aXm<+{E51JVd0odSY@NJy8Y0umxfNJ=+I zw=|L>B_J&gFWrrxBHf+R(h>qHb>_SG`2K!poN@j*dyF;q+G~&DdU<)C`=0Zf*Y%lB zikpP9Rg-u)(kB0BNG}D>2eBm(c=hGaizj#4}0_Q?`m6D4K9}1-TYFpLYCr$+68h}gJ3XZKjj=b%05$wO`=VJ(s z2Yghq>Mt4|rm9J)>J#HJIk@+@s=F;0C;rkAg=;O&pZ+%ib!EY-aDtlj4$6&B*&}KC zyhcg-YV{aWtXz=5{WQDIZH7~Ld~{@eLIb9FPGo2oYMfP=E9dxKU$N`dgn^hrm0mD; z+Z0}(G!fSbu#wDWNH>IiOLR+ZBwLgs*z1WA$&txtN$oxJP$ZJqKSv|P3eF5FK=Al4@-p>?6>AC_=f|N7`mv(9etZ!dGCMtzWrHs`bF%!wN2ko!y%_n8%2 z%*@Cb1i3?d^%#CqF#!F5Wfq1|P8~%vfezZ|gqSrrvfhK+zZhq^QGUOe%9?ok1S1*y zjQ10Qtw5o9O(gL>UJ)YVZql`=n#Ob{GczkTdGu{Y*@q5Gl4pB4(c*}jG;be${!0(D z%(>dV0WYvj{DnZ377zlUV15Wu#}<%OTK;Vp^NTz$#d2zL|1}7u!Vugh;gON60NVg2 zL(Obt+13}<4sUo0^Y)}SZ&OMdmnHuxktSHz?_?Fvj<2E((oxdn{+k5xky|>Wny_|VV4&hf#O|qGpnLAUp|JCi_mr`8bwmq1_ft{hy&kvzmxtcOC z+Ac&WR~mM8>2Ii?UAYK1#7{GxPm7;2$2imnqL9eQQTWCc`VuheQr7TGPre1u&+EZ)K#vAux-aI`^z)E> zti~67n6|%1UQ6gozKs{tvw#0y?ko#|Td0ARnio1I&sDO(PA7FBfb^dm{@?P8b9fnC zY;3*h4CfHCFRtkaZVmkG(qKP_`x$vC)05o3y_^xifXzR_!WK4(D$8nzk9w240aKqp z@5jG5(UbO~G2)Mz&$P^O+1RQ|GUA_|@BU4z>WyHe6q4~`%?juD8NKt8d=A=&NcKJ; z6!o=wkm}v{={;)KNL=Ok-y)6%iQLO@Ni9Qq2goW7(WQEgapbQ&Q2pVV%RF!xs@E=Z zC8UC;jOBU88tA>XVs9O8^NN}tv6syVn@JVcdWv1@P#=!izyvD|lej?i1YNI`0fjUH z+m8`5{X1=mUMn4uvdq1qmBO_dppPAc%K{1CQBD);2*x4)2w6j5r$YFm4U z9z6HAMu0+syxYLL#z9t!%O4k`7C5kFJ(8=?dOt=dM@@l(yeT>~#NFKb`m~I*aUcGg zW^~-2ce*k6_MpClo5F>PMB{!E>r^f=<)h&I37XMUf18kbI78ZzM@4uzyfpzWEsrp7 z-RW=fJVq?om$F5Rol+S1{=El?eQ9-7&B{|g4sroLcA3ftJR$=#?g@e4d_JbylJajJ+Bd{Ql8SW z+mHzA`X)SZ#Y0}$?%kNH;$}#FO!?N-N+g!qH7|mil1Q}(w?j8$igBVp^K5Kv z@Ia<{V<^*LeM1H!frW*vX9K1@MzuO1tGI7h4+fHtet7NX9`m5mgelN;)^XbBLdEYT zRm>}I!6frh%~(>Q51Q@iL9@KI2BP~E(;3T^8Rg?-=viByG{JYgce&xcM#9p#S`N^V zf&I5UNqSB=$P@PmP$N*n6kKOh1j;s^G`6>z$vKo|?6l2sP7Z7q&OHgW z{_pN)LZ_;Gr&SclZI6*;qxqp05uMURa1u7u$B_mjKGO2UF=fRvxjA!0AhN1!q8*fP z#7sAmccOOuNr~K~@N1vASAZ}jZ*1CCUe`=3qorPnRAs57xlI+#B#-ZOta%56p?Jcp z1Et33D<<-3+Tt$NjAV~QHO}(FndwBaTW6Hds6@4Y^Lw16J(L z@89E~kO7~G%>_CZ0nH}}mjO3&@=xWL&U-xVVP$-C0ZdYl9(TW(TV_mn7&Gzd%W_+i z$tgZPlVJRy+-XC-`>@s0(MJdMT9;Y3EjU)L9>w0%c_O`f`&kwhd|-XI8M8t}FSOX! z7wA9U9OK6^aU(e#5}FMSF3~q#PW+M<7_4S`pP}50_m$02b=-{FrF0@iNwRZ$cK$Np z-nsIa$S~HPr_WCWZlk&Ak3F$x)&Y63WlspvpL>!7LxU8kT(Al?f(cA5?_|D#Rsm@g z1u`LMFe*C=xa6TK1~*!Dus)3`>>Jj+Y$Br;e z8MPokBQ!YIo3$&L`n6|pZCp#UT2d57Isw3JMuB_#kj9T3&Of$lj7;0I)J z1^@+=wY4<|Kp()<8a!bw12Yh2eQZ0W+(%;{`)(BQN; z6mF)B0+_#fDmKgy}+QL#@(tuBqC!I6lArR&xM8#K0fq~9Lk+uNzvr! z!basQWKjH0L1|!qJGa#(TLNx)s7C`2?0jvwxHb z^2t|HvOi^iP@Y?iO_M9{mQ?aOyeD61Ky;G1yp)~!QH3^LSq{L6pivF*ptJ&RObH6Z zAAZ-g4yB%KtgK7m9$p6{dP$9_s-=!ykWWL7pQ!Yk-}@!lh+Lx^V<;4PmvlNbxwSj} zhh;t^Y&>7D^a2qGA+ss8NuM5Jly_TH+D28#f0C}87SUbCf&FZtm{;@)yvc81xVCxX zg%tMSDg1_{?bKKiLl*TLkR;*%HxY;=JsF6SFE`VRp8T^}yDzoa`mR6{pHWNXE6M;B ziOl*?Y&_bR_SCQpd~PXObqbIzI> z+m@3_T@)xWLqXhXPVEL_Xbb$vFmI2IkN*l1W=a)8n)L1srFXmYxKWd}I|$+%e!Xg_ z4GQNRg}9EFA@St%5$)NJFn66=-#b~A$oC1FxOR6(L}aUYIn%myBfQaqA;!=Js3iEq zfL_JI%p9Wox-sv|p}#-M)z#VOW0>WRfaij_Fl#CNz0nnV@^AXarja_f_=-Z`CsuKr zr3)e1W0gkZQ7G?pFY&u^5!rY9c$QI_>sU4%UYDmLGVq_=El3+CMA9q3AX($OqlqFL zeMf)&W-GOQORV>PW9Ta&@0m{oQ$5_|n-{ORaT~R4E!XWCy)Mbi;p9)(L@F~5>rDOP zS5NX-Ml61PAFX5{rAyBr#oz0#^MBgSX>Rw1OvZRj6fngQ2L|&creqSQKE&gZ>NDuvjmumj9xGH+61Y9z`K;vDrh&$ zXFib92{hZ8Iy-7$r)+eR8<;{{l3P$9==cod`AHb=lbl%AMClo(W}U}Vn-X#w8k13N zIK?BOrv=Z4&&x{-5el!v)1@QRyZw*rJYp1BY>V08H)ZG;^WeolAe|k|(yPB%p>pxv ztDX7-G6vH04{szRyp7O_#6T(?a=xAbim9Blxk4RR`Qb*jO|7mrl_mZfgN#Ks$fj;S zbCl2Brm)@(tMe-0!gHMorA)W7dxGkP#(N7go;vRx1q;dq*S?|%g{%p<1;ZD@JMTwM zbtu|{nNfNbF=0G$d_Up~__>8VkCYzT|7~{?hL$JJTmqr zp#3?~QS)1qfH8Loc)>qmdWHl5gSlmL^TNo8+{doUriAorSlk)m6(Ac3xhx|a{peKNI4DgPgR)q5Fumdt1zEa3!X)r6j6xV zc{cT8TQ{8mRrcCj=o!c(k>0jZd1>Zv-S&yNy57tNv&6`p*gP=^14N zVx(%{5I6eWR>wP|^spf|WBoT|Kg%tLc<1I(u?=4u6O_K2RZzPg4-sr7;79;~m3DHI z*z+5vN(U>*Svdo(^T6WU`g|UND@kq61`DmyAuY$HV760 z(+s6{mV0s{VT|WBM`_!{f|m?N)`aE5&6??&(rM;Kf!5~1KNz2m<}}o}&;N`F?2#nx zzcOeVW6S-Sd^oamAh`X&=kd$aEYrHa71x8RRQNpl^7t;tnqcw(w&&0I=i(gz@Qe1l z2m(R|s3Ty40F>atMyfqLgI_@=f=i2TJMT*dTOZEL1&?UupVrs{T`rHM*Ez#+?=p{< z|DI#EHKY=lc=GO)!ly=;`yBINPNN>p;WC12xSI!oAR6nX^Pfaze%I7{y-TX?c5ORu zZMg^MI>d8N3ZSb5)kivx2{{6K4Ybya%gYBJke~!l2py?vBmla!R++T42+~ey4gg_e z>q~p&NrXr8rpH^noB?|9cUh;(DgXxxvLp3YT5U6LJ>W-|4q6Hb=CHq^1md+0L9 zhSIj+OQfxO$h-Ypp$g2@M#cIKVSDE3Q$B!~ysh7niboZZ!h26q)Bo0rk~pya~rOXXNP<%)brI z6O%%}+Drb8X?jQWxqLR^{aax?zlSnkv4ZC!fOo&qT$9GZwOJPZ;OedH^1{Z#`7hdE+MdUW8!k zgY>zC_z$FbRXR?Zs_M`MYZpr6Vp&xq8Bk=HFo@@ zRMk)KtygUuQbnGnGk^Kv|2fN;If|&cKQWj$%IjI6`)w<4>-a7psFD|PT44`PC(a%zkk004)=NrVr!{WGZH7BA816I zt~yGXv{X?cQAegnA2frlswnLA0@W;*l5DOq+rRzz{I$FRrFx)eaZQh)fV|>DlIpQ& zh|ze0A8-wK<$Jysh26vr9Hy|Q4F=qdq>&K=a$;XM52tfaUmsHMuJu9a@FpuE;~vO6 z79^2iAd$d-kSZ*Ysg|JpBukyGeK?bsjQ>UnlL@Cr2j8m|6HC_Dbsn#s|GWJ`Y{ZPX z17FWb`a$gnhk+D(RSnYAg@CWiDJ2ektuc$L9i$nLRhM%HaA2URy$smo7z$zp(%}F| zRbmZ|WC+m#ji%H=45GHnFp>2OFQ|vZ@@zs0u`V|H7@(lf zMn#CXnY%Z8=?W&Su@3}q-`(cdmt!tkR7NuJCTnl+oM^tZdxSB-KhR&iTRf-R#*Ap zoh9~!QaV|&_{q2$ASJJnB;=J9V_N}g1i}fdClQg6hi7L$!Q5mDV9FB>gXOyx<5m>3 z#NSI>vm5FZA3%k7GYbFb#?@X!iP{5YYB^`=HuNAhBg>E$mxS|2>bUpNu9Q+vL` zKJc;hetJP^(Gf@4-C_rxf?zYOu}aZSp;!kaGfLv^^NrH&7Qz+4lA85?xW7AB9}SAF zn!0*05X)#q-H@{pNHC7eiD6{v(0;wxqSzQ}$grDk^Cn0?er?ilC^)HI_ESA{e|OXG z-s4ldrF^r@gI|>8*<;qwETQBO1W85a^`fjQ1nbzk$5~VoYd^PogD&L&f~ta|;#cUA z$;d)pm0KJvbs)*BqgCK;f%q$o#x`|csuMoSLa^CXix3V@=#?3KrS-jDHh6pd=WmKP zMS~yjCBd)U^FyJP=F_fEV-L%`v6R=6D@k;QM2BYH^;TtPPX%UbwXk8Ilua%;BK6hE zt~O%K+}b?RMU;rnU+TXnDk62q-@{jUBP&Hn-diLY z!s9nBKp_$IUa6Y4z)9e;>al7Mk7yVU;$tjCzKOkhMmL3Dw5!~89;IyUOb}IJk*~RR zXr@)5`P+tC+NFXk{RzD~0o8;y za1=7T=`}T%KfJLPtu|8_x6_=qaNi{66A%wrC1P>mxmtE41i}%Q;CU%9q@k|T6lPQ= zOo4Fwv_`_6k&fVVs+j&?tJ6-DNff6Kza6kpbEdX8NciPHo3tvsT=kw@IK^h+!P|PH zY;G5?9I5)iD8BEPliO93rgq+Z9pT;u{>}G@k6F469(> zAWFWGXd|IR&(m;3ZCe-4$25^1G>-y4*&C~d+PdAatZigmw(q3ZRE zNL%=qz+)?;Q7J-N$MmyG-u>3rU>&-RQ)AB=@99ZX+Sl}RV+WB2tG^aPW^e6S1}h$L zr`p$Ln$84#V9R`rk$vOY%{@ZdAKfTtmwRZ>TnI=P2BnXY*cI{%a9=O+h|B z39_)`|I$FcT0$O)Yu&L(Xfc3Ro%%TH55QZi*&Oex0rE5zuenlGuVUOcfK98;6%eCG z3n{Q*rOky@ikhD0YxOuh>RD}?dB=U(%iK5d#``j;|MHAcuhO0Nb5uj@xAzOGs@$73 zB-*>^e>D2vtDHvtR#(P(Ku|!uZDXj{rE>AkOG(3)np5vxO52w4|BIVL53rIz-xZ0- z2GVL+RMb5#u4u>v!?p`#MFdtl?L1Mtmtc=Vj^U$UgP(an6C*2227}^I%wDyq)rH$S z`!)95uF1$#Ha|R%=ry-W+qU0qDEnIf7$Qnm99Xq%mC@dje$Gt)aW5`Lzdz%{8{aUX z2F2CN1`dCK8@3PTh)6Bv^YxWzBsrHk_^evMT)*ie0)pibh{j^#KcIN^fDTKA<5OB20-FI`4JYSy3*x<;!Nm*rU7tHCA#&_T=oacR0s0ps5+6g$-)=vc0z7#yj$+_njWPVG%! ze!g9Z``d~b?wi<0)#-)wbS_j{?ky{I1QFSv05tR7)ZynRf+)WZ>FP0>@4*nEMXtqw zN(lz}sYvC%62`TT+vE4eFAg5V5B2Mi01L_cL?C!zm;l(aEvGIp%JLwI?MML&z}Fq% zQqkWRE(Qyt3s^2+RrH%gi+xABx*+Ue0G_#5a|J}fRENBqNL#CB!Mlkf!{MhFMD8hT z5bsILVy_eH<{J~8-@O+0e#~XkS(uvKvSIUD|LVTCw|+>8;K9#WrB^BAx9qmY>s#-8 zPKaBy0e)_v8#trDTLt6CFwDbnyMX2DhWyZ{`wNQDRD+z}xFqZjzy=kwpcR<$Au-WV zqk#o=(~;16SlKp8_A4G&i$BP808O^-hR=wrB*M|bEY^leTW>)1^~TrchfUr#0;1*X zVL4pPJ-t2wzp9MKNsbiAD_*sFQX+6=G)1|%X1Y>>%3hnc=5N<4%&hF;vwXw!kUpM% z&dSLNzUdoSKuZ9U26WdbU<~o>Kz6{u;j+K_JLKmCcsNa+{9PZE4}E3M4EW-4R1_3X z!C(k8ORG)zKx|fgM8E>@s>hd=`8ri+QGsCgqCDm0^ANjEeMsw1J@w|9p%G_Qwy`_w zg(rKw$rc7k#0^UV1b%ts4m{0AaGhpxL&1(Z42=v#b}_Obp^lgF9GJGo->~zQ(-mNh z@_+;BZ3Kck%I0WZWS6Vmhpk5tbi5l-G|WDojw@37M8NKE<)1q!ua6D7vlx8jEvN7e zij(J(xLgukg&ccvSq4cC_sW=#6m4s6@fba_C!24iexKfdUrP0XfdP{q6V*ez=g{0V z>T0NEJ3Bd{VB_PLR;7R#<-c>>ScXKmAESGn?LUKtvm5g^lBGgi^_C5E98 zqcV#TRY+w>x3sdfQSqK(46PpDkN)(O=&Sp+)EP0B3To)ro`CT;Jdq_NS~TA*NO=qG zumxWc4Y;<>ej0na-lX{6oV4=D!K<+hXL)5bX2FqB_8k(fy+4PvUt7_ZXii;eVLqPN z%6TVi(pXh%RzK$n)=AjuM50q#_kHek+{^e2@6aQ)b#5pt=Juc$jDt6oUOw(4Eeju> zNNGr=*zCdT{*xLVF}%pkm1}A9;jV^IJAJt--){8pwgx@FJMlj9dZR{YDk=vghgDQZ zzKAv>9T6XocJO1II*Blzh`m{&+<9WeAkVasg3PZKI1EiGU3R&V z^X%Lr^Oj?2D5!yyUfBE!#)mEmt122$1HwR-GLFgfchoPK{;g+t?-%W<0jP0%j1#^3 zvH8NXi_;o~FK1)w+=YaZPJ3vJ(}L(t@rv-%t%3%xJ|4~JhT8>WwStM7JF_Va_kQ%h z6eVtKd(Ow=98oDU#2KTZL5dUp_EgNJzFmS$gb}ba0>U$oycPXnvNTTc;@U~*OnhvE3QMJBC ziCdEJE1T^>1x$tCLqv>?Fcz$Cu{ zZaWiLT~Ld#DGeG1IqcP3D6Vw8t`A>)zwrYCrZ;bt-e?{0UE_KOi+^w3rRM(_yr;kA zB9bxZd->tkz6WON*Kh=@rK^P?!nqrl3MVZ>XDf+a<89Cu#?454xd&~*`g|#m$@cz- zfL$blWvoq>3ZZnWbZ;;%Bl{#E>AjO>1SnpSYmc0B z400SCcVOz_;P(IL&ObrRdMDEzd?Sw_Z-tB=z@7!TkG4tt+rQH1vMRLBqh|>Z+wkuz zVSA;M;S6u_mDK7F`Of80Fo_EO{u6tW6n$eUqw`v7)g?~NH1B1wgqSW?qT6}%U>2G_ z3Z3)Y#2U<~V1F`=o@@ z`BD^5Adeqp_{^H59kHV7u2=r5b^GE84Afy0mPn=?;kH6?EX6FtyC|0G5i5Rlj6dMq zg1hQDZsuBT1=ePvM91N8OhiP)L+Jm1kH|qiI;p5HhAVA65VT|mR;nij0e149 zU>pefR>LUL-W`fuk0L&}yX42iV0yo=;MwxOXuq|5euK)|9|^n9(b8pu1~#5(>ixot zms0F{=m!}Lm=v=;0&?h6wzO_`Qb0hCpP92f8|>^a!o}3oWh9J9sH# z-fnq4ir_L*2Ff}TtM9#g4V98HKu=MC9S@6g609@5!H%m3e|KkMEQkI#)OlVmJW`hO zO)}`C94jrQ4fm!^s5>zGw90<}P46q4e)6Sh&_%>CusPA^TZ@%*m|`z8``WIOaIwBD zqtscqWF5=8p`-e)m!>*tj;8LiZ^t=bXgJPN3d0$^^~kMpRn`-1Ac+8l7a5wj8q4Q? zJuehJRQn(J_us#N|BGEPqojVsP?Vjl_F!g4hO|jPg;756;J}|u?MMD;Z*^Nr+KHfr;2TIIh%62H%93E6M2^8bj)ZY09nC-2f`@4qpf=eV-D@jAgPK@Gh z>W;T2iN6JFw6?lCz3wa%`R^COAzwO$lYq=y0(Sil@E6#V+H~WXz@FCG`<~`?clN$k#T6+XT?Z`YtaMM$rcBE5emvdjdgIa;&&oEvS7j5DzLv6| zu5W2(+4Zn412Ih-t7f{M!@;secDp@HdD$4Xo?fLZaTuImjjQiPr(uquTmVYZ0?dl0 zt1WK97D5&v92b}W!<7yieM*$nS+|lOK)XqDyM3tB-LZtPr|8&GEP_CGPv`Mx#xgN2 zc1`a_`yz2nj-c64qLrL-ht~yY0tH_JYS0LBN%i30 zE9>!bMuFC0fnB>*T!u?tVdmjycO2G1In@qx=e&I@@)gAb&9cK_8!s87(WKT^^|NQH zr0N>?800{OLK|nm28zAKw5gpwbFZ=a}HNg;srw+Jp@?1kX96^h8I{8Im>Ltx}l!*#)#l*WD5DxQ2BCUs$AUoy|LcRLaM_-%YLf>eU@M@R^a`**HZ`qjrB(q-KX)Qh7HrNTnk=u39@Zy-M0G zmJ}Xrtc0u*){L9}*9-TA7;A2dHzYi8zkZK9P2=>I`woZ)cT;cVMNpVHvhE6}4_%F4 zU^Y=nSzdu`3A~Z5@gic#$xI|3!$vFsxxpX_0yEZtMoEBa;4!?PV9=F@0|LG!V=$Q` zo03QHIfQ85%a$h%zj^yFV2ilOVNbqsI{id6?#JXj&o88rHJ*1RUp_MOoR}yJ z12(NnV+;^g4WWa210yGjDA~z!gI~%94A>|yzlV&7zyr;A`?ldXm4EIJT>heduo*q$bO?`NhX?d0yCTiNA1C6v|Nb&vA*)nttf_rY1$9X}3sER=52hRr}br%}L29scQ1N?0)Q_Dwh6FSmf95l(Y&W?=_ zZ%ULgB+^3`N2I=4kTBTPTGmpjYb^W8jBOQ4DATQqmkgym6th{cEH_yF+qGeGa`>17 zU)C-3opP~Mjw41zFY_09A|Z_g+VCO*D9GE;Y3BoM-ue#p zKf1~ehZV-JTEkaUjyhN^JU z{Ppo8)&&VgjSgd16+Pp}iKJz_w`CmeMQZgmt*KAARtu?5rgvM9+mLN1TVi^aC>zw? zWn_fI&j7h54vL;t$Rj{xcnSPia8Oc;dGUcnV;?7vg95t)$&gMr7y+9D=mz>V!&)8W zEac(C7R6g~AQ~ibd{m9yJRl!S)c^VT z)f(OMbK_kTxeO-9&J_va`J!7kT&ZC%LwSvH8k$alZL_w4;v2cE?4_o1n$MwJQi@5|n#NJNH8FUs)B zyp4A_8@(koQbsL5k{&aF+a`_~c&Xo!>zrzMnn@nq+q5}8dYkFl*2^Du1;-xrbqOzr z-dW?~U%rY_xSlu@Zq*2K6`>P#yD6gzohzP*{_2?>Io##2MFwVes7Rs&l>5&?aDmlZ z@EFkj$E^>?95V5W+&#rF?x(EWH%%oKr)S@k_~OTgp=1M>j!ahjHdDXc^C3fGs7O%0 zS&-cYT|0p!T2+2ZOW{}@%thl2h7|4 zZcrl~G02JA)ZIzgQRD!p6H0b=HmqP1q~NnuS+LQ)0lTW!ASDf>!2{4?2`M&bTly{e zoM318b@X#jy^( zxUxBS3QCNfyV==1VhH}BH~pjO{QDuXFzH3(b%AGp^Qth3_Ogc;!;PjoS&ikR_se>V z+%*1aMAQbqI5S_4@Tcm^Fv^>fYFp8<2dem3ADl@)ez)pj4{<+YVmR;{z(wr=L!rLB zHRQD~?6ejpn(7A14D73v%z6G6Y1=>ne^`~k<F9&QVvi4HGeVA+@FT7}*LlqJ*kN~-!W(OGiwN7aLH^_QNpzuNvFXkUm&|ne`UlTVFt>Dq{ z1hwek@X!b>swbLO&jJ5-!vU;~AnWV}z0%Yqd_+pR_7(qfZuyri^6~x6W27jtO>QZ?p};x;o@g+zV~2kJH(% z>jJdEgt^07CD;w+2UE$$D%b$ic+V{j5usV!0U7yUHj+89)5eqoaoM^kD!)Q2G-vv+ zwy%dpXg_G}LjIBo4B?dFRs7Orn$hy*_i~0Kkd3XXs(P5>0Lzt9?9)R=j|3b8r5>@3%N*&<$8(OW)+R69MGkYR^&BxK4%AZc+{3B#jfh~UBg?dM>4foQ)% z&g8QL0+5wvN9_v{2$-%NayOFYT&cJSHnS%&Zb^AcXM1-rFog>VdxBX$@IqnPN8?Lx*z=hQ zD-)2q5{WR3M*%BJ41k5R*-1&*1L^_(VrV0g+bSV<XSW^r2IlfQCG$*9g`Fv?JR)frcd zvet=o_w$+vh$80+jKb6BCk-0EhB3%h{C`n z&rP8hPDM+A1$$L+!A%YV=A>?(7(aAwi5$A$VY#`2x;hDT^^mlAi(FJ_GszBV%F)f4 zR*YYxIj)35dJFN%IZZ~a__AKD1oCkeh_;sW^IN#<^tlvEQh(+~FIV@n3^6-$1EV5U0<7@RVue*n$VqDiO*tuga)cxaY z#$y)YWs7bD;xEV11B_e^3Epn$%5WAYJWOQfn6SPFy8@}?rOUZ8PZe@TU_!S!#~g-| zlTlWBG4jgr_)$kSoY%=s9&7PYS`TKHDmazAIPmuARLg(ba>B4=8%g+qWE{9n!HH#P zNDt@@S1yH<<6}nHp$yCLU?0z>1|&n-#>Cjd+V-Sl+DVlZx+34tdRJE%<`)l>VDBe) zsYPyNJ5MWA+ck?^q8pR|ee94vJGRbjY&rjW?V!tsm@MjdfQ=%oulVeTY@O{_*SP zMVQScdCsiVKZ$7yz7ULh@wdtauJ!(WR0n7LFt3Vb!pTuyZ90BL74>~VCTE2z^N81y z@(#7~4hr{o?d0#)I0JeOMN&G_*Nyfbtr^vgg|3Q)@0jF+-@Z-2lU$m;@`kL+D@uR# zEVdi7p`)DRLt^qBmg6~7O&ZbZ$RVq#-mi&O#m?BrrdhlI zt8d*oB(l0%_kyw;3S4s#B)YVwq;p!1OgD`=zg0Ynk>4lcbNoO?W!4fh`!}1=u`)TJm z1-e}h6?2liu*{2Km!QGkk_8fRH%0K>WX$?{Y)LdY2D~*>>~uxu-m=J-Eoj>*zeS6@ zp(Z(In|XJbe!*gKp7vz{{Rc=Qfn2J>d|i<@HTZhI3;Md zB%kAIc4GU`FKrlST&>Vi*peaHM(Ub-&yD)R+1uvh+B?P{r8&*Kew?7D8tZ?X_Upk& zq-G3cYntx;M)s5`DGDGnCd1GX><%R=8*ro`rA}Bsd;p{wCs;u>QB)N;Ow)tt&G;=% zj6$i}Tr?IHs44qbN)_Y~Gu_uyuE`Y94MfNXm|TU6+Fxo_+c2 z)rSYzCq^**CMQbU&virKk%$pF^RxIIh?1XB8O&n=L>DJqC>GzHN+;CDyaUU@0lCrVL z<2(Py7Y6`NpfA0Jy^!j~=fYVP!cnRbyATp6V|pn~P$cR#)%#E598#jup}<^n;5GR=b0y z65SVhVH;SFE6ze;$%G>jpK+SiR&&HVD$L_=q|Z3KRg>1sY2H^vGb@9c5g#J6a(r$7 zYj8COG1wLDx8GWA#(b{ul->v*8#mCu;a8YW!mLiIYmuwn2%@%j-_^j{hC}@l@maIE zfjkMJUK$p7_ft2sB7IEo?v82d<>LAI>Y$Q&RcvrD(^t>)l*E1@FY&}DTMP;hc`A>c zyx9@PEom=xSUr;KDPv>!Wc>$?YN&j^C#l)m%l2{Cg7oKk-7bkK^07DmV%ddV6cxOk z0#-3sks6l-(ky8XXmI=4PFG}gts-;V@cs&Kd^GuYt`hjLgf{W^P{W##bb_-w?W6|Z z@kEDT zbyIvVlfJ2JY~#pSK<4wwd{dAd^{+0oBTel#%nn@_YWTKO9r z5pl58aPe+~B4=Z6-;SLCHH;ULqB8JUoTrUKmmP#08udWF2!+@G(~bx<*nEDMI|hxw z-o~mq41B299TzO0c;H@%5!9JYL0TCk5n8puHxMc@oZ+QkZhqvk>NB6@_F#kYvLEp; z1yAB1R(Yl;Mha%Jn`U)ZLxw?yBSo^j8;UGTXDq3G&X=u_r4@~wh`>W3ohK`3A|+g< z7Rs-5%6(bl*<+JfLq^W6ABu2t&)?qG-)jh96=#zt0{^MR((z4l#yqmrLR$9&62V4o zgT-LXk7nT)=ntrSqdJRI^5ZkjEsP`5r>4kPk1*e@1Z8alamJIJ&e`m3*Y76kfD$ z4IAkdS9U0AKXR6+7xTPTum78m(;JOh{^tUI-bap&r4=n&{kVsW?*Br{UAZ4^;#+>; ztBXzAZnq{1cuJvToUckqkgYD~5~3ZkAnmCCz+8qWWc*A0(+h*KXS+`1{x^8a%GMLj zZu#dEVOx5h|8go&&thJ#L%l7 z7(Cb3rUYp-vI%AkNdQVf%ALsVvNyjy#`zNFrX!`6f$c{F6Qs5Idu=6r#&OfND!0Fp2lQNg(k1MHcAN*Lvc1P(~ zS2R@odaib?9~v~je@YVGrBxx_LvCn*jr9@#{w?PDEc#tvVjVdIK3oxIXZGc@v28#* z{rvfUNA6S0h<8i@5}$4hvrlC+AF7N!ev~~Q<{FW7Y_s^uVMo0!S%6MsLRAU(Rc6G* z-7Hp~@{)x<`@yvL=q0mikzEBjMP3eCoDHN;4lWRw_#AiO8=y$_+PuehGqHoUn)s`l z^yM#{Qtj#x$adA>=)9mf^GmDr5-M#cnW%euM2`_>!;_ z3>H`qqwu{XG!A_}A@oR)G?d><@-C;7#3w`g+1>Pk$fzka!^ZZZ1#0`Q-IGsSpD^Ej z$wuVgwouL9NPmRN|4)%&nSx|}C(dhI$J-!8aWkOMaFzwmbwIR#1AjSi1~PKqi$oyz z;U*<@K?Bp>*JrZW;(4)r%Wo+=k`p-}LmGIH--pnqjt|?9$(n;_u6QT=H;Q{SC)YL% zs1-bSnsKW}iG;G~@zfls9b{r1zflIT^6;O1&N%*)dvz0qhZCMsjaz|bSvjjGMbk<= zFKI+$8^U&5(2J8vyni~0#s=Kat!X5Y z>*r|O_91!nM3n@Ra;-OPis)}L*h`vdG{(o7bDit7yir{wDa%-(%iJ&PETBSdryV|^ z&)NyL>Ala~2*A;yM*G}~ER>RmJ0Md~MYX%53DqS%mNAR@|sNfu3OqtviJQ_b>59|nrx z1_6xJ$>)T?hu^jz`LcVgs)}d336QZU72tX<+~FX@ErS^f1)uuCK6$0;_5v z&|!F>JM8E077}I3)c!P8oDY27(|azf1ixFg^0Z@xMYw9kOgI`Y19c~2O@-MAXG%7f zq$f8$vo)^b|5i9LpfpDIYF!LuqU2btpI{vPL(?J+&-lleWtf|jv$dDB%`8Y~Pi!^! zWogHqFa=#ch-Yr2+SJhBBn{Q> zc>O|4fAQPKtU%plZKYFYwLt*3WaP(8R25U4_`4>Rtjj0TZpF#f?`irj!jrqJY)QIr zE?#^7I3bx(LcvROIZ{wwI5ZOagsvX-U6aeaN9glV`N|2_Fdx3KF{>(zmlnahtVW_( zjwvo<V`_S{NjWX=G3ton-#gXv9oGCtwQQC|C5!rfbt#DlDR&to2cN1p zbR83xJ|pP%-|4z|Tgl(4iub}jNw^4Mhr?;fA2>2iA{sAuFD8?WZsN|fu`fxQ(RB6Y z*OdN&!_=*_&kH5c0#Kr&qH^=|vso)&7P;r{4l$k*Q+XuVy_(dNWtmk{tmeIccji-0 z*{jeKvnbo5*9?RY0Me7)(v9fE#mz1&ba7&eEKW~GhgYdUQ1V6 z3MH{PXUUMIDu&NaVQL`G>!E`xoKhsrU{po8}#N;O!+DvhY?F@^aDBlC?I2g|-H-KW*H zT-dH3*M0XSbyoN$$C8zJnBxPPD8S97flATkTrt z{9}-L*L4y;-77`-?`a~_`vH05!9pNUbUGWq=1Jsy(Qw8ho?R8t!(>vM67{Iia6w2- z5Kq%g`@1bq9C^v@pMTo@2zGicf^Jrm+peYkT4W#`hT8tZmo(ELuW^7vz~x;1s>zxh zfryPAUThvw=V1F^biHL%R!{gY42nufBZ9PaOE(D864KpBcQ;5$Bi-HI-QC?S-7Q^b zp5OnRcfB9Z`NUcewfF4VGxuEg75w}&A?sXqbHDq_WR+Kzch}@lT!3pj;XfZ5v8`@3 z>?rL+C6H;yO8+4k4euunCMoxto-Bqex>>vr=u?pq6Y-NbU-^Ks$onC^BQs{s%u2$~ zsLr%+xixe2CS>&wU;4)78zU127wtwQtq(IcD`Il&4zgq&a=$Hun{S_}EW(k4#oYA& z`HPO8@SJ}nh5bg-VX|@Cymw`b862phC&!^D&e|6yO%5d*86p;25g%iv;3pc9wC-$A z-Dd6rHA9_+n|oP*s9CJ(_+|fVAHflJ!*Z(?R8_)?*|N!VW2J^1VPb|^OSP469d?jxt$O{_*!g{^+aIH zTyd^uele7QpQ=K?bJ6?W~e_1_X<%Z_UEv{8x_XVrH@!cQy-L||F{Vw z+?+UZ*JCLllW`l>FY`)Nc4JT3QWRKjx2X*>3^2aQiiGmUwsE=5EadcP8_ZkED$0h{ zKrvN#(C>bm0YWY=fj{JplZ1u_9%P9GsX%B~S69Gq4_hqq7JTat$kA|DJp@qvgFb&x z=HLiMzno&HqmQx83uC0BVAp_=&#KQS5y7_{em79*i>p3uGK`09D;lJ$e$#46WO|K# z`AsCHBJk8)E36RPmRq=tteyU&M4y48({q&oFMaWj5AAmTr)shov znFF_Abf7}}39G@XSK4?$wYca)SM3D)IdZD1gFs<11maD5fmT=wD zm|0%kUjCb8NZ67h zKJv-xkd{3K?hicM)>G)?qAYCe4qQH`rAI~5mFwa7XT~$}PmAm~{mp-O94BUKzxheE zEy^+JkIje@B2Ic%mjH7FYPHVCnp!)2M9>9K=7>t_>w>)HdpM_U?z;CHl{HBel(izeSLdyLFKtG!cUT+Pl1;iysp62P6`pFcMGGd9MI z|44y>UKqu*cT6uxAD+2&@9~M}DYZH^*mm45URD=R8Vdd-Q(m3BAgVsT$fkq1CNg7p zkf`zQ_zp#PEdWjcoI)Y7&N<)XUO`kxK;Jxdd=BZQLV-%0s-U1C#iH$YBN+O2D@yvz ziQ8vfmuMF8ALr>JEB&_Qv1hQXRsV=CgWnvYSfp={*~VUAg0jT%40;Gh*0mnV07YL_ z7f)c^(C9nD&3B>8=U0>Y7)PpkNsIT2g@=j8##dh~)j5%hI7}GwN{wX-Y;dkw%WH~% zY0Qk|FShf(tI%erMYm~Mfv8sjN*D!6DY0DT_PDM}JBO6Q^QW$Wc@IoPzkw5G_U7wwd*go+F>p1jR3(&$ z8H3E+2+b)9`p}Cj3ExfCNRpAV%ai;4-X(#1K4=ceyk|gpN1j%j>ZhiZUci}XBENk7 zM*bCa=#CmEFC|_Jq=CCG8caSiwvn6P z(^W`_`pVYwMsiN2Wo#g5<1H_(aeC#9=|7L?zxQd{o&5QEdhf%ryKGF@O-I?4^1TI& z3>BkvG58cPuq9>dTMpQ6-N-1smWp4(9~<4*(>KoFp4};c8dcm7=g>hx55D9bJpPpR z%AcX*u3h9GvU7tUg=&h|=K2qDZr0IicKkyjbW@;NVE{JMywA6Kt1gGMyifn+AcArU zGW74UH0z*rKf1YtPzpi&vGujZE||=q-cEMf2yEf3Ehq^5+U~?;$Aa-OGCBD@mhrOp zxLOIG3vUEpT#Zu}*}a+@m1~McqwK^+PGwEYnepBx;FxV`v-pmGkuXY;7B!0Esv7Xk z#NsEfzDvO^tWT#<9`0?HiQ$V{i_tyokub>70F>}lk4)yFk$ z9+2~0e}&zPIf=t9sUdhpv8~85i?^O%earb3-fDX#iOz937EAPpoWtWXQZEi=Q>2hV z_zX>CtN}LR-ed;Pt?~p=`y+pn+Bo#@YJb(hSGYb${o-Hv)=?V~X~@|fT3*snz~3in zEV(y4oaGvN3T`Ia^c2y#xi?iP!j&N5gYkIU%j<@JJ1r;(5TUfZ!cWjx)i~L{24X@i zFCdrsAv5vdo&|Y?z;dV^LS9`ZTK}4G?b+W?JalXs6y}Fd?3d}Zb>0#a>!2OufLt3f zySje#PoGQc#5{d1OnWX+c-TS=m|sI!n4Gug_a5itY@SA^yE(b*F0ab{J9o{p(h~FUObmZRK=!YWX75AFr++);{qg zcxY36yS);R3}Mr-T%`WDx=zU|%0Okv#+5Z!G%_msw~Enl+FsSFG<);VO5B602}j+i zaWrhPRvWLre>Hsi84>@hi5A0#l0Alyuo4S~%IEY0ijFtMk=evz@R8Z;m!`@RjGApy z?u0(%HyWLIn=fzqyw_H*KC3ZaP>PSdY2S_edgEPc`!b|uy>utSNXPW6BnNSw^$_*f zk5|bf_`?S1<|Uf5xqVE|@*B{+O+Hy{r+(uM#2OTGB~2XGgt)#yJnHJc3V{&-aPk}U za=p%$AASW45bD=00WRUKTPyyqt3VxiA?#fx90k6itt@QYfyGDo-35AygtV=l=NW%_ z+co@aa+cBIt!Q?5oY01J=A?x4fnHu-JgwjCQJw1vy}vbeG;lJqUum#mR@~eFz{vVq z&;uSi0?ZidlP(xN8sk0fe{S-KlDM!b+PchZGwxsQC3L`l*EPEA7o1I5;cF?FRmBN}x zY!ew+hcp%**Wp3`zIS7C{7zLZ%dx3OnMOm3V|s4x^=m$IUeD)8O@bvg1`cwPAx1!6 zeBBs64fglMPkP&q9v;tLydFM%W24$ouP7|8WhcnQQ*gy|!GT-YgDNjfa{YFhM4|;N zlaqT0Ryb0>_%0zX&Y$D+1MP?fQKgH6h_I};b@4#9c9lxG>d5*LXOtM+btDP?{1X#* zA$D%Zt+B##&Hd>*ei(iFhRwtIJGq*w$Rk{(FYvH$QuZV`>|kL+w%)cCLXhhhRV5n6 z?YA9p@6k z&EncF7g6S*POB;2dm>c{WX?=)HtT0o?w=>~5`{K!0DH+$Jy&yTI3(&Sn~U_-t5Kw`M@s+gZuT%npv53BoiBm<$0yMm8uoux+sxU-n-8rB?VA| zEIZ?X?{4i7t1l}$UNOh{FN`XFqxDWdD2M``J!Mp?uI*xw8Y2#um+rUpRhzX*$hX?OR91W?ymaYo!fnmRWQwS9V7ZdPR4sXz!5prQ8U6%uo_R zf3V7MEH@{|PwR2xOTO$^T?^HbGaBs)|^bXn9RViH%gc3 z^d$_H8#;6nlYYBoHJ`zW=$eCPqDz?*D_EJBcPjLPN4&f`+}Z~hHJape+rD@Q5w9MO zwUEr0BnQ8eV0~F< zeY;!G>=6_6iCj;1BR+b9x1-F2v!wNF9fG6Zub9ZlSL53s&;GnlKqnAoc(_sr(-rLL zbPZc*5YtsDU{eQZM1qo%h&44efLH-J4*{s??e_W9=5Ti3744aC{UcQobyC-w2a~G% z@KDg{Re9K#%ACcl7Yh=?6^r#->-}Py!k+%=Sq4h@$lT3YJB&B-3gneG-Za!OufW67 zt4cg`dfi_s=$7nfAlYT2Fh9;5^CFKoawF{S_hQKS<|f+q@Se>{J5@$)V)M1wb>!c2 zZPuh8`dMF19*~M%ZeK_TMAOeu{$|5rugf35txHqL33ZZ3Ec$HwIIlms(U?|*1%fMf zb;_SptLPya#X!RqzF@k&z1`kE7I>pDeC-Pb6a`&C+%W=}jZ(l_)z8n*sYNr4@7W3B zH8Ki#&lwiFapJ1YGF|jF7JP`AbaMfjhn(9bnnB4Hi4W}je4HJ<$;l)ewD53>=x_Fs zW&sT1aL3+47$rw;c=3eI@o1;X8);^Cj8aJO5$(PXO-8Ikm$ep2I-o8xR#!wuAFSWf z7#f1Xd`Op0h*JJT4#j`FBPH`qjF`CiSP+F3V`;=B2%t9nTluYbbc}V8b#h;vB7l}qj*g+i^tPmZm*d4z%$~Y#{SLrp8DOaJ5mw+#e zN$XCnrP;vsFrk+q99bGf*Lp^jRFF|fVXX_tjAP>-o<4xnW~rHrJ#;Ftye`)@#@k@#7Js?7~e03JE^@gBG1Mmd({k{I?m z#!QVct$OI7PGEBL{^uMnCfZ*?Cgey>Z_4P~_5Ap@Uc%JHCkyDfUs$XKW*j_fH_=m* zY(6y>PVL!6q;3$dS_sYA*D5hPsQxR!v2UHQcXGBTqIR77{2fgMKrN&LQb8l#I{W8O zZvMgnIzMXP{RM{lndRkwfC3EAg8Bg)*x14XY3$7k=xUMtzT$deX|KQn2eRx> z`?Y(V1B&P`w8c6Lv*MFzW;EP1Nt7yq!Yk~Y(RYEjO%VZ_-!Qm|6oauNPoGD6Mq0t>L8K1AjBW4BhB)=i6nw^P!7rUU= zLqSjOCzD#CT4$ZwhXjQ1e&Gm`ARJZa%|rLwS5zieD^f;>epcGB&$zHgMvYR0=^Hmi z%iOyHmq zVwa81L&T3ol7)+T5oOk`7HttuX<~OSCPr*ZooM{;R;)Jh%MhBewZTrP1wD+3qJAhg&dY1wmmFJJ~hfE(r z?zOEy-WAl%C+yJZozEhlyJ)9EFuRj~Ix}IswX--G{(u!>=GA8tHjV-$OnP?QrXEr50JpcD#!Fso z^$LD$=@kZ!=4ol@H*K$N9WOFn<0vIOE`VyXxx+)B_w; zkW?S;mWW>yj}>Cx{2(4lLS`qb+%H{i&y_~_9j!r(bvmE~ck#8jek9aaeQ$w(dj5kC z6yo_u;oe;qq!T(l_=X+2icUHAuI%pC5|V{m!Ixw*meyZN8oYbBUVazu=O^|arhUAK zd$H&!J6LzlF9n?gNpmK}sNqMr1b2^A-+3|!Y#bpJTb`7;#!30K%w;HS@X8j9LZSgV z-#~BfqT(ub;pUKyVSOAJwJQq(dpZJzlHU8QAKDC*;$JQ$JM|;8T3LorasJxlh9Qh# z`(c*760Ky2He{u&7u!1hunTn-Osr_N`(BUXu!M^*JG}v30dY342!1v)Yximz8u1aI zFYt-xCrhLtvJcWSsp5Z6h(rwSvJzdiDxo|{{{pQTBm0E!O%simb1(>je}`z?%2#9SkfmBkbcZ* z>mQN+LkY0gFtoHsAM>m%SsRN&Ndlhsz8(Q=)VNHX5psQGwu1hfUUgQE_A-OLAAS@V zoy$%vwi0E2pXryX&gd6L6W|x-{x~wcJ}s8uzBY!n^|XR(t#_4lCBSAXYzyZ38|q>4m=D>sCjJG#S_oI8JbHO*EVfo8Z9 z6ougO*jsACxpq>LH;KLZ@IFv1gBO)w6y?5PaXTw};hQPnjt{4JMPh}+yeIjP&VIB# zxft4}?6JCwK3yDM!qEBVq-c5KUGB1&aTS+tKCLd6$YsJsVMEf0 zhzPHN?6bC6CQ1uQV(L=AQ@n~m*IW-|uO>&2_W4;(W;|65kKA3dDE+#Vy2YwOlgG`= zlqb(j-*`xJ6->>&!k}skv&*%Xnca5{9PsKbsPArEUXXoqu}(`>mSiLk5!112j*)2c zYgh;ju~8lfs?!b@ zz#uudAhYUQhbb7FuZ+&NVr@$&-S6-VLh}kyym`oBz5H%dHy^sb@+Xb7ll%hZvFf&?k zSJ177!K|?x#bfU#v)Dh{ID2-tX$DR}QK%tCXW=(EP z*m?>EI?@bavIXaP^wQ^Q1bk<;wRxhWqg4woG-hscQ-9oZRcE*47JCrmJuCX8byR#Z zbIF1h*zMa2dHh}ic}e{dWhoumUcavG?WvPYmgcwZE`^-Y(@so*iS#$2q;UI~5&0VX z)vyH}#rTMr_Tgd}G#{Q&P&3YSm@GyRNGImv*mAR0$sqDa$mm}`@aNhUQX9fl7Y~!* zo+HgFdqB63W%X7;b}o7t+O zF5UUUfJ@(35?h>jQJGjV=p=9|GK=4D`fdKz9R>ssWDCAw)|j(qZMt=lrY(!X?VX*4 zW0&ByNO|Uq-AZY1>}DW&$Ngx$#K z&gQ3GqPv!AdI&bAEF_$R?xwAqlx|tAO}Kj9)CY~7CnPRzA`8WR@{B^p`1GrA}= zD>Tk2ZgB4(!>zIWV{MVs6`$Bstj$`3JT#yI3>nOIdt2XOW z3sVIZmE-Vj{ON|s`NLxrlvD8;-~200Zq1mD3o`E2ul2Mmh;L$NYtFClN1Hst?C?0_ zUpoXUfZ$$%AB7{s*<0-3a&J7X_#`C)H@6rDa8pwH3-sjJKQpCP_2yW+Xi{0{o)nqC zCJ}^bVs7#qcA^F_&1FTrWHK*hRNBbEW_+_e<7P=VNAdb!baB`XGJz*%ViZbc z+TO*CKQaT>-2_*#P;pYXiDGaw+_9dFq_z4N+)@^lcf-nD7(XbfO8MvPX~cJ>r70iz z%1eqXw8pYfxFCzQ56ysyZgiJ7tukGo3BaN#NR*d+{*Z_%W5C&d88TO|3_Tw>zLc_P z6HnnnIoigeoEHkUXfEuHJ;40L18t(pE%S@KI_8^eulny7Z(HFAG+afS%1HKyeC`uX zW}KybJ?k7=!3g`4gez2wo=$W0vA2KcdZ-8NS<;O^)r8U|UzKn>-!aV7iq{qN`hAeB zcZb#u7M(mn040DarIWq1_rs&=LWs& z#S-}88kd)QC&)ioKx0qi=am_y@!zd|juc+$Z{fMG+wSI+qS?BgKD^0L1CO%vi;j$b z*qG$bLll$p7rGdXq==*O8MmMr5?kfz$H?w@7#yy{#mp1*MLk#}WPuL9B5-ov9bZ)o zYR2kv3(CZL2{ZCZ{E|}WlvTffYT)imC$`MJ@0u_Am~X(;$94khkop#A-Ua2(QE@|d zN@BM_cCDhmu_yvF{=>dhiLQuv^#AH29T+$xPN{GL%deXO#W1dHRIMqd}Ra71@t9wgcwlwhT~0itSW_8u)(G1IBYxAmh6E_Sl2_z}1)XODmC zP^rsTbVgM8X@k_%brl{WKkMse6e7Kmn5$i!UX~&|TsM$1rMi+||I;c)0}H5d0H&4~ z^3C*R+lKHeec@))q9Q!b3XC0InsEJi0ZpCdIvx@`s;OTzQXO;(@0P%l_Yj&ogC}kj zBYLLA+!6ZOjyin1kI2(Ujk$WRm-op*p~Py`ch)mxc9MBHGtxr#a;~2RMNsEj+A5+o z6eM5Y_`(r;Ls*dlW~IhGc}p#hD{ouufN>yhwGHPwXh& zWi}@ivJ%YD@tIO3W>LB9k_pDW{q(`|r-j4kbAva(Ro3&51R0MoceZn_22eTF?QV@s z7Mq*vs{9WWwen;+GuX4Th>84Mg=G|wzEE*Aw-khwegCA~(nNNEYkI6Sg;{PRFU+yK zYuQtxT+jBx40S?v7v1gkPIAh~*0my?iE02pX2CGqzb@@`o8IC4#6J@C>5ce*l|%+s zW!X24N^zxKg_|ywEb^~HN%Y)XcKHR44{(BRw+CO%1!H^%3LFeV#kD28W4xKUE^Qs%J_@GGN2N}7KzP$*J~&}fDZC*&R?^J@Ga3pO#j5VllV zSC~B8qJR6hBa2r!mRS>*CHVOI{p4#p4~=^csF4!QVluxdq@l3>@nEE{Xn(H`-OkJ@ z!&~Y&-p(PzX`u2`_{Vd)O~qhybm268T5*$E81_$8$M?~vKEF{hLeWd z*PKj(G#1cD@*Rd5(&62qOQrYhKGUF}T{Khd?6Nkf3an>GP%H}EdYW!!g3tEm83haN zfLbicXj;l|-g7c}(u6KqliPFO(ELi!KMA2)Vv8#w8(Q)%J$y7gwvb9l^_c+(8w*CX zfE^yyrzI!XZ^mV5O*%qbMmLaosV^>$8~dY$PTM81rSCIfGJl;~z^?F={yIfz7V-=3 zfOoK5EgoYc2{2zs>wcpNqo}JfIl~agah7s=iNDH;h_TU-64P}`}(5nQeXJzDJ zv2=qCr51FMZ)(HfEdN=y@Au)^d}3kno8sTFsJ^`x_d0s`* zRh&%Ho72reN}PI`YiO(PK~-4ln5g%M1g@yZ7wsU$4%MxgjH7v5Xpc2-NjhOF)ODDp zdaocv+HA}4jg}9I^-cX0bbYHE?ZT>oon2VV-3MG&+q`@Gj7t6tk!d?TW8Y`Q0FDe$ zDpK?+e@OVp&V*!p)AI!(#e$c@c*`fUS7&0goPv=9>HD<(9S_X7a#h_x*Flg0>r72W zVRHhfBUDl4OI>bT@ExzG)smU?*Ue3ytKt%)+|F$gMg7TRO!4HCd@A?|2{ONZjsXli zWps>BgIo@7E^%E=210Lpq|~0vpz9y{KXg;_KF2XeD2Uz7|AVTFD}`y_Mm!tcq%F40>dDJI?8W^qla&YS_^aT(g#~FpsrTwGBq)#9~4cKwT$N`+&k*RT&lM{)n#8J>&fFO z9VL4>ZFr=>Q9w=x5nXOGo}H>-Y7=VRVTRfD_TfO|Ge1#pAfa7=@num;8G>Ewi8kz?T6k=!ocL$t!o&bPRq zk=_WZBX}-qXu>FVcQtggh}gFFNJ)W1J6pDk(KMJN{p&~jSxeG{YRV%DP>&A1;%FoI zin$Vhr?$?O?PIvSTZq!MHVf)nb?);8r8v#x^WGGXuM#gR%Z?$WeYifj!(tWG6-W!& zBm4)VNM(QgXa}wIiDL$UaxUA?X(T%=8smZ>OI(m?2#MYUHWi7pv)?T7Br9hyW~$=6 zFicNbf1)zVKAL-7nw+IW#J>-lr=Pgw4ZOn`fxJ!S`uBZDwn!E}XoEvH|QEkR} zjES+3A5Zw3?~sIsj3b$sR!AMW7k9j^b*1kByr}h6{+)|^=8c{=+ky@?A)iNfc4E7f zpnc~MpNcO`FP1~oeTI%VUwG%cIjSxqxJW1kM-dAWrL4_^_Yix^QE_}B!5ko$Xmyie zD2{#?w6%6a*;dmF3xh!Lm8`7ne5*SbBnIcBx)rp7g2KCkp000|Gu=nSPLVY5Vwip^ z3Fjoigv{Aw;N5eS=avJHHZ7%nzI)ZYP-%Y8pl&LZD}DXnTjho^Y|Z7wPlh|wkJVC? ztAUE>K{OF2b-ur6I59C5^x=}k_U+s)Y;cDh^H|teU=`VIBvWIprgeLG-vA|XG{-xtwX$`A;wL>oY4t5_{| z%bI>tV3uuUXCFaITu@E$iu%&yr$Q2XaZh&RN4NQPvF5E@PLP;i9h zQ7&9sAe5!F=YM(3EG$<}M{6(7j^M6yRvMo8xNddcz*`1HSP z+V}qQ7p)|PFTSNvO0K(e#wj?Ei9FkOT}LIEgDB-TfVOjU7@m)pF-|{;qj^m_pdwy@ zjEgd?xSM_2qBVFoZ$4`$_T+IL_kt1Kx$#IB%EMz`H8)TG^5+FRuOxoBkWvHfJkG@f zi|QhGexj85H)?z>D7eKN{2;8ij}IT4?(b;u+;qkBErlges3<9QI=tUNB5u5rEE)ro zlanpNwVE7gp@5ZwpbTf53OO)K0B!)#^B}^4uv!`AtrCA>%TR{A+Q%0ElUW=Uj06B! z`4>^xHA@F|2{^{26$cF`$W>*QR;i89aJzh_lpEU&-f@oC56ug6{z#JY?jm$`T;anZ z*0Jf^^x9U$y1DRDpF)%Vpykwb6pO0v)J4Tt2N^1(l(V7ngz^dsLO*|!0!sN7@ax_M zqj!3K3k<%a0L3I8*hJMV=?Um96mtGs(D5EuswAcCU}m5^}0P6gM(!bAOw zSeO*el11pvXBF>hc7!OVji%qQ|1i|tHqk_%y)8cEB-UI(y7Pv7j{eB#tq%%=wf`3VFu z009jya4h`<^z>_|=fHSzgi|uq=N7e&3^lDO2)palsf;wM z+R{BN%Jv64UL;{t-;vm(X_1DJN+DQ%-`^Fs6!ja(iYkZsjmq_bEhh9IY`E5T(}nQ! zlO)_&$)e;pHM^PHb%9~Hs}Vr-dJWn}CoMOc!21Zf-Mntazi0C1eMQIpH=JU=)eH-t zdfer?^`!&M=cc+}$iXnv}Xj+*%K(=z2EefKv?4I^H`Fo)QTGS;P8M8JiYjdl~Xe$fF=Rav0kzqJ~se}aB~vCQF%aZ&gj}aE zxn-U<#X!lZDAY^yo!Mc2hJ}(cEF?sbu3vPETY>3S1kL$*E&S|hiHO|Q8ONj?E)WJt zhb6T84#P-sUdXr+l=LXRV26)6hX@Fw$Ns0YxdXM~hQV2wT<-h3K(6$uk5RsZ)-W-($g1HcQ(Q!n_NFUS-^GQJYoGQ{1r08F~YgRU(;yO4m0Zlbd;AHf+{ezNvho$Gk(rXu;Z+=7~L4be; zu3qyus2~kg;FT6)N&5qsE>#Mm8vja_OikgDEJ;+~zmhplNJ$A0ir{cOpcqWz=|=-ZXOjSAF zJ)}iWRu=+^%e<{CawEgmD!8dho!fmao<6)@#cFE*cb`ahXdX?Cl8*%D$ z(!_rVgy?(vaw5@-hs_oBFXWCwBu_l_y7BN1dO`5Po*<6McJ3E4j<7klm2nRa5Oc#*F?A`<_^t(^sE=Ks0t22eSms84#%TxxiY{wXDCzfDtA(F&i1t-5I^(1& zlEVX1`rwqiZ*9P>L4r5k_@pcW&lk@bR7L*t&;FjqNaG(`g%Oz<#0?twUEJ7_;${6- zDsxzR8$=^ctr%uP6|}qWGxkvGY(H79MA+vO|47QVcU|=eSI8;&Y4JW7Pj8ZRtAtcr zM}=g<)V=My)z)mNYAllu{W9EbhGJr3vH{A)+=>bymWFx0u4}ViG|v0)(nR(998;iG z=fYdE1umI0EO#?FP~-%|2g-!Q9sL~KXj$;O4j*=izjJzW+#{wYy1+y6tvzsvLF>^S zUY7i9Zu5}7ZJiP($5Hz}o?%Fc4Q;VKs-x(uZ0C1RV&F3l44;LCgx-LpH$bn3q=jZ! zL=wJFkU^rp6d~79$mAQjm(|Fq?CGjBk7=&V@g5642bQJD@V8C|>$sG}Gjk$S&&a#2)FX_+~JPPky8`@Bbj+d;T3$HGf*0ZYym z&FT!gG3+HJgbM-$`V~! zpPMmCd3eirLlhXWeOm$L`xP{C%k;KQg-(}0emEacQy>Y0xz^7y44=21m$~nf=j#Ld z15$U*jG`;y_D$ZP zJ6WHSm15m+e56(HyQUXmsHqG}Lg3qQWTJ!8?mAIbUDia~2>DxUwP@4~&7%H^B061L zK_9KS%aCogL;2sQA!m7FPFTO$N4sk6j#m(K>pyD5u*4!t*p?%!doE_QsC-;BWE&EU zCjmNTrQXv0s99)tnb}0#p3zbI#PmH#?e)ci9**bSm@7BLVUlYD*}f)0WkX)B>w`Q+ zw})F%l#baMuY+GKN$FRrp`eOX)E>~RFHAhF?LsLe1=y*~wen&9m zeLf$ZwNX4RFmyL2wlt&3Dr~sa)zGeKakrjiE#kYv5;Dto!-Fm+J$a}0ShvE-rEWO=-mwD5eWrAZvUKG^AS z3G(G91f4xtuZoTp(D)in{4>hXAf_zo{^B&h@>kbXlG@zkLmqj%q3a=~r9)L?Hgq1j z*A%+8z1ZuT4)}RK4reNQ1&?scPko!^xA_l0xhu16PyN|C38b`6@;9F6S~q6nTHDJ^ zZX1;^F*ww6`oD4gnyi4o{i>lG15i@J_wn~ge$r2gQa^*)s6_Xw%cK)|SwpL{1wE>+ z46EN3XNOz%c!mu>CTb)rT$?*7j~>cVmRfB1y_oB%I_S!m#&_w$zu;Q3SnEq&Xg|4h z5~6@%_5GqSRbYE(boS33mHMmrZ)Z}W*hUF$(OPT{8DlusXRB@N{PRs`r(Geae!giP zn&sz_r1@8^`GX5!s2J&JQwi`n{8bt#aoKoN((ss45e&9$u645Noo2Dn%(@8Wq-f-i zSpeS84;AtzCoPUcMPaqu@FBUl%xv}4-w97r%J#>fllDweb{cr{t(?d-GsEjWlHp2U zmDu>06hQ}XTDP={eK>XN1LoBdo?p@?hM5$c&pnI{tuCdD*D~x;W2bYS_S?O=oa{M- z!C8GddNTSpk(*d)_~9eVbtNNy8Elzy)o=K**j)bo!{q*~wTwU+w-ZmXu(Pv4-;8JD2=-;ix%u!MjVfECY z1+RP`L1SHxIBU^RVRGA+*~t%qqy{exW)vVPWi;S)+hxUbMLeaQE!}C_# z@-;ym^W+AT=5DeRbwtkg5m~~&`q4{jQb~N)x!TIIv_tE`M4suUkZKc!DdVdGxAH2? zGLrMtrBPiUQ%w5kPsU643RZ~^I8wB$P-qxRb!Tmo5BFE~oo6K8f1tbo_h9ZX{L9gt zodc`GsIMctA-_iJRO? z=ZP@eVUg;*%-ZZJt1+I7%Hd!#Af<=y;&xna^KB*NzRG6*8)wz0L?5xm=Do^9V6lF< z!qVb_Yx(u?ayi!O40KeX()T9_q@bYBdqc4)Yfth#iNBwds7T_bqK;MDy{o13Z@qSy z=WMPIF6q7@C!Y`x8d=^ym7EHt|JElpKtxR&(d4l9HH#klf^gHD%;NE&=FB=t{JJe6 zW$Ji$O^w>=r!B|Jb7`co;|t@nZwD#3XRMzp!j7Ujc+@6VJt3f7Pdtg&o%CTC57XAb zj$vyyB@BUI@<|!XB=RSwgt(z>Bk{pKT!8~9XS)n`&WFN#B4YbmTtDI@ZKlAlNk94~ z#BfEB29DJ#oSn?MHhOra&yXUn<7*d5|FpMuPg`0f(5*0812^i6m#_|?-<0z})*XW$ zCNh4Q4CTl){mtl#f#is^&U!%{V^(zZNVDO+jJN6{OpF_FJ$ORiU9Q$zCBgVLKwbZFbapZ*$Yhdr5j2$S6yv+&4Fe0hwVY^K5JpA;Ds4BsqE{q_r@%=;iX$ z7=b+pl$tlrnms932WF|GEjnjE z8_l*3H_A5C@MKnMv45pU)~j+mV2xg(D$!5IgsiwCu3<}+-H9CT9M@&yD8!?v6o#GD z8U4?R5f>AF5)U^nZgJbXa~y0auwb`nfxHtnGK(8{2RpFeif8gJti@iRo*Mt{+IX9I z|EKbF&aT>f+xfDpI{|c^H#Z!9?MishDG?7t*xc;N z&!^NysT($GMv-vI^&@YZop8yXV%+TTreAam=$kpNpefr~JKZ$D_%}1VX9(<=@Ipb? zM8`{sn2V3X(!F@&x4FnX*ukImPV%J>pdDUMUkoa_DmS!LO7G&+OcFkQEQ0(Oz&+u4romMefTrmFu&4GRltE*- z!!9PfoUf9`dI9du<9ekY7RxRptGosbqSe;iVZ!ywqSfg^(#BJsIYL)Btbl-WpWV`P z_8NQzaTk6{<4T;oh1WTy15FSH9aof*0%uAU{Uo|sva3Ari|8}QkQNuRLwilxGpa}x zI#koo_$`&d^?F`FHGt*%Jc26K#v+C`HF@-HiBLxrh~f>^BSSHY0-FV?t19nfW#Y6M ztZg*m<)&~Yq#dm$=P@KMez|WsJy9u0T4?e<7)JjLBhAVARkV7G&Kf1*k{K$=qdx@K zHTC80fbji0zzmeCAe-7z5-X=jnKbtM7AzKfU+tey4Tp*TJLl$+Vd_8*ke|!@(Hh`p z@jn`n?Sm+MMj7d<|Xm@HGJAxD_>x zQ6RcrdqN!5%hxAk0O#+Nd#G8d`S#%f=IpgDa+awSB_S6_*hNK@iu1ZX)Z^Y2UzDPp zf9YZI>dZr%?94_*a_MNM< zsx}_q?6+rc5`~QCNr}3h)Vp}l8RZrF+91ob5LNrygG`)Zga%R^SpQ)*LDl*iOcn?BqnM= z%>D}tb;JOwS}<~L$2=U1zsM$-X)roQ3nTEGjTE|zIAkh2m3m}J>9X#8k(NGBZ@P800totz5jw_TQgjLfah1#fe0YU8` zx6P0B6|zu=?5)=W--Q?;UjoTJp_*%XH8n9Hg);$s04ztj0!q+f_))G6yRZL0oPPHK zn6rG7mzRGp5DdQ8t*x#V+MhbUSYz67P*`MSdbmWj7elR7X|_hWhd2@1Y)p7>tNth~U$Kl|JS$d=x-S1Wym}0GT*~86g$;WwmlkKlw_8^c+5Dp6!7F^psOY}; zdJC050gUABe7R#iKpOXcuVHEuX;mupwN7>on_}Rc&K}~mDWPoj1DSyjMAr+#cE5lN z07;fc?Z4L#4%M*W)aJiOp6BBH|Nej;U6TD$S55;1^cjDDsJbX)J5kuHr3uIBCEAvi!B#}iTfiY)kQ(%8F7?XBmLWF>a z!W`Yd?10tt-x%E*N{t}a1f(<7t&ft(?acV=Yx>d>o7p@HFC8y$>f__1&orYBdsQOI zGO8bY@nC?8FgYx-BDfZyZEfmXLV$;dst3M=@obi>9Y&E~Ug1XUXq($3Xe#v4d>B;{Ts16VaX~t|6>QD z_(HQ_p%Ob}jRznJ0AKmNxhHTSiFzrPPy-Qce?Cl6lNuUJ6D9>CGbeQ?Y6apl$6Z6??PAqRN+!i#1z-4!Xe~e0Y7A4AP%;CNhN}0BgNE9WYfmyK{r!8IVpNaGJTg zONOivgzrg=|IoSHy*%AO@|z&B2Ym#d!)lf-J)j*p2p}2%0e#(pNK!Z8zTCpAMTqjZ z@vyWDypG`gtaQ0Dd44+etO5}o9v4w*f3I8`fM2tbnc0yXm(c&L8(@>3`}qIV`8L9P z0qE=BeKN%J6sYe*@Ocu!l!i?jdFut-lL0IVi5q2RW4qi4roS#I`R|guj` z3Z{(0m6Vjo%&F1DN?kI2t)H8mF(*}J;mCv6v?3)Zhpt&xw{+>}ts>2n)PD)&S*sQVb@aRM z|C{$ZFnbnzCDg!r67=`h?Kqow$e1moVq<5EF8zS2@N8K+`zzts@87?djbVRAgKQDH z!;oGX1vT~Ib^OJJ4b;Wu<&A4=adENL-~E$hU|En~xcGlY5=9Rzq0rT39}n^y8#$Xr zuRsjc(ais9?d-#$PS-d-B1vpqrN$;q)0K*~qzhB>GPAZ9CsfDOZcP|TwUI(zLnSGa zj-upkwNWHtb}-aLO|;%>b>($dau`g~pyd60pXv0^o_~+)a_Ns|<~Psp`905lKllCp zd>NN5->Oh>u+?sSY#}EjF_Fb)vkThSl5LF{#~7(IQ}Cb-{9U9Jn!KgZw~I*u!)wVk z9nE1JbIy5i=w+7m?=EP@)QF-cf=ADgq@G1_0vzQoQJ&k?(crFgODUyrb>1j0;qk6! zWv##oY1Vxk%rNbZCyfCA>V{FPdQR+Qn6+-$2Rp)G2Tu0$bEoh>bNJgrR_8ckZHUnZ zZD-%fR!`XYWUW?BG;qo;D`QwK^~dJq2V8T2pmR-5Dn$E?|E`#q1m38P5v&o9$8#%b z*M@Cc7nj?(<2-_b}ME{JoHS!h4bTvTA&HFiI1yG+n8)KJKo4q z&YWhvjiD1zG&#Jq<#Ja*jRuP(qC+P=0TPN*)|aiHR_M4|S^ZhkBW5QG=(1+v%r(NL zGP?qa7o-2T#8N0kCwWOss^w|hNWJO4%}2$8YuE;(Ncn>${*9G_Zk}g7CyqmT^Z+Xg zE;e!1_Nsn=vRJSS_SdUhbUcQz=e*#C=@9ncUQ{b{%F49uci_1)O35w^9NLew@#X0{ z>FYfIaJKlEF!HXru?W)fUwxuAR`y15>uitp8;)}P{LCymd==~K>vbZgWcT)!{fkhX ziI);lvl1hwwzi+cWwEZKd)W5WAYvE}O2+bmgDRRoXk4V7ExcXuA`nhCx3J0rk%{WG z&6OKBv>$n6!=CE-K7zJp%>}?BW`KYD#@%7zch(t~JEwXr$jltJsCu&qy;W-RVM5h@ zNhFDaV9D!Pk^^AD?z_iYi+VEogU+7-uDbzwmhr>UoiI(07BH9zq}wU8WK?T{6lx`) zvyl2{->2)&J9D$u-#s#8Hp8y1#&vdLHy#VJo|0E7UAeBo3Ms#R3{-~|ncl6WiS_*h<%@e9+vVBLOd=@?fz#HbRvwgT*Z65C>OxUn@jn*nNo6 zN+A6S5rAvO z>Di>C41V~|O}alabt>kw$%pnKRYebgIjmrx9JwPyif2pr?Gh3H^=meYGABWF!A12q z`D9d8(s37S$X!&6v(wU_c^)Xu6&mw>L&NM+u8{BObxApH|~ z^7sJKs>r`x;Omx~n_D_DkhjLjNa>B2&7`()=3{~V!ajXs07^l34C#sy>jq8^miXb< z3W!#FDb{ zFn~=H;m87s-a@W4Y75u!Jay;3eRXH%E`Y@+sHT@?-PN1LGbnrvW4d2FcIs@MWaRiu z`=v5*V5htJ&EVnZ28`*^rt^ZIm{BjDd1qbx^kR`8)AZlA{826C22e8^@!9hpBf>MB z1Hq52TD9mplyb3{e5wl;{8Z}ep1gNL7otE`#~&>{BjZ8v0iY0S{9b;XXKhkI=oCub zEd|Ss=hE0{%Jg9FotP2Mj?I!G!H57VMFeXj1pZtF7hqkXc^ z6%`d{UmDp_`A<`^0G}~A@b#}ed-&ftNxqM(u!tms8Am1RxFLiRR76y7ulMIvOGb7;Rf)bF`7c^6p1|lKw*H`W_pZ@>7ckW2j}DqU!J}bO55_2gUlpPh`c|C zr_qZxUr9^bWcyug@5hjFJOdQV;Trnnsr0ii*>+S_@{;J>-1X+>MO=|8H2p``Z|_E= zOEWOYX_O2jteqOJr6A)thX~@dkFl1P7TLZ3$!4#pU5BiZBW&<9A=hYspc*5Os_X0S zLBbET5c}^cXv~prK$JzcF^ul2j&fo-G9i8z`~9QRrU1|>qNA0O*eM{uo_ZfB^k_(B zu-b50@tB>_`SH@I_1kad=U;*;EP9%dD6Q}*xru!1R;_)iIA2c{Bi|7$Nh6u#v`;te zE(8w;OS|JeW~RndBWA|or!^Mz<$Hd4!}qV}kB3#LT9t%}hA3yNgTuy5bNJDl<#MFW1(Gr0>?Uk=IRZfn+T_B83VrgMN!N^u z(yZndez>JK9fN%lW(!p$`9)sQez@w9jr4?1h3v;8zx=Y1lYuvf&Q>zbm$rCZ_9Sk9 zVKNb-mJ`STMhYUPW9KhgH5$}8!*kK#p2peAkN2D}FIYjQ0>WBmE+3JEX4P|9xTKIkPg=RPD?+d4+te+{wx|gsWMd)y6mow_EiLR$ zPQJ*r7uJ-`r6t9rCzx>2CE^vS8JA5gyz~3t!ThZ2&aL=4Z-5SXZ+gK_;~Sz@p~v5s zl0d*}@?9|nKrgpF#&52!ynqxyuedcX`*6ppF)@fMzxpKUs~K`F9jSc8ZIyQxdz)q#S!dApr095kZUF{G+1`4kwxbp*3?5!gN;Tj_T!15$=%^|4M^tp`G8@H70Sy#6=YL{sHdkVV@ zF;Q~pc+K|+RJ9=I!V2h>i|UYWDW>KS@p!}|q{qCv?P_m)*neex*v*dZ3gj5yye zAJFmG9V3u7=!~FzrmWm4Pwl2kXLw*Kz+DuLIW;GL1t!RfTEi1YQ| z*1(}US6hZhkNys3KDGJr&68EHo(znt=BQt!L6^A9KNwADxfNHUtviOP)NxJey{T#4 z@l2h|j}H1@%la+pC0}kSZohfRa5)udv`T2=(rkI zo&S`d^MEFB#^-8h{m(Z{_S$8Fu!np--`1!E?Py-TdWA{MlSEx?U$cP#n8>>V;ovTc}ytY=CslI!5z7)B1&`Djbol{zhU)*^4B+YYI2zN9j z$tV;pnpmrFY+8+mjs@I7)v_;Dgw%4p=){F@itj)BPc+zgwJY*Fk*9Nd)a)$5E$a0X z78d)(w)@p7+US2>%gumop*&1g3e3u)v(?B}i=Y(wG&QAFZoM^D*!uN(%;3bt`Zuj; ze8NcRXeC~MalrSM=W|R9J~ee@f2xSl_4&d1dUhmDKnZh`>zE#RtGo;o>z7rA<5*}1H-Sn-zMkc%nowljNmXeZE z`Thp{)U2g>DqQ(oZZJ7*{AsUH{`M-dNKE7WVlAD^`_k!pg~Jy{Q@qv$ehCT>mz9yZ z2TWyu)^%RUd(P+PGI8|nw^y{Hq7>u;Hf_GQN7QD#4~I`nN;ti4PR7}<5`(;A^@=-x zeZ-7TNeLSqRB_rG!v>bnK9nur*TcupPshT7c{b}x4Hm`1Ij)<>w11(ndhQpohK}FK z);KcsZ?^6$vFMnXPv54zuS!Cbw9z7QE8q$!SF}J?Z_`~wBUP; zCvDLB2^-;X2e(&y$dI1*iQ4h{5OS)BYlpzR7cwO1x=Rtq`u0OKy*wQ)ZHtw{=2)Tj zzr}I7rS>_8HF%!M?aejV_p()IeEoWFXlRI}G+REB%H)hqyUGgSPJsCxunUSCVwKk) zkfdd0Ki2I2+>&u}syJUwwhd@8z>`KVwVvi5D%O{PNrpY(k^2%Chd~?QwwCJJrlz6$ z2ttPztEO!T^}SDG2Q4adtPKqf-vN;M_vZck_j7i7<2kCe0)PFIj!sBm2Foqu?p}*0 z9WF>F;>Q+ocKOJr@UxQQL?x#Cqi zaFtT83kQ4x0=mVerH^viTsw7O$5}U>c4vg_H@?MV$f~x1g`p3?%PK8Z{hcE88p6A| zIwJ+RqV7wzEgNo)DupN z-swS@YRzIAh%e=p+%Wlqwt?5OB{PASPHEV`JmRNZ;#hh$crN z@!hHSfY@2e#u`L(yLWf1EPAzFF0D#5Ty>w2F-R?6J(%3KUNs;vFu7`NZB5(D_r;5l z(JL(4fV}VD@t+3b@KN54Y1_WN+0%Ocnx2lHzFkpZmf;~edFpw16apatSeX5^lepf0 z8hVqfluDrc(~0X5wMT>A8+G-No}L%@IJ%W>c`uYuN9Jb zyPYCtW@bnTahGK4fc=#3;EJDTY)k+%$nRu)^k@W8ou_6COZQd8x;_c@yh~$#7`Lc^QUmU9vUAX z-{St?Rz#pff(Hc$H=yA-suTc)SVuZ`lyX?(b+o#2C9#2^oC-xL* zmj0@^$w{^$aGkN2Pxi&3(>JX*+?%S*ui3~+ZUch~z>`i9a+DLjT+hzg$_9_j`uera zNypGIb9QShl%tVz=dP9dmWImb+)!0roiPCK-P!JJj-@AnDU!~Icj^MZ&uVPv#fOE? zcBYvEqI|RS^Yh!Qtfv*OIwB}p(tIw>RW&r2^n5Oi@d*j(Zx14U6Z&JKqlY%zo}$zG zoc~1|J{S-^3LE7{K|w)+pKs)*7wqQ7aUGyTEE+{bkc^jC{ovM#dN1qSvbN0_bfYpn zDk>ZM;kgko_H9Ng?P?poo#LXRs@gq&T=5c*TM*HwvC(JiTuGre5YlCJbyFuB2gI*_ zJKa`VjwkKZEk%gjgFrwuv{y2E*_$0HZgC=#=%(UnP%l*)=Z5|_ZOfo5iZ%xgY3!Z4 zhsVzi&t!2F=L#iM{}!j1=%^@~A3uJyZI0&4f`NS>jc1N}P`oAXeHrxW6Kd#9^{h+s zhVTnTMLug=E2|1mZ%R?O!3y7wum>bp)Sla1Fv+|(PeMImORbIMHZ?6)o=>0pZ=~dF z6ocUd@8myOEisuaGq!#q8X)Maj|Xhe!qSrMwCVb=H%q_Chd(km&OS^YI$x8xyAP4^ zn&ANpDu}BE(24&L&`r&<_rd0MSzX_B5L5xc#pJ4M-stI_#>L-2YK6TMkA}%c%c5G; z=;&w&zSJ36y?NasbnSVz8@{k$Q10!0dCb*d+o)x(rS*_eInAoF_{Tw$nzM7|>>eZC zIJe$_nCEH5!*ax)27LSolg!U)eDnQ{W}}zTuhv%8H*W$0seQ;I#V?uXeDAzve=`7+2zY@ZB9Ea?Lo8>ssHYorVPm zrVnqOOjKEuLm6N?{JqZWgD?EhwZA{PBhT zqa|z%gT&+GjbRY1_x;TA5?TzJrz$PE+z;PxPnLI9ga>)aySWLmq?8st0!zpVq7>jfV+B&rp9jC(lp{h< zy2WPY;5eH&OB1w5;xYN%oPKw0>a;o1UC`b>Jz~L^=5_cSa_Hy_Cl^RMy#XuG!8fks z-_|B$tHwdY35KYcZc_0@0fF{&0((Ux>V%96lG4&h&}7P!B!yY+*RTD-me2_aJ!lQY zb=^1BZ<#4Dk=(2 z?R$-{EPlZNLZ6DZb|_Pt8xrsw1fSOZgEssi-RJVVc|#~toE%iR)pu)a z(mwDQ+!!Y14q)y$l0^dh-Aw5<1raj0zbA-)0AfOQF@4@fsJu|Smexw?I^&m{?lZOP zhHZ<1jonTkDT)N0gY3k9xeI@LsuD90hw>L&^~~bR)P)2im5)-Py3ukM@ZZJ7cN73! zOeQ~kK!Tdrhq7lKT5!oYp=1GDx$z?1=;Y*3!1n$E_mfdjz;fB0F&}gOMYy@Og&>J! zSf~g_ihlq8!TK5D1)-s_pQ`1w=n4oi5M1JBL%C4+wohOl5g?+{(jwfCRug~vE2WF4 z>J|mjXq=;J`GyM_0l&@ph>{$!v5zX>;Vcd!2p~tCWLTONX87ubS|1OVI+L}e^G*`n z?!iGWHgY^SwXF#E@~H8?a)CGtU+rSa+eo_XOnsE6a=(Yj?ZA%X5Rs4|B8(g0Ia*eR z_MO=MfN&_}$7_k)1rsts3AkZQ7PeutI7dfEY^QwIvex1%BdJcplnxFK8O#{Br`1hD z-q&*to(I=Q155gMm!#6t(s&OahOG3)C;!xWkZwXysZm*3iNFdXS+2h2do_E8fPRu& z`N$97H=jB@tNHem+%r&+yQ307Q3AIy24rw?xN^SViYt^H8_Ed+lkeqlx*Io+GL z^`I2@n%G@%T@orxB^R7m{GIgU$CKf!jt;rutDJI6MBF}}|CW`76e)H}1{NM$a!%&~ z7V7IzJgEGwQ<$!J5K^@Li{E|80!#CEw*t@wn%B-$rQ7-6Kt-c!pW6%5_yNfE`rN+U za%}x%Twh*R7R975$(Uc4fAFyK`|ySx$W<3WzSstQ*l0@JXshXaM9nVwi6{S74u^(%*@YbT&Ar}^1ouxk}_c2zmE^eJbM;2QRiAb zd0TEekfhFCRkc45Ld>Etk1&(us;v_bF1rQE@;&8e&+q`bU#uM0BLt~>g}Ht_yKWo! zm*u7H*zsD!@t>EnfZ7{1q0>nm9Suk%7jaxSezw=tOjw_(El04IHtO4bwBbg};)b!! z7mNMe?8_i+ZmY3hYAe#M3&1-}0u1x}pc(JtkUVvzCTqbr%krF@jtb5x;4N&8X8;Pg zDalDl7{vk4<-cQAd+?3o6`*=7f|Bm=byUX6Li_u zgh_&cJ!$g50SA$4gIxOi`!OFv*|As`3fvKV2G{_=$ZjO$|-GfAgX0;d!@Z5!}?nMf+J zfEVA&n0Y`Tr47&tt}s7@&ufVB6{*~gyjBkG>UuWZ7!`$Qe|K{hO30*yP8%TTah#VR zXrC1n5kW#J;z9)8B?63*SQ;JB6$Vu7hYZ3_>omJHOE~tczaK=$#y$c}hHaCOf`XM% zF=;tX|6z1|AxK&41mUg&lD7he6N?N+d(v8jWFMsVr6FL6nh4v$;!%V1Db_GC$Lv3u!*5dcZcy! zHQQ@+hmYpH&r)lEO4Sb704vC_pCB?u#5h6ZW5=NqHB&zYoE#5CHInf_kh&qV$d7o^ zzZ1BgBIq8g`@b*yA*0FI+m|AuUEgh5Cm1xTo?FW?C0KeQMCJifb3!qXW4z%UMV|IV zutCAVHba0o5(@S^6r>ozAhhP=axN_`^{LA?Z57r1F7jT=2OqoxP?_U^>MtdFHsgrc zX~c?{rnz@)ZZ0db>HZv{3(l%iz5lm;$e)Pw#ful5hQIDz17xrM`AoyxTTCfUG#I3l zB#5Ybcyxr&@;FAm1l3!Eh}PBDC;Q?B2Eg%pT}nE-d_9kiNA$r^c}z(+x*DcCf_DZOKF*9afzE_Ld0cfbDjg! zYWJBHMDzN}%FAI8fSy($16oyYgGd$t7~W4W*i*X0Fl00ww>k_N8FmdFoiMO!GIDZR zMMXG~qKD{3b-O?L#jI#wB5v~e^JfSG8j|=2fB%CCqexmIp~;FSaAh*T^)KM4p~Jb# zMt~2^{dj_38O`zuSR>E7k zs76dSHa5;do(4f~APOO{%n2}Hz*K<(^ie&(9T4R}z|;!#o93*aVfF)>C%76hcEfdX@G$UsKRkGGJM z*?B7^1+!_oaRGq90bHaF$Sroj>fP(KVBLEJxc)8hd7mq6ke}tm3I%sL2H@ot6vzNV zkg4ujJoKd$-c?728PwG^PLQxW$@85row|qKs`{vCXpxMniv3Xz`!J=KcNbsVgvk#iVgN=AB-oIx+#)>9& zuX~9MKD0GprJ>7?TZEZb{*$Na{(ouML0volyBK~{7uy@$m4b(ajg1ZX5)O5?dVc1R zS$*Ro=SA_@wXb|*U@3emq?Cr!?Fk7`fDd1Xhlc}27z+rYLxY10#|IC?QNa=+XJ+ooWCHL9Ks@Wm z4-BBRU1Vwm2+(BcU%9?;$c1I8yN9$ke~ z0}2KJ8mKDL=zp^wzM^qhxpQ6iB*W}d4MXwkn=OS0qeZ8io0&;IeTob~Sl6KuFs5Ol zU@QBR|GE$#TsV;Wp9{JADHeY;#&;aq$q|%wj{axvH1eDz_rzU0kbsWt)1&5pE=U%Y z(sHMdMCx0;jCFfQP&0E;XZ(LFL`aNJOavMC#u?t--pmzY;72R|t44@!1F;_AgzOE+ zudp6)-$SVUK$ZOS!_oV4Blnq-QU@}wC>*f5DHLV$>h&@*Eg z6@Rt(qs^);jV<-80K=p@?&WBrdGrVcgr&CAooQeKh*T(yT7pXA_MCps`%E{mzZ{4w z2ofdee#oFL9CZC9f3byUK-B*uCMg||-hpm+zEeHF517Xyh)kW461PDJbh==&$I?br zQAEGi*HeH81Y|L50t^HY0vW6iW+reMp~kW6h9H10(-8=_xBx*Ag6CkRrG~&*QqW9` z+Q9aA99my53ZyR*Cgrp?poxDtKL?d1wZDKO1Sb0ubp9*y97eg$xuXF;L=;$n z!~8x4inBKaPvkKbu6SoRTzgunRcOibLdIt8huc07!O20Q(g742#c5Prs<5}^CNKyX zm5$EQ7^oF3=LX=3J5$kFO#b=y5(d%BM^sFZ0s;T)R|X0RABwkc-%=Glz;{n#S(E}c zZqlC;JTaje>J5S#^iNsfBX)rytU#_XF5cS6DEnoCx%(6S!Frcunj~AzpdV_@WZt(kSCehpTCF_F1t$ii`t^uHvgC8*Q+GQ^g zKyn-jqOZ1R>&B1g&Kb&TLH!3AI^CXJiWbI?cC8Viq5w%eNd5W7iuEG{0s_X={$K+n zxOfoz;v=x^FY)o&RaI4rYd?Vh0dkI5vCB}x=q;dn_a8U9``Tm!cY&HWhI7SUG0`33 zxV9tQ@cJnIt}RwWFBl|!R+DAltcjhulyYA#2ZEB8D#%emNd!b7a5E$@7o119|MB#) zG6G^^Vvy{WP6>SJVtR1gJa-}aoNCaWjFW~~<*GBiEGg;X@DO~DEIBEEZRj%ntpxt0JG+ZhfAQ1tJ4FpLGAdlBOw!W=^bnF8;y{h34 z`+`IhEgkoL3=C<2EC>Jrnb4QmSRrqma5?|=bu&=+paV#B63gHa*l^@Gy8+#^J3NEM zBb$1b%i&;RWAioGnwgb&lpCfrFtW1#Haej@e0j8nys-htgWK<)SltDoz&#gR5Mm1= z`Tr+oEqx@_YX+QtA23-XK%2x%08v)fi0o?mdh4?zK)Li+UX&PD*mW1H`SkbO zvM}%Fdd9^Q@?KBmnqKIt-$^e+c+Qtw33sTu=BjK^a zn7hlNW(RuZHiTFsojqg#>ScxEfh_;!%9r?eE6~e(NN2zGL7( zh?El{gGWV2{~b#2rTSNXq~i6tcC(tU!UjH2bGez%<#ld{s9PY)R~q`>#{3N@*44A0 zfC~e8X>?H(0Tl>k56hA}kDrH!5ENGv1Z>mfeMp+h9lqTR$WV=qxeaE^ECE)D{ zxwPo#<`XPRVItec3r2)8UJsrl&X*YW0)0v6{cR@5w*jm(b8rY0u0NAWTVff{C?3gf z7~F6I#bQ8x=_<4eL2cM(VS8^vqev=u)Bf+r=ArC038qId`G}h853o&B4V$LrH2Be>>n9GG zwO<)7fCOr=s<1Z}oR@kqp}znin1-Gnxz2S@&diJ%2rh_2V-^x6nuXt1%`_fDG zxEX%Ws@|qgL0T;_rI6PQ^SO60h zwZRKNTEqPj6>pP}pc6WoNZgh?o_o|ZVdVd3WJ_9QclkIna-=I5zWN*1)1z}rEVImD z+lGYo4CQB-@ZE(I|Ne4-osS7GzA9Pq z?+UFaz$HQ{Df`J&r;G0%p-mVG(t}})5Fo!)YcT?`6)Lfr6^{3DwfM186@n4(gMu&A zm0a4KRYweskia}wf1Y{BLDJmW`cSJy;{Ob7M$U+8 z_LC=1e(Oan$PmjkwkDTC$OWPwA@~R42ufuc_EBK!o0CLS@du}6Dnr^xkjCD0yzGqz>Z8OcOwm=f^?DI(XW+BzJ~Is_#+IBwd)QmDC}7;x2i5#MT? zohYJ*4=p_A2L}!Kn#oKHKz>~A5doxx*O0^5qj+d?ay31;>!_X*6HnkFbGO)CZ7(y8 zyZToDsM2>|Ux#7PaIlgTRY&GqZ6P4>&C*iT>@_Qy(4Xs$<{;$XlpUIQ=Q9s5XOi67 z_{{$l{P-cQpb#dT2tp?$34~hR+Z)R#HyaYgb+>m2}8WG(_F$DZnuyFWnm@*amsXoxbYyol$HD0 zFA0uiqx^@^Hy4_FgYW{xivYlB-huuUb>tv>mrzhGdAse1lGVF?S+Vn!26{3j= zZ*W|`irF$=xU2oKEO7#+ z3gTmhM!kWQU=ZywrOi7UqktYqAVzSs+E=p@r~UiC2fw(zbk4tCFD+d72MfvV7VpL2 z(kUOgutE@pSMMPYA#Nb3Owxiz57Yh>DG-uC(@(wbBL~?3i^|Z?Z=AT5{OWg_nw)gV zxY(ZDz1W4CHSrQe@iAx8+yG8u7dMRX{lQA>Ps{!m@*4w)QbRz6bSBC;Z$p!S7%<(NsaSfniLNqtGJjl36xF;KJ>4inj9)p9!%H$C0a#2%Us@m@&E3*@p z$8%?uxBBI$%#P}?xf4w2<8BnKgJi89ZWtA|(|f|RSZj)(I;H#Jpg(V^fQOLcp!bq;$Ie^Y=@|9VmN<4IK-L8S=& zIFbcR==qmrB+pg1Msb;C$`B-{J)1_w;`l;xf7G{e^A*q81qE$VuH)HgWD5VV6W~H- z;%ud0@RVDKr^YjDW!yQAol$DGspDpyzCV25YmI_Z=Ic_dw>lk30sHd@ezN6v>{JEE zt9(`WT$H`G%|Tm_N?R;wDs?##PGDTykQr7;C9~80J5kc9V&$|w)KA|Rg`0bsutzof zz4SYVdnE>bGvY3++LA#jgEj<_e3k{aYc!5oE^>uX>aBtIe2c*3rqqZYGlt!yaoqIF zmn(fz7EelSQcu1+I}6h=p>_4V!$glJoKjrO97R%9r*bec?fqUic_=j!;q<(;v7wP@ zB6hbs2`^gU+e8q`X-Vw~;CT&>5X7FT6??K4c2ivIW^stT<^5p@WdOjaE`hLys2ekC8V*b+OSe zMh_G4vRn#u8L6}iDaMC*)yX!TDE6dAitYs>3#@9}kcKz!@-8erqp{@8SR=fj1t+1x zSzbfN#+J-gTD@{`Sbou#EuSor`i4m8DAs;+mQ?=>kM3g(JR*j=SHIKx?5Sm%EaQU% zhm!cX@0+uWkPn&(P7|xvWtDNCV?tP!%^Ow*&hkP_#K1(Ra;LQ1{RbQBF0j-)xM;S< zx?$PL0?6Uv@D}JxEX;A$ZUzmYhcm(!9z7b1!EMm13JLhsWAj!)G6+d${=w-Pxl?l* z)-r@s03ZJ*J)>Xp8h)19$M_dD;S13HboplI%~X zXv+XjSf)$fEE5$xjF4PlN?E+h>OjXks0(uhgVT=Ru2m`#ZkA;oZ_OOLBq6@@dsjoo z@0sedW_TEuyJN8pygwPoMeF4u)Q z7`_VsWF!%Ul*R?yxO(4fOy2YUEI-@`m?p}@rHSxx@)c?y?H4bNL*?W?U0YF@rA5<{ z;?}KEZFO2tEpI*~ybxuiQY162d%{-Ps9!80aZ1k~0boXwr^seEXt=gnPrQKvL(_6h zv*^gMua^UPK%50FX&{X)CVu427E3lcR#7oibfnRup{!Gdf_PT8b^K!v(?cnu!La;f zCSopOD4ixLyuth`t#d0%FSbmsTRpYg~S3p)rIGZv3Ivi)DD@F zmbbUAl7(@`;r^rH?Dd27+gY;pei`si5?nM{d1N&;ZpMiuHQWU(cNy4#;OSD_i|N@S zNN9Rgz;!>1kSw$UKU0CSX5g$p^t9oM#* zs2x|KYxLl0X$UN|x(!+TehZaX~C8$m(+t0|W$LSn+bzmLcfPKkTTDvlu zwtW1U_1@#zEz{fWhAN%FdV58NvB$$k!+0j z3oN%BNKxB9vP4~BYzP!<$yB^goBn2XtrxbUTc;%f=0lM%=OiUfC(+*4+WxC`CCrUp zPScmO)EJZWA%g`e5!>KdHwni5g>?tu1{S!exK&N_2GHV?_1-}Ls@Kgj=w`0*Q)lUP z=H=C#pRX;q;#%>?%z^}Hh{-q!(Ra=26rBBZw)}&TK%b98b8X?pd1wgy`)lg~ClpXT z8c0Svv{VqCVP$B$JVn8LkM!$4OAu0meQC?{HTVR6RqswJ@^(sJ9B!6m&S(#8jmLC~ z{pin22a2w)=rO`C+43M}`-BGvCR2)-cz-a*Q{2?tf$9w518C=oeyGMbDMQG)w zy|)vfYrx^Ryi&vtQ@qs)jYLOVYu`Jg6}Y2zNC;ft=Rngrs7srOZ9o3?skXR}_ea1c z{FGGT*yP*QUXWxw`&c!#SWj$Uw=HO0f=_4)Er>qpxx9VJ0q&6HA~l4xX%l9<5vl3k9B!m4p^CEoA1LX}t4yy4-@)$sZ7V7p2igj?h-WJVy5uUG-OU`b)DCQ#n85WxJzs4cN z#l5=q+?xIf(a{?_0OwH}Lel*-IXADu7!x_0xa|SJAn!8ia0eCo!=T!aP{`)~JqypQcWI^6;=1 zEO8U)NqYIt$htGZW)=}5M1f(}Wv(n|XJVaKQP=6&5|Bg+mCC&Hr! zj28dO&imprFlf$?7m}kT6QYP39da2kLg70OqbS=BvLjRlZ;`R6Z9JVFL8$Qy!%`}L zDIOUdNNQf$98Dh=qednx&vQY8;np$QXIl*8rL>M0sU323rlZ>%wD40*UJg^Qn)qoB z!QGDlD-#FC6aN^)?z-m08@Tk{ZCW8NzI(71>{8Uk^Da>|;)KRR*^2GfnB(!#mT_-q ziqP(NLRE5iv4gzg;!eof=umAb=oBxW`BZpnarbBb^ z!`t%Z&0kgMhTfj$k2Uz15cgRE*-krX2~`EO6r2e9||1Q2is8#F%L~Nh+EJ@kYjwKCG-rYCRkr>S-f#ci$}}S7mWyIM8hJ5yL`7 zwrRXD0ezIo4M6Z?`mrGJs}=C{%Esb)it`Pofw91@Q8HW#gOrUYUHvirqeGHnxefGp z?V1Z2`*t*Zqo=p=`lzVbWixvExH@i`UiLXGhxk;_MG^h=DI%^oh$cYLv_%ho?x=Huy7BO6E>Fzq*76KYwOlrADVEQ`EeyhvXWSA+OmT@}st>EkhySU)Hdr@B) z^y%fgtO3Q-ZqC{W@x@tIy~|d_lEygaH*p!w)YH`cSKahz-g6It4VIC z85FdlO--RUKq%YX+*C+sdGZ90nwt7tncwGZSh>tImhb5&h@8Lcqf)SFd#o~PYB1W4 zFk-&G($K_PLDm8$yBi-#LrIze1J-?{2CABMIw9;Fw${Mj$J_$eWx6J(R+Bd&U9w&| z?b)?8HG-_VKZ!tP0|f%rAQWyWH1W@7|muWb^%rs-vEwsK?nZHnhWGRv~T0YOs|V zf#K$gAAFQmx+vS zPr?gZ&Vf%l7 zw7lFEhf615XSsL)&aWU2g|r}w;Gk*55F9E2tqq7Cm4i-++kbtuRKC~tuIjWj=9Q8* zMK{Y!S)qcf{$7|%e&l(?3%@+InBPO<;U?8AhY!HBxGlcuG_|I=AHh51j;zNBqERqG z+?@GUh>4CtTVnTD`g%+MPTI#u9HQak!UrA2ouG@G3lw5<2R3?8La$SmnCkRmUOVG`j%k}x)`8k6^KSf(|lAM!)#MFXS-^SNZ zN|Nz$2;G%U(^;C%=uFZVA{v(7+h!*^K_5yFua(29cW|!U;qG9zB#CCT9~DGF5vQ85 z%*_`)eCsSH`wvjX_Nl{fxTWwVn{wei+J615aM<^<(SST+ua$?#u^#7G4SFu&C9X!` zH~}f$%unLH;`mu+tKbM!_B!AX-@hwJcRi6WetJ8mL3F0v znVt^!6^ms0gJwSst9bK*FUb9{g=G&(GPu+R)psg<_n<6jK!T%AZSvI{2Gbhu%}GLL z)(X9<0<4J|)yB;&zgkCKEnN%!df|NHS~(|PmDdQ0;N8>$$;jAMv1GwrH@q^IR62V} z3+(iDgStHb46jH!SiWA<8m_BWkRi}cD0tU`RHUh3{i}^$(yX#MN0GawP!MaKZ zRu=r5I{ZLLGF~+zwwQe}!!b+pEAv|JfOFe`1oB=J?u>W!P2*$-Q)0IKk;w2OjDrIYy45qrC~}i4rIMFFBGk7iIJoHr6Q?fyL%Q| zPJ1^`Bweb!lDgj(cRg1SMN)98&`GH%`{R;$=y1{eAwPu>g&APF8wZ>uXN*@EP~+6S z{)hO{0zkAH5Mxs=pMIknZS{C#wD;B?1x3<|b#0d^7qs`P{QcWp+%z>;Jl?C;pPiiu z$3yuF``+B_L}SC6QB|H*Iy8r(V;04X_bsP~i`uAjN`H1{z3sjb|MDQMP=eR0f_tlh zbwlK#0}b~p#wS3~K(iB`g z(2SX45>K)CuiDqj@g=r94$Bi0{viAzN`W@Wpe1u-?gte%PCb6y+!bA>d{$zZ;!&My ze=PhyR32WpfHdhmtjAhZ9N*p99g~(%itir9|1jar{d;F6`u!QmF1avjdFX96ObpE* zABD(BAh4$=F8zgxDL7__OsdDMtw4n0wktHf;^?^YTN9k)GdFLpvA05@#Z(ZT@>@5% zu*G;f*@jPj4gij_KB_!Xzeop++-@1#ej6)zONAP*1{vS}*=v^NqLJoRsG%bvx+ zMT?-0FJGA~cjv()=_t~WfjuvT#%-XV6`ZTBd7F6@M=d}H*f*;zW z>1r#qr1sLN4Hf6h@R39Gt1QUK>SCRDru5MC5PoL{zY9Q0Z-YckdGKj5h_niC%pH@T zaG=rALE)%D!KFIS>?TU$2EZBQ!hEKSM~qbWBqOf!zMBilQAn^G{VpFUbN<4dkw zEhjV`ORzG*g-SW7g0T(!vfs}3CaB9X%t(MD5%g*b-23(ogzQ7X?2$Kn1_ONT6Mo8F8$I+*+{ww~M<-6KmaDv0r zS1X`JcOufT^&I|zc_E-3sd~JZBnl^(Eq+`BYGQ|!iqKqg9sf#YNoJ1rOcp$R_@3q2 z%llGq9}LzWT@<|m>QzgN!{%(#!-ZfbE%7;E*G7^^NZO)ZhD^#m=FZv##E*IpVX_8? z|25E!9{7N;u%6y9{`%EDZE>WqVjcg+SCKByb7Kk#oSh@6d0YxoEJ&lCx1|ViXWG3f z)^qsgJoo;bsLCy>x4pf4443x3gW*f}+U>OOqdh=^B{HZOYKA99#M?5X05nVQaM%}8 zrLi~J)XfG`Y7PFH#Kave86!C^2YI~`viPzsY&ZZkwrzAm zye44iT8jB7RaVhPzfFV(x9B*O`#svnaI>H+b$E*-Tst4m{y2i#G!J=J_{xQfH|%QhNi@%T;(40P%TNn^BS?V0SpdO(pqp2nD(Nt3M8B`3Qu} zdV@YCbybe_Hq`H~g!BMiY1k_5Mj z+5>6;SdmZtl(SYU8f1vbKxEtI>g=_hL^9(&d~Pxhg9rq<}WGs#PY1UAexm$5V z+-ymGSTI`cM^FlR8c4y?WELHU*+D!Q%q*EloH1YCPd%=J<2Cj`lM=ZAV@W|%#t)<} zYn{HJzQM(HNKC?LIsj^%i7LmNE9dSQm@5brRBXO9C2`BXRJ{2wwGgVpwcE)R6`+bsS}8F=57rE!D#LX|2t)ox1Rj< z*ew|8gZ*se(AM&Cov#ZW9@%}deRER-4Pin&I$sl=D|(ifb417Me`gN9eOoQp?@MDt z3l-+}jKd#?9bkZ=*_W1dq#^TcTP=+>%2Y_ zYa#~bMFD#szFLDz=Szyvry1*1g@#dBB=oDCKzV3aU0LiAVRWgHG2Q1l#+aBmGD5sU zbsYZi;OI^se0xmrD7Ds4-S@uM)U1?+hdY>v#$vdgzU{b2*OY7KS1Qy@DQwWpx)#B= z4j-OuW>RhD;PDGzg3l&e-KRa&09CW5=(yDxdyfXuqSs79DnwDCA$=+LDFkU^VoHs) z)7F|wRnzh--V~v|vr+`+CQP-=)6?_b(o!+pXvOpN-szsL?wN{(n0_s)_cy9#I#jU| zQyjZx?~E#RNtQcal#fWMMW}K`f3;|AR{sIKzm80CyudAsM$h|<0xV_@*IQ97HoHE) z<|MwuhU_h0-qu&Z1p=GV;iyqh*!OAf)z^lJt;_x6*#?ta-B8J~W(BQk&U!&JGmKXW{t z`Zc#{gyX!j3E~0&*pI6y47Ti#9s8o=^N%NIV+eZ~LNek6JES7}?(mE?HSgnR^;iOc-P>f14FiB+FuumBU{+_<4wj11#$((v**^ zvVq)Os&r;Gb4AjBr-)(JpM%5ohu}IR^gS*##whF=5$~~%OJccA9-_Os}w;& z_)3Sh)4$?ti3$#@wbecL8t8wp_Lc!vrft9XTC^aYBDqlMZUiL7AXPdgL{dUR8c|X} zlx|TFB&3l>k&qNAk(88{6r}cXIWy0m``OQa-!J>iIL^RYSDfc@9{Kx!tv9U9B0%#P zoYNI_SMqDHSMFO*V}3WGUeXeDs6N>sBnF8=U6T=)2Nu8bf86C$x-$Fg2@$zT3hp7N zMp5t@ha$D6>F)#7HUrdP`7U3X?S=pAIL7fjESbLT&TDi)jZ~5VU0cB6qJ|4&beZ*> zWSXFLl#f*MGfZ1lG4;m_aK=tTy^q=NsbF)=Rj!WCIgtsjxRr3X_qdL4G33>w0h1Y? z@v~^Hpg`=mQho*U?6hpsKk=L_N>+N5m5w_lE=D4)6supkS^`$wVQk8jn0R5BLchFy zgFW8O4FbZ=qhR7qQ)|jZ_W)j|*AeS>O*P{_M-Wo_z7wJW6EW^Z;-viI}`%yqq4 zQfP1Z4&ehn?vo#Pldc^8&bOE&BAP?pk0XTSXq67UBIUw%N4-yFXq<~4_KK1}^;M=i zmE7NBHa%M9f1E$xbDp?q|NV?bTY3hXoBO)s@?d9)tEF|Be-*W=G{+P?zFRs{6KPA~ z+?G$I9(<|)<7O6NyV&io7cv*>VOwh8{Tx(oT2sBiqI9gP)x%EQQ)x6ihXyxkqp8}} zio)f`Q=?CH**i*)Q05lZADo4`SQ*Y7-!pZ07lS0Rp!2kn?!YHLl>|$6AujIc%K-yJ zQaZ<9t_KzxrkTFXtuOW<7NU8o@h$DtisPI}9V(Lq9V@`{o5F0CzUR@-#a67%>t6M# zc;c5P_bn(XEHT(9kMZ-bhtkA*j|F35gwW^!I4Zwn;Y^U(sl06#tMEi-hUhN&NyCV0 zWQPCo$Q?;m90aSv{kDz*#=4rJ`N0{|rL2vjjrTF^$|{{t9)Q6(-Bt zR<()fp5V^*Ltpa9+YiqTJnCMk_XN91oo)ZF@MssNKYDLcO{IHx(K6o`A?M(FHeMXX z6ep~Yi(e%j{3>huP|#?<&aKPEtC`e4FR9)jR2omKi zn{E3=I=iBuyaC3Gw-$Osu4R9a`88%y$q$29fPfK(kw9ctr6Px3sgQ=&!w==v7R8$| zS#RjxSo6!I=+pp}1$ti;;+RRS`z}uJOXjbMp-q3`Z8J!B=*ju1X$9z-piMkqxV6C{ zlM*g$JuC4veqiuZN_Z6GTx{d&kJb-`Wd^>-`wPg-E?>BiR@8I=Y(FdGQ5;~jpCM|fl$e8L5mjSUx_hUSoQLw^5OczY_y@!3H` zW-X$F%5b-;;yw#ExPG^ybccoI-3GF-G8BtT# zVH}kS_>HCGoY7``5ykp{$_FrHBvH9+XJ zhy~{m%g86C>0w+s{XoMvbN7%(%1H?AaH<5hc8n>qv`@v!A!8nj|U;D39F}C~CtyqL~;H1Z* zw>8|>-id}aMQcTn)5_T2AI~rKa zqn;{Fu)@l!Z`zpI?Z)2iax<-$2BSl;(B@}p*^bVLDlI9_Nve^OR2*6v@f(R#IRA*O zhiL#t3V|U-c<^goJjJ>e259J{?sNQsY;AhgGu^A-q0uSO3nXEb%7m#*-~Tj_d&f?y(cRfs0R}8Qd zZ+}d5gadP|*c}}xYl_9snj_}Zp(gbK-s^F8PdKjG*)9knXUsL}x-fL`;rkjlNG$Dk z-W7q7v(mwVjJ-d#43^To`O`m@t=l@ewVF)Tf2(bN|0|Yh&w0aD9bO%|WA}}Rw|hCL zm$9B?T>1@z)y`Z~Ysp$ZG!3YDN@!}K zPoJ3{bB>Cl6fDY3PhZ;_e+v_G)t|6QQ2=alsrEa<@`lc|S{eqDZU4RvBn`>$g|%~h z(K9x*06cSE!+<@{w&<%@oa#ok{Tfu|=6~-d3c?hR>V|V@NfpL_wedPG)Z}{@4>;rPYZB-zbe2DGBTc7N)L|GYkIf^+N+47RZH+%q3uF zlc;W;%szK{Mu;I4fQ_3%d^+(|Qy4n)z!a}xi5EYgQp=2h6u&3!IraxeEnWP>UyV^2 zjm2a?22Rn*d}ALzM22Y5eSI$V(UA5wb?jl7TKE5TB`&o6`CrF|H!mu3rfrZ4YjXQ` zC#00MsH$0}o}5{eJb^ypfBB^P-NZF%L~Ox0un5ra`~`90H&e%(;e9UxyG(;F?STKMK0j2}3D1RN zUVo7BAOUxy#Dbna078}iA8&5$cE-nj;-k{ncPWwQSFi5;2m>&DjYcF=_iWzx9jrY! zmhvsgzd&C7P>lYHyZN`05zU8v)Wb#H9CxyhMl`6w(t0ZgVrJ~AN4{4^e~ zz{sYtD~wX^E=L=5z`dH)7uqLqc5)Wsm@6}U zP)r%`gOSUsK6J?}EuC{Y_|;jYYqTE3fqLA6<(uKUmUzVPS`YnVF9)&s8-9!l!qKJ} z(n0h5=wOwd8OVp$HT2>=Y{Dj-jxra?E3SFIW4Pbo&MR>H;ZZ59BA8q8|NY#0>9P`& z%O@k2E7&W>s7yFWdK__eYyyjMSeyx;O5d!^B#SvomND!x+L`c{(~7ZZvmfWmP~Tm` zRZYSes>$xj^*kKBWs<%!bpDb3c|pI7l;W14_7FgcG`-HKG;;ia!y-W^;o5oxT}h-` z+)Y!GO{-Gi97Hj*(+4j3m}%e@w|V#9p@@l~dp*j_6Kf$XLf;n6%YmBjidiRR!g=(~0X^T-(I@_dmlOmq8;nI2=s#+Dluy^yagDqW`53V_eeCJH!KcdtSP9K9`r|HK02 zSX)~LL+RqYUlY$ybq(Y#3?FIc1-uXHzC?O2=y%fiBYN9F)~A4^4SeeyY%yDEn)~dalu;t;2t~K=33r zc`2UjY~CY*%C~zV|7wzn>d{rDk{c?-ZjJURu)i9nYGCvUM*d9m@MGFwjJLNJjc@9@ zCZR^{HM<5Dtr1E@N`mC{)4~h;`+@p%LmaqYzT%~AH0Cn0>5^%oLL$vhC~>=_Db20v z)isI3g*xapp(kGHu^i^klA~baJDKWDUHn?ZY-P3ky05#_wKLNdES=xVLn2G*yRsM4 zMU87bEyEo#o8?nZEDz#m<}|EfrZBKR-MAz%bWBxi_Oydkt zd6pC3%wfx-U-DE}Zrq$p1gO_jW440Gle@pEZXhEGJVWQTerQolshy1MTX)m*0hN&h@=8LWpi)Yr@K|-m&>HkU*D#>1j2@e)-T`YEW zR7J&ZC)D|dPdifpDxu;g^f&IjeD%>U;__|Q&#y^qq5Q;9fq5R9ay=mMOu)CmobHEl zYj2^do9?{vo=pWphf9;bgipuMCmSwK=ry@(XQ8Oiax>f0S$|9sZWDSh;dRTs5vr2a zIhsUebL26XV1YM{1PHWicSVXY1_s}`IWw4!a?eI^Xxcy377NvVYrsPv&bvn@nNRS?U|7&-LYhe+~gD$-ioDM2tku}4a)o=xQR z1SW0z%2O5=`!{`WJhPIdZKK0%io)ChK!}bq@H0zIik3KDkDVv9+->!zt9Ifth76R_ z>a&sxQBm!v6VDUhk#FdC(ye4M{AYi9XRJSyX4$1@@jtKWyM1^}A^VucmNq%+1ll?~ z1)2Du6qCznmmcuWvj$e7TX*g4yoa;X56MusTvQ3jaU14mE{*MoI-cNRHXksBi!048 zCszj0Syy5(F66M1m6Xnj-b1ruTv$o?*kKMA^ZyVc^8Z29PPt9POLb%_^E15vtsD!dWlj{%Xe4GIfxD^IX1--WKBDo>=&SRhpAcQ4PVg?B^7-V+H z!y|ui27Vk3R29pNFUc^--%$*p##C8fdYJUGE2$&Hg1NTjL0{lrTn4y`-M_y?GDkZM zVTGjo?&_nO0Pa?7JIGZ#2V}$R2qveze89f;TDG|p>!t;KK8^suSS$?UJOTLF?_H=f zYQ7JwB3%BupIBKhUm9+?Db2nF^a}xkWoawt+Hh(`#=h;xYp5Y`{o3e%34zc+_UHr8 z6>_a93;3ykl7L(p*Ms{tKraJ|8^T8eERge{w(fV}Cfe@U(<;qo{QZ%(y<-#8&OoF! zU-??{wal8d;pEtxLDB^WVJHGqI}{k*BLnOM@c?0f%ukYRLP7#I3T9!)4DMk{dpuW9 zv8GBzl>~4UBexOLydhWKH;{J|7Znp9KV+^S^qvLr_MumdmH?%YeIpFPNv{do*w|p9 zOno-yEZzdnuNA9dZ#tqRfWKi+s6H9Sn&FcAVj<-NK*L7}8XA%>U#nf&=ev@EoM&1` zq~{Uj!A%VrtKaqlbWT7AMre(T$C*gYIXYU!*;x>3&W1;>PY*Uc<^VqSH%iCQm!uWT z1<&8KA*>`oI}a_+A5&%4vNsVFIf;<$Cqf$fU$@c@%cPDN!|VGm=LfQ9I)tZ<`w z0z-tyq|5AkwVP^1$!pI_0#e^kCIEPb<=)hKr#Q6#jmf?ni$`Yd-AAl|+zPbH4IRvIx#n)0RqBUqujP|vL%ly*cFSF}A;B{zR0Wt3Y z#c{(o{8lX6Q~svMZ@YP!;O9}Z1r*&!K=Vty_&}nmtb(Ye-~0d7QkWIgN=tq0g3?uAtCe^7-nXZ zlA?$9*;W8BJ^`i+^ZWPjiw>@aw$J=~`Txb$cL~=08&8zA`@;Af6S7)?BH;w|M023n zzFR5nME2`F-H3v__Vyp4NiXU;Uo{T283Iu5BM@yiU^>>T))wiIK7@o-_1T#~e;^16 zV47CHmMFqD4F@=t;lS`P@XipzGX$Gtq|!eF66{pefJf-O)h$kh0v_{=8+kaWe!IRb z<%uH9zF;fX$$LGyHE1Gch9PSWId&#M4gG_k1OKMX7jQFJ0RTg&_TW;XIo|K}4~GOt zcxoyGG%K>a0fsPeXSjiy1*~2GVFNF1e%1CFvpLUCen{4+Kfyl^0>%N({ppP_*ZEJO z%pqk#a{&Ap929WMN&EXrHjCg!l>kU@Xg^tI9Sy`itN?_KC1WbM>HP%v7}nER*hZ5- zAcN8am}W}uFWx{wV-*|kE{vtK0b;c+nps6hCqBgPayO%d6KbY4QV{_(?-B!J6O4f* zN>W8S25?9Jer&4f6wlb$*r`7lO#t8-@;*;ZJ&n?fMsGFfcr!r**bp=<`zKOI6!3EF)QRCgWg42*wXB+ z*znlN60s^GUQ&xuPb|sS|j3hD{fk{sFJ(bkbFM z08om}4YMEvG*Qpp5oMnd`JaID%kqEX3{_X;UanAB7trypM3+3Qcsn*UGc>E zAOMXmt;6p!26yhe#wJ*d7J=CAv!hD=~R6N1cDrxIcfEbU5@7TG#!}d00H);xEBmI$I`X^uIYOsx<%R zsN4zaZm%6GGKLz%9##Y`f8|$QFfWp>^HZ~*o}1*J*%yY*H50C9CP1fo>(*=$*Ru?B z>7V>{{K%&Dg%u8n%v)nnQpsv)FadHRq|227f0hVA8<=C0q8InPf$yda#CC*VICg9d z1Ud=?4hck_C87YZNkMQ?R%{{LDOChsXUK_^%3uIz+&nAF!=xE`gZyh7Z_DWOrit_|y?%%6Ye}CU_OhMsB8Z z4Qx}Cq^ytNOnd!qXUMPx4*&A`u3v59zPD1lHoG{0(0C4L$zcPSYoYJ@qW=?EevmC|^ zjcaa=0hubt1r$YSTCpeRI}Wfm8M#;=IoUlY+^;}jb)aeR5s_#BAaVQXpmXS@p`>=* zGyq@$Q19K+oBU$GBQI1bQ9n3OK)DNo%;F44ASeK(4iJ)q^AC0qo-hjdp&}E02M#DX zsQ6uuVptq_fWQy{O>P0L?w;Ule7glsp-Uu~ANi=HOa2YrzOa5Ipg8EehBv{ytU4PF zWJCWKfNz3sYGH?)`Gb3)kl+jleOIz55#Z`SfL$~yP1ODCfOY~XPSv6`tZs)QA`n)g zp^SFtyLjTVH-E5Zbqr`jjL=G00$#`% z$e2J0Y@#T<`LLu%>A2wCyRV2`M;7Y+$CqgxAXftHFsG#f&X5k~i|(i4NOdfV^F7wH z#`q8W)My#P|#>%tKf?YyhT0xM|1;3Y;k^9SC^r&nyp! zZU9$$8eSwRU=3`%_4Mc(j(^*s9qV^=z^W$p37LW4jJy`JQM27`uDvoLh$9gkZ2mEnd=FGWR*vg{PK3yw^i|z61;S9) zy~&2X(aGcB!$Y5&XLN@~IK;(i0rbKSQXwGX5DJ_7_TJC$dyOXtmjHaIC(}xOi9hBo zAT`%jhjnh>W<^cGaW7muFLrO@321*H>l|6ceZWui0RpL5Z?*fX0f+{WgNe8d5NCua zjhyCy40gC_JY1k31iXZox^GQ>4Cd1!81cHgI_33K@rCF z9JLglsLq}qu{80E7e{T!p+4b^d>y!87hsSF%B+V_B*^kVIfj7hVgDip`99qRCRwG| z{Yc7O(4zHpgfAl1u^9amu;N|2^$4rj7l={<4vm0&TH(vGUcWHG0ada!wL?S?0tGb)u&VX+Pv_P%OY>;CRg_+vqJYmbyc;`5waI*_EG zFx;JDUGlc3#sIO9C^CS`0a>xb3Kq+y(l}4Lx%v5TYSK_W<_1le^Kck;R}K#kM*xwG z5QX97{1hueR}t&km3C1VMTSt8TN(fQ`0-$C<4wXCvPQHOuGvMHGyqU)LZVIdR0M-sE3UDb+z#MS~@Git3 zXcQ8Z^=~JG@i|JHE8U9zZxpw=TE1Ep$DKz0pbFu6ciOV zKs(1^g_MY>8JtNH6cQ>SySePB@aRDpR$M(|Y5f#|`GM?O@Z^(L`|pa-T?C%W6cUKm zJt%9Qd;mHhmX?+*LP8XzGTTpEj^V7Mg9k^F5e?ZV#SM4dA9dN+6R=RnhYObs$C()! ziG$vw($w+mO-Pkv8f5{Y2RLsF2vaz?xIO@u^+`bikI#0W3UGemu9G!hjHC*l!Rnce zJS1ID#sc)II5l)gY?fPY`%-@@J5JG5D|KeNQQ;BAAKF{P!UPv zZmg-P(O&q23^y(sD$utO!;ahVw!AMxJf|$oqn;*RGXH1c#CdktNSuD6NS=chsusP+?x_;Y%Kah6rSIsb>qfEn8i^n)Iq@gz_j(y-Z6SpS2wnO z42LDtk)uV`)A$+%(bWdn&?`eyvs-iT*hzWYa}4NIu-&zTcH1PKrQoQD#scByp=2qC4%7Tknc=L-gx~Do4$0ja5d`HqkHwvJiY+zUy*I6-0FAFLFx^K?>nbiYoy2TYW zHGsHkMl3vuin?rM#DFpbZYcD|l-qG#S5gAKv}P5+P8xx%4k`d3Y*U~mP;S5nB24`C z+s{T~YoSx21xV!42nreykMdA#kLNdaTyoiIXN%U8(d}R4b#RlRP$=J3DZTo#FY(UW zw|eiY?u;E!U-|&X3po$_D=UZgVJQkma_@r?wkk{AIJIg4@Q1R~S|E&)Zf~r+TU3=J zye$J&SqZnLSmmVBQX%AI@r3=rSkw>R5=u^14(_GGp!F+pJ|NA%Z&8rPc*FcRD>$-Q zHZ?;h2aPAq2#6RqD?<5)lgM-P6T9=c+wg4|5Y1V`lS(52nHqd1pP%wZuHB+JuEYSz z(~#c4K_T4XJ=m|jfZ6U+&(|r$VxbI#2AKZx`qI)bOWthWyuv6=ZEai>jWGvw?WkV; zXn3#wF|ej?!*3!<6Qs8Y_8>we5-QC5{zeMXN`@N|3I7kk-aLguG}{o&J2HHU$TL9XS`5>li1+bhqW&VF z!!6zIZEW&@dp7$Ww0%TdqM=FWd*17Gp+OBGSi_v0U`4Fs*gJC2xGDc869-nWE5DQW z*<<*zQxygd1|?OC2*w`aU+0v95A{cB3iT0T#P{rgVp38RF)+LlApFQN?6L?zciv25 zlJN=!v4n7#p;RMaMRw)h4D-p|Z~D07=!|QD9PU04x1w65LE*nYG3Xj_^MKD^PSou}~?K13#DI!Gi}yC!~;9RR<_Q z5Rkh0;9;Muxxa{kAAmUW&vSwR>}8%RK-nQA5IyPxJ4|uWeMMk(viNooL?|@=vj}iK z(RUcpkm<|U!lO$mT^3Ge~i$9w56uCOw@G zM4MpK(E`jXZ=?h)9_^&hR^-U96Np--!9}EjYXNv>D3~Ecs7wt3u+95t3=LIRLy7~* znnb|xZXZ~pzD9q4gvzx6xg^6_w?XinNFfbKgg6}eVG2e@sfbz~vYO9B8kBd}uEIdj z|JbK&D=t1h9I)>4F!rbd=L5*r@qw3(fsQ`&7)?YykLQIz1A@2zqq!6}USXH;?r3*Z z8IW_zpoV~eZb7Ic23&n}u&WqEo<|c@D(W=OKRPS5K?zHQoLuz1;D1Uo{*O58|1%S< z4o7&Z72wTA?*R!Gg9R@B=pd`D$A6_Df#$tFf{P%y_pd>w_T;-qSQ~)hg8_edPZ#(O z+Rh%=};`##{UNXd1GdC%Pw3$1G(9f!uR zP@f=R0+R2Ox_6xWf1HO$VBVj+ACdh9m;LFkog4Xw%|@)tkfUSqC#Rw`3j>O|%Kr)R zUR`<`0m~iMGK-iP4d8k~d~yF&Yfuw(Kq;j|;bFzr-X1Xif-px8xWvcch~ePkZY(A; zQ~p8VL9Yx4um&6)cwx}{L9;wB3@Rq!wVYDNo7w3@B34dTjqansc{7V$HWGhSDHd62G%`yi8}nk0k^JCPHKG7*yK^>`lV-_qdrh8PqEU&|Kq2Ey`24h(d^ z>dM9{*= zp-{mjjN#x`nk|0GMgo5ZsbP@h`vdI;rx*m`M7^Op5dn27S@_V*JfP(hfqUod><|`e z6af`{{5sJ1g2<{BbPNH?c)Jp^A8Xhs(EjUxK^;WPYw!rtv}Y0Ce^iv1Hz(m)!7!gB zZi_%IpzR}_MUbSfDKCN>ZiS8s?EjfJ3Mwt$>2Nq8Uj?b&W(aR1K$HXI40;%~FTj+y zHqYH9I6gms;$9$3=<8}f4{hf~8fElBnhEr-PNRNIHZ~3l{lnEBkr@VsL8LALH5F{6 z2y;O-5#~p0ZUdqK($V)FTEg0u2+)ez=t%3cw{u1G7%c`VbX&1rLVgB`c3VK4X6C*x zoQ^O}9Xe(YMT4AQ!1yjU$N{eh6#xPTUuA|76)NNxAh1@3ObfIW2Y>l;<5fN&MKyRCiNjvPeL0-Fs0kb9+adoo13?x)ln(-5D28C68X(cvl`b=?TyY^QN2$K}V1&Hr z2`=g<5@CSHAP-JLDx_p$#9{AbycYivlavzX%-zZ=EKcbaG%>2}0+Mn6uuWSVMj((= zPdk84nfDM13xNC$%4O;Sq%W4auFc{c z^Ar_3PKQYxpb}Teg$1uLF+RBpSFZhO)uu zPYe6*(*B(_{x1mk3m7^D2zRcIe{{)-C!~_0u7)vv&6oqfBNdC&vOU5K_6CmUws|C` zPmBwTjC8mj2Rj=2srF$yVQ(;z#14USuZ&ewA~bxE`7*Cuhq9rB=T8=Mb8`W35q13A ze(x+hw@~Y{aB}7q0*FnYtD=L=LTapqy2K1Z4zXWn3}sg0STUP4?iHBLfPZI}yZ)2V z{r+EsZnZfiaD=?WAJ3&_zpS(rdGin|j@DlyAg>7HHb;}kG@2vrYjEd!CFZ!`vLVrb z@|~i6a8^pp-eal4NDh*7$~#0VOGwdTrx!duQIMK?3<8H}NQ*bWZ9FCndLMv1X($|_ zkgT2&+)ny&UugTOqEK8VrDLSOECgIiCI|@>-P}Zr8h+cJW|n1u8L9K&K@+xz@pK%;J6j{W;oKuU?r=e+)xZ zRDeEHX+QE1Tz8na^Zy8TdO3c5@a%SC1$uvVXNY{%R_6_VxVU{@ zSbott_`=;4$l>5}%(?@18W9ZzB_oS3udae$B`^v`^cNZhou@X*H$KPdteM#S0+@0X zuwdWXd>u4{zmRLOxOh+hUu$Kx`3g!VAN8El1ByXMIFy47_|H)PeGep9H0r+rsr^r8 z<)5$mUBLAIbm#dg${M7w0)N2}DmgOR)C1YQ{{X@nJ>GtBkx@+$)fny8tKr8*FNqS$ zzhODOF3FJBeA9TBQE67h*QYpmSc^hWBSLH=Vb*%KifftEssBil@t zBGOe~gDCF6bV*JxI262o>;G6rH1(}3%t=uroMmZwQsmW7k+;z|x0u-pg?_u6DL7|6`y1LFJt{f{u_%E2}wyO1>N*c^9>fjK-#akzA*{ zv%CMfT9NMHy`JU#9ff;S%wE=~-Uq%7?4oQmMeg|JxkPcHvpr`tt4k>=QfygIA3LXk zGsk!A7}h>M_HB@hj}Pu0x`|=)(pZ6LDGG%&!vDcq_dnNE0o$gmE>BWQREkF7TH$hV za5n`X5~G?NbxCgITbX?Oi)nrFjDKV6WYtAaZkj#%RRP{@T(2KQbJ%2x)#zXs?Ct%{ zGJcO*a6ElLaYkvNp<1*CgbpC1Zxs0pB)gD;9)#IVR+IU;)cM@8WutMfupJ=5zZm=! z>!y`e_M*os-$XcW!{uz9kta0`6RY9iLO#IIkZB#vLl-|()&K{Lg<2V{>IK~dd-0c- zBV86f#Md1Mzqpsa`WK+u#cEFO76@PlQyNrCMFh~b~2-L-}l<>R^nOgLg1Em#=a z$+6>vH4unsL(Ig3tviSWz@7hA$a7u%l>-mQKs|YIb@ms(_3Qw?2!Y@ydkLkwCsCk&BlNn5pN2fYEplP`JP`UDdR1BF$IdJ;H(5P)4k5U}n5b0R%P|FCqC7+lkbQbnmQb75`f5eJ-X)k2t=pb@M z20O35CD|2ABCGM{Zx>F@Ny{L@&rzQhE~+lmo+4=SB;%-~CJN2<-Mj*I(^~h{51^Ii zwD=0;hR_4_ei+0H?D8A8mlMF zFVa$-^Plb=W+8tN(ndk5>wMw!BC%K3q%`xr!=HFPgXyM{k{3kqqD^-s3}r!nK-W>s zC!48|^|V5f`Ed}*U7;~W#=^_9+gBQGb~1OnGv3N$HlqU43kTt>!NH~yQ)?CAvJ1l0ddyMJGDG*{@~&7*TS#N-%F2Pd1#+<@aKaS$BU#= z4jx4r7lLX1iF4S#6i-1^WT~z+!D8#cPHXGX+56}T_P~y^7ssh^Q?(Yz9?rljE1)kt>^eulHg=V}u>6TEA3Y6`1LwX?63 zTiZ_;q|`-0c_l_SS0SZBog?5`ZhM7vaA$?|zkSfc5qsU=n63A$-IpL~u%8^zxU4fk zC}n#wxzMagyZj1cI$^zhG#ne{LzyPZ>Ft zAEZ@LO8EPxSFYlKKy2q#!R`Ih0_Q;a^YVfY!pPyUX|+1duigI&8`ZJYA;9iIB1Y>V zMl9XS*M7ON>frn5NsvYM_!Q`zJ#fJ5 zbup8K`>O+;QGtF7?O%zr!e&m&HQ_<>D`4O)es^C3#RoN(!` z=p!F{dp6-Z^iVbW!N zEzo8^dht?yP`|Lc#qs=pPJC4ALk5CW|11ucpA-D+?^#ZNHK?O*rU+(r^W{y+5hPnuO#xd$qTI{e z=+t}NbXDf5`d@Cxn#M;z89R-#hgQd7tvqc_kDD(`GW&eILkY<}R5D$xvRecd*fV>F z4ZB>F!TDJJ)}0SDPejf}S;4RWNp-*=r^YNXTh zCRTpKgW$E%X>0w+$zxsHIxi6o45|E{%Y9V#aE&EF6)#k6HtyoVB>6S0NZC;5T(HsaL++gO)72vs@*yfLi zA>`qzASBmNmZSc1u9ZM8Azu+pA4w>m|5_)oAdpb<3l zfgGLa91F=WrTtHqaVc9@{ZLKRMzI)HY_m8SCcHuQ7R6jUTNaZKe+<q&8KCFAE{Um-=5~!iSv5*T!0{!m*=^iyWUHzhtols+qXV@ z7W56&cf8BFe3O+;;p>t--yl;Fyhq-NQ{vBIr<~mq|F+_Vi?XT_GTQV{$ej9w72(TR z!N?0O&kyb4NX-c932WzsO|}Z>1kPu@b1CAO*BxgYzo}K|P(}wE6U&8Pw7m*eDA9d# z@QtL!aQ%x1*lA z#}ctu&wXVjb(;p33@!t!vNQwJT$Q=$Yp8(TYn@$e99#r(+}v8v4THXo8Qdx=5Gi~D zam?%~hMDh~Euc5v58*GEY7CqM>A>U|FZ%Md`Rz_qW@@HJPzb z->`fuQtY&<@_Ob4-#0&mqJ`!!3r0VP{f_S7w*$@naP%J*y5ui= ze0}w}y99GB>tSduTUX_v;~P=6HllYPJFc6it2^}PvW6^lx$$kNd9U4x{c7C#QpYr6 zJM})|@~l;Z2_i_N4Npw45V+_qR%=3zEH`Qla~KW`(6_6HYEAPp2Z%5mPXExOglxSx zfYe!~B^b^NUwitce|JCt3k$ry;1N9%yZo2S#9pyW*95Km8M?+rh8>Wz@}{qO}1lO@0R5@VFxji3dwXh6svDZaCHBIj2(^Z;{&G{5q_zDZ9i7!GU z@4J&^kGPvHKk;_}$X=aXP?*V=Zs zbZ!iUw>%7h3l=!5MPFt1w_kNS1DrZuE+D5kP> z*BJIlBVg4v`-^VaNZROhQfX7MvI?QKShYCba#tD5?>M}j8F|sGkpDB9hrB}7bfre; zhVS=%S56sfIpVUE;~e8U)wXwe*JCTzVXd9C6zMp^i9EQ*qw}C`^Rr<2%kI~)V7|7! z^AQSnjN;f3?p0!?F~&d$4BU13tP`O6;eta+Dt=cgB90eAX#y>Ur*v_lKc3$0JetGh z1$v7TPHM*YYt#o4EU1wz4))J#Xge&-X4_771n2SA=y1=T(X#b6!<>&9pVW1%^@e-b)z~Da;w{z0O z&C3jTX`s$p3y~_K0V~DV{IOXP@$13FD?IJ^?Q?MIZnE=hmeI7n|f&iD- zidd=~`lO$iJV(g&LSe7msoFF1COeKU5%fVOd>>$A%F-_XD&fY~>L);>zpqboaQ%<7 zqL|h|LhVLPbAXE@M(en%q#f3-F_PS><8Kt*ARMD8kko z6Gxu`_j3H`t%El)YxoX24OUl93qcr`mUjex(H&PBE}7XkbA_4wpB3L)!0jnHEd1Z_ z;xz-`^K|f^on73PDidTiLG=6;#Fa4(mhMf7a5Q34b8y&>i=u<^f^-2l#jCjS4?DgR>5<8TF33u+I~J ze#a3X2yOR;r`G#*j?2a6941GJB{yZc#$=IbC-*q_o7DmvCTq8OHLMLf$FRr049HM8C{@QAKibMoft99NZGNz+tXFw@K5snh-h1e)W z(h(XI#5#uu2VX$dY`YpV&X5oUJd6rdtVfrZIU(4a(RrfiE??O#bd~YBQ~7r8;HnDK z#p#|U@+3r@nv1LB{BR}!y6Zn;dE^~t-YBwND`3$x26SJR@{iEZV#5)K3EYrut{`P% zW~2jkZD^D;hq59n018-Ukkk?DH`puG7xWRjHyPit%4BkolV&Ja)qG?)H z`YwM-ld;s;2>O~v%RZ;FeSv!qHLSaKeUp^G5H!3&!v{T7d{Vj*JwNC_*)S`tyVo(r**<3Jn-(>_XQ^*n2ao-9RQ1DV8^?CXoImYzM4e7hl@Lk|ODBy)aoZ`Cnj-$G!?!6gm z$!w`IyLT8Hi$Lvm6*mS`+M7>V0xjBSQD4Q&lk_>u$RN|VJB}6~*|DZXY!soUb%REgahncQ3~gin z6A7O2GM8G~d52Q$mw5Q)kH<1JQuRLO`nR+!wdSuZl0zid2o3O(TyD!X2HJH7=p#<< z4JG{8M&lkwT{sXDbZZR?{{sb{Ap&ls2tB z;;2nrd-4F=KkfNV7ea^US-IE;*oPHr=mlNn7Y+t;+rOPg$D3uCyt~43QzpFGyYeW} zFGP6DF&(!K1?wj+lFv7+Ilrw<@kqF+G`fwCHL97ao`d}xd*H2V^0sb|jfP8u|G>wb ztIu7b$dEkT9}FtW3~3i`_UG4YL5>YnF?ep{*+jN-!6b6x%(kx*E^V3o0JJ z$o=KPJuYFlte-3w0Z58)g`zfo73LMuua$FQOYn|jv75ZU0>@Jl79oTb^|0oh6uT)POTfs znv6*GaV9^Es5GS#jPZH3Gq>FLW#nOHQKg`+_#5swNn7&H*Awgnj9X(q)peWnTe+!F z65{-*mm>R~rc`{Y_@rI7sO|N3i`~=Eu4^{h+(PQ{mJIa=9M|m6YegTlWcUZxSFJq$ zCC`teRAf{J&se7pgK4)CvJ8=K2!4n$1^3p=#};Jyol|L=H#Q2S=)%EwNt^!eds_zea{Tt26t-J%PAXG5D_dNqlCl z+v(#60-I^yoPy+AvYSSy85iz`g>v)@{%jX0JvTFO^xCZA$@u$`!S5gTHBzJf8xAup zWKAr**=&ttYF|-mxf9^9;CfKY6@{9d=cgEF^cGe0HGEt((n(E*$>M2kV#A(OJ5%eg zA{X)+`=Dm`#hY@j`56a?(GIBY)04Dt~lu2a`qzr#{c$fs1eF?LhHwsdy7MOMp*SKA6j3MkeFiGFPQ49Pzm+N`B z0>yW;++2!SF&$#3rG;Y8UHe*RDJ*u&o^Fe-aji`eLhJ_|i$o>weRx-K;=BXv0LN8qxu^~yYc`@&zJXH@Z$KBC81Wd7)l zhO(ccY>)S$^pDRaeI?}CyI%yO-#QdMo}$wHt;hKr@8Fq$Ii>?=NtU{%&4(#?t&e!l zhvOdCXR0DEGIA?QJf<`16z4_8hp0sNJ|EIYRY$)lswT-|nQqo*&Z^0xethW zVstpr@`+A}+$!MJy~p%8URAqU*4CuY;czI$!H&MlLgv%OnM%3!HN=4VgR+JRjyzd$ zrH{ja#YJza5kN~^f9&v>zV_+FyS;C|&7bCZRmIpb$t!f8sua&SZnqp#3r26*nlLQO z;=S%Xg;wYaeiZ1(%u{_m))=cBH+zJ_GUW7VeRI7mPd3d~*aBYedM>$t(Sck1_w$(K zb2!Gs!nQQ)i;IEXcY@kxplM3}O~`W{k;dR`e!j=~%~n75vda>t2SE-tA>&X;N}5qC zni`ipU6g57?bG#-nw&w|ouY|+GwnKStB#7*3}EB~0u>AAboSKuSg5ZT^OY-%zgCbb z2$qgsc^YFFb9OS5^Mxmb$@)eciAv|RK1>+ye$Ze1_-y358F?1%&`E!r|A%G=(wX)S zw%nrJ%Xx)VrRUgmJ01soek0;HPI{o|&hx8MUlzBVMX;q$(?WC~-Z|ALsqt!IyzOO;Xaozj!%Auu9*WT4qS zft}Kws`47P0B`@Q8G-&T)=S7mHQD!BDXP@qR&zgM^q5p&OpYiD3(Eta{wpSo2syb> z6GMIjL6f+xXovo~p}V7%K5mRbOykXql%-eF*JC|-Fe`06@p|%8yREefZF~O@i zi8SfGokHoike>GchIN;zK_Gd;&t76bG`LBma2r-mL?APWD;}ndRE0eQA_>+XXVx?UBrVRg;KCN3P6`x`ks{cgen<{o<`tgJ z>pU!q@MeL-=|Y3_>AW)mYq&LFzA zqc!ndTtfWas0ID+i=TM)qNkZKBA|lulXa$fm%ULVLT37ceOj8HIel-)*pbBT?IEn{ zB4+iCLLaPq_s2^~AK?9B_@(nP?-nimJ~H%p&qv+?`n}u(@AXjQnWC6CXn@(0amXtD z_kn4_(UsPPC z_%ToFL=-i|WWVbe?_I(7rNLobf70*JxtBtk;z_VaBkp%w#>ZL#HuAWpcmp{wtk3C~ zN0h>IHJl1>xvZx&0eCz6F#TBP;YQ#mBL1CbHGj&&aZsIqdnOYkEH|{WOEy$ZMKvY{3!ET+eU| zRIquVeZuw6UK8gqs|49pdnS6B2i2RbhH2EGRVz9JyLT3VNWFO2i3 z=(%1BR@_s65|jJxk=7z(Sz23gBMT2gV8W^?Hl&{+Yn@H{FWiWp0uTjI{UFSQ#gCVPAkG?Mrn~{SH405cu=h5>n zZo}NHqHPH&hxJ(hd#&%!Jz?d9AGG*64_>uItwSIL&_aS?+3NWzcm}>(Q}4>5#9yI7 z>owc}gu7>jl#JT~L4$sMt~)#uR!3t4)VGmkHFGjdafHgOep`xB#@khb3=Wx5+d)ll zOh&%#d+T<|)Z6fHOCTgTuqb|hz@1DQu(RQyVg8R!gsus=LTGpbfI0J|C?x4a+hIN zg+R?Z#j%HcX&)h#b4R!8J~a+#A9mc&d^4D6!7k?i-<_QTN$gTf<4{Vdu`iv1wjetA zjgt1!a@a^KHCc&*3#@v)+Ml(WS?`r2Ox-$5y+=kzLMz*jJReGz9CVbBX`AcBDK!p{ zF8`Eh3E}dJ5;0=kv)LF@jv|sOq?PyB-)B|dqaf$P$0Ads2S)gIK|TG}m~hH?g@L_4 zNiwX%c(v>OaX>WCLn~@MtwA#5e#D*?O$|9Yk-F+n_1`rhPWpD@JD$hm==Hsa;J&av zoAviHZE=$~wE9^1(opa`0;)50ZDvuOy*4z%me1SyWEk)Vog7+*iWSVpx7AWVFpD54*knx zb~j9#!=KJ)g?C(rSlb5X5nyXU-Z8OUHM?$8liTvHc@2kt1N&Iqxhu~_j&O|ToFw1_ zg(*RNnG7Z{4d!)Oi0!cz+y8`2yG^~4+B&7~06$L5cpbC(%Y*wJitXPb=Q7OSG6)_p z$|2>zE`?n3F@eQ;4#(2aP#=HJTWFva=cBP#F=quT@xD0{oZeYSNzZ)v`>K}=c;9LR z6ZJ58Kzp2b_|8@lU$K~{KR84*X1G^BMkQPAhO2zA^6U1Q`LwW`Hr?dgL{{=3%oH@6 zKBvtTxH%ZG}m)_{3Ghe@l$(EIRff zpUNjqI6|{wNs;GDL*tM>F?q|e0L zD*U%xTSrQnb)&G$mt)8-kmlGP?R%YJ2fx1%4ubtv=!XcOQ_axB2|sc+8k8 z8U`zGm4D7&eTAOImjo8gj;L9pT|0$p~>Ycy31D6>wj;Yw2QpaDIJYuWb<7YS@ z0ffk6{>Tu^lZl*{xp~c4am5Q+BcuS^~uzI z#pB$3B#z5^KL>q+R*Vw%>1NN4U(DmZ&lQp$Z4#^*_*-{7pG4uWol0nOFAMjbU(1MI|`a=oxiGvyUp+!&-0XH_L14YI$dwzSb0Qk&z zNznEt*fc+jdca%XUz}w@mVD^j?^8B(p=o;K>~&l4t<+l~n{8qvIFVMl9L`>d#bo)5 z&gIFO8all@55kt$Ngv)Zu=z1)3#JWM{oIas5J$|y+Scxdf*X&vN!+>{W?|K1rWRqF;E6dUFMki5Gne|;zqD)3zvKq7r$ zNeMcq7|r+=yM5bwcc$@xIHU%__r=Smn?YL)XJV%TxBO=8OC`K;^%E&`t;pa=hkLho z8_$>>9jEM1d@I*f+@H7$8T;*3e}V)$-1}JUrh%JD1k+imS^SyUhk-*&{w!_NOdt}I zwcUuh2mA2VMIc^BpXrW;7W@aS;s#m9K=@dx;okyW`HN0@xa}pXBm}H74kJ`%lzS=O~5fTanQ~~_pKv4O0dqoc1EhxJnXYt*~xcWJN#h+~r z#aY$-qKuMdqMZ`L&KR@XU>vB-t^P#*ao}T-OED^lg|WT5IU)C8{O(NshMeBeH7emM z?al0vB#k!m3);6s{Im}H2OFNDQmoq3C$1sNzdcVD7&P35$k~xpw1)Bb_}Tz{;sBH{ zE(Q|`w1Z0e&$}-r7(uDIg%?|T=Q}?3CHr7w=i}=>v0?5QbT^Dnd)p*g8gDcfmMY>L%Jg^hMp+*< z<1uY`mqj!(!x5gzXJf;ltP%pTyxcP6m<#yAl?s6X+Btp#3M*q^^3E811ZeiogXRR( z7|v{Y1F!}044a8=`b6+Pnf2K$KRM8s?>XZCo|kg?bKk@2OFUPV8rt@)KHA04BPj=clftx&Jgj&q<&Q4z&DtBH_{Q4h~#l7)JqacBu|de5$(gH$H)ka|rZ+ zK?{;5>29|_1S)U@sQFD0{fpWuNpON!E)+b0!|ei2Bb0iQRY$zbJzB zBsT%pJOnT-hB&n8?<7Xbp2?M)E6)vhTeFP5F~CuCkFJ-a-*~yTO+4#-`)p4gF7|`d zvvdp;tYSa_q=9^o<%jDA*i3O=u_YxNo0|luIlVAdMAeg1W^h)t(OS$*yc=vMQ+F+# zwrO6Z9Pxd%YaZ{4dE!u09R0K-UluuBB4#IYRru;N2ng0}bjV6)f>q$J4Ro;*f`Tw0 z?SKcwKIih$BqU&WZx1-~l$Eg@#ZC9Gkw|108G`$^Dq^AR`O-#0Jn}rq`5~2Int!Zw z0Ru|5vy=(gGbH-MzqbARC#A5q=Z$iHH?kDJCHiLz0k7r{c{b%(Em9V5Y278Sd{&ME zg0&>0SeBAzPp|A>`^Rr0xeM}fnHw8BzjiAtC#mDbU!0B>Cp9;L01!2E!p)NaLqo$Q zJT+tGl*bLu?$*lP;SDSxg)waPFqMJSO1$2&CpO~AyTW4bXIP032XKPQC8yj5JVd3` z;_UUyfhN}dG8v?rkAm(zO%zwNi}aBStI31|`=S(Is9R+uJc-*S$HQ zruGMULbXXb+k7|$mlE*4CBt$**4{QUn1E?cR5jX)j`Nv>fa4}`E(s60l{!n9Yl$(t zbZzrm3^nB+f*TmA``Pt~Gbx=yPCGC zDEpfGThaI41rLD20LFu>_8}Za+S(}+9T9MX1;XwR-+YMd*W-5MO}MvCV=>CB=qKBZ z*fICRl!r)d0Wl9P_a~x*ua;WMwoj8v8d<06vWyx`L?p2dM-x6OQ=9^9+H@35r-qz@{Cf+ zNpGaK7H?~Dn8NtNoD-?>X0&}7c-@r&E(Kjo4>EqkX6I*Q%zTcT=P#W_A`~B|fzz~0 zZeztNMEmGFyP3~mK@qG%=tEpdX+6>Rt@j<}4a>B)YpP>rLfLj6%f|e0E?(vsMsZH?G(eZSy18+!Mx`^?rxw>= z_UC8wMRg7cX-N}Ln(xEY9n6AI0H75gc^Z z25p6vJ35SDWd&(F=@x7li2kPb?qaw2`~e9bt3mUkJ8-h<3~L9bI{OmD*wH-;emOo~ zDvW}CYnKW7_BSN7a^D69pMs7IFayevZdKus; z?T_4J!GO$pEt8-lnDb}j^-A#rU%qq%TptJIfqoNc7!Cj&R)NxnqLOG(!Gx|}T)sAi zaw!TyjAa=EjZ|!Iyz$sL`IcuH42upQ9LeQ)=`Ntg!aLBA+zeDP9n$H&2nF=+baZ~g z{T=A4*tCglV8!Ono+6x1eb`er&#o#vn|abv+)E}q(HRB*QV5RBtyNS`H>ZhnI27M(Ad``x-bCE8D0Uq7|CT)CSGhi}FQ;ps3kx9z%hW_=A>yk$`P z%Z^UU;DD!h77_E?rEI9k$q+u0#uKu={Y&K&({}Z_oJe_4r`X|rLvxcJXFWddO?v2PZhC$7CljIH$vaJp1C7U5Mw3$;Vk!r%F+2p ztcl@IuW(g_c>j@#uxX#fPW83rhEp4g3lU%b$vw zambT+h-D&|Ks1d$MOcQO4PErwRQX zdPsbHU5Sq>gkbCLkZL4cc8qnw|1(J?@7efmcBDr~dk72z97=%CfnKh)_C2L{a`nov z&904WQ>M|`k}fU_qPicO(oUT&!GGuJ9ZjOS6t$i!guIAV`it*kRvzR{oU1-YG$w3R zoNFDP38V$aihF|=AXbF-f!5UO6y0Q=cestoYq2VbS0<<@ZuY~X9Zy+JHSvi~w6@*6c484~+7oWQi= zNAO46XPQ}t`X)CHX_UlZ)zS=<;U-=i66)-N^T7+a+t{Hy0o=>{5Hz zu^ciib=SN;r5Dws?4&bNU+SXURtQHl(t1I;RGswsE3Uqcg(tW;x^x8#@(X$TYU*h+ za^yW0()-9WCc<+++K{zDmo)Th_HL_ywd&@d;c4oT;NUkniM)^TUx2PBuYXf6Vg%Wy zbbHA~1+l7Z4-e0ex;R_G;go@3H75gAv&JHpG4;Z8VHv9`I#1LLRR@$@iA7N`QnQsT zKE3DuSfPjU)82em9*dv_!aRYvB=j>JjqF95q>5)w3RpE@yVP8z!`th6aA{SCgwldV zM#V$tXkIN&0M|J;`&(A929se`KOO8lp`0O>sU`knqwc`HX$_7S2gC^!z5lKtG<}nU zG7Lvg>_I=4zZQ6g`mbi>MC{1Nz!N5h z0X)jZcv@`tdWAi+2OLB_%+#L{o#CEhaJ-2{1Zt+f!L9WZ5gFOAQnO%1@eN2fMJ;Hb zLp|E$?5w!gZm#h^Jn_wW!%A3%;1pWK>NKBk+){*Z1_$AdU{`;AL0rbtZaiK~obx^J zkJaiMUJ|BPyLImAj@fJ9YzsOZb7D299=NV<6V9SmwvQB_>IWxqO)6h!JzraeUo;vk zXDM6C*hMu8-i+Ot?IvA^Bbd48&!lwd!D?ZW-)yg;NzE-N)>%)&zzMm} z>UHEd7WpKorVu#R_`VVy|I|tfw7+n|ac4sKIBrY8#QDk8P%Cctofj4g;J~#%q?JnP zKbtUBG8Gz|(Ic3y3E;uN$TDfB*4;I@m7??(s@6^M%ejx}dO-l9)Cw`blp&byTFMh3 zreV@1EA3R>IY`5_a@}dZ++B>k|CBjfeiG!^>IRvXN9yL+l~Bjn@r(Fg7-pXlqR)DI zL)D)12F`8lBKJWYc{Y=#PKCD&rVvA+o7F$P6gE|+biC22|DmU8YFo$Q_38&B7f5^WM`iS%(u zp0sLDT-Z-vF0=R@>Y!b> zj92TO8~*PYUi@JGeR7jbPI8c(!uI{hjhg3caXQ{=^mA&q{Pmbp!^huTqqbWzeg&7_ z%&T|8q4VHaZE7n4i-}R-m@pqlu%j-ryhqc z*o`;`D#@j~q@HlKQcTPBNW1WyoQh`8BK}(|M7C5i+E!kfSCm(aGD$G=kxqk0k&(%0 z>HRjDi|*c@Ty$71^;;>I>!?cz62ZX-yTq=1jQ+F0$W8{@G;xt+7oe^?IVs)Cn z8ST7Pc39pqF*vbGBc=Zo+8I=w@33gwZ0y!-KiJ2-_ZV}=B_Kcm^c9p`zy(cT5D z1sL99_Mv_4?^ZpFGi;u#x}kknflS!bx1{U4&An zEhtxD754Ii`XAFwvtW5s1huoVCQ?%1!}(NFs`?C)VElxLHFCv3(iN%aAw!kS2D!~` zlOGcGl0#+~+((Y>Esxp)36Gq&!yfX5l{*MQxq)_lE~yhPRli^+!J8Ex@5$@j@?z)q zsMy%M)&jYmtC}Sd?(FxGX57lRPM1R7kLQLR`Mo=$#OEX2y%lMkOQ_)WT>(FQP;Xv` zV~$iN!05@52%V&!JF7JD%Ci$_^-%8yYosbriT5*gB0-=-@#4R@WEzO=9h?NALe_B& z-*!?1mdG9jmnd9FZ^ zP4g^+mVCqu#B%K^Kwxmo%yaT|P%D#JA}%O5D2)VvfHNoIU&M`rJk3h3vHSdtv;p^> zctG`*b$QjJ5)Lt8855C)-HAn~10_FG9G^!CqTiP9iKe5M1uYPG+{Gq_PD0j<5KcwH z&BvsWLACdroWK5^PomnBn_io?R8}S(_G919OJLIc5Cakl=q^k(D?mhv8@JwsTvIo% z{=rYLS9l-?CyeoM@(MLPI)@!&rRc5dJu1?KkhxpGqiq*`{QLIv?DWU`Nz+BXv#nK5 zMpqW{K9;~UB?RF{<}chNMyje&6eNxj=gdb;txYA`0MD*i-5pGbh5VHiBxQuFkJEYp zH;*$Uf%q|dh5rfE@nNrS6C6Pd9-*cS7ljLHuaMvSjQYd^0#VAlPw32%{gf^u4d8`N zcoKgS#SX|}iLBE8%#H^~*z>(tM{sfK1lRUO<;hD$-?n}BnRlfsRzRnRpzP7gd}hK- zv{|QV9=1;VL)61bgCDGd(TrtP2mx{~`X@J#d{n*H_Ph4smd6n*UQnGE1ZBy@p2Uj7 zVTp_&nh!^-%&@!b0Z^Skgk^76f=?OY2(uXnQ0@Res;G8QvI#!P;P~|yOU1>61=23T zM@@=5m6CiUbof#VIM?#mv88P&$!*DS0klet4ef5@&&a9FYILkOe1Fof!%H z+Vyep=l|~>uiTab+#2eGR=~CFw5#nFC1zI>9>f7p|M;O;=hj#$2IQtzX8Tvc zHpbs4^A~G(U@(}%%a<>Ef!k;Sj|55F(-;V5DK?sS9~vr{g0hwT!#rDVTK@>3g{r21 z9>_3}7x4Ty<~Q}|meaM2$$A$SM{x$UZw90hF9Eka{%N}s{58uuCP*mQNjZAnWLocx z1KFAT#6Tu@!b;6&6i6h{z`EOa2aZUWpaF%-w)OdyUNbMIof_8OKHCTAv!&yFC7ub%Ao<|Hrp2X zV+|LV%HmL0@N})8_4VjR!+%-2hA0=aWHc`b@w)`L!FNSPk(Gwwk$-$Po8m#d2RKPYcTo>k%v^iu zp5)tR;|Hw2PPp#*lDdPw-q%oEW(+{$L#M3^xy;F+Tj>E;3v~?FQnf+p4TI9#D^FfD z%QkeGYHPRO$t3q+lOmwdH~*!vl-uZ_yrZPyrTZcOacCbZS%{jP2)^K$oIPQDy=(#~zfLm|$gqYIkbIguK5#tV=G zpkF?d5BTUX1qK8i89{T2KYaYyv3$_(TyF!~I-q&a2jIC_^a?dpXXZmAxf#(bn_c8q z1&}E<0Uc{!(jX0L)QxoVvLjzyDb{p4q zW%;7p*AEw~QOunMsTR>QGiGQ2E5LNOozL#+%8Er>yShRFN#|8pCJ8;m`umloOpych zxX8z53kLu{v0U?2Af#d&jrjq1_6PtSTLvuUZl;$rNn48}_)Qhd((|XJ;8M)!F00!5 zH$Hv(7Z8C81N4?@eN4G}mO0Tcbb zPnuYC;nRlgist=((IEwB=tHubHm?3^a)UgSG42@TTqbvMnEwJh;Tn#h-1sxV*tvr8 ziyiRg;CpxTE&))w8}P=oO-$%t%mW8+ELu{wyV4n`34+Y>leIf-QAC0*LSxEbV3|3| zG46d`=N5!`J|(kp!|oR_T9xNf>af2_ROWK?9{Y$aVn2e6j(A`HyL6Xs{r_ zbIR>-|8YCOF-L$)F9Q&pI+zv0f3s4Je$68HiP>^mm6R+2<}w-{6)ZX^!7aa^DRF7UEJ9{~Jd=%2Q)tC*07`ud8{(8z*E zQHOdZU`W1yL%v=X_B;E_`;8!D>9M@}l^W?X7t|*LP>YnZGSQ1ba}w1Yp60yx110JbMBX2*g6Z2r(9&}9JN6vpYJ>i`(h4A;LcufyKw z_)G1y0=bIr`|x+-MsQd=MVMm_>hJ zo4{X+whnc^3Ge@Hj)Tm%Spa2y;Pby)kpH)VcCWGI-a$iLoQeTL5CTzE(SlbfSq1+O DS?QRl literal 0 HcmV?d00001 diff --git a/docs/build/jupyter_execute/Examples.ipynb b/docs/build/jupyter_execute/Examples.ipynb index 01c71c2..d68acab 100644 --- a/docs/build/jupyter_execute/Examples.ipynb +++ b/docs/build/jupyter_execute/Examples.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "30a235e9", + "id": "7f5433b7", "metadata": {}, "source": [ "# IsoModulator example\n", @@ -15,7 +15,7 @@ { "cell_type": "code", "execution_count": 1, - "id": "c7ab0522", + "id": "aee3642d", "metadata": {}, "outputs": [], "source": [ @@ -38,7 +38,7 @@ }, { "cell_type": "markdown", - "id": "5a23a287", + "id": "02c4738c", "metadata": {}, "source": [ "## set paths" @@ -47,7 +47,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "a525cb51", + "id": "14fcd48c", "metadata": {}, "outputs": [], "source": [ @@ -62,7 +62,7 @@ }, { "cell_type": "markdown", - "id": "6331f786", + "id": "be12cc8b", "metadata": {}, "source": [ "### Plotting kwargs" @@ -71,7 +71,7 @@ { "cell_type": "code", "execution_count": 3, - "id": "fdbd1e9d", + "id": "d7744dd4", "metadata": {}, "outputs": [], "source": [ @@ -84,7 +84,7 @@ }, { "cell_type": "markdown", - "id": "bf9e2e4f", + "id": "7d46c97c", "metadata": {}, "source": [ "## 1. Define parameter uncertainty values" @@ -93,7 +93,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "84ca6050", + "id": "f8998a99", "metadata": {}, "outputs": [], "source": [ @@ -110,7 +110,7 @@ }, { "cell_type": "markdown", - "id": "1a1acceb", + "id": "2dea5e7f", "metadata": {}, "source": [ "## 2. Initialize class object" @@ -119,7 +119,7 @@ { "cell_type": "code", "execution_count": 5, - "id": "5f09e314", + "id": "2038b40c", "metadata": {}, "outputs": [], "source": [ @@ -131,7 +131,7 @@ }, { "cell_type": "markdown", - "id": "f7388a52", + "id": "46958166", "metadata": {}, "source": [ "## 3. Add uncertainties and plot the result" @@ -140,14 +140,14 @@ { "cell_type": "code", "execution_count": 6, - "id": "0e0f6bd5", + "id": "3a80b986", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/Users/alena/PycharmProjects/PaperI/EmpiricalArchive/IsoModulator/Simulation_functions.py:195: SettingWithCopyWarning:\n", + "/Users/alena/PycharmProjects/PaperI/EmpiricalArchive/IsoModulator/Simulation_functions.py:201: SettingWithCopyWarning:\n", "\n", "\n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", @@ -162,7 +162,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/z6/y4rdkpdx3vlbwtmngx04x_1w0000gp/T/ipykernel_18950/3922852537.py:3: UserWarning:\n", + "/var/folders/z6/y4rdkpdx3vlbwtmngx04x_1w0000gp/T/ipykernel_24080/3922852537.py:3: UserWarning:\n", "\n", "Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n", "\n" @@ -170,7 +170,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -187,7 +187,7 @@ }, { "cell_type": "markdown", - "id": "9c347175", + "id": "50adf926", "metadata": {}, "source": [ "## 4. Calculate the new isochrone" @@ -196,7 +196,7 @@ { "cell_type": "code", "execution_count": 7, - "id": "ca96f598", + "id": "18bd41e3", "metadata": {}, "outputs": [ { @@ -210,7 +210,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The resampling of 100 curves took 16.07006287574768 s (6 parallel jobs).\n" + "The resampling of 100 curves took 15.633490800857544 s (6 parallel jobs).\n" ] } ], @@ -233,7 +233,7 @@ }, { "cell_type": "markdown", - "id": "8be39ad4", + "id": "03f1e38d", "metadata": {}, "source": [ "## 5. Plot the result" @@ -242,12 +242,12 @@ { "cell_type": "code", "execution_count": 8, - "id": "a895c9a2", + "id": "6b34c2e4", "metadata": {}, "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "096a31e2", + "id": "bc6bdc90", "metadata": {}, "source": [ "## 6. Calculate the difference between the curves" @@ -278,14 +278,14 @@ { "cell_type": "code", "execution_count": 9, - "id": "eac6d68a", + "id": "a7e45d8f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Area between curves: 1.1641176307170609\n" + "Area between curves: 0.690393920974019\n" ] } ],